diff --git a/.github/workflows/android_arm64.yml b/.github/workflows/android_arm64.yml index 6e60051cd0c0ab..3f3ab41662fcde 100644 --- a/.github/workflows/android_arm64.yml +++ b/.github/workflows/android_arm64.yml @@ -94,6 +94,8 @@ jobs: uses: actions/checkout@v4 with: repository: 'microsoft/vcpkg' + # Keep in sync with /vcpkg.json + ref: '7ba0ba7334c3346e7eee1e049ba85da193a8d821' path: 'vcpkg' fetch-depth: '0' diff --git a/.github/workflows/build_doc.yml b/.github/workflows/build_doc.yml index f56d4614a3cd27..ec87e04b234492 100644 --- a/.github/workflows/build_doc.yml +++ b/.github/workflows/build_doc.yml @@ -21,7 +21,7 @@ jobs: lfs: 'true' - name: Install apt-get dependencies - uses: awalsh128/cache-apt-pkgs-action@v1.3.1 + uses: awalsh128/cache-apt-pkgs-action@v1.4.1 with: packages: graphviz texlive liblua5.2-0 libclang1-9 libclang-cpp9 version: 3.0 diff --git a/.github/workflows/code_snippets.yml b/.github/workflows/code_snippets.yml index e9431dee1b44bf..5181e26f378da0 100644 --- a/.github/workflows/code_snippets.yml +++ b/.github/workflows/code_snippets.yml @@ -30,7 +30,7 @@ jobs: submodules: 'true' - name: Install OpenCL - uses: awalsh128/cache-apt-pkgs-action@v1.3.1 + uses: awalsh128/cache-apt-pkgs-action@v1.4.1 if: runner.os == 'Linux' with: packages: ocl-icd-opencl-dev opencl-headers diff --git a/.github/workflows/coverity.yml b/.github/workflows/coverity.yml index de7d53265ca2e3..255f1355d0c35f 100644 --- a/.github/workflows/coverity.yml +++ b/.github/workflows/coverity.yml @@ -149,7 +149,7 @@ jobs: - name: Show Coverity configure logs continue-on-error: true - run: cov-configure -c ${COVERITY_TOOL_DIR}/cov-analysis-linux64-2023.6.2/config/coverity_config.xml -lscc text + run: ${COVERITY_TOOL_DIR}/cov-analysis*/bin/cov-configure -c ${COVERITY_TOOL_DIR}/cov-analysis-linux64-2023.6.2/config/coverity_config.xml -lscc text - name: Upload Coverity logs uses: actions/upload-artifact@v3 diff --git a/.github/workflows/job_onnx_models_tests.yml b/.github/workflows/job_onnx_models_tests.yml index 48972d64be8db2..24bb24ec6f0d46 100644 --- a/.github/workflows/job_onnx_models_tests.yml +++ b/.github/workflows/job_onnx_models_tests.yml @@ -28,7 +28,10 @@ jobs: INSTALL_DIR: ${{ github.workspace }}/install INSTALL_TEST_DIR: ${{ github.workspace }}/install/tests ONNX_MODELS_PATH: ${{ github.workspace }}/onnx_test_models - MODELS_SHARE_PATH: "/mount/onnxtestdata" + # instead of using static MODELS_SHARE_PATH + # choose one of the replicas dynamically instead + # depending on GITHUB_RUN_NUMBER variable + NUMBER_OF_REPLICAS: 2 ONNX_MODEL_ZOO_SHA: "5faef4c33eba0395177850e1e31c4a6a9e634c82" if: ${{ github.event_name != 'merge_group' }} steps: @@ -53,6 +56,8 @@ jobs: echo "OPENVINO_REPO=$GITHUB_WORKSPACE/openvino" >> "$GITHUB_ENV" echo "INSTALL_DIR=$GITHUB_WORKSPACE/install" >> "$GITHUB_ENV" echo "INSTALL_TEST_DIR=$GITHUB_WORKSPACE/install/tests" >> "$GITHUB_ENV" + echo "MODELS_SHARE_PATH=/mount/onnxtestdata$((GITHUB_RUN_NUMBER % NUMBER_OF_REPLICAS))" >> "$GITHUB_ENV" + echo $MODELS_SHARE_PATH - name: Extract OpenVINO packages run: | diff --git a/.github/workflows/job_python_unit_tests.yml b/.github/workflows/job_python_unit_tests.yml index a2129b7267293e..dc5441d0bbfc1d 100644 --- a/.github/workflows/job_python_unit_tests.yml +++ b/.github/workflows/job_python_unit_tests.yml @@ -52,6 +52,13 @@ jobs: name: openvino_tests path: ${{ env.INSTALL_TEST_DIR }} + - name: Download OpenVINO tokenizers extension + if: ${{ runner.os != 'macOS' && runner.arch != 'ARM64' }} # Ticket: 126287 + uses: actions/download-artifact@v3 + with: + name: openvino_tokenizers_wheel + path: ${{ env.INSTALL_DIR }} + # Needed as ${{ github.workspace }} is not working correctly when using Docker - name: Setup Variables run: | @@ -97,9 +104,13 @@ jobs: run: | # Install the core OV wheel python3 -m pip install ${INSTALL_DIR}/tools/openvino-*.whl - + + if [[ "${{ runner.arch }}" != "ARM64" ]]; then + python3 -m pip install ${INSTALL_DIR}/openvino_tokenizers-*.whl + fi + extras_to_install="caffe,kaldi,onnx,tensorflow2,pytorch" - + if [[ "${{ runner.arch }}" != "ARM64" ]]; then extras_to_install="mxnet,$extras_to_install" fi @@ -144,14 +155,14 @@ jobs: # Skips under Ticket: 122666 skip_filter='--ignore-glob=**/mo/unit_tests/mo/front/mxnet/**' fi - + python3 -m pytest -s ${INSTALL_TEST_DIR}/mo/unit_tests \ --junitxml=${INSTALL_TEST_DIR}/TEST-ModelOptimizer.xml \ "$skip_filter" - name: Python ONNX operators tests if: (fromJSON(inputs.affected-components).Python_API.test || - fromJSON(inputs.affected-components).ONNX_FE.test) && + fromJSON(inputs.affected-components).ONNX_FE.test) && runner.arch != 'ARM64' # Ticket: 123325 run: | # Skip test_onnx/test_zoo_models and test_onnx/test_backend due to long execution time - ONNX Model Zoo tests are run separately @@ -174,13 +185,13 @@ jobs: # Import 'test_utils' installed in '/tests/python/openvino' export LD_LIBRARY_PATH=${PIP_INSTALL_PATH}/openvino/libs:$LD_LIBRARY_PATH export PYTHONPATH=${INSTALL_TEST_DIR}/python - + if [[ "${{ runner.os }}" == "Linux" ]] && [[ "${{ runner.arch }}" == "ARM64" ]]; then # Find gomp lib GOMP_LIB=$(find "${PIP_INSTALL_PATH}/torch/lib/../../torch.libs/" -name '*libgomp-*so*') export LD_PRELOAD=${GOMP_LIB} fi - + python3 -m pytest ${LAYER_TESTS_INSTALL_DIR}/mo_python_api_tests --junitxml=${INSTALL_TEST_DIR}/TEST-test_mo_convert.xml env: TEST_DEVICE: CPU @@ -192,13 +203,13 @@ jobs: # Import 'test_utils' installed in '/tests/python/openvino' export PYTHONPATH=${INSTALL_TEST_DIR}/python export LD_LIBRARY_PATH=${PIP_INSTALL_PATH}/openvino/libs:$LD_LIBRARY_PATH - + if [[ "${{ runner.os }}" == "Linux" ]] && [[ "${{ runner.arch }}" == "ARM64" ]]; then # Find gomp lib GOMP_LIB=$(find "${PIP_INSTALL_PATH}/torch/lib/../../torch.libs/" -name '*libgomp-*so*') export LD_PRELOAD=${GOMP_LIB} fi - + python3 -m pytest ${LAYER_TESTS_INSTALL_DIR}/ovc_python_api_tests --junitxml=${INSTALL_TEST_DIR}/TEST-test_ovc_convert.xml env: TEST_DEVICE: CPU @@ -229,7 +240,7 @@ jobs: PYTORCH_TRACING_MODE: EXPORT - name: PyTorch torch.compile TORCHFX Layer Tests - if: ${{ fromJSON(inputs.affected-components).PyTorch_FE.test && runner.os != 'macOS' }} + if: ${{ fromJSON(inputs.affected-components).PyTorch_FE.test && runner.os != 'macOS' && runner.arch != 'ARM64' }} # Ticket: 126287 run: | python3 -m pytest ${LAYER_TESTS_INSTALL_DIR}/pytorch_tests -m precommit_fx_backend --junitxml=${INSTALL_TEST_DIR}/TEST-pytorch.xml env: @@ -238,7 +249,7 @@ jobs: PYTORCH_TRACING_MODE: TORCHFX - name: PyTorch torch.compile TORCHSCRIPT Layer Tests - if: ${{ fromJSON(inputs.affected-components).PyTorch_FE.test && runner.os != 'macOS' }} + if: ${{ fromJSON(inputs.affected-components).PyTorch_FE.test && runner.os != 'macOS' && runner.arch != 'ARM64' }} # Ticket: 126287 run: | python3 -m pytest ${LAYER_TESTS_INSTALL_DIR}/pytorch_tests -m precommit_ts_backend --junitxml=${INSTALL_TEST_DIR}/TEST-pytorch.xml env: @@ -261,7 +272,7 @@ jobs: run: | # requires 'unit_tests' from 'mo' export PYTHONPATH=${INSTALL_TEST_DIR}/mo - python3 -m pytest ${LAYER_TESTS_INSTALL_DIR}/tensorflow_tests/ --use_new_frontend -m precommit_tf_fe -n logical --junitxml=${INSTALL_TEST_DIR}/TEST-tf_fe.xml + python3 -m pytest ${LAYER_TESTS_INSTALL_DIR}/tensorflow_tests/ -m precommit_tf_fe -n logical --junitxml=${INSTALL_TEST_DIR}/TEST-tf_fe.xml env: TEST_DEVICE: CPU TEST_PRECISION: FP16 @@ -271,7 +282,7 @@ jobs: run: | # requires 'unit_tests' from 'mo' export PYTHONPATH=${INSTALL_TEST_DIR}/mo - python3 -m pytest ${LAYER_TESTS_INSTALL_DIR}/tensorflow2_keras_tests/ --use_new_frontend -m precommit_tf_fe --junitxml=${INSTALL_TEST_DIR}/TEST-tf2_fe.xml + python3 -m pytest ${LAYER_TESTS_INSTALL_DIR}/tensorflow2_keras_tests/ -m precommit_tf_fe --junitxml=${INSTALL_TEST_DIR}/TEST-tf2_fe.xml env: TEST_DEVICE: CPU TEST_PRECISION: FP16 @@ -284,11 +295,11 @@ jobs: - name: TensorFlow 1 Layer Tests - Legacy FE if: fromJSON(inputs.affected-components).TF_FE.test - run: python3 -m pytest ${LAYER_TESTS_INSTALL_DIR}/tensorflow_tests/test_tf_Roll.py --ir_version=10 --junitxml=${INSTALL_TEST_DIR}/TEST-tf_Roll.xml + run: python3 -m pytest ${LAYER_TESTS_INSTALL_DIR}/tensorflow_tests/test_tf_Roll.py --use_legacy_frontend --ir_version=10 --junitxml=${INSTALL_TEST_DIR}/TEST-tf_Roll.xml - name: TensorFlow 2 Layer Tests - Legacy FE if: fromJSON(inputs.affected-components).TF_FE.test - run: python3 -m pytest ${LAYER_TESTS_INSTALL_DIR}/tensorflow2_keras_tests/test_tf2_keras_activation.py --ir_version=11 -k "sigmoid" --junitxml=${INSTALL_TEST_DIR}/TEST-tf2_Activation.xml + run: python3 -m pytest ${LAYER_TESTS_INSTALL_DIR}/tensorflow2_keras_tests/test_tf2_keras_activation.py --use_legacy_frontend --ir_version=11 -k "sigmoid" --junitxml=${INSTALL_TEST_DIR}/TEST-tf2_Activation.xml env: TEST_DEVICE: CPU TEST_PRECISION: FP16 diff --git a/.github/workflows/job_samples_tests.yml b/.github/workflows/job_samples_tests.yml index 84f3562f4392f0..c9f66f2bf864d5 100644 --- a/.github/workflows/job_samples_tests.yml +++ b/.github/workflows/job_samples_tests.yml @@ -124,7 +124,6 @@ jobs: source ${INSTALL_DIR}/setupvars.sh PYTHONCOERCECLOCALE=warn python3 -bb -W error -X dev -X warn_default_encoding -m pytest $INSTALL_TEST_DIR/smoke_tests \ - --env_conf $INSTALL_TEST_DIR/smoke_tests/env_config.yml \ --junitxml=$INSTALL_TEST_DIR/TEST-SamplesSmokeTests.xml - name: Upload Test Results diff --git a/.github/workflows/linux.yml b/.github/workflows/linux.yml index 4328619d757efe..1f1915588a5fa6 100644 --- a/.github/workflows/linux.yml +++ b/.github/workflows/linux.yml @@ -419,6 +419,32 @@ jobs: name: conformance_artifacts_${{ matrix.TEST_TYPE }}-${{ env.TEST_DEVICE }} path: ${{ env.CONFORMANCE_ARTIFACTS_DIR }}/conformance_artifacts.tar.gz if-no-files-found: 'error' + + - name: Mandatory API Conformance Tests (Template) + if: ${{ matrix.TEST_TYPE == 'API' }} + run: | + source ${INSTALL_DIR}/setupvars.sh + + python3 ${CONFORMANCE_TOOLS_DIR}/run_conformance.py -ov=${INSTALL_DIR}/tests \ + -d=TEMPLATE \ + -t=${{ matrix.TEST_TYPE }} \ + -w=${CONFORMANCE_ARTIFACTS_DIR} \ + -sm=mandatory + + - name: Pack Conformance Artifacts + if: ${{ matrix.TEST_TYPE == 'API' }} + run: | + pushd ${CONFORMANCE_ARTIFACTS_DIR} + tar -czvf ${CONFORMANCE_ARTIFACTS_DIR}/conformance_artifacts.tar.gz * + popd + + - name: Upload Conformance Artifacts + if: ${{ matrix.TEST_TYPE == 'API' }} + uses: actions/upload-artifact@v3 + with: + name: conformance_artifacts_${{ matrix.TEST_TYPE }}-TEMPLATE + path: ${{ env.CONFORMANCE_ARTIFACTS_DIR }}/conformance_artifacts.tar.gz + if-no-files-found: 'error' ONNX_Runtime: name: ONNX Runtime Integration @@ -454,7 +480,7 @@ jobs: Python_Unit_Tests: name: Python unit tests - needs: [ Build, Smart_CI ] + needs: [ Build, Smart_CI, Openvino_tokenizers ] uses: ./.github/workflows/job_python_unit_tests.yml with: runner: 'aks-linux-4-cores-16gb' @@ -638,9 +664,8 @@ jobs: - /mount:/mount env: INSTALL_DIR: /__w/openvino/openvino/install - OPENVINO_CONTRIB_REPO: /__w/openvino/openvino/openvino_contrib - OPENVINO_TOKENIZERS_REPO: /__w/openvino/openvino/openvino_contrib/modules/custom_operations - EXTENSION_BUILD_DIR: /__w/openvino/openvino/openvino_tokenizers + OPENVINO_TOKENIZERS_REPO: /__w/openvino/openvino/openvino_tokenizers + EXTENSION_BUILD_DIR: /__w/openvino/openvino/build if: fromJSON(needs.smart_ci.outputs.affected_components).TOKENIZERS steps: @@ -660,11 +685,11 @@ jobs: self-hosted-runner: 'true' show-cache-info: 'false' - - name: Clone OpenVINO Contrib + - name: Clone OpenVINO Tokenizers uses: actions/checkout@v4 with: - repository: 'openvinotoolkit/openvino_contrib' - path: ${{ env.OPENVINO_CONTRIB_REPO }} + repository: 'openvinotoolkit/openvino_tokenizers' + path: ${{ env.OPENVINO_TOKENIZERS_REPO }} ref: 'master' - name: Download OpenVINO package diff --git a/.github/workflows/linux_conditional_compilation.yml b/.github/workflows/linux_conditional_compilation.yml index 4f2d7d8ec91bed..f74802072c0910 100644 --- a/.github/workflows/linux_conditional_compilation.yml +++ b/.github/workflows/linux_conditional_compilation.yml @@ -152,6 +152,7 @@ jobs: run: | cmake \ -G "${{ env.CMAKE_GENERATOR }}" \ + -DCMAKE_CXX_STANDARD=20 \ -DBUILD_SHARED_LIBS=OFF \ -DENABLE_TESTS=ON \ -DENABLE_CPPLINT=OFF \ diff --git a/.github/workflows/linux_riscv.yml b/.github/workflows/linux_riscv.yml index 2f1ca29890fc47..023986afa2af61 100644 --- a/.github/workflows/linux_riscv.yml +++ b/.github/workflows/linux_riscv.yml @@ -60,8 +60,8 @@ jobs: OPENVINO_REPO: /__w/openvino/openvino/openvino OPENVINO_BUILD_DIR: /__w/openvino/openvino/openvino_build INSTALL_DIR: /__w/openvino/openvino/openvino_install - CONAN_USER_HOME: /mount/caches/ccache/ubuntu22_riscv64_master/.conan - CCACHE_DIR: /mount/caches/ccache/ubuntu22_riscv64_master + CONAN_USER_HOME: /mount/caches/ccache/ubuntu22_riscv64_master_release/.conan + CCACHE_DIR: /mount/caches/ccache/ubuntu22_riscv64_master_release CCACHE_TEMPDIR: /__w/openvino/openvino/ccache_temp CCACHE_MAXSIZE: 50G if: ${{ !needs.smart_ci.outputs.skip_workflow && github.event_name != 'merge_group' }} diff --git a/.github/workflows/ovc.yml b/.github/workflows/ovc.yml index 74d891f8262e3a..5a4459a59d81ad 100644 --- a/.github/workflows/ovc.yml +++ b/.github/workflows/ovc.yml @@ -51,4 +51,18 @@ jobs: - name: Pylint-OVC run: pylint -d C,R,W openvino/tools/ovc - working-directory: tools/ovc \ No newline at end of file + working-directory: tools/ovc + + Overall_Status: + name: ci/gha_overall_status_ovc + needs: [Pylint-UT] + if: ${{ always() }} + runs-on: ubuntu-latest + steps: + - name: Check status of all jobs + if: >- + ${{ + contains(needs.*.result, 'failure') || + contains(needs.*.result, 'cancelled') + }} + run: exit 1 diff --git a/.github/workflows/windows.yml b/.github/workflows/windows.yml index 795366d9ec67b7..4814182e802445 100644 --- a/.github/workflows/windows.yml +++ b/.github/workflows/windows.yml @@ -55,6 +55,7 @@ jobs: CMAKE_C_COMPILER_LAUNCHER: sccache SCCACHE_IGNORE_SERVER_IO_ERROR: 1 SCCACHE_SERVER_PORT: 35555 + SCCACHE_IDLE_TIMEOUT: 0 SCCACHE_ERROR_LOG: "${{ github.workspace }}\\openvino\\sccache_log.txt" SCCACHE_LOG: warn OPENVINO_REPO: "${{ github.workspace }}\\openvino" @@ -330,7 +331,7 @@ jobs: python3 -m pip install --ignore-installed PyYAML -r ${{ env.INSTALL_TEST_DIR }}/smoke_tests/requirements.txt "$ovCoreWheelPath" . "${{ env.INSTALL_DIR }}/setupvars.ps1" $Env:PYTHONCOERCECLOCALE="warn" - python3 -bb -W error -X dev -X warn_default_encoding -m pytest ${{ env.INSTALL_TEST_DIR }}/smoke_tests --env_conf ${{ env.INSTALL_TEST_DIR }}/smoke_tests/env_config.yml --junitxml=${{ env.INSTALL_TEST_DIR }}/TEST-SamplesSmokeTests.xml + python3 -bb -W error -X dev -X warn_default_encoding -m pytest ${{ env.INSTALL_TEST_DIR }}/smoke_tests --numprocesses logical --junitxml=${{ env.INSTALL_TEST_DIR }}/TEST-SamplesSmokeTests.xml env: IE_APP_PATH: ${{ env.INSTALL_DIR }}/samples_bin IE_APP_PYTHON_PATH: ${{ env.INSTALL_DIR }}/samples/python @@ -410,8 +411,7 @@ jobs: runs-on: aks-win-4-cores-8gb env: INSTALL_DIR: "${{ github.workspace }}\\install" - OPENVINO_CONTRIB_REPO: "${{ github.workspace }}\\openvino_contrib" - OPENVINO_TOKENIZERS_REPO: "${{ github.workspace }}\\openvino_contrib\\modules\\custom_operations" + OPENVINO_TOKENIZERS_REPO: "${{ github.workspace }}\\openvino_tokenizers" EXTENSION_BUILD_DIR: "${{ github.workspace }}\\build\\openvino_tokenizers" if: fromJSON(needs.smart_ci.outputs.affected_components).TOKENIZERS @@ -431,11 +431,11 @@ jobs: self-hosted-runner: 'true' show-cache-info: 'false' - - name: Clone OpenVINO Contrib + - name: Clone OpenVINO Tokenizers uses: actions/checkout@v4 with: - repository: 'openvinotoolkit/openvino_contrib' - path: ${{ env.OPENVINO_CONTRIB_REPO }} + repository: 'openvinotoolkit/openvino_tokenizers' + path: ${{ env.OPENVINO_TOKENIZERS_REPO }} ref: 'master' - name: Download OpenVINO package @@ -485,7 +485,7 @@ jobs: Python_Unit_Tests: name: Python unit tests - needs: [ Build, Smart_CI ] + needs: [ Build, Smart_CI, Openvino_tokenizers ] timeout-minutes: 75 defaults: run: @@ -506,6 +506,12 @@ jobs: name: openvino_package path: ${{ env.INSTALL_DIR }} + - name: Download OpenVINO tokenizers extension + uses: actions/download-artifact@v3 + with: + name: openvino_tokenizers_wheel + path: ${{ env.INSTALL_DIR }} + - name: Download OpenVINO tests package uses: actions/download-artifact@v3 with: @@ -543,6 +549,10 @@ jobs: $ovCoreWheelPath=Get-ChildItem -Path "${{ env.INSTALL_DIR }}\tools" -Filter openvino-*.whl | % { $_.FullName } python3 -m pip install "$ovCoreWheelPath" + # Find and install the core OV Tokenizers wheel + $ovCoreWheelPath=Get-ChildItem -Path "${{ env.INSTALL_DIR }}" -Filter openvino_tokenizers-*.whl | % { $_.FullName } + python3 -m pip install "$ovCoreWheelPath" + # Find and install the dev OV wheel $ovDevWheelPath=Get-ChildItem -Path "${{ env.INSTALL_DIR }}\tools" -Filter openvino_dev*.whl | % { $_.FullName } python3 -m pip install "$ovDevWheelPath[mxnet,caffe,kaldi,onnx,tensorflow2,pytorch]" @@ -608,7 +618,7 @@ jobs: run: | :: requires 'unit_tests' from 'tools/mo' set PYTHONPATH=${{ env.INSTALL_TEST_DIR }}\mo;%PYTHONPATH% - python3 -m pytest ${{ env.LAYER_TESTS_INSTALL_DIR }}/tensorflow_tests/ --use_new_frontend -n logical -m precommit_tf_fe --junitxml=${{ env.INSTALL_TEST_DIR }}/TEST-tf_fe.xml + python3 -m pytest ${{ env.LAYER_TESTS_INSTALL_DIR }}/tensorflow_tests/ -n logical -m precommit_tf_fe --junitxml=${{ env.INSTALL_TEST_DIR }}/TEST-tf_fe.xml env: TEST_DEVICE: CPU TEST_PRECISION: FP16 @@ -620,7 +630,7 @@ jobs: :: requires 'unit_tests' from 'tools/mo' set PYTHONPATH=${{ env.INSTALL_TEST_DIR }}\mo;%PYTHONPATH% - python3 -m pytest ${{ env.LAYER_TESTS_INSTALL_DIR }}/tensorflow2_keras_tests/ --use_new_frontend -m precommit_tf_fe --junitxml=${{ env.INSTALL_TEST_DIR }}/TEST-tf2_fe.xml + python3 -m pytest ${{ env.LAYER_TESTS_INSTALL_DIR }}/tensorflow2_keras_tests/ -m precommit_tf_fe --junitxml=${{ env.INSTALL_TEST_DIR }}/TEST-tf2_fe.xml env: TEST_DEVICE: CPU @@ -628,13 +638,13 @@ jobs: if: fromJSON(needs.smart_ci.outputs.affected_components).TF_FE.test shell: cmd run: | - python3 -m pytest ${{ env.LAYER_TESTS_INSTALL_DIR }}/tensorflow_tests/test_tf_Roll.py --ir_version=10 --junitxml=${{ env.INSTALL_TEST_DIR }}/TEST-tf_Roll.xml + python3 -m pytest ${{ env.LAYER_TESTS_INSTALL_DIR }}/tensorflow_tests/test_tf_Roll.py --use_legacy_frontend --ir_version=10 --junitxml=${{ env.INSTALL_TEST_DIR }}/TEST-tf_Roll.xml - name: TensorFlow 2 Layer Tests - Legacy FE if: fromJSON(needs.smart_ci.outputs.affected_components).TF_FE.test shell: cmd run: | - python3 -m pytest ${{ env.LAYER_TESTS_INSTALL_DIR }}/tensorflow2_keras_tests/test_tf2_keras_activation.py --ir_version=11 --junitxml=${{ env.INSTALL_TEST_DIR }}/TEST-tf2_Activation.xml -k "sigmoid" + python3 -m pytest ${{ env.LAYER_TESTS_INSTALL_DIR }}/tensorflow2_keras_tests/test_tf2_keras_activation.py --use_legacy_frontend --ir_version=11 --junitxml=${{ env.INSTALL_TEST_DIR }}/TEST-tf2_Activation.xml -k "sigmoid" env: TEST_DEVICE: CPU TEST_PRECISION: FP16 diff --git a/.github/workflows/windows_conditional_compilation.yml b/.github/workflows/windows_conditional_compilation.yml index 6a47f620e73b30..8f025e66588e64 100644 --- a/.github/workflows/windows_conditional_compilation.yml +++ b/.github/workflows/windows_conditional_compilation.yml @@ -58,6 +58,7 @@ jobs: CMAKE_C_COMPILER_LAUNCHER: sccache SCCACHE_IGNORE_SERVER_IO_ERROR: 1 SCCACHE_SERVER_PORT: 35555 + SCCACHE_IDLE_TIMEOUT: 0 SCCACHE_ERROR_LOG: "${{ github.workspace }}\\openvino\\sccache_log.txt" SCCACHE_LOG: warn OPENVINO_REPO: "${{ github.workspace }}\\openvino" @@ -147,6 +148,7 @@ jobs: run: | cmake -G "${{ env.CMAKE_GENERATOR }}" ` -DBUILD_SHARED_LIBS=OFF ` + -DCMAKE_CXX_STANDARD=20 ` -DENABLE_TESTS=ON ` -DENABLE_CPPLINT=OFF ` -DENABLE_NCC_STYLE=OFF ` @@ -277,6 +279,7 @@ jobs: CMAKE_C_COMPILER_LAUNCHER: sccache SCCACHE_IGNORE_SERVER_IO_ERROR: 1 SCCACHE_SERVER_PORT: 35555 + SCCACHE_IDLE_TIMEOUT: 0 OPENVINO_REPO: "${{ github.workspace }}\\openvino" BUILD_DIR: "${{ github.workspace }}\\openvino_build" MODELS_PATH: "${{ github.workspace }}\\testdata" diff --git a/cmake/developer_package/packaging/debian/debian.cmake b/cmake/developer_package/packaging/debian/debian.cmake index d8e7bdc869baa9..fbff0d3828bcc7 100644 --- a/cmake/developer_package/packaging/debian/debian.cmake +++ b/cmake/developer_package/packaging/debian/debian.cmake @@ -153,7 +153,7 @@ macro(ov_debian_specific_settings) list(APPEND CPACK_DEBIAN_PACKAGE_SHLIBDEPS_PRIVATE_DIRS "${CMAKE_LIBRARY_OUTPUT_DIRECTORY}/${config}") endforeach() else() - set(CPACK_DEBIAN_PACKAGE_SHLIBDEPS_PRIVATE_DIRS "${CMAKE_LIBRARY_OUTPUT_DIRECTORY}") + list(APPEND CPACK_DEBIAN_PACKAGE_SHLIBDEPS_PRIVATE_DIRS "${CMAKE_LIBRARY_OUTPUT_DIRECTORY}") endif() else() message(FATAL_ERROR "CMAKE_LIBRARY_OUTPUT_DIRECTORY is empty") diff --git a/cmake/developer_package/version.cmake b/cmake/developer_package/version.cmake index f6114ab58c304d..adcd36f22646bb 100644 --- a/cmake/developer_package/version.cmake +++ b/cmake/developer_package/version.cmake @@ -160,13 +160,18 @@ macro (ov_add_version_defines FILE TARGET) if(NOT EXISTS ${__version_file}) message(FATAL_ERROR "${FILE} does not exists in current source directory") endif() + if (NOT TARGET ${TARGET}) + message(FATAL_ERROR "Invalid target ${TARGET}") + endif() _remove_source_from_target(${TARGET} ${FILE}) _remove_source_from_target(${TARGET} ${__version_file}) - if (BUILD_SHARED_LIBS) - add_library(${TARGET}_version OBJECT ${__version_file}) + get_target_property(__target_type ${TARGET} TYPE) + if (__target_type STREQUAL "STATIC_LIBRARY") + set(__lib_type STATIC) else() - add_library(${TARGET}_version STATIC ${__version_file}) + set(__lib_type OBJECT) endif() + add_library(${TARGET}_version ${__lib_type} ${__version_file}) if(SUGGEST_OVERRIDE_SUPPORTED) set_source_files_properties(${__version_file} PROPERTIES COMPILE_OPTIONS -Wno-suggest-override) diff --git a/cmake/packaging/copyrights/generic b/cmake/packaging/copyrights/generic index 8c09d518f8e501..2af564aad4bf65 100644 --- a/cmake/packaging/copyrights/generic +++ b/cmake/packaging/copyrights/generic @@ -414,7 +414,7 @@ License: Comment: The following third party programs have their own third party program files. These additional third party program files are as follows: oneAPI Deep Neural Network Library (oneDNN) Third Party Programs File is available here https://github.com/openvinotoolkit/openvino/blob/master/licensing/onednn_third-party-programs.txt - Intel(R) Threading Building Blocks Third Party Programs File is available here https://github.com/openvinotoolkit/openvino/blob/master/licensing/tbb_third-party-programs.txt + Intel(R) Threading Building Blocks Third Party Programs File is available here https://github.com/openvinotoolkit/openvino/blob/master/licensing/onetbb_third-party-programs.txt ------------------------------------------------------------- diff --git a/cmake/packaging/debian.cmake b/cmake/packaging/debian.cmake index 1d8d4a8cc7522b..835d6b0cab78b2 100644 --- a/cmake/packaging/debian.cmake +++ b/cmake/packaging/debian.cmake @@ -51,8 +51,8 @@ macro(ov_cpack_settings) NOT item MATCHES "^${OV_CPACK_COMP_PYTHON_OPENVINO}_python.*" AND # because in case of .deb package, pyopenvino_package_python${Python3_VERSION_MAJOR}${Python3_VERSION_MINOR} is installed (NOT item MATCHES "^${OV_CPACK_COMP_PYTHON_OPENVINO_PACKAGE}_python.*" OR ENABLE_PYTHON_PACKAGING) AND - # temporary block NVIDIA and NPU - NOT item MATCHES "^(nvidia|npu)$" AND + # temporary block nvidia + NOT item STREQUAL "nvidia" AND # don't install Intel OpenMP NOT item STREQUAL "omp" AND # the same for pugixml @@ -89,6 +89,7 @@ macro(ov_cpack_settings) 2023.1.0 2023.2.0 2023.3.0 2023.3.1 2023.3.2 2023.3.3 2023.3.4 2023.3.5 + 2024.0 ) # @@ -181,6 +182,27 @@ macro(ov_cpack_settings) set(gpu_copyright "generic") endif() + # intel-npu + if(ENABLE_INTEL_NPU OR BUILD_npu OR BUILD_vpux-plugin OR BUILD_applications.ai.vpu-accelerators.vpux-plugin) + set(CPACK_COMPONENT_NPU_DESCRIPTION "Intel® Neural Processing Unit inference plugin") + set(CPACK_COMPONENT_NPU_DEPENDS "${OV_CPACK_COMP_CORE}") + set(CPACK_DEBIAN_NPU_PACKAGE_NAME "libopenvino-intel-npu-plugin-${cpack_name_ver}") + set(CPACK_DEBIAN_NPU_PACKAGE_CONTROL_EXTRA "${def_postinst};${def_postrm}") + _ov_add_plugin(npu OFF) + set(npu_copyright "generic") + + # NPU plugin also builds level-zero as thirdparty + # let's add it to the list of dependency search directories to avoid missing dependncy on libze_loader.so.1 + if(OV_GENERATOR_MULTI_CONFIG) + # $ generator expression does not work in this place, have to add all possible configs + foreach(config IN LISTS CMAKE_CONFIGURATION_TYPES) + list(APPEND CPACK_DEBIAN_PACKAGE_SHLIBDEPS_PRIVATE_DIRS "${CMAKE_BINARY_DIR}/lib/${config}") + endforeach() + else() + list(APPEND CPACK_DEBIAN_PACKAGE_SHLIBDEPS_PRIVATE_DIRS "${CMAKE_BINARY_DIR}/lib") + endif() + endif() + # # add pseudo plugins are recommended to core component # if(pseudo_plugins_recommends) # # see https://superuser.com/questions/70031/what-is-the-difference-between-recommended-and-suggested-packages-ubuntu. diff --git a/cmake/packaging/rpm.cmake b/cmake/packaging/rpm.cmake index 55d52a4035815b..b3f3db1aa9e40f 100644 --- a/cmake/packaging/rpm.cmake +++ b/cmake/packaging/rpm.cmake @@ -37,8 +37,8 @@ macro(ov_cpack_settings) NOT item MATCHES "^${OV_CPACK_COMP_PYTHON_OPENVINO}_python.*" AND # because in case of .rpm package, pyopenvino_package_python${Python3_VERSION_MAJOR}${Python3_VERSION_MINOR} is installed (NOT item MATCHES "^${OV_CPACK_COMP_PYTHON_OPENVINO_PACKAGE}_python.*" OR ENABLE_PYTHON_PACKAGING) AND - # temporary block NVIDIA and NPU - NOT item MATCHES "^(nvidia|npu)$" AND + # temporary block nvidia + NOT item STREQUAL "nvidia" AND # don't install Intel OpenMP NOT item STREQUAL "omp" AND # the same for pugixml @@ -75,6 +75,7 @@ macro(ov_cpack_settings) 2023.1.0 2023.2.0 2023.3.0 2023.3.1 2023.3.2 2023.3.3 2023.3.4 2023.3.5 + 2024.0 ) find_host_program(rpmlint_PROGRAM NAMES rpmlint DOC "Path to rpmlint") @@ -177,6 +178,15 @@ macro(ov_cpack_settings) set(gpu_copyright "generic") endif() + # intel-npu + if(ENABLE_INTEL_NPU OR BUILD_npu OR BUILD_vpux-plugin OR BUILD_applications.ai.vpu-accelerators.vpux-plugin) + set(CPACK_COMPONENT_NPU_DESCRIPTION "Intel® Neural Processing Unit inference plugin") + set(CPACK_RPM_NPU_PACKAGE_REQUIRES "${core_package}") + set(CPACK_RPM_NPU_PACKAGE_NAME "libopenvino-intel-npu-plugin-${cpack_name_ver}") + _ov_add_package(plugin_packages npu) + set(npu_copyright "generic") + endif() + # # Frontends # diff --git a/cmake/toolchains/mt.runtime.win32.toolchain.cmake b/cmake/toolchains/mt.runtime.win32.toolchain.cmake index 440818e28f54fd..cfa275cb0ddae0 100644 --- a/cmake/toolchains/mt.runtime.win32.toolchain.cmake +++ b/cmake/toolchains/mt.runtime.win32.toolchain.cmake @@ -37,8 +37,6 @@ macro(ov_set_msvc_runtime var value) endif() endmacro() -# ade -ov_set_msvc_runtime(BUILD_WITH_STATIC_CRT ${use_static_runtime}) # static TBBBind_2_5 is built with dynamic CRT runtime ov_set_msvc_runtime(ENABLE_TBBBIND_2_5 ${use_dynamic_runtime}) # ONNX diff --git a/conan.lock b/conan.lock index d5e4bd423148e6..19142643d16ad3 100644 --- a/conan.lock +++ b/conan.lock @@ -14,8 +14,7 @@ "onetbb/2021.10.0#cbb2fc43088070b48f6e4339bc8fa0e1%1693812561.235", "ittapi/3.24.0#9246125f13e7686dee2b0c992b71db94%1682969872.743", "hwloc/2.9.2#1c63e2eccac57048ae226e6c946ebf0e%1688677682.002", - "flatbuffers/23.5.26#b153646f6546daab4c7326970b6cd89c%1685838458.449", - "ade/0.1.2d#f225d0a218a7c9fbb81746806c7de53d%1697752528.048" + "flatbuffers/23.5.26#b153646f6546daab4c7326970b6cd89c%1685838458.449" ], "build_requires": [ "zlib/1.2.13#97d5730b529b4224045fe7090592d4c1%1692672717.049", diff --git a/conanfile.txt b/conanfile.txt index cb23849a5daac5..5d9920874a629b 100644 --- a/conanfile.txt +++ b/conanfile.txt @@ -1,5 +1,4 @@ [requires] -ade/0.1.2d onetbb/[>=2021.2.1] pugixml/[>=1.10] protobuf/3.21.12 diff --git a/docs/articles_en/about_openvino.rst b/docs/articles_en/about-openvino.rst similarity index 100% rename from docs/articles_en/about_openvino.rst rename to docs/articles_en/about-openvino.rst diff --git a/docs/articles_en/about_openvino/additional_resources.rst b/docs/articles_en/about-openvino/additional-resources.rst similarity index 100% rename from docs/articles_en/about_openvino/additional_resources.rst rename to docs/articles_en/about-openvino/additional-resources.rst diff --git a/docs/articles_en/about_openvino/additional_resources/glossary.rst b/docs/articles_en/about-openvino/additional-resources/glossary.rst similarity index 91% rename from docs/articles_en/about_openvino/additional_resources/glossary.rst rename to docs/articles_en/about-openvino/additional-resources/glossary.rst index 24bbbd8b382644..c620fc3504fad0 100644 --- a/docs/articles_en/about_openvino/additional_resources/glossary.rst +++ b/docs/articles_en/about-openvino/additional-resources/glossary.rst @@ -114,16 +114,18 @@ Glossary of terms used in OpenVINO™ | Represents data element type. For example, f32 is 32-bit floating point, f16 is 16-bit floating point. | *plugin / Inference Device / Inference Mode* -| OpenVINO makes hardware available for inference based on several core components. They used to be called "plugins" in earlier versions of documentation and you may still find this term in some articles. Because of their role in the software, they are now referred to as Devices and Modes ("virtual" devices). For a detailed description of the concept, refer to [Inference Modes](@ref openvino_docs_Runtime_Inference_Modes_Overview) and [Inference Devices](@ref openvino_docs_OV_UG_Working_with_devices). +| OpenVINO makes hardware available for inference based on several core components. + They used to be called "plugins" in earlier versions of documentation and you may + still find this term in some articles. Because of their role in the software, + they are now referred to as Devices and Modes ("virtual" devices). For a detailed + description of the concept, refer to + :doc:`Inference Devices and Modes `. | *Tensor* -| A memory container used for storing inputs and outputs of the model, as well as weights and biases of the operations. +| A memory container used for storing inputs and outputs of the model, as well as + weights and biases of the operations. See Also ################################################# * :doc:`Available Operations Sets ` -* :doc:`Terminology ` - - - diff --git a/docs/articles_en/about_openvino/additional_resources/Legal_Information.rst b/docs/articles_en/about-openvino/additional-resources/legal-information.rst similarity index 100% rename from docs/articles_en/about_openvino/additional_resources/Legal_Information.rst rename to docs/articles_en/about-openvino/additional-resources/legal-information.rst diff --git a/docs/articles_en/about_openvino/additional_resources/telemetry_information.rst b/docs/articles_en/about-openvino/additional-resources/telemetry.rst similarity index 100% rename from docs/articles_en/about_openvino/additional_resources/telemetry_information.rst rename to docs/articles_en/about-openvino/additional-resources/telemetry.rst diff --git a/docs/articles_en/about_openvino/compatibility_and_support.rst b/docs/articles_en/about-openvino/compatibility-and-support.rst similarity index 68% rename from docs/articles_en/about_openvino/compatibility_and_support.rst rename to docs/articles_en/about-openvino/compatibility-and-support.rst index 1084fbdc7c646d..829fb3a39fe2d2 100644 --- a/docs/articles_en/about_openvino/compatibility_and_support.rst +++ b/docs/articles_en/about-openvino/compatibility-and-support.rst @@ -9,16 +9,16 @@ Compatibility and Support :hidden: openvino_supported_models - openvino_docs_OV_UG_supported_plugins_Supported_Devices + openvino_supported_devices openvino_resources_supported_operations openvino_resources_supported_operations_frontend -:doc:`Supported Devices ` - compatibility information for supported hardware accelerators. +:doc:`Supported Devices ` - compatibility information for supported hardware accelerators. :doc:`Supported Models ` - a table of models officially supported by OpenVINO. -:doc:`Supported Operations ` - a listing of framework layers supported by OpenVINO. +:doc:`Supported Operations ` - a listing of framework layers supported by OpenVINO. :doc:`Supported Operations ` - a listing of layers supported by OpenVINO inference devices. diff --git a/docs/articles_en/about-openvino/compatibility-and-support/supported-devices.rst b/docs/articles_en/about-openvino/compatibility-and-support/supported-devices.rst new file mode 100644 index 00000000000000..587e5beb8256eb --- /dev/null +++ b/docs/articles_en/about-openvino/compatibility-and-support/supported-devices.rst @@ -0,0 +1,104 @@ +.. {#openvino_supported_devices} + + +Inference Device Support +======================== + +.. meta:: + :description: Check the list of devices used by OpenVINO to run inference + of deep learning models. + + +The OpenVINO™ runtime enables you to use a selection of devices to run your +deep learning models: +:doc:`CPU `, +:doc:`GPU `, +:doc:`NPU `. + +| For their usage guides, see :doc:`Devices and Modes `. +| For a detailed list of devices, see :doc:`System Requirements `. + +Beside running inference with a specific device, +OpenVINO offers the option of running automated inference with the following inference modes: + +* :doc:`Automatic Device Selection ` - automatically selects the best device + available for the given task. It offers many additional options and optimizations, including inference on + multiple devices at the same time. +* :doc:`Heterogeneous Inference ` - enables splitting inference among several devices + automatically, for example, if one device doesn't support certain operations. +* :doc:`Multi-device Inference ` - executes inference on multiple devices. + Currently, this mode is considered a legacy solution. Using Automatic Device Selection is advised. +* :doc:`Automatic Batching ` - automatically groups inference requests to improve + device utilization. + + + +Feature Support and API Coverage +################################# + +================================================================================== ======= ========== =========== + Supported Feature CPU GPU NPU +================================================================================== ======= ========== =========== + :doc:`Heterogeneous execution ` Yes Yes No + :doc:`Multi-device execution ` Yes Yes Partial + :doc:`Automatic batching ` No Yes No + :doc:`Multi-stream execution ` Yes Yes No + :doc:`Models caching ` Yes Partial Yes + :doc:`Dynamic shapes ` Yes Partial No + :doc:`Import/Export ` Yes No Yes + :doc:`Preprocessing acceleration ` Yes Yes No + :doc:`Stateful models ` Yes No Yes + :doc:`Extensibility ` Yes Yes No +================================================================================== ======= ========== =========== + + ++-------------------------+-----------+------------------+-------------------+ +| **API Coverage:** | plugin | infer_request | compiled_model | ++=========================+===========+==================+===================+ +| CPU | 80.0 % | 100.0 % | 89.74 % | ++-------------------------+-----------+------------------+-------------------+ +| CPU_ARM | 80.0 % | 100.0 % | 89.74 % | ++-------------------------+-----------+------------------+-------------------+ +| GPU | 84.0 % | 100.0 % | 100.0 % | ++-------------------------+-----------+------------------+-------------------+ +| dGPU | 82.0 % | 100.0 % | 100.0 % | ++-------------------------+-----------+------------------+-------------------+ +| NPU | 16.0 % | 0.0 % | 10.26 % | ++-------------------------+-----------+------------------+-------------------+ +| AUTO | 40.0 % | 100.0 % | 97.44 % | ++-------------------------+-----------+------------------+-------------------+ +| BATCH | 26.0 % | 100.0 % | 58.97 % | ++-------------------------+-----------+------------------+-------------------+ +| MULTI | 30.0 % | 100.0 % | 58.97 % | ++-------------------------+-----------+------------------+-------------------+ +| HETERO | 30.0 % | 99.23 % | 58.97 % | ++-------------------------+-----------+------------------+-------------------+ +| || Percentage of API supported by the device, | +| || as of OpenVINO 2023.3, 08 Jan, 2024. | ++-------------------------+-----------+------------------+-------------------+ + + +Devices similar to the ones used for benchmarking can be accessed using +`Intel® DevCloud for the Edge `__, +a remote development environment with access to Intel® hardware and the latest versions +of the Intel® Distribution of OpenVINO™ Toolkit. +`Learn more `__ or +`Register here `__. + +For setting up a relevant configuration, refer to the +:doc:`Integrate with Customer Application ` +topic (step 3 "Configure input and output"). + + + +.. note:: + + With OpenVINO 2024.0 release, support for GNA has been discontinued. To keep using it + in your solutions, revert to the 2023.3 (LTS) version. + + With OpenVINO™ 2023.0 release, support has been cancelled for: + - Intel® Neural Compute Stick 2 powered by the Intel® Movidius™ Myriad™ X + - Intel® Vision Accelerator Design with Intel® Movidius™ + + To keep using the MYRIAD and HDDL plugins with your hardware, + revert to the OpenVINO 2022.3 (LTS) version. diff --git a/docs/articles_en/about_openvino/compatibility_and_support/supported_models.rst b/docs/articles_en/about-openvino/compatibility-and-support/supported-models.rst similarity index 100% rename from docs/articles_en/about_openvino/compatibility_and_support/supported_models.rst rename to docs/articles_en/about-openvino/compatibility-and-support/supported-models.rst diff --git a/docs/articles_en/about-openvino/compatibility-and-support/supported-operations-framework-frontend.rst b/docs/articles_en/about-openvino/compatibility-and-support/supported-operations-framework-frontend.rst new file mode 100644 index 00000000000000..ec60d5a4fdb638 --- /dev/null +++ b/docs/articles_en/about-openvino/compatibility-and-support/supported-operations-framework-frontend.rst @@ -0,0 +1,1079 @@ +.. {#openvino_resources_supported_operations_frontend} + +Supported Operations - by Framework Frontend +============================================ + + +.. meta:: + :description: Check the list of operations supported by OpenVINO Framework Frontend. + + +This page lists operations supported by OpenVINO Framework Frontend. + + +.. tab-set:: + + .. tab-item:: PyTorch + + ========================================== ========================================================================================== + PyTorch Supported Operations Limitations + ========================================== ========================================================================================== + aten::__and__ + aten::__derive_index + aten::__getitem__ + aten::__not__ + aten::__or__ + aten::__range_length + aten::__xor__ + aten::_convolution + aten::_convolution_mode + aten::_native_multi_head_attention + aten::_set_item + aten::_shape_as_tensor + aten::_upsample_bicubic2d_aa + aten::_upsample_bilinear2d_aa + aten::_weight_norm + aten::abs + aten::acos + aten::acos_ + aten::acosh + aten::acosh_ + aten::adaptive_avg_pool1d + aten::adaptive_avg_pool2d + aten::adaptive_avg_pool3d + aten::adaptive_max_pool1d + aten::adaptive_max_pool2d + aten::adaptive_max_pool3d + aten::add + aten::add_ + aten::addcmul + aten::addmm + aten::alias + aten::alias_copy + aten::all + aten::amax + aten::amin + aten::append Supported in limited set of patterns + aten::arange + aten::argmax + aten::argmin + aten::argsort + aten::as_strided + aten::as_tensor + aten::asin + aten::asin_ + aten::asinh + aten::asinh_ + aten::atan + aten::atan_ + aten::atanh + aten::atanh_ + aten::avg_pool1d + aten::avg_pool2d + aten::avg_pool3d + aten::baddbmm + aten::batch_norm + aten::bitwise_and + aten::bitwise_not + aten::bitwise_or + aten::bitwise_xor + aten::bmm + aten::Bool + aten::broadcast_tensors Supported in limited set of patterns + aten::broadcast_to + aten::cat + aten::cdist + aten::ceil + aten::ceil_ + aten::channel_shuffle + aten::chunk Supported in limited set of patterns + aten::clamp + aten::clamp_ + aten::clamp_max + aten::clamp_min + aten::clip + aten::clip_ + aten::clone + aten::complex Supported in limited set of patterns + aten::concat + aten::contiguous + aten::conv1d + aten::conv2d + aten::conv3d + aten::conv_transpose1d + aten::conv_transpose2d + aten::conv_transpose3d + aten::convolution + aten::copy + aten::copy_ + aten::cos + aten::cos_ + aten::cosh + aten::cosh_ + aten::cross + aten::cumsum + aten::dequantize + aten::detach + aten::dim + aten::div + aten::div_ + aten::dropout + aten::dropout_ + aten::einsum Supported in limited set of patterns + aten::elu + aten::embedding + aten::embedding_bag + aten::empty + aten::empty_like + aten::eq + aten::erf + aten::erf_ + aten::erfc + aten::erfc_ + aten::exp + aten::exp_ + aten::expand + aten::expand_as + aten::eye + aten::fake_quantize_per_channel_affine + aten::fake_quantize_per_tensor_affine + aten::feature_dropout + aten::fft_irfftn Supported in limited set of patterns + aten::fft_rfftn Supported in limited set of patterns + aten::fill + aten::fill_ + aten::fill_diagonal_ + aten::flatten + aten::flip + aten::floor + aten::floor_ + aten::floor_divide + aten::floordiv + aten::fmod + aten::frobenius_norm + aten::full + aten::full_like + aten::gather + aten::ge + aten::gelu + aten::glu + aten::grid_sampler + aten::group_norm + aten::gru + aten::gt + aten::hardsigmoid + aten::hardswish + aten::hardswish_ + aten::hardtanh + aten::hardtanh_ + aten::im2col + aten::imag Supported in limited set of patterns + aten::index Supported in limited set of patterns + aten::index_put_ + aten::index_select + aten::instance_norm + aten::Int + aten::IntImplicit + aten::is_grad_enabled + aten::is_nonzero + aten::item + aten::layer_norm + aten::le + aten::leaky_relu + aten::leaky_relu_ + aten::len + aten::lift + aten::lift_fresh + aten::lift_fresh_copy + aten::linalg_cross + aten::linalg_matrix_norm + aten::linalg_norm + aten::linalg_vector_norm + aten::linear + aten::linspace + aten::log + aten::log10 + aten::log10_ + aten::log1p + aten::log1p_ + aten::log2 + aten::log2_ + aten::log_ + aten::log_softmax + aten::logical_and + aten::logical_not + aten::logical_or + aten::logical_xor + aten::lstm + aten::lt + aten::masked_fill + aten::masked_fill_ + aten::masked_scatter + aten::masked_scatter_ + aten::matmul + aten::max + aten::max_pool1d + aten::max_pool1d_with_indices + aten::max_pool2d + aten::max_pool2d_with_indices + aten::max_pool3d + aten::max_pool3d_with_indices + aten::maximum + aten::mean + aten::meshgrid + aten::min + aten::minimum + aten::mm + aten::mul + aten::mul_ + aten::multinomial + aten::multiply + aten::multiply_ + aten::narrow + aten::ne + aten::neg + aten::new_empty + aten::new_full + aten::new_ones + aten::new_zeros + aten::nonzero + aten::nonzero_numpy Supported in limited set of patterns + aten::norm + aten::normal + aten::normal_ + aten::numel + aten::numpy_T + aten::one_hot + aten::ones + aten::ones_like + aten::outer + aten::pad + aten::pairwise_distance + aten::permute + aten::pixel_shuffle + aten::pixel_unshuffle + aten::pow + aten::pow_ + aten::prelu + aten::prod + aten::quantize_per_channel + aten::quantize_per_tensor + aten::rand + aten::rand_like + aten::randint + aten::randn + aten::randn_like + aten::real Supported in limited set of patterns + aten::reciprocal + aten::reflection_pad2d Supported in limited set of patterns + aten::relu + aten::relu6 + aten::relu_ + aten::remainder + aten::repeat + aten::repeat_interleave + aten::reshape + aten::reshape_as + aten::resolve_conj + aten::resolve_neg + aten::rnn_relu + aten::rnn_tanh + aten::roll + aten::round + aten::rsqrt + aten::rsub + aten::ScalarImplicit + aten::scaled_dot_product_attention + aten::scatter + aten::scatter_ + aten::scatter_add + aten::scatter_add_ + aten::scatter_reduce + aten::scatter_reduce_ + aten::select + aten::selu + aten::selu_ + aten::sigmoid + aten::sigmoid_ + aten::sign + aten::silu + aten::silu_ + aten::sin + aten::sin_ + aten::sinh + aten::sinh_ + aten::size + aten::slice + aten::softmax + aten::softplus + aten::sort + aten::split Supported in limited set of patterns + aten::split_with_sizes Supported in limited set of patterns + aten::sqrt + aten::square + aten::squeeze + aten::stack Supported in limited set of patterns + aten::std + aten::std_mean + aten::sub + aten::sub_ + aten::sum + aten::swapaxes + aten::t + aten::t_ + aten::take_along_dim + aten::tan + aten::tan_ + aten::tanh + aten::tanh_ + aten::tensor + aten::tensor_split Supported in limited set of patterns + aten::tile + aten::to + aten::topk + aten::transpose + aten::tril + aten::tril_ + aten::triu + aten::triu_ + aten::type_as + aten::unbind Supported in limited set of patterns + aten::unflatten + aten::unfold + aten::unsqueeze + aten::unsqueeze_ + aten::upsample_bicubic2d + aten::upsample_bilinear2d + aten::upsample_linear1d + aten::upsample_nearest1d + aten::upsample_nearest2d + aten::upsample_nearest3d + aten::upsample_trilinear3d + aten::var + aten::var_mean + aten::view + aten::view_as + aten::where + aten::zero_ + aten::zeros + aten::zeros_like + prim::Constant + prim::device + prim::DictConstruct Supported in limited set of patterns + prim::GetAttr + prim::If + prim::is_cuda + prim::ListConstruct + prim::ListUnpack + prim::Loop + prim::NumToTensor + prim::PythonOp + prim::requires_grad + prim::TupleConstruct Supported in limited set of patterns + prim::TupleIndex + prim::TupleUnpack Supported in limited set of patterns + prim::type + quantized::add + quantized::add_relu + quantized::cat + quantized::conv2d + quantized::conv2d_relu + quantized::hardswish + quantized::linear + quantized::mul + torchvision::deform_conv2d + torchvision::nms + torchvision::roi_align + ========================================== ========================================================================================== + + .. tab-item:: ONNX + + ========================================== ========================================================================================== + ONNX Supported Operations (standard) Limitations + ========================================== ========================================================================================== + Abs + Acos + Acosh + Add + And + ArgMin + ArgMax + Asin + Asinh + Atan + ATen + Atanh + AveragePool + BatchNormalization + BitShift + Cast + CastLike + Ceil + Clip + Concat + Constant + ConstantOfShape + Conv + ConvInteger + ConvTranspose + Compress + Cos + Cosh + ConstantFill + CumSum + DepthToSpace + DequantizeLinear + Div + Dropout + Einsum + Elu + Equal + Erf + Exp + Expand + EyeLike + Flatten + Floor + Gather + GatherElements + GatherND + Gemm + GlobalAveragePool + GlobalLpPool + GlobalMaxPool + Greater + GRU + Hardmax + HardSigmoid + HardSwish + Identity + If + ImageScaler + InstanceNormalization + LeakyRelu + Less + Log + LogSoftmax + Loop + LpNormalization + LRN + LSTM + MatMulInteger + MatMul + MaxPool + Max + Mean + MeanVarianceNormalization + Min + Mod + Mul + Neg + NonMaxSuppression + NonZero + Not + Or + OneHot + Pad + Pow + PRelu + QLinearConv + QLinearMatMul + QuantizeLinear + Range + RandomNormal + RandomNormalLike + RandomUniform + RandomUniformLike + Reciprocal + ReduceLogSum + ReduceLogSumExp + ReduceL1 + ReduceL2 + ReduceMax + ReduceMean + ReduceMin + ReduceProd + ReduceSum + ReduceSumSquare + Relu + Reshape + Resize + ReverseSequence + RNN + RoiAlign + Round + ScatterElements + ScatterND + Selu + Shape + Shrink + Sigmoid + Sign + Sin + Sinh + Size + Slice + Softmax + Softplus + Softsign + SpaceToDepth + Split + Sqrt + Squeeze + Sub + Sum + Tan + Tanh + ThresholdedRelu + Tile + TopK + Transpose + Unsqueeze + Where + Xor + ========================================== ========================================================================================== + + ========================================== ========================================================================================== + ONNX Supported Operations (deprecated) Limitations + ========================================== ========================================================================================== + Affine + Crop + Scatter + Upsample + ========================================== ========================================================================================== + + ====================================================================== ============================================================== + ONNX Supported Operations (custom - the org.openvinotoolkit Domain) Limitations + ====================================================================== ============================================================== + DeformableConv2D + DetectionOutput + ExperimentalDetectronDetectionOutput + ExperimentalDetectronGenerateProposalsSingleImage + ExperimentalDetectronGroupNorm + ExperimentalDetectronPriorGridGenerator + ExperimentalDetectronROIFeatureExtractor + ExperimentalDetectronTopKROIs + FakeQuantize + GroupNorm + Normalize + PriorBox + PriorBoxClustered + Swish + ====================================================================== ============================================================== + + ====================================================================== ============================================================== + ONNX Supported Operations (custom - com.microsoft Domain) Limitations + ====================================================================== ============================================================== + Attention + BiasGelu + EmbedLayerNormalization + SkipLayerNormalization + ====================================================================== ============================================================== + + .. tab-item:: PaddlePaddle + + ====================================================================== ============================================================== + PaddlePaddle Supported Operations (v. >= 2.1) Limitations + ====================================================================== ============================================================== + arg_max The ``int32`` output data_type is not supported. + adaptive_pool2d The ``NHWC`` data_layout is not supported. + assign + assign_value + batch_norm + bicubic_interp + bilinear_interp ``NCW``, ``NWC``, ``NHWC``, ``NCDHW``, ``NDHWC`` data_layout are not supported + bmm + box_coder + cast + ceil + clip + concat + conditional_block + conv2d ``NHWC`` data_layout is not supported + conv2d_transpose + cumsum + deformable_conv + depthwise_conv2d ``NHWC`` data_layout is not supported. + depthwise_conv2d_transpose + dropout + elementwise_add + elementwise_div + elementwise_floordiv + elementwise_max + elementwise_min + elementwise_mod + elementwise_mul + elementwise_pow + elementwise_sub + equal + exp + expand + fill_any_like + fill_constant + fill_constant_batch_size_like + flatten_contiguous_range + floor + gather + gather_nd + gelu + generate_proposals + greater_equal + greater_than + group_norm + hard_sigmoid + hard_swish + layer_norm + leaky_relu + less_than + linear_interp + log + logical_and + logical_not + logical_or + logical_xor + lookup_table + matmul + matrix_nms Only supports CPU plugin with "number of selected boxes" static shape (e.g.: ``min(min(num_boxes, nms_top_k) * num_classes_output, keep_top_k)``). + max_pool2d_with_index + meshgrid + multiclass_nms Only supports CPU plugin with "number of selected boxes" static shape (e.g.: ``min(min(num_boxes, nms_top_k) * num_classes_output, keep_top_k)``). + nearest_interp ``NCW``, ``NWC``, ``NHWC``, ``NCDHW``, ``NDHWC`` data_layout are not supported. + not_equal + p_norm + pad3d ``Circular`` mode is not supported. + pool2d ``NHWC`` data_layout is not supported. + pow + prior_box + range + reduce_max + reduce_mean + reduce_min + reduce_prod + reduce_sum + relu + reshape + reverse + rnn ``SimpleRNN`` and ``GRU`` modes are not supported. + roi_align + scale + select_input + shape + sigmoid + slice + softmax + softplus + split + sqrt + squeeze + stack + strided_slice + sum + swish + sync_batch_norm + tanh + tile + top_k + transpose + trilinear_interp + unsqueeze + where + where_index + while + yolo_box + ====================================================================== ============================================================== + + .. tab-item:: TensorFlow + + ========================================== ========================================================================================== + TensorFlow Supported Operations Limitations + ========================================== ========================================================================================== + Abs + Acosh + Add + AddV2 + AddN + All + Any + ArgMax + ArgMin + Asinh + Assert Not needed for inference. + Assign Not needed for inference. + AssignSub Not needed for inference. + Atanh + AvgPool + AvgPoolV2 Supported only for constant-foldable ``kernel_size`` and strides inputs. + AvgPool3D + BatchMatMul + BatchMatMulV2 + BatchToSpaceND + BiasAdd + BlockLSTM + Bucketize CPU only. + BroadcastTo + Cast + Ceil + ClipByValue + Concat + ConcatV2 + Const + Conv2D + Conv2DBackpropInput + Conv3D + Conv3DBackpropInputV2 + Cos + Cosh + CropAndResize ``method`` = ``bilinear`` only. + CTCGreedyDecoder Supported only with decoded indices output in a dense format. + CTCLoss Supported only with decoded indices input in a dense format. + CumSum + DepthToSpace + DepthwiseConv2dNative + Einsum Supported only with equation that does not contain repeated labels within a subscript. + Elu + EmptyTensorList Supported only when it is part of a sub-graph of the special form. + Enter Supported only when it is fused to the TensorIterator layer. + Equal + Erf + Exit Supported only when it is fused to the TensorIterator layer. + Exp + ExpandDims + ExperimentalSparseWeightedSum CPU only. + ExtractImagePatches + EuclideanNorm + FakeQuantWithMinMaxVars + FakeQuantWithMinMaxVarsPerChannel + FFT Supported only when it is part of a sub-graph of the special form. + FFT2D Supported only when it is part of a sub-graph of the special form. + FFT3D Supported only when it is part of a sub-graph of the special form. + FIFOQueueV2 Supported only when it is part of a sub-graph of the special form. + Fill + Floor + FloorDiv + FloorMod + FusedBatchNorm + FusedBatchNormV2 + FusedBatchNormV3 + Gather + GatherNd + GatherTree + GatherV2 + Greater + GreaterEqual + Identity Not needed for shape inference. + IdentityN + IFFT Supported only when it is part of a sub-graph of the special form. + IFFT2D Supported only when it is part of a sub-graph of the special form. + IFFT3D Supported only when it is part of a sub-graph of the special form. + IteratorGetNext Supported only when it is part of a sub-graph of the special form. + LRN + LeakyRelu + Less + LessEqual + Log + Log1p + LogicalAnd + LogicalOr + LogicalNot + LogSoftmax + LookupTableInsertV2 Supported only when it is part of a sub-graph of the special form. + LoopCond Supported only when it is fused to the TensorIterator layer. + MatMul + Max + MaxPool + MaxPoolV2 Supported only for constant-foldable ``kernel_size`` and strides inputs. + MaxPool3D + Maximum + Mean + Merge Supported only when it is fused to the TensorIterator layer. + Min + Minimum + MirrorPad + Mod + Mul + Neg + NextIteration Supported only when it is fused to the TensorIterator layer. + NonMaxSuppressionV2 + NonMaxSuppressionV3 + NonMaxSuppressionV4 + NonMaxSuppressionV5 + NotEqual + NoOp + OneHot + Pack + Pad + PadV2 + Placeholder + PlaceholderWithDefault + Prod + QueueDequeue Supported only when it is part of a sub-graph of the special form. + QueueDequeueUpToV2 Supported only when it is part of a sub-graph of the special form. + QueueDequeueV2 Supported only when it is part of a sub-graph of the special form. + RandomUniform + RandomUniformInt + Range + Rank + RealDiv + Reciprocal + Relu + Relu6 + Reshape + ResizeBilinear + ResizeNearestNeighbor + ResourceGather + ReverseSequence + ReverseV2 Supported only when it can be converted to the ReverseSequence operation. + Roll + Round + Pow + Rsqrt + ScatterNd + Select + SelectV2 + Shape + Sigmoid + Sin + Sinh + Size + Slice + Softmax + Softplus + Softsign + SpaceToBatchND + SpaceToDepth + SparseFillEmptyRows Supported only when it is part of a sub-graph of the special form. + SparseReshape Supported only when it is part of a sub-graph of the special form. + SparseSegmentSum Supported only when it is part of a sub-graph of the special form. + SparseSegmentMean Supported only when it is part of a sub-graph of the special form. + SparseToDense CPU only + Split + SplitV + Sqrt + Square + SquaredDifference + Square + Squeeze Cases in which squeeze axis is not specified are not supported. + StatelessWhile + StopGradient Not needed for shape inference. + StridedSlice Supported only for constant-foldable ``begin``, ``end``, and ``strides`` inputs. + Sub + Sum + Swish + swish_f32 + Switch Control flow propagation. + Tan + Tanh + TensorArrayGatherV3 Supported only when it is fused to the TensorIterator layer. + TensorArrayReadV3 Supported only when it is fused to the TensorIterator layer. + TensorArrayScatterV3 Supported only when it is fused to the TensorIterator layer. + TensorArraySizeV3 Supported only when it is fused to the TensorIterator layer. + TensorArrayV3 Supported only when it is fused to the TensorIterator layer. + TensorArrayWriteV3 Supported only when it is fused to the TensorIterator layer. + TensorListPushBack Supported only when it is part of a sub-graph of the special form. + Tile + TopkV2 + Transpose + Unpack + Variable + VariableV2 + Where Supported only when it is part of a sub-graph of the special form. + ZerosLike + ========================================== ========================================================================================== + + .. tab-item:: TensorFlow Lite + + ========================================== =============================================================================== + TensorFlow Lite Supported Operations Limitations + ========================================== =============================================================================== + ABS + ADD + ADD_N + ARG_MAX + ARG_MIN + AVERAGE_POOL_2D + BATCH_MATMUL + BATCH_TO_SPACE_ND + BROADCAST_ARGS + BROADCAST_TO + CAST + CEIL + COMPLEX_ABS Supported in a specific pattern with RFFT2D + CONCATENATION + CONV_2D + COS + DEPTH_TO_SPACE + DEPTHWISE_CONV_2D + DEQUANTIZE + DIV + ELU + EQUAL + EXP + EXPAND_DIMS + FILL + FLOOR + FLOOR_DIV + FLOOR_MOD + FULLY_CONNECTED + GATHER + GATHER_ND + GREATER + GREATER_EQUAL + HARD_SWISH + L2_NORMALIZATION + LEAKY_RELU + LESS + LESS_EQUAL + LOG + LOG_SOFTMAX + LOGICAL_AND + LOGICAL_NOT + LOGICAL_OR + LOGISTIC + MATRIX_DIAG + MAX_POOL_2D + MAXIMUM + MEAN + MINIMUM + MIRROR_PAD + MUL + NEG + NOT_EQUAL + ONE_HOT + PACK + PAD + PADV2 + POW + PRELU + QUANTIZE + RANGE + RANK + REDUCE_ALL + REDUCE_ANY + REDUCE_MAX + REDUCE_MIN + REDUCE_PROD + RELU + RELU6 + RESHAPE + RESIZE_BILINEAR + RESIZE_NEAREST_NEIGHBOR + REVERSE_V2 + RFFT2D Supported in a specific pattern with COMPLEX_ABS + ROUND + RSQRT + SCATTER_ND + SEGMENT_SUM + SELECT + SELECT_V2 + SHAPE + SIGN + SIN + SLICE + SOFTMAX + SPACE_TO_BATCH_ND + SPACE_TO_DEPTH + SPLIT + SPLIT_V + SQRT + SQUARE + SQUARED_DIFFERENCE + SQUEEZE + STRIDED_SLICE + SUB + SUM + TANH + TILE + TOPK_V2 + TRANSPOSE + TRANSPOSE_CONV + UNIQUE + UNPACK + WHERE + ZEROS_LIKE + ========================================== =============================================================================== + + .. tab-item:: TensorFlow2 Keras + + ========================================== ========================================================================================== + TensorFlow 2 Keras Supported Operations Limitations + ========================================== ========================================================================================== + ActivityRegularization + Add + AdditiveAttention + AlphaDropout + Attention + Average + AveragePooling1D + AveragePooling2D + AveragePooling3D + BatchNormalization + Bidirectional + Concatenate + Conv1D + Conv1DTranspose Not supported if ``dilation`` is not equal to 1. + Conv2D + Conv2DTranspose + Conv3D + Conv3DTranspose + Cropping1D + Cropping2D + Cropping3D + Dense + DenseFeatures Not supported for categorical and crossed features. + DepthwiseConv2D + Dot + Dropout + ELU + Embedding + Flatten + GRU + GRUCell + GaussianDropout + GaussianNoise + GlobalAveragePooling1D + GlobalAveragePooling2D + GlobalAveragePooling3D + GlobalMaxPool1D + GlobalMaxPool2D + GlobalMaxPool3D + LSTM + LSTMCell + Lambda + LayerNormalization + LeakyReLU + LocallyConnected1D + LocallyConnected2D + MaxPool1D + MaxPool2D + MaxPool3D + Maximum + Minimum + Multiply + PReLU + Permute + RNN Not supported for some custom cells. + ReLU + RepeatVector + Reshape + Roll + SeparableConv1D + SeparableConv2D + SimpleRNN + SimpleRNNCell + Softmax + SpatialDropout1D + SpatialDropout2D + SpatialDropout3D + StackedRNNCells + Subtract + ThresholdedReLU + TimeDistributed + UpSampling1D + UpSampling2D + UpSampling3D + ZeroPadding1D + ZeroPadding2D + ZeroPadding3D + ========================================== ========================================================================================== + + diff --git a/docs/articles_en/about_openvino/compatibility_and_support/supported_operations_inference_devices.rst b/docs/articles_en/about-openvino/compatibility-and-support/supported-operations-inference-devices.rst similarity index 100% rename from docs/articles_en/about_openvino/compatibility_and_support/supported_operations_inference_devices.rst rename to docs/articles_en/about-openvino/compatibility-and-support/supported-operations-inference-devices.rst diff --git a/docs/articles_en/about_openvino/performance_benchmarks.rst b/docs/articles_en/about-openvino/performance-benchmarks.rst similarity index 100% rename from docs/articles_en/about_openvino/performance_benchmarks.rst rename to docs/articles_en/about-openvino/performance-benchmarks.rst diff --git a/docs/articles_en/about_openvino/performance_benchmarks/Getting_performance_numbers.rst b/docs/articles_en/about-openvino/performance-benchmarks/getting-performance-numbers.rst similarity index 86% rename from docs/articles_en/about_openvino/performance_benchmarks/Getting_performance_numbers.rst rename to docs/articles_en/about-openvino/performance-benchmarks/getting-performance-numbers.rst index a10546e3e0a235..2253a5d581723d 100644 --- a/docs/articles_en/about_openvino/performance_benchmarks/Getting_performance_numbers.rst +++ b/docs/articles_en/about-openvino/performance-benchmarks/getting-performance-numbers.rst @@ -5,8 +5,8 @@ Getting Performance Numbers -This guide explains how to use the benchmark_app to get performance numbers. It also explains how the performance -numbers are reflected through internal inference performance counters and execution graphs. It also includes +This guide explains how to use the benchmark_app to get performance numbers. It also explains how the performance +numbers are reflected through internal inference performance counters and execution graphs. It also includes information on using ITT and Intel® VTune™ Profiler to get performance insights. Test performance with the benchmark_app @@ -19,7 +19,7 @@ The Python one is part of OpenVINO Runtime installation, while C++ is available For a detailed description, see: :doc:`benchmark_app `. Make sure to install the latest release package with support for frameworks of the models you want to test. -For the most reliable performance benchmarks, :doc:`prepare the model for use with OpenVINO `. +For the most reliable performance benchmarks, :doc:`prepare the model for use with OpenVINO `. Running the benchmark application @@ -32,10 +32,10 @@ The benchmark_app includes a lot of device-specific options, but the primary usa benchmark_app -m -d -i -Each of the :doc:`OpenVINO supported devices ` offers +Each of the :doc:`OpenVINO supported devices ` offers performance settings that contain command-line equivalents in the Benchmark app. -While these settings provide really low-level control for the optimal model performance on the *specific* device, +While these settings provide really low-level control for the optimal model performance on the *specific* device, it is recommended to always start performance evaluation with the :doc:`OpenVINO High-Level Performance Hints ` first, like so: .. code-block:: sh @@ -55,32 +55,32 @@ Additional benchmarking considerations When evaluating performance of a model with OpenVINO Runtime, it is required to measure a proper set of operations. - Avoid including one-time costs such as model loading. -- Track operations that occur outside OpenVINO Runtime (such as video decoding) separately. +- Track operations that occur outside OpenVINO Runtime (such as video decoding) separately. .. note:: - Some image pre-processing can be baked into OpenVINO IR and accelerated accordingly. For more information, - refer to :doc:`Embedding Pre-processing ` and + Some image pre-processing can be baked into OpenVINO IR and accelerated accordingly. For more information, + refer to :doc:`Embedding Pre-processing ` and :doc:`General Runtime Optimizations `. 2 - Try to Get Credible Data +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ -Performance conclusions should be build upon reproducible data. As for the performance measurements, they should -be done with a large number of invocations of the same routine. Since the first iteration is almost always significantly +Performance conclusions should be build upon reproducible data. As for the performance measurements, they should +be done with a large number of invocations of the same routine. Since the first iteration is almost always significantly slower than the subsequent ones, an aggregated value can be used for the execution time for final projections: -- If the warm-up run does not help or execution time still varies, you can try running a large number of iterations +- If the warm-up run does not help or execution time still varies, you can try running a large number of iterations and then average or find a mean of the results. - If the time values range too much, consider geomean. -- Be aware of the throttling and other power oddities. A device can exist in one of several different power states. - When optimizing your model, consider fixing the device frequency for better performance data reproducibility. +- Be aware of the throttling and other power oddities. A device can exist in one of several different power states. + When optimizing your model, consider fixing the device frequency for better performance data reproducibility. However, the end-to-end (application) benchmarking should also be performed under real operational conditions. -3 - Compare Performance with Native/Framework Code +3 - Compare Performance with Native/Framework Code +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ When comparing the OpenVINO Runtime performance with the framework or another reference code, make sure that both versions are as similar as possible: @@ -96,61 +96,61 @@ Internal Inference Performance Counters and Execution Graphs +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ More detailed insights into inference performance breakdown can be achieved with device-specific performance counters and/or execution graphs. -Both :doc:`C++ and Python ` +Both :doc:`C++ and Python ` versions of the *benchmark_app* support a ``-pc`` command-line parameter that outputs internal execution breakdown. -For example, the table shown below is part of performance counters for quantized -`TensorFlow implementation of ResNet-50 `__ +For example, the table shown below is part of performance counters for quantized +`TensorFlow implementation of ResNet-50 `__ model inference on :doc:`CPU Plugin `. -Keep in mind that since the device is CPU, the ``realTime`` wall clock and the ``cpu`` time layers are the same. -Information about layer precision is also stored in the performance counters. +Keep in mind that since the device is CPU, the ``realTime`` wall clock and the ``cpu`` time layers are the same. +Information about layer precision is also stored in the performance counters. =========================================================== ============= ============== ===================== ================= ============== - layerName execStatus layerType execType realTime (ms) cpuTime (ms) + layerName execStatus layerType execType realTime (ms) cpuTime (ms) =========================================================== ============= ============== ===================== ================= ============== - resnet\_model/batch\_normalization\_15/FusedBatchNorm/Add EXECUTED Convolution jit\_avx512\_1x1\_I8 0.377 0.377 - resnet\_model/conv2d\_16/Conv2D/fq\_input\_0 NOT\_RUN FakeQuantize undef 0 0 - resnet\_model/batch\_normalization\_16/FusedBatchNorm/Add EXECUTED Convolution jit\_avx512\_I8 0.499 0.499 - resnet\_model/conv2d\_17/Conv2D/fq\_input\_0 NOT\_RUN FakeQuantize undef 0 0 - resnet\_model/batch\_normalization\_17/FusedBatchNorm/Add EXECUTED Convolution jit\_avx512\_1x1\_I8 0.399 0.399 - resnet\_model/add\_4/fq\_input\_0 NOT\_RUN FakeQuantize undef 0 0 - resnet\_model/add\_4 NOT\_RUN Eltwise undef 0 0 - resnet\_model/add\_5/fq\_input\_1 NOT\_RUN FakeQuantize undef 0 0 + resnet\_model/batch\_normalization\_15/FusedBatchNorm/Add EXECUTED Convolution jit\_avx512\_1x1\_I8 0.377 0.377 + resnet\_model/conv2d\_16/Conv2D/fq\_input\_0 NOT\_RUN FakeQuantize undef 0 0 + resnet\_model/batch\_normalization\_16/FusedBatchNorm/Add EXECUTED Convolution jit\_avx512\_I8 0.499 0.499 + resnet\_model/conv2d\_17/Conv2D/fq\_input\_0 NOT\_RUN FakeQuantize undef 0 0 + resnet\_model/batch\_normalization\_17/FusedBatchNorm/Add EXECUTED Convolution jit\_avx512\_1x1\_I8 0.399 0.399 + resnet\_model/add\_4/fq\_input\_0 NOT\_RUN FakeQuantize undef 0 0 + resnet\_model/add\_4 NOT\_RUN Eltwise undef 0 0 + resnet\_model/add\_5/fq\_input\_1 NOT\_RUN FakeQuantize undef 0 0 =========================================================== ============= ============== ===================== ================= ============== | The ``execStatus`` column of the table includes the following possible values: | - ``EXECUTED`` - the layer was executed by standalone primitive. -| - ``NOT_RUN`` - the layer was not executed by standalone primitive or was fused with another operation and executed in another layer primitive. -| +| - ``NOT_RUN`` - the layer was not executed by standalone primitive or was fused with another operation and executed in another layer primitive. +| | The ``execType`` column of the table includes inference primitives with specific suffixes. The layers could have the following marks: | - The ``I8`` suffix is for layers that had 8-bit data type input and were computed in 8-bit precision. | - The ``FP32`` suffix is for layers computed in 32-bit precision. -| -| All ``Convolution`` layers are executed in ``int8`` precision. The rest of the layers are fused into Convolutions using post-operation optimization, - as described in :doc:`CPU Device `. This contains layer names +| +| All ``Convolution`` layers are executed in ``int8`` precision. The rest of the layers are fused into Convolutions using post-operation optimization, + as described in :doc:`CPU Device `. This contains layer names (as seen in OpenVINO IR), type of the layer, and execution statistics. -Both *benchmark_app* versions also support the ``exec_graph_path`` command-line option. It requires OpenVINO to output the same execution +Both *benchmark_app* versions also support the ``exec_graph_path`` command-line option. It requires OpenVINO to output the same execution statistics per layer, but in the form of plugin-specific `Netron-viewable `__ graph to the specified file. -Especially when performance-debugging the :doc:`latency `, note that the counters -do not reflect the time spent in the ``plugin/device/driver/etc`` queues. If the sum of the counters is too different from the latency -of an inference request, consider testing with less inference requests. For example, running single -:doc:`OpenVINO stream ` with multiple requests would produce nearly identical +Especially when performance-debugging the :doc:`latency `, note that the counters +do not reflect the time spent in the ``plugin/device/driver/etc`` queues. If the sum of the counters is too different from the latency +of an inference request, consider testing with less inference requests. For example, running single +:doc:`OpenVINO stream ` with multiple requests would produce nearly identical counters as running a single inference request, while the actual latency can be quite different. -Lastly, the performance statistics with both performance counters and execution graphs are averaged, -so such data for the :doc:`inputs of dynamic shapes ` should be measured carefully, +Lastly, the performance statistics with both performance counters and execution graphs are averaged, +so such data for the :doc:`inputs of dynamic shapes ` should be measured carefully, preferably by isolating the specific shape and executing multiple times in a loop, to gather reliable data. Use ITT to Get Performance Insights +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ -In general, OpenVINO and its individual plugins are heavily instrumented with Intel® Instrumentation and Tracing Technology (ITT). -Therefore, you can also compile OpenVINO from the source code with ITT enabled and use tools like -`Intel® VTune™ Profiler `__ to get detailed inference performance breakdown and additional +In general, OpenVINO and its individual plugins are heavily instrumented with Intel® Instrumentation and Tracing Technology (ITT). +Therefore, you can also compile OpenVINO from the source code with ITT enabled and use tools like +`Intel® VTune™ Profiler `__ to get detailed inference performance breakdown and additional insights in the application-level performance on the timeline view. diff --git a/docs/articles_en/about_openvino/performance_benchmarks/performance_int8_vs_fp32.rst b/docs/articles_en/about-openvino/performance-benchmarks/model-accuracy-int8-fp32.rst similarity index 100% rename from docs/articles_en/about_openvino/performance_benchmarks/performance_int8_vs_fp32.rst rename to docs/articles_en/about-openvino/performance-benchmarks/model-accuracy-int8-fp32.rst diff --git a/docs/articles_en/about_openvino/performance_benchmarks/performance_benchmarks_faq.rst b/docs/articles_en/about-openvino/performance-benchmarks/performance-benchmarks-faq.rst similarity index 93% rename from docs/articles_en/about_openvino/performance_benchmarks/performance_benchmarks_faq.rst rename to docs/articles_en/about-openvino/performance-benchmarks/performance-benchmarks-faq.rst index 8c22f86a446e00..8e90ba3c2f92c3 100644 --- a/docs/articles_en/about_openvino/performance_benchmarks/performance_benchmarks_faq.rst +++ b/docs/articles_en/about-openvino/performance-benchmarks/performance-benchmarks-faq.rst @@ -92,36 +92,35 @@ Performance Information F.A.Q. * - `ssd-mobilenet-v1-coco `__ - ssd-mobilenet-V1-coco onnx model - object detection - - 300x300 + - 300x300 * - `ssd-resnet34-1200-onnx `__ - ssd-resnet34 onnx model - object detection - - 1200x1200 + - 1200x1200 * - `unet-camvid-onnx-0001 `__ - U-Net - semantic segmentation - - 368x480 + - 368x480 * - `yolo-v3-tiny `__ - YOLO v3 Tiny - object detection - - 416x416 + - 416x416 * - `yolov8n `__ - - Yolov8nano + - Yolov8nano - object detection - 608x608 .. dropdown:: Where can I purchase the specific hardware used in the benchmarking? - Intel partners with vendors all over the world. For a list of Hardware Manufacturers, see the - `Intel® AI: In Production Partners & Solutions Catalog `__. - For more details, see the :doc:`Supported Devices `. - documentation. Before purchasing any hardware, you can test and run - models remotely, using `Intel® DevCloud for the Edge `__. + Intel partners with vendors all over the world. For a list of Hardware Manufacturers, see the + `Intel® AI: In Production Partners & Solutions Catalog `__. + Before purchasing any hardware, you can test and run models remotely, using + `Intel® DevCloud for the Edge `__. .. dropdown:: How can I optimize my models for better performance or accuracy? - Set of guidelines and recommendations to optimize models are available in the + Set of guidelines and recommendations to optimize models are available in the :doc:`optimization guide `. Join the conversation in the `Community Forum `__ for further support. diff --git a/docs/articles_en/about_openvino/releasenotes_for_openvino.rst b/docs/articles_en/about-openvino/release-notes-openvino.rst similarity index 100% rename from docs/articles_en/about_openvino/releasenotes_for_openvino.rst rename to docs/articles_en/about-openvino/release-notes-openvino.rst diff --git a/docs/articles_en/about_openvino/system_requirements.rst b/docs/articles_en/about-openvino/system-requirements.rst similarity index 99% rename from docs/articles_en/about_openvino/system_requirements.rst rename to docs/articles_en/about-openvino/system-requirements.rst index 35e9412705328c..be3b0da2329e7e 100644 --- a/docs/articles_en/about_openvino/system_requirements.rst +++ b/docs/articles_en/about-openvino/system-requirements.rst @@ -163,7 +163,6 @@ Operating systems and developer environment .. tab-item:: DL frameworks versions: * TensorFlow 1.15, 2.12 - * MxNet 1.9.0 * ONNX 1.14.1 * PaddlePaddle 2.4 diff --git a/docs/articles_en/about_openvino/compatibility_and_support/Supported_Devices.rst b/docs/articles_en/about_openvino/compatibility_and_support/Supported_Devices.rst deleted file mode 100644 index 22a24c8858a992..00000000000000 --- a/docs/articles_en/about_openvino/compatibility_and_support/Supported_Devices.rst +++ /dev/null @@ -1,61 +0,0 @@ -.. {#openvino_docs_OV_UG_supported_plugins_Supported_Devices} - -Supported Devices -================= - - - -.. meta:: - :description: Check the list of officially supported models in Intel® - Distribution of OpenVINO™ toolkit. - - -OpenVINO enables you to implement its inference capabilities in your own software, -utilizing various hardware. It currently supports the following processing units -(for more details, see :doc:`system requirements `): - -* :doc:`CPU ` -* :doc:`GPU ` - - -.. note:: - - With OpenVINO 2024 release, GNA has been deprecated together - with the hardware being discontinued in future CPU solutions. - - With OpenVINO™ 2023.0 release, support has been cancelled for: - - Intel® Neural Compute Stick 2 powered by the Intel® Movidius™ Myriad™ X - - Intel® Vision Accelerator Design with Intel® Movidius™ - - To keep using the MYRIAD and HDDL plugins with your hardware, revert to the OpenVINO 2022.3 LTS release. - - -Beside running inference with a specific device, -OpenVINO offers automated inference management with the following inference modes: - -* :doc:`Automatic Device Selection ` - automatically selects the best device - available for the given task. It offers many additional options and optimizations, including inference on - multiple devices at the same time. -* :doc:`Multi-device Inference ` - executes inference on multiple devices. - Currently, this mode is considered a legacy solution. Using Automatic Device Selection is advised. -* :doc:`Heterogeneous Inference ` - enables splitting inference among several devices - automatically, for example, if one device doesn’t support certain operations. - - -Devices similar to the ones used for benchmarking can be accessed using `Intel® DevCloud for the Edge `__, -a remote development environment with access to Intel® hardware and the latest versions of the Intel® Distribution -of OpenVINO™ Toolkit. `Learn more `__ or `Register here `__. - - -To learn more about each of the supported devices and modes, refer to the sections of: -* :doc:`Inference Device Support ` -* :doc:`Inference Modes ` - -For setting up a relevant configuration, refer to the -:doc:`Integrate with Customer Application ` -topic (step 3 "Configure input and output"). - - - - - diff --git a/docs/articles_en/about_openvino/compatibility_and_support/supported_operations_framework_frontend.rst b/docs/articles_en/about_openvino/compatibility_and_support/supported_operations_framework_frontend.rst deleted file mode 100644 index 1c4edeac967758..00000000000000 --- a/docs/articles_en/about_openvino/compatibility_and_support/supported_operations_framework_frontend.rst +++ /dev/null @@ -1,1275 +0,0 @@ -.. {#openvino_resources_supported_operations_frontend} - -Supported Operations - by Framework Frontend -============================================ - - -.. meta:: - :description: Check the list of operations supported by OpenVINO Framework Frontend. - - -This page lists operations supported by OpenVINO Framework Frontend. - - -.. tab-set:: - - .. tab-item:: PyTorch - - ========================================== ========================================================================================== - PyTorch Supported Operations Limitations - ========================================== ========================================================================================== - aten::__and__ - aten::__derive_index - aten::__getitem__ - aten::__not__ - aten::__or__ - aten::__range_length - aten::__xor__ - aten::_convolution - aten::_convolution_mode - aten::_native_multi_head_attention - aten::_set_item - aten::_shape_as_tensor - aten::_upsample_bicubic2d_aa - aten::_upsample_bilinear2d_aa - aten::_weight_norm - aten::abs - aten::acos - aten::acos_ - aten::acosh - aten::acosh_ - aten::adaptive_avg_pool1d - aten::adaptive_avg_pool2d - aten::adaptive_avg_pool3d - aten::adaptive_max_pool1d - aten::adaptive_max_pool2d - aten::adaptive_max_pool3d - aten::add - aten::add_ - aten::addcmul - aten::addmm - aten::alias - aten::alias_copy - aten::all - aten::amax - aten::amin - aten::append Supported in limited set of patterns - aten::arange - aten::argmax - aten::argmin - aten::argsort - aten::as_strided - aten::as_tensor - aten::asin - aten::asin_ - aten::asinh - aten::asinh_ - aten::atan - aten::atan_ - aten::atanh - aten::atanh_ - aten::avg_pool1d - aten::avg_pool2d - aten::avg_pool3d - aten::baddbmm - aten::batch_norm - aten::bitwise_and - aten::bitwise_not - aten::bitwise_or - aten::bitwise_xor - aten::bmm - aten::Bool - aten::broadcast_tensors Supported in limited set of patterns - aten::broadcast_to - aten::cat - aten::cdist - aten::ceil - aten::ceil_ - aten::channel_shuffle - aten::chunk Supported in limited set of patterns - aten::clamp - aten::clamp_ - aten::clamp_max - aten::clamp_min - aten::clip - aten::clip_ - aten::clone - aten::complex Supported in limited set of patterns - aten::concat - aten::contiguous - aten::conv1d - aten::conv2d - aten::conv3d - aten::conv_transpose1d - aten::conv_transpose2d - aten::conv_transpose3d - aten::convolution - aten::copy - aten::copy_ - aten::cos - aten::cos_ - aten::cosh - aten::cosh_ - aten::cross - aten::cumsum - aten::dequantize - aten::detach - aten::dim - aten::div - aten::div_ - aten::dropout - aten::dropout_ - aten::einsum Supported in limited set of patterns - aten::elu - aten::embedding - aten::embedding_bag - aten::empty - aten::empty_like - aten::eq - aten::erf - aten::erf_ - aten::erfc - aten::erfc_ - aten::exp - aten::exp_ - aten::expand - aten::expand_as - aten::eye - aten::fake_quantize_per_channel_affine - aten::fake_quantize_per_tensor_affine - aten::feature_dropout - aten::fft_irfftn Supported in limited set of patterns - aten::fft_rfftn Supported in limited set of patterns - aten::fill - aten::fill_ - aten::fill_diagonal_ - aten::flatten - aten::flip - aten::floor - aten::floor_ - aten::floor_divide - aten::floordiv - aten::fmod - aten::frobenius_norm - aten::full - aten::full_like - aten::gather - aten::ge - aten::gelu - aten::glu - aten::grid_sampler - aten::group_norm - aten::gru - aten::gt - aten::hardsigmoid - aten::hardswish - aten::hardswish_ - aten::hardtanh - aten::hardtanh_ - aten::im2col - aten::imag Supported in limited set of patterns - aten::index Supported in limited set of patterns - aten::index_put_ - aten::index_select - aten::instance_norm - aten::Int - aten::IntImplicit - aten::is_grad_enabled - aten::is_nonzero - aten::item - aten::layer_norm - aten::le - aten::leaky_relu - aten::leaky_relu_ - aten::len - aten::lift - aten::lift_fresh - aten::lift_fresh_copy - aten::linalg_cross - aten::linalg_matrix_norm - aten::linalg_norm - aten::linalg_vector_norm - aten::linear - aten::linspace - aten::log - aten::log10 - aten::log10_ - aten::log1p - aten::log1p_ - aten::log2 - aten::log2_ - aten::log_ - aten::log_softmax - aten::logical_and - aten::logical_not - aten::logical_or - aten::logical_xor - aten::lstm - aten::lt - aten::masked_fill - aten::masked_fill_ - aten::masked_scatter - aten::masked_scatter_ - aten::matmul - aten::max - aten::max_pool1d - aten::max_pool1d_with_indices - aten::max_pool2d - aten::max_pool2d_with_indices - aten::max_pool3d - aten::max_pool3d_with_indices - aten::maximum - aten::mean - aten::meshgrid - aten::min - aten::minimum - aten::mm - aten::mul - aten::mul_ - aten::multinomial - aten::multiply - aten::multiply_ - aten::narrow - aten::ne - aten::neg - aten::new_empty - aten::new_full - aten::new_ones - aten::new_zeros - aten::nonzero - aten::nonzero_numpy Supported in limited set of patterns - aten::norm - aten::normal - aten::normal_ - aten::numel - aten::numpy_T - aten::one_hot - aten::ones - aten::ones_like - aten::outer - aten::pad - aten::pairwise_distance - aten::permute - aten::pixel_shuffle - aten::pixel_unshuffle - aten::pow - aten::pow_ - aten::prelu - aten::prod - aten::quantize_per_channel - aten::quantize_per_tensor - aten::rand - aten::rand_like - aten::randint - aten::randn - aten::randn_like - aten::real Supported in limited set of patterns - aten::reciprocal - aten::reflection_pad2d Supported in limited set of patterns - aten::relu - aten::relu6 - aten::relu_ - aten::remainder - aten::repeat - aten::repeat_interleave - aten::reshape - aten::reshape_as - aten::resolve_conj - aten::resolve_neg - aten::rnn_relu - aten::rnn_tanh - aten::roll - aten::round - aten::rsqrt - aten::rsub - aten::ScalarImplicit - aten::scaled_dot_product_attention - aten::scatter - aten::scatter_ - aten::scatter_add - aten::scatter_add_ - aten::scatter_reduce - aten::scatter_reduce_ - aten::select - aten::selu - aten::selu_ - aten::sigmoid - aten::sigmoid_ - aten::sign - aten::silu - aten::silu_ - aten::sin - aten::sin_ - aten::sinh - aten::sinh_ - aten::size - aten::slice - aten::softmax - aten::softplus - aten::sort - aten::split Supported in limited set of patterns - aten::split_with_sizes Supported in limited set of patterns - aten::sqrt - aten::square - aten::squeeze - aten::stack Supported in limited set of patterns - aten::std - aten::std_mean - aten::sub - aten::sub_ - aten::sum - aten::swapaxes - aten::t - aten::t_ - aten::take_along_dim - aten::tan - aten::tan_ - aten::tanh - aten::tanh_ - aten::tensor - aten::tensor_split Supported in limited set of patterns - aten::tile - aten::to - aten::topk - aten::transpose - aten::tril - aten::tril_ - aten::triu - aten::triu_ - aten::type_as - aten::unbind Supported in limited set of patterns - aten::unflatten - aten::unfold - aten::unsqueeze - aten::unsqueeze_ - aten::upsample_bicubic2d - aten::upsample_bilinear2d - aten::upsample_linear1d - aten::upsample_nearest1d - aten::upsample_nearest2d - aten::upsample_nearest3d - aten::upsample_trilinear3d - aten::var - aten::var_mean - aten::view - aten::view_as - aten::where - aten::zero_ - aten::zeros - aten::zeros_like - prim::Constant - prim::device - prim::DictConstruct Supported in limited set of patterns - prim::GetAttr - prim::If - prim::is_cuda - prim::ListConstruct - prim::ListUnpack - prim::Loop - prim::NumToTensor - prim::PythonOp - prim::requires_grad - prim::TupleConstruct Supported in limited set of patterns - prim::TupleIndex - prim::TupleUnpack Supported in limited set of patterns - prim::type - quantized::add - quantized::add_relu - quantized::cat - quantized::conv2d - quantized::conv2d_relu - quantized::hardswish - quantized::linear - quantized::mul - torchvision::deform_conv2d - torchvision::nms - torchvision::roi_align - ========================================== ========================================================================================== - - .. tab-item:: ONNX - - ========================================== ========================================================================================== - ONNX Supported Operations (standard) Limitations - ========================================== ========================================================================================== - Abs - Acos - Acosh - Add - And - ArgMin - ArgMax - Asin - Asinh - Atan - ATen - Atanh - AveragePool - BatchNormalization - BitShift - Cast - CastLike - Ceil - Clip - Concat - Constant - ConstantOfShape - Conv - ConvInteger - ConvTranspose - Compress - Cos - Cosh - ConstantFill - CumSum - DepthToSpace - DequantizeLinear - Div - Dropout - Einsum - Elu - Equal - Erf - Exp - Expand - EyeLike - Flatten - Floor - Gather - GatherElements - GatherND - Gemm - GlobalAveragePool - GlobalLpPool - GlobalMaxPool - Greater - GRU - Hardmax - HardSigmoid - HardSwish - Identity - If - ImageScaler - InstanceNormalization - LeakyRelu - Less - Log - LogSoftmax - Loop - LpNormalization - LRN - LSTM - MatMulInteger - MatMul - MaxPool - Max - Mean - MeanVarianceNormalization - Min - Mod - Mul - Neg - NonMaxSuppression - NonZero - Not - Or - OneHot - Pad - Pow - PRelu - QLinearConv - QLinearMatMul - QuantizeLinear - Range - RandomNormal - RandomNormalLike - RandomUniform - RandomUniformLike - Reciprocal - ReduceLogSum - ReduceLogSumExp - ReduceL1 - ReduceL2 - ReduceMax - ReduceMean - ReduceMin - ReduceProd - ReduceSum - ReduceSumSquare - Relu - Reshape - Resize - ReverseSequence - RNN - RoiAlign - Round - ScatterElements - ScatterND - Selu - Shape - Shrink - Sigmoid - Sign - Sin - Sinh - Size - Slice - Softmax - Softplus - Softsign - SpaceToDepth - Split - Sqrt - Squeeze - Sub - Sum - Tan - Tanh - ThresholdedRelu - Tile - TopK - Transpose - Unsqueeze - Where - Xor - ========================================== ========================================================================================== - - ========================================== ========================================================================================== - ONNX Supported Operations (deprecated) Limitations - ========================================== ========================================================================================== - Affine - Crop - Scatter - Upsample - ========================================== ========================================================================================== - - ====================================================================== ============================================================== - ONNX Supported Operations (custom - the org.openvinotoolkit Domain) Limitations - ====================================================================== ============================================================== - DeformableConv2D - DetectionOutput - ExperimentalDetectronDetectionOutput - ExperimentalDetectronGenerateProposalsSingleImage - ExperimentalDetectronGroupNorm - ExperimentalDetectronPriorGridGenerator - ExperimentalDetectronROIFeatureExtractor - ExperimentalDetectronTopKROIs - FakeQuantize - GroupNorm - Normalize - PriorBox - PriorBoxClustered - Swish - ====================================================================== ============================================================== - - ====================================================================== ============================================================== - ONNX Supported Operations (custom - com.microsoft Domain) Limitations - ====================================================================== ============================================================== - Attention - BiasGelu - EmbedLayerNormalization - SkipLayerNormalization - ====================================================================== ============================================================== - - .. tab-item:: PaddlePaddle - - ====================================================================== ============================================================== - PaddlePaddle Supported Operations (v. >= 2.1) Limitations - ====================================================================== ============================================================== - arg_max The ``int32`` output data_type is not supported. - adaptive_pool2d The ``NHWC`` data_layout is not supported. - assign - assign_value - batch_norm - bicubic_interp - bilinear_interp ``NCW``, ``NWC``, ``NHWC``, ``NCDHW``, ``NDHWC`` data_layout are not supported - bmm - box_coder - cast - ceil - clip - concat - conditional_block - conv2d ``NHWC`` data_layout is not supported - conv2d_transpose - cumsum - deformable_conv - depthwise_conv2d ``NHWC`` data_layout is not supported. - depthwise_conv2d_transpose - dropout - elementwise_add - elementwise_div - elementwise_floordiv - elementwise_max - elementwise_min - elementwise_mod - elementwise_mul - elementwise_pow - elementwise_sub - equal - exp - expand - fill_any_like - fill_constant - fill_constant_batch_size_like - flatten_contiguous_range - floor - gather - gather_nd - gelu - generate_proposals - greater_equal - greater_than - group_norm - hard_sigmoid - hard_swish - layer_norm - leaky_relu - less_than - linear_interp - log - logical_and - logical_not - logical_or - logical_xor - lookup_table - matmul - matrix_nms Only supports IE CPU plugin with "number of selected boxes" static shape (e.g.: ``min(min(num_boxes, nms_top_k) * num_classes_output, keep_top_k)``). - max_pool2d_with_index - meshgrid - multiclass_nms Only supports IE CPU plugin with "number of selected boxes" static shape (e.g.: ``min(min(num_boxes, nms_top_k) * num_classes_output, keep_top_k)``). - nearest_interp ``NCW``, ``NWC``, ``NHWC``, ``NCDHW``, ``NDHWC`` data_layout are not supported. - not_equal - p_norm - pad3d ``Circular`` mode is not supported. - pool2d ``NHWC`` data_layout is not supported. - pow - prior_box - range - reduce_max - reduce_mean - reduce_min - reduce_prod - reduce_sum - relu - reshape - reverse - rnn ``SimpleRNN`` and ``GRU`` modes are not supported. - roi_align - scale - select_input - shape - sigmoid - slice - softmax - softplus - split - sqrt - squeeze - stack - strided_slice - sum - swish - sync_batch_norm - tanh - tile - top_k - transpose - trilinear_interp - unsqueeze - where - where_index - while - yolo_box - ====================================================================== ============================================================== - - .. tab-item:: Caffe - - ========================================== ========================================================================================== - Caffe Supported Operations Limitations - ========================================== ========================================================================================== - Axpy - BN - BatchNorm - Bias - Binarization (Intel experimental) - Concat - Convolution - ConvolutionBinary - Crop - Deconvolution - DetectionOutput - Dropout Not needed for inference. - Eltwise - Flatten - GlobalInput - InnerProduct - Input - LRN - Normalize - Python Supported only for the Python Proposal operation. - Permute - Pooling - Power - PReLU - PriorBox - PriorBoxClustered - Proposal - PSROIPooling - ROIPooling - RegionYolo - ReorgYolo - ReLU - Resample - Reshape - Scale - ShuffleChannel - Sigmoid - Slice - Softmax - Tile - ========================================== ========================================================================================== - - .. tab-item:: Kaldi - - ========================================== ========================================================================================== - Kaldi Supported Operations Limitations - ========================================== ========================================================================================== - addshift - affinecomponent - affinecomponentpreconditionedonline - affinetransform - backproptruncationcomponent - batchnormcomponent - clipgradientcomponent Not needed for inference. - concat - convolutional1dcomponent - convolutionalcomponent - copy - dropoutmaskcomponent - elementwiseproductcomponent - fixedaffinecomponent - fixedbiascomponent - fixedscalecomponent - generaldropoutcomponent Not needed for inference. - linearcomponent - logsoftmaxcomponent - lstmnonlinearitycomponent - lstmprojected - lstmprojectedstreams - maxpoolingcomponent - naturalgradientaffinecomponent - naturalgradientperelementscalecomponent - noopcomponent Not needed for inference. - normalizecomponent - parallelcomponent - pnormcomponent - rectifiedlinearcomponent - rescale - sigmoid - sigmoidcomponent - softmax - softmaxComponent - specaugmenttimemaskcomponent Not needed for inference. - splicecomponent - tanhcomponent - tdnncomponent - timeheightconvolutioncomponent - ========================================== ========================================================================================== - - .. tab-item:: Apache MXNet - - ========================================== ========================================================================================== - Apache MXNet Supported Operations Limitations - ========================================== ========================================================================================== - _Plus - _contrib_arange_like - _contrib_box_nms - _contrib_DeformableConvolution - _contrib_DeformablePSROIPooling - _contrib_div_sqrt_dim - _contrib_MultiBoxDetection ``force_suppress`` = 1 is not supported, non-default variances are not supported. - _contrib_MultiBoxPrior - _contrib_Proposal - _copy Not needed for inference - _div_scalar - _greater_scalar - _minus_scalar - _mul_scalar - _plus_scalar - _random_uniform Operation provides sequence from uniform distribution, but exact values won't match. - _rnn_param_concat - _arange - _contrib_AdaptiveAvgPooling2D Converted to the Average Pooling with fixed paddings. - _maximum - _minimum - _np_roll - _zeros - add_n - arccosh - arcsinh - arctanh - batch_dot - broadcast_add - broadcast_div - broadcast_mul - broadcast_sub - BlockGrad - cumsum - div_scalar - elementwise_sub - elemwise_add - elemwise_mul - elemwise_sub - exp - expand_dims - greater_scalar - max - minus_scalar - null Not needed for inference. - LayerNorm ``output_mean_var`` = True is not supported. - repeat - rnn - rnn_param_concat - round - sigmoid - slice - SliceChannel - slice_axis - slice_channel - slice_like - softmax - stack - swapaxis - tile - transpose - zeros - Activation Supported ``act_type`` = ``relu``, ``sigmoid``, ``softrelu`` or ``tanh`` - BatchNorm - Concat - Convolution - Crop ``center_crop`` = 1 is not supported. - Custom See :doc:`Custom Layers in Model Optimizer ` - Deconvolution - DeformableConvolution - DeformablePSROIPooling - Dropout Not needed for inference. - ElementWiseSum - Embedding - Flatten - FullyConnected - InstanceNorm - L2Normalization Only 4D input is supported. - LRN - LeakyReLU Supported ``act_type`` = ``prelu``, ``elu``, ``leaky``, ``gelu`` - ones_like - Pad - Pooling - ROIPooling - ReLU - Reshape - ScaleShift - SoftmaxActivation - SoftmaxOutput - SoftSign - Take The attribute ``mode`` is not supported. - Tile - UpSampling - Where - zeros_like - ========================================== ========================================================================================== - - .. tab-item:: TensorFlow - - ========================================== ========================================================================================== - TensorFlow Supported Operations Limitations - ========================================== ========================================================================================== - Abs - Acosh - Add - AddV2 - AddN - All - Any - ArgMax - ArgMin - Asinh - Assert Not needed for inference. - Assign Not needed for inference. - AssignSub Not needed for inference. - Atanh - AvgPool - AvgPoolV2 Supported only for constant-foldable ``kernel_size`` and strides inputs. - AvgPool3D - BatchMatMul - BatchMatMulV2 - BatchToSpaceND - BiasAdd - BlockLSTM - Bucketize CPU only. - BroadcastTo - Cast - Ceil - ClipByValue - Concat - ConcatV2 - Const - Conv2D - Conv2DBackpropInput - Conv3D - Conv3DBackpropInputV2 - Cos - Cosh - CropAndResize ``method`` = ``bilinear`` only. - CTCGreedyDecoder Supported only with decoded indices output in a dense format. - CTCLoss Supported only with decoded indices input in a dense format. - CumSum - DepthToSpace - DepthwiseConv2dNative - Einsum Supported only with equation that does not contain repeated labels within a subscript. - Elu - EmptyTensorList Supported only when it is part of a sub-graph of the special form. - Enter Supported only when it is fused to the TensorIterator layer. - Equal - Erf - Exit Supported only when it is fused to the TensorIterator layer. - Exp - ExpandDims - ExperimentalSparseWeightedSum CPU only. - ExtractImagePatches - EuclideanNorm - FakeQuantWithMinMaxVars - FakeQuantWithMinMaxVarsPerChannel - FFT Supported only when it is part of a sub-graph of the special form. - FFT2D Supported only when it is part of a sub-graph of the special form. - FFT3D Supported only when it is part of a sub-graph of the special form. - FIFOQueueV2 Supported only when it is part of a sub-graph of the special form. - Fill - Floor - FloorDiv - FloorMod - FusedBatchNorm - FusedBatchNormV2 - FusedBatchNormV3 - Gather - GatherNd - GatherTree - GatherV2 - Greater - GreaterEqual - Identity Not needed for shape inference. - IdentityN - IFFT Supported only when it is part of a sub-graph of the special form. - IFFT2D Supported only when it is part of a sub-graph of the special form. - IFFT3D Supported only when it is part of a sub-graph of the special form. - IteratorGetNext Supported only when it is part of a sub-graph of the special form. - LRN - LeakyRelu - Less - LessEqual - Log - Log1p - LogicalAnd - LogicalOr - LogicalNot - LogSoftmax - LookupTableInsertV2 Supported only when it is part of a sub-graph of the special form. - LoopCond Supported only when it is fused to the TensorIterator layer. - MatMul - Max - MaxPool - MaxPoolV2 Supported only for constant-foldable ``kernel_size`` and strides inputs. - MaxPool3D - Maximum - Mean - Merge Supported only when it is fused to the TensorIterator layer. - Min - Minimum - MirrorPad - Mod - Mul - Neg - NextIteration Supported only when it is fused to the TensorIterator layer. - NonMaxSuppressionV2 - NonMaxSuppressionV3 - NonMaxSuppressionV4 - NonMaxSuppressionV5 - NotEqual - NoOp - OneHot - Pack - Pad - PadV2 - Placeholder - PlaceholderWithDefault - Prod - QueueDequeue Supported only when it is part of a sub-graph of the special form. - QueueDequeueUpToV2 Supported only when it is part of a sub-graph of the special form. - QueueDequeueV2 Supported only when it is part of a sub-graph of the special form. - RandomUniform - RandomUniformInt - Range - Rank - RealDiv - Reciprocal - Relu - Relu6 - Reshape - ResizeBilinear - ResizeNearestNeighbor - ResourceGather - ReverseSequence - ReverseV2 Supported only when it can be converted to the ReverseSequence operation. - Roll - Round - Pow - Rsqrt - ScatterNd - Select - SelectV2 - Shape - Sigmoid - Sin - Sinh - Size - Slice - Softmax - Softplus - Softsign - SpaceToBatchND - SpaceToDepth - SparseFillEmptyRows Supported only when it is part of a sub-graph of the special form. - SparseReshape Supported only when it is part of a sub-graph of the special form. - SparseSegmentSum Supported only when it is part of a sub-graph of the special form. - SparseSegmentMean Supported only when it is part of a sub-graph of the special form. - SparseToDense CPU only - Split - SplitV - Sqrt - Square - SquaredDifference - Square - Squeeze Cases in which squeeze axis is not specified are not supported. - StatelessWhile - StopGradient Not needed for shape inference. - StridedSlice Supported only for constant-foldable ``begin``, ``end``, and ``strides`` inputs. - Sub - Sum - Swish - swish_f32 - Switch Control flow propagation. - Tan - Tanh - TensorArrayGatherV3 Supported only when it is fused to the TensorIterator layer. - TensorArrayReadV3 Supported only when it is fused to the TensorIterator layer. - TensorArrayScatterV3 Supported only when it is fused to the TensorIterator layer. - TensorArraySizeV3 Supported only when it is fused to the TensorIterator layer. - TensorArrayV3 Supported only when it is fused to the TensorIterator layer. - TensorArrayWriteV3 Supported only when it is fused to the TensorIterator layer. - TensorListPushBack Supported only when it is part of a sub-graph of the special form. - Tile - TopkV2 - Transpose - Unpack - Variable - VariableV2 - Where Supported only when it is part of a sub-graph of the special form. - ZerosLike - ========================================== ========================================================================================== - - .. tab-item:: TensorFlow Lite - - ========================================== =============================================================================== - TensorFlow Lite Supported Operations Limitations - ========================================== =============================================================================== - ABS - ADD - ADD_N - ARG_MAX - ARG_MIN - AVERAGE_POOL_2D - BATCH_MATMUL - BATCH_TO_SPACE_ND - BROADCAST_ARGS - BROADCAST_TO - CAST - CEIL - COMPLEX_ABS Supported in a specific pattern with RFFT2D - CONCATENATION - CONV_2D - COS - DEPTH_TO_SPACE - DEPTHWISE_CONV_2D - DEQUANTIZE - DIV - ELU - EQUAL - EXP - EXPAND_DIMS - FILL - FLOOR - FLOOR_DIV - FLOOR_MOD - FULLY_CONNECTED - GATHER - GATHER_ND - GREATER - GREATER_EQUAL - HARD_SWISH - L2_NORMALIZATION - LEAKY_RELU - LESS - LESS_EQUAL - LOG - LOG_SOFTMAX - LOGICAL_AND - LOGICAL_NOT - LOGICAL_OR - LOGISTIC - MATRIX_DIAG - MAX_POOL_2D - MAXIMUM - MEAN - MINIMUM - MIRROR_PAD - MUL - NEG - NOT_EQUAL - ONE_HOT - PACK - PAD - PADV2 - POW - PRELU - QUANTIZE - RANGE - RANK - REDUCE_ALL - REDUCE_ANY - REDUCE_MAX - REDUCE_MIN - REDUCE_PROD - RELU - RELU6 - RESHAPE - RESIZE_BILINEAR - RESIZE_NEAREST_NEIGHBOR - REVERSE_V2 - RFFT2D Supported in a specific pattern with COMPLEX_ABS - ROUND - RSQRT - SCATTER_ND - SEGMENT_SUM - SELECT - SELECT_V2 - SHAPE - SIGN - SIN - SLICE - SOFTMAX - SPACE_TO_BATCH_ND - SPACE_TO_DEPTH - SPLIT - SPLIT_V - SQRT - SQUARE - SQUARED_DIFFERENCE - SQUEEZE - STRIDED_SLICE - SUB - SUM - TANH - TILE - TOPK_V2 - TRANSPOSE - TRANSPOSE_CONV - UNIQUE - UNPACK - WHERE - ZEROS_LIKE - ========================================== =============================================================================== - - .. tab-item:: TensorFlow2 Keras - - ========================================== ========================================================================================== - TensorFlow 2 Keras Supported Operations Limitations - ========================================== ========================================================================================== - ActivityRegularization - Add - AdditiveAttention - AlphaDropout - Attention - Average - AveragePooling1D - AveragePooling2D - AveragePooling3D - BatchNormalization - Bidirectional - Concatenate - Conv1D - Conv1DTranspose Not supported if ``dilation`` is not equal to 1. - Conv2D - Conv2DTranspose - Conv3D - Conv3DTranspose - Cropping1D - Cropping2D - Cropping3D - Dense - DenseFeatures Not supported for categorical and crossed features. - DepthwiseConv2D - Dot - Dropout - ELU - Embedding - Flatten - GRU - GRUCell - GaussianDropout - GaussianNoise - GlobalAveragePooling1D - GlobalAveragePooling2D - GlobalAveragePooling3D - GlobalMaxPool1D - GlobalMaxPool2D - GlobalMaxPool3D - LSTM - LSTMCell - Lambda - LayerNormalization - LeakyReLU - LocallyConnected1D - LocallyConnected2D - MaxPool1D - MaxPool2D - MaxPool3D - Maximum - Minimum - Multiply - PReLU - Permute - RNN Not supported for some custom cells. - ReLU - RepeatVector - Reshape - Roll - SeparableConv1D - SeparableConv2D - SimpleRNN - SimpleRNNCell - Softmax - SpatialDropout1D - SpatialDropout2D - SpatialDropout3D - StackedRNNCells - Subtract - ThresholdedReLU - TimeDistributed - UpSampling1D - UpSampling2D - UpSampling3D - ZeroPadding1D - ZeroPadding2D - ZeroPadding3D - ========================================== ========================================================================================== - - diff --git a/docs/articles_en/documentation.rst b/docs/articles_en/documentation.rst index d1b8da2a1bd814..d7e6585ec3dfc7 100644 --- a/docs/articles_en/documentation.rst +++ b/docs/articles_en/documentation.rst @@ -5,7 +5,7 @@ Documentation .. meta:: - :description: Explore the OpenVINO toolkit workflow that entails preparing, + :description: Explore the OpenVINO toolkit workflow that entails preparing, optimizing and deploying models in deep learning applications. @@ -14,8 +14,8 @@ Documentation :hidden: API Reference - OpenVINO IR format and Operation Sets - Legacy Features + OpenVINO IR format and Operation Sets + Legacy Features Tool Ecosystem OpenVINO Extensibility OpenVINO™ Security @@ -24,14 +24,14 @@ Documentation This section provides reference documents that guide you through the OpenVINO toolkit workflow, from preparing models, optimizing them, to deploying them in your own deep learning applications. | :doc:`API Reference doc path ` -| A collection of reference articles for OpenVINO C++, C, and Python APIs. +| A collection of reference articles for OpenVINO C++, C, and Python APIs. | :doc:`OpenVINO Ecosystem ` | Apart from the core components, OpenVINO offers tools, plugins, and expansions revolving around it, even if not constituting necessary parts of its workflow. This section gives you an overview of what makes up the OpenVINO toolkit. | :doc:`OpenVINO Extensibility Mechanism ` -| The Intel® Distribution of OpenVINO™ toolkit supports neural network models trained with various frameworks, including TensorFlow, PyTorch, ONNX, TensorFlow Lite, and PaddlePaddle (OpenVINO support for Apache MXNet, Caffe, and Kaldi is being deprecated and will be removed in the future). Learn how to extend OpenVINO functionality with custom settings. +| The Intel® Distribution of OpenVINO™ toolkit supports neural network models trained with various frameworks, including TensorFlow, PyTorch, ONNX, TensorFlow Lite, and PaddlePaddle. Learn how to extend OpenVINO functionality with custom settings. | :doc:`OpenVINO™ Security ` -| Learn how to use OpenVINO securely and protect your data to meet specific security and privacy requirements. +| Learn how to use OpenVINO securely and protect your data to meet specific security and privacy requirements. diff --git a/docs/articles_en/documentation/openvino_legacy_features.rst b/docs/articles_en/documentation/legacy-features.rst similarity index 80% rename from docs/articles_en/documentation/openvino_legacy_features.rst rename to docs/articles_en/documentation/legacy-features.rst index 311e1bc2529bd9..ba2d3d94301970 100644 --- a/docs/articles_en/documentation/openvino_legacy_features.rst +++ b/docs/articles_en/documentation/legacy-features.rst @@ -60,26 +60,24 @@ offering. | :doc:`See the Open Model ZOO documentation ` | `Check the OMZ GitHub project `__ - | **Apache MXNet, Caffe, and Kaldi model formats** | *New solution:* conversion to ONNX via external tools | *Old solution:* model support discontinued with OpenVINO 2024.0 | -| `See the previous conversion instructions `__ +| `The last version supporting Apache MXNet, Caffe, and Kaldi model formats `__ | :doc:`See the currently supported frameworks ` | **Post-training Optimization Tool (POT)** | *New solution:* NNCF extended in OpenVINO 2023.0 -| *Old solution:* POT discontinuation planned for 2024.0 +| *Old solution:* POT discontinued with OpenVINO 2024.0 | | Neural Network Compression Framework (NNCF) now offers the same functionality as POT, - apart from its original feature set. It is currently the default tool for performing - both, post-training and quantization optimizations, while POT is considered deprecated. + apart from its original feature set. + | :doc:`See how to use NNCF for model optimization ` | `Check the NNCF GitHub project, including documentation `__ - | **Inference API 1.0** | *New solution:* API 2.0 launched in OpenVINO 2022.1 | *Old solution:* discontinued with OpenVINO 2024.0 @@ -90,28 +88,24 @@ offering. | *New solution:* the tool is no longer needed | *Old solution:* deprecated in OpenVINO 2023.0 | -| Compile tool is now deprecated. If you need to compile a model for inference on - a specific device, use the following script: +| If you need to compile a model for inference on a specific device, use the following script: - .. tab-set:: +.. tab-set:: - .. tab-item:: Python - :sync: py + .. tab-item:: Python + :sync: py - .. doxygensnippet:: docs/snippets/export_compiled_model.py - :language: python - :fragment: [export_compiled_model] + .. doxygensnippet:: docs/snippets/export_compiled_model.py + :language: python + :fragment: [export_compiled_model] - .. tab-item:: C++ - :sync: cpp + .. tab-item:: C++ + :sync: cpp - .. doxygensnippet:: docs/snippets/export_compiled_model.cpp - :language: cpp - :fragment: [export_compiled_model] + .. doxygensnippet:: docs/snippets/export_compiled_model.cpp + :language: cpp + :fragment: [export_compiled_model] -| :doc:`see which devices support import / export ` -| :doc:`Learn more on preprocessing steps ` -| :doc:`See how to integrate and save preprocessing steps into OpenVINO IR ` | **DL Workbench** | *New solution:* DevCloud version diff --git a/docs/articles_en/documentation/openvino_legacy_features/--installing-model-dev-tools.rst b/docs/articles_en/documentation/legacy-features/install-dev-tools.rst similarity index 98% rename from docs/articles_en/documentation/openvino_legacy_features/--installing-model-dev-tools.rst rename to docs/articles_en/documentation/legacy-features/install-dev-tools.rst index 956228c3603fb5..f09d372df51cd3 100644 --- a/docs/articles_en/documentation/openvino_legacy_features/--installing-model-dev-tools.rst +++ b/docs/articles_en/documentation/legacy-features/install-dev-tools.rst @@ -13,7 +13,6 @@ OpenVINO Development Tools is a set of utilities that make it easy to develop an * Model conversion API * Benchmark Tool * Accuracy Checker and Annotation Converter -* Post-Training Optimization Tool * Model Downloader and other Open Model Zoo tools The instructions on this page show how to install OpenVINO Development Tools. If you are a Python developer, it only takes a few simple steps to install the tools with PyPI. If you are developing in C/C++, OpenVINO Runtime must be installed separately before installing OpenVINO Development Tools. @@ -138,7 +137,7 @@ To install and configure the components of the development package together with where the ``extras`` parameter specifies the source deep learning framework for the input model -and is one or more of the following values separated with "," : ``caffe``, ``kaldi``, ``mxnet``, ``onnx``, ``pytorch``, ``tensorflow``, ``tensorflow2``. +and is one or more of the following values separated with "," : ``onnx``, ``pytorch``, ``tensorflow``, ``tensorflow2``. For example, to install and configure dependencies required for working with TensorFlow 2.x and ONNX models, use the following command: diff --git a/docs/articles_en/documentation/openvino_legacy_features/model_zoo.rst b/docs/articles_en/documentation/legacy-features/model-zoo.rst similarity index 100% rename from docs/articles_en/documentation/openvino_legacy_features/model_zoo.rst rename to docs/articles_en/documentation/legacy-features/model-zoo.rst diff --git a/docs/articles_en/documentation/openvino_legacy_features/mo_ovc_transition.rst b/docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api.rst similarity index 99% rename from docs/articles_en/documentation/openvino_legacy_features/mo_ovc_transition.rst rename to docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api.rst index 456b612a1bb511..210592cdeb2038 100644 --- a/docs/articles_en/documentation/openvino_legacy_features/mo_ovc_transition.rst +++ b/docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api.rst @@ -860,7 +860,6 @@ Supported Frameworks in MO vs OVC ################################# ov.convert_model() and OVC tool support conversion from PyTorch, TF, TF Lite, ONNX, PaddlePaddle. -The following frameworks are supported only in MO and mo.convert_model(): Caffe, MxNet, Kaldi. diff --git a/docs/articles_en/documentation/openvino_legacy_features/mo_ovc_transition/legacy_conversion_api.rst b/docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api.rst similarity index 100% rename from docs/articles_en/documentation/openvino_legacy_features/mo_ovc_transition/legacy_conversion_api.rst rename to docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api.rst diff --git a/docs/articles_en/documentation/openvino_legacy_features/mo_ovc_transition/legacy_conversion_api/fp16_compression.rst b/docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api/[legacy]-compressing-model-to-fp16.rst similarity index 95% rename from docs/articles_en/documentation/openvino_legacy_features/mo_ovc_transition/legacy_conversion_api/fp16_compression.rst rename to docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api/[legacy]-compressing-model-to-fp16.rst index a692fe389451ae..421010ab6b333b 100644 --- a/docs/articles_en/documentation/openvino_legacy_features/mo_ovc_transition/legacy_conversion_api/fp16_compression.rst +++ b/docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api/[legacy]-compressing-model-to-fp16.rst @@ -7,8 +7,8 @@ The code described here has been **deprecated!** Do not use it to avoid working with a legacy solution. It will be kept for some time to ensure backwards compatibility, but **you should not use** it in contemporary applications. - This guide describes a deprecated conversion method. The guide on the new and recommended method can be found in the :doc:`Conversion Parameters ` article. - + This guide describes a deprecated conversion method. The guide on the new and recommended method can be found in the :doc:`Conversion Parameters ` article. + By default, when IR is saved all relevant floating-point weights are compressed to ``FP16`` data type during model conversion. It results in creating a "compressed ``FP16`` model", which occupies about half of the original space in the file system. The compression may introduce a minor drop in accuracy, @@ -37,7 +37,7 @@ To disable compression, use the ``compress_to_fp16=False`` option: For details on how plugins handle compressed ``FP16`` models, see -:doc:`Working with devices `. +:doc:`Inference Devices and Modes `. .. note:: diff --git a/docs/articles_en/documentation/openvino_legacy_features/mo_ovc_transition/legacy_conversion_api/convert_python_model_objects.rst b/docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api/[legacy]-convert-models-as-python-objects.rst similarity index 100% rename from docs/articles_en/documentation/openvino_legacy_features/mo_ovc_transition/legacy_conversion_api/convert_python_model_objects.rst rename to docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api/[legacy]-convert-models-as-python-objects.rst diff --git a/docs/articles_en/documentation/openvino_legacy_features/mo_ovc_transition/legacy_conversion_api/cutting_model.rst b/docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api/[legacy]-cutting-parts-of-a-model.rst similarity index 100% rename from docs/articles_en/documentation/openvino_legacy_features/mo_ovc_transition/legacy_conversion_api/cutting_model.rst rename to docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api/[legacy]-cutting-parts-of-a-model.rst diff --git a/docs/articles_en/documentation/openvino_legacy_features/mo_ovc_transition/legacy_conversion_api/embedding_preprocessing_computation.rst b/docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api/[legacy]-embedding-preprocessing-computation.rst similarity index 100% rename from docs/articles_en/documentation/openvino_legacy_features/mo_ovc_transition/legacy_conversion_api/embedding_preprocessing_computation.rst rename to docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api/[legacy]-embedding-preprocessing-computation.rst diff --git a/docs/articles_en/documentation/openvino_legacy_features/mo_ovc_transition/legacy_conversion_api/model_optimizer_faq.rst b/docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api/[legacy]-model-optimizer-faq.rst similarity index 99% rename from docs/articles_en/documentation/openvino_legacy_features/mo_ovc_transition/legacy_conversion_api/model_optimizer_faq.rst rename to docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api/[legacy]-model-optimizer-faq.rst index 030cd6c7dbbdf2..713610807eb47b 100644 --- a/docs/articles_en/documentation/openvino_legacy_features/mo_ovc_transition/legacy_conversion_api/model_optimizer_faq.rst +++ b/docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api/[legacy]-model-optimizer-faq.rst @@ -14,8 +14,7 @@ where you can participate in a free forum discussion. .. warning:: - Note that OpenVINO support for Apache MXNet, Caffe, and Kaldi is currently being deprecated. - As legacy formats, they will not be supported as actively as the main frontends and will be removed entirely in the future. + Note that OpenVINO support for Apache MXNet, Caffe, and Kaldi has been discontinued. .. _question-1: diff --git a/docs/articles_en/documentation/openvino_legacy_features/mo_ovc_transition/legacy_conversion_api/setting_input_shapes.rst b/docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api/[legacy]-setting-input-shapes.rst similarity index 96% rename from docs/articles_en/documentation/openvino_legacy_features/mo_ovc_transition/legacy_conversion_api/setting_input_shapes.rst rename to docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api/[legacy]-setting-input-shapes.rst index a4e5e1fb935149..ef1872b73f8f94 100644 --- a/docs/articles_en/documentation/openvino_legacy_features/mo_ovc_transition/legacy_conversion_api/setting_input_shapes.rst +++ b/docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api/[legacy]-setting-input-shapes.rst @@ -7,12 +7,12 @@ The code described here has been **deprecated!** Do not use it to avoid working with a legacy solution. It will be kept for some time to ensure backwards compatibility, but **you should not use** it in contemporary applications. - This guide describes a deprecated conversion method. The guide on the new and recommended method can be found in the :doc:`Setting Input Shapes ` article. + This guide describes a deprecated conversion method. The guide on the new and recommended method can be found in the :doc:`Setting Input Shapes ` article. With model conversion API you can increase your model's efficiency by providing an additional shape definition, with these two parameters: `input_shape` and `static_shape`. -.. meta:: +.. meta:: :description: Learn how to increase the efficiency of a model with MO by providing an additional shape definition with the input_shape and static_shape parameters. @@ -27,7 +27,7 @@ To set up static shapes, model conversion API provides the ``input_shape`` param For more information on input shapes under runtime, refer to the :doc:`Changing input shapes ` guide. To learn more about dynamic shapes in runtime, refer to the :doc:`Dynamic Shapes ` guide. -The OpenVINO Runtime API may present certain limitations in inferring models with undefined dimensions on some hardware. See the :doc:`Features support matrix ` for reference. +The OpenVINO Runtime API may present certain limitations in inferring models with undefined dimensions on some hardware. In this case, the ``input_shape`` parameter and the :doc:`reshape method ` can help to resolve undefined dimensions. For example, run model conversion for the TensorFlow MobileNet model with the single input diff --git a/docs/articles_en/documentation/openvino_legacy_features/mo_ovc_transition/legacy_conversion_api/supported_model_formats.rst b/docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api/[legacy]-supported-model-formats.rst similarity index 97% rename from docs/articles_en/documentation/openvino_legacy_features/mo_ovc_transition/legacy_conversion_api/supported_model_formats.rst rename to docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api/[legacy]-supported-model-formats.rst index c4fb928e807e01..bbc40b8b774e72 100644 --- a/docs/articles_en/documentation/openvino_legacy_features/mo_ovc_transition/legacy_conversion_api/supported_model_formats.rst +++ b/docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api/[legacy]-supported-model-formats.rst @@ -7,7 +7,7 @@ The code described here has been **deprecated!** Do not use it to avoid working with a legacy solution. It will be kept for some time to ensure backwards compatibility, but **you should not use** it in contemporary applications. - This guide describes a deprecated conversion method. The guide on the new and recommended method can be found in the :doc:`Supported Model Formats ` article. + This guide describes a deprecated conversion method. The guide on the new and recommended method can be found in the :doc:`Supported Model Formats ` article. .. toctree:: :maxdepth: 1 @@ -26,16 +26,16 @@ **OpenVINO IR (Intermediate Representation)** - the proprietary and default format of OpenVINO, benefiting from the full extent of its features. All other supported model formats, as listed below, are converted to :doc:`OpenVINO IR ` to enable inference. Consider storing your model in this format to minimize first-inference latency, perform model optimization, and, in some cases, save space on your drive. -**PyTorch, TensorFlow, ONNX, and PaddlePaddle** - can be used with OpenVINO Runtime API directly, +**PyTorch, TensorFlow, ONNX, and PaddlePaddle** - can be used with OpenVINO Runtime API directly, which means you do not need to save them as OpenVINO IR before including them in your application. OpenVINO can read, compile, and convert them automatically, as part of its pipeline. -In the Python API, these options are provided as three separate methods: +In the Python API, these options are provided as three separate methods: ``read_model()``, ``compile_model()``, and ``convert_model()``. -The ``convert_model()`` method enables you to perform additional adjustments -to the model, such as setting shapes, changing model input types or layouts, -cutting parts of the model, freezing inputs, etc. For a detailed description -of the conversion process, see the +The ``convert_model()`` method enables you to perform additional adjustments +to the model, such as setting shapes, changing model input types or layouts, +cutting parts of the model, freezing inputs, etc. For a detailed description +of the conversion process, see the :doc:`model conversion guide `. Here are code examples of how to use these methods with different model formats: @@ -544,16 +544,15 @@ Here are code examples of how to use these methods with different model formats: :doc:`article `. -**MXNet, Caffe, and Kaldi** are legacy formats that need to be converted explicitly to OpenVINO IR or ONNX before running inference. -As OpenVINO is currently proceeding **to deprecate these formats** and **remove their support entirely in the future**, -converting them to ONNX for use with OpenVINO should be considered the default path. +As OpenVINO support for **MXNet, Caffe, and Kaldi formats** has been **discontinued**, converting these legacy formats +to OpenVINO IR or ONNX before running inference should be considered the default path for use with OpenVINO. .. note:: - If you want to keep working with the legacy formats the old way, refer to a previous + If you want to keep working with the legacy formats the old way, refer to a previous `OpenVINO LTS version and its documentation `__ . - - OpenVINO versions of 2023 are mostly compatible with the old instructions, + + OpenVINO versions of 2023 are mostly compatible with the old instructions, through a deprecated MO tool, installed with the deprecated OpenVINO Developer Tools package. `OpenVINO 2023.0 `__ is the last diff --git a/docs/articles_en/documentation/openvino_legacy_features/mo_ovc_transition/legacy_conversion_api/supported_model_formats/convert_model_tutorials.rst b/docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api/[legacy]-supported-model-formats/[legacy]-conversion-tutorials.rst similarity index 90% rename from docs/articles_en/documentation/openvino_legacy_features/mo_ovc_transition/legacy_conversion_api/supported_model_formats/convert_model_tutorials.rst rename to docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api/[legacy]-supported-model-formats/[legacy]-conversion-tutorials.rst index ae8a20f937a9b0..24e295fa9dca92 100644 --- a/docs/articles_en/documentation/openvino_legacy_features/mo_ovc_transition/legacy_conversion_api/supported_model_formats/convert_model_tutorials.rst +++ b/docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api/[legacy]-supported-model-formats/[legacy]-conversion-tutorials.rst @@ -36,7 +36,7 @@ .. meta:: - :description: Get to know conversion methods for specific TensorFlow, ONNX, PyTorch, MXNet, and Kaldi models. + :description: Get to know conversion methods for specific TensorFlow, ONNX, and PyTorch models. .. danger:: @@ -45,19 +45,17 @@ This guide describes a deprecated conversion method. The guide on the new and recommended method can be found in the :doc:`Python tutorials `. -This section provides a set of tutorials that demonstrate conversion methods for specific -TensorFlow, ONNX, and PyTorch models. Note that these instructions do not cover all use +This section provides a set of tutorials that demonstrate conversion methods for specific +TensorFlow, ONNX, and PyTorch models. Note that these instructions do not cover all use cases and may not reflect your particular needs. -Before studying the tutorials, try to convert the model out-of-the-box by specifying only the +Before studying the tutorials, try to convert the model out-of-the-box by specifying only the ``--input_model`` parameter in the command line. .. note:: - Apache MXNet, Caffe, and Kaldi are no longer directly supported by OpenVINO. - They will remain available for some time, so make sure to transition to other - frameworks before they are fully discontinued. - -You will find a collection of :doc:`Python tutorials ` written for running on Jupyter notebooks -that provide an introduction to the OpenVINO™ toolkit and explain how to use the Python API and tools for + Apache MXNet, Caffe, and Kaldi are no longer directly supported by OpenVINO. + +You will find a collection of :doc:`Python tutorials ` written for running on Jupyter notebooks +that provide an introduction to the OpenVINO™ toolkit and 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b/docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-model-optimizer-extensibility/[legacy]-model-optimizer-extensions/[legacy]-graph-transformation-extensions.rst @@ -4,14 +4,14 @@ ========================================== .. meta:: - :description: Learn about various base classes for front, middle and back phase + :description: Learn about various base classes for front, middle and back phase transformations applied during model conversion with Model Optimizer. .. danger:: The code described here has been **deprecated!** Do not use it to avoid working with a legacy solution. It will be kept for some time to ensure backwards compatibility, but **you should not use** it in contemporary applications. - This guide describes a deprecated TensorFlow conversion method. The guide on the new and recommended method, using a new frontend, can be found in the :doc:`Frontend Extensions ` article. + This guide describes a deprecated TensorFlow conversion method. The guide on the new and recommended method, using a new frontend, can be found in the :doc:`Frontend Extensions ` article. Model Optimizer provides various base classes to implement :ref:`Front Phase Transformations `, :ref:`Middle Phase Transformations `, and :ref:`Back Phase Transformations `. @@ -26,7 +26,7 @@ All classes have the following common class attributes and methods: 7. Method ``run_before()`` returns a list of transformation classes which this transformation should be executed before. 8. Method ``run_after()`` returns a list of transformation classes which this transformation should be executed after. -.. note:: +.. note:: Some of the transformation types have specific class attributes and methods, which are explained in the corresponding sections of this document. Model Optimizer builds a graph of dependencies between registered transformations and executes them in the topological @@ -39,7 +39,7 @@ The diagram below shows anchor transformations, some of built-in transformations User-defined transformations are executed after the corresponding ``Start`` and before the corresponding ``Finish`` anchor transformations by default (if ``run_before()`` and ``run_after()`` methods have not been overridden). -.. note:: +.. note:: The ``PreMiddleStart`` and ``PostMiddleStart`` anchors were introduced due to historical reasons to refactor the Model Optimizer pipeline, which initially had a hardcoded order of transformations. .. _mo_front_phase_transformations: @@ -53,7 +53,7 @@ There are several types of a front phase transformation: 1. :ref:`Pattern-Defined Front Phase Transformations ` triggered for each sub-graph of the original graph isomorphic to the specified pattern. 2. :ref:`Specific Operation Front Phase Transformations ` triggered for the node with a specific ``op`` attribute value. 3. :ref:`Generic Front Phase Transformations `. -4. Manually enabled transformation, defined with a JSON configuration file (for TensorFlow, ONNX, Apache MXNet, and PaddlePaddle models), specified using the ``--transformations_config`` command-line parameter: +4. Manually enabled transformation, defined with a JSON configuration file (for TensorFlow, ONNX, and PaddlePaddle models), specified using the ``--transformations_config`` command-line parameter: 1. :ref:`Node Name Pattern Front Phase Transformations `. 2. :ref:`Front Phase Transformations Using Start and End Points `. @@ -72,7 +72,7 @@ This type of transformation is implemented using ``mo.front.common.replacement.F 3. Model Optimizer executes the defined function performing graph transformation for each instance of a matched sub-graph. You can override different functions in the base transformation class so the Model Optimizer works differently: 1. The ``replace_sub_graph(self, graph, match)`` override the method. In this case Model Optimizer only executes the overridden function, pass the ``graph`` object and a dictionary describing the matched sub-graph. You are required to write the transformation and connect the newly created nodes to the rest of the graph. - 2. The ``generate_sub_graph(self, graph, match)`` override the method. This case is not recommended for use because it is the most complicated approach. It can be effectively replaced with one of two previous approaches. + 2. The ``generate_sub_graph(self, graph, match)`` override the method. This case is not recommended for use because it is the most complicated approach. It can be effectively replaced with one of two previous approaches. The sub-graph pattern is defined in the ``pattern()`` function. This function should return a dictionary with two keys: ``nodes`` and ``edges``: @@ -100,17 +100,17 @@ operation: from openvino.tools.mo.front.common.replacement import FrontReplacementSubgraph from openvino.tools.mo.front.subgraph_matcher import SubgraphMatch from openvino.tools.mo.graph.graph import Graph, rename_nodes - - + + class MishFusion(FrontReplacementSubgraph): """ The transformation looks for the pattern with Softplus defining the Mish function: Mish(x) = x * tanh(SoftPlus(x)). """ enabled = True # Transformation is enabled. - + def run_after(self): # Run this transformation after "SoftplusFusion" transformation. return [SoftplusFusion] - + def pattern(self): # Define pattern according to formulae x * tanh(SoftPlus(x)). return dict( nodes=[ @@ -122,23 +122,23 @@ operation: ('softplus', 'tanh'), ('tanh', 'mul'), ]) - + def replace_sub_graph(self, graph: Graph, match: [dict, SubgraphMatch]): # Entry point for the transformation. mul = match['mul'] # Get the Node corresponding to matched "mul" node. mul_name = mul.soft_get('name', mul.id) softplus = match['softplus'] # Get the Node corresponding to the matched "softplus" node. - + # Determine the input port of Mul which gets the 'input' node output. input_port_idx = int(mul.in_port(0).get_connection().get_source().node.soft_get('op') == 'Tanh') - + # Check that the same tensor is provided as input to Mul and SoftPlus. if mul.in_port(input_port_idx).get_source() != softplus.in_port(0).get_source(): return - + mish = Mish(graph, {}).create_node() # Create Mish operation. mish.in_port(0).connect(mul.in_port(input_port_idx).get_source()) # Connect input to the Mish. mul.out_port(0).get_connection().set_source(mish.out_port(0)) # Reconnect outgoing edge from "mul" to Mish. - + # Rename the created Mish operation to have the name of the "mul" node, which produced the value equal to the # Mish output. rename_nodes([(mul, mul_name + '/TBR'), (mish, mul_name)]) @@ -167,31 +167,31 @@ the TensorFlow: .. code-block:: py :force: - + from openvino.tools.mo.front.common.partial_infer.utils import int64_array from openvino.tools.mo.front.common.replacement import FrontReplacementOp from openvino.tools.mo.front.tf.graph_utils import create_op_with_const_inputs from openvino.tools.mo.graph.graph import Node, Graph, rename_nodes from openvino.tools.mo.ops.concat import Concat from openvino.tools.mo.ops.unsqueeze import Unsqueeze - - + + class Pack(FrontReplacementOp): - op = "Pack" # Trigger transformation for all nodes in the graph with the op = "Pack" attribute + op = "Pack" # Trigger transformation for all nodes in the graph with the op = "Pack" attribute enabled = True # Transformation is enabled. - + def replace_op(self, graph: Graph, node: Node): # Entry point for the transformation. # Create a Concat operation with a number of inputs equal to a number of inputs to Pack. out_node = Concat(graph, {'axis': node.axis, 'in_ports_count': len(node.in_ports())}).create_node() pack_name = node.soft_get('name', node.id) - + for ind in node.in_ports(): # Add dimension of size 1 to all inputs of the Pack operation and add them as Concat inputs. unsqueeze_node = create_op_with_const_inputs(graph, Unsqueeze, {1: int64_array([node.axis])}, {'name': node.soft_get('name', node.id) + '/Unsqueeze'}) node.in_port(ind).get_connection().set_destination(unsqueeze_node.in_port(0)) unsqueeze_node.out_port(0).connect(out_node.in_port(ind)) - + # Rename the created Concat operation to have the name of the "pack" node, which produced the value equal to the # Concat output. rename_nodes([(node, pack_name + '/TBR'), (out_node, pack_name)]) @@ -205,7 +205,7 @@ Generic Front Phase Transformations Model Optimizer provides a mechanism to implement generic front phase transformation. This type of transformation is implemented using ``mo.front.common.replacement.FrontReplacementSubgraph`` or -``mo.front.common.replacement.FrontReplacementPattern`` as base classes. Make sure the transformation is enabled before trying to execute it. +``mo.front.common.replacement.FrontReplacementPattern`` as base classes. Make sure the transformation is enabled before trying to execute it. Then, Model Optimizer executes the ``find_and_replace_pattern(self, graph)`` method and provides a ``Graph`` object as an input. @@ -219,21 +219,21 @@ specification. :force: import logging as log - + from openvino.tools.mo.front.common.partial_infer.utils import int64_array from openvino.tools.mo.front.common.replacement import FrontReplacementPattern from openvino.tools.mo.graph.graph import Graph from openvino.tools.mo.ops.const import Const from openvino.tools.mo.utils.error import Error - - + + class SqueezeNormalize(FrontReplacementPattern): """ Normalizes inputs of the Squeeze layers. The layers should have two inputs: the input with data and input with the dimensions to squeeze. If the second input is omitted then all dimensions of size 1 should be removed. """ enabled = True # The transformation is enabled. - + def find_and_replace_pattern(self, graph: Graph): # The function is called unconditionally. for squeeze_node in graph.get_op_nodes(op='Squeeze'): # Iterate over all nodes with op='Squeeze'. # If the operation has only 1 input node and no 'squeeze_dims' Node attribute, then convert the attribute to @@ -272,7 +272,7 @@ Consider a situation when these Inception blocks are implemented extremely effic Engine operation called ``InceptionBlock`` and these blocks in the model need to be replaced with instances of this operation. Model Optimizer provides mechanism to trigger the transformation for a sub-graph of operations defined by the node name regular expressions (scope). In this particular case, some of the patterns are: ``.*InceptionV4/Mixed_5b``, -``.*InceptionV4/Mixed_5c`` and ``.*InceptionV4/Mixed_5d``. Each pattern starts with ``.*``, because the ``InceptionV4`` prefix +``.*InceptionV4/Mixed_5c`` and ``.*InceptionV4/Mixed_5d``. Each pattern starts with ``.*``, because the ``InceptionV4`` prefix is added to all nodes names during a model freeze. This type of transformation is implemented using ``mo.front.tf.replacement.FrontReplacementFromConfigFileSubGraph`` as a @@ -371,7 +371,7 @@ contains one list corresponding to this tensor. Four input nodes of the sub-grap The order of items in the internal list describing nodes does not matter, but the order of elements in the top-level list is important. This order defines how Model Optimizer attaches input tensors to a new generated -node if the sub-graph is replaced with a single node. The ``i``-th input node of the sub-graph is obtained using +node if the sub-graph is replaced with a single node. The ``i``-th input node of the sub-graph is obtained using ``match.single_input_node(i)`` call in the sub-graph transformation code. More information about API is given below. If it is necessary to change the order of input tensors, the configuration file can be edited in the text editor. @@ -406,7 +406,7 @@ The example of a JSON configuration file for a transformation with start and end ``extensions/front/tf/ssd_support_api_v1.15.json``: .. code-block:: json - + [ { "custom_attributes": { @@ -443,10 +443,10 @@ the value of the ``match_kind`` parameter, which should be equal to the ``points which should be a dictionary with two keys ``start_points`` and ``end_points``, defining start and end node names respectively. -.. note:: +.. note:: The ``include_inputs_to_sub_graph`` and ``include_outputs_to_sub_graph`` parameters are redundant and should be always equal to ``true``. -.. note:: +.. note:: This sub-graph match algorithm has a limitation that each start node must have only one input. Therefore, it is not possible to specify, for example, the :doc:`Convolution ` node as input because it has two inputs: data tensor and tensor with weights. For other examples of transformations with points, refer to the @@ -463,14 +463,14 @@ but require a JSON configuration file to enable it similarly to :ref:`Front Phase Transformations Using Start and End Points `. The base class for this type of transformation is -``mo.front.common.replacement.FrontReplacementFromConfigFileGeneral``. Model Optimizer executes the +``mo.front.common.replacement.FrontReplacementFromConfigFileGeneral``. Model Optimizer executes the ``transform_graph(self, graph, replacement_descriptions)`` method and provides the ``Graph`` object and dictionary with values parsed from the `custom_attributes` attribute of the provided JSON configuration file. The example of the configuration file for this type of transformation is ``extensions/front/tf/yolo_v1_tiny.json``: .. code-block:: json - + [ { "id": "TFYOLO", @@ -488,7 +488,7 @@ and the corresponding transformation file is ``./extensions/front/YOLO.py``: .. code-block:: py :force: - + from openvino.tools.mo.front.no_op_eraser import NoOpEraser from openvino.tools.mo.front.standalone_const_eraser import StandaloneConstEraser from openvino.tools.mo.ops.regionyolo import RegionYoloOp @@ -496,18 +496,18 @@ and the corresponding transformation file is ``./extensions/front/YOLO.py``: from openvino.tools.mo.graph.graph import Node, Graph from openvino.tools.mo.ops.result import Result from openvino.tools.mo.utils.error import Error - - + + class YoloRegionAddon(FrontReplacementFromConfigFileGeneral): """ Replaces all Result nodes in graph with YoloRegion->Result nodes chain. YoloRegion node attributes are taken from configuration file """ replacement_id = 'TFYOLO' # The identifier matching the "id" attribute in the JSON file. - + def run_after(self): return [NoOpEraser, StandaloneConstEraser] - + def transform_graph(self, graph: Graph, replacement_descriptions): op_outputs = [n for n, d in graph.nodes(data=True) if 'op' in d and d['op'] == 'Result'] for op_output in op_outputs: @@ -572,7 +572,7 @@ There are two types of back phase transformations: 1. :ref:`Pattern-Defined Back Phase Transformations ` triggered for each sub-graph of the original graph, isomorphic to the specified pattern. 2. :ref:`Generic Back Phase Transformations `. -.. note:: +.. note:: The graph layout during the back phase is always NCHW. However, during the front and middle phases it could be NHWC if the original model was using it. For more details, refer to :ref:`Model Conversion Pipeline `. .. _pattern_defined_back_phase_transformations: diff --git a/docs/articles_en/documentation/openvino_legacy_features/mo_ovc_transition/customize_model_optimizer/model_optimizer_extensions/model_optimizer_operation.rst b/docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-model-optimizer-extensibility/[legacy]-model-optimizer-extensions/[legacy]-model-optimizer-operation.rst similarity index 100% rename from docs/articles_en/documentation/openvino_legacy_features/mo_ovc_transition/customize_model_optimizer/model_optimizer_extensions/model_optimizer_operation.rst rename to docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-model-optimizer-extensibility/[legacy]-model-optimizer-extensions/[legacy]-model-optimizer-operation.rst diff --git a/docs/articles_en/documentation/openvino_legacy_features/mo_ovc_transition/customize_model_optimizer/model_optimizer_extensions/model_optimizer_extractor.rst b/docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-model-optimizer-extensibility/[legacy]-model-optimizer-extensions/[legacy]-optimizer-extractor.rst similarity index 100% rename from docs/articles_en/documentation/openvino_legacy_features/mo_ovc_transition/customize_model_optimizer/model_optimizer_extensions/model_optimizer_extractor.rst rename to docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-model-optimizer-extensibility/[legacy]-model-optimizer-extensions/[legacy]-optimizer-extractor.rst diff --git a/docs/articles_en/documentation/openvino_ecosystem.rst b/docs/articles_en/documentation/openvino-ecosystem.rst similarity index 100% rename from docs/articles_en/documentation/openvino_ecosystem.rst rename to docs/articles_en/documentation/openvino-ecosystem.rst diff --git a/docs/articles_en/documentation/openvino_ecosystem/datumaro.rst b/docs/articles_en/documentation/openvino-ecosystem/datumaro.rst similarity index 100% rename from docs/articles_en/documentation/openvino_ecosystem/datumaro.rst rename to docs/articles_en/documentation/openvino-ecosystem/datumaro.rst diff --git a/docs/articles_en/documentation/openvino_ecosystem/ovsa_get_started.rst b/docs/articles_en/documentation/openvino-ecosystem/openvino-security-add-on.rst similarity index 100% rename from docs/articles_en/documentation/openvino_ecosystem/ovsa_get_started.rst rename to docs/articles_en/documentation/openvino-ecosystem/openvino-security-add-on.rst diff --git a/docs/articles_en/documentation/openvino_ecosystem/openvino_training_extensions.rst b/docs/articles_en/documentation/openvino-ecosystem/openvino-training-extensions.rst similarity index 100% rename from docs/articles_en/documentation/openvino_ecosystem/openvino_training_extensions.rst rename to docs/articles_en/documentation/openvino-ecosystem/openvino-training-extensions.rst diff --git a/docs/articles_en/documentation/openvino_extensibility.rst b/docs/articles_en/documentation/openvino-extensibility.rst similarity index 85% rename from docs/articles_en/documentation/openvino_extensibility.rst rename to docs/articles_en/documentation/openvino-extensibility.rst index 64f62c923986da..702a3b5fb6ed3d 100644 --- a/docs/articles_en/documentation/openvino_extensibility.rst +++ b/docs/articles_en/documentation/openvino-extensibility.rst @@ -26,8 +26,7 @@ OpenVINO Extensibility Mechanism The Intel® Distribution of OpenVINO™ toolkit supports neural-network models trained with various frameworks, including -TensorFlow, PyTorch, ONNX, TensorFlow Lite, and PaddlePaddle (OpenVINO support for Apache MXNet, Caffe, and Kaldi is currently -being deprecated and will be removed entirely in the future). The list of supported operations is different for each of the supported frameworks. +TensorFlow, PyTorch, ONNX, TensorFlow Lite, and PaddlePaddle. The list of supported operations is different for each of the supported frameworks. To see the operations supported by your framework, refer to :doc:`Supported Framework Operations `. Custom operations, which are not included in the list, are not recognized by OpenVINO out-of-the-box. The need for custom operation may appear in two cases: @@ -57,15 +56,15 @@ You might prefer implementing a custom operation class if you already have a gen Mapping from Framework Operation ################################ -Mapping of custom operation is implemented differently, depending on model format used for import. You may choose one of the following: +Mapping of custom operation is implemented differently, depending on model format used for import. +If a model is represented in the ONNX (including models exported from PyTorch in ONNX), TensorFlow Lite, PaddlePaddle or +TensorFlow formats, then one of the classes from :doc:`Frontend Extension API ` +should be used. It consists of several classes available in C++ which can be used with the ``--extensions`` option in Model Optimizer +or when a model is imported directly to OpenVINO runtime using the ``read_model`` method. +Python API is also available for runtime model import. -1. If a model is represented in the ONNX (including models exported from PyTorch in ONNX), TensorFlow Lite, PaddlePaddle or TensorFlow formats, then one of the classes from :doc:`Frontend Extension API ` should be used. It consists of several classes available in C++ which can be used with the ``--extensions`` option in Model Optimizer or when a model is imported directly to OpenVINO runtime using the ``read_model`` method. Python API is also available for runtime model import. - -2. If a model is represented in the Caffe, Kaldi or MXNet formats (as legacy frontends), then :doc:`[Legacy] Model Optimizer Extensions ` should be used. This approach is available for model conversion in Model Optimizer only. - -Existing of two approaches simultaneously is explained by two different types of frontends used for model conversion in OpenVINO: new frontends (ONNX, PaddlePaddle, TensorFlow Lite, and TensorFlow) and legacy frontends (Caffe, Kaldi, and Apache MXNet). Model Optimizer can use both frontends in contrast to the direct import of model with ``read_model`` method which can use new frontends only. Follow one of the appropriate guides referenced above to implement mappings depending on framework frontend. - -If you are implementing extensions for new ONNX, PaddlePaddle, TensorFlow Lite or TensorFlow frontends and plan to use the ``--extensions`` option in Model Optimizer for model conversion, then the extensions should be: +If you are implementing extensions for new ONNX, PaddlePaddle, TensorFlow Lite or TensorFlow frontends and plan to use the ``--extensions`` +option in Model Optimizer for model conversion, then the extensions should be: 1. 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docs/articles_en/documentation/openvino-ir-format/intermediate-representation-int8-inference.rst diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets.rst similarity index 100% rename from docs/articles_en/documentation/openvino_ir/operation_sets.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets.rst diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/available_opsets.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/available-opsets.rst similarity index 96% rename from docs/articles_en/documentation/openvino_ir/operation_sets/available_opsets.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets/available-opsets.rst index 430aca7770f980..9762efce375c22 100644 --- a/docs/articles_en/documentation/openvino_ir/operation_sets/available_opsets.rst +++ b/docs/articles_en/documentation/openvino-ir-format/operation-sets/available-opsets.rst @@ -12,6 +12,7 @@ Available Operation Sets :maxdepth: 1 :hidden: + openvino_docs_ops_opset14 openvino_docs_ops_opset13 openvino_docs_ops_opset12 openvino_docs_ops_opset11 @@ -36,6 +37,8 @@ This topic provides a complete list of available sets of operations supported in * - OpenVINO™ Version - Actual Operations Set + * - 2024.0 + - :doc:`opset14 ` * - 2023.2 - :doc:`opset13 ` * - 2023.1 diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/available_opsets/opset1.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/available-opsets/opset1.rst similarity index 100% rename from docs/articles_en/documentation/openvino_ir/operation_sets/available_opsets/opset1.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets/available-opsets/opset1.rst diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/available_opsets/opset10.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/available-opsets/opset10.rst similarity index 100% rename from docs/articles_en/documentation/openvino_ir/operation_sets/available_opsets/opset10.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets/available-opsets/opset10.rst diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/available_opsets/opset11.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/available-opsets/opset11.rst similarity index 100% rename from docs/articles_en/documentation/openvino_ir/operation_sets/available_opsets/opset11.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets/available-opsets/opset11.rst diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/available_opsets/opset12.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/available-opsets/opset12.rst similarity index 100% rename from docs/articles_en/documentation/openvino_ir/operation_sets/available_opsets/opset12.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets/available-opsets/opset12.rst diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/available_opsets/opset13.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/available-opsets/opset13.rst similarity index 100% rename from docs/articles_en/documentation/openvino_ir/operation_sets/available_opsets/opset13.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets/available-opsets/opset13.rst diff --git a/docs/articles_en/documentation/openvino-ir-format/operation-sets/available-opsets/opset14.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/available-opsets/opset14.rst new file mode 100644 index 00000000000000..d3a7fdc1652a66 --- /dev/null +++ b/docs/articles_en/documentation/openvino-ir-format/operation-sets/available-opsets/opset14.rst @@ -0,0 +1,208 @@ +.. {#openvino_docs_ops_opset14} + +opset14 +======= + + +.. meta:: + :description: Explore the examples of operation instances expressed as IR + XML snippets in the opset14 operation set, supported in OpenVINO™ + toolkit. + +This specification document describes the ``opset14`` operation set supported in OpenVINO™. +Support for each particular operation from the list below depends on the capabilities of an inference plugin +and may vary among different hardware platforms and devices. Examples of operation instances are provided as IR xml +snippets. Such IR is generated by the Model Optimizer. The semantics match corresponding OpenVINO operation classes +declared in ``namespace opset14``. + + +Table of Contents +################## + +* :doc:`Abs ` +* :doc:`Acos ` +* :doc:`Acosh ` +* :doc:`AdaptiveAvgPool ` +* :doc:`AdaptiveMaxPool ` +* :doc:`Add ` +* :doc:`Asin ` +* :doc:`Asinh ` +* :doc:`Assign ` +* :doc:`Atan ` +* :doc:`Atanh ` +* :doc:`AvgPool ` +* :doc:`BatchNormInference ` +* :doc:`BatchToSpace ` +* :doc:`BinaryConvolution ` +* :doc:`BitwiseAnd ` +* :doc:`BitwiseOr ` +* :doc:`BitwiseXor ` +* :doc:`BitwiseNot ` +* :doc:`Broadcast ` +* :doc:`Bucketize ` +* :doc:`CTCGreedyDecoder ` +* :doc:`CTCGreedyDecoderSeqLen ` +* :doc:`CTCLoss ` +* :doc:`Ceiling ` +* :doc:`Clamp ` +* :doc:`Concat ` +* :doc:`Constant ` +* :doc:`Convert ` +* :doc:`ConvertLike ` +* :doc:`Convolution ` +* :doc:`ConvolutionBackpropData ` +* :doc:`Cos ` +* :doc:`Cosh ` +* :doc:`CumSum ` +* :doc:`DeformableConvolution ` +* :doc:`DeformablePSROIPooling ` +* :doc:`DepthToSpace ` +* :doc:`DetectionOutput ` +* :doc:`DFT ` +* :doc:`Divide ` +* :doc:`Einsum ` +* :doc:`Elu ` +* :doc:`EmbeddingBagOffsetsSum ` +* :doc:`EmbeddingBagPackedSum ` +* :doc:`EmbeddingSegmentsSum ` +* :doc:`Equal ` +* :doc:`Erf ` +* :doc:`Exp ` +* :doc:`ExperimentalDetectronDetectionOutput_6 ` +* :doc:`ExperimentalDetectronGenerateProposalsSingleImage_6 ` +* :doc:`ExperimentalDetectronPriorGridGenerator_6 ` +* :doc:`ExperimentalDetectronROIFeatureExtractor_6 ` +* :doc:`ExperimentalDetectronTopKROIs_6 ` +* :doc:`ExtractImagePatches ` +* :doc:`Eye ` +* :doc:`FakeConvert ` +* :doc:`FakeQuantize ` +* :doc:`Floor ` +* :doc:`FloorMod ` +* :doc:`Gather ` +* :doc:`GatherElements ` +* :doc:`GatherND ` +* :doc:`GatherTree ` +* :doc:`Gelu ` +* :doc:`GenerateProposals ` +* :doc:`Greater ` +* :doc:`GreaterEqual ` +* :doc:`GridSample ` +* :doc:`GRN ` +* :doc:`GroupConvolution ` +* :doc:`GroupConvolutionBackpropData ` +* :doc:`GroupNormalization ` +* :doc:`GRUCell ` +* :doc:`GRUSequence ` +* :doc:`HardSigmoid ` +* :doc:`HSigmoid ` +* :doc:`HSwish ` +* :doc:`IDFT ` +* :doc:`I420toBGR ` +* :doc:`I420toRGB ` +* :doc:`If ` +* :doc:`Interpolate ` +* :doc:`Inverse ` +* :doc:`IRDFT ` +* :doc:`IsInf ` +* :doc:`IsNaN ` +* :doc:`Less ` +* :doc:`LessEqual ` +* :doc:`Log ` +* :doc:`LogicalAnd ` +* :doc:`LogicalNot ` +* :doc:`LogicalOr ` +* :doc:`LogicalXor ` +* :doc:`LogSoftmax ` +* :doc:`Loop ` +* :doc:`LRN ` +* :doc:`LSTMCell ` +* :doc:`LSTMSequence ` +* :doc:`MatMul ` +* :doc:`MatrixNMS ` +* :doc:`MaxPool ` +* :doc:`Maximum ` +* :doc:`Minimum ` +* :doc:`Mish ` +* :doc:`Mod ` +* :doc:`MVN ` +* :doc:`MulticlassNMS ` +* :doc:`Multinomial ` +* :doc:`Multiply ` +* :doc:`Negative ` +* :doc:`NMSRotated ` +* :doc:`NonMaxSuppression ` +* :doc:`NonZero ` +* :doc:`NormalizeL2 ` +* :doc:`NotEqual ` +* :doc:`NV12toBGR ` +* :doc:`NV12toRGB ` +* :doc:`OneHot ` +* :doc:`Pad ` +* :doc:`Parameter ` +* :doc:`Power ` +* :doc:`PReLU ` +* :doc:`PriorBoxClustered ` +* :doc:`PriorBox ` +* :doc:`Proposal ` +* :doc:`PSROIPooling ` +* :doc:`RandomUniform ` +* :doc:`Range ` +* :doc:`RDFT ` +* :doc:`ReLU ` +* :doc:`ReadValue ` +* :doc:`ReduceL1 ` +* :doc:`ReduceL2 ` +* :doc:`ReduceLogicalAnd ` +* :doc:`ReduceLogicalOr ` +* :doc:`ReduceMax ` +* :doc:`ReduceMean ` +* :doc:`ReduceMin ` +* :doc:`ReduceProd ` +* :doc:`ReduceSum ` +* :doc:`RegionYolo ` +* :doc:`ReorgYolo ` +* :doc:`Reshape ` +* :doc:`Result ` +* :doc:`ReverseSequence ` +* :doc:`RNNCell ` +* :doc:`RNNSequence ` +* :doc:`ROIAlign ` +* :doc:`ROIPooling ` +* :doc:`Roll ` +* :doc:`Round ` +* :doc:`ScaledDotProductAttention ` +* :doc:`ScatterElementsUpdate ` +* :doc:`ScatterNDUpdate ` +* :doc:`ScatterUpdate ` +* :doc:`Select ` +* :doc:`Selu ` +* :doc:`ShapeOf ` +* :doc:`ShuffleChannels ` +* :doc:`Sigmoid ` +* :doc:`Sign ` +* :doc:`Sin ` +* :doc:`Sinh ` +* :doc:`Slice ` +* :doc:`SoftMax ` +* :doc:`SoftPlus ` +* :doc:`SoftSign ` +* :doc:`SpaceToBatch ` +* :doc:`SpaceToDepth ` +* :doc:`Split ` +* :doc:`Sqrt ` +* :doc:`SquaredDifference ` +* :doc:`Squeeze ` +* :doc:`StridedSlice ` +* :doc:`Subtract ` +* :doc:`Swish ` +* :doc:`Tan ` +* :doc:`Tanh ` +* :doc:`TensorIterator ` +* :doc:`Tile ` +* :doc:`TopK ` +* :doc:`Transpose ` +* :doc:`Unique ` +* :doc:`Unsqueeze ` +* :doc:`VariadicSplit ` + diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/available_opsets/opset2.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/available-opsets/opset2.rst similarity index 100% rename from docs/articles_en/documentation/openvino_ir/operation_sets/available_opsets/opset2.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets/available-opsets/opset2.rst diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/available_opsets/opset3.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/available-opsets/opset3.rst similarity index 100% rename from docs/articles_en/documentation/openvino_ir/operation_sets/available_opsets/opset3.rst rename to 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docs/articles_en/documentation/openvino_ir/operation_sets/broadcast_rules.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets/broadcast-rules.rst diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications.rst similarity index 99% rename from docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications.rst index 3d7efb29ddd98e..da295e12b54d02 100644 --- a/docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications.rst +++ b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications.rst @@ -105,6 +105,7 @@ Operation Specifications Interpolate-1 Interpolate-4 Interpolate-11 + Inverse-14 IsFinite-10 IsInf-10 IsNaN-10 diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/activation/Clamp_1.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/activation/clamp-1.rst similarity index 100% rename from docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/activation/Clamp_1.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/activation/clamp-1.rst diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/activation/Elu_1.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/activation/elu-1.rst similarity index 100% rename from docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/activation/Elu_1.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/activation/elu-1.rst diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/activation/Exp_1.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/activation/exp-1.rst similarity index 100% rename from docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/activation/Exp_1.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/activation/exp-1.rst diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/activation/GELU_2.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/activation/gelu-2.rst similarity index 100% rename from docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/activation/GELU_2.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/activation/gelu-2.rst diff --git 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similarity index 100% rename from docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/activation/Mish_4.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/activation/mish-4.rst diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/activation/PReLU_1.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/activation/prelu-1.rst similarity index 100% rename from docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/activation/PReLU_1.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/activation/prelu-1.rst diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/activation/ReLU_1.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/activation/relu-1.rst similarity index 98% rename from docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/activation/ReLU_1.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/activation/relu-1.rst index e19eeae2050462..95fae9153f88be 100644 --- a/docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/activation/ReLU_1.rst +++ b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/activation/relu-1.rst @@ -5,7 +5,7 @@ ReLU .. meta:: - :description: Learn about ReLU-1 - an element-wise, activation operation, which + :description: Learn about ReLU-1 - an element-wise, activation operation, which can be performed on a single tensor in OpenVINO. **Versioned name**: *ReLU-1* diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/activation/Selu_1.rst 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docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/comparison/NotEqual_1.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/comparison/notequal-1.rst diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/condition/Bucketize_3.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/condition/bucketize-3.rst similarity index 100% rename from docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/condition/Bucketize_3.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/condition/bucketize-3.rst diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/condition/If_8.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/condition/if-8.rst similarity index 100% rename from docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/condition/If_8.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/condition/if-8.rst diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/condition/NonZero_3.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/condition/nonzero-3.rst similarity index 100% rename from docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/condition/NonZero_3.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/condition/nonzero-3.rst diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/condition/Select_1.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/condition/select-1.rst similarity index 100% rename from docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/condition/Select_1.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/condition/select-1.rst diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/convolution/BinaryConvolution_1.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/convolution/binary-convolution-1.rst similarity index 100% rename from docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/convolution/BinaryConvolution_1.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/convolution/binary-convolution-1.rst diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/convolution/Convolution_1.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/convolution/convolution-1.rst similarity index 98% rename from docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/convolution/Convolution_1.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/convolution/convolution-1.rst index 13c213e0d2e99f..3a3f2de3ee5064 100644 --- a/docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/convolution/Convolution_1.rst +++ b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/convolution/convolution-1.rst @@ -5,7 +5,7 @@ Convolution .. meta:: - :description: Learn about Convolution-1 - a 1D, 2D or 3D convolution operation, which + :description: Learn about Convolution-1 - a 1D, 2D or 3D convolution operation, which can be performed on input and kernel tensors in OpenVINO. **Versioned name**: *Convolution-1* @@ -19,33 +19,33 @@ Convolution For the convolutional layer, the number of output features in each dimension is calculated using the formula: .. math:: - + n_{out} = \left ( \frac{n_{in} + 2p - k}{s} \right ) + 1 The receptive field in each layer is calculated using the formulas: * Jump in the output feature map: - + .. math:: - + j_{out} = j_{in} \cdot s - + * Size of the receptive field of output feature: - + .. math:: - + r_{out} = r_{in} + ( k - 1 ) \cdot j_{in} - + * Center position of the receptive field of the first output feature: - + .. math:: - + start_{out} = start_{in} + ( \frac{k - 1}{2} - p ) \cdot j_{in} - + * Output is calculated using the following formula: - + .. math:: - + out = \sum_{i = 0}^{n}w_{i}x_{i} + b **Attributes**: @@ -83,7 +83,7 @@ The receptive field in each layer is calculated using the formulas: * *auto_pad* * **Description**: *auto_pad* how the padding is calculated. Possible values: - + * *explicit* - use explicit padding values from *pads_begin* and *pads_end*. * *same_upper* - the input is padded to match the output size. In case of odd padding value an extra padding is added at the end. * *same_lower* - the input is padded to match the output size. In case of odd padding value an extra padding is added at the beginning. @@ -98,7 +98,7 @@ The receptive field in each layer is calculated using the formulas: * **1**: Input tensor of type *T* and rank 3, 4 or 5. Layout is ``[N, C_IN, Z, Y, X]`` (number of batches, number of channels, spatial axes Z, Y, X). **Required.** * **2**: Kernel tensor of type *T* and rank 3, 4 or 5. Layout is ``[C_OUT, C_IN, Z, Y, X]`` (number of output channels, number of input channels, spatial axes Z, Y, X). **Required.** * **Note**: Type of the convolution (1D, 2D or 3D) is derived from the rank of the input tensors and not specified by any attribute: - + * 1D convolution (input tensors rank 3) means that there is only one spatial axis X * 2D convolution (input tensors rank 4) means that there are two spatial axes Y, X * 3D convolution (input tensors rank 5) means that there are three spatial axes Z, Y, X @@ -117,7 +117,7 @@ The receptive field in each layer is calculated using the formulas: .. code-block:: xml :force: - + @@ -146,7 +146,7 @@ The receptive field in each layer is calculated using the formulas: .. code-block:: xml :force: - + @@ -177,7 +177,7 @@ The receptive field in each layer is calculated using the formulas: .. code-block:: xml :force: - + diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/convolution/ConvolutionBackpropData_1.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/convolution/convolution-backprop-data-1.rst similarity index 100% rename from docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/convolution/ConvolutionBackpropData_1.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/convolution/convolution-backprop-data-1.rst diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/convolution/DeformableConvolution_1.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/convolution/deformable-convolution-1.rst similarity index 100% rename from docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/convolution/DeformableConvolution_1.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/convolution/deformable-convolution-1.rst diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/convolution/DeformableConvolution_8.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/convolution/deformable-convolution-8.rst similarity index 100% rename from docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/convolution/DeformableConvolution_8.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/convolution/deformable-convolution-8.rst diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/convolution/GroupConvolution_1.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/convolution/group-convolution-1.rst similarity index 100% rename from docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/convolution/GroupConvolution_1.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/convolution/group-convolution-1.rst diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/convolution/GroupConvolutionBackpropData_1.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/convolution/group-convolution-backprop-data-1.rst similarity index 100% rename from docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/convolution/GroupConvolutionBackpropData_1.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/convolution/group-convolution-backprop-data-1.rst diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/detection/DeformablePSROIPooling_1.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/detection/deformable-psroi-pooling-1.rst similarity index 99% rename from docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/detection/DeformablePSROIPooling_1.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/detection/deformable-psroi-pooling-1.rst index 04292993ef732d..7bd477465794e7 100644 --- a/docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/detection/DeformablePSROIPooling_1.rst +++ b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/detection/deformable-psroi-pooling-1.rst @@ -5,7 +5,7 @@ DeformablePSROIPooling .. meta:: - :description: Learn about DeformablePSROIPooling-1 - an object detection operation, which + :description: Learn about DeformablePSROIPooling-1 - an object detection operation, which can be performed on two or three input tensors in OpenVINO. **Versioned name**: *DeformablePSROIPooling-1* @@ -110,7 +110,7 @@ This operation is compatible with `Apache MXNet DeformablePSROIPooling @@ -140,7 +140,7 @@ This operation is compatible with `Apache MXNet DeformablePSROIPooling diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/detection/DetectionOutput_1.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/detection/detectionoutput-1.rst similarity index 100% rename from docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/detection/DetectionOutput_1.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/detection/detectionoutput-1.rst diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/detection/DetectionOutput_8.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/detection/detectionoutput-8.rst similarity index 100% rename from docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/detection/DetectionOutput_8.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/detection/detectionoutput-8.rst diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/detection/ExperimentalDetectronDetectionOutput_6.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/detection/experimental-detectron-detection-output-6.rst similarity index 100% rename from docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/detection/ExperimentalDetectronDetectionOutput_6.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/detection/experimental-detectron-detection-output-6.rst diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/detection/ExperimentalDetectronGenerateProposalsSingleImage_6.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/detection/experimental-detectron-generate-proposals-single-image-6.rst similarity index 100% rename from docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/detection/ExperimentalDetectronGenerateProposalsSingleImage_6.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/detection/experimental-detectron-generate-proposals-single-image-6.rst diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/detection/ExperimentalDetectronPriorGridGenerator_6.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/detection/experimental-detectron-prior-grid-generator-6.rst similarity index 100% rename from docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/detection/ExperimentalDetectronPriorGridGenerator_6.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/detection/experimental-detectron-prior-grid-generator-6.rst diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/detection/ExperimentalDetectronROIFeatureExtractor_6.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/detection/experimental-detectron-roi-feature-extractor-6.rst similarity index 100% rename from docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/detection/ExperimentalDetectronROIFeatureExtractor_6.rst rename to 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docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/detection/PriorBox_1.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/detection/prior-box-1.rst diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/detection/PriorBox_8.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/detection/prior-box-8.rst similarity index 100% rename from docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/detection/PriorBox_8.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/detection/prior-box-8.rst diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/detection/PriorBoxClustered_1.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/detection/prior-box-clustered-1.rst similarity index 100% rename from docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/detection/PriorBoxClustered_1.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/detection/prior-box-clustered-1.rst diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/detection/Proposal_1.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/detection/proposal-1.rst similarity index 99% rename from docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/detection/Proposal_1.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/detection/proposal-1.rst index 35f3d9910619a1..5f151b00bf4104 100644 --- a/docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/detection/Proposal_1.rst +++ b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/detection/proposal-1.rst @@ -5,7 +5,7 @@ Proposal .. meta:: - :description: Learn about Proposal-1 - an object detection operation, + :description: Learn about Proposal-1 - an object detection operation, which can be performed on three required input tensors. **Versioned name**: *Proposal-1* @@ -134,7 +134,7 @@ Proposal * **Description**: *framework* specifies how the box coordinates are calculated. * **Range of values**: - + * "" (empty string) - calculate box coordinates like in Caffe * *tensorflow* - calculate box coordinates like in the TensorFlow* Object Detection API models * **Type**: string diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/detection/Proposal_4.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/detection/proposal-4.rst similarity index 99% rename from docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/detection/Proposal_4.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/detection/proposal-4.rst index 6faa16b3444da6..82584fb9fa8447 100644 --- a/docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/detection/Proposal_4.rst +++ b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/detection/proposal-4.rst @@ -5,7 +5,7 @@ Proposal .. meta:: - :description: Learn about Proposal-4 - an object detection operation, + :description: Learn about Proposal-4 - an object detection operation, which can be performed on three required input tensors. **Versioned name**: *Proposal-4* @@ -31,7 +31,7 @@ the second optional tensor of shape ``[batch_size * post_nms_topn]`` with probab * pins anchor boxes to the image according to the second input tensor that contains four deltas for each box: for *x* and *y* of center, for *width* and for *height* * finds out score in the first input tensor - + 3. Filters out boxes with size less than *min_size* 4. Sorts all proposals (*box*, *score*) by score from highest to lowest 5. Takes top *pre_nms_topn* proposals diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/detection/PSROIPooling_1.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/detection/psroi-pooling-1.rst similarity index 100% rename from docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/detection/PSROIPooling_1.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/detection/psroi-pooling-1.rst diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/detection/RegionYolo_1.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/detection/region-yolo-1.rst similarity index 100% rename from docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/detection/RegionYolo_1.rst rename to 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100644 index 00000000000000..60812117ff5b78 --- /dev/null +++ b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/matrix/Inverse_14.rst @@ -0,0 +1,135 @@ +.. {#openvino_docs_ops_matrix_Inverse_14} + +Inverse +======= + + +.. meta:: + :description: Learn about Inverse-14 - a matrix operation that computes the inverse or adjoint for one matrix or a batch of input matrice. + +**Versioned name**: *Inverse-14* + +**Category**: *Matrix* + +**Short description**: *Inverse* operation computes either the inverse or adjoint (conjugate transposes) of one or a batch of square invertible matrices. + +**Detailed description**: *Inverse* operation computes the inverse of a square matrix. The operation uses LU decomposition with partial pivoting to compute the inverses. (`LU decomposotion with partial pivoting algorithm `__) + +The inverse matrix A^(-1) of a square matrix A is defined as: + +.. math:: + + A \cdot A^{-1} = A^{-1} \cdot A = I + +where **I** is the n-dimensional identity matrix. + +The inverse matrix exists if and only if the input matrix is invertible. In that case, the inverse is unique. If the matrix is not invertible however, the operation may raise an exception or return an undefined result. + +This operation can be used to compute the adjugate matrix instead of the inverse. + +The adjugate matrix adj(A) of a square matrix A is defined as: + +.. math:: + + adj(A) = det(A) \cdot A^{-1} + +where **A^{-1}** is the matrix inverse of A, and **det(A)** is the determinant of A. + +The adjugate matrix exists if and only if the inverse matrix exists. + +**Attribute**: + +* *adjoint* + + * **Description**: Modifies the return value of the operation. If true, the operation returns the adjoint (conjugate transpose) of the input matrices instead of finding the inverse. + * **Range of values**: `true`, `false` + + * ``true`` - output adjugate matrix. + * ``false`` - output inverse matrix. + + * **Type**: `bool` + * **Default value**: `false` + * **Required**: *No* + +**Input**: + +* **1**: `input` - A tensor of shape [B1, B2, ..., Bn, ROW, COL] and type `T` representing the input square matrices. **The inner-most 2 dimensions form square matrices and must be of the same size.** B1, B2, ..., Bn represent any amount of batch dimensions (can be 0 for a single matrix input). **Required.** + +**Output**: + +* **1**: `output` - A tensor with the same type `T` as the input and same shape [B1, B2, ..., Bn, ROW, COL] as the input, representing the inverse matrices (or adjugate matrices) of the input matrices. + +**Types** + +* **T**: any supported floating-point type. + +*Example 1: 2D input matrix.* + +.. code-block:: xml + :force: + + + + + + 3 + 3 + + + + + 3 + 3 + + + + +*Example 2: 3D input tensor with one batch dimension and adjoint=true.* + +.. code-block:: xml + :force: + + + + + + 2 + 4 + 4 + + + + + 2 + 4 + 4 + + + + +*Example 3: 5D input tensor with three batch dimensions.* + +.. code-block:: xml + :force: + + + + + + 5 + 4 + 3 + 2 + 2 + + + + + 5 + 4 + 3 + 2 + 2 + + + diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/matrix/Einsum_7.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/matrix/einsum-7.rst similarity index 100% rename from docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/matrix/Einsum_7.rst rename to docs/articles_en/documentation/openvino-ir-format/operation-sets/operations-specifications/matrix/einsum-7.rst diff --git a/docs/articles_en/documentation/openvino_ir/operation_sets/operations_specifications/matrix/MatMul_1.rst 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b/docs/articles_en/get-started/install-openvino-overview.rst similarity index 100% rename from docs/articles_en/get_started/installing-openvino-overview.rst rename to docs/articles_en/get-started/install-openvino-overview.rst diff --git a/docs/articles_en/get_started/installing-openvino-overview/installing-openvino-linux-header.rst b/docs/articles_en/get-started/install-openvino-overview/install-openvino-linux-header.rst similarity index 100% rename from docs/articles_en/get_started/installing-openvino-overview/installing-openvino-linux-header.rst rename to docs/articles_en/get-started/install-openvino-overview/install-openvino-linux-header.rst diff --git a/docs/articles_en/get_started/installing-openvino-overview/installing-openvino-linux-header/installing-openvino-apt.rst b/docs/articles_en/get-started/install-openvino-overview/install-openvino-linux-header/install-openvino-apt.rst similarity index 99% rename from docs/articles_en/get_started/installing-openvino-overview/installing-openvino-linux-header/installing-openvino-apt.rst rename to docs/articles_en/get-started/install-openvino-overview/install-openvino-linux-header/install-openvino-apt.rst index ff3b4778958c68..7d593d907ee949 100644 --- a/docs/articles_en/get_started/installing-openvino-overview/installing-openvino-linux-header/installing-openvino-apt.rst +++ b/docs/articles_en/get-started/install-openvino-overview/install-openvino-linux-header/install-openvino-apt.rst @@ -13,7 +13,6 @@ Install Intel® Distribution of OpenVINO™ Toolkit for Linux Using APT Reposito Note that the APT distribution: * offers both C/C++ and Python APIs - * does not offer support for NPU inference * is dedicated to Linux users only * additionally includes code samples diff --git a/docs/articles_en/get_started/installing-openvino-overview/installing-openvino-linux-header/installing-openvino-from-archive-linux.rst b/docs/articles_en/get-started/install-openvino-overview/install-openvino-linux-header/install-openvino-archive-linux.rst similarity index 100% rename from docs/articles_en/get_started/installing-openvino-overview/installing-openvino-linux-header/installing-openvino-from-archive-linux.rst rename to docs/articles_en/get-started/install-openvino-overview/install-openvino-linux-header/install-openvino-archive-linux.rst diff --git a/docs/articles_en/get_started/installing-openvino-overview/installing-openvino-linux-header/installing-openvino-yum.rst b/docs/articles_en/get-started/install-openvino-overview/install-openvino-linux-header/install-openvino-yum.rst similarity index 100% rename from docs/articles_en/get_started/installing-openvino-overview/installing-openvino-linux-header/installing-openvino-yum.rst rename to docs/articles_en/get-started/install-openvino-overview/install-openvino-linux-header/install-openvino-yum.rst diff --git a/docs/articles_en/get_started/installing-openvino-overview/installing-openvino-macos-header.rst b/docs/articles_en/get-started/install-openvino-overview/install-openvino-macos-header.rst similarity index 100% rename from docs/articles_en/get_started/installing-openvino-overview/installing-openvino-macos-header.rst rename to docs/articles_en/get-started/install-openvino-overview/install-openvino-macos-header.rst diff --git a/docs/articles_en/get_started/installing-openvino-overview/installing-openvino-macos-header/installing-openvino-from-archive-macos.rst b/docs/articles_en/get-started/install-openvino-overview/install-openvino-macos-header/install-openvino-archive-macos.rst similarity index 100% rename from docs/articles_en/get_started/installing-openvino-overview/installing-openvino-macos-header/installing-openvino-from-archive-macos.rst rename to docs/articles_en/get-started/install-openvino-overview/install-openvino-macos-header/install-openvino-archive-macos.rst diff --git a/docs/articles_en/get_started/installing-openvino-overview/installing-openvino-shared/installing-openvino-brew.rst b/docs/articles_en/get-started/install-openvino-overview/install-openvino-shared/install-openvino-brew.rst similarity index 100% rename from docs/articles_en/get_started/installing-openvino-overview/installing-openvino-shared/installing-openvino-brew.rst rename to docs/articles_en/get-started/install-openvino-overview/install-openvino-shared/install-openvino-brew.rst diff --git a/docs/articles_en/get_started/installing-openvino-overview/installing-openvino-shared/installing-openvino-conan.rst b/docs/articles_en/get-started/install-openvino-overview/install-openvino-shared/install-openvino-conan.rst similarity index 100% rename from docs/articles_en/get_started/installing-openvino-overview/installing-openvino-shared/installing-openvino-conan.rst rename to docs/articles_en/get-started/install-openvino-overview/install-openvino-shared/install-openvino-conan.rst diff --git a/docs/articles_en/get_started/installing-openvino-overview/installing-openvino-shared/installing-openvino-conda.rst b/docs/articles_en/get-started/install-openvino-overview/install-openvino-shared/install-openvino-conda.rst similarity index 100% rename from docs/articles_en/get_started/installing-openvino-overview/installing-openvino-shared/installing-openvino-conda.rst rename to docs/articles_en/get-started/install-openvino-overview/install-openvino-shared/install-openvino-conda.rst diff --git a/docs/articles_en/get_started/installing-openvino-overview/installing-openvino-shared/installing-openvino-docker-linux.rst b/docs/articles_en/get-started/install-openvino-overview/install-openvino-shared/install-openvino-docker-linux.rst similarity index 100% rename from docs/articles_en/get_started/installing-openvino-overview/installing-openvino-shared/installing-openvino-docker-linux.rst rename to docs/articles_en/get-started/install-openvino-overview/install-openvino-shared/install-openvino-docker-linux.rst diff --git a/docs/articles_en/get_started/installing-openvino-overview/installing-openvino-shared/installing-openvino-pip.rst b/docs/articles_en/get-started/install-openvino-overview/install-openvino-shared/install-openvino-pip.rst similarity index 98% rename from docs/articles_en/get_started/installing-openvino-overview/installing-openvino-shared/installing-openvino-pip.rst rename to docs/articles_en/get-started/install-openvino-overview/install-openvino-shared/install-openvino-pip.rst index 6b7475a9858d9b..1a80152624a5e7 100644 --- a/docs/articles_en/get_started/installing-openvino-overview/installing-openvino-shared/installing-openvino-pip.rst +++ b/docs/articles_en/get-started/install-openvino-overview/install-openvino-shared/install-openvino-pip.rst @@ -16,7 +16,6 @@ Install Intel® Distribution of OpenVINO™ Toolkit from PyPI Repository * offers the Python API only * is dedicated to users of all major OSes: Windows, Linux, and macOS (all x86_64 / arm64 architectures) - * Windows and Linux do not offer support for NPU inference * macOS offers support only for CPU inference .. tab-set:: diff --git a/docs/articles_en/get_started/installing-openvino-overview/installing-openvino-shared/installing-openvino-vcpkg.rst b/docs/articles_en/get-started/install-openvino-overview/install-openvino-shared/install-openvino-vcpkg.rst similarity index 100% rename from docs/articles_en/get_started/installing-openvino-overview/installing-openvino-shared/installing-openvino-vcpkg.rst rename to docs/articles_en/get-started/install-openvino-overview/install-openvino-shared/install-openvino-vcpkg.rst diff --git a/docs/articles_en/get_started/installing-openvino-overview/installing-openvino-windows-header.rst b/docs/articles_en/get-started/install-openvino-overview/install-openvino-windows-header.rst similarity index 100% rename from docs/articles_en/get_started/installing-openvino-overview/installing-openvino-windows-header.rst rename to docs/articles_en/get-started/install-openvino-overview/install-openvino-windows-header.rst diff --git a/docs/articles_en/get_started/installing-openvino-overview/installing-openvino-windows-header/installing-openvino-from-archive-windows.rst b/docs/articles_en/get-started/install-openvino-overview/install-openvino-windows-header/install-openvino-archive-windows.rst similarity index 95% rename from docs/articles_en/get_started/installing-openvino-overview/installing-openvino-windows-header/installing-openvino-from-archive-windows.rst rename to docs/articles_en/get-started/install-openvino-overview/install-openvino-windows-header/install-openvino-archive-windows.rst index 92683e866d6448..079e1cbd2c31c2 100644 --- a/docs/articles_en/get_started/installing-openvino-overview/installing-openvino-windows-header/installing-openvino-from-archive-windows.rst +++ b/docs/articles_en/get-started/install-openvino-overview/install-openvino-windows-header/install-openvino-archive-windows.rst @@ -254,13 +254,3 @@ Additional Resources * Pre-trained deep learning models: :ref:`Overview of OpenVINO™ Toolkit Pre-Trained Models ` * IoT libraries and code samples in the GitHUB repository: `Intel® IoT Developer Kit `__ - - diff --git a/docs/articles_en/get_started/installing-openvino-overview/installing-openvino-yocto.rst b/docs/articles_en/get-started/install-openvino-overview/install-openvino-yocto.rst similarity index 100% rename from docs/articles_en/get_started/installing-openvino-overview/installing-openvino-yocto.rst rename to docs/articles_en/get-started/install-openvino-overview/install-openvino-yocto.rst diff --git a/docs/articles_en/get_started/troubleshooting.rst b/docs/articles_en/get-started/troubleshooting-install-config.rst similarity index 100% rename from docs/articles_en/get_started/troubleshooting.rst rename to docs/articles_en/get-started/troubleshooting-install-config.rst diff --git a/docs/articles_en/learn_openvino.rst b/docs/articles_en/learn-openvino.rst similarity index 100% rename from docs/articles_en/learn_openvino.rst rename to docs/articles_en/learn-openvino.rst diff --git a/docs/articles_en/learn_openvino/tutorials.rst b/docs/articles_en/learn-openvino/interactive-tutorials-python.rst similarity index 90% rename from docs/articles_en/learn_openvino/tutorials.rst rename to docs/articles_en/learn-openvino/interactive-tutorials-python.rst index f354633498200d..700793becd45a9 100644 --- a/docs/articles_en/learn_openvino/tutorials.rst +++ b/docs/articles_en/learn-openvino/interactive-tutorials-python.rst @@ -59,6 +59,24 @@ The Jupyter notebooks are categorized into following classes: Below you will find a selection of recommended tutorials that demonstrate inference on a particular model. These tutorials are guaranteed to provide a great experience with inference in OpenVINO: +.. showcase:: + :title: 284-openvoice + :img: https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/main/notebooks/284-openvoice/284-openvoice.png + + Voice tone cloning with OpenVoice and OpenVINO. + +.. showcase:: + :title: 283-photo-maker + :img: https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/main/notebooks/283-photo-maker/283-photo-maker.gif + + Text-to-image generation using PhotoMaker and OpenVINO. + +.. showcase:: + :title: 281-kosmos2-multimodal-large-language-model + :img: https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/main/notebooks/281-kosmos2-multimodal-large-language-model/281-kosmos2-multimodal-large-language-model.png + + Kosmos-2: Multimodal Large Language Model and OpenVINO. + .. showcase:: :title: 280-depth-anything :img: https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/main/notebooks/280-depth-anything/280-depth-anything.gif @@ -83,14 +101,12 @@ Below you will find a selection of recommended tutorials that demonstrate infere LLM Instruction-following pipeline with OpenVINO. - .. showcase:: :title: 274-efficient-sam :img: https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/main/notebooks/274-efficient-sam/274-efficient-sam.png Object segmentations with EfficientSAM and OpenVINO. - .. showcase:: :title: 273-stable-zephyr-3b-chatbot :img: _static/images/notebook_eye.png @@ -104,25 +120,6 @@ Below you will find a selection of recommended tutorials that demonstrate infere Paint by Example using Stable Diffusion and OpenVINO. -.. showcase:: - :title: 271-sdxl-turbo - :img: https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/main/notebooks/271-sdxl-turbo/271-sdxl-turbo.png - - Single step image generation using SDXL-turbo and OpenVINO. - -.. showcase:: - :title: 270-sound-generation-audioldm2 - :img: https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/main/notebooks/270-sound-generation-audioldm2/270-sound-generation-audioldm2.png - - Sound Generation with AudioLDM2 and OpenVINO. - -.. showcase:: - :title: 269-film-slowmo - :img: https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/main/notebooks/269-film-slowmo/269-film-slowmo.gif - - Frame interpolation using FILM and OpenVINO. - - .. note:: If there are any issues while running the notebooks, refer to the **Troubleshooting** and **FAQ** sections in the :doc:`Installation Guide ` or start a GitHub diff --git a/docs/articles_en/learn_openvino/tutorials/notebooks-installation.rst b/docs/articles_en/learn-openvino/interactive-tutorials-python/notebooks-installation.rst similarity index 100% rename from docs/articles_en/learn_openvino/tutorials/notebooks-installation.rst rename to docs/articles_en/learn-openvino/interactive-tutorials-python/notebooks-installation.rst diff --git a/docs/articles_en/learn_openvino/tutorials/notebooks_section_0.rst b/docs/articles_en/learn-openvino/interactive-tutorials-python/notebooks-section-0-first-steps.rst similarity index 100% rename from docs/articles_en/learn_openvino/tutorials/notebooks_section_0.rst rename to docs/articles_en/learn-openvino/interactive-tutorials-python/notebooks-section-0-first-steps.rst diff --git a/docs/articles_en/learn_openvino/tutorials/notebooks_section_1.rst b/docs/articles_en/learn-openvino/interactive-tutorials-python/notebooks-section-1-convert-and-optimize.rst similarity index 97% rename from docs/articles_en/learn_openvino/tutorials/notebooks_section_1.rst rename to docs/articles_en/learn-openvino/interactive-tutorials-python/notebooks-section-1-convert-and-optimize.rst index 67906f5067926d..4a3f4c26ccfbc7 100644 --- a/docs/articles_en/learn_openvino/tutorials/notebooks_section_1.rst +++ b/docs/articles_en/learn-openvino/interactive-tutorials-python/notebooks-section-1-convert-and-optimize.rst @@ -11,6 +11,12 @@ Convert & Optimize Tutorials that explain how to optimize and quantize models with OpenVINO tools. +.. showcase:: + :title: 127-tensorflow-bit-image-classification-nncf-quantization + :img: _static/images/notebook_eye.png + + BiT Image Classification OpenVINO IR model Quantization with NNCF. + .. showcase:: :title: 126-tensorflow-hub :img: _static/images/notebook_eye.png @@ -113,12 +119,6 @@ Tutorials that explain how to optimize and quantize models with OpenVINO tools. Use Neural Network Compression Framework (NNCF) to quantize PyTorch model in post-training mode (without model fine-tuning). -.. showcase:: - :title: 111-yolov5-quantization-migration - :img: _static/images/notebook_eye.png - - Migrate YOLOv5 POT API based quantization pipeline on Neural Network Compression Framework (NNCF). - .. showcase:: :title: 110-ct-segmentation-quantize-nncf :img: _static/images/notebook_eye.png diff --git a/docs/articles_en/learn_openvino/tutorials/notebooks_section_2.rst b/docs/articles_en/learn-openvino/interactive-tutorials-python/notebooks-section-2-model-demos.rst similarity index 95% rename from docs/articles_en/learn_openvino/tutorials/notebooks_section_2.rst rename to docs/articles_en/learn-openvino/interactive-tutorials-python/notebooks-section-2-model-demos.rst index caef030dc31cf2..716dffba35712b 100644 --- a/docs/articles_en/learn_openvino/tutorials/notebooks_section_2.rst +++ b/docs/articles_en/learn-openvino/interactive-tutorials-python/notebooks-section-2-model-demos.rst @@ -11,6 +11,31 @@ Model Demos Demos that demonstrate inference on a particular model. + +.. showcase:: + :title: 284-openvoice + :img: https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/main/notebooks/284-openvoice/284-openvoice.png + + Voice tone cloning with OpenVoice and OpenVINO. + +.. showcase:: + :title: 283-photo-maker + :img: https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/main/notebooks/283-photo-maker/283-photo-maker.gif + + Text-to-image generation using PhotoMaker and OpenVINO. + +.. showcase:: + :title: 282-siglip-zero-shot-image-classification + :img: https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/main/notebooks/228-clip-zero-shot-image-classification/228-clip-zero-shot-convert.png + + Zero-shot Image Classification with SigLIP. + +.. showcase:: + :title: 281-kosmos2-multimodal-large-language-model + :img: https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/main/notebooks/281-kosmos2-multimodal-large-language-model/281-kosmos2-multimodal-large-language-model.png + + Kosmos-2: Multimodal Large Language Model and OpenVINO. + .. showcase:: :title: 280-depth-anything :img: https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/main/notebooks/280-depth-anything/280-depth-anything.gif @@ -441,11 +466,6 @@ Demos that demonstrate inference on a particular model. Use pre-trained models to detect and recognize vehicles and their attributes with OpenVINO. -.. showcase:: - :title: 217-vision-deblur - :img: https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/main/notebooks/217-vision-deblur/217-vision-deblur.png - - Deblur images with DeblurGAN-v2. .. showcase:: :title: 216-attention-center diff --git a/docs/articles_en/learn_openvino/tutorials/notebooks_section_3.rst b/docs/articles_en/learn-openvino/interactive-tutorials-python/notebooks-section-3-model-training.rst similarity index 81% rename from docs/articles_en/learn_openvino/tutorials/notebooks_section_3.rst rename to docs/articles_en/learn-openvino/interactive-tutorials-python/notebooks-section-3-model-training.rst index a1397c746b88df..834051bffa5a02 100644 --- a/docs/articles_en/learn_openvino/tutorials/notebooks_section_3.rst +++ b/docs/articles_en/learn-openvino/interactive-tutorials-python/notebooks-section-3-model-training.rst @@ -23,6 +23,12 @@ Tutorials that include code to train neural networks. Use Neural Network Compression Framework (NNCF) to quantize PyTorch model. +.. showcase:: + :title: 301-tensorflow-training-openvino + :img: _static/images/notebook_eye.png + + From Training to Deployment with TensorFlow and OpenVINO™. + .. showcase:: :title: 301-tensorflow-training-openvino-nncf :img: _static/images/notebook_eye.png diff --git a/docs/articles_en/learn_openvino/tutorials/notebooks_section_4.rst b/docs/articles_en/learn-openvino/interactive-tutorials-python/notebooks-section-4-live-demos.rst similarity index 100% rename from docs/articles_en/learn_openvino/tutorials/notebooks_section_4.rst rename to docs/articles_en/learn-openvino/interactive-tutorials-python/notebooks-section-4-live-demos.rst diff --git a/docs/articles_en/learn_openvino/openvino_samples.rst b/docs/articles_en/learn-openvino/openvino-samples.rst similarity index 100% rename from docs/articles_en/learn_openvino/openvino_samples.rst rename to docs/articles_en/learn-openvino/openvino-samples.rst diff --git a/docs/articles_en/learn_openvino/openvino_samples/benchmark_tool.rst b/docs/articles_en/learn-openvino/openvino-samples/benchmark-tool.rst similarity index 99% rename from docs/articles_en/learn_openvino/openvino_samples/benchmark_tool.rst rename to docs/articles_en/learn-openvino/openvino-samples/benchmark-tool.rst index eb746da602d9a4..541983b769d45d 100644 --- a/docs/articles_en/learn_openvino/openvino_samples/benchmark_tool.rst +++ b/docs/articles_en/learn-openvino/openvino-samples/benchmark-tool.rst @@ -583,8 +583,8 @@ following usage message: -pcsort Optional. Report performance counters and analysis the sort hotpoint opts. "sort" Analysis opts time cost, print by hotpoint order "no_sort" Analysis opts time cost, print by normal order "simple_sort" Analysis opts time cost, only print EXECUTED opts by normal order -pcseq Optional. Report latencies for each shape in -data_shape sequence. -exec_graph_path Optional. Path to a file where to store executable graph information serialized. - -dump_config Optional. Path to JSON file to dump IE parameters, which were set by application. - -load_config Optional. Path to JSON file to load custom IE parameters. Please note, command line parameters have higher priority then parameters from configuration file. + -dump_config Optional. Path to JSON file to dump device properties, which were set by application. + -load_config Optional. Path to JSON file to load custom device properties. Please note, command line parameters have higher priority then parameters from configuration file. Example 1: a simple JSON file for HW device with primary properties. { "CPU": {"NUM_STREAMS": "3", "PERF_COUNT": "NO"} diff --git a/docs/articles_en/learn_openvino/openvino_samples/bert_benchmark.rst b/docs/articles_en/learn-openvino/openvino-samples/bert-benchmark.rst similarity index 100% rename from docs/articles_en/learn_openvino/openvino_samples/bert_benchmark.rst rename to docs/articles_en/learn-openvino/openvino-samples/bert-benchmark.rst diff --git a/docs/articles_en/learn_openvino/openvino_samples/get_started_demos.rst b/docs/articles_en/learn-openvino/openvino-samples/get-started-demos.rst similarity index 100% rename from docs/articles_en/learn_openvino/openvino_samples/get_started_demos.rst rename to docs/articles_en/learn-openvino/openvino-samples/get-started-demos.rst diff --git a/docs/articles_en/learn_openvino/openvino_samples/hello_classification.rst b/docs/articles_en/learn-openvino/openvino-samples/hello-classification.rst similarity index 100% rename from docs/articles_en/learn_openvino/openvino_samples/hello_classification.rst rename to docs/articles_en/learn-openvino/openvino-samples/hello-classification.rst diff --git a/docs/articles_en/learn_openvino/openvino_samples/hello_nv12_input_classification.rst b/docs/articles_en/learn-openvino/openvino-samples/hello-nv12-input-classification.rst similarity index 100% rename from docs/articles_en/learn_openvino/openvino_samples/hello_nv12_input_classification.rst rename to docs/articles_en/learn-openvino/openvino-samples/hello-nv12-input-classification.rst diff --git a/docs/articles_en/learn_openvino/openvino_samples/hello_query_device.rst b/docs/articles_en/learn-openvino/openvino-samples/hello-query-device.rst similarity index 100% rename from docs/articles_en/learn_openvino/openvino_samples/hello_query_device.rst rename to docs/articles_en/learn-openvino/openvino-samples/hello-query-device.rst diff --git a/docs/articles_en/learn_openvino/openvino_samples/hello_reshape_ssd.rst b/docs/articles_en/learn-openvino/openvino-samples/hello-reshape-ssd.rst similarity index 100% rename from docs/articles_en/learn_openvino/openvino_samples/hello_reshape_ssd.rst rename to docs/articles_en/learn-openvino/openvino-samples/hello-reshape-ssd.rst diff --git a/docs/articles_en/learn_openvino/openvino_samples/image_classification_async.rst b/docs/articles_en/learn-openvino/openvino-samples/image-classification-async.rst similarity index 100% rename from docs/articles_en/learn_openvino/openvino_samples/image_classification_async.rst rename to docs/articles_en/learn-openvino/openvino-samples/image-classification-async.rst diff --git a/docs/articles_en/learn_openvino/openvino_samples/model_creation.rst b/docs/articles_en/learn-openvino/openvino-samples/model-creation.rst similarity index 100% rename from docs/articles_en/learn_openvino/openvino_samples/model_creation.rst rename to docs/articles_en/learn-openvino/openvino-samples/model-creation.rst diff --git a/docs/articles_en/learn_openvino/openvino_samples/sync_benchmark.rst b/docs/articles_en/learn-openvino/openvino-samples/sync-benchmark.rst similarity index 100% rename from docs/articles_en/learn_openvino/openvino_samples/sync_benchmark.rst rename to docs/articles_en/learn-openvino/openvino-samples/sync-benchmark.rst diff --git a/docs/articles_en/learn_openvino/openvino_samples/throughput_benchmark.rst b/docs/articles_en/learn-openvino/openvino-samples/throughput-benchmark.rst similarity index 100% rename from docs/articles_en/learn_openvino/openvino_samples/throughput_benchmark.rst rename to docs/articles_en/learn-openvino/openvino-samples/throughput-benchmark.rst diff --git a/docs/articles_en/openvino_workflow.rst b/docs/articles_en/openvino-workflow.rst similarity index 100% rename from docs/articles_en/openvino_workflow.rst rename to docs/articles_en/openvino-workflow.rst diff --git a/docs/articles_en/openvino_workflow/deployment_intro.rst b/docs/articles_en/openvino-workflow/deployment-locally.rst similarity index 99% rename from docs/articles_en/openvino_workflow/deployment_intro.rst rename to docs/articles_en/openvino-workflow/deployment-locally.rst index 5ab6e9a0eeabd9..b86bf64d5644f1 100644 --- a/docs/articles_en/openvino_workflow/deployment_intro.rst +++ b/docs/articles_en/openvino-workflow/deployment-locally.rst @@ -64,7 +64,7 @@ The granularity of OpenVINO packages may vary for different distribution types. .. image:: _static/images/deployment_simplified.svg -- The main library ``openvino`` is used by users' C++ applications to link against with. For C language applications, ``openvino_c`` is additionally required for distribution. The library includes OpenVINO API 2.0. +- The main library ``openvino`` is used by users' C++ applications to link against with. For C language applications, ``openvino_c`` is additionally required for distribution. The library includes OpenVINO API. - The "optional" plugin libraries like ``openvino_intel_cpu_plugin`` (matching the ``openvino_.+_plugin`` pattern) are used to provide inference capabilities on specific devices or additional capabilities like :doc:`Hetero Execution ` and :doc:`Multi-Device Execution `. - The "optional" plugin libraries like ``openvino_ir_frontend`` (matching ``openvino_.+_frontend``) are used to provide capabilities to read models of different file formats such as OpenVINO IR, TensorFlow, ONNX, and PaddlePaddle. diff --git a/docs/articles_en/openvino_workflow/deployment_intro/local-distribution.rst b/docs/articles_en/openvino-workflow/deployment-locally/local-distribution-libraries.rst similarity index 95% rename from docs/articles_en/openvino_workflow/deployment_intro/local-distribution.rst rename to docs/articles_en/openvino-workflow/deployment-locally/local-distribution-libraries.rst index d1b3cc898241e2..5b82226b8ccf92 100644 --- a/docs/articles_en/openvino_workflow/deployment_intro/local-distribution.rst +++ b/docs/articles_en/openvino-workflow/deployment-locally/local-distribution-libraries.rst @@ -111,13 +111,17 @@ As shown in the picture above, some plugin libraries may have OS-specific depend Libraries for Execution Modes +++++++++++++++++++++++++++++ -The ``HETERO``, ``MULTI``, ``BATCH`` and ``AUTO`` execution modes can also be used by the application explicitly or implicitly. Use the following recommendation scheme to decide whether to add the appropriate libraries to the distribution package: +The ``HETERO``, ``MULTI``, ``BATCH``, and ``AUTO`` execution modes can also be used by the application explicitly or implicitly. +Use the following recommendation scheme to decide whether to add the appropriate libraries to the distribution package: - If :doc:`AUTO ` is used explicitly in the application or `ov::Core::compile_model `__ is used without specifying a device, put ``openvino_auto_plugin`` to the distribution. .. note:: - Automatic Device Selection relies on :doc:`inference device plugins `. If you are not sure which inference devices are available on the target system, put all inference plugin libraries in the distribution. If `ov::device::priorities `__ is used for `AUTO` to specify a limited device list, grab the corresponding device plugins only. + Automatic Device Selection relies on :doc:`inference device plugins `. + If you are not sure which inference devices are available on the target system, put all inference plugin libraries in the distribution. + If `ov::device::priorities `__ + is used for `AUTO` to specify a limited device list, grab the corresponding device plugins only. - If :doc:`MULTI ` is used explicitly, put ``openvino_auto_plugin`` in the distribution. - If :doc:`HETERO ` is either used explicitly or `ov::hint::performance_mode `__ is used with GPU, put ``openvino_hetero_plugin`` in the distribution. diff --git a/docs/articles_en/openvino_workflow/deployment_intro/conditional_compilation_deployment.rst b/docs/articles_en/openvino-workflow/deployment-locally/optimial-binary-size-conditional-compilation.rst similarity index 100% rename from docs/articles_en/openvino_workflow/deployment_intro/conditional_compilation_deployment.rst rename to docs/articles_en/openvino-workflow/deployment-locally/optimial-binary-size-conditional-compilation.rst diff --git a/docs/articles_en/openvino_workflow/gen_ai.rst b/docs/articles_en/openvino-workflow/generative-ai-models-guide.rst similarity index 100% rename from docs/articles_en/openvino_workflow/gen_ai.rst rename to docs/articles_en/openvino-workflow/generative-ai-models-guide.rst diff --git a/docs/articles_en/openvino_workflow/model_optimization_guide/tmo_introduction.rst b/docs/articles_en/openvino-workflow/model-optimization-guide/compressing-models-during-training.rst similarity index 100% rename from docs/articles_en/openvino_workflow/model_optimization_guide/tmo_introduction.rst rename to docs/articles_en/openvino-workflow/model-optimization-guide/compressing-models-during-training.rst diff --git a/docs/articles_en/openvino_workflow/model_optimization_guide/tmo_introduction/filter_pruning.rst b/docs/articles_en/openvino-workflow/model-optimization-guide/compressing-models-during-training/filter-pruning.rst similarity index 100% rename from docs/articles_en/openvino_workflow/model_optimization_guide/tmo_introduction/filter_pruning.rst rename to docs/articles_en/openvino-workflow/model-optimization-guide/compressing-models-during-training/filter-pruning.rst diff --git a/docs/articles_en/openvino_workflow/model_optimization_guide/tmo_introduction/qat.rst b/docs/articles_en/openvino-workflow/model-optimization-guide/compressing-models-during-training/quantization-aware-training.rst similarity index 100% rename from docs/articles_en/openvino_workflow/model_optimization_guide/tmo_introduction/qat.rst rename to docs/articles_en/openvino-workflow/model-optimization-guide/compressing-models-during-training/quantization-aware-training.rst diff --git a/docs/articles_en/openvino_workflow/model_optimization_guide/ptq_introduction.rst b/docs/articles_en/openvino-workflow/model-optimization-guide/quantizing-models-post-training.rst similarity index 92% rename from docs/articles_en/openvino_workflow/model_optimization_guide/ptq_introduction.rst rename to docs/articles_en/openvino-workflow/model-optimization-guide/quantizing-models-post-training.rst index 2e4b139fec769b..983ffd9232af61 100644 --- a/docs/articles_en/openvino_workflow/model_optimization_guide/ptq_introduction.rst +++ b/docs/articles_en/openvino-workflow/model-optimization-guide/quantizing-models-post-training.rst @@ -10,7 +10,7 @@ Quantizing Models Post-training basic_quantization_flow quantization_w_accuracy_control - + Post-training model optimization is the process of applying special methods that transform the model into a more hardware-friendly representation without retraining or fine-tuning. The most popular and widely-spread method here is 8-bit post-training quantization because it is: @@ -23,7 +23,7 @@ Post-training model optimization is the process of applying special methods that .. image:: _static/images/quantization_picture.svg -`Neural Network Compression Framework (NNCF) `__ provides a post-training quantization API available in Python that is aimed at reusing the code for model training or validation that is usually available with the model in the source framework, for example, PyTorch or TensroFlow. The NNCF API is cross-framework and currently supports models in the following frameworks: OpenVINO, PyTorch, TensorFlow 2.x, and ONNX. Currently, post-training quantization for models in OpenVINO Intermediate Representation is the most mature in terms of supported methods and models coverage. +`Neural Network Compression Framework (NNCF) `__ provides a post-training quantization API available in Python that is aimed at reusing the code for model training or validation that is usually available with the model in the source framework, for example, PyTorch or TensroFlow. The NNCF API is cross-framework and currently supports models in the following frameworks: OpenVINO, PyTorch, TensorFlow 2.x, and ONNX. Currently, post-training quantization for models in OpenVINO Intermediate Representation is the most mature in terms of supported methods and models coverage. NNCF API has two main capabilities to apply 8-bit post-training quantization: @@ -35,5 +35,4 @@ Additional Resources * :doc:`Optimizing Models at Training Time ` * `NNCF GitHub `__ -* `Tutorial: Migrate quantization from POT API to NNCF API `__ diff --git a/docs/articles_en/openvino_workflow/model_optimization_guide/ptq_introduction/basic_quantization_flow.rst b/docs/articles_en/openvino-workflow/model-optimization-guide/quantizing-models-post-training/basic-quantization-flow.rst similarity index 100% rename from docs/articles_en/openvino_workflow/model_optimization_guide/ptq_introduction/basic_quantization_flow.rst rename to docs/articles_en/openvino-workflow/model-optimization-guide/quantizing-models-post-training/basic-quantization-flow.rst diff --git a/docs/articles_en/openvino_workflow/model_optimization_guide/ptq_introduction/quantization_w_accuracy_control.rst b/docs/articles_en/openvino-workflow/model-optimization-guide/quantizing-models-post-training/quantizing-with-accuracy-control.rst similarity index 100% rename from docs/articles_en/openvino_workflow/model_optimization_guide/ptq_introduction/quantization_w_accuracy_control.rst rename to docs/articles_en/openvino-workflow/model-optimization-guide/quantizing-models-post-training/quantizing-with-accuracy-control.rst diff --git a/docs/articles_en/openvino_workflow/model_optimization_guide/weight_compression.rst b/docs/articles_en/openvino-workflow/model-optimization-guide/weight-compression.rst similarity index 100% rename from docs/articles_en/openvino_workflow/model_optimization_guide/weight_compression.rst rename to docs/articles_en/openvino-workflow/model-optimization-guide/weight-compression.rst diff --git a/docs/articles_en/openvino_workflow/model_optimization_guide.rst b/docs/articles_en/openvino-workflow/model-optimization.rst similarity index 100% rename from docs/articles_en/openvino_workflow/model_optimization_guide.rst rename to docs/articles_en/openvino-workflow/model-optimization.rst diff --git a/docs/articles_en/openvino_workflow/model_preparation.rst b/docs/articles_en/openvino-workflow/model-preparation.rst similarity index 71% rename from docs/articles_en/openvino_workflow/model_preparation.rst rename to docs/articles_en/openvino-workflow/model-preparation.rst index d46c81eb006f01..88caefb8bf52ce 100644 --- a/docs/articles_en/openvino_workflow/model_preparation.rst +++ b/docs/articles_en/openvino-workflow/model-preparation.rst @@ -26,43 +26,52 @@ OpenVINO supports the following model formats: * PaddlePaddle, * OpenVINO IR. -The easiest way to obtain a model is to download it from an online database, such as `TensorFlow Hub `__, `Hugging Face `__, -and `Torchvision models `__. Now you have two options: +The easiest way to obtain a model is to download it from an online database, such as +`TensorFlow Hub `__, `Hugging Face `__, and +`Torchvision models `__. Now you have two options: -* Skip model conversion and :doc:`run inference ` directly from the **TensorFlow, TensorFlow Lite, ONNX, and PaddlePaddle** source format. Conversion - will still be performed but it will happen automatically and "under the hood". - This option, while convenient, offers lower performance and stability, as well as - fewer optimization options. +* Skip model conversion and :doc:`run inference ` + directly from the **TensorFlow, TensorFlow Lite, ONNX, or PaddlePaddle** source format. + Conversion will still be performed but it will happen automatically and "under the hood". + This option, while convenient, offers lower performance and stability, as well as fewer + optimization options. * Explicitly :doc:`convert the model to OpenVINO IR `. - This approach offers the best possible results and is the recommended one, - especially for production-ready solutions. Consider storing your model in this format to minimize first-inference latency, - perform model optimizations, and save space on your drive, in some cases. Explicit conversion can be done in two ways: + This approach offers the best possible results and is the recommended one, especially for + production-ready solutions. Consider storing your model in this format to minimize + first-inference latency, perform model optimizations, and save space on your drive, in some + cases. Explicit conversion can be done in two ways: - * the `Python API functions <#convert-a-model-with-python-convert-model>`__ (``openvino.convert_model`` and ``openvino.save_model``) + * the `Python API functions <#convert-a-model-with-python-convert-model>`__ + (``openvino.convert_model`` and ``openvino.save_model``) * the `ovc <#convert-a-model-in-cli-ovc>`__ command line tool. - Once saved as :doc:`OpenVINO IR ` (a set of ``.xml`` and ``.bin`` files), - the model may be deployed with maximum performance. Because it is already optimized - for :doc:`OpenVINO inference `, it can be read, compiled, and inferred with no additional delay. + Once saved as :doc:`OpenVINO IR ` + (a set of ``.xml`` and ``.bin`` files), the model may be deployed with maximum performance. + Because it is already optimized for + :doc:`OpenVINO inference `, + it can be read, compiled, and inferred with no additional delay. .. note:: - Model conversion API prior to OpenVINO 2023.1 is considered deprecated. - Existing and new projects are recommended to transition to the new - solutions, keeping in mind that they are not fully backwards compatible - with ``openvino.tools.mo.convert_model`` or the ``mo`` CLI tool. - For more details, see the :doc:`Model Conversion API Transition Guide `. + Model conversion API prior to OpenVINO 2023.1 is considered deprecated. Existing and new + projects are recommended to transition to the new solutions, keeping in mind that they are + not fully backwards compatible with ``openvino.tools.mo.convert_model`` or the ``mo`` + CLI tool. For more details, see the + :doc:`Model Conversion API Transition Guide `. - For PyTorch models, `Python API <#convert-a-model-with-python-convert-model>`__ is the only conversion option. + For PyTorch models, `Python API <#convert-a-model-with-python-convert-model>`__ is the only + conversion option. Model States ############################################## -There are three states a model in OpenVINO can be: saved on disk, loaded but not compiled (``ov.Model``) or loaded and compiled (``ov.CompiledModel``). +There are three states a model in OpenVINO can be: saved on disk, loaded but not compiled +(``ov.Model``) or loaded and compiled (``ov.CompiledModel``). | **Saved on disk** -| A model in this state consists of one or more files that fully represent the neural network. A model can be stored in different ways. For example: +| A model in this state consists of one or more files that fully represent the neural + network. A model can be stored in different ways. For example: | OpenVINO IR: pair of .xml and .bin files | ONNX: .onnx file | TensorFlow: directory with a .pb file and two subfolders or just a .pb file @@ -70,21 +79,26 @@ There are three states a model in OpenVINO can be: saved on disk, loaded but not | PaddlePaddle: .pdmodel file | **Loaded but not compiled** -| A model object (``ov.Model``) is created in memory either by parsing a file or converting an existing framework object. Inference cannot be done with this object yet as it is not attached to any specific device, but it allows customization such as reshaping its input, applying quantization or even adding preprocessing steps before compiling the model. +| A model object (``ov.Model``) is created in memory either by parsing a file or converting + an existing framework object. Inference cannot be done with this object yet as it is not + attached to any specific device, but it allows customization such as reshaping its input, + applying quantization or even adding preprocessing steps before compiling the model. | **Loaded and compiled** -| This state is achieved when one or more devices are specified for a model object to run on (``ov.CompiledModel``), allowing device optimizations to be made and enabling inference. +| This state is achieved when one or more devices are specified for a model object to + run on (``ov.CompiledModel``), allowing device optimizations to be made and enabling + inference. -For more information on each function, see the :doc:`OpenVINO workflow ` page. +For more information on each function, see the :doc:`OpenVINO workflow ` +page. Convert a Model with Python: ``convert_model`` ############################################## -The Model conversion API in Python uses the ``openvino.convert_model`` function, -turning a given model into the `openvino.Model `__ -object and loading it to memory. Now it can be: saved to a drive with ``openvino.save_model`` -or further :doc:`optimized with NNCF ` -prior to saving. +Model Conversion API in Python uses the ``openvino.convert_model`` function, to turn a model +into the `openvino.Model `__ +object and load it to memory. Now it can be: saved to a drive with ``openvino.save_model`` +or further :doc:`optimized with NNCF ` before saving. See how to use ``openvino.convert_model`` with models from some of the most popular @@ -193,8 +207,7 @@ public repositories: # Check model page for information about input shape: https://tfhub.dev/google/imagenet/mobilenet_v1_100_224/classification/5 model.build([None, 224, 224, 3]) - model.save('mobilenet_v1_100_224') # use a temporary directory - ov_model = ov.convert_model('mobilenet_v1_100_224') + ov_model = ov.convert_model(model) ###### Option 1: Save to OpenVINO IR: @@ -247,19 +260,23 @@ public repositories: * Compiling the model, **Option 2**, provides a convenient way to quickly switch from framework-based code to OpenVINO-based code in your existing Python inference application. - The converted model is not saved to IR but compiled and used for inference within the same application. + The converted model is not saved to IR but compiled and used for inference within the same + application. -Before saving the model to OpenVINO IR, consider :doc:`Post-training Optimization ` -to achieve more efficient inference and smaller model size. +Before saving the model to OpenVINO IR, consider +:doc:`Post-training Optimization ` to achieve more efficient inference and +a smaller model. Convert a Model in CLI: ``ovc`` ############################### ``ovc`` is a command-line model converter, combining the ``openvino.convert_model`` -and ``openvino.save_model`` functionalities, providing the exact same results, if the same set of -parameters is used for saving into OpenVINO IR. It converts files from one of the to :doc:`OpenVINO IR `, which can then be read, compiled, -and run by the final inference application. +and ``openvino.save_model`` functionalities, providing the exact same results, if the same set +of parameters is used for saving into OpenVINO IR. It converts files from one of the supported +formats to +:doc:`OpenVINO IR `, +which can then be read, compiled, and run by the final inference application. .. note:: PyTorch models cannot be converted with ``ovc``, use ``openvino.convert_model`` instead. @@ -267,17 +284,20 @@ and run by the final inference application. Additional Resources #################### -The following articles describe in detail how to obtain and prepare your model depending on the source model type: +The following articles describe in detail how to obtain and prepare your model depending on +the source model type: * :doc:`Convert different model formats to the ov.Model format `. * :doc:`Review all available conversion parameters `. -To achieve the best model inference performance and more compact OpenVINO IR representation follow: +To achieve the best model inference performance and more compact OpenVINO IR representation +follow: * :doc:`Post-training optimization ` * :doc:`Model inference in OpenVINO Runtime ` -If you are still using the legacy conversion API (``mo`` or ``openvino.tools.mo.convert_model``), please refer to the following materials: +If you are still using the legacy conversion API (``mo`` or ``openvino.tools.mo.convert_model``), +refer to the following materials: * :doc:`Transition from legacy mo and ov.tools.mo.convert_model ` * :doc:`Legacy Model Conversion API ` diff --git a/docs/articles_en/openvino_workflow/model_preparation/conversion_parameters.rst b/docs/articles_en/openvino-workflow/model-preparation/conversion-parameters.rst similarity index 98% rename from docs/articles_en/openvino_workflow/model_preparation/conversion_parameters.rst rename to docs/articles_en/openvino-workflow/model-preparation/conversion-parameters.rst index 2c23f6f4810b56..e664a26917582a 100644 --- a/docs/articles_en/openvino_workflow/model_preparation/conversion_parameters.rst +++ b/docs/articles_en/openvino-workflow/model-preparation/conversion-parameters.rst @@ -67,7 +67,7 @@ Providing just a path to the model or model object as ``openvino.convert_model`` ovc path_to_your_model --compress_to_fp16=False For details on how plugins handle compressed ``FP16`` models, see -:doc:`Working with devices `. +:doc:`Inference Devices and Modes `. .. note:: diff --git a/docs/articles_en/openvino_workflow/model_preparation/Convert_Model_From_ONNX.rst b/docs/articles_en/openvino-workflow/model-preparation/convert-model-onnx.rst similarity index 100% rename from docs/articles_en/openvino_workflow/model_preparation/Convert_Model_From_ONNX.rst rename to docs/articles_en/openvino-workflow/model-preparation/convert-model-onnx.rst diff --git a/docs/articles_en/openvino_workflow/model_preparation/Convert_Model_From_Paddle.rst b/docs/articles_en/openvino-workflow/model-preparation/convert-model-paddle.rst similarity index 100% rename from docs/articles_en/openvino_workflow/model_preparation/Convert_Model_From_Paddle.rst rename to docs/articles_en/openvino-workflow/model-preparation/convert-model-paddle.rst diff --git a/docs/articles_en/openvino_workflow/model_preparation/Convert_Model_From_PyTorch.rst b/docs/articles_en/openvino-workflow/model-preparation/convert-model-pytorch.rst similarity index 100% rename from docs/articles_en/openvino_workflow/model_preparation/Convert_Model_From_PyTorch.rst rename to docs/articles_en/openvino-workflow/model-preparation/convert-model-pytorch.rst diff --git a/docs/articles_en/openvino_workflow/model_preparation/Convert_Model_From_TensorFlow_Lite.rst b/docs/articles_en/openvino-workflow/model-preparation/convert-model-tensorflow-lite.rst similarity index 100% rename from docs/articles_en/openvino_workflow/model_preparation/Convert_Model_From_TensorFlow_Lite.rst rename to docs/articles_en/openvino-workflow/model-preparation/convert-model-tensorflow-lite.rst diff --git a/docs/articles_en/openvino_workflow/model_preparation/Convert_Model_From_TensorFlow.rst b/docs/articles_en/openvino-workflow/model-preparation/convert-model-tensorflow.rst similarity index 100% rename from docs/articles_en/openvino_workflow/model_preparation/Convert_Model_From_TensorFlow.rst rename to docs/articles_en/openvino-workflow/model-preparation/convert-model-tensorflow.rst diff --git a/docs/articles_en/openvino_workflow/model_preparation/Convert_Model_IR.rst b/docs/articles_en/openvino-workflow/model-preparation/convert-model-to-ir.rst similarity index 100% rename from docs/articles_en/openvino_workflow/model_preparation/Convert_Model_IR.rst rename to docs/articles_en/openvino-workflow/model-preparation/convert-model-to-ir.rst diff --git a/docs/articles_en/openvino_workflow/model_preparation/setting_input_shapes.rst b/docs/articles_en/openvino-workflow/model-preparation/setting-input-shapes.rst similarity index 91% rename from docs/articles_en/openvino_workflow/model_preparation/setting_input_shapes.rst rename to docs/articles_en/openvino-workflow/model-preparation/setting-input-shapes.rst index f8ce36ba96ce13..7edb16ed772c16 100644 --- a/docs/articles_en/openvino_workflow/model_preparation/setting_input_shapes.rst +++ b/docs/articles_en/openvino-workflow/model-preparation/setting-input-shapes.rst @@ -5,7 +5,9 @@ Setting Input Shapes .. meta:: - :description: Learn how to increase the efficiency of a model by providing an additional shape definition with the ``input`` parameter of ``openvino.convert_model`` and ``ovc``. + :description: Learn how to increase the efficiency of a model by providing an additional + shape definition with the ``input`` parameter of ``openvino.convert_model`` + and ``ovc``. ``openvino.convert_model`` supports conversion of models with dynamic input shapes that @@ -15,14 +17,16 @@ one inference request to another, it is recommended to **set up static shapes** Doing so at the model preparation stage, not at runtime, can be beneficial in terms of performance and memory consumption. -For more information on changing input shapes in runtime, refer to the +For more information on changing input shapes in runtime, refer to the :doc:`Changing input shapes ` guide. -To learn more about dynamic shapes in runtime, refer to the +To learn more about dynamic shapes in runtime, refer to the :doc:`Dynamic Shapes ` guide. -The OpenVINO Runtime API may present certain limitations in inferring models with undefined dimensions on some hardware. -See the :doc:`Feature support matrix ` for reference. -In this case, the ``input`` parameter and the :doc:`reshape method ` can help to resolve undefined dimensions. +The OpenVINO Runtime API may present certain limitations in inferring models with undefined +dimensions on some hardware. See the :doc:`Feature support matrix ` +for reference. In this case, the ``input`` parameter and the +:doc:`reshape method ` can help to resolve undefined +dimensions. For example, run model conversion for the TensorFlow MobileNet model with the single input and specify the input shape of ``[2,300,300,3]``: diff --git a/docs/articles_en/openvino_workflow/running_inference_with_openvino.rst b/docs/articles_en/openvino-workflow/running-inference.rst similarity index 98% rename from docs/articles_en/openvino_workflow/running_inference_with_openvino.rst rename to docs/articles_en/openvino-workflow/running-inference.rst index 18e86c559871c9..2127ff0d5f65e7 100644 --- a/docs/articles_en/openvino_workflow/running_inference_with_openvino.rst +++ b/docs/articles_en/openvino-workflow/running-inference.rst @@ -10,7 +10,6 @@ Running Inference with OpenVINO™ openvino_docs_OV_UG_Integrate_OV_with_your_application openvino_docs_Runtime_Inference_Modes_Overview - openvino_docs_OV_UG_Working_with_devices openvino_docs_OV_UG_ShapeInference openvino_docs_OV_UG_DynamicShapes openvino_docs_OV_UG_stateful_models_intro diff --git a/docs/articles_en/openvino_workflow/running_inference_with_openvino/ShapeInference.rst b/docs/articles_en/openvino-workflow/running-inference/changing-input-shape.rst similarity index 100% rename from docs/articles_en/openvino_workflow/running_inference_with_openvino/ShapeInference.rst rename to docs/articles_en/openvino-workflow/running-inference/changing-input-shape.rst diff --git a/docs/articles_en/openvino_workflow/running_inference_with_openvino/ov_dynamic_shapes.rst b/docs/articles_en/openvino-workflow/running-inference/dynamic-shapes.rst similarity index 98% rename from docs/articles_en/openvino_workflow/running_inference_with_openvino/ov_dynamic_shapes.rst rename to docs/articles_en/openvino-workflow/running-inference/dynamic-shapes.rst index 26b8a369a9b548..7e932380d124cd 100644 --- a/docs/articles_en/openvino_workflow/running_inference_with_openvino/ov_dynamic_shapes.rst +++ b/docs/articles_en/openvino-workflow/running-inference/dynamic-shapes.rst @@ -11,8 +11,8 @@ Dynamic Shapes openvino_docs_OV_UG_NoDynamicShapes .. meta:: - :description: The Reshape method in OpenVINO Runtime API can handle dynamic - shapes of models that support changing input shapes before + :description: The Reshape method in OpenVINO Runtime API can handle dynamic + shapes of models that support changing input shapes before model compilation. @@ -61,7 +61,7 @@ Configuring the Model Model input dimensions can be specified as dynamic using the model.reshape method. To set a dynamic dimension, use ``-1``, ``ov::Dimension()`` (C++), or ``ov.Dimension()`` (Python) as the value for that dimension. .. note:: - + Some models may already have dynamic shapes out of the box and do not require additional configuration. This can either be because it was generated with dynamic shapes from the source framework, or because it was converted with Model Conversion API to use dynamic shapes. For more information, see the Dynamic Dimensions “Out of the Box” section. The examples below show how to set dynamic dimensions with a model that has a static ``[1, 3, 224, 224]`` input shape (such as `mobilenet-v2 `__). The first example shows how to change the first dimension (batch size) to be dynamic. In the second example, the third and fourth dimensions (height and width) are set as dynamic. @@ -74,7 +74,7 @@ The examples below show how to set dynamic dimensions with a model that has a st .. doxygensnippet:: docs/snippets/ov_dynamic_shapes.py :language: cpp :fragment: [reshape_undefined] - + With Python, you may also pass all dimensions as a string and use ``?`` for the dynamic dimensions (e.g. ``model.reshape(“1, 3, ?, ?”)``). .. tab-item:: C++ @@ -146,37 +146,37 @@ Static and dynamic dimensions can also be set when converting the model with ``c Dimension Bounds ---------------- -The lower and/or upper bounds of a dynamic dimension can also be specified. They define a range of allowed values for the dimension. Dimension bounds can be set by passing the lower and upper bounds into the ``reshape`` method using the options shown below. +The lower and/or upper bounds of a dynamic dimension can also be specified. They define a range of allowed values for the dimension. Dimension bounds can be set by passing the lower and upper bounds into the ``reshape`` method using the options shown below. .. tab-set:: .. tab-item:: Python :sync: py - + Each of these options are equivalent: - + - Pass the lower and upper bounds directly into the ``reshape`` method, e.g. ``model.reshape([1, 10), (8,512)])`` - Pass the lower and upper bounds using ov.Dimension, e.g. ``model.reshape([ov.Dimension(1, 10), (8, 512)])`` - Pass the dimension ranges as strings, e.g. ``model.reshape(“1..10, 8..512”)`` - + The examples below show how to set dynamic dimension bounds for a mobilenet-v2 model with a default static shape of ``[1,3,224,224]``. .. doxygensnippet:: docs/snippets/ov_dynamic_shapes.py :language: python :fragment: reshape_bounds - + .. tab-item:: C++ :sync: cpp - + The dimension bounds can be coded as arguments for ``ov::Dimension``, as shown in these examples: - + .. doxygensnippet:: docs/snippets/ov_dynamic_shapes.cpp :language: cpp :fragment: ov_dynamic_shapes:reshape_bounds - + .. tab-item:: C :sync: c - + The dimension bounds can be coded as arguments for `ov_dimension `__, as shown in these examples: .. doxygensnippet:: docs/snippets/ov_dynamic_shapes.c @@ -192,7 +192,7 @@ For the same reason, it is not recommended to leave dimensions as undefined, wit When specifying bounds, the lower bound is not as important as the upper one. The upper bound allows inference devices to allocate memory for intermediate tensors more precisely. It also allows using a fewer number of tuned kernels for different sizes. More precisely, benefits of specifying the lower or upper bound is device dependent. -Depending on the plugin, specifying the upper bounds can be required. For information about dynamic shapes support on different devices, refer to the :ref:`feature support table `. +Depending on the plugin, specifying the upper bounds can be required. For information about dynamic shapes support on different devices, refer to the :doc:`feature support table `. If the lower and upper bounds for a dimension are known, it is recommended to specify them, even if a plugin can execute a model without the bounds. @@ -218,7 +218,7 @@ The sample below shows how a model can accept different input shapes. In the fir .. doxygensnippet:: docs/snippets/ov_dynamic_shapes.cpp :language: cpp :fragment: ov_dynamic_shapes:set_input_tensor - + .. tab-item:: C :sync: c diff --git a/docs/articles_en/openvino_workflow/running_inference_with_openvino/ov_dynamic_shapes/ov_without_dynamic_shapes.rst b/docs/articles_en/openvino-workflow/running-inference/dynamic-shapes/openvino-without-dynamic-shapes-api.rst similarity index 100% rename from docs/articles_en/openvino_workflow/running_inference_with_openvino/ov_dynamic_shapes/ov_without_dynamic_shapes.rst rename to docs/articles_en/openvino-workflow/running-inference/dynamic-shapes/openvino-without-dynamic-shapes-api.rst diff --git a/docs/articles_en/openvino-workflow/running-inference/inference-devices-and-modes.rst b/docs/articles_en/openvino-workflow/running-inference/inference-devices-and-modes.rst new file mode 100644 index 00000000000000..2162d44dc4e05e --- /dev/null +++ b/docs/articles_en/openvino-workflow/running-inference/inference-devices-and-modes.rst @@ -0,0 +1,86 @@ +.. {#openvino_docs_Runtime_Inference_Modes_Overview} + +Inference Devices and Modes +============================ + + +.. toctree:: + :maxdepth: 1 + :hidden: + + openvino_docs_OV_UG_supported_plugins_CPU + openvino_docs_OV_UG_supported_plugins_GPU + openvino_docs_OV_UG_supported_plugins_NPU + openvino_docs_OV_UG_supported_plugins_AUTO + openvino_docs_OV_UG_Running_on_multiple_devices + openvino_docs_OV_UG_Hetero_execution + openvino_docs_OV_UG_Automatic_Batching + openvino_docs_OV_UG_query_api + + +The OpenVINO runtime offers multiple inference modes to enable the best hardware utilization under +different conditions: + +| **single-device inference** +| Define just one device responsible for the entire inference workload. It supports a range of + processors by means of the following plugins embedded in the Runtime library: +| - :doc:`CPU ` +| - :doc:`GPU ` +| - :doc:`NPU ` + +| **automated inference modes** +| Assume certain level of automation in selecting devices for inference. They may potentially + increase your deployed solution's performance and portability. The automated modes are: +| - :doc:`Automatic Device Selection (AUTO) ` +| - :doc:`Multi-Device Execution (MULTI) ` +| - :doc:`Heterogeneous Execution (HETERO) ` +| - :doc:`Automatic Batching Execution (Auto-batching) ` + + + +Enumerating Available Devices +####################################### + +The OpenVINO Runtime API features dedicated methods of enumerating devices and their capabilities. +Note that beyond the typical "CPU" or "GPU" device names, more qualified names are used when multiple +instances of a device are available (iGPU is always GPU.0). +The output you receive may look like this (truncated to device names only, two GPUs are listed +as an example): + +.. code-block:: sh + + ./hello_query_device + Available devices: + Device: CPU + ... + Device: GPU.0 + ... + Device: GPU.1 + + +You may see how to obtain this information in the :doc:`Hello Query Device Sample `. +Here is an example of a simple programmatic way to enumerate the devices and use them with the +multi-device mode: + +.. tab-set:: + + .. tab-item:: C++ + :sync: cpp + + .. doxygensnippet:: docs/snippets/MULTI2.cpp + :language: cpp + :fragment: [part2] + +With two GPU devices used in one setup, the explicit configuration would be "MULTI:GPU.1,GPU.0". +Accordingly, the code that loops over all available devices of the "GPU" type only is as follows: + +.. tab-set:: + + .. tab-item:: C++ + :sync: cpp + + .. doxygensnippet:: docs/snippets/MULTI3.cpp + :language: cpp + :fragment: [part3] + + diff --git a/docs/articles_en/openvino_workflow/running_inference_with_openvino/inference_modes_overview/auto_device_selection.rst b/docs/articles_en/openvino-workflow/running-inference/inference-devices-and-modes/auto-device-selection.rst similarity index 99% rename from docs/articles_en/openvino_workflow/running_inference_with_openvino/inference_modes_overview/auto_device_selection.rst rename to docs/articles_en/openvino-workflow/running-inference/inference-devices-and-modes/auto-device-selection.rst index 5ed1ff72c34fe0..bf8f9bdf84c653 100644 --- a/docs/articles_en/openvino_workflow/running_inference_with_openvino/inference_modes_overview/auto_device_selection.rst +++ b/docs/articles_en/openvino-workflow/running-inference/inference-devices-and-modes/auto-device-selection.rst @@ -247,7 +247,8 @@ See the following code for using AUTO and specifying devices: -Note that OpenVINO Runtime lets you use "GPU" as an alias for "GPU.0" in function calls. More details on enumerating devices can be found in :doc:`Working with devices `. +Note that OpenVINO Runtime lets you use "GPU" as an alias for "GPU.0" in function calls. +More details on enumerating devices can be found in :doc:`Inference Devices and Modes `. Checking Available Devices -------------------------- @@ -508,6 +509,6 @@ Additional Resources - :doc:`Debugging AUTO ` - :doc:`Running on Multiple Devices Simultaneously ` -- :doc:`Supported Devices ` +- :doc:`Inference Devices and Modes ` diff --git a/docs/articles_en/openvino_workflow/running_inference_with_openvino/inference_modes_overview/auto_device_selection/AutoPlugin_Debugging.rst b/docs/articles_en/openvino-workflow/running-inference/inference-devices-and-modes/auto-device-selection/gpu-remote-tensor-apirst.rst similarity index 100% rename from docs/articles_en/openvino_workflow/running_inference_with_openvino/inference_modes_overview/auto_device_selection/AutoPlugin_Debugging.rst rename to docs/articles_en/openvino-workflow/running-inference/inference-devices-and-modes/auto-device-selection/gpu-remote-tensor-apirst.rst diff --git a/docs/articles_en/openvino_workflow/running_inference_with_openvino/inference_modes_overview/automatic_batching.rst b/docs/articles_en/openvino-workflow/running-inference/inference-devices-and-modes/automatic-batching.rst similarity index 96% rename from docs/articles_en/openvino_workflow/running_inference_with_openvino/inference_modes_overview/automatic_batching.rst rename to docs/articles_en/openvino-workflow/running-inference/inference-devices-and-modes/automatic-batching.rst index 70751372526d52..c3867da72af72d 100644 --- a/docs/articles_en/openvino_workflow/running_inference_with_openvino/inference_modes_overview/automatic_batching.rst +++ b/docs/articles_en/openvino-workflow/running-inference/inference-devices-and-modes/automatic-batching.rst @@ -5,18 +5,18 @@ Automatic Batching .. meta:: - :description: The Automatic Batching Execution mode in OpenVINO Runtime - performs automatic batching to improve device utilization + :description: The Automatic Batching Execution mode in OpenVINO Runtime + performs automatic batching to improve device utilization by grouping inference requests. The Automatic Batching Execution mode (or Auto-batching for short) performs automatic batching on-the-fly to improve device utilization by grouping inference requests together, without programming effort from the user. -With Automatic Batching, gathering the input and scattering the output from the individual inference requests required for the batch happen transparently, without affecting the application code. +With Automatic Batching, gathering the input and scattering the output from the individual inference requests required for the batch happen transparently, without affecting the application code. Auto Batching can be used :ref:`directly as a virtual device ` or as an :ref:`option for inference on CPU/GPU/NPU ` (by means of configuration/hint). These 2 ways are provided for the user to enable the BATCH devices **explicitly** or **implicitly**, with the underlying logic remaining the same. An example of the difference is that the CPU device doesn’t support implicitly to enable BATCH device, commands such as ``./benchmark_app -m -d CPU -hint tput`` will not apply BATCH device **implicitly**, but ``./benchmark_app -m -d "BATCH:CPU(16)`` can **explicitly** load BATCH device. -Auto-batching primarily targets the existing code written for inferencing many requests, each instance with the batch size 1. To get corresponding performance improvements, the application **must be running multiple inference requests simultaneously**. -Auto-batching can also be used via a particular *virtual* device. +Auto-batching primarily targets the existing code written for inferencing many requests, each instance with the batch size 1. To get corresponding performance improvements, the application **must be running multiple inference requests simultaneously**. +Auto-batching can also be used via a particular *virtual* device. This article provides a preview of the Automatic Batching function, including how it works, its configurations, and testing performance. @@ -24,28 +24,28 @@ How Automatic Batching Works ############################ .. tab-set:: - + .. tab-item:: Enabling Automatic Batching :sync: enabling-automatic-batching - + Batching is a straightforward way of leveraging the compute power of GPU and saving on communication overheads. Automatic Batching is "implicitly" triggered on the GPU when ``ov::hint::PerformanceMode::THROUGHPUT`` is specified for the ``ov::hint::performance_mode`` property for the ``compile_model`` or ``set_property`` calls. .. tab-set:: - + .. tab-item:: Python :sync: py - + .. doxygensnippet:: docs/snippets/ov_auto_batching.py :language: Python :fragment: [compile_model] - + .. tab-item:: C++ :sync: cpp - + .. doxygensnippet:: docs/snippets/ov_auto_batching.cpp :language: cpp :fragment: [compile_model] - + To enable Auto-batching in the legacy apps not akin to the notion of performance hints, you need to use the **explicit** device notion, such as ``BATCH:GPU``. .. tab-item:: Disabling Automatic Batching @@ -54,17 +54,17 @@ How Automatic Batching Works Auto-Batching can be disabled (for example, for the GPU device) to prevent being triggered by ``ov::hint::PerformanceMode::THROUGHPUT``. To do that, set ``ov::hint::allow_auto_batching`` to **false** in addition to the ``ov::hint::performance_mode``, as shown below: .. tab-set:: - + .. tab-item:: Python :sync: py - + .. doxygensnippet:: docs/snippets/ov_auto_batching.py :language: Python :fragment: [compile_model_no_auto_batching] .. tab-item:: C++ :sync: cpp - + .. doxygensnippet:: docs/snippets/ov_auto_batching.cpp :language: cpp :fragment: [compile_model_no_auto_batching] @@ -99,10 +99,10 @@ This "automatic batch size selection" works on the presumption that the applicat .. doxygensnippet:: docs/snippets/ov_auto_batching.py :language: Python :fragment: [query_optimal_num_requests] - + .. tab-item:: C++ :sync: cpp - + .. doxygensnippet:: docs/snippets/ov_auto_batching.cpp :language: cpp :fragment: [query_optimal_num_requests] @@ -127,10 +127,10 @@ For example, when the application processes only 4 video streams, there is no ne .. doxygensnippet:: docs/snippets/ov_auto_batching.py :language: Python :fragment: [hint_num_requests] - + .. tab-item:: C++ :sync: cpp - + .. doxygensnippet:: docs/snippets/ov_auto_batching.cpp :language: cpp :fragment: [hint_num_requests] @@ -153,7 +153,7 @@ The below examples show how AUTO Batching can be used in the form of device that ./benchmark_app -m -d "BATCH:CPU(16)" -* ``BATCH`` -- load BATCH device explicitly, +* ``BATCH`` -- load BATCH device explicitly, * ``:GPU(16)`` -- BATCH devices configuration, which tell BATCH device to apply GPU device with batch size = 16. .. _auto-batching-as-option: @@ -167,7 +167,7 @@ In the following example, BATCH device will be configured to another device in c ./benchmark_app -m -d GPU -hint tput ./benchmark_app -m -d AUTO -hint tput - ./benchmark_app -m -d AUTO -hint ctput + ./benchmark_app -m -d AUTO -hint ctput ./benchmark_app -m -d AUTO:GPU -hint ctput .. note:: @@ -199,7 +199,7 @@ The following are limitations of the current AUTO Batching implementations: - Although it is less critical for the throughput-oriented scenarios, the load time with Auto-batching increases by almost double. - Certain networks are not safely reshapable by the "batching" dimension (specified as ``N`` in the layout terms). Besides, if the batching dimension is not zeroth, Auto-batching will not be triggered "implicitly" by the throughput hint. - The "explicit" notion, for example, ``BATCH:GPU``, using the relaxed dimensions tracking, often makes Auto-batching possible. For example, this method unlocks most **detection networks**. -- When *forcing* Auto-batching via the "explicit" device notion, make sure that you validate the results for correctness. +- When *forcing* Auto-batching via the "explicit" device notion, make sure that you validate the results for correctness. - Performance improvements happen at the cost of the growth of memory footprint. However, Auto-batching queries the available memory (especially for dGPU) and limits the selected batch size accordingly. @@ -209,13 +209,13 @@ Testing Performance with Benchmark_app Using the :doc:`benchmark_app sample ` is the best way to evaluate the performance of Automatic Batching: - The most straightforward way is using the performance hints: - + - benchmark_app **-hint tput** -d GPU -m 'path to your favorite model' - You can also use the "explicit" device notion to override the strict rules of the implicit reshaping by the batch dimension: - + - benchmark_app **-hint none -d BATCH:GPU** -m 'path to your favorite model' - or override the automatically deduced batch size as well: - + - $benchmark_app -hint none -d **BATCH:GPU(16)** -m 'path to your favorite model' - This example also applies to CPU or any other device that generally supports batch execution. - Keep in mind that some shell versions (e.g. ``bash``) may require adding quotes around complex device names, i.e. ``-d "BATCH:GPU(16)"`` in this example. @@ -225,21 +225,21 @@ Note that Benchmark_app performs a warm-up run of a *single* request. As Auto-Ba .. code-block:: sh - [ INFO ] First inference took 1000.18ms + [ INFO ] First inference took 1000.18ms This value also exposed as the final execution statistics on the ``benchmark_app`` exit: - + .. code-block:: sh - [ INFO ] Latency: + [ INFO ] Latency: [ INFO ] Max: 1000.18 ms -This is NOT the actual latency of the batched execution, so you are recommended to refer to other metrics in the same log, for example, "Median" or "Average" execution. +This is NOT the actual latency of the batched execution, so you are recommended to refer to other metrics in the same log, for example, "Median" or "Average" execution. Additional Resources #################### -* :doc:`Supported Devices ` +* :doc:`Inference Devices and Modes ` diff --git a/docs/articles_en/openvino_workflow/running_inference_with_openvino/Device_Plugins/CPU.rst b/docs/articles_en/openvino-workflow/running-inference/inference-devices-and-modes/cpu-device.rst similarity index 99% rename from docs/articles_en/openvino_workflow/running_inference_with_openvino/Device_Plugins/CPU.rst rename to docs/articles_en/openvino-workflow/running-inference/inference-devices-and-modes/cpu-device.rst index 8462af0f83ca21..98514b3d57518d 100644 --- a/docs/articles_en/openvino_workflow/running_inference_with_openvino/Device_Plugins/CPU.rst +++ b/docs/articles_en/openvino-workflow/running-inference/inference-devices-and-modes/cpu-device.rst @@ -543,7 +543,7 @@ Currently, the ``sparse weights decompression feature`` is supported with the fo Additional Resources ########################################################### -* :doc:`Supported Devices ` +* :doc:`Inference Devices and Modes ` * :doc:`Optimization guide ` * `CPU plugin developers documentation `__ diff --git a/docs/articles_en/openvino_workflow/running_inference_with_openvino/Device_Plugins/GPU.rst b/docs/articles_en/openvino-workflow/running-inference/inference-devices-and-modes/gpu-device.rst similarity index 99% rename from docs/articles_en/openvino_workflow/running_inference_with_openvino/Device_Plugins/GPU.rst rename to docs/articles_en/openvino-workflow/running-inference/inference-devices-and-modes/gpu-device.rst index 348a8f4570880f..e4956230bbfc19 100644 --- a/docs/articles_en/openvino_workflow/running_inference_with_openvino/Device_Plugins/GPU.rst +++ b/docs/articles_en/openvino-workflow/running-inference/inference-devices-and-modes/gpu-device.rst @@ -476,7 +476,7 @@ Since OpenVINO relies on the OpenCL kernels for the GPU implementation, many gen Additional Resources ####################################### -* :doc:`Supported Devices `. +* :doc:`Inference Devices and Modes `. * :doc:`Optimization guide `. * `GPU plugin developers documentation `__ diff --git a/docs/articles_en/openvino_workflow/running_inference_with_openvino/Device_Plugins/GPU/GPU_RemoteTensor_API.rst b/docs/articles_en/openvino-workflow/running-inference/inference-devices-and-modes/gpu-device/remote-tensor-api-gpu-plugin.rst similarity index 100% rename from docs/articles_en/openvino_workflow/running_inference_with_openvino/Device_Plugins/GPU/GPU_RemoteTensor_API.rst rename to docs/articles_en/openvino-workflow/running-inference/inference-devices-and-modes/gpu-device/remote-tensor-api-gpu-plugin.rst diff --git a/docs/articles_en/openvino_workflow/running_inference_with_openvino/inference_modes_overview/hetero_execution.rst b/docs/articles_en/openvino-workflow/running-inference/inference-devices-and-modes/hetero-execution.rst similarity index 99% rename from docs/articles_en/openvino_workflow/running_inference_with_openvino/inference_modes_overview/hetero_execution.rst rename to docs/articles_en/openvino-workflow/running-inference/inference-devices-and-modes/hetero-execution.rst index b7d62da2c3701b..824ac3b6dfb0cd 100644 --- a/docs/articles_en/openvino_workflow/running_inference_with_openvino/inference_modes_overview/hetero_execution.rst +++ b/docs/articles_en/openvino-workflow/running-inference/inference-devices-and-modes/hetero-execution.rst @@ -204,5 +204,5 @@ You can also point to more than two devices: ``-d HETERO:GPU,CPU`` Additional Resources #################### -* :doc:`Supported Devices ` +* :doc:`Inference Devices and Modes ` diff --git a/docs/articles_en/openvino_workflow/running_inference_with_openvino/inference_modes_overview/multi_device.rst b/docs/articles_en/openvino-workflow/running-inference/inference-devices-and-modes/multi-device.rst similarity index 97% rename from docs/articles_en/openvino_workflow/running_inference_with_openvino/inference_modes_overview/multi_device.rst rename to docs/articles_en/openvino-workflow/running-inference/inference-devices-and-modes/multi-device.rst index 74ca070830ff09..5e57b1572fa935 100644 --- a/docs/articles_en/openvino_workflow/running_inference_with_openvino/inference_modes_overview/multi_device.rst +++ b/docs/articles_en/openvino-workflow/running-inference/inference-devices-and-modes/multi-device.rst @@ -5,8 +5,8 @@ Multi-device execution .. meta:: - :description: The Multi-Device execution mode in OpenVINO Runtime assigns - multiple available computing devices to particular inference + :description: The Multi-Device execution mode in OpenVINO Runtime assigns + multiple available computing devices to particular inference requests to execute in parallel. @@ -49,7 +49,7 @@ Following the OpenVINO™ naming convention, the Multi-Device mode is assigned t Specifying the device list explicitly is required by MULTI, as it defines the devices available for inference and sets their priorities. -Note that OpenVINO™ Runtime enables you to use “GPU” as an alias for “GPU.0” in function calls. More details on enumerating devices can be found in :doc:`Working with devices `. +Note that OpenVINO™ Runtime enables you to use “GPU” as an alias for “GPU.0” in function calls. More details on enumerating devices can be found in :doc:`Inference Devices and Modes `. The following commands are accepted by the API: @@ -57,14 +57,14 @@ The following commands are accepted by the API: .. tab-item:: Python :sync: py - + .. doxygensnippet:: docs/snippets/ov_multi.py :language: python :fragment: [MULTI_0] .. tab-item:: C++ :sync: cpp - + .. doxygensnippet:: docs/snippets/MULTI0.cpp :language: cpp :fragment: [part0] @@ -82,14 +82,14 @@ As mentioned previously, executing inference with MULTI may be set up by configu .. tab-item:: Python :sync: py - + .. doxygensnippet:: docs/snippets/ov_multi.py :language: python :fragment: [MULTI_4] .. tab-item:: C++ :sync: cpp - + .. doxygensnippet:: docs/snippets/MULTI4.cpp :language: cpp :fragment: [part4] @@ -106,7 +106,7 @@ using the :doc:`configure devices ` property: .. tab-set:: .. tab-item:: C++ - + .. doxygensnippet:: docs/snippets/MULTI5.cpp :language: cpp :fragment: [part5] @@ -148,7 +148,7 @@ For best performance when using the MULTI execution mode you should consider a f Additional Resources #################### -- :doc:`Supported Devices ` +- :doc:`Inference Devices and Modes ` - :doc:`Automatic Device Selection ` diff --git a/docs/articles_en/openvino_workflow/running_inference_with_openvino/Device_Plugins/NPU.rst b/docs/articles_en/openvino-workflow/running-inference/inference-devices-and-modes/npu-device.rst similarity index 97% rename from docs/articles_en/openvino_workflow/running_inference_with_openvino/Device_Plugins/NPU.rst rename to docs/articles_en/openvino-workflow/running-inference/inference-devices-and-modes/npu-device.rst index 416225e4544898..3f5b8ae93d603a 100644 --- a/docs/articles_en/openvino_workflow/running_inference_with_openvino/Device_Plugins/NPU.rst +++ b/docs/articles_en/openvino-workflow/running-inference/inference-devices-and-modes/npu-device.rst @@ -152,4 +152,3 @@ Additional Resources * `3D Human Pose Estimation Python Demo `__ * `Object Detection C++ Demo `__ * `Object Detection Python Demo `__ -* `POT-specific sample with sparse resnet-50 generation `__ diff --git a/docs/articles_en/openvino_workflow/running_inference_with_openvino/Device_Plugins/config_properties.rst b/docs/articles_en/openvino-workflow/running-inference/inference-devices-and-modes/query-device-properties.rst similarity index 100% rename from docs/articles_en/openvino_workflow/running_inference_with_openvino/Device_Plugins/config_properties.rst rename to docs/articles_en/openvino-workflow/running-inference/inference-devices-and-modes/query-device-properties.rst diff --git a/docs/articles_en/openvino_workflow/running_inference_with_openvino/integrate_with_your_application.rst b/docs/articles_en/openvino-workflow/running-inference/integrate-openvino-with-your-application.rst similarity index 100% rename from docs/articles_en/openvino_workflow/running_inference_with_openvino/integrate_with_your_application.rst rename to docs/articles_en/openvino-workflow/running-inference/integrate-openvino-with-your-application.rst diff --git a/docs/articles_en/openvino_workflow/running_inference_with_openvino/integrate_with_your_application/ov_infer_request.rst b/docs/articles_en/openvino-workflow/running-inference/integrate-openvino-with-your-application/inference-request.rst similarity index 100% rename from docs/articles_en/openvino_workflow/running_inference_with_openvino/integrate_with_your_application/ov_infer_request.rst rename to docs/articles_en/openvino-workflow/running-inference/integrate-openvino-with-your-application/inference-request.rst diff --git a/docs/articles_en/openvino_workflow/running_inference_with_openvino/integrate_with_your_application/model_representation.rst b/docs/articles_en/openvino-workflow/running-inference/integrate-openvino-with-your-application/model-representation.rst similarity index 100% rename from docs/articles_en/openvino_workflow/running_inference_with_openvino/integrate_with_your_application/model_representation.rst rename to docs/articles_en/openvino-workflow/running-inference/integrate-openvino-with-your-application/model-representation.rst diff --git a/docs/articles_en/openvino_workflow/running_inference_with_openvino/integrate_with_your_application/Python_API_inference.rst b/docs/articles_en/openvino-workflow/running-inference/integrate-openvino-with-your-application/python-api-advanced-inference.rst similarity index 100% rename from docs/articles_en/openvino_workflow/running_inference_with_openvino/integrate_with_your_application/Python_API_inference.rst rename to docs/articles_en/openvino-workflow/running-inference/integrate-openvino-with-your-application/python-api-advanced-inference.rst diff --git a/docs/articles_en/openvino_workflow/running_inference_with_openvino/integrate_with_your_application/Python_API_exclusives.rst b/docs/articles_en/openvino-workflow/running-inference/integrate-openvino-with-your-application/python-api-exclusives.rst similarity index 100% rename from docs/articles_en/openvino_workflow/running_inference_with_openvino/integrate_with_your_application/Python_API_exclusives.rst rename to docs/articles_en/openvino-workflow/running-inference/integrate-openvino-with-your-application/python-api-exclusives.rst diff --git a/docs/articles_en/openvino_workflow/running_inference_with_openvino/dldt_deployment_optimization_guide.rst b/docs/articles_en/openvino-workflow/running-inference/optimize-inference.rst similarity index 97% rename from docs/articles_en/openvino_workflow/running_inference_with_openvino/dldt_deployment_optimization_guide.rst rename to docs/articles_en/openvino-workflow/running-inference/optimize-inference.rst index 5c389e3d789aa5..f612e0def505f8 100644 --- a/docs/articles_en/openvino_workflow/running_inference_with_openvino/dldt_deployment_optimization_guide.rst +++ b/docs/articles_en/openvino-workflow/running-inference/optimize-inference.rst @@ -17,11 +17,11 @@ Optimize Inference openvino_docs_OV_UG_Preprocessing_Overview openvino_docs_deployment_optimization_guide_internals Optimizing memory usage - + .. meta:: - :description: Improving inference performance involves model and runtime - optimizations that can be done independently. Inference + :description: Improving inference performance involves model and runtime + optimizations that can be done independently. Inference speed depends on latency and throughput. @@ -34,7 +34,8 @@ It is also important to understand how the full-stack application would use the For more information on this topic, see the following articles: -* :ref:`feature support by device ` +* :doc:`Supported Devices ` +* :doc:`Inference Devices and Modes ` * :ref:`Inputs Pre-processing with the OpenVINO ` * :ref:`Async API ` * :ref:`The 'get_tensor' Idiom ` diff --git a/docs/articles_en/openvino_workflow/running_inference_with_openvino/dldt_deployment_optimization_guide/dldt_deployment_optimization_common.rst b/docs/articles_en/openvino-workflow/running-inference/optimize-inference/general-optimizations.rst similarity index 100% rename from docs/articles_en/openvino_workflow/running_inference_with_openvino/dldt_deployment_optimization_guide/dldt_deployment_optimization_common.rst rename to docs/articles_en/openvino-workflow/running-inference/optimize-inference/general-optimizations.rst diff --git a/docs/articles_en/openvino_workflow/running_inference_with_openvino/dldt_deployment_optimization_guide/performance_hints.rst b/docs/articles_en/openvino-workflow/running-inference/optimize-inference/high-level-performance-hints.rst similarity index 90% rename from docs/articles_en/openvino_workflow/running_inference_with_openvino/dldt_deployment_optimization_guide/performance_hints.rst rename to docs/articles_en/openvino-workflow/running-inference/optimize-inference/high-level-performance-hints.rst index 048f01062f081f..15438b4b7741e3 100644 --- a/docs/articles_en/openvino_workflow/running_inference_with_openvino/dldt_deployment_optimization_guide/performance_hints.rst +++ b/docs/articles_en/openvino-workflow/running-inference/optimize-inference/high-level-performance-hints.rst @@ -5,17 +5,17 @@ High-level Performance Hints .. meta:: - :description: OpenVINO Runtime offers two dedicated high-level performance - hints, namely throughput and latency, that help to configure + :description: OpenVINO Runtime offers two dedicated high-level performance + hints, namely throughput and latency, that help to configure an inference device. -Even though all :doc:`supported devices ` in OpenVINO™ offer low-level performance settings, utilizing them is not recommended outside of very few cases. -The preferred way to configure performance in OpenVINO Runtime is using performance hints. This is a future-proof solution fully compatible with the :doc:`automatic device selection inference mode ` and designed with *portability* in mind. +Even though all :doc:`supported devices ` in OpenVINO™ offer low-level performance settings, utilizing them is not recommended outside of very few cases. +The preferred way to configure performance in OpenVINO Runtime is using performance hints. This is a future-proof solution fully compatible with the :doc:`automatic device selection inference mode ` and designed with *portability* in mind. The hints also set the direction of the configuration in the right order. Instead of mapping the application needs to the low-level performance settings, and keeping an associated application logic to configure each possible device separately, the hints express a target scenario with a single config key and let the *device* configure itself in response. -Previously, a certain level of automatic configuration was the result of the *default* values of the parameters. For example, the number of CPU streams was deduced from the number of CPU cores, when `ov::streams::AUTO `__ (``CPU_THROUGHPUT_AUTO`` in the pre-API 2.0 terminology) was set. However, the resulting number of streams did not account for actual compute requirements of the model to be inferred. +Previously, a certain level of automatic configuration was the result of the *default* values of the parameters. For example, the number of CPU streams was deduced from the number of CPU cores, when `ov::streams::AUTO `__ was set. However, the resulting number of streams did not account for actual compute requirements of the model to be inferred. The hints, in contrast, respect the actual model, so the parameters for optimal throughput are calculated for each model individually (based on its compute versus memory bandwidth requirements and capabilities of the device). Performance Hints: Latency and Throughput @@ -34,7 +34,7 @@ Performance Hints: How It Works Internally, every device "translates" the value of the hint to the actual performance settings. For example, the ``ov::hint::PerformanceMode::THROUGHPUT`` selects the number of CPU or GPU streams. -Additionally, the optimal batch size is selected for the GPU and the :doc:`automatic batching ` is applied whenever possible. To check whether the device supports it, refer to the :doc:`devices/features support matrix ` article. +Additionally, the optimal batch size is selected for the GPU and the :doc:`automatic batching ` is applied whenever possible. To check whether the device supports it, refer to the :doc:`Supported devices ` article. The resulting (device-specific) settings can be queried back from the instance of the ``ov:Compiled_Model``. Be aware that the ``benchmark_app`` outputs the actual settings for the ``THROUGHPUT`` hint. See the example of the output below: @@ -61,14 +61,14 @@ In the example code snippet below, ``ov::hint::PerformanceMode::THROUGHPUT`` is .. tab-item:: Python :sync: py - + .. doxygensnippet:: docs/snippets/ov_auto_batching.py :language: python :fragment: [compile_model] .. tab-item:: C++ :sync: cpp - + .. doxygensnippet:: docs/snippets/ov_auto_batching.cpp :language: cpp :fragment: [compile_model] @@ -77,21 +77,21 @@ In the example code snippet below, ``ov::hint::PerformanceMode::THROUGHPUT`` is Additional (Optional) Hints from the App ######################################## -For an application that processes 4 video streams, the most future-proof way to communicate the limitation of the parallel slack is to equip the performance hint with the optional ``ov::hint::num_requests`` configuration key set to 4. +For an application that processes 4 video streams, the most future-proof way to communicate the limitation of the parallel slack is to equip the performance hint with the optional ``ov::hint::num_requests`` configuration key set to 4. As mentioned earlier, this will limit the batch size for the GPU and the number of inference streams for the CPU. Thus, each device uses the ``ov::hint::num_requests`` while converting the hint to the actual device configuration options: .. tab-set:: .. tab-item:: Python :sync: py - + .. doxygensnippet:: docs/snippets/ov_auto_batching.py :language: python :fragment: [hint_num_requests] .. tab-item:: C++ :sync: cpp - + .. doxygensnippet:: docs/snippets/ov_auto_batching.cpp :language: cpp :fragment: [hint_num_requests] @@ -106,20 +106,20 @@ The hints are used on the presumption that the application queries ``ov::optimal .. tab-item:: Python :sync: py - + .. doxygensnippet:: docs/snippets/ov_auto_batching.py :language: python :fragment: [query_optimal_num_requests] .. tab-item:: C++ :sync: cpp - + .. doxygensnippet:: docs/snippets/ov_auto_batching.cpp :language: cpp :fragment: [query_optimal_num_requests] -While an application is free to create more requests if needed (for example to support asynchronous inputs population) **it is very important to at least run the** ``ov::optimal_number_of_infer_requests`` **of the inference requests in parallel**. It is recommended for efficiency, or device utilization, reasons. +While an application is free to create more requests if needed (for example to support asynchronous inputs population) **it is very important to at least run the** ``ov::optimal_number_of_infer_requests`` **of the inference requests in parallel**. It is recommended for efficiency, or device utilization, reasons. Keep in mind that ``ov::hint::PerformanceMode::LATENCY`` does not necessarily imply using single inference request. For example, multi-socket CPUs can deliver as many requests at the same minimal latency as the number of NUMA nodes in the system. To make your application fully scalable, make sure to query the ``ov::optimal_number_of_infer_requests`` directly. @@ -131,30 +131,30 @@ Prefer Async API The API of the inference requests offers Sync and Async execution. The ``ov::InferRequest::infer()`` is inherently synchronous and simple to operate (as it serializes the execution flow in the current application thread). The Async "splits" the ``infer()`` into ``ov::InferRequest::start_async()`` and ``ov::InferRequest::wait()`` (or callbacks). For more information on synchronous and asynchronous modes, refer to the :doc:`OpenVINO Inference Request documentation `. -Although the synchronous API can be easier to start with, it is recommended to use the asynchronous (callbacks-based) API in production code. It is the most general and scalable way to implement the flow control for any possible number of requests. The ``THROUGHPUT`` and ``LATENCY`` performance hints automatically configure the Asynchronous pipeline to use the optimal number of processing streams and inference requests. +Although the synchronous API can be easier to start with, it is recommended to use the asynchronous (callbacks-based) API in production code. It is the most general and scalable way to implement the flow control for any possible number of requests. The ``THROUGHPUT`` and ``LATENCY`` performance hints automatically configure the Asynchronous pipeline to use the optimal number of processing streams and inference requests. .. note:: - + **Important:** Performance Hints only work when asynchronous execution mode is used. They do not affect the performance of a synchronous pipeline. Combining the Hints and Individual Low-Level Settings ##################################################### -While sacrificing the portability to some extent, it is possible to combine the hints with individual device-specific settings. +While sacrificing the portability to some extent, it is possible to combine the hints with individual device-specific settings. For example, use ``ov::hint::PerformanceMode::THROUGHPUT`` to prepare a general configuration and override any of its specific values: .. tab-set:: .. tab-item:: Python :sync: py - + .. doxygensnippet:: docs/snippets/ov_auto_batching.py :language: python :fragment: [hint_plus_low_level] .. tab-item:: C++ :sync: cpp - + .. doxygensnippet:: docs/snippets/ov_auto_batching.cpp :language: cpp :fragment: [hint_plus_low_level] @@ -171,10 +171,3 @@ Using the :doc:`benchmark_app sample `is the bes Disabling the hints to emulate the pre-hints era (highly recommended before trying the individual low-level settings, such as the number of streams as below, threads, etc): * benchmark_app **-hint none -nstreams 1** -d 'device' -m 'path to your model' - - -Additional Resources -#################### - -* :doc:`Supported Devices ` - diff --git a/docs/articles_en/openvino_workflow/running_inference_with_openvino/dldt_deployment_optimization_guide/preprocessing_overview.rst b/docs/articles_en/openvino-workflow/running-inference/optimize-inference/optimizie-preprocessing.rst similarity index 100% rename from docs/articles_en/openvino_workflow/running_inference_with_openvino/dldt_deployment_optimization_guide/preprocessing_overview.rst rename to docs/articles_en/openvino-workflow/running-inference/optimize-inference/optimizie-preprocessing.rst diff --git a/docs/articles_en/openvino_workflow/running_inference_with_openvino/dldt_deployment_optimization_guide/preprocessing_overview/preprocessing_usecase_save.rst b/docs/articles_en/openvino-workflow/running-inference/optimize-inference/optimizie-preprocessing/integrate-save-preprocessing-use-case.rst similarity index 100% rename from docs/articles_en/openvino_workflow/running_inference_with_openvino/dldt_deployment_optimization_guide/preprocessing_overview/preprocessing_usecase_save.rst rename to docs/articles_en/openvino-workflow/running-inference/optimize-inference/optimizie-preprocessing/integrate-save-preprocessing-use-case.rst diff --git a/docs/articles_en/openvino_workflow/running_inference_with_openvino/dldt_deployment_optimization_guide/preprocessing_overview/layout_overview.rst b/docs/articles_en/openvino-workflow/running-inference/optimize-inference/optimizie-preprocessing/layout-api-overview.rst similarity index 100% rename from docs/articles_en/openvino_workflow/running_inference_with_openvino/dldt_deployment_optimization_guide/preprocessing_overview/layout_overview.rst rename to docs/articles_en/openvino-workflow/running-inference/optimize-inference/optimizie-preprocessing/layout-api-overview.rst diff --git a/docs/articles_en/openvino_workflow/running_inference_with_openvino/dldt_deployment_optimization_guide/preprocessing_overview/preprocessing_details.rst b/docs/articles_en/openvino-workflow/running-inference/optimize-inference/optimizie-preprocessing/preprocessing-api-details.rst similarity index 100% rename from docs/articles_en/openvino_workflow/running_inference_with_openvino/dldt_deployment_optimization_guide/preprocessing_overview/preprocessing_details.rst rename to docs/articles_en/openvino-workflow/running-inference/optimize-inference/optimizie-preprocessing/preprocessing-api-details.rst diff --git a/docs/articles_en/openvino_workflow/running_inference_with_openvino/dldt_deployment_optimization_guide/preprocessing_overview/torchvision_preprocessing_converter.rst b/docs/articles_en/openvino-workflow/running-inference/optimize-inference/optimizie-preprocessing/torchvision-preprocessing-converter.rst similarity index 100% rename from docs/articles_en/openvino_workflow/running_inference_with_openvino/dldt_deployment_optimization_guide/preprocessing_overview/torchvision_preprocessing_converter.rst rename to docs/articles_en/openvino-workflow/running-inference/optimize-inference/optimizie-preprocessing/torchvision-preprocessing-converter.rst diff --git a/docs/articles_en/openvino_workflow/running_inference_with_openvino/dldt_deployment_optimization_guide/dldt_deployment_optimization_latency.rst b/docs/articles_en/openvino-workflow/running-inference/optimize-inference/optimizing-latency.rst similarity index 95% rename from docs/articles_en/openvino_workflow/running_inference_with_openvino/dldt_deployment_optimization_guide/dldt_deployment_optimization_latency.rst rename to docs/articles_en/openvino-workflow/running-inference/optimize-inference/optimizing-latency.rst index 04fe228486fb0a..bfa684659a4f00 100644 --- a/docs/articles_en/openvino_workflow/running_inference_with_openvino/dldt_deployment_optimization_guide/dldt_deployment_optimization_latency.rst +++ b/docs/articles_en/openvino-workflow/running-inference/optimize-inference/optimizing-latency.rst @@ -11,8 +11,8 @@ Optimizing for Latency openvino_docs_OV_UG_Model_caching_overview .. meta:: - :description: OpenVINO provides methods that help to preserve minimal - latency despite the number of inference requests and + :description: OpenVINO provides methods that help to preserve minimal + latency despite the number of inference requests and improve throughput without degrading latency. @@ -34,15 +34,15 @@ Typically, human expertise is required to get more "throughput" out of the devic * feature support by device -When multiple models are to be used simultaneously, consider running inference on separate devices for each of them. Finally, when multiple models are executed in parallel on a device, using additional ``ov::hint::model_priority`` may help to define relative priorities of the models. Refer to the documentation on the :ref:`OpenVINO feature support for devices ` to check if your device supports the feature. +When multiple models are to be used simultaneously, consider running inference on separate devices for each of them. Finally, when multiple models are executed in parallel on a device, using additional ``ov::hint::model_priority`` may help to define relative priorities of the models. Refer to the documentation on the :ref:`OpenVINO feature support for devices ` to check if your device supports the feature. **First-Inference Latency and Model Load/Compile Time** -In some cases, model loading and compilation contribute to the "end-to-end" latency more than usual. +In some cases, model loading and compilation contribute to the "end-to-end" latency more than usual. For example, when the model is used exactly once, or when it is unloaded and reloaded in a cycle, to free the memory for another inference due to on-device memory limitations. Such a "first-inference latency" scenario may pose an additional limitation on the model load\compilation time, as inference accelerators (other than the CPU) usually require a certain level of model compilation upon loading. -The :doc:`model caching ` option is a way to lessen the impact over multiple application runs. If model caching is not possible, for example, it may require write permissions for the application, the CPU offers the fastest model load time almost every time. +The :doc:`model caching ` option is a way to lessen the impact over multiple application runs. If model caching is not possible, for example, it may require write permissions for the application, the CPU offers the fastest model load time almost every time. To improve common "first-inference latency" scenario, model reading was replaced with model mapping (using `mmap`) into a memory. But in some use cases (first of all, if model is located on removable or network drive) mapping may lead to latency increase. To switch mapping to reading, specify ``ov::enable_mmap(false)`` property for the ``ov::Core``. diff --git a/docs/articles_en/openvino_workflow/running_inference_with_openvino/dldt_deployment_optimization_guide/dldt_deployment_optimization_latency/Model_caching_overview.rst b/docs/articles_en/openvino-workflow/running-inference/optimize-inference/optimizing-latency/model-caching-overview.rst similarity index 82% rename from docs/articles_en/openvino_workflow/running_inference_with_openvino/dldt_deployment_optimization_guide/dldt_deployment_optimization_latency/Model_caching_overview.rst rename to docs/articles_en/openvino-workflow/running-inference/optimize-inference/optimizing-latency/model-caching-overview.rst index b38c93767a8d9a..133e351e8730be 100644 --- a/docs/articles_en/openvino_workflow/running_inference_with_openvino/dldt_deployment_optimization_guide/dldt_deployment_optimization_latency/Model_caching_overview.rst +++ b/docs/articles_en/openvino-workflow/running-inference/optimize-inference/optimizing-latency/model-caching-overview.rst @@ -5,34 +5,34 @@ Model Caching Overview .. meta:: - :description: Enabling model caching to export compiled model - automatically and reusing it can significantly + :description: Enabling model caching to export compiled model + automatically and reusing it can significantly reduce duration of model compilation on application startup. -As described in :doc:`Integrate OpenVINO™ with Your Application `, +As described in :doc:`Integrate OpenVINO™ with Your Application `, a common application flow consists of the following steps: -1. | **Create a Core object**: +1. | **Create a Core object**: | First step to manage available devices and read model objects -2. | **Read the Intermediate Representation**: +2. | **Read the Intermediate Representation**: | Read an Intermediate Representation file into an object of the `ov::Model `__ -3. | **Prepare inputs and outputs**: +3. | **Prepare inputs and outputs**: | If needed, manipulate precision, memory layout, size or color format -4. | **Set configuration**: +4. | **Set configuration**: | Pass device-specific loading configurations to the device -5. | **Compile and Load Network to device**: +5. | **Compile and Load Network to device**: | Use the `ov::Core::compile_model() `__ method with a specific device -6. | **Set input data**: +6. | **Set input data**: | Specify input tensor -7. | **Execute**: +7. | **Execute**: | Carry out inference and process results -Step 5 can potentially perform several time-consuming device-specific optimizations and network compilations. -To reduce the resulting delays at application startup, you can use Model Caching. It exports the compiled model +Step 5 can potentially perform several time-consuming device-specific optimizations and network compilations. +To reduce the resulting delays at application startup, you can use Model Caching. It exports the compiled model automatically and reuses it to significantly reduce the model compilation time. -.. important:: +.. important:: Not all devices support the network import/export feature. They will perform normally but will not enable the compilation stage speed-up. @@ -60,11 +60,11 @@ To enable model caching, the application must specify a folder to store the cach :fragment: [ov:caching:part0] -With this code, if the device specified by ``device_name`` supports import/export model capability, +With this code, if the device specified by ``device_name`` supports import/export model capability, a cached blob is automatically created inside the ``/path/to/cache/dir`` folder. If the device does not support the import/export capability, cache is not created and no error is thrown. -Note that the first ``compile_model`` operation takes slightly longer, as the cache needs to be created - +Note that the first ``compile_model`` operation takes slightly longer, as the cache needs to be created - the compiled blob is saved into a cache file: .. image:: _static/images/caching_enabled.svg @@ -137,10 +137,3 @@ To check in advance if a particular device supports model caching, your applicat :language: cpp :fragment: [ov:caching:part3] - -.. note:: - - For GPU, model caching is currently supported fully for static models only. For dynamic models, - kernel caching is used and multiple ‘.cl_cache’ files are generated along with the ‘.blob’ file. - See the :doc:`GPU plugin documentation `. - diff --git a/docs/articles_en/openvino_workflow/running_inference_with_openvino/dldt_deployment_optimization_guide/dldt_deployment_optimization_internals.rst b/docs/articles_en/openvino-workflow/running-inference/optimize-inference/optimizing-low-level-implementation.rst similarity index 100% rename from docs/articles_en/openvino_workflow/running_inference_with_openvino/dldt_deployment_optimization_guide/dldt_deployment_optimization_internals.rst rename to docs/articles_en/openvino-workflow/running-inference/optimize-inference/optimizing-low-level-implementation.rst diff --git a/docs/articles_en/openvino_workflow/running_inference_with_openvino/dldt_deployment_optimization_guide/memory_optimization_guide.rst b/docs/articles_en/openvino-workflow/running-inference/optimize-inference/optimizing-memory-usage.rst similarity index 100% rename from docs/articles_en/openvino_workflow/running_inference_with_openvino/dldt_deployment_optimization_guide/memory_optimization_guide.rst rename to docs/articles_en/openvino-workflow/running-inference/optimize-inference/optimizing-memory-usage.rst diff --git a/docs/articles_en/openvino_workflow/running_inference_with_openvino/dldt_deployment_optimization_guide/dldt_deployment_optimization_tput_advanced.rst b/docs/articles_en/openvino-workflow/running-inference/optimize-inference/optimizing-throughput-advanced.rst similarity index 100% rename from docs/articles_en/openvino_workflow/running_inference_with_openvino/dldt_deployment_optimization_guide/dldt_deployment_optimization_tput_advanced.rst rename to docs/articles_en/openvino-workflow/running-inference/optimize-inference/optimizing-throughput-advanced.rst diff --git a/docs/articles_en/openvino_workflow/running_inference_with_openvino/dldt_deployment_optimization_guide/dldt_deployment_optimization_tput.rst b/docs/articles_en/openvino-workflow/running-inference/optimize-inference/optimizing-throughput.rst similarity index 100% rename from docs/articles_en/openvino_workflow/running_inference_with_openvino/dldt_deployment_optimization_guide/dldt_deployment_optimization_tput.rst rename to docs/articles_en/openvino-workflow/running-inference/optimize-inference/optimizing-throughput.rst diff --git a/docs/articles_en/openvino_workflow/running_inference_with_openvino/dldt_deployment_optimization_guide/precision_control.rst b/docs/articles_en/openvino-workflow/running-inference/optimize-inference/precision-control.rst similarity index 98% rename from docs/articles_en/openvino_workflow/running_inference_with_openvino/dldt_deployment_optimization_guide/precision_control.rst rename to docs/articles_en/openvino-workflow/running-inference/optimize-inference/precision-control.rst index 25d5535808f378..db349a7c541b78 100644 --- a/docs/articles_en/openvino_workflow/running_inference_with_openvino/dldt_deployment_optimization_guide/precision_control.rst +++ b/docs/articles_en/openvino-workflow/running-inference/optimize-inference/precision-control.rst @@ -59,6 +59,6 @@ Inference Precision Additional Resources #################### -* :doc:`Supported Devices ` +* :doc:`Inference Devices and Modes ` diff --git a/docs/articles_en/openvino_workflow/running_inference_with_openvino/stateful_models_intro.rst b/docs/articles_en/openvino-workflow/running-inference/stateful-models-intro.rst similarity index 100% rename from docs/articles_en/openvino_workflow/running_inference_with_openvino/stateful_models_intro.rst rename to docs/articles_en/openvino-workflow/running-inference/stateful-models-intro.rst diff --git a/docs/articles_en/openvino_workflow/running_inference_with_openvino/stateful_models_intro/ways_to_get_stateful_model.rst b/docs/articles_en/openvino-workflow/running-inference/stateful-models-intro/obtaining-stateful-openvino-model.rst similarity index 100% rename from docs/articles_en/openvino_workflow/running_inference_with_openvino/stateful_models_intro/ways_to_get_stateful_model.rst rename to docs/articles_en/openvino-workflow/running-inference/stateful-models-intro/obtaining-stateful-openvino-model.rst diff --git a/docs/articles_en/openvino_workflow/running_inference_with_openvino/string_tensors.rst b/docs/articles_en/openvino-workflow/running-inference/string-tensors.rst similarity index 100% rename from docs/articles_en/openvino_workflow/running_inference_with_openvino/string_tensors.rst rename to docs/articles_en/openvino-workflow/running-inference/string-tensors.rst diff --git a/docs/articles_en/openvino_workflow/torch_compile.rst b/docs/articles_en/openvino-workflow/torch-compile.rst similarity index 100% rename from docs/articles_en/openvino_workflow/torch_compile.rst rename to docs/articles_en/openvino-workflow/torch-compile.rst diff --git a/docs/articles_en/openvino_workflow/running_inference_with_openvino/Device_Plugins.rst b/docs/articles_en/openvino_workflow/running_inference_with_openvino/Device_Plugins.rst deleted file mode 100644 index bb1839a2c3d22f..00000000000000 --- a/docs/articles_en/openvino_workflow/running_inference_with_openvino/Device_Plugins.rst +++ /dev/null @@ -1,111 +0,0 @@ -.. {#openvino_docs_OV_UG_Working_with_devices} - -Inference Device Support -======================== - - -.. meta:: - :description: The list of types of devices and corresponding plugins which - are compatible with OpenVINO Runtime and support inference - of deep learning models. - - -.. toctree:: - :maxdepth: 1 - :hidden: - - openvino_docs_OV_UG_supported_plugins_CPU - openvino_docs_OV_UG_supported_plugins_GPU - openvino_docs_OV_UG_supported_plugins_NPU - openvino_docs_OV_UG_query_api - - -OpenVINO™ Runtime can infer deep learning models using the following device types: - -* :doc:`CPU ` -* :doc:`GPU ` -* :doc:`NPU ` -* :doc:`Arm® CPU ` - -For a more detailed list of hardware, see :doc:`Supported Devices `. - -.. _devicesupport-feature-support-matrix: - - -Feature Support Matrix -####################################### - -The table below demonstrates support of key features by OpenVINO device plugins. - -========================================================================================= ============================ ========== =========== - Capability CPU GPU NPU -========================================================================================= ============================ ========== =========== - :doc:`Heterogeneous execution ` Yes Yes Partial - :doc:`Multi-device execution ` Yes Yes Yes - :doc:`Automatic batching ` No Yes No - :doc:`Multi-stream execution ` Yes (Intel® x86-64 only) Yes Yes - :doc:`Models caching ` Yes Partial Yes - :doc:`Dynamic shapes ` Yes Partial No - :doc:`Import/Export ` Yes No No* - :doc:`Preprocessing acceleration ` Yes Yes Partial - :doc:`Stateful models ` Yes No Yes - :doc:`Extensibility ` Yes Yes Partial -========================================================================================= ============================ ========== =========== - -For more details on plugin-specific feature limitations, see the corresponding plugin pages. - -Enumerating Available Devices -####################################### - -The OpenVINO Runtime API features dedicated methods of enumerating devices and their capabilities. See the :doc:`Hello Query Device C++ Sample `. This is an example output from the sample (truncated to device names only): - -.. code-block:: sh - - ./hello_query_device - Available devices: - Device: CPU - ... - Device: GPU.0 - ... - Device: GPU.1 - - -A simple programmatic way to enumerate the devices and use with the multi-device is as follows: - -.. tab-set:: - - .. tab-item:: C++ - :sync: cpp - - .. doxygensnippet:: docs/snippets/MULTI2.cpp - :language: cpp - :fragment: [part2] - - - -Beyond the typical "CPU", "GPU", and so on, when multiple instances of a device are available, the names are more qualified. -For example, this is how two GPUs can be listed (iGPU is always GPU.0): - -.. code-block:: sh - - ... - Device: GPU.0 - ... - Device: GPU.1 - - -So, the explicit configuration to use both would be "MULTI:GPU.1,GPU.0". Accordingly, the code that loops over all available devices of the "GPU" type only is as follows: - -.. tab-set:: - - .. tab-item:: C++ - :sync: cpp - - .. doxygensnippet:: docs/snippets/MULTI3.cpp - :language: cpp - :fragment: [part3] - - - - - diff --git a/docs/articles_en/openvino_workflow/running_inference_with_openvino/Device_Plugins/assets/GNA_Maximum_Input_Tensor_Widths_i16.csv b/docs/articles_en/openvino_workflow/running_inference_with_openvino/Device_Plugins/assets/GNA_Maximum_Input_Tensor_Widths_i16.csv deleted file mode 100644 index e4f9df38ee09d9..00000000000000 --- a/docs/articles_en/openvino_workflow/running_inference_with_openvino/Device_Plugins/assets/GNA_Maximum_Input_Tensor_Widths_i16.csv +++ /dev/null @@ -1,27976 +0,0 @@ -KH, KW, SH, SW, PH, PW, SH, SW, H, W (Ci=8/Co=256), W (Ci=16/Co=256), W (Ci=32/Co=256), W (Ci=64/Co=256), W (Ci=128/Co=256), W (Ci=256/Co=256), W (Ci=384/Co=256) -1, 1, 1, 1, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240, 240, 170 -1, 1, 1, 1, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240, 128, 85 -1, 1, 1, 1, 1, 1, 1, 1, 384, 240, 240, 240, 240, 170, 85, 56 -1, 2, 1, 1, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -1, 2, 1, 1, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -1, 2, 1, 1, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -1, 2, 1, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -1, 2, 1, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -1, 2, 1, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -1, 3, 1, 1, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -1, 3, 1, 1, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -1, 3, 1, 1, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -1, 3, 1, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -1, 3, 1, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -1, 3, 1, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -1, 3, 1, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -1, 3, 1, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -1, 3, 1, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -1, 4, 1, 1, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -1, 4, 1, 1, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -1, 4, 1, 1, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -1, 4, 1, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -1, 4, 1, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -1, 4, 1, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -1, 4, 1, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -1, 4, 1, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -1, 4, 1, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -1, 4, 1, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -1, 4, 1, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -1, 4, 1, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -1, 5, 1, 1, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -1, 5, 1, 1, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -1, 5, 1, 1, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -1, 5, 1, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -1, 5, 1, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -1, 5, 1, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -1, 5, 1, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -1, 5, 1, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -1, 5, 1, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -1, 5, 1, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -1, 5, 1, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -1, 5, 1, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -1, 5, 1, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -1, 5, 1, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -1, 5, 1, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -1, 6, 1, 1, 1, 1, 1, 1, 128, 240, 240, 240,,,, -1, 6, 1, 1, 1, 1, 1, 1, 256, 240, 240, 240,,,, -1, 6, 1, 1, 1, 1, 1, 1, 384, 240, 240, 240,,,, -1, 6, 1, 2, 1, 1, 1, 1, 128, 240, 240, 240,,,, -1, 6, 1, 2, 1, 1, 1, 1, 256, 240, 240, 240,,,, -1, 6, 1, 2, 1, 1, 1, 1, 384, 240, 240, 240,,,, -1, 6, 1, 3, 1, 1, 1, 1, 128, 240, 240, 240,,,, -1, 6, 1, 3, 1, 1, 1, 1, 256, 240, 240, 240,,,, -1, 6, 1, 3, 1, 1, 1, 1, 384, 240, 240, 240,,,, -1, 6, 1, 4, 1, 1, 1, 1, 128, 240, 240, 240,,,, -1, 6, 1, 4, 1, 1, 1, 1, 256, 240, 240, 240,,,, -1, 6, 1, 4, 1, 1, 1, 1, 384, 240, 240, 240,,,, -1, 6, 1, 5, 1, 1, 1, 1, 128, 240, 240, 240,,,, -1, 6, 1, 5, 1, 1, 1, 1, 256, 240, 240, 240,,,, -1, 6, 1, 5, 1, 1, 1, 1, 384, 240, 240, 240,,,, -1, 6, 1, 6, 1, 1, 1, 1, 128, 240, 240, 240,,,, -1, 6, 1, 6, 1, 1, 1, 1, 256, 240, 240, 240,,,, -1, 6, 1, 6, 1, 1, 1, 1, 384, 240, 240, 240,,,, -1, 7, 1, 1, 1, 1, 1, 1, 128, 240, 240, 240,,,, -1, 7, 1, 1, 1, 1, 1, 1, 256, 240, 240, 240,,,, -1, 7, 1, 1, 1, 1, 1, 1, 384, 240, 240, 240,,,, -1, 7, 1, 2, 1, 1, 1, 1, 128, 240, 240, 240,,,, -1, 7, 1, 2, 1, 1, 1, 1, 256, 240, 240, 240,,,, -1, 7, 1, 2, 1, 1, 1, 1, 384, 240, 240, 240,,,, -1, 7, 1, 3, 1, 1, 1, 1, 128, 240, 240, 240,,,, -1, 7, 1, 3, 1, 1, 1, 1, 256, 240, 240, 240,,,, -1, 7, 1, 3, 1, 1, 1, 1, 384, 240, 240, 240,,,, -1, 7, 1, 4, 1, 1, 1, 1, 128, 240, 240, 240,,,, -1, 7, 1, 4, 1, 1, 1, 1, 256, 240, 240, 240,,,, -1, 7, 1, 4, 1, 1, 1, 1, 384, 240, 240, 240,,,, -1, 7, 1, 5, 1, 1, 1, 1, 128, 240, 240, 240,,,, -1, 7, 1, 5, 1, 1, 1, 1, 256, 240, 240, 240,,,, -1, 7, 1, 5, 1, 1, 1, 1, 384, 240, 240, 240,,,, -1, 7, 1, 6, 1, 1, 1, 1, 128, 240, 240, 240,,,, -1, 7, 1, 6, 1, 1, 1, 1, 256, 240, 240, 240,,,, -1, 7, 1, 6, 1, 1, 1, 1, 384, 240, 240, 240,,,, -1, 7, 1, 7, 1, 1, 1, 1, 128, 240, 240, 240,,,, -1, 7, 1, 7, 1, 1, 1, 1, 256, 240, 240, 240,,,, -1, 7, 1, 7, 1, 1, 1, 1, 384, 240, 240, 240,,,, -2, 1, 1, 1, 1, 1, 1, 1, 128, 192, 192, 192, 192, 192, 192, 128 -2, 1, 1, 1, 1, 1, 1, 1, 256, 192, 192, 192, 192, 192, 128, 85 -2, 1, 1, 1, 1, 1, 1, 1, 384, 192, 192, 192, 192, 170, 85, 56 -2, 1, 2, 1, 1, 1, 1, 1, 128, 192, 192, 192, 192, 192, 192, 128 -2, 1, 2, 1, 1, 1, 1, 1, 256, 192, 192, 192, 192, 192, 128, 85 -2, 1, 2, 1, 1, 1, 1, 1, 384, 192, 192, 192, 192, 170, 85, 56 -2, 2, 1, 1, 1, 1, 1, 1, 128, 193, 193, 193, 193,,, -2, 2, 1, 1, 1, 1, 1, 1, 256, 193, 193, 193, 193,,, -2, 2, 1, 1, 1, 1, 1, 1, 384, 193, 193, 193, 193,,, -2, 2, 1, 1, 2, 2, 1, 1, 128, 193, 193, 192, 179,,, -2, 2, 1, 1, 2, 2, 1, 1, 256, 193, 193, 192, 179,,, -2, 2, 1, 1, 2, 2, 1, 1, 384, 193, 193, 192, 179,,, -2, 2, 1, 1, 2, 2, 1, 2, 128, 193, 193, 192, 179,,, -2, 2, 1, 1, 2, 2, 1, 2, 256, 193, 193, 192, 179,,, -2, 2, 1, 1, 2, 2, 1, 2, 384, 193, 193, 192, 179,,, -2, 2, 1, 1, 2, 2, 2, 1, 128, 193, 193, 192, 179,,, -2, 2, 1, 1, 2, 2, 2, 1, 256, 193, 193, 192, 179,,, -2, 2, 1, 1, 2, 2, 2, 1, 384, 193, 193, 192, 179,,, -2, 2, 1, 1, 2, 2, 2, 2, 128, 193, 193, 192, 179,,, -2, 2, 1, 1, 2, 2, 2, 2, 256, 193, 193, 192, 179,,, -2, 2, 1, 1, 2, 2, 2, 2, 384, 193, 193, 192, 179,,, -2, 2, 1, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 2, 1, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 2, 1, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 2, 1, 2, 2, 2, 1, 1, 128, 240, 240, 240, 240,,, -2, 2, 1, 2, 2, 2, 1, 1, 256, 240, 240, 240, 240,,, -2, 2, 1, 2, 2, 2, 1, 1, 384, 240, 240, 240, 240,,, -2, 2, 1, 2, 2, 2, 1, 2, 128, 240, 240, 240, 240,,, -2, 2, 1, 2, 2, 2, 1, 2, 256, 240, 240, 240, 240,,, -2, 2, 1, 2, 2, 2, 1, 2, 384, 240, 240, 240, 240,,, -2, 2, 1, 2, 2, 2, 2, 1, 128, 240, 240, 240, 240,,, -2, 2, 1, 2, 2, 2, 2, 1, 256, 240, 240, 240, 240,,, -2, 2, 1, 2, 2, 2, 2, 1, 384, 240, 240, 240, 240,,, -2, 2, 1, 2, 2, 2, 2, 2, 128, 240, 240, 240, 240,,, -2, 2, 1, 2, 2, 2, 2, 2, 256, 240, 240, 240, 240,,, -2, 2, 1, 2, 2, 2, 2, 2, 384, 240, 240, 240, 240,,, -2, 2, 2, 1, 1, 1, 1, 1, 128, 193, 193, 193, 193,,, -2, 2, 2, 1, 1, 1, 1, 1, 256, 193, 193, 193, 193,,, -2, 2, 2, 1, 1, 1, 1, 1, 384, 193, 193, 193, 193,,, -2, 2, 2, 1, 2, 2, 1, 1, 128, 193, 193, 192, 179,,, -2, 2, 2, 1, 2, 2, 1, 1, 256, 193, 193, 192, 179,,, -2, 2, 2, 1, 2, 2, 1, 1, 384, 193, 193, 192, 179,,, -2, 2, 2, 1, 2, 2, 1, 2, 128, 193, 193, 192, 179,,, -2, 2, 2, 1, 2, 2, 1, 2, 256, 193, 193, 192, 179,,, -2, 2, 2, 1, 2, 2, 1, 2, 384, 193, 193, 192, 179,,, -2, 2, 2, 1, 2, 2, 2, 1, 128, 193, 193, 192, 179,,, -2, 2, 2, 1, 2, 2, 2, 1, 256, 193, 193, 192, 179,,, -2, 2, 2, 1, 2, 2, 2, 1, 384, 193, 193, 192, 179,,, -2, 2, 2, 1, 2, 2, 2, 2, 128, 193, 193, 192, 179,,, -2, 2, 2, 1, 2, 2, 2, 2, 256, 193, 193, 192, 179,,, -2, 2, 2, 1, 2, 2, 2, 2, 384, 193, 193, 192, 179,,, -2, 2, 2, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 2, 2, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 2, 2, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 2, 2, 2, 2, 2, 1, 1, 128, 240, 240, 240, 240,,, -2, 2, 2, 2, 2, 2, 1, 1, 256, 240, 240, 240, 240,,, -2, 2, 2, 2, 2, 2, 1, 1, 384, 240, 240, 240, 240,,, -2, 2, 2, 2, 2, 2, 1, 2, 128, 240, 240, 240, 240,,, -2, 2, 2, 2, 2, 2, 1, 2, 256, 240, 240, 240, 240,,, -2, 2, 2, 2, 2, 2, 1, 2, 384, 240, 240, 240, 240,,, -2, 2, 2, 2, 2, 2, 2, 1, 128, 240, 240, 240, 240,,, -2, 2, 2, 2, 2, 2, 2, 1, 256, 240, 240, 240, 240,,, -2, 2, 2, 2, 2, 2, 2, 1, 384, 240, 240, 240, 240,,, -2, 2, 2, 2, 2, 2, 2, 2, 128, 240, 240, 240, 240,,, -2, 2, 2, 2, 2, 2, 2, 2, 256, 240, 240, 240, 240,,, -2, 2, 2, 2, 2, 2, 2, 2, 384, 240, 240, 240, 240,,, -2, 3, 1, 1, 1, 1, 1, 1, 128, 194, 194, 194, 194,,, -2, 3, 1, 1, 1, 1, 1, 1, 256, 194, 194, 194, 194,,, -2, 3, 1, 1, 1, 1, 1, 1, 384, 194, 194, 194, 194,,, -2, 3, 1, 1, 2, 2, 1, 1, 128, 194, 194, 186, 167,,, -2, 3, 1, 1, 2, 2, 1, 1, 256, 194, 194, 186, 167,,, -2, 3, 1, 1, 2, 2, 1, 1, 384, 194, 194, 186, 167,,, -2, 3, 1, 1, 2, 2, 1, 2, 128, 194, 194, 186, 167,,, -2, 3, 1, 1, 2, 2, 1, 2, 256, 194, 194, 186, 167,,, -2, 3, 1, 1, 2, 2, 1, 2, 384, 194, 194, 186, 167,,, -2, 3, 1, 1, 2, 2, 2, 1, 128, 194, 194, 186, 167,,, -2, 3, 1, 1, 2, 2, 2, 1, 256, 194, 194, 186, 167,,, -2, 3, 1, 1, 2, 2, 2, 1, 384, 194, 194, 186, 167,,, -2, 3, 1, 1, 2, 2, 2, 2, 128, 194, 194, 186, 167,,, -2, 3, 1, 1, 2, 2, 2, 2, 256, 194, 194, 186, 167,,, -2, 3, 1, 1, 2, 2, 2, 2, 384, 194, 194, 186, 167,,, -2, 3, 1, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 3, 1, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 3, 1, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 3, 1, 2, 2, 2, 1, 1, 128, 240, 240, 240, 240,,, -2, 3, 1, 2, 2, 2, 1, 1, 256, 240, 240, 240, 240,,, -2, 3, 1, 2, 2, 2, 1, 1, 384, 240, 240, 240, 240,,, -2, 3, 1, 2, 2, 2, 1, 2, 128, 240, 240, 240, 240,,, -2, 3, 1, 2, 2, 2, 1, 2, 256, 240, 240, 240, 240,,, -2, 3, 1, 2, 2, 2, 1, 2, 384, 240, 240, 240, 240,,, -2, 3, 1, 2, 2, 2, 2, 1, 128, 240, 240, 240, 240,,, -2, 3, 1, 2, 2, 2, 2, 1, 256, 240, 240, 240, 240,,, -2, 3, 1, 2, 2, 2, 2, 1, 384, 240, 240, 240, 240,,, -2, 3, 1, 2, 2, 2, 2, 2, 128, 240, 240, 240, 240,,, -2, 3, 1, 2, 2, 2, 2, 2, 256, 240, 240, 240, 240,,, -2, 3, 1, 2, 2, 2, 2, 2, 384, 240, 240, 240, 240,,, -2, 3, 1, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 3, 1, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 3, 1, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 3, 1, 3, 2, 2, 1, 1, 128, 240, 240, 240, 240,,, -2, 3, 1, 3, 2, 2, 1, 1, 256, 240, 240, 240, 240,,, -2, 3, 1, 3, 2, 2, 1, 1, 384, 240, 240, 240, 240,,, -2, 3, 1, 3, 2, 2, 1, 2, 128, 240, 240, 240, 240,,, -2, 3, 1, 3, 2, 2, 1, 2, 256, 240, 240, 240, 240,,, -2, 3, 1, 3, 2, 2, 1, 2, 384, 240, 240, 240, 240,,, -2, 3, 1, 3, 2, 2, 2, 1, 128, 240, 240, 240, 240,,, -2, 3, 1, 3, 2, 2, 2, 1, 256, 240, 240, 240, 240,,, -2, 3, 1, 3, 2, 2, 2, 1, 384, 240, 240, 240, 240,,, -2, 3, 1, 3, 2, 2, 2, 2, 128, 240, 240, 240, 240,,, -2, 3, 1, 3, 2, 2, 2, 2, 256, 240, 240, 240, 240,,, -2, 3, 1, 3, 2, 2, 2, 2, 384, 240, 240, 240, 240,,, -2, 3, 2, 1, 1, 1, 1, 1, 128, 194, 194, 194, 194,,, -2, 3, 2, 1, 1, 1, 1, 1, 256, 194, 194, 194, 194,,, -2, 3, 2, 1, 1, 1, 1, 1, 384, 194, 194, 194, 194,,, -2, 3, 2, 1, 2, 2, 1, 1, 128, 194, 194, 186, 167,,, -2, 3, 2, 1, 2, 2, 1, 1, 256, 194, 194, 186, 167,,, -2, 3, 2, 1, 2, 2, 1, 1, 384, 194, 194, 186, 167,,, -2, 3, 2, 1, 2, 2, 1, 2, 128, 194, 194, 186, 167,,, -2, 3, 2, 1, 2, 2, 1, 2, 256, 194, 194, 186, 167,,, -2, 3, 2, 1, 2, 2, 1, 2, 384, 194, 194, 186, 167,,, -2, 3, 2, 1, 2, 2, 2, 1, 128, 194, 194, 186, 167,,, -2, 3, 2, 1, 2, 2, 2, 1, 256, 194, 194, 186, 167,,, -2, 3, 2, 1, 2, 2, 2, 1, 384, 194, 194, 186, 167,,, -2, 3, 2, 1, 2, 2, 2, 2, 128, 194, 194, 186, 167,,, -2, 3, 2, 1, 2, 2, 2, 2, 256, 194, 194, 186, 167,,, -2, 3, 2, 1, 2, 2, 2, 2, 384, 194, 194, 186, 167,,, -2, 3, 2, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 3, 2, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 3, 2, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 3, 2, 2, 2, 2, 1, 1, 128, 240, 240, 240, 240,,, -2, 3, 2, 2, 2, 2, 1, 1, 256, 240, 240, 240, 240,,, -2, 3, 2, 2, 2, 2, 1, 1, 384, 240, 240, 240, 240,,, -2, 3, 2, 2, 2, 2, 1, 2, 128, 240, 240, 240, 240,,, -2, 3, 2, 2, 2, 2, 1, 2, 256, 240, 240, 240, 240,,, -2, 3, 2, 2, 2, 2, 1, 2, 384, 240, 240, 240, 240,,, -2, 3, 2, 2, 2, 2, 2, 1, 128, 240, 240, 240, 240,,, -2, 3, 2, 2, 2, 2, 2, 1, 256, 240, 240, 240, 240,,, -2, 3, 2, 2, 2, 2, 2, 1, 384, 240, 240, 240, 240,,, -2, 3, 2, 2, 2, 2, 2, 2, 128, 240, 240, 240, 240,,, -2, 3, 2, 2, 2, 2, 2, 2, 256, 240, 240, 240, 240,,, -2, 3, 2, 2, 2, 2, 2, 2, 384, 240, 240, 240, 240,,, -2, 3, 2, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 3, 2, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 3, 2, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 3, 2, 3, 2, 2, 1, 1, 128, 240, 240, 240, 240,,, -2, 3, 2, 3, 2, 2, 1, 1, 256, 240, 240, 240, 240,,, -2, 3, 2, 3, 2, 2, 1, 1, 384, 240, 240, 240, 240,,, -2, 3, 2, 3, 2, 2, 1, 2, 128, 240, 240, 240, 240,,, -2, 3, 2, 3, 2, 2, 1, 2, 256, 240, 240, 240, 240,,, -2, 3, 2, 3, 2, 2, 1, 2, 384, 240, 240, 240, 240,,, -2, 3, 2, 3, 2, 2, 2, 1, 128, 240, 240, 240, 240,,, -2, 3, 2, 3, 2, 2, 2, 1, 256, 240, 240, 240, 240,,, -2, 3, 2, 3, 2, 2, 2, 1, 384, 240, 240, 240, 240,,, -2, 3, 2, 3, 2, 2, 2, 2, 128, 240, 240, 240, 240,,, -2, 3, 2, 3, 2, 2, 2, 2, 256, 240, 240, 240, 240,,, -2, 3, 2, 3, 2, 2, 2, 2, 384, 240, 240, 240, 240,,, -2, 4, 1, 1, 1, 1, 1, 1, 128, 195, 195, 195, 195,,, -2, 4, 1, 1, 1, 1, 1, 1, 256, 195, 195, 195, 195,,, -2, 4, 1, 1, 1, 1, 1, 1, 384, 195, 195, 195, 195,,, -2, 4, 1, 1, 2, 2, 1, 1, 128, 195, 194, 181, 155,,, -2, 4, 1, 1, 2, 2, 1, 1, 256, 195, 194, 181, 155,,, -2, 4, 1, 1, 2, 2, 1, 1, 384, 195, 194, 181, 155,,, -2, 4, 1, 1, 2, 2, 1, 2, 128, 195, 194, 181, 155,,, -2, 4, 1, 1, 2, 2, 1, 2, 256, 195, 194, 181, 155,,, -2, 4, 1, 1, 2, 2, 1, 2, 384, 195, 194, 181, 155,,, -2, 4, 1, 1, 2, 2, 2, 1, 128, 195, 194, 181, 155,,, -2, 4, 1, 1, 2, 2, 2, 1, 256, 195, 194, 181, 155,,, -2, 4, 1, 1, 2, 2, 2, 1, 384, 195, 194, 181, 155,,, -2, 4, 1, 1, 2, 2, 2, 2, 128, 195, 194, 181, 155,,, -2, 4, 1, 1, 2, 2, 2, 2, 256, 195, 194, 181, 155,,, -2, 4, 1, 1, 2, 2, 2, 2, 384, 195, 194, 181, 155,,, -2, 4, 1, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 4, 1, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 4, 1, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 4, 1, 2, 2, 2, 1, 1, 128, 240, 240, 240, 240,,, -2, 4, 1, 2, 2, 2, 1, 1, 256, 240, 240, 240, 240,,, -2, 4, 1, 2, 2, 2, 1, 1, 384, 240, 240, 240, 240,,, -2, 4, 1, 2, 2, 2, 1, 2, 128, 240, 240, 240, 240,,, -2, 4, 1, 2, 2, 2, 1, 2, 256, 240, 240, 240, 240,,, -2, 4, 1, 2, 2, 2, 1, 2, 384, 240, 240, 240, 240,,, -2, 4, 1, 2, 2, 2, 2, 1, 128, 240, 240, 240, 240,,, -2, 4, 1, 2, 2, 2, 2, 1, 256, 240, 240, 240, 240,,, -2, 4, 1, 2, 2, 2, 2, 1, 384, 240, 240, 240, 240,,, -2, 4, 1, 2, 2, 2, 2, 2, 128, 240, 240, 240, 240,,, -2, 4, 1, 2, 2, 2, 2, 2, 256, 240, 240, 240, 240,,, -2, 4, 1, 2, 2, 2, 2, 2, 384, 240, 240, 240, 240,,, -2, 4, 1, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 4, 1, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 4, 1, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 4, 1, 3, 2, 2, 1, 1, 128, 240, 240, 240, 240,,, -2, 4, 1, 3, 2, 2, 1, 1, 256, 240, 240, 240, 240,,, -2, 4, 1, 3, 2, 2, 1, 1, 384, 240, 240, 240, 240,,, -2, 4, 1, 3, 2, 2, 1, 2, 128, 240, 240, 240, 240,,, -2, 4, 1, 3, 2, 2, 1, 2, 256, 240, 240, 240, 240,,, -2, 4, 1, 3, 2, 2, 1, 2, 384, 240, 240, 240, 240,,, -2, 4, 1, 3, 2, 2, 2, 1, 128, 240, 240, 240, 240,,, -2, 4, 1, 3, 2, 2, 2, 1, 256, 240, 240, 240, 240,,, -2, 4, 1, 3, 2, 2, 2, 1, 384, 240, 240, 240, 240,,, -2, 4, 1, 3, 2, 2, 2, 2, 128, 240, 240, 240, 240,,, -2, 4, 1, 3, 2, 2, 2, 2, 256, 240, 240, 240, 240,,, -2, 4, 1, 3, 2, 2, 2, 2, 384, 240, 240, 240, 240,,, -2, 4, 1, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 4, 1, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 4, 1, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 4, 1, 4, 2, 2, 1, 1, 128, 240, 240, 240, 240,,, -2, 4, 1, 4, 2, 2, 1, 1, 256, 240, 240, 240, 240,,, -2, 4, 1, 4, 2, 2, 1, 1, 384, 240, 240, 240, 240,,, -2, 4, 1, 4, 2, 2, 1, 2, 128, 240, 240, 240, 240,,, -2, 4, 1, 4, 2, 2, 1, 2, 256, 240, 240, 240, 240,,, -2, 4, 1, 4, 2, 2, 1, 2, 384, 240, 240, 240, 240,,, -2, 4, 1, 4, 2, 2, 2, 1, 128, 240, 240, 240, 240,,, -2, 4, 1, 4, 2, 2, 2, 1, 256, 240, 240, 240, 240,,, -2, 4, 1, 4, 2, 2, 2, 1, 384, 240, 240, 240, 240,,, -2, 4, 1, 4, 2, 2, 2, 2, 128, 240, 240, 240, 240,,, -2, 4, 1, 4, 2, 2, 2, 2, 256, 240, 240, 240, 240,,, -2, 4, 1, 4, 2, 2, 2, 2, 384, 240, 240, 240, 240,,, -2, 4, 2, 1, 1, 1, 1, 1, 128, 195, 195, 195, 195,,, -2, 4, 2, 1, 1, 1, 1, 1, 256, 195, 195, 195, 195,,, -2, 4, 2, 1, 1, 1, 1, 1, 384, 195, 195, 195, 195,,, -2, 4, 2, 1, 2, 2, 1, 1, 128, 195, 194, 181, 155,,, -2, 4, 2, 1, 2, 2, 1, 1, 256, 195, 194, 181, 155,,, -2, 4, 2, 1, 2, 2, 1, 1, 384, 195, 194, 181, 155,,, -2, 4, 2, 1, 2, 2, 1, 2, 128, 195, 194, 181, 155,,, -2, 4, 2, 1, 2, 2, 1, 2, 256, 195, 194, 181, 155,,, -2, 4, 2, 1, 2, 2, 1, 2, 384, 195, 194, 181, 155,,, -2, 4, 2, 1, 2, 2, 2, 1, 128, 195, 194, 181, 155,,, -2, 4, 2, 1, 2, 2, 2, 1, 256, 195, 194, 181, 155,,, -2, 4, 2, 1, 2, 2, 2, 1, 384, 195, 194, 181, 155,,, -2, 4, 2, 1, 2, 2, 2, 2, 128, 195, 194, 181, 155,,, -2, 4, 2, 1, 2, 2, 2, 2, 256, 195, 194, 181, 155,,, -2, 4, 2, 1, 2, 2, 2, 2, 384, 195, 194, 181, 155,,, -2, 4, 2, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 4, 2, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 4, 2, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 4, 2, 2, 2, 2, 1, 1, 128, 240, 240, 240, 240,,, -2, 4, 2, 2, 2, 2, 1, 1, 256, 240, 240, 240, 240,,, -2, 4, 2, 2, 2, 2, 1, 1, 384, 240, 240, 240, 240,,, -2, 4, 2, 2, 2, 2, 1, 2, 128, 240, 240, 240, 240,,, -2, 4, 2, 2, 2, 2, 1, 2, 256, 240, 240, 240, 240,,, -2, 4, 2, 2, 2, 2, 1, 2, 384, 240, 240, 240, 240,,, -2, 4, 2, 2, 2, 2, 2, 1, 128, 240, 240, 240, 240,,, -2, 4, 2, 2, 2, 2, 2, 1, 256, 240, 240, 240, 240,,, -2, 4, 2, 2, 2, 2, 2, 1, 384, 240, 240, 240, 240,,, -2, 4, 2, 2, 2, 2, 2, 2, 128, 240, 240, 240, 240,,, -2, 4, 2, 2, 2, 2, 2, 2, 256, 240, 240, 240, 240,,, -2, 4, 2, 2, 2, 2, 2, 2, 384, 240, 240, 240, 240,,, -2, 4, 2, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 4, 2, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 4, 2, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 4, 2, 3, 2, 2, 1, 1, 128, 240, 240, 240, 240,,, -2, 4, 2, 3, 2, 2, 1, 1, 256, 240, 240, 240, 240,,, -2, 4, 2, 3, 2, 2, 1, 1, 384, 240, 240, 240, 240,,, -2, 4, 2, 3, 2, 2, 1, 2, 128, 240, 240, 240, 240,,, -2, 4, 2, 3, 2, 2, 1, 2, 256, 240, 240, 240, 240,,, -2, 4, 2, 3, 2, 2, 1, 2, 384, 240, 240, 240, 240,,, -2, 4, 2, 3, 2, 2, 2, 1, 128, 240, 240, 240, 240,,, -2, 4, 2, 3, 2, 2, 2, 1, 256, 240, 240, 240, 240,,, -2, 4, 2, 3, 2, 2, 2, 1, 384, 240, 240, 240, 240,,, -2, 4, 2, 3, 2, 2, 2, 2, 128, 240, 240, 240, 240,,, -2, 4, 2, 3, 2, 2, 2, 2, 256, 240, 240, 240, 240,,, -2, 4, 2, 3, 2, 2, 2, 2, 384, 240, 240, 240, 240,,, -2, 4, 2, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 4, 2, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 4, 2, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 4, 2, 4, 2, 2, 1, 1, 128, 240, 240, 240, 240,,, -2, 4, 2, 4, 2, 2, 1, 1, 256, 240, 240, 240, 240,,, -2, 4, 2, 4, 2, 2, 1, 1, 384, 240, 240, 240, 240,,, -2, 4, 2, 4, 2, 2, 1, 2, 128, 240, 240, 240, 240,,, -2, 4, 2, 4, 2, 2, 1, 2, 256, 240, 240, 240, 240,,, -2, 4, 2, 4, 2, 2, 1, 2, 384, 240, 240, 240, 240,,, -2, 4, 2, 4, 2, 2, 2, 1, 128, 240, 240, 240, 240,,, -2, 4, 2, 4, 2, 2, 2, 1, 256, 240, 240, 240, 240,,, -2, 4, 2, 4, 2, 2, 2, 1, 384, 240, 240, 240, 240,,, -2, 4, 2, 4, 2, 2, 2, 2, 128, 240, 240, 240, 240,,, -2, 4, 2, 4, 2, 2, 2, 2, 256, 240, 240, 240, 240,,, -2, 4, 2, 4, 2, 2, 2, 2, 384, 240, 240, 240, 240,,, -2, 5, 1, 1, 1, 1, 1, 1, 128, 196, 196, 196, 132,,, -2, 5, 1, 1, 1, 1, 1, 1, 256, 196, 196, 196, 132,,, -2, 5, 1, 1, 1, 1, 1, 1, 384, 196, 196, 196, 132,,, -2, 5, 1, 1, 2, 2, 1, 1, 128, 196, 192, 176, 132,,, -2, 5, 1, 1, 2, 2, 1, 1, 256, 196, 192, 176, 132,,, -2, 5, 1, 1, 2, 2, 1, 1, 384, 196, 192, 176, 132,,, -2, 5, 1, 1, 2, 2, 1, 2, 128, 196, 192, 176, 132,,, -2, 5, 1, 1, 2, 2, 1, 2, 256, 196, 192, 176, 132,,, -2, 5, 1, 1, 2, 2, 1, 2, 384, 196, 192, 176, 132,,, -2, 5, 1, 1, 2, 2, 2, 1, 128, 196, 192, 176, 132,,, -2, 5, 1, 1, 2, 2, 2, 1, 256, 196, 192, 176, 132,,, -2, 5, 1, 1, 2, 2, 2, 1, 384, 196, 192, 176, 132,,, -2, 5, 1, 1, 2, 2, 2, 2, 128, 196, 192, 176, 132,,, -2, 5, 1, 1, 2, 2, 2, 2, 256, 196, 192, 176, 132,,, -2, 5, 1, 1, 2, 2, 2, 2, 384, 196, 192, 176, 132,,, -2, 5, 1, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 5, 1, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 5, 1, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 5, 1, 2, 2, 2, 1, 1, 128, 240, 240, 240, 240,,, -2, 5, 1, 2, 2, 2, 1, 1, 256, 240, 240, 240, 240,,, -2, 5, 1, 2, 2, 2, 1, 1, 384, 240, 240, 240, 240,,, -2, 5, 1, 2, 2, 2, 1, 2, 128, 240, 240, 240, 240,,, -2, 5, 1, 2, 2, 2, 1, 2, 256, 240, 240, 240, 240,,, -2, 5, 1, 2, 2, 2, 1, 2, 384, 240, 240, 240, 240,,, -2, 5, 1, 2, 2, 2, 2, 1, 128, 240, 240, 240, 240,,, -2, 5, 1, 2, 2, 2, 2, 1, 256, 240, 240, 240, 240,,, -2, 5, 1, 2, 2, 2, 2, 1, 384, 240, 240, 240, 240,,, -2, 5, 1, 2, 2, 2, 2, 2, 128, 240, 240, 240, 240,,, -2, 5, 1, 2, 2, 2, 2, 2, 256, 240, 240, 240, 240,,, -2, 5, 1, 2, 2, 2, 2, 2, 384, 240, 240, 240, 240,,, -2, 5, 1, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 5, 1, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 5, 1, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 5, 1, 3, 2, 2, 1, 1, 128, 240, 240, 240, 240,,, -2, 5, 1, 3, 2, 2, 1, 1, 256, 240, 240, 240, 240,,, -2, 5, 1, 3, 2, 2, 1, 1, 384, 240, 240, 240, 240,,, -2, 5, 1, 3, 2, 2, 1, 2, 128, 240, 240, 240, 240,,, -2, 5, 1, 3, 2, 2, 1, 2, 256, 240, 240, 240, 240,,, -2, 5, 1, 3, 2, 2, 1, 2, 384, 240, 240, 240, 240,,, -2, 5, 1, 3, 2, 2, 2, 1, 128, 240, 240, 240, 240,,, -2, 5, 1, 3, 2, 2, 2, 1, 256, 240, 240, 240, 240,,, -2, 5, 1, 3, 2, 2, 2, 1, 384, 240, 240, 240, 240,,, -2, 5, 1, 3, 2, 2, 2, 2, 128, 240, 240, 240, 240,,, -2, 5, 1, 3, 2, 2, 2, 2, 256, 240, 240, 240, 240,,, -2, 5, 1, 3, 2, 2, 2, 2, 384, 240, 240, 240, 240,,, -2, 5, 1, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 5, 1, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 5, 1, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 5, 1, 4, 2, 2, 1, 1, 128, 240, 240, 240, 240,,, -2, 5, 1, 4, 2, 2, 1, 1, 256, 240, 240, 240, 240,,, -2, 5, 1, 4, 2, 2, 1, 1, 384, 240, 240, 240, 240,,, -2, 5, 1, 4, 2, 2, 1, 2, 128, 240, 240, 240, 240,,, -2, 5, 1, 4, 2, 2, 1, 2, 256, 240, 240, 240, 240,,, -2, 5, 1, 4, 2, 2, 1, 2, 384, 240, 240, 240, 240,,, -2, 5, 1, 4, 2, 2, 2, 1, 128, 240, 240, 240, 240,,, -2, 5, 1, 4, 2, 2, 2, 1, 256, 240, 240, 240, 240,,, -2, 5, 1, 4, 2, 2, 2, 1, 384, 240, 240, 240, 240,,, -2, 5, 1, 4, 2, 2, 2, 2, 128, 240, 240, 240, 240,,, -2, 5, 1, 4, 2, 2, 2, 2, 256, 240, 240, 240, 240,,, -2, 5, 1, 4, 2, 2, 2, 2, 384, 240, 240, 240, 240,,, -2, 5, 1, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 5, 1, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 5, 1, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 5, 1, 5, 2, 2, 1, 1, 128, 240, 240, 240, 240,,, -2, 5, 1, 5, 2, 2, 1, 1, 256, 240, 240, 240, 240,,, -2, 5, 1, 5, 2, 2, 1, 1, 384, 240, 240, 240, 240,,, -2, 5, 1, 5, 2, 2, 1, 2, 128, 240, 240, 240, 240,,, -2, 5, 1, 5, 2, 2, 1, 2, 256, 240, 240, 240, 240,,, -2, 5, 1, 5, 2, 2, 1, 2, 384, 240, 240, 240, 240,,, -2, 5, 1, 5, 2, 2, 2, 1, 128, 240, 240, 240, 240,,, -2, 5, 1, 5, 2, 2, 2, 1, 256, 240, 240, 240, 240,,, -2, 5, 1, 5, 2, 2, 2, 1, 384, 240, 240, 240, 240,,, -2, 5, 1, 5, 2, 2, 2, 2, 128, 240, 240, 240, 240,,, -2, 5, 1, 5, 2, 2, 2, 2, 256, 240, 240, 240, 240,,, -2, 5, 1, 5, 2, 2, 2, 2, 384, 240, 240, 240, 240,,, -2, 5, 2, 1, 1, 1, 1, 1, 128, 196, 196, 196, 132,,, -2, 5, 2, 1, 1, 1, 1, 1, 256, 196, 196, 196, 132,,, -2, 5, 2, 1, 1, 1, 1, 1, 384, 196, 196, 196, 132,,, -2, 5, 2, 1, 2, 2, 1, 1, 128, 196, 192, 176, 132,,, -2, 5, 2, 1, 2, 2, 1, 1, 256, 196, 192, 176, 132,,, -2, 5, 2, 1, 2, 2, 1, 1, 384, 196, 192, 176, 132,,, -2, 5, 2, 1, 2, 2, 1, 2, 128, 196, 192, 176, 132,,, -2, 5, 2, 1, 2, 2, 1, 2, 256, 196, 192, 176, 132,,, -2, 5, 2, 1, 2, 2, 1, 2, 384, 196, 192, 176, 132,,, -2, 5, 2, 1, 2, 2, 2, 1, 128, 196, 192, 176, 132,,, -2, 5, 2, 1, 2, 2, 2, 1, 256, 196, 192, 176, 132,,, -2, 5, 2, 1, 2, 2, 2, 1, 384, 196, 192, 176, 132,,, -2, 5, 2, 1, 2, 2, 2, 2, 128, 196, 192, 176, 132,,, -2, 5, 2, 1, 2, 2, 2, 2, 256, 196, 192, 176, 132,,, -2, 5, 2, 1, 2, 2, 2, 2, 384, 196, 192, 176, 132,,, -2, 5, 2, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 5, 2, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 5, 2, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 5, 2, 2, 2, 2, 1, 1, 128, 240, 240, 240, 240,,, -2, 5, 2, 2, 2, 2, 1, 1, 256, 240, 240, 240, 240,,, -2, 5, 2, 2, 2, 2, 1, 1, 384, 240, 240, 240, 240,,, -2, 5, 2, 2, 2, 2, 1, 2, 128, 240, 240, 240, 240,,, -2, 5, 2, 2, 2, 2, 1, 2, 256, 240, 240, 240, 240,,, -2, 5, 2, 2, 2, 2, 1, 2, 384, 240, 240, 240, 240,,, -2, 5, 2, 2, 2, 2, 2, 1, 128, 240, 240, 240, 240,,, -2, 5, 2, 2, 2, 2, 2, 1, 256, 240, 240, 240, 240,,, -2, 5, 2, 2, 2, 2, 2, 1, 384, 240, 240, 240, 240,,, -2, 5, 2, 2, 2, 2, 2, 2, 128, 240, 240, 240, 240,,, -2, 5, 2, 2, 2, 2, 2, 2, 256, 240, 240, 240, 240,,, -2, 5, 2, 2, 2, 2, 2, 2, 384, 240, 240, 240, 240,,, -2, 5, 2, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 5, 2, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 5, 2, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 5, 2, 3, 2, 2, 1, 1, 128, 240, 240, 240, 240,,, -2, 5, 2, 3, 2, 2, 1, 1, 256, 240, 240, 240, 240,,, -2, 5, 2, 3, 2, 2, 1, 1, 384, 240, 240, 240, 240,,, -2, 5, 2, 3, 2, 2, 1, 2, 128, 240, 240, 240, 240,,, -2, 5, 2, 3, 2, 2, 1, 2, 256, 240, 240, 240, 240,,, -2, 5, 2, 3, 2, 2, 1, 2, 384, 240, 240, 240, 240,,, -2, 5, 2, 3, 2, 2, 2, 1, 128, 240, 240, 240, 240,,, -2, 5, 2, 3, 2, 2, 2, 1, 256, 240, 240, 240, 240,,, -2, 5, 2, 3, 2, 2, 2, 1, 384, 240, 240, 240, 240,,, -2, 5, 2, 3, 2, 2, 2, 2, 128, 240, 240, 240, 240,,, -2, 5, 2, 3, 2, 2, 2, 2, 256, 240, 240, 240, 240,,, -2, 5, 2, 3, 2, 2, 2, 2, 384, 240, 240, 240, 240,,, -2, 5, 2, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 5, 2, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 5, 2, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 5, 2, 4, 2, 2, 1, 1, 128, 240, 240, 240, 240,,, -2, 5, 2, 4, 2, 2, 1, 1, 256, 240, 240, 240, 240,,, -2, 5, 2, 4, 2, 2, 1, 1, 384, 240, 240, 240, 240,,, -2, 5, 2, 4, 2, 2, 1, 2, 128, 240, 240, 240, 240,,, -2, 5, 2, 4, 2, 2, 1, 2, 256, 240, 240, 240, 240,,, -2, 5, 2, 4, 2, 2, 1, 2, 384, 240, 240, 240, 240,,, -2, 5, 2, 4, 2, 2, 2, 1, 128, 240, 240, 240, 240,,, -2, 5, 2, 4, 2, 2, 2, 1, 256, 240, 240, 240, 240,,, -2, 5, 2, 4, 2, 2, 2, 1, 384, 240, 240, 240, 240,,, -2, 5, 2, 4, 2, 2, 2, 2, 128, 240, 240, 240, 240,,, -2, 5, 2, 4, 2, 2, 2, 2, 256, 240, 240, 240, 240,,, -2, 5, 2, 4, 2, 2, 2, 2, 384, 240, 240, 240, 240,,, -2, 5, 2, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 5, 2, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 5, 2, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 5, 2, 5, 2, 2, 1, 1, 128, 240, 240, 240, 240,,, -2, 5, 2, 5, 2, 2, 1, 1, 256, 240, 240, 240, 240,,, -2, 5, 2, 5, 2, 2, 1, 1, 384, 240, 240, 240, 240,,, -2, 5, 2, 5, 2, 2, 1, 2, 128, 240, 240, 240, 240,,, -2, 5, 2, 5, 2, 2, 1, 2, 256, 240, 240, 240, 240,,, -2, 5, 2, 5, 2, 2, 1, 2, 384, 240, 240, 240, 240,,, -2, 5, 2, 5, 2, 2, 2, 1, 128, 240, 240, 240, 240,,, -2, 5, 2, 5, 2, 2, 2, 1, 256, 240, 240, 240, 240,,, -2, 5, 2, 5, 2, 2, 2, 1, 384, 240, 240, 240, 240,,, -2, 5, 2, 5, 2, 2, 2, 2, 128, 240, 240, 240, 240,,, -2, 5, 2, 5, 2, 2, 2, 2, 256, 240, 240, 240, 240,,, -2, 5, 2, 5, 2, 2, 2, 2, 384, 240, 240, 240, 240,,, -2, 6, 1, 1, 1, 1, 1, 1, 128, 197, 197, 197,,,, -2, 6, 1, 1, 1, 1, 1, 1, 256, 197, 197, 197,,,, -2, 6, 1, 1, 1, 1, 1, 1, 384, 197, 197, 197,,,, -2, 6, 1, 1, 2, 2, 1, 1, 128, 197, 189, 170,,,, -2, 6, 1, 1, 2, 2, 1, 1, 256, 197, 189, 170,,,, -2, 6, 1, 1, 2, 2, 1, 1, 384, 197, 189, 170,,,, -2, 6, 1, 1, 2, 2, 1, 2, 128, 197, 189, 170,,,, -2, 6, 1, 1, 2, 2, 1, 2, 256, 197, 189, 170,,,, -2, 6, 1, 1, 2, 2, 1, 2, 384, 197, 189, 170,,,, -2, 6, 1, 1, 2, 2, 2, 1, 128, 197, 189, 170,,,, -2, 6, 1, 1, 2, 2, 2, 1, 256, 197, 189, 170,,,, -2, 6, 1, 1, 2, 2, 2, 1, 384, 197, 189, 170,,,, -2, 6, 1, 1, 2, 2, 2, 2, 128, 197, 189, 170,,,, -2, 6, 1, 1, 2, 2, 2, 2, 256, 197, 189, 170,,,, -2, 6, 1, 1, 2, 2, 2, 2, 384, 197, 189, 170,,,, -2, 6, 1, 2, 1, 1, 1, 1, 128, 240, 240, 240,,,, -2, 6, 1, 2, 1, 1, 1, 1, 256, 240, 240, 240,,,, -2, 6, 1, 2, 1, 1, 1, 1, 384, 240, 240, 240,,,, -2, 6, 1, 2, 2, 2, 1, 1, 128, 240, 240, 240,,,, -2, 6, 1, 2, 2, 2, 1, 1, 256, 240, 240, 240,,,, -2, 6, 1, 2, 2, 2, 1, 1, 384, 240, 240, 240,,,, -2, 6, 1, 2, 2, 2, 1, 2, 128, 240, 240, 240,,,, -2, 6, 1, 2, 2, 2, 1, 2, 256, 240, 240, 240,,,, -2, 6, 1, 2, 2, 2, 1, 2, 384, 240, 240, 240,,,, -2, 6, 1, 2, 2, 2, 2, 1, 128, 240, 240, 240,,,, -2, 6, 1, 2, 2, 2, 2, 1, 256, 240, 240, 240,,,, -2, 6, 1, 2, 2, 2, 2, 1, 384, 240, 240, 240,,,, -2, 6, 1, 2, 2, 2, 2, 2, 128, 240, 240, 240,,,, -2, 6, 1, 2, 2, 2, 2, 2, 256, 240, 240, 240,,,, -2, 6, 1, 2, 2, 2, 2, 2, 384, 240, 240, 240,,,, -2, 6, 1, 3, 1, 1, 1, 1, 128, 240, 240, 240,,,, -2, 6, 1, 3, 1, 1, 1, 1, 256, 240, 240, 240,,,, -2, 6, 1, 3, 1, 1, 1, 1, 384, 240, 240, 240,,,, -2, 6, 1, 3, 2, 2, 1, 1, 128, 240, 240, 240,,,, -2, 6, 1, 3, 2, 2, 1, 1, 256, 240, 240, 240,,,, -2, 6, 1, 3, 2, 2, 1, 1, 384, 240, 240, 240,,,, -2, 6, 1, 3, 2, 2, 1, 2, 128, 240, 240, 240,,,, -2, 6, 1, 3, 2, 2, 1, 2, 256, 240, 240, 240,,,, -2, 6, 1, 3, 2, 2, 1, 2, 384, 240, 240, 240,,,, -2, 6, 1, 3, 2, 2, 2, 1, 128, 240, 240, 240,,,, -2, 6, 1, 3, 2, 2, 2, 1, 256, 240, 240, 240,,,, -2, 6, 1, 3, 2, 2, 2, 1, 384, 240, 240, 240,,,, -2, 6, 1, 3, 2, 2, 2, 2, 128, 240, 240, 240,,,, -2, 6, 1, 3, 2, 2, 2, 2, 256, 240, 240, 240,,,, -2, 6, 1, 3, 2, 2, 2, 2, 384, 240, 240, 240,,,, -2, 6, 1, 4, 1, 1, 1, 1, 128, 240, 240, 240,,,, -2, 6, 1, 4, 1, 1, 1, 1, 256, 240, 240, 240,,,, -2, 6, 1, 4, 1, 1, 1, 1, 384, 240, 240, 240,,,, -2, 6, 1, 4, 2, 2, 1, 1, 128, 240, 240, 240,,,, -2, 6, 1, 4, 2, 2, 1, 1, 256, 240, 240, 240,,,, -2, 6, 1, 4, 2, 2, 1, 1, 384, 240, 240, 240,,,, -2, 6, 1, 4, 2, 2, 1, 2, 128, 240, 240, 240,,,, -2, 6, 1, 4, 2, 2, 1, 2, 256, 240, 240, 240,,,, -2, 6, 1, 4, 2, 2, 1, 2, 384, 240, 240, 240,,,, -2, 6, 1, 4, 2, 2, 2, 1, 128, 240, 240, 240,,,, -2, 6, 1, 4, 2, 2, 2, 1, 256, 240, 240, 240,,,, -2, 6, 1, 4, 2, 2, 2, 1, 384, 240, 240, 240,,,, -2, 6, 1, 4, 2, 2, 2, 2, 128, 240, 240, 240,,,, -2, 6, 1, 4, 2, 2, 2, 2, 256, 240, 240, 240,,,, -2, 6, 1, 4, 2, 2, 2, 2, 384, 240, 240, 240,,,, -2, 6, 1, 5, 1, 1, 1, 1, 128, 240, 240, 240,,,, -2, 6, 1, 5, 1, 1, 1, 1, 256, 240, 240, 240,,,, -2, 6, 1, 5, 1, 1, 1, 1, 384, 240, 240, 240,,,, -2, 6, 1, 5, 2, 2, 1, 1, 128, 240, 240, 240,,,, -2, 6, 1, 5, 2, 2, 1, 1, 256, 240, 240, 240,,,, -2, 6, 1, 5, 2, 2, 1, 1, 384, 240, 240, 240,,,, -2, 6, 1, 5, 2, 2, 1, 2, 128, 240, 240, 240,,,, -2, 6, 1, 5, 2, 2, 1, 2, 256, 240, 240, 240,,,, -2, 6, 1, 5, 2, 2, 1, 2, 384, 240, 240, 240,,,, -2, 6, 1, 5, 2, 2, 2, 1, 128, 240, 240, 240,,,, -2, 6, 1, 5, 2, 2, 2, 1, 256, 240, 240, 240,,,, -2, 6, 1, 5, 2, 2, 2, 1, 384, 240, 240, 240,,,, -2, 6, 1, 5, 2, 2, 2, 2, 128, 240, 240, 240,,,, -2, 6, 1, 5, 2, 2, 2, 2, 256, 240, 240, 240,,,, -2, 6, 1, 5, 2, 2, 2, 2, 384, 240, 240, 240,,,, -2, 6, 1, 6, 1, 1, 1, 1, 128, 240, 240, 240,,,, -2, 6, 1, 6, 1, 1, 1, 1, 256, 240, 240, 240,,,, -2, 6, 1, 6, 1, 1, 1, 1, 384, 240, 240, 240,,,, -2, 6, 1, 6, 2, 2, 1, 1, 128, 240, 240, 240,,,, -2, 6, 1, 6, 2, 2, 1, 1, 256, 240, 240, 240,,,, -2, 6, 1, 6, 2, 2, 1, 1, 384, 240, 240, 240,,,, -2, 6, 1, 6, 2, 2, 1, 2, 128, 240, 240, 240,,,, -2, 6, 1, 6, 2, 2, 1, 2, 256, 240, 240, 240,,,, -2, 6, 1, 6, 2, 2, 1, 2, 384, 240, 240, 240,,,, -2, 6, 1, 6, 2, 2, 2, 1, 128, 240, 240, 240,,,, -2, 6, 1, 6, 2, 2, 2, 1, 256, 240, 240, 240,,,, -2, 6, 1, 6, 2, 2, 2, 1, 384, 240, 240, 240,,,, -2, 6, 1, 6, 2, 2, 2, 2, 128, 240, 240, 240,,,, -2, 6, 1, 6, 2, 2, 2, 2, 256, 240, 240, 240,,,, -2, 6, 1, 6, 2, 2, 2, 2, 384, 240, 240, 240,,,, -2, 6, 2, 1, 1, 1, 1, 1, 128, 197, 197, 197,,,, -2, 6, 2, 1, 1, 1, 1, 1, 256, 197, 197, 197,,,, -2, 6, 2, 1, 1, 1, 1, 1, 384, 197, 197, 197,,,, -2, 6, 2, 1, 2, 2, 1, 1, 128, 197, 189, 170,,,, -2, 6, 2, 1, 2, 2, 1, 1, 256, 197, 189, 170,,,, -2, 6, 2, 1, 2, 2, 1, 1, 384, 197, 189, 170,,,, -2, 6, 2, 1, 2, 2, 1, 2, 128, 197, 189, 170,,,, -2, 6, 2, 1, 2, 2, 1, 2, 256, 197, 189, 170,,,, -2, 6, 2, 1, 2, 2, 1, 2, 384, 197, 189, 170,,,, -2, 6, 2, 1, 2, 2, 2, 1, 128, 197, 189, 170,,,, -2, 6, 2, 1, 2, 2, 2, 1, 256, 197, 189, 170,,,, -2, 6, 2, 1, 2, 2, 2, 1, 384, 197, 189, 170,,,, -2, 6, 2, 1, 2, 2, 2, 2, 128, 197, 189, 170,,,, -2, 6, 2, 1, 2, 2, 2, 2, 256, 197, 189, 170,,,, -2, 6, 2, 1, 2, 2, 2, 2, 384, 197, 189, 170,,,, -2, 6, 2, 2, 1, 1, 1, 1, 128, 240, 240, 240,,,, -2, 6, 2, 2, 1, 1, 1, 1, 256, 240, 240, 240,,,, -2, 6, 2, 2, 1, 1, 1, 1, 384, 240, 240, 240,,,, -2, 6, 2, 2, 2, 2, 1, 1, 128, 240, 240, 240,,,, -2, 6, 2, 2, 2, 2, 1, 1, 256, 240, 240, 240,,,, -2, 6, 2, 2, 2, 2, 1, 1, 384, 240, 240, 240,,,, -2, 6, 2, 2, 2, 2, 1, 2, 128, 240, 240, 240,,,, -2, 6, 2, 2, 2, 2, 1, 2, 256, 240, 240, 240,,,, -2, 6, 2, 2, 2, 2, 1, 2, 384, 240, 240, 240,,,, -2, 6, 2, 2, 2, 2, 2, 1, 128, 240, 240, 240,,,, -2, 6, 2, 2, 2, 2, 2, 1, 256, 240, 240, 240,,,, -2, 6, 2, 2, 2, 2, 2, 1, 384, 240, 240, 240,,,, -2, 6, 2, 2, 2, 2, 2, 2, 128, 240, 240, 240,,,, -2, 6, 2, 2, 2, 2, 2, 2, 256, 240, 240, 240,,,, -2, 6, 2, 2, 2, 2, 2, 2, 384, 240, 240, 240,,,, -2, 6, 2, 3, 1, 1, 1, 1, 128, 240, 240, 240,,,, -2, 6, 2, 3, 1, 1, 1, 1, 256, 240, 240, 240,,,, -2, 6, 2, 3, 1, 1, 1, 1, 384, 240, 240, 240,,,, -2, 6, 2, 3, 2, 2, 1, 1, 128, 240, 240, 240,,,, -2, 6, 2, 3, 2, 2, 1, 1, 256, 240, 240, 240,,,, -2, 6, 2, 3, 2, 2, 1, 1, 384, 240, 240, 240,,,, -2, 6, 2, 3, 2, 2, 1, 2, 128, 240, 240, 240,,,, -2, 6, 2, 3, 2, 2, 1, 2, 256, 240, 240, 240,,,, -2, 6, 2, 3, 2, 2, 1, 2, 384, 240, 240, 240,,,, -2, 6, 2, 3, 2, 2, 2, 1, 128, 240, 240, 240,,,, -2, 6, 2, 3, 2, 2, 2, 1, 256, 240, 240, 240,,,, -2, 6, 2, 3, 2, 2, 2, 1, 384, 240, 240, 240,,,, -2, 6, 2, 3, 2, 2, 2, 2, 128, 240, 240, 240,,,, -2, 6, 2, 3, 2, 2, 2, 2, 256, 240, 240, 240,,,, -2, 6, 2, 3, 2, 2, 2, 2, 384, 240, 240, 240,,,, -2, 6, 2, 4, 1, 1, 1, 1, 128, 240, 240, 240,,,, -2, 6, 2, 4, 1, 1, 1, 1, 256, 240, 240, 240,,,, -2, 6, 2, 4, 1, 1, 1, 1, 384, 240, 240, 240,,,, -2, 6, 2, 4, 2, 2, 1, 1, 128, 240, 240, 240,,,, -2, 6, 2, 4, 2, 2, 1, 1, 256, 240, 240, 240,,,, -2, 6, 2, 4, 2, 2, 1, 1, 384, 240, 240, 240,,,, -2, 6, 2, 4, 2, 2, 1, 2, 128, 240, 240, 240,,,, -2, 6, 2, 4, 2, 2, 1, 2, 256, 240, 240, 240,,,, -2, 6, 2, 4, 2, 2, 1, 2, 384, 240, 240, 240,,,, -2, 6, 2, 4, 2, 2, 2, 1, 128, 240, 240, 240,,,, -2, 6, 2, 4, 2, 2, 2, 1, 256, 240, 240, 240,,,, -2, 6, 2, 4, 2, 2, 2, 1, 384, 240, 240, 240,,,, -2, 6, 2, 4, 2, 2, 2, 2, 128, 240, 240, 240,,,, -2, 6, 2, 4, 2, 2, 2, 2, 256, 240, 240, 240,,,, -2, 6, 2, 4, 2, 2, 2, 2, 384, 240, 240, 240,,,, -2, 6, 2, 5, 1, 1, 1, 1, 128, 240, 240, 240,,,, -2, 6, 2, 5, 1, 1, 1, 1, 256, 240, 240, 240,,,, -2, 6, 2, 5, 1, 1, 1, 1, 384, 240, 240, 240,,,, -2, 6, 2, 5, 2, 2, 1, 1, 128, 240, 240, 240,,,, -2, 6, 2, 5, 2, 2, 1, 1, 256, 240, 240, 240,,,, -2, 6, 2, 5, 2, 2, 1, 1, 384, 240, 240, 240,,,, -2, 6, 2, 5, 2, 2, 1, 2, 128, 240, 240, 240,,,, -2, 6, 2, 5, 2, 2, 1, 2, 256, 240, 240, 240,,,, -2, 6, 2, 5, 2, 2, 1, 2, 384, 240, 240, 240,,,, -2, 6, 2, 5, 2, 2, 2, 1, 128, 240, 240, 240,,,, -2, 6, 2, 5, 2, 2, 2, 1, 256, 240, 240, 240,,,, -2, 6, 2, 5, 2, 2, 2, 1, 384, 240, 240, 240,,,, -2, 6, 2, 5, 2, 2, 2, 2, 128, 240, 240, 240,,,, -2, 6, 2, 5, 2, 2, 2, 2, 256, 240, 240, 240,,,, -2, 6, 2, 5, 2, 2, 2, 2, 384, 240, 240, 240,,,, -2, 6, 2, 6, 1, 1, 1, 1, 128, 240, 240, 240,,,, -2, 6, 2, 6, 1, 1, 1, 1, 256, 240, 240, 240,,,, -2, 6, 2, 6, 1, 1, 1, 1, 384, 240, 240, 240,,,, -2, 6, 2, 6, 2, 2, 1, 1, 128, 240, 240, 240,,,, -2, 6, 2, 6, 2, 2, 1, 1, 256, 240, 240, 240,,,, -2, 6, 2, 6, 2, 2, 1, 1, 384, 240, 240, 240,,,, -2, 6, 2, 6, 2, 2, 1, 2, 128, 240, 240, 240,,,, -2, 6, 2, 6, 2, 2, 1, 2, 256, 240, 240, 240,,,, -2, 6, 2, 6, 2, 2, 1, 2, 384, 240, 240, 240,,,, -2, 6, 2, 6, 2, 2, 2, 1, 128, 240, 240, 240,,,, -2, 6, 2, 6, 2, 2, 2, 1, 256, 240, 240, 240,,,, -2, 6, 2, 6, 2, 2, 2, 1, 384, 240, 240, 240,,,, -2, 6, 2, 6, 2, 2, 2, 2, 128, 240, 240, 240,,,, -2, 6, 2, 6, 2, 2, 2, 2, 256, 240, 240, 240,,,, -2, 6, 2, 6, 2, 2, 2, 2, 384, 240, 240, 240,,,, -2, 7, 1, 1, 1, 1, 1, 1, 128, 198, 198, 198,,,, -2, 7, 1, 1, 1, 1, 1, 1, 256, 198, 198, 198,,,, -2, 7, 1, 1, 1, 1, 1, 1, 384, 198, 198, 198,,,, -2, 7, 1, 1, 2, 2, 1, 1, 128, 198, 187, 165,,,, -2, 7, 1, 1, 2, 2, 1, 1, 256, 198, 187, 165,,,, -2, 7, 1, 1, 2, 2, 1, 1, 384, 198, 187, 165,,,, -2, 7, 1, 1, 2, 2, 1, 2, 128, 198, 187, 165,,,, -2, 7, 1, 1, 2, 2, 1, 2, 256, 198, 187, 165,,,, -2, 7, 1, 1, 2, 2, 1, 2, 384, 198, 187, 165,,,, -2, 7, 1, 1, 2, 2, 2, 1, 128, 198, 187, 165,,,, -2, 7, 1, 1, 2, 2, 2, 1, 256, 198, 187, 165,,,, -2, 7, 1, 1, 2, 2, 2, 1, 384, 198, 187, 165,,,, -2, 7, 1, 1, 2, 2, 2, 2, 128, 198, 187, 165,,,, -2, 7, 1, 1, 2, 2, 2, 2, 256, 198, 187, 165,,,, -2, 7, 1, 1, 2, 2, 2, 2, 384, 198, 187, 165,,,, -2, 7, 1, 2, 1, 1, 1, 1, 128, 240, 240, 240,,,, -2, 7, 1, 2, 1, 1, 1, 1, 256, 240, 240, 240,,,, -2, 7, 1, 2, 1, 1, 1, 1, 384, 240, 240, 240,,,, -2, 7, 1, 2, 2, 2, 1, 1, 128, 240, 240, 240,,,, -2, 7, 1, 2, 2, 2, 1, 1, 256, 240, 240, 240,,,, -2, 7, 1, 2, 2, 2, 1, 1, 384, 240, 240, 240,,,, -2, 7, 1, 2, 2, 2, 1, 2, 128, 240, 240, 240,,,, -2, 7, 1, 2, 2, 2, 1, 2, 256, 240, 240, 240,,,, -2, 7, 1, 2, 2, 2, 1, 2, 384, 240, 240, 240,,,, -2, 7, 1, 2, 2, 2, 2, 1, 128, 240, 240, 240,,,, -2, 7, 1, 2, 2, 2, 2, 1, 256, 240, 240, 240,,,, -2, 7, 1, 2, 2, 2, 2, 1, 384, 240, 240, 240,,,, -2, 7, 1, 2, 2, 2, 2, 2, 128, 240, 240, 240,,,, -2, 7, 1, 2, 2, 2, 2, 2, 256, 240, 240, 240,,,, -2, 7, 1, 2, 2, 2, 2, 2, 384, 240, 240, 240,,,, -2, 7, 1, 3, 1, 1, 1, 1, 128, 240, 240, 240,,,, -2, 7, 1, 3, 1, 1, 1, 1, 256, 240, 240, 240,,,, -2, 7, 1, 3, 1, 1, 1, 1, 384, 240, 240, 240,,,, -2, 7, 1, 3, 2, 2, 1, 1, 128, 240, 240, 240,,,, -2, 7, 1, 3, 2, 2, 1, 1, 256, 240, 240, 240,,,, -2, 7, 1, 3, 2, 2, 1, 1, 384, 240, 240, 240,,,, -2, 7, 1, 3, 2, 2, 1, 2, 128, 240, 240, 240,,,, -2, 7, 1, 3, 2, 2, 1, 2, 256, 240, 240, 240,,,, -2, 7, 1, 3, 2, 2, 1, 2, 384, 240, 240, 240,,,, -2, 7, 1, 3, 2, 2, 2, 1, 128, 240, 240, 240,,,, -2, 7, 1, 3, 2, 2, 2, 1, 256, 240, 240, 240,,,, -2, 7, 1, 3, 2, 2, 2, 1, 384, 240, 240, 240,,,, -2, 7, 1, 3, 2, 2, 2, 2, 128, 240, 240, 240,,,, -2, 7, 1, 3, 2, 2, 2, 2, 256, 240, 240, 240,,,, -2, 7, 1, 3, 2, 2, 2, 2, 384, 240, 240, 240,,,, -2, 7, 1, 4, 1, 1, 1, 1, 128, 240, 240, 240,,,, -2, 7, 1, 4, 1, 1, 1, 1, 256, 240, 240, 240,,,, -2, 7, 1, 4, 1, 1, 1, 1, 384, 240, 240, 240,,,, -2, 7, 1, 4, 2, 2, 1, 1, 128, 240, 240, 240,,,, -2, 7, 1, 4, 2, 2, 1, 1, 256, 240, 240, 240,,,, -2, 7, 1, 4, 2, 2, 1, 1, 384, 240, 240, 240,,,, -2, 7, 1, 4, 2, 2, 1, 2, 128, 240, 240, 240,,,, -2, 7, 1, 4, 2, 2, 1, 2, 256, 240, 240, 240,,,, -2, 7, 1, 4, 2, 2, 1, 2, 384, 240, 240, 240,,,, -2, 7, 1, 4, 2, 2, 2, 1, 128, 240, 240, 240,,,, -2, 7, 1, 4, 2, 2, 2, 1, 256, 240, 240, 240,,,, -2, 7, 1, 4, 2, 2, 2, 1, 384, 240, 240, 240,,,, -2, 7, 1, 4, 2, 2, 2, 2, 128, 240, 240, 240,,,, -2, 7, 1, 4, 2, 2, 2, 2, 256, 240, 240, 240,,,, -2, 7, 1, 4, 2, 2, 2, 2, 384, 240, 240, 240,,,, -2, 7, 1, 5, 1, 1, 1, 1, 128, 240, 240, 240,,,, -2, 7, 1, 5, 1, 1, 1, 1, 256, 240, 240, 240,,,, -2, 7, 1, 5, 1, 1, 1, 1, 384, 240, 240, 240,,,, -2, 7, 1, 5, 2, 2, 1, 1, 128, 240, 240, 240,,,, -2, 7, 1, 5, 2, 2, 1, 1, 256, 240, 240, 240,,,, -2, 7, 1, 5, 2, 2, 1, 1, 384, 240, 240, 240,,,, -2, 7, 1, 5, 2, 2, 1, 2, 128, 240, 240, 240,,,, -2, 7, 1, 5, 2, 2, 1, 2, 256, 240, 240, 240,,,, -2, 7, 1, 5, 2, 2, 1, 2, 384, 240, 240, 240,,,, -2, 7, 1, 5, 2, 2, 2, 1, 128, 240, 240, 240,,,, -2, 7, 1, 5, 2, 2, 2, 1, 256, 240, 240, 240,,,, -2, 7, 1, 5, 2, 2, 2, 1, 384, 240, 240, 240,,,, -2, 7, 1, 5, 2, 2, 2, 2, 128, 240, 240, 240,,,, -2, 7, 1, 5, 2, 2, 2, 2, 256, 240, 240, 240,,,, -2, 7, 1, 5, 2, 2, 2, 2, 384, 240, 240, 240,,,, -2, 7, 1, 6, 1, 1, 1, 1, 128, 240, 240, 240,,,, -2, 7, 1, 6, 1, 1, 1, 1, 256, 240, 240, 240,,,, -2, 7, 1, 6, 1, 1, 1, 1, 384, 240, 240, 240,,,, -2, 7, 1, 6, 2, 2, 1, 1, 128, 240, 240, 240,,,, -2, 7, 1, 6, 2, 2, 1, 1, 256, 240, 240, 240,,,, -2, 7, 1, 6, 2, 2, 1, 1, 384, 240, 240, 240,,,, -2, 7, 1, 6, 2, 2, 1, 2, 128, 240, 240, 240,,,, -2, 7, 1, 6, 2, 2, 1, 2, 256, 240, 240, 240,,,, -2, 7, 1, 6, 2, 2, 1, 2, 384, 240, 240, 240,,,, -2, 7, 1, 6, 2, 2, 2, 1, 128, 240, 240, 240,,,, -2, 7, 1, 6, 2, 2, 2, 1, 256, 240, 240, 240,,,, -2, 7, 1, 6, 2, 2, 2, 1, 384, 240, 240, 240,,,, -2, 7, 1, 6, 2, 2, 2, 2, 128, 240, 240, 240,,,, -2, 7, 1, 6, 2, 2, 2, 2, 256, 240, 240, 240,,,, -2, 7, 1, 6, 2, 2, 2, 2, 384, 240, 240, 240,,,, -2, 7, 1, 7, 1, 1, 1, 1, 128, 240, 240, 240,,,, -2, 7, 1, 7, 1, 1, 1, 1, 256, 240, 240, 240,,,, -2, 7, 1, 7, 1, 1, 1, 1, 384, 240, 240, 240,,,, -2, 7, 1, 7, 2, 2, 1, 1, 128, 240, 240, 240,,,, -2, 7, 1, 7, 2, 2, 1, 1, 256, 240, 240, 240,,,, -2, 7, 1, 7, 2, 2, 1, 1, 384, 240, 240, 240,,,, -2, 7, 1, 7, 2, 2, 1, 2, 128, 240, 240, 240,,,, -2, 7, 1, 7, 2, 2, 1, 2, 256, 240, 240, 240,,,, -2, 7, 1, 7, 2, 2, 1, 2, 384, 240, 240, 240,,,, -2, 7, 1, 7, 2, 2, 2, 1, 128, 240, 240, 240,,,, -2, 7, 1, 7, 2, 2, 2, 1, 256, 240, 240, 240,,,, -2, 7, 1, 7, 2, 2, 2, 1, 384, 240, 240, 240,,,, -2, 7, 1, 7, 2, 2, 2, 2, 128, 240, 240, 240,,,, -2, 7, 1, 7, 2, 2, 2, 2, 256, 240, 240, 240,,,, -2, 7, 1, 7, 2, 2, 2, 2, 384, 240, 240, 240,,,, -2, 7, 2, 1, 1, 1, 1, 1, 128, 198, 198, 198,,,, -2, 7, 2, 1, 1, 1, 1, 1, 256, 198, 198, 198,,,, -2, 7, 2, 1, 1, 1, 1, 1, 384, 198, 198, 198,,,, -2, 7, 2, 1, 2, 2, 1, 1, 128, 198, 187, 165,,,, -2, 7, 2, 1, 2, 2, 1, 1, 256, 198, 187, 165,,,, -2, 7, 2, 1, 2, 2, 1, 1, 384, 198, 187, 165,,,, -2, 7, 2, 1, 2, 2, 1, 2, 128, 198, 187, 165,,,, -2, 7, 2, 1, 2, 2, 1, 2, 256, 198, 187, 165,,,, -2, 7, 2, 1, 2, 2, 1, 2, 384, 198, 187, 165,,,, -2, 7, 2, 1, 2, 2, 2, 1, 128, 198, 187, 165,,,, -2, 7, 2, 1, 2, 2, 2, 1, 256, 198, 187, 165,,,, -2, 7, 2, 1, 2, 2, 2, 1, 384, 198, 187, 165,,,, -2, 7, 2, 1, 2, 2, 2, 2, 128, 198, 187, 165,,,, -2, 7, 2, 1, 2, 2, 2, 2, 256, 198, 187, 165,,,, -2, 7, 2, 1, 2, 2, 2, 2, 384, 198, 187, 165,,,, -2, 7, 2, 2, 1, 1, 1, 1, 128, 240, 240, 240,,,, -2, 7, 2, 2, 1, 1, 1, 1, 256, 240, 240, 240,,,, -2, 7, 2, 2, 1, 1, 1, 1, 384, 240, 240, 240,,,, -2, 7, 2, 2, 2, 2, 1, 1, 128, 240, 240, 240,,,, -2, 7, 2, 2, 2, 2, 1, 1, 256, 240, 240, 240,,,, -2, 7, 2, 2, 2, 2, 1, 1, 384, 240, 240, 240,,,, -2, 7, 2, 2, 2, 2, 1, 2, 128, 240, 240, 240,,,, -2, 7, 2, 2, 2, 2, 1, 2, 256, 240, 240, 240,,,, -2, 7, 2, 2, 2, 2, 1, 2, 384, 240, 240, 240,,,, -2, 7, 2, 2, 2, 2, 2, 1, 128, 240, 240, 240,,,, -2, 7, 2, 2, 2, 2, 2, 1, 256, 240, 240, 240,,,, -2, 7, 2, 2, 2, 2, 2, 1, 384, 240, 240, 240,,,, -2, 7, 2, 2, 2, 2, 2, 2, 128, 240, 240, 240,,,, -2, 7, 2, 2, 2, 2, 2, 2, 256, 240, 240, 240,,,, -2, 7, 2, 2, 2, 2, 2, 2, 384, 240, 240, 240,,,, -2, 7, 2, 3, 1, 1, 1, 1, 128, 240, 240, 240,,,, -2, 7, 2, 3, 1, 1, 1, 1, 256, 240, 240, 240,,,, -2, 7, 2, 3, 1, 1, 1, 1, 384, 240, 240, 240,,,, -2, 7, 2, 3, 2, 2, 1, 1, 128, 240, 240, 240,,,, -2, 7, 2, 3, 2, 2, 1, 1, 256, 240, 240, 240,,,, -2, 7, 2, 3, 2, 2, 1, 1, 384, 240, 240, 240,,,, -2, 7, 2, 3, 2, 2, 1, 2, 128, 240, 240, 240,,,, -2, 7, 2, 3, 2, 2, 1, 2, 256, 240, 240, 240,,,, -2, 7, 2, 3, 2, 2, 1, 2, 384, 240, 240, 240,,,, -2, 7, 2, 3, 2, 2, 2, 1, 128, 240, 240, 240,,,, -2, 7, 2, 3, 2, 2, 2, 1, 256, 240, 240, 240,,,, -2, 7, 2, 3, 2, 2, 2, 1, 384, 240, 240, 240,,,, -2, 7, 2, 3, 2, 2, 2, 2, 128, 240, 240, 240,,,, -2, 7, 2, 3, 2, 2, 2, 2, 256, 240, 240, 240,,,, -2, 7, 2, 3, 2, 2, 2, 2, 384, 240, 240, 240,,,, -2, 7, 2, 4, 1, 1, 1, 1, 128, 240, 240, 240,,,, -2, 7, 2, 4, 1, 1, 1, 1, 256, 240, 240, 240,,,, -2, 7, 2, 4, 1, 1, 1, 1, 384, 240, 240, 240,,,, -2, 7, 2, 4, 2, 2, 1, 1, 128, 240, 240, 240,,,, -2, 7, 2, 4, 2, 2, 1, 1, 256, 240, 240, 240,,,, -2, 7, 2, 4, 2, 2, 1, 1, 384, 240, 240, 240,,,, -2, 7, 2, 4, 2, 2, 1, 2, 128, 240, 240, 240,,,, -2, 7, 2, 4, 2, 2, 1, 2, 256, 240, 240, 240,,,, -2, 7, 2, 4, 2, 2, 1, 2, 384, 240, 240, 240,,,, -2, 7, 2, 4, 2, 2, 2, 1, 128, 240, 240, 240,,,, -2, 7, 2, 4, 2, 2, 2, 1, 256, 240, 240, 240,,,, -2, 7, 2, 4, 2, 2, 2, 1, 384, 240, 240, 240,,,, -2, 7, 2, 4, 2, 2, 2, 2, 128, 240, 240, 240,,,, -2, 7, 2, 4, 2, 2, 2, 2, 256, 240, 240, 240,,,, -2, 7, 2, 4, 2, 2, 2, 2, 384, 240, 240, 240,,,, -2, 7, 2, 5, 1, 1, 1, 1, 128, 240, 240, 240,,,, -2, 7, 2, 5, 1, 1, 1, 1, 256, 240, 240, 240,,,, -2, 7, 2, 5, 1, 1, 1, 1, 384, 240, 240, 240,,,, -2, 7, 2, 5, 2, 2, 1, 1, 128, 240, 240, 240,,,, -2, 7, 2, 5, 2, 2, 1, 1, 256, 240, 240, 240,,,, -2, 7, 2, 5, 2, 2, 1, 1, 384, 240, 240, 240,,,, -2, 7, 2, 5, 2, 2, 1, 2, 128, 240, 240, 240,,,, -2, 7, 2, 5, 2, 2, 1, 2, 256, 240, 240, 240,,,, -2, 7, 2, 5, 2, 2, 1, 2, 384, 240, 240, 240,,,, -2, 7, 2, 5, 2, 2, 2, 1, 128, 240, 240, 240,,,, -2, 7, 2, 5, 2, 2, 2, 1, 256, 240, 240, 240,,,, -2, 7, 2, 5, 2, 2, 2, 1, 384, 240, 240, 240,,,, -2, 7, 2, 5, 2, 2, 2, 2, 128, 240, 240, 240,,,, -2, 7, 2, 5, 2, 2, 2, 2, 256, 240, 240, 240,,,, -2, 7, 2, 5, 2, 2, 2, 2, 384, 240, 240, 240,,,, -2, 7, 2, 6, 1, 1, 1, 1, 128, 240, 240, 240,,,, -2, 7, 2, 6, 1, 1, 1, 1, 256, 240, 240, 240,,,, -2, 7, 2, 6, 1, 1, 1, 1, 384, 240, 240, 240,,,, -2, 7, 2, 6, 2, 2, 1, 1, 128, 240, 240, 240,,,, -2, 7, 2, 6, 2, 2, 1, 1, 256, 240, 240, 240,,,, -2, 7, 2, 6, 2, 2, 1, 1, 384, 240, 240, 240,,,, -2, 7, 2, 6, 2, 2, 1, 2, 128, 240, 240, 240,,,, -2, 7, 2, 6, 2, 2, 1, 2, 256, 240, 240, 240,,,, -2, 7, 2, 6, 2, 2, 1, 2, 384, 240, 240, 240,,,, -2, 7, 2, 6, 2, 2, 2, 1, 128, 240, 240, 240,,,, -2, 7, 2, 6, 2, 2, 2, 1, 256, 240, 240, 240,,,, -2, 7, 2, 6, 2, 2, 2, 1, 384, 240, 240, 240,,,, -2, 7, 2, 6, 2, 2, 2, 2, 128, 240, 240, 240,,,, -2, 7, 2, 6, 2, 2, 2, 2, 256, 240, 240, 240,,,, -2, 7, 2, 6, 2, 2, 2, 2, 384, 240, 240, 240,,,, -2, 7, 2, 7, 1, 1, 1, 1, 128, 240, 240, 240,,,, -2, 7, 2, 7, 1, 1, 1, 1, 256, 240, 240, 240,,,, -2, 7, 2, 7, 1, 1, 1, 1, 384, 240, 240, 240,,,, -2, 7, 2, 7, 2, 2, 1, 1, 128, 240, 240, 240,,,, -2, 7, 2, 7, 2, 2, 1, 1, 256, 240, 240, 240,,,, -2, 7, 2, 7, 2, 2, 1, 1, 384, 240, 240, 240,,,, -2, 7, 2, 7, 2, 2, 1, 2, 128, 240, 240, 240,,,, -2, 7, 2, 7, 2, 2, 1, 2, 256, 240, 240, 240,,,, -2, 7, 2, 7, 2, 2, 1, 2, 384, 240, 240, 240,,,, -2, 7, 2, 7, 2, 2, 2, 1, 128, 240, 240, 240,,,, -2, 7, 2, 7, 2, 2, 2, 1, 256, 240, 240, 240,,,, -2, 7, 2, 7, 2, 2, 2, 1, 384, 240, 240, 240,,,, -2, 7, 2, 7, 2, 2, 2, 2, 128, 240, 240, 240,,,, -2, 7, 2, 7, 2, 2, 2, 2, 256, 240, 240, 240,,,, -2, 7, 2, 7, 2, 2, 2, 2, 384, 240, 240, 240,,,, -3, 1, 1, 1, 1, 1, 1, 1, 128, 128, 128, 128, 128, 128, 85, 42 -3, 1, 1, 1, 1, 1, 1, 1, 256, 128, 128, 128, 128, 128, 85, 42 -3, 1, 1, 1, 1, 1, 1, 1, 384, 128, 128, 128, 128, 128, 85, 42 -3, 1, 2, 1, 1, 1, 1, 1, 128, 128, 128, 128, 128, 128, 85, 42 -3, 1, 2, 1, 1, 1, 1, 1, 256, 128, 128, 128, 128, 128, 85, 42 -3, 1, 2, 1, 1, 1, 1, 1, 384, 128, 128, 128, 128, 128, 85, 42 -3, 1, 3, 1, 1, 1, 1, 1, 128, 128, 128, 128, 128, 128, 85, 42 -3, 1, 3, 1, 1, 1, 1, 1, 256, 128, 128, 128, 128, 128, 85, 42 -3, 1, 3, 1, 1, 1, 1, 1, 384, 128, 128, 128, 128, 128, 85, 42 -3, 2, 1, 1, 1, 1, 1, 1, 128, 129, 129, 129, 129,,, -3, 2, 1, 1, 1, 1, 1, 1, 256, 129, 129, 129, 129,,, -3, 2, 1, 1, 1, 1, 1, 1, 384, 129, 129, 129, 129,,, -3, 2, 1, 1, 2, 2, 1, 1, 128, 129, 129, 129, 119,,, -3, 2, 1, 1, 2, 2, 1, 1, 256, 129, 129, 129, 119,,, -3, 2, 1, 1, 2, 2, 1, 1, 384, 129, 129, 129, 119,,, -3, 2, 1, 1, 2, 2, 1, 2, 128, 129, 129, 129, 119,,, -3, 2, 1, 1, 2, 2, 1, 2, 256, 129, 129, 129, 119,,, -3, 2, 1, 1, 2, 2, 1, 2, 384, 129, 129, 129, 119,,, -3, 2, 1, 1, 2, 2, 2, 1, 128, 129, 129, 129, 119,,, -3, 2, 1, 1, 2, 2, 2, 1, 256, 129, 129, 129, 119,,, -3, 2, 1, 1, 2, 2, 2, 1, 384, 129, 129, 129, 119,,, -3, 2, 1, 1, 2, 2, 2, 2, 128, 129, 129, 129, 119,,, -3, 2, 1, 1, 2, 2, 2, 2, 256, 129, 129, 129, 119,,, -3, 2, 1, 1, 2, 2, 2, 2, 384, 129, 129, 129, 119,,, -3, 2, 1, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 2, 1, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 2, 1, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 2, 1, 2, 2, 2, 1, 1, 128, 240, 240, 240, 237,,, -3, 2, 1, 2, 2, 2, 1, 1, 256, 240, 240, 240, 237,,, -3, 2, 1, 2, 2, 2, 1, 1, 384, 240, 240, 240, 237,,, -3, 2, 1, 2, 2, 2, 1, 2, 128, 240, 240, 240, 237,,, -3, 2, 1, 2, 2, 2, 1, 2, 256, 240, 240, 240, 237,,, -3, 2, 1, 2, 2, 2, 1, 2, 384, 240, 240, 240, 237,,, -3, 2, 1, 2, 2, 2, 2, 1, 128, 240, 240, 240, 237,,, -3, 2, 1, 2, 2, 2, 2, 1, 256, 240, 240, 240, 237,,, -3, 2, 1, 2, 2, 2, 2, 1, 384, 240, 240, 240, 237,,, -3, 2, 1, 2, 2, 2, 2, 2, 128, 240, 240, 240, 237,,, -3, 2, 1, 2, 2, 2, 2, 2, 256, 240, 240, 240, 237,,, -3, 2, 1, 2, 2, 2, 2, 2, 384, 240, 240, 240, 237,,, -3, 2, 2, 1, 1, 1, 1, 1, 128, 129, 129, 129, 129,,, -3, 2, 2, 1, 1, 1, 1, 1, 256, 129, 129, 129, 129,,, -3, 2, 2, 1, 1, 1, 1, 1, 384, 129, 129, 129, 129,,, -3, 2, 2, 1, 2, 2, 1, 1, 128, 129, 129, 129, 119,,, -3, 2, 2, 1, 2, 2, 1, 1, 256, 129, 129, 129, 119,,, -3, 2, 2, 1, 2, 2, 1, 1, 384, 129, 129, 129, 119,,, -3, 2, 2, 1, 2, 2, 1, 2, 128, 129, 129, 129, 119,,, -3, 2, 2, 1, 2, 2, 1, 2, 256, 129, 129, 129, 119,,, -3, 2, 2, 1, 2, 2, 1, 2, 384, 129, 129, 129, 119,,, -3, 2, 2, 1, 2, 2, 2, 1, 128, 129, 129, 129, 119,,, -3, 2, 2, 1, 2, 2, 2, 1, 256, 129, 129, 129, 119,,, -3, 2, 2, 1, 2, 2, 2, 1, 384, 129, 129, 129, 119,,, -3, 2, 2, 1, 2, 2, 2, 2, 128, 129, 129, 129, 119,,, -3, 2, 2, 1, 2, 2, 2, 2, 256, 129, 129, 129, 119,,, -3, 2, 2, 1, 2, 2, 2, 2, 384, 129, 129, 129, 119,,, -3, 2, 2, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 2, 2, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 2, 2, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 2, 2, 2, 2, 2, 1, 1, 128, 240, 240, 240, 237,,, -3, 2, 2, 2, 2, 2, 1, 1, 256, 240, 240, 240, 237,,, -3, 2, 2, 2, 2, 2, 1, 1, 384, 240, 240, 240, 237,,, -3, 2, 2, 2, 2, 2, 1, 2, 128, 240, 240, 240, 237,,, -3, 2, 2, 2, 2, 2, 1, 2, 256, 240, 240, 240, 237,,, -3, 2, 2, 2, 2, 2, 1, 2, 384, 240, 240, 240, 237,,, -3, 2, 2, 2, 2, 2, 2, 1, 128, 240, 240, 240, 237,,, -3, 2, 2, 2, 2, 2, 2, 1, 256, 240, 240, 240, 237,,, -3, 2, 2, 2, 2, 2, 2, 1, 384, 240, 240, 240, 237,,, -3, 2, 2, 2, 2, 2, 2, 2, 128, 240, 240, 240, 237,,, -3, 2, 2, 2, 2, 2, 2, 2, 256, 240, 240, 240, 237,,, -3, 2, 2, 2, 2, 2, 2, 2, 384, 240, 240, 240, 237,,, -3, 2, 3, 1, 1, 1, 1, 1, 128, 129, 129, 129, 129,,, -3, 2, 3, 1, 1, 1, 1, 1, 256, 129, 129, 129, 129,,, -3, 2, 3, 1, 1, 1, 1, 1, 384, 129, 129, 129, 129,,, -3, 2, 3, 1, 2, 2, 1, 1, 128, 129, 129, 129, 119,,, -3, 2, 3, 1, 2, 2, 1, 1, 256, 129, 129, 129, 119,,, -3, 2, 3, 1, 2, 2, 1, 1, 384, 129, 129, 129, 119,,, -3, 2, 3, 1, 2, 2, 1, 2, 128, 129, 129, 129, 119,,, -3, 2, 3, 1, 2, 2, 1, 2, 256, 129, 129, 129, 119,,, -3, 2, 3, 1, 2, 2, 1, 2, 384, 129, 129, 129, 119,,, -3, 2, 3, 1, 2, 2, 2, 1, 128, 129, 129, 129, 119,,, -3, 2, 3, 1, 2, 2, 2, 1, 256, 129, 129, 129, 119,,, -3, 2, 3, 1, 2, 2, 2, 1, 384, 129, 129, 129, 119,,, -3, 2, 3, 1, 2, 2, 2, 2, 128, 129, 129, 129, 119,,, -3, 2, 3, 1, 2, 2, 2, 2, 256, 129, 129, 129, 119,,, -3, 2, 3, 1, 2, 2, 2, 2, 384, 129, 129, 129, 119,,, -3, 2, 3, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 2, 3, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 2, 3, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 2, 3, 2, 2, 2, 1, 1, 128, 240, 240, 240, 237,,, -3, 2, 3, 2, 2, 2, 1, 1, 256, 240, 240, 240, 237,,, -3, 2, 3, 2, 2, 2, 1, 1, 384, 240, 240, 240, 237,,, -3, 2, 3, 2, 2, 2, 1, 2, 128, 240, 240, 240, 237,,, -3, 2, 3, 2, 2, 2, 1, 2, 256, 240, 240, 240, 237,,, -3, 2, 3, 2, 2, 2, 1, 2, 384, 240, 240, 240, 237,,, -3, 2, 3, 2, 2, 2, 2, 1, 128, 240, 240, 240, 237,,, -3, 2, 3, 2, 2, 2, 2, 1, 256, 240, 240, 240, 237,,, -3, 2, 3, 2, 2, 2, 2, 1, 384, 240, 240, 240, 237,,, -3, 2, 3, 2, 2, 2, 2, 2, 128, 240, 240, 240, 237,,, -3, 2, 3, 2, 2, 2, 2, 2, 256, 240, 240, 240, 237,,, -3, 2, 3, 2, 2, 2, 2, 2, 384, 240, 240, 240, 237,,, -3, 3, 1, 1, 1, 1, 1, 1, 128, 130, 130, 130, 87,,, -3, 3, 1, 1, 1, 1, 1, 1, 256, 130, 130, 130, 87,,, -3, 3, 1, 1, 1, 1, 1, 1, 384, 130, 130, 130, 87,,, -3, 3, 1, 1, 2, 2, 1, 1, 128, 130, 130, 126, 87,,, -3, 3, 1, 1, 2, 2, 1, 1, 256, 130, 130, 126, 87,,, -3, 3, 1, 1, 2, 2, 1, 1, 384, 130, 130, 126, 87,,, -3, 3, 1, 1, 2, 2, 1, 2, 128, 130, 130, 126, 87,,, -3, 3, 1, 1, 2, 2, 1, 2, 256, 130, 130, 126, 87,,, -3, 3, 1, 1, 2, 2, 1, 2, 384, 130, 130, 126, 87,,, -3, 3, 1, 1, 2, 2, 2, 1, 128, 130, 130, 126, 87,,, -3, 3, 1, 1, 2, 2, 2, 1, 256, 130, 130, 126, 87,,, -3, 3, 1, 1, 2, 2, 2, 1, 384, 130, 130, 126, 87,,, -3, 3, 1, 1, 2, 2, 2, 2, 128, 130, 130, 126, 87,,, -3, 3, 1, 1, 2, 2, 2, 2, 256, 130, 130, 126, 87,,, -3, 3, 1, 1, 2, 2, 2, 2, 384, 130, 130, 126, 87,,, -3, 3, 1, 1, 3, 3, 1, 1, 128, 130, 128, 118, 87,,, -3, 3, 1, 1, 3, 3, 1, 1, 256, 130, 128, 118, 87,,, -3, 3, 1, 1, 3, 3, 1, 1, 384, 130, 128, 118, 87,,, -3, 3, 1, 1, 3, 3, 1, 2, 128, 130, 128, 118, 87,,, -3, 3, 1, 1, 3, 3, 1, 2, 256, 130, 128, 118, 87,,, -3, 3, 1, 1, 3, 3, 1, 2, 384, 130, 128, 118, 87,,, -3, 3, 1, 1, 3, 3, 1, 3, 128, 130, 128, 118, 87,,, -3, 3, 1, 1, 3, 3, 1, 3, 256, 130, 128, 118, 87,,, -3, 3, 1, 1, 3, 3, 1, 3, 384, 130, 128, 118, 87,,, -3, 3, 1, 1, 3, 3, 2, 1, 128, 130, 128, 118, 87,,, -3, 3, 1, 1, 3, 3, 2, 1, 256, 130, 128, 118, 87,,, -3, 3, 1, 1, 3, 3, 2, 1, 384, 130, 128, 118, 87,,, -3, 3, 1, 1, 3, 3, 2, 2, 128, 130, 128, 118, 87,,, -3, 3, 1, 1, 3, 3, 2, 2, 256, 130, 128, 118, 87,,, -3, 3, 1, 1, 3, 3, 2, 2, 384, 130, 128, 118, 87,,, -3, 3, 1, 1, 3, 3, 2, 3, 128, 130, 128, 118, 87,,, -3, 3, 1, 1, 3, 3, 2, 3, 256, 130, 128, 118, 87,,, -3, 3, 1, 1, 3, 3, 2, 3, 384, 130, 128, 118, 87,,, -3, 3, 1, 1, 3, 3, 3, 1, 128, 130, 128, 118, 87,,, -3, 3, 1, 1, 3, 3, 3, 1, 256, 130, 128, 118, 87,,, -3, 3, 1, 1, 3, 3, 3, 1, 384, 130, 128, 118, 87,,, -3, 3, 1, 1, 3, 3, 3, 2, 128, 130, 128, 118, 87,,, -3, 3, 1, 1, 3, 3, 3, 2, 256, 130, 128, 118, 87,,, -3, 3, 1, 1, 3, 3, 3, 2, 384, 130, 128, 118, 87,,, -3, 3, 1, 1, 3, 3, 3, 3, 128, 130, 128, 118, 87,,, -3, 3, 1, 1, 3, 3, 3, 3, 256, 130, 128, 118, 87,,, -3, 3, 1, 1, 3, 3, 3, 3, 384, 130, 128, 118, 87,,, -3, 3, 1, 2, 1, 1, 1, 1, 128, 240, 240, 240, 172,,, -3, 3, 1, 2, 1, 1, 1, 1, 256, 240, 240, 240, 172,,, -3, 3, 1, 2, 1, 1, 1, 1, 384, 240, 240, 240, 172,,, -3, 3, 1, 2, 2, 2, 1, 1, 128, 240, 240, 240, 172,,, -3, 3, 1, 2, 2, 2, 1, 1, 256, 240, 240, 240, 172,,, -3, 3, 1, 2, 2, 2, 1, 1, 384, 240, 240, 240, 172,,, -3, 3, 1, 2, 2, 2, 1, 2, 128, 240, 240, 240, 172,,, -3, 3, 1, 2, 2, 2, 1, 2, 256, 240, 240, 240, 172,,, -3, 3, 1, 2, 2, 2, 1, 2, 384, 240, 240, 240, 172,,, -3, 3, 1, 2, 2, 2, 2, 1, 128, 240, 240, 240, 172,,, -3, 3, 1, 2, 2, 2, 2, 1, 256, 240, 240, 240, 172,,, -3, 3, 1, 2, 2, 2, 2, 1, 384, 240, 240, 240, 172,,, -3, 3, 1, 2, 2, 2, 2, 2, 128, 240, 240, 240, 172,,, -3, 3, 1, 2, 2, 2, 2, 2, 256, 240, 240, 240, 172,,, -3, 3, 1, 2, 2, 2, 2, 2, 384, 240, 240, 240, 172,,, -3, 3, 1, 2, 3, 3, 1, 1, 128, 240, 240, 234, 172,,, -3, 3, 1, 2, 3, 3, 1, 1, 256, 240, 240, 234, 172,,, -3, 3, 1, 2, 3, 3, 1, 1, 384, 240, 240, 234, 172,,, -3, 3, 1, 2, 3, 3, 1, 2, 128, 240, 240, 234, 172,,, -3, 3, 1, 2, 3, 3, 1, 2, 256, 240, 240, 234, 172,,, -3, 3, 1, 2, 3, 3, 1, 2, 384, 240, 240, 234, 172,,, -3, 3, 1, 2, 3, 3, 1, 3, 128, 240, 240, 234, 172,,, -3, 3, 1, 2, 3, 3, 1, 3, 256, 240, 240, 234, 172,,, -3, 3, 1, 2, 3, 3, 1, 3, 384, 240, 240, 234, 172,,, -3, 3, 1, 2, 3, 3, 2, 1, 128, 240, 240, 234, 172,,, -3, 3, 1, 2, 3, 3, 2, 1, 256, 240, 240, 234, 172,,, -3, 3, 1, 2, 3, 3, 2, 1, 384, 240, 240, 234, 172,,, -3, 3, 1, 2, 3, 3, 2, 2, 128, 240, 240, 234, 172,,, -3, 3, 1, 2, 3, 3, 2, 2, 256, 240, 240, 234, 172,,, -3, 3, 1, 2, 3, 3, 2, 2, 384, 240, 240, 234, 172,,, -3, 3, 1, 2, 3, 3, 2, 3, 128, 240, 240, 234, 172,,, -3, 3, 1, 2, 3, 3, 2, 3, 256, 240, 240, 234, 172,,, -3, 3, 1, 2, 3, 3, 2, 3, 384, 240, 240, 234, 172,,, -3, 3, 1, 2, 3, 3, 3, 1, 128, 240, 240, 234, 172,,, -3, 3, 1, 2, 3, 3, 3, 1, 256, 240, 240, 234, 172,,, -3, 3, 1, 2, 3, 3, 3, 1, 384, 240, 240, 234, 172,,, -3, 3, 1, 2, 3, 3, 3, 2, 128, 240, 240, 234, 172,,, -3, 3, 1, 2, 3, 3, 3, 2, 256, 240, 240, 234, 172,,, -3, 3, 1, 2, 3, 3, 3, 2, 384, 240, 240, 234, 172,,, -3, 3, 1, 2, 3, 3, 3, 3, 128, 240, 240, 234, 172,,, -3, 3, 1, 2, 3, 3, 3, 3, 256, 240, 240, 234, 172,,, -3, 3, 1, 2, 3, 3, 3, 3, 384, 240, 240, 234, 172,,, -3, 3, 1, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 3, 1, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 3, 1, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 3, 1, 3, 2, 2, 1, 1, 128, 240, 240, 240, 240,,, -3, 3, 1, 3, 2, 2, 1, 1, 256, 240, 240, 240, 240,,, -3, 3, 1, 3, 2, 2, 1, 1, 384, 240, 240, 240, 240,,, -3, 3, 1, 3, 2, 2, 1, 2, 128, 240, 240, 240, 240,,, -3, 3, 1, 3, 2, 2, 1, 2, 256, 240, 240, 240, 240,,, -3, 3, 1, 3, 2, 2, 1, 2, 384, 240, 240, 240, 240,,, -3, 3, 1, 3, 2, 2, 2, 1, 128, 240, 240, 240, 240,,, -3, 3, 1, 3, 2, 2, 2, 1, 256, 240, 240, 240, 240,,, -3, 3, 1, 3, 2, 2, 2, 1, 384, 240, 240, 240, 240,,, -3, 3, 1, 3, 2, 2, 2, 2, 128, 240, 240, 240, 240,,, -3, 3, 1, 3, 2, 2, 2, 2, 256, 240, 240, 240, 240,,, -3, 3, 1, 3, 2, 2, 2, 2, 384, 240, 240, 240, 240,,, -3, 3, 1, 3, 3, 3, 1, 1, 128, 240, 240, 240, 240,,, -3, 3, 1, 3, 3, 3, 1, 1, 256, 240, 240, 240, 240,,, -3, 3, 1, 3, 3, 3, 1, 1, 384, 240, 240, 240, 240,,, -3, 3, 1, 3, 3, 3, 1, 2, 128, 240, 240, 240, 240,,, -3, 3, 1, 3, 3, 3, 1, 2, 256, 240, 240, 240, 240,,, -3, 3, 1, 3, 3, 3, 1, 2, 384, 240, 240, 240, 240,,, -3, 3, 1, 3, 3, 3, 1, 3, 128, 240, 240, 240, 240,,, -3, 3, 1, 3, 3, 3, 1, 3, 256, 240, 240, 240, 240,,, -3, 3, 1, 3, 3, 3, 1, 3, 384, 240, 240, 240, 240,,, -3, 3, 1, 3, 3, 3, 2, 1, 128, 240, 240, 240, 240,,, -3, 3, 1, 3, 3, 3, 2, 1, 256, 240, 240, 240, 240,,, -3, 3, 1, 3, 3, 3, 2, 1, 384, 240, 240, 240, 240,,, -3, 3, 1, 3, 3, 3, 2, 2, 128, 240, 240, 240, 240,,, -3, 3, 1, 3, 3, 3, 2, 2, 256, 240, 240, 240, 240,,, -3, 3, 1, 3, 3, 3, 2, 2, 384, 240, 240, 240, 240,,, -3, 3, 1, 3, 3, 3, 2, 3, 128, 240, 240, 240, 240,,, -3, 3, 1, 3, 3, 3, 2, 3, 256, 240, 240, 240, 240,,, -3, 3, 1, 3, 3, 3, 2, 3, 384, 240, 240, 240, 240,,, -3, 3, 1, 3, 3, 3, 3, 1, 128, 240, 240, 240, 240,,, -3, 3, 1, 3, 3, 3, 3, 1, 256, 240, 240, 240, 240,,, -3, 3, 1, 3, 3, 3, 3, 1, 384, 240, 240, 240, 240,,, -3, 3, 1, 3, 3, 3, 3, 2, 128, 240, 240, 240, 240,,, -3, 3, 1, 3, 3, 3, 3, 2, 256, 240, 240, 240, 240,,, -3, 3, 1, 3, 3, 3, 3, 2, 384, 240, 240, 240, 240,,, -3, 3, 1, 3, 3, 3, 3, 3, 128, 240, 240, 240, 240,,, -3, 3, 1, 3, 3, 3, 3, 3, 256, 240, 240, 240, 240,,, -3, 3, 1, 3, 3, 3, 3, 3, 384, 240, 240, 240, 240,,, -3, 3, 2, 1, 1, 1, 1, 1, 128, 130, 130, 130, 87,,, -3, 3, 2, 1, 1, 1, 1, 1, 256, 130, 130, 130, 87,,, -3, 3, 2, 1, 1, 1, 1, 1, 384, 130, 130, 130, 87,,, -3, 3, 2, 1, 2, 2, 1, 1, 128, 130, 130, 126, 87,,, -3, 3, 2, 1, 2, 2, 1, 1, 256, 130, 130, 126, 87,,, -3, 3, 2, 1, 2, 2, 1, 1, 384, 130, 130, 126, 87,,, -3, 3, 2, 1, 2, 2, 1, 2, 128, 130, 130, 126, 87,,, -3, 3, 2, 1, 2, 2, 1, 2, 256, 130, 130, 126, 87,,, -3, 3, 2, 1, 2, 2, 1, 2, 384, 130, 130, 126, 87,,, -3, 3, 2, 1, 2, 2, 2, 1, 128, 130, 130, 126, 87,,, -3, 3, 2, 1, 2, 2, 2, 1, 256, 130, 130, 126, 87,,, -3, 3, 2, 1, 2, 2, 2, 1, 384, 130, 130, 126, 87,,, -3, 3, 2, 1, 2, 2, 2, 2, 128, 130, 130, 126, 87,,, -3, 3, 2, 1, 2, 2, 2, 2, 256, 130, 130, 126, 87,,, -3, 3, 2, 1, 2, 2, 2, 2, 384, 130, 130, 126, 87,,, -3, 3, 2, 1, 3, 3, 1, 1, 128, 130, 128, 118, 87,,, -3, 3, 2, 1, 3, 3, 1, 1, 256, 130, 128, 118, 87,,, -3, 3, 2, 1, 3, 3, 1, 1, 384, 130, 128, 118, 87,,, -3, 3, 2, 1, 3, 3, 1, 2, 128, 130, 128, 118, 87,,, -3, 3, 2, 1, 3, 3, 1, 2, 256, 130, 128, 118, 87,,, -3, 3, 2, 1, 3, 3, 1, 2, 384, 130, 128, 118, 87,,, -3, 3, 2, 1, 3, 3, 1, 3, 128, 130, 128, 118, 87,,, -3, 3, 2, 1, 3, 3, 1, 3, 256, 130, 128, 118, 87,,, -3, 3, 2, 1, 3, 3, 1, 3, 384, 130, 128, 118, 87,,, -3, 3, 2, 1, 3, 3, 2, 1, 128, 130, 128, 118, 87,,, -3, 3, 2, 1, 3, 3, 2, 1, 256, 130, 128, 118, 87,,, -3, 3, 2, 1, 3, 3, 2, 1, 384, 130, 128, 118, 87,,, -3, 3, 2, 1, 3, 3, 2, 2, 128, 130, 128, 118, 87,,, -3, 3, 2, 1, 3, 3, 2, 2, 256, 130, 128, 118, 87,,, -3, 3, 2, 1, 3, 3, 2, 2, 384, 130, 128, 118, 87,,, -3, 3, 2, 1, 3, 3, 2, 3, 128, 130, 128, 118, 87,,, -3, 3, 2, 1, 3, 3, 2, 3, 256, 130, 128, 118, 87,,, -3, 3, 2, 1, 3, 3, 2, 3, 384, 130, 128, 118, 87,,, -3, 3, 2, 1, 3, 3, 3, 1, 128, 130, 128, 118, 87,,, -3, 3, 2, 1, 3, 3, 3, 1, 256, 130, 128, 118, 87,,, -3, 3, 2, 1, 3, 3, 3, 1, 384, 130, 128, 118, 87,,, -3, 3, 2, 1, 3, 3, 3, 2, 128, 130, 128, 118, 87,,, -3, 3, 2, 1, 3, 3, 3, 2, 256, 130, 128, 118, 87,,, -3, 3, 2, 1, 3, 3, 3, 2, 384, 130, 128, 118, 87,,, -3, 3, 2, 1, 3, 3, 3, 3, 128, 130, 128, 118, 87,,, -3, 3, 2, 1, 3, 3, 3, 3, 256, 130, 128, 118, 87,,, -3, 3, 2, 1, 3, 3, 3, 3, 384, 130, 128, 118, 87,,, -3, 3, 2, 2, 1, 1, 1, 1, 128, 240, 240, 240, 172,,, -3, 3, 2, 2, 1, 1, 1, 1, 256, 240, 240, 240, 172,,, -3, 3, 2, 2, 1, 1, 1, 1, 384, 240, 240, 240, 172,,, -3, 3, 2, 2, 2, 2, 1, 1, 128, 240, 240, 240, 172,,, -3, 3, 2, 2, 2, 2, 1, 1, 256, 240, 240, 240, 172,,, -3, 3, 2, 2, 2, 2, 1, 1, 384, 240, 240, 240, 172,,, -3, 3, 2, 2, 2, 2, 1, 2, 128, 240, 240, 240, 172,,, -3, 3, 2, 2, 2, 2, 1, 2, 256, 240, 240, 240, 172,,, -3, 3, 2, 2, 2, 2, 1, 2, 384, 240, 240, 240, 172,,, -3, 3, 2, 2, 2, 2, 2, 1, 128, 240, 240, 240, 172,,, -3, 3, 2, 2, 2, 2, 2, 1, 256, 240, 240, 240, 172,,, -3, 3, 2, 2, 2, 2, 2, 1, 384, 240, 240, 240, 172,,, -3, 3, 2, 2, 2, 2, 2, 2, 128, 240, 240, 240, 172,,, -3, 3, 2, 2, 2, 2, 2, 2, 256, 240, 240, 240, 172,,, -3, 3, 2, 2, 2, 2, 2, 2, 384, 240, 240, 240, 172,,, -3, 3, 2, 2, 3, 3, 1, 1, 128, 240, 240, 234, 172,,, -3, 3, 2, 2, 3, 3, 1, 1, 256, 240, 240, 234, 172,,, -3, 3, 2, 2, 3, 3, 1, 1, 384, 240, 240, 234, 172,,, -3, 3, 2, 2, 3, 3, 1, 2, 128, 240, 240, 234, 172,,, -3, 3, 2, 2, 3, 3, 1, 2, 256, 240, 240, 234, 172,,, -3, 3, 2, 2, 3, 3, 1, 2, 384, 240, 240, 234, 172,,, -3, 3, 2, 2, 3, 3, 1, 3, 128, 240, 240, 234, 172,,, -3, 3, 2, 2, 3, 3, 1, 3, 256, 240, 240, 234, 172,,, -3, 3, 2, 2, 3, 3, 1, 3, 384, 240, 240, 234, 172,,, -3, 3, 2, 2, 3, 3, 2, 1, 128, 240, 240, 234, 172,,, -3, 3, 2, 2, 3, 3, 2, 1, 256, 240, 240, 234, 172,,, -3, 3, 2, 2, 3, 3, 2, 1, 384, 240, 240, 234, 172,,, -3, 3, 2, 2, 3, 3, 2, 2, 128, 240, 240, 234, 172,,, -3, 3, 2, 2, 3, 3, 2, 2, 256, 240, 240, 234, 172,,, -3, 3, 2, 2, 3, 3, 2, 2, 384, 240, 240, 234, 172,,, -3, 3, 2, 2, 3, 3, 2, 3, 128, 240, 240, 234, 172,,, -3, 3, 2, 2, 3, 3, 2, 3, 256, 240, 240, 234, 172,,, -3, 3, 2, 2, 3, 3, 2, 3, 384, 240, 240, 234, 172,,, -3, 3, 2, 2, 3, 3, 3, 1, 128, 240, 240, 234, 172,,, -3, 3, 2, 2, 3, 3, 3, 1, 256, 240, 240, 234, 172,,, -3, 3, 2, 2, 3, 3, 3, 1, 384, 240, 240, 234, 172,,, -3, 3, 2, 2, 3, 3, 3, 2, 128, 240, 240, 234, 172,,, -3, 3, 2, 2, 3, 3, 3, 2, 256, 240, 240, 234, 172,,, -3, 3, 2, 2, 3, 3, 3, 2, 384, 240, 240, 234, 172,,, -3, 3, 2, 2, 3, 3, 3, 3, 128, 240, 240, 234, 172,,, -3, 3, 2, 2, 3, 3, 3, 3, 256, 240, 240, 234, 172,,, -3, 3, 2, 2, 3, 3, 3, 3, 384, 240, 240, 234, 172,,, -3, 3, 2, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 3, 2, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 3, 2, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 3, 2, 3, 2, 2, 1, 1, 128, 240, 240, 240, 240,,, -3, 3, 2, 3, 2, 2, 1, 1, 256, 240, 240, 240, 240,,, -3, 3, 2, 3, 2, 2, 1, 1, 384, 240, 240, 240, 240,,, -3, 3, 2, 3, 2, 2, 1, 2, 128, 240, 240, 240, 240,,, -3, 3, 2, 3, 2, 2, 1, 2, 256, 240, 240, 240, 240,,, -3, 3, 2, 3, 2, 2, 1, 2, 384, 240, 240, 240, 240,,, -3, 3, 2, 3, 2, 2, 2, 1, 128, 240, 240, 240, 240,,, -3, 3, 2, 3, 2, 2, 2, 1, 256, 240, 240, 240, 240,,, -3, 3, 2, 3, 2, 2, 2, 1, 384, 240, 240, 240, 240,,, -3, 3, 2, 3, 2, 2, 2, 2, 128, 240, 240, 240, 240,,, -3, 3, 2, 3, 2, 2, 2, 2, 256, 240, 240, 240, 240,,, -3, 3, 2, 3, 2, 2, 2, 2, 384, 240, 240, 240, 240,,, -3, 3, 2, 3, 3, 3, 1, 1, 128, 240, 240, 240, 240,,, -3, 3, 2, 3, 3, 3, 1, 1, 256, 240, 240, 240, 240,,, -3, 3, 2, 3, 3, 3, 1, 1, 384, 240, 240, 240, 240,,, -3, 3, 2, 3, 3, 3, 1, 2, 128, 240, 240, 240, 240,,, -3, 3, 2, 3, 3, 3, 1, 2, 256, 240, 240, 240, 240,,, -3, 3, 2, 3, 3, 3, 1, 2, 384, 240, 240, 240, 240,,, -3, 3, 2, 3, 3, 3, 1, 3, 128, 240, 240, 240, 240,,, -3, 3, 2, 3, 3, 3, 1, 3, 256, 240, 240, 240, 240,,, -3, 3, 2, 3, 3, 3, 1, 3, 384, 240, 240, 240, 240,,, -3, 3, 2, 3, 3, 3, 2, 1, 128, 240, 240, 240, 240,,, -3, 3, 2, 3, 3, 3, 2, 1, 256, 240, 240, 240, 240,,, -3, 3, 2, 3, 3, 3, 2, 1, 384, 240, 240, 240, 240,,, -3, 3, 2, 3, 3, 3, 2, 2, 128, 240, 240, 240, 240,,, -3, 3, 2, 3, 3, 3, 2, 2, 256, 240, 240, 240, 240,,, -3, 3, 2, 3, 3, 3, 2, 2, 384, 240, 240, 240, 240,,, -3, 3, 2, 3, 3, 3, 2, 3, 128, 240, 240, 240, 240,,, -3, 3, 2, 3, 3, 3, 2, 3, 256, 240, 240, 240, 240,,, -3, 3, 2, 3, 3, 3, 2, 3, 384, 240, 240, 240, 240,,, -3, 3, 2, 3, 3, 3, 3, 1, 128, 240, 240, 240, 240,,, -3, 3, 2, 3, 3, 3, 3, 1, 256, 240, 240, 240, 240,,, -3, 3, 2, 3, 3, 3, 3, 1, 384, 240, 240, 240, 240,,, -3, 3, 2, 3, 3, 3, 3, 2, 128, 240, 240, 240, 240,,, -3, 3, 2, 3, 3, 3, 3, 2, 256, 240, 240, 240, 240,,, -3, 3, 2, 3, 3, 3, 3, 2, 384, 240, 240, 240, 240,,, -3, 3, 2, 3, 3, 3, 3, 3, 128, 240, 240, 240, 240,,, -3, 3, 2, 3, 3, 3, 3, 3, 256, 240, 240, 240, 240,,, -3, 3, 2, 3, 3, 3, 3, 3, 384, 240, 240, 240, 240,,, -3, 3, 3, 1, 1, 1, 1, 1, 128, 130, 130, 130, 87,,, -3, 3, 3, 1, 1, 1, 1, 1, 256, 130, 130, 130, 87,,, -3, 3, 3, 1, 1, 1, 1, 1, 384, 130, 130, 130, 87,,, -3, 3, 3, 1, 2, 2, 1, 1, 128, 130, 130, 126, 87,,, -3, 3, 3, 1, 2, 2, 1, 1, 256, 130, 130, 126, 87,,, -3, 3, 3, 1, 2, 2, 1, 1, 384, 130, 130, 126, 87,,, -3, 3, 3, 1, 2, 2, 1, 2, 128, 130, 130, 126, 87,,, -3, 3, 3, 1, 2, 2, 1, 2, 256, 130, 130, 126, 87,,, -3, 3, 3, 1, 2, 2, 1, 2, 384, 130, 130, 126, 87,,, -3, 3, 3, 1, 2, 2, 2, 1, 128, 130, 130, 126, 87,,, -3, 3, 3, 1, 2, 2, 2, 1, 256, 130, 130, 126, 87,,, -3, 3, 3, 1, 2, 2, 2, 1, 384, 130, 130, 126, 87,,, -3, 3, 3, 1, 2, 2, 2, 2, 128, 130, 130, 126, 87,,, -3, 3, 3, 1, 2, 2, 2, 2, 256, 130, 130, 126, 87,,, -3, 3, 3, 1, 2, 2, 2, 2, 384, 130, 130, 126, 87,,, -3, 3, 3, 1, 3, 3, 1, 1, 128, 130, 128, 118, 87,,, -3, 3, 3, 1, 3, 3, 1, 1, 256, 130, 128, 118, 87,,, -3, 3, 3, 1, 3, 3, 1, 1, 384, 130, 128, 118, 87,,, -3, 3, 3, 1, 3, 3, 1, 2, 128, 130, 128, 118, 87,,, -3, 3, 3, 1, 3, 3, 1, 2, 256, 130, 128, 118, 87,,, -3, 3, 3, 1, 3, 3, 1, 2, 384, 130, 128, 118, 87,,, -3, 3, 3, 1, 3, 3, 1, 3, 128, 130, 128, 118, 87,,, -3, 3, 3, 1, 3, 3, 1, 3, 256, 130, 128, 118, 87,,, -3, 3, 3, 1, 3, 3, 1, 3, 384, 130, 128, 118, 87,,, -3, 3, 3, 1, 3, 3, 2, 1, 128, 130, 128, 118, 87,,, -3, 3, 3, 1, 3, 3, 2, 1, 256, 130, 128, 118, 87,,, -3, 3, 3, 1, 3, 3, 2, 1, 384, 130, 128, 118, 87,,, -3, 3, 3, 1, 3, 3, 2, 2, 128, 130, 128, 118, 87,,, -3, 3, 3, 1, 3, 3, 2, 2, 256, 130, 128, 118, 87,,, -3, 3, 3, 1, 3, 3, 2, 2, 384, 130, 128, 118, 87,,, -3, 3, 3, 1, 3, 3, 2, 3, 128, 130, 128, 118, 87,,, -3, 3, 3, 1, 3, 3, 2, 3, 256, 130, 128, 118, 87,,, -3, 3, 3, 1, 3, 3, 2, 3, 384, 130, 128, 118, 87,,, -3, 3, 3, 1, 3, 3, 3, 1, 128, 130, 128, 118, 87,,, -3, 3, 3, 1, 3, 3, 3, 1, 256, 130, 128, 118, 87,,, -3, 3, 3, 1, 3, 3, 3, 1, 384, 130, 128, 118, 87,,, -3, 3, 3, 1, 3, 3, 3, 2, 128, 130, 128, 118, 87,,, -3, 3, 3, 1, 3, 3, 3, 2, 256, 130, 128, 118, 87,,, -3, 3, 3, 1, 3, 3, 3, 2, 384, 130, 128, 118, 87,,, -3, 3, 3, 1, 3, 3, 3, 3, 128, 130, 128, 118, 87,,, -3, 3, 3, 1, 3, 3, 3, 3, 256, 130, 128, 118, 87,,, -3, 3, 3, 1, 3, 3, 3, 3, 384, 130, 128, 118, 87,,, -3, 3, 3, 2, 1, 1, 1, 1, 128, 240, 240, 240, 172,,, -3, 3, 3, 2, 1, 1, 1, 1, 256, 240, 240, 240, 172,,, -3, 3, 3, 2, 1, 1, 1, 1, 384, 240, 240, 240, 172,,, -3, 3, 3, 2, 2, 2, 1, 1, 128, 240, 240, 240, 172,,, -3, 3, 3, 2, 2, 2, 1, 1, 256, 240, 240, 240, 172,,, -3, 3, 3, 2, 2, 2, 1, 1, 384, 240, 240, 240, 172,,, -3, 3, 3, 2, 2, 2, 1, 2, 128, 240, 240, 240, 172,,, -3, 3, 3, 2, 2, 2, 1, 2, 256, 240, 240, 240, 172,,, -3, 3, 3, 2, 2, 2, 1, 2, 384, 240, 240, 240, 172,,, -3, 3, 3, 2, 2, 2, 2, 1, 128, 240, 240, 240, 172,,, -3, 3, 3, 2, 2, 2, 2, 1, 256, 240, 240, 240, 172,,, -3, 3, 3, 2, 2, 2, 2, 1, 384, 240, 240, 240, 172,,, -3, 3, 3, 2, 2, 2, 2, 2, 128, 240, 240, 240, 172,,, -3, 3, 3, 2, 2, 2, 2, 2, 256, 240, 240, 240, 172,,, -3, 3, 3, 2, 2, 2, 2, 2, 384, 240, 240, 240, 172,,, -3, 3, 3, 2, 3, 3, 1, 1, 128, 240, 240, 234, 172,,, -3, 3, 3, 2, 3, 3, 1, 1, 256, 240, 240, 234, 172,,, -3, 3, 3, 2, 3, 3, 1, 1, 384, 240, 240, 234, 172,,, -3, 3, 3, 2, 3, 3, 1, 2, 128, 240, 240, 234, 172,,, -3, 3, 3, 2, 3, 3, 1, 2, 256, 240, 240, 234, 172,,, -3, 3, 3, 2, 3, 3, 1, 2, 384, 240, 240, 234, 172,,, -3, 3, 3, 2, 3, 3, 1, 3, 128, 240, 240, 234, 172,,, -3, 3, 3, 2, 3, 3, 1, 3, 256, 240, 240, 234, 172,,, -3, 3, 3, 2, 3, 3, 1, 3, 384, 240, 240, 234, 172,,, -3, 3, 3, 2, 3, 3, 2, 1, 128, 240, 240, 234, 172,,, -3, 3, 3, 2, 3, 3, 2, 1, 256, 240, 240, 234, 172,,, -3, 3, 3, 2, 3, 3, 2, 1, 384, 240, 240, 234, 172,,, -3, 3, 3, 2, 3, 3, 2, 2, 128, 240, 240, 234, 172,,, -3, 3, 3, 2, 3, 3, 2, 2, 256, 240, 240, 234, 172,,, -3, 3, 3, 2, 3, 3, 2, 2, 384, 240, 240, 234, 172,,, -3, 3, 3, 2, 3, 3, 2, 3, 128, 240, 240, 234, 172,,, -3, 3, 3, 2, 3, 3, 2, 3, 256, 240, 240, 234, 172,,, -3, 3, 3, 2, 3, 3, 2, 3, 384, 240, 240, 234, 172,,, -3, 3, 3, 2, 3, 3, 3, 1, 128, 240, 240, 234, 172,,, -3, 3, 3, 2, 3, 3, 3, 1, 256, 240, 240, 234, 172,,, -3, 3, 3, 2, 3, 3, 3, 1, 384, 240, 240, 234, 172,,, -3, 3, 3, 2, 3, 3, 3, 2, 128, 240, 240, 234, 172,,, -3, 3, 3, 2, 3, 3, 3, 2, 256, 240, 240, 234, 172,,, -3, 3, 3, 2, 3, 3, 3, 2, 384, 240, 240, 234, 172,,, -3, 3, 3, 2, 3, 3, 3, 3, 128, 240, 240, 234, 172,,, -3, 3, 3, 2, 3, 3, 3, 3, 256, 240, 240, 234, 172,,, -3, 3, 3, 2, 3, 3, 3, 3, 384, 240, 240, 234, 172,,, -3, 3, 3, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 3, 3, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 3, 3, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 3, 3, 3, 2, 2, 1, 1, 128, 240, 240, 240, 240,,, -3, 3, 3, 3, 2, 2, 1, 1, 256, 240, 240, 240, 240,,, -3, 3, 3, 3, 2, 2, 1, 1, 384, 240, 240, 240, 240,,, -3, 3, 3, 3, 2, 2, 1, 2, 128, 240, 240, 240, 240,,, -3, 3, 3, 3, 2, 2, 1, 2, 256, 240, 240, 240, 240,,, -3, 3, 3, 3, 2, 2, 1, 2, 384, 240, 240, 240, 240,,, -3, 3, 3, 3, 2, 2, 2, 1, 128, 240, 240, 240, 240,,, -3, 3, 3, 3, 2, 2, 2, 1, 256, 240, 240, 240, 240,,, -3, 3, 3, 3, 2, 2, 2, 1, 384, 240, 240, 240, 240,,, -3, 3, 3, 3, 2, 2, 2, 2, 128, 240, 240, 240, 240,,, -3, 3, 3, 3, 2, 2, 2, 2, 256, 240, 240, 240, 240,,, -3, 3, 3, 3, 2, 2, 2, 2, 384, 240, 240, 240, 240,,, -3, 3, 3, 3, 3, 3, 1, 1, 128, 240, 240, 240, 240,,, -3, 3, 3, 3, 3, 3, 1, 1, 256, 240, 240, 240, 240,,, -3, 3, 3, 3, 3, 3, 1, 1, 384, 240, 240, 240, 240,,, -3, 3, 3, 3, 3, 3, 1, 2, 128, 240, 240, 240, 240,,, -3, 3, 3, 3, 3, 3, 1, 2, 256, 240, 240, 240, 240,,, -3, 3, 3, 3, 3, 3, 1, 2, 384, 240, 240, 240, 240,,, -3, 3, 3, 3, 3, 3, 1, 3, 128, 240, 240, 240, 240,,, -3, 3, 3, 3, 3, 3, 1, 3, 256, 240, 240, 240, 240,,, -3, 3, 3, 3, 3, 3, 1, 3, 384, 240, 240, 240, 240,,, -3, 3, 3, 3, 3, 3, 2, 1, 128, 240, 240, 240, 240,,, -3, 3, 3, 3, 3, 3, 2, 1, 256, 240, 240, 240, 240,,, -3, 3, 3, 3, 3, 3, 2, 1, 384, 240, 240, 240, 240,,, -3, 3, 3, 3, 3, 3, 2, 2, 128, 240, 240, 240, 240,,, -3, 3, 3, 3, 3, 3, 2, 2, 256, 240, 240, 240, 240,,, -3, 3, 3, 3, 3, 3, 2, 2, 384, 240, 240, 240, 240,,, -3, 3, 3, 3, 3, 3, 2, 3, 128, 240, 240, 240, 240,,, -3, 3, 3, 3, 3, 3, 2, 3, 256, 240, 240, 240, 240,,, -3, 3, 3, 3, 3, 3, 2, 3, 384, 240, 240, 240, 240,,, -3, 3, 3, 3, 3, 3, 3, 1, 128, 240, 240, 240, 240,,, -3, 3, 3, 3, 3, 3, 3, 1, 256, 240, 240, 240, 240,,, -3, 3, 3, 3, 3, 3, 3, 1, 384, 240, 240, 240, 240,,, -3, 3, 3, 3, 3, 3, 3, 2, 128, 240, 240, 240, 240,,, -3, 3, 3, 3, 3, 3, 3, 2, 256, 240, 240, 240, 240,,, -3, 3, 3, 3, 3, 3, 3, 2, 384, 240, 240, 240, 240,,, -3, 3, 3, 3, 3, 3, 3, 3, 128, 240, 240, 240, 240,,, -3, 3, 3, 3, 3, 3, 3, 3, 256, 240, 240, 240, 240,,, -3, 3, 3, 3, 3, 3, 3, 3, 384, 240, 240, 240, 240,,, -3, 4, 1, 1, 1, 1, 1, 1, 128, 131, 131, 131, 88,,, -3, 4, 1, 1, 1, 1, 1, 1, 256, 131, 131, 131, 88,,, -3, 4, 1, 1, 1, 1, 1, 1, 384, 131, 131, 131, 88,,, -3, 4, 1, 1, 2, 2, 1, 1, 128, 131, 131, 121, 88,,, -3, 4, 1, 1, 2, 2, 1, 1, 256, 131, 131, 121, 88,,, -3, 4, 1, 1, 2, 2, 1, 1, 384, 131, 131, 121, 88,,, -3, 4, 1, 1, 2, 2, 1, 2, 128, 131, 131, 121, 88,,, -3, 4, 1, 1, 2, 2, 1, 2, 256, 131, 131, 121, 88,,, -3, 4, 1, 1, 2, 2, 1, 2, 384, 131, 131, 121, 88,,, -3, 4, 1, 1, 2, 2, 2, 1, 128, 131, 131, 121, 88,,, -3, 4, 1, 1, 2, 2, 2, 1, 256, 131, 131, 121, 88,,, -3, 4, 1, 1, 2, 2, 2, 1, 384, 131, 131, 121, 88,,, -3, 4, 1, 1, 2, 2, 2, 2, 128, 131, 131, 121, 88,,, -3, 4, 1, 1, 2, 2, 2, 2, 256, 131, 131, 121, 88,,, -3, 4, 1, 1, 2, 2, 2, 2, 384, 131, 131, 121, 88,,, -3, 4, 1, 1, 3, 3, 1, 1, 128, 131, 125, 113, 87,,, -3, 4, 1, 1, 3, 3, 1, 1, 256, 131, 125, 113, 87,,, -3, 4, 1, 1, 3, 3, 1, 1, 384, 131, 125, 113, 87,,, -3, 4, 1, 1, 3, 3, 1, 2, 128, 131, 125, 113, 87,,, -3, 4, 1, 1, 3, 3, 1, 2, 256, 131, 125, 113, 87,,, -3, 4, 1, 1, 3, 3, 1, 2, 384, 131, 125, 113, 87,,, -3, 4, 1, 1, 3, 3, 1, 3, 128, 131, 125, 113, 87,,, -3, 4, 1, 1, 3, 3, 1, 3, 256, 131, 125, 113, 87,,, -3, 4, 1, 1, 3, 3, 1, 3, 384, 131, 125, 113, 87,,, -3, 4, 1, 1, 3, 3, 2, 1, 128, 131, 125, 113, 87,,, -3, 4, 1, 1, 3, 3, 2, 1, 256, 131, 125, 113, 87,,, -3, 4, 1, 1, 3, 3, 2, 1, 384, 131, 125, 113, 87,,, -3, 4, 1, 1, 3, 3, 2, 2, 128, 131, 125, 113, 87,,, -3, 4, 1, 1, 3, 3, 2, 2, 256, 131, 125, 113, 87,,, -3, 4, 1, 1, 3, 3, 2, 2, 384, 131, 125, 113, 87,,, -3, 4, 1, 1, 3, 3, 2, 3, 128, 131, 125, 113, 87,,, -3, 4, 1, 1, 3, 3, 2, 3, 256, 131, 125, 113, 87,,, -3, 4, 1, 1, 3, 3, 2, 3, 384, 131, 125, 113, 87,,, -3, 4, 1, 1, 3, 3, 3, 1, 128, 131, 125, 113, 87,,, -3, 4, 1, 1, 3, 3, 3, 1, 256, 131, 125, 113, 87,,, -3, 4, 1, 1, 3, 3, 3, 1, 384, 131, 125, 113, 87,,, -3, 4, 1, 1, 3, 3, 3, 2, 128, 131, 125, 113, 87,,, -3, 4, 1, 1, 3, 3, 3, 2, 256, 131, 125, 113, 87,,, -3, 4, 1, 1, 3, 3, 3, 2, 384, 131, 125, 113, 87,,, -3, 4, 1, 1, 3, 3, 3, 3, 128, 131, 125, 113, 87,,, -3, 4, 1, 1, 3, 3, 3, 3, 256, 131, 125, 113, 87,,, -3, 4, 1, 1, 3, 3, 3, 3, 384, 131, 125, 113, 87,,, -3, 4, 1, 2, 1, 1, 1, 1, 128, 240, 240, 240, 173,,, -3, 4, 1, 2, 1, 1, 1, 1, 256, 240, 240, 240, 173,,, -3, 4, 1, 2, 1, 1, 1, 1, 384, 240, 240, 240, 173,,, -3, 4, 1, 2, 2, 2, 1, 1, 128, 240, 240, 239, 173,,, -3, 4, 1, 2, 2, 2, 1, 1, 256, 240, 240, 239, 173,,, -3, 4, 1, 2, 2, 2, 1, 1, 384, 240, 240, 239, 173,,, -3, 4, 1, 2, 2, 2, 1, 2, 128, 240, 240, 239, 173,,, -3, 4, 1, 2, 2, 2, 1, 2, 256, 240, 240, 239, 173,,, -3, 4, 1, 2, 2, 2, 1, 2, 384, 240, 240, 239, 173,,, -3, 4, 1, 2, 2, 2, 2, 1, 128, 240, 240, 239, 173,,, -3, 4, 1, 2, 2, 2, 2, 1, 256, 240, 240, 239, 173,,, -3, 4, 1, 2, 2, 2, 2, 1, 384, 240, 240, 239, 173,,, -3, 4, 1, 2, 2, 2, 2, 2, 128, 240, 240, 239, 173,,, -3, 4, 1, 2, 2, 2, 2, 2, 256, 240, 240, 239, 173,,, -3, 4, 1, 2, 2, 2, 2, 2, 384, 240, 240, 239, 173,,, -3, 4, 1, 2, 3, 3, 1, 1, 128, 240, 240, 223, 171,,, -3, 4, 1, 2, 3, 3, 1, 1, 256, 240, 240, 223, 171,,, -3, 4, 1, 2, 3, 3, 1, 1, 384, 240, 240, 223, 171,,, -3, 4, 1, 2, 3, 3, 1, 2, 128, 240, 240, 223, 171,,, -3, 4, 1, 2, 3, 3, 1, 2, 256, 240, 240, 223, 171,,, -3, 4, 1, 2, 3, 3, 1, 2, 384, 240, 240, 223, 171,,, -3, 4, 1, 2, 3, 3, 1, 3, 128, 240, 240, 223, 171,,, -3, 4, 1, 2, 3, 3, 1, 3, 256, 240, 240, 223, 171,,, -3, 4, 1, 2, 3, 3, 1, 3, 384, 240, 240, 223, 171,,, -3, 4, 1, 2, 3, 3, 2, 1, 128, 240, 240, 223, 171,,, -3, 4, 1, 2, 3, 3, 2, 1, 256, 240, 240, 223, 171,,, -3, 4, 1, 2, 3, 3, 2, 1, 384, 240, 240, 223, 171,,, -3, 4, 1, 2, 3, 3, 2, 2, 128, 240, 240, 223, 171,,, -3, 4, 1, 2, 3, 3, 2, 2, 256, 240, 240, 223, 171,,, -3, 4, 1, 2, 3, 3, 2, 2, 384, 240, 240, 223, 171,,, -3, 4, 1, 2, 3, 3, 2, 3, 128, 240, 240, 223, 171,,, -3, 4, 1, 2, 3, 3, 2, 3, 256, 240, 240, 223, 171,,, -3, 4, 1, 2, 3, 3, 2, 3, 384, 240, 240, 223, 171,,, -3, 4, 1, 2, 3, 3, 3, 1, 128, 240, 240, 223, 171,,, -3, 4, 1, 2, 3, 3, 3, 1, 256, 240, 240, 223, 171,,, -3, 4, 1, 2, 3, 3, 3, 1, 384, 240, 240, 223, 171,,, -3, 4, 1, 2, 3, 3, 3, 2, 128, 240, 240, 223, 171,,, -3, 4, 1, 2, 3, 3, 3, 2, 256, 240, 240, 223, 171,,, -3, 4, 1, 2, 3, 3, 3, 2, 384, 240, 240, 223, 171,,, -3, 4, 1, 2, 3, 3, 3, 3, 128, 240, 240, 223, 171,,, -3, 4, 1, 2, 3, 3, 3, 3, 256, 240, 240, 223, 171,,, -3, 4, 1, 2, 3, 3, 3, 3, 384, 240, 240, 223, 171,,, -3, 4, 1, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 4, 1, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 4, 1, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 4, 1, 3, 2, 2, 1, 1, 128, 240, 240, 240, 240,,, -3, 4, 1, 3, 2, 2, 1, 1, 256, 240, 240, 240, 240,,, -3, 4, 1, 3, 2, 2, 1, 1, 384, 240, 240, 240, 240,,, -3, 4, 1, 3, 2, 2, 1, 2, 128, 240, 240, 240, 240,,, -3, 4, 1, 3, 2, 2, 1, 2, 256, 240, 240, 240, 240,,, -3, 4, 1, 3, 2, 2, 1, 2, 384, 240, 240, 240, 240,,, -3, 4, 1, 3, 2, 2, 2, 1, 128, 240, 240, 240, 240,,, -3, 4, 1, 3, 2, 2, 2, 1, 256, 240, 240, 240, 240,,, -3, 4, 1, 3, 2, 2, 2, 1, 384, 240, 240, 240, 240,,, -3, 4, 1, 3, 2, 2, 2, 2, 128, 240, 240, 240, 240,,, -3, 4, 1, 3, 2, 2, 2, 2, 256, 240, 240, 240, 240,,, -3, 4, 1, 3, 2, 2, 2, 2, 384, 240, 240, 240, 240,,, -3, 4, 1, 3, 3, 3, 1, 1, 128, 240, 240, 240, 240,,, -3, 4, 1, 3, 3, 3, 1, 1, 256, 240, 240, 240, 240,,, -3, 4, 1, 3, 3, 3, 1, 1, 384, 240, 240, 240, 240,,, -3, 4, 1, 3, 3, 3, 1, 2, 128, 240, 240, 240, 240,,, -3, 4, 1, 3, 3, 3, 1, 2, 256, 240, 240, 240, 240,,, -3, 4, 1, 3, 3, 3, 1, 2, 384, 240, 240, 240, 240,,, -3, 4, 1, 3, 3, 3, 1, 3, 128, 240, 240, 240, 240,,, -3, 4, 1, 3, 3, 3, 1, 3, 256, 240, 240, 240, 240,,, -3, 4, 1, 3, 3, 3, 1, 3, 384, 240, 240, 240, 240,,, -3, 4, 1, 3, 3, 3, 2, 1, 128, 240, 240, 240, 240,,, -3, 4, 1, 3, 3, 3, 2, 1, 256, 240, 240, 240, 240,,, -3, 4, 1, 3, 3, 3, 2, 1, 384, 240, 240, 240, 240,,, -3, 4, 1, 3, 3, 3, 2, 2, 128, 240, 240, 240, 240,,, -3, 4, 1, 3, 3, 3, 2, 2, 256, 240, 240, 240, 240,,, -3, 4, 1, 3, 3, 3, 2, 2, 384, 240, 240, 240, 240,,, -3, 4, 1, 3, 3, 3, 2, 3, 128, 240, 240, 240, 240,,, -3, 4, 1, 3, 3, 3, 2, 3, 256, 240, 240, 240, 240,,, -3, 4, 1, 3, 3, 3, 2, 3, 384, 240, 240, 240, 240,,, -3, 4, 1, 3, 3, 3, 3, 1, 128, 240, 240, 240, 240,,, -3, 4, 1, 3, 3, 3, 3, 1, 256, 240, 240, 240, 240,,, -3, 4, 1, 3, 3, 3, 3, 1, 384, 240, 240, 240, 240,,, -3, 4, 1, 3, 3, 3, 3, 2, 128, 240, 240, 240, 240,,, -3, 4, 1, 3, 3, 3, 3, 2, 256, 240, 240, 240, 240,,, -3, 4, 1, 3, 3, 3, 3, 2, 384, 240, 240, 240, 240,,, -3, 4, 1, 3, 3, 3, 3, 3, 128, 240, 240, 240, 240,,, -3, 4, 1, 3, 3, 3, 3, 3, 256, 240, 240, 240, 240,,, -3, 4, 1, 3, 3, 3, 3, 3, 384, 240, 240, 240, 240,,, -3, 4, 1, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 4, 1, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 4, 1, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 4, 1, 4, 2, 2, 1, 1, 128, 240, 240, 240, 240,,, -3, 4, 1, 4, 2, 2, 1, 1, 256, 240, 240, 240, 240,,, -3, 4, 1, 4, 2, 2, 1, 1, 384, 240, 240, 240, 240,,, -3, 4, 1, 4, 2, 2, 1, 2, 128, 240, 240, 240, 240,,, -3, 4, 1, 4, 2, 2, 1, 2, 256, 240, 240, 240, 240,,, -3, 4, 1, 4, 2, 2, 1, 2, 384, 240, 240, 240, 240,,, -3, 4, 1, 4, 2, 2, 2, 1, 128, 240, 240, 240, 240,,, -3, 4, 1, 4, 2, 2, 2, 1, 256, 240, 240, 240, 240,,, -3, 4, 1, 4, 2, 2, 2, 1, 384, 240, 240, 240, 240,,, -3, 4, 1, 4, 2, 2, 2, 2, 128, 240, 240, 240, 240,,, -3, 4, 1, 4, 2, 2, 2, 2, 256, 240, 240, 240, 240,,, -3, 4, 1, 4, 2, 2, 2, 2, 384, 240, 240, 240, 240,,, -3, 4, 1, 4, 3, 3, 1, 1, 128, 240, 240, 240, 240,,, -3, 4, 1, 4, 3, 3, 1, 1, 256, 240, 240, 240, 240,,, -3, 4, 1, 4, 3, 3, 1, 1, 384, 240, 240, 240, 240,,, -3, 4, 1, 4, 3, 3, 1, 2, 128, 240, 240, 240, 240,,, -3, 4, 1, 4, 3, 3, 1, 2, 256, 240, 240, 240, 240,,, -3, 4, 1, 4, 3, 3, 1, 2, 384, 240, 240, 240, 240,,, -3, 4, 1, 4, 3, 3, 1, 3, 128, 240, 240, 240, 240,,, -3, 4, 1, 4, 3, 3, 1, 3, 256, 240, 240, 240, 240,,, -3, 4, 1, 4, 3, 3, 1, 3, 384, 240, 240, 240, 240,,, -3, 4, 1, 4, 3, 3, 2, 1, 128, 240, 240, 240, 240,,, -3, 4, 1, 4, 3, 3, 2, 1, 256, 240, 240, 240, 240,,, -3, 4, 1, 4, 3, 3, 2, 1, 384, 240, 240, 240, 240,,, -3, 4, 1, 4, 3, 3, 2, 2, 128, 240, 240, 240, 240,,, -3, 4, 1, 4, 3, 3, 2, 2, 256, 240, 240, 240, 240,,, -3, 4, 1, 4, 3, 3, 2, 2, 384, 240, 240, 240, 240,,, -3, 4, 1, 4, 3, 3, 2, 3, 128, 240, 240, 240, 240,,, -3, 4, 1, 4, 3, 3, 2, 3, 256, 240, 240, 240, 240,,, -3, 4, 1, 4, 3, 3, 2, 3, 384, 240, 240, 240, 240,,, -3, 4, 1, 4, 3, 3, 3, 1, 128, 240, 240, 240, 240,,, -3, 4, 1, 4, 3, 3, 3, 1, 256, 240, 240, 240, 240,,, -3, 4, 1, 4, 3, 3, 3, 1, 384, 240, 240, 240, 240,,, -3, 4, 1, 4, 3, 3, 3, 2, 128, 240, 240, 240, 240,,, -3, 4, 1, 4, 3, 3, 3, 2, 256, 240, 240, 240, 240,,, -3, 4, 1, 4, 3, 3, 3, 2, 384, 240, 240, 240, 240,,, -3, 4, 1, 4, 3, 3, 3, 3, 128, 240, 240, 240, 240,,, -3, 4, 1, 4, 3, 3, 3, 3, 256, 240, 240, 240, 240,,, -3, 4, 1, 4, 3, 3, 3, 3, 384, 240, 240, 240, 240,,, -3, 4, 2, 1, 1, 1, 1, 1, 128, 131, 131, 131, 88,,, -3, 4, 2, 1, 1, 1, 1, 1, 256, 131, 131, 131, 88,,, -3, 4, 2, 1, 1, 1, 1, 1, 384, 131, 131, 131, 88,,, -3, 4, 2, 1, 2, 2, 1, 1, 128, 131, 131, 121, 88,,, -3, 4, 2, 1, 2, 2, 1, 1, 256, 131, 131, 121, 88,,, -3, 4, 2, 1, 2, 2, 1, 1, 384, 131, 131, 121, 88,,, -3, 4, 2, 1, 2, 2, 1, 2, 128, 131, 131, 121, 88,,, -3, 4, 2, 1, 2, 2, 1, 2, 256, 131, 131, 121, 88,,, -3, 4, 2, 1, 2, 2, 1, 2, 384, 131, 131, 121, 88,,, -3, 4, 2, 1, 2, 2, 2, 1, 128, 131, 131, 121, 88,,, -3, 4, 2, 1, 2, 2, 2, 1, 256, 131, 131, 121, 88,,, -3, 4, 2, 1, 2, 2, 2, 1, 384, 131, 131, 121, 88,,, -3, 4, 2, 1, 2, 2, 2, 2, 128, 131, 131, 121, 88,,, -3, 4, 2, 1, 2, 2, 2, 2, 256, 131, 131, 121, 88,,, -3, 4, 2, 1, 2, 2, 2, 2, 384, 131, 131, 121, 88,,, -3, 4, 2, 1, 3, 3, 1, 1, 128, 131, 125, 113, 87,,, -3, 4, 2, 1, 3, 3, 1, 1, 256, 131, 125, 113, 87,,, -3, 4, 2, 1, 3, 3, 1, 1, 384, 131, 125, 113, 87,,, -3, 4, 2, 1, 3, 3, 1, 2, 128, 131, 125, 113, 87,,, -3, 4, 2, 1, 3, 3, 1, 2, 256, 131, 125, 113, 87,,, -3, 4, 2, 1, 3, 3, 1, 2, 384, 131, 125, 113, 87,,, -3, 4, 2, 1, 3, 3, 1, 3, 128, 131, 125, 113, 87,,, -3, 4, 2, 1, 3, 3, 1, 3, 256, 131, 125, 113, 87,,, -3, 4, 2, 1, 3, 3, 1, 3, 384, 131, 125, 113, 87,,, -3, 4, 2, 1, 3, 3, 2, 1, 128, 131, 125, 113, 87,,, -3, 4, 2, 1, 3, 3, 2, 1, 256, 131, 125, 113, 87,,, -3, 4, 2, 1, 3, 3, 2, 1, 384, 131, 125, 113, 87,,, -3, 4, 2, 1, 3, 3, 2, 2, 128, 131, 125, 113, 87,,, -3, 4, 2, 1, 3, 3, 2, 2, 256, 131, 125, 113, 87,,, -3, 4, 2, 1, 3, 3, 2, 2, 384, 131, 125, 113, 87,,, -3, 4, 2, 1, 3, 3, 2, 3, 128, 131, 125, 113, 87,,, -3, 4, 2, 1, 3, 3, 2, 3, 256, 131, 125, 113, 87,,, -3, 4, 2, 1, 3, 3, 2, 3, 384, 131, 125, 113, 87,,, -3, 4, 2, 1, 3, 3, 3, 1, 128, 131, 125, 113, 87,,, -3, 4, 2, 1, 3, 3, 3, 1, 256, 131, 125, 113, 87,,, -3, 4, 2, 1, 3, 3, 3, 1, 384, 131, 125, 113, 87,,, -3, 4, 2, 1, 3, 3, 3, 2, 128, 131, 125, 113, 87,,, -3, 4, 2, 1, 3, 3, 3, 2, 256, 131, 125, 113, 87,,, -3, 4, 2, 1, 3, 3, 3, 2, 384, 131, 125, 113, 87,,, -3, 4, 2, 1, 3, 3, 3, 3, 128, 131, 125, 113, 87,,, -3, 4, 2, 1, 3, 3, 3, 3, 256, 131, 125, 113, 87,,, -3, 4, 2, 1, 3, 3, 3, 3, 384, 131, 125, 113, 87,,, -3, 4, 2, 2, 1, 1, 1, 1, 128, 240, 240, 240, 173,,, -3, 4, 2, 2, 1, 1, 1, 1, 256, 240, 240, 240, 173,,, -3, 4, 2, 2, 1, 1, 1, 1, 384, 240, 240, 240, 173,,, -3, 4, 2, 2, 2, 2, 1, 1, 128, 240, 240, 239, 173,,, -3, 4, 2, 2, 2, 2, 1, 1, 256, 240, 240, 239, 173,,, -3, 4, 2, 2, 2, 2, 1, 1, 384, 240, 240, 239, 173,,, -3, 4, 2, 2, 2, 2, 1, 2, 128, 240, 240, 239, 173,,, -3, 4, 2, 2, 2, 2, 1, 2, 256, 240, 240, 239, 173,,, -3, 4, 2, 2, 2, 2, 1, 2, 384, 240, 240, 239, 173,,, -3, 4, 2, 2, 2, 2, 2, 1, 128, 240, 240, 239, 173,,, -3, 4, 2, 2, 2, 2, 2, 1, 256, 240, 240, 239, 173,,, -3, 4, 2, 2, 2, 2, 2, 1, 384, 240, 240, 239, 173,,, -3, 4, 2, 2, 2, 2, 2, 2, 128, 240, 240, 239, 173,,, -3, 4, 2, 2, 2, 2, 2, 2, 256, 240, 240, 239, 173,,, -3, 4, 2, 2, 2, 2, 2, 2, 384, 240, 240, 239, 173,,, -3, 4, 2, 2, 3, 3, 1, 1, 128, 240, 240, 223, 171,,, -3, 4, 2, 2, 3, 3, 1, 1, 256, 240, 240, 223, 171,,, -3, 4, 2, 2, 3, 3, 1, 1, 384, 240, 240, 223, 171,,, -3, 4, 2, 2, 3, 3, 1, 2, 128, 240, 240, 223, 171,,, -3, 4, 2, 2, 3, 3, 1, 2, 256, 240, 240, 223, 171,,, -3, 4, 2, 2, 3, 3, 1, 2, 384, 240, 240, 223, 171,,, -3, 4, 2, 2, 3, 3, 1, 3, 128, 240, 240, 223, 171,,, -3, 4, 2, 2, 3, 3, 1, 3, 256, 240, 240, 223, 171,,, -3, 4, 2, 2, 3, 3, 1, 3, 384, 240, 240, 223, 171,,, -3, 4, 2, 2, 3, 3, 2, 1, 128, 240, 240, 223, 171,,, -3, 4, 2, 2, 3, 3, 2, 1, 256, 240, 240, 223, 171,,, -3, 4, 2, 2, 3, 3, 2, 1, 384, 240, 240, 223, 171,,, -3, 4, 2, 2, 3, 3, 2, 2, 128, 240, 240, 223, 171,,, -3, 4, 2, 2, 3, 3, 2, 2, 256, 240, 240, 223, 171,,, -3, 4, 2, 2, 3, 3, 2, 2, 384, 240, 240, 223, 171,,, -3, 4, 2, 2, 3, 3, 2, 3, 128, 240, 240, 223, 171,,, -3, 4, 2, 2, 3, 3, 2, 3, 256, 240, 240, 223, 171,,, -3, 4, 2, 2, 3, 3, 2, 3, 384, 240, 240, 223, 171,,, -3, 4, 2, 2, 3, 3, 3, 1, 128, 240, 240, 223, 171,,, -3, 4, 2, 2, 3, 3, 3, 1, 256, 240, 240, 223, 171,,, -3, 4, 2, 2, 3, 3, 3, 1, 384, 240, 240, 223, 171,,, -3, 4, 2, 2, 3, 3, 3, 2, 128, 240, 240, 223, 171,,, -3, 4, 2, 2, 3, 3, 3, 2, 256, 240, 240, 223, 171,,, -3, 4, 2, 2, 3, 3, 3, 2, 384, 240, 240, 223, 171,,, -3, 4, 2, 2, 3, 3, 3, 3, 128, 240, 240, 223, 171,,, -3, 4, 2, 2, 3, 3, 3, 3, 256, 240, 240, 223, 171,,, -3, 4, 2, 2, 3, 3, 3, 3, 384, 240, 240, 223, 171,,, -3, 4, 2, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 4, 2, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 4, 2, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 4, 2, 3, 2, 2, 1, 1, 128, 240, 240, 240, 240,,, -3, 4, 2, 3, 2, 2, 1, 1, 256, 240, 240, 240, 240,,, -3, 4, 2, 3, 2, 2, 1, 1, 384, 240, 240, 240, 240,,, -3, 4, 2, 3, 2, 2, 1, 2, 128, 240, 240, 240, 240,,, -3, 4, 2, 3, 2, 2, 1, 2, 256, 240, 240, 240, 240,,, -3, 4, 2, 3, 2, 2, 1, 2, 384, 240, 240, 240, 240,,, -3, 4, 2, 3, 2, 2, 2, 1, 128, 240, 240, 240, 240,,, -3, 4, 2, 3, 2, 2, 2, 1, 256, 240, 240, 240, 240,,, -3, 4, 2, 3, 2, 2, 2, 1, 384, 240, 240, 240, 240,,, -3, 4, 2, 3, 2, 2, 2, 2, 128, 240, 240, 240, 240,,, -3, 4, 2, 3, 2, 2, 2, 2, 256, 240, 240, 240, 240,,, -3, 4, 2, 3, 2, 2, 2, 2, 384, 240, 240, 240, 240,,, -3, 4, 2, 3, 3, 3, 1, 1, 128, 240, 240, 240, 240,,, -3, 4, 2, 3, 3, 3, 1, 1, 256, 240, 240, 240, 240,,, -3, 4, 2, 3, 3, 3, 1, 1, 384, 240, 240, 240, 240,,, -3, 4, 2, 3, 3, 3, 1, 2, 128, 240, 240, 240, 240,,, -3, 4, 2, 3, 3, 3, 1, 2, 256, 240, 240, 240, 240,,, -3, 4, 2, 3, 3, 3, 1, 2, 384, 240, 240, 240, 240,,, -3, 4, 2, 3, 3, 3, 1, 3, 128, 240, 240, 240, 240,,, -3, 4, 2, 3, 3, 3, 1, 3, 256, 240, 240, 240, 240,,, -3, 4, 2, 3, 3, 3, 1, 3, 384, 240, 240, 240, 240,,, -3, 4, 2, 3, 3, 3, 2, 1, 128, 240, 240, 240, 240,,, -3, 4, 2, 3, 3, 3, 2, 1, 256, 240, 240, 240, 240,,, -3, 4, 2, 3, 3, 3, 2, 1, 384, 240, 240, 240, 240,,, -3, 4, 2, 3, 3, 3, 2, 2, 128, 240, 240, 240, 240,,, -3, 4, 2, 3, 3, 3, 2, 2, 256, 240, 240, 240, 240,,, -3, 4, 2, 3, 3, 3, 2, 2, 384, 240, 240, 240, 240,,, -3, 4, 2, 3, 3, 3, 2, 3, 128, 240, 240, 240, 240,,, -3, 4, 2, 3, 3, 3, 2, 3, 256, 240, 240, 240, 240,,, -3, 4, 2, 3, 3, 3, 2, 3, 384, 240, 240, 240, 240,,, -3, 4, 2, 3, 3, 3, 3, 1, 128, 240, 240, 240, 240,,, -3, 4, 2, 3, 3, 3, 3, 1, 256, 240, 240, 240, 240,,, -3, 4, 2, 3, 3, 3, 3, 1, 384, 240, 240, 240, 240,,, -3, 4, 2, 3, 3, 3, 3, 2, 128, 240, 240, 240, 240,,, -3, 4, 2, 3, 3, 3, 3, 2, 256, 240, 240, 240, 240,,, -3, 4, 2, 3, 3, 3, 3, 2, 384, 240, 240, 240, 240,,, -3, 4, 2, 3, 3, 3, 3, 3, 128, 240, 240, 240, 240,,, -3, 4, 2, 3, 3, 3, 3, 3, 256, 240, 240, 240, 240,,, -3, 4, 2, 3, 3, 3, 3, 3, 384, 240, 240, 240, 240,,, -3, 4, 2, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 4, 2, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 4, 2, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 4, 2, 4, 2, 2, 1, 1, 128, 240, 240, 240, 240,,, -3, 4, 2, 4, 2, 2, 1, 1, 256, 240, 240, 240, 240,,, -3, 4, 2, 4, 2, 2, 1, 1, 384, 240, 240, 240, 240,,, -3, 4, 2, 4, 2, 2, 1, 2, 128, 240, 240, 240, 240,,, -3, 4, 2, 4, 2, 2, 1, 2, 256, 240, 240, 240, 240,,, -3, 4, 2, 4, 2, 2, 1, 2, 384, 240, 240, 240, 240,,, -3, 4, 2, 4, 2, 2, 2, 1, 128, 240, 240, 240, 240,,, -3, 4, 2, 4, 2, 2, 2, 1, 256, 240, 240, 240, 240,,, -3, 4, 2, 4, 2, 2, 2, 1, 384, 240, 240, 240, 240,,, -3, 4, 2, 4, 2, 2, 2, 2, 128, 240, 240, 240, 240,,, -3, 4, 2, 4, 2, 2, 2, 2, 256, 240, 240, 240, 240,,, -3, 4, 2, 4, 2, 2, 2, 2, 384, 240, 240, 240, 240,,, -3, 4, 2, 4, 3, 3, 1, 1, 128, 240, 240, 240, 240,,, -3, 4, 2, 4, 3, 3, 1, 1, 256, 240, 240, 240, 240,,, -3, 4, 2, 4, 3, 3, 1, 1, 384, 240, 240, 240, 240,,, -3, 4, 2, 4, 3, 3, 1, 2, 128, 240, 240, 240, 240,,, -3, 4, 2, 4, 3, 3, 1, 2, 256, 240, 240, 240, 240,,, -3, 4, 2, 4, 3, 3, 1, 2, 384, 240, 240, 240, 240,,, -3, 4, 2, 4, 3, 3, 1, 3, 128, 240, 240, 240, 240,,, -3, 4, 2, 4, 3, 3, 1, 3, 256, 240, 240, 240, 240,,, -3, 4, 2, 4, 3, 3, 1, 3, 384, 240, 240, 240, 240,,, -3, 4, 2, 4, 3, 3, 2, 1, 128, 240, 240, 240, 240,,, -3, 4, 2, 4, 3, 3, 2, 1, 256, 240, 240, 240, 240,,, -3, 4, 2, 4, 3, 3, 2, 1, 384, 240, 240, 240, 240,,, -3, 4, 2, 4, 3, 3, 2, 2, 128, 240, 240, 240, 240,,, -3, 4, 2, 4, 3, 3, 2, 2, 256, 240, 240, 240, 240,,, -3, 4, 2, 4, 3, 3, 2, 2, 384, 240, 240, 240, 240,,, -3, 4, 2, 4, 3, 3, 2, 3, 128, 240, 240, 240, 240,,, -3, 4, 2, 4, 3, 3, 2, 3, 256, 240, 240, 240, 240,,, -3, 4, 2, 4, 3, 3, 2, 3, 384, 240, 240, 240, 240,,, -3, 4, 2, 4, 3, 3, 3, 1, 128, 240, 240, 240, 240,,, -3, 4, 2, 4, 3, 3, 3, 1, 256, 240, 240, 240, 240,,, -3, 4, 2, 4, 3, 3, 3, 1, 384, 240, 240, 240, 240,,, -3, 4, 2, 4, 3, 3, 3, 2, 128, 240, 240, 240, 240,,, -3, 4, 2, 4, 3, 3, 3, 2, 256, 240, 240, 240, 240,,, -3, 4, 2, 4, 3, 3, 3, 2, 384, 240, 240, 240, 240,,, -3, 4, 2, 4, 3, 3, 3, 3, 128, 240, 240, 240, 240,,, -3, 4, 2, 4, 3, 3, 3, 3, 256, 240, 240, 240, 240,,, -3, 4, 2, 4, 3, 3, 3, 3, 384, 240, 240, 240, 240,,, -3, 4, 3, 1, 1, 1, 1, 1, 128, 131, 131, 131, 88,,, -3, 4, 3, 1, 1, 1, 1, 1, 256, 131, 131, 131, 88,,, -3, 4, 3, 1, 1, 1, 1, 1, 384, 131, 131, 131, 88,,, -3, 4, 3, 1, 2, 2, 1, 1, 128, 131, 131, 121, 88,,, -3, 4, 3, 1, 2, 2, 1, 1, 256, 131, 131, 121, 88,,, -3, 4, 3, 1, 2, 2, 1, 1, 384, 131, 131, 121, 88,,, -3, 4, 3, 1, 2, 2, 1, 2, 128, 131, 131, 121, 88,,, -3, 4, 3, 1, 2, 2, 1, 2, 256, 131, 131, 121, 88,,, -3, 4, 3, 1, 2, 2, 1, 2, 384, 131, 131, 121, 88,,, -3, 4, 3, 1, 2, 2, 2, 1, 128, 131, 131, 121, 88,,, -3, 4, 3, 1, 2, 2, 2, 1, 256, 131, 131, 121, 88,,, -3, 4, 3, 1, 2, 2, 2, 1, 384, 131, 131, 121, 88,,, -3, 4, 3, 1, 2, 2, 2, 2, 128, 131, 131, 121, 88,,, -3, 4, 3, 1, 2, 2, 2, 2, 256, 131, 131, 121, 88,,, -3, 4, 3, 1, 2, 2, 2, 2, 384, 131, 131, 121, 88,,, -3, 4, 3, 1, 3, 3, 1, 1, 128, 131, 125, 113, 87,,, -3, 4, 3, 1, 3, 3, 1, 1, 256, 131, 125, 113, 87,,, -3, 4, 3, 1, 3, 3, 1, 1, 384, 131, 125, 113, 87,,, -3, 4, 3, 1, 3, 3, 1, 2, 128, 131, 125, 113, 87,,, -3, 4, 3, 1, 3, 3, 1, 2, 256, 131, 125, 113, 87,,, -3, 4, 3, 1, 3, 3, 1, 2, 384, 131, 125, 113, 87,,, -3, 4, 3, 1, 3, 3, 1, 3, 128, 131, 125, 113, 87,,, -3, 4, 3, 1, 3, 3, 1, 3, 256, 131, 125, 113, 87,,, -3, 4, 3, 1, 3, 3, 1, 3, 384, 131, 125, 113, 87,,, -3, 4, 3, 1, 3, 3, 2, 1, 128, 131, 125, 113, 87,,, -3, 4, 3, 1, 3, 3, 2, 1, 256, 131, 125, 113, 87,,, -3, 4, 3, 1, 3, 3, 2, 1, 384, 131, 125, 113, 87,,, -3, 4, 3, 1, 3, 3, 2, 2, 128, 131, 125, 113, 87,,, -3, 4, 3, 1, 3, 3, 2, 2, 256, 131, 125, 113, 87,,, -3, 4, 3, 1, 3, 3, 2, 2, 384, 131, 125, 113, 87,,, -3, 4, 3, 1, 3, 3, 2, 3, 128, 131, 125, 113, 87,,, -3, 4, 3, 1, 3, 3, 2, 3, 256, 131, 125, 113, 87,,, -3, 4, 3, 1, 3, 3, 2, 3, 384, 131, 125, 113, 87,,, -3, 4, 3, 1, 3, 3, 3, 1, 128, 131, 125, 113, 87,,, -3, 4, 3, 1, 3, 3, 3, 1, 256, 131, 125, 113, 87,,, -3, 4, 3, 1, 3, 3, 3, 1, 384, 131, 125, 113, 87,,, -3, 4, 3, 1, 3, 3, 3, 2, 128, 131, 125, 113, 87,,, -3, 4, 3, 1, 3, 3, 3, 2, 256, 131, 125, 113, 87,,, -3, 4, 3, 1, 3, 3, 3, 2, 384, 131, 125, 113, 87,,, -3, 4, 3, 1, 3, 3, 3, 3, 128, 131, 125, 113, 87,,, -3, 4, 3, 1, 3, 3, 3, 3, 256, 131, 125, 113, 87,,, -3, 4, 3, 1, 3, 3, 3, 3, 384, 131, 125, 113, 87,,, -3, 4, 3, 2, 1, 1, 1, 1, 128, 240, 240, 240, 173,,, -3, 4, 3, 2, 1, 1, 1, 1, 256, 240, 240, 240, 173,,, -3, 4, 3, 2, 1, 1, 1, 1, 384, 240, 240, 240, 173,,, -3, 4, 3, 2, 2, 2, 1, 1, 128, 240, 240, 239, 173,,, -3, 4, 3, 2, 2, 2, 1, 1, 256, 240, 240, 239, 173,,, -3, 4, 3, 2, 2, 2, 1, 1, 384, 240, 240, 239, 173,,, -3, 4, 3, 2, 2, 2, 1, 2, 128, 240, 240, 239, 173,,, -3, 4, 3, 2, 2, 2, 1, 2, 256, 240, 240, 239, 173,,, -3, 4, 3, 2, 2, 2, 1, 2, 384, 240, 240, 239, 173,,, -3, 4, 3, 2, 2, 2, 2, 1, 128, 240, 240, 239, 173,,, -3, 4, 3, 2, 2, 2, 2, 1, 256, 240, 240, 239, 173,,, -3, 4, 3, 2, 2, 2, 2, 1, 384, 240, 240, 239, 173,,, -3, 4, 3, 2, 2, 2, 2, 2, 128, 240, 240, 239, 173,,, -3, 4, 3, 2, 2, 2, 2, 2, 256, 240, 240, 239, 173,,, -3, 4, 3, 2, 2, 2, 2, 2, 384, 240, 240, 239, 173,,, -3, 4, 3, 2, 3, 3, 1, 1, 128, 240, 240, 223, 171,,, -3, 4, 3, 2, 3, 3, 1, 1, 256, 240, 240, 223, 171,,, -3, 4, 3, 2, 3, 3, 1, 1, 384, 240, 240, 223, 171,,, -3, 4, 3, 2, 3, 3, 1, 2, 128, 240, 240, 223, 171,,, -3, 4, 3, 2, 3, 3, 1, 2, 256, 240, 240, 223, 171,,, -3, 4, 3, 2, 3, 3, 1, 2, 384, 240, 240, 223, 171,,, -3, 4, 3, 2, 3, 3, 1, 3, 128, 240, 240, 223, 171,,, -3, 4, 3, 2, 3, 3, 1, 3, 256, 240, 240, 223, 171,,, -3, 4, 3, 2, 3, 3, 1, 3, 384, 240, 240, 223, 171,,, -3, 4, 3, 2, 3, 3, 2, 1, 128, 240, 240, 223, 171,,, -3, 4, 3, 2, 3, 3, 2, 1, 256, 240, 240, 223, 171,,, -3, 4, 3, 2, 3, 3, 2, 1, 384, 240, 240, 223, 171,,, -3, 4, 3, 2, 3, 3, 2, 2, 128, 240, 240, 223, 171,,, -3, 4, 3, 2, 3, 3, 2, 2, 256, 240, 240, 223, 171,,, -3, 4, 3, 2, 3, 3, 2, 2, 384, 240, 240, 223, 171,,, -3, 4, 3, 2, 3, 3, 2, 3, 128, 240, 240, 223, 171,,, -3, 4, 3, 2, 3, 3, 2, 3, 256, 240, 240, 223, 171,,, -3, 4, 3, 2, 3, 3, 2, 3, 384, 240, 240, 223, 171,,, -3, 4, 3, 2, 3, 3, 3, 1, 128, 240, 240, 223, 171,,, -3, 4, 3, 2, 3, 3, 3, 1, 256, 240, 240, 223, 171,,, -3, 4, 3, 2, 3, 3, 3, 1, 384, 240, 240, 223, 171,,, -3, 4, 3, 2, 3, 3, 3, 2, 128, 240, 240, 223, 171,,, -3, 4, 3, 2, 3, 3, 3, 2, 256, 240, 240, 223, 171,,, -3, 4, 3, 2, 3, 3, 3, 2, 384, 240, 240, 223, 171,,, -3, 4, 3, 2, 3, 3, 3, 3, 128, 240, 240, 223, 171,,, -3, 4, 3, 2, 3, 3, 3, 3, 256, 240, 240, 223, 171,,, -3, 4, 3, 2, 3, 3, 3, 3, 384, 240, 240, 223, 171,,, -3, 4, 3, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 4, 3, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 4, 3, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 4, 3, 3, 2, 2, 1, 1, 128, 240, 240, 240, 240,,, -3, 4, 3, 3, 2, 2, 1, 1, 256, 240, 240, 240, 240,,, -3, 4, 3, 3, 2, 2, 1, 1, 384, 240, 240, 240, 240,,, -3, 4, 3, 3, 2, 2, 1, 2, 128, 240, 240, 240, 240,,, -3, 4, 3, 3, 2, 2, 1, 2, 256, 240, 240, 240, 240,,, -3, 4, 3, 3, 2, 2, 1, 2, 384, 240, 240, 240, 240,,, -3, 4, 3, 3, 2, 2, 2, 1, 128, 240, 240, 240, 240,,, -3, 4, 3, 3, 2, 2, 2, 1, 256, 240, 240, 240, 240,,, -3, 4, 3, 3, 2, 2, 2, 1, 384, 240, 240, 240, 240,,, -3, 4, 3, 3, 2, 2, 2, 2, 128, 240, 240, 240, 240,,, -3, 4, 3, 3, 2, 2, 2, 2, 256, 240, 240, 240, 240,,, -3, 4, 3, 3, 2, 2, 2, 2, 384, 240, 240, 240, 240,,, -3, 4, 3, 3, 3, 3, 1, 1, 128, 240, 240, 240, 240,,, -3, 4, 3, 3, 3, 3, 1, 1, 256, 240, 240, 240, 240,,, -3, 4, 3, 3, 3, 3, 1, 1, 384, 240, 240, 240, 240,,, -3, 4, 3, 3, 3, 3, 1, 2, 128, 240, 240, 240, 240,,, -3, 4, 3, 3, 3, 3, 1, 2, 256, 240, 240, 240, 240,,, -3, 4, 3, 3, 3, 3, 1, 2, 384, 240, 240, 240, 240,,, -3, 4, 3, 3, 3, 3, 1, 3, 128, 240, 240, 240, 240,,, -3, 4, 3, 3, 3, 3, 1, 3, 256, 240, 240, 240, 240,,, -3, 4, 3, 3, 3, 3, 1, 3, 384, 240, 240, 240, 240,,, -3, 4, 3, 3, 3, 3, 2, 1, 128, 240, 240, 240, 240,,, -3, 4, 3, 3, 3, 3, 2, 1, 256, 240, 240, 240, 240,,, -3, 4, 3, 3, 3, 3, 2, 1, 384, 240, 240, 240, 240,,, -3, 4, 3, 3, 3, 3, 2, 2, 128, 240, 240, 240, 240,,, -3, 4, 3, 3, 3, 3, 2, 2, 256, 240, 240, 240, 240,,, -3, 4, 3, 3, 3, 3, 2, 2, 384, 240, 240, 240, 240,,, -3, 4, 3, 3, 3, 3, 2, 3, 128, 240, 240, 240, 240,,, -3, 4, 3, 3, 3, 3, 2, 3, 256, 240, 240, 240, 240,,, -3, 4, 3, 3, 3, 3, 2, 3, 384, 240, 240, 240, 240,,, -3, 4, 3, 3, 3, 3, 3, 1, 128, 240, 240, 240, 240,,, -3, 4, 3, 3, 3, 3, 3, 1, 256, 240, 240, 240, 240,,, -3, 4, 3, 3, 3, 3, 3, 1, 384, 240, 240, 240, 240,,, -3, 4, 3, 3, 3, 3, 3, 2, 128, 240, 240, 240, 240,,, -3, 4, 3, 3, 3, 3, 3, 2, 256, 240, 240, 240, 240,,, -3, 4, 3, 3, 3, 3, 3, 2, 384, 240, 240, 240, 240,,, -3, 4, 3, 3, 3, 3, 3, 3, 128, 240, 240, 240, 240,,, -3, 4, 3, 3, 3, 3, 3, 3, 256, 240, 240, 240, 240,,, -3, 4, 3, 3, 3, 3, 3, 3, 384, 240, 240, 240, 240,,, -3, 4, 3, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 4, 3, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 4, 3, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 4, 3, 4, 2, 2, 1, 1, 128, 240, 240, 240, 240,,, -3, 4, 3, 4, 2, 2, 1, 1, 256, 240, 240, 240, 240,,, -3, 4, 3, 4, 2, 2, 1, 1, 384, 240, 240, 240, 240,,, -3, 4, 3, 4, 2, 2, 1, 2, 128, 240, 240, 240, 240,,, -3, 4, 3, 4, 2, 2, 1, 2, 256, 240, 240, 240, 240,,, -3, 4, 3, 4, 2, 2, 1, 2, 384, 240, 240, 240, 240,,, -3, 4, 3, 4, 2, 2, 2, 1, 128, 240, 240, 240, 240,,, -3, 4, 3, 4, 2, 2, 2, 1, 256, 240, 240, 240, 240,,, -3, 4, 3, 4, 2, 2, 2, 1, 384, 240, 240, 240, 240,,, -3, 4, 3, 4, 2, 2, 2, 2, 128, 240, 240, 240, 240,,, -3, 4, 3, 4, 2, 2, 2, 2, 256, 240, 240, 240, 240,,, -3, 4, 3, 4, 2, 2, 2, 2, 384, 240, 240, 240, 240,,, -3, 4, 3, 4, 3, 3, 1, 1, 128, 240, 240, 240, 240,,, -3, 4, 3, 4, 3, 3, 1, 1, 256, 240, 240, 240, 240,,, -3, 4, 3, 4, 3, 3, 1, 1, 384, 240, 240, 240, 240,,, -3, 4, 3, 4, 3, 3, 1, 2, 128, 240, 240, 240, 240,,, -3, 4, 3, 4, 3, 3, 1, 2, 256, 240, 240, 240, 240,,, -3, 4, 3, 4, 3, 3, 1, 2, 384, 240, 240, 240, 240,,, -3, 4, 3, 4, 3, 3, 1, 3, 128, 240, 240, 240, 240,,, -3, 4, 3, 4, 3, 3, 1, 3, 256, 240, 240, 240, 240,,, -3, 4, 3, 4, 3, 3, 1, 3, 384, 240, 240, 240, 240,,, -3, 4, 3, 4, 3, 3, 2, 1, 128, 240, 240, 240, 240,,, -3, 4, 3, 4, 3, 3, 2, 1, 256, 240, 240, 240, 240,,, -3, 4, 3, 4, 3, 3, 2, 1, 384, 240, 240, 240, 240,,, -3, 4, 3, 4, 3, 3, 2, 2, 128, 240, 240, 240, 240,,, -3, 4, 3, 4, 3, 3, 2, 2, 256, 240, 240, 240, 240,,, -3, 4, 3, 4, 3, 3, 2, 2, 384, 240, 240, 240, 240,,, -3, 4, 3, 4, 3, 3, 2, 3, 128, 240, 240, 240, 240,,, -3, 4, 3, 4, 3, 3, 2, 3, 256, 240, 240, 240, 240,,, -3, 4, 3, 4, 3, 3, 2, 3, 384, 240, 240, 240, 240,,, -3, 4, 3, 4, 3, 3, 3, 1, 128, 240, 240, 240, 240,,, -3, 4, 3, 4, 3, 3, 3, 1, 256, 240, 240, 240, 240,,, -3, 4, 3, 4, 3, 3, 3, 1, 384, 240, 240, 240, 240,,, -3, 4, 3, 4, 3, 3, 3, 2, 128, 240, 240, 240, 240,,, -3, 4, 3, 4, 3, 3, 3, 2, 256, 240, 240, 240, 240,,, -3, 4, 3, 4, 3, 3, 3, 2, 384, 240, 240, 240, 240,,, -3, 4, 3, 4, 3, 3, 3, 3, 128, 240, 240, 240, 240,,, -3, 4, 3, 4, 3, 3, 3, 3, 256, 240, 240, 240, 240,,, -3, 4, 3, 4, 3, 3, 3, 3, 384, 240, 240, 240, 240,,, -3, 5, 1, 1, 1, 1, 1, 1, 128, 132, 132, 132, 89,,, -3, 5, 1, 1, 1, 1, 1, 1, 256, 132, 132, 132, 89,,, -3, 5, 1, 1, 1, 1, 1, 1, 384, 132, 132, 132, 89,,, -3, 5, 1, 1, 2, 2, 1, 1, 128, 132, 132, 115, 80,,, -3, 5, 1, 1, 2, 2, 1, 1, 256, 132, 132, 115, 80,,, -3, 5, 1, 1, 2, 2, 1, 1, 384, 132, 132, 115, 80,,, -3, 5, 1, 1, 2, 2, 1, 2, 128, 132, 132, 115, 80,,, -3, 5, 1, 1, 2, 2, 1, 2, 256, 132, 132, 115, 80,,, -3, 5, 1, 1, 2, 2, 1, 2, 384, 132, 132, 115, 80,,, -3, 5, 1, 1, 2, 2, 2, 1, 128, 132, 132, 115, 80,,, -3, 5, 1, 1, 2, 2, 2, 1, 256, 132, 132, 115, 80,,, -3, 5, 1, 1, 2, 2, 2, 1, 384, 132, 132, 115, 80,,, -3, 5, 1, 1, 2, 2, 2, 2, 128, 132, 132, 115, 80,,, -3, 5, 1, 1, 2, 2, 2, 2, 256, 132, 132, 115, 80,,, -3, 5, 1, 1, 2, 2, 2, 2, 384, 132, 132, 115, 80,,, -3, 5, 1, 1, 3, 3, 1, 1, 128, 132, 124, 108, 76,,, -3, 5, 1, 1, 3, 3, 1, 1, 256, 132, 124, 108, 76,,, -3, 5, 1, 1, 3, 3, 1, 1, 384, 132, 124, 108, 76,,, -3, 5, 1, 1, 3, 3, 1, 2, 128, 132, 124, 108, 76,,, -3, 5, 1, 1, 3, 3, 1, 2, 256, 132, 124, 108, 76,,, -3, 5, 1, 1, 3, 3, 1, 2, 384, 132, 124, 108, 76,,, -3, 5, 1, 1, 3, 3, 1, 3, 128, 132, 124, 108, 76,,, -3, 5, 1, 1, 3, 3, 1, 3, 256, 132, 124, 108, 76,,, -3, 5, 1, 1, 3, 3, 1, 3, 384, 132, 124, 108, 76,,, -3, 5, 1, 1, 3, 3, 2, 1, 128, 132, 124, 108, 76,,, -3, 5, 1, 1, 3, 3, 2, 1, 256, 132, 124, 108, 76,,, -3, 5, 1, 1, 3, 3, 2, 1, 384, 132, 124, 108, 76,,, -3, 5, 1, 1, 3, 3, 2, 2, 128, 132, 124, 108, 76,,, -3, 5, 1, 1, 3, 3, 2, 2, 256, 132, 124, 108, 76,,, -3, 5, 1, 1, 3, 3, 2, 2, 384, 132, 124, 108, 76,,, -3, 5, 1, 1, 3, 3, 2, 3, 128, 132, 124, 108, 76,,, -3, 5, 1, 1, 3, 3, 2, 3, 256, 132, 124, 108, 76,,, -3, 5, 1, 1, 3, 3, 2, 3, 384, 132, 124, 108, 76,,, -3, 5, 1, 1, 3, 3, 3, 1, 128, 132, 124, 108, 76,,, -3, 5, 1, 1, 3, 3, 3, 1, 256, 132, 124, 108, 76,,, -3, 5, 1, 1, 3, 3, 3, 1, 384, 132, 124, 108, 76,,, -3, 5, 1, 1, 3, 3, 3, 2, 128, 132, 124, 108, 76,,, -3, 5, 1, 1, 3, 3, 3, 2, 256, 132, 124, 108, 76,,, -3, 5, 1, 1, 3, 3, 3, 2, 384, 132, 124, 108, 76,,, -3, 5, 1, 1, 3, 3, 3, 3, 128, 132, 124, 108, 76,,, -3, 5, 1, 1, 3, 3, 3, 3, 256, 132, 124, 108, 76,,, -3, 5, 1, 1, 3, 3, 3, 3, 384, 132, 124, 108, 76,,, -3, 5, 1, 2, 1, 1, 1, 1, 128, 240, 240, 240, 174,,, -3, 5, 1, 2, 1, 1, 1, 1, 256, 240, 240, 240, 174,,, -3, 5, 1, 2, 1, 1, 1, 1, 384, 240, 240, 240, 174,,, -3, 5, 1, 2, 2, 2, 1, 1, 128, 240, 240, 226, 156,,, -3, 5, 1, 2, 2, 2, 1, 1, 256, 240, 240, 226, 156,,, -3, 5, 1, 2, 2, 2, 1, 1, 384, 240, 240, 226, 156,,, -3, 5, 1, 2, 2, 2, 1, 2, 128, 240, 240, 226, 156,,, -3, 5, 1, 2, 2, 2, 1, 2, 256, 240, 240, 226, 156,,, -3, 5, 1, 2, 2, 2, 1, 2, 384, 240, 240, 226, 156,,, -3, 5, 1, 2, 2, 2, 2, 1, 128, 240, 240, 226, 156,,, -3, 5, 1, 2, 2, 2, 2, 1, 256, 240, 240, 226, 156,,, -3, 5, 1, 2, 2, 2, 2, 1, 384, 240, 240, 226, 156,,, -3, 5, 1, 2, 2, 2, 2, 2, 128, 240, 240, 226, 156,,, -3, 5, 1, 2, 2, 2, 2, 2, 256, 240, 240, 226, 156,,, -3, 5, 1, 2, 2, 2, 2, 2, 384, 240, 240, 226, 156,,, -3, 5, 1, 2, 3, 3, 1, 1, 128, 240, 240, 212, 148,,, -3, 5, 1, 2, 3, 3, 1, 1, 256, 240, 240, 212, 148,,, -3, 5, 1, 2, 3, 3, 1, 1, 384, 240, 240, 212, 148,,, -3, 5, 1, 2, 3, 3, 1, 2, 128, 240, 240, 212, 148,,, -3, 5, 1, 2, 3, 3, 1, 2, 256, 240, 240, 212, 148,,, -3, 5, 1, 2, 3, 3, 1, 2, 384, 240, 240, 212, 148,,, -3, 5, 1, 2, 3, 3, 1, 3, 128, 240, 240, 212, 148,,, -3, 5, 1, 2, 3, 3, 1, 3, 256, 240, 240, 212, 148,,, -3, 5, 1, 2, 3, 3, 1, 3, 384, 240, 240, 212, 148,,, -3, 5, 1, 2, 3, 3, 2, 1, 128, 240, 240, 212, 148,,, -3, 5, 1, 2, 3, 3, 2, 1, 256, 240, 240, 212, 148,,, -3, 5, 1, 2, 3, 3, 2, 1, 384, 240, 240, 212, 148,,, -3, 5, 1, 2, 3, 3, 2, 2, 128, 240, 240, 212, 148,,, -3, 5, 1, 2, 3, 3, 2, 2, 256, 240, 240, 212, 148,,, -3, 5, 1, 2, 3, 3, 2, 2, 384, 240, 240, 212, 148,,, -3, 5, 1, 2, 3, 3, 2, 3, 128, 240, 240, 212, 148,,, -3, 5, 1, 2, 3, 3, 2, 3, 256, 240, 240, 212, 148,,, -3, 5, 1, 2, 3, 3, 2, 3, 384, 240, 240, 212, 148,,, -3, 5, 1, 2, 3, 3, 3, 1, 128, 240, 240, 212, 148,,, -3, 5, 1, 2, 3, 3, 3, 1, 256, 240, 240, 212, 148,,, -3, 5, 1, 2, 3, 3, 3, 1, 384, 240, 240, 212, 148,,, -3, 5, 1, 2, 3, 3, 3, 2, 128, 240, 240, 212, 148,,, -3, 5, 1, 2, 3, 3, 3, 2, 256, 240, 240, 212, 148,,, -3, 5, 1, 2, 3, 3, 3, 2, 384, 240, 240, 212, 148,,, -3, 5, 1, 2, 3, 3, 3, 3, 128, 240, 240, 212, 148,,, -3, 5, 1, 2, 3, 3, 3, 3, 256, 240, 240, 212, 148,,, -3, 5, 1, 2, 3, 3, 3, 3, 384, 240, 240, 212, 148,,, -3, 5, 1, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 5, 1, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 5, 1, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 5, 1, 3, 2, 2, 1, 1, 128, 240, 240, 240, 232,,, -3, 5, 1, 3, 2, 2, 1, 1, 256, 240, 240, 240, 232,,, -3, 5, 1, 3, 2, 2, 1, 1, 384, 240, 240, 240, 232,,, -3, 5, 1, 3, 2, 2, 1, 2, 128, 240, 240, 240, 232,,, -3, 5, 1, 3, 2, 2, 1, 2, 256, 240, 240, 240, 232,,, -3, 5, 1, 3, 2, 2, 1, 2, 384, 240, 240, 240, 232,,, -3, 5, 1, 3, 2, 2, 2, 1, 128, 240, 240, 240, 232,,, -3, 5, 1, 3, 2, 2, 2, 1, 256, 240, 240, 240, 232,,, -3, 5, 1, 3, 2, 2, 2, 1, 384, 240, 240, 240, 232,,, -3, 5, 1, 3, 2, 2, 2, 2, 128, 240, 240, 240, 232,,, -3, 5, 1, 3, 2, 2, 2, 2, 256, 240, 240, 240, 232,,, -3, 5, 1, 3, 2, 2, 2, 2, 384, 240, 240, 240, 232,,, -3, 5, 1, 3, 3, 3, 1, 1, 128, 240, 240, 240, 220,,, -3, 5, 1, 3, 3, 3, 1, 1, 256, 240, 240, 240, 220,,, -3, 5, 1, 3, 3, 3, 1, 1, 384, 240, 240, 240, 220,,, -3, 5, 1, 3, 3, 3, 1, 2, 128, 240, 240, 240, 220,,, -3, 5, 1, 3, 3, 3, 1, 2, 256, 240, 240, 240, 220,,, -3, 5, 1, 3, 3, 3, 1, 2, 384, 240, 240, 240, 220,,, -3, 5, 1, 3, 3, 3, 1, 3, 128, 240, 240, 240, 220,,, -3, 5, 1, 3, 3, 3, 1, 3, 256, 240, 240, 240, 220,,, -3, 5, 1, 3, 3, 3, 1, 3, 384, 240, 240, 240, 220,,, -3, 5, 1, 3, 3, 3, 2, 1, 128, 240, 240, 240, 220,,, -3, 5, 1, 3, 3, 3, 2, 1, 256, 240, 240, 240, 220,,, -3, 5, 1, 3, 3, 3, 2, 1, 384, 240, 240, 240, 220,,, -3, 5, 1, 3, 3, 3, 2, 2, 128, 240, 240, 240, 220,,, -3, 5, 1, 3, 3, 3, 2, 2, 256, 240, 240, 240, 220,,, -3, 5, 1, 3, 3, 3, 2, 2, 384, 240, 240, 240, 220,,, -3, 5, 1, 3, 3, 3, 2, 3, 128, 240, 240, 240, 220,,, -3, 5, 1, 3, 3, 3, 2, 3, 256, 240, 240, 240, 220,,, -3, 5, 1, 3, 3, 3, 2, 3, 384, 240, 240, 240, 220,,, -3, 5, 1, 3, 3, 3, 3, 1, 128, 240, 240, 240, 220,,, -3, 5, 1, 3, 3, 3, 3, 1, 256, 240, 240, 240, 220,,, -3, 5, 1, 3, 3, 3, 3, 1, 384, 240, 240, 240, 220,,, -3, 5, 1, 3, 3, 3, 3, 2, 128, 240, 240, 240, 220,,, -3, 5, 1, 3, 3, 3, 3, 2, 256, 240, 240, 240, 220,,, -3, 5, 1, 3, 3, 3, 3, 2, 384, 240, 240, 240, 220,,, -3, 5, 1, 3, 3, 3, 3, 3, 128, 240, 240, 240, 220,,, -3, 5, 1, 3, 3, 3, 3, 3, 256, 240, 240, 240, 220,,, -3, 5, 1, 3, 3, 3, 3, 3, 384, 240, 240, 240, 220,,, -3, 5, 1, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 5, 1, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 5, 1, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 5, 1, 4, 2, 2, 1, 1, 128, 240, 240, 240, 240,,, -3, 5, 1, 4, 2, 2, 1, 1, 256, 240, 240, 240, 240,,, -3, 5, 1, 4, 2, 2, 1, 1, 384, 240, 240, 240, 240,,, -3, 5, 1, 4, 2, 2, 1, 2, 128, 240, 240, 240, 240,,, -3, 5, 1, 4, 2, 2, 1, 2, 256, 240, 240, 240, 240,,, -3, 5, 1, 4, 2, 2, 1, 2, 384, 240, 240, 240, 240,,, -3, 5, 1, 4, 2, 2, 2, 1, 128, 240, 240, 240, 240,,, -3, 5, 1, 4, 2, 2, 2, 1, 256, 240, 240, 240, 240,,, -3, 5, 1, 4, 2, 2, 2, 1, 384, 240, 240, 240, 240,,, -3, 5, 1, 4, 2, 2, 2, 2, 128, 240, 240, 240, 240,,, -3, 5, 1, 4, 2, 2, 2, 2, 256, 240, 240, 240, 240,,, -3, 5, 1, 4, 2, 2, 2, 2, 384, 240, 240, 240, 240,,, -3, 5, 1, 4, 3, 3, 1, 1, 128, 240, 240, 240, 240,,, -3, 5, 1, 4, 3, 3, 1, 1, 256, 240, 240, 240, 240,,, -3, 5, 1, 4, 3, 3, 1, 1, 384, 240, 240, 240, 240,,, -3, 5, 1, 4, 3, 3, 1, 2, 128, 240, 240, 240, 240,,, -3, 5, 1, 4, 3, 3, 1, 2, 256, 240, 240, 240, 240,,, -3, 5, 1, 4, 3, 3, 1, 2, 384, 240, 240, 240, 240,,, -3, 5, 1, 4, 3, 3, 1, 3, 128, 240, 240, 240, 240,,, -3, 5, 1, 4, 3, 3, 1, 3, 256, 240, 240, 240, 240,,, -3, 5, 1, 4, 3, 3, 1, 3, 384, 240, 240, 240, 240,,, -3, 5, 1, 4, 3, 3, 2, 1, 128, 240, 240, 240, 240,,, -3, 5, 1, 4, 3, 3, 2, 1, 256, 240, 240, 240, 240,,, -3, 5, 1, 4, 3, 3, 2, 1, 384, 240, 240, 240, 240,,, -3, 5, 1, 4, 3, 3, 2, 2, 128, 240, 240, 240, 240,,, -3, 5, 1, 4, 3, 3, 2, 2, 256, 240, 240, 240, 240,,, -3, 5, 1, 4, 3, 3, 2, 2, 384, 240, 240, 240, 240,,, -3, 5, 1, 4, 3, 3, 2, 3, 128, 240, 240, 240, 240,,, -3, 5, 1, 4, 3, 3, 2, 3, 256, 240, 240, 240, 240,,, -3, 5, 1, 4, 3, 3, 2, 3, 384, 240, 240, 240, 240,,, -3, 5, 1, 4, 3, 3, 3, 1, 128, 240, 240, 240, 240,,, -3, 5, 1, 4, 3, 3, 3, 1, 256, 240, 240, 240, 240,,, -3, 5, 1, 4, 3, 3, 3, 1, 384, 240, 240, 240, 240,,, -3, 5, 1, 4, 3, 3, 3, 2, 128, 240, 240, 240, 240,,, -3, 5, 1, 4, 3, 3, 3, 2, 256, 240, 240, 240, 240,,, -3, 5, 1, 4, 3, 3, 3, 2, 384, 240, 240, 240, 240,,, -3, 5, 1, 4, 3, 3, 3, 3, 128, 240, 240, 240, 240,,, -3, 5, 1, 4, 3, 3, 3, 3, 256, 240, 240, 240, 240,,, -3, 5, 1, 4, 3, 3, 3, 3, 384, 240, 240, 240, 240,,, -3, 5, 1, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 5, 1, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 5, 1, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 5, 1, 5, 2, 2, 1, 1, 128, 240, 240, 240, 240,,, -3, 5, 1, 5, 2, 2, 1, 1, 256, 240, 240, 240, 240,,, -3, 5, 1, 5, 2, 2, 1, 1, 384, 240, 240, 240, 240,,, -3, 5, 1, 5, 2, 2, 1, 2, 128, 240, 240, 240, 240,,, -3, 5, 1, 5, 2, 2, 1, 2, 256, 240, 240, 240, 240,,, -3, 5, 1, 5, 2, 2, 1, 2, 384, 240, 240, 240, 240,,, -3, 5, 1, 5, 2, 2, 2, 1, 128, 240, 240, 240, 240,,, -3, 5, 1, 5, 2, 2, 2, 1, 256, 240, 240, 240, 240,,, -3, 5, 1, 5, 2, 2, 2, 1, 384, 240, 240, 240, 240,,, -3, 5, 1, 5, 2, 2, 2, 2, 128, 240, 240, 240, 240,,, -3, 5, 1, 5, 2, 2, 2, 2, 256, 240, 240, 240, 240,,, -3, 5, 1, 5, 2, 2, 2, 2, 384, 240, 240, 240, 240,,, -3, 5, 1, 5, 3, 3, 1, 1, 128, 240, 240, 240, 240,,, -3, 5, 1, 5, 3, 3, 1, 1, 256, 240, 240, 240, 240,,, -3, 5, 1, 5, 3, 3, 1, 1, 384, 240, 240, 240, 240,,, -3, 5, 1, 5, 3, 3, 1, 2, 128, 240, 240, 240, 240,,, -3, 5, 1, 5, 3, 3, 1, 2, 256, 240, 240, 240, 240,,, -3, 5, 1, 5, 3, 3, 1, 2, 384, 240, 240, 240, 240,,, -3, 5, 1, 5, 3, 3, 1, 3, 128, 240, 240, 240, 240,,, -3, 5, 1, 5, 3, 3, 1, 3, 256, 240, 240, 240, 240,,, -3, 5, 1, 5, 3, 3, 1, 3, 384, 240, 240, 240, 240,,, -3, 5, 1, 5, 3, 3, 2, 1, 128, 240, 240, 240, 240,,, -3, 5, 1, 5, 3, 3, 2, 1, 256, 240, 240, 240, 240,,, -3, 5, 1, 5, 3, 3, 2, 1, 384, 240, 240, 240, 240,,, -3, 5, 1, 5, 3, 3, 2, 2, 128, 240, 240, 240, 240,,, -3, 5, 1, 5, 3, 3, 2, 2, 256, 240, 240, 240, 240,,, -3, 5, 1, 5, 3, 3, 2, 2, 384, 240, 240, 240, 240,,, -3, 5, 1, 5, 3, 3, 2, 3, 128, 240, 240, 240, 240,,, -3, 5, 1, 5, 3, 3, 2, 3, 256, 240, 240, 240, 240,,, -3, 5, 1, 5, 3, 3, 2, 3, 384, 240, 240, 240, 240,,, -3, 5, 1, 5, 3, 3, 3, 1, 128, 240, 240, 240, 240,,, -3, 5, 1, 5, 3, 3, 3, 1, 256, 240, 240, 240, 240,,, -3, 5, 1, 5, 3, 3, 3, 1, 384, 240, 240, 240, 240,,, -3, 5, 1, 5, 3, 3, 3, 2, 128, 240, 240, 240, 240,,, -3, 5, 1, 5, 3, 3, 3, 2, 256, 240, 240, 240, 240,,, -3, 5, 1, 5, 3, 3, 3, 2, 384, 240, 240, 240, 240,,, -3, 5, 1, 5, 3, 3, 3, 3, 128, 240, 240, 240, 240,,, -3, 5, 1, 5, 3, 3, 3, 3, 256, 240, 240, 240, 240,,, -3, 5, 1, 5, 3, 3, 3, 3, 384, 240, 240, 240, 240,,, -3, 5, 2, 1, 1, 1, 1, 1, 128, 132, 132, 132, 89,,, -3, 5, 2, 1, 1, 1, 1, 1, 256, 132, 132, 132, 89,,, -3, 5, 2, 1, 1, 1, 1, 1, 384, 132, 132, 132, 89,,, -3, 5, 2, 1, 2, 2, 1, 1, 128, 132, 132, 115, 80,,, -3, 5, 2, 1, 2, 2, 1, 1, 256, 132, 132, 115, 80,,, -3, 5, 2, 1, 2, 2, 1, 1, 384, 132, 132, 115, 80,,, -3, 5, 2, 1, 2, 2, 1, 2, 128, 132, 132, 115, 80,,, -3, 5, 2, 1, 2, 2, 1, 2, 256, 132, 132, 115, 80,,, -3, 5, 2, 1, 2, 2, 1, 2, 384, 132, 132, 115, 80,,, -3, 5, 2, 1, 2, 2, 2, 1, 128, 132, 132, 115, 80,,, -3, 5, 2, 1, 2, 2, 2, 1, 256, 132, 132, 115, 80,,, -3, 5, 2, 1, 2, 2, 2, 1, 384, 132, 132, 115, 80,,, -3, 5, 2, 1, 2, 2, 2, 2, 128, 132, 132, 115, 80,,, -3, 5, 2, 1, 2, 2, 2, 2, 256, 132, 132, 115, 80,,, -3, 5, 2, 1, 2, 2, 2, 2, 384, 132, 132, 115, 80,,, -3, 5, 2, 1, 3, 3, 1, 1, 128, 132, 124, 108, 76,,, -3, 5, 2, 1, 3, 3, 1, 1, 256, 132, 124, 108, 76,,, -3, 5, 2, 1, 3, 3, 1, 1, 384, 132, 124, 108, 76,,, -3, 5, 2, 1, 3, 3, 1, 2, 128, 132, 124, 108, 76,,, -3, 5, 2, 1, 3, 3, 1, 2, 256, 132, 124, 108, 76,,, -3, 5, 2, 1, 3, 3, 1, 2, 384, 132, 124, 108, 76,,, -3, 5, 2, 1, 3, 3, 1, 3, 128, 132, 124, 108, 76,,, -3, 5, 2, 1, 3, 3, 1, 3, 256, 132, 124, 108, 76,,, -3, 5, 2, 1, 3, 3, 1, 3, 384, 132, 124, 108, 76,,, -3, 5, 2, 1, 3, 3, 2, 1, 128, 132, 124, 108, 76,,, -3, 5, 2, 1, 3, 3, 2, 1, 256, 132, 124, 108, 76,,, -3, 5, 2, 1, 3, 3, 2, 1, 384, 132, 124, 108, 76,,, -3, 5, 2, 1, 3, 3, 2, 2, 128, 132, 124, 108, 76,,, -3, 5, 2, 1, 3, 3, 2, 2, 256, 132, 124, 108, 76,,, -3, 5, 2, 1, 3, 3, 2, 2, 384, 132, 124, 108, 76,,, -3, 5, 2, 1, 3, 3, 2, 3, 128, 132, 124, 108, 76,,, -3, 5, 2, 1, 3, 3, 2, 3, 256, 132, 124, 108, 76,,, -3, 5, 2, 1, 3, 3, 2, 3, 384, 132, 124, 108, 76,,, -3, 5, 2, 1, 3, 3, 3, 1, 128, 132, 124, 108, 76,,, -3, 5, 2, 1, 3, 3, 3, 1, 256, 132, 124, 108, 76,,, -3, 5, 2, 1, 3, 3, 3, 1, 384, 132, 124, 108, 76,,, -3, 5, 2, 1, 3, 3, 3, 2, 128, 132, 124, 108, 76,,, -3, 5, 2, 1, 3, 3, 3, 2, 256, 132, 124, 108, 76,,, -3, 5, 2, 1, 3, 3, 3, 2, 384, 132, 124, 108, 76,,, -3, 5, 2, 1, 3, 3, 3, 3, 128, 132, 124, 108, 76,,, -3, 5, 2, 1, 3, 3, 3, 3, 256, 132, 124, 108, 76,,, -3, 5, 2, 1, 3, 3, 3, 3, 384, 132, 124, 108, 76,,, -3, 5, 2, 2, 1, 1, 1, 1, 128, 240, 240, 240, 174,,, -3, 5, 2, 2, 1, 1, 1, 1, 256, 240, 240, 240, 174,,, -3, 5, 2, 2, 1, 1, 1, 1, 384, 240, 240, 240, 174,,, -3, 5, 2, 2, 2, 2, 1, 1, 128, 240, 240, 226, 156,,, -3, 5, 2, 2, 2, 2, 1, 1, 256, 240, 240, 226, 156,,, -3, 5, 2, 2, 2, 2, 1, 1, 384, 240, 240, 226, 156,,, -3, 5, 2, 2, 2, 2, 1, 2, 128, 240, 240, 226, 156,,, -3, 5, 2, 2, 2, 2, 1, 2, 256, 240, 240, 226, 156,,, -3, 5, 2, 2, 2, 2, 1, 2, 384, 240, 240, 226, 156,,, -3, 5, 2, 2, 2, 2, 2, 1, 128, 240, 240, 226, 156,,, -3, 5, 2, 2, 2, 2, 2, 1, 256, 240, 240, 226, 156,,, -3, 5, 2, 2, 2, 2, 2, 1, 384, 240, 240, 226, 156,,, -3, 5, 2, 2, 2, 2, 2, 2, 128, 240, 240, 226, 156,,, -3, 5, 2, 2, 2, 2, 2, 2, 256, 240, 240, 226, 156,,, -3, 5, 2, 2, 2, 2, 2, 2, 384, 240, 240, 226, 156,,, -3, 5, 2, 2, 3, 3, 1, 1, 128, 240, 240, 212, 148,,, -3, 5, 2, 2, 3, 3, 1, 1, 256, 240, 240, 212, 148,,, -3, 5, 2, 2, 3, 3, 1, 1, 384, 240, 240, 212, 148,,, -3, 5, 2, 2, 3, 3, 1, 2, 128, 240, 240, 212, 148,,, -3, 5, 2, 2, 3, 3, 1, 2, 256, 240, 240, 212, 148,,, -3, 5, 2, 2, 3, 3, 1, 2, 384, 240, 240, 212, 148,,, -3, 5, 2, 2, 3, 3, 1, 3, 128, 240, 240, 212, 148,,, -3, 5, 2, 2, 3, 3, 1, 3, 256, 240, 240, 212, 148,,, -3, 5, 2, 2, 3, 3, 1, 3, 384, 240, 240, 212, 148,,, -3, 5, 2, 2, 3, 3, 2, 1, 128, 240, 240, 212, 148,,, -3, 5, 2, 2, 3, 3, 2, 1, 256, 240, 240, 212, 148,,, -3, 5, 2, 2, 3, 3, 2, 1, 384, 240, 240, 212, 148,,, -3, 5, 2, 2, 3, 3, 2, 2, 128, 240, 240, 212, 148,,, -3, 5, 2, 2, 3, 3, 2, 2, 256, 240, 240, 212, 148,,, -3, 5, 2, 2, 3, 3, 2, 2, 384, 240, 240, 212, 148,,, -3, 5, 2, 2, 3, 3, 2, 3, 128, 240, 240, 212, 148,,, -3, 5, 2, 2, 3, 3, 2, 3, 256, 240, 240, 212, 148,,, -3, 5, 2, 2, 3, 3, 2, 3, 384, 240, 240, 212, 148,,, -3, 5, 2, 2, 3, 3, 3, 1, 128, 240, 240, 212, 148,,, -3, 5, 2, 2, 3, 3, 3, 1, 256, 240, 240, 212, 148,,, -3, 5, 2, 2, 3, 3, 3, 1, 384, 240, 240, 212, 148,,, -3, 5, 2, 2, 3, 3, 3, 2, 128, 240, 240, 212, 148,,, -3, 5, 2, 2, 3, 3, 3, 2, 256, 240, 240, 212, 148,,, -3, 5, 2, 2, 3, 3, 3, 2, 384, 240, 240, 212, 148,,, -3, 5, 2, 2, 3, 3, 3, 3, 128, 240, 240, 212, 148,,, -3, 5, 2, 2, 3, 3, 3, 3, 256, 240, 240, 212, 148,,, -3, 5, 2, 2, 3, 3, 3, 3, 384, 240, 240, 212, 148,,, -3, 5, 2, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 5, 2, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 5, 2, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 5, 2, 3, 2, 2, 1, 1, 128, 240, 240, 240, 232,,, -3, 5, 2, 3, 2, 2, 1, 1, 256, 240, 240, 240, 232,,, -3, 5, 2, 3, 2, 2, 1, 1, 384, 240, 240, 240, 232,,, -3, 5, 2, 3, 2, 2, 1, 2, 128, 240, 240, 240, 232,,, -3, 5, 2, 3, 2, 2, 1, 2, 256, 240, 240, 240, 232,,, -3, 5, 2, 3, 2, 2, 1, 2, 384, 240, 240, 240, 232,,, -3, 5, 2, 3, 2, 2, 2, 1, 128, 240, 240, 240, 232,,, -3, 5, 2, 3, 2, 2, 2, 1, 256, 240, 240, 240, 232,,, -3, 5, 2, 3, 2, 2, 2, 1, 384, 240, 240, 240, 232,,, -3, 5, 2, 3, 2, 2, 2, 2, 128, 240, 240, 240, 232,,, -3, 5, 2, 3, 2, 2, 2, 2, 256, 240, 240, 240, 232,,, -3, 5, 2, 3, 2, 2, 2, 2, 384, 240, 240, 240, 232,,, -3, 5, 2, 3, 3, 3, 1, 1, 128, 240, 240, 240, 220,,, -3, 5, 2, 3, 3, 3, 1, 1, 256, 240, 240, 240, 220,,, -3, 5, 2, 3, 3, 3, 1, 1, 384, 240, 240, 240, 220,,, -3, 5, 2, 3, 3, 3, 1, 2, 128, 240, 240, 240, 220,,, -3, 5, 2, 3, 3, 3, 1, 2, 256, 240, 240, 240, 220,,, -3, 5, 2, 3, 3, 3, 1, 2, 384, 240, 240, 240, 220,,, -3, 5, 2, 3, 3, 3, 1, 3, 128, 240, 240, 240, 220,,, -3, 5, 2, 3, 3, 3, 1, 3, 256, 240, 240, 240, 220,,, -3, 5, 2, 3, 3, 3, 1, 3, 384, 240, 240, 240, 220,,, -3, 5, 2, 3, 3, 3, 2, 1, 128, 240, 240, 240, 220,,, -3, 5, 2, 3, 3, 3, 2, 1, 256, 240, 240, 240, 220,,, -3, 5, 2, 3, 3, 3, 2, 1, 384, 240, 240, 240, 220,,, -3, 5, 2, 3, 3, 3, 2, 2, 128, 240, 240, 240, 220,,, -3, 5, 2, 3, 3, 3, 2, 2, 256, 240, 240, 240, 220,,, -3, 5, 2, 3, 3, 3, 2, 2, 384, 240, 240, 240, 220,,, -3, 5, 2, 3, 3, 3, 2, 3, 128, 240, 240, 240, 220,,, -3, 5, 2, 3, 3, 3, 2, 3, 256, 240, 240, 240, 220,,, -3, 5, 2, 3, 3, 3, 2, 3, 384, 240, 240, 240, 220,,, -3, 5, 2, 3, 3, 3, 3, 1, 128, 240, 240, 240, 220,,, -3, 5, 2, 3, 3, 3, 3, 1, 256, 240, 240, 240, 220,,, -3, 5, 2, 3, 3, 3, 3, 1, 384, 240, 240, 240, 220,,, -3, 5, 2, 3, 3, 3, 3, 2, 128, 240, 240, 240, 220,,, -3, 5, 2, 3, 3, 3, 3, 2, 256, 240, 240, 240, 220,,, -3, 5, 2, 3, 3, 3, 3, 2, 384, 240, 240, 240, 220,,, -3, 5, 2, 3, 3, 3, 3, 3, 128, 240, 240, 240, 220,,, -3, 5, 2, 3, 3, 3, 3, 3, 256, 240, 240, 240, 220,,, -3, 5, 2, 3, 3, 3, 3, 3, 384, 240, 240, 240, 220,,, -3, 5, 2, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 5, 2, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 5, 2, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 5, 2, 4, 2, 2, 1, 1, 128, 240, 240, 240, 240,,, -3, 5, 2, 4, 2, 2, 1, 1, 256, 240, 240, 240, 240,,, -3, 5, 2, 4, 2, 2, 1, 1, 384, 240, 240, 240, 240,,, -3, 5, 2, 4, 2, 2, 1, 2, 128, 240, 240, 240, 240,,, -3, 5, 2, 4, 2, 2, 1, 2, 256, 240, 240, 240, 240,,, -3, 5, 2, 4, 2, 2, 1, 2, 384, 240, 240, 240, 240,,, -3, 5, 2, 4, 2, 2, 2, 1, 128, 240, 240, 240, 240,,, -3, 5, 2, 4, 2, 2, 2, 1, 256, 240, 240, 240, 240,,, -3, 5, 2, 4, 2, 2, 2, 1, 384, 240, 240, 240, 240,,, -3, 5, 2, 4, 2, 2, 2, 2, 128, 240, 240, 240, 240,,, -3, 5, 2, 4, 2, 2, 2, 2, 256, 240, 240, 240, 240,,, -3, 5, 2, 4, 2, 2, 2, 2, 384, 240, 240, 240, 240,,, -3, 5, 2, 4, 3, 3, 1, 1, 128, 240, 240, 240, 240,,, -3, 5, 2, 4, 3, 3, 1, 1, 256, 240, 240, 240, 240,,, -3, 5, 2, 4, 3, 3, 1, 1, 384, 240, 240, 240, 240,,, -3, 5, 2, 4, 3, 3, 1, 2, 128, 240, 240, 240, 240,,, -3, 5, 2, 4, 3, 3, 1, 2, 256, 240, 240, 240, 240,,, -3, 5, 2, 4, 3, 3, 1, 2, 384, 240, 240, 240, 240,,, -3, 5, 2, 4, 3, 3, 1, 3, 128, 240, 240, 240, 240,,, -3, 5, 2, 4, 3, 3, 1, 3, 256, 240, 240, 240, 240,,, -3, 5, 2, 4, 3, 3, 1, 3, 384, 240, 240, 240, 240,,, -3, 5, 2, 4, 3, 3, 2, 1, 128, 240, 240, 240, 240,,, -3, 5, 2, 4, 3, 3, 2, 1, 256, 240, 240, 240, 240,,, -3, 5, 2, 4, 3, 3, 2, 1, 384, 240, 240, 240, 240,,, -3, 5, 2, 4, 3, 3, 2, 2, 128, 240, 240, 240, 240,,, -3, 5, 2, 4, 3, 3, 2, 2, 256, 240, 240, 240, 240,,, -3, 5, 2, 4, 3, 3, 2, 2, 384, 240, 240, 240, 240,,, -3, 5, 2, 4, 3, 3, 2, 3, 128, 240, 240, 240, 240,,, -3, 5, 2, 4, 3, 3, 2, 3, 256, 240, 240, 240, 240,,, -3, 5, 2, 4, 3, 3, 2, 3, 384, 240, 240, 240, 240,,, -3, 5, 2, 4, 3, 3, 3, 1, 128, 240, 240, 240, 240,,, -3, 5, 2, 4, 3, 3, 3, 1, 256, 240, 240, 240, 240,,, -3, 5, 2, 4, 3, 3, 3, 1, 384, 240, 240, 240, 240,,, -3, 5, 2, 4, 3, 3, 3, 2, 128, 240, 240, 240, 240,,, -3, 5, 2, 4, 3, 3, 3, 2, 256, 240, 240, 240, 240,,, -3, 5, 2, 4, 3, 3, 3, 2, 384, 240, 240, 240, 240,,, -3, 5, 2, 4, 3, 3, 3, 3, 128, 240, 240, 240, 240,,, -3, 5, 2, 4, 3, 3, 3, 3, 256, 240, 240, 240, 240,,, -3, 5, 2, 4, 3, 3, 3, 3, 384, 240, 240, 240, 240,,, -3, 5, 2, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 5, 2, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 5, 2, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 5, 2, 5, 2, 2, 1, 1, 128, 240, 240, 240, 240,,, -3, 5, 2, 5, 2, 2, 1, 1, 256, 240, 240, 240, 240,,, -3, 5, 2, 5, 2, 2, 1, 1, 384, 240, 240, 240, 240,,, -3, 5, 2, 5, 2, 2, 1, 2, 128, 240, 240, 240, 240,,, -3, 5, 2, 5, 2, 2, 1, 2, 256, 240, 240, 240, 240,,, -3, 5, 2, 5, 2, 2, 1, 2, 384, 240, 240, 240, 240,,, -3, 5, 2, 5, 2, 2, 2, 1, 128, 240, 240, 240, 240,,, -3, 5, 2, 5, 2, 2, 2, 1, 256, 240, 240, 240, 240,,, -3, 5, 2, 5, 2, 2, 2, 1, 384, 240, 240, 240, 240,,, -3, 5, 2, 5, 2, 2, 2, 2, 128, 240, 240, 240, 240,,, -3, 5, 2, 5, 2, 2, 2, 2, 256, 240, 240, 240, 240,,, -3, 5, 2, 5, 2, 2, 2, 2, 384, 240, 240, 240, 240,,, -3, 5, 2, 5, 3, 3, 1, 1, 128, 240, 240, 240, 240,,, -3, 5, 2, 5, 3, 3, 1, 1, 256, 240, 240, 240, 240,,, -3, 5, 2, 5, 3, 3, 1, 1, 384, 240, 240, 240, 240,,, -3, 5, 2, 5, 3, 3, 1, 2, 128, 240, 240, 240, 240,,, -3, 5, 2, 5, 3, 3, 1, 2, 256, 240, 240, 240, 240,,, -3, 5, 2, 5, 3, 3, 1, 2, 384, 240, 240, 240, 240,,, -3, 5, 2, 5, 3, 3, 1, 3, 128, 240, 240, 240, 240,,, -3, 5, 2, 5, 3, 3, 1, 3, 256, 240, 240, 240, 240,,, -3, 5, 2, 5, 3, 3, 1, 3, 384, 240, 240, 240, 240,,, -3, 5, 2, 5, 3, 3, 2, 1, 128, 240, 240, 240, 240,,, -3, 5, 2, 5, 3, 3, 2, 1, 256, 240, 240, 240, 240,,, -3, 5, 2, 5, 3, 3, 2, 1, 384, 240, 240, 240, 240,,, -3, 5, 2, 5, 3, 3, 2, 2, 128, 240, 240, 240, 240,,, -3, 5, 2, 5, 3, 3, 2, 2, 256, 240, 240, 240, 240,,, -3, 5, 2, 5, 3, 3, 2, 2, 384, 240, 240, 240, 240,,, -3, 5, 2, 5, 3, 3, 2, 3, 128, 240, 240, 240, 240,,, -3, 5, 2, 5, 3, 3, 2, 3, 256, 240, 240, 240, 240,,, -3, 5, 2, 5, 3, 3, 2, 3, 384, 240, 240, 240, 240,,, -3, 5, 2, 5, 3, 3, 3, 1, 128, 240, 240, 240, 240,,, -3, 5, 2, 5, 3, 3, 3, 1, 256, 240, 240, 240, 240,,, -3, 5, 2, 5, 3, 3, 3, 1, 384, 240, 240, 240, 240,,, -3, 5, 2, 5, 3, 3, 3, 2, 128, 240, 240, 240, 240,,, -3, 5, 2, 5, 3, 3, 3, 2, 256, 240, 240, 240, 240,,, -3, 5, 2, 5, 3, 3, 3, 2, 384, 240, 240, 240, 240,,, -3, 5, 2, 5, 3, 3, 3, 3, 128, 240, 240, 240, 240,,, -3, 5, 2, 5, 3, 3, 3, 3, 256, 240, 240, 240, 240,,, -3, 5, 2, 5, 3, 3, 3, 3, 384, 240, 240, 240, 240,,, -3, 5, 3, 1, 1, 1, 1, 1, 128, 132, 132, 132, 89,,, -3, 5, 3, 1, 1, 1, 1, 1, 256, 132, 132, 132, 89,,, -3, 5, 3, 1, 1, 1, 1, 1, 384, 132, 132, 132, 89,,, -3, 5, 3, 1, 2, 2, 1, 1, 128, 132, 132, 115, 80,,, -3, 5, 3, 1, 2, 2, 1, 1, 256, 132, 132, 115, 80,,, -3, 5, 3, 1, 2, 2, 1, 1, 384, 132, 132, 115, 80,,, -3, 5, 3, 1, 2, 2, 1, 2, 128, 132, 132, 115, 80,,, -3, 5, 3, 1, 2, 2, 1, 2, 256, 132, 132, 115, 80,,, -3, 5, 3, 1, 2, 2, 1, 2, 384, 132, 132, 115, 80,,, -3, 5, 3, 1, 2, 2, 2, 1, 128, 132, 132, 115, 80,,, -3, 5, 3, 1, 2, 2, 2, 1, 256, 132, 132, 115, 80,,, -3, 5, 3, 1, 2, 2, 2, 1, 384, 132, 132, 115, 80,,, -3, 5, 3, 1, 2, 2, 2, 2, 128, 132, 132, 115, 80,,, -3, 5, 3, 1, 2, 2, 2, 2, 256, 132, 132, 115, 80,,, -3, 5, 3, 1, 2, 2, 2, 2, 384, 132, 132, 115, 80,,, -3, 5, 3, 1, 3, 3, 1, 1, 128, 132, 124, 108, 76,,, -3, 5, 3, 1, 3, 3, 1, 1, 256, 132, 124, 108, 76,,, -3, 5, 3, 1, 3, 3, 1, 1, 384, 132, 124, 108, 76,,, -3, 5, 3, 1, 3, 3, 1, 2, 128, 132, 124, 108, 76,,, -3, 5, 3, 1, 3, 3, 1, 2, 256, 132, 124, 108, 76,,, -3, 5, 3, 1, 3, 3, 1, 2, 384, 132, 124, 108, 76,,, -3, 5, 3, 1, 3, 3, 1, 3, 128, 132, 124, 108, 76,,, -3, 5, 3, 1, 3, 3, 1, 3, 256, 132, 124, 108, 76,,, -3, 5, 3, 1, 3, 3, 1, 3, 384, 132, 124, 108, 76,,, -3, 5, 3, 1, 3, 3, 2, 1, 128, 132, 124, 108, 76,,, -3, 5, 3, 1, 3, 3, 2, 1, 256, 132, 124, 108, 76,,, -3, 5, 3, 1, 3, 3, 2, 1, 384, 132, 124, 108, 76,,, -3, 5, 3, 1, 3, 3, 2, 2, 128, 132, 124, 108, 76,,, -3, 5, 3, 1, 3, 3, 2, 2, 256, 132, 124, 108, 76,,, -3, 5, 3, 1, 3, 3, 2, 2, 384, 132, 124, 108, 76,,, -3, 5, 3, 1, 3, 3, 2, 3, 128, 132, 124, 108, 76,,, -3, 5, 3, 1, 3, 3, 2, 3, 256, 132, 124, 108, 76,,, -3, 5, 3, 1, 3, 3, 2, 3, 384, 132, 124, 108, 76,,, -3, 5, 3, 1, 3, 3, 3, 1, 128, 132, 124, 108, 76,,, -3, 5, 3, 1, 3, 3, 3, 1, 256, 132, 124, 108, 76,,, -3, 5, 3, 1, 3, 3, 3, 1, 384, 132, 124, 108, 76,,, -3, 5, 3, 1, 3, 3, 3, 2, 128, 132, 124, 108, 76,,, -3, 5, 3, 1, 3, 3, 3, 2, 256, 132, 124, 108, 76,,, -3, 5, 3, 1, 3, 3, 3, 2, 384, 132, 124, 108, 76,,, -3, 5, 3, 1, 3, 3, 3, 3, 128, 132, 124, 108, 76,,, -3, 5, 3, 1, 3, 3, 3, 3, 256, 132, 124, 108, 76,,, -3, 5, 3, 1, 3, 3, 3, 3, 384, 132, 124, 108, 76,,, -3, 5, 3, 2, 1, 1, 1, 1, 128, 240, 240, 240, 174,,, -3, 5, 3, 2, 1, 1, 1, 1, 256, 240, 240, 240, 174,,, -3, 5, 3, 2, 1, 1, 1, 1, 384, 240, 240, 240, 174,,, -3, 5, 3, 2, 2, 2, 1, 1, 128, 240, 240, 226, 156,,, -3, 5, 3, 2, 2, 2, 1, 1, 256, 240, 240, 226, 156,,, -3, 5, 3, 2, 2, 2, 1, 1, 384, 240, 240, 226, 156,,, -3, 5, 3, 2, 2, 2, 1, 2, 128, 240, 240, 226, 156,,, -3, 5, 3, 2, 2, 2, 1, 2, 256, 240, 240, 226, 156,,, -3, 5, 3, 2, 2, 2, 1, 2, 384, 240, 240, 226, 156,,, -3, 5, 3, 2, 2, 2, 2, 1, 128, 240, 240, 226, 156,,, -3, 5, 3, 2, 2, 2, 2, 1, 256, 240, 240, 226, 156,,, -3, 5, 3, 2, 2, 2, 2, 1, 384, 240, 240, 226, 156,,, -3, 5, 3, 2, 2, 2, 2, 2, 128, 240, 240, 226, 156,,, -3, 5, 3, 2, 2, 2, 2, 2, 256, 240, 240, 226, 156,,, -3, 5, 3, 2, 2, 2, 2, 2, 384, 240, 240, 226, 156,,, -3, 5, 3, 2, 3, 3, 1, 1, 128, 240, 240, 212, 148,,, -3, 5, 3, 2, 3, 3, 1, 1, 256, 240, 240, 212, 148,,, -3, 5, 3, 2, 3, 3, 1, 1, 384, 240, 240, 212, 148,,, -3, 5, 3, 2, 3, 3, 1, 2, 128, 240, 240, 212, 148,,, -3, 5, 3, 2, 3, 3, 1, 2, 256, 240, 240, 212, 148,,, -3, 5, 3, 2, 3, 3, 1, 2, 384, 240, 240, 212, 148,,, -3, 5, 3, 2, 3, 3, 1, 3, 128, 240, 240, 212, 148,,, -3, 5, 3, 2, 3, 3, 1, 3, 256, 240, 240, 212, 148,,, -3, 5, 3, 2, 3, 3, 1, 3, 384, 240, 240, 212, 148,,, -3, 5, 3, 2, 3, 3, 2, 1, 128, 240, 240, 212, 148,,, -3, 5, 3, 2, 3, 3, 2, 1, 256, 240, 240, 212, 148,,, -3, 5, 3, 2, 3, 3, 2, 1, 384, 240, 240, 212, 148,,, -3, 5, 3, 2, 3, 3, 2, 2, 128, 240, 240, 212, 148,,, -3, 5, 3, 2, 3, 3, 2, 2, 256, 240, 240, 212, 148,,, -3, 5, 3, 2, 3, 3, 2, 2, 384, 240, 240, 212, 148,,, -3, 5, 3, 2, 3, 3, 2, 3, 128, 240, 240, 212, 148,,, -3, 5, 3, 2, 3, 3, 2, 3, 256, 240, 240, 212, 148,,, -3, 5, 3, 2, 3, 3, 2, 3, 384, 240, 240, 212, 148,,, -3, 5, 3, 2, 3, 3, 3, 1, 128, 240, 240, 212, 148,,, -3, 5, 3, 2, 3, 3, 3, 1, 256, 240, 240, 212, 148,,, -3, 5, 3, 2, 3, 3, 3, 1, 384, 240, 240, 212, 148,,, -3, 5, 3, 2, 3, 3, 3, 2, 128, 240, 240, 212, 148,,, -3, 5, 3, 2, 3, 3, 3, 2, 256, 240, 240, 212, 148,,, -3, 5, 3, 2, 3, 3, 3, 2, 384, 240, 240, 212, 148,,, -3, 5, 3, 2, 3, 3, 3, 3, 128, 240, 240, 212, 148,,, -3, 5, 3, 2, 3, 3, 3, 3, 256, 240, 240, 212, 148,,, -3, 5, 3, 2, 3, 3, 3, 3, 384, 240, 240, 212, 148,,, -3, 5, 3, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 5, 3, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 5, 3, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 5, 3, 3, 2, 2, 1, 1, 128, 240, 240, 240, 232,,, -3, 5, 3, 3, 2, 2, 1, 1, 256, 240, 240, 240, 232,,, -3, 5, 3, 3, 2, 2, 1, 1, 384, 240, 240, 240, 232,,, -3, 5, 3, 3, 2, 2, 1, 2, 128, 240, 240, 240, 232,,, -3, 5, 3, 3, 2, 2, 1, 2, 256, 240, 240, 240, 232,,, -3, 5, 3, 3, 2, 2, 1, 2, 384, 240, 240, 240, 232,,, -3, 5, 3, 3, 2, 2, 2, 1, 128, 240, 240, 240, 232,,, -3, 5, 3, 3, 2, 2, 2, 1, 256, 240, 240, 240, 232,,, -3, 5, 3, 3, 2, 2, 2, 1, 384, 240, 240, 240, 232,,, -3, 5, 3, 3, 2, 2, 2, 2, 128, 240, 240, 240, 232,,, -3, 5, 3, 3, 2, 2, 2, 2, 256, 240, 240, 240, 232,,, -3, 5, 3, 3, 2, 2, 2, 2, 384, 240, 240, 240, 232,,, -3, 5, 3, 3, 3, 3, 1, 1, 128, 240, 240, 240, 220,,, -3, 5, 3, 3, 3, 3, 1, 1, 256, 240, 240, 240, 220,,, -3, 5, 3, 3, 3, 3, 1, 1, 384, 240, 240, 240, 220,,, -3, 5, 3, 3, 3, 3, 1, 2, 128, 240, 240, 240, 220,,, -3, 5, 3, 3, 3, 3, 1, 2, 256, 240, 240, 240, 220,,, -3, 5, 3, 3, 3, 3, 1, 2, 384, 240, 240, 240, 220,,, -3, 5, 3, 3, 3, 3, 1, 3, 128, 240, 240, 240, 220,,, -3, 5, 3, 3, 3, 3, 1, 3, 256, 240, 240, 240, 220,,, -3, 5, 3, 3, 3, 3, 1, 3, 384, 240, 240, 240, 220,,, -3, 5, 3, 3, 3, 3, 2, 1, 128, 240, 240, 240, 220,,, -3, 5, 3, 3, 3, 3, 2, 1, 256, 240, 240, 240, 220,,, -3, 5, 3, 3, 3, 3, 2, 1, 384, 240, 240, 240, 220,,, -3, 5, 3, 3, 3, 3, 2, 2, 128, 240, 240, 240, 220,,, -3, 5, 3, 3, 3, 3, 2, 2, 256, 240, 240, 240, 220,,, -3, 5, 3, 3, 3, 3, 2, 2, 384, 240, 240, 240, 220,,, -3, 5, 3, 3, 3, 3, 2, 3, 128, 240, 240, 240, 220,,, -3, 5, 3, 3, 3, 3, 2, 3, 256, 240, 240, 240, 220,,, -3, 5, 3, 3, 3, 3, 2, 3, 384, 240, 240, 240, 220,,, -3, 5, 3, 3, 3, 3, 3, 1, 128, 240, 240, 240, 220,,, -3, 5, 3, 3, 3, 3, 3, 1, 256, 240, 240, 240, 220,,, -3, 5, 3, 3, 3, 3, 3, 1, 384, 240, 240, 240, 220,,, -3, 5, 3, 3, 3, 3, 3, 2, 128, 240, 240, 240, 220,,, -3, 5, 3, 3, 3, 3, 3, 2, 256, 240, 240, 240, 220,,, -3, 5, 3, 3, 3, 3, 3, 2, 384, 240, 240, 240, 220,,, -3, 5, 3, 3, 3, 3, 3, 3, 128, 240, 240, 240, 220,,, -3, 5, 3, 3, 3, 3, 3, 3, 256, 240, 240, 240, 220,,, -3, 5, 3, 3, 3, 3, 3, 3, 384, 240, 240, 240, 220,,, -3, 5, 3, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 5, 3, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 5, 3, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 5, 3, 4, 2, 2, 1, 1, 128, 240, 240, 240, 240,,, -3, 5, 3, 4, 2, 2, 1, 1, 256, 240, 240, 240, 240,,, -3, 5, 3, 4, 2, 2, 1, 1, 384, 240, 240, 240, 240,,, -3, 5, 3, 4, 2, 2, 1, 2, 128, 240, 240, 240, 240,,, -3, 5, 3, 4, 2, 2, 1, 2, 256, 240, 240, 240, 240,,, -3, 5, 3, 4, 2, 2, 1, 2, 384, 240, 240, 240, 240,,, -3, 5, 3, 4, 2, 2, 2, 1, 128, 240, 240, 240, 240,,, -3, 5, 3, 4, 2, 2, 2, 1, 256, 240, 240, 240, 240,,, -3, 5, 3, 4, 2, 2, 2, 1, 384, 240, 240, 240, 240,,, -3, 5, 3, 4, 2, 2, 2, 2, 128, 240, 240, 240, 240,,, -3, 5, 3, 4, 2, 2, 2, 2, 256, 240, 240, 240, 240,,, -3, 5, 3, 4, 2, 2, 2, 2, 384, 240, 240, 240, 240,,, -3, 5, 3, 4, 3, 3, 1, 1, 128, 240, 240, 240, 240,,, -3, 5, 3, 4, 3, 3, 1, 1, 256, 240, 240, 240, 240,,, -3, 5, 3, 4, 3, 3, 1, 1, 384, 240, 240, 240, 240,,, -3, 5, 3, 4, 3, 3, 1, 2, 128, 240, 240, 240, 240,,, -3, 5, 3, 4, 3, 3, 1, 2, 256, 240, 240, 240, 240,,, -3, 5, 3, 4, 3, 3, 1, 2, 384, 240, 240, 240, 240,,, -3, 5, 3, 4, 3, 3, 1, 3, 128, 240, 240, 240, 240,,, -3, 5, 3, 4, 3, 3, 1, 3, 256, 240, 240, 240, 240,,, -3, 5, 3, 4, 3, 3, 1, 3, 384, 240, 240, 240, 240,,, -3, 5, 3, 4, 3, 3, 2, 1, 128, 240, 240, 240, 240,,, -3, 5, 3, 4, 3, 3, 2, 1, 256, 240, 240, 240, 240,,, -3, 5, 3, 4, 3, 3, 2, 1, 384, 240, 240, 240, 240,,, -3, 5, 3, 4, 3, 3, 2, 2, 128, 240, 240, 240, 240,,, -3, 5, 3, 4, 3, 3, 2, 2, 256, 240, 240, 240, 240,,, -3, 5, 3, 4, 3, 3, 2, 2, 384, 240, 240, 240, 240,,, -3, 5, 3, 4, 3, 3, 2, 3, 128, 240, 240, 240, 240,,, -3, 5, 3, 4, 3, 3, 2, 3, 256, 240, 240, 240, 240,,, -3, 5, 3, 4, 3, 3, 2, 3, 384, 240, 240, 240, 240,,, -3, 5, 3, 4, 3, 3, 3, 1, 128, 240, 240, 240, 240,,, -3, 5, 3, 4, 3, 3, 3, 1, 256, 240, 240, 240, 240,,, -3, 5, 3, 4, 3, 3, 3, 1, 384, 240, 240, 240, 240,,, -3, 5, 3, 4, 3, 3, 3, 2, 128, 240, 240, 240, 240,,, -3, 5, 3, 4, 3, 3, 3, 2, 256, 240, 240, 240, 240,,, -3, 5, 3, 4, 3, 3, 3, 2, 384, 240, 240, 240, 240,,, -3, 5, 3, 4, 3, 3, 3, 3, 128, 240, 240, 240, 240,,, -3, 5, 3, 4, 3, 3, 3, 3, 256, 240, 240, 240, 240,,, -3, 5, 3, 4, 3, 3, 3, 3, 384, 240, 240, 240, 240,,, -3, 5, 3, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 5, 3, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 5, 3, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 5, 3, 5, 2, 2, 1, 1, 128, 240, 240, 240, 240,,, -3, 5, 3, 5, 2, 2, 1, 1, 256, 240, 240, 240, 240,,, -3, 5, 3, 5, 2, 2, 1, 1, 384, 240, 240, 240, 240,,, -3, 5, 3, 5, 2, 2, 1, 2, 128, 240, 240, 240, 240,,, -3, 5, 3, 5, 2, 2, 1, 2, 256, 240, 240, 240, 240,,, -3, 5, 3, 5, 2, 2, 1, 2, 384, 240, 240, 240, 240,,, -3, 5, 3, 5, 2, 2, 2, 1, 128, 240, 240, 240, 240,,, -3, 5, 3, 5, 2, 2, 2, 1, 256, 240, 240, 240, 240,,, -3, 5, 3, 5, 2, 2, 2, 1, 384, 240, 240, 240, 240,,, -3, 5, 3, 5, 2, 2, 2, 2, 128, 240, 240, 240, 240,,, -3, 5, 3, 5, 2, 2, 2, 2, 256, 240, 240, 240, 240,,, -3, 5, 3, 5, 2, 2, 2, 2, 384, 240, 240, 240, 240,,, -3, 5, 3, 5, 3, 3, 1, 1, 128, 240, 240, 240, 240,,, -3, 5, 3, 5, 3, 3, 1, 1, 256, 240, 240, 240, 240,,, -3, 5, 3, 5, 3, 3, 1, 1, 384, 240, 240, 240, 240,,, -3, 5, 3, 5, 3, 3, 1, 2, 128, 240, 240, 240, 240,,, -3, 5, 3, 5, 3, 3, 1, 2, 256, 240, 240, 240, 240,,, -3, 5, 3, 5, 3, 3, 1, 2, 384, 240, 240, 240, 240,,, -3, 5, 3, 5, 3, 3, 1, 3, 128, 240, 240, 240, 240,,, -3, 5, 3, 5, 3, 3, 1, 3, 256, 240, 240, 240, 240,,, -3, 5, 3, 5, 3, 3, 1, 3, 384, 240, 240, 240, 240,,, -3, 5, 3, 5, 3, 3, 2, 1, 128, 240, 240, 240, 240,,, -3, 5, 3, 5, 3, 3, 2, 1, 256, 240, 240, 240, 240,,, -3, 5, 3, 5, 3, 3, 2, 1, 384, 240, 240, 240, 240,,, -3, 5, 3, 5, 3, 3, 2, 2, 128, 240, 240, 240, 240,,, -3, 5, 3, 5, 3, 3, 2, 2, 256, 240, 240, 240, 240,,, -3, 5, 3, 5, 3, 3, 2, 2, 384, 240, 240, 240, 240,,, -3, 5, 3, 5, 3, 3, 2, 3, 128, 240, 240, 240, 240,,, -3, 5, 3, 5, 3, 3, 2, 3, 256, 240, 240, 240, 240,,, -3, 5, 3, 5, 3, 3, 2, 3, 384, 240, 240, 240, 240,,, -3, 5, 3, 5, 3, 3, 3, 1, 128, 240, 240, 240, 240,,, -3, 5, 3, 5, 3, 3, 3, 1, 256, 240, 240, 240, 240,,, -3, 5, 3, 5, 3, 3, 3, 1, 384, 240, 240, 240, 240,,, -3, 5, 3, 5, 3, 3, 3, 2, 128, 240, 240, 240, 240,,, -3, 5, 3, 5, 3, 3, 3, 2, 256, 240, 240, 240, 240,,, -3, 5, 3, 5, 3, 3, 3, 2, 384, 240, 240, 240, 240,,, -3, 5, 3, 5, 3, 3, 3, 3, 128, 240, 240, 240, 240,,, -3, 5, 3, 5, 3, 3, 3, 3, 256, 240, 240, 240, 240,,, -3, 5, 3, 5, 3, 3, 3, 3, 384, 240, 240, 240, 240,,, -3, 6, 1, 1, 1, 1, 1, 1, 128, 133, 133, 90,,,, -3, 6, 1, 1, 1, 1, 1, 1, 256, 133, 133, 90,,,, -3, 6, 1, 1, 1, 1, 1, 1, 384, 133, 133, 90,,,, -3, 6, 1, 1, 2, 2, 1, 1, 128, 133, 129, 90,,,, -3, 6, 1, 1, 2, 2, 1, 1, 256, 133, 129, 90,,,, -3, 6, 1, 1, 2, 2, 1, 1, 384, 133, 129, 90,,,, -3, 6, 1, 1, 2, 2, 1, 2, 128, 133, 129, 90,,,, -3, 6, 1, 1, 2, 2, 1, 2, 256, 133, 129, 90,,,, -3, 6, 1, 1, 2, 2, 1, 2, 384, 133, 129, 90,,,, -3, 6, 1, 1, 2, 2, 2, 1, 128, 133, 129, 90,,,, -3, 6, 1, 1, 2, 2, 2, 1, 256, 133, 129, 90,,,, -3, 6, 1, 1, 2, 2, 2, 1, 384, 133, 129, 90,,,, -3, 6, 1, 1, 2, 2, 2, 2, 128, 133, 129, 90,,,, -3, 6, 1, 1, 2, 2, 2, 2, 256, 133, 129, 90,,,, -3, 6, 1, 1, 2, 2, 2, 2, 384, 133, 129, 90,,,, -3, 6, 1, 1, 3, 3, 1, 1, 128, 131, 121, 90,,,, -3, 6, 1, 1, 3, 3, 1, 1, 256, 131, 121, 90,,,, -3, 6, 1, 1, 3, 3, 1, 1, 384, 131, 121, 90,,,, -3, 6, 1, 1, 3, 3, 1, 2, 128, 131, 121, 90,,,, -3, 6, 1, 1, 3, 3, 1, 2, 256, 131, 121, 90,,,, -3, 6, 1, 1, 3, 3, 1, 2, 384, 131, 121, 90,,,, -3, 6, 1, 1, 3, 3, 1, 3, 128, 131, 121, 90,,,, -3, 6, 1, 1, 3, 3, 1, 3, 256, 131, 121, 90,,,, -3, 6, 1, 1, 3, 3, 1, 3, 384, 131, 121, 90,,,, -3, 6, 1, 1, 3, 3, 2, 1, 128, 131, 121, 90,,,, -3, 6, 1, 1, 3, 3, 2, 1, 256, 131, 121, 90,,,, -3, 6, 1, 1, 3, 3, 2, 1, 384, 131, 121, 90,,,, -3, 6, 1, 1, 3, 3, 2, 2, 128, 131, 121, 90,,,, -3, 6, 1, 1, 3, 3, 2, 2, 256, 131, 121, 90,,,, -3, 6, 1, 1, 3, 3, 2, 2, 384, 131, 121, 90,,,, -3, 6, 1, 1, 3, 3, 2, 3, 128, 131, 121, 90,,,, -3, 6, 1, 1, 3, 3, 2, 3, 256, 131, 121, 90,,,, -3, 6, 1, 1, 3, 3, 2, 3, 384, 131, 121, 90,,,, -3, 6, 1, 1, 3, 3, 3, 1, 128, 131, 121, 90,,,, -3, 6, 1, 1, 3, 3, 3, 1, 256, 131, 121, 90,,,, -3, 6, 1, 1, 3, 3, 3, 1, 384, 131, 121, 90,,,, -3, 6, 1, 1, 3, 3, 3, 2, 128, 131, 121, 90,,,, -3, 6, 1, 1, 3, 3, 3, 2, 256, 131, 121, 90,,,, -3, 6, 1, 1, 3, 3, 3, 2, 384, 131, 121, 90,,,, -3, 6, 1, 1, 3, 3, 3, 3, 128, 131, 121, 90,,,, -3, 6, 1, 1, 3, 3, 3, 3, 256, 131, 121, 90,,,, -3, 6, 1, 1, 3, 3, 3, 3, 384, 131, 121, 90,,,, -3, 6, 1, 2, 1, 1, 1, 1, 128, 240, 240, 175,,,, -3, 6, 1, 2, 1, 1, 1, 1, 256, 240, 240, 175,,,, -3, 6, 1, 2, 1, 1, 1, 1, 384, 240, 240, 175,,,, -3, 6, 1, 2, 2, 2, 1, 1, 128, 240, 240, 175,,,, -3, 6, 1, 2, 2, 2, 1, 1, 256, 240, 240, 175,,,, -3, 6, 1, 2, 2, 2, 1, 1, 384, 240, 240, 175,,,, -3, 6, 1, 2, 2, 2, 1, 2, 128, 240, 240, 175,,,, -3, 6, 1, 2, 2, 2, 1, 2, 256, 240, 240, 175,,,, -3, 6, 1, 2, 2, 2, 1, 2, 384, 240, 240, 175,,,, -3, 6, 1, 2, 2, 2, 2, 1, 128, 240, 240, 175,,,, -3, 6, 1, 2, 2, 2, 2, 1, 256, 240, 240, 175,,,, -3, 6, 1, 2, 2, 2, 2, 1, 384, 240, 240, 175,,,, -3, 6, 1, 2, 2, 2, 2, 2, 128, 240, 240, 175,,,, -3, 6, 1, 2, 2, 2, 2, 2, 256, 240, 240, 175,,,, -3, 6, 1, 2, 2, 2, 2, 2, 384, 240, 240, 175,,,, -3, 6, 1, 2, 3, 3, 1, 1, 128, 240, 237, 175,,,, -3, 6, 1, 2, 3, 3, 1, 1, 256, 240, 237, 175,,,, -3, 6, 1, 2, 3, 3, 1, 1, 384, 240, 237, 175,,,, -3, 6, 1, 2, 3, 3, 1, 2, 128, 240, 237, 175,,,, -3, 6, 1, 2, 3, 3, 1, 2, 256, 240, 237, 175,,,, -3, 6, 1, 2, 3, 3, 1, 2, 384, 240, 237, 175,,,, -3, 6, 1, 2, 3, 3, 1, 3, 128, 240, 237, 175,,,, -3, 6, 1, 2, 3, 3, 1, 3, 256, 240, 237, 175,,,, -3, 6, 1, 2, 3, 3, 1, 3, 384, 240, 237, 175,,,, -3, 6, 1, 2, 3, 3, 2, 1, 128, 240, 237, 175,,,, -3, 6, 1, 2, 3, 3, 2, 1, 256, 240, 237, 175,,,, -3, 6, 1, 2, 3, 3, 2, 1, 384, 240, 237, 175,,,, -3, 6, 1, 2, 3, 3, 2, 2, 128, 240, 237, 175,,,, -3, 6, 1, 2, 3, 3, 2, 2, 256, 240, 237, 175,,,, -3, 6, 1, 2, 3, 3, 2, 2, 384, 240, 237, 175,,,, -3, 6, 1, 2, 3, 3, 2, 3, 128, 240, 237, 175,,,, -3, 6, 1, 2, 3, 3, 2, 3, 256, 240, 237, 175,,,, -3, 6, 1, 2, 3, 3, 2, 3, 384, 240, 237, 175,,,, -3, 6, 1, 2, 3, 3, 3, 1, 128, 240, 237, 175,,,, -3, 6, 1, 2, 3, 3, 3, 1, 256, 240, 237, 175,,,, -3, 6, 1, 2, 3, 3, 3, 1, 384, 240, 237, 175,,,, -3, 6, 1, 2, 3, 3, 3, 2, 128, 240, 237, 175,,,, -3, 6, 1, 2, 3, 3, 3, 2, 256, 240, 237, 175,,,, -3, 6, 1, 2, 3, 3, 3, 2, 384, 240, 237, 175,,,, -3, 6, 1, 2, 3, 3, 3, 3, 128, 240, 237, 175,,,, -3, 6, 1, 2, 3, 3, 3, 3, 256, 240, 237, 175,,,, -3, 6, 1, 2, 3, 3, 3, 3, 384, 240, 237, 175,,,, -3, 6, 1, 3, 1, 1, 1, 1, 128, 240, 240, 240,,,, -3, 6, 1, 3, 1, 1, 1, 1, 256, 240, 240, 240,,,, -3, 6, 1, 3, 1, 1, 1, 1, 384, 240, 240, 240,,,, -3, 6, 1, 3, 2, 2, 1, 1, 128, 240, 240, 240,,,, -3, 6, 1, 3, 2, 2, 1, 1, 256, 240, 240, 240,,,, -3, 6, 1, 3, 2, 2, 1, 1, 384, 240, 240, 240,,,, -3, 6, 1, 3, 2, 2, 1, 2, 128, 240, 240, 240,,,, -3, 6, 1, 3, 2, 2, 1, 2, 256, 240, 240, 240,,,, -3, 6, 1, 3, 2, 2, 1, 2, 384, 240, 240, 240,,,, -3, 6, 1, 3, 2, 2, 2, 1, 128, 240, 240, 240,,,, -3, 6, 1, 3, 2, 2, 2, 1, 256, 240, 240, 240,,,, -3, 6, 1, 3, 2, 2, 2, 1, 384, 240, 240, 240,,,, -3, 6, 1, 3, 2, 2, 2, 2, 128, 240, 240, 240,,,, -3, 6, 1, 3, 2, 2, 2, 2, 256, 240, 240, 240,,,, -3, 6, 1, 3, 2, 2, 2, 2, 384, 240, 240, 240,,,, -3, 6, 1, 3, 3, 3, 1, 1, 128, 240, 240, 240,,,, -3, 6, 1, 3, 3, 3, 1, 1, 256, 240, 240, 240,,,, -3, 6, 1, 3, 3, 3, 1, 1, 384, 240, 240, 240,,,, -3, 6, 1, 3, 3, 3, 1, 2, 128, 240, 240, 240,,,, -3, 6, 1, 3, 3, 3, 1, 2, 256, 240, 240, 240,,,, -3, 6, 1, 3, 3, 3, 1, 2, 384, 240, 240, 240,,,, -3, 6, 1, 3, 3, 3, 1, 3, 128, 240, 240, 240,,,, -3, 6, 1, 3, 3, 3, 1, 3, 256, 240, 240, 240,,,, -3, 6, 1, 3, 3, 3, 1, 3, 384, 240, 240, 240,,,, -3, 6, 1, 3, 3, 3, 2, 1, 128, 240, 240, 240,,,, -3, 6, 1, 3, 3, 3, 2, 1, 256, 240, 240, 240,,,, -3, 6, 1, 3, 3, 3, 2, 1, 384, 240, 240, 240,,,, -3, 6, 1, 3, 3, 3, 2, 2, 128, 240, 240, 240,,,, -3, 6, 1, 3, 3, 3, 2, 2, 256, 240, 240, 240,,,, -3, 6, 1, 3, 3, 3, 2, 2, 384, 240, 240, 240,,,, -3, 6, 1, 3, 3, 3, 2, 3, 128, 240, 240, 240,,,, -3, 6, 1, 3, 3, 3, 2, 3, 256, 240, 240, 240,,,, -3, 6, 1, 3, 3, 3, 2, 3, 384, 240, 240, 240,,,, -3, 6, 1, 3, 3, 3, 3, 1, 128, 240, 240, 240,,,, -3, 6, 1, 3, 3, 3, 3, 1, 256, 240, 240, 240,,,, -3, 6, 1, 3, 3, 3, 3, 1, 384, 240, 240, 240,,,, -3, 6, 1, 3, 3, 3, 3, 2, 128, 240, 240, 240,,,, -3, 6, 1, 3, 3, 3, 3, 2, 256, 240, 240, 240,,,, -3, 6, 1, 3, 3, 3, 3, 2, 384, 240, 240, 240,,,, -3, 6, 1, 3, 3, 3, 3, 3, 128, 240, 240, 240,,,, -3, 6, 1, 3, 3, 3, 3, 3, 256, 240, 240, 240,,,, -3, 6, 1, 3, 3, 3, 3, 3, 384, 240, 240, 240,,,, -3, 6, 1, 4, 1, 1, 1, 1, 128, 240, 240, 240,,,, -3, 6, 1, 4, 1, 1, 1, 1, 256, 240, 240, 240,,,, -3, 6, 1, 4, 1, 1, 1, 1, 384, 240, 240, 240,,,, -3, 6, 1, 4, 2, 2, 1, 1, 128, 240, 240, 240,,,, -3, 6, 1, 4, 2, 2, 1, 1, 256, 240, 240, 240,,,, -3, 6, 1, 4, 2, 2, 1, 1, 384, 240, 240, 240,,,, -3, 6, 1, 4, 2, 2, 1, 2, 128, 240, 240, 240,,,, -3, 6, 1, 4, 2, 2, 1, 2, 256, 240, 240, 240,,,, -3, 6, 1, 4, 2, 2, 1, 2, 384, 240, 240, 240,,,, -3, 6, 1, 4, 2, 2, 2, 1, 128, 240, 240, 240,,,, -3, 6, 1, 4, 2, 2, 2, 1, 256, 240, 240, 240,,,, -3, 6, 1, 4, 2, 2, 2, 1, 384, 240, 240, 240,,,, -3, 6, 1, 4, 2, 2, 2, 2, 128, 240, 240, 240,,,, -3, 6, 1, 4, 2, 2, 2, 2, 256, 240, 240, 240,,,, -3, 6, 1, 4, 2, 2, 2, 2, 384, 240, 240, 240,,,, -3, 6, 1, 4, 3, 3, 1, 1, 128, 240, 240, 240,,,, -3, 6, 1, 4, 3, 3, 1, 1, 256, 240, 240, 240,,,, -3, 6, 1, 4, 3, 3, 1, 1, 384, 240, 240, 240,,,, -3, 6, 1, 4, 3, 3, 1, 2, 128, 240, 240, 240,,,, -3, 6, 1, 4, 3, 3, 1, 2, 256, 240, 240, 240,,,, -3, 6, 1, 4, 3, 3, 1, 2, 384, 240, 240, 240,,,, -3, 6, 1, 4, 3, 3, 1, 3, 128, 240, 240, 240,,,, -3, 6, 1, 4, 3, 3, 1, 3, 256, 240, 240, 240,,,, -3, 6, 1, 4, 3, 3, 1, 3, 384, 240, 240, 240,,,, -3, 6, 1, 4, 3, 3, 2, 1, 128, 240, 240, 240,,,, -3, 6, 1, 4, 3, 3, 2, 1, 256, 240, 240, 240,,,, -3, 6, 1, 4, 3, 3, 2, 1, 384, 240, 240, 240,,,, -3, 6, 1, 4, 3, 3, 2, 2, 128, 240, 240, 240,,,, -3, 6, 1, 4, 3, 3, 2, 2, 256, 240, 240, 240,,,, -3, 6, 1, 4, 3, 3, 2, 2, 384, 240, 240, 240,,,, -3, 6, 1, 4, 3, 3, 2, 3, 128, 240, 240, 240,,,, -3, 6, 1, 4, 3, 3, 2, 3, 256, 240, 240, 240,,,, -3, 6, 1, 4, 3, 3, 2, 3, 384, 240, 240, 240,,,, -3, 6, 1, 4, 3, 3, 3, 1, 128, 240, 240, 240,,,, -3, 6, 1, 4, 3, 3, 3, 1, 256, 240, 240, 240,,,, -3, 6, 1, 4, 3, 3, 3, 1, 384, 240, 240, 240,,,, -3, 6, 1, 4, 3, 3, 3, 2, 128, 240, 240, 240,,,, -3, 6, 1, 4, 3, 3, 3, 2, 256, 240, 240, 240,,,, -3, 6, 1, 4, 3, 3, 3, 2, 384, 240, 240, 240,,,, -3, 6, 1, 4, 3, 3, 3, 3, 128, 240, 240, 240,,,, -3, 6, 1, 4, 3, 3, 3, 3, 256, 240, 240, 240,,,, -3, 6, 1, 4, 3, 3, 3, 3, 384, 240, 240, 240,,,, -3, 6, 1, 5, 1, 1, 1, 1, 128, 240, 240, 240,,,, -3, 6, 1, 5, 1, 1, 1, 1, 256, 240, 240, 240,,,, -3, 6, 1, 5, 1, 1, 1, 1, 384, 240, 240, 240,,,, -3, 6, 1, 5, 2, 2, 1, 1, 128, 240, 240, 240,,,, -3, 6, 1, 5, 2, 2, 1, 1, 256, 240, 240, 240,,,, -3, 6, 1, 5, 2, 2, 1, 1, 384, 240, 240, 240,,,, -3, 6, 1, 5, 2, 2, 1, 2, 128, 240, 240, 240,,,, -3, 6, 1, 5, 2, 2, 1, 2, 256, 240, 240, 240,,,, -3, 6, 1, 5, 2, 2, 1, 2, 384, 240, 240, 240,,,, -3, 6, 1, 5, 2, 2, 2, 1, 128, 240, 240, 240,,,, -3, 6, 1, 5, 2, 2, 2, 1, 256, 240, 240, 240,,,, -3, 6, 1, 5, 2, 2, 2, 1, 384, 240, 240, 240,,,, -3, 6, 1, 5, 2, 2, 2, 2, 128, 240, 240, 240,,,, -3, 6, 1, 5, 2, 2, 2, 2, 256, 240, 240, 240,,,, -3, 6, 1, 5, 2, 2, 2, 2, 384, 240, 240, 240,,,, -3, 6, 1, 5, 3, 3, 1, 1, 128, 240, 240, 240,,,, -3, 6, 1, 5, 3, 3, 1, 1, 256, 240, 240, 240,,,, -3, 6, 1, 5, 3, 3, 1, 1, 384, 240, 240, 240,,,, -3, 6, 1, 5, 3, 3, 1, 2, 128, 240, 240, 240,,,, -3, 6, 1, 5, 3, 3, 1, 2, 256, 240, 240, 240,,,, -3, 6, 1, 5, 3, 3, 1, 2, 384, 240, 240, 240,,,, -3, 6, 1, 5, 3, 3, 1, 3, 128, 240, 240, 240,,,, -3, 6, 1, 5, 3, 3, 1, 3, 256, 240, 240, 240,,,, -3, 6, 1, 5, 3, 3, 1, 3, 384, 240, 240, 240,,,, -3, 6, 1, 5, 3, 3, 2, 1, 128, 240, 240, 240,,,, -3, 6, 1, 5, 3, 3, 2, 1, 256, 240, 240, 240,,,, -3, 6, 1, 5, 3, 3, 2, 1, 384, 240, 240, 240,,,, -3, 6, 1, 5, 3, 3, 2, 2, 128, 240, 240, 240,,,, -3, 6, 1, 5, 3, 3, 2, 2, 256, 240, 240, 240,,,, -3, 6, 1, 5, 3, 3, 2, 2, 384, 240, 240, 240,,,, -3, 6, 1, 5, 3, 3, 2, 3, 128, 240, 240, 240,,,, -3, 6, 1, 5, 3, 3, 2, 3, 256, 240, 240, 240,,,, -3, 6, 1, 5, 3, 3, 2, 3, 384, 240, 240, 240,,,, -3, 6, 1, 5, 3, 3, 3, 1, 128, 240, 240, 240,,,, -3, 6, 1, 5, 3, 3, 3, 1, 256, 240, 240, 240,,,, -3, 6, 1, 5, 3, 3, 3, 1, 384, 240, 240, 240,,,, -3, 6, 1, 5, 3, 3, 3, 2, 128, 240, 240, 240,,,, -3, 6, 1, 5, 3, 3, 3, 2, 256, 240, 240, 240,,,, -3, 6, 1, 5, 3, 3, 3, 2, 384, 240, 240, 240,,,, -3, 6, 1, 5, 3, 3, 3, 3, 128, 240, 240, 240,,,, -3, 6, 1, 5, 3, 3, 3, 3, 256, 240, 240, 240,,,, -3, 6, 1, 5, 3, 3, 3, 3, 384, 240, 240, 240,,,, -3, 6, 1, 6, 1, 1, 1, 1, 128, 240, 240, 240,,,, -3, 6, 1, 6, 1, 1, 1, 1, 256, 240, 240, 240,,,, -3, 6, 1, 6, 1, 1, 1, 1, 384, 240, 240, 240,,,, -3, 6, 1, 6, 2, 2, 1, 1, 128, 240, 240, 240,,,, -3, 6, 1, 6, 2, 2, 1, 1, 256, 240, 240, 240,,,, -3, 6, 1, 6, 2, 2, 1, 1, 384, 240, 240, 240,,,, -3, 6, 1, 6, 2, 2, 1, 2, 128, 240, 240, 240,,,, -3, 6, 1, 6, 2, 2, 1, 2, 256, 240, 240, 240,,,, -3, 6, 1, 6, 2, 2, 1, 2, 384, 240, 240, 240,,,, -3, 6, 1, 6, 2, 2, 2, 1, 128, 240, 240, 240,,,, -3, 6, 1, 6, 2, 2, 2, 1, 256, 240, 240, 240,,,, -3, 6, 1, 6, 2, 2, 2, 1, 384, 240, 240, 240,,,, -3, 6, 1, 6, 2, 2, 2, 2, 128, 240, 240, 240,,,, -3, 6, 1, 6, 2, 2, 2, 2, 256, 240, 240, 240,,,, -3, 6, 1, 6, 2, 2, 2, 2, 384, 240, 240, 240,,,, -3, 6, 1, 6, 3, 3, 1, 1, 128, 240, 240, 240,,,, -3, 6, 1, 6, 3, 3, 1, 1, 256, 240, 240, 240,,,, -3, 6, 1, 6, 3, 3, 1, 1, 384, 240, 240, 240,,,, -3, 6, 1, 6, 3, 3, 1, 2, 128, 240, 240, 240,,,, -3, 6, 1, 6, 3, 3, 1, 2, 256, 240, 240, 240,,,, -3, 6, 1, 6, 3, 3, 1, 2, 384, 240, 240, 240,,,, -3, 6, 1, 6, 3, 3, 1, 3, 128, 240, 240, 240,,,, -3, 6, 1, 6, 3, 3, 1, 3, 256, 240, 240, 240,,,, -3, 6, 1, 6, 3, 3, 1, 3, 384, 240, 240, 240,,,, -3, 6, 1, 6, 3, 3, 2, 1, 128, 240, 240, 240,,,, -3, 6, 1, 6, 3, 3, 2, 1, 256, 240, 240, 240,,,, -3, 6, 1, 6, 3, 3, 2, 1, 384, 240, 240, 240,,,, -3, 6, 1, 6, 3, 3, 2, 2, 128, 240, 240, 240,,,, -3, 6, 1, 6, 3, 3, 2, 2, 256, 240, 240, 240,,,, -3, 6, 1, 6, 3, 3, 2, 2, 384, 240, 240, 240,,,, -3, 6, 1, 6, 3, 3, 2, 3, 128, 240, 240, 240,,,, -3, 6, 1, 6, 3, 3, 2, 3, 256, 240, 240, 240,,,, -3, 6, 1, 6, 3, 3, 2, 3, 384, 240, 240, 240,,,, -3, 6, 1, 6, 3, 3, 3, 1, 128, 240, 240, 240,,,, -3, 6, 1, 6, 3, 3, 3, 1, 256, 240, 240, 240,,,, -3, 6, 1, 6, 3, 3, 3, 1, 384, 240, 240, 240,,,, -3, 6, 1, 6, 3, 3, 3, 2, 128, 240, 240, 240,,,, -3, 6, 1, 6, 3, 3, 3, 2, 256, 240, 240, 240,,,, -3, 6, 1, 6, 3, 3, 3, 2, 384, 240, 240, 240,,,, -3, 6, 1, 6, 3, 3, 3, 3, 128, 240, 240, 240,,,, -3, 6, 1, 6, 3, 3, 3, 3, 256, 240, 240, 240,,,, -3, 6, 1, 6, 3, 3, 3, 3, 384, 240, 240, 240,,,, -3, 6, 2, 1, 1, 1, 1, 1, 128, 133, 133, 90,,,, -3, 6, 2, 1, 1, 1, 1, 1, 256, 133, 133, 90,,,, -3, 6, 2, 1, 1, 1, 1, 1, 384, 133, 133, 90,,,, -3, 6, 2, 1, 2, 2, 1, 1, 128, 133, 129, 90,,,, -3, 6, 2, 1, 2, 2, 1, 1, 256, 133, 129, 90,,,, -3, 6, 2, 1, 2, 2, 1, 1, 384, 133, 129, 90,,,, -3, 6, 2, 1, 2, 2, 1, 2, 128, 133, 129, 90,,,, -3, 6, 2, 1, 2, 2, 1, 2, 256, 133, 129, 90,,,, -3, 6, 2, 1, 2, 2, 1, 2, 384, 133, 129, 90,,,, -3, 6, 2, 1, 2, 2, 2, 1, 128, 133, 129, 90,,,, -3, 6, 2, 1, 2, 2, 2, 1, 256, 133, 129, 90,,,, -3, 6, 2, 1, 2, 2, 2, 1, 384, 133, 129, 90,,,, -3, 6, 2, 1, 2, 2, 2, 2, 128, 133, 129, 90,,,, -3, 6, 2, 1, 2, 2, 2, 2, 256, 133, 129, 90,,,, -3, 6, 2, 1, 2, 2, 2, 2, 384, 133, 129, 90,,,, -3, 6, 2, 1, 3, 3, 1, 1, 128, 131, 121, 90,,,, -3, 6, 2, 1, 3, 3, 1, 1, 256, 131, 121, 90,,,, -3, 6, 2, 1, 3, 3, 1, 1, 384, 131, 121, 90,,,, -3, 6, 2, 1, 3, 3, 1, 2, 128, 131, 121, 90,,,, -3, 6, 2, 1, 3, 3, 1, 2, 256, 131, 121, 90,,,, -3, 6, 2, 1, 3, 3, 1, 2, 384, 131, 121, 90,,,, -3, 6, 2, 1, 3, 3, 1, 3, 128, 131, 121, 90,,,, -3, 6, 2, 1, 3, 3, 1, 3, 256, 131, 121, 90,,,, -3, 6, 2, 1, 3, 3, 1, 3, 384, 131, 121, 90,,,, -3, 6, 2, 1, 3, 3, 2, 1, 128, 131, 121, 90,,,, -3, 6, 2, 1, 3, 3, 2, 1, 256, 131, 121, 90,,,, -3, 6, 2, 1, 3, 3, 2, 1, 384, 131, 121, 90,,,, -3, 6, 2, 1, 3, 3, 2, 2, 128, 131, 121, 90,,,, -3, 6, 2, 1, 3, 3, 2, 2, 256, 131, 121, 90,,,, -3, 6, 2, 1, 3, 3, 2, 2, 384, 131, 121, 90,,,, -3, 6, 2, 1, 3, 3, 2, 3, 128, 131, 121, 90,,,, -3, 6, 2, 1, 3, 3, 2, 3, 256, 131, 121, 90,,,, -3, 6, 2, 1, 3, 3, 2, 3, 384, 131, 121, 90,,,, -3, 6, 2, 1, 3, 3, 3, 1, 128, 131, 121, 90,,,, -3, 6, 2, 1, 3, 3, 3, 1, 256, 131, 121, 90,,,, -3, 6, 2, 1, 3, 3, 3, 1, 384, 131, 121, 90,,,, -3, 6, 2, 1, 3, 3, 3, 2, 128, 131, 121, 90,,,, -3, 6, 2, 1, 3, 3, 3, 2, 256, 131, 121, 90,,,, -3, 6, 2, 1, 3, 3, 3, 2, 384, 131, 121, 90,,,, -3, 6, 2, 1, 3, 3, 3, 3, 128, 131, 121, 90,,,, -3, 6, 2, 1, 3, 3, 3, 3, 256, 131, 121, 90,,,, -3, 6, 2, 1, 3, 3, 3, 3, 384, 131, 121, 90,,,, -3, 6, 2, 2, 1, 1, 1, 1, 128, 240, 240, 175,,,, -3, 6, 2, 2, 1, 1, 1, 1, 256, 240, 240, 175,,,, -3, 6, 2, 2, 1, 1, 1, 1, 384, 240, 240, 175,,,, -3, 6, 2, 2, 2, 2, 1, 1, 128, 240, 240, 175,,,, -3, 6, 2, 2, 2, 2, 1, 1, 256, 240, 240, 175,,,, -3, 6, 2, 2, 2, 2, 1, 1, 384, 240, 240, 175,,,, -3, 6, 2, 2, 2, 2, 1, 2, 128, 240, 240, 175,,,, -3, 6, 2, 2, 2, 2, 1, 2, 256, 240, 240, 175,,,, -3, 6, 2, 2, 2, 2, 1, 2, 384, 240, 240, 175,,,, -3, 6, 2, 2, 2, 2, 2, 1, 128, 240, 240, 175,,,, -3, 6, 2, 2, 2, 2, 2, 1, 256, 240, 240, 175,,,, -3, 6, 2, 2, 2, 2, 2, 1, 384, 240, 240, 175,,,, -3, 6, 2, 2, 2, 2, 2, 2, 128, 240, 240, 175,,,, -3, 6, 2, 2, 2, 2, 2, 2, 256, 240, 240, 175,,,, -3, 6, 2, 2, 2, 2, 2, 2, 384, 240, 240, 175,,,, -3, 6, 2, 2, 3, 3, 1, 1, 128, 240, 237, 175,,,, -3, 6, 2, 2, 3, 3, 1, 1, 256, 240, 237, 175,,,, -3, 6, 2, 2, 3, 3, 1, 1, 384, 240, 237, 175,,,, -3, 6, 2, 2, 3, 3, 1, 2, 128, 240, 237, 175,,,, -3, 6, 2, 2, 3, 3, 1, 2, 256, 240, 237, 175,,,, -3, 6, 2, 2, 3, 3, 1, 2, 384, 240, 237, 175,,,, -3, 6, 2, 2, 3, 3, 1, 3, 128, 240, 237, 175,,,, -3, 6, 2, 2, 3, 3, 1, 3, 256, 240, 237, 175,,,, -3, 6, 2, 2, 3, 3, 1, 3, 384, 240, 237, 175,,,, -3, 6, 2, 2, 3, 3, 2, 1, 128, 240, 237, 175,,,, -3, 6, 2, 2, 3, 3, 2, 1, 256, 240, 237, 175,,,, -3, 6, 2, 2, 3, 3, 2, 1, 384, 240, 237, 175,,,, -3, 6, 2, 2, 3, 3, 2, 2, 128, 240, 237, 175,,,, -3, 6, 2, 2, 3, 3, 2, 2, 256, 240, 237, 175,,,, -3, 6, 2, 2, 3, 3, 2, 2, 384, 240, 237, 175,,,, -3, 6, 2, 2, 3, 3, 2, 3, 128, 240, 237, 175,,,, -3, 6, 2, 2, 3, 3, 2, 3, 256, 240, 237, 175,,,, -3, 6, 2, 2, 3, 3, 2, 3, 384, 240, 237, 175,,,, -3, 6, 2, 2, 3, 3, 3, 1, 128, 240, 237, 175,,,, -3, 6, 2, 2, 3, 3, 3, 1, 256, 240, 237, 175,,,, -3, 6, 2, 2, 3, 3, 3, 1, 384, 240, 237, 175,,,, -3, 6, 2, 2, 3, 3, 3, 2, 128, 240, 237, 175,,,, -3, 6, 2, 2, 3, 3, 3, 2, 256, 240, 237, 175,,,, -3, 6, 2, 2, 3, 3, 3, 2, 384, 240, 237, 175,,,, -3, 6, 2, 2, 3, 3, 3, 3, 128, 240, 237, 175,,,, -3, 6, 2, 2, 3, 3, 3, 3, 256, 240, 237, 175,,,, -3, 6, 2, 2, 3, 3, 3, 3, 384, 240, 237, 175,,,, -3, 6, 2, 3, 1, 1, 1, 1, 128, 240, 240, 240,,,, -3, 6, 2, 3, 1, 1, 1, 1, 256, 240, 240, 240,,,, -3, 6, 2, 3, 1, 1, 1, 1, 384, 240, 240, 240,,,, -3, 6, 2, 3, 2, 2, 1, 1, 128, 240, 240, 240,,,, -3, 6, 2, 3, 2, 2, 1, 1, 256, 240, 240, 240,,,, -3, 6, 2, 3, 2, 2, 1, 1, 384, 240, 240, 240,,,, -3, 6, 2, 3, 2, 2, 1, 2, 128, 240, 240, 240,,,, -3, 6, 2, 3, 2, 2, 1, 2, 256, 240, 240, 240,,,, -3, 6, 2, 3, 2, 2, 1, 2, 384, 240, 240, 240,,,, -3, 6, 2, 3, 2, 2, 2, 1, 128, 240, 240, 240,,,, -3, 6, 2, 3, 2, 2, 2, 1, 256, 240, 240, 240,,,, -3, 6, 2, 3, 2, 2, 2, 1, 384, 240, 240, 240,,,, -3, 6, 2, 3, 2, 2, 2, 2, 128, 240, 240, 240,,,, -3, 6, 2, 3, 2, 2, 2, 2, 256, 240, 240, 240,,,, -3, 6, 2, 3, 2, 2, 2, 2, 384, 240, 240, 240,,,, -3, 6, 2, 3, 3, 3, 1, 1, 128, 240, 240, 240,,,, -3, 6, 2, 3, 3, 3, 1, 1, 256, 240, 240, 240,,,, -3, 6, 2, 3, 3, 3, 1, 1, 384, 240, 240, 240,,,, -3, 6, 2, 3, 3, 3, 1, 2, 128, 240, 240, 240,,,, -3, 6, 2, 3, 3, 3, 1, 2, 256, 240, 240, 240,,,, -3, 6, 2, 3, 3, 3, 1, 2, 384, 240, 240, 240,,,, -3, 6, 2, 3, 3, 3, 1, 3, 128, 240, 240, 240,,,, -3, 6, 2, 3, 3, 3, 1, 3, 256, 240, 240, 240,,,, -3, 6, 2, 3, 3, 3, 1, 3, 384, 240, 240, 240,,,, -3, 6, 2, 3, 3, 3, 2, 1, 128, 240, 240, 240,,,, -3, 6, 2, 3, 3, 3, 2, 1, 256, 240, 240, 240,,,, -3, 6, 2, 3, 3, 3, 2, 1, 384, 240, 240, 240,,,, -3, 6, 2, 3, 3, 3, 2, 2, 128, 240, 240, 240,,,, -3, 6, 2, 3, 3, 3, 2, 2, 256, 240, 240, 240,,,, -3, 6, 2, 3, 3, 3, 2, 2, 384, 240, 240, 240,,,, -3, 6, 2, 3, 3, 3, 2, 3, 128, 240, 240, 240,,,, -3, 6, 2, 3, 3, 3, 2, 3, 256, 240, 240, 240,,,, -3, 6, 2, 3, 3, 3, 2, 3, 384, 240, 240, 240,,,, -3, 6, 2, 3, 3, 3, 3, 1, 128, 240, 240, 240,,,, -3, 6, 2, 3, 3, 3, 3, 1, 256, 240, 240, 240,,,, -3, 6, 2, 3, 3, 3, 3, 1, 384, 240, 240, 240,,,, -3, 6, 2, 3, 3, 3, 3, 2, 128, 240, 240, 240,,,, -3, 6, 2, 3, 3, 3, 3, 2, 256, 240, 240, 240,,,, -3, 6, 2, 3, 3, 3, 3, 2, 384, 240, 240, 240,,,, -3, 6, 2, 3, 3, 3, 3, 3, 128, 240, 240, 240,,,, -3, 6, 2, 3, 3, 3, 3, 3, 256, 240, 240, 240,,,, -3, 6, 2, 3, 3, 3, 3, 3, 384, 240, 240, 240,,,, -3, 6, 2, 4, 1, 1, 1, 1, 128, 240, 240, 240,,,, -3, 6, 2, 4, 1, 1, 1, 1, 256, 240, 240, 240,,,, -3, 6, 2, 4, 1, 1, 1, 1, 384, 240, 240, 240,,,, -3, 6, 2, 4, 2, 2, 1, 1, 128, 240, 240, 240,,,, -3, 6, 2, 4, 2, 2, 1, 1, 256, 240, 240, 240,,,, -3, 6, 2, 4, 2, 2, 1, 1, 384, 240, 240, 240,,,, -3, 6, 2, 4, 2, 2, 1, 2, 128, 240, 240, 240,,,, -3, 6, 2, 4, 2, 2, 1, 2, 256, 240, 240, 240,,,, -3, 6, 2, 4, 2, 2, 1, 2, 384, 240, 240, 240,,,, -3, 6, 2, 4, 2, 2, 2, 1, 128, 240, 240, 240,,,, -3, 6, 2, 4, 2, 2, 2, 1, 256, 240, 240, 240,,,, -3, 6, 2, 4, 2, 2, 2, 1, 384, 240, 240, 240,,,, -3, 6, 2, 4, 2, 2, 2, 2, 128, 240, 240, 240,,,, -3, 6, 2, 4, 2, 2, 2, 2, 256, 240, 240, 240,,,, -3, 6, 2, 4, 2, 2, 2, 2, 384, 240, 240, 240,,,, -3, 6, 2, 4, 3, 3, 1, 1, 128, 240, 240, 240,,,, -3, 6, 2, 4, 3, 3, 1, 1, 256, 240, 240, 240,,,, -3, 6, 2, 4, 3, 3, 1, 1, 384, 240, 240, 240,,,, -3, 6, 2, 4, 3, 3, 1, 2, 128, 240, 240, 240,,,, -3, 6, 2, 4, 3, 3, 1, 2, 256, 240, 240, 240,,,, -3, 6, 2, 4, 3, 3, 1, 2, 384, 240, 240, 240,,,, -3, 6, 2, 4, 3, 3, 1, 3, 128, 240, 240, 240,,,, -3, 6, 2, 4, 3, 3, 1, 3, 256, 240, 240, 240,,,, -3, 6, 2, 4, 3, 3, 1, 3, 384, 240, 240, 240,,,, -3, 6, 2, 4, 3, 3, 2, 1, 128, 240, 240, 240,,,, -3, 6, 2, 4, 3, 3, 2, 1, 256, 240, 240, 240,,,, -3, 6, 2, 4, 3, 3, 2, 1, 384, 240, 240, 240,,,, -3, 6, 2, 4, 3, 3, 2, 2, 128, 240, 240, 240,,,, -3, 6, 2, 4, 3, 3, 2, 2, 256, 240, 240, 240,,,, -3, 6, 2, 4, 3, 3, 2, 2, 384, 240, 240, 240,,,, -3, 6, 2, 4, 3, 3, 2, 3, 128, 240, 240, 240,,,, -3, 6, 2, 4, 3, 3, 2, 3, 256, 240, 240, 240,,,, -3, 6, 2, 4, 3, 3, 2, 3, 384, 240, 240, 240,,,, -3, 6, 2, 4, 3, 3, 3, 1, 128, 240, 240, 240,,,, -3, 6, 2, 4, 3, 3, 3, 1, 256, 240, 240, 240,,,, -3, 6, 2, 4, 3, 3, 3, 1, 384, 240, 240, 240,,,, -3, 6, 2, 4, 3, 3, 3, 2, 128, 240, 240, 240,,,, -3, 6, 2, 4, 3, 3, 3, 2, 256, 240, 240, 240,,,, -3, 6, 2, 4, 3, 3, 3, 2, 384, 240, 240, 240,,,, -3, 6, 2, 4, 3, 3, 3, 3, 128, 240, 240, 240,,,, -3, 6, 2, 4, 3, 3, 3, 3, 256, 240, 240, 240,,,, -3, 6, 2, 4, 3, 3, 3, 3, 384, 240, 240, 240,,,, -3, 6, 2, 5, 1, 1, 1, 1, 128, 240, 240, 240,,,, -3, 6, 2, 5, 1, 1, 1, 1, 256, 240, 240, 240,,,, -3, 6, 2, 5, 1, 1, 1, 1, 384, 240, 240, 240,,,, -3, 6, 2, 5, 2, 2, 1, 1, 128, 240, 240, 240,,,, -3, 6, 2, 5, 2, 2, 1, 1, 256, 240, 240, 240,,,, -3, 6, 2, 5, 2, 2, 1, 1, 384, 240, 240, 240,,,, -3, 6, 2, 5, 2, 2, 1, 2, 128, 240, 240, 240,,,, -3, 6, 2, 5, 2, 2, 1, 2, 256, 240, 240, 240,,,, -3, 6, 2, 5, 2, 2, 1, 2, 384, 240, 240, 240,,,, -3, 6, 2, 5, 2, 2, 2, 1, 128, 240, 240, 240,,,, -3, 6, 2, 5, 2, 2, 2, 1, 256, 240, 240, 240,,,, -3, 6, 2, 5, 2, 2, 2, 1, 384, 240, 240, 240,,,, -3, 6, 2, 5, 2, 2, 2, 2, 128, 240, 240, 240,,,, -3, 6, 2, 5, 2, 2, 2, 2, 256, 240, 240, 240,,,, -3, 6, 2, 5, 2, 2, 2, 2, 384, 240, 240, 240,,,, -3, 6, 2, 5, 3, 3, 1, 1, 128, 240, 240, 240,,,, -3, 6, 2, 5, 3, 3, 1, 1, 256, 240, 240, 240,,,, -3, 6, 2, 5, 3, 3, 1, 1, 384, 240, 240, 240,,,, -3, 6, 2, 5, 3, 3, 1, 2, 128, 240, 240, 240,,,, -3, 6, 2, 5, 3, 3, 1, 2, 256, 240, 240, 240,,,, -3, 6, 2, 5, 3, 3, 1, 2, 384, 240, 240, 240,,,, -3, 6, 2, 5, 3, 3, 1, 3, 128, 240, 240, 240,,,, -3, 6, 2, 5, 3, 3, 1, 3, 256, 240, 240, 240,,,, -3, 6, 2, 5, 3, 3, 1, 3, 384, 240, 240, 240,,,, -3, 6, 2, 5, 3, 3, 2, 1, 128, 240, 240, 240,,,, -3, 6, 2, 5, 3, 3, 2, 1, 256, 240, 240, 240,,,, -3, 6, 2, 5, 3, 3, 2, 1, 384, 240, 240, 240,,,, -3, 6, 2, 5, 3, 3, 2, 2, 128, 240, 240, 240,,,, -3, 6, 2, 5, 3, 3, 2, 2, 256, 240, 240, 240,,,, -3, 6, 2, 5, 3, 3, 2, 2, 384, 240, 240, 240,,,, -3, 6, 2, 5, 3, 3, 2, 3, 128, 240, 240, 240,,,, -3, 6, 2, 5, 3, 3, 2, 3, 256, 240, 240, 240,,,, -3, 6, 2, 5, 3, 3, 2, 3, 384, 240, 240, 240,,,, -3, 6, 2, 5, 3, 3, 3, 1, 128, 240, 240, 240,,,, -3, 6, 2, 5, 3, 3, 3, 1, 256, 240, 240, 240,,,, -3, 6, 2, 5, 3, 3, 3, 1, 384, 240, 240, 240,,,, -3, 6, 2, 5, 3, 3, 3, 2, 128, 240, 240, 240,,,, -3, 6, 2, 5, 3, 3, 3, 2, 256, 240, 240, 240,,,, -3, 6, 2, 5, 3, 3, 3, 2, 384, 240, 240, 240,,,, -3, 6, 2, 5, 3, 3, 3, 3, 128, 240, 240, 240,,,, -3, 6, 2, 5, 3, 3, 3, 3, 256, 240, 240, 240,,,, -3, 6, 2, 5, 3, 3, 3, 3, 384, 240, 240, 240,,,, -3, 6, 2, 6, 1, 1, 1, 1, 128, 240, 240, 240,,,, -3, 6, 2, 6, 1, 1, 1, 1, 256, 240, 240, 240,,,, -3, 6, 2, 6, 1, 1, 1, 1, 384, 240, 240, 240,,,, -3, 6, 2, 6, 2, 2, 1, 1, 128, 240, 240, 240,,,, -3, 6, 2, 6, 2, 2, 1, 1, 256, 240, 240, 240,,,, -3, 6, 2, 6, 2, 2, 1, 1, 384, 240, 240, 240,,,, -3, 6, 2, 6, 2, 2, 1, 2, 128, 240, 240, 240,,,, -3, 6, 2, 6, 2, 2, 1, 2, 256, 240, 240, 240,,,, -3, 6, 2, 6, 2, 2, 1, 2, 384, 240, 240, 240,,,, -3, 6, 2, 6, 2, 2, 2, 1, 128, 240, 240, 240,,,, -3, 6, 2, 6, 2, 2, 2, 1, 256, 240, 240, 240,,,, -3, 6, 2, 6, 2, 2, 2, 1, 384, 240, 240, 240,,,, -3, 6, 2, 6, 2, 2, 2, 2, 128, 240, 240, 240,,,, -3, 6, 2, 6, 2, 2, 2, 2, 256, 240, 240, 240,,,, -3, 6, 2, 6, 2, 2, 2, 2, 384, 240, 240, 240,,,, -3, 6, 2, 6, 3, 3, 1, 1, 128, 240, 240, 240,,,, -3, 6, 2, 6, 3, 3, 1, 1, 256, 240, 240, 240,,,, -3, 6, 2, 6, 3, 3, 1, 1, 384, 240, 240, 240,,,, -3, 6, 2, 6, 3, 3, 1, 2, 128, 240, 240, 240,,,, -3, 6, 2, 6, 3, 3, 1, 2, 256, 240, 240, 240,,,, -3, 6, 2, 6, 3, 3, 1, 2, 384, 240, 240, 240,,,, -3, 6, 2, 6, 3, 3, 1, 3, 128, 240, 240, 240,,,, -3, 6, 2, 6, 3, 3, 1, 3, 256, 240, 240, 240,,,, -3, 6, 2, 6, 3, 3, 1, 3, 384, 240, 240, 240,,,, -3, 6, 2, 6, 3, 3, 2, 1, 128, 240, 240, 240,,,, -3, 6, 2, 6, 3, 3, 2, 1, 256, 240, 240, 240,,,, -3, 6, 2, 6, 3, 3, 2, 1, 384, 240, 240, 240,,,, -3, 6, 2, 6, 3, 3, 2, 2, 128, 240, 240, 240,,,, -3, 6, 2, 6, 3, 3, 2, 2, 256, 240, 240, 240,,,, -3, 6, 2, 6, 3, 3, 2, 2, 384, 240, 240, 240,,,, -3, 6, 2, 6, 3, 3, 2, 3, 128, 240, 240, 240,,,, -3, 6, 2, 6, 3, 3, 2, 3, 256, 240, 240, 240,,,, -3, 6, 2, 6, 3, 3, 2, 3, 384, 240, 240, 240,,,, -3, 6, 2, 6, 3, 3, 3, 1, 128, 240, 240, 240,,,, -3, 6, 2, 6, 3, 3, 3, 1, 256, 240, 240, 240,,,, -3, 6, 2, 6, 3, 3, 3, 1, 384, 240, 240, 240,,,, -3, 6, 2, 6, 3, 3, 3, 2, 128, 240, 240, 240,,,, -3, 6, 2, 6, 3, 3, 3, 2, 256, 240, 240, 240,,,, -3, 6, 2, 6, 3, 3, 3, 2, 384, 240, 240, 240,,,, -3, 6, 2, 6, 3, 3, 3, 3, 128, 240, 240, 240,,,, -3, 6, 2, 6, 3, 3, 3, 3, 256, 240, 240, 240,,,, -3, 6, 2, 6, 3, 3, 3, 3, 384, 240, 240, 240,,,, -3, 6, 3, 1, 1, 1, 1, 1, 128, 133, 133, 90,,,, -3, 6, 3, 1, 1, 1, 1, 1, 256, 133, 133, 90,,,, -3, 6, 3, 1, 1, 1, 1, 1, 384, 133, 133, 90,,,, -3, 6, 3, 1, 2, 2, 1, 1, 128, 133, 129, 90,,,, -3, 6, 3, 1, 2, 2, 1, 1, 256, 133, 129, 90,,,, -3, 6, 3, 1, 2, 2, 1, 1, 384, 133, 129, 90,,,, -3, 6, 3, 1, 2, 2, 1, 2, 128, 133, 129, 90,,,, -3, 6, 3, 1, 2, 2, 1, 2, 256, 133, 129, 90,,,, -3, 6, 3, 1, 2, 2, 1, 2, 384, 133, 129, 90,,,, -3, 6, 3, 1, 2, 2, 2, 1, 128, 133, 129, 90,,,, -3, 6, 3, 1, 2, 2, 2, 1, 256, 133, 129, 90,,,, -3, 6, 3, 1, 2, 2, 2, 1, 384, 133, 129, 90,,,, -3, 6, 3, 1, 2, 2, 2, 2, 128, 133, 129, 90,,,, -3, 6, 3, 1, 2, 2, 2, 2, 256, 133, 129, 90,,,, -3, 6, 3, 1, 2, 2, 2, 2, 384, 133, 129, 90,,,, -3, 6, 3, 1, 3, 3, 1, 1, 128, 131, 121, 90,,,, -3, 6, 3, 1, 3, 3, 1, 1, 256, 131, 121, 90,,,, -3, 6, 3, 1, 3, 3, 1, 1, 384, 131, 121, 90,,,, -3, 6, 3, 1, 3, 3, 1, 2, 128, 131, 121, 90,,,, -3, 6, 3, 1, 3, 3, 1, 2, 256, 131, 121, 90,,,, -3, 6, 3, 1, 3, 3, 1, 2, 384, 131, 121, 90,,,, -3, 6, 3, 1, 3, 3, 1, 3, 128, 131, 121, 90,,,, -3, 6, 3, 1, 3, 3, 1, 3, 256, 131, 121, 90,,,, -3, 6, 3, 1, 3, 3, 1, 3, 384, 131, 121, 90,,,, -3, 6, 3, 1, 3, 3, 2, 1, 128, 131, 121, 90,,,, -3, 6, 3, 1, 3, 3, 2, 1, 256, 131, 121, 90,,,, -3, 6, 3, 1, 3, 3, 2, 1, 384, 131, 121, 90,,,, -3, 6, 3, 1, 3, 3, 2, 2, 128, 131, 121, 90,,,, -3, 6, 3, 1, 3, 3, 2, 2, 256, 131, 121, 90,,,, -3, 6, 3, 1, 3, 3, 2, 2, 384, 131, 121, 90,,,, -3, 6, 3, 1, 3, 3, 2, 3, 128, 131, 121, 90,,,, -3, 6, 3, 1, 3, 3, 2, 3, 256, 131, 121, 90,,,, -3, 6, 3, 1, 3, 3, 2, 3, 384, 131, 121, 90,,,, -3, 6, 3, 1, 3, 3, 3, 1, 128, 131, 121, 90,,,, -3, 6, 3, 1, 3, 3, 3, 1, 256, 131, 121, 90,,,, -3, 6, 3, 1, 3, 3, 3, 1, 384, 131, 121, 90,,,, -3, 6, 3, 1, 3, 3, 3, 2, 128, 131, 121, 90,,,, -3, 6, 3, 1, 3, 3, 3, 2, 256, 131, 121, 90,,,, -3, 6, 3, 1, 3, 3, 3, 2, 384, 131, 121, 90,,,, -3, 6, 3, 1, 3, 3, 3, 3, 128, 131, 121, 90,,,, -3, 6, 3, 1, 3, 3, 3, 3, 256, 131, 121, 90,,,, -3, 6, 3, 1, 3, 3, 3, 3, 384, 131, 121, 90,,,, -3, 6, 3, 2, 1, 1, 1, 1, 128, 240, 240, 175,,,, -3, 6, 3, 2, 1, 1, 1, 1, 256, 240, 240, 175,,,, -3, 6, 3, 2, 1, 1, 1, 1, 384, 240, 240, 175,,,, -3, 6, 3, 2, 2, 2, 1, 1, 128, 240, 240, 175,,,, -3, 6, 3, 2, 2, 2, 1, 1, 256, 240, 240, 175,,,, -3, 6, 3, 2, 2, 2, 1, 1, 384, 240, 240, 175,,,, -3, 6, 3, 2, 2, 2, 1, 2, 128, 240, 240, 175,,,, -3, 6, 3, 2, 2, 2, 1, 2, 256, 240, 240, 175,,,, -3, 6, 3, 2, 2, 2, 1, 2, 384, 240, 240, 175,,,, -3, 6, 3, 2, 2, 2, 2, 1, 128, 240, 240, 175,,,, -3, 6, 3, 2, 2, 2, 2, 1, 256, 240, 240, 175,,,, -3, 6, 3, 2, 2, 2, 2, 1, 384, 240, 240, 175,,,, -3, 6, 3, 2, 2, 2, 2, 2, 128, 240, 240, 175,,,, -3, 6, 3, 2, 2, 2, 2, 2, 256, 240, 240, 175,,,, -3, 6, 3, 2, 2, 2, 2, 2, 384, 240, 240, 175,,,, -3, 6, 3, 2, 3, 3, 1, 1, 128, 240, 237, 175,,,, -3, 6, 3, 2, 3, 3, 1, 1, 256, 240, 237, 175,,,, -3, 6, 3, 2, 3, 3, 1, 1, 384, 240, 237, 175,,,, -3, 6, 3, 2, 3, 3, 1, 2, 128, 240, 237, 175,,,, -3, 6, 3, 2, 3, 3, 1, 2, 256, 240, 237, 175,,,, -3, 6, 3, 2, 3, 3, 1, 2, 384, 240, 237, 175,,,, -3, 6, 3, 2, 3, 3, 1, 3, 128, 240, 237, 175,,,, -3, 6, 3, 2, 3, 3, 1, 3, 256, 240, 237, 175,,,, -3, 6, 3, 2, 3, 3, 1, 3, 384, 240, 237, 175,,,, -3, 6, 3, 2, 3, 3, 2, 1, 128, 240, 237, 175,,,, -3, 6, 3, 2, 3, 3, 2, 1, 256, 240, 237, 175,,,, -3, 6, 3, 2, 3, 3, 2, 1, 384, 240, 237, 175,,,, -3, 6, 3, 2, 3, 3, 2, 2, 128, 240, 237, 175,,,, -3, 6, 3, 2, 3, 3, 2, 2, 256, 240, 237, 175,,,, -3, 6, 3, 2, 3, 3, 2, 2, 384, 240, 237, 175,,,, -3, 6, 3, 2, 3, 3, 2, 3, 128, 240, 237, 175,,,, -3, 6, 3, 2, 3, 3, 2, 3, 256, 240, 237, 175,,,, -3, 6, 3, 2, 3, 3, 2, 3, 384, 240, 237, 175,,,, -3, 6, 3, 2, 3, 3, 3, 1, 128, 240, 237, 175,,,, -3, 6, 3, 2, 3, 3, 3, 1, 256, 240, 237, 175,,,, -3, 6, 3, 2, 3, 3, 3, 1, 384, 240, 237, 175,,,, -3, 6, 3, 2, 3, 3, 3, 2, 128, 240, 237, 175,,,, -3, 6, 3, 2, 3, 3, 3, 2, 256, 240, 237, 175,,,, -3, 6, 3, 2, 3, 3, 3, 2, 384, 240, 237, 175,,,, -3, 6, 3, 2, 3, 3, 3, 3, 128, 240, 237, 175,,,, -3, 6, 3, 2, 3, 3, 3, 3, 256, 240, 237, 175,,,, -3, 6, 3, 2, 3, 3, 3, 3, 384, 240, 237, 175,,,, -3, 6, 3, 3, 1, 1, 1, 1, 128, 240, 240, 240,,,, -3, 6, 3, 3, 1, 1, 1, 1, 256, 240, 240, 240,,,, -3, 6, 3, 3, 1, 1, 1, 1, 384, 240, 240, 240,,,, -3, 6, 3, 3, 2, 2, 1, 1, 128, 240, 240, 240,,,, -3, 6, 3, 3, 2, 2, 1, 1, 256, 240, 240, 240,,,, -3, 6, 3, 3, 2, 2, 1, 1, 384, 240, 240, 240,,,, -3, 6, 3, 3, 2, 2, 1, 2, 128, 240, 240, 240,,,, -3, 6, 3, 3, 2, 2, 1, 2, 256, 240, 240, 240,,,, -3, 6, 3, 3, 2, 2, 1, 2, 384, 240, 240, 240,,,, -3, 6, 3, 3, 2, 2, 2, 1, 128, 240, 240, 240,,,, -3, 6, 3, 3, 2, 2, 2, 1, 256, 240, 240, 240,,,, -3, 6, 3, 3, 2, 2, 2, 1, 384, 240, 240, 240,,,, -3, 6, 3, 3, 2, 2, 2, 2, 128, 240, 240, 240,,,, -3, 6, 3, 3, 2, 2, 2, 2, 256, 240, 240, 240,,,, -3, 6, 3, 3, 2, 2, 2, 2, 384, 240, 240, 240,,,, -3, 6, 3, 3, 3, 3, 1, 1, 128, 240, 240, 240,,,, -3, 6, 3, 3, 3, 3, 1, 1, 256, 240, 240, 240,,,, -3, 6, 3, 3, 3, 3, 1, 1, 384, 240, 240, 240,,,, -3, 6, 3, 3, 3, 3, 1, 2, 128, 240, 240, 240,,,, -3, 6, 3, 3, 3, 3, 1, 2, 256, 240, 240, 240,,,, -3, 6, 3, 3, 3, 3, 1, 2, 384, 240, 240, 240,,,, -3, 6, 3, 3, 3, 3, 1, 3, 128, 240, 240, 240,,,, -3, 6, 3, 3, 3, 3, 1, 3, 256, 240, 240, 240,,,, -3, 6, 3, 3, 3, 3, 1, 3, 384, 240, 240, 240,,,, -3, 6, 3, 3, 3, 3, 2, 1, 128, 240, 240, 240,,,, -3, 6, 3, 3, 3, 3, 2, 1, 256, 240, 240, 240,,,, -3, 6, 3, 3, 3, 3, 2, 1, 384, 240, 240, 240,,,, -3, 6, 3, 3, 3, 3, 2, 2, 128, 240, 240, 240,,,, -3, 6, 3, 3, 3, 3, 2, 2, 256, 240, 240, 240,,,, -3, 6, 3, 3, 3, 3, 2, 2, 384, 240, 240, 240,,,, -3, 6, 3, 3, 3, 3, 2, 3, 128, 240, 240, 240,,,, -3, 6, 3, 3, 3, 3, 2, 3, 256, 240, 240, 240,,,, -3, 6, 3, 3, 3, 3, 2, 3, 384, 240, 240, 240,,,, -3, 6, 3, 3, 3, 3, 3, 1, 128, 240, 240, 240,,,, -3, 6, 3, 3, 3, 3, 3, 1, 256, 240, 240, 240,,,, -3, 6, 3, 3, 3, 3, 3, 1, 384, 240, 240, 240,,,, -3, 6, 3, 3, 3, 3, 3, 2, 128, 240, 240, 240,,,, -3, 6, 3, 3, 3, 3, 3, 2, 256, 240, 240, 240,,,, -3, 6, 3, 3, 3, 3, 3, 2, 384, 240, 240, 240,,,, -3, 6, 3, 3, 3, 3, 3, 3, 128, 240, 240, 240,,,, -3, 6, 3, 3, 3, 3, 3, 3, 256, 240, 240, 240,,,, -3, 6, 3, 3, 3, 3, 3, 3, 384, 240, 240, 240,,,, -3, 6, 3, 4, 1, 1, 1, 1, 128, 240, 240, 240,,,, -3, 6, 3, 4, 1, 1, 1, 1, 256, 240, 240, 240,,,, -3, 6, 3, 4, 1, 1, 1, 1, 384, 240, 240, 240,,,, -3, 6, 3, 4, 2, 2, 1, 1, 128, 240, 240, 240,,,, -3, 6, 3, 4, 2, 2, 1, 1, 256, 240, 240, 240,,,, -3, 6, 3, 4, 2, 2, 1, 1, 384, 240, 240, 240,,,, -3, 6, 3, 4, 2, 2, 1, 2, 128, 240, 240, 240,,,, -3, 6, 3, 4, 2, 2, 1, 2, 256, 240, 240, 240,,,, -3, 6, 3, 4, 2, 2, 1, 2, 384, 240, 240, 240,,,, -3, 6, 3, 4, 2, 2, 2, 1, 128, 240, 240, 240,,,, -3, 6, 3, 4, 2, 2, 2, 1, 256, 240, 240, 240,,,, -3, 6, 3, 4, 2, 2, 2, 1, 384, 240, 240, 240,,,, -3, 6, 3, 4, 2, 2, 2, 2, 128, 240, 240, 240,,,, -3, 6, 3, 4, 2, 2, 2, 2, 256, 240, 240, 240,,,, -3, 6, 3, 4, 2, 2, 2, 2, 384, 240, 240, 240,,,, -3, 6, 3, 4, 3, 3, 1, 1, 128, 240, 240, 240,,,, -3, 6, 3, 4, 3, 3, 1, 1, 256, 240, 240, 240,,,, -3, 6, 3, 4, 3, 3, 1, 1, 384, 240, 240, 240,,,, -3, 6, 3, 4, 3, 3, 1, 2, 128, 240, 240, 240,,,, -3, 6, 3, 4, 3, 3, 1, 2, 256, 240, 240, 240,,,, -3, 6, 3, 4, 3, 3, 1, 2, 384, 240, 240, 240,,,, -3, 6, 3, 4, 3, 3, 1, 3, 128, 240, 240, 240,,,, -3, 6, 3, 4, 3, 3, 1, 3, 256, 240, 240, 240,,,, -3, 6, 3, 4, 3, 3, 1, 3, 384, 240, 240, 240,,,, -3, 6, 3, 4, 3, 3, 2, 1, 128, 240, 240, 240,,,, -3, 6, 3, 4, 3, 3, 2, 1, 256, 240, 240, 240,,,, -3, 6, 3, 4, 3, 3, 2, 1, 384, 240, 240, 240,,,, -3, 6, 3, 4, 3, 3, 2, 2, 128, 240, 240, 240,,,, -3, 6, 3, 4, 3, 3, 2, 2, 256, 240, 240, 240,,,, -3, 6, 3, 4, 3, 3, 2, 2, 384, 240, 240, 240,,,, -3, 6, 3, 4, 3, 3, 2, 3, 128, 240, 240, 240,,,, -3, 6, 3, 4, 3, 3, 2, 3, 256, 240, 240, 240,,,, -3, 6, 3, 4, 3, 3, 2, 3, 384, 240, 240, 240,,,, -3, 6, 3, 4, 3, 3, 3, 1, 128, 240, 240, 240,,,, -3, 6, 3, 4, 3, 3, 3, 1, 256, 240, 240, 240,,,, -3, 6, 3, 4, 3, 3, 3, 1, 384, 240, 240, 240,,,, -3, 6, 3, 4, 3, 3, 3, 2, 128, 240, 240, 240,,,, -3, 6, 3, 4, 3, 3, 3, 2, 256, 240, 240, 240,,,, -3, 6, 3, 4, 3, 3, 3, 2, 384, 240, 240, 240,,,, -3, 6, 3, 4, 3, 3, 3, 3, 128, 240, 240, 240,,,, -3, 6, 3, 4, 3, 3, 3, 3, 256, 240, 240, 240,,,, -3, 6, 3, 4, 3, 3, 3, 3, 384, 240, 240, 240,,,, -3, 6, 3, 5, 1, 1, 1, 1, 128, 240, 240, 240,,,, -3, 6, 3, 5, 1, 1, 1, 1, 256, 240, 240, 240,,,, -3, 6, 3, 5, 1, 1, 1, 1, 384, 240, 240, 240,,,, -3, 6, 3, 5, 2, 2, 1, 1, 128, 240, 240, 240,,,, -3, 6, 3, 5, 2, 2, 1, 1, 256, 240, 240, 240,,,, -3, 6, 3, 5, 2, 2, 1, 1, 384, 240, 240, 240,,,, -3, 6, 3, 5, 2, 2, 1, 2, 128, 240, 240, 240,,,, -3, 6, 3, 5, 2, 2, 1, 2, 256, 240, 240, 240,,,, -3, 6, 3, 5, 2, 2, 1, 2, 384, 240, 240, 240,,,, -3, 6, 3, 5, 2, 2, 2, 1, 128, 240, 240, 240,,,, -3, 6, 3, 5, 2, 2, 2, 1, 256, 240, 240, 240,,,, -3, 6, 3, 5, 2, 2, 2, 1, 384, 240, 240, 240,,,, -3, 6, 3, 5, 2, 2, 2, 2, 128, 240, 240, 240,,,, -3, 6, 3, 5, 2, 2, 2, 2, 256, 240, 240, 240,,,, -3, 6, 3, 5, 2, 2, 2, 2, 384, 240, 240, 240,,,, -3, 6, 3, 5, 3, 3, 1, 1, 128, 240, 240, 240,,,, -3, 6, 3, 5, 3, 3, 1, 1, 256, 240, 240, 240,,,, -3, 6, 3, 5, 3, 3, 1, 1, 384, 240, 240, 240,,,, -3, 6, 3, 5, 3, 3, 1, 2, 128, 240, 240, 240,,,, -3, 6, 3, 5, 3, 3, 1, 2, 256, 240, 240, 240,,,, -3, 6, 3, 5, 3, 3, 1, 2, 384, 240, 240, 240,,,, -3, 6, 3, 5, 3, 3, 1, 3, 128, 240, 240, 240,,,, -3, 6, 3, 5, 3, 3, 1, 3, 256, 240, 240, 240,,,, -3, 6, 3, 5, 3, 3, 1, 3, 384, 240, 240, 240,,,, -3, 6, 3, 5, 3, 3, 2, 1, 128, 240, 240, 240,,,, -3, 6, 3, 5, 3, 3, 2, 1, 256, 240, 240, 240,,,, -3, 6, 3, 5, 3, 3, 2, 1, 384, 240, 240, 240,,,, -3, 6, 3, 5, 3, 3, 2, 2, 128, 240, 240, 240,,,, -3, 6, 3, 5, 3, 3, 2, 2, 256, 240, 240, 240,,,, -3, 6, 3, 5, 3, 3, 2, 2, 384, 240, 240, 240,,,, -3, 6, 3, 5, 3, 3, 2, 3, 128, 240, 240, 240,,,, -3, 6, 3, 5, 3, 3, 2, 3, 256, 240, 240, 240,,,, -3, 6, 3, 5, 3, 3, 2, 3, 384, 240, 240, 240,,,, -3, 6, 3, 5, 3, 3, 3, 1, 128, 240, 240, 240,,,, -3, 6, 3, 5, 3, 3, 3, 1, 256, 240, 240, 240,,,, -3, 6, 3, 5, 3, 3, 3, 1, 384, 240, 240, 240,,,, -3, 6, 3, 5, 3, 3, 3, 2, 128, 240, 240, 240,,,, -3, 6, 3, 5, 3, 3, 3, 2, 256, 240, 240, 240,,,, -3, 6, 3, 5, 3, 3, 3, 2, 384, 240, 240, 240,,,, -3, 6, 3, 5, 3, 3, 3, 3, 128, 240, 240, 240,,,, -3, 6, 3, 5, 3, 3, 3, 3, 256, 240, 240, 240,,,, -3, 6, 3, 5, 3, 3, 3, 3, 384, 240, 240, 240,,,, -3, 6, 3, 6, 1, 1, 1, 1, 128, 240, 240, 240,,,, -3, 6, 3, 6, 1, 1, 1, 1, 256, 240, 240, 240,,,, -3, 6, 3, 6, 1, 1, 1, 1, 384, 240, 240, 240,,,, -3, 6, 3, 6, 2, 2, 1, 1, 128, 240, 240, 240,,,, -3, 6, 3, 6, 2, 2, 1, 1, 256, 240, 240, 240,,,, -3, 6, 3, 6, 2, 2, 1, 1, 384, 240, 240, 240,,,, -3, 6, 3, 6, 2, 2, 1, 2, 128, 240, 240, 240,,,, -3, 6, 3, 6, 2, 2, 1, 2, 256, 240, 240, 240,,,, -3, 6, 3, 6, 2, 2, 1, 2, 384, 240, 240, 240,,,, -3, 6, 3, 6, 2, 2, 2, 1, 128, 240, 240, 240,,,, -3, 6, 3, 6, 2, 2, 2, 1, 256, 240, 240, 240,,,, -3, 6, 3, 6, 2, 2, 2, 1, 384, 240, 240, 240,,,, -3, 6, 3, 6, 2, 2, 2, 2, 128, 240, 240, 240,,,, -3, 6, 3, 6, 2, 2, 2, 2, 256, 240, 240, 240,,,, -3, 6, 3, 6, 2, 2, 2, 2, 384, 240, 240, 240,,,, -3, 6, 3, 6, 3, 3, 1, 1, 128, 240, 240, 240,,,, -3, 6, 3, 6, 3, 3, 1, 1, 256, 240, 240, 240,,,, -3, 6, 3, 6, 3, 3, 1, 1, 384, 240, 240, 240,,,, -3, 6, 3, 6, 3, 3, 1, 2, 128, 240, 240, 240,,,, -3, 6, 3, 6, 3, 3, 1, 2, 256, 240, 240, 240,,,, -3, 6, 3, 6, 3, 3, 1, 2, 384, 240, 240, 240,,,, -3, 6, 3, 6, 3, 3, 1, 3, 128, 240, 240, 240,,,, -3, 6, 3, 6, 3, 3, 1, 3, 256, 240, 240, 240,,,, -3, 6, 3, 6, 3, 3, 1, 3, 384, 240, 240, 240,,,, -3, 6, 3, 6, 3, 3, 2, 1, 128, 240, 240, 240,,,, -3, 6, 3, 6, 3, 3, 2, 1, 256, 240, 240, 240,,,, -3, 6, 3, 6, 3, 3, 2, 1, 384, 240, 240, 240,,,, -3, 6, 3, 6, 3, 3, 2, 2, 128, 240, 240, 240,,,, -3, 6, 3, 6, 3, 3, 2, 2, 256, 240, 240, 240,,,, -3, 6, 3, 6, 3, 3, 2, 2, 384, 240, 240, 240,,,, -3, 6, 3, 6, 3, 3, 2, 3, 128, 240, 240, 240,,,, -3, 6, 3, 6, 3, 3, 2, 3, 256, 240, 240, 240,,,, -3, 6, 3, 6, 3, 3, 2, 3, 384, 240, 240, 240,,,, -3, 6, 3, 6, 3, 3, 3, 1, 128, 240, 240, 240,,,, -3, 6, 3, 6, 3, 3, 3, 1, 256, 240, 240, 240,,,, -3, 6, 3, 6, 3, 3, 3, 1, 384, 240, 240, 240,,,, -3, 6, 3, 6, 3, 3, 3, 2, 128, 240, 240, 240,,,, -3, 6, 3, 6, 3, 3, 3, 2, 256, 240, 240, 240,,,, -3, 6, 3, 6, 3, 3, 3, 2, 384, 240, 240, 240,,,, -3, 6, 3, 6, 3, 3, 3, 3, 128, 240, 240, 240,,,, -3, 6, 3, 6, 3, 3, 3, 3, 256, 240, 240, 240,,,, -3, 6, 3, 6, 3, 3, 3, 3, 384, 240, 240, 240,,,, -3, 7, 1, 1, 1, 1, 1, 1, 128, 134, 134, 91,,,, -3, 7, 1, 1, 1, 1, 1, 1, 256, 134, 134, 91,,,, -3, 7, 1, 1, 1, 1, 1, 1, 384, 134, 134, 91,,,, -3, 7, 1, 1, 2, 2, 1, 1, 128, 134, 127, 91,,,, -3, 7, 1, 1, 2, 2, 1, 1, 256, 134, 127, 91,,,, -3, 7, 1, 1, 2, 2, 1, 1, 384, 134, 127, 91,,,, -3, 7, 1, 1, 2, 2, 1, 2, 128, 134, 127, 91,,,, -3, 7, 1, 1, 2, 2, 1, 2, 256, 134, 127, 91,,,, -3, 7, 1, 1, 2, 2, 1, 2, 384, 134, 127, 91,,,, -3, 7, 1, 1, 2, 2, 2, 1, 128, 134, 127, 91,,,, -3, 7, 1, 1, 2, 2, 2, 1, 256, 134, 127, 91,,,, -3, 7, 1, 1, 2, 2, 2, 1, 384, 134, 127, 91,,,, -3, 7, 1, 1, 2, 2, 2, 2, 128, 134, 127, 91,,,, -3, 7, 1, 1, 2, 2, 2, 2, 256, 134, 127, 91,,,, -3, 7, 1, 1, 2, 2, 2, 2, 384, 134, 127, 91,,,, -3, 7, 1, 1, 3, 3, 1, 1, 128, 130, 119, 91,,,, -3, 7, 1, 1, 3, 3, 1, 1, 256, 130, 119, 91,,,, -3, 7, 1, 1, 3, 3, 1, 1, 384, 130, 119, 91,,,, -3, 7, 1, 1, 3, 3, 1, 2, 128, 130, 119, 91,,,, -3, 7, 1, 1, 3, 3, 1, 2, 256, 130, 119, 91,,,, -3, 7, 1, 1, 3, 3, 1, 2, 384, 130, 119, 91,,,, -3, 7, 1, 1, 3, 3, 1, 3, 128, 130, 119, 91,,,, -3, 7, 1, 1, 3, 3, 1, 3, 256, 130, 119, 91,,,, -3, 7, 1, 1, 3, 3, 1, 3, 384, 130, 119, 91,,,, -3, 7, 1, 1, 3, 3, 2, 1, 128, 130, 119, 91,,,, -3, 7, 1, 1, 3, 3, 2, 1, 256, 130, 119, 91,,,, -3, 7, 1, 1, 3, 3, 2, 1, 384, 130, 119, 91,,,, -3, 7, 1, 1, 3, 3, 2, 2, 128, 130, 119, 91,,,, -3, 7, 1, 1, 3, 3, 2, 2, 256, 130, 119, 91,,,, -3, 7, 1, 1, 3, 3, 2, 2, 384, 130, 119, 91,,,, -3, 7, 1, 1, 3, 3, 2, 3, 128, 130, 119, 91,,,, -3, 7, 1, 1, 3, 3, 2, 3, 256, 130, 119, 91,,,, -3, 7, 1, 1, 3, 3, 2, 3, 384, 130, 119, 91,,,, -3, 7, 1, 1, 3, 3, 3, 1, 128, 130, 119, 91,,,, -3, 7, 1, 1, 3, 3, 3, 1, 256, 130, 119, 91,,,, -3, 7, 1, 1, 3, 3, 3, 1, 384, 130, 119, 91,,,, -3, 7, 1, 1, 3, 3, 3, 2, 128, 130, 119, 91,,,, -3, 7, 1, 1, 3, 3, 3, 2, 256, 130, 119, 91,,,, -3, 7, 1, 1, 3, 3, 3, 2, 384, 130, 119, 91,,,, -3, 7, 1, 1, 3, 3, 3, 3, 128, 130, 119, 91,,,, -3, 7, 1, 1, 3, 3, 3, 3, 256, 130, 119, 91,,,, -3, 7, 1, 1, 3, 3, 3, 3, 384, 130, 119, 91,,,, -3, 7, 1, 2, 1, 1, 1, 1, 128, 240, 240, 176,,,, -3, 7, 1, 2, 1, 1, 1, 1, 256, 240, 240, 176,,,, -3, 7, 1, 2, 1, 1, 1, 1, 384, 240, 240, 176,,,, -3, 7, 1, 2, 2, 2, 1, 1, 128, 240, 240, 176,,,, -3, 7, 1, 2, 2, 2, 1, 1, 256, 240, 240, 176,,,, -3, 7, 1, 2, 2, 2, 1, 1, 384, 240, 240, 176,,,, -3, 7, 1, 2, 2, 2, 1, 2, 128, 240, 240, 176,,,, -3, 7, 1, 2, 2, 2, 1, 2, 256, 240, 240, 176,,,, -3, 7, 1, 2, 2, 2, 1, 2, 384, 240, 240, 176,,,, -3, 7, 1, 2, 2, 2, 2, 1, 128, 240, 240, 176,,,, -3, 7, 1, 2, 2, 2, 2, 1, 256, 240, 240, 176,,,, -3, 7, 1, 2, 2, 2, 2, 1, 384, 240, 240, 176,,,, -3, 7, 1, 2, 2, 2, 2, 2, 128, 240, 240, 176,,,, -3, 7, 1, 2, 2, 2, 2, 2, 256, 240, 240, 176,,,, -3, 7, 1, 2, 2, 2, 2, 2, 384, 240, 240, 176,,,, -3, 7, 1, 2, 3, 3, 1, 1, 128, 240, 232, 176,,,, -3, 7, 1, 2, 3, 3, 1, 1, 256, 240, 232, 176,,,, -3, 7, 1, 2, 3, 3, 1, 1, 384, 240, 232, 176,,,, -3, 7, 1, 2, 3, 3, 1, 2, 128, 240, 232, 176,,,, -3, 7, 1, 2, 3, 3, 1, 2, 256, 240, 232, 176,,,, -3, 7, 1, 2, 3, 3, 1, 2, 384, 240, 232, 176,,,, -3, 7, 1, 2, 3, 3, 1, 3, 128, 240, 232, 176,,,, -3, 7, 1, 2, 3, 3, 1, 3, 256, 240, 232, 176,,,, -3, 7, 1, 2, 3, 3, 1, 3, 384, 240, 232, 176,,,, -3, 7, 1, 2, 3, 3, 2, 1, 128, 240, 232, 176,,,, -3, 7, 1, 2, 3, 3, 2, 1, 256, 240, 232, 176,,,, -3, 7, 1, 2, 3, 3, 2, 1, 384, 240, 232, 176,,,, -3, 7, 1, 2, 3, 3, 2, 2, 128, 240, 232, 176,,,, -3, 7, 1, 2, 3, 3, 2, 2, 256, 240, 232, 176,,,, -3, 7, 1, 2, 3, 3, 2, 2, 384, 240, 232, 176,,,, -3, 7, 1, 2, 3, 3, 2, 3, 128, 240, 232, 176,,,, -3, 7, 1, 2, 3, 3, 2, 3, 256, 240, 232, 176,,,, -3, 7, 1, 2, 3, 3, 2, 3, 384, 240, 232, 176,,,, -3, 7, 1, 2, 3, 3, 3, 1, 128, 240, 232, 176,,,, -3, 7, 1, 2, 3, 3, 3, 1, 256, 240, 232, 176,,,, -3, 7, 1, 2, 3, 3, 3, 1, 384, 240, 232, 176,,,, -3, 7, 1, 2, 3, 3, 3, 2, 128, 240, 232, 176,,,, -3, 7, 1, 2, 3, 3, 3, 2, 256, 240, 232, 176,,,, -3, 7, 1, 2, 3, 3, 3, 2, 384, 240, 232, 176,,,, -3, 7, 1, 2, 3, 3, 3, 3, 128, 240, 232, 176,,,, -3, 7, 1, 2, 3, 3, 3, 3, 256, 240, 232, 176,,,, -3, 7, 1, 2, 3, 3, 3, 3, 384, 240, 232, 176,,,, -3, 7, 1, 3, 1, 1, 1, 1, 128, 240, 240, 240,,,, -3, 7, 1, 3, 1, 1, 1, 1, 256, 240, 240, 240,,,, -3, 7, 1, 3, 1, 1, 1, 1, 384, 240, 240, 240,,,, -3, 7, 1, 3, 2, 2, 1, 1, 128, 240, 240, 240,,,, -3, 7, 1, 3, 2, 2, 1, 1, 256, 240, 240, 240,,,, -3, 7, 1, 3, 2, 2, 1, 1, 384, 240, 240, 240,,,, -3, 7, 1, 3, 2, 2, 1, 2, 128, 240, 240, 240,,,, -3, 7, 1, 3, 2, 2, 1, 2, 256, 240, 240, 240,,,, -3, 7, 1, 3, 2, 2, 1, 2, 384, 240, 240, 240,,,, -3, 7, 1, 3, 2, 2, 2, 1, 128, 240, 240, 240,,,, -3, 7, 1, 3, 2, 2, 2, 1, 256, 240, 240, 240,,,, -3, 7, 1, 3, 2, 2, 2, 1, 384, 240, 240, 240,,,, -3, 7, 1, 3, 2, 2, 2, 2, 128, 240, 240, 240,,,, -3, 7, 1, 3, 2, 2, 2, 2, 256, 240, 240, 240,,,, -3, 7, 1, 3, 2, 2, 2, 2, 384, 240, 240, 240,,,, -3, 7, 1, 3, 3, 3, 1, 1, 128, 240, 240, 240,,,, -3, 7, 1, 3, 3, 3, 1, 1, 256, 240, 240, 240,,,, -3, 7, 1, 3, 3, 3, 1, 1, 384, 240, 240, 240,,,, -3, 7, 1, 3, 3, 3, 1, 2, 128, 240, 240, 240,,,, -3, 7, 1, 3, 3, 3, 1, 2, 256, 240, 240, 240,,,, -3, 7, 1, 3, 3, 3, 1, 2, 384, 240, 240, 240,,,, -3, 7, 1, 3, 3, 3, 1, 3, 128, 240, 240, 240,,,, -3, 7, 1, 3, 3, 3, 1, 3, 256, 240, 240, 240,,,, -3, 7, 1, 3, 3, 3, 1, 3, 384, 240, 240, 240,,,, -3, 7, 1, 3, 3, 3, 2, 1, 128, 240, 240, 240,,,, -3, 7, 1, 3, 3, 3, 2, 1, 256, 240, 240, 240,,,, -3, 7, 1, 3, 3, 3, 2, 1, 384, 240, 240, 240,,,, -3, 7, 1, 3, 3, 3, 2, 2, 128, 240, 240, 240,,,, -3, 7, 1, 3, 3, 3, 2, 2, 256, 240, 240, 240,,,, -3, 7, 1, 3, 3, 3, 2, 2, 384, 240, 240, 240,,,, -3, 7, 1, 3, 3, 3, 2, 3, 128, 240, 240, 240,,,, -3, 7, 1, 3, 3, 3, 2, 3, 256, 240, 240, 240,,,, -3, 7, 1, 3, 3, 3, 2, 3, 384, 240, 240, 240,,,, -3, 7, 1, 3, 3, 3, 3, 1, 128, 240, 240, 240,,,, -3, 7, 1, 3, 3, 3, 3, 1, 256, 240, 240, 240,,,, -3, 7, 1, 3, 3, 3, 3, 1, 384, 240, 240, 240,,,, -3, 7, 1, 3, 3, 3, 3, 2, 128, 240, 240, 240,,,, -3, 7, 1, 3, 3, 3, 3, 2, 256, 240, 240, 240,,,, -3, 7, 1, 3, 3, 3, 3, 2, 384, 240, 240, 240,,,, -3, 7, 1, 3, 3, 3, 3, 3, 128, 240, 240, 240,,,, -3, 7, 1, 3, 3, 3, 3, 3, 256, 240, 240, 240,,,, -3, 7, 1, 3, 3, 3, 3, 3, 384, 240, 240, 240,,,, -3, 7, 1, 4, 1, 1, 1, 1, 128, 240, 240, 240,,,, -3, 7, 1, 4, 1, 1, 1, 1, 256, 240, 240, 240,,,, -3, 7, 1, 4, 1, 1, 1, 1, 384, 240, 240, 240,,,, -3, 7, 1, 4, 2, 2, 1, 1, 128, 240, 240, 240,,,, -3, 7, 1, 4, 2, 2, 1, 1, 256, 240, 240, 240,,,, -3, 7, 1, 4, 2, 2, 1, 1, 384, 240, 240, 240,,,, -3, 7, 1, 4, 2, 2, 1, 2, 128, 240, 240, 240,,,, -3, 7, 1, 4, 2, 2, 1, 2, 256, 240, 240, 240,,,, -3, 7, 1, 4, 2, 2, 1, 2, 384, 240, 240, 240,,,, -3, 7, 1, 4, 2, 2, 2, 1, 128, 240, 240, 240,,,, -3, 7, 1, 4, 2, 2, 2, 1, 256, 240, 240, 240,,,, -3, 7, 1, 4, 2, 2, 2, 1, 384, 240, 240, 240,,,, -3, 7, 1, 4, 2, 2, 2, 2, 128, 240, 240, 240,,,, -3, 7, 1, 4, 2, 2, 2, 2, 256, 240, 240, 240,,,, -3, 7, 1, 4, 2, 2, 2, 2, 384, 240, 240, 240,,,, -3, 7, 1, 4, 3, 3, 1, 1, 128, 240, 240, 240,,,, -3, 7, 1, 4, 3, 3, 1, 1, 256, 240, 240, 240,,,, -3, 7, 1, 4, 3, 3, 1, 1, 384, 240, 240, 240,,,, -3, 7, 1, 4, 3, 3, 1, 2, 128, 240, 240, 240,,,, -3, 7, 1, 4, 3, 3, 1, 2, 256, 240, 240, 240,,,, -3, 7, 1, 4, 3, 3, 1, 2, 384, 240, 240, 240,,,, -3, 7, 1, 4, 3, 3, 1, 3, 128, 240, 240, 240,,,, -3, 7, 1, 4, 3, 3, 1, 3, 256, 240, 240, 240,,,, -3, 7, 1, 4, 3, 3, 1, 3, 384, 240, 240, 240,,,, -3, 7, 1, 4, 3, 3, 2, 1, 128, 240, 240, 240,,,, -3, 7, 1, 4, 3, 3, 2, 1, 256, 240, 240, 240,,,, -3, 7, 1, 4, 3, 3, 2, 1, 384, 240, 240, 240,,,, -3, 7, 1, 4, 3, 3, 2, 2, 128, 240, 240, 240,,,, -3, 7, 1, 4, 3, 3, 2, 2, 256, 240, 240, 240,,,, -3, 7, 1, 4, 3, 3, 2, 2, 384, 240, 240, 240,,,, -3, 7, 1, 4, 3, 3, 2, 3, 128, 240, 240, 240,,,, -3, 7, 1, 4, 3, 3, 2, 3, 256, 240, 240, 240,,,, -3, 7, 1, 4, 3, 3, 2, 3, 384, 240, 240, 240,,,, -3, 7, 1, 4, 3, 3, 3, 1, 128, 240, 240, 240,,,, -3, 7, 1, 4, 3, 3, 3, 1, 256, 240, 240, 240,,,, -3, 7, 1, 4, 3, 3, 3, 1, 384, 240, 240, 240,,,, -3, 7, 1, 4, 3, 3, 3, 2, 128, 240, 240, 240,,,, -3, 7, 1, 4, 3, 3, 3, 2, 256, 240, 240, 240,,,, -3, 7, 1, 4, 3, 3, 3, 2, 384, 240, 240, 240,,,, -3, 7, 1, 4, 3, 3, 3, 3, 128, 240, 240, 240,,,, -3, 7, 1, 4, 3, 3, 3, 3, 256, 240, 240, 240,,,, -3, 7, 1, 4, 3, 3, 3, 3, 384, 240, 240, 240,,,, -3, 7, 1, 5, 1, 1, 1, 1, 128, 240, 240, 240,,,, -3, 7, 1, 5, 1, 1, 1, 1, 256, 240, 240, 240,,,, -3, 7, 1, 5, 1, 1, 1, 1, 384, 240, 240, 240,,,, -3, 7, 1, 5, 2, 2, 1, 1, 128, 240, 240, 240,,,, -3, 7, 1, 5, 2, 2, 1, 1, 256, 240, 240, 240,,,, -3, 7, 1, 5, 2, 2, 1, 1, 384, 240, 240, 240,,,, -3, 7, 1, 5, 2, 2, 1, 2, 128, 240, 240, 240,,,, -3, 7, 1, 5, 2, 2, 1, 2, 256, 240, 240, 240,,,, -3, 7, 1, 5, 2, 2, 1, 2, 384, 240, 240, 240,,,, -3, 7, 1, 5, 2, 2, 2, 1, 128, 240, 240, 240,,,, -3, 7, 1, 5, 2, 2, 2, 1, 256, 240, 240, 240,,,, -3, 7, 1, 5, 2, 2, 2, 1, 384, 240, 240, 240,,,, -3, 7, 1, 5, 2, 2, 2, 2, 128, 240, 240, 240,,,, -3, 7, 1, 5, 2, 2, 2, 2, 256, 240, 240, 240,,,, -3, 7, 1, 5, 2, 2, 2, 2, 384, 240, 240, 240,,,, -3, 7, 1, 5, 3, 3, 1, 1, 128, 240, 240, 240,,,, -3, 7, 1, 5, 3, 3, 1, 1, 256, 240, 240, 240,,,, -3, 7, 1, 5, 3, 3, 1, 1, 384, 240, 240, 240,,,, -3, 7, 1, 5, 3, 3, 1, 2, 128, 240, 240, 240,,,, -3, 7, 1, 5, 3, 3, 1, 2, 256, 240, 240, 240,,,, -3, 7, 1, 5, 3, 3, 1, 2, 384, 240, 240, 240,,,, -3, 7, 1, 5, 3, 3, 1, 3, 128, 240, 240, 240,,,, -3, 7, 1, 5, 3, 3, 1, 3, 256, 240, 240, 240,,,, -3, 7, 1, 5, 3, 3, 1, 3, 384, 240, 240, 240,,,, -3, 7, 1, 5, 3, 3, 2, 1, 128, 240, 240, 240,,,, -3, 7, 1, 5, 3, 3, 2, 1, 256, 240, 240, 240,,,, -3, 7, 1, 5, 3, 3, 2, 1, 384, 240, 240, 240,,,, -3, 7, 1, 5, 3, 3, 2, 2, 128, 240, 240, 240,,,, -3, 7, 1, 5, 3, 3, 2, 2, 256, 240, 240, 240,,,, -3, 7, 1, 5, 3, 3, 2, 2, 384, 240, 240, 240,,,, -3, 7, 1, 5, 3, 3, 2, 3, 128, 240, 240, 240,,,, -3, 7, 1, 5, 3, 3, 2, 3, 256, 240, 240, 240,,,, -3, 7, 1, 5, 3, 3, 2, 3, 384, 240, 240, 240,,,, -3, 7, 1, 5, 3, 3, 3, 1, 128, 240, 240, 240,,,, -3, 7, 1, 5, 3, 3, 3, 1, 256, 240, 240, 240,,,, -3, 7, 1, 5, 3, 3, 3, 1, 384, 240, 240, 240,,,, -3, 7, 1, 5, 3, 3, 3, 2, 128, 240, 240, 240,,,, -3, 7, 1, 5, 3, 3, 3, 2, 256, 240, 240, 240,,,, -3, 7, 1, 5, 3, 3, 3, 2, 384, 240, 240, 240,,,, -3, 7, 1, 5, 3, 3, 3, 3, 128, 240, 240, 240,,,, -3, 7, 1, 5, 3, 3, 3, 3, 256, 240, 240, 240,,,, -3, 7, 1, 5, 3, 3, 3, 3, 384, 240, 240, 240,,,, -3, 7, 1, 6, 1, 1, 1, 1, 128, 240, 240, 240,,,, -3, 7, 1, 6, 1, 1, 1, 1, 256, 240, 240, 240,,,, -3, 7, 1, 6, 1, 1, 1, 1, 384, 240, 240, 240,,,, -3, 7, 1, 6, 2, 2, 1, 1, 128, 240, 240, 240,,,, -3, 7, 1, 6, 2, 2, 1, 1, 256, 240, 240, 240,,,, -3, 7, 1, 6, 2, 2, 1, 1, 384, 240, 240, 240,,,, -3, 7, 1, 6, 2, 2, 1, 2, 128, 240, 240, 240,,,, -3, 7, 1, 6, 2, 2, 1, 2, 256, 240, 240, 240,,,, -3, 7, 1, 6, 2, 2, 1, 2, 384, 240, 240, 240,,,, -3, 7, 1, 6, 2, 2, 2, 1, 128, 240, 240, 240,,,, -3, 7, 1, 6, 2, 2, 2, 1, 256, 240, 240, 240,,,, -3, 7, 1, 6, 2, 2, 2, 1, 384, 240, 240, 240,,,, -3, 7, 1, 6, 2, 2, 2, 2, 128, 240, 240, 240,,,, -3, 7, 1, 6, 2, 2, 2, 2, 256, 240, 240, 240,,,, -3, 7, 1, 6, 2, 2, 2, 2, 384, 240, 240, 240,,,, -3, 7, 1, 6, 3, 3, 1, 1, 128, 240, 240, 240,,,, -3, 7, 1, 6, 3, 3, 1, 1, 256, 240, 240, 240,,,, -3, 7, 1, 6, 3, 3, 1, 1, 384, 240, 240, 240,,,, -3, 7, 1, 6, 3, 3, 1, 2, 128, 240, 240, 240,,,, -3, 7, 1, 6, 3, 3, 1, 2, 256, 240, 240, 240,,,, -3, 7, 1, 6, 3, 3, 1, 2, 384, 240, 240, 240,,,, -3, 7, 1, 6, 3, 3, 1, 3, 128, 240, 240, 240,,,, -3, 7, 1, 6, 3, 3, 1, 3, 256, 240, 240, 240,,,, -3, 7, 1, 6, 3, 3, 1, 3, 384, 240, 240, 240,,,, -3, 7, 1, 6, 3, 3, 2, 1, 128, 240, 240, 240,,,, -3, 7, 1, 6, 3, 3, 2, 1, 256, 240, 240, 240,,,, -3, 7, 1, 6, 3, 3, 2, 1, 384, 240, 240, 240,,,, -3, 7, 1, 6, 3, 3, 2, 2, 128, 240, 240, 240,,,, -3, 7, 1, 6, 3, 3, 2, 2, 256, 240, 240, 240,,,, -3, 7, 1, 6, 3, 3, 2, 2, 384, 240, 240, 240,,,, -3, 7, 1, 6, 3, 3, 2, 3, 128, 240, 240, 240,,,, -3, 7, 1, 6, 3, 3, 2, 3, 256, 240, 240, 240,,,, -3, 7, 1, 6, 3, 3, 2, 3, 384, 240, 240, 240,,,, -3, 7, 1, 6, 3, 3, 3, 1, 128, 240, 240, 240,,,, -3, 7, 1, 6, 3, 3, 3, 1, 256, 240, 240, 240,,,, -3, 7, 1, 6, 3, 3, 3, 1, 384, 240, 240, 240,,,, -3, 7, 1, 6, 3, 3, 3, 2, 128, 240, 240, 240,,,, -3, 7, 1, 6, 3, 3, 3, 2, 256, 240, 240, 240,,,, -3, 7, 1, 6, 3, 3, 3, 2, 384, 240, 240, 240,,,, -3, 7, 1, 6, 3, 3, 3, 3, 128, 240, 240, 240,,,, -3, 7, 1, 6, 3, 3, 3, 3, 256, 240, 240, 240,,,, -3, 7, 1, 6, 3, 3, 3, 3, 384, 240, 240, 240,,,, -3, 7, 1, 7, 1, 1, 1, 1, 128, 240, 240, 240,,,, -3, 7, 1, 7, 1, 1, 1, 1, 256, 240, 240, 240,,,, -3, 7, 1, 7, 1, 1, 1, 1, 384, 240, 240, 240,,,, -3, 7, 1, 7, 2, 2, 1, 1, 128, 240, 240, 240,,,, -3, 7, 1, 7, 2, 2, 1, 1, 256, 240, 240, 240,,,, -3, 7, 1, 7, 2, 2, 1, 1, 384, 240, 240, 240,,,, -3, 7, 1, 7, 2, 2, 1, 2, 128, 240, 240, 240,,,, -3, 7, 1, 7, 2, 2, 1, 2, 256, 240, 240, 240,,,, -3, 7, 1, 7, 2, 2, 1, 2, 384, 240, 240, 240,,,, -3, 7, 1, 7, 2, 2, 2, 1, 128, 240, 240, 240,,,, -3, 7, 1, 7, 2, 2, 2, 1, 256, 240, 240, 240,,,, -3, 7, 1, 7, 2, 2, 2, 1, 384, 240, 240, 240,,,, -3, 7, 1, 7, 2, 2, 2, 2, 128, 240, 240, 240,,,, -3, 7, 1, 7, 2, 2, 2, 2, 256, 240, 240, 240,,,, -3, 7, 1, 7, 2, 2, 2, 2, 384, 240, 240, 240,,,, -3, 7, 1, 7, 3, 3, 1, 1, 128, 240, 240, 240,,,, -3, 7, 1, 7, 3, 3, 1, 1, 256, 240, 240, 240,,,, -3, 7, 1, 7, 3, 3, 1, 1, 384, 240, 240, 240,,,, -3, 7, 1, 7, 3, 3, 1, 2, 128, 240, 240, 240,,,, -3, 7, 1, 7, 3, 3, 1, 2, 256, 240, 240, 240,,,, -3, 7, 1, 7, 3, 3, 1, 2, 384, 240, 240, 240,,,, -3, 7, 1, 7, 3, 3, 1, 3, 128, 240, 240, 240,,,, -3, 7, 1, 7, 3, 3, 1, 3, 256, 240, 240, 240,,,, -3, 7, 1, 7, 3, 3, 1, 3, 384, 240, 240, 240,,,, -3, 7, 1, 7, 3, 3, 2, 1, 128, 240, 240, 240,,,, -3, 7, 1, 7, 3, 3, 2, 1, 256, 240, 240, 240,,,, -3, 7, 1, 7, 3, 3, 2, 1, 384, 240, 240, 240,,,, -3, 7, 1, 7, 3, 3, 2, 2, 128, 240, 240, 240,,,, -3, 7, 1, 7, 3, 3, 2, 2, 256, 240, 240, 240,,,, -3, 7, 1, 7, 3, 3, 2, 2, 384, 240, 240, 240,,,, -3, 7, 1, 7, 3, 3, 2, 3, 128, 240, 240, 240,,,, -3, 7, 1, 7, 3, 3, 2, 3, 256, 240, 240, 240,,,, -3, 7, 1, 7, 3, 3, 2, 3, 384, 240, 240, 240,,,, -3, 7, 1, 7, 3, 3, 3, 1, 128, 240, 240, 240,,,, -3, 7, 1, 7, 3, 3, 3, 1, 256, 240, 240, 240,,,, -3, 7, 1, 7, 3, 3, 3, 1, 384, 240, 240, 240,,,, -3, 7, 1, 7, 3, 3, 3, 2, 128, 240, 240, 240,,,, -3, 7, 1, 7, 3, 3, 3, 2, 256, 240, 240, 240,,,, -3, 7, 1, 7, 3, 3, 3, 2, 384, 240, 240, 240,,,, -3, 7, 1, 7, 3, 3, 3, 3, 128, 240, 240, 240,,,, -3, 7, 1, 7, 3, 3, 3, 3, 256, 240, 240, 240,,,, -3, 7, 1, 7, 3, 3, 3, 3, 384, 240, 240, 240,,,, -3, 7, 2, 1, 1, 1, 1, 1, 128, 134, 134, 91,,,, -3, 7, 2, 1, 1, 1, 1, 1, 256, 134, 134, 91,,,, -3, 7, 2, 1, 1, 1, 1, 1, 384, 134, 134, 91,,,, -3, 7, 2, 1, 2, 2, 1, 1, 128, 134, 127, 91,,,, -3, 7, 2, 1, 2, 2, 1, 1, 256, 134, 127, 91,,,, -3, 7, 2, 1, 2, 2, 1, 1, 384, 134, 127, 91,,,, -3, 7, 2, 1, 2, 2, 1, 2, 128, 134, 127, 91,,,, -3, 7, 2, 1, 2, 2, 1, 2, 256, 134, 127, 91,,,, -3, 7, 2, 1, 2, 2, 1, 2, 384, 134, 127, 91,,,, -3, 7, 2, 1, 2, 2, 2, 1, 128, 134, 127, 91,,,, -3, 7, 2, 1, 2, 2, 2, 1, 256, 134, 127, 91,,,, -3, 7, 2, 1, 2, 2, 2, 1, 384, 134, 127, 91,,,, -3, 7, 2, 1, 2, 2, 2, 2, 128, 134, 127, 91,,,, -3, 7, 2, 1, 2, 2, 2, 2, 256, 134, 127, 91,,,, -3, 7, 2, 1, 2, 2, 2, 2, 384, 134, 127, 91,,,, -3, 7, 2, 1, 3, 3, 1, 1, 128, 130, 119, 91,,,, -3, 7, 2, 1, 3, 3, 1, 1, 256, 130, 119, 91,,,, -3, 7, 2, 1, 3, 3, 1, 1, 384, 130, 119, 91,,,, -3, 7, 2, 1, 3, 3, 1, 2, 128, 130, 119, 91,,,, -3, 7, 2, 1, 3, 3, 1, 2, 256, 130, 119, 91,,,, -3, 7, 2, 1, 3, 3, 1, 2, 384, 130, 119, 91,,,, -3, 7, 2, 1, 3, 3, 1, 3, 128, 130, 119, 91,,,, -3, 7, 2, 1, 3, 3, 1, 3, 256, 130, 119, 91,,,, -3, 7, 2, 1, 3, 3, 1, 3, 384, 130, 119, 91,,,, -3, 7, 2, 1, 3, 3, 2, 1, 128, 130, 119, 91,,,, -3, 7, 2, 1, 3, 3, 2, 1, 256, 130, 119, 91,,,, -3, 7, 2, 1, 3, 3, 2, 1, 384, 130, 119, 91,,,, -3, 7, 2, 1, 3, 3, 2, 2, 128, 130, 119, 91,,,, -3, 7, 2, 1, 3, 3, 2, 2, 256, 130, 119, 91,,,, -3, 7, 2, 1, 3, 3, 2, 2, 384, 130, 119, 91,,,, -3, 7, 2, 1, 3, 3, 2, 3, 128, 130, 119, 91,,,, -3, 7, 2, 1, 3, 3, 2, 3, 256, 130, 119, 91,,,, -3, 7, 2, 1, 3, 3, 2, 3, 384, 130, 119, 91,,,, -3, 7, 2, 1, 3, 3, 3, 1, 128, 130, 119, 91,,,, -3, 7, 2, 1, 3, 3, 3, 1, 256, 130, 119, 91,,,, -3, 7, 2, 1, 3, 3, 3, 1, 384, 130, 119, 91,,,, -3, 7, 2, 1, 3, 3, 3, 2, 128, 130, 119, 91,,,, -3, 7, 2, 1, 3, 3, 3, 2, 256, 130, 119, 91,,,, -3, 7, 2, 1, 3, 3, 3, 2, 384, 130, 119, 91,,,, -3, 7, 2, 1, 3, 3, 3, 3, 128, 130, 119, 91,,,, -3, 7, 2, 1, 3, 3, 3, 3, 256, 130, 119, 91,,,, -3, 7, 2, 1, 3, 3, 3, 3, 384, 130, 119, 91,,,, -3, 7, 2, 2, 1, 1, 1, 1, 128, 240, 240, 176,,,, -3, 7, 2, 2, 1, 1, 1, 1, 256, 240, 240, 176,,,, -3, 7, 2, 2, 1, 1, 1, 1, 384, 240, 240, 176,,,, -3, 7, 2, 2, 2, 2, 1, 1, 128, 240, 240, 176,,,, -3, 7, 2, 2, 2, 2, 1, 1, 256, 240, 240, 176,,,, -3, 7, 2, 2, 2, 2, 1, 1, 384, 240, 240, 176,,,, -3, 7, 2, 2, 2, 2, 1, 2, 128, 240, 240, 176,,,, -3, 7, 2, 2, 2, 2, 1, 2, 256, 240, 240, 176,,,, -3, 7, 2, 2, 2, 2, 1, 2, 384, 240, 240, 176,,,, -3, 7, 2, 2, 2, 2, 2, 1, 128, 240, 240, 176,,,, -3, 7, 2, 2, 2, 2, 2, 1, 256, 240, 240, 176,,,, -3, 7, 2, 2, 2, 2, 2, 1, 384, 240, 240, 176,,,, -3, 7, 2, 2, 2, 2, 2, 2, 128, 240, 240, 176,,,, -3, 7, 2, 2, 2, 2, 2, 2, 256, 240, 240, 176,,,, -3, 7, 2, 2, 2, 2, 2, 2, 384, 240, 240, 176,,,, -3, 7, 2, 2, 3, 3, 1, 1, 128, 240, 232, 176,,,, -3, 7, 2, 2, 3, 3, 1, 1, 256, 240, 232, 176,,,, -3, 7, 2, 2, 3, 3, 1, 1, 384, 240, 232, 176,,,, -3, 7, 2, 2, 3, 3, 1, 2, 128, 240, 232, 176,,,, -3, 7, 2, 2, 3, 3, 1, 2, 256, 240, 232, 176,,,, -3, 7, 2, 2, 3, 3, 1, 2, 384, 240, 232, 176,,,, -3, 7, 2, 2, 3, 3, 1, 3, 128, 240, 232, 176,,,, -3, 7, 2, 2, 3, 3, 1, 3, 256, 240, 232, 176,,,, -3, 7, 2, 2, 3, 3, 1, 3, 384, 240, 232, 176,,,, -3, 7, 2, 2, 3, 3, 2, 1, 128, 240, 232, 176,,,, -3, 7, 2, 2, 3, 3, 2, 1, 256, 240, 232, 176,,,, -3, 7, 2, 2, 3, 3, 2, 1, 384, 240, 232, 176,,,, -3, 7, 2, 2, 3, 3, 2, 2, 128, 240, 232, 176,,,, -3, 7, 2, 2, 3, 3, 2, 2, 256, 240, 232, 176,,,, -3, 7, 2, 2, 3, 3, 2, 2, 384, 240, 232, 176,,,, -3, 7, 2, 2, 3, 3, 2, 3, 128, 240, 232, 176,,,, -3, 7, 2, 2, 3, 3, 2, 3, 256, 240, 232, 176,,,, -3, 7, 2, 2, 3, 3, 2, 3, 384, 240, 232, 176,,,, -3, 7, 2, 2, 3, 3, 3, 1, 128, 240, 232, 176,,,, -3, 7, 2, 2, 3, 3, 3, 1, 256, 240, 232, 176,,,, -3, 7, 2, 2, 3, 3, 3, 1, 384, 240, 232, 176,,,, -3, 7, 2, 2, 3, 3, 3, 2, 128, 240, 232, 176,,,, -3, 7, 2, 2, 3, 3, 3, 2, 256, 240, 232, 176,,,, -3, 7, 2, 2, 3, 3, 3, 2, 384, 240, 232, 176,,,, -3, 7, 2, 2, 3, 3, 3, 3, 128, 240, 232, 176,,,, -3, 7, 2, 2, 3, 3, 3, 3, 256, 240, 232, 176,,,, -3, 7, 2, 2, 3, 3, 3, 3, 384, 240, 232, 176,,,, -3, 7, 2, 3, 1, 1, 1, 1, 128, 240, 240, 240,,,, -3, 7, 2, 3, 1, 1, 1, 1, 256, 240, 240, 240,,,, -3, 7, 2, 3, 1, 1, 1, 1, 384, 240, 240, 240,,,, -3, 7, 2, 3, 2, 2, 1, 1, 128, 240, 240, 240,,,, -3, 7, 2, 3, 2, 2, 1, 1, 256, 240, 240, 240,,,, -3, 7, 2, 3, 2, 2, 1, 1, 384, 240, 240, 240,,,, -3, 7, 2, 3, 2, 2, 1, 2, 128, 240, 240, 240,,,, -3, 7, 2, 3, 2, 2, 1, 2, 256, 240, 240, 240,,,, -3, 7, 2, 3, 2, 2, 1, 2, 384, 240, 240, 240,,,, -3, 7, 2, 3, 2, 2, 2, 1, 128, 240, 240, 240,,,, -3, 7, 2, 3, 2, 2, 2, 1, 256, 240, 240, 240,,,, -3, 7, 2, 3, 2, 2, 2, 1, 384, 240, 240, 240,,,, -3, 7, 2, 3, 2, 2, 2, 2, 128, 240, 240, 240,,,, -3, 7, 2, 3, 2, 2, 2, 2, 256, 240, 240, 240,,,, -3, 7, 2, 3, 2, 2, 2, 2, 384, 240, 240, 240,,,, -3, 7, 2, 3, 3, 3, 1, 1, 128, 240, 240, 240,,,, -3, 7, 2, 3, 3, 3, 1, 1, 256, 240, 240, 240,,,, -3, 7, 2, 3, 3, 3, 1, 1, 384, 240, 240, 240,,,, -3, 7, 2, 3, 3, 3, 1, 2, 128, 240, 240, 240,,,, -3, 7, 2, 3, 3, 3, 1, 2, 256, 240, 240, 240,,,, -3, 7, 2, 3, 3, 3, 1, 2, 384, 240, 240, 240,,,, -3, 7, 2, 3, 3, 3, 1, 3, 128, 240, 240, 240,,,, -3, 7, 2, 3, 3, 3, 1, 3, 256, 240, 240, 240,,,, -3, 7, 2, 3, 3, 3, 1, 3, 384, 240, 240, 240,,,, -3, 7, 2, 3, 3, 3, 2, 1, 128, 240, 240, 240,,,, -3, 7, 2, 3, 3, 3, 2, 1, 256, 240, 240, 240,,,, -3, 7, 2, 3, 3, 3, 2, 1, 384, 240, 240, 240,,,, -3, 7, 2, 3, 3, 3, 2, 2, 128, 240, 240, 240,,,, -3, 7, 2, 3, 3, 3, 2, 2, 256, 240, 240, 240,,,, -3, 7, 2, 3, 3, 3, 2, 2, 384, 240, 240, 240,,,, -3, 7, 2, 3, 3, 3, 2, 3, 128, 240, 240, 240,,,, -3, 7, 2, 3, 3, 3, 2, 3, 256, 240, 240, 240,,,, -3, 7, 2, 3, 3, 3, 2, 3, 384, 240, 240, 240,,,, -3, 7, 2, 3, 3, 3, 3, 1, 128, 240, 240, 240,,,, -3, 7, 2, 3, 3, 3, 3, 1, 256, 240, 240, 240,,,, -3, 7, 2, 3, 3, 3, 3, 1, 384, 240, 240, 240,,,, -3, 7, 2, 3, 3, 3, 3, 2, 128, 240, 240, 240,,,, -3, 7, 2, 3, 3, 3, 3, 2, 256, 240, 240, 240,,,, -3, 7, 2, 3, 3, 3, 3, 2, 384, 240, 240, 240,,,, -3, 7, 2, 3, 3, 3, 3, 3, 128, 240, 240, 240,,,, -3, 7, 2, 3, 3, 3, 3, 3, 256, 240, 240, 240,,,, -3, 7, 2, 3, 3, 3, 3, 3, 384, 240, 240, 240,,,, -3, 7, 2, 4, 1, 1, 1, 1, 128, 240, 240, 240,,,, -3, 7, 2, 4, 1, 1, 1, 1, 256, 240, 240, 240,,,, -3, 7, 2, 4, 1, 1, 1, 1, 384, 240, 240, 240,,,, -3, 7, 2, 4, 2, 2, 1, 1, 128, 240, 240, 240,,,, -3, 7, 2, 4, 2, 2, 1, 1, 256, 240, 240, 240,,,, -3, 7, 2, 4, 2, 2, 1, 1, 384, 240, 240, 240,,,, -3, 7, 2, 4, 2, 2, 1, 2, 128, 240, 240, 240,,,, -3, 7, 2, 4, 2, 2, 1, 2, 256, 240, 240, 240,,,, -3, 7, 2, 4, 2, 2, 1, 2, 384, 240, 240, 240,,,, -3, 7, 2, 4, 2, 2, 2, 1, 128, 240, 240, 240,,,, -3, 7, 2, 4, 2, 2, 2, 1, 256, 240, 240, 240,,,, -3, 7, 2, 4, 2, 2, 2, 1, 384, 240, 240, 240,,,, -3, 7, 2, 4, 2, 2, 2, 2, 128, 240, 240, 240,,,, -3, 7, 2, 4, 2, 2, 2, 2, 256, 240, 240, 240,,,, -3, 7, 2, 4, 2, 2, 2, 2, 384, 240, 240, 240,,,, -3, 7, 2, 4, 3, 3, 1, 1, 128, 240, 240, 240,,,, -3, 7, 2, 4, 3, 3, 1, 1, 256, 240, 240, 240,,,, -3, 7, 2, 4, 3, 3, 1, 1, 384, 240, 240, 240,,,, -3, 7, 2, 4, 3, 3, 1, 2, 128, 240, 240, 240,,,, -3, 7, 2, 4, 3, 3, 1, 2, 256, 240, 240, 240,,,, -3, 7, 2, 4, 3, 3, 1, 2, 384, 240, 240, 240,,,, -3, 7, 2, 4, 3, 3, 1, 3, 128, 240, 240, 240,,,, -3, 7, 2, 4, 3, 3, 1, 3, 256, 240, 240, 240,,,, -3, 7, 2, 4, 3, 3, 1, 3, 384, 240, 240, 240,,,, -3, 7, 2, 4, 3, 3, 2, 1, 128, 240, 240, 240,,,, -3, 7, 2, 4, 3, 3, 2, 1, 256, 240, 240, 240,,,, -3, 7, 2, 4, 3, 3, 2, 1, 384, 240, 240, 240,,,, -3, 7, 2, 4, 3, 3, 2, 2, 128, 240, 240, 240,,,, -3, 7, 2, 4, 3, 3, 2, 2, 256, 240, 240, 240,,,, -3, 7, 2, 4, 3, 3, 2, 2, 384, 240, 240, 240,,,, -3, 7, 2, 4, 3, 3, 2, 3, 128, 240, 240, 240,,,, -3, 7, 2, 4, 3, 3, 2, 3, 256, 240, 240, 240,,,, -3, 7, 2, 4, 3, 3, 2, 3, 384, 240, 240, 240,,,, -3, 7, 2, 4, 3, 3, 3, 1, 128, 240, 240, 240,,,, -3, 7, 2, 4, 3, 3, 3, 1, 256, 240, 240, 240,,,, -3, 7, 2, 4, 3, 3, 3, 1, 384, 240, 240, 240,,,, -3, 7, 2, 4, 3, 3, 3, 2, 128, 240, 240, 240,,,, -3, 7, 2, 4, 3, 3, 3, 2, 256, 240, 240, 240,,,, -3, 7, 2, 4, 3, 3, 3, 2, 384, 240, 240, 240,,,, -3, 7, 2, 4, 3, 3, 3, 3, 128, 240, 240, 240,,,, -3, 7, 2, 4, 3, 3, 3, 3, 256, 240, 240, 240,,,, -3, 7, 2, 4, 3, 3, 3, 3, 384, 240, 240, 240,,,, -3, 7, 2, 5, 1, 1, 1, 1, 128, 240, 240, 240,,,, -3, 7, 2, 5, 1, 1, 1, 1, 256, 240, 240, 240,,,, -3, 7, 2, 5, 1, 1, 1, 1, 384, 240, 240, 240,,,, -3, 7, 2, 5, 2, 2, 1, 1, 128, 240, 240, 240,,,, -3, 7, 2, 5, 2, 2, 1, 1, 256, 240, 240, 240,,,, -3, 7, 2, 5, 2, 2, 1, 1, 384, 240, 240, 240,,,, -3, 7, 2, 5, 2, 2, 1, 2, 128, 240, 240, 240,,,, -3, 7, 2, 5, 2, 2, 1, 2, 256, 240, 240, 240,,,, -3, 7, 2, 5, 2, 2, 1, 2, 384, 240, 240, 240,,,, -3, 7, 2, 5, 2, 2, 2, 1, 128, 240, 240, 240,,,, -3, 7, 2, 5, 2, 2, 2, 1, 256, 240, 240, 240,,,, -3, 7, 2, 5, 2, 2, 2, 1, 384, 240, 240, 240,,,, -3, 7, 2, 5, 2, 2, 2, 2, 128, 240, 240, 240,,,, -3, 7, 2, 5, 2, 2, 2, 2, 256, 240, 240, 240,,,, -3, 7, 2, 5, 2, 2, 2, 2, 384, 240, 240, 240,,,, -3, 7, 2, 5, 3, 3, 1, 1, 128, 240, 240, 240,,,, -3, 7, 2, 5, 3, 3, 1, 1, 256, 240, 240, 240,,,, -3, 7, 2, 5, 3, 3, 1, 1, 384, 240, 240, 240,,,, -3, 7, 2, 5, 3, 3, 1, 2, 128, 240, 240, 240,,,, -3, 7, 2, 5, 3, 3, 1, 2, 256, 240, 240, 240,,,, -3, 7, 2, 5, 3, 3, 1, 2, 384, 240, 240, 240,,,, -3, 7, 2, 5, 3, 3, 1, 3, 128, 240, 240, 240,,,, -3, 7, 2, 5, 3, 3, 1, 3, 256, 240, 240, 240,,,, -3, 7, 2, 5, 3, 3, 1, 3, 384, 240, 240, 240,,,, -3, 7, 2, 5, 3, 3, 2, 1, 128, 240, 240, 240,,,, -3, 7, 2, 5, 3, 3, 2, 1, 256, 240, 240, 240,,,, -3, 7, 2, 5, 3, 3, 2, 1, 384, 240, 240, 240,,,, -3, 7, 2, 5, 3, 3, 2, 2, 128, 240, 240, 240,,,, -3, 7, 2, 5, 3, 3, 2, 2, 256, 240, 240, 240,,,, -3, 7, 2, 5, 3, 3, 2, 2, 384, 240, 240, 240,,,, -3, 7, 2, 5, 3, 3, 2, 3, 128, 240, 240, 240,,,, -3, 7, 2, 5, 3, 3, 2, 3, 256, 240, 240, 240,,,, -3, 7, 2, 5, 3, 3, 2, 3, 384, 240, 240, 240,,,, -3, 7, 2, 5, 3, 3, 3, 1, 128, 240, 240, 240,,,, -3, 7, 2, 5, 3, 3, 3, 1, 256, 240, 240, 240,,,, -3, 7, 2, 5, 3, 3, 3, 1, 384, 240, 240, 240,,,, -3, 7, 2, 5, 3, 3, 3, 2, 128, 240, 240, 240,,,, -3, 7, 2, 5, 3, 3, 3, 2, 256, 240, 240, 240,,,, -3, 7, 2, 5, 3, 3, 3, 2, 384, 240, 240, 240,,,, -3, 7, 2, 5, 3, 3, 3, 3, 128, 240, 240, 240,,,, -3, 7, 2, 5, 3, 3, 3, 3, 256, 240, 240, 240,,,, -3, 7, 2, 5, 3, 3, 3, 3, 384, 240, 240, 240,,,, -3, 7, 2, 6, 1, 1, 1, 1, 128, 240, 240, 240,,,, -3, 7, 2, 6, 1, 1, 1, 1, 256, 240, 240, 240,,,, -3, 7, 2, 6, 1, 1, 1, 1, 384, 240, 240, 240,,,, -3, 7, 2, 6, 2, 2, 1, 1, 128, 240, 240, 240,,,, -3, 7, 2, 6, 2, 2, 1, 1, 256, 240, 240, 240,,,, -3, 7, 2, 6, 2, 2, 1, 1, 384, 240, 240, 240,,,, -3, 7, 2, 6, 2, 2, 1, 2, 128, 240, 240, 240,,,, -3, 7, 2, 6, 2, 2, 1, 2, 256, 240, 240, 240,,,, -3, 7, 2, 6, 2, 2, 1, 2, 384, 240, 240, 240,,,, -3, 7, 2, 6, 2, 2, 2, 1, 128, 240, 240, 240,,,, -3, 7, 2, 6, 2, 2, 2, 1, 256, 240, 240, 240,,,, -3, 7, 2, 6, 2, 2, 2, 1, 384, 240, 240, 240,,,, -3, 7, 2, 6, 2, 2, 2, 2, 128, 240, 240, 240,,,, -3, 7, 2, 6, 2, 2, 2, 2, 256, 240, 240, 240,,,, -3, 7, 2, 6, 2, 2, 2, 2, 384, 240, 240, 240,,,, -3, 7, 2, 6, 3, 3, 1, 1, 128, 240, 240, 240,,,, -3, 7, 2, 6, 3, 3, 1, 1, 256, 240, 240, 240,,,, -3, 7, 2, 6, 3, 3, 1, 1, 384, 240, 240, 240,,,, -3, 7, 2, 6, 3, 3, 1, 2, 128, 240, 240, 240,,,, -3, 7, 2, 6, 3, 3, 1, 2, 256, 240, 240, 240,,,, -3, 7, 2, 6, 3, 3, 1, 2, 384, 240, 240, 240,,,, -3, 7, 2, 6, 3, 3, 1, 3, 128, 240, 240, 240,,,, -3, 7, 2, 6, 3, 3, 1, 3, 256, 240, 240, 240,,,, -3, 7, 2, 6, 3, 3, 1, 3, 384, 240, 240, 240,,,, -3, 7, 2, 6, 3, 3, 2, 1, 128, 240, 240, 240,,,, -3, 7, 2, 6, 3, 3, 2, 1, 256, 240, 240, 240,,,, -3, 7, 2, 6, 3, 3, 2, 1, 384, 240, 240, 240,,,, -3, 7, 2, 6, 3, 3, 2, 2, 128, 240, 240, 240,,,, -3, 7, 2, 6, 3, 3, 2, 2, 256, 240, 240, 240,,,, -3, 7, 2, 6, 3, 3, 2, 2, 384, 240, 240, 240,,,, -3, 7, 2, 6, 3, 3, 2, 3, 128, 240, 240, 240,,,, -3, 7, 2, 6, 3, 3, 2, 3, 256, 240, 240, 240,,,, -3, 7, 2, 6, 3, 3, 2, 3, 384, 240, 240, 240,,,, -3, 7, 2, 6, 3, 3, 3, 1, 128, 240, 240, 240,,,, -3, 7, 2, 6, 3, 3, 3, 1, 256, 240, 240, 240,,,, -3, 7, 2, 6, 3, 3, 3, 1, 384, 240, 240, 240,,,, -3, 7, 2, 6, 3, 3, 3, 2, 128, 240, 240, 240,,,, -3, 7, 2, 6, 3, 3, 3, 2, 256, 240, 240, 240,,,, -3, 7, 2, 6, 3, 3, 3, 2, 384, 240, 240, 240,,,, -3, 7, 2, 6, 3, 3, 3, 3, 128, 240, 240, 240,,,, -3, 7, 2, 6, 3, 3, 3, 3, 256, 240, 240, 240,,,, -3, 7, 2, 6, 3, 3, 3, 3, 384, 240, 240, 240,,,, -3, 7, 2, 7, 1, 1, 1, 1, 128, 240, 240, 240,,,, -3, 7, 2, 7, 1, 1, 1, 1, 256, 240, 240, 240,,,, -3, 7, 2, 7, 1, 1, 1, 1, 384, 240, 240, 240,,,, -3, 7, 2, 7, 2, 2, 1, 1, 128, 240, 240, 240,,,, -3, 7, 2, 7, 2, 2, 1, 1, 256, 240, 240, 240,,,, -3, 7, 2, 7, 2, 2, 1, 1, 384, 240, 240, 240,,,, -3, 7, 2, 7, 2, 2, 1, 2, 128, 240, 240, 240,,,, -3, 7, 2, 7, 2, 2, 1, 2, 256, 240, 240, 240,,,, -3, 7, 2, 7, 2, 2, 1, 2, 384, 240, 240, 240,,,, -3, 7, 2, 7, 2, 2, 2, 1, 128, 240, 240, 240,,,, -3, 7, 2, 7, 2, 2, 2, 1, 256, 240, 240, 240,,,, -3, 7, 2, 7, 2, 2, 2, 1, 384, 240, 240, 240,,,, -3, 7, 2, 7, 2, 2, 2, 2, 128, 240, 240, 240,,,, -3, 7, 2, 7, 2, 2, 2, 2, 256, 240, 240, 240,,,, -3, 7, 2, 7, 2, 2, 2, 2, 384, 240, 240, 240,,,, -3, 7, 2, 7, 3, 3, 1, 1, 128, 240, 240, 240,,,, -3, 7, 2, 7, 3, 3, 1, 1, 256, 240, 240, 240,,,, -3, 7, 2, 7, 3, 3, 1, 1, 384, 240, 240, 240,,,, -3, 7, 2, 7, 3, 3, 1, 2, 128, 240, 240, 240,,,, -3, 7, 2, 7, 3, 3, 1, 2, 256, 240, 240, 240,,,, -3, 7, 2, 7, 3, 3, 1, 2, 384, 240, 240, 240,,,, -3, 7, 2, 7, 3, 3, 1, 3, 128, 240, 240, 240,,,, -3, 7, 2, 7, 3, 3, 1, 3, 256, 240, 240, 240,,,, -3, 7, 2, 7, 3, 3, 1, 3, 384, 240, 240, 240,,,, -3, 7, 2, 7, 3, 3, 2, 1, 128, 240, 240, 240,,,, -3, 7, 2, 7, 3, 3, 2, 1, 256, 240, 240, 240,,,, -3, 7, 2, 7, 3, 3, 2, 1, 384, 240, 240, 240,,,, -3, 7, 2, 7, 3, 3, 2, 2, 128, 240, 240, 240,,,, -3, 7, 2, 7, 3, 3, 2, 2, 256, 240, 240, 240,,,, -3, 7, 2, 7, 3, 3, 2, 2, 384, 240, 240, 240,,,, -3, 7, 2, 7, 3, 3, 2, 3, 128, 240, 240, 240,,,, -3, 7, 2, 7, 3, 3, 2, 3, 256, 240, 240, 240,,,, -3, 7, 2, 7, 3, 3, 2, 3, 384, 240, 240, 240,,,, -3, 7, 2, 7, 3, 3, 3, 1, 128, 240, 240, 240,,,, -3, 7, 2, 7, 3, 3, 3, 1, 256, 240, 240, 240,,,, -3, 7, 2, 7, 3, 3, 3, 1, 384, 240, 240, 240,,,, -3, 7, 2, 7, 3, 3, 3, 2, 128, 240, 240, 240,,,, -3, 7, 2, 7, 3, 3, 3, 2, 256, 240, 240, 240,,,, -3, 7, 2, 7, 3, 3, 3, 2, 384, 240, 240, 240,,,, -3, 7, 2, 7, 3, 3, 3, 3, 128, 240, 240, 240,,,, -3, 7, 2, 7, 3, 3, 3, 3, 256, 240, 240, 240,,,, -3, 7, 2, 7, 3, 3, 3, 3, 384, 240, 240, 240,,,, -3, 7, 3, 1, 1, 1, 1, 1, 128, 134, 134, 91,,,, -3, 7, 3, 1, 1, 1, 1, 1, 256, 134, 134, 91,,,, -3, 7, 3, 1, 1, 1, 1, 1, 384, 134, 134, 91,,,, -3, 7, 3, 1, 2, 2, 1, 1, 128, 134, 127, 91,,,, -3, 7, 3, 1, 2, 2, 1, 1, 256, 134, 127, 91,,,, -3, 7, 3, 1, 2, 2, 1, 1, 384, 134, 127, 91,,,, -3, 7, 3, 1, 2, 2, 1, 2, 128, 134, 127, 91,,,, -3, 7, 3, 1, 2, 2, 1, 2, 256, 134, 127, 91,,,, -3, 7, 3, 1, 2, 2, 1, 2, 384, 134, 127, 91,,,, -3, 7, 3, 1, 2, 2, 2, 1, 128, 134, 127, 91,,,, -3, 7, 3, 1, 2, 2, 2, 1, 256, 134, 127, 91,,,, -3, 7, 3, 1, 2, 2, 2, 1, 384, 134, 127, 91,,,, -3, 7, 3, 1, 2, 2, 2, 2, 128, 134, 127, 91,,,, -3, 7, 3, 1, 2, 2, 2, 2, 256, 134, 127, 91,,,, -3, 7, 3, 1, 2, 2, 2, 2, 384, 134, 127, 91,,,, -3, 7, 3, 1, 3, 3, 1, 1, 128, 130, 119, 91,,,, -3, 7, 3, 1, 3, 3, 1, 1, 256, 130, 119, 91,,,, -3, 7, 3, 1, 3, 3, 1, 1, 384, 130, 119, 91,,,, -3, 7, 3, 1, 3, 3, 1, 2, 128, 130, 119, 91,,,, -3, 7, 3, 1, 3, 3, 1, 2, 256, 130, 119, 91,,,, -3, 7, 3, 1, 3, 3, 1, 2, 384, 130, 119, 91,,,, -3, 7, 3, 1, 3, 3, 1, 3, 128, 130, 119, 91,,,, -3, 7, 3, 1, 3, 3, 1, 3, 256, 130, 119, 91,,,, -3, 7, 3, 1, 3, 3, 1, 3, 384, 130, 119, 91,,,, -3, 7, 3, 1, 3, 3, 2, 1, 128, 130, 119, 91,,,, -3, 7, 3, 1, 3, 3, 2, 1, 256, 130, 119, 91,,,, -3, 7, 3, 1, 3, 3, 2, 1, 384, 130, 119, 91,,,, -3, 7, 3, 1, 3, 3, 2, 2, 128, 130, 119, 91,,,, -3, 7, 3, 1, 3, 3, 2, 2, 256, 130, 119, 91,,,, -3, 7, 3, 1, 3, 3, 2, 2, 384, 130, 119, 91,,,, -3, 7, 3, 1, 3, 3, 2, 3, 128, 130, 119, 91,,,, -3, 7, 3, 1, 3, 3, 2, 3, 256, 130, 119, 91,,,, -3, 7, 3, 1, 3, 3, 2, 3, 384, 130, 119, 91,,,, -3, 7, 3, 1, 3, 3, 3, 1, 128, 130, 119, 91,,,, -3, 7, 3, 1, 3, 3, 3, 1, 256, 130, 119, 91,,,, -3, 7, 3, 1, 3, 3, 3, 1, 384, 130, 119, 91,,,, -3, 7, 3, 1, 3, 3, 3, 2, 128, 130, 119, 91,,,, -3, 7, 3, 1, 3, 3, 3, 2, 256, 130, 119, 91,,,, -3, 7, 3, 1, 3, 3, 3, 2, 384, 130, 119, 91,,,, -3, 7, 3, 1, 3, 3, 3, 3, 128, 130, 119, 91,,,, -3, 7, 3, 1, 3, 3, 3, 3, 256, 130, 119, 91,,,, -3, 7, 3, 1, 3, 3, 3, 3, 384, 130, 119, 91,,,, -3, 7, 3, 2, 1, 1, 1, 1, 128, 240, 240, 176,,,, -3, 7, 3, 2, 1, 1, 1, 1, 256, 240, 240, 176,,,, -3, 7, 3, 2, 1, 1, 1, 1, 384, 240, 240, 176,,,, -3, 7, 3, 2, 2, 2, 1, 1, 128, 240, 240, 176,,,, -3, 7, 3, 2, 2, 2, 1, 1, 256, 240, 240, 176,,,, -3, 7, 3, 2, 2, 2, 1, 1, 384, 240, 240, 176,,,, -3, 7, 3, 2, 2, 2, 1, 2, 128, 240, 240, 176,,,, -3, 7, 3, 2, 2, 2, 1, 2, 256, 240, 240, 176,,,, -3, 7, 3, 2, 2, 2, 1, 2, 384, 240, 240, 176,,,, -3, 7, 3, 2, 2, 2, 2, 1, 128, 240, 240, 176,,,, -3, 7, 3, 2, 2, 2, 2, 1, 256, 240, 240, 176,,,, -3, 7, 3, 2, 2, 2, 2, 1, 384, 240, 240, 176,,,, -3, 7, 3, 2, 2, 2, 2, 2, 128, 240, 240, 176,,,, -3, 7, 3, 2, 2, 2, 2, 2, 256, 240, 240, 176,,,, -3, 7, 3, 2, 2, 2, 2, 2, 384, 240, 240, 176,,,, -3, 7, 3, 2, 3, 3, 1, 1, 128, 240, 232, 176,,,, -3, 7, 3, 2, 3, 3, 1, 1, 256, 240, 232, 176,,,, -3, 7, 3, 2, 3, 3, 1, 1, 384, 240, 232, 176,,,, -3, 7, 3, 2, 3, 3, 1, 2, 128, 240, 232, 176,,,, -3, 7, 3, 2, 3, 3, 1, 2, 256, 240, 232, 176,,,, -3, 7, 3, 2, 3, 3, 1, 2, 384, 240, 232, 176,,,, -3, 7, 3, 2, 3, 3, 1, 3, 128, 240, 232, 176,,,, -3, 7, 3, 2, 3, 3, 1, 3, 256, 240, 232, 176,,,, -3, 7, 3, 2, 3, 3, 1, 3, 384, 240, 232, 176,,,, -3, 7, 3, 2, 3, 3, 2, 1, 128, 240, 232, 176,,,, -3, 7, 3, 2, 3, 3, 2, 1, 256, 240, 232, 176,,,, -3, 7, 3, 2, 3, 3, 2, 1, 384, 240, 232, 176,,,, -3, 7, 3, 2, 3, 3, 2, 2, 128, 240, 232, 176,,,, -3, 7, 3, 2, 3, 3, 2, 2, 256, 240, 232, 176,,,, -3, 7, 3, 2, 3, 3, 2, 2, 384, 240, 232, 176,,,, -3, 7, 3, 2, 3, 3, 2, 3, 128, 240, 232, 176,,,, -3, 7, 3, 2, 3, 3, 2, 3, 256, 240, 232, 176,,,, -3, 7, 3, 2, 3, 3, 2, 3, 384, 240, 232, 176,,,, -3, 7, 3, 2, 3, 3, 3, 1, 128, 240, 232, 176,,,, -3, 7, 3, 2, 3, 3, 3, 1, 256, 240, 232, 176,,,, -3, 7, 3, 2, 3, 3, 3, 1, 384, 240, 232, 176,,,, -3, 7, 3, 2, 3, 3, 3, 2, 128, 240, 232, 176,,,, -3, 7, 3, 2, 3, 3, 3, 2, 256, 240, 232, 176,,,, -3, 7, 3, 2, 3, 3, 3, 2, 384, 240, 232, 176,,,, -3, 7, 3, 2, 3, 3, 3, 3, 128, 240, 232, 176,,,, -3, 7, 3, 2, 3, 3, 3, 3, 256, 240, 232, 176,,,, -3, 7, 3, 2, 3, 3, 3, 3, 384, 240, 232, 176,,,, -3, 7, 3, 3, 1, 1, 1, 1, 128, 240, 240, 240,,,, -3, 7, 3, 3, 1, 1, 1, 1, 256, 240, 240, 240,,,, -3, 7, 3, 3, 1, 1, 1, 1, 384, 240, 240, 240,,,, -3, 7, 3, 3, 2, 2, 1, 1, 128, 240, 240, 240,,,, -3, 7, 3, 3, 2, 2, 1, 1, 256, 240, 240, 240,,,, -3, 7, 3, 3, 2, 2, 1, 1, 384, 240, 240, 240,,,, -3, 7, 3, 3, 2, 2, 1, 2, 128, 240, 240, 240,,,, -3, 7, 3, 3, 2, 2, 1, 2, 256, 240, 240, 240,,,, -3, 7, 3, 3, 2, 2, 1, 2, 384, 240, 240, 240,,,, -3, 7, 3, 3, 2, 2, 2, 1, 128, 240, 240, 240,,,, -3, 7, 3, 3, 2, 2, 2, 1, 256, 240, 240, 240,,,, -3, 7, 3, 3, 2, 2, 2, 1, 384, 240, 240, 240,,,, -3, 7, 3, 3, 2, 2, 2, 2, 128, 240, 240, 240,,,, -3, 7, 3, 3, 2, 2, 2, 2, 256, 240, 240, 240,,,, -3, 7, 3, 3, 2, 2, 2, 2, 384, 240, 240, 240,,,, -3, 7, 3, 3, 3, 3, 1, 1, 128, 240, 240, 240,,,, -3, 7, 3, 3, 3, 3, 1, 1, 256, 240, 240, 240,,,, -3, 7, 3, 3, 3, 3, 1, 1, 384, 240, 240, 240,,,, -3, 7, 3, 3, 3, 3, 1, 2, 128, 240, 240, 240,,,, -3, 7, 3, 3, 3, 3, 1, 2, 256, 240, 240, 240,,,, -3, 7, 3, 3, 3, 3, 1, 2, 384, 240, 240, 240,,,, -3, 7, 3, 3, 3, 3, 1, 3, 128, 240, 240, 240,,,, -3, 7, 3, 3, 3, 3, 1, 3, 256, 240, 240, 240,,,, -3, 7, 3, 3, 3, 3, 1, 3, 384, 240, 240, 240,,,, -3, 7, 3, 3, 3, 3, 2, 1, 128, 240, 240, 240,,,, -3, 7, 3, 3, 3, 3, 2, 1, 256, 240, 240, 240,,,, -3, 7, 3, 3, 3, 3, 2, 1, 384, 240, 240, 240,,,, -3, 7, 3, 3, 3, 3, 2, 2, 128, 240, 240, 240,,,, -3, 7, 3, 3, 3, 3, 2, 2, 256, 240, 240, 240,,,, -3, 7, 3, 3, 3, 3, 2, 2, 384, 240, 240, 240,,,, -3, 7, 3, 3, 3, 3, 2, 3, 128, 240, 240, 240,,,, -3, 7, 3, 3, 3, 3, 2, 3, 256, 240, 240, 240,,,, -3, 7, 3, 3, 3, 3, 2, 3, 384, 240, 240, 240,,,, -3, 7, 3, 3, 3, 3, 3, 1, 128, 240, 240, 240,,,, -3, 7, 3, 3, 3, 3, 3, 1, 256, 240, 240, 240,,,, -3, 7, 3, 3, 3, 3, 3, 1, 384, 240, 240, 240,,,, -3, 7, 3, 3, 3, 3, 3, 2, 128, 240, 240, 240,,,, -3, 7, 3, 3, 3, 3, 3, 2, 256, 240, 240, 240,,,, -3, 7, 3, 3, 3, 3, 3, 2, 384, 240, 240, 240,,,, -3, 7, 3, 3, 3, 3, 3, 3, 128, 240, 240, 240,,,, -3, 7, 3, 3, 3, 3, 3, 3, 256, 240, 240, 240,,,, -3, 7, 3, 3, 3, 3, 3, 3, 384, 240, 240, 240,,,, -3, 7, 3, 4, 1, 1, 1, 1, 128, 240, 240, 240,,,, -3, 7, 3, 4, 1, 1, 1, 1, 256, 240, 240, 240,,,, -3, 7, 3, 4, 1, 1, 1, 1, 384, 240, 240, 240,,,, -3, 7, 3, 4, 2, 2, 1, 1, 128, 240, 240, 240,,,, -3, 7, 3, 4, 2, 2, 1, 1, 256, 240, 240, 240,,,, -3, 7, 3, 4, 2, 2, 1, 1, 384, 240, 240, 240,,,, -3, 7, 3, 4, 2, 2, 1, 2, 128, 240, 240, 240,,,, -3, 7, 3, 4, 2, 2, 1, 2, 256, 240, 240, 240,,,, -3, 7, 3, 4, 2, 2, 1, 2, 384, 240, 240, 240,,,, -3, 7, 3, 4, 2, 2, 2, 1, 128, 240, 240, 240,,,, -3, 7, 3, 4, 2, 2, 2, 1, 256, 240, 240, 240,,,, -3, 7, 3, 4, 2, 2, 2, 1, 384, 240, 240, 240,,,, -3, 7, 3, 4, 2, 2, 2, 2, 128, 240, 240, 240,,,, -3, 7, 3, 4, 2, 2, 2, 2, 256, 240, 240, 240,,,, -3, 7, 3, 4, 2, 2, 2, 2, 384, 240, 240, 240,,,, -3, 7, 3, 4, 3, 3, 1, 1, 128, 240, 240, 240,,,, -3, 7, 3, 4, 3, 3, 1, 1, 256, 240, 240, 240,,,, -3, 7, 3, 4, 3, 3, 1, 1, 384, 240, 240, 240,,,, -3, 7, 3, 4, 3, 3, 1, 2, 128, 240, 240, 240,,,, -3, 7, 3, 4, 3, 3, 1, 2, 256, 240, 240, 240,,,, -3, 7, 3, 4, 3, 3, 1, 2, 384, 240, 240, 240,,,, -3, 7, 3, 4, 3, 3, 1, 3, 128, 240, 240, 240,,,, -3, 7, 3, 4, 3, 3, 1, 3, 256, 240, 240, 240,,,, -3, 7, 3, 4, 3, 3, 1, 3, 384, 240, 240, 240,,,, -3, 7, 3, 4, 3, 3, 2, 1, 128, 240, 240, 240,,,, -3, 7, 3, 4, 3, 3, 2, 1, 256, 240, 240, 240,,,, -3, 7, 3, 4, 3, 3, 2, 1, 384, 240, 240, 240,,,, -3, 7, 3, 4, 3, 3, 2, 2, 128, 240, 240, 240,,,, -3, 7, 3, 4, 3, 3, 2, 2, 256, 240, 240, 240,,,, -3, 7, 3, 4, 3, 3, 2, 2, 384, 240, 240, 240,,,, -3, 7, 3, 4, 3, 3, 2, 3, 128, 240, 240, 240,,,, -3, 7, 3, 4, 3, 3, 2, 3, 256, 240, 240, 240,,,, -3, 7, 3, 4, 3, 3, 2, 3, 384, 240, 240, 240,,,, -3, 7, 3, 4, 3, 3, 3, 1, 128, 240, 240, 240,,,, -3, 7, 3, 4, 3, 3, 3, 1, 256, 240, 240, 240,,,, -3, 7, 3, 4, 3, 3, 3, 1, 384, 240, 240, 240,,,, -3, 7, 3, 4, 3, 3, 3, 2, 128, 240, 240, 240,,,, -3, 7, 3, 4, 3, 3, 3, 2, 256, 240, 240, 240,,,, -3, 7, 3, 4, 3, 3, 3, 2, 384, 240, 240, 240,,,, -3, 7, 3, 4, 3, 3, 3, 3, 128, 240, 240, 240,,,, -3, 7, 3, 4, 3, 3, 3, 3, 256, 240, 240, 240,,,, -3, 7, 3, 4, 3, 3, 3, 3, 384, 240, 240, 240,,,, -3, 7, 3, 5, 1, 1, 1, 1, 128, 240, 240, 240,,,, -3, 7, 3, 5, 1, 1, 1, 1, 256, 240, 240, 240,,,, -3, 7, 3, 5, 1, 1, 1, 1, 384, 240, 240, 240,,,, -3, 7, 3, 5, 2, 2, 1, 1, 128, 240, 240, 240,,,, -3, 7, 3, 5, 2, 2, 1, 1, 256, 240, 240, 240,,,, -3, 7, 3, 5, 2, 2, 1, 1, 384, 240, 240, 240,,,, -3, 7, 3, 5, 2, 2, 1, 2, 128, 240, 240, 240,,,, -3, 7, 3, 5, 2, 2, 1, 2, 256, 240, 240, 240,,,, -3, 7, 3, 5, 2, 2, 1, 2, 384, 240, 240, 240,,,, -3, 7, 3, 5, 2, 2, 2, 1, 128, 240, 240, 240,,,, -3, 7, 3, 5, 2, 2, 2, 1, 256, 240, 240, 240,,,, -3, 7, 3, 5, 2, 2, 2, 1, 384, 240, 240, 240,,,, -3, 7, 3, 5, 2, 2, 2, 2, 128, 240, 240, 240,,,, -3, 7, 3, 5, 2, 2, 2, 2, 256, 240, 240, 240,,,, -3, 7, 3, 5, 2, 2, 2, 2, 384, 240, 240, 240,,,, -3, 7, 3, 5, 3, 3, 1, 1, 128, 240, 240, 240,,,, -3, 7, 3, 5, 3, 3, 1, 1, 256, 240, 240, 240,,,, -3, 7, 3, 5, 3, 3, 1, 1, 384, 240, 240, 240,,,, -3, 7, 3, 5, 3, 3, 1, 2, 128, 240, 240, 240,,,, -3, 7, 3, 5, 3, 3, 1, 2, 256, 240, 240, 240,,,, -3, 7, 3, 5, 3, 3, 1, 2, 384, 240, 240, 240,,,, -3, 7, 3, 5, 3, 3, 1, 3, 128, 240, 240, 240,,,, -3, 7, 3, 5, 3, 3, 1, 3, 256, 240, 240, 240,,,, -3, 7, 3, 5, 3, 3, 1, 3, 384, 240, 240, 240,,,, -3, 7, 3, 5, 3, 3, 2, 1, 128, 240, 240, 240,,,, -3, 7, 3, 5, 3, 3, 2, 1, 256, 240, 240, 240,,,, -3, 7, 3, 5, 3, 3, 2, 1, 384, 240, 240, 240,,,, -3, 7, 3, 5, 3, 3, 2, 2, 128, 240, 240, 240,,,, -3, 7, 3, 5, 3, 3, 2, 2, 256, 240, 240, 240,,,, -3, 7, 3, 5, 3, 3, 2, 2, 384, 240, 240, 240,,,, -3, 7, 3, 5, 3, 3, 2, 3, 128, 240, 240, 240,,,, -3, 7, 3, 5, 3, 3, 2, 3, 256, 240, 240, 240,,,, -3, 7, 3, 5, 3, 3, 2, 3, 384, 240, 240, 240,,,, -3, 7, 3, 5, 3, 3, 3, 1, 128, 240, 240, 240,,,, -3, 7, 3, 5, 3, 3, 3, 1, 256, 240, 240, 240,,,, -3, 7, 3, 5, 3, 3, 3, 1, 384, 240, 240, 240,,,, -3, 7, 3, 5, 3, 3, 3, 2, 128, 240, 240, 240,,,, -3, 7, 3, 5, 3, 3, 3, 2, 256, 240, 240, 240,,,, -3, 7, 3, 5, 3, 3, 3, 2, 384, 240, 240, 240,,,, -3, 7, 3, 5, 3, 3, 3, 3, 128, 240, 240, 240,,,, -3, 7, 3, 5, 3, 3, 3, 3, 256, 240, 240, 240,,,, -3, 7, 3, 5, 3, 3, 3, 3, 384, 240, 240, 240,,,, -3, 7, 3, 6, 1, 1, 1, 1, 128, 240, 240, 240,,,, -3, 7, 3, 6, 1, 1, 1, 1, 256, 240, 240, 240,,,, -3, 7, 3, 6, 1, 1, 1, 1, 384, 240, 240, 240,,,, -3, 7, 3, 6, 2, 2, 1, 1, 128, 240, 240, 240,,,, -3, 7, 3, 6, 2, 2, 1, 1, 256, 240, 240, 240,,,, -3, 7, 3, 6, 2, 2, 1, 1, 384, 240, 240, 240,,,, -3, 7, 3, 6, 2, 2, 1, 2, 128, 240, 240, 240,,,, -3, 7, 3, 6, 2, 2, 1, 2, 256, 240, 240, 240,,,, -3, 7, 3, 6, 2, 2, 1, 2, 384, 240, 240, 240,,,, -3, 7, 3, 6, 2, 2, 2, 1, 128, 240, 240, 240,,,, -3, 7, 3, 6, 2, 2, 2, 1, 256, 240, 240, 240,,,, -3, 7, 3, 6, 2, 2, 2, 1, 384, 240, 240, 240,,,, -3, 7, 3, 6, 2, 2, 2, 2, 128, 240, 240, 240,,,, -3, 7, 3, 6, 2, 2, 2, 2, 256, 240, 240, 240,,,, -3, 7, 3, 6, 2, 2, 2, 2, 384, 240, 240, 240,,,, -3, 7, 3, 6, 3, 3, 1, 1, 128, 240, 240, 240,,,, -3, 7, 3, 6, 3, 3, 1, 1, 256, 240, 240, 240,,,, -3, 7, 3, 6, 3, 3, 1, 1, 384, 240, 240, 240,,,, -3, 7, 3, 6, 3, 3, 1, 2, 128, 240, 240, 240,,,, -3, 7, 3, 6, 3, 3, 1, 2, 256, 240, 240, 240,,,, -3, 7, 3, 6, 3, 3, 1, 2, 384, 240, 240, 240,,,, -3, 7, 3, 6, 3, 3, 1, 3, 128, 240, 240, 240,,,, -3, 7, 3, 6, 3, 3, 1, 3, 256, 240, 240, 240,,,, -3, 7, 3, 6, 3, 3, 1, 3, 384, 240, 240, 240,,,, -3, 7, 3, 6, 3, 3, 2, 1, 128, 240, 240, 240,,,, -3, 7, 3, 6, 3, 3, 2, 1, 256, 240, 240, 240,,,, -3, 7, 3, 6, 3, 3, 2, 1, 384, 240, 240, 240,,,, -3, 7, 3, 6, 3, 3, 2, 2, 128, 240, 240, 240,,,, -3, 7, 3, 6, 3, 3, 2, 2, 256, 240, 240, 240,,,, -3, 7, 3, 6, 3, 3, 2, 2, 384, 240, 240, 240,,,, -3, 7, 3, 6, 3, 3, 2, 3, 128, 240, 240, 240,,,, -3, 7, 3, 6, 3, 3, 2, 3, 256, 240, 240, 240,,,, -3, 7, 3, 6, 3, 3, 2, 3, 384, 240, 240, 240,,,, -3, 7, 3, 6, 3, 3, 3, 1, 128, 240, 240, 240,,,, -3, 7, 3, 6, 3, 3, 3, 1, 256, 240, 240, 240,,,, -3, 7, 3, 6, 3, 3, 3, 1, 384, 240, 240, 240,,,, -3, 7, 3, 6, 3, 3, 3, 2, 128, 240, 240, 240,,,, -3, 7, 3, 6, 3, 3, 3, 2, 256, 240, 240, 240,,,, -3, 7, 3, 6, 3, 3, 3, 2, 384, 240, 240, 240,,,, -3, 7, 3, 6, 3, 3, 3, 3, 128, 240, 240, 240,,,, -3, 7, 3, 6, 3, 3, 3, 3, 256, 240, 240, 240,,,, -3, 7, 3, 6, 3, 3, 3, 3, 384, 240, 240, 240,,,, -3, 7, 3, 7, 1, 1, 1, 1, 128, 240, 240, 240,,,, -3, 7, 3, 7, 1, 1, 1, 1, 256, 240, 240, 240,,,, -3, 7, 3, 7, 1, 1, 1, 1, 384, 240, 240, 240,,,, -3, 7, 3, 7, 2, 2, 1, 1, 128, 240, 240, 240,,,, -3, 7, 3, 7, 2, 2, 1, 1, 256, 240, 240, 240,,,, -3, 7, 3, 7, 2, 2, 1, 1, 384, 240, 240, 240,,,, -3, 7, 3, 7, 2, 2, 1, 2, 128, 240, 240, 240,,,, -3, 7, 3, 7, 2, 2, 1, 2, 256, 240, 240, 240,,,, -3, 7, 3, 7, 2, 2, 1, 2, 384, 240, 240, 240,,,, -3, 7, 3, 7, 2, 2, 2, 1, 128, 240, 240, 240,,,, -3, 7, 3, 7, 2, 2, 2, 1, 256, 240, 240, 240,,,, -3, 7, 3, 7, 2, 2, 2, 1, 384, 240, 240, 240,,,, -3, 7, 3, 7, 2, 2, 2, 2, 128, 240, 240, 240,,,, -3, 7, 3, 7, 2, 2, 2, 2, 256, 240, 240, 240,,,, -3, 7, 3, 7, 2, 2, 2, 2, 384, 240, 240, 240,,,, -3, 7, 3, 7, 3, 3, 1, 1, 128, 240, 240, 240,,,, -3, 7, 3, 7, 3, 3, 1, 1, 256, 240, 240, 240,,,, -3, 7, 3, 7, 3, 3, 1, 1, 384, 240, 240, 240,,,, -3, 7, 3, 7, 3, 3, 1, 2, 128, 240, 240, 240,,,, -3, 7, 3, 7, 3, 3, 1, 2, 256, 240, 240, 240,,,, -3, 7, 3, 7, 3, 3, 1, 2, 384, 240, 240, 240,,,, -3, 7, 3, 7, 3, 3, 1, 3, 128, 240, 240, 240,,,, -3, 7, 3, 7, 3, 3, 1, 3, 256, 240, 240, 240,,,, -3, 7, 3, 7, 3, 3, 1, 3, 384, 240, 240, 240,,,, -3, 7, 3, 7, 3, 3, 2, 1, 128, 240, 240, 240,,,, -3, 7, 3, 7, 3, 3, 2, 1, 256, 240, 240, 240,,,, -3, 7, 3, 7, 3, 3, 2, 1, 384, 240, 240, 240,,,, -3, 7, 3, 7, 3, 3, 2, 2, 128, 240, 240, 240,,,, -3, 7, 3, 7, 3, 3, 2, 2, 256, 240, 240, 240,,,, -3, 7, 3, 7, 3, 3, 2, 2, 384, 240, 240, 240,,,, -3, 7, 3, 7, 3, 3, 2, 3, 128, 240, 240, 240,,,, -3, 7, 3, 7, 3, 3, 2, 3, 256, 240, 240, 240,,,, -3, 7, 3, 7, 3, 3, 2, 3, 384, 240, 240, 240,,,, -3, 7, 3, 7, 3, 3, 3, 1, 128, 240, 240, 240,,,, -3, 7, 3, 7, 3, 3, 3, 1, 256, 240, 240, 240,,,, -3, 7, 3, 7, 3, 3, 3, 1, 384, 240, 240, 240,,,, -3, 7, 3, 7, 3, 3, 3, 2, 128, 240, 240, 240,,,, -3, 7, 3, 7, 3, 3, 3, 2, 256, 240, 240, 240,,,, -3, 7, 3, 7, 3, 3, 3, 2, 384, 240, 240, 240,,,, -3, 7, 3, 7, 3, 3, 3, 3, 128, 240, 240, 240,,,, -3, 7, 3, 7, 3, 3, 3, 3, 256, 240, 240, 240,,,, -3, 7, 3, 7, 3, 3, 3, 3, 384, 240, 240, 240,,,, -4, 1, 1, 1, 1, 1, 1, 1, 128, 96, 96, 96, 96, 96, 64, 32 -4, 1, 1, 1, 1, 1, 1, 1, 256, 96, 96, 96, 96, 96, 64, 32 -4, 1, 1, 1, 1, 1, 1, 1, 384, 96, 96, 96, 96, 96, 64, 32 -4, 1, 2, 1, 1, 1, 1, 1, 128, 96, 96, 96, 96, 96, 64, 32 -4, 1, 2, 1, 1, 1, 1, 1, 256, 96, 96, 96, 96, 96, 64, 32 -4, 1, 2, 1, 1, 1, 1, 1, 384, 96, 96, 96, 96, 96, 64, 32 -4, 1, 3, 1, 1, 1, 1, 1, 128, 96, 96, 96, 96, 96, 64, 32 -4, 1, 3, 1, 1, 1, 1, 1, 256, 96, 96, 96, 96, 96, 64, 32 -4, 1, 3, 1, 1, 1, 1, 1, 384, 96, 96, 96, 96, 96, 64, 32 -4, 1, 4, 1, 1, 1, 1, 1, 128, 96, 96, 96, 96, 96, 64, 32 -4, 1, 4, 1, 1, 1, 1, 1, 256, 96, 96, 96, 96, 96, 64, 32 -4, 1, 4, 1, 1, 1, 1, 1, 384, 96, 96, 96, 96, 96, 64, 32 -4, 2, 1, 1, 1, 1, 1, 1, 128, 97, 97, 97, 97,,, -4, 2, 1, 1, 1, 1, 1, 1, 256, 97, 97, 97, 97,,, -4, 2, 1, 1, 1, 1, 1, 1, 384, 97, 97, 97, 97,,, -4, 2, 1, 1, 2, 2, 1, 1, 128, 97, 97, 97, 85,,, -4, 2, 1, 1, 2, 2, 1, 1, 256, 97, 97, 97, 85,,, -4, 2, 1, 1, 2, 2, 1, 1, 384, 97, 97, 97, 85,,, -4, 2, 1, 1, 2, 2, 1, 2, 128, 97, 97, 97, 85,,, -4, 2, 1, 1, 2, 2, 1, 2, 256, 97, 97, 97, 85,,, -4, 2, 1, 1, 2, 2, 1, 2, 384, 97, 97, 97, 85,,, -4, 2, 1, 1, 2, 2, 2, 1, 128, 97, 97, 97, 85,,, -4, 2, 1, 1, 2, 2, 2, 1, 256, 97, 97, 97, 85,,, -4, 2, 1, 1, 2, 2, 2, 1, 384, 97, 97, 97, 85,,, -4, 2, 1, 1, 2, 2, 2, 2, 128, 97, 97, 97, 85,,, -4, 2, 1, 1, 2, 2, 2, 2, 256, 97, 97, 97, 85,,, -4, 2, 1, 1, 2, 2, 2, 2, 384, 97, 97, 97, 85,,, -4, 2, 1, 2, 1, 1, 1, 1, 128, 193, 193, 193, 193,,, -4, 2, 1, 2, 1, 1, 1, 1, 256, 193, 193, 193, 193,,, -4, 2, 1, 2, 1, 1, 1, 1, 384, 193, 193, 193, 193,,, -4, 2, 1, 2, 2, 2, 1, 1, 128, 193, 193, 193, 169,,, -4, 2, 1, 2, 2, 2, 1, 1, 256, 193, 193, 193, 169,,, -4, 2, 1, 2, 2, 2, 1, 1, 384, 193, 193, 193, 169,,, -4, 2, 1, 2, 2, 2, 1, 2, 128, 193, 193, 193, 169,,, -4, 2, 1, 2, 2, 2, 1, 2, 256, 193, 193, 193, 169,,, -4, 2, 1, 2, 2, 2, 1, 2, 384, 193, 193, 193, 169,,, -4, 2, 1, 2, 2, 2, 2, 1, 128, 193, 193, 193, 169,,, -4, 2, 1, 2, 2, 2, 2, 1, 256, 193, 193, 193, 169,,, -4, 2, 1, 2, 2, 2, 2, 1, 384, 193, 193, 193, 169,,, -4, 2, 1, 2, 2, 2, 2, 2, 128, 193, 193, 193, 169,,, -4, 2, 1, 2, 2, 2, 2, 2, 256, 193, 193, 193, 169,,, -4, 2, 1, 2, 2, 2, 2, 2, 384, 193, 193, 193, 169,,, -4, 2, 2, 1, 1, 1, 1, 1, 128, 97, 97, 97, 97,,, -4, 2, 2, 1, 1, 1, 1, 1, 256, 97, 97, 97, 97,,, -4, 2, 2, 1, 1, 1, 1, 1, 384, 97, 97, 97, 97,,, -4, 2, 2, 1, 2, 2, 1, 1, 128, 97, 97, 97, 85,,, -4, 2, 2, 1, 2, 2, 1, 1, 256, 97, 97, 97, 85,,, -4, 2, 2, 1, 2, 2, 1, 1, 384, 97, 97, 97, 85,,, -4, 2, 2, 1, 2, 2, 1, 2, 128, 97, 97, 97, 85,,, -4, 2, 2, 1, 2, 2, 1, 2, 256, 97, 97, 97, 85,,, -4, 2, 2, 1, 2, 2, 1, 2, 384, 97, 97, 97, 85,,, -4, 2, 2, 1, 2, 2, 2, 1, 128, 97, 97, 97, 85,,, -4, 2, 2, 1, 2, 2, 2, 1, 256, 97, 97, 97, 85,,, -4, 2, 2, 1, 2, 2, 2, 1, 384, 97, 97, 97, 85,,, -4, 2, 2, 1, 2, 2, 2, 2, 128, 97, 97, 97, 85,,, -4, 2, 2, 1, 2, 2, 2, 2, 256, 97, 97, 97, 85,,, -4, 2, 2, 1, 2, 2, 2, 2, 384, 97, 97, 97, 85,,, -4, 2, 2, 2, 1, 1, 1, 1, 128, 193, 193, 193, 193,,, -4, 2, 2, 2, 1, 1, 1, 1, 256, 193, 193, 193, 193,,, -4, 2, 2, 2, 1, 1, 1, 1, 384, 193, 193, 193, 193,,, -4, 2, 2, 2, 2, 2, 1, 1, 128, 193, 193, 193, 169,,, -4, 2, 2, 2, 2, 2, 1, 1, 256, 193, 193, 193, 169,,, -4, 2, 2, 2, 2, 2, 1, 1, 384, 193, 193, 193, 169,,, -4, 2, 2, 2, 2, 2, 1, 2, 128, 193, 193, 193, 169,,, -4, 2, 2, 2, 2, 2, 1, 2, 256, 193, 193, 193, 169,,, -4, 2, 2, 2, 2, 2, 1, 2, 384, 193, 193, 193, 169,,, -4, 2, 2, 2, 2, 2, 2, 1, 128, 193, 193, 193, 169,,, -4, 2, 2, 2, 2, 2, 2, 1, 256, 193, 193, 193, 169,,, -4, 2, 2, 2, 2, 2, 2, 1, 384, 193, 193, 193, 169,,, -4, 2, 2, 2, 2, 2, 2, 2, 128, 193, 193, 193, 169,,, -4, 2, 2, 2, 2, 2, 2, 2, 256, 193, 193, 193, 169,,, -4, 2, 2, 2, 2, 2, 2, 2, 384, 193, 193, 193, 169,,, -4, 2, 3, 1, 1, 1, 1, 1, 128, 97, 97, 97, 97,,, -4, 2, 3, 1, 1, 1, 1, 1, 256, 97, 97, 97, 97,,, -4, 2, 3, 1, 1, 1, 1, 1, 384, 97, 97, 97, 97,,, -4, 2, 3, 1, 2, 2, 1, 1, 128, 97, 97, 97, 85,,, -4, 2, 3, 1, 2, 2, 1, 1, 256, 97, 97, 97, 85,,, -4, 2, 3, 1, 2, 2, 1, 1, 384, 97, 97, 97, 85,,, -4, 2, 3, 1, 2, 2, 1, 2, 128, 97, 97, 97, 85,,, -4, 2, 3, 1, 2, 2, 1, 2, 256, 97, 97, 97, 85,,, -4, 2, 3, 1, 2, 2, 1, 2, 384, 97, 97, 97, 85,,, -4, 2, 3, 1, 2, 2, 2, 1, 128, 97, 97, 97, 85,,, -4, 2, 3, 1, 2, 2, 2, 1, 256, 97, 97, 97, 85,,, -4, 2, 3, 1, 2, 2, 2, 1, 384, 97, 97, 97, 85,,, -4, 2, 3, 1, 2, 2, 2, 2, 128, 97, 97, 97, 85,,, -4, 2, 3, 1, 2, 2, 2, 2, 256, 97, 97, 97, 85,,, -4, 2, 3, 1, 2, 2, 2, 2, 384, 97, 97, 97, 85,,, -4, 2, 3, 2, 1, 1, 1, 1, 128, 193, 193, 193, 193,,, -4, 2, 3, 2, 1, 1, 1, 1, 256, 193, 193, 193, 193,,, -4, 2, 3, 2, 1, 1, 1, 1, 384, 193, 193, 193, 193,,, -4, 2, 3, 2, 2, 2, 1, 1, 128, 193, 193, 193, 169,,, -4, 2, 3, 2, 2, 2, 1, 1, 256, 193, 193, 193, 169,,, -4, 2, 3, 2, 2, 2, 1, 1, 384, 193, 193, 193, 169,,, -4, 2, 3, 2, 2, 2, 1, 2, 128, 193, 193, 193, 169,,, -4, 2, 3, 2, 2, 2, 1, 2, 256, 193, 193, 193, 169,,, -4, 2, 3, 2, 2, 2, 1, 2, 384, 193, 193, 193, 169,,, -4, 2, 3, 2, 2, 2, 2, 1, 128, 193, 193, 193, 169,,, -4, 2, 3, 2, 2, 2, 2, 1, 256, 193, 193, 193, 169,,, -4, 2, 3, 2, 2, 2, 2, 1, 384, 193, 193, 193, 169,,, -4, 2, 3, 2, 2, 2, 2, 2, 128, 193, 193, 193, 169,,, -4, 2, 3, 2, 2, 2, 2, 2, 256, 193, 193, 193, 169,,, -4, 2, 3, 2, 2, 2, 2, 2, 384, 193, 193, 193, 169,,, -4, 2, 4, 1, 1, 1, 1, 1, 128, 97, 97, 97, 97,,, -4, 2, 4, 1, 1, 1, 1, 1, 256, 97, 97, 97, 97,,, -4, 2, 4, 1, 1, 1, 1, 1, 384, 97, 97, 97, 97,,, -4, 2, 4, 1, 2, 2, 1, 1, 128, 97, 97, 97, 85,,, -4, 2, 4, 1, 2, 2, 1, 1, 256, 97, 97, 97, 85,,, -4, 2, 4, 1, 2, 2, 1, 1, 384, 97, 97, 97, 85,,, -4, 2, 4, 1, 2, 2, 1, 2, 128, 97, 97, 97, 85,,, -4, 2, 4, 1, 2, 2, 1, 2, 256, 97, 97, 97, 85,,, -4, 2, 4, 1, 2, 2, 1, 2, 384, 97, 97, 97, 85,,, -4, 2, 4, 1, 2, 2, 2, 1, 128, 97, 97, 97, 85,,, -4, 2, 4, 1, 2, 2, 2, 1, 256, 97, 97, 97, 85,,, -4, 2, 4, 1, 2, 2, 2, 1, 384, 97, 97, 97, 85,,, -4, 2, 4, 1, 2, 2, 2, 2, 128, 97, 97, 97, 85,,, -4, 2, 4, 1, 2, 2, 2, 2, 256, 97, 97, 97, 85,,, -4, 2, 4, 1, 2, 2, 2, 2, 384, 97, 97, 97, 85,,, -4, 2, 4, 2, 1, 1, 1, 1, 128, 193, 193, 193, 193,,, -4, 2, 4, 2, 1, 1, 1, 1, 256, 193, 193, 193, 193,,, -4, 2, 4, 2, 1, 1, 1, 1, 384, 193, 193, 193, 193,,, -4, 2, 4, 2, 2, 2, 1, 1, 128, 193, 193, 193, 169,,, -4, 2, 4, 2, 2, 2, 1, 1, 256, 193, 193, 193, 169,,, -4, 2, 4, 2, 2, 2, 1, 1, 384, 193, 193, 193, 169,,, -4, 2, 4, 2, 2, 2, 1, 2, 128, 193, 193, 193, 169,,, -4, 2, 4, 2, 2, 2, 1, 2, 256, 193, 193, 193, 169,,, -4, 2, 4, 2, 2, 2, 1, 2, 384, 193, 193, 193, 169,,, -4, 2, 4, 2, 2, 2, 2, 1, 128, 193, 193, 193, 169,,, -4, 2, 4, 2, 2, 2, 2, 1, 256, 193, 193, 193, 169,,, -4, 2, 4, 2, 2, 2, 2, 1, 384, 193, 193, 193, 169,,, -4, 2, 4, 2, 2, 2, 2, 2, 128, 193, 193, 193, 169,,, -4, 2, 4, 2, 2, 2, 2, 2, 256, 193, 193, 193, 169,,, -4, 2, 4, 2, 2, 2, 2, 2, 384, 193, 193, 193, 169,,, -4, 3, 1, 1, 1, 1, 1, 1, 128, 98, 98, 98, 66,,, -4, 3, 1, 1, 1, 1, 1, 1, 256, 98, 98, 98, 66,,, -4, 3, 1, 1, 1, 1, 1, 1, 384, 98, 98, 98, 66,,, -4, 3, 1, 1, 2, 2, 1, 1, 128, 98, 98, 94, 66,,, -4, 3, 1, 1, 2, 2, 1, 1, 256, 98, 98, 94, 66,,, -4, 3, 1, 1, 2, 2, 1, 1, 384, 98, 98, 94, 66,,, -4, 3, 1, 1, 2, 2, 1, 2, 128, 98, 98, 94, 66,,, -4, 3, 1, 1, 2, 2, 1, 2, 256, 98, 98, 94, 66,,, -4, 3, 1, 1, 2, 2, 1, 2, 384, 98, 98, 94, 66,,, -4, 3, 1, 1, 2, 2, 2, 1, 128, 98, 98, 94, 66,,, -4, 3, 1, 1, 2, 2, 2, 1, 256, 98, 98, 94, 66,,, -4, 3, 1, 1, 2, 2, 2, 1, 384, 98, 98, 94, 66,,, -4, 3, 1, 1, 2, 2, 2, 2, 128, 98, 98, 94, 66,,, -4, 3, 1, 1, 2, 2, 2, 2, 256, 98, 98, 94, 66,,, -4, 3, 1, 1, 2, 2, 2, 2, 384, 98, 98, 94, 66,,, -4, 3, 1, 1, 3, 3, 1, 1, 128, 98, 98, 89, 66,,, -4, 3, 1, 1, 3, 3, 1, 1, 256, 98, 98, 89, 66,,, -4, 3, 1, 1, 3, 3, 1, 1, 384, 98, 98, 89, 66,,, -4, 3, 1, 1, 3, 3, 1, 2, 128, 98, 98, 89, 66,,, -4, 3, 1, 1, 3, 3, 1, 2, 256, 98, 98, 89, 66,,, -4, 3, 1, 1, 3, 3, 1, 2, 384, 98, 98, 89, 66,,, -4, 3, 1, 1, 3, 3, 1, 3, 128, 98, 98, 89, 66,,, -4, 3, 1, 1, 3, 3, 1, 3, 256, 98, 98, 89, 66,,, -4, 3, 1, 1, 3, 3, 1, 3, 384, 98, 98, 89, 66,,, -4, 3, 1, 1, 3, 3, 2, 1, 128, 98, 98, 89, 66,,, -4, 3, 1, 1, 3, 3, 2, 1, 256, 98, 98, 89, 66,,, -4, 3, 1, 1, 3, 3, 2, 1, 384, 98, 98, 89, 66,,, -4, 3, 1, 1, 3, 3, 2, 2, 128, 98, 98, 89, 66,,, -4, 3, 1, 1, 3, 3, 2, 2, 256, 98, 98, 89, 66,,, -4, 3, 1, 1, 3, 3, 2, 2, 384, 98, 98, 89, 66,,, -4, 3, 1, 1, 3, 3, 2, 3, 128, 98, 98, 89, 66,,, -4, 3, 1, 1, 3, 3, 2, 3, 256, 98, 98, 89, 66,,, -4, 3, 1, 1, 3, 3, 2, 3, 384, 98, 98, 89, 66,,, -4, 3, 1, 1, 3, 3, 3, 1, 128, 98, 98, 89, 66,,, -4, 3, 1, 1, 3, 3, 3, 1, 256, 98, 98, 89, 66,,, -4, 3, 1, 1, 3, 3, 3, 1, 384, 98, 98, 89, 66,,, -4, 3, 1, 1, 3, 3, 3, 2, 128, 98, 98, 89, 66,,, -4, 3, 1, 1, 3, 3, 3, 2, 256, 98, 98, 89, 66,,, -4, 3, 1, 1, 3, 3, 3, 2, 384, 98, 98, 89, 66,,, -4, 3, 1, 1, 3, 3, 3, 3, 128, 98, 98, 89, 66,,, -4, 3, 1, 1, 3, 3, 3, 3, 256, 98, 98, 89, 66,,, -4, 3, 1, 1, 3, 3, 3, 3, 384, 98, 98, 89, 66,,, -4, 3, 1, 2, 1, 1, 1, 1, 128, 194, 194, 194, 130,,, -4, 3, 1, 2, 1, 1, 1, 1, 256, 194, 194, 194, 130,,, -4, 3, 1, 2, 1, 1, 1, 1, 384, 194, 194, 194, 130,,, -4, 3, 1, 2, 2, 2, 1, 1, 128, 194, 194, 186, 130,,, -4, 3, 1, 2, 2, 2, 1, 1, 256, 194, 194, 186, 130,,, -4, 3, 1, 2, 2, 2, 1, 1, 384, 194, 194, 186, 130,,, -4, 3, 1, 2, 2, 2, 1, 2, 128, 194, 194, 186, 130,,, -4, 3, 1, 2, 2, 2, 1, 2, 256, 194, 194, 186, 130,,, -4, 3, 1, 2, 2, 2, 1, 2, 384, 194, 194, 186, 130,,, -4, 3, 1, 2, 2, 2, 2, 1, 128, 194, 194, 186, 130,,, -4, 3, 1, 2, 2, 2, 2, 1, 256, 194, 194, 186, 130,,, -4, 3, 1, 2, 2, 2, 2, 1, 384, 194, 194, 186, 130,,, -4, 3, 1, 2, 2, 2, 2, 2, 128, 194, 194, 186, 130,,, -4, 3, 1, 2, 2, 2, 2, 2, 256, 194, 194, 186, 130,,, -4, 3, 1, 2, 2, 2, 2, 2, 384, 194, 194, 186, 130,,, -4, 3, 1, 2, 3, 3, 1, 1, 128, 194, 194, 176, 130,,, -4, 3, 1, 2, 3, 3, 1, 1, 256, 194, 194, 176, 130,,, -4, 3, 1, 2, 3, 3, 1, 1, 384, 194, 194, 176, 130,,, -4, 3, 1, 2, 3, 3, 1, 2, 128, 194, 194, 176, 130,,, -4, 3, 1, 2, 3, 3, 1, 2, 256, 194, 194, 176, 130,,, -4, 3, 1, 2, 3, 3, 1, 2, 384, 194, 194, 176, 130,,, -4, 3, 1, 2, 3, 3, 1, 3, 128, 194, 194, 176, 130,,, -4, 3, 1, 2, 3, 3, 1, 3, 256, 194, 194, 176, 130,,, -4, 3, 1, 2, 3, 3, 1, 3, 384, 194, 194, 176, 130,,, -4, 3, 1, 2, 3, 3, 2, 1, 128, 194, 194, 176, 130,,, -4, 3, 1, 2, 3, 3, 2, 1, 256, 194, 194, 176, 130,,, -4, 3, 1, 2, 3, 3, 2, 1, 384, 194, 194, 176, 130,,, -4, 3, 1, 2, 3, 3, 2, 2, 128, 194, 194, 176, 130,,, -4, 3, 1, 2, 3, 3, 2, 2, 256, 194, 194, 176, 130,,, -4, 3, 1, 2, 3, 3, 2, 2, 384, 194, 194, 176, 130,,, -4, 3, 1, 2, 3, 3, 2, 3, 128, 194, 194, 176, 130,,, -4, 3, 1, 2, 3, 3, 2, 3, 256, 194, 194, 176, 130,,, -4, 3, 1, 2, 3, 3, 2, 3, 384, 194, 194, 176, 130,,, -4, 3, 1, 2, 3, 3, 3, 1, 128, 194, 194, 176, 130,,, -4, 3, 1, 2, 3, 3, 3, 1, 256, 194, 194, 176, 130,,, -4, 3, 1, 2, 3, 3, 3, 1, 384, 194, 194, 176, 130,,, -4, 3, 1, 2, 3, 3, 3, 2, 128, 194, 194, 176, 130,,, -4, 3, 1, 2, 3, 3, 3, 2, 256, 194, 194, 176, 130,,, -4, 3, 1, 2, 3, 3, 3, 2, 384, 194, 194, 176, 130,,, -4, 3, 1, 2, 3, 3, 3, 3, 128, 194, 194, 176, 130,,, -4, 3, 1, 2, 3, 3, 3, 3, 256, 194, 194, 176, 130,,, -4, 3, 1, 2, 3, 3, 3, 3, 384, 194, 194, 176, 130,,, -4, 3, 1, 3, 1, 1, 1, 1, 128, 240, 240, 240, 194,,, -4, 3, 1, 3, 1, 1, 1, 1, 256, 240, 240, 240, 194,,, -4, 3, 1, 3, 1, 1, 1, 1, 384, 240, 240, 240, 194,,, -4, 3, 1, 3, 2, 2, 1, 1, 128, 240, 240, 240, 194,,, -4, 3, 1, 3, 2, 2, 1, 1, 256, 240, 240, 240, 194,,, -4, 3, 1, 3, 2, 2, 1, 1, 384, 240, 240, 240, 194,,, -4, 3, 1, 3, 2, 2, 1, 2, 128, 240, 240, 240, 194,,, -4, 3, 1, 3, 2, 2, 1, 2, 256, 240, 240, 240, 194,,, -4, 3, 1, 3, 2, 2, 1, 2, 384, 240, 240, 240, 194,,, -4, 3, 1, 3, 2, 2, 2, 1, 128, 240, 240, 240, 194,,, -4, 3, 1, 3, 2, 2, 2, 1, 256, 240, 240, 240, 194,,, -4, 3, 1, 3, 2, 2, 2, 1, 384, 240, 240, 240, 194,,, -4, 3, 1, 3, 2, 2, 2, 2, 128, 240, 240, 240, 194,,, -4, 3, 1, 3, 2, 2, 2, 2, 256, 240, 240, 240, 194,,, -4, 3, 1, 3, 2, 2, 2, 2, 384, 240, 240, 240, 194,,, -4, 3, 1, 3, 3, 3, 1, 1, 128, 240, 240, 240, 194,,, -4, 3, 1, 3, 3, 3, 1, 1, 256, 240, 240, 240, 194,,, -4, 3, 1, 3, 3, 3, 1, 1, 384, 240, 240, 240, 194,,, -4, 3, 1, 3, 3, 3, 1, 2, 128, 240, 240, 240, 194,,, -4, 3, 1, 3, 3, 3, 1, 2, 256, 240, 240, 240, 194,,, -4, 3, 1, 3, 3, 3, 1, 2, 384, 240, 240, 240, 194,,, -4, 3, 1, 3, 3, 3, 1, 3, 128, 240, 240, 240, 194,,, -4, 3, 1, 3, 3, 3, 1, 3, 256, 240, 240, 240, 194,,, -4, 3, 1, 3, 3, 3, 1, 3, 384, 240, 240, 240, 194,,, -4, 3, 1, 3, 3, 3, 2, 1, 128, 240, 240, 240, 194,,, -4, 3, 1, 3, 3, 3, 2, 1, 256, 240, 240, 240, 194,,, -4, 3, 1, 3, 3, 3, 2, 1, 384, 240, 240, 240, 194,,, -4, 3, 1, 3, 3, 3, 2, 2, 128, 240, 240, 240, 194,,, -4, 3, 1, 3, 3, 3, 2, 2, 256, 240, 240, 240, 194,,, -4, 3, 1, 3, 3, 3, 2, 2, 384, 240, 240, 240, 194,,, -4, 3, 1, 3, 3, 3, 2, 3, 128, 240, 240, 240, 194,,, -4, 3, 1, 3, 3, 3, 2, 3, 256, 240, 240, 240, 194,,, -4, 3, 1, 3, 3, 3, 2, 3, 384, 240, 240, 240, 194,,, -4, 3, 1, 3, 3, 3, 3, 1, 128, 240, 240, 240, 194,,, -4, 3, 1, 3, 3, 3, 3, 1, 256, 240, 240, 240, 194,,, -4, 3, 1, 3, 3, 3, 3, 1, 384, 240, 240, 240, 194,,, -4, 3, 1, 3, 3, 3, 3, 2, 128, 240, 240, 240, 194,,, -4, 3, 1, 3, 3, 3, 3, 2, 256, 240, 240, 240, 194,,, -4, 3, 1, 3, 3, 3, 3, 2, 384, 240, 240, 240, 194,,, -4, 3, 1, 3, 3, 3, 3, 3, 128, 240, 240, 240, 194,,, -4, 3, 1, 3, 3, 3, 3, 3, 256, 240, 240, 240, 194,,, -4, 3, 1, 3, 3, 3, 3, 3, 384, 240, 240, 240, 194,,, -4, 3, 2, 1, 1, 1, 1, 1, 128, 98, 98, 98, 66,,, -4, 3, 2, 1, 1, 1, 1, 1, 256, 98, 98, 98, 66,,, -4, 3, 2, 1, 1, 1, 1, 1, 384, 98, 98, 98, 66,,, -4, 3, 2, 1, 2, 2, 1, 1, 128, 98, 98, 94, 66,,, -4, 3, 2, 1, 2, 2, 1, 1, 256, 98, 98, 94, 66,,, -4, 3, 2, 1, 2, 2, 1, 1, 384, 98, 98, 94, 66,,, -4, 3, 2, 1, 2, 2, 1, 2, 128, 98, 98, 94, 66,,, -4, 3, 2, 1, 2, 2, 1, 2, 256, 98, 98, 94, 66,,, -4, 3, 2, 1, 2, 2, 1, 2, 384, 98, 98, 94, 66,,, -4, 3, 2, 1, 2, 2, 2, 1, 128, 98, 98, 94, 66,,, -4, 3, 2, 1, 2, 2, 2, 1, 256, 98, 98, 94, 66,,, -4, 3, 2, 1, 2, 2, 2, 1, 384, 98, 98, 94, 66,,, -4, 3, 2, 1, 2, 2, 2, 2, 128, 98, 98, 94, 66,,, -4, 3, 2, 1, 2, 2, 2, 2, 256, 98, 98, 94, 66,,, -4, 3, 2, 1, 2, 2, 2, 2, 384, 98, 98, 94, 66,,, -4, 3, 2, 1, 3, 3, 1, 1, 128, 98, 98, 89, 66,,, -4, 3, 2, 1, 3, 3, 1, 1, 256, 98, 98, 89, 66,,, -4, 3, 2, 1, 3, 3, 1, 1, 384, 98, 98, 89, 66,,, -4, 3, 2, 1, 3, 3, 1, 2, 128, 98, 98, 89, 66,,, -4, 3, 2, 1, 3, 3, 1, 2, 256, 98, 98, 89, 66,,, -4, 3, 2, 1, 3, 3, 1, 2, 384, 98, 98, 89, 66,,, -4, 3, 2, 1, 3, 3, 1, 3, 128, 98, 98, 89, 66,,, -4, 3, 2, 1, 3, 3, 1, 3, 256, 98, 98, 89, 66,,, -4, 3, 2, 1, 3, 3, 1, 3, 384, 98, 98, 89, 66,,, -4, 3, 2, 1, 3, 3, 2, 1, 128, 98, 98, 89, 66,,, -4, 3, 2, 1, 3, 3, 2, 1, 256, 98, 98, 89, 66,,, -4, 3, 2, 1, 3, 3, 2, 1, 384, 98, 98, 89, 66,,, -4, 3, 2, 1, 3, 3, 2, 2, 128, 98, 98, 89, 66,,, -4, 3, 2, 1, 3, 3, 2, 2, 256, 98, 98, 89, 66,,, -4, 3, 2, 1, 3, 3, 2, 2, 384, 98, 98, 89, 66,,, -4, 3, 2, 1, 3, 3, 2, 3, 128, 98, 98, 89, 66,,, -4, 3, 2, 1, 3, 3, 2, 3, 256, 98, 98, 89, 66,,, -4, 3, 2, 1, 3, 3, 2, 3, 384, 98, 98, 89, 66,,, -4, 3, 2, 1, 3, 3, 3, 1, 128, 98, 98, 89, 66,,, -4, 3, 2, 1, 3, 3, 3, 1, 256, 98, 98, 89, 66,,, -4, 3, 2, 1, 3, 3, 3, 1, 384, 98, 98, 89, 66,,, -4, 3, 2, 1, 3, 3, 3, 2, 128, 98, 98, 89, 66,,, -4, 3, 2, 1, 3, 3, 3, 2, 256, 98, 98, 89, 66,,, -4, 3, 2, 1, 3, 3, 3, 2, 384, 98, 98, 89, 66,,, -4, 3, 2, 1, 3, 3, 3, 3, 128, 98, 98, 89, 66,,, -4, 3, 2, 1, 3, 3, 3, 3, 256, 98, 98, 89, 66,,, -4, 3, 2, 1, 3, 3, 3, 3, 384, 98, 98, 89, 66,,, -4, 3, 2, 2, 1, 1, 1, 1, 128, 194, 194, 194, 130,,, -4, 3, 2, 2, 1, 1, 1, 1, 256, 194, 194, 194, 130,,, -4, 3, 2, 2, 1, 1, 1, 1, 384, 194, 194, 194, 130,,, -4, 3, 2, 2, 2, 2, 1, 1, 128, 194, 194, 186, 130,,, -4, 3, 2, 2, 2, 2, 1, 1, 256, 194, 194, 186, 130,,, -4, 3, 2, 2, 2, 2, 1, 1, 384, 194, 194, 186, 130,,, -4, 3, 2, 2, 2, 2, 1, 2, 128, 194, 194, 186, 130,,, -4, 3, 2, 2, 2, 2, 1, 2, 256, 194, 194, 186, 130,,, -4, 3, 2, 2, 2, 2, 1, 2, 384, 194, 194, 186, 130,,, -4, 3, 2, 2, 2, 2, 2, 1, 128, 194, 194, 186, 130,,, -4, 3, 2, 2, 2, 2, 2, 1, 256, 194, 194, 186, 130,,, -4, 3, 2, 2, 2, 2, 2, 1, 384, 194, 194, 186, 130,,, -4, 3, 2, 2, 2, 2, 2, 2, 128, 194, 194, 186, 130,,, -4, 3, 2, 2, 2, 2, 2, 2, 256, 194, 194, 186, 130,,, -4, 3, 2, 2, 2, 2, 2, 2, 384, 194, 194, 186, 130,,, -4, 3, 2, 2, 3, 3, 1, 1, 128, 194, 194, 176, 130,,, -4, 3, 2, 2, 3, 3, 1, 1, 256, 194, 194, 176, 130,,, -4, 3, 2, 2, 3, 3, 1, 1, 384, 194, 194, 176, 130,,, -4, 3, 2, 2, 3, 3, 1, 2, 128, 194, 194, 176, 130,,, -4, 3, 2, 2, 3, 3, 1, 2, 256, 194, 194, 176, 130,,, -4, 3, 2, 2, 3, 3, 1, 2, 384, 194, 194, 176, 130,,, -4, 3, 2, 2, 3, 3, 1, 3, 128, 194, 194, 176, 130,,, -4, 3, 2, 2, 3, 3, 1, 3, 256, 194, 194, 176, 130,,, -4, 3, 2, 2, 3, 3, 1, 3, 384, 194, 194, 176, 130,,, -4, 3, 2, 2, 3, 3, 2, 1, 128, 194, 194, 176, 130,,, -4, 3, 2, 2, 3, 3, 2, 1, 256, 194, 194, 176, 130,,, -4, 3, 2, 2, 3, 3, 2, 1, 384, 194, 194, 176, 130,,, -4, 3, 2, 2, 3, 3, 2, 2, 128, 194, 194, 176, 130,,, -4, 3, 2, 2, 3, 3, 2, 2, 256, 194, 194, 176, 130,,, -4, 3, 2, 2, 3, 3, 2, 2, 384, 194, 194, 176, 130,,, -4, 3, 2, 2, 3, 3, 2, 3, 128, 194, 194, 176, 130,,, -4, 3, 2, 2, 3, 3, 2, 3, 256, 194, 194, 176, 130,,, -4, 3, 2, 2, 3, 3, 2, 3, 384, 194, 194, 176, 130,,, -4, 3, 2, 2, 3, 3, 3, 1, 128, 194, 194, 176, 130,,, -4, 3, 2, 2, 3, 3, 3, 1, 256, 194, 194, 176, 130,,, -4, 3, 2, 2, 3, 3, 3, 1, 384, 194, 194, 176, 130,,, -4, 3, 2, 2, 3, 3, 3, 2, 128, 194, 194, 176, 130,,, -4, 3, 2, 2, 3, 3, 3, 2, 256, 194, 194, 176, 130,,, -4, 3, 2, 2, 3, 3, 3, 2, 384, 194, 194, 176, 130,,, -4, 3, 2, 2, 3, 3, 3, 3, 128, 194, 194, 176, 130,,, -4, 3, 2, 2, 3, 3, 3, 3, 256, 194, 194, 176, 130,,, -4, 3, 2, 2, 3, 3, 3, 3, 384, 194, 194, 176, 130,,, -4, 3, 2, 3, 1, 1, 1, 1, 128, 240, 240, 240, 194,,, -4, 3, 2, 3, 1, 1, 1, 1, 256, 240, 240, 240, 194,,, -4, 3, 2, 3, 1, 1, 1, 1, 384, 240, 240, 240, 194,,, -4, 3, 2, 3, 2, 2, 1, 1, 128, 240, 240, 240, 194,,, -4, 3, 2, 3, 2, 2, 1, 1, 256, 240, 240, 240, 194,,, -4, 3, 2, 3, 2, 2, 1, 1, 384, 240, 240, 240, 194,,, -4, 3, 2, 3, 2, 2, 1, 2, 128, 240, 240, 240, 194,,, -4, 3, 2, 3, 2, 2, 1, 2, 256, 240, 240, 240, 194,,, -4, 3, 2, 3, 2, 2, 1, 2, 384, 240, 240, 240, 194,,, -4, 3, 2, 3, 2, 2, 2, 1, 128, 240, 240, 240, 194,,, -4, 3, 2, 3, 2, 2, 2, 1, 256, 240, 240, 240, 194,,, -4, 3, 2, 3, 2, 2, 2, 1, 384, 240, 240, 240, 194,,, -4, 3, 2, 3, 2, 2, 2, 2, 128, 240, 240, 240, 194,,, -4, 3, 2, 3, 2, 2, 2, 2, 256, 240, 240, 240, 194,,, -4, 3, 2, 3, 2, 2, 2, 2, 384, 240, 240, 240, 194,,, -4, 3, 2, 3, 3, 3, 1, 1, 128, 240, 240, 240, 194,,, -4, 3, 2, 3, 3, 3, 1, 1, 256, 240, 240, 240, 194,,, -4, 3, 2, 3, 3, 3, 1, 1, 384, 240, 240, 240, 194,,, -4, 3, 2, 3, 3, 3, 1, 2, 128, 240, 240, 240, 194,,, -4, 3, 2, 3, 3, 3, 1, 2, 256, 240, 240, 240, 194,,, -4, 3, 2, 3, 3, 3, 1, 2, 384, 240, 240, 240, 194,,, -4, 3, 2, 3, 3, 3, 1, 3, 128, 240, 240, 240, 194,,, -4, 3, 2, 3, 3, 3, 1, 3, 256, 240, 240, 240, 194,,, -4, 3, 2, 3, 3, 3, 1, 3, 384, 240, 240, 240, 194,,, -4, 3, 2, 3, 3, 3, 2, 1, 128, 240, 240, 240, 194,,, -4, 3, 2, 3, 3, 3, 2, 1, 256, 240, 240, 240, 194,,, -4, 3, 2, 3, 3, 3, 2, 1, 384, 240, 240, 240, 194,,, -4, 3, 2, 3, 3, 3, 2, 2, 128, 240, 240, 240, 194,,, -4, 3, 2, 3, 3, 3, 2, 2, 256, 240, 240, 240, 194,,, -4, 3, 2, 3, 3, 3, 2, 2, 384, 240, 240, 240, 194,,, -4, 3, 2, 3, 3, 3, 2, 3, 128, 240, 240, 240, 194,,, -4, 3, 2, 3, 3, 3, 2, 3, 256, 240, 240, 240, 194,,, -4, 3, 2, 3, 3, 3, 2, 3, 384, 240, 240, 240, 194,,, -4, 3, 2, 3, 3, 3, 3, 1, 128, 240, 240, 240, 194,,, -4, 3, 2, 3, 3, 3, 3, 1, 256, 240, 240, 240, 194,,, -4, 3, 2, 3, 3, 3, 3, 1, 384, 240, 240, 240, 194,,, -4, 3, 2, 3, 3, 3, 3, 2, 128, 240, 240, 240, 194,,, -4, 3, 2, 3, 3, 3, 3, 2, 256, 240, 240, 240, 194,,, -4, 3, 2, 3, 3, 3, 3, 2, 384, 240, 240, 240, 194,,, -4, 3, 2, 3, 3, 3, 3, 3, 128, 240, 240, 240, 194,,, -4, 3, 2, 3, 3, 3, 3, 3, 256, 240, 240, 240, 194,,, -4, 3, 2, 3, 3, 3, 3, 3, 384, 240, 240, 240, 194,,, -4, 3, 3, 1, 1, 1, 1, 1, 128, 98, 98, 98, 66,,, -4, 3, 3, 1, 1, 1, 1, 1, 256, 98, 98, 98, 66,,, -4, 3, 3, 1, 1, 1, 1, 1, 384, 98, 98, 98, 66,,, -4, 3, 3, 1, 2, 2, 1, 1, 128, 98, 98, 94, 66,,, -4, 3, 3, 1, 2, 2, 1, 1, 256, 98, 98, 94, 66,,, -4, 3, 3, 1, 2, 2, 1, 1, 384, 98, 98, 94, 66,,, -4, 3, 3, 1, 2, 2, 1, 2, 128, 98, 98, 94, 66,,, -4, 3, 3, 1, 2, 2, 1, 2, 256, 98, 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-4, 3, 3, 2, 3, 3, 2, 1, 384, 194, 194, 176, 130,,, -4, 3, 3, 2, 3, 3, 2, 2, 128, 194, 194, 176, 130,,, -4, 3, 3, 2, 3, 3, 2, 2, 256, 194, 194, 176, 130,,, -4, 3, 3, 2, 3, 3, 2, 2, 384, 194, 194, 176, 130,,, -4, 3, 3, 2, 3, 3, 2, 3, 128, 194, 194, 176, 130,,, -4, 3, 3, 2, 3, 3, 2, 3, 256, 194, 194, 176, 130,,, -4, 3, 3, 2, 3, 3, 2, 3, 384, 194, 194, 176, 130,,, -4, 3, 3, 2, 3, 3, 3, 1, 128, 194, 194, 176, 130,,, -4, 3, 3, 2, 3, 3, 3, 1, 256, 194, 194, 176, 130,,, -4, 3, 3, 2, 3, 3, 3, 1, 384, 194, 194, 176, 130,,, -4, 3, 3, 2, 3, 3, 3, 2, 128, 194, 194, 176, 130,,, -4, 3, 3, 2, 3, 3, 3, 2, 256, 194, 194, 176, 130,,, -4, 3, 3, 2, 3, 3, 3, 2, 384, 194, 194, 176, 130,,, -4, 3, 3, 2, 3, 3, 3, 3, 128, 194, 194, 176, 130,,, -4, 3, 3, 2, 3, 3, 3, 3, 256, 194, 194, 176, 130,,, -4, 3, 3, 2, 3, 3, 3, 3, 384, 194, 194, 176, 130,,, -4, 3, 3, 3, 1, 1, 1, 1, 128, 240, 240, 240, 194,,, -4, 3, 3, 3, 1, 1, 1, 1, 256, 240, 240, 240, 194,,, -4, 3, 3, 3, 1, 1, 1, 1, 384, 240, 240, 240, 194,,, -4, 3, 3, 3, 2, 2, 1, 1, 128, 240, 240, 240, 194,,, -4, 3, 3, 3, 2, 2, 1, 1, 256, 240, 240, 240, 194,,, -4, 3, 3, 3, 2, 2, 1, 1, 384, 240, 240, 240, 194,,, -4, 3, 3, 3, 2, 2, 1, 2, 128, 240, 240, 240, 194,,, -4, 3, 3, 3, 2, 2, 1, 2, 256, 240, 240, 240, 194,,, -4, 3, 3, 3, 2, 2, 1, 2, 384, 240, 240, 240, 194,,, -4, 3, 3, 3, 2, 2, 2, 1, 128, 240, 240, 240, 194,,, -4, 3, 3, 3, 2, 2, 2, 1, 256, 240, 240, 240, 194,,, -4, 3, 3, 3, 2, 2, 2, 1, 384, 240, 240, 240, 194,,, -4, 3, 3, 3, 2, 2, 2, 2, 128, 240, 240, 240, 194,,, -4, 3, 3, 3, 2, 2, 2, 2, 256, 240, 240, 240, 194,,, -4, 3, 3, 3, 2, 2, 2, 2, 384, 240, 240, 240, 194,,, -4, 3, 3, 3, 3, 3, 1, 1, 128, 240, 240, 240, 194,,, -4, 3, 3, 3, 3, 3, 1, 1, 256, 240, 240, 240, 194,,, -4, 3, 3, 3, 3, 3, 1, 1, 384, 240, 240, 240, 194,,, -4, 3, 3, 3, 3, 3, 1, 2, 128, 240, 240, 240, 194,,, -4, 3, 3, 3, 3, 3, 1, 2, 256, 240, 240, 240, 194,,, -4, 3, 3, 3, 3, 3, 1, 2, 384, 240, 240, 240, 194,,, -4, 3, 3, 3, 3, 3, 1, 3, 128, 240, 240, 240, 194,,, -4, 3, 3, 3, 3, 3, 1, 3, 256, 240, 240, 240, 194,,, -4, 3, 3, 3, 3, 3, 1, 3, 384, 240, 240, 240, 194,,, -4, 3, 3, 3, 3, 3, 2, 1, 128, 240, 240, 240, 194,,, -4, 3, 3, 3, 3, 3, 2, 1, 256, 240, 240, 240, 194,,, -4, 3, 3, 3, 3, 3, 2, 1, 384, 240, 240, 240, 194,,, -4, 3, 3, 3, 3, 3, 2, 2, 128, 240, 240, 240, 194,,, -4, 3, 3, 3, 3, 3, 2, 2, 256, 240, 240, 240, 194,,, -4, 3, 3, 3, 3, 3, 2, 2, 384, 240, 240, 240, 194,,, -4, 3, 3, 3, 3, 3, 2, 3, 128, 240, 240, 240, 194,,, -4, 3, 3, 3, 3, 3, 2, 3, 256, 240, 240, 240, 194,,, -4, 3, 3, 3, 3, 3, 2, 3, 384, 240, 240, 240, 194,,, -4, 3, 3, 3, 3, 3, 3, 1, 128, 240, 240, 240, 194,,, -4, 3, 3, 3, 3, 3, 3, 1, 256, 240, 240, 240, 194,,, -4, 3, 3, 3, 3, 3, 3, 1, 384, 240, 240, 240, 194,,, -4, 3, 3, 3, 3, 3, 3, 2, 128, 240, 240, 240, 194,,, -4, 3, 3, 3, 3, 3, 3, 2, 256, 240, 240, 240, 194,,, -4, 3, 3, 3, 3, 3, 3, 2, 384, 240, 240, 240, 194,,, -4, 3, 3, 3, 3, 3, 3, 3, 128, 240, 240, 240, 194,,, -4, 3, 3, 3, 3, 3, 3, 3, 256, 240, 240, 240, 194,,, -4, 3, 3, 3, 3, 3, 3, 3, 384, 240, 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2, 384, 98, 98, 89, 66,,, -4, 3, 4, 1, 3, 3, 1, 3, 128, 98, 98, 89, 66,,, -4, 3, 4, 1, 3, 3, 1, 3, 256, 98, 98, 89, 66,,, -4, 3, 4, 1, 3, 3, 1, 3, 384, 98, 98, 89, 66,,, -4, 3, 4, 1, 3, 3, 2, 1, 128, 98, 98, 89, 66,,, -4, 3, 4, 1, 3, 3, 2, 1, 256, 98, 98, 89, 66,,, -4, 3, 4, 1, 3, 3, 2, 1, 384, 98, 98, 89, 66,,, -4, 3, 4, 1, 3, 3, 2, 2, 128, 98, 98, 89, 66,,, -4, 3, 4, 1, 3, 3, 2, 2, 256, 98, 98, 89, 66,,, -4, 3, 4, 1, 3, 3, 2, 2, 384, 98, 98, 89, 66,,, -4, 3, 4, 1, 3, 3, 2, 3, 128, 98, 98, 89, 66,,, -4, 3, 4, 1, 3, 3, 2, 3, 256, 98, 98, 89, 66,,, -4, 3, 4, 1, 3, 3, 2, 3, 384, 98, 98, 89, 66,,, -4, 3, 4, 1, 3, 3, 3, 1, 128, 98, 98, 89, 66,,, -4, 3, 4, 1, 3, 3, 3, 1, 256, 98, 98, 89, 66,,, -4, 3, 4, 1, 3, 3, 3, 1, 384, 98, 98, 89, 66,,, -4, 3, 4, 1, 3, 3, 3, 2, 128, 98, 98, 89, 66,,, -4, 3, 4, 1, 3, 3, 3, 2, 256, 98, 98, 89, 66,,, -4, 3, 4, 1, 3, 3, 3, 2, 384, 98, 98, 89, 66,,, -4, 3, 4, 1, 3, 3, 3, 3, 128, 98, 98, 89, 66,,, -4, 3, 4, 1, 3, 3, 3, 3, 256, 98, 98, 89, 66,,, -4, 3, 4, 1, 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176, 130,,, -4, 3, 4, 2, 3, 3, 3, 2, 384, 194, 194, 176, 130,,, -4, 3, 4, 2, 3, 3, 3, 3, 128, 194, 194, 176, 130,,, -4, 3, 4, 2, 3, 3, 3, 3, 256, 194, 194, 176, 130,,, -4, 3, 4, 2, 3, 3, 3, 3, 384, 194, 194, 176, 130,,, -4, 3, 4, 3, 1, 1, 1, 1, 128, 240, 240, 240, 194,,, -4, 3, 4, 3, 1, 1, 1, 1, 256, 240, 240, 240, 194,,, -4, 3, 4, 3, 1, 1, 1, 1, 384, 240, 240, 240, 194,,, -4, 3, 4, 3, 2, 2, 1, 1, 128, 240, 240, 240, 194,,, -4, 3, 4, 3, 2, 2, 1, 1, 256, 240, 240, 240, 194,,, -4, 3, 4, 3, 2, 2, 1, 1, 384, 240, 240, 240, 194,,, -4, 3, 4, 3, 2, 2, 1, 2, 128, 240, 240, 240, 194,,, -4, 3, 4, 3, 2, 2, 1, 2, 256, 240, 240, 240, 194,,, -4, 3, 4, 3, 2, 2, 1, 2, 384, 240, 240, 240, 194,,, -4, 3, 4, 3, 2, 2, 2, 1, 128, 240, 240, 240, 194,,, -4, 3, 4, 3, 2, 2, 2, 1, 256, 240, 240, 240, 194,,, -4, 3, 4, 3, 2, 2, 2, 1, 384, 240, 240, 240, 194,,, -4, 3, 4, 3, 2, 2, 2, 2, 128, 240, 240, 240, 194,,, -4, 3, 4, 3, 2, 2, 2, 2, 256, 240, 240, 240, 194,,, -4, 3, 4, 3, 2, 2, 2, 2, 384, 240, 240, 240, 194,,, -4, 3, 4, 3, 3, 3, 1, 1, 128, 240, 240, 240, 194,,, -4, 3, 4, 3, 3, 3, 1, 1, 256, 240, 240, 240, 194,,, -4, 3, 4, 3, 3, 3, 1, 1, 384, 240, 240, 240, 194,,, -4, 3, 4, 3, 3, 3, 1, 2, 128, 240, 240, 240, 194,,, -4, 3, 4, 3, 3, 3, 1, 2, 256, 240, 240, 240, 194,,, -4, 3, 4, 3, 3, 3, 1, 2, 384, 240, 240, 240, 194,,, -4, 3, 4, 3, 3, 3, 1, 3, 128, 240, 240, 240, 194,,, -4, 3, 4, 3, 3, 3, 1, 3, 256, 240, 240, 240, 194,,, -4, 3, 4, 3, 3, 3, 1, 3, 384, 240, 240, 240, 194,,, -4, 3, 4, 3, 3, 3, 2, 1, 128, 240, 240, 240, 194,,, -4, 3, 4, 3, 3, 3, 2, 1, 256, 240, 240, 240, 194,,, -4, 3, 4, 3, 3, 3, 2, 1, 384, 240, 240, 240, 194,,, -4, 3, 4, 3, 3, 3, 2, 2, 128, 240, 240, 240, 194,,, -4, 3, 4, 3, 3, 3, 2, 2, 256, 240, 240, 240, 194,,, -4, 3, 4, 3, 3, 3, 2, 2, 384, 240, 240, 240, 194,,, -4, 3, 4, 3, 3, 3, 2, 3, 128, 240, 240, 240, 194,,, -4, 3, 4, 3, 3, 3, 2, 3, 256, 240, 240, 240, 194,,, -4, 3, 4, 3, 3, 3, 2, 3, 384, 240, 240, 240, 194,,, -4, 3, 4, 3, 3, 3, 3, 1, 128, 240, 240, 240, 194,,, -4, 3, 4, 3, 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3, 3, 3, 1, 128, 99, 96, 83, 56,,, -4, 4, 1, 1, 3, 3, 3, 1, 256, 99, 96, 83, 56,,, -4, 4, 1, 1, 3, 3, 3, 1, 384, 99, 96, 83, 56,,, -4, 4, 1, 1, 3, 3, 3, 2, 128, 99, 96, 83, 56,,, -4, 4, 1, 1, 3, 3, 3, 2, 256, 99, 96, 83, 56,,, -4, 4, 1, 1, 3, 3, 3, 2, 384, 99, 96, 83, 56,,, -4, 4, 1, 1, 3, 3, 3, 3, 128, 99, 96, 83, 56,,, -4, 4, 1, 1, 3, 3, 3, 3, 256, 99, 96, 83, 56,,, -4, 4, 1, 1, 3, 3, 3, 3, 384, 99, 96, 83, 56,,, -4, 4, 1, 2, 1, 1, 1, 1, 128, 195, 195, 195, 131,,, -4, 4, 1, 2, 1, 1, 1, 1, 256, 195, 195, 195, 131,,, -4, 4, 1, 2, 1, 1, 1, 1, 384, 195, 195, 195, 131,,, -4, 4, 1, 2, 2, 2, 1, 1, 128, 195, 195, 171, 115,,, -4, 4, 1, 2, 2, 2, 1, 1, 256, 195, 195, 171, 115,,, -4, 4, 1, 2, 2, 2, 1, 1, 384, 195, 195, 171, 115,,, -4, 4, 1, 2, 2, 2, 1, 2, 128, 195, 195, 171, 115,,, -4, 4, 1, 2, 2, 2, 1, 2, 256, 195, 195, 171, 115,,, -4, 4, 1, 2, 2, 2, 1, 2, 384, 195, 195, 171, 115,,, -4, 4, 1, 2, 2, 2, 2, 1, 128, 195, 195, 171, 115,,, -4, 4, 1, 2, 2, 2, 2, 1, 256, 195, 195, 171, 115,,, -4, 4, 1, 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3, 128, 195, 189, 163, 109,,, -4, 4, 1, 2, 3, 3, 2, 3, 256, 195, 189, 163, 109,,, -4, 4, 1, 2, 3, 3, 2, 3, 384, 195, 189, 163, 109,,, -4, 4, 1, 2, 3, 3, 3, 1, 128, 195, 189, 163, 109,,, -4, 4, 1, 2, 3, 3, 3, 1, 256, 195, 189, 163, 109,,, -4, 4, 1, 2, 3, 3, 3, 1, 384, 195, 189, 163, 109,,, -4, 4, 1, 2, 3, 3, 3, 2, 128, 195, 189, 163, 109,,, -4, 4, 1, 2, 3, 3, 3, 2, 256, 195, 189, 163, 109,,, -4, 4, 1, 2, 3, 3, 3, 2, 384, 195, 189, 163, 109,,, -4, 4, 1, 2, 3, 3, 3, 3, 128, 195, 189, 163, 109,,, -4, 4, 1, 2, 3, 3, 3, 3, 256, 195, 189, 163, 109,,, -4, 4, 1, 2, 3, 3, 3, 3, 384, 195, 189, 163, 109,,, -4, 4, 1, 3, 1, 1, 1, 1, 128, 240, 240, 240, 195,,, -4, 4, 1, 3, 1, 1, 1, 1, 256, 240, 240, 240, 195,,, -4, 4, 1, 3, 1, 1, 1, 1, 384, 240, 240, 240, 195,,, -4, 4, 1, 3, 2, 2, 1, 1, 128, 240, 240, 240, 171,,, -4, 4, 1, 3, 2, 2, 1, 1, 256, 240, 240, 240, 171,,, -4, 4, 1, 3, 2, 2, 1, 1, 384, 240, 240, 240, 171,,, -4, 4, 1, 3, 2, 2, 1, 2, 128, 240, 240, 240, 171,,, -4, 4, 1, 3, 2, 2, 1, 2, 256, 240, 240, 240, 171,,, -4, 4, 1, 3, 2, 2, 1, 2, 384, 240, 240, 240, 171,,, -4, 4, 1, 3, 2, 2, 2, 1, 128, 240, 240, 240, 171,,, -4, 4, 1, 3, 2, 2, 2, 1, 256, 240, 240, 240, 171,,, -4, 4, 1, 3, 2, 2, 2, 1, 384, 240, 240, 240, 171,,, -4, 4, 1, 3, 2, 2, 2, 2, 128, 240, 240, 240, 171,,, -4, 4, 1, 3, 2, 2, 2, 2, 256, 240, 240, 240, 171,,, -4, 4, 1, 3, 2, 2, 2, 2, 384, 240, 240, 240, 171,,, -4, 4, 1, 3, 3, 3, 1, 1, 128, 240, 240, 240, 162,,, -4, 4, 1, 3, 3, 3, 1, 1, 256, 240, 240, 240, 162,,, -4, 4, 1, 3, 3, 3, 1, 1, 384, 240, 240, 240, 162,,, -4, 4, 1, 3, 3, 3, 1, 2, 128, 240, 240, 240, 162,,, -4, 4, 1, 3, 3, 3, 1, 2, 256, 240, 240, 240, 162,,, -4, 4, 1, 3, 3, 3, 1, 2, 384, 240, 240, 240, 162,,, -4, 4, 1, 3, 3, 3, 1, 3, 128, 240, 240, 240, 162,,, -4, 4, 1, 3, 3, 3, 1, 3, 256, 240, 240, 240, 162,,, -4, 4, 1, 3, 3, 3, 1, 3, 384, 240, 240, 240, 162,,, -4, 4, 1, 3, 3, 3, 2, 1, 128, 240, 240, 240, 162,,, -4, 4, 1, 3, 3, 3, 2, 1, 256, 240, 240, 240, 162,,, -4, 4, 1, 3, 3, 3, 2, 1, 384, 240, 240, 240, 162,,, -4, 4, 1, 3, 3, 3, 2, 2, 128, 240, 240, 240, 162,,, -4, 4, 1, 3, 3, 3, 2, 2, 256, 240, 240, 240, 162,,, -4, 4, 1, 3, 3, 3, 2, 2, 384, 240, 240, 240, 162,,, -4, 4, 1, 3, 3, 3, 2, 3, 128, 240, 240, 240, 162,,, -4, 4, 1, 3, 3, 3, 2, 3, 256, 240, 240, 240, 162,,, -4, 4, 1, 3, 3, 3, 2, 3, 384, 240, 240, 240, 162,,, -4, 4, 1, 3, 3, 3, 3, 1, 128, 240, 240, 240, 162,,, -4, 4, 1, 3, 3, 3, 3, 1, 256, 240, 240, 240, 162,,, -4, 4, 1, 3, 3, 3, 3, 1, 384, 240, 240, 240, 162,,, -4, 4, 1, 3, 3, 3, 3, 2, 128, 240, 240, 240, 162,,, -4, 4, 1, 3, 3, 3, 3, 2, 256, 240, 240, 240, 162,,, -4, 4, 1, 3, 3, 3, 3, 2, 384, 240, 240, 240, 162,,, -4, 4, 1, 3, 3, 3, 3, 3, 128, 240, 240, 240, 162,,, -4, 4, 1, 3, 3, 3, 3, 3, 256, 240, 240, 240, 162,,, -4, 4, 1, 3, 3, 3, 3, 3, 384, 240, 240, 240, 162,,, -4, 4, 1, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -4, 4, 1, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -4, 4, 1, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -4, 4, 1, 4, 2, 2, 1, 1, 128, 240, 240, 240, 227,,, -4, 4, 1, 4, 2, 2, 1, 1, 256, 240, 240, 240, 227,,, -4, 4, 1, 4, 2, 2, 1, 1, 384, 240, 240, 240, 227,,, -4, 4, 1, 4, 2, 2, 1, 2, 128, 240, 240, 240, 227,,, -4, 4, 1, 4, 2, 2, 1, 2, 256, 240, 240, 240, 227,,, -4, 4, 1, 4, 2, 2, 1, 2, 384, 240, 240, 240, 227,,, -4, 4, 1, 4, 2, 2, 2, 1, 128, 240, 240, 240, 227,,, -4, 4, 1, 4, 2, 2, 2, 1, 256, 240, 240, 240, 227,,, -4, 4, 1, 4, 2, 2, 2, 1, 384, 240, 240, 240, 227,,, -4, 4, 1, 4, 2, 2, 2, 2, 128, 240, 240, 240, 227,,, -4, 4, 1, 4, 2, 2, 2, 2, 256, 240, 240, 240, 227,,, -4, 4, 1, 4, 2, 2, 2, 2, 384, 240, 240, 240, 227,,, -4, 4, 1, 4, 3, 3, 1, 1, 128, 240, 240, 240, 215,,, -4, 4, 1, 4, 3, 3, 1, 1, 256, 240, 240, 240, 215,,, -4, 4, 1, 4, 3, 3, 1, 1, 384, 240, 240, 240, 215,,, -4, 4, 1, 4, 3, 3, 1, 2, 128, 240, 240, 240, 215,,, -4, 4, 1, 4, 3, 3, 1, 2, 256, 240, 240, 240, 215,,, -4, 4, 1, 4, 3, 3, 1, 2, 384, 240, 240, 240, 215,,, -4, 4, 1, 4, 3, 3, 1, 3, 128, 240, 240, 240, 215,,, -4, 4, 1, 4, 3, 3, 1, 3, 256, 240, 240, 240, 215,,, -4, 4, 1, 4, 3, 3, 1, 3, 384, 240, 240, 240, 215,,, -4, 4, 1, 4, 3, 3, 2, 1, 128, 240, 240, 240, 215,,, -4, 4, 1, 4, 3, 3, 2, 1, 256, 240, 240, 240, 215,,, -4, 4, 1, 4, 3, 3, 2, 1, 384, 240, 240, 240, 215,,, -4, 4, 1, 4, 3, 3, 2, 2, 128, 240, 240, 240, 215,,, -4, 4, 1, 4, 3, 3, 2, 2, 256, 240, 240, 240, 215,,, -4, 4, 1, 4, 3, 3, 2, 2, 384, 240, 240, 240, 215,,, -4, 4, 1, 4, 3, 3, 2, 3, 128, 240, 240, 240, 215,,, -4, 4, 1, 4, 3, 3, 2, 3, 256, 240, 240, 240, 215,,, -4, 4, 1, 4, 3, 3, 2, 3, 384, 240, 240, 240, 215,,, -4, 4, 1, 4, 3, 3, 3, 1, 128, 240, 240, 240, 215,,, -4, 4, 1, 4, 3, 3, 3, 1, 256, 240, 240, 240, 215,,, -4, 4, 1, 4, 3, 3, 3, 1, 384, 240, 240, 240, 215,,, -4, 4, 1, 4, 3, 3, 3, 2, 128, 240, 240, 240, 215,,, -4, 4, 1, 4, 3, 3, 3, 2, 256, 240, 240, 240, 215,,, -4, 4, 1, 4, 3, 3, 3, 2, 384, 240, 240, 240, 215,,, -4, 4, 1, 4, 3, 3, 3, 3, 128, 240, 240, 240, 215,,, -4, 4, 1, 4, 3, 3, 3, 3, 256, 240, 240, 240, 215,,, -4, 4, 1, 4, 3, 3, 3, 3, 384, 240, 240, 240, 215,,, -4, 4, 2, 1, 1, 1, 1, 1, 128, 99, 99, 99, 67,,, -4, 4, 2, 1, 1, 1, 1, 1, 256, 99, 99, 99, 67,,, -4, 4, 2, 1, 1, 1, 1, 1, 384, 99, 99, 99, 67,,, -4, 4, 2, 1, 2, 2, 1, 1, 128, 99, 99, 87, 59,,, -4, 4, 2, 1, 2, 2, 1, 1, 256, 99, 99, 87, 59,,, -4, 4, 2, 1, 2, 2, 1, 1, 384, 99, 99, 87, 59,,, -4, 4, 2, 1, 2, 2, 1, 2, 128, 99, 99, 87, 59,,, -4, 4, 2, 1, 2, 2, 1, 2, 256, 99, 99, 87, 59,,, -4, 4, 2, 1, 2, 2, 1, 2, 384, 99, 99, 87, 59,,, -4, 4, 2, 1, 2, 2, 2, 1, 128, 99, 99, 87, 59,,, -4, 4, 2, 1, 2, 2, 2, 1, 256, 99, 99, 87, 59,,, -4, 4, 2, 1, 2, 2, 2, 1, 384, 99, 99, 87, 59,,, -4, 4, 2, 1, 2, 2, 2, 2, 128, 99, 99, 87, 59,,, -4, 4, 2, 1, 2, 2, 2, 2, 256, 99, 99, 87, 59,,, -4, 4, 2, 1, 2, 2, 2, 2, 384, 99, 99, 87, 59,,, -4, 4, 2, 1, 3, 3, 1, 1, 128, 99, 96, 83, 56,,, -4, 4, 2, 1, 3, 3, 1, 1, 256, 99, 96, 83, 56,,, -4, 4, 2, 1, 3, 3, 1, 1, 384, 99, 96, 83, 56,,, -4, 4, 2, 1, 3, 3, 1, 2, 128, 99, 96, 83, 56,,, -4, 4, 2, 1, 3, 3, 1, 2, 256, 99, 96, 83, 56,,, -4, 4, 2, 1, 3, 3, 1, 2, 384, 99, 96, 83, 56,,, -4, 4, 2, 1, 3, 3, 1, 3, 128, 99, 96, 83, 56,,, -4, 4, 2, 1, 3, 3, 1, 3, 256, 99, 96, 83, 56,,, -4, 4, 2, 1, 3, 3, 1, 3, 384, 99, 96, 83, 56,,, -4, 4, 2, 1, 3, 3, 2, 1, 128, 99, 96, 83, 56,,, -4, 4, 2, 1, 3, 3, 2, 1, 256, 99, 96, 83, 56,,, -4, 4, 2, 1, 3, 3, 2, 1, 384, 99, 96, 83, 56,,, -4, 4, 2, 1, 3, 3, 2, 2, 128, 99, 96, 83, 56,,, -4, 4, 2, 1, 3, 3, 2, 2, 256, 99, 96, 83, 56,,, -4, 4, 2, 1, 3, 3, 2, 2, 384, 99, 96, 83, 56,,, -4, 4, 2, 1, 3, 3, 2, 3, 128, 99, 96, 83, 56,,, -4, 4, 2, 1, 3, 3, 2, 3, 256, 99, 96, 83, 56,,, -4, 4, 2, 1, 3, 3, 2, 3, 384, 99, 96, 83, 56,,, -4, 4, 2, 1, 3, 3, 3, 1, 128, 99, 96, 83, 56,,, -4, 4, 2, 1, 3, 3, 3, 1, 256, 99, 96, 83, 56,,, -4, 4, 2, 1, 3, 3, 3, 1, 384, 99, 96, 83, 56,,, -4, 4, 2, 1, 3, 3, 3, 2, 128, 99, 96, 83, 56,,, -4, 4, 2, 1, 3, 3, 3, 2, 256, 99, 96, 83, 56,,, -4, 4, 2, 1, 3, 3, 3, 2, 384, 99, 96, 83, 56,,, -4, 4, 2, 1, 3, 3, 3, 3, 128, 99, 96, 83, 56,,, -4, 4, 2, 1, 3, 3, 3, 3, 256, 99, 96, 83, 56,,, -4, 4, 2, 1, 3, 3, 3, 3, 384, 99, 96, 83, 56,,, -4, 4, 2, 2, 1, 1, 1, 1, 128, 195, 195, 195, 131,,, -4, 4, 2, 2, 1, 1, 1, 1, 256, 195, 195, 195, 131,,, -4, 4, 2, 2, 1, 1, 1, 1, 384, 195, 195, 195, 131,,, -4, 4, 2, 2, 2, 2, 1, 1, 128, 195, 195, 171, 115,,, -4, 4, 2, 2, 2, 2, 1, 1, 256, 195, 195, 171, 115,,, -4, 4, 2, 2, 2, 2, 1, 1, 384, 195, 195, 171, 115,,, -4, 4, 2, 2, 2, 2, 1, 2, 128, 195, 195, 171, 115,,, -4, 4, 2, 2, 2, 2, 1, 2, 256, 195, 195, 171, 115,,, -4, 4, 2, 2, 2, 2, 1, 2, 384, 195, 195, 171, 115,,, -4, 4, 2, 2, 2, 2, 2, 1, 128, 195, 195, 171, 115,,, -4, 4, 2, 2, 2, 2, 2, 1, 256, 195, 195, 171, 115,,, -4, 4, 2, 2, 2, 2, 2, 1, 384, 195, 195, 171, 115,,, -4, 4, 2, 2, 2, 2, 2, 2, 128, 195, 195, 171, 115,,, -4, 4, 2, 2, 2, 2, 2, 2, 256, 195, 195, 171, 115,,, -4, 4, 2, 2, 2, 2, 2, 2, 384, 195, 195, 171, 115,,, -4, 4, 2, 2, 3, 3, 1, 1, 128, 195, 189, 163, 109,,, -4, 4, 2, 2, 3, 3, 1, 1, 256, 195, 189, 163, 109,,, -4, 4, 2, 2, 3, 3, 1, 1, 384, 195, 189, 163, 109,,, -4, 4, 2, 2, 3, 3, 1, 2, 128, 195, 189, 163, 109,,, -4, 4, 2, 2, 3, 3, 1, 2, 256, 195, 189, 163, 109,,, -4, 4, 2, 2, 3, 3, 1, 2, 384, 195, 189, 163, 109,,, -4, 4, 2, 2, 3, 3, 1, 3, 128, 195, 189, 163, 109,,, -4, 4, 2, 2, 3, 3, 1, 3, 256, 195, 189, 163, 109,,, -4, 4, 2, 2, 3, 3, 1, 3, 384, 195, 189, 163, 109,,, -4, 4, 2, 2, 3, 3, 2, 1, 128, 195, 189, 163, 109,,, -4, 4, 2, 2, 3, 3, 2, 1, 256, 195, 189, 163, 109,,, -4, 4, 2, 2, 3, 3, 2, 1, 384, 195, 189, 163, 109,,, -4, 4, 2, 2, 3, 3, 2, 2, 128, 195, 189, 163, 109,,, -4, 4, 2, 2, 3, 3, 2, 2, 256, 195, 189, 163, 109,,, -4, 4, 2, 2, 3, 3, 2, 2, 384, 195, 189, 163, 109,,, -4, 4, 2, 2, 3, 3, 2, 3, 128, 195, 189, 163, 109,,, -4, 4, 2, 2, 3, 3, 2, 3, 256, 195, 189, 163, 109,,, -4, 4, 2, 2, 3, 3, 2, 3, 384, 195, 189, 163, 109,,, -4, 4, 2, 2, 3, 3, 3, 1, 128, 195, 189, 163, 109,,, -4, 4, 2, 2, 3, 3, 3, 1, 256, 195, 189, 163, 109,,, -4, 4, 2, 2, 3, 3, 3, 1, 384, 195, 189, 163, 109,,, -4, 4, 2, 2, 3, 3, 3, 2, 128, 195, 189, 163, 109,,, -4, 4, 2, 2, 3, 3, 3, 2, 256, 195, 189, 163, 109,,, -4, 4, 2, 2, 3, 3, 3, 2, 384, 195, 189, 163, 109,,, -4, 4, 2, 2, 3, 3, 3, 3, 128, 195, 189, 163, 109,,, -4, 4, 2, 2, 3, 3, 3, 3, 256, 195, 189, 163, 109,,, -4, 4, 2, 2, 3, 3, 3, 3, 384, 195, 189, 163, 109,,, -4, 4, 2, 3, 1, 1, 1, 1, 128, 240, 240, 240, 195,,, -4, 4, 2, 3, 1, 1, 1, 1, 256, 240, 240, 240, 195,,, -4, 4, 2, 3, 1, 1, 1, 1, 384, 240, 240, 240, 195,,, -4, 4, 2, 3, 2, 2, 1, 1, 128, 240, 240, 240, 171,,, -4, 4, 2, 3, 2, 2, 1, 1, 256, 240, 240, 240, 171,,, -4, 4, 2, 3, 2, 2, 1, 1, 384, 240, 240, 240, 171,,, -4, 4, 2, 3, 2, 2, 1, 2, 128, 240, 240, 240, 171,,, -4, 4, 2, 3, 2, 2, 1, 2, 256, 240, 240, 240, 171,,, -4, 4, 2, 3, 2, 2, 1, 2, 384, 240, 240, 240, 171,,, -4, 4, 2, 3, 2, 2, 2, 1, 128, 240, 240, 240, 171,,, -4, 4, 2, 3, 2, 2, 2, 1, 256, 240, 240, 240, 171,,, -4, 4, 2, 3, 2, 2, 2, 1, 384, 240, 240, 240, 171,,, -4, 4, 2, 3, 2, 2, 2, 2, 128, 240, 240, 240, 171,,, -4, 4, 2, 3, 2, 2, 2, 2, 256, 240, 240, 240, 171,,, -4, 4, 2, 3, 2, 2, 2, 2, 384, 240, 240, 240, 171,,, -4, 4, 2, 3, 3, 3, 1, 1, 128, 240, 240, 240, 162,,, -4, 4, 2, 3, 3, 3, 1, 1, 256, 240, 240, 240, 162,,, -4, 4, 2, 3, 3, 3, 1, 1, 384, 240, 240, 240, 162,,, -4, 4, 2, 3, 3, 3, 1, 2, 128, 240, 240, 240, 162,,, -4, 4, 2, 3, 3, 3, 1, 2, 256, 240, 240, 240, 162,,, -4, 4, 2, 3, 3, 3, 1, 2, 384, 240, 240, 240, 162,,, -4, 4, 2, 3, 3, 3, 1, 3, 128, 240, 240, 240, 162,,, -4, 4, 2, 3, 3, 3, 1, 3, 256, 240, 240, 240, 162,,, -4, 4, 2, 3, 3, 3, 1, 3, 384, 240, 240, 240, 162,,, -4, 4, 2, 3, 3, 3, 2, 1, 128, 240, 240, 240, 162,,, -4, 4, 2, 3, 3, 3, 2, 1, 256, 240, 240, 240, 162,,, -4, 4, 2, 3, 3, 3, 2, 1, 384, 240, 240, 240, 162,,, -4, 4, 2, 3, 3, 3, 2, 2, 128, 240, 240, 240, 162,,, -4, 4, 2, 3, 3, 3, 2, 2, 256, 240, 240, 240, 162,,, -4, 4, 2, 3, 3, 3, 2, 2, 384, 240, 240, 240, 162,,, -4, 4, 2, 3, 3, 3, 2, 3, 128, 240, 240, 240, 162,,, -4, 4, 2, 3, 3, 3, 2, 3, 256, 240, 240, 240, 162,,, -4, 4, 2, 3, 3, 3, 2, 3, 384, 240, 240, 240, 162,,, -4, 4, 2, 3, 3, 3, 3, 1, 128, 240, 240, 240, 162,,, -4, 4, 2, 3, 3, 3, 3, 1, 256, 240, 240, 240, 162,,, -4, 4, 2, 3, 3, 3, 3, 1, 384, 240, 240, 240, 162,,, -4, 4, 2, 3, 3, 3, 3, 2, 128, 240, 240, 240, 162,,, -4, 4, 2, 3, 3, 3, 3, 2, 256, 240, 240, 240, 162,,, -4, 4, 2, 3, 3, 3, 3, 2, 384, 240, 240, 240, 162,,, -4, 4, 2, 3, 3, 3, 3, 3, 128, 240, 240, 240, 162,,, -4, 4, 2, 3, 3, 3, 3, 3, 256, 240, 240, 240, 162,,, -4, 4, 2, 3, 3, 3, 3, 3, 384, 240, 240, 240, 162,,, -4, 4, 2, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -4, 4, 2, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -4, 4, 2, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -4, 4, 2, 4, 2, 2, 1, 1, 128, 240, 240, 240, 227,,, -4, 4, 2, 4, 2, 2, 1, 1, 256, 240, 240, 240, 227,,, -4, 4, 2, 4, 2, 2, 1, 1, 384, 240, 240, 240, 227,,, -4, 4, 2, 4, 2, 2, 1, 2, 128, 240, 240, 240, 227,,, -4, 4, 2, 4, 2, 2, 1, 2, 256, 240, 240, 240, 227,,, -4, 4, 2, 4, 2, 2, 1, 2, 384, 240, 240, 240, 227,,, -4, 4, 2, 4, 2, 2, 2, 1, 128, 240, 240, 240, 227,,, -4, 4, 2, 4, 2, 2, 2, 1, 256, 240, 240, 240, 227,,, -4, 4, 2, 4, 2, 2, 2, 1, 384, 240, 240, 240, 227,,, -4, 4, 2, 4, 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256, 240, 240, 240, 215,,, -4, 4, 2, 4, 3, 3, 2, 3, 384, 240, 240, 240, 215,,, -4, 4, 2, 4, 3, 3, 3, 1, 128, 240, 240, 240, 215,,, -4, 4, 2, 4, 3, 3, 3, 1, 256, 240, 240, 240, 215,,, -4, 4, 2, 4, 3, 3, 3, 1, 384, 240, 240, 240, 215,,, -4, 4, 2, 4, 3, 3, 3, 2, 128, 240, 240, 240, 215,,, -4, 4, 2, 4, 3, 3, 3, 2, 256, 240, 240, 240, 215,,, -4, 4, 2, 4, 3, 3, 3, 2, 384, 240, 240, 240, 215,,, -4, 4, 2, 4, 3, 3, 3, 3, 128, 240, 240, 240, 215,,, -4, 4, 2, 4, 3, 3, 3, 3, 256, 240, 240, 240, 215,,, -4, 4, 2, 4, 3, 3, 3, 3, 384, 240, 240, 240, 215,,, -4, 4, 3, 1, 1, 1, 1, 1, 128, 99, 99, 99, 67,,, -4, 4, 3, 1, 1, 1, 1, 1, 256, 99, 99, 99, 67,,, -4, 4, 3, 1, 1, 1, 1, 1, 384, 99, 99, 99, 67,,, -4, 4, 3, 1, 2, 2, 1, 1, 128, 99, 99, 87, 59,,, -4, 4, 3, 1, 2, 2, 1, 1, 256, 99, 99, 87, 59,,, -4, 4, 3, 1, 2, 2, 1, 1, 384, 99, 99, 87, 59,,, -4, 4, 3, 1, 2, 2, 1, 2, 128, 99, 99, 87, 59,,, -4, 4, 3, 1, 2, 2, 1, 2, 256, 99, 99, 87, 59,,, -4, 4, 3, 1, 2, 2, 1, 2, 384, 99, 99, 87, 59,,, -4, 4, 3, 1, 2, 2, 2, 1, 128, 99, 99, 87, 59,,, -4, 4, 3, 1, 2, 2, 2, 1, 256, 99, 99, 87, 59,,, -4, 4, 3, 1, 2, 2, 2, 1, 384, 99, 99, 87, 59,,, -4, 4, 3, 1, 2, 2, 2, 2, 128, 99, 99, 87, 59,,, -4, 4, 3, 1, 2, 2, 2, 2, 256, 99, 99, 87, 59,,, -4, 4, 3, 1, 2, 2, 2, 2, 384, 99, 99, 87, 59,,, -4, 4, 3, 1, 3, 3, 1, 1, 128, 99, 96, 83, 56,,, -4, 4, 3, 1, 3, 3, 1, 1, 256, 99, 96, 83, 56,,, -4, 4, 3, 1, 3, 3, 1, 1, 384, 99, 96, 83, 56,,, -4, 4, 3, 1, 3, 3, 1, 2, 128, 99, 96, 83, 56,,, -4, 4, 3, 1, 3, 3, 1, 2, 256, 99, 96, 83, 56,,, -4, 4, 3, 1, 3, 3, 1, 2, 384, 99, 96, 83, 56,,, -4, 4, 3, 1, 3, 3, 1, 3, 128, 99, 96, 83, 56,,, -4, 4, 3, 1, 3, 3, 1, 3, 256, 99, 96, 83, 56,,, -4, 4, 3, 1, 3, 3, 1, 3, 384, 99, 96, 83, 56,,, -4, 4, 3, 1, 3, 3, 2, 1, 128, 99, 96, 83, 56,,, -4, 4, 3, 1, 3, 3, 2, 1, 256, 99, 96, 83, 56,,, -4, 4, 3, 1, 3, 3, 2, 1, 384, 99, 96, 83, 56,,, -4, 4, 3, 1, 3, 3, 2, 2, 128, 99, 96, 83, 56,,, -4, 4, 3, 1, 3, 3, 2, 2, 256, 99, 96, 83, 56,,, -4, 4, 3, 1, 3, 3, 2, 2, 384, 99, 96, 83, 56,,, -4, 4, 3, 1, 3, 3, 2, 3, 128, 99, 96, 83, 56,,, -4, 4, 3, 1, 3, 3, 2, 3, 256, 99, 96, 83, 56,,, -4, 4, 3, 1, 3, 3, 2, 3, 384, 99, 96, 83, 56,,, -4, 4, 3, 1, 3, 3, 3, 1, 128, 99, 96, 83, 56,,, -4, 4, 3, 1, 3, 3, 3, 1, 256, 99, 96, 83, 56,,, -4, 4, 3, 1, 3, 3, 3, 1, 384, 99, 96, 83, 56,,, -4, 4, 3, 1, 3, 3, 3, 2, 128, 99, 96, 83, 56,,, -4, 4, 3, 1, 3, 3, 3, 2, 256, 99, 96, 83, 56,,, -4, 4, 3, 1, 3, 3, 3, 2, 384, 99, 96, 83, 56,,, -4, 4, 3, 1, 3, 3, 3, 3, 128, 99, 96, 83, 56,,, -4, 4, 3, 1, 3, 3, 3, 3, 256, 99, 96, 83, 56,,, -4, 4, 3, 1, 3, 3, 3, 3, 384, 99, 96, 83, 56,,, -4, 4, 3, 2, 1, 1, 1, 1, 128, 195, 195, 195, 131,,, -4, 4, 3, 2, 1, 1, 1, 1, 256, 195, 195, 195, 131,,, -4, 4, 3, 2, 1, 1, 1, 1, 384, 195, 195, 195, 131,,, -4, 4, 3, 2, 2, 2, 1, 1, 128, 195, 195, 171, 115,,, -4, 4, 3, 2, 2, 2, 1, 1, 256, 195, 195, 171, 115,,, -4, 4, 3, 2, 2, 2, 1, 1, 384, 195, 195, 171, 115,,, -4, 4, 3, 2, 2, 2, 1, 2, 128, 195, 195, 171, 115,,, -4, 4, 3, 2, 2, 2, 1, 2, 256, 195, 195, 171, 115,,, -4, 4, 3, 2, 2, 2, 1, 2, 384, 195, 195, 171, 115,,, -4, 4, 3, 2, 2, 2, 2, 1, 128, 195, 195, 171, 115,,, -4, 4, 3, 2, 2, 2, 2, 1, 256, 195, 195, 171, 115,,, -4, 4, 3, 2, 2, 2, 2, 1, 384, 195, 195, 171, 115,,, -4, 4, 3, 2, 2, 2, 2, 2, 128, 195, 195, 171, 115,,, -4, 4, 3, 2, 2, 2, 2, 2, 256, 195, 195, 171, 115,,, -4, 4, 3, 2, 2, 2, 2, 2, 384, 195, 195, 171, 115,,, -4, 4, 3, 2, 3, 3, 1, 1, 128, 195, 189, 163, 109,,, -4, 4, 3, 2, 3, 3, 1, 1, 256, 195, 189, 163, 109,,, -4, 4, 3, 2, 3, 3, 1, 1, 384, 195, 189, 163, 109,,, -4, 4, 3, 2, 3, 3, 1, 2, 128, 195, 189, 163, 109,,, -4, 4, 3, 2, 3, 3, 1, 2, 256, 195, 189, 163, 109,,, -4, 4, 3, 2, 3, 3, 1, 2, 384, 195, 189, 163, 109,,, -4, 4, 3, 2, 3, 3, 1, 3, 128, 195, 189, 163, 109,,, -4, 4, 3, 2, 3, 3, 1, 3, 256, 195, 189, 163, 109,,, -4, 4, 3, 2, 3, 3, 1, 3, 384, 195, 189, 163, 109,,, -4, 4, 3, 2, 3, 3, 2, 1, 128, 195, 189, 163, 109,,, -4, 4, 3, 2, 3, 3, 2, 1, 256, 195, 189, 163, 109,,, -4, 4, 3, 2, 3, 3, 2, 1, 384, 195, 189, 163, 109,,, -4, 4, 3, 2, 3, 3, 2, 2, 128, 195, 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171,,, -4, 4, 3, 3, 2, 2, 1, 1, 384, 240, 240, 240, 171,,, -4, 4, 3, 3, 2, 2, 1, 2, 128, 240, 240, 240, 171,,, -4, 4, 3, 3, 2, 2, 1, 2, 256, 240, 240, 240, 171,,, -4, 4, 3, 3, 2, 2, 1, 2, 384, 240, 240, 240, 171,,, -4, 4, 3, 3, 2, 2, 2, 1, 128, 240, 240, 240, 171,,, -4, 4, 3, 3, 2, 2, 2, 1, 256, 240, 240, 240, 171,,, -4, 4, 3, 3, 2, 2, 2, 1, 384, 240, 240, 240, 171,,, -4, 4, 3, 3, 2, 2, 2, 2, 128, 240, 240, 240, 171,,, -4, 4, 3, 3, 2, 2, 2, 2, 256, 240, 240, 240, 171,,, -4, 4, 3, 3, 2, 2, 2, 2, 384, 240, 240, 240, 171,,, -4, 4, 3, 3, 3, 3, 1, 1, 128, 240, 240, 240, 162,,, -4, 4, 3, 3, 3, 3, 1, 1, 256, 240, 240, 240, 162,,, -4, 4, 3, 3, 3, 3, 1, 1, 384, 240, 240, 240, 162,,, -4, 4, 3, 3, 3, 3, 1, 2, 128, 240, 240, 240, 162,,, -4, 4, 3, 3, 3, 3, 1, 2, 256, 240, 240, 240, 162,,, -4, 4, 3, 3, 3, 3, 1, 2, 384, 240, 240, 240, 162,,, -4, 4, 3, 3, 3, 3, 1, 3, 128, 240, 240, 240, 162,,, -4, 4, 3, 3, 3, 3, 1, 3, 256, 240, 240, 240, 162,,, -4, 4, 3, 3, 3, 3, 1, 3, 384, 240, 240, 240, 162,,, -4, 4, 3, 3, 3, 3, 2, 1, 128, 240, 240, 240, 162,,, -4, 4, 3, 3, 3, 3, 2, 1, 256, 240, 240, 240, 162,,, -4, 4, 3, 3, 3, 3, 2, 1, 384, 240, 240, 240, 162,,, -4, 4, 3, 3, 3, 3, 2, 2, 128, 240, 240, 240, 162,,, -4, 4, 3, 3, 3, 3, 2, 2, 256, 240, 240, 240, 162,,, -4, 4, 3, 3, 3, 3, 2, 2, 384, 240, 240, 240, 162,,, -4, 4, 3, 3, 3, 3, 2, 3, 128, 240, 240, 240, 162,,, -4, 4, 3, 3, 3, 3, 2, 3, 256, 240, 240, 240, 162,,, -4, 4, 3, 3, 3, 3, 2, 3, 384, 240, 240, 240, 162,,, -4, 4, 3, 3, 3, 3, 3, 1, 128, 240, 240, 240, 162,,, -4, 4, 3, 3, 3, 3, 3, 1, 256, 240, 240, 240, 162,,, -4, 4, 3, 3, 3, 3, 3, 1, 384, 240, 240, 240, 162,,, -4, 4, 3, 3, 3, 3, 3, 2, 128, 240, 240, 240, 162,,, -4, 4, 3, 3, 3, 3, 3, 2, 256, 240, 240, 240, 162,,, -4, 4, 3, 3, 3, 3, 3, 2, 384, 240, 240, 240, 162,,, -4, 4, 3, 3, 3, 3, 3, 3, 128, 240, 240, 240, 162,,, -4, 4, 3, 3, 3, 3, 3, 3, 256, 240, 240, 240, 162,,, -4, 4, 3, 3, 3, 3, 3, 3, 384, 240, 240, 240, 162,,, -4, 4, 3, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -4, 4, 3, 4, 1, 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163, 109,,, -4, 4, 4, 2, 3, 3, 3, 2, 128, 195, 189, 163, 109,,, -4, 4, 4, 2, 3, 3, 3, 2, 256, 195, 189, 163, 109,,, -4, 4, 4, 2, 3, 3, 3, 2, 384, 195, 189, 163, 109,,, -4, 4, 4, 2, 3, 3, 3, 3, 128, 195, 189, 163, 109,,, -4, 4, 4, 2, 3, 3, 3, 3, 256, 195, 189, 163, 109,,, -4, 4, 4, 2, 3, 3, 3, 3, 384, 195, 189, 163, 109,,, -4, 4, 4, 3, 1, 1, 1, 1, 128, 240, 240, 240, 195,,, -4, 4, 4, 3, 1, 1, 1, 1, 256, 240, 240, 240, 195,,, -4, 4, 4, 3, 1, 1, 1, 1, 384, 240, 240, 240, 195,,, -4, 4, 4, 3, 2, 2, 1, 1, 128, 240, 240, 240, 171,,, -4, 4, 4, 3, 2, 2, 1, 1, 256, 240, 240, 240, 171,,, -4, 4, 4, 3, 2, 2, 1, 1, 384, 240, 240, 240, 171,,, -4, 4, 4, 3, 2, 2, 1, 2, 128, 240, 240, 240, 171,,, -4, 4, 4, 3, 2, 2, 1, 2, 256, 240, 240, 240, 171,,, -4, 4, 4, 3, 2, 2, 1, 2, 384, 240, 240, 240, 171,,, -4, 4, 4, 3, 2, 2, 2, 1, 128, 240, 240, 240, 171,,, -4, 4, 4, 3, 2, 2, 2, 1, 256, 240, 240, 240, 171,,, -4, 4, 4, 3, 2, 2, 2, 1, 384, 240, 240, 240, 171,,, -4, 4, 4, 3, 2, 2, 2, 2, 128, 240, 240, 240, 171,,, -4, 4, 4, 3, 2, 2, 2, 2, 256, 240, 240, 240, 171,,, -4, 4, 4, 3, 2, 2, 2, 2, 384, 240, 240, 240, 171,,, -4, 4, 4, 3, 3, 3, 1, 1, 128, 240, 240, 240, 162,,, -4, 4, 4, 3, 3, 3, 1, 1, 256, 240, 240, 240, 162,,, -4, 4, 4, 3, 3, 3, 1, 1, 384, 240, 240, 240, 162,,, -4, 4, 4, 3, 3, 3, 1, 2, 128, 240, 240, 240, 162,,, -4, 4, 4, 3, 3, 3, 1, 2, 256, 240, 240, 240, 162,,, -4, 4, 4, 3, 3, 3, 1, 2, 384, 240, 240, 240, 162,,, -4, 4, 4, 3, 3, 3, 1, 3, 128, 240, 240, 240, 162,,, -4, 4, 4, 3, 3, 3, 1, 3, 256, 240, 240, 240, 162,,, -4, 4, 4, 3, 3, 3, 1, 3, 384, 240, 240, 240, 162,,, -4, 4, 4, 3, 3, 3, 2, 1, 128, 240, 240, 240, 162,,, -4, 4, 4, 3, 3, 3, 2, 1, 256, 240, 240, 240, 162,,, -4, 4, 4, 3, 3, 3, 2, 1, 384, 240, 240, 240, 162,,, -4, 4, 4, 3, 3, 3, 2, 2, 128, 240, 240, 240, 162,,, -4, 4, 4, 3, 3, 3, 2, 2, 256, 240, 240, 240, 162,,, -4, 4, 4, 3, 3, 3, 2, 2, 384, 240, 240, 240, 162,,, -4, 4, 4, 3, 3, 3, 2, 3, 128, 240, 240, 240, 162,,, -4, 4, 4, 3, 3, 3, 2, 3, 256, 240, 240, 240, 162,,, -4, 4, 4, 3, 3, 3, 2, 3, 384, 240, 240, 240, 162,,, -4, 4, 4, 3, 3, 3, 3, 1, 128, 240, 240, 240, 162,,, -4, 4, 4, 3, 3, 3, 3, 1, 256, 240, 240, 240, 162,,, -4, 4, 4, 3, 3, 3, 3, 1, 384, 240, 240, 240, 162,,, -4, 4, 4, 3, 3, 3, 3, 2, 128, 240, 240, 240, 162,,, -4, 4, 4, 3, 3, 3, 3, 2, 256, 240, 240, 240, 162,,, -4, 4, 4, 3, 3, 3, 3, 2, 384, 240, 240, 240, 162,,, -4, 4, 4, 3, 3, 3, 3, 3, 128, 240, 240, 240, 162,,, -4, 4, 4, 3, 3, 3, 3, 3, 256, 240, 240, 240, 162,,, -4, 4, 4, 3, 3, 3, 3, 3, 384, 240, 240, 240, 162,,, -4, 4, 4, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -4, 4, 4, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -4, 4, 4, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -4, 4, 4, 4, 2, 2, 1, 1, 128, 240, 240, 240, 227,,, -4, 4, 4, 4, 2, 2, 1, 1, 256, 240, 240, 240, 227,,, -4, 4, 4, 4, 2, 2, 1, 1, 384, 240, 240, 240, 227,,, -4, 4, 4, 4, 2, 2, 1, 2, 128, 240, 240, 240, 227,,, -4, 4, 4, 4, 2, 2, 1, 2, 256, 240, 240, 240, 227,,, -4, 4, 4, 4, 2, 2, 1, 2, 384, 240, 240, 240, 227,,, -4, 4, 4, 4, 2, 2, 2, 1, 128, 240, 240, 240, 227,,, -4, 4, 4, 4, 2, 2, 2, 1, 256, 240, 240, 240, 227,,, -4, 4, 4, 4, 2, 2, 2, 1, 384, 240, 240, 240, 227,,, -4, 4, 4, 4, 2, 2, 2, 2, 128, 240, 240, 240, 227,,, -4, 4, 4, 4, 2, 2, 2, 2, 256, 240, 240, 240, 227,,, -4, 4, 4, 4, 2, 2, 2, 2, 384, 240, 240, 240, 227,,, -4, 4, 4, 4, 3, 3, 1, 1, 128, 240, 240, 240, 215,,, -4, 4, 4, 4, 3, 3, 1, 1, 256, 240, 240, 240, 215,,, -4, 4, 4, 4, 3, 3, 1, 1, 384, 240, 240, 240, 215,,, -4, 4, 4, 4, 3, 3, 1, 2, 128, 240, 240, 240, 215,,, -4, 4, 4, 4, 3, 3, 1, 2, 256, 240, 240, 240, 215,,, -4, 4, 4, 4, 3, 3, 1, 2, 384, 240, 240, 240, 215,,, -4, 4, 4, 4, 3, 3, 1, 3, 128, 240, 240, 240, 215,,, -4, 4, 4, 4, 3, 3, 1, 3, 256, 240, 240, 240, 215,,, -4, 4, 4, 4, 3, 3, 1, 3, 384, 240, 240, 240, 215,,, -4, 4, 4, 4, 3, 3, 2, 1, 128, 240, 240, 240, 215,,, -4, 4, 4, 4, 3, 3, 2, 1, 256, 240, 240, 240, 215,,, -4, 4, 4, 4, 3, 3, 2, 1, 384, 240, 240, 240, 215,,, -4, 4, 4, 4, 3, 3, 2, 2, 128, 240, 240, 240, 215,,, -4, 4, 4, 4, 3, 3, 2, 2, 256, 240, 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2, 1, 2, 384, 240, 240, 240, 164,,, -4, 5, 4, 5, 2, 2, 2, 1, 128, 240, 240, 240, 164,,, -4, 5, 4, 5, 2, 2, 2, 1, 256, 240, 240, 240, 164,,, -4, 5, 4, 5, 2, 2, 2, 1, 384, 240, 240, 240, 164,,, -4, 5, 4, 5, 2, 2, 2, 2, 128, 240, 240, 240, 164,,, -4, 5, 4, 5, 2, 2, 2, 2, 256, 240, 240, 240, 164,,, -4, 5, 4, 5, 2, 2, 2, 2, 384, 240, 240, 240, 164,,, -4, 5, 4, 5, 3, 3, 1, 1, 128, 240, 240, 240, 164,,, -4, 5, 4, 5, 3, 3, 1, 1, 256, 240, 240, 240, 164,,, -4, 5, 4, 5, 3, 3, 1, 1, 384, 240, 240, 240, 164,,, -4, 5, 4, 5, 3, 3, 1, 2, 128, 240, 240, 240, 164,,, -4, 5, 4, 5, 3, 3, 1, 2, 256, 240, 240, 240, 164,,, -4, 5, 4, 5, 3, 3, 1, 2, 384, 240, 240, 240, 164,,, -4, 5, 4, 5, 3, 3, 1, 3, 128, 240, 240, 240, 164,,, -4, 5, 4, 5, 3, 3, 1, 3, 256, 240, 240, 240, 164,,, -4, 5, 4, 5, 3, 3, 1, 3, 384, 240, 240, 240, 164,,, -4, 5, 4, 5, 3, 3, 2, 1, 128, 240, 240, 240, 164,,, -4, 5, 4, 5, 3, 3, 2, 1, 256, 240, 240, 240, 164,,, -4, 5, 4, 5, 3, 3, 2, 1, 384, 240, 240, 240, 164,,, -4, 5, 4, 5, 3, 3, 2, 2, 128, 240, 240, 240, 164,,, -4, 5, 4, 5, 3, 3, 2, 2, 256, 240, 240, 240, 164,,, -4, 5, 4, 5, 3, 3, 2, 2, 384, 240, 240, 240, 164,,, -4, 5, 4, 5, 3, 3, 2, 3, 128, 240, 240, 240, 164,,, -4, 5, 4, 5, 3, 3, 2, 3, 256, 240, 240, 240, 164,,, -4, 5, 4, 5, 3, 3, 2, 3, 384, 240, 240, 240, 164,,, -4, 5, 4, 5, 3, 3, 3, 1, 128, 240, 240, 240, 164,,, -4, 5, 4, 5, 3, 3, 3, 1, 256, 240, 240, 240, 164,,, -4, 5, 4, 5, 3, 3, 3, 1, 384, 240, 240, 240, 164,,, -4, 5, 4, 5, 3, 3, 3, 2, 128, 240, 240, 240, 164,,, -4, 5, 4, 5, 3, 3, 3, 2, 256, 240, 240, 240, 164,,, -4, 5, 4, 5, 3, 3, 3, 2, 384, 240, 240, 240, 164,,, -4, 5, 4, 5, 3, 3, 3, 3, 128, 240, 240, 240, 164,,, -4, 5, 4, 5, 3, 3, 3, 3, 256, 240, 240, 240, 164,,, -4, 5, 4, 5, 3, 3, 3, 3, 384, 240, 240, 240, 164,,, -4, 6, 1, 1, 1, 1, 1, 1, 128, 101, 101, 69,,,, -4, 6, 1, 1, 1, 1, 1, 1, 256, 101, 101, 69,,,, -4, 6, 1, 1, 1, 1, 1, 1, 384, 101, 101, 69,,,, -4, 6, 1, 1, 2, 2, 1, 1, 128, 101, 97, 69,,,, -4, 6, 1, 1, 2, 2, 1, 1, 256, 101, 97, 69,,,, -4, 6, 1, 1, 2, 2, 1, 1, 384, 101, 97, 69,,,, -4, 6, 1, 1, 2, 2, 1, 2, 128, 101, 97, 69,,,, -4, 6, 1, 1, 2, 2, 1, 2, 256, 101, 97, 69,,,, -4, 6, 1, 1, 2, 2, 1, 2, 384, 101, 97, 69,,,, -4, 6, 1, 1, 2, 2, 2, 1, 128, 101, 97, 69,,,, -4, 6, 1, 1, 2, 2, 2, 1, 256, 101, 97, 69,,,, -4, 6, 1, 1, 2, 2, 2, 1, 384, 101, 97, 69,,,, -4, 6, 1, 1, 2, 2, 2, 2, 128, 101, 97, 69,,,, -4, 6, 1, 1, 2, 2, 2, 2, 256, 101, 97, 69,,,, -4, 6, 1, 1, 2, 2, 2, 2, 384, 101, 97, 69,,,, -4, 6, 1, 1, 3, 3, 1, 1, 128, 101, 92, 69,,,, -4, 6, 1, 1, 3, 3, 1, 1, 256, 101, 92, 69,,,, -4, 6, 1, 1, 3, 3, 1, 1, 384, 101, 92, 69,,,, -4, 6, 1, 1, 3, 3, 1, 2, 128, 101, 92, 69,,,, -4, 6, 1, 1, 3, 3, 1, 2, 256, 101, 92, 69,,,, -4, 6, 1, 1, 3, 3, 1, 2, 384, 101, 92, 69,,,, -4, 6, 1, 1, 3, 3, 1, 3, 128, 101, 92, 69,,,, -4, 6, 1, 1, 3, 3, 1, 3, 256, 101, 92, 69,,,, -4, 6, 1, 1, 3, 3, 1, 3, 384, 101, 92, 69,,,, -4, 6, 1, 1, 3, 3, 2, 1, 128, 101, 92, 69,,,, -4, 6, 1, 1, 3, 3, 2, 1, 256, 101, 92, 69,,,, -4, 6, 1, 1, 3, 3, 2, 1, 384, 101, 92, 69,,,, -4, 6, 1, 1, 3, 3, 2, 2, 128, 101, 92, 69,,,, -4, 6, 1, 1, 3, 3, 2, 2, 256, 101, 92, 69,,,, -4, 6, 1, 1, 3, 3, 2, 2, 384, 101, 92, 69,,,, -4, 6, 1, 1, 3, 3, 2, 3, 128, 101, 92, 69,,,, -4, 6, 1, 1, 3, 3, 2, 3, 256, 101, 92, 69,,,, -4, 6, 1, 1, 3, 3, 2, 3, 384, 101, 92, 69,,,, -4, 6, 1, 1, 3, 3, 3, 1, 128, 101, 92, 69,,,, -4, 6, 1, 1, 3, 3, 3, 1, 256, 101, 92, 69,,,, -4, 6, 1, 1, 3, 3, 3, 1, 384, 101, 92, 69,,,, -4, 6, 1, 1, 3, 3, 3, 2, 128, 101, 92, 69,,,, -4, 6, 1, 1, 3, 3, 3, 2, 256, 101, 92, 69,,,, -4, 6, 1, 1, 3, 3, 3, 2, 384, 101, 92, 69,,,, -4, 6, 1, 1, 3, 3, 3, 3, 128, 101, 92, 69,,,, -4, 6, 1, 1, 3, 3, 3, 3, 256, 101, 92, 69,,,, -4, 6, 1, 1, 3, 3, 3, 3, 384, 101, 92, 69,,,, -4, 6, 1, 2, 1, 1, 1, 1, 128, 197, 197, 133,,,, -4, 6, 1, 2, 1, 1, 1, 1, 256, 197, 197, 133,,,, -4, 6, 1, 2, 1, 1, 1, 1, 384, 197, 197, 133,,,, -4, 6, 1, 2, 2, 2, 1, 1, 128, 197, 189, 133,,,, -4, 6, 1, 2, 2, 2, 1, 1, 256, 197, 189, 133,,,, -4, 6, 1, 2, 2, 2, 1, 1, 384, 197, 189, 133,,,, -4, 6, 1, 2, 2, 2, 1, 2, 128, 197, 189, 133,,,, -4, 6, 1, 2, 2, 2, 1, 2, 256, 197, 189, 133,,,, -4, 6, 1, 2, 2, 2, 1, 2, 384, 197, 189, 133,,,, -4, 6, 1, 2, 2, 2, 2, 1, 128, 197, 189, 133,,,, -4, 6, 1, 2, 2, 2, 2, 1, 256, 197, 189, 133,,,, -4, 6, 1, 2, 2, 2, 2, 1, 384, 197, 189, 133,,,, -4, 6, 1, 2, 2, 2, 2, 2, 128, 197, 189, 133,,,, -4, 6, 1, 2, 2, 2, 2, 2, 256, 197, 189, 133,,,, -4, 6, 1, 2, 2, 2, 2, 2, 384, 197, 189, 133,,,, -4, 6, 1, 2, 3, 3, 1, 1, 128, 197, 179, 133,,,, -4, 6, 1, 2, 3, 3, 1, 1, 256, 197, 179, 133,,,, -4, 6, 1, 2, 3, 3, 1, 1, 384, 197, 179, 133,,,, -4, 6, 1, 2, 3, 3, 1, 2, 128, 197, 179, 133,,,, -4, 6, 1, 2, 3, 3, 1, 2, 256, 197, 179, 133,,,, -4, 6, 1, 2, 3, 3, 1, 2, 384, 197, 179, 133,,,, -4, 6, 1, 2, 3, 3, 1, 3, 128, 197, 179, 133,,,, -4, 6, 1, 2, 3, 3, 1, 3, 256, 197, 179, 133,,,, -4, 6, 1, 2, 3, 3, 1, 3, 384, 197, 179, 133,,,, -4, 6, 1, 2, 3, 3, 2, 1, 128, 197, 179, 133,,,, -4, 6, 1, 2, 3, 3, 2, 1, 256, 197, 179, 133,,,, -4, 6, 1, 2, 3, 3, 2, 1, 384, 197, 179, 133,,,, -4, 6, 1, 2, 3, 3, 2, 2, 128, 197, 179, 133,,,, -4, 6, 1, 2, 3, 3, 2, 2, 256, 197, 179, 133,,,, -4, 6, 1, 2, 3, 3, 2, 2, 384, 197, 179, 133,,,, -4, 6, 1, 2, 3, 3, 2, 3, 128, 197, 179, 133,,,, -4, 6, 1, 2, 3, 3, 2, 3, 256, 197, 179, 133,,,, -4, 6, 1, 2, 3, 3, 2, 3, 384, 197, 179, 133,,,, -4, 6, 1, 2, 3, 3, 3, 1, 128, 197, 179, 133,,,, -4, 6, 1, 2, 3, 3, 3, 1, 256, 197, 179, 133,,,, -4, 6, 1, 2, 3, 3, 3, 1, 384, 197, 179, 133,,,, -4, 6, 1, 2, 3, 3, 3, 2, 128, 197, 179, 133,,,, -4, 6, 1, 2, 3, 3, 3, 2, 256, 197, 179, 133,,,, -4, 6, 1, 2, 3, 3, 3, 2, 384, 197, 179, 133,,,, -4, 6, 1, 2, 3, 3, 3, 3, 128, 197, 179, 133,,,, -4, 6, 1, 2, 3, 3, 3, 3, 256, 197, 179, 133,,,, -4, 6, 1, 2, 3, 3, 3, 3, 384, 197, 179, 133,,,, -4, 6, 1, 3, 1, 1, 1, 1, 128, 240, 240, 197,,,, -4, 6, 1, 3, 1, 1, 1, 1, 256, 240, 240, 197,,,, -4, 6, 1, 3, 1, 1, 1, 1, 384, 240, 240, 197,,,, -4, 6, 1, 3, 2, 2, 1, 1, 128, 240, 240, 197,,,, -4, 6, 1, 3, 2, 2, 1, 1, 256, 240, 240, 197,,,, -4, 6, 1, 3, 2, 2, 1, 1, 384, 240, 240, 197,,,, -4, 6, 1, 3, 2, 2, 1, 2, 128, 240, 240, 197,,,, -4, 6, 1, 3, 2, 2, 1, 2, 256, 240, 240, 197,,,, -4, 6, 1, 3, 2, 2, 1, 2, 384, 240, 240, 197,,,, -4, 6, 1, 3, 2, 2, 2, 1, 128, 240, 240, 197,,,, -4, 6, 1, 3, 2, 2, 2, 1, 256, 240, 240, 197,,,, -4, 6, 1, 3, 2, 2, 2, 1, 384, 240, 240, 197,,,, -4, 6, 1, 3, 2, 2, 2, 2, 128, 240, 240, 197,,,, -4, 6, 1, 3, 2, 2, 2, 2, 256, 240, 240, 197,,,, -4, 6, 1, 3, 2, 2, 2, 2, 384, 240, 240, 197,,,, -4, 6, 1, 3, 3, 3, 1, 1, 128, 240, 240, 197,,,, -4, 6, 1, 3, 3, 3, 1, 1, 256, 240, 240, 197,,,, -4, 6, 1, 3, 3, 3, 1, 1, 384, 240, 240, 197,,,, -4, 6, 1, 3, 3, 3, 1, 2, 128, 240, 240, 197,,,, -4, 6, 1, 3, 3, 3, 1, 2, 256, 240, 240, 197,,,, -4, 6, 1, 3, 3, 3, 1, 2, 384, 240, 240, 197,,,, -4, 6, 1, 3, 3, 3, 1, 3, 128, 240, 240, 197,,,, -4, 6, 1, 3, 3, 3, 1, 3, 256, 240, 240, 197,,,, -4, 6, 1, 3, 3, 3, 1, 3, 384, 240, 240, 197,,,, -4, 6, 1, 3, 3, 3, 2, 1, 128, 240, 240, 197,,,, -4, 6, 1, 3, 3, 3, 2, 1, 256, 240, 240, 197,,,, -4, 6, 1, 3, 3, 3, 2, 1, 384, 240, 240, 197,,,, -4, 6, 1, 3, 3, 3, 2, 2, 128, 240, 240, 197,,,, -4, 6, 1, 3, 3, 3, 2, 2, 256, 240, 240, 197,,,, -4, 6, 1, 3, 3, 3, 2, 2, 384, 240, 240, 197,,,, -4, 6, 1, 3, 3, 3, 2, 3, 128, 240, 240, 197,,,, -4, 6, 1, 3, 3, 3, 2, 3, 256, 240, 240, 197,,,, -4, 6, 1, 3, 3, 3, 2, 3, 384, 240, 240, 197,,,, -4, 6, 1, 3, 3, 3, 3, 1, 128, 240, 240, 197,,,, -4, 6, 1, 3, 3, 3, 3, 1, 256, 240, 240, 197,,,, -4, 6, 1, 3, 3, 3, 3, 1, 384, 240, 240, 197,,,, -4, 6, 1, 3, 3, 3, 3, 2, 128, 240, 240, 197,,,, -4, 6, 1, 3, 3, 3, 3, 2, 256, 240, 240, 197,,,, -4, 6, 1, 3, 3, 3, 3, 2, 384, 240, 240, 197,,,, -4, 6, 1, 3, 3, 3, 3, 3, 128, 240, 240, 197,,,, -4, 6, 1, 3, 3, 3, 3, 3, 256, 240, 240, 197,,,, -4, 6, 1, 3, 3, 3, 3, 3, 384, 240, 240, 197,,,, -4, 6, 1, 4, 1, 1, 1, 1, 128, 240, 240, 240,,,, -4, 6, 1, 4, 1, 1, 1, 1, 256, 240, 240, 240,,,, -4, 6, 1, 4, 1, 1, 1, 1, 384, 240, 240, 240,,,, -4, 6, 1, 4, 2, 2, 1, 1, 128, 240, 240, 240,,,, -4, 6, 1, 4, 2, 2, 1, 1, 256, 240, 240, 240,,,, -4, 6, 1, 4, 2, 2, 1, 1, 384, 240, 240, 240,,,, -4, 6, 1, 4, 2, 2, 1, 2, 128, 240, 240, 240,,,, -4, 6, 1, 4, 2, 2, 1, 2, 256, 240, 240, 240,,,, -4, 6, 1, 4, 2, 2, 1, 2, 384, 240, 240, 240,,,, -4, 6, 1, 4, 2, 2, 2, 1, 128, 240, 240, 240,,,, -4, 6, 1, 4, 2, 2, 2, 1, 256, 240, 240, 240,,,, -4, 6, 1, 4, 2, 2, 2, 1, 384, 240, 240, 240,,,, -4, 6, 1, 4, 2, 2, 2, 2, 128, 240, 240, 240,,,, -4, 6, 1, 4, 2, 2, 2, 2, 256, 240, 240, 240,,,, -4, 6, 1, 4, 2, 2, 2, 2, 384, 240, 240, 240,,,, -4, 6, 1, 4, 3, 3, 1, 1, 128, 240, 240, 240,,,, -4, 6, 1, 4, 3, 3, 1, 1, 256, 240, 240, 240,,,, -4, 6, 1, 4, 3, 3, 1, 1, 384, 240, 240, 240,,,, -4, 6, 1, 4, 3, 3, 1, 2, 128, 240, 240, 240,,,, -4, 6, 1, 4, 3, 3, 1, 2, 256, 240, 240, 240,,,, -4, 6, 1, 4, 3, 3, 1, 2, 384, 240, 240, 240,,,, -4, 6, 1, 4, 3, 3, 1, 3, 128, 240, 240, 240,,,, -4, 6, 1, 4, 3, 3, 1, 3, 256, 240, 240, 240,,,, -4, 6, 1, 4, 3, 3, 1, 3, 384, 240, 240, 240,,,, -4, 6, 1, 4, 3, 3, 2, 1, 128, 240, 240, 240,,,, -4, 6, 1, 4, 3, 3, 2, 1, 256, 240, 240, 240,,,, -4, 6, 1, 4, 3, 3, 2, 1, 384, 240, 240, 240,,,, -4, 6, 1, 4, 3, 3, 2, 2, 128, 240, 240, 240,,,, -4, 6, 1, 4, 3, 3, 2, 2, 256, 240, 240, 240,,,, -4, 6, 1, 4, 3, 3, 2, 2, 384, 240, 240, 240,,,, -4, 6, 1, 4, 3, 3, 2, 3, 128, 240, 240, 240,,,, -4, 6, 1, 4, 3, 3, 2, 3, 256, 240, 240, 240,,,, -4, 6, 1, 4, 3, 3, 2, 3, 384, 240, 240, 240,,,, -4, 6, 1, 4, 3, 3, 3, 1, 128, 240, 240, 240,,,, -4, 6, 1, 4, 3, 3, 3, 1, 256, 240, 240, 240,,,, -4, 6, 1, 4, 3, 3, 3, 1, 384, 240, 240, 240,,,, -4, 6, 1, 4, 3, 3, 3, 2, 128, 240, 240, 240,,,, -4, 6, 1, 4, 3, 3, 3, 2, 256, 240, 240, 240,,,, -4, 6, 1, 4, 3, 3, 3, 2, 384, 240, 240, 240,,,, -4, 6, 1, 4, 3, 3, 3, 3, 128, 240, 240, 240,,,, -4, 6, 1, 4, 3, 3, 3, 3, 256, 240, 240, 240,,,, -4, 6, 1, 4, 3, 3, 3, 3, 384, 240, 240, 240,,,, -4, 6, 1, 5, 1, 1, 1, 1, 128, 240, 240, 240,,,, -4, 6, 1, 5, 1, 1, 1, 1, 256, 240, 240, 240,,,, -4, 6, 1, 5, 1, 1, 1, 1, 384, 240, 240, 240,,,, -4, 6, 1, 5, 2, 2, 1, 1, 128, 240, 240, 240,,,, -4, 6, 1, 5, 2, 2, 1, 1, 256, 240, 240, 240,,,, -4, 6, 1, 5, 2, 2, 1, 1, 384, 240, 240, 240,,,, -4, 6, 1, 5, 2, 2, 1, 2, 128, 240, 240, 240,,,, -4, 6, 1, 5, 2, 2, 1, 2, 256, 240, 240, 240,,,, -4, 6, 1, 5, 2, 2, 1, 2, 384, 240, 240, 240,,,, -4, 6, 1, 5, 2, 2, 2, 1, 128, 240, 240, 240,,,, -4, 6, 1, 5, 2, 2, 2, 1, 256, 240, 240, 240,,,, -4, 6, 1, 5, 2, 2, 2, 1, 384, 240, 240, 240,,,, -4, 6, 1, 5, 2, 2, 2, 2, 128, 240, 240, 240,,,, -4, 6, 1, 5, 2, 2, 2, 2, 256, 240, 240, 240,,,, -4, 6, 1, 5, 2, 2, 2, 2, 384, 240, 240, 240,,,, -4, 6, 1, 5, 3, 3, 1, 1, 128, 240, 240, 240,,,, -4, 6, 1, 5, 3, 3, 1, 1, 256, 240, 240, 240,,,, -4, 6, 1, 5, 3, 3, 1, 1, 384, 240, 240, 240,,,, -4, 6, 1, 5, 3, 3, 1, 2, 128, 240, 240, 240,,,, -4, 6, 1, 5, 3, 3, 1, 2, 256, 240, 240, 240,,,, -4, 6, 1, 5, 3, 3, 1, 2, 384, 240, 240, 240,,,, -4, 6, 1, 5, 3, 3, 1, 3, 128, 240, 240, 240,,,, -4, 6, 1, 5, 3, 3, 1, 3, 256, 240, 240, 240,,,, -4, 6, 1, 5, 3, 3, 1, 3, 384, 240, 240, 240,,,, -4, 6, 1, 5, 3, 3, 2, 1, 128, 240, 240, 240,,,, -4, 6, 1, 5, 3, 3, 2, 1, 256, 240, 240, 240,,,, -4, 6, 1, 5, 3, 3, 2, 1, 384, 240, 240, 240,,,, -4, 6, 1, 5, 3, 3, 2, 2, 128, 240, 240, 240,,,, -4, 6, 1, 5, 3, 3, 2, 2, 256, 240, 240, 240,,,, -4, 6, 1, 5, 3, 3, 2, 2, 384, 240, 240, 240,,,, -4, 6, 1, 5, 3, 3, 2, 3, 128, 240, 240, 240,,,, -4, 6, 1, 5, 3, 3, 2, 3, 256, 240, 240, 240,,,, -4, 6, 1, 5, 3, 3, 2, 3, 384, 240, 240, 240,,,, -4, 6, 1, 5, 3, 3, 3, 1, 128, 240, 240, 240,,,, -4, 6, 1, 5, 3, 3, 3, 1, 256, 240, 240, 240,,,, -4, 6, 1, 5, 3, 3, 3, 1, 384, 240, 240, 240,,,, -4, 6, 1, 5, 3, 3, 3, 2, 128, 240, 240, 240,,,, -4, 6, 1, 5, 3, 3, 3, 2, 256, 240, 240, 240,,,, -4, 6, 1, 5, 3, 3, 3, 2, 384, 240, 240, 240,,,, -4, 6, 1, 5, 3, 3, 3, 3, 128, 240, 240, 240,,,, -4, 6, 1, 5, 3, 3, 3, 3, 256, 240, 240, 240,,,, -4, 6, 1, 5, 3, 3, 3, 3, 384, 240, 240, 240,,,, -4, 6, 1, 6, 1, 1, 1, 1, 128, 240, 240, 240,,,, -4, 6, 1, 6, 1, 1, 1, 1, 256, 240, 240, 240,,,, -4, 6, 1, 6, 1, 1, 1, 1, 384, 240, 240, 240,,,, -4, 6, 1, 6, 2, 2, 1, 1, 128, 240, 240, 240,,,, -4, 6, 1, 6, 2, 2, 1, 1, 256, 240, 240, 240,,,, -4, 6, 1, 6, 2, 2, 1, 1, 384, 240, 240, 240,,,, -4, 6, 1, 6, 2, 2, 1, 2, 128, 240, 240, 240,,,, -4, 6, 1, 6, 2, 2, 1, 2, 256, 240, 240, 240,,,, -4, 6, 1, 6, 2, 2, 1, 2, 384, 240, 240, 240,,,, -4, 6, 1, 6, 2, 2, 2, 1, 128, 240, 240, 240,,,, -4, 6, 1, 6, 2, 2, 2, 1, 256, 240, 240, 240,,,, -4, 6, 1, 6, 2, 2, 2, 1, 384, 240, 240, 240,,,, -4, 6, 1, 6, 2, 2, 2, 2, 128, 240, 240, 240,,,, -4, 6, 1, 6, 2, 2, 2, 2, 256, 240, 240, 240,,,, -4, 6, 1, 6, 2, 2, 2, 2, 384, 240, 240, 240,,,, -4, 6, 1, 6, 3, 3, 1, 1, 128, 240, 240, 240,,,, -4, 6, 1, 6, 3, 3, 1, 1, 256, 240, 240, 240,,,, -4, 6, 1, 6, 3, 3, 1, 1, 384, 240, 240, 240,,,, -4, 6, 1, 6, 3, 3, 1, 2, 128, 240, 240, 240,,,, -4, 6, 1, 6, 3, 3, 1, 2, 256, 240, 240, 240,,,, -4, 6, 1, 6, 3, 3, 1, 2, 384, 240, 240, 240,,,, -4, 6, 1, 6, 3, 3, 1, 3, 128, 240, 240, 240,,,, -4, 6, 1, 6, 3, 3, 1, 3, 256, 240, 240, 240,,,, -4, 6, 1, 6, 3, 3, 1, 3, 384, 240, 240, 240,,,, -4, 6, 1, 6, 3, 3, 2, 1, 128, 240, 240, 240,,,, -4, 6, 1, 6, 3, 3, 2, 1, 256, 240, 240, 240,,,, -4, 6, 1, 6, 3, 3, 2, 1, 384, 240, 240, 240,,,, -4, 6, 1, 6, 3, 3, 2, 2, 128, 240, 240, 240,,,, -4, 6, 1, 6, 3, 3, 2, 2, 256, 240, 240, 240,,,, -4, 6, 1, 6, 3, 3, 2, 2, 384, 240, 240, 240,,,, -4, 6, 1, 6, 3, 3, 2, 3, 128, 240, 240, 240,,,, -4, 6, 1, 6, 3, 3, 2, 3, 256, 240, 240, 240,,,, -4, 6, 1, 6, 3, 3, 2, 3, 384, 240, 240, 240,,,, -4, 6, 1, 6, 3, 3, 3, 1, 128, 240, 240, 240,,,, -4, 6, 1, 6, 3, 3, 3, 1, 256, 240, 240, 240,,,, -4, 6, 1, 6, 3, 3, 3, 1, 384, 240, 240, 240,,,, -4, 6, 1, 6, 3, 3, 3, 2, 128, 240, 240, 240,,,, -4, 6, 1, 6, 3, 3, 3, 2, 256, 240, 240, 240,,,, -4, 6, 1, 6, 3, 3, 3, 2, 384, 240, 240, 240,,,, -4, 6, 1, 6, 3, 3, 3, 3, 128, 240, 240, 240,,,, -4, 6, 1, 6, 3, 3, 3, 3, 256, 240, 240, 240,,,, -4, 6, 1, 6, 3, 3, 3, 3, 384, 240, 240, 240,,,, -4, 6, 2, 1, 1, 1, 1, 1, 128, 101, 101, 69,,,, -4, 6, 2, 1, 1, 1, 1, 1, 256, 101, 101, 69,,,, -4, 6, 2, 1, 1, 1, 1, 1, 384, 101, 101, 69,,,, -4, 6, 2, 1, 2, 2, 1, 1, 128, 101, 97, 69,,,, -4, 6, 2, 1, 2, 2, 1, 1, 256, 101, 97, 69,,,, -4, 6, 2, 1, 2, 2, 1, 1, 384, 101, 97, 69,,,, -4, 6, 2, 1, 2, 2, 1, 2, 128, 101, 97, 69,,,, -4, 6, 2, 1, 2, 2, 1, 2, 256, 101, 97, 69,,,, -4, 6, 2, 1, 2, 2, 1, 2, 384, 101, 97, 69,,,, -4, 6, 2, 1, 2, 2, 2, 1, 128, 101, 97, 69,,,, -4, 6, 2, 1, 2, 2, 2, 1, 256, 101, 97, 69,,,, -4, 6, 2, 1, 2, 2, 2, 1, 384, 101, 97, 69,,,, -4, 6, 2, 1, 2, 2, 2, 2, 128, 101, 97, 69,,,, -4, 6, 2, 1, 2, 2, 2, 2, 256, 101, 97, 69,,,, -4, 6, 2, 1, 2, 2, 2, 2, 384, 101, 97, 69,,,, -4, 6, 2, 1, 3, 3, 1, 1, 128, 101, 92, 69,,,, -4, 6, 2, 1, 3, 3, 1, 1, 256, 101, 92, 69,,,, -4, 6, 2, 1, 3, 3, 1, 1, 384, 101, 92, 69,,,, -4, 6, 2, 1, 3, 3, 1, 2, 128, 101, 92, 69,,,, -4, 6, 2, 1, 3, 3, 1, 2, 256, 101, 92, 69,,,, -4, 6, 2, 1, 3, 3, 1, 2, 384, 101, 92, 69,,,, -4, 6, 2, 1, 3, 3, 1, 3, 128, 101, 92, 69,,,, -4, 6, 2, 1, 3, 3, 1, 3, 256, 101, 92, 69,,,, -4, 6, 2, 1, 3, 3, 1, 3, 384, 101, 92, 69,,,, -4, 6, 2, 1, 3, 3, 2, 1, 128, 101, 92, 69,,,, -4, 6, 2, 1, 3, 3, 2, 1, 256, 101, 92, 69,,,, -4, 6, 2, 1, 3, 3, 2, 1, 384, 101, 92, 69,,,, -4, 6, 2, 1, 3, 3, 2, 2, 128, 101, 92, 69,,,, -4, 6, 2, 1, 3, 3, 2, 2, 256, 101, 92, 69,,,, -4, 6, 2, 1, 3, 3, 2, 2, 384, 101, 92, 69,,,, -4, 6, 2, 1, 3, 3, 2, 3, 128, 101, 92, 69,,,, -4, 6, 2, 1, 3, 3, 2, 3, 256, 101, 92, 69,,,, -4, 6, 2, 1, 3, 3, 2, 3, 384, 101, 92, 69,,,, -4, 6, 2, 1, 3, 3, 3, 1, 128, 101, 92, 69,,,, -4, 6, 2, 1, 3, 3, 3, 1, 256, 101, 92, 69,,,, -4, 6, 2, 1, 3, 3, 3, 1, 384, 101, 92, 69,,,, -4, 6, 2, 1, 3, 3, 3, 2, 128, 101, 92, 69,,,, -4, 6, 2, 1, 3, 3, 3, 2, 256, 101, 92, 69,,,, -4, 6, 2, 1, 3, 3, 3, 2, 384, 101, 92, 69,,,, -4, 6, 2, 1, 3, 3, 3, 3, 128, 101, 92, 69,,,, -4, 6, 2, 1, 3, 3, 3, 3, 256, 101, 92, 69,,,, -4, 6, 2, 1, 3, 3, 3, 3, 384, 101, 92, 69,,,, -4, 6, 2, 2, 1, 1, 1, 1, 128, 197, 197, 133,,,, -4, 6, 2, 2, 1, 1, 1, 1, 256, 197, 197, 133,,,, -4, 6, 2, 2, 1, 1, 1, 1, 384, 197, 197, 133,,,, -4, 6, 2, 2, 2, 2, 1, 1, 128, 197, 189, 133,,,, -4, 6, 2, 2, 2, 2, 1, 1, 256, 197, 189, 133,,,, -4, 6, 2, 2, 2, 2, 1, 1, 384, 197, 189, 133,,,, -4, 6, 2, 2, 2, 2, 1, 2, 128, 197, 189, 133,,,, -4, 6, 2, 2, 2, 2, 1, 2, 256, 197, 189, 133,,,, -4, 6, 2, 2, 2, 2, 1, 2, 384, 197, 189, 133,,,, -4, 6, 2, 2, 2, 2, 2, 1, 128, 197, 189, 133,,,, -4, 6, 2, 2, 2, 2, 2, 1, 256, 197, 189, 133,,,, -4, 6, 2, 2, 2, 2, 2, 1, 384, 197, 189, 133,,,, -4, 6, 2, 2, 2, 2, 2, 2, 128, 197, 189, 133,,,, -4, 6, 2, 2, 2, 2, 2, 2, 256, 197, 189, 133,,,, -4, 6, 2, 2, 2, 2, 2, 2, 384, 197, 189, 133,,,, -4, 6, 2, 2, 3, 3, 1, 1, 128, 197, 179, 133,,,, -4, 6, 2, 2, 3, 3, 1, 1, 256, 197, 179, 133,,,, -4, 6, 2, 2, 3, 3, 1, 1, 384, 197, 179, 133,,,, -4, 6, 2, 2, 3, 3, 1, 2, 128, 197, 179, 133,,,, -4, 6, 2, 2, 3, 3, 1, 2, 256, 197, 179, 133,,,, -4, 6, 2, 2, 3, 3, 1, 2, 384, 197, 179, 133,,,, -4, 6, 2, 2, 3, 3, 1, 3, 128, 197, 179, 133,,,, -4, 6, 2, 2, 3, 3, 1, 3, 256, 197, 179, 133,,,, -4, 6, 2, 2, 3, 3, 1, 3, 384, 197, 179, 133,,,, -4, 6, 2, 2, 3, 3, 2, 1, 128, 197, 179, 133,,,, -4, 6, 2, 2, 3, 3, 2, 1, 256, 197, 179, 133,,,, -4, 6, 2, 2, 3, 3, 2, 1, 384, 197, 179, 133,,,, -4, 6, 2, 2, 3, 3, 2, 2, 128, 197, 179, 133,,,, -4, 6, 2, 2, 3, 3, 2, 2, 256, 197, 179, 133,,,, -4, 6, 2, 2, 3, 3, 2, 2, 384, 197, 179, 133,,,, -4, 6, 2, 2, 3, 3, 2, 3, 128, 197, 179, 133,,,, -4, 6, 2, 2, 3, 3, 2, 3, 256, 197, 179, 133,,,, -4, 6, 2, 2, 3, 3, 2, 3, 384, 197, 179, 133,,,, -4, 6, 2, 2, 3, 3, 3, 1, 128, 197, 179, 133,,,, -4, 6, 2, 2, 3, 3, 3, 1, 256, 197, 179, 133,,,, -4, 6, 2, 2, 3, 3, 3, 1, 384, 197, 179, 133,,,, -4, 6, 2, 2, 3, 3, 3, 2, 128, 197, 179, 133,,,, -4, 6, 2, 2, 3, 3, 3, 2, 256, 197, 179, 133,,,, -4, 6, 2, 2, 3, 3, 3, 2, 384, 197, 179, 133,,,, -4, 6, 2, 2, 3, 3, 3, 3, 128, 197, 179, 133,,,, -4, 6, 2, 2, 3, 3, 3, 3, 256, 197, 179, 133,,,, -4, 6, 2, 2, 3, 3, 3, 3, 384, 197, 179, 133,,,, -4, 6, 2, 3, 1, 1, 1, 1, 128, 240, 240, 197,,,, -4, 6, 2, 3, 1, 1, 1, 1, 256, 240, 240, 197,,,, -4, 6, 2, 3, 1, 1, 1, 1, 384, 240, 240, 197,,,, -4, 6, 2, 3, 2, 2, 1, 1, 128, 240, 240, 197,,,, -4, 6, 2, 3, 2, 2, 1, 1, 256, 240, 240, 197,,,, -4, 6, 2, 3, 2, 2, 1, 1, 384, 240, 240, 197,,,, -4, 6, 2, 3, 2, 2, 1, 2, 128, 240, 240, 197,,,, -4, 6, 2, 3, 2, 2, 1, 2, 256, 240, 240, 197,,,, -4, 6, 2, 3, 2, 2, 1, 2, 384, 240, 240, 197,,,, -4, 6, 2, 3, 2, 2, 2, 1, 128, 240, 240, 197,,,, -4, 6, 2, 3, 2, 2, 2, 1, 256, 240, 240, 197,,,, -4, 6, 2, 3, 2, 2, 2, 1, 384, 240, 240, 197,,,, -4, 6, 2, 3, 2, 2, 2, 2, 128, 240, 240, 197,,,, -4, 6, 2, 3, 2, 2, 2, 2, 256, 240, 240, 197,,,, -4, 6, 2, 3, 2, 2, 2, 2, 384, 240, 240, 197,,,, -4, 6, 2, 3, 3, 3, 1, 1, 128, 240, 240, 197,,,, -4, 6, 2, 3, 3, 3, 1, 1, 256, 240, 240, 197,,,, -4, 6, 2, 3, 3, 3, 1, 1, 384, 240, 240, 197,,,, -4, 6, 2, 3, 3, 3, 1, 2, 128, 240, 240, 197,,,, -4, 6, 2, 3, 3, 3, 1, 2, 256, 240, 240, 197,,,, -4, 6, 2, 3, 3, 3, 1, 2, 384, 240, 240, 197,,,, -4, 6, 2, 3, 3, 3, 1, 3, 128, 240, 240, 197,,,, -4, 6, 2, 3, 3, 3, 1, 3, 256, 240, 240, 197,,,, -4, 6, 2, 3, 3, 3, 1, 3, 384, 240, 240, 197,,,, -4, 6, 2, 3, 3, 3, 2, 1, 128, 240, 240, 197,,,, -4, 6, 2, 3, 3, 3, 2, 1, 256, 240, 240, 197,,,, -4, 6, 2, 3, 3, 3, 2, 1, 384, 240, 240, 197,,,, -4, 6, 2, 3, 3, 3, 2, 2, 128, 240, 240, 197,,,, -4, 6, 2, 3, 3, 3, 2, 2, 256, 240, 240, 197,,,, -4, 6, 2, 3, 3, 3, 2, 2, 384, 240, 240, 197,,,, -4, 6, 2, 3, 3, 3, 2, 3, 128, 240, 240, 197,,,, -4, 6, 2, 3, 3, 3, 2, 3, 256, 240, 240, 197,,,, -4, 6, 2, 3, 3, 3, 2, 3, 384, 240, 240, 197,,,, -4, 6, 2, 3, 3, 3, 3, 1, 128, 240, 240, 197,,,, -4, 6, 2, 3, 3, 3, 3, 1, 256, 240, 240, 197,,,, -4, 6, 2, 3, 3, 3, 3, 1, 384, 240, 240, 197,,,, -4, 6, 2, 3, 3, 3, 3, 2, 128, 240, 240, 197,,,, -4, 6, 2, 3, 3, 3, 3, 2, 256, 240, 240, 197,,,, -4, 6, 2, 3, 3, 3, 3, 2, 384, 240, 240, 197,,,, -4, 6, 2, 3, 3, 3, 3, 3, 128, 240, 240, 197,,,, -4, 6, 2, 3, 3, 3, 3, 3, 256, 240, 240, 197,,,, -4, 6, 2, 3, 3, 3, 3, 3, 384, 240, 240, 197,,,, -4, 6, 2, 4, 1, 1, 1, 1, 128, 240, 240, 240,,,, -4, 6, 2, 4, 1, 1, 1, 1, 256, 240, 240, 240,,,, -4, 6, 2, 4, 1, 1, 1, 1, 384, 240, 240, 240,,,, -4, 6, 2, 4, 2, 2, 1, 1, 128, 240, 240, 240,,,, -4, 6, 2, 4, 2, 2, 1, 1, 256, 240, 240, 240,,,, -4, 6, 2, 4, 2, 2, 1, 1, 384, 240, 240, 240,,,, -4, 6, 2, 4, 2, 2, 1, 2, 128, 240, 240, 240,,,, -4, 6, 2, 4, 2, 2, 1, 2, 256, 240, 240, 240,,,, -4, 6, 2, 4, 2, 2, 1, 2, 384, 240, 240, 240,,,, -4, 6, 2, 4, 2, 2, 2, 1, 128, 240, 240, 240,,,, -4, 6, 2, 4, 2, 2, 2, 1, 256, 240, 240, 240,,,, -4, 6, 2, 4, 2, 2, 2, 1, 384, 240, 240, 240,,,, -4, 6, 2, 4, 2, 2, 2, 2, 128, 240, 240, 240,,,, -4, 6, 2, 4, 2, 2, 2, 2, 256, 240, 240, 240,,,, -4, 6, 2, 4, 2, 2, 2, 2, 384, 240, 240, 240,,,, -4, 6, 2, 4, 3, 3, 1, 1, 128, 240, 240, 240,,,, -4, 6, 2, 4, 3, 3, 1, 1, 256, 240, 240, 240,,,, -4, 6, 2, 4, 3, 3, 1, 1, 384, 240, 240, 240,,,, -4, 6, 2, 4, 3, 3, 1, 2, 128, 240, 240, 240,,,, -4, 6, 2, 4, 3, 3, 1, 2, 256, 240, 240, 240,,,, -4, 6, 2, 4, 3, 3, 1, 2, 384, 240, 240, 240,,,, -4, 6, 2, 4, 3, 3, 1, 3, 128, 240, 240, 240,,,, -4, 6, 2, 4, 3, 3, 1, 3, 256, 240, 240, 240,,,, -4, 6, 2, 4, 3, 3, 1, 3, 384, 240, 240, 240,,,, -4, 6, 2, 4, 3, 3, 2, 1, 128, 240, 240, 240,,,, -4, 6, 2, 4, 3, 3, 2, 1, 256, 240, 240, 240,,,, -4, 6, 2, 4, 3, 3, 2, 1, 384, 240, 240, 240,,,, -4, 6, 2, 4, 3, 3, 2, 2, 128, 240, 240, 240,,,, -4, 6, 2, 4, 3, 3, 2, 2, 256, 240, 240, 240,,,, -4, 6, 2, 4, 3, 3, 2, 2, 384, 240, 240, 240,,,, -4, 6, 2, 4, 3, 3, 2, 3, 128, 240, 240, 240,,,, -4, 6, 2, 4, 3, 3, 2, 3, 256, 240, 240, 240,,,, -4, 6, 2, 4, 3, 3, 2, 3, 384, 240, 240, 240,,,, -4, 6, 2, 4, 3, 3, 3, 1, 128, 240, 240, 240,,,, -4, 6, 2, 4, 3, 3, 3, 1, 256, 240, 240, 240,,,, -4, 6, 2, 4, 3, 3, 3, 1, 384, 240, 240, 240,,,, -4, 6, 2, 4, 3, 3, 3, 2, 128, 240, 240, 240,,,, -4, 6, 2, 4, 3, 3, 3, 2, 256, 240, 240, 240,,,, -4, 6, 2, 4, 3, 3, 3, 2, 384, 240, 240, 240,,,, -4, 6, 2, 4, 3, 3, 3, 3, 128, 240, 240, 240,,,, -4, 6, 2, 4, 3, 3, 3, 3, 256, 240, 240, 240,,,, -4, 6, 2, 4, 3, 3, 3, 3, 384, 240, 240, 240,,,, -4, 6, 2, 5, 1, 1, 1, 1, 128, 240, 240, 240,,,, -4, 6, 2, 5, 1, 1, 1, 1, 256, 240, 240, 240,,,, -4, 6, 2, 5, 1, 1, 1, 1, 384, 240, 240, 240,,,, -4, 6, 2, 5, 2, 2, 1, 1, 128, 240, 240, 240,,,, -4, 6, 2, 5, 2, 2, 1, 1, 256, 240, 240, 240,,,, -4, 6, 2, 5, 2, 2, 1, 1, 384, 240, 240, 240,,,, -4, 6, 2, 5, 2, 2, 1, 2, 128, 240, 240, 240,,,, -4, 6, 2, 5, 2, 2, 1, 2, 256, 240, 240, 240,,,, -4, 6, 2, 5, 2, 2, 1, 2, 384, 240, 240, 240,,,, -4, 6, 2, 5, 2, 2, 2, 1, 128, 240, 240, 240,,,, -4, 6, 2, 5, 2, 2, 2, 1, 256, 240, 240, 240,,,, -4, 6, 2, 5, 2, 2, 2, 1, 384, 240, 240, 240,,,, -4, 6, 2, 5, 2, 2, 2, 2, 128, 240, 240, 240,,,, -4, 6, 2, 5, 2, 2, 2, 2, 256, 240, 240, 240,,,, -4, 6, 2, 5, 2, 2, 2, 2, 384, 240, 240, 240,,,, -4, 6, 2, 5, 3, 3, 1, 1, 128, 240, 240, 240,,,, -4, 6, 2, 5, 3, 3, 1, 1, 256, 240, 240, 240,,,, -4, 6, 2, 5, 3, 3, 1, 1, 384, 240, 240, 240,,,, -4, 6, 2, 5, 3, 3, 1, 2, 128, 240, 240, 240,,,, -4, 6, 2, 5, 3, 3, 1, 2, 256, 240, 240, 240,,,, -4, 6, 2, 5, 3, 3, 1, 2, 384, 240, 240, 240,,,, -4, 6, 2, 5, 3, 3, 1, 3, 128, 240, 240, 240,,,, -4, 6, 2, 5, 3, 3, 1, 3, 256, 240, 240, 240,,,, -4, 6, 2, 5, 3, 3, 1, 3, 384, 240, 240, 240,,,, -4, 6, 2, 5, 3, 3, 2, 1, 128, 240, 240, 240,,,, -4, 6, 2, 5, 3, 3, 2, 1, 256, 240, 240, 240,,,, -4, 6, 2, 5, 3, 3, 2, 1, 384, 240, 240, 240,,,, -4, 6, 2, 5, 3, 3, 2, 2, 128, 240, 240, 240,,,, -4, 6, 2, 5, 3, 3, 2, 2, 256, 240, 240, 240,,,, -4, 6, 2, 5, 3, 3, 2, 2, 384, 240, 240, 240,,,, -4, 6, 2, 5, 3, 3, 2, 3, 128, 240, 240, 240,,,, -4, 6, 2, 5, 3, 3, 2, 3, 256, 240, 240, 240,,,, -4, 6, 2, 5, 3, 3, 2, 3, 384, 240, 240, 240,,,, -4, 6, 2, 5, 3, 3, 3, 1, 128, 240, 240, 240,,,, -4, 6, 2, 5, 3, 3, 3, 1, 256, 240, 240, 240,,,, -4, 6, 2, 5, 3, 3, 3, 1, 384, 240, 240, 240,,,, -4, 6, 2, 5, 3, 3, 3, 2, 128, 240, 240, 240,,,, -4, 6, 2, 5, 3, 3, 3, 2, 256, 240, 240, 240,,,, -4, 6, 2, 5, 3, 3, 3, 2, 384, 240, 240, 240,,,, -4, 6, 2, 5, 3, 3, 3, 3, 128, 240, 240, 240,,,, -4, 6, 2, 5, 3, 3, 3, 3, 256, 240, 240, 240,,,, -4, 6, 2, 5, 3, 3, 3, 3, 384, 240, 240, 240,,,, -4, 6, 2, 6, 1, 1, 1, 1, 128, 240, 240, 240,,,, -4, 6, 2, 6, 1, 1, 1, 1, 256, 240, 240, 240,,,, -4, 6, 2, 6, 1, 1, 1, 1, 384, 240, 240, 240,,,, -4, 6, 2, 6, 2, 2, 1, 1, 128, 240, 240, 240,,,, -4, 6, 2, 6, 2, 2, 1, 1, 256, 240, 240, 240,,,, -4, 6, 2, 6, 2, 2, 1, 1, 384, 240, 240, 240,,,, -4, 6, 2, 6, 2, 2, 1, 2, 128, 240, 240, 240,,,, -4, 6, 2, 6, 2, 2, 1, 2, 256, 240, 240, 240,,,, -4, 6, 2, 6, 2, 2, 1, 2, 384, 240, 240, 240,,,, -4, 6, 2, 6, 2, 2, 2, 1, 128, 240, 240, 240,,,, -4, 6, 2, 6, 2, 2, 2, 1, 256, 240, 240, 240,,,, -4, 6, 2, 6, 2, 2, 2, 1, 384, 240, 240, 240,,,, -4, 6, 2, 6, 2, 2, 2, 2, 128, 240, 240, 240,,,, -4, 6, 2, 6, 2, 2, 2, 2, 256, 240, 240, 240,,,, -4, 6, 2, 6, 2, 2, 2, 2, 384, 240, 240, 240,,,, -4, 6, 2, 6, 3, 3, 1, 1, 128, 240, 240, 240,,,, -4, 6, 2, 6, 3, 3, 1, 1, 256, 240, 240, 240,,,, -4, 6, 2, 6, 3, 3, 1, 1, 384, 240, 240, 240,,,, -4, 6, 2, 6, 3, 3, 1, 2, 128, 240, 240, 240,,,, -4, 6, 2, 6, 3, 3, 1, 2, 256, 240, 240, 240,,,, -4, 6, 2, 6, 3, 3, 1, 2, 384, 240, 240, 240,,,, -4, 6, 2, 6, 3, 3, 1, 3, 128, 240, 240, 240,,,, -4, 6, 2, 6, 3, 3, 1, 3, 256, 240, 240, 240,,,, -4, 6, 2, 6, 3, 3, 1, 3, 384, 240, 240, 240,,,, -4, 6, 2, 6, 3, 3, 2, 1, 128, 240, 240, 240,,,, -4, 6, 2, 6, 3, 3, 2, 1, 256, 240, 240, 240,,,, -4, 6, 2, 6, 3, 3, 2, 1, 384, 240, 240, 240,,,, -4, 6, 2, 6, 3, 3, 2, 2, 128, 240, 240, 240,,,, -4, 6, 2, 6, 3, 3, 2, 2, 256, 240, 240, 240,,,, -4, 6, 2, 6, 3, 3, 2, 2, 384, 240, 240, 240,,,, -4, 6, 2, 6, 3, 3, 2, 3, 128, 240, 240, 240,,,, -4, 6, 2, 6, 3, 3, 2, 3, 256, 240, 240, 240,,,, -4, 6, 2, 6, 3, 3, 2, 3, 384, 240, 240, 240,,,, -4, 6, 2, 6, 3, 3, 3, 1, 128, 240, 240, 240,,,, -4, 6, 2, 6, 3, 3, 3, 1, 256, 240, 240, 240,,,, -4, 6, 2, 6, 3, 3, 3, 1, 384, 240, 240, 240,,,, -4, 6, 2, 6, 3, 3, 3, 2, 128, 240, 240, 240,,,, -4, 6, 2, 6, 3, 3, 3, 2, 256, 240, 240, 240,,,, -4, 6, 2, 6, 3, 3, 3, 2, 384, 240, 240, 240,,,, -4, 6, 2, 6, 3, 3, 3, 3, 128, 240, 240, 240,,,, -4, 6, 2, 6, 3, 3, 3, 3, 256, 240, 240, 240,,,, -4, 6, 2, 6, 3, 3, 3, 3, 384, 240, 240, 240,,,, -4, 6, 3, 1, 1, 1, 1, 1, 128, 101, 101, 69,,,, -4, 6, 3, 1, 1, 1, 1, 1, 256, 101, 101, 69,,,, -4, 6, 3, 1, 1, 1, 1, 1, 384, 101, 101, 69,,,, -4, 6, 3, 1, 2, 2, 1, 1, 128, 101, 97, 69,,,, -4, 6, 3, 1, 2, 2, 1, 1, 256, 101, 97, 69,,,, -4, 6, 3, 1, 2, 2, 1, 1, 384, 101, 97, 69,,,, -4, 6, 3, 1, 2, 2, 1, 2, 128, 101, 97, 69,,,, -4, 6, 3, 1, 2, 2, 1, 2, 256, 101, 97, 69,,,, -4, 6, 3, 1, 2, 2, 1, 2, 384, 101, 97, 69,,,, -4, 6, 3, 1, 2, 2, 2, 1, 128, 101, 97, 69,,,, -4, 6, 3, 1, 2, 2, 2, 1, 256, 101, 97, 69,,,, -4, 6, 3, 1, 2, 2, 2, 1, 384, 101, 97, 69,,,, -4, 6, 3, 1, 2, 2, 2, 2, 128, 101, 97, 69,,,, -4, 6, 3, 1, 2, 2, 2, 2, 256, 101, 97, 69,,,, -4, 6, 3, 1, 2, 2, 2, 2, 384, 101, 97, 69,,,, -4, 6, 3, 1, 3, 3, 1, 1, 128, 101, 92, 69,,,, -4, 6, 3, 1, 3, 3, 1, 1, 256, 101, 92, 69,,,, -4, 6, 3, 1, 3, 3, 1, 1, 384, 101, 92, 69,,,, -4, 6, 3, 1, 3, 3, 1, 2, 128, 101, 92, 69,,,, -4, 6, 3, 1, 3, 3, 1, 2, 256, 101, 92, 69,,,, -4, 6, 3, 1, 3, 3, 1, 2, 384, 101, 92, 69,,,, -4, 6, 3, 1, 3, 3, 1, 3, 128, 101, 92, 69,,,, -4, 6, 3, 1, 3, 3, 1, 3, 256, 101, 92, 69,,,, -4, 6, 3, 1, 3, 3, 1, 3, 384, 101, 92, 69,,,, -4, 6, 3, 1, 3, 3, 2, 1, 128, 101, 92, 69,,,, -4, 6, 3, 1, 3, 3, 2, 1, 256, 101, 92, 69,,,, -4, 6, 3, 1, 3, 3, 2, 1, 384, 101, 92, 69,,,, -4, 6, 3, 1, 3, 3, 2, 2, 128, 101, 92, 69,,,, -4, 6, 3, 1, 3, 3, 2, 2, 256, 101, 92, 69,,,, -4, 6, 3, 1, 3, 3, 2, 2, 384, 101, 92, 69,,,, -4, 6, 3, 1, 3, 3, 2, 3, 128, 101, 92, 69,,,, -4, 6, 3, 1, 3, 3, 2, 3, 256, 101, 92, 69,,,, -4, 6, 3, 1, 3, 3, 2, 3, 384, 101, 92, 69,,,, -4, 6, 3, 1, 3, 3, 3, 1, 128, 101, 92, 69,,,, -4, 6, 3, 1, 3, 3, 3, 1, 256, 101, 92, 69,,,, -4, 6, 3, 1, 3, 3, 3, 1, 384, 101, 92, 69,,,, -4, 6, 3, 1, 3, 3, 3, 2, 128, 101, 92, 69,,,, -4, 6, 3, 1, 3, 3, 3, 2, 256, 101, 92, 69,,,, -4, 6, 3, 1, 3, 3, 3, 2, 384, 101, 92, 69,,,, -4, 6, 3, 1, 3, 3, 3, 3, 128, 101, 92, 69,,,, -4, 6, 3, 1, 3, 3, 3, 3, 256, 101, 92, 69,,,, -4, 6, 3, 1, 3, 3, 3, 3, 384, 101, 92, 69,,,, -4, 6, 3, 2, 1, 1, 1, 1, 128, 197, 197, 133,,,, -4, 6, 3, 2, 1, 1, 1, 1, 256, 197, 197, 133,,,, -4, 6, 3, 2, 1, 1, 1, 1, 384, 197, 197, 133,,,, -4, 6, 3, 2, 2, 2, 1, 1, 128, 197, 189, 133,,,, -4, 6, 3, 2, 2, 2, 1, 1, 256, 197, 189, 133,,,, -4, 6, 3, 2, 2, 2, 1, 1, 384, 197, 189, 133,,,, -4, 6, 3, 2, 2, 2, 1, 2, 128, 197, 189, 133,,,, -4, 6, 3, 2, 2, 2, 1, 2, 256, 197, 189, 133,,,, -4, 6, 3, 2, 2, 2, 1, 2, 384, 197, 189, 133,,,, -4, 6, 3, 2, 2, 2, 2, 1, 128, 197, 189, 133,,,, -4, 6, 3, 2, 2, 2, 2, 1, 256, 197, 189, 133,,,, -4, 6, 3, 2, 2, 2, 2, 1, 384, 197, 189, 133,,,, -4, 6, 3, 2, 2, 2, 2, 2, 128, 197, 189, 133,,,, -4, 6, 3, 2, 2, 2, 2, 2, 256, 197, 189, 133,,,, -4, 6, 3, 2, 2, 2, 2, 2, 384, 197, 189, 133,,,, -4, 6, 3, 2, 3, 3, 1, 1, 128, 197, 179, 133,,,, -4, 6, 3, 2, 3, 3, 1, 1, 256, 197, 179, 133,,,, -4, 6, 3, 2, 3, 3, 1, 1, 384, 197, 179, 133,,,, -4, 6, 3, 2, 3, 3, 1, 2, 128, 197, 179, 133,,,, -4, 6, 3, 2, 3, 3, 1, 2, 256, 197, 179, 133,,,, -4, 6, 3, 2, 3, 3, 1, 2, 384, 197, 179, 133,,,, -4, 6, 3, 2, 3, 3, 1, 3, 128, 197, 179, 133,,,, -4, 6, 3, 2, 3, 3, 1, 3, 256, 197, 179, 133,,,, -4, 6, 3, 2, 3, 3, 1, 3, 384, 197, 179, 133,,,, -4, 6, 3, 2, 3, 3, 2, 1, 128, 197, 179, 133,,,, -4, 6, 3, 2, 3, 3, 2, 1, 256, 197, 179, 133,,,, -4, 6, 3, 2, 3, 3, 2, 1, 384, 197, 179, 133,,,, -4, 6, 3, 2, 3, 3, 2, 2, 128, 197, 179, 133,,,, -4, 6, 3, 2, 3, 3, 2, 2, 256, 197, 179, 133,,,, -4, 6, 3, 2, 3, 3, 2, 2, 384, 197, 179, 133,,,, -4, 6, 3, 2, 3, 3, 2, 3, 128, 197, 179, 133,,,, -4, 6, 3, 2, 3, 3, 2, 3, 256, 197, 179, 133,,,, -4, 6, 3, 2, 3, 3, 2, 3, 384, 197, 179, 133,,,, -4, 6, 3, 2, 3, 3, 3, 1, 128, 197, 179, 133,,,, -4, 6, 3, 2, 3, 3, 3, 1, 256, 197, 179, 133,,,, -4, 6, 3, 2, 3, 3, 3, 1, 384, 197, 179, 133,,,, -4, 6, 3, 2, 3, 3, 3, 2, 128, 197, 179, 133,,,, -4, 6, 3, 2, 3, 3, 3, 2, 256, 197, 179, 133,,,, -4, 6, 3, 2, 3, 3, 3, 2, 384, 197, 179, 133,,,, -4, 6, 3, 2, 3, 3, 3, 3, 128, 197, 179, 133,,,, -4, 6, 3, 2, 3, 3, 3, 3, 256, 197, 179, 133,,,, -4, 6, 3, 2, 3, 3, 3, 3, 384, 197, 179, 133,,,, -4, 6, 3, 3, 1, 1, 1, 1, 128, 240, 240, 197,,,, -4, 6, 3, 3, 1, 1, 1, 1, 256, 240, 240, 197,,,, -4, 6, 3, 3, 1, 1, 1, 1, 384, 240, 240, 197,,,, -4, 6, 3, 3, 2, 2, 1, 1, 128, 240, 240, 197,,,, -4, 6, 3, 3, 2, 2, 1, 1, 256, 240, 240, 197,,,, -4, 6, 3, 3, 2, 2, 1, 1, 384, 240, 240, 197,,,, -4, 6, 3, 3, 2, 2, 1, 2, 128, 240, 240, 197,,,, -4, 6, 3, 3, 2, 2, 1, 2, 256, 240, 240, 197,,,, -4, 6, 3, 3, 2, 2, 1, 2, 384, 240, 240, 197,,,, -4, 6, 3, 3, 2, 2, 2, 1, 128, 240, 240, 197,,,, -4, 6, 3, 3, 2, 2, 2, 1, 256, 240, 240, 197,,,, -4, 6, 3, 3, 2, 2, 2, 1, 384, 240, 240, 197,,,, -4, 6, 3, 3, 2, 2, 2, 2, 128, 240, 240, 197,,,, -4, 6, 3, 3, 2, 2, 2, 2, 256, 240, 240, 197,,,, -4, 6, 3, 3, 2, 2, 2, 2, 384, 240, 240, 197,,,, -4, 6, 3, 3, 3, 3, 1, 1, 128, 240, 240, 197,,,, -4, 6, 3, 3, 3, 3, 1, 1, 256, 240, 240, 197,,,, -4, 6, 3, 3, 3, 3, 1, 1, 384, 240, 240, 197,,,, -4, 6, 3, 3, 3, 3, 1, 2, 128, 240, 240, 197,,,, -4, 6, 3, 3, 3, 3, 1, 2, 256, 240, 240, 197,,,, -4, 6, 3, 3, 3, 3, 1, 2, 384, 240, 240, 197,,,, -4, 6, 3, 3, 3, 3, 1, 3, 128, 240, 240, 197,,,, -4, 6, 3, 3, 3, 3, 1, 3, 256, 240, 240, 197,,,, -4, 6, 3, 3, 3, 3, 1, 3, 384, 240, 240, 197,,,, -4, 6, 3, 3, 3, 3, 2, 1, 128, 240, 240, 197,,,, -4, 6, 3, 3, 3, 3, 2, 1, 256, 240, 240, 197,,,, -4, 6, 3, 3, 3, 3, 2, 1, 384, 240, 240, 197,,,, -4, 6, 3, 3, 3, 3, 2, 2, 128, 240, 240, 197,,,, -4, 6, 3, 3, 3, 3, 2, 2, 256, 240, 240, 197,,,, -4, 6, 3, 3, 3, 3, 2, 2, 384, 240, 240, 197,,,, -4, 6, 3, 3, 3, 3, 2, 3, 128, 240, 240, 197,,,, -4, 6, 3, 3, 3, 3, 2, 3, 256, 240, 240, 197,,,, -4, 6, 3, 3, 3, 3, 2, 3, 384, 240, 240, 197,,,, -4, 6, 3, 3, 3, 3, 3, 1, 128, 240, 240, 197,,,, -4, 6, 3, 3, 3, 3, 3, 1, 256, 240, 240, 197,,,, -4, 6, 3, 3, 3, 3, 3, 1, 384, 240, 240, 197,,,, -4, 6, 3, 3, 3, 3, 3, 2, 128, 240, 240, 197,,,, -4, 6, 3, 3, 3, 3, 3, 2, 256, 240, 240, 197,,,, -4, 6, 3, 3, 3, 3, 3, 2, 384, 240, 240, 197,,,, -4, 6, 3, 3, 3, 3, 3, 3, 128, 240, 240, 197,,,, -4, 6, 3, 3, 3, 3, 3, 3, 256, 240, 240, 197,,,, -4, 6, 3, 3, 3, 3, 3, 3, 384, 240, 240, 197,,,, -4, 6, 3, 4, 1, 1, 1, 1, 128, 240, 240, 240,,,, -4, 6, 3, 4, 1, 1, 1, 1, 256, 240, 240, 240,,,, -4, 6, 3, 4, 1, 1, 1, 1, 384, 240, 240, 240,,,, -4, 6, 3, 4, 2, 2, 1, 1, 128, 240, 240, 240,,,, -4, 6, 3, 4, 2, 2, 1, 1, 256, 240, 240, 240,,,, -4, 6, 3, 4, 2, 2, 1, 1, 384, 240, 240, 240,,,, -4, 6, 3, 4, 2, 2, 1, 2, 128, 240, 240, 240,,,, -4, 6, 3, 4, 2, 2, 1, 2, 256, 240, 240, 240,,,, -4, 6, 3, 4, 2, 2, 1, 2, 384, 240, 240, 240,,,, -4, 6, 3, 4, 2, 2, 2, 1, 128, 240, 240, 240,,,, -4, 6, 3, 4, 2, 2, 2, 1, 256, 240, 240, 240,,,, -4, 6, 3, 4, 2, 2, 2, 1, 384, 240, 240, 240,,,, -4, 6, 3, 4, 2, 2, 2, 2, 128, 240, 240, 240,,,, -4, 6, 3, 4, 2, 2, 2, 2, 256, 240, 240, 240,,,, -4, 6, 3, 4, 2, 2, 2, 2, 384, 240, 240, 240,,,, -4, 6, 3, 4, 3, 3, 1, 1, 128, 240, 240, 240,,,, -4, 6, 3, 4, 3, 3, 1, 1, 256, 240, 240, 240,,,, -4, 6, 3, 4, 3, 3, 1, 1, 384, 240, 240, 240,,,, -4, 6, 3, 4, 3, 3, 1, 2, 128, 240, 240, 240,,,, -4, 6, 3, 4, 3, 3, 1, 2, 256, 240, 240, 240,,,, -4, 6, 3, 4, 3, 3, 1, 2, 384, 240, 240, 240,,,, -4, 6, 3, 4, 3, 3, 1, 3, 128, 240, 240, 240,,,, -4, 6, 3, 4, 3, 3, 1, 3, 256, 240, 240, 240,,,, -4, 6, 3, 4, 3, 3, 1, 3, 384, 240, 240, 240,,,, -4, 6, 3, 4, 3, 3, 2, 1, 128, 240, 240, 240,,,, -4, 6, 3, 4, 3, 3, 2, 1, 256, 240, 240, 240,,,, -4, 6, 3, 4, 3, 3, 2, 1, 384, 240, 240, 240,,,, -4, 6, 3, 4, 3, 3, 2, 2, 128, 240, 240, 240,,,, -4, 6, 3, 4, 3, 3, 2, 2, 256, 240, 240, 240,,,, -4, 6, 3, 4, 3, 3, 2, 2, 384, 240, 240, 240,,,, -4, 6, 3, 4, 3, 3, 2, 3, 128, 240, 240, 240,,,, -4, 6, 3, 4, 3, 3, 2, 3, 256, 240, 240, 240,,,, -4, 6, 3, 4, 3, 3, 2, 3, 384, 240, 240, 240,,,, -4, 6, 3, 4, 3, 3, 3, 1, 128, 240, 240, 240,,,, -4, 6, 3, 4, 3, 3, 3, 1, 256, 240, 240, 240,,,, -4, 6, 3, 4, 3, 3, 3, 1, 384, 240, 240, 240,,,, -4, 6, 3, 4, 3, 3, 3, 2, 128, 240, 240, 240,,,, -4, 6, 3, 4, 3, 3, 3, 2, 256, 240, 240, 240,,,, -4, 6, 3, 4, 3, 3, 3, 2, 384, 240, 240, 240,,,, -4, 6, 3, 4, 3, 3, 3, 3, 128, 240, 240, 240,,,, -4, 6, 3, 4, 3, 3, 3, 3, 256, 240, 240, 240,,,, -4, 6, 3, 4, 3, 3, 3, 3, 384, 240, 240, 240,,,, -4, 6, 3, 5, 1, 1, 1, 1, 128, 240, 240, 240,,,, -4, 6, 3, 5, 1, 1, 1, 1, 256, 240, 240, 240,,,, -4, 6, 3, 5, 1, 1, 1, 1, 384, 240, 240, 240,,,, -4, 6, 3, 5, 2, 2, 1, 1, 128, 240, 240, 240,,,, -4, 6, 3, 5, 2, 2, 1, 1, 256, 240, 240, 240,,,, -4, 6, 3, 5, 2, 2, 1, 1, 384, 240, 240, 240,,,, -4, 6, 3, 5, 2, 2, 1, 2, 128, 240, 240, 240,,,, -4, 6, 3, 5, 2, 2, 1, 2, 256, 240, 240, 240,,,, -4, 6, 3, 5, 2, 2, 1, 2, 384, 240, 240, 240,,,, -4, 6, 3, 5, 2, 2, 2, 1, 128, 240, 240, 240,,,, -4, 6, 3, 5, 2, 2, 2, 1, 256, 240, 240, 240,,,, -4, 6, 3, 5, 2, 2, 2, 1, 384, 240, 240, 240,,,, -4, 6, 3, 5, 2, 2, 2, 2, 128, 240, 240, 240,,,, -4, 6, 3, 5, 2, 2, 2, 2, 256, 240, 240, 240,,,, -4, 6, 3, 5, 2, 2, 2, 2, 384, 240, 240, 240,,,, -4, 6, 3, 5, 3, 3, 1, 1, 128, 240, 240, 240,,,, -4, 6, 3, 5, 3, 3, 1, 1, 256, 240, 240, 240,,,, -4, 6, 3, 5, 3, 3, 1, 1, 384, 240, 240, 240,,,, -4, 6, 3, 5, 3, 3, 1, 2, 128, 240, 240, 240,,,, -4, 6, 3, 5, 3, 3, 1, 2, 256, 240, 240, 240,,,, -4, 6, 3, 5, 3, 3, 1, 2, 384, 240, 240, 240,,,, -4, 6, 3, 5, 3, 3, 1, 3, 128, 240, 240, 240,,,, -4, 6, 3, 5, 3, 3, 1, 3, 256, 240, 240, 240,,,, -4, 6, 3, 5, 3, 3, 1, 3, 384, 240, 240, 240,,,, -4, 6, 3, 5, 3, 3, 2, 1, 128, 240, 240, 240,,,, -4, 6, 3, 5, 3, 3, 2, 1, 256, 240, 240, 240,,,, -4, 6, 3, 5, 3, 3, 2, 1, 384, 240, 240, 240,,,, -4, 6, 3, 5, 3, 3, 2, 2, 128, 240, 240, 240,,,, -4, 6, 3, 5, 3, 3, 2, 2, 256, 240, 240, 240,,,, -4, 6, 3, 5, 3, 3, 2, 2, 384, 240, 240, 240,,,, -4, 6, 3, 5, 3, 3, 2, 3, 128, 240, 240, 240,,,, -4, 6, 3, 5, 3, 3, 2, 3, 256, 240, 240, 240,,,, -4, 6, 3, 5, 3, 3, 2, 3, 384, 240, 240, 240,,,, -4, 6, 3, 5, 3, 3, 3, 1, 128, 240, 240, 240,,,, -4, 6, 3, 5, 3, 3, 3, 1, 256, 240, 240, 240,,,, -4, 6, 3, 5, 3, 3, 3, 1, 384, 240, 240, 240,,,, -4, 6, 3, 5, 3, 3, 3, 2, 128, 240, 240, 240,,,, -4, 6, 3, 5, 3, 3, 3, 2, 256, 240, 240, 240,,,, -4, 6, 3, 5, 3, 3, 3, 2, 384, 240, 240, 240,,,, -4, 6, 3, 5, 3, 3, 3, 3, 128, 240, 240, 240,,,, -4, 6, 3, 5, 3, 3, 3, 3, 256, 240, 240, 240,,,, -4, 6, 3, 5, 3, 3, 3, 3, 384, 240, 240, 240,,,, -4, 6, 3, 6, 1, 1, 1, 1, 128, 240, 240, 240,,,, -4, 6, 3, 6, 1, 1, 1, 1, 256, 240, 240, 240,,,, -4, 6, 3, 6, 1, 1, 1, 1, 384, 240, 240, 240,,,, -4, 6, 3, 6, 2, 2, 1, 1, 128, 240, 240, 240,,,, -4, 6, 3, 6, 2, 2, 1, 1, 256, 240, 240, 240,,,, -4, 6, 3, 6, 2, 2, 1, 1, 384, 240, 240, 240,,,, -4, 6, 3, 6, 2, 2, 1, 2, 128, 240, 240, 240,,,, -4, 6, 3, 6, 2, 2, 1, 2, 256, 240, 240, 240,,,, -4, 6, 3, 6, 2, 2, 1, 2, 384, 240, 240, 240,,,, -4, 6, 3, 6, 2, 2, 2, 1, 128, 240, 240, 240,,,, -4, 6, 3, 6, 2, 2, 2, 1, 256, 240, 240, 240,,,, -4, 6, 3, 6, 2, 2, 2, 1, 384, 240, 240, 240,,,, -4, 6, 3, 6, 2, 2, 2, 2, 128, 240, 240, 240,,,, -4, 6, 3, 6, 2, 2, 2, 2, 256, 240, 240, 240,,,, -4, 6, 3, 6, 2, 2, 2, 2, 384, 240, 240, 240,,,, -4, 6, 3, 6, 3, 3, 1, 1, 128, 240, 240, 240,,,, -4, 6, 3, 6, 3, 3, 1, 1, 256, 240, 240, 240,,,, -4, 6, 3, 6, 3, 3, 1, 1, 384, 240, 240, 240,,,, -4, 6, 3, 6, 3, 3, 1, 2, 128, 240, 240, 240,,,, -4, 6, 3, 6, 3, 3, 1, 2, 256, 240, 240, 240,,,, -4, 6, 3, 6, 3, 3, 1, 2, 384, 240, 240, 240,,,, -4, 6, 3, 6, 3, 3, 1, 3, 128, 240, 240, 240,,,, -4, 6, 3, 6, 3, 3, 1, 3, 256, 240, 240, 240,,,, -4, 6, 3, 6, 3, 3, 1, 3, 384, 240, 240, 240,,,, -4, 6, 3, 6, 3, 3, 2, 1, 128, 240, 240, 240,,,, -4, 6, 3, 6, 3, 3, 2, 1, 256, 240, 240, 240,,,, -4, 6, 3, 6, 3, 3, 2, 1, 384, 240, 240, 240,,,, -4, 6, 3, 6, 3, 3, 2, 2, 128, 240, 240, 240,,,, -4, 6, 3, 6, 3, 3, 2, 2, 256, 240, 240, 240,,,, -4, 6, 3, 6, 3, 3, 2, 2, 384, 240, 240, 240,,,, -4, 6, 3, 6, 3, 3, 2, 3, 128, 240, 240, 240,,,, -4, 6, 3, 6, 3, 3, 2, 3, 256, 240, 240, 240,,,, -4, 6, 3, 6, 3, 3, 2, 3, 384, 240, 240, 240,,,, -4, 6, 3, 6, 3, 3, 3, 1, 128, 240, 240, 240,,,, -4, 6, 3, 6, 3, 3, 3, 1, 256, 240, 240, 240,,,, -4, 6, 3, 6, 3, 3, 3, 1, 384, 240, 240, 240,,,, -4, 6, 3, 6, 3, 3, 3, 2, 128, 240, 240, 240,,,, -4, 6, 3, 6, 3, 3, 3, 2, 256, 240, 240, 240,,,, -4, 6, 3, 6, 3, 3, 3, 2, 384, 240, 240, 240,,,, -4, 6, 3, 6, 3, 3, 3, 3, 128, 240, 240, 240,,,, -4, 6, 3, 6, 3, 3, 3, 3, 256, 240, 240, 240,,,, -4, 6, 3, 6, 3, 3, 3, 3, 384, 240, 240, 240,,,, -4, 6, 4, 1, 1, 1, 1, 1, 128, 101, 101, 69,,,, -4, 6, 4, 1, 1, 1, 1, 1, 256, 101, 101, 69,,,, -4, 6, 4, 1, 1, 1, 1, 1, 384, 101, 101, 69,,,, -4, 6, 4, 1, 2, 2, 1, 1, 128, 101, 97, 69,,,, -4, 6, 4, 1, 2, 2, 1, 1, 256, 101, 97, 69,,,, -4, 6, 4, 1, 2, 2, 1, 1, 384, 101, 97, 69,,,, -4, 6, 4, 1, 2, 2, 1, 2, 128, 101, 97, 69,,,, -4, 6, 4, 1, 2, 2, 1, 2, 256, 101, 97, 69,,,, -4, 6, 4, 1, 2, 2, 1, 2, 384, 101, 97, 69,,,, -4, 6, 4, 1, 2, 2, 2, 1, 128, 101, 97, 69,,,, -4, 6, 4, 1, 2, 2, 2, 1, 256, 101, 97, 69,,,, -4, 6, 4, 1, 2, 2, 2, 1, 384, 101, 97, 69,,,, -4, 6, 4, 1, 2, 2, 2, 2, 128, 101, 97, 69,,,, -4, 6, 4, 1, 2, 2, 2, 2, 256, 101, 97, 69,,,, -4, 6, 4, 1, 2, 2, 2, 2, 384, 101, 97, 69,,,, -4, 6, 4, 1, 3, 3, 1, 1, 128, 101, 92, 69,,,, -4, 6, 4, 1, 3, 3, 1, 1, 256, 101, 92, 69,,,, -4, 6, 4, 1, 3, 3, 1, 1, 384, 101, 92, 69,,,, -4, 6, 4, 1, 3, 3, 1, 2, 128, 101, 92, 69,,,, -4, 6, 4, 1, 3, 3, 1, 2, 256, 101, 92, 69,,,, -4, 6, 4, 1, 3, 3, 1, 2, 384, 101, 92, 69,,,, -4, 6, 4, 1, 3, 3, 1, 3, 128, 101, 92, 69,,,, -4, 6, 4, 1, 3, 3, 1, 3, 256, 101, 92, 69,,,, -4, 6, 4, 1, 3, 3, 1, 3, 384, 101, 92, 69,,,, -4, 6, 4, 1, 3, 3, 2, 1, 128, 101, 92, 69,,,, -4, 6, 4, 1, 3, 3, 2, 1, 256, 101, 92, 69,,,, -4, 6, 4, 1, 3, 3, 2, 1, 384, 101, 92, 69,,,, -4, 6, 4, 1, 3, 3, 2, 2, 128, 101, 92, 69,,,, -4, 6, 4, 1, 3, 3, 2, 2, 256, 101, 92, 69,,,, -4, 6, 4, 1, 3, 3, 2, 2, 384, 101, 92, 69,,,, -4, 6, 4, 1, 3, 3, 2, 3, 128, 101, 92, 69,,,, -4, 6, 4, 1, 3, 3, 2, 3, 256, 101, 92, 69,,,, -4, 6, 4, 1, 3, 3, 2, 3, 384, 101, 92, 69,,,, -4, 6, 4, 1, 3, 3, 3, 1, 128, 101, 92, 69,,,, -4, 6, 4, 1, 3, 3, 3, 1, 256, 101, 92, 69,,,, -4, 6, 4, 1, 3, 3, 3, 1, 384, 101, 92, 69,,,, -4, 6, 4, 1, 3, 3, 3, 2, 128, 101, 92, 69,,,, -4, 6, 4, 1, 3, 3, 3, 2, 256, 101, 92, 69,,,, -4, 6, 4, 1, 3, 3, 3, 2, 384, 101, 92, 69,,,, -4, 6, 4, 1, 3, 3, 3, 3, 128, 101, 92, 69,,,, -4, 6, 4, 1, 3, 3, 3, 3, 256, 101, 92, 69,,,, -4, 6, 4, 1, 3, 3, 3, 3, 384, 101, 92, 69,,,, -4, 6, 4, 2, 1, 1, 1, 1, 128, 197, 197, 133,,,, -4, 6, 4, 2, 1, 1, 1, 1, 256, 197, 197, 133,,,, -4, 6, 4, 2, 1, 1, 1, 1, 384, 197, 197, 133,,,, -4, 6, 4, 2, 2, 2, 1, 1, 128, 197, 189, 133,,,, -4, 6, 4, 2, 2, 2, 1, 1, 256, 197, 189, 133,,,, -4, 6, 4, 2, 2, 2, 1, 1, 384, 197, 189, 133,,,, -4, 6, 4, 2, 2, 2, 1, 2, 128, 197, 189, 133,,,, -4, 6, 4, 2, 2, 2, 1, 2, 256, 197, 189, 133,,,, -4, 6, 4, 2, 2, 2, 1, 2, 384, 197, 189, 133,,,, -4, 6, 4, 2, 2, 2, 2, 1, 128, 197, 189, 133,,,, -4, 6, 4, 2, 2, 2, 2, 1, 256, 197, 189, 133,,,, -4, 6, 4, 2, 2, 2, 2, 1, 384, 197, 189, 133,,,, -4, 6, 4, 2, 2, 2, 2, 2, 128, 197, 189, 133,,,, -4, 6, 4, 2, 2, 2, 2, 2, 256, 197, 189, 133,,,, -4, 6, 4, 2, 2, 2, 2, 2, 384, 197, 189, 133,,,, -4, 6, 4, 2, 3, 3, 1, 1, 128, 197, 179, 133,,,, -4, 6, 4, 2, 3, 3, 1, 1, 256, 197, 179, 133,,,, -4, 6, 4, 2, 3, 3, 1, 1, 384, 197, 179, 133,,,, -4, 6, 4, 2, 3, 3, 1, 2, 128, 197, 179, 133,,,, -4, 6, 4, 2, 3, 3, 1, 2, 256, 197, 179, 133,,,, -4, 6, 4, 2, 3, 3, 1, 2, 384, 197, 179, 133,,,, -4, 6, 4, 2, 3, 3, 1, 3, 128, 197, 179, 133,,,, -4, 6, 4, 2, 3, 3, 1, 3, 256, 197, 179, 133,,,, -4, 6, 4, 2, 3, 3, 1, 3, 384, 197, 179, 133,,,, -4, 6, 4, 2, 3, 3, 2, 1, 128, 197, 179, 133,,,, -4, 6, 4, 2, 3, 3, 2, 1, 256, 197, 179, 133,,,, -4, 6, 4, 2, 3, 3, 2, 1, 384, 197, 179, 133,,,, -4, 6, 4, 2, 3, 3, 2, 2, 128, 197, 179, 133,,,, -4, 6, 4, 2, 3, 3, 2, 2, 256, 197, 179, 133,,,, -4, 6, 4, 2, 3, 3, 2, 2, 384, 197, 179, 133,,,, -4, 6, 4, 2, 3, 3, 2, 3, 128, 197, 179, 133,,,, -4, 6, 4, 2, 3, 3, 2, 3, 256, 197, 179, 133,,,, -4, 6, 4, 2, 3, 3, 2, 3, 384, 197, 179, 133,,,, -4, 6, 4, 2, 3, 3, 3, 1, 128, 197, 179, 133,,,, -4, 6, 4, 2, 3, 3, 3, 1, 256, 197, 179, 133,,,, -4, 6, 4, 2, 3, 3, 3, 1, 384, 197, 179, 133,,,, -4, 6, 4, 2, 3, 3, 3, 2, 128, 197, 179, 133,,,, -4, 6, 4, 2, 3, 3, 3, 2, 256, 197, 179, 133,,,, -4, 6, 4, 2, 3, 3, 3, 2, 384, 197, 179, 133,,,, -4, 6, 4, 2, 3, 3, 3, 3, 128, 197, 179, 133,,,, -4, 6, 4, 2, 3, 3, 3, 3, 256, 197, 179, 133,,,, -4, 6, 4, 2, 3, 3, 3, 3, 384, 197, 179, 133,,,, -4, 6, 4, 3, 1, 1, 1, 1, 128, 240, 240, 197,,,, -4, 6, 4, 3, 1, 1, 1, 1, 256, 240, 240, 197,,,, -4, 6, 4, 3, 1, 1, 1, 1, 384, 240, 240, 197,,,, -4, 6, 4, 3, 2, 2, 1, 1, 128, 240, 240, 197,,,, -4, 6, 4, 3, 2, 2, 1, 1, 256, 240, 240, 197,,,, -4, 6, 4, 3, 2, 2, 1, 1, 384, 240, 240, 197,,,, -4, 6, 4, 3, 2, 2, 1, 2, 128, 240, 240, 197,,,, -4, 6, 4, 3, 2, 2, 1, 2, 256, 240, 240, 197,,,, -4, 6, 4, 3, 2, 2, 1, 2, 384, 240, 240, 197,,,, -4, 6, 4, 3, 2, 2, 2, 1, 128, 240, 240, 197,,,, -4, 6, 4, 3, 2, 2, 2, 1, 256, 240, 240, 197,,,, -4, 6, 4, 3, 2, 2, 2, 1, 384, 240, 240, 197,,,, -4, 6, 4, 3, 2, 2, 2, 2, 128, 240, 240, 197,,,, -4, 6, 4, 3, 2, 2, 2, 2, 256, 240, 240, 197,,,, -4, 6, 4, 3, 2, 2, 2, 2, 384, 240, 240, 197,,,, -4, 6, 4, 3, 3, 3, 1, 1, 128, 240, 240, 197,,,, -4, 6, 4, 3, 3, 3, 1, 1, 256, 240, 240, 197,,,, -4, 6, 4, 3, 3, 3, 1, 1, 384, 240, 240, 197,,,, -4, 6, 4, 3, 3, 3, 1, 2, 128, 240, 240, 197,,,, -4, 6, 4, 3, 3, 3, 1, 2, 256, 240, 240, 197,,,, -4, 6, 4, 3, 3, 3, 1, 2, 384, 240, 240, 197,,,, -4, 6, 4, 3, 3, 3, 1, 3, 128, 240, 240, 197,,,, -4, 6, 4, 3, 3, 3, 1, 3, 256, 240, 240, 197,,,, -4, 6, 4, 3, 3, 3, 1, 3, 384, 240, 240, 197,,,, -4, 6, 4, 3, 3, 3, 2, 1, 128, 240, 240, 197,,,, -4, 6, 4, 3, 3, 3, 2, 1, 256, 240, 240, 197,,,, -4, 6, 4, 3, 3, 3, 2, 1, 384, 240, 240, 197,,,, -4, 6, 4, 3, 3, 3, 2, 2, 128, 240, 240, 197,,,, -4, 6, 4, 3, 3, 3, 2, 2, 256, 240, 240, 197,,,, -4, 6, 4, 3, 3, 3, 2, 2, 384, 240, 240, 197,,,, -4, 6, 4, 3, 3, 3, 2, 3, 128, 240, 240, 197,,,, -4, 6, 4, 3, 3, 3, 2, 3, 256, 240, 240, 197,,,, -4, 6, 4, 3, 3, 3, 2, 3, 384, 240, 240, 197,,,, -4, 6, 4, 3, 3, 3, 3, 1, 128, 240, 240, 197,,,, -4, 6, 4, 3, 3, 3, 3, 1, 256, 240, 240, 197,,,, -4, 6, 4, 3, 3, 3, 3, 1, 384, 240, 240, 197,,,, -4, 6, 4, 3, 3, 3, 3, 2, 128, 240, 240, 197,,,, -4, 6, 4, 3, 3, 3, 3, 2, 256, 240, 240, 197,,,, -4, 6, 4, 3, 3, 3, 3, 2, 384, 240, 240, 197,,,, -4, 6, 4, 3, 3, 3, 3, 3, 128, 240, 240, 197,,,, -4, 6, 4, 3, 3, 3, 3, 3, 256, 240, 240, 197,,,, -4, 6, 4, 3, 3, 3, 3, 3, 384, 240, 240, 197,,,, -4, 6, 4, 4, 1, 1, 1, 1, 128, 240, 240, 240,,,, -4, 6, 4, 4, 1, 1, 1, 1, 256, 240, 240, 240,,,, -4, 6, 4, 4, 1, 1, 1, 1, 384, 240, 240, 240,,,, -4, 6, 4, 4, 2, 2, 1, 1, 128, 240, 240, 240,,,, -4, 6, 4, 4, 2, 2, 1, 1, 256, 240, 240, 240,,,, -4, 6, 4, 4, 2, 2, 1, 1, 384, 240, 240, 240,,,, -4, 6, 4, 4, 2, 2, 1, 2, 128, 240, 240, 240,,,, -4, 6, 4, 4, 2, 2, 1, 2, 256, 240, 240, 240,,,, -4, 6, 4, 4, 2, 2, 1, 2, 384, 240, 240, 240,,,, -4, 6, 4, 4, 2, 2, 2, 1, 128, 240, 240, 240,,,, -4, 6, 4, 4, 2, 2, 2, 1, 256, 240, 240, 240,,,, -4, 6, 4, 4, 2, 2, 2, 1, 384, 240, 240, 240,,,, -4, 6, 4, 4, 2, 2, 2, 2, 128, 240, 240, 240,,,, -4, 6, 4, 4, 2, 2, 2, 2, 256, 240, 240, 240,,,, -4, 6, 4, 4, 2, 2, 2, 2, 384, 240, 240, 240,,,, -4, 6, 4, 4, 3, 3, 1, 1, 128, 240, 240, 240,,,, -4, 6, 4, 4, 3, 3, 1, 1, 256, 240, 240, 240,,,, -4, 6, 4, 4, 3, 3, 1, 1, 384, 240, 240, 240,,,, -4, 6, 4, 4, 3, 3, 1, 2, 128, 240, 240, 240,,,, -4, 6, 4, 4, 3, 3, 1, 2, 256, 240, 240, 240,,,, -4, 6, 4, 4, 3, 3, 1, 2, 384, 240, 240, 240,,,, -4, 6, 4, 4, 3, 3, 1, 3, 128, 240, 240, 240,,,, -4, 6, 4, 4, 3, 3, 1, 3, 256, 240, 240, 240,,,, -4, 6, 4, 4, 3, 3, 1, 3, 384, 240, 240, 240,,,, -4, 6, 4, 4, 3, 3, 2, 1, 128, 240, 240, 240,,,, -4, 6, 4, 4, 3, 3, 2, 1, 256, 240, 240, 240,,,, -4, 6, 4, 4, 3, 3, 2, 1, 384, 240, 240, 240,,,, -4, 6, 4, 4, 3, 3, 2, 2, 128, 240, 240, 240,,,, -4, 6, 4, 4, 3, 3, 2, 2, 256, 240, 240, 240,,,, -4, 6, 4, 4, 3, 3, 2, 2, 384, 240, 240, 240,,,, -4, 6, 4, 4, 3, 3, 2, 3, 128, 240, 240, 240,,,, -4, 6, 4, 4, 3, 3, 2, 3, 256, 240, 240, 240,,,, -4, 6, 4, 4, 3, 3, 2, 3, 384, 240, 240, 240,,,, -4, 6, 4, 4, 3, 3, 3, 1, 128, 240, 240, 240,,,, -4, 6, 4, 4, 3, 3, 3, 1, 256, 240, 240, 240,,,, -4, 6, 4, 4, 3, 3, 3, 1, 384, 240, 240, 240,,,, -4, 6, 4, 4, 3, 3, 3, 2, 128, 240, 240, 240,,,, -4, 6, 4, 4, 3, 3, 3, 2, 256, 240, 240, 240,,,, -4, 6, 4, 4, 3, 3, 3, 2, 384, 240, 240, 240,,,, -4, 6, 4, 4, 3, 3, 3, 3, 128, 240, 240, 240,,,, -4, 6, 4, 4, 3, 3, 3, 3, 256, 240, 240, 240,,,, -4, 6, 4, 4, 3, 3, 3, 3, 384, 240, 240, 240,,,, -4, 6, 4, 5, 1, 1, 1, 1, 128, 240, 240, 240,,,, -4, 6, 4, 5, 1, 1, 1, 1, 256, 240, 240, 240,,,, -4, 6, 4, 5, 1, 1, 1, 1, 384, 240, 240, 240,,,, -4, 6, 4, 5, 2, 2, 1, 1, 128, 240, 240, 240,,,, -4, 6, 4, 5, 2, 2, 1, 1, 256, 240, 240, 240,,,, -4, 6, 4, 5, 2, 2, 1, 1, 384, 240, 240, 240,,,, -4, 6, 4, 5, 2, 2, 1, 2, 128, 240, 240, 240,,,, -4, 6, 4, 5, 2, 2, 1, 2, 256, 240, 240, 240,,,, -4, 6, 4, 5, 2, 2, 1, 2, 384, 240, 240, 240,,,, -4, 6, 4, 5, 2, 2, 2, 1, 128, 240, 240, 240,,,, -4, 6, 4, 5, 2, 2, 2, 1, 256, 240, 240, 240,,,, -4, 6, 4, 5, 2, 2, 2, 1, 384, 240, 240, 240,,,, -4, 6, 4, 5, 2, 2, 2, 2, 128, 240, 240, 240,,,, -4, 6, 4, 5, 2, 2, 2, 2, 256, 240, 240, 240,,,, -4, 6, 4, 5, 2, 2, 2, 2, 384, 240, 240, 240,,,, -4, 6, 4, 5, 3, 3, 1, 1, 128, 240, 240, 240,,,, -4, 6, 4, 5, 3, 3, 1, 1, 256, 240, 240, 240,,,, -4, 6, 4, 5, 3, 3, 1, 1, 384, 240, 240, 240,,,, -4, 6, 4, 5, 3, 3, 1, 2, 128, 240, 240, 240,,,, -4, 6, 4, 5, 3, 3, 1, 2, 256, 240, 240, 240,,,, -4, 6, 4, 5, 3, 3, 1, 2, 384, 240, 240, 240,,,, -4, 6, 4, 5, 3, 3, 1, 3, 128, 240, 240, 240,,,, -4, 6, 4, 5, 3, 3, 1, 3, 256, 240, 240, 240,,,, -4, 6, 4, 5, 3, 3, 1, 3, 384, 240, 240, 240,,,, -4, 6, 4, 5, 3, 3, 2, 1, 128, 240, 240, 240,,,, -4, 6, 4, 5, 3, 3, 2, 1, 256, 240, 240, 240,,,, -4, 6, 4, 5, 3, 3, 2, 1, 384, 240, 240, 240,,,, -4, 6, 4, 5, 3, 3, 2, 2, 128, 240, 240, 240,,,, -4, 6, 4, 5, 3, 3, 2, 2, 256, 240, 240, 240,,,, -4, 6, 4, 5, 3, 3, 2, 2, 384, 240, 240, 240,,,, -4, 6, 4, 5, 3, 3, 2, 3, 128, 240, 240, 240,,,, -4, 6, 4, 5, 3, 3, 2, 3, 256, 240, 240, 240,,,, -4, 6, 4, 5, 3, 3, 2, 3, 384, 240, 240, 240,,,, -4, 6, 4, 5, 3, 3, 3, 1, 128, 240, 240, 240,,,, -4, 6, 4, 5, 3, 3, 3, 1, 256, 240, 240, 240,,,, -4, 6, 4, 5, 3, 3, 3, 1, 384, 240, 240, 240,,,, -4, 6, 4, 5, 3, 3, 3, 2, 128, 240, 240, 240,,,, -4, 6, 4, 5, 3, 3, 3, 2, 256, 240, 240, 240,,,, -4, 6, 4, 5, 3, 3, 3, 2, 384, 240, 240, 240,,,, -4, 6, 4, 5, 3, 3, 3, 3, 128, 240, 240, 240,,,, -4, 6, 4, 5, 3, 3, 3, 3, 256, 240, 240, 240,,,, -4, 6, 4, 5, 3, 3, 3, 3, 384, 240, 240, 240,,,, -4, 6, 4, 6, 1, 1, 1, 1, 128, 240, 240, 240,,,, -4, 6, 4, 6, 1, 1, 1, 1, 256, 240, 240, 240,,,, -4, 6, 4, 6, 1, 1, 1, 1, 384, 240, 240, 240,,,, -4, 6, 4, 6, 2, 2, 1, 1, 128, 240, 240, 240,,,, -4, 6, 4, 6, 2, 2, 1, 1, 256, 240, 240, 240,,,, -4, 6, 4, 6, 2, 2, 1, 1, 384, 240, 240, 240,,,, -4, 6, 4, 6, 2, 2, 1, 2, 128, 240, 240, 240,,,, -4, 6, 4, 6, 2, 2, 1, 2, 256, 240, 240, 240,,,, -4, 6, 4, 6, 2, 2, 1, 2, 384, 240, 240, 240,,,, -4, 6, 4, 6, 2, 2, 2, 1, 128, 240, 240, 240,,,, -4, 6, 4, 6, 2, 2, 2, 1, 256, 240, 240, 240,,,, -4, 6, 4, 6, 2, 2, 2, 1, 384, 240, 240, 240,,,, -4, 6, 4, 6, 2, 2, 2, 2, 128, 240, 240, 240,,,, -4, 6, 4, 6, 2, 2, 2, 2, 256, 240, 240, 240,,,, -4, 6, 4, 6, 2, 2, 2, 2, 384, 240, 240, 240,,,, -4, 6, 4, 6, 3, 3, 1, 1, 128, 240, 240, 240,,,, -4, 6, 4, 6, 3, 3, 1, 1, 256, 240, 240, 240,,,, -4, 6, 4, 6, 3, 3, 1, 1, 384, 240, 240, 240,,,, -4, 6, 4, 6, 3, 3, 1, 2, 128, 240, 240, 240,,,, -4, 6, 4, 6, 3, 3, 1, 2, 256, 240, 240, 240,,,, -4, 6, 4, 6, 3, 3, 1, 2, 384, 240, 240, 240,,,, -4, 6, 4, 6, 3, 3, 1, 3, 128, 240, 240, 240,,,, -4, 6, 4, 6, 3, 3, 1, 3, 256, 240, 240, 240,,,, -4, 6, 4, 6, 3, 3, 1, 3, 384, 240, 240, 240,,,, -4, 6, 4, 6, 3, 3, 2, 1, 128, 240, 240, 240,,,, -4, 6, 4, 6, 3, 3, 2, 1, 256, 240, 240, 240,,,, -4, 6, 4, 6, 3, 3, 2, 1, 384, 240, 240, 240,,,, -4, 6, 4, 6, 3, 3, 2, 2, 128, 240, 240, 240,,,, -4, 6, 4, 6, 3, 3, 2, 2, 256, 240, 240, 240,,,, -4, 6, 4, 6, 3, 3, 2, 2, 384, 240, 240, 240,,,, -4, 6, 4, 6, 3, 3, 2, 3, 128, 240, 240, 240,,,, -4, 6, 4, 6, 3, 3, 2, 3, 256, 240, 240, 240,,,, -4, 6, 4, 6, 3, 3, 2, 3, 384, 240, 240, 240,,,, -4, 6, 4, 6, 3, 3, 3, 1, 128, 240, 240, 240,,,, -4, 6, 4, 6, 3, 3, 3, 1, 256, 240, 240, 240,,,, -4, 6, 4, 6, 3, 3, 3, 1, 384, 240, 240, 240,,,, -4, 6, 4, 6, 3, 3, 3, 2, 128, 240, 240, 240,,,, -4, 6, 4, 6, 3, 3, 3, 2, 256, 240, 240, 240,,,, -4, 6, 4, 6, 3, 3, 3, 2, 384, 240, 240, 240,,,, -4, 6, 4, 6, 3, 3, 3, 3, 128, 240, 240, 240,,,, -4, 6, 4, 6, 3, 3, 3, 3, 256, 240, 240, 240,,,, -4, 6, 4, 6, 3, 3, 3, 3, 384, 240, 240, 240,,,, -4, 7, 1, 1, 1, 1, 1, 1, 128, 102, 102, 70,,,, -4, 7, 1, 1, 1, 1, 1, 1, 256, 102, 102, 70,,,, -4, 7, 1, 1, 1, 1, 1, 1, 384, 102, 102, 70,,,, -4, 7, 1, 1, 2, 2, 1, 1, 128, 102, 94, 69,,,, -4, 7, 1, 1, 2, 2, 1, 1, 256, 102, 94, 69,,,, -4, 7, 1, 1, 2, 2, 1, 1, 384, 102, 94, 69,,,, -4, 7, 1, 1, 2, 2, 1, 2, 128, 102, 94, 69,,,, -4, 7, 1, 1, 2, 2, 1, 2, 256, 102, 94, 69,,,, -4, 7, 1, 1, 2, 2, 1, 2, 384, 102, 94, 69,,,, -4, 7, 1, 1, 2, 2, 2, 1, 128, 102, 94, 69,,,, -4, 7, 1, 1, 2, 2, 2, 1, 256, 102, 94, 69,,,, -4, 7, 1, 1, 2, 2, 2, 1, 384, 102, 94, 69,,,, -4, 7, 1, 1, 2, 2, 2, 2, 128, 102, 94, 69,,,, -4, 7, 1, 1, 2, 2, 2, 2, 256, 102, 94, 69,,,, -4, 7, 1, 1, 2, 2, 2, 2, 384, 102, 94, 69,,,, -4, 7, 1, 1, 3, 3, 1, 1, 128, 101, 89, 66,,,, -4, 7, 1, 1, 3, 3, 1, 1, 256, 101, 89, 66,,,, -4, 7, 1, 1, 3, 3, 1, 1, 384, 101, 89, 66,,,, -4, 7, 1, 1, 3, 3, 1, 2, 128, 101, 89, 66,,,, -4, 7, 1, 1, 3, 3, 1, 2, 256, 101, 89, 66,,,, -4, 7, 1, 1, 3, 3, 1, 2, 384, 101, 89, 66,,,, -4, 7, 1, 1, 3, 3, 1, 3, 128, 101, 89, 66,,,, -4, 7, 1, 1, 3, 3, 1, 3, 256, 101, 89, 66,,,, -4, 7, 1, 1, 3, 3, 1, 3, 384, 101, 89, 66,,,, -4, 7, 1, 1, 3, 3, 2, 1, 128, 101, 89, 66,,,, -4, 7, 1, 1, 3, 3, 2, 1, 256, 101, 89, 66,,,, -4, 7, 1, 1, 3, 3, 2, 1, 384, 101, 89, 66,,,, -4, 7, 1, 1, 3, 3, 2, 2, 128, 101, 89, 66,,,, -4, 7, 1, 1, 3, 3, 2, 2, 256, 101, 89, 66,,,, -4, 7, 1, 1, 3, 3, 2, 2, 384, 101, 89, 66,,,, -4, 7, 1, 1, 3, 3, 2, 3, 128, 101, 89, 66,,,, -4, 7, 1, 1, 3, 3, 2, 3, 256, 101, 89, 66,,,, -4, 7, 1, 1, 3, 3, 2, 3, 384, 101, 89, 66,,,, -4, 7, 1, 1, 3, 3, 3, 1, 128, 101, 89, 66,,,, -4, 7, 1, 1, 3, 3, 3, 1, 256, 101, 89, 66,,,, -4, 7, 1, 1, 3, 3, 3, 1, 384, 101, 89, 66,,,, -4, 7, 1, 1, 3, 3, 3, 2, 128, 101, 89, 66,,,, -4, 7, 1, 1, 3, 3, 3, 2, 256, 101, 89, 66,,,, -4, 7, 1, 1, 3, 3, 3, 2, 384, 101, 89, 66,,,, -4, 7, 1, 1, 3, 3, 3, 3, 128, 101, 89, 66,,,, -4, 7, 1, 1, 3, 3, 3, 3, 256, 101, 89, 66,,,, -4, 7, 1, 1, 3, 3, 3, 3, 384, 101, 89, 66,,,, -4, 7, 1, 2, 1, 1, 1, 1, 128, 198, 198, 134,,,, -4, 7, 1, 2, 1, 1, 1, 1, 256, 198, 198, 134,,,, -4, 7, 1, 2, 1, 1, 1, 1, 384, 198, 198, 134,,,, -4, 7, 1, 2, 2, 2, 1, 1, 128, 198, 182, 132,,,, -4, 7, 1, 2, 2, 2, 1, 1, 256, 198, 182, 132,,,, -4, 7, 1, 2, 2, 2, 1, 1, 384, 198, 182, 132,,,, -4, 7, 1, 2, 2, 2, 1, 2, 128, 198, 182, 132,,,, -4, 7, 1, 2, 2, 2, 1, 2, 256, 198, 182, 132,,,, -4, 7, 1, 2, 2, 2, 1, 2, 384, 198, 182, 132,,,, -4, 7, 1, 2, 2, 2, 2, 1, 128, 198, 182, 132,,,, -4, 7, 1, 2, 2, 2, 2, 1, 256, 198, 182, 132,,,, -4, 7, 1, 2, 2, 2, 2, 1, 384, 198, 182, 132,,,, -4, 7, 1, 2, 2, 2, 2, 2, 128, 198, 182, 132,,,, -4, 7, 1, 2, 2, 2, 2, 2, 256, 198, 182, 132,,,, -4, 7, 1, 2, 2, 2, 2, 2, 384, 198, 182, 132,,,, -4, 7, 1, 2, 3, 3, 1, 1, 128, 196, 172, 126,,,, -4, 7, 1, 2, 3, 3, 1, 1, 256, 196, 172, 126,,,, -4, 7, 1, 2, 3, 3, 1, 1, 384, 196, 172, 126,,,, -4, 7, 1, 2, 3, 3, 1, 2, 128, 196, 172, 126,,,, -4, 7, 1, 2, 3, 3, 1, 2, 256, 196, 172, 126,,,, -4, 7, 1, 2, 3, 3, 1, 2, 384, 196, 172, 126,,,, -4, 7, 1, 2, 3, 3, 1, 3, 128, 196, 172, 126,,,, -4, 7, 1, 2, 3, 3, 1, 3, 256, 196, 172, 126,,,, -4, 7, 1, 2, 3, 3, 1, 3, 384, 196, 172, 126,,,, -4, 7, 1, 2, 3, 3, 2, 1, 128, 196, 172, 126,,,, -4, 7, 1, 2, 3, 3, 2, 1, 256, 196, 172, 126,,,, -4, 7, 1, 2, 3, 3, 2, 1, 384, 196, 172, 126,,,, -4, 7, 1, 2, 3, 3, 2, 2, 128, 196, 172, 126,,,, -4, 7, 1, 2, 3, 3, 2, 2, 256, 196, 172, 126,,,, -4, 7, 1, 2, 3, 3, 2, 2, 384, 196, 172, 126,,,, -4, 7, 1, 2, 3, 3, 2, 3, 128, 196, 172, 126,,,, -4, 7, 1, 2, 3, 3, 2, 3, 256, 196, 172, 126,,,, -4, 7, 1, 2, 3, 3, 2, 3, 384, 196, 172, 126,,,, -4, 7, 1, 2, 3, 3, 3, 1, 128, 196, 172, 126,,,, -4, 7, 1, 2, 3, 3, 3, 1, 256, 196, 172, 126,,,, -4, 7, 1, 2, 3, 3, 3, 1, 384, 196, 172, 126,,,, -4, 7, 1, 2, 3, 3, 3, 2, 128, 196, 172, 126,,,, -4, 7, 1, 2, 3, 3, 3, 2, 256, 196, 172, 126,,,, -4, 7, 1, 2, 3, 3, 3, 2, 384, 196, 172, 126,,,, -4, 7, 1, 2, 3, 3, 3, 3, 128, 196, 172, 126,,,, -4, 7, 1, 2, 3, 3, 3, 3, 256, 196, 172, 126,,,, -4, 7, 1, 2, 3, 3, 3, 3, 384, 196, 172, 126,,,, -4, 7, 1, 3, 1, 1, 1, 1, 128, 240, 240, 198,,,, -4, 7, 1, 3, 1, 1, 1, 1, 256, 240, 240, 198,,,, -4, 7, 1, 3, 1, 1, 1, 1, 384, 240, 240, 198,,,, -4, 7, 1, 3, 2, 2, 1, 1, 128, 240, 240, 195,,,, -4, 7, 1, 3, 2, 2, 1, 1, 256, 240, 240, 195,,,, -4, 7, 1, 3, 2, 2, 1, 1, 384, 240, 240, 195,,,, -4, 7, 1, 3, 2, 2, 1, 2, 128, 240, 240, 195,,,, -4, 7, 1, 3, 2, 2, 1, 2, 256, 240, 240, 195,,,, -4, 7, 1, 3, 2, 2, 1, 2, 384, 240, 240, 195,,,, -4, 7, 1, 3, 2, 2, 2, 1, 128, 240, 240, 195,,,, -4, 7, 1, 3, 2, 2, 2, 1, 256, 240, 240, 195,,,, -4, 7, 1, 3, 2, 2, 2, 1, 384, 240, 240, 195,,,, -4, 7, 1, 3, 2, 2, 2, 2, 128, 240, 240, 195,,,, -4, 7, 1, 3, 2, 2, 2, 2, 256, 240, 240, 195,,,, -4, 7, 1, 3, 2, 2, 2, 2, 384, 240, 240, 195,,,, -4, 7, 1, 3, 3, 3, 1, 1, 128, 240, 240, 186,,,, -4, 7, 1, 3, 3, 3, 1, 1, 256, 240, 240, 186,,,, -4, 7, 1, 3, 3, 3, 1, 1, 384, 240, 240, 186,,,, -4, 7, 1, 3, 3, 3, 1, 2, 128, 240, 240, 186,,,, -4, 7, 1, 3, 3, 3, 1, 2, 256, 240, 240, 186,,,, -4, 7, 1, 3, 3, 3, 1, 2, 384, 240, 240, 186,,,, -4, 7, 1, 3, 3, 3, 1, 3, 128, 240, 240, 186,,,, -4, 7, 1, 3, 3, 3, 1, 3, 256, 240, 240, 186,,,, -4, 7, 1, 3, 3, 3, 1, 3, 384, 240, 240, 186,,,, -4, 7, 1, 3, 3, 3, 2, 1, 128, 240, 240, 186,,,, -4, 7, 1, 3, 3, 3, 2, 1, 256, 240, 240, 186,,,, -4, 7, 1, 3, 3, 3, 2, 1, 384, 240, 240, 186,,,, -4, 7, 1, 3, 3, 3, 2, 2, 128, 240, 240, 186,,,, -4, 7, 1, 3, 3, 3, 2, 2, 256, 240, 240, 186,,,, -4, 7, 1, 3, 3, 3, 2, 2, 384, 240, 240, 186,,,, -4, 7, 1, 3, 3, 3, 2, 3, 128, 240, 240, 186,,,, -4, 7, 1, 3, 3, 3, 2, 3, 256, 240, 240, 186,,,, -4, 7, 1, 3, 3, 3, 2, 3, 384, 240, 240, 186,,,, -4, 7, 1, 3, 3, 3, 3, 1, 128, 240, 240, 186,,,, -4, 7, 1, 3, 3, 3, 3, 1, 256, 240, 240, 186,,,, -4, 7, 1, 3, 3, 3, 3, 1, 384, 240, 240, 186,,,, -4, 7, 1, 3, 3, 3, 3, 2, 128, 240, 240, 186,,,, -4, 7, 1, 3, 3, 3, 3, 2, 256, 240, 240, 186,,,, -4, 7, 1, 3, 3, 3, 3, 2, 384, 240, 240, 186,,,, -4, 7, 1, 3, 3, 3, 3, 3, 128, 240, 240, 186,,,, -4, 7, 1, 3, 3, 3, 3, 3, 256, 240, 240, 186,,,, -4, 7, 1, 3, 3, 3, 3, 3, 384, 240, 240, 186,,,, -4, 7, 1, 4, 1, 1, 1, 1, 128, 240, 240, 240,,,, -4, 7, 1, 4, 1, 1, 1, 1, 256, 240, 240, 240,,,, -4, 7, 1, 4, 1, 1, 1, 1, 384, 240, 240, 240,,,, -4, 7, 1, 4, 2, 2, 1, 1, 128, 240, 240, 240,,,, -4, 7, 1, 4, 2, 2, 1, 1, 256, 240, 240, 240,,,, -4, 7, 1, 4, 2, 2, 1, 1, 384, 240, 240, 240,,,, -4, 7, 1, 4, 2, 2, 1, 2, 128, 240, 240, 240,,,, -4, 7, 1, 4, 2, 2, 1, 2, 256, 240, 240, 240,,,, -4, 7, 1, 4, 2, 2, 1, 2, 384, 240, 240, 240,,,, -4, 7, 1, 4, 2, 2, 2, 1, 128, 240, 240, 240,,,, -4, 7, 1, 4, 2, 2, 2, 1, 256, 240, 240, 240,,,, -4, 7, 1, 4, 2, 2, 2, 1, 384, 240, 240, 240,,,, -4, 7, 1, 4, 2, 2, 2, 2, 128, 240, 240, 240,,,, -4, 7, 1, 4, 2, 2, 2, 2, 256, 240, 240, 240,,,, -4, 7, 1, 4, 2, 2, 2, 2, 384, 240, 240, 240,,,, -4, 7, 1, 4, 3, 3, 1, 1, 128, 240, 240, 240,,,, -4, 7, 1, 4, 3, 3, 1, 1, 256, 240, 240, 240,,,, -4, 7, 1, 4, 3, 3, 1, 1, 384, 240, 240, 240,,,, -4, 7, 1, 4, 3, 3, 1, 2, 128, 240, 240, 240,,,, -4, 7, 1, 4, 3, 3, 1, 2, 256, 240, 240, 240,,,, -4, 7, 1, 4, 3, 3, 1, 2, 384, 240, 240, 240,,,, -4, 7, 1, 4, 3, 3, 1, 3, 128, 240, 240, 240,,,, -4, 7, 1, 4, 3, 3, 1, 3, 256, 240, 240, 240,,,, -4, 7, 1, 4, 3, 3, 1, 3, 384, 240, 240, 240,,,, -4, 7, 1, 4, 3, 3, 2, 1, 128, 240, 240, 240,,,, -4, 7, 1, 4, 3, 3, 2, 1, 256, 240, 240, 240,,,, -4, 7, 1, 4, 3, 3, 2, 1, 384, 240, 240, 240,,,, -4, 7, 1, 4, 3, 3, 2, 2, 128, 240, 240, 240,,,, -4, 7, 1, 4, 3, 3, 2, 2, 256, 240, 240, 240,,,, -4, 7, 1, 4, 3, 3, 2, 2, 384, 240, 240, 240,,,, -4, 7, 1, 4, 3, 3, 2, 3, 128, 240, 240, 240,,,, -4, 7, 1, 4, 3, 3, 2, 3, 256, 240, 240, 240,,,, -4, 7, 1, 4, 3, 3, 2, 3, 384, 240, 240, 240,,,, -4, 7, 1, 4, 3, 3, 3, 1, 128, 240, 240, 240,,,, -4, 7, 1, 4, 3, 3, 3, 1, 256, 240, 240, 240,,,, -4, 7, 1, 4, 3, 3, 3, 1, 384, 240, 240, 240,,,, -4, 7, 1, 4, 3, 3, 3, 2, 128, 240, 240, 240,,,, -4, 7, 1, 4, 3, 3, 3, 2, 256, 240, 240, 240,,,, -4, 7, 1, 4, 3, 3, 3, 2, 384, 240, 240, 240,,,, -4, 7, 1, 4, 3, 3, 3, 3, 128, 240, 240, 240,,,, -4, 7, 1, 4, 3, 3, 3, 3, 256, 240, 240, 240,,,, -4, 7, 1, 4, 3, 3, 3, 3, 384, 240, 240, 240,,,, -4, 7, 1, 5, 1, 1, 1, 1, 128, 240, 240, 240,,,, -4, 7, 1, 5, 1, 1, 1, 1, 256, 240, 240, 240,,,, -4, 7, 1, 5, 1, 1, 1, 1, 384, 240, 240, 240,,,, -4, 7, 1, 5, 2, 2, 1, 1, 128, 240, 240, 240,,,, -4, 7, 1, 5, 2, 2, 1, 1, 256, 240, 240, 240,,,, -4, 7, 1, 5, 2, 2, 1, 1, 384, 240, 240, 240,,,, -4, 7, 1, 5, 2, 2, 1, 2, 128, 240, 240, 240,,,, -4, 7, 1, 5, 2, 2, 1, 2, 256, 240, 240, 240,,,, -4, 7, 1, 5, 2, 2, 1, 2, 384, 240, 240, 240,,,, -4, 7, 1, 5, 2, 2, 2, 1, 128, 240, 240, 240,,,, -4, 7, 1, 5, 2, 2, 2, 1, 256, 240, 240, 240,,,, -4, 7, 1, 5, 2, 2, 2, 1, 384, 240, 240, 240,,,, -4, 7, 1, 5, 2, 2, 2, 2, 128, 240, 240, 240,,,, -4, 7, 1, 5, 2, 2, 2, 2, 256, 240, 240, 240,,,, -4, 7, 1, 5, 2, 2, 2, 2, 384, 240, 240, 240,,,, -4, 7, 1, 5, 3, 3, 1, 1, 128, 240, 240, 240,,,, -4, 7, 1, 5, 3, 3, 1, 1, 256, 240, 240, 240,,,, -4, 7, 1, 5, 3, 3, 1, 1, 384, 240, 240, 240,,,, -4, 7, 1, 5, 3, 3, 1, 2, 128, 240, 240, 240,,,, -4, 7, 1, 5, 3, 3, 1, 2, 256, 240, 240, 240,,,, -4, 7, 1, 5, 3, 3, 1, 2, 384, 240, 240, 240,,,, -4, 7, 1, 5, 3, 3, 1, 3, 128, 240, 240, 240,,,, -4, 7, 1, 5, 3, 3, 1, 3, 256, 240, 240, 240,,,, -4, 7, 1, 5, 3, 3, 1, 3, 384, 240, 240, 240,,,, -4, 7, 1, 5, 3, 3, 2, 1, 128, 240, 240, 240,,,, -4, 7, 1, 5, 3, 3, 2, 1, 256, 240, 240, 240,,,, -4, 7, 1, 5, 3, 3, 2, 1, 384, 240, 240, 240,,,, -4, 7, 1, 5, 3, 3, 2, 2, 128, 240, 240, 240,,,, -4, 7, 1, 5, 3, 3, 2, 2, 256, 240, 240, 240,,,, -4, 7, 1, 5, 3, 3, 2, 2, 384, 240, 240, 240,,,, -4, 7, 1, 5, 3, 3, 2, 3, 128, 240, 240, 240,,,, -4, 7, 1, 5, 3, 3, 2, 3, 256, 240, 240, 240,,,, -4, 7, 1, 5, 3, 3, 2, 3, 384, 240, 240, 240,,,, -4, 7, 1, 5, 3, 3, 3, 1, 128, 240, 240, 240,,,, -4, 7, 1, 5, 3, 3, 3, 1, 256, 240, 240, 240,,,, -4, 7, 1, 5, 3, 3, 3, 1, 384, 240, 240, 240,,,, -4, 7, 1, 5, 3, 3, 3, 2, 128, 240, 240, 240,,,, -4, 7, 1, 5, 3, 3, 3, 2, 256, 240, 240, 240,,,, -4, 7, 1, 5, 3, 3, 3, 2, 384, 240, 240, 240,,,, -4, 7, 1, 5, 3, 3, 3, 3, 128, 240, 240, 240,,,, -4, 7, 1, 5, 3, 3, 3, 3, 256, 240, 240, 240,,,, -4, 7, 1, 5, 3, 3, 3, 3, 384, 240, 240, 240,,,, -4, 7, 1, 6, 1, 1, 1, 1, 128, 240, 240, 240,,,, -4, 7, 1, 6, 1, 1, 1, 1, 256, 240, 240, 240,,,, -4, 7, 1, 6, 1, 1, 1, 1, 384, 240, 240, 240,,,, -4, 7, 1, 6, 2, 2, 1, 1, 128, 240, 240, 240,,,, -4, 7, 1, 6, 2, 2, 1, 1, 256, 240, 240, 240,,,, -4, 7, 1, 6, 2, 2, 1, 1, 384, 240, 240, 240,,,, -4, 7, 1, 6, 2, 2, 1, 2, 128, 240, 240, 240,,,, -4, 7, 1, 6, 2, 2, 1, 2, 256, 240, 240, 240,,,, -4, 7, 1, 6, 2, 2, 1, 2, 384, 240, 240, 240,,,, -4, 7, 1, 6, 2, 2, 2, 1, 128, 240, 240, 240,,,, -4, 7, 1, 6, 2, 2, 2, 1, 256, 240, 240, 240,,,, -4, 7, 1, 6, 2, 2, 2, 1, 384, 240, 240, 240,,,, -4, 7, 1, 6, 2, 2, 2, 2, 128, 240, 240, 240,,,, -4, 7, 1, 6, 2, 2, 2, 2, 256, 240, 240, 240,,,, -4, 7, 1, 6, 2, 2, 2, 2, 384, 240, 240, 240,,,, -4, 7, 1, 6, 3, 3, 1, 1, 128, 240, 240, 240,,,, -4, 7, 1, 6, 3, 3, 1, 1, 256, 240, 240, 240,,,, -4, 7, 1, 6, 3, 3, 1, 1, 384, 240, 240, 240,,,, -4, 7, 1, 6, 3, 3, 1, 2, 128, 240, 240, 240,,,, -4, 7, 1, 6, 3, 3, 1, 2, 256, 240, 240, 240,,,, -4, 7, 1, 6, 3, 3, 1, 2, 384, 240, 240, 240,,,, -4, 7, 1, 6, 3, 3, 1, 3, 128, 240, 240, 240,,,, -4, 7, 1, 6, 3, 3, 1, 3, 256, 240, 240, 240,,,, -4, 7, 1, 6, 3, 3, 1, 3, 384, 240, 240, 240,,,, -4, 7, 1, 6, 3, 3, 2, 1, 128, 240, 240, 240,,,, -4, 7, 1, 6, 3, 3, 2, 1, 256, 240, 240, 240,,,, -4, 7, 1, 6, 3, 3, 2, 1, 384, 240, 240, 240,,,, -4, 7, 1, 6, 3, 3, 2, 2, 128, 240, 240, 240,,,, -4, 7, 1, 6, 3, 3, 2, 2, 256, 240, 240, 240,,,, -4, 7, 1, 6, 3, 3, 2, 2, 384, 240, 240, 240,,,, -4, 7, 1, 6, 3, 3, 2, 3, 128, 240, 240, 240,,,, -4, 7, 1, 6, 3, 3, 2, 3, 256, 240, 240, 240,,,, -4, 7, 1, 6, 3, 3, 2, 3, 384, 240, 240, 240,,,, -4, 7, 1, 6, 3, 3, 3, 1, 128, 240, 240, 240,,,, -4, 7, 1, 6, 3, 3, 3, 1, 256, 240, 240, 240,,,, -4, 7, 1, 6, 3, 3, 3, 1, 384, 240, 240, 240,,,, -4, 7, 1, 6, 3, 3, 3, 2, 128, 240, 240, 240,,,, -4, 7, 1, 6, 3, 3, 3, 2, 256, 240, 240, 240,,,, -4, 7, 1, 6, 3, 3, 3, 2, 384, 240, 240, 240,,,, -4, 7, 1, 6, 3, 3, 3, 3, 128, 240, 240, 240,,,, -4, 7, 1, 6, 3, 3, 3, 3, 256, 240, 240, 240,,,, -4, 7, 1, 6, 3, 3, 3, 3, 384, 240, 240, 240,,,, -4, 7, 1, 7, 1, 1, 1, 1, 128, 240, 240, 240,,,, -4, 7, 1, 7, 1, 1, 1, 1, 256, 240, 240, 240,,,, -4, 7, 1, 7, 1, 1, 1, 1, 384, 240, 240, 240,,,, -4, 7, 1, 7, 2, 2, 1, 1, 128, 240, 240, 240,,,, -4, 7, 1, 7, 2, 2, 1, 1, 256, 240, 240, 240,,,, -4, 7, 1, 7, 2, 2, 1, 1, 384, 240, 240, 240,,,, -4, 7, 1, 7, 2, 2, 1, 2, 128, 240, 240, 240,,,, -4, 7, 1, 7, 2, 2, 1, 2, 256, 240, 240, 240,,,, -4, 7, 1, 7, 2, 2, 1, 2, 384, 240, 240, 240,,,, -4, 7, 1, 7, 2, 2, 2, 1, 128, 240, 240, 240,,,, -4, 7, 1, 7, 2, 2, 2, 1, 256, 240, 240, 240,,,, -4, 7, 1, 7, 2, 2, 2, 1, 384, 240, 240, 240,,,, -4, 7, 1, 7, 2, 2, 2, 2, 128, 240, 240, 240,,,, -4, 7, 1, 7, 2, 2, 2, 2, 256, 240, 240, 240,,,, -4, 7, 1, 7, 2, 2, 2, 2, 384, 240, 240, 240,,,, -4, 7, 1, 7, 3, 3, 1, 1, 128, 240, 240, 240,,,, -4, 7, 1, 7, 3, 3, 1, 1, 256, 240, 240, 240,,,, -4, 7, 1, 7, 3, 3, 1, 1, 384, 240, 240, 240,,,, -4, 7, 1, 7, 3, 3, 1, 2, 128, 240, 240, 240,,,, -4, 7, 1, 7, 3, 3, 1, 2, 256, 240, 240, 240,,,, -4, 7, 1, 7, 3, 3, 1, 2, 384, 240, 240, 240,,,, -4, 7, 1, 7, 3, 3, 1, 3, 128, 240, 240, 240,,,, -4, 7, 1, 7, 3, 3, 1, 3, 256, 240, 240, 240,,,, -4, 7, 1, 7, 3, 3, 1, 3, 384, 240, 240, 240,,,, -4, 7, 1, 7, 3, 3, 2, 1, 128, 240, 240, 240,,,, -4, 7, 1, 7, 3, 3, 2, 1, 256, 240, 240, 240,,,, -4, 7, 1, 7, 3, 3, 2, 1, 384, 240, 240, 240,,,, -4, 7, 1, 7, 3, 3, 2, 2, 128, 240, 240, 240,,,, -4, 7, 1, 7, 3, 3, 2, 2, 256, 240, 240, 240,,,, -4, 7, 1, 7, 3, 3, 2, 2, 384, 240, 240, 240,,,, -4, 7, 1, 7, 3, 3, 2, 3, 128, 240, 240, 240,,,, -4, 7, 1, 7, 3, 3, 2, 3, 256, 240, 240, 240,,,, -4, 7, 1, 7, 3, 3, 2, 3, 384, 240, 240, 240,,,, -4, 7, 1, 7, 3, 3, 3, 1, 128, 240, 240, 240,,,, -4, 7, 1, 7, 3, 3, 3, 1, 256, 240, 240, 240,,,, -4, 7, 1, 7, 3, 3, 3, 1, 384, 240, 240, 240,,,, -4, 7, 1, 7, 3, 3, 3, 2, 128, 240, 240, 240,,,, -4, 7, 1, 7, 3, 3, 3, 2, 256, 240, 240, 240,,,, -4, 7, 1, 7, 3, 3, 3, 2, 384, 240, 240, 240,,,, -4, 7, 1, 7, 3, 3, 3, 3, 128, 240, 240, 240,,,, -4, 7, 1, 7, 3, 3, 3, 3, 256, 240, 240, 240,,,, -4, 7, 1, 7, 3, 3, 3, 3, 384, 240, 240, 240,,,, -4, 7, 2, 1, 1, 1, 1, 1, 128, 102, 102, 70,,,, -4, 7, 2, 1, 1, 1, 1, 1, 256, 102, 102, 70,,,, -4, 7, 2, 1, 1, 1, 1, 1, 384, 102, 102, 70,,,, -4, 7, 2, 1, 2, 2, 1, 1, 128, 102, 94, 69,,,, -4, 7, 2, 1, 2, 2, 1, 1, 256, 102, 94, 69,,,, -4, 7, 2, 1, 2, 2, 1, 1, 384, 102, 94, 69,,,, -4, 7, 2, 1, 2, 2, 1, 2, 128, 102, 94, 69,,,, -4, 7, 2, 1, 2, 2, 1, 2, 256, 102, 94, 69,,,, -4, 7, 2, 1, 2, 2, 1, 2, 384, 102, 94, 69,,,, -4, 7, 2, 1, 2, 2, 2, 1, 128, 102, 94, 69,,,, -4, 7, 2, 1, 2, 2, 2, 1, 256, 102, 94, 69,,,, -4, 7, 2, 1, 2, 2, 2, 1, 384, 102, 94, 69,,,, -4, 7, 2, 1, 2, 2, 2, 2, 128, 102, 94, 69,,,, -4, 7, 2, 1, 2, 2, 2, 2, 256, 102, 94, 69,,,, -4, 7, 2, 1, 2, 2, 2, 2, 384, 102, 94, 69,,,, -4, 7, 2, 1, 3, 3, 1, 1, 128, 101, 89, 66,,,, -4, 7, 2, 1, 3, 3, 1, 1, 256, 101, 89, 66,,,, -4, 7, 2, 1, 3, 3, 1, 1, 384, 101, 89, 66,,,, -4, 7, 2, 1, 3, 3, 1, 2, 128, 101, 89, 66,,,, -4, 7, 2, 1, 3, 3, 1, 2, 256, 101, 89, 66,,,, -4, 7, 2, 1, 3, 3, 1, 2, 384, 101, 89, 66,,,, -4, 7, 2, 1, 3, 3, 1, 3, 128, 101, 89, 66,,,, -4, 7, 2, 1, 3, 3, 1, 3, 256, 101, 89, 66,,,, -4, 7, 2, 1, 3, 3, 1, 3, 384, 101, 89, 66,,,, -4, 7, 2, 1, 3, 3, 2, 1, 128, 101, 89, 66,,,, -4, 7, 2, 1, 3, 3, 2, 1, 256, 101, 89, 66,,,, -4, 7, 2, 1, 3, 3, 2, 1, 384, 101, 89, 66,,,, -4, 7, 2, 1, 3, 3, 2, 2, 128, 101, 89, 66,,,, -4, 7, 2, 1, 3, 3, 2, 2, 256, 101, 89, 66,,,, -4, 7, 2, 1, 3, 3, 2, 2, 384, 101, 89, 66,,,, -4, 7, 2, 1, 3, 3, 2, 3, 128, 101, 89, 66,,,, -4, 7, 2, 1, 3, 3, 2, 3, 256, 101, 89, 66,,,, -4, 7, 2, 1, 3, 3, 2, 3, 384, 101, 89, 66,,,, -4, 7, 2, 1, 3, 3, 3, 1, 128, 101, 89, 66,,,, -4, 7, 2, 1, 3, 3, 3, 1, 256, 101, 89, 66,,,, -4, 7, 2, 1, 3, 3, 3, 1, 384, 101, 89, 66,,,, -4, 7, 2, 1, 3, 3, 3, 2, 128, 101, 89, 66,,,, -4, 7, 2, 1, 3, 3, 3, 2, 256, 101, 89, 66,,,, -4, 7, 2, 1, 3, 3, 3, 2, 384, 101, 89, 66,,,, -4, 7, 2, 1, 3, 3, 3, 3, 128, 101, 89, 66,,,, -4, 7, 2, 1, 3, 3, 3, 3, 256, 101, 89, 66,,,, -4, 7, 2, 1, 3, 3, 3, 3, 384, 101, 89, 66,,,, -4, 7, 2, 2, 1, 1, 1, 1, 128, 198, 198, 134,,,, -4, 7, 2, 2, 1, 1, 1, 1, 256, 198, 198, 134,,,, -4, 7, 2, 2, 1, 1, 1, 1, 384, 198, 198, 134,,,, -4, 7, 2, 2, 2, 2, 1, 1, 128, 198, 182, 132,,,, -4, 7, 2, 2, 2, 2, 1, 1, 256, 198, 182, 132,,,, -4, 7, 2, 2, 2, 2, 1, 1, 384, 198, 182, 132,,,, -4, 7, 2, 2, 2, 2, 1, 2, 128, 198, 182, 132,,,, -4, 7, 2, 2, 2, 2, 1, 2, 256, 198, 182, 132,,,, -4, 7, 2, 2, 2, 2, 1, 2, 384, 198, 182, 132,,,, -4, 7, 2, 2, 2, 2, 2, 1, 128, 198, 182, 132,,,, -4, 7, 2, 2, 2, 2, 2, 1, 256, 198, 182, 132,,,, -4, 7, 2, 2, 2, 2, 2, 1, 384, 198, 182, 132,,,, -4, 7, 2, 2, 2, 2, 2, 2, 128, 198, 182, 132,,,, -4, 7, 2, 2, 2, 2, 2, 2, 256, 198, 182, 132,,,, -4, 7, 2, 2, 2, 2, 2, 2, 384, 198, 182, 132,,,, -4, 7, 2, 2, 3, 3, 1, 1, 128, 196, 172, 126,,,, -4, 7, 2, 2, 3, 3, 1, 1, 256, 196, 172, 126,,,, -4, 7, 2, 2, 3, 3, 1, 1, 384, 196, 172, 126,,,, -4, 7, 2, 2, 3, 3, 1, 2, 128, 196, 172, 126,,,, -4, 7, 2, 2, 3, 3, 1, 2, 256, 196, 172, 126,,,, -4, 7, 2, 2, 3, 3, 1, 2, 384, 196, 172, 126,,,, -4, 7, 2, 2, 3, 3, 1, 3, 128, 196, 172, 126,,,, -4, 7, 2, 2, 3, 3, 1, 3, 256, 196, 172, 126,,,, -4, 7, 2, 2, 3, 3, 1, 3, 384, 196, 172, 126,,,, -4, 7, 2, 2, 3, 3, 2, 1, 128, 196, 172, 126,,,, -4, 7, 2, 2, 3, 3, 2, 1, 256, 196, 172, 126,,,, -4, 7, 2, 2, 3, 3, 2, 1, 384, 196, 172, 126,,,, -4, 7, 2, 2, 3, 3, 2, 2, 128, 196, 172, 126,,,, -4, 7, 2, 2, 3, 3, 2, 2, 256, 196, 172, 126,,,, -4, 7, 2, 2, 3, 3, 2, 2, 384, 196, 172, 126,,,, -4, 7, 2, 2, 3, 3, 2, 3, 128, 196, 172, 126,,,, -4, 7, 2, 2, 3, 3, 2, 3, 256, 196, 172, 126,,,, -4, 7, 2, 2, 3, 3, 2, 3, 384, 196, 172, 126,,,, -4, 7, 2, 2, 3, 3, 3, 1, 128, 196, 172, 126,,,, -4, 7, 2, 2, 3, 3, 3, 1, 256, 196, 172, 126,,,, -4, 7, 2, 2, 3, 3, 3, 1, 384, 196, 172, 126,,,, -4, 7, 2, 2, 3, 3, 3, 2, 128, 196, 172, 126,,,, -4, 7, 2, 2, 3, 3, 3, 2, 256, 196, 172, 126,,,, -4, 7, 2, 2, 3, 3, 3, 2, 384, 196, 172, 126,,,, -4, 7, 2, 2, 3, 3, 3, 3, 128, 196, 172, 126,,,, -4, 7, 2, 2, 3, 3, 3, 3, 256, 196, 172, 126,,,, -4, 7, 2, 2, 3, 3, 3, 3, 384, 196, 172, 126,,,, -4, 7, 2, 3, 1, 1, 1, 1, 128, 240, 240, 198,,,, -4, 7, 2, 3, 1, 1, 1, 1, 256, 240, 240, 198,,,, -4, 7, 2, 3, 1, 1, 1, 1, 384, 240, 240, 198,,,, -4, 7, 2, 3, 2, 2, 1, 1, 128, 240, 240, 195,,,, -4, 7, 2, 3, 2, 2, 1, 1, 256, 240, 240, 195,,,, -4, 7, 2, 3, 2, 2, 1, 1, 384, 240, 240, 195,,,, -4, 7, 2, 3, 2, 2, 1, 2, 128, 240, 240, 195,,,, -4, 7, 2, 3, 2, 2, 1, 2, 256, 240, 240, 195,,,, -4, 7, 2, 3, 2, 2, 1, 2, 384, 240, 240, 195,,,, -4, 7, 2, 3, 2, 2, 2, 1, 128, 240, 240, 195,,,, -4, 7, 2, 3, 2, 2, 2, 1, 256, 240, 240, 195,,,, -4, 7, 2, 3, 2, 2, 2, 1, 384, 240, 240, 195,,,, -4, 7, 2, 3, 2, 2, 2, 2, 128, 240, 240, 195,,,, -4, 7, 2, 3, 2, 2, 2, 2, 256, 240, 240, 195,,,, -4, 7, 2, 3, 2, 2, 2, 2, 384, 240, 240, 195,,,, -4, 7, 2, 3, 3, 3, 1, 1, 128, 240, 240, 186,,,, -4, 7, 2, 3, 3, 3, 1, 1, 256, 240, 240, 186,,,, -4, 7, 2, 3, 3, 3, 1, 1, 384, 240, 240, 186,,,, -4, 7, 2, 3, 3, 3, 1, 2, 128, 240, 240, 186,,,, -4, 7, 2, 3, 3, 3, 1, 2, 256, 240, 240, 186,,,, -4, 7, 2, 3, 3, 3, 1, 2, 384, 240, 240, 186,,,, -4, 7, 2, 3, 3, 3, 1, 3, 128, 240, 240, 186,,,, -4, 7, 2, 3, 3, 3, 1, 3, 256, 240, 240, 186,,,, -4, 7, 2, 3, 3, 3, 1, 3, 384, 240, 240, 186,,,, -4, 7, 2, 3, 3, 3, 2, 1, 128, 240, 240, 186,,,, -4, 7, 2, 3, 3, 3, 2, 1, 256, 240, 240, 186,,,, -4, 7, 2, 3, 3, 3, 2, 1, 384, 240, 240, 186,,,, -4, 7, 2, 3, 3, 3, 2, 2, 128, 240, 240, 186,,,, -4, 7, 2, 3, 3, 3, 2, 2, 256, 240, 240, 186,,,, -4, 7, 2, 3, 3, 3, 2, 2, 384, 240, 240, 186,,,, -4, 7, 2, 3, 3, 3, 2, 3, 128, 240, 240, 186,,,, -4, 7, 2, 3, 3, 3, 2, 3, 256, 240, 240, 186,,,, -4, 7, 2, 3, 3, 3, 2, 3, 384, 240, 240, 186,,,, -4, 7, 2, 3, 3, 3, 3, 1, 128, 240, 240, 186,,,, -4, 7, 2, 3, 3, 3, 3, 1, 256, 240, 240, 186,,,, -4, 7, 2, 3, 3, 3, 3, 1, 384, 240, 240, 186,,,, -4, 7, 2, 3, 3, 3, 3, 2, 128, 240, 240, 186,,,, -4, 7, 2, 3, 3, 3, 3, 2, 256, 240, 240, 186,,,, -4, 7, 2, 3, 3, 3, 3, 2, 384, 240, 240, 186,,,, -4, 7, 2, 3, 3, 3, 3, 3, 128, 240, 240, 186,,,, -4, 7, 2, 3, 3, 3, 3, 3, 256, 240, 240, 186,,,, -4, 7, 2, 3, 3, 3, 3, 3, 384, 240, 240, 186,,,, -4, 7, 2, 4, 1, 1, 1, 1, 128, 240, 240, 240,,,, -4, 7, 2, 4, 1, 1, 1, 1, 256, 240, 240, 240,,,, -4, 7, 2, 4, 1, 1, 1, 1, 384, 240, 240, 240,,,, -4, 7, 2, 4, 2, 2, 1, 1, 128, 240, 240, 240,,,, -4, 7, 2, 4, 2, 2, 1, 1, 256, 240, 240, 240,,,, -4, 7, 2, 4, 2, 2, 1, 1, 384, 240, 240, 240,,,, -4, 7, 2, 4, 2, 2, 1, 2, 128, 240, 240, 240,,,, -4, 7, 2, 4, 2, 2, 1, 2, 256, 240, 240, 240,,,, -4, 7, 2, 4, 2, 2, 1, 2, 384, 240, 240, 240,,,, -4, 7, 2, 4, 2, 2, 2, 1, 128, 240, 240, 240,,,, -4, 7, 2, 4, 2, 2, 2, 1, 256, 240, 240, 240,,,, -4, 7, 2, 4, 2, 2, 2, 1, 384, 240, 240, 240,,,, -4, 7, 2, 4, 2, 2, 2, 2, 128, 240, 240, 240,,,, -4, 7, 2, 4, 2, 2, 2, 2, 256, 240, 240, 240,,,, -4, 7, 2, 4, 2, 2, 2, 2, 384, 240, 240, 240,,,, -4, 7, 2, 4, 3, 3, 1, 1, 128, 240, 240, 240,,,, -4, 7, 2, 4, 3, 3, 1, 1, 256, 240, 240, 240,,,, -4, 7, 2, 4, 3, 3, 1, 1, 384, 240, 240, 240,,,, -4, 7, 2, 4, 3, 3, 1, 2, 128, 240, 240, 240,,,, -4, 7, 2, 4, 3, 3, 1, 2, 256, 240, 240, 240,,,, -4, 7, 2, 4, 3, 3, 1, 2, 384, 240, 240, 240,,,, -4, 7, 2, 4, 3, 3, 1, 3, 128, 240, 240, 240,,,, -4, 7, 2, 4, 3, 3, 1, 3, 256, 240, 240, 240,,,, -4, 7, 2, 4, 3, 3, 1, 3, 384, 240, 240, 240,,,, -4, 7, 2, 4, 3, 3, 2, 1, 128, 240, 240, 240,,,, -4, 7, 2, 4, 3, 3, 2, 1, 256, 240, 240, 240,,,, -4, 7, 2, 4, 3, 3, 2, 1, 384, 240, 240, 240,,,, -4, 7, 2, 4, 3, 3, 2, 2, 128, 240, 240, 240,,,, -4, 7, 2, 4, 3, 3, 2, 2, 256, 240, 240, 240,,,, -4, 7, 2, 4, 3, 3, 2, 2, 384, 240, 240, 240,,,, -4, 7, 2, 4, 3, 3, 2, 3, 128, 240, 240, 240,,,, -4, 7, 2, 4, 3, 3, 2, 3, 256, 240, 240, 240,,,, -4, 7, 2, 4, 3, 3, 2, 3, 384, 240, 240, 240,,,, -4, 7, 2, 4, 3, 3, 3, 1, 128, 240, 240, 240,,,, -4, 7, 2, 4, 3, 3, 3, 1, 256, 240, 240, 240,,,, -4, 7, 2, 4, 3, 3, 3, 1, 384, 240, 240, 240,,,, -4, 7, 2, 4, 3, 3, 3, 2, 128, 240, 240, 240,,,, -4, 7, 2, 4, 3, 3, 3, 2, 256, 240, 240, 240,,,, -4, 7, 2, 4, 3, 3, 3, 2, 384, 240, 240, 240,,,, -4, 7, 2, 4, 3, 3, 3, 3, 128, 240, 240, 240,,,, -4, 7, 2, 4, 3, 3, 3, 3, 256, 240, 240, 240,,,, -4, 7, 2, 4, 3, 3, 3, 3, 384, 240, 240, 240,,,, -4, 7, 2, 5, 1, 1, 1, 1, 128, 240, 240, 240,,,, -4, 7, 2, 5, 1, 1, 1, 1, 256, 240, 240, 240,,,, -4, 7, 2, 5, 1, 1, 1, 1, 384, 240, 240, 240,,,, -4, 7, 2, 5, 2, 2, 1, 1, 128, 240, 240, 240,,,, -4, 7, 2, 5, 2, 2, 1, 1, 256, 240, 240, 240,,,, -4, 7, 2, 5, 2, 2, 1, 1, 384, 240, 240, 240,,,, -4, 7, 2, 5, 2, 2, 1, 2, 128, 240, 240, 240,,,, -4, 7, 2, 5, 2, 2, 1, 2, 256, 240, 240, 240,,,, -4, 7, 2, 5, 2, 2, 1, 2, 384, 240, 240, 240,,,, -4, 7, 2, 5, 2, 2, 2, 1, 128, 240, 240, 240,,,, -4, 7, 2, 5, 2, 2, 2, 1, 256, 240, 240, 240,,,, -4, 7, 2, 5, 2, 2, 2, 1, 384, 240, 240, 240,,,, -4, 7, 2, 5, 2, 2, 2, 2, 128, 240, 240, 240,,,, -4, 7, 2, 5, 2, 2, 2, 2, 256, 240, 240, 240,,,, -4, 7, 2, 5, 2, 2, 2, 2, 384, 240, 240, 240,,,, -4, 7, 2, 5, 3, 3, 1, 1, 128, 240, 240, 240,,,, -4, 7, 2, 5, 3, 3, 1, 1, 256, 240, 240, 240,,,, -4, 7, 2, 5, 3, 3, 1, 1, 384, 240, 240, 240,,,, -4, 7, 2, 5, 3, 3, 1, 2, 128, 240, 240, 240,,,, -4, 7, 2, 5, 3, 3, 1, 2, 256, 240, 240, 240,,,, -4, 7, 2, 5, 3, 3, 1, 2, 384, 240, 240, 240,,,, -4, 7, 2, 5, 3, 3, 1, 3, 128, 240, 240, 240,,,, -4, 7, 2, 5, 3, 3, 1, 3, 256, 240, 240, 240,,,, -4, 7, 2, 5, 3, 3, 1, 3, 384, 240, 240, 240,,,, -4, 7, 2, 5, 3, 3, 2, 1, 128, 240, 240, 240,,,, -4, 7, 2, 5, 3, 3, 2, 1, 256, 240, 240, 240,,,, -4, 7, 2, 5, 3, 3, 2, 1, 384, 240, 240, 240,,,, -4, 7, 2, 5, 3, 3, 2, 2, 128, 240, 240, 240,,,, -4, 7, 2, 5, 3, 3, 2, 2, 256, 240, 240, 240,,,, -4, 7, 2, 5, 3, 3, 2, 2, 384, 240, 240, 240,,,, -4, 7, 2, 5, 3, 3, 2, 3, 128, 240, 240, 240,,,, -4, 7, 2, 5, 3, 3, 2, 3, 256, 240, 240, 240,,,, -4, 7, 2, 5, 3, 3, 2, 3, 384, 240, 240, 240,,,, -4, 7, 2, 5, 3, 3, 3, 1, 128, 240, 240, 240,,,, -4, 7, 2, 5, 3, 3, 3, 1, 256, 240, 240, 240,,,, -4, 7, 2, 5, 3, 3, 3, 1, 384, 240, 240, 240,,,, -4, 7, 2, 5, 3, 3, 3, 2, 128, 240, 240, 240,,,, -4, 7, 2, 5, 3, 3, 3, 2, 256, 240, 240, 240,,,, -4, 7, 2, 5, 3, 3, 3, 2, 384, 240, 240, 240,,,, -4, 7, 2, 5, 3, 3, 3, 3, 128, 240, 240, 240,,,, -4, 7, 2, 5, 3, 3, 3, 3, 256, 240, 240, 240,,,, -4, 7, 2, 5, 3, 3, 3, 3, 384, 240, 240, 240,,,, -4, 7, 2, 6, 1, 1, 1, 1, 128, 240, 240, 240,,,, -4, 7, 2, 6, 1, 1, 1, 1, 256, 240, 240, 240,,,, -4, 7, 2, 6, 1, 1, 1, 1, 384, 240, 240, 240,,,, -4, 7, 2, 6, 2, 2, 1, 1, 128, 240, 240, 240,,,, -4, 7, 2, 6, 2, 2, 1, 1, 256, 240, 240, 240,,,, -4, 7, 2, 6, 2, 2, 1, 1, 384, 240, 240, 240,,,, -4, 7, 2, 6, 2, 2, 1, 2, 128, 240, 240, 240,,,, -4, 7, 2, 6, 2, 2, 1, 2, 256, 240, 240, 240,,,, -4, 7, 2, 6, 2, 2, 1, 2, 384, 240, 240, 240,,,, -4, 7, 2, 6, 2, 2, 2, 1, 128, 240, 240, 240,,,, -4, 7, 2, 6, 2, 2, 2, 1, 256, 240, 240, 240,,,, -4, 7, 2, 6, 2, 2, 2, 1, 384, 240, 240, 240,,,, -4, 7, 2, 6, 2, 2, 2, 2, 128, 240, 240, 240,,,, -4, 7, 2, 6, 2, 2, 2, 2, 256, 240, 240, 240,,,, -4, 7, 2, 6, 2, 2, 2, 2, 384, 240, 240, 240,,,, -4, 7, 2, 6, 3, 3, 1, 1, 128, 240, 240, 240,,,, -4, 7, 2, 6, 3, 3, 1, 1, 256, 240, 240, 240,,,, -4, 7, 2, 6, 3, 3, 1, 1, 384, 240, 240, 240,,,, -4, 7, 2, 6, 3, 3, 1, 2, 128, 240, 240, 240,,,, -4, 7, 2, 6, 3, 3, 1, 2, 256, 240, 240, 240,,,, -4, 7, 2, 6, 3, 3, 1, 2, 384, 240, 240, 240,,,, -4, 7, 2, 6, 3, 3, 1, 3, 128, 240, 240, 240,,,, -4, 7, 2, 6, 3, 3, 1, 3, 256, 240, 240, 240,,,, -4, 7, 2, 6, 3, 3, 1, 3, 384, 240, 240, 240,,,, -4, 7, 2, 6, 3, 3, 2, 1, 128, 240, 240, 240,,,, -4, 7, 2, 6, 3, 3, 2, 1, 256, 240, 240, 240,,,, -4, 7, 2, 6, 3, 3, 2, 1, 384, 240, 240, 240,,,, -4, 7, 2, 6, 3, 3, 2, 2, 128, 240, 240, 240,,,, -4, 7, 2, 6, 3, 3, 2, 2, 256, 240, 240, 240,,,, -4, 7, 2, 6, 3, 3, 2, 2, 384, 240, 240, 240,,,, -4, 7, 2, 6, 3, 3, 2, 3, 128, 240, 240, 240,,,, -4, 7, 2, 6, 3, 3, 2, 3, 256, 240, 240, 240,,,, -4, 7, 2, 6, 3, 3, 2, 3, 384, 240, 240, 240,,,, -4, 7, 2, 6, 3, 3, 3, 1, 128, 240, 240, 240,,,, -4, 7, 2, 6, 3, 3, 3, 1, 256, 240, 240, 240,,,, -4, 7, 2, 6, 3, 3, 3, 1, 384, 240, 240, 240,,,, -4, 7, 2, 6, 3, 3, 3, 2, 128, 240, 240, 240,,,, -4, 7, 2, 6, 3, 3, 3, 2, 256, 240, 240, 240,,,, -4, 7, 2, 6, 3, 3, 3, 2, 384, 240, 240, 240,,,, -4, 7, 2, 6, 3, 3, 3, 3, 128, 240, 240, 240,,,, -4, 7, 2, 6, 3, 3, 3, 3, 256, 240, 240, 240,,,, -4, 7, 2, 6, 3, 3, 3, 3, 384, 240, 240, 240,,,, -4, 7, 2, 7, 1, 1, 1, 1, 128, 240, 240, 240,,,, -4, 7, 2, 7, 1, 1, 1, 1, 256, 240, 240, 240,,,, -4, 7, 2, 7, 1, 1, 1, 1, 384, 240, 240, 240,,,, -4, 7, 2, 7, 2, 2, 1, 1, 128, 240, 240, 240,,,, -4, 7, 2, 7, 2, 2, 1, 1, 256, 240, 240, 240,,,, -4, 7, 2, 7, 2, 2, 1, 1, 384, 240, 240, 240,,,, -4, 7, 2, 7, 2, 2, 1, 2, 128, 240, 240, 240,,,, -4, 7, 2, 7, 2, 2, 1, 2, 256, 240, 240, 240,,,, -4, 7, 2, 7, 2, 2, 1, 2, 384, 240, 240, 240,,,, -4, 7, 2, 7, 2, 2, 2, 1, 128, 240, 240, 240,,,, -4, 7, 2, 7, 2, 2, 2, 1, 256, 240, 240, 240,,,, -4, 7, 2, 7, 2, 2, 2, 1, 384, 240, 240, 240,,,, -4, 7, 2, 7, 2, 2, 2, 2, 128, 240, 240, 240,,,, -4, 7, 2, 7, 2, 2, 2, 2, 256, 240, 240, 240,,,, -4, 7, 2, 7, 2, 2, 2, 2, 384, 240, 240, 240,,,, -4, 7, 2, 7, 3, 3, 1, 1, 128, 240, 240, 240,,,, -4, 7, 2, 7, 3, 3, 1, 1, 256, 240, 240, 240,,,, -4, 7, 2, 7, 3, 3, 1, 1, 384, 240, 240, 240,,,, -4, 7, 2, 7, 3, 3, 1, 2, 128, 240, 240, 240,,,, -4, 7, 2, 7, 3, 3, 1, 2, 256, 240, 240, 240,,,, -4, 7, 2, 7, 3, 3, 1, 2, 384, 240, 240, 240,,,, -4, 7, 2, 7, 3, 3, 1, 3, 128, 240, 240, 240,,,, -4, 7, 2, 7, 3, 3, 1, 3, 256, 240, 240, 240,,,, -4, 7, 2, 7, 3, 3, 1, 3, 384, 240, 240, 240,,,, -4, 7, 2, 7, 3, 3, 2, 1, 128, 240, 240, 240,,,, -4, 7, 2, 7, 3, 3, 2, 1, 256, 240, 240, 240,,,, -4, 7, 2, 7, 3, 3, 2, 1, 384, 240, 240, 240,,,, -4, 7, 2, 7, 3, 3, 2, 2, 128, 240, 240, 240,,,, -4, 7, 2, 7, 3, 3, 2, 2, 256, 240, 240, 240,,,, -4, 7, 2, 7, 3, 3, 2, 2, 384, 240, 240, 240,,,, -4, 7, 2, 7, 3, 3, 2, 3, 128, 240, 240, 240,,,, -4, 7, 2, 7, 3, 3, 2, 3, 256, 240, 240, 240,,,, -4, 7, 2, 7, 3, 3, 2, 3, 384, 240, 240, 240,,,, -4, 7, 2, 7, 3, 3, 3, 1, 128, 240, 240, 240,,,, -4, 7, 2, 7, 3, 3, 3, 1, 256, 240, 240, 240,,,, -4, 7, 2, 7, 3, 3, 3, 1, 384, 240, 240, 240,,,, -4, 7, 2, 7, 3, 3, 3, 2, 128, 240, 240, 240,,,, -4, 7, 2, 7, 3, 3, 3, 2, 256, 240, 240, 240,,,, -4, 7, 2, 7, 3, 3, 3, 2, 384, 240, 240, 240,,,, -4, 7, 2, 7, 3, 3, 3, 3, 128, 240, 240, 240,,,, -4, 7, 2, 7, 3, 3, 3, 3, 256, 240, 240, 240,,,, -4, 7, 2, 7, 3, 3, 3, 3, 384, 240, 240, 240,,,, -4, 7, 3, 1, 1, 1, 1, 1, 128, 102, 102, 70,,,, -4, 7, 3, 1, 1, 1, 1, 1, 256, 102, 102, 70,,,, -4, 7, 3, 1, 1, 1, 1, 1, 384, 102, 102, 70,,,, -4, 7, 3, 1, 2, 2, 1, 1, 128, 102, 94, 69,,,, -4, 7, 3, 1, 2, 2, 1, 1, 256, 102, 94, 69,,,, -4, 7, 3, 1, 2, 2, 1, 1, 384, 102, 94, 69,,,, -4, 7, 3, 1, 2, 2, 1, 2, 128, 102, 94, 69,,,, -4, 7, 3, 1, 2, 2, 1, 2, 256, 102, 94, 69,,,, -4, 7, 3, 1, 2, 2, 1, 2, 384, 102, 94, 69,,,, -4, 7, 3, 1, 2, 2, 2, 1, 128, 102, 94, 69,,,, -4, 7, 3, 1, 2, 2, 2, 1, 256, 102, 94, 69,,,, -4, 7, 3, 1, 2, 2, 2, 1, 384, 102, 94, 69,,,, -4, 7, 3, 1, 2, 2, 2, 2, 128, 102, 94, 69,,,, -4, 7, 3, 1, 2, 2, 2, 2, 256, 102, 94, 69,,,, -4, 7, 3, 1, 2, 2, 2, 2, 384, 102, 94, 69,,,, -4, 7, 3, 1, 3, 3, 1, 1, 128, 101, 89, 66,,,, -4, 7, 3, 1, 3, 3, 1, 1, 256, 101, 89, 66,,,, -4, 7, 3, 1, 3, 3, 1, 1, 384, 101, 89, 66,,,, -4, 7, 3, 1, 3, 3, 1, 2, 128, 101, 89, 66,,,, -4, 7, 3, 1, 3, 3, 1, 2, 256, 101, 89, 66,,,, -4, 7, 3, 1, 3, 3, 1, 2, 384, 101, 89, 66,,,, -4, 7, 3, 1, 3, 3, 1, 3, 128, 101, 89, 66,,,, -4, 7, 3, 1, 3, 3, 1, 3, 256, 101, 89, 66,,,, -4, 7, 3, 1, 3, 3, 1, 3, 384, 101, 89, 66,,,, -4, 7, 3, 1, 3, 3, 2, 1, 128, 101, 89, 66,,,, -4, 7, 3, 1, 3, 3, 2, 1, 256, 101, 89, 66,,,, -4, 7, 3, 1, 3, 3, 2, 1, 384, 101, 89, 66,,,, -4, 7, 3, 1, 3, 3, 2, 2, 128, 101, 89, 66,,,, -4, 7, 3, 1, 3, 3, 2, 2, 256, 101, 89, 66,,,, -4, 7, 3, 1, 3, 3, 2, 2, 384, 101, 89, 66,,,, -4, 7, 3, 1, 3, 3, 2, 3, 128, 101, 89, 66,,,, -4, 7, 3, 1, 3, 3, 2, 3, 256, 101, 89, 66,,,, -4, 7, 3, 1, 3, 3, 2, 3, 384, 101, 89, 66,,,, -4, 7, 3, 1, 3, 3, 3, 1, 128, 101, 89, 66,,,, -4, 7, 3, 1, 3, 3, 3, 1, 256, 101, 89, 66,,,, -4, 7, 3, 1, 3, 3, 3, 1, 384, 101, 89, 66,,,, -4, 7, 3, 1, 3, 3, 3, 2, 128, 101, 89, 66,,,, -4, 7, 3, 1, 3, 3, 3, 2, 256, 101, 89, 66,,,, -4, 7, 3, 1, 3, 3, 3, 2, 384, 101, 89, 66,,,, -4, 7, 3, 1, 3, 3, 3, 3, 128, 101, 89, 66,,,, -4, 7, 3, 1, 3, 3, 3, 3, 256, 101, 89, 66,,,, -4, 7, 3, 1, 3, 3, 3, 3, 384, 101, 89, 66,,,, -4, 7, 3, 2, 1, 1, 1, 1, 128, 198, 198, 134,,,, -4, 7, 3, 2, 1, 1, 1, 1, 256, 198, 198, 134,,,, -4, 7, 3, 2, 1, 1, 1, 1, 384, 198, 198, 134,,,, -4, 7, 3, 2, 2, 2, 1, 1, 128, 198, 182, 132,,,, -4, 7, 3, 2, 2, 2, 1, 1, 256, 198, 182, 132,,,, -4, 7, 3, 2, 2, 2, 1, 1, 384, 198, 182, 132,,,, -4, 7, 3, 2, 2, 2, 1, 2, 128, 198, 182, 132,,,, -4, 7, 3, 2, 2, 2, 1, 2, 256, 198, 182, 132,,,, -4, 7, 3, 2, 2, 2, 1, 2, 384, 198, 182, 132,,,, -4, 7, 3, 2, 2, 2, 2, 1, 128, 198, 182, 132,,,, -4, 7, 3, 2, 2, 2, 2, 1, 256, 198, 182, 132,,,, -4, 7, 3, 2, 2, 2, 2, 1, 384, 198, 182, 132,,,, -4, 7, 3, 2, 2, 2, 2, 2, 128, 198, 182, 132,,,, -4, 7, 3, 2, 2, 2, 2, 2, 256, 198, 182, 132,,,, -4, 7, 3, 2, 2, 2, 2, 2, 384, 198, 182, 132,,,, -4, 7, 3, 2, 3, 3, 1, 1, 128, 196, 172, 126,,,, -4, 7, 3, 2, 3, 3, 1, 1, 256, 196, 172, 126,,,, -4, 7, 3, 2, 3, 3, 1, 1, 384, 196, 172, 126,,,, -4, 7, 3, 2, 3, 3, 1, 2, 128, 196, 172, 126,,,, -4, 7, 3, 2, 3, 3, 1, 2, 256, 196, 172, 126,,,, -4, 7, 3, 2, 3, 3, 1, 2, 384, 196, 172, 126,,,, -4, 7, 3, 2, 3, 3, 1, 3, 128, 196, 172, 126,,,, -4, 7, 3, 2, 3, 3, 1, 3, 256, 196, 172, 126,,,, -4, 7, 3, 2, 3, 3, 1, 3, 384, 196, 172, 126,,,, -4, 7, 3, 2, 3, 3, 2, 1, 128, 196, 172, 126,,,, -4, 7, 3, 2, 3, 3, 2, 1, 256, 196, 172, 126,,,, -4, 7, 3, 2, 3, 3, 2, 1, 384, 196, 172, 126,,,, -4, 7, 3, 2, 3, 3, 2, 2, 128, 196, 172, 126,,,, -4, 7, 3, 2, 3, 3, 2, 2, 256, 196, 172, 126,,,, -4, 7, 3, 2, 3, 3, 2, 2, 384, 196, 172, 126,,,, -4, 7, 3, 2, 3, 3, 2, 3, 128, 196, 172, 126,,,, -4, 7, 3, 2, 3, 3, 2, 3, 256, 196, 172, 126,,,, -4, 7, 3, 2, 3, 3, 2, 3, 384, 196, 172, 126,,,, -4, 7, 3, 2, 3, 3, 3, 1, 128, 196, 172, 126,,,, -4, 7, 3, 2, 3, 3, 3, 1, 256, 196, 172, 126,,,, -4, 7, 3, 2, 3, 3, 3, 1, 384, 196, 172, 126,,,, -4, 7, 3, 2, 3, 3, 3, 2, 128, 196, 172, 126,,,, -4, 7, 3, 2, 3, 3, 3, 2, 256, 196, 172, 126,,,, -4, 7, 3, 2, 3, 3, 3, 2, 384, 196, 172, 126,,,, -4, 7, 3, 2, 3, 3, 3, 3, 128, 196, 172, 126,,,, -4, 7, 3, 2, 3, 3, 3, 3, 256, 196, 172, 126,,,, -4, 7, 3, 2, 3, 3, 3, 3, 384, 196, 172, 126,,,, -4, 7, 3, 3, 1, 1, 1, 1, 128, 240, 240, 198,,,, -4, 7, 3, 3, 1, 1, 1, 1, 256, 240, 240, 198,,,, -4, 7, 3, 3, 1, 1, 1, 1, 384, 240, 240, 198,,,, -4, 7, 3, 3, 2, 2, 1, 1, 128, 240, 240, 195,,,, -4, 7, 3, 3, 2, 2, 1, 1, 256, 240, 240, 195,,,, -4, 7, 3, 3, 2, 2, 1, 1, 384, 240, 240, 195,,,, -4, 7, 3, 3, 2, 2, 1, 2, 128, 240, 240, 195,,,, -4, 7, 3, 3, 2, 2, 1, 2, 256, 240, 240, 195,,,, -4, 7, 3, 3, 2, 2, 1, 2, 384, 240, 240, 195,,,, -4, 7, 3, 3, 2, 2, 2, 1, 128, 240, 240, 195,,,, -4, 7, 3, 3, 2, 2, 2, 1, 256, 240, 240, 195,,,, -4, 7, 3, 3, 2, 2, 2, 1, 384, 240, 240, 195,,,, -4, 7, 3, 3, 2, 2, 2, 2, 128, 240, 240, 195,,,, -4, 7, 3, 3, 2, 2, 2, 2, 256, 240, 240, 195,,,, -4, 7, 3, 3, 2, 2, 2, 2, 384, 240, 240, 195,,,, -4, 7, 3, 3, 3, 3, 1, 1, 128, 240, 240, 186,,,, -4, 7, 3, 3, 3, 3, 1, 1, 256, 240, 240, 186,,,, -4, 7, 3, 3, 3, 3, 1, 1, 384, 240, 240, 186,,,, -4, 7, 3, 3, 3, 3, 1, 2, 128, 240, 240, 186,,,, -4, 7, 3, 3, 3, 3, 1, 2, 256, 240, 240, 186,,,, -4, 7, 3, 3, 3, 3, 1, 2, 384, 240, 240, 186,,,, -4, 7, 3, 3, 3, 3, 1, 3, 128, 240, 240, 186,,,, -4, 7, 3, 3, 3, 3, 1, 3, 256, 240, 240, 186,,,, -4, 7, 3, 3, 3, 3, 1, 3, 384, 240, 240, 186,,,, -4, 7, 3, 3, 3, 3, 2, 1, 128, 240, 240, 186,,,, -4, 7, 3, 3, 3, 3, 2, 1, 256, 240, 240, 186,,,, -4, 7, 3, 3, 3, 3, 2, 1, 384, 240, 240, 186,,,, -4, 7, 3, 3, 3, 3, 2, 2, 128, 240, 240, 186,,,, -4, 7, 3, 3, 3, 3, 2, 2, 256, 240, 240, 186,,,, -4, 7, 3, 3, 3, 3, 2, 2, 384, 240, 240, 186,,,, -4, 7, 3, 3, 3, 3, 2, 3, 128, 240, 240, 186,,,, -4, 7, 3, 3, 3, 3, 2, 3, 256, 240, 240, 186,,,, -4, 7, 3, 3, 3, 3, 2, 3, 384, 240, 240, 186,,,, -4, 7, 3, 3, 3, 3, 3, 1, 128, 240, 240, 186,,,, -4, 7, 3, 3, 3, 3, 3, 1, 256, 240, 240, 186,,,, -4, 7, 3, 3, 3, 3, 3, 1, 384, 240, 240, 186,,,, -4, 7, 3, 3, 3, 3, 3, 2, 128, 240, 240, 186,,,, -4, 7, 3, 3, 3, 3, 3, 2, 256, 240, 240, 186,,,, -4, 7, 3, 3, 3, 3, 3, 2, 384, 240, 240, 186,,,, -4, 7, 3, 3, 3, 3, 3, 3, 128, 240, 240, 186,,,, -4, 7, 3, 3, 3, 3, 3, 3, 256, 240, 240, 186,,,, -4, 7, 3, 3, 3, 3, 3, 3, 384, 240, 240, 186,,,, -4, 7, 3, 4, 1, 1, 1, 1, 128, 240, 240, 240,,,, -4, 7, 3, 4, 1, 1, 1, 1, 256, 240, 240, 240,,,, -4, 7, 3, 4, 1, 1, 1, 1, 384, 240, 240, 240,,,, -4, 7, 3, 4, 2, 2, 1, 1, 128, 240, 240, 240,,,, -4, 7, 3, 4, 2, 2, 1, 1, 256, 240, 240, 240,,,, -4, 7, 3, 4, 2, 2, 1, 1, 384, 240, 240, 240,,,, -4, 7, 3, 4, 2, 2, 1, 2, 128, 240, 240, 240,,,, -4, 7, 3, 4, 2, 2, 1, 2, 256, 240, 240, 240,,,, -4, 7, 3, 4, 2, 2, 1, 2, 384, 240, 240, 240,,,, -4, 7, 3, 4, 2, 2, 2, 1, 128, 240, 240, 240,,,, -4, 7, 3, 4, 2, 2, 2, 1, 256, 240, 240, 240,,,, -4, 7, 3, 4, 2, 2, 2, 1, 384, 240, 240, 240,,,, -4, 7, 3, 4, 2, 2, 2, 2, 128, 240, 240, 240,,,, -4, 7, 3, 4, 2, 2, 2, 2, 256, 240, 240, 240,,,, -4, 7, 3, 4, 2, 2, 2, 2, 384, 240, 240, 240,,,, -4, 7, 3, 4, 3, 3, 1, 1, 128, 240, 240, 240,,,, -4, 7, 3, 4, 3, 3, 1, 1, 256, 240, 240, 240,,,, -4, 7, 3, 4, 3, 3, 1, 1, 384, 240, 240, 240,,,, -4, 7, 3, 4, 3, 3, 1, 2, 128, 240, 240, 240,,,, -4, 7, 3, 4, 3, 3, 1, 2, 256, 240, 240, 240,,,, -4, 7, 3, 4, 3, 3, 1, 2, 384, 240, 240, 240,,,, -4, 7, 3, 4, 3, 3, 1, 3, 128, 240, 240, 240,,,, -4, 7, 3, 4, 3, 3, 1, 3, 256, 240, 240, 240,,,, -4, 7, 3, 4, 3, 3, 1, 3, 384, 240, 240, 240,,,, -4, 7, 3, 4, 3, 3, 2, 1, 128, 240, 240, 240,,,, -4, 7, 3, 4, 3, 3, 2, 1, 256, 240, 240, 240,,,, -4, 7, 3, 4, 3, 3, 2, 1, 384, 240, 240, 240,,,, -4, 7, 3, 4, 3, 3, 2, 2, 128, 240, 240, 240,,,, -4, 7, 3, 4, 3, 3, 2, 2, 256, 240, 240, 240,,,, -4, 7, 3, 4, 3, 3, 2, 2, 384, 240, 240, 240,,,, -4, 7, 3, 4, 3, 3, 2, 3, 128, 240, 240, 240,,,, -4, 7, 3, 4, 3, 3, 2, 3, 256, 240, 240, 240,,,, -4, 7, 3, 4, 3, 3, 2, 3, 384, 240, 240, 240,,,, -4, 7, 3, 4, 3, 3, 3, 1, 128, 240, 240, 240,,,, -4, 7, 3, 4, 3, 3, 3, 1, 256, 240, 240, 240,,,, -4, 7, 3, 4, 3, 3, 3, 1, 384, 240, 240, 240,,,, -4, 7, 3, 4, 3, 3, 3, 2, 128, 240, 240, 240,,,, -4, 7, 3, 4, 3, 3, 3, 2, 256, 240, 240, 240,,,, -4, 7, 3, 4, 3, 3, 3, 2, 384, 240, 240, 240,,,, -4, 7, 3, 4, 3, 3, 3, 3, 128, 240, 240, 240,,,, -4, 7, 3, 4, 3, 3, 3, 3, 256, 240, 240, 240,,,, -4, 7, 3, 4, 3, 3, 3, 3, 384, 240, 240, 240,,,, -4, 7, 3, 5, 1, 1, 1, 1, 128, 240, 240, 240,,,, -4, 7, 3, 5, 1, 1, 1, 1, 256, 240, 240, 240,,,, -4, 7, 3, 5, 1, 1, 1, 1, 384, 240, 240, 240,,,, -4, 7, 3, 5, 2, 2, 1, 1, 128, 240, 240, 240,,,, -4, 7, 3, 5, 2, 2, 1, 1, 256, 240, 240, 240,,,, -4, 7, 3, 5, 2, 2, 1, 1, 384, 240, 240, 240,,,, -4, 7, 3, 5, 2, 2, 1, 2, 128, 240, 240, 240,,,, -4, 7, 3, 5, 2, 2, 1, 2, 256, 240, 240, 240,,,, -4, 7, 3, 5, 2, 2, 1, 2, 384, 240, 240, 240,,,, -4, 7, 3, 5, 2, 2, 2, 1, 128, 240, 240, 240,,,, -4, 7, 3, 5, 2, 2, 2, 1, 256, 240, 240, 240,,,, -4, 7, 3, 5, 2, 2, 2, 1, 384, 240, 240, 240,,,, -4, 7, 3, 5, 2, 2, 2, 2, 128, 240, 240, 240,,,, -4, 7, 3, 5, 2, 2, 2, 2, 256, 240, 240, 240,,,, -4, 7, 3, 5, 2, 2, 2, 2, 384, 240, 240, 240,,,, -4, 7, 3, 5, 3, 3, 1, 1, 128, 240, 240, 240,,,, -4, 7, 3, 5, 3, 3, 1, 1, 256, 240, 240, 240,,,, -4, 7, 3, 5, 3, 3, 1, 1, 384, 240, 240, 240,,,, -4, 7, 3, 5, 3, 3, 1, 2, 128, 240, 240, 240,,,, -4, 7, 3, 5, 3, 3, 1, 2, 256, 240, 240, 240,,,, -4, 7, 3, 5, 3, 3, 1, 2, 384, 240, 240, 240,,,, -4, 7, 3, 5, 3, 3, 1, 3, 128, 240, 240, 240,,,, -4, 7, 3, 5, 3, 3, 1, 3, 256, 240, 240, 240,,,, -4, 7, 3, 5, 3, 3, 1, 3, 384, 240, 240, 240,,,, -4, 7, 3, 5, 3, 3, 2, 1, 128, 240, 240, 240,,,, -4, 7, 3, 5, 3, 3, 2, 1, 256, 240, 240, 240,,,, -4, 7, 3, 5, 3, 3, 2, 1, 384, 240, 240, 240,,,, -4, 7, 3, 5, 3, 3, 2, 2, 128, 240, 240, 240,,,, -4, 7, 3, 5, 3, 3, 2, 2, 256, 240, 240, 240,,,, -4, 7, 3, 5, 3, 3, 2, 2, 384, 240, 240, 240,,,, -4, 7, 3, 5, 3, 3, 2, 3, 128, 240, 240, 240,,,, -4, 7, 3, 5, 3, 3, 2, 3, 256, 240, 240, 240,,,, -4, 7, 3, 5, 3, 3, 2, 3, 384, 240, 240, 240,,,, -4, 7, 3, 5, 3, 3, 3, 1, 128, 240, 240, 240,,,, -4, 7, 3, 5, 3, 3, 3, 1, 256, 240, 240, 240,,,, -4, 7, 3, 5, 3, 3, 3, 1, 384, 240, 240, 240,,,, -4, 7, 3, 5, 3, 3, 3, 2, 128, 240, 240, 240,,,, -4, 7, 3, 5, 3, 3, 3, 2, 256, 240, 240, 240,,,, -4, 7, 3, 5, 3, 3, 3, 2, 384, 240, 240, 240,,,, -4, 7, 3, 5, 3, 3, 3, 3, 128, 240, 240, 240,,,, -4, 7, 3, 5, 3, 3, 3, 3, 256, 240, 240, 240,,,, -4, 7, 3, 5, 3, 3, 3, 3, 384, 240, 240, 240,,,, -4, 7, 3, 6, 1, 1, 1, 1, 128, 240, 240, 240,,,, -4, 7, 3, 6, 1, 1, 1, 1, 256, 240, 240, 240,,,, -4, 7, 3, 6, 1, 1, 1, 1, 384, 240, 240, 240,,,, -4, 7, 3, 6, 2, 2, 1, 1, 128, 240, 240, 240,,,, -4, 7, 3, 6, 2, 2, 1, 1, 256, 240, 240, 240,,,, -4, 7, 3, 6, 2, 2, 1, 1, 384, 240, 240, 240,,,, -4, 7, 3, 6, 2, 2, 1, 2, 128, 240, 240, 240,,,, -4, 7, 3, 6, 2, 2, 1, 2, 256, 240, 240, 240,,,, -4, 7, 3, 6, 2, 2, 1, 2, 384, 240, 240, 240,,,, -4, 7, 3, 6, 2, 2, 2, 1, 128, 240, 240, 240,,,, -4, 7, 3, 6, 2, 2, 2, 1, 256, 240, 240, 240,,,, -4, 7, 3, 6, 2, 2, 2, 1, 384, 240, 240, 240,,,, -4, 7, 3, 6, 2, 2, 2, 2, 128, 240, 240, 240,,,, -4, 7, 3, 6, 2, 2, 2, 2, 256, 240, 240, 240,,,, -4, 7, 3, 6, 2, 2, 2, 2, 384, 240, 240, 240,,,, -4, 7, 3, 6, 3, 3, 1, 1, 128, 240, 240, 240,,,, -4, 7, 3, 6, 3, 3, 1, 1, 256, 240, 240, 240,,,, -4, 7, 3, 6, 3, 3, 1, 1, 384, 240, 240, 240,,,, -4, 7, 3, 6, 3, 3, 1, 2, 128, 240, 240, 240,,,, -4, 7, 3, 6, 3, 3, 1, 2, 256, 240, 240, 240,,,, -4, 7, 3, 6, 3, 3, 1, 2, 384, 240, 240, 240,,,, -4, 7, 3, 6, 3, 3, 1, 3, 128, 240, 240, 240,,,, -4, 7, 3, 6, 3, 3, 1, 3, 256, 240, 240, 240,,,, -4, 7, 3, 6, 3, 3, 1, 3, 384, 240, 240, 240,,,, -4, 7, 3, 6, 3, 3, 2, 1, 128, 240, 240, 240,,,, -4, 7, 3, 6, 3, 3, 2, 1, 256, 240, 240, 240,,,, -4, 7, 3, 6, 3, 3, 2, 1, 384, 240, 240, 240,,,, -4, 7, 3, 6, 3, 3, 2, 2, 128, 240, 240, 240,,,, -4, 7, 3, 6, 3, 3, 2, 2, 256, 240, 240, 240,,,, -4, 7, 3, 6, 3, 3, 2, 2, 384, 240, 240, 240,,,, -4, 7, 3, 6, 3, 3, 2, 3, 128, 240, 240, 240,,,, -4, 7, 3, 6, 3, 3, 2, 3, 256, 240, 240, 240,,,, -4, 7, 3, 6, 3, 3, 2, 3, 384, 240, 240, 240,,,, -4, 7, 3, 6, 3, 3, 3, 1, 128, 240, 240, 240,,,, -4, 7, 3, 6, 3, 3, 3, 1, 256, 240, 240, 240,,,, -4, 7, 3, 6, 3, 3, 3, 1, 384, 240, 240, 240,,,, -4, 7, 3, 6, 3, 3, 3, 2, 128, 240, 240, 240,,,, -4, 7, 3, 6, 3, 3, 3, 2, 256, 240, 240, 240,,,, -4, 7, 3, 6, 3, 3, 3, 2, 384, 240, 240, 240,,,, -4, 7, 3, 6, 3, 3, 3, 3, 128, 240, 240, 240,,,, -4, 7, 3, 6, 3, 3, 3, 3, 256, 240, 240, 240,,,, -4, 7, 3, 6, 3, 3, 3, 3, 384, 240, 240, 240,,,, -4, 7, 3, 7, 1, 1, 1, 1, 128, 240, 240, 240,,,, -4, 7, 3, 7, 1, 1, 1, 1, 256, 240, 240, 240,,,, -4, 7, 3, 7, 1, 1, 1, 1, 384, 240, 240, 240,,,, -4, 7, 3, 7, 2, 2, 1, 1, 128, 240, 240, 240,,,, -4, 7, 3, 7, 2, 2, 1, 1, 256, 240, 240, 240,,,, -4, 7, 3, 7, 2, 2, 1, 1, 384, 240, 240, 240,,,, -4, 7, 3, 7, 2, 2, 1, 2, 128, 240, 240, 240,,,, -4, 7, 3, 7, 2, 2, 1, 2, 256, 240, 240, 240,,,, -4, 7, 3, 7, 2, 2, 1, 2, 384, 240, 240, 240,,,, -4, 7, 3, 7, 2, 2, 2, 1, 128, 240, 240, 240,,,, -4, 7, 3, 7, 2, 2, 2, 1, 256, 240, 240, 240,,,, -4, 7, 3, 7, 2, 2, 2, 1, 384, 240, 240, 240,,,, -4, 7, 3, 7, 2, 2, 2, 2, 128, 240, 240, 240,,,, -4, 7, 3, 7, 2, 2, 2, 2, 256, 240, 240, 240,,,, -4, 7, 3, 7, 2, 2, 2, 2, 384, 240, 240, 240,,,, -4, 7, 3, 7, 3, 3, 1, 1, 128, 240, 240, 240,,,, -4, 7, 3, 7, 3, 3, 1, 1, 256, 240, 240, 240,,,, -4, 7, 3, 7, 3, 3, 1, 1, 384, 240, 240, 240,,,, -4, 7, 3, 7, 3, 3, 1, 2, 128, 240, 240, 240,,,, -4, 7, 3, 7, 3, 3, 1, 2, 256, 240, 240, 240,,,, -4, 7, 3, 7, 3, 3, 1, 2, 384, 240, 240, 240,,,, -4, 7, 3, 7, 3, 3, 1, 3, 128, 240, 240, 240,,,, -4, 7, 3, 7, 3, 3, 1, 3, 256, 240, 240, 240,,,, -4, 7, 3, 7, 3, 3, 1, 3, 384, 240, 240, 240,,,, -4, 7, 3, 7, 3, 3, 2, 1, 128, 240, 240, 240,,,, -4, 7, 3, 7, 3, 3, 2, 1, 256, 240, 240, 240,,,, -4, 7, 3, 7, 3, 3, 2, 1, 384, 240, 240, 240,,,, -4, 7, 3, 7, 3, 3, 2, 2, 128, 240, 240, 240,,,, -4, 7, 3, 7, 3, 3, 2, 2, 256, 240, 240, 240,,,, -4, 7, 3, 7, 3, 3, 2, 2, 384, 240, 240, 240,,,, -4, 7, 3, 7, 3, 3, 2, 3, 128, 240, 240, 240,,,, -4, 7, 3, 7, 3, 3, 2, 3, 256, 240, 240, 240,,,, -4, 7, 3, 7, 3, 3, 2, 3, 384, 240, 240, 240,,,, -4, 7, 3, 7, 3, 3, 3, 1, 128, 240, 240, 240,,,, -4, 7, 3, 7, 3, 3, 3, 1, 256, 240, 240, 240,,,, -4, 7, 3, 7, 3, 3, 3, 1, 384, 240, 240, 240,,,, -4, 7, 3, 7, 3, 3, 3, 2, 128, 240, 240, 240,,,, -4, 7, 3, 7, 3, 3, 3, 2, 256, 240, 240, 240,,,, -4, 7, 3, 7, 3, 3, 3, 2, 384, 240, 240, 240,,,, -4, 7, 3, 7, 3, 3, 3, 3, 128, 240, 240, 240,,,, -4, 7, 3, 7, 3, 3, 3, 3, 256, 240, 240, 240,,,, -4, 7, 3, 7, 3, 3, 3, 3, 384, 240, 240, 240,,,, -4, 7, 4, 1, 1, 1, 1, 1, 128, 102, 102, 70,,,, -4, 7, 4, 1, 1, 1, 1, 1, 256, 102, 102, 70,,,, -4, 7, 4, 1, 1, 1, 1, 1, 384, 102, 102, 70,,,, -4, 7, 4, 1, 2, 2, 1, 1, 128, 102, 94, 69,,,, -4, 7, 4, 1, 2, 2, 1, 1, 256, 102, 94, 69,,,, -4, 7, 4, 1, 2, 2, 1, 1, 384, 102, 94, 69,,,, -4, 7, 4, 1, 2, 2, 1, 2, 128, 102, 94, 69,,,, -4, 7, 4, 1, 2, 2, 1, 2, 256, 102, 94, 69,,,, -4, 7, 4, 1, 2, 2, 1, 2, 384, 102, 94, 69,,,, -4, 7, 4, 1, 2, 2, 2, 1, 128, 102, 94, 69,,,, -4, 7, 4, 1, 2, 2, 2, 1, 256, 102, 94, 69,,,, -4, 7, 4, 1, 2, 2, 2, 1, 384, 102, 94, 69,,,, -4, 7, 4, 1, 2, 2, 2, 2, 128, 102, 94, 69,,,, -4, 7, 4, 1, 2, 2, 2, 2, 256, 102, 94, 69,,,, -4, 7, 4, 1, 2, 2, 2, 2, 384, 102, 94, 69,,,, -4, 7, 4, 1, 3, 3, 1, 1, 128, 101, 89, 66,,,, -4, 7, 4, 1, 3, 3, 1, 1, 256, 101, 89, 66,,,, -4, 7, 4, 1, 3, 3, 1, 1, 384, 101, 89, 66,,,, -4, 7, 4, 1, 3, 3, 1, 2, 128, 101, 89, 66,,,, -4, 7, 4, 1, 3, 3, 1, 2, 256, 101, 89, 66,,,, -4, 7, 4, 1, 3, 3, 1, 2, 384, 101, 89, 66,,,, -4, 7, 4, 1, 3, 3, 1, 3, 128, 101, 89, 66,,,, -4, 7, 4, 1, 3, 3, 1, 3, 256, 101, 89, 66,,,, -4, 7, 4, 1, 3, 3, 1, 3, 384, 101, 89, 66,,,, -4, 7, 4, 1, 3, 3, 2, 1, 128, 101, 89, 66,,,, -4, 7, 4, 1, 3, 3, 2, 1, 256, 101, 89, 66,,,, -4, 7, 4, 1, 3, 3, 2, 1, 384, 101, 89, 66,,,, -4, 7, 4, 1, 3, 3, 2, 2, 128, 101, 89, 66,,,, -4, 7, 4, 1, 3, 3, 2, 2, 256, 101, 89, 66,,,, -4, 7, 4, 1, 3, 3, 2, 2, 384, 101, 89, 66,,,, -4, 7, 4, 1, 3, 3, 2, 3, 128, 101, 89, 66,,,, -4, 7, 4, 1, 3, 3, 2, 3, 256, 101, 89, 66,,,, -4, 7, 4, 1, 3, 3, 2, 3, 384, 101, 89, 66,,,, -4, 7, 4, 1, 3, 3, 3, 1, 128, 101, 89, 66,,,, -4, 7, 4, 1, 3, 3, 3, 1, 256, 101, 89, 66,,,, -4, 7, 4, 1, 3, 3, 3, 1, 384, 101, 89, 66,,,, -4, 7, 4, 1, 3, 3, 3, 2, 128, 101, 89, 66,,,, -4, 7, 4, 1, 3, 3, 3, 2, 256, 101, 89, 66,,,, -4, 7, 4, 1, 3, 3, 3, 2, 384, 101, 89, 66,,,, -4, 7, 4, 1, 3, 3, 3, 3, 128, 101, 89, 66,,,, -4, 7, 4, 1, 3, 3, 3, 3, 256, 101, 89, 66,,,, -4, 7, 4, 1, 3, 3, 3, 3, 384, 101, 89, 66,,,, -4, 7, 4, 2, 1, 1, 1, 1, 128, 198, 198, 134,,,, -4, 7, 4, 2, 1, 1, 1, 1, 256, 198, 198, 134,,,, -4, 7, 4, 2, 1, 1, 1, 1, 384, 198, 198, 134,,,, -4, 7, 4, 2, 2, 2, 1, 1, 128, 198, 182, 132,,,, -4, 7, 4, 2, 2, 2, 1, 1, 256, 198, 182, 132,,,, -4, 7, 4, 2, 2, 2, 1, 1, 384, 198, 182, 132,,,, -4, 7, 4, 2, 2, 2, 1, 2, 128, 198, 182, 132,,,, -4, 7, 4, 2, 2, 2, 1, 2, 256, 198, 182, 132,,,, -4, 7, 4, 2, 2, 2, 1, 2, 384, 198, 182, 132,,,, -4, 7, 4, 2, 2, 2, 2, 1, 128, 198, 182, 132,,,, -4, 7, 4, 2, 2, 2, 2, 1, 256, 198, 182, 132,,,, -4, 7, 4, 2, 2, 2, 2, 1, 384, 198, 182, 132,,,, -4, 7, 4, 2, 2, 2, 2, 2, 128, 198, 182, 132,,,, -4, 7, 4, 2, 2, 2, 2, 2, 256, 198, 182, 132,,,, -4, 7, 4, 2, 2, 2, 2, 2, 384, 198, 182, 132,,,, -4, 7, 4, 2, 3, 3, 1, 1, 128, 196, 172, 126,,,, -4, 7, 4, 2, 3, 3, 1, 1, 256, 196, 172, 126,,,, -4, 7, 4, 2, 3, 3, 1, 1, 384, 196, 172, 126,,,, -4, 7, 4, 2, 3, 3, 1, 2, 128, 196, 172, 126,,,, -4, 7, 4, 2, 3, 3, 1, 2, 256, 196, 172, 126,,,, -4, 7, 4, 2, 3, 3, 1, 2, 384, 196, 172, 126,,,, -4, 7, 4, 2, 3, 3, 1, 3, 128, 196, 172, 126,,,, -4, 7, 4, 2, 3, 3, 1, 3, 256, 196, 172, 126,,,, -4, 7, 4, 2, 3, 3, 1, 3, 384, 196, 172, 126,,,, -4, 7, 4, 2, 3, 3, 2, 1, 128, 196, 172, 126,,,, -4, 7, 4, 2, 3, 3, 2, 1, 256, 196, 172, 126,,,, -4, 7, 4, 2, 3, 3, 2, 1, 384, 196, 172, 126,,,, -4, 7, 4, 2, 3, 3, 2, 2, 128, 196, 172, 126,,,, -4, 7, 4, 2, 3, 3, 2, 2, 256, 196, 172, 126,,,, -4, 7, 4, 2, 3, 3, 2, 2, 384, 196, 172, 126,,,, -4, 7, 4, 2, 3, 3, 2, 3, 128, 196, 172, 126,,,, -4, 7, 4, 2, 3, 3, 2, 3, 256, 196, 172, 126,,,, -4, 7, 4, 2, 3, 3, 2, 3, 384, 196, 172, 126,,,, -4, 7, 4, 2, 3, 3, 3, 1, 128, 196, 172, 126,,,, -4, 7, 4, 2, 3, 3, 3, 1, 256, 196, 172, 126,,,, -4, 7, 4, 2, 3, 3, 3, 1, 384, 196, 172, 126,,,, -4, 7, 4, 2, 3, 3, 3, 2, 128, 196, 172, 126,,,, -4, 7, 4, 2, 3, 3, 3, 2, 256, 196, 172, 126,,,, -4, 7, 4, 2, 3, 3, 3, 2, 384, 196, 172, 126,,,, -4, 7, 4, 2, 3, 3, 3, 3, 128, 196, 172, 126,,,, -4, 7, 4, 2, 3, 3, 3, 3, 256, 196, 172, 126,,,, -4, 7, 4, 2, 3, 3, 3, 3, 384, 196, 172, 126,,,, -4, 7, 4, 3, 1, 1, 1, 1, 128, 240, 240, 198,,,, -4, 7, 4, 3, 1, 1, 1, 1, 256, 240, 240, 198,,,, -4, 7, 4, 3, 1, 1, 1, 1, 384, 240, 240, 198,,,, -4, 7, 4, 3, 2, 2, 1, 1, 128, 240, 240, 195,,,, -4, 7, 4, 3, 2, 2, 1, 1, 256, 240, 240, 195,,,, -4, 7, 4, 3, 2, 2, 1, 1, 384, 240, 240, 195,,,, -4, 7, 4, 3, 2, 2, 1, 2, 128, 240, 240, 195,,,, -4, 7, 4, 3, 2, 2, 1, 2, 256, 240, 240, 195,,,, -4, 7, 4, 3, 2, 2, 1, 2, 384, 240, 240, 195,,,, -4, 7, 4, 3, 2, 2, 2, 1, 128, 240, 240, 195,,,, -4, 7, 4, 3, 2, 2, 2, 1, 256, 240, 240, 195,,,, -4, 7, 4, 3, 2, 2, 2, 1, 384, 240, 240, 195,,,, -4, 7, 4, 3, 2, 2, 2, 2, 128, 240, 240, 195,,,, -4, 7, 4, 3, 2, 2, 2, 2, 256, 240, 240, 195,,,, -4, 7, 4, 3, 2, 2, 2, 2, 384, 240, 240, 195,,,, -4, 7, 4, 3, 3, 3, 1, 1, 128, 240, 240, 186,,,, -4, 7, 4, 3, 3, 3, 1, 1, 256, 240, 240, 186,,,, -4, 7, 4, 3, 3, 3, 1, 1, 384, 240, 240, 186,,,, -4, 7, 4, 3, 3, 3, 1, 2, 128, 240, 240, 186,,,, -4, 7, 4, 3, 3, 3, 1, 2, 256, 240, 240, 186,,,, -4, 7, 4, 3, 3, 3, 1, 2, 384, 240, 240, 186,,,, -4, 7, 4, 3, 3, 3, 1, 3, 128, 240, 240, 186,,,, -4, 7, 4, 3, 3, 3, 1, 3, 256, 240, 240, 186,,,, -4, 7, 4, 3, 3, 3, 1, 3, 384, 240, 240, 186,,,, -4, 7, 4, 3, 3, 3, 2, 1, 128, 240, 240, 186,,,, -4, 7, 4, 3, 3, 3, 2, 1, 256, 240, 240, 186,,,, -4, 7, 4, 3, 3, 3, 2, 1, 384, 240, 240, 186,,,, -4, 7, 4, 3, 3, 3, 2, 2, 128, 240, 240, 186,,,, -4, 7, 4, 3, 3, 3, 2, 2, 256, 240, 240, 186,,,, -4, 7, 4, 3, 3, 3, 2, 2, 384, 240, 240, 186,,,, -4, 7, 4, 3, 3, 3, 2, 3, 128, 240, 240, 186,,,, -4, 7, 4, 3, 3, 3, 2, 3, 256, 240, 240, 186,,,, -4, 7, 4, 3, 3, 3, 2, 3, 384, 240, 240, 186,,,, -4, 7, 4, 3, 3, 3, 3, 1, 128, 240, 240, 186,,,, -4, 7, 4, 3, 3, 3, 3, 1, 256, 240, 240, 186,,,, -4, 7, 4, 3, 3, 3, 3, 1, 384, 240, 240, 186,,,, -4, 7, 4, 3, 3, 3, 3, 2, 128, 240, 240, 186,,,, -4, 7, 4, 3, 3, 3, 3, 2, 256, 240, 240, 186,,,, -4, 7, 4, 3, 3, 3, 3, 2, 384, 240, 240, 186,,,, -4, 7, 4, 3, 3, 3, 3, 3, 128, 240, 240, 186,,,, -4, 7, 4, 3, 3, 3, 3, 3, 256, 240, 240, 186,,,, -4, 7, 4, 3, 3, 3, 3, 3, 384, 240, 240, 186,,,, -4, 7, 4, 4, 1, 1, 1, 1, 128, 240, 240, 240,,,, -4, 7, 4, 4, 1, 1, 1, 1, 256, 240, 240, 240,,,, -4, 7, 4, 4, 1, 1, 1, 1, 384, 240, 240, 240,,,, -4, 7, 4, 4, 2, 2, 1, 1, 128, 240, 240, 240,,,, -4, 7, 4, 4, 2, 2, 1, 1, 256, 240, 240, 240,,,, -4, 7, 4, 4, 2, 2, 1, 1, 384, 240, 240, 240,,,, -4, 7, 4, 4, 2, 2, 1, 2, 128, 240, 240, 240,,,, -4, 7, 4, 4, 2, 2, 1, 2, 256, 240, 240, 240,,,, -4, 7, 4, 4, 2, 2, 1, 2, 384, 240, 240, 240,,,, -4, 7, 4, 4, 2, 2, 2, 1, 128, 240, 240, 240,,,, -4, 7, 4, 4, 2, 2, 2, 1, 256, 240, 240, 240,,,, -4, 7, 4, 4, 2, 2, 2, 1, 384, 240, 240, 240,,,, -4, 7, 4, 4, 2, 2, 2, 2, 128, 240, 240, 240,,,, -4, 7, 4, 4, 2, 2, 2, 2, 256, 240, 240, 240,,,, -4, 7, 4, 4, 2, 2, 2, 2, 384, 240, 240, 240,,,, -4, 7, 4, 4, 3, 3, 1, 1, 128, 240, 240, 240,,,, -4, 7, 4, 4, 3, 3, 1, 1, 256, 240, 240, 240,,,, -4, 7, 4, 4, 3, 3, 1, 1, 384, 240, 240, 240,,,, -4, 7, 4, 4, 3, 3, 1, 2, 128, 240, 240, 240,,,, -4, 7, 4, 4, 3, 3, 1, 2, 256, 240, 240, 240,,,, -4, 7, 4, 4, 3, 3, 1, 2, 384, 240, 240, 240,,,, -4, 7, 4, 4, 3, 3, 1, 3, 128, 240, 240, 240,,,, -4, 7, 4, 4, 3, 3, 1, 3, 256, 240, 240, 240,,,, -4, 7, 4, 4, 3, 3, 1, 3, 384, 240, 240, 240,,,, -4, 7, 4, 4, 3, 3, 2, 1, 128, 240, 240, 240,,,, -4, 7, 4, 4, 3, 3, 2, 1, 256, 240, 240, 240,,,, -4, 7, 4, 4, 3, 3, 2, 1, 384, 240, 240, 240,,,, -4, 7, 4, 4, 3, 3, 2, 2, 128, 240, 240, 240,,,, -4, 7, 4, 4, 3, 3, 2, 2, 256, 240, 240, 240,,,, -4, 7, 4, 4, 3, 3, 2, 2, 384, 240, 240, 240,,,, -4, 7, 4, 4, 3, 3, 2, 3, 128, 240, 240, 240,,,, -4, 7, 4, 4, 3, 3, 2, 3, 256, 240, 240, 240,,,, -4, 7, 4, 4, 3, 3, 2, 3, 384, 240, 240, 240,,,, -4, 7, 4, 4, 3, 3, 3, 1, 128, 240, 240, 240,,,, -4, 7, 4, 4, 3, 3, 3, 1, 256, 240, 240, 240,,,, -4, 7, 4, 4, 3, 3, 3, 1, 384, 240, 240, 240,,,, -4, 7, 4, 4, 3, 3, 3, 2, 128, 240, 240, 240,,,, -4, 7, 4, 4, 3, 3, 3, 2, 256, 240, 240, 240,,,, -4, 7, 4, 4, 3, 3, 3, 2, 384, 240, 240, 240,,,, -4, 7, 4, 4, 3, 3, 3, 3, 128, 240, 240, 240,,,, -4, 7, 4, 4, 3, 3, 3, 3, 256, 240, 240, 240,,,, -4, 7, 4, 4, 3, 3, 3, 3, 384, 240, 240, 240,,,, -4, 7, 4, 5, 1, 1, 1, 1, 128, 240, 240, 240,,,, -4, 7, 4, 5, 1, 1, 1, 1, 256, 240, 240, 240,,,, -4, 7, 4, 5, 1, 1, 1, 1, 384, 240, 240, 240,,,, -4, 7, 4, 5, 2, 2, 1, 1, 128, 240, 240, 240,,,, -4, 7, 4, 5, 2, 2, 1, 1, 256, 240, 240, 240,,,, -4, 7, 4, 5, 2, 2, 1, 1, 384, 240, 240, 240,,,, -4, 7, 4, 5, 2, 2, 1, 2, 128, 240, 240, 240,,,, -4, 7, 4, 5, 2, 2, 1, 2, 256, 240, 240, 240,,,, -4, 7, 4, 5, 2, 2, 1, 2, 384, 240, 240, 240,,,, -4, 7, 4, 5, 2, 2, 2, 1, 128, 240, 240, 240,,,, -4, 7, 4, 5, 2, 2, 2, 1, 256, 240, 240, 240,,,, -4, 7, 4, 5, 2, 2, 2, 1, 384, 240, 240, 240,,,, -4, 7, 4, 5, 2, 2, 2, 2, 128, 240, 240, 240,,,, -4, 7, 4, 5, 2, 2, 2, 2, 256, 240, 240, 240,,,, -4, 7, 4, 5, 2, 2, 2, 2, 384, 240, 240, 240,,,, -4, 7, 4, 5, 3, 3, 1, 1, 128, 240, 240, 240,,,, -4, 7, 4, 5, 3, 3, 1, 1, 256, 240, 240, 240,,,, -4, 7, 4, 5, 3, 3, 1, 1, 384, 240, 240, 240,,,, -4, 7, 4, 5, 3, 3, 1, 2, 128, 240, 240, 240,,,, -4, 7, 4, 5, 3, 3, 1, 2, 256, 240, 240, 240,,,, -4, 7, 4, 5, 3, 3, 1, 2, 384, 240, 240, 240,,,, -4, 7, 4, 5, 3, 3, 1, 3, 128, 240, 240, 240,,,, -4, 7, 4, 5, 3, 3, 1, 3, 256, 240, 240, 240,,,, -4, 7, 4, 5, 3, 3, 1, 3, 384, 240, 240, 240,,,, -4, 7, 4, 5, 3, 3, 2, 1, 128, 240, 240, 240,,,, -4, 7, 4, 5, 3, 3, 2, 1, 256, 240, 240, 240,,,, -4, 7, 4, 5, 3, 3, 2, 1, 384, 240, 240, 240,,,, -4, 7, 4, 5, 3, 3, 2, 2, 128, 240, 240, 240,,,, -4, 7, 4, 5, 3, 3, 2, 2, 256, 240, 240, 240,,,, -4, 7, 4, 5, 3, 3, 2, 2, 384, 240, 240, 240,,,, -4, 7, 4, 5, 3, 3, 2, 3, 128, 240, 240, 240,,,, -4, 7, 4, 5, 3, 3, 2, 3, 256, 240, 240, 240,,,, -4, 7, 4, 5, 3, 3, 2, 3, 384, 240, 240, 240,,,, -4, 7, 4, 5, 3, 3, 3, 1, 128, 240, 240, 240,,,, -4, 7, 4, 5, 3, 3, 3, 1, 256, 240, 240, 240,,,, -4, 7, 4, 5, 3, 3, 3, 1, 384, 240, 240, 240,,,, -4, 7, 4, 5, 3, 3, 3, 2, 128, 240, 240, 240,,,, -4, 7, 4, 5, 3, 3, 3, 2, 256, 240, 240, 240,,,, -4, 7, 4, 5, 3, 3, 3, 2, 384, 240, 240, 240,,,, -4, 7, 4, 5, 3, 3, 3, 3, 128, 240, 240, 240,,,, -4, 7, 4, 5, 3, 3, 3, 3, 256, 240, 240, 240,,,, -4, 7, 4, 5, 3, 3, 3, 3, 384, 240, 240, 240,,,, -4, 7, 4, 6, 1, 1, 1, 1, 128, 240, 240, 240,,,, -4, 7, 4, 6, 1, 1, 1, 1, 256, 240, 240, 240,,,, -4, 7, 4, 6, 1, 1, 1, 1, 384, 240, 240, 240,,,, -4, 7, 4, 6, 2, 2, 1, 1, 128, 240, 240, 240,,,, -4, 7, 4, 6, 2, 2, 1, 1, 256, 240, 240, 240,,,, -4, 7, 4, 6, 2, 2, 1, 1, 384, 240, 240, 240,,,, -4, 7, 4, 6, 2, 2, 1, 2, 128, 240, 240, 240,,,, -4, 7, 4, 6, 2, 2, 1, 2, 256, 240, 240, 240,,,, -4, 7, 4, 6, 2, 2, 1, 2, 384, 240, 240, 240,,,, -4, 7, 4, 6, 2, 2, 2, 1, 128, 240, 240, 240,,,, -4, 7, 4, 6, 2, 2, 2, 1, 256, 240, 240, 240,,,, -4, 7, 4, 6, 2, 2, 2, 1, 384, 240, 240, 240,,,, -4, 7, 4, 6, 2, 2, 2, 2, 128, 240, 240, 240,,,, -4, 7, 4, 6, 2, 2, 2, 2, 256, 240, 240, 240,,,, -4, 7, 4, 6, 2, 2, 2, 2, 384, 240, 240, 240,,,, -4, 7, 4, 6, 3, 3, 1, 1, 128, 240, 240, 240,,,, -4, 7, 4, 6, 3, 3, 1, 1, 256, 240, 240, 240,,,, -4, 7, 4, 6, 3, 3, 1, 1, 384, 240, 240, 240,,,, -4, 7, 4, 6, 3, 3, 1, 2, 128, 240, 240, 240,,,, -4, 7, 4, 6, 3, 3, 1, 2, 256, 240, 240, 240,,,, -4, 7, 4, 6, 3, 3, 1, 2, 384, 240, 240, 240,,,, -4, 7, 4, 6, 3, 3, 1, 3, 128, 240, 240, 240,,,, -4, 7, 4, 6, 3, 3, 1, 3, 256, 240, 240, 240,,,, -4, 7, 4, 6, 3, 3, 1, 3, 384, 240, 240, 240,,,, -4, 7, 4, 6, 3, 3, 2, 1, 128, 240, 240, 240,,,, -4, 7, 4, 6, 3, 3, 2, 1, 256, 240, 240, 240,,,, -4, 7, 4, 6, 3, 3, 2, 1, 384, 240, 240, 240,,,, -4, 7, 4, 6, 3, 3, 2, 2, 128, 240, 240, 240,,,, -4, 7, 4, 6, 3, 3, 2, 2, 256, 240, 240, 240,,,, -4, 7, 4, 6, 3, 3, 2, 2, 384, 240, 240, 240,,,, -4, 7, 4, 6, 3, 3, 2, 3, 128, 240, 240, 240,,,, -4, 7, 4, 6, 3, 3, 2, 3, 256, 240, 240, 240,,,, -4, 7, 4, 6, 3, 3, 2, 3, 384, 240, 240, 240,,,, -4, 7, 4, 6, 3, 3, 3, 1, 128, 240, 240, 240,,,, -4, 7, 4, 6, 3, 3, 3, 1, 256, 240, 240, 240,,,, -4, 7, 4, 6, 3, 3, 3, 1, 384, 240, 240, 240,,,, -4, 7, 4, 6, 3, 3, 3, 2, 128, 240, 240, 240,,,, -4, 7, 4, 6, 3, 3, 3, 2, 256, 240, 240, 240,,,, -4, 7, 4, 6, 3, 3, 3, 2, 384, 240, 240, 240,,,, -4, 7, 4, 6, 3, 3, 3, 3, 128, 240, 240, 240,,,, -4, 7, 4, 6, 3, 3, 3, 3, 256, 240, 240, 240,,,, -4, 7, 4, 6, 3, 3, 3, 3, 384, 240, 240, 240,,,, -4, 7, 4, 7, 1, 1, 1, 1, 128, 240, 240, 240,,,, -4, 7, 4, 7, 1, 1, 1, 1, 256, 240, 240, 240,,,, -4, 7, 4, 7, 1, 1, 1, 1, 384, 240, 240, 240,,,, -4, 7, 4, 7, 2, 2, 1, 1, 128, 240, 240, 240,,,, -4, 7, 4, 7, 2, 2, 1, 1, 256, 240, 240, 240,,,, -4, 7, 4, 7, 2, 2, 1, 1, 384, 240, 240, 240,,,, -4, 7, 4, 7, 2, 2, 1, 2, 128, 240, 240, 240,,,, -4, 7, 4, 7, 2, 2, 1, 2, 256, 240, 240, 240,,,, -4, 7, 4, 7, 2, 2, 1, 2, 384, 240, 240, 240,,,, -4, 7, 4, 7, 2, 2, 2, 1, 128, 240, 240, 240,,,, -4, 7, 4, 7, 2, 2, 2, 1, 256, 240, 240, 240,,,, -4, 7, 4, 7, 2, 2, 2, 1, 384, 240, 240, 240,,,, -4, 7, 4, 7, 2, 2, 2, 2, 128, 240, 240, 240,,,, -4, 7, 4, 7, 2, 2, 2, 2, 256, 240, 240, 240,,,, -4, 7, 4, 7, 2, 2, 2, 2, 384, 240, 240, 240,,,, -4, 7, 4, 7, 3, 3, 1, 1, 128, 240, 240, 240,,,, -4, 7, 4, 7, 3, 3, 1, 1, 256, 240, 240, 240,,,, -4, 7, 4, 7, 3, 3, 1, 1, 384, 240, 240, 240,,,, -4, 7, 4, 7, 3, 3, 1, 2, 128, 240, 240, 240,,,, -4, 7, 4, 7, 3, 3, 1, 2, 256, 240, 240, 240,,,, -4, 7, 4, 7, 3, 3, 1, 2, 384, 240, 240, 240,,,, -4, 7, 4, 7, 3, 3, 1, 3, 128, 240, 240, 240,,,, -4, 7, 4, 7, 3, 3, 1, 3, 256, 240, 240, 240,,,, -4, 7, 4, 7, 3, 3, 1, 3, 384, 240, 240, 240,,,, -4, 7, 4, 7, 3, 3, 2, 1, 128, 240, 240, 240,,,, -4, 7, 4, 7, 3, 3, 2, 1, 256, 240, 240, 240,,,, -4, 7, 4, 7, 3, 3, 2, 1, 384, 240, 240, 240,,,, -4, 7, 4, 7, 3, 3, 2, 2, 128, 240, 240, 240,,,, -4, 7, 4, 7, 3, 3, 2, 2, 256, 240, 240, 240,,,, -4, 7, 4, 7, 3, 3, 2, 2, 384, 240, 240, 240,,,, -4, 7, 4, 7, 3, 3, 2, 3, 128, 240, 240, 240,,,, -4, 7, 4, 7, 3, 3, 2, 3, 256, 240, 240, 240,,,, -4, 7, 4, 7, 3, 3, 2, 3, 384, 240, 240, 240,,,, -4, 7, 4, 7, 3, 3, 3, 1, 128, 240, 240, 240,,,, -4, 7, 4, 7, 3, 3, 3, 1, 256, 240, 240, 240,,,, -4, 7, 4, 7, 3, 3, 3, 1, 384, 240, 240, 240,,,, -4, 7, 4, 7, 3, 3, 3, 2, 128, 240, 240, 240,,,, -4, 7, 4, 7, 3, 3, 3, 2, 256, 240, 240, 240,,,, -4, 7, 4, 7, 3, 3, 3, 2, 384, 240, 240, 240,,,, -4, 7, 4, 7, 3, 3, 3, 3, 128, 240, 240, 240,,,, -4, 7, 4, 7, 3, 3, 3, 3, 256, 240, 240, 240,,,, -4, 7, 4, 7, 3, 3, 3, 3, 384, 240, 240, 240,,,, -5, 1, 1, 1, 1, 1, 1, 1, 128, 76, 76, 76, 76, 51, 25, -5, 1, 1, 1, 1, 1, 1, 1, 256, 76, 76, 76, 76, 51, 25, -5, 1, 1, 1, 1, 1, 1, 1, 384, 76, 76, 76, 76, 51, 25, -5, 1, 2, 1, 1, 1, 1, 1, 128, 76, 76, 76, 76, 51, 25, -5, 1, 2, 1, 1, 1, 1, 1, 256, 76, 76, 76, 76, 51, 25, -5, 1, 2, 1, 1, 1, 1, 1, 384, 76, 76, 76, 76, 51, 25, -5, 1, 3, 1, 1, 1, 1, 1, 128, 76, 76, 76, 76, 51, 25, -5, 1, 3, 1, 1, 1, 1, 1, 256, 76, 76, 76, 76, 51, 25, -5, 1, 3, 1, 1, 1, 1, 1, 384, 76, 76, 76, 76, 51, 25, -5, 1, 4, 1, 1, 1, 1, 1, 128, 76, 76, 76, 76, 51, 25, -5, 1, 4, 1, 1, 1, 1, 1, 256, 76, 76, 76, 76, 51, 25, -5, 1, 4, 1, 1, 1, 1, 1, 384, 76, 76, 76, 76, 51, 25, -5, 1, 5, 1, 1, 1, 1, 1, 128, 76, 76, 76, 76, 51, 25, -5, 1, 5, 1, 1, 1, 1, 1, 256, 76, 76, 76, 76, 51, 25, -5, 1, 5, 1, 1, 1, 1, 1, 384, 76, 76, 76, 76, 51, 25, -5, 2, 1, 1, 1, 1, 1, 1, 128, 77, 77, 77, 52,,, -5, 2, 1, 1, 1, 1, 1, 1, 256, 77, 77, 77, 52,,, -5, 2, 1, 1, 1, 1, 1, 1, 384, 77, 77, 77, 52,,, -5, 2, 1, 1, 2, 2, 1, 1, 128, 77, 77, 77, 52,,, -5, 2, 1, 1, 2, 2, 1, 1, 256, 77, 77, 77, 52,,, -5, 2, 1, 1, 2, 2, 1, 1, 384, 77, 77, 77, 52,,, -5, 2, 1, 1, 2, 2, 1, 2, 128, 77, 77, 77, 52,,, -5, 2, 1, 1, 2, 2, 1, 2, 256, 77, 77, 77, 52,,, -5, 2, 1, 1, 2, 2, 1, 2, 384, 77, 77, 77, 52,,, -5, 2, 1, 1, 2, 2, 2, 1, 128, 77, 77, 77, 52,,, -5, 2, 1, 1, 2, 2, 2, 1, 256, 77, 77, 77, 52,,, -5, 2, 1, 1, 2, 2, 2, 1, 384, 77, 77, 77, 52,,, -5, 2, 1, 1, 2, 2, 2, 2, 128, 77, 77, 77, 52,,, -5, 2, 1, 1, 2, 2, 2, 2, 256, 77, 77, 77, 52,,, -5, 2, 1, 1, 2, 2, 2, 2, 384, 77, 77, 77, 52,,, -5, 2, 1, 2, 1, 1, 1, 1, 128, 153, 153, 153, 103,,, -5, 2, 1, 2, 1, 1, 1, 1, 256, 153, 153, 153, 103,,, -5, 2, 1, 2, 1, 1, 1, 1, 384, 153, 153, 153, 103,,, -5, 2, 1, 2, 2, 2, 1, 1, 128, 153, 153, 153, 103,,, -5, 2, 1, 2, 2, 2, 1, 1, 256, 153, 153, 153, 103,,, -5, 2, 1, 2, 2, 2, 1, 1, 384, 153, 153, 153, 103,,, -5, 2, 1, 2, 2, 2, 1, 2, 128, 153, 153, 153, 103,,, -5, 2, 1, 2, 2, 2, 1, 2, 256, 153, 153, 153, 103,,, -5, 2, 1, 2, 2, 2, 1, 2, 384, 153, 153, 153, 103,,, -5, 2, 1, 2, 2, 2, 2, 1, 128, 153, 153, 153, 103,,, -5, 2, 1, 2, 2, 2, 2, 1, 256, 153, 153, 153, 103,,, -5, 2, 1, 2, 2, 2, 2, 1, 384, 153, 153, 153, 103,,, -5, 2, 1, 2, 2, 2, 2, 2, 128, 153, 153, 153, 103,,, -5, 2, 1, 2, 2, 2, 2, 2, 256, 153, 153, 153, 103,,, -5, 2, 1, 2, 2, 2, 2, 2, 384, 153, 153, 153, 103,,, -5, 2, 2, 1, 1, 1, 1, 1, 128, 77, 77, 77, 52,,, -5, 2, 2, 1, 1, 1, 1, 1, 256, 77, 77, 77, 52,,, -5, 2, 2, 1, 1, 1, 1, 1, 384, 77, 77, 77, 52,,, -5, 2, 2, 1, 2, 2, 1, 1, 128, 77, 77, 77, 52,,, -5, 2, 2, 1, 2, 2, 1, 1, 256, 77, 77, 77, 52,,, -5, 2, 2, 1, 2, 2, 1, 1, 384, 77, 77, 77, 52,,, -5, 2, 2, 1, 2, 2, 1, 2, 128, 77, 77, 77, 52,,, -5, 2, 2, 1, 2, 2, 1, 2, 256, 77, 77, 77, 52,,, -5, 2, 2, 1, 2, 2, 1, 2, 384, 77, 77, 77, 52,,, -5, 2, 2, 1, 2, 2, 2, 1, 128, 77, 77, 77, 52,,, -5, 2, 2, 1, 2, 2, 2, 1, 256, 77, 77, 77, 52,,, -5, 2, 2, 1, 2, 2, 2, 1, 384, 77, 77, 77, 52,,, -5, 2, 2, 1, 2, 2, 2, 2, 128, 77, 77, 77, 52,,, -5, 2, 2, 1, 2, 2, 2, 2, 256, 77, 77, 77, 52,,, -5, 2, 2, 1, 2, 2, 2, 2, 384, 77, 77, 77, 52,,, -5, 2, 2, 2, 1, 1, 1, 1, 128, 153, 153, 153, 103,,, -5, 2, 2, 2, 1, 1, 1, 1, 256, 153, 153, 153, 103,,, -5, 2, 2, 2, 1, 1, 1, 1, 384, 153, 153, 153, 103,,, -5, 2, 2, 2, 2, 2, 1, 1, 128, 153, 153, 153, 103,,, -5, 2, 2, 2, 2, 2, 1, 1, 256, 153, 153, 153, 103,,, -5, 2, 2, 2, 2, 2, 1, 1, 384, 153, 153, 153, 103,,, -5, 2, 2, 2, 2, 2, 1, 2, 128, 153, 153, 153, 103,,, -5, 2, 2, 2, 2, 2, 1, 2, 256, 153, 153, 153, 103,,, -5, 2, 2, 2, 2, 2, 1, 2, 384, 153, 153, 153, 103,,, -5, 2, 2, 2, 2, 2, 2, 1, 128, 153, 153, 153, 103,,, -5, 2, 2, 2, 2, 2, 2, 1, 256, 153, 153, 153, 103,,, -5, 2, 2, 2, 2, 2, 2, 1, 384, 153, 153, 153, 103,,, -5, 2, 2, 2, 2, 2, 2, 2, 128, 153, 153, 153, 103,,, -5, 2, 2, 2, 2, 2, 2, 2, 256, 153, 153, 153, 103,,, -5, 2, 2, 2, 2, 2, 2, 2, 384, 153, 153, 153, 103,,, -5, 2, 3, 1, 1, 1, 1, 1, 128, 77, 77, 77, 52,,, -5, 2, 3, 1, 1, 1, 1, 1, 256, 77, 77, 77, 52,,, -5, 2, 3, 1, 1, 1, 1, 1, 384, 77, 77, 77, 52,,, -5, 2, 3, 1, 2, 2, 1, 1, 128, 77, 77, 77, 52,,, -5, 2, 3, 1, 2, 2, 1, 1, 256, 77, 77, 77, 52,,, -5, 2, 3, 1, 2, 2, 1, 1, 384, 77, 77, 77, 52,,, -5, 2, 3, 1, 2, 2, 1, 2, 128, 77, 77, 77, 52,,, -5, 2, 3, 1, 2, 2, 1, 2, 256, 77, 77, 77, 52,,, -5, 2, 3, 1, 2, 2, 1, 2, 384, 77, 77, 77, 52,,, -5, 2, 3, 1, 2, 2, 2, 1, 128, 77, 77, 77, 52,,, -5, 2, 3, 1, 2, 2, 2, 1, 256, 77, 77, 77, 52,,, -5, 2, 3, 1, 2, 2, 2, 1, 384, 77, 77, 77, 52,,, -5, 2, 3, 1, 2, 2, 2, 2, 128, 77, 77, 77, 52,,, -5, 2, 3, 1, 2, 2, 2, 2, 256, 77, 77, 77, 52,,, -5, 2, 3, 1, 2, 2, 2, 2, 384, 77, 77, 77, 52,,, -5, 2, 3, 2, 1, 1, 1, 1, 128, 153, 153, 153, 103,,, -5, 2, 3, 2, 1, 1, 1, 1, 256, 153, 153, 153, 103,,, -5, 2, 3, 2, 1, 1, 1, 1, 384, 153, 153, 153, 103,,, -5, 2, 3, 2, 2, 2, 1, 1, 128, 153, 153, 153, 103,,, -5, 2, 3, 2, 2, 2, 1, 1, 256, 153, 153, 153, 103,,, -5, 2, 3, 2, 2, 2, 1, 1, 384, 153, 153, 153, 103,,, -5, 2, 3, 2, 2, 2, 1, 2, 128, 153, 153, 153, 103,,, -5, 2, 3, 2, 2, 2, 1, 2, 256, 153, 153, 153, 103,,, -5, 2, 3, 2, 2, 2, 1, 2, 384, 153, 153, 153, 103,,, -5, 2, 3, 2, 2, 2, 2, 1, 128, 153, 153, 153, 103,,, -5, 2, 3, 2, 2, 2, 2, 1, 256, 153, 153, 153, 103,,, -5, 2, 3, 2, 2, 2, 2, 1, 384, 153, 153, 153, 103,,, -5, 2, 3, 2, 2, 2, 2, 2, 128, 153, 153, 153, 103,,, -5, 2, 3, 2, 2, 2, 2, 2, 256, 153, 153, 153, 103,,, -5, 2, 3, 2, 2, 2, 2, 2, 384, 153, 153, 153, 103,,, -5, 2, 4, 1, 1, 1, 1, 1, 128, 77, 77, 77, 52,,, -5, 2, 4, 1, 1, 1, 1, 1, 256, 77, 77, 77, 52,,, -5, 2, 4, 1, 1, 1, 1, 1, 384, 77, 77, 77, 52,,, -5, 2, 4, 1, 2, 2, 1, 1, 128, 77, 77, 77, 52,,, -5, 2, 4, 1, 2, 2, 1, 1, 256, 77, 77, 77, 52,,, -5, 2, 4, 1, 2, 2, 1, 1, 384, 77, 77, 77, 52,,, -5, 2, 4, 1, 2, 2, 1, 2, 128, 77, 77, 77, 52,,, -5, 2, 4, 1, 2, 2, 1, 2, 256, 77, 77, 77, 52,,, -5, 2, 4, 1, 2, 2, 1, 2, 384, 77, 77, 77, 52,,, -5, 2, 4, 1, 2, 2, 2, 1, 128, 77, 77, 77, 52,,, -5, 2, 4, 1, 2, 2, 2, 1, 256, 77, 77, 77, 52,,, -5, 2, 4, 1, 2, 2, 2, 1, 384, 77, 77, 77, 52,,, -5, 2, 4, 1, 2, 2, 2, 2, 128, 77, 77, 77, 52,,, -5, 2, 4, 1, 2, 2, 2, 2, 256, 77, 77, 77, 52,,, -5, 2, 4, 1, 2, 2, 2, 2, 384, 77, 77, 77, 52,,, -5, 2, 4, 2, 1, 1, 1, 1, 128, 153, 153, 153, 103,,, -5, 2, 4, 2, 1, 1, 1, 1, 256, 153, 153, 153, 103,,, -5, 2, 4, 2, 1, 1, 1, 1, 384, 153, 153, 153, 103,,, -5, 2, 4, 2, 2, 2, 1, 1, 128, 153, 153, 153, 103,,, -5, 2, 4, 2, 2, 2, 1, 1, 256, 153, 153, 153, 103,,, -5, 2, 4, 2, 2, 2, 1, 1, 384, 153, 153, 153, 103,,, -5, 2, 4, 2, 2, 2, 1, 2, 128, 153, 153, 153, 103,,, -5, 2, 4, 2, 2, 2, 1, 2, 256, 153, 153, 153, 103,,, -5, 2, 4, 2, 2, 2, 1, 2, 384, 153, 153, 153, 103,,, -5, 2, 4, 2, 2, 2, 2, 1, 128, 153, 153, 153, 103,,, -5, 2, 4, 2, 2, 2, 2, 1, 256, 153, 153, 153, 103,,, -5, 2, 4, 2, 2, 2, 2, 1, 384, 153, 153, 153, 103,,, -5, 2, 4, 2, 2, 2, 2, 2, 128, 153, 153, 153, 103,,, -5, 2, 4, 2, 2, 2, 2, 2, 256, 153, 153, 153, 103,,, -5, 2, 4, 2, 2, 2, 2, 2, 384, 153, 153, 153, 103,,, -5, 2, 5, 1, 1, 1, 1, 1, 128, 77, 77, 77, 52,,, -5, 2, 5, 1, 1, 1, 1, 1, 256, 77, 77, 77, 52,,, -5, 2, 5, 1, 1, 1, 1, 1, 384, 77, 77, 77, 52,,, -5, 2, 5, 1, 2, 2, 1, 1, 128, 77, 77, 77, 52,,, -5, 2, 5, 1, 2, 2, 1, 1, 256, 77, 77, 77, 52,,, -5, 2, 5, 1, 2, 2, 1, 1, 384, 77, 77, 77, 52,,, -5, 2, 5, 1, 2, 2, 1, 2, 128, 77, 77, 77, 52,,, -5, 2, 5, 1, 2, 2, 1, 2, 256, 77, 77, 77, 52,,, -5, 2, 5, 1, 2, 2, 1, 2, 384, 77, 77, 77, 52,,, -5, 2, 5, 1, 2, 2, 2, 1, 128, 77, 77, 77, 52,,, -5, 2, 5, 1, 2, 2, 2, 1, 256, 77, 77, 77, 52,,, -5, 2, 5, 1, 2, 2, 2, 1, 384, 77, 77, 77, 52,,, -5, 2, 5, 1, 2, 2, 2, 2, 128, 77, 77, 77, 52,,, -5, 2, 5, 1, 2, 2, 2, 2, 256, 77, 77, 77, 52,,, -5, 2, 5, 1, 2, 2, 2, 2, 384, 77, 77, 77, 52,,, -5, 2, 5, 2, 1, 1, 1, 1, 128, 153, 153, 153, 103,,, -5, 2, 5, 2, 1, 1, 1, 1, 256, 153, 153, 153, 103,,, -5, 2, 5, 2, 1, 1, 1, 1, 384, 153, 153, 153, 103,,, -5, 2, 5, 2, 2, 2, 1, 1, 128, 153, 153, 153, 103,,, -5, 2, 5, 2, 2, 2, 1, 1, 256, 153, 153, 153, 103,,, -5, 2, 5, 2, 2, 2, 1, 1, 384, 153, 153, 153, 103,,, -5, 2, 5, 2, 2, 2, 1, 2, 128, 153, 153, 153, 103,,, -5, 2, 5, 2, 2, 2, 1, 2, 256, 153, 153, 153, 103,,, -5, 2, 5, 2, 2, 2, 1, 2, 384, 153, 153, 153, 103,,, -5, 2, 5, 2, 2, 2, 2, 1, 128, 153, 153, 153, 103,,, -5, 2, 5, 2, 2, 2, 2, 1, 256, 153, 153, 153, 103,,, -5, 2, 5, 2, 2, 2, 2, 1, 384, 153, 153, 153, 103,,, -5, 2, 5, 2, 2, 2, 2, 2, 128, 153, 153, 153, 103,,, -5, 2, 5, 2, 2, 2, 2, 2, 256, 153, 153, 153, 103,,, -5, 2, 5, 2, 2, 2, 2, 2, 384, 153, 153, 153, 103,,, -5, 3, 1, 1, 1, 1, 1, 1, 128, 78, 78, 78, 53,,, -5, 3, 1, 1, 1, 1, 1, 1, 256, 78, 78, 78, 53,,, -5, 3, 1, 1, 1, 1, 1, 1, 384, 78, 78, 78, 53,,, -5, 3, 1, 1, 2, 2, 1, 1, 128, 78, 78, 72, 50,,, -5, 3, 1, 1, 2, 2, 1, 1, 256, 78, 78, 72, 50,,, -5, 3, 1, 1, 2, 2, 1, 1, 384, 78, 78, 72, 50,,, -5, 3, 1, 1, 2, 2, 1, 2, 128, 78, 78, 72, 50,,, -5, 3, 1, 1, 2, 2, 1, 2, 256, 78, 78, 72, 50,,, -5, 3, 1, 1, 2, 2, 1, 2, 384, 78, 78, 72, 50,,, -5, 3, 1, 1, 2, 2, 2, 1, 128, 78, 78, 72, 50,,, -5, 3, 1, 1, 2, 2, 2, 1, 256, 78, 78, 72, 50,,, -5, 3, 1, 1, 2, 2, 2, 1, 384, 78, 78, 72, 50,,, -5, 3, 1, 1, 2, 2, 2, 2, 128, 78, 78, 72, 50,,, -5, 3, 1, 1, 2, 2, 2, 2, 256, 78, 78, 72, 50,,, -5, 3, 1, 1, 2, 2, 2, 2, 384, 78, 78, 72, 50,,, -5, 3, 1, 1, 3, 3, 1, 1, 128, 78, 78, 69, 48,,, -5, 3, 1, 1, 3, 3, 1, 1, 256, 78, 78, 69, 48,,, -5, 3, 1, 1, 3, 3, 1, 1, 384, 78, 78, 69, 48,,, -5, 3, 1, 1, 3, 3, 1, 2, 128, 78, 78, 69, 48,,, -5, 3, 1, 1, 3, 3, 1, 2, 256, 78, 78, 69, 48,,, -5, 3, 1, 1, 3, 3, 1, 2, 384, 78, 78, 69, 48,,, -5, 3, 1, 1, 3, 3, 1, 3, 128, 78, 78, 69, 48,,, -5, 3, 1, 1, 3, 3, 1, 3, 256, 78, 78, 69, 48,,, -5, 3, 1, 1, 3, 3, 1, 3, 384, 78, 78, 69, 48,,, -5, 3, 1, 1, 3, 3, 2, 1, 128, 78, 78, 69, 48,,, -5, 3, 1, 1, 3, 3, 2, 1, 256, 78, 78, 69, 48,,, -5, 3, 1, 1, 3, 3, 2, 1, 384, 78, 78, 69, 48,,, -5, 3, 1, 1, 3, 3, 2, 2, 128, 78, 78, 69, 48,,, -5, 3, 1, 1, 3, 3, 2, 2, 256, 78, 78, 69, 48,,, -5, 3, 1, 1, 3, 3, 2, 2, 384, 78, 78, 69, 48,,, -5, 3, 1, 1, 3, 3, 2, 3, 128, 78, 78, 69, 48,,, -5, 3, 1, 1, 3, 3, 2, 3, 256, 78, 78, 69, 48,,, -5, 3, 1, 1, 3, 3, 2, 3, 384, 78, 78, 69, 48,,, -5, 3, 1, 1, 3, 3, 3, 1, 128, 78, 78, 69, 48,,, -5, 3, 1, 1, 3, 3, 3, 1, 256, 78, 78, 69, 48,,, -5, 3, 1, 1, 3, 3, 3, 1, 384, 78, 78, 69, 48,,, -5, 3, 1, 1, 3, 3, 3, 2, 128, 78, 78, 69, 48,,, -5, 3, 1, 1, 3, 3, 3, 2, 256, 78, 78, 69, 48,,, -5, 3, 1, 1, 3, 3, 3, 2, 384, 78, 78, 69, 48,,, -5, 3, 1, 1, 3, 3, 3, 3, 128, 78, 78, 69, 48,,, -5, 3, 1, 1, 3, 3, 3, 3, 256, 78, 78, 69, 48,,, -5, 3, 1, 1, 3, 3, 3, 3, 384, 78, 78, 69, 48,,, -5, 3, 1, 2, 1, 1, 1, 1, 128, 154, 154, 154, 104,,, -5, 3, 1, 2, 1, 1, 1, 1, 256, 154, 154, 154, 104,,, -5, 3, 1, 2, 1, 1, 1, 1, 384, 154, 154, 154, 104,,, -5, 3, 1, 2, 2, 2, 1, 1, 128, 154, 154, 142, 98,,, -5, 3, 1, 2, 2, 2, 1, 1, 256, 154, 154, 142, 98,,, -5, 3, 1, 2, 2, 2, 1, 1, 384, 154, 154, 142, 98,,, -5, 3, 1, 2, 2, 2, 1, 2, 128, 154, 154, 142, 98,,, -5, 3, 1, 2, 2, 2, 1, 2, 256, 154, 154, 142, 98,,, -5, 3, 1, 2, 2, 2, 1, 2, 384, 154, 154, 142, 98,,, -5, 3, 1, 2, 2, 2, 2, 1, 128, 154, 154, 142, 98,,, -5, 3, 1, 2, 2, 2, 2, 1, 256, 154, 154, 142, 98,,, -5, 3, 1, 2, 2, 2, 2, 1, 384, 154, 154, 142, 98,,, -5, 3, 1, 2, 2, 2, 2, 2, 128, 154, 154, 142, 98,,, -5, 3, 1, 2, 2, 2, 2, 2, 256, 154, 154, 142, 98,,, -5, 3, 1, 2, 2, 2, 2, 2, 384, 154, 154, 142, 98,,, -5, 3, 1, 2, 3, 3, 1, 1, 128, 154, 154, 136, 94,,, -5, 3, 1, 2, 3, 3, 1, 1, 256, 154, 154, 136, 94,,, -5, 3, 1, 2, 3, 3, 1, 1, 384, 154, 154, 136, 94,,, -5, 3, 1, 2, 3, 3, 1, 2, 128, 154, 154, 136, 94,,, -5, 3, 1, 2, 3, 3, 1, 2, 256, 154, 154, 136, 94,,, -5, 3, 1, 2, 3, 3, 1, 2, 384, 154, 154, 136, 94,,, -5, 3, 1, 2, 3, 3, 1, 3, 128, 154, 154, 136, 94,,, -5, 3, 1, 2, 3, 3, 1, 3, 256, 154, 154, 136, 94,,, -5, 3, 1, 2, 3, 3, 1, 3, 384, 154, 154, 136, 94,,, -5, 3, 1, 2, 3, 3, 2, 1, 128, 154, 154, 136, 94,,, -5, 3, 1, 2, 3, 3, 2, 1, 256, 154, 154, 136, 94,,, -5, 3, 1, 2, 3, 3, 2, 1, 384, 154, 154, 136, 94,,, -5, 3, 1, 2, 3, 3, 2, 2, 128, 154, 154, 136, 94,,, -5, 3, 1, 2, 3, 3, 2, 2, 256, 154, 154, 136, 94,,, -5, 3, 1, 2, 3, 3, 2, 2, 384, 154, 154, 136, 94,,, -5, 3, 1, 2, 3, 3, 2, 3, 128, 154, 154, 136, 94,,, -5, 3, 1, 2, 3, 3, 2, 3, 256, 154, 154, 136, 94,,, -5, 3, 1, 2, 3, 3, 2, 3, 384, 154, 154, 136, 94,,, -5, 3, 1, 2, 3, 3, 3, 1, 128, 154, 154, 136, 94,,, -5, 3, 1, 2, 3, 3, 3, 1, 256, 154, 154, 136, 94,,, -5, 3, 1, 2, 3, 3, 3, 1, 384, 154, 154, 136, 94,,, -5, 3, 1, 2, 3, 3, 3, 2, 128, 154, 154, 136, 94,,, -5, 3, 1, 2, 3, 3, 3, 2, 256, 154, 154, 136, 94,,, -5, 3, 1, 2, 3, 3, 3, 2, 384, 154, 154, 136, 94,,, -5, 3, 1, 2, 3, 3, 3, 3, 128, 154, 154, 136, 94,,, -5, 3, 1, 2, 3, 3, 3, 3, 256, 154, 154, 136, 94,,, -5, 3, 1, 2, 3, 3, 3, 3, 384, 154, 154, 136, 94,,, -5, 3, 1, 3, 1, 1, 1, 1, 128, 230, 230, 230, 155,,, -5, 3, 1, 3, 1, 1, 1, 1, 256, 230, 230, 230, 155,,, -5, 3, 1, 3, 1, 1, 1, 1, 384, 230, 230, 230, 155,,, -5, 3, 1, 3, 2, 2, 1, 1, 128, 230, 230, 212, 146,,, -5, 3, 1, 3, 2, 2, 1, 1, 256, 230, 230, 212, 146,,, -5, 3, 1, 3, 2, 2, 1, 1, 384, 230, 230, 212, 146,,, -5, 3, 1, 3, 2, 2, 1, 2, 128, 230, 230, 212, 146,,, -5, 3, 1, 3, 2, 2, 1, 2, 256, 230, 230, 212, 146,,, -5, 3, 1, 3, 2, 2, 1, 2, 384, 230, 230, 212, 146,,, -5, 3, 1, 3, 2, 2, 2, 1, 128, 230, 230, 212, 146,,, -5, 3, 1, 3, 2, 2, 2, 1, 256, 230, 230, 212, 146,,, -5, 3, 1, 3, 2, 2, 2, 1, 384, 230, 230, 212, 146,,, -5, 3, 1, 3, 2, 2, 2, 2, 128, 230, 230, 212, 146,,, -5, 3, 1, 3, 2, 2, 2, 2, 256, 230, 230, 212, 146,,, -5, 3, 1, 3, 2, 2, 2, 2, 384, 230, 230, 212, 146,,, -5, 3, 1, 3, 3, 3, 1, 1, 128, 230, 230, 203, 140,,, -5, 3, 1, 3, 3, 3, 1, 1, 256, 230, 230, 203, 140,,, -5, 3, 1, 3, 3, 3, 1, 1, 384, 230, 230, 203, 140,,, -5, 3, 1, 3, 3, 3, 1, 2, 128, 230, 230, 203, 140,,, -5, 3, 1, 3, 3, 3, 1, 2, 256, 230, 230, 203, 140,,, -5, 3, 1, 3, 3, 3, 1, 2, 384, 230, 230, 203, 140,,, -5, 3, 1, 3, 3, 3, 1, 3, 128, 230, 230, 203, 140,,, -5, 3, 1, 3, 3, 3, 1, 3, 256, 230, 230, 203, 140,,, -5, 3, 1, 3, 3, 3, 1, 3, 384, 230, 230, 203, 140,,, -5, 3, 1, 3, 3, 3, 2, 1, 128, 230, 230, 203, 140,,, -5, 3, 1, 3, 3, 3, 2, 1, 256, 230, 230, 203, 140,,, -5, 3, 1, 3, 3, 3, 2, 1, 384, 230, 230, 203, 140,,, -5, 3, 1, 3, 3, 3, 2, 2, 128, 230, 230, 203, 140,,, -5, 3, 1, 3, 3, 3, 2, 2, 256, 230, 230, 203, 140,,, -5, 3, 1, 3, 3, 3, 2, 2, 384, 230, 230, 203, 140,,, -5, 3, 1, 3, 3, 3, 2, 3, 128, 230, 230, 203, 140,,, -5, 3, 1, 3, 3, 3, 2, 3, 256, 230, 230, 203, 140,,, -5, 3, 1, 3, 3, 3, 2, 3, 384, 230, 230, 203, 140,,, -5, 3, 1, 3, 3, 3, 3, 1, 128, 230, 230, 203, 140,,, -5, 3, 1, 3, 3, 3, 3, 1, 256, 230, 230, 203, 140,,, -5, 3, 1, 3, 3, 3, 3, 1, 384, 230, 230, 203, 140,,, -5, 3, 1, 3, 3, 3, 3, 2, 128, 230, 230, 203, 140,,, -5, 3, 1, 3, 3, 3, 3, 2, 256, 230, 230, 203, 140,,, -5, 3, 1, 3, 3, 3, 3, 2, 384, 230, 230, 203, 140,,, -5, 3, 1, 3, 3, 3, 3, 3, 128, 230, 230, 203, 140,,, -5, 3, 1, 3, 3, 3, 3, 3, 256, 230, 230, 203, 140,,, -5, 3, 1, 3, 3, 3, 3, 3, 384, 230, 230, 203, 140,,, -5, 3, 2, 1, 1, 1, 1, 1, 128, 78, 78, 78, 53,,, -5, 3, 2, 1, 1, 1, 1, 1, 256, 78, 78, 78, 53,,, -5, 3, 2, 1, 1, 1, 1, 1, 384, 78, 78, 78, 53,,, -5, 3, 2, 1, 2, 2, 1, 1, 128, 78, 78, 72, 50,,, -5, 3, 2, 1, 2, 2, 1, 1, 256, 78, 78, 72, 50,,, -5, 3, 2, 1, 2, 2, 1, 1, 384, 78, 78, 72, 50,,, -5, 3, 2, 1, 2, 2, 1, 2, 128, 78, 78, 72, 50,,, -5, 3, 2, 1, 2, 2, 1, 2, 256, 78, 78, 72, 50,,, -5, 3, 2, 1, 2, 2, 1, 2, 384, 78, 78, 72, 50,,, -5, 3, 2, 1, 2, 2, 2, 1, 128, 78, 78, 72, 50,,, -5, 3, 2, 1, 2, 2, 2, 1, 256, 78, 78, 72, 50,,, -5, 3, 2, 1, 2, 2, 2, 1, 384, 78, 78, 72, 50,,, -5, 3, 2, 1, 2, 2, 2, 2, 128, 78, 78, 72, 50,,, -5, 3, 2, 1, 2, 2, 2, 2, 256, 78, 78, 72, 50,,, -5, 3, 2, 1, 2, 2, 2, 2, 384, 78, 78, 72, 50,,, -5, 3, 2, 1, 3, 3, 1, 1, 128, 78, 78, 69, 48,,, -5, 3, 2, 1, 3, 3, 1, 1, 256, 78, 78, 69, 48,,, -5, 3, 2, 1, 3, 3, 1, 1, 384, 78, 78, 69, 48,,, -5, 3, 2, 1, 3, 3, 1, 2, 128, 78, 78, 69, 48,,, -5, 3, 2, 1, 3, 3, 1, 2, 256, 78, 78, 69, 48,,, -5, 3, 2, 1, 3, 3, 1, 2, 384, 78, 78, 69, 48,,, -5, 3, 2, 1, 3, 3, 1, 3, 128, 78, 78, 69, 48,,, -5, 3, 2, 1, 3, 3, 1, 3, 256, 78, 78, 69, 48,,, -5, 3, 2, 1, 3, 3, 1, 3, 384, 78, 78, 69, 48,,, -5, 3, 2, 1, 3, 3, 2, 1, 128, 78, 78, 69, 48,,, -5, 3, 2, 1, 3, 3, 2, 1, 256, 78, 78, 69, 48,,, -5, 3, 2, 1, 3, 3, 2, 1, 384, 78, 78, 69, 48,,, -5, 3, 2, 1, 3, 3, 2, 2, 128, 78, 78, 69, 48,,, -5, 3, 2, 1, 3, 3, 2, 2, 256, 78, 78, 69, 48,,, -5, 3, 2, 1, 3, 3, 2, 2, 384, 78, 78, 69, 48,,, -5, 3, 2, 1, 3, 3, 2, 3, 128, 78, 78, 69, 48,,, -5, 3, 2, 1, 3, 3, 2, 3, 256, 78, 78, 69, 48,,, -5, 3, 2, 1, 3, 3, 2, 3, 384, 78, 78, 69, 48,,, -5, 3, 2, 1, 3, 3, 3, 1, 128, 78, 78, 69, 48,,, -5, 3, 2, 1, 3, 3, 3, 1, 256, 78, 78, 69, 48,,, -5, 3, 2, 1, 3, 3, 3, 1, 384, 78, 78, 69, 48,,, -5, 3, 2, 1, 3, 3, 3, 2, 128, 78, 78, 69, 48,,, -5, 3, 2, 1, 3, 3, 3, 2, 256, 78, 78, 69, 48,,, -5, 3, 2, 1, 3, 3, 3, 2, 384, 78, 78, 69, 48,,, -5, 3, 2, 1, 3, 3, 3, 3, 128, 78, 78, 69, 48,,, -5, 3, 2, 1, 3, 3, 3, 3, 256, 78, 78, 69, 48,,, -5, 3, 2, 1, 3, 3, 3, 3, 384, 78, 78, 69, 48,,, -5, 3, 2, 2, 1, 1, 1, 1, 128, 154, 154, 154, 104,,, -5, 3, 2, 2, 1, 1, 1, 1, 256, 154, 154, 154, 104,,, -5, 3, 2, 2, 1, 1, 1, 1, 384, 154, 154, 154, 104,,, -5, 3, 2, 2, 2, 2, 1, 1, 128, 154, 154, 142, 98,,, -5, 3, 2, 2, 2, 2, 1, 1, 256, 154, 154, 142, 98,,, -5, 3, 2, 2, 2, 2, 1, 1, 384, 154, 154, 142, 98,,, -5, 3, 2, 2, 2, 2, 1, 2, 128, 154, 154, 142, 98,,, -5, 3, 2, 2, 2, 2, 1, 2, 256, 154, 154, 142, 98,,, -5, 3, 2, 2, 2, 2, 1, 2, 384, 154, 154, 142, 98,,, -5, 3, 2, 2, 2, 2, 2, 1, 128, 154, 154, 142, 98,,, -5, 3, 2, 2, 2, 2, 2, 1, 256, 154, 154, 142, 98,,, -5, 3, 2, 2, 2, 2, 2, 1, 384, 154, 154, 142, 98,,, -5, 3, 2, 2, 2, 2, 2, 2, 128, 154, 154, 142, 98,,, -5, 3, 2, 2, 2, 2, 2, 2, 256, 154, 154, 142, 98,,, -5, 3, 2, 2, 2, 2, 2, 2, 384, 154, 154, 142, 98,,, -5, 3, 2, 2, 3, 3, 1, 1, 128, 154, 154, 136, 94,,, -5, 3, 2, 2, 3, 3, 1, 1, 256, 154, 154, 136, 94,,, -5, 3, 2, 2, 3, 3, 1, 1, 384, 154, 154, 136, 94,,, -5, 3, 2, 2, 3, 3, 1, 2, 128, 154, 154, 136, 94,,, -5, 3, 2, 2, 3, 3, 1, 2, 256, 154, 154, 136, 94,,, -5, 3, 2, 2, 3, 3, 1, 2, 384, 154, 154, 136, 94,,, -5, 3, 2, 2, 3, 3, 1, 3, 128, 154, 154, 136, 94,,, -5, 3, 2, 2, 3, 3, 1, 3, 256, 154, 154, 136, 94,,, -5, 3, 2, 2, 3, 3, 1, 3, 384, 154, 154, 136, 94,,, -5, 3, 2, 2, 3, 3, 2, 1, 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-5, 3, 4, 3, 3, 3, 2, 2, 128, 230, 230, 203, 140,,, -5, 3, 4, 3, 3, 3, 2, 2, 256, 230, 230, 203, 140,,, -5, 3, 4, 3, 3, 3, 2, 2, 384, 230, 230, 203, 140,,, -5, 3, 4, 3, 3, 3, 2, 3, 128, 230, 230, 203, 140,,, -5, 3, 4, 3, 3, 3, 2, 3, 256, 230, 230, 203, 140,,, -5, 3, 4, 3, 3, 3, 2, 3, 384, 230, 230, 203, 140,,, -5, 3, 4, 3, 3, 3, 3, 1, 128, 230, 230, 203, 140,,, -5, 3, 4, 3, 3, 3, 3, 1, 256, 230, 230, 203, 140,,, -5, 3, 4, 3, 3, 3, 3, 1, 384, 230, 230, 203, 140,,, -5, 3, 4, 3, 3, 3, 3, 2, 128, 230, 230, 203, 140,,, -5, 3, 4, 3, 3, 3, 3, 2, 256, 230, 230, 203, 140,,, -5, 3, 4, 3, 3, 3, 3, 2, 384, 230, 230, 203, 140,,, -5, 3, 4, 3, 3, 3, 3, 3, 128, 230, 230, 203, 140,,, -5, 3, 4, 3, 3, 3, 3, 3, 256, 230, 230, 203, 140,,, -5, 3, 4, 3, 3, 3, 3, 3, 384, 230, 230, 203, 140,,, -5, 3, 5, 1, 1, 1, 1, 1, 128, 78, 78, 78, 53,,, -5, 3, 5, 1, 1, 1, 1, 1, 256, 78, 78, 78, 53,,, -5, 3, 5, 1, 1, 1, 1, 1, 384, 78, 78, 78, 53,,, -5, 3, 5, 1, 2, 2, 1, 1, 128, 78, 78, 72, 50,,, -5, 3, 5, 1, 2, 2, 1, 1, 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98,,, -5, 3, 5, 2, 2, 2, 1, 1, 256, 154, 154, 142, 98,,, -5, 3, 5, 2, 2, 2, 1, 1, 384, 154, 154, 142, 98,,, -5, 3, 5, 2, 2, 2, 1, 2, 128, 154, 154, 142, 98,,, -5, 3, 5, 2, 2, 2, 1, 2, 256, 154, 154, 142, 98,,, -5, 3, 5, 2, 2, 2, 1, 2, 384, 154, 154, 142, 98,,, -5, 3, 5, 2, 2, 2, 2, 1, 128, 154, 154, 142, 98,,, -5, 3, 5, 2, 2, 2, 2, 1, 256, 154, 154, 142, 98,,, -5, 3, 5, 2, 2, 2, 2, 1, 384, 154, 154, 142, 98,,, -5, 3, 5, 2, 2, 2, 2, 2, 128, 154, 154, 142, 98,,, -5, 3, 5, 2, 2, 2, 2, 2, 256, 154, 154, 142, 98,,, -5, 3, 5, 2, 2, 2, 2, 2, 384, 154, 154, 142, 98,,, -5, 3, 5, 2, 3, 3, 1, 1, 128, 154, 154, 136, 94,,, -5, 3, 5, 2, 3, 3, 1, 1, 256, 154, 154, 136, 94,,, -5, 3, 5, 2, 3, 3, 1, 1, 384, 154, 154, 136, 94,,, -5, 3, 5, 2, 3, 3, 1, 2, 128, 154, 154, 136, 94,,, -5, 3, 5, 2, 3, 3, 1, 2, 256, 154, 154, 136, 94,,, -5, 3, 5, 2, 3, 3, 1, 2, 384, 154, 154, 136, 94,,, -5, 3, 5, 2, 3, 3, 1, 3, 128, 154, 154, 136, 94,,, -5, 3, 5, 2, 3, 3, 1, 3, 256, 154, 154, 136, 94,,, -5, 3, 5, 2, 3, 3, 1, 3, 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28,,, -5, 4, 1, 1, 3, 3, 3, 3, 128, 79, 77, 54, 28,,, -5, 4, 1, 1, 3, 3, 3, 3, 256, 79, 77, 54, 28,,, -5, 4, 1, 1, 3, 3, 3, 3, 384, 79, 77, 54, 28,,, -5, 4, 1, 2, 1, 1, 1, 1, 128, 155, 155, 105, 53,,, -5, 4, 1, 2, 1, 1, 1, 1, 256, 155, 155, 105, 53,,, -5, 4, 1, 2, 1, 1, 1, 1, 384, 155, 155, 105, 53,,, -5, 4, 1, 2, 2, 2, 1, 1, 128, 155, 155, 105, 53,,, -5, 4, 1, 2, 2, 2, 1, 1, 256, 155, 155, 105, 53,,, -5, 4, 1, 2, 2, 2, 1, 1, 384, 155, 155, 105, 53,,, -5, 4, 1, 2, 2, 2, 1, 2, 128, 155, 155, 105, 53,,, -5, 4, 1, 2, 2, 2, 1, 2, 256, 155, 155, 105, 53,,, -5, 4, 1, 2, 2, 2, 1, 2, 384, 155, 155, 105, 53,,, -5, 4, 1, 2, 2, 2, 2, 1, 128, 155, 155, 105, 53,,, -5, 4, 1, 2, 2, 2, 2, 1, 256, 155, 155, 105, 53,,, -5, 4, 1, 2, 2, 2, 2, 1, 384, 155, 155, 105, 53,,, -5, 4, 1, 2, 2, 2, 2, 2, 128, 155, 155, 105, 53,,, -5, 4, 1, 2, 2, 2, 2, 2, 256, 155, 155, 105, 53,,, -5, 4, 1, 2, 2, 2, 2, 2, 384, 155, 155, 105, 53,,, -5, 4, 1, 2, 3, 3, 1, 1, 128, 155, 151, 105, 53,,, -5, 4, 1, 2, 3, 3, 1, 1, 256, 155, 151, 105, 53,,, -5, 4, 1, 2, 3, 3, 1, 1, 384, 155, 151, 105, 53,,, -5, 4, 1, 2, 3, 3, 1, 2, 128, 155, 151, 105, 53,,, -5, 4, 1, 2, 3, 3, 1, 2, 256, 155, 151, 105, 53,,, -5, 4, 1, 2, 3, 3, 1, 2, 384, 155, 151, 105, 53,,, -5, 4, 1, 2, 3, 3, 1, 3, 128, 155, 151, 105, 53,,, -5, 4, 1, 2, 3, 3, 1, 3, 256, 155, 151, 105, 53,,, -5, 4, 1, 2, 3, 3, 1, 3, 384, 155, 151, 105, 53,,, -5, 4, 1, 2, 3, 3, 2, 1, 128, 155, 151, 105, 53,,, -5, 4, 1, 2, 3, 3, 2, 1, 256, 155, 151, 105, 53,,, -5, 4, 1, 2, 3, 3, 2, 1, 384, 155, 151, 105, 53,,, -5, 4, 1, 2, 3, 3, 2, 2, 128, 155, 151, 105, 53,,, -5, 4, 1, 2, 3, 3, 2, 2, 256, 155, 151, 105, 53,,, -5, 4, 1, 2, 3, 3, 2, 2, 384, 155, 151, 105, 53,,, -5, 4, 1, 2, 3, 3, 2, 3, 128, 155, 151, 105, 53,,, -5, 4, 1, 2, 3, 3, 2, 3, 256, 155, 151, 105, 53,,, -5, 4, 1, 2, 3, 3, 2, 3, 384, 155, 151, 105, 53,,, -5, 4, 1, 2, 3, 3, 3, 1, 128, 155, 151, 105, 53,,, -5, 4, 1, 2, 3, 3, 3, 1, 256, 155, 151, 105, 53,,, -5, 4, 1, 2, 3, 3, 3, 1, 384, 155, 151, 105, 53,,, -5, 4, 1, 2, 3, 3, 3, 2, 128, 155, 151, 105, 53,,, -5, 4, 1, 2, 3, 3, 3, 2, 256, 155, 151, 105, 53,,, -5, 4, 1, 2, 3, 3, 3, 2, 384, 155, 151, 105, 53,,, -5, 4, 1, 2, 3, 3, 3, 3, 128, 155, 151, 105, 53,,, -5, 4, 1, 2, 3, 3, 3, 3, 256, 155, 151, 105, 53,,, -5, 4, 1, 2, 3, 3, 3, 3, 384, 155, 151, 105, 53,,, -5, 4, 1, 3, 1, 1, 1, 1, 128, 231, 231, 156, 78,,, -5, 4, 1, 3, 1, 1, 1, 1, 256, 231, 231, 156, 78,,, -5, 4, 1, 3, 1, 1, 1, 1, 384, 231, 231, 156, 78,,, -5, 4, 1, 3, 2, 2, 1, 1, 128, 231, 231, 156, 78,,, -5, 4, 1, 3, 2, 2, 1, 1, 256, 231, 231, 156, 78,,, -5, 4, 1, 3, 2, 2, 1, 1, 384, 231, 231, 156, 78,,, -5, 4, 1, 3, 2, 2, 1, 2, 128, 231, 231, 156, 78,,, -5, 4, 1, 3, 2, 2, 1, 2, 256, 231, 231, 156, 78,,, -5, 4, 1, 3, 2, 2, 1, 2, 384, 231, 231, 156, 78,,, -5, 4, 1, 3, 2, 2, 2, 1, 128, 231, 231, 156, 78,,, -5, 4, 1, 3, 2, 2, 2, 1, 256, 231, 231, 156, 78,,, -5, 4, 1, 3, 2, 2, 2, 1, 384, 231, 231, 156, 78,,, -5, 4, 1, 3, 2, 2, 2, 2, 128, 231, 231, 156, 78,,, -5, 4, 1, 3, 2, 2, 2, 2, 256, 231, 231, 156, 78,,, -5, 4, 1, 3, 2, 2, 2, 2, 384, 231, 231, 156, 78,,, -5, 4, 1, 3, 3, 3, 1, 1, 128, 231, 225, 156, 78,,, -5, 4, 1, 3, 3, 3, 1, 1, 256, 231, 225, 156, 78,,, -5, 4, 1, 3, 3, 3, 1, 1, 384, 231, 225, 156, 78,,, -5, 4, 1, 3, 3, 3, 1, 2, 128, 231, 225, 156, 78,,, -5, 4, 1, 3, 3, 3, 1, 2, 256, 231, 225, 156, 78,,, -5, 4, 1, 3, 3, 3, 1, 2, 384, 231, 225, 156, 78,,, -5, 4, 1, 3, 3, 3, 1, 3, 128, 231, 225, 156, 78,,, -5, 4, 1, 3, 3, 3, 1, 3, 256, 231, 225, 156, 78,,, -5, 4, 1, 3, 3, 3, 1, 3, 384, 231, 225, 156, 78,,, -5, 4, 1, 3, 3, 3, 2, 1, 128, 231, 225, 156, 78,,, -5, 4, 1, 3, 3, 3, 2, 1, 256, 231, 225, 156, 78,,, -5, 4, 1, 3, 3, 3, 2, 1, 384, 231, 225, 156, 78,,, -5, 4, 1, 3, 3, 3, 2, 2, 128, 231, 225, 156, 78,,, -5, 4, 1, 3, 3, 3, 2, 2, 256, 231, 225, 156, 78,,, -5, 4, 1, 3, 3, 3, 2, 2, 384, 231, 225, 156, 78,,, -5, 4, 1, 3, 3, 3, 2, 3, 128, 231, 225, 156, 78,,, -5, 4, 1, 3, 3, 3, 2, 3, 256, 231, 225, 156, 78,,, -5, 4, 1, 3, 3, 3, 2, 3, 384, 231, 225, 156, 78,,, -5, 4, 1, 3, 3, 3, 3, 1, 128, 231, 225, 156, 78,,, -5, 4, 1, 3, 3, 3, 3, 1, 256, 231, 225, 156, 78,,, -5, 4, 1, 3, 3, 3, 3, 1, 384, 231, 225, 156, 78,,, -5, 4, 1, 3, 3, 3, 3, 2, 128, 231, 225, 156, 78,,, -5, 4, 1, 3, 3, 3, 3, 2, 256, 231, 225, 156, 78,,, -5, 4, 1, 3, 3, 3, 3, 2, 384, 231, 225, 156, 78,,, -5, 4, 1, 3, 3, 3, 3, 3, 128, 231, 225, 156, 78,,, -5, 4, 1, 3, 3, 3, 3, 3, 256, 231, 225, 156, 78,,, -5, 4, 1, 3, 3, 3, 3, 3, 384, 231, 225, 156, 78,,, -5, 4, 1, 4, 1, 1, 1, 1, 128, 240, 240, 207, 103,,, -5, 4, 1, 4, 1, 1, 1, 1, 256, 240, 240, 207, 103,,, -5, 4, 1, 4, 1, 1, 1, 1, 384, 240, 240, 207, 103,,, -5, 4, 1, 4, 2, 2, 1, 1, 128, 240, 240, 207, 103,,, -5, 4, 1, 4, 2, 2, 1, 1, 256, 240, 240, 207, 103,,, -5, 4, 1, 4, 2, 2, 1, 1, 384, 240, 240, 207, 103,,, -5, 4, 1, 4, 2, 2, 1, 2, 128, 240, 240, 207, 103,,, -5, 4, 1, 4, 2, 2, 1, 2, 256, 240, 240, 207, 103,,, -5, 4, 1, 4, 2, 2, 1, 2, 384, 240, 240, 207, 103,,, -5, 4, 1, 4, 2, 2, 2, 1, 128, 240, 240, 207, 103,,, -5, 4, 1, 4, 2, 2, 2, 1, 256, 240, 240, 207, 103,,, -5, 4, 1, 4, 2, 2, 2, 1, 384, 240, 240, 207, 103,,, -5, 4, 1, 4, 2, 2, 2, 2, 128, 240, 240, 207, 103,,, -5, 4, 1, 4, 2, 2, 2, 2, 256, 240, 240, 207, 103,,, -5, 4, 1, 4, 2, 2, 2, 2, 384, 240, 240, 207, 103,,, -5, 4, 1, 4, 3, 3, 1, 1, 128, 240, 240, 207, 103,,, -5, 4, 1, 4, 3, 3, 1, 1, 256, 240, 240, 207, 103,,, -5, 4, 1, 4, 3, 3, 1, 1, 384, 240, 240, 207, 103,,, -5, 4, 1, 4, 3, 3, 1, 2, 128, 240, 240, 207, 103,,, -5, 4, 1, 4, 3, 3, 1, 2, 256, 240, 240, 207, 103,,, -5, 4, 1, 4, 3, 3, 1, 2, 384, 240, 240, 207, 103,,, -5, 4, 1, 4, 3, 3, 1, 3, 128, 240, 240, 207, 103,,, -5, 4, 1, 4, 3, 3, 1, 3, 256, 240, 240, 207, 103,,, -5, 4, 1, 4, 3, 3, 1, 3, 384, 240, 240, 207, 103,,, -5, 4, 1, 4, 3, 3, 2, 1, 128, 240, 240, 207, 103,,, -5, 4, 1, 4, 3, 3, 2, 1, 256, 240, 240, 207, 103,,, -5, 4, 1, 4, 3, 3, 2, 1, 384, 240, 240, 207, 103,,, -5, 4, 1, 4, 3, 3, 2, 2, 128, 240, 240, 207, 103,,, -5, 4, 1, 4, 3, 3, 2, 2, 256, 240, 240, 207, 103,,, -5, 4, 1, 4, 3, 3, 2, 2, 384, 240, 240, 207, 103,,, -5, 4, 1, 4, 3, 3, 2, 3, 128, 240, 240, 207, 103,,, -5, 4, 1, 4, 3, 3, 2, 3, 256, 240, 240, 207, 103,,, -5, 4, 1, 4, 3, 3, 2, 3, 384, 240, 240, 207, 103,,, -5, 4, 1, 4, 3, 3, 3, 1, 128, 240, 240, 207, 103,,, -5, 4, 1, 4, 3, 3, 3, 1, 256, 240, 240, 207, 103,,, -5, 4, 1, 4, 3, 3, 3, 1, 384, 240, 240, 207, 103,,, -5, 4, 1, 4, 3, 3, 3, 2, 128, 240, 240, 207, 103,,, -5, 4, 1, 4, 3, 3, 3, 2, 256, 240, 240, 207, 103,,, -5, 4, 1, 4, 3, 3, 3, 2, 384, 240, 240, 207, 103,,, -5, 4, 1, 4, 3, 3, 3, 3, 128, 240, 240, 207, 103,,, -5, 4, 1, 4, 3, 3, 3, 3, 256, 240, 240, 207, 103,,, -5, 4, 1, 4, 3, 3, 3, 3, 384, 240, 240, 207, 103,,, -5, 4, 2, 1, 1, 1, 1, 1, 128, 79, 79, 54, 28,,, -5, 4, 2, 1, 1, 1, 1, 1, 256, 79, 79, 54, 28,,, -5, 4, 2, 1, 1, 1, 1, 1, 384, 79, 79, 54, 28,,, -5, 4, 2, 1, 2, 2, 1, 1, 128, 79, 79, 54, 28,,, -5, 4, 2, 1, 2, 2, 1, 1, 256, 79, 79, 54, 28,,, -5, 4, 2, 1, 2, 2, 1, 1, 384, 79, 79, 54, 28,,, -5, 4, 2, 1, 2, 2, 1, 2, 128, 79, 79, 54, 28,,, -5, 4, 2, 1, 2, 2, 1, 2, 256, 79, 79, 54, 28,,, -5, 4, 2, 1, 2, 2, 1, 2, 384, 79, 79, 54, 28,,, -5, 4, 2, 1, 2, 2, 2, 1, 128, 79, 79, 54, 28,,, -5, 4, 2, 1, 2, 2, 2, 1, 256, 79, 79, 54, 28,,, -5, 4, 2, 1, 2, 2, 2, 1, 384, 79, 79, 54, 28,,, -5, 4, 2, 1, 2, 2, 2, 2, 128, 79, 79, 54, 28,,, -5, 4, 2, 1, 2, 2, 2, 2, 256, 79, 79, 54, 28,,, -5, 4, 2, 1, 2, 2, 2, 2, 384, 79, 79, 54, 28,,, -5, 4, 2, 1, 3, 3, 1, 1, 128, 79, 77, 54, 28,,, -5, 4, 2, 1, 3, 3, 1, 1, 256, 79, 77, 54, 28,,, -5, 4, 2, 1, 3, 3, 1, 1, 384, 79, 77, 54, 28,,, -5, 4, 2, 1, 3, 3, 1, 2, 128, 79, 77, 54, 28,,, -5, 4, 2, 1, 3, 3, 1, 2, 256, 79, 77, 54, 28,,, -5, 4, 2, 1, 3, 3, 1, 2, 384, 79, 77, 54, 28,,, -5, 4, 2, 1, 3, 3, 1, 3, 128, 79, 77, 54, 28,,, -5, 4, 2, 1, 3, 3, 1, 3, 256, 79, 77, 54, 28,,, -5, 4, 2, 1, 3, 3, 1, 3, 384, 79, 77, 54, 28,,, -5, 4, 2, 1, 3, 3, 2, 1, 128, 79, 77, 54, 28,,, -5, 4, 2, 1, 3, 3, 2, 1, 256, 79, 77, 54, 28,,, -5, 4, 2, 1, 3, 3, 2, 1, 384, 79, 77, 54, 28,,, -5, 4, 2, 1, 3, 3, 2, 2, 128, 79, 77, 54, 28,,, -5, 4, 2, 1, 3, 3, 2, 2, 256, 79, 77, 54, 28,,, -5, 4, 2, 1, 3, 3, 2, 2, 384, 79, 77, 54, 28,,, -5, 4, 2, 1, 3, 3, 2, 3, 128, 79, 77, 54, 28,,, -5, 4, 2, 1, 3, 3, 2, 3, 256, 79, 77, 54, 28,,, -5, 4, 2, 1, 3, 3, 2, 3, 384, 79, 77, 54, 28,,, -5, 4, 2, 1, 3, 3, 3, 1, 128, 79, 77, 54, 28,,, -5, 4, 2, 1, 3, 3, 3, 1, 256, 79, 77, 54, 28,,, -5, 4, 2, 1, 3, 3, 3, 1, 384, 79, 77, 54, 28,,, -5, 4, 2, 1, 3, 3, 3, 2, 128, 79, 77, 54, 28,,, -5, 4, 2, 1, 3, 3, 3, 2, 256, 79, 77, 54, 28,,, -5, 4, 2, 1, 3, 3, 3, 2, 384, 79, 77, 54, 28,,, -5, 4, 2, 1, 3, 3, 3, 3, 128, 79, 77, 54, 28,,, -5, 4, 2, 1, 3, 3, 3, 3, 256, 79, 77, 54, 28,,, -5, 4, 2, 1, 3, 3, 3, 3, 384, 79, 77, 54, 28,,, -5, 4, 2, 2, 1, 1, 1, 1, 128, 155, 155, 105, 53,,, -5, 4, 2, 2, 1, 1, 1, 1, 256, 155, 155, 105, 53,,, -5, 4, 2, 2, 1, 1, 1, 1, 384, 155, 155, 105, 53,,, -5, 4, 2, 2, 2, 2, 1, 1, 128, 155, 155, 105, 53,,, -5, 4, 2, 2, 2, 2, 1, 1, 256, 155, 155, 105, 53,,, -5, 4, 2, 2, 2, 2, 1, 1, 384, 155, 155, 105, 53,,, -5, 4, 2, 2, 2, 2, 1, 2, 128, 155, 155, 105, 53,,, -5, 4, 2, 2, 2, 2, 1, 2, 256, 155, 155, 105, 53,,, -5, 4, 2, 2, 2, 2, 1, 2, 384, 155, 155, 105, 53,,, -5, 4, 2, 2, 2, 2, 2, 1, 128, 155, 155, 105, 53,,, -5, 4, 2, 2, 2, 2, 2, 1, 256, 155, 155, 105, 53,,, -5, 4, 2, 2, 2, 2, 2, 1, 384, 155, 155, 105, 53,,, -5, 4, 2, 2, 2, 2, 2, 2, 128, 155, 155, 105, 53,,, -5, 4, 2, 2, 2, 2, 2, 2, 256, 155, 155, 105, 53,,, -5, 4, 2, 2, 2, 2, 2, 2, 384, 155, 155, 105, 53,,, -5, 4, 2, 2, 3, 3, 1, 1, 128, 155, 151, 105, 53,,, -5, 4, 2, 2, 3, 3, 1, 1, 256, 155, 151, 105, 53,,, -5, 4, 2, 2, 3, 3, 1, 1, 384, 155, 151, 105, 53,,, -5, 4, 2, 2, 3, 3, 1, 2, 128, 155, 151, 105, 53,,, -5, 4, 2, 2, 3, 3, 1, 2, 256, 155, 151, 105, 53,,, -5, 4, 2, 2, 3, 3, 1, 2, 384, 155, 151, 105, 53,,, -5, 4, 2, 2, 3, 3, 1, 3, 128, 155, 151, 105, 53,,, -5, 4, 2, 2, 3, 3, 1, 3, 256, 155, 151, 105, 53,,, -5, 4, 2, 2, 3, 3, 1, 3, 384, 155, 151, 105, 53,,, -5, 4, 2, 2, 3, 3, 2, 1, 128, 155, 151, 105, 53,,, -5, 4, 2, 2, 3, 3, 2, 1, 256, 155, 151, 105, 53,,, -5, 4, 2, 2, 3, 3, 2, 1, 384, 155, 151, 105, 53,,, -5, 4, 2, 2, 3, 3, 2, 2, 128, 155, 151, 105, 53,,, -5, 4, 2, 2, 3, 3, 2, 2, 256, 155, 151, 105, 53,,, -5, 4, 2, 2, 3, 3, 2, 2, 384, 155, 151, 105, 53,,, -5, 4, 2, 2, 3, 3, 2, 3, 128, 155, 151, 105, 53,,, -5, 4, 2, 2, 3, 3, 2, 3, 256, 155, 151, 105, 53,,, -5, 4, 2, 2, 3, 3, 2, 3, 384, 155, 151, 105, 53,,, -5, 4, 2, 2, 3, 3, 3, 1, 128, 155, 151, 105, 53,,, -5, 4, 2, 2, 3, 3, 3, 1, 256, 155, 151, 105, 53,,, -5, 4, 2, 2, 3, 3, 3, 1, 384, 155, 151, 105, 53,,, -5, 4, 2, 2, 3, 3, 3, 2, 128, 155, 151, 105, 53,,, -5, 4, 2, 2, 3, 3, 3, 2, 256, 155, 151, 105, 53,,, -5, 4, 2, 2, 3, 3, 3, 2, 384, 155, 151, 105, 53,,, -5, 4, 2, 2, 3, 3, 3, 3, 128, 155, 151, 105, 53,,, -5, 4, 2, 2, 3, 3, 3, 3, 256, 155, 151, 105, 53,,, -5, 4, 2, 2, 3, 3, 3, 3, 384, 155, 151, 105, 53,,, -5, 4, 2, 3, 1, 1, 1, 1, 128, 231, 231, 156, 78,,, -5, 4, 2, 3, 1, 1, 1, 1, 256, 231, 231, 156, 78,,, -5, 4, 2, 3, 1, 1, 1, 1, 384, 231, 231, 156, 78,,, -5, 4, 2, 3, 2, 2, 1, 1, 128, 231, 231, 156, 78,,, -5, 4, 2, 3, 2, 2, 1, 1, 256, 231, 231, 156, 78,,, -5, 4, 2, 3, 2, 2, 1, 1, 384, 231, 231, 156, 78,,, -5, 4, 2, 3, 2, 2, 1, 2, 128, 231, 231, 156, 78,,, -5, 4, 2, 3, 2, 2, 1, 2, 256, 231, 231, 156, 78,,, -5, 4, 2, 3, 2, 2, 1, 2, 384, 231, 231, 156, 78,,, -5, 4, 2, 3, 2, 2, 2, 1, 128, 231, 231, 156, 78,,, -5, 4, 2, 3, 2, 2, 2, 1, 256, 231, 231, 156, 78,,, -5, 4, 2, 3, 2, 2, 2, 1, 384, 231, 231, 156, 78,,, -5, 4, 2, 3, 2, 2, 2, 2, 128, 231, 231, 156, 78,,, -5, 4, 2, 3, 2, 2, 2, 2, 256, 231, 231, 156, 78,,, -5, 4, 2, 3, 2, 2, 2, 2, 384, 231, 231, 156, 78,,, -5, 4, 2, 3, 3, 3, 1, 1, 128, 231, 225, 156, 78,,, -5, 4, 2, 3, 3, 3, 1, 1, 256, 231, 225, 156, 78,,, -5, 4, 2, 3, 3, 3, 1, 1, 384, 231, 225, 156, 78,,, -5, 4, 2, 3, 3, 3, 1, 2, 128, 231, 225, 156, 78,,, -5, 4, 2, 3, 3, 3, 1, 2, 256, 231, 225, 156, 78,,, -5, 4, 2, 3, 3, 3, 1, 2, 384, 231, 225, 156, 78,,, -5, 4, 2, 3, 3, 3, 1, 3, 128, 231, 225, 156, 78,,, -5, 4, 2, 3, 3, 3, 1, 3, 256, 231, 225, 156, 78,,, -5, 4, 2, 3, 3, 3, 1, 3, 384, 231, 225, 156, 78,,, -5, 4, 2, 3, 3, 3, 2, 1, 128, 231, 225, 156, 78,,, -5, 4, 2, 3, 3, 3, 2, 1, 256, 231, 225, 156, 78,,, -5, 4, 2, 3, 3, 3, 2, 1, 384, 231, 225, 156, 78,,, -5, 4, 2, 3, 3, 3, 2, 2, 128, 231, 225, 156, 78,,, -5, 4, 2, 3, 3, 3, 2, 2, 256, 231, 225, 156, 78,,, -5, 4, 2, 3, 3, 3, 2, 2, 384, 231, 225, 156, 78,,, -5, 4, 2, 3, 3, 3, 2, 3, 128, 231, 225, 156, 78,,, -5, 4, 2, 3, 3, 3, 2, 3, 256, 231, 225, 156, 78,,, -5, 4, 2, 3, 3, 3, 2, 3, 384, 231, 225, 156, 78,,, -5, 4, 2, 3, 3, 3, 3, 1, 128, 231, 225, 156, 78,,, -5, 4, 2, 3, 3, 3, 3, 1, 256, 231, 225, 156, 78,,, -5, 4, 2, 3, 3, 3, 3, 1, 384, 231, 225, 156, 78,,, -5, 4, 2, 3, 3, 3, 3, 2, 128, 231, 225, 156, 78,,, -5, 4, 2, 3, 3, 3, 3, 2, 256, 231, 225, 156, 78,,, -5, 4, 2, 3, 3, 3, 3, 2, 384, 231, 225, 156, 78,,, -5, 4, 2, 3, 3, 3, 3, 3, 128, 231, 225, 156, 78,,, -5, 4, 2, 3, 3, 3, 3, 3, 256, 231, 225, 156, 78,,, -5, 4, 2, 3, 3, 3, 3, 3, 384, 231, 225, 156, 78,,, -5, 4, 2, 4, 1, 1, 1, 1, 128, 240, 240, 207, 103,,, -5, 4, 2, 4, 1, 1, 1, 1, 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4, 5, 2, 3, 3, 3, 2, 256, 155, 151, 105, 53,,, -5, 4, 5, 2, 3, 3, 3, 2, 384, 155, 151, 105, 53,,, -5, 4, 5, 2, 3, 3, 3, 3, 128, 155, 151, 105, 53,,, -5, 4, 5, 2, 3, 3, 3, 3, 256, 155, 151, 105, 53,,, -5, 4, 5, 2, 3, 3, 3, 3, 384, 155, 151, 105, 53,,, -5, 4, 5, 3, 1, 1, 1, 1, 128, 231, 231, 156, 78,,, -5, 4, 5, 3, 1, 1, 1, 1, 256, 231, 231, 156, 78,,, -5, 4, 5, 3, 1, 1, 1, 1, 384, 231, 231, 156, 78,,, -5, 4, 5, 3, 2, 2, 1, 1, 128, 231, 231, 156, 78,,, -5, 4, 5, 3, 2, 2, 1, 1, 256, 231, 231, 156, 78,,, -5, 4, 5, 3, 2, 2, 1, 1, 384, 231, 231, 156, 78,,, -5, 4, 5, 3, 2, 2, 1, 2, 128, 231, 231, 156, 78,,, -5, 4, 5, 3, 2, 2, 1, 2, 256, 231, 231, 156, 78,,, -5, 4, 5, 3, 2, 2, 1, 2, 384, 231, 231, 156, 78,,, -5, 4, 5, 3, 2, 2, 2, 1, 128, 231, 231, 156, 78,,, -5, 4, 5, 3, 2, 2, 2, 1, 256, 231, 231, 156, 78,,, -5, 4, 5, 3, 2, 2, 2, 1, 384, 231, 231, 156, 78,,, -5, 4, 5, 3, 2, 2, 2, 2, 128, 231, 231, 156, 78,,, -5, 4, 5, 3, 2, 2, 2, 2, 256, 231, 231, 156, 78,,, -5, 4, 5, 3, 2, 2, 2, 2, 384, 231, 231, 156, 78,,, -5, 4, 5, 3, 3, 3, 1, 1, 128, 231, 225, 156, 78,,, -5, 4, 5, 3, 3, 3, 1, 1, 256, 231, 225, 156, 78,,, -5, 4, 5, 3, 3, 3, 1, 1, 384, 231, 225, 156, 78,,, -5, 4, 5, 3, 3, 3, 1, 2, 128, 231, 225, 156, 78,,, -5, 4, 5, 3, 3, 3, 1, 2, 256, 231, 225, 156, 78,,, -5, 4, 5, 3, 3, 3, 1, 2, 384, 231, 225, 156, 78,,, -5, 4, 5, 3, 3, 3, 1, 3, 128, 231, 225, 156, 78,,, -5, 4, 5, 3, 3, 3, 1, 3, 256, 231, 225, 156, 78,,, -5, 4, 5, 3, 3, 3, 1, 3, 384, 231, 225, 156, 78,,, -5, 4, 5, 3, 3, 3, 2, 1, 128, 231, 225, 156, 78,,, -5, 4, 5, 3, 3, 3, 2, 1, 256, 231, 225, 156, 78,,, -5, 4, 5, 3, 3, 3, 2, 1, 384, 231, 225, 156, 78,,, -5, 4, 5, 3, 3, 3, 2, 2, 128, 231, 225, 156, 78,,, -5, 4, 5, 3, 3, 3, 2, 2, 256, 231, 225, 156, 78,,, -5, 4, 5, 3, 3, 3, 2, 2, 384, 231, 225, 156, 78,,, -5, 4, 5, 3, 3, 3, 2, 3, 128, 231, 225, 156, 78,,, -5, 4, 5, 3, 3, 3, 2, 3, 256, 231, 225, 156, 78,,, -5, 4, 5, 3, 3, 3, 2, 3, 384, 231, 225, 156, 78,,, -5, 4, 5, 3, 3, 3, 3, 1, 128, 231, 225, 156, 78,,, -5, 4, 5, 3, 3, 3, 3, 1, 256, 231, 225, 156, 78,,, -5, 4, 5, 3, 3, 3, 3, 1, 384, 231, 225, 156, 78,,, -5, 4, 5, 3, 3, 3, 3, 2, 128, 231, 225, 156, 78,,, -5, 4, 5, 3, 3, 3, 3, 2, 256, 231, 225, 156, 78,,, -5, 4, 5, 3, 3, 3, 3, 2, 384, 231, 225, 156, 78,,, -5, 4, 5, 3, 3, 3, 3, 3, 128, 231, 225, 156, 78,,, -5, 4, 5, 3, 3, 3, 3, 3, 256, 231, 225, 156, 78,,, -5, 4, 5, 3, 3, 3, 3, 3, 384, 231, 225, 156, 78,,, -5, 4, 5, 4, 1, 1, 1, 1, 128, 240, 240, 207, 103,,, -5, 4, 5, 4, 1, 1, 1, 1, 256, 240, 240, 207, 103,,, -5, 4, 5, 4, 1, 1, 1, 1, 384, 240, 240, 207, 103,,, -5, 4, 5, 4, 2, 2, 1, 1, 128, 240, 240, 207, 103,,, -5, 4, 5, 4, 2, 2, 1, 1, 256, 240, 240, 207, 103,,, -5, 4, 5, 4, 2, 2, 1, 1, 384, 240, 240, 207, 103,,, -5, 4, 5, 4, 2, 2, 1, 2, 128, 240, 240, 207, 103,,, -5, 4, 5, 4, 2, 2, 1, 2, 256, 240, 240, 207, 103,,, -5, 4, 5, 4, 2, 2, 1, 2, 384, 240, 240, 207, 103,,, -5, 4, 5, 4, 2, 2, 2, 1, 128, 240, 240, 207, 103,,, -5, 4, 5, 4, 2, 2, 2, 1, 256, 240, 240, 207, 103,,, -5, 4, 5, 4, 2, 2, 2, 1, 384, 240, 240, 207, 103,,, -5, 4, 5, 4, 2, 2, 2, 2, 128, 240, 240, 207, 103,,, -5, 4, 5, 4, 2, 2, 2, 2, 256, 240, 240, 207, 103,,, -5, 4, 5, 4, 2, 2, 2, 2, 384, 240, 240, 207, 103,,, -5, 4, 5, 4, 3, 3, 1, 1, 128, 240, 240, 207, 103,,, -5, 4, 5, 4, 3, 3, 1, 1, 256, 240, 240, 207, 103,,, -5, 4, 5, 4, 3, 3, 1, 1, 384, 240, 240, 207, 103,,, -5, 4, 5, 4, 3, 3, 1, 2, 128, 240, 240, 207, 103,,, -5, 4, 5, 4, 3, 3, 1, 2, 256, 240, 240, 207, 103,,, -5, 4, 5, 4, 3, 3, 1, 2, 384, 240, 240, 207, 103,,, -5, 4, 5, 4, 3, 3, 1, 3, 128, 240, 240, 207, 103,,, -5, 4, 5, 4, 3, 3, 1, 3, 256, 240, 240, 207, 103,,, -5, 4, 5, 4, 3, 3, 1, 3, 384, 240, 240, 207, 103,,, -5, 4, 5, 4, 3, 3, 2, 1, 128, 240, 240, 207, 103,,, -5, 4, 5, 4, 3, 3, 2, 1, 256, 240, 240, 207, 103,,, -5, 4, 5, 4, 3, 3, 2, 1, 384, 240, 240, 207, 103,,, -5, 4, 5, 4, 3, 3, 2, 2, 128, 240, 240, 207, 103,,, -5, 4, 5, 4, 3, 3, 2, 2, 256, 240, 240, 207, 103,,, -5, 4, 5, 4, 3, 3, 2, 2, 384, 240, 240, 207, 103,,, -5, 4, 5, 4, 3, 3, 2, 3, 128, 240, 240, 207, 103,,, -5, 4, 5, 4, 3, 3, 2, 3, 256, 240, 240, 207, 103,,, -5, 4, 5, 4, 3, 3, 2, 3, 384, 240, 240, 207, 103,,, -5, 4, 5, 4, 3, 3, 3, 1, 128, 240, 240, 207, 103,,, -5, 4, 5, 4, 3, 3, 3, 1, 256, 240, 240, 207, 103,,, -5, 4, 5, 4, 3, 3, 3, 1, 384, 240, 240, 207, 103,,, -5, 4, 5, 4, 3, 3, 3, 2, 128, 240, 240, 207, 103,,, -5, 4, 5, 4, 3, 3, 3, 2, 256, 240, 240, 207, 103,,, -5, 4, 5, 4, 3, 3, 3, 2, 384, 240, 240, 207, 103,,, -5, 4, 5, 4, 3, 3, 3, 3, 128, 240, 240, 207, 103,,, -5, 4, 5, 4, 3, 3, 3, 3, 256, 240, 240, 207, 103,,, -5, 4, 5, 4, 3, 3, 3, 3, 384, 240, 240, 207, 103,,, -5, 5, 1, 1, 1, 1, 1, 1, 128, 80, 80, 55,,,, -5, 5, 1, 1, 1, 1, 1, 1, 256, 80, 80, 55,,,, -5, 5, 1, 1, 1, 1, 1, 1, 384, 80, 80, 55,,,, -5, 5, 1, 1, 2, 2, 1, 1, 128, 80, 78, 55,,,, -5, 5, 1, 1, 2, 2, 1, 1, 256, 80, 78, 55,,,, -5, 5, 1, 1, 2, 2, 1, 1, 384, 80, 78, 55,,,, -5, 5, 1, 1, 2, 2, 1, 2, 128, 80, 78, 55,,,, -5, 5, 1, 1, 2, 2, 1, 2, 256, 80, 78, 55,,,, -5, 5, 1, 1, 2, 2, 1, 2, 384, 80, 78, 55,,,, -5, 5, 1, 1, 2, 2, 2, 1, 128, 80, 78, 55,,,, -5, 5, 1, 1, 2, 2, 2, 1, 256, 80, 78, 55,,,, -5, 5, 1, 1, 2, 2, 2, 1, 384, 80, 78, 55,,,, -5, 5, 1, 1, 2, 2, 2, 2, 128, 80, 78, 55,,,, -5, 5, 1, 1, 2, 2, 2, 2, 256, 80, 78, 55,,,, -5, 5, 1, 1, 2, 2, 2, 2, 384, 80, 78, 55,,,, -5, 5, 1, 1, 3, 3, 1, 1, 128, 80, 75, 55,,,, -5, 5, 1, 1, 3, 3, 1, 1, 256, 80, 75, 55,,,, -5, 5, 1, 1, 3, 3, 1, 1, 384, 80, 75, 55,,,, -5, 5, 1, 1, 3, 3, 1, 2, 128, 80, 75, 55,,,, -5, 5, 1, 1, 3, 3, 1, 2, 256, 80, 75, 55,,,, -5, 5, 1, 1, 3, 3, 1, 2, 384, 80, 75, 55,,,, -5, 5, 1, 1, 3, 3, 1, 3, 128, 80, 75, 55,,,, -5, 5, 1, 1, 3, 3, 1, 3, 256, 80, 75, 55,,,, -5, 5, 1, 1, 3, 3, 1, 3, 384, 80, 75, 55,,,, -5, 5, 1, 1, 3, 3, 2, 1, 128, 80, 75, 55,,,, -5, 5, 1, 1, 3, 3, 2, 1, 256, 80, 75, 55,,,, -5, 5, 1, 1, 3, 3, 2, 1, 384, 80, 75, 55,,,, -5, 5, 1, 1, 3, 3, 2, 2, 128, 80, 75, 55,,,, -5, 5, 1, 1, 3, 3, 2, 2, 256, 80, 75, 55,,,, -5, 5, 1, 1, 3, 3, 2, 2, 384, 80, 75, 55,,,, -5, 5, 1, 1, 3, 3, 2, 3, 128, 80, 75, 55,,,, -5, 5, 1, 1, 3, 3, 2, 3, 256, 80, 75, 55,,,, -5, 5, 1, 1, 3, 3, 2, 3, 384, 80, 75, 55,,,, -5, 5, 1, 1, 3, 3, 3, 1, 128, 80, 75, 55,,,, -5, 5, 1, 1, 3, 3, 3, 1, 256, 80, 75, 55,,,, -5, 5, 1, 1, 3, 3, 3, 1, 384, 80, 75, 55,,,, -5, 5, 1, 1, 3, 3, 3, 2, 128, 80, 75, 55,,,, -5, 5, 1, 1, 3, 3, 3, 2, 256, 80, 75, 55,,,, -5, 5, 1, 1, 3, 3, 3, 2, 384, 80, 75, 55,,,, -5, 5, 1, 1, 3, 3, 3, 3, 128, 80, 75, 55,,,, -5, 5, 1, 1, 3, 3, 3, 3, 256, 80, 75, 55,,,, -5, 5, 1, 1, 3, 3, 3, 3, 384, 80, 75, 55,,,, -5, 5, 1, 2, 1, 1, 1, 1, 128, 156, 156, 106,,,, -5, 5, 1, 2, 1, 1, 1, 1, 256, 156, 156, 106,,,, -5, 5, 1, 2, 1, 1, 1, 1, 384, 156, 156, 106,,,, -5, 5, 1, 2, 2, 2, 1, 1, 128, 156, 152, 106,,,, -5, 5, 1, 2, 2, 2, 1, 1, 256, 156, 152, 106,,,, -5, 5, 1, 2, 2, 2, 1, 1, 384, 156, 152, 106,,,, -5, 5, 1, 2, 2, 2, 1, 2, 128, 156, 152, 106,,,, -5, 5, 1, 2, 2, 2, 1, 2, 256, 156, 152, 106,,,, -5, 5, 1, 2, 2, 2, 1, 2, 384, 156, 152, 106,,,, -5, 5, 1, 2, 2, 2, 2, 1, 128, 156, 152, 106,,,, -5, 5, 1, 2, 2, 2, 2, 1, 256, 156, 152, 106,,,, -5, 5, 1, 2, 2, 2, 2, 1, 384, 156, 152, 106,,,, -5, 5, 1, 2, 2, 2, 2, 2, 128, 156, 152, 106,,,, -5, 5, 1, 2, 2, 2, 2, 2, 256, 156, 152, 106,,,, -5, 5, 1, 2, 2, 2, 2, 2, 384, 156, 152, 106,,,, -5, 5, 1, 2, 3, 3, 1, 1, 128, 156, 146, 106,,,, -5, 5, 1, 2, 3, 3, 1, 1, 256, 156, 146, 106,,,, -5, 5, 1, 2, 3, 3, 1, 1, 384, 156, 146, 106,,,, -5, 5, 1, 2, 3, 3, 1, 2, 128, 156, 146, 106,,,, -5, 5, 1, 2, 3, 3, 1, 2, 256, 156, 146, 106,,,, -5, 5, 1, 2, 3, 3, 1, 2, 384, 156, 146, 106,,,, -5, 5, 1, 2, 3, 3, 1, 3, 128, 156, 146, 106,,,, -5, 5, 1, 2, 3, 3, 1, 3, 256, 156, 146, 106,,,, -5, 5, 1, 2, 3, 3, 1, 3, 384, 156, 146, 106,,,, -5, 5, 1, 2, 3, 3, 2, 1, 128, 156, 146, 106,,,, -5, 5, 1, 2, 3, 3, 2, 1, 256, 156, 146, 106,,,, -5, 5, 1, 2, 3, 3, 2, 1, 384, 156, 146, 106,,,, -5, 5, 1, 2, 3, 3, 2, 2, 128, 156, 146, 106,,,, -5, 5, 1, 2, 3, 3, 2, 2, 256, 156, 146, 106,,,, -5, 5, 1, 2, 3, 3, 2, 2, 384, 156, 146, 106,,,, -5, 5, 1, 2, 3, 3, 2, 3, 128, 156, 146, 106,,,, -5, 5, 1, 2, 3, 3, 2, 3, 256, 156, 146, 106,,,, -5, 5, 1, 2, 3, 3, 2, 3, 384, 156, 146, 106,,,, -5, 5, 1, 2, 3, 3, 3, 1, 128, 156, 146, 106,,,, -5, 5, 1, 2, 3, 3, 3, 1, 256, 156, 146, 106,,,, -5, 5, 1, 2, 3, 3, 3, 1, 384, 156, 146, 106,,,, -5, 5, 1, 2, 3, 3, 3, 2, 128, 156, 146, 106,,,, -5, 5, 1, 2, 3, 3, 3, 2, 256, 156, 146, 106,,,, -5, 5, 1, 2, 3, 3, 3, 2, 384, 156, 146, 106,,,, -5, 5, 1, 2, 3, 3, 3, 3, 128, 156, 146, 106,,,, -5, 5, 1, 2, 3, 3, 3, 3, 256, 156, 146, 106,,,, -5, 5, 1, 2, 3, 3, 3, 3, 384, 156, 146, 106,,,, -5, 5, 1, 3, 1, 1, 1, 1, 128, 232, 232, 157,,,, -5, 5, 1, 3, 1, 1, 1, 1, 256, 232, 232, 157,,,, -5, 5, 1, 3, 1, 1, 1, 1, 384, 232, 232, 157,,,, -5, 5, 1, 3, 2, 2, 1, 1, 128, 232, 226, 157,,,, -5, 5, 1, 3, 2, 2, 1, 1, 256, 232, 226, 157,,,, -5, 5, 1, 3, 2, 2, 1, 1, 384, 232, 226, 157,,,, -5, 5, 1, 3, 2, 2, 1, 2, 128, 232, 226, 157,,,, -5, 5, 1, 3, 2, 2, 1, 2, 256, 232, 226, 157,,,, -5, 5, 1, 3, 2, 2, 1, 2, 384, 232, 226, 157,,,, -5, 5, 1, 3, 2, 2, 2, 1, 128, 232, 226, 157,,,, -5, 5, 1, 3, 2, 2, 2, 1, 256, 232, 226, 157,,,, -5, 5, 1, 3, 2, 2, 2, 1, 384, 232, 226, 157,,,, -5, 5, 1, 3, 2, 2, 2, 2, 128, 232, 226, 157,,,, -5, 5, 1, 3, 2, 2, 2, 2, 256, 232, 226, 157,,,, -5, 5, 1, 3, 2, 2, 2, 2, 384, 232, 226, 157,,,, -5, 5, 1, 3, 3, 3, 1, 1, 128, 232, 217, 157,,,, -5, 5, 1, 3, 3, 3, 1, 1, 256, 232, 217, 157,,,, -5, 5, 1, 3, 3, 3, 1, 1, 384, 232, 217, 157,,,, -5, 5, 1, 3, 3, 3, 1, 2, 128, 232, 217, 157,,,, -5, 5, 1, 3, 3, 3, 1, 2, 256, 232, 217, 157,,,, -5, 5, 1, 3, 3, 3, 1, 2, 384, 232, 217, 157,,,, -5, 5, 1, 3, 3, 3, 1, 3, 128, 232, 217, 157,,,, -5, 5, 1, 3, 3, 3, 1, 3, 256, 232, 217, 157,,,, -5, 5, 1, 3, 3, 3, 1, 3, 384, 232, 217, 157,,,, -5, 5, 1, 3, 3, 3, 2, 1, 128, 232, 217, 157,,,, -5, 5, 1, 3, 3, 3, 2, 1, 256, 232, 217, 157,,,, -5, 5, 1, 3, 3, 3, 2, 1, 384, 232, 217, 157,,,, -5, 5, 1, 3, 3, 3, 2, 2, 128, 232, 217, 157,,,, -5, 5, 1, 3, 3, 3, 2, 2, 256, 232, 217, 157,,,, -5, 5, 1, 3, 3, 3, 2, 2, 384, 232, 217, 157,,,, -5, 5, 1, 3, 3, 3, 2, 3, 128, 232, 217, 157,,,, -5, 5, 1, 3, 3, 3, 2, 3, 256, 232, 217, 157,,,, -5, 5, 1, 3, 3, 3, 2, 3, 384, 232, 217, 157,,,, -5, 5, 1, 3, 3, 3, 3, 1, 128, 232, 217, 157,,,, -5, 5, 1, 3, 3, 3, 3, 1, 256, 232, 217, 157,,,, -5, 5, 1, 3, 3, 3, 3, 1, 384, 232, 217, 157,,,, -5, 5, 1, 3, 3, 3, 3, 2, 128, 232, 217, 157,,,, -5, 5, 1, 3, 3, 3, 3, 2, 256, 232, 217, 157,,,, -5, 5, 1, 3, 3, 3, 3, 2, 384, 232, 217, 157,,,, -5, 5, 1, 3, 3, 3, 3, 3, 128, 232, 217, 157,,,, -5, 5, 1, 3, 3, 3, 3, 3, 256, 232, 217, 157,,,, -5, 5, 1, 3, 3, 3, 3, 3, 384, 232, 217, 157,,,, -5, 5, 1, 4, 1, 1, 1, 1, 128, 240, 240, 208,,,, -5, 5, 1, 4, 1, 1, 1, 1, 256, 240, 240, 208,,,, -5, 5, 1, 4, 1, 1, 1, 1, 384, 240, 240, 208,,,, -5, 5, 1, 4, 2, 2, 1, 1, 128, 240, 240, 208,,,, -5, 5, 1, 4, 2, 2, 1, 1, 256, 240, 240, 208,,,, -5, 5, 1, 4, 2, 2, 1, 1, 384, 240, 240, 208,,,, -5, 5, 1, 4, 2, 2, 1, 2, 128, 240, 240, 208,,,, -5, 5, 1, 4, 2, 2, 1, 2, 256, 240, 240, 208,,,, -5, 5, 1, 4, 2, 2, 1, 2, 384, 240, 240, 208,,,, -5, 5, 1, 4, 2, 2, 2, 1, 128, 240, 240, 208,,,, -5, 5, 1, 4, 2, 2, 2, 1, 256, 240, 240, 208,,,, -5, 5, 1, 4, 2, 2, 2, 1, 384, 240, 240, 208,,,, -5, 5, 1, 4, 2, 2, 2, 2, 128, 240, 240, 208,,,, -5, 5, 1, 4, 2, 2, 2, 2, 256, 240, 240, 208,,,, -5, 5, 1, 4, 2, 2, 2, 2, 384, 240, 240, 208,,,, -5, 5, 1, 4, 3, 3, 1, 1, 128, 240, 240, 208,,,, -5, 5, 1, 4, 3, 3, 1, 1, 256, 240, 240, 208,,,, -5, 5, 1, 4, 3, 3, 1, 1, 384, 240, 240, 208,,,, -5, 5, 1, 4, 3, 3, 1, 2, 128, 240, 240, 208,,,, -5, 5, 1, 4, 3, 3, 1, 2, 256, 240, 240, 208,,,, -5, 5, 1, 4, 3, 3, 1, 2, 384, 240, 240, 208,,,, -5, 5, 1, 4, 3, 3, 1, 3, 128, 240, 240, 208,,,, -5, 5, 1, 4, 3, 3, 1, 3, 256, 240, 240, 208,,,, -5, 5, 1, 4, 3, 3, 1, 3, 384, 240, 240, 208,,,, -5, 5, 1, 4, 3, 3, 2, 1, 128, 240, 240, 208,,,, -5, 5, 1, 4, 3, 3, 2, 1, 256, 240, 240, 208,,,, -5, 5, 1, 4, 3, 3, 2, 1, 384, 240, 240, 208,,,, -5, 5, 1, 4, 3, 3, 2, 2, 128, 240, 240, 208,,,, -5, 5, 1, 4, 3, 3, 2, 2, 256, 240, 240, 208,,,, -5, 5, 1, 4, 3, 3, 2, 2, 384, 240, 240, 208,,,, -5, 5, 1, 4, 3, 3, 2, 3, 128, 240, 240, 208,,,, -5, 5, 1, 4, 3, 3, 2, 3, 256, 240, 240, 208,,,, -5, 5, 1, 4, 3, 3, 2, 3, 384, 240, 240, 208,,,, -5, 5, 1, 4, 3, 3, 3, 1, 128, 240, 240, 208,,,, -5, 5, 1, 4, 3, 3, 3, 1, 256, 240, 240, 208,,,, -5, 5, 1, 4, 3, 3, 3, 1, 384, 240, 240, 208,,,, -5, 5, 1, 4, 3, 3, 3, 2, 128, 240, 240, 208,,,, -5, 5, 1, 4, 3, 3, 3, 2, 256, 240, 240, 208,,,, -5, 5, 1, 4, 3, 3, 3, 2, 384, 240, 240, 208,,,, -5, 5, 1, 4, 3, 3, 3, 3, 128, 240, 240, 208,,,, -5, 5, 1, 4, 3, 3, 3, 3, 256, 240, 240, 208,,,, -5, 5, 1, 4, 3, 3, 3, 3, 384, 240, 240, 208,,,, -5, 5, 1, 5, 1, 1, 1, 1, 128, 240, 240, 240,,,, -5, 5, 1, 5, 1, 1, 1, 1, 256, 240, 240, 240,,,, -5, 5, 1, 5, 1, 1, 1, 1, 384, 240, 240, 240,,,, -5, 5, 1, 5, 2, 2, 1, 1, 128, 240, 240, 240,,,, -5, 5, 1, 5, 2, 2, 1, 1, 256, 240, 240, 240,,,, -5, 5, 1, 5, 2, 2, 1, 1, 384, 240, 240, 240,,,, -5, 5, 1, 5, 2, 2, 1, 2, 128, 240, 240, 240,,,, -5, 5, 1, 5, 2, 2, 1, 2, 256, 240, 240, 240,,,, -5, 5, 1, 5, 2, 2, 1, 2, 384, 240, 240, 240,,,, -5, 5, 1, 5, 2, 2, 2, 1, 128, 240, 240, 240,,,, -5, 5, 1, 5, 2, 2, 2, 1, 256, 240, 240, 240,,,, -5, 5, 1, 5, 2, 2, 2, 1, 384, 240, 240, 240,,,, -5, 5, 1, 5, 2, 2, 2, 2, 128, 240, 240, 240,,,, -5, 5, 1, 5, 2, 2, 2, 2, 256, 240, 240, 240,,,, -5, 5, 1, 5, 2, 2, 2, 2, 384, 240, 240, 240,,,, -5, 5, 1, 5, 3, 3, 1, 1, 128, 240, 240, 240,,,, -5, 5, 1, 5, 3, 3, 1, 1, 256, 240, 240, 240,,,, -5, 5, 1, 5, 3, 3, 1, 1, 384, 240, 240, 240,,,, -5, 5, 1, 5, 3, 3, 1, 2, 128, 240, 240, 240,,,, -5, 5, 1, 5, 3, 3, 1, 2, 256, 240, 240, 240,,,, -5, 5, 1, 5, 3, 3, 1, 2, 384, 240, 240, 240,,,, -5, 5, 1, 5, 3, 3, 1, 3, 128, 240, 240, 240,,,, -5, 5, 1, 5, 3, 3, 1, 3, 256, 240, 240, 240,,,, -5, 5, 1, 5, 3, 3, 1, 3, 384, 240, 240, 240,,,, -5, 5, 1, 5, 3, 3, 2, 1, 128, 240, 240, 240,,,, -5, 5, 1, 5, 3, 3, 2, 1, 256, 240, 240, 240,,,, -5, 5, 1, 5, 3, 3, 2, 1, 384, 240, 240, 240,,,, -5, 5, 1, 5, 3, 3, 2, 2, 128, 240, 240, 240,,,, -5, 5, 1, 5, 3, 3, 2, 2, 256, 240, 240, 240,,,, -5, 5, 1, 5, 3, 3, 2, 2, 384, 240, 240, 240,,,, -5, 5, 1, 5, 3, 3, 2, 3, 128, 240, 240, 240,,,, -5, 5, 1, 5, 3, 3, 2, 3, 256, 240, 240, 240,,,, -5, 5, 1, 5, 3, 3, 2, 3, 384, 240, 240, 240,,,, -5, 5, 1, 5, 3, 3, 3, 1, 128, 240, 240, 240,,,, -5, 5, 1, 5, 3, 3, 3, 1, 256, 240, 240, 240,,,, -5, 5, 1, 5, 3, 3, 3, 1, 384, 240, 240, 240,,,, -5, 5, 1, 5, 3, 3, 3, 2, 128, 240, 240, 240,,,, -5, 5, 1, 5, 3, 3, 3, 2, 256, 240, 240, 240,,,, -5, 5, 1, 5, 3, 3, 3, 2, 384, 240, 240, 240,,,, -5, 5, 1, 5, 3, 3, 3, 3, 128, 240, 240, 240,,,, -5, 5, 1, 5, 3, 3, 3, 3, 256, 240, 240, 240,,,, -5, 5, 1, 5, 3, 3, 3, 3, 384, 240, 240, 240,,,, -5, 5, 2, 1, 1, 1, 1, 1, 128, 80, 80, 55,,,, -5, 5, 2, 1, 1, 1, 1, 1, 256, 80, 80, 55,,,, -5, 5, 2, 1, 1, 1, 1, 1, 384, 80, 80, 55,,,, -5, 5, 2, 1, 2, 2, 1, 1, 128, 80, 78, 55,,,, -5, 5, 2, 1, 2, 2, 1, 1, 256, 80, 78, 55,,,, -5, 5, 2, 1, 2, 2, 1, 1, 384, 80, 78, 55,,,, -5, 5, 2, 1, 2, 2, 1, 2, 128, 80, 78, 55,,,, -5, 5, 2, 1, 2, 2, 1, 2, 256, 80, 78, 55,,,, -5, 5, 2, 1, 2, 2, 1, 2, 384, 80, 78, 55,,,, -5, 5, 2, 1, 2, 2, 2, 1, 128, 80, 78, 55,,,, -5, 5, 2, 1, 2, 2, 2, 1, 256, 80, 78, 55,,,, -5, 5, 2, 1, 2, 2, 2, 1, 384, 80, 78, 55,,,, -5, 5, 2, 1, 2, 2, 2, 2, 128, 80, 78, 55,,,, -5, 5, 2, 1, 2, 2, 2, 2, 256, 80, 78, 55,,,, -5, 5, 2, 1, 2, 2, 2, 2, 384, 80, 78, 55,,,, -5, 5, 2, 1, 3, 3, 1, 1, 128, 80, 75, 55,,,, -5, 5, 2, 1, 3, 3, 1, 1, 256, 80, 75, 55,,,, -5, 5, 2, 1, 3, 3, 1, 1, 384, 80, 75, 55,,,, -5, 5, 2, 1, 3, 3, 1, 2, 128, 80, 75, 55,,,, -5, 5, 2, 1, 3, 3, 1, 2, 256, 80, 75, 55,,,, -5, 5, 2, 1, 3, 3, 1, 2, 384, 80, 75, 55,,,, -5, 5, 2, 1, 3, 3, 1, 3, 128, 80, 75, 55,,,, -5, 5, 2, 1, 3, 3, 1, 3, 256, 80, 75, 55,,,, -5, 5, 2, 1, 3, 3, 1, 3, 384, 80, 75, 55,,,, -5, 5, 2, 1, 3, 3, 2, 1, 128, 80, 75, 55,,,, -5, 5, 2, 1, 3, 3, 2, 1, 256, 80, 75, 55,,,, -5, 5, 2, 1, 3, 3, 2, 1, 384, 80, 75, 55,,,, -5, 5, 2, 1, 3, 3, 2, 2, 128, 80, 75, 55,,,, -5, 5, 2, 1, 3, 3, 2, 2, 256, 80, 75, 55,,,, -5, 5, 2, 1, 3, 3, 2, 2, 384, 80, 75, 55,,,, -5, 5, 2, 1, 3, 3, 2, 3, 128, 80, 75, 55,,,, -5, 5, 2, 1, 3, 3, 2, 3, 256, 80, 75, 55,,,, -5, 5, 2, 1, 3, 3, 2, 3, 384, 80, 75, 55,,,, -5, 5, 2, 1, 3, 3, 3, 1, 128, 80, 75, 55,,,, -5, 5, 2, 1, 3, 3, 3, 1, 256, 80, 75, 55,,,, -5, 5, 2, 1, 3, 3, 3, 1, 384, 80, 75, 55,,,, -5, 5, 2, 1, 3, 3, 3, 2, 128, 80, 75, 55,,,, -5, 5, 2, 1, 3, 3, 3, 2, 256, 80, 75, 55,,,, -5, 5, 2, 1, 3, 3, 3, 2, 384, 80, 75, 55,,,, -5, 5, 2, 1, 3, 3, 3, 3, 128, 80, 75, 55,,,, -5, 5, 2, 1, 3, 3, 3, 3, 256, 80, 75, 55,,,, -5, 5, 2, 1, 3, 3, 3, 3, 384, 80, 75, 55,,,, -5, 5, 2, 2, 1, 1, 1, 1, 128, 156, 156, 106,,,, -5, 5, 2, 2, 1, 1, 1, 1, 256, 156, 156, 106,,,, -5, 5, 2, 2, 1, 1, 1, 1, 384, 156, 156, 106,,,, -5, 5, 2, 2, 2, 2, 1, 1, 128, 156, 152, 106,,,, -5, 5, 2, 2, 2, 2, 1, 1, 256, 156, 152, 106,,,, -5, 5, 2, 2, 2, 2, 1, 1, 384, 156, 152, 106,,,, -5, 5, 2, 2, 2, 2, 1, 2, 128, 156, 152, 106,,,, -5, 5, 2, 2, 2, 2, 1, 2, 256, 156, 152, 106,,,, -5, 5, 2, 2, 2, 2, 1, 2, 384, 156, 152, 106,,,, -5, 5, 2, 2, 2, 2, 2, 1, 128, 156, 152, 106,,,, -5, 5, 2, 2, 2, 2, 2, 1, 256, 156, 152, 106,,,, -5, 5, 2, 2, 2, 2, 2, 1, 384, 156, 152, 106,,,, -5, 5, 2, 2, 2, 2, 2, 2, 128, 156, 152, 106,,,, -5, 5, 2, 2, 2, 2, 2, 2, 256, 156, 152, 106,,,, -5, 5, 2, 2, 2, 2, 2, 2, 384, 156, 152, 106,,,, -5, 5, 2, 2, 3, 3, 1, 1, 128, 156, 146, 106,,,, -5, 5, 2, 2, 3, 3, 1, 1, 256, 156, 146, 106,,,, -5, 5, 2, 2, 3, 3, 1, 1, 384, 156, 146, 106,,,, -5, 5, 2, 2, 3, 3, 1, 2, 128, 156, 146, 106,,,, -5, 5, 2, 2, 3, 3, 1, 2, 256, 156, 146, 106,,,, -5, 5, 2, 2, 3, 3, 1, 2, 384, 156, 146, 106,,,, -5, 5, 2, 2, 3, 3, 1, 3, 128, 156, 146, 106,,,, -5, 5, 2, 2, 3, 3, 1, 3, 256, 156, 146, 106,,,, -5, 5, 2, 2, 3, 3, 1, 3, 384, 156, 146, 106,,,, -5, 5, 2, 2, 3, 3, 2, 1, 128, 156, 146, 106,,,, -5, 5, 2, 2, 3, 3, 2, 1, 256, 156, 146, 106,,,, -5, 5, 2, 2, 3, 3, 2, 1, 384, 156, 146, 106,,,, -5, 5, 2, 2, 3, 3, 2, 2, 128, 156, 146, 106,,,, -5, 5, 2, 2, 3, 3, 2, 2, 256, 156, 146, 106,,,, -5, 5, 2, 2, 3, 3, 2, 2, 384, 156, 146, 106,,,, -5, 5, 2, 2, 3, 3, 2, 3, 128, 156, 146, 106,,,, -5, 5, 2, 2, 3, 3, 2, 3, 256, 156, 146, 106,,,, -5, 5, 2, 2, 3, 3, 2, 3, 384, 156, 146, 106,,,, -5, 5, 2, 2, 3, 3, 3, 1, 128, 156, 146, 106,,,, -5, 5, 2, 2, 3, 3, 3, 1, 256, 156, 146, 106,,,, -5, 5, 2, 2, 3, 3, 3, 1, 384, 156, 146, 106,,,, -5, 5, 2, 2, 3, 3, 3, 2, 128, 156, 146, 106,,,, -5, 5, 2, 2, 3, 3, 3, 2, 256, 156, 146, 106,,,, -5, 5, 2, 2, 3, 3, 3, 2, 384, 156, 146, 106,,,, -5, 5, 2, 2, 3, 3, 3, 3, 128, 156, 146, 106,,,, -5, 5, 2, 2, 3, 3, 3, 3, 256, 156, 146, 106,,,, -5, 5, 2, 2, 3, 3, 3, 3, 384, 156, 146, 106,,,, -5, 5, 2, 3, 1, 1, 1, 1, 128, 232, 232, 157,,,, -5, 5, 2, 3, 1, 1, 1, 1, 256, 232, 232, 157,,,, -5, 5, 2, 3, 1, 1, 1, 1, 384, 232, 232, 157,,,, -5, 5, 2, 3, 2, 2, 1, 1, 128, 232, 226, 157,,,, -5, 5, 2, 3, 2, 2, 1, 1, 256, 232, 226, 157,,,, -5, 5, 2, 3, 2, 2, 1, 1, 384, 232, 226, 157,,,, -5, 5, 2, 3, 2, 2, 1, 2, 128, 232, 226, 157,,,, -5, 5, 2, 3, 2, 2, 1, 2, 256, 232, 226, 157,,,, -5, 5, 2, 3, 2, 2, 1, 2, 384, 232, 226, 157,,,, -5, 5, 2, 3, 2, 2, 2, 1, 128, 232, 226, 157,,,, -5, 5, 2, 3, 2, 2, 2, 1, 256, 232, 226, 157,,,, -5, 5, 2, 3, 2, 2, 2, 1, 384, 232, 226, 157,,,, -5, 5, 2, 3, 2, 2, 2, 2, 128, 232, 226, 157,,,, -5, 5, 2, 3, 2, 2, 2, 2, 256, 232, 226, 157,,,, -5, 5, 2, 3, 2, 2, 2, 2, 384, 232, 226, 157,,,, -5, 5, 2, 3, 3, 3, 1, 1, 128, 232, 217, 157,,,, -5, 5, 2, 3, 3, 3, 1, 1, 256, 232, 217, 157,,,, -5, 5, 2, 3, 3, 3, 1, 1, 384, 232, 217, 157,,,, -5, 5, 2, 3, 3, 3, 1, 2, 128, 232, 217, 157,,,, -5, 5, 2, 3, 3, 3, 1, 2, 256, 232, 217, 157,,,, -5, 5, 2, 3, 3, 3, 1, 2, 384, 232, 217, 157,,,, -5, 5, 2, 3, 3, 3, 1, 3, 128, 232, 217, 157,,,, -5, 5, 2, 3, 3, 3, 1, 3, 256, 232, 217, 157,,,, -5, 5, 2, 3, 3, 3, 1, 3, 384, 232, 217, 157,,,, -5, 5, 2, 3, 3, 3, 2, 1, 128, 232, 217, 157,,,, -5, 5, 2, 3, 3, 3, 2, 1, 256, 232, 217, 157,,,, -5, 5, 2, 3, 3, 3, 2, 1, 384, 232, 217, 157,,,, -5, 5, 2, 3, 3, 3, 2, 2, 128, 232, 217, 157,,,, -5, 5, 2, 3, 3, 3, 2, 2, 256, 232, 217, 157,,,, -5, 5, 2, 3, 3, 3, 2, 2, 384, 232, 217, 157,,,, -5, 5, 2, 3, 3, 3, 2, 3, 128, 232, 217, 157,,,, -5, 5, 2, 3, 3, 3, 2, 3, 256, 232, 217, 157,,,, -5, 5, 2, 3, 3, 3, 2, 3, 384, 232, 217, 157,,,, -5, 5, 2, 3, 3, 3, 3, 1, 128, 232, 217, 157,,,, -5, 5, 2, 3, 3, 3, 3, 1, 256, 232, 217, 157,,,, -5, 5, 2, 3, 3, 3, 3, 1, 384, 232, 217, 157,,,, -5, 5, 2, 3, 3, 3, 3, 2, 128, 232, 217, 157,,,, -5, 5, 2, 3, 3, 3, 3, 2, 256, 232, 217, 157,,,, -5, 5, 2, 3, 3, 3, 3, 2, 384, 232, 217, 157,,,, -5, 5, 2, 3, 3, 3, 3, 3, 128, 232, 217, 157,,,, -5, 5, 2, 3, 3, 3, 3, 3, 256, 232, 217, 157,,,, -5, 5, 2, 3, 3, 3, 3, 3, 384, 232, 217, 157,,,, -5, 5, 2, 4, 1, 1, 1, 1, 128, 240, 240, 208,,,, -5, 5, 2, 4, 1, 1, 1, 1, 256, 240, 240, 208,,,, -5, 5, 2, 4, 1, 1, 1, 1, 384, 240, 240, 208,,,, -5, 5, 2, 4, 2, 2, 1, 1, 128, 240, 240, 208,,,, -5, 5, 2, 4, 2, 2, 1, 1, 256, 240, 240, 208,,,, -5, 5, 2, 4, 2, 2, 1, 1, 384, 240, 240, 208,,,, -5, 5, 2, 4, 2, 2, 1, 2, 128, 240, 240, 208,,,, -5, 5, 2, 4, 2, 2, 1, 2, 256, 240, 240, 208,,,, -5, 5, 2, 4, 2, 2, 1, 2, 384, 240, 240, 208,,,, -5, 5, 2, 4, 2, 2, 2, 1, 128, 240, 240, 208,,,, -5, 5, 2, 4, 2, 2, 2, 1, 256, 240, 240, 208,,,, -5, 5, 2, 4, 2, 2, 2, 1, 384, 240, 240, 208,,,, -5, 5, 2, 4, 2, 2, 2, 2, 128, 240, 240, 208,,,, -5, 5, 2, 4, 2, 2, 2, 2, 256, 240, 240, 208,,,, -5, 5, 2, 4, 2, 2, 2, 2, 384, 240, 240, 208,,,, -5, 5, 2, 4, 3, 3, 1, 1, 128, 240, 240, 208,,,, -5, 5, 2, 4, 3, 3, 1, 1, 256, 240, 240, 208,,,, -5, 5, 2, 4, 3, 3, 1, 1, 384, 240, 240, 208,,,, -5, 5, 2, 4, 3, 3, 1, 2, 128, 240, 240, 208,,,, -5, 5, 2, 4, 3, 3, 1, 2, 256, 240, 240, 208,,,, -5, 5, 2, 4, 3, 3, 1, 2, 384, 240, 240, 208,,,, -5, 5, 2, 4, 3, 3, 1, 3, 128, 240, 240, 208,,,, -5, 5, 2, 4, 3, 3, 1, 3, 256, 240, 240, 208,,,, -5, 5, 2, 4, 3, 3, 1, 3, 384, 240, 240, 208,,,, -5, 5, 2, 4, 3, 3, 2, 1, 128, 240, 240, 208,,,, -5, 5, 2, 4, 3, 3, 2, 1, 256, 240, 240, 208,,,, -5, 5, 2, 4, 3, 3, 2, 1, 384, 240, 240, 208,,,, -5, 5, 2, 4, 3, 3, 2, 2, 128, 240, 240, 208,,,, -5, 5, 2, 4, 3, 3, 2, 2, 256, 240, 240, 208,,,, -5, 5, 2, 4, 3, 3, 2, 2, 384, 240, 240, 208,,,, -5, 5, 2, 4, 3, 3, 2, 3, 128, 240, 240, 208,,,, -5, 5, 2, 4, 3, 3, 2, 3, 256, 240, 240, 208,,,, -5, 5, 2, 4, 3, 3, 2, 3, 384, 240, 240, 208,,,, -5, 5, 2, 4, 3, 3, 3, 1, 128, 240, 240, 208,,,, -5, 5, 2, 4, 3, 3, 3, 1, 256, 240, 240, 208,,,, -5, 5, 2, 4, 3, 3, 3, 1, 384, 240, 240, 208,,,, -5, 5, 2, 4, 3, 3, 3, 2, 128, 240, 240, 208,,,, -5, 5, 2, 4, 3, 3, 3, 2, 256, 240, 240, 208,,,, -5, 5, 2, 4, 3, 3, 3, 2, 384, 240, 240, 208,,,, -5, 5, 2, 4, 3, 3, 3, 3, 128, 240, 240, 208,,,, -5, 5, 2, 4, 3, 3, 3, 3, 256, 240, 240, 208,,,, -5, 5, 2, 4, 3, 3, 3, 3, 384, 240, 240, 208,,,, -5, 5, 2, 5, 1, 1, 1, 1, 128, 240, 240, 240,,,, -5, 5, 2, 5, 1, 1, 1, 1, 256, 240, 240, 240,,,, -5, 5, 2, 5, 1, 1, 1, 1, 384, 240, 240, 240,,,, -5, 5, 2, 5, 2, 2, 1, 1, 128, 240, 240, 240,,,, -5, 5, 2, 5, 2, 2, 1, 1, 256, 240, 240, 240,,,, -5, 5, 2, 5, 2, 2, 1, 1, 384, 240, 240, 240,,,, -5, 5, 2, 5, 2, 2, 1, 2, 128, 240, 240, 240,,,, -5, 5, 2, 5, 2, 2, 1, 2, 256, 240, 240, 240,,,, -5, 5, 2, 5, 2, 2, 1, 2, 384, 240, 240, 240,,,, -5, 5, 2, 5, 2, 2, 2, 1, 128, 240, 240, 240,,,, -5, 5, 2, 5, 2, 2, 2, 1, 256, 240, 240, 240,,,, -5, 5, 2, 5, 2, 2, 2, 1, 384, 240, 240, 240,,,, -5, 5, 2, 5, 2, 2, 2, 2, 128, 240, 240, 240,,,, -5, 5, 2, 5, 2, 2, 2, 2, 256, 240, 240, 240,,,, -5, 5, 2, 5, 2, 2, 2, 2, 384, 240, 240, 240,,,, -5, 5, 2, 5, 3, 3, 1, 1, 128, 240, 240, 240,,,, -5, 5, 2, 5, 3, 3, 1, 1, 256, 240, 240, 240,,,, -5, 5, 2, 5, 3, 3, 1, 1, 384, 240, 240, 240,,,, -5, 5, 2, 5, 3, 3, 1, 2, 128, 240, 240, 240,,,, -5, 5, 2, 5, 3, 3, 1, 2, 256, 240, 240, 240,,,, -5, 5, 2, 5, 3, 3, 1, 2, 384, 240, 240, 240,,,, -5, 5, 2, 5, 3, 3, 1, 3, 128, 240, 240, 240,,,, -5, 5, 2, 5, 3, 3, 1, 3, 256, 240, 240, 240,,,, -5, 5, 2, 5, 3, 3, 1, 3, 384, 240, 240, 240,,,, -5, 5, 2, 5, 3, 3, 2, 1, 128, 240, 240, 240,,,, -5, 5, 2, 5, 3, 3, 2, 1, 256, 240, 240, 240,,,, -5, 5, 2, 5, 3, 3, 2, 1, 384, 240, 240, 240,,,, -5, 5, 2, 5, 3, 3, 2, 2, 128, 240, 240, 240,,,, -5, 5, 2, 5, 3, 3, 2, 2, 256, 240, 240, 240,,,, -5, 5, 2, 5, 3, 3, 2, 2, 384, 240, 240, 240,,,, -5, 5, 2, 5, 3, 3, 2, 3, 128, 240, 240, 240,,,, -5, 5, 2, 5, 3, 3, 2, 3, 256, 240, 240, 240,,,, -5, 5, 2, 5, 3, 3, 2, 3, 384, 240, 240, 240,,,, -5, 5, 2, 5, 3, 3, 3, 1, 128, 240, 240, 240,,,, -5, 5, 2, 5, 3, 3, 3, 1, 256, 240, 240, 240,,,, -5, 5, 2, 5, 3, 3, 3, 1, 384, 240, 240, 240,,,, -5, 5, 2, 5, 3, 3, 3, 2, 128, 240, 240, 240,,,, -5, 5, 2, 5, 3, 3, 3, 2, 256, 240, 240, 240,,,, -5, 5, 2, 5, 3, 3, 3, 2, 384, 240, 240, 240,,,, -5, 5, 2, 5, 3, 3, 3, 3, 128, 240, 240, 240,,,, -5, 5, 2, 5, 3, 3, 3, 3, 256, 240, 240, 240,,,, -5, 5, 2, 5, 3, 3, 3, 3, 384, 240, 240, 240,,,, -5, 5, 3, 1, 1, 1, 1, 1, 128, 80, 80, 55,,,, -5, 5, 3, 1, 1, 1, 1, 1, 256, 80, 80, 55,,,, -5, 5, 3, 1, 1, 1, 1, 1, 384, 80, 80, 55,,,, -5, 5, 3, 1, 2, 2, 1, 1, 128, 80, 78, 55,,,, -5, 5, 3, 1, 2, 2, 1, 1, 256, 80, 78, 55,,,, -5, 5, 3, 1, 2, 2, 1, 1, 384, 80, 78, 55,,,, -5, 5, 3, 1, 2, 2, 1, 2, 128, 80, 78, 55,,,, -5, 5, 3, 1, 2, 2, 1, 2, 256, 80, 78, 55,,,, -5, 5, 3, 1, 2, 2, 1, 2, 384, 80, 78, 55,,,, -5, 5, 3, 1, 2, 2, 2, 1, 128, 80, 78, 55,,,, -5, 5, 3, 1, 2, 2, 2, 1, 256, 80, 78, 55,,,, -5, 5, 3, 1, 2, 2, 2, 1, 384, 80, 78, 55,,,, -5, 5, 3, 1, 2, 2, 2, 2, 128, 80, 78, 55,,,, -5, 5, 3, 1, 2, 2, 2, 2, 256, 80, 78, 55,,,, -5, 5, 3, 1, 2, 2, 2, 2, 384, 80, 78, 55,,,, -5, 5, 3, 1, 3, 3, 1, 1, 128, 80, 75, 55,,,, -5, 5, 3, 1, 3, 3, 1, 1, 256, 80, 75, 55,,,, -5, 5, 3, 1, 3, 3, 1, 1, 384, 80, 75, 55,,,, -5, 5, 3, 1, 3, 3, 1, 2, 128, 80, 75, 55,,,, -5, 5, 3, 1, 3, 3, 1, 2, 256, 80, 75, 55,,,, -5, 5, 3, 1, 3, 3, 1, 2, 384, 80, 75, 55,,,, -5, 5, 3, 1, 3, 3, 1, 3, 128, 80, 75, 55,,,, -5, 5, 3, 1, 3, 3, 1, 3, 256, 80, 75, 55,,,, -5, 5, 3, 1, 3, 3, 1, 3, 384, 80, 75, 55,,,, -5, 5, 3, 1, 3, 3, 2, 1, 128, 80, 75, 55,,,, -5, 5, 3, 1, 3, 3, 2, 1, 256, 80, 75, 55,,,, -5, 5, 3, 1, 3, 3, 2, 1, 384, 80, 75, 55,,,, -5, 5, 3, 1, 3, 3, 2, 2, 128, 80, 75, 55,,,, -5, 5, 3, 1, 3, 3, 2, 2, 256, 80, 75, 55,,,, -5, 5, 3, 1, 3, 3, 2, 2, 384, 80, 75, 55,,,, -5, 5, 3, 1, 3, 3, 2, 3, 128, 80, 75, 55,,,, -5, 5, 3, 1, 3, 3, 2, 3, 256, 80, 75, 55,,,, -5, 5, 3, 1, 3, 3, 2, 3, 384, 80, 75, 55,,,, -5, 5, 3, 1, 3, 3, 3, 1, 128, 80, 75, 55,,,, -5, 5, 3, 1, 3, 3, 3, 1, 256, 80, 75, 55,,,, -5, 5, 3, 1, 3, 3, 3, 1, 384, 80, 75, 55,,,, -5, 5, 3, 1, 3, 3, 3, 2, 128, 80, 75, 55,,,, -5, 5, 3, 1, 3, 3, 3, 2, 256, 80, 75, 55,,,, -5, 5, 3, 1, 3, 3, 3, 2, 384, 80, 75, 55,,,, -5, 5, 3, 1, 3, 3, 3, 3, 128, 80, 75, 55,,,, -5, 5, 3, 1, 3, 3, 3, 3, 256, 80, 75, 55,,,, -5, 5, 3, 1, 3, 3, 3, 3, 384, 80, 75, 55,,,, -5, 5, 3, 2, 1, 1, 1, 1, 128, 156, 156, 106,,,, -5, 5, 3, 2, 1, 1, 1, 1, 256, 156, 156, 106,,,, -5, 5, 3, 2, 1, 1, 1, 1, 384, 156, 156, 106,,,, -5, 5, 3, 2, 2, 2, 1, 1, 128, 156, 152, 106,,,, -5, 5, 3, 2, 2, 2, 1, 1, 256, 156, 152, 106,,,, -5, 5, 3, 2, 2, 2, 1, 1, 384, 156, 152, 106,,,, -5, 5, 3, 2, 2, 2, 1, 2, 128, 156, 152, 106,,,, -5, 5, 3, 2, 2, 2, 1, 2, 256, 156, 152, 106,,,, -5, 5, 3, 2, 2, 2, 1, 2, 384, 156, 152, 106,,,, -5, 5, 3, 2, 2, 2, 2, 1, 128, 156, 152, 106,,,, -5, 5, 3, 2, 2, 2, 2, 1, 256, 156, 152, 106,,,, -5, 5, 3, 2, 2, 2, 2, 1, 384, 156, 152, 106,,,, -5, 5, 3, 2, 2, 2, 2, 2, 128, 156, 152, 106,,,, -5, 5, 3, 2, 2, 2, 2, 2, 256, 156, 152, 106,,,, -5, 5, 3, 2, 2, 2, 2, 2, 384, 156, 152, 106,,,, -5, 5, 3, 2, 3, 3, 1, 1, 128, 156, 146, 106,,,, -5, 5, 3, 2, 3, 3, 1, 1, 256, 156, 146, 106,,,, -5, 5, 3, 2, 3, 3, 1, 1, 384, 156, 146, 106,,,, -5, 5, 3, 2, 3, 3, 1, 2, 128, 156, 146, 106,,,, -5, 5, 3, 2, 3, 3, 1, 2, 256, 156, 146, 106,,,, -5, 5, 3, 2, 3, 3, 1, 2, 384, 156, 146, 106,,,, -5, 5, 3, 2, 3, 3, 1, 3, 128, 156, 146, 106,,,, -5, 5, 3, 2, 3, 3, 1, 3, 256, 156, 146, 106,,,, -5, 5, 3, 2, 3, 3, 1, 3, 384, 156, 146, 106,,,, -5, 5, 3, 2, 3, 3, 2, 1, 128, 156, 146, 106,,,, -5, 5, 3, 2, 3, 3, 2, 1, 256, 156, 146, 106,,,, -5, 5, 3, 2, 3, 3, 2, 1, 384, 156, 146, 106,,,, -5, 5, 3, 2, 3, 3, 2, 2, 128, 156, 146, 106,,,, -5, 5, 3, 2, 3, 3, 2, 2, 256, 156, 146, 106,,,, -5, 5, 3, 2, 3, 3, 2, 2, 384, 156, 146, 106,,,, -5, 5, 3, 2, 3, 3, 2, 3, 128, 156, 146, 106,,,, -5, 5, 3, 2, 3, 3, 2, 3, 256, 156, 146, 106,,,, -5, 5, 3, 2, 3, 3, 2, 3, 384, 156, 146, 106,,,, -5, 5, 3, 2, 3, 3, 3, 1, 128, 156, 146, 106,,,, -5, 5, 3, 2, 3, 3, 3, 1, 256, 156, 146, 106,,,, -5, 5, 3, 2, 3, 3, 3, 1, 384, 156, 146, 106,,,, -5, 5, 3, 2, 3, 3, 3, 2, 128, 156, 146, 106,,,, -5, 5, 3, 2, 3, 3, 3, 2, 256, 156, 146, 106,,,, -5, 5, 3, 2, 3, 3, 3, 2, 384, 156, 146, 106,,,, -5, 5, 3, 2, 3, 3, 3, 3, 128, 156, 146, 106,,,, -5, 5, 3, 2, 3, 3, 3, 3, 256, 156, 146, 106,,,, -5, 5, 3, 2, 3, 3, 3, 3, 384, 156, 146, 106,,,, -5, 5, 3, 3, 1, 1, 1, 1, 128, 232, 232, 157,,,, -5, 5, 3, 3, 1, 1, 1, 1, 256, 232, 232, 157,,,, -5, 5, 3, 3, 1, 1, 1, 1, 384, 232, 232, 157,,,, -5, 5, 3, 3, 2, 2, 1, 1, 128, 232, 226, 157,,,, -5, 5, 3, 3, 2, 2, 1, 1, 256, 232, 226, 157,,,, -5, 5, 3, 3, 2, 2, 1, 1, 384, 232, 226, 157,,,, -5, 5, 3, 3, 2, 2, 1, 2, 128, 232, 226, 157,,,, -5, 5, 3, 3, 2, 2, 1, 2, 256, 232, 226, 157,,,, -5, 5, 3, 3, 2, 2, 1, 2, 384, 232, 226, 157,,,, -5, 5, 3, 3, 2, 2, 2, 1, 128, 232, 226, 157,,,, -5, 5, 3, 3, 2, 2, 2, 1, 256, 232, 226, 157,,,, -5, 5, 3, 3, 2, 2, 2, 1, 384, 232, 226, 157,,,, -5, 5, 3, 3, 2, 2, 2, 2, 128, 232, 226, 157,,,, -5, 5, 3, 3, 2, 2, 2, 2, 256, 232, 226, 157,,,, -5, 5, 3, 3, 2, 2, 2, 2, 384, 232, 226, 157,,,, -5, 5, 3, 3, 3, 3, 1, 1, 128, 232, 217, 157,,,, -5, 5, 3, 3, 3, 3, 1, 1, 256, 232, 217, 157,,,, -5, 5, 3, 3, 3, 3, 1, 1, 384, 232, 217, 157,,,, -5, 5, 3, 3, 3, 3, 1, 2, 128, 232, 217, 157,,,, -5, 5, 3, 3, 3, 3, 1, 2, 256, 232, 217, 157,,,, -5, 5, 3, 3, 3, 3, 1, 2, 384, 232, 217, 157,,,, -5, 5, 3, 3, 3, 3, 1, 3, 128, 232, 217, 157,,,, -5, 5, 3, 3, 3, 3, 1, 3, 256, 232, 217, 157,,,, -5, 5, 3, 3, 3, 3, 1, 3, 384, 232, 217, 157,,,, -5, 5, 3, 3, 3, 3, 2, 1, 128, 232, 217, 157,,,, -5, 5, 3, 3, 3, 3, 2, 1, 256, 232, 217, 157,,,, -5, 5, 3, 3, 3, 3, 2, 1, 384, 232, 217, 157,,,, -5, 5, 3, 3, 3, 3, 2, 2, 128, 232, 217, 157,,,, -5, 5, 3, 3, 3, 3, 2, 2, 256, 232, 217, 157,,,, -5, 5, 3, 3, 3, 3, 2, 2, 384, 232, 217, 157,,,, -5, 5, 3, 3, 3, 3, 2, 3, 128, 232, 217, 157,,,, -5, 5, 3, 3, 3, 3, 2, 3, 256, 232, 217, 157,,,, -5, 5, 3, 3, 3, 3, 2, 3, 384, 232, 217, 157,,,, -5, 5, 3, 3, 3, 3, 3, 1, 128, 232, 217, 157,,,, -5, 5, 3, 3, 3, 3, 3, 1, 256, 232, 217, 157,,,, -5, 5, 3, 3, 3, 3, 3, 1, 384, 232, 217, 157,,,, -5, 5, 3, 3, 3, 3, 3, 2, 128, 232, 217, 157,,,, -5, 5, 3, 3, 3, 3, 3, 2, 256, 232, 217, 157,,,, -5, 5, 3, 3, 3, 3, 3, 2, 384, 232, 217, 157,,,, -5, 5, 3, 3, 3, 3, 3, 3, 128, 232, 217, 157,,,, -5, 5, 3, 3, 3, 3, 3, 3, 256, 232, 217, 157,,,, -5, 5, 3, 3, 3, 3, 3, 3, 384, 232, 217, 157,,,, -5, 5, 3, 4, 1, 1, 1, 1, 128, 240, 240, 208,,,, -5, 5, 3, 4, 1, 1, 1, 1, 256, 240, 240, 208,,,, -5, 5, 3, 4, 1, 1, 1, 1, 384, 240, 240, 208,,,, -5, 5, 3, 4, 2, 2, 1, 1, 128, 240, 240, 208,,,, -5, 5, 3, 4, 2, 2, 1, 1, 256, 240, 240, 208,,,, -5, 5, 3, 4, 2, 2, 1, 1, 384, 240, 240, 208,,,, -5, 5, 3, 4, 2, 2, 1, 2, 128, 240, 240, 208,,,, -5, 5, 3, 4, 2, 2, 1, 2, 256, 240, 240, 208,,,, -5, 5, 3, 4, 2, 2, 1, 2, 384, 240, 240, 208,,,, -5, 5, 3, 4, 2, 2, 2, 1, 128, 240, 240, 208,,,, -5, 5, 3, 4, 2, 2, 2, 1, 256, 240, 240, 208,,,, -5, 5, 3, 4, 2, 2, 2, 1, 384, 240, 240, 208,,,, -5, 5, 3, 4, 2, 2, 2, 2, 128, 240, 240, 208,,,, -5, 5, 3, 4, 2, 2, 2, 2, 256, 240, 240, 208,,,, -5, 5, 3, 4, 2, 2, 2, 2, 384, 240, 240, 208,,,, -5, 5, 3, 4, 3, 3, 1, 1, 128, 240, 240, 208,,,, -5, 5, 3, 4, 3, 3, 1, 1, 256, 240, 240, 208,,,, -5, 5, 3, 4, 3, 3, 1, 1, 384, 240, 240, 208,,,, -5, 5, 3, 4, 3, 3, 1, 2, 128, 240, 240, 208,,,, -5, 5, 3, 4, 3, 3, 1, 2, 256, 240, 240, 208,,,, -5, 5, 3, 4, 3, 3, 1, 2, 384, 240, 240, 208,,,, -5, 5, 3, 4, 3, 3, 1, 3, 128, 240, 240, 208,,,, -5, 5, 3, 4, 3, 3, 1, 3, 256, 240, 240, 208,,,, -5, 5, 3, 4, 3, 3, 1, 3, 384, 240, 240, 208,,,, -5, 5, 3, 4, 3, 3, 2, 1, 128, 240, 240, 208,,,, -5, 5, 3, 4, 3, 3, 2, 1, 256, 240, 240, 208,,,, -5, 5, 3, 4, 3, 3, 2, 1, 384, 240, 240, 208,,,, -5, 5, 3, 4, 3, 3, 2, 2, 128, 240, 240, 208,,,, -5, 5, 3, 4, 3, 3, 2, 2, 256, 240, 240, 208,,,, -5, 5, 3, 4, 3, 3, 2, 2, 384, 240, 240, 208,,,, -5, 5, 3, 4, 3, 3, 2, 3, 128, 240, 240, 208,,,, -5, 5, 3, 4, 3, 3, 2, 3, 256, 240, 240, 208,,,, -5, 5, 3, 4, 3, 3, 2, 3, 384, 240, 240, 208,,,, -5, 5, 3, 4, 3, 3, 3, 1, 128, 240, 240, 208,,,, -5, 5, 3, 4, 3, 3, 3, 1, 256, 240, 240, 208,,,, -5, 5, 3, 4, 3, 3, 3, 1, 384, 240, 240, 208,,,, -5, 5, 3, 4, 3, 3, 3, 2, 128, 240, 240, 208,,,, -5, 5, 3, 4, 3, 3, 3, 2, 256, 240, 240, 208,,,, -5, 5, 3, 4, 3, 3, 3, 2, 384, 240, 240, 208,,,, -5, 5, 3, 4, 3, 3, 3, 3, 128, 240, 240, 208,,,, -5, 5, 3, 4, 3, 3, 3, 3, 256, 240, 240, 208,,,, -5, 5, 3, 4, 3, 3, 3, 3, 384, 240, 240, 208,,,, -5, 5, 3, 5, 1, 1, 1, 1, 128, 240, 240, 240,,,, -5, 5, 3, 5, 1, 1, 1, 1, 256, 240, 240, 240,,,, -5, 5, 3, 5, 1, 1, 1, 1, 384, 240, 240, 240,,,, -5, 5, 3, 5, 2, 2, 1, 1, 128, 240, 240, 240,,,, -5, 5, 3, 5, 2, 2, 1, 1, 256, 240, 240, 240,,,, -5, 5, 3, 5, 2, 2, 1, 1, 384, 240, 240, 240,,,, -5, 5, 3, 5, 2, 2, 1, 2, 128, 240, 240, 240,,,, -5, 5, 3, 5, 2, 2, 1, 2, 256, 240, 240, 240,,,, -5, 5, 3, 5, 2, 2, 1, 2, 384, 240, 240, 240,,,, -5, 5, 3, 5, 2, 2, 2, 1, 128, 240, 240, 240,,,, -5, 5, 3, 5, 2, 2, 2, 1, 256, 240, 240, 240,,,, -5, 5, 3, 5, 2, 2, 2, 1, 384, 240, 240, 240,,,, -5, 5, 3, 5, 2, 2, 2, 2, 128, 240, 240, 240,,,, -5, 5, 3, 5, 2, 2, 2, 2, 256, 240, 240, 240,,,, -5, 5, 3, 5, 2, 2, 2, 2, 384, 240, 240, 240,,,, -5, 5, 3, 5, 3, 3, 1, 1, 128, 240, 240, 240,,,, -5, 5, 3, 5, 3, 3, 1, 1, 256, 240, 240, 240,,,, -5, 5, 3, 5, 3, 3, 1, 1, 384, 240, 240, 240,,,, -5, 5, 3, 5, 3, 3, 1, 2, 128, 240, 240, 240,,,, -5, 5, 3, 5, 3, 3, 1, 2, 256, 240, 240, 240,,,, -5, 5, 3, 5, 3, 3, 1, 2, 384, 240, 240, 240,,,, -5, 5, 3, 5, 3, 3, 1, 3, 128, 240, 240, 240,,,, -5, 5, 3, 5, 3, 3, 1, 3, 256, 240, 240, 240,,,, -5, 5, 3, 5, 3, 3, 1, 3, 384, 240, 240, 240,,,, -5, 5, 3, 5, 3, 3, 2, 1, 128, 240, 240, 240,,,, -5, 5, 3, 5, 3, 3, 2, 1, 256, 240, 240, 240,,,, -5, 5, 3, 5, 3, 3, 2, 1, 384, 240, 240, 240,,,, -5, 5, 3, 5, 3, 3, 2, 2, 128, 240, 240, 240,,,, -5, 5, 3, 5, 3, 3, 2, 2, 256, 240, 240, 240,,,, -5, 5, 3, 5, 3, 3, 2, 2, 384, 240, 240, 240,,,, -5, 5, 3, 5, 3, 3, 2, 3, 128, 240, 240, 240,,,, -5, 5, 3, 5, 3, 3, 2, 3, 256, 240, 240, 240,,,, -5, 5, 3, 5, 3, 3, 2, 3, 384, 240, 240, 240,,,, -5, 5, 3, 5, 3, 3, 3, 1, 128, 240, 240, 240,,,, -5, 5, 3, 5, 3, 3, 3, 1, 256, 240, 240, 240,,,, -5, 5, 3, 5, 3, 3, 3, 1, 384, 240, 240, 240,,,, -5, 5, 3, 5, 3, 3, 3, 2, 128, 240, 240, 240,,,, -5, 5, 3, 5, 3, 3, 3, 2, 256, 240, 240, 240,,,, -5, 5, 3, 5, 3, 3, 3, 2, 384, 240, 240, 240,,,, -5, 5, 3, 5, 3, 3, 3, 3, 128, 240, 240, 240,,,, -5, 5, 3, 5, 3, 3, 3, 3, 256, 240, 240, 240,,,, -5, 5, 3, 5, 3, 3, 3, 3, 384, 240, 240, 240,,,, -5, 5, 4, 1, 1, 1, 1, 1, 128, 80, 80, 55,,,, -5, 5, 4, 1, 1, 1, 1, 1, 256, 80, 80, 55,,,, -5, 5, 4, 1, 1, 1, 1, 1, 384, 80, 80, 55,,,, -5, 5, 4, 1, 2, 2, 1, 1, 128, 80, 78, 55,,,, -5, 5, 4, 1, 2, 2, 1, 1, 256, 80, 78, 55,,,, -5, 5, 4, 1, 2, 2, 1, 1, 384, 80, 78, 55,,,, -5, 5, 4, 1, 2, 2, 1, 2, 128, 80, 78, 55,,,, -5, 5, 4, 1, 2, 2, 1, 2, 256, 80, 78, 55,,,, -5, 5, 4, 1, 2, 2, 1, 2, 384, 80, 78, 55,,,, -5, 5, 4, 1, 2, 2, 2, 1, 128, 80, 78, 55,,,, -5, 5, 4, 1, 2, 2, 2, 1, 256, 80, 78, 55,,,, -5, 5, 4, 1, 2, 2, 2, 1, 384, 80, 78, 55,,,, -5, 5, 4, 1, 2, 2, 2, 2, 128, 80, 78, 55,,,, -5, 5, 4, 1, 2, 2, 2, 2, 256, 80, 78, 55,,,, -5, 5, 4, 1, 2, 2, 2, 2, 384, 80, 78, 55,,,, -5, 5, 4, 1, 3, 3, 1, 1, 128, 80, 75, 55,,,, -5, 5, 4, 1, 3, 3, 1, 1, 256, 80, 75, 55,,,, -5, 5, 4, 1, 3, 3, 1, 1, 384, 80, 75, 55,,,, -5, 5, 4, 1, 3, 3, 1, 2, 128, 80, 75, 55,,,, -5, 5, 4, 1, 3, 3, 1, 2, 256, 80, 75, 55,,,, -5, 5, 4, 1, 3, 3, 1, 2, 384, 80, 75, 55,,,, -5, 5, 4, 1, 3, 3, 1, 3, 128, 80, 75, 55,,,, -5, 5, 4, 1, 3, 3, 1, 3, 256, 80, 75, 55,,,, -5, 5, 4, 1, 3, 3, 1, 3, 384, 80, 75, 55,,,, -5, 5, 4, 1, 3, 3, 2, 1, 128, 80, 75, 55,,,, -5, 5, 4, 1, 3, 3, 2, 1, 256, 80, 75, 55,,,, -5, 5, 4, 1, 3, 3, 2, 1, 384, 80, 75, 55,,,, -5, 5, 4, 1, 3, 3, 2, 2, 128, 80, 75, 55,,,, -5, 5, 4, 1, 3, 3, 2, 2, 256, 80, 75, 55,,,, -5, 5, 4, 1, 3, 3, 2, 2, 384, 80, 75, 55,,,, -5, 5, 4, 1, 3, 3, 2, 3, 128, 80, 75, 55,,,, -5, 5, 4, 1, 3, 3, 2, 3, 256, 80, 75, 55,,,, -5, 5, 4, 1, 3, 3, 2, 3, 384, 80, 75, 55,,,, -5, 5, 4, 1, 3, 3, 3, 1, 128, 80, 75, 55,,,, -5, 5, 4, 1, 3, 3, 3, 1, 256, 80, 75, 55,,,, -5, 5, 4, 1, 3, 3, 3, 1, 384, 80, 75, 55,,,, -5, 5, 4, 1, 3, 3, 3, 2, 128, 80, 75, 55,,,, -5, 5, 4, 1, 3, 3, 3, 2, 256, 80, 75, 55,,,, -5, 5, 4, 1, 3, 3, 3, 2, 384, 80, 75, 55,,,, -5, 5, 4, 1, 3, 3, 3, 3, 128, 80, 75, 55,,,, -5, 5, 4, 1, 3, 3, 3, 3, 256, 80, 75, 55,,,, -5, 5, 4, 1, 3, 3, 3, 3, 384, 80, 75, 55,,,, -5, 5, 4, 2, 1, 1, 1, 1, 128, 156, 156, 106,,,, -5, 5, 4, 2, 1, 1, 1, 1, 256, 156, 156, 106,,,, -5, 5, 4, 2, 1, 1, 1, 1, 384, 156, 156, 106,,,, -5, 5, 4, 2, 2, 2, 1, 1, 128, 156, 152, 106,,,, -5, 5, 4, 2, 2, 2, 1, 1, 256, 156, 152, 106,,,, -5, 5, 4, 2, 2, 2, 1, 1, 384, 156, 152, 106,,,, -5, 5, 4, 2, 2, 2, 1, 2, 128, 156, 152, 106,,,, -5, 5, 4, 2, 2, 2, 1, 2, 256, 156, 152, 106,,,, -5, 5, 4, 2, 2, 2, 1, 2, 384, 156, 152, 106,,,, -5, 5, 4, 2, 2, 2, 2, 1, 128, 156, 152, 106,,,, -5, 5, 4, 2, 2, 2, 2, 1, 256, 156, 152, 106,,,, -5, 5, 4, 2, 2, 2, 2, 1, 384, 156, 152, 106,,,, -5, 5, 4, 2, 2, 2, 2, 2, 128, 156, 152, 106,,,, -5, 5, 4, 2, 2, 2, 2, 2, 256, 156, 152, 106,,,, -5, 5, 4, 2, 2, 2, 2, 2, 384, 156, 152, 106,,,, -5, 5, 4, 2, 3, 3, 1, 1, 128, 156, 146, 106,,,, -5, 5, 4, 2, 3, 3, 1, 1, 256, 156, 146, 106,,,, -5, 5, 4, 2, 3, 3, 1, 1, 384, 156, 146, 106,,,, -5, 5, 4, 2, 3, 3, 1, 2, 128, 156, 146, 106,,,, -5, 5, 4, 2, 3, 3, 1, 2, 256, 156, 146, 106,,,, -5, 5, 4, 2, 3, 3, 1, 2, 384, 156, 146, 106,,,, -5, 5, 4, 2, 3, 3, 1, 3, 128, 156, 146, 106,,,, -5, 5, 4, 2, 3, 3, 1, 3, 256, 156, 146, 106,,,, -5, 5, 4, 2, 3, 3, 1, 3, 384, 156, 146, 106,,,, -5, 5, 4, 2, 3, 3, 2, 1, 128, 156, 146, 106,,,, -5, 5, 4, 2, 3, 3, 2, 1, 256, 156, 146, 106,,,, -5, 5, 4, 2, 3, 3, 2, 1, 384, 156, 146, 106,,,, -5, 5, 4, 2, 3, 3, 2, 2, 128, 156, 146, 106,,,, -5, 5, 4, 2, 3, 3, 2, 2, 256, 156, 146, 106,,,, -5, 5, 4, 2, 3, 3, 2, 2, 384, 156, 146, 106,,,, -5, 5, 4, 2, 3, 3, 2, 3, 128, 156, 146, 106,,,, -5, 5, 4, 2, 3, 3, 2, 3, 256, 156, 146, 106,,,, -5, 5, 4, 2, 3, 3, 2, 3, 384, 156, 146, 106,,,, -5, 5, 4, 2, 3, 3, 3, 1, 128, 156, 146, 106,,,, -5, 5, 4, 2, 3, 3, 3, 1, 256, 156, 146, 106,,,, -5, 5, 4, 2, 3, 3, 3, 1, 384, 156, 146, 106,,,, -5, 5, 4, 2, 3, 3, 3, 2, 128, 156, 146, 106,,,, -5, 5, 4, 2, 3, 3, 3, 2, 256, 156, 146, 106,,,, -5, 5, 4, 2, 3, 3, 3, 2, 384, 156, 146, 106,,,, -5, 5, 4, 2, 3, 3, 3, 3, 128, 156, 146, 106,,,, -5, 5, 4, 2, 3, 3, 3, 3, 256, 156, 146, 106,,,, -5, 5, 4, 2, 3, 3, 3, 3, 384, 156, 146, 106,,,, -5, 5, 4, 3, 1, 1, 1, 1, 128, 232, 232, 157,,,, -5, 5, 4, 3, 1, 1, 1, 1, 256, 232, 232, 157,,,, -5, 5, 4, 3, 1, 1, 1, 1, 384, 232, 232, 157,,,, -5, 5, 4, 3, 2, 2, 1, 1, 128, 232, 226, 157,,,, -5, 5, 4, 3, 2, 2, 1, 1, 256, 232, 226, 157,,,, -5, 5, 4, 3, 2, 2, 1, 1, 384, 232, 226, 157,,,, -5, 5, 4, 3, 2, 2, 1, 2, 128, 232, 226, 157,,,, -5, 5, 4, 3, 2, 2, 1, 2, 256, 232, 226, 157,,,, -5, 5, 4, 3, 2, 2, 1, 2, 384, 232, 226, 157,,,, -5, 5, 4, 3, 2, 2, 2, 1, 128, 232, 226, 157,,,, -5, 5, 4, 3, 2, 2, 2, 1, 256, 232, 226, 157,,,, -5, 5, 4, 3, 2, 2, 2, 1, 384, 232, 226, 157,,,, -5, 5, 4, 3, 2, 2, 2, 2, 128, 232, 226, 157,,,, -5, 5, 4, 3, 2, 2, 2, 2, 256, 232, 226, 157,,,, -5, 5, 4, 3, 2, 2, 2, 2, 384, 232, 226, 157,,,, -5, 5, 4, 3, 3, 3, 1, 1, 128, 232, 217, 157,,,, -5, 5, 4, 3, 3, 3, 1, 1, 256, 232, 217, 157,,,, -5, 5, 4, 3, 3, 3, 1, 1, 384, 232, 217, 157,,,, -5, 5, 4, 3, 3, 3, 1, 2, 128, 232, 217, 157,,,, -5, 5, 4, 3, 3, 3, 1, 2, 256, 232, 217, 157,,,, -5, 5, 4, 3, 3, 3, 1, 2, 384, 232, 217, 157,,,, -5, 5, 4, 3, 3, 3, 1, 3, 128, 232, 217, 157,,,, -5, 5, 4, 3, 3, 3, 1, 3, 256, 232, 217, 157,,,, -5, 5, 4, 3, 3, 3, 1, 3, 384, 232, 217, 157,,,, -5, 5, 4, 3, 3, 3, 2, 1, 128, 232, 217, 157,,,, -5, 5, 4, 3, 3, 3, 2, 1, 256, 232, 217, 157,,,, -5, 5, 4, 3, 3, 3, 2, 1, 384, 232, 217, 157,,,, -5, 5, 4, 3, 3, 3, 2, 2, 128, 232, 217, 157,,,, -5, 5, 4, 3, 3, 3, 2, 2, 256, 232, 217, 157,,,, -5, 5, 4, 3, 3, 3, 2, 2, 384, 232, 217, 157,,,, -5, 5, 4, 3, 3, 3, 2, 3, 128, 232, 217, 157,,,, -5, 5, 4, 3, 3, 3, 2, 3, 256, 232, 217, 157,,,, -5, 5, 4, 3, 3, 3, 2, 3, 384, 232, 217, 157,,,, -5, 5, 4, 3, 3, 3, 3, 1, 128, 232, 217, 157,,,, -5, 5, 4, 3, 3, 3, 3, 1, 256, 232, 217, 157,,,, -5, 5, 4, 3, 3, 3, 3, 1, 384, 232, 217, 157,,,, -5, 5, 4, 3, 3, 3, 3, 2, 128, 232, 217, 157,,,, -5, 5, 4, 3, 3, 3, 3, 2, 256, 232, 217, 157,,,, -5, 5, 4, 3, 3, 3, 3, 2, 384, 232, 217, 157,,,, -5, 5, 4, 3, 3, 3, 3, 3, 128, 232, 217, 157,,,, -5, 5, 4, 3, 3, 3, 3, 3, 256, 232, 217, 157,,,, -5, 5, 4, 3, 3, 3, 3, 3, 384, 232, 217, 157,,,, -5, 5, 4, 4, 1, 1, 1, 1, 128, 240, 240, 208,,,, -5, 5, 4, 4, 1, 1, 1, 1, 256, 240, 240, 208,,,, -5, 5, 4, 4, 1, 1, 1, 1, 384, 240, 240, 208,,,, -5, 5, 4, 4, 2, 2, 1, 1, 128, 240, 240, 208,,,, -5, 5, 4, 4, 2, 2, 1, 1, 256, 240, 240, 208,,,, -5, 5, 4, 4, 2, 2, 1, 1, 384, 240, 240, 208,,,, -5, 5, 4, 4, 2, 2, 1, 2, 128, 240, 240, 208,,,, -5, 5, 4, 4, 2, 2, 1, 2, 256, 240, 240, 208,,,, -5, 5, 4, 4, 2, 2, 1, 2, 384, 240, 240, 208,,,, -5, 5, 4, 4, 2, 2, 2, 1, 128, 240, 240, 208,,,, -5, 5, 4, 4, 2, 2, 2, 1, 256, 240, 240, 208,,,, -5, 5, 4, 4, 2, 2, 2, 1, 384, 240, 240, 208,,,, -5, 5, 4, 4, 2, 2, 2, 2, 128, 240, 240, 208,,,, -5, 5, 4, 4, 2, 2, 2, 2, 256, 240, 240, 208,,,, -5, 5, 4, 4, 2, 2, 2, 2, 384, 240, 240, 208,,,, -5, 5, 4, 4, 3, 3, 1, 1, 128, 240, 240, 208,,,, -5, 5, 4, 4, 3, 3, 1, 1, 256, 240, 240, 208,,,, -5, 5, 4, 4, 3, 3, 1, 1, 384, 240, 240, 208,,,, -5, 5, 4, 4, 3, 3, 1, 2, 128, 240, 240, 208,,,, -5, 5, 4, 4, 3, 3, 1, 2, 256, 240, 240, 208,,,, -5, 5, 4, 4, 3, 3, 1, 2, 384, 240, 240, 208,,,, -5, 5, 4, 4, 3, 3, 1, 3, 128, 240, 240, 208,,,, -5, 5, 4, 4, 3, 3, 1, 3, 256, 240, 240, 208,,,, -5, 5, 4, 4, 3, 3, 1, 3, 384, 240, 240, 208,,,, -5, 5, 4, 4, 3, 3, 2, 1, 128, 240, 240, 208,,,, -5, 5, 4, 4, 3, 3, 2, 1, 256, 240, 240, 208,,,, -5, 5, 4, 4, 3, 3, 2, 1, 384, 240, 240, 208,,,, -5, 5, 4, 4, 3, 3, 2, 2, 128, 240, 240, 208,,,, -5, 5, 4, 4, 3, 3, 2, 2, 256, 240, 240, 208,,,, -5, 5, 4, 4, 3, 3, 2, 2, 384, 240, 240, 208,,,, -5, 5, 4, 4, 3, 3, 2, 3, 128, 240, 240, 208,,,, -5, 5, 4, 4, 3, 3, 2, 3, 256, 240, 240, 208,,,, -5, 5, 4, 4, 3, 3, 2, 3, 384, 240, 240, 208,,,, -5, 5, 4, 4, 3, 3, 3, 1, 128, 240, 240, 208,,,, -5, 5, 4, 4, 3, 3, 3, 1, 256, 240, 240, 208,,,, -5, 5, 4, 4, 3, 3, 3, 1, 384, 240, 240, 208,,,, -5, 5, 4, 4, 3, 3, 3, 2, 128, 240, 240, 208,,,, -5, 5, 4, 4, 3, 3, 3, 2, 256, 240, 240, 208,,,, -5, 5, 4, 4, 3, 3, 3, 2, 384, 240, 240, 208,,,, -5, 5, 4, 4, 3, 3, 3, 3, 128, 240, 240, 208,,,, -5, 5, 4, 4, 3, 3, 3, 3, 256, 240, 240, 208,,,, -5, 5, 4, 4, 3, 3, 3, 3, 384, 240, 240, 208,,,, -5, 5, 4, 5, 1, 1, 1, 1, 128, 240, 240, 240,,,, -5, 5, 4, 5, 1, 1, 1, 1, 256, 240, 240, 240,,,, -5, 5, 4, 5, 1, 1, 1, 1, 384, 240, 240, 240,,,, -5, 5, 4, 5, 2, 2, 1, 1, 128, 240, 240, 240,,,, -5, 5, 4, 5, 2, 2, 1, 1, 256, 240, 240, 240,,,, -5, 5, 4, 5, 2, 2, 1, 1, 384, 240, 240, 240,,,, -5, 5, 4, 5, 2, 2, 1, 2, 128, 240, 240, 240,,,, -5, 5, 4, 5, 2, 2, 1, 2, 256, 240, 240, 240,,,, -5, 5, 4, 5, 2, 2, 1, 2, 384, 240, 240, 240,,,, -5, 5, 4, 5, 2, 2, 2, 1, 128, 240, 240, 240,,,, -5, 5, 4, 5, 2, 2, 2, 1, 256, 240, 240, 240,,,, -5, 5, 4, 5, 2, 2, 2, 1, 384, 240, 240, 240,,,, -5, 5, 4, 5, 2, 2, 2, 2, 128, 240, 240, 240,,,, -5, 5, 4, 5, 2, 2, 2, 2, 256, 240, 240, 240,,,, -5, 5, 4, 5, 2, 2, 2, 2, 384, 240, 240, 240,,,, -5, 5, 4, 5, 3, 3, 1, 1, 128, 240, 240, 240,,,, -5, 5, 4, 5, 3, 3, 1, 1, 256, 240, 240, 240,,,, -5, 5, 4, 5, 3, 3, 1, 1, 384, 240, 240, 240,,,, -5, 5, 4, 5, 3, 3, 1, 2, 128, 240, 240, 240,,,, -5, 5, 4, 5, 3, 3, 1, 2, 256, 240, 240, 240,,,, -5, 5, 4, 5, 3, 3, 1, 2, 384, 240, 240, 240,,,, -5, 5, 4, 5, 3, 3, 1, 3, 128, 240, 240, 240,,,, -5, 5, 4, 5, 3, 3, 1, 3, 256, 240, 240, 240,,,, -5, 5, 4, 5, 3, 3, 1, 3, 384, 240, 240, 240,,,, -5, 5, 4, 5, 3, 3, 2, 1, 128, 240, 240, 240,,,, -5, 5, 4, 5, 3, 3, 2, 1, 256, 240, 240, 240,,,, -5, 5, 4, 5, 3, 3, 2, 1, 384, 240, 240, 240,,,, -5, 5, 4, 5, 3, 3, 2, 2, 128, 240, 240, 240,,,, -5, 5, 4, 5, 3, 3, 2, 2, 256, 240, 240, 240,,,, -5, 5, 4, 5, 3, 3, 2, 2, 384, 240, 240, 240,,,, -5, 5, 4, 5, 3, 3, 2, 3, 128, 240, 240, 240,,,, -5, 5, 4, 5, 3, 3, 2, 3, 256, 240, 240, 240,,,, -5, 5, 4, 5, 3, 3, 2, 3, 384, 240, 240, 240,,,, -5, 5, 4, 5, 3, 3, 3, 1, 128, 240, 240, 240,,,, -5, 5, 4, 5, 3, 3, 3, 1, 256, 240, 240, 240,,,, -5, 5, 4, 5, 3, 3, 3, 1, 384, 240, 240, 240,,,, -5, 5, 4, 5, 3, 3, 3, 2, 128, 240, 240, 240,,,, -5, 5, 4, 5, 3, 3, 3, 2, 256, 240, 240, 240,,,, -5, 5, 4, 5, 3, 3, 3, 2, 384, 240, 240, 240,,,, -5, 5, 4, 5, 3, 3, 3, 3, 128, 240, 240, 240,,,, -5, 5, 4, 5, 3, 3, 3, 3, 256, 240, 240, 240,,,, -5, 5, 4, 5, 3, 3, 3, 3, 384, 240, 240, 240,,,, -5, 5, 5, 1, 1, 1, 1, 1, 128, 80, 80, 55,,,, -5, 5, 5, 1, 1, 1, 1, 1, 256, 80, 80, 55,,,, -5, 5, 5, 1, 1, 1, 1, 1, 384, 80, 80, 55,,,, -5, 5, 5, 1, 2, 2, 1, 1, 128, 80, 78, 55,,,, -5, 5, 5, 1, 2, 2, 1, 1, 256, 80, 78, 55,,,, -5, 5, 5, 1, 2, 2, 1, 1, 384, 80, 78, 55,,,, -5, 5, 5, 1, 2, 2, 1, 2, 128, 80, 78, 55,,,, -5, 5, 5, 1, 2, 2, 1, 2, 256, 80, 78, 55,,,, -5, 5, 5, 1, 2, 2, 1, 2, 384, 80, 78, 55,,,, -5, 5, 5, 1, 2, 2, 2, 1, 128, 80, 78, 55,,,, -5, 5, 5, 1, 2, 2, 2, 1, 256, 80, 78, 55,,,, -5, 5, 5, 1, 2, 2, 2, 1, 384, 80, 78, 55,,,, -5, 5, 5, 1, 2, 2, 2, 2, 128, 80, 78, 55,,,, -5, 5, 5, 1, 2, 2, 2, 2, 256, 80, 78, 55,,,, -5, 5, 5, 1, 2, 2, 2, 2, 384, 80, 78, 55,,,, -5, 5, 5, 1, 3, 3, 1, 1, 128, 80, 75, 55,,,, -5, 5, 5, 1, 3, 3, 1, 1, 256, 80, 75, 55,,,, -5, 5, 5, 1, 3, 3, 1, 1, 384, 80, 75, 55,,,, -5, 5, 5, 1, 3, 3, 1, 2, 128, 80, 75, 55,,,, -5, 5, 5, 1, 3, 3, 1, 2, 256, 80, 75, 55,,,, -5, 5, 5, 1, 3, 3, 1, 2, 384, 80, 75, 55,,,, -5, 5, 5, 1, 3, 3, 1, 3, 128, 80, 75, 55,,,, -5, 5, 5, 1, 3, 3, 1, 3, 256, 80, 75, 55,,,, -5, 5, 5, 1, 3, 3, 1, 3, 384, 80, 75, 55,,,, -5, 5, 5, 1, 3, 3, 2, 1, 128, 80, 75, 55,,,, -5, 5, 5, 1, 3, 3, 2, 1, 256, 80, 75, 55,,,, -5, 5, 5, 1, 3, 3, 2, 1, 384, 80, 75, 55,,,, -5, 5, 5, 1, 3, 3, 2, 2, 128, 80, 75, 55,,,, -5, 5, 5, 1, 3, 3, 2, 2, 256, 80, 75, 55,,,, -5, 5, 5, 1, 3, 3, 2, 2, 384, 80, 75, 55,,,, -5, 5, 5, 1, 3, 3, 2, 3, 128, 80, 75, 55,,,, -5, 5, 5, 1, 3, 3, 2, 3, 256, 80, 75, 55,,,, -5, 5, 5, 1, 3, 3, 2, 3, 384, 80, 75, 55,,,, -5, 5, 5, 1, 3, 3, 3, 1, 128, 80, 75, 55,,,, -5, 5, 5, 1, 3, 3, 3, 1, 256, 80, 75, 55,,,, -5, 5, 5, 1, 3, 3, 3, 1, 384, 80, 75, 55,,,, -5, 5, 5, 1, 3, 3, 3, 2, 128, 80, 75, 55,,,, -5, 5, 5, 1, 3, 3, 3, 2, 256, 80, 75, 55,,,, -5, 5, 5, 1, 3, 3, 3, 2, 384, 80, 75, 55,,,, -5, 5, 5, 1, 3, 3, 3, 3, 128, 80, 75, 55,,,, -5, 5, 5, 1, 3, 3, 3, 3, 256, 80, 75, 55,,,, -5, 5, 5, 1, 3, 3, 3, 3, 384, 80, 75, 55,,,, -5, 5, 5, 2, 1, 1, 1, 1, 128, 156, 156, 106,,,, -5, 5, 5, 2, 1, 1, 1, 1, 256, 156, 156, 106,,,, -5, 5, 5, 2, 1, 1, 1, 1, 384, 156, 156, 106,,,, -5, 5, 5, 2, 2, 2, 1, 1, 128, 156, 152, 106,,,, -5, 5, 5, 2, 2, 2, 1, 1, 256, 156, 152, 106,,,, -5, 5, 5, 2, 2, 2, 1, 1, 384, 156, 152, 106,,,, -5, 5, 5, 2, 2, 2, 1, 2, 128, 156, 152, 106,,,, -5, 5, 5, 2, 2, 2, 1, 2, 256, 156, 152, 106,,,, -5, 5, 5, 2, 2, 2, 1, 2, 384, 156, 152, 106,,,, -5, 5, 5, 2, 2, 2, 2, 1, 128, 156, 152, 106,,,, -5, 5, 5, 2, 2, 2, 2, 1, 256, 156, 152, 106,,,, -5, 5, 5, 2, 2, 2, 2, 1, 384, 156, 152, 106,,,, -5, 5, 5, 2, 2, 2, 2, 2, 128, 156, 152, 106,,,, -5, 5, 5, 2, 2, 2, 2, 2, 256, 156, 152, 106,,,, -5, 5, 5, 2, 2, 2, 2, 2, 384, 156, 152, 106,,,, -5, 5, 5, 2, 3, 3, 1, 1, 128, 156, 146, 106,,,, -5, 5, 5, 2, 3, 3, 1, 1, 256, 156, 146, 106,,,, -5, 5, 5, 2, 3, 3, 1, 1, 384, 156, 146, 106,,,, -5, 5, 5, 2, 3, 3, 1, 2, 128, 156, 146, 106,,,, -5, 5, 5, 2, 3, 3, 1, 2, 256, 156, 146, 106,,,, -5, 5, 5, 2, 3, 3, 1, 2, 384, 156, 146, 106,,,, -5, 5, 5, 2, 3, 3, 1, 3, 128, 156, 146, 106,,,, -5, 5, 5, 2, 3, 3, 1, 3, 256, 156, 146, 106,,,, -5, 5, 5, 2, 3, 3, 1, 3, 384, 156, 146, 106,,,, -5, 5, 5, 2, 3, 3, 2, 1, 128, 156, 146, 106,,,, -5, 5, 5, 2, 3, 3, 2, 1, 256, 156, 146, 106,,,, -5, 5, 5, 2, 3, 3, 2, 1, 384, 156, 146, 106,,,, -5, 5, 5, 2, 3, 3, 2, 2, 128, 156, 146, 106,,,, -5, 5, 5, 2, 3, 3, 2, 2, 256, 156, 146, 106,,,, -5, 5, 5, 2, 3, 3, 2, 2, 384, 156, 146, 106,,,, -5, 5, 5, 2, 3, 3, 2, 3, 128, 156, 146, 106,,,, -5, 5, 5, 2, 3, 3, 2, 3, 256, 156, 146, 106,,,, -5, 5, 5, 2, 3, 3, 2, 3, 384, 156, 146, 106,,,, -5, 5, 5, 2, 3, 3, 3, 1, 128, 156, 146, 106,,,, -5, 5, 5, 2, 3, 3, 3, 1, 256, 156, 146, 106,,,, -5, 5, 5, 2, 3, 3, 3, 1, 384, 156, 146, 106,,,, -5, 5, 5, 2, 3, 3, 3, 2, 128, 156, 146, 106,,,, -5, 5, 5, 2, 3, 3, 3, 2, 256, 156, 146, 106,,,, -5, 5, 5, 2, 3, 3, 3, 2, 384, 156, 146, 106,,,, -5, 5, 5, 2, 3, 3, 3, 3, 128, 156, 146, 106,,,, -5, 5, 5, 2, 3, 3, 3, 3, 256, 156, 146, 106,,,, -5, 5, 5, 2, 3, 3, 3, 3, 384, 156, 146, 106,,,, -5, 5, 5, 3, 1, 1, 1, 1, 128, 232, 232, 157,,,, -5, 5, 5, 3, 1, 1, 1, 1, 256, 232, 232, 157,,,, -5, 5, 5, 3, 1, 1, 1, 1, 384, 232, 232, 157,,,, -5, 5, 5, 3, 2, 2, 1, 1, 128, 232, 226, 157,,,, -5, 5, 5, 3, 2, 2, 1, 1, 256, 232, 226, 157,,,, -5, 5, 5, 3, 2, 2, 1, 1, 384, 232, 226, 157,,,, -5, 5, 5, 3, 2, 2, 1, 2, 128, 232, 226, 157,,,, -5, 5, 5, 3, 2, 2, 1, 2, 256, 232, 226, 157,,,, -5, 5, 5, 3, 2, 2, 1, 2, 384, 232, 226, 157,,,, -5, 5, 5, 3, 2, 2, 2, 1, 128, 232, 226, 157,,,, -5, 5, 5, 3, 2, 2, 2, 1, 256, 232, 226, 157,,,, -5, 5, 5, 3, 2, 2, 2, 1, 384, 232, 226, 157,,,, -5, 5, 5, 3, 2, 2, 2, 2, 128, 232, 226, 157,,,, -5, 5, 5, 3, 2, 2, 2, 2, 256, 232, 226, 157,,,, -5, 5, 5, 3, 2, 2, 2, 2, 384, 232, 226, 157,,,, -5, 5, 5, 3, 3, 3, 1, 1, 128, 232, 217, 157,,,, -5, 5, 5, 3, 3, 3, 1, 1, 256, 232, 217, 157,,,, -5, 5, 5, 3, 3, 3, 1, 1, 384, 232, 217, 157,,,, -5, 5, 5, 3, 3, 3, 1, 2, 128, 232, 217, 157,,,, -5, 5, 5, 3, 3, 3, 1, 2, 256, 232, 217, 157,,,, -5, 5, 5, 3, 3, 3, 1, 2, 384, 232, 217, 157,,,, -5, 5, 5, 3, 3, 3, 1, 3, 128, 232, 217, 157,,,, -5, 5, 5, 3, 3, 3, 1, 3, 256, 232, 217, 157,,,, -5, 5, 5, 3, 3, 3, 1, 3, 384, 232, 217, 157,,,, -5, 5, 5, 3, 3, 3, 2, 1, 128, 232, 217, 157,,,, -5, 5, 5, 3, 3, 3, 2, 1, 256, 232, 217, 157,,,, -5, 5, 5, 3, 3, 3, 2, 1, 384, 232, 217, 157,,,, -5, 5, 5, 3, 3, 3, 2, 2, 128, 232, 217, 157,,,, -5, 5, 5, 3, 3, 3, 2, 2, 256, 232, 217, 157,,,, -5, 5, 5, 3, 3, 3, 2, 2, 384, 232, 217, 157,,,, -5, 5, 5, 3, 3, 3, 2, 3, 128, 232, 217, 157,,,, -5, 5, 5, 3, 3, 3, 2, 3, 256, 232, 217, 157,,,, -5, 5, 5, 3, 3, 3, 2, 3, 384, 232, 217, 157,,,, -5, 5, 5, 3, 3, 3, 3, 1, 128, 232, 217, 157,,,, -5, 5, 5, 3, 3, 3, 3, 1, 256, 232, 217, 157,,,, -5, 5, 5, 3, 3, 3, 3, 1, 384, 232, 217, 157,,,, -5, 5, 5, 3, 3, 3, 3, 2, 128, 232, 217, 157,,,, -5, 5, 5, 3, 3, 3, 3, 2, 256, 232, 217, 157,,,, -5, 5, 5, 3, 3, 3, 3, 2, 384, 232, 217, 157,,,, -5, 5, 5, 3, 3, 3, 3, 3, 128, 232, 217, 157,,,, -5, 5, 5, 3, 3, 3, 3, 3, 256, 232, 217, 157,,,, -5, 5, 5, 3, 3, 3, 3, 3, 384, 232, 217, 157,,,, -5, 5, 5, 4, 1, 1, 1, 1, 128, 240, 240, 208,,,, -5, 5, 5, 4, 1, 1, 1, 1, 256, 240, 240, 208,,,, -5, 5, 5, 4, 1, 1, 1, 1, 384, 240, 240, 208,,,, -5, 5, 5, 4, 2, 2, 1, 1, 128, 240, 240, 208,,,, -5, 5, 5, 4, 2, 2, 1, 1, 256, 240, 240, 208,,,, -5, 5, 5, 4, 2, 2, 1, 1, 384, 240, 240, 208,,,, -5, 5, 5, 4, 2, 2, 1, 2, 128, 240, 240, 208,,,, -5, 5, 5, 4, 2, 2, 1, 2, 256, 240, 240, 208,,,, -5, 5, 5, 4, 2, 2, 1, 2, 384, 240, 240, 208,,,, -5, 5, 5, 4, 2, 2, 2, 1, 128, 240, 240, 208,,,, -5, 5, 5, 4, 2, 2, 2, 1, 256, 240, 240, 208,,,, -5, 5, 5, 4, 2, 2, 2, 1, 384, 240, 240, 208,,,, -5, 5, 5, 4, 2, 2, 2, 2, 128, 240, 240, 208,,,, -5, 5, 5, 4, 2, 2, 2, 2, 256, 240, 240, 208,,,, -5, 5, 5, 4, 2, 2, 2, 2, 384, 240, 240, 208,,,, -5, 5, 5, 4, 3, 3, 1, 1, 128, 240, 240, 208,,,, -5, 5, 5, 4, 3, 3, 1, 1, 256, 240, 240, 208,,,, -5, 5, 5, 4, 3, 3, 1, 1, 384, 240, 240, 208,,,, -5, 5, 5, 4, 3, 3, 1, 2, 128, 240, 240, 208,,,, -5, 5, 5, 4, 3, 3, 1, 2, 256, 240, 240, 208,,,, -5, 5, 5, 4, 3, 3, 1, 2, 384, 240, 240, 208,,,, -5, 5, 5, 4, 3, 3, 1, 3, 128, 240, 240, 208,,,, -5, 5, 5, 4, 3, 3, 1, 3, 256, 240, 240, 208,,,, -5, 5, 5, 4, 3, 3, 1, 3, 384, 240, 240, 208,,,, -5, 5, 5, 4, 3, 3, 2, 1, 128, 240, 240, 208,,,, -5, 5, 5, 4, 3, 3, 2, 1, 256, 240, 240, 208,,,, -5, 5, 5, 4, 3, 3, 2, 1, 384, 240, 240, 208,,,, -5, 5, 5, 4, 3, 3, 2, 2, 128, 240, 240, 208,,,, -5, 5, 5, 4, 3, 3, 2, 2, 256, 240, 240, 208,,,, -5, 5, 5, 4, 3, 3, 2, 2, 384, 240, 240, 208,,,, -5, 5, 5, 4, 3, 3, 2, 3, 128, 240, 240, 208,,,, -5, 5, 5, 4, 3, 3, 2, 3, 256, 240, 240, 208,,,, -5, 5, 5, 4, 3, 3, 2, 3, 384, 240, 240, 208,,,, -5, 5, 5, 4, 3, 3, 3, 1, 128, 240, 240, 208,,,, -5, 5, 5, 4, 3, 3, 3, 1, 256, 240, 240, 208,,,, -5, 5, 5, 4, 3, 3, 3, 1, 384, 240, 240, 208,,,, -5, 5, 5, 4, 3, 3, 3, 2, 128, 240, 240, 208,,,, -5, 5, 5, 4, 3, 3, 3, 2, 256, 240, 240, 208,,,, -5, 5, 5, 4, 3, 3, 3, 2, 384, 240, 240, 208,,,, -5, 5, 5, 4, 3, 3, 3, 3, 128, 240, 240, 208,,,, -5, 5, 5, 4, 3, 3, 3, 3, 256, 240, 240, 208,,,, -5, 5, 5, 4, 3, 3, 3, 3, 384, 240, 240, 208,,,, -5, 5, 5, 5, 1, 1, 1, 1, 128, 240, 240, 240,,,, -5, 5, 5, 5, 1, 1, 1, 1, 256, 240, 240, 240,,,, -5, 5, 5, 5, 1, 1, 1, 1, 384, 240, 240, 240,,,, -5, 5, 5, 5, 2, 2, 1, 1, 128, 240, 240, 240,,,, -5, 5, 5, 5, 2, 2, 1, 1, 256, 240, 240, 240,,,, -5, 5, 5, 5, 2, 2, 1, 1, 384, 240, 240, 240,,,, -5, 5, 5, 5, 2, 2, 1, 2, 128, 240, 240, 240,,,, -5, 5, 5, 5, 2, 2, 1, 2, 256, 240, 240, 240,,,, -5, 5, 5, 5, 2, 2, 1, 2, 384, 240, 240, 240,,,, -5, 5, 5, 5, 2, 2, 2, 1, 128, 240, 240, 240,,,, -5, 5, 5, 5, 2, 2, 2, 1, 256, 240, 240, 240,,,, -5, 5, 5, 5, 2, 2, 2, 1, 384, 240, 240, 240,,,, -5, 5, 5, 5, 2, 2, 2, 2, 128, 240, 240, 240,,,, -5, 5, 5, 5, 2, 2, 2, 2, 256, 240, 240, 240,,,, -5, 5, 5, 5, 2, 2, 2, 2, 384, 240, 240, 240,,,, -5, 5, 5, 5, 3, 3, 1, 1, 128, 240, 240, 240,,,, -5, 5, 5, 5, 3, 3, 1, 1, 256, 240, 240, 240,,,, -5, 5, 5, 5, 3, 3, 1, 1, 384, 240, 240, 240,,,, -5, 5, 5, 5, 3, 3, 1, 2, 128, 240, 240, 240,,,, -5, 5, 5, 5, 3, 3, 1, 2, 256, 240, 240, 240,,,, -5, 5, 5, 5, 3, 3, 1, 2, 384, 240, 240, 240,,,, -5, 5, 5, 5, 3, 3, 1, 3, 128, 240, 240, 240,,,, -5, 5, 5, 5, 3, 3, 1, 3, 256, 240, 240, 240,,,, -5, 5, 5, 5, 3, 3, 1, 3, 384, 240, 240, 240,,,, -5, 5, 5, 5, 3, 3, 2, 1, 128, 240, 240, 240,,,, -5, 5, 5, 5, 3, 3, 2, 1, 256, 240, 240, 240,,,, -5, 5, 5, 5, 3, 3, 2, 1, 384, 240, 240, 240,,,, -5, 5, 5, 5, 3, 3, 2, 2, 128, 240, 240, 240,,,, -5, 5, 5, 5, 3, 3, 2, 2, 256, 240, 240, 240,,,, -5, 5, 5, 5, 3, 3, 2, 2, 384, 240, 240, 240,,,, -5, 5, 5, 5, 3, 3, 2, 3, 128, 240, 240, 240,,,, -5, 5, 5, 5, 3, 3, 2, 3, 256, 240, 240, 240,,,, -5, 5, 5, 5, 3, 3, 2, 3, 384, 240, 240, 240,,,, -5, 5, 5, 5, 3, 3, 3, 1, 128, 240, 240, 240,,,, -5, 5, 5, 5, 3, 3, 3, 1, 256, 240, 240, 240,,,, -5, 5, 5, 5, 3, 3, 3, 1, 384, 240, 240, 240,,,, -5, 5, 5, 5, 3, 3, 3, 2, 128, 240, 240, 240,,,, -5, 5, 5, 5, 3, 3, 3, 2, 256, 240, 240, 240,,,, -5, 5, 5, 5, 3, 3, 3, 2, 384, 240, 240, 240,,,, -5, 5, 5, 5, 3, 3, 3, 3, 128, 240, 240, 240,,,, -5, 5, 5, 5, 3, 3, 3, 3, 256, 240, 240, 240,,,, -5, 5, 5, 5, 3, 3, 3, 3, 384, 240, 240, 240,,,, -5, 6, 1, 1, 1, 1, 1, 1, 128, 81, 81, 56,,,, -5, 6, 1, 1, 1, 1, 1, 1, 256, 81, 81, 56,,,, -5, 6, 1, 1, 1, 1, 1, 1, 384, 81, 81, 56,,,, -5, 6, 1, 1, 2, 2, 1, 1, 128, 81, 75, 53,,,, -5, 6, 1, 1, 2, 2, 1, 1, 256, 81, 75, 53,,,, -5, 6, 1, 1, 2, 2, 1, 1, 384, 81, 75, 53,,,, -5, 6, 1, 1, 2, 2, 1, 2, 128, 81, 75, 53,,,, -5, 6, 1, 1, 2, 2, 1, 2, 256, 81, 75, 53,,,, -5, 6, 1, 1, 2, 2, 1, 2, 384, 81, 75, 53,,,, -5, 6, 1, 1, 2, 2, 2, 1, 128, 81, 75, 53,,,, -5, 6, 1, 1, 2, 2, 2, 1, 256, 81, 75, 53,,,, -5, 6, 1, 1, 2, 2, 2, 1, 384, 81, 75, 53,,,, -5, 6, 1, 1, 2, 2, 2, 2, 128, 81, 75, 53,,,, -5, 6, 1, 1, 2, 2, 2, 2, 256, 81, 75, 53,,,, -5, 6, 1, 1, 2, 2, 2, 2, 384, 81, 75, 53,,,, -5, 6, 1, 1, 3, 3, 1, 1, 128, 81, 72, 51,,,, -5, 6, 1, 1, 3, 3, 1, 1, 256, 81, 72, 51,,,, -5, 6, 1, 1, 3, 3, 1, 1, 384, 81, 72, 51,,,, -5, 6, 1, 1, 3, 3, 1, 2, 128, 81, 72, 51,,,, -5, 6, 1, 1, 3, 3, 1, 2, 256, 81, 72, 51,,,, -5, 6, 1, 1, 3, 3, 1, 2, 384, 81, 72, 51,,,, -5, 6, 1, 1, 3, 3, 1, 3, 128, 81, 72, 51,,,, -5, 6, 1, 1, 3, 3, 1, 3, 256, 81, 72, 51,,,, -5, 6, 1, 1, 3, 3, 1, 3, 384, 81, 72, 51,,,, -5, 6, 1, 1, 3, 3, 2, 1, 128, 81, 72, 51,,,, -5, 6, 1, 1, 3, 3, 2, 1, 256, 81, 72, 51,,,, -5, 6, 1, 1, 3, 3, 2, 1, 384, 81, 72, 51,,,, -5, 6, 1, 1, 3, 3, 2, 2, 128, 81, 72, 51,,,, -5, 6, 1, 1, 3, 3, 2, 2, 256, 81, 72, 51,,,, -5, 6, 1, 1, 3, 3, 2, 2, 384, 81, 72, 51,,,, -5, 6, 1, 1, 3, 3, 2, 3, 128, 81, 72, 51,,,, -5, 6, 1, 1, 3, 3, 2, 3, 256, 81, 72, 51,,,, -5, 6, 1, 1, 3, 3, 2, 3, 384, 81, 72, 51,,,, -5, 6, 1, 1, 3, 3, 3, 1, 128, 81, 72, 51,,,, -5, 6, 1, 1, 3, 3, 3, 1, 256, 81, 72, 51,,,, -5, 6, 1, 1, 3, 3, 3, 1, 384, 81, 72, 51,,,, -5, 6, 1, 1, 3, 3, 3, 2, 128, 81, 72, 51,,,, -5, 6, 1, 1, 3, 3, 3, 2, 256, 81, 72, 51,,,, -5, 6, 1, 1, 3, 3, 3, 2, 384, 81, 72, 51,,,, -5, 6, 1, 1, 3, 3, 3, 3, 128, 81, 72, 51,,,, -5, 6, 1, 1, 3, 3, 3, 3, 256, 81, 72, 51,,,, -5, 6, 1, 1, 3, 3, 3, 3, 384, 81, 72, 51,,,, -5, 6, 1, 2, 1, 1, 1, 1, 128, 157, 157, 107,,,, -5, 6, 1, 2, 1, 1, 1, 1, 256, 157, 157, 107,,,, -5, 6, 1, 2, 1, 1, 1, 1, 384, 157, 157, 107,,,, -5, 6, 1, 2, 2, 2, 1, 1, 128, 157, 145, 101,,,, -5, 6, 1, 2, 2, 2, 1, 1, 256, 157, 145, 101,,,, -5, 6, 1, 2, 2, 2, 1, 1, 384, 157, 145, 101,,,, -5, 6, 1, 2, 2, 2, 1, 2, 128, 157, 145, 101,,,, -5, 6, 1, 2, 2, 2, 1, 2, 256, 157, 145, 101,,,, -5, 6, 1, 2, 2, 2, 1, 2, 384, 157, 145, 101,,,, -5, 6, 1, 2, 2, 2, 2, 1, 128, 157, 145, 101,,,, -5, 6, 1, 2, 2, 2, 2, 1, 256, 157, 145, 101,,,, -5, 6, 1, 2, 2, 2, 2, 1, 384, 157, 145, 101,,,, -5, 6, 1, 2, 2, 2, 2, 2, 128, 157, 145, 101,,,, -5, 6, 1, 2, 2, 2, 2, 2, 256, 157, 145, 101,,,, -5, 6, 1, 2, 2, 2, 2, 2, 384, 157, 145, 101,,,, -5, 6, 1, 2, 3, 3, 1, 1, 128, 157, 139, 97,,,, -5, 6, 1, 2, 3, 3, 1, 1, 256, 157, 139, 97,,,, -5, 6, 1, 2, 3, 3, 1, 1, 384, 157, 139, 97,,,, -5, 6, 1, 2, 3, 3, 1, 2, 128, 157, 139, 97,,,, -5, 6, 1, 2, 3, 3, 1, 2, 256, 157, 139, 97,,,, -5, 6, 1, 2, 3, 3, 1, 2, 384, 157, 139, 97,,,, -5, 6, 1, 2, 3, 3, 1, 3, 128, 157, 139, 97,,,, -5, 6, 1, 2, 3, 3, 1, 3, 256, 157, 139, 97,,,, -5, 6, 1, 2, 3, 3, 1, 3, 384, 157, 139, 97,,,, -5, 6, 1, 2, 3, 3, 2, 1, 128, 157, 139, 97,,,, -5, 6, 1, 2, 3, 3, 2, 1, 256, 157, 139, 97,,,, -5, 6, 1, 2, 3, 3, 2, 1, 384, 157, 139, 97,,,, -5, 6, 1, 2, 3, 3, 2, 2, 128, 157, 139, 97,,,, -5, 6, 1, 2, 3, 3, 2, 2, 256, 157, 139, 97,,,, -5, 6, 1, 2, 3, 3, 2, 2, 384, 157, 139, 97,,,, -5, 6, 1, 2, 3, 3, 2, 3, 128, 157, 139, 97,,,, -5, 6, 1, 2, 3, 3, 2, 3, 256, 157, 139, 97,,,, -5, 6, 1, 2, 3, 3, 2, 3, 384, 157, 139, 97,,,, -5, 6, 1, 2, 3, 3, 3, 1, 128, 157, 139, 97,,,, -5, 6, 1, 2, 3, 3, 3, 1, 256, 157, 139, 97,,,, -5, 6, 1, 2, 3, 3, 3, 1, 384, 157, 139, 97,,,, -5, 6, 1, 2, 3, 3, 3, 2, 128, 157, 139, 97,,,, -5, 6, 1, 2, 3, 3, 3, 2, 256, 157, 139, 97,,,, -5, 6, 1, 2, 3, 3, 3, 2, 384, 157, 139, 97,,,, -5, 6, 1, 2, 3, 3, 3, 3, 128, 157, 139, 97,,,, -5, 6, 1, 2, 3, 3, 3, 3, 256, 157, 139, 97,,,, -5, 6, 1, 2, 3, 3, 3, 3, 384, 157, 139, 97,,,, -5, 6, 1, 3, 1, 1, 1, 1, 128, 233, 233, 158,,,, -5, 6, 1, 3, 1, 1, 1, 1, 256, 233, 233, 158,,,, -5, 6, 1, 3, 1, 1, 1, 1, 384, 233, 233, 158,,,, -5, 6, 1, 3, 2, 2, 1, 1, 128, 233, 215, 149,,,, -5, 6, 1, 3, 2, 2, 1, 1, 256, 233, 215, 149,,,, -5, 6, 1, 3, 2, 2, 1, 1, 384, 233, 215, 149,,,, -5, 6, 1, 3, 2, 2, 1, 2, 128, 233, 215, 149,,,, -5, 6, 1, 3, 2, 2, 1, 2, 256, 233, 215, 149,,,, -5, 6, 1, 3, 2, 2, 1, 2, 384, 233, 215, 149,,,, -5, 6, 1, 3, 2, 2, 2, 1, 128, 233, 215, 149,,,, -5, 6, 1, 3, 2, 2, 2, 1, 256, 233, 215, 149,,,, -5, 6, 1, 3, 2, 2, 2, 1, 384, 233, 215, 149,,,, -5, 6, 1, 3, 2, 2, 2, 2, 128, 233, 215, 149,,,, -5, 6, 1, 3, 2, 2, 2, 2, 256, 233, 215, 149,,,, -5, 6, 1, 3, 2, 2, 2, 2, 384, 233, 215, 149,,,, -5, 6, 1, 3, 3, 3, 1, 1, 128, 233, 206, 143,,,, -5, 6, 1, 3, 3, 3, 1, 1, 256, 233, 206, 143,,,, -5, 6, 1, 3, 3, 3, 1, 1, 384, 233, 206, 143,,,, -5, 6, 1, 3, 3, 3, 1, 2, 128, 233, 206, 143,,,, -5, 6, 1, 3, 3, 3, 1, 2, 256, 233, 206, 143,,,, -5, 6, 1, 3, 3, 3, 1, 2, 384, 233, 206, 143,,,, -5, 6, 1, 3, 3, 3, 1, 3, 128, 233, 206, 143,,,, -5, 6, 1, 3, 3, 3, 1, 3, 256, 233, 206, 143,,,, -5, 6, 1, 3, 3, 3, 1, 3, 384, 233, 206, 143,,,, -5, 6, 1, 3, 3, 3, 2, 1, 128, 233, 206, 143,,,, -5, 6, 1, 3, 3, 3, 2, 1, 256, 233, 206, 143,,,, -5, 6, 1, 3, 3, 3, 2, 1, 384, 233, 206, 143,,,, -5, 6, 1, 3, 3, 3, 2, 2, 128, 233, 206, 143,,,, -5, 6, 1, 3, 3, 3, 2, 2, 256, 233, 206, 143,,,, -5, 6, 1, 3, 3, 3, 2, 2, 384, 233, 206, 143,,,, -5, 6, 1, 3, 3, 3, 2, 3, 128, 233, 206, 143,,,, -5, 6, 1, 3, 3, 3, 2, 3, 256, 233, 206, 143,,,, -5, 6, 1, 3, 3, 3, 2, 3, 384, 233, 206, 143,,,, -5, 6, 1, 3, 3, 3, 3, 1, 128, 233, 206, 143,,,, -5, 6, 1, 3, 3, 3, 3, 1, 256, 233, 206, 143,,,, -5, 6, 1, 3, 3, 3, 3, 1, 384, 233, 206, 143,,,, -5, 6, 1, 3, 3, 3, 3, 2, 128, 233, 206, 143,,,, -5, 6, 1, 3, 3, 3, 3, 2, 256, 233, 206, 143,,,, -5, 6, 1, 3, 3, 3, 3, 2, 384, 233, 206, 143,,,, -5, 6, 1, 3, 3, 3, 3, 3, 128, 233, 206, 143,,,, -5, 6, 1, 3, 3, 3, 3, 3, 256, 233, 206, 143,,,, -5, 6, 1, 3, 3, 3, 3, 3, 384, 233, 206, 143,,,, -5, 6, 1, 4, 1, 1, 1, 1, 128, 240, 240, 209,,,, -5, 6, 1, 4, 1, 1, 1, 1, 256, 240, 240, 209,,,, -5, 6, 1, 4, 1, 1, 1, 1, 384, 240, 240, 209,,,, -5, 6, 1, 4, 2, 2, 1, 1, 128, 240, 240, 197,,,, -5, 6, 1, 4, 2, 2, 1, 1, 256, 240, 240, 197,,,, -5, 6, 1, 4, 2, 2, 1, 1, 384, 240, 240, 197,,,, -5, 6, 1, 4, 2, 2, 1, 2, 128, 240, 240, 197,,,, -5, 6, 1, 4, 2, 2, 1, 2, 256, 240, 240, 197,,,, -5, 6, 1, 4, 2, 2, 1, 2, 384, 240, 240, 197,,,, -5, 6, 1, 4, 2, 2, 2, 1, 128, 240, 240, 197,,,, -5, 6, 1, 4, 2, 2, 2, 1, 256, 240, 240, 197,,,, -5, 6, 1, 4, 2, 2, 2, 1, 384, 240, 240, 197,,,, -5, 6, 1, 4, 2, 2, 2, 2, 128, 240, 240, 197,,,, -5, 6, 1, 4, 2, 2, 2, 2, 256, 240, 240, 197,,,, -5, 6, 1, 4, 2, 2, 2, 2, 384, 240, 240, 197,,,, -5, 6, 1, 4, 3, 3, 1, 1, 128, 240, 240, 189,,,, -5, 6, 1, 4, 3, 3, 1, 1, 256, 240, 240, 189,,,, -5, 6, 1, 4, 3, 3, 1, 1, 384, 240, 240, 189,,,, -5, 6, 1, 4, 3, 3, 1, 2, 128, 240, 240, 189,,,, -5, 6, 1, 4, 3, 3, 1, 2, 256, 240, 240, 189,,,, -5, 6, 1, 4, 3, 3, 1, 2, 384, 240, 240, 189,,,, -5, 6, 1, 4, 3, 3, 1, 3, 128, 240, 240, 189,,,, -5, 6, 1, 4, 3, 3, 1, 3, 256, 240, 240, 189,,,, -5, 6, 1, 4, 3, 3, 1, 3, 384, 240, 240, 189,,,, -5, 6, 1, 4, 3, 3, 2, 1, 128, 240, 240, 189,,,, -5, 6, 1, 4, 3, 3, 2, 1, 256, 240, 240, 189,,,, -5, 6, 1, 4, 3, 3, 2, 1, 384, 240, 240, 189,,,, -5, 6, 1, 4, 3, 3, 2, 2, 128, 240, 240, 189,,,, -5, 6, 1, 4, 3, 3, 2, 2, 256, 240, 240, 189,,,, -5, 6, 1, 4, 3, 3, 2, 2, 384, 240, 240, 189,,,, -5, 6, 1, 4, 3, 3, 2, 3, 128, 240, 240, 189,,,, -5, 6, 1, 4, 3, 3, 2, 3, 256, 240, 240, 189,,,, -5, 6, 1, 4, 3, 3, 2, 3, 384, 240, 240, 189,,,, -5, 6, 1, 4, 3, 3, 3, 1, 128, 240, 240, 189,,,, -5, 6, 1, 4, 3, 3, 3, 1, 256, 240, 240, 189,,,, -5, 6, 1, 4, 3, 3, 3, 1, 384, 240, 240, 189,,,, -5, 6, 1, 4, 3, 3, 3, 2, 128, 240, 240, 189,,,, -5, 6, 1, 4, 3, 3, 3, 2, 256, 240, 240, 189,,,, -5, 6, 1, 4, 3, 3, 3, 2, 384, 240, 240, 189,,,, -5, 6, 1, 4, 3, 3, 3, 3, 128, 240, 240, 189,,,, -5, 6, 1, 4, 3, 3, 3, 3, 256, 240, 240, 189,,,, -5, 6, 1, 4, 3, 3, 3, 3, 384, 240, 240, 189,,,, -5, 6, 1, 5, 1, 1, 1, 1, 128, 240, 240, 240,,,, -5, 6, 1, 5, 1, 1, 1, 1, 256, 240, 240, 240,,,, -5, 6, 1, 5, 1, 1, 1, 1, 384, 240, 240, 240,,,, -5, 6, 1, 5, 2, 2, 1, 1, 128, 240, 240, 240,,,, -5, 6, 1, 5, 2, 2, 1, 1, 256, 240, 240, 240,,,, -5, 6, 1, 5, 2, 2, 1, 1, 384, 240, 240, 240,,,, -5, 6, 1, 5, 2, 2, 1, 2, 128, 240, 240, 240,,,, -5, 6, 1, 5, 2, 2, 1, 2, 256, 240, 240, 240,,,, -5, 6, 1, 5, 2, 2, 1, 2, 384, 240, 240, 240,,,, -5, 6, 1, 5, 2, 2, 2, 1, 128, 240, 240, 240,,,, -5, 6, 1, 5, 2, 2, 2, 1, 256, 240, 240, 240,,,, -5, 6, 1, 5, 2, 2, 2, 1, 384, 240, 240, 240,,,, -5, 6, 1, 5, 2, 2, 2, 2, 128, 240, 240, 240,,,, -5, 6, 1, 5, 2, 2, 2, 2, 256, 240, 240, 240,,,, -5, 6, 1, 5, 2, 2, 2, 2, 384, 240, 240, 240,,,, -5, 6, 1, 5, 3, 3, 1, 1, 128, 240, 240, 235,,,, -5, 6, 1, 5, 3, 3, 1, 1, 256, 240, 240, 235,,,, -5, 6, 1, 5, 3, 3, 1, 1, 384, 240, 240, 235,,,, -5, 6, 1, 5, 3, 3, 1, 2, 128, 240, 240, 235,,,, -5, 6, 1, 5, 3, 3, 1, 2, 256, 240, 240, 235,,,, -5, 6, 1, 5, 3, 3, 1, 2, 384, 240, 240, 235,,,, -5, 6, 1, 5, 3, 3, 1, 3, 128, 240, 240, 235,,,, -5, 6, 1, 5, 3, 3, 1, 3, 256, 240, 240, 235,,,, -5, 6, 1, 5, 3, 3, 1, 3, 384, 240, 240, 235,,,, -5, 6, 1, 5, 3, 3, 2, 1, 128, 240, 240, 235,,,, -5, 6, 1, 5, 3, 3, 2, 1, 256, 240, 240, 235,,,, -5, 6, 1, 5, 3, 3, 2, 1, 384, 240, 240, 235,,,, -5, 6, 1, 5, 3, 3, 2, 2, 128, 240, 240, 235,,,, -5, 6, 1, 5, 3, 3, 2, 2, 256, 240, 240, 235,,,, -5, 6, 1, 5, 3, 3, 2, 2, 384, 240, 240, 235,,,, -5, 6, 1, 5, 3, 3, 2, 3, 128, 240, 240, 235,,,, -5, 6, 1, 5, 3, 3, 2, 3, 256, 240, 240, 235,,,, -5, 6, 1, 5, 3, 3, 2, 3, 384, 240, 240, 235,,,, -5, 6, 1, 5, 3, 3, 3, 1, 128, 240, 240, 235,,,, -5, 6, 1, 5, 3, 3, 3, 1, 256, 240, 240, 235,,,, -5, 6, 1, 5, 3, 3, 3, 1, 384, 240, 240, 235,,,, -5, 6, 1, 5, 3, 3, 3, 2, 128, 240, 240, 235,,,, -5, 6, 1, 5, 3, 3, 3, 2, 256, 240, 240, 235,,,, -5, 6, 1, 5, 3, 3, 3, 2, 384, 240, 240, 235,,,, -5, 6, 1, 5, 3, 3, 3, 3, 128, 240, 240, 235,,,, -5, 6, 1, 5, 3, 3, 3, 3, 256, 240, 240, 235,,,, -5, 6, 1, 5, 3, 3, 3, 3, 384, 240, 240, 235,,,, -5, 6, 1, 6, 1, 1, 1, 1, 128, 240, 240, 240,,,, -5, 6, 1, 6, 1, 1, 1, 1, 256, 240, 240, 240,,,, -5, 6, 1, 6, 1, 1, 1, 1, 384, 240, 240, 240,,,, -5, 6, 1, 6, 2, 2, 1, 1, 128, 240, 240, 240,,,, -5, 6, 1, 6, 2, 2, 1, 1, 256, 240, 240, 240,,,, -5, 6, 1, 6, 2, 2, 1, 1, 384, 240, 240, 240,,,, -5, 6, 1, 6, 2, 2, 1, 2, 128, 240, 240, 240,,,, -5, 6, 1, 6, 2, 2, 1, 2, 256, 240, 240, 240,,,, -5, 6, 1, 6, 2, 2, 1, 2, 384, 240, 240, 240,,,, -5, 6, 1, 6, 2, 2, 2, 1, 128, 240, 240, 240,,,, -5, 6, 1, 6, 2, 2, 2, 1, 256, 240, 240, 240,,,, -5, 6, 1, 6, 2, 2, 2, 1, 384, 240, 240, 240,,,, -5, 6, 1, 6, 2, 2, 2, 2, 128, 240, 240, 240,,,, -5, 6, 1, 6, 2, 2, 2, 2, 256, 240, 240, 240,,,, -5, 6, 1, 6, 2, 2, 2, 2, 384, 240, 240, 240,,,, -5, 6, 1, 6, 3, 3, 1, 1, 128, 240, 240, 240,,,, -5, 6, 1, 6, 3, 3, 1, 1, 256, 240, 240, 240,,,, -5, 6, 1, 6, 3, 3, 1, 1, 384, 240, 240, 240,,,, -5, 6, 1, 6, 3, 3, 1, 2, 128, 240, 240, 240,,,, -5, 6, 1, 6, 3, 3, 1, 2, 256, 240, 240, 240,,,, -5, 6, 1, 6, 3, 3, 1, 2, 384, 240, 240, 240,,,, -5, 6, 1, 6, 3, 3, 1, 3, 128, 240, 240, 240,,,, -5, 6, 1, 6, 3, 3, 1, 3, 256, 240, 240, 240,,,, -5, 6, 1, 6, 3, 3, 1, 3, 384, 240, 240, 240,,,, -5, 6, 1, 6, 3, 3, 2, 1, 128, 240, 240, 240,,,, -5, 6, 1, 6, 3, 3, 2, 1, 256, 240, 240, 240,,,, -5, 6, 1, 6, 3, 3, 2, 1, 384, 240, 240, 240,,,, -5, 6, 1, 6, 3, 3, 2, 2, 128, 240, 240, 240,,,, -5, 6, 1, 6, 3, 3, 2, 2, 256, 240, 240, 240,,,, -5, 6, 1, 6, 3, 3, 2, 2, 384, 240, 240, 240,,,, -5, 6, 1, 6, 3, 3, 2, 3, 128, 240, 240, 240,,,, -5, 6, 1, 6, 3, 3, 2, 3, 256, 240, 240, 240,,,, -5, 6, 1, 6, 3, 3, 2, 3, 384, 240, 240, 240,,,, -5, 6, 1, 6, 3, 3, 3, 1, 128, 240, 240, 240,,,, -5, 6, 1, 6, 3, 3, 3, 1, 256, 240, 240, 240,,,, -5, 6, 1, 6, 3, 3, 3, 1, 384, 240, 240, 240,,,, -5, 6, 1, 6, 3, 3, 3, 2, 128, 240, 240, 240,,,, -5, 6, 1, 6, 3, 3, 3, 2, 256, 240, 240, 240,,,, -5, 6, 1, 6, 3, 3, 3, 2, 384, 240, 240, 240,,,, -5, 6, 1, 6, 3, 3, 3, 3, 128, 240, 240, 240,,,, -5, 6, 1, 6, 3, 3, 3, 3, 256, 240, 240, 240,,,, -5, 6, 1, 6, 3, 3, 3, 3, 384, 240, 240, 240,,,, -5, 6, 2, 1, 1, 1, 1, 1, 128, 81, 81, 56,,,, -5, 6, 2, 1, 1, 1, 1, 1, 256, 81, 81, 56,,,, -5, 6, 2, 1, 1, 1, 1, 1, 384, 81, 81, 56,,,, -5, 6, 2, 1, 2, 2, 1, 1, 128, 81, 75, 53,,,, -5, 6, 2, 1, 2, 2, 1, 1, 256, 81, 75, 53,,,, -5, 6, 2, 1, 2, 2, 1, 1, 384, 81, 75, 53,,,, -5, 6, 2, 1, 2, 2, 1, 2, 128, 81, 75, 53,,,, -5, 6, 2, 1, 2, 2, 1, 2, 256, 81, 75, 53,,,, -5, 6, 2, 1, 2, 2, 1, 2, 384, 81, 75, 53,,,, -5, 6, 2, 1, 2, 2, 2, 1, 128, 81, 75, 53,,,, -5, 6, 2, 1, 2, 2, 2, 1, 256, 81, 75, 53,,,, -5, 6, 2, 1, 2, 2, 2, 1, 384, 81, 75, 53,,,, -5, 6, 2, 1, 2, 2, 2, 2, 128, 81, 75, 53,,,, -5, 6, 2, 1, 2, 2, 2, 2, 256, 81, 75, 53,,,, -5, 6, 2, 1, 2, 2, 2, 2, 384, 81, 75, 53,,,, -5, 6, 2, 1, 3, 3, 1, 1, 128, 81, 72, 51,,,, -5, 6, 2, 1, 3, 3, 1, 1, 256, 81, 72, 51,,,, -5, 6, 2, 1, 3, 3, 1, 1, 384, 81, 72, 51,,,, -5, 6, 2, 1, 3, 3, 1, 2, 128, 81, 72, 51,,,, -5, 6, 2, 1, 3, 3, 1, 2, 256, 81, 72, 51,,,, -5, 6, 2, 1, 3, 3, 1, 2, 384, 81, 72, 51,,,, -5, 6, 2, 1, 3, 3, 1, 3, 128, 81, 72, 51,,,, -5, 6, 2, 1, 3, 3, 1, 3, 256, 81, 72, 51,,,, -5, 6, 2, 1, 3, 3, 1, 3, 384, 81, 72, 51,,,, -5, 6, 2, 1, 3, 3, 2, 1, 128, 81, 72, 51,,,, -5, 6, 2, 1, 3, 3, 2, 1, 256, 81, 72, 51,,,, -5, 6, 2, 1, 3, 3, 2, 1, 384, 81, 72, 51,,,, -5, 6, 2, 1, 3, 3, 2, 2, 128, 81, 72, 51,,,, -5, 6, 2, 1, 3, 3, 2, 2, 256, 81, 72, 51,,,, -5, 6, 2, 1, 3, 3, 2, 2, 384, 81, 72, 51,,,, -5, 6, 2, 1, 3, 3, 2, 3, 128, 81, 72, 51,,,, -5, 6, 2, 1, 3, 3, 2, 3, 256, 81, 72, 51,,,, -5, 6, 2, 1, 3, 3, 2, 3, 384, 81, 72, 51,,,, -5, 6, 2, 1, 3, 3, 3, 1, 128, 81, 72, 51,,,, -5, 6, 2, 1, 3, 3, 3, 1, 256, 81, 72, 51,,,, -5, 6, 2, 1, 3, 3, 3, 1, 384, 81, 72, 51,,,, -5, 6, 2, 1, 3, 3, 3, 2, 128, 81, 72, 51,,,, -5, 6, 2, 1, 3, 3, 3, 2, 256, 81, 72, 51,,,, -5, 6, 2, 1, 3, 3, 3, 2, 384, 81, 72, 51,,,, -5, 6, 2, 1, 3, 3, 3, 3, 128, 81, 72, 51,,,, -5, 6, 2, 1, 3, 3, 3, 3, 256, 81, 72, 51,,,, -5, 6, 2, 1, 3, 3, 3, 3, 384, 81, 72, 51,,,, -5, 6, 2, 2, 1, 1, 1, 1, 128, 157, 157, 107,,,, -5, 6, 2, 2, 1, 1, 1, 1, 256, 157, 157, 107,,,, -5, 6, 2, 2, 1, 1, 1, 1, 384, 157, 157, 107,,,, -5, 6, 2, 2, 2, 2, 1, 1, 128, 157, 145, 101,,,, -5, 6, 2, 2, 2, 2, 1, 1, 256, 157, 145, 101,,,, -5, 6, 2, 2, 2, 2, 1, 1, 384, 157, 145, 101,,,, -5, 6, 2, 2, 2, 2, 1, 2, 128, 157, 145, 101,,,, -5, 6, 2, 2, 2, 2, 1, 2, 256, 157, 145, 101,,,, -5, 6, 2, 2, 2, 2, 1, 2, 384, 157, 145, 101,,,, -5, 6, 2, 2, 2, 2, 2, 1, 128, 157, 145, 101,,,, -5, 6, 2, 2, 2, 2, 2, 1, 256, 157, 145, 101,,,, -5, 6, 2, 2, 2, 2, 2, 1, 384, 157, 145, 101,,,, -5, 6, 2, 2, 2, 2, 2, 2, 128, 157, 145, 101,,,, -5, 6, 2, 2, 2, 2, 2, 2, 256, 157, 145, 101,,,, -5, 6, 2, 2, 2, 2, 2, 2, 384, 157, 145, 101,,,, -5, 6, 2, 2, 3, 3, 1, 1, 128, 157, 139, 97,,,, -5, 6, 2, 2, 3, 3, 1, 1, 256, 157, 139, 97,,,, -5, 6, 2, 2, 3, 3, 1, 1, 384, 157, 139, 97,,,, -5, 6, 2, 2, 3, 3, 1, 2, 128, 157, 139, 97,,,, -5, 6, 2, 2, 3, 3, 1, 2, 256, 157, 139, 97,,,, -5, 6, 2, 2, 3, 3, 1, 2, 384, 157, 139, 97,,,, -5, 6, 2, 2, 3, 3, 1, 3, 128, 157, 139, 97,,,, -5, 6, 2, 2, 3, 3, 1, 3, 256, 157, 139, 97,,,, -5, 6, 2, 2, 3, 3, 1, 3, 384, 157, 139, 97,,,, -5, 6, 2, 2, 3, 3, 2, 1, 128, 157, 139, 97,,,, -5, 6, 2, 2, 3, 3, 2, 1, 256, 157, 139, 97,,,, -5, 6, 2, 2, 3, 3, 2, 1, 384, 157, 139, 97,,,, -5, 6, 2, 2, 3, 3, 2, 2, 128, 157, 139, 97,,,, -5, 6, 2, 2, 3, 3, 2, 2, 256, 157, 139, 97,,,, -5, 6, 2, 2, 3, 3, 2, 2, 384, 157, 139, 97,,,, -5, 6, 2, 2, 3, 3, 2, 3, 128, 157, 139, 97,,,, -5, 6, 2, 2, 3, 3, 2, 3, 256, 157, 139, 97,,,, -5, 6, 2, 2, 3, 3, 2, 3, 384, 157, 139, 97,,,, -5, 6, 2, 2, 3, 3, 3, 1, 128, 157, 139, 97,,,, -5, 6, 2, 2, 3, 3, 3, 1, 256, 157, 139, 97,,,, -5, 6, 2, 2, 3, 3, 3, 1, 384, 157, 139, 97,,,, -5, 6, 2, 2, 3, 3, 3, 2, 128, 157, 139, 97,,,, -5, 6, 2, 2, 3, 3, 3, 2, 256, 157, 139, 97,,,, -5, 6, 2, 2, 3, 3, 3, 2, 384, 157, 139, 97,,,, -5, 6, 2, 2, 3, 3, 3, 3, 128, 157, 139, 97,,,, -5, 6, 2, 2, 3, 3, 3, 3, 256, 157, 139, 97,,,, -5, 6, 2, 2, 3, 3, 3, 3, 384, 157, 139, 97,,,, -5, 6, 2, 3, 1, 1, 1, 1, 128, 233, 233, 158,,,, -5, 6, 2, 3, 1, 1, 1, 1, 256, 233, 233, 158,,,, -5, 6, 2, 3, 1, 1, 1, 1, 384, 233, 233, 158,,,, -5, 6, 2, 3, 2, 2, 1, 1, 128, 233, 215, 149,,,, -5, 6, 2, 3, 2, 2, 1, 1, 256, 233, 215, 149,,,, -5, 6, 2, 3, 2, 2, 1, 1, 384, 233, 215, 149,,,, -5, 6, 2, 3, 2, 2, 1, 2, 128, 233, 215, 149,,,, -5, 6, 2, 3, 2, 2, 1, 2, 256, 233, 215, 149,,,, -5, 6, 2, 3, 2, 2, 1, 2, 384, 233, 215, 149,,,, -5, 6, 2, 3, 2, 2, 2, 1, 128, 233, 215, 149,,,, -5, 6, 2, 3, 2, 2, 2, 1, 256, 233, 215, 149,,,, -5, 6, 2, 3, 2, 2, 2, 1, 384, 233, 215, 149,,,, -5, 6, 2, 3, 2, 2, 2, 2, 128, 233, 215, 149,,,, -5, 6, 2, 3, 2, 2, 2, 2, 256, 233, 215, 149,,,, -5, 6, 2, 3, 2, 2, 2, 2, 384, 233, 215, 149,,,, -5, 6, 2, 3, 3, 3, 1, 1, 128, 233, 206, 143,,,, -5, 6, 2, 3, 3, 3, 1, 1, 256, 233, 206, 143,,,, -5, 6, 2, 3, 3, 3, 1, 1, 384, 233, 206, 143,,,, -5, 6, 2, 3, 3, 3, 1, 2, 128, 233, 206, 143,,,, -5, 6, 2, 3, 3, 3, 1, 2, 256, 233, 206, 143,,,, -5, 6, 2, 3, 3, 3, 1, 2, 384, 233, 206, 143,,,, -5, 6, 2, 3, 3, 3, 1, 3, 128, 233, 206, 143,,,, -5, 6, 2, 3, 3, 3, 1, 3, 256, 233, 206, 143,,,, -5, 6, 2, 3, 3, 3, 1, 3, 384, 233, 206, 143,,,, -5, 6, 2, 3, 3, 3, 2, 1, 128, 233, 206, 143,,,, -5, 6, 2, 3, 3, 3, 2, 1, 256, 233, 206, 143,,,, -5, 6, 2, 3, 3, 3, 2, 1, 384, 233, 206, 143,,,, -5, 6, 2, 3, 3, 3, 2, 2, 128, 233, 206, 143,,,, -5, 6, 2, 3, 3, 3, 2, 2, 256, 233, 206, 143,,,, -5, 6, 2, 3, 3, 3, 2, 2, 384, 233, 206, 143,,,, -5, 6, 2, 3, 3, 3, 2, 3, 128, 233, 206, 143,,,, -5, 6, 2, 3, 3, 3, 2, 3, 256, 233, 206, 143,,,, -5, 6, 2, 3, 3, 3, 2, 3, 384, 233, 206, 143,,,, -5, 6, 2, 3, 3, 3, 3, 1, 128, 233, 206, 143,,,, -5, 6, 2, 3, 3, 3, 3, 1, 256, 233, 206, 143,,,, -5, 6, 2, 3, 3, 3, 3, 1, 384, 233, 206, 143,,,, -5, 6, 2, 3, 3, 3, 3, 2, 128, 233, 206, 143,,,, -5, 6, 2, 3, 3, 3, 3, 2, 256, 233, 206, 143,,,, -5, 6, 2, 3, 3, 3, 3, 2, 384, 233, 206, 143,,,, -5, 6, 2, 3, 3, 3, 3, 3, 128, 233, 206, 143,,,, -5, 6, 2, 3, 3, 3, 3, 3, 256, 233, 206, 143,,,, -5, 6, 2, 3, 3, 3, 3, 3, 384, 233, 206, 143,,,, -5, 6, 2, 4, 1, 1, 1, 1, 128, 240, 240, 209,,,, -5, 6, 2, 4, 1, 1, 1, 1, 256, 240, 240, 209,,,, -5, 6, 2, 4, 1, 1, 1, 1, 384, 240, 240, 209,,,, -5, 6, 2, 4, 2, 2, 1, 1, 128, 240, 240, 197,,,, -5, 6, 2, 4, 2, 2, 1, 1, 256, 240, 240, 197,,,, -5, 6, 2, 4, 2, 2, 1, 1, 384, 240, 240, 197,,,, -5, 6, 2, 4, 2, 2, 1, 2, 128, 240, 240, 197,,,, -5, 6, 2, 4, 2, 2, 1, 2, 256, 240, 240, 197,,,, -5, 6, 2, 4, 2, 2, 1, 2, 384, 240, 240, 197,,,, -5, 6, 2, 4, 2, 2, 2, 1, 128, 240, 240, 197,,,, -5, 6, 2, 4, 2, 2, 2, 1, 256, 240, 240, 197,,,, -5, 6, 2, 4, 2, 2, 2, 1, 384, 240, 240, 197,,,, -5, 6, 2, 4, 2, 2, 2, 2, 128, 240, 240, 197,,,, -5, 6, 2, 4, 2, 2, 2, 2, 256, 240, 240, 197,,,, -5, 6, 2, 4, 2, 2, 2, 2, 384, 240, 240, 197,,,, -5, 6, 2, 4, 3, 3, 1, 1, 128, 240, 240, 189,,,, -5, 6, 2, 4, 3, 3, 1, 1, 256, 240, 240, 189,,,, -5, 6, 2, 4, 3, 3, 1, 1, 384, 240, 240, 189,,,, -5, 6, 2, 4, 3, 3, 1, 2, 128, 240, 240, 189,,,, -5, 6, 2, 4, 3, 3, 1, 2, 256, 240, 240, 189,,,, -5, 6, 2, 4, 3, 3, 1, 2, 384, 240, 240, 189,,,, -5, 6, 2, 4, 3, 3, 1, 3, 128, 240, 240, 189,,,, -5, 6, 2, 4, 3, 3, 1, 3, 256, 240, 240, 189,,,, -5, 6, 2, 4, 3, 3, 1, 3, 384, 240, 240, 189,,,, -5, 6, 2, 4, 3, 3, 2, 1, 128, 240, 240, 189,,,, -5, 6, 2, 4, 3, 3, 2, 1, 256, 240, 240, 189,,,, -5, 6, 2, 4, 3, 3, 2, 1, 384, 240, 240, 189,,,, -5, 6, 2, 4, 3, 3, 2, 2, 128, 240, 240, 189,,,, -5, 6, 2, 4, 3, 3, 2, 2, 256, 240, 240, 189,,,, -5, 6, 2, 4, 3, 3, 2, 2, 384, 240, 240, 189,,,, -5, 6, 2, 4, 3, 3, 2, 3, 128, 240, 240, 189,,,, -5, 6, 2, 4, 3, 3, 2, 3, 256, 240, 240, 189,,,, -5, 6, 2, 4, 3, 3, 2, 3, 384, 240, 240, 189,,,, -5, 6, 2, 4, 3, 3, 3, 1, 128, 240, 240, 189,,,, -5, 6, 2, 4, 3, 3, 3, 1, 256, 240, 240, 189,,,, -5, 6, 2, 4, 3, 3, 3, 1, 384, 240, 240, 189,,,, -5, 6, 2, 4, 3, 3, 3, 2, 128, 240, 240, 189,,,, -5, 6, 2, 4, 3, 3, 3, 2, 256, 240, 240, 189,,,, -5, 6, 2, 4, 3, 3, 3, 2, 384, 240, 240, 189,,,, -5, 6, 2, 4, 3, 3, 3, 3, 128, 240, 240, 189,,,, -5, 6, 2, 4, 3, 3, 3, 3, 256, 240, 240, 189,,,, -5, 6, 2, 4, 3, 3, 3, 3, 384, 240, 240, 189,,,, -5, 6, 2, 5, 1, 1, 1, 1, 128, 240, 240, 240,,,, -5, 6, 2, 5, 1, 1, 1, 1, 256, 240, 240, 240,,,, -5, 6, 2, 5, 1, 1, 1, 1, 384, 240, 240, 240,,,, -5, 6, 2, 5, 2, 2, 1, 1, 128, 240, 240, 240,,,, -5, 6, 2, 5, 2, 2, 1, 1, 256, 240, 240, 240,,,, -5, 6, 2, 5, 2, 2, 1, 1, 384, 240, 240, 240,,,, -5, 6, 2, 5, 2, 2, 1, 2, 128, 240, 240, 240,,,, -5, 6, 2, 5, 2, 2, 1, 2, 256, 240, 240, 240,,,, -5, 6, 2, 5, 2, 2, 1, 2, 384, 240, 240, 240,,,, -5, 6, 2, 5, 2, 2, 2, 1, 128, 240, 240, 240,,,, -5, 6, 2, 5, 2, 2, 2, 1, 256, 240, 240, 240,,,, -5, 6, 2, 5, 2, 2, 2, 1, 384, 240, 240, 240,,,, -5, 6, 2, 5, 2, 2, 2, 2, 128, 240, 240, 240,,,, -5, 6, 2, 5, 2, 2, 2, 2, 256, 240, 240, 240,,,, -5, 6, 2, 5, 2, 2, 2, 2, 384, 240, 240, 240,,,, -5, 6, 2, 5, 3, 3, 1, 1, 128, 240, 240, 235,,,, -5, 6, 2, 5, 3, 3, 1, 1, 256, 240, 240, 235,,,, -5, 6, 2, 5, 3, 3, 1, 1, 384, 240, 240, 235,,,, -5, 6, 2, 5, 3, 3, 1, 2, 128, 240, 240, 235,,,, -5, 6, 2, 5, 3, 3, 1, 2, 256, 240, 240, 235,,,, -5, 6, 2, 5, 3, 3, 1, 2, 384, 240, 240, 235,,,, -5, 6, 2, 5, 3, 3, 1, 3, 128, 240, 240, 235,,,, -5, 6, 2, 5, 3, 3, 1, 3, 256, 240, 240, 235,,,, -5, 6, 2, 5, 3, 3, 1, 3, 384, 240, 240, 235,,,, -5, 6, 2, 5, 3, 3, 2, 1, 128, 240, 240, 235,,,, -5, 6, 2, 5, 3, 3, 2, 1, 256, 240, 240, 235,,,, -5, 6, 2, 5, 3, 3, 2, 1, 384, 240, 240, 235,,,, -5, 6, 2, 5, 3, 3, 2, 2, 128, 240, 240, 235,,,, -5, 6, 2, 5, 3, 3, 2, 2, 256, 240, 240, 235,,,, -5, 6, 2, 5, 3, 3, 2, 2, 384, 240, 240, 235,,,, -5, 6, 2, 5, 3, 3, 2, 3, 128, 240, 240, 235,,,, -5, 6, 2, 5, 3, 3, 2, 3, 256, 240, 240, 235,,,, -5, 6, 2, 5, 3, 3, 2, 3, 384, 240, 240, 235,,,, -5, 6, 2, 5, 3, 3, 3, 1, 128, 240, 240, 235,,,, -5, 6, 2, 5, 3, 3, 3, 1, 256, 240, 240, 235,,,, -5, 6, 2, 5, 3, 3, 3, 1, 384, 240, 240, 235,,,, -5, 6, 2, 5, 3, 3, 3, 2, 128, 240, 240, 235,,,, -5, 6, 2, 5, 3, 3, 3, 2, 256, 240, 240, 235,,,, -5, 6, 2, 5, 3, 3, 3, 2, 384, 240, 240, 235,,,, -5, 6, 2, 5, 3, 3, 3, 3, 128, 240, 240, 235,,,, -5, 6, 2, 5, 3, 3, 3, 3, 256, 240, 240, 235,,,, -5, 6, 2, 5, 3, 3, 3, 3, 384, 240, 240, 235,,,, -5, 6, 2, 6, 1, 1, 1, 1, 128, 240, 240, 240,,,, -5, 6, 2, 6, 1, 1, 1, 1, 256, 240, 240, 240,,,, -5, 6, 2, 6, 1, 1, 1, 1, 384, 240, 240, 240,,,, -5, 6, 2, 6, 2, 2, 1, 1, 128, 240, 240, 240,,,, -5, 6, 2, 6, 2, 2, 1, 1, 256, 240, 240, 240,,,, -5, 6, 2, 6, 2, 2, 1, 1, 384, 240, 240, 240,,,, -5, 6, 2, 6, 2, 2, 1, 2, 128, 240, 240, 240,,,, -5, 6, 2, 6, 2, 2, 1, 2, 256, 240, 240, 240,,,, -5, 6, 2, 6, 2, 2, 1, 2, 384, 240, 240, 240,,,, -5, 6, 2, 6, 2, 2, 2, 1, 128, 240, 240, 240,,,, -5, 6, 2, 6, 2, 2, 2, 1, 256, 240, 240, 240,,,, -5, 6, 2, 6, 2, 2, 2, 1, 384, 240, 240, 240,,,, -5, 6, 2, 6, 2, 2, 2, 2, 128, 240, 240, 240,,,, -5, 6, 2, 6, 2, 2, 2, 2, 256, 240, 240, 240,,,, -5, 6, 2, 6, 2, 2, 2, 2, 384, 240, 240, 240,,,, -5, 6, 2, 6, 3, 3, 1, 1, 128, 240, 240, 240,,,, -5, 6, 2, 6, 3, 3, 1, 1, 256, 240, 240, 240,,,, -5, 6, 2, 6, 3, 3, 1, 1, 384, 240, 240, 240,,,, -5, 6, 2, 6, 3, 3, 1, 2, 128, 240, 240, 240,,,, -5, 6, 2, 6, 3, 3, 1, 2, 256, 240, 240, 240,,,, -5, 6, 2, 6, 3, 3, 1, 2, 384, 240, 240, 240,,,, -5, 6, 2, 6, 3, 3, 1, 3, 128, 240, 240, 240,,,, -5, 6, 2, 6, 3, 3, 1, 3, 256, 240, 240, 240,,,, -5, 6, 2, 6, 3, 3, 1, 3, 384, 240, 240, 240,,,, -5, 6, 2, 6, 3, 3, 2, 1, 128, 240, 240, 240,,,, -5, 6, 2, 6, 3, 3, 2, 1, 256, 240, 240, 240,,,, -5, 6, 2, 6, 3, 3, 2, 1, 384, 240, 240, 240,,,, -5, 6, 2, 6, 3, 3, 2, 2, 128, 240, 240, 240,,,, -5, 6, 2, 6, 3, 3, 2, 2, 256, 240, 240, 240,,,, -5, 6, 2, 6, 3, 3, 2, 2, 384, 240, 240, 240,,,, -5, 6, 2, 6, 3, 3, 2, 3, 128, 240, 240, 240,,,, -5, 6, 2, 6, 3, 3, 2, 3, 256, 240, 240, 240,,,, -5, 6, 2, 6, 3, 3, 2, 3, 384, 240, 240, 240,,,, -5, 6, 2, 6, 3, 3, 3, 1, 128, 240, 240, 240,,,, -5, 6, 2, 6, 3, 3, 3, 1, 256, 240, 240, 240,,,, -5, 6, 2, 6, 3, 3, 3, 1, 384, 240, 240, 240,,,, -5, 6, 2, 6, 3, 3, 3, 2, 128, 240, 240, 240,,,, -5, 6, 2, 6, 3, 3, 3, 2, 256, 240, 240, 240,,,, -5, 6, 2, 6, 3, 3, 3, 2, 384, 240, 240, 240,,,, -5, 6, 2, 6, 3, 3, 3, 3, 128, 240, 240, 240,,,, -5, 6, 2, 6, 3, 3, 3, 3, 256, 240, 240, 240,,,, -5, 6, 2, 6, 3, 3, 3, 3, 384, 240, 240, 240,,,, -5, 6, 3, 1, 1, 1, 1, 1, 128, 81, 81, 56,,,, -5, 6, 3, 1, 1, 1, 1, 1, 256, 81, 81, 56,,,, -5, 6, 3, 1, 1, 1, 1, 1, 384, 81, 81, 56,,,, -5, 6, 3, 1, 2, 2, 1, 1, 128, 81, 75, 53,,,, -5, 6, 3, 1, 2, 2, 1, 1, 256, 81, 75, 53,,,, -5, 6, 3, 1, 2, 2, 1, 1, 384, 81, 75, 53,,,, -5, 6, 3, 1, 2, 2, 1, 2, 128, 81, 75, 53,,,, -5, 6, 3, 1, 2, 2, 1, 2, 256, 81, 75, 53,,,, -5, 6, 3, 1, 2, 2, 1, 2, 384, 81, 75, 53,,,, -5, 6, 3, 1, 2, 2, 2, 1, 128, 81, 75, 53,,,, -5, 6, 3, 1, 2, 2, 2, 1, 256, 81, 75, 53,,,, -5, 6, 3, 1, 2, 2, 2, 1, 384, 81, 75, 53,,,, -5, 6, 3, 1, 2, 2, 2, 2, 128, 81, 75, 53,,,, -5, 6, 3, 1, 2, 2, 2, 2, 256, 81, 75, 53,,,, -5, 6, 3, 1, 2, 2, 2, 2, 384, 81, 75, 53,,,, -5, 6, 3, 1, 3, 3, 1, 1, 128, 81, 72, 51,,,, -5, 6, 3, 1, 3, 3, 1, 1, 256, 81, 72, 51,,,, -5, 6, 3, 1, 3, 3, 1, 1, 384, 81, 72, 51,,,, -5, 6, 3, 1, 3, 3, 1, 2, 128, 81, 72, 51,,,, -5, 6, 3, 1, 3, 3, 1, 2, 256, 81, 72, 51,,,, -5, 6, 3, 1, 3, 3, 1, 2, 384, 81, 72, 51,,,, -5, 6, 3, 1, 3, 3, 1, 3, 128, 81, 72, 51,,,, -5, 6, 3, 1, 3, 3, 1, 3, 256, 81, 72, 51,,,, -5, 6, 3, 1, 3, 3, 1, 3, 384, 81, 72, 51,,,, -5, 6, 3, 1, 3, 3, 2, 1, 128, 81, 72, 51,,,, -5, 6, 3, 1, 3, 3, 2, 1, 256, 81, 72, 51,,,, -5, 6, 3, 1, 3, 3, 2, 1, 384, 81, 72, 51,,,, -5, 6, 3, 1, 3, 3, 2, 2, 128, 81, 72, 51,,,, -5, 6, 3, 1, 3, 3, 2, 2, 256, 81, 72, 51,,,, -5, 6, 3, 1, 3, 3, 2, 2, 384, 81, 72, 51,,,, -5, 6, 3, 1, 3, 3, 2, 3, 128, 81, 72, 51,,,, -5, 6, 3, 1, 3, 3, 2, 3, 256, 81, 72, 51,,,, -5, 6, 3, 1, 3, 3, 2, 3, 384, 81, 72, 51,,,, -5, 6, 3, 1, 3, 3, 3, 1, 128, 81, 72, 51,,,, -5, 6, 3, 1, 3, 3, 3, 1, 256, 81, 72, 51,,,, -5, 6, 3, 1, 3, 3, 3, 1, 384, 81, 72, 51,,,, -5, 6, 3, 1, 3, 3, 3, 2, 128, 81, 72, 51,,,, -5, 6, 3, 1, 3, 3, 3, 2, 256, 81, 72, 51,,,, -5, 6, 3, 1, 3, 3, 3, 2, 384, 81, 72, 51,,,, -5, 6, 3, 1, 3, 3, 3, 3, 128, 81, 72, 51,,,, -5, 6, 3, 1, 3, 3, 3, 3, 256, 81, 72, 51,,,, -5, 6, 3, 1, 3, 3, 3, 3, 384, 81, 72, 51,,,, -5, 6, 3, 2, 1, 1, 1, 1, 128, 157, 157, 107,,,, -5, 6, 3, 2, 1, 1, 1, 1, 256, 157, 157, 107,,,, -5, 6, 3, 2, 1, 1, 1, 1, 384, 157, 157, 107,,,, -5, 6, 3, 2, 2, 2, 1, 1, 128, 157, 145, 101,,,, -5, 6, 3, 2, 2, 2, 1, 1, 256, 157, 145, 101,,,, -5, 6, 3, 2, 2, 2, 1, 1, 384, 157, 145, 101,,,, -5, 6, 3, 2, 2, 2, 1, 2, 128, 157, 145, 101,,,, -5, 6, 3, 2, 2, 2, 1, 2, 256, 157, 145, 101,,,, -5, 6, 3, 2, 2, 2, 1, 2, 384, 157, 145, 101,,,, -5, 6, 3, 2, 2, 2, 2, 1, 128, 157, 145, 101,,,, -5, 6, 3, 2, 2, 2, 2, 1, 256, 157, 145, 101,,,, -5, 6, 3, 2, 2, 2, 2, 1, 384, 157, 145, 101,,,, -5, 6, 3, 2, 2, 2, 2, 2, 128, 157, 145, 101,,,, -5, 6, 3, 2, 2, 2, 2, 2, 256, 157, 145, 101,,,, -5, 6, 3, 2, 2, 2, 2, 2, 384, 157, 145, 101,,,, -5, 6, 3, 2, 3, 3, 1, 1, 128, 157, 139, 97,,,, -5, 6, 3, 2, 3, 3, 1, 1, 256, 157, 139, 97,,,, -5, 6, 3, 2, 3, 3, 1, 1, 384, 157, 139, 97,,,, -5, 6, 3, 2, 3, 3, 1, 2, 128, 157, 139, 97,,,, -5, 6, 3, 2, 3, 3, 1, 2, 256, 157, 139, 97,,,, -5, 6, 3, 2, 3, 3, 1, 2, 384, 157, 139, 97,,,, -5, 6, 3, 2, 3, 3, 1, 3, 128, 157, 139, 97,,,, -5, 6, 3, 2, 3, 3, 1, 3, 256, 157, 139, 97,,,, -5, 6, 3, 2, 3, 3, 1, 3, 384, 157, 139, 97,,,, -5, 6, 3, 2, 3, 3, 2, 1, 128, 157, 139, 97,,,, -5, 6, 3, 2, 3, 3, 2, 1, 256, 157, 139, 97,,,, -5, 6, 3, 2, 3, 3, 2, 1, 384, 157, 139, 97,,,, -5, 6, 3, 2, 3, 3, 2, 2, 128, 157, 139, 97,,,, -5, 6, 3, 2, 3, 3, 2, 2, 256, 157, 139, 97,,,, -5, 6, 3, 2, 3, 3, 2, 2, 384, 157, 139, 97,,,, -5, 6, 3, 2, 3, 3, 2, 3, 128, 157, 139, 97,,,, -5, 6, 3, 2, 3, 3, 2, 3, 256, 157, 139, 97,,,, -5, 6, 3, 2, 3, 3, 2, 3, 384, 157, 139, 97,,,, -5, 6, 3, 2, 3, 3, 3, 1, 128, 157, 139, 97,,,, -5, 6, 3, 2, 3, 3, 3, 1, 256, 157, 139, 97,,,, -5, 6, 3, 2, 3, 3, 3, 1, 384, 157, 139, 97,,,, -5, 6, 3, 2, 3, 3, 3, 2, 128, 157, 139, 97,,,, -5, 6, 3, 2, 3, 3, 3, 2, 256, 157, 139, 97,,,, -5, 6, 3, 2, 3, 3, 3, 2, 384, 157, 139, 97,,,, -5, 6, 3, 2, 3, 3, 3, 3, 128, 157, 139, 97,,,, -5, 6, 3, 2, 3, 3, 3, 3, 256, 157, 139, 97,,,, -5, 6, 3, 2, 3, 3, 3, 3, 384, 157, 139, 97,,,, -5, 6, 3, 3, 1, 1, 1, 1, 128, 233, 233, 158,,,, -5, 6, 3, 3, 1, 1, 1, 1, 256, 233, 233, 158,,,, -5, 6, 3, 3, 1, 1, 1, 1, 384, 233, 233, 158,,,, -5, 6, 3, 3, 2, 2, 1, 1, 128, 233, 215, 149,,,, -5, 6, 3, 3, 2, 2, 1, 1, 256, 233, 215, 149,,,, -5, 6, 3, 3, 2, 2, 1, 1, 384, 233, 215, 149,,,, -5, 6, 3, 3, 2, 2, 1, 2, 128, 233, 215, 149,,,, -5, 6, 3, 3, 2, 2, 1, 2, 256, 233, 215, 149,,,, -5, 6, 3, 3, 2, 2, 1, 2, 384, 233, 215, 149,,,, -5, 6, 3, 3, 2, 2, 2, 1, 128, 233, 215, 149,,,, -5, 6, 3, 3, 2, 2, 2, 1, 256, 233, 215, 149,,,, -5, 6, 3, 3, 2, 2, 2, 1, 384, 233, 215, 149,,,, -5, 6, 3, 3, 2, 2, 2, 2, 128, 233, 215, 149,,,, -5, 6, 3, 3, 2, 2, 2, 2, 256, 233, 215, 149,,,, -5, 6, 3, 3, 2, 2, 2, 2, 384, 233, 215, 149,,,, -5, 6, 3, 3, 3, 3, 1, 1, 128, 233, 206, 143,,,, -5, 6, 3, 3, 3, 3, 1, 1, 256, 233, 206, 143,,,, -5, 6, 3, 3, 3, 3, 1, 1, 384, 233, 206, 143,,,, -5, 6, 3, 3, 3, 3, 1, 2, 128, 233, 206, 143,,,, -5, 6, 3, 3, 3, 3, 1, 2, 256, 233, 206, 143,,,, -5, 6, 3, 3, 3, 3, 1, 2, 384, 233, 206, 143,,,, -5, 6, 3, 3, 3, 3, 1, 3, 128, 233, 206, 143,,,, -5, 6, 3, 3, 3, 3, 1, 3, 256, 233, 206, 143,,,, -5, 6, 3, 3, 3, 3, 1, 3, 384, 233, 206, 143,,,, -5, 6, 3, 3, 3, 3, 2, 1, 128, 233, 206, 143,,,, -5, 6, 3, 3, 3, 3, 2, 1, 256, 233, 206, 143,,,, -5, 6, 3, 3, 3, 3, 2, 1, 384, 233, 206, 143,,,, -5, 6, 3, 3, 3, 3, 2, 2, 128, 233, 206, 143,,,, -5, 6, 3, 3, 3, 3, 2, 2, 256, 233, 206, 143,,,, -5, 6, 3, 3, 3, 3, 2, 2, 384, 233, 206, 143,,,, -5, 6, 3, 3, 3, 3, 2, 3, 128, 233, 206, 143,,,, -5, 6, 3, 3, 3, 3, 2, 3, 256, 233, 206, 143,,,, -5, 6, 3, 3, 3, 3, 2, 3, 384, 233, 206, 143,,,, -5, 6, 3, 3, 3, 3, 3, 1, 128, 233, 206, 143,,,, -5, 6, 3, 3, 3, 3, 3, 1, 256, 233, 206, 143,,,, -5, 6, 3, 3, 3, 3, 3, 1, 384, 233, 206, 143,,,, -5, 6, 3, 3, 3, 3, 3, 2, 128, 233, 206, 143,,,, -5, 6, 3, 3, 3, 3, 3, 2, 256, 233, 206, 143,,,, -5, 6, 3, 3, 3, 3, 3, 2, 384, 233, 206, 143,,,, -5, 6, 3, 3, 3, 3, 3, 3, 128, 233, 206, 143,,,, -5, 6, 3, 3, 3, 3, 3, 3, 256, 233, 206, 143,,,, -5, 6, 3, 3, 3, 3, 3, 3, 384, 233, 206, 143,,,, -5, 6, 3, 4, 1, 1, 1, 1, 128, 240, 240, 209,,,, -5, 6, 3, 4, 1, 1, 1, 1, 256, 240, 240, 209,,,, -5, 6, 3, 4, 1, 1, 1, 1, 384, 240, 240, 209,,,, -5, 6, 3, 4, 2, 2, 1, 1, 128, 240, 240, 197,,,, -5, 6, 3, 4, 2, 2, 1, 1, 256, 240, 240, 197,,,, -5, 6, 3, 4, 2, 2, 1, 1, 384, 240, 240, 197,,,, -5, 6, 3, 4, 2, 2, 1, 2, 128, 240, 240, 197,,,, -5, 6, 3, 4, 2, 2, 1, 2, 256, 240, 240, 197,,,, -5, 6, 3, 4, 2, 2, 1, 2, 384, 240, 240, 197,,,, -5, 6, 3, 4, 2, 2, 2, 1, 128, 240, 240, 197,,,, -5, 6, 3, 4, 2, 2, 2, 1, 256, 240, 240, 197,,,, -5, 6, 3, 4, 2, 2, 2, 1, 384, 240, 240, 197,,,, -5, 6, 3, 4, 2, 2, 2, 2, 128, 240, 240, 197,,,, -5, 6, 3, 4, 2, 2, 2, 2, 256, 240, 240, 197,,,, -5, 6, 3, 4, 2, 2, 2, 2, 384, 240, 240, 197,,,, -5, 6, 3, 4, 3, 3, 1, 1, 128, 240, 240, 189,,,, -5, 6, 3, 4, 3, 3, 1, 1, 256, 240, 240, 189,,,, -5, 6, 3, 4, 3, 3, 1, 1, 384, 240, 240, 189,,,, -5, 6, 3, 4, 3, 3, 1, 2, 128, 240, 240, 189,,,, -5, 6, 3, 4, 3, 3, 1, 2, 256, 240, 240, 189,,,, -5, 6, 3, 4, 3, 3, 1, 2, 384, 240, 240, 189,,,, -5, 6, 3, 4, 3, 3, 1, 3, 128, 240, 240, 189,,,, -5, 6, 3, 4, 3, 3, 1, 3, 256, 240, 240, 189,,,, -5, 6, 3, 4, 3, 3, 1, 3, 384, 240, 240, 189,,,, -5, 6, 3, 4, 3, 3, 2, 1, 128, 240, 240, 189,,,, -5, 6, 3, 4, 3, 3, 2, 1, 256, 240, 240, 189,,,, -5, 6, 3, 4, 3, 3, 2, 1, 384, 240, 240, 189,,,, -5, 6, 3, 4, 3, 3, 2, 2, 128, 240, 240, 189,,,, -5, 6, 3, 4, 3, 3, 2, 2, 256, 240, 240, 189,,,, -5, 6, 3, 4, 3, 3, 2, 2, 384, 240, 240, 189,,,, -5, 6, 3, 4, 3, 3, 2, 3, 128, 240, 240, 189,,,, -5, 6, 3, 4, 3, 3, 2, 3, 256, 240, 240, 189,,,, -5, 6, 3, 4, 3, 3, 2, 3, 384, 240, 240, 189,,,, -5, 6, 3, 4, 3, 3, 3, 1, 128, 240, 240, 189,,,, -5, 6, 3, 4, 3, 3, 3, 1, 256, 240, 240, 189,,,, -5, 6, 3, 4, 3, 3, 3, 1, 384, 240, 240, 189,,,, -5, 6, 3, 4, 3, 3, 3, 2, 128, 240, 240, 189,,,, -5, 6, 3, 4, 3, 3, 3, 2, 256, 240, 240, 189,,,, -5, 6, 3, 4, 3, 3, 3, 2, 384, 240, 240, 189,,,, -5, 6, 3, 4, 3, 3, 3, 3, 128, 240, 240, 189,,,, -5, 6, 3, 4, 3, 3, 3, 3, 256, 240, 240, 189,,,, -5, 6, 3, 4, 3, 3, 3, 3, 384, 240, 240, 189,,,, -5, 6, 3, 5, 1, 1, 1, 1, 128, 240, 240, 240,,,, -5, 6, 3, 5, 1, 1, 1, 1, 256, 240, 240, 240,,,, -5, 6, 3, 5, 1, 1, 1, 1, 384, 240, 240, 240,,,, -5, 6, 3, 5, 2, 2, 1, 1, 128, 240, 240, 240,,,, -5, 6, 3, 5, 2, 2, 1, 1, 256, 240, 240, 240,,,, -5, 6, 3, 5, 2, 2, 1, 1, 384, 240, 240, 240,,,, -5, 6, 3, 5, 2, 2, 1, 2, 128, 240, 240, 240,,,, -5, 6, 3, 5, 2, 2, 1, 2, 256, 240, 240, 240,,,, -5, 6, 3, 5, 2, 2, 1, 2, 384, 240, 240, 240,,,, -5, 6, 3, 5, 2, 2, 2, 1, 128, 240, 240, 240,,,, -5, 6, 3, 5, 2, 2, 2, 1, 256, 240, 240, 240,,,, -5, 6, 3, 5, 2, 2, 2, 1, 384, 240, 240, 240,,,, -5, 6, 3, 5, 2, 2, 2, 2, 128, 240, 240, 240,,,, -5, 6, 3, 5, 2, 2, 2, 2, 256, 240, 240, 240,,,, -5, 6, 3, 5, 2, 2, 2, 2, 384, 240, 240, 240,,,, -5, 6, 3, 5, 3, 3, 1, 1, 128, 240, 240, 235,,,, -5, 6, 3, 5, 3, 3, 1, 1, 256, 240, 240, 235,,,, -5, 6, 3, 5, 3, 3, 1, 1, 384, 240, 240, 235,,,, -5, 6, 3, 5, 3, 3, 1, 2, 128, 240, 240, 235,,,, -5, 6, 3, 5, 3, 3, 1, 2, 256, 240, 240, 235,,,, -5, 6, 3, 5, 3, 3, 1, 2, 384, 240, 240, 235,,,, -5, 6, 3, 5, 3, 3, 1, 3, 128, 240, 240, 235,,,, -5, 6, 3, 5, 3, 3, 1, 3, 256, 240, 240, 235,,,, -5, 6, 3, 5, 3, 3, 1, 3, 384, 240, 240, 235,,,, -5, 6, 3, 5, 3, 3, 2, 1, 128, 240, 240, 235,,,, -5, 6, 3, 5, 3, 3, 2, 1, 256, 240, 240, 235,,,, -5, 6, 3, 5, 3, 3, 2, 1, 384, 240, 240, 235,,,, -5, 6, 3, 5, 3, 3, 2, 2, 128, 240, 240, 235,,,, -5, 6, 3, 5, 3, 3, 2, 2, 256, 240, 240, 235,,,, -5, 6, 3, 5, 3, 3, 2, 2, 384, 240, 240, 235,,,, -5, 6, 3, 5, 3, 3, 2, 3, 128, 240, 240, 235,,,, -5, 6, 3, 5, 3, 3, 2, 3, 256, 240, 240, 235,,,, -5, 6, 3, 5, 3, 3, 2, 3, 384, 240, 240, 235,,,, -5, 6, 3, 5, 3, 3, 3, 1, 128, 240, 240, 235,,,, -5, 6, 3, 5, 3, 3, 3, 1, 256, 240, 240, 235,,,, -5, 6, 3, 5, 3, 3, 3, 1, 384, 240, 240, 235,,,, -5, 6, 3, 5, 3, 3, 3, 2, 128, 240, 240, 235,,,, -5, 6, 3, 5, 3, 3, 3, 2, 256, 240, 240, 235,,,, -5, 6, 3, 5, 3, 3, 3, 2, 384, 240, 240, 235,,,, -5, 6, 3, 5, 3, 3, 3, 3, 128, 240, 240, 235,,,, -5, 6, 3, 5, 3, 3, 3, 3, 256, 240, 240, 235,,,, -5, 6, 3, 5, 3, 3, 3, 3, 384, 240, 240, 235,,,, -5, 6, 3, 6, 1, 1, 1, 1, 128, 240, 240, 240,,,, -5, 6, 3, 6, 1, 1, 1, 1, 256, 240, 240, 240,,,, -5, 6, 3, 6, 1, 1, 1, 1, 384, 240, 240, 240,,,, -5, 6, 3, 6, 2, 2, 1, 1, 128, 240, 240, 240,,,, -5, 6, 3, 6, 2, 2, 1, 1, 256, 240, 240, 240,,,, -5, 6, 3, 6, 2, 2, 1, 1, 384, 240, 240, 240,,,, -5, 6, 3, 6, 2, 2, 1, 2, 128, 240, 240, 240,,,, -5, 6, 3, 6, 2, 2, 1, 2, 256, 240, 240, 240,,,, -5, 6, 3, 6, 2, 2, 1, 2, 384, 240, 240, 240,,,, -5, 6, 3, 6, 2, 2, 2, 1, 128, 240, 240, 240,,,, -5, 6, 3, 6, 2, 2, 2, 1, 256, 240, 240, 240,,,, -5, 6, 3, 6, 2, 2, 2, 1, 384, 240, 240, 240,,,, -5, 6, 3, 6, 2, 2, 2, 2, 128, 240, 240, 240,,,, -5, 6, 3, 6, 2, 2, 2, 2, 256, 240, 240, 240,,,, -5, 6, 3, 6, 2, 2, 2, 2, 384, 240, 240, 240,,,, -5, 6, 3, 6, 3, 3, 1, 1, 128, 240, 240, 240,,,, -5, 6, 3, 6, 3, 3, 1, 1, 256, 240, 240, 240,,,, -5, 6, 3, 6, 3, 3, 1, 1, 384, 240, 240, 240,,,, -5, 6, 3, 6, 3, 3, 1, 2, 128, 240, 240, 240,,,, -5, 6, 3, 6, 3, 3, 1, 2, 256, 240, 240, 240,,,, -5, 6, 3, 6, 3, 3, 1, 2, 384, 240, 240, 240,,,, -5, 6, 3, 6, 3, 3, 1, 3, 128, 240, 240, 240,,,, -5, 6, 3, 6, 3, 3, 1, 3, 256, 240, 240, 240,,,, -5, 6, 3, 6, 3, 3, 1, 3, 384, 240, 240, 240,,,, -5, 6, 3, 6, 3, 3, 2, 1, 128, 240, 240, 240,,,, -5, 6, 3, 6, 3, 3, 2, 1, 256, 240, 240, 240,,,, -5, 6, 3, 6, 3, 3, 2, 1, 384, 240, 240, 240,,,, -5, 6, 3, 6, 3, 3, 2, 2, 128, 240, 240, 240,,,, -5, 6, 3, 6, 3, 3, 2, 2, 256, 240, 240, 240,,,, -5, 6, 3, 6, 3, 3, 2, 2, 384, 240, 240, 240,,,, -5, 6, 3, 6, 3, 3, 2, 3, 128, 240, 240, 240,,,, -5, 6, 3, 6, 3, 3, 2, 3, 256, 240, 240, 240,,,, -5, 6, 3, 6, 3, 3, 2, 3, 384, 240, 240, 240,,,, -5, 6, 3, 6, 3, 3, 3, 1, 128, 240, 240, 240,,,, -5, 6, 3, 6, 3, 3, 3, 1, 256, 240, 240, 240,,,, -5, 6, 3, 6, 3, 3, 3, 1, 384, 240, 240, 240,,,, -5, 6, 3, 6, 3, 3, 3, 2, 128, 240, 240, 240,,,, -5, 6, 3, 6, 3, 3, 3, 2, 256, 240, 240, 240,,,, -5, 6, 3, 6, 3, 3, 3, 2, 384, 240, 240, 240,,,, -5, 6, 3, 6, 3, 3, 3, 3, 128, 240, 240, 240,,,, -5, 6, 3, 6, 3, 3, 3, 3, 256, 240, 240, 240,,,, -5, 6, 3, 6, 3, 3, 3, 3, 384, 240, 240, 240,,,, -5, 6, 4, 1, 1, 1, 1, 1, 128, 81, 81, 56,,,, -5, 6, 4, 1, 1, 1, 1, 1, 256, 81, 81, 56,,,, -5, 6, 4, 1, 1, 1, 1, 1, 384, 81, 81, 56,,,, -5, 6, 4, 1, 2, 2, 1, 1, 128, 81, 75, 53,,,, -5, 6, 4, 1, 2, 2, 1, 1, 256, 81, 75, 53,,,, -5, 6, 4, 1, 2, 2, 1, 1, 384, 81, 75, 53,,,, -5, 6, 4, 1, 2, 2, 1, 2, 128, 81, 75, 53,,,, -5, 6, 4, 1, 2, 2, 1, 2, 256, 81, 75, 53,,,, -5, 6, 4, 1, 2, 2, 1, 2, 384, 81, 75, 53,,,, -5, 6, 4, 1, 2, 2, 2, 1, 128, 81, 75, 53,,,, -5, 6, 4, 1, 2, 2, 2, 1, 256, 81, 75, 53,,,, -5, 6, 4, 1, 2, 2, 2, 1, 384, 81, 75, 53,,,, -5, 6, 4, 1, 2, 2, 2, 2, 128, 81, 75, 53,,,, -5, 6, 4, 1, 2, 2, 2, 2, 256, 81, 75, 53,,,, -5, 6, 4, 1, 2, 2, 2, 2, 384, 81, 75, 53,,,, -5, 6, 4, 1, 3, 3, 1, 1, 128, 81, 72, 51,,,, -5, 6, 4, 1, 3, 3, 1, 1, 256, 81, 72, 51,,,, -5, 6, 4, 1, 3, 3, 1, 1, 384, 81, 72, 51,,,, -5, 6, 4, 1, 3, 3, 1, 2, 128, 81, 72, 51,,,, -5, 6, 4, 1, 3, 3, 1, 2, 256, 81, 72, 51,,,, -5, 6, 4, 1, 3, 3, 1, 2, 384, 81, 72, 51,,,, -5, 6, 4, 1, 3, 3, 1, 3, 128, 81, 72, 51,,,, -5, 6, 4, 1, 3, 3, 1, 3, 256, 81, 72, 51,,,, -5, 6, 4, 1, 3, 3, 1, 3, 384, 81, 72, 51,,,, -5, 6, 4, 1, 3, 3, 2, 1, 128, 81, 72, 51,,,, -5, 6, 4, 1, 3, 3, 2, 1, 256, 81, 72, 51,,,, -5, 6, 4, 1, 3, 3, 2, 1, 384, 81, 72, 51,,,, -5, 6, 4, 1, 3, 3, 2, 2, 128, 81, 72, 51,,,, -5, 6, 4, 1, 3, 3, 2, 2, 256, 81, 72, 51,,,, -5, 6, 4, 1, 3, 3, 2, 2, 384, 81, 72, 51,,,, -5, 6, 4, 1, 3, 3, 2, 3, 128, 81, 72, 51,,,, -5, 6, 4, 1, 3, 3, 2, 3, 256, 81, 72, 51,,,, -5, 6, 4, 1, 3, 3, 2, 3, 384, 81, 72, 51,,,, -5, 6, 4, 1, 3, 3, 3, 1, 128, 81, 72, 51,,,, -5, 6, 4, 1, 3, 3, 3, 1, 256, 81, 72, 51,,,, -5, 6, 4, 1, 3, 3, 3, 1, 384, 81, 72, 51,,,, -5, 6, 4, 1, 3, 3, 3, 2, 128, 81, 72, 51,,,, -5, 6, 4, 1, 3, 3, 3, 2, 256, 81, 72, 51,,,, -5, 6, 4, 1, 3, 3, 3, 2, 384, 81, 72, 51,,,, -5, 6, 4, 1, 3, 3, 3, 3, 128, 81, 72, 51,,,, -5, 6, 4, 1, 3, 3, 3, 3, 256, 81, 72, 51,,,, -5, 6, 4, 1, 3, 3, 3, 3, 384, 81, 72, 51,,,, -5, 6, 4, 2, 1, 1, 1, 1, 128, 157, 157, 107,,,, -5, 6, 4, 2, 1, 1, 1, 1, 256, 157, 157, 107,,,, -5, 6, 4, 2, 1, 1, 1, 1, 384, 157, 157, 107,,,, -5, 6, 4, 2, 2, 2, 1, 1, 128, 157, 145, 101,,,, -5, 6, 4, 2, 2, 2, 1, 1, 256, 157, 145, 101,,,, -5, 6, 4, 2, 2, 2, 1, 1, 384, 157, 145, 101,,,, -5, 6, 4, 2, 2, 2, 1, 2, 128, 157, 145, 101,,,, -5, 6, 4, 2, 2, 2, 1, 2, 256, 157, 145, 101,,,, -5, 6, 4, 2, 2, 2, 1, 2, 384, 157, 145, 101,,,, -5, 6, 4, 2, 2, 2, 2, 1, 128, 157, 145, 101,,,, -5, 6, 4, 2, 2, 2, 2, 1, 256, 157, 145, 101,,,, -5, 6, 4, 2, 2, 2, 2, 1, 384, 157, 145, 101,,,, -5, 6, 4, 2, 2, 2, 2, 2, 128, 157, 145, 101,,,, -5, 6, 4, 2, 2, 2, 2, 2, 256, 157, 145, 101,,,, -5, 6, 4, 2, 2, 2, 2, 2, 384, 157, 145, 101,,,, -5, 6, 4, 2, 3, 3, 1, 1, 128, 157, 139, 97,,,, -5, 6, 4, 2, 3, 3, 1, 1, 256, 157, 139, 97,,,, -5, 6, 4, 2, 3, 3, 1, 1, 384, 157, 139, 97,,,, -5, 6, 4, 2, 3, 3, 1, 2, 128, 157, 139, 97,,,, -5, 6, 4, 2, 3, 3, 1, 2, 256, 157, 139, 97,,,, -5, 6, 4, 2, 3, 3, 1, 2, 384, 157, 139, 97,,,, -5, 6, 4, 2, 3, 3, 1, 3, 128, 157, 139, 97,,,, -5, 6, 4, 2, 3, 3, 1, 3, 256, 157, 139, 97,,,, -5, 6, 4, 2, 3, 3, 1, 3, 384, 157, 139, 97,,,, -5, 6, 4, 2, 3, 3, 2, 1, 128, 157, 139, 97,,,, -5, 6, 4, 2, 3, 3, 2, 1, 256, 157, 139, 97,,,, -5, 6, 4, 2, 3, 3, 2, 1, 384, 157, 139, 97,,,, -5, 6, 4, 2, 3, 3, 2, 2, 128, 157, 139, 97,,,, -5, 6, 4, 2, 3, 3, 2, 2, 256, 157, 139, 97,,,, -5, 6, 4, 2, 3, 3, 2, 2, 384, 157, 139, 97,,,, -5, 6, 4, 2, 3, 3, 2, 3, 128, 157, 139, 97,,,, -5, 6, 4, 2, 3, 3, 2, 3, 256, 157, 139, 97,,,, -5, 6, 4, 2, 3, 3, 2, 3, 384, 157, 139, 97,,,, -5, 6, 4, 2, 3, 3, 3, 1, 128, 157, 139, 97,,,, -5, 6, 4, 2, 3, 3, 3, 1, 256, 157, 139, 97,,,, -5, 6, 4, 2, 3, 3, 3, 1, 384, 157, 139, 97,,,, -5, 6, 4, 2, 3, 3, 3, 2, 128, 157, 139, 97,,,, -5, 6, 4, 2, 3, 3, 3, 2, 256, 157, 139, 97,,,, -5, 6, 4, 2, 3, 3, 3, 2, 384, 157, 139, 97,,,, -5, 6, 4, 2, 3, 3, 3, 3, 128, 157, 139, 97,,,, -5, 6, 4, 2, 3, 3, 3, 3, 256, 157, 139, 97,,,, -5, 6, 4, 2, 3, 3, 3, 3, 384, 157, 139, 97,,,, -5, 6, 4, 3, 1, 1, 1, 1, 128, 233, 233, 158,,,, -5, 6, 4, 3, 1, 1, 1, 1, 256, 233, 233, 158,,,, -5, 6, 4, 3, 1, 1, 1, 1, 384, 233, 233, 158,,,, -5, 6, 4, 3, 2, 2, 1, 1, 128, 233, 215, 149,,,, -5, 6, 4, 3, 2, 2, 1, 1, 256, 233, 215, 149,,,, -5, 6, 4, 3, 2, 2, 1, 1, 384, 233, 215, 149,,,, -5, 6, 4, 3, 2, 2, 1, 2, 128, 233, 215, 149,,,, -5, 6, 4, 3, 2, 2, 1, 2, 256, 233, 215, 149,,,, -5, 6, 4, 3, 2, 2, 1, 2, 384, 233, 215, 149,,,, -5, 6, 4, 3, 2, 2, 2, 1, 128, 233, 215, 149,,,, -5, 6, 4, 3, 2, 2, 2, 1, 256, 233, 215, 149,,,, -5, 6, 4, 3, 2, 2, 2, 1, 384, 233, 215, 149,,,, -5, 6, 4, 3, 2, 2, 2, 2, 128, 233, 215, 149,,,, -5, 6, 4, 3, 2, 2, 2, 2, 256, 233, 215, 149,,,, -5, 6, 4, 3, 2, 2, 2, 2, 384, 233, 215, 149,,,, -5, 6, 4, 3, 3, 3, 1, 1, 128, 233, 206, 143,,,, -5, 6, 4, 3, 3, 3, 1, 1, 256, 233, 206, 143,,,, -5, 6, 4, 3, 3, 3, 1, 1, 384, 233, 206, 143,,,, -5, 6, 4, 3, 3, 3, 1, 2, 128, 233, 206, 143,,,, -5, 6, 4, 3, 3, 3, 1, 2, 256, 233, 206, 143,,,, -5, 6, 4, 3, 3, 3, 1, 2, 384, 233, 206, 143,,,, -5, 6, 4, 3, 3, 3, 1, 3, 128, 233, 206, 143,,,, -5, 6, 4, 3, 3, 3, 1, 3, 256, 233, 206, 143,,,, -5, 6, 4, 3, 3, 3, 1, 3, 384, 233, 206, 143,,,, -5, 6, 4, 3, 3, 3, 2, 1, 128, 233, 206, 143,,,, -5, 6, 4, 3, 3, 3, 2, 1, 256, 233, 206, 143,,,, -5, 6, 4, 3, 3, 3, 2, 1, 384, 233, 206, 143,,,, -5, 6, 4, 3, 3, 3, 2, 2, 128, 233, 206, 143,,,, -5, 6, 4, 3, 3, 3, 2, 2, 256, 233, 206, 143,,,, -5, 6, 4, 3, 3, 3, 2, 2, 384, 233, 206, 143,,,, -5, 6, 4, 3, 3, 3, 2, 3, 128, 233, 206, 143,,,, -5, 6, 4, 3, 3, 3, 2, 3, 256, 233, 206, 143,,,, -5, 6, 4, 3, 3, 3, 2, 3, 384, 233, 206, 143,,,, -5, 6, 4, 3, 3, 3, 3, 1, 128, 233, 206, 143,,,, -5, 6, 4, 3, 3, 3, 3, 1, 256, 233, 206, 143,,,, -5, 6, 4, 3, 3, 3, 3, 1, 384, 233, 206, 143,,,, -5, 6, 4, 3, 3, 3, 3, 2, 128, 233, 206, 143,,,, -5, 6, 4, 3, 3, 3, 3, 2, 256, 233, 206, 143,,,, -5, 6, 4, 3, 3, 3, 3, 2, 384, 233, 206, 143,,,, -5, 6, 4, 3, 3, 3, 3, 3, 128, 233, 206, 143,,,, -5, 6, 4, 3, 3, 3, 3, 3, 256, 233, 206, 143,,,, -5, 6, 4, 3, 3, 3, 3, 3, 384, 233, 206, 143,,,, -5, 6, 4, 4, 1, 1, 1, 1, 128, 240, 240, 209,,,, -5, 6, 4, 4, 1, 1, 1, 1, 256, 240, 240, 209,,,, -5, 6, 4, 4, 1, 1, 1, 1, 384, 240, 240, 209,,,, -5, 6, 4, 4, 2, 2, 1, 1, 128, 240, 240, 197,,,, -5, 6, 4, 4, 2, 2, 1, 1, 256, 240, 240, 197,,,, -5, 6, 4, 4, 2, 2, 1, 1, 384, 240, 240, 197,,,, -5, 6, 4, 4, 2, 2, 1, 2, 128, 240, 240, 197,,,, -5, 6, 4, 4, 2, 2, 1, 2, 256, 240, 240, 197,,,, -5, 6, 4, 4, 2, 2, 1, 2, 384, 240, 240, 197,,,, -5, 6, 4, 4, 2, 2, 2, 1, 128, 240, 240, 197,,,, -5, 6, 4, 4, 2, 2, 2, 1, 256, 240, 240, 197,,,, -5, 6, 4, 4, 2, 2, 2, 1, 384, 240, 240, 197,,,, -5, 6, 4, 4, 2, 2, 2, 2, 128, 240, 240, 197,,,, -5, 6, 4, 4, 2, 2, 2, 2, 256, 240, 240, 197,,,, -5, 6, 4, 4, 2, 2, 2, 2, 384, 240, 240, 197,,,, -5, 6, 4, 4, 3, 3, 1, 1, 128, 240, 240, 189,,,, -5, 6, 4, 4, 3, 3, 1, 1, 256, 240, 240, 189,,,, -5, 6, 4, 4, 3, 3, 1, 1, 384, 240, 240, 189,,,, -5, 6, 4, 4, 3, 3, 1, 2, 128, 240, 240, 189,,,, -5, 6, 4, 4, 3, 3, 1, 2, 256, 240, 240, 189,,,, -5, 6, 4, 4, 3, 3, 1, 2, 384, 240, 240, 189,,,, -5, 6, 4, 4, 3, 3, 1, 3, 128, 240, 240, 189,,,, -5, 6, 4, 4, 3, 3, 1, 3, 256, 240, 240, 189,,,, -5, 6, 4, 4, 3, 3, 1, 3, 384, 240, 240, 189,,,, -5, 6, 4, 4, 3, 3, 2, 1, 128, 240, 240, 189,,,, -5, 6, 4, 4, 3, 3, 2, 1, 256, 240, 240, 189,,,, -5, 6, 4, 4, 3, 3, 2, 1, 384, 240, 240, 189,,,, -5, 6, 4, 4, 3, 3, 2, 2, 128, 240, 240, 189,,,, -5, 6, 4, 4, 3, 3, 2, 2, 256, 240, 240, 189,,,, -5, 6, 4, 4, 3, 3, 2, 2, 384, 240, 240, 189,,,, -5, 6, 4, 4, 3, 3, 2, 3, 128, 240, 240, 189,,,, -5, 6, 4, 4, 3, 3, 2, 3, 256, 240, 240, 189,,,, -5, 6, 4, 4, 3, 3, 2, 3, 384, 240, 240, 189,,,, -5, 6, 4, 4, 3, 3, 3, 1, 128, 240, 240, 189,,,, -5, 6, 4, 4, 3, 3, 3, 1, 256, 240, 240, 189,,,, -5, 6, 4, 4, 3, 3, 3, 1, 384, 240, 240, 189,,,, -5, 6, 4, 4, 3, 3, 3, 2, 128, 240, 240, 189,,,, -5, 6, 4, 4, 3, 3, 3, 2, 256, 240, 240, 189,,,, -5, 6, 4, 4, 3, 3, 3, 2, 384, 240, 240, 189,,,, -5, 6, 4, 4, 3, 3, 3, 3, 128, 240, 240, 189,,,, -5, 6, 4, 4, 3, 3, 3, 3, 256, 240, 240, 189,,,, -5, 6, 4, 4, 3, 3, 3, 3, 384, 240, 240, 189,,,, -5, 6, 4, 5, 1, 1, 1, 1, 128, 240, 240, 240,,,, -5, 6, 4, 5, 1, 1, 1, 1, 256, 240, 240, 240,,,, -5, 6, 4, 5, 1, 1, 1, 1, 384, 240, 240, 240,,,, -5, 6, 4, 5, 2, 2, 1, 1, 128, 240, 240, 240,,,, -5, 6, 4, 5, 2, 2, 1, 1, 256, 240, 240, 240,,,, -5, 6, 4, 5, 2, 2, 1, 1, 384, 240, 240, 240,,,, -5, 6, 4, 5, 2, 2, 1, 2, 128, 240, 240, 240,,,, -5, 6, 4, 5, 2, 2, 1, 2, 256, 240, 240, 240,,,, -5, 6, 4, 5, 2, 2, 1, 2, 384, 240, 240, 240,,,, -5, 6, 4, 5, 2, 2, 2, 1, 128, 240, 240, 240,,,, -5, 6, 4, 5, 2, 2, 2, 1, 256, 240, 240, 240,,,, -5, 6, 4, 5, 2, 2, 2, 1, 384, 240, 240, 240,,,, -5, 6, 4, 5, 2, 2, 2, 2, 128, 240, 240, 240,,,, -5, 6, 4, 5, 2, 2, 2, 2, 256, 240, 240, 240,,,, -5, 6, 4, 5, 2, 2, 2, 2, 384, 240, 240, 240,,,, -5, 6, 4, 5, 3, 3, 1, 1, 128, 240, 240, 235,,,, -5, 6, 4, 5, 3, 3, 1, 1, 256, 240, 240, 235,,,, -5, 6, 4, 5, 3, 3, 1, 1, 384, 240, 240, 235,,,, -5, 6, 4, 5, 3, 3, 1, 2, 128, 240, 240, 235,,,, -5, 6, 4, 5, 3, 3, 1, 2, 256, 240, 240, 235,,,, -5, 6, 4, 5, 3, 3, 1, 2, 384, 240, 240, 235,,,, -5, 6, 4, 5, 3, 3, 1, 3, 128, 240, 240, 235,,,, -5, 6, 4, 5, 3, 3, 1, 3, 256, 240, 240, 235,,,, -5, 6, 4, 5, 3, 3, 1, 3, 384, 240, 240, 235,,,, -5, 6, 4, 5, 3, 3, 2, 1, 128, 240, 240, 235,,,, -5, 6, 4, 5, 3, 3, 2, 1, 256, 240, 240, 235,,,, -5, 6, 4, 5, 3, 3, 2, 1, 384, 240, 240, 235,,,, -5, 6, 4, 5, 3, 3, 2, 2, 128, 240, 240, 235,,,, -5, 6, 4, 5, 3, 3, 2, 2, 256, 240, 240, 235,,,, -5, 6, 4, 5, 3, 3, 2, 2, 384, 240, 240, 235,,,, -5, 6, 4, 5, 3, 3, 2, 3, 128, 240, 240, 235,,,, -5, 6, 4, 5, 3, 3, 2, 3, 256, 240, 240, 235,,,, -5, 6, 4, 5, 3, 3, 2, 3, 384, 240, 240, 235,,,, -5, 6, 4, 5, 3, 3, 3, 1, 128, 240, 240, 235,,,, -5, 6, 4, 5, 3, 3, 3, 1, 256, 240, 240, 235,,,, -5, 6, 4, 5, 3, 3, 3, 1, 384, 240, 240, 235,,,, -5, 6, 4, 5, 3, 3, 3, 2, 128, 240, 240, 235,,,, -5, 6, 4, 5, 3, 3, 3, 2, 256, 240, 240, 235,,,, -5, 6, 4, 5, 3, 3, 3, 2, 384, 240, 240, 235,,,, -5, 6, 4, 5, 3, 3, 3, 3, 128, 240, 240, 235,,,, -5, 6, 4, 5, 3, 3, 3, 3, 256, 240, 240, 235,,,, -5, 6, 4, 5, 3, 3, 3, 3, 384, 240, 240, 235,,,, -5, 6, 4, 6, 1, 1, 1, 1, 128, 240, 240, 240,,,, -5, 6, 4, 6, 1, 1, 1, 1, 256, 240, 240, 240,,,, -5, 6, 4, 6, 1, 1, 1, 1, 384, 240, 240, 240,,,, -5, 6, 4, 6, 2, 2, 1, 1, 128, 240, 240, 240,,,, -5, 6, 4, 6, 2, 2, 1, 1, 256, 240, 240, 240,,,, -5, 6, 4, 6, 2, 2, 1, 1, 384, 240, 240, 240,,,, -5, 6, 4, 6, 2, 2, 1, 2, 128, 240, 240, 240,,,, -5, 6, 4, 6, 2, 2, 1, 2, 256, 240, 240, 240,,,, -5, 6, 4, 6, 2, 2, 1, 2, 384, 240, 240, 240,,,, -5, 6, 4, 6, 2, 2, 2, 1, 128, 240, 240, 240,,,, -5, 6, 4, 6, 2, 2, 2, 1, 256, 240, 240, 240,,,, -5, 6, 4, 6, 2, 2, 2, 1, 384, 240, 240, 240,,,, -5, 6, 4, 6, 2, 2, 2, 2, 128, 240, 240, 240,,,, -5, 6, 4, 6, 2, 2, 2, 2, 256, 240, 240, 240,,,, -5, 6, 4, 6, 2, 2, 2, 2, 384, 240, 240, 240,,,, -5, 6, 4, 6, 3, 3, 1, 1, 128, 240, 240, 240,,,, -5, 6, 4, 6, 3, 3, 1, 1, 256, 240, 240, 240,,,, -5, 6, 4, 6, 3, 3, 1, 1, 384, 240, 240, 240,,,, -5, 6, 4, 6, 3, 3, 1, 2, 128, 240, 240, 240,,,, -5, 6, 4, 6, 3, 3, 1, 2, 256, 240, 240, 240,,,, -5, 6, 4, 6, 3, 3, 1, 2, 384, 240, 240, 240,,,, -5, 6, 4, 6, 3, 3, 1, 3, 128, 240, 240, 240,,,, -5, 6, 4, 6, 3, 3, 1, 3, 256, 240, 240, 240,,,, -5, 6, 4, 6, 3, 3, 1, 3, 384, 240, 240, 240,,,, -5, 6, 4, 6, 3, 3, 2, 1, 128, 240, 240, 240,,,, -5, 6, 4, 6, 3, 3, 2, 1, 256, 240, 240, 240,,,, -5, 6, 4, 6, 3, 3, 2, 1, 384, 240, 240, 240,,,, -5, 6, 4, 6, 3, 3, 2, 2, 128, 240, 240, 240,,,, -5, 6, 4, 6, 3, 3, 2, 2, 256, 240, 240, 240,,,, -5, 6, 4, 6, 3, 3, 2, 2, 384, 240, 240, 240,,,, -5, 6, 4, 6, 3, 3, 2, 3, 128, 240, 240, 240,,,, -5, 6, 4, 6, 3, 3, 2, 3, 256, 240, 240, 240,,,, -5, 6, 4, 6, 3, 3, 2, 3, 384, 240, 240, 240,,,, -5, 6, 4, 6, 3, 3, 3, 1, 128, 240, 240, 240,,,, -5, 6, 4, 6, 3, 3, 3, 1, 256, 240, 240, 240,,,, -5, 6, 4, 6, 3, 3, 3, 1, 384, 240, 240, 240,,,, -5, 6, 4, 6, 3, 3, 3, 2, 128, 240, 240, 240,,,, -5, 6, 4, 6, 3, 3, 3, 2, 256, 240, 240, 240,,,, -5, 6, 4, 6, 3, 3, 3, 2, 384, 240, 240, 240,,,, -5, 6, 4, 6, 3, 3, 3, 3, 128, 240, 240, 240,,,, -5, 6, 4, 6, 3, 3, 3, 3, 256, 240, 240, 240,,,, -5, 6, 4, 6, 3, 3, 3, 3, 384, 240, 240, 240,,,, -5, 6, 5, 1, 1, 1, 1, 1, 128, 81, 81, 56,,,, -5, 6, 5, 1, 1, 1, 1, 1, 256, 81, 81, 56,,,, -5, 6, 5, 1, 1, 1, 1, 1, 384, 81, 81, 56,,,, -5, 6, 5, 1, 2, 2, 1, 1, 128, 81, 75, 53,,,, -5, 6, 5, 1, 2, 2, 1, 1, 256, 81, 75, 53,,,, -5, 6, 5, 1, 2, 2, 1, 1, 384, 81, 75, 53,,,, -5, 6, 5, 1, 2, 2, 1, 2, 128, 81, 75, 53,,,, -5, 6, 5, 1, 2, 2, 1, 2, 256, 81, 75, 53,,,, -5, 6, 5, 1, 2, 2, 1, 2, 384, 81, 75, 53,,,, -5, 6, 5, 1, 2, 2, 2, 1, 128, 81, 75, 53,,,, -5, 6, 5, 1, 2, 2, 2, 1, 256, 81, 75, 53,,,, -5, 6, 5, 1, 2, 2, 2, 1, 384, 81, 75, 53,,,, -5, 6, 5, 1, 2, 2, 2, 2, 128, 81, 75, 53,,,, -5, 6, 5, 1, 2, 2, 2, 2, 256, 81, 75, 53,,,, -5, 6, 5, 1, 2, 2, 2, 2, 384, 81, 75, 53,,,, -5, 6, 5, 1, 3, 3, 1, 1, 128, 81, 72, 51,,,, -5, 6, 5, 1, 3, 3, 1, 1, 256, 81, 72, 51,,,, -5, 6, 5, 1, 3, 3, 1, 1, 384, 81, 72, 51,,,, -5, 6, 5, 1, 3, 3, 1, 2, 128, 81, 72, 51,,,, -5, 6, 5, 1, 3, 3, 1, 2, 256, 81, 72, 51,,,, -5, 6, 5, 1, 3, 3, 1, 2, 384, 81, 72, 51,,,, -5, 6, 5, 1, 3, 3, 1, 3, 128, 81, 72, 51,,,, -5, 6, 5, 1, 3, 3, 1, 3, 256, 81, 72, 51,,,, -5, 6, 5, 1, 3, 3, 1, 3, 384, 81, 72, 51,,,, -5, 6, 5, 1, 3, 3, 2, 1, 128, 81, 72, 51,,,, -5, 6, 5, 1, 3, 3, 2, 1, 256, 81, 72, 51,,,, -5, 6, 5, 1, 3, 3, 2, 1, 384, 81, 72, 51,,,, -5, 6, 5, 1, 3, 3, 2, 2, 128, 81, 72, 51,,,, -5, 6, 5, 1, 3, 3, 2, 2, 256, 81, 72, 51,,,, -5, 6, 5, 1, 3, 3, 2, 2, 384, 81, 72, 51,,,, -5, 6, 5, 1, 3, 3, 2, 3, 128, 81, 72, 51,,,, -5, 6, 5, 1, 3, 3, 2, 3, 256, 81, 72, 51,,,, -5, 6, 5, 1, 3, 3, 2, 3, 384, 81, 72, 51,,,, -5, 6, 5, 1, 3, 3, 3, 1, 128, 81, 72, 51,,,, -5, 6, 5, 1, 3, 3, 3, 1, 256, 81, 72, 51,,,, -5, 6, 5, 1, 3, 3, 3, 1, 384, 81, 72, 51,,,, -5, 6, 5, 1, 3, 3, 3, 2, 128, 81, 72, 51,,,, -5, 6, 5, 1, 3, 3, 3, 2, 256, 81, 72, 51,,,, -5, 6, 5, 1, 3, 3, 3, 2, 384, 81, 72, 51,,,, -5, 6, 5, 1, 3, 3, 3, 3, 128, 81, 72, 51,,,, -5, 6, 5, 1, 3, 3, 3, 3, 256, 81, 72, 51,,,, -5, 6, 5, 1, 3, 3, 3, 3, 384, 81, 72, 51,,,, -5, 6, 5, 2, 1, 1, 1, 1, 128, 157, 157, 107,,,, -5, 6, 5, 2, 1, 1, 1, 1, 256, 157, 157, 107,,,, -5, 6, 5, 2, 1, 1, 1, 1, 384, 157, 157, 107,,,, -5, 6, 5, 2, 2, 2, 1, 1, 128, 157, 145, 101,,,, -5, 6, 5, 2, 2, 2, 1, 1, 256, 157, 145, 101,,,, -5, 6, 5, 2, 2, 2, 1, 1, 384, 157, 145, 101,,,, -5, 6, 5, 2, 2, 2, 1, 2, 128, 157, 145, 101,,,, -5, 6, 5, 2, 2, 2, 1, 2, 256, 157, 145, 101,,,, -5, 6, 5, 2, 2, 2, 1, 2, 384, 157, 145, 101,,,, -5, 6, 5, 2, 2, 2, 2, 1, 128, 157, 145, 101,,,, -5, 6, 5, 2, 2, 2, 2, 1, 256, 157, 145, 101,,,, -5, 6, 5, 2, 2, 2, 2, 1, 384, 157, 145, 101,,,, -5, 6, 5, 2, 2, 2, 2, 2, 128, 157, 145, 101,,,, -5, 6, 5, 2, 2, 2, 2, 2, 256, 157, 145, 101,,,, -5, 6, 5, 2, 2, 2, 2, 2, 384, 157, 145, 101,,,, -5, 6, 5, 2, 3, 3, 1, 1, 128, 157, 139, 97,,,, -5, 6, 5, 2, 3, 3, 1, 1, 256, 157, 139, 97,,,, -5, 6, 5, 2, 3, 3, 1, 1, 384, 157, 139, 97,,,, -5, 6, 5, 2, 3, 3, 1, 2, 128, 157, 139, 97,,,, -5, 6, 5, 2, 3, 3, 1, 2, 256, 157, 139, 97,,,, -5, 6, 5, 2, 3, 3, 1, 2, 384, 157, 139, 97,,,, -5, 6, 5, 2, 3, 3, 1, 3, 128, 157, 139, 97,,,, -5, 6, 5, 2, 3, 3, 1, 3, 256, 157, 139, 97,,,, -5, 6, 5, 2, 3, 3, 1, 3, 384, 157, 139, 97,,,, -5, 6, 5, 2, 3, 3, 2, 1, 128, 157, 139, 97,,,, -5, 6, 5, 2, 3, 3, 2, 1, 256, 157, 139, 97,,,, -5, 6, 5, 2, 3, 3, 2, 1, 384, 157, 139, 97,,,, -5, 6, 5, 2, 3, 3, 2, 2, 128, 157, 139, 97,,,, -5, 6, 5, 2, 3, 3, 2, 2, 256, 157, 139, 97,,,, -5, 6, 5, 2, 3, 3, 2, 2, 384, 157, 139, 97,,,, -5, 6, 5, 2, 3, 3, 2, 3, 128, 157, 139, 97,,,, -5, 6, 5, 2, 3, 3, 2, 3, 256, 157, 139, 97,,,, -5, 6, 5, 2, 3, 3, 2, 3, 384, 157, 139, 97,,,, -5, 6, 5, 2, 3, 3, 3, 1, 128, 157, 139, 97,,,, -5, 6, 5, 2, 3, 3, 3, 1, 256, 157, 139, 97,,,, -5, 6, 5, 2, 3, 3, 3, 1, 384, 157, 139, 97,,,, -5, 6, 5, 2, 3, 3, 3, 2, 128, 157, 139, 97,,,, -5, 6, 5, 2, 3, 3, 3, 2, 256, 157, 139, 97,,,, -5, 6, 5, 2, 3, 3, 3, 2, 384, 157, 139, 97,,,, -5, 6, 5, 2, 3, 3, 3, 3, 128, 157, 139, 97,,,, -5, 6, 5, 2, 3, 3, 3, 3, 256, 157, 139, 97,,,, -5, 6, 5, 2, 3, 3, 3, 3, 384, 157, 139, 97,,,, -5, 6, 5, 3, 1, 1, 1, 1, 128, 233, 233, 158,,,, -5, 6, 5, 3, 1, 1, 1, 1, 256, 233, 233, 158,,,, -5, 6, 5, 3, 1, 1, 1, 1, 384, 233, 233, 158,,,, -5, 6, 5, 3, 2, 2, 1, 1, 128, 233, 215, 149,,,, -5, 6, 5, 3, 2, 2, 1, 1, 256, 233, 215, 149,,,, -5, 6, 5, 3, 2, 2, 1, 1, 384, 233, 215, 149,,,, -5, 6, 5, 3, 2, 2, 1, 2, 128, 233, 215, 149,,,, -5, 6, 5, 3, 2, 2, 1, 2, 256, 233, 215, 149,,,, -5, 6, 5, 3, 2, 2, 1, 2, 384, 233, 215, 149,,,, -5, 6, 5, 3, 2, 2, 2, 1, 128, 233, 215, 149,,,, -5, 6, 5, 3, 2, 2, 2, 1, 256, 233, 215, 149,,,, -5, 6, 5, 3, 2, 2, 2, 1, 384, 233, 215, 149,,,, -5, 6, 5, 3, 2, 2, 2, 2, 128, 233, 215, 149,,,, -5, 6, 5, 3, 2, 2, 2, 2, 256, 233, 215, 149,,,, -5, 6, 5, 3, 2, 2, 2, 2, 384, 233, 215, 149,,,, -5, 6, 5, 3, 3, 3, 1, 1, 128, 233, 206, 143,,,, -5, 6, 5, 3, 3, 3, 1, 1, 256, 233, 206, 143,,,, -5, 6, 5, 3, 3, 3, 1, 1, 384, 233, 206, 143,,,, -5, 6, 5, 3, 3, 3, 1, 2, 128, 233, 206, 143,,,, -5, 6, 5, 3, 3, 3, 1, 2, 256, 233, 206, 143,,,, -5, 6, 5, 3, 3, 3, 1, 2, 384, 233, 206, 143,,,, -5, 6, 5, 3, 3, 3, 1, 3, 128, 233, 206, 143,,,, -5, 6, 5, 3, 3, 3, 1, 3, 256, 233, 206, 143,,,, -5, 6, 5, 3, 3, 3, 1, 3, 384, 233, 206, 143,,,, -5, 6, 5, 3, 3, 3, 2, 1, 128, 233, 206, 143,,,, -5, 6, 5, 3, 3, 3, 2, 1, 256, 233, 206, 143,,,, -5, 6, 5, 3, 3, 3, 2, 1, 384, 233, 206, 143,,,, -5, 6, 5, 3, 3, 3, 2, 2, 128, 233, 206, 143,,,, -5, 6, 5, 3, 3, 3, 2, 2, 256, 233, 206, 143,,,, -5, 6, 5, 3, 3, 3, 2, 2, 384, 233, 206, 143,,,, -5, 6, 5, 3, 3, 3, 2, 3, 128, 233, 206, 143,,,, -5, 6, 5, 3, 3, 3, 2, 3, 256, 233, 206, 143,,,, -5, 6, 5, 3, 3, 3, 2, 3, 384, 233, 206, 143,,,, -5, 6, 5, 3, 3, 3, 3, 1, 128, 233, 206, 143,,,, -5, 6, 5, 3, 3, 3, 3, 1, 256, 233, 206, 143,,,, -5, 6, 5, 3, 3, 3, 3, 1, 384, 233, 206, 143,,,, -5, 6, 5, 3, 3, 3, 3, 2, 128, 233, 206, 143,,,, -5, 6, 5, 3, 3, 3, 3, 2, 256, 233, 206, 143,,,, -5, 6, 5, 3, 3, 3, 3, 2, 384, 233, 206, 143,,,, -5, 6, 5, 3, 3, 3, 3, 3, 128, 233, 206, 143,,,, -5, 6, 5, 3, 3, 3, 3, 3, 256, 233, 206, 143,,,, -5, 6, 5, 3, 3, 3, 3, 3, 384, 233, 206, 143,,,, -5, 6, 5, 4, 1, 1, 1, 1, 128, 240, 240, 209,,,, -5, 6, 5, 4, 1, 1, 1, 1, 256, 240, 240, 209,,,, -5, 6, 5, 4, 1, 1, 1, 1, 384, 240, 240, 209,,,, -5, 6, 5, 4, 2, 2, 1, 1, 128, 240, 240, 197,,,, -5, 6, 5, 4, 2, 2, 1, 1, 256, 240, 240, 197,,,, -5, 6, 5, 4, 2, 2, 1, 1, 384, 240, 240, 197,,,, -5, 6, 5, 4, 2, 2, 1, 2, 128, 240, 240, 197,,,, -5, 6, 5, 4, 2, 2, 1, 2, 256, 240, 240, 197,,,, -5, 6, 5, 4, 2, 2, 1, 2, 384, 240, 240, 197,,,, -5, 6, 5, 4, 2, 2, 2, 1, 128, 240, 240, 197,,,, -5, 6, 5, 4, 2, 2, 2, 1, 256, 240, 240, 197,,,, -5, 6, 5, 4, 2, 2, 2, 1, 384, 240, 240, 197,,,, -5, 6, 5, 4, 2, 2, 2, 2, 128, 240, 240, 197,,,, -5, 6, 5, 4, 2, 2, 2, 2, 256, 240, 240, 197,,,, -5, 6, 5, 4, 2, 2, 2, 2, 384, 240, 240, 197,,,, -5, 6, 5, 4, 3, 3, 1, 1, 128, 240, 240, 189,,,, -5, 6, 5, 4, 3, 3, 1, 1, 256, 240, 240, 189,,,, -5, 6, 5, 4, 3, 3, 1, 1, 384, 240, 240, 189,,,, -5, 6, 5, 4, 3, 3, 1, 2, 128, 240, 240, 189,,,, -5, 6, 5, 4, 3, 3, 1, 2, 256, 240, 240, 189,,,, -5, 6, 5, 4, 3, 3, 1, 2, 384, 240, 240, 189,,,, -5, 6, 5, 4, 3, 3, 1, 3, 128, 240, 240, 189,,,, -5, 6, 5, 4, 3, 3, 1, 3, 256, 240, 240, 189,,,, -5, 6, 5, 4, 3, 3, 1, 3, 384, 240, 240, 189,,,, -5, 6, 5, 4, 3, 3, 2, 1, 128, 240, 240, 189,,,, -5, 6, 5, 4, 3, 3, 2, 1, 256, 240, 240, 189,,,, -5, 6, 5, 4, 3, 3, 2, 1, 384, 240, 240, 189,,,, -5, 6, 5, 4, 3, 3, 2, 2, 128, 240, 240, 189,,,, -5, 6, 5, 4, 3, 3, 2, 2, 256, 240, 240, 189,,,, -5, 6, 5, 4, 3, 3, 2, 2, 384, 240, 240, 189,,,, -5, 6, 5, 4, 3, 3, 2, 3, 128, 240, 240, 189,,,, -5, 6, 5, 4, 3, 3, 2, 3, 256, 240, 240, 189,,,, -5, 6, 5, 4, 3, 3, 2, 3, 384, 240, 240, 189,,,, -5, 6, 5, 4, 3, 3, 3, 1, 128, 240, 240, 189,,,, -5, 6, 5, 4, 3, 3, 3, 1, 256, 240, 240, 189,,,, -5, 6, 5, 4, 3, 3, 3, 1, 384, 240, 240, 189,,,, -5, 6, 5, 4, 3, 3, 3, 2, 128, 240, 240, 189,,,, -5, 6, 5, 4, 3, 3, 3, 2, 256, 240, 240, 189,,,, -5, 6, 5, 4, 3, 3, 3, 2, 384, 240, 240, 189,,,, -5, 6, 5, 4, 3, 3, 3, 3, 128, 240, 240, 189,,,, -5, 6, 5, 4, 3, 3, 3, 3, 256, 240, 240, 189,,,, -5, 6, 5, 4, 3, 3, 3, 3, 384, 240, 240, 189,,,, -5, 6, 5, 5, 1, 1, 1, 1, 128, 240, 240, 240,,,, -5, 6, 5, 5, 1, 1, 1, 1, 256, 240, 240, 240,,,, -5, 6, 5, 5, 1, 1, 1, 1, 384, 240, 240, 240,,,, -5, 6, 5, 5, 2, 2, 1, 1, 128, 240, 240, 240,,,, -5, 6, 5, 5, 2, 2, 1, 1, 256, 240, 240, 240,,,, -5, 6, 5, 5, 2, 2, 1, 1, 384, 240, 240, 240,,,, -5, 6, 5, 5, 2, 2, 1, 2, 128, 240, 240, 240,,,, -5, 6, 5, 5, 2, 2, 1, 2, 256, 240, 240, 240,,,, -5, 6, 5, 5, 2, 2, 1, 2, 384, 240, 240, 240,,,, -5, 6, 5, 5, 2, 2, 2, 1, 128, 240, 240, 240,,,, -5, 6, 5, 5, 2, 2, 2, 1, 256, 240, 240, 240,,,, -5, 6, 5, 5, 2, 2, 2, 1, 384, 240, 240, 240,,,, -5, 6, 5, 5, 2, 2, 2, 2, 128, 240, 240, 240,,,, -5, 6, 5, 5, 2, 2, 2, 2, 256, 240, 240, 240,,,, -5, 6, 5, 5, 2, 2, 2, 2, 384, 240, 240, 240,,,, -5, 6, 5, 5, 3, 3, 1, 1, 128, 240, 240, 235,,,, -5, 6, 5, 5, 3, 3, 1, 1, 256, 240, 240, 235,,,, -5, 6, 5, 5, 3, 3, 1, 1, 384, 240, 240, 235,,,, -5, 6, 5, 5, 3, 3, 1, 2, 128, 240, 240, 235,,,, -5, 6, 5, 5, 3, 3, 1, 2, 256, 240, 240, 235,,,, -5, 6, 5, 5, 3, 3, 1, 2, 384, 240, 240, 235,,,, -5, 6, 5, 5, 3, 3, 1, 3, 128, 240, 240, 235,,,, -5, 6, 5, 5, 3, 3, 1, 3, 256, 240, 240, 235,,,, -5, 6, 5, 5, 3, 3, 1, 3, 384, 240, 240, 235,,,, -5, 6, 5, 5, 3, 3, 2, 1, 128, 240, 240, 235,,,, -5, 6, 5, 5, 3, 3, 2, 1, 256, 240, 240, 235,,,, -5, 6, 5, 5, 3, 3, 2, 1, 384, 240, 240, 235,,,, -5, 6, 5, 5, 3, 3, 2, 2, 128, 240, 240, 235,,,, -5, 6, 5, 5, 3, 3, 2, 2, 256, 240, 240, 235,,,, -5, 6, 5, 5, 3, 3, 2, 2, 384, 240, 240, 235,,,, -5, 6, 5, 5, 3, 3, 2, 3, 128, 240, 240, 235,,,, -5, 6, 5, 5, 3, 3, 2, 3, 256, 240, 240, 235,,,, -5, 6, 5, 5, 3, 3, 2, 3, 384, 240, 240, 235,,,, -5, 6, 5, 5, 3, 3, 3, 1, 128, 240, 240, 235,,,, -5, 6, 5, 5, 3, 3, 3, 1, 256, 240, 240, 235,,,, -5, 6, 5, 5, 3, 3, 3, 1, 384, 240, 240, 235,,,, -5, 6, 5, 5, 3, 3, 3, 2, 128, 240, 240, 235,,,, -5, 6, 5, 5, 3, 3, 3, 2, 256, 240, 240, 235,,,, -5, 6, 5, 5, 3, 3, 3, 2, 384, 240, 240, 235,,,, -5, 6, 5, 5, 3, 3, 3, 3, 128, 240, 240, 235,,,, -5, 6, 5, 5, 3, 3, 3, 3, 256, 240, 240, 235,,,, -5, 6, 5, 5, 3, 3, 3, 3, 384, 240, 240, 235,,,, -5, 6, 5, 6, 1, 1, 1, 1, 128, 240, 240, 240,,,, -5, 6, 5, 6, 1, 1, 1, 1, 256, 240, 240, 240,,,, -5, 6, 5, 6, 1, 1, 1, 1, 384, 240, 240, 240,,,, -5, 6, 5, 6, 2, 2, 1, 1, 128, 240, 240, 240,,,, -5, 6, 5, 6, 2, 2, 1, 1, 256, 240, 240, 240,,,, -5, 6, 5, 6, 2, 2, 1, 1, 384, 240, 240, 240,,,, -5, 6, 5, 6, 2, 2, 1, 2, 128, 240, 240, 240,,,, -5, 6, 5, 6, 2, 2, 1, 2, 256, 240, 240, 240,,,, -5, 6, 5, 6, 2, 2, 1, 2, 384, 240, 240, 240,,,, -5, 6, 5, 6, 2, 2, 2, 1, 128, 240, 240, 240,,,, -5, 6, 5, 6, 2, 2, 2, 1, 256, 240, 240, 240,,,, -5, 6, 5, 6, 2, 2, 2, 1, 384, 240, 240, 240,,,, -5, 6, 5, 6, 2, 2, 2, 2, 128, 240, 240, 240,,,, -5, 6, 5, 6, 2, 2, 2, 2, 256, 240, 240, 240,,,, -5, 6, 5, 6, 2, 2, 2, 2, 384, 240, 240, 240,,,, -5, 6, 5, 6, 3, 3, 1, 1, 128, 240, 240, 240,,,, -5, 6, 5, 6, 3, 3, 1, 1, 256, 240, 240, 240,,,, -5, 6, 5, 6, 3, 3, 1, 1, 384, 240, 240, 240,,,, -5, 6, 5, 6, 3, 3, 1, 2, 128, 240, 240, 240,,,, -5, 6, 5, 6, 3, 3, 1, 2, 256, 240, 240, 240,,,, -5, 6, 5, 6, 3, 3, 1, 2, 384, 240, 240, 240,,,, -5, 6, 5, 6, 3, 3, 1, 3, 128, 240, 240, 240,,,, -5, 6, 5, 6, 3, 3, 1, 3, 256, 240, 240, 240,,,, -5, 6, 5, 6, 3, 3, 1, 3, 384, 240, 240, 240,,,, -5, 6, 5, 6, 3, 3, 2, 1, 128, 240, 240, 240,,,, -5, 6, 5, 6, 3, 3, 2, 1, 256, 240, 240, 240,,,, -5, 6, 5, 6, 3, 3, 2, 1, 384, 240, 240, 240,,,, -5, 6, 5, 6, 3, 3, 2, 2, 128, 240, 240, 240,,,, -5, 6, 5, 6, 3, 3, 2, 2, 256, 240, 240, 240,,,, -5, 6, 5, 6, 3, 3, 2, 2, 384, 240, 240, 240,,,, -5, 6, 5, 6, 3, 3, 2, 3, 128, 240, 240, 240,,,, -5, 6, 5, 6, 3, 3, 2, 3, 256, 240, 240, 240,,,, -5, 6, 5, 6, 3, 3, 2, 3, 384, 240, 240, 240,,,, -5, 6, 5, 6, 3, 3, 3, 1, 128, 240, 240, 240,,,, -5, 6, 5, 6, 3, 3, 3, 1, 256, 240, 240, 240,,,, -5, 6, 5, 6, 3, 3, 3, 1, 384, 240, 240, 240,,,, -5, 6, 5, 6, 3, 3, 3, 2, 128, 240, 240, 240,,,, -5, 6, 5, 6, 3, 3, 3, 2, 256, 240, 240, 240,,,, -5, 6, 5, 6, 3, 3, 3, 2, 384, 240, 240, 240,,,, -5, 6, 5, 6, 3, 3, 3, 3, 128, 240, 240, 240,,,, -5, 6, 5, 6, 3, 3, 3, 3, 256, 240, 240, 240,,,, -5, 6, 5, 6, 3, 3, 3, 3, 384, 240, 240, 240,,,, -5, 7, 1, 1, 1, 1, 1, 1, 128, 82, 57, 31,,,, -5, 7, 1, 1, 1, 1, 1, 1, 256, 82, 57, 31,,,, -5, 7, 1, 1, 1, 1, 1, 1, 384, 82, 57, 31,,,, -5, 7, 1, 1, 2, 2, 1, 1, 128, 82, 57, 31,,,, -5, 7, 1, 1, 2, 2, 1, 1, 256, 82, 57, 31,,,, -5, 7, 1, 1, 2, 2, 1, 1, 384, 82, 57, 31,,,, -5, 7, 1, 1, 2, 2, 1, 2, 128, 82, 57, 31,,,, -5, 7, 1, 1, 2, 2, 1, 2, 256, 82, 57, 31,,,, -5, 7, 1, 1, 2, 2, 1, 2, 384, 82, 57, 31,,,, -5, 7, 1, 1, 2, 2, 2, 1, 128, 82, 57, 31,,,, -5, 7, 1, 1, 2, 2, 2, 1, 256, 82, 57, 31,,,, -5, 7, 1, 1, 2, 2, 2, 1, 384, 82, 57, 31,,,, -5, 7, 1, 1, 2, 2, 2, 2, 128, 82, 57, 31,,,, -5, 7, 1, 1, 2, 2, 2, 2, 256, 82, 57, 31,,,, -5, 7, 1, 1, 2, 2, 2, 2, 384, 82, 57, 31,,,, -5, 7, 1, 1, 3, 3, 1, 1, 128, 82, 57, 31,,,, -5, 7, 1, 1, 3, 3, 1, 1, 256, 82, 57, 31,,,, -5, 7, 1, 1, 3, 3, 1, 1, 384, 82, 57, 31,,,, -5, 7, 1, 1, 3, 3, 1, 2, 128, 82, 57, 31,,,, -5, 7, 1, 1, 3, 3, 1, 2, 256, 82, 57, 31,,,, -5, 7, 1, 1, 3, 3, 1, 2, 384, 82, 57, 31,,,, -5, 7, 1, 1, 3, 3, 1, 3, 128, 82, 57, 31,,,, -5, 7, 1, 1, 3, 3, 1, 3, 256, 82, 57, 31,,,, -5, 7, 1, 1, 3, 3, 1, 3, 384, 82, 57, 31,,,, -5, 7, 1, 1, 3, 3, 2, 1, 128, 82, 57, 31,,,, -5, 7, 1, 1, 3, 3, 2, 1, 256, 82, 57, 31,,,, -5, 7, 1, 1, 3, 3, 2, 1, 384, 82, 57, 31,,,, -5, 7, 1, 1, 3, 3, 2, 2, 128, 82, 57, 31,,,, -5, 7, 1, 1, 3, 3, 2, 2, 256, 82, 57, 31,,,, -5, 7, 1, 1, 3, 3, 2, 2, 384, 82, 57, 31,,,, -5, 7, 1, 1, 3, 3, 2, 3, 128, 82, 57, 31,,,, -5, 7, 1, 1, 3, 3, 2, 3, 256, 82, 57, 31,,,, -5, 7, 1, 1, 3, 3, 2, 3, 384, 82, 57, 31,,,, -5, 7, 1, 1, 3, 3, 3, 1, 128, 82, 57, 31,,,, -5, 7, 1, 1, 3, 3, 3, 1, 256, 82, 57, 31,,,, -5, 7, 1, 1, 3, 3, 3, 1, 384, 82, 57, 31,,,, -5, 7, 1, 1, 3, 3, 3, 2, 128, 82, 57, 31,,,, -5, 7, 1, 1, 3, 3, 3, 2, 256, 82, 57, 31,,,, -5, 7, 1, 1, 3, 3, 3, 2, 384, 82, 57, 31,,,, -5, 7, 1, 1, 3, 3, 3, 3, 128, 82, 57, 31,,,, -5, 7, 1, 1, 3, 3, 3, 3, 256, 82, 57, 31,,,, -5, 7, 1, 1, 3, 3, 3, 3, 384, 82, 57, 31,,,, -5, 7, 1, 2, 1, 1, 1, 1, 128, 158, 108, 56,,,, -5, 7, 1, 2, 1, 1, 1, 1, 256, 158, 108, 56,,,, -5, 7, 1, 2, 1, 1, 1, 1, 384, 158, 108, 56,,,, -5, 7, 1, 2, 2, 2, 1, 1, 128, 158, 108, 56,,,, -5, 7, 1, 2, 2, 2, 1, 1, 256, 158, 108, 56,,,, -5, 7, 1, 2, 2, 2, 1, 1, 384, 158, 108, 56,,,, -5, 7, 1, 2, 2, 2, 1, 2, 128, 158, 108, 56,,,, -5, 7, 1, 2, 2, 2, 1, 2, 256, 158, 108, 56,,,, -5, 7, 1, 2, 2, 2, 1, 2, 384, 158, 108, 56,,,, -5, 7, 1, 2, 2, 2, 2, 1, 128, 158, 108, 56,,,, -5, 7, 1, 2, 2, 2, 2, 1, 256, 158, 108, 56,,,, -5, 7, 1, 2, 2, 2, 2, 1, 384, 158, 108, 56,,,, -5, 7, 1, 2, 2, 2, 2, 2, 128, 158, 108, 56,,,, -5, 7, 1, 2, 2, 2, 2, 2, 256, 158, 108, 56,,,, -5, 7, 1, 2, 2, 2, 2, 2, 384, 158, 108, 56,,,, -5, 7, 1, 2, 3, 3, 1, 1, 128, 158, 108, 56,,,, -5, 7, 1, 2, 3, 3, 1, 1, 256, 158, 108, 56,,,, -5, 7, 1, 2, 3, 3, 1, 1, 384, 158, 108, 56,,,, -5, 7, 1, 2, 3, 3, 1, 2, 128, 158, 108, 56,,,, -5, 7, 1, 2, 3, 3, 1, 2, 256, 158, 108, 56,,,, -5, 7, 1, 2, 3, 3, 1, 2, 384, 158, 108, 56,,,, -5, 7, 1, 2, 3, 3, 1, 3, 128, 158, 108, 56,,,, -5, 7, 1, 2, 3, 3, 1, 3, 256, 158, 108, 56,,,, -5, 7, 1, 2, 3, 3, 1, 3, 384, 158, 108, 56,,,, -5, 7, 1, 2, 3, 3, 2, 1, 128, 158, 108, 56,,,, -5, 7, 1, 2, 3, 3, 2, 1, 256, 158, 108, 56,,,, -5, 7, 1, 2, 3, 3, 2, 1, 384, 158, 108, 56,,,, -5, 7, 1, 2, 3, 3, 2, 2, 128, 158, 108, 56,,,, -5, 7, 1, 2, 3, 3, 2, 2, 256, 158, 108, 56,,,, -5, 7, 1, 2, 3, 3, 2, 2, 384, 158, 108, 56,,,, -5, 7, 1, 2, 3, 3, 2, 3, 128, 158, 108, 56,,,, -5, 7, 1, 2, 3, 3, 2, 3, 256, 158, 108, 56,,,, -5, 7, 1, 2, 3, 3, 2, 3, 384, 158, 108, 56,,,, -5, 7, 1, 2, 3, 3, 3, 1, 128, 158, 108, 56,,,, -5, 7, 1, 2, 3, 3, 3, 1, 256, 158, 108, 56,,,, -5, 7, 1, 2, 3, 3, 3, 1, 384, 158, 108, 56,,,, -5, 7, 1, 2, 3, 3, 3, 2, 128, 158, 108, 56,,,, -5, 7, 1, 2, 3, 3, 3, 2, 256, 158, 108, 56,,,, -5, 7, 1, 2, 3, 3, 3, 2, 384, 158, 108, 56,,,, -5, 7, 1, 2, 3, 3, 3, 3, 128, 158, 108, 56,,,, -5, 7, 1, 2, 3, 3, 3, 3, 256, 158, 108, 56,,,, -5, 7, 1, 2, 3, 3, 3, 3, 384, 158, 108, 56,,,, -5, 7, 1, 3, 1, 1, 1, 1, 128, 234, 159, 81,,,, -5, 7, 1, 3, 1, 1, 1, 1, 256, 234, 159, 81,,,, -5, 7, 1, 3, 1, 1, 1, 1, 384, 234, 159, 81,,,, -5, 7, 1, 3, 2, 2, 1, 1, 128, 234, 159, 81,,,, -5, 7, 1, 3, 2, 2, 1, 1, 256, 234, 159, 81,,,, -5, 7, 1, 3, 2, 2, 1, 1, 384, 234, 159, 81,,,, -5, 7, 1, 3, 2, 2, 1, 2, 128, 234, 159, 81,,,, -5, 7, 1, 3, 2, 2, 1, 2, 256, 234, 159, 81,,,, -5, 7, 1, 3, 2, 2, 1, 2, 384, 234, 159, 81,,,, -5, 7, 1, 3, 2, 2, 2, 1, 128, 234, 159, 81,,,, -5, 7, 1, 3, 2, 2, 2, 1, 256, 234, 159, 81,,,, -5, 7, 1, 3, 2, 2, 2, 1, 384, 234, 159, 81,,,, -5, 7, 1, 3, 2, 2, 2, 2, 128, 234, 159, 81,,,, -5, 7, 1, 3, 2, 2, 2, 2, 256, 234, 159, 81,,,, -5, 7, 1, 3, 2, 2, 2, 2, 384, 234, 159, 81,,,, -5, 7, 1, 3, 3, 3, 1, 1, 128, 234, 159, 81,,,, -5, 7, 1, 3, 3, 3, 1, 1, 256, 234, 159, 81,,,, -5, 7, 1, 3, 3, 3, 1, 1, 384, 234, 159, 81,,,, -5, 7, 1, 3, 3, 3, 1, 2, 128, 234, 159, 81,,,, -5, 7, 1, 3, 3, 3, 1, 2, 256, 234, 159, 81,,,, -5, 7, 1, 3, 3, 3, 1, 2, 384, 234, 159, 81,,,, -5, 7, 1, 3, 3, 3, 1, 3, 128, 234, 159, 81,,,, -5, 7, 1, 3, 3, 3, 1, 3, 256, 234, 159, 81,,,, -5, 7, 1, 3, 3, 3, 1, 3, 384, 234, 159, 81,,,, -5, 7, 1, 3, 3, 3, 2, 1, 128, 234, 159, 81,,,, -5, 7, 1, 3, 3, 3, 2, 1, 256, 234, 159, 81,,,, -5, 7, 1, 3, 3, 3, 2, 1, 384, 234, 159, 81,,,, -5, 7, 1, 3, 3, 3, 2, 2, 128, 234, 159, 81,,,, -5, 7, 1, 3, 3, 3, 2, 2, 256, 234, 159, 81,,,, -5, 7, 1, 3, 3, 3, 2, 2, 384, 234, 159, 81,,,, -5, 7, 1, 3, 3, 3, 2, 3, 128, 234, 159, 81,,,, -5, 7, 1, 3, 3, 3, 2, 3, 256, 234, 159, 81,,,, -5, 7, 1, 3, 3, 3, 2, 3, 384, 234, 159, 81,,,, -5, 7, 1, 3, 3, 3, 3, 1, 128, 234, 159, 81,,,, -5, 7, 1, 3, 3, 3, 3, 1, 256, 234, 159, 81,,,, -5, 7, 1, 3, 3, 3, 3, 1, 384, 234, 159, 81,,,, -5, 7, 1, 3, 3, 3, 3, 2, 128, 234, 159, 81,,,, -5, 7, 1, 3, 3, 3, 3, 2, 256, 234, 159, 81,,,, -5, 7, 1, 3, 3, 3, 3, 2, 384, 234, 159, 81,,,, -5, 7, 1, 3, 3, 3, 3, 3, 128, 234, 159, 81,,,, -5, 7, 1, 3, 3, 3, 3, 3, 256, 234, 159, 81,,,, -5, 7, 1, 3, 3, 3, 3, 3, 384, 234, 159, 81,,,, -5, 7, 1, 4, 1, 1, 1, 1, 128, 240, 210, 106,,,, -5, 7, 1, 4, 1, 1, 1, 1, 256, 240, 210, 106,,,, -5, 7, 1, 4, 1, 1, 1, 1, 384, 240, 210, 106,,,, -5, 7, 1, 4, 2, 2, 1, 1, 128, 240, 210, 106,,,, -5, 7, 1, 4, 2, 2, 1, 1, 256, 240, 210, 106,,,, -5, 7, 1, 4, 2, 2, 1, 1, 384, 240, 210, 106,,,, -5, 7, 1, 4, 2, 2, 1, 2, 128, 240, 210, 106,,,, -5, 7, 1, 4, 2, 2, 1, 2, 256, 240, 210, 106,,,, -5, 7, 1, 4, 2, 2, 1, 2, 384, 240, 210, 106,,,, -5, 7, 1, 4, 2, 2, 2, 1, 128, 240, 210, 106,,,, -5, 7, 1, 4, 2, 2, 2, 1, 256, 240, 210, 106,,,, -5, 7, 1, 4, 2, 2, 2, 1, 384, 240, 210, 106,,,, -5, 7, 1, 4, 2, 2, 2, 2, 128, 240, 210, 106,,,, -5, 7, 1, 4, 2, 2, 2, 2, 256, 240, 210, 106,,,, -5, 7, 1, 4, 2, 2, 2, 2, 384, 240, 210, 106,,,, -5, 7, 1, 4, 3, 3, 1, 1, 128, 240, 210, 106,,,, -5, 7, 1, 4, 3, 3, 1, 1, 256, 240, 210, 106,,,, -5, 7, 1, 4, 3, 3, 1, 1, 384, 240, 210, 106,,,, -5, 7, 1, 4, 3, 3, 1, 2, 128, 240, 210, 106,,,, -5, 7, 1, 4, 3, 3, 1, 2, 256, 240, 210, 106,,,, -5, 7, 1, 4, 3, 3, 1, 2, 384, 240, 210, 106,,,, -5, 7, 1, 4, 3, 3, 1, 3, 128, 240, 210, 106,,,, -5, 7, 1, 4, 3, 3, 1, 3, 256, 240, 210, 106,,,, -5, 7, 1, 4, 3, 3, 1, 3, 384, 240, 210, 106,,,, -5, 7, 1, 4, 3, 3, 2, 1, 128, 240, 210, 106,,,, -5, 7, 1, 4, 3, 3, 2, 1, 256, 240, 210, 106,,,, -5, 7, 1, 4, 3, 3, 2, 1, 384, 240, 210, 106,,,, -5, 7, 1, 4, 3, 3, 2, 2, 128, 240, 210, 106,,,, -5, 7, 1, 4, 3, 3, 2, 2, 256, 240, 210, 106,,,, -5, 7, 1, 4, 3, 3, 2, 2, 384, 240, 210, 106,,,, -5, 7, 1, 4, 3, 3, 2, 3, 128, 240, 210, 106,,,, -5, 7, 1, 4, 3, 3, 2, 3, 256, 240, 210, 106,,,, -5, 7, 1, 4, 3, 3, 2, 3, 384, 240, 210, 106,,,, -5, 7, 1, 4, 3, 3, 3, 1, 128, 240, 210, 106,,,, -5, 7, 1, 4, 3, 3, 3, 1, 256, 240, 210, 106,,,, -5, 7, 1, 4, 3, 3, 3, 1, 384, 240, 210, 106,,,, -5, 7, 1, 4, 3, 3, 3, 2, 128, 240, 210, 106,,,, -5, 7, 1, 4, 3, 3, 3, 2, 256, 240, 210, 106,,,, -5, 7, 1, 4, 3, 3, 3, 2, 384, 240, 210, 106,,,, -5, 7, 1, 4, 3, 3, 3, 3, 128, 240, 210, 106,,,, -5, 7, 1, 4, 3, 3, 3, 3, 256, 240, 210, 106,,,, -5, 7, 1, 4, 3, 3, 3, 3, 384, 240, 210, 106,,,, -5, 7, 1, 5, 1, 1, 1, 1, 128, 240, 240, 131,,,, -5, 7, 1, 5, 1, 1, 1, 1, 256, 240, 240, 131,,,, -5, 7, 1, 5, 1, 1, 1, 1, 384, 240, 240, 131,,,, -5, 7, 1, 5, 2, 2, 1, 1, 128, 240, 240, 131,,,, -5, 7, 1, 5, 2, 2, 1, 1, 256, 240, 240, 131,,,, -5, 7, 1, 5, 2, 2, 1, 1, 384, 240, 240, 131,,,, -5, 7, 1, 5, 2, 2, 1, 2, 128, 240, 240, 131,,,, -5, 7, 1, 5, 2, 2, 1, 2, 256, 240, 240, 131,,,, -5, 7, 1, 5, 2, 2, 1, 2, 384, 240, 240, 131,,,, -5, 7, 1, 5, 2, 2, 2, 1, 128, 240, 240, 131,,,, -5, 7, 1, 5, 2, 2, 2, 1, 256, 240, 240, 131,,,, -5, 7, 1, 5, 2, 2, 2, 1, 384, 240, 240, 131,,,, -5, 7, 1, 5, 2, 2, 2, 2, 128, 240, 240, 131,,,, -5, 7, 1, 5, 2, 2, 2, 2, 256, 240, 240, 131,,,, -5, 7, 1, 5, 2, 2, 2, 2, 384, 240, 240, 131,,,, -5, 7, 1, 5, 3, 3, 1, 1, 128, 240, 240, 131,,,, -5, 7, 1, 5, 3, 3, 1, 1, 256, 240, 240, 131,,,, -5, 7, 1, 5, 3, 3, 1, 1, 384, 240, 240, 131,,,, -5, 7, 1, 5, 3, 3, 1, 2, 128, 240, 240, 131,,,, -5, 7, 1, 5, 3, 3, 1, 2, 256, 240, 240, 131,,,, -5, 7, 1, 5, 3, 3, 1, 2, 384, 240, 240, 131,,,, -5, 7, 1, 5, 3, 3, 1, 3, 128, 240, 240, 131,,,, -5, 7, 1, 5, 3, 3, 1, 3, 256, 240, 240, 131,,,, -5, 7, 1, 5, 3, 3, 1, 3, 384, 240, 240, 131,,,, -5, 7, 1, 5, 3, 3, 2, 1, 128, 240, 240, 131,,,, -5, 7, 1, 5, 3, 3, 2, 1, 256, 240, 240, 131,,,, -5, 7, 1, 5, 3, 3, 2, 1, 384, 240, 240, 131,,,, -5, 7, 1, 5, 3, 3, 2, 2, 128, 240, 240, 131,,,, -5, 7, 1, 5, 3, 3, 2, 2, 256, 240, 240, 131,,,, -5, 7, 1, 5, 3, 3, 2, 2, 384, 240, 240, 131,,,, -5, 7, 1, 5, 3, 3, 2, 3, 128, 240, 240, 131,,,, -5, 7, 1, 5, 3, 3, 2, 3, 256, 240, 240, 131,,,, -5, 7, 1, 5, 3, 3, 2, 3, 384, 240, 240, 131,,,, -5, 7, 1, 5, 3, 3, 3, 1, 128, 240, 240, 131,,,, -5, 7, 1, 5, 3, 3, 3, 1, 256, 240, 240, 131,,,, -5, 7, 1, 5, 3, 3, 3, 1, 384, 240, 240, 131,,,, -5, 7, 1, 5, 3, 3, 3, 2, 128, 240, 240, 131,,,, -5, 7, 1, 5, 3, 3, 3, 2, 256, 240, 240, 131,,,, -5, 7, 1, 5, 3, 3, 3, 2, 384, 240, 240, 131,,,, -5, 7, 1, 5, 3, 3, 3, 3, 128, 240, 240, 131,,,, -5, 7, 1, 5, 3, 3, 3, 3, 256, 240, 240, 131,,,, -5, 7, 1, 5, 3, 3, 3, 3, 384, 240, 240, 131,,,, -5, 7, 1, 6, 1, 1, 1, 1, 128, 240, 240, 156,,,, -5, 7, 1, 6, 1, 1, 1, 1, 256, 240, 240, 156,,,, -5, 7, 1, 6, 1, 1, 1, 1, 384, 240, 240, 156,,,, -5, 7, 1, 6, 2, 2, 1, 1, 128, 240, 240, 156,,,, -5, 7, 1, 6, 2, 2, 1, 1, 256, 240, 240, 156,,,, -5, 7, 1, 6, 2, 2, 1, 1, 384, 240, 240, 156,,,, -5, 7, 1, 6, 2, 2, 1, 2, 128, 240, 240, 156,,,, -5, 7, 1, 6, 2, 2, 1, 2, 256, 240, 240, 156,,,, -5, 7, 1, 6, 2, 2, 1, 2, 384, 240, 240, 156,,,, -5, 7, 1, 6, 2, 2, 2, 1, 128, 240, 240, 156,,,, -5, 7, 1, 6, 2, 2, 2, 1, 256, 240, 240, 156,,,, -5, 7, 1, 6, 2, 2, 2, 1, 384, 240, 240, 156,,,, -5, 7, 1, 6, 2, 2, 2, 2, 128, 240, 240, 156,,,, -5, 7, 1, 6, 2, 2, 2, 2, 256, 240, 240, 156,,,, -5, 7, 1, 6, 2, 2, 2, 2, 384, 240, 240, 156,,,, -5, 7, 1, 6, 3, 3, 1, 1, 128, 240, 240, 156,,,, -5, 7, 1, 6, 3, 3, 1, 1, 256, 240, 240, 156,,,, -5, 7, 1, 6, 3, 3, 1, 1, 384, 240, 240, 156,,,, -5, 7, 1, 6, 3, 3, 1, 2, 128, 240, 240, 156,,,, -5, 7, 1, 6, 3, 3, 1, 2, 256, 240, 240, 156,,,, -5, 7, 1, 6, 3, 3, 1, 2, 384, 240, 240, 156,,,, -5, 7, 1, 6, 3, 3, 1, 3, 128, 240, 240, 156,,,, -5, 7, 1, 6, 3, 3, 1, 3, 256, 240, 240, 156,,,, -5, 7, 1, 6, 3, 3, 1, 3, 384, 240, 240, 156,,,, -5, 7, 1, 6, 3, 3, 2, 1, 128, 240, 240, 156,,,, -5, 7, 1, 6, 3, 3, 2, 1, 256, 240, 240, 156,,,, -5, 7, 1, 6, 3, 3, 2, 1, 384, 240, 240, 156,,,, -5, 7, 1, 6, 3, 3, 2, 2, 128, 240, 240, 156,,,, -5, 7, 1, 6, 3, 3, 2, 2, 256, 240, 240, 156,,,, -5, 7, 1, 6, 3, 3, 2, 2, 384, 240, 240, 156,,,, -5, 7, 1, 6, 3, 3, 2, 3, 128, 240, 240, 156,,,, -5, 7, 1, 6, 3, 3, 2, 3, 256, 240, 240, 156,,,, -5, 7, 1, 6, 3, 3, 2, 3, 384, 240, 240, 156,,,, -5, 7, 1, 6, 3, 3, 3, 1, 128, 240, 240, 156,,,, -5, 7, 1, 6, 3, 3, 3, 1, 256, 240, 240, 156,,,, -5, 7, 1, 6, 3, 3, 3, 1, 384, 240, 240, 156,,,, -5, 7, 1, 6, 3, 3, 3, 2, 128, 240, 240, 156,,,, -5, 7, 1, 6, 3, 3, 3, 2, 256, 240, 240, 156,,,, -5, 7, 1, 6, 3, 3, 3, 2, 384, 240, 240, 156,,,, -5, 7, 1, 6, 3, 3, 3, 3, 128, 240, 240, 156,,,, -5, 7, 1, 6, 3, 3, 3, 3, 256, 240, 240, 156,,,, -5, 7, 1, 6, 3, 3, 3, 3, 384, 240, 240, 156,,,, -5, 7, 1, 7, 1, 1, 1, 1, 128, 240, 240, 181,,,, -5, 7, 1, 7, 1, 1, 1, 1, 256, 240, 240, 181,,,, -5, 7, 1, 7, 1, 1, 1, 1, 384, 240, 240, 181,,,, -5, 7, 1, 7, 2, 2, 1, 1, 128, 240, 240, 181,,,, -5, 7, 1, 7, 2, 2, 1, 1, 256, 240, 240, 181,,,, -5, 7, 1, 7, 2, 2, 1, 1, 384, 240, 240, 181,,,, -5, 7, 1, 7, 2, 2, 1, 2, 128, 240, 240, 181,,,, -5, 7, 1, 7, 2, 2, 1, 2, 256, 240, 240, 181,,,, -5, 7, 1, 7, 2, 2, 1, 2, 384, 240, 240, 181,,,, -5, 7, 1, 7, 2, 2, 2, 1, 128, 240, 240, 181,,,, -5, 7, 1, 7, 2, 2, 2, 1, 256, 240, 240, 181,,,, -5, 7, 1, 7, 2, 2, 2, 1, 384, 240, 240, 181,,,, -5, 7, 1, 7, 2, 2, 2, 2, 128, 240, 240, 181,,,, -5, 7, 1, 7, 2, 2, 2, 2, 256, 240, 240, 181,,,, -5, 7, 1, 7, 2, 2, 2, 2, 384, 240, 240, 181,,,, -5, 7, 1, 7, 3, 3, 1, 1, 128, 240, 240, 181,,,, -5, 7, 1, 7, 3, 3, 1, 1, 256, 240, 240, 181,,,, -5, 7, 1, 7, 3, 3, 1, 1, 384, 240, 240, 181,,,, -5, 7, 1, 7, 3, 3, 1, 2, 128, 240, 240, 181,,,, -5, 7, 1, 7, 3, 3, 1, 2, 256, 240, 240, 181,,,, -5, 7, 1, 7, 3, 3, 1, 2, 384, 240, 240, 181,,,, -5, 7, 1, 7, 3, 3, 1, 3, 128, 240, 240, 181,,,, -5, 7, 1, 7, 3, 3, 1, 3, 256, 240, 240, 181,,,, -5, 7, 1, 7, 3, 3, 1, 3, 384, 240, 240, 181,,,, -5, 7, 1, 7, 3, 3, 2, 1, 128, 240, 240, 181,,,, -5, 7, 1, 7, 3, 3, 2, 1, 256, 240, 240, 181,,,, -5, 7, 1, 7, 3, 3, 2, 1, 384, 240, 240, 181,,,, -5, 7, 1, 7, 3, 3, 2, 2, 128, 240, 240, 181,,,, -5, 7, 1, 7, 3, 3, 2, 2, 256, 240, 240, 181,,,, -5, 7, 1, 7, 3, 3, 2, 2, 384, 240, 240, 181,,,, -5, 7, 1, 7, 3, 3, 2, 3, 128, 240, 240, 181,,,, -5, 7, 1, 7, 3, 3, 2, 3, 256, 240, 240, 181,,,, -5, 7, 1, 7, 3, 3, 2, 3, 384, 240, 240, 181,,,, -5, 7, 1, 7, 3, 3, 3, 1, 128, 240, 240, 181,,,, -5, 7, 1, 7, 3, 3, 3, 1, 256, 240, 240, 181,,,, -5, 7, 1, 7, 3, 3, 3, 1, 384, 240, 240, 181,,,, -5, 7, 1, 7, 3, 3, 3, 2, 128, 240, 240, 181,,,, -5, 7, 1, 7, 3, 3, 3, 2, 256, 240, 240, 181,,,, -5, 7, 1, 7, 3, 3, 3, 2, 384, 240, 240, 181,,,, -5, 7, 1, 7, 3, 3, 3, 3, 128, 240, 240, 181,,,, -5, 7, 1, 7, 3, 3, 3, 3, 256, 240, 240, 181,,,, -5, 7, 1, 7, 3, 3, 3, 3, 384, 240, 240, 181,,,, -5, 7, 2, 1, 1, 1, 1, 1, 128, 82, 57, 31,,,, -5, 7, 2, 1, 1, 1, 1, 1, 256, 82, 57, 31,,,, -5, 7, 2, 1, 1, 1, 1, 1, 384, 82, 57, 31,,,, -5, 7, 2, 1, 2, 2, 1, 1, 128, 82, 57, 31,,,, -5, 7, 2, 1, 2, 2, 1, 1, 256, 82, 57, 31,,,, -5, 7, 2, 1, 2, 2, 1, 1, 384, 82, 57, 31,,,, -5, 7, 2, 1, 2, 2, 1, 2, 128, 82, 57, 31,,,, -5, 7, 2, 1, 2, 2, 1, 2, 256, 82, 57, 31,,,, -5, 7, 2, 1, 2, 2, 1, 2, 384, 82, 57, 31,,,, -5, 7, 2, 1, 2, 2, 2, 1, 128, 82, 57, 31,,,, -5, 7, 2, 1, 2, 2, 2, 1, 256, 82, 57, 31,,,, -5, 7, 2, 1, 2, 2, 2, 1, 384, 82, 57, 31,,,, -5, 7, 2, 1, 2, 2, 2, 2, 128, 82, 57, 31,,,, -5, 7, 2, 1, 2, 2, 2, 2, 256, 82, 57, 31,,,, -5, 7, 2, 1, 2, 2, 2, 2, 384, 82, 57, 31,,,, -5, 7, 2, 1, 3, 3, 1, 1, 128, 82, 57, 31,,,, -5, 7, 2, 1, 3, 3, 1, 1, 256, 82, 57, 31,,,, -5, 7, 2, 1, 3, 3, 1, 1, 384, 82, 57, 31,,,, -5, 7, 2, 1, 3, 3, 1, 2, 128, 82, 57, 31,,,, -5, 7, 2, 1, 3, 3, 1, 2, 256, 82, 57, 31,,,, -5, 7, 2, 1, 3, 3, 1, 2, 384, 82, 57, 31,,,, -5, 7, 2, 1, 3, 3, 1, 3, 128, 82, 57, 31,,,, -5, 7, 2, 1, 3, 3, 1, 3, 256, 82, 57, 31,,,, -5, 7, 2, 1, 3, 3, 1, 3, 384, 82, 57, 31,,,, -5, 7, 2, 1, 3, 3, 2, 1, 128, 82, 57, 31,,,, -5, 7, 2, 1, 3, 3, 2, 1, 256, 82, 57, 31,,,, -5, 7, 2, 1, 3, 3, 2, 1, 384, 82, 57, 31,,,, -5, 7, 2, 1, 3, 3, 2, 2, 128, 82, 57, 31,,,, -5, 7, 2, 1, 3, 3, 2, 2, 256, 82, 57, 31,,,, -5, 7, 2, 1, 3, 3, 2, 2, 384, 82, 57, 31,,,, -5, 7, 2, 1, 3, 3, 2, 3, 128, 82, 57, 31,,,, -5, 7, 2, 1, 3, 3, 2, 3, 256, 82, 57, 31,,,, -5, 7, 2, 1, 3, 3, 2, 3, 384, 82, 57, 31,,,, -5, 7, 2, 1, 3, 3, 3, 1, 128, 82, 57, 31,,,, -5, 7, 2, 1, 3, 3, 3, 1, 256, 82, 57, 31,,,, -5, 7, 2, 1, 3, 3, 3, 1, 384, 82, 57, 31,,,, -5, 7, 2, 1, 3, 3, 3, 2, 128, 82, 57, 31,,,, -5, 7, 2, 1, 3, 3, 3, 2, 256, 82, 57, 31,,,, -5, 7, 2, 1, 3, 3, 3, 2, 384, 82, 57, 31,,,, -5, 7, 2, 1, 3, 3, 3, 3, 128, 82, 57, 31,,,, -5, 7, 2, 1, 3, 3, 3, 3, 256, 82, 57, 31,,,, -5, 7, 2, 1, 3, 3, 3, 3, 384, 82, 57, 31,,,, -5, 7, 2, 2, 1, 1, 1, 1, 128, 158, 108, 56,,,, -5, 7, 2, 2, 1, 1, 1, 1, 256, 158, 108, 56,,,, -5, 7, 2, 2, 1, 1, 1, 1, 384, 158, 108, 56,,,, -5, 7, 2, 2, 2, 2, 1, 1, 128, 158, 108, 56,,,, -5, 7, 2, 2, 2, 2, 1, 1, 256, 158, 108, 56,,,, -5, 7, 2, 2, 2, 2, 1, 1, 384, 158, 108, 56,,,, -5, 7, 2, 2, 2, 2, 1, 2, 128, 158, 108, 56,,,, -5, 7, 2, 2, 2, 2, 1, 2, 256, 158, 108, 56,,,, -5, 7, 2, 2, 2, 2, 1, 2, 384, 158, 108, 56,,,, -5, 7, 2, 2, 2, 2, 2, 1, 128, 158, 108, 56,,,, -5, 7, 2, 2, 2, 2, 2, 1, 256, 158, 108, 56,,,, -5, 7, 2, 2, 2, 2, 2, 1, 384, 158, 108, 56,,,, -5, 7, 2, 2, 2, 2, 2, 2, 128, 158, 108, 56,,,, -5, 7, 2, 2, 2, 2, 2, 2, 256, 158, 108, 56,,,, -5, 7, 2, 2, 2, 2, 2, 2, 384, 158, 108, 56,,,, -5, 7, 2, 2, 3, 3, 1, 1, 128, 158, 108, 56,,,, -5, 7, 2, 2, 3, 3, 1, 1, 256, 158, 108, 56,,,, -5, 7, 2, 2, 3, 3, 1, 1, 384, 158, 108, 56,,,, -5, 7, 2, 2, 3, 3, 1, 2, 128, 158, 108, 56,,,, -5, 7, 2, 2, 3, 3, 1, 2, 256, 158, 108, 56,,,, -5, 7, 2, 2, 3, 3, 1, 2, 384, 158, 108, 56,,,, -5, 7, 2, 2, 3, 3, 1, 3, 128, 158, 108, 56,,,, -5, 7, 2, 2, 3, 3, 1, 3, 256, 158, 108, 56,,,, -5, 7, 2, 2, 3, 3, 1, 3, 384, 158, 108, 56,,,, -5, 7, 2, 2, 3, 3, 2, 1, 128, 158, 108, 56,,,, -5, 7, 2, 2, 3, 3, 2, 1, 256, 158, 108, 56,,,, -5, 7, 2, 2, 3, 3, 2, 1, 384, 158, 108, 56,,,, -5, 7, 2, 2, 3, 3, 2, 2, 128, 158, 108, 56,,,, -5, 7, 2, 2, 3, 3, 2, 2, 256, 158, 108, 56,,,, -5, 7, 2, 2, 3, 3, 2, 2, 384, 158, 108, 56,,,, -5, 7, 2, 2, 3, 3, 2, 3, 128, 158, 108, 56,,,, -5, 7, 2, 2, 3, 3, 2, 3, 256, 158, 108, 56,,,, -5, 7, 2, 2, 3, 3, 2, 3, 384, 158, 108, 56,,,, -5, 7, 2, 2, 3, 3, 3, 1, 128, 158, 108, 56,,,, -5, 7, 2, 2, 3, 3, 3, 1, 256, 158, 108, 56,,,, -5, 7, 2, 2, 3, 3, 3, 1, 384, 158, 108, 56,,,, -5, 7, 2, 2, 3, 3, 3, 2, 128, 158, 108, 56,,,, -5, 7, 2, 2, 3, 3, 3, 2, 256, 158, 108, 56,,,, -5, 7, 2, 2, 3, 3, 3, 2, 384, 158, 108, 56,,,, -5, 7, 2, 2, 3, 3, 3, 3, 128, 158, 108, 56,,,, -5, 7, 2, 2, 3, 3, 3, 3, 256, 158, 108, 56,,,, -5, 7, 2, 2, 3, 3, 3, 3, 384, 158, 108, 56,,,, -5, 7, 2, 3, 1, 1, 1, 1, 128, 234, 159, 81,,,, -5, 7, 2, 3, 1, 1, 1, 1, 256, 234, 159, 81,,,, -5, 7, 2, 3, 1, 1, 1, 1, 384, 234, 159, 81,,,, -5, 7, 2, 3, 2, 2, 1, 1, 128, 234, 159, 81,,,, -5, 7, 2, 3, 2, 2, 1, 1, 256, 234, 159, 81,,,, -5, 7, 2, 3, 2, 2, 1, 1, 384, 234, 159, 81,,,, -5, 7, 2, 3, 2, 2, 1, 2, 128, 234, 159, 81,,,, -5, 7, 2, 3, 2, 2, 1, 2, 256, 234, 159, 81,,,, -5, 7, 2, 3, 2, 2, 1, 2, 384, 234, 159, 81,,,, -5, 7, 2, 3, 2, 2, 2, 1, 128, 234, 159, 81,,,, -5, 7, 2, 3, 2, 2, 2, 1, 256, 234, 159, 81,,,, -5, 7, 2, 3, 2, 2, 2, 1, 384, 234, 159, 81,,,, -5, 7, 2, 3, 2, 2, 2, 2, 128, 234, 159, 81,,,, -5, 7, 2, 3, 2, 2, 2, 2, 256, 234, 159, 81,,,, -5, 7, 2, 3, 2, 2, 2, 2, 384, 234, 159, 81,,,, -5, 7, 2, 3, 3, 3, 1, 1, 128, 234, 159, 81,,,, -5, 7, 2, 3, 3, 3, 1, 1, 256, 234, 159, 81,,,, -5, 7, 2, 3, 3, 3, 1, 1, 384, 234, 159, 81,,,, -5, 7, 2, 3, 3, 3, 1, 2, 128, 234, 159, 81,,,, -5, 7, 2, 3, 3, 3, 1, 2, 256, 234, 159, 81,,,, -5, 7, 2, 3, 3, 3, 1, 2, 384, 234, 159, 81,,,, -5, 7, 2, 3, 3, 3, 1, 3, 128, 234, 159, 81,,,, -5, 7, 2, 3, 3, 3, 1, 3, 256, 234, 159, 81,,,, -5, 7, 2, 3, 3, 3, 1, 3, 384, 234, 159, 81,,,, -5, 7, 2, 3, 3, 3, 2, 1, 128, 234, 159, 81,,,, -5, 7, 2, 3, 3, 3, 2, 1, 256, 234, 159, 81,,,, -5, 7, 2, 3, 3, 3, 2, 1, 384, 234, 159, 81,,,, -5, 7, 2, 3, 3, 3, 2, 2, 128, 234, 159, 81,,,, -5, 7, 2, 3, 3, 3, 2, 2, 256, 234, 159, 81,,,, -5, 7, 2, 3, 3, 3, 2, 2, 384, 234, 159, 81,,,, -5, 7, 2, 3, 3, 3, 2, 3, 128, 234, 159, 81,,,, -5, 7, 2, 3, 3, 3, 2, 3, 256, 234, 159, 81,,,, -5, 7, 2, 3, 3, 3, 2, 3, 384, 234, 159, 81,,,, -5, 7, 2, 3, 3, 3, 3, 1, 128, 234, 159, 81,,,, -5, 7, 2, 3, 3, 3, 3, 1, 256, 234, 159, 81,,,, -5, 7, 2, 3, 3, 3, 3, 1, 384, 234, 159, 81,,,, -5, 7, 2, 3, 3, 3, 3, 2, 128, 234, 159, 81,,,, -5, 7, 2, 3, 3, 3, 3, 2, 256, 234, 159, 81,,,, -5, 7, 2, 3, 3, 3, 3, 2, 384, 234, 159, 81,,,, -5, 7, 2, 3, 3, 3, 3, 3, 128, 234, 159, 81,,,, -5, 7, 2, 3, 3, 3, 3, 3, 256, 234, 159, 81,,,, -5, 7, 2, 3, 3, 3, 3, 3, 384, 234, 159, 81,,,, -5, 7, 2, 4, 1, 1, 1, 1, 128, 240, 210, 106,,,, -5, 7, 2, 4, 1, 1, 1, 1, 256, 240, 210, 106,,,, -5, 7, 2, 4, 1, 1, 1, 1, 384, 240, 210, 106,,,, -5, 7, 2, 4, 2, 2, 1, 1, 128, 240, 210, 106,,,, -5, 7, 2, 4, 2, 2, 1, 1, 256, 240, 210, 106,,,, -5, 7, 2, 4, 2, 2, 1, 1, 384, 240, 210, 106,,,, -5, 7, 2, 4, 2, 2, 1, 2, 128, 240, 210, 106,,,, -5, 7, 2, 4, 2, 2, 1, 2, 256, 240, 210, 106,,,, -5, 7, 2, 4, 2, 2, 1, 2, 384, 240, 210, 106,,,, -5, 7, 2, 4, 2, 2, 2, 1, 128, 240, 210, 106,,,, -5, 7, 2, 4, 2, 2, 2, 1, 256, 240, 210, 106,,,, -5, 7, 2, 4, 2, 2, 2, 1, 384, 240, 210, 106,,,, -5, 7, 2, 4, 2, 2, 2, 2, 128, 240, 210, 106,,,, -5, 7, 2, 4, 2, 2, 2, 2, 256, 240, 210, 106,,,, -5, 7, 2, 4, 2, 2, 2, 2, 384, 240, 210, 106,,,, -5, 7, 2, 4, 3, 3, 1, 1, 128, 240, 210, 106,,,, -5, 7, 2, 4, 3, 3, 1, 1, 256, 240, 210, 106,,,, -5, 7, 2, 4, 3, 3, 1, 1, 384, 240, 210, 106,,,, -5, 7, 2, 4, 3, 3, 1, 2, 128, 240, 210, 106,,,, -5, 7, 2, 4, 3, 3, 1, 2, 256, 240, 210, 106,,,, -5, 7, 2, 4, 3, 3, 1, 2, 384, 240, 210, 106,,,, -5, 7, 2, 4, 3, 3, 1, 3, 128, 240, 210, 106,,,, -5, 7, 2, 4, 3, 3, 1, 3, 256, 240, 210, 106,,,, -5, 7, 2, 4, 3, 3, 1, 3, 384, 240, 210, 106,,,, -5, 7, 2, 4, 3, 3, 2, 1, 128, 240, 210, 106,,,, -5, 7, 2, 4, 3, 3, 2, 1, 256, 240, 210, 106,,,, -5, 7, 2, 4, 3, 3, 2, 1, 384, 240, 210, 106,,,, -5, 7, 2, 4, 3, 3, 2, 2, 128, 240, 210, 106,,,, -5, 7, 2, 4, 3, 3, 2, 2, 256, 240, 210, 106,,,, -5, 7, 2, 4, 3, 3, 2, 2, 384, 240, 210, 106,,,, -5, 7, 2, 4, 3, 3, 2, 3, 128, 240, 210, 106,,,, -5, 7, 2, 4, 3, 3, 2, 3, 256, 240, 210, 106,,,, -5, 7, 2, 4, 3, 3, 2, 3, 384, 240, 210, 106,,,, -5, 7, 2, 4, 3, 3, 3, 1, 128, 240, 210, 106,,,, -5, 7, 2, 4, 3, 3, 3, 1, 256, 240, 210, 106,,,, -5, 7, 2, 4, 3, 3, 3, 1, 384, 240, 210, 106,,,, -5, 7, 2, 4, 3, 3, 3, 2, 128, 240, 210, 106,,,, -5, 7, 2, 4, 3, 3, 3, 2, 256, 240, 210, 106,,,, -5, 7, 2, 4, 3, 3, 3, 2, 384, 240, 210, 106,,,, -5, 7, 2, 4, 3, 3, 3, 3, 128, 240, 210, 106,,,, -5, 7, 2, 4, 3, 3, 3, 3, 256, 240, 210, 106,,,, -5, 7, 2, 4, 3, 3, 3, 3, 384, 240, 210, 106,,,, -5, 7, 2, 5, 1, 1, 1, 1, 128, 240, 240, 131,,,, -5, 7, 2, 5, 1, 1, 1, 1, 256, 240, 240, 131,,,, -5, 7, 2, 5, 1, 1, 1, 1, 384, 240, 240, 131,,,, -5, 7, 2, 5, 2, 2, 1, 1, 128, 240, 240, 131,,,, -5, 7, 2, 5, 2, 2, 1, 1, 256, 240, 240, 131,,,, -5, 7, 2, 5, 2, 2, 1, 1, 384, 240, 240, 131,,,, -5, 7, 2, 5, 2, 2, 1, 2, 128, 240, 240, 131,,,, -5, 7, 2, 5, 2, 2, 1, 2, 256, 240, 240, 131,,,, -5, 7, 2, 5, 2, 2, 1, 2, 384, 240, 240, 131,,,, -5, 7, 2, 5, 2, 2, 2, 1, 128, 240, 240, 131,,,, -5, 7, 2, 5, 2, 2, 2, 1, 256, 240, 240, 131,,,, -5, 7, 2, 5, 2, 2, 2, 1, 384, 240, 240, 131,,,, -5, 7, 2, 5, 2, 2, 2, 2, 128, 240, 240, 131,,,, -5, 7, 2, 5, 2, 2, 2, 2, 256, 240, 240, 131,,,, -5, 7, 2, 5, 2, 2, 2, 2, 384, 240, 240, 131,,,, -5, 7, 2, 5, 3, 3, 1, 1, 128, 240, 240, 131,,,, -5, 7, 2, 5, 3, 3, 1, 1, 256, 240, 240, 131,,,, -5, 7, 2, 5, 3, 3, 1, 1, 384, 240, 240, 131,,,, -5, 7, 2, 5, 3, 3, 1, 2, 128, 240, 240, 131,,,, -5, 7, 2, 5, 3, 3, 1, 2, 256, 240, 240, 131,,,, -5, 7, 2, 5, 3, 3, 1, 2, 384, 240, 240, 131,,,, -5, 7, 2, 5, 3, 3, 1, 3, 128, 240, 240, 131,,,, -5, 7, 2, 5, 3, 3, 1, 3, 256, 240, 240, 131,,,, -5, 7, 2, 5, 3, 3, 1, 3, 384, 240, 240, 131,,,, -5, 7, 2, 5, 3, 3, 2, 1, 128, 240, 240, 131,,,, -5, 7, 2, 5, 3, 3, 2, 1, 256, 240, 240, 131,,,, -5, 7, 2, 5, 3, 3, 2, 1, 384, 240, 240, 131,,,, -5, 7, 2, 5, 3, 3, 2, 2, 128, 240, 240, 131,,,, -5, 7, 2, 5, 3, 3, 2, 2, 256, 240, 240, 131,,,, -5, 7, 2, 5, 3, 3, 2, 2, 384, 240, 240, 131,,,, -5, 7, 2, 5, 3, 3, 2, 3, 128, 240, 240, 131,,,, -5, 7, 2, 5, 3, 3, 2, 3, 256, 240, 240, 131,,,, -5, 7, 2, 5, 3, 3, 2, 3, 384, 240, 240, 131,,,, -5, 7, 2, 5, 3, 3, 3, 1, 128, 240, 240, 131,,,, -5, 7, 2, 5, 3, 3, 3, 1, 256, 240, 240, 131,,,, -5, 7, 2, 5, 3, 3, 3, 1, 384, 240, 240, 131,,,, -5, 7, 2, 5, 3, 3, 3, 2, 128, 240, 240, 131,,,, -5, 7, 2, 5, 3, 3, 3, 2, 256, 240, 240, 131,,,, -5, 7, 2, 5, 3, 3, 3, 2, 384, 240, 240, 131,,,, -5, 7, 2, 5, 3, 3, 3, 3, 128, 240, 240, 131,,,, -5, 7, 2, 5, 3, 3, 3, 3, 256, 240, 240, 131,,,, -5, 7, 2, 5, 3, 3, 3, 3, 384, 240, 240, 131,,,, -5, 7, 2, 6, 1, 1, 1, 1, 128, 240, 240, 156,,,, -5, 7, 2, 6, 1, 1, 1, 1, 256, 240, 240, 156,,,, -5, 7, 2, 6, 1, 1, 1, 1, 384, 240, 240, 156,,,, -5, 7, 2, 6, 2, 2, 1, 1, 128, 240, 240, 156,,,, -5, 7, 2, 6, 2, 2, 1, 1, 256, 240, 240, 156,,,, -5, 7, 2, 6, 2, 2, 1, 1, 384, 240, 240, 156,,,, -5, 7, 2, 6, 2, 2, 1, 2, 128, 240, 240, 156,,,, -5, 7, 2, 6, 2, 2, 1, 2, 256, 240, 240, 156,,,, -5, 7, 2, 6, 2, 2, 1, 2, 384, 240, 240, 156,,,, -5, 7, 2, 6, 2, 2, 2, 1, 128, 240, 240, 156,,,, -5, 7, 2, 6, 2, 2, 2, 1, 256, 240, 240, 156,,,, -5, 7, 2, 6, 2, 2, 2, 1, 384, 240, 240, 156,,,, -5, 7, 2, 6, 2, 2, 2, 2, 128, 240, 240, 156,,,, -5, 7, 2, 6, 2, 2, 2, 2, 256, 240, 240, 156,,,, -5, 7, 2, 6, 2, 2, 2, 2, 384, 240, 240, 156,,,, -5, 7, 2, 6, 3, 3, 1, 1, 128, 240, 240, 156,,,, -5, 7, 2, 6, 3, 3, 1, 1, 256, 240, 240, 156,,,, -5, 7, 2, 6, 3, 3, 1, 1, 384, 240, 240, 156,,,, -5, 7, 2, 6, 3, 3, 1, 2, 128, 240, 240, 156,,,, -5, 7, 2, 6, 3, 3, 1, 2, 256, 240, 240, 156,,,, -5, 7, 2, 6, 3, 3, 1, 2, 384, 240, 240, 156,,,, -5, 7, 2, 6, 3, 3, 1, 3, 128, 240, 240, 156,,,, -5, 7, 2, 6, 3, 3, 1, 3, 256, 240, 240, 156,,,, -5, 7, 2, 6, 3, 3, 1, 3, 384, 240, 240, 156,,,, -5, 7, 2, 6, 3, 3, 2, 1, 128, 240, 240, 156,,,, -5, 7, 2, 6, 3, 3, 2, 1, 256, 240, 240, 156,,,, -5, 7, 2, 6, 3, 3, 2, 1, 384, 240, 240, 156,,,, -5, 7, 2, 6, 3, 3, 2, 2, 128, 240, 240, 156,,,, -5, 7, 2, 6, 3, 3, 2, 2, 256, 240, 240, 156,,,, -5, 7, 2, 6, 3, 3, 2, 2, 384, 240, 240, 156,,,, -5, 7, 2, 6, 3, 3, 2, 3, 128, 240, 240, 156,,,, -5, 7, 2, 6, 3, 3, 2, 3, 256, 240, 240, 156,,,, -5, 7, 2, 6, 3, 3, 2, 3, 384, 240, 240, 156,,,, -5, 7, 2, 6, 3, 3, 3, 1, 128, 240, 240, 156,,,, -5, 7, 2, 6, 3, 3, 3, 1, 256, 240, 240, 156,,,, -5, 7, 2, 6, 3, 3, 3, 1, 384, 240, 240, 156,,,, -5, 7, 2, 6, 3, 3, 3, 2, 128, 240, 240, 156,,,, -5, 7, 2, 6, 3, 3, 3, 2, 256, 240, 240, 156,,,, -5, 7, 2, 6, 3, 3, 3, 2, 384, 240, 240, 156,,,, -5, 7, 2, 6, 3, 3, 3, 3, 128, 240, 240, 156,,,, -5, 7, 2, 6, 3, 3, 3, 3, 256, 240, 240, 156,,,, -5, 7, 2, 6, 3, 3, 3, 3, 384, 240, 240, 156,,,, -5, 7, 2, 7, 1, 1, 1, 1, 128, 240, 240, 181,,,, -5, 7, 2, 7, 1, 1, 1, 1, 256, 240, 240, 181,,,, -5, 7, 2, 7, 1, 1, 1, 1, 384, 240, 240, 181,,,, -5, 7, 2, 7, 2, 2, 1, 1, 128, 240, 240, 181,,,, -5, 7, 2, 7, 2, 2, 1, 1, 256, 240, 240, 181,,,, -5, 7, 2, 7, 2, 2, 1, 1, 384, 240, 240, 181,,,, -5, 7, 2, 7, 2, 2, 1, 2, 128, 240, 240, 181,,,, -5, 7, 2, 7, 2, 2, 1, 2, 256, 240, 240, 181,,,, -5, 7, 2, 7, 2, 2, 1, 2, 384, 240, 240, 181,,,, -5, 7, 2, 7, 2, 2, 2, 1, 128, 240, 240, 181,,,, -5, 7, 2, 7, 2, 2, 2, 1, 256, 240, 240, 181,,,, -5, 7, 2, 7, 2, 2, 2, 1, 384, 240, 240, 181,,,, -5, 7, 2, 7, 2, 2, 2, 2, 128, 240, 240, 181,,,, -5, 7, 2, 7, 2, 2, 2, 2, 256, 240, 240, 181,,,, -5, 7, 2, 7, 2, 2, 2, 2, 384, 240, 240, 181,,,, -5, 7, 2, 7, 3, 3, 1, 1, 128, 240, 240, 181,,,, -5, 7, 2, 7, 3, 3, 1, 1, 256, 240, 240, 181,,,, -5, 7, 2, 7, 3, 3, 1, 1, 384, 240, 240, 181,,,, -5, 7, 2, 7, 3, 3, 1, 2, 128, 240, 240, 181,,,, -5, 7, 2, 7, 3, 3, 1, 2, 256, 240, 240, 181,,,, -5, 7, 2, 7, 3, 3, 1, 2, 384, 240, 240, 181,,,, -5, 7, 2, 7, 3, 3, 1, 3, 128, 240, 240, 181,,,, -5, 7, 2, 7, 3, 3, 1, 3, 256, 240, 240, 181,,,, -5, 7, 2, 7, 3, 3, 1, 3, 384, 240, 240, 181,,,, -5, 7, 2, 7, 3, 3, 2, 1, 128, 240, 240, 181,,,, -5, 7, 2, 7, 3, 3, 2, 1, 256, 240, 240, 181,,,, -5, 7, 2, 7, 3, 3, 2, 1, 384, 240, 240, 181,,,, -5, 7, 2, 7, 3, 3, 2, 2, 128, 240, 240, 181,,,, -5, 7, 2, 7, 3, 3, 2, 2, 256, 240, 240, 181,,,, -5, 7, 2, 7, 3, 3, 2, 2, 384, 240, 240, 181,,,, -5, 7, 2, 7, 3, 3, 2, 3, 128, 240, 240, 181,,,, -5, 7, 2, 7, 3, 3, 2, 3, 256, 240, 240, 181,,,, -5, 7, 2, 7, 3, 3, 2, 3, 384, 240, 240, 181,,,, -5, 7, 2, 7, 3, 3, 3, 1, 128, 240, 240, 181,,,, -5, 7, 2, 7, 3, 3, 3, 1, 256, 240, 240, 181,,,, -5, 7, 2, 7, 3, 3, 3, 1, 384, 240, 240, 181,,,, -5, 7, 2, 7, 3, 3, 3, 2, 128, 240, 240, 181,,,, -5, 7, 2, 7, 3, 3, 3, 2, 256, 240, 240, 181,,,, -5, 7, 2, 7, 3, 3, 3, 2, 384, 240, 240, 181,,,, -5, 7, 2, 7, 3, 3, 3, 3, 128, 240, 240, 181,,,, -5, 7, 2, 7, 3, 3, 3, 3, 256, 240, 240, 181,,,, -5, 7, 2, 7, 3, 3, 3, 3, 384, 240, 240, 181,,,, -5, 7, 3, 1, 1, 1, 1, 1, 128, 82, 57, 31,,,, -5, 7, 3, 1, 1, 1, 1, 1, 256, 82, 57, 31,,,, -5, 7, 3, 1, 1, 1, 1, 1, 384, 82, 57, 31,,,, -5, 7, 3, 1, 2, 2, 1, 1, 128, 82, 57, 31,,,, -5, 7, 3, 1, 2, 2, 1, 1, 256, 82, 57, 31,,,, -5, 7, 3, 1, 2, 2, 1, 1, 384, 82, 57, 31,,,, -5, 7, 3, 1, 2, 2, 1, 2, 128, 82, 57, 31,,,, -5, 7, 3, 1, 2, 2, 1, 2, 256, 82, 57, 31,,,, -5, 7, 3, 1, 2, 2, 1, 2, 384, 82, 57, 31,,,, -5, 7, 3, 1, 2, 2, 2, 1, 128, 82, 57, 31,,,, -5, 7, 3, 1, 2, 2, 2, 1, 256, 82, 57, 31,,,, -5, 7, 3, 1, 2, 2, 2, 1, 384, 82, 57, 31,,,, -5, 7, 3, 1, 2, 2, 2, 2, 128, 82, 57, 31,,,, -5, 7, 3, 1, 2, 2, 2, 2, 256, 82, 57, 31,,,, -5, 7, 3, 1, 2, 2, 2, 2, 384, 82, 57, 31,,,, -5, 7, 3, 1, 3, 3, 1, 1, 128, 82, 57, 31,,,, -5, 7, 3, 1, 3, 3, 1, 1, 256, 82, 57, 31,,,, -5, 7, 3, 1, 3, 3, 1, 1, 384, 82, 57, 31,,,, -5, 7, 3, 1, 3, 3, 1, 2, 128, 82, 57, 31,,,, -5, 7, 3, 1, 3, 3, 1, 2, 256, 82, 57, 31,,,, -5, 7, 3, 1, 3, 3, 1, 2, 384, 82, 57, 31,,,, -5, 7, 3, 1, 3, 3, 1, 3, 128, 82, 57, 31,,,, -5, 7, 3, 1, 3, 3, 1, 3, 256, 82, 57, 31,,,, -5, 7, 3, 1, 3, 3, 1, 3, 384, 82, 57, 31,,,, -5, 7, 3, 1, 3, 3, 2, 1, 128, 82, 57, 31,,,, -5, 7, 3, 1, 3, 3, 2, 1, 256, 82, 57, 31,,,, -5, 7, 3, 1, 3, 3, 2, 1, 384, 82, 57, 31,,,, -5, 7, 3, 1, 3, 3, 2, 2, 128, 82, 57, 31,,,, -5, 7, 3, 1, 3, 3, 2, 2, 256, 82, 57, 31,,,, -5, 7, 3, 1, 3, 3, 2, 2, 384, 82, 57, 31,,,, -5, 7, 3, 1, 3, 3, 2, 3, 128, 82, 57, 31,,,, -5, 7, 3, 1, 3, 3, 2, 3, 256, 82, 57, 31,,,, -5, 7, 3, 1, 3, 3, 2, 3, 384, 82, 57, 31,,,, -5, 7, 3, 1, 3, 3, 3, 1, 128, 82, 57, 31,,,, -5, 7, 3, 1, 3, 3, 3, 1, 256, 82, 57, 31,,,, -5, 7, 3, 1, 3, 3, 3, 1, 384, 82, 57, 31,,,, -5, 7, 3, 1, 3, 3, 3, 2, 128, 82, 57, 31,,,, -5, 7, 3, 1, 3, 3, 3, 2, 256, 82, 57, 31,,,, -5, 7, 3, 1, 3, 3, 3, 2, 384, 82, 57, 31,,,, -5, 7, 3, 1, 3, 3, 3, 3, 128, 82, 57, 31,,,, -5, 7, 3, 1, 3, 3, 3, 3, 256, 82, 57, 31,,,, -5, 7, 3, 1, 3, 3, 3, 3, 384, 82, 57, 31,,,, -5, 7, 3, 2, 1, 1, 1, 1, 128, 158, 108, 56,,,, -5, 7, 3, 2, 1, 1, 1, 1, 256, 158, 108, 56,,,, -5, 7, 3, 2, 1, 1, 1, 1, 384, 158, 108, 56,,,, -5, 7, 3, 2, 2, 2, 1, 1, 128, 158, 108, 56,,,, -5, 7, 3, 2, 2, 2, 1, 1, 256, 158, 108, 56,,,, -5, 7, 3, 2, 2, 2, 1, 1, 384, 158, 108, 56,,,, -5, 7, 3, 2, 2, 2, 1, 2, 128, 158, 108, 56,,,, -5, 7, 3, 2, 2, 2, 1, 2, 256, 158, 108, 56,,,, -5, 7, 3, 2, 2, 2, 1, 2, 384, 158, 108, 56,,,, -5, 7, 3, 2, 2, 2, 2, 1, 128, 158, 108, 56,,,, -5, 7, 3, 2, 2, 2, 2, 1, 256, 158, 108, 56,,,, -5, 7, 3, 2, 2, 2, 2, 1, 384, 158, 108, 56,,,, -5, 7, 3, 2, 2, 2, 2, 2, 128, 158, 108, 56,,,, -5, 7, 3, 2, 2, 2, 2, 2, 256, 158, 108, 56,,,, -5, 7, 3, 2, 2, 2, 2, 2, 384, 158, 108, 56,,,, -5, 7, 3, 2, 3, 3, 1, 1, 128, 158, 108, 56,,,, -5, 7, 3, 2, 3, 3, 1, 1, 256, 158, 108, 56,,,, -5, 7, 3, 2, 3, 3, 1, 1, 384, 158, 108, 56,,,, -5, 7, 3, 2, 3, 3, 1, 2, 128, 158, 108, 56,,,, -5, 7, 3, 2, 3, 3, 1, 2, 256, 158, 108, 56,,,, -5, 7, 3, 2, 3, 3, 1, 2, 384, 158, 108, 56,,,, -5, 7, 3, 2, 3, 3, 1, 3, 128, 158, 108, 56,,,, -5, 7, 3, 2, 3, 3, 1, 3, 256, 158, 108, 56,,,, -5, 7, 3, 2, 3, 3, 1, 3, 384, 158, 108, 56,,,, -5, 7, 3, 2, 3, 3, 2, 1, 128, 158, 108, 56,,,, -5, 7, 3, 2, 3, 3, 2, 1, 256, 158, 108, 56,,,, -5, 7, 3, 2, 3, 3, 2, 1, 384, 158, 108, 56,,,, -5, 7, 3, 2, 3, 3, 2, 2, 128, 158, 108, 56,,,, -5, 7, 3, 2, 3, 3, 2, 2, 256, 158, 108, 56,,,, -5, 7, 3, 2, 3, 3, 2, 2, 384, 158, 108, 56,,,, -5, 7, 3, 2, 3, 3, 2, 3, 128, 158, 108, 56,,,, -5, 7, 3, 2, 3, 3, 2, 3, 256, 158, 108, 56,,,, -5, 7, 3, 2, 3, 3, 2, 3, 384, 158, 108, 56,,,, -5, 7, 3, 2, 3, 3, 3, 1, 128, 158, 108, 56,,,, -5, 7, 3, 2, 3, 3, 3, 1, 256, 158, 108, 56,,,, -5, 7, 3, 2, 3, 3, 3, 1, 384, 158, 108, 56,,,, -5, 7, 3, 2, 3, 3, 3, 2, 128, 158, 108, 56,,,, -5, 7, 3, 2, 3, 3, 3, 2, 256, 158, 108, 56,,,, -5, 7, 3, 2, 3, 3, 3, 2, 384, 158, 108, 56,,,, -5, 7, 3, 2, 3, 3, 3, 3, 128, 158, 108, 56,,,, -5, 7, 3, 2, 3, 3, 3, 3, 256, 158, 108, 56,,,, -5, 7, 3, 2, 3, 3, 3, 3, 384, 158, 108, 56,,,, -5, 7, 3, 3, 1, 1, 1, 1, 128, 234, 159, 81,,,, -5, 7, 3, 3, 1, 1, 1, 1, 256, 234, 159, 81,,,, -5, 7, 3, 3, 1, 1, 1, 1, 384, 234, 159, 81,,,, -5, 7, 3, 3, 2, 2, 1, 1, 128, 234, 159, 81,,,, -5, 7, 3, 3, 2, 2, 1, 1, 256, 234, 159, 81,,,, -5, 7, 3, 3, 2, 2, 1, 1, 384, 234, 159, 81,,,, -5, 7, 3, 3, 2, 2, 1, 2, 128, 234, 159, 81,,,, -5, 7, 3, 3, 2, 2, 1, 2, 256, 234, 159, 81,,,, -5, 7, 3, 3, 2, 2, 1, 2, 384, 234, 159, 81,,,, -5, 7, 3, 3, 2, 2, 2, 1, 128, 234, 159, 81,,,, -5, 7, 3, 3, 2, 2, 2, 1, 256, 234, 159, 81,,,, -5, 7, 3, 3, 2, 2, 2, 1, 384, 234, 159, 81,,,, -5, 7, 3, 3, 2, 2, 2, 2, 128, 234, 159, 81,,,, -5, 7, 3, 3, 2, 2, 2, 2, 256, 234, 159, 81,,,, -5, 7, 3, 3, 2, 2, 2, 2, 384, 234, 159, 81,,,, -5, 7, 3, 3, 3, 3, 1, 1, 128, 234, 159, 81,,,, -5, 7, 3, 3, 3, 3, 1, 1, 256, 234, 159, 81,,,, -5, 7, 3, 3, 3, 3, 1, 1, 384, 234, 159, 81,,,, -5, 7, 3, 3, 3, 3, 1, 2, 128, 234, 159, 81,,,, -5, 7, 3, 3, 3, 3, 1, 2, 256, 234, 159, 81,,,, -5, 7, 3, 3, 3, 3, 1, 2, 384, 234, 159, 81,,,, -5, 7, 3, 3, 3, 3, 1, 3, 128, 234, 159, 81,,,, -5, 7, 3, 3, 3, 3, 1, 3, 256, 234, 159, 81,,,, -5, 7, 3, 3, 3, 3, 1, 3, 384, 234, 159, 81,,,, -5, 7, 3, 3, 3, 3, 2, 1, 128, 234, 159, 81,,,, -5, 7, 3, 3, 3, 3, 2, 1, 256, 234, 159, 81,,,, -5, 7, 3, 3, 3, 3, 2, 1, 384, 234, 159, 81,,,, -5, 7, 3, 3, 3, 3, 2, 2, 128, 234, 159, 81,,,, -5, 7, 3, 3, 3, 3, 2, 2, 256, 234, 159, 81,,,, -5, 7, 3, 3, 3, 3, 2, 2, 384, 234, 159, 81,,,, -5, 7, 3, 3, 3, 3, 2, 3, 128, 234, 159, 81,,,, -5, 7, 3, 3, 3, 3, 2, 3, 256, 234, 159, 81,,,, -5, 7, 3, 3, 3, 3, 2, 3, 384, 234, 159, 81,,,, -5, 7, 3, 3, 3, 3, 3, 1, 128, 234, 159, 81,,,, -5, 7, 3, 3, 3, 3, 3, 1, 256, 234, 159, 81,,,, -5, 7, 3, 3, 3, 3, 3, 1, 384, 234, 159, 81,,,, -5, 7, 3, 3, 3, 3, 3, 2, 128, 234, 159, 81,,,, -5, 7, 3, 3, 3, 3, 3, 2, 256, 234, 159, 81,,,, -5, 7, 3, 3, 3, 3, 3, 2, 384, 234, 159, 81,,,, -5, 7, 3, 3, 3, 3, 3, 3, 128, 234, 159, 81,,,, -5, 7, 3, 3, 3, 3, 3, 3, 256, 234, 159, 81,,,, -5, 7, 3, 3, 3, 3, 3, 3, 384, 234, 159, 81,,,, -5, 7, 3, 4, 1, 1, 1, 1, 128, 240, 210, 106,,,, -5, 7, 3, 4, 1, 1, 1, 1, 256, 240, 210, 106,,,, -5, 7, 3, 4, 1, 1, 1, 1, 384, 240, 210, 106,,,, -5, 7, 3, 4, 2, 2, 1, 1, 128, 240, 210, 106,,,, -5, 7, 3, 4, 2, 2, 1, 1, 256, 240, 210, 106,,,, -5, 7, 3, 4, 2, 2, 1, 1, 384, 240, 210, 106,,,, -5, 7, 3, 4, 2, 2, 1, 2, 128, 240, 210, 106,,,, -5, 7, 3, 4, 2, 2, 1, 2, 256, 240, 210, 106,,,, -5, 7, 3, 4, 2, 2, 1, 2, 384, 240, 210, 106,,,, -5, 7, 3, 4, 2, 2, 2, 1, 128, 240, 210, 106,,,, -5, 7, 3, 4, 2, 2, 2, 1, 256, 240, 210, 106,,,, -5, 7, 3, 4, 2, 2, 2, 1, 384, 240, 210, 106,,,, -5, 7, 3, 4, 2, 2, 2, 2, 128, 240, 210, 106,,,, -5, 7, 3, 4, 2, 2, 2, 2, 256, 240, 210, 106,,,, -5, 7, 3, 4, 2, 2, 2, 2, 384, 240, 210, 106,,,, -5, 7, 3, 4, 3, 3, 1, 1, 128, 240, 210, 106,,,, -5, 7, 3, 4, 3, 3, 1, 1, 256, 240, 210, 106,,,, -5, 7, 3, 4, 3, 3, 1, 1, 384, 240, 210, 106,,,, -5, 7, 3, 4, 3, 3, 1, 2, 128, 240, 210, 106,,,, -5, 7, 3, 4, 3, 3, 1, 2, 256, 240, 210, 106,,,, -5, 7, 3, 4, 3, 3, 1, 2, 384, 240, 210, 106,,,, -5, 7, 3, 4, 3, 3, 1, 3, 128, 240, 210, 106,,,, -5, 7, 3, 4, 3, 3, 1, 3, 256, 240, 210, 106,,,, -5, 7, 3, 4, 3, 3, 1, 3, 384, 240, 210, 106,,,, -5, 7, 3, 4, 3, 3, 2, 1, 128, 240, 210, 106,,,, -5, 7, 3, 4, 3, 3, 2, 1, 256, 240, 210, 106,,,, -5, 7, 3, 4, 3, 3, 2, 1, 384, 240, 210, 106,,,, -5, 7, 3, 4, 3, 3, 2, 2, 128, 240, 210, 106,,,, -5, 7, 3, 4, 3, 3, 2, 2, 256, 240, 210, 106,,,, -5, 7, 3, 4, 3, 3, 2, 2, 384, 240, 210, 106,,,, -5, 7, 3, 4, 3, 3, 2, 3, 128, 240, 210, 106,,,, -5, 7, 3, 4, 3, 3, 2, 3, 256, 240, 210, 106,,,, -5, 7, 3, 4, 3, 3, 2, 3, 384, 240, 210, 106,,,, -5, 7, 3, 4, 3, 3, 3, 1, 128, 240, 210, 106,,,, -5, 7, 3, 4, 3, 3, 3, 1, 256, 240, 210, 106,,,, -5, 7, 3, 4, 3, 3, 3, 1, 384, 240, 210, 106,,,, -5, 7, 3, 4, 3, 3, 3, 2, 128, 240, 210, 106,,,, -5, 7, 3, 4, 3, 3, 3, 2, 256, 240, 210, 106,,,, -5, 7, 3, 4, 3, 3, 3, 2, 384, 240, 210, 106,,,, -5, 7, 3, 4, 3, 3, 3, 3, 128, 240, 210, 106,,,, -5, 7, 3, 4, 3, 3, 3, 3, 256, 240, 210, 106,,,, -5, 7, 3, 4, 3, 3, 3, 3, 384, 240, 210, 106,,,, -5, 7, 3, 5, 1, 1, 1, 1, 128, 240, 240, 131,,,, -5, 7, 3, 5, 1, 1, 1, 1, 256, 240, 240, 131,,,, -5, 7, 3, 5, 1, 1, 1, 1, 384, 240, 240, 131,,,, -5, 7, 3, 5, 2, 2, 1, 1, 128, 240, 240, 131,,,, -5, 7, 3, 5, 2, 2, 1, 1, 256, 240, 240, 131,,,, -5, 7, 3, 5, 2, 2, 1, 1, 384, 240, 240, 131,,,, -5, 7, 3, 5, 2, 2, 1, 2, 128, 240, 240, 131,,,, -5, 7, 3, 5, 2, 2, 1, 2, 256, 240, 240, 131,,,, -5, 7, 3, 5, 2, 2, 1, 2, 384, 240, 240, 131,,,, -5, 7, 3, 5, 2, 2, 2, 1, 128, 240, 240, 131,,,, -5, 7, 3, 5, 2, 2, 2, 1, 256, 240, 240, 131,,,, -5, 7, 3, 5, 2, 2, 2, 1, 384, 240, 240, 131,,,, -5, 7, 3, 5, 2, 2, 2, 2, 128, 240, 240, 131,,,, -5, 7, 3, 5, 2, 2, 2, 2, 256, 240, 240, 131,,,, -5, 7, 3, 5, 2, 2, 2, 2, 384, 240, 240, 131,,,, -5, 7, 3, 5, 3, 3, 1, 1, 128, 240, 240, 131,,,, -5, 7, 3, 5, 3, 3, 1, 1, 256, 240, 240, 131,,,, -5, 7, 3, 5, 3, 3, 1, 1, 384, 240, 240, 131,,,, -5, 7, 3, 5, 3, 3, 1, 2, 128, 240, 240, 131,,,, -5, 7, 3, 5, 3, 3, 1, 2, 256, 240, 240, 131,,,, -5, 7, 3, 5, 3, 3, 1, 2, 384, 240, 240, 131,,,, -5, 7, 3, 5, 3, 3, 1, 3, 128, 240, 240, 131,,,, -5, 7, 3, 5, 3, 3, 1, 3, 256, 240, 240, 131,,,, -5, 7, 3, 5, 3, 3, 1, 3, 384, 240, 240, 131,,,, -5, 7, 3, 5, 3, 3, 2, 1, 128, 240, 240, 131,,,, -5, 7, 3, 5, 3, 3, 2, 1, 256, 240, 240, 131,,,, -5, 7, 3, 5, 3, 3, 2, 1, 384, 240, 240, 131,,,, -5, 7, 3, 5, 3, 3, 2, 2, 128, 240, 240, 131,,,, -5, 7, 3, 5, 3, 3, 2, 2, 256, 240, 240, 131,,,, -5, 7, 3, 5, 3, 3, 2, 2, 384, 240, 240, 131,,,, -5, 7, 3, 5, 3, 3, 2, 3, 128, 240, 240, 131,,,, -5, 7, 3, 5, 3, 3, 2, 3, 256, 240, 240, 131,,,, -5, 7, 3, 5, 3, 3, 2, 3, 384, 240, 240, 131,,,, -5, 7, 3, 5, 3, 3, 3, 1, 128, 240, 240, 131,,,, -5, 7, 3, 5, 3, 3, 3, 1, 256, 240, 240, 131,,,, -5, 7, 3, 5, 3, 3, 3, 1, 384, 240, 240, 131,,,, -5, 7, 3, 5, 3, 3, 3, 2, 128, 240, 240, 131,,,, -5, 7, 3, 5, 3, 3, 3, 2, 256, 240, 240, 131,,,, -5, 7, 3, 5, 3, 3, 3, 2, 384, 240, 240, 131,,,, -5, 7, 3, 5, 3, 3, 3, 3, 128, 240, 240, 131,,,, -5, 7, 3, 5, 3, 3, 3, 3, 256, 240, 240, 131,,,, -5, 7, 3, 5, 3, 3, 3, 3, 384, 240, 240, 131,,,, -5, 7, 3, 6, 1, 1, 1, 1, 128, 240, 240, 156,,,, -5, 7, 3, 6, 1, 1, 1, 1, 256, 240, 240, 156,,,, -5, 7, 3, 6, 1, 1, 1, 1, 384, 240, 240, 156,,,, -5, 7, 3, 6, 2, 2, 1, 1, 128, 240, 240, 156,,,, -5, 7, 3, 6, 2, 2, 1, 1, 256, 240, 240, 156,,,, -5, 7, 3, 6, 2, 2, 1, 1, 384, 240, 240, 156,,,, -5, 7, 3, 6, 2, 2, 1, 2, 128, 240, 240, 156,,,, -5, 7, 3, 6, 2, 2, 1, 2, 256, 240, 240, 156,,,, -5, 7, 3, 6, 2, 2, 1, 2, 384, 240, 240, 156,,,, -5, 7, 3, 6, 2, 2, 2, 1, 128, 240, 240, 156,,,, -5, 7, 3, 6, 2, 2, 2, 1, 256, 240, 240, 156,,,, -5, 7, 3, 6, 2, 2, 2, 1, 384, 240, 240, 156,,,, -5, 7, 3, 6, 2, 2, 2, 2, 128, 240, 240, 156,,,, -5, 7, 3, 6, 2, 2, 2, 2, 256, 240, 240, 156,,,, -5, 7, 3, 6, 2, 2, 2, 2, 384, 240, 240, 156,,,, -5, 7, 3, 6, 3, 3, 1, 1, 128, 240, 240, 156,,,, -5, 7, 3, 6, 3, 3, 1, 1, 256, 240, 240, 156,,,, -5, 7, 3, 6, 3, 3, 1, 1, 384, 240, 240, 156,,,, -5, 7, 3, 6, 3, 3, 1, 2, 128, 240, 240, 156,,,, -5, 7, 3, 6, 3, 3, 1, 2, 256, 240, 240, 156,,,, -5, 7, 3, 6, 3, 3, 1, 2, 384, 240, 240, 156,,,, -5, 7, 3, 6, 3, 3, 1, 3, 128, 240, 240, 156,,,, -5, 7, 3, 6, 3, 3, 1, 3, 256, 240, 240, 156,,,, -5, 7, 3, 6, 3, 3, 1, 3, 384, 240, 240, 156,,,, -5, 7, 3, 6, 3, 3, 2, 1, 128, 240, 240, 156,,,, -5, 7, 3, 6, 3, 3, 2, 1, 256, 240, 240, 156,,,, -5, 7, 3, 6, 3, 3, 2, 1, 384, 240, 240, 156,,,, -5, 7, 3, 6, 3, 3, 2, 2, 128, 240, 240, 156,,,, -5, 7, 3, 6, 3, 3, 2, 2, 256, 240, 240, 156,,,, -5, 7, 3, 6, 3, 3, 2, 2, 384, 240, 240, 156,,,, -5, 7, 3, 6, 3, 3, 2, 3, 128, 240, 240, 156,,,, -5, 7, 3, 6, 3, 3, 2, 3, 256, 240, 240, 156,,,, -5, 7, 3, 6, 3, 3, 2, 3, 384, 240, 240, 156,,,, -5, 7, 3, 6, 3, 3, 3, 1, 128, 240, 240, 156,,,, -5, 7, 3, 6, 3, 3, 3, 1, 256, 240, 240, 156,,,, -5, 7, 3, 6, 3, 3, 3, 1, 384, 240, 240, 156,,,, -5, 7, 3, 6, 3, 3, 3, 2, 128, 240, 240, 156,,,, -5, 7, 3, 6, 3, 3, 3, 2, 256, 240, 240, 156,,,, -5, 7, 3, 6, 3, 3, 3, 2, 384, 240, 240, 156,,,, -5, 7, 3, 6, 3, 3, 3, 3, 128, 240, 240, 156,,,, -5, 7, 3, 6, 3, 3, 3, 3, 256, 240, 240, 156,,,, -5, 7, 3, 6, 3, 3, 3, 3, 384, 240, 240, 156,,,, -5, 7, 3, 7, 1, 1, 1, 1, 128, 240, 240, 181,,,, -5, 7, 3, 7, 1, 1, 1, 1, 256, 240, 240, 181,,,, -5, 7, 3, 7, 1, 1, 1, 1, 384, 240, 240, 181,,,, -5, 7, 3, 7, 2, 2, 1, 1, 128, 240, 240, 181,,,, -5, 7, 3, 7, 2, 2, 1, 1, 256, 240, 240, 181,,,, -5, 7, 3, 7, 2, 2, 1, 1, 384, 240, 240, 181,,,, -5, 7, 3, 7, 2, 2, 1, 2, 128, 240, 240, 181,,,, -5, 7, 3, 7, 2, 2, 1, 2, 256, 240, 240, 181,,,, -5, 7, 3, 7, 2, 2, 1, 2, 384, 240, 240, 181,,,, -5, 7, 3, 7, 2, 2, 2, 1, 128, 240, 240, 181,,,, -5, 7, 3, 7, 2, 2, 2, 1, 256, 240, 240, 181,,,, -5, 7, 3, 7, 2, 2, 2, 1, 384, 240, 240, 181,,,, -5, 7, 3, 7, 2, 2, 2, 2, 128, 240, 240, 181,,,, -5, 7, 3, 7, 2, 2, 2, 2, 256, 240, 240, 181,,,, -5, 7, 3, 7, 2, 2, 2, 2, 384, 240, 240, 181,,,, -5, 7, 3, 7, 3, 3, 1, 1, 128, 240, 240, 181,,,, -5, 7, 3, 7, 3, 3, 1, 1, 256, 240, 240, 181,,,, -5, 7, 3, 7, 3, 3, 1, 1, 384, 240, 240, 181,,,, -5, 7, 3, 7, 3, 3, 1, 2, 128, 240, 240, 181,,,, -5, 7, 3, 7, 3, 3, 1, 2, 256, 240, 240, 181,,,, -5, 7, 3, 7, 3, 3, 1, 2, 384, 240, 240, 181,,,, -5, 7, 3, 7, 3, 3, 1, 3, 128, 240, 240, 181,,,, -5, 7, 3, 7, 3, 3, 1, 3, 256, 240, 240, 181,,,, -5, 7, 3, 7, 3, 3, 1, 3, 384, 240, 240, 181,,,, -5, 7, 3, 7, 3, 3, 2, 1, 128, 240, 240, 181,,,, -5, 7, 3, 7, 3, 3, 2, 1, 256, 240, 240, 181,,,, -5, 7, 3, 7, 3, 3, 2, 1, 384, 240, 240, 181,,,, -5, 7, 3, 7, 3, 3, 2, 2, 128, 240, 240, 181,,,, -5, 7, 3, 7, 3, 3, 2, 2, 256, 240, 240, 181,,,, -5, 7, 3, 7, 3, 3, 2, 2, 384, 240, 240, 181,,,, -5, 7, 3, 7, 3, 3, 2, 3, 128, 240, 240, 181,,,, -5, 7, 3, 7, 3, 3, 2, 3, 256, 240, 240, 181,,,, -5, 7, 3, 7, 3, 3, 2, 3, 384, 240, 240, 181,,,, -5, 7, 3, 7, 3, 3, 3, 1, 128, 240, 240, 181,,,, -5, 7, 3, 7, 3, 3, 3, 1, 256, 240, 240, 181,,,, -5, 7, 3, 7, 3, 3, 3, 1, 384, 240, 240, 181,,,, -5, 7, 3, 7, 3, 3, 3, 2, 128, 240, 240, 181,,,, -5, 7, 3, 7, 3, 3, 3, 2, 256, 240, 240, 181,,,, -5, 7, 3, 7, 3, 3, 3, 2, 384, 240, 240, 181,,,, -5, 7, 3, 7, 3, 3, 3, 3, 128, 240, 240, 181,,,, -5, 7, 3, 7, 3, 3, 3, 3, 256, 240, 240, 181,,,, -5, 7, 3, 7, 3, 3, 3, 3, 384, 240, 240, 181,,,, -5, 7, 4, 1, 1, 1, 1, 1, 128, 82, 57, 31,,,, -5, 7, 4, 1, 1, 1, 1, 1, 256, 82, 57, 31,,,, -5, 7, 4, 1, 1, 1, 1, 1, 384, 82, 57, 31,,,, -5, 7, 4, 1, 2, 2, 1, 1, 128, 82, 57, 31,,,, -5, 7, 4, 1, 2, 2, 1, 1, 256, 82, 57, 31,,,, -5, 7, 4, 1, 2, 2, 1, 1, 384, 82, 57, 31,,,, -5, 7, 4, 1, 2, 2, 1, 2, 128, 82, 57, 31,,,, -5, 7, 4, 1, 2, 2, 1, 2, 256, 82, 57, 31,,,, -5, 7, 4, 1, 2, 2, 1, 2, 384, 82, 57, 31,,,, -5, 7, 4, 1, 2, 2, 2, 1, 128, 82, 57, 31,,,, -5, 7, 4, 1, 2, 2, 2, 1, 256, 82, 57, 31,,,, -5, 7, 4, 1, 2, 2, 2, 1, 384, 82, 57, 31,,,, -5, 7, 4, 1, 2, 2, 2, 2, 128, 82, 57, 31,,,, -5, 7, 4, 1, 2, 2, 2, 2, 256, 82, 57, 31,,,, -5, 7, 4, 1, 2, 2, 2, 2, 384, 82, 57, 31,,,, -5, 7, 4, 1, 3, 3, 1, 1, 128, 82, 57, 31,,,, -5, 7, 4, 1, 3, 3, 1, 1, 256, 82, 57, 31,,,, -5, 7, 4, 1, 3, 3, 1, 1, 384, 82, 57, 31,,,, -5, 7, 4, 1, 3, 3, 1, 2, 128, 82, 57, 31,,,, -5, 7, 4, 1, 3, 3, 1, 2, 256, 82, 57, 31,,,, -5, 7, 4, 1, 3, 3, 1, 2, 384, 82, 57, 31,,,, -5, 7, 4, 1, 3, 3, 1, 3, 128, 82, 57, 31,,,, -5, 7, 4, 1, 3, 3, 1, 3, 256, 82, 57, 31,,,, -5, 7, 4, 1, 3, 3, 1, 3, 384, 82, 57, 31,,,, -5, 7, 4, 1, 3, 3, 2, 1, 128, 82, 57, 31,,,, -5, 7, 4, 1, 3, 3, 2, 1, 256, 82, 57, 31,,,, -5, 7, 4, 1, 3, 3, 2, 1, 384, 82, 57, 31,,,, -5, 7, 4, 1, 3, 3, 2, 2, 128, 82, 57, 31,,,, -5, 7, 4, 1, 3, 3, 2, 2, 256, 82, 57, 31,,,, -5, 7, 4, 1, 3, 3, 2, 2, 384, 82, 57, 31,,,, -5, 7, 4, 1, 3, 3, 2, 3, 128, 82, 57, 31,,,, -5, 7, 4, 1, 3, 3, 2, 3, 256, 82, 57, 31,,,, -5, 7, 4, 1, 3, 3, 2, 3, 384, 82, 57, 31,,,, -5, 7, 4, 1, 3, 3, 3, 1, 128, 82, 57, 31,,,, -5, 7, 4, 1, 3, 3, 3, 1, 256, 82, 57, 31,,,, -5, 7, 4, 1, 3, 3, 3, 1, 384, 82, 57, 31,,,, -5, 7, 4, 1, 3, 3, 3, 2, 128, 82, 57, 31,,,, -5, 7, 4, 1, 3, 3, 3, 2, 256, 82, 57, 31,,,, -5, 7, 4, 1, 3, 3, 3, 2, 384, 82, 57, 31,,,, -5, 7, 4, 1, 3, 3, 3, 3, 128, 82, 57, 31,,,, -5, 7, 4, 1, 3, 3, 3, 3, 256, 82, 57, 31,,,, -5, 7, 4, 1, 3, 3, 3, 3, 384, 82, 57, 31,,,, -5, 7, 4, 2, 1, 1, 1, 1, 128, 158, 108, 56,,,, -5, 7, 4, 2, 1, 1, 1, 1, 256, 158, 108, 56,,,, -5, 7, 4, 2, 1, 1, 1, 1, 384, 158, 108, 56,,,, -5, 7, 4, 2, 2, 2, 1, 1, 128, 158, 108, 56,,,, -5, 7, 4, 2, 2, 2, 1, 1, 256, 158, 108, 56,,,, -5, 7, 4, 2, 2, 2, 1, 1, 384, 158, 108, 56,,,, -5, 7, 4, 2, 2, 2, 1, 2, 128, 158, 108, 56,,,, -5, 7, 4, 2, 2, 2, 1, 2, 256, 158, 108, 56,,,, -5, 7, 4, 2, 2, 2, 1, 2, 384, 158, 108, 56,,,, -5, 7, 4, 2, 2, 2, 2, 1, 128, 158, 108, 56,,,, -5, 7, 4, 2, 2, 2, 2, 1, 256, 158, 108, 56,,,, -5, 7, 4, 2, 2, 2, 2, 1, 384, 158, 108, 56,,,, -5, 7, 4, 2, 2, 2, 2, 2, 128, 158, 108, 56,,,, -5, 7, 4, 2, 2, 2, 2, 2, 256, 158, 108, 56,,,, -5, 7, 4, 2, 2, 2, 2, 2, 384, 158, 108, 56,,,, -5, 7, 4, 2, 3, 3, 1, 1, 128, 158, 108, 56,,,, -5, 7, 4, 2, 3, 3, 1, 1, 256, 158, 108, 56,,,, -5, 7, 4, 2, 3, 3, 1, 1, 384, 158, 108, 56,,,, -5, 7, 4, 2, 3, 3, 1, 2, 128, 158, 108, 56,,,, -5, 7, 4, 2, 3, 3, 1, 2, 256, 158, 108, 56,,,, -5, 7, 4, 2, 3, 3, 1, 2, 384, 158, 108, 56,,,, -5, 7, 4, 2, 3, 3, 1, 3, 128, 158, 108, 56,,,, -5, 7, 4, 2, 3, 3, 1, 3, 256, 158, 108, 56,,,, -5, 7, 4, 2, 3, 3, 1, 3, 384, 158, 108, 56,,,, -5, 7, 4, 2, 3, 3, 2, 1, 128, 158, 108, 56,,,, -5, 7, 4, 2, 3, 3, 2, 1, 256, 158, 108, 56,,,, -5, 7, 4, 2, 3, 3, 2, 1, 384, 158, 108, 56,,,, -5, 7, 4, 2, 3, 3, 2, 2, 128, 158, 108, 56,,,, -5, 7, 4, 2, 3, 3, 2, 2, 256, 158, 108, 56,,,, -5, 7, 4, 2, 3, 3, 2, 2, 384, 158, 108, 56,,,, -5, 7, 4, 2, 3, 3, 2, 3, 128, 158, 108, 56,,,, -5, 7, 4, 2, 3, 3, 2, 3, 256, 158, 108, 56,,,, -5, 7, 4, 2, 3, 3, 2, 3, 384, 158, 108, 56,,,, -5, 7, 4, 2, 3, 3, 3, 1, 128, 158, 108, 56,,,, -5, 7, 4, 2, 3, 3, 3, 1, 256, 158, 108, 56,,,, -5, 7, 4, 2, 3, 3, 3, 1, 384, 158, 108, 56,,,, -5, 7, 4, 2, 3, 3, 3, 2, 128, 158, 108, 56,,,, -5, 7, 4, 2, 3, 3, 3, 2, 256, 158, 108, 56,,,, -5, 7, 4, 2, 3, 3, 3, 2, 384, 158, 108, 56,,,, -5, 7, 4, 2, 3, 3, 3, 3, 128, 158, 108, 56,,,, -5, 7, 4, 2, 3, 3, 3, 3, 256, 158, 108, 56,,,, -5, 7, 4, 2, 3, 3, 3, 3, 384, 158, 108, 56,,,, -5, 7, 4, 3, 1, 1, 1, 1, 128, 234, 159, 81,,,, -5, 7, 4, 3, 1, 1, 1, 1, 256, 234, 159, 81,,,, -5, 7, 4, 3, 1, 1, 1, 1, 384, 234, 159, 81,,,, -5, 7, 4, 3, 2, 2, 1, 1, 128, 234, 159, 81,,,, -5, 7, 4, 3, 2, 2, 1, 1, 256, 234, 159, 81,,,, -5, 7, 4, 3, 2, 2, 1, 1, 384, 234, 159, 81,,,, -5, 7, 4, 3, 2, 2, 1, 2, 128, 234, 159, 81,,,, -5, 7, 4, 3, 2, 2, 1, 2, 256, 234, 159, 81,,,, -5, 7, 4, 3, 2, 2, 1, 2, 384, 234, 159, 81,,,, -5, 7, 4, 3, 2, 2, 2, 1, 128, 234, 159, 81,,,, -5, 7, 4, 3, 2, 2, 2, 1, 256, 234, 159, 81,,,, -5, 7, 4, 3, 2, 2, 2, 1, 384, 234, 159, 81,,,, -5, 7, 4, 3, 2, 2, 2, 2, 128, 234, 159, 81,,,, -5, 7, 4, 3, 2, 2, 2, 2, 256, 234, 159, 81,,,, -5, 7, 4, 3, 2, 2, 2, 2, 384, 234, 159, 81,,,, -5, 7, 4, 3, 3, 3, 1, 1, 128, 234, 159, 81,,,, -5, 7, 4, 3, 3, 3, 1, 1, 256, 234, 159, 81,,,, -5, 7, 4, 3, 3, 3, 1, 1, 384, 234, 159, 81,,,, -5, 7, 4, 3, 3, 3, 1, 2, 128, 234, 159, 81,,,, -5, 7, 4, 3, 3, 3, 1, 2, 256, 234, 159, 81,,,, -5, 7, 4, 3, 3, 3, 1, 2, 384, 234, 159, 81,,,, -5, 7, 4, 3, 3, 3, 1, 3, 128, 234, 159, 81,,,, -5, 7, 4, 3, 3, 3, 1, 3, 256, 234, 159, 81,,,, -5, 7, 4, 3, 3, 3, 1, 3, 384, 234, 159, 81,,,, -5, 7, 4, 3, 3, 3, 2, 1, 128, 234, 159, 81,,,, -5, 7, 4, 3, 3, 3, 2, 1, 256, 234, 159, 81,,,, -5, 7, 4, 3, 3, 3, 2, 1, 384, 234, 159, 81,,,, -5, 7, 4, 3, 3, 3, 2, 2, 128, 234, 159, 81,,,, -5, 7, 4, 3, 3, 3, 2, 2, 256, 234, 159, 81,,,, -5, 7, 4, 3, 3, 3, 2, 2, 384, 234, 159, 81,,,, -5, 7, 4, 3, 3, 3, 2, 3, 128, 234, 159, 81,,,, -5, 7, 4, 3, 3, 3, 2, 3, 256, 234, 159, 81,,,, -5, 7, 4, 3, 3, 3, 2, 3, 384, 234, 159, 81,,,, -5, 7, 4, 3, 3, 3, 3, 1, 128, 234, 159, 81,,,, -5, 7, 4, 3, 3, 3, 3, 1, 256, 234, 159, 81,,,, -5, 7, 4, 3, 3, 3, 3, 1, 384, 234, 159, 81,,,, -5, 7, 4, 3, 3, 3, 3, 2, 128, 234, 159, 81,,,, -5, 7, 4, 3, 3, 3, 3, 2, 256, 234, 159, 81,,,, -5, 7, 4, 3, 3, 3, 3, 2, 384, 234, 159, 81,,,, -5, 7, 4, 3, 3, 3, 3, 3, 128, 234, 159, 81,,,, -5, 7, 4, 3, 3, 3, 3, 3, 256, 234, 159, 81,,,, -5, 7, 4, 3, 3, 3, 3, 3, 384, 234, 159, 81,,,, -5, 7, 4, 4, 1, 1, 1, 1, 128, 240, 210, 106,,,, -5, 7, 4, 4, 1, 1, 1, 1, 256, 240, 210, 106,,,, -5, 7, 4, 4, 1, 1, 1, 1, 384, 240, 210, 106,,,, -5, 7, 4, 4, 2, 2, 1, 1, 128, 240, 210, 106,,,, -5, 7, 4, 4, 2, 2, 1, 1, 256, 240, 210, 106,,,, -5, 7, 4, 4, 2, 2, 1, 1, 384, 240, 210, 106,,,, -5, 7, 4, 4, 2, 2, 1, 2, 128, 240, 210, 106,,,, -5, 7, 4, 4, 2, 2, 1, 2, 256, 240, 210, 106,,,, -5, 7, 4, 4, 2, 2, 1, 2, 384, 240, 210, 106,,,, -5, 7, 4, 4, 2, 2, 2, 1, 128, 240, 210, 106,,,, -5, 7, 4, 4, 2, 2, 2, 1, 256, 240, 210, 106,,,, -5, 7, 4, 4, 2, 2, 2, 1, 384, 240, 210, 106,,,, -5, 7, 4, 4, 2, 2, 2, 2, 128, 240, 210, 106,,,, -5, 7, 4, 4, 2, 2, 2, 2, 256, 240, 210, 106,,,, -5, 7, 4, 4, 2, 2, 2, 2, 384, 240, 210, 106,,,, -5, 7, 4, 4, 3, 3, 1, 1, 128, 240, 210, 106,,,, -5, 7, 4, 4, 3, 3, 1, 1, 256, 240, 210, 106,,,, -5, 7, 4, 4, 3, 3, 1, 1, 384, 240, 210, 106,,,, -5, 7, 4, 4, 3, 3, 1, 2, 128, 240, 210, 106,,,, -5, 7, 4, 4, 3, 3, 1, 2, 256, 240, 210, 106,,,, -5, 7, 4, 4, 3, 3, 1, 2, 384, 240, 210, 106,,,, -5, 7, 4, 4, 3, 3, 1, 3, 128, 240, 210, 106,,,, -5, 7, 4, 4, 3, 3, 1, 3, 256, 240, 210, 106,,,, -5, 7, 4, 4, 3, 3, 1, 3, 384, 240, 210, 106,,,, -5, 7, 4, 4, 3, 3, 2, 1, 128, 240, 210, 106,,,, -5, 7, 4, 4, 3, 3, 2, 1, 256, 240, 210, 106,,,, -5, 7, 4, 4, 3, 3, 2, 1, 384, 240, 210, 106,,,, -5, 7, 4, 4, 3, 3, 2, 2, 128, 240, 210, 106,,,, -5, 7, 4, 4, 3, 3, 2, 2, 256, 240, 210, 106,,,, -5, 7, 4, 4, 3, 3, 2, 2, 384, 240, 210, 106,,,, -5, 7, 4, 4, 3, 3, 2, 3, 128, 240, 210, 106,,,, -5, 7, 4, 4, 3, 3, 2, 3, 256, 240, 210, 106,,,, -5, 7, 4, 4, 3, 3, 2, 3, 384, 240, 210, 106,,,, -5, 7, 4, 4, 3, 3, 3, 1, 128, 240, 210, 106,,,, -5, 7, 4, 4, 3, 3, 3, 1, 256, 240, 210, 106,,,, -5, 7, 4, 4, 3, 3, 3, 1, 384, 240, 210, 106,,,, -5, 7, 4, 4, 3, 3, 3, 2, 128, 240, 210, 106,,,, -5, 7, 4, 4, 3, 3, 3, 2, 256, 240, 210, 106,,,, -5, 7, 4, 4, 3, 3, 3, 2, 384, 240, 210, 106,,,, -5, 7, 4, 4, 3, 3, 3, 3, 128, 240, 210, 106,,,, -5, 7, 4, 4, 3, 3, 3, 3, 256, 240, 210, 106,,,, -5, 7, 4, 4, 3, 3, 3, 3, 384, 240, 210, 106,,,, -5, 7, 4, 5, 1, 1, 1, 1, 128, 240, 240, 131,,,, -5, 7, 4, 5, 1, 1, 1, 1, 256, 240, 240, 131,,,, -5, 7, 4, 5, 1, 1, 1, 1, 384, 240, 240, 131,,,, -5, 7, 4, 5, 2, 2, 1, 1, 128, 240, 240, 131,,,, -5, 7, 4, 5, 2, 2, 1, 1, 256, 240, 240, 131,,,, -5, 7, 4, 5, 2, 2, 1, 1, 384, 240, 240, 131,,,, -5, 7, 4, 5, 2, 2, 1, 2, 128, 240, 240, 131,,,, -5, 7, 4, 5, 2, 2, 1, 2, 256, 240, 240, 131,,,, -5, 7, 4, 5, 2, 2, 1, 2, 384, 240, 240, 131,,,, -5, 7, 4, 5, 2, 2, 2, 1, 128, 240, 240, 131,,,, -5, 7, 4, 5, 2, 2, 2, 1, 256, 240, 240, 131,,,, -5, 7, 4, 5, 2, 2, 2, 1, 384, 240, 240, 131,,,, -5, 7, 4, 5, 2, 2, 2, 2, 128, 240, 240, 131,,,, -5, 7, 4, 5, 2, 2, 2, 2, 256, 240, 240, 131,,,, -5, 7, 4, 5, 2, 2, 2, 2, 384, 240, 240, 131,,,, -5, 7, 4, 5, 3, 3, 1, 1, 128, 240, 240, 131,,,, -5, 7, 4, 5, 3, 3, 1, 1, 256, 240, 240, 131,,,, -5, 7, 4, 5, 3, 3, 1, 1, 384, 240, 240, 131,,,, -5, 7, 4, 5, 3, 3, 1, 2, 128, 240, 240, 131,,,, -5, 7, 4, 5, 3, 3, 1, 2, 256, 240, 240, 131,,,, -5, 7, 4, 5, 3, 3, 1, 2, 384, 240, 240, 131,,,, -5, 7, 4, 5, 3, 3, 1, 3, 128, 240, 240, 131,,,, -5, 7, 4, 5, 3, 3, 1, 3, 256, 240, 240, 131,,,, -5, 7, 4, 5, 3, 3, 1, 3, 384, 240, 240, 131,,,, -5, 7, 4, 5, 3, 3, 2, 1, 128, 240, 240, 131,,,, -5, 7, 4, 5, 3, 3, 2, 1, 256, 240, 240, 131,,,, -5, 7, 4, 5, 3, 3, 2, 1, 384, 240, 240, 131,,,, -5, 7, 4, 5, 3, 3, 2, 2, 128, 240, 240, 131,,,, -5, 7, 4, 5, 3, 3, 2, 2, 256, 240, 240, 131,,,, -5, 7, 4, 5, 3, 3, 2, 2, 384, 240, 240, 131,,,, -5, 7, 4, 5, 3, 3, 2, 3, 128, 240, 240, 131,,,, -5, 7, 4, 5, 3, 3, 2, 3, 256, 240, 240, 131,,,, -5, 7, 4, 5, 3, 3, 2, 3, 384, 240, 240, 131,,,, -5, 7, 4, 5, 3, 3, 3, 1, 128, 240, 240, 131,,,, -5, 7, 4, 5, 3, 3, 3, 1, 256, 240, 240, 131,,,, -5, 7, 4, 5, 3, 3, 3, 1, 384, 240, 240, 131,,,, -5, 7, 4, 5, 3, 3, 3, 2, 128, 240, 240, 131,,,, -5, 7, 4, 5, 3, 3, 3, 2, 256, 240, 240, 131,,,, -5, 7, 4, 5, 3, 3, 3, 2, 384, 240, 240, 131,,,, -5, 7, 4, 5, 3, 3, 3, 3, 128, 240, 240, 131,,,, -5, 7, 4, 5, 3, 3, 3, 3, 256, 240, 240, 131,,,, -5, 7, 4, 5, 3, 3, 3, 3, 384, 240, 240, 131,,,, -5, 7, 4, 6, 1, 1, 1, 1, 128, 240, 240, 156,,,, -5, 7, 4, 6, 1, 1, 1, 1, 256, 240, 240, 156,,,, -5, 7, 4, 6, 1, 1, 1, 1, 384, 240, 240, 156,,,, -5, 7, 4, 6, 2, 2, 1, 1, 128, 240, 240, 156,,,, -5, 7, 4, 6, 2, 2, 1, 1, 256, 240, 240, 156,,,, -5, 7, 4, 6, 2, 2, 1, 1, 384, 240, 240, 156,,,, -5, 7, 4, 6, 2, 2, 1, 2, 128, 240, 240, 156,,,, -5, 7, 4, 6, 2, 2, 1, 2, 256, 240, 240, 156,,,, -5, 7, 4, 6, 2, 2, 1, 2, 384, 240, 240, 156,,,, -5, 7, 4, 6, 2, 2, 2, 1, 128, 240, 240, 156,,,, -5, 7, 4, 6, 2, 2, 2, 1, 256, 240, 240, 156,,,, -5, 7, 4, 6, 2, 2, 2, 1, 384, 240, 240, 156,,,, -5, 7, 4, 6, 2, 2, 2, 2, 128, 240, 240, 156,,,, -5, 7, 4, 6, 2, 2, 2, 2, 256, 240, 240, 156,,,, -5, 7, 4, 6, 2, 2, 2, 2, 384, 240, 240, 156,,,, -5, 7, 4, 6, 3, 3, 1, 1, 128, 240, 240, 156,,,, -5, 7, 4, 6, 3, 3, 1, 1, 256, 240, 240, 156,,,, -5, 7, 4, 6, 3, 3, 1, 1, 384, 240, 240, 156,,,, -5, 7, 4, 6, 3, 3, 1, 2, 128, 240, 240, 156,,,, -5, 7, 4, 6, 3, 3, 1, 2, 256, 240, 240, 156,,,, -5, 7, 4, 6, 3, 3, 1, 2, 384, 240, 240, 156,,,, -5, 7, 4, 6, 3, 3, 1, 3, 128, 240, 240, 156,,,, -5, 7, 4, 6, 3, 3, 1, 3, 256, 240, 240, 156,,,, -5, 7, 4, 6, 3, 3, 1, 3, 384, 240, 240, 156,,,, -5, 7, 4, 6, 3, 3, 2, 1, 128, 240, 240, 156,,,, -5, 7, 4, 6, 3, 3, 2, 1, 256, 240, 240, 156,,,, -5, 7, 4, 6, 3, 3, 2, 1, 384, 240, 240, 156,,,, -5, 7, 4, 6, 3, 3, 2, 2, 128, 240, 240, 156,,,, -5, 7, 4, 6, 3, 3, 2, 2, 256, 240, 240, 156,,,, -5, 7, 4, 6, 3, 3, 2, 2, 384, 240, 240, 156,,,, -5, 7, 4, 6, 3, 3, 2, 3, 128, 240, 240, 156,,,, -5, 7, 4, 6, 3, 3, 2, 3, 256, 240, 240, 156,,,, -5, 7, 4, 6, 3, 3, 2, 3, 384, 240, 240, 156,,,, -5, 7, 4, 6, 3, 3, 3, 1, 128, 240, 240, 156,,,, -5, 7, 4, 6, 3, 3, 3, 1, 256, 240, 240, 156,,,, -5, 7, 4, 6, 3, 3, 3, 1, 384, 240, 240, 156,,,, -5, 7, 4, 6, 3, 3, 3, 2, 128, 240, 240, 156,,,, -5, 7, 4, 6, 3, 3, 3, 2, 256, 240, 240, 156,,,, -5, 7, 4, 6, 3, 3, 3, 2, 384, 240, 240, 156,,,, -5, 7, 4, 6, 3, 3, 3, 3, 128, 240, 240, 156,,,, -5, 7, 4, 6, 3, 3, 3, 3, 256, 240, 240, 156,,,, -5, 7, 4, 6, 3, 3, 3, 3, 384, 240, 240, 156,,,, -5, 7, 4, 7, 1, 1, 1, 1, 128, 240, 240, 181,,,, -5, 7, 4, 7, 1, 1, 1, 1, 256, 240, 240, 181,,,, -5, 7, 4, 7, 1, 1, 1, 1, 384, 240, 240, 181,,,, -5, 7, 4, 7, 2, 2, 1, 1, 128, 240, 240, 181,,,, -5, 7, 4, 7, 2, 2, 1, 1, 256, 240, 240, 181,,,, -5, 7, 4, 7, 2, 2, 1, 1, 384, 240, 240, 181,,,, -5, 7, 4, 7, 2, 2, 1, 2, 128, 240, 240, 181,,,, -5, 7, 4, 7, 2, 2, 1, 2, 256, 240, 240, 181,,,, -5, 7, 4, 7, 2, 2, 1, 2, 384, 240, 240, 181,,,, -5, 7, 4, 7, 2, 2, 2, 1, 128, 240, 240, 181,,,, -5, 7, 4, 7, 2, 2, 2, 1, 256, 240, 240, 181,,,, -5, 7, 4, 7, 2, 2, 2, 1, 384, 240, 240, 181,,,, -5, 7, 4, 7, 2, 2, 2, 2, 128, 240, 240, 181,,,, -5, 7, 4, 7, 2, 2, 2, 2, 256, 240, 240, 181,,,, -5, 7, 4, 7, 2, 2, 2, 2, 384, 240, 240, 181,,,, -5, 7, 4, 7, 3, 3, 1, 1, 128, 240, 240, 181,,,, -5, 7, 4, 7, 3, 3, 1, 1, 256, 240, 240, 181,,,, -5, 7, 4, 7, 3, 3, 1, 1, 384, 240, 240, 181,,,, -5, 7, 4, 7, 3, 3, 1, 2, 128, 240, 240, 181,,,, -5, 7, 4, 7, 3, 3, 1, 2, 256, 240, 240, 181,,,, -5, 7, 4, 7, 3, 3, 1, 2, 384, 240, 240, 181,,,, -5, 7, 4, 7, 3, 3, 1, 3, 128, 240, 240, 181,,,, -5, 7, 4, 7, 3, 3, 1, 3, 256, 240, 240, 181,,,, -5, 7, 4, 7, 3, 3, 1, 3, 384, 240, 240, 181,,,, -5, 7, 4, 7, 3, 3, 2, 1, 128, 240, 240, 181,,,, -5, 7, 4, 7, 3, 3, 2, 1, 256, 240, 240, 181,,,, -5, 7, 4, 7, 3, 3, 2, 1, 384, 240, 240, 181,,,, -5, 7, 4, 7, 3, 3, 2, 2, 128, 240, 240, 181,,,, -5, 7, 4, 7, 3, 3, 2, 2, 256, 240, 240, 181,,,, -5, 7, 4, 7, 3, 3, 2, 2, 384, 240, 240, 181,,,, -5, 7, 4, 7, 3, 3, 2, 3, 128, 240, 240, 181,,,, -5, 7, 4, 7, 3, 3, 2, 3, 256, 240, 240, 181,,,, -5, 7, 4, 7, 3, 3, 2, 3, 384, 240, 240, 181,,,, -5, 7, 4, 7, 3, 3, 3, 1, 128, 240, 240, 181,,,, -5, 7, 4, 7, 3, 3, 3, 1, 256, 240, 240, 181,,,, -5, 7, 4, 7, 3, 3, 3, 1, 384, 240, 240, 181,,,, -5, 7, 4, 7, 3, 3, 3, 2, 128, 240, 240, 181,,,, -5, 7, 4, 7, 3, 3, 3, 2, 256, 240, 240, 181,,,, -5, 7, 4, 7, 3, 3, 3, 2, 384, 240, 240, 181,,,, -5, 7, 4, 7, 3, 3, 3, 3, 128, 240, 240, 181,,,, -5, 7, 4, 7, 3, 3, 3, 3, 256, 240, 240, 181,,,, -5, 7, 4, 7, 3, 3, 3, 3, 384, 240, 240, 181,,,, -5, 7, 5, 1, 1, 1, 1, 1, 128, 82, 57, 31,,,, -5, 7, 5, 1, 1, 1, 1, 1, 256, 82, 57, 31,,,, -5, 7, 5, 1, 1, 1, 1, 1, 384, 82, 57, 31,,,, -5, 7, 5, 1, 2, 2, 1, 1, 128, 82, 57, 31,,,, -5, 7, 5, 1, 2, 2, 1, 1, 256, 82, 57, 31,,,, -5, 7, 5, 1, 2, 2, 1, 1, 384, 82, 57, 31,,,, -5, 7, 5, 1, 2, 2, 1, 2, 128, 82, 57, 31,,,, -5, 7, 5, 1, 2, 2, 1, 2, 256, 82, 57, 31,,,, -5, 7, 5, 1, 2, 2, 1, 2, 384, 82, 57, 31,,,, -5, 7, 5, 1, 2, 2, 2, 1, 128, 82, 57, 31,,,, -5, 7, 5, 1, 2, 2, 2, 1, 256, 82, 57, 31,,,, -5, 7, 5, 1, 2, 2, 2, 1, 384, 82, 57, 31,,,, -5, 7, 5, 1, 2, 2, 2, 2, 128, 82, 57, 31,,,, -5, 7, 5, 1, 2, 2, 2, 2, 256, 82, 57, 31,,,, -5, 7, 5, 1, 2, 2, 2, 2, 384, 82, 57, 31,,,, -5, 7, 5, 1, 3, 3, 1, 1, 128, 82, 57, 31,,,, -5, 7, 5, 1, 3, 3, 1, 1, 256, 82, 57, 31,,,, -5, 7, 5, 1, 3, 3, 1, 1, 384, 82, 57, 31,,,, -5, 7, 5, 1, 3, 3, 1, 2, 128, 82, 57, 31,,,, -5, 7, 5, 1, 3, 3, 1, 2, 256, 82, 57, 31,,,, -5, 7, 5, 1, 3, 3, 1, 2, 384, 82, 57, 31,,,, -5, 7, 5, 1, 3, 3, 1, 3, 128, 82, 57, 31,,,, -5, 7, 5, 1, 3, 3, 1, 3, 256, 82, 57, 31,,,, -5, 7, 5, 1, 3, 3, 1, 3, 384, 82, 57, 31,,,, -5, 7, 5, 1, 3, 3, 2, 1, 128, 82, 57, 31,,,, -5, 7, 5, 1, 3, 3, 2, 1, 256, 82, 57, 31,,,, -5, 7, 5, 1, 3, 3, 2, 1, 384, 82, 57, 31,,,, -5, 7, 5, 1, 3, 3, 2, 2, 128, 82, 57, 31,,,, -5, 7, 5, 1, 3, 3, 2, 2, 256, 82, 57, 31,,,, -5, 7, 5, 1, 3, 3, 2, 2, 384, 82, 57, 31,,,, -5, 7, 5, 1, 3, 3, 2, 3, 128, 82, 57, 31,,,, -5, 7, 5, 1, 3, 3, 2, 3, 256, 82, 57, 31,,,, -5, 7, 5, 1, 3, 3, 2, 3, 384, 82, 57, 31,,,, -5, 7, 5, 1, 3, 3, 3, 1, 128, 82, 57, 31,,,, -5, 7, 5, 1, 3, 3, 3, 1, 256, 82, 57, 31,,,, -5, 7, 5, 1, 3, 3, 3, 1, 384, 82, 57, 31,,,, -5, 7, 5, 1, 3, 3, 3, 2, 128, 82, 57, 31,,,, -5, 7, 5, 1, 3, 3, 3, 2, 256, 82, 57, 31,,,, -5, 7, 5, 1, 3, 3, 3, 2, 384, 82, 57, 31,,,, -5, 7, 5, 1, 3, 3, 3, 3, 128, 82, 57, 31,,,, -5, 7, 5, 1, 3, 3, 3, 3, 256, 82, 57, 31,,,, -5, 7, 5, 1, 3, 3, 3, 3, 384, 82, 57, 31,,,, -5, 7, 5, 2, 1, 1, 1, 1, 128, 158, 108, 56,,,, -5, 7, 5, 2, 1, 1, 1, 1, 256, 158, 108, 56,,,, -5, 7, 5, 2, 1, 1, 1, 1, 384, 158, 108, 56,,,, -5, 7, 5, 2, 2, 2, 1, 1, 128, 158, 108, 56,,,, -5, 7, 5, 2, 2, 2, 1, 1, 256, 158, 108, 56,,,, -5, 7, 5, 2, 2, 2, 1, 1, 384, 158, 108, 56,,,, -5, 7, 5, 2, 2, 2, 1, 2, 128, 158, 108, 56,,,, -5, 7, 5, 2, 2, 2, 1, 2, 256, 158, 108, 56,,,, -5, 7, 5, 2, 2, 2, 1, 2, 384, 158, 108, 56,,,, -5, 7, 5, 2, 2, 2, 2, 1, 128, 158, 108, 56,,,, -5, 7, 5, 2, 2, 2, 2, 1, 256, 158, 108, 56,,,, -5, 7, 5, 2, 2, 2, 2, 1, 384, 158, 108, 56,,,, -5, 7, 5, 2, 2, 2, 2, 2, 128, 158, 108, 56,,,, -5, 7, 5, 2, 2, 2, 2, 2, 256, 158, 108, 56,,,, -5, 7, 5, 2, 2, 2, 2, 2, 384, 158, 108, 56,,,, -5, 7, 5, 2, 3, 3, 1, 1, 128, 158, 108, 56,,,, -5, 7, 5, 2, 3, 3, 1, 1, 256, 158, 108, 56,,,, -5, 7, 5, 2, 3, 3, 1, 1, 384, 158, 108, 56,,,, -5, 7, 5, 2, 3, 3, 1, 2, 128, 158, 108, 56,,,, -5, 7, 5, 2, 3, 3, 1, 2, 256, 158, 108, 56,,,, -5, 7, 5, 2, 3, 3, 1, 2, 384, 158, 108, 56,,,, -5, 7, 5, 2, 3, 3, 1, 3, 128, 158, 108, 56,,,, -5, 7, 5, 2, 3, 3, 1, 3, 256, 158, 108, 56,,,, -5, 7, 5, 2, 3, 3, 1, 3, 384, 158, 108, 56,,,, -5, 7, 5, 2, 3, 3, 2, 1, 128, 158, 108, 56,,,, -5, 7, 5, 2, 3, 3, 2, 1, 256, 158, 108, 56,,,, -5, 7, 5, 2, 3, 3, 2, 1, 384, 158, 108, 56,,,, -5, 7, 5, 2, 3, 3, 2, 2, 128, 158, 108, 56,,,, -5, 7, 5, 2, 3, 3, 2, 2, 256, 158, 108, 56,,,, -5, 7, 5, 2, 3, 3, 2, 2, 384, 158, 108, 56,,,, -5, 7, 5, 2, 3, 3, 2, 3, 128, 158, 108, 56,,,, -5, 7, 5, 2, 3, 3, 2, 3, 256, 158, 108, 56,,,, -5, 7, 5, 2, 3, 3, 2, 3, 384, 158, 108, 56,,,, -5, 7, 5, 2, 3, 3, 3, 1, 128, 158, 108, 56,,,, -5, 7, 5, 2, 3, 3, 3, 1, 256, 158, 108, 56,,,, -5, 7, 5, 2, 3, 3, 3, 1, 384, 158, 108, 56,,,, -5, 7, 5, 2, 3, 3, 3, 2, 128, 158, 108, 56,,,, -5, 7, 5, 2, 3, 3, 3, 2, 256, 158, 108, 56,,,, -5, 7, 5, 2, 3, 3, 3, 2, 384, 158, 108, 56,,,, -5, 7, 5, 2, 3, 3, 3, 3, 128, 158, 108, 56,,,, -5, 7, 5, 2, 3, 3, 3, 3, 256, 158, 108, 56,,,, -5, 7, 5, 2, 3, 3, 3, 3, 384, 158, 108, 56,,,, -5, 7, 5, 3, 1, 1, 1, 1, 128, 234, 159, 81,,,, -5, 7, 5, 3, 1, 1, 1, 1, 256, 234, 159, 81,,,, -5, 7, 5, 3, 1, 1, 1, 1, 384, 234, 159, 81,,,, -5, 7, 5, 3, 2, 2, 1, 1, 128, 234, 159, 81,,,, -5, 7, 5, 3, 2, 2, 1, 1, 256, 234, 159, 81,,,, -5, 7, 5, 3, 2, 2, 1, 1, 384, 234, 159, 81,,,, -5, 7, 5, 3, 2, 2, 1, 2, 128, 234, 159, 81,,,, -5, 7, 5, 3, 2, 2, 1, 2, 256, 234, 159, 81,,,, -5, 7, 5, 3, 2, 2, 1, 2, 384, 234, 159, 81,,,, -5, 7, 5, 3, 2, 2, 2, 1, 128, 234, 159, 81,,,, -5, 7, 5, 3, 2, 2, 2, 1, 256, 234, 159, 81,,,, -5, 7, 5, 3, 2, 2, 2, 1, 384, 234, 159, 81,,,, -5, 7, 5, 3, 2, 2, 2, 2, 128, 234, 159, 81,,,, -5, 7, 5, 3, 2, 2, 2, 2, 256, 234, 159, 81,,,, -5, 7, 5, 3, 2, 2, 2, 2, 384, 234, 159, 81,,,, -5, 7, 5, 3, 3, 3, 1, 1, 128, 234, 159, 81,,,, -5, 7, 5, 3, 3, 3, 1, 1, 256, 234, 159, 81,,,, -5, 7, 5, 3, 3, 3, 1, 1, 384, 234, 159, 81,,,, -5, 7, 5, 3, 3, 3, 1, 2, 128, 234, 159, 81,,,, -5, 7, 5, 3, 3, 3, 1, 2, 256, 234, 159, 81,,,, -5, 7, 5, 3, 3, 3, 1, 2, 384, 234, 159, 81,,,, -5, 7, 5, 3, 3, 3, 1, 3, 128, 234, 159, 81,,,, -5, 7, 5, 3, 3, 3, 1, 3, 256, 234, 159, 81,,,, -5, 7, 5, 3, 3, 3, 1, 3, 384, 234, 159, 81,,,, -5, 7, 5, 3, 3, 3, 2, 1, 128, 234, 159, 81,,,, -5, 7, 5, 3, 3, 3, 2, 1, 256, 234, 159, 81,,,, -5, 7, 5, 3, 3, 3, 2, 1, 384, 234, 159, 81,,,, -5, 7, 5, 3, 3, 3, 2, 2, 128, 234, 159, 81,,,, -5, 7, 5, 3, 3, 3, 2, 2, 256, 234, 159, 81,,,, -5, 7, 5, 3, 3, 3, 2, 2, 384, 234, 159, 81,,,, -5, 7, 5, 3, 3, 3, 2, 3, 128, 234, 159, 81,,,, -5, 7, 5, 3, 3, 3, 2, 3, 256, 234, 159, 81,,,, -5, 7, 5, 3, 3, 3, 2, 3, 384, 234, 159, 81,,,, -5, 7, 5, 3, 3, 3, 3, 1, 128, 234, 159, 81,,,, -5, 7, 5, 3, 3, 3, 3, 1, 256, 234, 159, 81,,,, -5, 7, 5, 3, 3, 3, 3, 1, 384, 234, 159, 81,,,, -5, 7, 5, 3, 3, 3, 3, 2, 128, 234, 159, 81,,,, -5, 7, 5, 3, 3, 3, 3, 2, 256, 234, 159, 81,,,, -5, 7, 5, 3, 3, 3, 3, 2, 384, 234, 159, 81,,,, -5, 7, 5, 3, 3, 3, 3, 3, 128, 234, 159, 81,,,, -5, 7, 5, 3, 3, 3, 3, 3, 256, 234, 159, 81,,,, -5, 7, 5, 3, 3, 3, 3, 3, 384, 234, 159, 81,,,, -5, 7, 5, 4, 1, 1, 1, 1, 128, 240, 210, 106,,,, -5, 7, 5, 4, 1, 1, 1, 1, 256, 240, 210, 106,,,, -5, 7, 5, 4, 1, 1, 1, 1, 384, 240, 210, 106,,,, -5, 7, 5, 4, 2, 2, 1, 1, 128, 240, 210, 106,,,, -5, 7, 5, 4, 2, 2, 1, 1, 256, 240, 210, 106,,,, -5, 7, 5, 4, 2, 2, 1, 1, 384, 240, 210, 106,,,, -5, 7, 5, 4, 2, 2, 1, 2, 128, 240, 210, 106,,,, -5, 7, 5, 4, 2, 2, 1, 2, 256, 240, 210, 106,,,, -5, 7, 5, 4, 2, 2, 1, 2, 384, 240, 210, 106,,,, -5, 7, 5, 4, 2, 2, 2, 1, 128, 240, 210, 106,,,, -5, 7, 5, 4, 2, 2, 2, 1, 256, 240, 210, 106,,,, -5, 7, 5, 4, 2, 2, 2, 1, 384, 240, 210, 106,,,, -5, 7, 5, 4, 2, 2, 2, 2, 128, 240, 210, 106,,,, -5, 7, 5, 4, 2, 2, 2, 2, 256, 240, 210, 106,,,, -5, 7, 5, 4, 2, 2, 2, 2, 384, 240, 210, 106,,,, -5, 7, 5, 4, 3, 3, 1, 1, 128, 240, 210, 106,,,, -5, 7, 5, 4, 3, 3, 1, 1, 256, 240, 210, 106,,,, -5, 7, 5, 4, 3, 3, 1, 1, 384, 240, 210, 106,,,, -5, 7, 5, 4, 3, 3, 1, 2, 128, 240, 210, 106,,,, -5, 7, 5, 4, 3, 3, 1, 2, 256, 240, 210, 106,,,, -5, 7, 5, 4, 3, 3, 1, 2, 384, 240, 210, 106,,,, -5, 7, 5, 4, 3, 3, 1, 3, 128, 240, 210, 106,,,, -5, 7, 5, 4, 3, 3, 1, 3, 256, 240, 210, 106,,,, -5, 7, 5, 4, 3, 3, 1, 3, 384, 240, 210, 106,,,, -5, 7, 5, 4, 3, 3, 2, 1, 128, 240, 210, 106,,,, -5, 7, 5, 4, 3, 3, 2, 1, 256, 240, 210, 106,,,, -5, 7, 5, 4, 3, 3, 2, 1, 384, 240, 210, 106,,,, -5, 7, 5, 4, 3, 3, 2, 2, 128, 240, 210, 106,,,, -5, 7, 5, 4, 3, 3, 2, 2, 256, 240, 210, 106,,,, -5, 7, 5, 4, 3, 3, 2, 2, 384, 240, 210, 106,,,, -5, 7, 5, 4, 3, 3, 2, 3, 128, 240, 210, 106,,,, -5, 7, 5, 4, 3, 3, 2, 3, 256, 240, 210, 106,,,, -5, 7, 5, 4, 3, 3, 2, 3, 384, 240, 210, 106,,,, -5, 7, 5, 4, 3, 3, 3, 1, 128, 240, 210, 106,,,, -5, 7, 5, 4, 3, 3, 3, 1, 256, 240, 210, 106,,,, -5, 7, 5, 4, 3, 3, 3, 1, 384, 240, 210, 106,,,, -5, 7, 5, 4, 3, 3, 3, 2, 128, 240, 210, 106,,,, -5, 7, 5, 4, 3, 3, 3, 2, 256, 240, 210, 106,,,, -5, 7, 5, 4, 3, 3, 3, 2, 384, 240, 210, 106,,,, -5, 7, 5, 4, 3, 3, 3, 3, 128, 240, 210, 106,,,, -5, 7, 5, 4, 3, 3, 3, 3, 256, 240, 210, 106,,,, -5, 7, 5, 4, 3, 3, 3, 3, 384, 240, 210, 106,,,, -5, 7, 5, 5, 1, 1, 1, 1, 128, 240, 240, 131,,,, -5, 7, 5, 5, 1, 1, 1, 1, 256, 240, 240, 131,,,, -5, 7, 5, 5, 1, 1, 1, 1, 384, 240, 240, 131,,,, -5, 7, 5, 5, 2, 2, 1, 1, 128, 240, 240, 131,,,, -5, 7, 5, 5, 2, 2, 1, 1, 256, 240, 240, 131,,,, -5, 7, 5, 5, 2, 2, 1, 1, 384, 240, 240, 131,,,, -5, 7, 5, 5, 2, 2, 1, 2, 128, 240, 240, 131,,,, -5, 7, 5, 5, 2, 2, 1, 2, 256, 240, 240, 131,,,, -5, 7, 5, 5, 2, 2, 1, 2, 384, 240, 240, 131,,,, -5, 7, 5, 5, 2, 2, 2, 1, 128, 240, 240, 131,,,, -5, 7, 5, 5, 2, 2, 2, 1, 256, 240, 240, 131,,,, -5, 7, 5, 5, 2, 2, 2, 1, 384, 240, 240, 131,,,, -5, 7, 5, 5, 2, 2, 2, 2, 128, 240, 240, 131,,,, -5, 7, 5, 5, 2, 2, 2, 2, 256, 240, 240, 131,,,, -5, 7, 5, 5, 2, 2, 2, 2, 384, 240, 240, 131,,,, -5, 7, 5, 5, 3, 3, 1, 1, 128, 240, 240, 131,,,, -5, 7, 5, 5, 3, 3, 1, 1, 256, 240, 240, 131,,,, -5, 7, 5, 5, 3, 3, 1, 1, 384, 240, 240, 131,,,, -5, 7, 5, 5, 3, 3, 1, 2, 128, 240, 240, 131,,,, -5, 7, 5, 5, 3, 3, 1, 2, 256, 240, 240, 131,,,, -5, 7, 5, 5, 3, 3, 1, 2, 384, 240, 240, 131,,,, -5, 7, 5, 5, 3, 3, 1, 3, 128, 240, 240, 131,,,, -5, 7, 5, 5, 3, 3, 1, 3, 256, 240, 240, 131,,,, -5, 7, 5, 5, 3, 3, 1, 3, 384, 240, 240, 131,,,, -5, 7, 5, 5, 3, 3, 2, 1, 128, 240, 240, 131,,,, -5, 7, 5, 5, 3, 3, 2, 1, 256, 240, 240, 131,,,, -5, 7, 5, 5, 3, 3, 2, 1, 384, 240, 240, 131,,,, -5, 7, 5, 5, 3, 3, 2, 2, 128, 240, 240, 131,,,, -5, 7, 5, 5, 3, 3, 2, 2, 256, 240, 240, 131,,,, -5, 7, 5, 5, 3, 3, 2, 2, 384, 240, 240, 131,,,, -5, 7, 5, 5, 3, 3, 2, 3, 128, 240, 240, 131,,,, -5, 7, 5, 5, 3, 3, 2, 3, 256, 240, 240, 131,,,, -5, 7, 5, 5, 3, 3, 2, 3, 384, 240, 240, 131,,,, -5, 7, 5, 5, 3, 3, 3, 1, 128, 240, 240, 131,,,, -5, 7, 5, 5, 3, 3, 3, 1, 256, 240, 240, 131,,,, -5, 7, 5, 5, 3, 3, 3, 1, 384, 240, 240, 131,,,, -5, 7, 5, 5, 3, 3, 3, 2, 128, 240, 240, 131,,,, -5, 7, 5, 5, 3, 3, 3, 2, 256, 240, 240, 131,,,, -5, 7, 5, 5, 3, 3, 3, 2, 384, 240, 240, 131,,,, -5, 7, 5, 5, 3, 3, 3, 3, 128, 240, 240, 131,,,, -5, 7, 5, 5, 3, 3, 3, 3, 256, 240, 240, 131,,,, -5, 7, 5, 5, 3, 3, 3, 3, 384, 240, 240, 131,,,, -5, 7, 5, 6, 1, 1, 1, 1, 128, 240, 240, 156,,,, -5, 7, 5, 6, 1, 1, 1, 1, 256, 240, 240, 156,,,, -5, 7, 5, 6, 1, 1, 1, 1, 384, 240, 240, 156,,,, -5, 7, 5, 6, 2, 2, 1, 1, 128, 240, 240, 156,,,, -5, 7, 5, 6, 2, 2, 1, 1, 256, 240, 240, 156,,,, -5, 7, 5, 6, 2, 2, 1, 1, 384, 240, 240, 156,,,, -5, 7, 5, 6, 2, 2, 1, 2, 128, 240, 240, 156,,,, -5, 7, 5, 6, 2, 2, 1, 2, 256, 240, 240, 156,,,, -5, 7, 5, 6, 2, 2, 1, 2, 384, 240, 240, 156,,,, -5, 7, 5, 6, 2, 2, 2, 1, 128, 240, 240, 156,,,, -5, 7, 5, 6, 2, 2, 2, 1, 256, 240, 240, 156,,,, -5, 7, 5, 6, 2, 2, 2, 1, 384, 240, 240, 156,,,, -5, 7, 5, 6, 2, 2, 2, 2, 128, 240, 240, 156,,,, -5, 7, 5, 6, 2, 2, 2, 2, 256, 240, 240, 156,,,, -5, 7, 5, 6, 2, 2, 2, 2, 384, 240, 240, 156,,,, -5, 7, 5, 6, 3, 3, 1, 1, 128, 240, 240, 156,,,, -5, 7, 5, 6, 3, 3, 1, 1, 256, 240, 240, 156,,,, -5, 7, 5, 6, 3, 3, 1, 1, 384, 240, 240, 156,,,, -5, 7, 5, 6, 3, 3, 1, 2, 128, 240, 240, 156,,,, -5, 7, 5, 6, 3, 3, 1, 2, 256, 240, 240, 156,,,, -5, 7, 5, 6, 3, 3, 1, 2, 384, 240, 240, 156,,,, -5, 7, 5, 6, 3, 3, 1, 3, 128, 240, 240, 156,,,, -5, 7, 5, 6, 3, 3, 1, 3, 256, 240, 240, 156,,,, -5, 7, 5, 6, 3, 3, 1, 3, 384, 240, 240, 156,,,, -5, 7, 5, 6, 3, 3, 2, 1, 128, 240, 240, 156,,,, -5, 7, 5, 6, 3, 3, 2, 1, 256, 240, 240, 156,,,, -5, 7, 5, 6, 3, 3, 2, 1, 384, 240, 240, 156,,,, -5, 7, 5, 6, 3, 3, 2, 2, 128, 240, 240, 156,,,, -5, 7, 5, 6, 3, 3, 2, 2, 256, 240, 240, 156,,,, -5, 7, 5, 6, 3, 3, 2, 2, 384, 240, 240, 156,,,, -5, 7, 5, 6, 3, 3, 2, 3, 128, 240, 240, 156,,,, -5, 7, 5, 6, 3, 3, 2, 3, 256, 240, 240, 156,,,, -5, 7, 5, 6, 3, 3, 2, 3, 384, 240, 240, 156,,,, -5, 7, 5, 6, 3, 3, 3, 1, 128, 240, 240, 156,,,, -5, 7, 5, 6, 3, 3, 3, 1, 256, 240, 240, 156,,,, -5, 7, 5, 6, 3, 3, 3, 1, 384, 240, 240, 156,,,, -5, 7, 5, 6, 3, 3, 3, 2, 128, 240, 240, 156,,,, -5, 7, 5, 6, 3, 3, 3, 2, 256, 240, 240, 156,,,, -5, 7, 5, 6, 3, 3, 3, 2, 384, 240, 240, 156,,,, -5, 7, 5, 6, 3, 3, 3, 3, 128, 240, 240, 156,,,, -5, 7, 5, 6, 3, 3, 3, 3, 256, 240, 240, 156,,,, -5, 7, 5, 6, 3, 3, 3, 3, 384, 240, 240, 156,,,, -5, 7, 5, 7, 1, 1, 1, 1, 128, 240, 240, 181,,,, -5, 7, 5, 7, 1, 1, 1, 1, 256, 240, 240, 181,,,, -5, 7, 5, 7, 1, 1, 1, 1, 384, 240, 240, 181,,,, -5, 7, 5, 7, 2, 2, 1, 1, 128, 240, 240, 181,,,, -5, 7, 5, 7, 2, 2, 1, 1, 256, 240, 240, 181,,,, -5, 7, 5, 7, 2, 2, 1, 1, 384, 240, 240, 181,,,, -5, 7, 5, 7, 2, 2, 1, 2, 128, 240, 240, 181,,,, -5, 7, 5, 7, 2, 2, 1, 2, 256, 240, 240, 181,,,, -5, 7, 5, 7, 2, 2, 1, 2, 384, 240, 240, 181,,,, -5, 7, 5, 7, 2, 2, 2, 1, 128, 240, 240, 181,,,, -5, 7, 5, 7, 2, 2, 2, 1, 256, 240, 240, 181,,,, -5, 7, 5, 7, 2, 2, 2, 1, 384, 240, 240, 181,,,, -5, 7, 5, 7, 2, 2, 2, 2, 128, 240, 240, 181,,,, -5, 7, 5, 7, 2, 2, 2, 2, 256, 240, 240, 181,,,, -5, 7, 5, 7, 2, 2, 2, 2, 384, 240, 240, 181,,,, -5, 7, 5, 7, 3, 3, 1, 1, 128, 240, 240, 181,,,, -5, 7, 5, 7, 3, 3, 1, 1, 256, 240, 240, 181,,,, -5, 7, 5, 7, 3, 3, 1, 1, 384, 240, 240, 181,,,, -5, 7, 5, 7, 3, 3, 1, 2, 128, 240, 240, 181,,,, -5, 7, 5, 7, 3, 3, 1, 2, 256, 240, 240, 181,,,, -5, 7, 5, 7, 3, 3, 1, 2, 384, 240, 240, 181,,,, -5, 7, 5, 7, 3, 3, 1, 3, 128, 240, 240, 181,,,, -5, 7, 5, 7, 3, 3, 1, 3, 256, 240, 240, 181,,,, -5, 7, 5, 7, 3, 3, 1, 3, 384, 240, 240, 181,,,, -5, 7, 5, 7, 3, 3, 2, 1, 128, 240, 240, 181,,,, -5, 7, 5, 7, 3, 3, 2, 1, 256, 240, 240, 181,,,, -5, 7, 5, 7, 3, 3, 2, 1, 384, 240, 240, 181,,,, -5, 7, 5, 7, 3, 3, 2, 2, 128, 240, 240, 181,,,, -5, 7, 5, 7, 3, 3, 2, 2, 256, 240, 240, 181,,,, -5, 7, 5, 7, 3, 3, 2, 2, 384, 240, 240, 181,,,, -5, 7, 5, 7, 3, 3, 2, 3, 128, 240, 240, 181,,,, -5, 7, 5, 7, 3, 3, 2, 3, 256, 240, 240, 181,,,, -5, 7, 5, 7, 3, 3, 2, 3, 384, 240, 240, 181,,,, -5, 7, 5, 7, 3, 3, 3, 1, 128, 240, 240, 181,,,, -5, 7, 5, 7, 3, 3, 3, 1, 256, 240, 240, 181,,,, -5, 7, 5, 7, 3, 3, 3, 1, 384, 240, 240, 181,,,, -5, 7, 5, 7, 3, 3, 3, 2, 128, 240, 240, 181,,,, -5, 7, 5, 7, 3, 3, 3, 2, 256, 240, 240, 181,,,, -5, 7, 5, 7, 3, 3, 3, 2, 384, 240, 240, 181,,,, -5, 7, 5, 7, 3, 3, 3, 3, 128, 240, 240, 181,,,, -5, 7, 5, 7, 3, 3, 3, 3, 256, 240, 240, 181,,,, -5, 7, 5, 7, 3, 3, 3, 3, 384, 240, 240, 181,,,, -6, 1, 1, 1, 1, 1, 1, 1, 128, 64, 64, 64, 64, 42, 21, -6, 1, 1, 1, 1, 1, 1, 1, 256, 64, 64, 64, 64, 42, 21, -6, 1, 1, 1, 1, 1, 1, 1, 384, 64, 64, 64, 64, 42, 21, -6, 1, 2, 1, 1, 1, 1, 1, 128, 64, 64, 64, 64, 42, 21, -6, 1, 2, 1, 1, 1, 1, 1, 256, 64, 64, 64, 64, 42, 21, -6, 1, 2, 1, 1, 1, 1, 1, 384, 64, 64, 64, 64, 42, 21, -6, 1, 3, 1, 1, 1, 1, 1, 128, 64, 64, 64, 64, 42, 21, -6, 1, 3, 1, 1, 1, 1, 1, 256, 64, 64, 64, 64, 42, 21, -6, 1, 3, 1, 1, 1, 1, 1, 384, 64, 64, 64, 64, 42, 21, -6, 1, 4, 1, 1, 1, 1, 1, 128, 64, 64, 64, 64, 42, 21, -6, 1, 4, 1, 1, 1, 1, 1, 256, 64, 64, 64, 64, 42, 21, -6, 1, 4, 1, 1, 1, 1, 1, 384, 64, 64, 64, 64, 42, 21, -6, 1, 5, 1, 1, 1, 1, 1, 128, 64, 64, 64, 64, 42, 21, -6, 1, 5, 1, 1, 1, 1, 1, 256, 64, 64, 64, 64, 42, 21, -6, 1, 5, 1, 1, 1, 1, 1, 384, 64, 64, 64, 64, 42, 21, -6, 1, 6, 1, 1, 1, 1, 1, 128, 64, 64, 64, 64, 42, 21, -6, 1, 6, 1, 1, 1, 1, 1, 256, 64, 64, 64, 64, 42, 21, -6, 1, 6, 1, 1, 1, 1, 1, 384, 64, 64, 64, 64, 42, 21, -6, 2, 1, 1, 1, 1, 1, 1, 128, 65, 65, 65, 43,,, -6, 2, 1, 1, 1, 1, 1, 1, 256, 65, 65, 65, 43,,, -6, 2, 1, 1, 1, 1, 1, 1, 384, 65, 65, 65, 43,,, -6, 2, 1, 1, 2, 2, 1, 1, 128, 65, 65, 64, 43,,, -6, 2, 1, 1, 2, 2, 1, 1, 256, 65, 65, 64, 43,,, -6, 2, 1, 1, 2, 2, 1, 1, 384, 65, 65, 64, 43,,, -6, 2, 1, 1, 2, 2, 1, 2, 128, 65, 65, 64, 43,,, -6, 2, 1, 1, 2, 2, 1, 2, 256, 65, 65, 64, 43,,, -6, 2, 1, 1, 2, 2, 1, 2, 384, 65, 65, 64, 43,,, -6, 2, 1, 1, 2, 2, 2, 1, 128, 65, 65, 64, 43,,, -6, 2, 1, 1, 2, 2, 2, 1, 256, 65, 65, 64, 43,,, -6, 2, 1, 1, 2, 2, 2, 1, 384, 65, 65, 64, 43,,, -6, 2, 1, 1, 2, 2, 2, 2, 128, 65, 65, 64, 43,,, -6, 2, 1, 1, 2, 2, 2, 2, 256, 65, 65, 64, 43,,, -6, 2, 1, 1, 2, 2, 2, 2, 384, 65, 65, 64, 43,,, -6, 2, 1, 2, 1, 1, 1, 1, 128, 129, 129, 129, 85,,, -6, 2, 1, 2, 1, 1, 1, 1, 256, 129, 129, 129, 85,,, -6, 2, 1, 2, 1, 1, 1, 1, 384, 129, 129, 129, 85,,, -6, 2, 1, 2, 2, 2, 1, 1, 128, 129, 129, 127, 85,,, -6, 2, 1, 2, 2, 2, 1, 1, 256, 129, 129, 127, 85,,, -6, 2, 1, 2, 2, 2, 1, 1, 384, 129, 129, 127, 85,,, -6, 2, 1, 2, 2, 2, 1, 2, 128, 129, 129, 127, 85,,, -6, 2, 1, 2, 2, 2, 1, 2, 256, 129, 129, 127, 85,,, -6, 2, 1, 2, 2, 2, 1, 2, 384, 129, 129, 127, 85,,, -6, 2, 1, 2, 2, 2, 2, 1, 128, 129, 129, 127, 85,,, -6, 2, 1, 2, 2, 2, 2, 1, 256, 129, 129, 127, 85,,, -6, 2, 1, 2, 2, 2, 2, 1, 384, 129, 129, 127, 85,,, -6, 2, 1, 2, 2, 2, 2, 2, 128, 129, 129, 127, 85,,, -6, 2, 1, 2, 2, 2, 2, 2, 256, 129, 129, 127, 85,,, -6, 2, 1, 2, 2, 2, 2, 2, 384, 129, 129, 127, 85,,, -6, 2, 2, 1, 1, 1, 1, 1, 128, 65, 65, 65, 43,,, -6, 2, 2, 1, 1, 1, 1, 1, 256, 65, 65, 65, 43,,, -6, 2, 2, 1, 1, 1, 1, 1, 384, 65, 65, 65, 43,,, -6, 2, 2, 1, 2, 2, 1, 1, 128, 65, 65, 64, 43,,, -6, 2, 2, 1, 2, 2, 1, 1, 256, 65, 65, 64, 43,,, -6, 2, 2, 1, 2, 2, 1, 1, 384, 65, 65, 64, 43,,, -6, 2, 2, 1, 2, 2, 1, 2, 128, 65, 65, 64, 43,,, -6, 2, 2, 1, 2, 2, 1, 2, 256, 65, 65, 64, 43,,, -6, 2, 2, 1, 2, 2, 1, 2, 384, 65, 65, 64, 43,,, -6, 2, 2, 1, 2, 2, 2, 1, 128, 65, 65, 64, 43,,, -6, 2, 2, 1, 2, 2, 2, 1, 256, 65, 65, 64, 43,,, -6, 2, 2, 1, 2, 2, 2, 1, 384, 65, 65, 64, 43,,, -6, 2, 2, 1, 2, 2, 2, 2, 128, 65, 65, 64, 43,,, -6, 2, 2, 1, 2, 2, 2, 2, 256, 65, 65, 64, 43,,, -6, 2, 2, 1, 2, 2, 2, 2, 384, 65, 65, 64, 43,,, -6, 2, 2, 2, 1, 1, 1, 1, 128, 129, 129, 129, 85,,, -6, 2, 2, 2, 1, 1, 1, 1, 256, 129, 129, 129, 85,,, -6, 2, 2, 2, 1, 1, 1, 1, 384, 129, 129, 129, 85,,, -6, 2, 2, 2, 2, 2, 1, 1, 128, 129, 129, 127, 85,,, -6, 2, 2, 2, 2, 2, 1, 1, 256, 129, 129, 127, 85,,, -6, 2, 2, 2, 2, 2, 1, 1, 384, 129, 129, 127, 85,,, -6, 2, 2, 2, 2, 2, 1, 2, 128, 129, 129, 127, 85,,, -6, 2, 2, 2, 2, 2, 1, 2, 256, 129, 129, 127, 85,,, -6, 2, 2, 2, 2, 2, 1, 2, 384, 129, 129, 127, 85,,, -6, 2, 2, 2, 2, 2, 2, 1, 128, 129, 129, 127, 85,,, -6, 2, 2, 2, 2, 2, 2, 1, 256, 129, 129, 127, 85,,, -6, 2, 2, 2, 2, 2, 2, 1, 384, 129, 129, 127, 85,,, -6, 2, 2, 2, 2, 2, 2, 2, 128, 129, 129, 127, 85,,, -6, 2, 2, 2, 2, 2, 2, 2, 256, 129, 129, 127, 85,,, -6, 2, 2, 2, 2, 2, 2, 2, 384, 129, 129, 127, 85,,, -6, 2, 3, 1, 1, 1, 1, 1, 128, 65, 65, 65, 43,,, -6, 2, 3, 1, 1, 1, 1, 1, 256, 65, 65, 65, 43,,, -6, 2, 3, 1, 1, 1, 1, 1, 384, 65, 65, 65, 43,,, -6, 2, 3, 1, 2, 2, 1, 1, 128, 65, 65, 64, 43,,, -6, 2, 3, 1, 2, 2, 1, 1, 256, 65, 65, 64, 43,,, -6, 2, 3, 1, 2, 2, 1, 1, 384, 65, 65, 64, 43,,, -6, 2, 3, 1, 2, 2, 1, 2, 128, 65, 65, 64, 43,,, -6, 2, 3, 1, 2, 2, 1, 2, 256, 65, 65, 64, 43,,, -6, 2, 3, 1, 2, 2, 1, 2, 384, 65, 65, 64, 43,,, -6, 2, 3, 1, 2, 2, 2, 1, 128, 65, 65, 64, 43,,, -6, 2, 3, 1, 2, 2, 2, 1, 256, 65, 65, 64, 43,,, -6, 2, 3, 1, 2, 2, 2, 1, 384, 65, 65, 64, 43,,, -6, 2, 3, 1, 2, 2, 2, 2, 128, 65, 65, 64, 43,,, -6, 2, 3, 1, 2, 2, 2, 2, 256, 65, 65, 64, 43,,, -6, 2, 3, 1, 2, 2, 2, 2, 384, 65, 65, 64, 43,,, -6, 2, 3, 2, 1, 1, 1, 1, 128, 129, 129, 129, 85,,, -6, 2, 3, 2, 1, 1, 1, 1, 256, 129, 129, 129, 85,,, -6, 2, 3, 2, 1, 1, 1, 1, 384, 129, 129, 129, 85,,, -6, 2, 3, 2, 2, 2, 1, 1, 128, 129, 129, 127, 85,,, -6, 2, 3, 2, 2, 2, 1, 1, 256, 129, 129, 127, 85,,, -6, 2, 3, 2, 2, 2, 1, 1, 384, 129, 129, 127, 85,,, -6, 2, 3, 2, 2, 2, 1, 2, 128, 129, 129, 127, 85,,, -6, 2, 3, 2, 2, 2, 1, 2, 256, 129, 129, 127, 85,,, -6, 2, 3, 2, 2, 2, 1, 2, 384, 129, 129, 127, 85,,, -6, 2, 3, 2, 2, 2, 2, 1, 128, 129, 129, 127, 85,,, -6, 2, 3, 2, 2, 2, 2, 1, 256, 129, 129, 127, 85,,, -6, 2, 3, 2, 2, 2, 2, 1, 384, 129, 129, 127, 85,,, -6, 2, 3, 2, 2, 2, 2, 2, 128, 129, 129, 127, 85,,, -6, 2, 3, 2, 2, 2, 2, 2, 256, 129, 129, 127, 85,,, -6, 2, 3, 2, 2, 2, 2, 2, 384, 129, 129, 127, 85,,, -6, 2, 4, 1, 1, 1, 1, 1, 128, 65, 65, 65, 43,,, -6, 2, 4, 1, 1, 1, 1, 1, 256, 65, 65, 65, 43,,, -6, 2, 4, 1, 1, 1, 1, 1, 384, 65, 65, 65, 43,,, -6, 2, 4, 1, 2, 2, 1, 1, 128, 65, 65, 64, 43,,, -6, 2, 4, 1, 2, 2, 1, 1, 256, 65, 65, 64, 43,,, -6, 2, 4, 1, 2, 2, 1, 1, 384, 65, 65, 64, 43,,, -6, 2, 4, 1, 2, 2, 1, 2, 128, 65, 65, 64, 43,,, -6, 2, 4, 1, 2, 2, 1, 2, 256, 65, 65, 64, 43,,, -6, 2, 4, 1, 2, 2, 1, 2, 384, 65, 65, 64, 43,,, -6, 2, 4, 1, 2, 2, 2, 1, 128, 65, 65, 64, 43,,, -6, 2, 4, 1, 2, 2, 2, 1, 256, 65, 65, 64, 43,,, -6, 2, 4, 1, 2, 2, 2, 1, 384, 65, 65, 64, 43,,, -6, 2, 4, 1, 2, 2, 2, 2, 128, 65, 65, 64, 43,,, -6, 2, 4, 1, 2, 2, 2, 2, 256, 65, 65, 64, 43,,, -6, 2, 4, 1, 2, 2, 2, 2, 384, 65, 65, 64, 43,,, -6, 2, 4, 2, 1, 1, 1, 1, 128, 129, 129, 129, 85,,, -6, 2, 4, 2, 1, 1, 1, 1, 256, 129, 129, 129, 85,,, -6, 2, 4, 2, 1, 1, 1, 1, 384, 129, 129, 129, 85,,, -6, 2, 4, 2, 2, 2, 1, 1, 128, 129, 129, 127, 85,,, -6, 2, 4, 2, 2, 2, 1, 1, 256, 129, 129, 127, 85,,, -6, 2, 4, 2, 2, 2, 1, 1, 384, 129, 129, 127, 85,,, -6, 2, 4, 2, 2, 2, 1, 2, 128, 129, 129, 127, 85,,, -6, 2, 4, 2, 2, 2, 1, 2, 256, 129, 129, 127, 85,,, -6, 2, 4, 2, 2, 2, 1, 2, 384, 129, 129, 127, 85,,, -6, 2, 4, 2, 2, 2, 2, 1, 128, 129, 129, 127, 85,,, -6, 2, 4, 2, 2, 2, 2, 1, 256, 129, 129, 127, 85,,, -6, 2, 4, 2, 2, 2, 2, 1, 384, 129, 129, 127, 85,,, -6, 2, 4, 2, 2, 2, 2, 2, 128, 129, 129, 127, 85,,, -6, 2, 4, 2, 2, 2, 2, 2, 256, 129, 129, 127, 85,,, -6, 2, 4, 2, 2, 2, 2, 2, 384, 129, 129, 127, 85,,, -6, 2, 5, 1, 1, 1, 1, 1, 128, 65, 65, 65, 43,,, -6, 2, 5, 1, 1, 1, 1, 1, 256, 65, 65, 65, 43,,, -6, 2, 5, 1, 1, 1, 1, 1, 384, 65, 65, 65, 43,,, -6, 2, 5, 1, 2, 2, 1, 1, 128, 65, 65, 64, 43,,, -6, 2, 5, 1, 2, 2, 1, 1, 256, 65, 65, 64, 43,,, -6, 2, 5, 1, 2, 2, 1, 1, 384, 65, 65, 64, 43,,, -6, 2, 5, 1, 2, 2, 1, 2, 128, 65, 65, 64, 43,,, -6, 2, 5, 1, 2, 2, 1, 2, 256, 65, 65, 64, 43,,, -6, 2, 5, 1, 2, 2, 1, 2, 384, 65, 65, 64, 43,,, -6, 2, 5, 1, 2, 2, 2, 1, 128, 65, 65, 64, 43,,, -6, 2, 5, 1, 2, 2, 2, 1, 256, 65, 65, 64, 43,,, -6, 2, 5, 1, 2, 2, 2, 1, 384, 65, 65, 64, 43,,, -6, 2, 5, 1, 2, 2, 2, 2, 128, 65, 65, 64, 43,,, -6, 2, 5, 1, 2, 2, 2, 2, 256, 65, 65, 64, 43,,, -6, 2, 5, 1, 2, 2, 2, 2, 384, 65, 65, 64, 43,,, -6, 2, 5, 2, 1, 1, 1, 1, 128, 129, 129, 129, 85,,, -6, 2, 5, 2, 1, 1, 1, 1, 256, 129, 129, 129, 85,,, -6, 2, 5, 2, 1, 1, 1, 1, 384, 129, 129, 129, 85,,, -6, 2, 5, 2, 2, 2, 1, 1, 128, 129, 129, 127, 85,,, -6, 2, 5, 2, 2, 2, 1, 1, 256, 129, 129, 127, 85,,, -6, 2, 5, 2, 2, 2, 1, 1, 384, 129, 129, 127, 85,,, -6, 2, 5, 2, 2, 2, 1, 2, 128, 129, 129, 127, 85,,, -6, 2, 5, 2, 2, 2, 1, 2, 256, 129, 129, 127, 85,,, -6, 2, 5, 2, 2, 2, 1, 2, 384, 129, 129, 127, 85,,, -6, 2, 5, 2, 2, 2, 2, 1, 128, 129, 129, 127, 85,,, -6, 2, 5, 2, 2, 2, 2, 1, 256, 129, 129, 127, 85,,, -6, 2, 5, 2, 2, 2, 2, 1, 384, 129, 129, 127, 85,,, -6, 2, 5, 2, 2, 2, 2, 2, 128, 129, 129, 127, 85,,, -6, 2, 5, 2, 2, 2, 2, 2, 256, 129, 129, 127, 85,,, -6, 2, 5, 2, 2, 2, 2, 2, 384, 129, 129, 127, 85,,, -6, 2, 6, 1, 1, 1, 1, 1, 128, 65, 65, 65, 43,,, -6, 2, 6, 1, 1, 1, 1, 1, 256, 65, 65, 65, 43,,, -6, 2, 6, 1, 1, 1, 1, 1, 384, 65, 65, 65, 43,,, -6, 2, 6, 1, 2, 2, 1, 1, 128, 65, 65, 64, 43,,, -6, 2, 6, 1, 2, 2, 1, 1, 256, 65, 65, 64, 43,,, -6, 2, 6, 1, 2, 2, 1, 1, 384, 65, 65, 64, 43,,, -6, 2, 6, 1, 2, 2, 1, 2, 128, 65, 65, 64, 43,,, -6, 2, 6, 1, 2, 2, 1, 2, 256, 65, 65, 64, 43,,, -6, 2, 6, 1, 2, 2, 1, 2, 384, 65, 65, 64, 43,,, -6, 2, 6, 1, 2, 2, 2, 1, 128, 65, 65, 64, 43,,, -6, 2, 6, 1, 2, 2, 2, 1, 256, 65, 65, 64, 43,,, -6, 2, 6, 1, 2, 2, 2, 1, 384, 65, 65, 64, 43,,, -6, 2, 6, 1, 2, 2, 2, 2, 128, 65, 65, 64, 43,,, -6, 2, 6, 1, 2, 2, 2, 2, 256, 65, 65, 64, 43,,, -6, 2, 6, 1, 2, 2, 2, 2, 384, 65, 65, 64, 43,,, -6, 2, 6, 2, 1, 1, 1, 1, 128, 129, 129, 129, 85,,, -6, 2, 6, 2, 1, 1, 1, 1, 256, 129, 129, 129, 85,,, -6, 2, 6, 2, 1, 1, 1, 1, 384, 129, 129, 129, 85,,, -6, 2, 6, 2, 2, 2, 1, 1, 128, 129, 129, 127, 85,,, -6, 2, 6, 2, 2, 2, 1, 1, 256, 129, 129, 127, 85,,, -6, 2, 6, 2, 2, 2, 1, 1, 384, 129, 129, 127, 85,,, -6, 2, 6, 2, 2, 2, 1, 2, 128, 129, 129, 127, 85,,, -6, 2, 6, 2, 2, 2, 1, 2, 256, 129, 129, 127, 85,,, -6, 2, 6, 2, 2, 2, 1, 2, 384, 129, 129, 127, 85,,, -6, 2, 6, 2, 2, 2, 2, 1, 128, 129, 129, 127, 85,,, -6, 2, 6, 2, 2, 2, 2, 1, 256, 129, 129, 127, 85,,, -6, 2, 6, 2, 2, 2, 2, 1, 384, 129, 129, 127, 85,,, -6, 2, 6, 2, 2, 2, 2, 2, 128, 129, 129, 127, 85,,, -6, 2, 6, 2, 2, 2, 2, 2, 256, 129, 129, 127, 85,,, -6, 2, 6, 2, 2, 2, 2, 2, 384, 129, 129, 127, 85,,, -6, 3, 1, 1, 1, 1, 1, 1, 128, 66, 66, 44, 23,,, -6, 3, 1, 1, 1, 1, 1, 1, 256, 66, 66, 44, 23,,, -6, 3, 1, 1, 1, 1, 1, 1, 384, 66, 66, 44, 23,,, -6, 3, 1, 1, 2, 2, 1, 1, 128, 66, 66, 44, 23,,, -6, 3, 1, 1, 2, 2, 1, 1, 256, 66, 66, 44, 23,,, -6, 3, 1, 1, 2, 2, 1, 1, 384, 66, 66, 44, 23,,, -6, 3, 1, 1, 2, 2, 1, 2, 128, 66, 66, 44, 23,,, -6, 3, 1, 1, 2, 2, 1, 2, 256, 66, 66, 44, 23,,, -6, 3, 1, 1, 2, 2, 1, 2, 384, 66, 66, 44, 23,,, -6, 3, 1, 1, 2, 2, 2, 1, 128, 66, 66, 44, 23,,, -6, 3, 1, 1, 2, 2, 2, 1, 256, 66, 66, 44, 23,,, -6, 3, 1, 1, 2, 2, 2, 1, 384, 66, 66, 44, 23,,, -6, 3, 1, 1, 2, 2, 2, 2, 128, 66, 66, 44, 23,,, -6, 3, 1, 1, 2, 2, 2, 2, 256, 66, 66, 44, 23,,, -6, 3, 1, 1, 2, 2, 2, 2, 384, 66, 66, 44, 23,,, -6, 3, 1, 1, 3, 3, 1, 1, 128, 66, 66, 44, 23,,, -6, 3, 1, 1, 3, 3, 1, 1, 256, 66, 66, 44, 23,,, -6, 3, 1, 1, 3, 3, 1, 1, 384, 66, 66, 44, 23,,, -6, 3, 1, 1, 3, 3, 1, 2, 128, 66, 66, 44, 23,,, -6, 3, 1, 1, 3, 3, 1, 2, 256, 66, 66, 44, 23,,, -6, 3, 1, 1, 3, 3, 1, 2, 384, 66, 66, 44, 23,,, -6, 3, 1, 1, 3, 3, 1, 3, 128, 66, 66, 44, 23,,, -6, 3, 1, 1, 3, 3, 1, 3, 256, 66, 66, 44, 23,,, -6, 3, 1, 1, 3, 3, 1, 3, 384, 66, 66, 44, 23,,, -6, 3, 1, 1, 3, 3, 2, 1, 128, 66, 66, 44, 23,,, -6, 3, 1, 1, 3, 3, 2, 1, 256, 66, 66, 44, 23,,, -6, 3, 1, 1, 3, 3, 2, 1, 384, 66, 66, 44, 23,,, -6, 3, 1, 1, 3, 3, 2, 2, 128, 66, 66, 44, 23,,, -6, 3, 1, 1, 3, 3, 2, 2, 256, 66, 66, 44, 23,,, -6, 3, 1, 1, 3, 3, 2, 2, 384, 66, 66, 44, 23,,, -6, 3, 1, 1, 3, 3, 2, 3, 128, 66, 66, 44, 23,,, -6, 3, 1, 1, 3, 3, 2, 3, 256, 66, 66, 44, 23,,, -6, 3, 1, 1, 3, 3, 2, 3, 384, 66, 66, 44, 23,,, -6, 3, 1, 1, 3, 3, 3, 1, 128, 66, 66, 44, 23,,, -6, 3, 1, 1, 3, 3, 3, 1, 256, 66, 66, 44, 23,,, -6, 3, 1, 1, 3, 3, 3, 1, 384, 66, 66, 44, 23,,, -6, 3, 1, 1, 3, 3, 3, 2, 128, 66, 66, 44, 23,,, -6, 3, 1, 1, 3, 3, 3, 2, 256, 66, 66, 44, 23,,, -6, 3, 1, 1, 3, 3, 3, 2, 384, 66, 66, 44, 23,,, -6, 3, 1, 1, 3, 3, 3, 3, 128, 66, 66, 44, 23,,, -6, 3, 1, 1, 3, 3, 3, 3, 256, 66, 66, 44, 23,,, -6, 3, 1, 1, 3, 3, 3, 3, 384, 66, 66, 44, 23,,, -6, 3, 1, 2, 1, 1, 1, 1, 128, 130, 130, 86, 44,,, -6, 3, 1, 2, 1, 1, 1, 1, 256, 130, 130, 86, 44,,, -6, 3, 1, 2, 1, 1, 1, 1, 384, 130, 130, 86, 44,,, -6, 3, 1, 2, 2, 2, 1, 1, 128, 130, 130, 86, 44,,, -6, 3, 1, 2, 2, 2, 1, 1, 256, 130, 130, 86, 44,,, -6, 3, 1, 2, 2, 2, 1, 1, 384, 130, 130, 86, 44,,, -6, 3, 1, 2, 2, 2, 1, 2, 128, 130, 130, 86, 44,,, -6, 3, 1, 2, 2, 2, 1, 2, 256, 130, 130, 86, 44,,, -6, 3, 1, 2, 2, 2, 1, 2, 384, 130, 130, 86, 44,,, -6, 3, 1, 2, 2, 2, 2, 1, 128, 130, 130, 86, 44,,, -6, 3, 1, 2, 2, 2, 2, 1, 256, 130, 130, 86, 44,,, -6, 3, 1, 2, 2, 2, 2, 1, 384, 130, 130, 86, 44,,, -6, 3, 1, 2, 2, 2, 2, 2, 128, 130, 130, 86, 44,,, -6, 3, 1, 2, 2, 2, 2, 2, 256, 130, 130, 86, 44,,, -6, 3, 1, 2, 2, 2, 2, 2, 384, 130, 130, 86, 44,,, -6, 3, 1, 2, 3, 3, 1, 1, 128, 130, 130, 86, 44,,, -6, 3, 1, 2, 3, 3, 1, 1, 256, 130, 130, 86, 44,,, -6, 3, 1, 2, 3, 3, 1, 1, 384, 130, 130, 86, 44,,, -6, 3, 1, 2, 3, 3, 1, 2, 128, 130, 130, 86, 44,,, -6, 3, 1, 2, 3, 3, 1, 2, 256, 130, 130, 86, 44,,, -6, 3, 1, 2, 3, 3, 1, 2, 384, 130, 130, 86, 44,,, -6, 3, 1, 2, 3, 3, 1, 3, 128, 130, 130, 86, 44,,, -6, 3, 1, 2, 3, 3, 1, 3, 256, 130, 130, 86, 44,,, -6, 3, 1, 2, 3, 3, 1, 3, 384, 130, 130, 86, 44,,, -6, 3, 1, 2, 3, 3, 2, 1, 128, 130, 130, 86, 44,,, -6, 3, 1, 2, 3, 3, 2, 1, 256, 130, 130, 86, 44,,, -6, 3, 1, 2, 3, 3, 2, 1, 384, 130, 130, 86, 44,,, -6, 3, 1, 2, 3, 3, 2, 2, 128, 130, 130, 86, 44,,, -6, 3, 1, 2, 3, 3, 2, 2, 256, 130, 130, 86, 44,,, -6, 3, 1, 2, 3, 3, 2, 2, 384, 130, 130, 86, 44,,, -6, 3, 1, 2, 3, 3, 2, 3, 128, 130, 130, 86, 44,,, -6, 3, 1, 2, 3, 3, 2, 3, 256, 130, 130, 86, 44,,, -6, 3, 1, 2, 3, 3, 2, 3, 384, 130, 130, 86, 44,,, -6, 3, 1, 2, 3, 3, 3, 1, 128, 130, 130, 86, 44,,, -6, 3, 1, 2, 3, 3, 3, 1, 256, 130, 130, 86, 44,,, -6, 3, 1, 2, 3, 3, 3, 1, 384, 130, 130, 86, 44,,, -6, 3, 1, 2, 3, 3, 3, 2, 128, 130, 130, 86, 44,,, -6, 3, 1, 2, 3, 3, 3, 2, 256, 130, 130, 86, 44,,, -6, 3, 1, 2, 3, 3, 3, 2, 384, 130, 130, 86, 44,,, -6, 3, 1, 2, 3, 3, 3, 3, 128, 130, 130, 86, 44,,, -6, 3, 1, 2, 3, 3, 3, 3, 256, 130, 130, 86, 44,,, -6, 3, 1, 2, 3, 3, 3, 3, 384, 130, 130, 86, 44,,, -6, 3, 1, 3, 1, 1, 1, 1, 128, 194, 194, 128, 65,,, -6, 3, 1, 3, 1, 1, 1, 1, 256, 194, 194, 128, 65,,, -6, 3, 1, 3, 1, 1, 1, 1, 384, 194, 194, 128, 65,,, -6, 3, 1, 3, 2, 2, 1, 1, 128, 194, 194, 128, 65,,, -6, 3, 1, 3, 2, 2, 1, 1, 256, 194, 194, 128, 65,,, -6, 3, 1, 3, 2, 2, 1, 1, 384, 194, 194, 128, 65,,, -6, 3, 1, 3, 2, 2, 1, 2, 128, 194, 194, 128, 65,,, -6, 3, 1, 3, 2, 2, 1, 2, 256, 194, 194, 128, 65,,, -6, 3, 1, 3, 2, 2, 1, 2, 384, 194, 194, 128, 65,,, -6, 3, 1, 3, 2, 2, 2, 1, 128, 194, 194, 128, 65,,, -6, 3, 1, 3, 2, 2, 2, 1, 256, 194, 194, 128, 65,,, -6, 3, 1, 3, 2, 2, 2, 1, 384, 194, 194, 128, 65,,, -6, 3, 1, 3, 2, 2, 2, 2, 128, 194, 194, 128, 65,,, -6, 3, 1, 3, 2, 2, 2, 2, 256, 194, 194, 128, 65,,, -6, 3, 1, 3, 2, 2, 2, 2, 384, 194, 194, 128, 65,,, -6, 3, 1, 3, 3, 3, 1, 1, 128, 194, 194, 128, 65,,, -6, 3, 1, 3, 3, 3, 1, 1, 256, 194, 194, 128, 65,,, -6, 3, 1, 3, 3, 3, 1, 1, 384, 194, 194, 128, 65,,, -6, 3, 1, 3, 3, 3, 1, 2, 128, 194, 194, 128, 65,,, -6, 3, 1, 3, 3, 3, 1, 2, 256, 194, 194, 128, 65,,, -6, 3, 1, 3, 3, 3, 1, 2, 384, 194, 194, 128, 65,,, -6, 3, 1, 3, 3, 3, 1, 3, 128, 194, 194, 128, 65,,, -6, 3, 1, 3, 3, 3, 1, 3, 256, 194, 194, 128, 65,,, -6, 3, 1, 3, 3, 3, 1, 3, 384, 194, 194, 128, 65,,, -6, 3, 1, 3, 3, 3, 2, 1, 128, 194, 194, 128, 65,,, -6, 3, 1, 3, 3, 3, 2, 1, 256, 194, 194, 128, 65,,, -6, 3, 1, 3, 3, 3, 2, 1, 384, 194, 194, 128, 65,,, -6, 3, 1, 3, 3, 3, 2, 2, 128, 194, 194, 128, 65,,, -6, 3, 1, 3, 3, 3, 2, 2, 256, 194, 194, 128, 65,,, -6, 3, 1, 3, 3, 3, 2, 2, 384, 194, 194, 128, 65,,, -6, 3, 1, 3, 3, 3, 2, 3, 128, 194, 194, 128, 65,,, -6, 3, 1, 3, 3, 3, 2, 3, 256, 194, 194, 128, 65,,, -6, 3, 1, 3, 3, 3, 2, 3, 384, 194, 194, 128, 65,,, -6, 3, 1, 3, 3, 3, 3, 1, 128, 194, 194, 128, 65,,, -6, 3, 1, 3, 3, 3, 3, 1, 256, 194, 194, 128, 65,,, -6, 3, 1, 3, 3, 3, 3, 1, 384, 194, 194, 128, 65,,, -6, 3, 1, 3, 3, 3, 3, 2, 128, 194, 194, 128, 65,,, -6, 3, 1, 3, 3, 3, 3, 2, 256, 194, 194, 128, 65,,, -6, 3, 1, 3, 3, 3, 3, 2, 384, 194, 194, 128, 65,,, -6, 3, 1, 3, 3, 3, 3, 3, 128, 194, 194, 128, 65,,, -6, 3, 1, 3, 3, 3, 3, 3, 256, 194, 194, 128, 65,,, -6, 3, 1, 3, 3, 3, 3, 3, 384, 194, 194, 128, 65,,, -6, 3, 2, 1, 1, 1, 1, 1, 128, 66, 66, 44, 23,,, -6, 3, 2, 1, 1, 1, 1, 1, 256, 66, 66, 44, 23,,, -6, 3, 2, 1, 1, 1, 1, 1, 384, 66, 66, 44, 23,,, -6, 3, 2, 1, 2, 2, 1, 1, 128, 66, 66, 44, 23,,, -6, 3, 2, 1, 2, 2, 1, 1, 256, 66, 66, 44, 23,,, -6, 3, 2, 1, 2, 2, 1, 1, 384, 66, 66, 44, 23,,, -6, 3, 2, 1, 2, 2, 1, 2, 128, 66, 66, 44, 23,,, -6, 3, 2, 1, 2, 2, 1, 2, 256, 66, 66, 44, 23,,, -6, 3, 2, 1, 2, 2, 1, 2, 384, 66, 66, 44, 23,,, -6, 3, 2, 1, 2, 2, 2, 1, 128, 66, 66, 44, 23,,, -6, 3, 2, 1, 2, 2, 2, 1, 256, 66, 66, 44, 23,,, -6, 3, 2, 1, 2, 2, 2, 1, 384, 66, 66, 44, 23,,, -6, 3, 2, 1, 2, 2, 2, 2, 128, 66, 66, 44, 23,,, -6, 3, 2, 1, 2, 2, 2, 2, 256, 66, 66, 44, 23,,, -6, 3, 2, 1, 2, 2, 2, 2, 384, 66, 66, 44, 23,,, -6, 3, 2, 1, 3, 3, 1, 1, 128, 66, 66, 44, 23,,, -6, 3, 2, 1, 3, 3, 1, 1, 256, 66, 66, 44, 23,,, -6, 3, 2, 1, 3, 3, 1, 1, 384, 66, 66, 44, 23,,, -6, 3, 2, 1, 3, 3, 1, 2, 128, 66, 66, 44, 23,,, -6, 3, 2, 1, 3, 3, 1, 2, 256, 66, 66, 44, 23,,, -6, 3, 2, 1, 3, 3, 1, 2, 384, 66, 66, 44, 23,,, -6, 3, 2, 1, 3, 3, 1, 3, 128, 66, 66, 44, 23,,, -6, 3, 2, 1, 3, 3, 1, 3, 256, 66, 66, 44, 23,,, -6, 3, 2, 1, 3, 3, 1, 3, 384, 66, 66, 44, 23,,, -6, 3, 2, 1, 3, 3, 2, 1, 128, 66, 66, 44, 23,,, -6, 3, 2, 1, 3, 3, 2, 1, 256, 66, 66, 44, 23,,, -6, 3, 2, 1, 3, 3, 2, 1, 384, 66, 66, 44, 23,,, -6, 3, 2, 1, 3, 3, 2, 2, 128, 66, 66, 44, 23,,, -6, 3, 2, 1, 3, 3, 2, 2, 256, 66, 66, 44, 23,,, -6, 3, 2, 1, 3, 3, 2, 2, 384, 66, 66, 44, 23,,, -6, 3, 2, 1, 3, 3, 2, 3, 128, 66, 66, 44, 23,,, -6, 3, 2, 1, 3, 3, 2, 3, 256, 66, 66, 44, 23,,, -6, 3, 2, 1, 3, 3, 2, 3, 384, 66, 66, 44, 23,,, -6, 3, 2, 1, 3, 3, 3, 1, 128, 66, 66, 44, 23,,, -6, 3, 2, 1, 3, 3, 3, 1, 256, 66, 66, 44, 23,,, -6, 3, 2, 1, 3, 3, 3, 1, 384, 66, 66, 44, 23,,, -6, 3, 2, 1, 3, 3, 3, 2, 128, 66, 66, 44, 23,,, -6, 3, 2, 1, 3, 3, 3, 2, 256, 66, 66, 44, 23,,, -6, 3, 2, 1, 3, 3, 3, 2, 384, 66, 66, 44, 23,,, -6, 3, 2, 1, 3, 3, 3, 3, 128, 66, 66, 44, 23,,, -6, 3, 2, 1, 3, 3, 3, 3, 256, 66, 66, 44, 23,,, -6, 3, 2, 1, 3, 3, 3, 3, 384, 66, 66, 44, 23,,, -6, 3, 2, 2, 1, 1, 1, 1, 128, 130, 130, 86, 44,,, -6, 3, 2, 2, 1, 1, 1, 1, 256, 130, 130, 86, 44,,, -6, 3, 2, 2, 1, 1, 1, 1, 384, 130, 130, 86, 44,,, -6, 3, 2, 2, 2, 2, 1, 1, 128, 130, 130, 86, 44,,, -6, 3, 2, 2, 2, 2, 1, 1, 256, 130, 130, 86, 44,,, -6, 3, 2, 2, 2, 2, 1, 1, 384, 130, 130, 86, 44,,, -6, 3, 2, 2, 2, 2, 1, 2, 128, 130, 130, 86, 44,,, -6, 3, 2, 2, 2, 2, 1, 2, 256, 130, 130, 86, 44,,, -6, 3, 2, 2, 2, 2, 1, 2, 384, 130, 130, 86, 44,,, -6, 3, 2, 2, 2, 2, 2, 1, 128, 130, 130, 86, 44,,, -6, 3, 2, 2, 2, 2, 2, 1, 256, 130, 130, 86, 44,,, -6, 3, 2, 2, 2, 2, 2, 1, 384, 130, 130, 86, 44,,, -6, 3, 2, 2, 2, 2, 2, 2, 128, 130, 130, 86, 44,,, -6, 3, 2, 2, 2, 2, 2, 2, 256, 130, 130, 86, 44,,, -6, 3, 2, 2, 2, 2, 2, 2, 384, 130, 130, 86, 44,,, -6, 3, 2, 2, 3, 3, 1, 1, 128, 130, 130, 86, 44,,, -6, 3, 2, 2, 3, 3, 1, 1, 256, 130, 130, 86, 44,,, -6, 3, 2, 2, 3, 3, 1, 1, 384, 130, 130, 86, 44,,, -6, 3, 2, 2, 3, 3, 1, 2, 128, 130, 130, 86, 44,,, -6, 3, 2, 2, 3, 3, 1, 2, 256, 130, 130, 86, 44,,, -6, 3, 2, 2, 3, 3, 1, 2, 384, 130, 130, 86, 44,,, -6, 3, 2, 2, 3, 3, 1, 3, 128, 130, 130, 86, 44,,, -6, 3, 2, 2, 3, 3, 1, 3, 256, 130, 130, 86, 44,,, -6, 3, 2, 2, 3, 3, 1, 3, 384, 130, 130, 86, 44,,, -6, 3, 2, 2, 3, 3, 2, 1, 128, 130, 130, 86, 44,,, -6, 3, 2, 2, 3, 3, 2, 1, 256, 130, 130, 86, 44,,, -6, 3, 2, 2, 3, 3, 2, 1, 384, 130, 130, 86, 44,,, -6, 3, 2, 2, 3, 3, 2, 2, 128, 130, 130, 86, 44,,, -6, 3, 2, 2, 3, 3, 2, 2, 256, 130, 130, 86, 44,,, -6, 3, 2, 2, 3, 3, 2, 2, 384, 130, 130, 86, 44,,, -6, 3, 2, 2, 3, 3, 2, 3, 128, 130, 130, 86, 44,,, -6, 3, 2, 2, 3, 3, 2, 3, 256, 130, 130, 86, 44,,, -6, 3, 2, 2, 3, 3, 2, 3, 384, 130, 130, 86, 44,,, -6, 3, 2, 2, 3, 3, 3, 1, 128, 130, 130, 86, 44,,, -6, 3, 2, 2, 3, 3, 3, 1, 256, 130, 130, 86, 44,,, -6, 3, 2, 2, 3, 3, 3, 1, 384, 130, 130, 86, 44,,, -6, 3, 2, 2, 3, 3, 3, 2, 128, 130, 130, 86, 44,,, -6, 3, 2, 2, 3, 3, 3, 2, 256, 130, 130, 86, 44,,, -6, 3, 2, 2, 3, 3, 3, 2, 384, 130, 130, 86, 44,,, -6, 3, 2, 2, 3, 3, 3, 3, 128, 130, 130, 86, 44,,, -6, 3, 2, 2, 3, 3, 3, 3, 256, 130, 130, 86, 44,,, -6, 3, 2, 2, 3, 3, 3, 3, 384, 130, 130, 86, 44,,, -6, 3, 2, 3, 1, 1, 1, 1, 128, 194, 194, 128, 65,,, -6, 3, 2, 3, 1, 1, 1, 1, 256, 194, 194, 128, 65,,, -6, 3, 2, 3, 1, 1, 1, 1, 384, 194, 194, 128, 65,,, -6, 3, 2, 3, 2, 2, 1, 1, 128, 194, 194, 128, 65,,, -6, 3, 2, 3, 2, 2, 1, 1, 256, 194, 194, 128, 65,,, -6, 3, 2, 3, 2, 2, 1, 1, 384, 194, 194, 128, 65,,, -6, 3, 2, 3, 2, 2, 1, 2, 128, 194, 194, 128, 65,,, -6, 3, 2, 3, 2, 2, 1, 2, 256, 194, 194, 128, 65,,, -6, 3, 2, 3, 2, 2, 1, 2, 384, 194, 194, 128, 65,,, -6, 3, 2, 3, 2, 2, 2, 1, 128, 194, 194, 128, 65,,, -6, 3, 2, 3, 2, 2, 2, 1, 256, 194, 194, 128, 65,,, -6, 3, 2, 3, 2, 2, 2, 1, 384, 194, 194, 128, 65,,, -6, 3, 2, 3, 2, 2, 2, 2, 128, 194, 194, 128, 65,,, -6, 3, 2, 3, 2, 2, 2, 2, 256, 194, 194, 128, 65,,, -6, 3, 2, 3, 2, 2, 2, 2, 384, 194, 194, 128, 65,,, -6, 3, 2, 3, 3, 3, 1, 1, 128, 194, 194, 128, 65,,, -6, 3, 2, 3, 3, 3, 1, 1, 256, 194, 194, 128, 65,,, -6, 3, 2, 3, 3, 3, 1, 1, 384, 194, 194, 128, 65,,, -6, 3, 2, 3, 3, 3, 1, 2, 128, 194, 194, 128, 65,,, -6, 3, 2, 3, 3, 3, 1, 2, 256, 194, 194, 128, 65,,, -6, 3, 2, 3, 3, 3, 1, 2, 384, 194, 194, 128, 65,,, -6, 3, 2, 3, 3, 3, 1, 3, 128, 194, 194, 128, 65,,, -6, 3, 2, 3, 3, 3, 1, 3, 256, 194, 194, 128, 65,,, -6, 3, 2, 3, 3, 3, 1, 3, 384, 194, 194, 128, 65,,, -6, 3, 2, 3, 3, 3, 2, 1, 128, 194, 194, 128, 65,,, -6, 3, 2, 3, 3, 3, 2, 1, 256, 194, 194, 128, 65,,, -6, 3, 2, 3, 3, 3, 2, 1, 384, 194, 194, 128, 65,,, -6, 3, 2, 3, 3, 3, 2, 2, 128, 194, 194, 128, 65,,, -6, 3, 2, 3, 3, 3, 2, 2, 256, 194, 194, 128, 65,,, -6, 3, 2, 3, 3, 3, 2, 2, 384, 194, 194, 128, 65,,, -6, 3, 2, 3, 3, 3, 2, 3, 128, 194, 194, 128, 65,,, -6, 3, 2, 3, 3, 3, 2, 3, 256, 194, 194, 128, 65,,, -6, 3, 2, 3, 3, 3, 2, 3, 384, 194, 194, 128, 65,,, -6, 3, 2, 3, 3, 3, 3, 1, 128, 194, 194, 128, 65,,, -6, 3, 2, 3, 3, 3, 3, 1, 256, 194, 194, 128, 65,,, -6, 3, 2, 3, 3, 3, 3, 1, 384, 194, 194, 128, 65,,, -6, 3, 2, 3, 3, 3, 3, 2, 128, 194, 194, 128, 65,,, -6, 3, 2, 3, 3, 3, 3, 2, 256, 194, 194, 128, 65,,, -6, 3, 2, 3, 3, 3, 3, 2, 384, 194, 194, 128, 65,,, -6, 3, 2, 3, 3, 3, 3, 3, 128, 194, 194, 128, 65,,, -6, 3, 2, 3, 3, 3, 3, 3, 256, 194, 194, 128, 65,,, -6, 3, 2, 3, 3, 3, 3, 3, 384, 194, 194, 128, 65,,, -6, 3, 3, 1, 1, 1, 1, 1, 128, 66, 66, 44, 23,,, -6, 3, 3, 1, 1, 1, 1, 1, 256, 66, 66, 44, 23,,, -6, 3, 3, 1, 1, 1, 1, 1, 384, 66, 66, 44, 23,,, -6, 3, 3, 1, 2, 2, 1, 1, 128, 66, 66, 44, 23,,, -6, 3, 3, 1, 2, 2, 1, 1, 256, 66, 66, 44, 23,,, -6, 3, 3, 1, 2, 2, 1, 1, 384, 66, 66, 44, 23,,, -6, 3, 3, 1, 2, 2, 1, 2, 128, 66, 66, 44, 23,,, -6, 3, 3, 1, 2, 2, 1, 2, 256, 66, 66, 44, 23,,, -6, 3, 3, 1, 2, 2, 1, 2, 384, 66, 66, 44, 23,,, -6, 3, 3, 1, 2, 2, 2, 1, 128, 66, 66, 44, 23,,, -6, 3, 3, 1, 2, 2, 2, 1, 256, 66, 66, 44, 23,,, -6, 3, 3, 1, 2, 2, 2, 1, 384, 66, 66, 44, 23,,, -6, 3, 3, 1, 2, 2, 2, 2, 128, 66, 66, 44, 23,,, -6, 3, 3, 1, 2, 2, 2, 2, 256, 66, 66, 44, 23,,, -6, 3, 3, 1, 2, 2, 2, 2, 384, 66, 66, 44, 23,,, -6, 3, 3, 1, 3, 3, 1, 1, 128, 66, 66, 44, 23,,, -6, 3, 3, 1, 3, 3, 1, 1, 256, 66, 66, 44, 23,,, -6, 3, 3, 1, 3, 3, 1, 1, 384, 66, 66, 44, 23,,, -6, 3, 3, 1, 3, 3, 1, 2, 128, 66, 66, 44, 23,,, -6, 3, 3, 1, 3, 3, 1, 2, 256, 66, 66, 44, 23,,, -6, 3, 3, 1, 3, 3, 1, 2, 384, 66, 66, 44, 23,,, -6, 3, 3, 1, 3, 3, 1, 3, 128, 66, 66, 44, 23,,, -6, 3, 3, 1, 3, 3, 1, 3, 256, 66, 66, 44, 23,,, -6, 3, 3, 1, 3, 3, 1, 3, 384, 66, 66, 44, 23,,, -6, 3, 3, 1, 3, 3, 2, 1, 128, 66, 66, 44, 23,,, -6, 3, 3, 1, 3, 3, 2, 1, 256, 66, 66, 44, 23,,, -6, 3, 3, 1, 3, 3, 2, 1, 384, 66, 66, 44, 23,,, -6, 3, 3, 1, 3, 3, 2, 2, 128, 66, 66, 44, 23,,, -6, 3, 3, 1, 3, 3, 2, 2, 256, 66, 66, 44, 23,,, -6, 3, 3, 1, 3, 3, 2, 2, 384, 66, 66, 44, 23,,, -6, 3, 3, 1, 3, 3, 2, 3, 128, 66, 66, 44, 23,,, -6, 3, 3, 1, 3, 3, 2, 3, 256, 66, 66, 44, 23,,, -6, 3, 3, 1, 3, 3, 2, 3, 384, 66, 66, 44, 23,,, -6, 3, 3, 1, 3, 3, 3, 1, 128, 66, 66, 44, 23,,, -6, 3, 3, 1, 3, 3, 3, 1, 256, 66, 66, 44, 23,,, -6, 3, 3, 1, 3, 3, 3, 1, 384, 66, 66, 44, 23,,, -6, 3, 3, 1, 3, 3, 3, 2, 128, 66, 66, 44, 23,,, -6, 3, 3, 1, 3, 3, 3, 2, 256, 66, 66, 44, 23,,, -6, 3, 3, 1, 3, 3, 3, 2, 384, 66, 66, 44, 23,,, -6, 3, 3, 1, 3, 3, 3, 3, 128, 66, 66, 44, 23,,, -6, 3, 3, 1, 3, 3, 3, 3, 256, 66, 66, 44, 23,,, -6, 3, 3, 1, 3, 3, 3, 3, 384, 66, 66, 44, 23,,, -6, 3, 3, 2, 1, 1, 1, 1, 128, 130, 130, 86, 44,,, -6, 3, 3, 2, 1, 1, 1, 1, 256, 130, 130, 86, 44,,, -6, 3, 3, 2, 1, 1, 1, 1, 384, 130, 130, 86, 44,,, -6, 3, 3, 2, 2, 2, 1, 1, 128, 130, 130, 86, 44,,, -6, 3, 3, 2, 2, 2, 1, 1, 256, 130, 130, 86, 44,,, -6, 3, 3, 2, 2, 2, 1, 1, 384, 130, 130, 86, 44,,, -6, 3, 3, 2, 2, 2, 1, 2, 128, 130, 130, 86, 44,,, -6, 3, 3, 2, 2, 2, 1, 2, 256, 130, 130, 86, 44,,, -6, 3, 3, 2, 2, 2, 1, 2, 384, 130, 130, 86, 44,,, -6, 3, 3, 2, 2, 2, 2, 1, 128, 130, 130, 86, 44,,, -6, 3, 3, 2, 2, 2, 2, 1, 256, 130, 130, 86, 44,,, -6, 3, 3, 2, 2, 2, 2, 1, 384, 130, 130, 86, 44,,, -6, 3, 3, 2, 2, 2, 2, 2, 128, 130, 130, 86, 44,,, -6, 3, 3, 2, 2, 2, 2, 2, 256, 130, 130, 86, 44,,, -6, 3, 3, 2, 2, 2, 2, 2, 384, 130, 130, 86, 44,,, -6, 3, 3, 2, 3, 3, 1, 1, 128, 130, 130, 86, 44,,, -6, 3, 3, 2, 3, 3, 1, 1, 256, 130, 130, 86, 44,,, -6, 3, 3, 2, 3, 3, 1, 1, 384, 130, 130, 86, 44,,, -6, 3, 3, 2, 3, 3, 1, 2, 128, 130, 130, 86, 44,,, -6, 3, 3, 2, 3, 3, 1, 2, 256, 130, 130, 86, 44,,, -6, 3, 3, 2, 3, 3, 1, 2, 384, 130, 130, 86, 44,,, -6, 3, 3, 2, 3, 3, 1, 3, 128, 130, 130, 86, 44,,, -6, 3, 3, 2, 3, 3, 1, 3, 256, 130, 130, 86, 44,,, -6, 3, 3, 2, 3, 3, 1, 3, 384, 130, 130, 86, 44,,, -6, 3, 3, 2, 3, 3, 2, 1, 128, 130, 130, 86, 44,,, -6, 3, 3, 2, 3, 3, 2, 1, 256, 130, 130, 86, 44,,, -6, 3, 3, 2, 3, 3, 2, 1, 384, 130, 130, 86, 44,,, -6, 3, 3, 2, 3, 3, 2, 2, 128, 130, 130, 86, 44,,, -6, 3, 3, 2, 3, 3, 2, 2, 256, 130, 130, 86, 44,,, -6, 3, 3, 2, 3, 3, 2, 2, 384, 130, 130, 86, 44,,, -6, 3, 3, 2, 3, 3, 2, 3, 128, 130, 130, 86, 44,,, -6, 3, 3, 2, 3, 3, 2, 3, 256, 130, 130, 86, 44,,, -6, 3, 3, 2, 3, 3, 2, 3, 384, 130, 130, 86, 44,,, -6, 3, 3, 2, 3, 3, 3, 1, 128, 130, 130, 86, 44,,, -6, 3, 3, 2, 3, 3, 3, 1, 256, 130, 130, 86, 44,,, -6, 3, 3, 2, 3, 3, 3, 1, 384, 130, 130, 86, 44,,, -6, 3, 3, 2, 3, 3, 3, 2, 128, 130, 130, 86, 44,,, -6, 3, 3, 2, 3, 3, 3, 2, 256, 130, 130, 86, 44,,, -6, 3, 3, 2, 3, 3, 3, 2, 384, 130, 130, 86, 44,,, -6, 3, 3, 2, 3, 3, 3, 3, 128, 130, 130, 86, 44,,, -6, 3, 3, 2, 3, 3, 3, 3, 256, 130, 130, 86, 44,,, -6, 3, 3, 2, 3, 3, 3, 3, 384, 130, 130, 86, 44,,, -6, 3, 3, 3, 1, 1, 1, 1, 128, 194, 194, 128, 65,,, -6, 3, 3, 3, 1, 1, 1, 1, 256, 194, 194, 128, 65,,, -6, 3, 3, 3, 1, 1, 1, 1, 384, 194, 194, 128, 65,,, -6, 3, 3, 3, 2, 2, 1, 1, 128, 194, 194, 128, 65,,, -6, 3, 3, 3, 2, 2, 1, 1, 256, 194, 194, 128, 65,,, -6, 3, 3, 3, 2, 2, 1, 1, 384, 194, 194, 128, 65,,, -6, 3, 3, 3, 2, 2, 1, 2, 128, 194, 194, 128, 65,,, -6, 3, 3, 3, 2, 2, 1, 2, 256, 194, 194, 128, 65,,, -6, 3, 3, 3, 2, 2, 1, 2, 384, 194, 194, 128, 65,,, -6, 3, 3, 3, 2, 2, 2, 1, 128, 194, 194, 128, 65,,, -6, 3, 3, 3, 2, 2, 2, 1, 256, 194, 194, 128, 65,,, -6, 3, 3, 3, 2, 2, 2, 1, 384, 194, 194, 128, 65,,, -6, 3, 3, 3, 2, 2, 2, 2, 128, 194, 194, 128, 65,,, -6, 3, 3, 3, 2, 2, 2, 2, 256, 194, 194, 128, 65,,, -6, 3, 3, 3, 2, 2, 2, 2, 384, 194, 194, 128, 65,,, -6, 3, 3, 3, 3, 3, 1, 1, 128, 194, 194, 128, 65,,, -6, 3, 3, 3, 3, 3, 1, 1, 256, 194, 194, 128, 65,,, -6, 3, 3, 3, 3, 3, 1, 1, 384, 194, 194, 128, 65,,, -6, 3, 3, 3, 3, 3, 1, 2, 128, 194, 194, 128, 65,,, -6, 3, 3, 3, 3, 3, 1, 2, 256, 194, 194, 128, 65,,, -6, 3, 3, 3, 3, 3, 1, 2, 384, 194, 194, 128, 65,,, -6, 3, 3, 3, 3, 3, 1, 3, 128, 194, 194, 128, 65,,, -6, 3, 3, 3, 3, 3, 1, 3, 256, 194, 194, 128, 65,,, -6, 3, 3, 3, 3, 3, 1, 3, 384, 194, 194, 128, 65,,, -6, 3, 3, 3, 3, 3, 2, 1, 128, 194, 194, 128, 65,,, -6, 3, 3, 3, 3, 3, 2, 1, 256, 194, 194, 128, 65,,, -6, 3, 3, 3, 3, 3, 2, 1, 384, 194, 194, 128, 65,,, -6, 3, 3, 3, 3, 3, 2, 2, 128, 194, 194, 128, 65,,, -6, 3, 3, 3, 3, 3, 2, 2, 256, 194, 194, 128, 65,,, -6, 3, 3, 3, 3, 3, 2, 2, 384, 194, 194, 128, 65,,, -6, 3, 3, 3, 3, 3, 2, 3, 128, 194, 194, 128, 65,,, -6, 3, 3, 3, 3, 3, 2, 3, 256, 194, 194, 128, 65,,, -6, 3, 3, 3, 3, 3, 2, 3, 384, 194, 194, 128, 65,,, -6, 3, 3, 3, 3, 3, 3, 1, 128, 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23,,, -6, 3, 4, 1, 2, 2, 2, 2, 128, 66, 66, 44, 23,,, -6, 3, 4, 1, 2, 2, 2, 2, 256, 66, 66, 44, 23,,, -6, 3, 4, 1, 2, 2, 2, 2, 384, 66, 66, 44, 23,,, -6, 3, 4, 1, 3, 3, 1, 1, 128, 66, 66, 44, 23,,, -6, 3, 4, 1, 3, 3, 1, 1, 256, 66, 66, 44, 23,,, -6, 3, 4, 1, 3, 3, 1, 1, 384, 66, 66, 44, 23,,, -6, 3, 4, 1, 3, 3, 1, 2, 128, 66, 66, 44, 23,,, -6, 3, 4, 1, 3, 3, 1, 2, 256, 66, 66, 44, 23,,, -6, 3, 4, 1, 3, 3, 1, 2, 384, 66, 66, 44, 23,,, -6, 3, 4, 1, 3, 3, 1, 3, 128, 66, 66, 44, 23,,, -6, 3, 4, 1, 3, 3, 1, 3, 256, 66, 66, 44, 23,,, -6, 3, 4, 1, 3, 3, 1, 3, 384, 66, 66, 44, 23,,, -6, 3, 4, 1, 3, 3, 2, 1, 128, 66, 66, 44, 23,,, -6, 3, 4, 1, 3, 3, 2, 1, 256, 66, 66, 44, 23,,, -6, 3, 4, 1, 3, 3, 2, 1, 384, 66, 66, 44, 23,,, -6, 3, 4, 1, 3, 3, 2, 2, 128, 66, 66, 44, 23,,, -6, 3, 4, 1, 3, 3, 2, 2, 256, 66, 66, 44, 23,,, -6, 3, 4, 1, 3, 3, 2, 2, 384, 66, 66, 44, 23,,, -6, 3, 4, 1, 3, 3, 2, 3, 128, 66, 66, 44, 23,,, -6, 3, 4, 1, 3, 3, 2, 3, 256, 66, 66, 44, 23,,, -6, 3, 4, 1, 3, 3, 2, 3, 384, 66, 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3, 4, 2, 3, 3, 2, 3, 256, 130, 130, 86, 44,,, -6, 3, 4, 2, 3, 3, 2, 3, 384, 130, 130, 86, 44,,, -6, 3, 4, 2, 3, 3, 3, 1, 128, 130, 130, 86, 44,,, -6, 3, 4, 2, 3, 3, 3, 1, 256, 130, 130, 86, 44,,, -6, 3, 4, 2, 3, 3, 3, 1, 384, 130, 130, 86, 44,,, -6, 3, 4, 2, 3, 3, 3, 2, 128, 130, 130, 86, 44,,, -6, 3, 4, 2, 3, 3, 3, 2, 256, 130, 130, 86, 44,,, -6, 3, 4, 2, 3, 3, 3, 2, 384, 130, 130, 86, 44,,, -6, 3, 4, 2, 3, 3, 3, 3, 128, 130, 130, 86, 44,,, -6, 3, 4, 2, 3, 3, 3, 3, 256, 130, 130, 86, 44,,, -6, 3, 4, 2, 3, 3, 3, 3, 384, 130, 130, 86, 44,,, -6, 3, 4, 3, 1, 1, 1, 1, 128, 194, 194, 128, 65,,, -6, 3, 4, 3, 1, 1, 1, 1, 256, 194, 194, 128, 65,,, -6, 3, 4, 3, 1, 1, 1, 1, 384, 194, 194, 128, 65,,, -6, 3, 4, 3, 2, 2, 1, 1, 128, 194, 194, 128, 65,,, -6, 3, 4, 3, 2, 2, 1, 1, 256, 194, 194, 128, 65,,, -6, 3, 4, 3, 2, 2, 1, 1, 384, 194, 194, 128, 65,,, -6, 3, 4, 3, 2, 2, 1, 2, 128, 194, 194, 128, 65,,, -6, 3, 4, 3, 2, 2, 1, 2, 256, 194, 194, 128, 65,,, -6, 3, 4, 3, 2, 2, 1, 2, 384, 194, 194, 128, 65,,, -6, 3, 4, 3, 2, 2, 2, 1, 128, 194, 194, 128, 65,,, -6, 3, 4, 3, 2, 2, 2, 1, 256, 194, 194, 128, 65,,, -6, 3, 4, 3, 2, 2, 2, 1, 384, 194, 194, 128, 65,,, -6, 3, 4, 3, 2, 2, 2, 2, 128, 194, 194, 128, 65,,, -6, 3, 4, 3, 2, 2, 2, 2, 256, 194, 194, 128, 65,,, -6, 3, 4, 3, 2, 2, 2, 2, 384, 194, 194, 128, 65,,, -6, 3, 4, 3, 3, 3, 1, 1, 128, 194, 194, 128, 65,,, -6, 3, 4, 3, 3, 3, 1, 1, 256, 194, 194, 128, 65,,, -6, 3, 4, 3, 3, 3, 1, 1, 384, 194, 194, 128, 65,,, -6, 3, 4, 3, 3, 3, 1, 2, 128, 194, 194, 128, 65,,, -6, 3, 4, 3, 3, 3, 1, 2, 256, 194, 194, 128, 65,,, -6, 3, 4, 3, 3, 3, 1, 2, 384, 194, 194, 128, 65,,, -6, 3, 4, 3, 3, 3, 1, 3, 128, 194, 194, 128, 65,,, -6, 3, 4, 3, 3, 3, 1, 3, 256, 194, 194, 128, 65,,, -6, 3, 4, 3, 3, 3, 1, 3, 384, 194, 194, 128, 65,,, -6, 3, 4, 3, 3, 3, 2, 1, 128, 194, 194, 128, 65,,, -6, 3, 4, 3, 3, 3, 2, 1, 256, 194, 194, 128, 65,,, -6, 3, 4, 3, 3, 3, 2, 1, 384, 194, 194, 128, 65,,, -6, 3, 4, 3, 3, 3, 2, 2, 128, 194, 194, 128, 65,,, -6, 3, 4, 3, 3, 3, 2, 2, 256, 194, 194, 128, 65,,, -6, 3, 4, 3, 3, 3, 2, 2, 384, 194, 194, 128, 65,,, -6, 3, 4, 3, 3, 3, 2, 3, 128, 194, 194, 128, 65,,, -6, 3, 4, 3, 3, 3, 2, 3, 256, 194, 194, 128, 65,,, -6, 3, 4, 3, 3, 3, 2, 3, 384, 194, 194, 128, 65,,, -6, 3, 4, 3, 3, 3, 3, 1, 128, 194, 194, 128, 65,,, -6, 3, 4, 3, 3, 3, 3, 1, 256, 194, 194, 128, 65,,, -6, 3, 4, 3, 3, 3, 3, 1, 384, 194, 194, 128, 65,,, -6, 3, 4, 3, 3, 3, 3, 2, 128, 194, 194, 128, 65,,, -6, 3, 4, 3, 3, 3, 3, 2, 256, 194, 194, 128, 65,,, -6, 3, 4, 3, 3, 3, 3, 2, 384, 194, 194, 128, 65,,, -6, 3, 4, 3, 3, 3, 3, 3, 128, 194, 194, 128, 65,,, -6, 3, 4, 3, 3, 3, 3, 3, 256, 194, 194, 128, 65,,, -6, 3, 4, 3, 3, 3, 3, 3, 384, 194, 194, 128, 65,,, -6, 3, 5, 1, 1, 1, 1, 1, 128, 66, 66, 44, 23,,, -6, 3, 5, 1, 1, 1, 1, 1, 256, 66, 66, 44, 23,,, -6, 3, 5, 1, 1, 1, 1, 1, 384, 66, 66, 44, 23,,, -6, 3, 5, 1, 2, 2, 1, 1, 128, 66, 66, 44, 23,,, -6, 3, 5, 1, 2, 2, 1, 1, 256, 66, 66, 44, 23,,, -6, 3, 5, 1, 2, 2, 1, 1, 384, 66, 66, 44, 23,,, -6, 3, 5, 1, 2, 2, 1, 2, 128, 66, 66, 44, 23,,, -6, 3, 5, 1, 2, 2, 1, 2, 256, 66, 66, 44, 23,,, -6, 3, 5, 1, 2, 2, 1, 2, 384, 66, 66, 44, 23,,, -6, 3, 5, 1, 2, 2, 2, 1, 128, 66, 66, 44, 23,,, -6, 3, 5, 1, 2, 2, 2, 1, 256, 66, 66, 44, 23,,, -6, 3, 5, 1, 2, 2, 2, 1, 384, 66, 66, 44, 23,,, -6, 3, 5, 1, 2, 2, 2, 2, 128, 66, 66, 44, 23,,, -6, 3, 5, 1, 2, 2, 2, 2, 256, 66, 66, 44, 23,,, -6, 3, 5, 1, 2, 2, 2, 2, 384, 66, 66, 44, 23,,, -6, 3, 5, 1, 3, 3, 1, 1, 128, 66, 66, 44, 23,,, -6, 3, 5, 1, 3, 3, 1, 1, 256, 66, 66, 44, 23,,, -6, 3, 5, 1, 3, 3, 1, 1, 384, 66, 66, 44, 23,,, -6, 3, 5, 1, 3, 3, 1, 2, 128, 66, 66, 44, 23,,, -6, 3, 5, 1, 3, 3, 1, 2, 256, 66, 66, 44, 23,,, -6, 3, 5, 1, 3, 3, 1, 2, 384, 66, 66, 44, 23,,, -6, 3, 5, 1, 3, 3, 1, 3, 128, 66, 66, 44, 23,,, -6, 3, 5, 1, 3, 3, 1, 3, 256, 66, 66, 44, 23,,, -6, 3, 5, 1, 3, 3, 1, 3, 384, 66, 66, 44, 23,,, -6, 3, 5, 1, 3, 3, 2, 1, 128, 66, 66, 44, 23,,, -6, 3, 5, 1, 3, 3, 2, 1, 256, 66, 66, 44, 23,,, -6, 3, 5, 1, 3, 3, 2, 1, 384, 66, 66, 44, 23,,, -6, 3, 5, 1, 3, 3, 2, 2, 128, 66, 66, 44, 23,,, -6, 3, 5, 1, 3, 3, 2, 2, 256, 66, 66, 44, 23,,, -6, 3, 5, 1, 3, 3, 2, 2, 384, 66, 66, 44, 23,,, -6, 3, 5, 1, 3, 3, 2, 3, 128, 66, 66, 44, 23,,, -6, 3, 5, 1, 3, 3, 2, 3, 256, 66, 66, 44, 23,,, -6, 3, 5, 1, 3, 3, 2, 3, 384, 66, 66, 44, 23,,, -6, 3, 5, 1, 3, 3, 3, 1, 128, 66, 66, 44, 23,,, -6, 3, 5, 1, 3, 3, 3, 1, 256, 66, 66, 44, 23,,, -6, 3, 5, 1, 3, 3, 3, 1, 384, 66, 66, 44, 23,,, -6, 3, 5, 1, 3, 3, 3, 2, 128, 66, 66, 44, 23,,, -6, 3, 5, 1, 3, 3, 3, 2, 256, 66, 66, 44, 23,,, -6, 3, 5, 1, 3, 3, 3, 2, 384, 66, 66, 44, 23,,, -6, 3, 5, 1, 3, 3, 3, 3, 128, 66, 66, 44, 23,,, -6, 3, 5, 1, 3, 3, 3, 3, 256, 66, 66, 44, 23,,, -6, 3, 5, 1, 3, 3, 3, 3, 384, 66, 66, 44, 23,,, -6, 3, 5, 2, 1, 1, 1, 1, 128, 130, 130, 86, 44,,, -6, 3, 5, 2, 1, 1, 1, 1, 256, 130, 130, 86, 44,,, -6, 3, 5, 2, 1, 1, 1, 1, 384, 130, 130, 86, 44,,, -6, 3, 5, 2, 2, 2, 1, 1, 128, 130, 130, 86, 44,,, -6, 3, 5, 2, 2, 2, 1, 1, 256, 130, 130, 86, 44,,, -6, 3, 5, 2, 2, 2, 1, 1, 384, 130, 130, 86, 44,,, -6, 3, 5, 2, 2, 2, 1, 2, 128, 130, 130, 86, 44,,, -6, 3, 5, 2, 2, 2, 1, 2, 256, 130, 130, 86, 44,,, -6, 3, 5, 2, 2, 2, 1, 2, 384, 130, 130, 86, 44,,, -6, 3, 5, 2, 2, 2, 2, 1, 128, 130, 130, 86, 44,,, -6, 3, 5, 2, 2, 2, 2, 1, 256, 130, 130, 86, 44,,, -6, 3, 5, 2, 2, 2, 2, 1, 384, 130, 130, 86, 44,,, -6, 3, 5, 2, 2, 2, 2, 2, 128, 130, 130, 86, 44,,, -6, 3, 5, 2, 2, 2, 2, 2, 256, 130, 130, 86, 44,,, -6, 3, 5, 2, 2, 2, 2, 2, 384, 130, 130, 86, 44,,, -6, 3, 5, 2, 3, 3, 1, 1, 128, 130, 130, 86, 44,,, -6, 3, 5, 2, 3, 3, 1, 1, 256, 130, 130, 86, 44,,, -6, 3, 5, 2, 3, 3, 1, 1, 384, 130, 130, 86, 44,,, -6, 3, 5, 2, 3, 3, 1, 2, 128, 130, 130, 86, 44,,, -6, 3, 5, 2, 3, 3, 1, 2, 256, 130, 130, 86, 44,,, -6, 3, 5, 2, 3, 3, 1, 2, 384, 130, 130, 86, 44,,, -6, 3, 5, 2, 3, 3, 1, 3, 128, 130, 130, 86, 44,,, -6, 3, 5, 2, 3, 3, 1, 3, 256, 130, 130, 86, 44,,, -6, 3, 5, 2, 3, 3, 1, 3, 384, 130, 130, 86, 44,,, -6, 3, 5, 2, 3, 3, 2, 1, 128, 130, 130, 86, 44,,, -6, 3, 5, 2, 3, 3, 2, 1, 256, 130, 130, 86, 44,,, -6, 3, 5, 2, 3, 3, 2, 1, 384, 130, 130, 86, 44,,, -6, 3, 5, 2, 3, 3, 2, 2, 128, 130, 130, 86, 44,,, -6, 3, 5, 2, 3, 3, 2, 2, 256, 130, 130, 86, 44,,, -6, 3, 5, 2, 3, 3, 2, 2, 384, 130, 130, 86, 44,,, -6, 3, 5, 2, 3, 3, 2, 3, 128, 130, 130, 86, 44,,, -6, 3, 5, 2, 3, 3, 2, 3, 256, 130, 130, 86, 44,,, -6, 3, 5, 2, 3, 3, 2, 3, 384, 130, 130, 86, 44,,, -6, 3, 5, 2, 3, 3, 3, 1, 128, 130, 130, 86, 44,,, -6, 3, 5, 2, 3, 3, 3, 1, 256, 130, 130, 86, 44,,, -6, 3, 5, 2, 3, 3, 3, 1, 384, 130, 130, 86, 44,,, -6, 3, 5, 2, 3, 3, 3, 2, 128, 130, 130, 86, 44,,, -6, 3, 5, 2, 3, 3, 3, 2, 256, 130, 130, 86, 44,,, -6, 3, 5, 2, 3, 3, 3, 2, 384, 130, 130, 86, 44,,, -6, 3, 5, 2, 3, 3, 3, 3, 128, 130, 130, 86, 44,,, -6, 3, 5, 2, 3, 3, 3, 3, 256, 130, 130, 86, 44,,, -6, 3, 5, 2, 3, 3, 3, 3, 384, 130, 130, 86, 44,,, -6, 3, 5, 3, 1, 1, 1, 1, 128, 194, 194, 128, 65,,, -6, 3, 5, 3, 1, 1, 1, 1, 256, 194, 194, 128, 65,,, -6, 3, 5, 3, 1, 1, 1, 1, 384, 194, 194, 128, 65,,, -6, 3, 5, 3, 2, 2, 1, 1, 128, 194, 194, 128, 65,,, -6, 3, 5, 3, 2, 2, 1, 1, 256, 194, 194, 128, 65,,, -6, 3, 5, 3, 2, 2, 1, 1, 384, 194, 194, 128, 65,,, -6, 3, 5, 3, 2, 2, 1, 2, 128, 194, 194, 128, 65,,, -6, 3, 5, 3, 2, 2, 1, 2, 256, 194, 194, 128, 65,,, -6, 3, 5, 3, 2, 2, 1, 2, 384, 194, 194, 128, 65,,, -6, 3, 5, 3, 2, 2, 2, 1, 128, 194, 194, 128, 65,,, -6, 3, 5, 3, 2, 2, 2, 1, 256, 194, 194, 128, 65,,, -6, 3, 5, 3, 2, 2, 2, 1, 384, 194, 194, 128, 65,,, -6, 3, 5, 3, 2, 2, 2, 2, 128, 194, 194, 128, 65,,, -6, 3, 5, 3, 2, 2, 2, 2, 256, 194, 194, 128, 65,,, -6, 3, 5, 3, 2, 2, 2, 2, 384, 194, 194, 128, 65,,, -6, 3, 5, 3, 3, 3, 1, 1, 128, 194, 194, 128, 65,,, -6, 3, 5, 3, 3, 3, 1, 1, 256, 194, 194, 128, 65,,, -6, 3, 5, 3, 3, 3, 1, 1, 384, 194, 194, 128, 65,,, -6, 3, 5, 3, 3, 3, 1, 2, 128, 194, 194, 128, 65,,, -6, 3, 5, 3, 3, 3, 1, 2, 256, 194, 194, 128, 65,,, -6, 3, 5, 3, 3, 3, 1, 2, 384, 194, 194, 128, 65,,, -6, 3, 5, 3, 3, 3, 1, 3, 128, 194, 194, 128, 65,,, -6, 3, 5, 3, 3, 3, 1, 3, 256, 194, 194, 128, 65,,, -6, 3, 5, 3, 3, 3, 1, 3, 384, 194, 194, 128, 65,,, -6, 3, 5, 3, 3, 3, 2, 1, 128, 194, 194, 128, 65,,, -6, 3, 5, 3, 3, 3, 2, 1, 256, 194, 194, 128, 65,,, -6, 3, 5, 3, 3, 3, 2, 1, 384, 194, 194, 128, 65,,, -6, 3, 5, 3, 3, 3, 2, 2, 128, 194, 194, 128, 65,,, -6, 3, 5, 3, 3, 3, 2, 2, 256, 194, 194, 128, 65,,, -6, 3, 5, 3, 3, 3, 2, 2, 384, 194, 194, 128, 65,,, -6, 3, 5, 3, 3, 3, 2, 3, 128, 194, 194, 128, 65,,, -6, 3, 5, 3, 3, 3, 2, 3, 256, 194, 194, 128, 65,,, -6, 3, 5, 3, 3, 3, 2, 3, 384, 194, 194, 128, 65,,, -6, 3, 5, 3, 3, 3, 3, 1, 128, 194, 194, 128, 65,,, -6, 3, 5, 3, 3, 3, 3, 1, 256, 194, 194, 128, 65,,, -6, 3, 5, 3, 3, 3, 3, 1, 384, 194, 194, 128, 65,,, -6, 3, 5, 3, 3, 3, 3, 2, 128, 194, 194, 128, 65,,, -6, 3, 5, 3, 3, 3, 3, 2, 256, 194, 194, 128, 65,,, -6, 3, 5, 3, 3, 3, 3, 2, 384, 194, 194, 128, 65,,, -6, 3, 5, 3, 3, 3, 3, 3, 128, 194, 194, 128, 65,,, -6, 3, 5, 3, 3, 3, 3, 3, 256, 194, 194, 128, 65,,, -6, 3, 5, 3, 3, 3, 3, 3, 384, 194, 194, 128, 65,,, -6, 3, 6, 1, 1, 1, 1, 1, 128, 66, 66, 44, 23,,, -6, 3, 6, 1, 1, 1, 1, 1, 256, 66, 66, 44, 23,,, -6, 3, 6, 1, 1, 1, 1, 1, 384, 66, 66, 44, 23,,, -6, 3, 6, 1, 2, 2, 1, 1, 128, 66, 66, 44, 23,,, -6, 3, 6, 1, 2, 2, 1, 1, 256, 66, 66, 44, 23,,, -6, 3, 6, 1, 2, 2, 1, 1, 384, 66, 66, 44, 23,,, -6, 3, 6, 1, 2, 2, 1, 2, 128, 66, 66, 44, 23,,, -6, 3, 6, 1, 2, 2, 1, 2, 256, 66, 66, 44, 23,,, -6, 3, 6, 1, 2, 2, 1, 2, 384, 66, 66, 44, 23,,, -6, 3, 6, 1, 2, 2, 2, 1, 128, 66, 66, 44, 23,,, -6, 3, 6, 1, 2, 2, 2, 1, 256, 66, 66, 44, 23,,, -6, 3, 6, 1, 2, 2, 2, 1, 384, 66, 66, 44, 23,,, -6, 3, 6, 1, 2, 2, 2, 2, 128, 66, 66, 44, 23,,, -6, 3, 6, 1, 2, 2, 2, 2, 256, 66, 66, 44, 23,,, -6, 3, 6, 1, 2, 2, 2, 2, 384, 66, 66, 44, 23,,, -6, 3, 6, 1, 3, 3, 1, 1, 128, 66, 66, 44, 23,,, -6, 3, 6, 1, 3, 3, 1, 1, 256, 66, 66, 44, 23,,, -6, 3, 6, 1, 3, 3, 1, 1, 384, 66, 66, 44, 23,,, -6, 3, 6, 1, 3, 3, 1, 2, 128, 66, 66, 44, 23,,, -6, 3, 6, 1, 3, 3, 1, 2, 256, 66, 66, 44, 23,,, -6, 3, 6, 1, 3, 3, 1, 2, 384, 66, 66, 44, 23,,, -6, 3, 6, 1, 3, 3, 1, 3, 128, 66, 66, 44, 23,,, -6, 3, 6, 1, 3, 3, 1, 3, 256, 66, 66, 44, 23,,, -6, 3, 6, 1, 3, 3, 1, 3, 384, 66, 66, 44, 23,,, -6, 3, 6, 1, 3, 3, 2, 1, 128, 66, 66, 44, 23,,, -6, 3, 6, 1, 3, 3, 2, 1, 256, 66, 66, 44, 23,,, -6, 3, 6, 1, 3, 3, 2, 1, 384, 66, 66, 44, 23,,, -6, 3, 6, 1, 3, 3, 2, 2, 128, 66, 66, 44, 23,,, -6, 3, 6, 1, 3, 3, 2, 2, 256, 66, 66, 44, 23,,, -6, 3, 6, 1, 3, 3, 2, 2, 384, 66, 66, 44, 23,,, -6, 3, 6, 1, 3, 3, 2, 3, 128, 66, 66, 44, 23,,, -6, 3, 6, 1, 3, 3, 2, 3, 256, 66, 66, 44, 23,,, -6, 3, 6, 1, 3, 3, 2, 3, 384, 66, 66, 44, 23,,, -6, 3, 6, 1, 3, 3, 3, 1, 128, 66, 66, 44, 23,,, -6, 3, 6, 1, 3, 3, 3, 1, 256, 66, 66, 44, 23,,, -6, 3, 6, 1, 3, 3, 3, 1, 384, 66, 66, 44, 23,,, -6, 3, 6, 1, 3, 3, 3, 2, 128, 66, 66, 44, 23,,, -6, 3, 6, 1, 3, 3, 3, 2, 256, 66, 66, 44, 23,,, -6, 3, 6, 1, 3, 3, 3, 2, 384, 66, 66, 44, 23,,, -6, 3, 6, 1, 3, 3, 3, 3, 128, 66, 66, 44, 23,,, -6, 3, 6, 1, 3, 3, 3, 3, 256, 66, 66, 44, 23,,, -6, 3, 6, 1, 3, 3, 3, 3, 384, 66, 66, 44, 23,,, -6, 3, 6, 2, 1, 1, 1, 1, 128, 130, 130, 86, 44,,, -6, 3, 6, 2, 1, 1, 1, 1, 256, 130, 130, 86, 44,,, -6, 3, 6, 2, 1, 1, 1, 1, 384, 130, 130, 86, 44,,, -6, 3, 6, 2, 2, 2, 1, 1, 128, 130, 130, 86, 44,,, -6, 3, 6, 2, 2, 2, 1, 1, 256, 130, 130, 86, 44,,, -6, 3, 6, 2, 2, 2, 1, 1, 384, 130, 130, 86, 44,,, -6, 3, 6, 2, 2, 2, 1, 2, 128, 130, 130, 86, 44,,, -6, 3, 6, 2, 2, 2, 1, 2, 256, 130, 130, 86, 44,,, -6, 3, 6, 2, 2, 2, 1, 2, 384, 130, 130, 86, 44,,, -6, 3, 6, 2, 2, 2, 2, 1, 128, 130, 130, 86, 44,,, -6, 3, 6, 2, 2, 2, 2, 1, 256, 130, 130, 86, 44,,, -6, 3, 6, 2, 2, 2, 2, 1, 384, 130, 130, 86, 44,,, -6, 3, 6, 2, 2, 2, 2, 2, 128, 130, 130, 86, 44,,, -6, 3, 6, 2, 2, 2, 2, 2, 256, 130, 130, 86, 44,,, -6, 3, 6, 2, 2, 2, 2, 2, 384, 130, 130, 86, 44,,, -6, 3, 6, 2, 3, 3, 1, 1, 128, 130, 130, 86, 44,,, -6, 3, 6, 2, 3, 3, 1, 1, 256, 130, 130, 86, 44,,, -6, 3, 6, 2, 3, 3, 1, 1, 384, 130, 130, 86, 44,,, -6, 3, 6, 2, 3, 3, 1, 2, 128, 130, 130, 86, 44,,, -6, 3, 6, 2, 3, 3, 1, 2, 256, 130, 130, 86, 44,,, -6, 3, 6, 2, 3, 3, 1, 2, 384, 130, 130, 86, 44,,, -6, 3, 6, 2, 3, 3, 1, 3, 128, 130, 130, 86, 44,,, -6, 3, 6, 2, 3, 3, 1, 3, 256, 130, 130, 86, 44,,, -6, 3, 6, 2, 3, 3, 1, 3, 384, 130, 130, 86, 44,,, -6, 3, 6, 2, 3, 3, 2, 1, 128, 130, 130, 86, 44,,, -6, 3, 6, 2, 3, 3, 2, 1, 256, 130, 130, 86, 44,,, -6, 3, 6, 2, 3, 3, 2, 1, 384, 130, 130, 86, 44,,, -6, 3, 6, 2, 3, 3, 2, 2, 128, 130, 130, 86, 44,,, -6, 3, 6, 2, 3, 3, 2, 2, 256, 130, 130, 86, 44,,, -6, 3, 6, 2, 3, 3, 2, 2, 384, 130, 130, 86, 44,,, -6, 3, 6, 2, 3, 3, 2, 3, 128, 130, 130, 86, 44,,, -6, 3, 6, 2, 3, 3, 2, 3, 256, 130, 130, 86, 44,,, -6, 3, 6, 2, 3, 3, 2, 3, 384, 130, 130, 86, 44,,, -6, 3, 6, 2, 3, 3, 3, 1, 128, 130, 130, 86, 44,,, -6, 3, 6, 2, 3, 3, 3, 1, 256, 130, 130, 86, 44,,, -6, 3, 6, 2, 3, 3, 3, 1, 384, 130, 130, 86, 44,,, -6, 3, 6, 2, 3, 3, 3, 2, 128, 130, 130, 86, 44,,, -6, 3, 6, 2, 3, 3, 3, 2, 256, 130, 130, 86, 44,,, -6, 3, 6, 2, 3, 3, 3, 2, 384, 130, 130, 86, 44,,, -6, 3, 6, 2, 3, 3, 3, 3, 128, 130, 130, 86, 44,,, -6, 3, 6, 2, 3, 3, 3, 3, 256, 130, 130, 86, 44,,, -6, 3, 6, 2, 3, 3, 3, 3, 384, 130, 130, 86, 44,,, -6, 3, 6, 3, 1, 1, 1, 1, 128, 194, 194, 128, 65,,, -6, 3, 6, 3, 1, 1, 1, 1, 256, 194, 194, 128, 65,,, -6, 3, 6, 3, 1, 1, 1, 1, 384, 194, 194, 128, 65,,, -6, 3, 6, 3, 2, 2, 1, 1, 128, 194, 194, 128, 65,,, -6, 3, 6, 3, 2, 2, 1, 1, 256, 194, 194, 128, 65,,, -6, 3, 6, 3, 2, 2, 1, 1, 384, 194, 194, 128, 65,,, -6, 3, 6, 3, 2, 2, 1, 2, 128, 194, 194, 128, 65,,, -6, 3, 6, 3, 2, 2, 1, 2, 256, 194, 194, 128, 65,,, -6, 3, 6, 3, 2, 2, 1, 2, 384, 194, 194, 128, 65,,, -6, 3, 6, 3, 2, 2, 2, 1, 128, 194, 194, 128, 65,,, -6, 3, 6, 3, 2, 2, 2, 1, 256, 194, 194, 128, 65,,, -6, 3, 6, 3, 2, 2, 2, 1, 384, 194, 194, 128, 65,,, -6, 3, 6, 3, 2, 2, 2, 2, 128, 194, 194, 128, 65,,, -6, 3, 6, 3, 2, 2, 2, 2, 256, 194, 194, 128, 65,,, -6, 3, 6, 3, 2, 2, 2, 2, 384, 194, 194, 128, 65,,, -6, 3, 6, 3, 3, 3, 1, 1, 128, 194, 194, 128, 65,,, -6, 3, 6, 3, 3, 3, 1, 1, 256, 194, 194, 128, 65,,, -6, 3, 6, 3, 3, 3, 1, 1, 384, 194, 194, 128, 65,,, -6, 3, 6, 3, 3, 3, 1, 2, 128, 194, 194, 128, 65,,, -6, 3, 6, 3, 3, 3, 1, 2, 256, 194, 194, 128, 65,,, -6, 3, 6, 3, 3, 3, 1, 2, 384, 194, 194, 128, 65,,, -6, 3, 6, 3, 3, 3, 1, 3, 128, 194, 194, 128, 65,,, -6, 3, 6, 3, 3, 3, 1, 3, 256, 194, 194, 128, 65,,, -6, 3, 6, 3, 3, 3, 1, 3, 384, 194, 194, 128, 65,,, -6, 3, 6, 3, 3, 3, 2, 1, 128, 194, 194, 128, 65,,, -6, 3, 6, 3, 3, 3, 2, 1, 256, 194, 194, 128, 65,,, -6, 3, 6, 3, 3, 3, 2, 1, 384, 194, 194, 128, 65,,, -6, 3, 6, 3, 3, 3, 2, 2, 128, 194, 194, 128, 65,,, -6, 3, 6, 3, 3, 3, 2, 2, 256, 194, 194, 128, 65,,, -6, 3, 6, 3, 3, 3, 2, 2, 384, 194, 194, 128, 65,,, -6, 3, 6, 3, 3, 3, 2, 3, 128, 194, 194, 128, 65,,, -6, 3, 6, 3, 3, 3, 2, 3, 256, 194, 194, 128, 65,,, -6, 3, 6, 3, 3, 3, 2, 3, 384, 194, 194, 128, 65,,, -6, 3, 6, 3, 3, 3, 3, 1, 128, 194, 194, 128, 65,,, -6, 3, 6, 3, 3, 3, 3, 1, 256, 194, 194, 128, 65,,, -6, 3, 6, 3, 3, 3, 3, 1, 384, 194, 194, 128, 65,,, -6, 3, 6, 3, 3, 3, 3, 2, 128, 194, 194, 128, 65,,, -6, 3, 6, 3, 3, 3, 3, 2, 256, 194, 194, 128, 65,,, -6, 3, 6, 3, 3, 3, 3, 2, 384, 194, 194, 128, 65,,, -6, 3, 6, 3, 3, 3, 3, 3, 128, 194, 194, 128, 65,,, -6, 3, 6, 3, 3, 3, 3, 3, 256, 194, 194, 128, 65,,, -6, 3, 6, 3, 3, 3, 3, 3, 384, 194, 194, 128, 65,,, -6, 4, 1, 1, 1, 1, 1, 1, 128, 67, 67, 45, 24,,, -6, 4, 1, 1, 1, 1, 1, 1, 256, 67, 67, 45, 24,,, -6, 4, 1, 1, 1, 1, 1, 1, 384, 67, 67, 45, 24,,, -6, 4, 1, 1, 2, 2, 1, 1, 128, 67, 66, 45, 22,,, -6, 4, 1, 1, 2, 2, 1, 1, 256, 67, 66, 45, 22,,, -6, 4, 1, 1, 2, 2, 1, 1, 384, 67, 66, 45, 22,,, -6, 4, 1, 1, 2, 2, 1, 2, 128, 67, 66, 45, 22,,, -6, 4, 1, 1, 2, 2, 1, 2, 256, 67, 66, 45, 22,,, -6, 4, 1, 1, 2, 2, 1, 2, 384, 67, 66, 45, 22,,, -6, 4, 1, 1, 2, 2, 2, 1, 128, 67, 66, 45, 22,,, -6, 4, 1, 1, 2, 2, 2, 1, 256, 67, 66, 45, 22,,, -6, 4, 1, 1, 2, 2, 2, 1, 384, 67, 66, 45, 22,,, -6, 4, 1, 1, 2, 2, 2, 2, 128, 67, 66, 45, 22,,, -6, 4, 1, 1, 2, 2, 2, 2, 256, 67, 66, 45, 22,,, -6, 4, 1, 1, 2, 2, 2, 2, 384, 67, 66, 45, 22,,, -6, 4, 1, 1, 3, 3, 1, 1, 128, 67, 64, 45, 21,,, -6, 4, 1, 1, 3, 3, 1, 1, 256, 67, 64, 45, 21,,, -6, 4, 1, 1, 3, 3, 1, 1, 384, 67, 64, 45, 21,,, -6, 4, 1, 1, 3, 3, 1, 2, 128, 67, 64, 45, 21,,, -6, 4, 1, 1, 3, 3, 1, 2, 256, 67, 64, 45, 21,,, -6, 4, 1, 1, 3, 3, 1, 2, 384, 67, 64, 45, 21,,, -6, 4, 1, 1, 3, 3, 1, 3, 128, 67, 64, 45, 21,,, -6, 4, 1, 1, 3, 3, 1, 3, 256, 67, 64, 45, 21,,, -6, 4, 1, 1, 3, 3, 1, 3, 384, 67, 64, 45, 21,,, -6, 4, 1, 1, 3, 3, 2, 1, 128, 67, 64, 45, 21,,, -6, 4, 1, 1, 3, 3, 2, 1, 256, 67, 64, 45, 21,,, -6, 4, 1, 1, 3, 3, 2, 1, 384, 67, 64, 45, 21,,, -6, 4, 1, 1, 3, 3, 2, 2, 128, 67, 64, 45, 21,,, -6, 4, 1, 1, 3, 3, 2, 2, 256, 67, 64, 45, 21,,, -6, 4, 1, 1, 3, 3, 2, 2, 384, 67, 64, 45, 21,,, -6, 4, 1, 1, 3, 3, 2, 3, 128, 67, 64, 45, 21,,, -6, 4, 1, 1, 3, 3, 2, 3, 256, 67, 64, 45, 21,,, -6, 4, 1, 1, 3, 3, 2, 3, 384, 67, 64, 45, 21,,, -6, 4, 1, 1, 3, 3, 3, 1, 128, 67, 64, 45, 21,,, -6, 4, 1, 1, 3, 3, 3, 1, 256, 67, 64, 45, 21,,, -6, 4, 1, 1, 3, 3, 3, 1, 384, 67, 64, 45, 21,,, -6, 4, 1, 1, 3, 3, 3, 2, 128, 67, 64, 45, 21,,, -6, 4, 1, 1, 3, 3, 3, 2, 256, 67, 64, 45, 21,,, -6, 4, 1, 1, 3, 3, 3, 2, 384, 67, 64, 45, 21,,, -6, 4, 1, 1, 3, 3, 3, 3, 128, 67, 64, 45, 21,,, -6, 4, 1, 1, 3, 3, 3, 3, 256, 67, 64, 45, 21,,, -6, 4, 1, 1, 3, 3, 3, 3, 384, 67, 64, 45, 21,,, -6, 4, 1, 2, 1, 1, 1, 1, 128, 131, 131, 87, 45,,, -6, 4, 1, 2, 1, 1, 1, 1, 256, 131, 131, 87, 45,,, -6, 4, 1, 2, 1, 1, 1, 1, 384, 131, 131, 87, 45,,, -6, 4, 1, 2, 2, 2, 1, 1, 128, 131, 129, 87, 41,,, -6, 4, 1, 2, 2, 2, 1, 1, 256, 131, 129, 87, 41,,, -6, 4, 1, 2, 2, 2, 1, 1, 384, 131, 129, 87, 41,,, -6, 4, 1, 2, 2, 2, 1, 2, 128, 131, 129, 87, 41,,, -6, 4, 1, 2, 2, 2, 1, 2, 256, 131, 129, 87, 41,,, -6, 4, 1, 2, 2, 2, 1, 2, 384, 131, 129, 87, 41,,, -6, 4, 1, 2, 2, 2, 2, 1, 128, 131, 129, 87, 41,,, -6, 4, 1, 2, 2, 2, 2, 1, 256, 131, 129, 87, 41,,, -6, 4, 1, 2, 2, 2, 2, 1, 384, 131, 129, 87, 41,,, -6, 4, 1, 2, 2, 2, 2, 2, 128, 131, 129, 87, 41,,, -6, 4, 1, 2, 2, 2, 2, 2, 256, 131, 129, 87, 41,,, -6, 4, 1, 2, 2, 2, 2, 2, 384, 131, 129, 87, 41,,, -6, 4, 1, 2, 3, 3, 1, 1, 128, 131, 125, 87, 39,,, -6, 4, 1, 2, 3, 3, 1, 1, 256, 131, 125, 87, 39,,, -6, 4, 1, 2, 3, 3, 1, 1, 384, 131, 125, 87, 39,,, -6, 4, 1, 2, 3, 3, 1, 2, 128, 131, 125, 87, 39,,, -6, 4, 1, 2, 3, 3, 1, 2, 256, 131, 125, 87, 39,,, -6, 4, 1, 2, 3, 3, 1, 2, 384, 131, 125, 87, 39,,, -6, 4, 1, 2, 3, 3, 1, 3, 128, 131, 125, 87, 39,,, -6, 4, 1, 2, 3, 3, 1, 3, 256, 131, 125, 87, 39,,, -6, 4, 1, 2, 3, 3, 1, 3, 384, 131, 125, 87, 39,,, -6, 4, 1, 2, 3, 3, 2, 1, 128, 131, 125, 87, 39,,, -6, 4, 1, 2, 3, 3, 2, 1, 256, 131, 125, 87, 39,,, -6, 4, 1, 2, 3, 3, 2, 1, 384, 131, 125, 87, 39,,, -6, 4, 1, 2, 3, 3, 2, 2, 128, 131, 125, 87, 39,,, -6, 4, 1, 2, 3, 3, 2, 2, 256, 131, 125, 87, 39,,, -6, 4, 1, 2, 3, 3, 2, 2, 384, 131, 125, 87, 39,,, -6, 4, 1, 2, 3, 3, 2, 3, 128, 131, 125, 87, 39,,, -6, 4, 1, 2, 3, 3, 2, 3, 256, 131, 125, 87, 39,,, -6, 4, 1, 2, 3, 3, 2, 3, 384, 131, 125, 87, 39,,, -6, 4, 1, 2, 3, 3, 3, 1, 128, 131, 125, 87, 39,,, -6, 4, 1, 2, 3, 3, 3, 1, 256, 131, 125, 87, 39,,, -6, 4, 1, 2, 3, 3, 3, 1, 384, 131, 125, 87, 39,,, -6, 4, 1, 2, 3, 3, 3, 2, 128, 131, 125, 87, 39,,, -6, 4, 1, 2, 3, 3, 3, 2, 256, 131, 125, 87, 39,,, -6, 4, 1, 2, 3, 3, 3, 2, 384, 131, 125, 87, 39,,, -6, 4, 1, 2, 3, 3, 3, 3, 128, 131, 125, 87, 39,,, -6, 4, 1, 2, 3, 3, 3, 3, 256, 131, 125, 87, 39,,, -6, 4, 1, 2, 3, 3, 3, 3, 384, 131, 125, 87, 39,,, -6, 4, 1, 3, 1, 1, 1, 1, 128, 195, 195, 129, 66,,, -6, 4, 1, 3, 1, 1, 1, 1, 256, 195, 195, 129, 66,,, -6, 4, 1, 3, 1, 1, 1, 1, 384, 195, 195, 129, 66,,, -6, 4, 1, 3, 2, 2, 1, 1, 128, 195, 192, 129, 60,,, -6, 4, 1, 3, 2, 2, 1, 1, 256, 195, 192, 129, 60,,, -6, 4, 1, 3, 2, 2, 1, 1, 384, 195, 192, 129, 60,,, -6, 4, 1, 3, 2, 2, 1, 2, 128, 195, 192, 129, 60,,, -6, 4, 1, 3, 2, 2, 1, 2, 256, 195, 192, 129, 60,,, -6, 4, 1, 3, 2, 2, 1, 2, 384, 195, 192, 129, 60,,, -6, 4, 1, 3, 2, 2, 2, 1, 128, 195, 192, 129, 60,,, -6, 4, 1, 3, 2, 2, 2, 1, 256, 195, 192, 129, 60,,, -6, 4, 1, 3, 2, 2, 2, 1, 384, 195, 192, 129, 60,,, -6, 4, 1, 3, 2, 2, 2, 2, 128, 195, 192, 129, 60,,, -6, 4, 1, 3, 2, 2, 2, 2, 256, 195, 192, 129, 60,,, -6, 4, 1, 3, 2, 2, 2, 2, 384, 195, 192, 129, 60,,, -6, 4, 1, 3, 3, 3, 1, 1, 128, 195, 186, 129, 57,,, -6, 4, 1, 3, 3, 3, 1, 1, 256, 195, 186, 129, 57,,, -6, 4, 1, 3, 3, 3, 1, 1, 384, 195, 186, 129, 57,,, -6, 4, 1, 3, 3, 3, 1, 2, 128, 195, 186, 129, 57,,, -6, 4, 1, 3, 3, 3, 1, 2, 256, 195, 186, 129, 57,,, -6, 4, 1, 3, 3, 3, 1, 2, 384, 195, 186, 129, 57,,, -6, 4, 1, 3, 3, 3, 1, 3, 128, 195, 186, 129, 57,,, -6, 4, 1, 3, 3, 3, 1, 3, 256, 195, 186, 129, 57,,, -6, 4, 1, 3, 3, 3, 1, 3, 384, 195, 186, 129, 57,,, -6, 4, 1, 3, 3, 3, 2, 1, 128, 195, 186, 129, 57,,, -6, 4, 1, 3, 3, 3, 2, 1, 256, 195, 186, 129, 57,,, -6, 4, 1, 3, 3, 3, 2, 1, 384, 195, 186, 129, 57,,, -6, 4, 1, 3, 3, 3, 2, 2, 128, 195, 186, 129, 57,,, -6, 4, 1, 3, 3, 3, 2, 2, 256, 195, 186, 129, 57,,, -6, 4, 1, 3, 3, 3, 2, 2, 384, 195, 186, 129, 57,,, -6, 4, 1, 3, 3, 3, 2, 3, 128, 195, 186, 129, 57,,, -6, 4, 1, 3, 3, 3, 2, 3, 256, 195, 186, 129, 57,,, -6, 4, 1, 3, 3, 3, 2, 3, 384, 195, 186, 129, 57,,, -6, 4, 1, 3, 3, 3, 3, 1, 128, 195, 186, 129, 57,,, -6, 4, 1, 3, 3, 3, 3, 1, 256, 195, 186, 129, 57,,, -6, 4, 1, 3, 3, 3, 3, 1, 384, 195, 186, 129, 57,,, -6, 4, 1, 3, 3, 3, 3, 2, 128, 195, 186, 129, 57,,, -6, 4, 1, 3, 3, 3, 3, 2, 256, 195, 186, 129, 57,,, -6, 4, 1, 3, 3, 3, 3, 2, 384, 195, 186, 129, 57,,, -6, 4, 1, 3, 3, 3, 3, 3, 128, 195, 186, 129, 57,,, -6, 4, 1, 3, 3, 3, 3, 3, 256, 195, 186, 129, 57,,, -6, 4, 1, 3, 3, 3, 3, 3, 384, 195, 186, 129, 57,,, -6, 4, 1, 4, 1, 1, 1, 1, 128, 240, 240, 171, 87,,, -6, 4, 1, 4, 1, 1, 1, 1, 256, 240, 240, 171, 87,,, -6, 4, 1, 4, 1, 1, 1, 1, 384, 240, 240, 171, 87,,, -6, 4, 1, 4, 2, 2, 1, 1, 128, 240, 240, 171, 79,,, -6, 4, 1, 4, 2, 2, 1, 1, 256, 240, 240, 171, 79,,, -6, 4, 1, 4, 2, 2, 1, 1, 384, 240, 240, 171, 79,,, -6, 4, 1, 4, 2, 2, 1, 2, 128, 240, 240, 171, 79,,, -6, 4, 1, 4, 2, 2, 1, 2, 256, 240, 240, 171, 79,,, -6, 4, 1, 4, 2, 2, 1, 2, 384, 240, 240, 171, 79,,, -6, 4, 1, 4, 2, 2, 2, 1, 128, 240, 240, 171, 79,,, -6, 4, 1, 4, 2, 2, 2, 1, 256, 240, 240, 171, 79,,, -6, 4, 1, 4, 2, 2, 2, 1, 384, 240, 240, 171, 79,,, -6, 4, 1, 4, 2, 2, 2, 2, 128, 240, 240, 171, 79,,, -6, 4, 1, 4, 2, 2, 2, 2, 256, 240, 240, 171, 79,,, -6, 4, 1, 4, 2, 2, 2, 2, 384, 240, 240, 171, 79,,, -6, 4, 1, 4, 3, 3, 1, 1, 128, 240, 240, 171, 75,,, -6, 4, 1, 4, 3, 3, 1, 1, 256, 240, 240, 171, 75,,, -6, 4, 1, 4, 3, 3, 1, 1, 384, 240, 240, 171, 75,,, -6, 4, 1, 4, 3, 3, 1, 2, 128, 240, 240, 171, 75,,, -6, 4, 1, 4, 3, 3, 1, 2, 256, 240, 240, 171, 75,,, -6, 4, 1, 4, 3, 3, 1, 2, 384, 240, 240, 171, 75,,, -6, 4, 1, 4, 3, 3, 1, 3, 128, 240, 240, 171, 75,,, -6, 4, 1, 4, 3, 3, 1, 3, 256, 240, 240, 171, 75,,, -6, 4, 1, 4, 3, 3, 1, 3, 384, 240, 240, 171, 75,,, -6, 4, 1, 4, 3, 3, 2, 1, 128, 240, 240, 171, 75,,, -6, 4, 1, 4, 3, 3, 2, 1, 256, 240, 240, 171, 75,,, -6, 4, 1, 4, 3, 3, 2, 1, 384, 240, 240, 171, 75,,, -6, 4, 1, 4, 3, 3, 2, 2, 128, 240, 240, 171, 75,,, -6, 4, 1, 4, 3, 3, 2, 2, 256, 240, 240, 171, 75,,, -6, 4, 1, 4, 3, 3, 2, 2, 384, 240, 240, 171, 75,,, -6, 4, 1, 4, 3, 3, 2, 3, 128, 240, 240, 171, 75,,, -6, 4, 1, 4, 3, 3, 2, 3, 256, 240, 240, 171, 75,,, -6, 4, 1, 4, 3, 3, 2, 3, 384, 240, 240, 171, 75,,, -6, 4, 1, 4, 3, 3, 3, 1, 128, 240, 240, 171, 75,,, -6, 4, 1, 4, 3, 3, 3, 1, 256, 240, 240, 171, 75,,, -6, 4, 1, 4, 3, 3, 3, 1, 384, 240, 240, 171, 75,,, -6, 4, 1, 4, 3, 3, 3, 2, 128, 240, 240, 171, 75,,, -6, 4, 1, 4, 3, 3, 3, 2, 256, 240, 240, 171, 75,,, -6, 4, 1, 4, 3, 3, 3, 2, 384, 240, 240, 171, 75,,, -6, 4, 1, 4, 3, 3, 3, 3, 128, 240, 240, 171, 75,,, -6, 4, 1, 4, 3, 3, 3, 3, 256, 240, 240, 171, 75,,, -6, 4, 1, 4, 3, 3, 3, 3, 384, 240, 240, 171, 75,,, -6, 4, 2, 1, 1, 1, 1, 1, 128, 67, 67, 45, 24,,, -6, 4, 2, 1, 1, 1, 1, 1, 256, 67, 67, 45, 24,,, -6, 4, 2, 1, 1, 1, 1, 1, 384, 67, 67, 45, 24,,, -6, 4, 2, 1, 2, 2, 1, 1, 128, 67, 66, 45, 22,,, -6, 4, 2, 1, 2, 2, 1, 1, 256, 67, 66, 45, 22,,, -6, 4, 2, 1, 2, 2, 1, 1, 384, 67, 66, 45, 22,,, -6, 4, 2, 1, 2, 2, 1, 2, 128, 67, 66, 45, 22,,, -6, 4, 2, 1, 2, 2, 1, 2, 256, 67, 66, 45, 22,,, -6, 4, 2, 1, 2, 2, 1, 2, 384, 67, 66, 45, 22,,, -6, 4, 2, 1, 2, 2, 2, 1, 128, 67, 66, 45, 22,,, -6, 4, 2, 1, 2, 2, 2, 1, 256, 67, 66, 45, 22,,, -6, 4, 2, 1, 2, 2, 2, 1, 384, 67, 66, 45, 22,,, -6, 4, 2, 1, 2, 2, 2, 2, 128, 67, 66, 45, 22,,, -6, 4, 2, 1, 2, 2, 2, 2, 256, 67, 66, 45, 22,,, -6, 4, 2, 1, 2, 2, 2, 2, 384, 67, 66, 45, 22,,, -6, 4, 2, 1, 3, 3, 1, 1, 128, 67, 64, 45, 21,,, -6, 4, 2, 1, 3, 3, 1, 1, 256, 67, 64, 45, 21,,, -6, 4, 2, 1, 3, 3, 1, 1, 384, 67, 64, 45, 21,,, -6, 4, 2, 1, 3, 3, 1, 2, 128, 67, 64, 45, 21,,, -6, 4, 2, 1, 3, 3, 1, 2, 256, 67, 64, 45, 21,,, -6, 4, 2, 1, 3, 3, 1, 2, 384, 67, 64, 45, 21,,, -6, 4, 2, 1, 3, 3, 1, 3, 128, 67, 64, 45, 21,,, -6, 4, 2, 1, 3, 3, 1, 3, 256, 67, 64, 45, 21,,, -6, 4, 2, 1, 3, 3, 1, 3, 384, 67, 64, 45, 21,,, -6, 4, 2, 1, 3, 3, 2, 1, 128, 67, 64, 45, 21,,, -6, 4, 2, 1, 3, 3, 2, 1, 256, 67, 64, 45, 21,,, -6, 4, 2, 1, 3, 3, 2, 1, 384, 67, 64, 45, 21,,, -6, 4, 2, 1, 3, 3, 2, 2, 128, 67, 64, 45, 21,,, -6, 4, 2, 1, 3, 3, 2, 2, 256, 67, 64, 45, 21,,, -6, 4, 2, 1, 3, 3, 2, 2, 384, 67, 64, 45, 21,,, -6, 4, 2, 1, 3, 3, 2, 3, 128, 67, 64, 45, 21,,, -6, 4, 2, 1, 3, 3, 2, 3, 256, 67, 64, 45, 21,,, -6, 4, 2, 1, 3, 3, 2, 3, 384, 67, 64, 45, 21,,, -6, 4, 2, 1, 3, 3, 3, 1, 128, 67, 64, 45, 21,,, -6, 4, 2, 1, 3, 3, 3, 1, 256, 67, 64, 45, 21,,, -6, 4, 2, 1, 3, 3, 3, 1, 384, 67, 64, 45, 21,,, -6, 4, 2, 1, 3, 3, 3, 2, 128, 67, 64, 45, 21,,, -6, 4, 2, 1, 3, 3, 3, 2, 256, 67, 64, 45, 21,,, -6, 4, 2, 1, 3, 3, 3, 2, 384, 67, 64, 45, 21,,, -6, 4, 2, 1, 3, 3, 3, 3, 128, 67, 64, 45, 21,,, -6, 4, 2, 1, 3, 3, 3, 3, 256, 67, 64, 45, 21,,, -6, 4, 2, 1, 3, 3, 3, 3, 384, 67, 64, 45, 21,,, -6, 4, 2, 2, 1, 1, 1, 1, 128, 131, 131, 87, 45,,, -6, 4, 2, 2, 1, 1, 1, 1, 256, 131, 131, 87, 45,,, -6, 4, 2, 2, 1, 1, 1, 1, 384, 131, 131, 87, 45,,, -6, 4, 2, 2, 2, 2, 1, 1, 128, 131, 129, 87, 41,,, -6, 4, 2, 2, 2, 2, 1, 1, 256, 131, 129, 87, 41,,, -6, 4, 2, 2, 2, 2, 1, 1, 384, 131, 129, 87, 41,,, -6, 4, 2, 2, 2, 2, 1, 2, 128, 131, 129, 87, 41,,, -6, 4, 2, 2, 2, 2, 1, 2, 256, 131, 129, 87, 41,,, -6, 4, 2, 2, 2, 2, 1, 2, 384, 131, 129, 87, 41,,, -6, 4, 2, 2, 2, 2, 2, 1, 128, 131, 129, 87, 41,,, -6, 4, 2, 2, 2, 2, 2, 1, 256, 131, 129, 87, 41,,, -6, 4, 2, 2, 2, 2, 2, 1, 384, 131, 129, 87, 41,,, -6, 4, 2, 2, 2, 2, 2, 2, 128, 131, 129, 87, 41,,, -6, 4, 2, 2, 2, 2, 2, 2, 256, 131, 129, 87, 41,,, -6, 4, 2, 2, 2, 2, 2, 2, 384, 131, 129, 87, 41,,, -6, 4, 2, 2, 3, 3, 1, 1, 128, 131, 125, 87, 39,,, -6, 4, 2, 2, 3, 3, 1, 1, 256, 131, 125, 87, 39,,, -6, 4, 2, 2, 3, 3, 1, 1, 384, 131, 125, 87, 39,,, -6, 4, 2, 2, 3, 3, 1, 2, 128, 131, 125, 87, 39,,, -6, 4, 2, 2, 3, 3, 1, 2, 256, 131, 125, 87, 39,,, -6, 4, 2, 2, 3, 3, 1, 2, 384, 131, 125, 87, 39,,, -6, 4, 2, 2, 3, 3, 1, 3, 128, 131, 125, 87, 39,,, -6, 4, 2, 2, 3, 3, 1, 3, 256, 131, 125, 87, 39,,, -6, 4, 2, 2, 3, 3, 1, 3, 384, 131, 125, 87, 39,,, -6, 4, 2, 2, 3, 3, 2, 1, 128, 131, 125, 87, 39,,, -6, 4, 2, 2, 3, 3, 2, 1, 256, 131, 125, 87, 39,,, -6, 4, 2, 2, 3, 3, 2, 1, 384, 131, 125, 87, 39,,, -6, 4, 2, 2, 3, 3, 2, 2, 128, 131, 125, 87, 39,,, -6, 4, 2, 2, 3, 3, 2, 2, 256, 131, 125, 87, 39,,, -6, 4, 2, 2, 3, 3, 2, 2, 384, 131, 125, 87, 39,,, -6, 4, 2, 2, 3, 3, 2, 3, 128, 131, 125, 87, 39,,, -6, 4, 2, 2, 3, 3, 2, 3, 256, 131, 125, 87, 39,,, -6, 4, 2, 2, 3, 3, 2, 3, 384, 131, 125, 87, 39,,, -6, 4, 2, 2, 3, 3, 3, 1, 128, 131, 125, 87, 39,,, -6, 4, 2, 2, 3, 3, 3, 1, 256, 131, 125, 87, 39,,, -6, 4, 2, 2, 3, 3, 3, 1, 384, 131, 125, 87, 39,,, -6, 4, 2, 2, 3, 3, 3, 2, 128, 131, 125, 87, 39,,, -6, 4, 2, 2, 3, 3, 3, 2, 256, 131, 125, 87, 39,,, -6, 4, 2, 2, 3, 3, 3, 2, 384, 131, 125, 87, 39,,, -6, 4, 2, 2, 3, 3, 3, 3, 128, 131, 125, 87, 39,,, -6, 4, 2, 2, 3, 3, 3, 3, 256, 131, 125, 87, 39,,, -6, 4, 2, 2, 3, 3, 3, 3, 384, 131, 125, 87, 39,,, -6, 4, 2, 3, 1, 1, 1, 1, 128, 195, 195, 129, 66,,, -6, 4, 2, 3, 1, 1, 1, 1, 256, 195, 195, 129, 66,,, -6, 4, 2, 3, 1, 1, 1, 1, 384, 195, 195, 129, 66,,, -6, 4, 2, 3, 2, 2, 1, 1, 128, 195, 192, 129, 60,,, -6, 4, 2, 3, 2, 2, 1, 1, 256, 195, 192, 129, 60,,, -6, 4, 2, 3, 2, 2, 1, 1, 384, 195, 192, 129, 60,,, -6, 4, 2, 3, 2, 2, 1, 2, 128, 195, 192, 129, 60,,, -6, 4, 2, 3, 2, 2, 1, 2, 256, 195, 192, 129, 60,,, -6, 4, 2, 3, 2, 2, 1, 2, 384, 195, 192, 129, 60,,, -6, 4, 2, 3, 2, 2, 2, 1, 128, 195, 192, 129, 60,,, -6, 4, 2, 3, 2, 2, 2, 1, 256, 195, 192, 129, 60,,, -6, 4, 2, 3, 2, 2, 2, 1, 384, 195, 192, 129, 60,,, -6, 4, 2, 3, 2, 2, 2, 2, 128, 195, 192, 129, 60,,, -6, 4, 2, 3, 2, 2, 2, 2, 256, 195, 192, 129, 60,,, -6, 4, 2, 3, 2, 2, 2, 2, 384, 195, 192, 129, 60,,, -6, 4, 2, 3, 3, 3, 1, 1, 128, 195, 186, 129, 57,,, -6, 4, 2, 3, 3, 3, 1, 1, 256, 195, 186, 129, 57,,, -6, 4, 2, 3, 3, 3, 1, 1, 384, 195, 186, 129, 57,,, -6, 4, 2, 3, 3, 3, 1, 2, 128, 195, 186, 129, 57,,, -6, 4, 2, 3, 3, 3, 1, 2, 256, 195, 186, 129, 57,,, -6, 4, 2, 3, 3, 3, 1, 2, 384, 195, 186, 129, 57,,, -6, 4, 2, 3, 3, 3, 1, 3, 128, 195, 186, 129, 57,,, -6, 4, 2, 3, 3, 3, 1, 3, 256, 195, 186, 129, 57,,, -6, 4, 2, 3, 3, 3, 1, 3, 384, 195, 186, 129, 57,,, -6, 4, 2, 3, 3, 3, 2, 1, 128, 195, 186, 129, 57,,, -6, 4, 2, 3, 3, 3, 2, 1, 256, 195, 186, 129, 57,,, -6, 4, 2, 3, 3, 3, 2, 1, 384, 195, 186, 129, 57,,, -6, 4, 2, 3, 3, 3, 2, 2, 128, 195, 186, 129, 57,,, -6, 4, 2, 3, 3, 3, 2, 2, 256, 195, 186, 129, 57,,, -6, 4, 2, 3, 3, 3, 2, 2, 384, 195, 186, 129, 57,,, -6, 4, 2, 3, 3, 3, 2, 3, 128, 195, 186, 129, 57,,, -6, 4, 2, 3, 3, 3, 2, 3, 256, 195, 186, 129, 57,,, -6, 4, 2, 3, 3, 3, 2, 3, 384, 195, 186, 129, 57,,, -6, 4, 2, 3, 3, 3, 3, 1, 128, 195, 186, 129, 57,,, -6, 4, 2, 3, 3, 3, 3, 1, 256, 195, 186, 129, 57,,, -6, 4, 2, 3, 3, 3, 3, 1, 384, 195, 186, 129, 57,,, -6, 4, 2, 3, 3, 3, 3, 2, 128, 195, 186, 129, 57,,, -6, 4, 2, 3, 3, 3, 3, 2, 256, 195, 186, 129, 57,,, -6, 4, 2, 3, 3, 3, 3, 2, 384, 195, 186, 129, 57,,, -6, 4, 2, 3, 3, 3, 3, 3, 128, 195, 186, 129, 57,,, -6, 4, 2, 3, 3, 3, 3, 3, 256, 195, 186, 129, 57,,, -6, 4, 2, 3, 3, 3, 3, 3, 384, 195, 186, 129, 57,,, -6, 4, 2, 4, 1, 1, 1, 1, 128, 240, 240, 171, 87,,, -6, 4, 2, 4, 1, 1, 1, 1, 256, 240, 240, 171, 87,,, -6, 4, 2, 4, 1, 1, 1, 1, 384, 240, 240, 171, 87,,, -6, 4, 2, 4, 2, 2, 1, 1, 128, 240, 240, 171, 79,,, -6, 4, 2, 4, 2, 2, 1, 1, 256, 240, 240, 171, 79,,, -6, 4, 2, 4, 2, 2, 1, 1, 384, 240, 240, 171, 79,,, -6, 4, 2, 4, 2, 2, 1, 2, 128, 240, 240, 171, 79,,, -6, 4, 2, 4, 2, 2, 1, 2, 256, 240, 240, 171, 79,,, -6, 4, 2, 4, 2, 2, 1, 2, 384, 240, 240, 171, 79,,, -6, 4, 2, 4, 2, 2, 2, 1, 128, 240, 240, 171, 79,,, -6, 4, 2, 4, 2, 2, 2, 1, 256, 240, 240, 171, 79,,, -6, 4, 2, 4, 2, 2, 2, 1, 384, 240, 240, 171, 79,,, -6, 4, 2, 4, 2, 2, 2, 2, 128, 240, 240, 171, 79,,, -6, 4, 2, 4, 2, 2, 2, 2, 256, 240, 240, 171, 79,,, -6, 4, 2, 4, 2, 2, 2, 2, 384, 240, 240, 171, 79,,, -6, 4, 2, 4, 3, 3, 1, 1, 128, 240, 240, 171, 75,,, -6, 4, 2, 4, 3, 3, 1, 1, 256, 240, 240, 171, 75,,, -6, 4, 2, 4, 3, 3, 1, 1, 384, 240, 240, 171, 75,,, -6, 4, 2, 4, 3, 3, 1, 2, 128, 240, 240, 171, 75,,, -6, 4, 2, 4, 3, 3, 1, 2, 256, 240, 240, 171, 75,,, -6, 4, 2, 4, 3, 3, 1, 2, 384, 240, 240, 171, 75,,, -6, 4, 2, 4, 3, 3, 1, 3, 128, 240, 240, 171, 75,,, -6, 4, 2, 4, 3, 3, 1, 3, 256, 240, 240, 171, 75,,, -6, 4, 2, 4, 3, 3, 1, 3, 384, 240, 240, 171, 75,,, -6, 4, 2, 4, 3, 3, 2, 1, 128, 240, 240, 171, 75,,, -6, 4, 2, 4, 3, 3, 2, 1, 256, 240, 240, 171, 75,,, -6, 4, 2, 4, 3, 3, 2, 1, 384, 240, 240, 171, 75,,, -6, 4, 2, 4, 3, 3, 2, 2, 128, 240, 240, 171, 75,,, -6, 4, 2, 4, 3, 3, 2, 2, 256, 240, 240, 171, 75,,, -6, 4, 2, 4, 3, 3, 2, 2, 384, 240, 240, 171, 75,,, -6, 4, 2, 4, 3, 3, 2, 3, 128, 240, 240, 171, 75,,, -6, 4, 2, 4, 3, 3, 2, 3, 256, 240, 240, 171, 75,,, -6, 4, 2, 4, 3, 3, 2, 3, 384, 240, 240, 171, 75,,, -6, 4, 2, 4, 3, 3, 3, 1, 128, 240, 240, 171, 75,,, -6, 4, 2, 4, 3, 3, 3, 1, 256, 240, 240, 171, 75,,, -6, 4, 2, 4, 3, 3, 3, 1, 384, 240, 240, 171, 75,,, -6, 4, 2, 4, 3, 3, 3, 2, 128, 240, 240, 171, 75,,, -6, 4, 2, 4, 3, 3, 3, 2, 256, 240, 240, 171, 75,,, -6, 4, 2, 4, 3, 3, 3, 2, 384, 240, 240, 171, 75,,, -6, 4, 2, 4, 3, 3, 3, 3, 128, 240, 240, 171, 75,,, -6, 4, 2, 4, 3, 3, 3, 3, 256, 240, 240, 171, 75,,, -6, 4, 2, 4, 3, 3, 3, 3, 384, 240, 240, 171, 75,,, -6, 4, 3, 1, 1, 1, 1, 1, 128, 67, 67, 45, 24,,, -6, 4, 3, 1, 1, 1, 1, 1, 256, 67, 67, 45, 24,,, -6, 4, 3, 1, 1, 1, 1, 1, 384, 67, 67, 45, 24,,, -6, 4, 3, 1, 2, 2, 1, 1, 128, 67, 66, 45, 22,,, -6, 4, 3, 1, 2, 2, 1, 1, 256, 67, 66, 45, 22,,, -6, 4, 3, 1, 2, 2, 1, 1, 384, 67, 66, 45, 22,,, -6, 4, 3, 1, 2, 2, 1, 2, 128, 67, 66, 45, 22,,, -6, 4, 3, 1, 2, 2, 1, 2, 256, 67, 66, 45, 22,,, -6, 4, 3, 1, 2, 2, 1, 2, 384, 67, 66, 45, 22,,, -6, 4, 3, 1, 2, 2, 2, 1, 128, 67, 66, 45, 22,,, -6, 4, 3, 1, 2, 2, 2, 1, 256, 67, 66, 45, 22,,, -6, 4, 3, 1, 2, 2, 2, 1, 384, 67, 66, 45, 22,,, -6, 4, 3, 1, 2, 2, 2, 2, 128, 67, 66, 45, 22,,, -6, 4, 3, 1, 2, 2, 2, 2, 256, 67, 66, 45, 22,,, -6, 4, 3, 1, 2, 2, 2, 2, 384, 67, 66, 45, 22,,, -6, 4, 3, 1, 3, 3, 1, 1, 128, 67, 64, 45, 21,,, -6, 4, 3, 1, 3, 3, 1, 1, 256, 67, 64, 45, 21,,, -6, 4, 3, 1, 3, 3, 1, 1, 384, 67, 64, 45, 21,,, -6, 4, 3, 1, 3, 3, 1, 2, 128, 67, 64, 45, 21,,, -6, 4, 3, 1, 3, 3, 1, 2, 256, 67, 64, 45, 21,,, -6, 4, 3, 1, 3, 3, 1, 2, 384, 67, 64, 45, 21,,, -6, 4, 3, 1, 3, 3, 1, 3, 128, 67, 64, 45, 21,,, -6, 4, 3, 1, 3, 3, 1, 3, 256, 67, 64, 45, 21,,, -6, 4, 3, 1, 3, 3, 1, 3, 384, 67, 64, 45, 21,,, -6, 4, 3, 1, 3, 3, 2, 1, 128, 67, 64, 45, 21,,, -6, 4, 3, 1, 3, 3, 2, 1, 256, 67, 64, 45, 21,,, -6, 4, 3, 1, 3, 3, 2, 1, 384, 67, 64, 45, 21,,, -6, 4, 3, 1, 3, 3, 2, 2, 128, 67, 64, 45, 21,,, -6, 4, 3, 1, 3, 3, 2, 2, 256, 67, 64, 45, 21,,, -6, 4, 3, 1, 3, 3, 2, 2, 384, 67, 64, 45, 21,,, -6, 4, 3, 1, 3, 3, 2, 3, 128, 67, 64, 45, 21,,, -6, 4, 3, 1, 3, 3, 2, 3, 256, 67, 64, 45, 21,,, -6, 4, 3, 1, 3, 3, 2, 3, 384, 67, 64, 45, 21,,, -6, 4, 3, 1, 3, 3, 3, 1, 128, 67, 64, 45, 21,,, -6, 4, 3, 1, 3, 3, 3, 1, 256, 67, 64, 45, 21,,, -6, 4, 3, 1, 3, 3, 3, 1, 384, 67, 64, 45, 21,,, -6, 4, 3, 1, 3, 3, 3, 2, 128, 67, 64, 45, 21,,, -6, 4, 3, 1, 3, 3, 3, 2, 256, 67, 64, 45, 21,,, -6, 4, 3, 1, 3, 3, 3, 2, 384, 67, 64, 45, 21,,, -6, 4, 3, 1, 3, 3, 3, 3, 128, 67, 64, 45, 21,,, -6, 4, 3, 1, 3, 3, 3, 3, 256, 67, 64, 45, 21,,, -6, 4, 3, 1, 3, 3, 3, 3, 384, 67, 64, 45, 21,,, -6, 4, 3, 2, 1, 1, 1, 1, 128, 131, 131, 87, 45,,, -6, 4, 3, 2, 1, 1, 1, 1, 256, 131, 131, 87, 45,,, -6, 4, 3, 2, 1, 1, 1, 1, 384, 131, 131, 87, 45,,, -6, 4, 3, 2, 2, 2, 1, 1, 128, 131, 129, 87, 41,,, -6, 4, 3, 2, 2, 2, 1, 1, 256, 131, 129, 87, 41,,, -6, 4, 3, 2, 2, 2, 1, 1, 384, 131, 129, 87, 41,,, -6, 4, 3, 2, 2, 2, 1, 2, 128, 131, 129, 87, 41,,, -6, 4, 3, 2, 2, 2, 1, 2, 256, 131, 129, 87, 41,,, -6, 4, 3, 2, 2, 2, 1, 2, 384, 131, 129, 87, 41,,, -6, 4, 3, 2, 2, 2, 2, 1, 128, 131, 129, 87, 41,,, -6, 4, 3, 2, 2, 2, 2, 1, 256, 131, 129, 87, 41,,, -6, 4, 3, 2, 2, 2, 2, 1, 384, 131, 129, 87, 41,,, -6, 4, 3, 2, 2, 2, 2, 2, 128, 131, 129, 87, 41,,, -6, 4, 3, 2, 2, 2, 2, 2, 256, 131, 129, 87, 41,,, -6, 4, 3, 2, 2, 2, 2, 2, 384, 131, 129, 87, 41,,, -6, 4, 3, 2, 3, 3, 1, 1, 128, 131, 125, 87, 39,,, -6, 4, 3, 2, 3, 3, 1, 1, 256, 131, 125, 87, 39,,, -6, 4, 3, 2, 3, 3, 1, 1, 384, 131, 125, 87, 39,,, -6, 4, 3, 2, 3, 3, 1, 2, 128, 131, 125, 87, 39,,, -6, 4, 3, 2, 3, 3, 1, 2, 256, 131, 125, 87, 39,,, -6, 4, 3, 2, 3, 3, 1, 2, 384, 131, 125, 87, 39,,, -6, 4, 3, 2, 3, 3, 1, 3, 128, 131, 125, 87, 39,,, -6, 4, 3, 2, 3, 3, 1, 3, 256, 131, 125, 87, 39,,, -6, 4, 3, 2, 3, 3, 1, 3, 384, 131, 125, 87, 39,,, -6, 4, 3, 2, 3, 3, 2, 1, 128, 131, 125, 87, 39,,, -6, 4, 3, 2, 3, 3, 2, 1, 256, 131, 125, 87, 39,,, -6, 4, 3, 2, 3, 3, 2, 1, 384, 131, 125, 87, 39,,, -6, 4, 3, 2, 3, 3, 2, 2, 128, 131, 125, 87, 39,,, -6, 4, 3, 2, 3, 3, 2, 2, 256, 131, 125, 87, 39,,, -6, 4, 3, 2, 3, 3, 2, 2, 384, 131, 125, 87, 39,,, -6, 4, 3, 2, 3, 3, 2, 3, 128, 131, 125, 87, 39,,, -6, 4, 3, 2, 3, 3, 2, 3, 256, 131, 125, 87, 39,,, -6, 4, 3, 2, 3, 3, 2, 3, 384, 131, 125, 87, 39,,, -6, 4, 3, 2, 3, 3, 3, 1, 128, 131, 125, 87, 39,,, -6, 4, 3, 2, 3, 3, 3, 1, 256, 131, 125, 87, 39,,, -6, 4, 3, 2, 3, 3, 3, 1, 384, 131, 125, 87, 39,,, -6, 4, 3, 2, 3, 3, 3, 2, 128, 131, 125, 87, 39,,, -6, 4, 3, 2, 3, 3, 3, 2, 256, 131, 125, 87, 39,,, -6, 4, 3, 2, 3, 3, 3, 2, 384, 131, 125, 87, 39,,, -6, 4, 3, 2, 3, 3, 3, 3, 128, 131, 125, 87, 39,,, -6, 4, 3, 2, 3, 3, 3, 3, 256, 131, 125, 87, 39,,, -6, 4, 3, 2, 3, 3, 3, 3, 384, 131, 125, 87, 39,,, -6, 4, 3, 3, 1, 1, 1, 1, 128, 195, 195, 129, 66,,, -6, 4, 3, 3, 1, 1, 1, 1, 256, 195, 195, 129, 66,,, -6, 4, 3, 3, 1, 1, 1, 1, 384, 195, 195, 129, 66,,, -6, 4, 3, 3, 2, 2, 1, 1, 128, 195, 192, 129, 60,,, -6, 4, 3, 3, 2, 2, 1, 1, 256, 195, 192, 129, 60,,, -6, 4, 3, 3, 2, 2, 1, 1, 384, 195, 192, 129, 60,,, -6, 4, 3, 3, 2, 2, 1, 2, 128, 195, 192, 129, 60,,, -6, 4, 3, 3, 2, 2, 1, 2, 256, 195, 192, 129, 60,,, -6, 4, 3, 3, 2, 2, 1, 2, 384, 195, 192, 129, 60,,, -6, 4, 3, 3, 2, 2, 2, 1, 128, 195, 192, 129, 60,,, -6, 4, 3, 3, 2, 2, 2, 1, 256, 195, 192, 129, 60,,, -6, 4, 3, 3, 2, 2, 2, 1, 384, 195, 192, 129, 60,,, -6, 4, 3, 3, 2, 2, 2, 2, 128, 195, 192, 129, 60,,, -6, 4, 3, 3, 2, 2, 2, 2, 256, 195, 192, 129, 60,,, -6, 4, 3, 3, 2, 2, 2, 2, 384, 195, 192, 129, 60,,, -6, 4, 3, 3, 3, 3, 1, 1, 128, 195, 186, 129, 57,,, -6, 4, 3, 3, 3, 3, 1, 1, 256, 195, 186, 129, 57,,, -6, 4, 3, 3, 3, 3, 1, 1, 384, 195, 186, 129, 57,,, -6, 4, 3, 3, 3, 3, 1, 2, 128, 195, 186, 129, 57,,, -6, 4, 3, 3, 3, 3, 1, 2, 256, 195, 186, 129, 57,,, -6, 4, 3, 3, 3, 3, 1, 2, 384, 195, 186, 129, 57,,, -6, 4, 3, 3, 3, 3, 1, 3, 128, 195, 186, 129, 57,,, -6, 4, 3, 3, 3, 3, 1, 3, 256, 195, 186, 129, 57,,, -6, 4, 3, 3, 3, 3, 1, 3, 384, 195, 186, 129, 57,,, -6, 4, 3, 3, 3, 3, 2, 1, 128, 195, 186, 129, 57,,, -6, 4, 3, 3, 3, 3, 2, 1, 256, 195, 186, 129, 57,,, -6, 4, 3, 3, 3, 3, 2, 1, 384, 195, 186, 129, 57,,, -6, 4, 3, 3, 3, 3, 2, 2, 128, 195, 186, 129, 57,,, -6, 4, 3, 3, 3, 3, 2, 2, 256, 195, 186, 129, 57,,, -6, 4, 3, 3, 3, 3, 2, 2, 384, 195, 186, 129, 57,,, -6, 4, 3, 3, 3, 3, 2, 3, 128, 195, 186, 129, 57,,, -6, 4, 3, 3, 3, 3, 2, 3, 256, 195, 186, 129, 57,,, -6, 4, 3, 3, 3, 3, 2, 3, 384, 195, 186, 129, 57,,, -6, 4, 3, 3, 3, 3, 3, 1, 128, 195, 186, 129, 57,,, -6, 4, 3, 3, 3, 3, 3, 1, 256, 195, 186, 129, 57,,, -6, 4, 3, 3, 3, 3, 3, 1, 384, 195, 186, 129, 57,,, -6, 4, 3, 3, 3, 3, 3, 2, 128, 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4, 2, 2, 2, 2, 384, 240, 240, 171, 79,,, -6, 4, 3, 4, 3, 3, 1, 1, 128, 240, 240, 171, 75,,, -6, 4, 3, 4, 3, 3, 1, 1, 256, 240, 240, 171, 75,,, -6, 4, 3, 4, 3, 3, 1, 1, 384, 240, 240, 171, 75,,, -6, 4, 3, 4, 3, 3, 1, 2, 128, 240, 240, 171, 75,,, -6, 4, 3, 4, 3, 3, 1, 2, 256, 240, 240, 171, 75,,, -6, 4, 3, 4, 3, 3, 1, 2, 384, 240, 240, 171, 75,,, -6, 4, 3, 4, 3, 3, 1, 3, 128, 240, 240, 171, 75,,, -6, 4, 3, 4, 3, 3, 1, 3, 256, 240, 240, 171, 75,,, -6, 4, 3, 4, 3, 3, 1, 3, 384, 240, 240, 171, 75,,, -6, 4, 3, 4, 3, 3, 2, 1, 128, 240, 240, 171, 75,,, -6, 4, 3, 4, 3, 3, 2, 1, 256, 240, 240, 171, 75,,, -6, 4, 3, 4, 3, 3, 2, 1, 384, 240, 240, 171, 75,,, -6, 4, 3, 4, 3, 3, 2, 2, 128, 240, 240, 171, 75,,, -6, 4, 3, 4, 3, 3, 2, 2, 256, 240, 240, 171, 75,,, -6, 4, 3, 4, 3, 3, 2, 2, 384, 240, 240, 171, 75,,, -6, 4, 3, 4, 3, 3, 2, 3, 128, 240, 240, 171, 75,,, -6, 4, 3, 4, 3, 3, 2, 3, 256, 240, 240, 171, 75,,, -6, 4, 3, 4, 3, 3, 2, 3, 384, 240, 240, 171, 75,,, -6, 4, 3, 4, 3, 3, 3, 1, 128, 240, 240, 171, 75,,, -6, 4, 3, 4, 3, 3, 3, 1, 256, 240, 240, 171, 75,,, -6, 4, 3, 4, 3, 3, 3, 1, 384, 240, 240, 171, 75,,, -6, 4, 3, 4, 3, 3, 3, 2, 128, 240, 240, 171, 75,,, -6, 4, 3, 4, 3, 3, 3, 2, 256, 240, 240, 171, 75,,, -6, 4, 3, 4, 3, 3, 3, 2, 384, 240, 240, 171, 75,,, -6, 4, 3, 4, 3, 3, 3, 3, 128, 240, 240, 171, 75,,, -6, 4, 3, 4, 3, 3, 3, 3, 256, 240, 240, 171, 75,,, -6, 4, 3, 4, 3, 3, 3, 3, 384, 240, 240, 171, 75,,, -6, 4, 4, 1, 1, 1, 1, 1, 128, 67, 67, 45, 24,,, -6, 4, 4, 1, 1, 1, 1, 1, 256, 67, 67, 45, 24,,, -6, 4, 4, 1, 1, 1, 1, 1, 384, 67, 67, 45, 24,,, -6, 4, 4, 1, 2, 2, 1, 1, 128, 67, 66, 45, 22,,, -6, 4, 4, 1, 2, 2, 1, 1, 256, 67, 66, 45, 22,,, -6, 4, 4, 1, 2, 2, 1, 1, 384, 67, 66, 45, 22,,, -6, 4, 4, 1, 2, 2, 1, 2, 128, 67, 66, 45, 22,,, -6, 4, 4, 1, 2, 2, 1, 2, 256, 67, 66, 45, 22,,, -6, 4, 4, 1, 2, 2, 1, 2, 384, 67, 66, 45, 22,,, -6, 4, 4, 1, 2, 2, 2, 1, 128, 67, 66, 45, 22,,, -6, 4, 4, 1, 2, 2, 2, 1, 256, 67, 66, 45, 22,,, -6, 4, 4, 1, 2, 2, 2, 1, 384, 67, 66, 45, 22,,, -6, 4, 4, 1, 2, 2, 2, 2, 128, 67, 66, 45, 22,,, -6, 4, 4, 1, 2, 2, 2, 2, 256, 67, 66, 45, 22,,, -6, 4, 4, 1, 2, 2, 2, 2, 384, 67, 66, 45, 22,,, -6, 4, 4, 1, 3, 3, 1, 1, 128, 67, 64, 45, 21,,, -6, 4, 4, 1, 3, 3, 1, 1, 256, 67, 64, 45, 21,,, -6, 4, 4, 1, 3, 3, 1, 1, 384, 67, 64, 45, 21,,, -6, 4, 4, 1, 3, 3, 1, 2, 128, 67, 64, 45, 21,,, -6, 4, 4, 1, 3, 3, 1, 2, 256, 67, 64, 45, 21,,, -6, 4, 4, 1, 3, 3, 1, 2, 384, 67, 64, 45, 21,,, -6, 4, 4, 1, 3, 3, 1, 3, 128, 67, 64, 45, 21,,, -6, 4, 4, 1, 3, 3, 1, 3, 256, 67, 64, 45, 21,,, -6, 4, 4, 1, 3, 3, 1, 3, 384, 67, 64, 45, 21,,, -6, 4, 4, 1, 3, 3, 2, 1, 128, 67, 64, 45, 21,,, -6, 4, 4, 1, 3, 3, 2, 1, 256, 67, 64, 45, 21,,, -6, 4, 4, 1, 3, 3, 2, 1, 384, 67, 64, 45, 21,,, -6, 4, 4, 1, 3, 3, 2, 2, 128, 67, 64, 45, 21,,, -6, 4, 4, 1, 3, 3, 2, 2, 256, 67, 64, 45, 21,,, -6, 4, 4, 1, 3, 3, 2, 2, 384, 67, 64, 45, 21,,, -6, 4, 4, 1, 3, 3, 2, 3, 128, 67, 64, 45, 21,,, -6, 4, 4, 1, 3, 3, 2, 3, 256, 67, 64, 45, 21,,, -6, 4, 4, 1, 3, 3, 2, 3, 384, 67, 64, 45, 21,,, -6, 4, 4, 1, 3, 3, 3, 1, 128, 67, 64, 45, 21,,, -6, 4, 4, 1, 3, 3, 3, 1, 256, 67, 64, 45, 21,,, -6, 4, 4, 1, 3, 3, 3, 1, 384, 67, 64, 45, 21,,, -6, 4, 4, 1, 3, 3, 3, 2, 128, 67, 64, 45, 21,,, -6, 4, 4, 1, 3, 3, 3, 2, 256, 67, 64, 45, 21,,, -6, 4, 4, 1, 3, 3, 3, 2, 384, 67, 64, 45, 21,,, -6, 4, 4, 1, 3, 3, 3, 3, 128, 67, 64, 45, 21,,, -6, 4, 4, 1, 3, 3, 3, 3, 256, 67, 64, 45, 21,,, -6, 4, 4, 1, 3, 3, 3, 3, 384, 67, 64, 45, 21,,, -6, 4, 4, 2, 1, 1, 1, 1, 128, 131, 131, 87, 45,,, -6, 4, 4, 2, 1, 1, 1, 1, 256, 131, 131, 87, 45,,, -6, 4, 4, 2, 1, 1, 1, 1, 384, 131, 131, 87, 45,,, -6, 4, 4, 2, 2, 2, 1, 1, 128, 131, 129, 87, 41,,, -6, 4, 4, 2, 2, 2, 1, 1, 256, 131, 129, 87, 41,,, -6, 4, 4, 2, 2, 2, 1, 1, 384, 131, 129, 87, 41,,, -6, 4, 4, 2, 2, 2, 1, 2, 128, 131, 129, 87, 41,,, -6, 4, 4, 2, 2, 2, 1, 2, 256, 131, 129, 87, 41,,, -6, 4, 4, 2, 2, 2, 1, 2, 384, 131, 129, 87, 41,,, -6, 4, 4, 2, 2, 2, 2, 1, 128, 131, 129, 87, 41,,, -6, 4, 4, 2, 2, 2, 2, 1, 256, 131, 129, 87, 41,,, -6, 4, 4, 2, 2, 2, 2, 1, 384, 131, 129, 87, 41,,, -6, 4, 4, 2, 2, 2, 2, 2, 128, 131, 129, 87, 41,,, -6, 4, 4, 2, 2, 2, 2, 2, 256, 131, 129, 87, 41,,, -6, 4, 4, 2, 2, 2, 2, 2, 384, 131, 129, 87, 41,,, -6, 4, 4, 2, 3, 3, 1, 1, 128, 131, 125, 87, 39,,, -6, 4, 4, 2, 3, 3, 1, 1, 256, 131, 125, 87, 39,,, -6, 4, 4, 2, 3, 3, 1, 1, 384, 131, 125, 87, 39,,, -6, 4, 4, 2, 3, 3, 1, 2, 128, 131, 125, 87, 39,,, -6, 4, 4, 2, 3, 3, 1, 2, 256, 131, 125, 87, 39,,, -6, 4, 4, 2, 3, 3, 1, 2, 384, 131, 125, 87, 39,,, -6, 4, 4, 2, 3, 3, 1, 3, 128, 131, 125, 87, 39,,, -6, 4, 4, 2, 3, 3, 1, 3, 256, 131, 125, 87, 39,,, -6, 4, 4, 2, 3, 3, 1, 3, 384, 131, 125, 87, 39,,, -6, 4, 4, 2, 3, 3, 2, 1, 128, 131, 125, 87, 39,,, -6, 4, 4, 2, 3, 3, 2, 1, 256, 131, 125, 87, 39,,, -6, 4, 4, 2, 3, 3, 2, 1, 384, 131, 125, 87, 39,,, -6, 4, 4, 2, 3, 3, 2, 2, 128, 131, 125, 87, 39,,, -6, 4, 4, 2, 3, 3, 2, 2, 256, 131, 125, 87, 39,,, -6, 4, 4, 2, 3, 3, 2, 2, 384, 131, 125, 87, 39,,, -6, 4, 4, 2, 3, 3, 2, 3, 128, 131, 125, 87, 39,,, -6, 4, 4, 2, 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75,,, -6, 4, 4, 4, 3, 3, 2, 1, 384, 240, 240, 171, 75,,, -6, 4, 4, 4, 3, 3, 2, 2, 128, 240, 240, 171, 75,,, -6, 4, 4, 4, 3, 3, 2, 2, 256, 240, 240, 171, 75,,, -6, 4, 4, 4, 3, 3, 2, 2, 384, 240, 240, 171, 75,,, -6, 4, 4, 4, 3, 3, 2, 3, 128, 240, 240, 171, 75,,, -6, 4, 4, 4, 3, 3, 2, 3, 256, 240, 240, 171, 75,,, -6, 4, 4, 4, 3, 3, 2, 3, 384, 240, 240, 171, 75,,, -6, 4, 4, 4, 3, 3, 3, 1, 128, 240, 240, 171, 75,,, -6, 4, 4, 4, 3, 3, 3, 1, 256, 240, 240, 171, 75,,, -6, 4, 4, 4, 3, 3, 3, 1, 384, 240, 240, 171, 75,,, -6, 4, 4, 4, 3, 3, 3, 2, 128, 240, 240, 171, 75,,, -6, 4, 4, 4, 3, 3, 3, 2, 256, 240, 240, 171, 75,,, -6, 4, 4, 4, 3, 3, 3, 2, 384, 240, 240, 171, 75,,, -6, 4, 4, 4, 3, 3, 3, 3, 128, 240, 240, 171, 75,,, -6, 4, 4, 4, 3, 3, 3, 3, 256, 240, 240, 171, 75,,, -6, 4, 4, 4, 3, 3, 3, 3, 384, 240, 240, 171, 75,,, -6, 4, 5, 1, 1, 1, 1, 1, 128, 67, 67, 45, 24,,, -6, 4, 5, 1, 1, 1, 1, 1, 256, 67, 67, 45, 24,,, -6, 4, 5, 1, 1, 1, 1, 1, 384, 67, 67, 45, 24,,, -6, 4, 5, 1, 2, 2, 1, 1, 128, 67, 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128, 67, 64, 45, 21,,, -6, 4, 5, 1, 3, 3, 2, 1, 256, 67, 64, 45, 21,,, -6, 4, 5, 1, 3, 3, 2, 1, 384, 67, 64, 45, 21,,, -6, 4, 5, 1, 3, 3, 2, 2, 128, 67, 64, 45, 21,,, -6, 4, 5, 1, 3, 3, 2, 2, 256, 67, 64, 45, 21,,, -6, 4, 5, 1, 3, 3, 2, 2, 384, 67, 64, 45, 21,,, -6, 4, 5, 1, 3, 3, 2, 3, 128, 67, 64, 45, 21,,, -6, 4, 5, 1, 3, 3, 2, 3, 256, 67, 64, 45, 21,,, -6, 4, 5, 1, 3, 3, 2, 3, 384, 67, 64, 45, 21,,, -6, 4, 5, 1, 3, 3, 3, 1, 128, 67, 64, 45, 21,,, -6, 4, 5, 1, 3, 3, 3, 1, 256, 67, 64, 45, 21,,, -6, 4, 5, 1, 3, 3, 3, 1, 384, 67, 64, 45, 21,,, -6, 4, 5, 1, 3, 3, 3, 2, 128, 67, 64, 45, 21,,, -6, 4, 5, 1, 3, 3, 3, 2, 256, 67, 64, 45, 21,,, -6, 4, 5, 1, 3, 3, 3, 2, 384, 67, 64, 45, 21,,, -6, 4, 5, 1, 3, 3, 3, 3, 128, 67, 64, 45, 21,,, -6, 4, 5, 1, 3, 3, 3, 3, 256, 67, 64, 45, 21,,, -6, 4, 5, 1, 3, 3, 3, 3, 384, 67, 64, 45, 21,,, -6, 4, 5, 2, 1, 1, 1, 1, 128, 131, 131, 87, 45,,, -6, 4, 5, 2, 1, 1, 1, 1, 256, 131, 131, 87, 45,,, -6, 4, 5, 2, 1, 1, 1, 1, 384, 131, 131, 87, 45,,, -6, 4, 5, 2, 2, 2, 1, 1, 128, 131, 129, 87, 41,,, -6, 4, 5, 2, 2, 2, 1, 1, 256, 131, 129, 87, 41,,, -6, 4, 5, 2, 2, 2, 1, 1, 384, 131, 129, 87, 41,,, -6, 4, 5, 2, 2, 2, 1, 2, 128, 131, 129, 87, 41,,, -6, 4, 5, 2, 2, 2, 1, 2, 256, 131, 129, 87, 41,,, -6, 4, 5, 2, 2, 2, 1, 2, 384, 131, 129, 87, 41,,, -6, 4, 5, 2, 2, 2, 2, 1, 128, 131, 129, 87, 41,,, -6, 4, 5, 2, 2, 2, 2, 1, 256, 131, 129, 87, 41,,, -6, 4, 5, 2, 2, 2, 2, 1, 384, 131, 129, 87, 41,,, -6, 4, 5, 2, 2, 2, 2, 2, 128, 131, 129, 87, 41,,, -6, 4, 5, 2, 2, 2, 2, 2, 256, 131, 129, 87, 41,,, -6, 4, 5, 2, 2, 2, 2, 2, 384, 131, 129, 87, 41,,, -6, 4, 5, 2, 3, 3, 1, 1, 128, 131, 125, 87, 39,,, -6, 4, 5, 2, 3, 3, 1, 1, 256, 131, 125, 87, 39,,, -6, 4, 5, 2, 3, 3, 1, 1, 384, 131, 125, 87, 39,,, -6, 4, 5, 2, 3, 3, 1, 2, 128, 131, 125, 87, 39,,, -6, 4, 5, 2, 3, 3, 1, 2, 256, 131, 125, 87, 39,,, -6, 4, 5, 2, 3, 3, 1, 2, 384, 131, 125, 87, 39,,, -6, 4, 5, 2, 3, 3, 1, 3, 128, 131, 125, 87, 39,,, -6, 4, 5, 2, 3, 3, 1, 3, 256, 131, 125, 87, 39,,, -6, 4, 5, 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3, 3, 256, 195, 186, 129, 57,,, -6, 4, 5, 3, 3, 3, 3, 3, 384, 195, 186, 129, 57,,, -6, 4, 5, 4, 1, 1, 1, 1, 128, 240, 240, 171, 87,,, -6, 4, 5, 4, 1, 1, 1, 1, 256, 240, 240, 171, 87,,, -6, 4, 5, 4, 1, 1, 1, 1, 384, 240, 240, 171, 87,,, -6, 4, 5, 4, 2, 2, 1, 1, 128, 240, 240, 171, 79,,, -6, 4, 5, 4, 2, 2, 1, 1, 256, 240, 240, 171, 79,,, -6, 4, 5, 4, 2, 2, 1, 1, 384, 240, 240, 171, 79,,, -6, 4, 5, 4, 2, 2, 1, 2, 128, 240, 240, 171, 79,,, -6, 4, 5, 4, 2, 2, 1, 2, 256, 240, 240, 171, 79,,, -6, 4, 5, 4, 2, 2, 1, 2, 384, 240, 240, 171, 79,,, -6, 4, 5, 4, 2, 2, 2, 1, 128, 240, 240, 171, 79,,, -6, 4, 5, 4, 2, 2, 2, 1, 256, 240, 240, 171, 79,,, -6, 4, 5, 4, 2, 2, 2, 1, 384, 240, 240, 171, 79,,, -6, 4, 5, 4, 2, 2, 2, 2, 128, 240, 240, 171, 79,,, -6, 4, 5, 4, 2, 2, 2, 2, 256, 240, 240, 171, 79,,, -6, 4, 5, 4, 2, 2, 2, 2, 384, 240, 240, 171, 79,,, -6, 4, 5, 4, 3, 3, 1, 1, 128, 240, 240, 171, 75,,, -6, 4, 5, 4, 3, 3, 1, 1, 256, 240, 240, 171, 75,,, -6, 4, 5, 4, 3, 3, 1, 1, 384, 240, 240, 171, 75,,, -6, 4, 5, 4, 3, 3, 1, 2, 128, 240, 240, 171, 75,,, -6, 4, 5, 4, 3, 3, 1, 2, 256, 240, 240, 171, 75,,, -6, 4, 5, 4, 3, 3, 1, 2, 384, 240, 240, 171, 75,,, -6, 4, 5, 4, 3, 3, 1, 3, 128, 240, 240, 171, 75,,, -6, 4, 5, 4, 3, 3, 1, 3, 256, 240, 240, 171, 75,,, -6, 4, 5, 4, 3, 3, 1, 3, 384, 240, 240, 171, 75,,, -6, 4, 5, 4, 3, 3, 2, 1, 128, 240, 240, 171, 75,,, -6, 4, 5, 4, 3, 3, 2, 1, 256, 240, 240, 171, 75,,, -6, 4, 5, 4, 3, 3, 2, 1, 384, 240, 240, 171, 75,,, -6, 4, 5, 4, 3, 3, 2, 2, 128, 240, 240, 171, 75,,, -6, 4, 5, 4, 3, 3, 2, 2, 256, 240, 240, 171, 75,,, -6, 4, 5, 4, 3, 3, 2, 2, 384, 240, 240, 171, 75,,, -6, 4, 5, 4, 3, 3, 2, 3, 128, 240, 240, 171, 75,,, -6, 4, 5, 4, 3, 3, 2, 3, 256, 240, 240, 171, 75,,, -6, 4, 5, 4, 3, 3, 2, 3, 384, 240, 240, 171, 75,,, -6, 4, 5, 4, 3, 3, 3, 1, 128, 240, 240, 171, 75,,, -6, 4, 5, 4, 3, 3, 3, 1, 256, 240, 240, 171, 75,,, -6, 4, 5, 4, 3, 3, 3, 1, 384, 240, 240, 171, 75,,, -6, 4, 5, 4, 3, 3, 3, 2, 128, 240, 240, 171, 75,,, -6, 4, 5, 4, 3, 3, 3, 2, 256, 240, 240, 171, 75,,, -6, 4, 5, 4, 3, 3, 3, 2, 384, 240, 240, 171, 75,,, -6, 4, 5, 4, 3, 3, 3, 3, 128, 240, 240, 171, 75,,, -6, 4, 5, 4, 3, 3, 3, 3, 256, 240, 240, 171, 75,,, -6, 4, 5, 4, 3, 3, 3, 3, 384, 240, 240, 171, 75,,, -6, 4, 6, 1, 1, 1, 1, 1, 128, 67, 67, 45, 24,,, -6, 4, 6, 1, 1, 1, 1, 1, 256, 67, 67, 45, 24,,, -6, 4, 6, 1, 1, 1, 1, 1, 384, 67, 67, 45, 24,,, -6, 4, 6, 1, 2, 2, 1, 1, 128, 67, 66, 45, 22,,, -6, 4, 6, 1, 2, 2, 1, 1, 256, 67, 66, 45, 22,,, -6, 4, 6, 1, 2, 2, 1, 1, 384, 67, 66, 45, 22,,, -6, 4, 6, 1, 2, 2, 1, 2, 128, 67, 66, 45, 22,,, -6, 4, 6, 1, 2, 2, 1, 2, 256, 67, 66, 45, 22,,, -6, 4, 6, 1, 2, 2, 1, 2, 384, 67, 66, 45, 22,,, -6, 4, 6, 1, 2, 2, 2, 1, 128, 67, 66, 45, 22,,, -6, 4, 6, 1, 2, 2, 2, 1, 256, 67, 66, 45, 22,,, -6, 4, 6, 1, 2, 2, 2, 1, 384, 67, 66, 45, 22,,, -6, 4, 6, 1, 2, 2, 2, 2, 128, 67, 66, 45, 22,,, -6, 4, 6, 1, 2, 2, 2, 2, 256, 67, 66, 45, 22,,, -6, 4, 6, 1, 2, 2, 2, 2, 384, 67, 66, 45, 22,,, -6, 4, 6, 1, 3, 3, 1, 1, 128, 67, 64, 45, 21,,, -6, 4, 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2, 3, 3, 1, 1, 128, 131, 125, 87, 39,,, -6, 4, 6, 2, 3, 3, 1, 1, 256, 131, 125, 87, 39,,, -6, 4, 6, 2, 3, 3, 1, 1, 384, 131, 125, 87, 39,,, -6, 4, 6, 2, 3, 3, 1, 2, 128, 131, 125, 87, 39,,, -6, 4, 6, 2, 3, 3, 1, 2, 256, 131, 125, 87, 39,,, -6, 4, 6, 2, 3, 3, 1, 2, 384, 131, 125, 87, 39,,, -6, 4, 6, 2, 3, 3, 1, 3, 128, 131, 125, 87, 39,,, -6, 4, 6, 2, 3, 3, 1, 3, 256, 131, 125, 87, 39,,, -6, 4, 6, 2, 3, 3, 1, 3, 384, 131, 125, 87, 39,,, -6, 4, 6, 2, 3, 3, 2, 1, 128, 131, 125, 87, 39,,, -6, 4, 6, 2, 3, 3, 2, 1, 256, 131, 125, 87, 39,,, -6, 4, 6, 2, 3, 3, 2, 1, 384, 131, 125, 87, 39,,, -6, 4, 6, 2, 3, 3, 2, 2, 128, 131, 125, 87, 39,,, -6, 4, 6, 2, 3, 3, 2, 2, 256, 131, 125, 87, 39,,, -6, 4, 6, 2, 3, 3, 2, 2, 384, 131, 125, 87, 39,,, -6, 4, 6, 2, 3, 3, 2, 3, 128, 131, 125, 87, 39,,, -6, 4, 6, 2, 3, 3, 2, 3, 256, 131, 125, 87, 39,,, -6, 4, 6, 2, 3, 3, 2, 3, 384, 131, 125, 87, 39,,, -6, 4, 6, 2, 3, 3, 3, 1, 128, 131, 125, 87, 39,,, -6, 4, 6, 2, 3, 3, 3, 1, 256, 131, 125, 87, 39,,, -6, 4, 6, 2, 3, 3, 3, 1, 384, 131, 125, 87, 39,,, -6, 4, 6, 2, 3, 3, 3, 2, 128, 131, 125, 87, 39,,, -6, 4, 6, 2, 3, 3, 3, 2, 256, 131, 125, 87, 39,,, -6, 4, 6, 2, 3, 3, 3, 2, 384, 131, 125, 87, 39,,, -6, 4, 6, 2, 3, 3, 3, 3, 128, 131, 125, 87, 39,,, -6, 4, 6, 2, 3, 3, 3, 3, 256, 131, 125, 87, 39,,, -6, 4, 6, 2, 3, 3, 3, 3, 384, 131, 125, 87, 39,,, -6, 4, 6, 3, 1, 1, 1, 1, 128, 195, 195, 129, 66,,, -6, 4, 6, 3, 1, 1, 1, 1, 256, 195, 195, 129, 66,,, -6, 4, 6, 3, 1, 1, 1, 1, 384, 195, 195, 129, 66,,, -6, 4, 6, 3, 2, 2, 1, 1, 128, 195, 192, 129, 60,,, -6, 4, 6, 3, 2, 2, 1, 1, 256, 195, 192, 129, 60,,, -6, 4, 6, 3, 2, 2, 1, 1, 384, 195, 192, 129, 60,,, -6, 4, 6, 3, 2, 2, 1, 2, 128, 195, 192, 129, 60,,, -6, 4, 6, 3, 2, 2, 1, 2, 256, 195, 192, 129, 60,,, -6, 4, 6, 3, 2, 2, 1, 2, 384, 195, 192, 129, 60,,, -6, 4, 6, 3, 2, 2, 2, 1, 128, 195, 192, 129, 60,,, -6, 4, 6, 3, 2, 2, 2, 1, 256, 195, 192, 129, 60,,, -6, 4, 6, 3, 2, 2, 2, 1, 384, 195, 192, 129, 60,,, -6, 4, 6, 3, 2, 2, 2, 2, 128, 195, 192, 129, 60,,, -6, 4, 6, 3, 2, 2, 2, 2, 256, 195, 192, 129, 60,,, -6, 4, 6, 3, 2, 2, 2, 2, 384, 195, 192, 129, 60,,, -6, 4, 6, 3, 3, 3, 1, 1, 128, 195, 186, 129, 57,,, -6, 4, 6, 3, 3, 3, 1, 1, 256, 195, 186, 129, 57,,, -6, 4, 6, 3, 3, 3, 1, 1, 384, 195, 186, 129, 57,,, -6, 4, 6, 3, 3, 3, 1, 2, 128, 195, 186, 129, 57,,, -6, 4, 6, 3, 3, 3, 1, 2, 256, 195, 186, 129, 57,,, -6, 4, 6, 3, 3, 3, 1, 2, 384, 195, 186, 129, 57,,, -6, 4, 6, 3, 3, 3, 1, 3, 128, 195, 186, 129, 57,,, -6, 4, 6, 3, 3, 3, 1, 3, 256, 195, 186, 129, 57,,, -6, 4, 6, 3, 3, 3, 1, 3, 384, 195, 186, 129, 57,,, -6, 4, 6, 3, 3, 3, 2, 1, 128, 195, 186, 129, 57,,, -6, 4, 6, 3, 3, 3, 2, 1, 256, 195, 186, 129, 57,,, -6, 4, 6, 3, 3, 3, 2, 1, 384, 195, 186, 129, 57,,, -6, 4, 6, 3, 3, 3, 2, 2, 128, 195, 186, 129, 57,,, -6, 4, 6, 3, 3, 3, 2, 2, 256, 195, 186, 129, 57,,, -6, 4, 6, 3, 3, 3, 2, 2, 384, 195, 186, 129, 57,,, -6, 4, 6, 3, 3, 3, 2, 3, 128, 195, 186, 129, 57,,, -6, 4, 6, 3, 3, 3, 2, 3, 256, 195, 186, 129, 57,,, -6, 4, 6, 3, 3, 3, 2, 3, 384, 195, 186, 129, 57,,, -6, 4, 6, 3, 3, 3, 3, 1, 128, 195, 186, 129, 57,,, -6, 4, 6, 3, 3, 3, 3, 1, 256, 195, 186, 129, 57,,, -6, 4, 6, 3, 3, 3, 3, 1, 384, 195, 186, 129, 57,,, -6, 4, 6, 3, 3, 3, 3, 2, 128, 195, 186, 129, 57,,, -6, 4, 6, 3, 3, 3, 3, 2, 256, 195, 186, 129, 57,,, -6, 4, 6, 3, 3, 3, 3, 2, 384, 195, 186, 129, 57,,, -6, 4, 6, 3, 3, 3, 3, 3, 128, 195, 186, 129, 57,,, -6, 4, 6, 3, 3, 3, 3, 3, 256, 195, 186, 129, 57,,, -6, 4, 6, 3, 3, 3, 3, 3, 384, 195, 186, 129, 57,,, -6, 4, 6, 4, 1, 1, 1, 1, 128, 240, 240, 171, 87,,, -6, 4, 6, 4, 1, 1, 1, 1, 256, 240, 240, 171, 87,,, -6, 4, 6, 4, 1, 1, 1, 1, 384, 240, 240, 171, 87,,, -6, 4, 6, 4, 2, 2, 1, 1, 128, 240, 240, 171, 79,,, -6, 4, 6, 4, 2, 2, 1, 1, 256, 240, 240, 171, 79,,, -6, 4, 6, 4, 2, 2, 1, 1, 384, 240, 240, 171, 79,,, -6, 4, 6, 4, 2, 2, 1, 2, 128, 240, 240, 171, 79,,, -6, 4, 6, 4, 2, 2, 1, 2, 256, 240, 240, 171, 79,,, -6, 4, 6, 4, 2, 2, 1, 2, 384, 240, 240, 171, 79,,, -6, 4, 6, 4, 2, 2, 2, 1, 128, 240, 240, 171, 79,,, -6, 4, 6, 4, 2, 2, 2, 1, 256, 240, 240, 171, 79,,, -6, 4, 6, 4, 2, 2, 2, 1, 384, 240, 240, 171, 79,,, -6, 4, 6, 4, 2, 2, 2, 2, 128, 240, 240, 171, 79,,, -6, 4, 6, 4, 2, 2, 2, 2, 256, 240, 240, 171, 79,,, -6, 4, 6, 4, 2, 2, 2, 2, 384, 240, 240, 171, 79,,, -6, 4, 6, 4, 3, 3, 1, 1, 128, 240, 240, 171, 75,,, -6, 4, 6, 4, 3, 3, 1, 1, 256, 240, 240, 171, 75,,, -6, 4, 6, 4, 3, 3, 1, 1, 384, 240, 240, 171, 75,,, -6, 4, 6, 4, 3, 3, 1, 2, 128, 240, 240, 171, 75,,, -6, 4, 6, 4, 3, 3, 1, 2, 256, 240, 240, 171, 75,,, -6, 4, 6, 4, 3, 3, 1, 2, 384, 240, 240, 171, 75,,, -6, 4, 6, 4, 3, 3, 1, 3, 128, 240, 240, 171, 75,,, -6, 4, 6, 4, 3, 3, 1, 3, 256, 240, 240, 171, 75,,, -6, 4, 6, 4, 3, 3, 1, 3, 384, 240, 240, 171, 75,,, -6, 4, 6, 4, 3, 3, 2, 1, 128, 240, 240, 171, 75,,, -6, 4, 6, 4, 3, 3, 2, 1, 256, 240, 240, 171, 75,,, -6, 4, 6, 4, 3, 3, 2, 1, 384, 240, 240, 171, 75,,, -6, 4, 6, 4, 3, 3, 2, 2, 128, 240, 240, 171, 75,,, -6, 4, 6, 4, 3, 3, 2, 2, 256, 240, 240, 171, 75,,, -6, 4, 6, 4, 3, 3, 2, 2, 384, 240, 240, 171, 75,,, -6, 4, 6, 4, 3, 3, 2, 3, 128, 240, 240, 171, 75,,, -6, 4, 6, 4, 3, 3, 2, 3, 256, 240, 240, 171, 75,,, -6, 4, 6, 4, 3, 3, 2, 3, 384, 240, 240, 171, 75,,, -6, 4, 6, 4, 3, 3, 3, 1, 128, 240, 240, 171, 75,,, -6, 4, 6, 4, 3, 3, 3, 1, 256, 240, 240, 171, 75,,, -6, 4, 6, 4, 3, 3, 3, 1, 384, 240, 240, 171, 75,,, -6, 4, 6, 4, 3, 3, 3, 2, 128, 240, 240, 171, 75,,, -6, 4, 6, 4, 3, 3, 3, 2, 256, 240, 240, 171, 75,,, -6, 4, 6, 4, 3, 3, 3, 2, 384, 240, 240, 171, 75,,, -6, 4, 6, 4, 3, 3, 3, 3, 128, 240, 240, 171, 75,,, -6, 4, 6, 4, 3, 3, 3, 3, 256, 240, 240, 171, 75,,, -6, 4, 6, 4, 3, 3, 3, 3, 384, 240, 240, 171, 75,,, -6, 5, 1, 1, 1, 1, 1, 1, 128, 68, 68, 46,,,, -6, 5, 1, 1, 1, 1, 1, 1, 256, 68, 68, 46,,,, -6, 5, 1, 1, 1, 1, 1, 1, 384, 68, 68, 46,,,, -6, 5, 1, 1, 2, 2, 1, 1, 128, 68, 64, 45,,,, -6, 5, 1, 1, 2, 2, 1, 1, 256, 68, 64, 45,,,, -6, 5, 1, 1, 2, 2, 1, 1, 384, 68, 64, 45,,,, -6, 5, 1, 1, 2, 2, 1, 2, 128, 68, 64, 45,,,, -6, 5, 1, 1, 2, 2, 1, 2, 256, 68, 64, 45,,,, -6, 5, 1, 1, 2, 2, 1, 2, 384, 68, 64, 45,,,, -6, 5, 1, 1, 2, 2, 2, 1, 128, 68, 64, 45,,,, -6, 5, 1, 1, 2, 2, 2, 1, 256, 68, 64, 45,,,, -6, 5, 1, 1, 2, 2, 2, 1, 384, 68, 64, 45,,,, -6, 5, 1, 1, 2, 2, 2, 2, 128, 68, 64, 45,,,, -6, 5, 1, 1, 2, 2, 2, 2, 256, 68, 64, 45,,,, -6, 5, 1, 1, 2, 2, 2, 2, 384, 68, 64, 45,,,, -6, 5, 1, 1, 3, 3, 1, 1, 128, 68, 61, 44,,,, -6, 5, 1, 1, 3, 3, 1, 1, 256, 68, 61, 44,,,, -6, 5, 1, 1, 3, 3, 1, 1, 384, 68, 61, 44,,,, -6, 5, 1, 1, 3, 3, 1, 2, 128, 68, 61, 44,,,, -6, 5, 1, 1, 3, 3, 1, 2, 256, 68, 61, 44,,,, -6, 5, 1, 1, 3, 3, 1, 2, 384, 68, 61, 44,,,, -6, 5, 1, 1, 3, 3, 1, 3, 128, 68, 61, 44,,,, -6, 5, 1, 1, 3, 3, 1, 3, 256, 68, 61, 44,,,, -6, 5, 1, 1, 3, 3, 1, 3, 384, 68, 61, 44,,,, -6, 5, 1, 1, 3, 3, 2, 1, 128, 68, 61, 44,,,, -6, 5, 1, 1, 3, 3, 2, 1, 256, 68, 61, 44,,,, -6, 5, 1, 1, 3, 3, 2, 1, 384, 68, 61, 44,,,, -6, 5, 1, 1, 3, 3, 2, 2, 128, 68, 61, 44,,,, -6, 5, 1, 1, 3, 3, 2, 2, 256, 68, 61, 44,,,, -6, 5, 1, 1, 3, 3, 2, 2, 384, 68, 61, 44,,,, -6, 5, 1, 1, 3, 3, 2, 3, 128, 68, 61, 44,,,, -6, 5, 1, 1, 3, 3, 2, 3, 256, 68, 61, 44,,,, -6, 5, 1, 1, 3, 3, 2, 3, 384, 68, 61, 44,,,, -6, 5, 1, 1, 3, 3, 3, 1, 128, 68, 61, 44,,,, -6, 5, 1, 1, 3, 3, 3, 1, 256, 68, 61, 44,,,, -6, 5, 1, 1, 3, 3, 3, 1, 384, 68, 61, 44,,,, -6, 5, 1, 1, 3, 3, 3, 2, 128, 68, 61, 44,,,, -6, 5, 1, 1, 3, 3, 3, 2, 256, 68, 61, 44,,,, -6, 5, 1, 1, 3, 3, 3, 2, 384, 68, 61, 44,,,, -6, 5, 1, 1, 3, 3, 3, 3, 128, 68, 61, 44,,,, -6, 5, 1, 1, 3, 3, 3, 3, 256, 68, 61, 44,,,, -6, 5, 1, 1, 3, 3, 3, 3, 384, 68, 61, 44,,,, -6, 5, 1, 2, 1, 1, 1, 1, 128, 132, 132, 88,,,, -6, 5, 1, 2, 1, 1, 1, 1, 256, 132, 132, 88,,,, -6, 5, 1, 2, 1, 1, 1, 1, 384, 132, 132, 88,,,, -6, 5, 1, 2, 2, 2, 1, 1, 128, 132, 124, 86,,,, -6, 5, 1, 2, 2, 2, 1, 1, 256, 132, 124, 86,,,, -6, 5, 1, 2, 2, 2, 1, 1, 384, 132, 124, 86,,,, -6, 5, 1, 2, 2, 2, 1, 2, 128, 132, 124, 86,,,, -6, 5, 1, 2, 2, 2, 1, 2, 256, 132, 124, 86,,,, -6, 5, 1, 2, 2, 2, 1, 2, 384, 132, 124, 86,,,, -6, 5, 1, 2, 2, 2, 2, 1, 128, 132, 124, 86,,,, -6, 5, 1, 2, 2, 2, 2, 1, 256, 132, 124, 86,,,, -6, 5, 1, 2, 2, 2, 2, 1, 384, 132, 124, 86,,,, -6, 5, 1, 2, 2, 2, 2, 2, 128, 132, 124, 86,,,, -6, 5, 1, 2, 2, 2, 2, 2, 256, 132, 124, 86,,,, -6, 5, 1, 2, 2, 2, 2, 2, 384, 132, 124, 86,,,, -6, 5, 1, 2, 3, 3, 1, 1, 128, 132, 118, 84,,,, -6, 5, 1, 2, 3, 3, 1, 1, 256, 132, 118, 84,,,, -6, 5, 1, 2, 3, 3, 1, 1, 384, 132, 118, 84,,,, -6, 5, 1, 2, 3, 3, 1, 2, 128, 132, 118, 84,,,, -6, 5, 1, 2, 3, 3, 1, 2, 256, 132, 118, 84,,,, -6, 5, 1, 2, 3, 3, 1, 2, 384, 132, 118, 84,,,, -6, 5, 1, 2, 3, 3, 1, 3, 128, 132, 118, 84,,,, -6, 5, 1, 2, 3, 3, 1, 3, 256, 132, 118, 84,,,, -6, 5, 1, 2, 3, 3, 1, 3, 384, 132, 118, 84,,,, -6, 5, 1, 2, 3, 3, 2, 1, 128, 132, 118, 84,,,, -6, 5, 1, 2, 3, 3, 2, 1, 256, 132, 118, 84,,,, -6, 5, 1, 2, 3, 3, 2, 1, 384, 132, 118, 84,,,, -6, 5, 1, 2, 3, 3, 2, 2, 128, 132, 118, 84,,,, -6, 5, 1, 2, 3, 3, 2, 2, 256, 132, 118, 84,,,, -6, 5, 1, 2, 3, 3, 2, 2, 384, 132, 118, 84,,,, -6, 5, 1, 2, 3, 3, 2, 3, 128, 132, 118, 84,,,, -6, 5, 1, 2, 3, 3, 2, 3, 256, 132, 118, 84,,,, -6, 5, 1, 2, 3, 3, 2, 3, 384, 132, 118, 84,,,, -6, 5, 1, 2, 3, 3, 3, 1, 128, 132, 118, 84,,,, -6, 5, 1, 2, 3, 3, 3, 1, 256, 132, 118, 84,,,, -6, 5, 1, 2, 3, 3, 3, 1, 384, 132, 118, 84,,,, -6, 5, 1, 2, 3, 3, 3, 2, 128, 132, 118, 84,,,, -6, 5, 1, 2, 3, 3, 3, 2, 256, 132, 118, 84,,,, -6, 5, 1, 2, 3, 3, 3, 2, 384, 132, 118, 84,,,, -6, 5, 1, 2, 3, 3, 3, 3, 128, 132, 118, 84,,,, -6, 5, 1, 2, 3, 3, 3, 3, 256, 132, 118, 84,,,, -6, 5, 1, 2, 3, 3, 3, 3, 384, 132, 118, 84,,,, -6, 5, 1, 3, 1, 1, 1, 1, 128, 196, 196, 130,,,, -6, 5, 1, 3, 1, 1, 1, 1, 256, 196, 196, 130,,,, -6, 5, 1, 3, 1, 1, 1, 1, 384, 196, 196, 130,,,, -6, 5, 1, 3, 2, 2, 1, 1, 128, 196, 184, 127,,,, -6, 5, 1, 3, 2, 2, 1, 1, 256, 196, 184, 127,,,, -6, 5, 1, 3, 2, 2, 1, 1, 384, 196, 184, 127,,,, -6, 5, 1, 3, 2, 2, 1, 2, 128, 196, 184, 127,,,, -6, 5, 1, 3, 2, 2, 1, 2, 256, 196, 184, 127,,,, -6, 5, 1, 3, 2, 2, 1, 2, 384, 196, 184, 127,,,, -6, 5, 1, 3, 2, 2, 2, 1, 128, 196, 184, 127,,,, -6, 5, 1, 3, 2, 2, 2, 1, 256, 196, 184, 127,,,, -6, 5, 1, 3, 2, 2, 2, 1, 384, 196, 184, 127,,,, -6, 5, 1, 3, 2, 2, 2, 2, 128, 196, 184, 127,,,, -6, 5, 1, 3, 2, 2, 2, 2, 256, 196, 184, 127,,,, -6, 5, 1, 3, 2, 2, 2, 2, 384, 196, 184, 127,,,, -6, 5, 1, 3, 3, 3, 1, 1, 128, 196, 175, 124,,,, -6, 5, 1, 3, 3, 3, 1, 1, 256, 196, 175, 124,,,, -6, 5, 1, 3, 3, 3, 1, 1, 384, 196, 175, 124,,,, -6, 5, 1, 3, 3, 3, 1, 2, 128, 196, 175, 124,,,, -6, 5, 1, 3, 3, 3, 1, 2, 256, 196, 175, 124,,,, -6, 5, 1, 3, 3, 3, 1, 2, 384, 196, 175, 124,,,, -6, 5, 1, 3, 3, 3, 1, 3, 128, 196, 175, 124,,,, -6, 5, 1, 3, 3, 3, 1, 3, 256, 196, 175, 124,,,, -6, 5, 1, 3, 3, 3, 1, 3, 384, 196, 175, 124,,,, -6, 5, 1, 3, 3, 3, 2, 1, 128, 196, 175, 124,,,, -6, 5, 1, 3, 3, 3, 2, 1, 256, 196, 175, 124,,,, -6, 5, 1, 3, 3, 3, 2, 1, 384, 196, 175, 124,,,, -6, 5, 1, 3, 3, 3, 2, 2, 128, 196, 175, 124,,,, -6, 5, 1, 3, 3, 3, 2, 2, 256, 196, 175, 124,,,, -6, 5, 1, 3, 3, 3, 2, 2, 384, 196, 175, 124,,,, -6, 5, 1, 3, 3, 3, 2, 3, 128, 196, 175, 124,,,, -6, 5, 1, 3, 3, 3, 2, 3, 256, 196, 175, 124,,,, -6, 5, 1, 3, 3, 3, 2, 3, 384, 196, 175, 124,,,, -6, 5, 1, 3, 3, 3, 3, 1, 128, 196, 175, 124,,,, -6, 5, 1, 3, 3, 3, 3, 1, 256, 196, 175, 124,,,, -6, 5, 1, 3, 3, 3, 3, 1, 384, 196, 175, 124,,,, -6, 5, 1, 3, 3, 3, 3, 2, 128, 196, 175, 124,,,, -6, 5, 1, 3, 3, 3, 3, 2, 256, 196, 175, 124,,,, -6, 5, 1, 3, 3, 3, 3, 2, 384, 196, 175, 124,,,, -6, 5, 1, 3, 3, 3, 3, 3, 128, 196, 175, 124,,,, -6, 5, 1, 3, 3, 3, 3, 3, 256, 196, 175, 124,,,, -6, 5, 1, 3, 3, 3, 3, 3, 384, 196, 175, 124,,,, -6, 5, 1, 4, 1, 1, 1, 1, 128, 240, 240, 172,,,, -6, 5, 1, 4, 1, 1, 1, 1, 256, 240, 240, 172,,,, -6, 5, 1, 4, 1, 1, 1, 1, 384, 240, 240, 172,,,, -6, 5, 1, 4, 2, 2, 1, 1, 128, 240, 240, 168,,,, -6, 5, 1, 4, 2, 2, 1, 1, 256, 240, 240, 168,,,, -6, 5, 1, 4, 2, 2, 1, 1, 384, 240, 240, 168,,,, -6, 5, 1, 4, 2, 2, 1, 2, 128, 240, 240, 168,,,, -6, 5, 1, 4, 2, 2, 1, 2, 256, 240, 240, 168,,,, -6, 5, 1, 4, 2, 2, 1, 2, 384, 240, 240, 168,,,, -6, 5, 1, 4, 2, 2, 2, 1, 128, 240, 240, 168,,,, -6, 5, 1, 4, 2, 2, 2, 1, 256, 240, 240, 168,,,, -6, 5, 1, 4, 2, 2, 2, 1, 384, 240, 240, 168,,,, -6, 5, 1, 4, 2, 2, 2, 2, 128, 240, 240, 168,,,, -6, 5, 1, 4, 2, 2, 2, 2, 256, 240, 240, 168,,,, -6, 5, 1, 4, 2, 2, 2, 2, 384, 240, 240, 168,,,, -6, 5, 1, 4, 3, 3, 1, 1, 128, 240, 232, 164,,,, -6, 5, 1, 4, 3, 3, 1, 1, 256, 240, 232, 164,,,, -6, 5, 1, 4, 3, 3, 1, 1, 384, 240, 232, 164,,,, -6, 5, 1, 4, 3, 3, 1, 2, 128, 240, 232, 164,,,, -6, 5, 1, 4, 3, 3, 1, 2, 256, 240, 232, 164,,,, -6, 5, 1, 4, 3, 3, 1, 2, 384, 240, 232, 164,,,, -6, 5, 1, 4, 3, 3, 1, 3, 128, 240, 232, 164,,,, -6, 5, 1, 4, 3, 3, 1, 3, 256, 240, 232, 164,,,, -6, 5, 1, 4, 3, 3, 1, 3, 384, 240, 232, 164,,,, -6, 5, 1, 4, 3, 3, 2, 1, 128, 240, 232, 164,,,, -6, 5, 1, 4, 3, 3, 2, 1, 256, 240, 232, 164,,,, -6, 5, 1, 4, 3, 3, 2, 1, 384, 240, 232, 164,,,, -6, 5, 1, 4, 3, 3, 2, 2, 128, 240, 232, 164,,,, -6, 5, 1, 4, 3, 3, 2, 2, 256, 240, 232, 164,,,, -6, 5, 1, 4, 3, 3, 2, 2, 384, 240, 232, 164,,,, -6, 5, 1, 4, 3, 3, 2, 3, 128, 240, 232, 164,,,, -6, 5, 1, 4, 3, 3, 2, 3, 256, 240, 232, 164,,,, -6, 5, 1, 4, 3, 3, 2, 3, 384, 240, 232, 164,,,, -6, 5, 1, 4, 3, 3, 3, 1, 128, 240, 232, 164,,,, -6, 5, 1, 4, 3, 3, 3, 1, 256, 240, 232, 164,,,, -6, 5, 1, 4, 3, 3, 3, 1, 384, 240, 232, 164,,,, -6, 5, 1, 4, 3, 3, 3, 2, 128, 240, 232, 164,,,, -6, 5, 1, 4, 3, 3, 3, 2, 256, 240, 232, 164,,,, -6, 5, 1, 4, 3, 3, 3, 2, 384, 240, 232, 164,,,, -6, 5, 1, 4, 3, 3, 3, 3, 128, 240, 232, 164,,,, -6, 5, 1, 4, 3, 3, 3, 3, 256, 240, 232, 164,,,, -6, 5, 1, 4, 3, 3, 3, 3, 384, 240, 232, 164,,,, -6, 5, 1, 5, 1, 1, 1, 1, 128, 240, 240, 214,,,, -6, 5, 1, 5, 1, 1, 1, 1, 256, 240, 240, 214,,,, -6, 5, 1, 5, 1, 1, 1, 1, 384, 240, 240, 214,,,, -6, 5, 1, 5, 2, 2, 1, 1, 128, 240, 240, 209,,,, -6, 5, 1, 5, 2, 2, 1, 1, 256, 240, 240, 209,,,, -6, 5, 1, 5, 2, 2, 1, 1, 384, 240, 240, 209,,,, -6, 5, 1, 5, 2, 2, 1, 2, 128, 240, 240, 209,,,, -6, 5, 1, 5, 2, 2, 1, 2, 256, 240, 240, 209,,,, -6, 5, 1, 5, 2, 2, 1, 2, 384, 240, 240, 209,,,, -6, 5, 1, 5, 2, 2, 2, 1, 128, 240, 240, 209,,,, -6, 5, 1, 5, 2, 2, 2, 1, 256, 240, 240, 209,,,, -6, 5, 1, 5, 2, 2, 2, 1, 384, 240, 240, 209,,,, -6, 5, 1, 5, 2, 2, 2, 2, 128, 240, 240, 209,,,, -6, 5, 1, 5, 2, 2, 2, 2, 256, 240, 240, 209,,,, -6, 5, 1, 5, 2, 2, 2, 2, 384, 240, 240, 209,,,, -6, 5, 1, 5, 3, 3, 1, 1, 128, 240, 240, 204,,,, -6, 5, 1, 5, 3, 3, 1, 1, 256, 240, 240, 204,,,, -6, 5, 1, 5, 3, 3, 1, 1, 384, 240, 240, 204,,,, -6, 5, 1, 5, 3, 3, 1, 2, 128, 240, 240, 204,,,, -6, 5, 1, 5, 3, 3, 1, 2, 256, 240, 240, 204,,,, -6, 5, 1, 5, 3, 3, 1, 2, 384, 240, 240, 204,,,, -6, 5, 1, 5, 3, 3, 1, 3, 128, 240, 240, 204,,,, -6, 5, 1, 5, 3, 3, 1, 3, 256, 240, 240, 204,,,, -6, 5, 1, 5, 3, 3, 1, 3, 384, 240, 240, 204,,,, -6, 5, 1, 5, 3, 3, 2, 1, 128, 240, 240, 204,,,, -6, 5, 1, 5, 3, 3, 2, 1, 256, 240, 240, 204,,,, -6, 5, 1, 5, 3, 3, 2, 1, 384, 240, 240, 204,,,, -6, 5, 1, 5, 3, 3, 2, 2, 128, 240, 240, 204,,,, -6, 5, 1, 5, 3, 3, 2, 2, 256, 240, 240, 204,,,, -6, 5, 1, 5, 3, 3, 2, 2, 384, 240, 240, 204,,,, -6, 5, 1, 5, 3, 3, 2, 3, 128, 240, 240, 204,,,, -6, 5, 1, 5, 3, 3, 2, 3, 256, 240, 240, 204,,,, -6, 5, 1, 5, 3, 3, 2, 3, 384, 240, 240, 204,,,, -6, 5, 1, 5, 3, 3, 3, 1, 128, 240, 240, 204,,,, -6, 5, 1, 5, 3, 3, 3, 1, 256, 240, 240, 204,,,, -6, 5, 1, 5, 3, 3, 3, 1, 384, 240, 240, 204,,,, -6, 5, 1, 5, 3, 3, 3, 2, 128, 240, 240, 204,,,, -6, 5, 1, 5, 3, 3, 3, 2, 256, 240, 240, 204,,,, -6, 5, 1, 5, 3, 3, 3, 2, 384, 240, 240, 204,,,, -6, 5, 1, 5, 3, 3, 3, 3, 128, 240, 240, 204,,,, -6, 5, 1, 5, 3, 3, 3, 3, 256, 240, 240, 204,,,, -6, 5, 1, 5, 3, 3, 3, 3, 384, 240, 240, 204,,,, -6, 5, 2, 1, 1, 1, 1, 1, 128, 68, 68, 46,,,, -6, 5, 2, 1, 1, 1, 1, 1, 256, 68, 68, 46,,,, -6, 5, 2, 1, 1, 1, 1, 1, 384, 68, 68, 46,,,, -6, 5, 2, 1, 2, 2, 1, 1, 128, 68, 64, 45,,,, -6, 5, 2, 1, 2, 2, 1, 1, 256, 68, 64, 45,,,, -6, 5, 2, 1, 2, 2, 1, 1, 384, 68, 64, 45,,,, -6, 5, 2, 1, 2, 2, 1, 2, 128, 68, 64, 45,,,, -6, 5, 2, 1, 2, 2, 1, 2, 256, 68, 64, 45,,,, -6, 5, 2, 1, 2, 2, 1, 2, 384, 68, 64, 45,,,, -6, 5, 2, 1, 2, 2, 2, 1, 128, 68, 64, 45,,,, -6, 5, 2, 1, 2, 2, 2, 1, 256, 68, 64, 45,,,, -6, 5, 2, 1, 2, 2, 2, 1, 384, 68, 64, 45,,,, -6, 5, 2, 1, 2, 2, 2, 2, 128, 68, 64, 45,,,, -6, 5, 2, 1, 2, 2, 2, 2, 256, 68, 64, 45,,,, -6, 5, 2, 1, 2, 2, 2, 2, 384, 68, 64, 45,,,, -6, 5, 2, 1, 3, 3, 1, 1, 128, 68, 61, 44,,,, -6, 5, 2, 1, 3, 3, 1, 1, 256, 68, 61, 44,,,, -6, 5, 2, 1, 3, 3, 1, 1, 384, 68, 61, 44,,,, -6, 5, 2, 1, 3, 3, 1, 2, 128, 68, 61, 44,,,, -6, 5, 2, 1, 3, 3, 1, 2, 256, 68, 61, 44,,,, -6, 5, 2, 1, 3, 3, 1, 2, 384, 68, 61, 44,,,, -6, 5, 2, 1, 3, 3, 1, 3, 128, 68, 61, 44,,,, -6, 5, 2, 1, 3, 3, 1, 3, 256, 68, 61, 44,,,, -6, 5, 2, 1, 3, 3, 1, 3, 384, 68, 61, 44,,,, -6, 5, 2, 1, 3, 3, 2, 1, 128, 68, 61, 44,,,, -6, 5, 2, 1, 3, 3, 2, 1, 256, 68, 61, 44,,,, -6, 5, 2, 1, 3, 3, 2, 1, 384, 68, 61, 44,,,, -6, 5, 2, 1, 3, 3, 2, 2, 128, 68, 61, 44,,,, -6, 5, 2, 1, 3, 3, 2, 2, 256, 68, 61, 44,,,, -6, 5, 2, 1, 3, 3, 2, 2, 384, 68, 61, 44,,,, -6, 5, 2, 1, 3, 3, 2, 3, 128, 68, 61, 44,,,, -6, 5, 2, 1, 3, 3, 2, 3, 256, 68, 61, 44,,,, -6, 5, 2, 1, 3, 3, 2, 3, 384, 68, 61, 44,,,, -6, 5, 2, 1, 3, 3, 3, 1, 128, 68, 61, 44,,,, -6, 5, 2, 1, 3, 3, 3, 1, 256, 68, 61, 44,,,, -6, 5, 2, 1, 3, 3, 3, 1, 384, 68, 61, 44,,,, -6, 5, 2, 1, 3, 3, 3, 2, 128, 68, 61, 44,,,, -6, 5, 2, 1, 3, 3, 3, 2, 256, 68, 61, 44,,,, -6, 5, 2, 1, 3, 3, 3, 2, 384, 68, 61, 44,,,, -6, 5, 2, 1, 3, 3, 3, 3, 128, 68, 61, 44,,,, -6, 5, 2, 1, 3, 3, 3, 3, 256, 68, 61, 44,,,, -6, 5, 2, 1, 3, 3, 3, 3, 384, 68, 61, 44,,,, -6, 5, 2, 2, 1, 1, 1, 1, 128, 132, 132, 88,,,, -6, 5, 2, 2, 1, 1, 1, 1, 256, 132, 132, 88,,,, -6, 5, 2, 2, 1, 1, 1, 1, 384, 132, 132, 88,,,, -6, 5, 2, 2, 2, 2, 1, 1, 128, 132, 124, 86,,,, -6, 5, 2, 2, 2, 2, 1, 1, 256, 132, 124, 86,,,, -6, 5, 2, 2, 2, 2, 1, 1, 384, 132, 124, 86,,,, -6, 5, 2, 2, 2, 2, 1, 2, 128, 132, 124, 86,,,, -6, 5, 2, 2, 2, 2, 1, 2, 256, 132, 124, 86,,,, -6, 5, 2, 2, 2, 2, 1, 2, 384, 132, 124, 86,,,, -6, 5, 2, 2, 2, 2, 2, 1, 128, 132, 124, 86,,,, -6, 5, 2, 2, 2, 2, 2, 1, 256, 132, 124, 86,,,, -6, 5, 2, 2, 2, 2, 2, 1, 384, 132, 124, 86,,,, -6, 5, 2, 2, 2, 2, 2, 2, 128, 132, 124, 86,,,, -6, 5, 2, 2, 2, 2, 2, 2, 256, 132, 124, 86,,,, -6, 5, 2, 2, 2, 2, 2, 2, 384, 132, 124, 86,,,, -6, 5, 2, 2, 3, 3, 1, 1, 128, 132, 118, 84,,,, -6, 5, 2, 2, 3, 3, 1, 1, 256, 132, 118, 84,,,, -6, 5, 2, 2, 3, 3, 1, 1, 384, 132, 118, 84,,,, -6, 5, 2, 2, 3, 3, 1, 2, 128, 132, 118, 84,,,, -6, 5, 2, 2, 3, 3, 1, 2, 256, 132, 118, 84,,,, -6, 5, 2, 2, 3, 3, 1, 2, 384, 132, 118, 84,,,, -6, 5, 2, 2, 3, 3, 1, 3, 128, 132, 118, 84,,,, -6, 5, 2, 2, 3, 3, 1, 3, 256, 132, 118, 84,,,, -6, 5, 2, 2, 3, 3, 1, 3, 384, 132, 118, 84,,,, -6, 5, 2, 2, 3, 3, 2, 1, 128, 132, 118, 84,,,, -6, 5, 2, 2, 3, 3, 2, 1, 256, 132, 118, 84,,,, -6, 5, 2, 2, 3, 3, 2, 1, 384, 132, 118, 84,,,, -6, 5, 2, 2, 3, 3, 2, 2, 128, 132, 118, 84,,,, -6, 5, 2, 2, 3, 3, 2, 2, 256, 132, 118, 84,,,, -6, 5, 2, 2, 3, 3, 2, 2, 384, 132, 118, 84,,,, -6, 5, 2, 2, 3, 3, 2, 3, 128, 132, 118, 84,,,, -6, 5, 2, 2, 3, 3, 2, 3, 256, 132, 118, 84,,,, -6, 5, 2, 2, 3, 3, 2, 3, 384, 132, 118, 84,,,, -6, 5, 2, 2, 3, 3, 3, 1, 128, 132, 118, 84,,,, -6, 5, 2, 2, 3, 3, 3, 1, 256, 132, 118, 84,,,, -6, 5, 2, 2, 3, 3, 3, 1, 384, 132, 118, 84,,,, -6, 5, 2, 2, 3, 3, 3, 2, 128, 132, 118, 84,,,, -6, 5, 2, 2, 3, 3, 3, 2, 256, 132, 118, 84,,,, -6, 5, 2, 2, 3, 3, 3, 2, 384, 132, 118, 84,,,, -6, 5, 2, 2, 3, 3, 3, 3, 128, 132, 118, 84,,,, -6, 5, 2, 2, 3, 3, 3, 3, 256, 132, 118, 84,,,, -6, 5, 2, 2, 3, 3, 3, 3, 384, 132, 118, 84,,,, -6, 5, 2, 3, 1, 1, 1, 1, 128, 196, 196, 130,,,, -6, 5, 2, 3, 1, 1, 1, 1, 256, 196, 196, 130,,,, -6, 5, 2, 3, 1, 1, 1, 1, 384, 196, 196, 130,,,, -6, 5, 2, 3, 2, 2, 1, 1, 128, 196, 184, 127,,,, -6, 5, 2, 3, 2, 2, 1, 1, 256, 196, 184, 127,,,, -6, 5, 2, 3, 2, 2, 1, 1, 384, 196, 184, 127,,,, -6, 5, 2, 3, 2, 2, 1, 2, 128, 196, 184, 127,,,, -6, 5, 2, 3, 2, 2, 1, 2, 256, 196, 184, 127,,,, -6, 5, 2, 3, 2, 2, 1, 2, 384, 196, 184, 127,,,, -6, 5, 2, 3, 2, 2, 2, 1, 128, 196, 184, 127,,,, -6, 5, 2, 3, 2, 2, 2, 1, 256, 196, 184, 127,,,, -6, 5, 2, 3, 2, 2, 2, 1, 384, 196, 184, 127,,,, -6, 5, 2, 3, 2, 2, 2, 2, 128, 196, 184, 127,,,, -6, 5, 2, 3, 2, 2, 2, 2, 256, 196, 184, 127,,,, -6, 5, 2, 3, 2, 2, 2, 2, 384, 196, 184, 127,,,, -6, 5, 2, 3, 3, 3, 1, 1, 128, 196, 175, 124,,,, -6, 5, 2, 3, 3, 3, 1, 1, 256, 196, 175, 124,,,, -6, 5, 2, 3, 3, 3, 1, 1, 384, 196, 175, 124,,,, -6, 5, 2, 3, 3, 3, 1, 2, 128, 196, 175, 124,,,, -6, 5, 2, 3, 3, 3, 1, 2, 256, 196, 175, 124,,,, -6, 5, 2, 3, 3, 3, 1, 2, 384, 196, 175, 124,,,, -6, 5, 2, 3, 3, 3, 1, 3, 128, 196, 175, 124,,,, -6, 5, 2, 3, 3, 3, 1, 3, 256, 196, 175, 124,,,, -6, 5, 2, 3, 3, 3, 1, 3, 384, 196, 175, 124,,,, -6, 5, 2, 3, 3, 3, 2, 1, 128, 196, 175, 124,,,, -6, 5, 2, 3, 3, 3, 2, 1, 256, 196, 175, 124,,,, -6, 5, 2, 3, 3, 3, 2, 1, 384, 196, 175, 124,,,, -6, 5, 2, 3, 3, 3, 2, 2, 128, 196, 175, 124,,,, -6, 5, 2, 3, 3, 3, 2, 2, 256, 196, 175, 124,,,, -6, 5, 2, 3, 3, 3, 2, 2, 384, 196, 175, 124,,,, -6, 5, 2, 3, 3, 3, 2, 3, 128, 196, 175, 124,,,, -6, 5, 2, 3, 3, 3, 2, 3, 256, 196, 175, 124,,,, -6, 5, 2, 3, 3, 3, 2, 3, 384, 196, 175, 124,,,, -6, 5, 2, 3, 3, 3, 3, 1, 128, 196, 175, 124,,,, -6, 5, 2, 3, 3, 3, 3, 1, 256, 196, 175, 124,,,, -6, 5, 2, 3, 3, 3, 3, 1, 384, 196, 175, 124,,,, -6, 5, 2, 3, 3, 3, 3, 2, 128, 196, 175, 124,,,, -6, 5, 2, 3, 3, 3, 3, 2, 256, 196, 175, 124,,,, -6, 5, 2, 3, 3, 3, 3, 2, 384, 196, 175, 124,,,, -6, 5, 2, 3, 3, 3, 3, 3, 128, 196, 175, 124,,,, -6, 5, 2, 3, 3, 3, 3, 3, 256, 196, 175, 124,,,, -6, 5, 2, 3, 3, 3, 3, 3, 384, 196, 175, 124,,,, -6, 5, 2, 4, 1, 1, 1, 1, 128, 240, 240, 172,,,, -6, 5, 2, 4, 1, 1, 1, 1, 256, 240, 240, 172,,,, -6, 5, 2, 4, 1, 1, 1, 1, 384, 240, 240, 172,,,, -6, 5, 2, 4, 2, 2, 1, 1, 128, 240, 240, 168,,,, -6, 5, 2, 4, 2, 2, 1, 1, 256, 240, 240, 168,,,, -6, 5, 2, 4, 2, 2, 1, 1, 384, 240, 240, 168,,,, -6, 5, 2, 4, 2, 2, 1, 2, 128, 240, 240, 168,,,, -6, 5, 2, 4, 2, 2, 1, 2, 256, 240, 240, 168,,,, -6, 5, 2, 4, 2, 2, 1, 2, 384, 240, 240, 168,,,, -6, 5, 2, 4, 2, 2, 2, 1, 128, 240, 240, 168,,,, -6, 5, 2, 4, 2, 2, 2, 1, 256, 240, 240, 168,,,, -6, 5, 2, 4, 2, 2, 2, 1, 384, 240, 240, 168,,,, -6, 5, 2, 4, 2, 2, 2, 2, 128, 240, 240, 168,,,, -6, 5, 2, 4, 2, 2, 2, 2, 256, 240, 240, 168,,,, -6, 5, 2, 4, 2, 2, 2, 2, 384, 240, 240, 168,,,, -6, 5, 2, 4, 3, 3, 1, 1, 128, 240, 232, 164,,,, -6, 5, 2, 4, 3, 3, 1, 1, 256, 240, 232, 164,,,, -6, 5, 2, 4, 3, 3, 1, 1, 384, 240, 232, 164,,,, -6, 5, 2, 4, 3, 3, 1, 2, 128, 240, 232, 164,,,, -6, 5, 2, 4, 3, 3, 1, 2, 256, 240, 232, 164,,,, -6, 5, 2, 4, 3, 3, 1, 2, 384, 240, 232, 164,,,, -6, 5, 2, 4, 3, 3, 1, 3, 128, 240, 232, 164,,,, -6, 5, 2, 4, 3, 3, 1, 3, 256, 240, 232, 164,,,, -6, 5, 2, 4, 3, 3, 1, 3, 384, 240, 232, 164,,,, -6, 5, 2, 4, 3, 3, 2, 1, 128, 240, 232, 164,,,, -6, 5, 2, 4, 3, 3, 2, 1, 256, 240, 232, 164,,,, -6, 5, 2, 4, 3, 3, 2, 1, 384, 240, 232, 164,,,, -6, 5, 2, 4, 3, 3, 2, 2, 128, 240, 232, 164,,,, -6, 5, 2, 4, 3, 3, 2, 2, 256, 240, 232, 164,,,, -6, 5, 2, 4, 3, 3, 2, 2, 384, 240, 232, 164,,,, -6, 5, 2, 4, 3, 3, 2, 3, 128, 240, 232, 164,,,, -6, 5, 2, 4, 3, 3, 2, 3, 256, 240, 232, 164,,,, -6, 5, 2, 4, 3, 3, 2, 3, 384, 240, 232, 164,,,, -6, 5, 2, 4, 3, 3, 3, 1, 128, 240, 232, 164,,,, -6, 5, 2, 4, 3, 3, 3, 1, 256, 240, 232, 164,,,, -6, 5, 2, 4, 3, 3, 3, 1, 384, 240, 232, 164,,,, -6, 5, 2, 4, 3, 3, 3, 2, 128, 240, 232, 164,,,, -6, 5, 2, 4, 3, 3, 3, 2, 256, 240, 232, 164,,,, -6, 5, 2, 4, 3, 3, 3, 2, 384, 240, 232, 164,,,, -6, 5, 2, 4, 3, 3, 3, 3, 128, 240, 232, 164,,,, -6, 5, 2, 4, 3, 3, 3, 3, 256, 240, 232, 164,,,, -6, 5, 2, 4, 3, 3, 3, 3, 384, 240, 232, 164,,,, -6, 5, 2, 5, 1, 1, 1, 1, 128, 240, 240, 214,,,, -6, 5, 2, 5, 1, 1, 1, 1, 256, 240, 240, 214,,,, -6, 5, 2, 5, 1, 1, 1, 1, 384, 240, 240, 214,,,, -6, 5, 2, 5, 2, 2, 1, 1, 128, 240, 240, 209,,,, -6, 5, 2, 5, 2, 2, 1, 1, 256, 240, 240, 209,,,, -6, 5, 2, 5, 2, 2, 1, 1, 384, 240, 240, 209,,,, -6, 5, 2, 5, 2, 2, 1, 2, 128, 240, 240, 209,,,, -6, 5, 2, 5, 2, 2, 1, 2, 256, 240, 240, 209,,,, -6, 5, 2, 5, 2, 2, 1, 2, 384, 240, 240, 209,,,, -6, 5, 2, 5, 2, 2, 2, 1, 128, 240, 240, 209,,,, -6, 5, 2, 5, 2, 2, 2, 1, 256, 240, 240, 209,,,, -6, 5, 2, 5, 2, 2, 2, 1, 384, 240, 240, 209,,,, -6, 5, 2, 5, 2, 2, 2, 2, 128, 240, 240, 209,,,, -6, 5, 2, 5, 2, 2, 2, 2, 256, 240, 240, 209,,,, -6, 5, 2, 5, 2, 2, 2, 2, 384, 240, 240, 209,,,, -6, 5, 2, 5, 3, 3, 1, 1, 128, 240, 240, 204,,,, -6, 5, 2, 5, 3, 3, 1, 1, 256, 240, 240, 204,,,, -6, 5, 2, 5, 3, 3, 1, 1, 384, 240, 240, 204,,,, -6, 5, 2, 5, 3, 3, 1, 2, 128, 240, 240, 204,,,, -6, 5, 2, 5, 3, 3, 1, 2, 256, 240, 240, 204,,,, -6, 5, 2, 5, 3, 3, 1, 2, 384, 240, 240, 204,,,, -6, 5, 2, 5, 3, 3, 1, 3, 128, 240, 240, 204,,,, -6, 5, 2, 5, 3, 3, 1, 3, 256, 240, 240, 204,,,, -6, 5, 2, 5, 3, 3, 1, 3, 384, 240, 240, 204,,,, -6, 5, 2, 5, 3, 3, 2, 1, 128, 240, 240, 204,,,, -6, 5, 2, 5, 3, 3, 2, 1, 256, 240, 240, 204,,,, -6, 5, 2, 5, 3, 3, 2, 1, 384, 240, 240, 204,,,, -6, 5, 2, 5, 3, 3, 2, 2, 128, 240, 240, 204,,,, -6, 5, 2, 5, 3, 3, 2, 2, 256, 240, 240, 204,,,, -6, 5, 2, 5, 3, 3, 2, 2, 384, 240, 240, 204,,,, -6, 5, 2, 5, 3, 3, 2, 3, 128, 240, 240, 204,,,, -6, 5, 2, 5, 3, 3, 2, 3, 256, 240, 240, 204,,,, -6, 5, 2, 5, 3, 3, 2, 3, 384, 240, 240, 204,,,, -6, 5, 2, 5, 3, 3, 3, 1, 128, 240, 240, 204,,,, -6, 5, 2, 5, 3, 3, 3, 1, 256, 240, 240, 204,,,, -6, 5, 2, 5, 3, 3, 3, 1, 384, 240, 240, 204,,,, -6, 5, 2, 5, 3, 3, 3, 2, 128, 240, 240, 204,,,, -6, 5, 2, 5, 3, 3, 3, 2, 256, 240, 240, 204,,,, -6, 5, 2, 5, 3, 3, 3, 2, 384, 240, 240, 204,,,, -6, 5, 2, 5, 3, 3, 3, 3, 128, 240, 240, 204,,,, -6, 5, 2, 5, 3, 3, 3, 3, 256, 240, 240, 204,,,, -6, 5, 2, 5, 3, 3, 3, 3, 384, 240, 240, 204,,,, -6, 5, 3, 1, 1, 1, 1, 1, 128, 68, 68, 46,,,, -6, 5, 3, 1, 1, 1, 1, 1, 256, 68, 68, 46,,,, -6, 5, 3, 1, 1, 1, 1, 1, 384, 68, 68, 46,,,, -6, 5, 3, 1, 2, 2, 1, 1, 128, 68, 64, 45,,,, -6, 5, 3, 1, 2, 2, 1, 1, 256, 68, 64, 45,,,, -6, 5, 3, 1, 2, 2, 1, 1, 384, 68, 64, 45,,,, -6, 5, 3, 1, 2, 2, 1, 2, 128, 68, 64, 45,,,, -6, 5, 3, 1, 2, 2, 1, 2, 256, 68, 64, 45,,,, -6, 5, 3, 1, 2, 2, 1, 2, 384, 68, 64, 45,,,, -6, 5, 3, 1, 2, 2, 2, 1, 128, 68, 64, 45,,,, -6, 5, 3, 1, 2, 2, 2, 1, 256, 68, 64, 45,,,, -6, 5, 3, 1, 2, 2, 2, 1, 384, 68, 64, 45,,,, -6, 5, 3, 1, 2, 2, 2, 2, 128, 68, 64, 45,,,, -6, 5, 3, 1, 2, 2, 2, 2, 256, 68, 64, 45,,,, -6, 5, 3, 1, 2, 2, 2, 2, 384, 68, 64, 45,,,, -6, 5, 3, 1, 3, 3, 1, 1, 128, 68, 61, 44,,,, -6, 5, 3, 1, 3, 3, 1, 1, 256, 68, 61, 44,,,, -6, 5, 3, 1, 3, 3, 1, 1, 384, 68, 61, 44,,,, -6, 5, 3, 1, 3, 3, 1, 2, 128, 68, 61, 44,,,, -6, 5, 3, 1, 3, 3, 1, 2, 256, 68, 61, 44,,,, -6, 5, 3, 1, 3, 3, 1, 2, 384, 68, 61, 44,,,, -6, 5, 3, 1, 3, 3, 1, 3, 128, 68, 61, 44,,,, -6, 5, 3, 1, 3, 3, 1, 3, 256, 68, 61, 44,,,, -6, 5, 3, 1, 3, 3, 1, 3, 384, 68, 61, 44,,,, -6, 5, 3, 1, 3, 3, 2, 1, 128, 68, 61, 44,,,, -6, 5, 3, 1, 3, 3, 2, 1, 256, 68, 61, 44,,,, -6, 5, 3, 1, 3, 3, 2, 1, 384, 68, 61, 44,,,, -6, 5, 3, 1, 3, 3, 2, 2, 128, 68, 61, 44,,,, -6, 5, 3, 1, 3, 3, 2, 2, 256, 68, 61, 44,,,, -6, 5, 3, 1, 3, 3, 2, 2, 384, 68, 61, 44,,,, -6, 5, 3, 1, 3, 3, 2, 3, 128, 68, 61, 44,,,, -6, 5, 3, 1, 3, 3, 2, 3, 256, 68, 61, 44,,,, -6, 5, 3, 1, 3, 3, 2, 3, 384, 68, 61, 44,,,, -6, 5, 3, 1, 3, 3, 3, 1, 128, 68, 61, 44,,,, -6, 5, 3, 1, 3, 3, 3, 1, 256, 68, 61, 44,,,, -6, 5, 3, 1, 3, 3, 3, 1, 384, 68, 61, 44,,,, -6, 5, 3, 1, 3, 3, 3, 2, 128, 68, 61, 44,,,, -6, 5, 3, 1, 3, 3, 3, 2, 256, 68, 61, 44,,,, -6, 5, 3, 1, 3, 3, 3, 2, 384, 68, 61, 44,,,, -6, 5, 3, 1, 3, 3, 3, 3, 128, 68, 61, 44,,,, -6, 5, 3, 1, 3, 3, 3, 3, 256, 68, 61, 44,,,, -6, 5, 3, 1, 3, 3, 3, 3, 384, 68, 61, 44,,,, -6, 5, 3, 2, 1, 1, 1, 1, 128, 132, 132, 88,,,, -6, 5, 3, 2, 1, 1, 1, 1, 256, 132, 132, 88,,,, -6, 5, 3, 2, 1, 1, 1, 1, 384, 132, 132, 88,,,, -6, 5, 3, 2, 2, 2, 1, 1, 128, 132, 124, 86,,,, -6, 5, 3, 2, 2, 2, 1, 1, 256, 132, 124, 86,,,, -6, 5, 3, 2, 2, 2, 1, 1, 384, 132, 124, 86,,,, -6, 5, 3, 2, 2, 2, 1, 2, 128, 132, 124, 86,,,, -6, 5, 3, 2, 2, 2, 1, 2, 256, 132, 124, 86,,,, -6, 5, 3, 2, 2, 2, 1, 2, 384, 132, 124, 86,,,, -6, 5, 3, 2, 2, 2, 2, 1, 128, 132, 124, 86,,,, -6, 5, 3, 2, 2, 2, 2, 1, 256, 132, 124, 86,,,, -6, 5, 3, 2, 2, 2, 2, 1, 384, 132, 124, 86,,,, -6, 5, 3, 2, 2, 2, 2, 2, 128, 132, 124, 86,,,, -6, 5, 3, 2, 2, 2, 2, 2, 256, 132, 124, 86,,,, -6, 5, 3, 2, 2, 2, 2, 2, 384, 132, 124, 86,,,, -6, 5, 3, 2, 3, 3, 1, 1, 128, 132, 118, 84,,,, -6, 5, 3, 2, 3, 3, 1, 1, 256, 132, 118, 84,,,, -6, 5, 3, 2, 3, 3, 1, 1, 384, 132, 118, 84,,,, -6, 5, 3, 2, 3, 3, 1, 2, 128, 132, 118, 84,,,, -6, 5, 3, 2, 3, 3, 1, 2, 256, 132, 118, 84,,,, -6, 5, 3, 2, 3, 3, 1, 2, 384, 132, 118, 84,,,, -6, 5, 3, 2, 3, 3, 1, 3, 128, 132, 118, 84,,,, -6, 5, 3, 2, 3, 3, 1, 3, 256, 132, 118, 84,,,, -6, 5, 3, 2, 3, 3, 1, 3, 384, 132, 118, 84,,,, -6, 5, 3, 2, 3, 3, 2, 1, 128, 132, 118, 84,,,, -6, 5, 3, 2, 3, 3, 2, 1, 256, 132, 118, 84,,,, -6, 5, 3, 2, 3, 3, 2, 1, 384, 132, 118, 84,,,, -6, 5, 3, 2, 3, 3, 2, 2, 128, 132, 118, 84,,,, -6, 5, 3, 2, 3, 3, 2, 2, 256, 132, 118, 84,,,, -6, 5, 3, 2, 3, 3, 2, 2, 384, 132, 118, 84,,,, -6, 5, 3, 2, 3, 3, 2, 3, 128, 132, 118, 84,,,, -6, 5, 3, 2, 3, 3, 2, 3, 256, 132, 118, 84,,,, -6, 5, 3, 2, 3, 3, 2, 3, 384, 132, 118, 84,,,, -6, 5, 3, 2, 3, 3, 3, 1, 128, 132, 118, 84,,,, -6, 5, 3, 2, 3, 3, 3, 1, 256, 132, 118, 84,,,, -6, 5, 3, 2, 3, 3, 3, 1, 384, 132, 118, 84,,,, -6, 5, 3, 2, 3, 3, 3, 2, 128, 132, 118, 84,,,, -6, 5, 3, 2, 3, 3, 3, 2, 256, 132, 118, 84,,,, -6, 5, 3, 2, 3, 3, 3, 2, 384, 132, 118, 84,,,, -6, 5, 3, 2, 3, 3, 3, 3, 128, 132, 118, 84,,,, -6, 5, 3, 2, 3, 3, 3, 3, 256, 132, 118, 84,,,, -6, 5, 3, 2, 3, 3, 3, 3, 384, 132, 118, 84,,,, -6, 5, 3, 3, 1, 1, 1, 1, 128, 196, 196, 130,,,, -6, 5, 3, 3, 1, 1, 1, 1, 256, 196, 196, 130,,,, -6, 5, 3, 3, 1, 1, 1, 1, 384, 196, 196, 130,,,, -6, 5, 3, 3, 2, 2, 1, 1, 128, 196, 184, 127,,,, -6, 5, 3, 3, 2, 2, 1, 1, 256, 196, 184, 127,,,, -6, 5, 3, 3, 2, 2, 1, 1, 384, 196, 184, 127,,,, -6, 5, 3, 3, 2, 2, 1, 2, 128, 196, 184, 127,,,, -6, 5, 3, 3, 2, 2, 1, 2, 256, 196, 184, 127,,,, -6, 5, 3, 3, 2, 2, 1, 2, 384, 196, 184, 127,,,, -6, 5, 3, 3, 2, 2, 2, 1, 128, 196, 184, 127,,,, -6, 5, 3, 3, 2, 2, 2, 1, 256, 196, 184, 127,,,, -6, 5, 3, 3, 2, 2, 2, 1, 384, 196, 184, 127,,,, -6, 5, 3, 3, 2, 2, 2, 2, 128, 196, 184, 127,,,, -6, 5, 3, 3, 2, 2, 2, 2, 256, 196, 184, 127,,,, -6, 5, 3, 3, 2, 2, 2, 2, 384, 196, 184, 127,,,, -6, 5, 3, 3, 3, 3, 1, 1, 128, 196, 175, 124,,,, -6, 5, 3, 3, 3, 3, 1, 1, 256, 196, 175, 124,,,, -6, 5, 3, 3, 3, 3, 1, 1, 384, 196, 175, 124,,,, -6, 5, 3, 3, 3, 3, 1, 2, 128, 196, 175, 124,,,, -6, 5, 3, 3, 3, 3, 1, 2, 256, 196, 175, 124,,,, -6, 5, 3, 3, 3, 3, 1, 2, 384, 196, 175, 124,,,, -6, 5, 3, 3, 3, 3, 1, 3, 128, 196, 175, 124,,,, -6, 5, 3, 3, 3, 3, 1, 3, 256, 196, 175, 124,,,, -6, 5, 3, 3, 3, 3, 1, 3, 384, 196, 175, 124,,,, -6, 5, 3, 3, 3, 3, 2, 1, 128, 196, 175, 124,,,, -6, 5, 3, 3, 3, 3, 2, 1, 256, 196, 175, 124,,,, -6, 5, 3, 3, 3, 3, 2, 1, 384, 196, 175, 124,,,, -6, 5, 3, 3, 3, 3, 2, 2, 128, 196, 175, 124,,,, -6, 5, 3, 3, 3, 3, 2, 2, 256, 196, 175, 124,,,, -6, 5, 3, 3, 3, 3, 2, 2, 384, 196, 175, 124,,,, -6, 5, 3, 3, 3, 3, 2, 3, 128, 196, 175, 124,,,, -6, 5, 3, 3, 3, 3, 2, 3, 256, 196, 175, 124,,,, -6, 5, 3, 3, 3, 3, 2, 3, 384, 196, 175, 124,,,, -6, 5, 3, 3, 3, 3, 3, 1, 128, 196, 175, 124,,,, -6, 5, 3, 3, 3, 3, 3, 1, 256, 196, 175, 124,,,, -6, 5, 3, 3, 3, 3, 3, 1, 384, 196, 175, 124,,,, -6, 5, 3, 3, 3, 3, 3, 2, 128, 196, 175, 124,,,, -6, 5, 3, 3, 3, 3, 3, 2, 256, 196, 175, 124,,,, -6, 5, 3, 3, 3, 3, 3, 2, 384, 196, 175, 124,,,, -6, 5, 3, 3, 3, 3, 3, 3, 128, 196, 175, 124,,,, -6, 5, 3, 3, 3, 3, 3, 3, 256, 196, 175, 124,,,, -6, 5, 3, 3, 3, 3, 3, 3, 384, 196, 175, 124,,,, -6, 5, 3, 4, 1, 1, 1, 1, 128, 240, 240, 172,,,, -6, 5, 3, 4, 1, 1, 1, 1, 256, 240, 240, 172,,,, -6, 5, 3, 4, 1, 1, 1, 1, 384, 240, 240, 172,,,, -6, 5, 3, 4, 2, 2, 1, 1, 128, 240, 240, 168,,,, -6, 5, 3, 4, 2, 2, 1, 1, 256, 240, 240, 168,,,, -6, 5, 3, 4, 2, 2, 1, 1, 384, 240, 240, 168,,,, -6, 5, 3, 4, 2, 2, 1, 2, 128, 240, 240, 168,,,, -6, 5, 3, 4, 2, 2, 1, 2, 256, 240, 240, 168,,,, -6, 5, 3, 4, 2, 2, 1, 2, 384, 240, 240, 168,,,, -6, 5, 3, 4, 2, 2, 2, 1, 128, 240, 240, 168,,,, -6, 5, 3, 4, 2, 2, 2, 1, 256, 240, 240, 168,,,, -6, 5, 3, 4, 2, 2, 2, 1, 384, 240, 240, 168,,,, -6, 5, 3, 4, 2, 2, 2, 2, 128, 240, 240, 168,,,, -6, 5, 3, 4, 2, 2, 2, 2, 256, 240, 240, 168,,,, -6, 5, 3, 4, 2, 2, 2, 2, 384, 240, 240, 168,,,, -6, 5, 3, 4, 3, 3, 1, 1, 128, 240, 232, 164,,,, -6, 5, 3, 4, 3, 3, 1, 1, 256, 240, 232, 164,,,, -6, 5, 3, 4, 3, 3, 1, 1, 384, 240, 232, 164,,,, -6, 5, 3, 4, 3, 3, 1, 2, 128, 240, 232, 164,,,, -6, 5, 3, 4, 3, 3, 1, 2, 256, 240, 232, 164,,,, -6, 5, 3, 4, 3, 3, 1, 2, 384, 240, 232, 164,,,, -6, 5, 3, 4, 3, 3, 1, 3, 128, 240, 232, 164,,,, -6, 5, 3, 4, 3, 3, 1, 3, 256, 240, 232, 164,,,, -6, 5, 3, 4, 3, 3, 1, 3, 384, 240, 232, 164,,,, -6, 5, 3, 4, 3, 3, 2, 1, 128, 240, 232, 164,,,, -6, 5, 3, 4, 3, 3, 2, 1, 256, 240, 232, 164,,,, -6, 5, 3, 4, 3, 3, 2, 1, 384, 240, 232, 164,,,, -6, 5, 3, 4, 3, 3, 2, 2, 128, 240, 232, 164,,,, -6, 5, 3, 4, 3, 3, 2, 2, 256, 240, 232, 164,,,, -6, 5, 3, 4, 3, 3, 2, 2, 384, 240, 232, 164,,,, -6, 5, 3, 4, 3, 3, 2, 3, 128, 240, 232, 164,,,, -6, 5, 3, 4, 3, 3, 2, 3, 256, 240, 232, 164,,,, -6, 5, 3, 4, 3, 3, 2, 3, 384, 240, 232, 164,,,, -6, 5, 3, 4, 3, 3, 3, 1, 128, 240, 232, 164,,,, -6, 5, 3, 4, 3, 3, 3, 1, 256, 240, 232, 164,,,, -6, 5, 3, 4, 3, 3, 3, 1, 384, 240, 232, 164,,,, -6, 5, 3, 4, 3, 3, 3, 2, 128, 240, 232, 164,,,, -6, 5, 3, 4, 3, 3, 3, 2, 256, 240, 232, 164,,,, -6, 5, 3, 4, 3, 3, 3, 2, 384, 240, 232, 164,,,, -6, 5, 3, 4, 3, 3, 3, 3, 128, 240, 232, 164,,,, -6, 5, 3, 4, 3, 3, 3, 3, 256, 240, 232, 164,,,, -6, 5, 3, 4, 3, 3, 3, 3, 384, 240, 232, 164,,,, -6, 5, 3, 5, 1, 1, 1, 1, 128, 240, 240, 214,,,, -6, 5, 3, 5, 1, 1, 1, 1, 256, 240, 240, 214,,,, -6, 5, 3, 5, 1, 1, 1, 1, 384, 240, 240, 214,,,, -6, 5, 3, 5, 2, 2, 1, 1, 128, 240, 240, 209,,,, -6, 5, 3, 5, 2, 2, 1, 1, 256, 240, 240, 209,,,, -6, 5, 3, 5, 2, 2, 1, 1, 384, 240, 240, 209,,,, -6, 5, 3, 5, 2, 2, 1, 2, 128, 240, 240, 209,,,, -6, 5, 3, 5, 2, 2, 1, 2, 256, 240, 240, 209,,,, -6, 5, 3, 5, 2, 2, 1, 2, 384, 240, 240, 209,,,, -6, 5, 3, 5, 2, 2, 2, 1, 128, 240, 240, 209,,,, -6, 5, 3, 5, 2, 2, 2, 1, 256, 240, 240, 209,,,, -6, 5, 3, 5, 2, 2, 2, 1, 384, 240, 240, 209,,,, -6, 5, 3, 5, 2, 2, 2, 2, 128, 240, 240, 209,,,, -6, 5, 3, 5, 2, 2, 2, 2, 256, 240, 240, 209,,,, -6, 5, 3, 5, 2, 2, 2, 2, 384, 240, 240, 209,,,, -6, 5, 3, 5, 3, 3, 1, 1, 128, 240, 240, 204,,,, -6, 5, 3, 5, 3, 3, 1, 1, 256, 240, 240, 204,,,, -6, 5, 3, 5, 3, 3, 1, 1, 384, 240, 240, 204,,,, -6, 5, 3, 5, 3, 3, 1, 2, 128, 240, 240, 204,,,, -6, 5, 3, 5, 3, 3, 1, 2, 256, 240, 240, 204,,,, -6, 5, 3, 5, 3, 3, 1, 2, 384, 240, 240, 204,,,, -6, 5, 3, 5, 3, 3, 1, 3, 128, 240, 240, 204,,,, -6, 5, 3, 5, 3, 3, 1, 3, 256, 240, 240, 204,,,, -6, 5, 3, 5, 3, 3, 1, 3, 384, 240, 240, 204,,,, -6, 5, 3, 5, 3, 3, 2, 1, 128, 240, 240, 204,,,, -6, 5, 3, 5, 3, 3, 2, 1, 256, 240, 240, 204,,,, -6, 5, 3, 5, 3, 3, 2, 1, 384, 240, 240, 204,,,, -6, 5, 3, 5, 3, 3, 2, 2, 128, 240, 240, 204,,,, -6, 5, 3, 5, 3, 3, 2, 2, 256, 240, 240, 204,,,, -6, 5, 3, 5, 3, 3, 2, 2, 384, 240, 240, 204,,,, -6, 5, 3, 5, 3, 3, 2, 3, 128, 240, 240, 204,,,, -6, 5, 3, 5, 3, 3, 2, 3, 256, 240, 240, 204,,,, -6, 5, 3, 5, 3, 3, 2, 3, 384, 240, 240, 204,,,, -6, 5, 3, 5, 3, 3, 3, 1, 128, 240, 240, 204,,,, -6, 5, 3, 5, 3, 3, 3, 1, 256, 240, 240, 204,,,, -6, 5, 3, 5, 3, 3, 3, 1, 384, 240, 240, 204,,,, -6, 5, 3, 5, 3, 3, 3, 2, 128, 240, 240, 204,,,, -6, 5, 3, 5, 3, 3, 3, 2, 256, 240, 240, 204,,,, -6, 5, 3, 5, 3, 3, 3, 2, 384, 240, 240, 204,,,, -6, 5, 3, 5, 3, 3, 3, 3, 128, 240, 240, 204,,,, -6, 5, 3, 5, 3, 3, 3, 3, 256, 240, 240, 204,,,, -6, 5, 3, 5, 3, 3, 3, 3, 384, 240, 240, 204,,,, -6, 5, 4, 1, 1, 1, 1, 1, 128, 68, 68, 46,,,, -6, 5, 4, 1, 1, 1, 1, 1, 256, 68, 68, 46,,,, -6, 5, 4, 1, 1, 1, 1, 1, 384, 68, 68, 46,,,, -6, 5, 4, 1, 2, 2, 1, 1, 128, 68, 64, 45,,,, -6, 5, 4, 1, 2, 2, 1, 1, 256, 68, 64, 45,,,, -6, 5, 4, 1, 2, 2, 1, 1, 384, 68, 64, 45,,,, -6, 5, 4, 1, 2, 2, 1, 2, 128, 68, 64, 45,,,, -6, 5, 4, 1, 2, 2, 1, 2, 256, 68, 64, 45,,,, -6, 5, 4, 1, 2, 2, 1, 2, 384, 68, 64, 45,,,, -6, 5, 4, 1, 2, 2, 2, 1, 128, 68, 64, 45,,,, -6, 5, 4, 1, 2, 2, 2, 1, 256, 68, 64, 45,,,, -6, 5, 4, 1, 2, 2, 2, 1, 384, 68, 64, 45,,,, -6, 5, 4, 1, 2, 2, 2, 2, 128, 68, 64, 45,,,, -6, 5, 4, 1, 2, 2, 2, 2, 256, 68, 64, 45,,,, -6, 5, 4, 1, 2, 2, 2, 2, 384, 68, 64, 45,,,, -6, 5, 4, 1, 3, 3, 1, 1, 128, 68, 61, 44,,,, -6, 5, 4, 1, 3, 3, 1, 1, 256, 68, 61, 44,,,, -6, 5, 4, 1, 3, 3, 1, 1, 384, 68, 61, 44,,,, -6, 5, 4, 1, 3, 3, 1, 2, 128, 68, 61, 44,,,, -6, 5, 4, 1, 3, 3, 1, 2, 256, 68, 61, 44,,,, -6, 5, 4, 1, 3, 3, 1, 2, 384, 68, 61, 44,,,, -6, 5, 4, 1, 3, 3, 1, 3, 128, 68, 61, 44,,,, -6, 5, 4, 1, 3, 3, 1, 3, 256, 68, 61, 44,,,, -6, 5, 4, 1, 3, 3, 1, 3, 384, 68, 61, 44,,,, -6, 5, 4, 1, 3, 3, 2, 1, 128, 68, 61, 44,,,, -6, 5, 4, 1, 3, 3, 2, 1, 256, 68, 61, 44,,,, -6, 5, 4, 1, 3, 3, 2, 1, 384, 68, 61, 44,,,, -6, 5, 4, 1, 3, 3, 2, 2, 128, 68, 61, 44,,,, -6, 5, 4, 1, 3, 3, 2, 2, 256, 68, 61, 44,,,, -6, 5, 4, 1, 3, 3, 2, 2, 384, 68, 61, 44,,,, -6, 5, 4, 1, 3, 3, 2, 3, 128, 68, 61, 44,,,, -6, 5, 4, 1, 3, 3, 2, 3, 256, 68, 61, 44,,,, -6, 5, 4, 1, 3, 3, 2, 3, 384, 68, 61, 44,,,, -6, 5, 4, 1, 3, 3, 3, 1, 128, 68, 61, 44,,,, -6, 5, 4, 1, 3, 3, 3, 1, 256, 68, 61, 44,,,, -6, 5, 4, 1, 3, 3, 3, 1, 384, 68, 61, 44,,,, -6, 5, 4, 1, 3, 3, 3, 2, 128, 68, 61, 44,,,, -6, 5, 4, 1, 3, 3, 3, 2, 256, 68, 61, 44,,,, -6, 5, 4, 1, 3, 3, 3, 2, 384, 68, 61, 44,,,, -6, 5, 4, 1, 3, 3, 3, 3, 128, 68, 61, 44,,,, -6, 5, 4, 1, 3, 3, 3, 3, 256, 68, 61, 44,,,, -6, 5, 4, 1, 3, 3, 3, 3, 384, 68, 61, 44,,,, -6, 5, 4, 2, 1, 1, 1, 1, 128, 132, 132, 88,,,, -6, 5, 4, 2, 1, 1, 1, 1, 256, 132, 132, 88,,,, -6, 5, 4, 2, 1, 1, 1, 1, 384, 132, 132, 88,,,, -6, 5, 4, 2, 2, 2, 1, 1, 128, 132, 124, 86,,,, -6, 5, 4, 2, 2, 2, 1, 1, 256, 132, 124, 86,,,, -6, 5, 4, 2, 2, 2, 1, 1, 384, 132, 124, 86,,,, -6, 5, 4, 2, 2, 2, 1, 2, 128, 132, 124, 86,,,, -6, 5, 4, 2, 2, 2, 1, 2, 256, 132, 124, 86,,,, -6, 5, 4, 2, 2, 2, 1, 2, 384, 132, 124, 86,,,, -6, 5, 4, 2, 2, 2, 2, 1, 128, 132, 124, 86,,,, -6, 5, 4, 2, 2, 2, 2, 1, 256, 132, 124, 86,,,, -6, 5, 4, 2, 2, 2, 2, 1, 384, 132, 124, 86,,,, -6, 5, 4, 2, 2, 2, 2, 2, 128, 132, 124, 86,,,, -6, 5, 4, 2, 2, 2, 2, 2, 256, 132, 124, 86,,,, -6, 5, 4, 2, 2, 2, 2, 2, 384, 132, 124, 86,,,, -6, 5, 4, 2, 3, 3, 1, 1, 128, 132, 118, 84,,,, -6, 5, 4, 2, 3, 3, 1, 1, 256, 132, 118, 84,,,, -6, 5, 4, 2, 3, 3, 1, 1, 384, 132, 118, 84,,,, -6, 5, 4, 2, 3, 3, 1, 2, 128, 132, 118, 84,,,, -6, 5, 4, 2, 3, 3, 1, 2, 256, 132, 118, 84,,,, -6, 5, 4, 2, 3, 3, 1, 2, 384, 132, 118, 84,,,, -6, 5, 4, 2, 3, 3, 1, 3, 128, 132, 118, 84,,,, -6, 5, 4, 2, 3, 3, 1, 3, 256, 132, 118, 84,,,, -6, 5, 4, 2, 3, 3, 1, 3, 384, 132, 118, 84,,,, -6, 5, 4, 2, 3, 3, 2, 1, 128, 132, 118, 84,,,, -6, 5, 4, 2, 3, 3, 2, 1, 256, 132, 118, 84,,,, -6, 5, 4, 2, 3, 3, 2, 1, 384, 132, 118, 84,,,, -6, 5, 4, 2, 3, 3, 2, 2, 128, 132, 118, 84,,,, -6, 5, 4, 2, 3, 3, 2, 2, 256, 132, 118, 84,,,, -6, 5, 4, 2, 3, 3, 2, 2, 384, 132, 118, 84,,,, -6, 5, 4, 2, 3, 3, 2, 3, 128, 132, 118, 84,,,, -6, 5, 4, 2, 3, 3, 2, 3, 256, 132, 118, 84,,,, -6, 5, 4, 2, 3, 3, 2, 3, 384, 132, 118, 84,,,, -6, 5, 4, 2, 3, 3, 3, 1, 128, 132, 118, 84,,,, -6, 5, 4, 2, 3, 3, 3, 1, 256, 132, 118, 84,,,, -6, 5, 4, 2, 3, 3, 3, 1, 384, 132, 118, 84,,,, -6, 5, 4, 2, 3, 3, 3, 2, 128, 132, 118, 84,,,, -6, 5, 4, 2, 3, 3, 3, 2, 256, 132, 118, 84,,,, -6, 5, 4, 2, 3, 3, 3, 2, 384, 132, 118, 84,,,, -6, 5, 4, 2, 3, 3, 3, 3, 128, 132, 118, 84,,,, -6, 5, 4, 2, 3, 3, 3, 3, 256, 132, 118, 84,,,, -6, 5, 4, 2, 3, 3, 3, 3, 384, 132, 118, 84,,,, -6, 5, 4, 3, 1, 1, 1, 1, 128, 196, 196, 130,,,, -6, 5, 4, 3, 1, 1, 1, 1, 256, 196, 196, 130,,,, -6, 5, 4, 3, 1, 1, 1, 1, 384, 196, 196, 130,,,, -6, 5, 4, 3, 2, 2, 1, 1, 128, 196, 184, 127,,,, -6, 5, 4, 3, 2, 2, 1, 1, 256, 196, 184, 127,,,, -6, 5, 4, 3, 2, 2, 1, 1, 384, 196, 184, 127,,,, -6, 5, 4, 3, 2, 2, 1, 2, 128, 196, 184, 127,,,, -6, 5, 4, 3, 2, 2, 1, 2, 256, 196, 184, 127,,,, -6, 5, 4, 3, 2, 2, 1, 2, 384, 196, 184, 127,,,, -6, 5, 4, 3, 2, 2, 2, 1, 128, 196, 184, 127,,,, -6, 5, 4, 3, 2, 2, 2, 1, 256, 196, 184, 127,,,, -6, 5, 4, 3, 2, 2, 2, 1, 384, 196, 184, 127,,,, -6, 5, 4, 3, 2, 2, 2, 2, 128, 196, 184, 127,,,, -6, 5, 4, 3, 2, 2, 2, 2, 256, 196, 184, 127,,,, -6, 5, 4, 3, 2, 2, 2, 2, 384, 196, 184, 127,,,, -6, 5, 4, 3, 3, 3, 1, 1, 128, 196, 175, 124,,,, -6, 5, 4, 3, 3, 3, 1, 1, 256, 196, 175, 124,,,, -6, 5, 4, 3, 3, 3, 1, 1, 384, 196, 175, 124,,,, -6, 5, 4, 3, 3, 3, 1, 2, 128, 196, 175, 124,,,, -6, 5, 4, 3, 3, 3, 1, 2, 256, 196, 175, 124,,,, -6, 5, 4, 3, 3, 3, 1, 2, 384, 196, 175, 124,,,, -6, 5, 4, 3, 3, 3, 1, 3, 128, 196, 175, 124,,,, -6, 5, 4, 3, 3, 3, 1, 3, 256, 196, 175, 124,,,, -6, 5, 4, 3, 3, 3, 1, 3, 384, 196, 175, 124,,,, -6, 5, 4, 3, 3, 3, 2, 1, 128, 196, 175, 124,,,, -6, 5, 4, 3, 3, 3, 2, 1, 256, 196, 175, 124,,,, -6, 5, 4, 3, 3, 3, 2, 1, 384, 196, 175, 124,,,, -6, 5, 4, 3, 3, 3, 2, 2, 128, 196, 175, 124,,,, -6, 5, 4, 3, 3, 3, 2, 2, 256, 196, 175, 124,,,, -6, 5, 4, 3, 3, 3, 2, 2, 384, 196, 175, 124,,,, -6, 5, 4, 3, 3, 3, 2, 3, 128, 196, 175, 124,,,, -6, 5, 4, 3, 3, 3, 2, 3, 256, 196, 175, 124,,,, -6, 5, 4, 3, 3, 3, 2, 3, 384, 196, 175, 124,,,, -6, 5, 4, 3, 3, 3, 3, 1, 128, 196, 175, 124,,,, -6, 5, 4, 3, 3, 3, 3, 1, 256, 196, 175, 124,,,, -6, 5, 4, 3, 3, 3, 3, 1, 384, 196, 175, 124,,,, -6, 5, 4, 3, 3, 3, 3, 2, 128, 196, 175, 124,,,, -6, 5, 4, 3, 3, 3, 3, 2, 256, 196, 175, 124,,,, -6, 5, 4, 3, 3, 3, 3, 2, 384, 196, 175, 124,,,, -6, 5, 4, 3, 3, 3, 3, 3, 128, 196, 175, 124,,,, -6, 5, 4, 3, 3, 3, 3, 3, 256, 196, 175, 124,,,, -6, 5, 4, 3, 3, 3, 3, 3, 384, 196, 175, 124,,,, -6, 5, 4, 4, 1, 1, 1, 1, 128, 240, 240, 172,,,, -6, 5, 4, 4, 1, 1, 1, 1, 256, 240, 240, 172,,,, -6, 5, 4, 4, 1, 1, 1, 1, 384, 240, 240, 172,,,, -6, 5, 4, 4, 2, 2, 1, 1, 128, 240, 240, 168,,,, -6, 5, 4, 4, 2, 2, 1, 1, 256, 240, 240, 168,,,, -6, 5, 4, 4, 2, 2, 1, 1, 384, 240, 240, 168,,,, -6, 5, 4, 4, 2, 2, 1, 2, 128, 240, 240, 168,,,, -6, 5, 4, 4, 2, 2, 1, 2, 256, 240, 240, 168,,,, -6, 5, 4, 4, 2, 2, 1, 2, 384, 240, 240, 168,,,, -6, 5, 4, 4, 2, 2, 2, 1, 128, 240, 240, 168,,,, -6, 5, 4, 4, 2, 2, 2, 1, 256, 240, 240, 168,,,, -6, 5, 4, 4, 2, 2, 2, 1, 384, 240, 240, 168,,,, -6, 5, 4, 4, 2, 2, 2, 2, 128, 240, 240, 168,,,, -6, 5, 4, 4, 2, 2, 2, 2, 256, 240, 240, 168,,,, -6, 5, 4, 4, 2, 2, 2, 2, 384, 240, 240, 168,,,, -6, 5, 4, 4, 3, 3, 1, 1, 128, 240, 232, 164,,,, -6, 5, 4, 4, 3, 3, 1, 1, 256, 240, 232, 164,,,, -6, 5, 4, 4, 3, 3, 1, 1, 384, 240, 232, 164,,,, -6, 5, 4, 4, 3, 3, 1, 2, 128, 240, 232, 164,,,, -6, 5, 4, 4, 3, 3, 1, 2, 256, 240, 232, 164,,,, -6, 5, 4, 4, 3, 3, 1, 2, 384, 240, 232, 164,,,, -6, 5, 4, 4, 3, 3, 1, 3, 128, 240, 232, 164,,,, -6, 5, 4, 4, 3, 3, 1, 3, 256, 240, 232, 164,,,, -6, 5, 4, 4, 3, 3, 1, 3, 384, 240, 232, 164,,,, -6, 5, 4, 4, 3, 3, 2, 1, 128, 240, 232, 164,,,, -6, 5, 4, 4, 3, 3, 2, 1, 256, 240, 232, 164,,,, -6, 5, 4, 4, 3, 3, 2, 1, 384, 240, 232, 164,,,, -6, 5, 4, 4, 3, 3, 2, 2, 128, 240, 232, 164,,,, -6, 5, 4, 4, 3, 3, 2, 2, 256, 240, 232, 164,,,, -6, 5, 4, 4, 3, 3, 2, 2, 384, 240, 232, 164,,,, -6, 5, 4, 4, 3, 3, 2, 3, 128, 240, 232, 164,,,, -6, 5, 4, 4, 3, 3, 2, 3, 256, 240, 232, 164,,,, -6, 5, 4, 4, 3, 3, 2, 3, 384, 240, 232, 164,,,, -6, 5, 4, 4, 3, 3, 3, 1, 128, 240, 232, 164,,,, -6, 5, 4, 4, 3, 3, 3, 1, 256, 240, 232, 164,,,, -6, 5, 4, 4, 3, 3, 3, 1, 384, 240, 232, 164,,,, -6, 5, 4, 4, 3, 3, 3, 2, 128, 240, 232, 164,,,, -6, 5, 4, 4, 3, 3, 3, 2, 256, 240, 232, 164,,,, -6, 5, 4, 4, 3, 3, 3, 2, 384, 240, 232, 164,,,, -6, 5, 4, 4, 3, 3, 3, 3, 128, 240, 232, 164,,,, -6, 5, 4, 4, 3, 3, 3, 3, 256, 240, 232, 164,,,, -6, 5, 4, 4, 3, 3, 3, 3, 384, 240, 232, 164,,,, -6, 5, 4, 5, 1, 1, 1, 1, 128, 240, 240, 214,,,, -6, 5, 4, 5, 1, 1, 1, 1, 256, 240, 240, 214,,,, -6, 5, 4, 5, 1, 1, 1, 1, 384, 240, 240, 214,,,, -6, 5, 4, 5, 2, 2, 1, 1, 128, 240, 240, 209,,,, -6, 5, 4, 5, 2, 2, 1, 1, 256, 240, 240, 209,,,, -6, 5, 4, 5, 2, 2, 1, 1, 384, 240, 240, 209,,,, -6, 5, 4, 5, 2, 2, 1, 2, 128, 240, 240, 209,,,, -6, 5, 4, 5, 2, 2, 1, 2, 256, 240, 240, 209,,,, -6, 5, 4, 5, 2, 2, 1, 2, 384, 240, 240, 209,,,, -6, 5, 4, 5, 2, 2, 2, 1, 128, 240, 240, 209,,,, -6, 5, 4, 5, 2, 2, 2, 1, 256, 240, 240, 209,,,, -6, 5, 4, 5, 2, 2, 2, 1, 384, 240, 240, 209,,,, -6, 5, 4, 5, 2, 2, 2, 2, 128, 240, 240, 209,,,, -6, 5, 4, 5, 2, 2, 2, 2, 256, 240, 240, 209,,,, -6, 5, 4, 5, 2, 2, 2, 2, 384, 240, 240, 209,,,, -6, 5, 4, 5, 3, 3, 1, 1, 128, 240, 240, 204,,,, -6, 5, 4, 5, 3, 3, 1, 1, 256, 240, 240, 204,,,, -6, 5, 4, 5, 3, 3, 1, 1, 384, 240, 240, 204,,,, -6, 5, 4, 5, 3, 3, 1, 2, 128, 240, 240, 204,,,, -6, 5, 4, 5, 3, 3, 1, 2, 256, 240, 240, 204,,,, -6, 5, 4, 5, 3, 3, 1, 2, 384, 240, 240, 204,,,, -6, 5, 4, 5, 3, 3, 1, 3, 128, 240, 240, 204,,,, -6, 5, 4, 5, 3, 3, 1, 3, 256, 240, 240, 204,,,, -6, 5, 4, 5, 3, 3, 1, 3, 384, 240, 240, 204,,,, -6, 5, 4, 5, 3, 3, 2, 1, 128, 240, 240, 204,,,, -6, 5, 4, 5, 3, 3, 2, 1, 256, 240, 240, 204,,,, -6, 5, 4, 5, 3, 3, 2, 1, 384, 240, 240, 204,,,, -6, 5, 4, 5, 3, 3, 2, 2, 128, 240, 240, 204,,,, -6, 5, 4, 5, 3, 3, 2, 2, 256, 240, 240, 204,,,, -6, 5, 4, 5, 3, 3, 2, 2, 384, 240, 240, 204,,,, -6, 5, 4, 5, 3, 3, 2, 3, 128, 240, 240, 204,,,, -6, 5, 4, 5, 3, 3, 2, 3, 256, 240, 240, 204,,,, -6, 5, 4, 5, 3, 3, 2, 3, 384, 240, 240, 204,,,, -6, 5, 4, 5, 3, 3, 3, 1, 128, 240, 240, 204,,,, -6, 5, 4, 5, 3, 3, 3, 1, 256, 240, 240, 204,,,, -6, 5, 4, 5, 3, 3, 3, 1, 384, 240, 240, 204,,,, -6, 5, 4, 5, 3, 3, 3, 2, 128, 240, 240, 204,,,, -6, 5, 4, 5, 3, 3, 3, 2, 256, 240, 240, 204,,,, -6, 5, 4, 5, 3, 3, 3, 2, 384, 240, 240, 204,,,, -6, 5, 4, 5, 3, 3, 3, 3, 128, 240, 240, 204,,,, -6, 5, 4, 5, 3, 3, 3, 3, 256, 240, 240, 204,,,, -6, 5, 4, 5, 3, 3, 3, 3, 384, 240, 240, 204,,,, -6, 5, 5, 1, 1, 1, 1, 1, 128, 68, 68, 46,,,, -6, 5, 5, 1, 1, 1, 1, 1, 256, 68, 68, 46,,,, -6, 5, 5, 1, 1, 1, 1, 1, 384, 68, 68, 46,,,, -6, 5, 5, 1, 2, 2, 1, 1, 128, 68, 64, 45,,,, -6, 5, 5, 1, 2, 2, 1, 1, 256, 68, 64, 45,,,, -6, 5, 5, 1, 2, 2, 1, 1, 384, 68, 64, 45,,,, -6, 5, 5, 1, 2, 2, 1, 2, 128, 68, 64, 45,,,, -6, 5, 5, 1, 2, 2, 1, 2, 256, 68, 64, 45,,,, -6, 5, 5, 1, 2, 2, 1, 2, 384, 68, 64, 45,,,, -6, 5, 5, 1, 2, 2, 2, 1, 128, 68, 64, 45,,,, -6, 5, 5, 1, 2, 2, 2, 1, 256, 68, 64, 45,,,, -6, 5, 5, 1, 2, 2, 2, 1, 384, 68, 64, 45,,,, -6, 5, 5, 1, 2, 2, 2, 2, 128, 68, 64, 45,,,, -6, 5, 5, 1, 2, 2, 2, 2, 256, 68, 64, 45,,,, -6, 5, 5, 1, 2, 2, 2, 2, 384, 68, 64, 45,,,, -6, 5, 5, 1, 3, 3, 1, 1, 128, 68, 61, 44,,,, -6, 5, 5, 1, 3, 3, 1, 1, 256, 68, 61, 44,,,, -6, 5, 5, 1, 3, 3, 1, 1, 384, 68, 61, 44,,,, -6, 5, 5, 1, 3, 3, 1, 2, 128, 68, 61, 44,,,, -6, 5, 5, 1, 3, 3, 1, 2, 256, 68, 61, 44,,,, -6, 5, 5, 1, 3, 3, 1, 2, 384, 68, 61, 44,,,, -6, 5, 5, 1, 3, 3, 1, 3, 128, 68, 61, 44,,,, -6, 5, 5, 1, 3, 3, 1, 3, 256, 68, 61, 44,,,, -6, 5, 5, 1, 3, 3, 1, 3, 384, 68, 61, 44,,,, -6, 5, 5, 1, 3, 3, 2, 1, 128, 68, 61, 44,,,, -6, 5, 5, 1, 3, 3, 2, 1, 256, 68, 61, 44,,,, -6, 5, 5, 1, 3, 3, 2, 1, 384, 68, 61, 44,,,, -6, 5, 5, 1, 3, 3, 2, 2, 128, 68, 61, 44,,,, -6, 5, 5, 1, 3, 3, 2, 2, 256, 68, 61, 44,,,, -6, 5, 5, 1, 3, 3, 2, 2, 384, 68, 61, 44,,,, -6, 5, 5, 1, 3, 3, 2, 3, 128, 68, 61, 44,,,, -6, 5, 5, 1, 3, 3, 2, 3, 256, 68, 61, 44,,,, -6, 5, 5, 1, 3, 3, 2, 3, 384, 68, 61, 44,,,, -6, 5, 5, 1, 3, 3, 3, 1, 128, 68, 61, 44,,,, -6, 5, 5, 1, 3, 3, 3, 1, 256, 68, 61, 44,,,, -6, 5, 5, 1, 3, 3, 3, 1, 384, 68, 61, 44,,,, -6, 5, 5, 1, 3, 3, 3, 2, 128, 68, 61, 44,,,, -6, 5, 5, 1, 3, 3, 3, 2, 256, 68, 61, 44,,,, -6, 5, 5, 1, 3, 3, 3, 2, 384, 68, 61, 44,,,, -6, 5, 5, 1, 3, 3, 3, 3, 128, 68, 61, 44,,,, -6, 5, 5, 1, 3, 3, 3, 3, 256, 68, 61, 44,,,, -6, 5, 5, 1, 3, 3, 3, 3, 384, 68, 61, 44,,,, -6, 5, 5, 2, 1, 1, 1, 1, 128, 132, 132, 88,,,, -6, 5, 5, 2, 1, 1, 1, 1, 256, 132, 132, 88,,,, -6, 5, 5, 2, 1, 1, 1, 1, 384, 132, 132, 88,,,, -6, 5, 5, 2, 2, 2, 1, 1, 128, 132, 124, 86,,,, -6, 5, 5, 2, 2, 2, 1, 1, 256, 132, 124, 86,,,, -6, 5, 5, 2, 2, 2, 1, 1, 384, 132, 124, 86,,,, -6, 5, 5, 2, 2, 2, 1, 2, 128, 132, 124, 86,,,, -6, 5, 5, 2, 2, 2, 1, 2, 256, 132, 124, 86,,,, -6, 5, 5, 2, 2, 2, 1, 2, 384, 132, 124, 86,,,, -6, 5, 5, 2, 2, 2, 2, 1, 128, 132, 124, 86,,,, -6, 5, 5, 2, 2, 2, 2, 1, 256, 132, 124, 86,,,, -6, 5, 5, 2, 2, 2, 2, 1, 384, 132, 124, 86,,,, -6, 5, 5, 2, 2, 2, 2, 2, 128, 132, 124, 86,,,, -6, 5, 5, 2, 2, 2, 2, 2, 256, 132, 124, 86,,,, -6, 5, 5, 2, 2, 2, 2, 2, 384, 132, 124, 86,,,, -6, 5, 5, 2, 3, 3, 1, 1, 128, 132, 118, 84,,,, -6, 5, 5, 2, 3, 3, 1, 1, 256, 132, 118, 84,,,, -6, 5, 5, 2, 3, 3, 1, 1, 384, 132, 118, 84,,,, -6, 5, 5, 2, 3, 3, 1, 2, 128, 132, 118, 84,,,, -6, 5, 5, 2, 3, 3, 1, 2, 256, 132, 118, 84,,,, -6, 5, 5, 2, 3, 3, 1, 2, 384, 132, 118, 84,,,, -6, 5, 5, 2, 3, 3, 1, 3, 128, 132, 118, 84,,,, -6, 5, 5, 2, 3, 3, 1, 3, 256, 132, 118, 84,,,, -6, 5, 5, 2, 3, 3, 1, 3, 384, 132, 118, 84,,,, -6, 5, 5, 2, 3, 3, 2, 1, 128, 132, 118, 84,,,, -6, 5, 5, 2, 3, 3, 2, 1, 256, 132, 118, 84,,,, -6, 5, 5, 2, 3, 3, 2, 1, 384, 132, 118, 84,,,, -6, 5, 5, 2, 3, 3, 2, 2, 128, 132, 118, 84,,,, -6, 5, 5, 2, 3, 3, 2, 2, 256, 132, 118, 84,,,, -6, 5, 5, 2, 3, 3, 2, 2, 384, 132, 118, 84,,,, -6, 5, 5, 2, 3, 3, 2, 3, 128, 132, 118, 84,,,, -6, 5, 5, 2, 3, 3, 2, 3, 256, 132, 118, 84,,,, -6, 5, 5, 2, 3, 3, 2, 3, 384, 132, 118, 84,,,, -6, 5, 5, 2, 3, 3, 3, 1, 128, 132, 118, 84,,,, -6, 5, 5, 2, 3, 3, 3, 1, 256, 132, 118, 84,,,, -6, 5, 5, 2, 3, 3, 3, 1, 384, 132, 118, 84,,,, -6, 5, 5, 2, 3, 3, 3, 2, 128, 132, 118, 84,,,, -6, 5, 5, 2, 3, 3, 3, 2, 256, 132, 118, 84,,,, -6, 5, 5, 2, 3, 3, 3, 2, 384, 132, 118, 84,,,, -6, 5, 5, 2, 3, 3, 3, 3, 128, 132, 118, 84,,,, -6, 5, 5, 2, 3, 3, 3, 3, 256, 132, 118, 84,,,, -6, 5, 5, 2, 3, 3, 3, 3, 384, 132, 118, 84,,,, -6, 5, 5, 3, 1, 1, 1, 1, 128, 196, 196, 130,,,, -6, 5, 5, 3, 1, 1, 1, 1, 256, 196, 196, 130,,,, -6, 5, 5, 3, 1, 1, 1, 1, 384, 196, 196, 130,,,, -6, 5, 5, 3, 2, 2, 1, 1, 128, 196, 184, 127,,,, -6, 5, 5, 3, 2, 2, 1, 1, 256, 196, 184, 127,,,, -6, 5, 5, 3, 2, 2, 1, 1, 384, 196, 184, 127,,,, -6, 5, 5, 3, 2, 2, 1, 2, 128, 196, 184, 127,,,, -6, 5, 5, 3, 2, 2, 1, 2, 256, 196, 184, 127,,,, -6, 5, 5, 3, 2, 2, 1, 2, 384, 196, 184, 127,,,, -6, 5, 5, 3, 2, 2, 2, 1, 128, 196, 184, 127,,,, -6, 5, 5, 3, 2, 2, 2, 1, 256, 196, 184, 127,,,, -6, 5, 5, 3, 2, 2, 2, 1, 384, 196, 184, 127,,,, -6, 5, 5, 3, 2, 2, 2, 2, 128, 196, 184, 127,,,, -6, 5, 5, 3, 2, 2, 2, 2, 256, 196, 184, 127,,,, -6, 5, 5, 3, 2, 2, 2, 2, 384, 196, 184, 127,,,, -6, 5, 5, 3, 3, 3, 1, 1, 128, 196, 175, 124,,,, -6, 5, 5, 3, 3, 3, 1, 1, 256, 196, 175, 124,,,, -6, 5, 5, 3, 3, 3, 1, 1, 384, 196, 175, 124,,,, -6, 5, 5, 3, 3, 3, 1, 2, 128, 196, 175, 124,,,, -6, 5, 5, 3, 3, 3, 1, 2, 256, 196, 175, 124,,,, -6, 5, 5, 3, 3, 3, 1, 2, 384, 196, 175, 124,,,, -6, 5, 5, 3, 3, 3, 1, 3, 128, 196, 175, 124,,,, -6, 5, 5, 3, 3, 3, 1, 3, 256, 196, 175, 124,,,, -6, 5, 5, 3, 3, 3, 1, 3, 384, 196, 175, 124,,,, -6, 5, 5, 3, 3, 3, 2, 1, 128, 196, 175, 124,,,, -6, 5, 5, 3, 3, 3, 2, 1, 256, 196, 175, 124,,,, -6, 5, 5, 3, 3, 3, 2, 1, 384, 196, 175, 124,,,, -6, 5, 5, 3, 3, 3, 2, 2, 128, 196, 175, 124,,,, -6, 5, 5, 3, 3, 3, 2, 2, 256, 196, 175, 124,,,, -6, 5, 5, 3, 3, 3, 2, 2, 384, 196, 175, 124,,,, -6, 5, 5, 3, 3, 3, 2, 3, 128, 196, 175, 124,,,, -6, 5, 5, 3, 3, 3, 2, 3, 256, 196, 175, 124,,,, -6, 5, 5, 3, 3, 3, 2, 3, 384, 196, 175, 124,,,, -6, 5, 5, 3, 3, 3, 3, 1, 128, 196, 175, 124,,,, -6, 5, 5, 3, 3, 3, 3, 1, 256, 196, 175, 124,,,, -6, 5, 5, 3, 3, 3, 3, 1, 384, 196, 175, 124,,,, -6, 5, 5, 3, 3, 3, 3, 2, 128, 196, 175, 124,,,, -6, 5, 5, 3, 3, 3, 3, 2, 256, 196, 175, 124,,,, -6, 5, 5, 3, 3, 3, 3, 2, 384, 196, 175, 124,,,, -6, 5, 5, 3, 3, 3, 3, 3, 128, 196, 175, 124,,,, -6, 5, 5, 3, 3, 3, 3, 3, 256, 196, 175, 124,,,, -6, 5, 5, 3, 3, 3, 3, 3, 384, 196, 175, 124,,,, -6, 5, 5, 4, 1, 1, 1, 1, 128, 240, 240, 172,,,, -6, 5, 5, 4, 1, 1, 1, 1, 256, 240, 240, 172,,,, -6, 5, 5, 4, 1, 1, 1, 1, 384, 240, 240, 172,,,, -6, 5, 5, 4, 2, 2, 1, 1, 128, 240, 240, 168,,,, -6, 5, 5, 4, 2, 2, 1, 1, 256, 240, 240, 168,,,, -6, 5, 5, 4, 2, 2, 1, 1, 384, 240, 240, 168,,,, -6, 5, 5, 4, 2, 2, 1, 2, 128, 240, 240, 168,,,, -6, 5, 5, 4, 2, 2, 1, 2, 256, 240, 240, 168,,,, -6, 5, 5, 4, 2, 2, 1, 2, 384, 240, 240, 168,,,, -6, 5, 5, 4, 2, 2, 2, 1, 128, 240, 240, 168,,,, -6, 5, 5, 4, 2, 2, 2, 1, 256, 240, 240, 168,,,, -6, 5, 5, 4, 2, 2, 2, 1, 384, 240, 240, 168,,,, -6, 5, 5, 4, 2, 2, 2, 2, 128, 240, 240, 168,,,, -6, 5, 5, 4, 2, 2, 2, 2, 256, 240, 240, 168,,,, -6, 5, 5, 4, 2, 2, 2, 2, 384, 240, 240, 168,,,, -6, 5, 5, 4, 3, 3, 1, 1, 128, 240, 232, 164,,,, -6, 5, 5, 4, 3, 3, 1, 1, 256, 240, 232, 164,,,, -6, 5, 5, 4, 3, 3, 1, 1, 384, 240, 232, 164,,,, -6, 5, 5, 4, 3, 3, 1, 2, 128, 240, 232, 164,,,, -6, 5, 5, 4, 3, 3, 1, 2, 256, 240, 232, 164,,,, -6, 5, 5, 4, 3, 3, 1, 2, 384, 240, 232, 164,,,, -6, 5, 5, 4, 3, 3, 1, 3, 128, 240, 232, 164,,,, -6, 5, 5, 4, 3, 3, 1, 3, 256, 240, 232, 164,,,, -6, 5, 5, 4, 3, 3, 1, 3, 384, 240, 232, 164,,,, -6, 5, 5, 4, 3, 3, 2, 1, 128, 240, 232, 164,,,, -6, 5, 5, 4, 3, 3, 2, 1, 256, 240, 232, 164,,,, -6, 5, 5, 4, 3, 3, 2, 1, 384, 240, 232, 164,,,, -6, 5, 5, 4, 3, 3, 2, 2, 128, 240, 232, 164,,,, -6, 5, 5, 4, 3, 3, 2, 2, 256, 240, 232, 164,,,, -6, 5, 5, 4, 3, 3, 2, 2, 384, 240, 232, 164,,,, -6, 5, 5, 4, 3, 3, 2, 3, 128, 240, 232, 164,,,, -6, 5, 5, 4, 3, 3, 2, 3, 256, 240, 232, 164,,,, -6, 5, 5, 4, 3, 3, 2, 3, 384, 240, 232, 164,,,, -6, 5, 5, 4, 3, 3, 3, 1, 128, 240, 232, 164,,,, -6, 5, 5, 4, 3, 3, 3, 1, 256, 240, 232, 164,,,, -6, 5, 5, 4, 3, 3, 3, 1, 384, 240, 232, 164,,,, -6, 5, 5, 4, 3, 3, 3, 2, 128, 240, 232, 164,,,, -6, 5, 5, 4, 3, 3, 3, 2, 256, 240, 232, 164,,,, -6, 5, 5, 4, 3, 3, 3, 2, 384, 240, 232, 164,,,, -6, 5, 5, 4, 3, 3, 3, 3, 128, 240, 232, 164,,,, -6, 5, 5, 4, 3, 3, 3, 3, 256, 240, 232, 164,,,, -6, 5, 5, 4, 3, 3, 3, 3, 384, 240, 232, 164,,,, -6, 5, 5, 5, 1, 1, 1, 1, 128, 240, 240, 214,,,, -6, 5, 5, 5, 1, 1, 1, 1, 256, 240, 240, 214,,,, -6, 5, 5, 5, 1, 1, 1, 1, 384, 240, 240, 214,,,, -6, 5, 5, 5, 2, 2, 1, 1, 128, 240, 240, 209,,,, -6, 5, 5, 5, 2, 2, 1, 1, 256, 240, 240, 209,,,, -6, 5, 5, 5, 2, 2, 1, 1, 384, 240, 240, 209,,,, -6, 5, 5, 5, 2, 2, 1, 2, 128, 240, 240, 209,,,, -6, 5, 5, 5, 2, 2, 1, 2, 256, 240, 240, 209,,,, -6, 5, 5, 5, 2, 2, 1, 2, 384, 240, 240, 209,,,, -6, 5, 5, 5, 2, 2, 2, 1, 128, 240, 240, 209,,,, -6, 5, 5, 5, 2, 2, 2, 1, 256, 240, 240, 209,,,, -6, 5, 5, 5, 2, 2, 2, 1, 384, 240, 240, 209,,,, -6, 5, 5, 5, 2, 2, 2, 2, 128, 240, 240, 209,,,, -6, 5, 5, 5, 2, 2, 2, 2, 256, 240, 240, 209,,,, -6, 5, 5, 5, 2, 2, 2, 2, 384, 240, 240, 209,,,, -6, 5, 5, 5, 3, 3, 1, 1, 128, 240, 240, 204,,,, -6, 5, 5, 5, 3, 3, 1, 1, 256, 240, 240, 204,,,, -6, 5, 5, 5, 3, 3, 1, 1, 384, 240, 240, 204,,,, -6, 5, 5, 5, 3, 3, 1, 2, 128, 240, 240, 204,,,, -6, 5, 5, 5, 3, 3, 1, 2, 256, 240, 240, 204,,,, -6, 5, 5, 5, 3, 3, 1, 2, 384, 240, 240, 204,,,, -6, 5, 5, 5, 3, 3, 1, 3, 128, 240, 240, 204,,,, -6, 5, 5, 5, 3, 3, 1, 3, 256, 240, 240, 204,,,, -6, 5, 5, 5, 3, 3, 1, 3, 384, 240, 240, 204,,,, -6, 5, 5, 5, 3, 3, 2, 1, 128, 240, 240, 204,,,, -6, 5, 5, 5, 3, 3, 2, 1, 256, 240, 240, 204,,,, -6, 5, 5, 5, 3, 3, 2, 1, 384, 240, 240, 204,,,, -6, 5, 5, 5, 3, 3, 2, 2, 128, 240, 240, 204,,,, -6, 5, 5, 5, 3, 3, 2, 2, 256, 240, 240, 204,,,, -6, 5, 5, 5, 3, 3, 2, 2, 384, 240, 240, 204,,,, -6, 5, 5, 5, 3, 3, 2, 3, 128, 240, 240, 204,,,, -6, 5, 5, 5, 3, 3, 2, 3, 256, 240, 240, 204,,,, -6, 5, 5, 5, 3, 3, 2, 3, 384, 240, 240, 204,,,, -6, 5, 5, 5, 3, 3, 3, 1, 128, 240, 240, 204,,,, -6, 5, 5, 5, 3, 3, 3, 1, 256, 240, 240, 204,,,, -6, 5, 5, 5, 3, 3, 3, 1, 384, 240, 240, 204,,,, -6, 5, 5, 5, 3, 3, 3, 2, 128, 240, 240, 204,,,, -6, 5, 5, 5, 3, 3, 3, 2, 256, 240, 240, 204,,,, -6, 5, 5, 5, 3, 3, 3, 2, 384, 240, 240, 204,,,, -6, 5, 5, 5, 3, 3, 3, 3, 128, 240, 240, 204,,,, -6, 5, 5, 5, 3, 3, 3, 3, 256, 240, 240, 204,,,, -6, 5, 5, 5, 3, 3, 3, 3, 384, 240, 240, 204,,,, -6, 5, 6, 1, 1, 1, 1, 1, 128, 68, 68, 46,,,, -6, 5, 6, 1, 1, 1, 1, 1, 256, 68, 68, 46,,,, -6, 5, 6, 1, 1, 1, 1, 1, 384, 68, 68, 46,,,, -6, 5, 6, 1, 2, 2, 1, 1, 128, 68, 64, 45,,,, -6, 5, 6, 1, 2, 2, 1, 1, 256, 68, 64, 45,,,, -6, 5, 6, 1, 2, 2, 1, 1, 384, 68, 64, 45,,,, -6, 5, 6, 1, 2, 2, 1, 2, 128, 68, 64, 45,,,, -6, 5, 6, 1, 2, 2, 1, 2, 256, 68, 64, 45,,,, -6, 5, 6, 1, 2, 2, 1, 2, 384, 68, 64, 45,,,, -6, 5, 6, 1, 2, 2, 2, 1, 128, 68, 64, 45,,,, -6, 5, 6, 1, 2, 2, 2, 1, 256, 68, 64, 45,,,, -6, 5, 6, 1, 2, 2, 2, 1, 384, 68, 64, 45,,,, -6, 5, 6, 1, 2, 2, 2, 2, 128, 68, 64, 45,,,, -6, 5, 6, 1, 2, 2, 2, 2, 256, 68, 64, 45,,,, -6, 5, 6, 1, 2, 2, 2, 2, 384, 68, 64, 45,,,, -6, 5, 6, 1, 3, 3, 1, 1, 128, 68, 61, 44,,,, -6, 5, 6, 1, 3, 3, 1, 1, 256, 68, 61, 44,,,, -6, 5, 6, 1, 3, 3, 1, 1, 384, 68, 61, 44,,,, -6, 5, 6, 1, 3, 3, 1, 2, 128, 68, 61, 44,,,, -6, 5, 6, 1, 3, 3, 1, 2, 256, 68, 61, 44,,,, -6, 5, 6, 1, 3, 3, 1, 2, 384, 68, 61, 44,,,, -6, 5, 6, 1, 3, 3, 1, 3, 128, 68, 61, 44,,,, -6, 5, 6, 1, 3, 3, 1, 3, 256, 68, 61, 44,,,, -6, 5, 6, 1, 3, 3, 1, 3, 384, 68, 61, 44,,,, -6, 5, 6, 1, 3, 3, 2, 1, 128, 68, 61, 44,,,, -6, 5, 6, 1, 3, 3, 2, 1, 256, 68, 61, 44,,,, -6, 5, 6, 1, 3, 3, 2, 1, 384, 68, 61, 44,,,, -6, 5, 6, 1, 3, 3, 2, 2, 128, 68, 61, 44,,,, -6, 5, 6, 1, 3, 3, 2, 2, 256, 68, 61, 44,,,, -6, 5, 6, 1, 3, 3, 2, 2, 384, 68, 61, 44,,,, -6, 5, 6, 1, 3, 3, 2, 3, 128, 68, 61, 44,,,, -6, 5, 6, 1, 3, 3, 2, 3, 256, 68, 61, 44,,,, -6, 5, 6, 1, 3, 3, 2, 3, 384, 68, 61, 44,,,, -6, 5, 6, 1, 3, 3, 3, 1, 128, 68, 61, 44,,,, -6, 5, 6, 1, 3, 3, 3, 1, 256, 68, 61, 44,,,, -6, 5, 6, 1, 3, 3, 3, 1, 384, 68, 61, 44,,,, -6, 5, 6, 1, 3, 3, 3, 2, 128, 68, 61, 44,,,, -6, 5, 6, 1, 3, 3, 3, 2, 256, 68, 61, 44,,,, -6, 5, 6, 1, 3, 3, 3, 2, 384, 68, 61, 44,,,, -6, 5, 6, 1, 3, 3, 3, 3, 128, 68, 61, 44,,,, -6, 5, 6, 1, 3, 3, 3, 3, 256, 68, 61, 44,,,, -6, 5, 6, 1, 3, 3, 3, 3, 384, 68, 61, 44,,,, -6, 5, 6, 2, 1, 1, 1, 1, 128, 132, 132, 88,,,, -6, 5, 6, 2, 1, 1, 1, 1, 256, 132, 132, 88,,,, -6, 5, 6, 2, 1, 1, 1, 1, 384, 132, 132, 88,,,, -6, 5, 6, 2, 2, 2, 1, 1, 128, 132, 124, 86,,,, -6, 5, 6, 2, 2, 2, 1, 1, 256, 132, 124, 86,,,, -6, 5, 6, 2, 2, 2, 1, 1, 384, 132, 124, 86,,,, -6, 5, 6, 2, 2, 2, 1, 2, 128, 132, 124, 86,,,, -6, 5, 6, 2, 2, 2, 1, 2, 256, 132, 124, 86,,,, -6, 5, 6, 2, 2, 2, 1, 2, 384, 132, 124, 86,,,, -6, 5, 6, 2, 2, 2, 2, 1, 128, 132, 124, 86,,,, -6, 5, 6, 2, 2, 2, 2, 1, 256, 132, 124, 86,,,, -6, 5, 6, 2, 2, 2, 2, 1, 384, 132, 124, 86,,,, -6, 5, 6, 2, 2, 2, 2, 2, 128, 132, 124, 86,,,, -6, 5, 6, 2, 2, 2, 2, 2, 256, 132, 124, 86,,,, -6, 5, 6, 2, 2, 2, 2, 2, 384, 132, 124, 86,,,, -6, 5, 6, 2, 3, 3, 1, 1, 128, 132, 118, 84,,,, -6, 5, 6, 2, 3, 3, 1, 1, 256, 132, 118, 84,,,, -6, 5, 6, 2, 3, 3, 1, 1, 384, 132, 118, 84,,,, -6, 5, 6, 2, 3, 3, 1, 2, 128, 132, 118, 84,,,, -6, 5, 6, 2, 3, 3, 1, 2, 256, 132, 118, 84,,,, -6, 5, 6, 2, 3, 3, 1, 2, 384, 132, 118, 84,,,, -6, 5, 6, 2, 3, 3, 1, 3, 128, 132, 118, 84,,,, -6, 5, 6, 2, 3, 3, 1, 3, 256, 132, 118, 84,,,, -6, 5, 6, 2, 3, 3, 1, 3, 384, 132, 118, 84,,,, -6, 5, 6, 2, 3, 3, 2, 1, 128, 132, 118, 84,,,, -6, 5, 6, 2, 3, 3, 2, 1, 256, 132, 118, 84,,,, -6, 5, 6, 2, 3, 3, 2, 1, 384, 132, 118, 84,,,, -6, 5, 6, 2, 3, 3, 2, 2, 128, 132, 118, 84,,,, -6, 5, 6, 2, 3, 3, 2, 2, 256, 132, 118, 84,,,, -6, 5, 6, 2, 3, 3, 2, 2, 384, 132, 118, 84,,,, -6, 5, 6, 2, 3, 3, 2, 3, 128, 132, 118, 84,,,, -6, 5, 6, 2, 3, 3, 2, 3, 256, 132, 118, 84,,,, -6, 5, 6, 2, 3, 3, 2, 3, 384, 132, 118, 84,,,, -6, 5, 6, 2, 3, 3, 3, 1, 128, 132, 118, 84,,,, -6, 5, 6, 2, 3, 3, 3, 1, 256, 132, 118, 84,,,, -6, 5, 6, 2, 3, 3, 3, 1, 384, 132, 118, 84,,,, -6, 5, 6, 2, 3, 3, 3, 2, 128, 132, 118, 84,,,, -6, 5, 6, 2, 3, 3, 3, 2, 256, 132, 118, 84,,,, -6, 5, 6, 2, 3, 3, 3, 2, 384, 132, 118, 84,,,, -6, 5, 6, 2, 3, 3, 3, 3, 128, 132, 118, 84,,,, -6, 5, 6, 2, 3, 3, 3, 3, 256, 132, 118, 84,,,, -6, 5, 6, 2, 3, 3, 3, 3, 384, 132, 118, 84,,,, -6, 5, 6, 3, 1, 1, 1, 1, 128, 196, 196, 130,,,, -6, 5, 6, 3, 1, 1, 1, 1, 256, 196, 196, 130,,,, -6, 5, 6, 3, 1, 1, 1, 1, 384, 196, 196, 130,,,, -6, 5, 6, 3, 2, 2, 1, 1, 128, 196, 184, 127,,,, -6, 5, 6, 3, 2, 2, 1, 1, 256, 196, 184, 127,,,, -6, 5, 6, 3, 2, 2, 1, 1, 384, 196, 184, 127,,,, -6, 5, 6, 3, 2, 2, 1, 2, 128, 196, 184, 127,,,, -6, 5, 6, 3, 2, 2, 1, 2, 256, 196, 184, 127,,,, -6, 5, 6, 3, 2, 2, 1, 2, 384, 196, 184, 127,,,, -6, 5, 6, 3, 2, 2, 2, 1, 128, 196, 184, 127,,,, -6, 5, 6, 3, 2, 2, 2, 1, 256, 196, 184, 127,,,, -6, 5, 6, 3, 2, 2, 2, 1, 384, 196, 184, 127,,,, -6, 5, 6, 3, 2, 2, 2, 2, 128, 196, 184, 127,,,, -6, 5, 6, 3, 2, 2, 2, 2, 256, 196, 184, 127,,,, -6, 5, 6, 3, 2, 2, 2, 2, 384, 196, 184, 127,,,, -6, 5, 6, 3, 3, 3, 1, 1, 128, 196, 175, 124,,,, -6, 5, 6, 3, 3, 3, 1, 1, 256, 196, 175, 124,,,, -6, 5, 6, 3, 3, 3, 1, 1, 384, 196, 175, 124,,,, -6, 5, 6, 3, 3, 3, 1, 2, 128, 196, 175, 124,,,, -6, 5, 6, 3, 3, 3, 1, 2, 256, 196, 175, 124,,,, -6, 5, 6, 3, 3, 3, 1, 2, 384, 196, 175, 124,,,, -6, 5, 6, 3, 3, 3, 1, 3, 128, 196, 175, 124,,,, -6, 5, 6, 3, 3, 3, 1, 3, 256, 196, 175, 124,,,, -6, 5, 6, 3, 3, 3, 1, 3, 384, 196, 175, 124,,,, -6, 5, 6, 3, 3, 3, 2, 1, 128, 196, 175, 124,,,, -6, 5, 6, 3, 3, 3, 2, 1, 256, 196, 175, 124,,,, -6, 5, 6, 3, 3, 3, 2, 1, 384, 196, 175, 124,,,, -6, 5, 6, 3, 3, 3, 2, 2, 128, 196, 175, 124,,,, -6, 5, 6, 3, 3, 3, 2, 2, 256, 196, 175, 124,,,, -6, 5, 6, 3, 3, 3, 2, 2, 384, 196, 175, 124,,,, -6, 5, 6, 3, 3, 3, 2, 3, 128, 196, 175, 124,,,, -6, 5, 6, 3, 3, 3, 2, 3, 256, 196, 175, 124,,,, -6, 5, 6, 3, 3, 3, 2, 3, 384, 196, 175, 124,,,, -6, 5, 6, 3, 3, 3, 3, 1, 128, 196, 175, 124,,,, -6, 5, 6, 3, 3, 3, 3, 1, 256, 196, 175, 124,,,, -6, 5, 6, 3, 3, 3, 3, 1, 384, 196, 175, 124,,,, -6, 5, 6, 3, 3, 3, 3, 2, 128, 196, 175, 124,,,, -6, 5, 6, 3, 3, 3, 3, 2, 256, 196, 175, 124,,,, -6, 5, 6, 3, 3, 3, 3, 2, 384, 196, 175, 124,,,, -6, 5, 6, 3, 3, 3, 3, 3, 128, 196, 175, 124,,,, -6, 5, 6, 3, 3, 3, 3, 3, 256, 196, 175, 124,,,, -6, 5, 6, 3, 3, 3, 3, 3, 384, 196, 175, 124,,,, -6, 5, 6, 4, 1, 1, 1, 1, 128, 240, 240, 172,,,, -6, 5, 6, 4, 1, 1, 1, 1, 256, 240, 240, 172,,,, -6, 5, 6, 4, 1, 1, 1, 1, 384, 240, 240, 172,,,, -6, 5, 6, 4, 2, 2, 1, 1, 128, 240, 240, 168,,,, -6, 5, 6, 4, 2, 2, 1, 1, 256, 240, 240, 168,,,, -6, 5, 6, 4, 2, 2, 1, 1, 384, 240, 240, 168,,,, -6, 5, 6, 4, 2, 2, 1, 2, 128, 240, 240, 168,,,, -6, 5, 6, 4, 2, 2, 1, 2, 256, 240, 240, 168,,,, -6, 5, 6, 4, 2, 2, 1, 2, 384, 240, 240, 168,,,, -6, 5, 6, 4, 2, 2, 2, 1, 128, 240, 240, 168,,,, -6, 5, 6, 4, 2, 2, 2, 1, 256, 240, 240, 168,,,, -6, 5, 6, 4, 2, 2, 2, 1, 384, 240, 240, 168,,,, -6, 5, 6, 4, 2, 2, 2, 2, 128, 240, 240, 168,,,, -6, 5, 6, 4, 2, 2, 2, 2, 256, 240, 240, 168,,,, -6, 5, 6, 4, 2, 2, 2, 2, 384, 240, 240, 168,,,, -6, 5, 6, 4, 3, 3, 1, 1, 128, 240, 232, 164,,,, -6, 5, 6, 4, 3, 3, 1, 1, 256, 240, 232, 164,,,, -6, 5, 6, 4, 3, 3, 1, 1, 384, 240, 232, 164,,,, -6, 5, 6, 4, 3, 3, 1, 2, 128, 240, 232, 164,,,, -6, 5, 6, 4, 3, 3, 1, 2, 256, 240, 232, 164,,,, -6, 5, 6, 4, 3, 3, 1, 2, 384, 240, 232, 164,,,, -6, 5, 6, 4, 3, 3, 1, 3, 128, 240, 232, 164,,,, -6, 5, 6, 4, 3, 3, 1, 3, 256, 240, 232, 164,,,, -6, 5, 6, 4, 3, 3, 1, 3, 384, 240, 232, 164,,,, -6, 5, 6, 4, 3, 3, 2, 1, 128, 240, 232, 164,,,, -6, 5, 6, 4, 3, 3, 2, 1, 256, 240, 232, 164,,,, -6, 5, 6, 4, 3, 3, 2, 1, 384, 240, 232, 164,,,, -6, 5, 6, 4, 3, 3, 2, 2, 128, 240, 232, 164,,,, -6, 5, 6, 4, 3, 3, 2, 2, 256, 240, 232, 164,,,, -6, 5, 6, 4, 3, 3, 2, 2, 384, 240, 232, 164,,,, -6, 5, 6, 4, 3, 3, 2, 3, 128, 240, 232, 164,,,, -6, 5, 6, 4, 3, 3, 2, 3, 256, 240, 232, 164,,,, -6, 5, 6, 4, 3, 3, 2, 3, 384, 240, 232, 164,,,, -6, 5, 6, 4, 3, 3, 3, 1, 128, 240, 232, 164,,,, -6, 5, 6, 4, 3, 3, 3, 1, 256, 240, 232, 164,,,, -6, 5, 6, 4, 3, 3, 3, 1, 384, 240, 232, 164,,,, -6, 5, 6, 4, 3, 3, 3, 2, 128, 240, 232, 164,,,, -6, 5, 6, 4, 3, 3, 3, 2, 256, 240, 232, 164,,,, -6, 5, 6, 4, 3, 3, 3, 2, 384, 240, 232, 164,,,, -6, 5, 6, 4, 3, 3, 3, 3, 128, 240, 232, 164,,,, -6, 5, 6, 4, 3, 3, 3, 3, 256, 240, 232, 164,,,, -6, 5, 6, 4, 3, 3, 3, 3, 384, 240, 232, 164,,,, -6, 5, 6, 5, 1, 1, 1, 1, 128, 240, 240, 214,,,, -6, 5, 6, 5, 1, 1, 1, 1, 256, 240, 240, 214,,,, -6, 5, 6, 5, 1, 1, 1, 1, 384, 240, 240, 214,,,, -6, 5, 6, 5, 2, 2, 1, 1, 128, 240, 240, 209,,,, -6, 5, 6, 5, 2, 2, 1, 1, 256, 240, 240, 209,,,, -6, 5, 6, 5, 2, 2, 1, 1, 384, 240, 240, 209,,,, -6, 5, 6, 5, 2, 2, 1, 2, 128, 240, 240, 209,,,, -6, 5, 6, 5, 2, 2, 1, 2, 256, 240, 240, 209,,,, -6, 5, 6, 5, 2, 2, 1, 2, 384, 240, 240, 209,,,, -6, 5, 6, 5, 2, 2, 2, 1, 128, 240, 240, 209,,,, -6, 5, 6, 5, 2, 2, 2, 1, 256, 240, 240, 209,,,, -6, 5, 6, 5, 2, 2, 2, 1, 384, 240, 240, 209,,,, -6, 5, 6, 5, 2, 2, 2, 2, 128, 240, 240, 209,,,, -6, 5, 6, 5, 2, 2, 2, 2, 256, 240, 240, 209,,,, -6, 5, 6, 5, 2, 2, 2, 2, 384, 240, 240, 209,,,, -6, 5, 6, 5, 3, 3, 1, 1, 128, 240, 240, 204,,,, -6, 5, 6, 5, 3, 3, 1, 1, 256, 240, 240, 204,,,, -6, 5, 6, 5, 3, 3, 1, 1, 384, 240, 240, 204,,,, -6, 5, 6, 5, 3, 3, 1, 2, 128, 240, 240, 204,,,, -6, 5, 6, 5, 3, 3, 1, 2, 256, 240, 240, 204,,,, -6, 5, 6, 5, 3, 3, 1, 2, 384, 240, 240, 204,,,, -6, 5, 6, 5, 3, 3, 1, 3, 128, 240, 240, 204,,,, -6, 5, 6, 5, 3, 3, 1, 3, 256, 240, 240, 204,,,, -6, 5, 6, 5, 3, 3, 1, 3, 384, 240, 240, 204,,,, -6, 5, 6, 5, 3, 3, 2, 1, 128, 240, 240, 204,,,, -6, 5, 6, 5, 3, 3, 2, 1, 256, 240, 240, 204,,,, -6, 5, 6, 5, 3, 3, 2, 1, 384, 240, 240, 204,,,, -6, 5, 6, 5, 3, 3, 2, 2, 128, 240, 240, 204,,,, -6, 5, 6, 5, 3, 3, 2, 2, 256, 240, 240, 204,,,, -6, 5, 6, 5, 3, 3, 2, 2, 384, 240, 240, 204,,,, -6, 5, 6, 5, 3, 3, 2, 3, 128, 240, 240, 204,,,, -6, 5, 6, 5, 3, 3, 2, 3, 256, 240, 240, 204,,,, -6, 5, 6, 5, 3, 3, 2, 3, 384, 240, 240, 204,,,, -6, 5, 6, 5, 3, 3, 3, 1, 128, 240, 240, 204,,,, -6, 5, 6, 5, 3, 3, 3, 1, 256, 240, 240, 204,,,, -6, 5, 6, 5, 3, 3, 3, 1, 384, 240, 240, 204,,,, -6, 5, 6, 5, 3, 3, 3, 2, 128, 240, 240, 204,,,, -6, 5, 6, 5, 3, 3, 3, 2, 256, 240, 240, 204,,,, -6, 5, 6, 5, 3, 3, 3, 2, 384, 240, 240, 204,,,, -6, 5, 6, 5, 3, 3, 3, 3, 128, 240, 240, 204,,,, -6, 5, 6, 5, 3, 3, 3, 3, 256, 240, 240, 204,,,, -6, 5, 6, 5, 3, 3, 3, 3, 384, 240, 240, 204,,,, -6, 6, 1, 1, 1, 1, 1, 1, 128, 69, 47, 26,,,, -6, 6, 1, 1, 1, 1, 1, 1, 256, 69, 47, 26,,,, -6, 6, 1, 1, 1, 1, 1, 1, 384, 69, 47, 26,,,, -6, 6, 1, 1, 2, 2, 1, 1, 128, 69, 47, 26,,,, -6, 6, 1, 1, 2, 2, 1, 1, 256, 69, 47, 26,,,, -6, 6, 1, 1, 2, 2, 1, 1, 384, 69, 47, 26,,,, -6, 6, 1, 1, 2, 2, 1, 2, 128, 69, 47, 26,,,, -6, 6, 1, 1, 2, 2, 1, 2, 256, 69, 47, 26,,,, -6, 6, 1, 1, 2, 2, 1, 2, 384, 69, 47, 26,,,, -6, 6, 1, 1, 2, 2, 2, 1, 128, 69, 47, 26,,,, -6, 6, 1, 1, 2, 2, 2, 1, 256, 69, 47, 26,,,, -6, 6, 1, 1, 2, 2, 2, 1, 384, 69, 47, 26,,,, -6, 6, 1, 1, 2, 2, 2, 2, 128, 69, 47, 26,,,, -6, 6, 1, 1, 2, 2, 2, 2, 256, 69, 47, 26,,,, -6, 6, 1, 1, 2, 2, 2, 2, 384, 69, 47, 26,,,, -6, 6, 1, 1, 3, 3, 1, 1, 128, 69, 47, 26,,,, -6, 6, 1, 1, 3, 3, 1, 1, 256, 69, 47, 26,,,, -6, 6, 1, 1, 3, 3, 1, 1, 384, 69, 47, 26,,,, -6, 6, 1, 1, 3, 3, 1, 2, 128, 69, 47, 26,,,, -6, 6, 1, 1, 3, 3, 1, 2, 256, 69, 47, 26,,,, -6, 6, 1, 1, 3, 3, 1, 2, 384, 69, 47, 26,,,, -6, 6, 1, 1, 3, 3, 1, 3, 128, 69, 47, 26,,,, -6, 6, 1, 1, 3, 3, 1, 3, 256, 69, 47, 26,,,, -6, 6, 1, 1, 3, 3, 1, 3, 384, 69, 47, 26,,,, -6, 6, 1, 1, 3, 3, 2, 1, 128, 69, 47, 26,,,, -6, 6, 1, 1, 3, 3, 2, 1, 256, 69, 47, 26,,,, -6, 6, 1, 1, 3, 3, 2, 1, 384, 69, 47, 26,,,, -6, 6, 1, 1, 3, 3, 2, 2, 128, 69, 47, 26,,,, -6, 6, 1, 1, 3, 3, 2, 2, 256, 69, 47, 26,,,, -6, 6, 1, 1, 3, 3, 2, 2, 384, 69, 47, 26,,,, -6, 6, 1, 1, 3, 3, 2, 3, 128, 69, 47, 26,,,, -6, 6, 1, 1, 3, 3, 2, 3, 256, 69, 47, 26,,,, -6, 6, 1, 1, 3, 3, 2, 3, 384, 69, 47, 26,,,, -6, 6, 1, 1, 3, 3, 3, 1, 128, 69, 47, 26,,,, -6, 6, 1, 1, 3, 3, 3, 1, 256, 69, 47, 26,,,, -6, 6, 1, 1, 3, 3, 3, 1, 384, 69, 47, 26,,,, -6, 6, 1, 1, 3, 3, 3, 2, 128, 69, 47, 26,,,, -6, 6, 1, 1, 3, 3, 3, 2, 256, 69, 47, 26,,,, -6, 6, 1, 1, 3, 3, 3, 2, 384, 69, 47, 26,,,, -6, 6, 1, 1, 3, 3, 3, 3, 128, 69, 47, 26,,,, -6, 6, 1, 1, 3, 3, 3, 3, 256, 69, 47, 26,,,, -6, 6, 1, 1, 3, 3, 3, 3, 384, 69, 47, 26,,,, -6, 6, 1, 2, 1, 1, 1, 1, 128, 133, 89, 47,,,, -6, 6, 1, 2, 1, 1, 1, 1, 256, 133, 89, 47,,,, -6, 6, 1, 2, 1, 1, 1, 1, 384, 133, 89, 47,,,, -6, 6, 1, 2, 2, 2, 1, 1, 128, 133, 89, 47,,,, -6, 6, 1, 2, 2, 2, 1, 1, 256, 133, 89, 47,,,, -6, 6, 1, 2, 2, 2, 1, 1, 384, 133, 89, 47,,,, -6, 6, 1, 2, 2, 2, 1, 2, 128, 133, 89, 47,,,, -6, 6, 1, 2, 2, 2, 1, 2, 256, 133, 89, 47,,,, -6, 6, 1, 2, 2, 2, 1, 2, 384, 133, 89, 47,,,, -6, 6, 1, 2, 2, 2, 2, 1, 128, 133, 89, 47,,,, -6, 6, 1, 2, 2, 2, 2, 1, 256, 133, 89, 47,,,, -6, 6, 1, 2, 2, 2, 2, 1, 384, 133, 89, 47,,,, -6, 6, 1, 2, 2, 2, 2, 2, 128, 133, 89, 47,,,, -6, 6, 1, 2, 2, 2, 2, 2, 256, 133, 89, 47,,,, -6, 6, 1, 2, 2, 2, 2, 2, 384, 133, 89, 47,,,, -6, 6, 1, 2, 3, 3, 1, 1, 128, 133, 89, 47,,,, -6, 6, 1, 2, 3, 3, 1, 1, 256, 133, 89, 47,,,, -6, 6, 1, 2, 3, 3, 1, 1, 384, 133, 89, 47,,,, -6, 6, 1, 2, 3, 3, 1, 2, 128, 133, 89, 47,,,, -6, 6, 1, 2, 3, 3, 1, 2, 256, 133, 89, 47,,,, -6, 6, 1, 2, 3, 3, 1, 2, 384, 133, 89, 47,,,, -6, 6, 1, 2, 3, 3, 1, 3, 128, 133, 89, 47,,,, -6, 6, 1, 2, 3, 3, 1, 3, 256, 133, 89, 47,,,, -6, 6, 1, 2, 3, 3, 1, 3, 384, 133, 89, 47,,,, -6, 6, 1, 2, 3, 3, 2, 1, 128, 133, 89, 47,,,, -6, 6, 1, 2, 3, 3, 2, 1, 256, 133, 89, 47,,,, -6, 6, 1, 2, 3, 3, 2, 1, 384, 133, 89, 47,,,, -6, 6, 1, 2, 3, 3, 2, 2, 128, 133, 89, 47,,,, -6, 6, 1, 2, 3, 3, 2, 2, 256, 133, 89, 47,,,, -6, 6, 1, 2, 3, 3, 2, 2, 384, 133, 89, 47,,,, -6, 6, 1, 2, 3, 3, 2, 3, 128, 133, 89, 47,,,, -6, 6, 1, 2, 3, 3, 2, 3, 256, 133, 89, 47,,,, -6, 6, 1, 2, 3, 3, 2, 3, 384, 133, 89, 47,,,, -6, 6, 1, 2, 3, 3, 3, 1, 128, 133, 89, 47,,,, -6, 6, 1, 2, 3, 3, 3, 1, 256, 133, 89, 47,,,, -6, 6, 1, 2, 3, 3, 3, 1, 384, 133, 89, 47,,,, -6, 6, 1, 2, 3, 3, 3, 2, 128, 133, 89, 47,,,, -6, 6, 1, 2, 3, 3, 3, 2, 256, 133, 89, 47,,,, -6, 6, 1, 2, 3, 3, 3, 2, 384, 133, 89, 47,,,, -6, 6, 1, 2, 3, 3, 3, 3, 128, 133, 89, 47,,,, -6, 6, 1, 2, 3, 3, 3, 3, 256, 133, 89, 47,,,, -6, 6, 1, 2, 3, 3, 3, 3, 384, 133, 89, 47,,,, -6, 6, 1, 3, 1, 1, 1, 1, 128, 197, 131, 68,,,, -6, 6, 1, 3, 1, 1, 1, 1, 256, 197, 131, 68,,,, -6, 6, 1, 3, 1, 1, 1, 1, 384, 197, 131, 68,,,, -6, 6, 1, 3, 2, 2, 1, 1, 128, 197, 131, 68,,,, -6, 6, 1, 3, 2, 2, 1, 1, 256, 197, 131, 68,,,, -6, 6, 1, 3, 2, 2, 1, 1, 384, 197, 131, 68,,,, -6, 6, 1, 3, 2, 2, 1, 2, 128, 197, 131, 68,,,, -6, 6, 1, 3, 2, 2, 1, 2, 256, 197, 131, 68,,,, -6, 6, 1, 3, 2, 2, 1, 2, 384, 197, 131, 68,,,, -6, 6, 1, 3, 2, 2, 2, 1, 128, 197, 131, 68,,,, -6, 6, 1, 3, 2, 2, 2, 1, 256, 197, 131, 68,,,, -6, 6, 1, 3, 2, 2, 2, 1, 384, 197, 131, 68,,,, -6, 6, 1, 3, 2, 2, 2, 2, 128, 197, 131, 68,,,, -6, 6, 1, 3, 2, 2, 2, 2, 256, 197, 131, 68,,,, -6, 6, 1, 3, 2, 2, 2, 2, 384, 197, 131, 68,,,, -6, 6, 1, 3, 3, 3, 1, 1, 128, 197, 131, 68,,,, -6, 6, 1, 3, 3, 3, 1, 1, 256, 197, 131, 68,,,, -6, 6, 1, 3, 3, 3, 1, 1, 384, 197, 131, 68,,,, -6, 6, 1, 3, 3, 3, 1, 2, 128, 197, 131, 68,,,, -6, 6, 1, 3, 3, 3, 1, 2, 256, 197, 131, 68,,,, -6, 6, 1, 3, 3, 3, 1, 2, 384, 197, 131, 68,,,, -6, 6, 1, 3, 3, 3, 1, 3, 128, 197, 131, 68,,,, -6, 6, 1, 3, 3, 3, 1, 3, 256, 197, 131, 68,,,, -6, 6, 1, 3, 3, 3, 1, 3, 384, 197, 131, 68,,,, -6, 6, 1, 3, 3, 3, 2, 1, 128, 197, 131, 68,,,, -6, 6, 1, 3, 3, 3, 2, 1, 256, 197, 131, 68,,,, -6, 6, 1, 3, 3, 3, 2, 1, 384, 197, 131, 68,,,, -6, 6, 1, 3, 3, 3, 2, 2, 128, 197, 131, 68,,,, -6, 6, 1, 3, 3, 3, 2, 2, 256, 197, 131, 68,,,, -6, 6, 1, 3, 3, 3, 2, 2, 384, 197, 131, 68,,,, -6, 6, 1, 3, 3, 3, 2, 3, 128, 197, 131, 68,,,, -6, 6, 1, 3, 3, 3, 2, 3, 256, 197, 131, 68,,,, -6, 6, 1, 3, 3, 3, 2, 3, 384, 197, 131, 68,,,, -6, 6, 1, 3, 3, 3, 3, 1, 128, 197, 131, 68,,,, -6, 6, 1, 3, 3, 3, 3, 1, 256, 197, 131, 68,,,, -6, 6, 1, 3, 3, 3, 3, 1, 384, 197, 131, 68,,,, -6, 6, 1, 3, 3, 3, 3, 2, 128, 197, 131, 68,,,, -6, 6, 1, 3, 3, 3, 3, 2, 256, 197, 131, 68,,,, -6, 6, 1, 3, 3, 3, 3, 2, 384, 197, 131, 68,,,, -6, 6, 1, 3, 3, 3, 3, 3, 128, 197, 131, 68,,,, -6, 6, 1, 3, 3, 3, 3, 3, 256, 197, 131, 68,,,, -6, 6, 1, 3, 3, 3, 3, 3, 384, 197, 131, 68,,,, -6, 6, 1, 4, 1, 1, 1, 1, 128, 240, 173, 89,,,, -6, 6, 1, 4, 1, 1, 1, 1, 256, 240, 173, 89,,,, -6, 6, 1, 4, 1, 1, 1, 1, 384, 240, 173, 89,,,, -6, 6, 1, 4, 2, 2, 1, 1, 128, 240, 173, 89,,,, -6, 6, 1, 4, 2, 2, 1, 1, 256, 240, 173, 89,,,, -6, 6, 1, 4, 2, 2, 1, 1, 384, 240, 173, 89,,,, -6, 6, 1, 4, 2, 2, 1, 2, 128, 240, 173, 89,,,, -6, 6, 1, 4, 2, 2, 1, 2, 256, 240, 173, 89,,,, -6, 6, 1, 4, 2, 2, 1, 2, 384, 240, 173, 89,,,, -6, 6, 1, 4, 2, 2, 2, 1, 128, 240, 173, 89,,,, -6, 6, 1, 4, 2, 2, 2, 1, 256, 240, 173, 89,,,, -6, 6, 1, 4, 2, 2, 2, 1, 384, 240, 173, 89,,,, -6, 6, 1, 4, 2, 2, 2, 2, 128, 240, 173, 89,,,, -6, 6, 1, 4, 2, 2, 2, 2, 256, 240, 173, 89,,,, -6, 6, 1, 4, 2, 2, 2, 2, 384, 240, 173, 89,,,, -6, 6, 1, 4, 3, 3, 1, 1, 128, 240, 173, 89,,,, -6, 6, 1, 4, 3, 3, 1, 1, 256, 240, 173, 89,,,, -6, 6, 1, 4, 3, 3, 1, 1, 384, 240, 173, 89,,,, -6, 6, 1, 4, 3, 3, 1, 2, 128, 240, 173, 89,,,, -6, 6, 1, 4, 3, 3, 1, 2, 256, 240, 173, 89,,,, -6, 6, 1, 4, 3, 3, 1, 2, 384, 240, 173, 89,,,, -6, 6, 1, 4, 3, 3, 1, 3, 128, 240, 173, 89,,,, -6, 6, 1, 4, 3, 3, 1, 3, 256, 240, 173, 89,,,, -6, 6, 1, 4, 3, 3, 1, 3, 384, 240, 173, 89,,,, -6, 6, 1, 4, 3, 3, 2, 1, 128, 240, 173, 89,,,, -6, 6, 1, 4, 3, 3, 2, 1, 256, 240, 173, 89,,,, -6, 6, 1, 4, 3, 3, 2, 1, 384, 240, 173, 89,,,, -6, 6, 1, 4, 3, 3, 2, 2, 128, 240, 173, 89,,,, -6, 6, 1, 4, 3, 3, 2, 2, 256, 240, 173, 89,,,, -6, 6, 1, 4, 3, 3, 2, 2, 384, 240, 173, 89,,,, -6, 6, 1, 4, 3, 3, 2, 3, 128, 240, 173, 89,,,, -6, 6, 1, 4, 3, 3, 2, 3, 256, 240, 173, 89,,,, -6, 6, 1, 4, 3, 3, 2, 3, 384, 240, 173, 89,,,, -6, 6, 1, 4, 3, 3, 3, 1, 128, 240, 173, 89,,,, -6, 6, 1, 4, 3, 3, 3, 1, 256, 240, 173, 89,,,, -6, 6, 1, 4, 3, 3, 3, 1, 384, 240, 173, 89,,,, -6, 6, 1, 4, 3, 3, 3, 2, 128, 240, 173, 89,,,, -6, 6, 1, 4, 3, 3, 3, 2, 256, 240, 173, 89,,,, -6, 6, 1, 4, 3, 3, 3, 2, 384, 240, 173, 89,,,, -6, 6, 1, 4, 3, 3, 3, 3, 128, 240, 173, 89,,,, -6, 6, 1, 4, 3, 3, 3, 3, 256, 240, 173, 89,,,, -6, 6, 1, 4, 3, 3, 3, 3, 384, 240, 173, 89,,,, -6, 6, 1, 5, 1, 1, 1, 1, 128, 240, 215, 110,,,, -6, 6, 1, 5, 1, 1, 1, 1, 256, 240, 215, 110,,,, -6, 6, 1, 5, 1, 1, 1, 1, 384, 240, 215, 110,,,, -6, 6, 1, 5, 2, 2, 1, 1, 128, 240, 215, 110,,,, -6, 6, 1, 5, 2, 2, 1, 1, 256, 240, 215, 110,,,, -6, 6, 1, 5, 2, 2, 1, 1, 384, 240, 215, 110,,,, -6, 6, 1, 5, 2, 2, 1, 2, 128, 240, 215, 110,,,, -6, 6, 1, 5, 2, 2, 1, 2, 256, 240, 215, 110,,,, -6, 6, 1, 5, 2, 2, 1, 2, 384, 240, 215, 110,,,, -6, 6, 1, 5, 2, 2, 2, 1, 128, 240, 215, 110,,,, -6, 6, 1, 5, 2, 2, 2, 1, 256, 240, 215, 110,,,, -6, 6, 1, 5, 2, 2, 2, 1, 384, 240, 215, 110,,,, -6, 6, 1, 5, 2, 2, 2, 2, 128, 240, 215, 110,,,, -6, 6, 1, 5, 2, 2, 2, 2, 256, 240, 215, 110,,,, -6, 6, 1, 5, 2, 2, 2, 2, 384, 240, 215, 110,,,, -6, 6, 1, 5, 3, 3, 1, 1, 128, 240, 215, 110,,,, -6, 6, 1, 5, 3, 3, 1, 1, 256, 240, 215, 110,,,, -6, 6, 1, 5, 3, 3, 1, 1, 384, 240, 215, 110,,,, -6, 6, 1, 5, 3, 3, 1, 2, 128, 240, 215, 110,,,, -6, 6, 1, 5, 3, 3, 1, 2, 256, 240, 215, 110,,,, -6, 6, 1, 5, 3, 3, 1, 2, 384, 240, 215, 110,,,, -6, 6, 1, 5, 3, 3, 1, 3, 128, 240, 215, 110,,,, -6, 6, 1, 5, 3, 3, 1, 3, 256, 240, 215, 110,,,, -6, 6, 1, 5, 3, 3, 1, 3, 384, 240, 215, 110,,,, -6, 6, 1, 5, 3, 3, 2, 1, 128, 240, 215, 110,,,, -6, 6, 1, 5, 3, 3, 2, 1, 256, 240, 215, 110,,,, -6, 6, 1, 5, 3, 3, 2, 1, 384, 240, 215, 110,,,, -6, 6, 1, 5, 3, 3, 2, 2, 128, 240, 215, 110,,,, -6, 6, 1, 5, 3, 3, 2, 2, 256, 240, 215, 110,,,, -6, 6, 1, 5, 3, 3, 2, 2, 384, 240, 215, 110,,,, -6, 6, 1, 5, 3, 3, 2, 3, 128, 240, 215, 110,,,, -6, 6, 1, 5, 3, 3, 2, 3, 256, 240, 215, 110,,,, -6, 6, 1, 5, 3, 3, 2, 3, 384, 240, 215, 110,,,, -6, 6, 1, 5, 3, 3, 3, 1, 128, 240, 215, 110,,,, -6, 6, 1, 5, 3, 3, 3, 1, 256, 240, 215, 110,,,, -6, 6, 1, 5, 3, 3, 3, 1, 384, 240, 215, 110,,,, -6, 6, 1, 5, 3, 3, 3, 2, 128, 240, 215, 110,,,, -6, 6, 1, 5, 3, 3, 3, 2, 256, 240, 215, 110,,,, -6, 6, 1, 5, 3, 3, 3, 2, 384, 240, 215, 110,,,, -6, 6, 1, 5, 3, 3, 3, 3, 128, 240, 215, 110,,,, -6, 6, 1, 5, 3, 3, 3, 3, 256, 240, 215, 110,,,, -6, 6, 1, 5, 3, 3, 3, 3, 384, 240, 215, 110,,,, -6, 6, 1, 6, 1, 1, 1, 1, 128, 240, 240, 131,,,, -6, 6, 1, 6, 1, 1, 1, 1, 256, 240, 240, 131,,,, -6, 6, 1, 6, 1, 1, 1, 1, 384, 240, 240, 131,,,, -6, 6, 1, 6, 2, 2, 1, 1, 128, 240, 240, 131,,,, -6, 6, 1, 6, 2, 2, 1, 1, 256, 240, 240, 131,,,, -6, 6, 1, 6, 2, 2, 1, 1, 384, 240, 240, 131,,,, -6, 6, 1, 6, 2, 2, 1, 2, 128, 240, 240, 131,,,, -6, 6, 1, 6, 2, 2, 1, 2, 256, 240, 240, 131,,,, -6, 6, 1, 6, 2, 2, 1, 2, 384, 240, 240, 131,,,, -6, 6, 1, 6, 2, 2, 2, 1, 128, 240, 240, 131,,,, -6, 6, 1, 6, 2, 2, 2, 1, 256, 240, 240, 131,,,, -6, 6, 1, 6, 2, 2, 2, 1, 384, 240, 240, 131,,,, -6, 6, 1, 6, 2, 2, 2, 2, 128, 240, 240, 131,,,, -6, 6, 1, 6, 2, 2, 2, 2, 256, 240, 240, 131,,,, -6, 6, 1, 6, 2, 2, 2, 2, 384, 240, 240, 131,,,, -6, 6, 1, 6, 3, 3, 1, 1, 128, 240, 240, 131,,,, -6, 6, 1, 6, 3, 3, 1, 1, 256, 240, 240, 131,,,, -6, 6, 1, 6, 3, 3, 1, 1, 384, 240, 240, 131,,,, -6, 6, 1, 6, 3, 3, 1, 2, 128, 240, 240, 131,,,, -6, 6, 1, 6, 3, 3, 1, 2, 256, 240, 240, 131,,,, -6, 6, 1, 6, 3, 3, 1, 2, 384, 240, 240, 131,,,, -6, 6, 1, 6, 3, 3, 1, 3, 128, 240, 240, 131,,,, -6, 6, 1, 6, 3, 3, 1, 3, 256, 240, 240, 131,,,, -6, 6, 1, 6, 3, 3, 1, 3, 384, 240, 240, 131,,,, -6, 6, 1, 6, 3, 3, 2, 1, 128, 240, 240, 131,,,, -6, 6, 1, 6, 3, 3, 2, 1, 256, 240, 240, 131,,,, -6, 6, 1, 6, 3, 3, 2, 1, 384, 240, 240, 131,,,, -6, 6, 1, 6, 3, 3, 2, 2, 128, 240, 240, 131,,,, -6, 6, 1, 6, 3, 3, 2, 2, 256, 240, 240, 131,,,, -6, 6, 1, 6, 3, 3, 2, 2, 384, 240, 240, 131,,,, -6, 6, 1, 6, 3, 3, 2, 3, 128, 240, 240, 131,,,, -6, 6, 1, 6, 3, 3, 2, 3, 256, 240, 240, 131,,,, -6, 6, 1, 6, 3, 3, 2, 3, 384, 240, 240, 131,,,, -6, 6, 1, 6, 3, 3, 3, 1, 128, 240, 240, 131,,,, -6, 6, 1, 6, 3, 3, 3, 1, 256, 240, 240, 131,,,, -6, 6, 1, 6, 3, 3, 3, 1, 384, 240, 240, 131,,,, -6, 6, 1, 6, 3, 3, 3, 2, 128, 240, 240, 131,,,, -6, 6, 1, 6, 3, 3, 3, 2, 256, 240, 240, 131,,,, -6, 6, 1, 6, 3, 3, 3, 2, 384, 240, 240, 131,,,, -6, 6, 1, 6, 3, 3, 3, 3, 128, 240, 240, 131,,,, -6, 6, 1, 6, 3, 3, 3, 3, 256, 240, 240, 131,,,, -6, 6, 1, 6, 3, 3, 3, 3, 384, 240, 240, 131,,,, -6, 6, 2, 1, 1, 1, 1, 1, 128, 69, 47, 26,,,, -6, 6, 2, 1, 1, 1, 1, 1, 256, 69, 47, 26,,,, -6, 6, 2, 1, 1, 1, 1, 1, 384, 69, 47, 26,,,, -6, 6, 2, 1, 2, 2, 1, 1, 128, 69, 47, 26,,,, -6, 6, 2, 1, 2, 2, 1, 1, 256, 69, 47, 26,,,, -6, 6, 2, 1, 2, 2, 1, 1, 384, 69, 47, 26,,,, -6, 6, 2, 1, 2, 2, 1, 2, 128, 69, 47, 26,,,, -6, 6, 2, 1, 2, 2, 1, 2, 256, 69, 47, 26,,,, -6, 6, 2, 1, 2, 2, 1, 2, 384, 69, 47, 26,,,, -6, 6, 2, 1, 2, 2, 2, 1, 128, 69, 47, 26,,,, -6, 6, 2, 1, 2, 2, 2, 1, 256, 69, 47, 26,,,, -6, 6, 2, 1, 2, 2, 2, 1, 384, 69, 47, 26,,,, -6, 6, 2, 1, 2, 2, 2, 2, 128, 69, 47, 26,,,, -6, 6, 2, 1, 2, 2, 2, 2, 256, 69, 47, 26,,,, -6, 6, 2, 1, 2, 2, 2, 2, 384, 69, 47, 26,,,, -6, 6, 2, 1, 3, 3, 1, 1, 128, 69, 47, 26,,,, -6, 6, 2, 1, 3, 3, 1, 1, 256, 69, 47, 26,,,, -6, 6, 2, 1, 3, 3, 1, 1, 384, 69, 47, 26,,,, -6, 6, 2, 1, 3, 3, 1, 2, 128, 69, 47, 26,,,, -6, 6, 2, 1, 3, 3, 1, 2, 256, 69, 47, 26,,,, -6, 6, 2, 1, 3, 3, 1, 2, 384, 69, 47, 26,,,, -6, 6, 2, 1, 3, 3, 1, 3, 128, 69, 47, 26,,,, -6, 6, 2, 1, 3, 3, 1, 3, 256, 69, 47, 26,,,, -6, 6, 2, 1, 3, 3, 1, 3, 384, 69, 47, 26,,,, -6, 6, 2, 1, 3, 3, 2, 1, 128, 69, 47, 26,,,, -6, 6, 2, 1, 3, 3, 2, 1, 256, 69, 47, 26,,,, -6, 6, 2, 1, 3, 3, 2, 1, 384, 69, 47, 26,,,, -6, 6, 2, 1, 3, 3, 2, 2, 128, 69, 47, 26,,,, -6, 6, 2, 1, 3, 3, 2, 2, 256, 69, 47, 26,,,, -6, 6, 2, 1, 3, 3, 2, 2, 384, 69, 47, 26,,,, -6, 6, 2, 1, 3, 3, 2, 3, 128, 69, 47, 26,,,, -6, 6, 2, 1, 3, 3, 2, 3, 256, 69, 47, 26,,,, -6, 6, 2, 1, 3, 3, 2, 3, 384, 69, 47, 26,,,, -6, 6, 2, 1, 3, 3, 3, 1, 128, 69, 47, 26,,,, -6, 6, 2, 1, 3, 3, 3, 1, 256, 69, 47, 26,,,, -6, 6, 2, 1, 3, 3, 3, 1, 384, 69, 47, 26,,,, -6, 6, 2, 1, 3, 3, 3, 2, 128, 69, 47, 26,,,, -6, 6, 2, 1, 3, 3, 3, 2, 256, 69, 47, 26,,,, -6, 6, 2, 1, 3, 3, 3, 2, 384, 69, 47, 26,,,, -6, 6, 2, 1, 3, 3, 3, 3, 128, 69, 47, 26,,,, -6, 6, 2, 1, 3, 3, 3, 3, 256, 69, 47, 26,,,, -6, 6, 2, 1, 3, 3, 3, 3, 384, 69, 47, 26,,,, -6, 6, 2, 2, 1, 1, 1, 1, 128, 133, 89, 47,,,, -6, 6, 2, 2, 1, 1, 1, 1, 256, 133, 89, 47,,,, -6, 6, 2, 2, 1, 1, 1, 1, 384, 133, 89, 47,,,, -6, 6, 2, 2, 2, 2, 1, 1, 128, 133, 89, 47,,,, -6, 6, 2, 2, 2, 2, 1, 1, 256, 133, 89, 47,,,, -6, 6, 2, 2, 2, 2, 1, 1, 384, 133, 89, 47,,,, -6, 6, 2, 2, 2, 2, 1, 2, 128, 133, 89, 47,,,, -6, 6, 2, 2, 2, 2, 1, 2, 256, 133, 89, 47,,,, -6, 6, 2, 2, 2, 2, 1, 2, 384, 133, 89, 47,,,, -6, 6, 2, 2, 2, 2, 2, 1, 128, 133, 89, 47,,,, -6, 6, 2, 2, 2, 2, 2, 1, 256, 133, 89, 47,,,, -6, 6, 2, 2, 2, 2, 2, 1, 384, 133, 89, 47,,,, -6, 6, 2, 2, 2, 2, 2, 2, 128, 133, 89, 47,,,, -6, 6, 2, 2, 2, 2, 2, 2, 256, 133, 89, 47,,,, -6, 6, 2, 2, 2, 2, 2, 2, 384, 133, 89, 47,,,, -6, 6, 2, 2, 3, 3, 1, 1, 128, 133, 89, 47,,,, -6, 6, 2, 2, 3, 3, 1, 1, 256, 133, 89, 47,,,, -6, 6, 2, 2, 3, 3, 1, 1, 384, 133, 89, 47,,,, -6, 6, 2, 2, 3, 3, 1, 2, 128, 133, 89, 47,,,, -6, 6, 2, 2, 3, 3, 1, 2, 256, 133, 89, 47,,,, -6, 6, 2, 2, 3, 3, 1, 2, 384, 133, 89, 47,,,, -6, 6, 2, 2, 3, 3, 1, 3, 128, 133, 89, 47,,,, -6, 6, 2, 2, 3, 3, 1, 3, 256, 133, 89, 47,,,, -6, 6, 2, 2, 3, 3, 1, 3, 384, 133, 89, 47,,,, -6, 6, 2, 2, 3, 3, 2, 1, 128, 133, 89, 47,,,, -6, 6, 2, 2, 3, 3, 2, 1, 256, 133, 89, 47,,,, -6, 6, 2, 2, 3, 3, 2, 1, 384, 133, 89, 47,,,, -6, 6, 2, 2, 3, 3, 2, 2, 128, 133, 89, 47,,,, -6, 6, 2, 2, 3, 3, 2, 2, 256, 133, 89, 47,,,, -6, 6, 2, 2, 3, 3, 2, 2, 384, 133, 89, 47,,,, -6, 6, 2, 2, 3, 3, 2, 3, 128, 133, 89, 47,,,, -6, 6, 2, 2, 3, 3, 2, 3, 256, 133, 89, 47,,,, -6, 6, 2, 2, 3, 3, 2, 3, 384, 133, 89, 47,,,, -6, 6, 2, 2, 3, 3, 3, 1, 128, 133, 89, 47,,,, -6, 6, 2, 2, 3, 3, 3, 1, 256, 133, 89, 47,,,, -6, 6, 2, 2, 3, 3, 3, 1, 384, 133, 89, 47,,,, -6, 6, 2, 2, 3, 3, 3, 2, 128, 133, 89, 47,,,, -6, 6, 2, 2, 3, 3, 3, 2, 256, 133, 89, 47,,,, -6, 6, 2, 2, 3, 3, 3, 2, 384, 133, 89, 47,,,, -6, 6, 2, 2, 3, 3, 3, 3, 128, 133, 89, 47,,,, -6, 6, 2, 2, 3, 3, 3, 3, 256, 133, 89, 47,,,, -6, 6, 2, 2, 3, 3, 3, 3, 384, 133, 89, 47,,,, -6, 6, 2, 3, 1, 1, 1, 1, 128, 197, 131, 68,,,, -6, 6, 2, 3, 1, 1, 1, 1, 256, 197, 131, 68,,,, -6, 6, 2, 3, 1, 1, 1, 1, 384, 197, 131, 68,,,, -6, 6, 2, 3, 2, 2, 1, 1, 128, 197, 131, 68,,,, -6, 6, 2, 3, 2, 2, 1, 1, 256, 197, 131, 68,,,, -6, 6, 2, 3, 2, 2, 1, 1, 384, 197, 131, 68,,,, -6, 6, 2, 3, 2, 2, 1, 2, 128, 197, 131, 68,,,, -6, 6, 2, 3, 2, 2, 1, 2, 256, 197, 131, 68,,,, -6, 6, 2, 3, 2, 2, 1, 2, 384, 197, 131, 68,,,, -6, 6, 2, 3, 2, 2, 2, 1, 128, 197, 131, 68,,,, -6, 6, 2, 3, 2, 2, 2, 1, 256, 197, 131, 68,,,, -6, 6, 2, 3, 2, 2, 2, 1, 384, 197, 131, 68,,,, -6, 6, 2, 3, 2, 2, 2, 2, 128, 197, 131, 68,,,, -6, 6, 2, 3, 2, 2, 2, 2, 256, 197, 131, 68,,,, -6, 6, 2, 3, 2, 2, 2, 2, 384, 197, 131, 68,,,, -6, 6, 2, 3, 3, 3, 1, 1, 128, 197, 131, 68,,,, -6, 6, 2, 3, 3, 3, 1, 1, 256, 197, 131, 68,,,, -6, 6, 2, 3, 3, 3, 1, 1, 384, 197, 131, 68,,,, -6, 6, 2, 3, 3, 3, 1, 2, 128, 197, 131, 68,,,, -6, 6, 2, 3, 3, 3, 1, 2, 256, 197, 131, 68,,,, -6, 6, 2, 3, 3, 3, 1, 2, 384, 197, 131, 68,,,, -6, 6, 2, 3, 3, 3, 1, 3, 128, 197, 131, 68,,,, -6, 6, 2, 3, 3, 3, 1, 3, 256, 197, 131, 68,,,, -6, 6, 2, 3, 3, 3, 1, 3, 384, 197, 131, 68,,,, -6, 6, 2, 3, 3, 3, 2, 1, 128, 197, 131, 68,,,, -6, 6, 2, 3, 3, 3, 2, 1, 256, 197, 131, 68,,,, -6, 6, 2, 3, 3, 3, 2, 1, 384, 197, 131, 68,,,, -6, 6, 2, 3, 3, 3, 2, 2, 128, 197, 131, 68,,,, -6, 6, 2, 3, 3, 3, 2, 2, 256, 197, 131, 68,,,, -6, 6, 2, 3, 3, 3, 2, 2, 384, 197, 131, 68,,,, -6, 6, 2, 3, 3, 3, 2, 3, 128, 197, 131, 68,,,, -6, 6, 2, 3, 3, 3, 2, 3, 256, 197, 131, 68,,,, -6, 6, 2, 3, 3, 3, 2, 3, 384, 197, 131, 68,,,, -6, 6, 2, 3, 3, 3, 3, 1, 128, 197, 131, 68,,,, -6, 6, 2, 3, 3, 3, 3, 1, 256, 197, 131, 68,,,, -6, 6, 2, 3, 3, 3, 3, 1, 384, 197, 131, 68,,,, -6, 6, 2, 3, 3, 3, 3, 2, 128, 197, 131, 68,,,, -6, 6, 2, 3, 3, 3, 3, 2, 256, 197, 131, 68,,,, -6, 6, 2, 3, 3, 3, 3, 2, 384, 197, 131, 68,,,, -6, 6, 2, 3, 3, 3, 3, 3, 128, 197, 131, 68,,,, -6, 6, 2, 3, 3, 3, 3, 3, 256, 197, 131, 68,,,, -6, 6, 2, 3, 3, 3, 3, 3, 384, 197, 131, 68,,,, -6, 6, 2, 4, 1, 1, 1, 1, 128, 240, 173, 89,,,, -6, 6, 2, 4, 1, 1, 1, 1, 256, 240, 173, 89,,,, -6, 6, 2, 4, 1, 1, 1, 1, 384, 240, 173, 89,,,, -6, 6, 2, 4, 2, 2, 1, 1, 128, 240, 173, 89,,,, -6, 6, 2, 4, 2, 2, 1, 1, 256, 240, 173, 89,,,, -6, 6, 2, 4, 2, 2, 1, 1, 384, 240, 173, 89,,,, -6, 6, 2, 4, 2, 2, 1, 2, 128, 240, 173, 89,,,, -6, 6, 2, 4, 2, 2, 1, 2, 256, 240, 173, 89,,,, -6, 6, 2, 4, 2, 2, 1, 2, 384, 240, 173, 89,,,, -6, 6, 2, 4, 2, 2, 2, 1, 128, 240, 173, 89,,,, -6, 6, 2, 4, 2, 2, 2, 1, 256, 240, 173, 89,,,, -6, 6, 2, 4, 2, 2, 2, 1, 384, 240, 173, 89,,,, -6, 6, 2, 4, 2, 2, 2, 2, 128, 240, 173, 89,,,, -6, 6, 2, 4, 2, 2, 2, 2, 256, 240, 173, 89,,,, -6, 6, 2, 4, 2, 2, 2, 2, 384, 240, 173, 89,,,, -6, 6, 2, 4, 3, 3, 1, 1, 128, 240, 173, 89,,,, -6, 6, 2, 4, 3, 3, 1, 1, 256, 240, 173, 89,,,, -6, 6, 2, 4, 3, 3, 1, 1, 384, 240, 173, 89,,,, -6, 6, 2, 4, 3, 3, 1, 2, 128, 240, 173, 89,,,, -6, 6, 2, 4, 3, 3, 1, 2, 256, 240, 173, 89,,,, -6, 6, 2, 4, 3, 3, 1, 2, 384, 240, 173, 89,,,, -6, 6, 2, 4, 3, 3, 1, 3, 128, 240, 173, 89,,,, -6, 6, 2, 4, 3, 3, 1, 3, 256, 240, 173, 89,,,, -6, 6, 2, 4, 3, 3, 1, 3, 384, 240, 173, 89,,,, -6, 6, 2, 4, 3, 3, 2, 1, 128, 240, 173, 89,,,, -6, 6, 2, 4, 3, 3, 2, 1, 256, 240, 173, 89,,,, -6, 6, 2, 4, 3, 3, 2, 1, 384, 240, 173, 89,,,, -6, 6, 2, 4, 3, 3, 2, 2, 128, 240, 173, 89,,,, -6, 6, 2, 4, 3, 3, 2, 2, 256, 240, 173, 89,,,, -6, 6, 2, 4, 3, 3, 2, 2, 384, 240, 173, 89,,,, -6, 6, 2, 4, 3, 3, 2, 3, 128, 240, 173, 89,,,, -6, 6, 2, 4, 3, 3, 2, 3, 256, 240, 173, 89,,,, -6, 6, 2, 4, 3, 3, 2, 3, 384, 240, 173, 89,,,, -6, 6, 2, 4, 3, 3, 3, 1, 128, 240, 173, 89,,,, -6, 6, 2, 4, 3, 3, 3, 1, 256, 240, 173, 89,,,, -6, 6, 2, 4, 3, 3, 3, 1, 384, 240, 173, 89,,,, -6, 6, 2, 4, 3, 3, 3, 2, 128, 240, 173, 89,,,, -6, 6, 2, 4, 3, 3, 3, 2, 256, 240, 173, 89,,,, -6, 6, 2, 4, 3, 3, 3, 2, 384, 240, 173, 89,,,, -6, 6, 2, 4, 3, 3, 3, 3, 128, 240, 173, 89,,,, -6, 6, 2, 4, 3, 3, 3, 3, 256, 240, 173, 89,,,, -6, 6, 2, 4, 3, 3, 3, 3, 384, 240, 173, 89,,,, -6, 6, 2, 5, 1, 1, 1, 1, 128, 240, 215, 110,,,, -6, 6, 2, 5, 1, 1, 1, 1, 256, 240, 215, 110,,,, -6, 6, 2, 5, 1, 1, 1, 1, 384, 240, 215, 110,,,, -6, 6, 2, 5, 2, 2, 1, 1, 128, 240, 215, 110,,,, -6, 6, 2, 5, 2, 2, 1, 1, 256, 240, 215, 110,,,, -6, 6, 2, 5, 2, 2, 1, 1, 384, 240, 215, 110,,,, -6, 6, 2, 5, 2, 2, 1, 2, 128, 240, 215, 110,,,, -6, 6, 2, 5, 2, 2, 1, 2, 256, 240, 215, 110,,,, -6, 6, 2, 5, 2, 2, 1, 2, 384, 240, 215, 110,,,, -6, 6, 2, 5, 2, 2, 2, 1, 128, 240, 215, 110,,,, -6, 6, 2, 5, 2, 2, 2, 1, 256, 240, 215, 110,,,, -6, 6, 2, 5, 2, 2, 2, 1, 384, 240, 215, 110,,,, -6, 6, 2, 5, 2, 2, 2, 2, 128, 240, 215, 110,,,, -6, 6, 2, 5, 2, 2, 2, 2, 256, 240, 215, 110,,,, -6, 6, 2, 5, 2, 2, 2, 2, 384, 240, 215, 110,,,, -6, 6, 2, 5, 3, 3, 1, 1, 128, 240, 215, 110,,,, -6, 6, 2, 5, 3, 3, 1, 1, 256, 240, 215, 110,,,, -6, 6, 2, 5, 3, 3, 1, 1, 384, 240, 215, 110,,,, -6, 6, 2, 5, 3, 3, 1, 2, 128, 240, 215, 110,,,, -6, 6, 2, 5, 3, 3, 1, 2, 256, 240, 215, 110,,,, -6, 6, 2, 5, 3, 3, 1, 2, 384, 240, 215, 110,,,, -6, 6, 2, 5, 3, 3, 1, 3, 128, 240, 215, 110,,,, -6, 6, 2, 5, 3, 3, 1, 3, 256, 240, 215, 110,,,, -6, 6, 2, 5, 3, 3, 1, 3, 384, 240, 215, 110,,,, -6, 6, 2, 5, 3, 3, 2, 1, 128, 240, 215, 110,,,, -6, 6, 2, 5, 3, 3, 2, 1, 256, 240, 215, 110,,,, -6, 6, 2, 5, 3, 3, 2, 1, 384, 240, 215, 110,,,, -6, 6, 2, 5, 3, 3, 2, 2, 128, 240, 215, 110,,,, -6, 6, 2, 5, 3, 3, 2, 2, 256, 240, 215, 110,,,, -6, 6, 2, 5, 3, 3, 2, 2, 384, 240, 215, 110,,,, -6, 6, 2, 5, 3, 3, 2, 3, 128, 240, 215, 110,,,, -6, 6, 2, 5, 3, 3, 2, 3, 256, 240, 215, 110,,,, -6, 6, 2, 5, 3, 3, 2, 3, 384, 240, 215, 110,,,, -6, 6, 2, 5, 3, 3, 3, 1, 128, 240, 215, 110,,,, -6, 6, 2, 5, 3, 3, 3, 1, 256, 240, 215, 110,,,, -6, 6, 2, 5, 3, 3, 3, 1, 384, 240, 215, 110,,,, -6, 6, 2, 5, 3, 3, 3, 2, 128, 240, 215, 110,,,, -6, 6, 2, 5, 3, 3, 3, 2, 256, 240, 215, 110,,,, -6, 6, 2, 5, 3, 3, 3, 2, 384, 240, 215, 110,,,, -6, 6, 2, 5, 3, 3, 3, 3, 128, 240, 215, 110,,,, -6, 6, 2, 5, 3, 3, 3, 3, 256, 240, 215, 110,,,, -6, 6, 2, 5, 3, 3, 3, 3, 384, 240, 215, 110,,,, -6, 6, 2, 6, 1, 1, 1, 1, 128, 240, 240, 131,,,, -6, 6, 2, 6, 1, 1, 1, 1, 256, 240, 240, 131,,,, -6, 6, 2, 6, 1, 1, 1, 1, 384, 240, 240, 131,,,, -6, 6, 2, 6, 2, 2, 1, 1, 128, 240, 240, 131,,,, -6, 6, 2, 6, 2, 2, 1, 1, 256, 240, 240, 131,,,, -6, 6, 2, 6, 2, 2, 1, 1, 384, 240, 240, 131,,,, -6, 6, 2, 6, 2, 2, 1, 2, 128, 240, 240, 131,,,, -6, 6, 2, 6, 2, 2, 1, 2, 256, 240, 240, 131,,,, -6, 6, 2, 6, 2, 2, 1, 2, 384, 240, 240, 131,,,, -6, 6, 2, 6, 2, 2, 2, 1, 128, 240, 240, 131,,,, -6, 6, 2, 6, 2, 2, 2, 1, 256, 240, 240, 131,,,, -6, 6, 2, 6, 2, 2, 2, 1, 384, 240, 240, 131,,,, -6, 6, 2, 6, 2, 2, 2, 2, 128, 240, 240, 131,,,, -6, 6, 2, 6, 2, 2, 2, 2, 256, 240, 240, 131,,,, -6, 6, 2, 6, 2, 2, 2, 2, 384, 240, 240, 131,,,, -6, 6, 2, 6, 3, 3, 1, 1, 128, 240, 240, 131,,,, -6, 6, 2, 6, 3, 3, 1, 1, 256, 240, 240, 131,,,, -6, 6, 2, 6, 3, 3, 1, 1, 384, 240, 240, 131,,,, -6, 6, 2, 6, 3, 3, 1, 2, 128, 240, 240, 131,,,, -6, 6, 2, 6, 3, 3, 1, 2, 256, 240, 240, 131,,,, -6, 6, 2, 6, 3, 3, 1, 2, 384, 240, 240, 131,,,, -6, 6, 2, 6, 3, 3, 1, 3, 128, 240, 240, 131,,,, -6, 6, 2, 6, 3, 3, 1, 3, 256, 240, 240, 131,,,, -6, 6, 2, 6, 3, 3, 1, 3, 384, 240, 240, 131,,,, -6, 6, 2, 6, 3, 3, 2, 1, 128, 240, 240, 131,,,, -6, 6, 2, 6, 3, 3, 2, 1, 256, 240, 240, 131,,,, -6, 6, 2, 6, 3, 3, 2, 1, 384, 240, 240, 131,,,, -6, 6, 2, 6, 3, 3, 2, 2, 128, 240, 240, 131,,,, -6, 6, 2, 6, 3, 3, 2, 2, 256, 240, 240, 131,,,, -6, 6, 2, 6, 3, 3, 2, 2, 384, 240, 240, 131,,,, -6, 6, 2, 6, 3, 3, 2, 3, 128, 240, 240, 131,,,, -6, 6, 2, 6, 3, 3, 2, 3, 256, 240, 240, 131,,,, -6, 6, 2, 6, 3, 3, 2, 3, 384, 240, 240, 131,,,, -6, 6, 2, 6, 3, 3, 3, 1, 128, 240, 240, 131,,,, -6, 6, 2, 6, 3, 3, 3, 1, 256, 240, 240, 131,,,, -6, 6, 2, 6, 3, 3, 3, 1, 384, 240, 240, 131,,,, -6, 6, 2, 6, 3, 3, 3, 2, 128, 240, 240, 131,,,, -6, 6, 2, 6, 3, 3, 3, 2, 256, 240, 240, 131,,,, -6, 6, 2, 6, 3, 3, 3, 2, 384, 240, 240, 131,,,, -6, 6, 2, 6, 3, 3, 3, 3, 128, 240, 240, 131,,,, -6, 6, 2, 6, 3, 3, 3, 3, 256, 240, 240, 131,,,, -6, 6, 2, 6, 3, 3, 3, 3, 384, 240, 240, 131,,,, -6, 6, 3, 1, 1, 1, 1, 1, 128, 69, 47, 26,,,, -6, 6, 3, 1, 1, 1, 1, 1, 256, 69, 47, 26,,,, -6, 6, 3, 1, 1, 1, 1, 1, 384, 69, 47, 26,,,, -6, 6, 3, 1, 2, 2, 1, 1, 128, 69, 47, 26,,,, -6, 6, 3, 1, 2, 2, 1, 1, 256, 69, 47, 26,,,, -6, 6, 3, 1, 2, 2, 1, 1, 384, 69, 47, 26,,,, -6, 6, 3, 1, 2, 2, 1, 2, 128, 69, 47, 26,,,, -6, 6, 3, 1, 2, 2, 1, 2, 256, 69, 47, 26,,,, -6, 6, 3, 1, 2, 2, 1, 2, 384, 69, 47, 26,,,, -6, 6, 3, 1, 2, 2, 2, 1, 128, 69, 47, 26,,,, -6, 6, 3, 1, 2, 2, 2, 1, 256, 69, 47, 26,,,, -6, 6, 3, 1, 2, 2, 2, 1, 384, 69, 47, 26,,,, -6, 6, 3, 1, 2, 2, 2, 2, 128, 69, 47, 26,,,, -6, 6, 3, 1, 2, 2, 2, 2, 256, 69, 47, 26,,,, -6, 6, 3, 1, 2, 2, 2, 2, 384, 69, 47, 26,,,, -6, 6, 3, 1, 3, 3, 1, 1, 128, 69, 47, 26,,,, -6, 6, 3, 1, 3, 3, 1, 1, 256, 69, 47, 26,,,, -6, 6, 3, 1, 3, 3, 1, 1, 384, 69, 47, 26,,,, -6, 6, 3, 1, 3, 3, 1, 2, 128, 69, 47, 26,,,, -6, 6, 3, 1, 3, 3, 1, 2, 256, 69, 47, 26,,,, -6, 6, 3, 1, 3, 3, 1, 2, 384, 69, 47, 26,,,, -6, 6, 3, 1, 3, 3, 1, 3, 128, 69, 47, 26,,,, -6, 6, 3, 1, 3, 3, 1, 3, 256, 69, 47, 26,,,, -6, 6, 3, 1, 3, 3, 1, 3, 384, 69, 47, 26,,,, -6, 6, 3, 1, 3, 3, 2, 1, 128, 69, 47, 26,,,, -6, 6, 3, 1, 3, 3, 2, 1, 256, 69, 47, 26,,,, -6, 6, 3, 1, 3, 3, 2, 1, 384, 69, 47, 26,,,, -6, 6, 3, 1, 3, 3, 2, 2, 128, 69, 47, 26,,,, -6, 6, 3, 1, 3, 3, 2, 2, 256, 69, 47, 26,,,, -6, 6, 3, 1, 3, 3, 2, 2, 384, 69, 47, 26,,,, -6, 6, 3, 1, 3, 3, 2, 3, 128, 69, 47, 26,,,, -6, 6, 3, 1, 3, 3, 2, 3, 256, 69, 47, 26,,,, -6, 6, 3, 1, 3, 3, 2, 3, 384, 69, 47, 26,,,, -6, 6, 3, 1, 3, 3, 3, 1, 128, 69, 47, 26,,,, -6, 6, 3, 1, 3, 3, 3, 1, 256, 69, 47, 26,,,, -6, 6, 3, 1, 3, 3, 3, 1, 384, 69, 47, 26,,,, -6, 6, 3, 1, 3, 3, 3, 2, 128, 69, 47, 26,,,, -6, 6, 3, 1, 3, 3, 3, 2, 256, 69, 47, 26,,,, -6, 6, 3, 1, 3, 3, 3, 2, 384, 69, 47, 26,,,, -6, 6, 3, 1, 3, 3, 3, 3, 128, 69, 47, 26,,,, -6, 6, 3, 1, 3, 3, 3, 3, 256, 69, 47, 26,,,, -6, 6, 3, 1, 3, 3, 3, 3, 384, 69, 47, 26,,,, -6, 6, 3, 2, 1, 1, 1, 1, 128, 133, 89, 47,,,, -6, 6, 3, 2, 1, 1, 1, 1, 256, 133, 89, 47,,,, -6, 6, 3, 2, 1, 1, 1, 1, 384, 133, 89, 47,,,, -6, 6, 3, 2, 2, 2, 1, 1, 128, 133, 89, 47,,,, -6, 6, 3, 2, 2, 2, 1, 1, 256, 133, 89, 47,,,, -6, 6, 3, 2, 2, 2, 1, 1, 384, 133, 89, 47,,,, -6, 6, 3, 2, 2, 2, 1, 2, 128, 133, 89, 47,,,, -6, 6, 3, 2, 2, 2, 1, 2, 256, 133, 89, 47,,,, -6, 6, 3, 2, 2, 2, 1, 2, 384, 133, 89, 47,,,, -6, 6, 3, 2, 2, 2, 2, 1, 128, 133, 89, 47,,,, -6, 6, 3, 2, 2, 2, 2, 1, 256, 133, 89, 47,,,, -6, 6, 3, 2, 2, 2, 2, 1, 384, 133, 89, 47,,,, -6, 6, 3, 2, 2, 2, 2, 2, 128, 133, 89, 47,,,, -6, 6, 3, 2, 2, 2, 2, 2, 256, 133, 89, 47,,,, -6, 6, 3, 2, 2, 2, 2, 2, 384, 133, 89, 47,,,, -6, 6, 3, 2, 3, 3, 1, 1, 128, 133, 89, 47,,,, -6, 6, 3, 2, 3, 3, 1, 1, 256, 133, 89, 47,,,, -6, 6, 3, 2, 3, 3, 1, 1, 384, 133, 89, 47,,,, -6, 6, 3, 2, 3, 3, 1, 2, 128, 133, 89, 47,,,, -6, 6, 3, 2, 3, 3, 1, 2, 256, 133, 89, 47,,,, -6, 6, 3, 2, 3, 3, 1, 2, 384, 133, 89, 47,,,, -6, 6, 3, 2, 3, 3, 1, 3, 128, 133, 89, 47,,,, -6, 6, 3, 2, 3, 3, 1, 3, 256, 133, 89, 47,,,, -6, 6, 3, 2, 3, 3, 1, 3, 384, 133, 89, 47,,,, -6, 6, 3, 2, 3, 3, 2, 1, 128, 133, 89, 47,,,, -6, 6, 3, 2, 3, 3, 2, 1, 256, 133, 89, 47,,,, -6, 6, 3, 2, 3, 3, 2, 1, 384, 133, 89, 47,,,, -6, 6, 3, 2, 3, 3, 2, 2, 128, 133, 89, 47,,,, -6, 6, 3, 2, 3, 3, 2, 2, 256, 133, 89, 47,,,, -6, 6, 3, 2, 3, 3, 2, 2, 384, 133, 89, 47,,,, -6, 6, 3, 2, 3, 3, 2, 3, 128, 133, 89, 47,,,, -6, 6, 3, 2, 3, 3, 2, 3, 256, 133, 89, 47,,,, -6, 6, 3, 2, 3, 3, 2, 3, 384, 133, 89, 47,,,, -6, 6, 3, 2, 3, 3, 3, 1, 128, 133, 89, 47,,,, -6, 6, 3, 2, 3, 3, 3, 1, 256, 133, 89, 47,,,, -6, 6, 3, 2, 3, 3, 3, 1, 384, 133, 89, 47,,,, -6, 6, 3, 2, 3, 3, 3, 2, 128, 133, 89, 47,,,, -6, 6, 3, 2, 3, 3, 3, 2, 256, 133, 89, 47,,,, -6, 6, 3, 2, 3, 3, 3, 2, 384, 133, 89, 47,,,, -6, 6, 3, 2, 3, 3, 3, 3, 128, 133, 89, 47,,,, -6, 6, 3, 2, 3, 3, 3, 3, 256, 133, 89, 47,,,, -6, 6, 3, 2, 3, 3, 3, 3, 384, 133, 89, 47,,,, -6, 6, 3, 3, 1, 1, 1, 1, 128, 197, 131, 68,,,, -6, 6, 3, 3, 1, 1, 1, 1, 256, 197, 131, 68,,,, -6, 6, 3, 3, 1, 1, 1, 1, 384, 197, 131, 68,,,, -6, 6, 3, 3, 2, 2, 1, 1, 128, 197, 131, 68,,,, -6, 6, 3, 3, 2, 2, 1, 1, 256, 197, 131, 68,,,, -6, 6, 3, 3, 2, 2, 1, 1, 384, 197, 131, 68,,,, -6, 6, 3, 3, 2, 2, 1, 2, 128, 197, 131, 68,,,, -6, 6, 3, 3, 2, 2, 1, 2, 256, 197, 131, 68,,,, -6, 6, 3, 3, 2, 2, 1, 2, 384, 197, 131, 68,,,, -6, 6, 3, 3, 2, 2, 2, 1, 128, 197, 131, 68,,,, -6, 6, 3, 3, 2, 2, 2, 1, 256, 197, 131, 68,,,, -6, 6, 3, 3, 2, 2, 2, 1, 384, 197, 131, 68,,,, -6, 6, 3, 3, 2, 2, 2, 2, 128, 197, 131, 68,,,, -6, 6, 3, 3, 2, 2, 2, 2, 256, 197, 131, 68,,,, -6, 6, 3, 3, 2, 2, 2, 2, 384, 197, 131, 68,,,, -6, 6, 3, 3, 3, 3, 1, 1, 128, 197, 131, 68,,,, -6, 6, 3, 3, 3, 3, 1, 1, 256, 197, 131, 68,,,, -6, 6, 3, 3, 3, 3, 1, 1, 384, 197, 131, 68,,,, -6, 6, 3, 3, 3, 3, 1, 2, 128, 197, 131, 68,,,, -6, 6, 3, 3, 3, 3, 1, 2, 256, 197, 131, 68,,,, -6, 6, 3, 3, 3, 3, 1, 2, 384, 197, 131, 68,,,, -6, 6, 3, 3, 3, 3, 1, 3, 128, 197, 131, 68,,,, -6, 6, 3, 3, 3, 3, 1, 3, 256, 197, 131, 68,,,, -6, 6, 3, 3, 3, 3, 1, 3, 384, 197, 131, 68,,,, -6, 6, 3, 3, 3, 3, 2, 1, 128, 197, 131, 68,,,, -6, 6, 3, 3, 3, 3, 2, 1, 256, 197, 131, 68,,,, -6, 6, 3, 3, 3, 3, 2, 1, 384, 197, 131, 68,,,, -6, 6, 3, 3, 3, 3, 2, 2, 128, 197, 131, 68,,,, -6, 6, 3, 3, 3, 3, 2, 2, 256, 197, 131, 68,,,, -6, 6, 3, 3, 3, 3, 2, 2, 384, 197, 131, 68,,,, -6, 6, 3, 3, 3, 3, 2, 3, 128, 197, 131, 68,,,, -6, 6, 3, 3, 3, 3, 2, 3, 256, 197, 131, 68,,,, -6, 6, 3, 3, 3, 3, 2, 3, 384, 197, 131, 68,,,, -6, 6, 3, 3, 3, 3, 3, 1, 128, 197, 131, 68,,,, -6, 6, 3, 3, 3, 3, 3, 1, 256, 197, 131, 68,,,, -6, 6, 3, 3, 3, 3, 3, 1, 384, 197, 131, 68,,,, -6, 6, 3, 3, 3, 3, 3, 2, 128, 197, 131, 68,,,, -6, 6, 3, 3, 3, 3, 3, 2, 256, 197, 131, 68,,,, -6, 6, 3, 3, 3, 3, 3, 2, 384, 197, 131, 68,,,, -6, 6, 3, 3, 3, 3, 3, 3, 128, 197, 131, 68,,,, -6, 6, 3, 3, 3, 3, 3, 3, 256, 197, 131, 68,,,, -6, 6, 3, 3, 3, 3, 3, 3, 384, 197, 131, 68,,,, -6, 6, 3, 4, 1, 1, 1, 1, 128, 240, 173, 89,,,, -6, 6, 3, 4, 1, 1, 1, 1, 256, 240, 173, 89,,,, -6, 6, 3, 4, 1, 1, 1, 1, 384, 240, 173, 89,,,, -6, 6, 3, 4, 2, 2, 1, 1, 128, 240, 173, 89,,,, -6, 6, 3, 4, 2, 2, 1, 1, 256, 240, 173, 89,,,, -6, 6, 3, 4, 2, 2, 1, 1, 384, 240, 173, 89,,,, -6, 6, 3, 4, 2, 2, 1, 2, 128, 240, 173, 89,,,, -6, 6, 3, 4, 2, 2, 1, 2, 256, 240, 173, 89,,,, -6, 6, 3, 4, 2, 2, 1, 2, 384, 240, 173, 89,,,, -6, 6, 3, 4, 2, 2, 2, 1, 128, 240, 173, 89,,,, -6, 6, 3, 4, 2, 2, 2, 1, 256, 240, 173, 89,,,, -6, 6, 3, 4, 2, 2, 2, 1, 384, 240, 173, 89,,,, -6, 6, 3, 4, 2, 2, 2, 2, 128, 240, 173, 89,,,, -6, 6, 3, 4, 2, 2, 2, 2, 256, 240, 173, 89,,,, -6, 6, 3, 4, 2, 2, 2, 2, 384, 240, 173, 89,,,, -6, 6, 3, 4, 3, 3, 1, 1, 128, 240, 173, 89,,,, -6, 6, 3, 4, 3, 3, 1, 1, 256, 240, 173, 89,,,, -6, 6, 3, 4, 3, 3, 1, 1, 384, 240, 173, 89,,,, -6, 6, 3, 4, 3, 3, 1, 2, 128, 240, 173, 89,,,, -6, 6, 3, 4, 3, 3, 1, 2, 256, 240, 173, 89,,,, -6, 6, 3, 4, 3, 3, 1, 2, 384, 240, 173, 89,,,, -6, 6, 3, 4, 3, 3, 1, 3, 128, 240, 173, 89,,,, -6, 6, 3, 4, 3, 3, 1, 3, 256, 240, 173, 89,,,, -6, 6, 3, 4, 3, 3, 1, 3, 384, 240, 173, 89,,,, -6, 6, 3, 4, 3, 3, 2, 1, 128, 240, 173, 89,,,, -6, 6, 3, 4, 3, 3, 2, 1, 256, 240, 173, 89,,,, -6, 6, 3, 4, 3, 3, 2, 1, 384, 240, 173, 89,,,, -6, 6, 3, 4, 3, 3, 2, 2, 128, 240, 173, 89,,,, -6, 6, 3, 4, 3, 3, 2, 2, 256, 240, 173, 89,,,, -6, 6, 3, 4, 3, 3, 2, 2, 384, 240, 173, 89,,,, -6, 6, 3, 4, 3, 3, 2, 3, 128, 240, 173, 89,,,, -6, 6, 3, 4, 3, 3, 2, 3, 256, 240, 173, 89,,,, -6, 6, 3, 4, 3, 3, 2, 3, 384, 240, 173, 89,,,, -6, 6, 3, 4, 3, 3, 3, 1, 128, 240, 173, 89,,,, -6, 6, 3, 4, 3, 3, 3, 1, 256, 240, 173, 89,,,, -6, 6, 3, 4, 3, 3, 3, 1, 384, 240, 173, 89,,,, -6, 6, 3, 4, 3, 3, 3, 2, 128, 240, 173, 89,,,, -6, 6, 3, 4, 3, 3, 3, 2, 256, 240, 173, 89,,,, -6, 6, 3, 4, 3, 3, 3, 2, 384, 240, 173, 89,,,, -6, 6, 3, 4, 3, 3, 3, 3, 128, 240, 173, 89,,,, -6, 6, 3, 4, 3, 3, 3, 3, 256, 240, 173, 89,,,, -6, 6, 3, 4, 3, 3, 3, 3, 384, 240, 173, 89,,,, -6, 6, 3, 5, 1, 1, 1, 1, 128, 240, 215, 110,,,, -6, 6, 3, 5, 1, 1, 1, 1, 256, 240, 215, 110,,,, -6, 6, 3, 5, 1, 1, 1, 1, 384, 240, 215, 110,,,, -6, 6, 3, 5, 2, 2, 1, 1, 128, 240, 215, 110,,,, -6, 6, 3, 5, 2, 2, 1, 1, 256, 240, 215, 110,,,, -6, 6, 3, 5, 2, 2, 1, 1, 384, 240, 215, 110,,,, -6, 6, 3, 5, 2, 2, 1, 2, 128, 240, 215, 110,,,, -6, 6, 3, 5, 2, 2, 1, 2, 256, 240, 215, 110,,,, -6, 6, 3, 5, 2, 2, 1, 2, 384, 240, 215, 110,,,, -6, 6, 3, 5, 2, 2, 2, 1, 128, 240, 215, 110,,,, -6, 6, 3, 5, 2, 2, 2, 1, 256, 240, 215, 110,,,, -6, 6, 3, 5, 2, 2, 2, 1, 384, 240, 215, 110,,,, -6, 6, 3, 5, 2, 2, 2, 2, 128, 240, 215, 110,,,, -6, 6, 3, 5, 2, 2, 2, 2, 256, 240, 215, 110,,,, -6, 6, 3, 5, 2, 2, 2, 2, 384, 240, 215, 110,,,, -6, 6, 3, 5, 3, 3, 1, 1, 128, 240, 215, 110,,,, -6, 6, 3, 5, 3, 3, 1, 1, 256, 240, 215, 110,,,, -6, 6, 3, 5, 3, 3, 1, 1, 384, 240, 215, 110,,,, -6, 6, 3, 5, 3, 3, 1, 2, 128, 240, 215, 110,,,, -6, 6, 3, 5, 3, 3, 1, 2, 256, 240, 215, 110,,,, -6, 6, 3, 5, 3, 3, 1, 2, 384, 240, 215, 110,,,, -6, 6, 3, 5, 3, 3, 1, 3, 128, 240, 215, 110,,,, -6, 6, 3, 5, 3, 3, 1, 3, 256, 240, 215, 110,,,, -6, 6, 3, 5, 3, 3, 1, 3, 384, 240, 215, 110,,,, -6, 6, 3, 5, 3, 3, 2, 1, 128, 240, 215, 110,,,, -6, 6, 3, 5, 3, 3, 2, 1, 256, 240, 215, 110,,,, -6, 6, 3, 5, 3, 3, 2, 1, 384, 240, 215, 110,,,, -6, 6, 3, 5, 3, 3, 2, 2, 128, 240, 215, 110,,,, -6, 6, 3, 5, 3, 3, 2, 2, 256, 240, 215, 110,,,, -6, 6, 3, 5, 3, 3, 2, 2, 384, 240, 215, 110,,,, -6, 6, 3, 5, 3, 3, 2, 3, 128, 240, 215, 110,,,, -6, 6, 3, 5, 3, 3, 2, 3, 256, 240, 215, 110,,,, -6, 6, 3, 5, 3, 3, 2, 3, 384, 240, 215, 110,,,, -6, 6, 3, 5, 3, 3, 3, 1, 128, 240, 215, 110,,,, -6, 6, 3, 5, 3, 3, 3, 1, 256, 240, 215, 110,,,, -6, 6, 3, 5, 3, 3, 3, 1, 384, 240, 215, 110,,,, -6, 6, 3, 5, 3, 3, 3, 2, 128, 240, 215, 110,,,, -6, 6, 3, 5, 3, 3, 3, 2, 256, 240, 215, 110,,,, -6, 6, 3, 5, 3, 3, 3, 2, 384, 240, 215, 110,,,, -6, 6, 3, 5, 3, 3, 3, 3, 128, 240, 215, 110,,,, -6, 6, 3, 5, 3, 3, 3, 3, 256, 240, 215, 110,,,, -6, 6, 3, 5, 3, 3, 3, 3, 384, 240, 215, 110,,,, -6, 6, 3, 6, 1, 1, 1, 1, 128, 240, 240, 131,,,, -6, 6, 3, 6, 1, 1, 1, 1, 256, 240, 240, 131,,,, -6, 6, 3, 6, 1, 1, 1, 1, 384, 240, 240, 131,,,, -6, 6, 3, 6, 2, 2, 1, 1, 128, 240, 240, 131,,,, -6, 6, 3, 6, 2, 2, 1, 1, 256, 240, 240, 131,,,, -6, 6, 3, 6, 2, 2, 1, 1, 384, 240, 240, 131,,,, -6, 6, 3, 6, 2, 2, 1, 2, 128, 240, 240, 131,,,, -6, 6, 3, 6, 2, 2, 1, 2, 256, 240, 240, 131,,,, -6, 6, 3, 6, 2, 2, 1, 2, 384, 240, 240, 131,,,, -6, 6, 3, 6, 2, 2, 2, 1, 128, 240, 240, 131,,,, -6, 6, 3, 6, 2, 2, 2, 1, 256, 240, 240, 131,,,, -6, 6, 3, 6, 2, 2, 2, 1, 384, 240, 240, 131,,,, -6, 6, 3, 6, 2, 2, 2, 2, 128, 240, 240, 131,,,, -6, 6, 3, 6, 2, 2, 2, 2, 256, 240, 240, 131,,,, -6, 6, 3, 6, 2, 2, 2, 2, 384, 240, 240, 131,,,, -6, 6, 3, 6, 3, 3, 1, 1, 128, 240, 240, 131,,,, -6, 6, 3, 6, 3, 3, 1, 1, 256, 240, 240, 131,,,, -6, 6, 3, 6, 3, 3, 1, 1, 384, 240, 240, 131,,,, -6, 6, 3, 6, 3, 3, 1, 2, 128, 240, 240, 131,,,, -6, 6, 3, 6, 3, 3, 1, 2, 256, 240, 240, 131,,,, -6, 6, 3, 6, 3, 3, 1, 2, 384, 240, 240, 131,,,, -6, 6, 3, 6, 3, 3, 1, 3, 128, 240, 240, 131,,,, -6, 6, 3, 6, 3, 3, 1, 3, 256, 240, 240, 131,,,, -6, 6, 3, 6, 3, 3, 1, 3, 384, 240, 240, 131,,,, -6, 6, 3, 6, 3, 3, 2, 1, 128, 240, 240, 131,,,, -6, 6, 3, 6, 3, 3, 2, 1, 256, 240, 240, 131,,,, -6, 6, 3, 6, 3, 3, 2, 1, 384, 240, 240, 131,,,, -6, 6, 3, 6, 3, 3, 2, 2, 128, 240, 240, 131,,,, -6, 6, 3, 6, 3, 3, 2, 2, 256, 240, 240, 131,,,, -6, 6, 3, 6, 3, 3, 2, 2, 384, 240, 240, 131,,,, -6, 6, 3, 6, 3, 3, 2, 3, 128, 240, 240, 131,,,, -6, 6, 3, 6, 3, 3, 2, 3, 256, 240, 240, 131,,,, -6, 6, 3, 6, 3, 3, 2, 3, 384, 240, 240, 131,,,, -6, 6, 3, 6, 3, 3, 3, 1, 128, 240, 240, 131,,,, -6, 6, 3, 6, 3, 3, 3, 1, 256, 240, 240, 131,,,, -6, 6, 3, 6, 3, 3, 3, 1, 384, 240, 240, 131,,,, -6, 6, 3, 6, 3, 3, 3, 2, 128, 240, 240, 131,,,, -6, 6, 3, 6, 3, 3, 3, 2, 256, 240, 240, 131,,,, -6, 6, 3, 6, 3, 3, 3, 2, 384, 240, 240, 131,,,, -6, 6, 3, 6, 3, 3, 3, 3, 128, 240, 240, 131,,,, -6, 6, 3, 6, 3, 3, 3, 3, 256, 240, 240, 131,,,, -6, 6, 3, 6, 3, 3, 3, 3, 384, 240, 240, 131,,,, -6, 6, 4, 1, 1, 1, 1, 1, 128, 69, 47, 26,,,, -6, 6, 4, 1, 1, 1, 1, 1, 256, 69, 47, 26,,,, -6, 6, 4, 1, 1, 1, 1, 1, 384, 69, 47, 26,,,, -6, 6, 4, 1, 2, 2, 1, 1, 128, 69, 47, 26,,,, -6, 6, 4, 1, 2, 2, 1, 1, 256, 69, 47, 26,,,, -6, 6, 4, 1, 2, 2, 1, 1, 384, 69, 47, 26,,,, -6, 6, 4, 1, 2, 2, 1, 2, 128, 69, 47, 26,,,, -6, 6, 4, 1, 2, 2, 1, 2, 256, 69, 47, 26,,,, -6, 6, 4, 1, 2, 2, 1, 2, 384, 69, 47, 26,,,, -6, 6, 4, 1, 2, 2, 2, 1, 128, 69, 47, 26,,,, -6, 6, 4, 1, 2, 2, 2, 1, 256, 69, 47, 26,,,, -6, 6, 4, 1, 2, 2, 2, 1, 384, 69, 47, 26,,,, -6, 6, 4, 1, 2, 2, 2, 2, 128, 69, 47, 26,,,, -6, 6, 4, 1, 2, 2, 2, 2, 256, 69, 47, 26,,,, -6, 6, 4, 1, 2, 2, 2, 2, 384, 69, 47, 26,,,, -6, 6, 4, 1, 3, 3, 1, 1, 128, 69, 47, 26,,,, -6, 6, 4, 1, 3, 3, 1, 1, 256, 69, 47, 26,,,, -6, 6, 4, 1, 3, 3, 1, 1, 384, 69, 47, 26,,,, -6, 6, 4, 1, 3, 3, 1, 2, 128, 69, 47, 26,,,, -6, 6, 4, 1, 3, 3, 1, 2, 256, 69, 47, 26,,,, -6, 6, 4, 1, 3, 3, 1, 2, 384, 69, 47, 26,,,, -6, 6, 4, 1, 3, 3, 1, 3, 128, 69, 47, 26,,,, -6, 6, 4, 1, 3, 3, 1, 3, 256, 69, 47, 26,,,, -6, 6, 4, 1, 3, 3, 1, 3, 384, 69, 47, 26,,,, -6, 6, 4, 1, 3, 3, 2, 1, 128, 69, 47, 26,,,, -6, 6, 4, 1, 3, 3, 2, 1, 256, 69, 47, 26,,,, -6, 6, 4, 1, 3, 3, 2, 1, 384, 69, 47, 26,,,, -6, 6, 4, 1, 3, 3, 2, 2, 128, 69, 47, 26,,,, -6, 6, 4, 1, 3, 3, 2, 2, 256, 69, 47, 26,,,, -6, 6, 4, 1, 3, 3, 2, 2, 384, 69, 47, 26,,,, -6, 6, 4, 1, 3, 3, 2, 3, 128, 69, 47, 26,,,, -6, 6, 4, 1, 3, 3, 2, 3, 256, 69, 47, 26,,,, -6, 6, 4, 1, 3, 3, 2, 3, 384, 69, 47, 26,,,, -6, 6, 4, 1, 3, 3, 3, 1, 128, 69, 47, 26,,,, -6, 6, 4, 1, 3, 3, 3, 1, 256, 69, 47, 26,,,, -6, 6, 4, 1, 3, 3, 3, 1, 384, 69, 47, 26,,,, -6, 6, 4, 1, 3, 3, 3, 2, 128, 69, 47, 26,,,, -6, 6, 4, 1, 3, 3, 3, 2, 256, 69, 47, 26,,,, -6, 6, 4, 1, 3, 3, 3, 2, 384, 69, 47, 26,,,, -6, 6, 4, 1, 3, 3, 3, 3, 128, 69, 47, 26,,,, -6, 6, 4, 1, 3, 3, 3, 3, 256, 69, 47, 26,,,, -6, 6, 4, 1, 3, 3, 3, 3, 384, 69, 47, 26,,,, -6, 6, 4, 2, 1, 1, 1, 1, 128, 133, 89, 47,,,, -6, 6, 4, 2, 1, 1, 1, 1, 256, 133, 89, 47,,,, -6, 6, 4, 2, 1, 1, 1, 1, 384, 133, 89, 47,,,, -6, 6, 4, 2, 2, 2, 1, 1, 128, 133, 89, 47,,,, -6, 6, 4, 2, 2, 2, 1, 1, 256, 133, 89, 47,,,, -6, 6, 4, 2, 2, 2, 1, 1, 384, 133, 89, 47,,,, -6, 6, 4, 2, 2, 2, 1, 2, 128, 133, 89, 47,,,, -6, 6, 4, 2, 2, 2, 1, 2, 256, 133, 89, 47,,,, -6, 6, 4, 2, 2, 2, 1, 2, 384, 133, 89, 47,,,, -6, 6, 4, 2, 2, 2, 2, 1, 128, 133, 89, 47,,,, -6, 6, 4, 2, 2, 2, 2, 1, 256, 133, 89, 47,,,, -6, 6, 4, 2, 2, 2, 2, 1, 384, 133, 89, 47,,,, -6, 6, 4, 2, 2, 2, 2, 2, 128, 133, 89, 47,,,, -6, 6, 4, 2, 2, 2, 2, 2, 256, 133, 89, 47,,,, -6, 6, 4, 2, 2, 2, 2, 2, 384, 133, 89, 47,,,, -6, 6, 4, 2, 3, 3, 1, 1, 128, 133, 89, 47,,,, -6, 6, 4, 2, 3, 3, 1, 1, 256, 133, 89, 47,,,, -6, 6, 4, 2, 3, 3, 1, 1, 384, 133, 89, 47,,,, -6, 6, 4, 2, 3, 3, 1, 2, 128, 133, 89, 47,,,, -6, 6, 4, 2, 3, 3, 1, 2, 256, 133, 89, 47,,,, -6, 6, 4, 2, 3, 3, 1, 2, 384, 133, 89, 47,,,, -6, 6, 4, 2, 3, 3, 1, 3, 128, 133, 89, 47,,,, -6, 6, 4, 2, 3, 3, 1, 3, 256, 133, 89, 47,,,, -6, 6, 4, 2, 3, 3, 1, 3, 384, 133, 89, 47,,,, -6, 6, 4, 2, 3, 3, 2, 1, 128, 133, 89, 47,,,, -6, 6, 4, 2, 3, 3, 2, 1, 256, 133, 89, 47,,,, -6, 6, 4, 2, 3, 3, 2, 1, 384, 133, 89, 47,,,, -6, 6, 4, 2, 3, 3, 2, 2, 128, 133, 89, 47,,,, -6, 6, 4, 2, 3, 3, 2, 2, 256, 133, 89, 47,,,, -6, 6, 4, 2, 3, 3, 2, 2, 384, 133, 89, 47,,,, -6, 6, 4, 2, 3, 3, 2, 3, 128, 133, 89, 47,,,, -6, 6, 4, 2, 3, 3, 2, 3, 256, 133, 89, 47,,,, -6, 6, 4, 2, 3, 3, 2, 3, 384, 133, 89, 47,,,, -6, 6, 4, 2, 3, 3, 3, 1, 128, 133, 89, 47,,,, -6, 6, 4, 2, 3, 3, 3, 1, 256, 133, 89, 47,,,, -6, 6, 4, 2, 3, 3, 3, 1, 384, 133, 89, 47,,,, -6, 6, 4, 2, 3, 3, 3, 2, 128, 133, 89, 47,,,, -6, 6, 4, 2, 3, 3, 3, 2, 256, 133, 89, 47,,,, -6, 6, 4, 2, 3, 3, 3, 2, 384, 133, 89, 47,,,, -6, 6, 4, 2, 3, 3, 3, 3, 128, 133, 89, 47,,,, -6, 6, 4, 2, 3, 3, 3, 3, 256, 133, 89, 47,,,, -6, 6, 4, 2, 3, 3, 3, 3, 384, 133, 89, 47,,,, -6, 6, 4, 3, 1, 1, 1, 1, 128, 197, 131, 68,,,, -6, 6, 4, 3, 1, 1, 1, 1, 256, 197, 131, 68,,,, -6, 6, 4, 3, 1, 1, 1, 1, 384, 197, 131, 68,,,, -6, 6, 4, 3, 2, 2, 1, 1, 128, 197, 131, 68,,,, -6, 6, 4, 3, 2, 2, 1, 1, 256, 197, 131, 68,,,, -6, 6, 4, 3, 2, 2, 1, 1, 384, 197, 131, 68,,,, -6, 6, 4, 3, 2, 2, 1, 2, 128, 197, 131, 68,,,, -6, 6, 4, 3, 2, 2, 1, 2, 256, 197, 131, 68,,,, -6, 6, 4, 3, 2, 2, 1, 2, 384, 197, 131, 68,,,, -6, 6, 4, 3, 2, 2, 2, 1, 128, 197, 131, 68,,,, -6, 6, 4, 3, 2, 2, 2, 1, 256, 197, 131, 68,,,, -6, 6, 4, 3, 2, 2, 2, 1, 384, 197, 131, 68,,,, -6, 6, 4, 3, 2, 2, 2, 2, 128, 197, 131, 68,,,, -6, 6, 4, 3, 2, 2, 2, 2, 256, 197, 131, 68,,,, -6, 6, 4, 3, 2, 2, 2, 2, 384, 197, 131, 68,,,, -6, 6, 4, 3, 3, 3, 1, 1, 128, 197, 131, 68,,,, -6, 6, 4, 3, 3, 3, 1, 1, 256, 197, 131, 68,,,, -6, 6, 4, 3, 3, 3, 1, 1, 384, 197, 131, 68,,,, -6, 6, 4, 3, 3, 3, 1, 2, 128, 197, 131, 68,,,, -6, 6, 4, 3, 3, 3, 1, 2, 256, 197, 131, 68,,,, -6, 6, 4, 3, 3, 3, 1, 2, 384, 197, 131, 68,,,, -6, 6, 4, 3, 3, 3, 1, 3, 128, 197, 131, 68,,,, -6, 6, 4, 3, 3, 3, 1, 3, 256, 197, 131, 68,,,, -6, 6, 4, 3, 3, 3, 1, 3, 384, 197, 131, 68,,,, -6, 6, 4, 3, 3, 3, 2, 1, 128, 197, 131, 68,,,, -6, 6, 4, 3, 3, 3, 2, 1, 256, 197, 131, 68,,,, -6, 6, 4, 3, 3, 3, 2, 1, 384, 197, 131, 68,,,, -6, 6, 4, 3, 3, 3, 2, 2, 128, 197, 131, 68,,,, -6, 6, 4, 3, 3, 3, 2, 2, 256, 197, 131, 68,,,, -6, 6, 4, 3, 3, 3, 2, 2, 384, 197, 131, 68,,,, -6, 6, 4, 3, 3, 3, 2, 3, 128, 197, 131, 68,,,, -6, 6, 4, 3, 3, 3, 2, 3, 256, 197, 131, 68,,,, -6, 6, 4, 3, 3, 3, 2, 3, 384, 197, 131, 68,,,, -6, 6, 4, 3, 3, 3, 3, 1, 128, 197, 131, 68,,,, -6, 6, 4, 3, 3, 3, 3, 1, 256, 197, 131, 68,,,, -6, 6, 4, 3, 3, 3, 3, 1, 384, 197, 131, 68,,,, -6, 6, 4, 3, 3, 3, 3, 2, 128, 197, 131, 68,,,, -6, 6, 4, 3, 3, 3, 3, 2, 256, 197, 131, 68,,,, -6, 6, 4, 3, 3, 3, 3, 2, 384, 197, 131, 68,,,, -6, 6, 4, 3, 3, 3, 3, 3, 128, 197, 131, 68,,,, -6, 6, 4, 3, 3, 3, 3, 3, 256, 197, 131, 68,,,, -6, 6, 4, 3, 3, 3, 3, 3, 384, 197, 131, 68,,,, -6, 6, 4, 4, 1, 1, 1, 1, 128, 240, 173, 89,,,, -6, 6, 4, 4, 1, 1, 1, 1, 256, 240, 173, 89,,,, -6, 6, 4, 4, 1, 1, 1, 1, 384, 240, 173, 89,,,, -6, 6, 4, 4, 2, 2, 1, 1, 128, 240, 173, 89,,,, -6, 6, 4, 4, 2, 2, 1, 1, 256, 240, 173, 89,,,, -6, 6, 4, 4, 2, 2, 1, 1, 384, 240, 173, 89,,,, -6, 6, 4, 4, 2, 2, 1, 2, 128, 240, 173, 89,,,, -6, 6, 4, 4, 2, 2, 1, 2, 256, 240, 173, 89,,,, -6, 6, 4, 4, 2, 2, 1, 2, 384, 240, 173, 89,,,, -6, 6, 4, 4, 2, 2, 2, 1, 128, 240, 173, 89,,,, -6, 6, 4, 4, 2, 2, 2, 1, 256, 240, 173, 89,,,, -6, 6, 4, 4, 2, 2, 2, 1, 384, 240, 173, 89,,,, -6, 6, 4, 4, 2, 2, 2, 2, 128, 240, 173, 89,,,, -6, 6, 4, 4, 2, 2, 2, 2, 256, 240, 173, 89,,,, -6, 6, 4, 4, 2, 2, 2, 2, 384, 240, 173, 89,,,, -6, 6, 4, 4, 3, 3, 1, 1, 128, 240, 173, 89,,,, -6, 6, 4, 4, 3, 3, 1, 1, 256, 240, 173, 89,,,, -6, 6, 4, 4, 3, 3, 1, 1, 384, 240, 173, 89,,,, -6, 6, 4, 4, 3, 3, 1, 2, 128, 240, 173, 89,,,, -6, 6, 4, 4, 3, 3, 1, 2, 256, 240, 173, 89,,,, -6, 6, 4, 4, 3, 3, 1, 2, 384, 240, 173, 89,,,, -6, 6, 4, 4, 3, 3, 1, 3, 128, 240, 173, 89,,,, -6, 6, 4, 4, 3, 3, 1, 3, 256, 240, 173, 89,,,, -6, 6, 4, 4, 3, 3, 1, 3, 384, 240, 173, 89,,,, -6, 6, 4, 4, 3, 3, 2, 1, 128, 240, 173, 89,,,, -6, 6, 4, 4, 3, 3, 2, 1, 256, 240, 173, 89,,,, -6, 6, 4, 4, 3, 3, 2, 1, 384, 240, 173, 89,,,, -6, 6, 4, 4, 3, 3, 2, 2, 128, 240, 173, 89,,,, -6, 6, 4, 4, 3, 3, 2, 2, 256, 240, 173, 89,,,, -6, 6, 4, 4, 3, 3, 2, 2, 384, 240, 173, 89,,,, -6, 6, 4, 4, 3, 3, 2, 3, 128, 240, 173, 89,,,, -6, 6, 4, 4, 3, 3, 2, 3, 256, 240, 173, 89,,,, -6, 6, 4, 4, 3, 3, 2, 3, 384, 240, 173, 89,,,, -6, 6, 4, 4, 3, 3, 3, 1, 128, 240, 173, 89,,,, -6, 6, 4, 4, 3, 3, 3, 1, 256, 240, 173, 89,,,, -6, 6, 4, 4, 3, 3, 3, 1, 384, 240, 173, 89,,,, -6, 6, 4, 4, 3, 3, 3, 2, 128, 240, 173, 89,,,, -6, 6, 4, 4, 3, 3, 3, 2, 256, 240, 173, 89,,,, -6, 6, 4, 4, 3, 3, 3, 2, 384, 240, 173, 89,,,, -6, 6, 4, 4, 3, 3, 3, 3, 128, 240, 173, 89,,,, -6, 6, 4, 4, 3, 3, 3, 3, 256, 240, 173, 89,,,, -6, 6, 4, 4, 3, 3, 3, 3, 384, 240, 173, 89,,,, -6, 6, 4, 5, 1, 1, 1, 1, 128, 240, 215, 110,,,, -6, 6, 4, 5, 1, 1, 1, 1, 256, 240, 215, 110,,,, -6, 6, 4, 5, 1, 1, 1, 1, 384, 240, 215, 110,,,, -6, 6, 4, 5, 2, 2, 1, 1, 128, 240, 215, 110,,,, -6, 6, 4, 5, 2, 2, 1, 1, 256, 240, 215, 110,,,, -6, 6, 4, 5, 2, 2, 1, 1, 384, 240, 215, 110,,,, -6, 6, 4, 5, 2, 2, 1, 2, 128, 240, 215, 110,,,, -6, 6, 4, 5, 2, 2, 1, 2, 256, 240, 215, 110,,,, -6, 6, 4, 5, 2, 2, 1, 2, 384, 240, 215, 110,,,, -6, 6, 4, 5, 2, 2, 2, 1, 128, 240, 215, 110,,,, -6, 6, 4, 5, 2, 2, 2, 1, 256, 240, 215, 110,,,, -6, 6, 4, 5, 2, 2, 2, 1, 384, 240, 215, 110,,,, -6, 6, 4, 5, 2, 2, 2, 2, 128, 240, 215, 110,,,, -6, 6, 4, 5, 2, 2, 2, 2, 256, 240, 215, 110,,,, -6, 6, 4, 5, 2, 2, 2, 2, 384, 240, 215, 110,,,, -6, 6, 4, 5, 3, 3, 1, 1, 128, 240, 215, 110,,,, -6, 6, 4, 5, 3, 3, 1, 1, 256, 240, 215, 110,,,, -6, 6, 4, 5, 3, 3, 1, 1, 384, 240, 215, 110,,,, -6, 6, 4, 5, 3, 3, 1, 2, 128, 240, 215, 110,,,, -6, 6, 4, 5, 3, 3, 1, 2, 256, 240, 215, 110,,,, -6, 6, 4, 5, 3, 3, 1, 2, 384, 240, 215, 110,,,, -6, 6, 4, 5, 3, 3, 1, 3, 128, 240, 215, 110,,,, -6, 6, 4, 5, 3, 3, 1, 3, 256, 240, 215, 110,,,, -6, 6, 4, 5, 3, 3, 1, 3, 384, 240, 215, 110,,,, -6, 6, 4, 5, 3, 3, 2, 1, 128, 240, 215, 110,,,, -6, 6, 4, 5, 3, 3, 2, 1, 256, 240, 215, 110,,,, -6, 6, 4, 5, 3, 3, 2, 1, 384, 240, 215, 110,,,, -6, 6, 4, 5, 3, 3, 2, 2, 128, 240, 215, 110,,,, -6, 6, 4, 5, 3, 3, 2, 2, 256, 240, 215, 110,,,, -6, 6, 4, 5, 3, 3, 2, 2, 384, 240, 215, 110,,,, -6, 6, 4, 5, 3, 3, 2, 3, 128, 240, 215, 110,,,, -6, 6, 4, 5, 3, 3, 2, 3, 256, 240, 215, 110,,,, -6, 6, 4, 5, 3, 3, 2, 3, 384, 240, 215, 110,,,, -6, 6, 4, 5, 3, 3, 3, 1, 128, 240, 215, 110,,,, -6, 6, 4, 5, 3, 3, 3, 1, 256, 240, 215, 110,,,, -6, 6, 4, 5, 3, 3, 3, 1, 384, 240, 215, 110,,,, -6, 6, 4, 5, 3, 3, 3, 2, 128, 240, 215, 110,,,, -6, 6, 4, 5, 3, 3, 3, 2, 256, 240, 215, 110,,,, -6, 6, 4, 5, 3, 3, 3, 2, 384, 240, 215, 110,,,, -6, 6, 4, 5, 3, 3, 3, 3, 128, 240, 215, 110,,,, -6, 6, 4, 5, 3, 3, 3, 3, 256, 240, 215, 110,,,, -6, 6, 4, 5, 3, 3, 3, 3, 384, 240, 215, 110,,,, -6, 6, 4, 6, 1, 1, 1, 1, 128, 240, 240, 131,,,, -6, 6, 4, 6, 1, 1, 1, 1, 256, 240, 240, 131,,,, -6, 6, 4, 6, 1, 1, 1, 1, 384, 240, 240, 131,,,, -6, 6, 4, 6, 2, 2, 1, 1, 128, 240, 240, 131,,,, -6, 6, 4, 6, 2, 2, 1, 1, 256, 240, 240, 131,,,, -6, 6, 4, 6, 2, 2, 1, 1, 384, 240, 240, 131,,,, -6, 6, 4, 6, 2, 2, 1, 2, 128, 240, 240, 131,,,, -6, 6, 4, 6, 2, 2, 1, 2, 256, 240, 240, 131,,,, -6, 6, 4, 6, 2, 2, 1, 2, 384, 240, 240, 131,,,, -6, 6, 4, 6, 2, 2, 2, 1, 128, 240, 240, 131,,,, -6, 6, 4, 6, 2, 2, 2, 1, 256, 240, 240, 131,,,, -6, 6, 4, 6, 2, 2, 2, 1, 384, 240, 240, 131,,,, -6, 6, 4, 6, 2, 2, 2, 2, 128, 240, 240, 131,,,, -6, 6, 4, 6, 2, 2, 2, 2, 256, 240, 240, 131,,,, -6, 6, 4, 6, 2, 2, 2, 2, 384, 240, 240, 131,,,, -6, 6, 4, 6, 3, 3, 1, 1, 128, 240, 240, 131,,,, -6, 6, 4, 6, 3, 3, 1, 1, 256, 240, 240, 131,,,, -6, 6, 4, 6, 3, 3, 1, 1, 384, 240, 240, 131,,,, -6, 6, 4, 6, 3, 3, 1, 2, 128, 240, 240, 131,,,, -6, 6, 4, 6, 3, 3, 1, 2, 256, 240, 240, 131,,,, -6, 6, 4, 6, 3, 3, 1, 2, 384, 240, 240, 131,,,, -6, 6, 4, 6, 3, 3, 1, 3, 128, 240, 240, 131,,,, -6, 6, 4, 6, 3, 3, 1, 3, 256, 240, 240, 131,,,, -6, 6, 4, 6, 3, 3, 1, 3, 384, 240, 240, 131,,,, -6, 6, 4, 6, 3, 3, 2, 1, 128, 240, 240, 131,,,, -6, 6, 4, 6, 3, 3, 2, 1, 256, 240, 240, 131,,,, -6, 6, 4, 6, 3, 3, 2, 1, 384, 240, 240, 131,,,, -6, 6, 4, 6, 3, 3, 2, 2, 128, 240, 240, 131,,,, -6, 6, 4, 6, 3, 3, 2, 2, 256, 240, 240, 131,,,, -6, 6, 4, 6, 3, 3, 2, 2, 384, 240, 240, 131,,,, -6, 6, 4, 6, 3, 3, 2, 3, 128, 240, 240, 131,,,, -6, 6, 4, 6, 3, 3, 2, 3, 256, 240, 240, 131,,,, -6, 6, 4, 6, 3, 3, 2, 3, 384, 240, 240, 131,,,, -6, 6, 4, 6, 3, 3, 3, 1, 128, 240, 240, 131,,,, -6, 6, 4, 6, 3, 3, 3, 1, 256, 240, 240, 131,,,, -6, 6, 4, 6, 3, 3, 3, 1, 384, 240, 240, 131,,,, -6, 6, 4, 6, 3, 3, 3, 2, 128, 240, 240, 131,,,, -6, 6, 4, 6, 3, 3, 3, 2, 256, 240, 240, 131,,,, -6, 6, 4, 6, 3, 3, 3, 2, 384, 240, 240, 131,,,, -6, 6, 4, 6, 3, 3, 3, 3, 128, 240, 240, 131,,,, -6, 6, 4, 6, 3, 3, 3, 3, 256, 240, 240, 131,,,, -6, 6, 4, 6, 3, 3, 3, 3, 384, 240, 240, 131,,,, -6, 6, 5, 1, 1, 1, 1, 1, 128, 69, 47, 26,,,, -6, 6, 5, 1, 1, 1, 1, 1, 256, 69, 47, 26,,,, -6, 6, 5, 1, 1, 1, 1, 1, 384, 69, 47, 26,,,, -6, 6, 5, 1, 2, 2, 1, 1, 128, 69, 47, 26,,,, -6, 6, 5, 1, 2, 2, 1, 1, 256, 69, 47, 26,,,, -6, 6, 5, 1, 2, 2, 1, 1, 384, 69, 47, 26,,,, -6, 6, 5, 1, 2, 2, 1, 2, 128, 69, 47, 26,,,, -6, 6, 5, 1, 2, 2, 1, 2, 256, 69, 47, 26,,,, -6, 6, 5, 1, 2, 2, 1, 2, 384, 69, 47, 26,,,, -6, 6, 5, 1, 2, 2, 2, 1, 128, 69, 47, 26,,,, -6, 6, 5, 1, 2, 2, 2, 1, 256, 69, 47, 26,,,, -6, 6, 5, 1, 2, 2, 2, 1, 384, 69, 47, 26,,,, -6, 6, 5, 1, 2, 2, 2, 2, 128, 69, 47, 26,,,, -6, 6, 5, 1, 2, 2, 2, 2, 256, 69, 47, 26,,,, -6, 6, 5, 1, 2, 2, 2, 2, 384, 69, 47, 26,,,, -6, 6, 5, 1, 3, 3, 1, 1, 128, 69, 47, 26,,,, -6, 6, 5, 1, 3, 3, 1, 1, 256, 69, 47, 26,,,, -6, 6, 5, 1, 3, 3, 1, 1, 384, 69, 47, 26,,,, -6, 6, 5, 1, 3, 3, 1, 2, 128, 69, 47, 26,,,, -6, 6, 5, 1, 3, 3, 1, 2, 256, 69, 47, 26,,,, -6, 6, 5, 1, 3, 3, 1, 2, 384, 69, 47, 26,,,, -6, 6, 5, 1, 3, 3, 1, 3, 128, 69, 47, 26,,,, -6, 6, 5, 1, 3, 3, 1, 3, 256, 69, 47, 26,,,, -6, 6, 5, 1, 3, 3, 1, 3, 384, 69, 47, 26,,,, -6, 6, 5, 1, 3, 3, 2, 1, 128, 69, 47, 26,,,, -6, 6, 5, 1, 3, 3, 2, 1, 256, 69, 47, 26,,,, -6, 6, 5, 1, 3, 3, 2, 1, 384, 69, 47, 26,,,, -6, 6, 5, 1, 3, 3, 2, 2, 128, 69, 47, 26,,,, -6, 6, 5, 1, 3, 3, 2, 2, 256, 69, 47, 26,,,, -6, 6, 5, 1, 3, 3, 2, 2, 384, 69, 47, 26,,,, -6, 6, 5, 1, 3, 3, 2, 3, 128, 69, 47, 26,,,, -6, 6, 5, 1, 3, 3, 2, 3, 256, 69, 47, 26,,,, -6, 6, 5, 1, 3, 3, 2, 3, 384, 69, 47, 26,,,, -6, 6, 5, 1, 3, 3, 3, 1, 128, 69, 47, 26,,,, -6, 6, 5, 1, 3, 3, 3, 1, 256, 69, 47, 26,,,, -6, 6, 5, 1, 3, 3, 3, 1, 384, 69, 47, 26,,,, -6, 6, 5, 1, 3, 3, 3, 2, 128, 69, 47, 26,,,, -6, 6, 5, 1, 3, 3, 3, 2, 256, 69, 47, 26,,,, -6, 6, 5, 1, 3, 3, 3, 2, 384, 69, 47, 26,,,, -6, 6, 5, 1, 3, 3, 3, 3, 128, 69, 47, 26,,,, -6, 6, 5, 1, 3, 3, 3, 3, 256, 69, 47, 26,,,, -6, 6, 5, 1, 3, 3, 3, 3, 384, 69, 47, 26,,,, -6, 6, 5, 2, 1, 1, 1, 1, 128, 133, 89, 47,,,, -6, 6, 5, 2, 1, 1, 1, 1, 256, 133, 89, 47,,,, -6, 6, 5, 2, 1, 1, 1, 1, 384, 133, 89, 47,,,, -6, 6, 5, 2, 2, 2, 1, 1, 128, 133, 89, 47,,,, -6, 6, 5, 2, 2, 2, 1, 1, 256, 133, 89, 47,,,, -6, 6, 5, 2, 2, 2, 1, 1, 384, 133, 89, 47,,,, -6, 6, 5, 2, 2, 2, 1, 2, 128, 133, 89, 47,,,, -6, 6, 5, 2, 2, 2, 1, 2, 256, 133, 89, 47,,,, -6, 6, 5, 2, 2, 2, 1, 2, 384, 133, 89, 47,,,, -6, 6, 5, 2, 2, 2, 2, 1, 128, 133, 89, 47,,,, -6, 6, 5, 2, 2, 2, 2, 1, 256, 133, 89, 47,,,, -6, 6, 5, 2, 2, 2, 2, 1, 384, 133, 89, 47,,,, -6, 6, 5, 2, 2, 2, 2, 2, 128, 133, 89, 47,,,, -6, 6, 5, 2, 2, 2, 2, 2, 256, 133, 89, 47,,,, -6, 6, 5, 2, 2, 2, 2, 2, 384, 133, 89, 47,,,, -6, 6, 5, 2, 3, 3, 1, 1, 128, 133, 89, 47,,,, -6, 6, 5, 2, 3, 3, 1, 1, 256, 133, 89, 47,,,, -6, 6, 5, 2, 3, 3, 1, 1, 384, 133, 89, 47,,,, -6, 6, 5, 2, 3, 3, 1, 2, 128, 133, 89, 47,,,, -6, 6, 5, 2, 3, 3, 1, 2, 256, 133, 89, 47,,,, -6, 6, 5, 2, 3, 3, 1, 2, 384, 133, 89, 47,,,, -6, 6, 5, 2, 3, 3, 1, 3, 128, 133, 89, 47,,,, -6, 6, 5, 2, 3, 3, 1, 3, 256, 133, 89, 47,,,, -6, 6, 5, 2, 3, 3, 1, 3, 384, 133, 89, 47,,,, -6, 6, 5, 2, 3, 3, 2, 1, 128, 133, 89, 47,,,, -6, 6, 5, 2, 3, 3, 2, 1, 256, 133, 89, 47,,,, -6, 6, 5, 2, 3, 3, 2, 1, 384, 133, 89, 47,,,, -6, 6, 5, 2, 3, 3, 2, 2, 128, 133, 89, 47,,,, -6, 6, 5, 2, 3, 3, 2, 2, 256, 133, 89, 47,,,, -6, 6, 5, 2, 3, 3, 2, 2, 384, 133, 89, 47,,,, -6, 6, 5, 2, 3, 3, 2, 3, 128, 133, 89, 47,,,, -6, 6, 5, 2, 3, 3, 2, 3, 256, 133, 89, 47,,,, -6, 6, 5, 2, 3, 3, 2, 3, 384, 133, 89, 47,,,, -6, 6, 5, 2, 3, 3, 3, 1, 128, 133, 89, 47,,,, -6, 6, 5, 2, 3, 3, 3, 1, 256, 133, 89, 47,,,, -6, 6, 5, 2, 3, 3, 3, 1, 384, 133, 89, 47,,,, -6, 6, 5, 2, 3, 3, 3, 2, 128, 133, 89, 47,,,, -6, 6, 5, 2, 3, 3, 3, 2, 256, 133, 89, 47,,,, -6, 6, 5, 2, 3, 3, 3, 2, 384, 133, 89, 47,,,, -6, 6, 5, 2, 3, 3, 3, 3, 128, 133, 89, 47,,,, -6, 6, 5, 2, 3, 3, 3, 3, 256, 133, 89, 47,,,, -6, 6, 5, 2, 3, 3, 3, 3, 384, 133, 89, 47,,,, -6, 6, 5, 3, 1, 1, 1, 1, 128, 197, 131, 68,,,, -6, 6, 5, 3, 1, 1, 1, 1, 256, 197, 131, 68,,,, -6, 6, 5, 3, 1, 1, 1, 1, 384, 197, 131, 68,,,, -6, 6, 5, 3, 2, 2, 1, 1, 128, 197, 131, 68,,,, -6, 6, 5, 3, 2, 2, 1, 1, 256, 197, 131, 68,,,, -6, 6, 5, 3, 2, 2, 1, 1, 384, 197, 131, 68,,,, -6, 6, 5, 3, 2, 2, 1, 2, 128, 197, 131, 68,,,, -6, 6, 5, 3, 2, 2, 1, 2, 256, 197, 131, 68,,,, -6, 6, 5, 3, 2, 2, 1, 2, 384, 197, 131, 68,,,, -6, 6, 5, 3, 2, 2, 2, 1, 128, 197, 131, 68,,,, -6, 6, 5, 3, 2, 2, 2, 1, 256, 197, 131, 68,,,, -6, 6, 5, 3, 2, 2, 2, 1, 384, 197, 131, 68,,,, -6, 6, 5, 3, 2, 2, 2, 2, 128, 197, 131, 68,,,, -6, 6, 5, 3, 2, 2, 2, 2, 256, 197, 131, 68,,,, -6, 6, 5, 3, 2, 2, 2, 2, 384, 197, 131, 68,,,, -6, 6, 5, 3, 3, 3, 1, 1, 128, 197, 131, 68,,,, -6, 6, 5, 3, 3, 3, 1, 1, 256, 197, 131, 68,,,, -6, 6, 5, 3, 3, 3, 1, 1, 384, 197, 131, 68,,,, -6, 6, 5, 3, 3, 3, 1, 2, 128, 197, 131, 68,,,, -6, 6, 5, 3, 3, 3, 1, 2, 256, 197, 131, 68,,,, -6, 6, 5, 3, 3, 3, 1, 2, 384, 197, 131, 68,,,, -6, 6, 5, 3, 3, 3, 1, 3, 128, 197, 131, 68,,,, -6, 6, 5, 3, 3, 3, 1, 3, 256, 197, 131, 68,,,, -6, 6, 5, 3, 3, 3, 1, 3, 384, 197, 131, 68,,,, -6, 6, 5, 3, 3, 3, 2, 1, 128, 197, 131, 68,,,, -6, 6, 5, 3, 3, 3, 2, 1, 256, 197, 131, 68,,,, -6, 6, 5, 3, 3, 3, 2, 1, 384, 197, 131, 68,,,, -6, 6, 5, 3, 3, 3, 2, 2, 128, 197, 131, 68,,,, -6, 6, 5, 3, 3, 3, 2, 2, 256, 197, 131, 68,,,, -6, 6, 5, 3, 3, 3, 2, 2, 384, 197, 131, 68,,,, -6, 6, 5, 3, 3, 3, 2, 3, 128, 197, 131, 68,,,, -6, 6, 5, 3, 3, 3, 2, 3, 256, 197, 131, 68,,,, -6, 6, 5, 3, 3, 3, 2, 3, 384, 197, 131, 68,,,, -6, 6, 5, 3, 3, 3, 3, 1, 128, 197, 131, 68,,,, -6, 6, 5, 3, 3, 3, 3, 1, 256, 197, 131, 68,,,, -6, 6, 5, 3, 3, 3, 3, 1, 384, 197, 131, 68,,,, -6, 6, 5, 3, 3, 3, 3, 2, 128, 197, 131, 68,,,, -6, 6, 5, 3, 3, 3, 3, 2, 256, 197, 131, 68,,,, -6, 6, 5, 3, 3, 3, 3, 2, 384, 197, 131, 68,,,, -6, 6, 5, 3, 3, 3, 3, 3, 128, 197, 131, 68,,,, -6, 6, 5, 3, 3, 3, 3, 3, 256, 197, 131, 68,,,, -6, 6, 5, 3, 3, 3, 3, 3, 384, 197, 131, 68,,,, -6, 6, 5, 4, 1, 1, 1, 1, 128, 240, 173, 89,,,, -6, 6, 5, 4, 1, 1, 1, 1, 256, 240, 173, 89,,,, -6, 6, 5, 4, 1, 1, 1, 1, 384, 240, 173, 89,,,, -6, 6, 5, 4, 2, 2, 1, 1, 128, 240, 173, 89,,,, -6, 6, 5, 4, 2, 2, 1, 1, 256, 240, 173, 89,,,, -6, 6, 5, 4, 2, 2, 1, 1, 384, 240, 173, 89,,,, -6, 6, 5, 4, 2, 2, 1, 2, 128, 240, 173, 89,,,, -6, 6, 5, 4, 2, 2, 1, 2, 256, 240, 173, 89,,,, -6, 6, 5, 4, 2, 2, 1, 2, 384, 240, 173, 89,,,, -6, 6, 5, 4, 2, 2, 2, 1, 128, 240, 173, 89,,,, -6, 6, 5, 4, 2, 2, 2, 1, 256, 240, 173, 89,,,, -6, 6, 5, 4, 2, 2, 2, 1, 384, 240, 173, 89,,,, -6, 6, 5, 4, 2, 2, 2, 2, 128, 240, 173, 89,,,, -6, 6, 5, 4, 2, 2, 2, 2, 256, 240, 173, 89,,,, -6, 6, 5, 4, 2, 2, 2, 2, 384, 240, 173, 89,,,, -6, 6, 5, 4, 3, 3, 1, 1, 128, 240, 173, 89,,,, -6, 6, 5, 4, 3, 3, 1, 1, 256, 240, 173, 89,,,, -6, 6, 5, 4, 3, 3, 1, 1, 384, 240, 173, 89,,,, -6, 6, 5, 4, 3, 3, 1, 2, 128, 240, 173, 89,,,, -6, 6, 5, 4, 3, 3, 1, 2, 256, 240, 173, 89,,,, -6, 6, 5, 4, 3, 3, 1, 2, 384, 240, 173, 89,,,, -6, 6, 5, 4, 3, 3, 1, 3, 128, 240, 173, 89,,,, -6, 6, 5, 4, 3, 3, 1, 3, 256, 240, 173, 89,,,, -6, 6, 5, 4, 3, 3, 1, 3, 384, 240, 173, 89,,,, -6, 6, 5, 4, 3, 3, 2, 1, 128, 240, 173, 89,,,, -6, 6, 5, 4, 3, 3, 2, 1, 256, 240, 173, 89,,,, -6, 6, 5, 4, 3, 3, 2, 1, 384, 240, 173, 89,,,, -6, 6, 5, 4, 3, 3, 2, 2, 128, 240, 173, 89,,,, -6, 6, 5, 4, 3, 3, 2, 2, 256, 240, 173, 89,,,, -6, 6, 5, 4, 3, 3, 2, 2, 384, 240, 173, 89,,,, -6, 6, 5, 4, 3, 3, 2, 3, 128, 240, 173, 89,,,, -6, 6, 5, 4, 3, 3, 2, 3, 256, 240, 173, 89,,,, -6, 6, 5, 4, 3, 3, 2, 3, 384, 240, 173, 89,,,, -6, 6, 5, 4, 3, 3, 3, 1, 128, 240, 173, 89,,,, -6, 6, 5, 4, 3, 3, 3, 1, 256, 240, 173, 89,,,, -6, 6, 5, 4, 3, 3, 3, 1, 384, 240, 173, 89,,,, -6, 6, 5, 4, 3, 3, 3, 2, 128, 240, 173, 89,,,, -6, 6, 5, 4, 3, 3, 3, 2, 256, 240, 173, 89,,,, -6, 6, 5, 4, 3, 3, 3, 2, 384, 240, 173, 89,,,, -6, 6, 5, 4, 3, 3, 3, 3, 128, 240, 173, 89,,,, -6, 6, 5, 4, 3, 3, 3, 3, 256, 240, 173, 89,,,, -6, 6, 5, 4, 3, 3, 3, 3, 384, 240, 173, 89,,,, -6, 6, 5, 5, 1, 1, 1, 1, 128, 240, 215, 110,,,, -6, 6, 5, 5, 1, 1, 1, 1, 256, 240, 215, 110,,,, -6, 6, 5, 5, 1, 1, 1, 1, 384, 240, 215, 110,,,, -6, 6, 5, 5, 2, 2, 1, 1, 128, 240, 215, 110,,,, -6, 6, 5, 5, 2, 2, 1, 1, 256, 240, 215, 110,,,, -6, 6, 5, 5, 2, 2, 1, 1, 384, 240, 215, 110,,,, -6, 6, 5, 5, 2, 2, 1, 2, 128, 240, 215, 110,,,, -6, 6, 5, 5, 2, 2, 1, 2, 256, 240, 215, 110,,,, -6, 6, 5, 5, 2, 2, 1, 2, 384, 240, 215, 110,,,, -6, 6, 5, 5, 2, 2, 2, 1, 128, 240, 215, 110,,,, -6, 6, 5, 5, 2, 2, 2, 1, 256, 240, 215, 110,,,, -6, 6, 5, 5, 2, 2, 2, 1, 384, 240, 215, 110,,,, -6, 6, 5, 5, 2, 2, 2, 2, 128, 240, 215, 110,,,, -6, 6, 5, 5, 2, 2, 2, 2, 256, 240, 215, 110,,,, -6, 6, 5, 5, 2, 2, 2, 2, 384, 240, 215, 110,,,, -6, 6, 5, 5, 3, 3, 1, 1, 128, 240, 215, 110,,,, -6, 6, 5, 5, 3, 3, 1, 1, 256, 240, 215, 110,,,, -6, 6, 5, 5, 3, 3, 1, 1, 384, 240, 215, 110,,,, -6, 6, 5, 5, 3, 3, 1, 2, 128, 240, 215, 110,,,, -6, 6, 5, 5, 3, 3, 1, 2, 256, 240, 215, 110,,,, -6, 6, 5, 5, 3, 3, 1, 2, 384, 240, 215, 110,,,, -6, 6, 5, 5, 3, 3, 1, 3, 128, 240, 215, 110,,,, -6, 6, 5, 5, 3, 3, 1, 3, 256, 240, 215, 110,,,, -6, 6, 5, 5, 3, 3, 1, 3, 384, 240, 215, 110,,,, -6, 6, 5, 5, 3, 3, 2, 1, 128, 240, 215, 110,,,, -6, 6, 5, 5, 3, 3, 2, 1, 256, 240, 215, 110,,,, -6, 6, 5, 5, 3, 3, 2, 1, 384, 240, 215, 110,,,, -6, 6, 5, 5, 3, 3, 2, 2, 128, 240, 215, 110,,,, -6, 6, 5, 5, 3, 3, 2, 2, 256, 240, 215, 110,,,, -6, 6, 5, 5, 3, 3, 2, 2, 384, 240, 215, 110,,,, -6, 6, 5, 5, 3, 3, 2, 3, 128, 240, 215, 110,,,, -6, 6, 5, 5, 3, 3, 2, 3, 256, 240, 215, 110,,,, -6, 6, 5, 5, 3, 3, 2, 3, 384, 240, 215, 110,,,, -6, 6, 5, 5, 3, 3, 3, 1, 128, 240, 215, 110,,,, -6, 6, 5, 5, 3, 3, 3, 1, 256, 240, 215, 110,,,, -6, 6, 5, 5, 3, 3, 3, 1, 384, 240, 215, 110,,,, -6, 6, 5, 5, 3, 3, 3, 2, 128, 240, 215, 110,,,, -6, 6, 5, 5, 3, 3, 3, 2, 256, 240, 215, 110,,,, -6, 6, 5, 5, 3, 3, 3, 2, 384, 240, 215, 110,,,, -6, 6, 5, 5, 3, 3, 3, 3, 128, 240, 215, 110,,,, -6, 6, 5, 5, 3, 3, 3, 3, 256, 240, 215, 110,,,, -6, 6, 5, 5, 3, 3, 3, 3, 384, 240, 215, 110,,,, -6, 6, 5, 6, 1, 1, 1, 1, 128, 240, 240, 131,,,, -6, 6, 5, 6, 1, 1, 1, 1, 256, 240, 240, 131,,,, -6, 6, 5, 6, 1, 1, 1, 1, 384, 240, 240, 131,,,, -6, 6, 5, 6, 2, 2, 1, 1, 128, 240, 240, 131,,,, -6, 6, 5, 6, 2, 2, 1, 1, 256, 240, 240, 131,,,, -6, 6, 5, 6, 2, 2, 1, 1, 384, 240, 240, 131,,,, -6, 6, 5, 6, 2, 2, 1, 2, 128, 240, 240, 131,,,, -6, 6, 5, 6, 2, 2, 1, 2, 256, 240, 240, 131,,,, -6, 6, 5, 6, 2, 2, 1, 2, 384, 240, 240, 131,,,, -6, 6, 5, 6, 2, 2, 2, 1, 128, 240, 240, 131,,,, -6, 6, 5, 6, 2, 2, 2, 1, 256, 240, 240, 131,,,, -6, 6, 5, 6, 2, 2, 2, 1, 384, 240, 240, 131,,,, -6, 6, 5, 6, 2, 2, 2, 2, 128, 240, 240, 131,,,, -6, 6, 5, 6, 2, 2, 2, 2, 256, 240, 240, 131,,,, -6, 6, 5, 6, 2, 2, 2, 2, 384, 240, 240, 131,,,, -6, 6, 5, 6, 3, 3, 1, 1, 128, 240, 240, 131,,,, -6, 6, 5, 6, 3, 3, 1, 1, 256, 240, 240, 131,,,, -6, 6, 5, 6, 3, 3, 1, 1, 384, 240, 240, 131,,,, -6, 6, 5, 6, 3, 3, 1, 2, 128, 240, 240, 131,,,, -6, 6, 5, 6, 3, 3, 1, 2, 256, 240, 240, 131,,,, -6, 6, 5, 6, 3, 3, 1, 2, 384, 240, 240, 131,,,, -6, 6, 5, 6, 3, 3, 1, 3, 128, 240, 240, 131,,,, -6, 6, 5, 6, 3, 3, 1, 3, 256, 240, 240, 131,,,, -6, 6, 5, 6, 3, 3, 1, 3, 384, 240, 240, 131,,,, -6, 6, 5, 6, 3, 3, 2, 1, 128, 240, 240, 131,,,, -6, 6, 5, 6, 3, 3, 2, 1, 256, 240, 240, 131,,,, -6, 6, 5, 6, 3, 3, 2, 1, 384, 240, 240, 131,,,, -6, 6, 5, 6, 3, 3, 2, 2, 128, 240, 240, 131,,,, -6, 6, 5, 6, 3, 3, 2, 2, 256, 240, 240, 131,,,, -6, 6, 5, 6, 3, 3, 2, 2, 384, 240, 240, 131,,,, -6, 6, 5, 6, 3, 3, 2, 3, 128, 240, 240, 131,,,, -6, 6, 5, 6, 3, 3, 2, 3, 256, 240, 240, 131,,,, -6, 6, 5, 6, 3, 3, 2, 3, 384, 240, 240, 131,,,, -6, 6, 5, 6, 3, 3, 3, 1, 128, 240, 240, 131,,,, -6, 6, 5, 6, 3, 3, 3, 1, 256, 240, 240, 131,,,, -6, 6, 5, 6, 3, 3, 3, 1, 384, 240, 240, 131,,,, -6, 6, 5, 6, 3, 3, 3, 2, 128, 240, 240, 131,,,, -6, 6, 5, 6, 3, 3, 3, 2, 256, 240, 240, 131,,,, -6, 6, 5, 6, 3, 3, 3, 2, 384, 240, 240, 131,,,, -6, 6, 5, 6, 3, 3, 3, 3, 128, 240, 240, 131,,,, -6, 6, 5, 6, 3, 3, 3, 3, 256, 240, 240, 131,,,, -6, 6, 5, 6, 3, 3, 3, 3, 384, 240, 240, 131,,,, -6, 6, 6, 1, 1, 1, 1, 1, 128, 69, 47, 26,,,, -6, 6, 6, 1, 1, 1, 1, 1, 256, 69, 47, 26,,,, -6, 6, 6, 1, 1, 1, 1, 1, 384, 69, 47, 26,,,, -6, 6, 6, 1, 2, 2, 1, 1, 128, 69, 47, 26,,,, -6, 6, 6, 1, 2, 2, 1, 1, 256, 69, 47, 26,,,, -6, 6, 6, 1, 2, 2, 1, 1, 384, 69, 47, 26,,,, -6, 6, 6, 1, 2, 2, 1, 2, 128, 69, 47, 26,,,, -6, 6, 6, 1, 2, 2, 1, 2, 256, 69, 47, 26,,,, -6, 6, 6, 1, 2, 2, 1, 2, 384, 69, 47, 26,,,, -6, 6, 6, 1, 2, 2, 2, 1, 128, 69, 47, 26,,,, -6, 6, 6, 1, 2, 2, 2, 1, 256, 69, 47, 26,,,, -6, 6, 6, 1, 2, 2, 2, 1, 384, 69, 47, 26,,,, -6, 6, 6, 1, 2, 2, 2, 2, 128, 69, 47, 26,,,, -6, 6, 6, 1, 2, 2, 2, 2, 256, 69, 47, 26,,,, -6, 6, 6, 1, 2, 2, 2, 2, 384, 69, 47, 26,,,, -6, 6, 6, 1, 3, 3, 1, 1, 128, 69, 47, 26,,,, -6, 6, 6, 1, 3, 3, 1, 1, 256, 69, 47, 26,,,, -6, 6, 6, 1, 3, 3, 1, 1, 384, 69, 47, 26,,,, -6, 6, 6, 1, 3, 3, 1, 2, 128, 69, 47, 26,,,, -6, 6, 6, 1, 3, 3, 1, 2, 256, 69, 47, 26,,,, -6, 6, 6, 1, 3, 3, 1, 2, 384, 69, 47, 26,,,, -6, 6, 6, 1, 3, 3, 1, 3, 128, 69, 47, 26,,,, -6, 6, 6, 1, 3, 3, 1, 3, 256, 69, 47, 26,,,, -6, 6, 6, 1, 3, 3, 1, 3, 384, 69, 47, 26,,,, -6, 6, 6, 1, 3, 3, 2, 1, 128, 69, 47, 26,,,, -6, 6, 6, 1, 3, 3, 2, 1, 256, 69, 47, 26,,,, -6, 6, 6, 1, 3, 3, 2, 1, 384, 69, 47, 26,,,, -6, 6, 6, 1, 3, 3, 2, 2, 128, 69, 47, 26,,,, -6, 6, 6, 1, 3, 3, 2, 2, 256, 69, 47, 26,,,, -6, 6, 6, 1, 3, 3, 2, 2, 384, 69, 47, 26,,,, -6, 6, 6, 1, 3, 3, 2, 3, 128, 69, 47, 26,,,, -6, 6, 6, 1, 3, 3, 2, 3, 256, 69, 47, 26,,,, -6, 6, 6, 1, 3, 3, 2, 3, 384, 69, 47, 26,,,, -6, 6, 6, 1, 3, 3, 3, 1, 128, 69, 47, 26,,,, -6, 6, 6, 1, 3, 3, 3, 1, 256, 69, 47, 26,,,, -6, 6, 6, 1, 3, 3, 3, 1, 384, 69, 47, 26,,,, -6, 6, 6, 1, 3, 3, 3, 2, 128, 69, 47, 26,,,, -6, 6, 6, 1, 3, 3, 3, 2, 256, 69, 47, 26,,,, -6, 6, 6, 1, 3, 3, 3, 2, 384, 69, 47, 26,,,, -6, 6, 6, 1, 3, 3, 3, 3, 128, 69, 47, 26,,,, -6, 6, 6, 1, 3, 3, 3, 3, 256, 69, 47, 26,,,, -6, 6, 6, 1, 3, 3, 3, 3, 384, 69, 47, 26,,,, -6, 6, 6, 2, 1, 1, 1, 1, 128, 133, 89, 47,,,, -6, 6, 6, 2, 1, 1, 1, 1, 256, 133, 89, 47,,,, -6, 6, 6, 2, 1, 1, 1, 1, 384, 133, 89, 47,,,, -6, 6, 6, 2, 2, 2, 1, 1, 128, 133, 89, 47,,,, -6, 6, 6, 2, 2, 2, 1, 1, 256, 133, 89, 47,,,, -6, 6, 6, 2, 2, 2, 1, 1, 384, 133, 89, 47,,,, -6, 6, 6, 2, 2, 2, 1, 2, 128, 133, 89, 47,,,, -6, 6, 6, 2, 2, 2, 1, 2, 256, 133, 89, 47,,,, -6, 6, 6, 2, 2, 2, 1, 2, 384, 133, 89, 47,,,, -6, 6, 6, 2, 2, 2, 2, 1, 128, 133, 89, 47,,,, -6, 6, 6, 2, 2, 2, 2, 1, 256, 133, 89, 47,,,, -6, 6, 6, 2, 2, 2, 2, 1, 384, 133, 89, 47,,,, -6, 6, 6, 2, 2, 2, 2, 2, 128, 133, 89, 47,,,, -6, 6, 6, 2, 2, 2, 2, 2, 256, 133, 89, 47,,,, -6, 6, 6, 2, 2, 2, 2, 2, 384, 133, 89, 47,,,, -6, 6, 6, 2, 3, 3, 1, 1, 128, 133, 89, 47,,,, -6, 6, 6, 2, 3, 3, 1, 1, 256, 133, 89, 47,,,, -6, 6, 6, 2, 3, 3, 1, 1, 384, 133, 89, 47,,,, -6, 6, 6, 2, 3, 3, 1, 2, 128, 133, 89, 47,,,, -6, 6, 6, 2, 3, 3, 1, 2, 256, 133, 89, 47,,,, -6, 6, 6, 2, 3, 3, 1, 2, 384, 133, 89, 47,,,, -6, 6, 6, 2, 3, 3, 1, 3, 128, 133, 89, 47,,,, -6, 6, 6, 2, 3, 3, 1, 3, 256, 133, 89, 47,,,, -6, 6, 6, 2, 3, 3, 1, 3, 384, 133, 89, 47,,,, -6, 6, 6, 2, 3, 3, 2, 1, 128, 133, 89, 47,,,, -6, 6, 6, 2, 3, 3, 2, 1, 256, 133, 89, 47,,,, -6, 6, 6, 2, 3, 3, 2, 1, 384, 133, 89, 47,,,, -6, 6, 6, 2, 3, 3, 2, 2, 128, 133, 89, 47,,,, -6, 6, 6, 2, 3, 3, 2, 2, 256, 133, 89, 47,,,, -6, 6, 6, 2, 3, 3, 2, 2, 384, 133, 89, 47,,,, -6, 6, 6, 2, 3, 3, 2, 3, 128, 133, 89, 47,,,, -6, 6, 6, 2, 3, 3, 2, 3, 256, 133, 89, 47,,,, -6, 6, 6, 2, 3, 3, 2, 3, 384, 133, 89, 47,,,, -6, 6, 6, 2, 3, 3, 3, 1, 128, 133, 89, 47,,,, -6, 6, 6, 2, 3, 3, 3, 1, 256, 133, 89, 47,,,, -6, 6, 6, 2, 3, 3, 3, 1, 384, 133, 89, 47,,,, -6, 6, 6, 2, 3, 3, 3, 2, 128, 133, 89, 47,,,, -6, 6, 6, 2, 3, 3, 3, 2, 256, 133, 89, 47,,,, -6, 6, 6, 2, 3, 3, 3, 2, 384, 133, 89, 47,,,, -6, 6, 6, 2, 3, 3, 3, 3, 128, 133, 89, 47,,,, -6, 6, 6, 2, 3, 3, 3, 3, 256, 133, 89, 47,,,, -6, 6, 6, 2, 3, 3, 3, 3, 384, 133, 89, 47,,,, -6, 6, 6, 3, 1, 1, 1, 1, 128, 197, 131, 68,,,, -6, 6, 6, 3, 1, 1, 1, 1, 256, 197, 131, 68,,,, -6, 6, 6, 3, 1, 1, 1, 1, 384, 197, 131, 68,,,, -6, 6, 6, 3, 2, 2, 1, 1, 128, 197, 131, 68,,,, -6, 6, 6, 3, 2, 2, 1, 1, 256, 197, 131, 68,,,, -6, 6, 6, 3, 2, 2, 1, 1, 384, 197, 131, 68,,,, -6, 6, 6, 3, 2, 2, 1, 2, 128, 197, 131, 68,,,, -6, 6, 6, 3, 2, 2, 1, 2, 256, 197, 131, 68,,,, -6, 6, 6, 3, 2, 2, 1, 2, 384, 197, 131, 68,,,, -6, 6, 6, 3, 2, 2, 2, 1, 128, 197, 131, 68,,,, -6, 6, 6, 3, 2, 2, 2, 1, 256, 197, 131, 68,,,, -6, 6, 6, 3, 2, 2, 2, 1, 384, 197, 131, 68,,,, -6, 6, 6, 3, 2, 2, 2, 2, 128, 197, 131, 68,,,, -6, 6, 6, 3, 2, 2, 2, 2, 256, 197, 131, 68,,,, -6, 6, 6, 3, 2, 2, 2, 2, 384, 197, 131, 68,,,, -6, 6, 6, 3, 3, 3, 1, 1, 128, 197, 131, 68,,,, -6, 6, 6, 3, 3, 3, 1, 1, 256, 197, 131, 68,,,, -6, 6, 6, 3, 3, 3, 1, 1, 384, 197, 131, 68,,,, -6, 6, 6, 3, 3, 3, 1, 2, 128, 197, 131, 68,,,, -6, 6, 6, 3, 3, 3, 1, 2, 256, 197, 131, 68,,,, -6, 6, 6, 3, 3, 3, 1, 2, 384, 197, 131, 68,,,, -6, 6, 6, 3, 3, 3, 1, 3, 128, 197, 131, 68,,,, -6, 6, 6, 3, 3, 3, 1, 3, 256, 197, 131, 68,,,, -6, 6, 6, 3, 3, 3, 1, 3, 384, 197, 131, 68,,,, -6, 6, 6, 3, 3, 3, 2, 1, 128, 197, 131, 68,,,, -6, 6, 6, 3, 3, 3, 2, 1, 256, 197, 131, 68,,,, -6, 6, 6, 3, 3, 3, 2, 1, 384, 197, 131, 68,,,, -6, 6, 6, 3, 3, 3, 2, 2, 128, 197, 131, 68,,,, -6, 6, 6, 3, 3, 3, 2, 2, 256, 197, 131, 68,,,, -6, 6, 6, 3, 3, 3, 2, 2, 384, 197, 131, 68,,,, -6, 6, 6, 3, 3, 3, 2, 3, 128, 197, 131, 68,,,, -6, 6, 6, 3, 3, 3, 2, 3, 256, 197, 131, 68,,,, -6, 6, 6, 3, 3, 3, 2, 3, 384, 197, 131, 68,,,, -6, 6, 6, 3, 3, 3, 3, 1, 128, 197, 131, 68,,,, -6, 6, 6, 3, 3, 3, 3, 1, 256, 197, 131, 68,,,, -6, 6, 6, 3, 3, 3, 3, 1, 384, 197, 131, 68,,,, -6, 6, 6, 3, 3, 3, 3, 2, 128, 197, 131, 68,,,, -6, 6, 6, 3, 3, 3, 3, 2, 256, 197, 131, 68,,,, -6, 6, 6, 3, 3, 3, 3, 2, 384, 197, 131, 68,,,, -6, 6, 6, 3, 3, 3, 3, 3, 128, 197, 131, 68,,,, -6, 6, 6, 3, 3, 3, 3, 3, 256, 197, 131, 68,,,, -6, 6, 6, 3, 3, 3, 3, 3, 384, 197, 131, 68,,,, -6, 6, 6, 4, 1, 1, 1, 1, 128, 240, 173, 89,,,, -6, 6, 6, 4, 1, 1, 1, 1, 256, 240, 173, 89,,,, -6, 6, 6, 4, 1, 1, 1, 1, 384, 240, 173, 89,,,, -6, 6, 6, 4, 2, 2, 1, 1, 128, 240, 173, 89,,,, -6, 6, 6, 4, 2, 2, 1, 1, 256, 240, 173, 89,,,, -6, 6, 6, 4, 2, 2, 1, 1, 384, 240, 173, 89,,,, -6, 6, 6, 4, 2, 2, 1, 2, 128, 240, 173, 89,,,, -6, 6, 6, 4, 2, 2, 1, 2, 256, 240, 173, 89,,,, -6, 6, 6, 4, 2, 2, 1, 2, 384, 240, 173, 89,,,, -6, 6, 6, 4, 2, 2, 2, 1, 128, 240, 173, 89,,,, -6, 6, 6, 4, 2, 2, 2, 1, 256, 240, 173, 89,,,, -6, 6, 6, 4, 2, 2, 2, 1, 384, 240, 173, 89,,,, -6, 6, 6, 4, 2, 2, 2, 2, 128, 240, 173, 89,,,, -6, 6, 6, 4, 2, 2, 2, 2, 256, 240, 173, 89,,,, -6, 6, 6, 4, 2, 2, 2, 2, 384, 240, 173, 89,,,, -6, 6, 6, 4, 3, 3, 1, 1, 128, 240, 173, 89,,,, -6, 6, 6, 4, 3, 3, 1, 1, 256, 240, 173, 89,,,, -6, 6, 6, 4, 3, 3, 1, 1, 384, 240, 173, 89,,,, -6, 6, 6, 4, 3, 3, 1, 2, 128, 240, 173, 89,,,, -6, 6, 6, 4, 3, 3, 1, 2, 256, 240, 173, 89,,,, -6, 6, 6, 4, 3, 3, 1, 2, 384, 240, 173, 89,,,, -6, 6, 6, 4, 3, 3, 1, 3, 128, 240, 173, 89,,,, -6, 6, 6, 4, 3, 3, 1, 3, 256, 240, 173, 89,,,, -6, 6, 6, 4, 3, 3, 1, 3, 384, 240, 173, 89,,,, -6, 6, 6, 4, 3, 3, 2, 1, 128, 240, 173, 89,,,, -6, 6, 6, 4, 3, 3, 2, 1, 256, 240, 173, 89,,,, -6, 6, 6, 4, 3, 3, 2, 1, 384, 240, 173, 89,,,, -6, 6, 6, 4, 3, 3, 2, 2, 128, 240, 173, 89,,,, -6, 6, 6, 4, 3, 3, 2, 2, 256, 240, 173, 89,,,, -6, 6, 6, 4, 3, 3, 2, 2, 384, 240, 173, 89,,,, -6, 6, 6, 4, 3, 3, 2, 3, 128, 240, 173, 89,,,, -6, 6, 6, 4, 3, 3, 2, 3, 256, 240, 173, 89,,,, -6, 6, 6, 4, 3, 3, 2, 3, 384, 240, 173, 89,,,, -6, 6, 6, 4, 3, 3, 3, 1, 128, 240, 173, 89,,,, -6, 6, 6, 4, 3, 3, 3, 1, 256, 240, 173, 89,,,, -6, 6, 6, 4, 3, 3, 3, 1, 384, 240, 173, 89,,,, -6, 6, 6, 4, 3, 3, 3, 2, 128, 240, 173, 89,,,, -6, 6, 6, 4, 3, 3, 3, 2, 256, 240, 173, 89,,,, -6, 6, 6, 4, 3, 3, 3, 2, 384, 240, 173, 89,,,, -6, 6, 6, 4, 3, 3, 3, 3, 128, 240, 173, 89,,,, -6, 6, 6, 4, 3, 3, 3, 3, 256, 240, 173, 89,,,, -6, 6, 6, 4, 3, 3, 3, 3, 384, 240, 173, 89,,,, -6, 6, 6, 5, 1, 1, 1, 1, 128, 240, 215, 110,,,, -6, 6, 6, 5, 1, 1, 1, 1, 256, 240, 215, 110,,,, -6, 6, 6, 5, 1, 1, 1, 1, 384, 240, 215, 110,,,, -6, 6, 6, 5, 2, 2, 1, 1, 128, 240, 215, 110,,,, -6, 6, 6, 5, 2, 2, 1, 1, 256, 240, 215, 110,,,, -6, 6, 6, 5, 2, 2, 1, 1, 384, 240, 215, 110,,,, -6, 6, 6, 5, 2, 2, 1, 2, 128, 240, 215, 110,,,, -6, 6, 6, 5, 2, 2, 1, 2, 256, 240, 215, 110,,,, -6, 6, 6, 5, 2, 2, 1, 2, 384, 240, 215, 110,,,, -6, 6, 6, 5, 2, 2, 2, 1, 128, 240, 215, 110,,,, -6, 6, 6, 5, 2, 2, 2, 1, 256, 240, 215, 110,,,, -6, 6, 6, 5, 2, 2, 2, 1, 384, 240, 215, 110,,,, -6, 6, 6, 5, 2, 2, 2, 2, 128, 240, 215, 110,,,, -6, 6, 6, 5, 2, 2, 2, 2, 256, 240, 215, 110,,,, -6, 6, 6, 5, 2, 2, 2, 2, 384, 240, 215, 110,,,, -6, 6, 6, 5, 3, 3, 1, 1, 128, 240, 215, 110,,,, -6, 6, 6, 5, 3, 3, 1, 1, 256, 240, 215, 110,,,, -6, 6, 6, 5, 3, 3, 1, 1, 384, 240, 215, 110,,,, -6, 6, 6, 5, 3, 3, 1, 2, 128, 240, 215, 110,,,, -6, 6, 6, 5, 3, 3, 1, 2, 256, 240, 215, 110,,,, -6, 6, 6, 5, 3, 3, 1, 2, 384, 240, 215, 110,,,, -6, 6, 6, 5, 3, 3, 1, 3, 128, 240, 215, 110,,,, -6, 6, 6, 5, 3, 3, 1, 3, 256, 240, 215, 110,,,, -6, 6, 6, 5, 3, 3, 1, 3, 384, 240, 215, 110,,,, -6, 6, 6, 5, 3, 3, 2, 1, 128, 240, 215, 110,,,, -6, 6, 6, 5, 3, 3, 2, 1, 256, 240, 215, 110,,,, -6, 6, 6, 5, 3, 3, 2, 1, 384, 240, 215, 110,,,, -6, 6, 6, 5, 3, 3, 2, 2, 128, 240, 215, 110,,,, -6, 6, 6, 5, 3, 3, 2, 2, 256, 240, 215, 110,,,, -6, 6, 6, 5, 3, 3, 2, 2, 384, 240, 215, 110,,,, -6, 6, 6, 5, 3, 3, 2, 3, 128, 240, 215, 110,,,, -6, 6, 6, 5, 3, 3, 2, 3, 256, 240, 215, 110,,,, -6, 6, 6, 5, 3, 3, 2, 3, 384, 240, 215, 110,,,, -6, 6, 6, 5, 3, 3, 3, 1, 128, 240, 215, 110,,,, -6, 6, 6, 5, 3, 3, 3, 1, 256, 240, 215, 110,,,, -6, 6, 6, 5, 3, 3, 3, 1, 384, 240, 215, 110,,,, -6, 6, 6, 5, 3, 3, 3, 2, 128, 240, 215, 110,,,, -6, 6, 6, 5, 3, 3, 3, 2, 256, 240, 215, 110,,,, -6, 6, 6, 5, 3, 3, 3, 2, 384, 240, 215, 110,,,, -6, 6, 6, 5, 3, 3, 3, 3, 128, 240, 215, 110,,,, -6, 6, 6, 5, 3, 3, 3, 3, 256, 240, 215, 110,,,, -6, 6, 6, 5, 3, 3, 3, 3, 384, 240, 215, 110,,,, -6, 6, 6, 6, 1, 1, 1, 1, 128, 240, 240, 131,,,, -6, 6, 6, 6, 1, 1, 1, 1, 256, 240, 240, 131,,,, -6, 6, 6, 6, 1, 1, 1, 1, 384, 240, 240, 131,,,, -6, 6, 6, 6, 2, 2, 1, 1, 128, 240, 240, 131,,,, -6, 6, 6, 6, 2, 2, 1, 1, 256, 240, 240, 131,,,, -6, 6, 6, 6, 2, 2, 1, 1, 384, 240, 240, 131,,,, -6, 6, 6, 6, 2, 2, 1, 2, 128, 240, 240, 131,,,, -6, 6, 6, 6, 2, 2, 1, 2, 256, 240, 240, 131,,,, -6, 6, 6, 6, 2, 2, 1, 2, 384, 240, 240, 131,,,, -6, 6, 6, 6, 2, 2, 2, 1, 128, 240, 240, 131,,,, -6, 6, 6, 6, 2, 2, 2, 1, 256, 240, 240, 131,,,, -6, 6, 6, 6, 2, 2, 2, 1, 384, 240, 240, 131,,,, -6, 6, 6, 6, 2, 2, 2, 2, 128, 240, 240, 131,,,, -6, 6, 6, 6, 2, 2, 2, 2, 256, 240, 240, 131,,,, -6, 6, 6, 6, 2, 2, 2, 2, 384, 240, 240, 131,,,, -6, 6, 6, 6, 3, 3, 1, 1, 128, 240, 240, 131,,,, -6, 6, 6, 6, 3, 3, 1, 1, 256, 240, 240, 131,,,, -6, 6, 6, 6, 3, 3, 1, 1, 384, 240, 240, 131,,,, -6, 6, 6, 6, 3, 3, 1, 2, 128, 240, 240, 131,,,, -6, 6, 6, 6, 3, 3, 1, 2, 256, 240, 240, 131,,,, -6, 6, 6, 6, 3, 3, 1, 2, 384, 240, 240, 131,,,, -6, 6, 6, 6, 3, 3, 1, 3, 128, 240, 240, 131,,,, -6, 6, 6, 6, 3, 3, 1, 3, 256, 240, 240, 131,,,, -6, 6, 6, 6, 3, 3, 1, 3, 384, 240, 240, 131,,,, -6, 6, 6, 6, 3, 3, 2, 1, 128, 240, 240, 131,,,, -6, 6, 6, 6, 3, 3, 2, 1, 256, 240, 240, 131,,,, -6, 6, 6, 6, 3, 3, 2, 1, 384, 240, 240, 131,,,, -6, 6, 6, 6, 3, 3, 2, 2, 128, 240, 240, 131,,,, -6, 6, 6, 6, 3, 3, 2, 2, 256, 240, 240, 131,,,, -6, 6, 6, 6, 3, 3, 2, 2, 384, 240, 240, 131,,,, -6, 6, 6, 6, 3, 3, 2, 3, 128, 240, 240, 131,,,, -6, 6, 6, 6, 3, 3, 2, 3, 256, 240, 240, 131,,,, -6, 6, 6, 6, 3, 3, 2, 3, 384, 240, 240, 131,,,, -6, 6, 6, 6, 3, 3, 3, 1, 128, 240, 240, 131,,,, -6, 6, 6, 6, 3, 3, 3, 1, 256, 240, 240, 131,,,, -6, 6, 6, 6, 3, 3, 3, 1, 384, 240, 240, 131,,,, -6, 6, 6, 6, 3, 3, 3, 2, 128, 240, 240, 131,,,, -6, 6, 6, 6, 3, 3, 3, 2, 256, 240, 240, 131,,,, -6, 6, 6, 6, 3, 3, 3, 2, 384, 240, 240, 131,,,, -6, 6, 6, 6, 3, 3, 3, 3, 128, 240, 240, 131,,,, -6, 6, 6, 6, 3, 3, 3, 3, 256, 240, 240, 131,,,, -6, 6, 6, 6, 3, 3, 3, 3, 384, 240, 240, 131,,,, -6, 7, 1, 1, 1, 1, 1, 1, 128, 70, 48, 27,,,, -6, 7, 1, 1, 1, 1, 1, 1, 256, 70, 48, 27,,,, -6, 7, 1, 1, 1, 1, 1, 1, 384, 70, 48, 27,,,, -6, 7, 1, 1, 2, 2, 1, 1, 128, 70, 48, 27,,,, -6, 7, 1, 1, 2, 2, 1, 1, 256, 70, 48, 27,,,, -6, 7, 1, 1, 2, 2, 1, 1, 384, 70, 48, 27,,,, -6, 7, 1, 1, 2, 2, 1, 2, 128, 70, 48, 27,,,, -6, 7, 1, 1, 2, 2, 1, 2, 256, 70, 48, 27,,,, -6, 7, 1, 1, 2, 2, 1, 2, 384, 70, 48, 27,,,, -6, 7, 1, 1, 2, 2, 2, 1, 128, 70, 48, 27,,,, -6, 7, 1, 1, 2, 2, 2, 1, 256, 70, 48, 27,,,, -6, 7, 1, 1, 2, 2, 2, 1, 384, 70, 48, 27,,,, -6, 7, 1, 1, 2, 2, 2, 2, 128, 70, 48, 27,,,, -6, 7, 1, 1, 2, 2, 2, 2, 256, 70, 48, 27,,,, -6, 7, 1, 1, 2, 2, 2, 2, 384, 70, 48, 27,,,, -6, 7, 1, 1, 3, 3, 1, 1, 128, 69, 48, 27,,,, -6, 7, 1, 1, 3, 3, 1, 1, 256, 69, 48, 27,,,, -6, 7, 1, 1, 3, 3, 1, 1, 384, 69, 48, 27,,,, -6, 7, 1, 1, 3, 3, 1, 2, 128, 69, 48, 27,,,, -6, 7, 1, 1, 3, 3, 1, 2, 256, 69, 48, 27,,,, -6, 7, 1, 1, 3, 3, 1, 2, 384, 69, 48, 27,,,, -6, 7, 1, 1, 3, 3, 1, 3, 128, 69, 48, 27,,,, -6, 7, 1, 1, 3, 3, 1, 3, 256, 69, 48, 27,,,, -6, 7, 1, 1, 3, 3, 1, 3, 384, 69, 48, 27,,,, -6, 7, 1, 1, 3, 3, 2, 1, 128, 69, 48, 27,,,, -6, 7, 1, 1, 3, 3, 2, 1, 256, 69, 48, 27,,,, -6, 7, 1, 1, 3, 3, 2, 1, 384, 69, 48, 27,,,, -6, 7, 1, 1, 3, 3, 2, 2, 128, 69, 48, 27,,,, -6, 7, 1, 1, 3, 3, 2, 2, 256, 69, 48, 27,,,, -6, 7, 1, 1, 3, 3, 2, 2, 384, 69, 48, 27,,,, -6, 7, 1, 1, 3, 3, 2, 3, 128, 69, 48, 27,,,, -6, 7, 1, 1, 3, 3, 2, 3, 256, 69, 48, 27,,,, -6, 7, 1, 1, 3, 3, 2, 3, 384, 69, 48, 27,,,, -6, 7, 1, 1, 3, 3, 3, 1, 128, 69, 48, 27,,,, -6, 7, 1, 1, 3, 3, 3, 1, 256, 69, 48, 27,,,, -6, 7, 1, 1, 3, 3, 3, 1, 384, 69, 48, 27,,,, -6, 7, 1, 1, 3, 3, 3, 2, 128, 69, 48, 27,,,, -6, 7, 1, 1, 3, 3, 3, 2, 256, 69, 48, 27,,,, -6, 7, 1, 1, 3, 3, 3, 2, 384, 69, 48, 27,,,, -6, 7, 1, 1, 3, 3, 3, 3, 128, 69, 48, 27,,,, -6, 7, 1, 1, 3, 3, 3, 3, 256, 69, 48, 27,,,, -6, 7, 1, 1, 3, 3, 3, 3, 384, 69, 48, 27,,,, -6, 7, 1, 2, 1, 1, 1, 1, 128, 134, 90, 48,,,, -6, 7, 1, 2, 1, 1, 1, 1, 256, 134, 90, 48,,,, -6, 7, 1, 2, 1, 1, 1, 1, 384, 134, 90, 48,,,, -6, 7, 1, 2, 2, 2, 1, 1, 128, 134, 90, 48,,,, -6, 7, 1, 2, 2, 2, 1, 1, 256, 134, 90, 48,,,, -6, 7, 1, 2, 2, 2, 1, 1, 384, 134, 90, 48,,,, -6, 7, 1, 2, 2, 2, 1, 2, 128, 134, 90, 48,,,, -6, 7, 1, 2, 2, 2, 1, 2, 256, 134, 90, 48,,,, -6, 7, 1, 2, 2, 2, 1, 2, 384, 134, 90, 48,,,, -6, 7, 1, 2, 2, 2, 2, 1, 128, 134, 90, 48,,,, -6, 7, 1, 2, 2, 2, 2, 1, 256, 134, 90, 48,,,, -6, 7, 1, 2, 2, 2, 2, 1, 384, 134, 90, 48,,,, -6, 7, 1, 2, 2, 2, 2, 2, 128, 134, 90, 48,,,, -6, 7, 1, 2, 2, 2, 2, 2, 256, 134, 90, 48,,,, -6, 7, 1, 2, 2, 2, 2, 2, 384, 134, 90, 48,,,, -6, 7, 1, 2, 3, 3, 1, 1, 128, 132, 90, 48,,,, -6, 7, 1, 2, 3, 3, 1, 1, 256, 132, 90, 48,,,, -6, 7, 1, 2, 3, 3, 1, 1, 384, 132, 90, 48,,,, -6, 7, 1, 2, 3, 3, 1, 2, 128, 132, 90, 48,,,, -6, 7, 1, 2, 3, 3, 1, 2, 256, 132, 90, 48,,,, -6, 7, 1, 2, 3, 3, 1, 2, 384, 132, 90, 48,,,, -6, 7, 1, 2, 3, 3, 1, 3, 128, 132, 90, 48,,,, -6, 7, 1, 2, 3, 3, 1, 3, 256, 132, 90, 48,,,, -6, 7, 1, 2, 3, 3, 1, 3, 384, 132, 90, 48,,,, -6, 7, 1, 2, 3, 3, 2, 1, 128, 132, 90, 48,,,, -6, 7, 1, 2, 3, 3, 2, 1, 256, 132, 90, 48,,,, -6, 7, 1, 2, 3, 3, 2, 1, 384, 132, 90, 48,,,, -6, 7, 1, 2, 3, 3, 2, 2, 128, 132, 90, 48,,,, -6, 7, 1, 2, 3, 3, 2, 2, 256, 132, 90, 48,,,, -6, 7, 1, 2, 3, 3, 2, 2, 384, 132, 90, 48,,,, -6, 7, 1, 2, 3, 3, 2, 3, 128, 132, 90, 48,,,, -6, 7, 1, 2, 3, 3, 2, 3, 256, 132, 90, 48,,,, -6, 7, 1, 2, 3, 3, 2, 3, 384, 132, 90, 48,,,, -6, 7, 1, 2, 3, 3, 3, 1, 128, 132, 90, 48,,,, -6, 7, 1, 2, 3, 3, 3, 1, 256, 132, 90, 48,,,, -6, 7, 1, 2, 3, 3, 3, 1, 384, 132, 90, 48,,,, -6, 7, 1, 2, 3, 3, 3, 2, 128, 132, 90, 48,,,, -6, 7, 1, 2, 3, 3, 3, 2, 256, 132, 90, 48,,,, -6, 7, 1, 2, 3, 3, 3, 2, 384, 132, 90, 48,,,, -6, 7, 1, 2, 3, 3, 3, 3, 128, 132, 90, 48,,,, -6, 7, 1, 2, 3, 3, 3, 3, 256, 132, 90, 48,,,, -6, 7, 1, 2, 3, 3, 3, 3, 384, 132, 90, 48,,,, -6, 7, 1, 3, 1, 1, 1, 1, 128, 198, 132, 69,,,, -6, 7, 1, 3, 1, 1, 1, 1, 256, 198, 132, 69,,,, -6, 7, 1, 3, 1, 1, 1, 1, 384, 198, 132, 69,,,, -6, 7, 1, 3, 2, 2, 1, 1, 128, 198, 132, 69,,,, -6, 7, 1, 3, 2, 2, 1, 1, 256, 198, 132, 69,,,, -6, 7, 1, 3, 2, 2, 1, 1, 384, 198, 132, 69,,,, -6, 7, 1, 3, 2, 2, 1, 2, 128, 198, 132, 69,,,, -6, 7, 1, 3, 2, 2, 1, 2, 256, 198, 132, 69,,,, -6, 7, 1, 3, 2, 2, 1, 2, 384, 198, 132, 69,,,, -6, 7, 1, 3, 2, 2, 2, 1, 128, 198, 132, 69,,,, -6, 7, 1, 3, 2, 2, 2, 1, 256, 198, 132, 69,,,, -6, 7, 1, 3, 2, 2, 2, 1, 384, 198, 132, 69,,,, -6, 7, 1, 3, 2, 2, 2, 2, 128, 198, 132, 69,,,, -6, 7, 1, 3, 2, 2, 2, 2, 256, 198, 132, 69,,,, -6, 7, 1, 3, 2, 2, 2, 2, 384, 198, 132, 69,,,, -6, 7, 1, 3, 3, 3, 1, 1, 128, 195, 132, 69,,,, -6, 7, 1, 3, 3, 3, 1, 1, 256, 195, 132, 69,,,, -6, 7, 1, 3, 3, 3, 1, 1, 384, 195, 132, 69,,,, -6, 7, 1, 3, 3, 3, 1, 2, 128, 195, 132, 69,,,, -6, 7, 1, 3, 3, 3, 1, 2, 256, 195, 132, 69,,,, -6, 7, 1, 3, 3, 3, 1, 2, 384, 195, 132, 69,,,, -6, 7, 1, 3, 3, 3, 1, 3, 128, 195, 132, 69,,,, -6, 7, 1, 3, 3, 3, 1, 3, 256, 195, 132, 69,,,, -6, 7, 1, 3, 3, 3, 1, 3, 384, 195, 132, 69,,,, -6, 7, 1, 3, 3, 3, 2, 1, 128, 195, 132, 69,,,, -6, 7, 1, 3, 3, 3, 2, 1, 256, 195, 132, 69,,,, -6, 7, 1, 3, 3, 3, 2, 1, 384, 195, 132, 69,,,, -6, 7, 1, 3, 3, 3, 2, 2, 128, 195, 132, 69,,,, -6, 7, 1, 3, 3, 3, 2, 2, 256, 195, 132, 69,,,, -6, 7, 1, 3, 3, 3, 2, 2, 384, 195, 132, 69,,,, -6, 7, 1, 3, 3, 3, 2, 3, 128, 195, 132, 69,,,, -6, 7, 1, 3, 3, 3, 2, 3, 256, 195, 132, 69,,,, -6, 7, 1, 3, 3, 3, 2, 3, 384, 195, 132, 69,,,, -6, 7, 1, 3, 3, 3, 3, 1, 128, 195, 132, 69,,,, -6, 7, 1, 3, 3, 3, 3, 1, 256, 195, 132, 69,,,, -6, 7, 1, 3, 3, 3, 3, 1, 384, 195, 132, 69,,,, -6, 7, 1, 3, 3, 3, 3, 2, 128, 195, 132, 69,,,, -6, 7, 1, 3, 3, 3, 3, 2, 256, 195, 132, 69,,,, -6, 7, 1, 3, 3, 3, 3, 2, 384, 195, 132, 69,,,, -6, 7, 1, 3, 3, 3, 3, 3, 128, 195, 132, 69,,,, -6, 7, 1, 3, 3, 3, 3, 3, 256, 195, 132, 69,,,, -6, 7, 1, 3, 3, 3, 3, 3, 384, 195, 132, 69,,,, -6, 7, 1, 4, 1, 1, 1, 1, 128, 240, 174, 90,,,, -6, 7, 1, 4, 1, 1, 1, 1, 256, 240, 174, 90,,,, -6, 7, 1, 4, 1, 1, 1, 1, 384, 240, 174, 90,,,, -6, 7, 1, 4, 2, 2, 1, 1, 128, 240, 174, 90,,,, -6, 7, 1, 4, 2, 2, 1, 1, 256, 240, 174, 90,,,, -6, 7, 1, 4, 2, 2, 1, 1, 384, 240, 174, 90,,,, -6, 7, 1, 4, 2, 2, 1, 2, 128, 240, 174, 90,,,, -6, 7, 1, 4, 2, 2, 1, 2, 256, 240, 174, 90,,,, -6, 7, 1, 4, 2, 2, 1, 2, 384, 240, 174, 90,,,, -6, 7, 1, 4, 2, 2, 2, 1, 128, 240, 174, 90,,,, -6, 7, 1, 4, 2, 2, 2, 1, 256, 240, 174, 90,,,, -6, 7, 1, 4, 2, 2, 2, 1, 384, 240, 174, 90,,,, -6, 7, 1, 4, 2, 2, 2, 2, 128, 240, 174, 90,,,, -6, 7, 1, 4, 2, 2, 2, 2, 256, 240, 174, 90,,,, -6, 7, 1, 4, 2, 2, 2, 2, 384, 240, 174, 90,,,, -6, 7, 1, 4, 3, 3, 1, 1, 128, 240, 174, 90,,,, -6, 7, 1, 4, 3, 3, 1, 1, 256, 240, 174, 90,,,, -6, 7, 1, 4, 3, 3, 1, 1, 384, 240, 174, 90,,,, -6, 7, 1, 4, 3, 3, 1, 2, 128, 240, 174, 90,,,, -6, 7, 1, 4, 3, 3, 1, 2, 256, 240, 174, 90,,,, -6, 7, 1, 4, 3, 3, 1, 2, 384, 240, 174, 90,,,, -6, 7, 1, 4, 3, 3, 1, 3, 128, 240, 174, 90,,,, -6, 7, 1, 4, 3, 3, 1, 3, 256, 240, 174, 90,,,, -6, 7, 1, 4, 3, 3, 1, 3, 384, 240, 174, 90,,,, -6, 7, 1, 4, 3, 3, 2, 1, 128, 240, 174, 90,,,, -6, 7, 1, 4, 3, 3, 2, 1, 256, 240, 174, 90,,,, -6, 7, 1, 4, 3, 3, 2, 1, 384, 240, 174, 90,,,, -6, 7, 1, 4, 3, 3, 2, 2, 128, 240, 174, 90,,,, -6, 7, 1, 4, 3, 3, 2, 2, 256, 240, 174, 90,,,, -6, 7, 1, 4, 3, 3, 2, 2, 384, 240, 174, 90,,,, -6, 7, 1, 4, 3, 3, 2, 3, 128, 240, 174, 90,,,, -6, 7, 1, 4, 3, 3, 2, 3, 256, 240, 174, 90,,,, -6, 7, 1, 4, 3, 3, 2, 3, 384, 240, 174, 90,,,, -6, 7, 1, 4, 3, 3, 3, 1, 128, 240, 174, 90,,,, -6, 7, 1, 4, 3, 3, 3, 1, 256, 240, 174, 90,,,, -6, 7, 1, 4, 3, 3, 3, 1, 384, 240, 174, 90,,,, -6, 7, 1, 4, 3, 3, 3, 2, 128, 240, 174, 90,,,, -6, 7, 1, 4, 3, 3, 3, 2, 256, 240, 174, 90,,,, -6, 7, 1, 4, 3, 3, 3, 2, 384, 240, 174, 90,,,, -6, 7, 1, 4, 3, 3, 3, 3, 128, 240, 174, 90,,,, -6, 7, 1, 4, 3, 3, 3, 3, 256, 240, 174, 90,,,, -6, 7, 1, 4, 3, 3, 3, 3, 384, 240, 174, 90,,,, -6, 7, 1, 5, 1, 1, 1, 1, 128, 240, 216, 111,,,, -6, 7, 1, 5, 1, 1, 1, 1, 256, 240, 216, 111,,,, -6, 7, 1, 5, 1, 1, 1, 1, 384, 240, 216, 111,,,, -6, 7, 1, 5, 2, 2, 1, 1, 128, 240, 216, 111,,,, -6, 7, 1, 5, 2, 2, 1, 1, 256, 240, 216, 111,,,, -6, 7, 1, 5, 2, 2, 1, 1, 384, 240, 216, 111,,,, -6, 7, 1, 5, 2, 2, 1, 2, 128, 240, 216, 111,,,, -6, 7, 1, 5, 2, 2, 1, 2, 256, 240, 216, 111,,,, -6, 7, 1, 5, 2, 2, 1, 2, 384, 240, 216, 111,,,, -6, 7, 1, 5, 2, 2, 2, 1, 128, 240, 216, 111,,,, -6, 7, 1, 5, 2, 2, 2, 1, 256, 240, 216, 111,,,, -6, 7, 1, 5, 2, 2, 2, 1, 384, 240, 216, 111,,,, -6, 7, 1, 5, 2, 2, 2, 2, 128, 240, 216, 111,,,, -6, 7, 1, 5, 2, 2, 2, 2, 256, 240, 216, 111,,,, -6, 7, 1, 5, 2, 2, 2, 2, 384, 240, 216, 111,,,, -6, 7, 1, 5, 3, 3, 1, 1, 128, 240, 216, 111,,,, -6, 7, 1, 5, 3, 3, 1, 1, 256, 240, 216, 111,,,, -6, 7, 1, 5, 3, 3, 1, 1, 384, 240, 216, 111,,,, -6, 7, 1, 5, 3, 3, 1, 2, 128, 240, 216, 111,,,, -6, 7, 1, 5, 3, 3, 1, 2, 256, 240, 216, 111,,,, -6, 7, 1, 5, 3, 3, 1, 2, 384, 240, 216, 111,,,, -6, 7, 1, 5, 3, 3, 1, 3, 128, 240, 216, 111,,,, -6, 7, 1, 5, 3, 3, 1, 3, 256, 240, 216, 111,,,, -6, 7, 1, 5, 3, 3, 1, 3, 384, 240, 216, 111,,,, -6, 7, 1, 5, 3, 3, 2, 1, 128, 240, 216, 111,,,, -6, 7, 1, 5, 3, 3, 2, 1, 256, 240, 216, 111,,,, -6, 7, 1, 5, 3, 3, 2, 1, 384, 240, 216, 111,,,, -6, 7, 1, 5, 3, 3, 2, 2, 128, 240, 216, 111,,,, -6, 7, 1, 5, 3, 3, 2, 2, 256, 240, 216, 111,,,, -6, 7, 1, 5, 3, 3, 2, 2, 384, 240, 216, 111,,,, -6, 7, 1, 5, 3, 3, 2, 3, 128, 240, 216, 111,,,, -6, 7, 1, 5, 3, 3, 2, 3, 256, 240, 216, 111,,,, -6, 7, 1, 5, 3, 3, 2, 3, 384, 240, 216, 111,,,, -6, 7, 1, 5, 3, 3, 3, 1, 128, 240, 216, 111,,,, -6, 7, 1, 5, 3, 3, 3, 1, 256, 240, 216, 111,,,, -6, 7, 1, 5, 3, 3, 3, 1, 384, 240, 216, 111,,,, -6, 7, 1, 5, 3, 3, 3, 2, 128, 240, 216, 111,,,, -6, 7, 1, 5, 3, 3, 3, 2, 256, 240, 216, 111,,,, -6, 7, 1, 5, 3, 3, 3, 2, 384, 240, 216, 111,,,, -6, 7, 1, 5, 3, 3, 3, 3, 128, 240, 216, 111,,,, -6, 7, 1, 5, 3, 3, 3, 3, 256, 240, 216, 111,,,, -6, 7, 1, 5, 3, 3, 3, 3, 384, 240, 216, 111,,,, -6, 7, 1, 6, 1, 1, 1, 1, 128, 240, 240, 132,,,, -6, 7, 1, 6, 1, 1, 1, 1, 256, 240, 240, 132,,,, -6, 7, 1, 6, 1, 1, 1, 1, 384, 240, 240, 132,,,, -6, 7, 1, 6, 2, 2, 1, 1, 128, 240, 240, 132,,,, -6, 7, 1, 6, 2, 2, 1, 1, 256, 240, 240, 132,,,, -6, 7, 1, 6, 2, 2, 1, 1, 384, 240, 240, 132,,,, -6, 7, 1, 6, 2, 2, 1, 2, 128, 240, 240, 132,,,, -6, 7, 1, 6, 2, 2, 1, 2, 256, 240, 240, 132,,,, -6, 7, 1, 6, 2, 2, 1, 2, 384, 240, 240, 132,,,, -6, 7, 1, 6, 2, 2, 2, 1, 128, 240, 240, 132,,,, -6, 7, 1, 6, 2, 2, 2, 1, 256, 240, 240, 132,,,, -6, 7, 1, 6, 2, 2, 2, 1, 384, 240, 240, 132,,,, -6, 7, 1, 6, 2, 2, 2, 2, 128, 240, 240, 132,,,, -6, 7, 1, 6, 2, 2, 2, 2, 256, 240, 240, 132,,,, -6, 7, 1, 6, 2, 2, 2, 2, 384, 240, 240, 132,,,, -6, 7, 1, 6, 3, 3, 1, 1, 128, 240, 240, 132,,,, -6, 7, 1, 6, 3, 3, 1, 1, 256, 240, 240, 132,,,, -6, 7, 1, 6, 3, 3, 1, 1, 384, 240, 240, 132,,,, -6, 7, 1, 6, 3, 3, 1, 2, 128, 240, 240, 132,,,, -6, 7, 1, 6, 3, 3, 1, 2, 256, 240, 240, 132,,,, -6, 7, 1, 6, 3, 3, 1, 2, 384, 240, 240, 132,,,, -6, 7, 1, 6, 3, 3, 1, 3, 128, 240, 240, 132,,,, -6, 7, 1, 6, 3, 3, 1, 3, 256, 240, 240, 132,,,, -6, 7, 1, 6, 3, 3, 1, 3, 384, 240, 240, 132,,,, -6, 7, 1, 6, 3, 3, 2, 1, 128, 240, 240, 132,,,, -6, 7, 1, 6, 3, 3, 2, 1, 256, 240, 240, 132,,,, -6, 7, 1, 6, 3, 3, 2, 1, 384, 240, 240, 132,,,, -6, 7, 1, 6, 3, 3, 2, 2, 128, 240, 240, 132,,,, -6, 7, 1, 6, 3, 3, 2, 2, 256, 240, 240, 132,,,, -6, 7, 1, 6, 3, 3, 2, 2, 384, 240, 240, 132,,,, -6, 7, 1, 6, 3, 3, 2, 3, 128, 240, 240, 132,,,, -6, 7, 1, 6, 3, 3, 2, 3, 256, 240, 240, 132,,,, -6, 7, 1, 6, 3, 3, 2, 3, 384, 240, 240, 132,,,, -6, 7, 1, 6, 3, 3, 3, 1, 128, 240, 240, 132,,,, -6, 7, 1, 6, 3, 3, 3, 1, 256, 240, 240, 132,,,, -6, 7, 1, 6, 3, 3, 3, 1, 384, 240, 240, 132,,,, -6, 7, 1, 6, 3, 3, 3, 2, 128, 240, 240, 132,,,, -6, 7, 1, 6, 3, 3, 3, 2, 256, 240, 240, 132,,,, -6, 7, 1, 6, 3, 3, 3, 2, 384, 240, 240, 132,,,, -6, 7, 1, 6, 3, 3, 3, 3, 128, 240, 240, 132,,,, -6, 7, 1, 6, 3, 3, 3, 3, 256, 240, 240, 132,,,, -6, 7, 1, 6, 3, 3, 3, 3, 384, 240, 240, 132,,,, -6, 7, 1, 7, 1, 1, 1, 1, 128, 240, 240, 153,,,, -6, 7, 1, 7, 1, 1, 1, 1, 256, 240, 240, 153,,,, -6, 7, 1, 7, 1, 1, 1, 1, 384, 240, 240, 153,,,, -6, 7, 1, 7, 2, 2, 1, 1, 128, 240, 240, 153,,,, -6, 7, 1, 7, 2, 2, 1, 1, 256, 240, 240, 153,,,, -6, 7, 1, 7, 2, 2, 1, 1, 384, 240, 240, 153,,,, -6, 7, 1, 7, 2, 2, 1, 2, 128, 240, 240, 153,,,, -6, 7, 1, 7, 2, 2, 1, 2, 256, 240, 240, 153,,,, -6, 7, 1, 7, 2, 2, 1, 2, 384, 240, 240, 153,,,, -6, 7, 1, 7, 2, 2, 2, 1, 128, 240, 240, 153,,,, -6, 7, 1, 7, 2, 2, 2, 1, 256, 240, 240, 153,,,, -6, 7, 1, 7, 2, 2, 2, 1, 384, 240, 240, 153,,,, -6, 7, 1, 7, 2, 2, 2, 2, 128, 240, 240, 153,,,, -6, 7, 1, 7, 2, 2, 2, 2, 256, 240, 240, 153,,,, -6, 7, 1, 7, 2, 2, 2, 2, 384, 240, 240, 153,,,, -6, 7, 1, 7, 3, 3, 1, 1, 128, 240, 240, 153,,,, -6, 7, 1, 7, 3, 3, 1, 1, 256, 240, 240, 153,,,, -6, 7, 1, 7, 3, 3, 1, 1, 384, 240, 240, 153,,,, -6, 7, 1, 7, 3, 3, 1, 2, 128, 240, 240, 153,,,, -6, 7, 1, 7, 3, 3, 1, 2, 256, 240, 240, 153,,,, -6, 7, 1, 7, 3, 3, 1, 2, 384, 240, 240, 153,,,, -6, 7, 1, 7, 3, 3, 1, 3, 128, 240, 240, 153,,,, -6, 7, 1, 7, 3, 3, 1, 3, 256, 240, 240, 153,,,, -6, 7, 1, 7, 3, 3, 1, 3, 384, 240, 240, 153,,,, -6, 7, 1, 7, 3, 3, 2, 1, 128, 240, 240, 153,,,, -6, 7, 1, 7, 3, 3, 2, 1, 256, 240, 240, 153,,,, -6, 7, 1, 7, 3, 3, 2, 1, 384, 240, 240, 153,,,, -6, 7, 1, 7, 3, 3, 2, 2, 128, 240, 240, 153,,,, -6, 7, 1, 7, 3, 3, 2, 2, 256, 240, 240, 153,,,, -6, 7, 1, 7, 3, 3, 2, 2, 384, 240, 240, 153,,,, -6, 7, 1, 7, 3, 3, 2, 3, 128, 240, 240, 153,,,, -6, 7, 1, 7, 3, 3, 2, 3, 256, 240, 240, 153,,,, -6, 7, 1, 7, 3, 3, 2, 3, 384, 240, 240, 153,,,, -6, 7, 1, 7, 3, 3, 3, 1, 128, 240, 240, 153,,,, -6, 7, 1, 7, 3, 3, 3, 1, 256, 240, 240, 153,,,, -6, 7, 1, 7, 3, 3, 3, 1, 384, 240, 240, 153,,,, -6, 7, 1, 7, 3, 3, 3, 2, 128, 240, 240, 153,,,, -6, 7, 1, 7, 3, 3, 3, 2, 256, 240, 240, 153,,,, -6, 7, 1, 7, 3, 3, 3, 2, 384, 240, 240, 153,,,, -6, 7, 1, 7, 3, 3, 3, 3, 128, 240, 240, 153,,,, -6, 7, 1, 7, 3, 3, 3, 3, 256, 240, 240, 153,,,, -6, 7, 1, 7, 3, 3, 3, 3, 384, 240, 240, 153,,,, -6, 7, 2, 1, 1, 1, 1, 1, 128, 70, 48, 27,,,, -6, 7, 2, 1, 1, 1, 1, 1, 256, 70, 48, 27,,,, -6, 7, 2, 1, 1, 1, 1, 1, 384, 70, 48, 27,,,, -6, 7, 2, 1, 2, 2, 1, 1, 128, 70, 48, 27,,,, -6, 7, 2, 1, 2, 2, 1, 1, 256, 70, 48, 27,,,, -6, 7, 2, 1, 2, 2, 1, 1, 384, 70, 48, 27,,,, -6, 7, 2, 1, 2, 2, 1, 2, 128, 70, 48, 27,,,, -6, 7, 2, 1, 2, 2, 1, 2, 256, 70, 48, 27,,,, -6, 7, 2, 1, 2, 2, 1, 2, 384, 70, 48, 27,,,, -6, 7, 2, 1, 2, 2, 2, 1, 128, 70, 48, 27,,,, -6, 7, 2, 1, 2, 2, 2, 1, 256, 70, 48, 27,,,, -6, 7, 2, 1, 2, 2, 2, 1, 384, 70, 48, 27,,,, -6, 7, 2, 1, 2, 2, 2, 2, 128, 70, 48, 27,,,, -6, 7, 2, 1, 2, 2, 2, 2, 256, 70, 48, 27,,,, -6, 7, 2, 1, 2, 2, 2, 2, 384, 70, 48, 27,,,, -6, 7, 2, 1, 3, 3, 1, 1, 128, 69, 48, 27,,,, -6, 7, 2, 1, 3, 3, 1, 1, 256, 69, 48, 27,,,, -6, 7, 2, 1, 3, 3, 1, 1, 384, 69, 48, 27,,,, -6, 7, 2, 1, 3, 3, 1, 2, 128, 69, 48, 27,,,, -6, 7, 2, 1, 3, 3, 1, 2, 256, 69, 48, 27,,,, -6, 7, 2, 1, 3, 3, 1, 2, 384, 69, 48, 27,,,, -6, 7, 2, 1, 3, 3, 1, 3, 128, 69, 48, 27,,,, -6, 7, 2, 1, 3, 3, 1, 3, 256, 69, 48, 27,,,, -6, 7, 2, 1, 3, 3, 1, 3, 384, 69, 48, 27,,,, -6, 7, 2, 1, 3, 3, 2, 1, 128, 69, 48, 27,,,, -6, 7, 2, 1, 3, 3, 2, 1, 256, 69, 48, 27,,,, -6, 7, 2, 1, 3, 3, 2, 1, 384, 69, 48, 27,,,, -6, 7, 2, 1, 3, 3, 2, 2, 128, 69, 48, 27,,,, -6, 7, 2, 1, 3, 3, 2, 2, 256, 69, 48, 27,,,, -6, 7, 2, 1, 3, 3, 2, 2, 384, 69, 48, 27,,,, -6, 7, 2, 1, 3, 3, 2, 3, 128, 69, 48, 27,,,, -6, 7, 2, 1, 3, 3, 2, 3, 256, 69, 48, 27,,,, -6, 7, 2, 1, 3, 3, 2, 3, 384, 69, 48, 27,,,, -6, 7, 2, 1, 3, 3, 3, 1, 128, 69, 48, 27,,,, -6, 7, 2, 1, 3, 3, 3, 1, 256, 69, 48, 27,,,, -6, 7, 2, 1, 3, 3, 3, 1, 384, 69, 48, 27,,,, -6, 7, 2, 1, 3, 3, 3, 2, 128, 69, 48, 27,,,, -6, 7, 2, 1, 3, 3, 3, 2, 256, 69, 48, 27,,,, -6, 7, 2, 1, 3, 3, 3, 2, 384, 69, 48, 27,,,, -6, 7, 2, 1, 3, 3, 3, 3, 128, 69, 48, 27,,,, -6, 7, 2, 1, 3, 3, 3, 3, 256, 69, 48, 27,,,, -6, 7, 2, 1, 3, 3, 3, 3, 384, 69, 48, 27,,,, -6, 7, 2, 2, 1, 1, 1, 1, 128, 134, 90, 48,,,, -6, 7, 2, 2, 1, 1, 1, 1, 256, 134, 90, 48,,,, -6, 7, 2, 2, 1, 1, 1, 1, 384, 134, 90, 48,,,, -6, 7, 2, 2, 2, 2, 1, 1, 128, 134, 90, 48,,,, -6, 7, 2, 2, 2, 2, 1, 1, 256, 134, 90, 48,,,, -6, 7, 2, 2, 2, 2, 1, 1, 384, 134, 90, 48,,,, -6, 7, 2, 2, 2, 2, 1, 2, 128, 134, 90, 48,,,, -6, 7, 2, 2, 2, 2, 1, 2, 256, 134, 90, 48,,,, -6, 7, 2, 2, 2, 2, 1, 2, 384, 134, 90, 48,,,, -6, 7, 2, 2, 2, 2, 2, 1, 128, 134, 90, 48,,,, -6, 7, 2, 2, 2, 2, 2, 1, 256, 134, 90, 48,,,, -6, 7, 2, 2, 2, 2, 2, 1, 384, 134, 90, 48,,,, -6, 7, 2, 2, 2, 2, 2, 2, 128, 134, 90, 48,,,, -6, 7, 2, 2, 2, 2, 2, 2, 256, 134, 90, 48,,,, -6, 7, 2, 2, 2, 2, 2, 2, 384, 134, 90, 48,,,, -6, 7, 2, 2, 3, 3, 1, 1, 128, 132, 90, 48,,,, -6, 7, 2, 2, 3, 3, 1, 1, 256, 132, 90, 48,,,, -6, 7, 2, 2, 3, 3, 1, 1, 384, 132, 90, 48,,,, -6, 7, 2, 2, 3, 3, 1, 2, 128, 132, 90, 48,,,, -6, 7, 2, 2, 3, 3, 1, 2, 256, 132, 90, 48,,,, -6, 7, 2, 2, 3, 3, 1, 2, 384, 132, 90, 48,,,, -6, 7, 2, 2, 3, 3, 1, 3, 128, 132, 90, 48,,,, -6, 7, 2, 2, 3, 3, 1, 3, 256, 132, 90, 48,,,, -6, 7, 2, 2, 3, 3, 1, 3, 384, 132, 90, 48,,,, -6, 7, 2, 2, 3, 3, 2, 1, 128, 132, 90, 48,,,, -6, 7, 2, 2, 3, 3, 2, 1, 256, 132, 90, 48,,,, -6, 7, 2, 2, 3, 3, 2, 1, 384, 132, 90, 48,,,, -6, 7, 2, 2, 3, 3, 2, 2, 128, 132, 90, 48,,,, -6, 7, 2, 2, 3, 3, 2, 2, 256, 132, 90, 48,,,, -6, 7, 2, 2, 3, 3, 2, 2, 384, 132, 90, 48,,,, -6, 7, 2, 2, 3, 3, 2, 3, 128, 132, 90, 48,,,, -6, 7, 2, 2, 3, 3, 2, 3, 256, 132, 90, 48,,,, -6, 7, 2, 2, 3, 3, 2, 3, 384, 132, 90, 48,,,, -6, 7, 2, 2, 3, 3, 3, 1, 128, 132, 90, 48,,,, -6, 7, 2, 2, 3, 3, 3, 1, 256, 132, 90, 48,,,, -6, 7, 2, 2, 3, 3, 3, 1, 384, 132, 90, 48,,,, -6, 7, 2, 2, 3, 3, 3, 2, 128, 132, 90, 48,,,, -6, 7, 2, 2, 3, 3, 3, 2, 256, 132, 90, 48,,,, -6, 7, 2, 2, 3, 3, 3, 2, 384, 132, 90, 48,,,, -6, 7, 2, 2, 3, 3, 3, 3, 128, 132, 90, 48,,,, -6, 7, 2, 2, 3, 3, 3, 3, 256, 132, 90, 48,,,, -6, 7, 2, 2, 3, 3, 3, 3, 384, 132, 90, 48,,,, -6, 7, 2, 3, 1, 1, 1, 1, 128, 198, 132, 69,,,, -6, 7, 2, 3, 1, 1, 1, 1, 256, 198, 132, 69,,,, -6, 7, 2, 3, 1, 1, 1, 1, 384, 198, 132, 69,,,, -6, 7, 2, 3, 2, 2, 1, 1, 128, 198, 132, 69,,,, -6, 7, 2, 3, 2, 2, 1, 1, 256, 198, 132, 69,,,, -6, 7, 2, 3, 2, 2, 1, 1, 384, 198, 132, 69,,,, -6, 7, 2, 3, 2, 2, 1, 2, 128, 198, 132, 69,,,, -6, 7, 2, 3, 2, 2, 1, 2, 256, 198, 132, 69,,,, -6, 7, 2, 3, 2, 2, 1, 2, 384, 198, 132, 69,,,, -6, 7, 2, 3, 2, 2, 2, 1, 128, 198, 132, 69,,,, -6, 7, 2, 3, 2, 2, 2, 1, 256, 198, 132, 69,,,, -6, 7, 2, 3, 2, 2, 2, 1, 384, 198, 132, 69,,,, -6, 7, 2, 3, 2, 2, 2, 2, 128, 198, 132, 69,,,, -6, 7, 2, 3, 2, 2, 2, 2, 256, 198, 132, 69,,,, -6, 7, 2, 3, 2, 2, 2, 2, 384, 198, 132, 69,,,, -6, 7, 2, 3, 3, 3, 1, 1, 128, 195, 132, 69,,,, -6, 7, 2, 3, 3, 3, 1, 1, 256, 195, 132, 69,,,, -6, 7, 2, 3, 3, 3, 1, 1, 384, 195, 132, 69,,,, -6, 7, 2, 3, 3, 3, 1, 2, 128, 195, 132, 69,,,, -6, 7, 2, 3, 3, 3, 1, 2, 256, 195, 132, 69,,,, -6, 7, 2, 3, 3, 3, 1, 2, 384, 195, 132, 69,,,, -6, 7, 2, 3, 3, 3, 1, 3, 128, 195, 132, 69,,,, -6, 7, 2, 3, 3, 3, 1, 3, 256, 195, 132, 69,,,, -6, 7, 2, 3, 3, 3, 1, 3, 384, 195, 132, 69,,,, -6, 7, 2, 3, 3, 3, 2, 1, 128, 195, 132, 69,,,, -6, 7, 2, 3, 3, 3, 2, 1, 256, 195, 132, 69,,,, -6, 7, 2, 3, 3, 3, 2, 1, 384, 195, 132, 69,,,, -6, 7, 2, 3, 3, 3, 2, 2, 128, 195, 132, 69,,,, -6, 7, 2, 3, 3, 3, 2, 2, 256, 195, 132, 69,,,, -6, 7, 2, 3, 3, 3, 2, 2, 384, 195, 132, 69,,,, -6, 7, 2, 3, 3, 3, 2, 3, 128, 195, 132, 69,,,, -6, 7, 2, 3, 3, 3, 2, 3, 256, 195, 132, 69,,,, -6, 7, 2, 3, 3, 3, 2, 3, 384, 195, 132, 69,,,, -6, 7, 2, 3, 3, 3, 3, 1, 128, 195, 132, 69,,,, -6, 7, 2, 3, 3, 3, 3, 1, 256, 195, 132, 69,,,, -6, 7, 2, 3, 3, 3, 3, 1, 384, 195, 132, 69,,,, -6, 7, 2, 3, 3, 3, 3, 2, 128, 195, 132, 69,,,, -6, 7, 2, 3, 3, 3, 3, 2, 256, 195, 132, 69,,,, -6, 7, 2, 3, 3, 3, 3, 2, 384, 195, 132, 69,,,, -6, 7, 2, 3, 3, 3, 3, 3, 128, 195, 132, 69,,,, -6, 7, 2, 3, 3, 3, 3, 3, 256, 195, 132, 69,,,, -6, 7, 2, 3, 3, 3, 3, 3, 384, 195, 132, 69,,,, -6, 7, 2, 4, 1, 1, 1, 1, 128, 240, 174, 90,,,, -6, 7, 2, 4, 1, 1, 1, 1, 256, 240, 174, 90,,,, -6, 7, 2, 4, 1, 1, 1, 1, 384, 240, 174, 90,,,, -6, 7, 2, 4, 2, 2, 1, 1, 128, 240, 174, 90,,,, -6, 7, 2, 4, 2, 2, 1, 1, 256, 240, 174, 90,,,, -6, 7, 2, 4, 2, 2, 1, 1, 384, 240, 174, 90,,,, -6, 7, 2, 4, 2, 2, 1, 2, 128, 240, 174, 90,,,, -6, 7, 2, 4, 2, 2, 1, 2, 256, 240, 174, 90,,,, -6, 7, 2, 4, 2, 2, 1, 2, 384, 240, 174, 90,,,, -6, 7, 2, 4, 2, 2, 2, 1, 128, 240, 174, 90,,,, -6, 7, 2, 4, 2, 2, 2, 1, 256, 240, 174, 90,,,, -6, 7, 2, 4, 2, 2, 2, 1, 384, 240, 174, 90,,,, -6, 7, 2, 4, 2, 2, 2, 2, 128, 240, 174, 90,,,, -6, 7, 2, 4, 2, 2, 2, 2, 256, 240, 174, 90,,,, -6, 7, 2, 4, 2, 2, 2, 2, 384, 240, 174, 90,,,, -6, 7, 2, 4, 3, 3, 1, 1, 128, 240, 174, 90,,,, -6, 7, 2, 4, 3, 3, 1, 1, 256, 240, 174, 90,,,, -6, 7, 2, 4, 3, 3, 1, 1, 384, 240, 174, 90,,,, -6, 7, 2, 4, 3, 3, 1, 2, 128, 240, 174, 90,,,, -6, 7, 2, 4, 3, 3, 1, 2, 256, 240, 174, 90,,,, -6, 7, 2, 4, 3, 3, 1, 2, 384, 240, 174, 90,,,, -6, 7, 2, 4, 3, 3, 1, 3, 128, 240, 174, 90,,,, -6, 7, 2, 4, 3, 3, 1, 3, 256, 240, 174, 90,,,, -6, 7, 2, 4, 3, 3, 1, 3, 384, 240, 174, 90,,,, -6, 7, 2, 4, 3, 3, 2, 1, 128, 240, 174, 90,,,, -6, 7, 2, 4, 3, 3, 2, 1, 256, 240, 174, 90,,,, -6, 7, 2, 4, 3, 3, 2, 1, 384, 240, 174, 90,,,, -6, 7, 2, 4, 3, 3, 2, 2, 128, 240, 174, 90,,,, -6, 7, 2, 4, 3, 3, 2, 2, 256, 240, 174, 90,,,, -6, 7, 2, 4, 3, 3, 2, 2, 384, 240, 174, 90,,,, -6, 7, 2, 4, 3, 3, 2, 3, 128, 240, 174, 90,,,, -6, 7, 2, 4, 3, 3, 2, 3, 256, 240, 174, 90,,,, -6, 7, 2, 4, 3, 3, 2, 3, 384, 240, 174, 90,,,, -6, 7, 2, 4, 3, 3, 3, 1, 128, 240, 174, 90,,,, -6, 7, 2, 4, 3, 3, 3, 1, 256, 240, 174, 90,,,, -6, 7, 2, 4, 3, 3, 3, 1, 384, 240, 174, 90,,,, -6, 7, 2, 4, 3, 3, 3, 2, 128, 240, 174, 90,,,, -6, 7, 2, 4, 3, 3, 3, 2, 256, 240, 174, 90,,,, -6, 7, 2, 4, 3, 3, 3, 2, 384, 240, 174, 90,,,, -6, 7, 2, 4, 3, 3, 3, 3, 128, 240, 174, 90,,,, -6, 7, 2, 4, 3, 3, 3, 3, 256, 240, 174, 90,,,, -6, 7, 2, 4, 3, 3, 3, 3, 384, 240, 174, 90,,,, -6, 7, 2, 5, 1, 1, 1, 1, 128, 240, 216, 111,,,, -6, 7, 2, 5, 1, 1, 1, 1, 256, 240, 216, 111,,,, -6, 7, 2, 5, 1, 1, 1, 1, 384, 240, 216, 111,,,, -6, 7, 2, 5, 2, 2, 1, 1, 128, 240, 216, 111,,,, -6, 7, 2, 5, 2, 2, 1, 1, 256, 240, 216, 111,,,, -6, 7, 2, 5, 2, 2, 1, 1, 384, 240, 216, 111,,,, -6, 7, 2, 5, 2, 2, 1, 2, 128, 240, 216, 111,,,, -6, 7, 2, 5, 2, 2, 1, 2, 256, 240, 216, 111,,,, -6, 7, 2, 5, 2, 2, 1, 2, 384, 240, 216, 111,,,, -6, 7, 2, 5, 2, 2, 2, 1, 128, 240, 216, 111,,,, -6, 7, 2, 5, 2, 2, 2, 1, 256, 240, 216, 111,,,, -6, 7, 2, 5, 2, 2, 2, 1, 384, 240, 216, 111,,,, -6, 7, 2, 5, 2, 2, 2, 2, 128, 240, 216, 111,,,, -6, 7, 2, 5, 2, 2, 2, 2, 256, 240, 216, 111,,,, -6, 7, 2, 5, 2, 2, 2, 2, 384, 240, 216, 111,,,, -6, 7, 2, 5, 3, 3, 1, 1, 128, 240, 216, 111,,,, -6, 7, 2, 5, 3, 3, 1, 1, 256, 240, 216, 111,,,, -6, 7, 2, 5, 3, 3, 1, 1, 384, 240, 216, 111,,,, -6, 7, 2, 5, 3, 3, 1, 2, 128, 240, 216, 111,,,, -6, 7, 2, 5, 3, 3, 1, 2, 256, 240, 216, 111,,,, -6, 7, 2, 5, 3, 3, 1, 2, 384, 240, 216, 111,,,, -6, 7, 2, 5, 3, 3, 1, 3, 128, 240, 216, 111,,,, -6, 7, 2, 5, 3, 3, 1, 3, 256, 240, 216, 111,,,, -6, 7, 2, 5, 3, 3, 1, 3, 384, 240, 216, 111,,,, -6, 7, 2, 5, 3, 3, 2, 1, 128, 240, 216, 111,,,, -6, 7, 2, 5, 3, 3, 2, 1, 256, 240, 216, 111,,,, -6, 7, 2, 5, 3, 3, 2, 1, 384, 240, 216, 111,,,, -6, 7, 2, 5, 3, 3, 2, 2, 128, 240, 216, 111,,,, -6, 7, 2, 5, 3, 3, 2, 2, 256, 240, 216, 111,,,, -6, 7, 2, 5, 3, 3, 2, 2, 384, 240, 216, 111,,,, -6, 7, 2, 5, 3, 3, 2, 3, 128, 240, 216, 111,,,, -6, 7, 2, 5, 3, 3, 2, 3, 256, 240, 216, 111,,,, -6, 7, 2, 5, 3, 3, 2, 3, 384, 240, 216, 111,,,, -6, 7, 2, 5, 3, 3, 3, 1, 128, 240, 216, 111,,,, -6, 7, 2, 5, 3, 3, 3, 1, 256, 240, 216, 111,,,, -6, 7, 2, 5, 3, 3, 3, 1, 384, 240, 216, 111,,,, -6, 7, 2, 5, 3, 3, 3, 2, 128, 240, 216, 111,,,, -6, 7, 2, 5, 3, 3, 3, 2, 256, 240, 216, 111,,,, -6, 7, 2, 5, 3, 3, 3, 2, 384, 240, 216, 111,,,, -6, 7, 2, 5, 3, 3, 3, 3, 128, 240, 216, 111,,,, -6, 7, 2, 5, 3, 3, 3, 3, 256, 240, 216, 111,,,, -6, 7, 2, 5, 3, 3, 3, 3, 384, 240, 216, 111,,,, -6, 7, 2, 6, 1, 1, 1, 1, 128, 240, 240, 132,,,, -6, 7, 2, 6, 1, 1, 1, 1, 256, 240, 240, 132,,,, -6, 7, 2, 6, 1, 1, 1, 1, 384, 240, 240, 132,,,, -6, 7, 2, 6, 2, 2, 1, 1, 128, 240, 240, 132,,,, -6, 7, 2, 6, 2, 2, 1, 1, 256, 240, 240, 132,,,, -6, 7, 2, 6, 2, 2, 1, 1, 384, 240, 240, 132,,,, -6, 7, 2, 6, 2, 2, 1, 2, 128, 240, 240, 132,,,, -6, 7, 2, 6, 2, 2, 1, 2, 256, 240, 240, 132,,,, -6, 7, 2, 6, 2, 2, 1, 2, 384, 240, 240, 132,,,, -6, 7, 2, 6, 2, 2, 2, 1, 128, 240, 240, 132,,,, -6, 7, 2, 6, 2, 2, 2, 1, 256, 240, 240, 132,,,, -6, 7, 2, 6, 2, 2, 2, 1, 384, 240, 240, 132,,,, -6, 7, 2, 6, 2, 2, 2, 2, 128, 240, 240, 132,,,, -6, 7, 2, 6, 2, 2, 2, 2, 256, 240, 240, 132,,,, -6, 7, 2, 6, 2, 2, 2, 2, 384, 240, 240, 132,,,, -6, 7, 2, 6, 3, 3, 1, 1, 128, 240, 240, 132,,,, -6, 7, 2, 6, 3, 3, 1, 1, 256, 240, 240, 132,,,, -6, 7, 2, 6, 3, 3, 1, 1, 384, 240, 240, 132,,,, -6, 7, 2, 6, 3, 3, 1, 2, 128, 240, 240, 132,,,, -6, 7, 2, 6, 3, 3, 1, 2, 256, 240, 240, 132,,,, -6, 7, 2, 6, 3, 3, 1, 2, 384, 240, 240, 132,,,, -6, 7, 2, 6, 3, 3, 1, 3, 128, 240, 240, 132,,,, -6, 7, 2, 6, 3, 3, 1, 3, 256, 240, 240, 132,,,, -6, 7, 2, 6, 3, 3, 1, 3, 384, 240, 240, 132,,,, -6, 7, 2, 6, 3, 3, 2, 1, 128, 240, 240, 132,,,, -6, 7, 2, 6, 3, 3, 2, 1, 256, 240, 240, 132,,,, -6, 7, 2, 6, 3, 3, 2, 1, 384, 240, 240, 132,,,, -6, 7, 2, 6, 3, 3, 2, 2, 128, 240, 240, 132,,,, -6, 7, 2, 6, 3, 3, 2, 2, 256, 240, 240, 132,,,, -6, 7, 2, 6, 3, 3, 2, 2, 384, 240, 240, 132,,,, -6, 7, 2, 6, 3, 3, 2, 3, 128, 240, 240, 132,,,, -6, 7, 2, 6, 3, 3, 2, 3, 256, 240, 240, 132,,,, -6, 7, 2, 6, 3, 3, 2, 3, 384, 240, 240, 132,,,, -6, 7, 2, 6, 3, 3, 3, 1, 128, 240, 240, 132,,,, -6, 7, 2, 6, 3, 3, 3, 1, 256, 240, 240, 132,,,, -6, 7, 2, 6, 3, 3, 3, 1, 384, 240, 240, 132,,,, -6, 7, 2, 6, 3, 3, 3, 2, 128, 240, 240, 132,,,, -6, 7, 2, 6, 3, 3, 3, 2, 256, 240, 240, 132,,,, -6, 7, 2, 6, 3, 3, 3, 2, 384, 240, 240, 132,,,, -6, 7, 2, 6, 3, 3, 3, 3, 128, 240, 240, 132,,,, -6, 7, 2, 6, 3, 3, 3, 3, 256, 240, 240, 132,,,, -6, 7, 2, 6, 3, 3, 3, 3, 384, 240, 240, 132,,,, -6, 7, 2, 7, 1, 1, 1, 1, 128, 240, 240, 153,,,, -6, 7, 2, 7, 1, 1, 1, 1, 256, 240, 240, 153,,,, -6, 7, 2, 7, 1, 1, 1, 1, 384, 240, 240, 153,,,, -6, 7, 2, 7, 2, 2, 1, 1, 128, 240, 240, 153,,,, -6, 7, 2, 7, 2, 2, 1, 1, 256, 240, 240, 153,,,, -6, 7, 2, 7, 2, 2, 1, 1, 384, 240, 240, 153,,,, -6, 7, 2, 7, 2, 2, 1, 2, 128, 240, 240, 153,,,, -6, 7, 2, 7, 2, 2, 1, 2, 256, 240, 240, 153,,,, -6, 7, 2, 7, 2, 2, 1, 2, 384, 240, 240, 153,,,, -6, 7, 2, 7, 2, 2, 2, 1, 128, 240, 240, 153,,,, -6, 7, 2, 7, 2, 2, 2, 1, 256, 240, 240, 153,,,, -6, 7, 2, 7, 2, 2, 2, 1, 384, 240, 240, 153,,,, -6, 7, 2, 7, 2, 2, 2, 2, 128, 240, 240, 153,,,, -6, 7, 2, 7, 2, 2, 2, 2, 256, 240, 240, 153,,,, -6, 7, 2, 7, 2, 2, 2, 2, 384, 240, 240, 153,,,, -6, 7, 2, 7, 3, 3, 1, 1, 128, 240, 240, 153,,,, -6, 7, 2, 7, 3, 3, 1, 1, 256, 240, 240, 153,,,, -6, 7, 2, 7, 3, 3, 1, 1, 384, 240, 240, 153,,,, -6, 7, 2, 7, 3, 3, 1, 2, 128, 240, 240, 153,,,, -6, 7, 2, 7, 3, 3, 1, 2, 256, 240, 240, 153,,,, -6, 7, 2, 7, 3, 3, 1, 2, 384, 240, 240, 153,,,, -6, 7, 2, 7, 3, 3, 1, 3, 128, 240, 240, 153,,,, -6, 7, 2, 7, 3, 3, 1, 3, 256, 240, 240, 153,,,, -6, 7, 2, 7, 3, 3, 1, 3, 384, 240, 240, 153,,,, -6, 7, 2, 7, 3, 3, 2, 1, 128, 240, 240, 153,,,, -6, 7, 2, 7, 3, 3, 2, 1, 256, 240, 240, 153,,,, -6, 7, 2, 7, 3, 3, 2, 1, 384, 240, 240, 153,,,, -6, 7, 2, 7, 3, 3, 2, 2, 128, 240, 240, 153,,,, -6, 7, 2, 7, 3, 3, 2, 2, 256, 240, 240, 153,,,, -6, 7, 2, 7, 3, 3, 2, 2, 384, 240, 240, 153,,,, -6, 7, 2, 7, 3, 3, 2, 3, 128, 240, 240, 153,,,, -6, 7, 2, 7, 3, 3, 2, 3, 256, 240, 240, 153,,,, -6, 7, 2, 7, 3, 3, 2, 3, 384, 240, 240, 153,,,, -6, 7, 2, 7, 3, 3, 3, 1, 128, 240, 240, 153,,,, -6, 7, 2, 7, 3, 3, 3, 1, 256, 240, 240, 153,,,, -6, 7, 2, 7, 3, 3, 3, 1, 384, 240, 240, 153,,,, -6, 7, 2, 7, 3, 3, 3, 2, 128, 240, 240, 153,,,, -6, 7, 2, 7, 3, 3, 3, 2, 256, 240, 240, 153,,,, -6, 7, 2, 7, 3, 3, 3, 2, 384, 240, 240, 153,,,, -6, 7, 2, 7, 3, 3, 3, 3, 128, 240, 240, 153,,,, -6, 7, 2, 7, 3, 3, 3, 3, 256, 240, 240, 153,,,, -6, 7, 2, 7, 3, 3, 3, 3, 384, 240, 240, 153,,,, -6, 7, 3, 1, 1, 1, 1, 1, 128, 70, 48, 27,,,, -6, 7, 3, 1, 1, 1, 1, 1, 256, 70, 48, 27,,,, -6, 7, 3, 1, 1, 1, 1, 1, 384, 70, 48, 27,,,, -6, 7, 3, 1, 2, 2, 1, 1, 128, 70, 48, 27,,,, -6, 7, 3, 1, 2, 2, 1, 1, 256, 70, 48, 27,,,, -6, 7, 3, 1, 2, 2, 1, 1, 384, 70, 48, 27,,,, -6, 7, 3, 1, 2, 2, 1, 2, 128, 70, 48, 27,,,, -6, 7, 3, 1, 2, 2, 1, 2, 256, 70, 48, 27,,,, -6, 7, 3, 1, 2, 2, 1, 2, 384, 70, 48, 27,,,, -6, 7, 3, 1, 2, 2, 2, 1, 128, 70, 48, 27,,,, -6, 7, 3, 1, 2, 2, 2, 1, 256, 70, 48, 27,,,, -6, 7, 3, 1, 2, 2, 2, 1, 384, 70, 48, 27,,,, -6, 7, 3, 1, 2, 2, 2, 2, 128, 70, 48, 27,,,, -6, 7, 3, 1, 2, 2, 2, 2, 256, 70, 48, 27,,,, -6, 7, 3, 1, 2, 2, 2, 2, 384, 70, 48, 27,,,, -6, 7, 3, 1, 3, 3, 1, 1, 128, 69, 48, 27,,,, -6, 7, 3, 1, 3, 3, 1, 1, 256, 69, 48, 27,,,, -6, 7, 3, 1, 3, 3, 1, 1, 384, 69, 48, 27,,,, -6, 7, 3, 1, 3, 3, 1, 2, 128, 69, 48, 27,,,, -6, 7, 3, 1, 3, 3, 1, 2, 256, 69, 48, 27,,,, -6, 7, 3, 1, 3, 3, 1, 2, 384, 69, 48, 27,,,, -6, 7, 3, 1, 3, 3, 1, 3, 128, 69, 48, 27,,,, -6, 7, 3, 1, 3, 3, 1, 3, 256, 69, 48, 27,,,, -6, 7, 3, 1, 3, 3, 1, 3, 384, 69, 48, 27,,,, -6, 7, 3, 1, 3, 3, 2, 1, 128, 69, 48, 27,,,, -6, 7, 3, 1, 3, 3, 2, 1, 256, 69, 48, 27,,,, -6, 7, 3, 1, 3, 3, 2, 1, 384, 69, 48, 27,,,, -6, 7, 3, 1, 3, 3, 2, 2, 128, 69, 48, 27,,,, -6, 7, 3, 1, 3, 3, 2, 2, 256, 69, 48, 27,,,, -6, 7, 3, 1, 3, 3, 2, 2, 384, 69, 48, 27,,,, -6, 7, 3, 1, 3, 3, 2, 3, 128, 69, 48, 27,,,, -6, 7, 3, 1, 3, 3, 2, 3, 256, 69, 48, 27,,,, -6, 7, 3, 1, 3, 3, 2, 3, 384, 69, 48, 27,,,, -6, 7, 3, 1, 3, 3, 3, 1, 128, 69, 48, 27,,,, -6, 7, 3, 1, 3, 3, 3, 1, 256, 69, 48, 27,,,, -6, 7, 3, 1, 3, 3, 3, 1, 384, 69, 48, 27,,,, -6, 7, 3, 1, 3, 3, 3, 2, 128, 69, 48, 27,,,, -6, 7, 3, 1, 3, 3, 3, 2, 256, 69, 48, 27,,,, -6, 7, 3, 1, 3, 3, 3, 2, 384, 69, 48, 27,,,, -6, 7, 3, 1, 3, 3, 3, 3, 128, 69, 48, 27,,,, -6, 7, 3, 1, 3, 3, 3, 3, 256, 69, 48, 27,,,, -6, 7, 3, 1, 3, 3, 3, 3, 384, 69, 48, 27,,,, -6, 7, 3, 2, 1, 1, 1, 1, 128, 134, 90, 48,,,, -6, 7, 3, 2, 1, 1, 1, 1, 256, 134, 90, 48,,,, -6, 7, 3, 2, 1, 1, 1, 1, 384, 134, 90, 48,,,, -6, 7, 3, 2, 2, 2, 1, 1, 128, 134, 90, 48,,,, -6, 7, 3, 2, 2, 2, 1, 1, 256, 134, 90, 48,,,, -6, 7, 3, 2, 2, 2, 1, 1, 384, 134, 90, 48,,,, -6, 7, 3, 2, 2, 2, 1, 2, 128, 134, 90, 48,,,, -6, 7, 3, 2, 2, 2, 1, 2, 256, 134, 90, 48,,,, -6, 7, 3, 2, 2, 2, 1, 2, 384, 134, 90, 48,,,, -6, 7, 3, 2, 2, 2, 2, 1, 128, 134, 90, 48,,,, -6, 7, 3, 2, 2, 2, 2, 1, 256, 134, 90, 48,,,, -6, 7, 3, 2, 2, 2, 2, 1, 384, 134, 90, 48,,,, -6, 7, 3, 2, 2, 2, 2, 2, 128, 134, 90, 48,,,, -6, 7, 3, 2, 2, 2, 2, 2, 256, 134, 90, 48,,,, -6, 7, 3, 2, 2, 2, 2, 2, 384, 134, 90, 48,,,, -6, 7, 3, 2, 3, 3, 1, 1, 128, 132, 90, 48,,,, -6, 7, 3, 2, 3, 3, 1, 1, 256, 132, 90, 48,,,, -6, 7, 3, 2, 3, 3, 1, 1, 384, 132, 90, 48,,,, -6, 7, 3, 2, 3, 3, 1, 2, 128, 132, 90, 48,,,, -6, 7, 3, 2, 3, 3, 1, 2, 256, 132, 90, 48,,,, -6, 7, 3, 2, 3, 3, 1, 2, 384, 132, 90, 48,,,, -6, 7, 3, 2, 3, 3, 1, 3, 128, 132, 90, 48,,,, -6, 7, 3, 2, 3, 3, 1, 3, 256, 132, 90, 48,,,, -6, 7, 3, 2, 3, 3, 1, 3, 384, 132, 90, 48,,,, -6, 7, 3, 2, 3, 3, 2, 1, 128, 132, 90, 48,,,, -6, 7, 3, 2, 3, 3, 2, 1, 256, 132, 90, 48,,,, -6, 7, 3, 2, 3, 3, 2, 1, 384, 132, 90, 48,,,, -6, 7, 3, 2, 3, 3, 2, 2, 128, 132, 90, 48,,,, -6, 7, 3, 2, 3, 3, 2, 2, 256, 132, 90, 48,,,, -6, 7, 3, 2, 3, 3, 2, 2, 384, 132, 90, 48,,,, -6, 7, 3, 2, 3, 3, 2, 3, 128, 132, 90, 48,,,, -6, 7, 3, 2, 3, 3, 2, 3, 256, 132, 90, 48,,,, -6, 7, 3, 2, 3, 3, 2, 3, 384, 132, 90, 48,,,, -6, 7, 3, 2, 3, 3, 3, 1, 128, 132, 90, 48,,,, -6, 7, 3, 2, 3, 3, 3, 1, 256, 132, 90, 48,,,, -6, 7, 3, 2, 3, 3, 3, 1, 384, 132, 90, 48,,,, -6, 7, 3, 2, 3, 3, 3, 2, 128, 132, 90, 48,,,, -6, 7, 3, 2, 3, 3, 3, 2, 256, 132, 90, 48,,,, -6, 7, 3, 2, 3, 3, 3, 2, 384, 132, 90, 48,,,, -6, 7, 3, 2, 3, 3, 3, 3, 128, 132, 90, 48,,,, -6, 7, 3, 2, 3, 3, 3, 3, 256, 132, 90, 48,,,, -6, 7, 3, 2, 3, 3, 3, 3, 384, 132, 90, 48,,,, -6, 7, 3, 3, 1, 1, 1, 1, 128, 198, 132, 69,,,, -6, 7, 3, 3, 1, 1, 1, 1, 256, 198, 132, 69,,,, -6, 7, 3, 3, 1, 1, 1, 1, 384, 198, 132, 69,,,, -6, 7, 3, 3, 2, 2, 1, 1, 128, 198, 132, 69,,,, -6, 7, 3, 3, 2, 2, 1, 1, 256, 198, 132, 69,,,, -6, 7, 3, 3, 2, 2, 1, 1, 384, 198, 132, 69,,,, -6, 7, 3, 3, 2, 2, 1, 2, 128, 198, 132, 69,,,, -6, 7, 3, 3, 2, 2, 1, 2, 256, 198, 132, 69,,,, -6, 7, 3, 3, 2, 2, 1, 2, 384, 198, 132, 69,,,, -6, 7, 3, 3, 2, 2, 2, 1, 128, 198, 132, 69,,,, -6, 7, 3, 3, 2, 2, 2, 1, 256, 198, 132, 69,,,, -6, 7, 3, 3, 2, 2, 2, 1, 384, 198, 132, 69,,,, -6, 7, 3, 3, 2, 2, 2, 2, 128, 198, 132, 69,,,, -6, 7, 3, 3, 2, 2, 2, 2, 256, 198, 132, 69,,,, -6, 7, 3, 3, 2, 2, 2, 2, 384, 198, 132, 69,,,, -6, 7, 3, 3, 3, 3, 1, 1, 128, 195, 132, 69,,,, -6, 7, 3, 3, 3, 3, 1, 1, 256, 195, 132, 69,,,, -6, 7, 3, 3, 3, 3, 1, 1, 384, 195, 132, 69,,,, -6, 7, 3, 3, 3, 3, 1, 2, 128, 195, 132, 69,,,, -6, 7, 3, 3, 3, 3, 1, 2, 256, 195, 132, 69,,,, -6, 7, 3, 3, 3, 3, 1, 2, 384, 195, 132, 69,,,, -6, 7, 3, 3, 3, 3, 1, 3, 128, 195, 132, 69,,,, -6, 7, 3, 3, 3, 3, 1, 3, 256, 195, 132, 69,,,, -6, 7, 3, 3, 3, 3, 1, 3, 384, 195, 132, 69,,,, -6, 7, 3, 3, 3, 3, 2, 1, 128, 195, 132, 69,,,, -6, 7, 3, 3, 3, 3, 2, 1, 256, 195, 132, 69,,,, -6, 7, 3, 3, 3, 3, 2, 1, 384, 195, 132, 69,,,, -6, 7, 3, 3, 3, 3, 2, 2, 128, 195, 132, 69,,,, -6, 7, 3, 3, 3, 3, 2, 2, 256, 195, 132, 69,,,, -6, 7, 3, 3, 3, 3, 2, 2, 384, 195, 132, 69,,,, -6, 7, 3, 3, 3, 3, 2, 3, 128, 195, 132, 69,,,, -6, 7, 3, 3, 3, 3, 2, 3, 256, 195, 132, 69,,,, -6, 7, 3, 3, 3, 3, 2, 3, 384, 195, 132, 69,,,, -6, 7, 3, 3, 3, 3, 3, 1, 128, 195, 132, 69,,,, -6, 7, 3, 3, 3, 3, 3, 1, 256, 195, 132, 69,,,, -6, 7, 3, 3, 3, 3, 3, 1, 384, 195, 132, 69,,,, -6, 7, 3, 3, 3, 3, 3, 2, 128, 195, 132, 69,,,, -6, 7, 3, 3, 3, 3, 3, 2, 256, 195, 132, 69,,,, -6, 7, 3, 3, 3, 3, 3, 2, 384, 195, 132, 69,,,, -6, 7, 3, 3, 3, 3, 3, 3, 128, 195, 132, 69,,,, -6, 7, 3, 3, 3, 3, 3, 3, 256, 195, 132, 69,,,, -6, 7, 3, 3, 3, 3, 3, 3, 384, 195, 132, 69,,,, -6, 7, 3, 4, 1, 1, 1, 1, 128, 240, 174, 90,,,, -6, 7, 3, 4, 1, 1, 1, 1, 256, 240, 174, 90,,,, -6, 7, 3, 4, 1, 1, 1, 1, 384, 240, 174, 90,,,, -6, 7, 3, 4, 2, 2, 1, 1, 128, 240, 174, 90,,,, -6, 7, 3, 4, 2, 2, 1, 1, 256, 240, 174, 90,,,, -6, 7, 3, 4, 2, 2, 1, 1, 384, 240, 174, 90,,,, -6, 7, 3, 4, 2, 2, 1, 2, 128, 240, 174, 90,,,, -6, 7, 3, 4, 2, 2, 1, 2, 256, 240, 174, 90,,,, -6, 7, 3, 4, 2, 2, 1, 2, 384, 240, 174, 90,,,, -6, 7, 3, 4, 2, 2, 2, 1, 128, 240, 174, 90,,,, -6, 7, 3, 4, 2, 2, 2, 1, 256, 240, 174, 90,,,, -6, 7, 3, 4, 2, 2, 2, 1, 384, 240, 174, 90,,,, -6, 7, 3, 4, 2, 2, 2, 2, 128, 240, 174, 90,,,, -6, 7, 3, 4, 2, 2, 2, 2, 256, 240, 174, 90,,,, -6, 7, 3, 4, 2, 2, 2, 2, 384, 240, 174, 90,,,, -6, 7, 3, 4, 3, 3, 1, 1, 128, 240, 174, 90,,,, -6, 7, 3, 4, 3, 3, 1, 1, 256, 240, 174, 90,,,, -6, 7, 3, 4, 3, 3, 1, 1, 384, 240, 174, 90,,,, -6, 7, 3, 4, 3, 3, 1, 2, 128, 240, 174, 90,,,, -6, 7, 3, 4, 3, 3, 1, 2, 256, 240, 174, 90,,,, -6, 7, 3, 4, 3, 3, 1, 2, 384, 240, 174, 90,,,, -6, 7, 3, 4, 3, 3, 1, 3, 128, 240, 174, 90,,,, -6, 7, 3, 4, 3, 3, 1, 3, 256, 240, 174, 90,,,, -6, 7, 3, 4, 3, 3, 1, 3, 384, 240, 174, 90,,,, -6, 7, 3, 4, 3, 3, 2, 1, 128, 240, 174, 90,,,, -6, 7, 3, 4, 3, 3, 2, 1, 256, 240, 174, 90,,,, -6, 7, 3, 4, 3, 3, 2, 1, 384, 240, 174, 90,,,, -6, 7, 3, 4, 3, 3, 2, 2, 128, 240, 174, 90,,,, -6, 7, 3, 4, 3, 3, 2, 2, 256, 240, 174, 90,,,, -6, 7, 3, 4, 3, 3, 2, 2, 384, 240, 174, 90,,,, -6, 7, 3, 4, 3, 3, 2, 3, 128, 240, 174, 90,,,, -6, 7, 3, 4, 3, 3, 2, 3, 256, 240, 174, 90,,,, -6, 7, 3, 4, 3, 3, 2, 3, 384, 240, 174, 90,,,, -6, 7, 3, 4, 3, 3, 3, 1, 128, 240, 174, 90,,,, -6, 7, 3, 4, 3, 3, 3, 1, 256, 240, 174, 90,,,, -6, 7, 3, 4, 3, 3, 3, 1, 384, 240, 174, 90,,,, -6, 7, 3, 4, 3, 3, 3, 2, 128, 240, 174, 90,,,, -6, 7, 3, 4, 3, 3, 3, 2, 256, 240, 174, 90,,,, -6, 7, 3, 4, 3, 3, 3, 2, 384, 240, 174, 90,,,, -6, 7, 3, 4, 3, 3, 3, 3, 128, 240, 174, 90,,,, -6, 7, 3, 4, 3, 3, 3, 3, 256, 240, 174, 90,,,, -6, 7, 3, 4, 3, 3, 3, 3, 384, 240, 174, 90,,,, -6, 7, 3, 5, 1, 1, 1, 1, 128, 240, 216, 111,,,, -6, 7, 3, 5, 1, 1, 1, 1, 256, 240, 216, 111,,,, -6, 7, 3, 5, 1, 1, 1, 1, 384, 240, 216, 111,,,, -6, 7, 3, 5, 2, 2, 1, 1, 128, 240, 216, 111,,,, -6, 7, 3, 5, 2, 2, 1, 1, 256, 240, 216, 111,,,, -6, 7, 3, 5, 2, 2, 1, 1, 384, 240, 216, 111,,,, -6, 7, 3, 5, 2, 2, 1, 2, 128, 240, 216, 111,,,, -6, 7, 3, 5, 2, 2, 1, 2, 256, 240, 216, 111,,,, -6, 7, 3, 5, 2, 2, 1, 2, 384, 240, 216, 111,,,, -6, 7, 3, 5, 2, 2, 2, 1, 128, 240, 216, 111,,,, -6, 7, 3, 5, 2, 2, 2, 1, 256, 240, 216, 111,,,, -6, 7, 3, 5, 2, 2, 2, 1, 384, 240, 216, 111,,,, -6, 7, 3, 5, 2, 2, 2, 2, 128, 240, 216, 111,,,, -6, 7, 3, 5, 2, 2, 2, 2, 256, 240, 216, 111,,,, -6, 7, 3, 5, 2, 2, 2, 2, 384, 240, 216, 111,,,, -6, 7, 3, 5, 3, 3, 1, 1, 128, 240, 216, 111,,,, -6, 7, 3, 5, 3, 3, 1, 1, 256, 240, 216, 111,,,, -6, 7, 3, 5, 3, 3, 1, 1, 384, 240, 216, 111,,,, -6, 7, 3, 5, 3, 3, 1, 2, 128, 240, 216, 111,,,, -6, 7, 3, 5, 3, 3, 1, 2, 256, 240, 216, 111,,,, -6, 7, 3, 5, 3, 3, 1, 2, 384, 240, 216, 111,,,, -6, 7, 3, 5, 3, 3, 1, 3, 128, 240, 216, 111,,,, -6, 7, 3, 5, 3, 3, 1, 3, 256, 240, 216, 111,,,, -6, 7, 3, 5, 3, 3, 1, 3, 384, 240, 216, 111,,,, -6, 7, 3, 5, 3, 3, 2, 1, 128, 240, 216, 111,,,, -6, 7, 3, 5, 3, 3, 2, 1, 256, 240, 216, 111,,,, -6, 7, 3, 5, 3, 3, 2, 1, 384, 240, 216, 111,,,, -6, 7, 3, 5, 3, 3, 2, 2, 128, 240, 216, 111,,,, -6, 7, 3, 5, 3, 3, 2, 2, 256, 240, 216, 111,,,, -6, 7, 3, 5, 3, 3, 2, 2, 384, 240, 216, 111,,,, -6, 7, 3, 5, 3, 3, 2, 3, 128, 240, 216, 111,,,, -6, 7, 3, 5, 3, 3, 2, 3, 256, 240, 216, 111,,,, -6, 7, 3, 5, 3, 3, 2, 3, 384, 240, 216, 111,,,, -6, 7, 3, 5, 3, 3, 3, 1, 128, 240, 216, 111,,,, -6, 7, 3, 5, 3, 3, 3, 1, 256, 240, 216, 111,,,, -6, 7, 3, 5, 3, 3, 3, 1, 384, 240, 216, 111,,,, -6, 7, 3, 5, 3, 3, 3, 2, 128, 240, 216, 111,,,, -6, 7, 3, 5, 3, 3, 3, 2, 256, 240, 216, 111,,,, -6, 7, 3, 5, 3, 3, 3, 2, 384, 240, 216, 111,,,, -6, 7, 3, 5, 3, 3, 3, 3, 128, 240, 216, 111,,,, -6, 7, 3, 5, 3, 3, 3, 3, 256, 240, 216, 111,,,, -6, 7, 3, 5, 3, 3, 3, 3, 384, 240, 216, 111,,,, -6, 7, 3, 6, 1, 1, 1, 1, 128, 240, 240, 132,,,, -6, 7, 3, 6, 1, 1, 1, 1, 256, 240, 240, 132,,,, -6, 7, 3, 6, 1, 1, 1, 1, 384, 240, 240, 132,,,, -6, 7, 3, 6, 2, 2, 1, 1, 128, 240, 240, 132,,,, -6, 7, 3, 6, 2, 2, 1, 1, 256, 240, 240, 132,,,, -6, 7, 3, 6, 2, 2, 1, 1, 384, 240, 240, 132,,,, -6, 7, 3, 6, 2, 2, 1, 2, 128, 240, 240, 132,,,, -6, 7, 3, 6, 2, 2, 1, 2, 256, 240, 240, 132,,,, -6, 7, 3, 6, 2, 2, 1, 2, 384, 240, 240, 132,,,, -6, 7, 3, 6, 2, 2, 2, 1, 128, 240, 240, 132,,,, -6, 7, 3, 6, 2, 2, 2, 1, 256, 240, 240, 132,,,, -6, 7, 3, 6, 2, 2, 2, 1, 384, 240, 240, 132,,,, -6, 7, 3, 6, 2, 2, 2, 2, 128, 240, 240, 132,,,, -6, 7, 3, 6, 2, 2, 2, 2, 256, 240, 240, 132,,,, -6, 7, 3, 6, 2, 2, 2, 2, 384, 240, 240, 132,,,, -6, 7, 3, 6, 3, 3, 1, 1, 128, 240, 240, 132,,,, -6, 7, 3, 6, 3, 3, 1, 1, 256, 240, 240, 132,,,, -6, 7, 3, 6, 3, 3, 1, 1, 384, 240, 240, 132,,,, -6, 7, 3, 6, 3, 3, 1, 2, 128, 240, 240, 132,,,, -6, 7, 3, 6, 3, 3, 1, 2, 256, 240, 240, 132,,,, -6, 7, 3, 6, 3, 3, 1, 2, 384, 240, 240, 132,,,, -6, 7, 3, 6, 3, 3, 1, 3, 128, 240, 240, 132,,,, -6, 7, 3, 6, 3, 3, 1, 3, 256, 240, 240, 132,,,, -6, 7, 3, 6, 3, 3, 1, 3, 384, 240, 240, 132,,,, -6, 7, 3, 6, 3, 3, 2, 1, 128, 240, 240, 132,,,, -6, 7, 3, 6, 3, 3, 2, 1, 256, 240, 240, 132,,,, -6, 7, 3, 6, 3, 3, 2, 1, 384, 240, 240, 132,,,, -6, 7, 3, 6, 3, 3, 2, 2, 128, 240, 240, 132,,,, -6, 7, 3, 6, 3, 3, 2, 2, 256, 240, 240, 132,,,, -6, 7, 3, 6, 3, 3, 2, 2, 384, 240, 240, 132,,,, -6, 7, 3, 6, 3, 3, 2, 3, 128, 240, 240, 132,,,, -6, 7, 3, 6, 3, 3, 2, 3, 256, 240, 240, 132,,,, -6, 7, 3, 6, 3, 3, 2, 3, 384, 240, 240, 132,,,, -6, 7, 3, 6, 3, 3, 3, 1, 128, 240, 240, 132,,,, -6, 7, 3, 6, 3, 3, 3, 1, 256, 240, 240, 132,,,, -6, 7, 3, 6, 3, 3, 3, 1, 384, 240, 240, 132,,,, -6, 7, 3, 6, 3, 3, 3, 2, 128, 240, 240, 132,,,, -6, 7, 3, 6, 3, 3, 3, 2, 256, 240, 240, 132,,,, -6, 7, 3, 6, 3, 3, 3, 2, 384, 240, 240, 132,,,, -6, 7, 3, 6, 3, 3, 3, 3, 128, 240, 240, 132,,,, -6, 7, 3, 6, 3, 3, 3, 3, 256, 240, 240, 132,,,, -6, 7, 3, 6, 3, 3, 3, 3, 384, 240, 240, 132,,,, -6, 7, 3, 7, 1, 1, 1, 1, 128, 240, 240, 153,,,, -6, 7, 3, 7, 1, 1, 1, 1, 256, 240, 240, 153,,,, -6, 7, 3, 7, 1, 1, 1, 1, 384, 240, 240, 153,,,, -6, 7, 3, 7, 2, 2, 1, 1, 128, 240, 240, 153,,,, -6, 7, 3, 7, 2, 2, 1, 1, 256, 240, 240, 153,,,, -6, 7, 3, 7, 2, 2, 1, 1, 384, 240, 240, 153,,,, -6, 7, 3, 7, 2, 2, 1, 2, 128, 240, 240, 153,,,, -6, 7, 3, 7, 2, 2, 1, 2, 256, 240, 240, 153,,,, -6, 7, 3, 7, 2, 2, 1, 2, 384, 240, 240, 153,,,, -6, 7, 3, 7, 2, 2, 2, 1, 128, 240, 240, 153,,,, -6, 7, 3, 7, 2, 2, 2, 1, 256, 240, 240, 153,,,, -6, 7, 3, 7, 2, 2, 2, 1, 384, 240, 240, 153,,,, -6, 7, 3, 7, 2, 2, 2, 2, 128, 240, 240, 153,,,, -6, 7, 3, 7, 2, 2, 2, 2, 256, 240, 240, 153,,,, -6, 7, 3, 7, 2, 2, 2, 2, 384, 240, 240, 153,,,, -6, 7, 3, 7, 3, 3, 1, 1, 128, 240, 240, 153,,,, -6, 7, 3, 7, 3, 3, 1, 1, 256, 240, 240, 153,,,, -6, 7, 3, 7, 3, 3, 1, 1, 384, 240, 240, 153,,,, -6, 7, 3, 7, 3, 3, 1, 2, 128, 240, 240, 153,,,, -6, 7, 3, 7, 3, 3, 1, 2, 256, 240, 240, 153,,,, -6, 7, 3, 7, 3, 3, 1, 2, 384, 240, 240, 153,,,, -6, 7, 3, 7, 3, 3, 1, 3, 128, 240, 240, 153,,,, -6, 7, 3, 7, 3, 3, 1, 3, 256, 240, 240, 153,,,, -6, 7, 3, 7, 3, 3, 1, 3, 384, 240, 240, 153,,,, -6, 7, 3, 7, 3, 3, 2, 1, 128, 240, 240, 153,,,, -6, 7, 3, 7, 3, 3, 2, 1, 256, 240, 240, 153,,,, -6, 7, 3, 7, 3, 3, 2, 1, 384, 240, 240, 153,,,, -6, 7, 3, 7, 3, 3, 2, 2, 128, 240, 240, 153,,,, -6, 7, 3, 7, 3, 3, 2, 2, 256, 240, 240, 153,,,, -6, 7, 3, 7, 3, 3, 2, 2, 384, 240, 240, 153,,,, -6, 7, 3, 7, 3, 3, 2, 3, 128, 240, 240, 153,,,, -6, 7, 3, 7, 3, 3, 2, 3, 256, 240, 240, 153,,,, -6, 7, 3, 7, 3, 3, 2, 3, 384, 240, 240, 153,,,, -6, 7, 3, 7, 3, 3, 3, 1, 128, 240, 240, 153,,,, -6, 7, 3, 7, 3, 3, 3, 1, 256, 240, 240, 153,,,, -6, 7, 3, 7, 3, 3, 3, 1, 384, 240, 240, 153,,,, -6, 7, 3, 7, 3, 3, 3, 2, 128, 240, 240, 153,,,, -6, 7, 3, 7, 3, 3, 3, 2, 256, 240, 240, 153,,,, -6, 7, 3, 7, 3, 3, 3, 2, 384, 240, 240, 153,,,, -6, 7, 3, 7, 3, 3, 3, 3, 128, 240, 240, 153,,,, -6, 7, 3, 7, 3, 3, 3, 3, 256, 240, 240, 153,,,, -6, 7, 3, 7, 3, 3, 3, 3, 384, 240, 240, 153,,,, -6, 7, 4, 1, 1, 1, 1, 1, 128, 70, 48, 27,,,, -6, 7, 4, 1, 1, 1, 1, 1, 256, 70, 48, 27,,,, -6, 7, 4, 1, 1, 1, 1, 1, 384, 70, 48, 27,,,, -6, 7, 4, 1, 2, 2, 1, 1, 128, 70, 48, 27,,,, -6, 7, 4, 1, 2, 2, 1, 1, 256, 70, 48, 27,,,, -6, 7, 4, 1, 2, 2, 1, 1, 384, 70, 48, 27,,,, -6, 7, 4, 1, 2, 2, 1, 2, 128, 70, 48, 27,,,, -6, 7, 4, 1, 2, 2, 1, 2, 256, 70, 48, 27,,,, -6, 7, 4, 1, 2, 2, 1, 2, 384, 70, 48, 27,,,, -6, 7, 4, 1, 2, 2, 2, 1, 128, 70, 48, 27,,,, -6, 7, 4, 1, 2, 2, 2, 1, 256, 70, 48, 27,,,, -6, 7, 4, 1, 2, 2, 2, 1, 384, 70, 48, 27,,,, -6, 7, 4, 1, 2, 2, 2, 2, 128, 70, 48, 27,,,, -6, 7, 4, 1, 2, 2, 2, 2, 256, 70, 48, 27,,,, -6, 7, 4, 1, 2, 2, 2, 2, 384, 70, 48, 27,,,, -6, 7, 4, 1, 3, 3, 1, 1, 128, 69, 48, 27,,,, -6, 7, 4, 1, 3, 3, 1, 1, 256, 69, 48, 27,,,, -6, 7, 4, 1, 3, 3, 1, 1, 384, 69, 48, 27,,,, -6, 7, 4, 1, 3, 3, 1, 2, 128, 69, 48, 27,,,, -6, 7, 4, 1, 3, 3, 1, 2, 256, 69, 48, 27,,,, -6, 7, 4, 1, 3, 3, 1, 2, 384, 69, 48, 27,,,, -6, 7, 4, 1, 3, 3, 1, 3, 128, 69, 48, 27,,,, -6, 7, 4, 1, 3, 3, 1, 3, 256, 69, 48, 27,,,, -6, 7, 4, 1, 3, 3, 1, 3, 384, 69, 48, 27,,,, -6, 7, 4, 1, 3, 3, 2, 1, 128, 69, 48, 27,,,, -6, 7, 4, 1, 3, 3, 2, 1, 256, 69, 48, 27,,,, -6, 7, 4, 1, 3, 3, 2, 1, 384, 69, 48, 27,,,, -6, 7, 4, 1, 3, 3, 2, 2, 128, 69, 48, 27,,,, -6, 7, 4, 1, 3, 3, 2, 2, 256, 69, 48, 27,,,, -6, 7, 4, 1, 3, 3, 2, 2, 384, 69, 48, 27,,,, -6, 7, 4, 1, 3, 3, 2, 3, 128, 69, 48, 27,,,, -6, 7, 4, 1, 3, 3, 2, 3, 256, 69, 48, 27,,,, -6, 7, 4, 1, 3, 3, 2, 3, 384, 69, 48, 27,,,, -6, 7, 4, 1, 3, 3, 3, 1, 128, 69, 48, 27,,,, -6, 7, 4, 1, 3, 3, 3, 1, 256, 69, 48, 27,,,, -6, 7, 4, 1, 3, 3, 3, 1, 384, 69, 48, 27,,,, -6, 7, 4, 1, 3, 3, 3, 2, 128, 69, 48, 27,,,, -6, 7, 4, 1, 3, 3, 3, 2, 256, 69, 48, 27,,,, -6, 7, 4, 1, 3, 3, 3, 2, 384, 69, 48, 27,,,, -6, 7, 4, 1, 3, 3, 3, 3, 128, 69, 48, 27,,,, -6, 7, 4, 1, 3, 3, 3, 3, 256, 69, 48, 27,,,, -6, 7, 4, 1, 3, 3, 3, 3, 384, 69, 48, 27,,,, -6, 7, 4, 2, 1, 1, 1, 1, 128, 134, 90, 48,,,, -6, 7, 4, 2, 1, 1, 1, 1, 256, 134, 90, 48,,,, -6, 7, 4, 2, 1, 1, 1, 1, 384, 134, 90, 48,,,, -6, 7, 4, 2, 2, 2, 1, 1, 128, 134, 90, 48,,,, -6, 7, 4, 2, 2, 2, 1, 1, 256, 134, 90, 48,,,, -6, 7, 4, 2, 2, 2, 1, 1, 384, 134, 90, 48,,,, -6, 7, 4, 2, 2, 2, 1, 2, 128, 134, 90, 48,,,, -6, 7, 4, 2, 2, 2, 1, 2, 256, 134, 90, 48,,,, -6, 7, 4, 2, 2, 2, 1, 2, 384, 134, 90, 48,,,, -6, 7, 4, 2, 2, 2, 2, 1, 128, 134, 90, 48,,,, -6, 7, 4, 2, 2, 2, 2, 1, 256, 134, 90, 48,,,, -6, 7, 4, 2, 2, 2, 2, 1, 384, 134, 90, 48,,,, -6, 7, 4, 2, 2, 2, 2, 2, 128, 134, 90, 48,,,, -6, 7, 4, 2, 2, 2, 2, 2, 256, 134, 90, 48,,,, -6, 7, 4, 2, 2, 2, 2, 2, 384, 134, 90, 48,,,, -6, 7, 4, 2, 3, 3, 1, 1, 128, 132, 90, 48,,,, -6, 7, 4, 2, 3, 3, 1, 1, 256, 132, 90, 48,,,, -6, 7, 4, 2, 3, 3, 1, 1, 384, 132, 90, 48,,,, -6, 7, 4, 2, 3, 3, 1, 2, 128, 132, 90, 48,,,, -6, 7, 4, 2, 3, 3, 1, 2, 256, 132, 90, 48,,,, -6, 7, 4, 2, 3, 3, 1, 2, 384, 132, 90, 48,,,, -6, 7, 4, 2, 3, 3, 1, 3, 128, 132, 90, 48,,,, -6, 7, 4, 2, 3, 3, 1, 3, 256, 132, 90, 48,,,, -6, 7, 4, 2, 3, 3, 1, 3, 384, 132, 90, 48,,,, -6, 7, 4, 2, 3, 3, 2, 1, 128, 132, 90, 48,,,, -6, 7, 4, 2, 3, 3, 2, 1, 256, 132, 90, 48,,,, -6, 7, 4, 2, 3, 3, 2, 1, 384, 132, 90, 48,,,, -6, 7, 4, 2, 3, 3, 2, 2, 128, 132, 90, 48,,,, -6, 7, 4, 2, 3, 3, 2, 2, 256, 132, 90, 48,,,, -6, 7, 4, 2, 3, 3, 2, 2, 384, 132, 90, 48,,,, -6, 7, 4, 2, 3, 3, 2, 3, 128, 132, 90, 48,,,, -6, 7, 4, 2, 3, 3, 2, 3, 256, 132, 90, 48,,,, -6, 7, 4, 2, 3, 3, 2, 3, 384, 132, 90, 48,,,, -6, 7, 4, 2, 3, 3, 3, 1, 128, 132, 90, 48,,,, -6, 7, 4, 2, 3, 3, 3, 1, 256, 132, 90, 48,,,, -6, 7, 4, 2, 3, 3, 3, 1, 384, 132, 90, 48,,,, -6, 7, 4, 2, 3, 3, 3, 2, 128, 132, 90, 48,,,, -6, 7, 4, 2, 3, 3, 3, 2, 256, 132, 90, 48,,,, -6, 7, 4, 2, 3, 3, 3, 2, 384, 132, 90, 48,,,, -6, 7, 4, 2, 3, 3, 3, 3, 128, 132, 90, 48,,,, -6, 7, 4, 2, 3, 3, 3, 3, 256, 132, 90, 48,,,, -6, 7, 4, 2, 3, 3, 3, 3, 384, 132, 90, 48,,,, -6, 7, 4, 3, 1, 1, 1, 1, 128, 198, 132, 69,,,, -6, 7, 4, 3, 1, 1, 1, 1, 256, 198, 132, 69,,,, -6, 7, 4, 3, 1, 1, 1, 1, 384, 198, 132, 69,,,, -6, 7, 4, 3, 2, 2, 1, 1, 128, 198, 132, 69,,,, -6, 7, 4, 3, 2, 2, 1, 1, 256, 198, 132, 69,,,, -6, 7, 4, 3, 2, 2, 1, 1, 384, 198, 132, 69,,,, -6, 7, 4, 3, 2, 2, 1, 2, 128, 198, 132, 69,,,, -6, 7, 4, 3, 2, 2, 1, 2, 256, 198, 132, 69,,,, -6, 7, 4, 3, 2, 2, 1, 2, 384, 198, 132, 69,,,, -6, 7, 4, 3, 2, 2, 2, 1, 128, 198, 132, 69,,,, -6, 7, 4, 3, 2, 2, 2, 1, 256, 198, 132, 69,,,, -6, 7, 4, 3, 2, 2, 2, 1, 384, 198, 132, 69,,,, -6, 7, 4, 3, 2, 2, 2, 2, 128, 198, 132, 69,,,, -6, 7, 4, 3, 2, 2, 2, 2, 256, 198, 132, 69,,,, -6, 7, 4, 3, 2, 2, 2, 2, 384, 198, 132, 69,,,, -6, 7, 4, 3, 3, 3, 1, 1, 128, 195, 132, 69,,,, -6, 7, 4, 3, 3, 3, 1, 1, 256, 195, 132, 69,,,, -6, 7, 4, 3, 3, 3, 1, 1, 384, 195, 132, 69,,,, -6, 7, 4, 3, 3, 3, 1, 2, 128, 195, 132, 69,,,, -6, 7, 4, 3, 3, 3, 1, 2, 256, 195, 132, 69,,,, -6, 7, 4, 3, 3, 3, 1, 2, 384, 195, 132, 69,,,, -6, 7, 4, 3, 3, 3, 1, 3, 128, 195, 132, 69,,,, -6, 7, 4, 3, 3, 3, 1, 3, 256, 195, 132, 69,,,, -6, 7, 4, 3, 3, 3, 1, 3, 384, 195, 132, 69,,,, -6, 7, 4, 3, 3, 3, 2, 1, 128, 195, 132, 69,,,, -6, 7, 4, 3, 3, 3, 2, 1, 256, 195, 132, 69,,,, -6, 7, 4, 3, 3, 3, 2, 1, 384, 195, 132, 69,,,, -6, 7, 4, 3, 3, 3, 2, 2, 128, 195, 132, 69,,,, -6, 7, 4, 3, 3, 3, 2, 2, 256, 195, 132, 69,,,, -6, 7, 4, 3, 3, 3, 2, 2, 384, 195, 132, 69,,,, -6, 7, 4, 3, 3, 3, 2, 3, 128, 195, 132, 69,,,, -6, 7, 4, 3, 3, 3, 2, 3, 256, 195, 132, 69,,,, -6, 7, 4, 3, 3, 3, 2, 3, 384, 195, 132, 69,,,, -6, 7, 4, 3, 3, 3, 3, 1, 128, 195, 132, 69,,,, -6, 7, 4, 3, 3, 3, 3, 1, 256, 195, 132, 69,,,, -6, 7, 4, 3, 3, 3, 3, 1, 384, 195, 132, 69,,,, -6, 7, 4, 3, 3, 3, 3, 2, 128, 195, 132, 69,,,, -6, 7, 4, 3, 3, 3, 3, 2, 256, 195, 132, 69,,,, -6, 7, 4, 3, 3, 3, 3, 2, 384, 195, 132, 69,,,, -6, 7, 4, 3, 3, 3, 3, 3, 128, 195, 132, 69,,,, -6, 7, 4, 3, 3, 3, 3, 3, 256, 195, 132, 69,,,, -6, 7, 4, 3, 3, 3, 3, 3, 384, 195, 132, 69,,,, -6, 7, 4, 4, 1, 1, 1, 1, 128, 240, 174, 90,,,, -6, 7, 4, 4, 1, 1, 1, 1, 256, 240, 174, 90,,,, -6, 7, 4, 4, 1, 1, 1, 1, 384, 240, 174, 90,,,, -6, 7, 4, 4, 2, 2, 1, 1, 128, 240, 174, 90,,,, -6, 7, 4, 4, 2, 2, 1, 1, 256, 240, 174, 90,,,, -6, 7, 4, 4, 2, 2, 1, 1, 384, 240, 174, 90,,,, -6, 7, 4, 4, 2, 2, 1, 2, 128, 240, 174, 90,,,, -6, 7, 4, 4, 2, 2, 1, 2, 256, 240, 174, 90,,,, -6, 7, 4, 4, 2, 2, 1, 2, 384, 240, 174, 90,,,, -6, 7, 4, 4, 2, 2, 2, 1, 128, 240, 174, 90,,,, -6, 7, 4, 4, 2, 2, 2, 1, 256, 240, 174, 90,,,, -6, 7, 4, 4, 2, 2, 2, 1, 384, 240, 174, 90,,,, -6, 7, 4, 4, 2, 2, 2, 2, 128, 240, 174, 90,,,, -6, 7, 4, 4, 2, 2, 2, 2, 256, 240, 174, 90,,,, -6, 7, 4, 4, 2, 2, 2, 2, 384, 240, 174, 90,,,, -6, 7, 4, 4, 3, 3, 1, 1, 128, 240, 174, 90,,,, -6, 7, 4, 4, 3, 3, 1, 1, 256, 240, 174, 90,,,, -6, 7, 4, 4, 3, 3, 1, 1, 384, 240, 174, 90,,,, -6, 7, 4, 4, 3, 3, 1, 2, 128, 240, 174, 90,,,, -6, 7, 4, 4, 3, 3, 1, 2, 256, 240, 174, 90,,,, -6, 7, 4, 4, 3, 3, 1, 2, 384, 240, 174, 90,,,, -6, 7, 4, 4, 3, 3, 1, 3, 128, 240, 174, 90,,,, -6, 7, 4, 4, 3, 3, 1, 3, 256, 240, 174, 90,,,, -6, 7, 4, 4, 3, 3, 1, 3, 384, 240, 174, 90,,,, -6, 7, 4, 4, 3, 3, 2, 1, 128, 240, 174, 90,,,, -6, 7, 4, 4, 3, 3, 2, 1, 256, 240, 174, 90,,,, -6, 7, 4, 4, 3, 3, 2, 1, 384, 240, 174, 90,,,, -6, 7, 4, 4, 3, 3, 2, 2, 128, 240, 174, 90,,,, -6, 7, 4, 4, 3, 3, 2, 2, 256, 240, 174, 90,,,, -6, 7, 4, 4, 3, 3, 2, 2, 384, 240, 174, 90,,,, -6, 7, 4, 4, 3, 3, 2, 3, 128, 240, 174, 90,,,, -6, 7, 4, 4, 3, 3, 2, 3, 256, 240, 174, 90,,,, -6, 7, 4, 4, 3, 3, 2, 3, 384, 240, 174, 90,,,, -6, 7, 4, 4, 3, 3, 3, 1, 128, 240, 174, 90,,,, -6, 7, 4, 4, 3, 3, 3, 1, 256, 240, 174, 90,,,, -6, 7, 4, 4, 3, 3, 3, 1, 384, 240, 174, 90,,,, -6, 7, 4, 4, 3, 3, 3, 2, 128, 240, 174, 90,,,, -6, 7, 4, 4, 3, 3, 3, 2, 256, 240, 174, 90,,,, -6, 7, 4, 4, 3, 3, 3, 2, 384, 240, 174, 90,,,, -6, 7, 4, 4, 3, 3, 3, 3, 128, 240, 174, 90,,,, -6, 7, 4, 4, 3, 3, 3, 3, 256, 240, 174, 90,,,, -6, 7, 4, 4, 3, 3, 3, 3, 384, 240, 174, 90,,,, -6, 7, 4, 5, 1, 1, 1, 1, 128, 240, 216, 111,,,, -6, 7, 4, 5, 1, 1, 1, 1, 256, 240, 216, 111,,,, -6, 7, 4, 5, 1, 1, 1, 1, 384, 240, 216, 111,,,, -6, 7, 4, 5, 2, 2, 1, 1, 128, 240, 216, 111,,,, -6, 7, 4, 5, 2, 2, 1, 1, 256, 240, 216, 111,,,, -6, 7, 4, 5, 2, 2, 1, 1, 384, 240, 216, 111,,,, -6, 7, 4, 5, 2, 2, 1, 2, 128, 240, 216, 111,,,, -6, 7, 4, 5, 2, 2, 1, 2, 256, 240, 216, 111,,,, -6, 7, 4, 5, 2, 2, 1, 2, 384, 240, 216, 111,,,, -6, 7, 4, 5, 2, 2, 2, 1, 128, 240, 216, 111,,,, -6, 7, 4, 5, 2, 2, 2, 1, 256, 240, 216, 111,,,, -6, 7, 4, 5, 2, 2, 2, 1, 384, 240, 216, 111,,,, -6, 7, 4, 5, 2, 2, 2, 2, 128, 240, 216, 111,,,, -6, 7, 4, 5, 2, 2, 2, 2, 256, 240, 216, 111,,,, -6, 7, 4, 5, 2, 2, 2, 2, 384, 240, 216, 111,,,, -6, 7, 4, 5, 3, 3, 1, 1, 128, 240, 216, 111,,,, -6, 7, 4, 5, 3, 3, 1, 1, 256, 240, 216, 111,,,, -6, 7, 4, 5, 3, 3, 1, 1, 384, 240, 216, 111,,,, -6, 7, 4, 5, 3, 3, 1, 2, 128, 240, 216, 111,,,, -6, 7, 4, 5, 3, 3, 1, 2, 256, 240, 216, 111,,,, -6, 7, 4, 5, 3, 3, 1, 2, 384, 240, 216, 111,,,, -6, 7, 4, 5, 3, 3, 1, 3, 128, 240, 216, 111,,,, -6, 7, 4, 5, 3, 3, 1, 3, 256, 240, 216, 111,,,, -6, 7, 4, 5, 3, 3, 1, 3, 384, 240, 216, 111,,,, -6, 7, 4, 5, 3, 3, 2, 1, 128, 240, 216, 111,,,, -6, 7, 4, 5, 3, 3, 2, 1, 256, 240, 216, 111,,,, -6, 7, 4, 5, 3, 3, 2, 1, 384, 240, 216, 111,,,, -6, 7, 4, 5, 3, 3, 2, 2, 128, 240, 216, 111,,,, -6, 7, 4, 5, 3, 3, 2, 2, 256, 240, 216, 111,,,, -6, 7, 4, 5, 3, 3, 2, 2, 384, 240, 216, 111,,,, -6, 7, 4, 5, 3, 3, 2, 3, 128, 240, 216, 111,,,, -6, 7, 4, 5, 3, 3, 2, 3, 256, 240, 216, 111,,,, -6, 7, 4, 5, 3, 3, 2, 3, 384, 240, 216, 111,,,, -6, 7, 4, 5, 3, 3, 3, 1, 128, 240, 216, 111,,,, -6, 7, 4, 5, 3, 3, 3, 1, 256, 240, 216, 111,,,, -6, 7, 4, 5, 3, 3, 3, 1, 384, 240, 216, 111,,,, -6, 7, 4, 5, 3, 3, 3, 2, 128, 240, 216, 111,,,, -6, 7, 4, 5, 3, 3, 3, 2, 256, 240, 216, 111,,,, -6, 7, 4, 5, 3, 3, 3, 2, 384, 240, 216, 111,,,, -6, 7, 4, 5, 3, 3, 3, 3, 128, 240, 216, 111,,,, -6, 7, 4, 5, 3, 3, 3, 3, 256, 240, 216, 111,,,, -6, 7, 4, 5, 3, 3, 3, 3, 384, 240, 216, 111,,,, -6, 7, 4, 6, 1, 1, 1, 1, 128, 240, 240, 132,,,, -6, 7, 4, 6, 1, 1, 1, 1, 256, 240, 240, 132,,,, -6, 7, 4, 6, 1, 1, 1, 1, 384, 240, 240, 132,,,, -6, 7, 4, 6, 2, 2, 1, 1, 128, 240, 240, 132,,,, -6, 7, 4, 6, 2, 2, 1, 1, 256, 240, 240, 132,,,, -6, 7, 4, 6, 2, 2, 1, 1, 384, 240, 240, 132,,,, -6, 7, 4, 6, 2, 2, 1, 2, 128, 240, 240, 132,,,, -6, 7, 4, 6, 2, 2, 1, 2, 256, 240, 240, 132,,,, -6, 7, 4, 6, 2, 2, 1, 2, 384, 240, 240, 132,,,, -6, 7, 4, 6, 2, 2, 2, 1, 128, 240, 240, 132,,,, -6, 7, 4, 6, 2, 2, 2, 1, 256, 240, 240, 132,,,, -6, 7, 4, 6, 2, 2, 2, 1, 384, 240, 240, 132,,,, -6, 7, 4, 6, 2, 2, 2, 2, 128, 240, 240, 132,,,, -6, 7, 4, 6, 2, 2, 2, 2, 256, 240, 240, 132,,,, -6, 7, 4, 6, 2, 2, 2, 2, 384, 240, 240, 132,,,, -6, 7, 4, 6, 3, 3, 1, 1, 128, 240, 240, 132,,,, -6, 7, 4, 6, 3, 3, 1, 1, 256, 240, 240, 132,,,, -6, 7, 4, 6, 3, 3, 1, 1, 384, 240, 240, 132,,,, -6, 7, 4, 6, 3, 3, 1, 2, 128, 240, 240, 132,,,, -6, 7, 4, 6, 3, 3, 1, 2, 256, 240, 240, 132,,,, -6, 7, 4, 6, 3, 3, 1, 2, 384, 240, 240, 132,,,, -6, 7, 4, 6, 3, 3, 1, 3, 128, 240, 240, 132,,,, -6, 7, 4, 6, 3, 3, 1, 3, 256, 240, 240, 132,,,, -6, 7, 4, 6, 3, 3, 1, 3, 384, 240, 240, 132,,,, -6, 7, 4, 6, 3, 3, 2, 1, 128, 240, 240, 132,,,, -6, 7, 4, 6, 3, 3, 2, 1, 256, 240, 240, 132,,,, -6, 7, 4, 6, 3, 3, 2, 1, 384, 240, 240, 132,,,, -6, 7, 4, 6, 3, 3, 2, 2, 128, 240, 240, 132,,,, -6, 7, 4, 6, 3, 3, 2, 2, 256, 240, 240, 132,,,, -6, 7, 4, 6, 3, 3, 2, 2, 384, 240, 240, 132,,,, -6, 7, 4, 6, 3, 3, 2, 3, 128, 240, 240, 132,,,, -6, 7, 4, 6, 3, 3, 2, 3, 256, 240, 240, 132,,,, -6, 7, 4, 6, 3, 3, 2, 3, 384, 240, 240, 132,,,, -6, 7, 4, 6, 3, 3, 3, 1, 128, 240, 240, 132,,,, -6, 7, 4, 6, 3, 3, 3, 1, 256, 240, 240, 132,,,, -6, 7, 4, 6, 3, 3, 3, 1, 384, 240, 240, 132,,,, -6, 7, 4, 6, 3, 3, 3, 2, 128, 240, 240, 132,,,, -6, 7, 4, 6, 3, 3, 3, 2, 256, 240, 240, 132,,,, -6, 7, 4, 6, 3, 3, 3, 2, 384, 240, 240, 132,,,, -6, 7, 4, 6, 3, 3, 3, 3, 128, 240, 240, 132,,,, -6, 7, 4, 6, 3, 3, 3, 3, 256, 240, 240, 132,,,, -6, 7, 4, 6, 3, 3, 3, 3, 384, 240, 240, 132,,,, -6, 7, 4, 7, 1, 1, 1, 1, 128, 240, 240, 153,,,, -6, 7, 4, 7, 1, 1, 1, 1, 256, 240, 240, 153,,,, -6, 7, 4, 7, 1, 1, 1, 1, 384, 240, 240, 153,,,, -6, 7, 4, 7, 2, 2, 1, 1, 128, 240, 240, 153,,,, -6, 7, 4, 7, 2, 2, 1, 1, 256, 240, 240, 153,,,, -6, 7, 4, 7, 2, 2, 1, 1, 384, 240, 240, 153,,,, -6, 7, 4, 7, 2, 2, 1, 2, 128, 240, 240, 153,,,, -6, 7, 4, 7, 2, 2, 1, 2, 256, 240, 240, 153,,,, -6, 7, 4, 7, 2, 2, 1, 2, 384, 240, 240, 153,,,, -6, 7, 4, 7, 2, 2, 2, 1, 128, 240, 240, 153,,,, -6, 7, 4, 7, 2, 2, 2, 1, 256, 240, 240, 153,,,, -6, 7, 4, 7, 2, 2, 2, 1, 384, 240, 240, 153,,,, -6, 7, 4, 7, 2, 2, 2, 2, 128, 240, 240, 153,,,, -6, 7, 4, 7, 2, 2, 2, 2, 256, 240, 240, 153,,,, -6, 7, 4, 7, 2, 2, 2, 2, 384, 240, 240, 153,,,, -6, 7, 4, 7, 3, 3, 1, 1, 128, 240, 240, 153,,,, -6, 7, 4, 7, 3, 3, 1, 1, 256, 240, 240, 153,,,, -6, 7, 4, 7, 3, 3, 1, 1, 384, 240, 240, 153,,,, -6, 7, 4, 7, 3, 3, 1, 2, 128, 240, 240, 153,,,, -6, 7, 4, 7, 3, 3, 1, 2, 256, 240, 240, 153,,,, -6, 7, 4, 7, 3, 3, 1, 2, 384, 240, 240, 153,,,, -6, 7, 4, 7, 3, 3, 1, 3, 128, 240, 240, 153,,,, -6, 7, 4, 7, 3, 3, 1, 3, 256, 240, 240, 153,,,, -6, 7, 4, 7, 3, 3, 1, 3, 384, 240, 240, 153,,,, -6, 7, 4, 7, 3, 3, 2, 1, 128, 240, 240, 153,,,, -6, 7, 4, 7, 3, 3, 2, 1, 256, 240, 240, 153,,,, -6, 7, 4, 7, 3, 3, 2, 1, 384, 240, 240, 153,,,, -6, 7, 4, 7, 3, 3, 2, 2, 128, 240, 240, 153,,,, -6, 7, 4, 7, 3, 3, 2, 2, 256, 240, 240, 153,,,, -6, 7, 4, 7, 3, 3, 2, 2, 384, 240, 240, 153,,,, -6, 7, 4, 7, 3, 3, 2, 3, 128, 240, 240, 153,,,, -6, 7, 4, 7, 3, 3, 2, 3, 256, 240, 240, 153,,,, -6, 7, 4, 7, 3, 3, 2, 3, 384, 240, 240, 153,,,, -6, 7, 4, 7, 3, 3, 3, 1, 128, 240, 240, 153,,,, -6, 7, 4, 7, 3, 3, 3, 1, 256, 240, 240, 153,,,, -6, 7, 4, 7, 3, 3, 3, 1, 384, 240, 240, 153,,,, -6, 7, 4, 7, 3, 3, 3, 2, 128, 240, 240, 153,,,, -6, 7, 4, 7, 3, 3, 3, 2, 256, 240, 240, 153,,,, -6, 7, 4, 7, 3, 3, 3, 2, 384, 240, 240, 153,,,, -6, 7, 4, 7, 3, 3, 3, 3, 128, 240, 240, 153,,,, -6, 7, 4, 7, 3, 3, 3, 3, 256, 240, 240, 153,,,, -6, 7, 4, 7, 3, 3, 3, 3, 384, 240, 240, 153,,,, -6, 7, 5, 1, 1, 1, 1, 1, 128, 70, 48, 27,,,, -6, 7, 5, 1, 1, 1, 1, 1, 256, 70, 48, 27,,,, -6, 7, 5, 1, 1, 1, 1, 1, 384, 70, 48, 27,,,, -6, 7, 5, 1, 2, 2, 1, 1, 128, 70, 48, 27,,,, -6, 7, 5, 1, 2, 2, 1, 1, 256, 70, 48, 27,,,, -6, 7, 5, 1, 2, 2, 1, 1, 384, 70, 48, 27,,,, -6, 7, 5, 1, 2, 2, 1, 2, 128, 70, 48, 27,,,, -6, 7, 5, 1, 2, 2, 1, 2, 256, 70, 48, 27,,,, -6, 7, 5, 1, 2, 2, 1, 2, 384, 70, 48, 27,,,, -6, 7, 5, 1, 2, 2, 2, 1, 128, 70, 48, 27,,,, -6, 7, 5, 1, 2, 2, 2, 1, 256, 70, 48, 27,,,, -6, 7, 5, 1, 2, 2, 2, 1, 384, 70, 48, 27,,,, -6, 7, 5, 1, 2, 2, 2, 2, 128, 70, 48, 27,,,, -6, 7, 5, 1, 2, 2, 2, 2, 256, 70, 48, 27,,,, -6, 7, 5, 1, 2, 2, 2, 2, 384, 70, 48, 27,,,, -6, 7, 5, 1, 3, 3, 1, 1, 128, 69, 48, 27,,,, -6, 7, 5, 1, 3, 3, 1, 1, 256, 69, 48, 27,,,, -6, 7, 5, 1, 3, 3, 1, 1, 384, 69, 48, 27,,,, -6, 7, 5, 1, 3, 3, 1, 2, 128, 69, 48, 27,,,, -6, 7, 5, 1, 3, 3, 1, 2, 256, 69, 48, 27,,,, -6, 7, 5, 1, 3, 3, 1, 2, 384, 69, 48, 27,,,, -6, 7, 5, 1, 3, 3, 1, 3, 128, 69, 48, 27,,,, -6, 7, 5, 1, 3, 3, 1, 3, 256, 69, 48, 27,,,, -6, 7, 5, 1, 3, 3, 1, 3, 384, 69, 48, 27,,,, -6, 7, 5, 1, 3, 3, 2, 1, 128, 69, 48, 27,,,, -6, 7, 5, 1, 3, 3, 2, 1, 256, 69, 48, 27,,,, -6, 7, 5, 1, 3, 3, 2, 1, 384, 69, 48, 27,,,, -6, 7, 5, 1, 3, 3, 2, 2, 128, 69, 48, 27,,,, -6, 7, 5, 1, 3, 3, 2, 2, 256, 69, 48, 27,,,, -6, 7, 5, 1, 3, 3, 2, 2, 384, 69, 48, 27,,,, -6, 7, 5, 1, 3, 3, 2, 3, 128, 69, 48, 27,,,, -6, 7, 5, 1, 3, 3, 2, 3, 256, 69, 48, 27,,,, -6, 7, 5, 1, 3, 3, 2, 3, 384, 69, 48, 27,,,, -6, 7, 5, 1, 3, 3, 3, 1, 128, 69, 48, 27,,,, -6, 7, 5, 1, 3, 3, 3, 1, 256, 69, 48, 27,,,, -6, 7, 5, 1, 3, 3, 3, 1, 384, 69, 48, 27,,,, -6, 7, 5, 1, 3, 3, 3, 2, 128, 69, 48, 27,,,, -6, 7, 5, 1, 3, 3, 3, 2, 256, 69, 48, 27,,,, -6, 7, 5, 1, 3, 3, 3, 2, 384, 69, 48, 27,,,, -6, 7, 5, 1, 3, 3, 3, 3, 128, 69, 48, 27,,,, -6, 7, 5, 1, 3, 3, 3, 3, 256, 69, 48, 27,,,, -6, 7, 5, 1, 3, 3, 3, 3, 384, 69, 48, 27,,,, -6, 7, 5, 2, 1, 1, 1, 1, 128, 134, 90, 48,,,, -6, 7, 5, 2, 1, 1, 1, 1, 256, 134, 90, 48,,,, -6, 7, 5, 2, 1, 1, 1, 1, 384, 134, 90, 48,,,, -6, 7, 5, 2, 2, 2, 1, 1, 128, 134, 90, 48,,,, -6, 7, 5, 2, 2, 2, 1, 1, 256, 134, 90, 48,,,, -6, 7, 5, 2, 2, 2, 1, 1, 384, 134, 90, 48,,,, -6, 7, 5, 2, 2, 2, 1, 2, 128, 134, 90, 48,,,, -6, 7, 5, 2, 2, 2, 1, 2, 256, 134, 90, 48,,,, -6, 7, 5, 2, 2, 2, 1, 2, 384, 134, 90, 48,,,, -6, 7, 5, 2, 2, 2, 2, 1, 128, 134, 90, 48,,,, -6, 7, 5, 2, 2, 2, 2, 1, 256, 134, 90, 48,,,, -6, 7, 5, 2, 2, 2, 2, 1, 384, 134, 90, 48,,,, -6, 7, 5, 2, 2, 2, 2, 2, 128, 134, 90, 48,,,, -6, 7, 5, 2, 2, 2, 2, 2, 256, 134, 90, 48,,,, -6, 7, 5, 2, 2, 2, 2, 2, 384, 134, 90, 48,,,, -6, 7, 5, 2, 3, 3, 1, 1, 128, 132, 90, 48,,,, -6, 7, 5, 2, 3, 3, 1, 1, 256, 132, 90, 48,,,, -6, 7, 5, 2, 3, 3, 1, 1, 384, 132, 90, 48,,,, -6, 7, 5, 2, 3, 3, 1, 2, 128, 132, 90, 48,,,, -6, 7, 5, 2, 3, 3, 1, 2, 256, 132, 90, 48,,,, -6, 7, 5, 2, 3, 3, 1, 2, 384, 132, 90, 48,,,, -6, 7, 5, 2, 3, 3, 1, 3, 128, 132, 90, 48,,,, -6, 7, 5, 2, 3, 3, 1, 3, 256, 132, 90, 48,,,, -6, 7, 5, 2, 3, 3, 1, 3, 384, 132, 90, 48,,,, -6, 7, 5, 2, 3, 3, 2, 1, 128, 132, 90, 48,,,, -6, 7, 5, 2, 3, 3, 2, 1, 256, 132, 90, 48,,,, -6, 7, 5, 2, 3, 3, 2, 1, 384, 132, 90, 48,,,, -6, 7, 5, 2, 3, 3, 2, 2, 128, 132, 90, 48,,,, -6, 7, 5, 2, 3, 3, 2, 2, 256, 132, 90, 48,,,, -6, 7, 5, 2, 3, 3, 2, 2, 384, 132, 90, 48,,,, -6, 7, 5, 2, 3, 3, 2, 3, 128, 132, 90, 48,,,, -6, 7, 5, 2, 3, 3, 2, 3, 256, 132, 90, 48,,,, -6, 7, 5, 2, 3, 3, 2, 3, 384, 132, 90, 48,,,, -6, 7, 5, 2, 3, 3, 3, 1, 128, 132, 90, 48,,,, -6, 7, 5, 2, 3, 3, 3, 1, 256, 132, 90, 48,,,, -6, 7, 5, 2, 3, 3, 3, 1, 384, 132, 90, 48,,,, -6, 7, 5, 2, 3, 3, 3, 2, 128, 132, 90, 48,,,, -6, 7, 5, 2, 3, 3, 3, 2, 256, 132, 90, 48,,,, -6, 7, 5, 2, 3, 3, 3, 2, 384, 132, 90, 48,,,, -6, 7, 5, 2, 3, 3, 3, 3, 128, 132, 90, 48,,,, -6, 7, 5, 2, 3, 3, 3, 3, 256, 132, 90, 48,,,, -6, 7, 5, 2, 3, 3, 3, 3, 384, 132, 90, 48,,,, -6, 7, 5, 3, 1, 1, 1, 1, 128, 198, 132, 69,,,, -6, 7, 5, 3, 1, 1, 1, 1, 256, 198, 132, 69,,,, -6, 7, 5, 3, 1, 1, 1, 1, 384, 198, 132, 69,,,, -6, 7, 5, 3, 2, 2, 1, 1, 128, 198, 132, 69,,,, -6, 7, 5, 3, 2, 2, 1, 1, 256, 198, 132, 69,,,, -6, 7, 5, 3, 2, 2, 1, 1, 384, 198, 132, 69,,,, -6, 7, 5, 3, 2, 2, 1, 2, 128, 198, 132, 69,,,, -6, 7, 5, 3, 2, 2, 1, 2, 256, 198, 132, 69,,,, -6, 7, 5, 3, 2, 2, 1, 2, 384, 198, 132, 69,,,, -6, 7, 5, 3, 2, 2, 2, 1, 128, 198, 132, 69,,,, -6, 7, 5, 3, 2, 2, 2, 1, 256, 198, 132, 69,,,, -6, 7, 5, 3, 2, 2, 2, 1, 384, 198, 132, 69,,,, -6, 7, 5, 3, 2, 2, 2, 2, 128, 198, 132, 69,,,, -6, 7, 5, 3, 2, 2, 2, 2, 256, 198, 132, 69,,,, -6, 7, 5, 3, 2, 2, 2, 2, 384, 198, 132, 69,,,, -6, 7, 5, 3, 3, 3, 1, 1, 128, 195, 132, 69,,,, -6, 7, 5, 3, 3, 3, 1, 1, 256, 195, 132, 69,,,, -6, 7, 5, 3, 3, 3, 1, 1, 384, 195, 132, 69,,,, -6, 7, 5, 3, 3, 3, 1, 2, 128, 195, 132, 69,,,, -6, 7, 5, 3, 3, 3, 1, 2, 256, 195, 132, 69,,,, -6, 7, 5, 3, 3, 3, 1, 2, 384, 195, 132, 69,,,, -6, 7, 5, 3, 3, 3, 1, 3, 128, 195, 132, 69,,,, -6, 7, 5, 3, 3, 3, 1, 3, 256, 195, 132, 69,,,, -6, 7, 5, 3, 3, 3, 1, 3, 384, 195, 132, 69,,,, -6, 7, 5, 3, 3, 3, 2, 1, 128, 195, 132, 69,,,, -6, 7, 5, 3, 3, 3, 2, 1, 256, 195, 132, 69,,,, -6, 7, 5, 3, 3, 3, 2, 1, 384, 195, 132, 69,,,, -6, 7, 5, 3, 3, 3, 2, 2, 128, 195, 132, 69,,,, -6, 7, 5, 3, 3, 3, 2, 2, 256, 195, 132, 69,,,, -6, 7, 5, 3, 3, 3, 2, 2, 384, 195, 132, 69,,,, -6, 7, 5, 3, 3, 3, 2, 3, 128, 195, 132, 69,,,, -6, 7, 5, 3, 3, 3, 2, 3, 256, 195, 132, 69,,,, -6, 7, 5, 3, 3, 3, 2, 3, 384, 195, 132, 69,,,, -6, 7, 5, 3, 3, 3, 3, 1, 128, 195, 132, 69,,,, -6, 7, 5, 3, 3, 3, 3, 1, 256, 195, 132, 69,,,, -6, 7, 5, 3, 3, 3, 3, 1, 384, 195, 132, 69,,,, -6, 7, 5, 3, 3, 3, 3, 2, 128, 195, 132, 69,,,, -6, 7, 5, 3, 3, 3, 3, 2, 256, 195, 132, 69,,,, -6, 7, 5, 3, 3, 3, 3, 2, 384, 195, 132, 69,,,, -6, 7, 5, 3, 3, 3, 3, 3, 128, 195, 132, 69,,,, -6, 7, 5, 3, 3, 3, 3, 3, 256, 195, 132, 69,,,, -6, 7, 5, 3, 3, 3, 3, 3, 384, 195, 132, 69,,,, -6, 7, 5, 4, 1, 1, 1, 1, 128, 240, 174, 90,,,, -6, 7, 5, 4, 1, 1, 1, 1, 256, 240, 174, 90,,,, -6, 7, 5, 4, 1, 1, 1, 1, 384, 240, 174, 90,,,, -6, 7, 5, 4, 2, 2, 1, 1, 128, 240, 174, 90,,,, -6, 7, 5, 4, 2, 2, 1, 1, 256, 240, 174, 90,,,, -6, 7, 5, 4, 2, 2, 1, 1, 384, 240, 174, 90,,,, -6, 7, 5, 4, 2, 2, 1, 2, 128, 240, 174, 90,,,, -6, 7, 5, 4, 2, 2, 1, 2, 256, 240, 174, 90,,,, -6, 7, 5, 4, 2, 2, 1, 2, 384, 240, 174, 90,,,, -6, 7, 5, 4, 2, 2, 2, 1, 128, 240, 174, 90,,,, -6, 7, 5, 4, 2, 2, 2, 1, 256, 240, 174, 90,,,, -6, 7, 5, 4, 2, 2, 2, 1, 384, 240, 174, 90,,,, -6, 7, 5, 4, 2, 2, 2, 2, 128, 240, 174, 90,,,, -6, 7, 5, 4, 2, 2, 2, 2, 256, 240, 174, 90,,,, -6, 7, 5, 4, 2, 2, 2, 2, 384, 240, 174, 90,,,, -6, 7, 5, 4, 3, 3, 1, 1, 128, 240, 174, 90,,,, -6, 7, 5, 4, 3, 3, 1, 1, 256, 240, 174, 90,,,, -6, 7, 5, 4, 3, 3, 1, 1, 384, 240, 174, 90,,,, -6, 7, 5, 4, 3, 3, 1, 2, 128, 240, 174, 90,,,, -6, 7, 5, 4, 3, 3, 1, 2, 256, 240, 174, 90,,,, -6, 7, 5, 4, 3, 3, 1, 2, 384, 240, 174, 90,,,, -6, 7, 5, 4, 3, 3, 1, 3, 128, 240, 174, 90,,,, -6, 7, 5, 4, 3, 3, 1, 3, 256, 240, 174, 90,,,, -6, 7, 5, 4, 3, 3, 1, 3, 384, 240, 174, 90,,,, -6, 7, 5, 4, 3, 3, 2, 1, 128, 240, 174, 90,,,, -6, 7, 5, 4, 3, 3, 2, 1, 256, 240, 174, 90,,,, -6, 7, 5, 4, 3, 3, 2, 1, 384, 240, 174, 90,,,, -6, 7, 5, 4, 3, 3, 2, 2, 128, 240, 174, 90,,,, -6, 7, 5, 4, 3, 3, 2, 2, 256, 240, 174, 90,,,, -6, 7, 5, 4, 3, 3, 2, 2, 384, 240, 174, 90,,,, -6, 7, 5, 4, 3, 3, 2, 3, 128, 240, 174, 90,,,, -6, 7, 5, 4, 3, 3, 2, 3, 256, 240, 174, 90,,,, -6, 7, 5, 4, 3, 3, 2, 3, 384, 240, 174, 90,,,, -6, 7, 5, 4, 3, 3, 3, 1, 128, 240, 174, 90,,,, -6, 7, 5, 4, 3, 3, 3, 1, 256, 240, 174, 90,,,, -6, 7, 5, 4, 3, 3, 3, 1, 384, 240, 174, 90,,,, -6, 7, 5, 4, 3, 3, 3, 2, 128, 240, 174, 90,,,, -6, 7, 5, 4, 3, 3, 3, 2, 256, 240, 174, 90,,,, -6, 7, 5, 4, 3, 3, 3, 2, 384, 240, 174, 90,,,, -6, 7, 5, 4, 3, 3, 3, 3, 128, 240, 174, 90,,,, -6, 7, 5, 4, 3, 3, 3, 3, 256, 240, 174, 90,,,, -6, 7, 5, 4, 3, 3, 3, 3, 384, 240, 174, 90,,,, -6, 7, 5, 5, 1, 1, 1, 1, 128, 240, 216, 111,,,, -6, 7, 5, 5, 1, 1, 1, 1, 256, 240, 216, 111,,,, -6, 7, 5, 5, 1, 1, 1, 1, 384, 240, 216, 111,,,, -6, 7, 5, 5, 2, 2, 1, 1, 128, 240, 216, 111,,,, -6, 7, 5, 5, 2, 2, 1, 1, 256, 240, 216, 111,,,, -6, 7, 5, 5, 2, 2, 1, 1, 384, 240, 216, 111,,,, -6, 7, 5, 5, 2, 2, 1, 2, 128, 240, 216, 111,,,, -6, 7, 5, 5, 2, 2, 1, 2, 256, 240, 216, 111,,,, -6, 7, 5, 5, 2, 2, 1, 2, 384, 240, 216, 111,,,, -6, 7, 5, 5, 2, 2, 2, 1, 128, 240, 216, 111,,,, -6, 7, 5, 5, 2, 2, 2, 1, 256, 240, 216, 111,,,, -6, 7, 5, 5, 2, 2, 2, 1, 384, 240, 216, 111,,,, -6, 7, 5, 5, 2, 2, 2, 2, 128, 240, 216, 111,,,, -6, 7, 5, 5, 2, 2, 2, 2, 256, 240, 216, 111,,,, -6, 7, 5, 5, 2, 2, 2, 2, 384, 240, 216, 111,,,, -6, 7, 5, 5, 3, 3, 1, 1, 128, 240, 216, 111,,,, -6, 7, 5, 5, 3, 3, 1, 1, 256, 240, 216, 111,,,, -6, 7, 5, 5, 3, 3, 1, 1, 384, 240, 216, 111,,,, -6, 7, 5, 5, 3, 3, 1, 2, 128, 240, 216, 111,,,, -6, 7, 5, 5, 3, 3, 1, 2, 256, 240, 216, 111,,,, -6, 7, 5, 5, 3, 3, 1, 2, 384, 240, 216, 111,,,, -6, 7, 5, 5, 3, 3, 1, 3, 128, 240, 216, 111,,,, -6, 7, 5, 5, 3, 3, 1, 3, 256, 240, 216, 111,,,, -6, 7, 5, 5, 3, 3, 1, 3, 384, 240, 216, 111,,,, -6, 7, 5, 5, 3, 3, 2, 1, 128, 240, 216, 111,,,, -6, 7, 5, 5, 3, 3, 2, 1, 256, 240, 216, 111,,,, -6, 7, 5, 5, 3, 3, 2, 1, 384, 240, 216, 111,,,, -6, 7, 5, 5, 3, 3, 2, 2, 128, 240, 216, 111,,,, -6, 7, 5, 5, 3, 3, 2, 2, 256, 240, 216, 111,,,, -6, 7, 5, 5, 3, 3, 2, 2, 384, 240, 216, 111,,,, -6, 7, 5, 5, 3, 3, 2, 3, 128, 240, 216, 111,,,, -6, 7, 5, 5, 3, 3, 2, 3, 256, 240, 216, 111,,,, -6, 7, 5, 5, 3, 3, 2, 3, 384, 240, 216, 111,,,, -6, 7, 5, 5, 3, 3, 3, 1, 128, 240, 216, 111,,,, -6, 7, 5, 5, 3, 3, 3, 1, 256, 240, 216, 111,,,, -6, 7, 5, 5, 3, 3, 3, 1, 384, 240, 216, 111,,,, -6, 7, 5, 5, 3, 3, 3, 2, 128, 240, 216, 111,,,, -6, 7, 5, 5, 3, 3, 3, 2, 256, 240, 216, 111,,,, -6, 7, 5, 5, 3, 3, 3, 2, 384, 240, 216, 111,,,, -6, 7, 5, 5, 3, 3, 3, 3, 128, 240, 216, 111,,,, -6, 7, 5, 5, 3, 3, 3, 3, 256, 240, 216, 111,,,, -6, 7, 5, 5, 3, 3, 3, 3, 384, 240, 216, 111,,,, -6, 7, 5, 6, 1, 1, 1, 1, 128, 240, 240, 132,,,, -6, 7, 5, 6, 1, 1, 1, 1, 256, 240, 240, 132,,,, -6, 7, 5, 6, 1, 1, 1, 1, 384, 240, 240, 132,,,, -6, 7, 5, 6, 2, 2, 1, 1, 128, 240, 240, 132,,,, -6, 7, 5, 6, 2, 2, 1, 1, 256, 240, 240, 132,,,, -6, 7, 5, 6, 2, 2, 1, 1, 384, 240, 240, 132,,,, -6, 7, 5, 6, 2, 2, 1, 2, 128, 240, 240, 132,,,, -6, 7, 5, 6, 2, 2, 1, 2, 256, 240, 240, 132,,,, -6, 7, 5, 6, 2, 2, 1, 2, 384, 240, 240, 132,,,, -6, 7, 5, 6, 2, 2, 2, 1, 128, 240, 240, 132,,,, -6, 7, 5, 6, 2, 2, 2, 1, 256, 240, 240, 132,,,, -6, 7, 5, 6, 2, 2, 2, 1, 384, 240, 240, 132,,,, -6, 7, 5, 6, 2, 2, 2, 2, 128, 240, 240, 132,,,, -6, 7, 5, 6, 2, 2, 2, 2, 256, 240, 240, 132,,,, -6, 7, 5, 6, 2, 2, 2, 2, 384, 240, 240, 132,,,, -6, 7, 5, 6, 3, 3, 1, 1, 128, 240, 240, 132,,,, -6, 7, 5, 6, 3, 3, 1, 1, 256, 240, 240, 132,,,, -6, 7, 5, 6, 3, 3, 1, 1, 384, 240, 240, 132,,,, -6, 7, 5, 6, 3, 3, 1, 2, 128, 240, 240, 132,,,, -6, 7, 5, 6, 3, 3, 1, 2, 256, 240, 240, 132,,,, -6, 7, 5, 6, 3, 3, 1, 2, 384, 240, 240, 132,,,, -6, 7, 5, 6, 3, 3, 1, 3, 128, 240, 240, 132,,,, -6, 7, 5, 6, 3, 3, 1, 3, 256, 240, 240, 132,,,, -6, 7, 5, 6, 3, 3, 1, 3, 384, 240, 240, 132,,,, -6, 7, 5, 6, 3, 3, 2, 1, 128, 240, 240, 132,,,, -6, 7, 5, 6, 3, 3, 2, 1, 256, 240, 240, 132,,,, -6, 7, 5, 6, 3, 3, 2, 1, 384, 240, 240, 132,,,, -6, 7, 5, 6, 3, 3, 2, 2, 128, 240, 240, 132,,,, -6, 7, 5, 6, 3, 3, 2, 2, 256, 240, 240, 132,,,, -6, 7, 5, 6, 3, 3, 2, 2, 384, 240, 240, 132,,,, -6, 7, 5, 6, 3, 3, 2, 3, 128, 240, 240, 132,,,, -6, 7, 5, 6, 3, 3, 2, 3, 256, 240, 240, 132,,,, -6, 7, 5, 6, 3, 3, 2, 3, 384, 240, 240, 132,,,, -6, 7, 5, 6, 3, 3, 3, 1, 128, 240, 240, 132,,,, -6, 7, 5, 6, 3, 3, 3, 1, 256, 240, 240, 132,,,, -6, 7, 5, 6, 3, 3, 3, 1, 384, 240, 240, 132,,,, -6, 7, 5, 6, 3, 3, 3, 2, 128, 240, 240, 132,,,, -6, 7, 5, 6, 3, 3, 3, 2, 256, 240, 240, 132,,,, -6, 7, 5, 6, 3, 3, 3, 2, 384, 240, 240, 132,,,, -6, 7, 5, 6, 3, 3, 3, 3, 128, 240, 240, 132,,,, -6, 7, 5, 6, 3, 3, 3, 3, 256, 240, 240, 132,,,, -6, 7, 5, 6, 3, 3, 3, 3, 384, 240, 240, 132,,,, -6, 7, 5, 7, 1, 1, 1, 1, 128, 240, 240, 153,,,, -6, 7, 5, 7, 1, 1, 1, 1, 256, 240, 240, 153,,,, -6, 7, 5, 7, 1, 1, 1, 1, 384, 240, 240, 153,,,, -6, 7, 5, 7, 2, 2, 1, 1, 128, 240, 240, 153,,,, -6, 7, 5, 7, 2, 2, 1, 1, 256, 240, 240, 153,,,, -6, 7, 5, 7, 2, 2, 1, 1, 384, 240, 240, 153,,,, -6, 7, 5, 7, 2, 2, 1, 2, 128, 240, 240, 153,,,, -6, 7, 5, 7, 2, 2, 1, 2, 256, 240, 240, 153,,,, -6, 7, 5, 7, 2, 2, 1, 2, 384, 240, 240, 153,,,, -6, 7, 5, 7, 2, 2, 2, 1, 128, 240, 240, 153,,,, -6, 7, 5, 7, 2, 2, 2, 1, 256, 240, 240, 153,,,, -6, 7, 5, 7, 2, 2, 2, 1, 384, 240, 240, 153,,,, -6, 7, 5, 7, 2, 2, 2, 2, 128, 240, 240, 153,,,, -6, 7, 5, 7, 2, 2, 2, 2, 256, 240, 240, 153,,,, -6, 7, 5, 7, 2, 2, 2, 2, 384, 240, 240, 153,,,, -6, 7, 5, 7, 3, 3, 1, 1, 128, 240, 240, 153,,,, -6, 7, 5, 7, 3, 3, 1, 1, 256, 240, 240, 153,,,, -6, 7, 5, 7, 3, 3, 1, 1, 384, 240, 240, 153,,,, -6, 7, 5, 7, 3, 3, 1, 2, 128, 240, 240, 153,,,, -6, 7, 5, 7, 3, 3, 1, 2, 256, 240, 240, 153,,,, -6, 7, 5, 7, 3, 3, 1, 2, 384, 240, 240, 153,,,, -6, 7, 5, 7, 3, 3, 1, 3, 128, 240, 240, 153,,,, -6, 7, 5, 7, 3, 3, 1, 3, 256, 240, 240, 153,,,, -6, 7, 5, 7, 3, 3, 1, 3, 384, 240, 240, 153,,,, -6, 7, 5, 7, 3, 3, 2, 1, 128, 240, 240, 153,,,, -6, 7, 5, 7, 3, 3, 2, 1, 256, 240, 240, 153,,,, -6, 7, 5, 7, 3, 3, 2, 1, 384, 240, 240, 153,,,, -6, 7, 5, 7, 3, 3, 2, 2, 128, 240, 240, 153,,,, -6, 7, 5, 7, 3, 3, 2, 2, 256, 240, 240, 153,,,, -6, 7, 5, 7, 3, 3, 2, 2, 384, 240, 240, 153,,,, -6, 7, 5, 7, 3, 3, 2, 3, 128, 240, 240, 153,,,, -6, 7, 5, 7, 3, 3, 2, 3, 256, 240, 240, 153,,,, -6, 7, 5, 7, 3, 3, 2, 3, 384, 240, 240, 153,,,, -6, 7, 5, 7, 3, 3, 3, 1, 128, 240, 240, 153,,,, -6, 7, 5, 7, 3, 3, 3, 1, 256, 240, 240, 153,,,, -6, 7, 5, 7, 3, 3, 3, 1, 384, 240, 240, 153,,,, -6, 7, 5, 7, 3, 3, 3, 2, 128, 240, 240, 153,,,, -6, 7, 5, 7, 3, 3, 3, 2, 256, 240, 240, 153,,,, -6, 7, 5, 7, 3, 3, 3, 2, 384, 240, 240, 153,,,, -6, 7, 5, 7, 3, 3, 3, 3, 128, 240, 240, 153,,,, -6, 7, 5, 7, 3, 3, 3, 3, 256, 240, 240, 153,,,, -6, 7, 5, 7, 3, 3, 3, 3, 384, 240, 240, 153,,,, -6, 7, 6, 1, 1, 1, 1, 1, 128, 70, 48, 27,,,, -6, 7, 6, 1, 1, 1, 1, 1, 256, 70, 48, 27,,,, -6, 7, 6, 1, 1, 1, 1, 1, 384, 70, 48, 27,,,, -6, 7, 6, 1, 2, 2, 1, 1, 128, 70, 48, 27,,,, -6, 7, 6, 1, 2, 2, 1, 1, 256, 70, 48, 27,,,, -6, 7, 6, 1, 2, 2, 1, 1, 384, 70, 48, 27,,,, -6, 7, 6, 1, 2, 2, 1, 2, 128, 70, 48, 27,,,, -6, 7, 6, 1, 2, 2, 1, 2, 256, 70, 48, 27,,,, -6, 7, 6, 1, 2, 2, 1, 2, 384, 70, 48, 27,,,, -6, 7, 6, 1, 2, 2, 2, 1, 128, 70, 48, 27,,,, -6, 7, 6, 1, 2, 2, 2, 1, 256, 70, 48, 27,,,, -6, 7, 6, 1, 2, 2, 2, 1, 384, 70, 48, 27,,,, -6, 7, 6, 1, 2, 2, 2, 2, 128, 70, 48, 27,,,, -6, 7, 6, 1, 2, 2, 2, 2, 256, 70, 48, 27,,,, -6, 7, 6, 1, 2, 2, 2, 2, 384, 70, 48, 27,,,, -6, 7, 6, 1, 3, 3, 1, 1, 128, 69, 48, 27,,,, -6, 7, 6, 1, 3, 3, 1, 1, 256, 69, 48, 27,,,, -6, 7, 6, 1, 3, 3, 1, 1, 384, 69, 48, 27,,,, -6, 7, 6, 1, 3, 3, 1, 2, 128, 69, 48, 27,,,, -6, 7, 6, 1, 3, 3, 1, 2, 256, 69, 48, 27,,,, -6, 7, 6, 1, 3, 3, 1, 2, 384, 69, 48, 27,,,, -6, 7, 6, 1, 3, 3, 1, 3, 128, 69, 48, 27,,,, -6, 7, 6, 1, 3, 3, 1, 3, 256, 69, 48, 27,,,, -6, 7, 6, 1, 3, 3, 1, 3, 384, 69, 48, 27,,,, -6, 7, 6, 1, 3, 3, 2, 1, 128, 69, 48, 27,,,, -6, 7, 6, 1, 3, 3, 2, 1, 256, 69, 48, 27,,,, -6, 7, 6, 1, 3, 3, 2, 1, 384, 69, 48, 27,,,, -6, 7, 6, 1, 3, 3, 2, 2, 128, 69, 48, 27,,,, -6, 7, 6, 1, 3, 3, 2, 2, 256, 69, 48, 27,,,, -6, 7, 6, 1, 3, 3, 2, 2, 384, 69, 48, 27,,,, -6, 7, 6, 1, 3, 3, 2, 3, 128, 69, 48, 27,,,, -6, 7, 6, 1, 3, 3, 2, 3, 256, 69, 48, 27,,,, -6, 7, 6, 1, 3, 3, 2, 3, 384, 69, 48, 27,,,, -6, 7, 6, 1, 3, 3, 3, 1, 128, 69, 48, 27,,,, -6, 7, 6, 1, 3, 3, 3, 1, 256, 69, 48, 27,,,, -6, 7, 6, 1, 3, 3, 3, 1, 384, 69, 48, 27,,,, -6, 7, 6, 1, 3, 3, 3, 2, 128, 69, 48, 27,,,, -6, 7, 6, 1, 3, 3, 3, 2, 256, 69, 48, 27,,,, -6, 7, 6, 1, 3, 3, 3, 2, 384, 69, 48, 27,,,, -6, 7, 6, 1, 3, 3, 3, 3, 128, 69, 48, 27,,,, -6, 7, 6, 1, 3, 3, 3, 3, 256, 69, 48, 27,,,, -6, 7, 6, 1, 3, 3, 3, 3, 384, 69, 48, 27,,,, -6, 7, 6, 2, 1, 1, 1, 1, 128, 134, 90, 48,,,, -6, 7, 6, 2, 1, 1, 1, 1, 256, 134, 90, 48,,,, -6, 7, 6, 2, 1, 1, 1, 1, 384, 134, 90, 48,,,, -6, 7, 6, 2, 2, 2, 1, 1, 128, 134, 90, 48,,,, -6, 7, 6, 2, 2, 2, 1, 1, 256, 134, 90, 48,,,, -6, 7, 6, 2, 2, 2, 1, 1, 384, 134, 90, 48,,,, -6, 7, 6, 2, 2, 2, 1, 2, 128, 134, 90, 48,,,, -6, 7, 6, 2, 2, 2, 1, 2, 256, 134, 90, 48,,,, -6, 7, 6, 2, 2, 2, 1, 2, 384, 134, 90, 48,,,, -6, 7, 6, 2, 2, 2, 2, 1, 128, 134, 90, 48,,,, -6, 7, 6, 2, 2, 2, 2, 1, 256, 134, 90, 48,,,, -6, 7, 6, 2, 2, 2, 2, 1, 384, 134, 90, 48,,,, -6, 7, 6, 2, 2, 2, 2, 2, 128, 134, 90, 48,,,, -6, 7, 6, 2, 2, 2, 2, 2, 256, 134, 90, 48,,,, -6, 7, 6, 2, 2, 2, 2, 2, 384, 134, 90, 48,,,, -6, 7, 6, 2, 3, 3, 1, 1, 128, 132, 90, 48,,,, -6, 7, 6, 2, 3, 3, 1, 1, 256, 132, 90, 48,,,, -6, 7, 6, 2, 3, 3, 1, 1, 384, 132, 90, 48,,,, -6, 7, 6, 2, 3, 3, 1, 2, 128, 132, 90, 48,,,, -6, 7, 6, 2, 3, 3, 1, 2, 256, 132, 90, 48,,,, -6, 7, 6, 2, 3, 3, 1, 2, 384, 132, 90, 48,,,, -6, 7, 6, 2, 3, 3, 1, 3, 128, 132, 90, 48,,,, -6, 7, 6, 2, 3, 3, 1, 3, 256, 132, 90, 48,,,, -6, 7, 6, 2, 3, 3, 1, 3, 384, 132, 90, 48,,,, -6, 7, 6, 2, 3, 3, 2, 1, 128, 132, 90, 48,,,, -6, 7, 6, 2, 3, 3, 2, 1, 256, 132, 90, 48,,,, -6, 7, 6, 2, 3, 3, 2, 1, 384, 132, 90, 48,,,, -6, 7, 6, 2, 3, 3, 2, 2, 128, 132, 90, 48,,,, -6, 7, 6, 2, 3, 3, 2, 2, 256, 132, 90, 48,,,, -6, 7, 6, 2, 3, 3, 2, 2, 384, 132, 90, 48,,,, -6, 7, 6, 2, 3, 3, 2, 3, 128, 132, 90, 48,,,, -6, 7, 6, 2, 3, 3, 2, 3, 256, 132, 90, 48,,,, -6, 7, 6, 2, 3, 3, 2, 3, 384, 132, 90, 48,,,, -6, 7, 6, 2, 3, 3, 3, 1, 128, 132, 90, 48,,,, -6, 7, 6, 2, 3, 3, 3, 1, 256, 132, 90, 48,,,, -6, 7, 6, 2, 3, 3, 3, 1, 384, 132, 90, 48,,,, -6, 7, 6, 2, 3, 3, 3, 2, 128, 132, 90, 48,,,, -6, 7, 6, 2, 3, 3, 3, 2, 256, 132, 90, 48,,,, -6, 7, 6, 2, 3, 3, 3, 2, 384, 132, 90, 48,,,, -6, 7, 6, 2, 3, 3, 3, 3, 128, 132, 90, 48,,,, -6, 7, 6, 2, 3, 3, 3, 3, 256, 132, 90, 48,,,, -6, 7, 6, 2, 3, 3, 3, 3, 384, 132, 90, 48,,,, -6, 7, 6, 3, 1, 1, 1, 1, 128, 198, 132, 69,,,, -6, 7, 6, 3, 1, 1, 1, 1, 256, 198, 132, 69,,,, -6, 7, 6, 3, 1, 1, 1, 1, 384, 198, 132, 69,,,, -6, 7, 6, 3, 2, 2, 1, 1, 128, 198, 132, 69,,,, -6, 7, 6, 3, 2, 2, 1, 1, 256, 198, 132, 69,,,, -6, 7, 6, 3, 2, 2, 1, 1, 384, 198, 132, 69,,,, -6, 7, 6, 3, 2, 2, 1, 2, 128, 198, 132, 69,,,, -6, 7, 6, 3, 2, 2, 1, 2, 256, 198, 132, 69,,,, -6, 7, 6, 3, 2, 2, 1, 2, 384, 198, 132, 69,,,, -6, 7, 6, 3, 2, 2, 2, 1, 128, 198, 132, 69,,,, -6, 7, 6, 3, 2, 2, 2, 1, 256, 198, 132, 69,,,, -6, 7, 6, 3, 2, 2, 2, 1, 384, 198, 132, 69,,,, -6, 7, 6, 3, 2, 2, 2, 2, 128, 198, 132, 69,,,, -6, 7, 6, 3, 2, 2, 2, 2, 256, 198, 132, 69,,,, -6, 7, 6, 3, 2, 2, 2, 2, 384, 198, 132, 69,,,, -6, 7, 6, 3, 3, 3, 1, 1, 128, 195, 132, 69,,,, -6, 7, 6, 3, 3, 3, 1, 1, 256, 195, 132, 69,,,, -6, 7, 6, 3, 3, 3, 1, 1, 384, 195, 132, 69,,,, -6, 7, 6, 3, 3, 3, 1, 2, 128, 195, 132, 69,,,, -6, 7, 6, 3, 3, 3, 1, 2, 256, 195, 132, 69,,,, -6, 7, 6, 3, 3, 3, 1, 2, 384, 195, 132, 69,,,, -6, 7, 6, 3, 3, 3, 1, 3, 128, 195, 132, 69,,,, -6, 7, 6, 3, 3, 3, 1, 3, 256, 195, 132, 69,,,, -6, 7, 6, 3, 3, 3, 1, 3, 384, 195, 132, 69,,,, -6, 7, 6, 3, 3, 3, 2, 1, 128, 195, 132, 69,,,, -6, 7, 6, 3, 3, 3, 2, 1, 256, 195, 132, 69,,,, -6, 7, 6, 3, 3, 3, 2, 1, 384, 195, 132, 69,,,, -6, 7, 6, 3, 3, 3, 2, 2, 128, 195, 132, 69,,,, -6, 7, 6, 3, 3, 3, 2, 2, 256, 195, 132, 69,,,, -6, 7, 6, 3, 3, 3, 2, 2, 384, 195, 132, 69,,,, -6, 7, 6, 3, 3, 3, 2, 3, 128, 195, 132, 69,,,, -6, 7, 6, 3, 3, 3, 2, 3, 256, 195, 132, 69,,,, -6, 7, 6, 3, 3, 3, 2, 3, 384, 195, 132, 69,,,, -6, 7, 6, 3, 3, 3, 3, 1, 128, 195, 132, 69,,,, -6, 7, 6, 3, 3, 3, 3, 1, 256, 195, 132, 69,,,, -6, 7, 6, 3, 3, 3, 3, 1, 384, 195, 132, 69,,,, -6, 7, 6, 3, 3, 3, 3, 2, 128, 195, 132, 69,,,, -6, 7, 6, 3, 3, 3, 3, 2, 256, 195, 132, 69,,,, -6, 7, 6, 3, 3, 3, 3, 2, 384, 195, 132, 69,,,, -6, 7, 6, 3, 3, 3, 3, 3, 128, 195, 132, 69,,,, -6, 7, 6, 3, 3, 3, 3, 3, 256, 195, 132, 69,,,, -6, 7, 6, 3, 3, 3, 3, 3, 384, 195, 132, 69,,,, -6, 7, 6, 4, 1, 1, 1, 1, 128, 240, 174, 90,,,, -6, 7, 6, 4, 1, 1, 1, 1, 256, 240, 174, 90,,,, -6, 7, 6, 4, 1, 1, 1, 1, 384, 240, 174, 90,,,, -6, 7, 6, 4, 2, 2, 1, 1, 128, 240, 174, 90,,,, -6, 7, 6, 4, 2, 2, 1, 1, 256, 240, 174, 90,,,, -6, 7, 6, 4, 2, 2, 1, 1, 384, 240, 174, 90,,,, -6, 7, 6, 4, 2, 2, 1, 2, 128, 240, 174, 90,,,, -6, 7, 6, 4, 2, 2, 1, 2, 256, 240, 174, 90,,,, -6, 7, 6, 4, 2, 2, 1, 2, 384, 240, 174, 90,,,, -6, 7, 6, 4, 2, 2, 2, 1, 128, 240, 174, 90,,,, -6, 7, 6, 4, 2, 2, 2, 1, 256, 240, 174, 90,,,, -6, 7, 6, 4, 2, 2, 2, 1, 384, 240, 174, 90,,,, -6, 7, 6, 4, 2, 2, 2, 2, 128, 240, 174, 90,,,, -6, 7, 6, 4, 2, 2, 2, 2, 256, 240, 174, 90,,,, -6, 7, 6, 4, 2, 2, 2, 2, 384, 240, 174, 90,,,, -6, 7, 6, 4, 3, 3, 1, 1, 128, 240, 174, 90,,,, -6, 7, 6, 4, 3, 3, 1, 1, 256, 240, 174, 90,,,, -6, 7, 6, 4, 3, 3, 1, 1, 384, 240, 174, 90,,,, -6, 7, 6, 4, 3, 3, 1, 2, 128, 240, 174, 90,,,, -6, 7, 6, 4, 3, 3, 1, 2, 256, 240, 174, 90,,,, -6, 7, 6, 4, 3, 3, 1, 2, 384, 240, 174, 90,,,, -6, 7, 6, 4, 3, 3, 1, 3, 128, 240, 174, 90,,,, -6, 7, 6, 4, 3, 3, 1, 3, 256, 240, 174, 90,,,, -6, 7, 6, 4, 3, 3, 1, 3, 384, 240, 174, 90,,,, -6, 7, 6, 4, 3, 3, 2, 1, 128, 240, 174, 90,,,, -6, 7, 6, 4, 3, 3, 2, 1, 256, 240, 174, 90,,,, -6, 7, 6, 4, 3, 3, 2, 1, 384, 240, 174, 90,,,, -6, 7, 6, 4, 3, 3, 2, 2, 128, 240, 174, 90,,,, -6, 7, 6, 4, 3, 3, 2, 2, 256, 240, 174, 90,,,, -6, 7, 6, 4, 3, 3, 2, 2, 384, 240, 174, 90,,,, -6, 7, 6, 4, 3, 3, 2, 3, 128, 240, 174, 90,,,, -6, 7, 6, 4, 3, 3, 2, 3, 256, 240, 174, 90,,,, -6, 7, 6, 4, 3, 3, 2, 3, 384, 240, 174, 90,,,, -6, 7, 6, 4, 3, 3, 3, 1, 128, 240, 174, 90,,,, -6, 7, 6, 4, 3, 3, 3, 1, 256, 240, 174, 90,,,, -6, 7, 6, 4, 3, 3, 3, 1, 384, 240, 174, 90,,,, -6, 7, 6, 4, 3, 3, 3, 2, 128, 240, 174, 90,,,, -6, 7, 6, 4, 3, 3, 3, 2, 256, 240, 174, 90,,,, -6, 7, 6, 4, 3, 3, 3, 2, 384, 240, 174, 90,,,, -6, 7, 6, 4, 3, 3, 3, 3, 128, 240, 174, 90,,,, -6, 7, 6, 4, 3, 3, 3, 3, 256, 240, 174, 90,,,, -6, 7, 6, 4, 3, 3, 3, 3, 384, 240, 174, 90,,,, -6, 7, 6, 5, 1, 1, 1, 1, 128, 240, 216, 111,,,, -6, 7, 6, 5, 1, 1, 1, 1, 256, 240, 216, 111,,,, -6, 7, 6, 5, 1, 1, 1, 1, 384, 240, 216, 111,,,, -6, 7, 6, 5, 2, 2, 1, 1, 128, 240, 216, 111,,,, -6, 7, 6, 5, 2, 2, 1, 1, 256, 240, 216, 111,,,, -6, 7, 6, 5, 2, 2, 1, 1, 384, 240, 216, 111,,,, -6, 7, 6, 5, 2, 2, 1, 2, 128, 240, 216, 111,,,, -6, 7, 6, 5, 2, 2, 1, 2, 256, 240, 216, 111,,,, -6, 7, 6, 5, 2, 2, 1, 2, 384, 240, 216, 111,,,, -6, 7, 6, 5, 2, 2, 2, 1, 128, 240, 216, 111,,,, -6, 7, 6, 5, 2, 2, 2, 1, 256, 240, 216, 111,,,, -6, 7, 6, 5, 2, 2, 2, 1, 384, 240, 216, 111,,,, -6, 7, 6, 5, 2, 2, 2, 2, 128, 240, 216, 111,,,, -6, 7, 6, 5, 2, 2, 2, 2, 256, 240, 216, 111,,,, -6, 7, 6, 5, 2, 2, 2, 2, 384, 240, 216, 111,,,, -6, 7, 6, 5, 3, 3, 1, 1, 128, 240, 216, 111,,,, -6, 7, 6, 5, 3, 3, 1, 1, 256, 240, 216, 111,,,, -6, 7, 6, 5, 3, 3, 1, 1, 384, 240, 216, 111,,,, -6, 7, 6, 5, 3, 3, 1, 2, 128, 240, 216, 111,,,, -6, 7, 6, 5, 3, 3, 1, 2, 256, 240, 216, 111,,,, -6, 7, 6, 5, 3, 3, 1, 2, 384, 240, 216, 111,,,, -6, 7, 6, 5, 3, 3, 1, 3, 128, 240, 216, 111,,,, -6, 7, 6, 5, 3, 3, 1, 3, 256, 240, 216, 111,,,, -6, 7, 6, 5, 3, 3, 1, 3, 384, 240, 216, 111,,,, -6, 7, 6, 5, 3, 3, 2, 1, 128, 240, 216, 111,,,, -6, 7, 6, 5, 3, 3, 2, 1, 256, 240, 216, 111,,,, -6, 7, 6, 5, 3, 3, 2, 1, 384, 240, 216, 111,,,, -6, 7, 6, 5, 3, 3, 2, 2, 128, 240, 216, 111,,,, -6, 7, 6, 5, 3, 3, 2, 2, 256, 240, 216, 111,,,, -6, 7, 6, 5, 3, 3, 2, 2, 384, 240, 216, 111,,,, -6, 7, 6, 5, 3, 3, 2, 3, 128, 240, 216, 111,,,, -6, 7, 6, 5, 3, 3, 2, 3, 256, 240, 216, 111,,,, -6, 7, 6, 5, 3, 3, 2, 3, 384, 240, 216, 111,,,, -6, 7, 6, 5, 3, 3, 3, 1, 128, 240, 216, 111,,,, -6, 7, 6, 5, 3, 3, 3, 1, 256, 240, 216, 111,,,, -6, 7, 6, 5, 3, 3, 3, 1, 384, 240, 216, 111,,,, -6, 7, 6, 5, 3, 3, 3, 2, 128, 240, 216, 111,,,, -6, 7, 6, 5, 3, 3, 3, 2, 256, 240, 216, 111,,,, -6, 7, 6, 5, 3, 3, 3, 2, 384, 240, 216, 111,,,, -6, 7, 6, 5, 3, 3, 3, 3, 128, 240, 216, 111,,,, -6, 7, 6, 5, 3, 3, 3, 3, 256, 240, 216, 111,,,, -6, 7, 6, 5, 3, 3, 3, 3, 384, 240, 216, 111,,,, -6, 7, 6, 6, 1, 1, 1, 1, 128, 240, 240, 132,,,, -6, 7, 6, 6, 1, 1, 1, 1, 256, 240, 240, 132,,,, -6, 7, 6, 6, 1, 1, 1, 1, 384, 240, 240, 132,,,, -6, 7, 6, 6, 2, 2, 1, 1, 128, 240, 240, 132,,,, -6, 7, 6, 6, 2, 2, 1, 1, 256, 240, 240, 132,,,, -6, 7, 6, 6, 2, 2, 1, 1, 384, 240, 240, 132,,,, -6, 7, 6, 6, 2, 2, 1, 2, 128, 240, 240, 132,,,, -6, 7, 6, 6, 2, 2, 1, 2, 256, 240, 240, 132,,,, -6, 7, 6, 6, 2, 2, 1, 2, 384, 240, 240, 132,,,, -6, 7, 6, 6, 2, 2, 2, 1, 128, 240, 240, 132,,,, -6, 7, 6, 6, 2, 2, 2, 1, 256, 240, 240, 132,,,, -6, 7, 6, 6, 2, 2, 2, 1, 384, 240, 240, 132,,,, -6, 7, 6, 6, 2, 2, 2, 2, 128, 240, 240, 132,,,, -6, 7, 6, 6, 2, 2, 2, 2, 256, 240, 240, 132,,,, -6, 7, 6, 6, 2, 2, 2, 2, 384, 240, 240, 132,,,, -6, 7, 6, 6, 3, 3, 1, 1, 128, 240, 240, 132,,,, -6, 7, 6, 6, 3, 3, 1, 1, 256, 240, 240, 132,,,, -6, 7, 6, 6, 3, 3, 1, 1, 384, 240, 240, 132,,,, -6, 7, 6, 6, 3, 3, 1, 2, 128, 240, 240, 132,,,, -6, 7, 6, 6, 3, 3, 1, 2, 256, 240, 240, 132,,,, -6, 7, 6, 6, 3, 3, 1, 2, 384, 240, 240, 132,,,, -6, 7, 6, 6, 3, 3, 1, 3, 128, 240, 240, 132,,,, -6, 7, 6, 6, 3, 3, 1, 3, 256, 240, 240, 132,,,, -6, 7, 6, 6, 3, 3, 1, 3, 384, 240, 240, 132,,,, -6, 7, 6, 6, 3, 3, 2, 1, 128, 240, 240, 132,,,, -6, 7, 6, 6, 3, 3, 2, 1, 256, 240, 240, 132,,,, -6, 7, 6, 6, 3, 3, 2, 1, 384, 240, 240, 132,,,, -6, 7, 6, 6, 3, 3, 2, 2, 128, 240, 240, 132,,,, -6, 7, 6, 6, 3, 3, 2, 2, 256, 240, 240, 132,,,, -6, 7, 6, 6, 3, 3, 2, 2, 384, 240, 240, 132,,,, -6, 7, 6, 6, 3, 3, 2, 3, 128, 240, 240, 132,,,, -6, 7, 6, 6, 3, 3, 2, 3, 256, 240, 240, 132,,,, -6, 7, 6, 6, 3, 3, 2, 3, 384, 240, 240, 132,,,, -6, 7, 6, 6, 3, 3, 3, 1, 128, 240, 240, 132,,,, -6, 7, 6, 6, 3, 3, 3, 1, 256, 240, 240, 132,,,, -6, 7, 6, 6, 3, 3, 3, 1, 384, 240, 240, 132,,,, -6, 7, 6, 6, 3, 3, 3, 2, 128, 240, 240, 132,,,, -6, 7, 6, 6, 3, 3, 3, 2, 256, 240, 240, 132,,,, -6, 7, 6, 6, 3, 3, 3, 2, 384, 240, 240, 132,,,, -6, 7, 6, 6, 3, 3, 3, 3, 128, 240, 240, 132,,,, -6, 7, 6, 6, 3, 3, 3, 3, 256, 240, 240, 132,,,, -6, 7, 6, 6, 3, 3, 3, 3, 384, 240, 240, 132,,,, -6, 7, 6, 7, 1, 1, 1, 1, 128, 240, 240, 153,,,, -6, 7, 6, 7, 1, 1, 1, 1, 256, 240, 240, 153,,,, -6, 7, 6, 7, 1, 1, 1, 1, 384, 240, 240, 153,,,, -6, 7, 6, 7, 2, 2, 1, 1, 128, 240, 240, 153,,,, -6, 7, 6, 7, 2, 2, 1, 1, 256, 240, 240, 153,,,, -6, 7, 6, 7, 2, 2, 1, 1, 384, 240, 240, 153,,,, -6, 7, 6, 7, 2, 2, 1, 2, 128, 240, 240, 153,,,, -6, 7, 6, 7, 2, 2, 1, 2, 256, 240, 240, 153,,,, -6, 7, 6, 7, 2, 2, 1, 2, 384, 240, 240, 153,,,, -6, 7, 6, 7, 2, 2, 2, 1, 128, 240, 240, 153,,,, -6, 7, 6, 7, 2, 2, 2, 1, 256, 240, 240, 153,,,, -6, 7, 6, 7, 2, 2, 2, 1, 384, 240, 240, 153,,,, -6, 7, 6, 7, 2, 2, 2, 2, 128, 240, 240, 153,,,, -6, 7, 6, 7, 2, 2, 2, 2, 256, 240, 240, 153,,,, -6, 7, 6, 7, 2, 2, 2, 2, 384, 240, 240, 153,,,, -6, 7, 6, 7, 3, 3, 1, 1, 128, 240, 240, 153,,,, -6, 7, 6, 7, 3, 3, 1, 1, 256, 240, 240, 153,,,, -6, 7, 6, 7, 3, 3, 1, 1, 384, 240, 240, 153,,,, -6, 7, 6, 7, 3, 3, 1, 2, 128, 240, 240, 153,,,, -6, 7, 6, 7, 3, 3, 1, 2, 256, 240, 240, 153,,,, -6, 7, 6, 7, 3, 3, 1, 2, 384, 240, 240, 153,,,, -6, 7, 6, 7, 3, 3, 1, 3, 128, 240, 240, 153,,,, -6, 7, 6, 7, 3, 3, 1, 3, 256, 240, 240, 153,,,, -6, 7, 6, 7, 3, 3, 1, 3, 384, 240, 240, 153,,,, -6, 7, 6, 7, 3, 3, 2, 1, 128, 240, 240, 153,,,, -6, 7, 6, 7, 3, 3, 2, 1, 256, 240, 240, 153,,,, -6, 7, 6, 7, 3, 3, 2, 1, 384, 240, 240, 153,,,, -6, 7, 6, 7, 3, 3, 2, 2, 128, 240, 240, 153,,,, -6, 7, 6, 7, 3, 3, 2, 2, 256, 240, 240, 153,,,, -6, 7, 6, 7, 3, 3, 2, 2, 384, 240, 240, 153,,,, -6, 7, 6, 7, 3, 3, 2, 3, 128, 240, 240, 153,,,, -6, 7, 6, 7, 3, 3, 2, 3, 256, 240, 240, 153,,,, -6, 7, 6, 7, 3, 3, 2, 3, 384, 240, 240, 153,,,, -6, 7, 6, 7, 3, 3, 3, 1, 128, 240, 240, 153,,,, -6, 7, 6, 7, 3, 3, 3, 1, 256, 240, 240, 153,,,, -6, 7, 6, 7, 3, 3, 3, 1, 384, 240, 240, 153,,,, -6, 7, 6, 7, 3, 3, 3, 2, 128, 240, 240, 153,,,, -6, 7, 6, 7, 3, 3, 3, 2, 256, 240, 240, 153,,,, -6, 7, 6, 7, 3, 3, 3, 2, 384, 240, 240, 153,,,, -6, 7, 6, 7, 3, 3, 3, 3, 128, 240, 240, 153,,,, -6, 7, 6, 7, 3, 3, 3, 3, 256, 240, 240, 153,,,, -6, 7, 6, 7, 3, 3, 3, 3, 384, 240, 240, 153,,,, -7, 1, 1, 1, 1, 1, 1, 1, 128, 54, 54, 54, 54, 36,, -7, 1, 1, 1, 1, 1, 1, 1, 256, 54, 54, 54, 54, 36,, -7, 1, 1, 1, 1, 1, 1, 1, 384, 54, 54, 54, 54, 36,, -7, 1, 2, 1, 1, 1, 1, 1, 128, 54, 54, 54, 54, 36,, -7, 1, 2, 1, 1, 1, 1, 1, 256, 54, 54, 54, 54, 36,, -7, 1, 2, 1, 1, 1, 1, 1, 384, 54, 54, 54, 54, 36,, -7, 1, 3, 1, 1, 1, 1, 1, 128, 54, 54, 54, 54, 36,, -7, 1, 3, 1, 1, 1, 1, 1, 256, 54, 54, 54, 54, 36,, -7, 1, 3, 1, 1, 1, 1, 1, 384, 54, 54, 54, 54, 36,, -7, 1, 4, 1, 1, 1, 1, 1, 128, 54, 54, 54, 54, 36,, -7, 1, 4, 1, 1, 1, 1, 1, 256, 54, 54, 54, 54, 36,, -7, 1, 4, 1, 1, 1, 1, 1, 384, 54, 54, 54, 54, 36,, -7, 1, 5, 1, 1, 1, 1, 1, 128, 54, 54, 54, 54, 36,, -7, 1, 5, 1, 1, 1, 1, 1, 256, 54, 54, 54, 54, 36,, -7, 1, 5, 1, 1, 1, 1, 1, 384, 54, 54, 54, 54, 36,, -7, 1, 6, 1, 1, 1, 1, 1, 128, 54, 54, 54, 54, 36,, -7, 1, 6, 1, 1, 1, 1, 1, 256, 54, 54, 54, 54, 36,, -7, 1, 6, 1, 1, 1, 1, 1, 384, 54, 54, 54, 54, 36,, -7, 1, 7, 1, 1, 1, 1, 1, 128, 54, 54, 54, 54, 36,, -7, 1, 7, 1, 1, 1, 1, 1, 256, 54, 54, 54, 54, 36,, -7, 1, 7, 1, 1, 1, 1, 1, 384, 54, 54, 54, 54, 36,, -7, 2, 1, 1, 1, 1, 1, 1, 128, 55, 55, 55, 37,,, -7, 2, 1, 1, 1, 1, 1, 1, 256, 55, 55, 55, 37,,, -7, 2, 1, 1, 1, 1, 1, 1, 384, 55, 55, 55, 37,,, -7, 2, 1, 1, 2, 2, 1, 1, 128, 55, 55, 53, 37,,, -7, 2, 1, 1, 2, 2, 1, 1, 256, 55, 55, 53, 37,,, -7, 2, 1, 1, 2, 2, 1, 1, 384, 55, 55, 53, 37,,, -7, 2, 1, 1, 2, 2, 1, 2, 128, 55, 55, 53, 37,,, -7, 2, 1, 1, 2, 2, 1, 2, 256, 55, 55, 53, 37,,, -7, 2, 1, 1, 2, 2, 1, 2, 384, 55, 55, 53, 37,,, -7, 2, 1, 1, 2, 2, 2, 1, 128, 55, 55, 53, 37,,, -7, 2, 1, 1, 2, 2, 2, 1, 256, 55, 55, 53, 37,,, -7, 2, 1, 1, 2, 2, 2, 1, 384, 55, 55, 53, 37,,, -7, 2, 1, 1, 2, 2, 2, 2, 128, 55, 55, 53, 37,,, -7, 2, 1, 1, 2, 2, 2, 2, 256, 55, 55, 53, 37,,, -7, 2, 1, 1, 2, 2, 2, 2, 384, 55, 55, 53, 37,,, -7, 2, 1, 2, 1, 1, 1, 1, 128, 109, 109, 109, 73,,, -7, 2, 1, 2, 1, 1, 1, 1, 256, 109, 109, 109, 73,,, -7, 2, 1, 2, 1, 1, 1, 1, 384, 109, 109, 109, 73,,, -7, 2, 1, 2, 2, 2, 1, 1, 128, 109, 109, 105, 73,,, -7, 2, 1, 2, 2, 2, 1, 1, 256, 109, 109, 105, 73,,, -7, 2, 1, 2, 2, 2, 1, 1, 384, 109, 109, 105, 73,,, -7, 2, 1, 2, 2, 2, 1, 2, 128, 109, 109, 105, 73,,, -7, 2, 1, 2, 2, 2, 1, 2, 256, 109, 109, 105, 73,,, -7, 2, 1, 2, 2, 2, 1, 2, 384, 109, 109, 105, 73,,, -7, 2, 1, 2, 2, 2, 2, 1, 128, 109, 109, 105, 73,,, -7, 2, 1, 2, 2, 2, 2, 1, 256, 109, 109, 105, 73,,, -7, 2, 1, 2, 2, 2, 2, 1, 384, 109, 109, 105, 73,,, -7, 2, 1, 2, 2, 2, 2, 2, 128, 109, 109, 105, 73,,, -7, 2, 1, 2, 2, 2, 2, 2, 256, 109, 109, 105, 73,,, -7, 2, 1, 2, 2, 2, 2, 2, 384, 109, 109, 105, 73,,, -7, 2, 2, 1, 1, 1, 1, 1, 128, 55, 55, 55, 37,,, -7, 2, 2, 1, 1, 1, 1, 1, 256, 55, 55, 55, 37,,, -7, 2, 2, 1, 1, 1, 1, 1, 384, 55, 55, 55, 37,,, -7, 2, 2, 1, 2, 2, 1, 1, 128, 55, 55, 53, 37,,, -7, 2, 2, 1, 2, 2, 1, 1, 256, 55, 55, 53, 37,,, -7, 2, 2, 1, 2, 2, 1, 1, 384, 55, 55, 53, 37,,, -7, 2, 2, 1, 2, 2, 1, 2, 128, 55, 55, 53, 37,,, -7, 2, 2, 1, 2, 2, 1, 2, 256, 55, 55, 53, 37,,, -7, 2, 2, 1, 2, 2, 1, 2, 384, 55, 55, 53, 37,,, -7, 2, 2, 1, 2, 2, 2, 1, 128, 55, 55, 53, 37,,, -7, 2, 2, 1, 2, 2, 2, 1, 256, 55, 55, 53, 37,,, -7, 2, 2, 1, 2, 2, 2, 1, 384, 55, 55, 53, 37,,, -7, 2, 2, 1, 2, 2, 2, 2, 128, 55, 55, 53, 37,,, -7, 2, 2, 1, 2, 2, 2, 2, 256, 55, 55, 53, 37,,, -7, 2, 2, 1, 2, 2, 2, 2, 384, 55, 55, 53, 37,,, -7, 2, 2, 2, 1, 1, 1, 1, 128, 109, 109, 109, 73,,, -7, 2, 2, 2, 1, 1, 1, 1, 256, 109, 109, 109, 73,,, -7, 2, 2, 2, 1, 1, 1, 1, 384, 109, 109, 109, 73,,, -7, 2, 2, 2, 2, 2, 1, 1, 128, 109, 109, 105, 73,,, -7, 2, 2, 2, 2, 2, 1, 1, 256, 109, 109, 105, 73,,, -7, 2, 2, 2, 2, 2, 1, 1, 384, 109, 109, 105, 73,,, -7, 2, 2, 2, 2, 2, 1, 2, 128, 109, 109, 105, 73,,, -7, 2, 2, 2, 2, 2, 1, 2, 256, 109, 109, 105, 73,,, -7, 2, 2, 2, 2, 2, 1, 2, 384, 109, 109, 105, 73,,, -7, 2, 2, 2, 2, 2, 2, 1, 128, 109, 109, 105, 73,,, -7, 2, 2, 2, 2, 2, 2, 1, 256, 109, 109, 105, 73,,, -7, 2, 2, 2, 2, 2, 2, 1, 384, 109, 109, 105, 73,,, -7, 2, 2, 2, 2, 2, 2, 2, 128, 109, 109, 105, 73,,, -7, 2, 2, 2, 2, 2, 2, 2, 256, 109, 109, 105, 73,,, -7, 2, 2, 2, 2, 2, 2, 2, 384, 109, 109, 105, 73,,, -7, 2, 3, 1, 1, 1, 1, 1, 128, 55, 55, 55, 37,,, -7, 2, 3, 1, 1, 1, 1, 1, 256, 55, 55, 55, 37,,, -7, 2, 3, 1, 1, 1, 1, 1, 384, 55, 55, 55, 37,,, -7, 2, 3, 1, 2, 2, 1, 1, 128, 55, 55, 53, 37,,, -7, 2, 3, 1, 2, 2, 1, 1, 256, 55, 55, 53, 37,,, -7, 2, 3, 1, 2, 2, 1, 1, 384, 55, 55, 53, 37,,, -7, 2, 3, 1, 2, 2, 1, 2, 128, 55, 55, 53, 37,,, -7, 2, 3, 1, 2, 2, 1, 2, 256, 55, 55, 53, 37,,, -7, 2, 3, 1, 2, 2, 1, 2, 384, 55, 55, 53, 37,,, -7, 2, 3, 1, 2, 2, 2, 1, 128, 55, 55, 53, 37,,, -7, 2, 3, 1, 2, 2, 2, 1, 256, 55, 55, 53, 37,,, -7, 2, 3, 1, 2, 2, 2, 1, 384, 55, 55, 53, 37,,, -7, 2, 3, 1, 2, 2, 2, 2, 128, 55, 55, 53, 37,,, -7, 2, 3, 1, 2, 2, 2, 2, 256, 55, 55, 53, 37,,, -7, 2, 3, 1, 2, 2, 2, 2, 384, 55, 55, 53, 37,,, -7, 2, 3, 2, 1, 1, 1, 1, 128, 109, 109, 109, 73,,, -7, 2, 3, 2, 1, 1, 1, 1, 256, 109, 109, 109, 73,,, -7, 2, 3, 2, 1, 1, 1, 1, 384, 109, 109, 109, 73,,, -7, 2, 3, 2, 2, 2, 1, 1, 128, 109, 109, 105, 73,,, -7, 2, 3, 2, 2, 2, 1, 1, 256, 109, 109, 105, 73,,, -7, 2, 3, 2, 2, 2, 1, 1, 384, 109, 109, 105, 73,,, -7, 2, 3, 2, 2, 2, 1, 2, 128, 109, 109, 105, 73,,, -7, 2, 3, 2, 2, 2, 1, 2, 256, 109, 109, 105, 73,,, -7, 2, 3, 2, 2, 2, 1, 2, 384, 109, 109, 105, 73,,, -7, 2, 3, 2, 2, 2, 2, 1, 128, 109, 109, 105, 73,,, -7, 2, 3, 2, 2, 2, 2, 1, 256, 109, 109, 105, 73,,, -7, 2, 3, 2, 2, 2, 2, 1, 384, 109, 109, 105, 73,,, -7, 2, 3, 2, 2, 2, 2, 2, 128, 109, 109, 105, 73,,, -7, 2, 3, 2, 2, 2, 2, 2, 256, 109, 109, 105, 73,,, -7, 2, 3, 2, 2, 2, 2, 2, 384, 109, 109, 105, 73,,, -7, 2, 4, 1, 1, 1, 1, 1, 128, 55, 55, 55, 37,,, -7, 2, 4, 1, 1, 1, 1, 1, 256, 55, 55, 55, 37,,, -7, 2, 4, 1, 1, 1, 1, 1, 384, 55, 55, 55, 37,,, -7, 2, 4, 1, 2, 2, 1, 1, 128, 55, 55, 53, 37,,, -7, 2, 4, 1, 2, 2, 1, 1, 256, 55, 55, 53, 37,,, -7, 2, 4, 1, 2, 2, 1, 1, 384, 55, 55, 53, 37,,, -7, 2, 4, 1, 2, 2, 1, 2, 128, 55, 55, 53, 37,,, -7, 2, 4, 1, 2, 2, 1, 2, 256, 55, 55, 53, 37,,, -7, 2, 4, 1, 2, 2, 1, 2, 384, 55, 55, 53, 37,,, -7, 2, 4, 1, 2, 2, 2, 1, 128, 55, 55, 53, 37,,, -7, 2, 4, 1, 2, 2, 2, 1, 256, 55, 55, 53, 37,,, -7, 2, 4, 1, 2, 2, 2, 1, 384, 55, 55, 53, 37,,, -7, 2, 4, 1, 2, 2, 2, 2, 128, 55, 55, 53, 37,,, -7, 2, 4, 1, 2, 2, 2, 2, 256, 55, 55, 53, 37,,, -7, 2, 4, 1, 2, 2, 2, 2, 384, 55, 55, 53, 37,,, -7, 2, 4, 2, 1, 1, 1, 1, 128, 109, 109, 109, 73,,, -7, 2, 4, 2, 1, 1, 1, 1, 256, 109, 109, 109, 73,,, -7, 2, 4, 2, 1, 1, 1, 1, 384, 109, 109, 109, 73,,, -7, 2, 4, 2, 2, 2, 1, 1, 128, 109, 109, 105, 73,,, -7, 2, 4, 2, 2, 2, 1, 1, 256, 109, 109, 105, 73,,, -7, 2, 4, 2, 2, 2, 1, 1, 384, 109, 109, 105, 73,,, -7, 2, 4, 2, 2, 2, 1, 2, 128, 109, 109, 105, 73,,, -7, 2, 4, 2, 2, 2, 1, 2, 256, 109, 109, 105, 73,,, -7, 2, 4, 2, 2, 2, 1, 2, 384, 109, 109, 105, 73,,, -7, 2, 4, 2, 2, 2, 2, 1, 128, 109, 109, 105, 73,,, -7, 2, 4, 2, 2, 2, 2, 1, 256, 109, 109, 105, 73,,, -7, 2, 4, 2, 2, 2, 2, 1, 384, 109, 109, 105, 73,,, -7, 2, 4, 2, 2, 2, 2, 2, 128, 109, 109, 105, 73,,, -7, 2, 4, 2, 2, 2, 2, 2, 256, 109, 109, 105, 73,,, -7, 2, 4, 2, 2, 2, 2, 2, 384, 109, 109, 105, 73,,, -7, 2, 5, 1, 1, 1, 1, 1, 128, 55, 55, 55, 37,,, -7, 2, 5, 1, 1, 1, 1, 1, 256, 55, 55, 55, 37,,, -7, 2, 5, 1, 1, 1, 1, 1, 384, 55, 55, 55, 37,,, -7, 2, 5, 1, 2, 2, 1, 1, 128, 55, 55, 53, 37,,, -7, 2, 5, 1, 2, 2, 1, 1, 256, 55, 55, 53, 37,,, -7, 2, 5, 1, 2, 2, 1, 1, 384, 55, 55, 53, 37,,, -7, 2, 5, 1, 2, 2, 1, 2, 128, 55, 55, 53, 37,,, -7, 2, 5, 1, 2, 2, 1, 2, 256, 55, 55, 53, 37,,, -7, 2, 5, 1, 2, 2, 1, 2, 384, 55, 55, 53, 37,,, -7, 2, 5, 1, 2, 2, 2, 1, 128, 55, 55, 53, 37,,, -7, 2, 5, 1, 2, 2, 2, 1, 256, 55, 55, 53, 37,,, -7, 2, 5, 1, 2, 2, 2, 1, 384, 55, 55, 53, 37,,, -7, 2, 5, 1, 2, 2, 2, 2, 128, 55, 55, 53, 37,,, -7, 2, 5, 1, 2, 2, 2, 2, 256, 55, 55, 53, 37,,, -7, 2, 5, 1, 2, 2, 2, 2, 384, 55, 55, 53, 37,,, -7, 2, 5, 2, 1, 1, 1, 1, 128, 109, 109, 109, 73,,, -7, 2, 5, 2, 1, 1, 1, 1, 256, 109, 109, 109, 73,,, -7, 2, 5, 2, 1, 1, 1, 1, 384, 109, 109, 109, 73,,, -7, 2, 5, 2, 2, 2, 1, 1, 128, 109, 109, 105, 73,,, -7, 2, 5, 2, 2, 2, 1, 1, 256, 109, 109, 105, 73,,, -7, 2, 5, 2, 2, 2, 1, 1, 384, 109, 109, 105, 73,,, -7, 2, 5, 2, 2, 2, 1, 2, 128, 109, 109, 105, 73,,, -7, 2, 5, 2, 2, 2, 1, 2, 256, 109, 109, 105, 73,,, -7, 2, 5, 2, 2, 2, 1, 2, 384, 109, 109, 105, 73,,, -7, 2, 5, 2, 2, 2, 2, 1, 128, 109, 109, 105, 73,,, -7, 2, 5, 2, 2, 2, 2, 1, 256, 109, 109, 105, 73,,, -7, 2, 5, 2, 2, 2, 2, 1, 384, 109, 109, 105, 73,,, -7, 2, 5, 2, 2, 2, 2, 2, 128, 109, 109, 105, 73,,, -7, 2, 5, 2, 2, 2, 2, 2, 256, 109, 109, 105, 73,,, -7, 2, 5, 2, 2, 2, 2, 2, 384, 109, 109, 105, 73,,, -7, 2, 6, 1, 1, 1, 1, 1, 128, 55, 55, 55, 37,,, -7, 2, 6, 1, 1, 1, 1, 1, 256, 55, 55, 55, 37,,, -7, 2, 6, 1, 1, 1, 1, 1, 384, 55, 55, 55, 37,,, -7, 2, 6, 1, 2, 2, 1, 1, 128, 55, 55, 53, 37,,, -7, 2, 6, 1, 2, 2, 1, 1, 256, 55, 55, 53, 37,,, -7, 2, 6, 1, 2, 2, 1, 1, 384, 55, 55, 53, 37,,, -7, 2, 6, 1, 2, 2, 1, 2, 128, 55, 55, 53, 37,,, -7, 2, 6, 1, 2, 2, 1, 2, 256, 55, 55, 53, 37,,, -7, 2, 6, 1, 2, 2, 1, 2, 384, 55, 55, 53, 37,,, -7, 2, 6, 1, 2, 2, 2, 1, 128, 55, 55, 53, 37,,, -7, 2, 6, 1, 2, 2, 2, 1, 256, 55, 55, 53, 37,,, -7, 2, 6, 1, 2, 2, 2, 1, 384, 55, 55, 53, 37,,, -7, 2, 6, 1, 2, 2, 2, 2, 128, 55, 55, 53, 37,,, -7, 2, 6, 1, 2, 2, 2, 2, 256, 55, 55, 53, 37,,, -7, 2, 6, 1, 2, 2, 2, 2, 384, 55, 55, 53, 37,,, -7, 2, 6, 2, 1, 1, 1, 1, 128, 109, 109, 109, 73,,, -7, 2, 6, 2, 1, 1, 1, 1, 256, 109, 109, 109, 73,,, -7, 2, 6, 2, 1, 1, 1, 1, 384, 109, 109, 109, 73,,, -7, 2, 6, 2, 2, 2, 1, 1, 128, 109, 109, 105, 73,,, -7, 2, 6, 2, 2, 2, 1, 1, 256, 109, 109, 105, 73,,, -7, 2, 6, 2, 2, 2, 1, 1, 384, 109, 109, 105, 73,,, -7, 2, 6, 2, 2, 2, 1, 2, 128, 109, 109, 105, 73,,, -7, 2, 6, 2, 2, 2, 1, 2, 256, 109, 109, 105, 73,,, -7, 2, 6, 2, 2, 2, 1, 2, 384, 109, 109, 105, 73,,, -7, 2, 6, 2, 2, 2, 2, 1, 128, 109, 109, 105, 73,,, -7, 2, 6, 2, 2, 2, 2, 1, 256, 109, 109, 105, 73,,, -7, 2, 6, 2, 2, 2, 2, 1, 384, 109, 109, 105, 73,,, -7, 2, 6, 2, 2, 2, 2, 2, 128, 109, 109, 105, 73,,, -7, 2, 6, 2, 2, 2, 2, 2, 256, 109, 109, 105, 73,,, -7, 2, 6, 2, 2, 2, 2, 2, 384, 109, 109, 105, 73,,, -7, 2, 7, 1, 1, 1, 1, 1, 128, 55, 55, 55, 37,,, -7, 2, 7, 1, 1, 1, 1, 1, 256, 55, 55, 55, 37,,, -7, 2, 7, 1, 1, 1, 1, 1, 384, 55, 55, 55, 37,,, -7, 2, 7, 1, 2, 2, 1, 1, 128, 55, 55, 53, 37,,, -7, 2, 7, 1, 2, 2, 1, 1, 256, 55, 55, 53, 37,,, -7, 2, 7, 1, 2, 2, 1, 1, 384, 55, 55, 53, 37,,, -7, 2, 7, 1, 2, 2, 1, 2, 128, 55, 55, 53, 37,,, -7, 2, 7, 1, 2, 2, 1, 2, 256, 55, 55, 53, 37,,, -7, 2, 7, 1, 2, 2, 1, 2, 384, 55, 55, 53, 37,,, -7, 2, 7, 1, 2, 2, 2, 1, 128, 55, 55, 53, 37,,, -7, 2, 7, 1, 2, 2, 2, 1, 256, 55, 55, 53, 37,,, -7, 2, 7, 1, 2, 2, 2, 1, 384, 55, 55, 53, 37,,, -7, 2, 7, 1, 2, 2, 2, 2, 128, 55, 55, 53, 37,,, -7, 2, 7, 1, 2, 2, 2, 2, 256, 55, 55, 53, 37,,, -7, 2, 7, 1, 2, 2, 2, 2, 384, 55, 55, 53, 37,,, -7, 2, 7, 2, 1, 1, 1, 1, 128, 109, 109, 109, 73,,, -7, 2, 7, 2, 1, 1, 1, 1, 256, 109, 109, 109, 73,,, -7, 2, 7, 2, 1, 1, 1, 1, 384, 109, 109, 109, 73,,, -7, 2, 7, 2, 2, 2, 1, 1, 128, 109, 109, 105, 73,,, -7, 2, 7, 2, 2, 2, 1, 1, 256, 109, 109, 105, 73,,, -7, 2, 7, 2, 2, 2, 1, 1, 384, 109, 109, 105, 73,,, -7, 2, 7, 2, 2, 2, 1, 2, 128, 109, 109, 105, 73,,, -7, 2, 7, 2, 2, 2, 1, 2, 256, 109, 109, 105, 73,,, -7, 2, 7, 2, 2, 2, 1, 2, 384, 109, 109, 105, 73,,, -7, 2, 7, 2, 2, 2, 2, 1, 128, 109, 109, 105, 73,,, -7, 2, 7, 2, 2, 2, 2, 1, 256, 109, 109, 105, 73,,, -7, 2, 7, 2, 2, 2, 2, 1, 384, 109, 109, 105, 73,,, -7, 2, 7, 2, 2, 2, 2, 2, 128, 109, 109, 105, 73,,, -7, 2, 7, 2, 2, 2, 2, 2, 256, 109, 109, 105, 73,,, -7, 2, 7, 2, 2, 2, 2, 2, 384, 109, 109, 105, 73,,, -7, 3, 1, 1, 1, 1, 1, 1, 128, 56, 56, 38, 20,,, -7, 3, 1, 1, 1, 1, 1, 1, 256, 56, 56, 38, 20,,, -7, 3, 1, 1, 1, 1, 1, 1, 384, 56, 56, 38, 20,,, -7, 3, 1, 1, 2, 2, 1, 1, 128, 56, 56, 38, 20,,, -7, 3, 1, 1, 2, 2, 1, 1, 256, 56, 56, 38, 20,,, -7, 3, 1, 1, 2, 2, 1, 1, 384, 56, 56, 38, 20,,, -7, 3, 1, 1, 2, 2, 1, 2, 128, 56, 56, 38, 20,,, -7, 3, 1, 1, 2, 2, 1, 2, 256, 56, 56, 38, 20,,, -7, 3, 1, 1, 2, 2, 1, 2, 384, 56, 56, 38, 20,,, -7, 3, 1, 1, 2, 2, 2, 1, 128, 56, 56, 38, 20,,, -7, 3, 1, 1, 2, 2, 2, 1, 256, 56, 56, 38, 20,,, -7, 3, 1, 1, 2, 2, 2, 1, 384, 56, 56, 38, 20,,, -7, 3, 1, 1, 2, 2, 2, 2, 128, 56, 56, 38, 20,,, -7, 3, 1, 1, 2, 2, 2, 2, 256, 56, 56, 38, 20,,, -7, 3, 1, 1, 2, 2, 2, 2, 384, 56, 56, 38, 20,,, -7, 3, 1, 1, 3, 3, 1, 1, 128, 56, 56, 38, 20,,, -7, 3, 1, 1, 3, 3, 1, 1, 256, 56, 56, 38, 20,,, -7, 3, 1, 1, 3, 3, 1, 1, 384, 56, 56, 38, 20,,, -7, 3, 1, 1, 3, 3, 1, 2, 128, 56, 56, 38, 20,,, -7, 3, 1, 1, 3, 3, 1, 2, 256, 56, 56, 38, 20,,, -7, 3, 1, 1, 3, 3, 1, 2, 384, 56, 56, 38, 20,,, -7, 3, 1, 1, 3, 3, 1, 3, 128, 56, 56, 38, 20,,, -7, 3, 1, 1, 3, 3, 1, 3, 256, 56, 56, 38, 20,,, -7, 3, 1, 1, 3, 3, 1, 3, 384, 56, 56, 38, 20,,, -7, 3, 1, 1, 3, 3, 2, 1, 128, 56, 56, 38, 20,,, -7, 3, 1, 1, 3, 3, 2, 1, 256, 56, 56, 38, 20,,, -7, 3, 1, 1, 3, 3, 2, 1, 384, 56, 56, 38, 20,,, -7, 3, 1, 1, 3, 3, 2, 2, 128, 56, 56, 38, 20,,, -7, 3, 1, 1, 3, 3, 2, 2, 256, 56, 56, 38, 20,,, -7, 3, 1, 1, 3, 3, 2, 2, 384, 56, 56, 38, 20,,, -7, 3, 1, 1, 3, 3, 2, 3, 128, 56, 56, 38, 20,,, -7, 3, 1, 1, 3, 3, 2, 3, 256, 56, 56, 38, 20,,, -7, 3, 1, 1, 3, 3, 2, 3, 384, 56, 56, 38, 20,,, -7, 3, 1, 1, 3, 3, 3, 1, 128, 56, 56, 38, 20,,, -7, 3, 1, 1, 3, 3, 3, 1, 256, 56, 56, 38, 20,,, -7, 3, 1, 1, 3, 3, 3, 1, 384, 56, 56, 38, 20,,, -7, 3, 1, 1, 3, 3, 3, 2, 128, 56, 56, 38, 20,,, -7, 3, 1, 1, 3, 3, 3, 2, 256, 56, 56, 38, 20,,, -7, 3, 1, 1, 3, 3, 3, 2, 384, 56, 56, 38, 20,,, -7, 3, 1, 1, 3, 3, 3, 3, 128, 56, 56, 38, 20,,, -7, 3, 1, 1, 3, 3, 3, 3, 256, 56, 56, 38, 20,,, -7, 3, 1, 1, 3, 3, 3, 3, 384, 56, 56, 38, 20,,, -7, 3, 1, 2, 1, 1, 1, 1, 128, 110, 110, 74, 38,,, -7, 3, 1, 2, 1, 1, 1, 1, 256, 110, 110, 74, 38,,, -7, 3, 1, 2, 1, 1, 1, 1, 384, 110, 110, 74, 38,,, -7, 3, 1, 2, 2, 2, 1, 1, 128, 110, 110, 74, 38,,, -7, 3, 1, 2, 2, 2, 1, 1, 256, 110, 110, 74, 38,,, -7, 3, 1, 2, 2, 2, 1, 1, 384, 110, 110, 74, 38,,, -7, 3, 1, 2, 2, 2, 1, 2, 128, 110, 110, 74, 38,,, -7, 3, 1, 2, 2, 2, 1, 2, 256, 110, 110, 74, 38,,, -7, 3, 1, 2, 2, 2, 1, 2, 384, 110, 110, 74, 38,,, -7, 3, 1, 2, 2, 2, 2, 1, 128, 110, 110, 74, 38,,, -7, 3, 1, 2, 2, 2, 2, 1, 256, 110, 110, 74, 38,,, -7, 3, 1, 2, 2, 2, 2, 1, 384, 110, 110, 74, 38,,, -7, 3, 1, 2, 2, 2, 2, 2, 128, 110, 110, 74, 38,,, -7, 3, 1, 2, 2, 2, 2, 2, 256, 110, 110, 74, 38,,, -7, 3, 1, 2, 2, 2, 2, 2, 384, 110, 110, 74, 38,,, -7, 3, 1, 2, 3, 3, 1, 1, 128, 110, 110, 74, 38,,, -7, 3, 1, 2, 3, 3, 1, 1, 256, 110, 110, 74, 38,,, -7, 3, 1, 2, 3, 3, 1, 1, 384, 110, 110, 74, 38,,, -7, 3, 1, 2, 3, 3, 1, 2, 128, 110, 110, 74, 38,,, -7, 3, 1, 2, 3, 3, 1, 2, 256, 110, 110, 74, 38,,, -7, 3, 1, 2, 3, 3, 1, 2, 384, 110, 110, 74, 38,,, -7, 3, 1, 2, 3, 3, 1, 3, 128, 110, 110, 74, 38,,, -7, 3, 1, 2, 3, 3, 1, 3, 256, 110, 110, 74, 38,,, -7, 3, 1, 2, 3, 3, 1, 3, 384, 110, 110, 74, 38,,, -7, 3, 1, 2, 3, 3, 2, 1, 128, 110, 110, 74, 38,,, -7, 3, 1, 2, 3, 3, 2, 1, 256, 110, 110, 74, 38,,, -7, 3, 1, 2, 3, 3, 2, 1, 384, 110, 110, 74, 38,,, -7, 3, 1, 2, 3, 3, 2, 2, 128, 110, 110, 74, 38,,, -7, 3, 1, 2, 3, 3, 2, 2, 256, 110, 110, 74, 38,,, -7, 3, 1, 2, 3, 3, 2, 2, 384, 110, 110, 74, 38,,, -7, 3, 1, 2, 3, 3, 2, 3, 128, 110, 110, 74, 38,,, -7, 3, 1, 2, 3, 3, 2, 3, 256, 110, 110, 74, 38,,, -7, 3, 1, 2, 3, 3, 2, 3, 384, 110, 110, 74, 38,,, -7, 3, 1, 2, 3, 3, 3, 1, 128, 110, 110, 74, 38,,, -7, 3, 1, 2, 3, 3, 3, 1, 256, 110, 110, 74, 38,,, -7, 3, 1, 2, 3, 3, 3, 1, 384, 110, 110, 74, 38,,, -7, 3, 1, 2, 3, 3, 3, 2, 128, 110, 110, 74, 38,,, -7, 3, 1, 2, 3, 3, 3, 2, 256, 110, 110, 74, 38,,, -7, 3, 1, 2, 3, 3, 3, 2, 384, 110, 110, 74, 38,,, -7, 3, 1, 2, 3, 3, 3, 3, 128, 110, 110, 74, 38,,, -7, 3, 1, 2, 3, 3, 3, 3, 256, 110, 110, 74, 38,,, -7, 3, 1, 2, 3, 3, 3, 3, 384, 110, 110, 74, 38,,, -7, 3, 1, 3, 1, 1, 1, 1, 128, 164, 164, 110, 56,,, -7, 3, 1, 3, 1, 1, 1, 1, 256, 164, 164, 110, 56,,, -7, 3, 1, 3, 1, 1, 1, 1, 384, 164, 164, 110, 56,,, -7, 3, 1, 3, 2, 2, 1, 1, 128, 164, 164, 110, 56,,, -7, 3, 1, 3, 2, 2, 1, 1, 256, 164, 164, 110, 56,,, -7, 3, 1, 3, 2, 2, 1, 1, 384, 164, 164, 110, 56,,, -7, 3, 1, 3, 2, 2, 1, 2, 128, 164, 164, 110, 56,,, -7, 3, 1, 3, 2, 2, 1, 2, 256, 164, 164, 110, 56,,, -7, 3, 1, 3, 2, 2, 1, 2, 384, 164, 164, 110, 56,,, -7, 3, 1, 3, 2, 2, 2, 1, 128, 164, 164, 110, 56,,, -7, 3, 1, 3, 2, 2, 2, 1, 256, 164, 164, 110, 56,,, -7, 3, 1, 3, 2, 2, 2, 1, 384, 164, 164, 110, 56,,, -7, 3, 1, 3, 2, 2, 2, 2, 128, 164, 164, 110, 56,,, -7, 3, 1, 3, 2, 2, 2, 2, 256, 164, 164, 110, 56,,, -7, 3, 1, 3, 2, 2, 2, 2, 384, 164, 164, 110, 56,,, -7, 3, 1, 3, 3, 3, 1, 1, 128, 164, 164, 110, 56,,, -7, 3, 1, 3, 3, 3, 1, 1, 256, 164, 164, 110, 56,,, -7, 3, 1, 3, 3, 3, 1, 1, 384, 164, 164, 110, 56,,, -7, 3, 1, 3, 3, 3, 1, 2, 128, 164, 164, 110, 56,,, -7, 3, 1, 3, 3, 3, 1, 2, 256, 164, 164, 110, 56,,, -7, 3, 1, 3, 3, 3, 1, 2, 384, 164, 164, 110, 56,,, -7, 3, 1, 3, 3, 3, 1, 3, 128, 164, 164, 110, 56,,, -7, 3, 1, 3, 3, 3, 1, 3, 256, 164, 164, 110, 56,,, -7, 3, 1, 3, 3, 3, 1, 3, 384, 164, 164, 110, 56,,, -7, 3, 1, 3, 3, 3, 2, 1, 128, 164, 164, 110, 56,,, -7, 3, 1, 3, 3, 3, 2, 1, 256, 164, 164, 110, 56,,, -7, 3, 1, 3, 3, 3, 2, 1, 384, 164, 164, 110, 56,,, -7, 3, 1, 3, 3, 3, 2, 2, 128, 164, 164, 110, 56,,, -7, 3, 1, 3, 3, 3, 2, 2, 256, 164, 164, 110, 56,,, -7, 3, 1, 3, 3, 3, 2, 2, 384, 164, 164, 110, 56,,, -7, 3, 1, 3, 3, 3, 2, 3, 128, 164, 164, 110, 56,,, -7, 3, 1, 3, 3, 3, 2, 3, 256, 164, 164, 110, 56,,, -7, 3, 1, 3, 3, 3, 2, 3, 384, 164, 164, 110, 56,,, -7, 3, 1, 3, 3, 3, 3, 1, 128, 164, 164, 110, 56,,, -7, 3, 1, 3, 3, 3, 3, 1, 256, 164, 164, 110, 56,,, -7, 3, 1, 3, 3, 3, 3, 1, 384, 164, 164, 110, 56,,, -7, 3, 1, 3, 3, 3, 3, 2, 128, 164, 164, 110, 56,,, -7, 3, 1, 3, 3, 3, 3, 2, 256, 164, 164, 110, 56,,, -7, 3, 1, 3, 3, 3, 3, 2, 384, 164, 164, 110, 56,,, -7, 3, 1, 3, 3, 3, 3, 3, 128, 164, 164, 110, 56,,, -7, 3, 1, 3, 3, 3, 3, 3, 256, 164, 164, 110, 56,,, -7, 3, 1, 3, 3, 3, 3, 3, 384, 164, 164, 110, 56,,, -7, 3, 2, 1, 1, 1, 1, 1, 128, 56, 56, 38, 20,,, -7, 3, 2, 1, 1, 1, 1, 1, 256, 56, 56, 38, 20,,, -7, 3, 2, 1, 1, 1, 1, 1, 384, 56, 56, 38, 20,,, -7, 3, 2, 1, 2, 2, 1, 1, 128, 56, 56, 38, 20,,, -7, 3, 2, 1, 2, 2, 1, 1, 256, 56, 56, 38, 20,,, -7, 3, 2, 1, 2, 2, 1, 1, 384, 56, 56, 38, 20,,, -7, 3, 2, 1, 2, 2, 1, 2, 128, 56, 56, 38, 20,,, -7, 3, 2, 1, 2, 2, 1, 2, 256, 56, 56, 38, 20,,, -7, 3, 2, 1, 2, 2, 1, 2, 384, 56, 56, 38, 20,,, -7, 3, 2, 1, 2, 2, 2, 1, 128, 56, 56, 38, 20,,, -7, 3, 2, 1, 2, 2, 2, 1, 256, 56, 56, 38, 20,,, -7, 3, 2, 1, 2, 2, 2, 1, 384, 56, 56, 38, 20,,, -7, 3, 2, 1, 2, 2, 2, 2, 128, 56, 56, 38, 20,,, -7, 3, 2, 1, 2, 2, 2, 2, 256, 56, 56, 38, 20,,, -7, 3, 2, 1, 2, 2, 2, 2, 384, 56, 56, 38, 20,,, -7, 3, 2, 1, 3, 3, 1, 1, 128, 56, 56, 38, 20,,, -7, 3, 2, 1, 3, 3, 1, 1, 256, 56, 56, 38, 20,,, -7, 3, 2, 1, 3, 3, 1, 1, 384, 56, 56, 38, 20,,, -7, 3, 2, 1, 3, 3, 1, 2, 128, 56, 56, 38, 20,,, -7, 3, 2, 1, 3, 3, 1, 2, 256, 56, 56, 38, 20,,, -7, 3, 2, 1, 3, 3, 1, 2, 384, 56, 56, 38, 20,,, -7, 3, 2, 1, 3, 3, 1, 3, 128, 56, 56, 38, 20,,, -7, 3, 2, 1, 3, 3, 1, 3, 256, 56, 56, 38, 20,,, -7, 3, 2, 1, 3, 3, 1, 3, 384, 56, 56, 38, 20,,, -7, 3, 2, 1, 3, 3, 2, 1, 128, 56, 56, 38, 20,,, -7, 3, 2, 1, 3, 3, 2, 1, 256, 56, 56, 38, 20,,, -7, 3, 2, 1, 3, 3, 2, 1, 384, 56, 56, 38, 20,,, -7, 3, 2, 1, 3, 3, 2, 2, 128, 56, 56, 38, 20,,, -7, 3, 2, 1, 3, 3, 2, 2, 256, 56, 56, 38, 20,,, -7, 3, 2, 1, 3, 3, 2, 2, 384, 56, 56, 38, 20,,, -7, 3, 2, 1, 3, 3, 2, 3, 128, 56, 56, 38, 20,,, -7, 3, 2, 1, 3, 3, 2, 3, 256, 56, 56, 38, 20,,, -7, 3, 2, 1, 3, 3, 2, 3, 384, 56, 56, 38, 20,,, -7, 3, 2, 1, 3, 3, 3, 1, 128, 56, 56, 38, 20,,, -7, 3, 2, 1, 3, 3, 3, 1, 256, 56, 56, 38, 20,,, -7, 3, 2, 1, 3, 3, 3, 1, 384, 56, 56, 38, 20,,, -7, 3, 2, 1, 3, 3, 3, 2, 128, 56, 56, 38, 20,,, -7, 3, 2, 1, 3, 3, 3, 2, 256, 56, 56, 38, 20,,, -7, 3, 2, 1, 3, 3, 3, 2, 384, 56, 56, 38, 20,,, -7, 3, 2, 1, 3, 3, 3, 3, 128, 56, 56, 38, 20,,, -7, 3, 2, 1, 3, 3, 3, 3, 256, 56, 56, 38, 20,,, -7, 3, 2, 1, 3, 3, 3, 3, 384, 56, 56, 38, 20,,, -7, 3, 2, 2, 1, 1, 1, 1, 128, 110, 110, 74, 38,,, -7, 3, 2, 2, 1, 1, 1, 1, 256, 110, 110, 74, 38,,, -7, 3, 2, 2, 1, 1, 1, 1, 384, 110, 110, 74, 38,,, -7, 3, 2, 2, 2, 2, 1, 1, 128, 110, 110, 74, 38,,, -7, 3, 2, 2, 2, 2, 1, 1, 256, 110, 110, 74, 38,,, -7, 3, 2, 2, 2, 2, 1, 1, 384, 110, 110, 74, 38,,, -7, 3, 2, 2, 2, 2, 1, 2, 128, 110, 110, 74, 38,,, -7, 3, 2, 2, 2, 2, 1, 2, 256, 110, 110, 74, 38,,, -7, 3, 2, 2, 2, 2, 1, 2, 384, 110, 110, 74, 38,,, -7, 3, 2, 2, 2, 2, 2, 1, 128, 110, 110, 74, 38,,, -7, 3, 2, 2, 2, 2, 2, 1, 256, 110, 110, 74, 38,,, -7, 3, 2, 2, 2, 2, 2, 1, 384, 110, 110, 74, 38,,, -7, 3, 2, 2, 2, 2, 2, 2, 128, 110, 110, 74, 38,,, -7, 3, 2, 2, 2, 2, 2, 2, 256, 110, 110, 74, 38,,, -7, 3, 2, 2, 2, 2, 2, 2, 384, 110, 110, 74, 38,,, -7, 3, 2, 2, 3, 3, 1, 1, 128, 110, 110, 74, 38,,, -7, 3, 2, 2, 3, 3, 1, 1, 256, 110, 110, 74, 38,,, -7, 3, 2, 2, 3, 3, 1, 1, 384, 110, 110, 74, 38,,, -7, 3, 2, 2, 3, 3, 1, 2, 128, 110, 110, 74, 38,,, -7, 3, 2, 2, 3, 3, 1, 2, 256, 110, 110, 74, 38,,, -7, 3, 2, 2, 3, 3, 1, 2, 384, 110, 110, 74, 38,,, -7, 3, 2, 2, 3, 3, 1, 3, 128, 110, 110, 74, 38,,, -7, 3, 2, 2, 3, 3, 1, 3, 256, 110, 110, 74, 38,,, -7, 3, 2, 2, 3, 3, 1, 3, 384, 110, 110, 74, 38,,, -7, 3, 2, 2, 3, 3, 2, 1, 128, 110, 110, 74, 38,,, -7, 3, 2, 2, 3, 3, 2, 1, 256, 110, 110, 74, 38,,, -7, 3, 2, 2, 3, 3, 2, 1, 384, 110, 110, 74, 38,,, -7, 3, 2, 2, 3, 3, 2, 2, 128, 110, 110, 74, 38,,, -7, 3, 2, 2, 3, 3, 2, 2, 256, 110, 110, 74, 38,,, -7, 3, 2, 2, 3, 3, 2, 2, 384, 110, 110, 74, 38,,, -7, 3, 2, 2, 3, 3, 2, 3, 128, 110, 110, 74, 38,,, -7, 3, 2, 2, 3, 3, 2, 3, 256, 110, 110, 74, 38,,, -7, 3, 2, 2, 3, 3, 2, 3, 384, 110, 110, 74, 38,,, -7, 3, 2, 2, 3, 3, 3, 1, 128, 110, 110, 74, 38,,, -7, 3, 2, 2, 3, 3, 3, 1, 256, 110, 110, 74, 38,,, -7, 3, 2, 2, 3, 3, 3, 1, 384, 110, 110, 74, 38,,, -7, 3, 2, 2, 3, 3, 3, 2, 128, 110, 110, 74, 38,,, -7, 3, 2, 2, 3, 3, 3, 2, 256, 110, 110, 74, 38,,, -7, 3, 2, 2, 3, 3, 3, 2, 384, 110, 110, 74, 38,,, -7, 3, 2, 2, 3, 3, 3, 3, 128, 110, 110, 74, 38,,, -7, 3, 2, 2, 3, 3, 3, 3, 256, 110, 110, 74, 38,,, -7, 3, 2, 2, 3, 3, 3, 3, 384, 110, 110, 74, 38,,, -7, 3, 2, 3, 1, 1, 1, 1, 128, 164, 164, 110, 56,,, -7, 3, 2, 3, 1, 1, 1, 1, 256, 164, 164, 110, 56,,, -7, 3, 2, 3, 1, 1, 1, 1, 384, 164, 164, 110, 56,,, -7, 3, 2, 3, 2, 2, 1, 1, 128, 164, 164, 110, 56,,, -7, 3, 2, 3, 2, 2, 1, 1, 256, 164, 164, 110, 56,,, -7, 3, 2, 3, 2, 2, 1, 1, 384, 164, 164, 110, 56,,, -7, 3, 2, 3, 2, 2, 1, 2, 128, 164, 164, 110, 56,,, -7, 3, 2, 3, 2, 2, 1, 2, 256, 164, 164, 110, 56,,, -7, 3, 2, 3, 2, 2, 1, 2, 384, 164, 164, 110, 56,,, -7, 3, 2, 3, 2, 2, 2, 1, 128, 164, 164, 110, 56,,, -7, 3, 2, 3, 2, 2, 2, 1, 256, 164, 164, 110, 56,,, -7, 3, 2, 3, 2, 2, 2, 1, 384, 164, 164, 110, 56,,, -7, 3, 2, 3, 2, 2, 2, 2, 128, 164, 164, 110, 56,,, -7, 3, 2, 3, 2, 2, 2, 2, 256, 164, 164, 110, 56,,, -7, 3, 2, 3, 2, 2, 2, 2, 384, 164, 164, 110, 56,,, -7, 3, 2, 3, 3, 3, 1, 1, 128, 164, 164, 110, 56,,, -7, 3, 2, 3, 3, 3, 1, 1, 256, 164, 164, 110, 56,,, -7, 3, 2, 3, 3, 3, 1, 1, 384, 164, 164, 110, 56,,, -7, 3, 2, 3, 3, 3, 1, 2, 128, 164, 164, 110, 56,,, -7, 3, 2, 3, 3, 3, 1, 2, 256, 164, 164, 110, 56,,, -7, 3, 2, 3, 3, 3, 1, 2, 384, 164, 164, 110, 56,,, -7, 3, 2, 3, 3, 3, 1, 3, 128, 164, 164, 110, 56,,, -7, 3, 2, 3, 3, 3, 1, 3, 256, 164, 164, 110, 56,,, -7, 3, 2, 3, 3, 3, 1, 3, 384, 164, 164, 110, 56,,, -7, 3, 2, 3, 3, 3, 2, 1, 128, 164, 164, 110, 56,,, -7, 3, 2, 3, 3, 3, 2, 1, 256, 164, 164, 110, 56,,, -7, 3, 2, 3, 3, 3, 2, 1, 384, 164, 164, 110, 56,,, -7, 3, 2, 3, 3, 3, 2, 2, 128, 164, 164, 110, 56,,, -7, 3, 2, 3, 3, 3, 2, 2, 256, 164, 164, 110, 56,,, -7, 3, 2, 3, 3, 3, 2, 2, 384, 164, 164, 110, 56,,, -7, 3, 2, 3, 3, 3, 2, 3, 128, 164, 164, 110, 56,,, -7, 3, 2, 3, 3, 3, 2, 3, 256, 164, 164, 110, 56,,, -7, 3, 2, 3, 3, 3, 2, 3, 384, 164, 164, 110, 56,,, -7, 3, 2, 3, 3, 3, 3, 1, 128, 164, 164, 110, 56,,, -7, 3, 2, 3, 3, 3, 3, 1, 256, 164, 164, 110, 56,,, -7, 3, 2, 3, 3, 3, 3, 1, 384, 164, 164, 110, 56,,, -7, 3, 2, 3, 3, 3, 3, 2, 128, 164, 164, 110, 56,,, -7, 3, 2, 3, 3, 3, 3, 2, 256, 164, 164, 110, 56,,, -7, 3, 2, 3, 3, 3, 3, 2, 384, 164, 164, 110, 56,,, -7, 3, 2, 3, 3, 3, 3, 3, 128, 164, 164, 110, 56,,, -7, 3, 2, 3, 3, 3, 3, 3, 256, 164, 164, 110, 56,,, -7, 3, 2, 3, 3, 3, 3, 3, 384, 164, 164, 110, 56,,, -7, 3, 3, 1, 1, 1, 1, 1, 128, 56, 56, 38, 20,,, -7, 3, 3, 1, 1, 1, 1, 1, 256, 56, 56, 38, 20,,, -7, 3, 3, 1, 1, 1, 1, 1, 384, 56, 56, 38, 20,,, -7, 3, 3, 1, 2, 2, 1, 1, 128, 56, 56, 38, 20,,, -7, 3, 3, 1, 2, 2, 1, 1, 256, 56, 56, 38, 20,,, -7, 3, 3, 1, 2, 2, 1, 1, 384, 56, 56, 38, 20,,, -7, 3, 3, 1, 2, 2, 1, 2, 128, 56, 56, 38, 20,,, -7, 3, 3, 1, 2, 2, 1, 2, 256, 56, 56, 38, 20,,, -7, 3, 3, 1, 2, 2, 1, 2, 384, 56, 56, 38, 20,,, -7, 3, 3, 1, 2, 2, 2, 1, 128, 56, 56, 38, 20,,, -7, 3, 3, 1, 2, 2, 2, 1, 256, 56, 56, 38, 20,,, -7, 3, 3, 1, 2, 2, 2, 1, 384, 56, 56, 38, 20,,, -7, 3, 3, 1, 2, 2, 2, 2, 128, 56, 56, 38, 20,,, -7, 3, 3, 1, 2, 2, 2, 2, 256, 56, 56, 38, 20,,, -7, 3, 3, 1, 2, 2, 2, 2, 384, 56, 56, 38, 20,,, -7, 3, 3, 1, 3, 3, 1, 1, 128, 56, 56, 38, 20,,, -7, 3, 3, 1, 3, 3, 1, 1, 256, 56, 56, 38, 20,,, -7, 3, 3, 1, 3, 3, 1, 1, 384, 56, 56, 38, 20,,, -7, 3, 3, 1, 3, 3, 1, 2, 128, 56, 56, 38, 20,,, -7, 3, 3, 1, 3, 3, 1, 2, 256, 56, 56, 38, 20,,, -7, 3, 3, 1, 3, 3, 1, 2, 384, 56, 56, 38, 20,,, -7, 3, 3, 1, 3, 3, 1, 3, 128, 56, 56, 38, 20,,, -7, 3, 3, 1, 3, 3, 1, 3, 256, 56, 56, 38, 20,,, -7, 3, 3, 1, 3, 3, 1, 3, 384, 56, 56, 38, 20,,, -7, 3, 3, 1, 3, 3, 2, 1, 128, 56, 56, 38, 20,,, -7, 3, 3, 1, 3, 3, 2, 1, 256, 56, 56, 38, 20,,, -7, 3, 3, 1, 3, 3, 2, 1, 384, 56, 56, 38, 20,,, -7, 3, 3, 1, 3, 3, 2, 2, 128, 56, 56, 38, 20,,, -7, 3, 3, 1, 3, 3, 2, 2, 256, 56, 56, 38, 20,,, -7, 3, 3, 1, 3, 3, 2, 2, 384, 56, 56, 38, 20,,, -7, 3, 3, 1, 3, 3, 2, 3, 128, 56, 56, 38, 20,,, -7, 3, 3, 1, 3, 3, 2, 3, 256, 56, 56, 38, 20,,, -7, 3, 3, 1, 3, 3, 2, 3, 384, 56, 56, 38, 20,,, -7, 3, 3, 1, 3, 3, 3, 1, 128, 56, 56, 38, 20,,, -7, 3, 3, 1, 3, 3, 3, 1, 256, 56, 56, 38, 20,,, -7, 3, 3, 1, 3, 3, 3, 1, 384, 56, 56, 38, 20,,, -7, 3, 3, 1, 3, 3, 3, 2, 128, 56, 56, 38, 20,,, -7, 3, 3, 1, 3, 3, 3, 2, 256, 56, 56, 38, 20,,, -7, 3, 3, 1, 3, 3, 3, 2, 384, 56, 56, 38, 20,,, -7, 3, 3, 1, 3, 3, 3, 3, 128, 56, 56, 38, 20,,, -7, 3, 3, 1, 3, 3, 3, 3, 256, 56, 56, 38, 20,,, -7, 3, 3, 1, 3, 3, 3, 3, 384, 56, 56, 38, 20,,, -7, 3, 3, 2, 1, 1, 1, 1, 128, 110, 110, 74, 38,,, -7, 3, 3, 2, 1, 1, 1, 1, 256, 110, 110, 74, 38,,, -7, 3, 3, 2, 1, 1, 1, 1, 384, 110, 110, 74, 38,,, -7, 3, 3, 2, 2, 2, 1, 1, 128, 110, 110, 74, 38,,, -7, 3, 3, 2, 2, 2, 1, 1, 256, 110, 110, 74, 38,,, -7, 3, 3, 2, 2, 2, 1, 1, 384, 110, 110, 74, 38,,, -7, 3, 3, 2, 2, 2, 1, 2, 128, 110, 110, 74, 38,,, -7, 3, 3, 2, 2, 2, 1, 2, 256, 110, 110, 74, 38,,, -7, 3, 3, 2, 2, 2, 1, 2, 384, 110, 110, 74, 38,,, -7, 3, 3, 2, 2, 2, 2, 1, 128, 110, 110, 74, 38,,, -7, 3, 3, 2, 2, 2, 2, 1, 256, 110, 110, 74, 38,,, -7, 3, 3, 2, 2, 2, 2, 1, 384, 110, 110, 74, 38,,, -7, 3, 3, 2, 2, 2, 2, 2, 128, 110, 110, 74, 38,,, -7, 3, 3, 2, 2, 2, 2, 2, 256, 110, 110, 74, 38,,, -7, 3, 3, 2, 2, 2, 2, 2, 384, 110, 110, 74, 38,,, -7, 3, 3, 2, 3, 3, 1, 1, 128, 110, 110, 74, 38,,, -7, 3, 3, 2, 3, 3, 1, 1, 256, 110, 110, 74, 38,,, -7, 3, 3, 2, 3, 3, 1, 1, 384, 110, 110, 74, 38,,, -7, 3, 3, 2, 3, 3, 1, 2, 128, 110, 110, 74, 38,,, -7, 3, 3, 2, 3, 3, 1, 2, 256, 110, 110, 74, 38,,, -7, 3, 3, 2, 3, 3, 1, 2, 384, 110, 110, 74, 38,,, -7, 3, 3, 2, 3, 3, 1, 3, 128, 110, 110, 74, 38,,, -7, 3, 3, 2, 3, 3, 1, 3, 256, 110, 110, 74, 38,,, -7, 3, 3, 2, 3, 3, 1, 3, 384, 110, 110, 74, 38,,, -7, 3, 3, 2, 3, 3, 2, 1, 128, 110, 110, 74, 38,,, -7, 3, 3, 2, 3, 3, 2, 1, 256, 110, 110, 74, 38,,, -7, 3, 3, 2, 3, 3, 2, 1, 384, 110, 110, 74, 38,,, -7, 3, 3, 2, 3, 3, 2, 2, 128, 110, 110, 74, 38,,, -7, 3, 3, 2, 3, 3, 2, 2, 256, 110, 110, 74, 38,,, -7, 3, 3, 2, 3, 3, 2, 2, 384, 110, 110, 74, 38,,, -7, 3, 3, 2, 3, 3, 2, 3, 128, 110, 110, 74, 38,,, -7, 3, 3, 2, 3, 3, 2, 3, 256, 110, 110, 74, 38,,, -7, 3, 3, 2, 3, 3, 2, 3, 384, 110, 110, 74, 38,,, -7, 3, 3, 2, 3, 3, 3, 1, 128, 110, 110, 74, 38,,, -7, 3, 3, 2, 3, 3, 3, 1, 256, 110, 110, 74, 38,,, -7, 3, 3, 2, 3, 3, 3, 1, 384, 110, 110, 74, 38,,, -7, 3, 3, 2, 3, 3, 3, 2, 128, 110, 110, 74, 38,,, -7, 3, 3, 2, 3, 3, 3, 2, 256, 110, 110, 74, 38,,, -7, 3, 3, 2, 3, 3, 3, 2, 384, 110, 110, 74, 38,,, -7, 3, 3, 2, 3, 3, 3, 3, 128, 110, 110, 74, 38,,, -7, 3, 3, 2, 3, 3, 3, 3, 256, 110, 110, 74, 38,,, -7, 3, 3, 2, 3, 3, 3, 3, 384, 110, 110, 74, 38,,, -7, 3, 3, 3, 1, 1, 1, 1, 128, 164, 164, 110, 56,,, -7, 3, 3, 3, 1, 1, 1, 1, 256, 164, 164, 110, 56,,, -7, 3, 3, 3, 1, 1, 1, 1, 384, 164, 164, 110, 56,,, -7, 3, 3, 3, 2, 2, 1, 1, 128, 164, 164, 110, 56,,, -7, 3, 3, 3, 2, 2, 1, 1, 256, 164, 164, 110, 56,,, -7, 3, 3, 3, 2, 2, 1, 1, 384, 164, 164, 110, 56,,, -7, 3, 3, 3, 2, 2, 1, 2, 128, 164, 164, 110, 56,,, -7, 3, 3, 3, 2, 2, 1, 2, 256, 164, 164, 110, 56,,, -7, 3, 3, 3, 2, 2, 1, 2, 384, 164, 164, 110, 56,,, -7, 3, 3, 3, 2, 2, 2, 1, 128, 164, 164, 110, 56,,, -7, 3, 3, 3, 2, 2, 2, 1, 256, 164, 164, 110, 56,,, -7, 3, 3, 3, 2, 2, 2, 1, 384, 164, 164, 110, 56,,, -7, 3, 3, 3, 2, 2, 2, 2, 128, 164, 164, 110, 56,,, -7, 3, 3, 3, 2, 2, 2, 2, 256, 164, 164, 110, 56,,, -7, 3, 3, 3, 2, 2, 2, 2, 384, 164, 164, 110, 56,,, -7, 3, 3, 3, 3, 3, 1, 1, 128, 164, 164, 110, 56,,, -7, 3, 3, 3, 3, 3, 1, 1, 256, 164, 164, 110, 56,,, -7, 3, 3, 3, 3, 3, 1, 1, 384, 164, 164, 110, 56,,, -7, 3, 3, 3, 3, 3, 1, 2, 128, 164, 164, 110, 56,,, -7, 3, 3, 3, 3, 3, 1, 2, 256, 164, 164, 110, 56,,, -7, 3, 3, 3, 3, 3, 1, 2, 384, 164, 164, 110, 56,,, -7, 3, 3, 3, 3, 3, 1, 3, 128, 164, 164, 110, 56,,, -7, 3, 3, 3, 3, 3, 1, 3, 256, 164, 164, 110, 56,,, -7, 3, 3, 3, 3, 3, 1, 3, 384, 164, 164, 110, 56,,, -7, 3, 3, 3, 3, 3, 2, 1, 128, 164, 164, 110, 56,,, -7, 3, 3, 3, 3, 3, 2, 1, 256, 164, 164, 110, 56,,, -7, 3, 3, 3, 3, 3, 2, 1, 384, 164, 164, 110, 56,,, -7, 3, 3, 3, 3, 3, 2, 2, 128, 164, 164, 110, 56,,, -7, 3, 3, 3, 3, 3, 2, 2, 256, 164, 164, 110, 56,,, -7, 3, 3, 3, 3, 3, 2, 2, 384, 164, 164, 110, 56,,, -7, 3, 3, 3, 3, 3, 2, 3, 128, 164, 164, 110, 56,,, -7, 3, 3, 3, 3, 3, 2, 3, 256, 164, 164, 110, 56,,, -7, 3, 3, 3, 3, 3, 2, 3, 384, 164, 164, 110, 56,,, -7, 3, 3, 3, 3, 3, 3, 1, 128, 164, 164, 110, 56,,, -7, 3, 3, 3, 3, 3, 3, 1, 256, 164, 164, 110, 56,,, -7, 3, 3, 3, 3, 3, 3, 1, 384, 164, 164, 110, 56,,, -7, 3, 3, 3, 3, 3, 3, 2, 128, 164, 164, 110, 56,,, -7, 3, 3, 3, 3, 3, 3, 2, 256, 164, 164, 110, 56,,, -7, 3, 3, 3, 3, 3, 3, 2, 384, 164, 164, 110, 56,,, -7, 3, 3, 3, 3, 3, 3, 3, 128, 164, 164, 110, 56,,, -7, 3, 3, 3, 3, 3, 3, 3, 256, 164, 164, 110, 56,,, -7, 3, 3, 3, 3, 3, 3, 3, 384, 164, 164, 110, 56,,, -7, 3, 4, 1, 1, 1, 1, 1, 128, 56, 56, 38, 20,,, -7, 3, 4, 1, 1, 1, 1, 1, 256, 56, 56, 38, 20,,, -7, 3, 4, 1, 1, 1, 1, 1, 384, 56, 56, 38, 20,,, -7, 3, 4, 1, 2, 2, 1, 1, 128, 56, 56, 38, 20,,, -7, 3, 4, 1, 2, 2, 1, 1, 256, 56, 56, 38, 20,,, -7, 3, 4, 1, 2, 2, 1, 1, 384, 56, 56, 38, 20,,, -7, 3, 4, 1, 2, 2, 1, 2, 128, 56, 56, 38, 20,,, -7, 3, 4, 1, 2, 2, 1, 2, 256, 56, 56, 38, 20,,, -7, 3, 4, 1, 2, 2, 1, 2, 384, 56, 56, 38, 20,,, -7, 3, 4, 1, 2, 2, 2, 1, 128, 56, 56, 38, 20,,, -7, 3, 4, 1, 2, 2, 2, 1, 256, 56, 56, 38, 20,,, -7, 3, 4, 1, 2, 2, 2, 1, 384, 56, 56, 38, 20,,, -7, 3, 4, 1, 2, 2, 2, 2, 128, 56, 56, 38, 20,,, -7, 3, 4, 1, 2, 2, 2, 2, 256, 56, 56, 38, 20,,, -7, 3, 4, 1, 2, 2, 2, 2, 384, 56, 56, 38, 20,,, -7, 3, 4, 1, 3, 3, 1, 1, 128, 56, 56, 38, 20,,, -7, 3, 4, 1, 3, 3, 1, 1, 256, 56, 56, 38, 20,,, -7, 3, 4, 1, 3, 3, 1, 1, 384, 56, 56, 38, 20,,, -7, 3, 4, 1, 3, 3, 1, 2, 128, 56, 56, 38, 20,,, -7, 3, 4, 1, 3, 3, 1, 2, 256, 56, 56, 38, 20,,, -7, 3, 4, 1, 3, 3, 1, 2, 384, 56, 56, 38, 20,,, -7, 3, 4, 1, 3, 3, 1, 3, 128, 56, 56, 38, 20,,, -7, 3, 4, 1, 3, 3, 1, 3, 256, 56, 56, 38, 20,,, -7, 3, 4, 1, 3, 3, 1, 3, 384, 56, 56, 38, 20,,, -7, 3, 4, 1, 3, 3, 2, 1, 128, 56, 56, 38, 20,,, -7, 3, 4, 1, 3, 3, 2, 1, 256, 56, 56, 38, 20,,, -7, 3, 4, 1, 3, 3, 2, 1, 384, 56, 56, 38, 20,,, -7, 3, 4, 1, 3, 3, 2, 2, 128, 56, 56, 38, 20,,, -7, 3, 4, 1, 3, 3, 2, 2, 256, 56, 56, 38, 20,,, -7, 3, 4, 1, 3, 3, 2, 2, 384, 56, 56, 38, 20,,, -7, 3, 4, 1, 3, 3, 2, 3, 128, 56, 56, 38, 20,,, -7, 3, 4, 1, 3, 3, 2, 3, 256, 56, 56, 38, 20,,, -7, 3, 4, 1, 3, 3, 2, 3, 384, 56, 56, 38, 20,,, -7, 3, 4, 1, 3, 3, 3, 1, 128, 56, 56, 38, 20,,, -7, 3, 4, 1, 3, 3, 3, 1, 256, 56, 56, 38, 20,,, -7, 3, 4, 1, 3, 3, 3, 1, 384, 56, 56, 38, 20,,, -7, 3, 4, 1, 3, 3, 3, 2, 128, 56, 56, 38, 20,,, -7, 3, 4, 1, 3, 3, 3, 2, 256, 56, 56, 38, 20,,, -7, 3, 4, 1, 3, 3, 3, 2, 384, 56, 56, 38, 20,,, -7, 3, 4, 1, 3, 3, 3, 3, 128, 56, 56, 38, 20,,, -7, 3, 4, 1, 3, 3, 3, 3, 256, 56, 56, 38, 20,,, -7, 3, 4, 1, 3, 3, 3, 3, 384, 56, 56, 38, 20,,, -7, 3, 4, 2, 1, 1, 1, 1, 128, 110, 110, 74, 38,,, -7, 3, 4, 2, 1, 1, 1, 1, 256, 110, 110, 74, 38,,, -7, 3, 4, 2, 1, 1, 1, 1, 384, 110, 110, 74, 38,,, -7, 3, 4, 2, 2, 2, 1, 1, 128, 110, 110, 74, 38,,, -7, 3, 4, 2, 2, 2, 1, 1, 256, 110, 110, 74, 38,,, -7, 3, 4, 2, 2, 2, 1, 1, 384, 110, 110, 74, 38,,, -7, 3, 4, 2, 2, 2, 1, 2, 128, 110, 110, 74, 38,,, -7, 3, 4, 2, 2, 2, 1, 2, 256, 110, 110, 74, 38,,, -7, 3, 4, 2, 2, 2, 1, 2, 384, 110, 110, 74, 38,,, -7, 3, 4, 2, 2, 2, 2, 1, 128, 110, 110, 74, 38,,, -7, 3, 4, 2, 2, 2, 2, 1, 256, 110, 110, 74, 38,,, -7, 3, 4, 2, 2, 2, 2, 1, 384, 110, 110, 74, 38,,, -7, 3, 4, 2, 2, 2, 2, 2, 128, 110, 110, 74, 38,,, -7, 3, 4, 2, 2, 2, 2, 2, 256, 110, 110, 74, 38,,, -7, 3, 4, 2, 2, 2, 2, 2, 384, 110, 110, 74, 38,,, -7, 3, 4, 2, 3, 3, 1, 1, 128, 110, 110, 74, 38,,, -7, 3, 4, 2, 3, 3, 1, 1, 256, 110, 110, 74, 38,,, -7, 3, 4, 2, 3, 3, 1, 1, 384, 110, 110, 74, 38,,, -7, 3, 4, 2, 3, 3, 1, 2, 128, 110, 110, 74, 38,,, -7, 3, 4, 2, 3, 3, 1, 2, 256, 110, 110, 74, 38,,, -7, 3, 4, 2, 3, 3, 1, 2, 384, 110, 110, 74, 38,,, -7, 3, 4, 2, 3, 3, 1, 3, 128, 110, 110, 74, 38,,, -7, 3, 4, 2, 3, 3, 1, 3, 256, 110, 110, 74, 38,,, -7, 3, 4, 2, 3, 3, 1, 3, 384, 110, 110, 74, 38,,, -7, 3, 4, 2, 3, 3, 2, 1, 128, 110, 110, 74, 38,,, -7, 3, 4, 2, 3, 3, 2, 1, 256, 110, 110, 74, 38,,, -7, 3, 4, 2, 3, 3, 2, 1, 384, 110, 110, 74, 38,,, -7, 3, 4, 2, 3, 3, 2, 2, 128, 110, 110, 74, 38,,, -7, 3, 4, 2, 3, 3, 2, 2, 256, 110, 110, 74, 38,,, -7, 3, 4, 2, 3, 3, 2, 2, 384, 110, 110, 74, 38,,, -7, 3, 4, 2, 3, 3, 2, 3, 128, 110, 110, 74, 38,,, -7, 3, 4, 2, 3, 3, 2, 3, 256, 110, 110, 74, 38,,, -7, 3, 4, 2, 3, 3, 2, 3, 384, 110, 110, 74, 38,,, -7, 3, 4, 2, 3, 3, 3, 1, 128, 110, 110, 74, 38,,, -7, 3, 4, 2, 3, 3, 3, 1, 256, 110, 110, 74, 38,,, -7, 3, 4, 2, 3, 3, 3, 1, 384, 110, 110, 74, 38,,, -7, 3, 4, 2, 3, 3, 3, 2, 128, 110, 110, 74, 38,,, -7, 3, 4, 2, 3, 3, 3, 2, 256, 110, 110, 74, 38,,, -7, 3, 4, 2, 3, 3, 3, 2, 384, 110, 110, 74, 38,,, -7, 3, 4, 2, 3, 3, 3, 3, 128, 110, 110, 74, 38,,, -7, 3, 4, 2, 3, 3, 3, 3, 256, 110, 110, 74, 38,,, -7, 3, 4, 2, 3, 3, 3, 3, 384, 110, 110, 74, 38,,, -7, 3, 4, 3, 1, 1, 1, 1, 128, 164, 164, 110, 56,,, -7, 3, 4, 3, 1, 1, 1, 1, 256, 164, 164, 110, 56,,, -7, 3, 4, 3, 1, 1, 1, 1, 384, 164, 164, 110, 56,,, -7, 3, 4, 3, 2, 2, 1, 1, 128, 164, 164, 110, 56,,, -7, 3, 4, 3, 2, 2, 1, 1, 256, 164, 164, 110, 56,,, -7, 3, 4, 3, 2, 2, 1, 1, 384, 164, 164, 110, 56,,, -7, 3, 4, 3, 2, 2, 1, 2, 128, 164, 164, 110, 56,,, -7, 3, 4, 3, 2, 2, 1, 2, 256, 164, 164, 110, 56,,, -7, 3, 4, 3, 2, 2, 1, 2, 384, 164, 164, 110, 56,,, -7, 3, 4, 3, 2, 2, 2, 1, 128, 164, 164, 110, 56,,, -7, 3, 4, 3, 2, 2, 2, 1, 256, 164, 164, 110, 56,,, -7, 3, 4, 3, 2, 2, 2, 1, 384, 164, 164, 110, 56,,, -7, 3, 4, 3, 2, 2, 2, 2, 128, 164, 164, 110, 56,,, -7, 3, 4, 3, 2, 2, 2, 2, 256, 164, 164, 110, 56,,, -7, 3, 4, 3, 2, 2, 2, 2, 384, 164, 164, 110, 56,,, -7, 3, 4, 3, 3, 3, 1, 1, 128, 164, 164, 110, 56,,, -7, 3, 4, 3, 3, 3, 1, 1, 256, 164, 164, 110, 56,,, -7, 3, 4, 3, 3, 3, 1, 1, 384, 164, 164, 110, 56,,, -7, 3, 4, 3, 3, 3, 1, 2, 128, 164, 164, 110, 56,,, -7, 3, 4, 3, 3, 3, 1, 2, 256, 164, 164, 110, 56,,, -7, 3, 4, 3, 3, 3, 1, 2, 384, 164, 164, 110, 56,,, -7, 3, 4, 3, 3, 3, 1, 3, 128, 164, 164, 110, 56,,, -7, 3, 4, 3, 3, 3, 1, 3, 256, 164, 164, 110, 56,,, -7, 3, 4, 3, 3, 3, 1, 3, 384, 164, 164, 110, 56,,, -7, 3, 4, 3, 3, 3, 2, 1, 128, 164, 164, 110, 56,,, -7, 3, 4, 3, 3, 3, 2, 1, 256, 164, 164, 110, 56,,, -7, 3, 4, 3, 3, 3, 2, 1, 384, 164, 164, 110, 56,,, -7, 3, 4, 3, 3, 3, 2, 2, 128, 164, 164, 110, 56,,, -7, 3, 4, 3, 3, 3, 2, 2, 256, 164, 164, 110, 56,,, -7, 3, 4, 3, 3, 3, 2, 2, 384, 164, 164, 110, 56,,, -7, 3, 4, 3, 3, 3, 2, 3, 128, 164, 164, 110, 56,,, -7, 3, 4, 3, 3, 3, 2, 3, 256, 164, 164, 110, 56,,, -7, 3, 4, 3, 3, 3, 2, 3, 384, 164, 164, 110, 56,,, -7, 3, 4, 3, 3, 3, 3, 1, 128, 164, 164, 110, 56,,, -7, 3, 4, 3, 3, 3, 3, 1, 256, 164, 164, 110, 56,,, -7, 3, 4, 3, 3, 3, 3, 1, 384, 164, 164, 110, 56,,, -7, 3, 4, 3, 3, 3, 3, 2, 128, 164, 164, 110, 56,,, -7, 3, 4, 3, 3, 3, 3, 2, 256, 164, 164, 110, 56,,, -7, 3, 4, 3, 3, 3, 3, 2, 384, 164, 164, 110, 56,,, -7, 3, 4, 3, 3, 3, 3, 3, 128, 164, 164, 110, 56,,, -7, 3, 4, 3, 3, 3, 3, 3, 256, 164, 164, 110, 56,,, -7, 3, 4, 3, 3, 3, 3, 3, 384, 164, 164, 110, 56,,, -7, 3, 5, 1, 1, 1, 1, 1, 128, 56, 56, 38, 20,,, -7, 3, 5, 1, 1, 1, 1, 1, 256, 56, 56, 38, 20,,, -7, 3, 5, 1, 1, 1, 1, 1, 384, 56, 56, 38, 20,,, -7, 3, 5, 1, 2, 2, 1, 1, 128, 56, 56, 38, 20,,, -7, 3, 5, 1, 2, 2, 1, 1, 256, 56, 56, 38, 20,,, -7, 3, 5, 1, 2, 2, 1, 1, 384, 56, 56, 38, 20,,, -7, 3, 5, 1, 2, 2, 1, 2, 128, 56, 56, 38, 20,,, -7, 3, 5, 1, 2, 2, 1, 2, 256, 56, 56, 38, 20,,, -7, 3, 5, 1, 2, 2, 1, 2, 384, 56, 56, 38, 20,,, -7, 3, 5, 1, 2, 2, 2, 1, 128, 56, 56, 38, 20,,, -7, 3, 5, 1, 2, 2, 2, 1, 256, 56, 56, 38, 20,,, -7, 3, 5, 1, 2, 2, 2, 1, 384, 56, 56, 38, 20,,, -7, 3, 5, 1, 2, 2, 2, 2, 128, 56, 56, 38, 20,,, -7, 3, 5, 1, 2, 2, 2, 2, 256, 56, 56, 38, 20,,, -7, 3, 5, 1, 2, 2, 2, 2, 384, 56, 56, 38, 20,,, -7, 3, 5, 1, 3, 3, 1, 1, 128, 56, 56, 38, 20,,, -7, 3, 5, 1, 3, 3, 1, 1, 256, 56, 56, 38, 20,,, -7, 3, 5, 1, 3, 3, 1, 1, 384, 56, 56, 38, 20,,, -7, 3, 5, 1, 3, 3, 1, 2, 128, 56, 56, 38, 20,,, -7, 3, 5, 1, 3, 3, 1, 2, 256, 56, 56, 38, 20,,, -7, 3, 5, 1, 3, 3, 1, 2, 384, 56, 56, 38, 20,,, -7, 3, 5, 1, 3, 3, 1, 3, 128, 56, 56, 38, 20,,, -7, 3, 5, 1, 3, 3, 1, 3, 256, 56, 56, 38, 20,,, -7, 3, 5, 1, 3, 3, 1, 3, 384, 56, 56, 38, 20,,, -7, 3, 5, 1, 3, 3, 2, 1, 128, 56, 56, 38, 20,,, -7, 3, 5, 1, 3, 3, 2, 1, 256, 56, 56, 38, 20,,, -7, 3, 5, 1, 3, 3, 2, 1, 384, 56, 56, 38, 20,,, -7, 3, 5, 1, 3, 3, 2, 2, 128, 56, 56, 38, 20,,, -7, 3, 5, 1, 3, 3, 2, 2, 256, 56, 56, 38, 20,,, -7, 3, 5, 1, 3, 3, 2, 2, 384, 56, 56, 38, 20,,, -7, 3, 5, 1, 3, 3, 2, 3, 128, 56, 56, 38, 20,,, -7, 3, 5, 1, 3, 3, 2, 3, 256, 56, 56, 38, 20,,, -7, 3, 5, 1, 3, 3, 2, 3, 384, 56, 56, 38, 20,,, -7, 3, 5, 1, 3, 3, 3, 1, 128, 56, 56, 38, 20,,, -7, 3, 5, 1, 3, 3, 3, 1, 256, 56, 56, 38, 20,,, -7, 3, 5, 1, 3, 3, 3, 1, 384, 56, 56, 38, 20,,, -7, 3, 5, 1, 3, 3, 3, 2, 128, 56, 56, 38, 20,,, -7, 3, 5, 1, 3, 3, 3, 2, 256, 56, 56, 38, 20,,, -7, 3, 5, 1, 3, 3, 3, 2, 384, 56, 56, 38, 20,,, -7, 3, 5, 1, 3, 3, 3, 3, 128, 56, 56, 38, 20,,, -7, 3, 5, 1, 3, 3, 3, 3, 256, 56, 56, 38, 20,,, -7, 3, 5, 1, 3, 3, 3, 3, 384, 56, 56, 38, 20,,, -7, 3, 5, 2, 1, 1, 1, 1, 128, 110, 110, 74, 38,,, -7, 3, 5, 2, 1, 1, 1, 1, 256, 110, 110, 74, 38,,, -7, 3, 5, 2, 1, 1, 1, 1, 384, 110, 110, 74, 38,,, -7, 3, 5, 2, 2, 2, 1, 1, 128, 110, 110, 74, 38,,, -7, 3, 5, 2, 2, 2, 1, 1, 256, 110, 110, 74, 38,,, -7, 3, 5, 2, 2, 2, 1, 1, 384, 110, 110, 74, 38,,, -7, 3, 5, 2, 2, 2, 1, 2, 128, 110, 110, 74, 38,,, -7, 3, 5, 2, 2, 2, 1, 2, 256, 110, 110, 74, 38,,, -7, 3, 5, 2, 2, 2, 1, 2, 384, 110, 110, 74, 38,,, -7, 3, 5, 2, 2, 2, 2, 1, 128, 110, 110, 74, 38,,, -7, 3, 5, 2, 2, 2, 2, 1, 256, 110, 110, 74, 38,,, -7, 3, 5, 2, 2, 2, 2, 1, 384, 110, 110, 74, 38,,, -7, 3, 5, 2, 2, 2, 2, 2, 128, 110, 110, 74, 38,,, -7, 3, 5, 2, 2, 2, 2, 2, 256, 110, 110, 74, 38,,, -7, 3, 5, 2, 2, 2, 2, 2, 384, 110, 110, 74, 38,,, -7, 3, 5, 2, 3, 3, 1, 1, 128, 110, 110, 74, 38,,, -7, 3, 5, 2, 3, 3, 1, 1, 256, 110, 110, 74, 38,,, -7, 3, 5, 2, 3, 3, 1, 1, 384, 110, 110, 74, 38,,, -7, 3, 5, 2, 3, 3, 1, 2, 128, 110, 110, 74, 38,,, -7, 3, 5, 2, 3, 3, 1, 2, 256, 110, 110, 74, 38,,, -7, 3, 5, 2, 3, 3, 1, 2, 384, 110, 110, 74, 38,,, -7, 3, 5, 2, 3, 3, 1, 3, 128, 110, 110, 74, 38,,, -7, 3, 5, 2, 3, 3, 1, 3, 256, 110, 110, 74, 38,,, -7, 3, 5, 2, 3, 3, 1, 3, 384, 110, 110, 74, 38,,, -7, 3, 5, 2, 3, 3, 2, 1, 128, 110, 110, 74, 38,,, -7, 3, 5, 2, 3, 3, 2, 1, 256, 110, 110, 74, 38,,, -7, 3, 5, 2, 3, 3, 2, 1, 384, 110, 110, 74, 38,,, -7, 3, 5, 2, 3, 3, 2, 2, 128, 110, 110, 74, 38,,, -7, 3, 5, 2, 3, 3, 2, 2, 256, 110, 110, 74, 38,,, -7, 3, 5, 2, 3, 3, 2, 2, 384, 110, 110, 74, 38,,, -7, 3, 5, 2, 3, 3, 2, 3, 128, 110, 110, 74, 38,,, -7, 3, 5, 2, 3, 3, 2, 3, 256, 110, 110, 74, 38,,, -7, 3, 5, 2, 3, 3, 2, 3, 384, 110, 110, 74, 38,,, -7, 3, 5, 2, 3, 3, 3, 1, 128, 110, 110, 74, 38,,, -7, 3, 5, 2, 3, 3, 3, 1, 256, 110, 110, 74, 38,,, -7, 3, 5, 2, 3, 3, 3, 1, 384, 110, 110, 74, 38,,, -7, 3, 5, 2, 3, 3, 3, 2, 128, 110, 110, 74, 38,,, -7, 3, 5, 2, 3, 3, 3, 2, 256, 110, 110, 74, 38,,, -7, 3, 5, 2, 3, 3, 3, 2, 384, 110, 110, 74, 38,,, -7, 3, 5, 2, 3, 3, 3, 3, 128, 110, 110, 74, 38,,, -7, 3, 5, 2, 3, 3, 3, 3, 256, 110, 110, 74, 38,,, -7, 3, 5, 2, 3, 3, 3, 3, 384, 110, 110, 74, 38,,, -7, 3, 5, 3, 1, 1, 1, 1, 128, 164, 164, 110, 56,,, -7, 3, 5, 3, 1, 1, 1, 1, 256, 164, 164, 110, 56,,, -7, 3, 5, 3, 1, 1, 1, 1, 384, 164, 164, 110, 56,,, -7, 3, 5, 3, 2, 2, 1, 1, 128, 164, 164, 110, 56,,, -7, 3, 5, 3, 2, 2, 1, 1, 256, 164, 164, 110, 56,,, -7, 3, 5, 3, 2, 2, 1, 1, 384, 164, 164, 110, 56,,, -7, 3, 5, 3, 2, 2, 1, 2, 128, 164, 164, 110, 56,,, -7, 3, 5, 3, 2, 2, 1, 2, 256, 164, 164, 110, 56,,, -7, 3, 5, 3, 2, 2, 1, 2, 384, 164, 164, 110, 56,,, -7, 3, 5, 3, 2, 2, 2, 1, 128, 164, 164, 110, 56,,, -7, 3, 5, 3, 2, 2, 2, 1, 256, 164, 164, 110, 56,,, -7, 3, 5, 3, 2, 2, 2, 1, 384, 164, 164, 110, 56,,, -7, 3, 5, 3, 2, 2, 2, 2, 128, 164, 164, 110, 56,,, -7, 3, 5, 3, 2, 2, 2, 2, 256, 164, 164, 110, 56,,, -7, 3, 5, 3, 2, 2, 2, 2, 384, 164, 164, 110, 56,,, -7, 3, 5, 3, 3, 3, 1, 1, 128, 164, 164, 110, 56,,, -7, 3, 5, 3, 3, 3, 1, 1, 256, 164, 164, 110, 56,,, -7, 3, 5, 3, 3, 3, 1, 1, 384, 164, 164, 110, 56,,, -7, 3, 5, 3, 3, 3, 1, 2, 128, 164, 164, 110, 56,,, -7, 3, 5, 3, 3, 3, 1, 2, 256, 164, 164, 110, 56,,, -7, 3, 5, 3, 3, 3, 1, 2, 384, 164, 164, 110, 56,,, -7, 3, 5, 3, 3, 3, 1, 3, 128, 164, 164, 110, 56,,, -7, 3, 5, 3, 3, 3, 1, 3, 256, 164, 164, 110, 56,,, -7, 3, 5, 3, 3, 3, 1, 3, 384, 164, 164, 110, 56,,, -7, 3, 5, 3, 3, 3, 2, 1, 128, 164, 164, 110, 56,,, -7, 3, 5, 3, 3, 3, 2, 1, 256, 164, 164, 110, 56,,, -7, 3, 5, 3, 3, 3, 2, 1, 384, 164, 164, 110, 56,,, -7, 3, 5, 3, 3, 3, 2, 2, 128, 164, 164, 110, 56,,, -7, 3, 5, 3, 3, 3, 2, 2, 256, 164, 164, 110, 56,,, -7, 3, 5, 3, 3, 3, 2, 2, 384, 164, 164, 110, 56,,, -7, 3, 5, 3, 3, 3, 2, 3, 128, 164, 164, 110, 56,,, -7, 3, 5, 3, 3, 3, 2, 3, 256, 164, 164, 110, 56,,, -7, 3, 5, 3, 3, 3, 2, 3, 384, 164, 164, 110, 56,,, -7, 3, 5, 3, 3, 3, 3, 1, 128, 164, 164, 110, 56,,, -7, 3, 5, 3, 3, 3, 3, 1, 256, 164, 164, 110, 56,,, -7, 3, 5, 3, 3, 3, 3, 1, 384, 164, 164, 110, 56,,, -7, 3, 5, 3, 3, 3, 3, 2, 128, 164, 164, 110, 56,,, -7, 3, 5, 3, 3, 3, 3, 2, 256, 164, 164, 110, 56,,, -7, 3, 5, 3, 3, 3, 3, 2, 384, 164, 164, 110, 56,,, -7, 3, 5, 3, 3, 3, 3, 3, 128, 164, 164, 110, 56,,, -7, 3, 5, 3, 3, 3, 3, 3, 256, 164, 164, 110, 56,,, -7, 3, 5, 3, 3, 3, 3, 3, 384, 164, 164, 110, 56,,, -7, 3, 6, 1, 1, 1, 1, 1, 128, 56, 56, 38, 20,,, -7, 3, 6, 1, 1, 1, 1, 1, 256, 56, 56, 38, 20,,, -7, 3, 6, 1, 1, 1, 1, 1, 384, 56, 56, 38, 20,,, -7, 3, 6, 1, 2, 2, 1, 1, 128, 56, 56, 38, 20,,, -7, 3, 6, 1, 2, 2, 1, 1, 256, 56, 56, 38, 20,,, -7, 3, 6, 1, 2, 2, 1, 1, 384, 56, 56, 38, 20,,, -7, 3, 6, 1, 2, 2, 1, 2, 128, 56, 56, 38, 20,,, -7, 3, 6, 1, 2, 2, 1, 2, 256, 56, 56, 38, 20,,, -7, 3, 6, 1, 2, 2, 1, 2, 384, 56, 56, 38, 20,,, -7, 3, 6, 1, 2, 2, 2, 1, 128, 56, 56, 38, 20,,, -7, 3, 6, 1, 2, 2, 2, 1, 256, 56, 56, 38, 20,,, -7, 3, 6, 1, 2, 2, 2, 1, 384, 56, 56, 38, 20,,, -7, 3, 6, 1, 2, 2, 2, 2, 128, 56, 56, 38, 20,,, -7, 3, 6, 1, 2, 2, 2, 2, 256, 56, 56, 38, 20,,, -7, 3, 6, 1, 2, 2, 2, 2, 384, 56, 56, 38, 20,,, -7, 3, 6, 1, 3, 3, 1, 1, 128, 56, 56, 38, 20,,, -7, 3, 6, 1, 3, 3, 1, 1, 256, 56, 56, 38, 20,,, -7, 3, 6, 1, 3, 3, 1, 1, 384, 56, 56, 38, 20,,, -7, 3, 6, 1, 3, 3, 1, 2, 128, 56, 56, 38, 20,,, -7, 3, 6, 1, 3, 3, 1, 2, 256, 56, 56, 38, 20,,, -7, 3, 6, 1, 3, 3, 1, 2, 384, 56, 56, 38, 20,,, -7, 3, 6, 1, 3, 3, 1, 3, 128, 56, 56, 38, 20,,, -7, 3, 6, 1, 3, 3, 1, 3, 256, 56, 56, 38, 20,,, -7, 3, 6, 1, 3, 3, 1, 3, 384, 56, 56, 38, 20,,, -7, 3, 6, 1, 3, 3, 2, 1, 128, 56, 56, 38, 20,,, -7, 3, 6, 1, 3, 3, 2, 1, 256, 56, 56, 38, 20,,, -7, 3, 6, 1, 3, 3, 2, 1, 384, 56, 56, 38, 20,,, -7, 3, 6, 1, 3, 3, 2, 2, 128, 56, 56, 38, 20,,, -7, 3, 6, 1, 3, 3, 2, 2, 256, 56, 56, 38, 20,,, -7, 3, 6, 1, 3, 3, 2, 2, 384, 56, 56, 38, 20,,, -7, 3, 6, 1, 3, 3, 2, 3, 128, 56, 56, 38, 20,,, -7, 3, 6, 1, 3, 3, 2, 3, 256, 56, 56, 38, 20,,, -7, 3, 6, 1, 3, 3, 2, 3, 384, 56, 56, 38, 20,,, -7, 3, 6, 1, 3, 3, 3, 1, 128, 56, 56, 38, 20,,, -7, 3, 6, 1, 3, 3, 3, 1, 256, 56, 56, 38, 20,,, -7, 3, 6, 1, 3, 3, 3, 1, 384, 56, 56, 38, 20,,, -7, 3, 6, 1, 3, 3, 3, 2, 128, 56, 56, 38, 20,,, -7, 3, 6, 1, 3, 3, 3, 2, 256, 56, 56, 38, 20,,, -7, 3, 6, 1, 3, 3, 3, 2, 384, 56, 56, 38, 20,,, -7, 3, 6, 1, 3, 3, 3, 3, 128, 56, 56, 38, 20,,, -7, 3, 6, 1, 3, 3, 3, 3, 256, 56, 56, 38, 20,,, -7, 3, 6, 1, 3, 3, 3, 3, 384, 56, 56, 38, 20,,, -7, 3, 6, 2, 1, 1, 1, 1, 128, 110, 110, 74, 38,,, -7, 3, 6, 2, 1, 1, 1, 1, 256, 110, 110, 74, 38,,, -7, 3, 6, 2, 1, 1, 1, 1, 384, 110, 110, 74, 38,,, -7, 3, 6, 2, 2, 2, 1, 1, 128, 110, 110, 74, 38,,, -7, 3, 6, 2, 2, 2, 1, 1, 256, 110, 110, 74, 38,,, -7, 3, 6, 2, 2, 2, 1, 1, 384, 110, 110, 74, 38,,, -7, 3, 6, 2, 2, 2, 1, 2, 128, 110, 110, 74, 38,,, -7, 3, 6, 2, 2, 2, 1, 2, 256, 110, 110, 74, 38,,, -7, 3, 6, 2, 2, 2, 1, 2, 384, 110, 110, 74, 38,,, -7, 3, 6, 2, 2, 2, 2, 1, 128, 110, 110, 74, 38,,, -7, 3, 6, 2, 2, 2, 2, 1, 256, 110, 110, 74, 38,,, -7, 3, 6, 2, 2, 2, 2, 1, 384, 110, 110, 74, 38,,, -7, 3, 6, 2, 2, 2, 2, 2, 128, 110, 110, 74, 38,,, -7, 3, 6, 2, 2, 2, 2, 2, 256, 110, 110, 74, 38,,, -7, 3, 6, 2, 2, 2, 2, 2, 384, 110, 110, 74, 38,,, -7, 3, 6, 2, 3, 3, 1, 1, 128, 110, 110, 74, 38,,, -7, 3, 6, 2, 3, 3, 1, 1, 256, 110, 110, 74, 38,,, -7, 3, 6, 2, 3, 3, 1, 1, 384, 110, 110, 74, 38,,, -7, 3, 6, 2, 3, 3, 1, 2, 128, 110, 110, 74, 38,,, -7, 3, 6, 2, 3, 3, 1, 2, 256, 110, 110, 74, 38,,, -7, 3, 6, 2, 3, 3, 1, 2, 384, 110, 110, 74, 38,,, -7, 3, 6, 2, 3, 3, 1, 3, 128, 110, 110, 74, 38,,, -7, 3, 6, 2, 3, 3, 1, 3, 256, 110, 110, 74, 38,,, -7, 3, 6, 2, 3, 3, 1, 3, 384, 110, 110, 74, 38,,, -7, 3, 6, 2, 3, 3, 2, 1, 128, 110, 110, 74, 38,,, -7, 3, 6, 2, 3, 3, 2, 1, 256, 110, 110, 74, 38,,, -7, 3, 6, 2, 3, 3, 2, 1, 384, 110, 110, 74, 38,,, -7, 3, 6, 2, 3, 3, 2, 2, 128, 110, 110, 74, 38,,, -7, 3, 6, 2, 3, 3, 2, 2, 256, 110, 110, 74, 38,,, -7, 3, 6, 2, 3, 3, 2, 2, 384, 110, 110, 74, 38,,, -7, 3, 6, 2, 3, 3, 2, 3, 128, 110, 110, 74, 38,,, -7, 3, 6, 2, 3, 3, 2, 3, 256, 110, 110, 74, 38,,, -7, 3, 6, 2, 3, 3, 2, 3, 384, 110, 110, 74, 38,,, -7, 3, 6, 2, 3, 3, 3, 1, 128, 110, 110, 74, 38,,, -7, 3, 6, 2, 3, 3, 3, 1, 256, 110, 110, 74, 38,,, -7, 3, 6, 2, 3, 3, 3, 1, 384, 110, 110, 74, 38,,, -7, 3, 6, 2, 3, 3, 3, 2, 128, 110, 110, 74, 38,,, -7, 3, 6, 2, 3, 3, 3, 2, 256, 110, 110, 74, 38,,, -7, 3, 6, 2, 3, 3, 3, 2, 384, 110, 110, 74, 38,,, -7, 3, 6, 2, 3, 3, 3, 3, 128, 110, 110, 74, 38,,, -7, 3, 6, 2, 3, 3, 3, 3, 256, 110, 110, 74, 38,,, -7, 3, 6, 2, 3, 3, 3, 3, 384, 110, 110, 74, 38,,, -7, 3, 6, 3, 1, 1, 1, 1, 128, 164, 164, 110, 56,,, -7, 3, 6, 3, 1, 1, 1, 1, 256, 164, 164, 110, 56,,, -7, 3, 6, 3, 1, 1, 1, 1, 384, 164, 164, 110, 56,,, -7, 3, 6, 3, 2, 2, 1, 1, 128, 164, 164, 110, 56,,, -7, 3, 6, 3, 2, 2, 1, 1, 256, 164, 164, 110, 56,,, -7, 3, 6, 3, 2, 2, 1, 1, 384, 164, 164, 110, 56,,, -7, 3, 6, 3, 2, 2, 1, 2, 128, 164, 164, 110, 56,,, -7, 3, 6, 3, 2, 2, 1, 2, 256, 164, 164, 110, 56,,, -7, 3, 6, 3, 2, 2, 1, 2, 384, 164, 164, 110, 56,,, -7, 3, 6, 3, 2, 2, 2, 1, 128, 164, 164, 110, 56,,, -7, 3, 6, 3, 2, 2, 2, 1, 256, 164, 164, 110, 56,,, -7, 3, 6, 3, 2, 2, 2, 1, 384, 164, 164, 110, 56,,, -7, 3, 6, 3, 2, 2, 2, 2, 128, 164, 164, 110, 56,,, -7, 3, 6, 3, 2, 2, 2, 2, 256, 164, 164, 110, 56,,, -7, 3, 6, 3, 2, 2, 2, 2, 384, 164, 164, 110, 56,,, -7, 3, 6, 3, 3, 3, 1, 1, 128, 164, 164, 110, 56,,, -7, 3, 6, 3, 3, 3, 1, 1, 256, 164, 164, 110, 56,,, -7, 3, 6, 3, 3, 3, 1, 1, 384, 164, 164, 110, 56,,, -7, 3, 6, 3, 3, 3, 1, 2, 128, 164, 164, 110, 56,,, -7, 3, 6, 3, 3, 3, 1, 2, 256, 164, 164, 110, 56,,, -7, 3, 6, 3, 3, 3, 1, 2, 384, 164, 164, 110, 56,,, -7, 3, 6, 3, 3, 3, 1, 3, 128, 164, 164, 110, 56,,, -7, 3, 6, 3, 3, 3, 1, 3, 256, 164, 164, 110, 56,,, -7, 3, 6, 3, 3, 3, 1, 3, 384, 164, 164, 110, 56,,, -7, 3, 6, 3, 3, 3, 2, 1, 128, 164, 164, 110, 56,,, -7, 3, 6, 3, 3, 3, 2, 1, 256, 164, 164, 110, 56,,, -7, 3, 6, 3, 3, 3, 2, 1, 384, 164, 164, 110, 56,,, -7, 3, 6, 3, 3, 3, 2, 2, 128, 164, 164, 110, 56,,, -7, 3, 6, 3, 3, 3, 2, 2, 256, 164, 164, 110, 56,,, -7, 3, 6, 3, 3, 3, 2, 2, 384, 164, 164, 110, 56,,, -7, 3, 6, 3, 3, 3, 2, 3, 128, 164, 164, 110, 56,,, -7, 3, 6, 3, 3, 3, 2, 3, 256, 164, 164, 110, 56,,, -7, 3, 6, 3, 3, 3, 2, 3, 384, 164, 164, 110, 56,,, -7, 3, 6, 3, 3, 3, 3, 1, 128, 164, 164, 110, 56,,, -7, 3, 6, 3, 3, 3, 3, 1, 256, 164, 164, 110, 56,,, -7, 3, 6, 3, 3, 3, 3, 1, 384, 164, 164, 110, 56,,, -7, 3, 6, 3, 3, 3, 3, 2, 128, 164, 164, 110, 56,,, -7, 3, 6, 3, 3, 3, 3, 2, 256, 164, 164, 110, 56,,, -7, 3, 6, 3, 3, 3, 3, 2, 384, 164, 164, 110, 56,,, -7, 3, 6, 3, 3, 3, 3, 3, 128, 164, 164, 110, 56,,, -7, 3, 6, 3, 3, 3, 3, 3, 256, 164, 164, 110, 56,,, -7, 3, 6, 3, 3, 3, 3, 3, 384, 164, 164, 110, 56,,, -7, 3, 7, 1, 1, 1, 1, 1, 128, 56, 56, 38, 20,,, -7, 3, 7, 1, 1, 1, 1, 1, 256, 56, 56, 38, 20,,, -7, 3, 7, 1, 1, 1, 1, 1, 384, 56, 56, 38, 20,,, -7, 3, 7, 1, 2, 2, 1, 1, 128, 56, 56, 38, 20,,, -7, 3, 7, 1, 2, 2, 1, 1, 256, 56, 56, 38, 20,,, -7, 3, 7, 1, 2, 2, 1, 1, 384, 56, 56, 38, 20,,, -7, 3, 7, 1, 2, 2, 1, 2, 128, 56, 56, 38, 20,,, -7, 3, 7, 1, 2, 2, 1, 2, 256, 56, 56, 38, 20,,, -7, 3, 7, 1, 2, 2, 1, 2, 384, 56, 56, 38, 20,,, -7, 3, 7, 1, 2, 2, 2, 1, 128, 56, 56, 38, 20,,, -7, 3, 7, 1, 2, 2, 2, 1, 256, 56, 56, 38, 20,,, -7, 3, 7, 1, 2, 2, 2, 1, 384, 56, 56, 38, 20,,, -7, 3, 7, 1, 2, 2, 2, 2, 128, 56, 56, 38, 20,,, -7, 3, 7, 1, 2, 2, 2, 2, 256, 56, 56, 38, 20,,, -7, 3, 7, 1, 2, 2, 2, 2, 384, 56, 56, 38, 20,,, -7, 3, 7, 1, 3, 3, 1, 1, 128, 56, 56, 38, 20,,, -7, 3, 7, 1, 3, 3, 1, 1, 256, 56, 56, 38, 20,,, -7, 3, 7, 1, 3, 3, 1, 1, 384, 56, 56, 38, 20,,, -7, 3, 7, 1, 3, 3, 1, 2, 128, 56, 56, 38, 20,,, -7, 3, 7, 1, 3, 3, 1, 2, 256, 56, 56, 38, 20,,, -7, 3, 7, 1, 3, 3, 1, 2, 384, 56, 56, 38, 20,,, -7, 3, 7, 1, 3, 3, 1, 3, 128, 56, 56, 38, 20,,, -7, 3, 7, 1, 3, 3, 1, 3, 256, 56, 56, 38, 20,,, -7, 3, 7, 1, 3, 3, 1, 3, 384, 56, 56, 38, 20,,, -7, 3, 7, 1, 3, 3, 2, 1, 128, 56, 56, 38, 20,,, -7, 3, 7, 1, 3, 3, 2, 1, 256, 56, 56, 38, 20,,, -7, 3, 7, 1, 3, 3, 2, 1, 384, 56, 56, 38, 20,,, -7, 3, 7, 1, 3, 3, 2, 2, 128, 56, 56, 38, 20,,, -7, 3, 7, 1, 3, 3, 2, 2, 256, 56, 56, 38, 20,,, -7, 3, 7, 1, 3, 3, 2, 2, 384, 56, 56, 38, 20,,, -7, 3, 7, 1, 3, 3, 2, 3, 128, 56, 56, 38, 20,,, -7, 3, 7, 1, 3, 3, 2, 3, 256, 56, 56, 38, 20,,, -7, 3, 7, 1, 3, 3, 2, 3, 384, 56, 56, 38, 20,,, -7, 3, 7, 1, 3, 3, 3, 1, 128, 56, 56, 38, 20,,, -7, 3, 7, 1, 3, 3, 3, 1, 256, 56, 56, 38, 20,,, -7, 3, 7, 1, 3, 3, 3, 1, 384, 56, 56, 38, 20,,, -7, 3, 7, 1, 3, 3, 3, 2, 128, 56, 56, 38, 20,,, -7, 3, 7, 1, 3, 3, 3, 2, 256, 56, 56, 38, 20,,, -7, 3, 7, 1, 3, 3, 3, 2, 384, 56, 56, 38, 20,,, -7, 3, 7, 1, 3, 3, 3, 3, 128, 56, 56, 38, 20,,, -7, 3, 7, 1, 3, 3, 3, 3, 256, 56, 56, 38, 20,,, -7, 3, 7, 1, 3, 3, 3, 3, 384, 56, 56, 38, 20,,, -7, 3, 7, 2, 1, 1, 1, 1, 128, 110, 110, 74, 38,,, -7, 3, 7, 2, 1, 1, 1, 1, 256, 110, 110, 74, 38,,, -7, 3, 7, 2, 1, 1, 1, 1, 384, 110, 110, 74, 38,,, -7, 3, 7, 2, 2, 2, 1, 1, 128, 110, 110, 74, 38,,, -7, 3, 7, 2, 2, 2, 1, 1, 256, 110, 110, 74, 38,,, -7, 3, 7, 2, 2, 2, 1, 1, 384, 110, 110, 74, 38,,, -7, 3, 7, 2, 2, 2, 1, 2, 128, 110, 110, 74, 38,,, -7, 3, 7, 2, 2, 2, 1, 2, 256, 110, 110, 74, 38,,, -7, 3, 7, 2, 2, 2, 1, 2, 384, 110, 110, 74, 38,,, -7, 3, 7, 2, 2, 2, 2, 1, 128, 110, 110, 74, 38,,, -7, 3, 7, 2, 2, 2, 2, 1, 256, 110, 110, 74, 38,,, -7, 3, 7, 2, 2, 2, 2, 1, 384, 110, 110, 74, 38,,, -7, 3, 7, 2, 2, 2, 2, 2, 128, 110, 110, 74, 38,,, -7, 3, 7, 2, 2, 2, 2, 2, 256, 110, 110, 74, 38,,, -7, 3, 7, 2, 2, 2, 2, 2, 384, 110, 110, 74, 38,,, -7, 3, 7, 2, 3, 3, 1, 1, 128, 110, 110, 74, 38,,, -7, 3, 7, 2, 3, 3, 1, 1, 256, 110, 110, 74, 38,,, -7, 3, 7, 2, 3, 3, 1, 1, 384, 110, 110, 74, 38,,, -7, 3, 7, 2, 3, 3, 1, 2, 128, 110, 110, 74, 38,,, -7, 3, 7, 2, 3, 3, 1, 2, 256, 110, 110, 74, 38,,, -7, 3, 7, 2, 3, 3, 1, 2, 384, 110, 110, 74, 38,,, -7, 3, 7, 2, 3, 3, 1, 3, 128, 110, 110, 74, 38,,, -7, 3, 7, 2, 3, 3, 1, 3, 256, 110, 110, 74, 38,,, -7, 3, 7, 2, 3, 3, 1, 3, 384, 110, 110, 74, 38,,, -7, 3, 7, 2, 3, 3, 2, 1, 128, 110, 110, 74, 38,,, -7, 3, 7, 2, 3, 3, 2, 1, 256, 110, 110, 74, 38,,, -7, 3, 7, 2, 3, 3, 2, 1, 384, 110, 110, 74, 38,,, -7, 3, 7, 2, 3, 3, 2, 2, 128, 110, 110, 74, 38,,, -7, 3, 7, 2, 3, 3, 2, 2, 256, 110, 110, 74, 38,,, -7, 3, 7, 2, 3, 3, 2, 2, 384, 110, 110, 74, 38,,, -7, 3, 7, 2, 3, 3, 2, 3, 128, 110, 110, 74, 38,,, -7, 3, 7, 2, 3, 3, 2, 3, 256, 110, 110, 74, 38,,, -7, 3, 7, 2, 3, 3, 2, 3, 384, 110, 110, 74, 38,,, -7, 3, 7, 2, 3, 3, 3, 1, 128, 110, 110, 74, 38,,, -7, 3, 7, 2, 3, 3, 3, 1, 256, 110, 110, 74, 38,,, -7, 3, 7, 2, 3, 3, 3, 1, 384, 110, 110, 74, 38,,, -7, 3, 7, 2, 3, 3, 3, 2, 128, 110, 110, 74, 38,,, -7, 3, 7, 2, 3, 3, 3, 2, 256, 110, 110, 74, 38,,, -7, 3, 7, 2, 3, 3, 3, 2, 384, 110, 110, 74, 38,,, -7, 3, 7, 2, 3, 3, 3, 3, 128, 110, 110, 74, 38,,, -7, 3, 7, 2, 3, 3, 3, 3, 256, 110, 110, 74, 38,,, -7, 3, 7, 2, 3, 3, 3, 3, 384, 110, 110, 74, 38,,, -7, 3, 7, 3, 1, 1, 1, 1, 128, 164, 164, 110, 56,,, -7, 3, 7, 3, 1, 1, 1, 1, 256, 164, 164, 110, 56,,, -7, 3, 7, 3, 1, 1, 1, 1, 384, 164, 164, 110, 56,,, -7, 3, 7, 3, 2, 2, 1, 1, 128, 164, 164, 110, 56,,, -7, 3, 7, 3, 2, 2, 1, 1, 256, 164, 164, 110, 56,,, -7, 3, 7, 3, 2, 2, 1, 1, 384, 164, 164, 110, 56,,, -7, 3, 7, 3, 2, 2, 1, 2, 128, 164, 164, 110, 56,,, -7, 3, 7, 3, 2, 2, 1, 2, 256, 164, 164, 110, 56,,, -7, 3, 7, 3, 2, 2, 1, 2, 384, 164, 164, 110, 56,,, -7, 3, 7, 3, 2, 2, 2, 1, 128, 164, 164, 110, 56,,, -7, 3, 7, 3, 2, 2, 2, 1, 256, 164, 164, 110, 56,,, -7, 3, 7, 3, 2, 2, 2, 1, 384, 164, 164, 110, 56,,, -7, 3, 7, 3, 2, 2, 2, 2, 128, 164, 164, 110, 56,,, -7, 3, 7, 3, 2, 2, 2, 2, 256, 164, 164, 110, 56,,, -7, 3, 7, 3, 2, 2, 2, 2, 384, 164, 164, 110, 56,,, -7, 3, 7, 3, 3, 3, 1, 1, 128, 164, 164, 110, 56,,, -7, 3, 7, 3, 3, 3, 1, 1, 256, 164, 164, 110, 56,,, -7, 3, 7, 3, 3, 3, 1, 1, 384, 164, 164, 110, 56,,, -7, 3, 7, 3, 3, 3, 1, 2, 128, 164, 164, 110, 56,,, -7, 3, 7, 3, 3, 3, 1, 2, 256, 164, 164, 110, 56,,, -7, 3, 7, 3, 3, 3, 1, 2, 384, 164, 164, 110, 56,,, -7, 3, 7, 3, 3, 3, 1, 3, 128, 164, 164, 110, 56,,, -7, 3, 7, 3, 3, 3, 1, 3, 256, 164, 164, 110, 56,,, -7, 3, 7, 3, 3, 3, 1, 3, 384, 164, 164, 110, 56,,, -7, 3, 7, 3, 3, 3, 2, 1, 128, 164, 164, 110, 56,,, -7, 3, 7, 3, 3, 3, 2, 1, 256, 164, 164, 110, 56,,, -7, 3, 7, 3, 3, 3, 2, 1, 384, 164, 164, 110, 56,,, -7, 3, 7, 3, 3, 3, 2, 2, 128, 164, 164, 110, 56,,, -7, 3, 7, 3, 3, 3, 2, 2, 256, 164, 164, 110, 56,,, -7, 3, 7, 3, 3, 3, 2, 2, 384, 164, 164, 110, 56,,, -7, 3, 7, 3, 3, 3, 2, 3, 128, 164, 164, 110, 56,,, -7, 3, 7, 3, 3, 3, 2, 3, 256, 164, 164, 110, 56,,, -7, 3, 7, 3, 3, 3, 2, 3, 384, 164, 164, 110, 56,,, -7, 3, 7, 3, 3, 3, 3, 1, 128, 164, 164, 110, 56,,, -7, 3, 7, 3, 3, 3, 3, 1, 256, 164, 164, 110, 56,,, -7, 3, 7, 3, 3, 3, 3, 1, 384, 164, 164, 110, 56,,, -7, 3, 7, 3, 3, 3, 3, 2, 128, 164, 164, 110, 56,,, -7, 3, 7, 3, 3, 3, 3, 2, 256, 164, 164, 110, 56,,, -7, 3, 7, 3, 3, 3, 3, 2, 384, 164, 164, 110, 56,,, -7, 3, 7, 3, 3, 3, 3, 3, 128, 164, 164, 110, 56,,, -7, 3, 7, 3, 3, 3, 3, 3, 256, 164, 164, 110, 56,,, -7, 3, 7, 3, 3, 3, 3, 3, 384, 164, 164, 110, 56,,, -7, 4, 1, 1, 1, 1, 1, 1, 128, 57, 57, 39,,,, -7, 4, 1, 1, 1, 1, 1, 1, 256, 57, 57, 39,,,, -7, 4, 1, 1, 1, 1, 1, 1, 384, 57, 57, 39,,,, -7, 4, 1, 1, 2, 2, 1, 1, 128, 57, 55, 39,,,, -7, 4, 1, 1, 2, 2, 1, 1, 256, 57, 55, 39,,,, -7, 4, 1, 1, 2, 2, 1, 1, 384, 57, 55, 39,,,, -7, 4, 1, 1, 2, 2, 1, 2, 128, 57, 55, 39,,,, -7, 4, 1, 1, 2, 2, 1, 2, 256, 57, 55, 39,,,, -7, 4, 1, 1, 2, 2, 1, 2, 384, 57, 55, 39,,,, -7, 4, 1, 1, 2, 2, 2, 1, 128, 57, 55, 39,,,, -7, 4, 1, 1, 2, 2, 2, 1, 256, 57, 55, 39,,,, -7, 4, 1, 1, 2, 2, 2, 1, 384, 57, 55, 39,,,, -7, 4, 1, 1, 2, 2, 2, 2, 128, 57, 55, 39,,,, -7, 4, 1, 1, 2, 2, 2, 2, 256, 57, 55, 39,,,, -7, 4, 1, 1, 2, 2, 2, 2, 384, 57, 55, 39,,,, -7, 4, 1, 1, 3, 3, 1, 1, 128, 57, 54, 39,,,, -7, 4, 1, 1, 3, 3, 1, 1, 256, 57, 54, 39,,,, -7, 4, 1, 1, 3, 3, 1, 1, 384, 57, 54, 39,,,, -7, 4, 1, 1, 3, 3, 1, 2, 128, 57, 54, 39,,,, -7, 4, 1, 1, 3, 3, 1, 2, 256, 57, 54, 39,,,, -7, 4, 1, 1, 3, 3, 1, 2, 384, 57, 54, 39,,,, -7, 4, 1, 1, 3, 3, 1, 3, 128, 57, 54, 39,,,, -7, 4, 1, 1, 3, 3, 1, 3, 256, 57, 54, 39,,,, -7, 4, 1, 1, 3, 3, 1, 3, 384, 57, 54, 39,,,, -7, 4, 1, 1, 3, 3, 2, 1, 128, 57, 54, 39,,,, -7, 4, 1, 1, 3, 3, 2, 1, 256, 57, 54, 39,,,, -7, 4, 1, 1, 3, 3, 2, 1, 384, 57, 54, 39,,,, -7, 4, 1, 1, 3, 3, 2, 2, 128, 57, 54, 39,,,, -7, 4, 1, 1, 3, 3, 2, 2, 256, 57, 54, 39,,,, -7, 4, 1, 1, 3, 3, 2, 2, 384, 57, 54, 39,,,, -7, 4, 1, 1, 3, 3, 2, 3, 128, 57, 54, 39,,,, -7, 4, 1, 1, 3, 3, 2, 3, 256, 57, 54, 39,,,, -7, 4, 1, 1, 3, 3, 2, 3, 384, 57, 54, 39,,,, -7, 4, 1, 1, 3, 3, 3, 1, 128, 57, 54, 39,,,, -7, 4, 1, 1, 3, 3, 3, 1, 256, 57, 54, 39,,,, -7, 4, 1, 1, 3, 3, 3, 1, 384, 57, 54, 39,,,, -7, 4, 1, 1, 3, 3, 3, 2, 128, 57, 54, 39,,,, -7, 4, 1, 1, 3, 3, 3, 2, 256, 57, 54, 39,,,, -7, 4, 1, 1, 3, 3, 3, 2, 384, 57, 54, 39,,,, -7, 4, 1, 1, 3, 3, 3, 3, 128, 57, 54, 39,,,, -7, 4, 1, 1, 3, 3, 3, 3, 256, 57, 54, 39,,,, -7, 4, 1, 1, 3, 3, 3, 3, 384, 57, 54, 39,,,, -7, 4, 1, 2, 1, 1, 1, 1, 128, 111, 111, 75,,,, -7, 4, 1, 2, 1, 1, 1, 1, 256, 111, 111, 75,,,, -7, 4, 1, 2, 1, 1, 1, 1, 384, 111, 111, 75,,,, -7, 4, 1, 2, 2, 2, 1, 1, 128, 111, 107, 75,,,, -7, 4, 1, 2, 2, 2, 1, 1, 256, 111, 107, 75,,,, -7, 4, 1, 2, 2, 2, 1, 1, 384, 111, 107, 75,,,, -7, 4, 1, 2, 2, 2, 1, 2, 128, 111, 107, 75,,,, -7, 4, 1, 2, 2, 2, 1, 2, 256, 111, 107, 75,,,, -7, 4, 1, 2, 2, 2, 1, 2, 384, 111, 107, 75,,,, -7, 4, 1, 2, 2, 2, 2, 1, 128, 111, 107, 75,,,, -7, 4, 1, 2, 2, 2, 2, 1, 256, 111, 107, 75,,,, -7, 4, 1, 2, 2, 2, 2, 1, 384, 111, 107, 75,,,, -7, 4, 1, 2, 2, 2, 2, 2, 128, 111, 107, 75,,,, -7, 4, 1, 2, 2, 2, 2, 2, 256, 111, 107, 75,,,, -7, 4, 1, 2, 2, 2, 2, 2, 384, 111, 107, 75,,,, -7, 4, 1, 2, 3, 3, 1, 1, 128, 111, 105, 75,,,, -7, 4, 1, 2, 3, 3, 1, 1, 256, 111, 105, 75,,,, -7, 4, 1, 2, 3, 3, 1, 1, 384, 111, 105, 75,,,, -7, 4, 1, 2, 3, 3, 1, 2, 128, 111, 105, 75,,,, -7, 4, 1, 2, 3, 3, 1, 2, 256, 111, 105, 75,,,, -7, 4, 1, 2, 3, 3, 1, 2, 384, 111, 105, 75,,,, -7, 4, 1, 2, 3, 3, 1, 3, 128, 111, 105, 75,,,, -7, 4, 1, 2, 3, 3, 1, 3, 256, 111, 105, 75,,,, -7, 4, 1, 2, 3, 3, 1, 3, 384, 111, 105, 75,,,, -7, 4, 1, 2, 3, 3, 2, 1, 128, 111, 105, 75,,,, -7, 4, 1, 2, 3, 3, 2, 1, 256, 111, 105, 75,,,, -7, 4, 1, 2, 3, 3, 2, 1, 384, 111, 105, 75,,,, -7, 4, 1, 2, 3, 3, 2, 2, 128, 111, 105, 75,,,, -7, 4, 1, 2, 3, 3, 2, 2, 256, 111, 105, 75,,,, -7, 4, 1, 2, 3, 3, 2, 2, 384, 111, 105, 75,,,, -7, 4, 1, 2, 3, 3, 2, 3, 128, 111, 105, 75,,,, -7, 4, 1, 2, 3, 3, 2, 3, 256, 111, 105, 75,,,, -7, 4, 1, 2, 3, 3, 2, 3, 384, 111, 105, 75,,,, -7, 4, 1, 2, 3, 3, 3, 1, 128, 111, 105, 75,,,, -7, 4, 1, 2, 3, 3, 3, 1, 256, 111, 105, 75,,,, -7, 4, 1, 2, 3, 3, 3, 1, 384, 111, 105, 75,,,, -7, 4, 1, 2, 3, 3, 3, 2, 128, 111, 105, 75,,,, -7, 4, 1, 2, 3, 3, 3, 2, 256, 111, 105, 75,,,, -7, 4, 1, 2, 3, 3, 3, 2, 384, 111, 105, 75,,,, -7, 4, 1, 2, 3, 3, 3, 3, 128, 111, 105, 75,,,, -7, 4, 1, 2, 3, 3, 3, 3, 256, 111, 105, 75,,,, -7, 4, 1, 2, 3, 3, 3, 3, 384, 111, 105, 75,,,, -7, 4, 1, 3, 1, 1, 1, 1, 128, 165, 165, 111,,,, -7, 4, 1, 3, 1, 1, 1, 1, 256, 165, 165, 111,,,, -7, 4, 1, 3, 1, 1, 1, 1, 384, 165, 165, 111,,,, -7, 4, 1, 3, 2, 2, 1, 1, 128, 165, 159, 111,,,, -7, 4, 1, 3, 2, 2, 1, 1, 256, 165, 159, 111,,,, -7, 4, 1, 3, 2, 2, 1, 1, 384, 165, 159, 111,,,, -7, 4, 1, 3, 2, 2, 1, 2, 128, 165, 159, 111,,,, -7, 4, 1, 3, 2, 2, 1, 2, 256, 165, 159, 111,,,, -7, 4, 1, 3, 2, 2, 1, 2, 384, 165, 159, 111,,,, -7, 4, 1, 3, 2, 2, 2, 1, 128, 165, 159, 111,,,, -7, 4, 1, 3, 2, 2, 2, 1, 256, 165, 159, 111,,,, -7, 4, 1, 3, 2, 2, 2, 1, 384, 165, 159, 111,,,, -7, 4, 1, 3, 2, 2, 2, 2, 128, 165, 159, 111,,,, -7, 4, 1, 3, 2, 2, 2, 2, 256, 165, 159, 111,,,, -7, 4, 1, 3, 2, 2, 2, 2, 384, 165, 159, 111,,,, -7, 4, 1, 3, 3, 3, 1, 1, 128, 165, 156, 111,,,, -7, 4, 1, 3, 3, 3, 1, 1, 256, 165, 156, 111,,,, -7, 4, 1, 3, 3, 3, 1, 1, 384, 165, 156, 111,,,, -7, 4, 1, 3, 3, 3, 1, 2, 128, 165, 156, 111,,,, -7, 4, 1, 3, 3, 3, 1, 2, 256, 165, 156, 111,,,, -7, 4, 1, 3, 3, 3, 1, 2, 384, 165, 156, 111,,,, -7, 4, 1, 3, 3, 3, 1, 3, 128, 165, 156, 111,,,, -7, 4, 1, 3, 3, 3, 1, 3, 256, 165, 156, 111,,,, -7, 4, 1, 3, 3, 3, 1, 3, 384, 165, 156, 111,,,, -7, 4, 1, 3, 3, 3, 2, 1, 128, 165, 156, 111,,,, -7, 4, 1, 3, 3, 3, 2, 1, 256, 165, 156, 111,,,, -7, 4, 1, 3, 3, 3, 2, 1, 384, 165, 156, 111,,,, -7, 4, 1, 3, 3, 3, 2, 2, 128, 165, 156, 111,,,, -7, 4, 1, 3, 3, 3, 2, 2, 256, 165, 156, 111,,,, -7, 4, 1, 3, 3, 3, 2, 2, 384, 165, 156, 111,,,, -7, 4, 1, 3, 3, 3, 2, 3, 128, 165, 156, 111,,,, -7, 4, 1, 3, 3, 3, 2, 3, 256, 165, 156, 111,,,, -7, 4, 1, 3, 3, 3, 2, 3, 384, 165, 156, 111,,,, -7, 4, 1, 3, 3, 3, 3, 1, 128, 165, 156, 111,,,, -7, 4, 1, 3, 3, 3, 3, 1, 256, 165, 156, 111,,,, -7, 4, 1, 3, 3, 3, 3, 1, 384, 165, 156, 111,,,, -7, 4, 1, 3, 3, 3, 3, 2, 128, 165, 156, 111,,,, -7, 4, 1, 3, 3, 3, 3, 2, 256, 165, 156, 111,,,, -7, 4, 1, 3, 3, 3, 3, 2, 384, 165, 156, 111,,,, -7, 4, 1, 3, 3, 3, 3, 3, 128, 165, 156, 111,,,, -7, 4, 1, 3, 3, 3, 3, 3, 256, 165, 156, 111,,,, -7, 4, 1, 3, 3, 3, 3, 3, 384, 165, 156, 111,,,, -7, 4, 1, 4, 1, 1, 1, 1, 128, 219, 219, 147,,,, -7, 4, 1, 4, 1, 1, 1, 1, 256, 219, 219, 147,,,, -7, 4, 1, 4, 1, 1, 1, 1, 384, 219, 219, 147,,,, -7, 4, 1, 4, 2, 2, 1, 1, 128, 219, 211, 147,,,, -7, 4, 1, 4, 2, 2, 1, 1, 256, 219, 211, 147,,,, -7, 4, 1, 4, 2, 2, 1, 1, 384, 219, 211, 147,,,, -7, 4, 1, 4, 2, 2, 1, 2, 128, 219, 211, 147,,,, -7, 4, 1, 4, 2, 2, 1, 2, 256, 219, 211, 147,,,, -7, 4, 1, 4, 2, 2, 1, 2, 384, 219, 211, 147,,,, -7, 4, 1, 4, 2, 2, 2, 1, 128, 219, 211, 147,,,, -7, 4, 1, 4, 2, 2, 2, 1, 256, 219, 211, 147,,,, -7, 4, 1, 4, 2, 2, 2, 1, 384, 219, 211, 147,,,, -7, 4, 1, 4, 2, 2, 2, 2, 128, 219, 211, 147,,,, -7, 4, 1, 4, 2, 2, 2, 2, 256, 219, 211, 147,,,, -7, 4, 1, 4, 2, 2, 2, 2, 384, 219, 211, 147,,,, -7, 4, 1, 4, 3, 3, 1, 1, 128, 219, 207, 147,,,, -7, 4, 1, 4, 3, 3, 1, 1, 256, 219, 207, 147,,,, -7, 4, 1, 4, 3, 3, 1, 1, 384, 219, 207, 147,,,, -7, 4, 1, 4, 3, 3, 1, 2, 128, 219, 207, 147,,,, -7, 4, 1, 4, 3, 3, 1, 2, 256, 219, 207, 147,,,, -7, 4, 1, 4, 3, 3, 1, 2, 384, 219, 207, 147,,,, -7, 4, 1, 4, 3, 3, 1, 3, 128, 219, 207, 147,,,, -7, 4, 1, 4, 3, 3, 1, 3, 256, 219, 207, 147,,,, -7, 4, 1, 4, 3, 3, 1, 3, 384, 219, 207, 147,,,, -7, 4, 1, 4, 3, 3, 2, 1, 128, 219, 207, 147,,,, -7, 4, 1, 4, 3, 3, 2, 1, 256, 219, 207, 147,,,, -7, 4, 1, 4, 3, 3, 2, 1, 384, 219, 207, 147,,,, -7, 4, 1, 4, 3, 3, 2, 2, 128, 219, 207, 147,,,, -7, 4, 1, 4, 3, 3, 2, 2, 256, 219, 207, 147,,,, -7, 4, 1, 4, 3, 3, 2, 2, 384, 219, 207, 147,,,, -7, 4, 1, 4, 3, 3, 2, 3, 128, 219, 207, 147,,,, -7, 4, 1, 4, 3, 3, 2, 3, 256, 219, 207, 147,,,, -7, 4, 1, 4, 3, 3, 2, 3, 384, 219, 207, 147,,,, -7, 4, 1, 4, 3, 3, 3, 1, 128, 219, 207, 147,,,, -7, 4, 1, 4, 3, 3, 3, 1, 256, 219, 207, 147,,,, -7, 4, 1, 4, 3, 3, 3, 1, 384, 219, 207, 147,,,, -7, 4, 1, 4, 3, 3, 3, 2, 128, 219, 207, 147,,,, -7, 4, 1, 4, 3, 3, 3, 2, 256, 219, 207, 147,,,, -7, 4, 1, 4, 3, 3, 3, 2, 384, 219, 207, 147,,,, -7, 4, 1, 4, 3, 3, 3, 3, 128, 219, 207, 147,,,, -7, 4, 1, 4, 3, 3, 3, 3, 256, 219, 207, 147,,,, -7, 4, 1, 4, 3, 3, 3, 3, 384, 219, 207, 147,,,, -7, 4, 2, 1, 1, 1, 1, 1, 128, 57, 57, 39,,,, -7, 4, 2, 1, 1, 1, 1, 1, 256, 57, 57, 39,,,, -7, 4, 2, 1, 1, 1, 1, 1, 384, 57, 57, 39,,,, -7, 4, 2, 1, 2, 2, 1, 1, 128, 57, 55, 39,,,, -7, 4, 2, 1, 2, 2, 1, 1, 256, 57, 55, 39,,,, -7, 4, 2, 1, 2, 2, 1, 1, 384, 57, 55, 39,,,, -7, 4, 2, 1, 2, 2, 1, 2, 128, 57, 55, 39,,,, -7, 4, 2, 1, 2, 2, 1, 2, 256, 57, 55, 39,,,, -7, 4, 2, 1, 2, 2, 1, 2, 384, 57, 55, 39,,,, -7, 4, 2, 1, 2, 2, 2, 1, 128, 57, 55, 39,,,, -7, 4, 2, 1, 2, 2, 2, 1, 256, 57, 55, 39,,,, -7, 4, 2, 1, 2, 2, 2, 1, 384, 57, 55, 39,,,, -7, 4, 2, 1, 2, 2, 2, 2, 128, 57, 55, 39,,,, -7, 4, 2, 1, 2, 2, 2, 2, 256, 57, 55, 39,,,, -7, 4, 2, 1, 2, 2, 2, 2, 384, 57, 55, 39,,,, -7, 4, 2, 1, 3, 3, 1, 1, 128, 57, 54, 39,,,, -7, 4, 2, 1, 3, 3, 1, 1, 256, 57, 54, 39,,,, -7, 4, 2, 1, 3, 3, 1, 1, 384, 57, 54, 39,,,, -7, 4, 2, 1, 3, 3, 1, 2, 128, 57, 54, 39,,,, -7, 4, 2, 1, 3, 3, 1, 2, 256, 57, 54, 39,,,, -7, 4, 2, 1, 3, 3, 1, 2, 384, 57, 54, 39,,,, -7, 4, 2, 1, 3, 3, 1, 3, 128, 57, 54, 39,,,, -7, 4, 2, 1, 3, 3, 1, 3, 256, 57, 54, 39,,,, -7, 4, 2, 1, 3, 3, 1, 3, 384, 57, 54, 39,,,, -7, 4, 2, 1, 3, 3, 2, 1, 128, 57, 54, 39,,,, -7, 4, 2, 1, 3, 3, 2, 1, 256, 57, 54, 39,,,, -7, 4, 2, 1, 3, 3, 2, 1, 384, 57, 54, 39,,,, -7, 4, 2, 1, 3, 3, 2, 2, 128, 57, 54, 39,,,, -7, 4, 2, 1, 3, 3, 2, 2, 256, 57, 54, 39,,,, -7, 4, 2, 1, 3, 3, 2, 2, 384, 57, 54, 39,,,, -7, 4, 2, 1, 3, 3, 2, 3, 128, 57, 54, 39,,,, -7, 4, 2, 1, 3, 3, 2, 3, 256, 57, 54, 39,,,, -7, 4, 2, 1, 3, 3, 2, 3, 384, 57, 54, 39,,,, -7, 4, 2, 1, 3, 3, 3, 1, 128, 57, 54, 39,,,, -7, 4, 2, 1, 3, 3, 3, 1, 256, 57, 54, 39,,,, -7, 4, 2, 1, 3, 3, 3, 1, 384, 57, 54, 39,,,, -7, 4, 2, 1, 3, 3, 3, 2, 128, 57, 54, 39,,,, -7, 4, 2, 1, 3, 3, 3, 2, 256, 57, 54, 39,,,, -7, 4, 2, 1, 3, 3, 3, 2, 384, 57, 54, 39,,,, -7, 4, 2, 1, 3, 3, 3, 3, 128, 57, 54, 39,,,, -7, 4, 2, 1, 3, 3, 3, 3, 256, 57, 54, 39,,,, -7, 4, 2, 1, 3, 3, 3, 3, 384, 57, 54, 39,,,, -7, 4, 2, 2, 1, 1, 1, 1, 128, 111, 111, 75,,,, -7, 4, 2, 2, 1, 1, 1, 1, 256, 111, 111, 75,,,, -7, 4, 2, 2, 1, 1, 1, 1, 384, 111, 111, 75,,,, -7, 4, 2, 2, 2, 2, 1, 1, 128, 111, 107, 75,,,, -7, 4, 2, 2, 2, 2, 1, 1, 256, 111, 107, 75,,,, -7, 4, 2, 2, 2, 2, 1, 1, 384, 111, 107, 75,,,, -7, 4, 2, 2, 2, 2, 1, 2, 128, 111, 107, 75,,,, -7, 4, 2, 2, 2, 2, 1, 2, 256, 111, 107, 75,,,, -7, 4, 2, 2, 2, 2, 1, 2, 384, 111, 107, 75,,,, -7, 4, 2, 2, 2, 2, 2, 1, 128, 111, 107, 75,,,, -7, 4, 2, 2, 2, 2, 2, 1, 256, 111, 107, 75,,,, -7, 4, 2, 2, 2, 2, 2, 1, 384, 111, 107, 75,,,, -7, 4, 2, 2, 2, 2, 2, 2, 128, 111, 107, 75,,,, -7, 4, 2, 2, 2, 2, 2, 2, 256, 111, 107, 75,,,, -7, 4, 2, 2, 2, 2, 2, 2, 384, 111, 107, 75,,,, -7, 4, 2, 2, 3, 3, 1, 1, 128, 111, 105, 75,,,, -7, 4, 2, 2, 3, 3, 1, 1, 256, 111, 105, 75,,,, -7, 4, 2, 2, 3, 3, 1, 1, 384, 111, 105, 75,,,, -7, 4, 2, 2, 3, 3, 1, 2, 128, 111, 105, 75,,,, -7, 4, 2, 2, 3, 3, 1, 2, 256, 111, 105, 75,,,, -7, 4, 2, 2, 3, 3, 1, 2, 384, 111, 105, 75,,,, -7, 4, 2, 2, 3, 3, 1, 3, 128, 111, 105, 75,,,, -7, 4, 2, 2, 3, 3, 1, 3, 256, 111, 105, 75,,,, -7, 4, 2, 2, 3, 3, 1, 3, 384, 111, 105, 75,,,, -7, 4, 2, 2, 3, 3, 2, 1, 128, 111, 105, 75,,,, -7, 4, 2, 2, 3, 3, 2, 1, 256, 111, 105, 75,,,, -7, 4, 2, 2, 3, 3, 2, 1, 384, 111, 105, 75,,,, -7, 4, 2, 2, 3, 3, 2, 2, 128, 111, 105, 75,,,, -7, 4, 2, 2, 3, 3, 2, 2, 256, 111, 105, 75,,,, -7, 4, 2, 2, 3, 3, 2, 2, 384, 111, 105, 75,,,, -7, 4, 2, 2, 3, 3, 2, 3, 128, 111, 105, 75,,,, -7, 4, 2, 2, 3, 3, 2, 3, 256, 111, 105, 75,,,, -7, 4, 2, 2, 3, 3, 2, 3, 384, 111, 105, 75,,,, -7, 4, 2, 2, 3, 3, 3, 1, 128, 111, 105, 75,,,, -7, 4, 2, 2, 3, 3, 3, 1, 256, 111, 105, 75,,,, -7, 4, 2, 2, 3, 3, 3, 1, 384, 111, 105, 75,,,, -7, 4, 2, 2, 3, 3, 3, 2, 128, 111, 105, 75,,,, -7, 4, 2, 2, 3, 3, 3, 2, 256, 111, 105, 75,,,, -7, 4, 2, 2, 3, 3, 3, 2, 384, 111, 105, 75,,,, -7, 4, 2, 2, 3, 3, 3, 3, 128, 111, 105, 75,,,, -7, 4, 2, 2, 3, 3, 3, 3, 256, 111, 105, 75,,,, -7, 4, 2, 2, 3, 3, 3, 3, 384, 111, 105, 75,,,, -7, 4, 2, 3, 1, 1, 1, 1, 128, 165, 165, 111,,,, -7, 4, 2, 3, 1, 1, 1, 1, 256, 165, 165, 111,,,, -7, 4, 2, 3, 1, 1, 1, 1, 384, 165, 165, 111,,,, -7, 4, 2, 3, 2, 2, 1, 1, 128, 165, 159, 111,,,, -7, 4, 2, 3, 2, 2, 1, 1, 256, 165, 159, 111,,,, -7, 4, 2, 3, 2, 2, 1, 1, 384, 165, 159, 111,,,, -7, 4, 2, 3, 2, 2, 1, 2, 128, 165, 159, 111,,,, -7, 4, 2, 3, 2, 2, 1, 2, 256, 165, 159, 111,,,, -7, 4, 2, 3, 2, 2, 1, 2, 384, 165, 159, 111,,,, -7, 4, 2, 3, 2, 2, 2, 1, 128, 165, 159, 111,,,, -7, 4, 2, 3, 2, 2, 2, 1, 256, 165, 159, 111,,,, -7, 4, 2, 3, 2, 2, 2, 1, 384, 165, 159, 111,,,, -7, 4, 2, 3, 2, 2, 2, 2, 128, 165, 159, 111,,,, -7, 4, 2, 3, 2, 2, 2, 2, 256, 165, 159, 111,,,, -7, 4, 2, 3, 2, 2, 2, 2, 384, 165, 159, 111,,,, -7, 4, 2, 3, 3, 3, 1, 1, 128, 165, 156, 111,,,, -7, 4, 2, 3, 3, 3, 1, 1, 256, 165, 156, 111,,,, -7, 4, 2, 3, 3, 3, 1, 1, 384, 165, 156, 111,,,, -7, 4, 2, 3, 3, 3, 1, 2, 128, 165, 156, 111,,,, -7, 4, 2, 3, 3, 3, 1, 2, 256, 165, 156, 111,,,, -7, 4, 2, 3, 3, 3, 1, 2, 384, 165, 156, 111,,,, -7, 4, 2, 3, 3, 3, 1, 3, 128, 165, 156, 111,,,, -7, 4, 2, 3, 3, 3, 1, 3, 256, 165, 156, 111,,,, -7, 4, 2, 3, 3, 3, 1, 3, 384, 165, 156, 111,,,, -7, 4, 2, 3, 3, 3, 2, 1, 128, 165, 156, 111,,,, -7, 4, 2, 3, 3, 3, 2, 1, 256, 165, 156, 111,,,, -7, 4, 2, 3, 3, 3, 2, 1, 384, 165, 156, 111,,,, -7, 4, 2, 3, 3, 3, 2, 2, 128, 165, 156, 111,,,, -7, 4, 2, 3, 3, 3, 2, 2, 256, 165, 156, 111,,,, -7, 4, 2, 3, 3, 3, 2, 2, 384, 165, 156, 111,,,, -7, 4, 2, 3, 3, 3, 2, 3, 128, 165, 156, 111,,,, -7, 4, 2, 3, 3, 3, 2, 3, 256, 165, 156, 111,,,, -7, 4, 2, 3, 3, 3, 2, 3, 384, 165, 156, 111,,,, -7, 4, 2, 3, 3, 3, 3, 1, 128, 165, 156, 111,,,, -7, 4, 2, 3, 3, 3, 3, 1, 256, 165, 156, 111,,,, -7, 4, 2, 3, 3, 3, 3, 1, 384, 165, 156, 111,,,, -7, 4, 2, 3, 3, 3, 3, 2, 128, 165, 156, 111,,,, -7, 4, 2, 3, 3, 3, 3, 2, 256, 165, 156, 111,,,, -7, 4, 2, 3, 3, 3, 3, 2, 384, 165, 156, 111,,,, -7, 4, 2, 3, 3, 3, 3, 3, 128, 165, 156, 111,,,, -7, 4, 2, 3, 3, 3, 3, 3, 256, 165, 156, 111,,,, -7, 4, 2, 3, 3, 3, 3, 3, 384, 165, 156, 111,,,, -7, 4, 2, 4, 1, 1, 1, 1, 128, 219, 219, 147,,,, -7, 4, 2, 4, 1, 1, 1, 1, 256, 219, 219, 147,,,, -7, 4, 2, 4, 1, 1, 1, 1, 384, 219, 219, 147,,,, -7, 4, 2, 4, 2, 2, 1, 1, 128, 219, 211, 147,,,, -7, 4, 2, 4, 2, 2, 1, 1, 256, 219, 211, 147,,,, -7, 4, 2, 4, 2, 2, 1, 1, 384, 219, 211, 147,,,, -7, 4, 2, 4, 2, 2, 1, 2, 128, 219, 211, 147,,,, -7, 4, 2, 4, 2, 2, 1, 2, 256, 219, 211, 147,,,, -7, 4, 2, 4, 2, 2, 1, 2, 384, 219, 211, 147,,,, -7, 4, 2, 4, 2, 2, 2, 1, 128, 219, 211, 147,,,, -7, 4, 2, 4, 2, 2, 2, 1, 256, 219, 211, 147,,,, -7, 4, 2, 4, 2, 2, 2, 1, 384, 219, 211, 147,,,, -7, 4, 2, 4, 2, 2, 2, 2, 128, 219, 211, 147,,,, -7, 4, 2, 4, 2, 2, 2, 2, 256, 219, 211, 147,,,, -7, 4, 2, 4, 2, 2, 2, 2, 384, 219, 211, 147,,,, -7, 4, 2, 4, 3, 3, 1, 1, 128, 219, 207, 147,,,, -7, 4, 2, 4, 3, 3, 1, 1, 256, 219, 207, 147,,,, -7, 4, 2, 4, 3, 3, 1, 1, 384, 219, 207, 147,,,, -7, 4, 2, 4, 3, 3, 1, 2, 128, 219, 207, 147,,,, -7, 4, 2, 4, 3, 3, 1, 2, 256, 219, 207, 147,,,, -7, 4, 2, 4, 3, 3, 1, 2, 384, 219, 207, 147,,,, -7, 4, 2, 4, 3, 3, 1, 3, 128, 219, 207, 147,,,, -7, 4, 2, 4, 3, 3, 1, 3, 256, 219, 207, 147,,,, -7, 4, 2, 4, 3, 3, 1, 3, 384, 219, 207, 147,,,, -7, 4, 2, 4, 3, 3, 2, 1, 128, 219, 207, 147,,,, -7, 4, 2, 4, 3, 3, 2, 1, 256, 219, 207, 147,,,, -7, 4, 2, 4, 3, 3, 2, 1, 384, 219, 207, 147,,,, -7, 4, 2, 4, 3, 3, 2, 2, 128, 219, 207, 147,,,, -7, 4, 2, 4, 3, 3, 2, 2, 256, 219, 207, 147,,,, -7, 4, 2, 4, 3, 3, 2, 2, 384, 219, 207, 147,,,, -7, 4, 2, 4, 3, 3, 2, 3, 128, 219, 207, 147,,,, -7, 4, 2, 4, 3, 3, 2, 3, 256, 219, 207, 147,,,, -7, 4, 2, 4, 3, 3, 2, 3, 384, 219, 207, 147,,,, -7, 4, 2, 4, 3, 3, 3, 1, 128, 219, 207, 147,,,, -7, 4, 2, 4, 3, 3, 3, 1, 256, 219, 207, 147,,,, -7, 4, 2, 4, 3, 3, 3, 1, 384, 219, 207, 147,,,, -7, 4, 2, 4, 3, 3, 3, 2, 128, 219, 207, 147,,,, -7, 4, 2, 4, 3, 3, 3, 2, 256, 219, 207, 147,,,, -7, 4, 2, 4, 3, 3, 3, 2, 384, 219, 207, 147,,,, -7, 4, 2, 4, 3, 3, 3, 3, 128, 219, 207, 147,,,, -7, 4, 2, 4, 3, 3, 3, 3, 256, 219, 207, 147,,,, -7, 4, 2, 4, 3, 3, 3, 3, 384, 219, 207, 147,,,, -7, 4, 3, 1, 1, 1, 1, 1, 128, 57, 57, 39,,,, -7, 4, 3, 1, 1, 1, 1, 1, 256, 57, 57, 39,,,, -7, 4, 3, 1, 1, 1, 1, 1, 384, 57, 57, 39,,,, -7, 4, 3, 1, 2, 2, 1, 1, 128, 57, 55, 39,,,, -7, 4, 3, 1, 2, 2, 1, 1, 256, 57, 55, 39,,,, -7, 4, 3, 1, 2, 2, 1, 1, 384, 57, 55, 39,,,, -7, 4, 3, 1, 2, 2, 1, 2, 128, 57, 55, 39,,,, -7, 4, 3, 1, 2, 2, 1, 2, 256, 57, 55, 39,,,, -7, 4, 3, 1, 2, 2, 1, 2, 384, 57, 55, 39,,,, -7, 4, 3, 1, 2, 2, 2, 1, 128, 57, 55, 39,,,, -7, 4, 3, 1, 2, 2, 2, 1, 256, 57, 55, 39,,,, -7, 4, 3, 1, 2, 2, 2, 1, 384, 57, 55, 39,,,, -7, 4, 3, 1, 2, 2, 2, 2, 128, 57, 55, 39,,,, -7, 4, 3, 1, 2, 2, 2, 2, 256, 57, 55, 39,,,, -7, 4, 3, 1, 2, 2, 2, 2, 384, 57, 55, 39,,,, -7, 4, 3, 1, 3, 3, 1, 1, 128, 57, 54, 39,,,, -7, 4, 3, 1, 3, 3, 1, 1, 256, 57, 54, 39,,,, -7, 4, 3, 1, 3, 3, 1, 1, 384, 57, 54, 39,,,, -7, 4, 3, 1, 3, 3, 1, 2, 128, 57, 54, 39,,,, -7, 4, 3, 1, 3, 3, 1, 2, 256, 57, 54, 39,,,, -7, 4, 3, 1, 3, 3, 1, 2, 384, 57, 54, 39,,,, -7, 4, 3, 1, 3, 3, 1, 3, 128, 57, 54, 39,,,, -7, 4, 3, 1, 3, 3, 1, 3, 256, 57, 54, 39,,,, -7, 4, 3, 1, 3, 3, 1, 3, 384, 57, 54, 39,,,, -7, 4, 3, 1, 3, 3, 2, 1, 128, 57, 54, 39,,,, -7, 4, 3, 1, 3, 3, 2, 1, 256, 57, 54, 39,,,, -7, 4, 3, 1, 3, 3, 2, 1, 384, 57, 54, 39,,,, -7, 4, 3, 1, 3, 3, 2, 2, 128, 57, 54, 39,,,, -7, 4, 3, 1, 3, 3, 2, 2, 256, 57, 54, 39,,,, -7, 4, 3, 1, 3, 3, 2, 2, 384, 57, 54, 39,,,, -7, 4, 3, 1, 3, 3, 2, 3, 128, 57, 54, 39,,,, -7, 4, 3, 1, 3, 3, 2, 3, 256, 57, 54, 39,,,, -7, 4, 3, 1, 3, 3, 2, 3, 384, 57, 54, 39,,,, -7, 4, 3, 1, 3, 3, 3, 1, 128, 57, 54, 39,,,, -7, 4, 3, 1, 3, 3, 3, 1, 256, 57, 54, 39,,,, -7, 4, 3, 1, 3, 3, 3, 1, 384, 57, 54, 39,,,, -7, 4, 3, 1, 3, 3, 3, 2, 128, 57, 54, 39,,,, -7, 4, 3, 1, 3, 3, 3, 2, 256, 57, 54, 39,,,, -7, 4, 3, 1, 3, 3, 3, 2, 384, 57, 54, 39,,,, -7, 4, 3, 1, 3, 3, 3, 3, 128, 57, 54, 39,,,, -7, 4, 3, 1, 3, 3, 3, 3, 256, 57, 54, 39,,,, -7, 4, 3, 1, 3, 3, 3, 3, 384, 57, 54, 39,,,, -7, 4, 3, 2, 1, 1, 1, 1, 128, 111, 111, 75,,,, -7, 4, 3, 2, 1, 1, 1, 1, 256, 111, 111, 75,,,, -7, 4, 3, 2, 1, 1, 1, 1, 384, 111, 111, 75,,,, -7, 4, 3, 2, 2, 2, 1, 1, 128, 111, 107, 75,,,, -7, 4, 3, 2, 2, 2, 1, 1, 256, 111, 107, 75,,,, -7, 4, 3, 2, 2, 2, 1, 1, 384, 111, 107, 75,,,, -7, 4, 3, 2, 2, 2, 1, 2, 128, 111, 107, 75,,,, -7, 4, 3, 2, 2, 2, 1, 2, 256, 111, 107, 75,,,, -7, 4, 3, 2, 2, 2, 1, 2, 384, 111, 107, 75,,,, -7, 4, 3, 2, 2, 2, 2, 1, 128, 111, 107, 75,,,, -7, 4, 3, 2, 2, 2, 2, 1, 256, 111, 107, 75,,,, -7, 4, 3, 2, 2, 2, 2, 1, 384, 111, 107, 75,,,, -7, 4, 3, 2, 2, 2, 2, 2, 128, 111, 107, 75,,,, -7, 4, 3, 2, 2, 2, 2, 2, 256, 111, 107, 75,,,, -7, 4, 3, 2, 2, 2, 2, 2, 384, 111, 107, 75,,,, -7, 4, 3, 2, 3, 3, 1, 1, 128, 111, 105, 75,,,, -7, 4, 3, 2, 3, 3, 1, 1, 256, 111, 105, 75,,,, -7, 4, 3, 2, 3, 3, 1, 1, 384, 111, 105, 75,,,, -7, 4, 3, 2, 3, 3, 1, 2, 128, 111, 105, 75,,,, -7, 4, 3, 2, 3, 3, 1, 2, 256, 111, 105, 75,,,, -7, 4, 3, 2, 3, 3, 1, 2, 384, 111, 105, 75,,,, -7, 4, 3, 2, 3, 3, 1, 3, 128, 111, 105, 75,,,, -7, 4, 3, 2, 3, 3, 1, 3, 256, 111, 105, 75,,,, -7, 4, 3, 2, 3, 3, 1, 3, 384, 111, 105, 75,,,, -7, 4, 3, 2, 3, 3, 2, 1, 128, 111, 105, 75,,,, -7, 4, 3, 2, 3, 3, 2, 1, 256, 111, 105, 75,,,, -7, 4, 3, 2, 3, 3, 2, 1, 384, 111, 105, 75,,,, -7, 4, 3, 2, 3, 3, 2, 2, 128, 111, 105, 75,,,, -7, 4, 3, 2, 3, 3, 2, 2, 256, 111, 105, 75,,,, -7, 4, 3, 2, 3, 3, 2, 2, 384, 111, 105, 75,,,, -7, 4, 3, 2, 3, 3, 2, 3, 128, 111, 105, 75,,,, -7, 4, 3, 2, 3, 3, 2, 3, 256, 111, 105, 75,,,, -7, 4, 3, 2, 3, 3, 2, 3, 384, 111, 105, 75,,,, -7, 4, 3, 2, 3, 3, 3, 1, 128, 111, 105, 75,,,, -7, 4, 3, 2, 3, 3, 3, 1, 256, 111, 105, 75,,,, -7, 4, 3, 2, 3, 3, 3, 1, 384, 111, 105, 75,,,, -7, 4, 3, 2, 3, 3, 3, 2, 128, 111, 105, 75,,,, -7, 4, 3, 2, 3, 3, 3, 2, 256, 111, 105, 75,,,, -7, 4, 3, 2, 3, 3, 3, 2, 384, 111, 105, 75,,,, -7, 4, 3, 2, 3, 3, 3, 3, 128, 111, 105, 75,,,, -7, 4, 3, 2, 3, 3, 3, 3, 256, 111, 105, 75,,,, -7, 4, 3, 2, 3, 3, 3, 3, 384, 111, 105, 75,,,, -7, 4, 3, 3, 1, 1, 1, 1, 128, 165, 165, 111,,,, -7, 4, 3, 3, 1, 1, 1, 1, 256, 165, 165, 111,,,, -7, 4, 3, 3, 1, 1, 1, 1, 384, 165, 165, 111,,,, -7, 4, 3, 3, 2, 2, 1, 1, 128, 165, 159, 111,,,, -7, 4, 3, 3, 2, 2, 1, 1, 256, 165, 159, 111,,,, -7, 4, 3, 3, 2, 2, 1, 1, 384, 165, 159, 111,,,, -7, 4, 3, 3, 2, 2, 1, 2, 128, 165, 159, 111,,,, -7, 4, 3, 3, 2, 2, 1, 2, 256, 165, 159, 111,,,, -7, 4, 3, 3, 2, 2, 1, 2, 384, 165, 159, 111,,,, -7, 4, 3, 3, 2, 2, 2, 1, 128, 165, 159, 111,,,, -7, 4, 3, 3, 2, 2, 2, 1, 256, 165, 159, 111,,,, -7, 4, 3, 3, 2, 2, 2, 1, 384, 165, 159, 111,,,, -7, 4, 3, 3, 2, 2, 2, 2, 128, 165, 159, 111,,,, -7, 4, 3, 3, 2, 2, 2, 2, 256, 165, 159, 111,,,, -7, 4, 3, 3, 2, 2, 2, 2, 384, 165, 159, 111,,,, -7, 4, 3, 3, 3, 3, 1, 1, 128, 165, 156, 111,,,, -7, 4, 3, 3, 3, 3, 1, 1, 256, 165, 156, 111,,,, -7, 4, 3, 3, 3, 3, 1, 1, 384, 165, 156, 111,,,, -7, 4, 3, 3, 3, 3, 1, 2, 128, 165, 156, 111,,,, -7, 4, 3, 3, 3, 3, 1, 2, 256, 165, 156, 111,,,, -7, 4, 3, 3, 3, 3, 1, 2, 384, 165, 156, 111,,,, -7, 4, 3, 3, 3, 3, 1, 3, 128, 165, 156, 111,,,, -7, 4, 3, 3, 3, 3, 1, 3, 256, 165, 156, 111,,,, -7, 4, 3, 3, 3, 3, 1, 3, 384, 165, 156, 111,,,, -7, 4, 3, 3, 3, 3, 2, 1, 128, 165, 156, 111,,,, -7, 4, 3, 3, 3, 3, 2, 1, 256, 165, 156, 111,,,, -7, 4, 3, 3, 3, 3, 2, 1, 384, 165, 156, 111,,,, -7, 4, 3, 3, 3, 3, 2, 2, 128, 165, 156, 111,,,, -7, 4, 3, 3, 3, 3, 2, 2, 256, 165, 156, 111,,,, -7, 4, 3, 3, 3, 3, 2, 2, 384, 165, 156, 111,,,, -7, 4, 3, 3, 3, 3, 2, 3, 128, 165, 156, 111,,,, -7, 4, 3, 3, 3, 3, 2, 3, 256, 165, 156, 111,,,, -7, 4, 3, 3, 3, 3, 2, 3, 384, 165, 156, 111,,,, -7, 4, 3, 3, 3, 3, 3, 1, 128, 165, 156, 111,,,, -7, 4, 3, 3, 3, 3, 3, 1, 256, 165, 156, 111,,,, -7, 4, 3, 3, 3, 3, 3, 1, 384, 165, 156, 111,,,, -7, 4, 3, 3, 3, 3, 3, 2, 128, 165, 156, 111,,,, -7, 4, 3, 3, 3, 3, 3, 2, 256, 165, 156, 111,,,, -7, 4, 3, 3, 3, 3, 3, 2, 384, 165, 156, 111,,,, -7, 4, 3, 3, 3, 3, 3, 3, 128, 165, 156, 111,,,, -7, 4, 3, 3, 3, 3, 3, 3, 256, 165, 156, 111,,,, -7, 4, 3, 3, 3, 3, 3, 3, 384, 165, 156, 111,,,, -7, 4, 3, 4, 1, 1, 1, 1, 128, 219, 219, 147,,,, -7, 4, 3, 4, 1, 1, 1, 1, 256, 219, 219, 147,,,, -7, 4, 3, 4, 1, 1, 1, 1, 384, 219, 219, 147,,,, -7, 4, 3, 4, 2, 2, 1, 1, 128, 219, 211, 147,,,, -7, 4, 3, 4, 2, 2, 1, 1, 256, 219, 211, 147,,,, -7, 4, 3, 4, 2, 2, 1, 1, 384, 219, 211, 147,,,, -7, 4, 3, 4, 2, 2, 1, 2, 128, 219, 211, 147,,,, -7, 4, 3, 4, 2, 2, 1, 2, 256, 219, 211, 147,,,, -7, 4, 3, 4, 2, 2, 1, 2, 384, 219, 211, 147,,,, -7, 4, 3, 4, 2, 2, 2, 1, 128, 219, 211, 147,,,, -7, 4, 3, 4, 2, 2, 2, 1, 256, 219, 211, 147,,,, -7, 4, 3, 4, 2, 2, 2, 1, 384, 219, 211, 147,,,, -7, 4, 3, 4, 2, 2, 2, 2, 128, 219, 211, 147,,,, -7, 4, 3, 4, 2, 2, 2, 2, 256, 219, 211, 147,,,, -7, 4, 3, 4, 2, 2, 2, 2, 384, 219, 211, 147,,,, -7, 4, 3, 4, 3, 3, 1, 1, 128, 219, 207, 147,,,, -7, 4, 3, 4, 3, 3, 1, 1, 256, 219, 207, 147,,,, -7, 4, 3, 4, 3, 3, 1, 1, 384, 219, 207, 147,,,, -7, 4, 3, 4, 3, 3, 1, 2, 128, 219, 207, 147,,,, -7, 4, 3, 4, 3, 3, 1, 2, 256, 219, 207, 147,,,, -7, 4, 3, 4, 3, 3, 1, 2, 384, 219, 207, 147,,,, -7, 4, 3, 4, 3, 3, 1, 3, 128, 219, 207, 147,,,, -7, 4, 3, 4, 3, 3, 1, 3, 256, 219, 207, 147,,,, -7, 4, 3, 4, 3, 3, 1, 3, 384, 219, 207, 147,,,, -7, 4, 3, 4, 3, 3, 2, 1, 128, 219, 207, 147,,,, -7, 4, 3, 4, 3, 3, 2, 1, 256, 219, 207, 147,,,, -7, 4, 3, 4, 3, 3, 2, 1, 384, 219, 207, 147,,,, -7, 4, 3, 4, 3, 3, 2, 2, 128, 219, 207, 147,,,, -7, 4, 3, 4, 3, 3, 2, 2, 256, 219, 207, 147,,,, -7, 4, 3, 4, 3, 3, 2, 2, 384, 219, 207, 147,,,, -7, 4, 3, 4, 3, 3, 2, 3, 128, 219, 207, 147,,,, -7, 4, 3, 4, 3, 3, 2, 3, 256, 219, 207, 147,,,, -7, 4, 3, 4, 3, 3, 2, 3, 384, 219, 207, 147,,,, -7, 4, 3, 4, 3, 3, 3, 1, 128, 219, 207, 147,,,, -7, 4, 3, 4, 3, 3, 3, 1, 256, 219, 207, 147,,,, -7, 4, 3, 4, 3, 3, 3, 1, 384, 219, 207, 147,,,, -7, 4, 3, 4, 3, 3, 3, 2, 128, 219, 207, 147,,,, -7, 4, 3, 4, 3, 3, 3, 2, 256, 219, 207, 147,,,, -7, 4, 3, 4, 3, 3, 3, 2, 384, 219, 207, 147,,,, -7, 4, 3, 4, 3, 3, 3, 3, 128, 219, 207, 147,,,, -7, 4, 3, 4, 3, 3, 3, 3, 256, 219, 207, 147,,,, -7, 4, 3, 4, 3, 3, 3, 3, 384, 219, 207, 147,,,, -7, 4, 4, 1, 1, 1, 1, 1, 128, 57, 57, 39,,,, -7, 4, 4, 1, 1, 1, 1, 1, 256, 57, 57, 39,,,, -7, 4, 4, 1, 1, 1, 1, 1, 384, 57, 57, 39,,,, -7, 4, 4, 1, 2, 2, 1, 1, 128, 57, 55, 39,,,, -7, 4, 4, 1, 2, 2, 1, 1, 256, 57, 55, 39,,,, -7, 4, 4, 1, 2, 2, 1, 1, 384, 57, 55, 39,,,, -7, 4, 4, 1, 2, 2, 1, 2, 128, 57, 55, 39,,,, -7, 4, 4, 1, 2, 2, 1, 2, 256, 57, 55, 39,,,, -7, 4, 4, 1, 2, 2, 1, 2, 384, 57, 55, 39,,,, -7, 4, 4, 1, 2, 2, 2, 1, 128, 57, 55, 39,,,, -7, 4, 4, 1, 2, 2, 2, 1, 256, 57, 55, 39,,,, -7, 4, 4, 1, 2, 2, 2, 1, 384, 57, 55, 39,,,, -7, 4, 4, 1, 2, 2, 2, 2, 128, 57, 55, 39,,,, -7, 4, 4, 1, 2, 2, 2, 2, 256, 57, 55, 39,,,, -7, 4, 4, 1, 2, 2, 2, 2, 384, 57, 55, 39,,,, -7, 4, 4, 1, 3, 3, 1, 1, 128, 57, 54, 39,,,, -7, 4, 4, 1, 3, 3, 1, 1, 256, 57, 54, 39,,,, -7, 4, 4, 1, 3, 3, 1, 1, 384, 57, 54, 39,,,, -7, 4, 4, 1, 3, 3, 1, 2, 128, 57, 54, 39,,,, -7, 4, 4, 1, 3, 3, 1, 2, 256, 57, 54, 39,,,, -7, 4, 4, 1, 3, 3, 1, 2, 384, 57, 54, 39,,,, -7, 4, 4, 1, 3, 3, 1, 3, 128, 57, 54, 39,,,, -7, 4, 4, 1, 3, 3, 1, 3, 256, 57, 54, 39,,,, -7, 4, 4, 1, 3, 3, 1, 3, 384, 57, 54, 39,,,, -7, 4, 4, 1, 3, 3, 2, 1, 128, 57, 54, 39,,,, -7, 4, 4, 1, 3, 3, 2, 1, 256, 57, 54, 39,,,, -7, 4, 4, 1, 3, 3, 2, 1, 384, 57, 54, 39,,,, -7, 4, 4, 1, 3, 3, 2, 2, 128, 57, 54, 39,,,, -7, 4, 4, 1, 3, 3, 2, 2, 256, 57, 54, 39,,,, -7, 4, 4, 1, 3, 3, 2, 2, 384, 57, 54, 39,,,, -7, 4, 4, 1, 3, 3, 2, 3, 128, 57, 54, 39,,,, -7, 4, 4, 1, 3, 3, 2, 3, 256, 57, 54, 39,,,, -7, 4, 4, 1, 3, 3, 2, 3, 384, 57, 54, 39,,,, -7, 4, 4, 1, 3, 3, 3, 1, 128, 57, 54, 39,,,, -7, 4, 4, 1, 3, 3, 3, 1, 256, 57, 54, 39,,,, -7, 4, 4, 1, 3, 3, 3, 1, 384, 57, 54, 39,,,, -7, 4, 4, 1, 3, 3, 3, 2, 128, 57, 54, 39,,,, -7, 4, 4, 1, 3, 3, 3, 2, 256, 57, 54, 39,,,, -7, 4, 4, 1, 3, 3, 3, 2, 384, 57, 54, 39,,,, -7, 4, 4, 1, 3, 3, 3, 3, 128, 57, 54, 39,,,, -7, 4, 4, 1, 3, 3, 3, 3, 256, 57, 54, 39,,,, -7, 4, 4, 1, 3, 3, 3, 3, 384, 57, 54, 39,,,, -7, 4, 4, 2, 1, 1, 1, 1, 128, 111, 111, 75,,,, -7, 4, 4, 2, 1, 1, 1, 1, 256, 111, 111, 75,,,, -7, 4, 4, 2, 1, 1, 1, 1, 384, 111, 111, 75,,,, -7, 4, 4, 2, 2, 2, 1, 1, 128, 111, 107, 75,,,, -7, 4, 4, 2, 2, 2, 1, 1, 256, 111, 107, 75,,,, -7, 4, 4, 2, 2, 2, 1, 1, 384, 111, 107, 75,,,, -7, 4, 4, 2, 2, 2, 1, 2, 128, 111, 107, 75,,,, -7, 4, 4, 2, 2, 2, 1, 2, 256, 111, 107, 75,,,, -7, 4, 4, 2, 2, 2, 1, 2, 384, 111, 107, 75,,,, -7, 4, 4, 2, 2, 2, 2, 1, 128, 111, 107, 75,,,, -7, 4, 4, 2, 2, 2, 2, 1, 256, 111, 107, 75,,,, -7, 4, 4, 2, 2, 2, 2, 1, 384, 111, 107, 75,,,, -7, 4, 4, 2, 2, 2, 2, 2, 128, 111, 107, 75,,,, -7, 4, 4, 2, 2, 2, 2, 2, 256, 111, 107, 75,,,, -7, 4, 4, 2, 2, 2, 2, 2, 384, 111, 107, 75,,,, -7, 4, 4, 2, 3, 3, 1, 1, 128, 111, 105, 75,,,, -7, 4, 4, 2, 3, 3, 1, 1, 256, 111, 105, 75,,,, -7, 4, 4, 2, 3, 3, 1, 1, 384, 111, 105, 75,,,, -7, 4, 4, 2, 3, 3, 1, 2, 128, 111, 105, 75,,,, -7, 4, 4, 2, 3, 3, 1, 2, 256, 111, 105, 75,,,, -7, 4, 4, 2, 3, 3, 1, 2, 384, 111, 105, 75,,,, -7, 4, 4, 2, 3, 3, 1, 3, 128, 111, 105, 75,,,, -7, 4, 4, 2, 3, 3, 1, 3, 256, 111, 105, 75,,,, -7, 4, 4, 2, 3, 3, 1, 3, 384, 111, 105, 75,,,, -7, 4, 4, 2, 3, 3, 2, 1, 128, 111, 105, 75,,,, -7, 4, 4, 2, 3, 3, 2, 1, 256, 111, 105, 75,,,, -7, 4, 4, 2, 3, 3, 2, 1, 384, 111, 105, 75,,,, -7, 4, 4, 2, 3, 3, 2, 2, 128, 111, 105, 75,,,, -7, 4, 4, 2, 3, 3, 2, 2, 256, 111, 105, 75,,,, -7, 4, 4, 2, 3, 3, 2, 2, 384, 111, 105, 75,,,, -7, 4, 4, 2, 3, 3, 2, 3, 128, 111, 105, 75,,,, -7, 4, 4, 2, 3, 3, 2, 3, 256, 111, 105, 75,,,, -7, 4, 4, 2, 3, 3, 2, 3, 384, 111, 105, 75,,,, -7, 4, 4, 2, 3, 3, 3, 1, 128, 111, 105, 75,,,, -7, 4, 4, 2, 3, 3, 3, 1, 256, 111, 105, 75,,,, -7, 4, 4, 2, 3, 3, 3, 1, 384, 111, 105, 75,,,, -7, 4, 4, 2, 3, 3, 3, 2, 128, 111, 105, 75,,,, -7, 4, 4, 2, 3, 3, 3, 2, 256, 111, 105, 75,,,, -7, 4, 4, 2, 3, 3, 3, 2, 384, 111, 105, 75,,,, -7, 4, 4, 2, 3, 3, 3, 3, 128, 111, 105, 75,,,, -7, 4, 4, 2, 3, 3, 3, 3, 256, 111, 105, 75,,,, -7, 4, 4, 2, 3, 3, 3, 3, 384, 111, 105, 75,,,, -7, 4, 4, 3, 1, 1, 1, 1, 128, 165, 165, 111,,,, -7, 4, 4, 3, 1, 1, 1, 1, 256, 165, 165, 111,,,, -7, 4, 4, 3, 1, 1, 1, 1, 384, 165, 165, 111,,,, -7, 4, 4, 3, 2, 2, 1, 1, 128, 165, 159, 111,,,, -7, 4, 4, 3, 2, 2, 1, 1, 256, 165, 159, 111,,,, -7, 4, 4, 3, 2, 2, 1, 1, 384, 165, 159, 111,,,, -7, 4, 4, 3, 2, 2, 1, 2, 128, 165, 159, 111,,,, -7, 4, 4, 3, 2, 2, 1, 2, 256, 165, 159, 111,,,, -7, 4, 4, 3, 2, 2, 1, 2, 384, 165, 159, 111,,,, -7, 4, 4, 3, 2, 2, 2, 1, 128, 165, 159, 111,,,, -7, 4, 4, 3, 2, 2, 2, 1, 256, 165, 159, 111,,,, -7, 4, 4, 3, 2, 2, 2, 1, 384, 165, 159, 111,,,, -7, 4, 4, 3, 2, 2, 2, 2, 128, 165, 159, 111,,,, -7, 4, 4, 3, 2, 2, 2, 2, 256, 165, 159, 111,,,, -7, 4, 4, 3, 2, 2, 2, 2, 384, 165, 159, 111,,,, -7, 4, 4, 3, 3, 3, 1, 1, 128, 165, 156, 111,,,, -7, 4, 4, 3, 3, 3, 1, 1, 256, 165, 156, 111,,,, -7, 4, 4, 3, 3, 3, 1, 1, 384, 165, 156, 111,,,, -7, 4, 4, 3, 3, 3, 1, 2, 128, 165, 156, 111,,,, -7, 4, 4, 3, 3, 3, 1, 2, 256, 165, 156, 111,,,, -7, 4, 4, 3, 3, 3, 1, 2, 384, 165, 156, 111,,,, -7, 4, 4, 3, 3, 3, 1, 3, 128, 165, 156, 111,,,, -7, 4, 4, 3, 3, 3, 1, 3, 256, 165, 156, 111,,,, -7, 4, 4, 3, 3, 3, 1, 3, 384, 165, 156, 111,,,, -7, 4, 4, 3, 3, 3, 2, 1, 128, 165, 156, 111,,,, -7, 4, 4, 3, 3, 3, 2, 1, 256, 165, 156, 111,,,, -7, 4, 4, 3, 3, 3, 2, 1, 384, 165, 156, 111,,,, -7, 4, 4, 3, 3, 3, 2, 2, 128, 165, 156, 111,,,, -7, 4, 4, 3, 3, 3, 2, 2, 256, 165, 156, 111,,,, -7, 4, 4, 3, 3, 3, 2, 2, 384, 165, 156, 111,,,, -7, 4, 4, 3, 3, 3, 2, 3, 128, 165, 156, 111,,,, -7, 4, 4, 3, 3, 3, 2, 3, 256, 165, 156, 111,,,, -7, 4, 4, 3, 3, 3, 2, 3, 384, 165, 156, 111,,,, -7, 4, 4, 3, 3, 3, 3, 1, 128, 165, 156, 111,,,, -7, 4, 4, 3, 3, 3, 3, 1, 256, 165, 156, 111,,,, -7, 4, 4, 3, 3, 3, 3, 1, 384, 165, 156, 111,,,, -7, 4, 4, 3, 3, 3, 3, 2, 128, 165, 156, 111,,,, -7, 4, 4, 3, 3, 3, 3, 2, 256, 165, 156, 111,,,, -7, 4, 4, 3, 3, 3, 3, 2, 384, 165, 156, 111,,,, -7, 4, 4, 3, 3, 3, 3, 3, 128, 165, 156, 111,,,, -7, 4, 4, 3, 3, 3, 3, 3, 256, 165, 156, 111,,,, -7, 4, 4, 3, 3, 3, 3, 3, 384, 165, 156, 111,,,, -7, 4, 4, 4, 1, 1, 1, 1, 128, 219, 219, 147,,,, -7, 4, 4, 4, 1, 1, 1, 1, 256, 219, 219, 147,,,, -7, 4, 4, 4, 1, 1, 1, 1, 384, 219, 219, 147,,,, -7, 4, 4, 4, 2, 2, 1, 1, 128, 219, 211, 147,,,, -7, 4, 4, 4, 2, 2, 1, 1, 256, 219, 211, 147,,,, -7, 4, 4, 4, 2, 2, 1, 1, 384, 219, 211, 147,,,, -7, 4, 4, 4, 2, 2, 1, 2, 128, 219, 211, 147,,,, -7, 4, 4, 4, 2, 2, 1, 2, 256, 219, 211, 147,,,, -7, 4, 4, 4, 2, 2, 1, 2, 384, 219, 211, 147,,,, -7, 4, 4, 4, 2, 2, 2, 1, 128, 219, 211, 147,,,, -7, 4, 4, 4, 2, 2, 2, 1, 256, 219, 211, 147,,,, -7, 4, 4, 4, 2, 2, 2, 1, 384, 219, 211, 147,,,, -7, 4, 4, 4, 2, 2, 2, 2, 128, 219, 211, 147,,,, -7, 4, 4, 4, 2, 2, 2, 2, 256, 219, 211, 147,,,, -7, 4, 4, 4, 2, 2, 2, 2, 384, 219, 211, 147,,,, -7, 4, 4, 4, 3, 3, 1, 1, 128, 219, 207, 147,,,, -7, 4, 4, 4, 3, 3, 1, 1, 256, 219, 207, 147,,,, -7, 4, 4, 4, 3, 3, 1, 1, 384, 219, 207, 147,,,, -7, 4, 4, 4, 3, 3, 1, 2, 128, 219, 207, 147,,,, -7, 4, 4, 4, 3, 3, 1, 2, 256, 219, 207, 147,,,, -7, 4, 4, 4, 3, 3, 1, 2, 384, 219, 207, 147,,,, -7, 4, 4, 4, 3, 3, 1, 3, 128, 219, 207, 147,,,, -7, 4, 4, 4, 3, 3, 1, 3, 256, 219, 207, 147,,,, -7, 4, 4, 4, 3, 3, 1, 3, 384, 219, 207, 147,,,, -7, 4, 4, 4, 3, 3, 2, 1, 128, 219, 207, 147,,,, -7, 4, 4, 4, 3, 3, 2, 1, 256, 219, 207, 147,,,, -7, 4, 4, 4, 3, 3, 2, 1, 384, 219, 207, 147,,,, -7, 4, 4, 4, 3, 3, 2, 2, 128, 219, 207, 147,,,, -7, 4, 4, 4, 3, 3, 2, 2, 256, 219, 207, 147,,,, -7, 4, 4, 4, 3, 3, 2, 2, 384, 219, 207, 147,,,, -7, 4, 4, 4, 3, 3, 2, 3, 128, 219, 207, 147,,,, -7, 4, 4, 4, 3, 3, 2, 3, 256, 219, 207, 147,,,, -7, 4, 4, 4, 3, 3, 2, 3, 384, 219, 207, 147,,,, -7, 4, 4, 4, 3, 3, 3, 1, 128, 219, 207, 147,,,, -7, 4, 4, 4, 3, 3, 3, 1, 256, 219, 207, 147,,,, -7, 4, 4, 4, 3, 3, 3, 1, 384, 219, 207, 147,,,, -7, 4, 4, 4, 3, 3, 3, 2, 128, 219, 207, 147,,,, -7, 4, 4, 4, 3, 3, 3, 2, 256, 219, 207, 147,,,, -7, 4, 4, 4, 3, 3, 3, 2, 384, 219, 207, 147,,,, -7, 4, 4, 4, 3, 3, 3, 3, 128, 219, 207, 147,,,, -7, 4, 4, 4, 3, 3, 3, 3, 256, 219, 207, 147,,,, -7, 4, 4, 4, 3, 3, 3, 3, 384, 219, 207, 147,,,, -7, 4, 5, 1, 1, 1, 1, 1, 128, 57, 57, 39,,,, -7, 4, 5, 1, 1, 1, 1, 1, 256, 57, 57, 39,,,, -7, 4, 5, 1, 1, 1, 1, 1, 384, 57, 57, 39,,,, -7, 4, 5, 1, 2, 2, 1, 1, 128, 57, 55, 39,,,, -7, 4, 5, 1, 2, 2, 1, 1, 256, 57, 55, 39,,,, -7, 4, 5, 1, 2, 2, 1, 1, 384, 57, 55, 39,,,, -7, 4, 5, 1, 2, 2, 1, 2, 128, 57, 55, 39,,,, -7, 4, 5, 1, 2, 2, 1, 2, 256, 57, 55, 39,,,, -7, 4, 5, 1, 2, 2, 1, 2, 384, 57, 55, 39,,,, -7, 4, 5, 1, 2, 2, 2, 1, 128, 57, 55, 39,,,, -7, 4, 5, 1, 2, 2, 2, 1, 256, 57, 55, 39,,,, -7, 4, 5, 1, 2, 2, 2, 1, 384, 57, 55, 39,,,, -7, 4, 5, 1, 2, 2, 2, 2, 128, 57, 55, 39,,,, -7, 4, 5, 1, 2, 2, 2, 2, 256, 57, 55, 39,,,, -7, 4, 5, 1, 2, 2, 2, 2, 384, 57, 55, 39,,,, -7, 4, 5, 1, 3, 3, 1, 1, 128, 57, 54, 39,,,, -7, 4, 5, 1, 3, 3, 1, 1, 256, 57, 54, 39,,,, -7, 4, 5, 1, 3, 3, 1, 1, 384, 57, 54, 39,,,, -7, 4, 5, 1, 3, 3, 1, 2, 128, 57, 54, 39,,,, -7, 4, 5, 1, 3, 3, 1, 2, 256, 57, 54, 39,,,, -7, 4, 5, 1, 3, 3, 1, 2, 384, 57, 54, 39,,,, -7, 4, 5, 1, 3, 3, 1, 3, 128, 57, 54, 39,,,, -7, 4, 5, 1, 3, 3, 1, 3, 256, 57, 54, 39,,,, -7, 4, 5, 1, 3, 3, 1, 3, 384, 57, 54, 39,,,, -7, 4, 5, 1, 3, 3, 2, 1, 128, 57, 54, 39,,,, -7, 4, 5, 1, 3, 3, 2, 1, 256, 57, 54, 39,,,, -7, 4, 5, 1, 3, 3, 2, 1, 384, 57, 54, 39,,,, -7, 4, 5, 1, 3, 3, 2, 2, 128, 57, 54, 39,,,, -7, 4, 5, 1, 3, 3, 2, 2, 256, 57, 54, 39,,,, -7, 4, 5, 1, 3, 3, 2, 2, 384, 57, 54, 39,,,, -7, 4, 5, 1, 3, 3, 2, 3, 128, 57, 54, 39,,,, -7, 4, 5, 1, 3, 3, 2, 3, 256, 57, 54, 39,,,, -7, 4, 5, 1, 3, 3, 2, 3, 384, 57, 54, 39,,,, -7, 4, 5, 1, 3, 3, 3, 1, 128, 57, 54, 39,,,, -7, 4, 5, 1, 3, 3, 3, 1, 256, 57, 54, 39,,,, -7, 4, 5, 1, 3, 3, 3, 1, 384, 57, 54, 39,,,, -7, 4, 5, 1, 3, 3, 3, 2, 128, 57, 54, 39,,,, -7, 4, 5, 1, 3, 3, 3, 2, 256, 57, 54, 39,,,, -7, 4, 5, 1, 3, 3, 3, 2, 384, 57, 54, 39,,,, -7, 4, 5, 1, 3, 3, 3, 3, 128, 57, 54, 39,,,, -7, 4, 5, 1, 3, 3, 3, 3, 256, 57, 54, 39,,,, -7, 4, 5, 1, 3, 3, 3, 3, 384, 57, 54, 39,,,, -7, 4, 5, 2, 1, 1, 1, 1, 128, 111, 111, 75,,,, -7, 4, 5, 2, 1, 1, 1, 1, 256, 111, 111, 75,,,, -7, 4, 5, 2, 1, 1, 1, 1, 384, 111, 111, 75,,,, -7, 4, 5, 2, 2, 2, 1, 1, 128, 111, 107, 75,,,, -7, 4, 5, 2, 2, 2, 1, 1, 256, 111, 107, 75,,,, -7, 4, 5, 2, 2, 2, 1, 1, 384, 111, 107, 75,,,, -7, 4, 5, 2, 2, 2, 1, 2, 128, 111, 107, 75,,,, -7, 4, 5, 2, 2, 2, 1, 2, 256, 111, 107, 75,,,, -7, 4, 5, 2, 2, 2, 1, 2, 384, 111, 107, 75,,,, -7, 4, 5, 2, 2, 2, 2, 1, 128, 111, 107, 75,,,, -7, 4, 5, 2, 2, 2, 2, 1, 256, 111, 107, 75,,,, -7, 4, 5, 2, 2, 2, 2, 1, 384, 111, 107, 75,,,, -7, 4, 5, 2, 2, 2, 2, 2, 128, 111, 107, 75,,,, -7, 4, 5, 2, 2, 2, 2, 2, 256, 111, 107, 75,,,, -7, 4, 5, 2, 2, 2, 2, 2, 384, 111, 107, 75,,,, -7, 4, 5, 2, 3, 3, 1, 1, 128, 111, 105, 75,,,, -7, 4, 5, 2, 3, 3, 1, 1, 256, 111, 105, 75,,,, -7, 4, 5, 2, 3, 3, 1, 1, 384, 111, 105, 75,,,, -7, 4, 5, 2, 3, 3, 1, 2, 128, 111, 105, 75,,,, -7, 4, 5, 2, 3, 3, 1, 2, 256, 111, 105, 75,,,, -7, 4, 5, 2, 3, 3, 1, 2, 384, 111, 105, 75,,,, -7, 4, 5, 2, 3, 3, 1, 3, 128, 111, 105, 75,,,, -7, 4, 5, 2, 3, 3, 1, 3, 256, 111, 105, 75,,,, -7, 4, 5, 2, 3, 3, 1, 3, 384, 111, 105, 75,,,, -7, 4, 5, 2, 3, 3, 2, 1, 128, 111, 105, 75,,,, -7, 4, 5, 2, 3, 3, 2, 1, 256, 111, 105, 75,,,, -7, 4, 5, 2, 3, 3, 2, 1, 384, 111, 105, 75,,,, -7, 4, 5, 2, 3, 3, 2, 2, 128, 111, 105, 75,,,, -7, 4, 5, 2, 3, 3, 2, 2, 256, 111, 105, 75,,,, -7, 4, 5, 2, 3, 3, 2, 2, 384, 111, 105, 75,,,, -7, 4, 5, 2, 3, 3, 2, 3, 128, 111, 105, 75,,,, -7, 4, 5, 2, 3, 3, 2, 3, 256, 111, 105, 75,,,, -7, 4, 5, 2, 3, 3, 2, 3, 384, 111, 105, 75,,,, -7, 4, 5, 2, 3, 3, 3, 1, 128, 111, 105, 75,,,, -7, 4, 5, 2, 3, 3, 3, 1, 256, 111, 105, 75,,,, -7, 4, 5, 2, 3, 3, 3, 1, 384, 111, 105, 75,,,, -7, 4, 5, 2, 3, 3, 3, 2, 128, 111, 105, 75,,,, -7, 4, 5, 2, 3, 3, 3, 2, 256, 111, 105, 75,,,, -7, 4, 5, 2, 3, 3, 3, 2, 384, 111, 105, 75,,,, -7, 4, 5, 2, 3, 3, 3, 3, 128, 111, 105, 75,,,, -7, 4, 5, 2, 3, 3, 3, 3, 256, 111, 105, 75,,,, -7, 4, 5, 2, 3, 3, 3, 3, 384, 111, 105, 75,,,, -7, 4, 5, 3, 1, 1, 1, 1, 128, 165, 165, 111,,,, -7, 4, 5, 3, 1, 1, 1, 1, 256, 165, 165, 111,,,, -7, 4, 5, 3, 1, 1, 1, 1, 384, 165, 165, 111,,,, -7, 4, 5, 3, 2, 2, 1, 1, 128, 165, 159, 111,,,, -7, 4, 5, 3, 2, 2, 1, 1, 256, 165, 159, 111,,,, -7, 4, 5, 3, 2, 2, 1, 1, 384, 165, 159, 111,,,, -7, 4, 5, 3, 2, 2, 1, 2, 128, 165, 159, 111,,,, -7, 4, 5, 3, 2, 2, 1, 2, 256, 165, 159, 111,,,, -7, 4, 5, 3, 2, 2, 1, 2, 384, 165, 159, 111,,,, -7, 4, 5, 3, 2, 2, 2, 1, 128, 165, 159, 111,,,, -7, 4, 5, 3, 2, 2, 2, 1, 256, 165, 159, 111,,,, -7, 4, 5, 3, 2, 2, 2, 1, 384, 165, 159, 111,,,, -7, 4, 5, 3, 2, 2, 2, 2, 128, 165, 159, 111,,,, -7, 4, 5, 3, 2, 2, 2, 2, 256, 165, 159, 111,,,, -7, 4, 5, 3, 2, 2, 2, 2, 384, 165, 159, 111,,,, -7, 4, 5, 3, 3, 3, 1, 1, 128, 165, 156, 111,,,, -7, 4, 5, 3, 3, 3, 1, 1, 256, 165, 156, 111,,,, -7, 4, 5, 3, 3, 3, 1, 1, 384, 165, 156, 111,,,, -7, 4, 5, 3, 3, 3, 1, 2, 128, 165, 156, 111,,,, -7, 4, 5, 3, 3, 3, 1, 2, 256, 165, 156, 111,,,, -7, 4, 5, 3, 3, 3, 1, 2, 384, 165, 156, 111,,,, -7, 4, 5, 3, 3, 3, 1, 3, 128, 165, 156, 111,,,, -7, 4, 5, 3, 3, 3, 1, 3, 256, 165, 156, 111,,,, -7, 4, 5, 3, 3, 3, 1, 3, 384, 165, 156, 111,,,, -7, 4, 5, 3, 3, 3, 2, 1, 128, 165, 156, 111,,,, -7, 4, 5, 3, 3, 3, 2, 1, 256, 165, 156, 111,,,, -7, 4, 5, 3, 3, 3, 2, 1, 384, 165, 156, 111,,,, -7, 4, 5, 3, 3, 3, 2, 2, 128, 165, 156, 111,,,, -7, 4, 5, 3, 3, 3, 2, 2, 256, 165, 156, 111,,,, -7, 4, 5, 3, 3, 3, 2, 2, 384, 165, 156, 111,,,, -7, 4, 5, 3, 3, 3, 2, 3, 128, 165, 156, 111,,,, -7, 4, 5, 3, 3, 3, 2, 3, 256, 165, 156, 111,,,, -7, 4, 5, 3, 3, 3, 2, 3, 384, 165, 156, 111,,,, -7, 4, 5, 3, 3, 3, 3, 1, 128, 165, 156, 111,,,, -7, 4, 5, 3, 3, 3, 3, 1, 256, 165, 156, 111,,,, -7, 4, 5, 3, 3, 3, 3, 1, 384, 165, 156, 111,,,, -7, 4, 5, 3, 3, 3, 3, 2, 128, 165, 156, 111,,,, -7, 4, 5, 3, 3, 3, 3, 2, 256, 165, 156, 111,,,, -7, 4, 5, 3, 3, 3, 3, 2, 384, 165, 156, 111,,,, -7, 4, 5, 3, 3, 3, 3, 3, 128, 165, 156, 111,,,, -7, 4, 5, 3, 3, 3, 3, 3, 256, 165, 156, 111,,,, -7, 4, 5, 3, 3, 3, 3, 3, 384, 165, 156, 111,,,, -7, 4, 5, 4, 1, 1, 1, 1, 128, 219, 219, 147,,,, -7, 4, 5, 4, 1, 1, 1, 1, 256, 219, 219, 147,,,, -7, 4, 5, 4, 1, 1, 1, 1, 384, 219, 219, 147,,,, -7, 4, 5, 4, 2, 2, 1, 1, 128, 219, 211, 147,,,, -7, 4, 5, 4, 2, 2, 1, 1, 256, 219, 211, 147,,,, -7, 4, 5, 4, 2, 2, 1, 1, 384, 219, 211, 147,,,, -7, 4, 5, 4, 2, 2, 1, 2, 128, 219, 211, 147,,,, -7, 4, 5, 4, 2, 2, 1, 2, 256, 219, 211, 147,,,, -7, 4, 5, 4, 2, 2, 1, 2, 384, 219, 211, 147,,,, -7, 4, 5, 4, 2, 2, 2, 1, 128, 219, 211, 147,,,, -7, 4, 5, 4, 2, 2, 2, 1, 256, 219, 211, 147,,,, -7, 4, 5, 4, 2, 2, 2, 1, 384, 219, 211, 147,,,, -7, 4, 5, 4, 2, 2, 2, 2, 128, 219, 211, 147,,,, -7, 4, 5, 4, 2, 2, 2, 2, 256, 219, 211, 147,,,, -7, 4, 5, 4, 2, 2, 2, 2, 384, 219, 211, 147,,,, -7, 4, 5, 4, 3, 3, 1, 1, 128, 219, 207, 147,,,, -7, 4, 5, 4, 3, 3, 1, 1, 256, 219, 207, 147,,,, -7, 4, 5, 4, 3, 3, 1, 1, 384, 219, 207, 147,,,, -7, 4, 5, 4, 3, 3, 1, 2, 128, 219, 207, 147,,,, -7, 4, 5, 4, 3, 3, 1, 2, 256, 219, 207, 147,,,, -7, 4, 5, 4, 3, 3, 1, 2, 384, 219, 207, 147,,,, -7, 4, 5, 4, 3, 3, 1, 3, 128, 219, 207, 147,,,, -7, 4, 5, 4, 3, 3, 1, 3, 256, 219, 207, 147,,,, -7, 4, 5, 4, 3, 3, 1, 3, 384, 219, 207, 147,,,, -7, 4, 5, 4, 3, 3, 2, 1, 128, 219, 207, 147,,,, -7, 4, 5, 4, 3, 3, 2, 1, 256, 219, 207, 147,,,, -7, 4, 5, 4, 3, 3, 2, 1, 384, 219, 207, 147,,,, -7, 4, 5, 4, 3, 3, 2, 2, 128, 219, 207, 147,,,, -7, 4, 5, 4, 3, 3, 2, 2, 256, 219, 207, 147,,,, -7, 4, 5, 4, 3, 3, 2, 2, 384, 219, 207, 147,,,, -7, 4, 5, 4, 3, 3, 2, 3, 128, 219, 207, 147,,,, -7, 4, 5, 4, 3, 3, 2, 3, 256, 219, 207, 147,,,, -7, 4, 5, 4, 3, 3, 2, 3, 384, 219, 207, 147,,,, -7, 4, 5, 4, 3, 3, 3, 1, 128, 219, 207, 147,,,, -7, 4, 5, 4, 3, 3, 3, 1, 256, 219, 207, 147,,,, -7, 4, 5, 4, 3, 3, 3, 1, 384, 219, 207, 147,,,, -7, 4, 5, 4, 3, 3, 3, 2, 128, 219, 207, 147,,,, -7, 4, 5, 4, 3, 3, 3, 2, 256, 219, 207, 147,,,, -7, 4, 5, 4, 3, 3, 3, 2, 384, 219, 207, 147,,,, -7, 4, 5, 4, 3, 3, 3, 3, 128, 219, 207, 147,,,, -7, 4, 5, 4, 3, 3, 3, 3, 256, 219, 207, 147,,,, -7, 4, 5, 4, 3, 3, 3, 3, 384, 219, 207, 147,,,, -7, 4, 6, 1, 1, 1, 1, 1, 128, 57, 57, 39,,,, -7, 4, 6, 1, 1, 1, 1, 1, 256, 57, 57, 39,,,, -7, 4, 6, 1, 1, 1, 1, 1, 384, 57, 57, 39,,,, -7, 4, 6, 1, 2, 2, 1, 1, 128, 57, 55, 39,,,, -7, 4, 6, 1, 2, 2, 1, 1, 256, 57, 55, 39,,,, -7, 4, 6, 1, 2, 2, 1, 1, 384, 57, 55, 39,,,, -7, 4, 6, 1, 2, 2, 1, 2, 128, 57, 55, 39,,,, -7, 4, 6, 1, 2, 2, 1, 2, 256, 57, 55, 39,,,, -7, 4, 6, 1, 2, 2, 1, 2, 384, 57, 55, 39,,,, -7, 4, 6, 1, 2, 2, 2, 1, 128, 57, 55, 39,,,, -7, 4, 6, 1, 2, 2, 2, 1, 256, 57, 55, 39,,,, -7, 4, 6, 1, 2, 2, 2, 1, 384, 57, 55, 39,,,, -7, 4, 6, 1, 2, 2, 2, 2, 128, 57, 55, 39,,,, -7, 4, 6, 1, 2, 2, 2, 2, 256, 57, 55, 39,,,, -7, 4, 6, 1, 2, 2, 2, 2, 384, 57, 55, 39,,,, -7, 4, 6, 1, 3, 3, 1, 1, 128, 57, 54, 39,,,, -7, 4, 6, 1, 3, 3, 1, 1, 256, 57, 54, 39,,,, -7, 4, 6, 1, 3, 3, 1, 1, 384, 57, 54, 39,,,, -7, 4, 6, 1, 3, 3, 1, 2, 128, 57, 54, 39,,,, -7, 4, 6, 1, 3, 3, 1, 2, 256, 57, 54, 39,,,, -7, 4, 6, 1, 3, 3, 1, 2, 384, 57, 54, 39,,,, -7, 4, 6, 1, 3, 3, 1, 3, 128, 57, 54, 39,,,, -7, 4, 6, 1, 3, 3, 1, 3, 256, 57, 54, 39,,,, -7, 4, 6, 1, 3, 3, 1, 3, 384, 57, 54, 39,,,, -7, 4, 6, 1, 3, 3, 2, 1, 128, 57, 54, 39,,,, -7, 4, 6, 1, 3, 3, 2, 1, 256, 57, 54, 39,,,, -7, 4, 6, 1, 3, 3, 2, 1, 384, 57, 54, 39,,,, -7, 4, 6, 1, 3, 3, 2, 2, 128, 57, 54, 39,,,, -7, 4, 6, 1, 3, 3, 2, 2, 256, 57, 54, 39,,,, -7, 4, 6, 1, 3, 3, 2, 2, 384, 57, 54, 39,,,, -7, 4, 6, 1, 3, 3, 2, 3, 128, 57, 54, 39,,,, -7, 4, 6, 1, 3, 3, 2, 3, 256, 57, 54, 39,,,, -7, 4, 6, 1, 3, 3, 2, 3, 384, 57, 54, 39,,,, -7, 4, 6, 1, 3, 3, 3, 1, 128, 57, 54, 39,,,, -7, 4, 6, 1, 3, 3, 3, 1, 256, 57, 54, 39,,,, -7, 4, 6, 1, 3, 3, 3, 1, 384, 57, 54, 39,,,, -7, 4, 6, 1, 3, 3, 3, 2, 128, 57, 54, 39,,,, -7, 4, 6, 1, 3, 3, 3, 2, 256, 57, 54, 39,,,, -7, 4, 6, 1, 3, 3, 3, 2, 384, 57, 54, 39,,,, -7, 4, 6, 1, 3, 3, 3, 3, 128, 57, 54, 39,,,, -7, 4, 6, 1, 3, 3, 3, 3, 256, 57, 54, 39,,,, -7, 4, 6, 1, 3, 3, 3, 3, 384, 57, 54, 39,,,, -7, 4, 6, 2, 1, 1, 1, 1, 128, 111, 111, 75,,,, -7, 4, 6, 2, 1, 1, 1, 1, 256, 111, 111, 75,,,, -7, 4, 6, 2, 1, 1, 1, 1, 384, 111, 111, 75,,,, -7, 4, 6, 2, 2, 2, 1, 1, 128, 111, 107, 75,,,, -7, 4, 6, 2, 2, 2, 1, 1, 256, 111, 107, 75,,,, -7, 4, 6, 2, 2, 2, 1, 1, 384, 111, 107, 75,,,, -7, 4, 6, 2, 2, 2, 1, 2, 128, 111, 107, 75,,,, -7, 4, 6, 2, 2, 2, 1, 2, 256, 111, 107, 75,,,, -7, 4, 6, 2, 2, 2, 1, 2, 384, 111, 107, 75,,,, -7, 4, 6, 2, 2, 2, 2, 1, 128, 111, 107, 75,,,, -7, 4, 6, 2, 2, 2, 2, 1, 256, 111, 107, 75,,,, -7, 4, 6, 2, 2, 2, 2, 1, 384, 111, 107, 75,,,, -7, 4, 6, 2, 2, 2, 2, 2, 128, 111, 107, 75,,,, -7, 4, 6, 2, 2, 2, 2, 2, 256, 111, 107, 75,,,, -7, 4, 6, 2, 2, 2, 2, 2, 384, 111, 107, 75,,,, -7, 4, 6, 2, 3, 3, 1, 1, 128, 111, 105, 75,,,, -7, 4, 6, 2, 3, 3, 1, 1, 256, 111, 105, 75,,,, -7, 4, 6, 2, 3, 3, 1, 1, 384, 111, 105, 75,,,, -7, 4, 6, 2, 3, 3, 1, 2, 128, 111, 105, 75,,,, -7, 4, 6, 2, 3, 3, 1, 2, 256, 111, 105, 75,,,, -7, 4, 6, 2, 3, 3, 1, 2, 384, 111, 105, 75,,,, -7, 4, 6, 2, 3, 3, 1, 3, 128, 111, 105, 75,,,, -7, 4, 6, 2, 3, 3, 1, 3, 256, 111, 105, 75,,,, -7, 4, 6, 2, 3, 3, 1, 3, 384, 111, 105, 75,,,, -7, 4, 6, 2, 3, 3, 2, 1, 128, 111, 105, 75,,,, -7, 4, 6, 2, 3, 3, 2, 1, 256, 111, 105, 75,,,, -7, 4, 6, 2, 3, 3, 2, 1, 384, 111, 105, 75,,,, -7, 4, 6, 2, 3, 3, 2, 2, 128, 111, 105, 75,,,, -7, 4, 6, 2, 3, 3, 2, 2, 256, 111, 105, 75,,,, -7, 4, 6, 2, 3, 3, 2, 2, 384, 111, 105, 75,,,, -7, 4, 6, 2, 3, 3, 2, 3, 128, 111, 105, 75,,,, -7, 4, 6, 2, 3, 3, 2, 3, 256, 111, 105, 75,,,, -7, 4, 6, 2, 3, 3, 2, 3, 384, 111, 105, 75,,,, -7, 4, 6, 2, 3, 3, 3, 1, 128, 111, 105, 75,,,, -7, 4, 6, 2, 3, 3, 3, 1, 256, 111, 105, 75,,,, -7, 4, 6, 2, 3, 3, 3, 1, 384, 111, 105, 75,,,, -7, 4, 6, 2, 3, 3, 3, 2, 128, 111, 105, 75,,,, -7, 4, 6, 2, 3, 3, 3, 2, 256, 111, 105, 75,,,, -7, 4, 6, 2, 3, 3, 3, 2, 384, 111, 105, 75,,,, -7, 4, 6, 2, 3, 3, 3, 3, 128, 111, 105, 75,,,, -7, 4, 6, 2, 3, 3, 3, 3, 256, 111, 105, 75,,,, -7, 4, 6, 2, 3, 3, 3, 3, 384, 111, 105, 75,,,, -7, 4, 6, 3, 1, 1, 1, 1, 128, 165, 165, 111,,,, -7, 4, 6, 3, 1, 1, 1, 1, 256, 165, 165, 111,,,, -7, 4, 6, 3, 1, 1, 1, 1, 384, 165, 165, 111,,,, -7, 4, 6, 3, 2, 2, 1, 1, 128, 165, 159, 111,,,, -7, 4, 6, 3, 2, 2, 1, 1, 256, 165, 159, 111,,,, -7, 4, 6, 3, 2, 2, 1, 1, 384, 165, 159, 111,,,, -7, 4, 6, 3, 2, 2, 1, 2, 128, 165, 159, 111,,,, -7, 4, 6, 3, 2, 2, 1, 2, 256, 165, 159, 111,,,, -7, 4, 6, 3, 2, 2, 1, 2, 384, 165, 159, 111,,,, -7, 4, 6, 3, 2, 2, 2, 1, 128, 165, 159, 111,,,, -7, 4, 6, 3, 2, 2, 2, 1, 256, 165, 159, 111,,,, -7, 4, 6, 3, 2, 2, 2, 1, 384, 165, 159, 111,,,, -7, 4, 6, 3, 2, 2, 2, 2, 128, 165, 159, 111,,,, -7, 4, 6, 3, 2, 2, 2, 2, 256, 165, 159, 111,,,, -7, 4, 6, 3, 2, 2, 2, 2, 384, 165, 159, 111,,,, -7, 4, 6, 3, 3, 3, 1, 1, 128, 165, 156, 111,,,, -7, 4, 6, 3, 3, 3, 1, 1, 256, 165, 156, 111,,,, -7, 4, 6, 3, 3, 3, 1, 1, 384, 165, 156, 111,,,, -7, 4, 6, 3, 3, 3, 1, 2, 128, 165, 156, 111,,,, -7, 4, 6, 3, 3, 3, 1, 2, 256, 165, 156, 111,,,, -7, 4, 6, 3, 3, 3, 1, 2, 384, 165, 156, 111,,,, -7, 4, 6, 3, 3, 3, 1, 3, 128, 165, 156, 111,,,, -7, 4, 6, 3, 3, 3, 1, 3, 256, 165, 156, 111,,,, -7, 4, 6, 3, 3, 3, 1, 3, 384, 165, 156, 111,,,, -7, 4, 6, 3, 3, 3, 2, 1, 128, 165, 156, 111,,,, -7, 4, 6, 3, 3, 3, 2, 1, 256, 165, 156, 111,,,, -7, 4, 6, 3, 3, 3, 2, 1, 384, 165, 156, 111,,,, -7, 4, 6, 3, 3, 3, 2, 2, 128, 165, 156, 111,,,, -7, 4, 6, 3, 3, 3, 2, 2, 256, 165, 156, 111,,,, -7, 4, 6, 3, 3, 3, 2, 2, 384, 165, 156, 111,,,, -7, 4, 6, 3, 3, 3, 2, 3, 128, 165, 156, 111,,,, -7, 4, 6, 3, 3, 3, 2, 3, 256, 165, 156, 111,,,, -7, 4, 6, 3, 3, 3, 2, 3, 384, 165, 156, 111,,,, -7, 4, 6, 3, 3, 3, 3, 1, 128, 165, 156, 111,,,, -7, 4, 6, 3, 3, 3, 3, 1, 256, 165, 156, 111,,,, -7, 4, 6, 3, 3, 3, 3, 1, 384, 165, 156, 111,,,, -7, 4, 6, 3, 3, 3, 3, 2, 128, 165, 156, 111,,,, -7, 4, 6, 3, 3, 3, 3, 2, 256, 165, 156, 111,,,, -7, 4, 6, 3, 3, 3, 3, 2, 384, 165, 156, 111,,,, -7, 4, 6, 3, 3, 3, 3, 3, 128, 165, 156, 111,,,, -7, 4, 6, 3, 3, 3, 3, 3, 256, 165, 156, 111,,,, -7, 4, 6, 3, 3, 3, 3, 3, 384, 165, 156, 111,,,, -7, 4, 6, 4, 1, 1, 1, 1, 128, 219, 219, 147,,,, -7, 4, 6, 4, 1, 1, 1, 1, 256, 219, 219, 147,,,, -7, 4, 6, 4, 1, 1, 1, 1, 384, 219, 219, 147,,,, -7, 4, 6, 4, 2, 2, 1, 1, 128, 219, 211, 147,,,, -7, 4, 6, 4, 2, 2, 1, 1, 256, 219, 211, 147,,,, -7, 4, 6, 4, 2, 2, 1, 1, 384, 219, 211, 147,,,, -7, 4, 6, 4, 2, 2, 1, 2, 128, 219, 211, 147,,,, -7, 4, 6, 4, 2, 2, 1, 2, 256, 219, 211, 147,,,, -7, 4, 6, 4, 2, 2, 1, 2, 384, 219, 211, 147,,,, -7, 4, 6, 4, 2, 2, 2, 1, 128, 219, 211, 147,,,, -7, 4, 6, 4, 2, 2, 2, 1, 256, 219, 211, 147,,,, -7, 4, 6, 4, 2, 2, 2, 1, 384, 219, 211, 147,,,, -7, 4, 6, 4, 2, 2, 2, 2, 128, 219, 211, 147,,,, -7, 4, 6, 4, 2, 2, 2, 2, 256, 219, 211, 147,,,, -7, 4, 6, 4, 2, 2, 2, 2, 384, 219, 211, 147,,,, -7, 4, 6, 4, 3, 3, 1, 1, 128, 219, 207, 147,,,, -7, 4, 6, 4, 3, 3, 1, 1, 256, 219, 207, 147,,,, -7, 4, 6, 4, 3, 3, 1, 1, 384, 219, 207, 147,,,, -7, 4, 6, 4, 3, 3, 1, 2, 128, 219, 207, 147,,,, -7, 4, 6, 4, 3, 3, 1, 2, 256, 219, 207, 147,,,, -7, 4, 6, 4, 3, 3, 1, 2, 384, 219, 207, 147,,,, -7, 4, 6, 4, 3, 3, 1, 3, 128, 219, 207, 147,,,, -7, 4, 6, 4, 3, 3, 1, 3, 256, 219, 207, 147,,,, -7, 4, 6, 4, 3, 3, 1, 3, 384, 219, 207, 147,,,, -7, 4, 6, 4, 3, 3, 2, 1, 128, 219, 207, 147,,,, -7, 4, 6, 4, 3, 3, 2, 1, 256, 219, 207, 147,,,, -7, 4, 6, 4, 3, 3, 2, 1, 384, 219, 207, 147,,,, -7, 4, 6, 4, 3, 3, 2, 2, 128, 219, 207, 147,,,, -7, 4, 6, 4, 3, 3, 2, 2, 256, 219, 207, 147,,,, -7, 4, 6, 4, 3, 3, 2, 2, 384, 219, 207, 147,,,, -7, 4, 6, 4, 3, 3, 2, 3, 128, 219, 207, 147,,,, -7, 4, 6, 4, 3, 3, 2, 3, 256, 219, 207, 147,,,, -7, 4, 6, 4, 3, 3, 2, 3, 384, 219, 207, 147,,,, -7, 4, 6, 4, 3, 3, 3, 1, 128, 219, 207, 147,,,, -7, 4, 6, 4, 3, 3, 3, 1, 256, 219, 207, 147,,,, -7, 4, 6, 4, 3, 3, 3, 1, 384, 219, 207, 147,,,, -7, 4, 6, 4, 3, 3, 3, 2, 128, 219, 207, 147,,,, -7, 4, 6, 4, 3, 3, 3, 2, 256, 219, 207, 147,,,, -7, 4, 6, 4, 3, 3, 3, 2, 384, 219, 207, 147,,,, -7, 4, 6, 4, 3, 3, 3, 3, 128, 219, 207, 147,,,, -7, 4, 6, 4, 3, 3, 3, 3, 256, 219, 207, 147,,,, -7, 4, 6, 4, 3, 3, 3, 3, 384, 219, 207, 147,,,, -7, 4, 7, 1, 1, 1, 1, 1, 128, 57, 57, 39,,,, -7, 4, 7, 1, 1, 1, 1, 1, 256, 57, 57, 39,,,, -7, 4, 7, 1, 1, 1, 1, 1, 384, 57, 57, 39,,,, -7, 4, 7, 1, 2, 2, 1, 1, 128, 57, 55, 39,,,, -7, 4, 7, 1, 2, 2, 1, 1, 256, 57, 55, 39,,,, -7, 4, 7, 1, 2, 2, 1, 1, 384, 57, 55, 39,,,, -7, 4, 7, 1, 2, 2, 1, 2, 128, 57, 55, 39,,,, -7, 4, 7, 1, 2, 2, 1, 2, 256, 57, 55, 39,,,, -7, 4, 7, 1, 2, 2, 1, 2, 384, 57, 55, 39,,,, -7, 4, 7, 1, 2, 2, 2, 1, 128, 57, 55, 39,,,, -7, 4, 7, 1, 2, 2, 2, 1, 256, 57, 55, 39,,,, -7, 4, 7, 1, 2, 2, 2, 1, 384, 57, 55, 39,,,, -7, 4, 7, 1, 2, 2, 2, 2, 128, 57, 55, 39,,,, -7, 4, 7, 1, 2, 2, 2, 2, 256, 57, 55, 39,,,, -7, 4, 7, 1, 2, 2, 2, 2, 384, 57, 55, 39,,,, -7, 4, 7, 1, 3, 3, 1, 1, 128, 57, 54, 39,,,, -7, 4, 7, 1, 3, 3, 1, 1, 256, 57, 54, 39,,,, -7, 4, 7, 1, 3, 3, 1, 1, 384, 57, 54, 39,,,, -7, 4, 7, 1, 3, 3, 1, 2, 128, 57, 54, 39,,,, -7, 4, 7, 1, 3, 3, 1, 2, 256, 57, 54, 39,,,, -7, 4, 7, 1, 3, 3, 1, 2, 384, 57, 54, 39,,,, -7, 4, 7, 1, 3, 3, 1, 3, 128, 57, 54, 39,,,, -7, 4, 7, 1, 3, 3, 1, 3, 256, 57, 54, 39,,,, -7, 4, 7, 1, 3, 3, 1, 3, 384, 57, 54, 39,,,, -7, 4, 7, 1, 3, 3, 2, 1, 128, 57, 54, 39,,,, -7, 4, 7, 1, 3, 3, 2, 1, 256, 57, 54, 39,,,, -7, 4, 7, 1, 3, 3, 2, 1, 384, 57, 54, 39,,,, -7, 4, 7, 1, 3, 3, 2, 2, 128, 57, 54, 39,,,, -7, 4, 7, 1, 3, 3, 2, 2, 256, 57, 54, 39,,,, -7, 4, 7, 1, 3, 3, 2, 2, 384, 57, 54, 39,,,, -7, 4, 7, 1, 3, 3, 2, 3, 128, 57, 54, 39,,,, -7, 4, 7, 1, 3, 3, 2, 3, 256, 57, 54, 39,,,, -7, 4, 7, 1, 3, 3, 2, 3, 384, 57, 54, 39,,,, -7, 4, 7, 1, 3, 3, 3, 1, 128, 57, 54, 39,,,, -7, 4, 7, 1, 3, 3, 3, 1, 256, 57, 54, 39,,,, -7, 4, 7, 1, 3, 3, 3, 1, 384, 57, 54, 39,,,, -7, 4, 7, 1, 3, 3, 3, 2, 128, 57, 54, 39,,,, -7, 4, 7, 1, 3, 3, 3, 2, 256, 57, 54, 39,,,, -7, 4, 7, 1, 3, 3, 3, 2, 384, 57, 54, 39,,,, -7, 4, 7, 1, 3, 3, 3, 3, 128, 57, 54, 39,,,, -7, 4, 7, 1, 3, 3, 3, 3, 256, 57, 54, 39,,,, -7, 4, 7, 1, 3, 3, 3, 3, 384, 57, 54, 39,,,, -7, 4, 7, 2, 1, 1, 1, 1, 128, 111, 111, 75,,,, -7, 4, 7, 2, 1, 1, 1, 1, 256, 111, 111, 75,,,, -7, 4, 7, 2, 1, 1, 1, 1, 384, 111, 111, 75,,,, -7, 4, 7, 2, 2, 2, 1, 1, 128, 111, 107, 75,,,, -7, 4, 7, 2, 2, 2, 1, 1, 256, 111, 107, 75,,,, -7, 4, 7, 2, 2, 2, 1, 1, 384, 111, 107, 75,,,, -7, 4, 7, 2, 2, 2, 1, 2, 128, 111, 107, 75,,,, -7, 4, 7, 2, 2, 2, 1, 2, 256, 111, 107, 75,,,, -7, 4, 7, 2, 2, 2, 1, 2, 384, 111, 107, 75,,,, -7, 4, 7, 2, 2, 2, 2, 1, 128, 111, 107, 75,,,, -7, 4, 7, 2, 2, 2, 2, 1, 256, 111, 107, 75,,,, -7, 4, 7, 2, 2, 2, 2, 1, 384, 111, 107, 75,,,, -7, 4, 7, 2, 2, 2, 2, 2, 128, 111, 107, 75,,,, -7, 4, 7, 2, 2, 2, 2, 2, 256, 111, 107, 75,,,, -7, 4, 7, 2, 2, 2, 2, 2, 384, 111, 107, 75,,,, -7, 4, 7, 2, 3, 3, 1, 1, 128, 111, 105, 75,,,, -7, 4, 7, 2, 3, 3, 1, 1, 256, 111, 105, 75,,,, -7, 4, 7, 2, 3, 3, 1, 1, 384, 111, 105, 75,,,, -7, 4, 7, 2, 3, 3, 1, 2, 128, 111, 105, 75,,,, -7, 4, 7, 2, 3, 3, 1, 2, 256, 111, 105, 75,,,, -7, 4, 7, 2, 3, 3, 1, 2, 384, 111, 105, 75,,,, -7, 4, 7, 2, 3, 3, 1, 3, 128, 111, 105, 75,,,, -7, 4, 7, 2, 3, 3, 1, 3, 256, 111, 105, 75,,,, -7, 4, 7, 2, 3, 3, 1, 3, 384, 111, 105, 75,,,, -7, 4, 7, 2, 3, 3, 2, 1, 128, 111, 105, 75,,,, -7, 4, 7, 2, 3, 3, 2, 1, 256, 111, 105, 75,,,, -7, 4, 7, 2, 3, 3, 2, 1, 384, 111, 105, 75,,,, -7, 4, 7, 2, 3, 3, 2, 2, 128, 111, 105, 75,,,, -7, 4, 7, 2, 3, 3, 2, 2, 256, 111, 105, 75,,,, -7, 4, 7, 2, 3, 3, 2, 2, 384, 111, 105, 75,,,, -7, 4, 7, 2, 3, 3, 2, 3, 128, 111, 105, 75,,,, -7, 4, 7, 2, 3, 3, 2, 3, 256, 111, 105, 75,,,, -7, 4, 7, 2, 3, 3, 2, 3, 384, 111, 105, 75,,,, -7, 4, 7, 2, 3, 3, 3, 1, 128, 111, 105, 75,,,, -7, 4, 7, 2, 3, 3, 3, 1, 256, 111, 105, 75,,,, -7, 4, 7, 2, 3, 3, 3, 1, 384, 111, 105, 75,,,, -7, 4, 7, 2, 3, 3, 3, 2, 128, 111, 105, 75,,,, -7, 4, 7, 2, 3, 3, 3, 2, 256, 111, 105, 75,,,, -7, 4, 7, 2, 3, 3, 3, 2, 384, 111, 105, 75,,,, -7, 4, 7, 2, 3, 3, 3, 3, 128, 111, 105, 75,,,, -7, 4, 7, 2, 3, 3, 3, 3, 256, 111, 105, 75,,,, -7, 4, 7, 2, 3, 3, 3, 3, 384, 111, 105, 75,,,, -7, 4, 7, 3, 1, 1, 1, 1, 128, 165, 165, 111,,,, -7, 4, 7, 3, 1, 1, 1, 1, 256, 165, 165, 111,,,, -7, 4, 7, 3, 1, 1, 1, 1, 384, 165, 165, 111,,,, -7, 4, 7, 3, 2, 2, 1, 1, 128, 165, 159, 111,,,, -7, 4, 7, 3, 2, 2, 1, 1, 256, 165, 159, 111,,,, -7, 4, 7, 3, 2, 2, 1, 1, 384, 165, 159, 111,,,, -7, 4, 7, 3, 2, 2, 1, 2, 128, 165, 159, 111,,,, -7, 4, 7, 3, 2, 2, 1, 2, 256, 165, 159, 111,,,, -7, 4, 7, 3, 2, 2, 1, 2, 384, 165, 159, 111,,,, -7, 4, 7, 3, 2, 2, 2, 1, 128, 165, 159, 111,,,, -7, 4, 7, 3, 2, 2, 2, 1, 256, 165, 159, 111,,,, -7, 4, 7, 3, 2, 2, 2, 1, 384, 165, 159, 111,,,, -7, 4, 7, 3, 2, 2, 2, 2, 128, 165, 159, 111,,,, -7, 4, 7, 3, 2, 2, 2, 2, 256, 165, 159, 111,,,, -7, 4, 7, 3, 2, 2, 2, 2, 384, 165, 159, 111,,,, -7, 4, 7, 3, 3, 3, 1, 1, 128, 165, 156, 111,,,, -7, 4, 7, 3, 3, 3, 1, 1, 256, 165, 156, 111,,,, -7, 4, 7, 3, 3, 3, 1, 1, 384, 165, 156, 111,,,, -7, 4, 7, 3, 3, 3, 1, 2, 128, 165, 156, 111,,,, -7, 4, 7, 3, 3, 3, 1, 2, 256, 165, 156, 111,,,, -7, 4, 7, 3, 3, 3, 1, 2, 384, 165, 156, 111,,,, -7, 4, 7, 3, 3, 3, 1, 3, 128, 165, 156, 111,,,, -7, 4, 7, 3, 3, 3, 1, 3, 256, 165, 156, 111,,,, -7, 4, 7, 3, 3, 3, 1, 3, 384, 165, 156, 111,,,, -7, 4, 7, 3, 3, 3, 2, 1, 128, 165, 156, 111,,,, -7, 4, 7, 3, 3, 3, 2, 1, 256, 165, 156, 111,,,, -7, 4, 7, 3, 3, 3, 2, 1, 384, 165, 156, 111,,,, -7, 4, 7, 3, 3, 3, 2, 2, 128, 165, 156, 111,,,, -7, 4, 7, 3, 3, 3, 2, 2, 256, 165, 156, 111,,,, -7, 4, 7, 3, 3, 3, 2, 2, 384, 165, 156, 111,,,, -7, 4, 7, 3, 3, 3, 2, 3, 128, 165, 156, 111,,,, -7, 4, 7, 3, 3, 3, 2, 3, 256, 165, 156, 111,,,, -7, 4, 7, 3, 3, 3, 2, 3, 384, 165, 156, 111,,,, -7, 4, 7, 3, 3, 3, 3, 1, 128, 165, 156, 111,,,, -7, 4, 7, 3, 3, 3, 3, 1, 256, 165, 156, 111,,,, -7, 4, 7, 3, 3, 3, 3, 1, 384, 165, 156, 111,,,, -7, 4, 7, 3, 3, 3, 3, 2, 128, 165, 156, 111,,,, -7, 4, 7, 3, 3, 3, 3, 2, 256, 165, 156, 111,,,, -7, 4, 7, 3, 3, 3, 3, 2, 384, 165, 156, 111,,,, -7, 4, 7, 3, 3, 3, 3, 3, 128, 165, 156, 111,,,, -7, 4, 7, 3, 3, 3, 3, 3, 256, 165, 156, 111,,,, -7, 4, 7, 3, 3, 3, 3, 3, 384, 165, 156, 111,,,, -7, 4, 7, 4, 1, 1, 1, 1, 128, 219, 219, 147,,,, -7, 4, 7, 4, 1, 1, 1, 1, 256, 219, 219, 147,,,, -7, 4, 7, 4, 1, 1, 1, 1, 384, 219, 219, 147,,,, -7, 4, 7, 4, 2, 2, 1, 1, 128, 219, 211, 147,,,, -7, 4, 7, 4, 2, 2, 1, 1, 256, 219, 211, 147,,,, -7, 4, 7, 4, 2, 2, 1, 1, 384, 219, 211, 147,,,, -7, 4, 7, 4, 2, 2, 1, 2, 128, 219, 211, 147,,,, -7, 4, 7, 4, 2, 2, 1, 2, 256, 219, 211, 147,,,, -7, 4, 7, 4, 2, 2, 1, 2, 384, 219, 211, 147,,,, -7, 4, 7, 4, 2, 2, 2, 1, 128, 219, 211, 147,,,, -7, 4, 7, 4, 2, 2, 2, 1, 256, 219, 211, 147,,,, -7, 4, 7, 4, 2, 2, 2, 1, 384, 219, 211, 147,,,, -7, 4, 7, 4, 2, 2, 2, 2, 128, 219, 211, 147,,,, -7, 4, 7, 4, 2, 2, 2, 2, 256, 219, 211, 147,,,, -7, 4, 7, 4, 2, 2, 2, 2, 384, 219, 211, 147,,,, -7, 4, 7, 4, 3, 3, 1, 1, 128, 219, 207, 147,,,, -7, 4, 7, 4, 3, 3, 1, 1, 256, 219, 207, 147,,,, -7, 4, 7, 4, 3, 3, 1, 1, 384, 219, 207, 147,,,, -7, 4, 7, 4, 3, 3, 1, 2, 128, 219, 207, 147,,,, -7, 4, 7, 4, 3, 3, 1, 2, 256, 219, 207, 147,,,, -7, 4, 7, 4, 3, 3, 1, 2, 384, 219, 207, 147,,,, -7, 4, 7, 4, 3, 3, 1, 3, 128, 219, 207, 147,,,, -7, 4, 7, 4, 3, 3, 1, 3, 256, 219, 207, 147,,,, -7, 4, 7, 4, 3, 3, 1, 3, 384, 219, 207, 147,,,, -7, 4, 7, 4, 3, 3, 2, 1, 128, 219, 207, 147,,,, -7, 4, 7, 4, 3, 3, 2, 1, 256, 219, 207, 147,,,, -7, 4, 7, 4, 3, 3, 2, 1, 384, 219, 207, 147,,,, -7, 4, 7, 4, 3, 3, 2, 2, 128, 219, 207, 147,,,, -7, 4, 7, 4, 3, 3, 2, 2, 256, 219, 207, 147,,,, -7, 4, 7, 4, 3, 3, 2, 2, 384, 219, 207, 147,,,, -7, 4, 7, 4, 3, 3, 2, 3, 128, 219, 207, 147,,,, -7, 4, 7, 4, 3, 3, 2, 3, 256, 219, 207, 147,,,, -7, 4, 7, 4, 3, 3, 2, 3, 384, 219, 207, 147,,,, -7, 4, 7, 4, 3, 3, 3, 1, 128, 219, 207, 147,,,, -7, 4, 7, 4, 3, 3, 3, 1, 256, 219, 207, 147,,,, -7, 4, 7, 4, 3, 3, 3, 1, 384, 219, 207, 147,,,, -7, 4, 7, 4, 3, 3, 3, 2, 128, 219, 207, 147,,,, -7, 4, 7, 4, 3, 3, 3, 2, 256, 219, 207, 147,,,, -7, 4, 7, 4, 3, 3, 3, 2, 384, 219, 207, 147,,,, -7, 4, 7, 4, 3, 3, 3, 3, 128, 219, 207, 147,,,, -7, 4, 7, 4, 3, 3, 3, 3, 256, 219, 207, 147,,,, -7, 4, 7, 4, 3, 3, 3, 3, 384, 219, 207, 147,,,, -7, 5, 1, 1, 1, 1, 1, 1, 128, 58, 40, 22,,,, -7, 5, 1, 1, 1, 1, 1, 1, 256, 58, 40, 22,,,, -7, 5, 1, 1, 1, 1, 1, 1, 384, 58, 40, 22,,,, -7, 5, 1, 1, 2, 2, 1, 1, 128, 58, 40, 22,,,, -7, 5, 1, 1, 2, 2, 1, 1, 256, 58, 40, 22,,,, -7, 5, 1, 1, 2, 2, 1, 1, 384, 58, 40, 22,,,, -7, 5, 1, 1, 2, 2, 1, 2, 128, 58, 40, 22,,,, -7, 5, 1, 1, 2, 2, 1, 2, 256, 58, 40, 22,,,, -7, 5, 1, 1, 2, 2, 1, 2, 384, 58, 40, 22,,,, -7, 5, 1, 1, 2, 2, 2, 1, 128, 58, 40, 22,,,, -7, 5, 1, 1, 2, 2, 2, 1, 256, 58, 40, 22,,,, -7, 5, 1, 1, 2, 2, 2, 1, 384, 58, 40, 22,,,, -7, 5, 1, 1, 2, 2, 2, 2, 128, 58, 40, 22,,,, -7, 5, 1, 1, 2, 2, 2, 2, 256, 58, 40, 22,,,, -7, 5, 1, 1, 2, 2, 2, 2, 384, 58, 40, 22,,,, -7, 5, 1, 1, 3, 3, 1, 1, 128, 58, 40, 22,,,, -7, 5, 1, 1, 3, 3, 1, 1, 256, 58, 40, 22,,,, -7, 5, 1, 1, 3, 3, 1, 1, 384, 58, 40, 22,,,, -7, 5, 1, 1, 3, 3, 1, 2, 128, 58, 40, 22,,,, -7, 5, 1, 1, 3, 3, 1, 2, 256, 58, 40, 22,,,, -7, 5, 1, 1, 3, 3, 1, 2, 384, 58, 40, 22,,,, -7, 5, 1, 1, 3, 3, 1, 3, 128, 58, 40, 22,,,, -7, 5, 1, 1, 3, 3, 1, 3, 256, 58, 40, 22,,,, -7, 5, 1, 1, 3, 3, 1, 3, 384, 58, 40, 22,,,, -7, 5, 1, 1, 3, 3, 2, 1, 128, 58, 40, 22,,,, -7, 5, 1, 1, 3, 3, 2, 1, 256, 58, 40, 22,,,, -7, 5, 1, 1, 3, 3, 2, 1, 384, 58, 40, 22,,,, -7, 5, 1, 1, 3, 3, 2, 2, 128, 58, 40, 22,,,, -7, 5, 1, 1, 3, 3, 2, 2, 256, 58, 40, 22,,,, -7, 5, 1, 1, 3, 3, 2, 2, 384, 58, 40, 22,,,, -7, 5, 1, 1, 3, 3, 2, 3, 128, 58, 40, 22,,,, -7, 5, 1, 1, 3, 3, 2, 3, 256, 58, 40, 22,,,, -7, 5, 1, 1, 3, 3, 2, 3, 384, 58, 40, 22,,,, -7, 5, 1, 1, 3, 3, 3, 1, 128, 58, 40, 22,,,, -7, 5, 1, 1, 3, 3, 3, 1, 256, 58, 40, 22,,,, -7, 5, 1, 1, 3, 3, 3, 1, 384, 58, 40, 22,,,, -7, 5, 1, 1, 3, 3, 3, 2, 128, 58, 40, 22,,,, -7, 5, 1, 1, 3, 3, 3, 2, 256, 58, 40, 22,,,, -7, 5, 1, 1, 3, 3, 3, 2, 384, 58, 40, 22,,,, -7, 5, 1, 1, 3, 3, 3, 3, 128, 58, 40, 22,,,, -7, 5, 1, 1, 3, 3, 3, 3, 256, 58, 40, 22,,,, -7, 5, 1, 1, 3, 3, 3, 3, 384, 58, 40, 22,,,, -7, 5, 1, 2, 1, 1, 1, 1, 128, 112, 76, 40,,,, -7, 5, 1, 2, 1, 1, 1, 1, 256, 112, 76, 40,,,, -7, 5, 1, 2, 1, 1, 1, 1, 384, 112, 76, 40,,,, -7, 5, 1, 2, 2, 2, 1, 1, 128, 112, 76, 40,,,, -7, 5, 1, 2, 2, 2, 1, 1, 256, 112, 76, 40,,,, -7, 5, 1, 2, 2, 2, 1, 1, 384, 112, 76, 40,,,, -7, 5, 1, 2, 2, 2, 1, 2, 128, 112, 76, 40,,,, -7, 5, 1, 2, 2, 2, 1, 2, 256, 112, 76, 40,,,, -7, 5, 1, 2, 2, 2, 1, 2, 384, 112, 76, 40,,,, -7, 5, 1, 2, 2, 2, 2, 1, 128, 112, 76, 40,,,, -7, 5, 1, 2, 2, 2, 2, 1, 256, 112, 76, 40,,,, -7, 5, 1, 2, 2, 2, 2, 1, 384, 112, 76, 40,,,, -7, 5, 1, 2, 2, 2, 2, 2, 128, 112, 76, 40,,,, -7, 5, 1, 2, 2, 2, 2, 2, 256, 112, 76, 40,,,, -7, 5, 1, 2, 2, 2, 2, 2, 384, 112, 76, 40,,,, -7, 5, 1, 2, 3, 3, 1, 1, 128, 112, 76, 40,,,, -7, 5, 1, 2, 3, 3, 1, 1, 256, 112, 76, 40,,,, -7, 5, 1, 2, 3, 3, 1, 1, 384, 112, 76, 40,,,, -7, 5, 1, 2, 3, 3, 1, 2, 128, 112, 76, 40,,,, -7, 5, 1, 2, 3, 3, 1, 2, 256, 112, 76, 40,,,, -7, 5, 1, 2, 3, 3, 1, 2, 384, 112, 76, 40,,,, -7, 5, 1, 2, 3, 3, 1, 3, 128, 112, 76, 40,,,, -7, 5, 1, 2, 3, 3, 1, 3, 256, 112, 76, 40,,,, -7, 5, 1, 2, 3, 3, 1, 3, 384, 112, 76, 40,,,, -7, 5, 1, 2, 3, 3, 2, 1, 128, 112, 76, 40,,,, -7, 5, 1, 2, 3, 3, 2, 1, 256, 112, 76, 40,,,, -7, 5, 1, 2, 3, 3, 2, 1, 384, 112, 76, 40,,,, -7, 5, 1, 2, 3, 3, 2, 2, 128, 112, 76, 40,,,, -7, 5, 1, 2, 3, 3, 2, 2, 256, 112, 76, 40,,,, -7, 5, 1, 2, 3, 3, 2, 2, 384, 112, 76, 40,,,, -7, 5, 1, 2, 3, 3, 2, 3, 128, 112, 76, 40,,,, -7, 5, 1, 2, 3, 3, 2, 3, 256, 112, 76, 40,,,, -7, 5, 1, 2, 3, 3, 2, 3, 384, 112, 76, 40,,,, -7, 5, 1, 2, 3, 3, 3, 1, 128, 112, 76, 40,,,, -7, 5, 1, 2, 3, 3, 3, 1, 256, 112, 76, 40,,,, -7, 5, 1, 2, 3, 3, 3, 1, 384, 112, 76, 40,,,, -7, 5, 1, 2, 3, 3, 3, 2, 128, 112, 76, 40,,,, -7, 5, 1, 2, 3, 3, 3, 2, 256, 112, 76, 40,,,, -7, 5, 1, 2, 3, 3, 3, 2, 384, 112, 76, 40,,,, -7, 5, 1, 2, 3, 3, 3, 3, 128, 112, 76, 40,,,, -7, 5, 1, 2, 3, 3, 3, 3, 256, 112, 76, 40,,,, -7, 5, 1, 2, 3, 3, 3, 3, 384, 112, 76, 40,,,, -7, 5, 1, 3, 1, 1, 1, 1, 128, 166, 112, 58,,,, -7, 5, 1, 3, 1, 1, 1, 1, 256, 166, 112, 58,,,, -7, 5, 1, 3, 1, 1, 1, 1, 384, 166, 112, 58,,,, -7, 5, 1, 3, 2, 2, 1, 1, 128, 166, 112, 58,,,, -7, 5, 1, 3, 2, 2, 1, 1, 256, 166, 112, 58,,,, -7, 5, 1, 3, 2, 2, 1, 1, 384, 166, 112, 58,,,, -7, 5, 1, 3, 2, 2, 1, 2, 128, 166, 112, 58,,,, -7, 5, 1, 3, 2, 2, 1, 2, 256, 166, 112, 58,,,, -7, 5, 1, 3, 2, 2, 1, 2, 384, 166, 112, 58,,,, -7, 5, 1, 3, 2, 2, 2, 1, 128, 166, 112, 58,,,, -7, 5, 1, 3, 2, 2, 2, 1, 256, 166, 112, 58,,,, -7, 5, 1, 3, 2, 2, 2, 1, 384, 166, 112, 58,,,, -7, 5, 1, 3, 2, 2, 2, 2, 128, 166, 112, 58,,,, -7, 5, 1, 3, 2, 2, 2, 2, 256, 166, 112, 58,,,, -7, 5, 1, 3, 2, 2, 2, 2, 384, 166, 112, 58,,,, -7, 5, 1, 3, 3, 3, 1, 1, 128, 166, 112, 58,,,, -7, 5, 1, 3, 3, 3, 1, 1, 256, 166, 112, 58,,,, -7, 5, 1, 3, 3, 3, 1, 1, 384, 166, 112, 58,,,, -7, 5, 1, 3, 3, 3, 1, 2, 128, 166, 112, 58,,,, -7, 5, 1, 3, 3, 3, 1, 2, 256, 166, 112, 58,,,, -7, 5, 1, 3, 3, 3, 1, 2, 384, 166, 112, 58,,,, -7, 5, 1, 3, 3, 3, 1, 3, 128, 166, 112, 58,,,, -7, 5, 1, 3, 3, 3, 1, 3, 256, 166, 112, 58,,,, -7, 5, 1, 3, 3, 3, 1, 3, 384, 166, 112, 58,,,, -7, 5, 1, 3, 3, 3, 2, 1, 128, 166, 112, 58,,,, -7, 5, 1, 3, 3, 3, 2, 1, 256, 166, 112, 58,,,, -7, 5, 1, 3, 3, 3, 2, 1, 384, 166, 112, 58,,,, -7, 5, 1, 3, 3, 3, 2, 2, 128, 166, 112, 58,,,, -7, 5, 1, 3, 3, 3, 2, 2, 256, 166, 112, 58,,,, -7, 5, 1, 3, 3, 3, 2, 2, 384, 166, 112, 58,,,, -7, 5, 1, 3, 3, 3, 2, 3, 128, 166, 112, 58,,,, -7, 5, 1, 3, 3, 3, 2, 3, 256, 166, 112, 58,,,, -7, 5, 1, 3, 3, 3, 2, 3, 384, 166, 112, 58,,,, -7, 5, 1, 3, 3, 3, 3, 1, 128, 166, 112, 58,,,, -7, 5, 1, 3, 3, 3, 3, 1, 256, 166, 112, 58,,,, -7, 5, 1, 3, 3, 3, 3, 1, 384, 166, 112, 58,,,, -7, 5, 1, 3, 3, 3, 3, 2, 128, 166, 112, 58,,,, -7, 5, 1, 3, 3, 3, 3, 2, 256, 166, 112, 58,,,, -7, 5, 1, 3, 3, 3, 3, 2, 384, 166, 112, 58,,,, -7, 5, 1, 3, 3, 3, 3, 3, 128, 166, 112, 58,,,, -7, 5, 1, 3, 3, 3, 3, 3, 256, 166, 112, 58,,,, -7, 5, 1, 3, 3, 3, 3, 3, 384, 166, 112, 58,,,, -7, 5, 1, 4, 1, 1, 1, 1, 128, 220, 148, 76,,,, -7, 5, 1, 4, 1, 1, 1, 1, 256, 220, 148, 76,,,, -7, 5, 1, 4, 1, 1, 1, 1, 384, 220, 148, 76,,,, -7, 5, 1, 4, 2, 2, 1, 1, 128, 220, 148, 76,,,, -7, 5, 1, 4, 2, 2, 1, 1, 256, 220, 148, 76,,,, -7, 5, 1, 4, 2, 2, 1, 1, 384, 220, 148, 76,,,, -7, 5, 1, 4, 2, 2, 1, 2, 128, 220, 148, 76,,,, -7, 5, 1, 4, 2, 2, 1, 2, 256, 220, 148, 76,,,, -7, 5, 1, 4, 2, 2, 1, 2, 384, 220, 148, 76,,,, -7, 5, 1, 4, 2, 2, 2, 1, 128, 220, 148, 76,,,, -7, 5, 1, 4, 2, 2, 2, 1, 256, 220, 148, 76,,,, -7, 5, 1, 4, 2, 2, 2, 1, 384, 220, 148, 76,,,, -7, 5, 1, 4, 2, 2, 2, 2, 128, 220, 148, 76,,,, -7, 5, 1, 4, 2, 2, 2, 2, 256, 220, 148, 76,,,, -7, 5, 1, 4, 2, 2, 2, 2, 384, 220, 148, 76,,,, -7, 5, 1, 4, 3, 3, 1, 1, 128, 220, 148, 76,,,, -7, 5, 1, 4, 3, 3, 1, 1, 256, 220, 148, 76,,,, -7, 5, 1, 4, 3, 3, 1, 1, 384, 220, 148, 76,,,, -7, 5, 1, 4, 3, 3, 1, 2, 128, 220, 148, 76,,,, -7, 5, 1, 4, 3, 3, 1, 2, 256, 220, 148, 76,,,, -7, 5, 1, 4, 3, 3, 1, 2, 384, 220, 148, 76,,,, -7, 5, 1, 4, 3, 3, 1, 3, 128, 220, 148, 76,,,, -7, 5, 1, 4, 3, 3, 1, 3, 256, 220, 148, 76,,,, -7, 5, 1, 4, 3, 3, 1, 3, 384, 220, 148, 76,,,, -7, 5, 1, 4, 3, 3, 2, 1, 128, 220, 148, 76,,,, -7, 5, 1, 4, 3, 3, 2, 1, 256, 220, 148, 76,,,, -7, 5, 1, 4, 3, 3, 2, 1, 384, 220, 148, 76,,,, -7, 5, 1, 4, 3, 3, 2, 2, 128, 220, 148, 76,,,, -7, 5, 1, 4, 3, 3, 2, 2, 256, 220, 148, 76,,,, -7, 5, 1, 4, 3, 3, 2, 2, 384, 220, 148, 76,,,, -7, 5, 1, 4, 3, 3, 2, 3, 128, 220, 148, 76,,,, -7, 5, 1, 4, 3, 3, 2, 3, 256, 220, 148, 76,,,, -7, 5, 1, 4, 3, 3, 2, 3, 384, 220, 148, 76,,,, -7, 5, 1, 4, 3, 3, 3, 1, 128, 220, 148, 76,,,, -7, 5, 1, 4, 3, 3, 3, 1, 256, 220, 148, 76,,,, -7, 5, 1, 4, 3, 3, 3, 1, 384, 220, 148, 76,,,, -7, 5, 1, 4, 3, 3, 3, 2, 128, 220, 148, 76,,,, -7, 5, 1, 4, 3, 3, 3, 2, 256, 220, 148, 76,,,, -7, 5, 1, 4, 3, 3, 3, 2, 384, 220, 148, 76,,,, -7, 5, 1, 4, 3, 3, 3, 3, 128, 220, 148, 76,,,, -7, 5, 1, 4, 3, 3, 3, 3, 256, 220, 148, 76,,,, -7, 5, 1, 4, 3, 3, 3, 3, 384, 220, 148, 76,,,, -7, 5, 1, 5, 1, 1, 1, 1, 128, 240, 184, 94,,,, -7, 5, 1, 5, 1, 1, 1, 1, 256, 240, 184, 94,,,, -7, 5, 1, 5, 1, 1, 1, 1, 384, 240, 184, 94,,,, -7, 5, 1, 5, 2, 2, 1, 1, 128, 240, 184, 94,,,, -7, 5, 1, 5, 2, 2, 1, 1, 256, 240, 184, 94,,,, -7, 5, 1, 5, 2, 2, 1, 1, 384, 240, 184, 94,,,, -7, 5, 1, 5, 2, 2, 1, 2, 128, 240, 184, 94,,,, -7, 5, 1, 5, 2, 2, 1, 2, 256, 240, 184, 94,,,, -7, 5, 1, 5, 2, 2, 1, 2, 384, 240, 184, 94,,,, -7, 5, 1, 5, 2, 2, 2, 1, 128, 240, 184, 94,,,, -7, 5, 1, 5, 2, 2, 2, 1, 256, 240, 184, 94,,,, -7, 5, 1, 5, 2, 2, 2, 1, 384, 240, 184, 94,,,, -7, 5, 1, 5, 2, 2, 2, 2, 128, 240, 184, 94,,,, -7, 5, 1, 5, 2, 2, 2, 2, 256, 240, 184, 94,,,, -7, 5, 1, 5, 2, 2, 2, 2, 384, 240, 184, 94,,,, -7, 5, 1, 5, 3, 3, 1, 1, 128, 240, 184, 94,,,, -7, 5, 1, 5, 3, 3, 1, 1, 256, 240, 184, 94,,,, -7, 5, 1, 5, 3, 3, 1, 1, 384, 240, 184, 94,,,, -7, 5, 1, 5, 3, 3, 1, 2, 128, 240, 184, 94,,,, -7, 5, 1, 5, 3, 3, 1, 2, 256, 240, 184, 94,,,, -7, 5, 1, 5, 3, 3, 1, 2, 384, 240, 184, 94,,,, -7, 5, 1, 5, 3, 3, 1, 3, 128, 240, 184, 94,,,, -7, 5, 1, 5, 3, 3, 1, 3, 256, 240, 184, 94,,,, -7, 5, 1, 5, 3, 3, 1, 3, 384, 240, 184, 94,,,, -7, 5, 1, 5, 3, 3, 2, 1, 128, 240, 184, 94,,,, -7, 5, 1, 5, 3, 3, 2, 1, 256, 240, 184, 94,,,, -7, 5, 1, 5, 3, 3, 2, 1, 384, 240, 184, 94,,,, -7, 5, 1, 5, 3, 3, 2, 2, 128, 240, 184, 94,,,, -7, 5, 1, 5, 3, 3, 2, 2, 256, 240, 184, 94,,,, -7, 5, 1, 5, 3, 3, 2, 2, 384, 240, 184, 94,,,, -7, 5, 1, 5, 3, 3, 2, 3, 128, 240, 184, 94,,,, -7, 5, 1, 5, 3, 3, 2, 3, 256, 240, 184, 94,,,, -7, 5, 1, 5, 3, 3, 2, 3, 384, 240, 184, 94,,,, -7, 5, 1, 5, 3, 3, 3, 1, 128, 240, 184, 94,,,, -7, 5, 1, 5, 3, 3, 3, 1, 256, 240, 184, 94,,,, -7, 5, 1, 5, 3, 3, 3, 1, 384, 240, 184, 94,,,, -7, 5, 1, 5, 3, 3, 3, 2, 128, 240, 184, 94,,,, -7, 5, 1, 5, 3, 3, 3, 2, 256, 240, 184, 94,,,, -7, 5, 1, 5, 3, 3, 3, 2, 384, 240, 184, 94,,,, -7, 5, 1, 5, 3, 3, 3, 3, 128, 240, 184, 94,,,, -7, 5, 1, 5, 3, 3, 3, 3, 256, 240, 184, 94,,,, -7, 5, 1, 5, 3, 3, 3, 3, 384, 240, 184, 94,,,, -7, 5, 2, 1, 1, 1, 1, 1, 128, 58, 40, 22,,,, -7, 5, 2, 1, 1, 1, 1, 1, 256, 58, 40, 22,,,, -7, 5, 2, 1, 1, 1, 1, 1, 384, 58, 40, 22,,,, -7, 5, 2, 1, 2, 2, 1, 1, 128, 58, 40, 22,,,, -7, 5, 2, 1, 2, 2, 1, 1, 256, 58, 40, 22,,,, -7, 5, 2, 1, 2, 2, 1, 1, 384, 58, 40, 22,,,, -7, 5, 2, 1, 2, 2, 1, 2, 128, 58, 40, 22,,,, -7, 5, 2, 1, 2, 2, 1, 2, 256, 58, 40, 22,,,, -7, 5, 2, 1, 2, 2, 1, 2, 384, 58, 40, 22,,,, -7, 5, 2, 1, 2, 2, 2, 1, 128, 58, 40, 22,,,, -7, 5, 2, 1, 2, 2, 2, 1, 256, 58, 40, 22,,,, -7, 5, 2, 1, 2, 2, 2, 1, 384, 58, 40, 22,,,, -7, 5, 2, 1, 2, 2, 2, 2, 128, 58, 40, 22,,,, -7, 5, 2, 1, 2, 2, 2, 2, 256, 58, 40, 22,,,, -7, 5, 2, 1, 2, 2, 2, 2, 384, 58, 40, 22,,,, -7, 5, 2, 1, 3, 3, 1, 1, 128, 58, 40, 22,,,, -7, 5, 2, 1, 3, 3, 1, 1, 256, 58, 40, 22,,,, -7, 5, 2, 1, 3, 3, 1, 1, 384, 58, 40, 22,,,, -7, 5, 2, 1, 3, 3, 1, 2, 128, 58, 40, 22,,,, -7, 5, 2, 1, 3, 3, 1, 2, 256, 58, 40, 22,,,, -7, 5, 2, 1, 3, 3, 1, 2, 384, 58, 40, 22,,,, -7, 5, 2, 1, 3, 3, 1, 3, 128, 58, 40, 22,,,, -7, 5, 2, 1, 3, 3, 1, 3, 256, 58, 40, 22,,,, -7, 5, 2, 1, 3, 3, 1, 3, 384, 58, 40, 22,,,, -7, 5, 2, 1, 3, 3, 2, 1, 128, 58, 40, 22,,,, -7, 5, 2, 1, 3, 3, 2, 1, 256, 58, 40, 22,,,, -7, 5, 2, 1, 3, 3, 2, 1, 384, 58, 40, 22,,,, -7, 5, 2, 1, 3, 3, 2, 2, 128, 58, 40, 22,,,, -7, 5, 2, 1, 3, 3, 2, 2, 256, 58, 40, 22,,,, -7, 5, 2, 1, 3, 3, 2, 2, 384, 58, 40, 22,,,, -7, 5, 2, 1, 3, 3, 2, 3, 128, 58, 40, 22,,,, -7, 5, 2, 1, 3, 3, 2, 3, 256, 58, 40, 22,,,, -7, 5, 2, 1, 3, 3, 2, 3, 384, 58, 40, 22,,,, -7, 5, 2, 1, 3, 3, 3, 1, 128, 58, 40, 22,,,, -7, 5, 2, 1, 3, 3, 3, 1, 256, 58, 40, 22,,,, -7, 5, 2, 1, 3, 3, 3, 1, 384, 58, 40, 22,,,, -7, 5, 2, 1, 3, 3, 3, 2, 128, 58, 40, 22,,,, -7, 5, 2, 1, 3, 3, 3, 2, 256, 58, 40, 22,,,, -7, 5, 2, 1, 3, 3, 3, 2, 384, 58, 40, 22,,,, -7, 5, 2, 1, 3, 3, 3, 3, 128, 58, 40, 22,,,, -7, 5, 2, 1, 3, 3, 3, 3, 256, 58, 40, 22,,,, -7, 5, 2, 1, 3, 3, 3, 3, 384, 58, 40, 22,,,, -7, 5, 2, 2, 1, 1, 1, 1, 128, 112, 76, 40,,,, -7, 5, 2, 2, 1, 1, 1, 1, 256, 112, 76, 40,,,, -7, 5, 2, 2, 1, 1, 1, 1, 384, 112, 76, 40,,,, -7, 5, 2, 2, 2, 2, 1, 1, 128, 112, 76, 40,,,, -7, 5, 2, 2, 2, 2, 1, 1, 256, 112, 76, 40,,,, -7, 5, 2, 2, 2, 2, 1, 1, 384, 112, 76, 40,,,, -7, 5, 2, 2, 2, 2, 1, 2, 128, 112, 76, 40,,,, -7, 5, 2, 2, 2, 2, 1, 2, 256, 112, 76, 40,,,, -7, 5, 2, 2, 2, 2, 1, 2, 384, 112, 76, 40,,,, -7, 5, 2, 2, 2, 2, 2, 1, 128, 112, 76, 40,,,, -7, 5, 2, 2, 2, 2, 2, 1, 256, 112, 76, 40,,,, -7, 5, 2, 2, 2, 2, 2, 1, 384, 112, 76, 40,,,, -7, 5, 2, 2, 2, 2, 2, 2, 128, 112, 76, 40,,,, -7, 5, 2, 2, 2, 2, 2, 2, 256, 112, 76, 40,,,, -7, 5, 2, 2, 2, 2, 2, 2, 384, 112, 76, 40,,,, -7, 5, 2, 2, 3, 3, 1, 1, 128, 112, 76, 40,,,, -7, 5, 2, 2, 3, 3, 1, 1, 256, 112, 76, 40,,,, -7, 5, 2, 2, 3, 3, 1, 1, 384, 112, 76, 40,,,, -7, 5, 2, 2, 3, 3, 1, 2, 128, 112, 76, 40,,,, -7, 5, 2, 2, 3, 3, 1, 2, 256, 112, 76, 40,,,, -7, 5, 2, 2, 3, 3, 1, 2, 384, 112, 76, 40,,,, -7, 5, 2, 2, 3, 3, 1, 3, 128, 112, 76, 40,,,, -7, 5, 2, 2, 3, 3, 1, 3, 256, 112, 76, 40,,,, -7, 5, 2, 2, 3, 3, 1, 3, 384, 112, 76, 40,,,, -7, 5, 2, 2, 3, 3, 2, 1, 128, 112, 76, 40,,,, -7, 5, 2, 2, 3, 3, 2, 1, 256, 112, 76, 40,,,, -7, 5, 2, 2, 3, 3, 2, 1, 384, 112, 76, 40,,,, -7, 5, 2, 2, 3, 3, 2, 2, 128, 112, 76, 40,,,, -7, 5, 2, 2, 3, 3, 2, 2, 256, 112, 76, 40,,,, -7, 5, 2, 2, 3, 3, 2, 2, 384, 112, 76, 40,,,, -7, 5, 2, 2, 3, 3, 2, 3, 128, 112, 76, 40,,,, -7, 5, 2, 2, 3, 3, 2, 3, 256, 112, 76, 40,,,, -7, 5, 2, 2, 3, 3, 2, 3, 384, 112, 76, 40,,,, -7, 5, 2, 2, 3, 3, 3, 1, 128, 112, 76, 40,,,, -7, 5, 2, 2, 3, 3, 3, 1, 256, 112, 76, 40,,,, -7, 5, 2, 2, 3, 3, 3, 1, 384, 112, 76, 40,,,, -7, 5, 2, 2, 3, 3, 3, 2, 128, 112, 76, 40,,,, -7, 5, 2, 2, 3, 3, 3, 2, 256, 112, 76, 40,,,, -7, 5, 2, 2, 3, 3, 3, 2, 384, 112, 76, 40,,,, -7, 5, 2, 2, 3, 3, 3, 3, 128, 112, 76, 40,,,, -7, 5, 2, 2, 3, 3, 3, 3, 256, 112, 76, 40,,,, -7, 5, 2, 2, 3, 3, 3, 3, 384, 112, 76, 40,,,, -7, 5, 2, 3, 1, 1, 1, 1, 128, 166, 112, 58,,,, -7, 5, 2, 3, 1, 1, 1, 1, 256, 166, 112, 58,,,, -7, 5, 2, 3, 1, 1, 1, 1, 384, 166, 112, 58,,,, -7, 5, 2, 3, 2, 2, 1, 1, 128, 166, 112, 58,,,, -7, 5, 2, 3, 2, 2, 1, 1, 256, 166, 112, 58,,,, -7, 5, 2, 3, 2, 2, 1, 1, 384, 166, 112, 58,,,, -7, 5, 2, 3, 2, 2, 1, 2, 128, 166, 112, 58,,,, -7, 5, 2, 3, 2, 2, 1, 2, 256, 166, 112, 58,,,, -7, 5, 2, 3, 2, 2, 1, 2, 384, 166, 112, 58,,,, -7, 5, 2, 3, 2, 2, 2, 1, 128, 166, 112, 58,,,, -7, 5, 2, 3, 2, 2, 2, 1, 256, 166, 112, 58,,,, -7, 5, 2, 3, 2, 2, 2, 1, 384, 166, 112, 58,,,, -7, 5, 2, 3, 2, 2, 2, 2, 128, 166, 112, 58,,,, -7, 5, 2, 3, 2, 2, 2, 2, 256, 166, 112, 58,,,, -7, 5, 2, 3, 2, 2, 2, 2, 384, 166, 112, 58,,,, -7, 5, 2, 3, 3, 3, 1, 1, 128, 166, 112, 58,,,, -7, 5, 2, 3, 3, 3, 1, 1, 256, 166, 112, 58,,,, -7, 5, 2, 3, 3, 3, 1, 1, 384, 166, 112, 58,,,, -7, 5, 2, 3, 3, 3, 1, 2, 128, 166, 112, 58,,,, -7, 5, 2, 3, 3, 3, 1, 2, 256, 166, 112, 58,,,, -7, 5, 2, 3, 3, 3, 1, 2, 384, 166, 112, 58,,,, -7, 5, 2, 3, 3, 3, 1, 3, 128, 166, 112, 58,,,, -7, 5, 2, 3, 3, 3, 1, 3, 256, 166, 112, 58,,,, -7, 5, 2, 3, 3, 3, 1, 3, 384, 166, 112, 58,,,, -7, 5, 2, 3, 3, 3, 2, 1, 128, 166, 112, 58,,,, -7, 5, 2, 3, 3, 3, 2, 1, 256, 166, 112, 58,,,, -7, 5, 2, 3, 3, 3, 2, 1, 384, 166, 112, 58,,,, -7, 5, 2, 3, 3, 3, 2, 2, 128, 166, 112, 58,,,, -7, 5, 2, 3, 3, 3, 2, 2, 256, 166, 112, 58,,,, -7, 5, 2, 3, 3, 3, 2, 2, 384, 166, 112, 58,,,, -7, 5, 2, 3, 3, 3, 2, 3, 128, 166, 112, 58,,,, -7, 5, 2, 3, 3, 3, 2, 3, 256, 166, 112, 58,,,, -7, 5, 2, 3, 3, 3, 2, 3, 384, 166, 112, 58,,,, -7, 5, 2, 3, 3, 3, 3, 1, 128, 166, 112, 58,,,, -7, 5, 2, 3, 3, 3, 3, 1, 256, 166, 112, 58,,,, -7, 5, 2, 3, 3, 3, 3, 1, 384, 166, 112, 58,,,, -7, 5, 2, 3, 3, 3, 3, 2, 128, 166, 112, 58,,,, -7, 5, 2, 3, 3, 3, 3, 2, 256, 166, 112, 58,,,, -7, 5, 2, 3, 3, 3, 3, 2, 384, 166, 112, 58,,,, -7, 5, 2, 3, 3, 3, 3, 3, 128, 166, 112, 58,,,, -7, 5, 2, 3, 3, 3, 3, 3, 256, 166, 112, 58,,,, -7, 5, 2, 3, 3, 3, 3, 3, 384, 166, 112, 58,,,, -7, 5, 2, 4, 1, 1, 1, 1, 128, 220, 148, 76,,,, -7, 5, 2, 4, 1, 1, 1, 1, 256, 220, 148, 76,,,, -7, 5, 2, 4, 1, 1, 1, 1, 384, 220, 148, 76,,,, -7, 5, 2, 4, 2, 2, 1, 1, 128, 220, 148, 76,,,, -7, 5, 2, 4, 2, 2, 1, 1, 256, 220, 148, 76,,,, -7, 5, 2, 4, 2, 2, 1, 1, 384, 220, 148, 76,,,, -7, 5, 2, 4, 2, 2, 1, 2, 128, 220, 148, 76,,,, -7, 5, 2, 4, 2, 2, 1, 2, 256, 220, 148, 76,,,, -7, 5, 2, 4, 2, 2, 1, 2, 384, 220, 148, 76,,,, -7, 5, 2, 4, 2, 2, 2, 1, 128, 220, 148, 76,,,, -7, 5, 2, 4, 2, 2, 2, 1, 256, 220, 148, 76,,,, -7, 5, 2, 4, 2, 2, 2, 1, 384, 220, 148, 76,,,, -7, 5, 2, 4, 2, 2, 2, 2, 128, 220, 148, 76,,,, -7, 5, 2, 4, 2, 2, 2, 2, 256, 220, 148, 76,,,, -7, 5, 2, 4, 2, 2, 2, 2, 384, 220, 148, 76,,,, -7, 5, 2, 4, 3, 3, 1, 1, 128, 220, 148, 76,,,, -7, 5, 2, 4, 3, 3, 1, 1, 256, 220, 148, 76,,,, -7, 5, 2, 4, 3, 3, 1, 1, 384, 220, 148, 76,,,, -7, 5, 2, 4, 3, 3, 1, 2, 128, 220, 148, 76,,,, -7, 5, 2, 4, 3, 3, 1, 2, 256, 220, 148, 76,,,, -7, 5, 2, 4, 3, 3, 1, 2, 384, 220, 148, 76,,,, -7, 5, 2, 4, 3, 3, 1, 3, 128, 220, 148, 76,,,, -7, 5, 2, 4, 3, 3, 1, 3, 256, 220, 148, 76,,,, -7, 5, 2, 4, 3, 3, 1, 3, 384, 220, 148, 76,,,, -7, 5, 2, 4, 3, 3, 2, 1, 128, 220, 148, 76,,,, -7, 5, 2, 4, 3, 3, 2, 1, 256, 220, 148, 76,,,, -7, 5, 2, 4, 3, 3, 2, 1, 384, 220, 148, 76,,,, -7, 5, 2, 4, 3, 3, 2, 2, 128, 220, 148, 76,,,, -7, 5, 2, 4, 3, 3, 2, 2, 256, 220, 148, 76,,,, -7, 5, 2, 4, 3, 3, 2, 2, 384, 220, 148, 76,,,, -7, 5, 2, 4, 3, 3, 2, 3, 128, 220, 148, 76,,,, -7, 5, 2, 4, 3, 3, 2, 3, 256, 220, 148, 76,,,, -7, 5, 2, 4, 3, 3, 2, 3, 384, 220, 148, 76,,,, -7, 5, 2, 4, 3, 3, 3, 1, 128, 220, 148, 76,,,, -7, 5, 2, 4, 3, 3, 3, 1, 256, 220, 148, 76,,,, -7, 5, 2, 4, 3, 3, 3, 1, 384, 220, 148, 76,,,, -7, 5, 2, 4, 3, 3, 3, 2, 128, 220, 148, 76,,,, -7, 5, 2, 4, 3, 3, 3, 2, 256, 220, 148, 76,,,, -7, 5, 2, 4, 3, 3, 3, 2, 384, 220, 148, 76,,,, -7, 5, 2, 4, 3, 3, 3, 3, 128, 220, 148, 76,,,, -7, 5, 2, 4, 3, 3, 3, 3, 256, 220, 148, 76,,,, -7, 5, 2, 4, 3, 3, 3, 3, 384, 220, 148, 76,,,, -7, 5, 2, 5, 1, 1, 1, 1, 128, 240, 184, 94,,,, -7, 5, 2, 5, 1, 1, 1, 1, 256, 240, 184, 94,,,, -7, 5, 2, 5, 1, 1, 1, 1, 384, 240, 184, 94,,,, -7, 5, 2, 5, 2, 2, 1, 1, 128, 240, 184, 94,,,, -7, 5, 2, 5, 2, 2, 1, 1, 256, 240, 184, 94,,,, -7, 5, 2, 5, 2, 2, 1, 1, 384, 240, 184, 94,,,, -7, 5, 2, 5, 2, 2, 1, 2, 128, 240, 184, 94,,,, -7, 5, 2, 5, 2, 2, 1, 2, 256, 240, 184, 94,,,, -7, 5, 2, 5, 2, 2, 1, 2, 384, 240, 184, 94,,,, -7, 5, 2, 5, 2, 2, 2, 1, 128, 240, 184, 94,,,, -7, 5, 2, 5, 2, 2, 2, 1, 256, 240, 184, 94,,,, -7, 5, 2, 5, 2, 2, 2, 1, 384, 240, 184, 94,,,, -7, 5, 2, 5, 2, 2, 2, 2, 128, 240, 184, 94,,,, -7, 5, 2, 5, 2, 2, 2, 2, 256, 240, 184, 94,,,, -7, 5, 2, 5, 2, 2, 2, 2, 384, 240, 184, 94,,,, -7, 5, 2, 5, 3, 3, 1, 1, 128, 240, 184, 94,,,, -7, 5, 2, 5, 3, 3, 1, 1, 256, 240, 184, 94,,,, -7, 5, 2, 5, 3, 3, 1, 1, 384, 240, 184, 94,,,, -7, 5, 2, 5, 3, 3, 1, 2, 128, 240, 184, 94,,,, -7, 5, 2, 5, 3, 3, 1, 2, 256, 240, 184, 94,,,, -7, 5, 2, 5, 3, 3, 1, 2, 384, 240, 184, 94,,,, -7, 5, 2, 5, 3, 3, 1, 3, 128, 240, 184, 94,,,, -7, 5, 2, 5, 3, 3, 1, 3, 256, 240, 184, 94,,,, -7, 5, 2, 5, 3, 3, 1, 3, 384, 240, 184, 94,,,, -7, 5, 2, 5, 3, 3, 2, 1, 128, 240, 184, 94,,,, -7, 5, 2, 5, 3, 3, 2, 1, 256, 240, 184, 94,,,, -7, 5, 2, 5, 3, 3, 2, 1, 384, 240, 184, 94,,,, -7, 5, 2, 5, 3, 3, 2, 2, 128, 240, 184, 94,,,, -7, 5, 2, 5, 3, 3, 2, 2, 256, 240, 184, 94,,,, -7, 5, 2, 5, 3, 3, 2, 2, 384, 240, 184, 94,,,, -7, 5, 2, 5, 3, 3, 2, 3, 128, 240, 184, 94,,,, -7, 5, 2, 5, 3, 3, 2, 3, 256, 240, 184, 94,,,, -7, 5, 2, 5, 3, 3, 2, 3, 384, 240, 184, 94,,,, -7, 5, 2, 5, 3, 3, 3, 1, 128, 240, 184, 94,,,, -7, 5, 2, 5, 3, 3, 3, 1, 256, 240, 184, 94,,,, -7, 5, 2, 5, 3, 3, 3, 1, 384, 240, 184, 94,,,, -7, 5, 2, 5, 3, 3, 3, 2, 128, 240, 184, 94,,,, -7, 5, 2, 5, 3, 3, 3, 2, 256, 240, 184, 94,,,, -7, 5, 2, 5, 3, 3, 3, 2, 384, 240, 184, 94,,,, -7, 5, 2, 5, 3, 3, 3, 3, 128, 240, 184, 94,,,, -7, 5, 2, 5, 3, 3, 3, 3, 256, 240, 184, 94,,,, -7, 5, 2, 5, 3, 3, 3, 3, 384, 240, 184, 94,,,, -7, 5, 3, 1, 1, 1, 1, 1, 128, 58, 40, 22,,,, -7, 5, 3, 1, 1, 1, 1, 1, 256, 58, 40, 22,,,, -7, 5, 3, 1, 1, 1, 1, 1, 384, 58, 40, 22,,,, -7, 5, 3, 1, 2, 2, 1, 1, 128, 58, 40, 22,,,, -7, 5, 3, 1, 2, 2, 1, 1, 256, 58, 40, 22,,,, -7, 5, 3, 1, 2, 2, 1, 1, 384, 58, 40, 22,,,, -7, 5, 3, 1, 2, 2, 1, 2, 128, 58, 40, 22,,,, -7, 5, 3, 1, 2, 2, 1, 2, 256, 58, 40, 22,,,, -7, 5, 3, 1, 2, 2, 1, 2, 384, 58, 40, 22,,,, -7, 5, 3, 1, 2, 2, 2, 1, 128, 58, 40, 22,,,, -7, 5, 3, 1, 2, 2, 2, 1, 256, 58, 40, 22,,,, -7, 5, 3, 1, 2, 2, 2, 1, 384, 58, 40, 22,,,, -7, 5, 3, 1, 2, 2, 2, 2, 128, 58, 40, 22,,,, -7, 5, 3, 1, 2, 2, 2, 2, 256, 58, 40, 22,,,, -7, 5, 3, 1, 2, 2, 2, 2, 384, 58, 40, 22,,,, -7, 5, 3, 1, 3, 3, 1, 1, 128, 58, 40, 22,,,, -7, 5, 3, 1, 3, 3, 1, 1, 256, 58, 40, 22,,,, -7, 5, 3, 1, 3, 3, 1, 1, 384, 58, 40, 22,,,, -7, 5, 3, 1, 3, 3, 1, 2, 128, 58, 40, 22,,,, -7, 5, 3, 1, 3, 3, 1, 2, 256, 58, 40, 22,,,, -7, 5, 3, 1, 3, 3, 1, 2, 384, 58, 40, 22,,,, -7, 5, 3, 1, 3, 3, 1, 3, 128, 58, 40, 22,,,, -7, 5, 3, 1, 3, 3, 1, 3, 256, 58, 40, 22,,,, -7, 5, 3, 1, 3, 3, 1, 3, 384, 58, 40, 22,,,, -7, 5, 3, 1, 3, 3, 2, 1, 128, 58, 40, 22,,,, -7, 5, 3, 1, 3, 3, 2, 1, 256, 58, 40, 22,,,, -7, 5, 3, 1, 3, 3, 2, 1, 384, 58, 40, 22,,,, -7, 5, 3, 1, 3, 3, 2, 2, 128, 58, 40, 22,,,, -7, 5, 3, 1, 3, 3, 2, 2, 256, 58, 40, 22,,,, -7, 5, 3, 1, 3, 3, 2, 2, 384, 58, 40, 22,,,, -7, 5, 3, 1, 3, 3, 2, 3, 128, 58, 40, 22,,,, -7, 5, 3, 1, 3, 3, 2, 3, 256, 58, 40, 22,,,, -7, 5, 3, 1, 3, 3, 2, 3, 384, 58, 40, 22,,,, -7, 5, 3, 1, 3, 3, 3, 1, 128, 58, 40, 22,,,, -7, 5, 3, 1, 3, 3, 3, 1, 256, 58, 40, 22,,,, -7, 5, 3, 1, 3, 3, 3, 1, 384, 58, 40, 22,,,, -7, 5, 3, 1, 3, 3, 3, 2, 128, 58, 40, 22,,,, -7, 5, 3, 1, 3, 3, 3, 2, 256, 58, 40, 22,,,, -7, 5, 3, 1, 3, 3, 3, 2, 384, 58, 40, 22,,,, -7, 5, 3, 1, 3, 3, 3, 3, 128, 58, 40, 22,,,, -7, 5, 3, 1, 3, 3, 3, 3, 256, 58, 40, 22,,,, -7, 5, 3, 1, 3, 3, 3, 3, 384, 58, 40, 22,,,, -7, 5, 3, 2, 1, 1, 1, 1, 128, 112, 76, 40,,,, -7, 5, 3, 2, 1, 1, 1, 1, 256, 112, 76, 40,,,, -7, 5, 3, 2, 1, 1, 1, 1, 384, 112, 76, 40,,,, -7, 5, 3, 2, 2, 2, 1, 1, 128, 112, 76, 40,,,, -7, 5, 3, 2, 2, 2, 1, 1, 256, 112, 76, 40,,,, -7, 5, 3, 2, 2, 2, 1, 1, 384, 112, 76, 40,,,, -7, 5, 3, 2, 2, 2, 1, 2, 128, 112, 76, 40,,,, -7, 5, 3, 2, 2, 2, 1, 2, 256, 112, 76, 40,,,, -7, 5, 3, 2, 2, 2, 1, 2, 384, 112, 76, 40,,,, -7, 5, 3, 2, 2, 2, 2, 1, 128, 112, 76, 40,,,, -7, 5, 3, 2, 2, 2, 2, 1, 256, 112, 76, 40,,,, -7, 5, 3, 2, 2, 2, 2, 1, 384, 112, 76, 40,,,, -7, 5, 3, 2, 2, 2, 2, 2, 128, 112, 76, 40,,,, -7, 5, 3, 2, 2, 2, 2, 2, 256, 112, 76, 40,,,, -7, 5, 3, 2, 2, 2, 2, 2, 384, 112, 76, 40,,,, -7, 5, 3, 2, 3, 3, 1, 1, 128, 112, 76, 40,,,, -7, 5, 3, 2, 3, 3, 1, 1, 256, 112, 76, 40,,,, -7, 5, 3, 2, 3, 3, 1, 1, 384, 112, 76, 40,,,, -7, 5, 3, 2, 3, 3, 1, 2, 128, 112, 76, 40,,,, -7, 5, 3, 2, 3, 3, 1, 2, 256, 112, 76, 40,,,, -7, 5, 3, 2, 3, 3, 1, 2, 384, 112, 76, 40,,,, -7, 5, 3, 2, 3, 3, 1, 3, 128, 112, 76, 40,,,, -7, 5, 3, 2, 3, 3, 1, 3, 256, 112, 76, 40,,,, -7, 5, 3, 2, 3, 3, 1, 3, 384, 112, 76, 40,,,, -7, 5, 3, 2, 3, 3, 2, 1, 128, 112, 76, 40,,,, -7, 5, 3, 2, 3, 3, 2, 1, 256, 112, 76, 40,,,, -7, 5, 3, 2, 3, 3, 2, 1, 384, 112, 76, 40,,,, -7, 5, 3, 2, 3, 3, 2, 2, 128, 112, 76, 40,,,, -7, 5, 3, 2, 3, 3, 2, 2, 256, 112, 76, 40,,,, -7, 5, 3, 2, 3, 3, 2, 2, 384, 112, 76, 40,,,, -7, 5, 3, 2, 3, 3, 2, 3, 128, 112, 76, 40,,,, -7, 5, 3, 2, 3, 3, 2, 3, 256, 112, 76, 40,,,, -7, 5, 3, 2, 3, 3, 2, 3, 384, 112, 76, 40,,,, -7, 5, 3, 2, 3, 3, 3, 1, 128, 112, 76, 40,,,, -7, 5, 3, 2, 3, 3, 3, 1, 256, 112, 76, 40,,,, -7, 5, 3, 2, 3, 3, 3, 1, 384, 112, 76, 40,,,, -7, 5, 3, 2, 3, 3, 3, 2, 128, 112, 76, 40,,,, -7, 5, 3, 2, 3, 3, 3, 2, 256, 112, 76, 40,,,, -7, 5, 3, 2, 3, 3, 3, 2, 384, 112, 76, 40,,,, -7, 5, 3, 2, 3, 3, 3, 3, 128, 112, 76, 40,,,, -7, 5, 3, 2, 3, 3, 3, 3, 256, 112, 76, 40,,,, -7, 5, 3, 2, 3, 3, 3, 3, 384, 112, 76, 40,,,, -7, 5, 3, 3, 1, 1, 1, 1, 128, 166, 112, 58,,,, -7, 5, 3, 3, 1, 1, 1, 1, 256, 166, 112, 58,,,, -7, 5, 3, 3, 1, 1, 1, 1, 384, 166, 112, 58,,,, -7, 5, 3, 3, 2, 2, 1, 1, 128, 166, 112, 58,,,, -7, 5, 3, 3, 2, 2, 1, 1, 256, 166, 112, 58,,,, -7, 5, 3, 3, 2, 2, 1, 1, 384, 166, 112, 58,,,, -7, 5, 3, 3, 2, 2, 1, 2, 128, 166, 112, 58,,,, -7, 5, 3, 3, 2, 2, 1, 2, 256, 166, 112, 58,,,, -7, 5, 3, 3, 2, 2, 1, 2, 384, 166, 112, 58,,,, -7, 5, 3, 3, 2, 2, 2, 1, 128, 166, 112, 58,,,, -7, 5, 3, 3, 2, 2, 2, 1, 256, 166, 112, 58,,,, -7, 5, 3, 3, 2, 2, 2, 1, 384, 166, 112, 58,,,, -7, 5, 3, 3, 2, 2, 2, 2, 128, 166, 112, 58,,,, -7, 5, 3, 3, 2, 2, 2, 2, 256, 166, 112, 58,,,, -7, 5, 3, 3, 2, 2, 2, 2, 384, 166, 112, 58,,,, -7, 5, 3, 3, 3, 3, 1, 1, 128, 166, 112, 58,,,, -7, 5, 3, 3, 3, 3, 1, 1, 256, 166, 112, 58,,,, -7, 5, 3, 3, 3, 3, 1, 1, 384, 166, 112, 58,,,, -7, 5, 3, 3, 3, 3, 1, 2, 128, 166, 112, 58,,,, -7, 5, 3, 3, 3, 3, 1, 2, 256, 166, 112, 58,,,, -7, 5, 3, 3, 3, 3, 1, 2, 384, 166, 112, 58,,,, -7, 5, 3, 3, 3, 3, 1, 3, 128, 166, 112, 58,,,, -7, 5, 3, 3, 3, 3, 1, 3, 256, 166, 112, 58,,,, -7, 5, 3, 3, 3, 3, 1, 3, 384, 166, 112, 58,,,, -7, 5, 3, 3, 3, 3, 2, 1, 128, 166, 112, 58,,,, -7, 5, 3, 3, 3, 3, 2, 1, 256, 166, 112, 58,,,, -7, 5, 3, 3, 3, 3, 2, 1, 384, 166, 112, 58,,,, -7, 5, 3, 3, 3, 3, 2, 2, 128, 166, 112, 58,,,, -7, 5, 3, 3, 3, 3, 2, 2, 256, 166, 112, 58,,,, -7, 5, 3, 3, 3, 3, 2, 2, 384, 166, 112, 58,,,, -7, 5, 3, 3, 3, 3, 2, 3, 128, 166, 112, 58,,,, -7, 5, 3, 3, 3, 3, 2, 3, 256, 166, 112, 58,,,, -7, 5, 3, 3, 3, 3, 2, 3, 384, 166, 112, 58,,,, -7, 5, 3, 3, 3, 3, 3, 1, 128, 166, 112, 58,,,, -7, 5, 3, 3, 3, 3, 3, 1, 256, 166, 112, 58,,,, -7, 5, 3, 3, 3, 3, 3, 1, 384, 166, 112, 58,,,, -7, 5, 3, 3, 3, 3, 3, 2, 128, 166, 112, 58,,,, -7, 5, 3, 3, 3, 3, 3, 2, 256, 166, 112, 58,,,, -7, 5, 3, 3, 3, 3, 3, 2, 384, 166, 112, 58,,,, -7, 5, 3, 3, 3, 3, 3, 3, 128, 166, 112, 58,,,, -7, 5, 3, 3, 3, 3, 3, 3, 256, 166, 112, 58,,,, -7, 5, 3, 3, 3, 3, 3, 3, 384, 166, 112, 58,,,, -7, 5, 3, 4, 1, 1, 1, 1, 128, 220, 148, 76,,,, -7, 5, 3, 4, 1, 1, 1, 1, 256, 220, 148, 76,,,, -7, 5, 3, 4, 1, 1, 1, 1, 384, 220, 148, 76,,,, -7, 5, 3, 4, 2, 2, 1, 1, 128, 220, 148, 76,,,, -7, 5, 3, 4, 2, 2, 1, 1, 256, 220, 148, 76,,,, -7, 5, 3, 4, 2, 2, 1, 1, 384, 220, 148, 76,,,, -7, 5, 3, 4, 2, 2, 1, 2, 128, 220, 148, 76,,,, -7, 5, 3, 4, 2, 2, 1, 2, 256, 220, 148, 76,,,, -7, 5, 3, 4, 2, 2, 1, 2, 384, 220, 148, 76,,,, -7, 5, 3, 4, 2, 2, 2, 1, 128, 220, 148, 76,,,, -7, 5, 3, 4, 2, 2, 2, 1, 256, 220, 148, 76,,,, -7, 5, 3, 4, 2, 2, 2, 1, 384, 220, 148, 76,,,, -7, 5, 3, 4, 2, 2, 2, 2, 128, 220, 148, 76,,,, -7, 5, 3, 4, 2, 2, 2, 2, 256, 220, 148, 76,,,, -7, 5, 3, 4, 2, 2, 2, 2, 384, 220, 148, 76,,,, -7, 5, 3, 4, 3, 3, 1, 1, 128, 220, 148, 76,,,, -7, 5, 3, 4, 3, 3, 1, 1, 256, 220, 148, 76,,,, -7, 5, 3, 4, 3, 3, 1, 1, 384, 220, 148, 76,,,, -7, 5, 3, 4, 3, 3, 1, 2, 128, 220, 148, 76,,,, -7, 5, 3, 4, 3, 3, 1, 2, 256, 220, 148, 76,,,, -7, 5, 3, 4, 3, 3, 1, 2, 384, 220, 148, 76,,,, -7, 5, 3, 4, 3, 3, 1, 3, 128, 220, 148, 76,,,, -7, 5, 3, 4, 3, 3, 1, 3, 256, 220, 148, 76,,,, -7, 5, 3, 4, 3, 3, 1, 3, 384, 220, 148, 76,,,, -7, 5, 3, 4, 3, 3, 2, 1, 128, 220, 148, 76,,,, -7, 5, 3, 4, 3, 3, 2, 1, 256, 220, 148, 76,,,, -7, 5, 3, 4, 3, 3, 2, 1, 384, 220, 148, 76,,,, -7, 5, 3, 4, 3, 3, 2, 2, 128, 220, 148, 76,,,, -7, 5, 3, 4, 3, 3, 2, 2, 256, 220, 148, 76,,,, -7, 5, 3, 4, 3, 3, 2, 2, 384, 220, 148, 76,,,, -7, 5, 3, 4, 3, 3, 2, 3, 128, 220, 148, 76,,,, -7, 5, 3, 4, 3, 3, 2, 3, 256, 220, 148, 76,,,, -7, 5, 3, 4, 3, 3, 2, 3, 384, 220, 148, 76,,,, -7, 5, 3, 4, 3, 3, 3, 1, 128, 220, 148, 76,,,, -7, 5, 3, 4, 3, 3, 3, 1, 256, 220, 148, 76,,,, -7, 5, 3, 4, 3, 3, 3, 1, 384, 220, 148, 76,,,, -7, 5, 3, 4, 3, 3, 3, 2, 128, 220, 148, 76,,,, -7, 5, 3, 4, 3, 3, 3, 2, 256, 220, 148, 76,,,, -7, 5, 3, 4, 3, 3, 3, 2, 384, 220, 148, 76,,,, -7, 5, 3, 4, 3, 3, 3, 3, 128, 220, 148, 76,,,, -7, 5, 3, 4, 3, 3, 3, 3, 256, 220, 148, 76,,,, -7, 5, 3, 4, 3, 3, 3, 3, 384, 220, 148, 76,,,, -7, 5, 3, 5, 1, 1, 1, 1, 128, 240, 184, 94,,,, -7, 5, 3, 5, 1, 1, 1, 1, 256, 240, 184, 94,,,, -7, 5, 3, 5, 1, 1, 1, 1, 384, 240, 184, 94,,,, -7, 5, 3, 5, 2, 2, 1, 1, 128, 240, 184, 94,,,, -7, 5, 3, 5, 2, 2, 1, 1, 256, 240, 184, 94,,,, -7, 5, 3, 5, 2, 2, 1, 1, 384, 240, 184, 94,,,, -7, 5, 3, 5, 2, 2, 1, 2, 128, 240, 184, 94,,,, -7, 5, 3, 5, 2, 2, 1, 2, 256, 240, 184, 94,,,, -7, 5, 3, 5, 2, 2, 1, 2, 384, 240, 184, 94,,,, -7, 5, 3, 5, 2, 2, 2, 1, 128, 240, 184, 94,,,, -7, 5, 3, 5, 2, 2, 2, 1, 256, 240, 184, 94,,,, -7, 5, 3, 5, 2, 2, 2, 1, 384, 240, 184, 94,,,, -7, 5, 3, 5, 2, 2, 2, 2, 128, 240, 184, 94,,,, -7, 5, 3, 5, 2, 2, 2, 2, 256, 240, 184, 94,,,, -7, 5, 3, 5, 2, 2, 2, 2, 384, 240, 184, 94,,,, -7, 5, 3, 5, 3, 3, 1, 1, 128, 240, 184, 94,,,, -7, 5, 3, 5, 3, 3, 1, 1, 256, 240, 184, 94,,,, -7, 5, 3, 5, 3, 3, 1, 1, 384, 240, 184, 94,,,, -7, 5, 3, 5, 3, 3, 1, 2, 128, 240, 184, 94,,,, -7, 5, 3, 5, 3, 3, 1, 2, 256, 240, 184, 94,,,, -7, 5, 3, 5, 3, 3, 1, 2, 384, 240, 184, 94,,,, -7, 5, 3, 5, 3, 3, 1, 3, 128, 240, 184, 94,,,, -7, 5, 3, 5, 3, 3, 1, 3, 256, 240, 184, 94,,,, -7, 5, 3, 5, 3, 3, 1, 3, 384, 240, 184, 94,,,, -7, 5, 3, 5, 3, 3, 2, 1, 128, 240, 184, 94,,,, -7, 5, 3, 5, 3, 3, 2, 1, 256, 240, 184, 94,,,, -7, 5, 3, 5, 3, 3, 2, 1, 384, 240, 184, 94,,,, -7, 5, 3, 5, 3, 3, 2, 2, 128, 240, 184, 94,,,, -7, 5, 3, 5, 3, 3, 2, 2, 256, 240, 184, 94,,,, -7, 5, 3, 5, 3, 3, 2, 2, 384, 240, 184, 94,,,, -7, 5, 3, 5, 3, 3, 2, 3, 128, 240, 184, 94,,,, -7, 5, 3, 5, 3, 3, 2, 3, 256, 240, 184, 94,,,, -7, 5, 3, 5, 3, 3, 2, 3, 384, 240, 184, 94,,,, -7, 5, 3, 5, 3, 3, 3, 1, 128, 240, 184, 94,,,, -7, 5, 3, 5, 3, 3, 3, 1, 256, 240, 184, 94,,,, -7, 5, 3, 5, 3, 3, 3, 1, 384, 240, 184, 94,,,, -7, 5, 3, 5, 3, 3, 3, 2, 128, 240, 184, 94,,,, -7, 5, 3, 5, 3, 3, 3, 2, 256, 240, 184, 94,,,, -7, 5, 3, 5, 3, 3, 3, 2, 384, 240, 184, 94,,,, -7, 5, 3, 5, 3, 3, 3, 3, 128, 240, 184, 94,,,, -7, 5, 3, 5, 3, 3, 3, 3, 256, 240, 184, 94,,,, -7, 5, 3, 5, 3, 3, 3, 3, 384, 240, 184, 94,,,, -7, 5, 4, 1, 1, 1, 1, 1, 128, 58, 40, 22,,,, -7, 5, 4, 1, 1, 1, 1, 1, 256, 58, 40, 22,,,, -7, 5, 4, 1, 1, 1, 1, 1, 384, 58, 40, 22,,,, -7, 5, 4, 1, 2, 2, 1, 1, 128, 58, 40, 22,,,, -7, 5, 4, 1, 2, 2, 1, 1, 256, 58, 40, 22,,,, -7, 5, 4, 1, 2, 2, 1, 1, 384, 58, 40, 22,,,, -7, 5, 4, 1, 2, 2, 1, 2, 128, 58, 40, 22,,,, -7, 5, 4, 1, 2, 2, 1, 2, 256, 58, 40, 22,,,, -7, 5, 4, 1, 2, 2, 1, 2, 384, 58, 40, 22,,,, -7, 5, 4, 1, 2, 2, 2, 1, 128, 58, 40, 22,,,, -7, 5, 4, 1, 2, 2, 2, 1, 256, 58, 40, 22,,,, -7, 5, 4, 1, 2, 2, 2, 1, 384, 58, 40, 22,,,, -7, 5, 4, 1, 2, 2, 2, 2, 128, 58, 40, 22,,,, -7, 5, 4, 1, 2, 2, 2, 2, 256, 58, 40, 22,,,, -7, 5, 4, 1, 2, 2, 2, 2, 384, 58, 40, 22,,,, -7, 5, 4, 1, 3, 3, 1, 1, 128, 58, 40, 22,,,, -7, 5, 4, 1, 3, 3, 1, 1, 256, 58, 40, 22,,,, -7, 5, 4, 1, 3, 3, 1, 1, 384, 58, 40, 22,,,, -7, 5, 4, 1, 3, 3, 1, 2, 128, 58, 40, 22,,,, -7, 5, 4, 1, 3, 3, 1, 2, 256, 58, 40, 22,,,, -7, 5, 4, 1, 3, 3, 1, 2, 384, 58, 40, 22,,,, -7, 5, 4, 1, 3, 3, 1, 3, 128, 58, 40, 22,,,, -7, 5, 4, 1, 3, 3, 1, 3, 256, 58, 40, 22,,,, -7, 5, 4, 1, 3, 3, 1, 3, 384, 58, 40, 22,,,, -7, 5, 4, 1, 3, 3, 2, 1, 128, 58, 40, 22,,,, -7, 5, 4, 1, 3, 3, 2, 1, 256, 58, 40, 22,,,, -7, 5, 4, 1, 3, 3, 2, 1, 384, 58, 40, 22,,,, -7, 5, 4, 1, 3, 3, 2, 2, 128, 58, 40, 22,,,, -7, 5, 4, 1, 3, 3, 2, 2, 256, 58, 40, 22,,,, -7, 5, 4, 1, 3, 3, 2, 2, 384, 58, 40, 22,,,, -7, 5, 4, 1, 3, 3, 2, 3, 128, 58, 40, 22,,,, -7, 5, 4, 1, 3, 3, 2, 3, 256, 58, 40, 22,,,, -7, 5, 4, 1, 3, 3, 2, 3, 384, 58, 40, 22,,,, -7, 5, 4, 1, 3, 3, 3, 1, 128, 58, 40, 22,,,, -7, 5, 4, 1, 3, 3, 3, 1, 256, 58, 40, 22,,,, -7, 5, 4, 1, 3, 3, 3, 1, 384, 58, 40, 22,,,, -7, 5, 4, 1, 3, 3, 3, 2, 128, 58, 40, 22,,,, -7, 5, 4, 1, 3, 3, 3, 2, 256, 58, 40, 22,,,, -7, 5, 4, 1, 3, 3, 3, 2, 384, 58, 40, 22,,,, -7, 5, 4, 1, 3, 3, 3, 3, 128, 58, 40, 22,,,, -7, 5, 4, 1, 3, 3, 3, 3, 256, 58, 40, 22,,,, -7, 5, 4, 1, 3, 3, 3, 3, 384, 58, 40, 22,,,, -7, 5, 4, 2, 1, 1, 1, 1, 128, 112, 76, 40,,,, -7, 5, 4, 2, 1, 1, 1, 1, 256, 112, 76, 40,,,, -7, 5, 4, 2, 1, 1, 1, 1, 384, 112, 76, 40,,,, -7, 5, 4, 2, 2, 2, 1, 1, 128, 112, 76, 40,,,, -7, 5, 4, 2, 2, 2, 1, 1, 256, 112, 76, 40,,,, -7, 5, 4, 2, 2, 2, 1, 1, 384, 112, 76, 40,,,, -7, 5, 4, 2, 2, 2, 1, 2, 128, 112, 76, 40,,,, -7, 5, 4, 2, 2, 2, 1, 2, 256, 112, 76, 40,,,, -7, 5, 4, 2, 2, 2, 1, 2, 384, 112, 76, 40,,,, -7, 5, 4, 2, 2, 2, 2, 1, 128, 112, 76, 40,,,, -7, 5, 4, 2, 2, 2, 2, 1, 256, 112, 76, 40,,,, -7, 5, 4, 2, 2, 2, 2, 1, 384, 112, 76, 40,,,, -7, 5, 4, 2, 2, 2, 2, 2, 128, 112, 76, 40,,,, -7, 5, 4, 2, 2, 2, 2, 2, 256, 112, 76, 40,,,, -7, 5, 4, 2, 2, 2, 2, 2, 384, 112, 76, 40,,,, -7, 5, 4, 2, 3, 3, 1, 1, 128, 112, 76, 40,,,, -7, 5, 4, 2, 3, 3, 1, 1, 256, 112, 76, 40,,,, -7, 5, 4, 2, 3, 3, 1, 1, 384, 112, 76, 40,,,, -7, 5, 4, 2, 3, 3, 1, 2, 128, 112, 76, 40,,,, -7, 5, 4, 2, 3, 3, 1, 2, 256, 112, 76, 40,,,, -7, 5, 4, 2, 3, 3, 1, 2, 384, 112, 76, 40,,,, -7, 5, 4, 2, 3, 3, 1, 3, 128, 112, 76, 40,,,, -7, 5, 4, 2, 3, 3, 1, 3, 256, 112, 76, 40,,,, -7, 5, 4, 2, 3, 3, 1, 3, 384, 112, 76, 40,,,, -7, 5, 4, 2, 3, 3, 2, 1, 128, 112, 76, 40,,,, -7, 5, 4, 2, 3, 3, 2, 1, 256, 112, 76, 40,,,, -7, 5, 4, 2, 3, 3, 2, 1, 384, 112, 76, 40,,,, -7, 5, 4, 2, 3, 3, 2, 2, 128, 112, 76, 40,,,, -7, 5, 4, 2, 3, 3, 2, 2, 256, 112, 76, 40,,,, -7, 5, 4, 2, 3, 3, 2, 2, 384, 112, 76, 40,,,, -7, 5, 4, 2, 3, 3, 2, 3, 128, 112, 76, 40,,,, -7, 5, 4, 2, 3, 3, 2, 3, 256, 112, 76, 40,,,, -7, 5, 4, 2, 3, 3, 2, 3, 384, 112, 76, 40,,,, -7, 5, 4, 2, 3, 3, 3, 1, 128, 112, 76, 40,,,, -7, 5, 4, 2, 3, 3, 3, 1, 256, 112, 76, 40,,,, -7, 5, 4, 2, 3, 3, 3, 1, 384, 112, 76, 40,,,, -7, 5, 4, 2, 3, 3, 3, 2, 128, 112, 76, 40,,,, -7, 5, 4, 2, 3, 3, 3, 2, 256, 112, 76, 40,,,, -7, 5, 4, 2, 3, 3, 3, 2, 384, 112, 76, 40,,,, -7, 5, 4, 2, 3, 3, 3, 3, 128, 112, 76, 40,,,, -7, 5, 4, 2, 3, 3, 3, 3, 256, 112, 76, 40,,,, -7, 5, 4, 2, 3, 3, 3, 3, 384, 112, 76, 40,,,, -7, 5, 4, 3, 1, 1, 1, 1, 128, 166, 112, 58,,,, -7, 5, 4, 3, 1, 1, 1, 1, 256, 166, 112, 58,,,, -7, 5, 4, 3, 1, 1, 1, 1, 384, 166, 112, 58,,,, -7, 5, 4, 3, 2, 2, 1, 1, 128, 166, 112, 58,,,, -7, 5, 4, 3, 2, 2, 1, 1, 256, 166, 112, 58,,,, -7, 5, 4, 3, 2, 2, 1, 1, 384, 166, 112, 58,,,, -7, 5, 4, 3, 2, 2, 1, 2, 128, 166, 112, 58,,,, -7, 5, 4, 3, 2, 2, 1, 2, 256, 166, 112, 58,,,, -7, 5, 4, 3, 2, 2, 1, 2, 384, 166, 112, 58,,,, -7, 5, 4, 3, 2, 2, 2, 1, 128, 166, 112, 58,,,, -7, 5, 4, 3, 2, 2, 2, 1, 256, 166, 112, 58,,,, -7, 5, 4, 3, 2, 2, 2, 1, 384, 166, 112, 58,,,, -7, 5, 4, 3, 2, 2, 2, 2, 128, 166, 112, 58,,,, -7, 5, 4, 3, 2, 2, 2, 2, 256, 166, 112, 58,,,, -7, 5, 4, 3, 2, 2, 2, 2, 384, 166, 112, 58,,,, -7, 5, 4, 3, 3, 3, 1, 1, 128, 166, 112, 58,,,, -7, 5, 4, 3, 3, 3, 1, 1, 256, 166, 112, 58,,,, -7, 5, 4, 3, 3, 3, 1, 1, 384, 166, 112, 58,,,, -7, 5, 4, 3, 3, 3, 1, 2, 128, 166, 112, 58,,,, -7, 5, 4, 3, 3, 3, 1, 2, 256, 166, 112, 58,,,, -7, 5, 4, 3, 3, 3, 1, 2, 384, 166, 112, 58,,,, -7, 5, 4, 3, 3, 3, 1, 3, 128, 166, 112, 58,,,, -7, 5, 4, 3, 3, 3, 1, 3, 256, 166, 112, 58,,,, -7, 5, 4, 3, 3, 3, 1, 3, 384, 166, 112, 58,,,, -7, 5, 4, 3, 3, 3, 2, 1, 128, 166, 112, 58,,,, -7, 5, 4, 3, 3, 3, 2, 1, 256, 166, 112, 58,,,, -7, 5, 4, 3, 3, 3, 2, 1, 384, 166, 112, 58,,,, -7, 5, 4, 3, 3, 3, 2, 2, 128, 166, 112, 58,,,, -7, 5, 4, 3, 3, 3, 2, 2, 256, 166, 112, 58,,,, -7, 5, 4, 3, 3, 3, 2, 2, 384, 166, 112, 58,,,, -7, 5, 4, 3, 3, 3, 2, 3, 128, 166, 112, 58,,,, -7, 5, 4, 3, 3, 3, 2, 3, 256, 166, 112, 58,,,, -7, 5, 4, 3, 3, 3, 2, 3, 384, 166, 112, 58,,,, -7, 5, 4, 3, 3, 3, 3, 1, 128, 166, 112, 58,,,, -7, 5, 4, 3, 3, 3, 3, 1, 256, 166, 112, 58,,,, -7, 5, 4, 3, 3, 3, 3, 1, 384, 166, 112, 58,,,, -7, 5, 4, 3, 3, 3, 3, 2, 128, 166, 112, 58,,,, -7, 5, 4, 3, 3, 3, 3, 2, 256, 166, 112, 58,,,, -7, 5, 4, 3, 3, 3, 3, 2, 384, 166, 112, 58,,,, -7, 5, 4, 3, 3, 3, 3, 3, 128, 166, 112, 58,,,, -7, 5, 4, 3, 3, 3, 3, 3, 256, 166, 112, 58,,,, -7, 5, 4, 3, 3, 3, 3, 3, 384, 166, 112, 58,,,, -7, 5, 4, 4, 1, 1, 1, 1, 128, 220, 148, 76,,,, -7, 5, 4, 4, 1, 1, 1, 1, 256, 220, 148, 76,,,, -7, 5, 4, 4, 1, 1, 1, 1, 384, 220, 148, 76,,,, -7, 5, 4, 4, 2, 2, 1, 1, 128, 220, 148, 76,,,, -7, 5, 4, 4, 2, 2, 1, 1, 256, 220, 148, 76,,,, -7, 5, 4, 4, 2, 2, 1, 1, 384, 220, 148, 76,,,, -7, 5, 4, 4, 2, 2, 1, 2, 128, 220, 148, 76,,,, -7, 5, 4, 4, 2, 2, 1, 2, 256, 220, 148, 76,,,, -7, 5, 4, 4, 2, 2, 1, 2, 384, 220, 148, 76,,,, -7, 5, 4, 4, 2, 2, 2, 1, 128, 220, 148, 76,,,, -7, 5, 4, 4, 2, 2, 2, 1, 256, 220, 148, 76,,,, -7, 5, 4, 4, 2, 2, 2, 1, 384, 220, 148, 76,,,, -7, 5, 4, 4, 2, 2, 2, 2, 128, 220, 148, 76,,,, -7, 5, 4, 4, 2, 2, 2, 2, 256, 220, 148, 76,,,, -7, 5, 4, 4, 2, 2, 2, 2, 384, 220, 148, 76,,,, -7, 5, 4, 4, 3, 3, 1, 1, 128, 220, 148, 76,,,, -7, 5, 4, 4, 3, 3, 1, 1, 256, 220, 148, 76,,,, -7, 5, 4, 4, 3, 3, 1, 1, 384, 220, 148, 76,,,, -7, 5, 4, 4, 3, 3, 1, 2, 128, 220, 148, 76,,,, -7, 5, 4, 4, 3, 3, 1, 2, 256, 220, 148, 76,,,, -7, 5, 4, 4, 3, 3, 1, 2, 384, 220, 148, 76,,,, -7, 5, 4, 4, 3, 3, 1, 3, 128, 220, 148, 76,,,, -7, 5, 4, 4, 3, 3, 1, 3, 256, 220, 148, 76,,,, -7, 5, 4, 4, 3, 3, 1, 3, 384, 220, 148, 76,,,, -7, 5, 4, 4, 3, 3, 2, 1, 128, 220, 148, 76,,,, -7, 5, 4, 4, 3, 3, 2, 1, 256, 220, 148, 76,,,, -7, 5, 4, 4, 3, 3, 2, 1, 384, 220, 148, 76,,,, -7, 5, 4, 4, 3, 3, 2, 2, 128, 220, 148, 76,,,, -7, 5, 4, 4, 3, 3, 2, 2, 256, 220, 148, 76,,,, -7, 5, 4, 4, 3, 3, 2, 2, 384, 220, 148, 76,,,, -7, 5, 4, 4, 3, 3, 2, 3, 128, 220, 148, 76,,,, -7, 5, 4, 4, 3, 3, 2, 3, 256, 220, 148, 76,,,, -7, 5, 4, 4, 3, 3, 2, 3, 384, 220, 148, 76,,,, -7, 5, 4, 4, 3, 3, 3, 1, 128, 220, 148, 76,,,, -7, 5, 4, 4, 3, 3, 3, 1, 256, 220, 148, 76,,,, -7, 5, 4, 4, 3, 3, 3, 1, 384, 220, 148, 76,,,, -7, 5, 4, 4, 3, 3, 3, 2, 128, 220, 148, 76,,,, -7, 5, 4, 4, 3, 3, 3, 2, 256, 220, 148, 76,,,, -7, 5, 4, 4, 3, 3, 3, 2, 384, 220, 148, 76,,,, -7, 5, 4, 4, 3, 3, 3, 3, 128, 220, 148, 76,,,, -7, 5, 4, 4, 3, 3, 3, 3, 256, 220, 148, 76,,,, -7, 5, 4, 4, 3, 3, 3, 3, 384, 220, 148, 76,,,, -7, 5, 4, 5, 1, 1, 1, 1, 128, 240, 184, 94,,,, -7, 5, 4, 5, 1, 1, 1, 1, 256, 240, 184, 94,,,, -7, 5, 4, 5, 1, 1, 1, 1, 384, 240, 184, 94,,,, -7, 5, 4, 5, 2, 2, 1, 1, 128, 240, 184, 94,,,, -7, 5, 4, 5, 2, 2, 1, 1, 256, 240, 184, 94,,,, -7, 5, 4, 5, 2, 2, 1, 1, 384, 240, 184, 94,,,, -7, 5, 4, 5, 2, 2, 1, 2, 128, 240, 184, 94,,,, -7, 5, 4, 5, 2, 2, 1, 2, 256, 240, 184, 94,,,, -7, 5, 4, 5, 2, 2, 1, 2, 384, 240, 184, 94,,,, -7, 5, 4, 5, 2, 2, 2, 1, 128, 240, 184, 94,,,, -7, 5, 4, 5, 2, 2, 2, 1, 256, 240, 184, 94,,,, -7, 5, 4, 5, 2, 2, 2, 1, 384, 240, 184, 94,,,, -7, 5, 4, 5, 2, 2, 2, 2, 128, 240, 184, 94,,,, -7, 5, 4, 5, 2, 2, 2, 2, 256, 240, 184, 94,,,, -7, 5, 4, 5, 2, 2, 2, 2, 384, 240, 184, 94,,,, -7, 5, 4, 5, 3, 3, 1, 1, 128, 240, 184, 94,,,, -7, 5, 4, 5, 3, 3, 1, 1, 256, 240, 184, 94,,,, -7, 5, 4, 5, 3, 3, 1, 1, 384, 240, 184, 94,,,, -7, 5, 4, 5, 3, 3, 1, 2, 128, 240, 184, 94,,,, -7, 5, 4, 5, 3, 3, 1, 2, 256, 240, 184, 94,,,, -7, 5, 4, 5, 3, 3, 1, 2, 384, 240, 184, 94,,,, -7, 5, 4, 5, 3, 3, 1, 3, 128, 240, 184, 94,,,, -7, 5, 4, 5, 3, 3, 1, 3, 256, 240, 184, 94,,,, -7, 5, 4, 5, 3, 3, 1, 3, 384, 240, 184, 94,,,, -7, 5, 4, 5, 3, 3, 2, 1, 128, 240, 184, 94,,,, -7, 5, 4, 5, 3, 3, 2, 1, 256, 240, 184, 94,,,, -7, 5, 4, 5, 3, 3, 2, 1, 384, 240, 184, 94,,,, -7, 5, 4, 5, 3, 3, 2, 2, 128, 240, 184, 94,,,, -7, 5, 4, 5, 3, 3, 2, 2, 256, 240, 184, 94,,,, -7, 5, 4, 5, 3, 3, 2, 2, 384, 240, 184, 94,,,, -7, 5, 4, 5, 3, 3, 2, 3, 128, 240, 184, 94,,,, -7, 5, 4, 5, 3, 3, 2, 3, 256, 240, 184, 94,,,, -7, 5, 4, 5, 3, 3, 2, 3, 384, 240, 184, 94,,,, -7, 5, 4, 5, 3, 3, 3, 1, 128, 240, 184, 94,,,, -7, 5, 4, 5, 3, 3, 3, 1, 256, 240, 184, 94,,,, -7, 5, 4, 5, 3, 3, 3, 1, 384, 240, 184, 94,,,, -7, 5, 4, 5, 3, 3, 3, 2, 128, 240, 184, 94,,,, -7, 5, 4, 5, 3, 3, 3, 2, 256, 240, 184, 94,,,, -7, 5, 4, 5, 3, 3, 3, 2, 384, 240, 184, 94,,,, -7, 5, 4, 5, 3, 3, 3, 3, 128, 240, 184, 94,,,, -7, 5, 4, 5, 3, 3, 3, 3, 256, 240, 184, 94,,,, -7, 5, 4, 5, 3, 3, 3, 3, 384, 240, 184, 94,,,, -7, 5, 5, 1, 1, 1, 1, 1, 128, 58, 40, 22,,,, -7, 5, 5, 1, 1, 1, 1, 1, 256, 58, 40, 22,,,, -7, 5, 5, 1, 1, 1, 1, 1, 384, 58, 40, 22,,,, -7, 5, 5, 1, 2, 2, 1, 1, 128, 58, 40, 22,,,, -7, 5, 5, 1, 2, 2, 1, 1, 256, 58, 40, 22,,,, -7, 5, 5, 1, 2, 2, 1, 1, 384, 58, 40, 22,,,, -7, 5, 5, 1, 2, 2, 1, 2, 128, 58, 40, 22,,,, -7, 5, 5, 1, 2, 2, 1, 2, 256, 58, 40, 22,,,, -7, 5, 5, 1, 2, 2, 1, 2, 384, 58, 40, 22,,,, -7, 5, 5, 1, 2, 2, 2, 1, 128, 58, 40, 22,,,, -7, 5, 5, 1, 2, 2, 2, 1, 256, 58, 40, 22,,,, -7, 5, 5, 1, 2, 2, 2, 1, 384, 58, 40, 22,,,, -7, 5, 5, 1, 2, 2, 2, 2, 128, 58, 40, 22,,,, -7, 5, 5, 1, 2, 2, 2, 2, 256, 58, 40, 22,,,, -7, 5, 5, 1, 2, 2, 2, 2, 384, 58, 40, 22,,,, -7, 5, 5, 1, 3, 3, 1, 1, 128, 58, 40, 22,,,, -7, 5, 5, 1, 3, 3, 1, 1, 256, 58, 40, 22,,,, -7, 5, 5, 1, 3, 3, 1, 1, 384, 58, 40, 22,,,, -7, 5, 5, 1, 3, 3, 1, 2, 128, 58, 40, 22,,,, -7, 5, 5, 1, 3, 3, 1, 2, 256, 58, 40, 22,,,, -7, 5, 5, 1, 3, 3, 1, 2, 384, 58, 40, 22,,,, -7, 5, 5, 1, 3, 3, 1, 3, 128, 58, 40, 22,,,, -7, 5, 5, 1, 3, 3, 1, 3, 256, 58, 40, 22,,,, -7, 5, 5, 1, 3, 3, 1, 3, 384, 58, 40, 22,,,, -7, 5, 5, 1, 3, 3, 2, 1, 128, 58, 40, 22,,,, -7, 5, 5, 1, 3, 3, 2, 1, 256, 58, 40, 22,,,, -7, 5, 5, 1, 3, 3, 2, 1, 384, 58, 40, 22,,,, -7, 5, 5, 1, 3, 3, 2, 2, 128, 58, 40, 22,,,, -7, 5, 5, 1, 3, 3, 2, 2, 256, 58, 40, 22,,,, -7, 5, 5, 1, 3, 3, 2, 2, 384, 58, 40, 22,,,, -7, 5, 5, 1, 3, 3, 2, 3, 128, 58, 40, 22,,,, -7, 5, 5, 1, 3, 3, 2, 3, 256, 58, 40, 22,,,, -7, 5, 5, 1, 3, 3, 2, 3, 384, 58, 40, 22,,,, -7, 5, 5, 1, 3, 3, 3, 1, 128, 58, 40, 22,,,, -7, 5, 5, 1, 3, 3, 3, 1, 256, 58, 40, 22,,,, -7, 5, 5, 1, 3, 3, 3, 1, 384, 58, 40, 22,,,, -7, 5, 5, 1, 3, 3, 3, 2, 128, 58, 40, 22,,,, -7, 5, 5, 1, 3, 3, 3, 2, 256, 58, 40, 22,,,, -7, 5, 5, 1, 3, 3, 3, 2, 384, 58, 40, 22,,,, -7, 5, 5, 1, 3, 3, 3, 3, 128, 58, 40, 22,,,, -7, 5, 5, 1, 3, 3, 3, 3, 256, 58, 40, 22,,,, -7, 5, 5, 1, 3, 3, 3, 3, 384, 58, 40, 22,,,, -7, 5, 5, 2, 1, 1, 1, 1, 128, 112, 76, 40,,,, -7, 5, 5, 2, 1, 1, 1, 1, 256, 112, 76, 40,,,, -7, 5, 5, 2, 1, 1, 1, 1, 384, 112, 76, 40,,,, -7, 5, 5, 2, 2, 2, 1, 1, 128, 112, 76, 40,,,, -7, 5, 5, 2, 2, 2, 1, 1, 256, 112, 76, 40,,,, -7, 5, 5, 2, 2, 2, 1, 1, 384, 112, 76, 40,,,, -7, 5, 5, 2, 2, 2, 1, 2, 128, 112, 76, 40,,,, -7, 5, 5, 2, 2, 2, 1, 2, 256, 112, 76, 40,,,, -7, 5, 5, 2, 2, 2, 1, 2, 384, 112, 76, 40,,,, -7, 5, 5, 2, 2, 2, 2, 1, 128, 112, 76, 40,,,, -7, 5, 5, 2, 2, 2, 2, 1, 256, 112, 76, 40,,,, -7, 5, 5, 2, 2, 2, 2, 1, 384, 112, 76, 40,,,, -7, 5, 5, 2, 2, 2, 2, 2, 128, 112, 76, 40,,,, -7, 5, 5, 2, 2, 2, 2, 2, 256, 112, 76, 40,,,, -7, 5, 5, 2, 2, 2, 2, 2, 384, 112, 76, 40,,,, -7, 5, 5, 2, 3, 3, 1, 1, 128, 112, 76, 40,,,, -7, 5, 5, 2, 3, 3, 1, 1, 256, 112, 76, 40,,,, -7, 5, 5, 2, 3, 3, 1, 1, 384, 112, 76, 40,,,, -7, 5, 5, 2, 3, 3, 1, 2, 128, 112, 76, 40,,,, -7, 5, 5, 2, 3, 3, 1, 2, 256, 112, 76, 40,,,, -7, 5, 5, 2, 3, 3, 1, 2, 384, 112, 76, 40,,,, -7, 5, 5, 2, 3, 3, 1, 3, 128, 112, 76, 40,,,, -7, 5, 5, 2, 3, 3, 1, 3, 256, 112, 76, 40,,,, -7, 5, 5, 2, 3, 3, 1, 3, 384, 112, 76, 40,,,, -7, 5, 5, 2, 3, 3, 2, 1, 128, 112, 76, 40,,,, -7, 5, 5, 2, 3, 3, 2, 1, 256, 112, 76, 40,,,, -7, 5, 5, 2, 3, 3, 2, 1, 384, 112, 76, 40,,,, -7, 5, 5, 2, 3, 3, 2, 2, 128, 112, 76, 40,,,, -7, 5, 5, 2, 3, 3, 2, 2, 256, 112, 76, 40,,,, -7, 5, 5, 2, 3, 3, 2, 2, 384, 112, 76, 40,,,, -7, 5, 5, 2, 3, 3, 2, 3, 128, 112, 76, 40,,,, -7, 5, 5, 2, 3, 3, 2, 3, 256, 112, 76, 40,,,, -7, 5, 5, 2, 3, 3, 2, 3, 384, 112, 76, 40,,,, -7, 5, 5, 2, 3, 3, 3, 1, 128, 112, 76, 40,,,, -7, 5, 5, 2, 3, 3, 3, 1, 256, 112, 76, 40,,,, -7, 5, 5, 2, 3, 3, 3, 1, 384, 112, 76, 40,,,, -7, 5, 5, 2, 3, 3, 3, 2, 128, 112, 76, 40,,,, -7, 5, 5, 2, 3, 3, 3, 2, 256, 112, 76, 40,,,, -7, 5, 5, 2, 3, 3, 3, 2, 384, 112, 76, 40,,,, -7, 5, 5, 2, 3, 3, 3, 3, 128, 112, 76, 40,,,, -7, 5, 5, 2, 3, 3, 3, 3, 256, 112, 76, 40,,,, -7, 5, 5, 2, 3, 3, 3, 3, 384, 112, 76, 40,,,, -7, 5, 5, 3, 1, 1, 1, 1, 128, 166, 112, 58,,,, -7, 5, 5, 3, 1, 1, 1, 1, 256, 166, 112, 58,,,, -7, 5, 5, 3, 1, 1, 1, 1, 384, 166, 112, 58,,,, -7, 5, 5, 3, 2, 2, 1, 1, 128, 166, 112, 58,,,, -7, 5, 5, 3, 2, 2, 1, 1, 256, 166, 112, 58,,,, -7, 5, 5, 3, 2, 2, 1, 1, 384, 166, 112, 58,,,, -7, 5, 5, 3, 2, 2, 1, 2, 128, 166, 112, 58,,,, -7, 5, 5, 3, 2, 2, 1, 2, 256, 166, 112, 58,,,, -7, 5, 5, 3, 2, 2, 1, 2, 384, 166, 112, 58,,,, -7, 5, 5, 3, 2, 2, 2, 1, 128, 166, 112, 58,,,, -7, 5, 5, 3, 2, 2, 2, 1, 256, 166, 112, 58,,,, -7, 5, 5, 3, 2, 2, 2, 1, 384, 166, 112, 58,,,, -7, 5, 5, 3, 2, 2, 2, 2, 128, 166, 112, 58,,,, -7, 5, 5, 3, 2, 2, 2, 2, 256, 166, 112, 58,,,, -7, 5, 5, 3, 2, 2, 2, 2, 384, 166, 112, 58,,,, -7, 5, 5, 3, 3, 3, 1, 1, 128, 166, 112, 58,,,, -7, 5, 5, 3, 3, 3, 1, 1, 256, 166, 112, 58,,,, -7, 5, 5, 3, 3, 3, 1, 1, 384, 166, 112, 58,,,, -7, 5, 5, 3, 3, 3, 1, 2, 128, 166, 112, 58,,,, -7, 5, 5, 3, 3, 3, 1, 2, 256, 166, 112, 58,,,, -7, 5, 5, 3, 3, 3, 1, 2, 384, 166, 112, 58,,,, -7, 5, 5, 3, 3, 3, 1, 3, 128, 166, 112, 58,,,, -7, 5, 5, 3, 3, 3, 1, 3, 256, 166, 112, 58,,,, -7, 5, 5, 3, 3, 3, 1, 3, 384, 166, 112, 58,,,, -7, 5, 5, 3, 3, 3, 2, 1, 128, 166, 112, 58,,,, -7, 5, 5, 3, 3, 3, 2, 1, 256, 166, 112, 58,,,, -7, 5, 5, 3, 3, 3, 2, 1, 384, 166, 112, 58,,,, -7, 5, 5, 3, 3, 3, 2, 2, 128, 166, 112, 58,,,, -7, 5, 5, 3, 3, 3, 2, 2, 256, 166, 112, 58,,,, -7, 5, 5, 3, 3, 3, 2, 2, 384, 166, 112, 58,,,, -7, 5, 5, 3, 3, 3, 2, 3, 128, 166, 112, 58,,,, -7, 5, 5, 3, 3, 3, 2, 3, 256, 166, 112, 58,,,, -7, 5, 5, 3, 3, 3, 2, 3, 384, 166, 112, 58,,,, -7, 5, 5, 3, 3, 3, 3, 1, 128, 166, 112, 58,,,, -7, 5, 5, 3, 3, 3, 3, 1, 256, 166, 112, 58,,,, -7, 5, 5, 3, 3, 3, 3, 1, 384, 166, 112, 58,,,, -7, 5, 5, 3, 3, 3, 3, 2, 128, 166, 112, 58,,,, -7, 5, 5, 3, 3, 3, 3, 2, 256, 166, 112, 58,,,, -7, 5, 5, 3, 3, 3, 3, 2, 384, 166, 112, 58,,,, -7, 5, 5, 3, 3, 3, 3, 3, 128, 166, 112, 58,,,, -7, 5, 5, 3, 3, 3, 3, 3, 256, 166, 112, 58,,,, -7, 5, 5, 3, 3, 3, 3, 3, 384, 166, 112, 58,,,, -7, 5, 5, 4, 1, 1, 1, 1, 128, 220, 148, 76,,,, -7, 5, 5, 4, 1, 1, 1, 1, 256, 220, 148, 76,,,, -7, 5, 5, 4, 1, 1, 1, 1, 384, 220, 148, 76,,,, -7, 5, 5, 4, 2, 2, 1, 1, 128, 220, 148, 76,,,, -7, 5, 5, 4, 2, 2, 1, 1, 256, 220, 148, 76,,,, -7, 5, 5, 4, 2, 2, 1, 1, 384, 220, 148, 76,,,, -7, 5, 5, 4, 2, 2, 1, 2, 128, 220, 148, 76,,,, -7, 5, 5, 4, 2, 2, 1, 2, 256, 220, 148, 76,,,, -7, 5, 5, 4, 2, 2, 1, 2, 384, 220, 148, 76,,,, -7, 5, 5, 4, 2, 2, 2, 1, 128, 220, 148, 76,,,, -7, 5, 5, 4, 2, 2, 2, 1, 256, 220, 148, 76,,,, -7, 5, 5, 4, 2, 2, 2, 1, 384, 220, 148, 76,,,, -7, 5, 5, 4, 2, 2, 2, 2, 128, 220, 148, 76,,,, -7, 5, 5, 4, 2, 2, 2, 2, 256, 220, 148, 76,,,, -7, 5, 5, 4, 2, 2, 2, 2, 384, 220, 148, 76,,,, -7, 5, 5, 4, 3, 3, 1, 1, 128, 220, 148, 76,,,, -7, 5, 5, 4, 3, 3, 1, 1, 256, 220, 148, 76,,,, -7, 5, 5, 4, 3, 3, 1, 1, 384, 220, 148, 76,,,, -7, 5, 5, 4, 3, 3, 1, 2, 128, 220, 148, 76,,,, -7, 5, 5, 4, 3, 3, 1, 2, 256, 220, 148, 76,,,, -7, 5, 5, 4, 3, 3, 1, 2, 384, 220, 148, 76,,,, -7, 5, 5, 4, 3, 3, 1, 3, 128, 220, 148, 76,,,, -7, 5, 5, 4, 3, 3, 1, 3, 256, 220, 148, 76,,,, -7, 5, 5, 4, 3, 3, 1, 3, 384, 220, 148, 76,,,, -7, 5, 5, 4, 3, 3, 2, 1, 128, 220, 148, 76,,,, -7, 5, 5, 4, 3, 3, 2, 1, 256, 220, 148, 76,,,, -7, 5, 5, 4, 3, 3, 2, 1, 384, 220, 148, 76,,,, -7, 5, 5, 4, 3, 3, 2, 2, 128, 220, 148, 76,,,, -7, 5, 5, 4, 3, 3, 2, 2, 256, 220, 148, 76,,,, -7, 5, 5, 4, 3, 3, 2, 2, 384, 220, 148, 76,,,, -7, 5, 5, 4, 3, 3, 2, 3, 128, 220, 148, 76,,,, -7, 5, 5, 4, 3, 3, 2, 3, 256, 220, 148, 76,,,, -7, 5, 5, 4, 3, 3, 2, 3, 384, 220, 148, 76,,,, -7, 5, 5, 4, 3, 3, 3, 1, 128, 220, 148, 76,,,, -7, 5, 5, 4, 3, 3, 3, 1, 256, 220, 148, 76,,,, -7, 5, 5, 4, 3, 3, 3, 1, 384, 220, 148, 76,,,, -7, 5, 5, 4, 3, 3, 3, 2, 128, 220, 148, 76,,,, -7, 5, 5, 4, 3, 3, 3, 2, 256, 220, 148, 76,,,, -7, 5, 5, 4, 3, 3, 3, 2, 384, 220, 148, 76,,,, -7, 5, 5, 4, 3, 3, 3, 3, 128, 220, 148, 76,,,, -7, 5, 5, 4, 3, 3, 3, 3, 256, 220, 148, 76,,,, -7, 5, 5, 4, 3, 3, 3, 3, 384, 220, 148, 76,,,, -7, 5, 5, 5, 1, 1, 1, 1, 128, 240, 184, 94,,,, -7, 5, 5, 5, 1, 1, 1, 1, 256, 240, 184, 94,,,, -7, 5, 5, 5, 1, 1, 1, 1, 384, 240, 184, 94,,,, -7, 5, 5, 5, 2, 2, 1, 1, 128, 240, 184, 94,,,, -7, 5, 5, 5, 2, 2, 1, 1, 256, 240, 184, 94,,,, -7, 5, 5, 5, 2, 2, 1, 1, 384, 240, 184, 94,,,, -7, 5, 5, 5, 2, 2, 1, 2, 128, 240, 184, 94,,,, -7, 5, 5, 5, 2, 2, 1, 2, 256, 240, 184, 94,,,, -7, 5, 5, 5, 2, 2, 1, 2, 384, 240, 184, 94,,,, -7, 5, 5, 5, 2, 2, 2, 1, 128, 240, 184, 94,,,, -7, 5, 5, 5, 2, 2, 2, 1, 256, 240, 184, 94,,,, -7, 5, 5, 5, 2, 2, 2, 1, 384, 240, 184, 94,,,, -7, 5, 5, 5, 2, 2, 2, 2, 128, 240, 184, 94,,,, -7, 5, 5, 5, 2, 2, 2, 2, 256, 240, 184, 94,,,, -7, 5, 5, 5, 2, 2, 2, 2, 384, 240, 184, 94,,,, -7, 5, 5, 5, 3, 3, 1, 1, 128, 240, 184, 94,,,, -7, 5, 5, 5, 3, 3, 1, 1, 256, 240, 184, 94,,,, -7, 5, 5, 5, 3, 3, 1, 1, 384, 240, 184, 94,,,, -7, 5, 5, 5, 3, 3, 1, 2, 128, 240, 184, 94,,,, -7, 5, 5, 5, 3, 3, 1, 2, 256, 240, 184, 94,,,, -7, 5, 5, 5, 3, 3, 1, 2, 384, 240, 184, 94,,,, -7, 5, 5, 5, 3, 3, 1, 3, 128, 240, 184, 94,,,, -7, 5, 5, 5, 3, 3, 1, 3, 256, 240, 184, 94,,,, -7, 5, 5, 5, 3, 3, 1, 3, 384, 240, 184, 94,,,, -7, 5, 5, 5, 3, 3, 2, 1, 128, 240, 184, 94,,,, -7, 5, 5, 5, 3, 3, 2, 1, 256, 240, 184, 94,,,, -7, 5, 5, 5, 3, 3, 2, 1, 384, 240, 184, 94,,,, -7, 5, 5, 5, 3, 3, 2, 2, 128, 240, 184, 94,,,, -7, 5, 5, 5, 3, 3, 2, 2, 256, 240, 184, 94,,,, -7, 5, 5, 5, 3, 3, 2, 2, 384, 240, 184, 94,,,, -7, 5, 5, 5, 3, 3, 2, 3, 128, 240, 184, 94,,,, -7, 5, 5, 5, 3, 3, 2, 3, 256, 240, 184, 94,,,, -7, 5, 5, 5, 3, 3, 2, 3, 384, 240, 184, 94,,,, -7, 5, 5, 5, 3, 3, 3, 1, 128, 240, 184, 94,,,, -7, 5, 5, 5, 3, 3, 3, 1, 256, 240, 184, 94,,,, -7, 5, 5, 5, 3, 3, 3, 1, 384, 240, 184, 94,,,, -7, 5, 5, 5, 3, 3, 3, 2, 128, 240, 184, 94,,,, -7, 5, 5, 5, 3, 3, 3, 2, 256, 240, 184, 94,,,, -7, 5, 5, 5, 3, 3, 3, 2, 384, 240, 184, 94,,,, -7, 5, 5, 5, 3, 3, 3, 3, 128, 240, 184, 94,,,, -7, 5, 5, 5, 3, 3, 3, 3, 256, 240, 184, 94,,,, -7, 5, 5, 5, 3, 3, 3, 3, 384, 240, 184, 94,,,, -7, 5, 6, 1, 1, 1, 1, 1, 128, 58, 40, 22,,,, -7, 5, 6, 1, 1, 1, 1, 1, 256, 58, 40, 22,,,, -7, 5, 6, 1, 1, 1, 1, 1, 384, 58, 40, 22,,,, -7, 5, 6, 1, 2, 2, 1, 1, 128, 58, 40, 22,,,, -7, 5, 6, 1, 2, 2, 1, 1, 256, 58, 40, 22,,,, -7, 5, 6, 1, 2, 2, 1, 1, 384, 58, 40, 22,,,, -7, 5, 6, 1, 2, 2, 1, 2, 128, 58, 40, 22,,,, -7, 5, 6, 1, 2, 2, 1, 2, 256, 58, 40, 22,,,, -7, 5, 6, 1, 2, 2, 1, 2, 384, 58, 40, 22,,,, -7, 5, 6, 1, 2, 2, 2, 1, 128, 58, 40, 22,,,, -7, 5, 6, 1, 2, 2, 2, 1, 256, 58, 40, 22,,,, -7, 5, 6, 1, 2, 2, 2, 1, 384, 58, 40, 22,,,, -7, 5, 6, 1, 2, 2, 2, 2, 128, 58, 40, 22,,,, -7, 5, 6, 1, 2, 2, 2, 2, 256, 58, 40, 22,,,, -7, 5, 6, 1, 2, 2, 2, 2, 384, 58, 40, 22,,,, -7, 5, 6, 1, 3, 3, 1, 1, 128, 58, 40, 22,,,, -7, 5, 6, 1, 3, 3, 1, 1, 256, 58, 40, 22,,,, -7, 5, 6, 1, 3, 3, 1, 1, 384, 58, 40, 22,,,, -7, 5, 6, 1, 3, 3, 1, 2, 128, 58, 40, 22,,,, -7, 5, 6, 1, 3, 3, 1, 2, 256, 58, 40, 22,,,, -7, 5, 6, 1, 3, 3, 1, 2, 384, 58, 40, 22,,,, -7, 5, 6, 1, 3, 3, 1, 3, 128, 58, 40, 22,,,, -7, 5, 6, 1, 3, 3, 1, 3, 256, 58, 40, 22,,,, -7, 5, 6, 1, 3, 3, 1, 3, 384, 58, 40, 22,,,, -7, 5, 6, 1, 3, 3, 2, 1, 128, 58, 40, 22,,,, -7, 5, 6, 1, 3, 3, 2, 1, 256, 58, 40, 22,,,, -7, 5, 6, 1, 3, 3, 2, 1, 384, 58, 40, 22,,,, -7, 5, 6, 1, 3, 3, 2, 2, 128, 58, 40, 22,,,, -7, 5, 6, 1, 3, 3, 2, 2, 256, 58, 40, 22,,,, -7, 5, 6, 1, 3, 3, 2, 2, 384, 58, 40, 22,,,, -7, 5, 6, 1, 3, 3, 2, 3, 128, 58, 40, 22,,,, -7, 5, 6, 1, 3, 3, 2, 3, 256, 58, 40, 22,,,, -7, 5, 6, 1, 3, 3, 2, 3, 384, 58, 40, 22,,,, -7, 5, 6, 1, 3, 3, 3, 1, 128, 58, 40, 22,,,, -7, 5, 6, 1, 3, 3, 3, 1, 256, 58, 40, 22,,,, -7, 5, 6, 1, 3, 3, 3, 1, 384, 58, 40, 22,,,, -7, 5, 6, 1, 3, 3, 3, 2, 128, 58, 40, 22,,,, -7, 5, 6, 1, 3, 3, 3, 2, 256, 58, 40, 22,,,, -7, 5, 6, 1, 3, 3, 3, 2, 384, 58, 40, 22,,,, -7, 5, 6, 1, 3, 3, 3, 3, 128, 58, 40, 22,,,, -7, 5, 6, 1, 3, 3, 3, 3, 256, 58, 40, 22,,,, -7, 5, 6, 1, 3, 3, 3, 3, 384, 58, 40, 22,,,, -7, 5, 6, 2, 1, 1, 1, 1, 128, 112, 76, 40,,,, -7, 5, 6, 2, 1, 1, 1, 1, 256, 112, 76, 40,,,, -7, 5, 6, 2, 1, 1, 1, 1, 384, 112, 76, 40,,,, -7, 5, 6, 2, 2, 2, 1, 1, 128, 112, 76, 40,,,, -7, 5, 6, 2, 2, 2, 1, 1, 256, 112, 76, 40,,,, -7, 5, 6, 2, 2, 2, 1, 1, 384, 112, 76, 40,,,, -7, 5, 6, 2, 2, 2, 1, 2, 128, 112, 76, 40,,,, -7, 5, 6, 2, 2, 2, 1, 2, 256, 112, 76, 40,,,, -7, 5, 6, 2, 2, 2, 1, 2, 384, 112, 76, 40,,,, -7, 5, 6, 2, 2, 2, 2, 1, 128, 112, 76, 40,,,, -7, 5, 6, 2, 2, 2, 2, 1, 256, 112, 76, 40,,,, -7, 5, 6, 2, 2, 2, 2, 1, 384, 112, 76, 40,,,, -7, 5, 6, 2, 2, 2, 2, 2, 128, 112, 76, 40,,,, -7, 5, 6, 2, 2, 2, 2, 2, 256, 112, 76, 40,,,, -7, 5, 6, 2, 2, 2, 2, 2, 384, 112, 76, 40,,,, -7, 5, 6, 2, 3, 3, 1, 1, 128, 112, 76, 40,,,, -7, 5, 6, 2, 3, 3, 1, 1, 256, 112, 76, 40,,,, -7, 5, 6, 2, 3, 3, 1, 1, 384, 112, 76, 40,,,, -7, 5, 6, 2, 3, 3, 1, 2, 128, 112, 76, 40,,,, -7, 5, 6, 2, 3, 3, 1, 2, 256, 112, 76, 40,,,, -7, 5, 6, 2, 3, 3, 1, 2, 384, 112, 76, 40,,,, -7, 5, 6, 2, 3, 3, 1, 3, 128, 112, 76, 40,,,, -7, 5, 6, 2, 3, 3, 1, 3, 256, 112, 76, 40,,,, -7, 5, 6, 2, 3, 3, 1, 3, 384, 112, 76, 40,,,, -7, 5, 6, 2, 3, 3, 2, 1, 128, 112, 76, 40,,,, -7, 5, 6, 2, 3, 3, 2, 1, 256, 112, 76, 40,,,, -7, 5, 6, 2, 3, 3, 2, 1, 384, 112, 76, 40,,,, -7, 5, 6, 2, 3, 3, 2, 2, 128, 112, 76, 40,,,, -7, 5, 6, 2, 3, 3, 2, 2, 256, 112, 76, 40,,,, -7, 5, 6, 2, 3, 3, 2, 2, 384, 112, 76, 40,,,, -7, 5, 6, 2, 3, 3, 2, 3, 128, 112, 76, 40,,,, -7, 5, 6, 2, 3, 3, 2, 3, 256, 112, 76, 40,,,, -7, 5, 6, 2, 3, 3, 2, 3, 384, 112, 76, 40,,,, -7, 5, 6, 2, 3, 3, 3, 1, 128, 112, 76, 40,,,, -7, 5, 6, 2, 3, 3, 3, 1, 256, 112, 76, 40,,,, -7, 5, 6, 2, 3, 3, 3, 1, 384, 112, 76, 40,,,, -7, 5, 6, 2, 3, 3, 3, 2, 128, 112, 76, 40,,,, -7, 5, 6, 2, 3, 3, 3, 2, 256, 112, 76, 40,,,, -7, 5, 6, 2, 3, 3, 3, 2, 384, 112, 76, 40,,,, -7, 5, 6, 2, 3, 3, 3, 3, 128, 112, 76, 40,,,, -7, 5, 6, 2, 3, 3, 3, 3, 256, 112, 76, 40,,,, -7, 5, 6, 2, 3, 3, 3, 3, 384, 112, 76, 40,,,, -7, 5, 6, 3, 1, 1, 1, 1, 128, 166, 112, 58,,,, -7, 5, 6, 3, 1, 1, 1, 1, 256, 166, 112, 58,,,, -7, 5, 6, 3, 1, 1, 1, 1, 384, 166, 112, 58,,,, -7, 5, 6, 3, 2, 2, 1, 1, 128, 166, 112, 58,,,, -7, 5, 6, 3, 2, 2, 1, 1, 256, 166, 112, 58,,,, -7, 5, 6, 3, 2, 2, 1, 1, 384, 166, 112, 58,,,, -7, 5, 6, 3, 2, 2, 1, 2, 128, 166, 112, 58,,,, -7, 5, 6, 3, 2, 2, 1, 2, 256, 166, 112, 58,,,, -7, 5, 6, 3, 2, 2, 1, 2, 384, 166, 112, 58,,,, -7, 5, 6, 3, 2, 2, 2, 1, 128, 166, 112, 58,,,, -7, 5, 6, 3, 2, 2, 2, 1, 256, 166, 112, 58,,,, -7, 5, 6, 3, 2, 2, 2, 1, 384, 166, 112, 58,,,, -7, 5, 6, 3, 2, 2, 2, 2, 128, 166, 112, 58,,,, -7, 5, 6, 3, 2, 2, 2, 2, 256, 166, 112, 58,,,, -7, 5, 6, 3, 2, 2, 2, 2, 384, 166, 112, 58,,,, -7, 5, 6, 3, 3, 3, 1, 1, 128, 166, 112, 58,,,, -7, 5, 6, 3, 3, 3, 1, 1, 256, 166, 112, 58,,,, -7, 5, 6, 3, 3, 3, 1, 1, 384, 166, 112, 58,,,, -7, 5, 6, 3, 3, 3, 1, 2, 128, 166, 112, 58,,,, -7, 5, 6, 3, 3, 3, 1, 2, 256, 166, 112, 58,,,, -7, 5, 6, 3, 3, 3, 1, 2, 384, 166, 112, 58,,,, -7, 5, 6, 3, 3, 3, 1, 3, 128, 166, 112, 58,,,, -7, 5, 6, 3, 3, 3, 1, 3, 256, 166, 112, 58,,,, -7, 5, 6, 3, 3, 3, 1, 3, 384, 166, 112, 58,,,, -7, 5, 6, 3, 3, 3, 2, 1, 128, 166, 112, 58,,,, -7, 5, 6, 3, 3, 3, 2, 1, 256, 166, 112, 58,,,, -7, 5, 6, 3, 3, 3, 2, 1, 384, 166, 112, 58,,,, -7, 5, 6, 3, 3, 3, 2, 2, 128, 166, 112, 58,,,, -7, 5, 6, 3, 3, 3, 2, 2, 256, 166, 112, 58,,,, -7, 5, 6, 3, 3, 3, 2, 2, 384, 166, 112, 58,,,, -7, 5, 6, 3, 3, 3, 2, 3, 128, 166, 112, 58,,,, -7, 5, 6, 3, 3, 3, 2, 3, 256, 166, 112, 58,,,, -7, 5, 6, 3, 3, 3, 2, 3, 384, 166, 112, 58,,,, -7, 5, 6, 3, 3, 3, 3, 1, 128, 166, 112, 58,,,, -7, 5, 6, 3, 3, 3, 3, 1, 256, 166, 112, 58,,,, -7, 5, 6, 3, 3, 3, 3, 1, 384, 166, 112, 58,,,, -7, 5, 6, 3, 3, 3, 3, 2, 128, 166, 112, 58,,,, -7, 5, 6, 3, 3, 3, 3, 2, 256, 166, 112, 58,,,, -7, 5, 6, 3, 3, 3, 3, 2, 384, 166, 112, 58,,,, -7, 5, 6, 3, 3, 3, 3, 3, 128, 166, 112, 58,,,, -7, 5, 6, 3, 3, 3, 3, 3, 256, 166, 112, 58,,,, -7, 5, 6, 3, 3, 3, 3, 3, 384, 166, 112, 58,,,, -7, 5, 6, 4, 1, 1, 1, 1, 128, 220, 148, 76,,,, -7, 5, 6, 4, 1, 1, 1, 1, 256, 220, 148, 76,,,, -7, 5, 6, 4, 1, 1, 1, 1, 384, 220, 148, 76,,,, -7, 5, 6, 4, 2, 2, 1, 1, 128, 220, 148, 76,,,, -7, 5, 6, 4, 2, 2, 1, 1, 256, 220, 148, 76,,,, -7, 5, 6, 4, 2, 2, 1, 1, 384, 220, 148, 76,,,, -7, 5, 6, 4, 2, 2, 1, 2, 128, 220, 148, 76,,,, -7, 5, 6, 4, 2, 2, 1, 2, 256, 220, 148, 76,,,, -7, 5, 6, 4, 2, 2, 1, 2, 384, 220, 148, 76,,,, -7, 5, 6, 4, 2, 2, 2, 1, 128, 220, 148, 76,,,, -7, 5, 6, 4, 2, 2, 2, 1, 256, 220, 148, 76,,,, -7, 5, 6, 4, 2, 2, 2, 1, 384, 220, 148, 76,,,, -7, 5, 6, 4, 2, 2, 2, 2, 128, 220, 148, 76,,,, -7, 5, 6, 4, 2, 2, 2, 2, 256, 220, 148, 76,,,, -7, 5, 6, 4, 2, 2, 2, 2, 384, 220, 148, 76,,,, -7, 5, 6, 4, 3, 3, 1, 1, 128, 220, 148, 76,,,, -7, 5, 6, 4, 3, 3, 1, 1, 256, 220, 148, 76,,,, -7, 5, 6, 4, 3, 3, 1, 1, 384, 220, 148, 76,,,, -7, 5, 6, 4, 3, 3, 1, 2, 128, 220, 148, 76,,,, -7, 5, 6, 4, 3, 3, 1, 2, 256, 220, 148, 76,,,, -7, 5, 6, 4, 3, 3, 1, 2, 384, 220, 148, 76,,,, -7, 5, 6, 4, 3, 3, 1, 3, 128, 220, 148, 76,,,, -7, 5, 6, 4, 3, 3, 1, 3, 256, 220, 148, 76,,,, -7, 5, 6, 4, 3, 3, 1, 3, 384, 220, 148, 76,,,, -7, 5, 6, 4, 3, 3, 2, 1, 128, 220, 148, 76,,,, -7, 5, 6, 4, 3, 3, 2, 1, 256, 220, 148, 76,,,, -7, 5, 6, 4, 3, 3, 2, 1, 384, 220, 148, 76,,,, -7, 5, 6, 4, 3, 3, 2, 2, 128, 220, 148, 76,,,, -7, 5, 6, 4, 3, 3, 2, 2, 256, 220, 148, 76,,,, -7, 5, 6, 4, 3, 3, 2, 2, 384, 220, 148, 76,,,, -7, 5, 6, 4, 3, 3, 2, 3, 128, 220, 148, 76,,,, -7, 5, 6, 4, 3, 3, 2, 3, 256, 220, 148, 76,,,, -7, 5, 6, 4, 3, 3, 2, 3, 384, 220, 148, 76,,,, -7, 5, 6, 4, 3, 3, 3, 1, 128, 220, 148, 76,,,, -7, 5, 6, 4, 3, 3, 3, 1, 256, 220, 148, 76,,,, -7, 5, 6, 4, 3, 3, 3, 1, 384, 220, 148, 76,,,, -7, 5, 6, 4, 3, 3, 3, 2, 128, 220, 148, 76,,,, -7, 5, 6, 4, 3, 3, 3, 2, 256, 220, 148, 76,,,, -7, 5, 6, 4, 3, 3, 3, 2, 384, 220, 148, 76,,,, -7, 5, 6, 4, 3, 3, 3, 3, 128, 220, 148, 76,,,, -7, 5, 6, 4, 3, 3, 3, 3, 256, 220, 148, 76,,,, -7, 5, 6, 4, 3, 3, 3, 3, 384, 220, 148, 76,,,, -7, 5, 6, 5, 1, 1, 1, 1, 128, 240, 184, 94,,,, -7, 5, 6, 5, 1, 1, 1, 1, 256, 240, 184, 94,,,, -7, 5, 6, 5, 1, 1, 1, 1, 384, 240, 184, 94,,,, -7, 5, 6, 5, 2, 2, 1, 1, 128, 240, 184, 94,,,, -7, 5, 6, 5, 2, 2, 1, 1, 256, 240, 184, 94,,,, -7, 5, 6, 5, 2, 2, 1, 1, 384, 240, 184, 94,,,, -7, 5, 6, 5, 2, 2, 1, 2, 128, 240, 184, 94,,,, -7, 5, 6, 5, 2, 2, 1, 2, 256, 240, 184, 94,,,, -7, 5, 6, 5, 2, 2, 1, 2, 384, 240, 184, 94,,,, -7, 5, 6, 5, 2, 2, 2, 1, 128, 240, 184, 94,,,, -7, 5, 6, 5, 2, 2, 2, 1, 256, 240, 184, 94,,,, -7, 5, 6, 5, 2, 2, 2, 1, 384, 240, 184, 94,,,, -7, 5, 6, 5, 2, 2, 2, 2, 128, 240, 184, 94,,,, -7, 5, 6, 5, 2, 2, 2, 2, 256, 240, 184, 94,,,, -7, 5, 6, 5, 2, 2, 2, 2, 384, 240, 184, 94,,,, -7, 5, 6, 5, 3, 3, 1, 1, 128, 240, 184, 94,,,, -7, 5, 6, 5, 3, 3, 1, 1, 256, 240, 184, 94,,,, -7, 5, 6, 5, 3, 3, 1, 1, 384, 240, 184, 94,,,, -7, 5, 6, 5, 3, 3, 1, 2, 128, 240, 184, 94,,,, -7, 5, 6, 5, 3, 3, 1, 2, 256, 240, 184, 94,,,, -7, 5, 6, 5, 3, 3, 1, 2, 384, 240, 184, 94,,,, -7, 5, 6, 5, 3, 3, 1, 3, 128, 240, 184, 94,,,, -7, 5, 6, 5, 3, 3, 1, 3, 256, 240, 184, 94,,,, -7, 5, 6, 5, 3, 3, 1, 3, 384, 240, 184, 94,,,, -7, 5, 6, 5, 3, 3, 2, 1, 128, 240, 184, 94,,,, -7, 5, 6, 5, 3, 3, 2, 1, 256, 240, 184, 94,,,, -7, 5, 6, 5, 3, 3, 2, 1, 384, 240, 184, 94,,,, -7, 5, 6, 5, 3, 3, 2, 2, 128, 240, 184, 94,,,, -7, 5, 6, 5, 3, 3, 2, 2, 256, 240, 184, 94,,,, -7, 5, 6, 5, 3, 3, 2, 2, 384, 240, 184, 94,,,, -7, 5, 6, 5, 3, 3, 2, 3, 128, 240, 184, 94,,,, -7, 5, 6, 5, 3, 3, 2, 3, 256, 240, 184, 94,,,, -7, 5, 6, 5, 3, 3, 2, 3, 384, 240, 184, 94,,,, -7, 5, 6, 5, 3, 3, 3, 1, 128, 240, 184, 94,,,, -7, 5, 6, 5, 3, 3, 3, 1, 256, 240, 184, 94,,,, -7, 5, 6, 5, 3, 3, 3, 1, 384, 240, 184, 94,,,, -7, 5, 6, 5, 3, 3, 3, 2, 128, 240, 184, 94,,,, -7, 5, 6, 5, 3, 3, 3, 2, 256, 240, 184, 94,,,, -7, 5, 6, 5, 3, 3, 3, 2, 384, 240, 184, 94,,,, -7, 5, 6, 5, 3, 3, 3, 3, 128, 240, 184, 94,,,, -7, 5, 6, 5, 3, 3, 3, 3, 256, 240, 184, 94,,,, -7, 5, 6, 5, 3, 3, 3, 3, 384, 240, 184, 94,,,, -7, 5, 7, 1, 1, 1, 1, 1, 128, 58, 40, 22,,,, -7, 5, 7, 1, 1, 1, 1, 1, 256, 58, 40, 22,,,, -7, 5, 7, 1, 1, 1, 1, 1, 384, 58, 40, 22,,,, -7, 5, 7, 1, 2, 2, 1, 1, 128, 58, 40, 22,,,, -7, 5, 7, 1, 2, 2, 1, 1, 256, 58, 40, 22,,,, -7, 5, 7, 1, 2, 2, 1, 1, 384, 58, 40, 22,,,, -7, 5, 7, 1, 2, 2, 1, 2, 128, 58, 40, 22,,,, -7, 5, 7, 1, 2, 2, 1, 2, 256, 58, 40, 22,,,, -7, 5, 7, 1, 2, 2, 1, 2, 384, 58, 40, 22,,,, -7, 5, 7, 1, 2, 2, 2, 1, 128, 58, 40, 22,,,, -7, 5, 7, 1, 2, 2, 2, 1, 256, 58, 40, 22,,,, -7, 5, 7, 1, 2, 2, 2, 1, 384, 58, 40, 22,,,, -7, 5, 7, 1, 2, 2, 2, 2, 128, 58, 40, 22,,,, -7, 5, 7, 1, 2, 2, 2, 2, 256, 58, 40, 22,,,, -7, 5, 7, 1, 2, 2, 2, 2, 384, 58, 40, 22,,,, -7, 5, 7, 1, 3, 3, 1, 1, 128, 58, 40, 22,,,, -7, 5, 7, 1, 3, 3, 1, 1, 256, 58, 40, 22,,,, -7, 5, 7, 1, 3, 3, 1, 1, 384, 58, 40, 22,,,, -7, 5, 7, 1, 3, 3, 1, 2, 128, 58, 40, 22,,,, -7, 5, 7, 1, 3, 3, 1, 2, 256, 58, 40, 22,,,, -7, 5, 7, 1, 3, 3, 1, 2, 384, 58, 40, 22,,,, -7, 5, 7, 1, 3, 3, 1, 3, 128, 58, 40, 22,,,, -7, 5, 7, 1, 3, 3, 1, 3, 256, 58, 40, 22,,,, -7, 5, 7, 1, 3, 3, 1, 3, 384, 58, 40, 22,,,, -7, 5, 7, 1, 3, 3, 2, 1, 128, 58, 40, 22,,,, -7, 5, 7, 1, 3, 3, 2, 1, 256, 58, 40, 22,,,, -7, 5, 7, 1, 3, 3, 2, 1, 384, 58, 40, 22,,,, -7, 5, 7, 1, 3, 3, 2, 2, 128, 58, 40, 22,,,, -7, 5, 7, 1, 3, 3, 2, 2, 256, 58, 40, 22,,,, -7, 5, 7, 1, 3, 3, 2, 2, 384, 58, 40, 22,,,, -7, 5, 7, 1, 3, 3, 2, 3, 128, 58, 40, 22,,,, -7, 5, 7, 1, 3, 3, 2, 3, 256, 58, 40, 22,,,, -7, 5, 7, 1, 3, 3, 2, 3, 384, 58, 40, 22,,,, -7, 5, 7, 1, 3, 3, 3, 1, 128, 58, 40, 22,,,, -7, 5, 7, 1, 3, 3, 3, 1, 256, 58, 40, 22,,,, -7, 5, 7, 1, 3, 3, 3, 1, 384, 58, 40, 22,,,, -7, 5, 7, 1, 3, 3, 3, 2, 128, 58, 40, 22,,,, -7, 5, 7, 1, 3, 3, 3, 2, 256, 58, 40, 22,,,, -7, 5, 7, 1, 3, 3, 3, 2, 384, 58, 40, 22,,,, -7, 5, 7, 1, 3, 3, 3, 3, 128, 58, 40, 22,,,, -7, 5, 7, 1, 3, 3, 3, 3, 256, 58, 40, 22,,,, -7, 5, 7, 1, 3, 3, 3, 3, 384, 58, 40, 22,,,, -7, 5, 7, 2, 1, 1, 1, 1, 128, 112, 76, 40,,,, -7, 5, 7, 2, 1, 1, 1, 1, 256, 112, 76, 40,,,, -7, 5, 7, 2, 1, 1, 1, 1, 384, 112, 76, 40,,,, -7, 5, 7, 2, 2, 2, 1, 1, 128, 112, 76, 40,,,, -7, 5, 7, 2, 2, 2, 1, 1, 256, 112, 76, 40,,,, -7, 5, 7, 2, 2, 2, 1, 1, 384, 112, 76, 40,,,, -7, 5, 7, 2, 2, 2, 1, 2, 128, 112, 76, 40,,,, -7, 5, 7, 2, 2, 2, 1, 2, 256, 112, 76, 40,,,, -7, 5, 7, 2, 2, 2, 1, 2, 384, 112, 76, 40,,,, -7, 5, 7, 2, 2, 2, 2, 1, 128, 112, 76, 40,,,, -7, 5, 7, 2, 2, 2, 2, 1, 256, 112, 76, 40,,,, -7, 5, 7, 2, 2, 2, 2, 1, 384, 112, 76, 40,,,, -7, 5, 7, 2, 2, 2, 2, 2, 128, 112, 76, 40,,,, -7, 5, 7, 2, 2, 2, 2, 2, 256, 112, 76, 40,,,, -7, 5, 7, 2, 2, 2, 2, 2, 384, 112, 76, 40,,,, -7, 5, 7, 2, 3, 3, 1, 1, 128, 112, 76, 40,,,, -7, 5, 7, 2, 3, 3, 1, 1, 256, 112, 76, 40,,,, -7, 5, 7, 2, 3, 3, 1, 1, 384, 112, 76, 40,,,, -7, 5, 7, 2, 3, 3, 1, 2, 128, 112, 76, 40,,,, -7, 5, 7, 2, 3, 3, 1, 2, 256, 112, 76, 40,,,, -7, 5, 7, 2, 3, 3, 1, 2, 384, 112, 76, 40,,,, -7, 5, 7, 2, 3, 3, 1, 3, 128, 112, 76, 40,,,, -7, 5, 7, 2, 3, 3, 1, 3, 256, 112, 76, 40,,,, -7, 5, 7, 2, 3, 3, 1, 3, 384, 112, 76, 40,,,, -7, 5, 7, 2, 3, 3, 2, 1, 128, 112, 76, 40,,,, -7, 5, 7, 2, 3, 3, 2, 1, 256, 112, 76, 40,,,, -7, 5, 7, 2, 3, 3, 2, 1, 384, 112, 76, 40,,,, -7, 5, 7, 2, 3, 3, 2, 2, 128, 112, 76, 40,,,, -7, 5, 7, 2, 3, 3, 2, 2, 256, 112, 76, 40,,,, -7, 5, 7, 2, 3, 3, 2, 2, 384, 112, 76, 40,,,, -7, 5, 7, 2, 3, 3, 2, 3, 128, 112, 76, 40,,,, -7, 5, 7, 2, 3, 3, 2, 3, 256, 112, 76, 40,,,, -7, 5, 7, 2, 3, 3, 2, 3, 384, 112, 76, 40,,,, -7, 5, 7, 2, 3, 3, 3, 1, 128, 112, 76, 40,,,, -7, 5, 7, 2, 3, 3, 3, 1, 256, 112, 76, 40,,,, -7, 5, 7, 2, 3, 3, 3, 1, 384, 112, 76, 40,,,, -7, 5, 7, 2, 3, 3, 3, 2, 128, 112, 76, 40,,,, -7, 5, 7, 2, 3, 3, 3, 2, 256, 112, 76, 40,,,, -7, 5, 7, 2, 3, 3, 3, 2, 384, 112, 76, 40,,,, -7, 5, 7, 2, 3, 3, 3, 3, 128, 112, 76, 40,,,, -7, 5, 7, 2, 3, 3, 3, 3, 256, 112, 76, 40,,,, -7, 5, 7, 2, 3, 3, 3, 3, 384, 112, 76, 40,,,, -7, 5, 7, 3, 1, 1, 1, 1, 128, 166, 112, 58,,,, -7, 5, 7, 3, 1, 1, 1, 1, 256, 166, 112, 58,,,, -7, 5, 7, 3, 1, 1, 1, 1, 384, 166, 112, 58,,,, -7, 5, 7, 3, 2, 2, 1, 1, 128, 166, 112, 58,,,, -7, 5, 7, 3, 2, 2, 1, 1, 256, 166, 112, 58,,,, -7, 5, 7, 3, 2, 2, 1, 1, 384, 166, 112, 58,,,, -7, 5, 7, 3, 2, 2, 1, 2, 128, 166, 112, 58,,,, -7, 5, 7, 3, 2, 2, 1, 2, 256, 166, 112, 58,,,, -7, 5, 7, 3, 2, 2, 1, 2, 384, 166, 112, 58,,,, -7, 5, 7, 3, 2, 2, 2, 1, 128, 166, 112, 58,,,, -7, 5, 7, 3, 2, 2, 2, 1, 256, 166, 112, 58,,,, -7, 5, 7, 3, 2, 2, 2, 1, 384, 166, 112, 58,,,, -7, 5, 7, 3, 2, 2, 2, 2, 128, 166, 112, 58,,,, -7, 5, 7, 3, 2, 2, 2, 2, 256, 166, 112, 58,,,, -7, 5, 7, 3, 2, 2, 2, 2, 384, 166, 112, 58,,,, -7, 5, 7, 3, 3, 3, 1, 1, 128, 166, 112, 58,,,, -7, 5, 7, 3, 3, 3, 1, 1, 256, 166, 112, 58,,,, -7, 5, 7, 3, 3, 3, 1, 1, 384, 166, 112, 58,,,, -7, 5, 7, 3, 3, 3, 1, 2, 128, 166, 112, 58,,,, -7, 5, 7, 3, 3, 3, 1, 2, 256, 166, 112, 58,,,, -7, 5, 7, 3, 3, 3, 1, 2, 384, 166, 112, 58,,,, -7, 5, 7, 3, 3, 3, 1, 3, 128, 166, 112, 58,,,, -7, 5, 7, 3, 3, 3, 1, 3, 256, 166, 112, 58,,,, -7, 5, 7, 3, 3, 3, 1, 3, 384, 166, 112, 58,,,, -7, 5, 7, 3, 3, 3, 2, 1, 128, 166, 112, 58,,,, -7, 5, 7, 3, 3, 3, 2, 1, 256, 166, 112, 58,,,, -7, 5, 7, 3, 3, 3, 2, 1, 384, 166, 112, 58,,,, -7, 5, 7, 3, 3, 3, 2, 2, 128, 166, 112, 58,,,, -7, 5, 7, 3, 3, 3, 2, 2, 256, 166, 112, 58,,,, -7, 5, 7, 3, 3, 3, 2, 2, 384, 166, 112, 58,,,, -7, 5, 7, 3, 3, 3, 2, 3, 128, 166, 112, 58,,,, -7, 5, 7, 3, 3, 3, 2, 3, 256, 166, 112, 58,,,, -7, 5, 7, 3, 3, 3, 2, 3, 384, 166, 112, 58,,,, -7, 5, 7, 3, 3, 3, 3, 1, 128, 166, 112, 58,,,, -7, 5, 7, 3, 3, 3, 3, 1, 256, 166, 112, 58,,,, -7, 5, 7, 3, 3, 3, 3, 1, 384, 166, 112, 58,,,, -7, 5, 7, 3, 3, 3, 3, 2, 128, 166, 112, 58,,,, -7, 5, 7, 3, 3, 3, 3, 2, 256, 166, 112, 58,,,, -7, 5, 7, 3, 3, 3, 3, 2, 384, 166, 112, 58,,,, -7, 5, 7, 3, 3, 3, 3, 3, 128, 166, 112, 58,,,, -7, 5, 7, 3, 3, 3, 3, 3, 256, 166, 112, 58,,,, -7, 5, 7, 3, 3, 3, 3, 3, 384, 166, 112, 58,,,, -7, 5, 7, 4, 1, 1, 1, 1, 128, 220, 148, 76,,,, -7, 5, 7, 4, 1, 1, 1, 1, 256, 220, 148, 76,,,, -7, 5, 7, 4, 1, 1, 1, 1, 384, 220, 148, 76,,,, -7, 5, 7, 4, 2, 2, 1, 1, 128, 220, 148, 76,,,, -7, 5, 7, 4, 2, 2, 1, 1, 256, 220, 148, 76,,,, -7, 5, 7, 4, 2, 2, 1, 1, 384, 220, 148, 76,,,, -7, 5, 7, 4, 2, 2, 1, 2, 128, 220, 148, 76,,,, -7, 5, 7, 4, 2, 2, 1, 2, 256, 220, 148, 76,,,, -7, 5, 7, 4, 2, 2, 1, 2, 384, 220, 148, 76,,,, -7, 5, 7, 4, 2, 2, 2, 1, 128, 220, 148, 76,,,, -7, 5, 7, 4, 2, 2, 2, 1, 256, 220, 148, 76,,,, -7, 5, 7, 4, 2, 2, 2, 1, 384, 220, 148, 76,,,, -7, 5, 7, 4, 2, 2, 2, 2, 128, 220, 148, 76,,,, -7, 5, 7, 4, 2, 2, 2, 2, 256, 220, 148, 76,,,, -7, 5, 7, 4, 2, 2, 2, 2, 384, 220, 148, 76,,,, -7, 5, 7, 4, 3, 3, 1, 1, 128, 220, 148, 76,,,, -7, 5, 7, 4, 3, 3, 1, 1, 256, 220, 148, 76,,,, -7, 5, 7, 4, 3, 3, 1, 1, 384, 220, 148, 76,,,, -7, 5, 7, 4, 3, 3, 1, 2, 128, 220, 148, 76,,,, -7, 5, 7, 4, 3, 3, 1, 2, 256, 220, 148, 76,,,, -7, 5, 7, 4, 3, 3, 1, 2, 384, 220, 148, 76,,,, -7, 5, 7, 4, 3, 3, 1, 3, 128, 220, 148, 76,,,, -7, 5, 7, 4, 3, 3, 1, 3, 256, 220, 148, 76,,,, -7, 5, 7, 4, 3, 3, 1, 3, 384, 220, 148, 76,,,, -7, 5, 7, 4, 3, 3, 2, 1, 128, 220, 148, 76,,,, -7, 5, 7, 4, 3, 3, 2, 1, 256, 220, 148, 76,,,, -7, 5, 7, 4, 3, 3, 2, 1, 384, 220, 148, 76,,,, -7, 5, 7, 4, 3, 3, 2, 2, 128, 220, 148, 76,,,, -7, 5, 7, 4, 3, 3, 2, 2, 256, 220, 148, 76,,,, -7, 5, 7, 4, 3, 3, 2, 2, 384, 220, 148, 76,,,, -7, 5, 7, 4, 3, 3, 2, 3, 128, 220, 148, 76,,,, -7, 5, 7, 4, 3, 3, 2, 3, 256, 220, 148, 76,,,, -7, 5, 7, 4, 3, 3, 2, 3, 384, 220, 148, 76,,,, -7, 5, 7, 4, 3, 3, 3, 1, 128, 220, 148, 76,,,, -7, 5, 7, 4, 3, 3, 3, 1, 256, 220, 148, 76,,,, -7, 5, 7, 4, 3, 3, 3, 1, 384, 220, 148, 76,,,, -7, 5, 7, 4, 3, 3, 3, 2, 128, 220, 148, 76,,,, -7, 5, 7, 4, 3, 3, 3, 2, 256, 220, 148, 76,,,, -7, 5, 7, 4, 3, 3, 3, 2, 384, 220, 148, 76,,,, -7, 5, 7, 4, 3, 3, 3, 3, 128, 220, 148, 76,,,, -7, 5, 7, 4, 3, 3, 3, 3, 256, 220, 148, 76,,,, -7, 5, 7, 4, 3, 3, 3, 3, 384, 220, 148, 76,,,, -7, 5, 7, 5, 1, 1, 1, 1, 128, 240, 184, 94,,,, -7, 5, 7, 5, 1, 1, 1, 1, 256, 240, 184, 94,,,, -7, 5, 7, 5, 1, 1, 1, 1, 384, 240, 184, 94,,,, -7, 5, 7, 5, 2, 2, 1, 1, 128, 240, 184, 94,,,, -7, 5, 7, 5, 2, 2, 1, 1, 256, 240, 184, 94,,,, -7, 5, 7, 5, 2, 2, 1, 1, 384, 240, 184, 94,,,, -7, 5, 7, 5, 2, 2, 1, 2, 128, 240, 184, 94,,,, -7, 5, 7, 5, 2, 2, 1, 2, 256, 240, 184, 94,,,, -7, 5, 7, 5, 2, 2, 1, 2, 384, 240, 184, 94,,,, -7, 5, 7, 5, 2, 2, 2, 1, 128, 240, 184, 94,,,, -7, 5, 7, 5, 2, 2, 2, 1, 256, 240, 184, 94,,,, -7, 5, 7, 5, 2, 2, 2, 1, 384, 240, 184, 94,,,, -7, 5, 7, 5, 2, 2, 2, 2, 128, 240, 184, 94,,,, -7, 5, 7, 5, 2, 2, 2, 2, 256, 240, 184, 94,,,, -7, 5, 7, 5, 2, 2, 2, 2, 384, 240, 184, 94,,,, -7, 5, 7, 5, 3, 3, 1, 1, 128, 240, 184, 94,,,, -7, 5, 7, 5, 3, 3, 1, 1, 256, 240, 184, 94,,,, -7, 5, 7, 5, 3, 3, 1, 1, 384, 240, 184, 94,,,, -7, 5, 7, 5, 3, 3, 1, 2, 128, 240, 184, 94,,,, -7, 5, 7, 5, 3, 3, 1, 2, 256, 240, 184, 94,,,, -7, 5, 7, 5, 3, 3, 1, 2, 384, 240, 184, 94,,,, -7, 5, 7, 5, 3, 3, 1, 3, 128, 240, 184, 94,,,, -7, 5, 7, 5, 3, 3, 1, 3, 256, 240, 184, 94,,,, -7, 5, 7, 5, 3, 3, 1, 3, 384, 240, 184, 94,,,, -7, 5, 7, 5, 3, 3, 2, 1, 128, 240, 184, 94,,,, -7, 5, 7, 5, 3, 3, 2, 1, 256, 240, 184, 94,,,, -7, 5, 7, 5, 3, 3, 2, 1, 384, 240, 184, 94,,,, -7, 5, 7, 5, 3, 3, 2, 2, 128, 240, 184, 94,,,, -7, 5, 7, 5, 3, 3, 2, 2, 256, 240, 184, 94,,,, -7, 5, 7, 5, 3, 3, 2, 2, 384, 240, 184, 94,,,, -7, 5, 7, 5, 3, 3, 2, 3, 128, 240, 184, 94,,,, -7, 5, 7, 5, 3, 3, 2, 3, 256, 240, 184, 94,,,, -7, 5, 7, 5, 3, 3, 2, 3, 384, 240, 184, 94,,,, -7, 5, 7, 5, 3, 3, 3, 1, 128, 240, 184, 94,,,, -7, 5, 7, 5, 3, 3, 3, 1, 256, 240, 184, 94,,,, -7, 5, 7, 5, 3, 3, 3, 1, 384, 240, 184, 94,,,, -7, 5, 7, 5, 3, 3, 3, 2, 128, 240, 184, 94,,,, -7, 5, 7, 5, 3, 3, 3, 2, 256, 240, 184, 94,,,, -7, 5, 7, 5, 3, 3, 3, 2, 384, 240, 184, 94,,,, -7, 5, 7, 5, 3, 3, 3, 3, 128, 240, 184, 94,,,, -7, 5, 7, 5, 3, 3, 3, 3, 256, 240, 184, 94,,,, -7, 5, 7, 5, 3, 3, 3, 3, 384, 240, 184, 94,,,, -7, 6, 1, 1, 1, 1, 1, 1, 128, 59, 41, 23,,,, -7, 6, 1, 1, 1, 1, 1, 1, 256, 59, 41, 23,,,, -7, 6, 1, 1, 1, 1, 1, 1, 384, 59, 41, 23,,,, -7, 6, 1, 1, 2, 2, 1, 1, 128, 59, 41, 23,,,, -7, 6, 1, 1, 2, 2, 1, 1, 256, 59, 41, 23,,,, -7, 6, 1, 1, 2, 2, 1, 1, 384, 59, 41, 23,,,, -7, 6, 1, 1, 2, 2, 1, 2, 128, 59, 41, 23,,,, -7, 6, 1, 1, 2, 2, 1, 2, 256, 59, 41, 23,,,, -7, 6, 1, 1, 2, 2, 1, 2, 384, 59, 41, 23,,,, -7, 6, 1, 1, 2, 2, 2, 1, 128, 59, 41, 23,,,, -7, 6, 1, 1, 2, 2, 2, 1, 256, 59, 41, 23,,,, -7, 6, 1, 1, 2, 2, 2, 1, 384, 59, 41, 23,,,, -7, 6, 1, 1, 2, 2, 2, 2, 128, 59, 41, 23,,,, -7, 6, 1, 1, 2, 2, 2, 2, 256, 59, 41, 23,,,, -7, 6, 1, 1, 2, 2, 2, 2, 384, 59, 41, 23,,,, -7, 6, 1, 1, 3, 3, 1, 1, 128, 59, 41, 23,,,, -7, 6, 1, 1, 3, 3, 1, 1, 256, 59, 41, 23,,,, -7, 6, 1, 1, 3, 3, 1, 1, 384, 59, 41, 23,,,, -7, 6, 1, 1, 3, 3, 1, 2, 128, 59, 41, 23,,,, -7, 6, 1, 1, 3, 3, 1, 2, 256, 59, 41, 23,,,, -7, 6, 1, 1, 3, 3, 1, 2, 384, 59, 41, 23,,,, -7, 6, 1, 1, 3, 3, 1, 3, 128, 59, 41, 23,,,, -7, 6, 1, 1, 3, 3, 1, 3, 256, 59, 41, 23,,,, -7, 6, 1, 1, 3, 3, 1, 3, 384, 59, 41, 23,,,, -7, 6, 1, 1, 3, 3, 2, 1, 128, 59, 41, 23,,,, -7, 6, 1, 1, 3, 3, 2, 1, 256, 59, 41, 23,,,, -7, 6, 1, 1, 3, 3, 2, 1, 384, 59, 41, 23,,,, -7, 6, 1, 1, 3, 3, 2, 2, 128, 59, 41, 23,,,, -7, 6, 1, 1, 3, 3, 2, 2, 256, 59, 41, 23,,,, -7, 6, 1, 1, 3, 3, 2, 2, 384, 59, 41, 23,,,, -7, 6, 1, 1, 3, 3, 2, 3, 128, 59, 41, 23,,,, -7, 6, 1, 1, 3, 3, 2, 3, 256, 59, 41, 23,,,, -7, 6, 1, 1, 3, 3, 2, 3, 384, 59, 41, 23,,,, -7, 6, 1, 1, 3, 3, 3, 1, 128, 59, 41, 23,,,, -7, 6, 1, 1, 3, 3, 3, 1, 256, 59, 41, 23,,,, -7, 6, 1, 1, 3, 3, 3, 1, 384, 59, 41, 23,,,, -7, 6, 1, 1, 3, 3, 3, 2, 128, 59, 41, 23,,,, -7, 6, 1, 1, 3, 3, 3, 2, 256, 59, 41, 23,,,, -7, 6, 1, 1, 3, 3, 3, 2, 384, 59, 41, 23,,,, -7, 6, 1, 1, 3, 3, 3, 3, 128, 59, 41, 23,,,, -7, 6, 1, 1, 3, 3, 3, 3, 256, 59, 41, 23,,,, -7, 6, 1, 1, 3, 3, 3, 3, 384, 59, 41, 23,,,, -7, 6, 1, 2, 1, 1, 1, 1, 128, 113, 77, 41,,,, -7, 6, 1, 2, 1, 1, 1, 1, 256, 113, 77, 41,,,, -7, 6, 1, 2, 1, 1, 1, 1, 384, 113, 77, 41,,,, -7, 6, 1, 2, 2, 2, 1, 1, 128, 113, 77, 41,,,, -7, 6, 1, 2, 2, 2, 1, 1, 256, 113, 77, 41,,,, -7, 6, 1, 2, 2, 2, 1, 1, 384, 113, 77, 41,,,, -7, 6, 1, 2, 2, 2, 1, 2, 128, 113, 77, 41,,,, -7, 6, 1, 2, 2, 2, 1, 2, 256, 113, 77, 41,,,, -7, 6, 1, 2, 2, 2, 1, 2, 384, 113, 77, 41,,,, -7, 6, 1, 2, 2, 2, 2, 1, 128, 113, 77, 41,,,, -7, 6, 1, 2, 2, 2, 2, 1, 256, 113, 77, 41,,,, -7, 6, 1, 2, 2, 2, 2, 1, 384, 113, 77, 41,,,, -7, 6, 1, 2, 2, 2, 2, 2, 128, 113, 77, 41,,,, -7, 6, 1, 2, 2, 2, 2, 2, 256, 113, 77, 41,,,, -7, 6, 1, 2, 2, 2, 2, 2, 384, 113, 77, 41,,,, -7, 6, 1, 2, 3, 3, 1, 1, 128, 113, 77, 41,,,, -7, 6, 1, 2, 3, 3, 1, 1, 256, 113, 77, 41,,,, -7, 6, 1, 2, 3, 3, 1, 1, 384, 113, 77, 41,,,, -7, 6, 1, 2, 3, 3, 1, 2, 128, 113, 77, 41,,,, -7, 6, 1, 2, 3, 3, 1, 2, 256, 113, 77, 41,,,, -7, 6, 1, 2, 3, 3, 1, 2, 384, 113, 77, 41,,,, -7, 6, 1, 2, 3, 3, 1, 3, 128, 113, 77, 41,,,, -7, 6, 1, 2, 3, 3, 1, 3, 256, 113, 77, 41,,,, -7, 6, 1, 2, 3, 3, 1, 3, 384, 113, 77, 41,,,, -7, 6, 1, 2, 3, 3, 2, 1, 128, 113, 77, 41,,,, -7, 6, 1, 2, 3, 3, 2, 1, 256, 113, 77, 41,,,, -7, 6, 1, 2, 3, 3, 2, 1, 384, 113, 77, 41,,,, -7, 6, 1, 2, 3, 3, 2, 2, 128, 113, 77, 41,,,, -7, 6, 1, 2, 3, 3, 2, 2, 256, 113, 77, 41,,,, -7, 6, 1, 2, 3, 3, 2, 2, 384, 113, 77, 41,,,, -7, 6, 1, 2, 3, 3, 2, 3, 128, 113, 77, 41,,,, -7, 6, 1, 2, 3, 3, 2, 3, 256, 113, 77, 41,,,, -7, 6, 1, 2, 3, 3, 2, 3, 384, 113, 77, 41,,,, -7, 6, 1, 2, 3, 3, 3, 1, 128, 113, 77, 41,,,, -7, 6, 1, 2, 3, 3, 3, 1, 256, 113, 77, 41,,,, -7, 6, 1, 2, 3, 3, 3, 1, 384, 113, 77, 41,,,, -7, 6, 1, 2, 3, 3, 3, 2, 128, 113, 77, 41,,,, -7, 6, 1, 2, 3, 3, 3, 2, 256, 113, 77, 41,,,, -7, 6, 1, 2, 3, 3, 3, 2, 384, 113, 77, 41,,,, -7, 6, 1, 2, 3, 3, 3, 3, 128, 113, 77, 41,,,, -7, 6, 1, 2, 3, 3, 3, 3, 256, 113, 77, 41,,,, -7, 6, 1, 2, 3, 3, 3, 3, 384, 113, 77, 41,,,, -7, 6, 1, 3, 1, 1, 1, 1, 128, 167, 113, 59,,,, -7, 6, 1, 3, 1, 1, 1, 1, 256, 167, 113, 59,,,, -7, 6, 1, 3, 1, 1, 1, 1, 384, 167, 113, 59,,,, -7, 6, 1, 3, 2, 2, 1, 1, 128, 167, 113, 59,,,, -7, 6, 1, 3, 2, 2, 1, 1, 256, 167, 113, 59,,,, -7, 6, 1, 3, 2, 2, 1, 1, 384, 167, 113, 59,,,, -7, 6, 1, 3, 2, 2, 1, 2, 128, 167, 113, 59,,,, -7, 6, 1, 3, 2, 2, 1, 2, 256, 167, 113, 59,,,, -7, 6, 1, 3, 2, 2, 1, 2, 384, 167, 113, 59,,,, -7, 6, 1, 3, 2, 2, 2, 1, 128, 167, 113, 59,,,, -7, 6, 1, 3, 2, 2, 2, 1, 256, 167, 113, 59,,,, -7, 6, 1, 3, 2, 2, 2, 1, 384, 167, 113, 59,,,, -7, 6, 1, 3, 2, 2, 2, 2, 128, 167, 113, 59,,,, -7, 6, 1, 3, 2, 2, 2, 2, 256, 167, 113, 59,,,, -7, 6, 1, 3, 2, 2, 2, 2, 384, 167, 113, 59,,,, -7, 6, 1, 3, 3, 3, 1, 1, 128, 167, 113, 59,,,, -7, 6, 1, 3, 3, 3, 1, 1, 256, 167, 113, 59,,,, -7, 6, 1, 3, 3, 3, 1, 1, 384, 167, 113, 59,,,, -7, 6, 1, 3, 3, 3, 1, 2, 128, 167, 113, 59,,,, -7, 6, 1, 3, 3, 3, 1, 2, 256, 167, 113, 59,,,, -7, 6, 1, 3, 3, 3, 1, 2, 384, 167, 113, 59,,,, -7, 6, 1, 3, 3, 3, 1, 3, 128, 167, 113, 59,,,, -7, 6, 1, 3, 3, 3, 1, 3, 256, 167, 113, 59,,,, -7, 6, 1, 3, 3, 3, 1, 3, 384, 167, 113, 59,,,, -7, 6, 1, 3, 3, 3, 2, 1, 128, 167, 113, 59,,,, -7, 6, 1, 3, 3, 3, 2, 1, 256, 167, 113, 59,,,, -7, 6, 1, 3, 3, 3, 2, 1, 384, 167, 113, 59,,,, -7, 6, 1, 3, 3, 3, 2, 2, 128, 167, 113, 59,,,, -7, 6, 1, 3, 3, 3, 2, 2, 256, 167, 113, 59,,,, -7, 6, 1, 3, 3, 3, 2, 2, 384, 167, 113, 59,,,, -7, 6, 1, 3, 3, 3, 2, 3, 128, 167, 113, 59,,,, -7, 6, 1, 3, 3, 3, 2, 3, 256, 167, 113, 59,,,, -7, 6, 1, 3, 3, 3, 2, 3, 384, 167, 113, 59,,,, -7, 6, 1, 3, 3, 3, 3, 1, 128, 167, 113, 59,,,, -7, 6, 1, 3, 3, 3, 3, 1, 256, 167, 113, 59,,,, -7, 6, 1, 3, 3, 3, 3, 1, 384, 167, 113, 59,,,, -7, 6, 1, 3, 3, 3, 3, 2, 128, 167, 113, 59,,,, -7, 6, 1, 3, 3, 3, 3, 2, 256, 167, 113, 59,,,, -7, 6, 1, 3, 3, 3, 3, 2, 384, 167, 113, 59,,,, -7, 6, 1, 3, 3, 3, 3, 3, 128, 167, 113, 59,,,, -7, 6, 1, 3, 3, 3, 3, 3, 256, 167, 113, 59,,,, -7, 6, 1, 3, 3, 3, 3, 3, 384, 167, 113, 59,,,, -7, 6, 1, 4, 1, 1, 1, 1, 128, 221, 149, 77,,,, -7, 6, 1, 4, 1, 1, 1, 1, 256, 221, 149, 77,,,, -7, 6, 1, 4, 1, 1, 1, 1, 384, 221, 149, 77,,,, -7, 6, 1, 4, 2, 2, 1, 1, 128, 221, 149, 77,,,, -7, 6, 1, 4, 2, 2, 1, 1, 256, 221, 149, 77,,,, -7, 6, 1, 4, 2, 2, 1, 1, 384, 221, 149, 77,,,, -7, 6, 1, 4, 2, 2, 1, 2, 128, 221, 149, 77,,,, -7, 6, 1, 4, 2, 2, 1, 2, 256, 221, 149, 77,,,, -7, 6, 1, 4, 2, 2, 1, 2, 384, 221, 149, 77,,,, -7, 6, 1, 4, 2, 2, 2, 1, 128, 221, 149, 77,,,, -7, 6, 1, 4, 2, 2, 2, 1, 256, 221, 149, 77,,,, -7, 6, 1, 4, 2, 2, 2, 1, 384, 221, 149, 77,,,, -7, 6, 1, 4, 2, 2, 2, 2, 128, 221, 149, 77,,,, -7, 6, 1, 4, 2, 2, 2, 2, 256, 221, 149, 77,,,, -7, 6, 1, 4, 2, 2, 2, 2, 384, 221, 149, 77,,,, -7, 6, 1, 4, 3, 3, 1, 1, 128, 221, 149, 77,,,, -7, 6, 1, 4, 3, 3, 1, 1, 256, 221, 149, 77,,,, -7, 6, 1, 4, 3, 3, 1, 1, 384, 221, 149, 77,,,, -7, 6, 1, 4, 3, 3, 1, 2, 128, 221, 149, 77,,,, -7, 6, 1, 4, 3, 3, 1, 2, 256, 221, 149, 77,,,, -7, 6, 1, 4, 3, 3, 1, 2, 384, 221, 149, 77,,,, -7, 6, 1, 4, 3, 3, 1, 3, 128, 221, 149, 77,,,, -7, 6, 1, 4, 3, 3, 1, 3, 256, 221, 149, 77,,,, -7, 6, 1, 4, 3, 3, 1, 3, 384, 221, 149, 77,,,, -7, 6, 1, 4, 3, 3, 2, 1, 128, 221, 149, 77,,,, -7, 6, 1, 4, 3, 3, 2, 1, 256, 221, 149, 77,,,, -7, 6, 1, 4, 3, 3, 2, 1, 384, 221, 149, 77,,,, -7, 6, 1, 4, 3, 3, 2, 2, 128, 221, 149, 77,,,, -7, 6, 1, 4, 3, 3, 2, 2, 256, 221, 149, 77,,,, -7, 6, 1, 4, 3, 3, 2, 2, 384, 221, 149, 77,,,, -7, 6, 1, 4, 3, 3, 2, 3, 128, 221, 149, 77,,,, -7, 6, 1, 4, 3, 3, 2, 3, 256, 221, 149, 77,,,, -7, 6, 1, 4, 3, 3, 2, 3, 384, 221, 149, 77,,,, -7, 6, 1, 4, 3, 3, 3, 1, 128, 221, 149, 77,,,, -7, 6, 1, 4, 3, 3, 3, 1, 256, 221, 149, 77,,,, -7, 6, 1, 4, 3, 3, 3, 1, 384, 221, 149, 77,,,, -7, 6, 1, 4, 3, 3, 3, 2, 128, 221, 149, 77,,,, -7, 6, 1, 4, 3, 3, 3, 2, 256, 221, 149, 77,,,, -7, 6, 1, 4, 3, 3, 3, 2, 384, 221, 149, 77,,,, -7, 6, 1, 4, 3, 3, 3, 3, 128, 221, 149, 77,,,, -7, 6, 1, 4, 3, 3, 3, 3, 256, 221, 149, 77,,,, -7, 6, 1, 4, 3, 3, 3, 3, 384, 221, 149, 77,,,, -7, 6, 1, 5, 1, 1, 1, 1, 128, 240, 185, 95,,,, -7, 6, 1, 5, 1, 1, 1, 1, 256, 240, 185, 95,,,, -7, 6, 1, 5, 1, 1, 1, 1, 384, 240, 185, 95,,,, -7, 6, 1, 5, 2, 2, 1, 1, 128, 240, 185, 95,,,, -7, 6, 1, 5, 2, 2, 1, 1, 256, 240, 185, 95,,,, -7, 6, 1, 5, 2, 2, 1, 1, 384, 240, 185, 95,,,, -7, 6, 1, 5, 2, 2, 1, 2, 128, 240, 185, 95,,,, -7, 6, 1, 5, 2, 2, 1, 2, 256, 240, 185, 95,,,, -7, 6, 1, 5, 2, 2, 1, 2, 384, 240, 185, 95,,,, -7, 6, 1, 5, 2, 2, 2, 1, 128, 240, 185, 95,,,, -7, 6, 1, 5, 2, 2, 2, 1, 256, 240, 185, 95,,,, -7, 6, 1, 5, 2, 2, 2, 1, 384, 240, 185, 95,,,, -7, 6, 1, 5, 2, 2, 2, 2, 128, 240, 185, 95,,,, -7, 6, 1, 5, 2, 2, 2, 2, 256, 240, 185, 95,,,, -7, 6, 1, 5, 2, 2, 2, 2, 384, 240, 185, 95,,,, -7, 6, 1, 5, 3, 3, 1, 1, 128, 240, 185, 95,,,, -7, 6, 1, 5, 3, 3, 1, 1, 256, 240, 185, 95,,,, -7, 6, 1, 5, 3, 3, 1, 1, 384, 240, 185, 95,,,, -7, 6, 1, 5, 3, 3, 1, 2, 128, 240, 185, 95,,,, -7, 6, 1, 5, 3, 3, 1, 2, 256, 240, 185, 95,,,, -7, 6, 1, 5, 3, 3, 1, 2, 384, 240, 185, 95,,,, -7, 6, 1, 5, 3, 3, 1, 3, 128, 240, 185, 95,,,, -7, 6, 1, 5, 3, 3, 1, 3, 256, 240, 185, 95,,,, -7, 6, 1, 5, 3, 3, 1, 3, 384, 240, 185, 95,,,, -7, 6, 1, 5, 3, 3, 2, 1, 128, 240, 185, 95,,,, -7, 6, 1, 5, 3, 3, 2, 1, 256, 240, 185, 95,,,, -7, 6, 1, 5, 3, 3, 2, 1, 384, 240, 185, 95,,,, -7, 6, 1, 5, 3, 3, 2, 2, 128, 240, 185, 95,,,, -7, 6, 1, 5, 3, 3, 2, 2, 256, 240, 185, 95,,,, -7, 6, 1, 5, 3, 3, 2, 2, 384, 240, 185, 95,,,, -7, 6, 1, 5, 3, 3, 2, 3, 128, 240, 185, 95,,,, -7, 6, 1, 5, 3, 3, 2, 3, 256, 240, 185, 95,,,, -7, 6, 1, 5, 3, 3, 2, 3, 384, 240, 185, 95,,,, -7, 6, 1, 5, 3, 3, 3, 1, 128, 240, 185, 95,,,, -7, 6, 1, 5, 3, 3, 3, 1, 256, 240, 185, 95,,,, -7, 6, 1, 5, 3, 3, 3, 1, 384, 240, 185, 95,,,, -7, 6, 1, 5, 3, 3, 3, 2, 128, 240, 185, 95,,,, -7, 6, 1, 5, 3, 3, 3, 2, 256, 240, 185, 95,,,, -7, 6, 1, 5, 3, 3, 3, 2, 384, 240, 185, 95,,,, -7, 6, 1, 5, 3, 3, 3, 3, 128, 240, 185, 95,,,, -7, 6, 1, 5, 3, 3, 3, 3, 256, 240, 185, 95,,,, -7, 6, 1, 5, 3, 3, 3, 3, 384, 240, 185, 95,,,, -7, 6, 1, 6, 1, 1, 1, 1, 128, 240, 221, 113,,,, -7, 6, 1, 6, 1, 1, 1, 1, 256, 240, 221, 113,,,, -7, 6, 1, 6, 1, 1, 1, 1, 384, 240, 221, 113,,,, -7, 6, 1, 6, 2, 2, 1, 1, 128, 240, 221, 113,,,, -7, 6, 1, 6, 2, 2, 1, 1, 256, 240, 221, 113,,,, -7, 6, 1, 6, 2, 2, 1, 1, 384, 240, 221, 113,,,, -7, 6, 1, 6, 2, 2, 1, 2, 128, 240, 221, 113,,,, -7, 6, 1, 6, 2, 2, 1, 2, 256, 240, 221, 113,,,, -7, 6, 1, 6, 2, 2, 1, 2, 384, 240, 221, 113,,,, -7, 6, 1, 6, 2, 2, 2, 1, 128, 240, 221, 113,,,, -7, 6, 1, 6, 2, 2, 2, 1, 256, 240, 221, 113,,,, -7, 6, 1, 6, 2, 2, 2, 1, 384, 240, 221, 113,,,, -7, 6, 1, 6, 2, 2, 2, 2, 128, 240, 221, 113,,,, -7, 6, 1, 6, 2, 2, 2, 2, 256, 240, 221, 113,,,, -7, 6, 1, 6, 2, 2, 2, 2, 384, 240, 221, 113,,,, -7, 6, 1, 6, 3, 3, 1, 1, 128, 240, 221, 113,,,, -7, 6, 1, 6, 3, 3, 1, 1, 256, 240, 221, 113,,,, -7, 6, 1, 6, 3, 3, 1, 1, 384, 240, 221, 113,,,, -7, 6, 1, 6, 3, 3, 1, 2, 128, 240, 221, 113,,,, -7, 6, 1, 6, 3, 3, 1, 2, 256, 240, 221, 113,,,, -7, 6, 1, 6, 3, 3, 1, 2, 384, 240, 221, 113,,,, -7, 6, 1, 6, 3, 3, 1, 3, 128, 240, 221, 113,,,, -7, 6, 1, 6, 3, 3, 1, 3, 256, 240, 221, 113,,,, -7, 6, 1, 6, 3, 3, 1, 3, 384, 240, 221, 113,,,, -7, 6, 1, 6, 3, 3, 2, 1, 128, 240, 221, 113,,,, -7, 6, 1, 6, 3, 3, 2, 1, 256, 240, 221, 113,,,, -7, 6, 1, 6, 3, 3, 2, 1, 384, 240, 221, 113,,,, -7, 6, 1, 6, 3, 3, 2, 2, 128, 240, 221, 113,,,, -7, 6, 1, 6, 3, 3, 2, 2, 256, 240, 221, 113,,,, -7, 6, 1, 6, 3, 3, 2, 2, 384, 240, 221, 113,,,, -7, 6, 1, 6, 3, 3, 2, 3, 128, 240, 221, 113,,,, -7, 6, 1, 6, 3, 3, 2, 3, 256, 240, 221, 113,,,, -7, 6, 1, 6, 3, 3, 2, 3, 384, 240, 221, 113,,,, -7, 6, 1, 6, 3, 3, 3, 1, 128, 240, 221, 113,,,, -7, 6, 1, 6, 3, 3, 3, 1, 256, 240, 221, 113,,,, -7, 6, 1, 6, 3, 3, 3, 1, 384, 240, 221, 113,,,, -7, 6, 1, 6, 3, 3, 3, 2, 128, 240, 221, 113,,,, -7, 6, 1, 6, 3, 3, 3, 2, 256, 240, 221, 113,,,, -7, 6, 1, 6, 3, 3, 3, 2, 384, 240, 221, 113,,,, -7, 6, 1, 6, 3, 3, 3, 3, 128, 240, 221, 113,,,, -7, 6, 1, 6, 3, 3, 3, 3, 256, 240, 221, 113,,,, -7, 6, 1, 6, 3, 3, 3, 3, 384, 240, 221, 113,,,, -7, 6, 2, 1, 1, 1, 1, 1, 128, 59, 41, 23,,,, -7, 6, 2, 1, 1, 1, 1, 1, 256, 59, 41, 23,,,, -7, 6, 2, 1, 1, 1, 1, 1, 384, 59, 41, 23,,,, -7, 6, 2, 1, 2, 2, 1, 1, 128, 59, 41, 23,,,, -7, 6, 2, 1, 2, 2, 1, 1, 256, 59, 41, 23,,,, -7, 6, 2, 1, 2, 2, 1, 1, 384, 59, 41, 23,,,, -7, 6, 2, 1, 2, 2, 1, 2, 128, 59, 41, 23,,,, -7, 6, 2, 1, 2, 2, 1, 2, 256, 59, 41, 23,,,, -7, 6, 2, 1, 2, 2, 1, 2, 384, 59, 41, 23,,,, -7, 6, 2, 1, 2, 2, 2, 1, 128, 59, 41, 23,,,, -7, 6, 2, 1, 2, 2, 2, 1, 256, 59, 41, 23,,,, -7, 6, 2, 1, 2, 2, 2, 1, 384, 59, 41, 23,,,, -7, 6, 2, 1, 2, 2, 2, 2, 128, 59, 41, 23,,,, -7, 6, 2, 1, 2, 2, 2, 2, 256, 59, 41, 23,,,, -7, 6, 2, 1, 2, 2, 2, 2, 384, 59, 41, 23,,,, -7, 6, 2, 1, 3, 3, 1, 1, 128, 59, 41, 23,,,, -7, 6, 2, 1, 3, 3, 1, 1, 256, 59, 41, 23,,,, -7, 6, 2, 1, 3, 3, 1, 1, 384, 59, 41, 23,,,, -7, 6, 2, 1, 3, 3, 1, 2, 128, 59, 41, 23,,,, -7, 6, 2, 1, 3, 3, 1, 2, 256, 59, 41, 23,,,, -7, 6, 2, 1, 3, 3, 1, 2, 384, 59, 41, 23,,,, -7, 6, 2, 1, 3, 3, 1, 3, 128, 59, 41, 23,,,, -7, 6, 2, 1, 3, 3, 1, 3, 256, 59, 41, 23,,,, -7, 6, 2, 1, 3, 3, 1, 3, 384, 59, 41, 23,,,, -7, 6, 2, 1, 3, 3, 2, 1, 128, 59, 41, 23,,,, -7, 6, 2, 1, 3, 3, 2, 1, 256, 59, 41, 23,,,, -7, 6, 2, 1, 3, 3, 2, 1, 384, 59, 41, 23,,,, -7, 6, 2, 1, 3, 3, 2, 2, 128, 59, 41, 23,,,, -7, 6, 2, 1, 3, 3, 2, 2, 256, 59, 41, 23,,,, -7, 6, 2, 1, 3, 3, 2, 2, 384, 59, 41, 23,,,, -7, 6, 2, 1, 3, 3, 2, 3, 128, 59, 41, 23,,,, -7, 6, 2, 1, 3, 3, 2, 3, 256, 59, 41, 23,,,, -7, 6, 2, 1, 3, 3, 2, 3, 384, 59, 41, 23,,,, -7, 6, 2, 1, 3, 3, 3, 1, 128, 59, 41, 23,,,, -7, 6, 2, 1, 3, 3, 3, 1, 256, 59, 41, 23,,,, -7, 6, 2, 1, 3, 3, 3, 1, 384, 59, 41, 23,,,, -7, 6, 2, 1, 3, 3, 3, 2, 128, 59, 41, 23,,,, -7, 6, 2, 1, 3, 3, 3, 2, 256, 59, 41, 23,,,, -7, 6, 2, 1, 3, 3, 3, 2, 384, 59, 41, 23,,,, -7, 6, 2, 1, 3, 3, 3, 3, 128, 59, 41, 23,,,, -7, 6, 2, 1, 3, 3, 3, 3, 256, 59, 41, 23,,,, -7, 6, 2, 1, 3, 3, 3, 3, 384, 59, 41, 23,,,, -7, 6, 2, 2, 1, 1, 1, 1, 128, 113, 77, 41,,,, -7, 6, 2, 2, 1, 1, 1, 1, 256, 113, 77, 41,,,, -7, 6, 2, 2, 1, 1, 1, 1, 384, 113, 77, 41,,,, -7, 6, 2, 2, 2, 2, 1, 1, 128, 113, 77, 41,,,, -7, 6, 2, 2, 2, 2, 1, 1, 256, 113, 77, 41,,,, -7, 6, 2, 2, 2, 2, 1, 1, 384, 113, 77, 41,,,, -7, 6, 2, 2, 2, 2, 1, 2, 128, 113, 77, 41,,,, -7, 6, 2, 2, 2, 2, 1, 2, 256, 113, 77, 41,,,, -7, 6, 2, 2, 2, 2, 1, 2, 384, 113, 77, 41,,,, -7, 6, 2, 2, 2, 2, 2, 1, 128, 113, 77, 41,,,, -7, 6, 2, 2, 2, 2, 2, 1, 256, 113, 77, 41,,,, -7, 6, 2, 2, 2, 2, 2, 1, 384, 113, 77, 41,,,, -7, 6, 2, 2, 2, 2, 2, 2, 128, 113, 77, 41,,,, -7, 6, 2, 2, 2, 2, 2, 2, 256, 113, 77, 41,,,, -7, 6, 2, 2, 2, 2, 2, 2, 384, 113, 77, 41,,,, -7, 6, 2, 2, 3, 3, 1, 1, 128, 113, 77, 41,,,, -7, 6, 2, 2, 3, 3, 1, 1, 256, 113, 77, 41,,,, -7, 6, 2, 2, 3, 3, 1, 1, 384, 113, 77, 41,,,, -7, 6, 2, 2, 3, 3, 1, 2, 128, 113, 77, 41,,,, -7, 6, 2, 2, 3, 3, 1, 2, 256, 113, 77, 41,,,, -7, 6, 2, 2, 3, 3, 1, 2, 384, 113, 77, 41,,,, -7, 6, 2, 2, 3, 3, 1, 3, 128, 113, 77, 41,,,, -7, 6, 2, 2, 3, 3, 1, 3, 256, 113, 77, 41,,,, -7, 6, 2, 2, 3, 3, 1, 3, 384, 113, 77, 41,,,, -7, 6, 2, 2, 3, 3, 2, 1, 128, 113, 77, 41,,,, -7, 6, 2, 2, 3, 3, 2, 1, 256, 113, 77, 41,,,, -7, 6, 2, 2, 3, 3, 2, 1, 384, 113, 77, 41,,,, -7, 6, 2, 2, 3, 3, 2, 2, 128, 113, 77, 41,,,, -7, 6, 2, 2, 3, 3, 2, 2, 256, 113, 77, 41,,,, -7, 6, 2, 2, 3, 3, 2, 2, 384, 113, 77, 41,,,, -7, 6, 2, 2, 3, 3, 2, 3, 128, 113, 77, 41,,,, -7, 6, 2, 2, 3, 3, 2, 3, 256, 113, 77, 41,,,, -7, 6, 2, 2, 3, 3, 2, 3, 384, 113, 77, 41,,,, -7, 6, 2, 2, 3, 3, 3, 1, 128, 113, 77, 41,,,, -7, 6, 2, 2, 3, 3, 3, 1, 256, 113, 77, 41,,,, -7, 6, 2, 2, 3, 3, 3, 1, 384, 113, 77, 41,,,, -7, 6, 2, 2, 3, 3, 3, 2, 128, 113, 77, 41,,,, -7, 6, 2, 2, 3, 3, 3, 2, 256, 113, 77, 41,,,, -7, 6, 2, 2, 3, 3, 3, 2, 384, 113, 77, 41,,,, -7, 6, 2, 2, 3, 3, 3, 3, 128, 113, 77, 41,,,, -7, 6, 2, 2, 3, 3, 3, 3, 256, 113, 77, 41,,,, -7, 6, 2, 2, 3, 3, 3, 3, 384, 113, 77, 41,,,, -7, 6, 2, 3, 1, 1, 1, 1, 128, 167, 113, 59,,,, -7, 6, 2, 3, 1, 1, 1, 1, 256, 167, 113, 59,,,, -7, 6, 2, 3, 1, 1, 1, 1, 384, 167, 113, 59,,,, -7, 6, 2, 3, 2, 2, 1, 1, 128, 167, 113, 59,,,, -7, 6, 2, 3, 2, 2, 1, 1, 256, 167, 113, 59,,,, -7, 6, 2, 3, 2, 2, 1, 1, 384, 167, 113, 59,,,, -7, 6, 2, 3, 2, 2, 1, 2, 128, 167, 113, 59,,,, -7, 6, 2, 3, 2, 2, 1, 2, 256, 167, 113, 59,,,, -7, 6, 2, 3, 2, 2, 1, 2, 384, 167, 113, 59,,,, -7, 6, 2, 3, 2, 2, 2, 1, 128, 167, 113, 59,,,, -7, 6, 2, 3, 2, 2, 2, 1, 256, 167, 113, 59,,,, -7, 6, 2, 3, 2, 2, 2, 1, 384, 167, 113, 59,,,, -7, 6, 2, 3, 2, 2, 2, 2, 128, 167, 113, 59,,,, -7, 6, 2, 3, 2, 2, 2, 2, 256, 167, 113, 59,,,, -7, 6, 2, 3, 2, 2, 2, 2, 384, 167, 113, 59,,,, -7, 6, 2, 3, 3, 3, 1, 1, 128, 167, 113, 59,,,, -7, 6, 2, 3, 3, 3, 1, 1, 256, 167, 113, 59,,,, -7, 6, 2, 3, 3, 3, 1, 1, 384, 167, 113, 59,,,, -7, 6, 2, 3, 3, 3, 1, 2, 128, 167, 113, 59,,,, -7, 6, 2, 3, 3, 3, 1, 2, 256, 167, 113, 59,,,, -7, 6, 2, 3, 3, 3, 1, 2, 384, 167, 113, 59,,,, -7, 6, 2, 3, 3, 3, 1, 3, 128, 167, 113, 59,,,, -7, 6, 2, 3, 3, 3, 1, 3, 256, 167, 113, 59,,,, -7, 6, 2, 3, 3, 3, 1, 3, 384, 167, 113, 59,,,, -7, 6, 2, 3, 3, 3, 2, 1, 128, 167, 113, 59,,,, -7, 6, 2, 3, 3, 3, 2, 1, 256, 167, 113, 59,,,, -7, 6, 2, 3, 3, 3, 2, 1, 384, 167, 113, 59,,,, -7, 6, 2, 3, 3, 3, 2, 2, 128, 167, 113, 59,,,, -7, 6, 2, 3, 3, 3, 2, 2, 256, 167, 113, 59,,,, -7, 6, 2, 3, 3, 3, 2, 2, 384, 167, 113, 59,,,, -7, 6, 2, 3, 3, 3, 2, 3, 128, 167, 113, 59,,,, -7, 6, 2, 3, 3, 3, 2, 3, 256, 167, 113, 59,,,, -7, 6, 2, 3, 3, 3, 2, 3, 384, 167, 113, 59,,,, -7, 6, 2, 3, 3, 3, 3, 1, 128, 167, 113, 59,,,, -7, 6, 2, 3, 3, 3, 3, 1, 256, 167, 113, 59,,,, -7, 6, 2, 3, 3, 3, 3, 1, 384, 167, 113, 59,,,, -7, 6, 2, 3, 3, 3, 3, 2, 128, 167, 113, 59,,,, -7, 6, 2, 3, 3, 3, 3, 2, 256, 167, 113, 59,,,, -7, 6, 2, 3, 3, 3, 3, 2, 384, 167, 113, 59,,,, -7, 6, 2, 3, 3, 3, 3, 3, 128, 167, 113, 59,,,, -7, 6, 2, 3, 3, 3, 3, 3, 256, 167, 113, 59,,,, -7, 6, 2, 3, 3, 3, 3, 3, 384, 167, 113, 59,,,, -7, 6, 2, 4, 1, 1, 1, 1, 128, 221, 149, 77,,,, -7, 6, 2, 4, 1, 1, 1, 1, 256, 221, 149, 77,,,, -7, 6, 2, 4, 1, 1, 1, 1, 384, 221, 149, 77,,,, -7, 6, 2, 4, 2, 2, 1, 1, 128, 221, 149, 77,,,, -7, 6, 2, 4, 2, 2, 1, 1, 256, 221, 149, 77,,,, -7, 6, 2, 4, 2, 2, 1, 1, 384, 221, 149, 77,,,, -7, 6, 2, 4, 2, 2, 1, 2, 128, 221, 149, 77,,,, -7, 6, 2, 4, 2, 2, 1, 2, 256, 221, 149, 77,,,, -7, 6, 2, 4, 2, 2, 1, 2, 384, 221, 149, 77,,,, -7, 6, 2, 4, 2, 2, 2, 1, 128, 221, 149, 77,,,, -7, 6, 2, 4, 2, 2, 2, 1, 256, 221, 149, 77,,,, -7, 6, 2, 4, 2, 2, 2, 1, 384, 221, 149, 77,,,, -7, 6, 2, 4, 2, 2, 2, 2, 128, 221, 149, 77,,,, -7, 6, 2, 4, 2, 2, 2, 2, 256, 221, 149, 77,,,, -7, 6, 2, 4, 2, 2, 2, 2, 384, 221, 149, 77,,,, -7, 6, 2, 4, 3, 3, 1, 1, 128, 221, 149, 77,,,, -7, 6, 2, 4, 3, 3, 1, 1, 256, 221, 149, 77,,,, -7, 6, 2, 4, 3, 3, 1, 1, 384, 221, 149, 77,,,, -7, 6, 2, 4, 3, 3, 1, 2, 128, 221, 149, 77,,,, -7, 6, 2, 4, 3, 3, 1, 2, 256, 221, 149, 77,,,, -7, 6, 2, 4, 3, 3, 1, 2, 384, 221, 149, 77,,,, -7, 6, 2, 4, 3, 3, 1, 3, 128, 221, 149, 77,,,, -7, 6, 2, 4, 3, 3, 1, 3, 256, 221, 149, 77,,,, -7, 6, 2, 4, 3, 3, 1, 3, 384, 221, 149, 77,,,, -7, 6, 2, 4, 3, 3, 2, 1, 128, 221, 149, 77,,,, -7, 6, 2, 4, 3, 3, 2, 1, 256, 221, 149, 77,,,, -7, 6, 2, 4, 3, 3, 2, 1, 384, 221, 149, 77,,,, -7, 6, 2, 4, 3, 3, 2, 2, 128, 221, 149, 77,,,, -7, 6, 2, 4, 3, 3, 2, 2, 256, 221, 149, 77,,,, -7, 6, 2, 4, 3, 3, 2, 2, 384, 221, 149, 77,,,, -7, 6, 2, 4, 3, 3, 2, 3, 128, 221, 149, 77,,,, -7, 6, 2, 4, 3, 3, 2, 3, 256, 221, 149, 77,,,, -7, 6, 2, 4, 3, 3, 2, 3, 384, 221, 149, 77,,,, -7, 6, 2, 4, 3, 3, 3, 1, 128, 221, 149, 77,,,, -7, 6, 2, 4, 3, 3, 3, 1, 256, 221, 149, 77,,,, -7, 6, 2, 4, 3, 3, 3, 1, 384, 221, 149, 77,,,, -7, 6, 2, 4, 3, 3, 3, 2, 128, 221, 149, 77,,,, -7, 6, 2, 4, 3, 3, 3, 2, 256, 221, 149, 77,,,, -7, 6, 2, 4, 3, 3, 3, 2, 384, 221, 149, 77,,,, -7, 6, 2, 4, 3, 3, 3, 3, 128, 221, 149, 77,,,, -7, 6, 2, 4, 3, 3, 3, 3, 256, 221, 149, 77,,,, -7, 6, 2, 4, 3, 3, 3, 3, 384, 221, 149, 77,,,, -7, 6, 2, 5, 1, 1, 1, 1, 128, 240, 185, 95,,,, -7, 6, 2, 5, 1, 1, 1, 1, 256, 240, 185, 95,,,, -7, 6, 2, 5, 1, 1, 1, 1, 384, 240, 185, 95,,,, -7, 6, 2, 5, 2, 2, 1, 1, 128, 240, 185, 95,,,, -7, 6, 2, 5, 2, 2, 1, 1, 256, 240, 185, 95,,,, -7, 6, 2, 5, 2, 2, 1, 1, 384, 240, 185, 95,,,, -7, 6, 2, 5, 2, 2, 1, 2, 128, 240, 185, 95,,,, -7, 6, 2, 5, 2, 2, 1, 2, 256, 240, 185, 95,,,, -7, 6, 2, 5, 2, 2, 1, 2, 384, 240, 185, 95,,,, -7, 6, 2, 5, 2, 2, 2, 1, 128, 240, 185, 95,,,, -7, 6, 2, 5, 2, 2, 2, 1, 256, 240, 185, 95,,,, -7, 6, 2, 5, 2, 2, 2, 1, 384, 240, 185, 95,,,, -7, 6, 2, 5, 2, 2, 2, 2, 128, 240, 185, 95,,,, -7, 6, 2, 5, 2, 2, 2, 2, 256, 240, 185, 95,,,, -7, 6, 2, 5, 2, 2, 2, 2, 384, 240, 185, 95,,,, -7, 6, 2, 5, 3, 3, 1, 1, 128, 240, 185, 95,,,, -7, 6, 2, 5, 3, 3, 1, 1, 256, 240, 185, 95,,,, -7, 6, 2, 5, 3, 3, 1, 1, 384, 240, 185, 95,,,, -7, 6, 2, 5, 3, 3, 1, 2, 128, 240, 185, 95,,,, -7, 6, 2, 5, 3, 3, 1, 2, 256, 240, 185, 95,,,, -7, 6, 2, 5, 3, 3, 1, 2, 384, 240, 185, 95,,,, -7, 6, 2, 5, 3, 3, 1, 3, 128, 240, 185, 95,,,, -7, 6, 2, 5, 3, 3, 1, 3, 256, 240, 185, 95,,,, -7, 6, 2, 5, 3, 3, 1, 3, 384, 240, 185, 95,,,, -7, 6, 2, 5, 3, 3, 2, 1, 128, 240, 185, 95,,,, -7, 6, 2, 5, 3, 3, 2, 1, 256, 240, 185, 95,,,, -7, 6, 2, 5, 3, 3, 2, 1, 384, 240, 185, 95,,,, -7, 6, 2, 5, 3, 3, 2, 2, 128, 240, 185, 95,,,, -7, 6, 2, 5, 3, 3, 2, 2, 256, 240, 185, 95,,,, -7, 6, 2, 5, 3, 3, 2, 2, 384, 240, 185, 95,,,, -7, 6, 2, 5, 3, 3, 2, 3, 128, 240, 185, 95,,,, -7, 6, 2, 5, 3, 3, 2, 3, 256, 240, 185, 95,,,, -7, 6, 2, 5, 3, 3, 2, 3, 384, 240, 185, 95,,,, -7, 6, 2, 5, 3, 3, 3, 1, 128, 240, 185, 95,,,, -7, 6, 2, 5, 3, 3, 3, 1, 256, 240, 185, 95,,,, -7, 6, 2, 5, 3, 3, 3, 1, 384, 240, 185, 95,,,, -7, 6, 2, 5, 3, 3, 3, 2, 128, 240, 185, 95,,,, -7, 6, 2, 5, 3, 3, 3, 2, 256, 240, 185, 95,,,, -7, 6, 2, 5, 3, 3, 3, 2, 384, 240, 185, 95,,,, -7, 6, 2, 5, 3, 3, 3, 3, 128, 240, 185, 95,,,, -7, 6, 2, 5, 3, 3, 3, 3, 256, 240, 185, 95,,,, -7, 6, 2, 5, 3, 3, 3, 3, 384, 240, 185, 95,,,, -7, 6, 2, 6, 1, 1, 1, 1, 128, 240, 221, 113,,,, -7, 6, 2, 6, 1, 1, 1, 1, 256, 240, 221, 113,,,, -7, 6, 2, 6, 1, 1, 1, 1, 384, 240, 221, 113,,,, -7, 6, 2, 6, 2, 2, 1, 1, 128, 240, 221, 113,,,, -7, 6, 2, 6, 2, 2, 1, 1, 256, 240, 221, 113,,,, -7, 6, 2, 6, 2, 2, 1, 1, 384, 240, 221, 113,,,, -7, 6, 2, 6, 2, 2, 1, 2, 128, 240, 221, 113,,,, -7, 6, 2, 6, 2, 2, 1, 2, 256, 240, 221, 113,,,, -7, 6, 2, 6, 2, 2, 1, 2, 384, 240, 221, 113,,,, -7, 6, 2, 6, 2, 2, 2, 1, 128, 240, 221, 113,,,, -7, 6, 2, 6, 2, 2, 2, 1, 256, 240, 221, 113,,,, -7, 6, 2, 6, 2, 2, 2, 1, 384, 240, 221, 113,,,, -7, 6, 2, 6, 2, 2, 2, 2, 128, 240, 221, 113,,,, -7, 6, 2, 6, 2, 2, 2, 2, 256, 240, 221, 113,,,, -7, 6, 2, 6, 2, 2, 2, 2, 384, 240, 221, 113,,,, -7, 6, 2, 6, 3, 3, 1, 1, 128, 240, 221, 113,,,, -7, 6, 2, 6, 3, 3, 1, 1, 256, 240, 221, 113,,,, -7, 6, 2, 6, 3, 3, 1, 1, 384, 240, 221, 113,,,, -7, 6, 2, 6, 3, 3, 1, 2, 128, 240, 221, 113,,,, -7, 6, 2, 6, 3, 3, 1, 2, 256, 240, 221, 113,,,, -7, 6, 2, 6, 3, 3, 1, 2, 384, 240, 221, 113,,,, -7, 6, 2, 6, 3, 3, 1, 3, 128, 240, 221, 113,,,, -7, 6, 2, 6, 3, 3, 1, 3, 256, 240, 221, 113,,,, -7, 6, 2, 6, 3, 3, 1, 3, 384, 240, 221, 113,,,, -7, 6, 2, 6, 3, 3, 2, 1, 128, 240, 221, 113,,,, -7, 6, 2, 6, 3, 3, 2, 1, 256, 240, 221, 113,,,, -7, 6, 2, 6, 3, 3, 2, 1, 384, 240, 221, 113,,,, -7, 6, 2, 6, 3, 3, 2, 2, 128, 240, 221, 113,,,, -7, 6, 2, 6, 3, 3, 2, 2, 256, 240, 221, 113,,,, -7, 6, 2, 6, 3, 3, 2, 2, 384, 240, 221, 113,,,, -7, 6, 2, 6, 3, 3, 2, 3, 128, 240, 221, 113,,,, -7, 6, 2, 6, 3, 3, 2, 3, 256, 240, 221, 113,,,, -7, 6, 2, 6, 3, 3, 2, 3, 384, 240, 221, 113,,,, -7, 6, 2, 6, 3, 3, 3, 1, 128, 240, 221, 113,,,, -7, 6, 2, 6, 3, 3, 3, 1, 256, 240, 221, 113,,,, -7, 6, 2, 6, 3, 3, 3, 1, 384, 240, 221, 113,,,, -7, 6, 2, 6, 3, 3, 3, 2, 128, 240, 221, 113,,,, -7, 6, 2, 6, 3, 3, 3, 2, 256, 240, 221, 113,,,, -7, 6, 2, 6, 3, 3, 3, 2, 384, 240, 221, 113,,,, -7, 6, 2, 6, 3, 3, 3, 3, 128, 240, 221, 113,,,, -7, 6, 2, 6, 3, 3, 3, 3, 256, 240, 221, 113,,,, -7, 6, 2, 6, 3, 3, 3, 3, 384, 240, 221, 113,,,, -7, 6, 3, 1, 1, 1, 1, 1, 128, 59, 41, 23,,,, -7, 6, 3, 1, 1, 1, 1, 1, 256, 59, 41, 23,,,, -7, 6, 3, 1, 1, 1, 1, 1, 384, 59, 41, 23,,,, -7, 6, 3, 1, 2, 2, 1, 1, 128, 59, 41, 23,,,, -7, 6, 3, 1, 2, 2, 1, 1, 256, 59, 41, 23,,,, -7, 6, 3, 1, 2, 2, 1, 1, 384, 59, 41, 23,,,, -7, 6, 3, 1, 2, 2, 1, 2, 128, 59, 41, 23,,,, -7, 6, 3, 1, 2, 2, 1, 2, 256, 59, 41, 23,,,, -7, 6, 3, 1, 2, 2, 1, 2, 384, 59, 41, 23,,,, -7, 6, 3, 1, 2, 2, 2, 1, 128, 59, 41, 23,,,, -7, 6, 3, 1, 2, 2, 2, 1, 256, 59, 41, 23,,,, -7, 6, 3, 1, 2, 2, 2, 1, 384, 59, 41, 23,,,, -7, 6, 3, 1, 2, 2, 2, 2, 128, 59, 41, 23,,,, -7, 6, 3, 1, 2, 2, 2, 2, 256, 59, 41, 23,,,, -7, 6, 3, 1, 2, 2, 2, 2, 384, 59, 41, 23,,,, -7, 6, 3, 1, 3, 3, 1, 1, 128, 59, 41, 23,,,, -7, 6, 3, 1, 3, 3, 1, 1, 256, 59, 41, 23,,,, -7, 6, 3, 1, 3, 3, 1, 1, 384, 59, 41, 23,,,, -7, 6, 3, 1, 3, 3, 1, 2, 128, 59, 41, 23,,,, -7, 6, 3, 1, 3, 3, 1, 2, 256, 59, 41, 23,,,, -7, 6, 3, 1, 3, 3, 1, 2, 384, 59, 41, 23,,,, -7, 6, 3, 1, 3, 3, 1, 3, 128, 59, 41, 23,,,, -7, 6, 3, 1, 3, 3, 1, 3, 256, 59, 41, 23,,,, -7, 6, 3, 1, 3, 3, 1, 3, 384, 59, 41, 23,,,, -7, 6, 3, 1, 3, 3, 2, 1, 128, 59, 41, 23,,,, -7, 6, 3, 1, 3, 3, 2, 1, 256, 59, 41, 23,,,, -7, 6, 3, 1, 3, 3, 2, 1, 384, 59, 41, 23,,,, -7, 6, 3, 1, 3, 3, 2, 2, 128, 59, 41, 23,,,, -7, 6, 3, 1, 3, 3, 2, 2, 256, 59, 41, 23,,,, -7, 6, 3, 1, 3, 3, 2, 2, 384, 59, 41, 23,,,, -7, 6, 3, 1, 3, 3, 2, 3, 128, 59, 41, 23,,,, -7, 6, 3, 1, 3, 3, 2, 3, 256, 59, 41, 23,,,, -7, 6, 3, 1, 3, 3, 2, 3, 384, 59, 41, 23,,,, -7, 6, 3, 1, 3, 3, 3, 1, 128, 59, 41, 23,,,, -7, 6, 3, 1, 3, 3, 3, 1, 256, 59, 41, 23,,,, -7, 6, 3, 1, 3, 3, 3, 1, 384, 59, 41, 23,,,, -7, 6, 3, 1, 3, 3, 3, 2, 128, 59, 41, 23,,,, -7, 6, 3, 1, 3, 3, 3, 2, 256, 59, 41, 23,,,, -7, 6, 3, 1, 3, 3, 3, 2, 384, 59, 41, 23,,,, -7, 6, 3, 1, 3, 3, 3, 3, 128, 59, 41, 23,,,, -7, 6, 3, 1, 3, 3, 3, 3, 256, 59, 41, 23,,,, -7, 6, 3, 1, 3, 3, 3, 3, 384, 59, 41, 23,,,, -7, 6, 3, 2, 1, 1, 1, 1, 128, 113, 77, 41,,,, -7, 6, 3, 2, 1, 1, 1, 1, 256, 113, 77, 41,,,, -7, 6, 3, 2, 1, 1, 1, 1, 384, 113, 77, 41,,,, -7, 6, 3, 2, 2, 2, 1, 1, 128, 113, 77, 41,,,, -7, 6, 3, 2, 2, 2, 1, 1, 256, 113, 77, 41,,,, -7, 6, 3, 2, 2, 2, 1, 1, 384, 113, 77, 41,,,, -7, 6, 3, 2, 2, 2, 1, 2, 128, 113, 77, 41,,,, -7, 6, 3, 2, 2, 2, 1, 2, 256, 113, 77, 41,,,, -7, 6, 3, 2, 2, 2, 1, 2, 384, 113, 77, 41,,,, -7, 6, 3, 2, 2, 2, 2, 1, 128, 113, 77, 41,,,, -7, 6, 3, 2, 2, 2, 2, 1, 256, 113, 77, 41,,,, -7, 6, 3, 2, 2, 2, 2, 1, 384, 113, 77, 41,,,, -7, 6, 3, 2, 2, 2, 2, 2, 128, 113, 77, 41,,,, -7, 6, 3, 2, 2, 2, 2, 2, 256, 113, 77, 41,,,, -7, 6, 3, 2, 2, 2, 2, 2, 384, 113, 77, 41,,,, -7, 6, 3, 2, 3, 3, 1, 1, 128, 113, 77, 41,,,, -7, 6, 3, 2, 3, 3, 1, 1, 256, 113, 77, 41,,,, -7, 6, 3, 2, 3, 3, 1, 1, 384, 113, 77, 41,,,, -7, 6, 3, 2, 3, 3, 1, 2, 128, 113, 77, 41,,,, -7, 6, 3, 2, 3, 3, 1, 2, 256, 113, 77, 41,,,, -7, 6, 3, 2, 3, 3, 1, 2, 384, 113, 77, 41,,,, -7, 6, 3, 2, 3, 3, 1, 3, 128, 113, 77, 41,,,, -7, 6, 3, 2, 3, 3, 1, 3, 256, 113, 77, 41,,,, -7, 6, 3, 2, 3, 3, 1, 3, 384, 113, 77, 41,,,, -7, 6, 3, 2, 3, 3, 2, 1, 128, 113, 77, 41,,,, -7, 6, 3, 2, 3, 3, 2, 1, 256, 113, 77, 41,,,, -7, 6, 3, 2, 3, 3, 2, 1, 384, 113, 77, 41,,,, -7, 6, 3, 2, 3, 3, 2, 2, 128, 113, 77, 41,,,, -7, 6, 3, 2, 3, 3, 2, 2, 256, 113, 77, 41,,,, -7, 6, 3, 2, 3, 3, 2, 2, 384, 113, 77, 41,,,, -7, 6, 3, 2, 3, 3, 2, 3, 128, 113, 77, 41,,,, -7, 6, 3, 2, 3, 3, 2, 3, 256, 113, 77, 41,,,, -7, 6, 3, 2, 3, 3, 2, 3, 384, 113, 77, 41,,,, -7, 6, 3, 2, 3, 3, 3, 1, 128, 113, 77, 41,,,, -7, 6, 3, 2, 3, 3, 3, 1, 256, 113, 77, 41,,,, -7, 6, 3, 2, 3, 3, 3, 1, 384, 113, 77, 41,,,, -7, 6, 3, 2, 3, 3, 3, 2, 128, 113, 77, 41,,,, -7, 6, 3, 2, 3, 3, 3, 2, 256, 113, 77, 41,,,, -7, 6, 3, 2, 3, 3, 3, 2, 384, 113, 77, 41,,,, -7, 6, 3, 2, 3, 3, 3, 3, 128, 113, 77, 41,,,, -7, 6, 3, 2, 3, 3, 3, 3, 256, 113, 77, 41,,,, -7, 6, 3, 2, 3, 3, 3, 3, 384, 113, 77, 41,,,, -7, 6, 3, 3, 1, 1, 1, 1, 128, 167, 113, 59,,,, -7, 6, 3, 3, 1, 1, 1, 1, 256, 167, 113, 59,,,, -7, 6, 3, 3, 1, 1, 1, 1, 384, 167, 113, 59,,,, -7, 6, 3, 3, 2, 2, 1, 1, 128, 167, 113, 59,,,, -7, 6, 3, 3, 2, 2, 1, 1, 256, 167, 113, 59,,,, -7, 6, 3, 3, 2, 2, 1, 1, 384, 167, 113, 59,,,, -7, 6, 3, 3, 2, 2, 1, 2, 128, 167, 113, 59,,,, -7, 6, 3, 3, 2, 2, 1, 2, 256, 167, 113, 59,,,, -7, 6, 3, 3, 2, 2, 1, 2, 384, 167, 113, 59,,,, -7, 6, 3, 3, 2, 2, 2, 1, 128, 167, 113, 59,,,, -7, 6, 3, 3, 2, 2, 2, 1, 256, 167, 113, 59,,,, -7, 6, 3, 3, 2, 2, 2, 1, 384, 167, 113, 59,,,, -7, 6, 3, 3, 2, 2, 2, 2, 128, 167, 113, 59,,,, -7, 6, 3, 3, 2, 2, 2, 2, 256, 167, 113, 59,,,, -7, 6, 3, 3, 2, 2, 2, 2, 384, 167, 113, 59,,,, -7, 6, 3, 3, 3, 3, 1, 1, 128, 167, 113, 59,,,, -7, 6, 3, 3, 3, 3, 1, 1, 256, 167, 113, 59,,,, -7, 6, 3, 3, 3, 3, 1, 1, 384, 167, 113, 59,,,, -7, 6, 3, 3, 3, 3, 1, 2, 128, 167, 113, 59,,,, -7, 6, 3, 3, 3, 3, 1, 2, 256, 167, 113, 59,,,, -7, 6, 3, 3, 3, 3, 1, 2, 384, 167, 113, 59,,,, -7, 6, 3, 3, 3, 3, 1, 3, 128, 167, 113, 59,,,, -7, 6, 3, 3, 3, 3, 1, 3, 256, 167, 113, 59,,,, -7, 6, 3, 3, 3, 3, 1, 3, 384, 167, 113, 59,,,, -7, 6, 3, 3, 3, 3, 2, 1, 128, 167, 113, 59,,,, -7, 6, 3, 3, 3, 3, 2, 1, 256, 167, 113, 59,,,, -7, 6, 3, 3, 3, 3, 2, 1, 384, 167, 113, 59,,,, -7, 6, 3, 3, 3, 3, 2, 2, 128, 167, 113, 59,,,, -7, 6, 3, 3, 3, 3, 2, 2, 256, 167, 113, 59,,,, -7, 6, 3, 3, 3, 3, 2, 2, 384, 167, 113, 59,,,, -7, 6, 3, 3, 3, 3, 2, 3, 128, 167, 113, 59,,,, -7, 6, 3, 3, 3, 3, 2, 3, 256, 167, 113, 59,,,, -7, 6, 3, 3, 3, 3, 2, 3, 384, 167, 113, 59,,,, -7, 6, 3, 3, 3, 3, 3, 1, 128, 167, 113, 59,,,, -7, 6, 3, 3, 3, 3, 3, 1, 256, 167, 113, 59,,,, -7, 6, 3, 3, 3, 3, 3, 1, 384, 167, 113, 59,,,, -7, 6, 3, 3, 3, 3, 3, 2, 128, 167, 113, 59,,,, -7, 6, 3, 3, 3, 3, 3, 2, 256, 167, 113, 59,,,, -7, 6, 3, 3, 3, 3, 3, 2, 384, 167, 113, 59,,,, -7, 6, 3, 3, 3, 3, 3, 3, 128, 167, 113, 59,,,, -7, 6, 3, 3, 3, 3, 3, 3, 256, 167, 113, 59,,,, -7, 6, 3, 3, 3, 3, 3, 3, 384, 167, 113, 59,,,, -7, 6, 3, 4, 1, 1, 1, 1, 128, 221, 149, 77,,,, -7, 6, 3, 4, 1, 1, 1, 1, 256, 221, 149, 77,,,, -7, 6, 3, 4, 1, 1, 1, 1, 384, 221, 149, 77,,,, -7, 6, 3, 4, 2, 2, 1, 1, 128, 221, 149, 77,,,, -7, 6, 3, 4, 2, 2, 1, 1, 256, 221, 149, 77,,,, -7, 6, 3, 4, 2, 2, 1, 1, 384, 221, 149, 77,,,, -7, 6, 3, 4, 2, 2, 1, 2, 128, 221, 149, 77,,,, -7, 6, 3, 4, 2, 2, 1, 2, 256, 221, 149, 77,,,, -7, 6, 3, 4, 2, 2, 1, 2, 384, 221, 149, 77,,,, -7, 6, 3, 4, 2, 2, 2, 1, 128, 221, 149, 77,,,, -7, 6, 3, 4, 2, 2, 2, 1, 256, 221, 149, 77,,,, -7, 6, 3, 4, 2, 2, 2, 1, 384, 221, 149, 77,,,, -7, 6, 3, 4, 2, 2, 2, 2, 128, 221, 149, 77,,,, -7, 6, 3, 4, 2, 2, 2, 2, 256, 221, 149, 77,,,, -7, 6, 3, 4, 2, 2, 2, 2, 384, 221, 149, 77,,,, -7, 6, 3, 4, 3, 3, 1, 1, 128, 221, 149, 77,,,, -7, 6, 3, 4, 3, 3, 1, 1, 256, 221, 149, 77,,,, -7, 6, 3, 4, 3, 3, 1, 1, 384, 221, 149, 77,,,, -7, 6, 3, 4, 3, 3, 1, 2, 128, 221, 149, 77,,,, -7, 6, 3, 4, 3, 3, 1, 2, 256, 221, 149, 77,,,, -7, 6, 3, 4, 3, 3, 1, 2, 384, 221, 149, 77,,,, -7, 6, 3, 4, 3, 3, 1, 3, 128, 221, 149, 77,,,, -7, 6, 3, 4, 3, 3, 1, 3, 256, 221, 149, 77,,,, -7, 6, 3, 4, 3, 3, 1, 3, 384, 221, 149, 77,,,, -7, 6, 3, 4, 3, 3, 2, 1, 128, 221, 149, 77,,,, -7, 6, 3, 4, 3, 3, 2, 1, 256, 221, 149, 77,,,, -7, 6, 3, 4, 3, 3, 2, 1, 384, 221, 149, 77,,,, -7, 6, 3, 4, 3, 3, 2, 2, 128, 221, 149, 77,,,, -7, 6, 3, 4, 3, 3, 2, 2, 256, 221, 149, 77,,,, -7, 6, 3, 4, 3, 3, 2, 2, 384, 221, 149, 77,,,, -7, 6, 3, 4, 3, 3, 2, 3, 128, 221, 149, 77,,,, -7, 6, 3, 4, 3, 3, 2, 3, 256, 221, 149, 77,,,, -7, 6, 3, 4, 3, 3, 2, 3, 384, 221, 149, 77,,,, -7, 6, 3, 4, 3, 3, 3, 1, 128, 221, 149, 77,,,, -7, 6, 3, 4, 3, 3, 3, 1, 256, 221, 149, 77,,,, -7, 6, 3, 4, 3, 3, 3, 1, 384, 221, 149, 77,,,, -7, 6, 3, 4, 3, 3, 3, 2, 128, 221, 149, 77,,,, -7, 6, 3, 4, 3, 3, 3, 2, 256, 221, 149, 77,,,, -7, 6, 3, 4, 3, 3, 3, 2, 384, 221, 149, 77,,,, -7, 6, 3, 4, 3, 3, 3, 3, 128, 221, 149, 77,,,, -7, 6, 3, 4, 3, 3, 3, 3, 256, 221, 149, 77,,,, -7, 6, 3, 4, 3, 3, 3, 3, 384, 221, 149, 77,,,, -7, 6, 3, 5, 1, 1, 1, 1, 128, 240, 185, 95,,,, -7, 6, 3, 5, 1, 1, 1, 1, 256, 240, 185, 95,,,, -7, 6, 3, 5, 1, 1, 1, 1, 384, 240, 185, 95,,,, -7, 6, 3, 5, 2, 2, 1, 1, 128, 240, 185, 95,,,, -7, 6, 3, 5, 2, 2, 1, 1, 256, 240, 185, 95,,,, -7, 6, 3, 5, 2, 2, 1, 1, 384, 240, 185, 95,,,, -7, 6, 3, 5, 2, 2, 1, 2, 128, 240, 185, 95,,,, -7, 6, 3, 5, 2, 2, 1, 2, 256, 240, 185, 95,,,, -7, 6, 3, 5, 2, 2, 1, 2, 384, 240, 185, 95,,,, -7, 6, 3, 5, 2, 2, 2, 1, 128, 240, 185, 95,,,, -7, 6, 3, 5, 2, 2, 2, 1, 256, 240, 185, 95,,,, -7, 6, 3, 5, 2, 2, 2, 1, 384, 240, 185, 95,,,, -7, 6, 3, 5, 2, 2, 2, 2, 128, 240, 185, 95,,,, -7, 6, 3, 5, 2, 2, 2, 2, 256, 240, 185, 95,,,, -7, 6, 3, 5, 2, 2, 2, 2, 384, 240, 185, 95,,,, -7, 6, 3, 5, 3, 3, 1, 1, 128, 240, 185, 95,,,, -7, 6, 3, 5, 3, 3, 1, 1, 256, 240, 185, 95,,,, -7, 6, 3, 5, 3, 3, 1, 1, 384, 240, 185, 95,,,, -7, 6, 3, 5, 3, 3, 1, 2, 128, 240, 185, 95,,,, -7, 6, 3, 5, 3, 3, 1, 2, 256, 240, 185, 95,,,, -7, 6, 3, 5, 3, 3, 1, 2, 384, 240, 185, 95,,,, -7, 6, 3, 5, 3, 3, 1, 3, 128, 240, 185, 95,,,, -7, 6, 3, 5, 3, 3, 1, 3, 256, 240, 185, 95,,,, -7, 6, 3, 5, 3, 3, 1, 3, 384, 240, 185, 95,,,, -7, 6, 3, 5, 3, 3, 2, 1, 128, 240, 185, 95,,,, -7, 6, 3, 5, 3, 3, 2, 1, 256, 240, 185, 95,,,, -7, 6, 3, 5, 3, 3, 2, 1, 384, 240, 185, 95,,,, -7, 6, 3, 5, 3, 3, 2, 2, 128, 240, 185, 95,,,, -7, 6, 3, 5, 3, 3, 2, 2, 256, 240, 185, 95,,,, -7, 6, 3, 5, 3, 3, 2, 2, 384, 240, 185, 95,,,, -7, 6, 3, 5, 3, 3, 2, 3, 128, 240, 185, 95,,,, -7, 6, 3, 5, 3, 3, 2, 3, 256, 240, 185, 95,,,, -7, 6, 3, 5, 3, 3, 2, 3, 384, 240, 185, 95,,,, -7, 6, 3, 5, 3, 3, 3, 1, 128, 240, 185, 95,,,, -7, 6, 3, 5, 3, 3, 3, 1, 256, 240, 185, 95,,,, -7, 6, 3, 5, 3, 3, 3, 1, 384, 240, 185, 95,,,, -7, 6, 3, 5, 3, 3, 3, 2, 128, 240, 185, 95,,,, -7, 6, 3, 5, 3, 3, 3, 2, 256, 240, 185, 95,,,, -7, 6, 3, 5, 3, 3, 3, 2, 384, 240, 185, 95,,,, -7, 6, 3, 5, 3, 3, 3, 3, 128, 240, 185, 95,,,, -7, 6, 3, 5, 3, 3, 3, 3, 256, 240, 185, 95,,,, -7, 6, 3, 5, 3, 3, 3, 3, 384, 240, 185, 95,,,, -7, 6, 3, 6, 1, 1, 1, 1, 128, 240, 221, 113,,,, -7, 6, 3, 6, 1, 1, 1, 1, 256, 240, 221, 113,,,, -7, 6, 3, 6, 1, 1, 1, 1, 384, 240, 221, 113,,,, -7, 6, 3, 6, 2, 2, 1, 1, 128, 240, 221, 113,,,, -7, 6, 3, 6, 2, 2, 1, 1, 256, 240, 221, 113,,,, -7, 6, 3, 6, 2, 2, 1, 1, 384, 240, 221, 113,,,, -7, 6, 3, 6, 2, 2, 1, 2, 128, 240, 221, 113,,,, -7, 6, 3, 6, 2, 2, 1, 2, 256, 240, 221, 113,,,, -7, 6, 3, 6, 2, 2, 1, 2, 384, 240, 221, 113,,,, -7, 6, 3, 6, 2, 2, 2, 1, 128, 240, 221, 113,,,, -7, 6, 3, 6, 2, 2, 2, 1, 256, 240, 221, 113,,,, -7, 6, 3, 6, 2, 2, 2, 1, 384, 240, 221, 113,,,, -7, 6, 3, 6, 2, 2, 2, 2, 128, 240, 221, 113,,,, -7, 6, 3, 6, 2, 2, 2, 2, 256, 240, 221, 113,,,, -7, 6, 3, 6, 2, 2, 2, 2, 384, 240, 221, 113,,,, -7, 6, 3, 6, 3, 3, 1, 1, 128, 240, 221, 113,,,, -7, 6, 3, 6, 3, 3, 1, 1, 256, 240, 221, 113,,,, -7, 6, 3, 6, 3, 3, 1, 1, 384, 240, 221, 113,,,, -7, 6, 3, 6, 3, 3, 1, 2, 128, 240, 221, 113,,,, -7, 6, 3, 6, 3, 3, 1, 2, 256, 240, 221, 113,,,, -7, 6, 3, 6, 3, 3, 1, 2, 384, 240, 221, 113,,,, -7, 6, 3, 6, 3, 3, 1, 3, 128, 240, 221, 113,,,, -7, 6, 3, 6, 3, 3, 1, 3, 256, 240, 221, 113,,,, -7, 6, 3, 6, 3, 3, 1, 3, 384, 240, 221, 113,,,, -7, 6, 3, 6, 3, 3, 2, 1, 128, 240, 221, 113,,,, -7, 6, 3, 6, 3, 3, 2, 1, 256, 240, 221, 113,,,, -7, 6, 3, 6, 3, 3, 2, 1, 384, 240, 221, 113,,,, -7, 6, 3, 6, 3, 3, 2, 2, 128, 240, 221, 113,,,, -7, 6, 3, 6, 3, 3, 2, 2, 256, 240, 221, 113,,,, -7, 6, 3, 6, 3, 3, 2, 2, 384, 240, 221, 113,,,, -7, 6, 3, 6, 3, 3, 2, 3, 128, 240, 221, 113,,,, -7, 6, 3, 6, 3, 3, 2, 3, 256, 240, 221, 113,,,, -7, 6, 3, 6, 3, 3, 2, 3, 384, 240, 221, 113,,,, -7, 6, 3, 6, 3, 3, 3, 1, 128, 240, 221, 113,,,, -7, 6, 3, 6, 3, 3, 3, 1, 256, 240, 221, 113,,,, -7, 6, 3, 6, 3, 3, 3, 1, 384, 240, 221, 113,,,, -7, 6, 3, 6, 3, 3, 3, 2, 128, 240, 221, 113,,,, -7, 6, 3, 6, 3, 3, 3, 2, 256, 240, 221, 113,,,, -7, 6, 3, 6, 3, 3, 3, 2, 384, 240, 221, 113,,,, -7, 6, 3, 6, 3, 3, 3, 3, 128, 240, 221, 113,,,, -7, 6, 3, 6, 3, 3, 3, 3, 256, 240, 221, 113,,,, -7, 6, 3, 6, 3, 3, 3, 3, 384, 240, 221, 113,,,, -7, 6, 4, 1, 1, 1, 1, 1, 128, 59, 41, 23,,,, -7, 6, 4, 1, 1, 1, 1, 1, 256, 59, 41, 23,,,, -7, 6, 4, 1, 1, 1, 1, 1, 384, 59, 41, 23,,,, -7, 6, 4, 1, 2, 2, 1, 1, 128, 59, 41, 23,,,, -7, 6, 4, 1, 2, 2, 1, 1, 256, 59, 41, 23,,,, -7, 6, 4, 1, 2, 2, 1, 1, 384, 59, 41, 23,,,, -7, 6, 4, 1, 2, 2, 1, 2, 128, 59, 41, 23,,,, -7, 6, 4, 1, 2, 2, 1, 2, 256, 59, 41, 23,,,, -7, 6, 4, 1, 2, 2, 1, 2, 384, 59, 41, 23,,,, -7, 6, 4, 1, 2, 2, 2, 1, 128, 59, 41, 23,,,, -7, 6, 4, 1, 2, 2, 2, 1, 256, 59, 41, 23,,,, -7, 6, 4, 1, 2, 2, 2, 1, 384, 59, 41, 23,,,, -7, 6, 4, 1, 2, 2, 2, 2, 128, 59, 41, 23,,,, -7, 6, 4, 1, 2, 2, 2, 2, 256, 59, 41, 23,,,, -7, 6, 4, 1, 2, 2, 2, 2, 384, 59, 41, 23,,,, -7, 6, 4, 1, 3, 3, 1, 1, 128, 59, 41, 23,,,, -7, 6, 4, 1, 3, 3, 1, 1, 256, 59, 41, 23,,,, -7, 6, 4, 1, 3, 3, 1, 1, 384, 59, 41, 23,,,, -7, 6, 4, 1, 3, 3, 1, 2, 128, 59, 41, 23,,,, -7, 6, 4, 1, 3, 3, 1, 2, 256, 59, 41, 23,,,, -7, 6, 4, 1, 3, 3, 1, 2, 384, 59, 41, 23,,,, -7, 6, 4, 1, 3, 3, 1, 3, 128, 59, 41, 23,,,, -7, 6, 4, 1, 3, 3, 1, 3, 256, 59, 41, 23,,,, -7, 6, 4, 1, 3, 3, 1, 3, 384, 59, 41, 23,,,, -7, 6, 4, 1, 3, 3, 2, 1, 128, 59, 41, 23,,,, -7, 6, 4, 1, 3, 3, 2, 1, 256, 59, 41, 23,,,, -7, 6, 4, 1, 3, 3, 2, 1, 384, 59, 41, 23,,,, -7, 6, 4, 1, 3, 3, 2, 2, 128, 59, 41, 23,,,, -7, 6, 4, 1, 3, 3, 2, 2, 256, 59, 41, 23,,,, -7, 6, 4, 1, 3, 3, 2, 2, 384, 59, 41, 23,,,, -7, 6, 4, 1, 3, 3, 2, 3, 128, 59, 41, 23,,,, -7, 6, 4, 1, 3, 3, 2, 3, 256, 59, 41, 23,,,, -7, 6, 4, 1, 3, 3, 2, 3, 384, 59, 41, 23,,,, -7, 6, 4, 1, 3, 3, 3, 1, 128, 59, 41, 23,,,, -7, 6, 4, 1, 3, 3, 3, 1, 256, 59, 41, 23,,,, -7, 6, 4, 1, 3, 3, 3, 1, 384, 59, 41, 23,,,, -7, 6, 4, 1, 3, 3, 3, 2, 128, 59, 41, 23,,,, -7, 6, 4, 1, 3, 3, 3, 2, 256, 59, 41, 23,,,, -7, 6, 4, 1, 3, 3, 3, 2, 384, 59, 41, 23,,,, -7, 6, 4, 1, 3, 3, 3, 3, 128, 59, 41, 23,,,, -7, 6, 4, 1, 3, 3, 3, 3, 256, 59, 41, 23,,,, -7, 6, 4, 1, 3, 3, 3, 3, 384, 59, 41, 23,,,, -7, 6, 4, 2, 1, 1, 1, 1, 128, 113, 77, 41,,,, -7, 6, 4, 2, 1, 1, 1, 1, 256, 113, 77, 41,,,, -7, 6, 4, 2, 1, 1, 1, 1, 384, 113, 77, 41,,,, -7, 6, 4, 2, 2, 2, 1, 1, 128, 113, 77, 41,,,, -7, 6, 4, 2, 2, 2, 1, 1, 256, 113, 77, 41,,,, -7, 6, 4, 2, 2, 2, 1, 1, 384, 113, 77, 41,,,, -7, 6, 4, 2, 2, 2, 1, 2, 128, 113, 77, 41,,,, -7, 6, 4, 2, 2, 2, 1, 2, 256, 113, 77, 41,,,, -7, 6, 4, 2, 2, 2, 1, 2, 384, 113, 77, 41,,,, -7, 6, 4, 2, 2, 2, 2, 1, 128, 113, 77, 41,,,, -7, 6, 4, 2, 2, 2, 2, 1, 256, 113, 77, 41,,,, -7, 6, 4, 2, 2, 2, 2, 1, 384, 113, 77, 41,,,, -7, 6, 4, 2, 2, 2, 2, 2, 128, 113, 77, 41,,,, -7, 6, 4, 2, 2, 2, 2, 2, 256, 113, 77, 41,,,, -7, 6, 4, 2, 2, 2, 2, 2, 384, 113, 77, 41,,,, -7, 6, 4, 2, 3, 3, 1, 1, 128, 113, 77, 41,,,, -7, 6, 4, 2, 3, 3, 1, 1, 256, 113, 77, 41,,,, -7, 6, 4, 2, 3, 3, 1, 1, 384, 113, 77, 41,,,, -7, 6, 4, 2, 3, 3, 1, 2, 128, 113, 77, 41,,,, -7, 6, 4, 2, 3, 3, 1, 2, 256, 113, 77, 41,,,, -7, 6, 4, 2, 3, 3, 1, 2, 384, 113, 77, 41,,,, -7, 6, 4, 2, 3, 3, 1, 3, 128, 113, 77, 41,,,, -7, 6, 4, 2, 3, 3, 1, 3, 256, 113, 77, 41,,,, -7, 6, 4, 2, 3, 3, 1, 3, 384, 113, 77, 41,,,, -7, 6, 4, 2, 3, 3, 2, 1, 128, 113, 77, 41,,,, -7, 6, 4, 2, 3, 3, 2, 1, 256, 113, 77, 41,,,, -7, 6, 4, 2, 3, 3, 2, 1, 384, 113, 77, 41,,,, -7, 6, 4, 2, 3, 3, 2, 2, 128, 113, 77, 41,,,, -7, 6, 4, 2, 3, 3, 2, 2, 256, 113, 77, 41,,,, -7, 6, 4, 2, 3, 3, 2, 2, 384, 113, 77, 41,,,, -7, 6, 4, 2, 3, 3, 2, 3, 128, 113, 77, 41,,,, -7, 6, 4, 2, 3, 3, 2, 3, 256, 113, 77, 41,,,, -7, 6, 4, 2, 3, 3, 2, 3, 384, 113, 77, 41,,,, -7, 6, 4, 2, 3, 3, 3, 1, 128, 113, 77, 41,,,, -7, 6, 4, 2, 3, 3, 3, 1, 256, 113, 77, 41,,,, -7, 6, 4, 2, 3, 3, 3, 1, 384, 113, 77, 41,,,, -7, 6, 4, 2, 3, 3, 3, 2, 128, 113, 77, 41,,,, -7, 6, 4, 2, 3, 3, 3, 2, 256, 113, 77, 41,,,, -7, 6, 4, 2, 3, 3, 3, 2, 384, 113, 77, 41,,,, -7, 6, 4, 2, 3, 3, 3, 3, 128, 113, 77, 41,,,, -7, 6, 4, 2, 3, 3, 3, 3, 256, 113, 77, 41,,,, -7, 6, 4, 2, 3, 3, 3, 3, 384, 113, 77, 41,,,, -7, 6, 4, 3, 1, 1, 1, 1, 128, 167, 113, 59,,,, -7, 6, 4, 3, 1, 1, 1, 1, 256, 167, 113, 59,,,, -7, 6, 4, 3, 1, 1, 1, 1, 384, 167, 113, 59,,,, -7, 6, 4, 3, 2, 2, 1, 1, 128, 167, 113, 59,,,, -7, 6, 4, 3, 2, 2, 1, 1, 256, 167, 113, 59,,,, -7, 6, 4, 3, 2, 2, 1, 1, 384, 167, 113, 59,,,, -7, 6, 4, 3, 2, 2, 1, 2, 128, 167, 113, 59,,,, -7, 6, 4, 3, 2, 2, 1, 2, 256, 167, 113, 59,,,, -7, 6, 4, 3, 2, 2, 1, 2, 384, 167, 113, 59,,,, -7, 6, 4, 3, 2, 2, 2, 1, 128, 167, 113, 59,,,, -7, 6, 4, 3, 2, 2, 2, 1, 256, 167, 113, 59,,,, -7, 6, 4, 3, 2, 2, 2, 1, 384, 167, 113, 59,,,, -7, 6, 4, 3, 2, 2, 2, 2, 128, 167, 113, 59,,,, -7, 6, 4, 3, 2, 2, 2, 2, 256, 167, 113, 59,,,, -7, 6, 4, 3, 2, 2, 2, 2, 384, 167, 113, 59,,,, -7, 6, 4, 3, 3, 3, 1, 1, 128, 167, 113, 59,,,, -7, 6, 4, 3, 3, 3, 1, 1, 256, 167, 113, 59,,,, -7, 6, 4, 3, 3, 3, 1, 1, 384, 167, 113, 59,,,, -7, 6, 4, 3, 3, 3, 1, 2, 128, 167, 113, 59,,,, -7, 6, 4, 3, 3, 3, 1, 2, 256, 167, 113, 59,,,, -7, 6, 4, 3, 3, 3, 1, 2, 384, 167, 113, 59,,,, -7, 6, 4, 3, 3, 3, 1, 3, 128, 167, 113, 59,,,, -7, 6, 4, 3, 3, 3, 1, 3, 256, 167, 113, 59,,,, -7, 6, 4, 3, 3, 3, 1, 3, 384, 167, 113, 59,,,, -7, 6, 4, 3, 3, 3, 2, 1, 128, 167, 113, 59,,,, -7, 6, 4, 3, 3, 3, 2, 1, 256, 167, 113, 59,,,, -7, 6, 4, 3, 3, 3, 2, 1, 384, 167, 113, 59,,,, -7, 6, 4, 3, 3, 3, 2, 2, 128, 167, 113, 59,,,, -7, 6, 4, 3, 3, 3, 2, 2, 256, 167, 113, 59,,,, -7, 6, 4, 3, 3, 3, 2, 2, 384, 167, 113, 59,,,, -7, 6, 4, 3, 3, 3, 2, 3, 128, 167, 113, 59,,,, -7, 6, 4, 3, 3, 3, 2, 3, 256, 167, 113, 59,,,, -7, 6, 4, 3, 3, 3, 2, 3, 384, 167, 113, 59,,,, -7, 6, 4, 3, 3, 3, 3, 1, 128, 167, 113, 59,,,, -7, 6, 4, 3, 3, 3, 3, 1, 256, 167, 113, 59,,,, -7, 6, 4, 3, 3, 3, 3, 1, 384, 167, 113, 59,,,, -7, 6, 4, 3, 3, 3, 3, 2, 128, 167, 113, 59,,,, -7, 6, 4, 3, 3, 3, 3, 2, 256, 167, 113, 59,,,, -7, 6, 4, 3, 3, 3, 3, 2, 384, 167, 113, 59,,,, -7, 6, 4, 3, 3, 3, 3, 3, 128, 167, 113, 59,,,, -7, 6, 4, 3, 3, 3, 3, 3, 256, 167, 113, 59,,,, -7, 6, 4, 3, 3, 3, 3, 3, 384, 167, 113, 59,,,, -7, 6, 4, 4, 1, 1, 1, 1, 128, 221, 149, 77,,,, -7, 6, 4, 4, 1, 1, 1, 1, 256, 221, 149, 77,,,, -7, 6, 4, 4, 1, 1, 1, 1, 384, 221, 149, 77,,,, -7, 6, 4, 4, 2, 2, 1, 1, 128, 221, 149, 77,,,, -7, 6, 4, 4, 2, 2, 1, 1, 256, 221, 149, 77,,,, -7, 6, 4, 4, 2, 2, 1, 1, 384, 221, 149, 77,,,, -7, 6, 4, 4, 2, 2, 1, 2, 128, 221, 149, 77,,,, -7, 6, 4, 4, 2, 2, 1, 2, 256, 221, 149, 77,,,, -7, 6, 4, 4, 2, 2, 1, 2, 384, 221, 149, 77,,,, -7, 6, 4, 4, 2, 2, 2, 1, 128, 221, 149, 77,,,, -7, 6, 4, 4, 2, 2, 2, 1, 256, 221, 149, 77,,,, -7, 6, 4, 4, 2, 2, 2, 1, 384, 221, 149, 77,,,, -7, 6, 4, 4, 2, 2, 2, 2, 128, 221, 149, 77,,,, -7, 6, 4, 4, 2, 2, 2, 2, 256, 221, 149, 77,,,, -7, 6, 4, 4, 2, 2, 2, 2, 384, 221, 149, 77,,,, -7, 6, 4, 4, 3, 3, 1, 1, 128, 221, 149, 77,,,, -7, 6, 4, 4, 3, 3, 1, 1, 256, 221, 149, 77,,,, -7, 6, 4, 4, 3, 3, 1, 1, 384, 221, 149, 77,,,, -7, 6, 4, 4, 3, 3, 1, 2, 128, 221, 149, 77,,,, -7, 6, 4, 4, 3, 3, 1, 2, 256, 221, 149, 77,,,, -7, 6, 4, 4, 3, 3, 1, 2, 384, 221, 149, 77,,,, -7, 6, 4, 4, 3, 3, 1, 3, 128, 221, 149, 77,,,, -7, 6, 4, 4, 3, 3, 1, 3, 256, 221, 149, 77,,,, -7, 6, 4, 4, 3, 3, 1, 3, 384, 221, 149, 77,,,, -7, 6, 4, 4, 3, 3, 2, 1, 128, 221, 149, 77,,,, -7, 6, 4, 4, 3, 3, 2, 1, 256, 221, 149, 77,,,, -7, 6, 4, 4, 3, 3, 2, 1, 384, 221, 149, 77,,,, -7, 6, 4, 4, 3, 3, 2, 2, 128, 221, 149, 77,,,, -7, 6, 4, 4, 3, 3, 2, 2, 256, 221, 149, 77,,,, -7, 6, 4, 4, 3, 3, 2, 2, 384, 221, 149, 77,,,, -7, 6, 4, 4, 3, 3, 2, 3, 128, 221, 149, 77,,,, -7, 6, 4, 4, 3, 3, 2, 3, 256, 221, 149, 77,,,, -7, 6, 4, 4, 3, 3, 2, 3, 384, 221, 149, 77,,,, -7, 6, 4, 4, 3, 3, 3, 1, 128, 221, 149, 77,,,, -7, 6, 4, 4, 3, 3, 3, 1, 256, 221, 149, 77,,,, -7, 6, 4, 4, 3, 3, 3, 1, 384, 221, 149, 77,,,, -7, 6, 4, 4, 3, 3, 3, 2, 128, 221, 149, 77,,,, -7, 6, 4, 4, 3, 3, 3, 2, 256, 221, 149, 77,,,, -7, 6, 4, 4, 3, 3, 3, 2, 384, 221, 149, 77,,,, -7, 6, 4, 4, 3, 3, 3, 3, 128, 221, 149, 77,,,, -7, 6, 4, 4, 3, 3, 3, 3, 256, 221, 149, 77,,,, -7, 6, 4, 4, 3, 3, 3, 3, 384, 221, 149, 77,,,, -7, 6, 4, 5, 1, 1, 1, 1, 128, 240, 185, 95,,,, -7, 6, 4, 5, 1, 1, 1, 1, 256, 240, 185, 95,,,, -7, 6, 4, 5, 1, 1, 1, 1, 384, 240, 185, 95,,,, -7, 6, 4, 5, 2, 2, 1, 1, 128, 240, 185, 95,,,, -7, 6, 4, 5, 2, 2, 1, 1, 256, 240, 185, 95,,,, -7, 6, 4, 5, 2, 2, 1, 1, 384, 240, 185, 95,,,, -7, 6, 4, 5, 2, 2, 1, 2, 128, 240, 185, 95,,,, -7, 6, 4, 5, 2, 2, 1, 2, 256, 240, 185, 95,,,, -7, 6, 4, 5, 2, 2, 1, 2, 384, 240, 185, 95,,,, -7, 6, 4, 5, 2, 2, 2, 1, 128, 240, 185, 95,,,, -7, 6, 4, 5, 2, 2, 2, 1, 256, 240, 185, 95,,,, -7, 6, 4, 5, 2, 2, 2, 1, 384, 240, 185, 95,,,, -7, 6, 4, 5, 2, 2, 2, 2, 128, 240, 185, 95,,,, -7, 6, 4, 5, 2, 2, 2, 2, 256, 240, 185, 95,,,, -7, 6, 4, 5, 2, 2, 2, 2, 384, 240, 185, 95,,,, -7, 6, 4, 5, 3, 3, 1, 1, 128, 240, 185, 95,,,, -7, 6, 4, 5, 3, 3, 1, 1, 256, 240, 185, 95,,,, -7, 6, 4, 5, 3, 3, 1, 1, 384, 240, 185, 95,,,, -7, 6, 4, 5, 3, 3, 1, 2, 128, 240, 185, 95,,,, -7, 6, 4, 5, 3, 3, 1, 2, 256, 240, 185, 95,,,, -7, 6, 4, 5, 3, 3, 1, 2, 384, 240, 185, 95,,,, -7, 6, 4, 5, 3, 3, 1, 3, 128, 240, 185, 95,,,, -7, 6, 4, 5, 3, 3, 1, 3, 256, 240, 185, 95,,,, -7, 6, 4, 5, 3, 3, 1, 3, 384, 240, 185, 95,,,, -7, 6, 4, 5, 3, 3, 2, 1, 128, 240, 185, 95,,,, -7, 6, 4, 5, 3, 3, 2, 1, 256, 240, 185, 95,,,, -7, 6, 4, 5, 3, 3, 2, 1, 384, 240, 185, 95,,,, -7, 6, 4, 5, 3, 3, 2, 2, 128, 240, 185, 95,,,, -7, 6, 4, 5, 3, 3, 2, 2, 256, 240, 185, 95,,,, -7, 6, 4, 5, 3, 3, 2, 2, 384, 240, 185, 95,,,, -7, 6, 4, 5, 3, 3, 2, 3, 128, 240, 185, 95,,,, -7, 6, 4, 5, 3, 3, 2, 3, 256, 240, 185, 95,,,, -7, 6, 4, 5, 3, 3, 2, 3, 384, 240, 185, 95,,,, -7, 6, 4, 5, 3, 3, 3, 1, 128, 240, 185, 95,,,, -7, 6, 4, 5, 3, 3, 3, 1, 256, 240, 185, 95,,,, -7, 6, 4, 5, 3, 3, 3, 1, 384, 240, 185, 95,,,, -7, 6, 4, 5, 3, 3, 3, 2, 128, 240, 185, 95,,,, -7, 6, 4, 5, 3, 3, 3, 2, 256, 240, 185, 95,,,, -7, 6, 4, 5, 3, 3, 3, 2, 384, 240, 185, 95,,,, -7, 6, 4, 5, 3, 3, 3, 3, 128, 240, 185, 95,,,, -7, 6, 4, 5, 3, 3, 3, 3, 256, 240, 185, 95,,,, -7, 6, 4, 5, 3, 3, 3, 3, 384, 240, 185, 95,,,, -7, 6, 4, 6, 1, 1, 1, 1, 128, 240, 221, 113,,,, -7, 6, 4, 6, 1, 1, 1, 1, 256, 240, 221, 113,,,, -7, 6, 4, 6, 1, 1, 1, 1, 384, 240, 221, 113,,,, -7, 6, 4, 6, 2, 2, 1, 1, 128, 240, 221, 113,,,, -7, 6, 4, 6, 2, 2, 1, 1, 256, 240, 221, 113,,,, -7, 6, 4, 6, 2, 2, 1, 1, 384, 240, 221, 113,,,, -7, 6, 4, 6, 2, 2, 1, 2, 128, 240, 221, 113,,,, -7, 6, 4, 6, 2, 2, 1, 2, 256, 240, 221, 113,,,, -7, 6, 4, 6, 2, 2, 1, 2, 384, 240, 221, 113,,,, -7, 6, 4, 6, 2, 2, 2, 1, 128, 240, 221, 113,,,, -7, 6, 4, 6, 2, 2, 2, 1, 256, 240, 221, 113,,,, -7, 6, 4, 6, 2, 2, 2, 1, 384, 240, 221, 113,,,, -7, 6, 4, 6, 2, 2, 2, 2, 128, 240, 221, 113,,,, -7, 6, 4, 6, 2, 2, 2, 2, 256, 240, 221, 113,,,, -7, 6, 4, 6, 2, 2, 2, 2, 384, 240, 221, 113,,,, -7, 6, 4, 6, 3, 3, 1, 1, 128, 240, 221, 113,,,, -7, 6, 4, 6, 3, 3, 1, 1, 256, 240, 221, 113,,,, -7, 6, 4, 6, 3, 3, 1, 1, 384, 240, 221, 113,,,, -7, 6, 4, 6, 3, 3, 1, 2, 128, 240, 221, 113,,,, -7, 6, 4, 6, 3, 3, 1, 2, 256, 240, 221, 113,,,, -7, 6, 4, 6, 3, 3, 1, 2, 384, 240, 221, 113,,,, -7, 6, 4, 6, 3, 3, 1, 3, 128, 240, 221, 113,,,, -7, 6, 4, 6, 3, 3, 1, 3, 256, 240, 221, 113,,,, -7, 6, 4, 6, 3, 3, 1, 3, 384, 240, 221, 113,,,, -7, 6, 4, 6, 3, 3, 2, 1, 128, 240, 221, 113,,,, -7, 6, 4, 6, 3, 3, 2, 1, 256, 240, 221, 113,,,, -7, 6, 4, 6, 3, 3, 2, 1, 384, 240, 221, 113,,,, -7, 6, 4, 6, 3, 3, 2, 2, 128, 240, 221, 113,,,, -7, 6, 4, 6, 3, 3, 2, 2, 256, 240, 221, 113,,,, -7, 6, 4, 6, 3, 3, 2, 2, 384, 240, 221, 113,,,, -7, 6, 4, 6, 3, 3, 2, 3, 128, 240, 221, 113,,,, -7, 6, 4, 6, 3, 3, 2, 3, 256, 240, 221, 113,,,, -7, 6, 4, 6, 3, 3, 2, 3, 384, 240, 221, 113,,,, -7, 6, 4, 6, 3, 3, 3, 1, 128, 240, 221, 113,,,, -7, 6, 4, 6, 3, 3, 3, 1, 256, 240, 221, 113,,,, -7, 6, 4, 6, 3, 3, 3, 1, 384, 240, 221, 113,,,, -7, 6, 4, 6, 3, 3, 3, 2, 128, 240, 221, 113,,,, -7, 6, 4, 6, 3, 3, 3, 2, 256, 240, 221, 113,,,, -7, 6, 4, 6, 3, 3, 3, 2, 384, 240, 221, 113,,,, -7, 6, 4, 6, 3, 3, 3, 3, 128, 240, 221, 113,,,, -7, 6, 4, 6, 3, 3, 3, 3, 256, 240, 221, 113,,,, -7, 6, 4, 6, 3, 3, 3, 3, 384, 240, 221, 113,,,, -7, 6, 5, 1, 1, 1, 1, 1, 128, 59, 41, 23,,,, -7, 6, 5, 1, 1, 1, 1, 1, 256, 59, 41, 23,,,, -7, 6, 5, 1, 1, 1, 1, 1, 384, 59, 41, 23,,,, -7, 6, 5, 1, 2, 2, 1, 1, 128, 59, 41, 23,,,, -7, 6, 5, 1, 2, 2, 1, 1, 256, 59, 41, 23,,,, -7, 6, 5, 1, 2, 2, 1, 1, 384, 59, 41, 23,,,, -7, 6, 5, 1, 2, 2, 1, 2, 128, 59, 41, 23,,,, -7, 6, 5, 1, 2, 2, 1, 2, 256, 59, 41, 23,,,, -7, 6, 5, 1, 2, 2, 1, 2, 384, 59, 41, 23,,,, -7, 6, 5, 1, 2, 2, 2, 1, 128, 59, 41, 23,,,, -7, 6, 5, 1, 2, 2, 2, 1, 256, 59, 41, 23,,,, -7, 6, 5, 1, 2, 2, 2, 1, 384, 59, 41, 23,,,, -7, 6, 5, 1, 2, 2, 2, 2, 128, 59, 41, 23,,,, -7, 6, 5, 1, 2, 2, 2, 2, 256, 59, 41, 23,,,, -7, 6, 5, 1, 2, 2, 2, 2, 384, 59, 41, 23,,,, -7, 6, 5, 1, 3, 3, 1, 1, 128, 59, 41, 23,,,, -7, 6, 5, 1, 3, 3, 1, 1, 256, 59, 41, 23,,,, -7, 6, 5, 1, 3, 3, 1, 1, 384, 59, 41, 23,,,, -7, 6, 5, 1, 3, 3, 1, 2, 128, 59, 41, 23,,,, -7, 6, 5, 1, 3, 3, 1, 2, 256, 59, 41, 23,,,, -7, 6, 5, 1, 3, 3, 1, 2, 384, 59, 41, 23,,,, -7, 6, 5, 1, 3, 3, 1, 3, 128, 59, 41, 23,,,, -7, 6, 5, 1, 3, 3, 1, 3, 256, 59, 41, 23,,,, -7, 6, 5, 1, 3, 3, 1, 3, 384, 59, 41, 23,,,, -7, 6, 5, 1, 3, 3, 2, 1, 128, 59, 41, 23,,,, -7, 6, 5, 1, 3, 3, 2, 1, 256, 59, 41, 23,,,, -7, 6, 5, 1, 3, 3, 2, 1, 384, 59, 41, 23,,,, -7, 6, 5, 1, 3, 3, 2, 2, 128, 59, 41, 23,,,, -7, 6, 5, 1, 3, 3, 2, 2, 256, 59, 41, 23,,,, -7, 6, 5, 1, 3, 3, 2, 2, 384, 59, 41, 23,,,, -7, 6, 5, 1, 3, 3, 2, 3, 128, 59, 41, 23,,,, -7, 6, 5, 1, 3, 3, 2, 3, 256, 59, 41, 23,,,, -7, 6, 5, 1, 3, 3, 2, 3, 384, 59, 41, 23,,,, -7, 6, 5, 1, 3, 3, 3, 1, 128, 59, 41, 23,,,, -7, 6, 5, 1, 3, 3, 3, 1, 256, 59, 41, 23,,,, -7, 6, 5, 1, 3, 3, 3, 1, 384, 59, 41, 23,,,, -7, 6, 5, 1, 3, 3, 3, 2, 128, 59, 41, 23,,,, -7, 6, 5, 1, 3, 3, 3, 2, 256, 59, 41, 23,,,, -7, 6, 5, 1, 3, 3, 3, 2, 384, 59, 41, 23,,,, -7, 6, 5, 1, 3, 3, 3, 3, 128, 59, 41, 23,,,, -7, 6, 5, 1, 3, 3, 3, 3, 256, 59, 41, 23,,,, -7, 6, 5, 1, 3, 3, 3, 3, 384, 59, 41, 23,,,, -7, 6, 5, 2, 1, 1, 1, 1, 128, 113, 77, 41,,,, -7, 6, 5, 2, 1, 1, 1, 1, 256, 113, 77, 41,,,, -7, 6, 5, 2, 1, 1, 1, 1, 384, 113, 77, 41,,,, -7, 6, 5, 2, 2, 2, 1, 1, 128, 113, 77, 41,,,, -7, 6, 5, 2, 2, 2, 1, 1, 256, 113, 77, 41,,,, -7, 6, 5, 2, 2, 2, 1, 1, 384, 113, 77, 41,,,, -7, 6, 5, 2, 2, 2, 1, 2, 128, 113, 77, 41,,,, -7, 6, 5, 2, 2, 2, 1, 2, 256, 113, 77, 41,,,, -7, 6, 5, 2, 2, 2, 1, 2, 384, 113, 77, 41,,,, -7, 6, 5, 2, 2, 2, 2, 1, 128, 113, 77, 41,,,, -7, 6, 5, 2, 2, 2, 2, 1, 256, 113, 77, 41,,,, -7, 6, 5, 2, 2, 2, 2, 1, 384, 113, 77, 41,,,, -7, 6, 5, 2, 2, 2, 2, 2, 128, 113, 77, 41,,,, -7, 6, 5, 2, 2, 2, 2, 2, 256, 113, 77, 41,,,, -7, 6, 5, 2, 2, 2, 2, 2, 384, 113, 77, 41,,,, -7, 6, 5, 2, 3, 3, 1, 1, 128, 113, 77, 41,,,, -7, 6, 5, 2, 3, 3, 1, 1, 256, 113, 77, 41,,,, -7, 6, 5, 2, 3, 3, 1, 1, 384, 113, 77, 41,,,, -7, 6, 5, 2, 3, 3, 1, 2, 128, 113, 77, 41,,,, -7, 6, 5, 2, 3, 3, 1, 2, 256, 113, 77, 41,,,, -7, 6, 5, 2, 3, 3, 1, 2, 384, 113, 77, 41,,,, -7, 6, 5, 2, 3, 3, 1, 3, 128, 113, 77, 41,,,, -7, 6, 5, 2, 3, 3, 1, 3, 256, 113, 77, 41,,,, -7, 6, 5, 2, 3, 3, 1, 3, 384, 113, 77, 41,,,, -7, 6, 5, 2, 3, 3, 2, 1, 128, 113, 77, 41,,,, -7, 6, 5, 2, 3, 3, 2, 1, 256, 113, 77, 41,,,, -7, 6, 5, 2, 3, 3, 2, 1, 384, 113, 77, 41,,,, -7, 6, 5, 2, 3, 3, 2, 2, 128, 113, 77, 41,,,, -7, 6, 5, 2, 3, 3, 2, 2, 256, 113, 77, 41,,,, -7, 6, 5, 2, 3, 3, 2, 2, 384, 113, 77, 41,,,, -7, 6, 5, 2, 3, 3, 2, 3, 128, 113, 77, 41,,,, -7, 6, 5, 2, 3, 3, 2, 3, 256, 113, 77, 41,,,, -7, 6, 5, 2, 3, 3, 2, 3, 384, 113, 77, 41,,,, -7, 6, 5, 2, 3, 3, 3, 1, 128, 113, 77, 41,,,, -7, 6, 5, 2, 3, 3, 3, 1, 256, 113, 77, 41,,,, -7, 6, 5, 2, 3, 3, 3, 1, 384, 113, 77, 41,,,, -7, 6, 5, 2, 3, 3, 3, 2, 128, 113, 77, 41,,,, -7, 6, 5, 2, 3, 3, 3, 2, 256, 113, 77, 41,,,, -7, 6, 5, 2, 3, 3, 3, 2, 384, 113, 77, 41,,,, -7, 6, 5, 2, 3, 3, 3, 3, 128, 113, 77, 41,,,, -7, 6, 5, 2, 3, 3, 3, 3, 256, 113, 77, 41,,,, -7, 6, 5, 2, 3, 3, 3, 3, 384, 113, 77, 41,,,, -7, 6, 5, 3, 1, 1, 1, 1, 128, 167, 113, 59,,,, -7, 6, 5, 3, 1, 1, 1, 1, 256, 167, 113, 59,,,, -7, 6, 5, 3, 1, 1, 1, 1, 384, 167, 113, 59,,,, -7, 6, 5, 3, 2, 2, 1, 1, 128, 167, 113, 59,,,, -7, 6, 5, 3, 2, 2, 1, 1, 256, 167, 113, 59,,,, -7, 6, 5, 3, 2, 2, 1, 1, 384, 167, 113, 59,,,, -7, 6, 5, 3, 2, 2, 1, 2, 128, 167, 113, 59,,,, -7, 6, 5, 3, 2, 2, 1, 2, 256, 167, 113, 59,,,, -7, 6, 5, 3, 2, 2, 1, 2, 384, 167, 113, 59,,,, -7, 6, 5, 3, 2, 2, 2, 1, 128, 167, 113, 59,,,, -7, 6, 5, 3, 2, 2, 2, 1, 256, 167, 113, 59,,,, -7, 6, 5, 3, 2, 2, 2, 1, 384, 167, 113, 59,,,, -7, 6, 5, 3, 2, 2, 2, 2, 128, 167, 113, 59,,,, -7, 6, 5, 3, 2, 2, 2, 2, 256, 167, 113, 59,,,, -7, 6, 5, 3, 2, 2, 2, 2, 384, 167, 113, 59,,,, -7, 6, 5, 3, 3, 3, 1, 1, 128, 167, 113, 59,,,, -7, 6, 5, 3, 3, 3, 1, 1, 256, 167, 113, 59,,,, -7, 6, 5, 3, 3, 3, 1, 1, 384, 167, 113, 59,,,, -7, 6, 5, 3, 3, 3, 1, 2, 128, 167, 113, 59,,,, -7, 6, 5, 3, 3, 3, 1, 2, 256, 167, 113, 59,,,, -7, 6, 5, 3, 3, 3, 1, 2, 384, 167, 113, 59,,,, -7, 6, 5, 3, 3, 3, 1, 3, 128, 167, 113, 59,,,, -7, 6, 5, 3, 3, 3, 1, 3, 256, 167, 113, 59,,,, -7, 6, 5, 3, 3, 3, 1, 3, 384, 167, 113, 59,,,, -7, 6, 5, 3, 3, 3, 2, 1, 128, 167, 113, 59,,,, -7, 6, 5, 3, 3, 3, 2, 1, 256, 167, 113, 59,,,, -7, 6, 5, 3, 3, 3, 2, 1, 384, 167, 113, 59,,,, -7, 6, 5, 3, 3, 3, 2, 2, 128, 167, 113, 59,,,, -7, 6, 5, 3, 3, 3, 2, 2, 256, 167, 113, 59,,,, -7, 6, 5, 3, 3, 3, 2, 2, 384, 167, 113, 59,,,, -7, 6, 5, 3, 3, 3, 2, 3, 128, 167, 113, 59,,,, -7, 6, 5, 3, 3, 3, 2, 3, 256, 167, 113, 59,,,, -7, 6, 5, 3, 3, 3, 2, 3, 384, 167, 113, 59,,,, -7, 6, 5, 3, 3, 3, 3, 1, 128, 167, 113, 59,,,, -7, 6, 5, 3, 3, 3, 3, 1, 256, 167, 113, 59,,,, -7, 6, 5, 3, 3, 3, 3, 1, 384, 167, 113, 59,,,, -7, 6, 5, 3, 3, 3, 3, 2, 128, 167, 113, 59,,,, -7, 6, 5, 3, 3, 3, 3, 2, 256, 167, 113, 59,,,, -7, 6, 5, 3, 3, 3, 3, 2, 384, 167, 113, 59,,,, -7, 6, 5, 3, 3, 3, 3, 3, 128, 167, 113, 59,,,, -7, 6, 5, 3, 3, 3, 3, 3, 256, 167, 113, 59,,,, -7, 6, 5, 3, 3, 3, 3, 3, 384, 167, 113, 59,,,, -7, 6, 5, 4, 1, 1, 1, 1, 128, 221, 149, 77,,,, -7, 6, 5, 4, 1, 1, 1, 1, 256, 221, 149, 77,,,, -7, 6, 5, 4, 1, 1, 1, 1, 384, 221, 149, 77,,,, -7, 6, 5, 4, 2, 2, 1, 1, 128, 221, 149, 77,,,, -7, 6, 5, 4, 2, 2, 1, 1, 256, 221, 149, 77,,,, -7, 6, 5, 4, 2, 2, 1, 1, 384, 221, 149, 77,,,, -7, 6, 5, 4, 2, 2, 1, 2, 128, 221, 149, 77,,,, -7, 6, 5, 4, 2, 2, 1, 2, 256, 221, 149, 77,,,, -7, 6, 5, 4, 2, 2, 1, 2, 384, 221, 149, 77,,,, -7, 6, 5, 4, 2, 2, 2, 1, 128, 221, 149, 77,,,, -7, 6, 5, 4, 2, 2, 2, 1, 256, 221, 149, 77,,,, -7, 6, 5, 4, 2, 2, 2, 1, 384, 221, 149, 77,,,, -7, 6, 5, 4, 2, 2, 2, 2, 128, 221, 149, 77,,,, -7, 6, 5, 4, 2, 2, 2, 2, 256, 221, 149, 77,,,, -7, 6, 5, 4, 2, 2, 2, 2, 384, 221, 149, 77,,,, -7, 6, 5, 4, 3, 3, 1, 1, 128, 221, 149, 77,,,, -7, 6, 5, 4, 3, 3, 1, 1, 256, 221, 149, 77,,,, -7, 6, 5, 4, 3, 3, 1, 1, 384, 221, 149, 77,,,, -7, 6, 5, 4, 3, 3, 1, 2, 128, 221, 149, 77,,,, -7, 6, 5, 4, 3, 3, 1, 2, 256, 221, 149, 77,,,, -7, 6, 5, 4, 3, 3, 1, 2, 384, 221, 149, 77,,,, -7, 6, 5, 4, 3, 3, 1, 3, 128, 221, 149, 77,,,, -7, 6, 5, 4, 3, 3, 1, 3, 256, 221, 149, 77,,,, -7, 6, 5, 4, 3, 3, 1, 3, 384, 221, 149, 77,,,, -7, 6, 5, 4, 3, 3, 2, 1, 128, 221, 149, 77,,,, -7, 6, 5, 4, 3, 3, 2, 1, 256, 221, 149, 77,,,, -7, 6, 5, 4, 3, 3, 2, 1, 384, 221, 149, 77,,,, -7, 6, 5, 4, 3, 3, 2, 2, 128, 221, 149, 77,,,, -7, 6, 5, 4, 3, 3, 2, 2, 256, 221, 149, 77,,,, -7, 6, 5, 4, 3, 3, 2, 2, 384, 221, 149, 77,,,, -7, 6, 5, 4, 3, 3, 2, 3, 128, 221, 149, 77,,,, -7, 6, 5, 4, 3, 3, 2, 3, 256, 221, 149, 77,,,, -7, 6, 5, 4, 3, 3, 2, 3, 384, 221, 149, 77,,,, -7, 6, 5, 4, 3, 3, 3, 1, 128, 221, 149, 77,,,, -7, 6, 5, 4, 3, 3, 3, 1, 256, 221, 149, 77,,,, -7, 6, 5, 4, 3, 3, 3, 1, 384, 221, 149, 77,,,, -7, 6, 5, 4, 3, 3, 3, 2, 128, 221, 149, 77,,,, -7, 6, 5, 4, 3, 3, 3, 2, 256, 221, 149, 77,,,, -7, 6, 5, 4, 3, 3, 3, 2, 384, 221, 149, 77,,,, -7, 6, 5, 4, 3, 3, 3, 3, 128, 221, 149, 77,,,, -7, 6, 5, 4, 3, 3, 3, 3, 256, 221, 149, 77,,,, -7, 6, 5, 4, 3, 3, 3, 3, 384, 221, 149, 77,,,, -7, 6, 5, 5, 1, 1, 1, 1, 128, 240, 185, 95,,,, -7, 6, 5, 5, 1, 1, 1, 1, 256, 240, 185, 95,,,, -7, 6, 5, 5, 1, 1, 1, 1, 384, 240, 185, 95,,,, -7, 6, 5, 5, 2, 2, 1, 1, 128, 240, 185, 95,,,, -7, 6, 5, 5, 2, 2, 1, 1, 256, 240, 185, 95,,,, -7, 6, 5, 5, 2, 2, 1, 1, 384, 240, 185, 95,,,, -7, 6, 5, 5, 2, 2, 1, 2, 128, 240, 185, 95,,,, -7, 6, 5, 5, 2, 2, 1, 2, 256, 240, 185, 95,,,, -7, 6, 5, 5, 2, 2, 1, 2, 384, 240, 185, 95,,,, -7, 6, 5, 5, 2, 2, 2, 1, 128, 240, 185, 95,,,, -7, 6, 5, 5, 2, 2, 2, 1, 256, 240, 185, 95,,,, -7, 6, 5, 5, 2, 2, 2, 1, 384, 240, 185, 95,,,, -7, 6, 5, 5, 2, 2, 2, 2, 128, 240, 185, 95,,,, -7, 6, 5, 5, 2, 2, 2, 2, 256, 240, 185, 95,,,, -7, 6, 5, 5, 2, 2, 2, 2, 384, 240, 185, 95,,,, -7, 6, 5, 5, 3, 3, 1, 1, 128, 240, 185, 95,,,, -7, 6, 5, 5, 3, 3, 1, 1, 256, 240, 185, 95,,,, -7, 6, 5, 5, 3, 3, 1, 1, 384, 240, 185, 95,,,, -7, 6, 5, 5, 3, 3, 1, 2, 128, 240, 185, 95,,,, -7, 6, 5, 5, 3, 3, 1, 2, 256, 240, 185, 95,,,, -7, 6, 5, 5, 3, 3, 1, 2, 384, 240, 185, 95,,,, -7, 6, 5, 5, 3, 3, 1, 3, 128, 240, 185, 95,,,, -7, 6, 5, 5, 3, 3, 1, 3, 256, 240, 185, 95,,,, -7, 6, 5, 5, 3, 3, 1, 3, 384, 240, 185, 95,,,, -7, 6, 5, 5, 3, 3, 2, 1, 128, 240, 185, 95,,,, -7, 6, 5, 5, 3, 3, 2, 1, 256, 240, 185, 95,,,, -7, 6, 5, 5, 3, 3, 2, 1, 384, 240, 185, 95,,,, -7, 6, 5, 5, 3, 3, 2, 2, 128, 240, 185, 95,,,, -7, 6, 5, 5, 3, 3, 2, 2, 256, 240, 185, 95,,,, -7, 6, 5, 5, 3, 3, 2, 2, 384, 240, 185, 95,,,, -7, 6, 5, 5, 3, 3, 2, 3, 128, 240, 185, 95,,,, -7, 6, 5, 5, 3, 3, 2, 3, 256, 240, 185, 95,,,, -7, 6, 5, 5, 3, 3, 2, 3, 384, 240, 185, 95,,,, -7, 6, 5, 5, 3, 3, 3, 1, 128, 240, 185, 95,,,, -7, 6, 5, 5, 3, 3, 3, 1, 256, 240, 185, 95,,,, -7, 6, 5, 5, 3, 3, 3, 1, 384, 240, 185, 95,,,, -7, 6, 5, 5, 3, 3, 3, 2, 128, 240, 185, 95,,,, -7, 6, 5, 5, 3, 3, 3, 2, 256, 240, 185, 95,,,, -7, 6, 5, 5, 3, 3, 3, 2, 384, 240, 185, 95,,,, -7, 6, 5, 5, 3, 3, 3, 3, 128, 240, 185, 95,,,, -7, 6, 5, 5, 3, 3, 3, 3, 256, 240, 185, 95,,,, -7, 6, 5, 5, 3, 3, 3, 3, 384, 240, 185, 95,,,, -7, 6, 5, 6, 1, 1, 1, 1, 128, 240, 221, 113,,,, -7, 6, 5, 6, 1, 1, 1, 1, 256, 240, 221, 113,,,, -7, 6, 5, 6, 1, 1, 1, 1, 384, 240, 221, 113,,,, -7, 6, 5, 6, 2, 2, 1, 1, 128, 240, 221, 113,,,, -7, 6, 5, 6, 2, 2, 1, 1, 256, 240, 221, 113,,,, -7, 6, 5, 6, 2, 2, 1, 1, 384, 240, 221, 113,,,, -7, 6, 5, 6, 2, 2, 1, 2, 128, 240, 221, 113,,,, -7, 6, 5, 6, 2, 2, 1, 2, 256, 240, 221, 113,,,, -7, 6, 5, 6, 2, 2, 1, 2, 384, 240, 221, 113,,,, -7, 6, 5, 6, 2, 2, 2, 1, 128, 240, 221, 113,,,, -7, 6, 5, 6, 2, 2, 2, 1, 256, 240, 221, 113,,,, -7, 6, 5, 6, 2, 2, 2, 1, 384, 240, 221, 113,,,, -7, 6, 5, 6, 2, 2, 2, 2, 128, 240, 221, 113,,,, -7, 6, 5, 6, 2, 2, 2, 2, 256, 240, 221, 113,,,, -7, 6, 5, 6, 2, 2, 2, 2, 384, 240, 221, 113,,,, -7, 6, 5, 6, 3, 3, 1, 1, 128, 240, 221, 113,,,, -7, 6, 5, 6, 3, 3, 1, 1, 256, 240, 221, 113,,,, -7, 6, 5, 6, 3, 3, 1, 1, 384, 240, 221, 113,,,, -7, 6, 5, 6, 3, 3, 1, 2, 128, 240, 221, 113,,,, -7, 6, 5, 6, 3, 3, 1, 2, 256, 240, 221, 113,,,, -7, 6, 5, 6, 3, 3, 1, 2, 384, 240, 221, 113,,,, -7, 6, 5, 6, 3, 3, 1, 3, 128, 240, 221, 113,,,, -7, 6, 5, 6, 3, 3, 1, 3, 256, 240, 221, 113,,,, -7, 6, 5, 6, 3, 3, 1, 3, 384, 240, 221, 113,,,, -7, 6, 5, 6, 3, 3, 2, 1, 128, 240, 221, 113,,,, -7, 6, 5, 6, 3, 3, 2, 1, 256, 240, 221, 113,,,, -7, 6, 5, 6, 3, 3, 2, 1, 384, 240, 221, 113,,,, -7, 6, 5, 6, 3, 3, 2, 2, 128, 240, 221, 113,,,, -7, 6, 5, 6, 3, 3, 2, 2, 256, 240, 221, 113,,,, -7, 6, 5, 6, 3, 3, 2, 2, 384, 240, 221, 113,,,, -7, 6, 5, 6, 3, 3, 2, 3, 128, 240, 221, 113,,,, -7, 6, 5, 6, 3, 3, 2, 3, 256, 240, 221, 113,,,, -7, 6, 5, 6, 3, 3, 2, 3, 384, 240, 221, 113,,,, -7, 6, 5, 6, 3, 3, 3, 1, 128, 240, 221, 113,,,, -7, 6, 5, 6, 3, 3, 3, 1, 256, 240, 221, 113,,,, -7, 6, 5, 6, 3, 3, 3, 1, 384, 240, 221, 113,,,, -7, 6, 5, 6, 3, 3, 3, 2, 128, 240, 221, 113,,,, -7, 6, 5, 6, 3, 3, 3, 2, 256, 240, 221, 113,,,, -7, 6, 5, 6, 3, 3, 3, 2, 384, 240, 221, 113,,,, -7, 6, 5, 6, 3, 3, 3, 3, 128, 240, 221, 113,,,, -7, 6, 5, 6, 3, 3, 3, 3, 256, 240, 221, 113,,,, -7, 6, 5, 6, 3, 3, 3, 3, 384, 240, 221, 113,,,, -7, 6, 6, 1, 1, 1, 1, 1, 128, 59, 41, 23,,,, -7, 6, 6, 1, 1, 1, 1, 1, 256, 59, 41, 23,,,, -7, 6, 6, 1, 1, 1, 1, 1, 384, 59, 41, 23,,,, -7, 6, 6, 1, 2, 2, 1, 1, 128, 59, 41, 23,,,, -7, 6, 6, 1, 2, 2, 1, 1, 256, 59, 41, 23,,,, -7, 6, 6, 1, 2, 2, 1, 1, 384, 59, 41, 23,,,, -7, 6, 6, 1, 2, 2, 1, 2, 128, 59, 41, 23,,,, -7, 6, 6, 1, 2, 2, 1, 2, 256, 59, 41, 23,,,, -7, 6, 6, 1, 2, 2, 1, 2, 384, 59, 41, 23,,,, -7, 6, 6, 1, 2, 2, 2, 1, 128, 59, 41, 23,,,, -7, 6, 6, 1, 2, 2, 2, 1, 256, 59, 41, 23,,,, -7, 6, 6, 1, 2, 2, 2, 1, 384, 59, 41, 23,,,, -7, 6, 6, 1, 2, 2, 2, 2, 128, 59, 41, 23,,,, -7, 6, 6, 1, 2, 2, 2, 2, 256, 59, 41, 23,,,, -7, 6, 6, 1, 2, 2, 2, 2, 384, 59, 41, 23,,,, -7, 6, 6, 1, 3, 3, 1, 1, 128, 59, 41, 23,,,, -7, 6, 6, 1, 3, 3, 1, 1, 256, 59, 41, 23,,,, -7, 6, 6, 1, 3, 3, 1, 1, 384, 59, 41, 23,,,, -7, 6, 6, 1, 3, 3, 1, 2, 128, 59, 41, 23,,,, -7, 6, 6, 1, 3, 3, 1, 2, 256, 59, 41, 23,,,, -7, 6, 6, 1, 3, 3, 1, 2, 384, 59, 41, 23,,,, -7, 6, 6, 1, 3, 3, 1, 3, 128, 59, 41, 23,,,, -7, 6, 6, 1, 3, 3, 1, 3, 256, 59, 41, 23,,,, -7, 6, 6, 1, 3, 3, 1, 3, 384, 59, 41, 23,,,, -7, 6, 6, 1, 3, 3, 2, 1, 128, 59, 41, 23,,,, -7, 6, 6, 1, 3, 3, 2, 1, 256, 59, 41, 23,,,, -7, 6, 6, 1, 3, 3, 2, 1, 384, 59, 41, 23,,,, -7, 6, 6, 1, 3, 3, 2, 2, 128, 59, 41, 23,,,, -7, 6, 6, 1, 3, 3, 2, 2, 256, 59, 41, 23,,,, -7, 6, 6, 1, 3, 3, 2, 2, 384, 59, 41, 23,,,, -7, 6, 6, 1, 3, 3, 2, 3, 128, 59, 41, 23,,,, -7, 6, 6, 1, 3, 3, 2, 3, 256, 59, 41, 23,,,, -7, 6, 6, 1, 3, 3, 2, 3, 384, 59, 41, 23,,,, -7, 6, 6, 1, 3, 3, 3, 1, 128, 59, 41, 23,,,, -7, 6, 6, 1, 3, 3, 3, 1, 256, 59, 41, 23,,,, -7, 6, 6, 1, 3, 3, 3, 1, 384, 59, 41, 23,,,, -7, 6, 6, 1, 3, 3, 3, 2, 128, 59, 41, 23,,,, -7, 6, 6, 1, 3, 3, 3, 2, 256, 59, 41, 23,,,, -7, 6, 6, 1, 3, 3, 3, 2, 384, 59, 41, 23,,,, -7, 6, 6, 1, 3, 3, 3, 3, 128, 59, 41, 23,,,, -7, 6, 6, 1, 3, 3, 3, 3, 256, 59, 41, 23,,,, -7, 6, 6, 1, 3, 3, 3, 3, 384, 59, 41, 23,,,, -7, 6, 6, 2, 1, 1, 1, 1, 128, 113, 77, 41,,,, -7, 6, 6, 2, 1, 1, 1, 1, 256, 113, 77, 41,,,, -7, 6, 6, 2, 1, 1, 1, 1, 384, 113, 77, 41,,,, -7, 6, 6, 2, 2, 2, 1, 1, 128, 113, 77, 41,,,, -7, 6, 6, 2, 2, 2, 1, 1, 256, 113, 77, 41,,,, -7, 6, 6, 2, 2, 2, 1, 1, 384, 113, 77, 41,,,, -7, 6, 6, 2, 2, 2, 1, 2, 128, 113, 77, 41,,,, -7, 6, 6, 2, 2, 2, 1, 2, 256, 113, 77, 41,,,, -7, 6, 6, 2, 2, 2, 1, 2, 384, 113, 77, 41,,,, -7, 6, 6, 2, 2, 2, 2, 1, 128, 113, 77, 41,,,, -7, 6, 6, 2, 2, 2, 2, 1, 256, 113, 77, 41,,,, -7, 6, 6, 2, 2, 2, 2, 1, 384, 113, 77, 41,,,, -7, 6, 6, 2, 2, 2, 2, 2, 128, 113, 77, 41,,,, -7, 6, 6, 2, 2, 2, 2, 2, 256, 113, 77, 41,,,, -7, 6, 6, 2, 2, 2, 2, 2, 384, 113, 77, 41,,,, -7, 6, 6, 2, 3, 3, 1, 1, 128, 113, 77, 41,,,, -7, 6, 6, 2, 3, 3, 1, 1, 256, 113, 77, 41,,,, -7, 6, 6, 2, 3, 3, 1, 1, 384, 113, 77, 41,,,, -7, 6, 6, 2, 3, 3, 1, 2, 128, 113, 77, 41,,,, -7, 6, 6, 2, 3, 3, 1, 2, 256, 113, 77, 41,,,, -7, 6, 6, 2, 3, 3, 1, 2, 384, 113, 77, 41,,,, -7, 6, 6, 2, 3, 3, 1, 3, 128, 113, 77, 41,,,, -7, 6, 6, 2, 3, 3, 1, 3, 256, 113, 77, 41,,,, -7, 6, 6, 2, 3, 3, 1, 3, 384, 113, 77, 41,,,, -7, 6, 6, 2, 3, 3, 2, 1, 128, 113, 77, 41,,,, -7, 6, 6, 2, 3, 3, 2, 1, 256, 113, 77, 41,,,, -7, 6, 6, 2, 3, 3, 2, 1, 384, 113, 77, 41,,,, -7, 6, 6, 2, 3, 3, 2, 2, 128, 113, 77, 41,,,, -7, 6, 6, 2, 3, 3, 2, 2, 256, 113, 77, 41,,,, -7, 6, 6, 2, 3, 3, 2, 2, 384, 113, 77, 41,,,, -7, 6, 6, 2, 3, 3, 2, 3, 128, 113, 77, 41,,,, -7, 6, 6, 2, 3, 3, 2, 3, 256, 113, 77, 41,,,, -7, 6, 6, 2, 3, 3, 2, 3, 384, 113, 77, 41,,,, -7, 6, 6, 2, 3, 3, 3, 1, 128, 113, 77, 41,,,, -7, 6, 6, 2, 3, 3, 3, 1, 256, 113, 77, 41,,,, -7, 6, 6, 2, 3, 3, 3, 1, 384, 113, 77, 41,,,, -7, 6, 6, 2, 3, 3, 3, 2, 128, 113, 77, 41,,,, -7, 6, 6, 2, 3, 3, 3, 2, 256, 113, 77, 41,,,, -7, 6, 6, 2, 3, 3, 3, 2, 384, 113, 77, 41,,,, -7, 6, 6, 2, 3, 3, 3, 3, 128, 113, 77, 41,,,, -7, 6, 6, 2, 3, 3, 3, 3, 256, 113, 77, 41,,,, -7, 6, 6, 2, 3, 3, 3, 3, 384, 113, 77, 41,,,, -7, 6, 6, 3, 1, 1, 1, 1, 128, 167, 113, 59,,,, -7, 6, 6, 3, 1, 1, 1, 1, 256, 167, 113, 59,,,, -7, 6, 6, 3, 1, 1, 1, 1, 384, 167, 113, 59,,,, -7, 6, 6, 3, 2, 2, 1, 1, 128, 167, 113, 59,,,, -7, 6, 6, 3, 2, 2, 1, 1, 256, 167, 113, 59,,,, -7, 6, 6, 3, 2, 2, 1, 1, 384, 167, 113, 59,,,, -7, 6, 6, 3, 2, 2, 1, 2, 128, 167, 113, 59,,,, -7, 6, 6, 3, 2, 2, 1, 2, 256, 167, 113, 59,,,, -7, 6, 6, 3, 2, 2, 1, 2, 384, 167, 113, 59,,,, -7, 6, 6, 3, 2, 2, 2, 1, 128, 167, 113, 59,,,, -7, 6, 6, 3, 2, 2, 2, 1, 256, 167, 113, 59,,,, -7, 6, 6, 3, 2, 2, 2, 1, 384, 167, 113, 59,,,, -7, 6, 6, 3, 2, 2, 2, 2, 128, 167, 113, 59,,,, -7, 6, 6, 3, 2, 2, 2, 2, 256, 167, 113, 59,,,, -7, 6, 6, 3, 2, 2, 2, 2, 384, 167, 113, 59,,,, -7, 6, 6, 3, 3, 3, 1, 1, 128, 167, 113, 59,,,, -7, 6, 6, 3, 3, 3, 1, 1, 256, 167, 113, 59,,,, -7, 6, 6, 3, 3, 3, 1, 1, 384, 167, 113, 59,,,, -7, 6, 6, 3, 3, 3, 1, 2, 128, 167, 113, 59,,,, -7, 6, 6, 3, 3, 3, 1, 2, 256, 167, 113, 59,,,, -7, 6, 6, 3, 3, 3, 1, 2, 384, 167, 113, 59,,,, -7, 6, 6, 3, 3, 3, 1, 3, 128, 167, 113, 59,,,, -7, 6, 6, 3, 3, 3, 1, 3, 256, 167, 113, 59,,,, -7, 6, 6, 3, 3, 3, 1, 3, 384, 167, 113, 59,,,, -7, 6, 6, 3, 3, 3, 2, 1, 128, 167, 113, 59,,,, -7, 6, 6, 3, 3, 3, 2, 1, 256, 167, 113, 59,,,, -7, 6, 6, 3, 3, 3, 2, 1, 384, 167, 113, 59,,,, -7, 6, 6, 3, 3, 3, 2, 2, 128, 167, 113, 59,,,, -7, 6, 6, 3, 3, 3, 2, 2, 256, 167, 113, 59,,,, -7, 6, 6, 3, 3, 3, 2, 2, 384, 167, 113, 59,,,, -7, 6, 6, 3, 3, 3, 2, 3, 128, 167, 113, 59,,,, -7, 6, 6, 3, 3, 3, 2, 3, 256, 167, 113, 59,,,, -7, 6, 6, 3, 3, 3, 2, 3, 384, 167, 113, 59,,,, -7, 6, 6, 3, 3, 3, 3, 1, 128, 167, 113, 59,,,, -7, 6, 6, 3, 3, 3, 3, 1, 256, 167, 113, 59,,,, -7, 6, 6, 3, 3, 3, 3, 1, 384, 167, 113, 59,,,, -7, 6, 6, 3, 3, 3, 3, 2, 128, 167, 113, 59,,,, -7, 6, 6, 3, 3, 3, 3, 2, 256, 167, 113, 59,,,, -7, 6, 6, 3, 3, 3, 3, 2, 384, 167, 113, 59,,,, -7, 6, 6, 3, 3, 3, 3, 3, 128, 167, 113, 59,,,, -7, 6, 6, 3, 3, 3, 3, 3, 256, 167, 113, 59,,,, -7, 6, 6, 3, 3, 3, 3, 3, 384, 167, 113, 59,,,, -7, 6, 6, 4, 1, 1, 1, 1, 128, 221, 149, 77,,,, -7, 6, 6, 4, 1, 1, 1, 1, 256, 221, 149, 77,,,, -7, 6, 6, 4, 1, 1, 1, 1, 384, 221, 149, 77,,,, -7, 6, 6, 4, 2, 2, 1, 1, 128, 221, 149, 77,,,, -7, 6, 6, 4, 2, 2, 1, 1, 256, 221, 149, 77,,,, -7, 6, 6, 4, 2, 2, 1, 1, 384, 221, 149, 77,,,, -7, 6, 6, 4, 2, 2, 1, 2, 128, 221, 149, 77,,,, -7, 6, 6, 4, 2, 2, 1, 2, 256, 221, 149, 77,,,, -7, 6, 6, 4, 2, 2, 1, 2, 384, 221, 149, 77,,,, -7, 6, 6, 4, 2, 2, 2, 1, 128, 221, 149, 77,,,, -7, 6, 6, 4, 2, 2, 2, 1, 256, 221, 149, 77,,,, -7, 6, 6, 4, 2, 2, 2, 1, 384, 221, 149, 77,,,, -7, 6, 6, 4, 2, 2, 2, 2, 128, 221, 149, 77,,,, -7, 6, 6, 4, 2, 2, 2, 2, 256, 221, 149, 77,,,, -7, 6, 6, 4, 2, 2, 2, 2, 384, 221, 149, 77,,,, -7, 6, 6, 4, 3, 3, 1, 1, 128, 221, 149, 77,,,, -7, 6, 6, 4, 3, 3, 1, 1, 256, 221, 149, 77,,,, -7, 6, 6, 4, 3, 3, 1, 1, 384, 221, 149, 77,,,, -7, 6, 6, 4, 3, 3, 1, 2, 128, 221, 149, 77,,,, -7, 6, 6, 4, 3, 3, 1, 2, 256, 221, 149, 77,,,, -7, 6, 6, 4, 3, 3, 1, 2, 384, 221, 149, 77,,,, -7, 6, 6, 4, 3, 3, 1, 3, 128, 221, 149, 77,,,, -7, 6, 6, 4, 3, 3, 1, 3, 256, 221, 149, 77,,,, -7, 6, 6, 4, 3, 3, 1, 3, 384, 221, 149, 77,,,, -7, 6, 6, 4, 3, 3, 2, 1, 128, 221, 149, 77,,,, -7, 6, 6, 4, 3, 3, 2, 1, 256, 221, 149, 77,,,, -7, 6, 6, 4, 3, 3, 2, 1, 384, 221, 149, 77,,,, -7, 6, 6, 4, 3, 3, 2, 2, 128, 221, 149, 77,,,, -7, 6, 6, 4, 3, 3, 2, 2, 256, 221, 149, 77,,,, -7, 6, 6, 4, 3, 3, 2, 2, 384, 221, 149, 77,,,, -7, 6, 6, 4, 3, 3, 2, 3, 128, 221, 149, 77,,,, -7, 6, 6, 4, 3, 3, 2, 3, 256, 221, 149, 77,,,, -7, 6, 6, 4, 3, 3, 2, 3, 384, 221, 149, 77,,,, -7, 6, 6, 4, 3, 3, 3, 1, 128, 221, 149, 77,,,, -7, 6, 6, 4, 3, 3, 3, 1, 256, 221, 149, 77,,,, -7, 6, 6, 4, 3, 3, 3, 1, 384, 221, 149, 77,,,, -7, 6, 6, 4, 3, 3, 3, 2, 128, 221, 149, 77,,,, -7, 6, 6, 4, 3, 3, 3, 2, 256, 221, 149, 77,,,, -7, 6, 6, 4, 3, 3, 3, 2, 384, 221, 149, 77,,,, -7, 6, 6, 4, 3, 3, 3, 3, 128, 221, 149, 77,,,, -7, 6, 6, 4, 3, 3, 3, 3, 256, 221, 149, 77,,,, -7, 6, 6, 4, 3, 3, 3, 3, 384, 221, 149, 77,,,, -7, 6, 6, 5, 1, 1, 1, 1, 128, 240, 185, 95,,,, -7, 6, 6, 5, 1, 1, 1, 1, 256, 240, 185, 95,,,, -7, 6, 6, 5, 1, 1, 1, 1, 384, 240, 185, 95,,,, -7, 6, 6, 5, 2, 2, 1, 1, 128, 240, 185, 95,,,, -7, 6, 6, 5, 2, 2, 1, 1, 256, 240, 185, 95,,,, -7, 6, 6, 5, 2, 2, 1, 1, 384, 240, 185, 95,,,, -7, 6, 6, 5, 2, 2, 1, 2, 128, 240, 185, 95,,,, -7, 6, 6, 5, 2, 2, 1, 2, 256, 240, 185, 95,,,, -7, 6, 6, 5, 2, 2, 1, 2, 384, 240, 185, 95,,,, -7, 6, 6, 5, 2, 2, 2, 1, 128, 240, 185, 95,,,, -7, 6, 6, 5, 2, 2, 2, 1, 256, 240, 185, 95,,,, -7, 6, 6, 5, 2, 2, 2, 1, 384, 240, 185, 95,,,, -7, 6, 6, 5, 2, 2, 2, 2, 128, 240, 185, 95,,,, -7, 6, 6, 5, 2, 2, 2, 2, 256, 240, 185, 95,,,, -7, 6, 6, 5, 2, 2, 2, 2, 384, 240, 185, 95,,,, -7, 6, 6, 5, 3, 3, 1, 1, 128, 240, 185, 95,,,, -7, 6, 6, 5, 3, 3, 1, 1, 256, 240, 185, 95,,,, -7, 6, 6, 5, 3, 3, 1, 1, 384, 240, 185, 95,,,, -7, 6, 6, 5, 3, 3, 1, 2, 128, 240, 185, 95,,,, -7, 6, 6, 5, 3, 3, 1, 2, 256, 240, 185, 95,,,, -7, 6, 6, 5, 3, 3, 1, 2, 384, 240, 185, 95,,,, -7, 6, 6, 5, 3, 3, 1, 3, 128, 240, 185, 95,,,, -7, 6, 6, 5, 3, 3, 1, 3, 256, 240, 185, 95,,,, -7, 6, 6, 5, 3, 3, 1, 3, 384, 240, 185, 95,,,, -7, 6, 6, 5, 3, 3, 2, 1, 128, 240, 185, 95,,,, -7, 6, 6, 5, 3, 3, 2, 1, 256, 240, 185, 95,,,, -7, 6, 6, 5, 3, 3, 2, 1, 384, 240, 185, 95,,,, -7, 6, 6, 5, 3, 3, 2, 2, 128, 240, 185, 95,,,, -7, 6, 6, 5, 3, 3, 2, 2, 256, 240, 185, 95,,,, -7, 6, 6, 5, 3, 3, 2, 2, 384, 240, 185, 95,,,, -7, 6, 6, 5, 3, 3, 2, 3, 128, 240, 185, 95,,,, -7, 6, 6, 5, 3, 3, 2, 3, 256, 240, 185, 95,,,, -7, 6, 6, 5, 3, 3, 2, 3, 384, 240, 185, 95,,,, -7, 6, 6, 5, 3, 3, 3, 1, 128, 240, 185, 95,,,, -7, 6, 6, 5, 3, 3, 3, 1, 256, 240, 185, 95,,,, -7, 6, 6, 5, 3, 3, 3, 1, 384, 240, 185, 95,,,, -7, 6, 6, 5, 3, 3, 3, 2, 128, 240, 185, 95,,,, -7, 6, 6, 5, 3, 3, 3, 2, 256, 240, 185, 95,,,, -7, 6, 6, 5, 3, 3, 3, 2, 384, 240, 185, 95,,,, -7, 6, 6, 5, 3, 3, 3, 3, 128, 240, 185, 95,,,, -7, 6, 6, 5, 3, 3, 3, 3, 256, 240, 185, 95,,,, -7, 6, 6, 5, 3, 3, 3, 3, 384, 240, 185, 95,,,, -7, 6, 6, 6, 1, 1, 1, 1, 128, 240, 221, 113,,,, -7, 6, 6, 6, 1, 1, 1, 1, 256, 240, 221, 113,,,, -7, 6, 6, 6, 1, 1, 1, 1, 384, 240, 221, 113,,,, -7, 6, 6, 6, 2, 2, 1, 1, 128, 240, 221, 113,,,, -7, 6, 6, 6, 2, 2, 1, 1, 256, 240, 221, 113,,,, -7, 6, 6, 6, 2, 2, 1, 1, 384, 240, 221, 113,,,, -7, 6, 6, 6, 2, 2, 1, 2, 128, 240, 221, 113,,,, -7, 6, 6, 6, 2, 2, 1, 2, 256, 240, 221, 113,,,, -7, 6, 6, 6, 2, 2, 1, 2, 384, 240, 221, 113,,,, -7, 6, 6, 6, 2, 2, 2, 1, 128, 240, 221, 113,,,, -7, 6, 6, 6, 2, 2, 2, 1, 256, 240, 221, 113,,,, -7, 6, 6, 6, 2, 2, 2, 1, 384, 240, 221, 113,,,, -7, 6, 6, 6, 2, 2, 2, 2, 128, 240, 221, 113,,,, -7, 6, 6, 6, 2, 2, 2, 2, 256, 240, 221, 113,,,, -7, 6, 6, 6, 2, 2, 2, 2, 384, 240, 221, 113,,,, -7, 6, 6, 6, 3, 3, 1, 1, 128, 240, 221, 113,,,, -7, 6, 6, 6, 3, 3, 1, 1, 256, 240, 221, 113,,,, -7, 6, 6, 6, 3, 3, 1, 1, 384, 240, 221, 113,,,, -7, 6, 6, 6, 3, 3, 1, 2, 128, 240, 221, 113,,,, -7, 6, 6, 6, 3, 3, 1, 2, 256, 240, 221, 113,,,, -7, 6, 6, 6, 3, 3, 1, 2, 384, 240, 221, 113,,,, -7, 6, 6, 6, 3, 3, 1, 3, 128, 240, 221, 113,,,, -7, 6, 6, 6, 3, 3, 1, 3, 256, 240, 221, 113,,,, -7, 6, 6, 6, 3, 3, 1, 3, 384, 240, 221, 113,,,, -7, 6, 6, 6, 3, 3, 2, 1, 128, 240, 221, 113,,,, -7, 6, 6, 6, 3, 3, 2, 1, 256, 240, 221, 113,,,, -7, 6, 6, 6, 3, 3, 2, 1, 384, 240, 221, 113,,,, -7, 6, 6, 6, 3, 3, 2, 2, 128, 240, 221, 113,,,, -7, 6, 6, 6, 3, 3, 2, 2, 256, 240, 221, 113,,,, -7, 6, 6, 6, 3, 3, 2, 2, 384, 240, 221, 113,,,, -7, 6, 6, 6, 3, 3, 2, 3, 128, 240, 221, 113,,,, -7, 6, 6, 6, 3, 3, 2, 3, 256, 240, 221, 113,,,, -7, 6, 6, 6, 3, 3, 2, 3, 384, 240, 221, 113,,,, -7, 6, 6, 6, 3, 3, 3, 1, 128, 240, 221, 113,,,, -7, 6, 6, 6, 3, 3, 3, 1, 256, 240, 221, 113,,,, -7, 6, 6, 6, 3, 3, 3, 1, 384, 240, 221, 113,,,, -7, 6, 6, 6, 3, 3, 3, 2, 128, 240, 221, 113,,,, -7, 6, 6, 6, 3, 3, 3, 2, 256, 240, 221, 113,,,, -7, 6, 6, 6, 3, 3, 3, 2, 384, 240, 221, 113,,,, -7, 6, 6, 6, 3, 3, 3, 3, 128, 240, 221, 113,,,, -7, 6, 6, 6, 3, 3, 3, 3, 256, 240, 221, 113,,,, -7, 6, 6, 6, 3, 3, 3, 3, 384, 240, 221, 113,,,, -7, 6, 7, 1, 1, 1, 1, 1, 128, 59, 41, 23,,,, -7, 6, 7, 1, 1, 1, 1, 1, 256, 59, 41, 23,,,, -7, 6, 7, 1, 1, 1, 1, 1, 384, 59, 41, 23,,,, -7, 6, 7, 1, 2, 2, 1, 1, 128, 59, 41, 23,,,, -7, 6, 7, 1, 2, 2, 1, 1, 256, 59, 41, 23,,,, -7, 6, 7, 1, 2, 2, 1, 1, 384, 59, 41, 23,,,, -7, 6, 7, 1, 2, 2, 1, 2, 128, 59, 41, 23,,,, -7, 6, 7, 1, 2, 2, 1, 2, 256, 59, 41, 23,,,, -7, 6, 7, 1, 2, 2, 1, 2, 384, 59, 41, 23,,,, -7, 6, 7, 1, 2, 2, 2, 1, 128, 59, 41, 23,,,, -7, 6, 7, 1, 2, 2, 2, 1, 256, 59, 41, 23,,,, -7, 6, 7, 1, 2, 2, 2, 1, 384, 59, 41, 23,,,, -7, 6, 7, 1, 2, 2, 2, 2, 128, 59, 41, 23,,,, -7, 6, 7, 1, 2, 2, 2, 2, 256, 59, 41, 23,,,, -7, 6, 7, 1, 2, 2, 2, 2, 384, 59, 41, 23,,,, -7, 6, 7, 1, 3, 3, 1, 1, 128, 59, 41, 23,,,, -7, 6, 7, 1, 3, 3, 1, 1, 256, 59, 41, 23,,,, -7, 6, 7, 1, 3, 3, 1, 1, 384, 59, 41, 23,,,, -7, 6, 7, 1, 3, 3, 1, 2, 128, 59, 41, 23,,,, -7, 6, 7, 1, 3, 3, 1, 2, 256, 59, 41, 23,,,, -7, 6, 7, 1, 3, 3, 1, 2, 384, 59, 41, 23,,,, -7, 6, 7, 1, 3, 3, 1, 3, 128, 59, 41, 23,,,, -7, 6, 7, 1, 3, 3, 1, 3, 256, 59, 41, 23,,,, -7, 6, 7, 1, 3, 3, 1, 3, 384, 59, 41, 23,,,, -7, 6, 7, 1, 3, 3, 2, 1, 128, 59, 41, 23,,,, -7, 6, 7, 1, 3, 3, 2, 1, 256, 59, 41, 23,,,, -7, 6, 7, 1, 3, 3, 2, 1, 384, 59, 41, 23,,,, -7, 6, 7, 1, 3, 3, 2, 2, 128, 59, 41, 23,,,, -7, 6, 7, 1, 3, 3, 2, 2, 256, 59, 41, 23,,,, -7, 6, 7, 1, 3, 3, 2, 2, 384, 59, 41, 23,,,, -7, 6, 7, 1, 3, 3, 2, 3, 128, 59, 41, 23,,,, -7, 6, 7, 1, 3, 3, 2, 3, 256, 59, 41, 23,,,, -7, 6, 7, 1, 3, 3, 2, 3, 384, 59, 41, 23,,,, -7, 6, 7, 1, 3, 3, 3, 1, 128, 59, 41, 23,,,, -7, 6, 7, 1, 3, 3, 3, 1, 256, 59, 41, 23,,,, -7, 6, 7, 1, 3, 3, 3, 1, 384, 59, 41, 23,,,, -7, 6, 7, 1, 3, 3, 3, 2, 128, 59, 41, 23,,,, -7, 6, 7, 1, 3, 3, 3, 2, 256, 59, 41, 23,,,, -7, 6, 7, 1, 3, 3, 3, 2, 384, 59, 41, 23,,,, -7, 6, 7, 1, 3, 3, 3, 3, 128, 59, 41, 23,,,, -7, 6, 7, 1, 3, 3, 3, 3, 256, 59, 41, 23,,,, -7, 6, 7, 1, 3, 3, 3, 3, 384, 59, 41, 23,,,, -7, 6, 7, 2, 1, 1, 1, 1, 128, 113, 77, 41,,,, -7, 6, 7, 2, 1, 1, 1, 1, 256, 113, 77, 41,,,, -7, 6, 7, 2, 1, 1, 1, 1, 384, 113, 77, 41,,,, -7, 6, 7, 2, 2, 2, 1, 1, 128, 113, 77, 41,,,, -7, 6, 7, 2, 2, 2, 1, 1, 256, 113, 77, 41,,,, -7, 6, 7, 2, 2, 2, 1, 1, 384, 113, 77, 41,,,, -7, 6, 7, 2, 2, 2, 1, 2, 128, 113, 77, 41,,,, -7, 6, 7, 2, 2, 2, 1, 2, 256, 113, 77, 41,,,, -7, 6, 7, 2, 2, 2, 1, 2, 384, 113, 77, 41,,,, -7, 6, 7, 2, 2, 2, 2, 1, 128, 113, 77, 41,,,, -7, 6, 7, 2, 2, 2, 2, 1, 256, 113, 77, 41,,,, -7, 6, 7, 2, 2, 2, 2, 1, 384, 113, 77, 41,,,, -7, 6, 7, 2, 2, 2, 2, 2, 128, 113, 77, 41,,,, -7, 6, 7, 2, 2, 2, 2, 2, 256, 113, 77, 41,,,, -7, 6, 7, 2, 2, 2, 2, 2, 384, 113, 77, 41,,,, -7, 6, 7, 2, 3, 3, 1, 1, 128, 113, 77, 41,,,, -7, 6, 7, 2, 3, 3, 1, 1, 256, 113, 77, 41,,,, -7, 6, 7, 2, 3, 3, 1, 1, 384, 113, 77, 41,,,, -7, 6, 7, 2, 3, 3, 1, 2, 128, 113, 77, 41,,,, -7, 6, 7, 2, 3, 3, 1, 2, 256, 113, 77, 41,,,, -7, 6, 7, 2, 3, 3, 1, 2, 384, 113, 77, 41,,,, -7, 6, 7, 2, 3, 3, 1, 3, 128, 113, 77, 41,,,, -7, 6, 7, 2, 3, 3, 1, 3, 256, 113, 77, 41,,,, -7, 6, 7, 2, 3, 3, 1, 3, 384, 113, 77, 41,,,, -7, 6, 7, 2, 3, 3, 2, 1, 128, 113, 77, 41,,,, -7, 6, 7, 2, 3, 3, 2, 1, 256, 113, 77, 41,,,, -7, 6, 7, 2, 3, 3, 2, 1, 384, 113, 77, 41,,,, -7, 6, 7, 2, 3, 3, 2, 2, 128, 113, 77, 41,,,, -7, 6, 7, 2, 3, 3, 2, 2, 256, 113, 77, 41,,,, -7, 6, 7, 2, 3, 3, 2, 2, 384, 113, 77, 41,,,, -7, 6, 7, 2, 3, 3, 2, 3, 128, 113, 77, 41,,,, -7, 6, 7, 2, 3, 3, 2, 3, 256, 113, 77, 41,,,, -7, 6, 7, 2, 3, 3, 2, 3, 384, 113, 77, 41,,,, -7, 6, 7, 2, 3, 3, 3, 1, 128, 113, 77, 41,,,, -7, 6, 7, 2, 3, 3, 3, 1, 256, 113, 77, 41,,,, -7, 6, 7, 2, 3, 3, 3, 1, 384, 113, 77, 41,,,, -7, 6, 7, 2, 3, 3, 3, 2, 128, 113, 77, 41,,,, -7, 6, 7, 2, 3, 3, 3, 2, 256, 113, 77, 41,,,, -7, 6, 7, 2, 3, 3, 3, 2, 384, 113, 77, 41,,,, -7, 6, 7, 2, 3, 3, 3, 3, 128, 113, 77, 41,,,, -7, 6, 7, 2, 3, 3, 3, 3, 256, 113, 77, 41,,,, -7, 6, 7, 2, 3, 3, 3, 3, 384, 113, 77, 41,,,, -7, 6, 7, 3, 1, 1, 1, 1, 128, 167, 113, 59,,,, -7, 6, 7, 3, 1, 1, 1, 1, 256, 167, 113, 59,,,, -7, 6, 7, 3, 1, 1, 1, 1, 384, 167, 113, 59,,,, -7, 6, 7, 3, 2, 2, 1, 1, 128, 167, 113, 59,,,, -7, 6, 7, 3, 2, 2, 1, 1, 256, 167, 113, 59,,,, -7, 6, 7, 3, 2, 2, 1, 1, 384, 167, 113, 59,,,, -7, 6, 7, 3, 2, 2, 1, 2, 128, 167, 113, 59,,,, -7, 6, 7, 3, 2, 2, 1, 2, 256, 167, 113, 59,,,, -7, 6, 7, 3, 2, 2, 1, 2, 384, 167, 113, 59,,,, -7, 6, 7, 3, 2, 2, 2, 1, 128, 167, 113, 59,,,, -7, 6, 7, 3, 2, 2, 2, 1, 256, 167, 113, 59,,,, -7, 6, 7, 3, 2, 2, 2, 1, 384, 167, 113, 59,,,, -7, 6, 7, 3, 2, 2, 2, 2, 128, 167, 113, 59,,,, -7, 6, 7, 3, 2, 2, 2, 2, 256, 167, 113, 59,,,, -7, 6, 7, 3, 2, 2, 2, 2, 384, 167, 113, 59,,,, -7, 6, 7, 3, 3, 3, 1, 1, 128, 167, 113, 59,,,, -7, 6, 7, 3, 3, 3, 1, 1, 256, 167, 113, 59,,,, -7, 6, 7, 3, 3, 3, 1, 1, 384, 167, 113, 59,,,, -7, 6, 7, 3, 3, 3, 1, 2, 128, 167, 113, 59,,,, -7, 6, 7, 3, 3, 3, 1, 2, 256, 167, 113, 59,,,, -7, 6, 7, 3, 3, 3, 1, 2, 384, 167, 113, 59,,,, -7, 6, 7, 3, 3, 3, 1, 3, 128, 167, 113, 59,,,, -7, 6, 7, 3, 3, 3, 1, 3, 256, 167, 113, 59,,,, -7, 6, 7, 3, 3, 3, 1, 3, 384, 167, 113, 59,,,, -7, 6, 7, 3, 3, 3, 2, 1, 128, 167, 113, 59,,,, -7, 6, 7, 3, 3, 3, 2, 1, 256, 167, 113, 59,,,, -7, 6, 7, 3, 3, 3, 2, 1, 384, 167, 113, 59,,,, -7, 6, 7, 3, 3, 3, 2, 2, 128, 167, 113, 59,,,, -7, 6, 7, 3, 3, 3, 2, 2, 256, 167, 113, 59,,,, -7, 6, 7, 3, 3, 3, 2, 2, 384, 167, 113, 59,,,, -7, 6, 7, 3, 3, 3, 2, 3, 128, 167, 113, 59,,,, -7, 6, 7, 3, 3, 3, 2, 3, 256, 167, 113, 59,,,, -7, 6, 7, 3, 3, 3, 2, 3, 384, 167, 113, 59,,,, -7, 6, 7, 3, 3, 3, 3, 1, 128, 167, 113, 59,,,, -7, 6, 7, 3, 3, 3, 3, 1, 256, 167, 113, 59,,,, -7, 6, 7, 3, 3, 3, 3, 1, 384, 167, 113, 59,,,, -7, 6, 7, 3, 3, 3, 3, 2, 128, 167, 113, 59,,,, -7, 6, 7, 3, 3, 3, 3, 2, 256, 167, 113, 59,,,, -7, 6, 7, 3, 3, 3, 3, 2, 384, 167, 113, 59,,,, -7, 6, 7, 3, 3, 3, 3, 3, 128, 167, 113, 59,,,, -7, 6, 7, 3, 3, 3, 3, 3, 256, 167, 113, 59,,,, -7, 6, 7, 3, 3, 3, 3, 3, 384, 167, 113, 59,,,, -7, 6, 7, 4, 1, 1, 1, 1, 128, 221, 149, 77,,,, -7, 6, 7, 4, 1, 1, 1, 1, 256, 221, 149, 77,,,, -7, 6, 7, 4, 1, 1, 1, 1, 384, 221, 149, 77,,,, -7, 6, 7, 4, 2, 2, 1, 1, 128, 221, 149, 77,,,, -7, 6, 7, 4, 2, 2, 1, 1, 256, 221, 149, 77,,,, -7, 6, 7, 4, 2, 2, 1, 1, 384, 221, 149, 77,,,, -7, 6, 7, 4, 2, 2, 1, 2, 128, 221, 149, 77,,,, -7, 6, 7, 4, 2, 2, 1, 2, 256, 221, 149, 77,,,, -7, 6, 7, 4, 2, 2, 1, 2, 384, 221, 149, 77,,,, -7, 6, 7, 4, 2, 2, 2, 1, 128, 221, 149, 77,,,, -7, 6, 7, 4, 2, 2, 2, 1, 256, 221, 149, 77,,,, -7, 6, 7, 4, 2, 2, 2, 1, 384, 221, 149, 77,,,, -7, 6, 7, 4, 2, 2, 2, 2, 128, 221, 149, 77,,,, -7, 6, 7, 4, 2, 2, 2, 2, 256, 221, 149, 77,,,, -7, 6, 7, 4, 2, 2, 2, 2, 384, 221, 149, 77,,,, -7, 6, 7, 4, 3, 3, 1, 1, 128, 221, 149, 77,,,, -7, 6, 7, 4, 3, 3, 1, 1, 256, 221, 149, 77,,,, -7, 6, 7, 4, 3, 3, 1, 1, 384, 221, 149, 77,,,, -7, 6, 7, 4, 3, 3, 1, 2, 128, 221, 149, 77,,,, -7, 6, 7, 4, 3, 3, 1, 2, 256, 221, 149, 77,,,, -7, 6, 7, 4, 3, 3, 1, 2, 384, 221, 149, 77,,,, -7, 6, 7, 4, 3, 3, 1, 3, 128, 221, 149, 77,,,, -7, 6, 7, 4, 3, 3, 1, 3, 256, 221, 149, 77,,,, -7, 6, 7, 4, 3, 3, 1, 3, 384, 221, 149, 77,,,, -7, 6, 7, 4, 3, 3, 2, 1, 128, 221, 149, 77,,,, -7, 6, 7, 4, 3, 3, 2, 1, 256, 221, 149, 77,,,, -7, 6, 7, 4, 3, 3, 2, 1, 384, 221, 149, 77,,,, -7, 6, 7, 4, 3, 3, 2, 2, 128, 221, 149, 77,,,, -7, 6, 7, 4, 3, 3, 2, 2, 256, 221, 149, 77,,,, -7, 6, 7, 4, 3, 3, 2, 2, 384, 221, 149, 77,,,, -7, 6, 7, 4, 3, 3, 2, 3, 128, 221, 149, 77,,,, -7, 6, 7, 4, 3, 3, 2, 3, 256, 221, 149, 77,,,, -7, 6, 7, 4, 3, 3, 2, 3, 384, 221, 149, 77,,,, -7, 6, 7, 4, 3, 3, 3, 1, 128, 221, 149, 77,,,, -7, 6, 7, 4, 3, 3, 3, 1, 256, 221, 149, 77,,,, -7, 6, 7, 4, 3, 3, 3, 1, 384, 221, 149, 77,,,, -7, 6, 7, 4, 3, 3, 3, 2, 128, 221, 149, 77,,,, -7, 6, 7, 4, 3, 3, 3, 2, 256, 221, 149, 77,,,, -7, 6, 7, 4, 3, 3, 3, 2, 384, 221, 149, 77,,,, -7, 6, 7, 4, 3, 3, 3, 3, 128, 221, 149, 77,,,, -7, 6, 7, 4, 3, 3, 3, 3, 256, 221, 149, 77,,,, -7, 6, 7, 4, 3, 3, 3, 3, 384, 221, 149, 77,,,, -7, 6, 7, 5, 1, 1, 1, 1, 128, 240, 185, 95,,,, -7, 6, 7, 5, 1, 1, 1, 1, 256, 240, 185, 95,,,, -7, 6, 7, 5, 1, 1, 1, 1, 384, 240, 185, 95,,,, -7, 6, 7, 5, 2, 2, 1, 1, 128, 240, 185, 95,,,, -7, 6, 7, 5, 2, 2, 1, 1, 256, 240, 185, 95,,,, -7, 6, 7, 5, 2, 2, 1, 1, 384, 240, 185, 95,,,, -7, 6, 7, 5, 2, 2, 1, 2, 128, 240, 185, 95,,,, -7, 6, 7, 5, 2, 2, 1, 2, 256, 240, 185, 95,,,, -7, 6, 7, 5, 2, 2, 1, 2, 384, 240, 185, 95,,,, -7, 6, 7, 5, 2, 2, 2, 1, 128, 240, 185, 95,,,, -7, 6, 7, 5, 2, 2, 2, 1, 256, 240, 185, 95,,,, -7, 6, 7, 5, 2, 2, 2, 1, 384, 240, 185, 95,,,, -7, 6, 7, 5, 2, 2, 2, 2, 128, 240, 185, 95,,,, -7, 6, 7, 5, 2, 2, 2, 2, 256, 240, 185, 95,,,, -7, 6, 7, 5, 2, 2, 2, 2, 384, 240, 185, 95,,,, -7, 6, 7, 5, 3, 3, 1, 1, 128, 240, 185, 95,,,, -7, 6, 7, 5, 3, 3, 1, 1, 256, 240, 185, 95,,,, -7, 6, 7, 5, 3, 3, 1, 1, 384, 240, 185, 95,,,, -7, 6, 7, 5, 3, 3, 1, 2, 128, 240, 185, 95,,,, -7, 6, 7, 5, 3, 3, 1, 2, 256, 240, 185, 95,,,, -7, 6, 7, 5, 3, 3, 1, 2, 384, 240, 185, 95,,,, -7, 6, 7, 5, 3, 3, 1, 3, 128, 240, 185, 95,,,, -7, 6, 7, 5, 3, 3, 1, 3, 256, 240, 185, 95,,,, -7, 6, 7, 5, 3, 3, 1, 3, 384, 240, 185, 95,,,, -7, 6, 7, 5, 3, 3, 2, 1, 128, 240, 185, 95,,,, -7, 6, 7, 5, 3, 3, 2, 1, 256, 240, 185, 95,,,, -7, 6, 7, 5, 3, 3, 2, 1, 384, 240, 185, 95,,,, -7, 6, 7, 5, 3, 3, 2, 2, 128, 240, 185, 95,,,, -7, 6, 7, 5, 3, 3, 2, 2, 256, 240, 185, 95,,,, -7, 6, 7, 5, 3, 3, 2, 2, 384, 240, 185, 95,,,, -7, 6, 7, 5, 3, 3, 2, 3, 128, 240, 185, 95,,,, -7, 6, 7, 5, 3, 3, 2, 3, 256, 240, 185, 95,,,, -7, 6, 7, 5, 3, 3, 2, 3, 384, 240, 185, 95,,,, -7, 6, 7, 5, 3, 3, 3, 1, 128, 240, 185, 95,,,, -7, 6, 7, 5, 3, 3, 3, 1, 256, 240, 185, 95,,,, -7, 6, 7, 5, 3, 3, 3, 1, 384, 240, 185, 95,,,, -7, 6, 7, 5, 3, 3, 3, 2, 128, 240, 185, 95,,,, -7, 6, 7, 5, 3, 3, 3, 2, 256, 240, 185, 95,,,, -7, 6, 7, 5, 3, 3, 3, 2, 384, 240, 185, 95,,,, -7, 6, 7, 5, 3, 3, 3, 3, 128, 240, 185, 95,,,, -7, 6, 7, 5, 3, 3, 3, 3, 256, 240, 185, 95,,,, -7, 6, 7, 5, 3, 3, 3, 3, 384, 240, 185, 95,,,, -7, 6, 7, 6, 1, 1, 1, 1, 128, 240, 221, 113,,,, -7, 6, 7, 6, 1, 1, 1, 1, 256, 240, 221, 113,,,, -7, 6, 7, 6, 1, 1, 1, 1, 384, 240, 221, 113,,,, -7, 6, 7, 6, 2, 2, 1, 1, 128, 240, 221, 113,,,, -7, 6, 7, 6, 2, 2, 1, 1, 256, 240, 221, 113,,,, -7, 6, 7, 6, 2, 2, 1, 1, 384, 240, 221, 113,,,, -7, 6, 7, 6, 2, 2, 1, 2, 128, 240, 221, 113,,,, -7, 6, 7, 6, 2, 2, 1, 2, 256, 240, 221, 113,,,, -7, 6, 7, 6, 2, 2, 1, 2, 384, 240, 221, 113,,,, -7, 6, 7, 6, 2, 2, 2, 1, 128, 240, 221, 113,,,, -7, 6, 7, 6, 2, 2, 2, 1, 256, 240, 221, 113,,,, -7, 6, 7, 6, 2, 2, 2, 1, 384, 240, 221, 113,,,, -7, 6, 7, 6, 2, 2, 2, 2, 128, 240, 221, 113,,,, -7, 6, 7, 6, 2, 2, 2, 2, 256, 240, 221, 113,,,, -7, 6, 7, 6, 2, 2, 2, 2, 384, 240, 221, 113,,,, -7, 6, 7, 6, 3, 3, 1, 1, 128, 240, 221, 113,,,, -7, 6, 7, 6, 3, 3, 1, 1, 256, 240, 221, 113,,,, -7, 6, 7, 6, 3, 3, 1, 1, 384, 240, 221, 113,,,, -7, 6, 7, 6, 3, 3, 1, 2, 128, 240, 221, 113,,,, -7, 6, 7, 6, 3, 3, 1, 2, 256, 240, 221, 113,,,, -7, 6, 7, 6, 3, 3, 1, 2, 384, 240, 221, 113,,,, -7, 6, 7, 6, 3, 3, 1, 3, 128, 240, 221, 113,,,, -7, 6, 7, 6, 3, 3, 1, 3, 256, 240, 221, 113,,,, -7, 6, 7, 6, 3, 3, 1, 3, 384, 240, 221, 113,,,, -7, 6, 7, 6, 3, 3, 2, 1, 128, 240, 221, 113,,,, -7, 6, 7, 6, 3, 3, 2, 1, 256, 240, 221, 113,,,, -7, 6, 7, 6, 3, 3, 2, 1, 384, 240, 221, 113,,,, -7, 6, 7, 6, 3, 3, 2, 2, 128, 240, 221, 113,,,, -7, 6, 7, 6, 3, 3, 2, 2, 256, 240, 221, 113,,,, -7, 6, 7, 6, 3, 3, 2, 2, 384, 240, 221, 113,,,, -7, 6, 7, 6, 3, 3, 2, 3, 128, 240, 221, 113,,,, -7, 6, 7, 6, 3, 3, 2, 3, 256, 240, 221, 113,,,, -7, 6, 7, 6, 3, 3, 2, 3, 384, 240, 221, 113,,,, -7, 6, 7, 6, 3, 3, 3, 1, 128, 240, 221, 113,,,, -7, 6, 7, 6, 3, 3, 3, 1, 256, 240, 221, 113,,,, -7, 6, 7, 6, 3, 3, 3, 1, 384, 240, 221, 113,,,, -7, 6, 7, 6, 3, 3, 3, 2, 128, 240, 221, 113,,,, -7, 6, 7, 6, 3, 3, 3, 2, 256, 240, 221, 113,,,, -7, 6, 7, 6, 3, 3, 3, 2, 384, 240, 221, 113,,,, -7, 6, 7, 6, 3, 3, 3, 3, 128, 240, 221, 113,,,, -7, 6, 7, 6, 3, 3, 3, 3, 256, 240, 221, 113,,,, -7, 6, 7, 6, 3, 3, 3, 3, 384, 240, 221, 113,,,, -7, 7, 1, 1, 1, 1, 1, 1, 128, 60, 42,,,,, -7, 7, 1, 1, 1, 1, 1, 1, 256, 60, 42,,,,, -7, 7, 1, 1, 1, 1, 1, 1, 384, 60, 42,,,,, -7, 7, 1, 1, 2, 2, 1, 1, 128, 60, 42,,,,, -7, 7, 1, 1, 2, 2, 1, 1, 256, 60, 42,,,,, -7, 7, 1, 1, 2, 2, 1, 1, 384, 60, 42,,,,, -7, 7, 1, 1, 2, 2, 1, 2, 128, 60, 42,,,,, -7, 7, 1, 1, 2, 2, 1, 2, 256, 60, 42,,,,, -7, 7, 1, 1, 2, 2, 1, 2, 384, 60, 42,,,,, -7, 7, 1, 1, 2, 2, 2, 1, 128, 60, 42,,,,, -7, 7, 1, 1, 2, 2, 2, 1, 256, 60, 42,,,,, -7, 7, 1, 1, 2, 2, 2, 1, 384, 60, 42,,,,, -7, 7, 1, 1, 2, 2, 2, 2, 128, 60, 42,,,,, -7, 7, 1, 1, 2, 2, 2, 2, 256, 60, 42,,,,, -7, 7, 1, 1, 2, 2, 2, 2, 384, 60, 42,,,,, -7, 7, 1, 1, 3, 3, 1, 1, 128, 59, 42,,,,, -7, 7, 1, 1, 3, 3, 1, 1, 256, 59, 42,,,,, -7, 7, 1, 1, 3, 3, 1, 1, 384, 59, 42,,,,, -7, 7, 1, 1, 3, 3, 1, 2, 128, 59, 42,,,,, -7, 7, 1, 1, 3, 3, 1, 2, 256, 59, 42,,,,, -7, 7, 1, 1, 3, 3, 1, 2, 384, 59, 42,,,,, -7, 7, 1, 1, 3, 3, 1, 3, 128, 59, 42,,,,, -7, 7, 1, 1, 3, 3, 1, 3, 256, 59, 42,,,,, -7, 7, 1, 1, 3, 3, 1, 3, 384, 59, 42,,,,, -7, 7, 1, 1, 3, 3, 2, 1, 128, 59, 42,,,,, -7, 7, 1, 1, 3, 3, 2, 1, 256, 59, 42,,,,, -7, 7, 1, 1, 3, 3, 2, 1, 384, 59, 42,,,,, -7, 7, 1, 1, 3, 3, 2, 2, 128, 59, 42,,,,, -7, 7, 1, 1, 3, 3, 2, 2, 256, 59, 42,,,,, -7, 7, 1, 1, 3, 3, 2, 2, 384, 59, 42,,,,, -7, 7, 1, 1, 3, 3, 2, 3, 128, 59, 42,,,,, -7, 7, 1, 1, 3, 3, 2, 3, 256, 59, 42,,,,, -7, 7, 1, 1, 3, 3, 2, 3, 384, 59, 42,,,,, -7, 7, 1, 1, 3, 3, 3, 1, 128, 59, 42,,,,, -7, 7, 1, 1, 3, 3, 3, 1, 256, 59, 42,,,,, -7, 7, 1, 1, 3, 3, 3, 1, 384, 59, 42,,,,, -7, 7, 1, 1, 3, 3, 3, 2, 128, 59, 42,,,,, -7, 7, 1, 1, 3, 3, 3, 2, 256, 59, 42,,,,, -7, 7, 1, 1, 3, 3, 3, 2, 384, 59, 42,,,,, -7, 7, 1, 1, 3, 3, 3, 3, 128, 59, 42,,,,, -7, 7, 1, 1, 3, 3, 3, 3, 256, 59, 42,,,,, -7, 7, 1, 1, 3, 3, 3, 3, 384, 59, 42,,,,, -7, 7, 1, 2, 1, 1, 1, 1, 128, 114, 78,,,,, -7, 7, 1, 2, 1, 1, 1, 1, 256, 114, 78,,,,, -7, 7, 1, 2, 1, 1, 1, 1, 384, 114, 78,,,,, -7, 7, 1, 2, 2, 2, 1, 1, 128, 114, 78,,,,, -7, 7, 1, 2, 2, 2, 1, 1, 256, 114, 78,,,,, -7, 7, 1, 2, 2, 2, 1, 1, 384, 114, 78,,,,, -7, 7, 1, 2, 2, 2, 1, 2, 128, 114, 78,,,,, -7, 7, 1, 2, 2, 2, 1, 2, 256, 114, 78,,,,, -7, 7, 1, 2, 2, 2, 1, 2, 384, 114, 78,,,,, -7, 7, 1, 2, 2, 2, 2, 1, 128, 114, 78,,,,, -7, 7, 1, 2, 2, 2, 2, 1, 256, 114, 78,,,,, -7, 7, 1, 2, 2, 2, 2, 1, 384, 114, 78,,,,, -7, 7, 1, 2, 2, 2, 2, 2, 128, 114, 78,,,,, -7, 7, 1, 2, 2, 2, 2, 2, 256, 114, 78,,,,, -7, 7, 1, 2, 2, 2, 2, 2, 384, 114, 78,,,,, -7, 7, 1, 2, 3, 3, 1, 1, 128, 112, 78,,,,, -7, 7, 1, 2, 3, 3, 1, 1, 256, 112, 78,,,,, -7, 7, 1, 2, 3, 3, 1, 1, 384, 112, 78,,,,, -7, 7, 1, 2, 3, 3, 1, 2, 128, 112, 78,,,,, -7, 7, 1, 2, 3, 3, 1, 2, 256, 112, 78,,,,, -7, 7, 1, 2, 3, 3, 1, 2, 384, 112, 78,,,,, -7, 7, 1, 2, 3, 3, 1, 3, 128, 112, 78,,,,, -7, 7, 1, 2, 3, 3, 1, 3, 256, 112, 78,,,,, -7, 7, 1, 2, 3, 3, 1, 3, 384, 112, 78,,,,, -7, 7, 1, 2, 3, 3, 2, 1, 128, 112, 78,,,,, -7, 7, 1, 2, 3, 3, 2, 1, 256, 112, 78,,,,, -7, 7, 1, 2, 3, 3, 2, 1, 384, 112, 78,,,,, -7, 7, 1, 2, 3, 3, 2, 2, 128, 112, 78,,,,, -7, 7, 1, 2, 3, 3, 2, 2, 256, 112, 78,,,,, -7, 7, 1, 2, 3, 3, 2, 2, 384, 112, 78,,,,, -7, 7, 1, 2, 3, 3, 2, 3, 128, 112, 78,,,,, -7, 7, 1, 2, 3, 3, 2, 3, 256, 112, 78,,,,, -7, 7, 1, 2, 3, 3, 2, 3, 384, 112, 78,,,,, -7, 7, 1, 2, 3, 3, 3, 1, 128, 112, 78,,,,, -7, 7, 1, 2, 3, 3, 3, 1, 256, 112, 78,,,,, -7, 7, 1, 2, 3, 3, 3, 1, 384, 112, 78,,,,, -7, 7, 1, 2, 3, 3, 3, 2, 128, 112, 78,,,,, -7, 7, 1, 2, 3, 3, 3, 2, 256, 112, 78,,,,, -7, 7, 1, 2, 3, 3, 3, 2, 384, 112, 78,,,,, -7, 7, 1, 2, 3, 3, 3, 3, 128, 112, 78,,,,, -7, 7, 1, 2, 3, 3, 3, 3, 256, 112, 78,,,,, -7, 7, 1, 2, 3, 3, 3, 3, 384, 112, 78,,,,, -7, 7, 1, 3, 1, 1, 1, 1, 128, 168, 114,,,,, -7, 7, 1, 3, 1, 1, 1, 1, 256, 168, 114,,,,, -7, 7, 1, 3, 1, 1, 1, 1, 384, 168, 114,,,,, -7, 7, 1, 3, 2, 2, 1, 1, 128, 168, 114,,,,, -7, 7, 1, 3, 2, 2, 1, 1, 256, 168, 114,,,,, -7, 7, 1, 3, 2, 2, 1, 1, 384, 168, 114,,,,, -7, 7, 1, 3, 2, 2, 1, 2, 128, 168, 114,,,,, -7, 7, 1, 3, 2, 2, 1, 2, 256, 168, 114,,,,, -7, 7, 1, 3, 2, 2, 1, 2, 384, 168, 114,,,,, -7, 7, 1, 3, 2, 2, 2, 1, 128, 168, 114,,,,, -7, 7, 1, 3, 2, 2, 2, 1, 256, 168, 114,,,,, -7, 7, 1, 3, 2, 2, 2, 1, 384, 168, 114,,,,, -7, 7, 1, 3, 2, 2, 2, 2, 128, 168, 114,,,,, -7, 7, 1, 3, 2, 2, 2, 2, 256, 168, 114,,,,, -7, 7, 1, 3, 2, 2, 2, 2, 384, 168, 114,,,,, -7, 7, 1, 3, 3, 3, 1, 1, 128, 165, 114,,,,, -7, 7, 1, 3, 3, 3, 1, 1, 256, 165, 114,,,,, -7, 7, 1, 3, 3, 3, 1, 1, 384, 165, 114,,,,, -7, 7, 1, 3, 3, 3, 1, 2, 128, 165, 114,,,,, -7, 7, 1, 3, 3, 3, 1, 2, 256, 165, 114,,,,, -7, 7, 1, 3, 3, 3, 1, 2, 384, 165, 114,,,,, -7, 7, 1, 3, 3, 3, 1, 3, 128, 165, 114,,,,, -7, 7, 1, 3, 3, 3, 1, 3, 256, 165, 114,,,,, -7, 7, 1, 3, 3, 3, 1, 3, 384, 165, 114,,,,, -7, 7, 1, 3, 3, 3, 2, 1, 128, 165, 114,,,,, -7, 7, 1, 3, 3, 3, 2, 1, 256, 165, 114,,,,, -7, 7, 1, 3, 3, 3, 2, 1, 384, 165, 114,,,,, -7, 7, 1, 3, 3, 3, 2, 2, 128, 165, 114,,,,, -7, 7, 1, 3, 3, 3, 2, 2, 256, 165, 114,,,,, -7, 7, 1, 3, 3, 3, 2, 2, 384, 165, 114,,,,, -7, 7, 1, 3, 3, 3, 2, 3, 128, 165, 114,,,,, -7, 7, 1, 3, 3, 3, 2, 3, 256, 165, 114,,,,, -7, 7, 1, 3, 3, 3, 2, 3, 384, 165, 114,,,,, -7, 7, 1, 3, 3, 3, 3, 1, 128, 165, 114,,,,, -7, 7, 1, 3, 3, 3, 3, 1, 256, 165, 114,,,,, -7, 7, 1, 3, 3, 3, 3, 1, 384, 165, 114,,,,, -7, 7, 1, 3, 3, 3, 3, 2, 128, 165, 114,,,,, -7, 7, 1, 3, 3, 3, 3, 2, 256, 165, 114,,,,, -7, 7, 1, 3, 3, 3, 3, 2, 384, 165, 114,,,,, -7, 7, 1, 3, 3, 3, 3, 3, 128, 165, 114,,,,, -7, 7, 1, 3, 3, 3, 3, 3, 256, 165, 114,,,,, -7, 7, 1, 3, 3, 3, 3, 3, 384, 165, 114,,,,, -7, 7, 1, 4, 1, 1, 1, 1, 128, 222, 150,,,,, -7, 7, 1, 4, 1, 1, 1, 1, 256, 222, 150,,,,, -7, 7, 1, 4, 1, 1, 1, 1, 384, 222, 150,,,,, -7, 7, 1, 4, 2, 2, 1, 1, 128, 222, 150,,,,, -7, 7, 1, 4, 2, 2, 1, 1, 256, 222, 150,,,,, -7, 7, 1, 4, 2, 2, 1, 1, 384, 222, 150,,,,, -7, 7, 1, 4, 2, 2, 1, 2, 128, 222, 150,,,,, -7, 7, 1, 4, 2, 2, 1, 2, 256, 222, 150,,,,, -7, 7, 1, 4, 2, 2, 1, 2, 384, 222, 150,,,,, -7, 7, 1, 4, 2, 2, 2, 1, 128, 222, 150,,,,, -7, 7, 1, 4, 2, 2, 2, 1, 256, 222, 150,,,,, -7, 7, 1, 4, 2, 2, 2, 1, 384, 222, 150,,,,, -7, 7, 1, 4, 2, 2, 2, 2, 128, 222, 150,,,,, -7, 7, 1, 4, 2, 2, 2, 2, 256, 222, 150,,,,, -7, 7, 1, 4, 2, 2, 2, 2, 384, 222, 150,,,,, -7, 7, 1, 4, 3, 3, 1, 1, 128, 218, 150,,,,, -7, 7, 1, 4, 3, 3, 1, 1, 256, 218, 150,,,,, -7, 7, 1, 4, 3, 3, 1, 1, 384, 218, 150,,,,, -7, 7, 1, 4, 3, 3, 1, 2, 128, 218, 150,,,,, -7, 7, 1, 4, 3, 3, 1, 2, 256, 218, 150,,,,, -7, 7, 1, 4, 3, 3, 1, 2, 384, 218, 150,,,,, -7, 7, 1, 4, 3, 3, 1, 3, 128, 218, 150,,,,, -7, 7, 1, 4, 3, 3, 1, 3, 256, 218, 150,,,,, -7, 7, 1, 4, 3, 3, 1, 3, 384, 218, 150,,,,, -7, 7, 1, 4, 3, 3, 2, 1, 128, 218, 150,,,,, -7, 7, 1, 4, 3, 3, 2, 1, 256, 218, 150,,,,, -7, 7, 1, 4, 3, 3, 2, 1, 384, 218, 150,,,,, -7, 7, 1, 4, 3, 3, 2, 2, 128, 218, 150,,,,, -7, 7, 1, 4, 3, 3, 2, 2, 256, 218, 150,,,,, -7, 7, 1, 4, 3, 3, 2, 2, 384, 218, 150,,,,, -7, 7, 1, 4, 3, 3, 2, 3, 128, 218, 150,,,,, -7, 7, 1, 4, 3, 3, 2, 3, 256, 218, 150,,,,, -7, 7, 1, 4, 3, 3, 2, 3, 384, 218, 150,,,,, -7, 7, 1, 4, 3, 3, 3, 1, 128, 218, 150,,,,, -7, 7, 1, 4, 3, 3, 3, 1, 256, 218, 150,,,,, -7, 7, 1, 4, 3, 3, 3, 1, 384, 218, 150,,,,, -7, 7, 1, 4, 3, 3, 3, 2, 128, 218, 150,,,,, -7, 7, 1, 4, 3, 3, 3, 2, 256, 218, 150,,,,, -7, 7, 1, 4, 3, 3, 3, 2, 384, 218, 150,,,,, -7, 7, 1, 4, 3, 3, 3, 3, 128, 218, 150,,,,, -7, 7, 1, 4, 3, 3, 3, 3, 256, 218, 150,,,,, -7, 7, 1, 4, 3, 3, 3, 3, 384, 218, 150,,,,, -7, 7, 1, 5, 1, 1, 1, 1, 128, 240, 186,,,,, -7, 7, 1, 5, 1, 1, 1, 1, 256, 240, 186,,,,, -7, 7, 1, 5, 1, 1, 1, 1, 384, 240, 186,,,,, -7, 7, 1, 5, 2, 2, 1, 1, 128, 240, 186,,,,, -7, 7, 1, 5, 2, 2, 1, 1, 256, 240, 186,,,,, -7, 7, 1, 5, 2, 2, 1, 1, 384, 240, 186,,,,, -7, 7, 1, 5, 2, 2, 1, 2, 128, 240, 186,,,,, -7, 7, 1, 5, 2, 2, 1, 2, 256, 240, 186,,,,, -7, 7, 1, 5, 2, 2, 1, 2, 384, 240, 186,,,,, -7, 7, 1, 5, 2, 2, 2, 1, 128, 240, 186,,,,, -7, 7, 1, 5, 2, 2, 2, 1, 256, 240, 186,,,,, -7, 7, 1, 5, 2, 2, 2, 1, 384, 240, 186,,,,, -7, 7, 1, 5, 2, 2, 2, 2, 128, 240, 186,,,,, -7, 7, 1, 5, 2, 2, 2, 2, 256, 240, 186,,,,, -7, 7, 1, 5, 2, 2, 2, 2, 384, 240, 186,,,,, -7, 7, 1, 5, 3, 3, 1, 1, 128, 240, 186,,,,, -7, 7, 1, 5, 3, 3, 1, 1, 256, 240, 186,,,,, -7, 7, 1, 5, 3, 3, 1, 1, 384, 240, 186,,,,, -7, 7, 1, 5, 3, 3, 1, 2, 128, 240, 186,,,,, -7, 7, 1, 5, 3, 3, 1, 2, 256, 240, 186,,,,, -7, 7, 1, 5, 3, 3, 1, 2, 384, 240, 186,,,,, -7, 7, 1, 5, 3, 3, 1, 3, 128, 240, 186,,,,, -7, 7, 1, 5, 3, 3, 1, 3, 256, 240, 186,,,,, -7, 7, 1, 5, 3, 3, 1, 3, 384, 240, 186,,,,, -7, 7, 1, 5, 3, 3, 2, 1, 128, 240, 186,,,,, -7, 7, 1, 5, 3, 3, 2, 1, 256, 240, 186,,,,, -7, 7, 1, 5, 3, 3, 2, 1, 384, 240, 186,,,,, -7, 7, 1, 5, 3, 3, 2, 2, 128, 240, 186,,,,, -7, 7, 1, 5, 3, 3, 2, 2, 256, 240, 186,,,,, -7, 7, 1, 5, 3, 3, 2, 2, 384, 240, 186,,,,, -7, 7, 1, 5, 3, 3, 2, 3, 128, 240, 186,,,,, -7, 7, 1, 5, 3, 3, 2, 3, 256, 240, 186,,,,, -7, 7, 1, 5, 3, 3, 2, 3, 384, 240, 186,,,,, -7, 7, 1, 5, 3, 3, 3, 1, 128, 240, 186,,,,, -7, 7, 1, 5, 3, 3, 3, 1, 256, 240, 186,,,,, -7, 7, 1, 5, 3, 3, 3, 1, 384, 240, 186,,,,, -7, 7, 1, 5, 3, 3, 3, 2, 128, 240, 186,,,,, -7, 7, 1, 5, 3, 3, 3, 2, 256, 240, 186,,,,, -7, 7, 1, 5, 3, 3, 3, 2, 384, 240, 186,,,,, -7, 7, 1, 5, 3, 3, 3, 3, 128, 240, 186,,,,, -7, 7, 1, 5, 3, 3, 3, 3, 256, 240, 186,,,,, -7, 7, 1, 5, 3, 3, 3, 3, 384, 240, 186,,,,, -7, 7, 1, 6, 1, 1, 1, 1, 128, 240, 222,,,,, -7, 7, 1, 6, 1, 1, 1, 1, 256, 240, 222,,,,, -7, 7, 1, 6, 1, 1, 1, 1, 384, 240, 222,,,,, -7, 7, 1, 6, 2, 2, 1, 1, 128, 240, 222,,,,, -7, 7, 1, 6, 2, 2, 1, 1, 256, 240, 222,,,,, -7, 7, 1, 6, 2, 2, 1, 1, 384, 240, 222,,,,, -7, 7, 1, 6, 2, 2, 1, 2, 128, 240, 222,,,,, -7, 7, 1, 6, 2, 2, 1, 2, 256, 240, 222,,,,, -7, 7, 1, 6, 2, 2, 1, 2, 384, 240, 222,,,,, -7, 7, 1, 6, 2, 2, 2, 1, 128, 240, 222,,,,, -7, 7, 1, 6, 2, 2, 2, 1, 256, 240, 222,,,,, -7, 7, 1, 6, 2, 2, 2, 1, 384, 240, 222,,,,, -7, 7, 1, 6, 2, 2, 2, 2, 128, 240, 222,,,,, -7, 7, 1, 6, 2, 2, 2, 2, 256, 240, 222,,,,, -7, 7, 1, 6, 2, 2, 2, 2, 384, 240, 222,,,,, -7, 7, 1, 6, 3, 3, 1, 1, 128, 240, 222,,,,, -7, 7, 1, 6, 3, 3, 1, 1, 256, 240, 222,,,,, -7, 7, 1, 6, 3, 3, 1, 1, 384, 240, 222,,,,, -7, 7, 1, 6, 3, 3, 1, 2, 128, 240, 222,,,,, -7, 7, 1, 6, 3, 3, 1, 2, 256, 240, 222,,,,, -7, 7, 1, 6, 3, 3, 1, 2, 384, 240, 222,,,,, -7, 7, 1, 6, 3, 3, 1, 3, 128, 240, 222,,,,, -7, 7, 1, 6, 3, 3, 1, 3, 256, 240, 222,,,,, -7, 7, 1, 6, 3, 3, 1, 3, 384, 240, 222,,,,, -7, 7, 1, 6, 3, 3, 2, 1, 128, 240, 222,,,,, -7, 7, 1, 6, 3, 3, 2, 1, 256, 240, 222,,,,, -7, 7, 1, 6, 3, 3, 2, 1, 384, 240, 222,,,,, -7, 7, 1, 6, 3, 3, 2, 2, 128, 240, 222,,,,, -7, 7, 1, 6, 3, 3, 2, 2, 256, 240, 222,,,,, -7, 7, 1, 6, 3, 3, 2, 2, 384, 240, 222,,,,, -7, 7, 1, 6, 3, 3, 2, 3, 128, 240, 222,,,,, -7, 7, 1, 6, 3, 3, 2, 3, 256, 240, 222,,,,, -7, 7, 1, 6, 3, 3, 2, 3, 384, 240, 222,,,,, -7, 7, 1, 6, 3, 3, 3, 1, 128, 240, 222,,,,, -7, 7, 1, 6, 3, 3, 3, 1, 256, 240, 222,,,,, -7, 7, 1, 6, 3, 3, 3, 1, 384, 240, 222,,,,, -7, 7, 1, 6, 3, 3, 3, 2, 128, 240, 222,,,,, -7, 7, 1, 6, 3, 3, 3, 2, 256, 240, 222,,,,, -7, 7, 1, 6, 3, 3, 3, 2, 384, 240, 222,,,,, -7, 7, 1, 6, 3, 3, 3, 3, 128, 240, 222,,,,, -7, 7, 1, 6, 3, 3, 3, 3, 256, 240, 222,,,,, -7, 7, 1, 6, 3, 3, 3, 3, 384, 240, 222,,,,, -7, 7, 1, 7, 1, 1, 1, 1, 128, 240, 240,,,,, -7, 7, 1, 7, 1, 1, 1, 1, 256, 240, 240,,,,, -7, 7, 1, 7, 1, 1, 1, 1, 384, 240, 240,,,,, -7, 7, 1, 7, 2, 2, 1, 1, 128, 240, 240,,,,, -7, 7, 1, 7, 2, 2, 1, 1, 256, 240, 240,,,,, -7, 7, 1, 7, 2, 2, 1, 1, 384, 240, 240,,,,, -7, 7, 1, 7, 2, 2, 1, 2, 128, 240, 240,,,,, -7, 7, 1, 7, 2, 2, 1, 2, 256, 240, 240,,,,, -7, 7, 1, 7, 2, 2, 1, 2, 384, 240, 240,,,,, -7, 7, 1, 7, 2, 2, 2, 1, 128, 240, 240,,,,, -7, 7, 1, 7, 2, 2, 2, 1, 256, 240, 240,,,,, -7, 7, 1, 7, 2, 2, 2, 1, 384, 240, 240,,,,, -7, 7, 1, 7, 2, 2, 2, 2, 128, 240, 240,,,,, -7, 7, 1, 7, 2, 2, 2, 2, 256, 240, 240,,,,, -7, 7, 1, 7, 2, 2, 2, 2, 384, 240, 240,,,,, -7, 7, 1, 7, 3, 3, 1, 1, 128, 240, 240,,,,, -7, 7, 1, 7, 3, 3, 1, 1, 256, 240, 240,,,,, -7, 7, 1, 7, 3, 3, 1, 1, 384, 240, 240,,,,, -7, 7, 1, 7, 3, 3, 1, 2, 128, 240, 240,,,,, -7, 7, 1, 7, 3, 3, 1, 2, 256, 240, 240,,,,, -7, 7, 1, 7, 3, 3, 1, 2, 384, 240, 240,,,,, -7, 7, 1, 7, 3, 3, 1, 3, 128, 240, 240,,,,, -7, 7, 1, 7, 3, 3, 1, 3, 256, 240, 240,,,,, -7, 7, 1, 7, 3, 3, 1, 3, 384, 240, 240,,,,, -7, 7, 1, 7, 3, 3, 2, 1, 128, 240, 240,,,,, -7, 7, 1, 7, 3, 3, 2, 1, 256, 240, 240,,,,, -7, 7, 1, 7, 3, 3, 2, 1, 384, 240, 240,,,,, -7, 7, 1, 7, 3, 3, 2, 2, 128, 240, 240,,,,, -7, 7, 1, 7, 3, 3, 2, 2, 256, 240, 240,,,,, -7, 7, 1, 7, 3, 3, 2, 2, 384, 240, 240,,,,, -7, 7, 1, 7, 3, 3, 2, 3, 128, 240, 240,,,,, -7, 7, 1, 7, 3, 3, 2, 3, 256, 240, 240,,,,, -7, 7, 1, 7, 3, 3, 2, 3, 384, 240, 240,,,,, -7, 7, 1, 7, 3, 3, 3, 1, 128, 240, 240,,,,, -7, 7, 1, 7, 3, 3, 3, 1, 256, 240, 240,,,,, -7, 7, 1, 7, 3, 3, 3, 1, 384, 240, 240,,,,, -7, 7, 1, 7, 3, 3, 3, 2, 128, 240, 240,,,,, -7, 7, 1, 7, 3, 3, 3, 2, 256, 240, 240,,,,, -7, 7, 1, 7, 3, 3, 3, 2, 384, 240, 240,,,,, -7, 7, 1, 7, 3, 3, 3, 3, 128, 240, 240,,,,, -7, 7, 1, 7, 3, 3, 3, 3, 256, 240, 240,,,,, -7, 7, 1, 7, 3, 3, 3, 3, 384, 240, 240,,,,, -7, 7, 2, 1, 1, 1, 1, 1, 128, 60, 42,,,,, -7, 7, 2, 1, 1, 1, 1, 1, 256, 60, 42,,,,, -7, 7, 2, 1, 1, 1, 1, 1, 384, 60, 42,,,,, -7, 7, 2, 1, 2, 2, 1, 1, 128, 60, 42,,,,, -7, 7, 2, 1, 2, 2, 1, 1, 256, 60, 42,,,,, -7, 7, 2, 1, 2, 2, 1, 1, 384, 60, 42,,,,, -7, 7, 2, 1, 2, 2, 1, 2, 128, 60, 42,,,,, -7, 7, 2, 1, 2, 2, 1, 2, 256, 60, 42,,,,, -7, 7, 2, 1, 2, 2, 1, 2, 384, 60, 42,,,,, -7, 7, 2, 1, 2, 2, 2, 1, 128, 60, 42,,,,, -7, 7, 2, 1, 2, 2, 2, 1, 256, 60, 42,,,,, -7, 7, 2, 1, 2, 2, 2, 1, 384, 60, 42,,,,, -7, 7, 2, 1, 2, 2, 2, 2, 128, 60, 42,,,,, -7, 7, 2, 1, 2, 2, 2, 2, 256, 60, 42,,,,, -7, 7, 2, 1, 2, 2, 2, 2, 384, 60, 42,,,,, -7, 7, 2, 1, 3, 3, 1, 1, 128, 59, 42,,,,, -7, 7, 2, 1, 3, 3, 1, 1, 256, 59, 42,,,,, -7, 7, 2, 1, 3, 3, 1, 1, 384, 59, 42,,,,, -7, 7, 2, 1, 3, 3, 1, 2, 128, 59, 42,,,,, -7, 7, 2, 1, 3, 3, 1, 2, 256, 59, 42,,,,, -7, 7, 2, 1, 3, 3, 1, 2, 384, 59, 42,,,,, -7, 7, 2, 1, 3, 3, 1, 3, 128, 59, 42,,,,, -7, 7, 2, 1, 3, 3, 1, 3, 256, 59, 42,,,,, -7, 7, 2, 1, 3, 3, 1, 3, 384, 59, 42,,,,, -7, 7, 2, 1, 3, 3, 2, 1, 128, 59, 42,,,,, -7, 7, 2, 1, 3, 3, 2, 1, 256, 59, 42,,,,, -7, 7, 2, 1, 3, 3, 2, 1, 384, 59, 42,,,,, -7, 7, 2, 1, 3, 3, 2, 2, 128, 59, 42,,,,, -7, 7, 2, 1, 3, 3, 2, 2, 256, 59, 42,,,,, -7, 7, 2, 1, 3, 3, 2, 2, 384, 59, 42,,,,, -7, 7, 2, 1, 3, 3, 2, 3, 128, 59, 42,,,,, -7, 7, 2, 1, 3, 3, 2, 3, 256, 59, 42,,,,, -7, 7, 2, 1, 3, 3, 2, 3, 384, 59, 42,,,,, -7, 7, 2, 1, 3, 3, 3, 1, 128, 59, 42,,,,, -7, 7, 2, 1, 3, 3, 3, 1, 256, 59, 42,,,,, -7, 7, 2, 1, 3, 3, 3, 1, 384, 59, 42,,,,, -7, 7, 2, 1, 3, 3, 3, 2, 128, 59, 42,,,,, -7, 7, 2, 1, 3, 3, 3, 2, 256, 59, 42,,,,, -7, 7, 2, 1, 3, 3, 3, 2, 384, 59, 42,,,,, -7, 7, 2, 1, 3, 3, 3, 3, 128, 59, 42,,,,, -7, 7, 2, 1, 3, 3, 3, 3, 256, 59, 42,,,,, -7, 7, 2, 1, 3, 3, 3, 3, 384, 59, 42,,,,, -7, 7, 2, 2, 1, 1, 1, 1, 128, 114, 78,,,,, -7, 7, 2, 2, 1, 1, 1, 1, 256, 114, 78,,,,, -7, 7, 2, 2, 1, 1, 1, 1, 384, 114, 78,,,,, -7, 7, 2, 2, 2, 2, 1, 1, 128, 114, 78,,,,, -7, 7, 2, 2, 2, 2, 1, 1, 256, 114, 78,,,,, -7, 7, 2, 2, 2, 2, 1, 1, 384, 114, 78,,,,, -7, 7, 2, 2, 2, 2, 1, 2, 128, 114, 78,,,,, -7, 7, 2, 2, 2, 2, 1, 2, 256, 114, 78,,,,, -7, 7, 2, 2, 2, 2, 1, 2, 384, 114, 78,,,,, -7, 7, 2, 2, 2, 2, 2, 1, 128, 114, 78,,,,, -7, 7, 2, 2, 2, 2, 2, 1, 256, 114, 78,,,,, -7, 7, 2, 2, 2, 2, 2, 1, 384, 114, 78,,,,, -7, 7, 2, 2, 2, 2, 2, 2, 128, 114, 78,,,,, -7, 7, 2, 2, 2, 2, 2, 2, 256, 114, 78,,,,, -7, 7, 2, 2, 2, 2, 2, 2, 384, 114, 78,,,,, -7, 7, 2, 2, 3, 3, 1, 1, 128, 112, 78,,,,, -7, 7, 2, 2, 3, 3, 1, 1, 256, 112, 78,,,,, -7, 7, 2, 2, 3, 3, 1, 1, 384, 112, 78,,,,, -7, 7, 2, 2, 3, 3, 1, 2, 128, 112, 78,,,,, -7, 7, 2, 2, 3, 3, 1, 2, 256, 112, 78,,,,, -7, 7, 2, 2, 3, 3, 1, 2, 384, 112, 78,,,,, -7, 7, 2, 2, 3, 3, 1, 3, 128, 112, 78,,,,, -7, 7, 2, 2, 3, 3, 1, 3, 256, 112, 78,,,,, -7, 7, 2, 2, 3, 3, 1, 3, 384, 112, 78,,,,, -7, 7, 2, 2, 3, 3, 2, 1, 128, 112, 78,,,,, -7, 7, 2, 2, 3, 3, 2, 1, 256, 112, 78,,,,, -7, 7, 2, 2, 3, 3, 2, 1, 384, 112, 78,,,,, -7, 7, 2, 2, 3, 3, 2, 2, 128, 112, 78,,,,, -7, 7, 2, 2, 3, 3, 2, 2, 256, 112, 78,,,,, -7, 7, 2, 2, 3, 3, 2, 2, 384, 112, 78,,,,, -7, 7, 2, 2, 3, 3, 2, 3, 128, 112, 78,,,,, -7, 7, 2, 2, 3, 3, 2, 3, 256, 112, 78,,,,, -7, 7, 2, 2, 3, 3, 2, 3, 384, 112, 78,,,,, -7, 7, 2, 2, 3, 3, 3, 1, 128, 112, 78,,,,, -7, 7, 2, 2, 3, 3, 3, 1, 256, 112, 78,,,,, -7, 7, 2, 2, 3, 3, 3, 1, 384, 112, 78,,,,, -7, 7, 2, 2, 3, 3, 3, 2, 128, 112, 78,,,,, -7, 7, 2, 2, 3, 3, 3, 2, 256, 112, 78,,,,, -7, 7, 2, 2, 3, 3, 3, 2, 384, 112, 78,,,,, -7, 7, 2, 2, 3, 3, 3, 3, 128, 112, 78,,,,, -7, 7, 2, 2, 3, 3, 3, 3, 256, 112, 78,,,,, -7, 7, 2, 2, 3, 3, 3, 3, 384, 112, 78,,,,, -7, 7, 2, 3, 1, 1, 1, 1, 128, 168, 114,,,,, -7, 7, 2, 3, 1, 1, 1, 1, 256, 168, 114,,,,, -7, 7, 2, 3, 1, 1, 1, 1, 384, 168, 114,,,,, -7, 7, 2, 3, 2, 2, 1, 1, 128, 168, 114,,,,, -7, 7, 2, 3, 2, 2, 1, 1, 256, 168, 114,,,,, -7, 7, 2, 3, 2, 2, 1, 1, 384, 168, 114,,,,, -7, 7, 2, 3, 2, 2, 1, 2, 128, 168, 114,,,,, -7, 7, 2, 3, 2, 2, 1, 2, 256, 168, 114,,,,, -7, 7, 2, 3, 2, 2, 1, 2, 384, 168, 114,,,,, -7, 7, 2, 3, 2, 2, 2, 1, 128, 168, 114,,,,, -7, 7, 2, 3, 2, 2, 2, 1, 256, 168, 114,,,,, -7, 7, 2, 3, 2, 2, 2, 1, 384, 168, 114,,,,, -7, 7, 2, 3, 2, 2, 2, 2, 128, 168, 114,,,,, -7, 7, 2, 3, 2, 2, 2, 2, 256, 168, 114,,,,, -7, 7, 2, 3, 2, 2, 2, 2, 384, 168, 114,,,,, -7, 7, 2, 3, 3, 3, 1, 1, 128, 165, 114,,,,, -7, 7, 2, 3, 3, 3, 1, 1, 256, 165, 114,,,,, -7, 7, 2, 3, 3, 3, 1, 1, 384, 165, 114,,,,, -7, 7, 2, 3, 3, 3, 1, 2, 128, 165, 114,,,,, -7, 7, 2, 3, 3, 3, 1, 2, 256, 165, 114,,,,, -7, 7, 2, 3, 3, 3, 1, 2, 384, 165, 114,,,,, -7, 7, 2, 3, 3, 3, 1, 3, 128, 165, 114,,,,, -7, 7, 2, 3, 3, 3, 1, 3, 256, 165, 114,,,,, -7, 7, 2, 3, 3, 3, 1, 3, 384, 165, 114,,,,, -7, 7, 2, 3, 3, 3, 2, 1, 128, 165, 114,,,,, -7, 7, 2, 3, 3, 3, 2, 1, 256, 165, 114,,,,, -7, 7, 2, 3, 3, 3, 2, 1, 384, 165, 114,,,,, -7, 7, 2, 3, 3, 3, 2, 2, 128, 165, 114,,,,, -7, 7, 2, 3, 3, 3, 2, 2, 256, 165, 114,,,,, -7, 7, 2, 3, 3, 3, 2, 2, 384, 165, 114,,,,, -7, 7, 2, 3, 3, 3, 2, 3, 128, 165, 114,,,,, -7, 7, 2, 3, 3, 3, 2, 3, 256, 165, 114,,,,, -7, 7, 2, 3, 3, 3, 2, 3, 384, 165, 114,,,,, -7, 7, 2, 3, 3, 3, 3, 1, 128, 165, 114,,,,, -7, 7, 2, 3, 3, 3, 3, 1, 256, 165, 114,,,,, -7, 7, 2, 3, 3, 3, 3, 1, 384, 165, 114,,,,, -7, 7, 2, 3, 3, 3, 3, 2, 128, 165, 114,,,,, -7, 7, 2, 3, 3, 3, 3, 2, 256, 165, 114,,,,, -7, 7, 2, 3, 3, 3, 3, 2, 384, 165, 114,,,,, -7, 7, 2, 3, 3, 3, 3, 3, 128, 165, 114,,,,, -7, 7, 2, 3, 3, 3, 3, 3, 256, 165, 114,,,,, -7, 7, 2, 3, 3, 3, 3, 3, 384, 165, 114,,,,, -7, 7, 2, 4, 1, 1, 1, 1, 128, 222, 150,,,,, -7, 7, 2, 4, 1, 1, 1, 1, 256, 222, 150,,,,, -7, 7, 2, 4, 1, 1, 1, 1, 384, 222, 150,,,,, -7, 7, 2, 4, 2, 2, 1, 1, 128, 222, 150,,,,, -7, 7, 2, 4, 2, 2, 1, 1, 256, 222, 150,,,,, -7, 7, 2, 4, 2, 2, 1, 1, 384, 222, 150,,,,, -7, 7, 2, 4, 2, 2, 1, 2, 128, 222, 150,,,,, -7, 7, 2, 4, 2, 2, 1, 2, 256, 222, 150,,,,, -7, 7, 2, 4, 2, 2, 1, 2, 384, 222, 150,,,,, -7, 7, 2, 4, 2, 2, 2, 1, 128, 222, 150,,,,, -7, 7, 2, 4, 2, 2, 2, 1, 256, 222, 150,,,,, -7, 7, 2, 4, 2, 2, 2, 1, 384, 222, 150,,,,, -7, 7, 2, 4, 2, 2, 2, 2, 128, 222, 150,,,,, -7, 7, 2, 4, 2, 2, 2, 2, 256, 222, 150,,,,, -7, 7, 2, 4, 2, 2, 2, 2, 384, 222, 150,,,,, -7, 7, 2, 4, 3, 3, 1, 1, 128, 218, 150,,,,, -7, 7, 2, 4, 3, 3, 1, 1, 256, 218, 150,,,,, -7, 7, 2, 4, 3, 3, 1, 1, 384, 218, 150,,,,, -7, 7, 2, 4, 3, 3, 1, 2, 128, 218, 150,,,,, -7, 7, 2, 4, 3, 3, 1, 2, 256, 218, 150,,,,, -7, 7, 2, 4, 3, 3, 1, 2, 384, 218, 150,,,,, -7, 7, 2, 4, 3, 3, 1, 3, 128, 218, 150,,,,, -7, 7, 2, 4, 3, 3, 1, 3, 256, 218, 150,,,,, -7, 7, 2, 4, 3, 3, 1, 3, 384, 218, 150,,,,, -7, 7, 2, 4, 3, 3, 2, 1, 128, 218, 150,,,,, -7, 7, 2, 4, 3, 3, 2, 1, 256, 218, 150,,,,, -7, 7, 2, 4, 3, 3, 2, 1, 384, 218, 150,,,,, -7, 7, 2, 4, 3, 3, 2, 2, 128, 218, 150,,,,, -7, 7, 2, 4, 3, 3, 2, 2, 256, 218, 150,,,,, -7, 7, 2, 4, 3, 3, 2, 2, 384, 218, 150,,,,, -7, 7, 2, 4, 3, 3, 2, 3, 128, 218, 150,,,,, -7, 7, 2, 4, 3, 3, 2, 3, 256, 218, 150,,,,, -7, 7, 2, 4, 3, 3, 2, 3, 384, 218, 150,,,,, -7, 7, 2, 4, 3, 3, 3, 1, 128, 218, 150,,,,, -7, 7, 2, 4, 3, 3, 3, 1, 256, 218, 150,,,,, -7, 7, 2, 4, 3, 3, 3, 1, 384, 218, 150,,,,, -7, 7, 2, 4, 3, 3, 3, 2, 128, 218, 150,,,,, -7, 7, 2, 4, 3, 3, 3, 2, 256, 218, 150,,,,, -7, 7, 2, 4, 3, 3, 3, 2, 384, 218, 150,,,,, -7, 7, 2, 4, 3, 3, 3, 3, 128, 218, 150,,,,, -7, 7, 2, 4, 3, 3, 3, 3, 256, 218, 150,,,,, -7, 7, 2, 4, 3, 3, 3, 3, 384, 218, 150,,,,, -7, 7, 2, 5, 1, 1, 1, 1, 128, 240, 186,,,,, -7, 7, 2, 5, 1, 1, 1, 1, 256, 240, 186,,,,, -7, 7, 2, 5, 1, 1, 1, 1, 384, 240, 186,,,,, -7, 7, 2, 5, 2, 2, 1, 1, 128, 240, 186,,,,, -7, 7, 2, 5, 2, 2, 1, 1, 256, 240, 186,,,,, -7, 7, 2, 5, 2, 2, 1, 1, 384, 240, 186,,,,, -7, 7, 2, 5, 2, 2, 1, 2, 128, 240, 186,,,,, -7, 7, 2, 5, 2, 2, 1, 2, 256, 240, 186,,,,, -7, 7, 2, 5, 2, 2, 1, 2, 384, 240, 186,,,,, -7, 7, 2, 5, 2, 2, 2, 1, 128, 240, 186,,,,, -7, 7, 2, 5, 2, 2, 2, 1, 256, 240, 186,,,,, -7, 7, 2, 5, 2, 2, 2, 1, 384, 240, 186,,,,, -7, 7, 2, 5, 2, 2, 2, 2, 128, 240, 186,,,,, -7, 7, 2, 5, 2, 2, 2, 2, 256, 240, 186,,,,, -7, 7, 2, 5, 2, 2, 2, 2, 384, 240, 186,,,,, -7, 7, 2, 5, 3, 3, 1, 1, 128, 240, 186,,,,, -7, 7, 2, 5, 3, 3, 1, 1, 256, 240, 186,,,,, -7, 7, 2, 5, 3, 3, 1, 1, 384, 240, 186,,,,, -7, 7, 2, 5, 3, 3, 1, 2, 128, 240, 186,,,,, -7, 7, 2, 5, 3, 3, 1, 2, 256, 240, 186,,,,, -7, 7, 2, 5, 3, 3, 1, 2, 384, 240, 186,,,,, -7, 7, 2, 5, 3, 3, 1, 3, 128, 240, 186,,,,, -7, 7, 2, 5, 3, 3, 1, 3, 256, 240, 186,,,,, -7, 7, 2, 5, 3, 3, 1, 3, 384, 240, 186,,,,, -7, 7, 2, 5, 3, 3, 2, 1, 128, 240, 186,,,,, -7, 7, 2, 5, 3, 3, 2, 1, 256, 240, 186,,,,, -7, 7, 2, 5, 3, 3, 2, 1, 384, 240, 186,,,,, -7, 7, 2, 5, 3, 3, 2, 2, 128, 240, 186,,,,, -7, 7, 2, 5, 3, 3, 2, 2, 256, 240, 186,,,,, -7, 7, 2, 5, 3, 3, 2, 2, 384, 240, 186,,,,, -7, 7, 2, 5, 3, 3, 2, 3, 128, 240, 186,,,,, -7, 7, 2, 5, 3, 3, 2, 3, 256, 240, 186,,,,, -7, 7, 2, 5, 3, 3, 2, 3, 384, 240, 186,,,,, -7, 7, 2, 5, 3, 3, 3, 1, 128, 240, 186,,,,, -7, 7, 2, 5, 3, 3, 3, 1, 256, 240, 186,,,,, -7, 7, 2, 5, 3, 3, 3, 1, 384, 240, 186,,,,, -7, 7, 2, 5, 3, 3, 3, 2, 128, 240, 186,,,,, -7, 7, 2, 5, 3, 3, 3, 2, 256, 240, 186,,,,, -7, 7, 2, 5, 3, 3, 3, 2, 384, 240, 186,,,,, -7, 7, 2, 5, 3, 3, 3, 3, 128, 240, 186,,,,, -7, 7, 2, 5, 3, 3, 3, 3, 256, 240, 186,,,,, -7, 7, 2, 5, 3, 3, 3, 3, 384, 240, 186,,,,, -7, 7, 2, 6, 1, 1, 1, 1, 128, 240, 222,,,,, -7, 7, 2, 6, 1, 1, 1, 1, 256, 240, 222,,,,, -7, 7, 2, 6, 1, 1, 1, 1, 384, 240, 222,,,,, -7, 7, 2, 6, 2, 2, 1, 1, 128, 240, 222,,,,, -7, 7, 2, 6, 2, 2, 1, 1, 256, 240, 222,,,,, -7, 7, 2, 6, 2, 2, 1, 1, 384, 240, 222,,,,, -7, 7, 2, 6, 2, 2, 1, 2, 128, 240, 222,,,,, -7, 7, 2, 6, 2, 2, 1, 2, 256, 240, 222,,,,, -7, 7, 2, 6, 2, 2, 1, 2, 384, 240, 222,,,,, -7, 7, 2, 6, 2, 2, 2, 1, 128, 240, 222,,,,, -7, 7, 2, 6, 2, 2, 2, 1, 256, 240, 222,,,,, -7, 7, 2, 6, 2, 2, 2, 1, 384, 240, 222,,,,, -7, 7, 2, 6, 2, 2, 2, 2, 128, 240, 222,,,,, -7, 7, 2, 6, 2, 2, 2, 2, 256, 240, 222,,,,, -7, 7, 2, 6, 2, 2, 2, 2, 384, 240, 222,,,,, -7, 7, 2, 6, 3, 3, 1, 1, 128, 240, 222,,,,, -7, 7, 2, 6, 3, 3, 1, 1, 256, 240, 222,,,,, -7, 7, 2, 6, 3, 3, 1, 1, 384, 240, 222,,,,, -7, 7, 2, 6, 3, 3, 1, 2, 128, 240, 222,,,,, -7, 7, 2, 6, 3, 3, 1, 2, 256, 240, 222,,,,, -7, 7, 2, 6, 3, 3, 1, 2, 384, 240, 222,,,,, -7, 7, 2, 6, 3, 3, 1, 3, 128, 240, 222,,,,, -7, 7, 2, 6, 3, 3, 1, 3, 256, 240, 222,,,,, -7, 7, 2, 6, 3, 3, 1, 3, 384, 240, 222,,,,, -7, 7, 2, 6, 3, 3, 2, 1, 128, 240, 222,,,,, -7, 7, 2, 6, 3, 3, 2, 1, 256, 240, 222,,,,, -7, 7, 2, 6, 3, 3, 2, 1, 384, 240, 222,,,,, -7, 7, 2, 6, 3, 3, 2, 2, 128, 240, 222,,,,, -7, 7, 2, 6, 3, 3, 2, 2, 256, 240, 222,,,,, -7, 7, 2, 6, 3, 3, 2, 2, 384, 240, 222,,,,, -7, 7, 2, 6, 3, 3, 2, 3, 128, 240, 222,,,,, -7, 7, 2, 6, 3, 3, 2, 3, 256, 240, 222,,,,, -7, 7, 2, 6, 3, 3, 2, 3, 384, 240, 222,,,,, -7, 7, 2, 6, 3, 3, 3, 1, 128, 240, 222,,,,, -7, 7, 2, 6, 3, 3, 3, 1, 256, 240, 222,,,,, -7, 7, 2, 6, 3, 3, 3, 1, 384, 240, 222,,,,, -7, 7, 2, 6, 3, 3, 3, 2, 128, 240, 222,,,,, -7, 7, 2, 6, 3, 3, 3, 2, 256, 240, 222,,,,, -7, 7, 2, 6, 3, 3, 3, 2, 384, 240, 222,,,,, -7, 7, 2, 6, 3, 3, 3, 3, 128, 240, 222,,,,, -7, 7, 2, 6, 3, 3, 3, 3, 256, 240, 222,,,,, -7, 7, 2, 6, 3, 3, 3, 3, 384, 240, 222,,,,, -7, 7, 2, 7, 1, 1, 1, 1, 128, 240, 240,,,,, -7, 7, 2, 7, 1, 1, 1, 1, 256, 240, 240,,,,, -7, 7, 2, 7, 1, 1, 1, 1, 384, 240, 240,,,,, -7, 7, 2, 7, 2, 2, 1, 1, 128, 240, 240,,,,, -7, 7, 2, 7, 2, 2, 1, 1, 256, 240, 240,,,,, -7, 7, 2, 7, 2, 2, 1, 1, 384, 240, 240,,,,, -7, 7, 2, 7, 2, 2, 1, 2, 128, 240, 240,,,,, -7, 7, 2, 7, 2, 2, 1, 2, 256, 240, 240,,,,, -7, 7, 2, 7, 2, 2, 1, 2, 384, 240, 240,,,,, -7, 7, 2, 7, 2, 2, 2, 1, 128, 240, 240,,,,, -7, 7, 2, 7, 2, 2, 2, 1, 256, 240, 240,,,,, -7, 7, 2, 7, 2, 2, 2, 1, 384, 240, 240,,,,, -7, 7, 2, 7, 2, 2, 2, 2, 128, 240, 240,,,,, -7, 7, 2, 7, 2, 2, 2, 2, 256, 240, 240,,,,, -7, 7, 2, 7, 2, 2, 2, 2, 384, 240, 240,,,,, -7, 7, 2, 7, 3, 3, 1, 1, 128, 240, 240,,,,, -7, 7, 2, 7, 3, 3, 1, 1, 256, 240, 240,,,,, -7, 7, 2, 7, 3, 3, 1, 1, 384, 240, 240,,,,, -7, 7, 2, 7, 3, 3, 1, 2, 128, 240, 240,,,,, -7, 7, 2, 7, 3, 3, 1, 2, 256, 240, 240,,,,, -7, 7, 2, 7, 3, 3, 1, 2, 384, 240, 240,,,,, -7, 7, 2, 7, 3, 3, 1, 3, 128, 240, 240,,,,, -7, 7, 2, 7, 3, 3, 1, 3, 256, 240, 240,,,,, -7, 7, 2, 7, 3, 3, 1, 3, 384, 240, 240,,,,, -7, 7, 2, 7, 3, 3, 2, 1, 128, 240, 240,,,,, -7, 7, 2, 7, 3, 3, 2, 1, 256, 240, 240,,,,, -7, 7, 2, 7, 3, 3, 2, 1, 384, 240, 240,,,,, -7, 7, 2, 7, 3, 3, 2, 2, 128, 240, 240,,,,, -7, 7, 2, 7, 3, 3, 2, 2, 256, 240, 240,,,,, -7, 7, 2, 7, 3, 3, 2, 2, 384, 240, 240,,,,, -7, 7, 2, 7, 3, 3, 2, 3, 128, 240, 240,,,,, -7, 7, 2, 7, 3, 3, 2, 3, 256, 240, 240,,,,, -7, 7, 2, 7, 3, 3, 2, 3, 384, 240, 240,,,,, -7, 7, 2, 7, 3, 3, 3, 1, 128, 240, 240,,,,, -7, 7, 2, 7, 3, 3, 3, 1, 256, 240, 240,,,,, -7, 7, 2, 7, 3, 3, 3, 1, 384, 240, 240,,,,, -7, 7, 2, 7, 3, 3, 3, 2, 128, 240, 240,,,,, -7, 7, 2, 7, 3, 3, 3, 2, 256, 240, 240,,,,, -7, 7, 2, 7, 3, 3, 3, 2, 384, 240, 240,,,,, -7, 7, 2, 7, 3, 3, 3, 3, 128, 240, 240,,,,, -7, 7, 2, 7, 3, 3, 3, 3, 256, 240, 240,,,,, -7, 7, 2, 7, 3, 3, 3, 3, 384, 240, 240,,,,, -7, 7, 3, 1, 1, 1, 1, 1, 128, 60, 42,,,,, -7, 7, 3, 1, 1, 1, 1, 1, 256, 60, 42,,,,, -7, 7, 3, 1, 1, 1, 1, 1, 384, 60, 42,,,,, -7, 7, 3, 1, 2, 2, 1, 1, 128, 60, 42,,,,, -7, 7, 3, 1, 2, 2, 1, 1, 256, 60, 42,,,,, -7, 7, 3, 1, 2, 2, 1, 1, 384, 60, 42,,,,, -7, 7, 3, 1, 2, 2, 1, 2, 128, 60, 42,,,,, -7, 7, 3, 1, 2, 2, 1, 2, 256, 60, 42,,,,, -7, 7, 3, 1, 2, 2, 1, 2, 384, 60, 42,,,,, -7, 7, 3, 1, 2, 2, 2, 1, 128, 60, 42,,,,, -7, 7, 3, 1, 2, 2, 2, 1, 256, 60, 42,,,,, -7, 7, 3, 1, 2, 2, 2, 1, 384, 60, 42,,,,, -7, 7, 3, 1, 2, 2, 2, 2, 128, 60, 42,,,,, -7, 7, 3, 1, 2, 2, 2, 2, 256, 60, 42,,,,, -7, 7, 3, 1, 2, 2, 2, 2, 384, 60, 42,,,,, -7, 7, 3, 1, 3, 3, 1, 1, 128, 59, 42,,,,, -7, 7, 3, 1, 3, 3, 1, 1, 256, 59, 42,,,,, -7, 7, 3, 1, 3, 3, 1, 1, 384, 59, 42,,,,, -7, 7, 3, 1, 3, 3, 1, 2, 128, 59, 42,,,,, -7, 7, 3, 1, 3, 3, 1, 2, 256, 59, 42,,,,, -7, 7, 3, 1, 3, 3, 1, 2, 384, 59, 42,,,,, -7, 7, 3, 1, 3, 3, 1, 3, 128, 59, 42,,,,, -7, 7, 3, 1, 3, 3, 1, 3, 256, 59, 42,,,,, -7, 7, 3, 1, 3, 3, 1, 3, 384, 59, 42,,,,, -7, 7, 3, 1, 3, 3, 2, 1, 128, 59, 42,,,,, -7, 7, 3, 1, 3, 3, 2, 1, 256, 59, 42,,,,, -7, 7, 3, 1, 3, 3, 2, 1, 384, 59, 42,,,,, -7, 7, 3, 1, 3, 3, 2, 2, 128, 59, 42,,,,, -7, 7, 3, 1, 3, 3, 2, 2, 256, 59, 42,,,,, -7, 7, 3, 1, 3, 3, 2, 2, 384, 59, 42,,,,, -7, 7, 3, 1, 3, 3, 2, 3, 128, 59, 42,,,,, -7, 7, 3, 1, 3, 3, 2, 3, 256, 59, 42,,,,, -7, 7, 3, 1, 3, 3, 2, 3, 384, 59, 42,,,,, -7, 7, 3, 1, 3, 3, 3, 1, 128, 59, 42,,,,, -7, 7, 3, 1, 3, 3, 3, 1, 256, 59, 42,,,,, -7, 7, 3, 1, 3, 3, 3, 1, 384, 59, 42,,,,, -7, 7, 3, 1, 3, 3, 3, 2, 128, 59, 42,,,,, -7, 7, 3, 1, 3, 3, 3, 2, 256, 59, 42,,,,, -7, 7, 3, 1, 3, 3, 3, 2, 384, 59, 42,,,,, -7, 7, 3, 1, 3, 3, 3, 3, 128, 59, 42,,,,, -7, 7, 3, 1, 3, 3, 3, 3, 256, 59, 42,,,,, -7, 7, 3, 1, 3, 3, 3, 3, 384, 59, 42,,,,, -7, 7, 3, 2, 1, 1, 1, 1, 128, 114, 78,,,,, -7, 7, 3, 2, 1, 1, 1, 1, 256, 114, 78,,,,, -7, 7, 3, 2, 1, 1, 1, 1, 384, 114, 78,,,,, -7, 7, 3, 2, 2, 2, 1, 1, 128, 114, 78,,,,, -7, 7, 3, 2, 2, 2, 1, 1, 256, 114, 78,,,,, -7, 7, 3, 2, 2, 2, 1, 1, 384, 114, 78,,,,, -7, 7, 3, 2, 2, 2, 1, 2, 128, 114, 78,,,,, -7, 7, 3, 2, 2, 2, 1, 2, 256, 114, 78,,,,, -7, 7, 3, 2, 2, 2, 1, 2, 384, 114, 78,,,,, -7, 7, 3, 2, 2, 2, 2, 1, 128, 114, 78,,,,, -7, 7, 3, 2, 2, 2, 2, 1, 256, 114, 78,,,,, -7, 7, 3, 2, 2, 2, 2, 1, 384, 114, 78,,,,, -7, 7, 3, 2, 2, 2, 2, 2, 128, 114, 78,,,,, -7, 7, 3, 2, 2, 2, 2, 2, 256, 114, 78,,,,, -7, 7, 3, 2, 2, 2, 2, 2, 384, 114, 78,,,,, -7, 7, 3, 2, 3, 3, 1, 1, 128, 112, 78,,,,, -7, 7, 3, 2, 3, 3, 1, 1, 256, 112, 78,,,,, -7, 7, 3, 2, 3, 3, 1, 1, 384, 112, 78,,,,, -7, 7, 3, 2, 3, 3, 1, 2, 128, 112, 78,,,,, -7, 7, 3, 2, 3, 3, 1, 2, 256, 112, 78,,,,, -7, 7, 3, 2, 3, 3, 1, 2, 384, 112, 78,,,,, -7, 7, 3, 2, 3, 3, 1, 3, 128, 112, 78,,,,, -7, 7, 3, 2, 3, 3, 1, 3, 256, 112, 78,,,,, -7, 7, 3, 2, 3, 3, 1, 3, 384, 112, 78,,,,, -7, 7, 3, 2, 3, 3, 2, 1, 128, 112, 78,,,,, -7, 7, 3, 2, 3, 3, 2, 1, 256, 112, 78,,,,, -7, 7, 3, 2, 3, 3, 2, 1, 384, 112, 78,,,,, -7, 7, 3, 2, 3, 3, 2, 2, 128, 112, 78,,,,, -7, 7, 3, 2, 3, 3, 2, 2, 256, 112, 78,,,,, -7, 7, 3, 2, 3, 3, 2, 2, 384, 112, 78,,,,, -7, 7, 3, 2, 3, 3, 2, 3, 128, 112, 78,,,,, -7, 7, 3, 2, 3, 3, 2, 3, 256, 112, 78,,,,, -7, 7, 3, 2, 3, 3, 2, 3, 384, 112, 78,,,,, -7, 7, 3, 2, 3, 3, 3, 1, 128, 112, 78,,,,, -7, 7, 3, 2, 3, 3, 3, 1, 256, 112, 78,,,,, -7, 7, 3, 2, 3, 3, 3, 1, 384, 112, 78,,,,, -7, 7, 3, 2, 3, 3, 3, 2, 128, 112, 78,,,,, -7, 7, 3, 2, 3, 3, 3, 2, 256, 112, 78,,,,, -7, 7, 3, 2, 3, 3, 3, 2, 384, 112, 78,,,,, -7, 7, 3, 2, 3, 3, 3, 3, 128, 112, 78,,,,, -7, 7, 3, 2, 3, 3, 3, 3, 256, 112, 78,,,,, -7, 7, 3, 2, 3, 3, 3, 3, 384, 112, 78,,,,, -7, 7, 3, 3, 1, 1, 1, 1, 128, 168, 114,,,,, -7, 7, 3, 3, 1, 1, 1, 1, 256, 168, 114,,,,, -7, 7, 3, 3, 1, 1, 1, 1, 384, 168, 114,,,,, -7, 7, 3, 3, 2, 2, 1, 1, 128, 168, 114,,,,, -7, 7, 3, 3, 2, 2, 1, 1, 256, 168, 114,,,,, -7, 7, 3, 3, 2, 2, 1, 1, 384, 168, 114,,,,, -7, 7, 3, 3, 2, 2, 1, 2, 128, 168, 114,,,,, -7, 7, 3, 3, 2, 2, 1, 2, 256, 168, 114,,,,, -7, 7, 3, 3, 2, 2, 1, 2, 384, 168, 114,,,,, -7, 7, 3, 3, 2, 2, 2, 1, 128, 168, 114,,,,, -7, 7, 3, 3, 2, 2, 2, 1, 256, 168, 114,,,,, -7, 7, 3, 3, 2, 2, 2, 1, 384, 168, 114,,,,, -7, 7, 3, 3, 2, 2, 2, 2, 128, 168, 114,,,,, -7, 7, 3, 3, 2, 2, 2, 2, 256, 168, 114,,,,, -7, 7, 3, 3, 2, 2, 2, 2, 384, 168, 114,,,,, -7, 7, 3, 3, 3, 3, 1, 1, 128, 165, 114,,,,, -7, 7, 3, 3, 3, 3, 1, 1, 256, 165, 114,,,,, -7, 7, 3, 3, 3, 3, 1, 1, 384, 165, 114,,,,, -7, 7, 3, 3, 3, 3, 1, 2, 128, 165, 114,,,,, -7, 7, 3, 3, 3, 3, 1, 2, 256, 165, 114,,,,, -7, 7, 3, 3, 3, 3, 1, 2, 384, 165, 114,,,,, -7, 7, 3, 3, 3, 3, 1, 3, 128, 165, 114,,,,, -7, 7, 3, 3, 3, 3, 1, 3, 256, 165, 114,,,,, -7, 7, 3, 3, 3, 3, 1, 3, 384, 165, 114,,,,, -7, 7, 3, 3, 3, 3, 2, 1, 128, 165, 114,,,,, -7, 7, 3, 3, 3, 3, 2, 1, 256, 165, 114,,,,, -7, 7, 3, 3, 3, 3, 2, 1, 384, 165, 114,,,,, -7, 7, 3, 3, 3, 3, 2, 2, 128, 165, 114,,,,, -7, 7, 3, 3, 3, 3, 2, 2, 256, 165, 114,,,,, -7, 7, 3, 3, 3, 3, 2, 2, 384, 165, 114,,,,, -7, 7, 3, 3, 3, 3, 2, 3, 128, 165, 114,,,,, -7, 7, 3, 3, 3, 3, 2, 3, 256, 165, 114,,,,, -7, 7, 3, 3, 3, 3, 2, 3, 384, 165, 114,,,,, -7, 7, 3, 3, 3, 3, 3, 1, 128, 165, 114,,,,, -7, 7, 3, 3, 3, 3, 3, 1, 256, 165, 114,,,,, -7, 7, 3, 3, 3, 3, 3, 1, 384, 165, 114,,,,, -7, 7, 3, 3, 3, 3, 3, 2, 128, 165, 114,,,,, -7, 7, 3, 3, 3, 3, 3, 2, 256, 165, 114,,,,, -7, 7, 3, 3, 3, 3, 3, 2, 384, 165, 114,,,,, -7, 7, 3, 3, 3, 3, 3, 3, 128, 165, 114,,,,, -7, 7, 3, 3, 3, 3, 3, 3, 256, 165, 114,,,,, -7, 7, 3, 3, 3, 3, 3, 3, 384, 165, 114,,,,, -7, 7, 3, 4, 1, 1, 1, 1, 128, 222, 150,,,,, -7, 7, 3, 4, 1, 1, 1, 1, 256, 222, 150,,,,, -7, 7, 3, 4, 1, 1, 1, 1, 384, 222, 150,,,,, -7, 7, 3, 4, 2, 2, 1, 1, 128, 222, 150,,,,, -7, 7, 3, 4, 2, 2, 1, 1, 256, 222, 150,,,,, -7, 7, 3, 4, 2, 2, 1, 1, 384, 222, 150,,,,, -7, 7, 3, 4, 2, 2, 1, 2, 128, 222, 150,,,,, -7, 7, 3, 4, 2, 2, 1, 2, 256, 222, 150,,,,, -7, 7, 3, 4, 2, 2, 1, 2, 384, 222, 150,,,,, -7, 7, 3, 4, 2, 2, 2, 1, 128, 222, 150,,,,, -7, 7, 3, 4, 2, 2, 2, 1, 256, 222, 150,,,,, -7, 7, 3, 4, 2, 2, 2, 1, 384, 222, 150,,,,, -7, 7, 3, 4, 2, 2, 2, 2, 128, 222, 150,,,,, -7, 7, 3, 4, 2, 2, 2, 2, 256, 222, 150,,,,, -7, 7, 3, 4, 2, 2, 2, 2, 384, 222, 150,,,,, -7, 7, 3, 4, 3, 3, 1, 1, 128, 218, 150,,,,, -7, 7, 3, 4, 3, 3, 1, 1, 256, 218, 150,,,,, -7, 7, 3, 4, 3, 3, 1, 1, 384, 218, 150,,,,, -7, 7, 3, 4, 3, 3, 1, 2, 128, 218, 150,,,,, -7, 7, 3, 4, 3, 3, 1, 2, 256, 218, 150,,,,, -7, 7, 3, 4, 3, 3, 1, 2, 384, 218, 150,,,,, -7, 7, 3, 4, 3, 3, 1, 3, 128, 218, 150,,,,, -7, 7, 3, 4, 3, 3, 1, 3, 256, 218, 150,,,,, -7, 7, 3, 4, 3, 3, 1, 3, 384, 218, 150,,,,, -7, 7, 3, 4, 3, 3, 2, 1, 128, 218, 150,,,,, -7, 7, 3, 4, 3, 3, 2, 1, 256, 218, 150,,,,, -7, 7, 3, 4, 3, 3, 2, 1, 384, 218, 150,,,,, -7, 7, 3, 4, 3, 3, 2, 2, 128, 218, 150,,,,, -7, 7, 3, 4, 3, 3, 2, 2, 256, 218, 150,,,,, -7, 7, 3, 4, 3, 3, 2, 2, 384, 218, 150,,,,, -7, 7, 3, 4, 3, 3, 2, 3, 128, 218, 150,,,,, -7, 7, 3, 4, 3, 3, 2, 3, 256, 218, 150,,,,, -7, 7, 3, 4, 3, 3, 2, 3, 384, 218, 150,,,,, -7, 7, 3, 4, 3, 3, 3, 1, 128, 218, 150,,,,, -7, 7, 3, 4, 3, 3, 3, 1, 256, 218, 150,,,,, -7, 7, 3, 4, 3, 3, 3, 1, 384, 218, 150,,,,, -7, 7, 3, 4, 3, 3, 3, 2, 128, 218, 150,,,,, -7, 7, 3, 4, 3, 3, 3, 2, 256, 218, 150,,,,, -7, 7, 3, 4, 3, 3, 3, 2, 384, 218, 150,,,,, -7, 7, 3, 4, 3, 3, 3, 3, 128, 218, 150,,,,, -7, 7, 3, 4, 3, 3, 3, 3, 256, 218, 150,,,,, -7, 7, 3, 4, 3, 3, 3, 3, 384, 218, 150,,,,, -7, 7, 3, 5, 1, 1, 1, 1, 128, 240, 186,,,,, -7, 7, 3, 5, 1, 1, 1, 1, 256, 240, 186,,,,, -7, 7, 3, 5, 1, 1, 1, 1, 384, 240, 186,,,,, -7, 7, 3, 5, 2, 2, 1, 1, 128, 240, 186,,,,, -7, 7, 3, 5, 2, 2, 1, 1, 256, 240, 186,,,,, -7, 7, 3, 5, 2, 2, 1, 1, 384, 240, 186,,,,, -7, 7, 3, 5, 2, 2, 1, 2, 128, 240, 186,,,,, -7, 7, 3, 5, 2, 2, 1, 2, 256, 240, 186,,,,, -7, 7, 3, 5, 2, 2, 1, 2, 384, 240, 186,,,,, -7, 7, 3, 5, 2, 2, 2, 1, 128, 240, 186,,,,, -7, 7, 3, 5, 2, 2, 2, 1, 256, 240, 186,,,,, -7, 7, 3, 5, 2, 2, 2, 1, 384, 240, 186,,,,, -7, 7, 3, 5, 2, 2, 2, 2, 128, 240, 186,,,,, -7, 7, 3, 5, 2, 2, 2, 2, 256, 240, 186,,,,, -7, 7, 3, 5, 2, 2, 2, 2, 384, 240, 186,,,,, -7, 7, 3, 5, 3, 3, 1, 1, 128, 240, 186,,,,, -7, 7, 3, 5, 3, 3, 1, 1, 256, 240, 186,,,,, -7, 7, 3, 5, 3, 3, 1, 1, 384, 240, 186,,,,, -7, 7, 3, 5, 3, 3, 1, 2, 128, 240, 186,,,,, -7, 7, 3, 5, 3, 3, 1, 2, 256, 240, 186,,,,, -7, 7, 3, 5, 3, 3, 1, 2, 384, 240, 186,,,,, -7, 7, 3, 5, 3, 3, 1, 3, 128, 240, 186,,,,, -7, 7, 3, 5, 3, 3, 1, 3, 256, 240, 186,,,,, -7, 7, 3, 5, 3, 3, 1, 3, 384, 240, 186,,,,, -7, 7, 3, 5, 3, 3, 2, 1, 128, 240, 186,,,,, -7, 7, 3, 5, 3, 3, 2, 1, 256, 240, 186,,,,, -7, 7, 3, 5, 3, 3, 2, 1, 384, 240, 186,,,,, -7, 7, 3, 5, 3, 3, 2, 2, 128, 240, 186,,,,, -7, 7, 3, 5, 3, 3, 2, 2, 256, 240, 186,,,,, -7, 7, 3, 5, 3, 3, 2, 2, 384, 240, 186,,,,, -7, 7, 3, 5, 3, 3, 2, 3, 128, 240, 186,,,,, -7, 7, 3, 5, 3, 3, 2, 3, 256, 240, 186,,,,, -7, 7, 3, 5, 3, 3, 2, 3, 384, 240, 186,,,,, -7, 7, 3, 5, 3, 3, 3, 1, 128, 240, 186,,,,, -7, 7, 3, 5, 3, 3, 3, 1, 256, 240, 186,,,,, -7, 7, 3, 5, 3, 3, 3, 1, 384, 240, 186,,,,, -7, 7, 3, 5, 3, 3, 3, 2, 128, 240, 186,,,,, -7, 7, 3, 5, 3, 3, 3, 2, 256, 240, 186,,,,, -7, 7, 3, 5, 3, 3, 3, 2, 384, 240, 186,,,,, -7, 7, 3, 5, 3, 3, 3, 3, 128, 240, 186,,,,, -7, 7, 3, 5, 3, 3, 3, 3, 256, 240, 186,,,,, -7, 7, 3, 5, 3, 3, 3, 3, 384, 240, 186,,,,, -7, 7, 3, 6, 1, 1, 1, 1, 128, 240, 222,,,,, -7, 7, 3, 6, 1, 1, 1, 1, 256, 240, 222,,,,, -7, 7, 3, 6, 1, 1, 1, 1, 384, 240, 222,,,,, -7, 7, 3, 6, 2, 2, 1, 1, 128, 240, 222,,,,, -7, 7, 3, 6, 2, 2, 1, 1, 256, 240, 222,,,,, -7, 7, 3, 6, 2, 2, 1, 1, 384, 240, 222,,,,, -7, 7, 3, 6, 2, 2, 1, 2, 128, 240, 222,,,,, -7, 7, 3, 6, 2, 2, 1, 2, 256, 240, 222,,,,, -7, 7, 3, 6, 2, 2, 1, 2, 384, 240, 222,,,,, -7, 7, 3, 6, 2, 2, 2, 1, 128, 240, 222,,,,, -7, 7, 3, 6, 2, 2, 2, 1, 256, 240, 222,,,,, -7, 7, 3, 6, 2, 2, 2, 1, 384, 240, 222,,,,, -7, 7, 3, 6, 2, 2, 2, 2, 128, 240, 222,,,,, -7, 7, 3, 6, 2, 2, 2, 2, 256, 240, 222,,,,, -7, 7, 3, 6, 2, 2, 2, 2, 384, 240, 222,,,,, -7, 7, 3, 6, 3, 3, 1, 1, 128, 240, 222,,,,, -7, 7, 3, 6, 3, 3, 1, 1, 256, 240, 222,,,,, -7, 7, 3, 6, 3, 3, 1, 1, 384, 240, 222,,,,, -7, 7, 3, 6, 3, 3, 1, 2, 128, 240, 222,,,,, -7, 7, 3, 6, 3, 3, 1, 2, 256, 240, 222,,,,, -7, 7, 3, 6, 3, 3, 1, 2, 384, 240, 222,,,,, -7, 7, 3, 6, 3, 3, 1, 3, 128, 240, 222,,,,, -7, 7, 3, 6, 3, 3, 1, 3, 256, 240, 222,,,,, -7, 7, 3, 6, 3, 3, 1, 3, 384, 240, 222,,,,, -7, 7, 3, 6, 3, 3, 2, 1, 128, 240, 222,,,,, -7, 7, 3, 6, 3, 3, 2, 1, 256, 240, 222,,,,, -7, 7, 3, 6, 3, 3, 2, 1, 384, 240, 222,,,,, -7, 7, 3, 6, 3, 3, 2, 2, 128, 240, 222,,,,, -7, 7, 3, 6, 3, 3, 2, 2, 256, 240, 222,,,,, -7, 7, 3, 6, 3, 3, 2, 2, 384, 240, 222,,,,, -7, 7, 3, 6, 3, 3, 2, 3, 128, 240, 222,,,,, -7, 7, 3, 6, 3, 3, 2, 3, 256, 240, 222,,,,, -7, 7, 3, 6, 3, 3, 2, 3, 384, 240, 222,,,,, -7, 7, 3, 6, 3, 3, 3, 1, 128, 240, 222,,,,, -7, 7, 3, 6, 3, 3, 3, 1, 256, 240, 222,,,,, -7, 7, 3, 6, 3, 3, 3, 1, 384, 240, 222,,,,, -7, 7, 3, 6, 3, 3, 3, 2, 128, 240, 222,,,,, -7, 7, 3, 6, 3, 3, 3, 2, 256, 240, 222,,,,, -7, 7, 3, 6, 3, 3, 3, 2, 384, 240, 222,,,,, -7, 7, 3, 6, 3, 3, 3, 3, 128, 240, 222,,,,, -7, 7, 3, 6, 3, 3, 3, 3, 256, 240, 222,,,,, -7, 7, 3, 6, 3, 3, 3, 3, 384, 240, 222,,,,, -7, 7, 3, 7, 1, 1, 1, 1, 128, 240, 240,,,,, -7, 7, 3, 7, 1, 1, 1, 1, 256, 240, 240,,,,, -7, 7, 3, 7, 1, 1, 1, 1, 384, 240, 240,,,,, -7, 7, 3, 7, 2, 2, 1, 1, 128, 240, 240,,,,, -7, 7, 3, 7, 2, 2, 1, 1, 256, 240, 240,,,,, -7, 7, 3, 7, 2, 2, 1, 1, 384, 240, 240,,,,, -7, 7, 3, 7, 2, 2, 1, 2, 128, 240, 240,,,,, -7, 7, 3, 7, 2, 2, 1, 2, 256, 240, 240,,,,, -7, 7, 3, 7, 2, 2, 1, 2, 384, 240, 240,,,,, -7, 7, 3, 7, 2, 2, 2, 1, 128, 240, 240,,,,, -7, 7, 3, 7, 2, 2, 2, 1, 256, 240, 240,,,,, -7, 7, 3, 7, 2, 2, 2, 1, 384, 240, 240,,,,, -7, 7, 3, 7, 2, 2, 2, 2, 128, 240, 240,,,,, -7, 7, 3, 7, 2, 2, 2, 2, 256, 240, 240,,,,, -7, 7, 3, 7, 2, 2, 2, 2, 384, 240, 240,,,,, -7, 7, 3, 7, 3, 3, 1, 1, 128, 240, 240,,,,, -7, 7, 3, 7, 3, 3, 1, 1, 256, 240, 240,,,,, -7, 7, 3, 7, 3, 3, 1, 1, 384, 240, 240,,,,, -7, 7, 3, 7, 3, 3, 1, 2, 128, 240, 240,,,,, -7, 7, 3, 7, 3, 3, 1, 2, 256, 240, 240,,,,, -7, 7, 3, 7, 3, 3, 1, 2, 384, 240, 240,,,,, -7, 7, 3, 7, 3, 3, 1, 3, 128, 240, 240,,,,, -7, 7, 3, 7, 3, 3, 1, 3, 256, 240, 240,,,,, -7, 7, 3, 7, 3, 3, 1, 3, 384, 240, 240,,,,, -7, 7, 3, 7, 3, 3, 2, 1, 128, 240, 240,,,,, -7, 7, 3, 7, 3, 3, 2, 1, 256, 240, 240,,,,, -7, 7, 3, 7, 3, 3, 2, 1, 384, 240, 240,,,,, -7, 7, 3, 7, 3, 3, 2, 2, 128, 240, 240,,,,, -7, 7, 3, 7, 3, 3, 2, 2, 256, 240, 240,,,,, -7, 7, 3, 7, 3, 3, 2, 2, 384, 240, 240,,,,, -7, 7, 3, 7, 3, 3, 2, 3, 128, 240, 240,,,,, -7, 7, 3, 7, 3, 3, 2, 3, 256, 240, 240,,,,, -7, 7, 3, 7, 3, 3, 2, 3, 384, 240, 240,,,,, -7, 7, 3, 7, 3, 3, 3, 1, 128, 240, 240,,,,, -7, 7, 3, 7, 3, 3, 3, 1, 256, 240, 240,,,,, -7, 7, 3, 7, 3, 3, 3, 1, 384, 240, 240,,,,, -7, 7, 3, 7, 3, 3, 3, 2, 128, 240, 240,,,,, -7, 7, 3, 7, 3, 3, 3, 2, 256, 240, 240,,,,, -7, 7, 3, 7, 3, 3, 3, 2, 384, 240, 240,,,,, -7, 7, 3, 7, 3, 3, 3, 3, 128, 240, 240,,,,, -7, 7, 3, 7, 3, 3, 3, 3, 256, 240, 240,,,,, -7, 7, 3, 7, 3, 3, 3, 3, 384, 240, 240,,,,, -7, 7, 4, 1, 1, 1, 1, 1, 128, 60, 42,,,,, -7, 7, 4, 1, 1, 1, 1, 1, 256, 60, 42,,,,, -7, 7, 4, 1, 1, 1, 1, 1, 384, 60, 42,,,,, -7, 7, 4, 1, 2, 2, 1, 1, 128, 60, 42,,,,, -7, 7, 4, 1, 2, 2, 1, 1, 256, 60, 42,,,,, -7, 7, 4, 1, 2, 2, 1, 1, 384, 60, 42,,,,, -7, 7, 4, 1, 2, 2, 1, 2, 128, 60, 42,,,,, -7, 7, 4, 1, 2, 2, 1, 2, 256, 60, 42,,,,, -7, 7, 4, 1, 2, 2, 1, 2, 384, 60, 42,,,,, -7, 7, 4, 1, 2, 2, 2, 1, 128, 60, 42,,,,, -7, 7, 4, 1, 2, 2, 2, 1, 256, 60, 42,,,,, -7, 7, 4, 1, 2, 2, 2, 1, 384, 60, 42,,,,, -7, 7, 4, 1, 2, 2, 2, 2, 128, 60, 42,,,,, -7, 7, 4, 1, 2, 2, 2, 2, 256, 60, 42,,,,, -7, 7, 4, 1, 2, 2, 2, 2, 384, 60, 42,,,,, -7, 7, 4, 1, 3, 3, 1, 1, 128, 59, 42,,,,, -7, 7, 4, 1, 3, 3, 1, 1, 256, 59, 42,,,,, -7, 7, 4, 1, 3, 3, 1, 1, 384, 59, 42,,,,, -7, 7, 4, 1, 3, 3, 1, 2, 128, 59, 42,,,,, -7, 7, 4, 1, 3, 3, 1, 2, 256, 59, 42,,,,, -7, 7, 4, 1, 3, 3, 1, 2, 384, 59, 42,,,,, -7, 7, 4, 1, 3, 3, 1, 3, 128, 59, 42,,,,, -7, 7, 4, 1, 3, 3, 1, 3, 256, 59, 42,,,,, -7, 7, 4, 1, 3, 3, 1, 3, 384, 59, 42,,,,, -7, 7, 4, 1, 3, 3, 2, 1, 128, 59, 42,,,,, -7, 7, 4, 1, 3, 3, 2, 1, 256, 59, 42,,,,, -7, 7, 4, 1, 3, 3, 2, 1, 384, 59, 42,,,,, -7, 7, 4, 1, 3, 3, 2, 2, 128, 59, 42,,,,, -7, 7, 4, 1, 3, 3, 2, 2, 256, 59, 42,,,,, -7, 7, 4, 1, 3, 3, 2, 2, 384, 59, 42,,,,, -7, 7, 4, 1, 3, 3, 2, 3, 128, 59, 42,,,,, -7, 7, 4, 1, 3, 3, 2, 3, 256, 59, 42,,,,, -7, 7, 4, 1, 3, 3, 2, 3, 384, 59, 42,,,,, -7, 7, 4, 1, 3, 3, 3, 1, 128, 59, 42,,,,, -7, 7, 4, 1, 3, 3, 3, 1, 256, 59, 42,,,,, -7, 7, 4, 1, 3, 3, 3, 1, 384, 59, 42,,,,, -7, 7, 4, 1, 3, 3, 3, 2, 128, 59, 42,,,,, -7, 7, 4, 1, 3, 3, 3, 2, 256, 59, 42,,,,, -7, 7, 4, 1, 3, 3, 3, 2, 384, 59, 42,,,,, -7, 7, 4, 1, 3, 3, 3, 3, 128, 59, 42,,,,, -7, 7, 4, 1, 3, 3, 3, 3, 256, 59, 42,,,,, -7, 7, 4, 1, 3, 3, 3, 3, 384, 59, 42,,,,, -7, 7, 4, 2, 1, 1, 1, 1, 128, 114, 78,,,,, -7, 7, 4, 2, 1, 1, 1, 1, 256, 114, 78,,,,, -7, 7, 4, 2, 1, 1, 1, 1, 384, 114, 78,,,,, -7, 7, 4, 2, 2, 2, 1, 1, 128, 114, 78,,,,, -7, 7, 4, 2, 2, 2, 1, 1, 256, 114, 78,,,,, -7, 7, 4, 2, 2, 2, 1, 1, 384, 114, 78,,,,, -7, 7, 4, 2, 2, 2, 1, 2, 128, 114, 78,,,,, -7, 7, 4, 2, 2, 2, 1, 2, 256, 114, 78,,,,, -7, 7, 4, 2, 2, 2, 1, 2, 384, 114, 78,,,,, -7, 7, 4, 2, 2, 2, 2, 1, 128, 114, 78,,,,, -7, 7, 4, 2, 2, 2, 2, 1, 256, 114, 78,,,,, -7, 7, 4, 2, 2, 2, 2, 1, 384, 114, 78,,,,, -7, 7, 4, 2, 2, 2, 2, 2, 128, 114, 78,,,,, -7, 7, 4, 2, 2, 2, 2, 2, 256, 114, 78,,,,, -7, 7, 4, 2, 2, 2, 2, 2, 384, 114, 78,,,,, -7, 7, 4, 2, 3, 3, 1, 1, 128, 112, 78,,,,, -7, 7, 4, 2, 3, 3, 1, 1, 256, 112, 78,,,,, -7, 7, 4, 2, 3, 3, 1, 1, 384, 112, 78,,,,, -7, 7, 4, 2, 3, 3, 1, 2, 128, 112, 78,,,,, -7, 7, 4, 2, 3, 3, 1, 2, 256, 112, 78,,,,, -7, 7, 4, 2, 3, 3, 1, 2, 384, 112, 78,,,,, -7, 7, 4, 2, 3, 3, 1, 3, 128, 112, 78,,,,, -7, 7, 4, 2, 3, 3, 1, 3, 256, 112, 78,,,,, -7, 7, 4, 2, 3, 3, 1, 3, 384, 112, 78,,,,, -7, 7, 4, 2, 3, 3, 2, 1, 128, 112, 78,,,,, -7, 7, 4, 2, 3, 3, 2, 1, 256, 112, 78,,,,, -7, 7, 4, 2, 3, 3, 2, 1, 384, 112, 78,,,,, -7, 7, 4, 2, 3, 3, 2, 2, 128, 112, 78,,,,, -7, 7, 4, 2, 3, 3, 2, 2, 256, 112, 78,,,,, -7, 7, 4, 2, 3, 3, 2, 2, 384, 112, 78,,,,, -7, 7, 4, 2, 3, 3, 2, 3, 128, 112, 78,,,,, -7, 7, 4, 2, 3, 3, 2, 3, 256, 112, 78,,,,, -7, 7, 4, 2, 3, 3, 2, 3, 384, 112, 78,,,,, -7, 7, 4, 2, 3, 3, 3, 1, 128, 112, 78,,,,, -7, 7, 4, 2, 3, 3, 3, 1, 256, 112, 78,,,,, -7, 7, 4, 2, 3, 3, 3, 1, 384, 112, 78,,,,, -7, 7, 4, 2, 3, 3, 3, 2, 128, 112, 78,,,,, -7, 7, 4, 2, 3, 3, 3, 2, 256, 112, 78,,,,, -7, 7, 4, 2, 3, 3, 3, 2, 384, 112, 78,,,,, -7, 7, 4, 2, 3, 3, 3, 3, 128, 112, 78,,,,, -7, 7, 4, 2, 3, 3, 3, 3, 256, 112, 78,,,,, -7, 7, 4, 2, 3, 3, 3, 3, 384, 112, 78,,,,, -7, 7, 4, 3, 1, 1, 1, 1, 128, 168, 114,,,,, -7, 7, 4, 3, 1, 1, 1, 1, 256, 168, 114,,,,, -7, 7, 4, 3, 1, 1, 1, 1, 384, 168, 114,,,,, -7, 7, 4, 3, 2, 2, 1, 1, 128, 168, 114,,,,, -7, 7, 4, 3, 2, 2, 1, 1, 256, 168, 114,,,,, -7, 7, 4, 3, 2, 2, 1, 1, 384, 168, 114,,,,, -7, 7, 4, 3, 2, 2, 1, 2, 128, 168, 114,,,,, -7, 7, 4, 3, 2, 2, 1, 2, 256, 168, 114,,,,, -7, 7, 4, 3, 2, 2, 1, 2, 384, 168, 114,,,,, -7, 7, 4, 3, 2, 2, 2, 1, 128, 168, 114,,,,, -7, 7, 4, 3, 2, 2, 2, 1, 256, 168, 114,,,,, -7, 7, 4, 3, 2, 2, 2, 1, 384, 168, 114,,,,, -7, 7, 4, 3, 2, 2, 2, 2, 128, 168, 114,,,,, -7, 7, 4, 3, 2, 2, 2, 2, 256, 168, 114,,,,, -7, 7, 4, 3, 2, 2, 2, 2, 384, 168, 114,,,,, -7, 7, 4, 3, 3, 3, 1, 1, 128, 165, 114,,,,, -7, 7, 4, 3, 3, 3, 1, 1, 256, 165, 114,,,,, -7, 7, 4, 3, 3, 3, 1, 1, 384, 165, 114,,,,, -7, 7, 4, 3, 3, 3, 1, 2, 128, 165, 114,,,,, -7, 7, 4, 3, 3, 3, 1, 2, 256, 165, 114,,,,, -7, 7, 4, 3, 3, 3, 1, 2, 384, 165, 114,,,,, -7, 7, 4, 3, 3, 3, 1, 3, 128, 165, 114,,,,, -7, 7, 4, 3, 3, 3, 1, 3, 256, 165, 114,,,,, -7, 7, 4, 3, 3, 3, 1, 3, 384, 165, 114,,,,, -7, 7, 4, 3, 3, 3, 2, 1, 128, 165, 114,,,,, -7, 7, 4, 3, 3, 3, 2, 1, 256, 165, 114,,,,, -7, 7, 4, 3, 3, 3, 2, 1, 384, 165, 114,,,,, -7, 7, 4, 3, 3, 3, 2, 2, 128, 165, 114,,,,, -7, 7, 4, 3, 3, 3, 2, 2, 256, 165, 114,,,,, -7, 7, 4, 3, 3, 3, 2, 2, 384, 165, 114,,,,, -7, 7, 4, 3, 3, 3, 2, 3, 128, 165, 114,,,,, -7, 7, 4, 3, 3, 3, 2, 3, 256, 165, 114,,,,, -7, 7, 4, 3, 3, 3, 2, 3, 384, 165, 114,,,,, -7, 7, 4, 3, 3, 3, 3, 1, 128, 165, 114,,,,, -7, 7, 4, 3, 3, 3, 3, 1, 256, 165, 114,,,,, -7, 7, 4, 3, 3, 3, 3, 1, 384, 165, 114,,,,, -7, 7, 4, 3, 3, 3, 3, 2, 128, 165, 114,,,,, -7, 7, 4, 3, 3, 3, 3, 2, 256, 165, 114,,,,, -7, 7, 4, 3, 3, 3, 3, 2, 384, 165, 114,,,,, -7, 7, 4, 3, 3, 3, 3, 3, 128, 165, 114,,,,, -7, 7, 4, 3, 3, 3, 3, 3, 256, 165, 114,,,,, -7, 7, 4, 3, 3, 3, 3, 3, 384, 165, 114,,,,, -7, 7, 4, 4, 1, 1, 1, 1, 128, 222, 150,,,,, -7, 7, 4, 4, 1, 1, 1, 1, 256, 222, 150,,,,, -7, 7, 4, 4, 1, 1, 1, 1, 384, 222, 150,,,,, -7, 7, 4, 4, 2, 2, 1, 1, 128, 222, 150,,,,, -7, 7, 4, 4, 2, 2, 1, 1, 256, 222, 150,,,,, -7, 7, 4, 4, 2, 2, 1, 1, 384, 222, 150,,,,, -7, 7, 4, 4, 2, 2, 1, 2, 128, 222, 150,,,,, -7, 7, 4, 4, 2, 2, 1, 2, 256, 222, 150,,,,, -7, 7, 4, 4, 2, 2, 1, 2, 384, 222, 150,,,,, -7, 7, 4, 4, 2, 2, 2, 1, 128, 222, 150,,,,, -7, 7, 4, 4, 2, 2, 2, 1, 256, 222, 150,,,,, -7, 7, 4, 4, 2, 2, 2, 1, 384, 222, 150,,,,, -7, 7, 4, 4, 2, 2, 2, 2, 128, 222, 150,,,,, -7, 7, 4, 4, 2, 2, 2, 2, 256, 222, 150,,,,, -7, 7, 4, 4, 2, 2, 2, 2, 384, 222, 150,,,,, -7, 7, 4, 4, 3, 3, 1, 1, 128, 218, 150,,,,, -7, 7, 4, 4, 3, 3, 1, 1, 256, 218, 150,,,,, -7, 7, 4, 4, 3, 3, 1, 1, 384, 218, 150,,,,, -7, 7, 4, 4, 3, 3, 1, 2, 128, 218, 150,,,,, -7, 7, 4, 4, 3, 3, 1, 2, 256, 218, 150,,,,, -7, 7, 4, 4, 3, 3, 1, 2, 384, 218, 150,,,,, -7, 7, 4, 4, 3, 3, 1, 3, 128, 218, 150,,,,, -7, 7, 4, 4, 3, 3, 1, 3, 256, 218, 150,,,,, -7, 7, 4, 4, 3, 3, 1, 3, 384, 218, 150,,,,, -7, 7, 4, 4, 3, 3, 2, 1, 128, 218, 150,,,,, -7, 7, 4, 4, 3, 3, 2, 1, 256, 218, 150,,,,, -7, 7, 4, 4, 3, 3, 2, 1, 384, 218, 150,,,,, -7, 7, 4, 4, 3, 3, 2, 2, 128, 218, 150,,,,, -7, 7, 4, 4, 3, 3, 2, 2, 256, 218, 150,,,,, -7, 7, 4, 4, 3, 3, 2, 2, 384, 218, 150,,,,, -7, 7, 4, 4, 3, 3, 2, 3, 128, 218, 150,,,,, -7, 7, 4, 4, 3, 3, 2, 3, 256, 218, 150,,,,, -7, 7, 4, 4, 3, 3, 2, 3, 384, 218, 150,,,,, -7, 7, 4, 4, 3, 3, 3, 1, 128, 218, 150,,,,, -7, 7, 4, 4, 3, 3, 3, 1, 256, 218, 150,,,,, -7, 7, 4, 4, 3, 3, 3, 1, 384, 218, 150,,,,, -7, 7, 4, 4, 3, 3, 3, 2, 128, 218, 150,,,,, -7, 7, 4, 4, 3, 3, 3, 2, 256, 218, 150,,,,, -7, 7, 4, 4, 3, 3, 3, 2, 384, 218, 150,,,,, -7, 7, 4, 4, 3, 3, 3, 3, 128, 218, 150,,,,, -7, 7, 4, 4, 3, 3, 3, 3, 256, 218, 150,,,,, -7, 7, 4, 4, 3, 3, 3, 3, 384, 218, 150,,,,, -7, 7, 4, 5, 1, 1, 1, 1, 128, 240, 186,,,,, -7, 7, 4, 5, 1, 1, 1, 1, 256, 240, 186,,,,, -7, 7, 4, 5, 1, 1, 1, 1, 384, 240, 186,,,,, -7, 7, 4, 5, 2, 2, 1, 1, 128, 240, 186,,,,, -7, 7, 4, 5, 2, 2, 1, 1, 256, 240, 186,,,,, -7, 7, 4, 5, 2, 2, 1, 1, 384, 240, 186,,,,, -7, 7, 4, 5, 2, 2, 1, 2, 128, 240, 186,,,,, -7, 7, 4, 5, 2, 2, 1, 2, 256, 240, 186,,,,, -7, 7, 4, 5, 2, 2, 1, 2, 384, 240, 186,,,,, -7, 7, 4, 5, 2, 2, 2, 1, 128, 240, 186,,,,, -7, 7, 4, 5, 2, 2, 2, 1, 256, 240, 186,,,,, -7, 7, 4, 5, 2, 2, 2, 1, 384, 240, 186,,,,, -7, 7, 4, 5, 2, 2, 2, 2, 128, 240, 186,,,,, -7, 7, 4, 5, 2, 2, 2, 2, 256, 240, 186,,,,, -7, 7, 4, 5, 2, 2, 2, 2, 384, 240, 186,,,,, -7, 7, 4, 5, 3, 3, 1, 1, 128, 240, 186,,,,, -7, 7, 4, 5, 3, 3, 1, 1, 256, 240, 186,,,,, -7, 7, 4, 5, 3, 3, 1, 1, 384, 240, 186,,,,, -7, 7, 4, 5, 3, 3, 1, 2, 128, 240, 186,,,,, -7, 7, 4, 5, 3, 3, 1, 2, 256, 240, 186,,,,, -7, 7, 4, 5, 3, 3, 1, 2, 384, 240, 186,,,,, -7, 7, 4, 5, 3, 3, 1, 3, 128, 240, 186,,,,, -7, 7, 4, 5, 3, 3, 1, 3, 256, 240, 186,,,,, -7, 7, 4, 5, 3, 3, 1, 3, 384, 240, 186,,,,, -7, 7, 4, 5, 3, 3, 2, 1, 128, 240, 186,,,,, -7, 7, 4, 5, 3, 3, 2, 1, 256, 240, 186,,,,, -7, 7, 4, 5, 3, 3, 2, 1, 384, 240, 186,,,,, -7, 7, 4, 5, 3, 3, 2, 2, 128, 240, 186,,,,, -7, 7, 4, 5, 3, 3, 2, 2, 256, 240, 186,,,,, -7, 7, 4, 5, 3, 3, 2, 2, 384, 240, 186,,,,, -7, 7, 4, 5, 3, 3, 2, 3, 128, 240, 186,,,,, -7, 7, 4, 5, 3, 3, 2, 3, 256, 240, 186,,,,, -7, 7, 4, 5, 3, 3, 2, 3, 384, 240, 186,,,,, -7, 7, 4, 5, 3, 3, 3, 1, 128, 240, 186,,,,, -7, 7, 4, 5, 3, 3, 3, 1, 256, 240, 186,,,,, -7, 7, 4, 5, 3, 3, 3, 1, 384, 240, 186,,,,, -7, 7, 4, 5, 3, 3, 3, 2, 128, 240, 186,,,,, -7, 7, 4, 5, 3, 3, 3, 2, 256, 240, 186,,,,, -7, 7, 4, 5, 3, 3, 3, 2, 384, 240, 186,,,,, -7, 7, 4, 5, 3, 3, 3, 3, 128, 240, 186,,,,, -7, 7, 4, 5, 3, 3, 3, 3, 256, 240, 186,,,,, -7, 7, 4, 5, 3, 3, 3, 3, 384, 240, 186,,,,, -7, 7, 4, 6, 1, 1, 1, 1, 128, 240, 222,,,,, -7, 7, 4, 6, 1, 1, 1, 1, 256, 240, 222,,,,, -7, 7, 4, 6, 1, 1, 1, 1, 384, 240, 222,,,,, -7, 7, 4, 6, 2, 2, 1, 1, 128, 240, 222,,,,, -7, 7, 4, 6, 2, 2, 1, 1, 256, 240, 222,,,,, -7, 7, 4, 6, 2, 2, 1, 1, 384, 240, 222,,,,, -7, 7, 4, 6, 2, 2, 1, 2, 128, 240, 222,,,,, -7, 7, 4, 6, 2, 2, 1, 2, 256, 240, 222,,,,, -7, 7, 4, 6, 2, 2, 1, 2, 384, 240, 222,,,,, -7, 7, 4, 6, 2, 2, 2, 1, 128, 240, 222,,,,, -7, 7, 4, 6, 2, 2, 2, 1, 256, 240, 222,,,,, -7, 7, 4, 6, 2, 2, 2, 1, 384, 240, 222,,,,, -7, 7, 4, 6, 2, 2, 2, 2, 128, 240, 222,,,,, -7, 7, 4, 6, 2, 2, 2, 2, 256, 240, 222,,,,, -7, 7, 4, 6, 2, 2, 2, 2, 384, 240, 222,,,,, -7, 7, 4, 6, 3, 3, 1, 1, 128, 240, 222,,,,, -7, 7, 4, 6, 3, 3, 1, 1, 256, 240, 222,,,,, -7, 7, 4, 6, 3, 3, 1, 1, 384, 240, 222,,,,, -7, 7, 4, 6, 3, 3, 1, 2, 128, 240, 222,,,,, -7, 7, 4, 6, 3, 3, 1, 2, 256, 240, 222,,,,, -7, 7, 4, 6, 3, 3, 1, 2, 384, 240, 222,,,,, -7, 7, 4, 6, 3, 3, 1, 3, 128, 240, 222,,,,, -7, 7, 4, 6, 3, 3, 1, 3, 256, 240, 222,,,,, -7, 7, 4, 6, 3, 3, 1, 3, 384, 240, 222,,,,, -7, 7, 4, 6, 3, 3, 2, 1, 128, 240, 222,,,,, -7, 7, 4, 6, 3, 3, 2, 1, 256, 240, 222,,,,, -7, 7, 4, 6, 3, 3, 2, 1, 384, 240, 222,,,,, -7, 7, 4, 6, 3, 3, 2, 2, 128, 240, 222,,,,, -7, 7, 4, 6, 3, 3, 2, 2, 256, 240, 222,,,,, -7, 7, 4, 6, 3, 3, 2, 2, 384, 240, 222,,,,, -7, 7, 4, 6, 3, 3, 2, 3, 128, 240, 222,,,,, -7, 7, 4, 6, 3, 3, 2, 3, 256, 240, 222,,,,, -7, 7, 4, 6, 3, 3, 2, 3, 384, 240, 222,,,,, -7, 7, 4, 6, 3, 3, 3, 1, 128, 240, 222,,,,, -7, 7, 4, 6, 3, 3, 3, 1, 256, 240, 222,,,,, -7, 7, 4, 6, 3, 3, 3, 1, 384, 240, 222,,,,, -7, 7, 4, 6, 3, 3, 3, 2, 128, 240, 222,,,,, -7, 7, 4, 6, 3, 3, 3, 2, 256, 240, 222,,,,, -7, 7, 4, 6, 3, 3, 3, 2, 384, 240, 222,,,,, -7, 7, 4, 6, 3, 3, 3, 3, 128, 240, 222,,,,, -7, 7, 4, 6, 3, 3, 3, 3, 256, 240, 222,,,,, -7, 7, 4, 6, 3, 3, 3, 3, 384, 240, 222,,,,, -7, 7, 4, 7, 1, 1, 1, 1, 128, 240, 240,,,,, -7, 7, 4, 7, 1, 1, 1, 1, 256, 240, 240,,,,, -7, 7, 4, 7, 1, 1, 1, 1, 384, 240, 240,,,,, -7, 7, 4, 7, 2, 2, 1, 1, 128, 240, 240,,,,, -7, 7, 4, 7, 2, 2, 1, 1, 256, 240, 240,,,,, -7, 7, 4, 7, 2, 2, 1, 1, 384, 240, 240,,,,, -7, 7, 4, 7, 2, 2, 1, 2, 128, 240, 240,,,,, -7, 7, 4, 7, 2, 2, 1, 2, 256, 240, 240,,,,, -7, 7, 4, 7, 2, 2, 1, 2, 384, 240, 240,,,,, -7, 7, 4, 7, 2, 2, 2, 1, 128, 240, 240,,,,, -7, 7, 4, 7, 2, 2, 2, 1, 256, 240, 240,,,,, -7, 7, 4, 7, 2, 2, 2, 1, 384, 240, 240,,,,, -7, 7, 4, 7, 2, 2, 2, 2, 128, 240, 240,,,,, -7, 7, 4, 7, 2, 2, 2, 2, 256, 240, 240,,,,, -7, 7, 4, 7, 2, 2, 2, 2, 384, 240, 240,,,,, -7, 7, 4, 7, 3, 3, 1, 1, 128, 240, 240,,,,, -7, 7, 4, 7, 3, 3, 1, 1, 256, 240, 240,,,,, -7, 7, 4, 7, 3, 3, 1, 1, 384, 240, 240,,,,, -7, 7, 4, 7, 3, 3, 1, 2, 128, 240, 240,,,,, -7, 7, 4, 7, 3, 3, 1, 2, 256, 240, 240,,,,, -7, 7, 4, 7, 3, 3, 1, 2, 384, 240, 240,,,,, -7, 7, 4, 7, 3, 3, 1, 3, 128, 240, 240,,,,, -7, 7, 4, 7, 3, 3, 1, 3, 256, 240, 240,,,,, -7, 7, 4, 7, 3, 3, 1, 3, 384, 240, 240,,,,, -7, 7, 4, 7, 3, 3, 2, 1, 128, 240, 240,,,,, -7, 7, 4, 7, 3, 3, 2, 1, 256, 240, 240,,,,, -7, 7, 4, 7, 3, 3, 2, 1, 384, 240, 240,,,,, -7, 7, 4, 7, 3, 3, 2, 2, 128, 240, 240,,,,, -7, 7, 4, 7, 3, 3, 2, 2, 256, 240, 240,,,,, -7, 7, 4, 7, 3, 3, 2, 2, 384, 240, 240,,,,, -7, 7, 4, 7, 3, 3, 2, 3, 128, 240, 240,,,,, -7, 7, 4, 7, 3, 3, 2, 3, 256, 240, 240,,,,, -7, 7, 4, 7, 3, 3, 2, 3, 384, 240, 240,,,,, -7, 7, 4, 7, 3, 3, 3, 1, 128, 240, 240,,,,, -7, 7, 4, 7, 3, 3, 3, 1, 256, 240, 240,,,,, -7, 7, 4, 7, 3, 3, 3, 1, 384, 240, 240,,,,, -7, 7, 4, 7, 3, 3, 3, 2, 128, 240, 240,,,,, -7, 7, 4, 7, 3, 3, 3, 2, 256, 240, 240,,,,, -7, 7, 4, 7, 3, 3, 3, 2, 384, 240, 240,,,,, -7, 7, 4, 7, 3, 3, 3, 3, 128, 240, 240,,,,, -7, 7, 4, 7, 3, 3, 3, 3, 256, 240, 240,,,,, -7, 7, 4, 7, 3, 3, 3, 3, 384, 240, 240,,,,, -7, 7, 5, 1, 1, 1, 1, 1, 128, 60, 42,,,,, -7, 7, 5, 1, 1, 1, 1, 1, 256, 60, 42,,,,, -7, 7, 5, 1, 1, 1, 1, 1, 384, 60, 42,,,,, -7, 7, 5, 1, 2, 2, 1, 1, 128, 60, 42,,,,, -7, 7, 5, 1, 2, 2, 1, 1, 256, 60, 42,,,,, -7, 7, 5, 1, 2, 2, 1, 1, 384, 60, 42,,,,, -7, 7, 5, 1, 2, 2, 1, 2, 128, 60, 42,,,,, -7, 7, 5, 1, 2, 2, 1, 2, 256, 60, 42,,,,, -7, 7, 5, 1, 2, 2, 1, 2, 384, 60, 42,,,,, -7, 7, 5, 1, 2, 2, 2, 1, 128, 60, 42,,,,, -7, 7, 5, 1, 2, 2, 2, 1, 256, 60, 42,,,,, -7, 7, 5, 1, 2, 2, 2, 1, 384, 60, 42,,,,, -7, 7, 5, 1, 2, 2, 2, 2, 128, 60, 42,,,,, -7, 7, 5, 1, 2, 2, 2, 2, 256, 60, 42,,,,, -7, 7, 5, 1, 2, 2, 2, 2, 384, 60, 42,,,,, -7, 7, 5, 1, 3, 3, 1, 1, 128, 59, 42,,,,, -7, 7, 5, 1, 3, 3, 1, 1, 256, 59, 42,,,,, -7, 7, 5, 1, 3, 3, 1, 1, 384, 59, 42,,,,, -7, 7, 5, 1, 3, 3, 1, 2, 128, 59, 42,,,,, -7, 7, 5, 1, 3, 3, 1, 2, 256, 59, 42,,,,, -7, 7, 5, 1, 3, 3, 1, 2, 384, 59, 42,,,,, -7, 7, 5, 1, 3, 3, 1, 3, 128, 59, 42,,,,, -7, 7, 5, 1, 3, 3, 1, 3, 256, 59, 42,,,,, -7, 7, 5, 1, 3, 3, 1, 3, 384, 59, 42,,,,, -7, 7, 5, 1, 3, 3, 2, 1, 128, 59, 42,,,,, -7, 7, 5, 1, 3, 3, 2, 1, 256, 59, 42,,,,, -7, 7, 5, 1, 3, 3, 2, 1, 384, 59, 42,,,,, -7, 7, 5, 1, 3, 3, 2, 2, 128, 59, 42,,,,, -7, 7, 5, 1, 3, 3, 2, 2, 256, 59, 42,,,,, -7, 7, 5, 1, 3, 3, 2, 2, 384, 59, 42,,,,, -7, 7, 5, 1, 3, 3, 2, 3, 128, 59, 42,,,,, -7, 7, 5, 1, 3, 3, 2, 3, 256, 59, 42,,,,, -7, 7, 5, 1, 3, 3, 2, 3, 384, 59, 42,,,,, -7, 7, 5, 1, 3, 3, 3, 1, 128, 59, 42,,,,, -7, 7, 5, 1, 3, 3, 3, 1, 256, 59, 42,,,,, -7, 7, 5, 1, 3, 3, 3, 1, 384, 59, 42,,,,, -7, 7, 5, 1, 3, 3, 3, 2, 128, 59, 42,,,,, -7, 7, 5, 1, 3, 3, 3, 2, 256, 59, 42,,,,, -7, 7, 5, 1, 3, 3, 3, 2, 384, 59, 42,,,,, -7, 7, 5, 1, 3, 3, 3, 3, 128, 59, 42,,,,, -7, 7, 5, 1, 3, 3, 3, 3, 256, 59, 42,,,,, -7, 7, 5, 1, 3, 3, 3, 3, 384, 59, 42,,,,, -7, 7, 5, 2, 1, 1, 1, 1, 128, 114, 78,,,,, -7, 7, 5, 2, 1, 1, 1, 1, 256, 114, 78,,,,, -7, 7, 5, 2, 1, 1, 1, 1, 384, 114, 78,,,,, -7, 7, 5, 2, 2, 2, 1, 1, 128, 114, 78,,,,, -7, 7, 5, 2, 2, 2, 1, 1, 256, 114, 78,,,,, -7, 7, 5, 2, 2, 2, 1, 1, 384, 114, 78,,,,, -7, 7, 5, 2, 2, 2, 1, 2, 128, 114, 78,,,,, -7, 7, 5, 2, 2, 2, 1, 2, 256, 114, 78,,,,, -7, 7, 5, 2, 2, 2, 1, 2, 384, 114, 78,,,,, -7, 7, 5, 2, 2, 2, 2, 1, 128, 114, 78,,,,, -7, 7, 5, 2, 2, 2, 2, 1, 256, 114, 78,,,,, -7, 7, 5, 2, 2, 2, 2, 1, 384, 114, 78,,,,, -7, 7, 5, 2, 2, 2, 2, 2, 128, 114, 78,,,,, -7, 7, 5, 2, 2, 2, 2, 2, 256, 114, 78,,,,, -7, 7, 5, 2, 2, 2, 2, 2, 384, 114, 78,,,,, -7, 7, 5, 2, 3, 3, 1, 1, 128, 112, 78,,,,, -7, 7, 5, 2, 3, 3, 1, 1, 256, 112, 78,,,,, -7, 7, 5, 2, 3, 3, 1, 1, 384, 112, 78,,,,, -7, 7, 5, 2, 3, 3, 1, 2, 128, 112, 78,,,,, -7, 7, 5, 2, 3, 3, 1, 2, 256, 112, 78,,,,, -7, 7, 5, 2, 3, 3, 1, 2, 384, 112, 78,,,,, -7, 7, 5, 2, 3, 3, 1, 3, 128, 112, 78,,,,, -7, 7, 5, 2, 3, 3, 1, 3, 256, 112, 78,,,,, -7, 7, 5, 2, 3, 3, 1, 3, 384, 112, 78,,,,, -7, 7, 5, 2, 3, 3, 2, 1, 128, 112, 78,,,,, -7, 7, 5, 2, 3, 3, 2, 1, 256, 112, 78,,,,, -7, 7, 5, 2, 3, 3, 2, 1, 384, 112, 78,,,,, -7, 7, 5, 2, 3, 3, 2, 2, 128, 112, 78,,,,, -7, 7, 5, 2, 3, 3, 2, 2, 256, 112, 78,,,,, -7, 7, 5, 2, 3, 3, 2, 2, 384, 112, 78,,,,, -7, 7, 5, 2, 3, 3, 2, 3, 128, 112, 78,,,,, -7, 7, 5, 2, 3, 3, 2, 3, 256, 112, 78,,,,, -7, 7, 5, 2, 3, 3, 2, 3, 384, 112, 78,,,,, -7, 7, 5, 2, 3, 3, 3, 1, 128, 112, 78,,,,, -7, 7, 5, 2, 3, 3, 3, 1, 256, 112, 78,,,,, -7, 7, 5, 2, 3, 3, 3, 1, 384, 112, 78,,,,, -7, 7, 5, 2, 3, 3, 3, 2, 128, 112, 78,,,,, -7, 7, 5, 2, 3, 3, 3, 2, 256, 112, 78,,,,, -7, 7, 5, 2, 3, 3, 3, 2, 384, 112, 78,,,,, -7, 7, 5, 2, 3, 3, 3, 3, 128, 112, 78,,,,, -7, 7, 5, 2, 3, 3, 3, 3, 256, 112, 78,,,,, -7, 7, 5, 2, 3, 3, 3, 3, 384, 112, 78,,,,, -7, 7, 5, 3, 1, 1, 1, 1, 128, 168, 114,,,,, -7, 7, 5, 3, 1, 1, 1, 1, 256, 168, 114,,,,, -7, 7, 5, 3, 1, 1, 1, 1, 384, 168, 114,,,,, -7, 7, 5, 3, 2, 2, 1, 1, 128, 168, 114,,,,, -7, 7, 5, 3, 2, 2, 1, 1, 256, 168, 114,,,,, -7, 7, 5, 3, 2, 2, 1, 1, 384, 168, 114,,,,, -7, 7, 5, 3, 2, 2, 1, 2, 128, 168, 114,,,,, -7, 7, 5, 3, 2, 2, 1, 2, 256, 168, 114,,,,, -7, 7, 5, 3, 2, 2, 1, 2, 384, 168, 114,,,,, -7, 7, 5, 3, 2, 2, 2, 1, 128, 168, 114,,,,, -7, 7, 5, 3, 2, 2, 2, 1, 256, 168, 114,,,,, -7, 7, 5, 3, 2, 2, 2, 1, 384, 168, 114,,,,, -7, 7, 5, 3, 2, 2, 2, 2, 128, 168, 114,,,,, -7, 7, 5, 3, 2, 2, 2, 2, 256, 168, 114,,,,, -7, 7, 5, 3, 2, 2, 2, 2, 384, 168, 114,,,,, -7, 7, 5, 3, 3, 3, 1, 1, 128, 165, 114,,,,, -7, 7, 5, 3, 3, 3, 1, 1, 256, 165, 114,,,,, -7, 7, 5, 3, 3, 3, 1, 1, 384, 165, 114,,,,, -7, 7, 5, 3, 3, 3, 1, 2, 128, 165, 114,,,,, -7, 7, 5, 3, 3, 3, 1, 2, 256, 165, 114,,,,, -7, 7, 5, 3, 3, 3, 1, 2, 384, 165, 114,,,,, -7, 7, 5, 3, 3, 3, 1, 3, 128, 165, 114,,,,, -7, 7, 5, 3, 3, 3, 1, 3, 256, 165, 114,,,,, -7, 7, 5, 3, 3, 3, 1, 3, 384, 165, 114,,,,, -7, 7, 5, 3, 3, 3, 2, 1, 128, 165, 114,,,,, -7, 7, 5, 3, 3, 3, 2, 1, 256, 165, 114,,,,, -7, 7, 5, 3, 3, 3, 2, 1, 384, 165, 114,,,,, -7, 7, 5, 3, 3, 3, 2, 2, 128, 165, 114,,,,, -7, 7, 5, 3, 3, 3, 2, 2, 256, 165, 114,,,,, -7, 7, 5, 3, 3, 3, 2, 2, 384, 165, 114,,,,, -7, 7, 5, 3, 3, 3, 2, 3, 128, 165, 114,,,,, -7, 7, 5, 3, 3, 3, 2, 3, 256, 165, 114,,,,, -7, 7, 5, 3, 3, 3, 2, 3, 384, 165, 114,,,,, -7, 7, 5, 3, 3, 3, 3, 1, 128, 165, 114,,,,, -7, 7, 5, 3, 3, 3, 3, 1, 256, 165, 114,,,,, -7, 7, 5, 3, 3, 3, 3, 1, 384, 165, 114,,,,, -7, 7, 5, 3, 3, 3, 3, 2, 128, 165, 114,,,,, -7, 7, 5, 3, 3, 3, 3, 2, 256, 165, 114,,,,, -7, 7, 5, 3, 3, 3, 3, 2, 384, 165, 114,,,,, -7, 7, 5, 3, 3, 3, 3, 3, 128, 165, 114,,,,, -7, 7, 5, 3, 3, 3, 3, 3, 256, 165, 114,,,,, -7, 7, 5, 3, 3, 3, 3, 3, 384, 165, 114,,,,, -7, 7, 5, 4, 1, 1, 1, 1, 128, 222, 150,,,,, -7, 7, 5, 4, 1, 1, 1, 1, 256, 222, 150,,,,, -7, 7, 5, 4, 1, 1, 1, 1, 384, 222, 150,,,,, -7, 7, 5, 4, 2, 2, 1, 1, 128, 222, 150,,,,, -7, 7, 5, 4, 2, 2, 1, 1, 256, 222, 150,,,,, -7, 7, 5, 4, 2, 2, 1, 1, 384, 222, 150,,,,, -7, 7, 5, 4, 2, 2, 1, 2, 128, 222, 150,,,,, -7, 7, 5, 4, 2, 2, 1, 2, 256, 222, 150,,,,, -7, 7, 5, 4, 2, 2, 1, 2, 384, 222, 150,,,,, -7, 7, 5, 4, 2, 2, 2, 1, 128, 222, 150,,,,, -7, 7, 5, 4, 2, 2, 2, 1, 256, 222, 150,,,,, -7, 7, 5, 4, 2, 2, 2, 1, 384, 222, 150,,,,, -7, 7, 5, 4, 2, 2, 2, 2, 128, 222, 150,,,,, -7, 7, 5, 4, 2, 2, 2, 2, 256, 222, 150,,,,, -7, 7, 5, 4, 2, 2, 2, 2, 384, 222, 150,,,,, -7, 7, 5, 4, 3, 3, 1, 1, 128, 218, 150,,,,, -7, 7, 5, 4, 3, 3, 1, 1, 256, 218, 150,,,,, -7, 7, 5, 4, 3, 3, 1, 1, 384, 218, 150,,,,, -7, 7, 5, 4, 3, 3, 1, 2, 128, 218, 150,,,,, -7, 7, 5, 4, 3, 3, 1, 2, 256, 218, 150,,,,, -7, 7, 5, 4, 3, 3, 1, 2, 384, 218, 150,,,,, -7, 7, 5, 4, 3, 3, 1, 3, 128, 218, 150,,,,, -7, 7, 5, 4, 3, 3, 1, 3, 256, 218, 150,,,,, -7, 7, 5, 4, 3, 3, 1, 3, 384, 218, 150,,,,, -7, 7, 5, 4, 3, 3, 2, 1, 128, 218, 150,,,,, -7, 7, 5, 4, 3, 3, 2, 1, 256, 218, 150,,,,, -7, 7, 5, 4, 3, 3, 2, 1, 384, 218, 150,,,,, -7, 7, 5, 4, 3, 3, 2, 2, 128, 218, 150,,,,, -7, 7, 5, 4, 3, 3, 2, 2, 256, 218, 150,,,,, -7, 7, 5, 4, 3, 3, 2, 2, 384, 218, 150,,,,, -7, 7, 5, 4, 3, 3, 2, 3, 128, 218, 150,,,,, -7, 7, 5, 4, 3, 3, 2, 3, 256, 218, 150,,,,, -7, 7, 5, 4, 3, 3, 2, 3, 384, 218, 150,,,,, -7, 7, 5, 4, 3, 3, 3, 1, 128, 218, 150,,,,, -7, 7, 5, 4, 3, 3, 3, 1, 256, 218, 150,,,,, -7, 7, 5, 4, 3, 3, 3, 1, 384, 218, 150,,,,, -7, 7, 5, 4, 3, 3, 3, 2, 128, 218, 150,,,,, -7, 7, 5, 4, 3, 3, 3, 2, 256, 218, 150,,,,, -7, 7, 5, 4, 3, 3, 3, 2, 384, 218, 150,,,,, -7, 7, 5, 4, 3, 3, 3, 3, 128, 218, 150,,,,, -7, 7, 5, 4, 3, 3, 3, 3, 256, 218, 150,,,,, -7, 7, 5, 4, 3, 3, 3, 3, 384, 218, 150,,,,, -7, 7, 5, 5, 1, 1, 1, 1, 128, 240, 186,,,,, -7, 7, 5, 5, 1, 1, 1, 1, 256, 240, 186,,,,, -7, 7, 5, 5, 1, 1, 1, 1, 384, 240, 186,,,,, -7, 7, 5, 5, 2, 2, 1, 1, 128, 240, 186,,,,, -7, 7, 5, 5, 2, 2, 1, 1, 256, 240, 186,,,,, -7, 7, 5, 5, 2, 2, 1, 1, 384, 240, 186,,,,, -7, 7, 5, 5, 2, 2, 1, 2, 128, 240, 186,,,,, -7, 7, 5, 5, 2, 2, 1, 2, 256, 240, 186,,,,, -7, 7, 5, 5, 2, 2, 1, 2, 384, 240, 186,,,,, -7, 7, 5, 5, 2, 2, 2, 1, 128, 240, 186,,,,, -7, 7, 5, 5, 2, 2, 2, 1, 256, 240, 186,,,,, -7, 7, 5, 5, 2, 2, 2, 1, 384, 240, 186,,,,, -7, 7, 5, 5, 2, 2, 2, 2, 128, 240, 186,,,,, -7, 7, 5, 5, 2, 2, 2, 2, 256, 240, 186,,,,, -7, 7, 5, 5, 2, 2, 2, 2, 384, 240, 186,,,,, -7, 7, 5, 5, 3, 3, 1, 1, 128, 240, 186,,,,, -7, 7, 5, 5, 3, 3, 1, 1, 256, 240, 186,,,,, -7, 7, 5, 5, 3, 3, 1, 1, 384, 240, 186,,,,, -7, 7, 5, 5, 3, 3, 1, 2, 128, 240, 186,,,,, -7, 7, 5, 5, 3, 3, 1, 2, 256, 240, 186,,,,, -7, 7, 5, 5, 3, 3, 1, 2, 384, 240, 186,,,,, -7, 7, 5, 5, 3, 3, 1, 3, 128, 240, 186,,,,, -7, 7, 5, 5, 3, 3, 1, 3, 256, 240, 186,,,,, -7, 7, 5, 5, 3, 3, 1, 3, 384, 240, 186,,,,, -7, 7, 5, 5, 3, 3, 2, 1, 128, 240, 186,,,,, -7, 7, 5, 5, 3, 3, 2, 1, 256, 240, 186,,,,, -7, 7, 5, 5, 3, 3, 2, 1, 384, 240, 186,,,,, -7, 7, 5, 5, 3, 3, 2, 2, 128, 240, 186,,,,, -7, 7, 5, 5, 3, 3, 2, 2, 256, 240, 186,,,,, -7, 7, 5, 5, 3, 3, 2, 2, 384, 240, 186,,,,, -7, 7, 5, 5, 3, 3, 2, 3, 128, 240, 186,,,,, -7, 7, 5, 5, 3, 3, 2, 3, 256, 240, 186,,,,, -7, 7, 5, 5, 3, 3, 2, 3, 384, 240, 186,,,,, -7, 7, 5, 5, 3, 3, 3, 1, 128, 240, 186,,,,, -7, 7, 5, 5, 3, 3, 3, 1, 256, 240, 186,,,,, -7, 7, 5, 5, 3, 3, 3, 1, 384, 240, 186,,,,, -7, 7, 5, 5, 3, 3, 3, 2, 128, 240, 186,,,,, -7, 7, 5, 5, 3, 3, 3, 2, 256, 240, 186,,,,, -7, 7, 5, 5, 3, 3, 3, 2, 384, 240, 186,,,,, -7, 7, 5, 5, 3, 3, 3, 3, 128, 240, 186,,,,, -7, 7, 5, 5, 3, 3, 3, 3, 256, 240, 186,,,,, -7, 7, 5, 5, 3, 3, 3, 3, 384, 240, 186,,,,, -7, 7, 5, 6, 1, 1, 1, 1, 128, 240, 222,,,,, -7, 7, 5, 6, 1, 1, 1, 1, 256, 240, 222,,,,, -7, 7, 5, 6, 1, 1, 1, 1, 384, 240, 222,,,,, -7, 7, 5, 6, 2, 2, 1, 1, 128, 240, 222,,,,, -7, 7, 5, 6, 2, 2, 1, 1, 256, 240, 222,,,,, -7, 7, 5, 6, 2, 2, 1, 1, 384, 240, 222,,,,, -7, 7, 5, 6, 2, 2, 1, 2, 128, 240, 222,,,,, -7, 7, 5, 6, 2, 2, 1, 2, 256, 240, 222,,,,, -7, 7, 5, 6, 2, 2, 1, 2, 384, 240, 222,,,,, -7, 7, 5, 6, 2, 2, 2, 1, 128, 240, 222,,,,, -7, 7, 5, 6, 2, 2, 2, 1, 256, 240, 222,,,,, -7, 7, 5, 6, 2, 2, 2, 1, 384, 240, 222,,,,, -7, 7, 5, 6, 2, 2, 2, 2, 128, 240, 222,,,,, -7, 7, 5, 6, 2, 2, 2, 2, 256, 240, 222,,,,, -7, 7, 5, 6, 2, 2, 2, 2, 384, 240, 222,,,,, -7, 7, 5, 6, 3, 3, 1, 1, 128, 240, 222,,,,, -7, 7, 5, 6, 3, 3, 1, 1, 256, 240, 222,,,,, -7, 7, 5, 6, 3, 3, 1, 1, 384, 240, 222,,,,, -7, 7, 5, 6, 3, 3, 1, 2, 128, 240, 222,,,,, -7, 7, 5, 6, 3, 3, 1, 2, 256, 240, 222,,,,, -7, 7, 5, 6, 3, 3, 1, 2, 384, 240, 222,,,,, -7, 7, 5, 6, 3, 3, 1, 3, 128, 240, 222,,,,, -7, 7, 5, 6, 3, 3, 1, 3, 256, 240, 222,,,,, -7, 7, 5, 6, 3, 3, 1, 3, 384, 240, 222,,,,, -7, 7, 5, 6, 3, 3, 2, 1, 128, 240, 222,,,,, -7, 7, 5, 6, 3, 3, 2, 1, 256, 240, 222,,,,, -7, 7, 5, 6, 3, 3, 2, 1, 384, 240, 222,,,,, -7, 7, 5, 6, 3, 3, 2, 2, 128, 240, 222,,,,, -7, 7, 5, 6, 3, 3, 2, 2, 256, 240, 222,,,,, -7, 7, 5, 6, 3, 3, 2, 2, 384, 240, 222,,,,, -7, 7, 5, 6, 3, 3, 2, 3, 128, 240, 222,,,,, -7, 7, 5, 6, 3, 3, 2, 3, 256, 240, 222,,,,, -7, 7, 5, 6, 3, 3, 2, 3, 384, 240, 222,,,,, -7, 7, 5, 6, 3, 3, 3, 1, 128, 240, 222,,,,, -7, 7, 5, 6, 3, 3, 3, 1, 256, 240, 222,,,,, -7, 7, 5, 6, 3, 3, 3, 1, 384, 240, 222,,,,, -7, 7, 5, 6, 3, 3, 3, 2, 128, 240, 222,,,,, -7, 7, 5, 6, 3, 3, 3, 2, 256, 240, 222,,,,, -7, 7, 5, 6, 3, 3, 3, 2, 384, 240, 222,,,,, -7, 7, 5, 6, 3, 3, 3, 3, 128, 240, 222,,,,, -7, 7, 5, 6, 3, 3, 3, 3, 256, 240, 222,,,,, -7, 7, 5, 6, 3, 3, 3, 3, 384, 240, 222,,,,, -7, 7, 5, 7, 1, 1, 1, 1, 128, 240, 240,,,,, -7, 7, 5, 7, 1, 1, 1, 1, 256, 240, 240,,,,, -7, 7, 5, 7, 1, 1, 1, 1, 384, 240, 240,,,,, -7, 7, 5, 7, 2, 2, 1, 1, 128, 240, 240,,,,, -7, 7, 5, 7, 2, 2, 1, 1, 256, 240, 240,,,,, -7, 7, 5, 7, 2, 2, 1, 1, 384, 240, 240,,,,, -7, 7, 5, 7, 2, 2, 1, 2, 128, 240, 240,,,,, -7, 7, 5, 7, 2, 2, 1, 2, 256, 240, 240,,,,, -7, 7, 5, 7, 2, 2, 1, 2, 384, 240, 240,,,,, -7, 7, 5, 7, 2, 2, 2, 1, 128, 240, 240,,,,, -7, 7, 5, 7, 2, 2, 2, 1, 256, 240, 240,,,,, -7, 7, 5, 7, 2, 2, 2, 1, 384, 240, 240,,,,, -7, 7, 5, 7, 2, 2, 2, 2, 128, 240, 240,,,,, -7, 7, 5, 7, 2, 2, 2, 2, 256, 240, 240,,,,, -7, 7, 5, 7, 2, 2, 2, 2, 384, 240, 240,,,,, -7, 7, 5, 7, 3, 3, 1, 1, 128, 240, 240,,,,, -7, 7, 5, 7, 3, 3, 1, 1, 256, 240, 240,,,,, -7, 7, 5, 7, 3, 3, 1, 1, 384, 240, 240,,,,, -7, 7, 5, 7, 3, 3, 1, 2, 128, 240, 240,,,,, -7, 7, 5, 7, 3, 3, 1, 2, 256, 240, 240,,,,, -7, 7, 5, 7, 3, 3, 1, 2, 384, 240, 240,,,,, -7, 7, 5, 7, 3, 3, 1, 3, 128, 240, 240,,,,, -7, 7, 5, 7, 3, 3, 1, 3, 256, 240, 240,,,,, -7, 7, 5, 7, 3, 3, 1, 3, 384, 240, 240,,,,, -7, 7, 5, 7, 3, 3, 2, 1, 128, 240, 240,,,,, -7, 7, 5, 7, 3, 3, 2, 1, 256, 240, 240,,,,, -7, 7, 5, 7, 3, 3, 2, 1, 384, 240, 240,,,,, -7, 7, 5, 7, 3, 3, 2, 2, 128, 240, 240,,,,, -7, 7, 5, 7, 3, 3, 2, 2, 256, 240, 240,,,,, -7, 7, 5, 7, 3, 3, 2, 2, 384, 240, 240,,,,, -7, 7, 5, 7, 3, 3, 2, 3, 128, 240, 240,,,,, -7, 7, 5, 7, 3, 3, 2, 3, 256, 240, 240,,,,, -7, 7, 5, 7, 3, 3, 2, 3, 384, 240, 240,,,,, -7, 7, 5, 7, 3, 3, 3, 1, 128, 240, 240,,,,, -7, 7, 5, 7, 3, 3, 3, 1, 256, 240, 240,,,,, -7, 7, 5, 7, 3, 3, 3, 1, 384, 240, 240,,,,, -7, 7, 5, 7, 3, 3, 3, 2, 128, 240, 240,,,,, -7, 7, 5, 7, 3, 3, 3, 2, 256, 240, 240,,,,, -7, 7, 5, 7, 3, 3, 3, 2, 384, 240, 240,,,,, -7, 7, 5, 7, 3, 3, 3, 3, 128, 240, 240,,,,, -7, 7, 5, 7, 3, 3, 3, 3, 256, 240, 240,,,,, -7, 7, 5, 7, 3, 3, 3, 3, 384, 240, 240,,,,, -7, 7, 6, 1, 1, 1, 1, 1, 128, 60, 42,,,,, -7, 7, 6, 1, 1, 1, 1, 1, 256, 60, 42,,,,, -7, 7, 6, 1, 1, 1, 1, 1, 384, 60, 42,,,,, -7, 7, 6, 1, 2, 2, 1, 1, 128, 60, 42,,,,, -7, 7, 6, 1, 2, 2, 1, 1, 256, 60, 42,,,,, -7, 7, 6, 1, 2, 2, 1, 1, 384, 60, 42,,,,, -7, 7, 6, 1, 2, 2, 1, 2, 128, 60, 42,,,,, -7, 7, 6, 1, 2, 2, 1, 2, 256, 60, 42,,,,, -7, 7, 6, 1, 2, 2, 1, 2, 384, 60, 42,,,,, -7, 7, 6, 1, 2, 2, 2, 1, 128, 60, 42,,,,, -7, 7, 6, 1, 2, 2, 2, 1, 256, 60, 42,,,,, -7, 7, 6, 1, 2, 2, 2, 1, 384, 60, 42,,,,, -7, 7, 6, 1, 2, 2, 2, 2, 128, 60, 42,,,,, -7, 7, 6, 1, 2, 2, 2, 2, 256, 60, 42,,,,, -7, 7, 6, 1, 2, 2, 2, 2, 384, 60, 42,,,,, -7, 7, 6, 1, 3, 3, 1, 1, 128, 59, 42,,,,, -7, 7, 6, 1, 3, 3, 1, 1, 256, 59, 42,,,,, -7, 7, 6, 1, 3, 3, 1, 1, 384, 59, 42,,,,, -7, 7, 6, 1, 3, 3, 1, 2, 128, 59, 42,,,,, -7, 7, 6, 1, 3, 3, 1, 2, 256, 59, 42,,,,, -7, 7, 6, 1, 3, 3, 1, 2, 384, 59, 42,,,,, -7, 7, 6, 1, 3, 3, 1, 3, 128, 59, 42,,,,, -7, 7, 6, 1, 3, 3, 1, 3, 256, 59, 42,,,,, -7, 7, 6, 1, 3, 3, 1, 3, 384, 59, 42,,,,, -7, 7, 6, 1, 3, 3, 2, 1, 128, 59, 42,,,,, -7, 7, 6, 1, 3, 3, 2, 1, 256, 59, 42,,,,, -7, 7, 6, 1, 3, 3, 2, 1, 384, 59, 42,,,,, -7, 7, 6, 1, 3, 3, 2, 2, 128, 59, 42,,,,, -7, 7, 6, 1, 3, 3, 2, 2, 256, 59, 42,,,,, -7, 7, 6, 1, 3, 3, 2, 2, 384, 59, 42,,,,, -7, 7, 6, 1, 3, 3, 2, 3, 128, 59, 42,,,,, -7, 7, 6, 1, 3, 3, 2, 3, 256, 59, 42,,,,, -7, 7, 6, 1, 3, 3, 2, 3, 384, 59, 42,,,,, -7, 7, 6, 1, 3, 3, 3, 1, 128, 59, 42,,,,, -7, 7, 6, 1, 3, 3, 3, 1, 256, 59, 42,,,,, -7, 7, 6, 1, 3, 3, 3, 1, 384, 59, 42,,,,, -7, 7, 6, 1, 3, 3, 3, 2, 128, 59, 42,,,,, -7, 7, 6, 1, 3, 3, 3, 2, 256, 59, 42,,,,, -7, 7, 6, 1, 3, 3, 3, 2, 384, 59, 42,,,,, -7, 7, 6, 1, 3, 3, 3, 3, 128, 59, 42,,,,, -7, 7, 6, 1, 3, 3, 3, 3, 256, 59, 42,,,,, -7, 7, 6, 1, 3, 3, 3, 3, 384, 59, 42,,,,, -7, 7, 6, 2, 1, 1, 1, 1, 128, 114, 78,,,,, -7, 7, 6, 2, 1, 1, 1, 1, 256, 114, 78,,,,, -7, 7, 6, 2, 1, 1, 1, 1, 384, 114, 78,,,,, -7, 7, 6, 2, 2, 2, 1, 1, 128, 114, 78,,,,, -7, 7, 6, 2, 2, 2, 1, 1, 256, 114, 78,,,,, -7, 7, 6, 2, 2, 2, 1, 1, 384, 114, 78,,,,, -7, 7, 6, 2, 2, 2, 1, 2, 128, 114, 78,,,,, -7, 7, 6, 2, 2, 2, 1, 2, 256, 114, 78,,,,, -7, 7, 6, 2, 2, 2, 1, 2, 384, 114, 78,,,,, -7, 7, 6, 2, 2, 2, 2, 1, 128, 114, 78,,,,, -7, 7, 6, 2, 2, 2, 2, 1, 256, 114, 78,,,,, -7, 7, 6, 2, 2, 2, 2, 1, 384, 114, 78,,,,, -7, 7, 6, 2, 2, 2, 2, 2, 128, 114, 78,,,,, -7, 7, 6, 2, 2, 2, 2, 2, 256, 114, 78,,,,, -7, 7, 6, 2, 2, 2, 2, 2, 384, 114, 78,,,,, -7, 7, 6, 2, 3, 3, 1, 1, 128, 112, 78,,,,, -7, 7, 6, 2, 3, 3, 1, 1, 256, 112, 78,,,,, -7, 7, 6, 2, 3, 3, 1, 1, 384, 112, 78,,,,, -7, 7, 6, 2, 3, 3, 1, 2, 128, 112, 78,,,,, -7, 7, 6, 2, 3, 3, 1, 2, 256, 112, 78,,,,, -7, 7, 6, 2, 3, 3, 1, 2, 384, 112, 78,,,,, -7, 7, 6, 2, 3, 3, 1, 3, 128, 112, 78,,,,, -7, 7, 6, 2, 3, 3, 1, 3, 256, 112, 78,,,,, -7, 7, 6, 2, 3, 3, 1, 3, 384, 112, 78,,,,, -7, 7, 6, 2, 3, 3, 2, 1, 128, 112, 78,,,,, -7, 7, 6, 2, 3, 3, 2, 1, 256, 112, 78,,,,, -7, 7, 6, 2, 3, 3, 2, 1, 384, 112, 78,,,,, -7, 7, 6, 2, 3, 3, 2, 2, 128, 112, 78,,,,, -7, 7, 6, 2, 3, 3, 2, 2, 256, 112, 78,,,,, -7, 7, 6, 2, 3, 3, 2, 2, 384, 112, 78,,,,, -7, 7, 6, 2, 3, 3, 2, 3, 128, 112, 78,,,,, -7, 7, 6, 2, 3, 3, 2, 3, 256, 112, 78,,,,, -7, 7, 6, 2, 3, 3, 2, 3, 384, 112, 78,,,,, -7, 7, 6, 2, 3, 3, 3, 1, 128, 112, 78,,,,, -7, 7, 6, 2, 3, 3, 3, 1, 256, 112, 78,,,,, -7, 7, 6, 2, 3, 3, 3, 1, 384, 112, 78,,,,, -7, 7, 6, 2, 3, 3, 3, 2, 128, 112, 78,,,,, -7, 7, 6, 2, 3, 3, 3, 2, 256, 112, 78,,,,, -7, 7, 6, 2, 3, 3, 3, 2, 384, 112, 78,,,,, -7, 7, 6, 2, 3, 3, 3, 3, 128, 112, 78,,,,, -7, 7, 6, 2, 3, 3, 3, 3, 256, 112, 78,,,,, -7, 7, 6, 2, 3, 3, 3, 3, 384, 112, 78,,,,, -7, 7, 6, 3, 1, 1, 1, 1, 128, 168, 114,,,,, -7, 7, 6, 3, 1, 1, 1, 1, 256, 168, 114,,,,, -7, 7, 6, 3, 1, 1, 1, 1, 384, 168, 114,,,,, -7, 7, 6, 3, 2, 2, 1, 1, 128, 168, 114,,,,, -7, 7, 6, 3, 2, 2, 1, 1, 256, 168, 114,,,,, -7, 7, 6, 3, 2, 2, 1, 1, 384, 168, 114,,,,, -7, 7, 6, 3, 2, 2, 1, 2, 128, 168, 114,,,,, -7, 7, 6, 3, 2, 2, 1, 2, 256, 168, 114,,,,, -7, 7, 6, 3, 2, 2, 1, 2, 384, 168, 114,,,,, -7, 7, 6, 3, 2, 2, 2, 1, 128, 168, 114,,,,, -7, 7, 6, 3, 2, 2, 2, 1, 256, 168, 114,,,,, -7, 7, 6, 3, 2, 2, 2, 1, 384, 168, 114,,,,, -7, 7, 6, 3, 2, 2, 2, 2, 128, 168, 114,,,,, -7, 7, 6, 3, 2, 2, 2, 2, 256, 168, 114,,,,, -7, 7, 6, 3, 2, 2, 2, 2, 384, 168, 114,,,,, -7, 7, 6, 3, 3, 3, 1, 1, 128, 165, 114,,,,, -7, 7, 6, 3, 3, 3, 1, 1, 256, 165, 114,,,,, -7, 7, 6, 3, 3, 3, 1, 1, 384, 165, 114,,,,, -7, 7, 6, 3, 3, 3, 1, 2, 128, 165, 114,,,,, -7, 7, 6, 3, 3, 3, 1, 2, 256, 165, 114,,,,, -7, 7, 6, 3, 3, 3, 1, 2, 384, 165, 114,,,,, -7, 7, 6, 3, 3, 3, 1, 3, 128, 165, 114,,,,, -7, 7, 6, 3, 3, 3, 1, 3, 256, 165, 114,,,,, -7, 7, 6, 3, 3, 3, 1, 3, 384, 165, 114,,,,, -7, 7, 6, 3, 3, 3, 2, 1, 128, 165, 114,,,,, -7, 7, 6, 3, 3, 3, 2, 1, 256, 165, 114,,,,, -7, 7, 6, 3, 3, 3, 2, 1, 384, 165, 114,,,,, -7, 7, 6, 3, 3, 3, 2, 2, 128, 165, 114,,,,, -7, 7, 6, 3, 3, 3, 2, 2, 256, 165, 114,,,,, -7, 7, 6, 3, 3, 3, 2, 2, 384, 165, 114,,,,, -7, 7, 6, 3, 3, 3, 2, 3, 128, 165, 114,,,,, -7, 7, 6, 3, 3, 3, 2, 3, 256, 165, 114,,,,, -7, 7, 6, 3, 3, 3, 2, 3, 384, 165, 114,,,,, -7, 7, 6, 3, 3, 3, 3, 1, 128, 165, 114,,,,, -7, 7, 6, 3, 3, 3, 3, 1, 256, 165, 114,,,,, -7, 7, 6, 3, 3, 3, 3, 1, 384, 165, 114,,,,, -7, 7, 6, 3, 3, 3, 3, 2, 128, 165, 114,,,,, -7, 7, 6, 3, 3, 3, 3, 2, 256, 165, 114,,,,, -7, 7, 6, 3, 3, 3, 3, 2, 384, 165, 114,,,,, -7, 7, 6, 3, 3, 3, 3, 3, 128, 165, 114,,,,, -7, 7, 6, 3, 3, 3, 3, 3, 256, 165, 114,,,,, -7, 7, 6, 3, 3, 3, 3, 3, 384, 165, 114,,,,, -7, 7, 6, 4, 1, 1, 1, 1, 128, 222, 150,,,,, -7, 7, 6, 4, 1, 1, 1, 1, 256, 222, 150,,,,, -7, 7, 6, 4, 1, 1, 1, 1, 384, 222, 150,,,,, -7, 7, 6, 4, 2, 2, 1, 1, 128, 222, 150,,,,, -7, 7, 6, 4, 2, 2, 1, 1, 256, 222, 150,,,,, -7, 7, 6, 4, 2, 2, 1, 1, 384, 222, 150,,,,, -7, 7, 6, 4, 2, 2, 1, 2, 128, 222, 150,,,,, -7, 7, 6, 4, 2, 2, 1, 2, 256, 222, 150,,,,, -7, 7, 6, 4, 2, 2, 1, 2, 384, 222, 150,,,,, -7, 7, 6, 4, 2, 2, 2, 1, 128, 222, 150,,,,, -7, 7, 6, 4, 2, 2, 2, 1, 256, 222, 150,,,,, -7, 7, 6, 4, 2, 2, 2, 1, 384, 222, 150,,,,, -7, 7, 6, 4, 2, 2, 2, 2, 128, 222, 150,,,,, -7, 7, 6, 4, 2, 2, 2, 2, 256, 222, 150,,,,, -7, 7, 6, 4, 2, 2, 2, 2, 384, 222, 150,,,,, -7, 7, 6, 4, 3, 3, 1, 1, 128, 218, 150,,,,, -7, 7, 6, 4, 3, 3, 1, 1, 256, 218, 150,,,,, -7, 7, 6, 4, 3, 3, 1, 1, 384, 218, 150,,,,, -7, 7, 6, 4, 3, 3, 1, 2, 128, 218, 150,,,,, -7, 7, 6, 4, 3, 3, 1, 2, 256, 218, 150,,,,, -7, 7, 6, 4, 3, 3, 1, 2, 384, 218, 150,,,,, -7, 7, 6, 4, 3, 3, 1, 3, 128, 218, 150,,,,, -7, 7, 6, 4, 3, 3, 1, 3, 256, 218, 150,,,,, -7, 7, 6, 4, 3, 3, 1, 3, 384, 218, 150,,,,, -7, 7, 6, 4, 3, 3, 2, 1, 128, 218, 150,,,,, -7, 7, 6, 4, 3, 3, 2, 1, 256, 218, 150,,,,, -7, 7, 6, 4, 3, 3, 2, 1, 384, 218, 150,,,,, -7, 7, 6, 4, 3, 3, 2, 2, 128, 218, 150,,,,, -7, 7, 6, 4, 3, 3, 2, 2, 256, 218, 150,,,,, -7, 7, 6, 4, 3, 3, 2, 2, 384, 218, 150,,,,, -7, 7, 6, 4, 3, 3, 2, 3, 128, 218, 150,,,,, -7, 7, 6, 4, 3, 3, 2, 3, 256, 218, 150,,,,, -7, 7, 6, 4, 3, 3, 2, 3, 384, 218, 150,,,,, -7, 7, 6, 4, 3, 3, 3, 1, 128, 218, 150,,,,, -7, 7, 6, 4, 3, 3, 3, 1, 256, 218, 150,,,,, -7, 7, 6, 4, 3, 3, 3, 1, 384, 218, 150,,,,, -7, 7, 6, 4, 3, 3, 3, 2, 128, 218, 150,,,,, -7, 7, 6, 4, 3, 3, 3, 2, 256, 218, 150,,,,, -7, 7, 6, 4, 3, 3, 3, 2, 384, 218, 150,,,,, -7, 7, 6, 4, 3, 3, 3, 3, 128, 218, 150,,,,, -7, 7, 6, 4, 3, 3, 3, 3, 256, 218, 150,,,,, -7, 7, 6, 4, 3, 3, 3, 3, 384, 218, 150,,,,, -7, 7, 6, 5, 1, 1, 1, 1, 128, 240, 186,,,,, -7, 7, 6, 5, 1, 1, 1, 1, 256, 240, 186,,,,, -7, 7, 6, 5, 1, 1, 1, 1, 384, 240, 186,,,,, -7, 7, 6, 5, 2, 2, 1, 1, 128, 240, 186,,,,, -7, 7, 6, 5, 2, 2, 1, 1, 256, 240, 186,,,,, -7, 7, 6, 5, 2, 2, 1, 1, 384, 240, 186,,,,, -7, 7, 6, 5, 2, 2, 1, 2, 128, 240, 186,,,,, -7, 7, 6, 5, 2, 2, 1, 2, 256, 240, 186,,,,, -7, 7, 6, 5, 2, 2, 1, 2, 384, 240, 186,,,,, -7, 7, 6, 5, 2, 2, 2, 1, 128, 240, 186,,,,, -7, 7, 6, 5, 2, 2, 2, 1, 256, 240, 186,,,,, -7, 7, 6, 5, 2, 2, 2, 1, 384, 240, 186,,,,, -7, 7, 6, 5, 2, 2, 2, 2, 128, 240, 186,,,,, -7, 7, 6, 5, 2, 2, 2, 2, 256, 240, 186,,,,, -7, 7, 6, 5, 2, 2, 2, 2, 384, 240, 186,,,,, -7, 7, 6, 5, 3, 3, 1, 1, 128, 240, 186,,,,, -7, 7, 6, 5, 3, 3, 1, 1, 256, 240, 186,,,,, -7, 7, 6, 5, 3, 3, 1, 1, 384, 240, 186,,,,, -7, 7, 6, 5, 3, 3, 1, 2, 128, 240, 186,,,,, -7, 7, 6, 5, 3, 3, 1, 2, 256, 240, 186,,,,, -7, 7, 6, 5, 3, 3, 1, 2, 384, 240, 186,,,,, -7, 7, 6, 5, 3, 3, 1, 3, 128, 240, 186,,,,, -7, 7, 6, 5, 3, 3, 1, 3, 256, 240, 186,,,,, -7, 7, 6, 5, 3, 3, 1, 3, 384, 240, 186,,,,, -7, 7, 6, 5, 3, 3, 2, 1, 128, 240, 186,,,,, -7, 7, 6, 5, 3, 3, 2, 1, 256, 240, 186,,,,, -7, 7, 6, 5, 3, 3, 2, 1, 384, 240, 186,,,,, -7, 7, 6, 5, 3, 3, 2, 2, 128, 240, 186,,,,, -7, 7, 6, 5, 3, 3, 2, 2, 256, 240, 186,,,,, -7, 7, 6, 5, 3, 3, 2, 2, 384, 240, 186,,,,, -7, 7, 6, 5, 3, 3, 2, 3, 128, 240, 186,,,,, -7, 7, 6, 5, 3, 3, 2, 3, 256, 240, 186,,,,, -7, 7, 6, 5, 3, 3, 2, 3, 384, 240, 186,,,,, -7, 7, 6, 5, 3, 3, 3, 1, 128, 240, 186,,,,, -7, 7, 6, 5, 3, 3, 3, 1, 256, 240, 186,,,,, -7, 7, 6, 5, 3, 3, 3, 1, 384, 240, 186,,,,, -7, 7, 6, 5, 3, 3, 3, 2, 128, 240, 186,,,,, -7, 7, 6, 5, 3, 3, 3, 2, 256, 240, 186,,,,, -7, 7, 6, 5, 3, 3, 3, 2, 384, 240, 186,,,,, -7, 7, 6, 5, 3, 3, 3, 3, 128, 240, 186,,,,, -7, 7, 6, 5, 3, 3, 3, 3, 256, 240, 186,,,,, -7, 7, 6, 5, 3, 3, 3, 3, 384, 240, 186,,,,, -7, 7, 6, 6, 1, 1, 1, 1, 128, 240, 222,,,,, -7, 7, 6, 6, 1, 1, 1, 1, 256, 240, 222,,,,, -7, 7, 6, 6, 1, 1, 1, 1, 384, 240, 222,,,,, -7, 7, 6, 6, 2, 2, 1, 1, 128, 240, 222,,,,, -7, 7, 6, 6, 2, 2, 1, 1, 256, 240, 222,,,,, -7, 7, 6, 6, 2, 2, 1, 1, 384, 240, 222,,,,, -7, 7, 6, 6, 2, 2, 1, 2, 128, 240, 222,,,,, -7, 7, 6, 6, 2, 2, 1, 2, 256, 240, 222,,,,, -7, 7, 6, 6, 2, 2, 1, 2, 384, 240, 222,,,,, -7, 7, 6, 6, 2, 2, 2, 1, 128, 240, 222,,,,, -7, 7, 6, 6, 2, 2, 2, 1, 256, 240, 222,,,,, -7, 7, 6, 6, 2, 2, 2, 1, 384, 240, 222,,,,, -7, 7, 6, 6, 2, 2, 2, 2, 128, 240, 222,,,,, -7, 7, 6, 6, 2, 2, 2, 2, 256, 240, 222,,,,, -7, 7, 6, 6, 2, 2, 2, 2, 384, 240, 222,,,,, -7, 7, 6, 6, 3, 3, 1, 1, 128, 240, 222,,,,, -7, 7, 6, 6, 3, 3, 1, 1, 256, 240, 222,,,,, -7, 7, 6, 6, 3, 3, 1, 1, 384, 240, 222,,,,, -7, 7, 6, 6, 3, 3, 1, 2, 128, 240, 222,,,,, -7, 7, 6, 6, 3, 3, 1, 2, 256, 240, 222,,,,, -7, 7, 6, 6, 3, 3, 1, 2, 384, 240, 222,,,,, -7, 7, 6, 6, 3, 3, 1, 3, 128, 240, 222,,,,, -7, 7, 6, 6, 3, 3, 1, 3, 256, 240, 222,,,,, -7, 7, 6, 6, 3, 3, 1, 3, 384, 240, 222,,,,, -7, 7, 6, 6, 3, 3, 2, 1, 128, 240, 222,,,,, -7, 7, 6, 6, 3, 3, 2, 1, 256, 240, 222,,,,, -7, 7, 6, 6, 3, 3, 2, 1, 384, 240, 222,,,,, -7, 7, 6, 6, 3, 3, 2, 2, 128, 240, 222,,,,, -7, 7, 6, 6, 3, 3, 2, 2, 256, 240, 222,,,,, -7, 7, 6, 6, 3, 3, 2, 2, 384, 240, 222,,,,, -7, 7, 6, 6, 3, 3, 2, 3, 128, 240, 222,,,,, -7, 7, 6, 6, 3, 3, 2, 3, 256, 240, 222,,,,, -7, 7, 6, 6, 3, 3, 2, 3, 384, 240, 222,,,,, -7, 7, 6, 6, 3, 3, 3, 1, 128, 240, 222,,,,, -7, 7, 6, 6, 3, 3, 3, 1, 256, 240, 222,,,,, -7, 7, 6, 6, 3, 3, 3, 1, 384, 240, 222,,,,, -7, 7, 6, 6, 3, 3, 3, 2, 128, 240, 222,,,,, -7, 7, 6, 6, 3, 3, 3, 2, 256, 240, 222,,,,, -7, 7, 6, 6, 3, 3, 3, 2, 384, 240, 222,,,,, -7, 7, 6, 6, 3, 3, 3, 3, 128, 240, 222,,,,, -7, 7, 6, 6, 3, 3, 3, 3, 256, 240, 222,,,,, -7, 7, 6, 6, 3, 3, 3, 3, 384, 240, 222,,,,, -7, 7, 6, 7, 1, 1, 1, 1, 128, 240, 240,,,,, -7, 7, 6, 7, 1, 1, 1, 1, 256, 240, 240,,,,, -7, 7, 6, 7, 1, 1, 1, 1, 384, 240, 240,,,,, -7, 7, 6, 7, 2, 2, 1, 1, 128, 240, 240,,,,, -7, 7, 6, 7, 2, 2, 1, 1, 256, 240, 240,,,,, -7, 7, 6, 7, 2, 2, 1, 1, 384, 240, 240,,,,, -7, 7, 6, 7, 2, 2, 1, 2, 128, 240, 240,,,,, -7, 7, 6, 7, 2, 2, 1, 2, 256, 240, 240,,,,, -7, 7, 6, 7, 2, 2, 1, 2, 384, 240, 240,,,,, -7, 7, 6, 7, 2, 2, 2, 1, 128, 240, 240,,,,, -7, 7, 6, 7, 2, 2, 2, 1, 256, 240, 240,,,,, -7, 7, 6, 7, 2, 2, 2, 1, 384, 240, 240,,,,, -7, 7, 6, 7, 2, 2, 2, 2, 128, 240, 240,,,,, -7, 7, 6, 7, 2, 2, 2, 2, 256, 240, 240,,,,, -7, 7, 6, 7, 2, 2, 2, 2, 384, 240, 240,,,,, -7, 7, 6, 7, 3, 3, 1, 1, 128, 240, 240,,,,, -7, 7, 6, 7, 3, 3, 1, 1, 256, 240, 240,,,,, -7, 7, 6, 7, 3, 3, 1, 1, 384, 240, 240,,,,, -7, 7, 6, 7, 3, 3, 1, 2, 128, 240, 240,,,,, -7, 7, 6, 7, 3, 3, 1, 2, 256, 240, 240,,,,, -7, 7, 6, 7, 3, 3, 1, 2, 384, 240, 240,,,,, -7, 7, 6, 7, 3, 3, 1, 3, 128, 240, 240,,,,, -7, 7, 6, 7, 3, 3, 1, 3, 256, 240, 240,,,,, -7, 7, 6, 7, 3, 3, 1, 3, 384, 240, 240,,,,, -7, 7, 6, 7, 3, 3, 2, 1, 128, 240, 240,,,,, -7, 7, 6, 7, 3, 3, 2, 1, 256, 240, 240,,,,, -7, 7, 6, 7, 3, 3, 2, 1, 384, 240, 240,,,,, -7, 7, 6, 7, 3, 3, 2, 2, 128, 240, 240,,,,, -7, 7, 6, 7, 3, 3, 2, 2, 256, 240, 240,,,,, -7, 7, 6, 7, 3, 3, 2, 2, 384, 240, 240,,,,, -7, 7, 6, 7, 3, 3, 2, 3, 128, 240, 240,,,,, -7, 7, 6, 7, 3, 3, 2, 3, 256, 240, 240,,,,, -7, 7, 6, 7, 3, 3, 2, 3, 384, 240, 240,,,,, -7, 7, 6, 7, 3, 3, 3, 1, 128, 240, 240,,,,, -7, 7, 6, 7, 3, 3, 3, 1, 256, 240, 240,,,,, -7, 7, 6, 7, 3, 3, 3, 1, 384, 240, 240,,,,, -7, 7, 6, 7, 3, 3, 3, 2, 128, 240, 240,,,,, -7, 7, 6, 7, 3, 3, 3, 2, 256, 240, 240,,,,, -7, 7, 6, 7, 3, 3, 3, 2, 384, 240, 240,,,,, -7, 7, 6, 7, 3, 3, 3, 3, 128, 240, 240,,,,, -7, 7, 6, 7, 3, 3, 3, 3, 256, 240, 240,,,,, -7, 7, 6, 7, 3, 3, 3, 3, 384, 240, 240,,,,, -7, 7, 7, 1, 1, 1, 1, 1, 128, 60, 42,,,,, -7, 7, 7, 1, 1, 1, 1, 1, 256, 60, 42,,,,, -7, 7, 7, 1, 1, 1, 1, 1, 384, 60, 42,,,,, -7, 7, 7, 1, 2, 2, 1, 1, 128, 60, 42,,,,, -7, 7, 7, 1, 2, 2, 1, 1, 256, 60, 42,,,,, -7, 7, 7, 1, 2, 2, 1, 1, 384, 60, 42,,,,, -7, 7, 7, 1, 2, 2, 1, 2, 128, 60, 42,,,,, -7, 7, 7, 1, 2, 2, 1, 2, 256, 60, 42,,,,, -7, 7, 7, 1, 2, 2, 1, 2, 384, 60, 42,,,,, -7, 7, 7, 1, 2, 2, 2, 1, 128, 60, 42,,,,, -7, 7, 7, 1, 2, 2, 2, 1, 256, 60, 42,,,,, -7, 7, 7, 1, 2, 2, 2, 1, 384, 60, 42,,,,, -7, 7, 7, 1, 2, 2, 2, 2, 128, 60, 42,,,,, -7, 7, 7, 1, 2, 2, 2, 2, 256, 60, 42,,,,, -7, 7, 7, 1, 2, 2, 2, 2, 384, 60, 42,,,,, -7, 7, 7, 1, 3, 3, 1, 1, 128, 59, 42,,,,, -7, 7, 7, 1, 3, 3, 1, 1, 256, 59, 42,,,,, -7, 7, 7, 1, 3, 3, 1, 1, 384, 59, 42,,,,, -7, 7, 7, 1, 3, 3, 1, 2, 128, 59, 42,,,,, -7, 7, 7, 1, 3, 3, 1, 2, 256, 59, 42,,,,, -7, 7, 7, 1, 3, 3, 1, 2, 384, 59, 42,,,,, -7, 7, 7, 1, 3, 3, 1, 3, 128, 59, 42,,,,, -7, 7, 7, 1, 3, 3, 1, 3, 256, 59, 42,,,,, -7, 7, 7, 1, 3, 3, 1, 3, 384, 59, 42,,,,, -7, 7, 7, 1, 3, 3, 2, 1, 128, 59, 42,,,,, -7, 7, 7, 1, 3, 3, 2, 1, 256, 59, 42,,,,, -7, 7, 7, 1, 3, 3, 2, 1, 384, 59, 42,,,,, -7, 7, 7, 1, 3, 3, 2, 2, 128, 59, 42,,,,, -7, 7, 7, 1, 3, 3, 2, 2, 256, 59, 42,,,,, -7, 7, 7, 1, 3, 3, 2, 2, 384, 59, 42,,,,, -7, 7, 7, 1, 3, 3, 2, 3, 128, 59, 42,,,,, -7, 7, 7, 1, 3, 3, 2, 3, 256, 59, 42,,,,, -7, 7, 7, 1, 3, 3, 2, 3, 384, 59, 42,,,,, -7, 7, 7, 1, 3, 3, 3, 1, 128, 59, 42,,,,, -7, 7, 7, 1, 3, 3, 3, 1, 256, 59, 42,,,,, -7, 7, 7, 1, 3, 3, 3, 1, 384, 59, 42,,,,, -7, 7, 7, 1, 3, 3, 3, 2, 128, 59, 42,,,,, -7, 7, 7, 1, 3, 3, 3, 2, 256, 59, 42,,,,, -7, 7, 7, 1, 3, 3, 3, 2, 384, 59, 42,,,,, -7, 7, 7, 1, 3, 3, 3, 3, 128, 59, 42,,,,, -7, 7, 7, 1, 3, 3, 3, 3, 256, 59, 42,,,,, -7, 7, 7, 1, 3, 3, 3, 3, 384, 59, 42,,,,, -7, 7, 7, 2, 1, 1, 1, 1, 128, 114, 78,,,,, -7, 7, 7, 2, 1, 1, 1, 1, 256, 114, 78,,,,, -7, 7, 7, 2, 1, 1, 1, 1, 384, 114, 78,,,,, -7, 7, 7, 2, 2, 2, 1, 1, 128, 114, 78,,,,, -7, 7, 7, 2, 2, 2, 1, 1, 256, 114, 78,,,,, -7, 7, 7, 2, 2, 2, 1, 1, 384, 114, 78,,,,, -7, 7, 7, 2, 2, 2, 1, 2, 128, 114, 78,,,,, -7, 7, 7, 2, 2, 2, 1, 2, 256, 114, 78,,,,, -7, 7, 7, 2, 2, 2, 1, 2, 384, 114, 78,,,,, -7, 7, 7, 2, 2, 2, 2, 1, 128, 114, 78,,,,, -7, 7, 7, 2, 2, 2, 2, 1, 256, 114, 78,,,,, -7, 7, 7, 2, 2, 2, 2, 1, 384, 114, 78,,,,, -7, 7, 7, 2, 2, 2, 2, 2, 128, 114, 78,,,,, -7, 7, 7, 2, 2, 2, 2, 2, 256, 114, 78,,,,, -7, 7, 7, 2, 2, 2, 2, 2, 384, 114, 78,,,,, -7, 7, 7, 2, 3, 3, 1, 1, 128, 112, 78,,,,, -7, 7, 7, 2, 3, 3, 1, 1, 256, 112, 78,,,,, -7, 7, 7, 2, 3, 3, 1, 1, 384, 112, 78,,,,, -7, 7, 7, 2, 3, 3, 1, 2, 128, 112, 78,,,,, -7, 7, 7, 2, 3, 3, 1, 2, 256, 112, 78,,,,, -7, 7, 7, 2, 3, 3, 1, 2, 384, 112, 78,,,,, -7, 7, 7, 2, 3, 3, 1, 3, 128, 112, 78,,,,, -7, 7, 7, 2, 3, 3, 1, 3, 256, 112, 78,,,,, -7, 7, 7, 2, 3, 3, 1, 3, 384, 112, 78,,,,, -7, 7, 7, 2, 3, 3, 2, 1, 128, 112, 78,,,,, -7, 7, 7, 2, 3, 3, 2, 1, 256, 112, 78,,,,, -7, 7, 7, 2, 3, 3, 2, 1, 384, 112, 78,,,,, -7, 7, 7, 2, 3, 3, 2, 2, 128, 112, 78,,,,, -7, 7, 7, 2, 3, 3, 2, 2, 256, 112, 78,,,,, -7, 7, 7, 2, 3, 3, 2, 2, 384, 112, 78,,,,, -7, 7, 7, 2, 3, 3, 2, 3, 128, 112, 78,,,,, -7, 7, 7, 2, 3, 3, 2, 3, 256, 112, 78,,,,, -7, 7, 7, 2, 3, 3, 2, 3, 384, 112, 78,,,,, -7, 7, 7, 2, 3, 3, 3, 1, 128, 112, 78,,,,, -7, 7, 7, 2, 3, 3, 3, 1, 256, 112, 78,,,,, -7, 7, 7, 2, 3, 3, 3, 1, 384, 112, 78,,,,, -7, 7, 7, 2, 3, 3, 3, 2, 128, 112, 78,,,,, -7, 7, 7, 2, 3, 3, 3, 2, 256, 112, 78,,,,, -7, 7, 7, 2, 3, 3, 3, 2, 384, 112, 78,,,,, -7, 7, 7, 2, 3, 3, 3, 3, 128, 112, 78,,,,, -7, 7, 7, 2, 3, 3, 3, 3, 256, 112, 78,,,,, -7, 7, 7, 2, 3, 3, 3, 3, 384, 112, 78,,,,, -7, 7, 7, 3, 1, 1, 1, 1, 128, 168, 114,,,,, -7, 7, 7, 3, 1, 1, 1, 1, 256, 168, 114,,,,, -7, 7, 7, 3, 1, 1, 1, 1, 384, 168, 114,,,,, -7, 7, 7, 3, 2, 2, 1, 1, 128, 168, 114,,,,, -7, 7, 7, 3, 2, 2, 1, 1, 256, 168, 114,,,,, -7, 7, 7, 3, 2, 2, 1, 1, 384, 168, 114,,,,, -7, 7, 7, 3, 2, 2, 1, 2, 128, 168, 114,,,,, -7, 7, 7, 3, 2, 2, 1, 2, 256, 168, 114,,,,, -7, 7, 7, 3, 2, 2, 1, 2, 384, 168, 114,,,,, -7, 7, 7, 3, 2, 2, 2, 1, 128, 168, 114,,,,, -7, 7, 7, 3, 2, 2, 2, 1, 256, 168, 114,,,,, -7, 7, 7, 3, 2, 2, 2, 1, 384, 168, 114,,,,, -7, 7, 7, 3, 2, 2, 2, 2, 128, 168, 114,,,,, -7, 7, 7, 3, 2, 2, 2, 2, 256, 168, 114,,,,, -7, 7, 7, 3, 2, 2, 2, 2, 384, 168, 114,,,,, -7, 7, 7, 3, 3, 3, 1, 1, 128, 165, 114,,,,, -7, 7, 7, 3, 3, 3, 1, 1, 256, 165, 114,,,,, -7, 7, 7, 3, 3, 3, 1, 1, 384, 165, 114,,,,, -7, 7, 7, 3, 3, 3, 1, 2, 128, 165, 114,,,,, -7, 7, 7, 3, 3, 3, 1, 2, 256, 165, 114,,,,, -7, 7, 7, 3, 3, 3, 1, 2, 384, 165, 114,,,,, -7, 7, 7, 3, 3, 3, 1, 3, 128, 165, 114,,,,, -7, 7, 7, 3, 3, 3, 1, 3, 256, 165, 114,,,,, -7, 7, 7, 3, 3, 3, 1, 3, 384, 165, 114,,,,, -7, 7, 7, 3, 3, 3, 2, 1, 128, 165, 114,,,,, -7, 7, 7, 3, 3, 3, 2, 1, 256, 165, 114,,,,, -7, 7, 7, 3, 3, 3, 2, 1, 384, 165, 114,,,,, -7, 7, 7, 3, 3, 3, 2, 2, 128, 165, 114,,,,, -7, 7, 7, 3, 3, 3, 2, 2, 256, 165, 114,,,,, -7, 7, 7, 3, 3, 3, 2, 2, 384, 165, 114,,,,, -7, 7, 7, 3, 3, 3, 2, 3, 128, 165, 114,,,,, -7, 7, 7, 3, 3, 3, 2, 3, 256, 165, 114,,,,, -7, 7, 7, 3, 3, 3, 2, 3, 384, 165, 114,,,,, -7, 7, 7, 3, 3, 3, 3, 1, 128, 165, 114,,,,, -7, 7, 7, 3, 3, 3, 3, 1, 256, 165, 114,,,,, -7, 7, 7, 3, 3, 3, 3, 1, 384, 165, 114,,,,, -7, 7, 7, 3, 3, 3, 3, 2, 128, 165, 114,,,,, -7, 7, 7, 3, 3, 3, 3, 2, 256, 165, 114,,,,, -7, 7, 7, 3, 3, 3, 3, 2, 384, 165, 114,,,,, -7, 7, 7, 3, 3, 3, 3, 3, 128, 165, 114,,,,, -7, 7, 7, 3, 3, 3, 3, 3, 256, 165, 114,,,,, -7, 7, 7, 3, 3, 3, 3, 3, 384, 165, 114,,,,, -7, 7, 7, 4, 1, 1, 1, 1, 128, 222, 150,,,,, -7, 7, 7, 4, 1, 1, 1, 1, 256, 222, 150,,,,, -7, 7, 7, 4, 1, 1, 1, 1, 384, 222, 150,,,,, -7, 7, 7, 4, 2, 2, 1, 1, 128, 222, 150,,,,, -7, 7, 7, 4, 2, 2, 1, 1, 256, 222, 150,,,,, -7, 7, 7, 4, 2, 2, 1, 1, 384, 222, 150,,,,, -7, 7, 7, 4, 2, 2, 1, 2, 128, 222, 150,,,,, -7, 7, 7, 4, 2, 2, 1, 2, 256, 222, 150,,,,, -7, 7, 7, 4, 2, 2, 1, 2, 384, 222, 150,,,,, -7, 7, 7, 4, 2, 2, 2, 1, 128, 222, 150,,,,, -7, 7, 7, 4, 2, 2, 2, 1, 256, 222, 150,,,,, -7, 7, 7, 4, 2, 2, 2, 1, 384, 222, 150,,,,, -7, 7, 7, 4, 2, 2, 2, 2, 128, 222, 150,,,,, -7, 7, 7, 4, 2, 2, 2, 2, 256, 222, 150,,,,, -7, 7, 7, 4, 2, 2, 2, 2, 384, 222, 150,,,,, -7, 7, 7, 4, 3, 3, 1, 1, 128, 218, 150,,,,, -7, 7, 7, 4, 3, 3, 1, 1, 256, 218, 150,,,,, -7, 7, 7, 4, 3, 3, 1, 1, 384, 218, 150,,,,, -7, 7, 7, 4, 3, 3, 1, 2, 128, 218, 150,,,,, -7, 7, 7, 4, 3, 3, 1, 2, 256, 218, 150,,,,, -7, 7, 7, 4, 3, 3, 1, 2, 384, 218, 150,,,,, -7, 7, 7, 4, 3, 3, 1, 3, 128, 218, 150,,,,, -7, 7, 7, 4, 3, 3, 1, 3, 256, 218, 150,,,,, -7, 7, 7, 4, 3, 3, 1, 3, 384, 218, 150,,,,, -7, 7, 7, 4, 3, 3, 2, 1, 128, 218, 150,,,,, -7, 7, 7, 4, 3, 3, 2, 1, 256, 218, 150,,,,, -7, 7, 7, 4, 3, 3, 2, 1, 384, 218, 150,,,,, -7, 7, 7, 4, 3, 3, 2, 2, 128, 218, 150,,,,, -7, 7, 7, 4, 3, 3, 2, 2, 256, 218, 150,,,,, -7, 7, 7, 4, 3, 3, 2, 2, 384, 218, 150,,,,, -7, 7, 7, 4, 3, 3, 2, 3, 128, 218, 150,,,,, -7, 7, 7, 4, 3, 3, 2, 3, 256, 218, 150,,,,, -7, 7, 7, 4, 3, 3, 2, 3, 384, 218, 150,,,,, -7, 7, 7, 4, 3, 3, 3, 1, 128, 218, 150,,,,, -7, 7, 7, 4, 3, 3, 3, 1, 256, 218, 150,,,,, -7, 7, 7, 4, 3, 3, 3, 1, 384, 218, 150,,,,, -7, 7, 7, 4, 3, 3, 3, 2, 128, 218, 150,,,,, -7, 7, 7, 4, 3, 3, 3, 2, 256, 218, 150,,,,, -7, 7, 7, 4, 3, 3, 3, 2, 384, 218, 150,,,,, -7, 7, 7, 4, 3, 3, 3, 3, 128, 218, 150,,,,, -7, 7, 7, 4, 3, 3, 3, 3, 256, 218, 150,,,,, -7, 7, 7, 4, 3, 3, 3, 3, 384, 218, 150,,,,, -7, 7, 7, 5, 1, 1, 1, 1, 128, 240, 186,,,,, -7, 7, 7, 5, 1, 1, 1, 1, 256, 240, 186,,,,, -7, 7, 7, 5, 1, 1, 1, 1, 384, 240, 186,,,,, -7, 7, 7, 5, 2, 2, 1, 1, 128, 240, 186,,,,, -7, 7, 7, 5, 2, 2, 1, 1, 256, 240, 186,,,,, -7, 7, 7, 5, 2, 2, 1, 1, 384, 240, 186,,,,, -7, 7, 7, 5, 2, 2, 1, 2, 128, 240, 186,,,,, -7, 7, 7, 5, 2, 2, 1, 2, 256, 240, 186,,,,, -7, 7, 7, 5, 2, 2, 1, 2, 384, 240, 186,,,,, -7, 7, 7, 5, 2, 2, 2, 1, 128, 240, 186,,,,, -7, 7, 7, 5, 2, 2, 2, 1, 256, 240, 186,,,,, -7, 7, 7, 5, 2, 2, 2, 1, 384, 240, 186,,,,, -7, 7, 7, 5, 2, 2, 2, 2, 128, 240, 186,,,,, -7, 7, 7, 5, 2, 2, 2, 2, 256, 240, 186,,,,, -7, 7, 7, 5, 2, 2, 2, 2, 384, 240, 186,,,,, -7, 7, 7, 5, 3, 3, 1, 1, 128, 240, 186,,,,, -7, 7, 7, 5, 3, 3, 1, 1, 256, 240, 186,,,,, -7, 7, 7, 5, 3, 3, 1, 1, 384, 240, 186,,,,, -7, 7, 7, 5, 3, 3, 1, 2, 128, 240, 186,,,,, -7, 7, 7, 5, 3, 3, 1, 2, 256, 240, 186,,,,, -7, 7, 7, 5, 3, 3, 1, 2, 384, 240, 186,,,,, -7, 7, 7, 5, 3, 3, 1, 3, 128, 240, 186,,,,, -7, 7, 7, 5, 3, 3, 1, 3, 256, 240, 186,,,,, -7, 7, 7, 5, 3, 3, 1, 3, 384, 240, 186,,,,, -7, 7, 7, 5, 3, 3, 2, 1, 128, 240, 186,,,,, -7, 7, 7, 5, 3, 3, 2, 1, 256, 240, 186,,,,, -7, 7, 7, 5, 3, 3, 2, 1, 384, 240, 186,,,,, -7, 7, 7, 5, 3, 3, 2, 2, 128, 240, 186,,,,, -7, 7, 7, 5, 3, 3, 2, 2, 256, 240, 186,,,,, -7, 7, 7, 5, 3, 3, 2, 2, 384, 240, 186,,,,, -7, 7, 7, 5, 3, 3, 2, 3, 128, 240, 186,,,,, -7, 7, 7, 5, 3, 3, 2, 3, 256, 240, 186,,,,, -7, 7, 7, 5, 3, 3, 2, 3, 384, 240, 186,,,,, -7, 7, 7, 5, 3, 3, 3, 1, 128, 240, 186,,,,, -7, 7, 7, 5, 3, 3, 3, 1, 256, 240, 186,,,,, -7, 7, 7, 5, 3, 3, 3, 1, 384, 240, 186,,,,, -7, 7, 7, 5, 3, 3, 3, 2, 128, 240, 186,,,,, -7, 7, 7, 5, 3, 3, 3, 2, 256, 240, 186,,,,, -7, 7, 7, 5, 3, 3, 3, 2, 384, 240, 186,,,,, -7, 7, 7, 5, 3, 3, 3, 3, 128, 240, 186,,,,, -7, 7, 7, 5, 3, 3, 3, 3, 256, 240, 186,,,,, -7, 7, 7, 5, 3, 3, 3, 3, 384, 240, 186,,,,, -7, 7, 7, 6, 1, 1, 1, 1, 128, 240, 222,,,,, -7, 7, 7, 6, 1, 1, 1, 1, 256, 240, 222,,,,, -7, 7, 7, 6, 1, 1, 1, 1, 384, 240, 222,,,,, -7, 7, 7, 6, 2, 2, 1, 1, 128, 240, 222,,,,, -7, 7, 7, 6, 2, 2, 1, 1, 256, 240, 222,,,,, -7, 7, 7, 6, 2, 2, 1, 1, 384, 240, 222,,,,, -7, 7, 7, 6, 2, 2, 1, 2, 128, 240, 222,,,,, -7, 7, 7, 6, 2, 2, 1, 2, 256, 240, 222,,,,, -7, 7, 7, 6, 2, 2, 1, 2, 384, 240, 222,,,,, -7, 7, 7, 6, 2, 2, 2, 1, 128, 240, 222,,,,, -7, 7, 7, 6, 2, 2, 2, 1, 256, 240, 222,,,,, -7, 7, 7, 6, 2, 2, 2, 1, 384, 240, 222,,,,, -7, 7, 7, 6, 2, 2, 2, 2, 128, 240, 222,,,,, -7, 7, 7, 6, 2, 2, 2, 2, 256, 240, 222,,,,, -7, 7, 7, 6, 2, 2, 2, 2, 384, 240, 222,,,,, -7, 7, 7, 6, 3, 3, 1, 1, 128, 240, 222,,,,, -7, 7, 7, 6, 3, 3, 1, 1, 256, 240, 222,,,,, -7, 7, 7, 6, 3, 3, 1, 1, 384, 240, 222,,,,, -7, 7, 7, 6, 3, 3, 1, 2, 128, 240, 222,,,,, -7, 7, 7, 6, 3, 3, 1, 2, 256, 240, 222,,,,, -7, 7, 7, 6, 3, 3, 1, 2, 384, 240, 222,,,,, -7, 7, 7, 6, 3, 3, 1, 3, 128, 240, 222,,,,, -7, 7, 7, 6, 3, 3, 1, 3, 256, 240, 222,,,,, -7, 7, 7, 6, 3, 3, 1, 3, 384, 240, 222,,,,, -7, 7, 7, 6, 3, 3, 2, 1, 128, 240, 222,,,,, -7, 7, 7, 6, 3, 3, 2, 1, 256, 240, 222,,,,, -7, 7, 7, 6, 3, 3, 2, 1, 384, 240, 222,,,,, -7, 7, 7, 6, 3, 3, 2, 2, 128, 240, 222,,,,, -7, 7, 7, 6, 3, 3, 2, 2, 256, 240, 222,,,,, -7, 7, 7, 6, 3, 3, 2, 2, 384, 240, 222,,,,, -7, 7, 7, 6, 3, 3, 2, 3, 128, 240, 222,,,,, -7, 7, 7, 6, 3, 3, 2, 3, 256, 240, 222,,,,, -7, 7, 7, 6, 3, 3, 2, 3, 384, 240, 222,,,,, -7, 7, 7, 6, 3, 3, 3, 1, 128, 240, 222,,,,, -7, 7, 7, 6, 3, 3, 3, 1, 256, 240, 222,,,,, -7, 7, 7, 6, 3, 3, 3, 1, 384, 240, 222,,,,, -7, 7, 7, 6, 3, 3, 3, 2, 128, 240, 222,,,,, -7, 7, 7, 6, 3, 3, 3, 2, 256, 240, 222,,,,, -7, 7, 7, 6, 3, 3, 3, 2, 384, 240, 222,,,,, -7, 7, 7, 6, 3, 3, 3, 3, 128, 240, 222,,,,, -7, 7, 7, 6, 3, 3, 3, 3, 256, 240, 222,,,,, -7, 7, 7, 6, 3, 3, 3, 3, 384, 240, 222,,,,, -7, 7, 7, 7, 1, 1, 1, 1, 128, 240, 240,,,,, -7, 7, 7, 7, 1, 1, 1, 1, 256, 240, 240,,,,, -7, 7, 7, 7, 1, 1, 1, 1, 384, 240, 240,,,,, -7, 7, 7, 7, 2, 2, 1, 1, 128, 240, 240,,,,, -7, 7, 7, 7, 2, 2, 1, 1, 256, 240, 240,,,,, -7, 7, 7, 7, 2, 2, 1, 1, 384, 240, 240,,,,, -7, 7, 7, 7, 2, 2, 1, 2, 128, 240, 240,,,,, -7, 7, 7, 7, 2, 2, 1, 2, 256, 240, 240,,,,, -7, 7, 7, 7, 2, 2, 1, 2, 384, 240, 240,,,,, -7, 7, 7, 7, 2, 2, 2, 1, 128, 240, 240,,,,, -7, 7, 7, 7, 2, 2, 2, 1, 256, 240, 240,,,,, -7, 7, 7, 7, 2, 2, 2, 1, 384, 240, 240,,,,, -7, 7, 7, 7, 2, 2, 2, 2, 128, 240, 240,,,,, -7, 7, 7, 7, 2, 2, 2, 2, 256, 240, 240,,,,, -7, 7, 7, 7, 2, 2, 2, 2, 384, 240, 240,,,,, -7, 7, 7, 7, 3, 3, 1, 1, 128, 240, 240,,,,, -7, 7, 7, 7, 3, 3, 1, 1, 256, 240, 240,,,,, -7, 7, 7, 7, 3, 3, 1, 1, 384, 240, 240,,,,, -7, 7, 7, 7, 3, 3, 1, 2, 128, 240, 240,,,,, -7, 7, 7, 7, 3, 3, 1, 2, 256, 240, 240,,,,, -7, 7, 7, 7, 3, 3, 1, 2, 384, 240, 240,,,,, -7, 7, 7, 7, 3, 3, 1, 3, 128, 240, 240,,,,, -7, 7, 7, 7, 3, 3, 1, 3, 256, 240, 240,,,,, -7, 7, 7, 7, 3, 3, 1, 3, 384, 240, 240,,,,, -7, 7, 7, 7, 3, 3, 2, 1, 128, 240, 240,,,,, -7, 7, 7, 7, 3, 3, 2, 1, 256, 240, 240,,,,, -7, 7, 7, 7, 3, 3, 2, 1, 384, 240, 240,,,,, -7, 7, 7, 7, 3, 3, 2, 2, 128, 240, 240,,,,, -7, 7, 7, 7, 3, 3, 2, 2, 256, 240, 240,,,,, -7, 7, 7, 7, 3, 3, 2, 2, 384, 240, 240,,,,, -7, 7, 7, 7, 3, 3, 2, 3, 128, 240, 240,,,,, -7, 7, 7, 7, 3, 3, 2, 3, 256, 240, 240,,,,, -7, 7, 7, 7, 3, 3, 2, 3, 384, 240, 240,,,,, -7, 7, 7, 7, 3, 3, 3, 1, 128, 240, 240,,,,, -7, 7, 7, 7, 3, 3, 3, 1, 256, 240, 240,,,,, -7, 7, 7, 7, 3, 3, 3, 1, 384, 240, 240,,,,, -7, 7, 7, 7, 3, 3, 3, 2, 128, 240, 240,,,,, -7, 7, 7, 7, 3, 3, 3, 2, 256, 240, 240,,,,, -7, 7, 7, 7, 3, 3, 3, 2, 384, 240, 240,,,,, -7, 7, 7, 7, 3, 3, 3, 3, 128, 240, 240,,,,, -7, 7, 7, 7, 3, 3, 3, 3, 256, 240, 240,,,,, -7, 7, 7, 7, 3, 3, 3, 3, 384, 240, 240,,,,, \ No newline at end of file diff --git a/docs/articles_en/openvino_workflow/running_inference_with_openvino/Device_Plugins/assets/GNA_Maximum_Input_Tensor_Widths_i8.csv b/docs/articles_en/openvino_workflow/running_inference_with_openvino/Device_Plugins/assets/GNA_Maximum_Input_Tensor_Widths_i8.csv deleted file mode 100644 index 64ca2b2cb93beb..00000000000000 --- a/docs/articles_en/openvino_workflow/running_inference_with_openvino/Device_Plugins/assets/GNA_Maximum_Input_Tensor_Widths_i8.csv +++ /dev/null @@ -1,2353 +0,0 @@ -KH, KW, SH, SW, PH, PW, SH, SW, H, W (Ci=8/Co=256), W (Ci=16/Co=256), W (Ci=32/Co=256), W (Ci=64/Co=256), W (Ci=128/Co=256),W (Ci=256/Co=256), W (Ci=384/Co=256) -1, 1, 1, 1, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240, 240, 240 -1, 1, 1, 1, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240, 240, 170 -1, 1, 1, 1, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240, 170, 113 -1, 2, 1, 1, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240, 240, 240 -1, 2, 1, 1, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240, 240, 170 -1, 2, 1, 1, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240, 170, 113 -1, 2, 1, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240, 240, 240 -1, 2, 1, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240, 240, 170 -1, 2, 1, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240, 170, 113 -1, 3, 1, 1, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -1, 3, 1, 1, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -1, 3, 1, 1, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -1, 3, 1, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -1, 3, 1, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -1, 3, 1, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -1, 3, 1, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -1, 3, 1, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -1, 3, 1, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -1, 4, 1, 1, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -1, 4, 1, 1, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -1, 4, 1, 1, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -1, 4, 1, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -1, 4, 1, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -1, 4, 1, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -1, 4, 1, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -1, 4, 1, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -1, 4, 1, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -1, 4, 1, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -1, 4, 1, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -1, 4, 1, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -1, 5, 1, 1, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -1, 5, 1, 1, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -1, 5, 1, 1, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -1, 5, 1, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -1, 5, 1, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -1, 5, 1, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -1, 5, 1, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -1, 5, 1, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -1, 5, 1, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -1, 5, 1, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -1, 5, 1, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -1, 5, 1, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -1, 5, 1, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -1, 5, 1, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -1, 5, 1, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -1, 6, 1, 1, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -1, 6, 1, 1, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -1, 6, 1, 1, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -1, 6, 1, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -1, 6, 1, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -1, 6, 1, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -1, 6, 1, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -1, 6, 1, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -1, 6, 1, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -1, 6, 1, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -1, 6, 1, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -1, 6, 1, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -1, 6, 1, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -1, 6, 1, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -1, 6, 1, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -1, 6, 1, 6, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -1, 6, 1, 6, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -1, 6, 1, 6, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -1, 7, 1, 1, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -1, 7, 1, 1, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -1, 7, 1, 1, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -1, 7, 1, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -1, 7, 1, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -1, 7, 1, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -1, 7, 1, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -1, 7, 1, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -1, 7, 1, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -1, 7, 1, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -1, 7, 1, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -1, 7, 1, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -1, 7, 1, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -1, 7, 1, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -1, 7, 1, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -1, 7, 1, 6, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -1, 7, 1, 6, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -1, 7, 1, 6, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -1, 7, 1, 7, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -1, 7, 1, 7, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -1, 7, 1, 7, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 1, 1, 1, 1, 1, 1, 1, 128, 192, 192, 192, 192, 192, 192, 192 -2, 1, 1, 1, 1, 1, 1, 1, 256, 192, 192, 192, 192, 192, 192, 170 -2, 1, 1, 1, 1, 1, 1, 1, 384, 192, 192, 192, 192, 192, 170, 113 -2, 1, 2, 1, 1, 1, 1, 1, 128, 192, 192, 192, 192, 192, 192, 192 -2, 1, 2, 1, 1, 1, 1, 1, 256, 192, 192, 192, 192, 192, 192, 170 -2, 1, 2, 1, 1, 1, 1, 1, 384, 192, 192, 192, 192, 192, 170, 113 -2, 2, 1, 1, 1, 1, 1, 1, 128, 193, 193, 193, 193, 193, 193, 129 -2, 2, 1, 1, 1, 1, 1, 1, 256, 193, 193, 193, 193, 193, 193, 129 -2, 2, 1, 1, 1, 1, 1, 1, 384, 193, 193, 193, 193, 193, 170, 113 -2, 2, 1, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240, 240, 240 -2, 2, 1, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240, 240, 170 -2, 2, 1, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240, 170, 113 -2, 2, 2, 1, 1, 1, 1, 1, 128, 193, 193, 193, 193, 193, 193, 129 -2, 2, 2, 1, 1, 1, 1, 1, 256, 193, 193, 193, 193, 193, 193, 129 -2, 2, 2, 1, 1, 1, 1, 1, 384, 193, 193, 193, 193, 193, 170, 113 -2, 2, 2, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240, 240, 240 -2, 2, 2, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240, 240, 170 -2, 2, 2, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240, 170, 113 -2, 3, 1, 1, 1, 1, 1, 1, 128, 194, 194, 194, 194, 194,, -2, 3, 1, 1, 1, 1, 1, 1, 256, 194, 194, 194, 194, 194,, -2, 3, 1, 1, 1, 1, 1, 1, 384, 194, 194, 194, 194, 194,, -2, 3, 1, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -2, 3, 1, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -2, 3, 1, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -2, 3, 1, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -2, 3, 1, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -2, 3, 1, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -2, 3, 2, 1, 1, 1, 1, 1, 128, 194, 194, 194, 194, 194,, -2, 3, 2, 1, 1, 1, 1, 1, 256, 194, 194, 194, 194, 194,, -2, 3, 2, 1, 1, 1, 1, 1, 384, 194, 194, 194, 194, 194,, -2, 3, 2, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -2, 3, 2, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -2, 3, 2, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -2, 3, 2, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -2, 3, 2, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -2, 3, 2, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -2, 4, 1, 1, 1, 1, 1, 1, 128, 195, 195, 195, 195, 195,, -2, 4, 1, 1, 1, 1, 1, 1, 256, 195, 195, 195, 195, 195,, -2, 4, 1, 1, 1, 1, 1, 1, 384, 195, 195, 195, 195, 195,, -2, 4, 1, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -2, 4, 1, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -2, 4, 1, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -2, 4, 1, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -2, 4, 1, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -2, 4, 1, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -2, 4, 1, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -2, 4, 1, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -2, 4, 1, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -2, 4, 2, 1, 1, 1, 1, 1, 128, 195, 195, 195, 195, 195,, -2, 4, 2, 1, 1, 1, 1, 1, 256, 195, 195, 195, 195, 195,, -2, 4, 2, 1, 1, 1, 1, 1, 384, 195, 195, 195, 195, 195,, -2, 4, 2, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -2, 4, 2, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -2, 4, 2, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -2, 4, 2, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -2, 4, 2, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -2, 4, 2, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -2, 4, 2, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -2, 4, 2, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -2, 4, 2, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -2, 5, 1, 1, 1, 1, 1, 1, 128, 196, 196, 196, 196, 132,, -2, 5, 1, 1, 1, 1, 1, 1, 256, 196, 196, 196, 196, 132,, -2, 5, 1, 1, 1, 1, 1, 1, 384, 196, 196, 196, 196, 132,, -2, 5, 1, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -2, 5, 1, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -2, 5, 1, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -2, 5, 1, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -2, 5, 1, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -2, 5, 1, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -2, 5, 1, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -2, 5, 1, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -2, 5, 1, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -2, 5, 1, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -2, 5, 1, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -2, 5, 1, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -2, 5, 2, 1, 1, 1, 1, 1, 128, 196, 196, 196, 196, 132,, -2, 5, 2, 1, 1, 1, 1, 1, 256, 196, 196, 196, 196, 132,, -2, 5, 2, 1, 1, 1, 1, 1, 384, 196, 196, 196, 196, 132,, -2, 5, 2, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -2, 5, 2, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -2, 5, 2, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -2, 5, 2, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -2, 5, 2, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -2, 5, 2, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -2, 5, 2, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -2, 5, 2, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -2, 5, 2, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -2, 5, 2, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -2, 5, 2, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -2, 5, 2, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -2, 6, 1, 1, 1, 1, 1, 1, 128, 197, 197, 197, 197,,, -2, 6, 1, 1, 1, 1, 1, 1, 256, 197, 197, 197, 197,,, -2, 6, 1, 1, 1, 1, 1, 1, 384, 197, 197, 197, 197,,, -2, 6, 1, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 6, 1, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 6, 1, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 6, 1, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 6, 1, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 6, 1, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 6, 1, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 6, 1, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 6, 1, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 6, 1, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 6, 1, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 6, 1, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 6, 1, 6, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 6, 1, 6, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 6, 1, 6, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 6, 2, 1, 1, 1, 1, 1, 128, 197, 197, 197, 197,,, -2, 6, 2, 1, 1, 1, 1, 1, 256, 197, 197, 197, 197,,, -2, 6, 2, 1, 1, 1, 1, 1, 384, 197, 197, 197, 197,,, -2, 6, 2, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 6, 2, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 6, 2, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 6, 2, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 6, 2, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 6, 2, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 6, 2, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 6, 2, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 6, 2, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 6, 2, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 6, 2, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 6, 2, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 6, 2, 6, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 6, 2, 6, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 6, 2, 6, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 7, 1, 1, 1, 1, 1, 1, 128, 198, 198, 198, 198,,, -2, 7, 1, 1, 1, 1, 1, 1, 256, 198, 198, 198, 198,,, -2, 7, 1, 1, 1, 1, 1, 1, 384, 198, 198, 198, 198,,, -2, 7, 1, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 7, 1, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 7, 1, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 7, 1, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 7, 1, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 7, 1, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 7, 1, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 7, 1, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 7, 1, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 7, 1, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 7, 1, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 7, 1, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 7, 1, 6, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 7, 1, 6, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 7, 1, 6, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 7, 1, 7, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 7, 1, 7, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 7, 1, 7, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 7, 2, 1, 1, 1, 1, 1, 128, 198, 198, 198, 198,,, -2, 7, 2, 1, 1, 1, 1, 1, 256, 198, 198, 198, 198,,, -2, 7, 2, 1, 1, 1, 1, 1, 384, 198, 198, 198, 198,,, -2, 7, 2, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 7, 2, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 7, 2, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 7, 2, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 7, 2, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 7, 2, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 7, 2, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 7, 2, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 7, 2, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 7, 2, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 7, 2, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 7, 2, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 7, 2, 6, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 7, 2, 6, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 7, 2, 6, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -2, 7, 2, 7, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -2, 7, 2, 7, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -2, 7, 2, 7, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 1, 1, 1, 1, 1, 1, 1, 128, 128, 128, 128, 128, 128, 128, 85 -3, 1, 1, 1, 1, 1, 1, 1, 256, 128, 128, 128, 128, 128, 128, 85 -3, 1, 1, 1, 1, 1, 1, 1, 384, 128, 128, 128, 128, 128, 128, 85 -3, 1, 2, 1, 1, 1, 1, 1, 128, 128, 128, 128, 128, 128, 128, 85 -3, 1, 2, 1, 1, 1, 1, 1, 256, 128, 128, 128, 128, 128, 128, 85 -3, 1, 2, 1, 1, 1, 1, 1, 384, 128, 128, 128, 128, 128, 128, 85 -3, 1, 3, 1, 1, 1, 1, 1, 128, 128, 128, 128, 128, 128, 128, 85 -3, 1, 3, 1, 1, 1, 1, 1, 256, 128, 128, 128, 128, 128, 128, 85 -3, 1, 3, 1, 1, 1, 1, 1, 384, 128, 128, 128, 128, 128, 128, 85 -3, 2, 1, 1, 1, 1, 1, 1, 128, 129, 129, 129, 129, 129, 86, 43 -3, 2, 1, 1, 1, 1, 1, 1, 256, 129, 129, 129, 129, 129, 86, 43 -3, 2, 1, 1, 1, 1, 1, 1, 384, 129, 129, 129, 129, 129, 86, 43 -3, 2, 1, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240, 171, 85 -3, 2, 1, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240, 171, 85 -3, 2, 1, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240, 170, 85 -3, 2, 2, 1, 1, 1, 1, 1, 128, 129, 129, 129, 129, 129, 86, 43 -3, 2, 2, 1, 1, 1, 1, 1, 256, 129, 129, 129, 129, 129, 86, 43 -3, 2, 2, 1, 1, 1, 1, 1, 384, 129, 129, 129, 129, 129, 86, 43 -3, 2, 2, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240, 171, 85 -3, 2, 2, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240, 171, 85 -3, 2, 2, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240, 170, 85 -3, 2, 3, 1, 1, 1, 1, 1, 128, 129, 129, 129, 129, 129, 86, 43 -3, 2, 3, 1, 1, 1, 1, 1, 256, 129, 129, 129, 129, 129, 86, 43 -3, 2, 3, 1, 1, 1, 1, 1, 384, 129, 129, 129, 129, 129, 86, 43 -3, 2, 3, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240, 171, 85 -3, 2, 3, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240, 171, 85 -3, 2, 3, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240, 170, 85 -3, 3, 1, 1, 1, 1, 1, 1, 128, 130, 130, 130, 130, 87,, -3, 3, 1, 1, 1, 1, 1, 1, 256, 130, 130, 130, 130, 87,, -3, 3, 1, 1, 1, 1, 1, 1, 384, 130, 130, 130, 130, 87,, -3, 3, 1, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240, 172,, -3, 3, 1, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240, 172,, -3, 3, 1, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240, 172,, -3, 3, 1, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -3, 3, 1, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -3, 3, 1, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -3, 3, 2, 1, 1, 1, 1, 1, 128, 130, 130, 130, 130, 87,, -3, 3, 2, 1, 1, 1, 1, 1, 256, 130, 130, 130, 130, 87,, -3, 3, 2, 1, 1, 1, 1, 1, 384, 130, 130, 130, 130, 87,, -3, 3, 2, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240, 172,, -3, 3, 2, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240, 172,, -3, 3, 2, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240, 172,, -3, 3, 2, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -3, 3, 2, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -3, 3, 2, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -3, 3, 3, 1, 1, 1, 1, 1, 128, 130, 130, 130, 130, 87,, -3, 3, 3, 1, 1, 1, 1, 1, 256, 130, 130, 130, 130, 87,, -3, 3, 3, 1, 1, 1, 1, 1, 384, 130, 130, 130, 130, 87,, -3, 3, 3, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240, 172,, -3, 3, 3, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240, 172,, -3, 3, 3, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240, 172,, -3, 3, 3, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -3, 3, 3, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -3, 3, 3, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -3, 4, 1, 1, 1, 1, 1, 1, 128, 131, 131, 131, 131, 88,, -3, 4, 1, 1, 1, 1, 1, 1, 256, 131, 131, 131, 131, 88,, -3, 4, 1, 1, 1, 1, 1, 1, 384, 131, 131, 131, 131, 88,, -3, 4, 1, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240, 173,, -3, 4, 1, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240, 173,, -3, 4, 1, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240, 173,, -3, 4, 1, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -3, 4, 1, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -3, 4, 1, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -3, 4, 1, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -3, 4, 1, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -3, 4, 1, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -3, 4, 2, 1, 1, 1, 1, 1, 128, 131, 131, 131, 131, 88,, -3, 4, 2, 1, 1, 1, 1, 1, 256, 131, 131, 131, 131, 88,, -3, 4, 2, 1, 1, 1, 1, 1, 384, 131, 131, 131, 131, 88,, -3, 4, 2, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240, 173,, -3, 4, 2, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240, 173,, -3, 4, 2, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240, 173,, -3, 4, 2, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -3, 4, 2, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -3, 4, 2, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -3, 4, 2, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -3, 4, 2, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -3, 4, 2, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -3, 4, 3, 1, 1, 1, 1, 1, 128, 131, 131, 131, 131, 88,, -3, 4, 3, 1, 1, 1, 1, 1, 256, 131, 131, 131, 131, 88,, -3, 4, 3, 1, 1, 1, 1, 1, 384, 131, 131, 131, 131, 88,, -3, 4, 3, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240, 173,, -3, 4, 3, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240, 173,, -3, 4, 3, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240, 173,, -3, 4, 3, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -3, 4, 3, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -3, 4, 3, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -3, 4, 3, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -3, 4, 3, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -3, 4, 3, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -3, 5, 1, 1, 1, 1, 1, 1, 128, 132, 132, 132, 132, 89,, -3, 5, 1, 1, 1, 1, 1, 1, 256, 132, 132, 132, 132, 89,, -3, 5, 1, 1, 1, 1, 1, 1, 384, 132, 132, 132, 132, 89,, -3, 5, 1, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240, 174,, -3, 5, 1, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240, 174,, -3, 5, 1, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240, 174,, -3, 5, 1, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -3, 5, 1, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -3, 5, 1, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -3, 5, 1, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -3, 5, 1, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -3, 5, 1, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -3, 5, 1, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -3, 5, 1, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -3, 5, 1, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -3, 5, 2, 1, 1, 1, 1, 1, 128, 132, 132, 132, 132, 89,, -3, 5, 2, 1, 1, 1, 1, 1, 256, 132, 132, 132, 132, 89,, -3, 5, 2, 1, 1, 1, 1, 1, 384, 132, 132, 132, 132, 89,, -3, 5, 2, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240, 174,, -3, 5, 2, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240, 174,, -3, 5, 2, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240, 174,, -3, 5, 2, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -3, 5, 2, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -3, 5, 2, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -3, 5, 2, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -3, 5, 2, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -3, 5, 2, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -3, 5, 2, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -3, 5, 2, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -3, 5, 2, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -3, 5, 3, 1, 1, 1, 1, 1, 128, 132, 132, 132, 132, 89,, -3, 5, 3, 1, 1, 1, 1, 1, 256, 132, 132, 132, 132, 89,, -3, 5, 3, 1, 1, 1, 1, 1, 384, 132, 132, 132, 132, 89,, -3, 5, 3, 2, 1, 1, 1, 1, 128, 240, 240, 240, 240, 174,, -3, 5, 3, 2, 1, 1, 1, 1, 256, 240, 240, 240, 240, 174,, -3, 5, 3, 2, 1, 1, 1, 1, 384, 240, 240, 240, 240, 174,, -3, 5, 3, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -3, 5, 3, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -3, 5, 3, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -3, 5, 3, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -3, 5, 3, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -3, 5, 3, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -3, 5, 3, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -3, 5, 3, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -3, 5, 3, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -3, 6, 1, 1, 1, 1, 1, 1, 128, 133, 133, 133, 90,,, -3, 6, 1, 1, 1, 1, 1, 1, 256, 133, 133, 133, 90,,, -3, 6, 1, 1, 1, 1, 1, 1, 384, 133, 133, 133, 90,,, -3, 6, 1, 2, 1, 1, 1, 1, 128, 240, 240, 240, 175,,, -3, 6, 1, 2, 1, 1, 1, 1, 256, 240, 240, 240, 175,,, -3, 6, 1, 2, 1, 1, 1, 1, 384, 240, 240, 240, 175,,, -3, 6, 1, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 6, 1, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 6, 1, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 6, 1, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 6, 1, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 6, 1, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 6, 1, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 6, 1, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 6, 1, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 6, 1, 6, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 6, 1, 6, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 6, 1, 6, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 6, 2, 1, 1, 1, 1, 1, 128, 133, 133, 133, 90,,, -3, 6, 2, 1, 1, 1, 1, 1, 256, 133, 133, 133, 90,,, -3, 6, 2, 1, 1, 1, 1, 1, 384, 133, 133, 133, 90,,, -3, 6, 2, 2, 1, 1, 1, 1, 128, 240, 240, 240, 175,,, -3, 6, 2, 2, 1, 1, 1, 1, 256, 240, 240, 240, 175,,, -3, 6, 2, 2, 1, 1, 1, 1, 384, 240, 240, 240, 175,,, -3, 6, 2, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 6, 2, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 6, 2, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 6, 2, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 6, 2, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 6, 2, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 6, 2, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 6, 2, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 6, 2, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 6, 2, 6, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 6, 2, 6, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 6, 2, 6, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 6, 3, 1, 1, 1, 1, 1, 128, 133, 133, 133, 90,,, -3, 6, 3, 1, 1, 1, 1, 1, 256, 133, 133, 133, 90,,, -3, 6, 3, 1, 1, 1, 1, 1, 384, 133, 133, 133, 90,,, -3, 6, 3, 2, 1, 1, 1, 1, 128, 240, 240, 240, 175,,, -3, 6, 3, 2, 1, 1, 1, 1, 256, 240, 240, 240, 175,,, -3, 6, 3, 2, 1, 1, 1, 1, 384, 240, 240, 240, 175,,, -3, 6, 3, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 6, 3, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 6, 3, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 6, 3, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 6, 3, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 6, 3, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 6, 3, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 6, 3, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 6, 3, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 6, 3, 6, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 6, 3, 6, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 6, 3, 6, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 7, 1, 1, 1, 1, 1, 1, 128, 134, 134, 134, 91,,, -3, 7, 1, 1, 1, 1, 1, 1, 256, 134, 134, 134, 91,,, -3, 7, 1, 1, 1, 1, 1, 1, 384, 134, 134, 134, 91,,, -3, 7, 1, 2, 1, 1, 1, 1, 128, 240, 240, 240, 176,,, -3, 7, 1, 2, 1, 1, 1, 1, 256, 240, 240, 240, 176,,, -3, 7, 1, 2, 1, 1, 1, 1, 384, 240, 240, 240, 176,,, -3, 7, 1, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 7, 1, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 7, 1, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 7, 1, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 7, 1, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 7, 1, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 7, 1, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 7, 1, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 7, 1, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 7, 1, 6, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 7, 1, 6, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 7, 1, 6, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 7, 1, 7, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 7, 1, 7, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 7, 1, 7, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 7, 2, 1, 1, 1, 1, 1, 128, 134, 134, 134, 91,,, -3, 7, 2, 1, 1, 1, 1, 1, 256, 134, 134, 134, 91,,, -3, 7, 2, 1, 1, 1, 1, 1, 384, 134, 134, 134, 91,,, -3, 7, 2, 2, 1, 1, 1, 1, 128, 240, 240, 240, 176,,, -3, 7, 2, 2, 1, 1, 1, 1, 256, 240, 240, 240, 176,,, -3, 7, 2, 2, 1, 1, 1, 1, 384, 240, 240, 240, 176,,, -3, 7, 2, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 7, 2, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 7, 2, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 7, 2, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 7, 2, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 7, 2, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 7, 2, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 7, 2, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 7, 2, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 7, 2, 6, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 7, 2, 6, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 7, 2, 6, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 7, 2, 7, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 7, 2, 7, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 7, 2, 7, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 7, 3, 1, 1, 1, 1, 1, 128, 134, 134, 134, 91,,, -3, 7, 3, 1, 1, 1, 1, 1, 256, 134, 134, 134, 91,,, -3, 7, 3, 1, 1, 1, 1, 1, 384, 134, 134, 134, 91,,, -3, 7, 3, 2, 1, 1, 1, 1, 128, 240, 240, 240, 176,,, -3, 7, 3, 2, 1, 1, 1, 1, 256, 240, 240, 240, 176,,, -3, 7, 3, 2, 1, 1, 1, 1, 384, 240, 240, 240, 176,,, -3, 7, 3, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 7, 3, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 7, 3, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 7, 3, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 7, 3, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 7, 3, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 7, 3, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 7, 3, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 7, 3, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 7, 3, 6, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 7, 3, 6, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 7, 3, 6, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -3, 7, 3, 7, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -3, 7, 3, 7, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -3, 7, 3, 7, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -4, 1, 1, 1, 1, 1, 1, 1, 128, 96, 96, 96, 96, 96, 96, 64 -4, 1, 1, 1, 1, 1, 1, 1, 256, 96, 96, 96, 96, 96, 96, 64 -4, 1, 1, 1, 1, 1, 1, 1, 384, 96, 96, 96, 96, 96, 96, 64 -4, 1, 2, 1, 1, 1, 1, 1, 128, 96, 96, 96, 96, 96, 96, 64 -4, 1, 2, 1, 1, 1, 1, 1, 256, 96, 96, 96, 96, 96, 96, 64 -4, 1, 2, 1, 1, 1, 1, 1, 384, 96, 96, 96, 96, 96, 96, 64 -4, 1, 3, 1, 1, 1, 1, 1, 128, 96, 96, 96, 96, 96, 96, 64 -4, 1, 3, 1, 1, 1, 1, 1, 256, 96, 96, 96, 96, 96, 96, 64 -4, 1, 3, 1, 1, 1, 1, 1, 384, 96, 96, 96, 96, 96, 96, 64 -4, 1, 4, 1, 1, 1, 1, 1, 128, 96, 96, 96, 96, 96, 96, 64 -4, 1, 4, 1, 1, 1, 1, 1, 256, 96, 96, 96, 96, 96, 96, 64 -4, 1, 4, 1, 1, 1, 1, 1, 384, 96, 96, 96, 96, 96, 96, 64 -4, 2, 1, 1, 1, 1, 1, 1, 128, 97, 97, 97, 97, 97, 65, 33 -4, 2, 1, 1, 1, 1, 1, 1, 256, 97, 97, 97, 97, 97, 65, 33 -4, 2, 1, 1, 1, 1, 1, 1, 384, 97, 97, 97, 97, 97, 65, 33 -4, 2, 1, 2, 1, 1, 1, 1, 128, 193, 193, 193, 193, 193, 129, 65 -4, 2, 1, 2, 1, 1, 1, 1, 256, 193, 193, 193, 193, 193, 129, 65 -4, 2, 1, 2, 1, 1, 1, 1, 384, 193, 193, 193, 193, 193, 129, 65 -4, 2, 2, 1, 1, 1, 1, 1, 128, 97, 97, 97, 97, 97, 65, 33 -4, 2, 2, 1, 1, 1, 1, 1, 256, 97, 97, 97, 97, 97, 65, 33 -4, 2, 2, 1, 1, 1, 1, 1, 384, 97, 97, 97, 97, 97, 65, 33 -4, 2, 2, 2, 1, 1, 1, 1, 128, 193, 193, 193, 193, 193, 129, 65 -4, 2, 2, 2, 1, 1, 1, 1, 256, 193, 193, 193, 193, 193, 129, 65 -4, 2, 2, 2, 1, 1, 1, 1, 384, 193, 193, 193, 193, 193, 129, 65 -4, 2, 3, 1, 1, 1, 1, 1, 128, 97, 97, 97, 97, 97, 65, 33 -4, 2, 3, 1, 1, 1, 1, 1, 256, 97, 97, 97, 97, 97, 65, 33 -4, 2, 3, 1, 1, 1, 1, 1, 384, 97, 97, 97, 97, 97, 65, 33 -4, 2, 3, 2, 1, 1, 1, 1, 128, 193, 193, 193, 193, 193, 129, 65 -4, 2, 3, 2, 1, 1, 1, 1, 256, 193, 193, 193, 193, 193, 129, 65 -4, 2, 3, 2, 1, 1, 1, 1, 384, 193, 193, 193, 193, 193, 129, 65 -4, 2, 4, 1, 1, 1, 1, 1, 128, 97, 97, 97, 97, 97, 65, 33 -4, 2, 4, 1, 1, 1, 1, 1, 256, 97, 97, 97, 97, 97, 65, 33 -4, 2, 4, 1, 1, 1, 1, 1, 384, 97, 97, 97, 97, 97, 65, 33 -4, 2, 4, 2, 1, 1, 1, 1, 128, 193, 193, 193, 193, 193, 129, 65 -4, 2, 4, 2, 1, 1, 1, 1, 256, 193, 193, 193, 193, 193, 129, 65 -4, 2, 4, 2, 1, 1, 1, 1, 384, 193, 193, 193, 193, 193, 129, 65 -4, 3, 1, 1, 1, 1, 1, 1, 128, 98, 98, 98, 98, 66,, -4, 3, 1, 1, 1, 1, 1, 1, 256, 98, 98, 98, 98, 66,, -4, 3, 1, 1, 1, 1, 1, 1, 384, 98, 98, 98, 98, 66,, -4, 3, 1, 2, 1, 1, 1, 1, 128, 194, 194, 194, 194, 130,, -4, 3, 1, 2, 1, 1, 1, 1, 256, 194, 194, 194, 194, 130,, -4, 3, 1, 2, 1, 1, 1, 1, 384, 194, 194, 194, 194, 130,, -4, 3, 1, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240, 194,, -4, 3, 1, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240, 194,, -4, 3, 1, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240, 194,, -4, 3, 2, 1, 1, 1, 1, 1, 128, 98, 98, 98, 98, 66,, -4, 3, 2, 1, 1, 1, 1, 1, 256, 98, 98, 98, 98, 66,, -4, 3, 2, 1, 1, 1, 1, 1, 384, 98, 98, 98, 98, 66,, -4, 3, 2, 2, 1, 1, 1, 1, 128, 194, 194, 194, 194, 130,, -4, 3, 2, 2, 1, 1, 1, 1, 256, 194, 194, 194, 194, 130,, -4, 3, 2, 2, 1, 1, 1, 1, 384, 194, 194, 194, 194, 130,, -4, 3, 2, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240, 194,, -4, 3, 2, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240, 194,, -4, 3, 2, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240, 194,, -4, 3, 3, 1, 1, 1, 1, 1, 128, 98, 98, 98, 98, 66,, -4, 3, 3, 1, 1, 1, 1, 1, 256, 98, 98, 98, 98, 66,, -4, 3, 3, 1, 1, 1, 1, 1, 384, 98, 98, 98, 98, 66,, -4, 3, 3, 2, 1, 1, 1, 1, 128, 194, 194, 194, 194, 130,, -4, 3, 3, 2, 1, 1, 1, 1, 256, 194, 194, 194, 194, 130,, -4, 3, 3, 2, 1, 1, 1, 1, 384, 194, 194, 194, 194, 130,, -4, 3, 3, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240, 194,, -4, 3, 3, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240, 194,, -4, 3, 3, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240, 194,, -4, 3, 4, 1, 1, 1, 1, 1, 128, 98, 98, 98, 98, 66,, -4, 3, 4, 1, 1, 1, 1, 1, 256, 98, 98, 98, 98, 66,, -4, 3, 4, 1, 1, 1, 1, 1, 384, 98, 98, 98, 98, 66,, -4, 3, 4, 2, 1, 1, 1, 1, 128, 194, 194, 194, 194, 130,, -4, 3, 4, 2, 1, 1, 1, 1, 256, 194, 194, 194, 194, 130,, -4, 3, 4, 2, 1, 1, 1, 1, 384, 194, 194, 194, 194, 130,, -4, 3, 4, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240, 194,, -4, 3, 4, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240, 194,, -4, 3, 4, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240, 194,, -4, 4, 1, 1, 1, 1, 1, 1, 128, 99, 99, 99, 99, 67,, -4, 4, 1, 1, 1, 1, 1, 1, 256, 99, 99, 99, 99, 67,, -4, 4, 1, 1, 1, 1, 1, 1, 384, 99, 99, 99, 99, 67,, -4, 4, 1, 2, 1, 1, 1, 1, 128, 195, 195, 195, 195, 131,, -4, 4, 1, 2, 1, 1, 1, 1, 256, 195, 195, 195, 195, 131,, -4, 4, 1, 2, 1, 1, 1, 1, 384, 195, 195, 195, 195, 131,, -4, 4, 1, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240, 195,, -4, 4, 1, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240, 195,, -4, 4, 1, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240, 195,, -4, 4, 1, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -4, 4, 1, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -4, 4, 1, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -4, 4, 2, 1, 1, 1, 1, 1, 128, 99, 99, 99, 99, 67,, -4, 4, 2, 1, 1, 1, 1, 1, 256, 99, 99, 99, 99, 67,, -4, 4, 2, 1, 1, 1, 1, 1, 384, 99, 99, 99, 99, 67,, -4, 4, 2, 2, 1, 1, 1, 1, 128, 195, 195, 195, 195, 131,, -4, 4, 2, 2, 1, 1, 1, 1, 256, 195, 195, 195, 195, 131,, -4, 4, 2, 2, 1, 1, 1, 1, 384, 195, 195, 195, 195, 131,, -4, 4, 2, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240, 195,, -4, 4, 2, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240, 195,, -4, 4, 2, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240, 195,, -4, 4, 2, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -4, 4, 2, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -4, 4, 2, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -4, 4, 3, 1, 1, 1, 1, 1, 128, 99, 99, 99, 99, 67,, -4, 4, 3, 1, 1, 1, 1, 1, 256, 99, 99, 99, 99, 67,, -4, 4, 3, 1, 1, 1, 1, 1, 384, 99, 99, 99, 99, 67,, -4, 4, 3, 2, 1, 1, 1, 1, 128, 195, 195, 195, 195, 131,, -4, 4, 3, 2, 1, 1, 1, 1, 256, 195, 195, 195, 195, 131,, -4, 4, 3, 2, 1, 1, 1, 1, 384, 195, 195, 195, 195, 131,, -4, 4, 3, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240, 195,, -4, 4, 3, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240, 195,, -4, 4, 3, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240, 195,, -4, 4, 3, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -4, 4, 3, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -4, 4, 3, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -4, 4, 4, 1, 1, 1, 1, 1, 128, 99, 99, 99, 99, 67,, -4, 4, 4, 1, 1, 1, 1, 1, 256, 99, 99, 99, 99, 67,, -4, 4, 4, 1, 1, 1, 1, 1, 384, 99, 99, 99, 99, 67,, -4, 4, 4, 2, 1, 1, 1, 1, 128, 195, 195, 195, 195, 131,, -4, 4, 4, 2, 1, 1, 1, 1, 256, 195, 195, 195, 195, 131,, -4, 4, 4, 2, 1, 1, 1, 1, 384, 195, 195, 195, 195, 131,, -4, 4, 4, 3, 1, 1, 1, 1, 128, 240, 240, 240, 240, 195,, -4, 4, 4, 3, 1, 1, 1, 1, 256, 240, 240, 240, 240, 195,, -4, 4, 4, 3, 1, 1, 1, 1, 384, 240, 240, 240, 240, 195,, -4, 4, 4, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240, 240,, -4, 4, 4, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240, 240,, -4, 4, 4, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240, 240,, -4, 5, 1, 1, 1, 1, 1, 1, 128, 100, 100, 100, 68, 36,, -4, 5, 1, 1, 1, 1, 1, 1, 256, 100, 100, 100, 68, 36,, -4, 5, 1, 1, 1, 1, 1, 1, 384, 100, 100, 100, 68, 36,, -4, 5, 1, 2, 1, 1, 1, 1, 128, 196, 196, 196, 132, 68,, -4, 5, 1, 2, 1, 1, 1, 1, 256, 196, 196, 196, 132, 68,, -4, 5, 1, 2, 1, 1, 1, 1, 384, 196, 196, 196, 132, 68,, -4, 5, 1, 3, 1, 1, 1, 1, 128, 240, 240, 240, 196, 100,, -4, 5, 1, 3, 1, 1, 1, 1, 256, 240, 240, 240, 196, 100,, -4, 5, 1, 3, 1, 1, 1, 1, 384, 240, 240, 240, 196, 100,, -4, 5, 1, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240, 132,, -4, 5, 1, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240, 132,, -4, 5, 1, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240, 132,, -4, 5, 1, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240, 164,, -4, 5, 1, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240, 164,, -4, 5, 1, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240, 164,, -4, 5, 2, 1, 1, 1, 1, 1, 128, 100, 100, 100, 68, 36,, -4, 5, 2, 1, 1, 1, 1, 1, 256, 100, 100, 100, 68, 36,, -4, 5, 2, 1, 1, 1, 1, 1, 384, 100, 100, 100, 68, 36,, -4, 5, 2, 2, 1, 1, 1, 1, 128, 196, 196, 196, 132, 68,, -4, 5, 2, 2, 1, 1, 1, 1, 256, 196, 196, 196, 132, 68,, -4, 5, 2, 2, 1, 1, 1, 1, 384, 196, 196, 196, 132, 68,, -4, 5, 2, 3, 1, 1, 1, 1, 128, 240, 240, 240, 196, 100,, -4, 5, 2, 3, 1, 1, 1, 1, 256, 240, 240, 240, 196, 100,, -4, 5, 2, 3, 1, 1, 1, 1, 384, 240, 240, 240, 196, 100,, -4, 5, 2, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240, 132,, -4, 5, 2, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240, 132,, -4, 5, 2, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240, 132,, -4, 5, 2, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240, 164,, -4, 5, 2, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240, 164,, -4, 5, 2, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240, 164,, -4, 5, 3, 1, 1, 1, 1, 1, 128, 100, 100, 100, 68, 36,, -4, 5, 3, 1, 1, 1, 1, 1, 256, 100, 100, 100, 68, 36,, -4, 5, 3, 1, 1, 1, 1, 1, 384, 100, 100, 100, 68, 36,, -4, 5, 3, 2, 1, 1, 1, 1, 128, 196, 196, 196, 132, 68,, -4, 5, 3, 2, 1, 1, 1, 1, 256, 196, 196, 196, 132, 68,, -4, 5, 3, 2, 1, 1, 1, 1, 384, 196, 196, 196, 132, 68,, -4, 5, 3, 3, 1, 1, 1, 1, 128, 240, 240, 240, 196, 100,, -4, 5, 3, 3, 1, 1, 1, 1, 256, 240, 240, 240, 196, 100,, -4, 5, 3, 3, 1, 1, 1, 1, 384, 240, 240, 240, 196, 100,, -4, 5, 3, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240, 132,, -4, 5, 3, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240, 132,, -4, 5, 3, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240, 132,, -4, 5, 3, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240, 164,, -4, 5, 3, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240, 164,, -4, 5, 3, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240, 164,, -4, 5, 4, 1, 1, 1, 1, 1, 128, 100, 100, 100, 68, 36,, -4, 5, 4, 1, 1, 1, 1, 1, 256, 100, 100, 100, 68, 36,, -4, 5, 4, 1, 1, 1, 1, 1, 384, 100, 100, 100, 68, 36,, -4, 5, 4, 2, 1, 1, 1, 1, 128, 196, 196, 196, 132, 68,, -4, 5, 4, 2, 1, 1, 1, 1, 256, 196, 196, 196, 132, 68,, -4, 5, 4, 2, 1, 1, 1, 1, 384, 196, 196, 196, 132, 68,, -4, 5, 4, 3, 1, 1, 1, 1, 128, 240, 240, 240, 196, 100,, -4, 5, 4, 3, 1, 1, 1, 1, 256, 240, 240, 240, 196, 100,, -4, 5, 4, 3, 1, 1, 1, 1, 384, 240, 240, 240, 196, 100,, -4, 5, 4, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240, 132,, -4, 5, 4, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240, 132,, -4, 5, 4, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240, 132,, -4, 5, 4, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240, 164,, -4, 5, 4, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240, 164,, -4, 5, 4, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240, 164,, -4, 6, 1, 1, 1, 1, 1, 1, 128, 101, 101, 101, 69,,, -4, 6, 1, 1, 1, 1, 1, 1, 256, 101, 101, 101, 69,,, -4, 6, 1, 1, 1, 1, 1, 1, 384, 101, 101, 101, 69,,, -4, 6, 1, 2, 1, 1, 1, 1, 128, 197, 197, 197, 133,,, -4, 6, 1, 2, 1, 1, 1, 1, 256, 197, 197, 197, 133,,, -4, 6, 1, 2, 1, 1, 1, 1, 384, 197, 197, 197, 133,,, -4, 6, 1, 3, 1, 1, 1, 1, 128, 240, 240, 240, 197,,, -4, 6, 1, 3, 1, 1, 1, 1, 256, 240, 240, 240, 197,,, -4, 6, 1, 3, 1, 1, 1, 1, 384, 240, 240, 240, 197,,, -4, 6, 1, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -4, 6, 1, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -4, 6, 1, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -4, 6, 1, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -4, 6, 1, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -4, 6, 1, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -4, 6, 1, 6, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -4, 6, 1, 6, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -4, 6, 1, 6, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -4, 6, 2, 1, 1, 1, 1, 1, 128, 101, 101, 101, 69,,, -4, 6, 2, 1, 1, 1, 1, 1, 256, 101, 101, 101, 69,,, -4, 6, 2, 1, 1, 1, 1, 1, 384, 101, 101, 101, 69,,, -4, 6, 2, 2, 1, 1, 1, 1, 128, 197, 197, 197, 133,,, -4, 6, 2, 2, 1, 1, 1, 1, 256, 197, 197, 197, 133,,, -4, 6, 2, 2, 1, 1, 1, 1, 384, 197, 197, 197, 133,,, -4, 6, 2, 3, 1, 1, 1, 1, 128, 240, 240, 240, 197,,, -4, 6, 2, 3, 1, 1, 1, 1, 256, 240, 240, 240, 197,,, -4, 6, 2, 3, 1, 1, 1, 1, 384, 240, 240, 240, 197,,, -4, 6, 2, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -4, 6, 2, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -4, 6, 2, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -4, 6, 2, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -4, 6, 2, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -4, 6, 2, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -4, 6, 2, 6, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -4, 6, 2, 6, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -4, 6, 2, 6, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -4, 6, 3, 1, 1, 1, 1, 1, 128, 101, 101, 101, 69,,, -4, 6, 3, 1, 1, 1, 1, 1, 256, 101, 101, 101, 69,,, -4, 6, 3, 1, 1, 1, 1, 1, 384, 101, 101, 101, 69,,, -4, 6, 3, 2, 1, 1, 1, 1, 128, 197, 197, 197, 133,,, -4, 6, 3, 2, 1, 1, 1, 1, 256, 197, 197, 197, 133,,, -4, 6, 3, 2, 1, 1, 1, 1, 384, 197, 197, 197, 133,,, -4, 6, 3, 3, 1, 1, 1, 1, 128, 240, 240, 240, 197,,, -4, 6, 3, 3, 1, 1, 1, 1, 256, 240, 240, 240, 197,,, -4, 6, 3, 3, 1, 1, 1, 1, 384, 240, 240, 240, 197,,, -4, 6, 3, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -4, 6, 3, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -4, 6, 3, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -4, 6, 3, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -4, 6, 3, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -4, 6, 3, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -4, 6, 3, 6, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -4, 6, 3, 6, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -4, 6, 3, 6, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -4, 6, 4, 1, 1, 1, 1, 1, 128, 101, 101, 101, 69,,, -4, 6, 4, 1, 1, 1, 1, 1, 256, 101, 101, 101, 69,,, -4, 6, 4, 1, 1, 1, 1, 1, 384, 101, 101, 101, 69,,, -4, 6, 4, 2, 1, 1, 1, 1, 128, 197, 197, 197, 133,,, -4, 6, 4, 2, 1, 1, 1, 1, 256, 197, 197, 197, 133,,, -4, 6, 4, 2, 1, 1, 1, 1, 384, 197, 197, 197, 133,,, -4, 6, 4, 3, 1, 1, 1, 1, 128, 240, 240, 240, 197,,, -4, 6, 4, 3, 1, 1, 1, 1, 256, 240, 240, 240, 197,,, -4, 6, 4, 3, 1, 1, 1, 1, 384, 240, 240, 240, 197,,, -4, 6, 4, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -4, 6, 4, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -4, 6, 4, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -4, 6, 4, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -4, 6, 4, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -4, 6, 4, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -4, 6, 4, 6, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -4, 6, 4, 6, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -4, 6, 4, 6, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -4, 7, 1, 1, 1, 1, 1, 1, 128, 102, 102, 102, 70,,, -4, 7, 1, 1, 1, 1, 1, 1, 256, 102, 102, 102, 70,,, -4, 7, 1, 1, 1, 1, 1, 1, 384, 102, 102, 102, 70,,, -4, 7, 1, 2, 1, 1, 1, 1, 128, 198, 198, 198, 134,,, -4, 7, 1, 2, 1, 1, 1, 1, 256, 198, 198, 198, 134,,, -4, 7, 1, 2, 1, 1, 1, 1, 384, 198, 198, 198, 134,,, -4, 7, 1, 3, 1, 1, 1, 1, 128, 240, 240, 240, 198,,, -4, 7, 1, 3, 1, 1, 1, 1, 256, 240, 240, 240, 198,,, -4, 7, 1, 3, 1, 1, 1, 1, 384, 240, 240, 240, 198,,, -4, 7, 1, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -4, 7, 1, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -4, 7, 1, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -4, 7, 1, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -4, 7, 1, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -4, 7, 1, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -4, 7, 1, 6, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -4, 7, 1, 6, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -4, 7, 1, 6, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -4, 7, 1, 7, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -4, 7, 1, 7, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -4, 7, 1, 7, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -4, 7, 2, 1, 1, 1, 1, 1, 128, 102, 102, 102, 70,,, -4, 7, 2, 1, 1, 1, 1, 1, 256, 102, 102, 102, 70,,, -4, 7, 2, 1, 1, 1, 1, 1, 384, 102, 102, 102, 70,,, -4, 7, 2, 2, 1, 1, 1, 1, 128, 198, 198, 198, 134,,, -4, 7, 2, 2, 1, 1, 1, 1, 256, 198, 198, 198, 134,,, -4, 7, 2, 2, 1, 1, 1, 1, 384, 198, 198, 198, 134,,, -4, 7, 2, 3, 1, 1, 1, 1, 128, 240, 240, 240, 198,,, -4, 7, 2, 3, 1, 1, 1, 1, 256, 240, 240, 240, 198,,, -4, 7, 2, 3, 1, 1, 1, 1, 384, 240, 240, 240, 198,,, -4, 7, 2, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -4, 7, 2, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -4, 7, 2, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -4, 7, 2, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -4, 7, 2, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -4, 7, 2, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -4, 7, 2, 6, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -4, 7, 2, 6, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -4, 7, 2, 6, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -4, 7, 2, 7, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -4, 7, 2, 7, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -4, 7, 2, 7, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -4, 7, 3, 1, 1, 1, 1, 1, 128, 102, 102, 102, 70,,, -4, 7, 3, 1, 1, 1, 1, 1, 256, 102, 102, 102, 70,,, -4, 7, 3, 1, 1, 1, 1, 1, 384, 102, 102, 102, 70,,, -4, 7, 3, 2, 1, 1, 1, 1, 128, 198, 198, 198, 134,,, -4, 7, 3, 2, 1, 1, 1, 1, 256, 198, 198, 198, 134,,, -4, 7, 3, 2, 1, 1, 1, 1, 384, 198, 198, 198, 134,,, -4, 7, 3, 3, 1, 1, 1, 1, 128, 240, 240, 240, 198,,, -4, 7, 3, 3, 1, 1, 1, 1, 256, 240, 240, 240, 198,,, -4, 7, 3, 3, 1, 1, 1, 1, 384, 240, 240, 240, 198,,, -4, 7, 3, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -4, 7, 3, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -4, 7, 3, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -4, 7, 3, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -4, 7, 3, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -4, 7, 3, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -4, 7, 3, 6, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -4, 7, 3, 6, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -4, 7, 3, 6, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -4, 7, 3, 7, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -4, 7, 3, 7, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -4, 7, 3, 7, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -4, 7, 4, 1, 1, 1, 1, 1, 128, 102, 102, 102, 70,,, -4, 7, 4, 1, 1, 1, 1, 1, 256, 102, 102, 102, 70,,, -4, 7, 4, 1, 1, 1, 1, 1, 384, 102, 102, 102, 70,,, -4, 7, 4, 2, 1, 1, 1, 1, 128, 198, 198, 198, 134,,, -4, 7, 4, 2, 1, 1, 1, 1, 256, 198, 198, 198, 134,,, -4, 7, 4, 2, 1, 1, 1, 1, 384, 198, 198, 198, 134,,, -4, 7, 4, 3, 1, 1, 1, 1, 128, 240, 240, 240, 198,,, -4, 7, 4, 3, 1, 1, 1, 1, 256, 240, 240, 240, 198,,, -4, 7, 4, 3, 1, 1, 1, 1, 384, 240, 240, 240, 198,,, -4, 7, 4, 4, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -4, 7, 4, 4, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -4, 7, 4, 4, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -4, 7, 4, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -4, 7, 4, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -4, 7, 4, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -4, 7, 4, 6, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -4, 7, 4, 6, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -4, 7, 4, 6, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -4, 7, 4, 7, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -4, 7, 4, 7, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -4, 7, 4, 7, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -5, 1, 1, 1, 1, 1, 1, 1, 128, 76, 76, 76, 76, 76, 51, 51 -5, 1, 1, 1, 1, 1, 1, 1, 256, 76, 76, 76, 76, 76, 51, 51 -5, 1, 1, 1, 1, 1, 1, 1, 384, 76, 76, 76, 76, 76, 51, 51 -5, 1, 2, 1, 1, 1, 1, 1, 128, 76, 76, 76, 76, 76, 51, 51 -5, 1, 2, 1, 1, 1, 1, 1, 256, 76, 76, 76, 76, 76, 51, 51 -5, 1, 2, 1, 1, 1, 1, 1, 384, 76, 76, 76, 76, 76, 51, 51 -5, 1, 3, 1, 1, 1, 1, 1, 128, 76, 76, 76, 76, 76, 51, 51 -5, 1, 3, 1, 1, 1, 1, 1, 256, 76, 76, 76, 76, 76, 51, 51 -5, 1, 3, 1, 1, 1, 1, 1, 384, 76, 76, 76, 76, 76, 51, 51 -5, 1, 4, 1, 1, 1, 1, 1, 128, 76, 76, 76, 76, 76, 51, 51 -5, 1, 4, 1, 1, 1, 1, 1, 256, 76, 76, 76, 76, 76, 51, 51 -5, 1, 4, 1, 1, 1, 1, 1, 384, 76, 76, 76, 76, 76, 51, 51 -5, 1, 5, 1, 1, 1, 1, 1, 128, 76, 76, 76, 76, 76, 51, 51 -5, 1, 5, 1, 1, 1, 1, 1, 256, 76, 76, 76, 76, 76, 51, 51 -5, 1, 5, 1, 1, 1, 1, 1, 384, 76, 76, 76, 76, 76, 51, 51 -5, 2, 1, 1, 1, 1, 1, 1, 128, 77, 77, 77, 77, 52, 26, -5, 2, 1, 1, 1, 1, 1, 1, 256, 77, 77, 77, 77, 52, 26, -5, 2, 1, 1, 1, 1, 1, 1, 384, 77, 77, 77, 77, 52, 26, -5, 2, 1, 2, 1, 1, 1, 1, 128, 153, 153, 153, 153, 103, 51, -5, 2, 1, 2, 1, 1, 1, 1, 256, 153, 153, 153, 153, 103, 51, -5, 2, 1, 2, 1, 1, 1, 1, 384, 153, 153, 153, 153, 103, 51, -5, 2, 2, 1, 1, 1, 1, 1, 128, 77, 77, 77, 77, 52, 26, -5, 2, 2, 1, 1, 1, 1, 1, 256, 77, 77, 77, 77, 52, 26, -5, 2, 2, 1, 1, 1, 1, 1, 384, 77, 77, 77, 77, 52, 26, -5, 2, 2, 2, 1, 1, 1, 1, 128, 153, 153, 153, 153, 103, 51, -5, 2, 2, 2, 1, 1, 1, 1, 256, 153, 153, 153, 153, 103, 51, -5, 2, 2, 2, 1, 1, 1, 1, 384, 153, 153, 153, 153, 103, 51, -5, 2, 3, 1, 1, 1, 1, 1, 128, 77, 77, 77, 77, 52, 26, -5, 2, 3, 1, 1, 1, 1, 1, 256, 77, 77, 77, 77, 52, 26, -5, 2, 3, 1, 1, 1, 1, 1, 384, 77, 77, 77, 77, 52, 26, -5, 2, 3, 2, 1, 1, 1, 1, 128, 153, 153, 153, 153, 103, 51, -5, 2, 3, 2, 1, 1, 1, 1, 256, 153, 153, 153, 153, 103, 51, -5, 2, 3, 2, 1, 1, 1, 1, 384, 153, 153, 153, 153, 103, 51, -5, 2, 4, 1, 1, 1, 1, 1, 128, 77, 77, 77, 77, 52, 26, -5, 2, 4, 1, 1, 1, 1, 1, 256, 77, 77, 77, 77, 52, 26, -5, 2, 4, 1, 1, 1, 1, 1, 384, 77, 77, 77, 77, 52, 26, -5, 2, 4, 2, 1, 1, 1, 1, 128, 153, 153, 153, 153, 103, 51, -5, 2, 4, 2, 1, 1, 1, 1, 256, 153, 153, 153, 153, 103, 51, -5, 2, 4, 2, 1, 1, 1, 1, 384, 153, 153, 153, 153, 103, 51, -5, 2, 5, 1, 1, 1, 1, 1, 128, 77, 77, 77, 77, 52, 26, -5, 2, 5, 1, 1, 1, 1, 1, 256, 77, 77, 77, 77, 52, 26, -5, 2, 5, 1, 1, 1, 1, 1, 384, 77, 77, 77, 77, 52, 26, -5, 2, 5, 2, 1, 1, 1, 1, 128, 153, 153, 153, 153, 103, 51, -5, 2, 5, 2, 1, 1, 1, 1, 256, 153, 153, 153, 153, 103, 51, -5, 2, 5, 2, 1, 1, 1, 1, 384, 153, 153, 153, 153, 103, 51, -5, 3, 1, 1, 1, 1, 1, 1, 128, 78, 78, 78, 78, 53,, -5, 3, 1, 1, 1, 1, 1, 1, 256, 78, 78, 78, 78, 53,, -5, 3, 1, 1, 1, 1, 1, 1, 384, 78, 78, 78, 78, 53,, -5, 3, 1, 2, 1, 1, 1, 1, 128, 154, 154, 154, 154, 104,, -5, 3, 1, 2, 1, 1, 1, 1, 256, 154, 154, 154, 154, 104,, -5, 3, 1, 2, 1, 1, 1, 1, 384, 154, 154, 154, 154, 104,, -5, 3, 1, 3, 1, 1, 1, 1, 128, 230, 230, 230, 230, 155,, -5, 3, 1, 3, 1, 1, 1, 1, 256, 230, 230, 230, 230, 155,, -5, 3, 1, 3, 1, 1, 1, 1, 384, 230, 230, 230, 230, 155,, -5, 3, 2, 1, 1, 1, 1, 1, 128, 78, 78, 78, 78, 53,, -5, 3, 2, 1, 1, 1, 1, 1, 256, 78, 78, 78, 78, 53,, -5, 3, 2, 1, 1, 1, 1, 1, 384, 78, 78, 78, 78, 53,, -5, 3, 2, 2, 1, 1, 1, 1, 128, 154, 154, 154, 154, 104,, -5, 3, 2, 2, 1, 1, 1, 1, 256, 154, 154, 154, 154, 104,, -5, 3, 2, 2, 1, 1, 1, 1, 384, 154, 154, 154, 154, 104,, -5, 3, 2, 3, 1, 1, 1, 1, 128, 230, 230, 230, 230, 155,, -5, 3, 2, 3, 1, 1, 1, 1, 256, 230, 230, 230, 230, 155,, -5, 3, 2, 3, 1, 1, 1, 1, 384, 230, 230, 230, 230, 155,, -5, 3, 3, 1, 1, 1, 1, 1, 128, 78, 78, 78, 78, 53,, -5, 3, 3, 1, 1, 1, 1, 1, 256, 78, 78, 78, 78, 53,, -5, 3, 3, 1, 1, 1, 1, 1, 384, 78, 78, 78, 78, 53,, -5, 3, 3, 2, 1, 1, 1, 1, 128, 154, 154, 154, 154, 104,, -5, 3, 3, 2, 1, 1, 1, 1, 256, 154, 154, 154, 154, 104,, -5, 3, 3, 2, 1, 1, 1, 1, 384, 154, 154, 154, 154, 104,, -5, 3, 3, 3, 1, 1, 1, 1, 128, 230, 230, 230, 230, 155,, -5, 3, 3, 3, 1, 1, 1, 1, 256, 230, 230, 230, 230, 155,, -5, 3, 3, 3, 1, 1, 1, 1, 384, 230, 230, 230, 230, 155,, -5, 3, 4, 1, 1, 1, 1, 1, 128, 78, 78, 78, 78, 53,, -5, 3, 4, 1, 1, 1, 1, 1, 256, 78, 78, 78, 78, 53,, -5, 3, 4, 1, 1, 1, 1, 1, 384, 78, 78, 78, 78, 53,, -5, 3, 4, 2, 1, 1, 1, 1, 128, 154, 154, 154, 154, 104,, -5, 3, 4, 2, 1, 1, 1, 1, 256, 154, 154, 154, 154, 104,, -5, 3, 4, 2, 1, 1, 1, 1, 384, 154, 154, 154, 154, 104,, -5, 3, 4, 3, 1, 1, 1, 1, 128, 230, 230, 230, 230, 155,, -5, 3, 4, 3, 1, 1, 1, 1, 256, 230, 230, 230, 230, 155,, -5, 3, 4, 3, 1, 1, 1, 1, 384, 230, 230, 230, 230, 155,, -5, 3, 5, 1, 1, 1, 1, 1, 128, 78, 78, 78, 78, 53,, -5, 3, 5, 1, 1, 1, 1, 1, 256, 78, 78, 78, 78, 53,, -5, 3, 5, 1, 1, 1, 1, 1, 384, 78, 78, 78, 78, 53,, -5, 3, 5, 2, 1, 1, 1, 1, 128, 154, 154, 154, 154, 104,, -5, 3, 5, 2, 1, 1, 1, 1, 256, 154, 154, 154, 154, 104,, -5, 3, 5, 2, 1, 1, 1, 1, 384, 154, 154, 154, 154, 104,, -5, 3, 5, 3, 1, 1, 1, 1, 128, 230, 230, 230, 230, 155,, -5, 3, 5, 3, 1, 1, 1, 1, 256, 230, 230, 230, 230, 155,, -5, 3, 5, 3, 1, 1, 1, 1, 384, 230, 230, 230, 230, 155,, -5, 4, 1, 1, 1, 1, 1, 1, 128, 79, 79, 79, 54, 28,, -5, 4, 1, 1, 1, 1, 1, 1, 256, 79, 79, 79, 54, 28,, -5, 4, 1, 1, 1, 1, 1, 1, 384, 79, 79, 79, 54, 28,, -5, 4, 1, 2, 1, 1, 1, 1, 128, 155, 155, 155, 105, 53,, -5, 4, 1, 2, 1, 1, 1, 1, 256, 155, 155, 155, 105, 53,, -5, 4, 1, 2, 1, 1, 1, 1, 384, 155, 155, 155, 105, 53,, -5, 4, 1, 3, 1, 1, 1, 1, 128, 231, 231, 231, 156, 78,, -5, 4, 1, 3, 1, 1, 1, 1, 256, 231, 231, 231, 156, 78,, -5, 4, 1, 3, 1, 1, 1, 1, 384, 231, 231, 231, 156, 78,, -5, 4, 1, 4, 1, 1, 1, 1, 128, 240, 240, 240, 207, 103,, -5, 4, 1, 4, 1, 1, 1, 1, 256, 240, 240, 240, 207, 103,, -5, 4, 1, 4, 1, 1, 1, 1, 384, 240, 240, 240, 207, 103,, -5, 4, 2, 1, 1, 1, 1, 1, 128, 79, 79, 79, 54, 28,, -5, 4, 2, 1, 1, 1, 1, 1, 256, 79, 79, 79, 54, 28,, -5, 4, 2, 1, 1, 1, 1, 1, 384, 79, 79, 79, 54, 28,, -5, 4, 2, 2, 1, 1, 1, 1, 128, 155, 155, 155, 105, 53,, -5, 4, 2, 2, 1, 1, 1, 1, 256, 155, 155, 155, 105, 53,, -5, 4, 2, 2, 1, 1, 1, 1, 384, 155, 155, 155, 105, 53,, -5, 4, 2, 3, 1, 1, 1, 1, 128, 231, 231, 231, 156, 78,, -5, 4, 2, 3, 1, 1, 1, 1, 256, 231, 231, 231, 156, 78,, -5, 4, 2, 3, 1, 1, 1, 1, 384, 231, 231, 231, 156, 78,, -5, 4, 2, 4, 1, 1, 1, 1, 128, 240, 240, 240, 207, 103,, -5, 4, 2, 4, 1, 1, 1, 1, 256, 240, 240, 240, 207, 103,, -5, 4, 2, 4, 1, 1, 1, 1, 384, 240, 240, 240, 207, 103,, -5, 4, 3, 1, 1, 1, 1, 1, 128, 79, 79, 79, 54, 28,, -5, 4, 3, 1, 1, 1, 1, 1, 256, 79, 79, 79, 54, 28,, -5, 4, 3, 1, 1, 1, 1, 1, 384, 79, 79, 79, 54, 28,, -5, 4, 3, 2, 1, 1, 1, 1, 128, 155, 155, 155, 105, 53,, -5, 4, 3, 2, 1, 1, 1, 1, 256, 155, 155, 155, 105, 53,, -5, 4, 3, 2, 1, 1, 1, 1, 384, 155, 155, 155, 105, 53,, -5, 4, 3, 3, 1, 1, 1, 1, 128, 231, 231, 231, 156, 78,, -5, 4, 3, 3, 1, 1, 1, 1, 256, 231, 231, 231, 156, 78,, -5, 4, 3, 3, 1, 1, 1, 1, 384, 231, 231, 231, 156, 78,, -5, 4, 3, 4, 1, 1, 1, 1, 128, 240, 240, 240, 207, 103,, -5, 4, 3, 4, 1, 1, 1, 1, 256, 240, 240, 240, 207, 103,, -5, 4, 3, 4, 1, 1, 1, 1, 384, 240, 240, 240, 207, 103,, -5, 4, 4, 1, 1, 1, 1, 1, 128, 79, 79, 79, 54, 28,, -5, 4, 4, 1, 1, 1, 1, 1, 256, 79, 79, 79, 54, 28,, -5, 4, 4, 1, 1, 1, 1, 1, 384, 79, 79, 79, 54, 28,, -5, 4, 4, 2, 1, 1, 1, 1, 128, 155, 155, 155, 105, 53,, -5, 4, 4, 2, 1, 1, 1, 1, 256, 155, 155, 155, 105, 53,, -5, 4, 4, 2, 1, 1, 1, 1, 384, 155, 155, 155, 105, 53,, -5, 4, 4, 3, 1, 1, 1, 1, 128, 231, 231, 231, 156, 78,, -5, 4, 4, 3, 1, 1, 1, 1, 256, 231, 231, 231, 156, 78,, -5, 4, 4, 3, 1, 1, 1, 1, 384, 231, 231, 231, 156, 78,, -5, 4, 4, 4, 1, 1, 1, 1, 128, 240, 240, 240, 207, 103,, -5, 4, 4, 4, 1, 1, 1, 1, 256, 240, 240, 240, 207, 103,, -5, 4, 4, 4, 1, 1, 1, 1, 384, 240, 240, 240, 207, 103,, -5, 4, 5, 1, 1, 1, 1, 1, 128, 79, 79, 79, 54, 28,, -5, 4, 5, 1, 1, 1, 1, 1, 256, 79, 79, 79, 54, 28,, -5, 4, 5, 1, 1, 1, 1, 1, 384, 79, 79, 79, 54, 28,, -5, 4, 5, 2, 1, 1, 1, 1, 128, 155, 155, 155, 105, 53,, -5, 4, 5, 2, 1, 1, 1, 1, 256, 155, 155, 155, 105, 53,, -5, 4, 5, 2, 1, 1, 1, 1, 384, 155, 155, 155, 105, 53,, -5, 4, 5, 3, 1, 1, 1, 1, 128, 231, 231, 231, 156, 78,, -5, 4, 5, 3, 1, 1, 1, 1, 256, 231, 231, 231, 156, 78,, -5, 4, 5, 3, 1, 1, 1, 1, 384, 231, 231, 231, 156, 78,, -5, 4, 5, 4, 1, 1, 1, 1, 128, 240, 240, 240, 207, 103,, -5, 4, 5, 4, 1, 1, 1, 1, 256, 240, 240, 240, 207, 103,, -5, 4, 5, 4, 1, 1, 1, 1, 384, 240, 240, 240, 207, 103,, -5, 5, 1, 1, 1, 1, 1, 1, 128, 80, 80, 80, 55,,, -5, 5, 1, 1, 1, 1, 1, 1, 256, 80, 80, 80, 55,,, -5, 5, 1, 1, 1, 1, 1, 1, 384, 80, 80, 80, 55,,, -5, 5, 1, 2, 1, 1, 1, 1, 128, 156, 156, 156, 106,,, -5, 5, 1, 2, 1, 1, 1, 1, 256, 156, 156, 156, 106,,, -5, 5, 1, 2, 1, 1, 1, 1, 384, 156, 156, 156, 106,,, -5, 5, 1, 3, 1, 1, 1, 1, 128, 232, 232, 232, 157,,, -5, 5, 1, 3, 1, 1, 1, 1, 256, 232, 232, 232, 157,,, -5, 5, 1, 3, 1, 1, 1, 1, 384, 232, 232, 232, 157,,, -5, 5, 1, 4, 1, 1, 1, 1, 128, 240, 240, 240, 208,,, -5, 5, 1, 4, 1, 1, 1, 1, 256, 240, 240, 240, 208,,, -5, 5, 1, 4, 1, 1, 1, 1, 384, 240, 240, 240, 208,,, -5, 5, 1, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -5, 5, 1, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -5, 5, 1, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -5, 5, 2, 1, 1, 1, 1, 1, 128, 80, 80, 80, 55,,, -5, 5, 2, 1, 1, 1, 1, 1, 256, 80, 80, 80, 55,,, -5, 5, 2, 1, 1, 1, 1, 1, 384, 80, 80, 80, 55,,, -5, 5, 2, 2, 1, 1, 1, 1, 128, 156, 156, 156, 106,,, -5, 5, 2, 2, 1, 1, 1, 1, 256, 156, 156, 156, 106,,, -5, 5, 2, 2, 1, 1, 1, 1, 384, 156, 156, 156, 106,,, -5, 5, 2, 3, 1, 1, 1, 1, 128, 232, 232, 232, 157,,, -5, 5, 2, 3, 1, 1, 1, 1, 256, 232, 232, 232, 157,,, -5, 5, 2, 3, 1, 1, 1, 1, 384, 232, 232, 232, 157,,, -5, 5, 2, 4, 1, 1, 1, 1, 128, 240, 240, 240, 208,,, -5, 5, 2, 4, 1, 1, 1, 1, 256, 240, 240, 240, 208,,, -5, 5, 2, 4, 1, 1, 1, 1, 384, 240, 240, 240, 208,,, -5, 5, 2, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -5, 5, 2, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -5, 5, 2, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -5, 5, 3, 1, 1, 1, 1, 1, 128, 80, 80, 80, 55,,, -5, 5, 3, 1, 1, 1, 1, 1, 256, 80, 80, 80, 55,,, -5, 5, 3, 1, 1, 1, 1, 1, 384, 80, 80, 80, 55,,, -5, 5, 3, 2, 1, 1, 1, 1, 128, 156, 156, 156, 106,,, -5, 5, 3, 2, 1, 1, 1, 1, 256, 156, 156, 156, 106,,, -5, 5, 3, 2, 1, 1, 1, 1, 384, 156, 156, 156, 106,,, -5, 5, 3, 3, 1, 1, 1, 1, 128, 232, 232, 232, 157,,, -5, 5, 3, 3, 1, 1, 1, 1, 256, 232, 232, 232, 157,,, -5, 5, 3, 3, 1, 1, 1, 1, 384, 232, 232, 232, 157,,, -5, 5, 3, 4, 1, 1, 1, 1, 128, 240, 240, 240, 208,,, -5, 5, 3, 4, 1, 1, 1, 1, 256, 240, 240, 240, 208,,, -5, 5, 3, 4, 1, 1, 1, 1, 384, 240, 240, 240, 208,,, -5, 5, 3, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -5, 5, 3, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -5, 5, 3, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -5, 5, 4, 1, 1, 1, 1, 1, 128, 80, 80, 80, 55,,, -5, 5, 4, 1, 1, 1, 1, 1, 256, 80, 80, 80, 55,,, -5, 5, 4, 1, 1, 1, 1, 1, 384, 80, 80, 80, 55,,, -5, 5, 4, 2, 1, 1, 1, 1, 128, 156, 156, 156, 106,,, -5, 5, 4, 2, 1, 1, 1, 1, 256, 156, 156, 156, 106,,, -5, 5, 4, 2, 1, 1, 1, 1, 384, 156, 156, 156, 106,,, -5, 5, 4, 3, 1, 1, 1, 1, 128, 232, 232, 232, 157,,, -5, 5, 4, 3, 1, 1, 1, 1, 256, 232, 232, 232, 157,,, -5, 5, 4, 3, 1, 1, 1, 1, 384, 232, 232, 232, 157,,, -5, 5, 4, 4, 1, 1, 1, 1, 128, 240, 240, 240, 208,,, -5, 5, 4, 4, 1, 1, 1, 1, 256, 240, 240, 240, 208,,, -5, 5, 4, 4, 1, 1, 1, 1, 384, 240, 240, 240, 208,,, -5, 5, 4, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -5, 5, 4, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -5, 5, 4, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -5, 5, 5, 1, 1, 1, 1, 1, 128, 80, 80, 80, 55,,, -5, 5, 5, 1, 1, 1, 1, 1, 256, 80, 80, 80, 55,,, -5, 5, 5, 1, 1, 1, 1, 1, 384, 80, 80, 80, 55,,, -5, 5, 5, 2, 1, 1, 1, 1, 128, 156, 156, 156, 106,,, -5, 5, 5, 2, 1, 1, 1, 1, 256, 156, 156, 156, 106,,, -5, 5, 5, 2, 1, 1, 1, 1, 384, 156, 156, 156, 106,,, -5, 5, 5, 3, 1, 1, 1, 1, 128, 232, 232, 232, 157,,, -5, 5, 5, 3, 1, 1, 1, 1, 256, 232, 232, 232, 157,,, -5, 5, 5, 3, 1, 1, 1, 1, 384, 232, 232, 232, 157,,, -5, 5, 5, 4, 1, 1, 1, 1, 128, 240, 240, 240, 208,,, -5, 5, 5, 4, 1, 1, 1, 1, 256, 240, 240, 240, 208,,, -5, 5, 5, 4, 1, 1, 1, 1, 384, 240, 240, 240, 208,,, -5, 5, 5, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -5, 5, 5, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -5, 5, 5, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -5, 6, 1, 1, 1, 1, 1, 1, 128, 81, 81, 81, 56,,, -5, 6, 1, 1, 1, 1, 1, 1, 256, 81, 81, 81, 56,,, -5, 6, 1, 1, 1, 1, 1, 1, 384, 81, 81, 81, 56,,, -5, 6, 1, 2, 1, 1, 1, 1, 128, 157, 157, 157, 107,,, -5, 6, 1, 2, 1, 1, 1, 1, 256, 157, 157, 157, 107,,, -5, 6, 1, 2, 1, 1, 1, 1, 384, 157, 157, 157, 107,,, -5, 6, 1, 3, 1, 1, 1, 1, 128, 233, 233, 233, 158,,, -5, 6, 1, 3, 1, 1, 1, 1, 256, 233, 233, 233, 158,,, -5, 6, 1, 3, 1, 1, 1, 1, 384, 233, 233, 233, 158,,, -5, 6, 1, 4, 1, 1, 1, 1, 128, 240, 240, 240, 209,,, -5, 6, 1, 4, 1, 1, 1, 1, 256, 240, 240, 240, 209,,, -5, 6, 1, 4, 1, 1, 1, 1, 384, 240, 240, 240, 209,,, -5, 6, 1, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -5, 6, 1, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -5, 6, 1, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -5, 6, 1, 6, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -5, 6, 1, 6, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -5, 6, 1, 6, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -5, 6, 2, 1, 1, 1, 1, 1, 128, 81, 81, 81, 56,,, -5, 6, 2, 1, 1, 1, 1, 1, 256, 81, 81, 81, 56,,, -5, 6, 2, 1, 1, 1, 1, 1, 384, 81, 81, 81, 56,,, -5, 6, 2, 2, 1, 1, 1, 1, 128, 157, 157, 157, 107,,, -5, 6, 2, 2, 1, 1, 1, 1, 256, 157, 157, 157, 107,,, -5, 6, 2, 2, 1, 1, 1, 1, 384, 157, 157, 157, 107,,, -5, 6, 2, 3, 1, 1, 1, 1, 128, 233, 233, 233, 158,,, -5, 6, 2, 3, 1, 1, 1, 1, 256, 233, 233, 233, 158,,, -5, 6, 2, 3, 1, 1, 1, 1, 384, 233, 233, 233, 158,,, -5, 6, 2, 4, 1, 1, 1, 1, 128, 240, 240, 240, 209,,, -5, 6, 2, 4, 1, 1, 1, 1, 256, 240, 240, 240, 209,,, -5, 6, 2, 4, 1, 1, 1, 1, 384, 240, 240, 240, 209,,, -5, 6, 2, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -5, 6, 2, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -5, 6, 2, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -5, 6, 2, 6, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -5, 6, 2, 6, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -5, 6, 2, 6, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -5, 6, 3, 1, 1, 1, 1, 1, 128, 81, 81, 81, 56,,, -5, 6, 3, 1, 1, 1, 1, 1, 256, 81, 81, 81, 56,,, -5, 6, 3, 1, 1, 1, 1, 1, 384, 81, 81, 81, 56,,, -5, 6, 3, 2, 1, 1, 1, 1, 128, 157, 157, 157, 107,,, -5, 6, 3, 2, 1, 1, 1, 1, 256, 157, 157, 157, 107,,, -5, 6, 3, 2, 1, 1, 1, 1, 384, 157, 157, 157, 107,,, -5, 6, 3, 3, 1, 1, 1, 1, 128, 233, 233, 233, 158,,, -5, 6, 3, 3, 1, 1, 1, 1, 256, 233, 233, 233, 158,,, -5, 6, 3, 3, 1, 1, 1, 1, 384, 233, 233, 233, 158,,, -5, 6, 3, 4, 1, 1, 1, 1, 128, 240, 240, 240, 209,,, -5, 6, 3, 4, 1, 1, 1, 1, 256, 240, 240, 240, 209,,, -5, 6, 3, 4, 1, 1, 1, 1, 384, 240, 240, 240, 209,,, -5, 6, 3, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -5, 6, 3, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -5, 6, 3, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -5, 6, 3, 6, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -5, 6, 3, 6, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -5, 6, 3, 6, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -5, 6, 4, 1, 1, 1, 1, 1, 128, 81, 81, 81, 56,,, -5, 6, 4, 1, 1, 1, 1, 1, 256, 81, 81, 81, 56,,, -5, 6, 4, 1, 1, 1, 1, 1, 384, 81, 81, 81, 56,,, -5, 6, 4, 2, 1, 1, 1, 1, 128, 157, 157, 157, 107,,, -5, 6, 4, 2, 1, 1, 1, 1, 256, 157, 157, 157, 107,,, -5, 6, 4, 2, 1, 1, 1, 1, 384, 157, 157, 157, 107,,, -5, 6, 4, 3, 1, 1, 1, 1, 128, 233, 233, 233, 158,,, -5, 6, 4, 3, 1, 1, 1, 1, 256, 233, 233, 233, 158,,, -5, 6, 4, 3, 1, 1, 1, 1, 384, 233, 233, 233, 158,,, -5, 6, 4, 4, 1, 1, 1, 1, 128, 240, 240, 240, 209,,, -5, 6, 4, 4, 1, 1, 1, 1, 256, 240, 240, 240, 209,,, -5, 6, 4, 4, 1, 1, 1, 1, 384, 240, 240, 240, 209,,, -5, 6, 4, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -5, 6, 4, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -5, 6, 4, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -5, 6, 4, 6, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -5, 6, 4, 6, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -5, 6, 4, 6, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -5, 6, 5, 1, 1, 1, 1, 1, 128, 81, 81, 81, 56,,, -5, 6, 5, 1, 1, 1, 1, 1, 256, 81, 81, 81, 56,,, -5, 6, 5, 1, 1, 1, 1, 1, 384, 81, 81, 81, 56,,, -5, 6, 5, 2, 1, 1, 1, 1, 128, 157, 157, 157, 107,,, -5, 6, 5, 2, 1, 1, 1, 1, 256, 157, 157, 157, 107,,, -5, 6, 5, 2, 1, 1, 1, 1, 384, 157, 157, 157, 107,,, -5, 6, 5, 3, 1, 1, 1, 1, 128, 233, 233, 233, 158,,, -5, 6, 5, 3, 1, 1, 1, 1, 256, 233, 233, 233, 158,,, -5, 6, 5, 3, 1, 1, 1, 1, 384, 233, 233, 233, 158,,, -5, 6, 5, 4, 1, 1, 1, 1, 128, 240, 240, 240, 209,,, -5, 6, 5, 4, 1, 1, 1, 1, 256, 240, 240, 240, 209,,, -5, 6, 5, 4, 1, 1, 1, 1, 384, 240, 240, 240, 209,,, -5, 6, 5, 5, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -5, 6, 5, 5, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -5, 6, 5, 5, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -5, 6, 5, 6, 1, 1, 1, 1, 128, 240, 240, 240, 240,,, -5, 6, 5, 6, 1, 1, 1, 1, 256, 240, 240, 240, 240,,, -5, 6, 5, 6, 1, 1, 1, 1, 384, 240, 240, 240, 240,,, -5, 7, 1, 1, 1, 1, 1, 1, 128, 82, 82, 57, 31,,, -5, 7, 1, 1, 1, 1, 1, 1, 256, 82, 82, 57, 31,,, -5, 7, 1, 1, 1, 1, 1, 1, 384, 82, 82, 57, 31,,, -5, 7, 1, 2, 1, 1, 1, 1, 128, 158, 158, 108, 56,,, -5, 7, 1, 2, 1, 1, 1, 1, 256, 158, 158, 108, 56,,, -5, 7, 1, 2, 1, 1, 1, 1, 384, 158, 158, 108, 56,,, -5, 7, 1, 3, 1, 1, 1, 1, 128, 234, 234, 159, 81,,, -5, 7, 1, 3, 1, 1, 1, 1, 256, 234, 234, 159, 81,,, -5, 7, 1, 3, 1, 1, 1, 1, 384, 234, 234, 159, 81,,, -5, 7, 1, 4, 1, 1, 1, 1, 128, 240, 240, 210, 106,,, -5, 7, 1, 4, 1, 1, 1, 1, 256, 240, 240, 210, 106,,, -5, 7, 1, 4, 1, 1, 1, 1, 384, 240, 240, 210, 106,,, -5, 7, 1, 5, 1, 1, 1, 1, 128, 240, 240, 240, 131,,, -5, 7, 1, 5, 1, 1, 1, 1, 256, 240, 240, 240, 131,,, -5, 7, 1, 5, 1, 1, 1, 1, 384, 240, 240, 240, 131,,, -5, 7, 1, 6, 1, 1, 1, 1, 128, 240, 240, 240, 156,,, -5, 7, 1, 6, 1, 1, 1, 1, 256, 240, 240, 240, 156,,, -5, 7, 1, 6, 1, 1, 1, 1, 384, 240, 240, 240, 156,,, -5, 7, 1, 7, 1, 1, 1, 1, 128, 240, 240, 240, 181,,, -5, 7, 1, 7, 1, 1, 1, 1, 256, 240, 240, 240, 181,,, -5, 7, 1, 7, 1, 1, 1, 1, 384, 240, 240, 240, 181,,, -5, 7, 2, 1, 1, 1, 1, 1, 128, 82, 82, 57, 31,,, -5, 7, 2, 1, 1, 1, 1, 1, 256, 82, 82, 57, 31,,, -5, 7, 2, 1, 1, 1, 1, 1, 384, 82, 82, 57, 31,,, -5, 7, 2, 2, 1, 1, 1, 1, 128, 158, 158, 108, 56,,, -5, 7, 2, 2, 1, 1, 1, 1, 256, 158, 158, 108, 56,,, -5, 7, 2, 2, 1, 1, 1, 1, 384, 158, 158, 108, 56,,, -5, 7, 2, 3, 1, 1, 1, 1, 128, 234, 234, 159, 81,,, -5, 7, 2, 3, 1, 1, 1, 1, 256, 234, 234, 159, 81,,, -5, 7, 2, 3, 1, 1, 1, 1, 384, 234, 234, 159, 81,,, -5, 7, 2, 4, 1, 1, 1, 1, 128, 240, 240, 210, 106,,, -5, 7, 2, 4, 1, 1, 1, 1, 256, 240, 240, 210, 106,,, -5, 7, 2, 4, 1, 1, 1, 1, 384, 240, 240, 210, 106,,, -5, 7, 2, 5, 1, 1, 1, 1, 128, 240, 240, 240, 131,,, -5, 7, 2, 5, 1, 1, 1, 1, 256, 240, 240, 240, 131,,, -5, 7, 2, 5, 1, 1, 1, 1, 384, 240, 240, 240, 131,,, -5, 7, 2, 6, 1, 1, 1, 1, 128, 240, 240, 240, 156,,, -5, 7, 2, 6, 1, 1, 1, 1, 256, 240, 240, 240, 156,,, -5, 7, 2, 6, 1, 1, 1, 1, 384, 240, 240, 240, 156,,, -5, 7, 2, 7, 1, 1, 1, 1, 128, 240, 240, 240, 181,,, -5, 7, 2, 7, 1, 1, 1, 1, 256, 240, 240, 240, 181,,, -5, 7, 2, 7, 1, 1, 1, 1, 384, 240, 240, 240, 181,,, -5, 7, 3, 1, 1, 1, 1, 1, 128, 82, 82, 57, 31,,, -5, 7, 3, 1, 1, 1, 1, 1, 256, 82, 82, 57, 31,,, -5, 7, 3, 1, 1, 1, 1, 1, 384, 82, 82, 57, 31,,, -5, 7, 3, 2, 1, 1, 1, 1, 128, 158, 158, 108, 56,,, -5, 7, 3, 2, 1, 1, 1, 1, 256, 158, 158, 108, 56,,, -5, 7, 3, 2, 1, 1, 1, 1, 384, 158, 158, 108, 56,,, -5, 7, 3, 3, 1, 1, 1, 1, 128, 234, 234, 159, 81,,, -5, 7, 3, 3, 1, 1, 1, 1, 256, 234, 234, 159, 81,,, -5, 7, 3, 3, 1, 1, 1, 1, 384, 234, 234, 159, 81,,, -5, 7, 3, 4, 1, 1, 1, 1, 128, 240, 240, 210, 106,,, -5, 7, 3, 4, 1, 1, 1, 1, 256, 240, 240, 210, 106,,, -5, 7, 3, 4, 1, 1, 1, 1, 384, 240, 240, 210, 106,,, -5, 7, 3, 5, 1, 1, 1, 1, 128, 240, 240, 240, 131,,, -5, 7, 3, 5, 1, 1, 1, 1, 256, 240, 240, 240, 131,,, -5, 7, 3, 5, 1, 1, 1, 1, 384, 240, 240, 240, 131,,, -5, 7, 3, 6, 1, 1, 1, 1, 128, 240, 240, 240, 156,,, -5, 7, 3, 6, 1, 1, 1, 1, 256, 240, 240, 240, 156,,, -5, 7, 3, 6, 1, 1, 1, 1, 384, 240, 240, 240, 156,,, -5, 7, 3, 7, 1, 1, 1, 1, 128, 240, 240, 240, 181,,, -5, 7, 3, 7, 1, 1, 1, 1, 256, 240, 240, 240, 181,,, -5, 7, 3, 7, 1, 1, 1, 1, 384, 240, 240, 240, 181,,, -5, 7, 4, 1, 1, 1, 1, 1, 128, 82, 82, 57, 31,,, -5, 7, 4, 1, 1, 1, 1, 1, 256, 82, 82, 57, 31,,, -5, 7, 4, 1, 1, 1, 1, 1, 384, 82, 82, 57, 31,,, -5, 7, 4, 2, 1, 1, 1, 1, 128, 158, 158, 108, 56,,, -5, 7, 4, 2, 1, 1, 1, 1, 256, 158, 158, 108, 56,,, -5, 7, 4, 2, 1, 1, 1, 1, 384, 158, 158, 108, 56,,, -5, 7, 4, 3, 1, 1, 1, 1, 128, 234, 234, 159, 81,,, -5, 7, 4, 3, 1, 1, 1, 1, 256, 234, 234, 159, 81,,, -5, 7, 4, 3, 1, 1, 1, 1, 384, 234, 234, 159, 81,,, -5, 7, 4, 4, 1, 1, 1, 1, 128, 240, 240, 210, 106,,, -5, 7, 4, 4, 1, 1, 1, 1, 256, 240, 240, 210, 106,,, -5, 7, 4, 4, 1, 1, 1, 1, 384, 240, 240, 210, 106,,, -5, 7, 4, 5, 1, 1, 1, 1, 128, 240, 240, 240, 131,,, -5, 7, 4, 5, 1, 1, 1, 1, 256, 240, 240, 240, 131,,, -5, 7, 4, 5, 1, 1, 1, 1, 384, 240, 240, 240, 131,,, -5, 7, 4, 6, 1, 1, 1, 1, 128, 240, 240, 240, 156,,, -5, 7, 4, 6, 1, 1, 1, 1, 256, 240, 240, 240, 156,,, -5, 7, 4, 6, 1, 1, 1, 1, 384, 240, 240, 240, 156,,, -5, 7, 4, 7, 1, 1, 1, 1, 128, 240, 240, 240, 181,,, -5, 7, 4, 7, 1, 1, 1, 1, 256, 240, 240, 240, 181,,, -5, 7, 4, 7, 1, 1, 1, 1, 384, 240, 240, 240, 181,,, -5, 7, 5, 1, 1, 1, 1, 1, 128, 82, 82, 57, 31,,, -5, 7, 5, 1, 1, 1, 1, 1, 256, 82, 82, 57, 31,,, -5, 7, 5, 1, 1, 1, 1, 1, 384, 82, 82, 57, 31,,, -5, 7, 5, 2, 1, 1, 1, 1, 128, 158, 158, 108, 56,,, -5, 7, 5, 2, 1, 1, 1, 1, 256, 158, 158, 108, 56,,, -5, 7, 5, 2, 1, 1, 1, 1, 384, 158, 158, 108, 56,,, -5, 7, 5, 3, 1, 1, 1, 1, 128, 234, 234, 159, 81,,, -5, 7, 5, 3, 1, 1, 1, 1, 256, 234, 234, 159, 81,,, -5, 7, 5, 3, 1, 1, 1, 1, 384, 234, 234, 159, 81,,, -5, 7, 5, 4, 1, 1, 1, 1, 128, 240, 240, 210, 106,,, -5, 7, 5, 4, 1, 1, 1, 1, 256, 240, 240, 210, 106,,, -5, 7, 5, 4, 1, 1, 1, 1, 384, 240, 240, 210, 106,,, -5, 7, 5, 5, 1, 1, 1, 1, 128, 240, 240, 240, 131,,, -5, 7, 5, 5, 1, 1, 1, 1, 256, 240, 240, 240, 131,,, -5, 7, 5, 5, 1, 1, 1, 1, 384, 240, 240, 240, 131,,, -5, 7, 5, 6, 1, 1, 1, 1, 128, 240, 240, 240, 156,,, -5, 7, 5, 6, 1, 1, 1, 1, 256, 240, 240, 240, 156,,, -5, 7, 5, 6, 1, 1, 1, 1, 384, 240, 240, 240, 156,,, -5, 7, 5, 7, 1, 1, 1, 1, 128, 240, 240, 240, 181,,, -5, 7, 5, 7, 1, 1, 1, 1, 256, 240, 240, 240, 181,,, -5, 7, 5, 7, 1, 1, 1, 1, 384, 240, 240, 240, 181,,, -6, 1, 1, 1, 1, 1, 1, 1, 128, 64, 64, 64, 64, 64, 42, 21 -6, 1, 1, 1, 1, 1, 1, 1, 256, 64, 64, 64, 64, 64, 42, 21 -6, 1, 1, 1, 1, 1, 1, 1, 384, 64, 64, 64, 64, 64, 42, 21 -6, 1, 2, 1, 1, 1, 1, 1, 128, 64, 64, 64, 64, 64, 42, 21 -6, 1, 2, 1, 1, 1, 1, 1, 256, 64, 64, 64, 64, 64, 42, 21 -6, 1, 2, 1, 1, 1, 1, 1, 384, 64, 64, 64, 64, 64, 42, 21 -6, 1, 3, 1, 1, 1, 1, 1, 128, 64, 64, 64, 64, 64, 42, 21 -6, 1, 3, 1, 1, 1, 1, 1, 256, 64, 64, 64, 64, 64, 42, 21 -6, 1, 3, 1, 1, 1, 1, 1, 384, 64, 64, 64, 64, 64, 42, 21 -6, 1, 4, 1, 1, 1, 1, 1, 128, 64, 64, 64, 64, 64, 42, 21 -6, 1, 4, 1, 1, 1, 1, 1, 256, 64, 64, 64, 64, 64, 42, 21 -6, 1, 4, 1, 1, 1, 1, 1, 384, 64, 64, 64, 64, 64, 42, 21 -6, 1, 5, 1, 1, 1, 1, 1, 128, 64, 64, 64, 64, 64, 42, 21 -6, 1, 5, 1, 1, 1, 1, 1, 256, 64, 64, 64, 64, 64, 42, 21 -6, 1, 5, 1, 1, 1, 1, 1, 384, 64, 64, 64, 64, 64, 42, 21 -6, 1, 6, 1, 1, 1, 1, 1, 128, 64, 64, 64, 64, 64, 42, 21 -6, 1, 6, 1, 1, 1, 1, 1, 256, 64, 64, 64, 64, 64, 42, 21 -6, 1, 6, 1, 1, 1, 1, 1, 384, 64, 64, 64, 64, 64, 42, 21 -6, 2, 1, 1, 1, 1, 1, 1, 128, 65, 65, 65, 65, 43, 22, -6, 2, 1, 1, 1, 1, 1, 1, 256, 65, 65, 65, 65, 43, 22, -6, 2, 1, 1, 1, 1, 1, 1, 384, 65, 65, 65, 65, 43, 22, -6, 2, 1, 2, 1, 1, 1, 1, 128, 129, 129, 129, 129, 85, 43, -6, 2, 1, 2, 1, 1, 1, 1, 256, 129, 129, 129, 129, 85, 43, -6, 2, 1, 2, 1, 1, 1, 1, 384, 129, 129, 129, 129, 85, 43, -6, 2, 2, 1, 1, 1, 1, 1, 128, 65, 65, 65, 65, 43, 22, -6, 2, 2, 1, 1, 1, 1, 1, 256, 65, 65, 65, 65, 43, 22, -6, 2, 2, 1, 1, 1, 1, 1, 384, 65, 65, 65, 65, 43, 22, -6, 2, 2, 2, 1, 1, 1, 1, 128, 129, 129, 129, 129, 85, 43, -6, 2, 2, 2, 1, 1, 1, 1, 256, 129, 129, 129, 129, 85, 43, -6, 2, 2, 2, 1, 1, 1, 1, 384, 129, 129, 129, 129, 85, 43, -6, 2, 3, 1, 1, 1, 1, 1, 128, 65, 65, 65, 65, 43, 22, -6, 2, 3, 1, 1, 1, 1, 1, 256, 65, 65, 65, 65, 43, 22, -6, 2, 3, 1, 1, 1, 1, 1, 384, 65, 65, 65, 65, 43, 22, -6, 2, 3, 2, 1, 1, 1, 1, 128, 129, 129, 129, 129, 85, 43, -6, 2, 3, 2, 1, 1, 1, 1, 256, 129, 129, 129, 129, 85, 43, -6, 2, 3, 2, 1, 1, 1, 1, 384, 129, 129, 129, 129, 85, 43, -6, 2, 4, 1, 1, 1, 1, 1, 128, 65, 65, 65, 65, 43, 22, -6, 2, 4, 1, 1, 1, 1, 1, 256, 65, 65, 65, 65, 43, 22, -6, 2, 4, 1, 1, 1, 1, 1, 384, 65, 65, 65, 65, 43, 22, -6, 2, 4, 2, 1, 1, 1, 1, 128, 129, 129, 129, 129, 85, 43, -6, 2, 4, 2, 1, 1, 1, 1, 256, 129, 129, 129, 129, 85, 43, -6, 2, 4, 2, 1, 1, 1, 1, 384, 129, 129, 129, 129, 85, 43, -6, 2, 5, 1, 1, 1, 1, 1, 128, 65, 65, 65, 65, 43, 22, -6, 2, 5, 1, 1, 1, 1, 1, 256, 65, 65, 65, 65, 43, 22, -6, 2, 5, 1, 1, 1, 1, 1, 384, 65, 65, 65, 65, 43, 22, -6, 2, 5, 2, 1, 1, 1, 1, 128, 129, 129, 129, 129, 85, 43, -6, 2, 5, 2, 1, 1, 1, 1, 256, 129, 129, 129, 129, 85, 43, -6, 2, 5, 2, 1, 1, 1, 1, 384, 129, 129, 129, 129, 85, 43, -6, 2, 6, 1, 1, 1, 1, 1, 128, 65, 65, 65, 65, 43, 22, -6, 2, 6, 1, 1, 1, 1, 1, 256, 65, 65, 65, 65, 43, 22, -6, 2, 6, 1, 1, 1, 1, 1, 384, 65, 65, 65, 65, 43, 22, -6, 2, 6, 2, 1, 1, 1, 1, 128, 129, 129, 129, 129, 85, 43, -6, 2, 6, 2, 1, 1, 1, 1, 256, 129, 129, 129, 129, 85, 43, -6, 2, 6, 2, 1, 1, 1, 1, 384, 129, 129, 129, 129, 85, 43, -6, 3, 1, 1, 1, 1, 1, 1, 128, 66, 66, 66, 44, 23,, -6, 3, 1, 1, 1, 1, 1, 1, 256, 66, 66, 66, 44, 23,, -6, 3, 1, 1, 1, 1, 1, 1, 384, 66, 66, 66, 44, 23,, -6, 3, 1, 2, 1, 1, 1, 1, 128, 130, 130, 130, 86, 44,, -6, 3, 1, 2, 1, 1, 1, 1, 256, 130, 130, 130, 86, 44,, -6, 3, 1, 2, 1, 1, 1, 1, 384, 130, 130, 130, 86, 44,, -6, 3, 1, 3, 1, 1, 1, 1, 128, 194, 194, 194, 128, 65,, -6, 3, 1, 3, 1, 1, 1, 1, 256, 194, 194, 194, 128, 65,, -6, 3, 1, 3, 1, 1, 1, 1, 384, 194, 194, 194, 128, 65,, -6, 3, 2, 1, 1, 1, 1, 1, 128, 66, 66, 66, 44, 23,, -6, 3, 2, 1, 1, 1, 1, 1, 256, 66, 66, 66, 44, 23,, -6, 3, 2, 1, 1, 1, 1, 1, 384, 66, 66, 66, 44, 23,, -6, 3, 2, 2, 1, 1, 1, 1, 128, 130, 130, 130, 86, 44,, -6, 3, 2, 2, 1, 1, 1, 1, 256, 130, 130, 130, 86, 44,, -6, 3, 2, 2, 1, 1, 1, 1, 384, 130, 130, 130, 86, 44,, -6, 3, 2, 3, 1, 1, 1, 1, 128, 194, 194, 194, 128, 65,, -6, 3, 2, 3, 1, 1, 1, 1, 256, 194, 194, 194, 128, 65,, -6, 3, 2, 3, 1, 1, 1, 1, 384, 194, 194, 194, 128, 65,, -6, 3, 3, 1, 1, 1, 1, 1, 128, 66, 66, 66, 44, 23,, -6, 3, 3, 1, 1, 1, 1, 1, 256, 66, 66, 66, 44, 23,, -6, 3, 3, 1, 1, 1, 1, 1, 384, 66, 66, 66, 44, 23,, -6, 3, 3, 2, 1, 1, 1, 1, 128, 130, 130, 130, 86, 44,, -6, 3, 3, 2, 1, 1, 1, 1, 256, 130, 130, 130, 86, 44,, -6, 3, 3, 2, 1, 1, 1, 1, 384, 130, 130, 130, 86, 44,, -6, 3, 3, 3, 1, 1, 1, 1, 128, 194, 194, 194, 128, 65,, -6, 3, 3, 3, 1, 1, 1, 1, 256, 194, 194, 194, 128, 65,, -6, 3, 3, 3, 1, 1, 1, 1, 384, 194, 194, 194, 128, 65,, -6, 3, 4, 1, 1, 1, 1, 1, 128, 66, 66, 66, 44, 23,, -6, 3, 4, 1, 1, 1, 1, 1, 256, 66, 66, 66, 44, 23,, -6, 3, 4, 1, 1, 1, 1, 1, 384, 66, 66, 66, 44, 23,, -6, 3, 4, 2, 1, 1, 1, 1, 128, 130, 130, 130, 86, 44,, -6, 3, 4, 2, 1, 1, 1, 1, 256, 130, 130, 130, 86, 44,, -6, 3, 4, 2, 1, 1, 1, 1, 384, 130, 130, 130, 86, 44,, -6, 3, 4, 3, 1, 1, 1, 1, 128, 194, 194, 194, 128, 65,, -6, 3, 4, 3, 1, 1, 1, 1, 256, 194, 194, 194, 128, 65,, -6, 3, 4, 3, 1, 1, 1, 1, 384, 194, 194, 194, 128, 65,, -6, 3, 5, 1, 1, 1, 1, 1, 128, 66, 66, 66, 44, 23,, -6, 3, 5, 1, 1, 1, 1, 1, 256, 66, 66, 66, 44, 23,, -6, 3, 5, 1, 1, 1, 1, 1, 384, 66, 66, 66, 44, 23,, -6, 3, 5, 2, 1, 1, 1, 1, 128, 130, 130, 130, 86, 44,, -6, 3, 5, 2, 1, 1, 1, 1, 256, 130, 130, 130, 86, 44,, -6, 3, 5, 2, 1, 1, 1, 1, 384, 130, 130, 130, 86, 44,, -6, 3, 5, 3, 1, 1, 1, 1, 128, 194, 194, 194, 128, 65,, -6, 3, 5, 3, 1, 1, 1, 1, 256, 194, 194, 194, 128, 65,, -6, 3, 5, 3, 1, 1, 1, 1, 384, 194, 194, 194, 128, 65,, -6, 3, 6, 1, 1, 1, 1, 1, 128, 66, 66, 66, 44, 23,, -6, 3, 6, 1, 1, 1, 1, 1, 256, 66, 66, 66, 44, 23,, -6, 3, 6, 1, 1, 1, 1, 1, 384, 66, 66, 66, 44, 23,, -6, 3, 6, 2, 1, 1, 1, 1, 128, 130, 130, 130, 86, 44,, -6, 3, 6, 2, 1, 1, 1, 1, 256, 130, 130, 130, 86, 44,, -6, 3, 6, 2, 1, 1, 1, 1, 384, 130, 130, 130, 86, 44,, -6, 3, 6, 3, 1, 1, 1, 1, 128, 194, 194, 194, 128, 65,, -6, 3, 6, 3, 1, 1, 1, 1, 256, 194, 194, 194, 128, 65,, -6, 3, 6, 3, 1, 1, 1, 1, 384, 194, 194, 194, 128, 65,, -6, 4, 1, 1, 1, 1, 1, 1, 128, 67, 67, 67, 45, 24,, -6, 4, 1, 1, 1, 1, 1, 1, 256, 67, 67, 67, 45, 24,, -6, 4, 1, 1, 1, 1, 1, 1, 384, 67, 67, 67, 45, 24,, -6, 4, 1, 2, 1, 1, 1, 1, 128, 131, 131, 131, 87, 45,, -6, 4, 1, 2, 1, 1, 1, 1, 256, 131, 131, 131, 87, 45,, -6, 4, 1, 2, 1, 1, 1, 1, 384, 131, 131, 131, 87, 45,, -6, 4, 1, 3, 1, 1, 1, 1, 128, 195, 195, 195, 129, 66,, -6, 4, 1, 3, 1, 1, 1, 1, 256, 195, 195, 195, 129, 66,, -6, 4, 1, 3, 1, 1, 1, 1, 384, 195, 195, 195, 129, 66,, -6, 4, 1, 4, 1, 1, 1, 1, 128, 240, 240, 240, 171, 87,, -6, 4, 1, 4, 1, 1, 1, 1, 256, 240, 240, 240, 171, 87,, -6, 4, 1, 4, 1, 1, 1, 1, 384, 240, 240, 240, 171, 87,, -6, 4, 2, 1, 1, 1, 1, 1, 128, 67, 67, 67, 45, 24,, -6, 4, 2, 1, 1, 1, 1, 1, 256, 67, 67, 67, 45, 24,, -6, 4, 2, 1, 1, 1, 1, 1, 384, 67, 67, 67, 45, 24,, -6, 4, 2, 2, 1, 1, 1, 1, 128, 131, 131, 131, 87, 45,, -6, 4, 2, 2, 1, 1, 1, 1, 256, 131, 131, 131, 87, 45,, -6, 4, 2, 2, 1, 1, 1, 1, 384, 131, 131, 131, 87, 45,, -6, 4, 2, 3, 1, 1, 1, 1, 128, 195, 195, 195, 129, 66,, -6, 4, 2, 3, 1, 1, 1, 1, 256, 195, 195, 195, 129, 66,, -6, 4, 2, 3, 1, 1, 1, 1, 384, 195, 195, 195, 129, 66,, -6, 4, 2, 4, 1, 1, 1, 1, 128, 240, 240, 240, 171, 87,, -6, 4, 2, 4, 1, 1, 1, 1, 256, 240, 240, 240, 171, 87,, -6, 4, 2, 4, 1, 1, 1, 1, 384, 240, 240, 240, 171, 87,, -6, 4, 3, 1, 1, 1, 1, 1, 128, 67, 67, 67, 45, 24,, -6, 4, 3, 1, 1, 1, 1, 1, 256, 67, 67, 67, 45, 24,, -6, 4, 3, 1, 1, 1, 1, 1, 384, 67, 67, 67, 45, 24,, -6, 4, 3, 2, 1, 1, 1, 1, 128, 131, 131, 131, 87, 45,, -6, 4, 3, 2, 1, 1, 1, 1, 256, 131, 131, 131, 87, 45,, -6, 4, 3, 2, 1, 1, 1, 1, 384, 131, 131, 131, 87, 45,, -6, 4, 3, 3, 1, 1, 1, 1, 128, 195, 195, 195, 129, 66,, -6, 4, 3, 3, 1, 1, 1, 1, 256, 195, 195, 195, 129, 66,, -6, 4, 3, 3, 1, 1, 1, 1, 384, 195, 195, 195, 129, 66,, -6, 4, 3, 4, 1, 1, 1, 1, 128, 240, 240, 240, 171, 87,, -6, 4, 3, 4, 1, 1, 1, 1, 256, 240, 240, 240, 171, 87,, -6, 4, 3, 4, 1, 1, 1, 1, 384, 240, 240, 240, 171, 87,, -6, 4, 4, 1, 1, 1, 1, 1, 128, 67, 67, 67, 45, 24,, -6, 4, 4, 1, 1, 1, 1, 1, 256, 67, 67, 67, 45, 24,, -6, 4, 4, 1, 1, 1, 1, 1, 384, 67, 67, 67, 45, 24,, -6, 4, 4, 2, 1, 1, 1, 1, 128, 131, 131, 131, 87, 45,, -6, 4, 4, 2, 1, 1, 1, 1, 256, 131, 131, 131, 87, 45,, -6, 4, 4, 2, 1, 1, 1, 1, 384, 131, 131, 131, 87, 45,, -6, 4, 4, 3, 1, 1, 1, 1, 128, 195, 195, 195, 129, 66,, -6, 4, 4, 3, 1, 1, 1, 1, 256, 195, 195, 195, 129, 66,, -6, 4, 4, 3, 1, 1, 1, 1, 384, 195, 195, 195, 129, 66,, -6, 4, 4, 4, 1, 1, 1, 1, 128, 240, 240, 240, 171, 87,, -6, 4, 4, 4, 1, 1, 1, 1, 256, 240, 240, 240, 171, 87,, -6, 4, 4, 4, 1, 1, 1, 1, 384, 240, 240, 240, 171, 87,, -6, 4, 5, 1, 1, 1, 1, 1, 128, 67, 67, 67, 45, 24,, -6, 4, 5, 1, 1, 1, 1, 1, 256, 67, 67, 67, 45, 24,, -6, 4, 5, 1, 1, 1, 1, 1, 384, 67, 67, 67, 45, 24,, -6, 4, 5, 2, 1, 1, 1, 1, 128, 131, 131, 131, 87, 45,, -6, 4, 5, 2, 1, 1, 1, 1, 256, 131, 131, 131, 87, 45,, -6, 4, 5, 2, 1, 1, 1, 1, 384, 131, 131, 131, 87, 45,, -6, 4, 5, 3, 1, 1, 1, 1, 128, 195, 195, 195, 129, 66,, -6, 4, 5, 3, 1, 1, 1, 1, 256, 195, 195, 195, 129, 66,, -6, 4, 5, 3, 1, 1, 1, 1, 384, 195, 195, 195, 129, 66,, -6, 4, 5, 4, 1, 1, 1, 1, 128, 240, 240, 240, 171, 87,, -6, 4, 5, 4, 1, 1, 1, 1, 256, 240, 240, 240, 171, 87,, -6, 4, 5, 4, 1, 1, 1, 1, 384, 240, 240, 240, 171, 87,, -6, 4, 6, 1, 1, 1, 1, 1, 128, 67, 67, 67, 45, 24,, -6, 4, 6, 1, 1, 1, 1, 1, 256, 67, 67, 67, 45, 24,, -6, 4, 6, 1, 1, 1, 1, 1, 384, 67, 67, 67, 45, 24,, -6, 4, 6, 2, 1, 1, 1, 1, 128, 131, 131, 131, 87, 45,, -6, 4, 6, 2, 1, 1, 1, 1, 256, 131, 131, 131, 87, 45,, -6, 4, 6, 2, 1, 1, 1, 1, 384, 131, 131, 131, 87, 45,, -6, 4, 6, 3, 1, 1, 1, 1, 128, 195, 195, 195, 129, 66,, -6, 4, 6, 3, 1, 1, 1, 1, 256, 195, 195, 195, 129, 66,, -6, 4, 6, 3, 1, 1, 1, 1, 384, 195, 195, 195, 129, 66,, -6, 4, 6, 4, 1, 1, 1, 1, 128, 240, 240, 240, 171, 87,, -6, 4, 6, 4, 1, 1, 1, 1, 256, 240, 240, 240, 171, 87,, -6, 4, 6, 4, 1, 1, 1, 1, 384, 240, 240, 240, 171, 87,, -6, 5, 1, 1, 1, 1, 1, 1, 128, 68, 68, 68, 46,,, -6, 5, 1, 1, 1, 1, 1, 1, 256, 68, 68, 68, 46,,, -6, 5, 1, 1, 1, 1, 1, 1, 384, 68, 68, 68, 46,,, -6, 5, 1, 2, 1, 1, 1, 1, 128, 132, 132, 132, 88,,, -6, 5, 1, 2, 1, 1, 1, 1, 256, 132, 132, 132, 88,,, -6, 5, 1, 2, 1, 1, 1, 1, 384, 132, 132, 132, 88,,, -6, 5, 1, 3, 1, 1, 1, 1, 128, 196, 196, 196, 130,,, -6, 5, 1, 3, 1, 1, 1, 1, 256, 196, 196, 196, 130,,, -6, 5, 1, 3, 1, 1, 1, 1, 384, 196, 196, 196, 130,,, -6, 5, 1, 4, 1, 1, 1, 1, 128, 240, 240, 240, 172,,, -6, 5, 1, 4, 1, 1, 1, 1, 256, 240, 240, 240, 172,,, -6, 5, 1, 4, 1, 1, 1, 1, 384, 240, 240, 240, 172,,, -6, 5, 1, 5, 1, 1, 1, 1, 128, 240, 240, 240, 214,,, -6, 5, 1, 5, 1, 1, 1, 1, 256, 240, 240, 240, 214,,, -6, 5, 1, 5, 1, 1, 1, 1, 384, 240, 240, 240, 214,,, -6, 5, 2, 1, 1, 1, 1, 1, 128, 68, 68, 68, 46,,, -6, 5, 2, 1, 1, 1, 1, 1, 256, 68, 68, 68, 46,,, -6, 5, 2, 1, 1, 1, 1, 1, 384, 68, 68, 68, 46,,, -6, 5, 2, 2, 1, 1, 1, 1, 128, 132, 132, 132, 88,,, -6, 5, 2, 2, 1, 1, 1, 1, 256, 132, 132, 132, 88,,, -6, 5, 2, 2, 1, 1, 1, 1, 384, 132, 132, 132, 88,,, -6, 5, 2, 3, 1, 1, 1, 1, 128, 196, 196, 196, 130,,, -6, 5, 2, 3, 1, 1, 1, 1, 256, 196, 196, 196, 130,,, -6, 5, 2, 3, 1, 1, 1, 1, 384, 196, 196, 196, 130,,, -6, 5, 2, 4, 1, 1, 1, 1, 128, 240, 240, 240, 172,,, -6, 5, 2, 4, 1, 1, 1, 1, 256, 240, 240, 240, 172,,, -6, 5, 2, 4, 1, 1, 1, 1, 384, 240, 240, 240, 172,,, -6, 5, 2, 5, 1, 1, 1, 1, 128, 240, 240, 240, 214,,, -6, 5, 2, 5, 1, 1, 1, 1, 256, 240, 240, 240, 214,,, -6, 5, 2, 5, 1, 1, 1, 1, 384, 240, 240, 240, 214,,, -6, 5, 3, 1, 1, 1, 1, 1, 128, 68, 68, 68, 46,,, -6, 5, 3, 1, 1, 1, 1, 1, 256, 68, 68, 68, 46,,, -6, 5, 3, 1, 1, 1, 1, 1, 384, 68, 68, 68, 46,,, -6, 5, 3, 2, 1, 1, 1, 1, 128, 132, 132, 132, 88,,, -6, 5, 3, 2, 1, 1, 1, 1, 256, 132, 132, 132, 88,,, -6, 5, 3, 2, 1, 1, 1, 1, 384, 132, 132, 132, 88,,, -6, 5, 3, 3, 1, 1, 1, 1, 128, 196, 196, 196, 130,,, -6, 5, 3, 3, 1, 1, 1, 1, 256, 196, 196, 196, 130,,, -6, 5, 3, 3, 1, 1, 1, 1, 384, 196, 196, 196, 130,,, -6, 5, 3, 4, 1, 1, 1, 1, 128, 240, 240, 240, 172,,, -6, 5, 3, 4, 1, 1, 1, 1, 256, 240, 240, 240, 172,,, -6, 5, 3, 4, 1, 1, 1, 1, 384, 240, 240, 240, 172,,, -6, 5, 3, 5, 1, 1, 1, 1, 128, 240, 240, 240, 214,,, -6, 5, 3, 5, 1, 1, 1, 1, 256, 240, 240, 240, 214,,, -6, 5, 3, 5, 1, 1, 1, 1, 384, 240, 240, 240, 214,,, -6, 5, 4, 1, 1, 1, 1, 1, 128, 68, 68, 68, 46,,, -6, 5, 4, 1, 1, 1, 1, 1, 256, 68, 68, 68, 46,,, -6, 5, 4, 1, 1, 1, 1, 1, 384, 68, 68, 68, 46,,, -6, 5, 4, 2, 1, 1, 1, 1, 128, 132, 132, 132, 88,,, -6, 5, 4, 2, 1, 1, 1, 1, 256, 132, 132, 132, 88,,, -6, 5, 4, 2, 1, 1, 1, 1, 384, 132, 132, 132, 88,,, -6, 5, 4, 3, 1, 1, 1, 1, 128, 196, 196, 196, 130,,, -6, 5, 4, 3, 1, 1, 1, 1, 256, 196, 196, 196, 130,,, -6, 5, 4, 3, 1, 1, 1, 1, 384, 196, 196, 196, 130,,, -6, 5, 4, 4, 1, 1, 1, 1, 128, 240, 240, 240, 172,,, -6, 5, 4, 4, 1, 1, 1, 1, 256, 240, 240, 240, 172,,, -6, 5, 4, 4, 1, 1, 1, 1, 384, 240, 240, 240, 172,,, -6, 5, 4, 5, 1, 1, 1, 1, 128, 240, 240, 240, 214,,, -6, 5, 4, 5, 1, 1, 1, 1, 256, 240, 240, 240, 214,,, -6, 5, 4, 5, 1, 1, 1, 1, 384, 240, 240, 240, 214,,, -6, 5, 5, 1, 1, 1, 1, 1, 128, 68, 68, 68, 46,,, -6, 5, 5, 1, 1, 1, 1, 1, 256, 68, 68, 68, 46,,, -6, 5, 5, 1, 1, 1, 1, 1, 384, 68, 68, 68, 46,,, -6, 5, 5, 2, 1, 1, 1, 1, 128, 132, 132, 132, 88,,, -6, 5, 5, 2, 1, 1, 1, 1, 256, 132, 132, 132, 88,,, -6, 5, 5, 2, 1, 1, 1, 1, 384, 132, 132, 132, 88,,, -6, 5, 5, 3, 1, 1, 1, 1, 128, 196, 196, 196, 130,,, -6, 5, 5, 3, 1, 1, 1, 1, 256, 196, 196, 196, 130,,, -6, 5, 5, 3, 1, 1, 1, 1, 384, 196, 196, 196, 130,,, -6, 5, 5, 4, 1, 1, 1, 1, 128, 240, 240, 240, 172,,, -6, 5, 5, 4, 1, 1, 1, 1, 256, 240, 240, 240, 172,,, -6, 5, 5, 4, 1, 1, 1, 1, 384, 240, 240, 240, 172,,, -6, 5, 5, 5, 1, 1, 1, 1, 128, 240, 240, 240, 214,,, -6, 5, 5, 5, 1, 1, 1, 1, 256, 240, 240, 240, 214,,, -6, 5, 5, 5, 1, 1, 1, 1, 384, 240, 240, 240, 214,,, -6, 5, 6, 1, 1, 1, 1, 1, 128, 68, 68, 68, 46,,, -6, 5, 6, 1, 1, 1, 1, 1, 256, 68, 68, 68, 46,,, -6, 5, 6, 1, 1, 1, 1, 1, 384, 68, 68, 68, 46,,, -6, 5, 6, 2, 1, 1, 1, 1, 128, 132, 132, 132, 88,,, -6, 5, 6, 2, 1, 1, 1, 1, 256, 132, 132, 132, 88,,, -6, 5, 6, 2, 1, 1, 1, 1, 384, 132, 132, 132, 88,,, -6, 5, 6, 3, 1, 1, 1, 1, 128, 196, 196, 196, 130,,, -6, 5, 6, 3, 1, 1, 1, 1, 256, 196, 196, 196, 130,,, -6, 5, 6, 3, 1, 1, 1, 1, 384, 196, 196, 196, 130,,, -6, 5, 6, 4, 1, 1, 1, 1, 128, 240, 240, 240, 172,,, -6, 5, 6, 4, 1, 1, 1, 1, 256, 240, 240, 240, 172,,, -6, 5, 6, 4, 1, 1, 1, 1, 384, 240, 240, 240, 172,,, -6, 5, 6, 5, 1, 1, 1, 1, 128, 240, 240, 240, 214,,, -6, 5, 6, 5, 1, 1, 1, 1, 256, 240, 240, 240, 214,,, -6, 5, 6, 5, 1, 1, 1, 1, 384, 240, 240, 240, 214,,, -6, 6, 1, 1, 1, 1, 1, 1, 128, 69, 69, 47, 26,,, -6, 6, 1, 1, 1, 1, 1, 1, 256, 69, 69, 47, 26,,, -6, 6, 1, 1, 1, 1, 1, 1, 384, 69, 69, 47, 26,,, -6, 6, 1, 2, 1, 1, 1, 1, 128, 133, 133, 89, 47,,, -6, 6, 1, 2, 1, 1, 1, 1, 256, 133, 133, 89, 47,,, -6, 6, 1, 2, 1, 1, 1, 1, 384, 133, 133, 89, 47,,, -6, 6, 1, 3, 1, 1, 1, 1, 128, 197, 197, 131, 68,,, -6, 6, 1, 3, 1, 1, 1, 1, 256, 197, 197, 131, 68,,, -6, 6, 1, 3, 1, 1, 1, 1, 384, 197, 197, 131, 68,,, -6, 6, 1, 4, 1, 1, 1, 1, 128, 240, 240, 173, 89,,, -6, 6, 1, 4, 1, 1, 1, 1, 256, 240, 240, 173, 89,,, -6, 6, 1, 4, 1, 1, 1, 1, 384, 240, 240, 173, 89,,, -6, 6, 1, 5, 1, 1, 1, 1, 128, 240, 240, 215, 110,,, -6, 6, 1, 5, 1, 1, 1, 1, 256, 240, 240, 215, 110,,, -6, 6, 1, 5, 1, 1, 1, 1, 384, 240, 240, 215, 110,,, -6, 6, 1, 6, 1, 1, 1, 1, 128, 240, 240, 240, 131,,, -6, 6, 1, 6, 1, 1, 1, 1, 256, 240, 240, 240, 131,,, -6, 6, 1, 6, 1, 1, 1, 1, 384, 240, 240, 240, 131,,, -6, 6, 2, 1, 1, 1, 1, 1, 128, 69, 69, 47, 26,,, -6, 6, 2, 1, 1, 1, 1, 1, 256, 69, 69, 47, 26,,, -6, 6, 2, 1, 1, 1, 1, 1, 384, 69, 69, 47, 26,,, -6, 6, 2, 2, 1, 1, 1, 1, 128, 133, 133, 89, 47,,, -6, 6, 2, 2, 1, 1, 1, 1, 256, 133, 133, 89, 47,,, -6, 6, 2, 2, 1, 1, 1, 1, 384, 133, 133, 89, 47,,, -6, 6, 2, 3, 1, 1, 1, 1, 128, 197, 197, 131, 68,,, -6, 6, 2, 3, 1, 1, 1, 1, 256, 197, 197, 131, 68,,, -6, 6, 2, 3, 1, 1, 1, 1, 384, 197, 197, 131, 68,,, -6, 6, 2, 4, 1, 1, 1, 1, 128, 240, 240, 173, 89,,, -6, 6, 2, 4, 1, 1, 1, 1, 256, 240, 240, 173, 89,,, -6, 6, 2, 4, 1, 1, 1, 1, 384, 240, 240, 173, 89,,, -6, 6, 2, 5, 1, 1, 1, 1, 128, 240, 240, 215, 110,,, -6, 6, 2, 5, 1, 1, 1, 1, 256, 240, 240, 215, 110,,, -6, 6, 2, 5, 1, 1, 1, 1, 384, 240, 240, 215, 110,,, -6, 6, 2, 6, 1, 1, 1, 1, 128, 240, 240, 240, 131,,, -6, 6, 2, 6, 1, 1, 1, 1, 256, 240, 240, 240, 131,,, -6, 6, 2, 6, 1, 1, 1, 1, 384, 240, 240, 240, 131,,, -6, 6, 3, 1, 1, 1, 1, 1, 128, 69, 69, 47, 26,,, -6, 6, 3, 1, 1, 1, 1, 1, 256, 69, 69, 47, 26,,, -6, 6, 3, 1, 1, 1, 1, 1, 384, 69, 69, 47, 26,,, -6, 6, 3, 2, 1, 1, 1, 1, 128, 133, 133, 89, 47,,, -6, 6, 3, 2, 1, 1, 1, 1, 256, 133, 133, 89, 47,,, -6, 6, 3, 2, 1, 1, 1, 1, 384, 133, 133, 89, 47,,, -6, 6, 3, 3, 1, 1, 1, 1, 128, 197, 197, 131, 68,,, -6, 6, 3, 3, 1, 1, 1, 1, 256, 197, 197, 131, 68,,, -6, 6, 3, 3, 1, 1, 1, 1, 384, 197, 197, 131, 68,,, -6, 6, 3, 4, 1, 1, 1, 1, 128, 240, 240, 173, 89,,, -6, 6, 3, 4, 1, 1, 1, 1, 256, 240, 240, 173, 89,,, -6, 6, 3, 4, 1, 1, 1, 1, 384, 240, 240, 173, 89,,, -6, 6, 3, 5, 1, 1, 1, 1, 128, 240, 240, 215, 110,,, -6, 6, 3, 5, 1, 1, 1, 1, 256, 240, 240, 215, 110,,, -6, 6, 3, 5, 1, 1, 1, 1, 384, 240, 240, 215, 110,,, -6, 6, 3, 6, 1, 1, 1, 1, 128, 240, 240, 240, 131,,, -6, 6, 3, 6, 1, 1, 1, 1, 256, 240, 240, 240, 131,,, -6, 6, 3, 6, 1, 1, 1, 1, 384, 240, 240, 240, 131,,, -6, 6, 4, 1, 1, 1, 1, 1, 128, 69, 69, 47, 26,,, -6, 6, 4, 1, 1, 1, 1, 1, 256, 69, 69, 47, 26,,, -6, 6, 4, 1, 1, 1, 1, 1, 384, 69, 69, 47, 26,,, -6, 6, 4, 2, 1, 1, 1, 1, 128, 133, 133, 89, 47,,, -6, 6, 4, 2, 1, 1, 1, 1, 256, 133, 133, 89, 47,,, -6, 6, 4, 2, 1, 1, 1, 1, 384, 133, 133, 89, 47,,, -6, 6, 4, 3, 1, 1, 1, 1, 128, 197, 197, 131, 68,,, -6, 6, 4, 3, 1, 1, 1, 1, 256, 197, 197, 131, 68,,, -6, 6, 4, 3, 1, 1, 1, 1, 384, 197, 197, 131, 68,,, -6, 6, 4, 4, 1, 1, 1, 1, 128, 240, 240, 173, 89,,, -6, 6, 4, 4, 1, 1, 1, 1, 256, 240, 240, 173, 89,,, -6, 6, 4, 4, 1, 1, 1, 1, 384, 240, 240, 173, 89,,, -6, 6, 4, 5, 1, 1, 1, 1, 128, 240, 240, 215, 110,,, -6, 6, 4, 5, 1, 1, 1, 1, 256, 240, 240, 215, 110,,, -6, 6, 4, 5, 1, 1, 1, 1, 384, 240, 240, 215, 110,,, -6, 6, 4, 6, 1, 1, 1, 1, 128, 240, 240, 240, 131,,, -6, 6, 4, 6, 1, 1, 1, 1, 256, 240, 240, 240, 131,,, -6, 6, 4, 6, 1, 1, 1, 1, 384, 240, 240, 240, 131,,, -6, 6, 5, 1, 1, 1, 1, 1, 128, 69, 69, 47, 26,,, -6, 6, 5, 1, 1, 1, 1, 1, 256, 69, 69, 47, 26,,, -6, 6, 5, 1, 1, 1, 1, 1, 384, 69, 69, 47, 26,,, -6, 6, 5, 2, 1, 1, 1, 1, 128, 133, 133, 89, 47,,, -6, 6, 5, 2, 1, 1, 1, 1, 256, 133, 133, 89, 47,,, -6, 6, 5, 2, 1, 1, 1, 1, 384, 133, 133, 89, 47,,, -6, 6, 5, 3, 1, 1, 1, 1, 128, 197, 197, 131, 68,,, -6, 6, 5, 3, 1, 1, 1, 1, 256, 197, 197, 131, 68,,, -6, 6, 5, 3, 1, 1, 1, 1, 384, 197, 197, 131, 68,,, -6, 6, 5, 4, 1, 1, 1, 1, 128, 240, 240, 173, 89,,, -6, 6, 5, 4, 1, 1, 1, 1, 256, 240, 240, 173, 89,,, -6, 6, 5, 4, 1, 1, 1, 1, 384, 240, 240, 173, 89,,, -6, 6, 5, 5, 1, 1, 1, 1, 128, 240, 240, 215, 110,,, -6, 6, 5, 5, 1, 1, 1, 1, 256, 240, 240, 215, 110,,, -6, 6, 5, 5, 1, 1, 1, 1, 384, 240, 240, 215, 110,,, -6, 6, 5, 6, 1, 1, 1, 1, 128, 240, 240, 240, 131,,, -6, 6, 5, 6, 1, 1, 1, 1, 256, 240, 240, 240, 131,,, -6, 6, 5, 6, 1, 1, 1, 1, 384, 240, 240, 240, 131,,, -6, 6, 6, 1, 1, 1, 1, 1, 128, 69, 69, 47, 26,,, -6, 6, 6, 1, 1, 1, 1, 1, 256, 69, 69, 47, 26,,, -6, 6, 6, 1, 1, 1, 1, 1, 384, 69, 69, 47, 26,,, -6, 6, 6, 2, 1, 1, 1, 1, 128, 133, 133, 89, 47,,, -6, 6, 6, 2, 1, 1, 1, 1, 256, 133, 133, 89, 47,,, -6, 6, 6, 2, 1, 1, 1, 1, 384, 133, 133, 89, 47,,, -6, 6, 6, 3, 1, 1, 1, 1, 128, 197, 197, 131, 68,,, -6, 6, 6, 3, 1, 1, 1, 1, 256, 197, 197, 131, 68,,, -6, 6, 6, 3, 1, 1, 1, 1, 384, 197, 197, 131, 68,,, -6, 6, 6, 4, 1, 1, 1, 1, 128, 240, 240, 173, 89,,, -6, 6, 6, 4, 1, 1, 1, 1, 256, 240, 240, 173, 89,,, -6, 6, 6, 4, 1, 1, 1, 1, 384, 240, 240, 173, 89,,, -6, 6, 6, 5, 1, 1, 1, 1, 128, 240, 240, 215, 110,,, -6, 6, 6, 5, 1, 1, 1, 1, 256, 240, 240, 215, 110,,, -6, 6, 6, 5, 1, 1, 1, 1, 384, 240, 240, 215, 110,,, -6, 6, 6, 6, 1, 1, 1, 1, 128, 240, 240, 240, 131,,, -6, 6, 6, 6, 1, 1, 1, 1, 256, 240, 240, 240, 131,,, -6, 6, 6, 6, 1, 1, 1, 1, 384, 240, 240, 240, 131,,, -6, 7, 1, 1, 1, 1, 1, 1, 128, 70, 70, 48, 27,,, -6, 7, 1, 1, 1, 1, 1, 1, 256, 70, 70, 48, 27,,, -6, 7, 1, 1, 1, 1, 1, 1, 384, 70, 70, 48, 27,,, -6, 7, 1, 2, 1, 1, 1, 1, 128, 134, 134, 90, 48,,, -6, 7, 1, 2, 1, 1, 1, 1, 256, 134, 134, 90, 48,,, -6, 7, 1, 2, 1, 1, 1, 1, 384, 134, 134, 90, 48,,, -6, 7, 1, 3, 1, 1, 1, 1, 128, 198, 198, 132, 69,,, -6, 7, 1, 3, 1, 1, 1, 1, 256, 198, 198, 132, 69,,, -6, 7, 1, 3, 1, 1, 1, 1, 384, 198, 198, 132, 69,,, -6, 7, 1, 4, 1, 1, 1, 1, 128, 240, 240, 174, 90,,, -6, 7, 1, 4, 1, 1, 1, 1, 256, 240, 240, 174, 90,,, -6, 7, 1, 4, 1, 1, 1, 1, 384, 240, 240, 174, 90,,, -6, 7, 1, 5, 1, 1, 1, 1, 128, 240, 240, 216, 111,,, -6, 7, 1, 5, 1, 1, 1, 1, 256, 240, 240, 216, 111,,, -6, 7, 1, 5, 1, 1, 1, 1, 384, 240, 240, 216, 111,,, -6, 7, 1, 6, 1, 1, 1, 1, 128, 240, 240, 240, 132,,, -6, 7, 1, 6, 1, 1, 1, 1, 256, 240, 240, 240, 132,,, -6, 7, 1, 6, 1, 1, 1, 1, 384, 240, 240, 240, 132,,, -6, 7, 1, 7, 1, 1, 1, 1, 128, 240, 240, 240, 153,,, -6, 7, 1, 7, 1, 1, 1, 1, 256, 240, 240, 240, 153,,, -6, 7, 1, 7, 1, 1, 1, 1, 384, 240, 240, 240, 153,,, -6, 7, 2, 1, 1, 1, 1, 1, 128, 70, 70, 48, 27,,, -6, 7, 2, 1, 1, 1, 1, 1, 256, 70, 70, 48, 27,,, -6, 7, 2, 1, 1, 1, 1, 1, 384, 70, 70, 48, 27,,, -6, 7, 2, 2, 1, 1, 1, 1, 128, 134, 134, 90, 48,,, -6, 7, 2, 2, 1, 1, 1, 1, 256, 134, 134, 90, 48,,, -6, 7, 2, 2, 1, 1, 1, 1, 384, 134, 134, 90, 48,,, -6, 7, 2, 3, 1, 1, 1, 1, 128, 198, 198, 132, 69,,, -6, 7, 2, 3, 1, 1, 1, 1, 256, 198, 198, 132, 69,,, -6, 7, 2, 3, 1, 1, 1, 1, 384, 198, 198, 132, 69,,, -6, 7, 2, 4, 1, 1, 1, 1, 128, 240, 240, 174, 90,,, -6, 7, 2, 4, 1, 1, 1, 1, 256, 240, 240, 174, 90,,, -6, 7, 2, 4, 1, 1, 1, 1, 384, 240, 240, 174, 90,,, -6, 7, 2, 5, 1, 1, 1, 1, 128, 240, 240, 216, 111,,, -6, 7, 2, 5, 1, 1, 1, 1, 256, 240, 240, 216, 111,,, -6, 7, 2, 5, 1, 1, 1, 1, 384, 240, 240, 216, 111,,, -6, 7, 2, 6, 1, 1, 1, 1, 128, 240, 240, 240, 132,,, -6, 7, 2, 6, 1, 1, 1, 1, 256, 240, 240, 240, 132,,, -6, 7, 2, 6, 1, 1, 1, 1, 384, 240, 240, 240, 132,,, -6, 7, 2, 7, 1, 1, 1, 1, 128, 240, 240, 240, 153,,, -6, 7, 2, 7, 1, 1, 1, 1, 256, 240, 240, 240, 153,,, -6, 7, 2, 7, 1, 1, 1, 1, 384, 240, 240, 240, 153,,, -6, 7, 3, 1, 1, 1, 1, 1, 128, 70, 70, 48, 27,,, -6, 7, 3, 1, 1, 1, 1, 1, 256, 70, 70, 48, 27,,, -6, 7, 3, 1, 1, 1, 1, 1, 384, 70, 70, 48, 27,,, -6, 7, 3, 2, 1, 1, 1, 1, 128, 134, 134, 90, 48,,, -6, 7, 3, 2, 1, 1, 1, 1, 256, 134, 134, 90, 48,,, -6, 7, 3, 2, 1, 1, 1, 1, 384, 134, 134, 90, 48,,, -6, 7, 3, 3, 1, 1, 1, 1, 128, 198, 198, 132, 69,,, -6, 7, 3, 3, 1, 1, 1, 1, 256, 198, 198, 132, 69,,, -6, 7, 3, 3, 1, 1, 1, 1, 384, 198, 198, 132, 69,,, -6, 7, 3, 4, 1, 1, 1, 1, 128, 240, 240, 174, 90,,, -6, 7, 3, 4, 1, 1, 1, 1, 256, 240, 240, 174, 90,,, -6, 7, 3, 4, 1, 1, 1, 1, 384, 240, 240, 174, 90,,, -6, 7, 3, 5, 1, 1, 1, 1, 128, 240, 240, 216, 111,,, -6, 7, 3, 5, 1, 1, 1, 1, 256, 240, 240, 216, 111,,, -6, 7, 3, 5, 1, 1, 1, 1, 384, 240, 240, 216, 111,,, -6, 7, 3, 6, 1, 1, 1, 1, 128, 240, 240, 240, 132,,, -6, 7, 3, 6, 1, 1, 1, 1, 256, 240, 240, 240, 132,,, -6, 7, 3, 6, 1, 1, 1, 1, 384, 240, 240, 240, 132,,, -6, 7, 3, 7, 1, 1, 1, 1, 128, 240, 240, 240, 153,,, -6, 7, 3, 7, 1, 1, 1, 1, 256, 240, 240, 240, 153,,, -6, 7, 3, 7, 1, 1, 1, 1, 384, 240, 240, 240, 153,,, -6, 7, 4, 1, 1, 1, 1, 1, 128, 70, 70, 48, 27,,, -6, 7, 4, 1, 1, 1, 1, 1, 256, 70, 70, 48, 27,,, -6, 7, 4, 1, 1, 1, 1, 1, 384, 70, 70, 48, 27,,, -6, 7, 4, 2, 1, 1, 1, 1, 128, 134, 134, 90, 48,,, -6, 7, 4, 2, 1, 1, 1, 1, 256, 134, 134, 90, 48,,, -6, 7, 4, 2, 1, 1, 1, 1, 384, 134, 134, 90, 48,,, -6, 7, 4, 3, 1, 1, 1, 1, 128, 198, 198, 132, 69,,, -6, 7, 4, 3, 1, 1, 1, 1, 256, 198, 198, 132, 69,,, -6, 7, 4, 3, 1, 1, 1, 1, 384, 198, 198, 132, 69,,, -6, 7, 4, 4, 1, 1, 1, 1, 128, 240, 240, 174, 90,,, -6, 7, 4, 4, 1, 1, 1, 1, 256, 240, 240, 174, 90,,, -6, 7, 4, 4, 1, 1, 1, 1, 384, 240, 240, 174, 90,,, -6, 7, 4, 5, 1, 1, 1, 1, 128, 240, 240, 216, 111,,, -6, 7, 4, 5, 1, 1, 1, 1, 256, 240, 240, 216, 111,,, -6, 7, 4, 5, 1, 1, 1, 1, 384, 240, 240, 216, 111,,, -6, 7, 4, 6, 1, 1, 1, 1, 128, 240, 240, 240, 132,,, -6, 7, 4, 6, 1, 1, 1, 1, 256, 240, 240, 240, 132,,, -6, 7, 4, 6, 1, 1, 1, 1, 384, 240, 240, 240, 132,,, -6, 7, 4, 7, 1, 1, 1, 1, 128, 240, 240, 240, 153,,, -6, 7, 4, 7, 1, 1, 1, 1, 256, 240, 240, 240, 153,,, -6, 7, 4, 7, 1, 1, 1, 1, 384, 240, 240, 240, 153,,, -6, 7, 5, 1, 1, 1, 1, 1, 128, 70, 70, 48, 27,,, -6, 7, 5, 1, 1, 1, 1, 1, 256, 70, 70, 48, 27,,, -6, 7, 5, 1, 1, 1, 1, 1, 384, 70, 70, 48, 27,,, -6, 7, 5, 2, 1, 1, 1, 1, 128, 134, 134, 90, 48,,, -6, 7, 5, 2, 1, 1, 1, 1, 256, 134, 134, 90, 48,,, -6, 7, 5, 2, 1, 1, 1, 1, 384, 134, 134, 90, 48,,, -6, 7, 5, 3, 1, 1, 1, 1, 128, 198, 198, 132, 69,,, -6, 7, 5, 3, 1, 1, 1, 1, 256, 198, 198, 132, 69,,, -6, 7, 5, 3, 1, 1, 1, 1, 384, 198, 198, 132, 69,,, -6, 7, 5, 4, 1, 1, 1, 1, 128, 240, 240, 174, 90,,, -6, 7, 5, 4, 1, 1, 1, 1, 256, 240, 240, 174, 90,,, -6, 7, 5, 4, 1, 1, 1, 1, 384, 240, 240, 174, 90,,, -6, 7, 5, 5, 1, 1, 1, 1, 128, 240, 240, 216, 111,,, -6, 7, 5, 5, 1, 1, 1, 1, 256, 240, 240, 216, 111,,, -6, 7, 5, 5, 1, 1, 1, 1, 384, 240, 240, 216, 111,,, -6, 7, 5, 6, 1, 1, 1, 1, 128, 240, 240, 240, 132,,, -6, 7, 5, 6, 1, 1, 1, 1, 256, 240, 240, 240, 132,,, -6, 7, 5, 6, 1, 1, 1, 1, 384, 240, 240, 240, 132,,, -6, 7, 5, 7, 1, 1, 1, 1, 128, 240, 240, 240, 153,,, -6, 7, 5, 7, 1, 1, 1, 1, 256, 240, 240, 240, 153,,, -6, 7, 5, 7, 1, 1, 1, 1, 384, 240, 240, 240, 153,,, -6, 7, 6, 1, 1, 1, 1, 1, 128, 70, 70, 48, 27,,, -6, 7, 6, 1, 1, 1, 1, 1, 256, 70, 70, 48, 27,,, -6, 7, 6, 1, 1, 1, 1, 1, 384, 70, 70, 48, 27,,, -6, 7, 6, 2, 1, 1, 1, 1, 128, 134, 134, 90, 48,,, -6, 7, 6, 2, 1, 1, 1, 1, 256, 134, 134, 90, 48,,, -6, 7, 6, 2, 1, 1, 1, 1, 384, 134, 134, 90, 48,,, -6, 7, 6, 3, 1, 1, 1, 1, 128, 198, 198, 132, 69,,, -6, 7, 6, 3, 1, 1, 1, 1, 256, 198, 198, 132, 69,,, -6, 7, 6, 3, 1, 1, 1, 1, 384, 198, 198, 132, 69,,, -6, 7, 6, 4, 1, 1, 1, 1, 128, 240, 240, 174, 90,,, -6, 7, 6, 4, 1, 1, 1, 1, 256, 240, 240, 174, 90,,, -6, 7, 6, 4, 1, 1, 1, 1, 384, 240, 240, 174, 90,,, -6, 7, 6, 5, 1, 1, 1, 1, 128, 240, 240, 216, 111,,, -6, 7, 6, 5, 1, 1, 1, 1, 256, 240, 240, 216, 111,,, -6, 7, 6, 5, 1, 1, 1, 1, 384, 240, 240, 216, 111,,, -6, 7, 6, 6, 1, 1, 1, 1, 128, 240, 240, 240, 132,,, -6, 7, 6, 6, 1, 1, 1, 1, 256, 240, 240, 240, 132,,, -6, 7, 6, 6, 1, 1, 1, 1, 384, 240, 240, 240, 132,,, -6, 7, 6, 7, 1, 1, 1, 1, 128, 240, 240, 240, 153,,, -6, 7, 6, 7, 1, 1, 1, 1, 256, 240, 240, 240, 153,,, -6, 7, 6, 7, 1, 1, 1, 1, 384, 240, 240, 240, 153,,, -7, 1, 1, 1, 1, 1, 1, 1, 128, 54, 54, 54, 54, 54, 36, 18 -7, 1, 1, 1, 1, 1, 1, 1, 256, 54, 54, 54, 54, 54, 36, 18 -7, 1, 1, 1, 1, 1, 1, 1, 384, 54, 54, 54, 54, 54, 36, 18 -7, 1, 2, 1, 1, 1, 1, 1, 128, 54, 54, 54, 54, 54, 36, 18 -7, 1, 2, 1, 1, 1, 1, 1, 256, 54, 54, 54, 54, 54, 36, 18 -7, 1, 2, 1, 1, 1, 1, 1, 384, 54, 54, 54, 54, 54, 36, 18 -7, 1, 3, 1, 1, 1, 1, 1, 128, 54, 54, 54, 54, 54, 36, 18 -7, 1, 3, 1, 1, 1, 1, 1, 256, 54, 54, 54, 54, 54, 36, 18 -7, 1, 3, 1, 1, 1, 1, 1, 384, 54, 54, 54, 54, 54, 36, 18 -7, 1, 4, 1, 1, 1, 1, 1, 128, 54, 54, 54, 54, 54, 36, 18 -7, 1, 4, 1, 1, 1, 1, 1, 256, 54, 54, 54, 54, 54, 36, 18 -7, 1, 4, 1, 1, 1, 1, 1, 384, 54, 54, 54, 54, 54, 36, 18 -7, 1, 5, 1, 1, 1, 1, 1, 128, 54, 54, 54, 54, 54, 36, 18 -7, 1, 5, 1, 1, 1, 1, 1, 256, 54, 54, 54, 54, 54, 36, 18 -7, 1, 5, 1, 1, 1, 1, 1, 384, 54, 54, 54, 54, 54, 36, 18 -7, 1, 6, 1, 1, 1, 1, 1, 128, 54, 54, 54, 54, 54, 36, 18 -7, 1, 6, 1, 1, 1, 1, 1, 256, 54, 54, 54, 54, 54, 36, 18 -7, 1, 6, 1, 1, 1, 1, 1, 384, 54, 54, 54, 54, 54, 36, 18 -7, 1, 7, 1, 1, 1, 1, 1, 128, 54, 54, 54, 54, 54, 36, 18 -7, 1, 7, 1, 1, 1, 1, 1, 256, 54, 54, 54, 54, 54, 36, 18 -7, 1, 7, 1, 1, 1, 1, 1, 384, 54, 54, 54, 54, 54, 36, 18 -7, 2, 1, 1, 1, 1, 1, 1, 128, 55, 55, 55, 55, 37,, -7, 2, 1, 1, 1, 1, 1, 1, 256, 55, 55, 55, 55, 37,, -7, 2, 1, 1, 1, 1, 1, 1, 384, 55, 55, 55, 55, 37,, -7, 2, 1, 2, 1, 1, 1, 1, 128, 109, 109, 109, 109, 73,, -7, 2, 1, 2, 1, 1, 1, 1, 256, 109, 109, 109, 109, 73,, -7, 2, 1, 2, 1, 1, 1, 1, 384, 109, 109, 109, 109, 73,, -7, 2, 2, 1, 1, 1, 1, 1, 128, 55, 55, 55, 55, 37,, -7, 2, 2, 1, 1, 1, 1, 1, 256, 55, 55, 55, 55, 37,, -7, 2, 2, 1, 1, 1, 1, 1, 384, 55, 55, 55, 55, 37,, -7, 2, 2, 2, 1, 1, 1, 1, 128, 109, 109, 109, 109, 73,, -7, 2, 2, 2, 1, 1, 1, 1, 256, 109, 109, 109, 109, 73,, -7, 2, 2, 2, 1, 1, 1, 1, 384, 109, 109, 109, 109, 73,, -7, 2, 3, 1, 1, 1, 1, 1, 128, 55, 55, 55, 55, 37,, -7, 2, 3, 1, 1, 1, 1, 1, 256, 55, 55, 55, 55, 37,, -7, 2, 3, 1, 1, 1, 1, 1, 384, 55, 55, 55, 55, 37,, -7, 2, 3, 2, 1, 1, 1, 1, 128, 109, 109, 109, 109, 73,, -7, 2, 3, 2, 1, 1, 1, 1, 256, 109, 109, 109, 109, 73,, -7, 2, 3, 2, 1, 1, 1, 1, 384, 109, 109, 109, 109, 73,, -7, 2, 4, 1, 1, 1, 1, 1, 128, 55, 55, 55, 55, 37,, -7, 2, 4, 1, 1, 1, 1, 1, 256, 55, 55, 55, 55, 37,, -7, 2, 4, 1, 1, 1, 1, 1, 384, 55, 55, 55, 55, 37,, -7, 2, 4, 2, 1, 1, 1, 1, 128, 109, 109, 109, 109, 73,, -7, 2, 4, 2, 1, 1, 1, 1, 256, 109, 109, 109, 109, 73,, -7, 2, 4, 2, 1, 1, 1, 1, 384, 109, 109, 109, 109, 73,, -7, 2, 5, 1, 1, 1, 1, 1, 128, 55, 55, 55, 55, 37,, -7, 2, 5, 1, 1, 1, 1, 1, 256, 55, 55, 55, 55, 37,, -7, 2, 5, 1, 1, 1, 1, 1, 384, 55, 55, 55, 55, 37,, -7, 2, 5, 2, 1, 1, 1, 1, 128, 109, 109, 109, 109, 73,, -7, 2, 5, 2, 1, 1, 1, 1, 256, 109, 109, 109, 109, 73,, -7, 2, 5, 2, 1, 1, 1, 1, 384, 109, 109, 109, 109, 73,, -7, 2, 6, 1, 1, 1, 1, 1, 128, 55, 55, 55, 55, 37,, -7, 2, 6, 1, 1, 1, 1, 1, 256, 55, 55, 55, 55, 37,, -7, 2, 6, 1, 1, 1, 1, 1, 384, 55, 55, 55, 55, 37,, -7, 2, 6, 2, 1, 1, 1, 1, 128, 109, 109, 109, 109, 73,, -7, 2, 6, 2, 1, 1, 1, 1, 256, 109, 109, 109, 109, 73,, -7, 2, 6, 2, 1, 1, 1, 1, 384, 109, 109, 109, 109, 73,, -7, 2, 7, 1, 1, 1, 1, 1, 128, 55, 55, 55, 55, 37,, -7, 2, 7, 1, 1, 1, 1, 1, 256, 55, 55, 55, 55, 37,, -7, 2, 7, 1, 1, 1, 1, 1, 384, 55, 55, 55, 55, 37,, -7, 2, 7, 2, 1, 1, 1, 1, 128, 109, 109, 109, 109, 73,, -7, 2, 7, 2, 1, 1, 1, 1, 256, 109, 109, 109, 109, 73,, -7, 2, 7, 2, 1, 1, 1, 1, 384, 109, 109, 109, 109, 73,, -7, 3, 1, 1, 1, 1, 1, 1, 128, 56, 56, 56, 38, 20,, -7, 3, 1, 1, 1, 1, 1, 1, 256, 56, 56, 56, 38, 20,, -7, 3, 1, 1, 1, 1, 1, 1, 384, 56, 56, 56, 38, 20,, -7, 3, 1, 2, 1, 1, 1, 1, 128, 110, 110, 110, 74, 38,, -7, 3, 1, 2, 1, 1, 1, 1, 256, 110, 110, 110, 74, 38,, -7, 3, 1, 2, 1, 1, 1, 1, 384, 110, 110, 110, 74, 38,, -7, 3, 1, 3, 1, 1, 1, 1, 128, 164, 164, 164, 110, 56,, -7, 3, 1, 3, 1, 1, 1, 1, 256, 164, 164, 164, 110, 56,, -7, 3, 1, 3, 1, 1, 1, 1, 384, 164, 164, 164, 110, 56,, -7, 3, 2, 1, 1, 1, 1, 1, 128, 56, 56, 56, 38, 20,, -7, 3, 2, 1, 1, 1, 1, 1, 256, 56, 56, 56, 38, 20,, -7, 3, 2, 1, 1, 1, 1, 1, 384, 56, 56, 56, 38, 20,, -7, 3, 2, 2, 1, 1, 1, 1, 128, 110, 110, 110, 74, 38,, -7, 3, 2, 2, 1, 1, 1, 1, 256, 110, 110, 110, 74, 38,, -7, 3, 2, 2, 1, 1, 1, 1, 384, 110, 110, 110, 74, 38,, -7, 3, 2, 3, 1, 1, 1, 1, 128, 164, 164, 164, 110, 56,, -7, 3, 2, 3, 1, 1, 1, 1, 256, 164, 164, 164, 110, 56,, -7, 3, 2, 3, 1, 1, 1, 1, 384, 164, 164, 164, 110, 56,, -7, 3, 3, 1, 1, 1, 1, 1, 128, 56, 56, 56, 38, 20,, -7, 3, 3, 1, 1, 1, 1, 1, 256, 56, 56, 56, 38, 20,, -7, 3, 3, 1, 1, 1, 1, 1, 384, 56, 56, 56, 38, 20,, -7, 3, 3, 2, 1, 1, 1, 1, 128, 110, 110, 110, 74, 38,, -7, 3, 3, 2, 1, 1, 1, 1, 256, 110, 110, 110, 74, 38,, -7, 3, 3, 2, 1, 1, 1, 1, 384, 110, 110, 110, 74, 38,, -7, 3, 3, 3, 1, 1, 1, 1, 128, 164, 164, 164, 110, 56,, -7, 3, 3, 3, 1, 1, 1, 1, 256, 164, 164, 164, 110, 56,, -7, 3, 3, 3, 1, 1, 1, 1, 384, 164, 164, 164, 110, 56,, -7, 3, 4, 1, 1, 1, 1, 1, 128, 56, 56, 56, 38, 20,, -7, 3, 4, 1, 1, 1, 1, 1, 256, 56, 56, 56, 38, 20,, -7, 3, 4, 1, 1, 1, 1, 1, 384, 56, 56, 56, 38, 20,, -7, 3, 4, 2, 1, 1, 1, 1, 128, 110, 110, 110, 74, 38,, -7, 3, 4, 2, 1, 1, 1, 1, 256, 110, 110, 110, 74, 38,, -7, 3, 4, 2, 1, 1, 1, 1, 384, 110, 110, 110, 74, 38,, -7, 3, 4, 3, 1, 1, 1, 1, 128, 164, 164, 164, 110, 56,, -7, 3, 4, 3, 1, 1, 1, 1, 256, 164, 164, 164, 110, 56,, -7, 3, 4, 3, 1, 1, 1, 1, 384, 164, 164, 164, 110, 56,, -7, 3, 5, 1, 1, 1, 1, 1, 128, 56, 56, 56, 38, 20,, -7, 3, 5, 1, 1, 1, 1, 1, 256, 56, 56, 56, 38, 20,, -7, 3, 5, 1, 1, 1, 1, 1, 384, 56, 56, 56, 38, 20,, -7, 3, 5, 2, 1, 1, 1, 1, 128, 110, 110, 110, 74, 38,, -7, 3, 5, 2, 1, 1, 1, 1, 256, 110, 110, 110, 74, 38,, -7, 3, 5, 2, 1, 1, 1, 1, 384, 110, 110, 110, 74, 38,, -7, 3, 5, 3, 1, 1, 1, 1, 128, 164, 164, 164, 110, 56,, -7, 3, 5, 3, 1, 1, 1, 1, 256, 164, 164, 164, 110, 56,, -7, 3, 5, 3, 1, 1, 1, 1, 384, 164, 164, 164, 110, 56,, -7, 3, 6, 1, 1, 1, 1, 1, 128, 56, 56, 56, 38, 20,, -7, 3, 6, 1, 1, 1, 1, 1, 256, 56, 56, 56, 38, 20,, -7, 3, 6, 1, 1, 1, 1, 1, 384, 56, 56, 56, 38, 20,, -7, 3, 6, 2, 1, 1, 1, 1, 128, 110, 110, 110, 74, 38,, -7, 3, 6, 2, 1, 1, 1, 1, 256, 110, 110, 110, 74, 38,, -7, 3, 6, 2, 1, 1, 1, 1, 384, 110, 110, 110, 74, 38,, -7, 3, 6, 3, 1, 1, 1, 1, 128, 164, 164, 164, 110, 56,, -7, 3, 6, 3, 1, 1, 1, 1, 256, 164, 164, 164, 110, 56,, -7, 3, 6, 3, 1, 1, 1, 1, 384, 164, 164, 164, 110, 56,, -7, 3, 7, 1, 1, 1, 1, 1, 128, 56, 56, 56, 38, 20,, -7, 3, 7, 1, 1, 1, 1, 1, 256, 56, 56, 56, 38, 20,, -7, 3, 7, 1, 1, 1, 1, 1, 384, 56, 56, 56, 38, 20,, -7, 3, 7, 2, 1, 1, 1, 1, 128, 110, 110, 110, 74, 38,, -7, 3, 7, 2, 1, 1, 1, 1, 256, 110, 110, 110, 74, 38,, -7, 3, 7, 2, 1, 1, 1, 1, 384, 110, 110, 110, 74, 38,, -7, 3, 7, 3, 1, 1, 1, 1, 128, 164, 164, 164, 110, 56,, -7, 3, 7, 3, 1, 1, 1, 1, 256, 164, 164, 164, 110, 56,, -7, 3, 7, 3, 1, 1, 1, 1, 384, 164, 164, 164, 110, 56,, -7, 4, 1, 1, 1, 1, 1, 1, 128, 57, 57, 57, 39,,, -7, 4, 1, 1, 1, 1, 1, 1, 256, 57, 57, 57, 39,,, -7, 4, 1, 1, 1, 1, 1, 1, 384, 57, 57, 57, 39,,, -7, 4, 1, 2, 1, 1, 1, 1, 128, 111, 111, 111, 75,,, -7, 4, 1, 2, 1, 1, 1, 1, 256, 111, 111, 111, 75,,, -7, 4, 1, 2, 1, 1, 1, 1, 384, 111, 111, 111, 75,,, -7, 4, 1, 3, 1, 1, 1, 1, 128, 165, 165, 165, 111,,, -7, 4, 1, 3, 1, 1, 1, 1, 256, 165, 165, 165, 111,,, -7, 4, 1, 3, 1, 1, 1, 1, 384, 165, 165, 165, 111,,, -7, 4, 1, 4, 1, 1, 1, 1, 128, 219, 219, 219, 147,,, -7, 4, 1, 4, 1, 1, 1, 1, 256, 219, 219, 219, 147,,, -7, 4, 1, 4, 1, 1, 1, 1, 384, 219, 219, 219, 147,,, -7, 4, 2, 1, 1, 1, 1, 1, 128, 57, 57, 57, 39,,, -7, 4, 2, 1, 1, 1, 1, 1, 256, 57, 57, 57, 39,,, -7, 4, 2, 1, 1, 1, 1, 1, 384, 57, 57, 57, 39,,, -7, 4, 2, 2, 1, 1, 1, 1, 128, 111, 111, 111, 75,,, -7, 4, 2, 2, 1, 1, 1, 1, 256, 111, 111, 111, 75,,, -7, 4, 2, 2, 1, 1, 1, 1, 384, 111, 111, 111, 75,,, -7, 4, 2, 3, 1, 1, 1, 1, 128, 165, 165, 165, 111,,, -7, 4, 2, 3, 1, 1, 1, 1, 256, 165, 165, 165, 111,,, -7, 4, 2, 3, 1, 1, 1, 1, 384, 165, 165, 165, 111,,, -7, 4, 2, 4, 1, 1, 1, 1, 128, 219, 219, 219, 147,,, -7, 4, 2, 4, 1, 1, 1, 1, 256, 219, 219, 219, 147,,, -7, 4, 2, 4, 1, 1, 1, 1, 384, 219, 219, 219, 147,,, -7, 4, 3, 1, 1, 1, 1, 1, 128, 57, 57, 57, 39,,, -7, 4, 3, 1, 1, 1, 1, 1, 256, 57, 57, 57, 39,,, -7, 4, 3, 1, 1, 1, 1, 1, 384, 57, 57, 57, 39,,, -7, 4, 3, 2, 1, 1, 1, 1, 128, 111, 111, 111, 75,,, -7, 4, 3, 2, 1, 1, 1, 1, 256, 111, 111, 111, 75,,, -7, 4, 3, 2, 1, 1, 1, 1, 384, 111, 111, 111, 75,,, -7, 4, 3, 3, 1, 1, 1, 1, 128, 165, 165, 165, 111,,, -7, 4, 3, 3, 1, 1, 1, 1, 256, 165, 165, 165, 111,,, -7, 4, 3, 3, 1, 1, 1, 1, 384, 165, 165, 165, 111,,, -7, 4, 3, 4, 1, 1, 1, 1, 128, 219, 219, 219, 147,,, -7, 4, 3, 4, 1, 1, 1, 1, 256, 219, 219, 219, 147,,, -7, 4, 3, 4, 1, 1, 1, 1, 384, 219, 219, 219, 147,,, -7, 4, 4, 1, 1, 1, 1, 1, 128, 57, 57, 57, 39,,, -7, 4, 4, 1, 1, 1, 1, 1, 256, 57, 57, 57, 39,,, -7, 4, 4, 1, 1, 1, 1, 1, 384, 57, 57, 57, 39,,, -7, 4, 4, 2, 1, 1, 1, 1, 128, 111, 111, 111, 75,,, -7, 4, 4, 2, 1, 1, 1, 1, 256, 111, 111, 111, 75,,, -7, 4, 4, 2, 1, 1, 1, 1, 384, 111, 111, 111, 75,,, -7, 4, 4, 3, 1, 1, 1, 1, 128, 165, 165, 165, 111,,, -7, 4, 4, 3, 1, 1, 1, 1, 256, 165, 165, 165, 111,,, -7, 4, 4, 3, 1, 1, 1, 1, 384, 165, 165, 165, 111,,, -7, 4, 4, 4, 1, 1, 1, 1, 128, 219, 219, 219, 147,,, -7, 4, 4, 4, 1, 1, 1, 1, 256, 219, 219, 219, 147,,, -7, 4, 4, 4, 1, 1, 1, 1, 384, 219, 219, 219, 147,,, -7, 4, 5, 1, 1, 1, 1, 1, 128, 57, 57, 57, 39,,, -7, 4, 5, 1, 1, 1, 1, 1, 256, 57, 57, 57, 39,,, -7, 4, 5, 1, 1, 1, 1, 1, 384, 57, 57, 57, 39,,, -7, 4, 5, 2, 1, 1, 1, 1, 128, 111, 111, 111, 75,,, -7, 4, 5, 2, 1, 1, 1, 1, 256, 111, 111, 111, 75,,, -7, 4, 5, 2, 1, 1, 1, 1, 384, 111, 111, 111, 75,,, -7, 4, 5, 3, 1, 1, 1, 1, 128, 165, 165, 165, 111,,, -7, 4, 5, 3, 1, 1, 1, 1, 256, 165, 165, 165, 111,,, -7, 4, 5, 3, 1, 1, 1, 1, 384, 165, 165, 165, 111,,, -7, 4, 5, 4, 1, 1, 1, 1, 128, 219, 219, 219, 147,,, -7, 4, 5, 4, 1, 1, 1, 1, 256, 219, 219, 219, 147,,, -7, 4, 5, 4, 1, 1, 1, 1, 384, 219, 219, 219, 147,,, -7, 4, 6, 1, 1, 1, 1, 1, 128, 57, 57, 57, 39,,, -7, 4, 6, 1, 1, 1, 1, 1, 256, 57, 57, 57, 39,,, -7, 4, 6, 1, 1, 1, 1, 1, 384, 57, 57, 57, 39,,, -7, 4, 6, 2, 1, 1, 1, 1, 128, 111, 111, 111, 75,,, -7, 4, 6, 2, 1, 1, 1, 1, 256, 111, 111, 111, 75,,, -7, 4, 6, 2, 1, 1, 1, 1, 384, 111, 111, 111, 75,,, -7, 4, 6, 3, 1, 1, 1, 1, 128, 165, 165, 165, 111,,, -7, 4, 6, 3, 1, 1, 1, 1, 256, 165, 165, 165, 111,,, -7, 4, 6, 3, 1, 1, 1, 1, 384, 165, 165, 165, 111,,, -7, 4, 6, 4, 1, 1, 1, 1, 128, 219, 219, 219, 147,,, -7, 4, 6, 4, 1, 1, 1, 1, 256, 219, 219, 219, 147,,, -7, 4, 6, 4, 1, 1, 1, 1, 384, 219, 219, 219, 147,,, -7, 4, 7, 1, 1, 1, 1, 1, 128, 57, 57, 57, 39,,, -7, 4, 7, 1, 1, 1, 1, 1, 256, 57, 57, 57, 39,,, -7, 4, 7, 1, 1, 1, 1, 1, 384, 57, 57, 57, 39,,, -7, 4, 7, 2, 1, 1, 1, 1, 128, 111, 111, 111, 75,,, -7, 4, 7, 2, 1, 1, 1, 1, 256, 111, 111, 111, 75,,, -7, 4, 7, 2, 1, 1, 1, 1, 384, 111, 111, 111, 75,,, -7, 4, 7, 3, 1, 1, 1, 1, 128, 165, 165, 165, 111,,, -7, 4, 7, 3, 1, 1, 1, 1, 256, 165, 165, 165, 111,,, -7, 4, 7, 3, 1, 1, 1, 1, 384, 165, 165, 165, 111,,, -7, 4, 7, 4, 1, 1, 1, 1, 128, 219, 219, 219, 147,,, -7, 4, 7, 4, 1, 1, 1, 1, 256, 219, 219, 219, 147,,, -7, 4, 7, 4, 1, 1, 1, 1, 384, 219, 219, 219, 147,,, -7, 5, 1, 1, 1, 1, 1, 1, 128, 58, 58, 40, 22,,, -7, 5, 1, 1, 1, 1, 1, 1, 256, 58, 58, 40, 22,,, -7, 5, 1, 1, 1, 1, 1, 1, 384, 58, 58, 40, 22,,, -7, 5, 1, 2, 1, 1, 1, 1, 128, 112, 112, 76, 40,,, -7, 5, 1, 2, 1, 1, 1, 1, 256, 112, 112, 76, 40,,, -7, 5, 1, 2, 1, 1, 1, 1, 384, 112, 112, 76, 40,,, -7, 5, 1, 3, 1, 1, 1, 1, 128, 166, 166, 112, 58,,, -7, 5, 1, 3, 1, 1, 1, 1, 256, 166, 166, 112, 58,,, -7, 5, 1, 3, 1, 1, 1, 1, 384, 166, 166, 112, 58,,, -7, 5, 1, 4, 1, 1, 1, 1, 128, 220, 220, 148, 76,,, -7, 5, 1, 4, 1, 1, 1, 1, 256, 220, 220, 148, 76,,, -7, 5, 1, 4, 1, 1, 1, 1, 384, 220, 220, 148, 76,,, -7, 5, 1, 5, 1, 1, 1, 1, 128, 240, 240, 184, 94,,, -7, 5, 1, 5, 1, 1, 1, 1, 256, 240, 240, 184, 94,,, -7, 5, 1, 5, 1, 1, 1, 1, 384, 240, 240, 184, 94,,, -7, 5, 2, 1, 1, 1, 1, 1, 128, 58, 58, 40, 22,,, -7, 5, 2, 1, 1, 1, 1, 1, 256, 58, 58, 40, 22,,, -7, 5, 2, 1, 1, 1, 1, 1, 384, 58, 58, 40, 22,,, -7, 5, 2, 2, 1, 1, 1, 1, 128, 112, 112, 76, 40,,, -7, 5, 2, 2, 1, 1, 1, 1, 256, 112, 112, 76, 40,,, -7, 5, 2, 2, 1, 1, 1, 1, 384, 112, 112, 76, 40,,, -7, 5, 2, 3, 1, 1, 1, 1, 128, 166, 166, 112, 58,,, -7, 5, 2, 3, 1, 1, 1, 1, 256, 166, 166, 112, 58,,, -7, 5, 2, 3, 1, 1, 1, 1, 384, 166, 166, 112, 58,,, -7, 5, 2, 4, 1, 1, 1, 1, 128, 220, 220, 148, 76,,, -7, 5, 2, 4, 1, 1, 1, 1, 256, 220, 220, 148, 76,,, -7, 5, 2, 4, 1, 1, 1, 1, 384, 220, 220, 148, 76,,, -7, 5, 2, 5, 1, 1, 1, 1, 128, 240, 240, 184, 94,,, -7, 5, 2, 5, 1, 1, 1, 1, 256, 240, 240, 184, 94,,, -7, 5, 2, 5, 1, 1, 1, 1, 384, 240, 240, 184, 94,,, -7, 5, 3, 1, 1, 1, 1, 1, 128, 58, 58, 40, 22,,, -7, 5, 3, 1, 1, 1, 1, 1, 256, 58, 58, 40, 22,,, -7, 5, 3, 1, 1, 1, 1, 1, 384, 58, 58, 40, 22,,, -7, 5, 3, 2, 1, 1, 1, 1, 128, 112, 112, 76, 40,,, -7, 5, 3, 2, 1, 1, 1, 1, 256, 112, 112, 76, 40,,, -7, 5, 3, 2, 1, 1, 1, 1, 384, 112, 112, 76, 40,,, -7, 5, 3, 3, 1, 1, 1, 1, 128, 166, 166, 112, 58,,, -7, 5, 3, 3, 1, 1, 1, 1, 256, 166, 166, 112, 58,,, -7, 5, 3, 3, 1, 1, 1, 1, 384, 166, 166, 112, 58,,, -7, 5, 3, 4, 1, 1, 1, 1, 128, 220, 220, 148, 76,,, -7, 5, 3, 4, 1, 1, 1, 1, 256, 220, 220, 148, 76,,, -7, 5, 3, 4, 1, 1, 1, 1, 384, 220, 220, 148, 76,,, -7, 5, 3, 5, 1, 1, 1, 1, 128, 240, 240, 184, 94,,, -7, 5, 3, 5, 1, 1, 1, 1, 256, 240, 240, 184, 94,,, -7, 5, 3, 5, 1, 1, 1, 1, 384, 240, 240, 184, 94,,, -7, 5, 4, 1, 1, 1, 1, 1, 128, 58, 58, 40, 22,,, -7, 5, 4, 1, 1, 1, 1, 1, 256, 58, 58, 40, 22,,, -7, 5, 4, 1, 1, 1, 1, 1, 384, 58, 58, 40, 22,,, -7, 5, 4, 2, 1, 1, 1, 1, 128, 112, 112, 76, 40,,, -7, 5, 4, 2, 1, 1, 1, 1, 256, 112, 112, 76, 40,,, -7, 5, 4, 2, 1, 1, 1, 1, 384, 112, 112, 76, 40,,, -7, 5, 4, 3, 1, 1, 1, 1, 128, 166, 166, 112, 58,,, -7, 5, 4, 3, 1, 1, 1, 1, 256, 166, 166, 112, 58,,, -7, 5, 4, 3, 1, 1, 1, 1, 384, 166, 166, 112, 58,,, -7, 5, 4, 4, 1, 1, 1, 1, 128, 220, 220, 148, 76,,, -7, 5, 4, 4, 1, 1, 1, 1, 256, 220, 220, 148, 76,,, -7, 5, 4, 4, 1, 1, 1, 1, 384, 220, 220, 148, 76,,, -7, 5, 4, 5, 1, 1, 1, 1, 128, 240, 240, 184, 94,,, -7, 5, 4, 5, 1, 1, 1, 1, 256, 240, 240, 184, 94,,, -7, 5, 4, 5, 1, 1, 1, 1, 384, 240, 240, 184, 94,,, -7, 5, 5, 1, 1, 1, 1, 1, 128, 58, 58, 40, 22,,, -7, 5, 5, 1, 1, 1, 1, 1, 256, 58, 58, 40, 22,,, -7, 5, 5, 1, 1, 1, 1, 1, 384, 58, 58, 40, 22,,, -7, 5, 5, 2, 1, 1, 1, 1, 128, 112, 112, 76, 40,,, -7, 5, 5, 2, 1, 1, 1, 1, 256, 112, 112, 76, 40,,, -7, 5, 5, 2, 1, 1, 1, 1, 384, 112, 112, 76, 40,,, -7, 5, 5, 3, 1, 1, 1, 1, 128, 166, 166, 112, 58,,, -7, 5, 5, 3, 1, 1, 1, 1, 256, 166, 166, 112, 58,,, -7, 5, 5, 3, 1, 1, 1, 1, 384, 166, 166, 112, 58,,, -7, 5, 5, 4, 1, 1, 1, 1, 128, 220, 220, 148, 76,,, -7, 5, 5, 4, 1, 1, 1, 1, 256, 220, 220, 148, 76,,, -7, 5, 5, 4, 1, 1, 1, 1, 384, 220, 220, 148, 76,,, -7, 5, 5, 5, 1, 1, 1, 1, 128, 240, 240, 184, 94,,, -7, 5, 5, 5, 1, 1, 1, 1, 256, 240, 240, 184, 94,,, -7, 5, 5, 5, 1, 1, 1, 1, 384, 240, 240, 184, 94,,, -7, 5, 6, 1, 1, 1, 1, 1, 128, 58, 58, 40, 22,,, -7, 5, 6, 1, 1, 1, 1, 1, 256, 58, 58, 40, 22,,, -7, 5, 6, 1, 1, 1, 1, 1, 384, 58, 58, 40, 22,,, -7, 5, 6, 2, 1, 1, 1, 1, 128, 112, 112, 76, 40,,, -7, 5, 6, 2, 1, 1, 1, 1, 256, 112, 112, 76, 40,,, -7, 5, 6, 2, 1, 1, 1, 1, 384, 112, 112, 76, 40,,, -7, 5, 6, 3, 1, 1, 1, 1, 128, 166, 166, 112, 58,,, -7, 5, 6, 3, 1, 1, 1, 1, 256, 166, 166, 112, 58,,, -7, 5, 6, 3, 1, 1, 1, 1, 384, 166, 166, 112, 58,,, -7, 5, 6, 4, 1, 1, 1, 1, 128, 220, 220, 148, 76,,, -7, 5, 6, 4, 1, 1, 1, 1, 256, 220, 220, 148, 76,,, -7, 5, 6, 4, 1, 1, 1, 1, 384, 220, 220, 148, 76,,, -7, 5, 6, 5, 1, 1, 1, 1, 128, 240, 240, 184, 94,,, -7, 5, 6, 5, 1, 1, 1, 1, 256, 240, 240, 184, 94,,, -7, 5, 6, 5, 1, 1, 1, 1, 384, 240, 240, 184, 94,,, -7, 5, 7, 1, 1, 1, 1, 1, 128, 58, 58, 40, 22,,, -7, 5, 7, 1, 1, 1, 1, 1, 256, 58, 58, 40, 22,,, -7, 5, 7, 1, 1, 1, 1, 1, 384, 58, 58, 40, 22,,, -7, 5, 7, 2, 1, 1, 1, 1, 128, 112, 112, 76, 40,,, -7, 5, 7, 2, 1, 1, 1, 1, 256, 112, 112, 76, 40,,, -7, 5, 7, 2, 1, 1, 1, 1, 384, 112, 112, 76, 40,,, -7, 5, 7, 3, 1, 1, 1, 1, 128, 166, 166, 112, 58,,, -7, 5, 7, 3, 1, 1, 1, 1, 256, 166, 166, 112, 58,,, -7, 5, 7, 3, 1, 1, 1, 1, 384, 166, 166, 112, 58,,, -7, 5, 7, 4, 1, 1, 1, 1, 128, 220, 220, 148, 76,,, -7, 5, 7, 4, 1, 1, 1, 1, 256, 220, 220, 148, 76,,, -7, 5, 7, 4, 1, 1, 1, 1, 384, 220, 220, 148, 76,,, -7, 5, 7, 5, 1, 1, 1, 1, 128, 240, 240, 184, 94,,, -7, 5, 7, 5, 1, 1, 1, 1, 256, 240, 240, 184, 94,,, -7, 5, 7, 5, 1, 1, 1, 1, 384, 240, 240, 184, 94,,, -7, 6, 1, 1, 1, 1, 1, 1, 128, 59, 59, 41, 23,,, -7, 6, 1, 1, 1, 1, 1, 1, 256, 59, 59, 41, 23,,, -7, 6, 1, 1, 1, 1, 1, 1, 384, 59, 59, 41, 23,,, -7, 6, 1, 2, 1, 1, 1, 1, 128, 113, 113, 77, 41,,, -7, 6, 1, 2, 1, 1, 1, 1, 256, 113, 113, 77, 41,,, -7, 6, 1, 2, 1, 1, 1, 1, 384, 113, 113, 77, 41,,, -7, 6, 1, 3, 1, 1, 1, 1, 128, 167, 167, 113, 59,,, -7, 6, 1, 3, 1, 1, 1, 1, 256, 167, 167, 113, 59,,, -7, 6, 1, 3, 1, 1, 1, 1, 384, 167, 167, 113, 59,,, -7, 6, 1, 4, 1, 1, 1, 1, 128, 221, 221, 149, 77,,, -7, 6, 1, 4, 1, 1, 1, 1, 256, 221, 221, 149, 77,,, -7, 6, 1, 4, 1, 1, 1, 1, 384, 221, 221, 149, 77,,, -7, 6, 1, 5, 1, 1, 1, 1, 128, 240, 240, 185, 95,,, -7, 6, 1, 5, 1, 1, 1, 1, 256, 240, 240, 185, 95,,, -7, 6, 1, 5, 1, 1, 1, 1, 384, 240, 240, 185, 95,,, -7, 6, 1, 6, 1, 1, 1, 1, 128, 240, 240, 221, 113,,, -7, 6, 1, 6, 1, 1, 1, 1, 256, 240, 240, 221, 113,,, -7, 6, 1, 6, 1, 1, 1, 1, 384, 240, 240, 221, 113,,, -7, 6, 2, 1, 1, 1, 1, 1, 128, 59, 59, 41, 23,,, -7, 6, 2, 1, 1, 1, 1, 1, 256, 59, 59, 41, 23,,, -7, 6, 2, 1, 1, 1, 1, 1, 384, 59, 59, 41, 23,,, -7, 6, 2, 2, 1, 1, 1, 1, 128, 113, 113, 77, 41,,, -7, 6, 2, 2, 1, 1, 1, 1, 256, 113, 113, 77, 41,,, -7, 6, 2, 2, 1, 1, 1, 1, 384, 113, 113, 77, 41,,, -7, 6, 2, 3, 1, 1, 1, 1, 128, 167, 167, 113, 59,,, -7, 6, 2, 3, 1, 1, 1, 1, 256, 167, 167, 113, 59,,, -7, 6, 2, 3, 1, 1, 1, 1, 384, 167, 167, 113, 59,,, -7, 6, 2, 4, 1, 1, 1, 1, 128, 221, 221, 149, 77,,, -7, 6, 2, 4, 1, 1, 1, 1, 256, 221, 221, 149, 77,,, -7, 6, 2, 4, 1, 1, 1, 1, 384, 221, 221, 149, 77,,, -7, 6, 2, 5, 1, 1, 1, 1, 128, 240, 240, 185, 95,,, -7, 6, 2, 5, 1, 1, 1, 1, 256, 240, 240, 185, 95,,, -7, 6, 2, 5, 1, 1, 1, 1, 384, 240, 240, 185, 95,,, -7, 6, 2, 6, 1, 1, 1, 1, 128, 240, 240, 221, 113,,, -7, 6, 2, 6, 1, 1, 1, 1, 256, 240, 240, 221, 113,,, -7, 6, 2, 6, 1, 1, 1, 1, 384, 240, 240, 221, 113,,, -7, 6, 3, 1, 1, 1, 1, 1, 128, 59, 59, 41, 23,,, -7, 6, 3, 1, 1, 1, 1, 1, 256, 59, 59, 41, 23,,, -7, 6, 3, 1, 1, 1, 1, 1, 384, 59, 59, 41, 23,,, -7, 6, 3, 2, 1, 1, 1, 1, 128, 113, 113, 77, 41,,, -7, 6, 3, 2, 1, 1, 1, 1, 256, 113, 113, 77, 41,,, -7, 6, 3, 2, 1, 1, 1, 1, 384, 113, 113, 77, 41,,, -7, 6, 3, 3, 1, 1, 1, 1, 128, 167, 167, 113, 59,,, -7, 6, 3, 3, 1, 1, 1, 1, 256, 167, 167, 113, 59,,, -7, 6, 3, 3, 1, 1, 1, 1, 384, 167, 167, 113, 59,,, -7, 6, 3, 4, 1, 1, 1, 1, 128, 221, 221, 149, 77,,, -7, 6, 3, 4, 1, 1, 1, 1, 256, 221, 221, 149, 77,,, -7, 6, 3, 4, 1, 1, 1, 1, 384, 221, 221, 149, 77,,, -7, 6, 3, 5, 1, 1, 1, 1, 128, 240, 240, 185, 95,,, -7, 6, 3, 5, 1, 1, 1, 1, 256, 240, 240, 185, 95,,, -7, 6, 3, 5, 1, 1, 1, 1, 384, 240, 240, 185, 95,,, -7, 6, 3, 6, 1, 1, 1, 1, 128, 240, 240, 221, 113,,, -7, 6, 3, 6, 1, 1, 1, 1, 256, 240, 240, 221, 113,,, -7, 6, 3, 6, 1, 1, 1, 1, 384, 240, 240, 221, 113,,, -7, 6, 4, 1, 1, 1, 1, 1, 128, 59, 59, 41, 23,,, -7, 6, 4, 1, 1, 1, 1, 1, 256, 59, 59, 41, 23,,, -7, 6, 4, 1, 1, 1, 1, 1, 384, 59, 59, 41, 23,,, -7, 6, 4, 2, 1, 1, 1, 1, 128, 113, 113, 77, 41,,, -7, 6, 4, 2, 1, 1, 1, 1, 256, 113, 113, 77, 41,,, -7, 6, 4, 2, 1, 1, 1, 1, 384, 113, 113, 77, 41,,, -7, 6, 4, 3, 1, 1, 1, 1, 128, 167, 167, 113, 59,,, -7, 6, 4, 3, 1, 1, 1, 1, 256, 167, 167, 113, 59,,, -7, 6, 4, 3, 1, 1, 1, 1, 384, 167, 167, 113, 59,,, -7, 6, 4, 4, 1, 1, 1, 1, 128, 221, 221, 149, 77,,, -7, 6, 4, 4, 1, 1, 1, 1, 256, 221, 221, 149, 77,,, -7, 6, 4, 4, 1, 1, 1, 1, 384, 221, 221, 149, 77,,, -7, 6, 4, 5, 1, 1, 1, 1, 128, 240, 240, 185, 95,,, -7, 6, 4, 5, 1, 1, 1, 1, 256, 240, 240, 185, 95,,, -7, 6, 4, 5, 1, 1, 1, 1, 384, 240, 240, 185, 95,,, -7, 6, 4, 6, 1, 1, 1, 1, 128, 240, 240, 221, 113,,, -7, 6, 4, 6, 1, 1, 1, 1, 256, 240, 240, 221, 113,,, -7, 6, 4, 6, 1, 1, 1, 1, 384, 240, 240, 221, 113,,, -7, 6, 5, 1, 1, 1, 1, 1, 128, 59, 59, 41, 23,,, -7, 6, 5, 1, 1, 1, 1, 1, 256, 59, 59, 41, 23,,, -7, 6, 5, 1, 1, 1, 1, 1, 384, 59, 59, 41, 23,,, -7, 6, 5, 2, 1, 1, 1, 1, 128, 113, 113, 77, 41,,, -7, 6, 5, 2, 1, 1, 1, 1, 256, 113, 113, 77, 41,,, -7, 6, 5, 2, 1, 1, 1, 1, 384, 113, 113, 77, 41,,, -7, 6, 5, 3, 1, 1, 1, 1, 128, 167, 167, 113, 59,,, -7, 6, 5, 3, 1, 1, 1, 1, 256, 167, 167, 113, 59,,, -7, 6, 5, 3, 1, 1, 1, 1, 384, 167, 167, 113, 59,,, -7, 6, 5, 4, 1, 1, 1, 1, 128, 221, 221, 149, 77,,, -7, 6, 5, 4, 1, 1, 1, 1, 256, 221, 221, 149, 77,,, -7, 6, 5, 4, 1, 1, 1, 1, 384, 221, 221, 149, 77,,, -7, 6, 5, 5, 1, 1, 1, 1, 128, 240, 240, 185, 95,,, -7, 6, 5, 5, 1, 1, 1, 1, 256, 240, 240, 185, 95,,, -7, 6, 5, 5, 1, 1, 1, 1, 384, 240, 240, 185, 95,,, -7, 6, 5, 6, 1, 1, 1, 1, 128, 240, 240, 221, 113,,, -7, 6, 5, 6, 1, 1, 1, 1, 256, 240, 240, 221, 113,,, -7, 6, 5, 6, 1, 1, 1, 1, 384, 240, 240, 221, 113,,, -7, 6, 6, 1, 1, 1, 1, 1, 128, 59, 59, 41, 23,,, -7, 6, 6, 1, 1, 1, 1, 1, 256, 59, 59, 41, 23,,, -7, 6, 6, 1, 1, 1, 1, 1, 384, 59, 59, 41, 23,,, -7, 6, 6, 2, 1, 1, 1, 1, 128, 113, 113, 77, 41,,, -7, 6, 6, 2, 1, 1, 1, 1, 256, 113, 113, 77, 41,,, -7, 6, 6, 2, 1, 1, 1, 1, 384, 113, 113, 77, 41,,, -7, 6, 6, 3, 1, 1, 1, 1, 128, 167, 167, 113, 59,,, -7, 6, 6, 3, 1, 1, 1, 1, 256, 167, 167, 113, 59,,, -7, 6, 6, 3, 1, 1, 1, 1, 384, 167, 167, 113, 59,,, -7, 6, 6, 4, 1, 1, 1, 1, 128, 221, 221, 149, 77,,, -7, 6, 6, 4, 1, 1, 1, 1, 256, 221, 221, 149, 77,,, -7, 6, 6, 4, 1, 1, 1, 1, 384, 221, 221, 149, 77,,, -7, 6, 6, 5, 1, 1, 1, 1, 128, 240, 240, 185, 95,,, -7, 6, 6, 5, 1, 1, 1, 1, 256, 240, 240, 185, 95,,, -7, 6, 6, 5, 1, 1, 1, 1, 384, 240, 240, 185, 95,,, -7, 6, 6, 6, 1, 1, 1, 1, 128, 240, 240, 221, 113,,, -7, 6, 6, 6, 1, 1, 1, 1, 256, 240, 240, 221, 113,,, -7, 6, 6, 6, 1, 1, 1, 1, 384, 240, 240, 221, 113,,, -7, 6, 7, 1, 1, 1, 1, 1, 128, 59, 59, 41, 23,,, -7, 6, 7, 1, 1, 1, 1, 1, 256, 59, 59, 41, 23,,, -7, 6, 7, 1, 1, 1, 1, 1, 384, 59, 59, 41, 23,,, -7, 6, 7, 2, 1, 1, 1, 1, 128, 113, 113, 77, 41,,, -7, 6, 7, 2, 1, 1, 1, 1, 256, 113, 113, 77, 41,,, -7, 6, 7, 2, 1, 1, 1, 1, 384, 113, 113, 77, 41,,, -7, 6, 7, 3, 1, 1, 1, 1, 128, 167, 167, 113, 59,,, -7, 6, 7, 3, 1, 1, 1, 1, 256, 167, 167, 113, 59,,, -7, 6, 7, 3, 1, 1, 1, 1, 384, 167, 167, 113, 59,,, -7, 6, 7, 4, 1, 1, 1, 1, 128, 221, 221, 149, 77,,, -7, 6, 7, 4, 1, 1, 1, 1, 256, 221, 221, 149, 77,,, -7, 6, 7, 4, 1, 1, 1, 1, 384, 221, 221, 149, 77,,, -7, 6, 7, 5, 1, 1, 1, 1, 128, 240, 240, 185, 95,,, -7, 6, 7, 5, 1, 1, 1, 1, 256, 240, 240, 185, 95,,, -7, 6, 7, 5, 1, 1, 1, 1, 384, 240, 240, 185, 95,,, -7, 6, 7, 6, 1, 1, 1, 1, 128, 240, 240, 221, 113,,, -7, 6, 7, 6, 1, 1, 1, 1, 256, 240, 240, 221, 113,,, -7, 6, 7, 6, 1, 1, 1, 1, 384, 240, 240, 221, 113,,, -7, 7, 1, 1, 1, 1, 1, 1, 128, 60, 60, 42,,,, -7, 7, 1, 1, 1, 1, 1, 1, 256, 60, 60, 42,,,, -7, 7, 1, 1, 1, 1, 1, 1, 384, 60, 60, 42,,,, -7, 7, 1, 2, 1, 1, 1, 1, 128, 114, 114, 78,,,, -7, 7, 1, 2, 1, 1, 1, 1, 256, 114, 114, 78,,,, -7, 7, 1, 2, 1, 1, 1, 1, 384, 114, 114, 78,,,, -7, 7, 1, 3, 1, 1, 1, 1, 128, 168, 168, 114,,,, -7, 7, 1, 3, 1, 1, 1, 1, 256, 168, 168, 114,,,, -7, 7, 1, 3, 1, 1, 1, 1, 384, 168, 168, 114,,,, -7, 7, 1, 4, 1, 1, 1, 1, 128, 222, 222, 150,,,, -7, 7, 1, 4, 1, 1, 1, 1, 256, 222, 222, 150,,,, -7, 7, 1, 4, 1, 1, 1, 1, 384, 222, 222, 150,,,, -7, 7, 1, 5, 1, 1, 1, 1, 128, 240, 240, 186,,,, -7, 7, 1, 5, 1, 1, 1, 1, 256, 240, 240, 186,,,, -7, 7, 1, 5, 1, 1, 1, 1, 384, 240, 240, 186,,,, -7, 7, 1, 6, 1, 1, 1, 1, 128, 240, 240, 222,,,, -7, 7, 1, 6, 1, 1, 1, 1, 256, 240, 240, 222,,,, -7, 7, 1, 6, 1, 1, 1, 1, 384, 240, 240, 222,,,, -7, 7, 1, 7, 1, 1, 1, 1, 128, 240, 240, 240,,,, -7, 7, 1, 7, 1, 1, 1, 1, 256, 240, 240, 240,,,, -7, 7, 1, 7, 1, 1, 1, 1, 384, 240, 240, 240,,,, -7, 7, 2, 1, 1, 1, 1, 1, 128, 60, 60, 42,,,, -7, 7, 2, 1, 1, 1, 1, 1, 256, 60, 60, 42,,,, -7, 7, 2, 1, 1, 1, 1, 1, 384, 60, 60, 42,,,, -7, 7, 2, 2, 1, 1, 1, 1, 128, 114, 114, 78,,,, -7, 7, 2, 2, 1, 1, 1, 1, 256, 114, 114, 78,,,, -7, 7, 2, 2, 1, 1, 1, 1, 384, 114, 114, 78,,,, -7, 7, 2, 3, 1, 1, 1, 1, 128, 168, 168, 114,,,, -7, 7, 2, 3, 1, 1, 1, 1, 256, 168, 168, 114,,,, -7, 7, 2, 3, 1, 1, 1, 1, 384, 168, 168, 114,,,, -7, 7, 2, 4, 1, 1, 1, 1, 128, 222, 222, 150,,,, -7, 7, 2, 4, 1, 1, 1, 1, 256, 222, 222, 150,,,, -7, 7, 2, 4, 1, 1, 1, 1, 384, 222, 222, 150,,,, -7, 7, 2, 5, 1, 1, 1, 1, 128, 240, 240, 186,,,, -7, 7, 2, 5, 1, 1, 1, 1, 256, 240, 240, 186,,,, -7, 7, 2, 5, 1, 1, 1, 1, 384, 240, 240, 186,,,, -7, 7, 2, 6, 1, 1, 1, 1, 128, 240, 240, 222,,,, -7, 7, 2, 6, 1, 1, 1, 1, 256, 240, 240, 222,,,, -7, 7, 2, 6, 1, 1, 1, 1, 384, 240, 240, 222,,,, -7, 7, 2, 7, 1, 1, 1, 1, 128, 240, 240, 240,,,, -7, 7, 2, 7, 1, 1, 1, 1, 256, 240, 240, 240,,,, -7, 7, 2, 7, 1, 1, 1, 1, 384, 240, 240, 240,,,, -7, 7, 3, 1, 1, 1, 1, 1, 128, 60, 60, 42,,,, -7, 7, 3, 1, 1, 1, 1, 1, 256, 60, 60, 42,,,, -7, 7, 3, 1, 1, 1, 1, 1, 384, 60, 60, 42,,,, -7, 7, 3, 2, 1, 1, 1, 1, 128, 114, 114, 78,,,, -7, 7, 3, 2, 1, 1, 1, 1, 256, 114, 114, 78,,,, -7, 7, 3, 2, 1, 1, 1, 1, 384, 114, 114, 78,,,, -7, 7, 3, 3, 1, 1, 1, 1, 128, 168, 168, 114,,,, -7, 7, 3, 3, 1, 1, 1, 1, 256, 168, 168, 114,,,, -7, 7, 3, 3, 1, 1, 1, 1, 384, 168, 168, 114,,,, -7, 7, 3, 4, 1, 1, 1, 1, 128, 222, 222, 150,,,, -7, 7, 3, 4, 1, 1, 1, 1, 256, 222, 222, 150,,,, -7, 7, 3, 4, 1, 1, 1, 1, 384, 222, 222, 150,,,, -7, 7, 3, 5, 1, 1, 1, 1, 128, 240, 240, 186,,,, -7, 7, 3, 5, 1, 1, 1, 1, 256, 240, 240, 186,,,, -7, 7, 3, 5, 1, 1, 1, 1, 384, 240, 240, 186,,,, -7, 7, 3, 6, 1, 1, 1, 1, 128, 240, 240, 222,,,, -7, 7, 3, 6, 1, 1, 1, 1, 256, 240, 240, 222,,,, -7, 7, 3, 6, 1, 1, 1, 1, 384, 240, 240, 222,,,, -7, 7, 3, 7, 1, 1, 1, 1, 128, 240, 240, 240,,,, -7, 7, 3, 7, 1, 1, 1, 1, 256, 240, 240, 240,,,, -7, 7, 3, 7, 1, 1, 1, 1, 384, 240, 240, 240,,,, -7, 7, 4, 1, 1, 1, 1, 1, 128, 60, 60, 42,,,, -7, 7, 4, 1, 1, 1, 1, 1, 256, 60, 60, 42,,,, -7, 7, 4, 1, 1, 1, 1, 1, 384, 60, 60, 42,,,, -7, 7, 4, 2, 1, 1, 1, 1, 128, 114, 114, 78,,,, -7, 7, 4, 2, 1, 1, 1, 1, 256, 114, 114, 78,,,, -7, 7, 4, 2, 1, 1, 1, 1, 384, 114, 114, 78,,,, -7, 7, 4, 3, 1, 1, 1, 1, 128, 168, 168, 114,,,, -7, 7, 4, 3, 1, 1, 1, 1, 256, 168, 168, 114,,,, -7, 7, 4, 3, 1, 1, 1, 1, 384, 168, 168, 114,,,, -7, 7, 4, 4, 1, 1, 1, 1, 128, 222, 222, 150,,,, -7, 7, 4, 4, 1, 1, 1, 1, 256, 222, 222, 150,,,, -7, 7, 4, 4, 1, 1, 1, 1, 384, 222, 222, 150,,,, -7, 7, 4, 5, 1, 1, 1, 1, 128, 240, 240, 186,,,, -7, 7, 4, 5, 1, 1, 1, 1, 256, 240, 240, 186,,,, -7, 7, 4, 5, 1, 1, 1, 1, 384, 240, 240, 186,,,, -7, 7, 4, 6, 1, 1, 1, 1, 128, 240, 240, 222,,,, -7, 7, 4, 6, 1, 1, 1, 1, 256, 240, 240, 222,,,, -7, 7, 4, 6, 1, 1, 1, 1, 384, 240, 240, 222,,,, -7, 7, 4, 7, 1, 1, 1, 1, 128, 240, 240, 240,,,, -7, 7, 4, 7, 1, 1, 1, 1, 256, 240, 240, 240,,,, -7, 7, 4, 7, 1, 1, 1, 1, 384, 240, 240, 240,,,, -7, 7, 5, 1, 1, 1, 1, 1, 128, 60, 60, 42,,,, -7, 7, 5, 1, 1, 1, 1, 1, 256, 60, 60, 42,,,, -7, 7, 5, 1, 1, 1, 1, 1, 384, 60, 60, 42,,,, -7, 7, 5, 2, 1, 1, 1, 1, 128, 114, 114, 78,,,, -7, 7, 5, 2, 1, 1, 1, 1, 256, 114, 114, 78,,,, -7, 7, 5, 2, 1, 1, 1, 1, 384, 114, 114, 78,,,, -7, 7, 5, 3, 1, 1, 1, 1, 128, 168, 168, 114,,,, -7, 7, 5, 3, 1, 1, 1, 1, 256, 168, 168, 114,,,, -7, 7, 5, 3, 1, 1, 1, 1, 384, 168, 168, 114,,,, -7, 7, 5, 4, 1, 1, 1, 1, 128, 222, 222, 150,,,, -7, 7, 5, 4, 1, 1, 1, 1, 256, 222, 222, 150,,,, -7, 7, 5, 4, 1, 1, 1, 1, 384, 222, 222, 150,,,, -7, 7, 5, 5, 1, 1, 1, 1, 128, 240, 240, 186,,,, -7, 7, 5, 5, 1, 1, 1, 1, 256, 240, 240, 186,,,, -7, 7, 5, 5, 1, 1, 1, 1, 384, 240, 240, 186,,,, -7, 7, 5, 6, 1, 1, 1, 1, 128, 240, 240, 222,,,, -7, 7, 5, 6, 1, 1, 1, 1, 256, 240, 240, 222,,,, -7, 7, 5, 6, 1, 1, 1, 1, 384, 240, 240, 222,,,, -7, 7, 5, 7, 1, 1, 1, 1, 128, 240, 240, 240,,,, -7, 7, 5, 7, 1, 1, 1, 1, 256, 240, 240, 240,,,, -7, 7, 5, 7, 1, 1, 1, 1, 384, 240, 240, 240,,,, -7, 7, 6, 1, 1, 1, 1, 1, 128, 60, 60, 42,,,, -7, 7, 6, 1, 1, 1, 1, 1, 256, 60, 60, 42,,,, -7, 7, 6, 1, 1, 1, 1, 1, 384, 60, 60, 42,,,, -7, 7, 6, 2, 1, 1, 1, 1, 128, 114, 114, 78,,,, -7, 7, 6, 2, 1, 1, 1, 1, 256, 114, 114, 78,,,, -7, 7, 6, 2, 1, 1, 1, 1, 384, 114, 114, 78,,,, -7, 7, 6, 3, 1, 1, 1, 1, 128, 168, 168, 114,,,, -7, 7, 6, 3, 1, 1, 1, 1, 256, 168, 168, 114,,,, -7, 7, 6, 3, 1, 1, 1, 1, 384, 168, 168, 114,,,, -7, 7, 6, 4, 1, 1, 1, 1, 128, 222, 222, 150,,,, -7, 7, 6, 4, 1, 1, 1, 1, 256, 222, 222, 150,,,, -7, 7, 6, 4, 1, 1, 1, 1, 384, 222, 222, 150,,,, -7, 7, 6, 5, 1, 1, 1, 1, 128, 240, 240, 186,,,, -7, 7, 6, 5, 1, 1, 1, 1, 256, 240, 240, 186,,,, -7, 7, 6, 5, 1, 1, 1, 1, 384, 240, 240, 186,,,, -7, 7, 6, 6, 1, 1, 1, 1, 128, 240, 240, 222,,,, -7, 7, 6, 6, 1, 1, 1, 1, 256, 240, 240, 222,,,, -7, 7, 6, 6, 1, 1, 1, 1, 384, 240, 240, 222,,,, -7, 7, 6, 7, 1, 1, 1, 1, 128, 240, 240, 240,,,, -7, 7, 6, 7, 1, 1, 1, 1, 256, 240, 240, 240,,,, -7, 7, 6, 7, 1, 1, 1, 1, 384, 240, 240, 240,,,, -7, 7, 7, 1, 1, 1, 1, 1, 128, 60, 60, 42,,,, -7, 7, 7, 1, 1, 1, 1, 1, 256, 60, 60, 42,,,, -7, 7, 7, 1, 1, 1, 1, 1, 384, 60, 60, 42,,,, -7, 7, 7, 2, 1, 1, 1, 1, 128, 114, 114, 78,,,, -7, 7, 7, 2, 1, 1, 1, 1, 256, 114, 114, 78,,,, -7, 7, 7, 2, 1, 1, 1, 1, 384, 114, 114, 78,,,, -7, 7, 7, 3, 1, 1, 1, 1, 128, 168, 168, 114,,,, -7, 7, 7, 3, 1, 1, 1, 1, 256, 168, 168, 114,,,, -7, 7, 7, 3, 1, 1, 1, 1, 384, 168, 168, 114,,,, -7, 7, 7, 4, 1, 1, 1, 1, 128, 222, 222, 150,,,, -7, 7, 7, 4, 1, 1, 1, 1, 256, 222, 222, 150,,,, -7, 7, 7, 4, 1, 1, 1, 1, 384, 222, 222, 150,,,, -7, 7, 7, 5, 1, 1, 1, 1, 128, 240, 240, 186,,,, -7, 7, 7, 5, 1, 1, 1, 1, 256, 240, 240, 186,,,, -7, 7, 7, 5, 1, 1, 1, 1, 384, 240, 240, 186,,,, -7, 7, 7, 6, 1, 1, 1, 1, 128, 240, 240, 222,,,, -7, 7, 7, 6, 1, 1, 1, 1, 256, 240, 240, 222,,,, -7, 7, 7, 6, 1, 1, 1, 1, 384, 240, 240, 222,,,, -7, 7, 7, 7, 1, 1, 1, 1, 128, 240, 240, 240,,,, -7, 7, 7, 7, 1, 1, 1, 1, 256, 240, 240, 240,,,, -7, 7, 7, 7, 1, 1, 1, 1, 384, 240, 240, 240,,,,, \ No newline at end of file diff --git a/docs/articles_en/openvino_workflow/running_inference_with_openvino/inference_modes_overview.rst b/docs/articles_en/openvino_workflow/running_inference_with_openvino/inference_modes_overview.rst deleted file mode 100644 index 58a9e8f8070963..00000000000000 --- a/docs/articles_en/openvino_workflow/running_inference_with_openvino/inference_modes_overview.rst +++ /dev/null @@ -1,25 +0,0 @@ -.. {#openvino_docs_Runtime_Inference_Modes_Overview} - -Inference Modes -=============== - - -.. toctree:: - :maxdepth: 1 - :hidden: - - openvino_docs_OV_UG_supported_plugins_AUTO - openvino_docs_OV_UG_Running_on_multiple_devices - openvino_docs_OV_UG_Hetero_execution - openvino_docs_OV_UG_Automatic_Batching - - -OpenVINO Runtime offers multiple inference modes to allow optimum hardware utilization under different conditions. The most basic one is a single-device mode, which defines just one device responsible for the entire inference workload. It supports a range of Intel hardware by means of plugins embedded in the Runtime library, each set up to offer the best possible performance. For a complete list of supported devices and instructions on how to use them, refer to the :doc:`guide on inference devices `. - -The remaining modes assume certain levels of automation in selecting devices for inference. Using them in the deployed solution may potentially increase its performance and portability. The automated modes are: - -* :doc:`Automatic Device Selection (AUTO) ` -* :doc:`Multi-Device Execution (MULTI) ` -* :doc:`Heterogeneous Execution (HETERO) ` -* :doc:`Automatic Batching Execution (Auto-batching) ` - diff --git a/docs/dev/assets/CI_check_results.png b/docs/dev/assets/CI_check_results.png new file mode 100644 index 00000000000000..e5a9e3d1c812e8 --- /dev/null +++ b/docs/dev/assets/CI_check_results.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:01a0e1f2bae4b1681f1b87b9918d01023a56cd8095980ba2fd5e6ba7be77c0de +size 76267 diff --git a/docs/dev/assets/CI_completed_job_list.png b/docs/dev/assets/CI_completed_job_list.png new file mode 100644 index 00000000000000..56429bef8d9bba --- /dev/null +++ b/docs/dev/assets/CI_completed_job_list.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:abe7de7949a2413024a8a00f3f57fa9723dfee0910eb61b8b64015fe3ce95f24 +size 35459 diff --git a/docs/dev/assets/CI_gha_cache_example.png b/docs/dev/assets/CI_gha_cache_example.png new file mode 100644 index 00000000000000..e5081a64adf122 --- /dev/null +++ b/docs/dev/assets/CI_gha_cache_example.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:f95cd9dc3c31131ae78711b207a2d7a7abcda23ceed844c6bc4806917110bdc0 +size 19503 diff --git a/docs/dev/assets/CI_pipeline_artifacts.png b/docs/dev/assets/CI_pipeline_artifacts.png new file mode 100644 index 00000000000000..4bbd4f3ea9acf1 --- /dev/null +++ b/docs/dev/assets/CI_pipeline_artifacts.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:52e2bb50ba3acd6afabf1a037b44e265fc64ff51d4adb0ed6d2f496635d92966 +size 70307 diff --git a/docs/dev/build_android.md b/docs/dev/build_android.md index 7db455e297e034..91cd94644a6e6e 100644 --- a/docs/dev/build_android.md +++ b/docs/dev/build_android.md @@ -1,6 +1,6 @@ # Build OpenVINO™ Runtime for Android systems -This article describes how to build Inference Engine for Android operating systems. +This article describes how to build OpenVINO for Android operating systems. ## Software requirements diff --git a/docs/dev/ci/github_actions/caches.md b/docs/dev/ci/github_actions/caches.md index bf82faafd0e01f..5ce7ff199bfefc 100644 --- a/docs/dev/ci/github_actions/caches.md +++ b/docs/dev/ci/github_actions/caches.md @@ -9,7 +9,7 @@ Three types of caches are available: * Available for both GitHub-hosted and self-hosted runners * Accessible by `actions/cache` action * Limited to 10 GB per repository - * Suitable for small dependencies caches and artefacts that could be reused between runs + * Suitable for small dependencies caches and artefacts that could be reused between runs * [Shared drive cache](#shared-drive-cache-usage-and-structure) * Available only to the self-hosted runners * Automatically available via a certain path @@ -40,10 +40,11 @@ CPU_Functional_Tests: key: ${{ runner.os }}-${{ runner.arch }}-tests-functional-cpu-stamp-${{ github.sha }} ... ``` -with a particular key: `${{ runner.os }}-${{ runner.arch }}-tests-functional-cpu-stamp-${{ github.sha }}`. +with a particular key: `${{ runner.os }}-${{ runner.arch }}-tests-functional-cpu-stamp-${{ github.sha }}`. Then it could be seen in the [repository's cache](https://github.com/openvinotoolkit/openvino/actions/caches): -![gha_cache_example](../../../sphinx_setup/_static/images/ci/gha_cache_example.png) + +![gha_cache_example](../../assets/CI_gha_cache_example.png) The next runs could download the artefact from the repository's cache with `actions/cache/restore` and use it: ```yaml @@ -66,11 +67,11 @@ Refer to the [`actions/cache`'s documentation](https://github.com/actions/cache) ## Shared Drive Cache Usage and Structure -This cache could be used to store dependencies and large assets (models, datasets, etc.) that are to be used by different workflow jobs. +This cache could be used to store dependencies and large assets (models, datasets, etc.) that are to be used by different workflow jobs. **Note**: This cache is enabled for the Linux [self-hosted runners](./runners.md) only. -The drive is available on the self-hosted machines, and to make it available inside [the Docker containers](./docker_images.md), +The drive is available on the self-hosted machines, and to make it available inside [the Docker containers](./docker_images.md), the mounting point should be added under the `container`'s `volumes` key in a job configuration: ```yaml Build: @@ -89,7 +90,7 @@ The first `/mount` in `- /mount:/mount` is the path on the runner, the second `/ * `pip` cache * Accessible via an environment variable `PIP_CACHE_PATH: /mount/caches/pip/linux` defined on a workflow level - * Used in the jobs that have Python usage + * Used in the jobs that have Python usage * onnx models for tests * Accessible by the path: `/mount/onnxtestdata` * Used in the `ONNX Models tests` job in the [`linux.yml`](./../../../../.github/workflows/linux.yml) workflow @@ -100,7 +101,7 @@ To add new resources, contact someone from the CI team for assistance. ## Cloud Storage via Azure Blob Storage -This cache is used for sharing OpenVINO build artefacts between runs. +This cache is used for sharing OpenVINO build artefacts between runs. The [`sccache`](https://github.com/mozilla/sccache) tool can cache, upload and download build files to/from [Azure Blob Storage](https://azure.microsoft.com/en-us/products/storage/blobs). **Note**: This cache is enabled for [self-hosted runners](./runners.md) only. diff --git a/docs/dev/ci/github_actions/overview.md b/docs/dev/ci/github_actions/overview.md index 270c2eddb0ce9c..70047d14aa0e72 100644 --- a/docs/dev/ci/github_actions/overview.md +++ b/docs/dev/ci/github_actions/overview.md @@ -1,6 +1,8 @@ # Overview of the OpenVINO GitHub Actions CI -Welcome to the OpenVINO Developer guide on the GitHub Actions infrastructure. This document gives a brief overview of the GitHub Actions setup used in OpenVINO. +Welcome to the OpenVINO Developer guide on the GitHub Actions infrastructure. +This document will give you an overview of the setup used in OpenVINO and point you at more +detailed instructions where necessary. ## Table of Contents @@ -9,7 +11,7 @@ Welcome to the OpenVINO Developer guide on the GitHub Actions infrastructure. Th * [Required workflows](#required-workflows) * [Workflow structure](#structure-of-the-workflows) * [Workflow and job organisation](#workflows-and-jobs-organisation) -* [Finding results, artefacts and logs](#finding-results-artefacts-and-logs) +* [Finding results, artifacts and logs](#finding-results-artifacts-and-logs) * [Custom actions overview](#custom-actions) * [Machines overview](#machines) * [Docker images overview](#docker-images) @@ -19,17 +21,17 @@ Welcome to the OpenVINO Developer guide on the GitHub Actions infrastructure. Th ## Workflows -GitHub Actions workflows are configurable automated processes that will run one or more jobs via a series of steps. +GitHub Actions workflows are configurable and automated processes that run one or multiple +consecutive jobs (for more details, refer to the +[official GitHub Actions documentation](https://docs.github.com/en/actions/using-workflows/about-workflows)). +They include: -In short, workflows comprise: -* a series of commands that you would usually execute in a terminal one by one -* the information about the environment in which the commands should be executed +* a series of commands that you would usually execute in a terminal, one by one +* information about the environment in which the commands should be executed -Refer to the [official GitHub Actions documentation](https://docs.github.com/en/actions/using-workflows/about-workflows) for more. -You can find all the workflows for this repository [here](../../../../.github/workflows). - -Three main ones provide the most coverage for different operating systems: +You can find all workflows for this repository in the [workflows folder](../../../../.github/workflows). +The three main ones, providing most coverage for different operating systems, are: * [Linux](../../../../.github/workflows/linux.yml) * [Windows](../../../../.github/workflows/windows.yml) * [macOS](../../../../.github/workflows/mac.yml) @@ -43,27 +45,40 @@ Additionally, several supporting workflows build and test OpenVINO for other ope ### Reusing GitHub Actions -The OpenVINO workflows make use of the rich official and community actions such as `actions/checkout`, `actions/upload-artifact` and others. +The OpenVINO workflows use both official and community-built actions, such as `actions/checkout` +and `actions/upload-artifact`. Additionally, jobs featured in several workflows are extracted +into _reusable workflows_. You can learn more about [using and writing them](./reusable_workflows.md), +check how to [reuse workflows](https://docs.github.com/en/actions/using-workflows/reusing-workflows), +and see what and how to [obtain additional actions](https://github.com/marketplace?type=actions). -Additionally, common jobs, i.e., those featured in several workflows, are extracted into _reusable workflows_. -Read more about the used reusable workflows and how to write one [here](./reusable_workflows.md). +### Workflows' Triggers and Schedule -You can find more information about reusing actions and workflows [here](https://github.com/marketplace?type=actions) and [here](https://docs.github.com/en/actions/using-workflows/reusing-workflows). +Workflows run whenever they are triggered by predefined [events](https://docs.github.com/en/actions/using-workflows/events-that-trigger-workflows). +These triggers **are not** mutually exclusive and multiple can be used by one workflow. +The OpenVINO repository has three, and as you may see in the example below, they are all +included in the [Linux workflow](../../../../.github/workflows/linux.yml). They are: -### Workflows' Triggers and Schedule +* `on: schedule` - schedule trigger + * This trigger runs the workflow on a specified interval (e.g., nightly). + * In the example below: `'0 0 * * 3,6'` - learn more on [cron syntax](https://crontab.guru/) +* `on: pull_request` - pre-commit trigger + * This trigger runs the workflow when a PR is created targeting the `master` or `release` + branch and every time the PR is updated with new commits. + * In the example below, it additionally requires that the changed files conform to the path + globs specified under the `paths` key. +* `on: push` - post-commit trigger. + * This trigger runs the workflow when a commit is pushed to the `master` or `release` branch + (e.g., when a PR is merged). + * In the example below, it additionally requires that the changed files conform to the path + globs specified under the `paths` key. -Workflows have triggers for different [events](https://docs.github.com/en/actions/using-workflows/events-that-trigger-workflows) that tell them when to start. +The triggers for each workflow can be found at the beginning of a workflow file, in the `on` +key. You should also learn how to use +[paths](https://docs.github.com/en/actions/using-workflows/workflow-syntax-for-github-actions#onpushpull_requestpull_request_targetpathspaths-ignore). -The workflows in the OpenVINO repository have the following triggers: -* `on: push` - post-commit trigger. If a workflow has this trigger, it runs when a commit is pushed to the `master` or `release` branch (e.g., when a PR is merged) -* `on: pull_request` - pre-commit trigger. If a workflow has this trigger, it runs when a PR is created targeting the `master` or `release` branch and every time the PR is updated with new commits -* `on: schedule` - schedule trigger. If a workflow has this trigger, it runs on a specified interval (e.g., nightly) -**NOTE**: these triggers **are not** mutually exclusive, one workflow could use any combination of them. -You can find the triggers for each workflow at the beginning of the workflow file, in the `on` key. -Example for the [Linux workflow](../../../../.github/workflows/linux.yml): ```yaml on: schedule: @@ -90,33 +105,33 @@ on: - 'releases/**' ``` -This workflow runs: -* On a specified interval (`schedule`) - * `'0 0 * * 3,6'` - `cron` syntax, see examples and configurator [here](https://crontab.guru/) -* On Pull Request update (`pull_request`) **if** the changed files conform to the path globs specified under the `paths` key -* On Push to the `master` and `releases/**` branches (`push`) **if** the changed files conform to the path globs specified under the `paths` key +--- +**NOTE** -**NOTE**: read more about the `paths` [here](https://docs.github.com/en/actions/using-workflows/workflow-syntax-for-github-actions#onpushpull_requestpull_request_targetpathspaths-ignore). +The workflows listed above are **required** for OpenVINO contributions. If they fail the PR +cannot be merged. It is always a good idea to check their +[results](#finding-results-artifacts-and-logs) while working within the OpenVINO repository. -### Required Workflows +--- -The listed above workflows are **required**, i.e., a PR could not be merged if any of their stages fail. It is strongly encouraged to pay attention to their [results](#finding-results-artefacts-and-logs) while working within the OpenVINO repository. -### Structure of the Workflows +### Workflow Structure -This section provides the structural overview of the Linux, Windows and macOS workflows. +The workflow structures for Linux, Windows, and macOS are mostly the same: -The structure for all of them is mostly the same: -1. Clone OpenVINO repository and required resources +1. Clone the OpenVINO repository and required resources 2. Install build dependencies 3. Build OpenVINO from source -4. Pack and upload the artefacts (built OpenVINO and tests) -5. Download and use the artefacts in the parallel jobs with different tests -6. Collect the test results and upload them as artefacts +4. Pack and upload the artifacts (the built OpenVINO and tests) +5. Download and use the artifacts in the parallel jobs with different tests +6. Collect the test results and upload them as artifacts + +**NOTE**: some workflows may use the same structure, while others may lack the last 3 steps, +with tests coming right after the `Build` step. -**NOTE**: some workflows may use the same structure or lack the last 3 steps and have tests present right after the `Build` step. +Overview of the [Linux workflow](../../../../.github/workflows/linux.yml). +There are several jobs present: -Overview of the [Linux workflow](../../../../.github/workflows/linux.yml). There are several jobs present: ```yaml jobs: Build: ... @@ -132,24 +147,25 @@ jobs: NVIDIA_Plugin: ... ``` -The `Build` job executes the first 4 steps: +The `Build` job executes the first 4 steps: * clones OpenVINO * installs dependencies * builds from source with `cmake` -* packs and uploads the artefacts using `actions/upload-artifact` +* packs and uploads the artifacts using `actions/upload-artifact` -The other jobs are responsible for running different tests using the built artefacts. They: -* download and unpack the artefacts using `actions/download-artifact` +The other jobs are responsible for running different tests using the built artifacts. They: +* download and unpack the artifacts using `actions/download-artifact` * install the needed dependencies * run tests * collect test results -* upload test results as [pipeline artefacts](#artefacts) +* upload test results as [pipeline artifacts](#artifacts) #### Single Job Overview -Each job has several keys that describe its environment. You can find the comprehensive overview of the syntax [here](https://docs.github.com/en/actions/using-workflows/workflow-syntax-for-github-actions). +Each job has several keys that describe its environment. Consider checking a comprehensive +[syntax overview](https://docs.github.com/en/actions/using-workflows/workflow-syntax-for-github-actions). -This section describes the specifics of the OpenVINO CI environment. +This section describes the specifics of the OpenVINO CI environment. Overview of the [Linux workflow's](../../../../.github/workflows/linux.yml) `Python_Unit_Tests` job: ```yaml @@ -174,77 +190,91 @@ Overview of the [Linux workflow's](../../../../.github/workflows/linux.yml) `Pyt steps: ... ``` -* All the test jobs have the `needs: Build` which means that they wait for the `Build` job to finish as they require artefacts from it -* The machine that is used for a job is specified using the `runs-on` key - * In this case `aks-linux-4-cores-16gb` is used. Read more [here](#machines) on what machines are available and how to choose one for a job -* Some jobs could run inside a Docker container. The image could be specified using the `image` key under the `container` key - * In this case `openvinogithubactions.azurecr.io/dockerhub/ubuntu:20.04` is used. Read more [here](#docker-images) on what images are available and when to use one -* Some jobs could benefit from caching, for example, Python dependencies or `cmake` build artefacts - * Read more [here](#caches) on how to utilize cache for a job -* A job must define `steps` - a series of commands that would be executed in the defined above environment - * All the steps are executed in the shell specified by the `shell` key under `defaults: run:` unless a shell is specified directly in a step - -## Finding Results, Artefacts and Logs +* All the test jobs have the `needs: Build` which means that they wait for the `Build` job to + finish as they require artifacts from it. +* The machine that is used for a job is specified using the `runs-on` key. + * In this case `aks-linux-4-cores-16gb` is used. [Read more](#machines) on what machines are + available and how to choose one for a job. +* Some jobs could run inside a Docker container. The image could be specified using the `image` + key under the `container` key. + * In this case, `openvinogithubactions.azurecr.io/dockerhub/ubuntu:20.04` is used. + [Read more](#docker-images) on what images are available and when to use one. +* Some jobs may benefit from caching, for example, Python dependencies or `cmake` build artifacts. + * [Read more](#caches) on how to utilize cache for a job. +* A job must define `steps` - a series of commands to execute in the predefined environment. + * All the steps are executed in the shell specified by the `shell` key under `defaults: run:` + unless a shell is specified directly in a step. + +## Finding Results, Artifacts, and Logs ### Results -To understand which jobs have successfully passed, which are running and which have failed, check the following: -* For Pull Requests: - * Open a Pull Request and navigate to the bottom of the page, you will see the list of jobs that ran or are running for the latest commit: - ![check_results](../../../sphinx_setup/_static/images/ci/check_results.png) -* For scheduled runs: +To understand which jobs have successfully passed, which are running and which have failed, +check the following: + +**For Pull Requests:** + * Open a Pull Request and scroll to the bottom of the page. You will see a list of jobs, + both finished and still running for the most recent commit: + + ![check_results](../../assets/CI_check_results.png) + +**For scheduled runs:** * Navigate to the [OpenVINO Repository Actions](https://github.com/openvinotoolkit/openvino/actions) * Select the required workflow from the list on the left * Filter the runs by clicking on `Event` and selecting `schedule` * You can additionally filter the results per branch, actor and result -### Artefacts +### Artifacts + +Artifacts, that is files produced by the workflow, are available only for the completed pipelines, +both successful or failed. To find artifacts for a pipeline, follow these steps: + +1. Open a Pull Request and scroll to the list of jobs, as described above. +2. Click `Details`, to the right of the selected job, to see more information about it. +3. Click `Summary`, above the list of jobs on the left side of the window: + + ![jobs_list](../../assets/CI_completed_job_list.png) -To find artefacts for a pipeline, use the following steps: -1. Open a Pull Request and navigate to the bottom of the page, you will see the list of jobs that ran or are running for the latest commit: - ![check_results](../../../sphinx_setup/_static/images/ci/check_results.png) -2. Click `Details` to see more information about a job -3. Click `Summary` above the list of the jobs: - ![jobs_list](../../../sphinx_setup/_static/images/ci/completed_job_list.png) 4. Scroll to the bottom of the page -5. You will find the artefacts produced by **all the jobs in this pipeline**: - ![pipeline_artefacts](../../../sphinx_setup/_static/images/ci/pipeline_artefacts.png) -6. Click on the artefact name to download it +5. You will find the artifacts produced by **all the jobs in this pipeline**: + + ![pipeline_artifacts](../../assets/CI_pipeline_artifacts.png) + +6. Click on the artifact name to download it. -**NOTE**: artefacts are available only for the completed, i.e., successful or failed, pipelines. ### Logs To find logs for a pipeline: -1. Open a Pull Request and navigate to the bottom of the page, you will see the list of jobs that ran or are running for the latest commit: - ![check_results](../../../sphinx_setup/_static/images/ci/check_results.png) -2. Click `Details` to see more information about a job +1. Open a Pull Request and scroll to the list of jobs, as described above. +2. Click `Details`, to the right of the selected job, to see more information about it. 3. Click on a step to see its logs ## Custom Actions -Several actions are written specifically for the needs of the OpenVINO workflows. - -Read more about the available custom actions and what they do [here](./custom_actions.md). +Several actions are written specifically for the needs of the OpenVINO workflows. Read more +about the available custom actions and what they do in the [custom actions document](./custom_actions.md). -You can find more information about reusing actions and workflows [here](https://github.com/marketplace?type=actions) and [here](https://docs.github.com/en/actions/using-workflows/reusing-workflows). +Check the [Reusing GitHub Actions](#reusing-github-actions) section for more information. ## Machines The machines that execute the commands from the workflows are called _runners_ in GitHub Actions. - Two types of runners are available for the OpenVINO organization: * [GitHub Actions Runners](https://docs.github.com/en/actions/using-github-hosted-runners/about-github-hosted-runners/about-github-hosted-runners) - runners provided and managed by GitHub -* [Self-hosted Runners](https://docs.github.com/en/actions/hosting-your-own-runners/managing-self-hosted-runners/about-self-hosted-runners) - runners created and managed by the OpenVINO CI team and linked to the OpenVINO repositories +* [Self-hosted Runners](https://docs.github.com/en/actions/hosting-your-own-runners/managing-self-hosted-runners/about-self-hosted-runners) - runners created and managed by the OpenVINO CI team and linked to the OpenVINO repositories -The jobs in the workflows utilize appropriate runners based on a job's needs. Read more about the available runners and how to choose one [here](./runners.md). +Workflows utilize appropriate runners based on their jobs' needs. Learn more about the +available runners and how to choose one in the [OpenVINO Runner Overview](./runners.md). ## Docker Images -You can run jobs in Docker containers, refer to [the documentation for syntax overview](https://docs.github.com/en/actions/using-jobs/running-jobs-in-a-container). +You can run jobs in Docker containers. +Refer to [the documentation for syntax overview](https://docs.github.com/en/actions/using-jobs/running-jobs-in-a-container). -The jobs in the workflows utilize appropriate Docker images based on a job's needs. Read more about the available images and how to choose one [here](./docker_images.md). +Workflows utilize appropriate Docker images based on their jobs' needs. Learn more about the +available images and how to choose one in the [hOpenVINO Docker Image Overview](./docker_images.md). ## Caches @@ -253,16 +283,17 @@ Three types of caches are available: * Shared drive cache * Remote build cache via [Azure Blob Storage](https://azure.microsoft.com/en-us/products/storage/blobs) -The jobs in the workflows utilize appropriate caches based on job's needs. Read more about the available caches and how to use one [here](./caches.md). +workflows utilize appropriate caches based on their jobs' needs. Learn more about the +available caches and how to use one in the [OpenVINO Cache Overview](./caches.md). ## Adding New Tests -If you would like to add new tests, refer to [this document](./adding_tests.md). +If you would like to add new tests, refer to the [How to add Tests](./adding_tests.md) document. -## Optimizing workflow based on PR changes +## Optimizing workflows based on PR changes -To optimize pre-commit workflow by running only those jobs that are actually required to validate changes in a pull -request, you can use Smart CI feature. Refer to [this document](./smart_ci.md) to learn more. +To optimize pre-commit workflow by running only the jobs that are actually required to validate +changes in a pull request, you can use the Smart CI feature - [learn more about it](./smart_ci.md). ## See also diff --git a/docs/dev/installing.md b/docs/dev/installing.md index a85fc68d44fa5d..de4c7ba9df9af6 100644 --- a/docs/dev/installing.md +++ b/docs/dev/installing.md @@ -223,7 +223,7 @@ classid probability

-## Adding OpenVINO Runtime (Inference Engine) to Your Project +## Adding OpenVINO Runtime to Your Project
For versions prior to 2022.1 @@ -256,7 +256,7 @@ For CMake projects, set the `OpenVINO_DIR` and when you run CMake tool: cmake -DOpenVINO_DIR=/runtime/cmake . ``` -Then you can find OpenVINO Runtime (Inference Engine) by [`find_package`]: +Then you can find OpenVINO Runtime by [`find_package`]: ```cmake find_package(OpenVINO REQUIRED) diff --git a/docs/nbdoc/consts.py b/docs/nbdoc/consts.py index 2ad6f691e5ac89..5ab6060fde2b3d 100644 --- a/docs/nbdoc/consts.py +++ b/docs/nbdoc/consts.py @@ -5,7 +5,7 @@ repo_owner = "openvinotoolkit" repo_name = "openvino_notebooks" repo_branch = "tree/main" -artifacts_link = "http://repository.toolbox.iotg.sclab.intel.com/projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/" +artifacts_link = "http://repository.toolbox.iotg.sclab.intel.com/projects/ov-notebook/0.1.0-latest/20240209220807/dist/rst_files/" blacklisted_extensions = ['.xml', '.bin'] notebooks_repo = "https://github.com/openvinotoolkit/openvino_notebooks/blob/main/" notebooks_binder = "https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?filepath=" diff --git a/docs/nbdoc/nbdoc.py b/docs/nbdoc/nbdoc.py index 5261940cbaaa72..42516e497bcc08 100644 --- a/docs/nbdoc/nbdoc.py +++ b/docs/nbdoc/nbdoc.py @@ -68,11 +68,11 @@ def fetch_colab_list(colab_list_file) -> list: def add_glob_directive(): - """This function modifies toctrees of the five node articles in tutorials + """This function modifies toctrees of the five node articles in tutorials section. It adds the notebooks found in docs/notebooks directory to the menu. """ - tutorials_path = Path('../../docs/articles_en/learn_openvino/tutorials').resolve(strict=True) - tutorials_files = [x for x in os.listdir(tutorials_path) if re.match("notebooks_section_[0-9]{1}\.", x)] + tutorials_path = Path('../../docs/articles_en/learn-openvino/interactive-tutorials-python').resolve(strict=True) + tutorials_files = [x for x in os.listdir(tutorials_path) if re.match("notebooks-section-[0-9]{1}.*?\.rst", x)] for tutorials_file in tutorials_files: file_name = os.path.join(tutorials_path, tutorials_file) with open(file_name, 'r+', encoding='cp437') as section_file: diff --git a/docs/notebooks/001-hello-world-with-output.rst b/docs/notebooks/001-hello-world-with-output.rst index e40432d96effe0..e23c8da91e8d4c 100644 --- a/docs/notebooks/001-hello-world-with-output.rst +++ b/docs/notebooks/001-hello-world-with-output.rst @@ -5,7 +5,7 @@ This basic introduction to OpenVINO™ shows how to do inference with an image classification model. A pre-trained `MobileNetV3 -model `__ +model `__ from `Open Model Zoo `__ is used in this tutorial. For more information about how OpenVINO IR models are diff --git a/docs/notebooks/001-hello-world-with-output_files/index.html.tmp b/docs/notebooks/001-hello-world-with-output_files/index.html.tmp deleted file mode 100644 index 0d4edf58fbbb1a..00000000000000 --- a/docs/notebooks/001-hello-world-with-output_files/index.html.tmp +++ /dev/null @@ -1,7 +0,0 @@ - -Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/001-hello-world-with-output_files/ - -

Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/001-hello-world-with-output_files/

../
-001-hello-world-with-output_11_1.png               26-Jan-2024 01:05              387941
-
- diff --git a/docs/notebooks/002-openvino-api-with-output.rst b/docs/notebooks/002-openvino-api-with-output.rst index 2f23557dafd767..0b210715fc4163 100644 --- a/docs/notebooks/002-openvino-api-with-output.rst +++ b/docs/notebooks/002-openvino-api-with-output.rst @@ -61,47 +61,43 @@ Table of contents: .. parsed-literal:: - Requirement already satisfied: requests in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (2.31.0) - Requirement already satisfied: tqdm in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (4.66.1) - Requirement already satisfied: ipywidgets in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (8.1.1) - Requirement already satisfied: charset-normalizer<4,>=2 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from requests) (3.3.2) - 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Requirement already satisfied: pexpect>4.3 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from ipython>=6.1.0->ipywidgets) (4.9.0) - Requirement already satisfied: parso<0.9.0,>=0.8.3 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from jedi>=0.16->ipython>=6.1.0->ipywidgets) (0.8.3) - Requirement already satisfied: ptyprocess>=0.5 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from pexpect>4.3->ipython>=6.1.0->ipywidgets) (0.7.0) - Requirement already satisfied: wcwidth in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from prompt-toolkit!=3.0.37,<3.1.0,>=3.0.30->ipython>=6.1.0->ipywidgets) (0.2.13) - Requirement already satisfied: executing>=1.2.0 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from stack-data->ipython>=6.1.0->ipywidgets) (2.0.1) - Requirement already satisfied: asttokens>=2.1.0 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from stack-data->ipython>=6.1.0->ipywidgets) (2.4.1) - Requirement already satisfied: pure-eval in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from stack-data->ipython>=6.1.0->ipywidgets) (0.2.2) - - -.. parsed-literal:: - - Requirement already satisfied: six>=1.12.0 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from asttokens>=2.1.0->stack-data->ipython>=6.1.0->ipywidgets) (1.16.0) + Requirement already satisfied: parso<0.9.0,>=0.8.3 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from jedi>=0.16->ipython>=6.1.0->ipywidgets) (0.8.3) + Requirement already satisfied: ptyprocess>=0.5 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from pexpect>4.3->ipython>=6.1.0->ipywidgets) (0.7.0) + Requirement already satisfied: wcwidth in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from prompt-toolkit!=3.0.37,<3.1.0,>=3.0.30->ipython>=6.1.0->ipywidgets) (0.2.13) + Requirement already satisfied: executing>=1.2.0 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from stack-data->ipython>=6.1.0->ipywidgets) (2.0.1) + Requirement already satisfied: asttokens>=2.1.0 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from stack-data->ipython>=6.1.0->ipywidgets) (2.4.1) + Requirement already satisfied: pure-eval in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from stack-data->ipython>=6.1.0->ipywidgets) (0.2.2) + Requirement already satisfied: six>=1.12.0 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from asttokens>=2.1.0->stack-data->ipython>=6.1.0->ipywidgets) (1.16.0) .. parsed-literal:: @@ -218,7 +214,7 @@ notebooks. .. parsed-literal:: - PosixPath('/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/002-openvino-api/model/classification.bin') + PosixPath('/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/notebooks/002-openvino-api/model/classification.bin') @@ -267,7 +263,7 @@ points to the filename of an ONNX model. .. parsed-literal:: - PosixPath('/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/002-openvino-api/model/segmentation.onnx') + PosixPath('/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/notebooks/002-openvino-api/model/segmentation.onnx') @@ -323,7 +319,7 @@ without any conversion step. Pass the filename with extension to .. parsed-literal:: - PosixPath('/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/002-openvino-api/model/inference.pdiparams') + PosixPath('/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/notebooks/002-openvino-api/model/inference.pdiparams') @@ -367,7 +363,7 @@ TensorFlow models saved in frozen graph format can also be passed to .. parsed-literal:: - PosixPath('/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/002-openvino-api/model/classification.pb') + PosixPath('/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/notebooks/002-openvino-api/model/classification.pb') @@ -419,7 +415,7 @@ It is pre-trained model optimized to work with TensorFlow Lite. .. parsed-literal:: - PosixPath('/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/002-openvino-api/model/classification.tflite') + PosixPath('/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/notebooks/002-openvino-api/model/classification.tflite') @@ -504,7 +500,7 @@ Information about the inputs and outputs of the model are in .. parsed-literal:: - PosixPath('/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/002-openvino-api/model/classification.bin') + PosixPath('/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/notebooks/002-openvino-api/model/classification.bin') @@ -714,7 +710,7 @@ produced data as values. .. parsed-literal:: - PosixPath('/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/002-openvino-api/model/classification.bin') + PosixPath('/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/notebooks/002-openvino-api/model/classification.bin') @@ -903,7 +899,7 @@ input shape. .. parsed-literal:: - PosixPath('/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/002-openvino-api/model/segmentation.bin') + PosixPath('/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/notebooks/002-openvino-api/model/segmentation.bin') @@ -1066,7 +1062,7 @@ the cache. .. parsed-literal:: - PosixPath('/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/002-openvino-api/model/classification.bin') + PosixPath('/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/notebooks/002-openvino-api/model/classification.bin') diff --git a/docs/notebooks/003-hello-segmentation-with-output.rst b/docs/notebooks/003-hello-segmentation-with-output.rst index 7894b3a3f6283d..cc95396e99ea4a 100644 --- a/docs/notebooks/003-hello-segmentation-with-output.rst +++ b/docs/notebooks/003-hello-segmentation-with-output.rst @@ -4,7 +4,7 @@ Hello Image Segmentation A very basic introduction to using segmentation models with OpenVINO™. In this tutorial, a pre-trained -`road-segmentation-adas-0001 `__ +`road-segmentation-adas-0001 `__ model from the `Open Model Zoo `__ is used. ADAS stands for Advanced Driver Assistance Services. The model @@ -182,7 +182,7 @@ is provided. .. parsed-literal:: - + @@ -209,7 +209,7 @@ Do Inference .. parsed-literal:: - + diff --git a/docs/notebooks/003-hello-segmentation-with-output_files/index.html.tmp b/docs/notebooks/003-hello-segmentation-with-output_files/index.html.tmp deleted file mode 100644 index 27eec1da5060e2..00000000000000 --- a/docs/notebooks/003-hello-segmentation-with-output_files/index.html.tmp +++ /dev/null @@ -1,9 +0,0 @@ - -Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/003-hello-segmentation-with-output_files/ - -

Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/003-hello-segmentation-with-output_files/

../
-003-hello-segmentation-with-output_11_2.png        26-Jan-2024 01:05              249032
-003-hello-segmentation-with-output_13_1.png        26-Jan-2024 01:05               20550
-003-hello-segmentation-with-output_17_0.png        26-Jan-2024 01:05              260045
-
- diff --git a/docs/notebooks/004-hello-detection-with-output.rst b/docs/notebooks/004-hello-detection-with-output.rst index d81ca1ee742849..054333cbaf5b4d 100644 --- a/docs/notebooks/004-hello-detection-with-output.rst +++ b/docs/notebooks/004-hello-detection-with-output.rst @@ -5,7 +5,7 @@ A very basic introduction to using object detection models with OpenVINO™. The -`horizontal-text-detection-0001 `__ +`horizontal-text-detection-0001 `__ model from `Open Model Zoo `__ is used. It detects horizontal text in images and returns a blob of data in the diff --git a/docs/notebooks/004-hello-detection-with-output_files/index.html.tmp b/docs/notebooks/004-hello-detection-with-output_files/index.html.tmp deleted file mode 100644 index cd39adc5cafa08..00000000000000 --- a/docs/notebooks/004-hello-detection-with-output_files/index.html.tmp +++ /dev/null @@ -1,8 +0,0 @@ - -Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/004-hello-detection-with-output_files/ - -

Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/004-hello-detection-with-output_files/

../
-004-hello-detection-with-output_11_1.png           26-Jan-2024 01:05              305482
-004-hello-detection-with-output_16_0.png           26-Jan-2024 01:05              457214
-
- diff --git a/docs/notebooks/101-tensorflow-classification-to-openvino-with-output.rst b/docs/notebooks/101-tensorflow-classification-to-openvino-with-output.rst index 97e849bdb5b2d2..82a4441bbdd578 100644 --- a/docs/notebooks/101-tensorflow-classification-to-openvino-with-output.rst +++ b/docs/notebooks/101-tensorflow-classification-to-openvino-with-output.rst @@ -2,7 +2,7 @@ Convert a TensorFlow Model to OpenVINO™ ======================================= This short tutorial shows how to convert a TensorFlow -`MobileNetV3 `__ +`MobileNetV3 `__ image classification model to OpenVINO `Intermediate Representation `__ (OpenVINO IR) format, using `Model Conversion @@ -75,14 +75,14 @@ Imports .. parsed-literal:: - 2024-01-25 22:33:56.723840: I tensorflow/core/util/port.cc:110] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`. - 2024-01-25 22:33:56.757735: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations. + 2024-02-09 22:34:07.759850: I tensorflow/core/util/port.cc:110] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`. + 2024-02-09 22:34:07.794264: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations. To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags. .. parsed-literal:: - 2024-01-25 22:33:57.273134: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT + 2024-02-09 22:34:08.310440: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT Settings @@ -122,12 +122,12 @@ and save it to the disk. .. parsed-literal:: - 2024-01-25 22:34:00.136277: E tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:266] failed call to cuInit: CUDA_ERROR_COMPAT_NOT_SUPPORTED_ON_DEVICE: forward compatibility was attempted on non supported HW - 2024-01-25 22:34:00.136313: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:168] retrieving CUDA diagnostic information for host: iotg-dev-workstation-07 - 2024-01-25 22:34:00.136317: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:175] hostname: iotg-dev-workstation-07 - 2024-01-25 22:34:00.136451: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:199] libcuda reported version is: 470.223.2 - 2024-01-25 22:34:00.136466: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:203] kernel reported version is: 470.182.3 - 2024-01-25 22:34:00.136470: E tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:312] kernel version 470.182.3 does not match DSO version 470.223.2 -- cannot find working devices in this configuration + 2024-02-09 22:34:11.190073: E tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:266] failed call to cuInit: CUDA_ERROR_COMPAT_NOT_SUPPORTED_ON_DEVICE: forward compatibility was attempted on non supported HW + 2024-02-09 22:34:11.190106: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:168] retrieving CUDA diagnostic information for host: iotg-dev-workstation-07 + 2024-02-09 22:34:11.190111: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:175] hostname: iotg-dev-workstation-07 + 2024-02-09 22:34:11.190249: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:199] libcuda reported version is: 470.223.2 + 2024-02-09 22:34:11.190264: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:203] kernel reported version is: 470.182.3 + 2024-02-09 22:34:11.190268: E tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:312] kernel version 470.182.3 does not match DSO version 470.223.2 -- cannot find working devices in this configuration .. parsed-literal:: @@ -137,13 +137,13 @@ and save it to the disk. .. parsed-literal:: - 2024-01-25 22:34:04.279915: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'inputs' with dtype float and shape [?,1,1,1024] + 2024-02-09 22:34:15.411337: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'inputs' with dtype float and shape [?,1,1,1024] [[{{node inputs}}]] .. parsed-literal:: - 2024-01-25 22:34:07.400979: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'inputs' with dtype float and shape [?,1,1,1024] + 2024-02-09 22:34:18.568762: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'inputs' with dtype float and shape [?,1,1,1024] [[{{node inputs}}]] WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op while saving (showing 5 of 54). These functions will not be directly callable after loading. @@ -362,5 +362,5 @@ performance. .. parsed-literal:: - IR model in OpenVINO Runtime/CPU: 0.0011 seconds per image, FPS: 933.95 + IR model in OpenVINO Runtime/CPU: 0.0011 seconds per image, FPS: 926.34 diff --git a/docs/notebooks/101-tensorflow-classification-to-openvino-with-output_files/index.html.tmp b/docs/notebooks/101-tensorflow-classification-to-openvino-with-output_files/index.html.tmp deleted file mode 100644 index fec1f1be4eb8d0..00000000000000 --- a/docs/notebooks/101-tensorflow-classification-to-openvino-with-output_files/index.html.tmp +++ /dev/null @@ -1,7 +0,0 @@ - -Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/101-tensorflow-classification-to-openvino-with-output_files/ - -

Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/101-tensorflow-classification-to-openvino-with-output_files/

../
-101-tensorflow-classification-to-openvino-with-..> 26-Jan-2024 01:05              387941
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- diff --git a/docs/notebooks/102-pytorch-onnx-to-openvino-with-output.rst b/docs/notebooks/102-pytorch-onnx-to-openvino-with-output.rst index 96fa90f154514e..6b5c1d5c9c2185 100644 --- a/docs/notebooks/102-pytorch-onnx-to-openvino-with-output.rst +++ b/docs/notebooks/102-pytorch-onnx-to-openvino-with-output.rst @@ -576,17 +576,17 @@ performance. .. parsed-literal:: - PyTorch model on CPU: 0.042 seconds per image, FPS: 24.02 + PyTorch model on CPU: 0.040 seconds per image, FPS: 24.69 .. parsed-literal:: - ONNX model in OpenVINO Runtime/CPU: 0.030 seconds per image, FPS: 33.66 + ONNX model in OpenVINO Runtime/CPU: 0.018 seconds per image, FPS: 56.48 .. parsed-literal:: - OpenVINO IR model in OpenVINO Runtime/CPU: 0.029 seconds per image, FPS: 35.01 + OpenVINO IR model in OpenVINO Runtime/CPU: 0.018 seconds per image, FPS: 55.11 **Show Device Information** diff --git a/docs/notebooks/102-pytorch-onnx-to-openvino-with-output_files/index.html.tmp b/docs/notebooks/102-pytorch-onnx-to-openvino-with-output_files/index.html.tmp deleted file mode 100644 index 9ac41953398664..00000000000000 --- a/docs/notebooks/102-pytorch-onnx-to-openvino-with-output_files/index.html.tmp +++ /dev/null @@ -1,9 +0,0 @@ - -Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/102-pytorch-onnx-to-openvino-with-output_files/ - -

Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/102-pytorch-onnx-to-openvino-with-output_files/

../
-102-pytorch-onnx-to-openvino-with-output_22_0.png  26-Jan-2024 01:05              465692
-102-pytorch-onnx-to-openvino-with-output_27_0.png  26-Jan-2024 01:05              465695
-102-pytorch-onnx-to-openvino-with-output_29_0.png  26-Jan-2024 01:05              465692
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- diff --git a/docs/notebooks/102-pytorch-to-openvino-with-output.rst b/docs/notebooks/102-pytorch-to-openvino-with-output.rst index 25a97931195713..e2ed8dfafba126 100644 --- a/docs/notebooks/102-pytorch-to-openvino-with-output.rst +++ b/docs/notebooks/102-pytorch-to-openvino-with-output.rst @@ -248,7 +248,7 @@ Benchmark PyTorch Model Inference .. parsed-literal:: - 16.4 ms ± 673 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) + 17.6 ms ± 52.8 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) Convert PyTorch Model to OpenVINO Intermediate Representation @@ -407,7 +407,7 @@ Benchmark OpenVINO Model Inference .. parsed-literal:: - 3.31 ms ± 28.8 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) + 3.42 ms ± 7.33 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) Convert PyTorch Model with Static Input Shape @@ -537,7 +537,7 @@ Benchmark OpenVINO Model Inference with Static Input Shape .. parsed-literal:: - 2.89 ms ± 38.3 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) + 2.9 ms ± 17.7 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) Convert TorchScript Model to OpenVINO Intermediate Representation @@ -632,7 +632,7 @@ Benchmark Scripted Model Inference .. parsed-literal:: - 12.8 ms ± 6.97 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) + 13 ms ± 50.6 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) Convert PyTorch Scripted Model to OpenVINO Intermediate Representation @@ -691,7 +691,7 @@ Benchmark OpenVINO Model Inference Converted From Scripted Model .. parsed-literal:: - 3.41 ms ± 6.84 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) + 3.42 ms ± 6.53 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) Traced Model @@ -767,7 +767,7 @@ Benchmark Traced Model Inference .. parsed-literal:: - 12.2 ms ± 29 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) + 13.4 ms ± 4.67 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) Convert PyTorch Traced Model to OpenVINO Intermediate Representation @@ -826,5 +826,5 @@ Benchmark OpenVINO Model Inference Converted From Traced Model .. parsed-literal:: - 3.4 ms ± 3.43 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) + 3.47 ms ± 10.3 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) diff --git a/docs/notebooks/102-pytorch-to-openvino-with-output_files/index.html.tmp b/docs/notebooks/102-pytorch-to-openvino-with-output_files/index.html.tmp deleted file mode 100644 index 5e046f8bcd6f85..00000000000000 --- a/docs/notebooks/102-pytorch-to-openvino-with-output_files/index.html.tmp +++ /dev/null @@ -1,20 +0,0 @@ - -Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/102-pytorch-to-openvino-with-output_files/ - -

Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/102-pytorch-to-openvino-with-output_files/

../
-102-pytorch-to-openvino-with-output_11_0.jpg       26-Jan-2024 01:05               54874
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- diff --git a/docs/notebooks/103-paddle-to-openvino-classification-with-output.rst b/docs/notebooks/103-paddle-to-openvino-classification-with-output.rst index 7934c4005913f0..c70e3b2917571a 100644 --- a/docs/notebooks/103-paddle-to-openvino-classification-with-output.rst +++ b/docs/notebooks/103-paddle-to-openvino-classification-with-output.rst @@ -94,7 +94,7 @@ Imports .. parsed-literal:: - --2024-01-25 22:35:57-- http://nz2.archive.ubuntu.com/ubuntu/pool/main/o/openssl/libssl1.1_1.1.1f-1ubuntu2.19_amd64.deb + --2024-02-09 22:36:08-- http://nz2.archive.ubuntu.com/ubuntu/pool/main/o/openssl/libssl1.1_1.1.1f-1ubuntu2.19_amd64.deb Resolving proxy-mu.intel.com (proxy-mu.intel.com)... 10.217.247.236 Connecting to proxy-mu.intel.com (proxy-mu.intel.com)|10.217.247.236|:911... connected. Proxy request sent, awaiting response... @@ -102,7 +102,7 @@ Imports .. parsed-literal:: 404 Not Found - 2024-01-25 22:35:57 ERROR 404: Not Found. + 2024-02-09 22:36:08 ERROR 404: Not Found. @@ -135,12 +135,12 @@ Imports .. parsed-literal:: - 2024-01-25 22:35:59 INFO: Loading faiss with AVX2 support. + 2024-02-09 22:36:10 INFO: Loading faiss with AVX2 support. .. parsed-literal:: - 2024-01-25 22:35:59 INFO: Successfully loaded faiss with AVX2 support. + 2024-02-09 22:36:10 INFO: Successfully loaded faiss with AVX2 support. Settings @@ -224,7 +224,7 @@ inference on that image, and then show the top three prediction results. .. parsed-literal:: - [2024/01/25 22:36:20] ppcls WARNING: The current running environment does not support the use of GPU. CPU has been used instead. + [2024/02/09 22:36:38] ppcls WARNING: The current running environment does not support the use of GPU. CPU has been used instead. .. parsed-literal:: @@ -294,7 +294,7 @@ clipping values. .. parsed-literal:: - 2024-01-25 22:36:20 WARNING: Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers). + 2024-02-09 22:36:39 WARNING: Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers). .. parsed-literal:: @@ -306,7 +306,7 @@ clipping values. .. parsed-literal:: - + @@ -489,7 +489,7 @@ Note that many optimizations are possible to improve the performance. .. parsed-literal:: - PaddlePaddle model on CPU: 0.0073 seconds per image, FPS: 137.36 + PaddlePaddle model on CPU: 0.0075 seconds per image, FPS: 133.16 PaddlePaddle result: Labrador retriever, 0.75138 @@ -553,7 +553,7 @@ select device from dropdown list for running inference using OpenVINO .. parsed-literal:: - OpenVINO IR model in OpenVINO Runtime (AUTO): 0.0031 seconds per image, FPS: 322.19 + OpenVINO IR model in OpenVINO Runtime (AUTO): 0.0030 seconds per image, FPS: 328.87 OpenVINO result: Labrador retriever, 0.74909 diff --git a/docs/notebooks/103-paddle-to-openvino-classification-with-output_files/index.html.tmp b/docs/notebooks/103-paddle-to-openvino-classification-with-output_files/index.html.tmp deleted file mode 100644 index 6165476573d22f..00000000000000 --- a/docs/notebooks/103-paddle-to-openvino-classification-with-output_files/index.html.tmp +++ /dev/null @@ -1,11 +0,0 @@ - -Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/103-paddle-to-openvino-classification-with-output_files/ - -

Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/103-paddle-to-openvino-classification-with-output_files/

../
-103-paddle-to-openvino-classification-with-outp..> 26-Jan-2024 01:05              120883
-103-paddle-to-openvino-classification-with-outp..> 26-Jan-2024 01:05              224886
-103-paddle-to-openvino-classification-with-outp..> 26-Jan-2024 01:05              224886
-103-paddle-to-openvino-classification-with-outp..> 26-Jan-2024 01:05              224886
-103-paddle-to-openvino-classification-with-outp..> 26-Jan-2024 01:05              224886
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- diff --git a/docs/notebooks/104-model-tools-with-output.rst b/docs/notebooks/104-model-tools-with-output.rst index e3befdb25707bf..46686ff41b1973 100644 --- a/docs/notebooks/104-model-tools-with-output.rst +++ b/docs/notebooks/104-model-tools-with-output.rst @@ -188,650 +188,662 @@ Downloading mobilenet-v2-pytorch… .. parsed-literal:: - ... 0%, 32 KB, 1358 KB/s, 0 seconds passed + ... 0%, 32 KB, 1147 KB/s, 0 seconds passed +... 0%, 64 KB, 1047 KB/s, 0 seconds passed .. parsed-literal:: - ... 0%, 64 KB, 1162 KB/s, 0 seconds passed -... 0%, 96 KB, 1715 KB/s, 0 seconds passed -... 0%, 128 KB, 1454 KB/s, 0 seconds passed -... 1%, 160 KB, 1683 KB/s, 0 seconds passed + ... 0%, 96 KB, 1108 KB/s, 0 seconds passed +... 0%, 128 KB, 1467 KB/s, 0 seconds passed +... 1%, 160 KB, 1676 KB/s, 0 seconds passed +... 1%, 192 KB, 1999 KB/s, 0 seconds passed +... 1%, 224 KB, 1847 KB/s, 0 seconds passed +... 1%, 256 KB, 2102 KB/s, 0 seconds passed .. parsed-literal:: - ... 1%, 192 KB, 1604 KB/s, 0 seconds passed -... 1%, 224 KB, 1859 KB/s, 0 seconds passed -... 1%, 256 KB, 2119 KB/s, 0 seconds passed -... 2%, 288 KB, 2263 KB/s, 0 seconds passed + ... 2%, 288 KB, 2214 KB/s, 0 seconds passed +... 2%, 320 KB, 2445 KB/s, 0 seconds passed +... 2%, 352 KB, 2259 KB/s, 0 seconds passed +... 2%, 384 KB, 2457 KB/s, 0 seconds passed +... 2%, 416 KB, 2526 KB/s, 0 seconds passed +... 3%, 448 KB, 2712 KB/s, 0 seconds passed .. parsed-literal:: - 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... 28%, 4000 KB, 3684 KB/s, 1 seconds passed -... 29%, 4032 KB, 3684 KB/s, 1 seconds passed -... 29%, 4064 KB, 3710 KB/s, 1 seconds passed -... 29%, 4096 KB, 3737 KB/s, 1 seconds passed -... 29%, 4128 KB, 3690 KB/s, 1 seconds passed + ... 28%, 3904 KB, 3481 KB/s, 1 seconds passed +... 28%, 3936 KB, 3502 KB/s, 1 seconds passed +... 28%, 3968 KB, 3525 KB/s, 1 seconds passed +... 28%, 4000 KB, 3527 KB/s, 1 seconds passed .. parsed-literal:: - ... 29%, 4160 KB, 3691 KB/s, 1 seconds passed -... 30%, 4192 KB, 3718 KB/s, 1 seconds passed -... 30%, 4224 KB, 3743 KB/s, 1 seconds passed -... 30%, 4256 KB, 3703 KB/s, 1 seconds passed -... 30%, 4288 KB, 3699 KB/s, 1 seconds passed -... 31%, 4320 KB, 3724 KB/s, 1 seconds passed -... 31%, 4352 KB, 3748 KB/s, 1 seconds passed + ... 29%, 4032 KB, 3491 KB/s, 1 seconds passed +... 29%, 4064 KB, 3508 KB/s, 1 seconds passed +... 29%, 4096 KB, 3531 KB/s, 1 seconds passed +... 29%, 4128 KB, 3532 KB/s, 1 seconds passed +... 29%, 4160 KB, 3497 KB/s, 1 seconds passed +... 30%, 4192 KB, 3515 KB/s, 1 seconds passed +... 30%, 4224 KB, 3536 KB/s, 1 seconds passed +... 30%, 4256 KB, 3537 KB/s, 1 seconds passed .. parsed-literal:: - ... 31%, 4384 KB, 3687 KB/s, 1 seconds passed -... 31%, 4416 KB, 3687 KB/s, 1 seconds passed -... 32%, 4448 KB, 3712 KB/s, 1 seconds passed -... 32%, 4480 KB, 3738 KB/s, 1 seconds passed -... 32%, 4512 KB, 3694 KB/s, 1 seconds passed + ... 30%, 4288 KB, 3498 KB/s, 1 seconds passed +... 31%, 4320 KB, 3515 KB/s, 1 seconds passed +... 31%, 4352 KB, 3529 KB/s, 1 seconds passed +... 31%, 4384 KB, 3539 KB/s, 1 seconds passed .. parsed-literal:: - ... 32%, 4544 KB, 3693 KB/s, 1 seconds passed -... 32%, 4576 KB, 3718 KB/s, 1 seconds passed -... 33%, 4608 KB, 3743 KB/s, 1 seconds passed -... 33%, 4640 KB, 3702 KB/s, 1 seconds passed -... 33%, 4672 KB, 3700 KB/s, 1 seconds passed -... 33%, 4704 KB, 3723 KB/s, 1 seconds passed -... 34%, 4736 KB, 3747 KB/s, 1 seconds passed + ... 31%, 4416 KB, 3505 KB/s, 1 seconds passed +... 32%, 4448 KB, 3522 KB/s, 1 seconds passed +... 32%, 4480 KB, 3535 KB/s, 1 seconds passed +... 32%, 4512 KB, 3544 KB/s, 1 seconds passed +... 32%, 4544 KB, 3511 KB/s, 1 seconds passed +... 32%, 4576 KB, 3527 KB/s, 1 seconds passed +... 33%, 4608 KB, 3549 KB/s, 1 seconds passed +... 33%, 4640 KB, 3548 KB/s, 1 seconds passed .. parsed-literal:: - ... 34%, 4768 KB, 3723 KB/s, 1 seconds passed -... 34%, 4800 KB, 3704 KB/s, 1 seconds passed -... 34%, 4832 KB, 3727 KB/s, 1 seconds passed -... 35%, 4864 KB, 3751 KB/s, 1 seconds passed -... 35%, 4896 KB, 3711 KB/s, 1 seconds passed + ... 33%, 4672 KB, 3517 KB/s, 1 seconds passed +... 33%, 4704 KB, 3533 KB/s, 1 seconds passed +... 34%, 4736 KB, 3545 KB/s, 1 seconds passed +... 34%, 4768 KB, 3553 KB/s, 1 seconds passed .. parsed-literal:: - ... 35%, 4928 KB, 3710 KB/s, 1 seconds passed -... 35%, 4960 KB, 3732 KB/s, 1 seconds passed -... 35%, 4992 KB, 3755 KB/s, 1 seconds passed -... 36%, 5024 KB, 3716 KB/s, 1 seconds passed -... 36%, 5056 KB, 3716 KB/s, 1 seconds passed -... 36%, 5088 KB, 3738 KB/s, 1 seconds passed -... 36%, 5120 KB, 3760 KB/s, 1 seconds passed + ... 34%, 4800 KB, 3522 KB/s, 1 seconds passed +... 34%, 4832 KB, 3537 KB/s, 1 seconds passed +... 35%, 4864 KB, 3550 KB/s, 1 seconds passed +... 35%, 4896 KB, 3557 KB/s, 1 seconds passed +... 35%, 4928 KB, 3525 KB/s, 1 seconds passed +... 35%, 4960 KB, 3539 KB/s, 1 seconds passed +... 35%, 4992 KB, 3553 KB/s, 1 seconds passed +... 36%, 5024 KB, 3561 KB/s, 1 seconds passed .. parsed-literal:: - ... 37%, 5152 KB, 3721 KB/s, 1 seconds passed -... 37%, 5184 KB, 3722 KB/s, 1 seconds passed -... 37%, 5216 KB, 3742 KB/s, 1 seconds passed -... 37%, 5248 KB, 3764 KB/s, 1 seconds passed -... 38%, 5280 KB, 3726 KB/s, 1 seconds passed -... 38%, 5312 KB, 3726 KB/s, 1 seconds passed -... 38%, 5344 KB, 3746 KB/s, 1 seconds passed + ... 36%, 5056 KB, 3532 KB/s, 1 seconds passed +... 36%, 5088 KB, 3546 KB/s, 1 seconds passed +... 36%, 5120 KB, 3558 KB/s, 1 seconds passed +... 37%, 5152 KB, 3564 KB/s, 1 seconds passed .. parsed-literal:: - ... 38%, 5376 KB, 3727 KB/s, 1 seconds passed -... 38%, 5408 KB, 3729 KB/s, 1 seconds passed -... 39%, 5440 KB, 3731 KB/s, 1 seconds passed -... 39%, 5472 KB, 3751 KB/s, 1 seconds passed -... 39%, 5504 KB, 3731 KB/s, 1 seconds passed + ... 37%, 5184 KB, 3534 KB/s, 1 seconds passed +... 37%, 5216 KB, 3546 KB/s, 1 seconds passed +... 37%, 5248 KB, 3559 KB/s, 1 seconds passed +... 38%, 5280 KB, 3566 KB/s, 1 seconds passed +... 38%, 5312 KB, 3536 KB/s, 1 seconds passed +... 38%, 5344 KB, 3549 KB/s, 1 seconds passed +... 38%, 5376 KB, 3563 KB/s, 1 seconds passed .. parsed-literal:: - ... 39%, 5536 KB, 3734 KB/s, 1 seconds passed -... 40%, 5568 KB, 3735 KB/s, 1 seconds passed -... 40%, 5600 KB, 3754 KB/s, 1 seconds passed -... 40%, 5632 KB, 3735 KB/s, 1 seconds passed -... 40%, 5664 KB, 3738 KB/s, 1 seconds passed -... 41%, 5696 KB, 3740 KB/s, 1 seconds passed -... 41%, 5728 KB, 3758 KB/s, 1 seconds passed + ... 38%, 5408 KB, 3570 KB/s, 1 seconds passed +... 39%, 5440 KB, 3540 KB/s, 1 seconds passed +... 39%, 5472 KB, 3554 KB/s, 1 seconds passed +... 39%, 5504 KB, 3565 KB/s, 1 seconds passed +... 39%, 5536 KB, 3573 KB/s, 1 seconds passed .. parsed-literal:: - ... 41%, 5760 KB, 3739 KB/s, 1 seconds passed -... 41%, 5792 KB, 3745 KB/s, 1 seconds passed -... 41%, 5824 KB, 3745 KB/s, 1 seconds passed -... 42%, 5856 KB, 3763 KB/s, 1 seconds passed -... 42%, 5888 KB, 3781 KB/s, 1 seconds passed -... 42%, 5920 KB, 3749 KB/s, 1 seconds passed + ... 40%, 5568 KB, 3543 KB/s, 1 seconds passed +... 40%, 5600 KB, 3557 KB/s, 1 seconds passed +... 40%, 5632 KB, 3567 KB/s, 1 seconds passed +... 40%, 5664 KB, 3575 KB/s, 1 seconds passed +... 41%, 5696 KB, 3545 KB/s, 1 seconds passed +... 41%, 5728 KB, 3560 KB/s, 1 seconds passed +... 41%, 5760 KB, 3570 KB/s, 1 seconds passed .. parsed-literal:: - ... 42%, 5952 KB, 3748 KB/s, 1 seconds passed -... 43%, 5984 KB, 3767 KB/s, 1 seconds passed -... 43%, 6016 KB, 3784 KB/s, 1 seconds passed -... 43%, 6048 KB, 3754 KB/s, 1 seconds passed -... 43%, 6080 KB, 3754 KB/s, 1 seconds passed -... 44%, 6112 KB, 3770 KB/s, 1 seconds passed -... 44%, 6144 KB, 3787 KB/s, 1 seconds passed + ... 41%, 5792 KB, 3577 KB/s, 1 seconds passed +... 41%, 5824 KB, 3548 KB/s, 1 seconds passed +... 42%, 5856 KB, 3561 KB/s, 1 seconds passed +... 42%, 5888 KB, 3572 KB/s, 1 seconds passed +... 42%, 5920 KB, 3579 KB/s, 1 seconds passed .. parsed-literal:: - ... 44%, 6176 KB, 3757 KB/s, 1 seconds passed -... 44%, 6208 KB, 3755 KB/s, 1 seconds passed -... 44%, 6240 KB, 3772 KB/s, 1 seconds passed -... 45%, 6272 KB, 3756 KB/s, 1 seconds passed -... 45%, 6304 KB, 3758 KB/s, 1 seconds passed -... 45%, 6336 KB, 3758 KB/s, 1 seconds passed -... 45%, 6368 KB, 3776 KB/s, 1 seconds passed + ... 42%, 5952 KB, 3551 KB/s, 1 seconds passed +... 43%, 5984 KB, 3564 KB/s, 1 seconds passed +... 43%, 6016 KB, 3574 KB/s, 1 seconds passed +... 43%, 6048 KB, 3582 KB/s, 1 seconds passed +... 43%, 6080 KB, 3555 KB/s, 1 seconds passed +... 44%, 6112 KB, 3568 KB/s, 1 seconds passed +... 44%, 6144 KB, 3577 KB/s, 1 seconds passed .. parsed-literal:: - ... 46%, 6400 KB, 3759 KB/s, 1 seconds passed -... 46%, 6432 KB, 3761 KB/s, 1 seconds passed -... 46%, 6464 KB, 3762 KB/s, 1 seconds passed -... 46%, 6496 KB, 3779 KB/s, 1 seconds passed -... 47%, 6528 KB, 3762 KB/s, 1 seconds passed + ... 44%, 6176 KB, 3585 KB/s, 1 seconds passed +... 44%, 6208 KB, 3558 KB/s, 1 seconds passed +... 44%, 6240 KB, 3570 KB/s, 1 seconds passed +... 45%, 6272 KB, 3580 KB/s, 1 seconds passed +... 45%, 6304 KB, 3587 KB/s, 1 seconds passed .. parsed-literal:: - ... 47%, 6560 KB, 3764 KB/s, 1 seconds passed -... 47%, 6592 KB, 3764 KB/s, 1 seconds passed -... 47%, 6624 KB, 3781 KB/s, 1 seconds passed -... 47%, 6656 KB, 3766 KB/s, 1 seconds passed -... 48%, 6688 KB, 3766 KB/s, 1 seconds passed -... 48%, 6720 KB, 3768 KB/s, 1 seconds passed -... 48%, 6752 KB, 3784 KB/s, 1 seconds passed + ... 45%, 6336 KB, 3561 KB/s, 1 seconds passed +... 45%, 6368 KB, 3574 KB/s, 1 seconds passed +... 46%, 6400 KB, 3582 KB/s, 1 seconds passed +... 46%, 6432 KB, 3589 KB/s, 1 seconds passed +... 46%, 6464 KB, 3562 KB/s, 1 seconds passed +... 46%, 6496 KB, 3575 KB/s, 1 seconds passed +... 47%, 6528 KB, 3585 KB/s, 1 seconds passed .. parsed-literal:: - ... 48%, 6784 KB, 3767 KB/s, 1 seconds passed -... 49%, 6816 KB, 3769 KB/s, 1 seconds passed -... 49%, 6848 KB, 3771 KB/s, 1 seconds passed -... 49%, 6880 KB, 3787 KB/s, 1 seconds passed -... 49%, 6912 KB, 3771 KB/s, 1 seconds passed + ... 47%, 6560 KB, 3593 KB/s, 1 seconds passed +... 47%, 6592 KB, 3567 KB/s, 1 seconds passed +... 47%, 6624 KB, 3579 KB/s, 1 seconds passed +... 47%, 6656 KB, 3588 KB/s, 1 seconds passed +... 48%, 6688 KB, 3593 KB/s, 1 seconds passed .. parsed-literal:: - ... 50%, 6944 KB, 3771 KB/s, 1 seconds passed -... 50%, 6976 KB, 3773 KB/s, 1 seconds passed -... 50%, 7008 KB, 3789 KB/s, 1 seconds passed -... 50%, 7040 KB, 3773 KB/s, 1 seconds passed -... 50%, 7072 KB, 3774 KB/s, 1 seconds passed -... 51%, 7104 KB, 3779 KB/s, 1 seconds passed -... 51%, 7136 KB, 3792 KB/s, 1 seconds passed + ... 48%, 6720 KB, 3567 KB/s, 1 seconds passed +... 48%, 6752 KB, 3581 KB/s, 1 seconds passed +... 48%, 6784 KB, 3590 KB/s, 1 seconds passed +... 49%, 6816 KB, 3597 KB/s, 1 seconds passed +... 49%, 6848 KB, 3572 KB/s, 1 seconds passed +... 49%, 6880 KB, 3583 KB/s, 1 seconds passed +... 49%, 6912 KB, 3592 KB/s, 1 seconds passed .. parsed-literal:: - ... 51%, 7168 KB, 3779 KB/s, 1 seconds passed -... 51%, 7200 KB, 3781 KB/s, 1 seconds passed -... 52%, 7232 KB, 3781 KB/s, 1 seconds passed -... 52%, 7264 KB, 3794 KB/s, 1 seconds passed -... 52%, 7296 KB, 3782 KB/s, 1 seconds passed -... 52%, 7328 KB, 3785 KB/s, 1 seconds passed + ... 50%, 6944 KB, 3599 KB/s, 1 seconds passed +... 50%, 6976 KB, 3574 KB/s, 1 seconds passed +... 50%, 7008 KB, 3585 KB/s, 1 seconds passed +... 50%, 7040 KB, 3593 KB/s, 1 seconds passed +... 50%, 7072 KB, 3600 KB/s, 1 seconds passed .. parsed-literal:: - ... 53%, 7360 KB, 3784 KB/s, 1 seconds passed -... 53%, 7392 KB, 3797 KB/s, 1 seconds passed -... 53%, 7424 KB, 3785 KB/s, 1 seconds passed -... 53%, 7456 KB, 3787 KB/s, 1 seconds passed -... 53%, 7488 KB, 3784 KB/s, 1 seconds passed -... 54%, 7520 KB, 3799 KB/s, 1 seconds passed + ... 51%, 7104 KB, 3575 KB/s, 1 seconds passed +... 51%, 7136 KB, 3586 KB/s, 1 seconds passed +... 51%, 7168 KB, 3595 KB/s, 1 seconds passed +... 51%, 7200 KB, 3602 KB/s, 1 seconds passed +... 52%, 7232 KB, 3579 KB/s, 2 seconds passed +... 52%, 7264 KB, 3590 KB/s, 2 seconds passed +... 52%, 7296 KB, 3598 KB/s, 2 seconds passed .. parsed-literal:: - ... 54%, 7552 KB, 3784 KB/s, 1 seconds passed -... 54%, 7584 KB, 3785 KB/s, 2 seconds passed -... 54%, 7616 KB, 3786 KB/s, 2 seconds passed -... 55%, 7648 KB, 3801 KB/s, 2 seconds passed -... 55%, 7680 KB, 3786 KB/s, 2 seconds passed -... 55%, 7712 KB, 3787 KB/s, 2 seconds passed -... 55%, 7744 KB, 3791 KB/s, 2 seconds passed -... 56%, 7776 KB, 3803 KB/s, 2 seconds passed + ... 52%, 7328 KB, 3604 KB/s, 2 seconds passed +... 53%, 7360 KB, 3579 KB/s, 2 seconds passed +... 53%, 7392 KB, 3591 KB/s, 2 seconds passed +... 53%, 7424 KB, 3599 KB/s, 2 seconds passed .. parsed-literal:: - ... 56%, 7808 KB, 3792 KB/s, 2 seconds passed -... 56%, 7840 KB, 3790 KB/s, 2 seconds passed -... 56%, 7872 KB, 3792 KB/s, 2 seconds passed -... 56%, 7904 KB, 3805 KB/s, 2 seconds passed -... 57%, 7936 KB, 3795 KB/s, 2 seconds passed + ... 53%, 7456 KB, 3573 KB/s, 2 seconds passed +... 53%, 7488 KB, 3580 KB/s, 2 seconds passed +... 54%, 7520 KB, 3591 KB/s, 2 seconds passed +... 54%, 7552 KB, 3599 KB/s, 2 seconds passed +... 54%, 7584 KB, 3574 KB/s, 2 seconds passed +... 54%, 7616 KB, 3581 KB/s, 2 seconds passed +... 55%, 7648 KB, 3593 KB/s, 2 seconds passed .. parsed-literal:: - ... 57%, 7968 KB, 3792 KB/s, 2 seconds passed -... 57%, 8000 KB, 3796 KB/s, 2 seconds passed -... 57%, 8032 KB, 3807 KB/s, 2 seconds passed -... 58%, 8064 KB, 3797 KB/s, 2 seconds passed -... 58%, 8096 KB, 3799 KB/s, 2 seconds passed -... 58%, 8128 KB, 3798 KB/s, 2 seconds passed -... 58%, 8160 KB, 3809 KB/s, 2 seconds passed + ... 55%, 7680 KB, 3598 KB/s, 2 seconds passed +... 55%, 7712 KB, 3575 KB/s, 2 seconds passed +... 55%, 7744 KB, 3583 KB/s, 2 seconds passed +... 56%, 7776 KB, 3593 KB/s, 2 seconds passed +... 56%, 7808 KB, 3598 KB/s, 2 seconds passed .. parsed-literal:: - ... 59%, 8192 KB, 3799 KB/s, 2 seconds passed -... 59%, 8224 KB, 3800 KB/s, 2 seconds passed -... 59%, 8256 KB, 3798 KB/s, 2 seconds passed -... 59%, 8288 KB, 3811 KB/s, 2 seconds passed -... 59%, 8320 KB, 3793 KB/s, 2 seconds passed + ... 56%, 7840 KB, 3577 KB/s, 2 seconds passed +... 56%, 7872 KB, 3584 KB/s, 2 seconds passed +... 56%, 7904 KB, 3595 KB/s, 2 seconds passed +... 57%, 7936 KB, 3600 KB/s, 2 seconds passed +... 57%, 7968 KB, 3578 KB/s, 2 seconds passed +... 57%, 8000 KB, 3586 KB/s, 2 seconds passed +... 57%, 8032 KB, 3597 KB/s, 2 seconds passed .. parsed-literal:: - ... 60%, 8352 KB, 3793 KB/s, 2 seconds passed -... 60%, 8384 KB, 3799 KB/s, 2 seconds passed -... 60%, 8416 KB, 3812 KB/s, 2 seconds passed -... 60%, 8448 KB, 3795 KB/s, 2 seconds passed -... 61%, 8480 KB, 3800 KB/s, 2 seconds passed -... 61%, 8512 KB, 3803 KB/s, 2 seconds passed -... 61%, 8544 KB, 3815 KB/s, 2 seconds passed + ... 58%, 8064 KB, 3601 KB/s, 2 seconds passed +... 58%, 8096 KB, 3579 KB/s, 2 seconds passed +... 58%, 8128 KB, 3588 KB/s, 2 seconds passed +... 58%, 8160 KB, 3598 KB/s, 2 seconds passed +... 59%, 8192 KB, 3602 KB/s, 2 seconds passed .. parsed-literal:: - ... 61%, 8576 KB, 3803 KB/s, 2 seconds passed -... 62%, 8608 KB, 3802 KB/s, 2 seconds passed -... 62%, 8640 KB, 3804 KB/s, 2 seconds passed -... 62%, 8672 KB, 3816 KB/s, 2 seconds passed -... 62%, 8704 KB, 3805 KB/s, 2 seconds passed -... 62%, 8736 KB, 3805 KB/s, 2 seconds passed + ... 59%, 8224 KB, 3581 KB/s, 2 seconds passed +... 59%, 8256 KB, 3589 KB/s, 2 seconds passed +... 59%, 8288 KB, 3599 KB/s, 2 seconds passed +... 59%, 8320 KB, 3604 KB/s, 2 seconds passed +... 60%, 8352 KB, 3582 KB/s, 2 seconds passed +... 60%, 8384 KB, 3591 KB/s, 2 seconds passed .. parsed-literal:: - ... 63%, 8768 KB, 3806 KB/s, 2 seconds passed -... 63%, 8800 KB, 3818 KB/s, 2 seconds passed -... 63%, 8832 KB, 3806 KB/s, 2 seconds passed -... 63%, 8864 KB, 3802 KB/s, 2 seconds passed -... 64%, 8896 KB, 3807 KB/s, 2 seconds passed -... 64%, 8928 KB, 3820 KB/s, 2 seconds passed -... 64%, 8960 KB, 3808 KB/s, 2 seconds passed + ... 60%, 8416 KB, 3602 KB/s, 2 seconds passed +... 60%, 8448 KB, 3605 KB/s, 2 seconds passed +... 61%, 8480 KB, 3584 KB/s, 2 seconds passed +... 61%, 8512 KB, 3594 KB/s, 2 seconds passed +... 61%, 8544 KB, 3604 KB/s, 2 seconds passed +... 61%, 8576 KB, 3611 KB/s, 2 seconds passed .. parsed-literal:: - ... 64%, 8992 KB, 3804 KB/s, 2 seconds passed -... 65%, 9024 KB, 3808 KB/s, 2 seconds passed -... 65%, 9056 KB, 3821 KB/s, 2 seconds passed -... 65%, 9088 KB, 3809 KB/s, 2 seconds passed -... 65%, 9120 KB, 3806 KB/s, 2 seconds passed -... 65%, 9152 KB, 3810 KB/s, 2 seconds passed -... 66%, 9184 KB, 3822 KB/s, 2 seconds passed + ... 62%, 8608 KB, 3588 KB/s, 2 seconds passed +... 62%, 8640 KB, 3596 KB/s, 2 seconds passed +... 62%, 8672 KB, 3606 KB/s, 2 seconds passed +... 62%, 8704 KB, 3613 KB/s, 2 seconds passed +... 62%, 8736 KB, 3589 KB/s, 2 seconds passed +... 63%, 8768 KB, 3599 KB/s, 2 seconds passed .. parsed-literal:: - ... 66%, 9216 KB, 3810 KB/s, 2 seconds passed -... 66%, 9248 KB, 3808 KB/s, 2 seconds passed -... 66%, 9280 KB, 3811 KB/s, 2 seconds passed -... 67%, 9312 KB, 3823 KB/s, 2 seconds passed -... 67%, 9344 KB, 3812 KB/s, 2 seconds passed + ... 63%, 8800 KB, 3607 KB/s, 2 seconds passed +... 63%, 8832 KB, 3615 KB/s, 2 seconds passed +... 63%, 8864 KB, 3594 KB/s, 2 seconds passed +... 64%, 8896 KB, 3600 KB/s, 2 seconds passed +... 64%, 8928 KB, 3608 KB/s, 2 seconds passed +... 64%, 8960 KB, 3616 KB/s, 2 seconds passed .. parsed-literal:: - ... 67%, 9376 KB, 3809 KB/s, 2 seconds passed -... 67%, 9408 KB, 3812 KB/s, 2 seconds passed -... 68%, 9440 KB, 3824 KB/s, 2 seconds passed -... 68%, 9472 KB, 3810 KB/s, 2 seconds passed -... 68%, 9504 KB, 3816 KB/s, 2 seconds passed -... 68%, 9536 KB, 3815 KB/s, 2 seconds passed -... 68%, 9568 KB, 3826 KB/s, 2 seconds passed + ... 64%, 8992 KB, 3596 KB/s, 2 seconds passed +... 65%, 9024 KB, 3600 KB/s, 2 seconds passed +... 65%, 9056 KB, 3609 KB/s, 2 seconds passed +... 65%, 9088 KB, 3617 KB/s, 2 seconds passed +... 65%, 9120 KB, 3594 KB/s, 2 seconds passed .. parsed-literal:: - ... 69%, 9600 KB, 3816 KB/s, 2 seconds passed -... 69%, 9632 KB, 3813 KB/s, 2 seconds passed -... 69%, 9664 KB, 3817 KB/s, 2 seconds passed -... 69%, 9696 KB, 3827 KB/s, 2 seconds passed -... 70%, 9728 KB, 3817 KB/s, 2 seconds passed + ... 65%, 9152 KB, 3601 KB/s, 2 seconds passed +... 66%, 9184 KB, 3610 KB/s, 2 seconds passed +... 66%, 9216 KB, 3613 KB/s, 2 seconds passed +... 66%, 9248 KB, 3593 KB/s, 2 seconds passed +... 66%, 9280 KB, 3601 KB/s, 2 seconds passed +... 67%, 9312 KB, 3611 KB/s, 2 seconds passed +... 67%, 9344 KB, 3613 KB/s, 2 seconds passed .. parsed-literal:: - ... 70%, 9760 KB, 3812 KB/s, 2 seconds passed -... 70%, 9792 KB, 3817 KB/s, 2 seconds passed -... 70%, 9824 KB, 3828 KB/s, 2 seconds passed -... 71%, 9856 KB, 3815 KB/s, 2 seconds passed -... 71%, 9888 KB, 3815 KB/s, 2 seconds passed -... 71%, 9920 KB, 3819 KB/s, 2 seconds passed -... 71%, 9952 KB, 3830 KB/s, 2 seconds passed + ... 67%, 9376 KB, 3595 KB/s, 2 seconds passed +... 67%, 9408 KB, 3603 KB/s, 2 seconds passed +... 68%, 9440 KB, 3612 KB/s, 2 seconds passed +... 68%, 9472 KB, 3616 KB/s, 2 seconds passed +... 68%, 9504 KB, 3596 KB/s, 2 seconds passed .. parsed-literal:: - 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Conversion to ONNX command: /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/bin/python -- /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/openvino/model_zoo/internal_scripts/pytorch_to_onnx.py --model-name=mobilenet_v2 --weights=model/public/mobilenet-v2-pytorch/mobilenet_v2-b0353104.pth --import-module=torchvision.models --input-shape=1,3,224,224 --output-file=model/public/mobilenet-v2-pytorch/mobilenet-v2.onnx --input-names=data --output-names=prob + Conversion to ONNX command: /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/bin/python -- /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/openvino/model_zoo/internal_scripts/pytorch_to_onnx.py --model-name=mobilenet_v2 --weights=model/public/mobilenet-v2-pytorch/mobilenet_v2-b0353104.pth --import-module=torchvision.models --input-shape=1,3,224,224 --output-file=model/public/mobilenet-v2-pytorch/mobilenet-v2.onnx --input-names=data --output-names=prob @@ -888,7 +900,7 @@ Converting mobilenet-v2-pytorch… ========== Converting mobilenet-v2-pytorch to IR (FP16) - Conversion command: /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/bin/python -- /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/bin/mo --framework=onnx --output_dir=model/public/mobilenet-v2-pytorch/FP16 --model_name=mobilenet-v2-pytorch --input=data '--mean_values=data[123.675,116.28,103.53]' '--scale_values=data[58.624,57.12,57.375]' --reverse_input_channels --output=prob --input_model=model/public/mobilenet-v2-pytorch/mobilenet-v2.onnx '--layout=data(NCHW)' '--input_shape=[1, 3, 224, 224]' --compress_to_fp16=True + Conversion command: /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/bin/python -- /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/bin/mo --framework=onnx --output_dir=model/public/mobilenet-v2-pytorch/FP16 --model_name=mobilenet-v2-pytorch --input=data '--mean_values=data[123.675,116.28,103.53]' '--scale_values=data[58.624,57.12,57.375]' --reverse_input_channels --output=prob --input_model=model/public/mobilenet-v2-pytorch/mobilenet-v2.onnx '--layout=data(NCHW)' '--input_shape=[1, 3, 224, 224]' --compress_to_fp16=True @@ -901,9 +913,8 @@ Converting mobilenet-v2-pytorch… [ INFO ] MO command line tool is considered as the legacy conversion API as of OpenVINO 2023.2 release. Please use OpenVINO Model Converter (OVC). OVC represents a lightweight alternative of MO and provides simplified model conversion API. Find more information about transition from MO to OVC at https://docs.openvino.ai/2023.2/openvino_docs_OV_Converter_UG_prepare_model_convert_model_MO_OVC_transition.html [ SUCCESS ] Generated IR version 11 model. - [ SUCCESS ] XML file: /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/104-model-tools/model/public/mobilenet-v2-pytorch/FP16/mobilenet-v2-pytorch.xml - [ SUCCESS ] BIN file: /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/104-model-tools/model/public/mobilenet-v2-pytorch/FP16/mobilenet-v2-pytorch.bin - + [ SUCCESS ] XML file: /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/notebooks/104-model-tools/model/public/mobilenet-v2-pytorch/FP16/mobilenet-v2-pytorch.xml + [ SUCCESS ] BIN file: /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/notebooks/104-model-tools/model/public/mobilenet-v2-pytorch/FP16/mobilenet-v2-pytorch.bin @@ -956,8 +967,8 @@ information in a dictionary. 'description': 'MobileNet V2 is image classification model pre-trained on ImageNet dataset. This is a PyTorch* implementation of MobileNetV2 architecture as described in the paper "Inverted Residuals and Linear Bottlenecks: Mobile Networks for Classification, Detection and Segmentation" .\nThe model input is a blob that consists of a single image of "1, 3, 224, 224" in "RGB" order.\nThe model output is typical object classifier for the 1000 different classifications matching with those in the ImageNet database.', 'framework': 'pytorch', 'license_url': 'https://raw.githubusercontent.com/pytorch/vision/master/LICENSE', - 'accuracy_config': '/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/openvino/model_zoo/models/public/mobilenet-v2-pytorch/accuracy-check.yml', - 'model_config': '/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/openvino/model_zoo/models/public/mobilenet-v2-pytorch/model.yml', + 'accuracy_config': '/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/openvino/model_zoo/models/public/mobilenet-v2-pytorch/accuracy-check.yml', + 'model_config': '/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/openvino/model_zoo/models/public/mobilenet-v2-pytorch/model.yml', 'precisions': ['FP16', 'FP32'], 'quantization_output_precisions': ['FP16-INT8', 'FP32-INT8'], 'subdirectory': 'public/mobilenet-v2-pytorch', @@ -1043,7 +1054,7 @@ seconds… [ WARNING ] Performance hint was not explicitly specified in command line. Device(CPU) performance hint will be set to PerformanceMode.THROUGHPUT. [Step 4/11] Reading model files [ INFO ] Loading model files - [ INFO ] Read model took 30.88 ms + [ INFO ] Read model took 28.83 ms [ INFO ] Original model I/O parameters: [ INFO ] Model inputs: [ INFO ] data (node: data) : f32 / [N,C,H,W] / [1,3,224,224] @@ -1061,7 +1072,7 @@ seconds… .. parsed-literal:: - [ INFO ] Compile model took 154.97 ms + [ INFO ] Compile model took 135.30 ms [Step 8/11] Querying optimal runtime parameters [ INFO ] Model: [ INFO ] NETWORK_NAME: main_graph @@ -1085,25 +1096,25 @@ seconds… [ INFO ] Fill input 'data' with random values [Step 10/11] Measuring performance (Start inference asynchronously, 6 inference requests, limits: 15000 ms duration) [ INFO ] Benchmarking in inference only mode (inputs filling are not included in measurement loop). + [ INFO ] First inference took 6.27 ms .. parsed-literal:: - [ INFO ] First inference took 6.26 ms + [Step 11/11] Dumping statistics report .. parsed-literal:: - [Step 11/11] Dumping statistics report [ INFO ] Execution Devices:['CPU'] - [ INFO ] Count: 20028 iterations - [ INFO ] Duration: 15005.22 ms + [ INFO ] Count: 20346 iterations + [ INFO ] Duration: 15007.48 ms [ INFO ] Latency: - [ INFO ] Median: 4.36 ms - [ INFO ] Average: 4.37 ms - [ INFO ] Min: 2.74 ms - [ INFO ] Max: 12.78 ms - [ INFO ] Throughput: 1334.74 FPS + [ INFO ] Median: 4.29 ms + [ INFO ] Average: 4.30 ms + [ INFO ] Min: 2.40 ms + [ INFO ] Max: 12.55 ms + [ INFO ] Throughput: 1355.72 FPS Benchmark with Different Settings @@ -1133,7 +1144,7 @@ In the next cell, define the ``benchmark_model()`` function that calls ``benchmark_app``. This makes it easy to try different combinations. In the cell below that, you display available devices on the system. - **Note**: In this notebook, ``benchmark_app`` runs for 15 seconds to + **NOTE**: In this notebook, ``benchmark_app`` runs for 15 seconds to give a quick indication of performance. For more accurate performance, it is recommended to run inference for at least one minute by setting the ``t`` parameter to 60 or higher, and run diff --git a/docs/notebooks/105-language-quantize-bert-with-output.rst b/docs/notebooks/105-language-quantize-bert-with-output.rst index 295fde2a3b16f6..f62318fe2296de 100644 --- a/docs/notebooks/105-language-quantize-bert-with-output.rst +++ b/docs/notebooks/105-language-quantize-bert-with-output.rst @@ -43,7 +43,7 @@ Table of contents: .. code:: ipython3 %pip install -q "nncf>=2.5.0" - %pip install -q "transformers" datasets evaluate --extra-index-url https://download.pytorch.org/whl/cpu + %pip install -q transformers datasets evaluate --extra-index-url https://download.pytorch.org/whl/cpu %pip install -q "openvino>=2023.1.0" @@ -96,14 +96,14 @@ Imports .. parsed-literal:: - 2024-01-25 22:37:51.906403: I tensorflow/core/util/port.cc:110] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`. - 2024-01-25 22:37:51.939998: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations. + 2024-02-09 22:38:10.763464: I tensorflow/core/util/port.cc:110] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`. + 2024-02-09 22:38:10.797722: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations. To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags. .. parsed-literal:: - 2024-01-25 22:37:52.576201: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT + 2024-02-09 22:38:11.441310: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT .. parsed-literal:: @@ -191,7 +191,7 @@ PyTorch model formats are supported: .. parsed-literal:: - /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/torch/_utils.py:831: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage() + /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/torch/_utils.py:831: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage() return self.fget.__get__(instance, owner)() @@ -286,13 +286,15 @@ The optimization process contains the following steps: -.. raw:: html - 

 
 
 
 
+.. raw:: html
+
+    
+    

 
 
 
@@ -303,13 +305,16 @@ The optimization process contains the following steps:
 
 
 
-.. raw:: html
 
-    

 
 
 
 
+.. raw:: html
+
+    
+    

+
 
 
 .. parsed-literal::
@@ -329,13 +334,15 @@ The optimization process contains the following steps:
 
 
 
-.. raw:: html
 
-    

 
 
 
 
+.. raw:: html
+
+    
+    

 
 
 
@@ -346,13 +353,15 @@ The optimization process contains the following steps:
 
 
 
-.. raw:: html
 
-    

 
 
 
 
+.. raw:: html
+
+    
+    

 
 
 
@@ -548,17 +557,17 @@ Frames Per Second (FPS) for images.
 
 .. parsed-literal::
 
-    PyTorch model on CPU: 0.074 seconds per sentence, SPS: 13.56
+    PyTorch model on CPU: 0.073 seconds per sentence, SPS: 13.77
 
 
 .. parsed-literal::
 
-    IR FP32 model in OpenVINO Runtime/AUTO: 0.021 seconds per sentence, SPS: 48.16
+    IR FP32 model in OpenVINO Runtime/AUTO: 0.021 seconds per sentence, SPS: 47.89
 
 
 .. parsed-literal::
 
-    OpenVINO IR INT8 model in OpenVINO Runtime/AUTO: 0.009 seconds per sentence, SPS: 109.03
+    OpenVINO IR INT8 model in OpenVINO Runtime/AUTO: 0.009 seconds per sentence, SPS: 109.72
 
 
 Finally, measure the inference performance of OpenVINO ``FP32`` and
@@ -566,7 +575,7 @@ Finally, measure the inference performance of OpenVINO ``FP32`` and
 Tool `__
 in OpenVINO.
 
-   **Note**: The ``benchmark_app`` tool is able to measure the
+   **NOTE**: The ``benchmark_app`` tool is able to measure the
    performance of the OpenVINO Intermediate Representation (OpenVINO IR)
    models only. For more accurate performance, run ``benchmark_app`` in
    a terminal/command prompt after closing other applications. Run
@@ -599,7 +608,7 @@ in OpenVINO.
     Device with "device" name is not registered in the OpenVINO Runtime
 
     Traceback (most recent call last):
-      File "/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/openvino/tools/benchmark/main.py", line 166, in main
+      File "/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/openvino/tools/benchmark/main.py", line 166, in main
         supported_properties = benchmark.core.get_property(device, properties.supported_properties())
     RuntimeError: Exception from src/inference/src/core.cpp:228:
     Exception from src/inference/src/dev/core_impl.cpp:560:
@@ -632,7 +641,7 @@ in OpenVINO.
     Device with "device" name is not registered in the OpenVINO Runtime
 
     Traceback (most recent call last):
-      File "/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/openvino/tools/benchmark/main.py", line 166, in main
+      File "/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/openvino/tools/benchmark/main.py", line 166, in main
         supported_properties = benchmark.core.get_property(device, properties.supported_properties())
     RuntimeError: Exception from src/inference/src/core.cpp:228:
     Exception from src/inference/src/dev/core_impl.cpp:560:
diff --git a/docs/notebooks/106-auto-device-with-output.rst b/docs/notebooks/106-auto-device-with-output.rst
index afa263abddebb0..b2b4bb85b78447 100644
--- a/docs/notebooks/106-auto-device-with-output.rst
+++ b/docs/notebooks/106-auto-device-with-output.rst
@@ -6,7 +6,7 @@ device `__.
+devices `__.
 The model precision (such as ``FP32``, ``FP16``, ``INT8``, etc.) is the
 first consideration to filter out the devices that cannot run the
 network efficiently.
@@ -81,13 +81,13 @@ Import modules and create Core
 
     import time
     import sys
-
+    
     import openvino as ov
-
+    
     from IPython.display import Markdown, display
-
+    
     core = ov.Core()
-
+    
     if "GPU" not in core.available_devices:
         display(Markdown('
Warning:  A GPU device is not available. This notebook requires GPU device to have meaningful results. 
'))
 
@@ -127,11 +127,11 @@ For more information about model conversion API, see this
 
     import torchvision
     from pathlib import Path
-
+    
     base_model_dir = Path("./model")
     base_model_dir.mkdir(exist_ok=True)
     model_path = base_model_dir / "resnet50.xml"
-
+    
     if not model_path.exists():
         pt_model = torchvision.models.resnet50(weights="DEFAULT")
         ov_model = ov.convert_model(pt_model, input=[[1,3,224,224]])
@@ -164,24 +164,24 @@ By default, ``compile_model`` API will select **AUTO** as
 
     # Set LOG_LEVEL to LOG_INFO.
     core.set_property("AUTO", {"LOG_LEVEL":"LOG_INFO"})
-
+    
     # Load the model onto the target device.
     compiled_model = core.compile_model(ov_model)
-
+    
     if isinstance(compiled_model, ov.CompiledModel):
-        print("Successfully compiled model without a device_name.")
+        print("Successfully compiled model without a device_name.")   
 
 
 .. parsed-literal::
 
-    [22:41:12.8903]I[plugin.cpp:536][AUTO] device:CPU, config:PERFORMANCE_HINT=LATENCY
-    [22:41:12.8903]I[plugin.cpp:536][AUTO] device:CPU, config:PERFORMANCE_HINT_NUM_REQUESTS=0
-    [22:41:12.8904]I[plugin.cpp:536][AUTO] device:CPU, config:PERF_COUNT=NO
-    [22:41:12.8904]I[plugin.cpp:541][AUTO] device:CPU, priority:0
-    [22:41:12.8904]I[schedule.cpp:17][AUTO] scheduler starting
-    [22:41:12.8904]I[auto_schedule.cpp:131][AUTO] select device:CPU
-    [22:41:13.0500]I[auto_schedule.cpp:109][AUTO] device:CPU compiling model finished
-    [22:41:13.0502]I[plugin.cpp:569][AUTO] underlying hardware does not support hardware context
+    [22:41:31.9445]I[plugin.cpp:536][AUTO] device:CPU, config:PERFORMANCE_HINT=LATENCY
+    [22:41:31.9445]I[plugin.cpp:536][AUTO] device:CPU, config:PERFORMANCE_HINT_NUM_REQUESTS=0
+    [22:41:31.9445]I[plugin.cpp:536][AUTO] device:CPU, config:PERF_COUNT=NO
+    [22:41:31.9445]I[plugin.cpp:541][AUTO] device:CPU, priority:0
+    [22:41:31.9446]I[schedule.cpp:17][AUTO] scheduler starting
+    [22:41:31.9446]I[auto_schedule.cpp:131][AUTO] select device:CPU
+    [22:41:32.0858]I[auto_schedule.cpp:109][AUTO] device:CPU compiling model finished
+    [22:41:32.0860]I[plugin.cpp:569][AUTO] underlying hardware does not support hardware context
     Successfully compiled model without a device_name.
 
 
@@ -195,7 +195,7 @@ By default, ``compile_model`` API will select **AUTO** as
 .. parsed-literal::
 
     Deleted compiled_model
-    [22:41:13.0623]I[schedule.cpp:303][AUTO] scheduler ending
+    [22:41:32.0982]I[schedule.cpp:303][AUTO] scheduler ending
 
 
 Explicitly pass AUTO as device_name to Core::compile_model API
@@ -210,9 +210,9 @@ improve readability of your code.
 
     # Set LOG_LEVEL to LOG_NONE.
     core.set_property("AUTO", {"LOG_LEVEL":"LOG_NONE"})
-
+    
     compiled_model = core.compile_model(model=ov_model, device_name="AUTO")
-
+    
     if isinstance(compiled_model, ov.CompiledModel):
         print("Successfully compiled model using AUTO.")
 
@@ -271,16 +271,16 @@ function, we will reuse it for preparing input data.
 .. code:: ipython3
 
     from PIL import Image
-
+    
     # Download the image from the openvino_notebooks storage
     image_filename = download_file(
         "https://storage.openvinotoolkit.org/repositories/openvino_notebooks/data/data/image/coco.jpg",
         directory="data"
     )
-
+    
     image = Image.open(str(image_filename))
     input_transform = torchvision.models.ResNet50_Weights.DEFAULT.transforms()
-
+    
     input_tensor = input_transform(image)
     input_tensor = input_tensor.unsqueeze(0).numpy()
     image
@@ -307,14 +307,14 @@ Load the model to GPU device and perform inference
 
     if "GPU" not in core.available_devices:
         print(f"A GPU device is not available. Available devices are: {core.available_devices}")
-    else :
+    else :       
         # Start time.
         gpu_load_start_time = time.perf_counter()
         compiled_model = core.compile_model(model=ov_model, device_name="GPU")  # load to GPU
-
+    
         # Execute the first inference.
         results = compiled_model(input_tensor)[0]
-
+    
         # Measure time to the first inference.
         gpu_fil_end_time = time.perf_counter()
         gpu_fil_span = gpu_fil_end_time - gpu_load_start_time
@@ -340,11 +340,11 @@ executed on CPU until GPU is ready.
     # Start time.
     auto_load_start_time = time.perf_counter()
     compiled_model = core.compile_model(model=ov_model)  # The device_name is AUTO by default.
-
+    
     # Execute the first inference.
     results = compiled_model(input_tensor)[0]
-
-
+    
+    
     # Measure time to the first inference.
     auto_fil_end_time = time.perf_counter()
     auto_fil_span = auto_fil_end_time - auto_load_start_time
@@ -353,7 +353,7 @@ executed on CPU until GPU is ready.
 
 .. parsed-literal::
 
-    Time to load model using AUTO device and get first inference: 0.15 seconds.
+    Time to load model using AUTO device and get first inference: 0.16 seconds.
 
 
 .. code:: ipython3
@@ -406,11 +406,11 @@ Class and callback definition
             """
             self.fps = 0
             self.latency = 0
-
+            
             self.start_time = time.perf_counter()
             self.latency_list = []
             self.interval = interval
-
+            
         def update(self, infer_request: ov.InferRequest) -> bool:
             """
             Update the metrics if current ongoing @interval seconds duration is expired. Record the latency only if it is not expired.
@@ -432,12 +432,12 @@ Class and callback definition
                 return True
             else :
                 return False
-
-
+    
+    
     class InferContext:
         """
         Inference context. Record and update peforamnce metrics via @metrics, set @feed_inference to False once @remaining_update_num <=0
-        :member: metrics: instance of class PerformanceMetrics
+        :member: metrics: instance of class PerformanceMetrics 
         :member: remaining_update_num: the remaining times for peforamnce metrics updating.
         :member: feed_inference: if feed inference request is required or not.
         """
@@ -452,7 +452,7 @@ Class and callback definition
             self.metrics = PerformanceMetrics(update_interval)
             self.remaining_update_num = num
             self.feed_inference = True
-
+            
         def update(self, infer_request: ov.InferRequest):
             """
             Update the context. Set @feed_inference to False if the number of remaining performance metric updates (@remaining_update_num) reaches 0
@@ -461,13 +461,13 @@ Class and callback definition
             """
             if self.remaining_update_num <= 0 :
                 self.feed_inference = False
-
+                
             if self.metrics.update(infer_request) :
                 self.remaining_update_num = self.remaining_update_num - 1
                 if self.remaining_update_num <= 0 :
                     self.feed_inference = False
-
-
+    
+    
     def completion_callback(infer_request: ov.InferRequest, context) -> None:
         """
         callback for the inference request, pass the @infer_request to @context for updating
@@ -476,8 +476,8 @@ Class and callback definition
         :returns: None
         """
         context.update(infer_request)
-
-
+    
+    
     # Performance metrics update interval (seconds) and number of times.
     metrics_update_interval = 10
     metrics_update_num = 6
@@ -493,29 +493,29 @@ Loop for inference and update the FPS/Latency every
 .. code:: ipython3
 
     THROUGHPUT_hint_context = InferContext(metrics_update_interval, metrics_update_num)
-
+    
     print("Compiling Model for AUTO device with THROUGHPUT hint")
     sys.stdout.flush()
-
+    
     compiled_model = core.compile_model(model=ov_model, config={"PERFORMANCE_HINT":"THROUGHPUT"})
-
+    
     infer_queue = ov.AsyncInferQueue(compiled_model, 0)  # Setting to 0 will query optimal number by default.
     infer_queue.set_callback(completion_callback)
-
+    
     print(f"Start inference, {metrics_update_num: .0f} groups of FPS/latency will be measured over {metrics_update_interval: .0f}s intervals")
     sys.stdout.flush()
-
+    
     while THROUGHPUT_hint_context.feed_inference:
         infer_queue.start_async(input_tensor, THROUGHPUT_hint_context)
-
+        
     infer_queue.wait_all()
-
+    
     # Take the FPS and latency of the latest period.
     THROUGHPUT_hint_fps = THROUGHPUT_hint_context.metrics.fps
     THROUGHPUT_hint_latency = THROUGHPUT_hint_context.metrics.latency
-
+    
     print("Done")
-
+    
     del compiled_model
 
 
@@ -531,32 +531,32 @@ Loop for inference and update the FPS/Latency every
 
 .. parsed-literal::
 
-    throughput:  184.87fps, latency:  30.81ms, time interval: 10.01s
+    throughput:  179.69fps, latency:  31.58ms, time interval: 10.00s
 
 
 .. parsed-literal::
 
-    throughput:  185.21fps, latency:  31.62ms, time interval: 10.02s
+    throughput:  182.30fps, latency:  32.10ms, time interval: 10.00s
 
 
 .. parsed-literal::
 
-    throughput:  185.47fps, latency:  31.54ms, time interval: 10.00s
+    throughput:  180.62fps, latency:  32.36ms, time interval: 10.02s
 
 
 .. parsed-literal::
 
-    throughput:  185.75fps, latency:  31.53ms, time interval: 10.01s
+    throughput:  179.76fps, latency:  32.61ms, time interval: 10.00s
 
 
 .. parsed-literal::
 
-    throughput:  185.09fps, latency:  31.64ms, time interval: 10.00s
+    throughput:  180.36fps, latency:  32.36ms, time interval: 10.02s
 
 
 .. parsed-literal::
 
-    throughput:  184.42fps, latency:  31.76ms, time interval: 10.00s
+    throughput:  179.77fps, latency:  32.58ms, time interval: 10.00s
 
 
 .. parsed-literal::
@@ -575,30 +575,30 @@ Loop for inference and update the FPS/Latency for each
 .. code:: ipython3
 
     LATENCY_hint_context = InferContext(metrics_update_interval, metrics_update_num)
-
+    
     print("Compiling Model for AUTO Device with LATENCY hint")
     sys.stdout.flush()
-
+    
     compiled_model = core.compile_model(model=ov_model, config={"PERFORMANCE_HINT":"LATENCY"})
-
+    
     # Setting to 0 will query optimal number by default.
     infer_queue = ov.AsyncInferQueue(compiled_model, 0)
     infer_queue.set_callback(completion_callback)
-
+    
     print(f"Start inference, {metrics_update_num: .0f} groups fps/latency will be out with {metrics_update_interval: .0f}s interval")
     sys.stdout.flush()
-
+    
     while LATENCY_hint_context.feed_inference:
         infer_queue.start_async(input_tensor, LATENCY_hint_context)
-
+        
     infer_queue.wait_all()
-
+    
     # Take the FPS and latency of the latest period.
     LATENCY_hint_fps = LATENCY_hint_context.metrics.fps
     LATENCY_hint_latency = LATENCY_hint_context.metrics.latency
-
+    
     print("Done")
-
+    
     del compiled_model
 
 
@@ -614,32 +614,32 @@ Loop for inference and update the FPS/Latency for each
 
 .. parsed-literal::
 
-    throughput:  138.57fps, latency:  6.67ms, time interval: 10.00s
+    throughput:  139.27fps, latency:  6.65ms, time interval: 10.00s
 
 
 .. parsed-literal::
 
-    throughput:  141.04fps, latency:  6.66ms, time interval: 10.00s
+    throughput:  141.22fps, latency:  6.62ms, time interval: 10.01s
 
 
 .. parsed-literal::
 
-    throughput:  140.74fps, latency:  6.66ms, time interval: 10.00s
+    throughput:  140.71fps, latency:  6.64ms, time interval: 10.01s
 
 
 .. parsed-literal::
 
-    throughput:  141.60fps, latency:  6.68ms, time interval: 10.01s
+    throughput:  141.11fps, latency:  6.63ms, time interval: 10.01s
 
 
 .. parsed-literal::
 
-    throughput:  141.73fps, latency:  6.68ms, time interval: 10.00s
+    throughput:  141.26fps, latency:  6.62ms, time interval: 10.00s
 
 
 .. parsed-literal::
 
-    throughput:  141.45fps, latency:  6.67ms, time interval: 10.00s
+    throughput:  141.18fps, latency:  6.63ms, time interval: 10.00s
 
 
 .. parsed-literal::
@@ -655,21 +655,21 @@ Difference in FPS and latency
 .. code:: ipython3
 
     import matplotlib.pyplot as plt
-
+    
     TPUT = 0
     LAT = 1
     labels = ["THROUGHPUT hint", "LATENCY hint"]
-
-    fig1, ax1 = plt.subplots(1, 1)
+    
+    fig1, ax1 = plt.subplots(1, 1) 
     fig1.patch.set_visible(False)
-    ax1.axis('tight')
-    ax1.axis('off')
-
+    ax1.axis('tight') 
+    ax1.axis('off') 
+    
     cell_text = []
     cell_text.append(['%.2f%s' % (THROUGHPUT_hint_fps," FPS"), '%.2f%s' % (THROUGHPUT_hint_latency, " ms")])
     cell_text.append(['%.2f%s' % (LATENCY_hint_fps," FPS"), '%.2f%s' % (LATENCY_hint_latency, " ms")])
-
-    table = ax1.table(cellText=cell_text, colLabels=["FPS (Higher is better)", "Latency (Lower is better)"], rowLabels=labels,
+    
+    table = ax1.table(cellText=cell_text, colLabels=["FPS (Higher is better)", "Latency (Lower is better)"], rowLabels=labels,  
                       rowColours=["deepskyblue"] * 2, colColours=["deepskyblue"] * 2,
                       cellLoc='center', loc='upper left')
     table.auto_set_font_size(False)
@@ -677,7 +677,7 @@ Difference in FPS and latency
     table.auto_set_column_width(0)
     table.auto_set_column_width(1)
     table.scale(1, 3)
-
+    
     fig1.tight_layout()
     plt.show()
 
@@ -691,28 +691,28 @@ Difference in FPS and latency
     # Output the difference.
     width = 0.4
     fontsize = 14
-
+    
     plt.rc('font', size=fontsize)
     fig, ax = plt.subplots(1,2, figsize=(10, 8))
-
+    
     rects1 = ax[0].bar([0], THROUGHPUT_hint_fps, width, label=labels[TPUT], color='#557f2d')
     rects2 = ax[0].bar([width], LATENCY_hint_fps, width, label=labels[LAT])
     ax[0].set_ylabel("frames per second")
-    ax[0].set_xticks([width / 2])
+    ax[0].set_xticks([width / 2]) 
     ax[0].set_xticklabels(["FPS"])
     ax[0].set_xlabel("Higher is better")
-
+    
     rects1 = ax[1].bar([0], THROUGHPUT_hint_latency, width, label=labels[TPUT], color='#557f2d')
     rects2 = ax[1].bar([width], LATENCY_hint_latency, width, label=labels[LAT])
     ax[1].set_ylabel("milliseconds")
     ax[1].set_xticks([width / 2])
     ax[1].set_xticklabels(["Latency (ms)"])
     ax[1].set_xlabel("Lower is better")
-
+    
     fig.suptitle('Performance Hints')
     fig.legend(labels, fontsize=fontsize)
     fig.tight_layout()
-
+    
     plt.show()
 
 
diff --git a/docs/notebooks/106-auto-device-with-output_files/106-auto-device-with-output_27_0.png b/docs/notebooks/106-auto-device-with-output_files/106-auto-device-with-output_27_0.png
index 619a80e73ac20a..73dff3229ae4f3 100644
--- a/docs/notebooks/106-auto-device-with-output_files/106-auto-device-with-output_27_0.png
+++ b/docs/notebooks/106-auto-device-with-output_files/106-auto-device-with-output_27_0.png
@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:1b8fb134deae365a3c5b358b032e2ad1e5ccaccae51cb176f250ba946461d8d6
-size 25724
+oid sha256:acc35ef9a1d6c2acf74782263f65bd81b65d7fd6663a146ffb88c9a9b64e343d
+size 26542
diff --git a/docs/notebooks/106-auto-device-with-output_files/106-auto-device-with-output_28_0.png b/docs/notebooks/106-auto-device-with-output_files/106-auto-device-with-output_28_0.png
index f69a128eb75f04..6ea25daababa4a 100644
--- a/docs/notebooks/106-auto-device-with-output_files/106-auto-device-with-output_28_0.png
+++ b/docs/notebooks/106-auto-device-with-output_files/106-auto-device-with-output_28_0.png
@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
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diff --git a/docs/notebooks/106-auto-device-with-output_files/index.html.tmp b/docs/notebooks/106-auto-device-with-output_files/index.html.tmp
deleted file mode 100644
index 1329909be0dbed..00000000000000
--- a/docs/notebooks/106-auto-device-with-output_files/index.html.tmp
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@@ -1,10 +0,0 @@
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-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/106-auto-device-with-output_files/
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Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/106-auto-device-with-output_files/
../
-106-auto-device-with-output_14_1.jpg               26-Jan-2024 01:05              121563
-106-auto-device-with-output_14_1.png               26-Jan-2024 01:05              869661
-106-auto-device-with-output_27_0.png               26-Jan-2024 01:05               25724
-106-auto-device-with-output_28_0.png               26-Jan-2024 01:05               40017
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diff --git a/docs/notebooks/107-speech-recognition-quantization-data2vec-with-output.rst b/docs/notebooks/107-speech-recognition-quantization-data2vec-with-output.rst
index 2ac739f7abf2c0..ca3683e05ef3dc 100644
--- a/docs/notebooks/107-speech-recognition-quantization-data2vec-with-output.rst
+++ b/docs/notebooks/107-speech-recognition-quantization-data2vec-with-output.rst
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diff --git a/docs/notebooks/107-speech-recognition-quantization-wav2vec2-with-output.rst b/docs/notebooks/107-speech-recognition-quantization-wav2vec2-with-output.rst
index 967464c1e95f7b..95e82386d073fe 100644
--- a/docs/notebooks/107-speech-recognition-quantization-wav2vec2-with-output.rst
+++ b/docs/notebooks/107-speech-recognition-quantization-wav2vec2-with-output.rst
@@ -50,84 +50,88 @@ Table of contents:
 .. parsed-literal::
 
     Looking in indexes: https://pypi.org/simple, https://download.pytorch.org/whl/cpu
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+    Requirement already satisfied: datasets in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (2.17.0)
 
 
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     Collecting torchmetrics>=0.11.0
       Using cached torchmetrics-1.3.0.post0-py3-none-any.whl.metadata (20 kB)
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+    Requirement already satisfied: torch>=2.1.0 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (2.1.0+cpu)
 
 
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+    Collecting lightning-utilities>=0.8.0 (from torchmetrics>=0.11.0)
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 .. parsed-literal::
 
-    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/transformers/models/wav2vec2/modeling_wav2vec2.py:593: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
+    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/transformers/models/wav2vec2/modeling_wav2vec2.py:593: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
       if attn_weights.size() != (bsz * self.num_heads, tgt_len, src_len):
-    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/transformers/models/wav2vec2/modeling_wav2vec2.py:632: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
+    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/transformers/models/wav2vec2/modeling_wav2vec2.py:632: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
       if attn_output.size() != (bsz * self.num_heads, tgt_len, self.head_dim):
 
 
@@ -260,7 +264,7 @@ dataset.
 
 .. parsed-literal::
 
-    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/datasets/load.py:1429: FutureWarning: The repository for patrickvonplaten/librispeech_asr_dummy contains custom code which must be executed to correctly load the dataset. You can inspect the repository content at https://hf.co/datasets/patrickvonplaten/librispeech_asr_dummy
+    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/datasets/load.py:1454: FutureWarning: The repository for patrickvonplaten/librispeech_asr_dummy contains custom code which must be executed to correctly load the dataset. You can inspect the repository content at https://hf.co/datasets/patrickvonplaten/librispeech_asr_dummy
     You can avoid this message in future by passing the argument `trust_remote_code=True`.
     Passing `trust_remote_code=True` will be mandatory to load this dataset from the next major release of `datasets`.
       warnings.warn(
@@ -334,14 +338,14 @@ steps:
 
 .. parsed-literal::
 
-    2024-01-25 22:43:51.310601: I tensorflow/core/util/port.cc:110] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
-    2024-01-25 22:43:51.341489: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+    2024-02-09 22:44:10.617295: I tensorflow/core/util/port.cc:110] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
+    2024-02-09 22:44:10.648558: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
     To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
 
 
 .. parsed-literal::
 
-    2024-01-25 22:43:51.934215: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+    2024-02-09 22:44:11.243901: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
 
 
 
@@ -351,14 +355,15 @@ steps:
 
 
 
-.. raw:: html
 
-    

 
 
 
 
+.. raw:: html
 
+    
+    

 
 
 
@@ -369,14 +374,15 @@ steps:
 
 
 
-.. raw:: html
 
-    

 
 
 
 
+.. raw:: html
 
+    
+    

 
 
 
@@ -422,14 +428,15 @@ steps:
 
 
 
-.. raw:: html
 
-    

 
 
 
 
+.. raw:: html
 
+    
+    

 
 
 
@@ -440,14 +447,15 @@ steps:
 
 
 
-.. raw:: html
 
-    

 
 
 
 
+.. raw:: html
 
+    
+    

 
 
 
@@ -582,7 +590,7 @@ quantized model.
 
 .. parsed-literal::
 
-    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/torchmetrics/utilities/prints.py:62: FutureWarning: Importing `WordErrorRate` from `torchmetrics` was deprecated and will be removed in 2.0. Import `WordErrorRate` from `torchmetrics.text` instead.
+    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/torchmetrics/utilities/prints.py:62: FutureWarning: Importing `WordErrorRate` from `torchmetrics` was deprecated and will be removed in 2.0. Import `WordErrorRate` from `torchmetrics.text` instead.
       _future_warning(
 
 
@@ -659,35 +667,35 @@ models.
 
 .. parsed-literal::
 
-    [ INFO ] Read model took 54.55 ms
+    [ INFO ] Read model took 56.59 ms
     [ INFO ] Original model I/O parameters:
     [ INFO ] Model inputs:
     [ INFO ]     input_values (node: input_values) : f32 / [...] / [?,?]
     [ INFO ] Model outputs:
-    [ INFO ]     logits , 1170 (node: __module.lm_head/aten::linear/Add) : f32 / [...] / [?,?,32]
+    [ INFO ]     1170 , logits (node: __module.lm_head/aten::linear/Add) : f32 / [...] / [?,?,32]
     [Step 5/11] Resizing model to match image sizes and given batch
     [ INFO ] Model batch size: 1
     [ INFO ] Reshaping model: 'input_values': [1,30480]
-    [ INFO ] Reshape model took 30.95 ms
+
+
+.. parsed-literal::
+
+    [ INFO ] Reshape model took 30.54 ms
     [Step 6/11] Configuring input of the model
     [ INFO ] Model inputs:
     [ INFO ]     input_values (node: input_values) : f32 / [...] / [1,30480]
     [ INFO ] Model outputs:
-    [ INFO ]     logits , 1170 (node: __module.lm_head/aten::linear/Add) : f32 / [...] / [1,95,32]
+    [ INFO ]     1170 , logits (node: __module.lm_head/aten::linear/Add) : f32 / [...] / [1,95,32]
     [Step 7/11] Loading the model to the device
 
 
 .. parsed-literal::
 
-    [ INFO ] Compile model took 560.02 ms
+    [ INFO ] Compile model took 559.12 ms
     [Step 8/11] Querying optimal runtime parameters
     [ INFO ] Model:
     [ INFO ]   NETWORK_NAME: Model0
     [ INFO ]   OPTIMAL_NUMBER_OF_INFER_REQUESTS: 6
-
-
-.. parsed-literal::
-
     [ INFO ]   NUM_STREAMS: 6
     [ INFO ]   AFFINITY: Affinity.CORE
     [ INFO ]   INFERENCE_NUM_THREADS: 24
@@ -711,21 +719,21 @@ models.
 
 .. parsed-literal::
 
-    [ INFO ] First inference took 58.98 ms
+    [ INFO ] First inference took 56.43 ms
 
 
 .. parsed-literal::
 
     [Step 11/11] Dumping statistics report
     [ INFO ] Execution Devices:['CPU']
-    [ INFO ] Count:            2766 iterations
-    [ INFO ] Duration:         60197.24 ms
+    [ INFO ] Count:            2778 iterations
+    [ INFO ] Duration:         60216.97 ms
     [ INFO ] Latency:
-    [ INFO ]    Median:        130.42 ms
-    [ INFO ]    Average:       130.38 ms
-    [ INFO ]    Min:           64.93 ms
-    [ INFO ]    Max:           148.03 ms
-    [ INFO ] Throughput:   45.95 FPS
+    [ INFO ]    Median:        129.97 ms
+    [ INFO ]    Average:       129.78 ms
+    [ INFO ]    Min:           110.04 ms
+    [ INFO ]    Max:           151.03 ms
+    [ INFO ] Throughput:   46.13 FPS
 
 
 .. code:: ipython3
@@ -759,7 +767,7 @@ models.
 
 .. parsed-literal::
 
-    [ INFO ] Read model took 70.41 ms
+    [ INFO ] Read model took 67.98 ms
     [ INFO ] Original model I/O parameters:
     [ INFO ] Model inputs:
     [ INFO ]     input_values (node: input_values) : f32 / [...] / [?,?]
@@ -772,7 +780,7 @@ models.
 
 .. parsed-literal::
 
-    [ INFO ] Reshape model took 37.13 ms
+    [ INFO ] Reshape model took 37.53 ms
     [Step 6/11] Configuring input of the model
     [ INFO ] Model inputs:
     [ INFO ]     input_values (node: input_values) : f32 / [...] / [1,30480]
@@ -783,7 +791,7 @@ models.
 
 .. parsed-literal::
 
-    [ INFO ] Compile model took 999.07 ms
+    [ INFO ] Compile model took 1060.01 ms
     [Step 8/11] Querying optimal runtime parameters
     [ INFO ] Model:
     [ INFO ]   NETWORK_NAME: Model0
@@ -803,10 +811,6 @@ models.
     [ INFO ]   CPU_DENORMALS_OPTIMIZATION: False
     [ INFO ]   CPU_SPARSE_WEIGHTS_DECOMPRESSION_RATE: 1.0
     [Step 9/11] Creating infer requests and preparing input tensors
-
-
-.. parsed-literal::
-
     [ WARNING ] No input files were given for input 'input_values'!. This input will be filled with random values!
     [ INFO ] Fill input 'input_values' with random values
     [Step 10/11] Measuring performance (Start inference asynchronously, 6 inference requests, limits: 60000 ms duration)
@@ -815,19 +819,19 @@ models.
 
 .. parsed-literal::
 
-    [ INFO ] First inference took 56.74 ms
+    [ INFO ] First inference took 62.07 ms
 
 
 .. parsed-literal::
 
     [Step 11/11] Dumping statistics report
     [ INFO ] Execution Devices:['CPU']
-    [ INFO ] Count:            4284 iterations
-    [ INFO ] Duration:         60076.08 ms
+    [ INFO ] Count:            4296 iterations
+    [ INFO ] Duration:         60070.01 ms
     [ INFO ] Latency:
-    [ INFO ]    Median:        84.26 ms
-    [ INFO ]    Average:       83.96 ms
-    [ INFO ]    Min:           73.47 ms
-    [ INFO ]    Max:           111.27 ms
-    [ INFO ] Throughput:   71.31 FPS
+    [ INFO ]    Median:        83.98 ms
+    [ INFO ]    Average:       83.75 ms
+    [ INFO ]    Min:           45.06 ms
+    [ INFO ]    Max:           106.14 ms
+    [ INFO ] Throughput:   71.52 FPS
 
diff --git a/docs/notebooks/108-gpu-device-with-output.rst b/docs/notebooks/108-gpu-device-with-output.rst
index 8cbc04a5516bc4..dd7df6cf65c356 100644
--- a/docs/notebooks/108-gpu-device-with-output.rst
+++ b/docs/notebooks/108-gpu-device-with-output.rst
@@ -218,7 +218,7 @@ for that property.
     indent = len(max(supported_properties, key=len))
     
     for property_key in supported_properties:
-        if property_key not in ('SUPPORTED_PROPERTIES'):
+        if property_key not in ('SUPPORTED_METRICS', 'SUPPORTED_CONFIG_KEYS', 'SUPPORTED_PROPERTIES'):
             try:
                 property_val = core.get_property(device, property_key)
             except TypeError:
@@ -1337,7 +1337,7 @@ Process Results
         # Draw info at the top left such as current fps, the devices and the performance hint being used
         cv2.putText(frame, f"fps {str(round(frame_fps[current_frame], 2))}", (5, 20), cv2.FONT_ITALIC, 0.6, (0, 0, 0), 1, cv2.LINE_AA)
         cv2.putText(frame, f"device {device_name}", (5, 40), cv2.FONT_ITALIC, 0.6, (0, 0, 0), 1, cv2.LINE_AA) 
-        cv2.putText(frame, f"hint {compiled_model.get_property('PERFORMANCE_HINT').name}", (5, 60), cv2.FONT_ITALIC, 0.6, (0, 0, 0), 1, cv2.LINE_AA)
+        cv2.putText(frame, f"hint {compiled_model.get_property('PERFORMANCE_HINT')}", (5, 60), cv2.FONT_ITALIC, 0.6, (0, 0, 0), 1, cv2.LINE_AA)
     
         # prediction contains [image_id, label, conf, x_min, y_min, x_max, y_max] according to model
         for prediction in np.squeeze(results[current_frame]):
diff --git a/docs/notebooks/109-latency-tricks-with-output.rst b/docs/notebooks/109-latency-tricks-with-output.rst
index 2807705b25a488..09b0f4edeb2caf 100644
--- a/docs/notebooks/109-latency-tricks-with-output.rst
+++ b/docs/notebooks/109-latency-tricks-with-output.rst
@@ -27,7 +27,7 @@ The quantization and pre-post-processing API are not included here as
 they change the precision (quantization) or processing graph
 (prepostprocessor). You can find examples of how to apply them to
 optimize performance on OpenVINO IR files in
-`111-detection-quantization <111-yolov5-quantization-migration-with-output.html>`__ and
+`111-detection-quantization <111-detection-quantization-with-output.html>`__ and
 `118-optimize-preprocessing <118-optimize-preprocessing-with-output.html>`__.
 
 |image0|
@@ -141,7 +141,7 @@ requirements of this particular object detection model.
 
 .. parsed-literal::
 
-    
+    
 
 
 
@@ -202,62 +202,54 @@ PyTorch Hub and small enough to see the difference in performance.
 .. parsed-literal::
 
 
-  5%|▌         | 208k/3.87M [00:00<00:01, 2.11MB/s]
+  7%|▋         | 272k/3.87M [00:00<00:01, 2.23MB/s]
 
 .. parsed-literal::
 
 
- 15%|█▍        | 576k/3.87M [00:00<00:01, 3.05MB/s]
+ 19%|█▉        | 752k/3.87M [00:00<00:00, 3.64MB/s]
 
 .. parsed-literal::
 
 
- 24%|██▍       | 952k/3.87M [00:00<00:00, 3.36MB/s]
+ 29%|██▉       | 1.13M/3.87M [00:00<00:00, 3.87MB/s]
 
 .. parsed-literal::
 
 
- 33%|███▎      | 1.30M/3.87M [00:00<00:00, 3.51MB/s]
+ 39%|███▉      | 1.52M/3.87M [00:00<00:00, 3.61MB/s]
 
 .. parsed-literal::
 
 
-   43%|████▎     | 1.67M/3.87M [00:00<00:00, 3.60MB/s]
+ 49%|████▉     | 1.89M/3.87M [00:00<00:00, 3.68MB/s]
 
 .. parsed-literal::
 
 
-   52%|█████▏    | 2.02M/3.87M [00:00<00:00, 3.16MB/s]
+ 61%|██████▏   | 2.38M/3.87M [00:00<00:00, 4.06MB/s]
 
 .. parsed-literal::
 
 
-   61%|██████    | 2.36M/3.87M [00:00<00:00, 3.26MB/s]
+ 72%|███████▏  | 2.77M/3.87M [00:00<00:00, 3.82MB/s]
 
 .. parsed-literal::
 
 
-   70%|███████   | 2.72M/3.87M [00:00<00:00, 3.38MB/s]
+ 83%|████████▎ | 3.23M/3.87M [00:00<00:00, 4.07MB/s]
 
 .. parsed-literal::
 
 
-   80%|███████▉  | 3.09M/3.87M [00:00<00:00, 3.49MB/s]
+ 94%|█████████▍| 3.63M/3.87M [00:01<00:00, 3.85MB/s]
 
 .. parsed-literal::
 
 
-   89%|████████▉ | 3.46M/3.87M [00:01<00:00, 3.58MB/s]
-
-.. parsed-literal::
-
-
-   99%|█████████▉| 3.84M/3.87M [00:01<00:00, 3.67MB/s]
-
-.. parsed-literal::
+    100%|██████████| 3.87M/3.87M [00:01<00:00, 3.87MB/s]
 
 
-   100%|██████████| 3.87M/3.87M [00:01<00:00, 3.45MB/s]
 
 .. parsed-literal::
 
@@ -473,12 +465,12 @@ optimizations applied. We will treat it as our baseline.
 
 .. parsed-literal::
 
-    PyTorch model on CPU. First inference time: 0.0268 seconds
+    PyTorch model on CPU. First inference time: 0.0280 seconds
 
 
 .. parsed-literal::
 
-    PyTorch model on CPU: 0.0213 seconds per image (46.98 FPS)
+    PyTorch model on CPU: 0.0218 seconds per image (45.96 FPS)
 
 
 ONNX model
@@ -528,12 +520,12 @@ Representation (IR) to leverage the OpenVINO Runtime.
 
 .. parsed-literal::
 
-    ONNX model on CPU. First inference time: 0.0186 seconds
+    ONNX model on CPU. First inference time: 0.0174 seconds
 
 
 .. parsed-literal::
 
-    ONNX model on CPU: 0.0123 seconds per image (81.52 FPS)
+    ONNX model on CPU: 0.0136 seconds per image (73.63 FPS)
 
 
 OpenVINO IR model
@@ -570,12 +562,12 @@ accuracy drop. That’s why we skip that step in this notebook.
 
 .. parsed-literal::
 
-    OpenVINO model on CPU. First inference time: 0.0166 seconds
+    OpenVINO model on CPU. First inference time: 0.0153 seconds
 
 
 .. parsed-literal::
 
-    OpenVINO model on CPU: 0.0122 seconds per image (81.86 FPS)
+    OpenVINO model on CPU: 0.0122 seconds per image (82.17 FPS)
 
 
 OpenVINO IR model on GPU
@@ -636,12 +628,12 @@ If it is the case, don’t use it.
 
 .. parsed-literal::
 
-    OpenVINO model + more threads on CPU. First inference time: 0.0153 seconds
+    OpenVINO model + more threads on CPU. First inference time: 0.0150 seconds
 
 
 .. parsed-literal::
 
-    OpenVINO model + more threads on CPU: 0.0122 seconds per image (82.19 FPS)
+    OpenVINO model + more threads on CPU: 0.0122 seconds per image (81.82 FPS)
 
 
 OpenVINO IR model in latency mode
@@ -672,12 +664,12 @@ devices as well.
 
 .. parsed-literal::
 
-    OpenVINO model on AUTO. First inference time: 0.0154 seconds
+    OpenVINO model on AUTO. First inference time: 0.0153 seconds
 
 
 .. parsed-literal::
 
-    OpenVINO model on AUTO: 0.0125 seconds per image (80.26 FPS)
+    OpenVINO model on AUTO: 0.0125 seconds per image (80.25 FPS)
 
 
 OpenVINO IR model in latency mode + shared memory
@@ -712,12 +704,12 @@ performance!
 
 .. parsed-literal::
 
-    OpenVINO model + shared memory on AUTO. First inference time: 0.0124 seconds
+    OpenVINO model + shared memory on AUTO. First inference time: 0.0113 seconds
 
 
 .. parsed-literal::
 
-    OpenVINO model + shared memory on AUTO: 0.0054 seconds per image (184.61 FPS)
+    OpenVINO model + shared memory on AUTO: 0.0054 seconds per image (186.01 FPS)
 
 
 Other tricks
@@ -728,8 +720,8 @@ Other tricks
 There are other tricks for performance improvement, such as quantization
 and pre-post-processing or dedicated to throughput mode. To get even
 more from your model, please visit
-`111-detection-quantization <111-yolov5-quantization-migration-with-output.html>`__,
-`118-optimize-preprocessing <118-optimize-preprocessing-with-output.html>`__, and
+`111-detection-quantization <111-detection-quantization-with-output.html>`__,
+`118-optimize-preprocessing <118-optimize-preprocessing>`__, and
 `109-throughput-tricks <109-throughput-tricks-with-output.html>`__.
 
 Performance comparison
diff --git a/docs/notebooks/109-latency-tricks-with-output_files/109-latency-tricks-with-output_31_0.png b/docs/notebooks/109-latency-tricks-with-output_files/109-latency-tricks-with-output_31_0.png
index e7096858ab6ae1..e0e710e167a199 100644
--- a/docs/notebooks/109-latency-tricks-with-output_files/109-latency-tricks-with-output_31_0.png
+++ b/docs/notebooks/109-latency-tricks-with-output_files/109-latency-tricks-with-output_31_0.png
@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:4f157b7f097e536fab10e5a103ae836be062794d8d7b4f9b16185e2e6900d2f5
-size 56983
+oid sha256:ae331df2cb3993ba23bef0c441831024024f4f1f946c2da17a2ef6a2e6a68d8f
+size 52876
diff --git a/docs/notebooks/109-latency-tricks-with-output_files/index.html.tmp b/docs/notebooks/109-latency-tricks-with-output_files/index.html.tmp
deleted file mode 100644
index dd9305981383fb..00000000000000
--- a/docs/notebooks/109-latency-tricks-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,14 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/109-latency-tricks-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/109-latency-tricks-with-output_files/
../
-109-latency-tricks-with-output_15_0.jpg            26-Jan-2024 01:04              162715
-109-latency-tricks-with-output_18_0.jpg            26-Jan-2024 01:04              162715
-109-latency-tricks-with-output_20_0.jpg            26-Jan-2024 01:04              162715
-109-latency-tricks-with-output_24_0.jpg            26-Jan-2024 01:04              162715
-109-latency-tricks-with-output_26_0.jpg            26-Jan-2024 01:04              162715
-109-latency-tricks-with-output_28_0.jpg            26-Jan-2024 01:04              162715
-109-latency-tricks-with-output_31_0.png            26-Jan-2024 01:04               56983
-109-latency-tricks-with-output_5_0.jpg             26-Jan-2024 01:04              155828
-

-
diff --git a/docs/notebooks/109-throughput-tricks-with-output.rst b/docs/notebooks/109-throughput-tricks-with-output.rst
index 30bc0a347f4b33..e6bdd1c78dec55 100644
--- a/docs/notebooks/109-throughput-tricks-with-output.rst
+++ b/docs/notebooks/109-throughput-tricks-with-output.rst
@@ -24,7 +24,7 @@ The quantization and pre-post-processing API are not included here as
 they change the precision (quantization) or processing graph
 (prepostprocessor). You can find examples of how to apply them to
 optimize performance on OpenVINO IR files in
-`111-detection-quantization <111-yolov5-quantization-migration-with-output.html>`__ and
+`111-detection-quantization <111-detection-quantization-with-output.html>`__ and
 `118-optimize-preprocessing <118-optimize-preprocessing-with-output.html>`__.
 
 |image0|
@@ -93,7 +93,7 @@ Prerequisites
     import time
     from pathlib import Path
     from typing import Any, List, Tuple
-
+    
     # Fetch `notebook_utils` module
     import urllib.request
     urllib.request.urlretrieve(
@@ -116,24 +116,24 @@ object detection model.
 
     import numpy as np
     import cv2
-
+    
     FRAMES_NUMBER = 1024
-
+    
     IMAGE_WIDTH = 640
     IMAGE_HEIGHT = 480
-
+    
     # load image
     image = utils.load_image("https://storage.openvinotoolkit.org/repositories/openvino_notebooks/data/data/image/coco_bike.jpg")
     image = cv2.resize(image, dsize=(IMAGE_WIDTH, IMAGE_HEIGHT), interpolation=cv2.INTER_AREA)
-
+    
     # preprocess it for YOLOv5
     input_image = image / 255.0
     input_image = np.transpose(input_image, axes=(2, 0, 1))
     input_image = np.expand_dims(input_image, axis=0)
-
+    
     # simulate video with many frames
     video_frames = np.tile(input_image, (FRAMES_NUMBER, 1, 1, 1, 1))
-
+    
     # show the image
     utils.show_array(image)
 
@@ -146,7 +146,7 @@ object detection model.
 
 .. parsed-literal::
 
-    
+    
 
 
 
@@ -164,13 +164,13 @@ PyTorch Hub and small enough to see the difference in performance.
 
     import torch
     from IPython.utils import io
-
+    
     # directory for all models
     base_model_dir = Path("model")
-
+    
     model_name = "yolov5n"
     model_path = base_model_dir / model_name
-
+    
     # load YOLOv5n from PyTorch Hub
     pytorch_model = torch.hub.load("ultralytics/yolov5", "custom", path=model_path, device="cpu", skip_validation=True)
     # don't print full model architecture
@@ -186,12 +186,12 @@ PyTorch Hub and small enough to see the difference in performance.
 .. parsed-literal::
 
     YOLOv5 🚀 2023-4-21 Python-3.8.10 torch-2.1.0+cpu CPU
-
+    
 
 
 .. parsed-literal::
 
-    Fusing layers...
+    Fusing layers... 
 
 
 .. parsed-literal::
@@ -201,7 +201,7 @@ PyTorch Hub and small enough to see the difference in performance.
 
 .. parsed-literal::
 
-    Adding AutoShape...
+    Adding AutoShape... 
 
 
 .. parsed-literal::
@@ -223,10 +223,10 @@ benchmarking process.
 .. code:: ipython3
 
     import openvino as ov
-
+    
     # initialize OpenVINO
     core = ov.Core()
-
+    
     # print available devices
     for device in core.available_devices:
         device_name = core.get_property(device, "FULL_DEVICE_NAME")
@@ -250,8 +250,8 @@ second (FPS).
 .. code:: ipython3
 
     from openvino.runtime import AsyncInferQueue
-
-
+    
+    
     def benchmark_model(model: Any, frames: np.ndarray, async_queue: AsyncInferQueue = None, benchmark_name: str = "OpenVINO model", device_name: str = "CPU") -> float:
         """
         Helper function for benchmarking the model. It measures the time and prints results.
@@ -264,7 +264,7 @@ second (FPS).
         end = time.perf_counter()
         first_infer_time = end - start
         print(f"{benchmark_name} on {device_name}. First inference time: {first_infer_time :.4f} seconds")
-
+    
         # benchmarking
         start = time.perf_counter()
         for batch in frames:
@@ -273,15 +273,15 @@ second (FPS).
         if async_queue:
             async_queue.wait_all()
         end = time.perf_counter()
-
+    
         # elapsed time
         infer_time = end - start
-
+    
         # print second per image and FPS
         mean_infer_time = infer_time / FRAMES_NUMBER
         mean_fps = FRAMES_NUMBER / infer_time
         print(f"{benchmark_name} on {device_name}: {mean_infer_time :.4f} seconds per image ({mean_fps :.2f} FPS)")
-
+    
         return mean_fps
 
 The following functions aim to post-process results and draw boxes on
@@ -300,21 +300,21 @@ the image.
         "cell phone", "microwave", "oven", "oaster", "sink", "refrigerator", "book", "clock", "vase", "scissors", "teddy bear",
         "hair drier", "toothbrush"
     ]
-
+    
     # Colors for the classes above (Rainbow Color Map).
     colors = cv2.applyColorMap(
         src=np.arange(0, 255, 255 / len(classes), dtype=np.float32).astype(np.uint8),
         colormap=cv2.COLORMAP_RAINBOW,
     ).squeeze()
-
-
+    
+    
     def postprocess(detections: np.ndarray) -> List[Tuple]:
         """
         Postprocess the raw results from the model.
         """
         # candidates - probability > 0.25
         detections = detections[detections[..., 4] > 0.25]
-
+    
         boxes = []
         labels = []
         scores = []
@@ -328,22 +328,22 @@ the image.
             )
             labels.append(int(label))
             scores.append(float(score))
-
+    
         # Apply non-maximum suppression to get rid of many overlapping entities.
         # See https://paperswithcode.com/method/non-maximum-suppression
         # This algorithm returns indices of objects to keep.
         indices = cv2.dnn.NMSBoxes(
             bboxes=boxes, scores=scores, score_threshold=0.25, nms_threshold=0.5
         )
-
+    
         # If there are no boxes.
         if len(indices) == 0:
             return []
-
+    
         # Filter detected objects.
         return [(labels[idx], scores[idx], boxes[idx]) for idx in indices.flatten()]
-
-
+    
+    
     def draw_boxes(img: np.ndarray, boxes):
         """
         Draw detected boxes on the image.
@@ -355,7 +355,7 @@ the image.
             x2 = box[0] + box[2]
             y2 = box[1] + box[3]
             cv2.rectangle(img=img, pt1=box[:2], pt2=(x2, y2), color=color, thickness=2)
-
+    
             # Draw a label name inside the box.
             cv2.putText(
                 img=img,
@@ -367,17 +367,17 @@ the image.
                 thickness=1,
                 lineType=cv2.LINE_AA,
             )
-
-
+    
+    
     def show_result(results: np.ndarray):
         """
         Postprocess the raw results, draw boxes and show the image.
         """
         output_img = image.copy()
-
+    
         detections = postprocess(results)
         draw_boxes(output_img, detections)
-
+    
         utils.show_array(output_img)
 
 Optimizations
@@ -400,7 +400,7 @@ optimizations applied. We will treat it as our baseline.
 .. code:: ipython3
 
     import torch
-
+    
     with torch.no_grad():
         result = pytorch_model(torch.as_tensor(video_frames[0])).detach().numpy()[0]
         show_result(result)
@@ -413,12 +413,12 @@ optimizations applied. We will treat it as our baseline.
 
 .. parsed-literal::
 
-    PyTorch model on CPU. First inference time: 0.0201 seconds
+    PyTorch model on CPU. First inference time: 0.0224 seconds
 
 
 .. parsed-literal::
 
-    PyTorch model on CPU: 0.0192 seconds per image (52.19 FPS)
+    PyTorch model on CPU: 0.0221 seconds per image (45.32 FPS)
 
 
 OpenVINO IR model
@@ -438,23 +438,23 @@ step in this notebook.
 .. code:: ipython3
 
     onnx_path = base_model_dir / Path(f"{model_name}_{IMAGE_WIDTH}_{IMAGE_HEIGHT}").with_suffix(".onnx")
-
+    
     # export PyTorch model to ONNX if it doesn't already exist
     if not onnx_path.exists():
         dummy_input = torch.randn(1, 3, IMAGE_HEIGHT, IMAGE_WIDTH)
         torch.onnx.export(pytorch_model, dummy_input, onnx_path)
-
+    
     # convert ONNX model to IR, use FP16
     ov_model = ov.convert_model(onnx_path)
 
 .. code:: ipython3
 
     ov_cpu_model = core.compile_model(ov_model, device_name="CPU")
-
+    
     result = ov_cpu_model(video_frames[0])[ov_cpu_model.output(0)][0]
     show_result(result)
     ov_cpu_fps = benchmark_model(model=ov_cpu_model, frames=video_frames, benchmark_name="OpenVINO model")
-
+    
     del ov_cpu_model  # release resources
 
 
@@ -464,12 +464,12 @@ step in this notebook.
 
 .. parsed-literal::
 
-    OpenVINO model on CPU. First inference time: 0.0134 seconds
+    OpenVINO model on CPU. First inference time: 0.0142 seconds
 
 
 .. parsed-literal::
 
-    OpenVINO model on CPU: 0.0070 seconds per image (142.35 FPS)
+    OpenVINO model on CPU: 0.0071 seconds per image (141.49 FPS)
 
 
 OpenVINO IR model + bigger batch
@@ -488,13 +488,13 @@ hardware and model.
 .. code:: ipython3
 
     batch_size = 4
-
+    
     onnx_batch_path = base_model_dir / Path(f"{model_name}_{IMAGE_WIDTH}_{IMAGE_HEIGHT}_batch_{batch_size}").with_suffix(".onnx")
-
+    
     if not onnx_batch_path.exists():
         dummy_input = torch.randn(batch_size, 3, IMAGE_HEIGHT, IMAGE_WIDTH)
         torch.onnx.export(pytorch_model, dummy_input, onnx_batch_path)
-
+    
     # export the model with the bigger batch size
     ov_batch_model = ov.convert_model(onnx_batch_path)
 
@@ -510,13 +510,13 @@ hardware and model.
 .. code:: ipython3
 
     ov_cpu_batch_model = core.compile_model(ov_batch_model, device_name="CPU")
-
+    
     batched_video_frames = video_frames.reshape([-1, batch_size, 3, IMAGE_HEIGHT, IMAGE_WIDTH])
-
+    
     result = ov_cpu_batch_model(batched_video_frames[0])[ov_cpu_batch_model.output(0)][0]
     show_result(result)
     ov_cpu_batch_fps = benchmark_model(model=ov_cpu_batch_model, frames=batched_video_frames, benchmark_name="OpenVINO model + bigger batch")
-
+    
     del ov_cpu_batch_model  # release resources
 
 
@@ -526,12 +526,12 @@ hardware and model.
 
 .. parsed-literal::
 
-    OpenVINO model + bigger batch on CPU. First inference time: 0.0435 seconds
+    OpenVINO model + bigger batch on CPU. First inference time: 0.0486 seconds
 
 
 .. parsed-literal::
 
-    OpenVINO model + bigger batch on CPU: 0.0068 seconds per image (147.59 FPS)
+    OpenVINO model + bigger batch on CPU: 0.0068 seconds per image (146.44 FPS)
 
 
 Asynchronous processing
@@ -561,17 +561,17 @@ the pipeline.
             result = infer_request.get_output_tensor(0).data[0]
             show_result(result)
             pass
-
+    
         infer_queue = ov.AsyncInferQueue(ov_model)
         infer_queue.set_callback(callback)  # set callback to post-process (show) results
-
+    
         infer_queue.start_async(video_frames[0])
         infer_queue.wait_all()
-
+    
         # don't show output for the remaining frames
         infer_queue.set_callback(lambda x, y: {})
         fps = benchmark_model(model=infer_queue.start_async, frames=video_frames, async_queue=infer_queue, benchmark_name=benchmark_name, device_name=device_name)
-
+    
         del infer_queue  # release resources
         return fps
 
@@ -592,9 +592,9 @@ feature, which sets the batch size to the optimal level.
 .. code:: ipython3
 
     ov_cpu_through_model = core.compile_model(ov_model, device_name="CPU", config={"PERFORMANCE_HINT": "THROUGHPUT"})
-
+    
     ov_cpu_through_fps = benchmark_async_mode(ov_cpu_through_model, benchmark_name="OpenVINO model", device_name="CPU (THROUGHPUT)")
-
+    
     del ov_cpu_through_model  # release resources
 
 
@@ -604,12 +604,12 @@ feature, which sets the batch size to the optimal level.
 
 .. parsed-literal::
 
-    OpenVINO model on CPU (THROUGHPUT). First inference time: 0.0260 seconds
+    OpenVINO model on CPU (THROUGHPUT). First inference time: 0.0221 seconds
 
 
 .. parsed-literal::
 
-    OpenVINO model on CPU (THROUGHPUT): 0.0040 seconds per image (248.03 FPS)
+    OpenVINO model on CPU (THROUGHPUT): 0.0040 seconds per image (249.65 FPS)
 
 
 OpenVINO IR model in throughput mode on GPU
@@ -633,9 +633,9 @@ execution.
     if "GPU" in core.available_devices:
         # compile for GPU
         ov_gpu_model = core.compile_model(ov_model, device_name="GPU", config={"PERFORMANCE_HINT": "THROUGHPUT"})
-
+    
         ov_gpu_fps = benchmark_async_mode(ov_gpu_model, benchmark_name="OpenVINO model", device_name="GPU (THROUGHPUT)")
-
+    
         del ov_gpu_model  # release resources
 
 OpenVINO IR model in throughput mode on AUTO
@@ -651,9 +651,9 @@ performance hint.
 .. code:: ipython3
 
     ov_auto_model = core.compile_model(ov_model, device_name="AUTO", config={"PERFORMANCE_HINT": "THROUGHPUT"})
-
+    
     ov_auto_fps = benchmark_async_mode(ov_auto_model, benchmark_name="OpenVINO model", device_name="AUTO (THROUGHPUT)")
-
+    
     del ov_auto_model  # release resources
 
 
@@ -663,12 +663,12 @@ performance hint.
 
 .. parsed-literal::
 
-    OpenVINO model on AUTO (THROUGHPUT). First inference time: 0.0244 seconds
+    OpenVINO model on AUTO (THROUGHPUT). First inference time: 0.0235 seconds
 
 
 .. parsed-literal::
 
-    OpenVINO model on AUTO (THROUGHPUT): 0.0040 seconds per image (250.62 FPS)
+    OpenVINO model on AUTO (THROUGHPUT): 0.0040 seconds per image (249.90 FPS)
 
 
 OpenVINO IR model in cumulative throughput mode on AUTO
@@ -685,7 +685,7 @@ activate all devices.
 .. code:: ipython3
 
     ov_auto_cumulative_model = core.compile_model(ov_model, device_name="AUTO", config={"PERFORMANCE_HINT": "CUMULATIVE_THROUGHPUT"})
-
+    
     ov_auto_cumulative_fps = benchmark_async_mode(ov_auto_cumulative_model, benchmark_name="OpenVINO model", device_name="AUTO (CUMULATIVE THROUGHPUT)")
 
 
@@ -695,12 +695,12 @@ activate all devices.
 
 .. parsed-literal::
 
-    OpenVINO model on AUTO (CUMULATIVE THROUGHPUT). First inference time: 0.0211 seconds
+    OpenVINO model on AUTO (CUMULATIVE THROUGHPUT). First inference time: 0.0227 seconds
 
 
 .. parsed-literal::
 
-    OpenVINO model on AUTO (CUMULATIVE THROUGHPUT): 0.0040 seconds per image (249.40 FPS)
+    OpenVINO model on AUTO (CUMULATIVE THROUGHPUT): 0.0040 seconds per image (250.47 FPS)
 
 
 Other tricks
@@ -714,7 +714,7 @@ mode. To get even more from your model, please visit `advanced
 throughput
 options `__,
 `109-latency-tricks <109-latency-tricks-with-output.html-with-output.html>`__,
-`111-detection-quantization <111-yolov5-quantization-migration-with-output.html>`__, and
+`111-detection-quantization <111-detection-quantization-with-output.html>`__, and
 `118-optimize-preprocessing <118-optimize-preprocessing-with-output.html>`__.
 
 Performance comparison
@@ -733,20 +733,20 @@ steps, just skip them.
 .. code:: ipython3
 
     from matplotlib import pyplot as plt
-
+    
     labels = ["PyTorch model", "OpenVINO IR model", "OpenVINO IR model + bigger batch", "OpenVINO IR model in throughput mode", "OpenVINO IR model in throughput mode on GPU",
               "OpenVINO IR model in throughput mode on AUTO", "OpenVINO IR model in cumulative throughput mode on AUTO"]
-
+    
     fps = [pytorch_fps, ov_cpu_fps, ov_cpu_batch_fps, ov_cpu_through_fps, ov_gpu_fps, ov_auto_fps, ov_auto_cumulative_fps]
-
+    
     bar_colors = colors[::10] / 255.0
-
+    
     fig, ax = plt.subplots(figsize=(16, 8))
     ax.bar(labels, fps, color=bar_colors)
-
+    
     ax.set_ylabel("Throughput [FPS]")
     ax.set_title("Performance difference")
-
+    
     plt.xticks(rotation='vertical')
     plt.show()
 
diff --git a/docs/notebooks/109-throughput-tricks-with-output_files/109-throughput-tricks-with-output_34_0.png b/docs/notebooks/109-throughput-tricks-with-output_files/109-throughput-tricks-with-output_34_0.png
index 94ae506479a8a3..b8a8311684201b 100644
--- a/docs/notebooks/109-throughput-tricks-with-output_files/109-throughput-tricks-with-output_34_0.png
+++ b/docs/notebooks/109-throughput-tricks-with-output_files/109-throughput-tricks-with-output_34_0.png
@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:8e1932b29ece3712ada3af1ea8df832692a5416111c7caeb3c884cd3ee628110
-size 62463
+oid sha256:c054b14da27759eeaf1a1791c919f28eade5a92ea995b1f07690c71c435b2092
+size 62458
diff --git a/docs/notebooks/109-throughput-tricks-with-output_files/index.html.tmp b/docs/notebooks/109-throughput-tricks-with-output_files/index.html.tmp
deleted file mode 100644
index ae0eb640611eec..00000000000000
--- a/docs/notebooks/109-throughput-tricks-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,14 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/109-throughput-tricks-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/109-throughput-tricks-with-output_files/
../
-109-throughput-tricks-with-output_15_0.jpg         26-Jan-2024 01:05              162715
-109-throughput-tricks-with-output_18_0.jpg         26-Jan-2024 01:05              162715
-109-throughput-tricks-with-output_21_0.jpg         26-Jan-2024 01:05              162715
-109-throughput-tricks-with-output_25_0.jpg         26-Jan-2024 01:05              162715
-109-throughput-tricks-with-output_29_0.jpg         26-Jan-2024 01:05              162715
-109-throughput-tricks-with-output_31_0.jpg         26-Jan-2024 01:05              162715
-109-throughput-tricks-with-output_34_0.png         26-Jan-2024 01:05               62463
-109-throughput-tricks-with-output_5_0.jpg          26-Jan-2024 01:05              155828
-

-
diff --git a/docs/notebooks/110-ct-scan-live-inference-with-output.rst b/docs/notebooks/110-ct-scan-live-inference-with-output.rst
index c430e11166a8a2..032eeb9b77d544 100644
--- a/docs/notebooks/110-ct-scan-live-inference-with-output.rst
+++ b/docs/notebooks/110-ct-scan-live-inference-with-output.rst
@@ -18,7 +18,7 @@ This notebook needs a quantized OpenVINO IR model and images from the
 `KiTS-19 `__ dataset, converted to
 2D images. (To learn how the model is quantized, see the `Convert and
 Quantize a UNet Model and Show Live
-Inference <110-ct-segmentation-quantize-nncf-with-output.html>`__ tutorial.)
+Inference <110-ct-segmentation-quantize-nncf.ipynb>`__ tutorial.)
 
 This notebook provides a pre-trained model, trained for 20 epochs with
 the full KiTS-19 frames dataset, which has an F1 score on the validation
@@ -80,14 +80,14 @@ Imports
 
 .. parsed-literal::
 
-    2024-01-25 22:50:13.572016: I tensorflow/core/util/port.cc:110] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
-    2024-01-25 22:50:13.606068: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+    2024-02-09 22:50:38.323593: I tensorflow/core/util/port.cc:110] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
+    2024-02-09 22:50:38.357752: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
     To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
 
 
 .. parsed-literal::
 
-    2024-01-25 22:50:14.166493: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+    2024-02-09 22:50:38.922511: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
 
 
 Settings
@@ -140,7 +140,7 @@ Tool `__
 is a command-line application that can be run in the notebook with
 ``! benchmark_app`` or ``%sx benchmark_app`` commands.
 
-   **Note**: The ``benchmark_app`` tool is able to measure the
+   **NOTE**: The ``benchmark_app`` tool is able to measure the
    performance of the OpenVINO Intermediate Representation (OpenVINO IR)
    models only. For more accurate performance, run ``benchmark_app`` in
    a terminal/command prompt after closing other applications. Run
@@ -198,7 +198,7 @@ is a command-line application that can be run in the notebook with
     [ WARNING ] Performance hint was not explicitly specified in command line. Device(AUTO) performance hint will be set to PerformanceMode.LATENCY.
     [Step 4/11] Reading model files
     [ INFO ] Loading model files
-    [ INFO ] Read model took 13.17 ms
+    [ INFO ] Read model took 13.02 ms
     [ INFO ] Original model I/O parameters:
     [ INFO ] Model inputs:
     [ INFO ]     input.1 (node: input.1) : f32 / [...] / [1,1,512,512]
@@ -216,7 +216,7 @@ is a command-line application that can be run in the notebook with
 
 .. parsed-literal::
 
-    [ INFO ] Compile model took 235.31 ms
+    [ INFO ] Compile model took 232.64 ms
     [Step 8/11] Querying optimal runtime parameters
     [ INFO ] Model:
     [ INFO ]   NETWORK_NAME: pretrained_unet_kits19
@@ -252,21 +252,21 @@ is a command-line application that can be run in the notebook with
 
 .. parsed-literal::
 
-    [ INFO ] First inference took 24.14 ms
+    [ INFO ] First inference took 24.68 ms
 
 
 .. parsed-literal::
 
     [Step 11/11] Dumping statistics report
     [ INFO ] Execution Devices:['CPU']
-    [ INFO ] Count:            1355 iterations
-    [ INFO ] Duration:         15007.81 ms
+    [ INFO ] Count:            1366 iterations
+    [ INFO ] Duration:         15004.33 ms
     [ INFO ] Latency:
-    [ INFO ]    Median:        10.84 ms
-    [ INFO ]    Average:       10.89 ms
-    [ INFO ]    Min:           10.58 ms
-    [ INFO ]    Max:           14.29 ms
-    [ INFO ] Throughput:   90.29 FPS
+    [ INFO ]    Median:        10.75 ms
+    [ INFO ]    Average:       10.80 ms
+    [ INFO ]    Min:           10.53 ms
+    [ INFO ]    Max:           12.59 ms
+    [ INFO ] Throughput:   91.04 FPS
 
 
 Download and Prepare Data
@@ -503,7 +503,7 @@ Create asynchronous inference queue and perform it
 
 .. parsed-literal::
 
-    Loaded model to Dropdown(description='Device:', index=1, options=('CPU', 'AUTO'), value='AUTO') in 0.24 seconds.
-    Total time to infer all frames: 2.762s
-    Time per frame: 0.040619s (24.619 FPS)
+    Loaded model to Dropdown(description='Device:', index=1, options=('CPU', 'AUTO'), value='AUTO') in 0.23 seconds.
+    Total time to infer all frames: 2.588s
+    Time per frame: 0.038061s (26.274 FPS)
 
diff --git a/docs/notebooks/110-ct-scan-live-inference-with-output_files/index.html.tmp b/docs/notebooks/110-ct-scan-live-inference-with-output_files/index.html.tmp
deleted file mode 100644
index d4e68e78ccfe66..00000000000000
--- a/docs/notebooks/110-ct-scan-live-inference-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,7 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/110-ct-scan-live-inference-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/110-ct-scan-live-inference-with-output_files/
../
-110-ct-scan-live-inference-with-output_21_0.png    26-Jan-2024 01:05               48780
-

-
diff --git a/docs/notebooks/110-ct-segmentation-quantize-nncf-with-output.rst b/docs/notebooks/110-ct-segmentation-quantize-nncf-with-output.rst
index 7191f618fd9cef..bc414952359c03 100644
--- a/docs/notebooks/110-ct-segmentation-quantize-nncf-with-output.rst
+++ b/docs/notebooks/110-ct-segmentation-quantize-nncf-with-output.rst
@@ -24,9 +24,9 @@ This third tutorial in the series shows how to:
 All notebooks in this series:
 
 -  `Data Preparation for 2D Segmentation of 3D Medical
-   Data `__
+   Data `__
 -  `Train a 2D-UNet Medical Imaging Model with PyTorch
-   Lightning `__
+   Lightning `__
 -  Convert and Quantize a Segmentation Model and Show Live Inference
    (this notebook)
 -  `Live Inference and Benchmark CT-scan
@@ -39,7 +39,7 @@ This notebook needs a trained UNet model. We provide a pre-trained
 model, trained for 20 epochs with the full
 `Kits-19 `__ frames dataset, which
 has an F1 score on the validation set of 0.9. The training code is
-available in `this notebook `__.
+available in `this notebook `__.
 
 NNCF for PyTorch models requires a C++ compiler. On Windows, install
 `Microsoft Visual Studio
@@ -182,14 +182,14 @@ Imports
 
 .. parsed-literal::
 
-    2024-01-25 22:50:47.254337: I tensorflow/core/util/port.cc:110] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
-    2024-01-25 22:50:47.287377: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+    2024-02-09 22:51:11.599112: I tensorflow/core/util/port.cc:110] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
+    2024-02-09 22:51:11.634091: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
     To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
 
 
 .. parsed-literal::
 
-    2024-01-25 22:50:47.852256: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+    2024-02-09 22:51:12.223414: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
 
 
 .. parsed-literal::
@@ -205,7 +205,7 @@ Settings
 By default, this notebook will download one CT scan from the KITS19
 dataset that will be used for quantization. To use the full dataset, set
 ``BASEDIR`` to the path of the dataset, as prepared according to the
-`Data Preparation `__ notebook.
+`Data Preparation `__ notebook.
 
 .. code:: ipython3
 
@@ -226,7 +226,7 @@ notebook is a
 `BasicUNet `__
 model from `MONAI `__. We provide a pre-trained
 checkpoint. To see how this model performs, check out the `training
-notebook `__.
+notebook `__.
 
 .. code:: ipython3
 
@@ -304,7 +304,7 @@ Dataset
 The ``KitsDataset`` class in the next cell expects images and masks in
 the *``basedir``* directory, in a folder per patient. It is a simplified
 version of the Dataset class in the `training
-notebook `__.
+notebook `__.
 
 Images are loaded with MONAI’s
 `LoadImage `__,
@@ -481,7 +481,7 @@ this notebook.
 
 .. parsed-literal::
 
-    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/monai/networks/nets/basic_unet.py:179: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
+    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/monai/networks/nets/basic_unet.py:179: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
       if x_e.shape[-i - 1] != x_0.shape[-i - 1]:
 
 
@@ -489,7 +489,7 @@ this notebook.
 advanced algorithms for Neural Networks inference optimization in
 OpenVINO with minimal accuracy drop.
 
-   **Note**: NNCF Post-training Quantization is available in OpenVINO
+   **NOTE**: NNCF Post-training Quantization is available in OpenVINO
    2023.0 release.
 
 Create a quantized model from the pre-trained ``FP32`` model and the
@@ -532,13 +532,15 @@ steps:
 
 
 
-.. raw:: html
 
-    

 
 
 
 
+.. raw:: html
+
+    
+    

 
 
 
@@ -549,14 +551,15 @@ steps:
 
 
 
-.. raw:: html
 
-    

 
 
 
 
+.. raw:: html
 
+    
+    

 
 
 
@@ -575,11 +578,11 @@ model and save it.
 
 .. parsed-literal::
 
-    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/nncf/torch/quantization/layers.py:334: TracerWarning: Converting a tensor to a Python number might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
+    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/nncf/torch/quantization/layers.py:334: TracerWarning: Converting a tensor to a Python number might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
       return self._level_low.item()
-    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/nncf/torch/quantization/layers.py:342: TracerWarning: Converting a tensor to a Python number might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
+    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/nncf/torch/quantization/layers.py:342: TracerWarning: Converting a tensor to a Python number might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
       return self._level_high.item()
-    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/monai/networks/nets/basic_unet.py:179: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
+    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/monai/networks/nets/basic_unet.py:179: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
       if x_e.shape[-i - 1] != x_0.shape[-i - 1]:
 
 
@@ -692,7 +695,7 @@ be run in the notebook with ``! benchmark_app`` or
     [ WARNING ] Performance hint was not explicitly specified in command line. Device(CPU) performance hint will be set to PerformanceMode.LATENCY.
     [Step 4/11] Reading model files
     [ INFO ] Loading model files
-    [ INFO ] Read model took 26.68 ms
+    [ INFO ] Read model took 26.51 ms
     [ INFO ] Original model I/O parameters:
     [ INFO ] Model inputs:
     [ INFO ]     x (node: x) : f32 / [...] / [?,?,?,?]
@@ -710,7 +713,7 @@ be run in the notebook with ``! benchmark_app`` or
 
 .. parsed-literal::
 
-    [ INFO ] Compile model took 86.15 ms
+    [ INFO ] Compile model took 87.61 ms
     [Step 8/11] Querying optimal runtime parameters
     [ INFO ] Model:
     [ INFO ]   NETWORK_NAME: Model0
@@ -732,9 +735,9 @@ be run in the notebook with ``! benchmark_app`` or
     [Step 9/11] Creating infer requests and preparing input tensors
     [ ERROR ] Input x is dynamic. Provide data shapes!
     Traceback (most recent call last):
-      File "/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/openvino/tools/benchmark/main.py", line 486, in main
+      File "/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/openvino/tools/benchmark/main.py", line 486, in main
         data_queue = get_input_data(paths_to_input, app_inputs_info)
-      File "/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/openvino/tools/benchmark/utils/inputs_filling.py", line 123, in get_input_data
+      File "/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/openvino/tools/benchmark/utils/inputs_filling.py", line 123, in get_input_data
         raise Exception(f"Input {info.name} is dynamic. Provide data shapes!")
     Exception: Input x is dynamic. Provide data shapes!
 
@@ -762,7 +765,7 @@ be run in the notebook with ``! benchmark_app`` or
     [ WARNING ] Performance hint was not explicitly specified in command line. Device(CPU) performance hint will be set to PerformanceMode.LATENCY.
     [Step 4/11] Reading model files
     [ INFO ] Loading model files
-    [ INFO ] Read model took 13.10 ms
+    [ INFO ] Read model took 13.17 ms
     [ INFO ] Original model I/O parameters:
     [ INFO ] Model inputs:
     [ INFO ]     x.1 (node: x.1) : f32 / [...] / [1,1,512,512]
@@ -772,10 +775,6 @@ be run in the notebook with ``! benchmark_app`` or
     [ INFO ] Model batch size: 1
     [Step 6/11] Configuring input of the model
     [ INFO ] Model inputs:
-
-
-.. parsed-literal::
-
     [ INFO ]     x.1 (node: x.1) : f32 / [N,C,H,W] / [1,1,512,512]
     [ INFO ] Model outputs:
     [ INFO ]     571 (node: 571) : f32 / [...] / [1,1,512,512]
@@ -784,7 +783,7 @@ be run in the notebook with ``! benchmark_app`` or
 
 .. parsed-literal::
 
-    [ INFO ] Compile model took 188.53 ms
+    [ INFO ] Compile model took 190.56 ms
     [Step 8/11] Querying optimal runtime parameters
     [ INFO ] Model:
     [ INFO ]   NETWORK_NAME: main_graph
@@ -812,21 +811,21 @@ be run in the notebook with ``! benchmark_app`` or
 
 .. parsed-literal::
 
-    [ INFO ] First inference took 30.02 ms
+    [ INFO ] First inference took 30.25 ms
 
 
 .. parsed-literal::
 
     [Step 11/11] Dumping statistics report
     [ INFO ] Execution Devices:['CPU']
-    [ INFO ] Count:            964 iterations
-    [ INFO ] Duration:         15009.54 ms
+    [ INFO ] Count:            973 iterations
+    [ INFO ] Duration:         15006.05 ms
     [ INFO ] Latency:
-    [ INFO ]    Median:        15.33 ms
-    [ INFO ]    Average:       15.36 ms
-    [ INFO ]    Min:           14.97 ms
-    [ INFO ]    Max:           17.10 ms
-    [ INFO ] Throughput:   64.23 FPS
+    [ INFO ]    Median:        15.16 ms
+    [ INFO ]    Average:       15.22 ms
+    [ INFO ]    Min:           14.87 ms
+    [ INFO ]    Max:           17.88 ms
+    [ INFO ] Throughput:   64.84 FPS
 
 
 Visually Compare Inference Results
@@ -911,7 +910,7 @@ seed is displayed to enable reproducing specific runs of this cell.
 
 .. parsed-literal::
 
-    Visualizing results with seed 1706219510
+    Visualizing results with seed 1707515536
 
 
 
@@ -994,8 +993,8 @@ performs inference, and displays the results on the frames loaded in
 
 .. parsed-literal::
 
-    Loaded model to CPU in 0.21 seconds.
-    Total time for 68 frames: 2.62 seconds, fps:26.34
+    Loaded model to CPU in 0.18 seconds.
+    Total time for 68 frames: 2.68 seconds, fps:25.70
 
 
 References
@@ -1003,16 +1002,20 @@ References
 
 
 
-**OpenVINO**
-
-- `NNCF Repository `__
-- `Neural Network Compression Framework for fast model inference `__
-- `OpenVINO API Tutorial <002-openvino-api-with-output.html>`__
-- `OpenVINO PyPI (pip install openvino-dev) `__
-
-**Kits19 Data**
-
-- `Kits19 Challenge Homepage `__
-- `Kits19 GitHub Repository `__
-- `The KiTS19 Challenge Data: 300 Kidney Tumor Cases with Clinical Context, CT Semantic Segmentations, and Surgical Outcomes `__
-- `The state of the art in kidney and kidney tumor segmentation in contrast-enhanced CT imaging: Results of the KiTS19 challenge `__
+**OpenVINO** - `NNCF
+Repository `__ - `Neural
+Network Compression Framework for fast model
+inference `__ - `OpenVINO API
+Tutorial <002-openvino-api-with-output.html>`__ - `OpenVINO
+PyPI (pip install
+openvino-dev) `__
+
+**Kits19 Data** - `Kits19 Challenge
+Homepage `__ - `Kits19 GitHub
+Repository `__ - `The KiTS19
+Challenge Data: 300 Kidney Tumor Cases with Clinical Context, CT
+Semantic Segmentations, and Surgical
+Outcomes `__ - `The state of the art
+in kidney and kidney tumor segmentation in contrast-enhanced CT imaging:
+Results of the KiTS19
+challenge `__
diff --git a/docs/notebooks/110-ct-segmentation-quantize-nncf-with-output_files/110-ct-segmentation-quantize-nncf-with-output_37_1.png b/docs/notebooks/110-ct-segmentation-quantize-nncf-with-output_files/110-ct-segmentation-quantize-nncf-with-output_37_1.png
index dda61ec5eb8c8c..f8b899fb48e2d9 100644
--- a/docs/notebooks/110-ct-segmentation-quantize-nncf-with-output_files/110-ct-segmentation-quantize-nncf-with-output_37_1.png
+++ b/docs/notebooks/110-ct-segmentation-quantize-nncf-with-output_files/110-ct-segmentation-quantize-nncf-with-output_37_1.png
@@ -1,3 +1,3 @@
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-oid sha256:8b31829da55a95766d9f5f4e8b93cec1e5bac3f1147fd2a5cea2e8d7f7b12abc
-size 386985
+oid sha256:fa3a987453cb9be2a1e6e3c9d6ef943c29914c0a1f740e2eac55ebad8bc9ac4a
+size 387367
diff --git a/docs/notebooks/110-ct-segmentation-quantize-nncf-with-output_files/index.html.tmp b/docs/notebooks/110-ct-segmentation-quantize-nncf-with-output_files/index.html.tmp
deleted file mode 100644
index 52627ffd092603..00000000000000
--- a/docs/notebooks/110-ct-segmentation-quantize-nncf-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,9 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/110-ct-segmentation-quantize-nncf-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/110-ct-segmentation-quantize-nncf-with-output_files/
../
-110-ct-segmentation-quantize-nncf-with-output_1..> 26-Jan-2024 01:05              158997
-110-ct-segmentation-quantize-nncf-with-output_3..> 26-Jan-2024 01:05              386985
-110-ct-segmentation-quantize-nncf-with-output_4..> 26-Jan-2024 01:05               73812
-

-
diff --git a/docs/notebooks/111-yolov5-quantization-migration-with-output.rst b/docs/notebooks/111-yolov5-quantization-migration-with-output.rst
deleted file mode 100644
index b3093fe2638c5b..00000000000000
--- a/docs/notebooks/111-yolov5-quantization-migration-with-output.rst
+++ /dev/null
@@ -1,2708 +0,0 @@
-Migrate quantization from POT API to NNCF API
-=============================================
-
-This tutorial demonstrates how to migrate quantization pipeline written
-using the OpenVINO `Post-Training Optimization Tool
-(POT) `__ to
-`NNCF Post-Training Quantization
-API `__.
-This tutorial is based on `Ultralytics
-YOLOv5 `__ model and additionally
-it compares model accuracy between the FP32 precision and quantized INT8
-precision models and runs a demo of model inference based on sample code
-from `Ultralytics YOLOv5 `__ with
-the OpenVINO backend.
-
-The tutorial consists from the following parts:
-
-1. Convert YOLOv5 model to OpenVINO IR.
-2. Prepare dataset for quantization.
-3. Configure quantization pipeline.
-4. Perform model optimization.
-5. Compare accuracy FP32 and INT8 models
-6. Run model inference demo
-7. Compare performance FP32 and INT8 models
-
-Table of contents:
-^^^^^^^^^^^^^^^^^^
-
--  `Preparation <#preparation>`__
-
-   -  `Download the YOLOv5 model <#download-the-yolov5-model>`__
-   -  `Conversion of the YOLOv5 model to
-      OpenVINO <#conversion-of-the-yolov5-model-to-openvino>`__
-   -  `Imports <#imports>`__
-
--  `Prepare dataset for
-   quantization <#prepare-dataset-for-quantization>`__
-
-   -  `Create YOLOv5 DataLoader class for
-      POT <#create-yolov5-dataloader-class-for-pot>`__
-   -  `Create NNCF Dataset <#create-nncf-dataset>`__
-
--  `Configure quantization
-   pipeline <#configure-quantization-pipeline>`__
-
-   -  `Prepare config and pipeline for
-      POT <#prepare-config-and-pipeline-for-pot>`__
-   -  `Prepare configuration parameters for
-      NNCF <#prepare-configuration-parameters-for-nncf>`__
-
--  `Perform model optimization <#perform-model-optimization>`__
-
-   -  `Run quantization using POT <#run-quantization-using-pot>`__
-   -  `Run quantization using NNCF <#run-quantization-using-nncf>`__
-
--  `Compare accuracy FP32 and INT8
-   models <#compare-accuracy-fp32-and-int8-models>`__
--  `Inference Demo Performance
-   Comparison <#inference-demo-performance-comparison>`__
--  `Benchmark <#benchmark>`__
--  `References <#references>`__
-
-Preparation
------------
-
-
-
-Download the YOLOv5 model
-~~~~~~~~~~~~~~~~~~~~~~~~~
-
-
-
-.. code:: ipython3
-
-    %pip install -q "openvino-dev>=2023.1.0" "nncf>=2.5.0"
-    %pip install -q psutil "seaborn>=0.11.0" matplotlib numpy onnx
-
-
-.. parsed-literal::
-
-    Note: you may need to restart the kernel to use updated packages.
-
-
-.. parsed-literal::
-
-    Note: you may need to restart the kernel to use updated packages.
-
-
-.. code:: ipython3
-
-    import sys
-    import numpy as np
-    import matplotlib.pyplot as plt
-    from pathlib import Path
-    from IPython.display import Markdown, display
-
-    if not Path("./yolov5/").exists():
-        command_download = (
-            f'{"git clone https://github.com/ultralytics/yolov5.git -b v7.0"}'
-        )
-        command_download = " ".join(command_download.split())
-        print("Download Ultralytics Yolov5 project source:")
-        display(Markdown(f"`{command_download}`"))
-        download_res = %sx $command_download
-    else:
-        print("Ultralytics Yolov5 repo already exists.")
-
-
-.. parsed-literal::
-
-    Download Ultralytics Yolov5 project source:
-
-
-
-``git clone https://github.com/ultralytics/yolov5.git -b v7.0``
-
-
-Conversion of the YOLOv5 model to OpenVINO
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-
-
-There are three variables provided for easy run through all the notebook
-cells.
-
--  ``IMAGE_SIZE`` - the image size for model input.
--  ``MODEL_NAME`` - the model you want to use. It can be either yolov5s,
-   yolov5m or yolov5l and so on.
--  ``MODEL_PATH`` - to the path of the model directory in the YOLOv5
-   repository.
-
-YOLOv5 ``export.py`` scripts support multiple model formats for
-conversion. ONNX is also represented among supported formats. We need to
-specify ``--include ONNX`` parameter for exporting. As the result,
-directory with the ``{MODEL_NAME}`` name will be created with the
-following content:
-
--  ``{MODEL_NAME}.pt`` - the downloaded pre-trained weight.
--  ``{MODEL_NAME}.onnx`` - the Open Neural Network Exchange (ONNX) is an
-   open format, built to represent machine learning models.
-
-.. code:: ipython3
-
-    IMAGE_SIZE = 640
-    MODEL_NAME = "yolov5m"
-    MODEL_PATH = f"yolov5/{MODEL_NAME}"
-
-.. code:: ipython3
-
-    print("Convert PyTorch model to OpenVINO Model:")
-    command_export = f"cd yolov5 && python export.py --weights {MODEL_NAME}/{MODEL_NAME}.pt --imgsz {IMAGE_SIZE} --batch-size 1 --include ONNX"
-    display(Markdown(f"`{command_export}`"))
-    ! $command_export
-
-
-.. parsed-literal::
-
-    Convert PyTorch model to OpenVINO Model:
-
-
-
-``cd yolov5 && python export.py --weights yolov5m/yolov5m.pt --imgsz 640 --batch-size 1 --include ONNX``
-
-
-.. parsed-literal::
-
-    export: data=data/coco128.yaml, weights=['yolov5m/yolov5m.pt'], imgsz=[640], batch_size=1, device=cpu, half=False, inplace=False, keras=False, optimize=False, int8=False, dynamic=False, simplify=False, opset=12, verbose=False, workspace=4, nms=False, agnostic_nms=False, topk_per_class=100, topk_all=100, iou_thres=0.45, conf_thres=0.25, include=['ONNX']
-
-
-.. parsed-literal::
-
-    YOLOv5 🚀 v7.0-0-g915bbf2 Python-3.8.10 torch-2.1.0+cpu CPU
-
-
-
-.. parsed-literal::
-
-    Downloading https://github.com/ultralytics/yolov5/releases/download/v7.0/yolov5m.pt to yolov5m/yolov5m.pt...
-
-
-.. parsed-literal::
-
-
-  0%|                                               | 0.00/40.8M [00:00`__.
-We will use the ``ov.convert_model`` function of model conversion Python
-API to convert ONNX model to OpenVINO Model, then it can be serialized
-using ``ov.save_model``. As the result, directory with the
-``{MODEL_DIR}`` name will be created with the following content: \*
-``{MODEL_NAME}_fp32.xml``, ``{MODEL_NAME}_fp32.bin`` - OpenVINO
-Intermediate Representation (IR) model generated by `Model Conversion
-API `__,
-saved with FP32 precision. \* ``{MODEL_NAME}_fp16.xml``,
-``{MODEL_NAME}_fp16.bin`` - OpenVINO Intermediate Representation (IR)
-model generated by `Model Conversion
-API `__,
-saved with FP16 precision.
-
-.. code:: ipython3
-
-    import openvino as ov
-
-    onnx_path = f"{MODEL_PATH}/{MODEL_NAME}.onnx"
-
-    # fp32 IR model
-    fp32_path = f"{MODEL_PATH}/FP32_openvino_model/{MODEL_NAME}_fp32.xml"
-
-    print(f"Export ONNX to OpenVINO FP32 IR to: {fp32_path}")
-    model = ov.convert_model(onnx_path)
-    ov.save_model(model, fp32_path, compress_to_fp16=False)
-
-    # fp16 IR model
-    fp16_path = f"{MODEL_PATH}/FP16_openvino_model/{MODEL_NAME}_fp16.xml"
-
-    print(f"Export ONNX to OpenVINO FP16 IR to: {fp16_path}")
-    model = ov.convert_model(onnx_path)
-    ov.save_model(model, fp16_path, compress_to_fp16=True)
-
-
-.. parsed-literal::
-
-    Export ONNX to OpenVINO FP32 IR to: yolov5/yolov5m/FP32_openvino_model/yolov5m_fp32.xml
-
-
-.. parsed-literal::
-
-    Export ONNX to OpenVINO FP16 IR to: yolov5/yolov5m/FP16_openvino_model/yolov5m_fp16.xml
-
-
-Imports
-~~~~~~~
-
-
-
-.. code:: ipython3
-
-    sys.path.append("./yolov5")
-
-    from yolov5.utils.dataloaders import create_dataloader
-    from yolov5.utils.general import check_dataset
-
-Prepare dataset for quantization
---------------------------------
-
-
-
-Before starting quantization, we should prepare dataset, which will be
-used for quantization. Ultralytics YOLOv5 provides data loader for
-iteration over dataset during training and validation. Let’s create it
-first.
-
-.. code:: ipython3
-
-    from yolov5.utils.general import download
-
-    DATASET_CONFIG = "./yolov5/data/coco128.yaml"
-
-
-    def create_data_source():
-        """
-        Creates COCO 2017 validation data loader. The method downloads COCO 2017
-        dataset if it does not exist.
-        """
-        if not Path("datasets/coco128").exists():
-            urls = ["https://ultralytics.com/assets/coco128.zip"]
-            download(urls, dir="datasets")
-
-        data = check_dataset(DATASET_CONFIG)
-        val_dataloader = create_dataloader(
-            data["val"], imgsz=640, batch_size=1, stride=32, pad=0.5, workers=1
-        )[0]
-
-        return val_dataloader
-
-
-    data_source = create_data_source()
-
-
-.. parsed-literal::
-
-    Downloading https://ultralytics.com/assets/coco128.zip to datasets/coco128.zip...
-
-
-.. parsed-literal::
-
-
-  0%|          | 0.00/6.66M [00:00`__.
-NNCF also expect providing model object in inference framework format,
-in our case ``ov.Model`` instance created using ``core.read_model`` or
-``ov.convert_model``.
-
-.. code:: ipython3
-
-    subset_size = 300
-    preset = nncf.QuantizationPreset.MIXED
-
-Perform model optimization
---------------------------
-
-
-
-Run quantization using POT
-~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-
-
-To start model quantization using POT API, we should call
-``pipeline.run(pot_model)`` method. As the result, we got quantized
-model representation from POT, which can be saved on disk using
-``openvino.tools.pot.graph.save_model`` function. Optionally, we can
-compress model weights to quantized precision in order to reduce the
-size of final .bin file.
-
-.. code:: ipython3
-
-    from openvino.tools.pot.graph.model_utils import compress_model_weights
-    from openvino.tools.pot.graph import load_model, save_model
-
-    compressed_model = pipeline.run(pot_model)
-    compress_model_weights(compressed_model)
-    optimized_save_dir = Path(f"{MODEL_PATH}/POT_INT8_openvino_model/")
-    save_model(compressed_model, optimized_save_dir, model_config["model_name"] + "_int8")
-    pot_int8_path = f"{optimized_save_dir}/{MODEL_NAME}_int8.xml"
-
-Run quantization using NNCF
-~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-
-
-To run NNCF quantization, we should call ``nncf.quantize`` function. As
-the result, the function returns quantized model in the same format like
-input model, so it means that quantized model ready to be compiled on
-device for inference and can be saved on disk using
-``openvino.save_model``.
-
-.. code:: ipython3
-
-    core = ov.Core()
-    ov_model = core.read_model(fp32_path)
-    quantized_model = nncf.quantize(
-        ov_model, nncf_calibration_dataset, preset=preset, subset_size=subset_size
-    )
-    nncf_int8_path = f"{MODEL_PATH}/NNCF_INT8_openvino_model/{MODEL_NAME}_int8.xml"
-    ov.save_model(quantized_model, nncf_int8_path, compress_to_fp16=False)
-
-
-.. parsed-literal::
-
-    2024-01-25 22:53:41.334050: I tensorflow/core/util/port.cc:110] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
-    2024-01-25 22:53:41.364872: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
-    To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
-
-
-.. parsed-literal::
-
-    2024-01-25 22:53:42.021326: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
-
-
-
-.. parsed-literal::
-
-    Output()
-
-
-
-.. raw:: html
-
-    

-
-
-
-
-
-
-
-
-
-.. parsed-literal::
-
-    Output()
-
-
-
-.. raw:: html
-
-    

-
-
-
-
-
-
-
-
-Compare accuracy FP32 and INT8 models
--------------------------------------
-
-
-
-For getting accuracy results, we will use ``yolov5.val.run`` function
-which already supports OpenVINO backend. For making int8 model is
-compatible with Ultralytics provided validation pipeline, we also should
-provide metadata with information about supported class names in the
-same directory, where model located.
-
-.. code:: ipython3
-
-    from yolov5.export import attempt_load, yaml_save
-    from yolov5.val import run as validation_fn
-
-
-    model = attempt_load(
-        f"{MODEL_PATH}/{MODEL_NAME}.pt", device="cpu", inplace=True, fuse=True
-    )
-    metadata = {"stride": int(max(model.stride)), "names": model.names}  # model metadata
-    yaml_save(Path(nncf_int8_path).with_suffix(".yaml"), metadata)
-    yaml_save(Path(pot_int8_path).with_suffix(".yaml"), metadata)
-    yaml_save(Path(fp32_path).with_suffix(".yaml"), metadata)
-
-
-.. parsed-literal::
-
-    Fusing layers...
-
-
-.. parsed-literal::
-
-    YOLOv5m summary: 290 layers, 21172173 parameters, 0 gradients
-
-
-.. code:: ipython3
-
-    print("Checking the accuracy of the original model:")
-    fp32_metrics = validation_fn(
-        data=DATASET_CONFIG,
-        weights=Path(fp32_path).parent,
-        batch_size=1,
-        workers=1,
-        plots=False,
-        device="cpu",
-        iou_thres=0.65,
-    )
-
-    fp32_ap5 = fp32_metrics[0][2]
-    fp32_ap_full = fp32_metrics[0][3]
-    print(f"mAP@.5 = {fp32_ap5}")
-    print(f"mAP@.5:.95 = {fp32_ap_full}")
-
-
-.. parsed-literal::
-
-    YOLOv5 🚀 v7.0-0-g915bbf2 Python-3.8.10 torch-2.1.0+cpu CPU
-
-
-
-.. parsed-literal::
-
-    Loading yolov5/yolov5m/FP32_openvino_model for OpenVINO inference...
-
-
-.. parsed-literal::
-
-    Checking the accuracy of the original model:
-
-
-.. parsed-literal::
-
-    Forcing --batch-size 1 square inference (1,3,640,640) for non-PyTorch models
-
-
-.. parsed-literal::
-
-
-   val: Scanning /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/111-yolov5-quantization-migration/datasets/coco128/labels/train2017.cache... 126 images, 2 backgrounds, 0 corrupt: 100%|██████████| 128/128 00:00
-
-.. parsed-literal::
-
-
-   val: Scanning /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/111-yolov5-quantization-migration/datasets/coco128/labels/train2017.cache... 126 images, 2 backgrounds, 0 corrupt: 100%|██████████| 128/128 00:00
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:   0%|          | 0/128 00:00
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:   2%|▏         | 2/128 00:00
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:   4%|▍         | 5/128 00:00
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:   6%|▋         | 8/128 00:00
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:   9%|▊         | 11/128 00:00
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  11%|█         | 14/128 00:00
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  13%|█▎        | 17/128 00:00
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  16%|█▌        | 20/128 00:00
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  18%|█▊        | 23/128 00:01
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  20%|██        | 26/128 00:01
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  23%|██▎       | 29/128 00:01
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  25%|██▌       | 32/128 00:01
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  27%|██▋       | 35/128 00:01
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  30%|██▉       | 38/128 00:01
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  32%|███▏      | 41/128 00:01
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  34%|███▍      | 44/128 00:02
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  37%|███▋      | 47/128 00:02
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  39%|███▉      | 50/128 00:02
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  41%|████▏     | 53/128 00:02
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  44%|████▍     | 56/128 00:02
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  46%|████▌     | 59/128 00:02
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  48%|████▊     | 62/128 00:02
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  51%|█████     | 65/128 00:03
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  53%|█████▎    | 68/128 00:03
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  55%|█████▌    | 71/128 00:03
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  58%|█████▊    | 74/128 00:03
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  60%|██████    | 77/128 00:03
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  62%|██████▎   | 80/128 00:03
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  65%|██████▍   | 83/128 00:03
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  67%|██████▋   | 86/128 00:03
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  70%|██████▉   | 89/128 00:04
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  72%|███████▏  | 92/128 00:04
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  74%|███████▍  | 95/128 00:04
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  77%|███████▋  | 98/128 00:04
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  79%|███████▉  | 101/128 00:04
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  81%|████████▏ | 104/128 00:04
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  84%|████████▎ | 107/128 00:04
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  86%|████████▌ | 110/128 00:05
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  88%|████████▊ | 113/128 00:05
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  91%|█████████ | 116/128 00:05
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  93%|█████████▎| 119/128 00:05
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  95%|█████████▌| 122/128 00:05
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  98%|█████████▊| 125/128 00:05
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100%|██████████| 128/128 00:05
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100%|██████████| 128/128 00:05
-
-.. parsed-literal::
-
-
-                       all        128        929      0.726      0.687      0.769      0.554
-
-
-.. parsed-literal::
-
-    Speed: 0.2ms pre-process, 35.5ms inference, 3.9ms NMS per image at shape (1, 3, 640, 640)
-
-
-.. parsed-literal::
-
-    Results saved to yolov5/runs/val/exp
-
-
-.. parsed-literal::
-
-    mAP@.5 = 0.7686009694748247
-    mAP@.5:.95 = 0.5541065589219657
-
-
-.. code:: ipython3
-
-    print("Checking the accuracy of the POT int8 model:")
-    int8_metrics = validation_fn(
-        data=DATASET_CONFIG,
-        weights=Path(pot_int8_path).parent,
-        batch_size=1,
-        workers=1,
-        plots=False,
-        device="cpu",
-        iou_thres=0.65,
-    )
-
-    pot_int8_ap5 = int8_metrics[0][2]
-    pot_int8_ap_full = int8_metrics[0][3]
-    print(f"mAP@.5 = {pot_int8_ap5}")
-    print(f"mAP@.5:.95 = {pot_int8_ap_full}")
-
-
-.. parsed-literal::
-
-    YOLOv5 🚀 v7.0-0-g915bbf2 Python-3.8.10 torch-2.1.0+cpu CPU
-
-
-
-.. parsed-literal::
-
-    Loading yolov5/yolov5m/POT_INT8_openvino_model for OpenVINO inference...
-
-
-.. parsed-literal::
-
-    Checking the accuracy of the POT int8 model:
-
-
-.. parsed-literal::
-
-    Forcing --batch-size 1 square inference (1,3,640,640) for non-PyTorch models
-
-
-.. parsed-literal::
-
-
-   val: Scanning /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/111-yolov5-quantization-migration/datasets/coco128/labels/train2017.cache... 126 images, 2 backgrounds, 0 corrupt: 100%|██████████| 128/128 00:00
-
-.. parsed-literal::
-
-
-   val: Scanning /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/111-yolov5-quantization-migration/datasets/coco128/labels/train2017.cache... 126 images, 2 backgrounds, 0 corrupt: 100%|██████████| 128/128 00:00
-
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:   0%|          | 0/128 00:00
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:   3%|▎         | 4/128 00:00
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:   6%|▋         | 8/128 00:00
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:   9%|▉         | 12/128 00:00
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  13%|█▎        | 17/128 00:00
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  16%|█▋        | 21/128 00:00
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  20%|█▉        | 25/128 00:00
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  23%|██▎       | 30/128 00:00
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  27%|██▋       | 34/128 00:00
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  30%|██▉       | 38/128 00:01
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  33%|███▎      | 42/128 00:01
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  36%|███▌      | 46/128 00:01
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  39%|███▉      | 50/128 00:01
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  42%|████▏     | 54/128 00:01
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  45%|████▌     | 58/128 00:01
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  49%|████▉     | 63/128 00:01
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  53%|█████▎    | 68/128 00:01
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  56%|█████▋    | 72/128 00:02
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  60%|██████    | 77/128 00:02
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  64%|██████▍   | 82/128 00:02
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  68%|██████▊   | 87/128 00:02
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  72%|███████▏  | 92/128 00:02
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  76%|███████▌  | 97/128 00:02
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  80%|███████▉  | 102/128 00:02
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  84%|████████▎ | 107/128 00:02
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  88%|████████▊ | 112/128 00:02
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  91%|█████████▏| 117/128 00:03
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  95%|█████████▌| 122/128 00:03
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  99%|█████████▉| 127/128 00:03
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100%|██████████| 128/128 00:03
-
-
-.. parsed-literal::
-
-                       all        128        929      0.761      0.677      0.773      0.548
-
-
-.. parsed-literal::
-
-    Speed: 0.2ms pre-process, 16.6ms inference, 3.8ms NMS per image at shape (1, 3, 640, 640)
-
-
-.. parsed-literal::
-
-    Results saved to yolov5/runs/val/exp2
-
-
-.. parsed-literal::
-
-    mAP@.5 = 0.7726143212109754
-    mAP@.5:.95 = 0.5482902837946336
-
-
-.. code:: ipython3
-
-    print("Checking the accuracy of the NNCF int8 model:")
-    int8_metrics = validation_fn(
-        data=DATASET_CONFIG,
-        weights=Path(nncf_int8_path).parent,
-        batch_size=1,
-        workers=1,
-        plots=False,
-        device="cpu",
-        iou_thres=0.65,
-    )
-
-    nncf_int8_ap5 = int8_metrics[0][2]
-    nncf_int8_ap_full = int8_metrics[0][3]
-    print(f"mAP@.5 = {nncf_int8_ap5}")
-    print(f"mAP@.5:.95 = {nncf_int8_ap_full}")
-
-
-.. parsed-literal::
-
-    YOLOv5 🚀 v7.0-0-g915bbf2 Python-3.8.10 torch-2.1.0+cpu CPU
-
-
-
-.. parsed-literal::
-
-    Loading yolov5/yolov5m/NNCF_INT8_openvino_model for OpenVINO inference...
-
-
-.. parsed-literal::
-
-    Checking the accuracy of the NNCF int8 model:
-
-
-.. parsed-literal::
-
-    Forcing --batch-size 1 square inference (1,3,640,640) for non-PyTorch models
-
-
-.. parsed-literal::
-
-
-   val: Scanning /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/111-yolov5-quantization-migration/datasets/coco128/labels/train2017.cache... 126 images, 2 backgrounds, 0 corrupt: 100%|██████████| 128/128 00:00
-
-.. parsed-literal::
-
-
-   val: Scanning /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/111-yolov5-quantization-migration/datasets/coco128/labels/train2017.cache... 126 images, 2 backgrounds, 0 corrupt: 100%|██████████| 128/128 00:00
-
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:   0%|          | 0/128 00:00
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:   3%|▎         | 4/128 00:00
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:   7%|▋         | 9/128 00:00
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  11%|█         | 14/128 00:00
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  15%|█▍        | 19/128 00:00
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  19%|█▉        | 24/128 00:00
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  22%|██▏       | 28/128 00:00
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  25%|██▌       | 32/128 00:00
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  28%|██▊       | 36/128 00:00
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  31%|███▏      | 40/128 00:01
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  34%|███▍      | 44/128 00:01
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  38%|███▊      | 48/128 00:01
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  41%|████      | 52/128 00:01
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  43%|████▎     | 55/128 00:01
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  46%|████▌     | 59/128 00:01
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  49%|████▉     | 63/128 00:01
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  52%|█████▏    | 67/128 00:01
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  55%|█████▌    | 71/128 00:02
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  59%|█████▊    | 75/128 00:02
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  62%|██████▎   | 80/128 00:02
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  66%|██████▌   | 84/128 00:02
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  70%|██████▉   | 89/128 00:02
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  73%|███████▎  | 94/128 00:02
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  77%|███████▋  | 99/128 00:02
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  81%|████████▏ | 104/128 00:02
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  84%|████████▍ | 108/128 00:03
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  88%|████████▊ | 112/128 00:03
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  91%|█████████▏| 117/128 00:03
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  95%|█████████▌| 122/128 00:03
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95:  99%|█████████▉| 127/128 00:03
-
-.. parsed-literal::
-
-
-                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100%|██████████| 128/128 00:03
-
-
-.. parsed-literal::
-
-                       all        128        929      0.738      0.682      0.768      0.549
-
-
-.. parsed-literal::
-
-    Speed: 0.2ms pre-process, 17.0ms inference, 3.9ms NMS per image at shape (1, 3, 640, 640)
-
-
-.. parsed-literal::
-
-    Results saved to yolov5/runs/val/exp3
-
-
-.. parsed-literal::
-
-    mAP@.5 = 0.7684598204433661
-    mAP@.5:.95 = 0.5487198807173201
-
-
-Compare Average Precision of quantized INT8 model with original FP32
-model.
-
-.. code:: ipython3
-
-    %matplotlib inline
-    plt.style.use("seaborn-deep")
-    fp32_acc = np.array([fp32_ap5, fp32_ap_full])
-    pot_int8_acc = np.array([pot_int8_ap5, pot_int8_ap_full])
-    nncf_int8_acc = np.array([nncf_int8_ap5, nncf_int8_ap_full])
-    x_data = ("AP@0.5", "AP@0.5:0.95")
-    x_axis = np.arange(len(x_data))
-    fig = plt.figure()
-    fig.patch.set_facecolor("#FFFFFF")
-    fig.patch.set_alpha(0.7)
-    ax = fig.add_subplot(111)
-    plt.bar(x_axis - 0.2, fp32_acc, 0.3, label="FP32")
-    for i in range(0, len(x_axis)):
-        plt.text(
-            i - 0.3,
-            round(fp32_acc[i], 3) + 0.01,
-            str(round(fp32_acc[i], 3)),
-            fontweight="bold",
-        )
-    plt.bar(x_axis + 0.15, pot_int8_acc, 0.3, label="POT INT8")
-    for i in range(0, len(x_axis)):
-        plt.text(
-            i + 0.05,
-            round(pot_int8_acc[i], 3) + 0.01,
-            str(round(pot_int8_acc[i], 3)),
-            fontweight="bold",
-        )
-
-    plt.bar(x_axis + 0.5, nncf_int8_acc, 0.3, label="NNCF INT8")
-    for i in range(0, len(x_axis)):
-        plt.text(
-            i + 0.4,
-            round(nncf_int8_acc[i], 3) + 0.01,
-            str(round(nncf_int8_acc[i], 3)),
-            fontweight="bold",
-        )
-    plt.xticks(x_axis, x_data)
-    plt.xlabel("Average Precision")
-    plt.title("Compare Yolov5 FP32 and INT8 model average precision")
-
-    plt.legend()
-    plt.show()
-
-
-
-.. image:: 111-yolov5-quantization-migration-with-output_files/111-yolov5-quantization-migration-with-output_34_0.png
-
-
-Inference Demo Performance Comparison
--------------------------------------
-
-
-
-This part shows how to use the Ultralytics model detection code
-`detect.py `__
-to run synchronous inference, using the OpenVINO Python API on two
-images.
-
-.. code:: ipython3
-
-    from yolov5.utils.general import increment_path
-
-    fp32_save_dir = increment_path(Path('./yolov5/runs/detect/exp'))
-
-.. code:: ipython3
-
-    command_detect = "cd yolov5 && python detect.py --weights ./yolov5m/FP32_openvino_model"
-    display(Markdown(f"`{command_detect}`"))
-    %sx $command_detect
-
-
-
-``cd yolov5 && python detect.py --weights ./yolov5m/FP32_openvino_model``
-
-
-
-
-.. parsed-literal::
-
-    ["\x1b[34m\x1b[1mdetect: \x1b[0mweights=['./yolov5m/FP32_openvino_model'], source=data/images, data=data/coco128.yaml, imgsz=[640, 640], conf_thres=0.25, iou_thres=0.45, max_det=1000, device=, view_img=False, save_txt=False, save_conf=False, save_crop=False, nosave=False, classes=None, agnostic_nms=False, augment=False, visualize=False, update=False, project=runs/detect, name=exp, exist_ok=False, line_thickness=3, hide_labels=False, hide_conf=False, half=False, dnn=False, vid_stride=1",
-     'YOLOv5 🚀 v7.0-0-g915bbf2 Python-3.8.10 torch-2.1.0+cpu CPU',
-     '',
-     'Loading yolov5m/FP32_openvino_model for OpenVINO inference...',
-     'image 1/2 /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/111-yolov5-quantization-migration/yolov5/data/images/bus.jpg: 640x640 4 persons, 1 bus, 55.6ms',
-     'image 2/2 /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/111-yolov5-quantization-migration/yolov5/data/images/zidane.jpg: 640x640 3 persons, 2 ties, 47.9ms',
-     'Speed: 2.0ms pre-process, 51.8ms inference, 1.3ms NMS per image at shape (1, 3, 640, 640)',
-     'Results saved to \x1b[1mruns/detect/exp\x1b[0m']
-
-
-
-.. code:: ipython3
-
-    pot_save_dir = increment_path(Path('./yolov5/runs/detect/exp'))
-    command_detect = "cd yolov5 && python detect.py --weights ./yolov5m/POT_INT8_openvino_model"
-    display(Markdown(f"`{command_detect}`"))
-    %sx $command_detect
-
-
-
-``cd yolov5 && python detect.py --weights ./yolov5m/POT_INT8_openvino_model``
-
-
-
-
-.. parsed-literal::
-
-    ["\x1b[34m\x1b[1mdetect: \x1b[0mweights=['./yolov5m/POT_INT8_openvino_model'], source=data/images, data=data/coco128.yaml, imgsz=[640, 640], conf_thres=0.25, iou_thres=0.45, max_det=1000, device=, view_img=False, save_txt=False, save_conf=False, save_crop=False, nosave=False, classes=None, agnostic_nms=False, augment=False, visualize=False, update=False, project=runs/detect, name=exp, exist_ok=False, line_thickness=3, hide_labels=False, hide_conf=False, half=False, dnn=False, vid_stride=1",
-     'YOLOv5 🚀 v7.0-0-g915bbf2 Python-3.8.10 torch-2.1.0+cpu CPU',
-     '',
-     'Loading yolov5m/POT_INT8_openvino_model for OpenVINO inference...',
-     'image 1/2 /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/111-yolov5-quantization-migration/yolov5/data/images/bus.jpg: 640x640 4 persons, 1 bus, 33.6ms',
-     'image 2/2 /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/111-yolov5-quantization-migration/yolov5/data/images/zidane.jpg: 640x640 3 persons, 1 tie, 27.4ms',
-     'Speed: 1.5ms pre-process, 30.5ms inference, 1.4ms NMS per image at shape (1, 3, 640, 640)',
-     'Results saved to \x1b[1mruns/detect/exp2\x1b[0m']
-
-
-
-.. code:: ipython3
-
-    nncf_save_dir = increment_path(Path('./yolov5/runs/detect/exp'))
-    command_detect = "cd yolov5 && python detect.py --weights ./yolov5m/NNCF_INT8_openvino_model"
-    display(Markdown(f"`{command_detect}`"))
-    %sx $command_detect
-
-
-
-``cd yolov5 && python detect.py --weights ./yolov5m/NNCF_INT8_openvino_model``
-
-
-
-
-.. parsed-literal::
-
-    ["\x1b[34m\x1b[1mdetect: \x1b[0mweights=['./yolov5m/NNCF_INT8_openvino_model'], source=data/images, data=data/coco128.yaml, imgsz=[640, 640], conf_thres=0.25, iou_thres=0.45, max_det=1000, device=, view_img=False, save_txt=False, save_conf=False, save_crop=False, nosave=False, classes=None, agnostic_nms=False, augment=False, visualize=False, update=False, project=runs/detect, name=exp, exist_ok=False, line_thickness=3, hide_labels=False, hide_conf=False, half=False, dnn=False, vid_stride=1",
-     'YOLOv5 🚀 v7.0-0-g915bbf2 Python-3.8.10 torch-2.1.0+cpu CPU',
-     '',
-     'Loading yolov5m/NNCF_INT8_openvino_model for OpenVINO inference...',
-     'image 1/2 /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/111-yolov5-quantization-migration/yolov5/data/images/bus.jpg: 640x640 4 persons, 1 bus, 33.6ms',
-     'image 2/2 /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/111-yolov5-quantization-migration/yolov5/data/images/zidane.jpg: 640x640 3 persons, 2 ties, 23.7ms',
-     'Speed: 1.5ms pre-process, 28.6ms inference, 1.4ms NMS per image at shape (1, 3, 640, 640)',
-     'Results saved to \x1b[1mruns/detect/exp3\x1b[0m']
-
-
-
-.. code:: ipython3
-
-    %matplotlib inline
-    import matplotlib.image as mpimg
-
-    fig2, axs = plt.subplots(1, 4, figsize=(20, 20))
-    fig2.patch.set_facecolor("#FFFFFF")
-    fig2.patch.set_alpha(0.7)
-    ori = mpimg.imread("./yolov5/data/images/bus.jpg")
-    fp32_result = mpimg.imread(fp32_save_dir / "bus.jpg")
-    pot_result = mpimg.imread(pot_save_dir / "bus.jpg")
-    nncf_result = mpimg.imread(nncf_save_dir / "bus.jpg")
-    titles = ["Original", "FP32", "POT INT8", "NNCF INT8"]
-    imgs = [ori, fp32_result, pot_result, nncf_result]
-    for ax, img, title in zip(axs, imgs, titles):
-        ax.imshow(img)
-        ax.set_title(title)
-        ax.grid(False)
-        ax.set_xticks([])
-        ax.set_yticks([])
-
-
-
-.. image:: 111-yolov5-quantization-migration-with-output_files/111-yolov5-quantization-migration-with-output_40_0.png
-
-
-Benchmark
----------
-
-
-
-.. code:: ipython3
-
-    gpu_available = "GPU" in core.available_devices
-
-    print("Inference FP32 model (OpenVINO IR) on CPU")
-    !benchmark_app -m  {fp32_path} -d CPU -api async -t 15
-
-    if gpu_available:
-        print("Inference FP32 model (OpenVINO IR) on GPU")
-        !benchmark_app -m  {fp32_path} -d GPU -api async -t 15
-
-
-.. parsed-literal::
-
-    Inference FP32 model (OpenVINO IR) on CPU
-
-
-.. parsed-literal::
-
-    [Step 1/11] Parsing and validating input arguments
-    [ INFO ] Parsing input parameters
-    [Step 2/11] Loading OpenVINO Runtime
-    [ INFO ] OpenVINO:
-    [ INFO ] Build ................................. 2023.3.0-13775-ceeafaf64f3-releases/2023/3
-    [ INFO ]
-    [ INFO ] Device info:
-    [ INFO ] CPU
-    [ INFO ] Build ................................. 2023.3.0-13775-ceeafaf64f3-releases/2023/3
-    [ INFO ]
-    [ INFO ]
-    [Step 3/11] Setting device configuration
-    [ WARNING ] Performance hint was not explicitly specified in command line. Device(CPU) performance hint will be set to PerformanceMode.THROUGHPUT.
-    [Step 4/11] Reading model files
-    [ INFO ] Loading model files
-
-
-.. parsed-literal::
-
-    [ INFO ] Read model took 36.38 ms
-    [ INFO ] Original model I/O parameters:
-    [ INFO ] Model inputs:
-    [ INFO ]     images (node: images) : f32 / [...] / [1,3,640,640]
-    [ INFO ] Model outputs:
-    [ INFO ]     output0 (node: output0) : f32 / [...] / [1,25200,85]
-    [Step 5/11] Resizing model to match image sizes and given batch
-    [ INFO ] Model batch size: 1
-    [Step 6/11] Configuring input of the model
-    [ INFO ] Model inputs:
-    [ INFO ]     images (node: images) : u8 / [N,C,H,W] / [1,3,640,640]
-    [ INFO ] Model outputs:
-    [ INFO ]     output0 (node: output0) : f32 / [...] / [1,25200,85]
-    [Step 7/11] Loading the model to the device
-
-
-.. parsed-literal::
-
-    [ INFO ] Compile model took 341.58 ms
-    [Step 8/11] Querying optimal runtime parameters
-    [ INFO ] Model:
-    [ INFO ]   NETWORK_NAME: main_graph
-    [ INFO ]   OPTIMAL_NUMBER_OF_INFER_REQUESTS: 6
-    [ INFO ]   NUM_STREAMS: 6
-    [ INFO ]   AFFINITY: Affinity.CORE
-    [ INFO ]   INFERENCE_NUM_THREADS: 24
-    [ INFO ]   PERF_COUNT: NO
-    [ INFO ]   INFERENCE_PRECISION_HINT: 
-    [ INFO ]   PERFORMANCE_HINT: THROUGHPUT
-    [ INFO ]   EXECUTION_MODE_HINT: ExecutionMode.PERFORMANCE
-    [ INFO ]   PERFORMANCE_HINT_NUM_REQUESTS: 0
-    [ INFO ]   ENABLE_CPU_PINNING: True
-    [ INFO ]   SCHEDULING_CORE_TYPE: SchedulingCoreType.ANY_CORE
-    [ INFO ]   ENABLE_HYPER_THREADING: True
-    [ INFO ]   EXECUTION_DEVICES: ['CPU']
-    [ INFO ]   CPU_DENORMALS_OPTIMIZATION: False
-    [ INFO ]   CPU_SPARSE_WEIGHTS_DECOMPRESSION_RATE: 1.0
-    [Step 9/11] Creating infer requests and preparing input tensors
-    [ WARNING ] No input files were given for input 'images'!. This input will be filled with random values!
-    [ INFO ] Fill input 'images' with random values
-    [Step 10/11] Measuring performance (Start inference asynchronously, 6 inference requests, limits: 15000 ms duration)
-    [ INFO ] Benchmarking in inference only mode (inputs filling are not included in measurement loop).
-
-
-.. parsed-literal::
-
-    [ INFO ] First inference took 101.86 ms
-
-
-.. parsed-literal::
-
-    [Step 11/11] Dumping statistics report
-    [ INFO ] Execution Devices:['CPU']
-    [ INFO ] Count:            462 iterations
-    [ INFO ] Duration:         15257.07 ms
-    [ INFO ] Latency:
-    [ INFO ]    Median:        197.03 ms
-    [ INFO ]    Average:       197.18 ms
-    [ INFO ]    Min:           123.46 ms
-    [ INFO ]    Max:           225.07 ms
-    [ INFO ] Throughput:   30.28 FPS
-
-
-.. code:: ipython3
-
-    print("Inference FP16 model (OpenVINO IR) on CPU")
-    !benchmark_app -m {fp16_path} -d CPU -api async -t 15
-
-    if gpu_available:
-        print("Inference FP16 model (OpenVINO IR) on GPU")
-        !benchmark_app -m {fp16_path} -d GPU -api async -t 15
-
-
-.. parsed-literal::
-
-    Inference FP16 model (OpenVINO IR) on CPU
-
-
-.. parsed-literal::
-
-    [Step 1/11] Parsing and validating input arguments
-    [ INFO ] Parsing input parameters
-    [Step 2/11] Loading OpenVINO Runtime
-    [ INFO ] OpenVINO:
-    [ INFO ] Build ................................. 2023.3.0-13775-ceeafaf64f3-releases/2023/3
-    [ INFO ]
-    [ INFO ] Device info:
-    [ INFO ] CPU
-    [ INFO ] Build ................................. 2023.3.0-13775-ceeafaf64f3-releases/2023/3
-    [ INFO ]
-    [ INFO ]
-    [Step 3/11] Setting device configuration
-    [ WARNING ] Performance hint was not explicitly specified in command line. Device(CPU) performance hint will be set to PerformanceMode.THROUGHPUT.
-
-
-.. parsed-literal::
-
-    [Step 4/11] Reading model files
-    [ INFO ] Loading model files
-    [ INFO ] Read model took 40.32 ms
-    [ INFO ] Original model I/O parameters:
-    [ INFO ] Model inputs:
-    [ INFO ]     images (node: images) : f32 / [...] / [1,3,640,640]
-    [ INFO ] Model outputs:
-    [ INFO ]     output0 (node: output0) : f32 / [...] / [1,25200,85]
-    [Step 5/11] Resizing model to match image sizes and given batch
-    [ INFO ] Model batch size: 1
-    [Step 6/11] Configuring input of the model
-    [ INFO ] Model inputs:
-    [ INFO ]     images (node: images) : u8 / [N,C,H,W] / [1,3,640,640]
-    [ INFO ] Model outputs:
-    [ INFO ]     output0 (node: output0) : f32 / [...] / [1,25200,85]
-    [Step 7/11] Loading the model to the device
-
-
-.. parsed-literal::
-
-    [ INFO ] Compile model took 366.42 ms
-    [Step 8/11] Querying optimal runtime parameters
-    [ INFO ] Model:
-
-
-.. parsed-literal::
-
-    [ INFO ]   NETWORK_NAME: main_graph
-    [ INFO ]   OPTIMAL_NUMBER_OF_INFER_REQUESTS: 6
-    [ INFO ]   NUM_STREAMS: 6
-    [ INFO ]   AFFINITY: Affinity.CORE
-    [ INFO ]   INFERENCE_NUM_THREADS: 24
-    [ INFO ]   PERF_COUNT: NO
-    [ INFO ]   INFERENCE_PRECISION_HINT: 
-    [ INFO ]   PERFORMANCE_HINT: THROUGHPUT
-    [ INFO ]   EXECUTION_MODE_HINT: ExecutionMode.PERFORMANCE
-    [ INFO ]   PERFORMANCE_HINT_NUM_REQUESTS: 0
-    [ INFO ]   ENABLE_CPU_PINNING: True
-    [ INFO ]   SCHEDULING_CORE_TYPE: SchedulingCoreType.ANY_CORE
-    [ INFO ]   ENABLE_HYPER_THREADING: True
-    [ INFO ]   EXECUTION_DEVICES: ['CPU']
-    [ INFO ]   CPU_DENORMALS_OPTIMIZATION: False
-    [ INFO ]   CPU_SPARSE_WEIGHTS_DECOMPRESSION_RATE: 1.0
-    [Step 9/11] Creating infer requests and preparing input tensors
-    [ WARNING ] No input files were given for input 'images'!. This input will be filled with random values!
-    [ INFO ] Fill input 'images' with random values
-    [Step 10/11] Measuring performance (Start inference asynchronously, 6 inference requests, limits: 15000 ms duration)
-    [ INFO ] Benchmarking in inference only mode (inputs filling are not included in measurement loop).
-
-
-.. parsed-literal::
-
-    [ INFO ] First inference took 99.93 ms
-
-
-.. parsed-literal::
-
-    [Step 11/11] Dumping statistics report
-    [ INFO ] Execution Devices:['CPU']
-    [ INFO ] Count:            462 iterations
-    [ INFO ] Duration:         15285.88 ms
-    [ INFO ] Latency:
-    [ INFO ]    Median:        198.09 ms
-    [ INFO ]    Average:       197.92 ms
-    [ INFO ]    Min:           95.17 ms
-    [ INFO ]    Max:           213.64 ms
-    [ INFO ] Throughput:   30.22 FPS
-
-
-.. code:: ipython3
-
-    print("Inference POT INT8 model (OpenVINO IR) on CPU")
-    !benchmark_app -m {pot_int8_path} -d CPU -api async -t 15
-
-    if gpu_available:
-        print("Inference POT INT8 model (OpenVINO IR) on GPU")
-        !benchmark_app -m {pot_int8_path} -d GPU -api async -t 15
-
-
-.. parsed-literal::
-
-    Inference POT INT8 model (OpenVINO IR) on CPU
-
-
-.. parsed-literal::
-
-    [Step 1/11] Parsing and validating input arguments
-    [ INFO ] Parsing input parameters
-    [Step 2/11] Loading OpenVINO Runtime
-    [ INFO ] OpenVINO:
-    [ INFO ] Build ................................. 2023.3.0-13775-ceeafaf64f3-releases/2023/3
-    [ INFO ]
-    [ INFO ] Device info:
-
-
-.. parsed-literal::
-
-    [ INFO ] CPU
-    [ INFO ] Build ................................. 2023.3.0-13775-ceeafaf64f3-releases/2023/3
-    [ INFO ]
-    [ INFO ]
-    [Step 3/11] Setting device configuration
-    [ WARNING ] Performance hint was not explicitly specified in command line. Device(CPU) performance hint will be set to PerformanceMode.THROUGHPUT.
-    [Step 4/11] Reading model files
-    [ INFO ] Loading model files
-
-
-.. parsed-literal::
-
-    [ INFO ] Read model took 49.60 ms
-    [ INFO ] Original model I/O parameters:
-    [ INFO ] Model inputs:
-    [ INFO ]     images (node: images) : f32 / [...] / [1,3,640,640]
-    [ INFO ] Model outputs:
-    [ INFO ]     output0 (node: output0) : f32 / [...] / [1,25200,85]
-    [Step 5/11] Resizing model to match image sizes and given batch
-    [ INFO ] Model batch size: 1
-    [Step 6/11] Configuring input of the model
-    [ INFO ] Model inputs:
-    [ INFO ]     images (node: images) : u8 / [N,C,H,W] / [1,3,640,640]
-    [ INFO ] Model outputs:
-    [ INFO ]     output0 (node: output0) : f32 / [...] / [1,25200,85]
-    [Step 7/11] Loading the model to the device
-
-
-.. parsed-literal::
-
-    [ INFO ] Compile model took 712.47 ms
-    [Step 8/11] Querying optimal runtime parameters
-    [ INFO ] Model:
-    [ INFO ]   NETWORK_NAME: main_graph
-    [ INFO ]   OPTIMAL_NUMBER_OF_INFER_REQUESTS: 6
-    [ INFO ]   NUM_STREAMS: 6
-    [ INFO ]   AFFINITY: Affinity.CORE
-    [ INFO ]   INFERENCE_NUM_THREADS: 24
-    [ INFO ]   PERF_COUNT: NO
-    [ INFO ]   INFERENCE_PRECISION_HINT: 
-    [ INFO ]   PERFORMANCE_HINT: THROUGHPUT
-    [ INFO ]   EXECUTION_MODE_HINT: ExecutionMode.PERFORMANCE
-    [ INFO ]   PERFORMANCE_HINT_NUM_REQUESTS: 0
-    [ INFO ]   ENABLE_CPU_PINNING: True
-    [ INFO ]   SCHEDULING_CORE_TYPE: SchedulingCoreType.ANY_CORE
-    [ INFO ]   ENABLE_HYPER_THREADING: True
-    [ INFO ]   EXECUTION_DEVICES: ['CPU']
-    [ INFO ]   CPU_DENORMALS_OPTIMIZATION: False
-    [ INFO ]   CPU_SPARSE_WEIGHTS_DECOMPRESSION_RATE: 1.0
-    [Step 9/11] Creating infer requests and preparing input tensors
-    [ WARNING ] No input files were given for input 'images'!. This input will be filled with random values!
-    [ INFO ] Fill input 'images' with random values
-
-
-.. parsed-literal::
-
-    [Step 10/11] Measuring performance (Start inference asynchronously, 6 inference requests, limits: 15000 ms duration)
-    [ INFO ] Benchmarking in inference only mode (inputs filling are not included in measurement loop).
-    [ INFO ] First inference took 47.98 ms
-
-
-.. parsed-literal::
-
-    [Step 11/11] Dumping statistics report
-    [ INFO ] Execution Devices:['CPU']
-    [ INFO ] Count:            1428 iterations
-    [ INFO ] Duration:         15050.87 ms
-    [ INFO ] Latency:
-    [ INFO ]    Median:        63.14 ms
-    [ INFO ]    Average:       63.05 ms
-    [ INFO ]    Min:           50.05 ms
-    [ INFO ]    Max:           80.66 ms
-    [ INFO ] Throughput:   94.88 FPS
-
-
-.. code:: ipython3
-
-    print("Inference NNCF INT8 model (OpenVINO IR) on CPU")
-    !benchmark_app -m {nncf_int8_path} -d CPU -api async -t 15
-
-    if gpu_available:
-        print("Inference NNCF INT8 model (OpenVINO IR) on GPU")
-        !benchmark_app -m {nncf_int8_path} -d GPU -api async -t 15
-
-
-.. parsed-literal::
-
-    Inference NNCF INT8 model (OpenVINO IR) on CPU
-
-
-.. parsed-literal::
-
-    [Step 1/11] Parsing and validating input arguments
-    [ INFO ] Parsing input parameters
-    [Step 2/11] Loading OpenVINO Runtime
-    [ INFO ] OpenVINO:
-    [ INFO ] Build ................................. 2023.3.0-13775-ceeafaf64f3-releases/2023/3
-    [ INFO ]
-    [ INFO ] Device info:
-    [ INFO ] CPU
-    [ INFO ] Build ................................. 2023.3.0-13775-ceeafaf64f3-releases/2023/3
-    [ INFO ]
-    [ INFO ]
-    [Step 3/11] Setting device configuration
-    [ WARNING ] Performance hint was not explicitly specified in command line. Device(CPU) performance hint will be set to PerformanceMode.THROUGHPUT.
-    [Step 4/11] Reading model files
-    [ INFO ] Loading model files
-
-
-.. parsed-literal::
-
-    [ INFO ] Read model took 53.45 ms
-    [ INFO ] Original model I/O parameters:
-    [ INFO ] Model inputs:
-    [ INFO ]     images (node: images) : f32 / [...] / [1,3,640,640]
-    [ INFO ] Model outputs:
-    [ INFO ]     output0 (node: output0) : f32 / [...] / [1,25200,85]
-    [Step 5/11] Resizing model to match image sizes and given batch
-    [ INFO ] Model batch size: 1
-    [Step 6/11] Configuring input of the model
-    [ INFO ] Model inputs:
-    [ INFO ]     images (node: images) : u8 / [N,C,H,W] / [1,3,640,640]
-    [ INFO ] Model outputs:
-    [ INFO ]     output0 (node: output0) : f32 / [...] / [1,25200,85]
-    [Step 7/11] Loading the model to the device
-
-
-.. parsed-literal::
-
-    [ INFO ] Compile model took 716.64 ms
-    [Step 8/11] Querying optimal runtime parameters
-    [ INFO ] Model:
-    [ INFO ]   NETWORK_NAME: main_graph
-    [ INFO ]   OPTIMAL_NUMBER_OF_INFER_REQUESTS: 6
-    [ INFO ]   NUM_STREAMS: 6
-    [ INFO ]   AFFINITY: Affinity.CORE
-    [ INFO ]   INFERENCE_NUM_THREADS: 24
-    [ INFO ]   PERF_COUNT: NO
-    [ INFO ]   INFERENCE_PRECISION_HINT: 
-    [ INFO ]   PERFORMANCE_HINT: THROUGHPUT
-    [ INFO ]   EXECUTION_MODE_HINT: ExecutionMode.PERFORMANCE
-    [ INFO ]   PERFORMANCE_HINT_NUM_REQUESTS: 0
-    [ INFO ]   ENABLE_CPU_PINNING: True
-    [ INFO ]   SCHEDULING_CORE_TYPE: SchedulingCoreType.ANY_CORE
-    [ INFO ]   ENABLE_HYPER_THREADING: True
-    [ INFO ]   EXECUTION_DEVICES: ['CPU']
-    [ INFO ]   CPU_DENORMALS_OPTIMIZATION: False
-    [ INFO ]   CPU_SPARSE_WEIGHTS_DECOMPRESSION_RATE: 1.0
-    [Step 9/11] Creating infer requests and preparing input tensors
-    [ WARNING ] No input files were given for input 'images'!. This input will be filled with random values!
-    [ INFO ] Fill input 'images' with random values
-    [Step 10/11] Measuring performance (Start inference asynchronously, 6 inference requests, limits: 15000 ms duration)
-    [ INFO ] Benchmarking in inference only mode (inputs filling are not included in measurement loop).
-
-
-.. parsed-literal::
-
-    [ INFO ] First inference took 49.90 ms
-
-
-.. parsed-literal::
-
-    [Step 11/11] Dumping statistics report
-    [ INFO ] Execution Devices:['CPU']
-    [ INFO ] Count:            1422 iterations
-    [ INFO ] Duration:         15056.36 ms
-    [ INFO ] Latency:
-    [ INFO ]    Median:        63.45 ms
-    [ INFO ]    Average:       63.30 ms
-    [ INFO ]    Min:           41.71 ms
-    [ INFO ]    Max:           85.51 ms
-    [ INFO ] Throughput:   94.45 FPS
-
-
-References
-----------
-
-
-
--  `Ultralytics YOLOv5 `__
--  `OpenVINO Post-training Optimization
-   Tool `__
--  `NNCF Post-training
-   quantization `__
--  `Model Conversion
-   API `__
diff --git a/docs/notebooks/111-yolov5-quantization-migration-with-output_files/111-yolov5-quantization-migration-with-output_34_0.png b/docs/notebooks/111-yolov5-quantization-migration-with-output_files/111-yolov5-quantization-migration-with-output_34_0.png
deleted file mode 100644
index b81921761a4a82..00000000000000
--- a/docs/notebooks/111-yolov5-quantization-migration-with-output_files/111-yolov5-quantization-migration-with-output_34_0.png
+++ /dev/null
@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:cf96b8c432fd043883f1adf03e2e5f554812455814af6245b9a13eacf0e39696
-size 33477
diff --git a/docs/notebooks/111-yolov5-quantization-migration-with-output_files/111-yolov5-quantization-migration-with-output_40_0.png b/docs/notebooks/111-yolov5-quantization-migration-with-output_files/111-yolov5-quantization-migration-with-output_40_0.png
deleted file mode 100644
index 6334455654fa50..00000000000000
--- a/docs/notebooks/111-yolov5-quantization-migration-with-output_files/111-yolov5-quantization-migration-with-output_40_0.png
+++ /dev/null
@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:8bbf27a2ad6605dcb53802f06b329b5189988d317d7770f689d6ff8ba6b450e3
-size 773347
diff --git a/docs/notebooks/111-yolov5-quantization-migration-with-output_files/index.html.tmp b/docs/notebooks/111-yolov5-quantization-migration-with-output_files/index.html.tmp
deleted file mode 100644
index 5a9d72cabd98b8..00000000000000
--- a/docs/notebooks/111-yolov5-quantization-migration-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,8 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/111-yolov5-quantization-migration-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/111-yolov5-quantization-migration-with-output_files/
../
-111-yolov5-quantization-migration-with-output_3..> 26-Jan-2024 01:05               33477
-111-yolov5-quantization-migration-with-output_4..> 26-Jan-2024 01:05              773347
-

-
diff --git a/docs/notebooks/112-pytorch-post-training-quantization-nncf-with-output.rst b/docs/notebooks/112-pytorch-post-training-quantization-nncf-with-output.rst
index 12c8b5df0eb260..44efb5ed678864 100644
--- a/docs/notebooks/112-pytorch-post-training-quantization-nncf-with-output.rst
+++ b/docs/notebooks/112-pytorch-post-training-quantization-nncf-with-output.rst
@@ -67,10 +67,6 @@ Preparations
     Note: you may need to restart the kernel to use updated packages.
 
 
-.. parsed-literal::
-
-    Note: you may need to restart the kernel to use updated packages.
-
 
 .. code:: ipython3
 
@@ -182,7 +178,7 @@ Settings
 
 .. parsed-literal::
 
-    PosixPath('/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/112-pytorch-post-training-quantization-nncf/model/resnet50_fp32.pth')
+    PosixPath('/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/notebooks/112-pytorch-post-training-quantization-nncf/model/resnet50_fp32.pth')
 
 
 
@@ -376,7 +372,8 @@ Create and load original uncompressed model
 
 
 
-ResNet-50 from the `torchivision repository `__ is pre-trained on
+ResNet-50 from the ```torchivision``
+repository `__ is pre-trained on
 ImageNet with more prediction classes than Tiny ImageNet, so the model
 is adjusted by swapping the last FC layer to one with fewer output
 values.
@@ -474,47 +471,47 @@ I. Evaluate the loaded model
 
 .. parsed-literal::
 
-    Test: [ 0/79]	Time 0.249 (0.249)	Acc@1 81.25 (81.25)	Acc@5 92.19 (92.19)
+    Test: [ 0/79]	Time 0.283 (0.283)	Acc@1 81.25 (81.25)	Acc@5 92.19 (92.19)
 
 
 .. parsed-literal::
 
-    Test: [10/79]	Time 0.223 (0.231)	Acc@1 56.25 (66.97)	Acc@5 86.72 (87.50)
+    Test: [10/79]	Time 0.242 (0.242)	Acc@1 56.25 (66.97)	Acc@5 86.72 (87.50)
 
 
 .. parsed-literal::
 
-    Test: [20/79]	Time 0.230 (0.231)	Acc@1 67.97 (64.29)	Acc@5 85.16 (87.35)
+    Test: [20/79]	Time 0.237 (0.241)	Acc@1 67.97 (64.29)	Acc@5 85.16 (87.35)
 
 
 .. parsed-literal::
 
-    Test: [30/79]	Time 0.229 (0.230)	Acc@1 53.12 (62.37)	Acc@5 77.34 (85.33)
+    Test: [30/79]	Time 0.238 (0.241)	Acc@1 53.12 (62.37)	Acc@5 77.34 (85.33)
 
 
 .. parsed-literal::
 
-    Test: [40/79]	Time 0.245 (0.229)	Acc@1 67.19 (60.86)	Acc@5 90.62 (84.51)
+    Test: [40/79]	Time 0.244 (0.241)	Acc@1 67.19 (60.86)	Acc@5 90.62 (84.51)
 
 
 .. parsed-literal::
 
-    Test: [50/79]	Time 0.223 (0.229)	Acc@1 60.16 (60.80)	Acc@5 88.28 (84.42)
+    Test: [50/79]	Time 0.270 (0.245)	Acc@1 60.16 (60.80)	Acc@5 88.28 (84.42)
 
 
 .. parsed-literal::
 
-    Test: [60/79]	Time 0.227 (0.229)	Acc@1 66.41 (60.46)	Acc@5 86.72 (83.79)
+    Test: [60/79]	Time 0.246 (0.245)	Acc@1 66.41 (60.46)	Acc@5 86.72 (83.79)
 
 
 .. parsed-literal::
 
-    Test: [70/79]	Time 0.227 (0.230)	Acc@1 52.34 (60.21)	Acc@5 80.47 (83.33)
+    Test: [70/79]	Time 0.263 (0.244)	Acc@1 52.34 (60.21)	Acc@5 80.47 (83.33)
 
 
 .. parsed-literal::
 
-     * Acc@1 60.740 Acc@5 83.960 Total time: 18.038
+     * Acc@1 60.740 Acc@5 83.960 Total time: 19.092
     Test accuracy of FP32 model: 60.740
 
 
@@ -557,14 +554,14 @@ Guide `__.
 
 .. parsed-literal::
 
-    2024-01-25 22:57:45.269741: I tensorflow/core/util/port.cc:110] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
-    2024-01-25 22:57:45.300230: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+    2024-02-09 22:53:51.860179: I tensorflow/core/util/port.cc:110] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
+    2024-02-09 22:53:51.891244: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
     To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
 
 
 .. parsed-literal::
 
-    2024-01-25 22:57:45.813067: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+    2024-02-09 22:53:52.407039: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
 
 
 .. parsed-literal::
@@ -584,13 +581,15 @@ Guide `__.
 
 
 
-.. raw:: html
 
-    

 
 
 
 
+.. raw:: html
+
+    
+    

 
 
 
@@ -611,13 +610,15 @@ Guide `__.
 
 
 
-.. raw:: html
 
-    

 
 
 
 
+.. raw:: html
+
+    
+    

 
 
 
@@ -634,48 +635,48 @@ Guide `__.
 
 .. parsed-literal::
 
-    Test: [ 0/79]	Time 0.430 (0.430)	Acc@1 81.25 (81.25)	Acc@5 89.84 (89.84)
+    Test: [ 0/79]	Time 0.435 (0.435)	Acc@1 82.81 (82.81)	Acc@5 92.19 (92.19)
 
 
 .. parsed-literal::
 
-    Test: [10/79]	Time 0.392 (0.397)	Acc@1 56.25 (66.26)	Acc@5 85.16 (87.14)
+    Test: [10/79]	Time 0.391 (0.395)	Acc@1 54.69 (66.34)	Acc@5 85.94 (87.50)
 
 
 .. parsed-literal::
 
-    Test: [20/79]	Time 0.393 (0.395)	Acc@1 68.75 (63.80)	Acc@5 84.38 (86.98)
+    Test: [20/79]	Time 0.389 (0.395)	Acc@1 69.53 (63.91)	Acc@5 84.38 (87.09)
 
 
 .. parsed-literal::
 
-    Test: [30/79]	Time 0.393 (0.396)	Acc@1 52.34 (62.15)	Acc@5 75.78 (85.01)
+    Test: [30/79]	Time 0.388 (0.395)	Acc@1 52.34 (62.22)	Acc@5 75.78 (84.90)
 
 
 .. parsed-literal::
 
-    Test: [40/79]	Time 0.392 (0.395)	Acc@1 67.19 (60.75)	Acc@5 89.84 (84.26)
+    Test: [40/79]	Time 0.392 (0.393)	Acc@1 67.97 (60.75)	Acc@5 89.84 (84.30)
 
 
 .. parsed-literal::
 
-    Test: [50/79]	Time 0.392 (0.395)	Acc@1 57.81 (60.68)	Acc@5 88.28 (84.15)
+    Test: [50/79]	Time 0.398 (0.393)	Acc@1 60.16 (60.72)	Acc@5 88.28 (84.30)
 
 
 .. parsed-literal::
 
-    Test: [60/79]	Time 0.393 (0.394)	Acc@1 64.06 (60.32)	Acc@5 85.94 (83.58)
+    Test: [60/79]	Time 0.390 (0.393)	Acc@1 66.41 (60.27)	Acc@5 86.72 (83.75)
 
 
 .. parsed-literal::
 
-    Test: [70/79]	Time 0.392 (0.394)	Acc@1 54.69 (60.17)	Acc@5 78.12 (83.08)
+    Test: [70/79]	Time 0.388 (0.392)	Acc@1 54.69 (60.06)	Acc@5 80.47 (83.29)
 
 
 .. parsed-literal::
 
-     * Acc@1 60.690 Acc@5 83.740 Total time: 30.882
-    Accuracy of initialized INT8 model: 60.690
+     * Acc@1 60.570 Acc@5 83.950 Total time: 30.736
+    Accuracy of initialized INT8 model: 60.570
 
 
 It should be noted that the inference time for the quantized PyTorch
@@ -724,20 +725,20 @@ For more information about model conversion, refer to this
 
 .. parsed-literal::
 
-    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/nncf/torch/quantization/layers.py:334: TracerWarning: Converting a tensor to a Python number might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
+    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/nncf/torch/quantization/layers.py:334: TracerWarning: Converting a tensor to a Python number might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
       return self._level_low.item()
-    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/nncf/torch/quantization/layers.py:342: TracerWarning: Converting a tensor to a Python number might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
+    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/nncf/torch/quantization/layers.py:342: TracerWarning: Converting a tensor to a Python number might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
       return self._level_high.item()
 
 
 .. parsed-literal::
 
-    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/torch/jit/_trace.py:1093: TracerWarning: Output nr 1. of the traced function does not match the corresponding output of the Python function. Detailed error:
+    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/torch/jit/_trace.py:1093: TracerWarning: Output nr 1. of the traced function does not match the corresponding output of the Python function. Detailed error:
     Tensor-likes are not close!
 
-    Mismatched elements: 25573 / 25600 (99.9%)
-    Greatest absolute difference: 0.5424436330795288 at index (1, 149) (up to 1e-05 allowed)
-    Greatest relative difference: 42.99047422811133 at index (90, 158) (up to 1e-05 allowed)
+    Mismatched elements: 25587 / 25600 (99.9%)
+    Greatest absolute difference: 0.5083470344543457 at index (42, 14) (up to 1e-05 allowed)
+    Greatest relative difference: 79.27243410505909 at index (126, 158) (up to 1e-05 allowed)
       _check_trace(
 
 
@@ -778,47 +779,47 @@ Evaluate the FP32 and INT8 models.
 
 .. parsed-literal::
 
-    Test: [ 0/79]	Time 0.184 (0.184)	Acc@1 81.25 (81.25)	Acc@5 92.19 (92.19)
+    Test: [ 0/79]	Time 0.185 (0.185)	Acc@1 81.25 (81.25)	Acc@5 92.19 (92.19)
 
 
 .. parsed-literal::
 
-    Test: [10/79]	Time 0.139 (0.143)	Acc@1 56.25 (66.97)	Acc@5 86.72 (87.50)
+    Test: [10/79]	Time 0.136 (0.143)	Acc@1 56.25 (66.97)	Acc@5 86.72 (87.50)
 
 
 .. parsed-literal::
 
-    Test: [20/79]	Time 0.139 (0.141)	Acc@1 67.97 (64.29)	Acc@5 85.16 (87.35)
+    Test: [20/79]	Time 0.141 (0.141)	Acc@1 67.97 (64.29)	Acc@5 85.16 (87.35)
 
 
 .. parsed-literal::
 
-    Test: [30/79]	Time 0.139 (0.140)	Acc@1 53.12 (62.37)	Acc@5 77.34 (85.33)
+    Test: [30/79]	Time 0.140 (0.140)	Acc@1 53.12 (62.37)	Acc@5 77.34 (85.33)
 
 
 .. parsed-literal::
 
-    Test: [40/79]	Time 0.135 (0.140)	Acc@1 67.19 (60.86)	Acc@5 90.62 (84.51)
+    Test: [40/79]	Time 0.140 (0.140)	Acc@1 67.19 (60.86)	Acc@5 90.62 (84.51)
 
 
 .. parsed-literal::
 
-    Test: [50/79]	Time 0.139 (0.140)	Acc@1 60.16 (60.80)	Acc@5 88.28 (84.42)
+    Test: [50/79]	Time 0.139 (0.139)	Acc@1 60.16 (60.80)	Acc@5 88.28 (84.42)
 
 
 .. parsed-literal::
 
-    Test: [60/79]	Time 0.139 (0.139)	Acc@1 66.41 (60.46)	Acc@5 86.72 (83.79)
+    Test: [60/79]	Time 0.138 (0.139)	Acc@1 66.41 (60.46)	Acc@5 86.72 (83.79)
 
 
 .. parsed-literal::
 
-    Test: [70/79]	Time 0.138 (0.139)	Acc@1 52.34 (60.21)	Acc@5 80.47 (83.33)
+    Test: [70/79]	Time 0.136 (0.139)	Acc@1 52.34 (60.21)	Acc@5 80.47 (83.33)
 
 
 .. parsed-literal::
 
-     * Acc@1 60.740 Acc@5 83.960 Total time: 10.882
+     * Acc@1 60.740 Acc@5 83.960 Total time: 10.886
     Accuracy of FP32 IR model: 60.740
 
 
@@ -831,48 +832,48 @@ Evaluate the FP32 and INT8 models.
 
 .. parsed-literal::
 
-    Test: [ 0/79]	Time 0.133 (0.133)	Acc@1 81.25 (81.25)	Acc@5 91.41 (91.41)
+    Test: [ 0/79]	Time 0.145 (0.145)	Acc@1 82.03 (82.03)	Acc@5 91.41 (91.41)
 
 
 .. parsed-literal::
 
-    Test: [10/79]	Time 0.076 (0.084)	Acc@1 54.69 (66.41)	Acc@5 85.94 (87.64)
+    Test: [10/79]	Time 0.076 (0.083)	Acc@1 55.47 (66.76)	Acc@5 86.72 (87.36)
 
 
 .. parsed-literal::
 
-    Test: [20/79]	Time 0.077 (0.080)	Acc@1 71.09 (64.10)	Acc@5 84.38 (87.05)
+    Test: [20/79]	Time 0.076 (0.080)	Acc@1 70.31 (64.43)	Acc@5 85.16 (87.02)
 
 
 .. parsed-literal::
 
-    Test: [30/79]	Time 0.075 (0.079)	Acc@1 52.34 (62.17)	Acc@5 75.00 (84.98)
+    Test: [30/79]	Time 0.076 (0.079)	Acc@1 53.12 (62.40)	Acc@5 75.78 (84.93)
 
 
 .. parsed-literal::
 
-    Test: [40/79]	Time 0.077 (0.079)	Acc@1 67.19 (60.67)	Acc@5 89.84 (84.22)
+    Test: [40/79]	Time 0.077 (0.078)	Acc@1 67.19 (60.84)	Acc@5 90.62 (84.20)
 
 
 .. parsed-literal::
 
-    Test: [50/79]	Time 0.077 (0.078)	Acc@1 60.16 (60.63)	Acc@5 88.28 (84.22)
+    Test: [50/79]	Time 0.078 (0.078)	Acc@1 59.38 (60.83)	Acc@5 88.28 (84.15)
 
 
 .. parsed-literal::
 
-    Test: [60/79]	Time 0.076 (0.078)	Acc@1 65.62 (60.31)	Acc@5 86.72 (83.67)
+    Test: [60/79]	Time 0.076 (0.078)	Acc@1 64.84 (60.40)	Acc@5 87.50 (83.63)
 
 
 .. parsed-literal::
 
-    Test: [70/79]	Time 0.076 (0.077)	Acc@1 53.12 (60.01)	Acc@5 78.91 (83.20)
+    Test: [70/79]	Time 0.077 (0.078)	Acc@1 53.12 (60.16)	Acc@5 80.47 (83.14)
 
 
 .. parsed-literal::
 
-     * Acc@1 60.540 Acc@5 83.840 Total time: 6.060
-    Accuracy of INT8 IR model: 60.540
+     * Acc@1 60.680 Acc@5 83.770 Total time: 6.075
+    Accuracy of INT8 IR model: 60.680
 
 
 IV. Compare performance of INT8 model and FP32 model in OpenVINO
@@ -941,25 +942,25 @@ throughput (frames per second) values.
 
 .. parsed-literal::
 
-    [ INFO ] Throughput:   38.82 FPS
+    [ INFO ] Throughput:   38.33 FPS
     Benchmark INT8 model (OpenVINO IR)
 
 
 .. parsed-literal::
 
-    [ INFO ] Throughput:   157.27 FPS
+    [ INFO ] Throughput:   155.58 FPS
     Benchmark FP32 model (OpenVINO IR) synchronously
 
 
 .. parsed-literal::
 
-    [ INFO ] Throughput:   40.19 FPS
+    [ INFO ] Throughput:   39.95 FPS
     Benchmark INT8 model (OpenVINO IR) synchronously
 
 
 .. parsed-literal::
 
-    [ INFO ] Throughput:   137.35 FPS
+    [ INFO ] Throughput:   137.77 FPS
 
 
 Show device Information for reference:
diff --git a/docs/notebooks/113-image-classification-quantization-with-output.rst b/docs/notebooks/113-image-classification-quantization-with-output.rst
index 938b55839b012f..b684b40764141f 100644
--- a/docs/notebooks/113-image-classification-quantization-with-output.rst
+++ b/docs/notebooks/113-image-classification-quantization-with-output.rst
@@ -380,94 +380,98 @@ Receiving objects:  75% (212/282)
 
 .. parsed-literal::
 
-    Receiving objects:  78% (220/282), 1.64 MiB | 3.23 MiB/s
+    Receiving objects:  78% (220/282)
 
 .. parsed-literal::
 
-    Receiving objects:  79% (223/282), 1.64 MiB | 3.23 MiB/s
+    Receiving objects:  79% (223/282), 1.71 MiB | 3.35 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  80% (226/282), 1.64 MiB | 3.23 MiB/s
+    Receiving objects:  80% (226/282), 1.71 MiB | 3.35 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  80% (227/282), 3.47 MiB | 3.40 MiB/s
+    Receiving objects:  80% (228/282), 1.71 MiB | 3.35 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  81% (229/282), 3.47 MiB | 3.40 MiB/s
+    Receiving objects:  81% (229/282), 3.54 MiB | 3.45 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  82% (232/282), 3.47 MiB | 3.40 MiB/s
+    Receiving objects:  82% (232/282), 3.54 MiB | 3.45 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  83% (235/282), 3.47 MiB | 3.40 MiB/s
+    Receiving objects:  83% (235/282), 3.54 MiB | 3.45 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  84% (237/282), 5.31 MiB | 3.45 MiB/s
+    Receiving objects:  84% (237/282), 5.36 MiB | 3.48 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  85% (240/282), 5.31 MiB | 3.45 MiB/s
+    Receiving objects:  85% (240/282), 5.36 MiB | 3.48 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  86% (243/282), 5.31 MiB | 3.45 MiB/s
+    Receiving objects:  86% (243/282), 5.36 MiB | 3.48 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  87% (246/282), 7.14 MiB | 3.47 MiB/s
+    Receiving objects:  86% (243/282), 7.20 MiB | 3.49 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  88% (249/282), 7.14 MiB | 3.47 MiB/s
+    Receiving objects:  87% (246/282), 7.20 MiB | 3.49 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  89% (251/282), 7.14 MiB | 3.47 MiB/s
+    Receiving objects:  88% (249/282), 7.20 MiB | 3.49 MiB/s
+
+.. parsed-literal::
+
+    Receiving objects:  89% (251/282), 7.20 MiB | 3.49 MiB/s
 
 .. parsed-literal::
 
     remote: Total 282 (delta 135), reused 269 (delta 128), pack-reused 1
-    Receiving objects:  90% (254/282), 8.97 MiB | 3.49 MiB/s
-Receiving objects:  91% (257/282), 8.97 MiB | 3.49 MiB/s
-Receiving objects:  92% (260/282), 8.97 MiB | 3.49 MiB/s
-Receiving objects:  93% (263/282), 8.97 MiB | 3.49 MiB/s
-Receiving objects:  94% (266/282), 8.97 MiB | 3.49 MiB/s
-Receiving objects:  95% (268/282), 8.97 MiB | 3.49 MiB/s
-Receiving objects:  96% (271/282), 8.97 MiB | 3.49 MiB/s
-Receiving objects:  97% (274/282), 8.97 MiB | 3.49 MiB/s
-Receiving objects:  98% (277/282), 8.97 MiB | 3.49 MiB/s
-Receiving objects:  99% (280/282), 8.97 MiB | 3.49 MiB/s
-Receiving objects: 100% (282/282), 8.97 MiB | 3.49 MiB/s
+    Receiving objects:  90% (254/282), 9.03 MiB | 3.50 MiB/s
+Receiving objects:  91% (257/282), 9.03 MiB | 3.50 MiB/s
+Receiving objects:  92% (260/282), 9.03 MiB | 3.50 MiB/s
+Receiving objects:  93% (263/282), 9.03 MiB | 3.50 MiB/s
+Receiving objects:  94% (266/282), 9.03 MiB | 3.50 MiB/s
+Receiving objects:  95% (268/282), 9.03 MiB | 3.50 MiB/s
+Receiving objects:  96% (271/282), 9.03 MiB | 3.50 MiB/s
+Receiving objects:  97% (274/282), 9.03 MiB | 3.50 MiB/s
+Receiving objects:  98% (277/282), 9.03 MiB | 3.50 MiB/s
+Receiving objects:  99% (280/282), 9.03 MiB | 3.50 MiB/s
+Receiving objects: 100% (282/282), 9.03 MiB | 3.50 MiB/s
 Receiving objects: 100% (282/282), 9.22 MiB | 3.52 MiB/s, done.
     Resolving deltas:   0% (0/135)
-Resolving deltas:   2% (4/135)
-Resolving deltas:   5% (7/135)
+Resolving deltas:   2% (3/135)
+Resolving deltas:   5% (8/135)
 Resolving deltas:   6% (9/135)
-Resolving deltas:  11% (16/135)
+Resolving deltas:  12% (17/135)
 Resolving deltas:  17% (24/135)
-Resolving deltas:  18% (25/135)
 Resolving deltas:  23% (32/135)
-Resolving deltas:  25% (34/135)
 Resolving deltas:  27% (37/135)
-Resolving deltas:  28% (38/135)
-Resolving deltas:  34% (46/135)
+Resolving deltas:  28% (39/135)
+Resolving deltas:  29% (40/135)
+Resolving deltas:  30% (41/135)
+Resolving deltas:  31% (42/135)
+Resolving deltas:  32% (44/135)
+Resolving deltas:  34% (47/135)
 Resolving deltas:  40% (54/135)
-Resolving deltas:  45% (62/135)
-Resolving deltas:  46% (63/135)
-Resolving deltas:  50% (68/135)
-Resolving deltas:  57% (77/135)
+Resolving deltas:  45% (61/135)
+Resolving deltas:  47% (64/135)
+Resolving deltas:  51% (69/135)
+Resolving deltas:  57% (78/135)
 Resolving deltas:  58% (79/135)
-Resolving deltas:  59% (80/135)
 Resolving deltas:  60% (81/135)
-Resolving deltas:  61% (83/135)
-Resolving deltas:  66% (90/135)
-Resolving deltas:  71% (97/135)
+Resolving deltas:  62% (84/135)
+Resolving deltas:  71% (96/135)
 
 .. parsed-literal::
 
@@ -544,2202 +548,2187 @@ Preprocessing for model obtained from training
 .. parsed-literal::
 
 
-  0%|          | 32768/170498071 [00:00<17:10, 165400.38it/s]
-
-.. parsed-literal::
-
-
-  0%|          | 98304/170498071 [00:00<07:53, 360146.13it/s]
+  0%|          | 32768/170498071 [00:00<17:05, 166212.70it/s]
 
 .. parsed-literal::
 
 
-  0%|          | 196608/170498071 [00:00<04:53, 580743.16it/s]
+  0%|          | 98304/170498071 [00:00<07:47, 364627.91it/s]
 
 .. parsed-literal::
 
 
-  0%|          | 425984/170498071 [00:00<02:29, 1138809.29it/s]
+  0%|          | 196608/170498071 [00:00<04:49, 587907.81it/s]
 
 .. parsed-literal::
 
 
-  0%|          | 819200/170498071 [00:00<01:25, 1980588.44it/s]
+  0%|          | 393216/170498071 [00:00<02:42, 1049548.10it/s]
 
 .. parsed-literal::
 
 
-  1%|          | 1179648/170498071 [00:00<01:09, 2421723.34it/s]
+  0%|          | 786432/170498071 [00:00<01:26, 1970714.89it/s]
 
 .. parsed-literal::
 
 
-  1%|          | 1572864/170498071 [00:00<01:00, 2795941.30it/s]
+  1%|          | 1179648/170498071 [00:00<01:06, 2549180.54it/s]
 
 .. parsed-literal::
 
 
-  1%|          | 1966080/170498071 [00:00<00:55, 3033037.53it/s]
+  1%|          | 1572864/170498071 [00:00<00:57, 2941902.04it/s]
 
 .. parsed-literal::
 
 
-  1%|▏         | 2359296/170498071 [00:01<00:52, 3206292.66it/s]
+  1%|          | 1966080/170498071 [00:00<00:52, 3207502.78it/s]
 
 .. parsed-literal::
 
 
-  2%|▏         | 2752512/170498071 [00:01<00:50, 3308414.12it/s]
+  1%|▏         | 2359296/170498071 [00:01<00:49, 3373409.86it/s]
 
 .. parsed-literal::
 
 
-  2%|▏         | 3145728/170498071 [00:01<00:49, 3382848.82it/s]
+  2%|▏         | 2752512/170498071 [00:01<00:48, 3484764.01it/s]
 
 .. parsed-literal::
 
 
-  2%|▏         | 3538944/170498071 [00:01<00:48, 3432400.57it/s]
+  2%|▏         | 3145728/170498071 [00:01<00:46, 3564118.02it/s]
 
 .. parsed-literal::
 
 
-  2%|▏         | 3932160/170498071 [00:01<00:47, 3479365.07it/s]
+  2%|▏         | 3538944/170498071 [00:01<00:45, 3634473.45it/s]
 
 .. parsed-literal::
 
 
-  3%|▎         | 4325376/170498071 [00:01<00:47, 3499116.91it/s]
+  2%|▏         | 3932160/170498071 [00:01<00:45, 3681580.62it/s]
 
 .. parsed-literal::
 
 
-  3%|▎         | 4718592/170498071 [00:01<00:47, 3527111.73it/s]
+  3%|▎         | 4325376/170498071 [00:01<00:44, 3700893.16it/s]
 
 .. parsed-literal::
 
 
-  3%|▎         | 5111808/170498071 [00:01<00:46, 3531519.62it/s]
+  3%|▎         | 4718592/170498071 [00:01<00:44, 3727400.96it/s]
 
 .. parsed-literal::
 
 
-  3%|▎         | 5472256/170498071 [00:01<00:46, 3529318.26it/s]
+  3%|▎         | 5111808/170498071 [00:01<00:44, 3729318.04it/s]
 
 .. parsed-literal::
 
 
-  3%|▎         | 5865472/170498071 [00:02<00:46, 3549149.70it/s]
+  3%|▎         | 5505024/170498071 [00:01<00:44, 3730061.67it/s]
 
 .. parsed-literal::
 
 
-  4%|▎         | 6258688/170498071 [00:02<00:46, 3562985.35it/s]
+  3%|▎         | 5898240/170498071 [00:01<00:43, 3750969.28it/s]
 
 .. parsed-literal::
 
 
-  4%|▍         | 6651904/170498071 [00:02<00:46, 3558474.98it/s]
+  4%|▎         | 6291456/170498071 [00:02<00:43, 3749865.11it/s]
 
 .. parsed-literal::
 
 
-  4%|▍         | 7045120/170498071 [00:02<00:45, 3570143.85it/s]
+  4%|▍         | 6684672/170498071 [00:02<00:43, 3763008.02it/s]
 
 .. parsed-literal::
 
 
-  4%|▍         | 7438336/170498071 [00:02<00:45, 3576922.18it/s]
+  4%|▍         | 7077888/170498071 [00:02<00:43, 3760280.87it/s]
 
 .. parsed-literal::
 
 
-  5%|▍         | 7831552/170498071 [00:02<00:45, 3568632.85it/s]
+  4%|▍         | 7471104/170498071 [00:02<00:43, 3772836.07it/s]
 
 .. parsed-literal::
 
 
-  5%|▍         | 8192000/170498071 [00:02<00:45, 3544062.59it/s]
+  5%|▍         | 7864320/170498071 [00:02<00:43, 3763036.38it/s]
 
 .. parsed-literal::
 
 
-  5%|▌         | 8585216/170498071 [00:02<00:45, 3544031.60it/s]
+  5%|▍         | 8257536/170498071 [00:02<00:43, 3756139.25it/s]
 
 .. parsed-literal::
 
 
-  5%|▌         | 8978432/170498071 [00:02<00:45, 3545268.29it/s]
+  5%|▌         | 8650752/170498071 [00:02<00:42, 3772264.41it/s]
 
 .. parsed-literal::
 
 
-  5%|▌         | 9371648/170498071 [00:03<00:45, 3543490.57it/s]
+  5%|▌         | 9043968/170498071 [00:02<00:42, 3761271.41it/s]
 
 .. parsed-literal::
 
 
-  6%|▌         | 9764864/170498071 [00:03<00:45, 3545636.67it/s]
+  6%|▌         | 9437184/170498071 [00:02<00:42, 3758117.66it/s]
 
 .. parsed-literal::
 
 
-  6%|▌         | 10158080/170498071 [00:03<00:45, 3545069.53it/s]
+  6%|▌         | 9830400/170498071 [00:03<00:42, 3771903.27it/s]
 
 .. parsed-literal::
 
 
-  6%|▌         | 10551296/170498071 [00:03<00:44, 3559881.78it/s]
+  6%|▌         | 10223616/170498071 [00:03<00:42, 3765693.38it/s]
 
 .. parsed-literal::
 
 
-  6%|▋         | 10944512/170498071 [00:03<00:44, 3551369.20it/s]
+  6%|▌         | 10616832/170498071 [00:03<00:42, 3760355.48it/s]
 
 .. parsed-literal::
 
 
-  7%|▋         | 11337728/170498071 [00:03<00:44, 3564879.33it/s]
+  6%|▋         | 11010048/170498071 [00:03<00:42, 3771889.89it/s]
 
 .. parsed-literal::
 
 
-  7%|▋         | 11698176/170498071 [00:03<00:44, 3562378.48it/s]
+  7%|▋         | 11403264/170498071 [00:03<00:42, 3765896.00it/s]
 
 .. parsed-literal::
 
 
-  7%|▋         | 12091392/170498071 [00:03<00:44, 3571556.14it/s]
+  7%|▋         | 11796480/170498071 [00:03<00:42, 3770225.19it/s]
 
 .. parsed-literal::
 
 
-  7%|▋         | 12484608/170498071 [00:03<00:44, 3574867.11it/s]
+  7%|▋         | 12189696/170498071 [00:03<00:42, 3761499.01it/s]
 
 .. parsed-literal::
 
 
-  8%|▊         | 12877824/170498071 [00:04<00:44, 3550308.74it/s]
+  7%|▋         | 12582912/170498071 [00:03<00:41, 3772024.31it/s]
 
 .. parsed-literal::
 
 
-  8%|▊         | 13271040/170498071 [00:04<00:44, 3561931.30it/s]
+  8%|▊         | 12976128/170498071 [00:03<00:43, 3646344.25it/s]
 
 .. parsed-literal::
 
 
-  8%|▊         | 13664256/170498071 [00:04<00:44, 3555095.20it/s]
+  8%|▊         | 13369344/170498071 [00:03<00:42, 3689742.42it/s]
 
 .. parsed-literal::
 
 
-  8%|▊         | 14057472/170498071 [00:04<00:44, 3548885.57it/s]
+  8%|▊         | 13762560/170498071 [00:04<00:42, 3722174.24it/s]
 
 .. parsed-literal::
 
 
-  8%|▊         | 14450688/170498071 [00:04<00:43, 3548289.35it/s]
+  8%|▊         | 14155776/170498071 [00:04<00:41, 3729804.42it/s]
 
 .. parsed-literal::
 
 
-  9%|▊         | 14843904/170498071 [00:04<00:43, 3547324.81it/s]
+  9%|▊         | 14548992/170498071 [00:04<00:41, 3748900.65it/s]
 
 .. parsed-literal::
 
 
-  9%|▉         | 15237120/170498071 [00:04<00:43, 3547333.38it/s]
+  9%|▉         | 14942208/170498071 [00:04<00:41, 3747256.60it/s]
 
 .. parsed-literal::
 
 
-  9%|▉         | 15630336/170498071 [00:04<00:43, 3560580.39it/s]
+  9%|▉         | 15335424/170498071 [00:04<00:41, 3760600.26it/s]
 
 .. parsed-literal::
 
 
-  9%|▉         | 16023552/170498071 [00:04<00:43, 3554961.53it/s]
+  9%|▉         | 15728640/170498071 [00:04<00:41, 3756190.99it/s]
 
 .. parsed-literal::
 
 
- 10%|▉         | 16416768/170498071 [00:05<00:43, 3549091.05it/s]
+  9%|▉         | 16121856/170498071 [00:04<00:40, 3769291.22it/s]
 
 .. parsed-literal::
 
 
- 10%|▉         | 16809984/170498071 [00:05<00:43, 3563993.52it/s]
+ 10%|▉         | 16515072/170498071 [00:04<00:40, 3765129.18it/s]
 
 .. parsed-literal::
 
 
- 10%|█         | 17203200/170498071 [00:05<00:43, 3559977.68it/s]
+ 10%|▉         | 16908288/170498071 [00:04<00:40, 3775219.04it/s]
 
 .. parsed-literal::
 
 
- 10%|█         | 17596416/170498071 [00:05<00:42, 3568951.11it/s]
+ 10%|█         | 17301504/170498071 [00:05<00:40, 3768045.55it/s]
 
 .. parsed-literal::
 
 
- 11%|█         | 17989632/170498071 [00:05<00:42, 3562048.91it/s]
+ 10%|█         | 17694720/170498071 [00:05<00:40, 3779356.16it/s]
 
 .. parsed-literal::
 
 
- 11%|█         | 18382848/170498071 [00:05<00:42, 3574349.36it/s]
+ 11%|█         | 18087936/170498071 [00:05<00:40, 3767156.95it/s]
 
 .. parsed-literal::
 
 
- 11%|█         | 18776064/170498071 [00:05<00:42, 3560324.50it/s]
+ 11%|█         | 18481152/170498071 [00:05<00:40, 3774439.30it/s]
 
 .. parsed-literal::
 
 
- 11%|█         | 19136512/170498071 [00:05<00:42, 3564354.68it/s]
+ 11%|█         | 18874368/170498071 [00:05<00:40, 3767749.65it/s]
 
 .. parsed-literal::
 
 
- 11%|█▏        | 19529728/170498071 [00:05<00:42, 3555540.30it/s]
+ 11%|█▏        | 19267584/170498071 [00:05<00:40, 3778430.90it/s]
 
 .. parsed-literal::
 
 
- 12%|█▏        | 19922944/170498071 [00:05<00:42, 3568736.92it/s]
+ 12%|█▏        | 19660800/170498071 [00:05<00:39, 3772794.54it/s]
 
 .. parsed-literal::
 
 
- 12%|█▏        | 20316160/170498071 [00:06<00:42, 3558457.50it/s]
+ 12%|█▏        | 20054016/170498071 [00:05<00:39, 3764866.27it/s]
 
 .. parsed-literal::
 
 
- 12%|█▏        | 20709376/170498071 [00:06<00:42, 3554587.73it/s]
+ 12%|█▏        | 20447232/170498071 [00:05<00:39, 3776940.26it/s]
 
 .. parsed-literal::
 
 
- 12%|█▏        | 21102592/170498071 [00:06<00:42, 3552073.22it/s]
+ 12%|█▏        | 20840448/170498071 [00:05<00:39, 3766939.32it/s]
 
 .. parsed-literal::
 
 
- 13%|█▎        | 21495808/170498071 [00:06<00:41, 3564788.39it/s]
+ 12%|█▏        | 21233664/170498071 [00:06<00:39, 3778488.77it/s]
 
 .. parsed-literal::
 
 
- 13%|█▎        | 21889024/170498071 [00:06<00:41, 3551887.34it/s]
+ 13%|█▎        | 21626880/170498071 [00:06<00:39, 3767888.28it/s]
 
 .. parsed-literal::
 
 
- 13%|█▎        | 22282240/170498071 [00:06<00:41, 3563483.58it/s]
+ 13%|█▎        | 22020096/170498071 [00:06<00:39, 3775536.50it/s]
 
 .. parsed-literal::
 
 
- 13%|█▎        | 22675456/170498071 [00:06<00:41, 3556453.43it/s]
+ 13%|█▎        | 22413312/170498071 [00:06<00:39, 3784667.31it/s]
 
 .. parsed-literal::
 
 
- 14%|█▎        | 23068672/170498071 [00:06<00:41, 3553670.60it/s]
+ 13%|█▎        | 22806528/170498071 [00:06<00:39, 3771695.19it/s]
 
 .. parsed-literal::
 
 
- 14%|█▍        | 23461888/170498071 [00:06<00:41, 3550202.48it/s]
+ 14%|█▎        | 23199744/170498071 [00:06<00:38, 3781098.36it/s]
 
 .. parsed-literal::
 
 
- 14%|█▍        | 23855104/170498071 [00:07<00:41, 3548895.43it/s]
+ 14%|█▍        | 23592960/170498071 [00:06<00:38, 3768526.04it/s]
 
 .. parsed-literal::
 
 
- 14%|█▍        | 24248320/170498071 [00:07<00:41, 3546992.15it/s]
+ 14%|█▍        | 23986176/170498071 [00:06<00:38, 3763839.52it/s]
 
 .. parsed-literal::
 
 
- 14%|█▍        | 24608768/170498071 [00:07<00:41, 3549544.21it/s]
+ 14%|█▍        | 24379392/170498071 [00:06<00:38, 3762730.51it/s]
 
 .. parsed-literal::
 
 
- 15%|█▍        | 25001984/170498071 [00:07<00:40, 3549882.59it/s]
+ 15%|█▍        | 24772608/170498071 [00:06<00:38, 3759140.43it/s]
 
 .. parsed-literal::
 
 
- 15%|█▍        | 25395200/170498071 [00:07<00:40, 3549485.17it/s]
+ 15%|█▍        | 25165824/170498071 [00:07<00:38, 3754317.43it/s]
 
 .. parsed-literal::
 
 
- 15%|█▌        | 25788416/170498071 [00:07<00:40, 3561550.83it/s]
+ 15%|█▍        | 25559040/170498071 [00:07<00:38, 3755740.60it/s]
 
 .. parsed-literal::
 
 
- 15%|█▌        | 26181632/170498071 [00:07<00:40, 3568879.63it/s]
+ 15%|█▌        | 25952256/170498071 [00:07<00:38, 3749437.85it/s]
 
 .. parsed-literal::
 
 
- 16%|█▌        | 26574848/170498071 [00:07<00:40, 3558381.72it/s]
+ 15%|█▌        | 26345472/170498071 [00:07<00:38, 3750633.95it/s]
 
 .. parsed-literal::
 
 
- 16%|█▌        | 26968064/170498071 [00:07<00:40, 3548967.93it/s]
+ 16%|█▌        | 26738688/170498071 [00:07<00:38, 3751863.38it/s]
 
 .. parsed-literal::
 
 
- 16%|█▌        | 27361280/170498071 [00:08<00:40, 3562580.09it/s]
+ 16%|█▌        | 27131904/170498071 [00:07<00:38, 3749632.52it/s]
 
 .. parsed-literal::
 
 
- 16%|█▋        | 27754496/170498071 [00:08<00:40, 3559588.22it/s]
+ 16%|█▌        | 27525120/170498071 [00:07<00:38, 3750481.16it/s]
 
 .. parsed-literal::
 
 
- 17%|█▋        | 28147712/170498071 [00:08<00:40, 3558630.93it/s]
+ 16%|█▋        | 27918336/170498071 [00:07<00:37, 3767501.75it/s]
 
 .. parsed-literal::
 
 
- 17%|█▋        | 28540928/170498071 [00:08<00:39, 3555414.89it/s]
+ 17%|█▋        | 28311552/170498071 [00:07<00:37, 3762282.12it/s]
 
 .. parsed-literal::
 
 
- 17%|█▋        | 28934144/170498071 [00:08<00:39, 3551700.71it/s]
+ 17%|█▋        | 28704768/170498071 [00:08<00:37, 3757208.73it/s]
 
 .. parsed-literal::
 
 
- 17%|█▋        | 29327360/170498071 [00:08<00:39, 3549475.40it/s]
+ 17%|█▋        | 29097984/170498071 [00:08<00:37, 3767048.10it/s]
 
 .. parsed-literal::
 
 
- 17%|█▋        | 29720576/170498071 [00:08<00:39, 3543596.42it/s]
+ 17%|█▋        | 29491200/170498071 [00:08<00:37, 3775503.33it/s]
 
 .. parsed-literal::
 
 
- 18%|█▊        | 30113792/170498071 [00:08<00:39, 3557966.72it/s]
+ 18%|█▊        | 29884416/170498071 [00:08<00:37, 3777539.29it/s]
 
 .. parsed-literal::
 
 
- 18%|█▊        | 30507008/170498071 [00:08<00:39, 3552269.41it/s]
+ 18%|█▊        | 30277632/170498071 [00:08<00:37, 3771522.68it/s]
 
 .. parsed-literal::
 
 
- 18%|█▊        | 30900224/170498071 [00:09<00:39, 3549800.19it/s]
+ 18%|█▊        | 30670848/170498071 [00:08<00:37, 3768097.10it/s]
 
 .. parsed-literal::
 
 
- 18%|█▊        | 31293440/170498071 [00:09<00:39, 3558197.12it/s]
+ 18%|█▊        | 31064064/170498071 [00:08<00:37, 3760340.19it/s]
 
 .. parsed-literal::
 
 
- 19%|█▊        | 31686656/170498071 [00:09<00:39, 3553319.24it/s]
+ 18%|█▊        | 31457280/170498071 [00:08<00:36, 3772414.30it/s]
 
 .. parsed-literal::
 
 
- 19%|█▉        | 32079872/170498071 [00:09<00:38, 3565816.87it/s]
+ 19%|█▊        | 31850496/170498071 [00:08<00:36, 3763910.45it/s]
 
 .. parsed-literal::
 
 
- 19%|█▉        | 32440320/170498071 [00:09<00:38, 3559251.24it/s]
+ 19%|█▉        | 32243712/170498071 [00:08<00:36, 3759185.71it/s]
 
 .. parsed-literal::
 
 
- 19%|█▉        | 32833536/170498071 [00:09<00:38, 3568883.69it/s]
+ 19%|█▉        | 32636928/170498071 [00:09<00:36, 3752188.93it/s]
 
 .. parsed-literal::
 
 
- 19%|█▉        | 33193984/170498071 [00:09<00:38, 3529843.65it/s]
+ 19%|█▉        | 33030144/170498071 [00:09<00:36, 3766797.06it/s]
 
 .. parsed-literal::
 
 
- 20%|█▉        | 33587200/170498071 [00:09<00:38, 3533902.78it/s]
+ 20%|█▉        | 33423360/170498071 [00:09<00:36, 3761136.47it/s]
 
 .. parsed-literal::
 
 
- 20%|█▉        | 33980416/170498071 [00:09<00:38, 3552288.24it/s]
+ 20%|█▉        | 33816576/170498071 [00:09<00:36, 3756244.61it/s]
 
 .. parsed-literal::
 
 
- 20%|██        | 34373632/170498071 [00:10<00:38, 3549985.87it/s]
+ 20%|██        | 34209792/170498071 [00:09<00:36, 3768659.77it/s]
 
 .. parsed-literal::
 
 
- 20%|██        | 34766848/170498071 [00:10<00:38, 3563816.63it/s]
+ 20%|██        | 34603008/170498071 [00:09<00:36, 3762173.64it/s]
 
 .. parsed-literal::
 
 
- 21%|██        | 35160064/170498071 [00:10<00:38, 3550534.02it/s]
+ 21%|██        | 34996224/170498071 [00:09<00:35, 3774047.75it/s]
 
 .. parsed-literal::
 
 
- 21%|██        | 35553280/170498071 [00:10<00:38, 3547626.36it/s]
+ 21%|██        | 35389440/170498071 [00:09<00:35, 3767572.06it/s]
 
 .. parsed-literal::
 
 
- 21%|██        | 35946496/170498071 [00:10<00:37, 3547746.28it/s]
+ 21%|██        | 35782656/170498071 [00:09<00:35, 3779984.10it/s]
 
 .. parsed-literal::
 
 
- 21%|██▏       | 36339712/170498071 [00:10<00:37, 3561814.91it/s]
+ 21%|██        | 36175872/170498071 [00:10<00:35, 3771377.51it/s]
 
 .. parsed-literal::
 
 
- 22%|██▏       | 36732928/170498071 [00:10<00:37, 3556634.66it/s]
+ 21%|██▏       | 36569088/170498071 [00:10<00:35, 3761817.99it/s]
 
 .. parsed-literal::
 
 
- 22%|██▏       | 37126144/170498071 [00:10<00:37, 3566448.11it/s]
+ 22%|██▏       | 36962304/170498071 [00:10<00:35, 3769026.33it/s]
 
 .. parsed-literal::
 
 
- 22%|██▏       | 37519360/170498071 [00:10<00:37, 3575430.66it/s]
+ 22%|██▏       | 37355520/170498071 [00:10<00:35, 3763490.51it/s]
 
 .. parsed-literal::
 
 
- 22%|██▏       | 37912576/170498071 [00:11<00:37, 3563826.39it/s]
+ 22%|██▏       | 37748736/170498071 [00:10<00:35, 3775898.32it/s]
 
 .. parsed-literal::
 
 
- 22%|██▏       | 38305792/170498071 [00:11<00:37, 3558700.72it/s]
+ 22%|██▏       | 38141952/170498071 [00:10<00:35, 3765847.42it/s]
 
 .. parsed-literal::
 
 
- 23%|██▎       | 38666240/170498071 [00:11<00:37, 3560403.05it/s]
+ 23%|██▎       | 38535168/170498071 [00:10<00:34, 3778934.96it/s]
 
 .. parsed-literal::
 
 
- 23%|██▎       | 39059456/170498071 [00:11<00:36, 3556571.47it/s]
+ 23%|██▎       | 38928384/170498071 [00:10<00:34, 3764725.55it/s]
 
 .. parsed-literal::
 
 
- 23%|██▎       | 39452672/170498071 [00:11<00:36, 3555197.40it/s]
+ 23%|██▎       | 39321600/170498071 [00:10<00:34, 3775183.84it/s]
 
 .. parsed-literal::
 
 
- 23%|██▎       | 39845888/170498071 [00:11<00:36, 3553779.08it/s]
+ 23%|██▎       | 39714816/170498071 [00:10<00:34, 3784262.94it/s]
 
 .. parsed-literal::
 
 
- 24%|██▎       | 40239104/170498071 [00:11<00:36, 3551417.01it/s]
+ 24%|██▎       | 40108032/170498071 [00:11<00:34, 3770568.22it/s]
 
 .. parsed-literal::
 
 
- 24%|██▍       | 40632320/170498071 [00:11<00:36, 3547718.37it/s]
+ 24%|██▍       | 40501248/170498071 [00:11<00:34, 3764569.11it/s]
 
 .. parsed-literal::
 
 
- 24%|██▍       | 41025536/170498071 [00:11<00:36, 3558821.35it/s]
+ 24%|██▍       | 40894464/170498071 [00:11<00:34, 3761003.64it/s]
 
 .. parsed-literal::
 
 
- 24%|██▍       | 41418752/170498071 [00:12<00:36, 3570243.40it/s]
+ 24%|██▍       | 41287680/170498071 [00:11<00:34, 3756783.29it/s]
 
 .. parsed-literal::
 
 
- 25%|██▍       | 41811968/170498071 [00:12<00:36, 3558069.54it/s]
+ 24%|██▍       | 41680896/170498071 [00:11<00:34, 3753770.60it/s]
 
 .. parsed-literal::
 
 
- 25%|██▍       | 42205184/170498071 [00:12<00:36, 3555392.32it/s]
+ 25%|██▍       | 42074112/170498071 [00:11<00:34, 3769468.00it/s]
 
 .. parsed-literal::
 
 
- 25%|██▍       | 42598400/170498071 [00:12<00:35, 3552945.21it/s]
+ 25%|██▍       | 42467328/170498071 [00:11<00:33, 3781392.65it/s]
 
 .. parsed-literal::
 
 
- 25%|██▌       | 42991616/170498071 [00:12<00:35, 3565505.94it/s]
+ 25%|██▌       | 42860544/170498071 [00:11<00:33, 3774928.49it/s]
 
 .. parsed-literal::
 
 
- 25%|██▌       | 43384832/170498071 [00:12<00:35, 3555857.99it/s]
+ 25%|██▌       | 43253760/170498071 [00:11<00:33, 3766898.03it/s]
 
 .. parsed-literal::
 
 
- 26%|██▌       | 43778048/170498071 [00:12<00:35, 3552596.59it/s]
+ 26%|██▌       | 43646976/170498071 [00:11<00:33, 3777327.77it/s]
 
 .. parsed-literal::
 
 
- 26%|██▌       | 44171264/170498071 [00:12<00:35, 3549274.48it/s]
+ 26%|██▌       | 44040192/170498071 [00:12<00:33, 3765844.02it/s]
 
 .. parsed-literal::
 
 
- 26%|██▌       | 44564480/170498071 [00:12<00:35, 3544741.17it/s]
+ 26%|██▌       | 44433408/170498071 [00:12<00:33, 3775911.40it/s]
 
 .. parsed-literal::
 
 
- 26%|██▋       | 44957696/170498071 [00:13<00:35, 3545828.65it/s]
+ 26%|██▋       | 44826624/170498071 [00:12<00:33, 3782290.53it/s]
 
 .. parsed-literal::
 
 
- 27%|██▋       | 45350912/170498071 [00:13<00:35, 3559659.89it/s]
+ 27%|██▋       | 45219840/170498071 [00:12<00:33, 3772901.52it/s]
 
 .. parsed-literal::
 
 
- 27%|██▋       | 45744128/170498071 [00:13<00:35, 3551098.29it/s]
+ 27%|██▋       | 45613056/170498071 [00:12<00:33, 3781793.44it/s]
 
 .. parsed-literal::
 
 
- 27%|██▋       | 46137344/170498071 [00:13<00:34, 3564204.76it/s]
+ 27%|██▋       | 46006272/170498071 [00:12<00:33, 3714231.21it/s]
 
 .. parsed-literal::
 
 
- 27%|██▋       | 46497792/170498071 [00:13<00:34, 3569395.47it/s]
+ 27%|██▋       | 46399488/170498071 [00:12<00:33, 3739005.08it/s]
 
 .. parsed-literal::
 
 
- 28%|██▊       | 46891008/170498071 [00:13<00:34, 3561863.01it/s]
+ 27%|██▋       | 46792704/170498071 [00:12<00:33, 3739775.61it/s]
 
 .. parsed-literal::
 
 
- 28%|██▊       | 47284224/170498071 [00:13<00:34, 3567880.10it/s]
+ 28%|██▊       | 47185920/170498071 [00:12<00:32, 3741206.05it/s]
 
 .. parsed-literal::
 
 
- 28%|██▊       | 47677440/170498071 [00:13<00:34, 3556957.85it/s]
+ 28%|██▊       | 47579136/170498071 [00:13<00:32, 3760037.28it/s]
 
 .. parsed-literal::
 
 
- 28%|██▊       | 48070656/170498071 [00:13<00:34, 3552223.84it/s]
+ 28%|██▊       | 47972352/170498071 [00:13<00:32, 3757286.61it/s]
 
 .. parsed-literal::
 
 
- 28%|██▊       | 48463872/170498071 [00:14<00:34, 3547628.03it/s]
+ 28%|██▊       | 48365568/170498071 [00:13<00:32, 3769642.07it/s]
 
 .. parsed-literal::
 
 
- 29%|██▊       | 48857088/170498071 [00:14<00:34, 3533134.95it/s]
+ 29%|██▊       | 48758784/170498071 [00:13<00:32, 3761617.83it/s]
 
 .. parsed-literal::
 
 
- 29%|██▉       | 49250304/170498071 [00:14<00:34, 3539026.54it/s]
+ 29%|██▉       | 49152000/170498071 [00:13<00:32, 3751118.48it/s]
 
 .. parsed-literal::
 
 
- 29%|██▉       | 49643520/170498071 [00:14<00:34, 3541345.88it/s]
+ 29%|██▉       | 49545216/170498071 [00:13<00:32, 3764275.43it/s]
 
 .. parsed-literal::
 
 
- 29%|██▉       | 50036736/170498071 [00:14<00:34, 3542782.10it/s]
+ 29%|██▉       | 49938432/170498071 [00:13<00:32, 3760927.09it/s]
 
 .. parsed-literal::
 
 
- 30%|██▉       | 50429952/170498071 [00:14<00:33, 3546294.62it/s]
+ 30%|██▉       | 50331648/170498071 [00:13<00:31, 3758265.61it/s]
 
 .. parsed-literal::
 
 
- 30%|██▉       | 50823168/170498071 [00:14<00:33, 3548538.54it/s]
+ 30%|██▉       | 50724864/170498071 [00:13<00:31, 3756510.05it/s]
 
 .. parsed-literal::
 
 
- 30%|███       | 51216384/170498071 [00:14<00:33, 3546227.48it/s]
+ 30%|██▉       | 51118080/170498071 [00:13<00:31, 3767986.62it/s]
 
 .. parsed-literal::
 
 
- 30%|███       | 51576832/170498071 [00:14<00:33, 3551977.46it/s]
+ 30%|███       | 51511296/170498071 [00:14<00:31, 3762906.44it/s]
 
 .. parsed-literal::
 
 
- 30%|███       | 51970048/170498071 [00:15<00:33, 3548814.09it/s]
+ 30%|███       | 51904512/170498071 [00:14<00:31, 3754549.63it/s]
 
 .. parsed-literal::
 
 
- 31%|███       | 52363264/170498071 [00:15<00:33, 3548685.66it/s]
+ 31%|███       | 52297728/170498071 [00:14<00:31, 3767516.91it/s]
 
 .. parsed-literal::
 
 
- 31%|███       | 52756480/170498071 [00:15<00:33, 3549116.53it/s]
+ 31%|███       | 52690944/170498071 [00:14<00:31, 3763114.22it/s]
 
 .. parsed-literal::
 
 
- 31%|███       | 53149696/170498071 [00:15<00:33, 3545436.68it/s]
+ 31%|███       | 53084160/170498071 [00:14<00:31, 3775150.93it/s]
 
 .. parsed-literal::
 
 
- 31%|███▏      | 53542912/170498071 [00:15<00:32, 3563283.62it/s]
+ 31%|███▏      | 53477376/170498071 [00:14<00:31, 3768186.59it/s]
 
 .. parsed-literal::
 
 
- 32%|███▏      | 53936128/170498071 [00:15<00:32, 3549644.55it/s]
+ 32%|███▏      | 53870592/170498071 [00:14<00:31, 3761714.83it/s]
 
 .. parsed-literal::
 
 
- 32%|███▏      | 54329344/170498071 [00:15<00:32, 3563056.99it/s]
+ 32%|███▏      | 54263808/170498071 [00:14<00:30, 3772328.82it/s]
 
 .. parsed-literal::
 
 
- 32%|███▏      | 54722560/170498071 [00:15<00:32, 3568583.27it/s]
+ 32%|███▏      | 54657024/170498071 [00:14<00:30, 3761829.12it/s]
 
 .. parsed-literal::
 
 
- 32%|███▏      | 55115776/170498071 [00:15<00:32, 3561331.09it/s]
+ 32%|███▏      | 55050240/170498071 [00:15<00:30, 3758328.18it/s]
 
 .. parsed-literal::
 
 
- 33%|███▎      | 55508992/170498071 [00:16<00:32, 3557590.83it/s]
+ 33%|███▎      | 55443456/170498071 [00:15<00:30, 3753068.63it/s]
 
 .. parsed-literal::
 
 
- 33%|███▎      | 55902208/170498071 [00:16<00:32, 3554532.54it/s]
+ 33%|███▎      | 55836672/170498071 [00:15<00:30, 3768905.29it/s]
 
 .. parsed-literal::
 
 
- 33%|███▎      | 56295424/170498071 [00:16<00:32, 3549222.73it/s]
+ 33%|███▎      | 56229888/170498071 [00:15<00:30, 3778844.32it/s]
 
 .. parsed-literal::
 
 
- 33%|███▎      | 56688640/170498071 [00:16<00:32, 3543742.29it/s]
+ 33%|███▎      | 56623104/170498071 [00:15<00:30, 3768435.39it/s]
 
 .. parsed-literal::
 
 
- 33%|███▎      | 57081856/170498071 [00:16<00:31, 3557420.27it/s]
+ 33%|███▎      | 57016320/170498071 [00:15<00:30, 3762990.47it/s]
 
 .. parsed-literal::
 
 
- 34%|███▎      | 57475072/170498071 [00:16<00:31, 3556208.15it/s]
+ 34%|███▎      | 57409536/170498071 [00:15<00:30, 3758085.96it/s]
 
 .. parsed-literal::
 
 
- 34%|███▍      | 57868288/170498071 [00:16<00:31, 3553788.06it/s]
+ 34%|███▍      | 57802752/170498071 [00:15<00:29, 3756772.02it/s]
 
 .. parsed-literal::
 
 
- 34%|███▍      | 58261504/170498071 [00:16<00:31, 3567339.52it/s]
+ 34%|███▍      | 58195968/170498071 [00:15<00:29, 3769499.15it/s]
 
 .. parsed-literal::
 
 
- 34%|███▍      | 58654720/170498071 [00:16<00:31, 3560489.44it/s]
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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 .. parsed-literal::
 
 
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-
-.. parsed-literal::
-
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-
-.. parsed-literal::
-
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+   100%|██████████| 170498071/170498071 [00:45<00:00, 3727583.78it/s]
 
 
 
@@ -2810,14 +2799,14 @@ about supported parameters can be found on this
 
 .. parsed-literal::
 
-    2024-01-25 23:03:23.248680: I tensorflow/core/util/port.cc:110] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
-    2024-01-25 23:03:23.308103: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+    2024-02-09 22:59:25.557733: I tensorflow/core/util/port.cc:110] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
+    2024-02-09 22:59:25.614970: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
     To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
 
 
 .. parsed-literal::
 
-    2024-01-25 23:03:23.827518: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+    2024-02-09 22:59:26.140513: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
 
 
 
@@ -2827,14 +2816,15 @@ about supported parameters can be found on this
 
 
 
-.. raw:: html
 
-    

 
 
 
 
+.. raw:: html
 
+    
+    

 
 
 
@@ -2845,14 +2835,15 @@ about supported parameters can be found on this
 
 
 
-.. raw:: html
 
-    

 
 
 
 
+.. raw:: html
 
+    
+    

 
 
 
@@ -2993,7 +2984,7 @@ Tool `__
     [ WARNING ] Performance hint was not explicitly specified in command line. Device(AUTO) performance hint will be set to PerformanceMode.THROUGHPUT.
     [Step 4/11] Reading model files
     [ INFO ] Loading model files
-    [ INFO ] Read model took 9.59 ms
+    [ INFO ] Read model took 9.75 ms
     [ INFO ] Original model I/O parameters:
     [ INFO ] Model inputs:
     [ INFO ]     x (node: x) : f32 / [...] / [1,3,32,32]
@@ -3011,7 +3002,7 @@ Tool `__
 
 .. parsed-literal::
 
-    [ INFO ] Compile model took 215.86 ms
+    [ INFO ] Compile model took 198.44 ms
     [Step 8/11] Querying optimal runtime parameters
     [ INFO ] Model:
     [ INFO ]   NETWORK_NAME: Model2
@@ -3019,6 +3010,10 @@ Tool `__
     [ INFO ]   PERFORMANCE_HINT: PerformanceMode.THROUGHPUT
     [ INFO ]   OPTIMAL_NUMBER_OF_INFER_REQUESTS: 12
     [ INFO ]   MULTI_DEVICE_PRIORITIES: CPU
+
+
+.. parsed-literal::
+
     [ INFO ]   CPU:
     [ INFO ]     AFFINITY: Affinity.CORE
     [ INFO ]     CPU_DENORMALS_OPTIMIZATION: False
@@ -3043,25 +3038,21 @@ Tool `__
     [ INFO ] Fill input 'x' with random values
     [Step 10/11] Measuring performance (Start inference asynchronously, 12 inference requests, limits: 15000 ms duration)
     [ INFO ] Benchmarking in inference only mode (inputs filling are not included in measurement loop).
-
-
-.. parsed-literal::
-
-    [ INFO ] First inference took 3.33 ms
+    [ INFO ] First inference took 2.83 ms
 
 
 .. parsed-literal::
 
     [Step 11/11] Dumping statistics report
     [ INFO ] Execution Devices:['CPU']
-    [ INFO ] Count:            88704 iterations
-    [ INFO ] Duration:         15002.65 ms
+    [ INFO ] Count:            88488 iterations
+    [ INFO ] Duration:         15003.02 ms
     [ INFO ] Latency:
-    [ INFO ]    Median:        1.84 ms
+    [ INFO ]    Median:        1.85 ms
     [ INFO ]    Average:       1.85 ms
-    [ INFO ]    Min:           1.19 ms
-    [ INFO ]    Max:           8.90 ms
-    [ INFO ] Throughput:   5912.55 FPS
+    [ INFO ]    Min:           1.17 ms
+    [ INFO ]    Max:           8.69 ms
+    [ INFO ] Throughput:   5898.01 FPS
 
 
 .. code:: ipython3
@@ -3087,7 +3078,7 @@ Tool `__
     [ WARNING ] Performance hint was not explicitly specified in command line. Device(AUTO) performance hint will be set to PerformanceMode.THROUGHPUT.
     [Step 4/11] Reading model files
     [ INFO ] Loading model files
-    [ INFO ] Read model took 19.08 ms
+    [ INFO ] Read model took 18.77 ms
     [ INFO ] Original model I/O parameters:
     [ INFO ] Model inputs:
     [ INFO ]     x (node: x) : f32 / [...] / [1,3,32,32]
@@ -3105,7 +3096,7 @@ Tool `__
 
 .. parsed-literal::
 
-    [ INFO ] Compile model took 331.25 ms
+    [ INFO ] Compile model took 330.74 ms
     [Step 8/11] Querying optimal runtime parameters
     [ INFO ] Model:
     [ INFO ]   NETWORK_NAME: Model2
@@ -3137,21 +3128,21 @@ Tool `__
     [ INFO ] Fill input 'x' with random values
     [Step 10/11] Measuring performance (Start inference asynchronously, 12 inference requests, limits: 15000 ms duration)
     [ INFO ] Benchmarking in inference only mode (inputs filling are not included in measurement loop).
-    [ INFO ] First inference took 1.87 ms
+    [ INFO ] First inference took 2.08 ms
 
 
 .. parsed-literal::
 
     [Step 11/11] Dumping statistics report
     [ INFO ] Execution Devices:['CPU']
-    [ INFO ] Count:            167340 iterations
-    [ INFO ] Duration:         15001.30 ms
+    [ INFO ] Count:            167472 iterations
+    [ INFO ] Duration:         15001.04 ms
     [ INFO ] Latency:
     [ INFO ]    Median:        1.00 ms
     [ INFO ]    Average:       1.03 ms
-    [ INFO ]    Min:           0.72 ms
-    [ INFO ]    Max:           7.10 ms
-    [ INFO ] Throughput:   11155.04 FPS
+    [ INFO ]    Min:           0.68 ms
+    [ INFO ]    Max:           7.03 ms
+    [ INFO ] Throughput:   11164.03 FPS
 
 
 Compare results on four pictures
diff --git a/docs/notebooks/113-image-classification-quantization-with-output_files/index.html.tmp b/docs/notebooks/113-image-classification-quantization-with-output_files/index.html.tmp
deleted file mode 100644
index 9fbe70d140f0be..00000000000000
--- a/docs/notebooks/113-image-classification-quantization-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,7 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/113-image-classification-quantization-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/113-image-classification-quantization-with-output_files/
../
-113-image-classification-quantization-with-outp..> 26-Jan-2024 01:05               14855
-

-
diff --git a/docs/notebooks/115-async-api-with-output.rst b/docs/notebooks/115-async-api-with-output.rst
index 578b1afafdd48c..3c49ba2c2888d2 100644
--- a/docs/notebooks/115-async-api-with-output.rst
+++ b/docs/notebooks/115-async-api-with-output.rst
@@ -122,199 +122,198 @@ each frame of the video.
 
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+... 100%, 248 KB, 1859 KB/s, 0 seconds passed
 
+    
+    ========== Downloading model/intel/person-detection-0202/FP16/person-detection-0202.bin
 
 
 .. parsed-literal::
 
-    
-    ========== Downloading model/intel/person-detection-0202/FP16/person-detection-0202.bin
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@@ -512,7 +511,7 @@ Test performance in Sync Mode
 .. parsed-literal::
 
     Source ended
-    average throuput in sync mode: 43.51 fps
+    average throuput in sync mode: 47.04 fps
 
 
 Async Mode
@@ -651,7 +650,7 @@ Test the performance in Async Mode
 .. parsed-literal::
 
     Source ended
-    average throuput in async mode: 74.01 fps
+    average throuput in async mode: 74.61 fps
 
 
 Compare the performance
@@ -794,5 +793,5 @@ Test the performance with ``AsyncInferQueue``
 
 .. parsed-literal::
 
-    average throughput in async mode with async infer queue: 110.03 fps
+    average throughput in async mode with async infer queue: 113.01 fps
 
diff --git a/docs/notebooks/115-async-api-with-output_files/115-async-api-with-output_21_0.png b/docs/notebooks/115-async-api-with-output_files/115-async-api-with-output_21_0.png
index 20c300e28e4cdd..375f0e9cc31d67 100644
--- a/docs/notebooks/115-async-api-with-output_files/115-async-api-with-output_21_0.png
+++ b/docs/notebooks/115-async-api-with-output_files/115-async-api-with-output_21_0.png
@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
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-size 30402
+oid sha256:8c51610ffd478d0bc5358648e0475259dc8eb04d090c6f55cb860d2e9b8a8cb6
+size 30356
diff --git a/docs/notebooks/115-async-api-with-output_files/index.html.tmp b/docs/notebooks/115-async-api-with-output_files/index.html.tmp
deleted file mode 100644
index c63e3eb059250b..00000000000000
--- a/docs/notebooks/115-async-api-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,10 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/115-async-api-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/115-async-api-with-output_files/
../
-115-async-api-with-output_15_0.png                 26-Jan-2024 01:05                4307
-115-async-api-with-output_19_0.png                 26-Jan-2024 01:05                4307
-115-async-api-with-output_21_0.png                 26-Jan-2024 01:05               30402
-115-async-api-with-output_27_0.png                 26-Jan-2024 01:05                4307
-

-
diff --git a/docs/notebooks/116-sparsity-optimization-with-output.rst b/docs/notebooks/116-sparsity-optimization-with-output.rst
index d2fbad4c9a9d18..4a4df59ee93b20 100644
--- a/docs/notebooks/116-sparsity-optimization-with-output.rst
+++ b/docs/notebooks/116-sparsity-optimization-with-output.rst
@@ -85,14 +85,14 @@ Imports
 
 .. parsed-literal::
 
-    2024-01-25 23:06:01.802535: I tensorflow/core/util/port.cc:110] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
-    2024-01-25 23:06:01.837209: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+    2024-02-09 23:02:05.779349: I tensorflow/core/util/port.cc:110] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
+    2024-02-09 23:02:05.814537: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
     To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
 
 
 .. parsed-literal::
 
-    2024-01-25 23:06:02.398511: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+    2024-02-09 23:02:06.378496: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
 
 
 Download, quantize and sparsify the model, using Hugging Face Optimum API
@@ -228,7 +228,7 @@ as an example. It is recommended to tune based on your applications.
 
 .. parsed-literal::
 
-    [ INFO ] Read model took 60.22 ms
+    [ INFO ] Read model took 62.38 ms
     [ INFO ] Original model I/O parameters:
     [ INFO ] Model inputs:
     [ INFO ]     input_ids (node: input_ids) : i64 / [...] / [?,?]
@@ -239,7 +239,7 @@ as an example. It is recommended to tune based on your applications.
     [Step 5/11] Resizing model to match image sizes and given batch
     [ INFO ] Model batch size: 1
     [ INFO ] Reshaping model: 'input_ids': [1,64], 'attention_mask': [1,64], 'token_type_ids': [1,64]
-    [ INFO ] Reshape model took 23.06 ms
+    [ INFO ] Reshape model took 23.14 ms
     [Step 6/11] Configuring input of the model
     [ INFO ] Model inputs:
     [ INFO ]     input_ids (node: input_ids) : i64 / [...] / [1,64]
@@ -252,7 +252,7 @@ as an example. It is recommended to tune based on your applications.
 
 .. parsed-literal::
 
-    [ INFO ] Compile model took 1064.23 ms
+    [ INFO ] Compile model took 1107.64 ms
     [Step 8/11] Querying optimal runtime parameters
     [ INFO ] Model:
     [ INFO ]   NETWORK_NAME: torch_jit
@@ -284,21 +284,21 @@ as an example. It is recommended to tune based on your applications.
 
 .. parsed-literal::
 
-    [ INFO ] First inference took 27.61 ms
+    [ INFO ] First inference took 30.14 ms
 
 
 .. parsed-literal::
 
     [Step 11/11] Dumping statistics report
     [ INFO ] Execution Devices:['CPU']
-    [ INFO ] Count:            8900 iterations
-    [ INFO ] Duration:         60039.72 ms
+    [ INFO ] Count:            8852 iterations
+    [ INFO ] Duration:         60038.32 ms
     [ INFO ] Latency:
-    [ INFO ]    Median:        26.68 ms
-    [ INFO ]    Average:       26.74 ms
-    [ INFO ]    Min:           25.09 ms
-    [ INFO ]    Max:           39.62 ms
-    [ INFO ] Throughput:   148.24 FPS
+    [ INFO ]    Median:        26.79 ms
+    [ INFO ]    Average:       26.86 ms
+    [ INFO ]    Min:           24.76 ms
+    [ INFO ]    Max:           42.20 ms
+    [ INFO ] Throughput:   147.44 FPS
 
 
 Benchmark quantized sparse inference performance
@@ -363,7 +363,7 @@ for which a layer will be enabled.
 
 .. parsed-literal::
 
-    [ INFO ] Read model took 67.79 ms
+    [ INFO ] Read model took 71.12 ms
     [ INFO ] Original model I/O parameters:
     [ INFO ] Model inputs:
     [ INFO ]     input_ids (node: input_ids) : i64 / [...] / [?,?]
@@ -378,7 +378,7 @@ for which a layer will be enabled.
 
 .. parsed-literal::
 
-    [ INFO ] Reshape model took 23.92 ms
+    [ INFO ] Reshape model took 23.54 ms
     [Step 6/11] Configuring input of the model
     [ INFO ] Model inputs:
     [ INFO ]     input_ids (node: input_ids) : i64 / [...] / [1,64]
@@ -392,9 +392,9 @@ for which a layer will be enabled.
     Wrong value for property key CPU_SPARSE_WEIGHTS_DECOMPRESSION_RATE. Expected only float numbers
     
     Traceback (most recent call last):
-      File "/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/openvino/tools/benchmark/main.py", line 408, in main
+      File "/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/openvino/tools/benchmark/main.py", line 408, in main
         compiled_model = benchmark.core.compile_model(model, benchmark.device, device_config)
-      File "/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/openvino/runtime/ie_api.py", line 547, in compile_model
+      File "/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/openvino/runtime/ie_api.py", line 547, in compile_model
         super().compile_model(model, device_name, {} if config is None else config),
     RuntimeError: Exception from src/inference/src/core.cpp:99:
     [ GENERAL_ERROR ] Exception from src/plugins/intel_cpu/src/config.cpp:158:
diff --git a/docs/notebooks/117-model-server-with-output.rst b/docs/notebooks/117-model-server-with-output.rst
index 0b412ccac64480..f14db107155cf1 100644
--- a/docs/notebooks/117-model-server-with-output.rst
+++ b/docs/notebooks/117-model-server-with-output.rst
@@ -269,7 +269,7 @@ Check whether the OVMS container is running normally:
 
 The required Model Server parameters are listed below. For additional
 configuration options, see the `Model Server Parameters
-section `__.
+section `__.
 
 .. raw:: html
 
@@ -928,6 +928,6 @@ References
 
 
 1. `OpenVINO™ Model Server
-   documentation `__
+   documentation `__
 2. `OpenVINO™ Model Server GitHub
    repository `__
diff --git a/docs/notebooks/117-model-server-with-output_files/index.html.tmp b/docs/notebooks/117-model-server-with-output_files/index.html.tmp
deleted file mode 100644
index 2074b102cd1172..00000000000000
--- a/docs/notebooks/117-model-server-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,8 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/117-model-server-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/117-model-server-with-output_files/
../
-117-model-server-with-output_23_2.png              26-Jan-2024 01:04              305482
-117-model-server-with-output_28_1.png              26-Jan-2024 01:04              458294
-

-
diff --git a/docs/notebooks/118-optimize-preprocessing-with-output.rst b/docs/notebooks/118-optimize-preprocessing-with-output.rst
index 7bf44e38ce9854..1b5ed13154dc70 100644
--- a/docs/notebooks/118-optimize-preprocessing-with-output.rst
+++ b/docs/notebooks/118-optimize-preprocessing-with-output.rst
@@ -106,14 +106,14 @@ Imports
 
 .. parsed-literal::
 
-    2024-01-25 23:07:18.341652: I tensorflow/core/util/port.cc:110] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
-    2024-01-25 23:07:18.375926: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+    2024-02-09 23:03:22.538807: I tensorflow/core/util/port.cc:110] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
+    2024-02-09 23:03:22.573455: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
     To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
 
 
 .. parsed-literal::
 
-    2024-01-25 23:07:18.888977: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+    2024-02-09 23:03:23.087260: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
 
 
 Setup image and device
@@ -194,12 +194,12 @@ and save it to the disk.
 
 .. parsed-literal::
 
-    2024-01-25 23:07:22.553946: E tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:266] failed call to cuInit: CUDA_ERROR_COMPAT_NOT_SUPPORTED_ON_DEVICE: forward compatibility was attempted on non supported HW
-    2024-01-25 23:07:22.553985: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:168] retrieving CUDA diagnostic information for host: iotg-dev-workstation-07
-    2024-01-25 23:07:22.553989: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:175] hostname: iotg-dev-workstation-07
-    2024-01-25 23:07:22.554129: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:199] libcuda reported version is: 470.223.2
-    2024-01-25 23:07:22.554144: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:203] kernel reported version is: 470.182.3
-    2024-01-25 23:07:22.554147: E tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:312] kernel version 470.182.3 does not match DSO version 470.223.2 -- cannot find working devices in this configuration
+    2024-02-09 23:03:26.685646: E tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:266] failed call to cuInit: CUDA_ERROR_COMPAT_NOT_SUPPORTED_ON_DEVICE: forward compatibility was attempted on non supported HW
+    2024-02-09 23:03:26.685683: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:168] retrieving CUDA diagnostic information for host: iotg-dev-workstation-07
+    2024-02-09 23:03:26.685688: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:175] hostname: iotg-dev-workstation-07
+    2024-02-09 23:03:26.685821: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:199] libcuda reported version is: 470.223.2
+    2024-02-09 23:03:26.685836: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:203] kernel reported version is: 470.182.3
+    2024-02-09 23:03:26.685841: E tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:312] kernel version 470.182.3 does not match DSO version 470.223.2 -- cannot find working devices in this configuration
 
 
 .. parsed-literal::
@@ -360,7 +360,7 @@ for mean/scale normalization.
 
 .. parsed-literal::
 
-    
+    
 
 
 
@@ -391,7 +391,7 @@ may be specified is input data
 
 .. parsed-literal::
 
-    
+    
 
 
 
@@ -432,7 +432,7 @@ then such conversion will be added explicitly.
 
 .. parsed-literal::
 
-    
+    
 
 
 
@@ -651,10 +651,10 @@ Compare performance
 
 .. parsed-literal::
 
-    IR model in OpenVINO Runtime/CPU with manual image preprocessing: 0.0149 seconds per image, FPS: 67.09
+    IR model in OpenVINO Runtime/CPU with manual image preprocessing: 0.0153 seconds per image, FPS: 65.53
 
 
 .. parsed-literal::
 
-    IR model in OpenVINO Runtime/CPU with preprocessing API: 0.0182 seconds per image, FPS: 54.89
+    IR model in OpenVINO Runtime/CPU with preprocessing API: 0.0183 seconds per image, FPS: 54.77
 
diff --git a/docs/notebooks/118-optimize-preprocessing-with-output_files/index.html.tmp b/docs/notebooks/118-optimize-preprocessing-with-output_files/index.html.tmp
deleted file mode 100644
index bd254a5f87c8d1..00000000000000
--- a/docs/notebooks/118-optimize-preprocessing-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,7 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/118-optimize-preprocessing-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/118-optimize-preprocessing-with-output_files/
../
-118-optimize-preprocessing-with-output_14_1.png    26-Jan-2024 01:04              387941
-

-
diff --git a/docs/notebooks/119-tflite-to-openvino-with-output.rst b/docs/notebooks/119-tflite-to-openvino-with-output.rst
index 28ea431fe3be66..1e8d7f1382d5e5 100644
--- a/docs/notebooks/119-tflite-to-openvino-with-output.rst
+++ b/docs/notebooks/119-tflite-to-openvino-with-output.rst
@@ -106,7 +106,7 @@ Download TFLite model
 
 .. parsed-literal::
 
-    PosixPath('/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/119-tflite-to-openvino/model/efficientnet_lite0_fp32_2.tflite')
+    PosixPath('/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/notebooks/119-tflite-to-openvino/model/efficientnet_lite0_fp32_2.tflite')
 
 
 
@@ -281,7 +281,11 @@ GPU.
     [ WARNING ] Performance hint was not explicitly specified in command line. Device(CPU) performance hint will be set to PerformanceMode.THROUGHPUT.
     [Step 4/11] Reading model files
     [ INFO ] Loading model files
-    [ INFO ] Read model took 10.06 ms
+
+
+.. parsed-literal::
+
+    [ INFO ] Read model took 21.35 ms
     [ INFO ] Original model I/O parameters:
     [ INFO ] Model inputs:
     [ INFO ]     images (node: images) : f32 / [...] / [1,224,224,3]
@@ -299,9 +303,13 @@ GPU.
 
 .. parsed-literal::
 
-    [ INFO ] Compile model took 138.70 ms
+    [ INFO ] Compile model took 147.38 ms
     [Step 8/11] Querying optimal runtime parameters
     [ INFO ] Model:
+
+
+.. parsed-literal::
+
     [ INFO ]   NETWORK_NAME: TensorFlow_Lite_Frontend_IR
     [ INFO ]   OPTIMAL_NUMBER_OF_INFER_REQUESTS: 6
     [ INFO ]   NUM_STREAMS: 6
@@ -323,19 +331,19 @@ GPU.
     [ INFO ] Fill input 'images' with random values
     [Step 10/11] Measuring performance (Start inference asynchronously, 6 inference requests, limits: 15000 ms duration)
     [ INFO ] Benchmarking in inference only mode (inputs filling are not included in measurement loop).
-    [ INFO ] First inference took 7.39 ms
+    [ INFO ] First inference took 7.28 ms
 
 
 .. parsed-literal::
 
     [Step 11/11] Dumping statistics report
     [ INFO ] Execution Devices:['CPU']
-    [ INFO ] Count:            17544 iterations
-    [ INFO ] Duration:         15006.83 ms
+    [ INFO ] Count:            17502 iterations
+    [ INFO ] Duration:         15007.36 ms
     [ INFO ] Latency:
-    [ INFO ]    Median:        5.01 ms
-    [ INFO ]    Average:       5.00 ms
-    [ INFO ]    Min:           2.90 ms
-    [ INFO ]    Max:           14.27 ms
-    [ INFO ] Throughput:   1169.07 FPS
+    [ INFO ]    Median:        5.02 ms
+    [ INFO ]    Average:       5.02 ms
+    [ INFO ]    Min:           3.02 ms
+    [ INFO ]    Max:           13.94 ms
+    [ INFO ] Throughput:   1166.23 FPS
 
diff --git a/docs/notebooks/119-tflite-to-openvino-with-output_files/index.html.tmp b/docs/notebooks/119-tflite-to-openvino-with-output_files/index.html.tmp
deleted file mode 100644
index 97316fb93fc459..00000000000000
--- a/docs/notebooks/119-tflite-to-openvino-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,8 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/119-tflite-to-openvino-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/119-tflite-to-openvino-with-output_files/
../
-119-tflite-to-openvino-with-output_16_1.jpg        26-Jan-2024 01:05               68170
-119-tflite-to-openvino-with-output_16_1.png        26-Jan-2024 01:05              621006
-

-
diff --git a/docs/notebooks/120-tensorflow-instance-segmentation-to-openvino-with-output.rst b/docs/notebooks/120-tensorflow-instance-segmentation-to-openvino-with-output.rst
index 38a836e7946943..71fadfc91f3072 100644
--- a/docs/notebooks/120-tensorflow-instance-segmentation-to-openvino-with-output.rst
+++ b/docs/notebooks/120-tensorflow-instance-segmentation-to-openvino-with-output.rst
@@ -24,23 +24,32 @@ After creating the OpenVINO IR, load the model in `OpenVINO
 Runtime `__
 and do inference with a sample image.
 
-**Table of contents:**
-
-- `Prerequisites <#prerequisites>`__
-- `Imports <#imports>`__
-- `Settings <#settings>`__
-- `Download Model from TensorFlow Hub <#download-model-from-tensorflow-hub>`__
-- `Convert Model to OpenVINO IR <#convert-model-to-openvino-ir>`__
-- `Test Inference on the Converted Model <#test-inference-on-the-converted-model>`__
-- `Select inference device <#select-inference-device>`__
-- `Load the Model <#load-the-model>`__
-- `Get Model Information <#get-model-information>`__
-- `Get an Image for Test Inference <#get-an-image-for-test-inference>`__
-- `Perform Inference <#perform-inference>`__
-- `Inference Result Visualization <#inference-result-visualization>`__
-- `Next Steps <#next-steps>`__
-- `Async inference pipeline <#async-inference-pipeline>`__
-- `Integration preprocessing to model <#integration-preprocessing-to-model>`__
+Table of contents:
+^^^^^^^^^^^^^^^^^^
+
+-  `Prerequisites <#prerequisites>`__
+-  `Imports <#imports>`__
+-  `Settings <#settings>`__
+-  `Download Model from TensorFlow
+   Hub <#download-model-from-tensorflow-hub>`__
+-  `Convert Model to OpenVINO IR <#convert-model-to-openvino-ir>`__
+-  `Test Inference on the Converted
+   Model <#test-inference-on-the-converted-model>`__
+-  `Select inference device <#select-inference-device>`__
+
+   -  `Load the Model <#load-the-model>`__
+   -  `Get Model Information <#get-model-information>`__
+   -  `Get an Image for Test
+      Inference <#get-an-image-for-test-inference>`__
+   -  `Perform Inference <#perform-inference>`__
+   -  `Inference Result
+      Visualization <#inference-result-visualization>`__
+
+-  `Next Steps <#next-steps>`__
+
+   -  `Async inference pipeline <#async-inference-pipeline>`__
+   -  `Integration preprocessing to
+      model <#integration-preprocessing-to-model>`__
 
 Prerequisites
 -------------
@@ -355,7 +364,7 @@ Read the image, resize and convert it to the input shape of the network:
 
 .. parsed-literal::
 
-    
+    
 
 
 
diff --git a/docs/notebooks/120-tensorflow-instance-segmentation-to-openvino-with-output_files/120-tensorflow-instance-segmentation-to-openvino-with-output_39_0.png b/docs/notebooks/120-tensorflow-instance-segmentation-to-openvino-with-output_files/120-tensorflow-instance-segmentation-to-openvino-with-output_39_0.png
index 176ce97e1f52ed..919f14f36ff3ab 100644
--- a/docs/notebooks/120-tensorflow-instance-segmentation-to-openvino-with-output_files/120-tensorflow-instance-segmentation-to-openvino-with-output_39_0.png
+++ b/docs/notebooks/120-tensorflow-instance-segmentation-to-openvino-with-output_files/120-tensorflow-instance-segmentation-to-openvino-with-output_39_0.png
@@ -1,3 +1,3 @@
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-size 393453
+oid sha256:8e7e8a03ae8a07e661d3a25306fe3dca53093416ecf98222fe478edaf13d07df
+size 393160
diff --git a/docs/notebooks/120-tensorflow-instance-segmentation-to-openvino-with-output_files/index.html.tmp b/docs/notebooks/120-tensorflow-instance-segmentation-to-openvino-with-output_files/index.html.tmp
deleted file mode 100644
index 9ebafdab39c783..00000000000000
--- a/docs/notebooks/120-tensorflow-instance-segmentation-to-openvino-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,8 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/120-tensorflow-instance-segmentation-to-openvino-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/120-tensorflow-instance-segmentation-to-openvino-with-output_files/
../
-120-tensorflow-instance-segmentation-to-openvin..> 26-Jan-2024 01:05              395346
-120-tensorflow-instance-segmentation-to-openvin..> 26-Jan-2024 01:05              393453
-

-
diff --git a/docs/notebooks/120-tensorflow-object-detection-to-openvino-with-output.rst b/docs/notebooks/120-tensorflow-object-detection-to-openvino-with-output.rst
index fcc8ba2cba6743..6bda545e1f6c1e 100644
--- a/docs/notebooks/120-tensorflow-object-detection-to-openvino-with-output.rst
+++ b/docs/notebooks/120-tensorflow-object-detection-to-openvino-with-output.rst
@@ -157,7 +157,7 @@ from TensorFlow Hub:
 
 .. parsed-literal::
 
-    PosixPath('/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/120-tensorflow-object-detection-to-openvino/model/tf/faster_rcnn_resnet50_v1_640x640.tar.gz')
+    PosixPath('/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/notebooks/120-tensorflow-object-detection-to-openvino/model/tf/faster_rcnn_resnet50_v1_640x640.tar.gz')
 
 
 
@@ -343,7 +343,7 @@ Load and save an image:
 
 .. parsed-literal::
 
-    PosixPath('/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/120-tensorflow-object-detection-to-openvino/data/coco_bike.jpg')
+    PosixPath('/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/notebooks/120-tensorflow-object-detection-to-openvino/data/coco_bike.jpg')
 
 
 
@@ -371,7 +371,7 @@ Read the image, resize and convert it to the input shape of the network:
 
 .. parsed-literal::
 
-    
+    
 
 
 
@@ -635,7 +635,7 @@ Zoo `__:
 
 .. parsed-literal::
 
-    PosixPath('/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/120-tensorflow-object-detection-to-openvino/data/coco_91cl.txt')
+    PosixPath('/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/notebooks/120-tensorflow-object-detection-to-openvino/data/coco_91cl.txt')
 
 
 
diff --git a/docs/notebooks/120-tensorflow-object-detection-to-openvino-with-output_files/120-tensorflow-object-detection-to-openvino-with-output_38_0.png b/docs/notebooks/120-tensorflow-object-detection-to-openvino-with-output_files/120-tensorflow-object-detection-to-openvino-with-output_38_0.png
index 957606ce732f6a..b3d76ace53ce03 100644
--- a/docs/notebooks/120-tensorflow-object-detection-to-openvino-with-output_files/120-tensorflow-object-detection-to-openvino-with-output_38_0.png
+++ b/docs/notebooks/120-tensorflow-object-detection-to-openvino-with-output_files/120-tensorflow-object-detection-to-openvino-with-output_38_0.png
@@ -1,3 +1,3 @@
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-oid sha256:a5b7ad5bc51c70dfab0037ca885aeb4e613947df3fd7fdff8d055c8d64aefd4a
-size 391815
+oid sha256:69ba7f4bdc1e3d85a98b34863980a347ab3bdf2aedb7d9d78a2f8d43484127b6
+size 391578
diff --git a/docs/notebooks/120-tensorflow-object-detection-to-openvino-with-output_files/index.html.tmp b/docs/notebooks/120-tensorflow-object-detection-to-openvino-with-output_files/index.html.tmp
deleted file mode 100644
index 915c42f44186aa..00000000000000
--- a/docs/notebooks/120-tensorflow-object-detection-to-openvino-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,8 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/120-tensorflow-object-detection-to-openvino-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/120-tensorflow-object-detection-to-openvino-with-output_files/
../
-120-tensorflow-object-detection-to-openvino-wit..> 26-Jan-2024 01:05              395346
-120-tensorflow-object-detection-to-openvino-wit..> 26-Jan-2024 01:05              391815
-

-
diff --git a/docs/notebooks/121-convert-to-openvino-with-output.rst b/docs/notebooks/121-convert-to-openvino-with-output.rst
index 4e74150ded1799..504bb7a94740ca 100644
--- a/docs/notebooks/121-convert-to-openvino-with-output.rst
+++ b/docs/notebooks/121-convert-to-openvino-with-output.rst
@@ -35,7 +35,7 @@ Table of contents:
 
 .. parsed-literal::
 
-    Requirement already satisfied: pip in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (23.3.2)
+    Requirement already satisfied: pip in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (24.0)
 
 
 .. parsed-literal::
@@ -79,7 +79,7 @@ documentation.
 .. code:: ipython3
 
     # OVC CLI tool parameters description
-    
+
     ! ovc --help
 
 
@@ -88,12 +88,12 @@ documentation.
     usage: ovc INPUT_MODEL... [-h] [--output_model OUTPUT_MODEL]
                [--compress_to_fp16 [True | False]] [--version] [--input INPUT]
                [--output OUTPUT] [--extension EXTENSION] [--verbose]
-    
+
     positional arguments:
       INPUT_MODEL           Input model file(s) from TensorFlow, ONNX,
                             PaddlePaddle. Use openvino.convert_model in Python to
                             convert models from PyTorch.
-    
+
     optional arguments:
       -h, --help            show this help message and exit
       --output_model OUTPUT_MODEL
@@ -152,7 +152,7 @@ This notebook uses two models for conversion examples:
 .. code:: ipython3
 
     from pathlib import Path
-    
+
     # create a directory for models files
     MODEL_DIRECTORY_PATH = Path("model")
     MODEL_DIRECTORY_PATH.mkdir(exist_ok=True)
@@ -165,9 +165,9 @@ NLP model from Hugging Face and export it in ONNX format:
 
     from transformers import AutoModelForSequenceClassification, AutoTokenizer
     from transformers.onnx import export, FeaturesManager
-    
+
     ONNX_NLP_MODEL_PATH = MODEL_DIRECTORY_PATH / "distilbert.onnx"
-    
+
     # download model
     hf_model = AutoModelForSequenceClassification.from_pretrained(
         "distilbert-base-uncased-finetuned-sst-2-english"
@@ -176,14 +176,14 @@ NLP model from Hugging Face and export it in ONNX format:
     tokenizer = AutoTokenizer.from_pretrained(
         "distilbert-base-uncased-finetuned-sst-2-english"
     )
-    
+
     # get model onnx config function for output feature format sequence-classification
     model_kind, model_onnx_config = FeaturesManager.check_supported_model_or_raise(
         hf_model, feature="sequence-classification"
     )
     # fill onnx config based on pytorch model config
     onnx_config = model_onnx_config(hf_model.config)
-    
+
     # export to onnx format
     export(
         preprocessor=tokenizer,
@@ -196,19 +196,19 @@ NLP model from Hugging Face and export it in ONNX format:
 
 .. parsed-literal::
 
-    2024-01-25 23:11:32.267646: I tensorflow/core/util/port.cc:110] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
-    2024-01-25 23:11:32.303561: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+    2024-02-09 23:07:37.212192: I tensorflow/core/util/port.cc:110] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
+    2024-02-09 23:07:37.247733: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
     To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
 
 
 .. parsed-literal::
 
-    2024-01-25 23:11:32.956586: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+    2024-02-09 23:07:37.883428: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
 
 
 .. parsed-literal::
 
-    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/transformers/models/distilbert/modeling_distilbert.py:246: TracerWarning: torch.tensor results are registered as constants in the trace. You can safely ignore this warning if you use this function to create tensors out of constant variables that would be the same every time you call this function. In any other case, this might cause the trace to be incorrect.
+    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/transformers/models/distilbert/modeling_distilbert.py:246: TracerWarning: torch.tensor results are registered as constants in the trace. You can safely ignore this warning if you use this function to create tensors out of constant variables that would be the same every time you call this function. In any other case, this might cause the trace to be incorrect.
       mask, torch.tensor(torch.finfo(scores.dtype).min)
 
 
@@ -227,7 +227,7 @@ CV classification model from torchvision:
 .. code:: ipython3
 
     from torchvision.models import resnet50, ResNet50_Weights
-    
+
     # create model object
     pytorch_model = resnet50(weights=ResNet50_Weights.DEFAULT)
     # switch model from training to inference mode
@@ -423,9 +423,9 @@ Convert PyTorch model to ONNX format:
 
     import torch
     import warnings
-    
+
     ONNX_CV_MODEL_PATH = MODEL_DIRECTORY_PATH / "resnet.onnx"
-    
+
     if ONNX_CV_MODEL_PATH.exists():
         print(f"ONNX model {ONNX_CV_MODEL_PATH} already exists.")
     else:
@@ -452,11 +452,11 @@ To convert a model to OpenVINO IR, use the following API:
 .. code:: ipython3
 
     import openvino as ov
-    
+
     # ov.convert_model returns an openvino.runtime.Model object
     print(ONNX_NLP_MODEL_PATH)
     ov_model = ov.convert_model(ONNX_NLP_MODEL_PATH)
-    
+
     # then model can be serialized to *.xml & *.bin files
     ov.save_model(ov_model, MODEL_DIRECTORY_PATH / "distilbert.xml")
 
@@ -510,7 +510,7 @@ documentation.
 .. code:: ipython3
 
     import openvino as ov
-    
+
     ov_model = ov.convert_model(
         ONNX_NLP_MODEL_PATH, input=[("input_ids", [1, 128]), ("attention_mask", [1, 128])]
     )
@@ -549,7 +549,7 @@ conversion API parameter as ``-1`` or ``?`` when using ``ovc``:
 .. code:: ipython3
 
     import openvino as ov
-    
+
     ov_model = ov.convert_model(
         ONNX_NLP_MODEL_PATH, input=[("input_ids", [1, -1]), ("attention_mask", [1, -1])]
     )
@@ -590,10 +590,10 @@ sequence length dimension:
 .. code:: ipython3
 
     import openvino as ov
-    
-    
+
+
     sequence_length_dim = ov.Dimension(10, 128)
-    
+
     ov_model = ov.convert_model(
         ONNX_NLP_MODEL_PATH, input=[("input_ids", [1, sequence_length_dim]), ("attention_mask", [1, sequence_length_dim])]
     )
@@ -636,7 +636,7 @@ disabled by setting ``compress_to_fp16`` flag to ``False``:
 .. code:: ipython3
 
     import openvino as ov
-    
+
     ov_model = ov.convert_model(ONNX_NLP_MODEL_PATH)
     ov.save_model(ov_model, MODEL_DIRECTORY_PATH / 'distilbert.xml', compress_to_fp16=False)
 
@@ -675,9 +675,9 @@ frameworks conversion guides.
 
     import openvino as ov
     import torch
-    
+
     example_input = torch.rand(1, 3, 224, 224)
-    
+
     ov_model = ov.convert_model(pytorch_model, example_input=example_input, input=example_input.shape)
 
 
@@ -690,21 +690,21 @@ frameworks conversion guides.
 
     import openvino as ov
     import tensorflow_hub as hub
-    
+
     model = hub.load("https://www.kaggle.com/models/google/movenet/frameworks/TensorFlow2/variations/singlepose-lightning/versions/4")
     movenet = model.signatures['serving_default']
-    
+
     ov_model = ov.convert_model(movenet)
 
 
 .. parsed-literal::
 
-    2024-01-25 23:11:51.061555: E tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:266] failed call to cuInit: CUDA_ERROR_COMPAT_NOT_SUPPORTED_ON_DEVICE: forward compatibility was attempted on non supported HW
-    2024-01-25 23:11:51.061587: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:168] retrieving CUDA diagnostic information for host: iotg-dev-workstation-07
-    2024-01-25 23:11:51.061592: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:175] hostname: iotg-dev-workstation-07
-    2024-01-25 23:11:51.061773: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:199] libcuda reported version is: 470.223.2
-    2024-01-25 23:11:51.061789: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:203] kernel reported version is: 470.182.3
-    2024-01-25 23:11:51.061793: E tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:312] kernel version 470.182.3 does not match DSO version 470.223.2 -- cannot find working devices in this configuration
+    2024-02-09 23:07:56.008045: E tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:266] failed call to cuInit: CUDA_ERROR_COMPAT_NOT_SUPPORTED_ON_DEVICE: forward compatibility was attempted on non supported HW
+    2024-02-09 23:07:56.008076: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:168] retrieving CUDA diagnostic information for host: iotg-dev-workstation-07
+    2024-02-09 23:07:56.008081: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:175] hostname: iotg-dev-workstation-07
+    2024-02-09 23:07:56.008267: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:199] libcuda reported version is: 470.223.2
+    2024-02-09 23:07:56.008284: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:203] kernel reported version is: 470.182.3
+    2024-02-09 23:07:56.008287: E tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:312] kernel version 470.182.3 does not match DSO version 470.223.2 -- cannot find working devices in this configuration
 
 
 Migration from Legacy conversion API
@@ -747,9 +747,9 @@ Resnet50 model that was exported to the ONNX format:
 
     # Converter API
     import openvino as ov
-    
+
     ov_model = ov.convert_model(ONNX_CV_MODEL_PATH)
-    
+
     prep = ov.preprocess.PrePostProcessor(ov_model)
     prep.input('input.1').model().set_layout(ov.Layout("nchw"))
     ov_model = prep.build()
@@ -758,7 +758,7 @@ Resnet50 model that was exported to the ONNX format:
 
     # Legacy Model Optimizer API
     from openvino.tools import mo
-    
+
     ov_model = mo.convert_model(ONNX_CV_MODEL_PATH, layout="nchw")
 
 
@@ -787,9 +787,9 @@ and the layout of an original model:
 
     # Converter API
     import openvino as ov
-    
+
     ov_model = ov.convert_model(ONNX_CV_MODEL_PATH)
-    
+
     prep = ov.preprocess.PrePostProcessor(ov_model)
     prep.input('input.1').tensor().set_layout(ov.Layout("nhwc"))
     prep.input('input.1').model().set_layout(ov.Layout("nchw"))
@@ -799,9 +799,9 @@ and the layout of an original model:
 
     # Legacy Model Optimizer API
     from openvino.tools import mo
-    
+
     ov_model = mo.convert_model(ONNX_CV_MODEL_PATH, layout="nchw->nhwc")
-    
+
     # alternatively use source_layout and target_layout parameters
     ov_model = mo.convert_model(
         ONNX_CV_MODEL_PATH, source_layout="nchw", target_layout="nhwc"
@@ -823,22 +823,22 @@ for more examples.
 
     # Converter API
     import openvino as ov
-    
+
     ov_model = ov.convert_model(ONNX_CV_MODEL_PATH)
-    
+
     prep = ov.preprocess.PrePostProcessor(ov_model)
     prep.input("input.1").tensor().set_layout(ov.Layout("nchw"))
     prep.input("input.1").preprocess().mean([255 * x for x in [0.485, 0.456, 0.406]])
     prep.input("input.1").preprocess().scale([255 * x for x in [0.229, 0.224, 0.225]])
-    
+
     ov_model = prep.build()
 
 .. code:: ipython3
 
     # Legacy Model Optimizer API
     from openvino.tools import mo
-    
-    
+
+
     ov_model = mo.convert_model(
         ONNX_CV_MODEL_PATH,
         mean_values=[255 * x for x in [0.485, 0.456, 0.406]],
@@ -860,9 +860,9 @@ the color channels before inference.
 
     # Converter API
     import openvino as ov
-    
+
     ov_model = ov.convert_model(ONNX_CV_MODEL_PATH)
-    
+
     prep = ov.preprocess.PrePostProcessor(ov_model)
     prep.input('input.1').tensor().set_layout(ov.Layout("nchw"))
     prep.input('input.1').preprocess().reverse_channels()
@@ -872,7 +872,7 @@ the color channels before inference.
 
     # Legacy Model Optimizer API
     from openvino.tools import mo
-    
+
     ov_model = mo.convert_model(ONNX_CV_MODEL_PATH, reverse_input_channels=True)
 
 Cutting Off Parts of a Model
diff --git a/docs/notebooks/121-legacy-mo-convert-to-openvino-with-output.rst b/docs/notebooks/121-legacy-mo-convert-to-openvino-with-output.rst
index b13d9b8f26c30c..078b506643857a 100644
--- a/docs/notebooks/121-legacy-mo-convert-to-openvino-with-output.rst
+++ b/docs/notebooks/121-legacy-mo-convert-to-openvino-with-output.rst
@@ -118,7 +118,7 @@ documentation.
                             conversion into IR. The legacy Frontend is Python
                             based and is available for TensorFlow*, ONNX*, MXNet*,
                             Caffe*, and Kaldi* models.
-      --input_model INPUT_MODEL, -w INPUT_MODEL, -m INPUT_MODEL
+      --input_model INPUT_MODEL, -m INPUT_MODEL, -w INPUT_MODEL
                             Tensorflow*: a file with a pre-trained model (binary
                             or text .pb file after freezing). Caffe*: a model
                             proto file with model weights.
@@ -256,11 +256,7 @@ documentation.
                             Paths or a comma-separated list of paths to libraries
                             (.so or .dll) with extensions. For the legacy MO path
                             (if `--use_legacy_frontend` is used), a directory or a
-                            comma
-
-.. parsed-literal::
-
-    -separated list of directories with extensions
+                            comma-separated list of directories with extensions
                             are supported. To disable all extensions including
                             those that are placed at the default location, pass an
                             empty string.
@@ -744,19 +740,19 @@ NLP model from Hugging Face and export it in ONNX format:
 
 .. parsed-literal::
 
-    2024-01-25 23:12:13.362144: I tensorflow/core/util/port.cc:110] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
-    2024-01-25 23:12:13.397165: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+    2024-02-09 23:08:18.586507: I tensorflow/core/util/port.cc:110] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
+    2024-02-09 23:08:18.621399: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
     To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
 
 
 .. parsed-literal::
 
-    2024-01-25 23:12:14.029251: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+    2024-02-09 23:08:19.256172: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
 
 
 .. parsed-literal::
 
-    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/transformers/models/distilbert/modeling_distilbert.py:246: TracerWarning: torch.tensor results are registered as constants in the trace. You can safely ignore this warning if you use this function to create tensors out of constant variables that would be the same every time you call this function. In any other case, this might cause the trace to be incorrect.
+    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/transformers/models/distilbert/modeling_distilbert.py:246: TracerWarning: torch.tensor results are registered as constants in the trace. You can safely ignore this warning if you use this function to create tensors out of constant variables that would be the same every time you call this function. In any other case, this might cause the trace to be incorrect.
       mask, torch.tensor(torch.finfo(scores.dtype).min)
 
 
@@ -1027,8 +1023,8 @@ To convert a model to OpenVINO IR, use the following command:
 .. parsed-literal::
 
     [ SUCCESS ] Generated IR version 11 model.
-    [ SUCCESS ] XML file: /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/121-convert-to-openvino/model/distilbert.xml
-    [ SUCCESS ] BIN file: /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/121-convert-to-openvino/model/distilbert.bin
+    [ SUCCESS ] XML file: /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/notebooks/121-convert-to-openvino/model/distilbert.xml
+    [ SUCCESS ] BIN file: /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/notebooks/121-convert-to-openvino/model/distilbert.bin
 
 
 .. code:: ipython3
@@ -1129,8 +1125,8 @@ guide `__ is
 Facebook AI Research’s library that provides state-of-the-art detection
diff --git a/docs/notebooks/123-detectron2-to-openvino-with-output_files/123-detectron2-to-openvino-with-output_22_0.jpg b/docs/notebooks/123-detectron2-to-openvino-with-output_files/123-detectron2-to-openvino-with-output_22_0.jpg
index 538e967fc1d4bd..c197c51e7fbe68 100644
--- a/docs/notebooks/123-detectron2-to-openvino-with-output_files/123-detectron2-to-openvino-with-output_22_0.jpg
+++ b/docs/notebooks/123-detectron2-to-openvino-with-output_files/123-detectron2-to-openvino-with-output_22_0.jpg
@@ -1,3 +1,3 @@
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-oid sha256:b9a59f5b6bc77d33212bcadd69faacc6c286d6eac7d7ed88ce28ccefe227f010
-size 59043
+oid sha256:97f44896da4cb3dee863ed6869c16015702bf26050467e2ff84110920318665b
+size 58781
diff --git a/docs/notebooks/123-detectron2-to-openvino-with-output_files/123-detectron2-to-openvino-with-output_22_0.png b/docs/notebooks/123-detectron2-to-openvino-with-output_files/123-detectron2-to-openvino-with-output_22_0.png
index 66d21176a7737c..6b284d06850dba 100644
--- a/docs/notebooks/123-detectron2-to-openvino-with-output_files/123-detectron2-to-openvino-with-output_22_0.png
+++ b/docs/notebooks/123-detectron2-to-openvino-with-output_files/123-detectron2-to-openvino-with-output_22_0.png
@@ -1,3 +1,3 @@
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-size 508506
+oid sha256:4398d08f29dcb59dd57f4cd453308897ac75f6f8b860558fb21cfdbcd479b6e3
+size 509675
diff --git a/docs/notebooks/123-detectron2-to-openvino-with-output_files/123-detectron2-to-openvino-with-output_32_0.jpg b/docs/notebooks/123-detectron2-to-openvino-with-output_files/123-detectron2-to-openvino-with-output_32_0.jpg
index 2e770dcb4d3898..563491edadd222 100644
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+++ b/docs/notebooks/123-detectron2-to-openvino-with-output_files/123-detectron2-to-openvino-with-output_32_0.jpg
@@ -1,3 +1,3 @@
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+oid sha256:ae3a4df87c84baa406e0d2ed491e25f28bd9d8e6e9fe649bd74c0b7eae35ac07
+size 55630
diff --git a/docs/notebooks/123-detectron2-to-openvino-with-output_files/123-detectron2-to-openvino-with-output_32_0.png b/docs/notebooks/123-detectron2-to-openvino-with-output_files/123-detectron2-to-openvino-with-output_32_0.png
index 0055ecd3517e14..491d8c6937c5d7 100644
--- a/docs/notebooks/123-detectron2-to-openvino-with-output_files/123-detectron2-to-openvino-with-output_32_0.png
+++ b/docs/notebooks/123-detectron2-to-openvino-with-output_files/123-detectron2-to-openvino-with-output_32_0.png
@@ -1,3 +1,3 @@
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-size 457794
+oid sha256:c832d80fe116434db304523dbc29d6e292e7a5733b70ae709e8eb2a0674506e6
+size 457756
diff --git a/docs/notebooks/123-detectron2-to-openvino-with-output_files/index.html.tmp b/docs/notebooks/123-detectron2-to-openvino-with-output_files/index.html.tmp
deleted file mode 100644
index eae6c301771f27..00000000000000
--- a/docs/notebooks/123-detectron2-to-openvino-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,12 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/123-detectron2-to-openvino-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/123-detectron2-to-openvino-with-output_files/
../
-123-detectron2-to-openvino-with-output_22_0.jpg    26-Jan-2024 01:05               59043
-123-detectron2-to-openvino-with-output_22_0.png    26-Jan-2024 01:05              508506
-123-detectron2-to-openvino-with-output_32_0.jpg    26-Jan-2024 01:05               55966
-123-detectron2-to-openvino-with-output_32_0.png    26-Jan-2024 01:05              457794
-123-detectron2-to-openvino-with-output_8_0.jpg     26-Jan-2024 01:05               46858
-123-detectron2-to-openvino-with-output_8_0.png     26-Jan-2024 01:05              503218
-

-
diff --git a/docs/notebooks/124-hugging-face-hub-with-output.rst b/docs/notebooks/124-hugging-face-hub-with-output.rst
index 73bf14b670e71a..eb4d32901b6867 100644
--- a/docs/notebooks/124-hugging-face-hub-with-output.rst
+++ b/docs/notebooks/124-hugging-face-hub-with-output.rst
@@ -1,4 +1,4 @@
-🤗 Hugging Face Model Hub with OpenVINO™
+Hugging Face Model Hub with OpenVINO™
 =========================================
 
 The Hugging Face (HF) `Model Hub `__ is a
@@ -129,7 +129,7 @@ tutorials `__.
 
 .. parsed-literal::
 
-    2024-01-25 23:14:43.057378: I tensorflow/core/util/port.cc:110] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
-    2024-01-25 23:14:43.091971: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+    2024-02-09 23:10:50.826096: I tensorflow/core/util/port.cc:110] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
+    2024-02-09 23:10:50.861099: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
     To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
 
 
 .. parsed-literal::
 
-    2024-01-25 23:14:43.657635: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+    2024-02-09 23:10:51.428729: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
 
 
 Initialize and Convert the Model Automatically using OVModel class
@@ -478,7 +478,7 @@ Full list of supported arguments available via ``--help``
 
 .. parsed-literal::
 
-    2024-01-25 23:14:55.440371: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+    2024-02-09 23:11:03.409282: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
 
 
 .. parsed-literal::
@@ -490,6 +490,7 @@ Full list of supported arguments available via ``--help``
                                        [--int8]
                                        [--weight-format {fp32,fp16,int8,int4_sym_g128,int4_asym_g128,int4_sym_g64,int4_asym_g64}]
                                        [--ratio RATIO] [--disable-stateful]
+                                       [--convert-tokenizer]
                                        output
 
     optional arguments:
@@ -506,21 +507,20 @@ Full list of supported arguments available via ``--help``
       --task TASK           The task to export the model for. If not specified,
                             the task will be auto-inferred based on the model.
                             Available tasks depend on the model, but are among:
-                            ['stable-diffusion', 'audio-xvector', 'text-
-                            classification', 'automatic-speech-recognition',
-                            'image-segmentation', 'audio-classification',
-                            'multiple-choice', 'image-to-text', 'stable-diffusion-
-                            xl', 'zero-shot-image-classification', 'text-to-
-                            audio', 'fill-mask', 'object-detection', 'image-to-
-                            image', 'mask-generation', 'image-classification',
-                            'feature-extraction', 'semantic-segmentation', 'text-
-                            generation', 'question-answering', 'conversational',
-                            'zero-shot-object-detection', 'masked-im', 'sentence-
-                            similarity', 'audio-frame-classification', 'text2text-
-                            generation', 'depth-estimation', 'token-
-                            classification']. For decoder models, use `xxx-with-
-                            past` to export the model using past key values in the
-                            decoder.
+                            ['sentence-similarity', 'object-detection', 'question-
+                            answering', 'text-to-audio', 'audio-xvector', 'stable-
+                            diffusion-xl', 'feature-extraction', 'image-to-image',
+                            'text-generation', 'mask-generation', 'text-
+                            classification', 'image-segmentation', 'automatic-
+                            speech-recognition', 'text2text-generation', 'stable-
+                            diffusion', 'audio-classification', 'semantic-
+                            segmentation', 'fill-mask', 'depth-estimation', 'zero-
+                            shot-image-classification', 'image-to-text', 'zero-
+                            shot-object-detection', 'multiple-choice',
+                            'conversational', 'image-classification', 'masked-im',
+                            'audio-frame-classification', 'token-classification'].
+                            For decoder models, use `xxx-with-past` to export the
+                            model using past key values in the decoder.
       --cache_dir CACHE_DIR
                             Path indicating where to store cache.
       --framework {pt,tf}   The framework to use for the export. If not provided,
@@ -558,6 +558,8 @@ Full list of supported arguments available via ``--help``
                             a stateless model, for example, to be compatible with
                             existing OpenVINO native inference code that expects
                             kv-cache inputs and outputs in the model.
+      --convert-tokenizer   Add converted tokenizer and detokenizer with OpenVINO
+                            Tokenizers
 
 
 The command line export for model from example above with FP16 weights
@@ -578,7 +580,7 @@ compression:
 
 .. parsed-literal::
 
-    2024-01-25 23:14:59.738992: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+    2024-02-09 23:11:07.691775: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
 
 
 .. parsed-literal::
@@ -593,7 +595,7 @@ compression:
 
 .. parsed-literal::
 
-    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/torch/_utils.py:831: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly.  To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()
+    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/torch/_utils.py:831: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly.  To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()
       return self.fget.__get__(instance, owner)()
 
 
@@ -658,13 +660,20 @@ Model inference is exactly the same as for the original model!
     3) negative 0.0031
 
 
-You can find more examples of using Optimum Intel here:
-
-1. `Accelerate Inference of Sparse Transformer Models `__
-2. `Grammatical Error Correction with OpenVINO `__
-3. `Stable Diffusion v2.1 using Optimum-Intel OpenVINO `__
-4. `Image generation with Stable Diffusion XL `__
-5. `Instruction following using Databricks Dolly 2.0 `__
-6. `Create LLM-powered Chatbot using OpenVINO `__
-7. `Document Visual Question Answering Using Pix2Struct and OpenVINO `__
-8. `Automatic speech recognition using Distil-Whisper and OpenVINO `__
+You can find more examples of using Optimum Intel here: 1. `Accelerate
+Inference of Sparse Transformer
+Models `__
+2. `Grammatical Error Correction with
+OpenVINO `__
+3. `Stable Diffusion v2.1 using Optimum-Intel
+OpenVINO `__
+4. `Image generation with Stable Diffusion
+XL `__
+5. `Instruction following using Databricks Dolly
+2.0 `__
+6. `Create LLM-powered Chatbot using
+OpenVINO `__
+7. `Document Visual Question Answering Using Pix2Struct and
+OpenVINO `__
+8. `Automatic speech recognition using Distil-Whisper and
+OpenVINO `__
diff --git a/docs/notebooks/125-convnext-classification-with-output.rst b/docs/notebooks/125-convnext-classification-with-output.rst
index 1360d031d98b10..1598cd2117f5be 100644
--- a/docs/notebooks/125-convnext-classification-with-output.rst
+++ b/docs/notebooks/125-convnext-classification-with-output.rst
@@ -37,8 +37,10 @@ Table of contents:
 -  `Use the OpenVINO IR model to run an
    inference <#use-the-openvino-ir-model-to-run-an-inference>`__
 
-Prerequisites\
--------------------------------------------------------
+Prerequisites
+-------------
+
+
 
 .. code:: ipython3
 
@@ -144,12 +146,14 @@ wight 
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/125-convnext-classification-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/125-convnext-classification-with-output_files/
../
-125-convnext-classification-with-output_4_0.jpg    26-Jan-2024 01:05               63187
-125-convnext-classification-with-output_4_0.png    26-Jan-2024 01:05              723717
-

-
diff --git a/docs/notebooks/125-lraspp-segmentation-with-output.rst b/docs/notebooks/125-lraspp-segmentation-with-output.rst
index d5af9bafe7aa25..4c47502d7ffc8f 100644
--- a/docs/notebooks/125-lraspp-segmentation-with-output.rst
+++ b/docs/notebooks/125-lraspp-segmentation-with-output.rst
@@ -22,27 +22,28 @@ plant, sheep, sofa, train, tv monitor**
 More information about the model is available in the `torchvision
 documentation `__
 
+Table of contents:
+^^^^^^^^^^^^^^^^^^
 
-
-**Table of contents:**
-
--  `Prerequisites <#prerequisites>`__
+-  `Prerequisites) <#prerequisites>`__
 -  `Get a test image <#get-a-test-image>`__
 -  `Download and prepare a model <#download-and-prepare-a-model>`__
 -  `Define a preprocessing and prepare an input
    data <#define-a-preprocessing-and-prepare-an-input-data>`__
 -  `Run an inference on the PyTorch
-   model <#run-an-inference-on-the-pytorch-model>`__
+   model) <#run-an-inference-on-the-pytorch-model>`__
 -  `Convert the original model to OpenVINO IR
    Format <#convert-the-original-model-to-openvino-ir-format>`__
 -  `Run an inference on the OpenVINO
-   model <#run-an-inference-on-the-openvino-model>`__
+   model) <#run-an-inference-on-the-openvino-model>`__
 -  `Show results <#show-results>`__
 -  `Show results for the OpenVINO IR
-   model <#show-results-for-the-openvino-ir-model>`__
+   model) <#show-results-for-the-openvino-ir-model>`__
+
+Prerequisites
+-------------
+
 
-Prerequisites\
--------------------------------------------------------
 
 .. code:: ipython3
 
@@ -69,24 +70,25 @@ Prerequisites\
 .. code:: ipython3
 
     from pathlib import Path
-
+    
     import openvino as ov
     import torch
 
 Get a test image
 ----------------
 
-First of all lets get a test
-image from an open dataset.
+
+
+First of all lets get a test image from an open dataset.
 
 .. code:: ipython3
 
     import urllib.request
-
+    
     from torchvision.io import read_image
     import torchvision.transforms as transforms
-
-
+    
+    
     img_path = 'cats_image.jpeg'
     urllib.request.urlretrieve(
         url='https://huggingface.co/datasets/huggingface/cats-image/resolve/main/cats_image.jpeg',
@@ -103,10 +105,11 @@ image from an open dataset.
 Download and prepare a model
 ----------------------------
 
-Define width and height of the
-image that will be used by the network during inference. According to
-the input transforms function, the model is pre-trained on images with a
-height of 480 and width of 640.
+
+
+Define width and height of the image that will be used by the network
+during inference. According to the input transforms function, the model
+is pre-trained on images with a height of 480 and width of 640.
 
 .. code:: ipython3
 
@@ -119,12 +122,12 @@ models `__.
 
 .. code:: ipython3
 
     import numpy as np
-
-
+    
+    
     preprocess = models.segmentation.LRASPP_MobileNet_V3_Large_Weights.COCO_WITH_VOC_LABELS_V1.transforms()
     preprocess.resize_size = (IMAGE_HEIGHT, IMAGE_WIDTH)  # change to an image size
-
+    
     input_data = preprocess(image)
     input_data = np.expand_dims(input_data, axis=0)
 
-Run an inference on the PyTorch model\
--------------------------------------------------------------------------------
+Run an inference on the PyTorch model
+-------------------------------------
+
+
 
 .. code:: ipython3
 
@@ -193,8 +199,8 @@ directory. For more information on how to convert models, see this
 .. code:: ipython3
 
     ov_model_xml_path = Path('models/ov_lraspp_model.xml')
-
-
+    
+    
     if not ov_model_xml_path.exists():
         ov_model_xml_path.parent.mkdir(parents=True, exist_ok=True)
         dummy_input = torch.randn(1, 3, IMAGE_HEIGHT, IMAGE_WIDTH)
@@ -203,15 +209,17 @@ directory. For more information on how to convert models, see this
     else:
         print(f"IR model {ov_model_xml_path} already exists.")
 
-Run an inference on the OpenVINO model\
---------------------------------------------------------------------------------
+Run an inference on the OpenVINO model
+--------------------------------------
+
+
 
 Select device from dropdown list for running inference using OpenVINO
 
 .. code:: ipython3
 
     import ipywidgets as widgets
-
+    
     core = ov.Core()
     device = widgets.Dropdown(
         options=core.available_devices + ["AUTO"],
@@ -219,7 +227,7 @@ Select device from dropdown list for running inference using OpenVINO
         description='Device:',
         disabled=False,
     )
-
+    
     device
 
 
@@ -244,9 +252,10 @@ Run an inference
 Show results
 ------------
 
-Confirm that the segmentation
-results look as expected by comparing model predictions on the OpenVINO
-IR and PyTorch models.
+
+
+Confirm that the segmentation results look as expected by comparing
+model predictions on the OpenVINO IR and PyTorch models.
 
 You can use `pytorch
 tutorial `__
@@ -257,13 +266,13 @@ visualize the image with a ``cat`` mask for the PyTorch model.
 
     import torch
     import matplotlib.pyplot as plt
-
+    
     import torchvision.transforms.functional as F
-
-
+    
+    
     plt.rcParams["savefig.bbox"] = 'tight'
-
-
+    
+    
     def show(imgs):
         if not isinstance(imgs, list):
             imgs = [imgs]
@@ -284,11 +293,11 @@ Prepare and display a cat mask.
         'person', 'pottedplant', 'sheep', 'sofa', 'train', 'tvmonitor'
     ]
     sem_class_to_idx = {cls: idx for (idx, cls) in enumerate(sem_classes)}
-
+    
     normalized_mask = torch.nn.functional.softmax(result_torch, dim=1)
-
+    
     cat_mask = normalized_mask[0, sem_class_to_idx['cat']]
-
+    
     show(cat_mask)
 
 
@@ -313,7 +322,7 @@ And now we can plot a boolean mask on top of the original image.
 .. code:: ipython3
 
     from torchvision.utils import draw_segmentation_masks
-
+    
     show(draw_segmentation_masks(image, masks=boolean_cat_mask, alpha=0.7, colors='yellow'))
 
 
@@ -321,8 +330,10 @@ And now we can plot a boolean mask on top of the original image.
 .. image:: 125-lraspp-segmentation-with-output_files/125-lraspp-segmentation-with-output_32_0.png
 
 
-Show results for the OpenVINO IR model\
---------------------------------------------------------------------------------
+Show results for the OpenVINO IR model
+--------------------------------------
+
+
 
 .. code:: ipython3
 
diff --git a/docs/notebooks/125-lraspp-segmentation-with-output_files/index.html.tmp b/docs/notebooks/125-lraspp-segmentation-with-output_files/index.html.tmp
deleted file mode 100644
index 8927625fe0d60d..00000000000000
--- a/docs/notebooks/125-lraspp-segmentation-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,11 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/125-lraspp-segmentation-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/125-lraspp-segmentation-with-output_files/
../
-125-lraspp-segmentation-with-output_28_0.png       26-Jan-2024 01:05               87576
-125-lraspp-segmentation-with-output_32_0.png       26-Jan-2024 01:05              385522
-125-lraspp-segmentation-with-output_34_0.png       26-Jan-2024 01:05              385520
-125-lraspp-segmentation-with-output_5_0.jpg        26-Jan-2024 01:05               63187
-125-lraspp-segmentation-with-output_5_0.png        26-Jan-2024 01:05              723717
-

-
diff --git a/docs/notebooks/126-tensorflow-hub-with-output.rst b/docs/notebooks/126-tensorflow-hub-with-output.rst
index ea70ac07bcf4c6..a1dd8fc87c65bf 100644
--- a/docs/notebooks/126-tensorflow-hub-with-output.rst
+++ b/docs/notebooks/126-tensorflow-hub-with-output.rst
@@ -21,22 +21,28 @@ You have the flexibility to run this tutorial notebook in its entirety
 or selectively execute specific sections, as each section operates
 independently.
 
-**Table of contents:**
-
-- `Image classification <#image-classification>`__
-- `Install required packages <#install-required-packages>`__
-- `Import libraries <#import-libraries>`__
-- `Download the classifier <#download-the-classifier>`__
-- `Download a single image to try the model on <#download-a-single-image-to-try-the-model-on>`__
-- `Convert model to OpenVINO IR <#convert-model-to-openvino-ir>`__
-- `Select inference device <#select-inference-device>`__
-- `Inference <#inference>`__
-- `Image style transfer <#image-style-transfer>`__
-- `Install required packages <#install-required-packages>`__
-- `Load the model <#load-the-model>`__
-- `Convert the model to OpenVINO IR <#convert-the-model-to-openvino-ir>`__
-- `Select inference device <#select-inference-device>`__
-- `Inference <#inference>`__
+Table of contents:
+^^^^^^^^^^^^^^^^^^
+
+-  `Image classification <#image-classification>`__
+
+   -  `Install required packages <#install-required-packages>`__
+   -  `Import libraries <#import-libraries>`__
+   -  `Download the classifier <#download-the-classifier>`__
+   -  `Download a single image to try the model
+      on <#download-a-single-image-to-try-the-model-on>`__
+   -  `Convert model to OpenVINO IR <#convert-model-to-openvino-ir>`__
+   -  `Select inference device <#select-inference-device>`__
+   -  `Inference <#inference>`__
+
+-  `Image style transfer <#image-style-transfer>`__
+
+   -  `Install required packages <#install-required-packages>`__
+   -  `Load the model <#load-the-model>`__
+   -  `Convert the model to OpenVINO
+      IR <#convert-the-model-to-openvino-ir>`__
+   -  `Select inference device <#select-inference-device>`__
+   -  `Inference <#inference>`__
 
 Image classification
 --------------------
@@ -125,8 +131,8 @@ and wrap it as a Keras layer with ``hub.KerasLayer``.
 
 .. parsed-literal::
 
-    2024-01-25 23:15:55.944757: E tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:266] failed call to cuInit: CUDA_ERROR_COMPAT_NOT_SUPPORTED_ON_DEVICE: forward compatibility was attempted on non supported HW
-    2024-01-25 23:15:55.944938: E tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:312] kernel version 470.182.3 does not match DSO version 470.223.2 -- cannot find working devices in this configuration
+    2024-02-09 23:12:03.569013: E tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:266] failed call to cuInit: CUDA_ERROR_COMPAT_NOT_SUPPORTED_ON_DEVICE: forward compatibility was attempted on non supported HW
+    2024-02-09 23:12:03.569190: E tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:312] kernel version 470.182.3 does not match DSO version 470.223.2 -- cannot find working devices in this configuration
 
 
 Download a single image to try the model on
diff --git a/docs/notebooks/126-tensorflow-hub-with-output_files/index.html.tmp b/docs/notebooks/126-tensorflow-hub-with-output_files/index.html.tmp
deleted file mode 100644
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diff --git a/docs/notebooks/127-tensorflow-bit-image-classification-nncf-quantization-with-output.rst b/docs/notebooks/127-tensorflow-bit-image-classification-nncf-quantization-with-output.rst
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+++ b/docs/notebooks/127-tensorflow-bit-image-classification-nncf-quantization-with-output.rst
@@ -0,0 +1,6226 @@
+Big Transfer Image Classification Model Quantization pipeline with NNCF
+=======================================================================
+
+This tutorial demonstrates the Quantization of the Big Transfer Image
+Classification model, which is fine-tuned on the sub-set of ImageNet
+dataset with 10 class labels with
+`NNCF `__. It uses
+`BiT-M-R50x1/1 `__
+model, which is trained on ImageNet-21k. Big Transfer is a recipe for
+pre-training image classification models on large supervised datasets
+and efficiently fine-tuning them on any given target task. The recipe
+achieves excellent performance on a wide variety of tasks, even when
+using very few labeled examples from the target dataset. This tutorial
+uses OpenVINO backend for performing model quantization in NNCF.
+
+Table of contents:
+^^^^^^^^^^^^^^^^^^
+
+-  `Prepare Dataset <#prepare-dataset>`__
+-  `Plotting data samples <#plotting-data-samples>`__
+-  `Model Fine-tuning <#model-fine-tuning>`__
+-  `Perform model optimization (IR)
+   step <#perform-model-optimization-ir-step>`__
+-  `Compute accuracy of the TF
+   model <#compute-accuracy-of-the-tf-model>`__
+-  `Compute accuracy of the OpenVINO
+   model <#compute-accuracy-of-the-openvino-model>`__
+-  `Quantize OpenVINO model using
+   NNCF <#quantize-openvino-model-using-nncf>`__
+-  `Compute accuracy of the quantized
+   model <#compute-accuracy-of-the-quantized-model>`__
+-  `Compare FP32 and INT8 accuracy <#compare-fp32-and-int8-accuracy>`__
+-  `Compare inference results on one
+   picture <#compare-inference-results-on-one-picture>`__
+
+.. code:: ipython3
+
+    %pip uninstall -q -y openvino-dev openvino openvino-nightly
+    %pip install -q "openvino-nightly" "nncf>=2.7.0" "tensorflow-hub>=0.15.0" "tensorflow_datasets"
+    %pip install -q "scikit-learn>=1.3.2"
+
+
+.. parsed-literal::
+
+    WARNING: Skipping openvino-nightly as it is not installed.
+
+
+.. parsed-literal::
+
+    Note: you may need to restart the kernel to use updated packages.
+
+
+.. parsed-literal::
+
+    Note: you may need to restart the kernel to use updated packages.
+
+
+.. parsed-literal::
+
+    Note: you may need to restart the kernel to use updated packages.
+
+
+.. code:: ipython3
+
+    import os
+    import sys
+    import numpy as np
+    from pathlib import Path
+
+    from openvino.runtime import Core
+    import openvino as ov
+    import nncf
+    import logging
+
+    sys.path.append("../utils")
+    from nncf.common.logging.logger import set_log_level
+    set_log_level(logging.ERROR)
+
+    from sklearn.metrics import accuracy_score
+
+    import tensorflow as tf
+    import tensorflow_datasets as tfds
+    import tensorflow_hub as hub
+
+    tfds.core.utils.gcs_utils._is_gcs_disabled = True
+    os.environ['NO_GCE_CHECK'] = 'true'
+
+
+.. parsed-literal::
+
+    INFO:nncf:NNCF initialized successfully. Supported frameworks detected: torch, tensorflow, onnx, openvino
+
+
+.. parsed-literal::
+
+    2024-02-09 23:12:32.801218: I tensorflow/core/util/port.cc:110] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
+    2024-02-09 23:12:32.834847: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+    To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
+
+
+.. parsed-literal::
+
+    2024-02-09 23:12:33.475171: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+
+
+.. code:: ipython3
+
+    core = Core()
+    tf.compat.v1.logging.set_verbosity(tf.compat.v1.logging.ERROR)
+    os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
+
+
+    # For top 5 labels.
+    MAX_PREDS = 1
+    TRAINING_BATCH_SIZE = 128
+    BATCH_SIZE = 1
+    IMG_SIZE = (256, 256)  # Default Imagenet image size
+    NUM_CLASSES = 10  # For Imagenette dataset
+    FINE_TUNING_STEPS = 1
+    LR = 1e-5
+
+    MEAN_RGB = (0.485 * 255, 0.456 * 255, 0.406 * 255)  # From Imagenet dataset
+    STDDEV_RGB = (0.229 * 255, 0.224 * 255, 0.225 * 255)  # From Imagenet dataset
+
+
+Prepare Dataset
+~~~~~~~~~~~~~~~
+
+
+
+.. code:: ipython3
+
+    datasets, datasets_info = tfds.load('imagenette/160px', shuffle_files=True, as_supervised=True, with_info=True,
+                                        read_config=tfds.ReadConfig(shuffle_seed=0))
+    train_ds, validation_ds = datasets['train'], datasets['validation']
+
+
+
+.. parsed-literal::
+
+    2024-02-09 23:12:36.325702: E tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:266] failed call to cuInit: CUDA_ERROR_COMPAT_NOT_SUPPORTED_ON_DEVICE: forward compatibility was attempted on non supported HW
+    2024-02-09 23:12:36.325736: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:168] retrieving CUDA diagnostic information for host: iotg-dev-workstation-07
+    2024-02-09 23:12:36.325741: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:175] hostname: iotg-dev-workstation-07
+    2024-02-09 23:12:36.325909: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:199] libcuda reported version is: 470.223.2
+    2024-02-09 23:12:36.325927: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:203] kernel reported version is: 470.182.3
+    2024-02-09 23:12:36.325931: E tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:312] kernel version 470.182.3 does not match DSO version 470.223.2 -- cannot find working devices in this configuration
+
+
+.. code:: ipython3
+
+    def preprocessing(image, label):
+        image = tf.image.resize(image, IMG_SIZE)
+        image = tf.cast(image, tf.float32) / 255.0
+        label = tf.one_hot(label, NUM_CLASSES)
+        return image, label
+
+    train_dataset = (train_ds.map(preprocessing, num_parallel_calls=tf.data.experimental.AUTOTUNE)
+                     .batch(TRAINING_BATCH_SIZE).prefetch(tf.data.experimental.AUTOTUNE))
+    validation_dataset = (validation_ds.map(preprocessing, num_parallel_calls=tf.data.experimental.AUTOTUNE)
+                          .batch(TRAINING_BATCH_SIZE).prefetch(tf.data.experimental.AUTOTUNE))
+
+.. code:: ipython3
+
+    # Class labels dictionary with imagenette sample names and classes
+    lbl_dict = dict(
+        n01440764='tench',
+        n02102040='English springer',
+        n02979186='cassette player',
+        n03000684='chain saw',
+        n03028079='church',
+        n03394916='French horn',
+        n03417042='garbage truck',
+        n03425413='gas pump',
+        n03445777='golf ball',
+        n03888257='parachute'
+    )
+
+    # Imagenette samples name index
+    class_idx_dict = ['n01440764', 'n02102040', 'n02979186', 'n03000684',
+                      'n03028079', 'n03394916', 'n03417042', 'n03425413',
+                      'n03445777', 'n03888257']
+
+    def label_func(key):
+        return lbl_dict[key]
+
+Plotting data samples
+~~~~~~~~~~~~~~~~~~~~~
+
+
+
+.. code:: ipython3
+
+    import matplotlib.pyplot as plt
+
+    # Get the class labels from the dataset info
+    class_labels = datasets_info.features['label'].names
+
+    # Display labels along with the examples
+    num_examples_to_display = 4
+    fig, axes = plt.subplots(nrows=1, ncols=num_examples_to_display, figsize=(10, 5))
+
+    for i, (image, label_index) in enumerate(train_ds.take(num_examples_to_display)):
+        label_name = class_labels[label_index.numpy()]
+
+        axes[i].imshow(image.numpy())
+        axes[i].set_title(f"{label_func(label_name)}")
+        axes[i].axis('off')
+        plt.tight_layout()
+    plt.show()
+
+
+.. parsed-literal::
+
+    2024-02-09 23:12:36.722857: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'Placeholder/_3' with dtype int64 and shape [1]
+    	 [[{{node Placeholder/_3}}]]
+    2024-02-09 23:12:36.723230: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'Placeholder/_4' with dtype int64 and shape [1]
+    	 [[{{node Placeholder/_4}}]]
+
+
+.. parsed-literal::
+
+    2024-02-09 23:12:36.934317: W tensorflow/core/kernels/data/cache_dataset_ops.cc:856] The calling iterator did not fully read the dataset being cached. In order to avoid unexpected truncation of the dataset, the partially cached contents of the dataset  will be discarded. This can happen if you have an input pipeline similar to `dataset.cache().take(k).repeat()`. You should use `dataset.take(k).cache().repeat()` instead.
+
+
+
+.. image:: 127-tensorflow-bit-image-classification-nncf-quantization-with-output_files/127-tensorflow-bit-image-classification-nncf-quantization-with-output_9_2.png
+
+
+.. code:: ipython3
+
+    # Get the class labels from the dataset info
+    class_labels = datasets_info.features['label'].names
+
+    # Display labels along with the examples
+    num_examples_to_display = 4
+    fig, axes = plt.subplots(nrows=1, ncols=num_examples_to_display, figsize=(10, 5))
+
+    for i, (image, label_index) in enumerate(validation_ds.take(num_examples_to_display)):
+        label_name = class_labels[label_index.numpy()]
+
+        axes[i].imshow(image.numpy())
+        axes[i].set_title(f"{label_func(label_name)}")
+        axes[i].axis('off')
+        plt.tight_layout()
+    plt.show()
+
+
+.. parsed-literal::
+
+    2024-02-09 23:12:37.419912: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'Placeholder/_4' with dtype int64 and shape [1]
+    	 [[{{node Placeholder/_4}}]]
+    2024-02-09 23:12:37.420269: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'Placeholder/_4' with dtype int64 and shape [1]
+    	 [[{{node Placeholder/_4}}]]
+    2024-02-09 23:12:37.609873: W tensorflow/core/kernels/data/cache_dataset_ops.cc:856] The calling iterator did not fully read the dataset being cached. In order to avoid unexpected truncation of the dataset, the partially cached contents of the dataset  will be discarded. This can happen if you have an input pipeline similar to `dataset.cache().take(k).repeat()`. You should use `dataset.take(k).cache().repeat()` instead.
+
+
+
+.. image:: 127-tensorflow-bit-image-classification-nncf-quantization-with-output_files/127-tensorflow-bit-image-classification-nncf-quantization-with-output_10_1.png
+
+
+Model Fine-tuning
+~~~~~~~~~~~~~~~~~
+
+
+
+.. code:: ipython3
+
+    # Load the Big Transfer model
+    bit_model_url = "https://www.kaggle.com/models/google/bit/frameworks/TensorFlow2/variations/m-r50x1/versions/1"
+    bit_m = hub.KerasLayer(bit_model_url, trainable=True)
+
+    # Customize the model for the new task
+    model = tf.keras.Sequential([
+        bit_m,
+        tf.keras.layers.Dense(NUM_CLASSES, activation='softmax')
+    ])
+
+    # Compile the model
+    model.compile(optimizer=tf.keras.optimizers.Adam(learning_rate=LR),
+                  loss='categorical_crossentropy',
+                  metrics=['accuracy'])
+
+    # Fine-tune the model
+    model.fit(train_dataset.take(3000),
+              epochs=FINE_TUNING_STEPS,
+              validation_data=validation_dataset.take(1000))
+    model.save("./bit_tf_model/", save_format='tf')
+
+
+.. parsed-literal::
+
+    2024-02-09 23:12:46.261759: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'Placeholder/_4' with dtype int64 and shape [1]
+    	 [[{{node Placeholder/_4}}]]
+    2024-02-09 23:12:46.262214: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'Placeholder/_3' with dtype int64 and shape [1]
+    	 [[{{node Placeholder/_3}}]]
+
+
+.. parsed-literal::
+
+    2024-02-09 23:12:46.814688: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/global_average_pooling2d/PartitionedCall_grad/global_average_pooling2d/PartitionedCall' with dtype float and shape [?,?,?,?]
+    	 [[{{node gradients/global_average_pooling2d/PartitionedCall_grad/global_average_pooling2d/PartitionedCall}}]]
+    2024-02-09 23:12:46.814757: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/global_average_pooling2d/PartitionedCall_grad/global_average_pooling2d/PartitionedCall_1' with dtype int32 and shape [2]
+    	 [[{{node gradients/global_average_pooling2d/PartitionedCall_grad/global_average_pooling2d/PartitionedCall_1}}]]
+    2024-02-09 23:12:46.873936: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/group_norm/StatefulPartitionedCall_grad/group_norm/StatefulPartitionedCall' with dtype float and shape [?,?,?,32,64]
+    	 [[{{node gradients/group_norm/StatefulPartitionedCall_grad/group_norm/StatefulPartitionedCall}}]]
+    2024-02-09 23:12:46.873995: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/group_norm/StatefulPartitionedCall_grad/group_norm/StatefulPartitionedCall_1' with dtype float and shape [?,?,?,32,64]
+    	 [[{{node gradients/group_norm/StatefulPartitionedCall_grad/group_norm/StatefulPartitionedCall_1}}]]
+    2024-02-09 23:12:46.874031: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/group_norm/StatefulPartitionedCall_grad/group_norm/StatefulPartitionedCall_2' with dtype float and shape [?,1,1,32,64]
+    	 [[{{node gradients/group_norm/StatefulPartitionedCall_grad/group_norm/StatefulPartitionedCall_2}}]]
+    2024-02-09 23:12:46.874063: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/group_norm/StatefulPartitionedCall_grad/group_norm/StatefulPartitionedCall_3' with dtype float and shape [?,?,?,32,64]
+    	 [[{{node gradients/group_norm/StatefulPartitionedCall_grad/group_norm/StatefulPartitionedCall_3}}]]
+    2024-02-09 23:12:46.874094: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/group_norm/StatefulPartitionedCall_grad/group_norm/StatefulPartitionedCall_4' with dtype float and shape [?,1,1,32,64]
+    	 [[{{node gradients/group_norm/StatefulPartitionedCall_grad/group_norm/StatefulPartitionedCall_4}}]]
+    2024-02-09 23:12:46.874125: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/group_norm/StatefulPartitionedCall_grad/group_norm/StatefulPartitionedCall_5' with dtype float and shape [32,64]
+    	 [[{{node gradients/group_norm/StatefulPartitionedCall_grad/group_norm/StatefulPartitionedCall_5}}]]
+    2024-02-09 23:12:46.874156: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/group_norm/StatefulPartitionedCall_grad/group_norm/StatefulPartitionedCall_6' with dtype float and shape [?,1,1,32,64]
+    	 [[{{node gradients/group_norm/StatefulPartitionedCall_grad/group_norm/StatefulPartitionedCall_6}}]]
+    2024-02-09 23:12:46.874189: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/group_norm/StatefulPartitionedCall_grad/group_norm/StatefulPartitionedCall_7' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/group_norm/StatefulPartitionedCall_grad/group_norm/StatefulPartitionedCall_7}}]]
+    2024-02-09 23:12:46.874221: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/group_norm/StatefulPartitionedCall_grad/group_norm/StatefulPartitionedCall_8' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/group_norm/StatefulPartitionedCall_grad/group_norm/StatefulPartitionedCall_8}}]]
+    2024-02-09 23:12:46.874252: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/group_norm/StatefulPartitionedCall_grad/group_norm/StatefulPartitionedCall_9' with dtype float and shape [32,64]
+    	 [[{{node gradients/group_norm/StatefulPartitionedCall_grad/group_norm/StatefulPartitionedCall_9}}]]
+    2024-02-09 23:12:46.874284: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/group_norm/StatefulPartitionedCall_grad/group_norm/StatefulPartitionedCall_10' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/group_norm/StatefulPartitionedCall_grad/group_norm/StatefulPartitionedCall_10}}]]
+    2024-02-09 23:12:46.874317: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/group_norm/StatefulPartitionedCall_grad/group_norm/StatefulPartitionedCall_11' with dtype float
+    	 [[{{node gradients/group_norm/StatefulPartitionedCall_grad/group_norm/StatefulPartitionedCall_11}}]]
+    2024-02-09 23:12:46.874350: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/group_norm/StatefulPartitionedCall_grad/group_norm/StatefulPartitionedCall_12' with dtype float and shape [?,?,?,32,64]
+    	 [[{{node gradients/group_norm/StatefulPartitionedCall_grad/group_norm/StatefulPartitionedCall_12}}]]
+    2024-02-09 23:12:46.874382: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/group_norm/StatefulPartitionedCall_grad/group_norm/StatefulPartitionedCall_13' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/group_norm/StatefulPartitionedCall_grad/group_norm/StatefulPartitionedCall_13}}]]
+    2024-02-09 23:12:46.874414: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/group_norm/StatefulPartitionedCall_grad/group_norm/StatefulPartitionedCall_14' with dtype float and shape [?,?,?,2048]
+    	 [[{{node gradients/group_norm/StatefulPartitionedCall_grad/group_norm/StatefulPartitionedCall_14}}]]
+
+
+.. parsed-literal::
+
+    2024-02-09 23:12:47.623559: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall' with dtype float and shape [?,?,?,2048]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall}}]]
+    2024-02-09 23:12:47.623635: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_1' with dtype float and shape [?,?,?,2048]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_1}}]]
+    2024-02-09 23:12:47.623673: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_2' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_2}}]]
+    2024-02-09 23:12:47.623706: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_6' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_6}}]]
+    2024-02-09 23:12:47.623739: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_7' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_7}}]]
+    2024-02-09 23:12:47.623770: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_8' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_8}}]]
+    2024-02-09 23:12:47.623818: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_9' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_9}}]]
+    2024-02-09 23:12:47.623851: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_10' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_10}}]]
+    2024-02-09 23:12:47.623883: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_11' with dtype float and shape [32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_11}}]]
+    2024-02-09 23:12:47.623915: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_12' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_12}}]]
+    2024-02-09 23:12:47.623948: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_13' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_13}}]]
+    2024-02-09 23:12:47.623979: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_16' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_16}}]]
+    2024-02-09 23:12:47.624011: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_17' with dtype float and shape [32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_17}}]]
+    2024-02-09 23:12:47.624042: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_18' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_18}}]]
+    2024-02-09 23:12:47.624075: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_19' with dtype float
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_19}}]]
+    2024-02-09 23:12:47.624106: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_20' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_20}}]]
+    2024-02-09 23:12:47.624138: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_21' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_21}}]]
+    2024-02-09 23:12:47.624169: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_22' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_22}}]]
+    2024-02-09 23:12:47.624202: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_23' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_23}}]]
+    2024-02-09 23:12:47.624234: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_25' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_25}}]]
+    2024-02-09 23:12:47.624265: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_26' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_26}}]]
+    2024-02-09 23:12:47.624297: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_29' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_29}}]]
+    2024-02-09 23:12:47.624329: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_30' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_30}}]]
+    2024-02-09 23:12:47.624363: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_31' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_31}}]]
+    2024-02-09 23:12:47.624394: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_32' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_32}}]]
+    2024-02-09 23:12:47.624429: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_33' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_33}}]]
+    2024-02-09 23:12:47.624463: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_34' with dtype float and shape [32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_34}}]]
+    2024-02-09 23:12:47.624497: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_35' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_35}}]]
+    2024-02-09 23:12:47.624531: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_38' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_38}}]]
+    2024-02-09 23:12:47.624565: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_39' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_39}}]]
+    2024-02-09 23:12:47.624598: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_40' with dtype float and shape [32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_40}}]]
+    2024-02-09 23:12:47.624631: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_41' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_41}}]]
+    2024-02-09 23:12:47.624664: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_42' with dtype float
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_42}}]]
+    2024-02-09 23:12:47.624699: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_43' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_43}}]]
+    2024-02-09 23:12:47.624732: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_44' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_44}}]]
+    2024-02-09 23:12:47.624766: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_45' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_45}}]]
+    2024-02-09 23:12:47.624799: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_46' with dtype float and shape [?,?,?,2048]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_46}}]]
+    2024-02-09 23:12:47.624833: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_50' with dtype float and shape [?,?,?,32,64]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_50}}]]
+    2024-02-09 23:12:47.624867: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_51' with dtype float and shape [?,?,?,32,64]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_51}}]]
+    2024-02-09 23:12:47.624901: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_52' with dtype float and shape [?,1,1,32,64]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_52}}]]
+    2024-02-09 23:12:47.624934: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_53' with dtype float and shape [?,?,?,32,64]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_53}}]]
+    2024-02-09 23:12:47.624968: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_54' with dtype float and shape [?,1,1,32,64]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_54}}]]
+    2024-02-09 23:12:47.625001: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_55' with dtype float and shape [32,64]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_55}}]]
+    2024-02-09 23:12:47.625036: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_56' with dtype float and shape [?,1,1,32,64]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_56}}]]
+    2024-02-09 23:12:47.625070: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_57' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_57}}]]
+    2024-02-09 23:12:47.625103: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_60' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_60}}]]
+    2024-02-09 23:12:47.625137: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_61' with dtype float and shape [32,64]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_61}}]]
+    2024-02-09 23:12:47.625170: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_62' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_62}}]]
+    2024-02-09 23:12:47.625203: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_63' with dtype float
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_63}}]]
+    2024-02-09 23:12:47.625237: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_64' with dtype float and shape [?,?,?,32,64]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_64}}]]
+    2024-02-09 23:12:47.625271: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_65' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_65}}]]
+    2024-02-09 23:12:47.625304: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_66' with dtype float and shape [?,?,?,2048]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_66}}]]
+    2024-02-09 23:12:47.625338: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_67' with dtype float and shape [?,?,?,2048]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_67}}]]
+    2024-02-09 23:12:47.625371: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_68' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_68}}]]
+    2024-02-09 23:12:47.625415: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_72' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_72}}]]
+    2024-02-09 23:12:47.625452: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_73' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_73}}]]
+    2024-02-09 23:12:47.625504: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_74' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_74}}]]
+    2024-02-09 23:12:47.625538: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_75' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_75}}]]
+    2024-02-09 23:12:47.625572: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_76' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_76}}]]
+    2024-02-09 23:12:47.625606: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_77' with dtype float and shape [32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_77}}]]
+    2024-02-09 23:12:47.625639: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_78' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_78}}]]
+    2024-02-09 23:12:47.625673: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_79' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_79}}]]
+    2024-02-09 23:12:47.625706: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_82' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_82}}]]
+    2024-02-09 23:12:47.625739: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_83' with dtype float and shape [32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_83}}]]
+    2024-02-09 23:12:47.625773: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_84' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_84}}]]
+    2024-02-09 23:12:47.625806: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_85' with dtype float
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_85}}]]
+    2024-02-09 23:12:47.625840: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_86' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_86}}]]
+    2024-02-09 23:12:47.625874: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_87' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_87}}]]
+    2024-02-09 23:12:47.625908: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_88' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_88}}]]
+    2024-02-09 23:12:47.625941: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_89' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_89}}]]
+    2024-02-09 23:12:47.625974: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_91' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_91}}]]
+    2024-02-09 23:12:47.626008: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_92' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_92}}]]
+    2024-02-09 23:12:47.626041: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_95' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_95}}]]
+    2024-02-09 23:12:47.626075: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_96' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_96}}]]
+    2024-02-09 23:12:47.626109: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_97' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_97}}]]
+    2024-02-09 23:12:47.626142: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_98' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_98}}]]
+    2024-02-09 23:12:47.626176: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_99' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_99}}]]
+    2024-02-09 23:12:47.626209: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_100' with dtype float and shape [32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_100}}]]
+    2024-02-09 23:12:47.626244: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_101' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_101}}]]
+    2024-02-09 23:12:47.626278: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_104' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_104}}]]
+    2024-02-09 23:12:47.626311: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_105' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_105}}]]
+    2024-02-09 23:12:47.626344: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_106' with dtype float and shape [32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_106}}]]
+    2024-02-09 23:12:47.626377: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_107' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_107}}]]
+    2024-02-09 23:12:47.626410: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_108' with dtype float
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_108}}]]
+    2024-02-09 23:12:47.626444: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_109' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_109}}]]
+    2024-02-09 23:12:47.626478: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_110' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_110}}]]
+    2024-02-09 23:12:47.626512: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_111' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_111}}]]
+    2024-02-09 23:12:47.626545: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_112' with dtype float and shape [?,?,?,2048]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_112}}]]
+    2024-02-09 23:12:47.626578: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_116' with dtype float and shape [?,?,?,32,64]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_116}}]]
+    2024-02-09 23:12:47.626612: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_117' with dtype float and shape [?,?,?,32,64]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_117}}]]
+    2024-02-09 23:12:47.626646: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_118' with dtype float and shape [?,1,1,32,64]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_118}}]]
+    2024-02-09 23:12:47.626679: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_119' with dtype float and shape [?,?,?,32,64]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_119}}]]
+    2024-02-09 23:12:47.626723: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_120' with dtype float and shape [?,1,1,32,64]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_120}}]]
+    2024-02-09 23:12:47.626755: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_121' with dtype float and shape [32,64]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_121}}]]
+    2024-02-09 23:12:47.626787: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_122' with dtype float and shape [?,1,1,32,64]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_122}}]]
+    2024-02-09 23:12:47.626819: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_123' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_123}}]]
+    2024-02-09 23:12:47.626852: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_126' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_126}}]]
+    2024-02-09 23:12:47.626884: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_127' with dtype float and shape [32,64]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_127}}]]
+    2024-02-09 23:12:47.626915: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_128' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_128}}]]
+    2024-02-09 23:12:47.626946: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_129' with dtype float
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_129}}]]
+    2024-02-09 23:12:47.626980: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_130' with dtype float and shape [?,?,?,32,64]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_130}}]]
+    2024-02-09 23:12:47.627012: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_131' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_131}}]]
+    2024-02-09 23:12:47.627044: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_132' with dtype float and shape [?,?,?,2048]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_132}}]]
+    2024-02-09 23:12:47.627077: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_133' with dtype float and shape [?,?,?,2048]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_133}}]]
+    2024-02-09 23:12:47.627109: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_134' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_134}}]]
+    2024-02-09 23:12:47.627140: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_136' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_136}}]]
+    2024-02-09 23:12:47.627172: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_142' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_142}}]]
+    2024-02-09 23:12:47.627204: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_143' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_143}}]]
+    2024-02-09 23:12:47.627236: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_144' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_144}}]]
+    2024-02-09 23:12:47.627267: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_145' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_145}}]]
+    2024-02-09 23:12:47.627299: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_146' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_146}}]]
+    2024-02-09 23:12:47.627331: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_147' with dtype float and shape [32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_147}}]]
+    2024-02-09 23:12:47.627364: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_148' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_148}}]]
+    2024-02-09 23:12:47.627396: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_149' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_149}}]]
+    2024-02-09 23:12:47.627428: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_154' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_154}}]]
+    2024-02-09 23:12:47.627460: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_155' with dtype float and shape [32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_155}}]]
+    2024-02-09 23:12:47.627493: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_156' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_156}}]]
+    2024-02-09 23:12:47.627525: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_157' with dtype float
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_157}}]]
+    2024-02-09 23:12:47.627557: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_158' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_158}}]]
+    2024-02-09 23:12:47.627589: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_159' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_159}}]]
+    2024-02-09 23:12:47.627621: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_160' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_160}}]]
+    2024-02-09 23:12:47.627652: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_161' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_161}}]]
+    2024-02-09 23:12:47.627685: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_163' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_163}}]]
+    2024-02-09 23:12:47.627718: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_164' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_164}}]]
+    2024-02-09 23:12:47.627750: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_167' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_167}}]]
+    2024-02-09 23:12:47.627782: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_168' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_168}}]]
+    2024-02-09 23:12:47.627813: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_169' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_169}}]]
+    2024-02-09 23:12:47.627845: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_170' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_170}}]]
+    2024-02-09 23:12:47.627877: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_171' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_171}}]]
+    2024-02-09 23:12:47.627909: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_172' with dtype float and shape [32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_172}}]]
+    2024-02-09 23:12:47.627942: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_173' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_173}}]]
+    2024-02-09 23:12:47.627974: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_176' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_176}}]]
+    2024-02-09 23:12:47.628005: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_177' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_177}}]]
+    2024-02-09 23:12:47.628038: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_178' with dtype float and shape [32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_178}}]]
+    2024-02-09 23:12:47.628070: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_179' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_179}}]]
+    2024-02-09 23:12:47.628102: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_180' with dtype float
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_180}}]]
+    2024-02-09 23:12:47.628134: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_181' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_181}}]]
+    2024-02-09 23:12:47.628166: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_182' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_182}}]]
+    2024-02-09 23:12:47.628197: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_183' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_183}}]]
+    2024-02-09 23:12:47.628230: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_187' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_187}}]]
+    2024-02-09 23:12:47.628262: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_188' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_188}}]]
+    2024-02-09 23:12:47.628294: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_189' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_189}}]]
+    2024-02-09 23:12:47.628326: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_190' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_190}}]]
+    2024-02-09 23:12:47.628358: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_191' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_191}}]]
+    2024-02-09 23:12:47.628390: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_192' with dtype float and shape [32,32]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_192}}]]
+    2024-02-09 23:12:47.628422: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_193' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_193}}]]
+    2024-02-09 23:12:47.628453: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_194' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_194}}]]
+    2024-02-09 23:12:47.628485: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_197' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_197}}]]
+    2024-02-09 23:12:47.628517: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_198' with dtype float and shape [32,32]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_198}}]]
+    2024-02-09 23:12:47.628548: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_199' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_199}}]]
+    2024-02-09 23:12:47.628580: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_200' with dtype float
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_200}}]]
+    2024-02-09 23:12:47.628612: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_201' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_201}}]]
+    2024-02-09 23:12:47.628644: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_202' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_202}}]]
+    2024-02-09 23:12:47.628676: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_203' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/block4/StatefulPartitionedCall_grad/block4/StatefulPartitionedCall_203}}]]
+
+
+.. parsed-literal::
+
+    2024-02-09 23:12:49.091548: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall}}]]
+    2024-02-09 23:12:49.091625: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_1' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_1}}]]
+    2024-02-09 23:12:49.091662: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_2' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_2}}]]
+    2024-02-09 23:12:49.091696: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_6' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_6}}]]
+    2024-02-09 23:12:49.091728: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_7' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_7}}]]
+    2024-02-09 23:12:49.091760: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_8' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_8}}]]
+    2024-02-09 23:12:49.091791: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_9' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_9}}]]
+    2024-02-09 23:12:49.091823: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_10' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_10}}]]
+    2024-02-09 23:12:49.091855: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_11' with dtype float and shape [32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_11}}]]
+    2024-02-09 23:12:49.091886: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_12' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_12}}]]
+    2024-02-09 23:12:49.091917: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_13' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_13}}]]
+    2024-02-09 23:12:49.091949: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_16' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_16}}]]
+    2024-02-09 23:12:49.091980: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_17' with dtype float and shape [32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_17}}]]
+    2024-02-09 23:12:49.092010: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_18' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_18}}]]
+    2024-02-09 23:12:49.092043: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_19' with dtype float
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_19}}]]
+    2024-02-09 23:12:49.092074: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_20' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_20}}]]
+    2024-02-09 23:12:49.092105: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_21' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_21}}]]
+    2024-02-09 23:12:49.092136: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_22' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_22}}]]
+    2024-02-09 23:12:49.092166: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_23' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_23}}]]
+    2024-02-09 23:12:49.092199: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_25' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_25}}]]
+    2024-02-09 23:12:49.092229: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_26' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_26}}]]
+    2024-02-09 23:12:49.092260: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_29' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_29}}]]
+    2024-02-09 23:12:49.092291: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_30' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_30}}]]
+    2024-02-09 23:12:49.092322: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_31' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_31}}]]
+    2024-02-09 23:12:49.092352: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_32' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_32}}]]
+    2024-02-09 23:12:49.092383: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_33' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_33}}]]
+    2024-02-09 23:12:49.092416: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_34' with dtype float and shape [32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_34}}]]
+    2024-02-09 23:12:49.092448: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_35' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_35}}]]
+    2024-02-09 23:12:49.092481: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_38' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_38}}]]
+    2024-02-09 23:12:49.092515: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_39' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_39}}]]
+    2024-02-09 23:12:49.092547: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_40' with dtype float and shape [32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_40}}]]
+    2024-02-09 23:12:49.092579: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_41' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_41}}]]
+    2024-02-09 23:12:49.092611: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_42' with dtype float
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_42}}]]
+    2024-02-09 23:12:49.092644: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_43' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_43}}]]
+    2024-02-09 23:12:49.092676: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_44' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_44}}]]
+    2024-02-09 23:12:49.092708: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_45' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_45}}]]
+    2024-02-09 23:12:49.092741: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_46' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_46}}]]
+    2024-02-09 23:12:49.092774: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_50' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_50}}]]
+    2024-02-09 23:12:49.092807: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_51' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_51}}]]
+    2024-02-09 23:12:49.092840: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_52' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_52}}]]
+    2024-02-09 23:12:49.092872: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_53' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_53}}]]
+    2024-02-09 23:12:49.092905: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_54' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_54}}]]
+    2024-02-09 23:12:49.092937: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_55' with dtype float and shape [32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_55}}]]
+    2024-02-09 23:12:49.092970: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_56' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_56}}]]
+    2024-02-09 23:12:49.093003: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_57' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_57}}]]
+    2024-02-09 23:12:49.093035: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_60' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_60}}]]
+    2024-02-09 23:12:49.093067: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_61' with dtype float and shape [32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_61}}]]
+    2024-02-09 23:12:49.093100: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_62' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_62}}]]
+    2024-02-09 23:12:49.093132: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_63' with dtype float
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_63}}]]
+    2024-02-09 23:12:49.093164: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_64' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_64}}]]
+    2024-02-09 23:12:49.093196: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_65' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_65}}]]
+    2024-02-09 23:12:49.093229: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_66' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_66}}]]
+    2024-02-09 23:12:49.093262: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_67' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_67}}]]
+    2024-02-09 23:12:49.093294: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_68' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_68}}]]
+    2024-02-09 23:12:49.093327: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_72' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_72}}]]
+    2024-02-09 23:12:49.093360: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_73' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_73}}]]
+    2024-02-09 23:12:49.093392: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_74' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_74}}]]
+    2024-02-09 23:12:49.093425: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_75' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_75}}]]
+    2024-02-09 23:12:49.093479: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_76' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_76}}]]
+    2024-02-09 23:12:49.093514: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_77' with dtype float and shape [32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_77}}]]
+    2024-02-09 23:12:49.093548: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_78' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_78}}]]
+    2024-02-09 23:12:49.093582: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_79' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_79}}]]
+    2024-02-09 23:12:49.093618: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_82' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_82}}]]
+    2024-02-09 23:12:49.093653: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_83' with dtype float and shape [32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_83}}]]
+    2024-02-09 23:12:49.093689: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_84' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_84}}]]
+    2024-02-09 23:12:49.093722: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_85' with dtype float
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_85}}]]
+    2024-02-09 23:12:49.093756: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_86' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_86}}]]
+    2024-02-09 23:12:49.093792: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_87' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_87}}]]
+    2024-02-09 23:12:49.093826: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_88' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_88}}]]
+    2024-02-09 23:12:49.093860: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_89' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_89}}]]
+    2024-02-09 23:12:49.093895: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_91' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_91}}]]
+    2024-02-09 23:12:49.093929: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_92' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_92}}]]
+    2024-02-09 23:12:49.093963: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_95' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_95}}]]
+    2024-02-09 23:12:49.093997: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_96' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_96}}]]
+    2024-02-09 23:12:49.094031: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_97' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_97}}]]
+    2024-02-09 23:12:49.094066: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_98' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_98}}]]
+    2024-02-09 23:12:49.094100: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_99' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_99}}]]
+    2024-02-09 23:12:49.094136: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_100' with dtype float and shape [32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_100}}]]
+    2024-02-09 23:12:49.094171: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_101' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_101}}]]
+    2024-02-09 23:12:49.094205: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_104' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_104}}]]
+    2024-02-09 23:12:49.094240: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_105' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_105}}]]
+    2024-02-09 23:12:49.094275: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_106' with dtype float and shape [32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_106}}]]
+    2024-02-09 23:12:49.094309: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_107' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_107}}]]
+    2024-02-09 23:12:49.094343: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_108' with dtype float
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_108}}]]
+    2024-02-09 23:12:49.094377: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_109' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_109}}]]
+    2024-02-09 23:12:49.094412: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_110' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_110}}]]
+    2024-02-09 23:12:49.094446: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_111' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_111}}]]
+    2024-02-09 23:12:49.094481: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_112' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_112}}]]
+    2024-02-09 23:12:49.094516: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_116' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_116}}]]
+    2024-02-09 23:12:49.094550: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_117' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_117}}]]
+    2024-02-09 23:12:49.094584: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_118' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_118}}]]
+    2024-02-09 23:12:49.094618: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_119' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_119}}]]
+    2024-02-09 23:12:49.094652: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_120' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_120}}]]
+    2024-02-09 23:12:49.094686: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_121' with dtype float and shape [32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_121}}]]
+    2024-02-09 23:12:49.094731: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_122' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_122}}]]
+    2024-02-09 23:12:49.094764: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_123' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_123}}]]
+    2024-02-09 23:12:49.094796: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_126' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_126}}]]
+    2024-02-09 23:12:49.094829: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_127' with dtype float and shape [32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_127}}]]
+    2024-02-09 23:12:49.094861: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_128' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_128}}]]
+    2024-02-09 23:12:49.094895: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_129' with dtype float
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_129}}]]
+    2024-02-09 23:12:49.094927: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_130' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_130}}]]
+    2024-02-09 23:12:49.094960: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_131' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_131}}]]
+    2024-02-09 23:12:49.094992: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_132' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_132}}]]
+    2024-02-09 23:12:49.095025: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_133' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_133}}]]
+    2024-02-09 23:12:49.095058: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_134' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_134}}]]
+    2024-02-09 23:12:49.095091: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_138' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_138}}]]
+    2024-02-09 23:12:49.095124: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_139' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_139}}]]
+    2024-02-09 23:12:49.095157: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_140' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_140}}]]
+    2024-02-09 23:12:49.095189: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_141' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_141}}]]
+    2024-02-09 23:12:49.095222: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_142' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_142}}]]
+    2024-02-09 23:12:49.095255: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_143' with dtype float and shape [32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_143}}]]
+    2024-02-09 23:12:49.095288: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_144' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_144}}]]
+    2024-02-09 23:12:49.095321: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_145' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_145}}]]
+    2024-02-09 23:12:49.095354: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_148' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_148}}]]
+    2024-02-09 23:12:49.095387: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_149' with dtype float and shape [32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_149}}]]
+    2024-02-09 23:12:49.095420: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_150' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_150}}]]
+    2024-02-09 23:12:49.095453: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_151' with dtype float
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_151}}]]
+    2024-02-09 23:12:49.095486: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_152' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_152}}]]
+    2024-02-09 23:12:49.095519: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_153' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_153}}]]
+    2024-02-09 23:12:49.095552: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_154' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_154}}]]
+    2024-02-09 23:12:49.095585: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_155' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_155}}]]
+    2024-02-09 23:12:49.095618: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_157' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_157}}]]
+    2024-02-09 23:12:49.095651: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_158' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_158}}]]
+    2024-02-09 23:12:49.095684: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_161' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_161}}]]
+    2024-02-09 23:12:49.095716: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_162' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_162}}]]
+    2024-02-09 23:12:49.095749: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_163' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_163}}]]
+    2024-02-09 23:12:49.095782: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_164' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_164}}]]
+    2024-02-09 23:12:49.095815: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_165' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_165}}]]
+    2024-02-09 23:12:49.095848: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_166' with dtype float and shape [32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_166}}]]
+    2024-02-09 23:12:49.095881: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_167' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_167}}]]
+    2024-02-09 23:12:49.095914: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_170' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_170}}]]
+    2024-02-09 23:12:49.095947: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_171' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_171}}]]
+    2024-02-09 23:12:49.095980: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_172' with dtype float and shape [32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_172}}]]
+    2024-02-09 23:12:49.096013: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_173' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_173}}]]
+    2024-02-09 23:12:49.096045: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_174' with dtype float
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_174}}]]
+    2024-02-09 23:12:49.096078: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_175' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_175}}]]
+    2024-02-09 23:12:49.096111: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_176' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_176}}]]
+    2024-02-09 23:12:49.096143: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_177' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_177}}]]
+    2024-02-09 23:12:49.096176: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_178' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_178}}]]
+    2024-02-09 23:12:49.096209: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_182' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_182}}]]
+    2024-02-09 23:12:49.096242: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_183' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_183}}]]
+    2024-02-09 23:12:49.096275: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_184' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_184}}]]
+    2024-02-09 23:12:49.096307: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_185' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_185}}]]
+    2024-02-09 23:12:49.096340: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_186' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_186}}]]
+    2024-02-09 23:12:49.096373: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_187' with dtype float and shape [32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_187}}]]
+    2024-02-09 23:12:49.096406: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_188' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_188}}]]
+    2024-02-09 23:12:49.096439: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_189' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_189}}]]
+    2024-02-09 23:12:49.096473: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_192' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_192}}]]
+    2024-02-09 23:12:49.096505: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_193' with dtype float and shape [32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_193}}]]
+    2024-02-09 23:12:49.096536: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_194' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_194}}]]
+    2024-02-09 23:12:49.096569: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_195' with dtype float
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_195}}]]
+    2024-02-09 23:12:49.096601: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_196' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_196}}]]
+    2024-02-09 23:12:49.096635: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_197' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_197}}]]
+    2024-02-09 23:12:49.096667: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_198' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_198}}]]
+    2024-02-09 23:12:49.096701: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_199' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_199}}]]
+    2024-02-09 23:12:49.096733: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_200' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_200}}]]
+    2024-02-09 23:12:49.096766: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_204' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_204}}]]
+    2024-02-09 23:12:49.096799: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_205' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_205}}]]
+    2024-02-09 23:12:49.096832: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_206' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_206}}]]
+    2024-02-09 23:12:49.096865: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_207' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_207}}]]
+    2024-02-09 23:12:49.096897: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_208' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_208}}]]
+    2024-02-09 23:12:49.096929: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_209' with dtype float and shape [32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_209}}]]
+    2024-02-09 23:12:49.096961: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_210' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_210}}]]
+    2024-02-09 23:12:49.096993: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_211' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_211}}]]
+    2024-02-09 23:12:49.097027: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_214' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_214}}]]
+    2024-02-09 23:12:49.097059: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_215' with dtype float and shape [32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_215}}]]
+    2024-02-09 23:12:49.097092: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_216' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_216}}]]
+    2024-02-09 23:12:49.097124: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_217' with dtype float
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_217}}]]
+    2024-02-09 23:12:49.097156: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_218' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_218}}]]
+    2024-02-09 23:12:49.097188: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_219' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_219}}]]
+    2024-02-09 23:12:49.097221: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_220' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_220}}]]
+    2024-02-09 23:12:49.097254: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_221' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_221}}]]
+    2024-02-09 23:12:49.097286: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_223' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_223}}]]
+    2024-02-09 23:12:49.097317: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_224' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_224}}]]
+    2024-02-09 23:12:49.097350: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_227' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_227}}]]
+    2024-02-09 23:12:49.097383: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_228' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_228}}]]
+    2024-02-09 23:12:49.097416: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_229' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_229}}]]
+    2024-02-09 23:12:49.097454: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_230' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_230}}]]
+    2024-02-09 23:12:49.097506: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_231' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_231}}]]
+    2024-02-09 23:12:49.097540: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_232' with dtype float and shape [32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_232}}]]
+    2024-02-09 23:12:49.097573: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_233' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_233}}]]
+    2024-02-09 23:12:49.097607: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_236' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_236}}]]
+    2024-02-09 23:12:49.097642: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_237' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_237}}]]
+    2024-02-09 23:12:49.097677: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_238' with dtype float and shape [32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_238}}]]
+    2024-02-09 23:12:49.097710: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_239' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_239}}]]
+    2024-02-09 23:12:49.097744: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_240' with dtype float
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_240}}]]
+    2024-02-09 23:12:49.097777: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_241' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_241}}]]
+    2024-02-09 23:12:49.097811: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_242' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_242}}]]
+    2024-02-09 23:12:49.097845: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_243' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_243}}]]
+    2024-02-09 23:12:49.097879: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_244' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_244}}]]
+    2024-02-09 23:12:49.097912: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_248' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_248}}]]
+    2024-02-09 23:12:49.097946: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_249' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_249}}]]
+    2024-02-09 23:12:49.097980: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_250' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_250}}]]
+    2024-02-09 23:12:49.098014: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_251' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_251}}]]
+    2024-02-09 23:12:49.098049: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_252' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_252}}]]
+    2024-02-09 23:12:49.098083: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_253' with dtype float and shape [32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_253}}]]
+    2024-02-09 23:12:49.098117: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_254' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_254}}]]
+    2024-02-09 23:12:49.098151: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_255' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_255}}]]
+    2024-02-09 23:12:49.098185: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_258' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_258}}]]
+    2024-02-09 23:12:49.098218: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_259' with dtype float and shape [32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_259}}]]
+    2024-02-09 23:12:49.098253: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_260' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_260}}]]
+    2024-02-09 23:12:49.098287: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_261' with dtype float
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_261}}]]
+    2024-02-09 23:12:49.098322: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_262' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_262}}]]
+    2024-02-09 23:12:49.098356: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_263' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_263}}]]
+    2024-02-09 23:12:49.098389: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_264' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_264}}]]
+    2024-02-09 23:12:49.098422: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_265' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_265}}]]
+    2024-02-09 23:12:49.098456: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_266' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_266}}]]
+    2024-02-09 23:12:49.098489: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_270' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_270}}]]
+    2024-02-09 23:12:49.098523: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_271' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_271}}]]
+    2024-02-09 23:12:49.098557: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_272' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_272}}]]
+    2024-02-09 23:12:49.098590: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_273' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_273}}]]
+    2024-02-09 23:12:49.098624: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_274' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_274}}]]
+    2024-02-09 23:12:49.098658: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_275' with dtype float and shape [32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_275}}]]
+    2024-02-09 23:12:49.098702: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_276' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_276}}]]
+    2024-02-09 23:12:49.098736: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_277' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_277}}]]
+    2024-02-09 23:12:49.098769: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_280' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_280}}]]
+    2024-02-09 23:12:49.098801: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_281' with dtype float and shape [32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_281}}]]
+    2024-02-09 23:12:49.098833: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_282' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_282}}]]
+    2024-02-09 23:12:49.098866: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_283' with dtype float
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_283}}]]
+    2024-02-09 23:12:49.098899: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_284' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_284}}]]
+    2024-02-09 23:12:49.098933: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_285' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_285}}]]
+    2024-02-09 23:12:49.098964: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_286' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_286}}]]
+    2024-02-09 23:12:49.098996: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_287' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_287}}]]
+    2024-02-09 23:12:49.099029: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_289' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_289}}]]
+    2024-02-09 23:12:49.099061: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_290' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_290}}]]
+    2024-02-09 23:12:49.099093: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_293' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_293}}]]
+    2024-02-09 23:12:49.099125: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_294' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_294}}]]
+    2024-02-09 23:12:49.099157: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_295' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_295}}]]
+    2024-02-09 23:12:49.099189: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_296' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_296}}]]
+    2024-02-09 23:12:49.099222: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_297' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_297}}]]
+    2024-02-09 23:12:49.099255: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_298' with dtype float and shape [32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_298}}]]
+    2024-02-09 23:12:49.099288: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_299' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_299}}]]
+    2024-02-09 23:12:49.099320: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_302' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_302}}]]
+    2024-02-09 23:12:49.099351: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_303' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_303}}]]
+    2024-02-09 23:12:49.099384: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_304' with dtype float and shape [32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_304}}]]
+    2024-02-09 23:12:49.099416: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_305' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_305}}]]
+    2024-02-09 23:12:49.099448: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_306' with dtype float
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_306}}]]
+    2024-02-09 23:12:49.099481: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_307' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_307}}]]
+    2024-02-09 23:12:49.099514: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_308' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_308}}]]
+    2024-02-09 23:12:49.099546: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_309' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_309}}]]
+    2024-02-09 23:12:49.099577: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_310' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_310}}]]
+    2024-02-09 23:12:49.099610: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_314' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_314}}]]
+    2024-02-09 23:12:49.099644: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_315' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_315}}]]
+    2024-02-09 23:12:49.099676: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_316' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_316}}]]
+    2024-02-09 23:12:49.099708: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_317' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_317}}]]
+    2024-02-09 23:12:49.099741: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_318' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_318}}]]
+    2024-02-09 23:12:49.099773: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_319' with dtype float and shape [32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_319}}]]
+    2024-02-09 23:12:49.099805: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_320' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_320}}]]
+    2024-02-09 23:12:49.099837: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_321' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_321}}]]
+    2024-02-09 23:12:49.099869: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_324' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_324}}]]
+    2024-02-09 23:12:49.099901: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_325' with dtype float and shape [32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_325}}]]
+    2024-02-09 23:12:49.099934: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_326' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_326}}]]
+    2024-02-09 23:12:49.099966: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_327' with dtype float
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_327}}]]
+    2024-02-09 23:12:49.099999: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_328' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_328}}]]
+    2024-02-09 23:12:49.100032: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_329' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_329}}]]
+    2024-02-09 23:12:49.100064: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_330' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_330}}]]
+    2024-02-09 23:12:49.100098: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_331' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_331}}]]
+    2024-02-09 23:12:49.100130: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_332' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_332}}]]
+    2024-02-09 23:12:49.100163: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_334' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_334}}]]
+    2024-02-09 23:12:49.100195: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_340' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_340}}]]
+    2024-02-09 23:12:49.100228: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_341' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_341}}]]
+    2024-02-09 23:12:49.100261: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_342' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_342}}]]
+    2024-02-09 23:12:49.100293: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_343' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_343}}]]
+    2024-02-09 23:12:49.100326: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_344' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_344}}]]
+    2024-02-09 23:12:49.100358: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_345' with dtype float and shape [32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_345}}]]
+    2024-02-09 23:12:49.100391: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_346' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_346}}]]
+    2024-02-09 23:12:49.100424: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_347' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_347}}]]
+    2024-02-09 23:12:49.100457: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_352' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_352}}]]
+    2024-02-09 23:12:49.100490: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_353' with dtype float and shape [32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_353}}]]
+    2024-02-09 23:12:49.100522: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_354' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_354}}]]
+    2024-02-09 23:12:49.100554: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_355' with dtype float
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_355}}]]
+    2024-02-09 23:12:49.100587: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_356' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_356}}]]
+    2024-02-09 23:12:49.100620: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_357' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_357}}]]
+    2024-02-09 23:12:49.100652: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_358' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_358}}]]
+    2024-02-09 23:12:49.100685: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_359' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_359}}]]
+    2024-02-09 23:12:49.100717: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_361' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_361}}]]
+    2024-02-09 23:12:49.100750: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_362' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_362}}]]
+    2024-02-09 23:12:49.100782: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_365' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_365}}]]
+    2024-02-09 23:12:49.100815: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_366' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_366}}]]
+    2024-02-09 23:12:49.100847: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_367' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_367}}]]
+    2024-02-09 23:12:49.100880: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_368' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_368}}]]
+    2024-02-09 23:12:49.100912: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_369' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_369}}]]
+    2024-02-09 23:12:49.100944: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_370' with dtype float and shape [32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_370}}]]
+    2024-02-09 23:12:49.100977: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_371' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_371}}]]
+    2024-02-09 23:12:49.101011: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_374' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_374}}]]
+    2024-02-09 23:12:49.101044: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_375' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_375}}]]
+    2024-02-09 23:12:49.101076: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_376' with dtype float and shape [32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_376}}]]
+    2024-02-09 23:12:49.101108: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_377' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_377}}]]
+    2024-02-09 23:12:49.101141: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_378' with dtype float
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_378}}]]
+    2024-02-09 23:12:49.101174: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_379' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_379}}]]
+    2024-02-09 23:12:49.101206: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_380' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_380}}]]
+    2024-02-09 23:12:49.101240: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_381' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_381}}]]
+    2024-02-09 23:12:49.101272: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_385' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_385}}]]
+    2024-02-09 23:12:49.101305: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_386' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_386}}]]
+    2024-02-09 23:12:49.101337: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_387' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_387}}]]
+    2024-02-09 23:12:49.101369: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_388' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_388}}]]
+    2024-02-09 23:12:49.101402: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_389' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_389}}]]
+    2024-02-09 23:12:49.101439: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_390' with dtype float and shape [32,16]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_390}}]]
+    2024-02-09 23:12:49.101489: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_391' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_391}}]]
+    2024-02-09 23:12:49.101523: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_392' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_392}}]]
+    2024-02-09 23:12:49.101556: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_395' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_395}}]]
+    2024-02-09 23:12:49.101590: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_396' with dtype float and shape [32,16]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_396}}]]
+    2024-02-09 23:12:49.101624: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_397' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_397}}]]
+    2024-02-09 23:12:49.101658: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_398' with dtype float
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_398}}]]
+    2024-02-09 23:12:49.101693: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_399' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_399}}]]
+    2024-02-09 23:12:49.101726: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_400' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_400}}]]
+    2024-02-09 23:12:49.101760: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_401' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/block3/StatefulPartitionedCall_grad/block3/StatefulPartitionedCall_401}}]]
+
+
+.. parsed-literal::
+
+    2024-02-09 23:12:50.091563: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall}}]]
+    2024-02-09 23:12:50.091636: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_1' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_1}}]]
+    2024-02-09 23:12:50.091671: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_2' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_2}}]]
+    2024-02-09 23:12:50.091705: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_6' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_6}}]]
+    2024-02-09 23:12:50.091737: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_7' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_7}}]]
+    2024-02-09 23:12:50.091768: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_8' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_8}}]]
+    2024-02-09 23:12:50.091800: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_9' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_9}}]]
+    2024-02-09 23:12:50.091831: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_10' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_10}}]]
+    2024-02-09 23:12:50.091862: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_11' with dtype float and shape [32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_11}}]]
+    2024-02-09 23:12:50.091893: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_12' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_12}}]]
+    2024-02-09 23:12:50.091923: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_13' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_13}}]]
+    2024-02-09 23:12:50.091955: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_16' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_16}}]]
+    2024-02-09 23:12:50.091986: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_17' with dtype float and shape [32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_17}}]]
+    2024-02-09 23:12:50.092016: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_18' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_18}}]]
+    2024-02-09 23:12:50.092047: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_19' with dtype float
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_19}}]]
+    2024-02-09 23:12:50.092078: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_20' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_20}}]]
+    2024-02-09 23:12:50.092108: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_21' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_21}}]]
+    2024-02-09 23:12:50.092138: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_22' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_22}}]]
+    2024-02-09 23:12:50.092168: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_23' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_23}}]]
+    2024-02-09 23:12:50.092199: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_25' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_25}}]]
+    2024-02-09 23:12:50.092229: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_26' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_26}}]]
+    2024-02-09 23:12:50.092259: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_29' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_29}}]]
+    2024-02-09 23:12:50.092289: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_30' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_30}}]]
+    2024-02-09 23:12:50.092319: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_31' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_31}}]]
+    2024-02-09 23:12:50.092350: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_32' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_32}}]]
+    2024-02-09 23:12:50.092379: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_33' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_33}}]]
+    2024-02-09 23:12:50.092413: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_34' with dtype float and shape [32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_34}}]]
+    2024-02-09 23:12:50.092445: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_35' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_35}}]]
+    2024-02-09 23:12:50.092478: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_38' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_38}}]]
+    2024-02-09 23:12:50.092510: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_39' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_39}}]]
+    2024-02-09 23:12:50.092542: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_40' with dtype float and shape [32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_40}}]]
+    2024-02-09 23:12:50.092575: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_41' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_41}}]]
+    2024-02-09 23:12:50.092607: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_42' with dtype float
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_42}}]]
+    2024-02-09 23:12:50.092640: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_43' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_43}}]]
+    2024-02-09 23:12:50.092671: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_44' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_44}}]]
+    2024-02-09 23:12:50.092704: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_45' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_45}}]]
+    2024-02-09 23:12:50.092736: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_46' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_46}}]]
+    2024-02-09 23:12:50.092768: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_50' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_50}}]]
+    2024-02-09 23:12:50.092800: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_51' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_51}}]]
+    2024-02-09 23:12:50.092832: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_52' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_52}}]]
+    2024-02-09 23:12:50.092864: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_53' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_53}}]]
+    2024-02-09 23:12:50.092897: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_54' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_54}}]]
+    2024-02-09 23:12:50.092929: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_55' with dtype float and shape [32,16]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_55}}]]
+    2024-02-09 23:12:50.092961: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_56' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_56}}]]
+    2024-02-09 23:12:50.092993: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_57' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_57}}]]
+    2024-02-09 23:12:50.093024: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_60' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_60}}]]
+    2024-02-09 23:12:50.093056: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_61' with dtype float and shape [32,16]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_61}}]]
+    2024-02-09 23:12:50.093088: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_62' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_62}}]]
+    2024-02-09 23:12:50.093120: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_63' with dtype float
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_63}}]]
+    2024-02-09 23:12:50.093152: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_64' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_64}}]]
+    2024-02-09 23:12:50.093184: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_65' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_65}}]]
+    2024-02-09 23:12:50.093215: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_66' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_66}}]]
+    2024-02-09 23:12:50.093247: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_67' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_67}}]]
+    2024-02-09 23:12:50.093279: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_68' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_68}}]]
+    2024-02-09 23:12:50.093311: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_72' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_72}}]]
+    2024-02-09 23:12:50.093343: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_73' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_73}}]]
+    2024-02-09 23:12:50.093375: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_74' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_74}}]]
+    2024-02-09 23:12:50.093407: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_75' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_75}}]]
+    2024-02-09 23:12:50.093444: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_76' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_76}}]]
+    2024-02-09 23:12:50.093478: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_77' with dtype float and shape [32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_77}}]]
+    2024-02-09 23:12:50.093509: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_78' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_78}}]]
+    2024-02-09 23:12:50.093541: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_79' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_79}}]]
+    2024-02-09 23:12:50.093573: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_82' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_82}}]]
+    2024-02-09 23:12:50.093605: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_83' with dtype float and shape [32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_83}}]]
+    2024-02-09 23:12:50.093637: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_84' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_84}}]]
+    2024-02-09 23:12:50.093669: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_85' with dtype float
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_85}}]]
+    2024-02-09 23:12:50.093702: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_86' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_86}}]]
+    2024-02-09 23:12:50.093734: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_87' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_87}}]]
+    2024-02-09 23:12:50.093766: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_88' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_88}}]]
+    2024-02-09 23:12:50.093798: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_89' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_89}}]]
+    2024-02-09 23:12:50.093830: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_91' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_91}}]]
+    2024-02-09 23:12:50.093862: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_92' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_92}}]]
+    2024-02-09 23:12:50.093894: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_95' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_95}}]]
+    2024-02-09 23:12:50.093926: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_96' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_96}}]]
+    2024-02-09 23:12:50.093958: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_97' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_97}}]]
+    2024-02-09 23:12:50.093990: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_98' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_98}}]]
+    2024-02-09 23:12:50.094022: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_99' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_99}}]]
+    2024-02-09 23:12:50.094053: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_100' with dtype float and shape [32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_100}}]]
+    2024-02-09 23:12:50.094085: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_101' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_101}}]]
+    2024-02-09 23:12:50.094117: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_104' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_104}}]]
+    2024-02-09 23:12:50.094149: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_105' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_105}}]]
+    2024-02-09 23:12:50.094181: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_106' with dtype float and shape [32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_106}}]]
+    2024-02-09 23:12:50.094213: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_107' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_107}}]]
+    2024-02-09 23:12:50.094245: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_108' with dtype float
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_108}}]]
+    2024-02-09 23:12:50.094277: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_109' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_109}}]]
+    2024-02-09 23:12:50.094309: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_110' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_110}}]]
+    2024-02-09 23:12:50.094341: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_111' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_111}}]]
+    2024-02-09 23:12:50.094373: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_112' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_112}}]]
+    2024-02-09 23:12:50.094406: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_116' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_116}}]]
+    2024-02-09 23:12:50.094437: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_117' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_117}}]]
+    2024-02-09 23:12:50.094469: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_118' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_118}}]]
+    2024-02-09 23:12:50.094501: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_119' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_119}}]]
+    2024-02-09 23:12:50.094533: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_120' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_120}}]]
+    2024-02-09 23:12:50.094564: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_121' with dtype float and shape [32,16]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_121}}]]
+    2024-02-09 23:12:50.094596: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_122' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_122}}]]
+    2024-02-09 23:12:50.094628: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_123' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_123}}]]
+    2024-02-09 23:12:50.094659: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_126' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_126}}]]
+    2024-02-09 23:12:50.094691: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_127' with dtype float and shape [32,16]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_127}}]]
+    2024-02-09 23:12:50.094723: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_128' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_128}}]]
+    2024-02-09 23:12:50.094755: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_129' with dtype float
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_129}}]]
+    2024-02-09 23:12:50.094787: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_130' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_130}}]]
+    2024-02-09 23:12:50.094819: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_131' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_131}}]]
+    2024-02-09 23:12:50.094851: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_132' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_132}}]]
+    2024-02-09 23:12:50.094883: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_133' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_133}}]]
+    2024-02-09 23:12:50.094915: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_134' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_134}}]]
+    2024-02-09 23:12:50.094947: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_138' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_138}}]]
+    2024-02-09 23:12:50.094978: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_139' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_139}}]]
+    2024-02-09 23:12:50.095010: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_140' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_140}}]]
+    2024-02-09 23:12:50.095042: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_141' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_141}}]]
+    2024-02-09 23:12:50.095074: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_142' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_142}}]]
+    2024-02-09 23:12:50.095106: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_143' with dtype float and shape [32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_143}}]]
+    2024-02-09 23:12:50.095138: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_144' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_144}}]]
+    2024-02-09 23:12:50.095169: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_145' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_145}}]]
+    2024-02-09 23:12:50.095201: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_148' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_148}}]]
+    2024-02-09 23:12:50.095233: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_149' with dtype float and shape [32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_149}}]]
+    2024-02-09 23:12:50.095264: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_150' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_150}}]]
+    2024-02-09 23:12:50.095295: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_151' with dtype float
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_151}}]]
+    2024-02-09 23:12:50.095327: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_152' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_152}}]]
+    2024-02-09 23:12:50.095359: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_153' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_153}}]]
+    2024-02-09 23:12:50.095391: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_154' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_154}}]]
+    2024-02-09 23:12:50.095423: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_155' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_155}}]]
+    2024-02-09 23:12:50.095454: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_157' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_157}}]]
+    2024-02-09 23:12:50.095486: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_158' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_158}}]]
+    2024-02-09 23:12:50.095518: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_161' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_161}}]]
+    2024-02-09 23:12:50.095550: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_162' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_162}}]]
+    2024-02-09 23:12:50.095582: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_163' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_163}}]]
+    2024-02-09 23:12:50.095614: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_164' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_164}}]]
+    2024-02-09 23:12:50.095645: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_165' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_165}}]]
+    2024-02-09 23:12:50.095677: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_166' with dtype float and shape [32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_166}}]]
+    2024-02-09 23:12:50.095709: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_167' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_167}}]]
+    2024-02-09 23:12:50.095741: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_170' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_170}}]]
+    2024-02-09 23:12:50.095773: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_171' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_171}}]]
+    2024-02-09 23:12:50.095805: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_172' with dtype float and shape [32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_172}}]]
+    2024-02-09 23:12:50.095836: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_173' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_173}}]]
+    2024-02-09 23:12:50.095868: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_174' with dtype float
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_174}}]]
+    2024-02-09 23:12:50.095899: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_175' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_175}}]]
+    2024-02-09 23:12:50.095931: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_176' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_176}}]]
+    2024-02-09 23:12:50.095963: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_177' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_177}}]]
+    2024-02-09 23:12:50.095995: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_178' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_178}}]]
+    2024-02-09 23:12:50.096027: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_182' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_182}}]]
+    2024-02-09 23:12:50.096059: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_183' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_183}}]]
+    2024-02-09 23:12:50.096090: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_184' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_184}}]]
+    2024-02-09 23:12:50.096122: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_185' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_185}}]]
+    2024-02-09 23:12:50.096154: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_186' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_186}}]]
+    2024-02-09 23:12:50.096186: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_187' with dtype float and shape [32,16]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_187}}]]
+    2024-02-09 23:12:50.096217: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_188' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_188}}]]
+    2024-02-09 23:12:50.096249: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_189' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_189}}]]
+    2024-02-09 23:12:50.096280: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_192' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_192}}]]
+    2024-02-09 23:12:50.096312: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_193' with dtype float and shape [32,16]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_193}}]]
+    2024-02-09 23:12:50.096343: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_194' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_194}}]]
+    2024-02-09 23:12:50.096374: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_195' with dtype float
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_195}}]]
+    2024-02-09 23:12:50.096406: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_196' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_196}}]]
+    2024-02-09 23:12:50.096438: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_197' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_197}}]]
+    2024-02-09 23:12:50.096469: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_198' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_198}}]]
+    2024-02-09 23:12:50.096501: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_199' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_199}}]]
+    2024-02-09 23:12:50.096532: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_200' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_200}}]]
+    2024-02-09 23:12:50.096564: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_202' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_202}}]]
+    2024-02-09 23:12:50.096596: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_208' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_208}}]]
+    2024-02-09 23:12:50.096628: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_209' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_209}}]]
+    2024-02-09 23:12:50.096660: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_210' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_210}}]]
+    2024-02-09 23:12:50.096692: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_211' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_211}}]]
+    2024-02-09 23:12:50.096724: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_212' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_212}}]]
+    2024-02-09 23:12:50.096756: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_213' with dtype float and shape [32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_213}}]]
+    2024-02-09 23:12:50.096788: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_214' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_214}}]]
+    2024-02-09 23:12:50.096820: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_215' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_215}}]]
+    2024-02-09 23:12:50.096851: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_220' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_220}}]]
+    2024-02-09 23:12:50.096883: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_221' with dtype float and shape [32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_221}}]]
+    2024-02-09 23:12:50.096915: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_222' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_222}}]]
+    2024-02-09 23:12:50.096947: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_223' with dtype float
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_223}}]]
+    2024-02-09 23:12:50.096979: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_224' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_224}}]]
+    2024-02-09 23:12:50.097012: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_225' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_225}}]]
+    2024-02-09 23:12:50.097044: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_226' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_226}}]]
+    2024-02-09 23:12:50.097076: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_227' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_227}}]]
+    2024-02-09 23:12:50.097108: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_229' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_229}}]]
+    2024-02-09 23:12:50.097140: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_230' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_230}}]]
+    2024-02-09 23:12:50.097172: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_233' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_233}}]]
+    2024-02-09 23:12:50.097204: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_234' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_234}}]]
+    2024-02-09 23:12:50.097236: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_235' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_235}}]]
+    2024-02-09 23:12:50.097268: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_236' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_236}}]]
+    2024-02-09 23:12:50.097299: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_237' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_237}}]]
+    2024-02-09 23:12:50.097332: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_238' with dtype float and shape [32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_238}}]]
+    2024-02-09 23:12:50.097364: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_239' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_239}}]]
+    2024-02-09 23:12:50.097396: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_242' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_242}}]]
+    2024-02-09 23:12:50.097428: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_243' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_243}}]]
+    2024-02-09 23:12:50.097482: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_244' with dtype float and shape [32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_244}}]]
+    2024-02-09 23:12:50.097515: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_245' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_245}}]]
+    2024-02-09 23:12:50.097549: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_246' with dtype float
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_246}}]]
+    2024-02-09 23:12:50.097582: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_247' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_247}}]]
+    2024-02-09 23:12:50.097616: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_248' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_248}}]]
+    2024-02-09 23:12:50.097650: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_249' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_249}}]]
+    2024-02-09 23:12:50.097683: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_253' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_253}}]]
+    2024-02-09 23:12:50.097717: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_254' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_254}}]]
+    2024-02-09 23:12:50.097750: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_255' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_255}}]]
+    2024-02-09 23:12:50.097784: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_256' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_256}}]]
+    2024-02-09 23:12:50.097818: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_257' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_257}}]]
+    2024-02-09 23:12:50.097851: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_258' with dtype float and shape [32,8]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_258}}]]
+    2024-02-09 23:12:50.097885: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_259' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_259}}]]
+    2024-02-09 23:12:50.097919: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_260' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_260}}]]
+    2024-02-09 23:12:50.097953: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_263' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_263}}]]
+    2024-02-09 23:12:50.097986: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_264' with dtype float and shape [32,8]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_264}}]]
+    2024-02-09 23:12:50.098020: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_265' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_265}}]]
+    2024-02-09 23:12:50.098053: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_266' with dtype float
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_266}}]]
+    2024-02-09 23:12:50.098087: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_267' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_267}}]]
+    2024-02-09 23:12:50.098120: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_268' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_268}}]]
+    2024-02-09 23:12:50.098154: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_269' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/block2/StatefulPartitionedCall_grad/block2/StatefulPartitionedCall_269}}]]
+
+
+.. parsed-literal::
+
+    2024-02-09 23:12:50.847316: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall}}]]
+    2024-02-09 23:12:50.847388: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_1' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_1}}]]
+    2024-02-09 23:12:50.847426: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_2' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_2}}]]
+    2024-02-09 23:12:50.847460: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_6' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_6}}]]
+    2024-02-09 23:12:50.847493: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_7' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_7}}]]
+    2024-02-09 23:12:50.847526: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_8' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_8}}]]
+    2024-02-09 23:12:50.847559: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_9' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_9}}]]
+    2024-02-09 23:12:50.847601: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_10' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_10}}]]
+    2024-02-09 23:12:50.847632: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_11' with dtype float and shape [32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_11}}]]
+    2024-02-09 23:12:50.847663: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_12' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_12}}]]
+    2024-02-09 23:12:50.847695: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_13' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_13}}]]
+    2024-02-09 23:12:50.847726: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_16' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_16}}]]
+    2024-02-09 23:12:50.847756: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_17' with dtype float and shape [32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_17}}]]
+    2024-02-09 23:12:50.847787: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_18' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_18}}]]
+    2024-02-09 23:12:50.847817: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_19' with dtype float
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_19}}]]
+    2024-02-09 23:12:50.847848: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_20' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_20}}]]
+    2024-02-09 23:12:50.847878: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_21' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_21}}]]
+    2024-02-09 23:12:50.847908: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_22' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_22}}]]
+    2024-02-09 23:12:50.847947: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_23' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_23}}]]
+    2024-02-09 23:12:50.847977: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_25' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_25}}]]
+    2024-02-09 23:12:50.848007: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_26' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_26}}]]
+    2024-02-09 23:12:50.848038: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_29' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_29}}]]
+    2024-02-09 23:12:50.848068: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_30' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_30}}]]
+    2024-02-09 23:12:50.848098: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_31' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_31}}]]
+    2024-02-09 23:12:50.848128: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_32' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_32}}]]
+    2024-02-09 23:12:50.848162: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_33' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_33}}]]
+    2024-02-09 23:12:50.848194: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_34' with dtype float and shape [32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_34}}]]
+    2024-02-09 23:12:50.848234: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_35' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_35}}]]
+    2024-02-09 23:12:50.848292: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_38' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_38}}]]
+    2024-02-09 23:12:50.848330: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_39' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_39}}]]
+    2024-02-09 23:12:50.848365: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_40' with dtype float and shape [32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_40}}]]
+    2024-02-09 23:12:50.848401: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_41' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_41}}]]
+    2024-02-09 23:12:50.848435: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_42' with dtype float
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_42}}]]
+    2024-02-09 23:12:50.848469: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_43' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_43}}]]
+    2024-02-09 23:12:50.848503: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_44' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_44}}]]
+    2024-02-09 23:12:50.848537: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_45' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_45}}]]
+    2024-02-09 23:12:50.848570: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_46' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_46}}]]
+    2024-02-09 23:12:50.848608: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_50' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_50}}]]
+    2024-02-09 23:12:50.848645: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_51' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_51}}]]
+    2024-02-09 23:12:50.848678: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_52' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_52}}]]
+    2024-02-09 23:12:50.848712: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_53' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_53}}]]
+    2024-02-09 23:12:50.848746: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_54' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_54}}]]
+    2024-02-09 23:12:50.848779: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_55' with dtype float and shape [32,8]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_55}}]]
+    2024-02-09 23:12:50.848814: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_56' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_56}}]]
+    2024-02-09 23:12:50.848848: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_57' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_57}}]]
+    2024-02-09 23:12:50.848881: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_60' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_60}}]]
+    2024-02-09 23:12:50.848915: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_61' with dtype float and shape [32,8]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_61}}]]
+    2024-02-09 23:12:50.848950: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_62' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_62}}]]
+    2024-02-09 23:12:50.848982: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_63' with dtype float
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_63}}]]
+    2024-02-09 23:12:50.849017: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_64' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_64}}]]
+    2024-02-09 23:12:50.849050: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_65' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_65}}]]
+    2024-02-09 23:12:50.849083: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_66' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_66}}]]
+    2024-02-09 23:12:50.849117: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_67' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_67}}]]
+    2024-02-09 23:12:50.849151: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_68' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_68}}]]
+    2024-02-09 23:12:50.849184: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_72' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_72}}]]
+    2024-02-09 23:12:50.849218: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_73' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_73}}]]
+    2024-02-09 23:12:50.849252: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_74' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_74}}]]
+    2024-02-09 23:12:50.849286: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_75' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_75}}]]
+    2024-02-09 23:12:50.849319: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_76' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_76}}]]
+    2024-02-09 23:12:50.849353: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_77' with dtype float and shape [32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_77}}]]
+    2024-02-09 23:12:50.849387: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_78' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_78}}]]
+    2024-02-09 23:12:50.849420: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_79' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_79}}]]
+    2024-02-09 23:12:50.849460: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_82' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_82}}]]
+    2024-02-09 23:12:50.849511: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_83' with dtype float and shape [32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_83}}]]
+    2024-02-09 23:12:50.849544: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_84' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_84}}]]
+    2024-02-09 23:12:50.849579: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_85' with dtype float
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_85}}]]
+    2024-02-09 23:12:50.849614: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_86' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_86}}]]
+    2024-02-09 23:12:50.849648: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_87' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_87}}]]
+    2024-02-09 23:12:50.849682: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_88' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_88}}]]
+    2024-02-09 23:12:50.849717: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_89' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_89}}]]
+    2024-02-09 23:12:50.849757: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_91' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_91}}]]
+    2024-02-09 23:12:50.849797: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_92' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_92}}]]
+    2024-02-09 23:12:50.849833: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_95' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_95}}]]
+    2024-02-09 23:12:50.849869: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_96' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_96}}]]
+    2024-02-09 23:12:50.849903: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_97' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_97}}]]
+    2024-02-09 23:12:50.849937: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_98' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_98}}]]
+    2024-02-09 23:12:50.849971: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_99' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_99}}]]
+    2024-02-09 23:12:50.850006: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_100' with dtype float and shape [32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_100}}]]
+    2024-02-09 23:12:50.850040: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_101' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_101}}]]
+    2024-02-09 23:12:50.850074: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_104' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_104}}]]
+    2024-02-09 23:12:50.850108: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_105' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_105}}]]
+    2024-02-09 23:12:50.850150: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_106' with dtype float and shape [32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_106}}]]
+    2024-02-09 23:12:50.850186: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_107' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_107}}]]
+    2024-02-09 23:12:50.850221: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_108' with dtype float
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_108}}]]
+    2024-02-09 23:12:50.850255: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_109' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_109}}]]
+    2024-02-09 23:12:50.850289: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_110' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_110}}]]
+    2024-02-09 23:12:50.850323: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_111' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_111}}]]
+    2024-02-09 23:12:50.850357: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_112' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_112}}]]
+    2024-02-09 23:12:50.850390: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_116' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_116}}]]
+    2024-02-09 23:12:50.850424: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_117' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_117}}]]
+    2024-02-09 23:12:50.850458: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_118' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_118}}]]
+    2024-02-09 23:12:50.850493: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_119' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_119}}]]
+    2024-02-09 23:12:50.850527: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_120' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_120}}]]
+    2024-02-09 23:12:50.850561: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_121' with dtype float and shape [32,8]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_121}}]]
+    2024-02-09 23:12:50.850595: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_122' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_122}}]]
+    2024-02-09 23:12:50.850629: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_123' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_123}}]]
+    2024-02-09 23:12:50.850663: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_126' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_126}}]]
+    2024-02-09 23:12:50.850697: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_127' with dtype float and shape [32,8]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_127}}]]
+    2024-02-09 23:12:50.850732: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_128' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_128}}]]
+    2024-02-09 23:12:50.850783: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_129' with dtype float
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_129}}]]
+    2024-02-09 23:12:50.850828: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_130' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_130}}]]
+    2024-02-09 23:12:50.850861: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_131' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_131}}]]
+    2024-02-09 23:12:50.850893: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_132' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_132}}]]
+    2024-02-09 23:12:50.850926: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_133' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_133}}]]
+    2024-02-09 23:12:50.850957: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_134' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_134}}]]
+    2024-02-09 23:12:50.850989: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_136' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_136}}]]
+    2024-02-09 23:12:50.851021: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_142' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_142}}]]
+    2024-02-09 23:12:50.851053: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_143' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_143}}]]
+    2024-02-09 23:12:50.851085: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_144' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_144}}]]
+    2024-02-09 23:12:50.851117: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_145' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_145}}]]
+    2024-02-09 23:12:50.851149: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_146' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_146}}]]
+    2024-02-09 23:12:50.851180: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_147' with dtype float and shape [32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_147}}]]
+    2024-02-09 23:12:50.851212: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_148' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_148}}]]
+    2024-02-09 23:12:50.851243: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_149' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_149}}]]
+    2024-02-09 23:12:50.851276: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_154' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_154}}]]
+    2024-02-09 23:12:50.851308: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_155' with dtype float and shape [32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_155}}]]
+    2024-02-09 23:12:50.851340: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_156' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_156}}]]
+    2024-02-09 23:12:50.851371: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_157' with dtype float
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_157}}]]
+    2024-02-09 23:12:50.851403: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_158' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_158}}]]
+    2024-02-09 23:12:50.851435: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_159' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_159}}]]
+    2024-02-09 23:12:50.851467: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_160' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_160}}]]
+    2024-02-09 23:12:50.851499: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_161' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_161}}]]
+    2024-02-09 23:12:50.851531: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_163' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_163}}]]
+    2024-02-09 23:12:50.851563: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_164' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_164}}]]
+    2024-02-09 23:12:50.851595: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_167' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_167}}]]
+    2024-02-09 23:12:50.851628: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_168' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_168}}]]
+    2024-02-09 23:12:50.851659: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_169' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_169}}]]
+    2024-02-09 23:12:50.851691: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_170' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_170}}]]
+    2024-02-09 23:12:50.851723: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_171' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_171}}]]
+    2024-02-09 23:12:50.851755: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_172' with dtype float and shape [32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_172}}]]
+    2024-02-09 23:12:50.851787: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_173' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_173}}]]
+    2024-02-09 23:12:50.851819: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_176' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_176}}]]
+    2024-02-09 23:12:50.851851: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_177' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_177}}]]
+    2024-02-09 23:12:50.851883: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_178' with dtype float and shape [32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_178}}]]
+    2024-02-09 23:12:50.851915: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_179' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_179}}]]
+    2024-02-09 23:12:50.851947: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_180' with dtype float
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_180}}]]
+    2024-02-09 23:12:50.851979: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_181' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_181}}]]
+    2024-02-09 23:12:50.852011: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_182' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_182}}]]
+    2024-02-09 23:12:50.852043: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_183' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_183}}]]
+    2024-02-09 23:12:50.852075: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_187' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_187}}]]
+    2024-02-09 23:12:50.852107: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_188' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_188}}]]
+    2024-02-09 23:12:50.852140: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_189' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_189}}]]
+    2024-02-09 23:12:50.852172: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_190' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_190}}]]
+    2024-02-09 23:12:50.852204: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_191' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_191}}]]
+    2024-02-09 23:12:50.852236: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_192' with dtype float and shape [32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_192}}]]
+    2024-02-09 23:12:50.852268: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_193' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_193}}]]
+    2024-02-09 23:12:50.852300: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_194' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_194}}]]
+    2024-02-09 23:12:50.852332: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_197' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_197}}]]
+    2024-02-09 23:12:50.852364: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_198' with dtype float and shape [32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_198}}]]
+    2024-02-09 23:12:50.852396: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_199' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_199}}]]
+    2024-02-09 23:12:50.852428: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_200' with dtype float
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_200}}]]
+    2024-02-09 23:12:50.852460: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_201' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_201}}]]
+    2024-02-09 23:12:50.852492: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_202' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_202}}]]
+    2024-02-09 23:12:50.852525: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_203' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/block1/StatefulPartitionedCall_grad/block1/StatefulPartitionedCall_203}}]]
+    2024-02-09 23:12:50.897333: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/root_block/StatefulPartitionedCall_grad/root_block/StatefulPartitionedCall_2' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/root_block/StatefulPartitionedCall_grad/root_block/StatefulPartitionedCall_2}}]]
+    2024-02-09 23:12:50.897390: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/root_block/StatefulPartitionedCall_grad/root_block/StatefulPartitionedCall_3' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/root_block/StatefulPartitionedCall_grad/root_block/StatefulPartitionedCall_3}}]]
+    2024-02-09 23:12:50.897426: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/root_block/StatefulPartitionedCall_grad/root_block/StatefulPartitionedCall_4' with dtype float and shape [?,?,?,3]
+    	 [[{{node gradients/root_block/StatefulPartitionedCall_grad/root_block/StatefulPartitionedCall_4}}]]
+    2024-02-09 23:12:50.897480: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/root_block/StatefulPartitionedCall_grad/root_block/StatefulPartitionedCall_6' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/root_block/StatefulPartitionedCall_grad/root_block/StatefulPartitionedCall_6}}]]
+    2024-02-09 23:12:50.897514: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/root_block/StatefulPartitionedCall_grad/root_block/StatefulPartitionedCall_7' with dtype float and shape [?,?,?,3]
+    	 [[{{node gradients/root_block/StatefulPartitionedCall_grad/root_block/StatefulPartitionedCall_7}}]]
+
+
+.. parsed-literal::
+
+    2024-02-09 23:12:51.373057: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall' with dtype float and shape [?,?,?,?]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall}}]]
+    2024-02-09 23:12:51.373139: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1' with dtype int32 and shape [2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1}}]]
+    2024-02-09 23:12:51.373179: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_4' with dtype float and shape [?,?,?,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_4}}]]
+    2024-02-09 23:12:51.373215: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_5' with dtype float and shape [?,?,?,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_5}}]]
+    2024-02-09 23:12:51.373254: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_6' with dtype float and shape [?,1,1,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_6}}]]
+    2024-02-09 23:12:51.373287: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_7' with dtype float and shape [?,?,?,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_7}}]]
+    2024-02-09 23:12:51.373321: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_8' with dtype float and shape [?,1,1,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_8}}]]
+    2024-02-09 23:12:51.373372: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_9' with dtype float and shape [32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_9}}]]
+    2024-02-09 23:12:51.373406: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_10' with dtype float and shape [?,1,1,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_10}}]]
+    2024-02-09 23:12:51.373445: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_11' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_11}}]]
+    2024-02-09 23:12:51.373480: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_12' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_12}}]]
+    2024-02-09 23:12:51.373516: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_13' with dtype float and shape [32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_13}}]]
+    2024-02-09 23:12:51.373550: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_14' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_14}}]]
+    2024-02-09 23:12:51.373584: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_15' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_15}}]]
+    2024-02-09 23:12:51.373618: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_16' with dtype float and shape [?,?,?,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_16}}]]
+    2024-02-09 23:12:51.373651: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_17' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_17}}]]
+    2024-02-09 23:12:51.373685: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_18' with dtype float and shape [?,?,?,2048]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_18}}]]
+    2024-02-09 23:12:51.373719: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_19' with dtype float and shape [?,?,?,2048]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_19}}]]
+    2024-02-09 23:12:51.373751: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_20' with dtype float and shape [?,?,?,2048]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_20}}]]
+    2024-02-09 23:12:51.373784: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_21' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_21}}]]
+    2024-02-09 23:12:51.373819: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_25' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_25}}]]
+    2024-02-09 23:12:51.373852: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_26' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_26}}]]
+    2024-02-09 23:12:51.373884: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_27' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_27}}]]
+    2024-02-09 23:12:51.373918: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_28' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_28}}]]
+    2024-02-09 23:12:51.373951: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_29' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_29}}]]
+    2024-02-09 23:12:51.373984: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_30' with dtype float and shape [32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_30}}]]
+    2024-02-09 23:12:51.374017: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_31' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_31}}]]
+    2024-02-09 23:12:51.374054: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_32' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_32}}]]
+    2024-02-09 23:12:51.374090: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_35' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_35}}]]
+    2024-02-09 23:12:51.374125: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_36' with dtype float and shape [32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_36}}]]
+    2024-02-09 23:12:51.374162: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_37' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_37}}]]
+    2024-02-09 23:12:51.374197: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_38' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_38}}]]
+    2024-02-09 23:12:51.374233: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_39' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_39}}]]
+    2024-02-09 23:12:51.374268: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_40' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_40}}]]
+    2024-02-09 23:12:51.374303: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_41' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_41}}]]
+    2024-02-09 23:12:51.374338: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_42' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_42}}]]
+    2024-02-09 23:12:51.374373: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_44' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_44}}]]
+    2024-02-09 23:12:51.374408: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_45' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_45}}]]
+    2024-02-09 23:12:51.374443: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_48' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_48}}]]
+    2024-02-09 23:12:51.374478: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_49' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_49}}]]
+    2024-02-09 23:12:51.374513: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_50' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_50}}]]
+    2024-02-09 23:12:51.374547: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_51' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_51}}]]
+    2024-02-09 23:12:51.374582: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_52' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_52}}]]
+    2024-02-09 23:12:51.374617: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_53' with dtype float and shape [32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_53}}]]
+    2024-02-09 23:12:51.374652: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_54' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_54}}]]
+    2024-02-09 23:12:51.374687: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_57' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_57}}]]
+    2024-02-09 23:12:51.374722: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_58' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_58}}]]
+    2024-02-09 23:12:51.374757: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_59' with dtype float and shape [32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_59}}]]
+    2024-02-09 23:12:51.374792: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_60' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_60}}]]
+    2024-02-09 23:12:51.374827: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_61' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_61}}]]
+    2024-02-09 23:12:51.374861: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_62' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_62}}]]
+    2024-02-09 23:12:51.374895: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_63' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_63}}]]
+    2024-02-09 23:12:51.374930: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_64' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_64}}]]
+    2024-02-09 23:12:51.374965: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_65' with dtype float and shape [?,?,?,2048]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_65}}]]
+    2024-02-09 23:12:51.375010: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_69' with dtype float and shape [?,?,?,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_69}}]]
+    2024-02-09 23:12:51.375043: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_70' with dtype float and shape [?,?,?,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_70}}]]
+    2024-02-09 23:12:51.375078: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_71' with dtype float and shape [?,1,1,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_71}}]]
+    2024-02-09 23:12:51.375111: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_72' with dtype float and shape [?,?,?,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_72}}]]
+    2024-02-09 23:12:51.375145: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_73' with dtype float and shape [?,1,1,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_73}}]]
+    2024-02-09 23:12:51.375179: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_74' with dtype float and shape [32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_74}}]]
+    2024-02-09 23:12:51.375212: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_75' with dtype float and shape [?,1,1,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_75}}]]
+    2024-02-09 23:12:51.375246: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_76' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_76}}]]
+    2024-02-09 23:12:51.375279: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_79' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_79}}]]
+    2024-02-09 23:12:51.375313: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_80' with dtype float and shape [32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_80}}]]
+    2024-02-09 23:12:51.375347: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_81' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_81}}]]
+    2024-02-09 23:12:51.375381: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_82' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_82}}]]
+    2024-02-09 23:12:51.375415: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_83' with dtype float and shape [?,?,?,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_83}}]]
+    2024-02-09 23:12:51.375450: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_84' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_84}}]]
+    2024-02-09 23:12:51.375483: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_85' with dtype float and shape [?,?,?,2048]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_85}}]]
+    2024-02-09 23:12:51.375517: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_86' with dtype float and shape [?,?,?,2048]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_86}}]]
+    2024-02-09 23:12:51.375550: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_87' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_87}}]]
+    2024-02-09 23:12:51.375583: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_91' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_91}}]]
+    2024-02-09 23:12:51.375617: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_92' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_92}}]]
+    2024-02-09 23:12:51.375650: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_93' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_93}}]]
+    2024-02-09 23:12:51.375682: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_94' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_94}}]]
+    2024-02-09 23:12:51.375715: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_95' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_95}}]]
+    2024-02-09 23:12:51.375749: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_96' with dtype float and shape [32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_96}}]]
+    2024-02-09 23:12:51.375782: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_97' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_97}}]]
+    2024-02-09 23:12:51.375816: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_98' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_98}}]]
+    2024-02-09 23:12:51.375849: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_101' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_101}}]]
+    2024-02-09 23:12:51.375883: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_102' with dtype float and shape [32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_102}}]]
+    2024-02-09 23:12:51.375917: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_103' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_103}}]]
+    2024-02-09 23:12:51.375950: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_104' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_104}}]]
+    2024-02-09 23:12:51.375985: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_105' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_105}}]]
+    2024-02-09 23:12:51.376019: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_106' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_106}}]]
+    2024-02-09 23:12:51.376052: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_107' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_107}}]]
+    2024-02-09 23:12:51.376085: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_108' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_108}}]]
+    2024-02-09 23:12:51.376119: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_110' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_110}}]]
+    2024-02-09 23:12:51.376152: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_111' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_111}}]]
+    2024-02-09 23:12:51.376186: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_114' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_114}}]]
+    2024-02-09 23:12:51.376220: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_115' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_115}}]]
+    2024-02-09 23:12:51.376253: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_116' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_116}}]]
+    2024-02-09 23:12:51.376287: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_117' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_117}}]]
+    2024-02-09 23:12:51.376321: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_118' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_118}}]]
+    2024-02-09 23:12:51.376354: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_119' with dtype float and shape [32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_119}}]]
+    2024-02-09 23:12:51.376387: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_120' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_120}}]]
+    2024-02-09 23:12:51.376421: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_123' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_123}}]]
+    2024-02-09 23:12:51.376454: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_124' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_124}}]]
+    2024-02-09 23:12:51.376487: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_125' with dtype float and shape [32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_125}}]]
+    2024-02-09 23:12:51.376520: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_126' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_126}}]]
+    2024-02-09 23:12:51.376554: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_127' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_127}}]]
+    2024-02-09 23:12:51.376605: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_128' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_128}}]]
+    2024-02-09 23:12:51.376640: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_129' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_129}}]]
+    2024-02-09 23:12:51.376675: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_130' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_130}}]]
+    2024-02-09 23:12:51.376710: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_131' with dtype float and shape [?,?,?,2048]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_131}}]]
+    2024-02-09 23:12:51.376745: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_135' with dtype float and shape [?,?,?,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_135}}]]
+    2024-02-09 23:12:51.376780: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_136' with dtype float and shape [?,?,?,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_136}}]]
+    2024-02-09 23:12:51.376814: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_137' with dtype float and shape [?,1,1,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_137}}]]
+    2024-02-09 23:12:51.376849: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_138' with dtype float and shape [?,?,?,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_138}}]]
+    2024-02-09 23:12:51.376884: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_139' with dtype float and shape [?,1,1,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_139}}]]
+    2024-02-09 23:12:51.376919: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_140' with dtype float and shape [32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_140}}]]
+    2024-02-09 23:12:51.376953: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_141' with dtype float and shape [?,1,1,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_141}}]]
+    2024-02-09 23:12:51.376988: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_142' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_142}}]]
+    2024-02-09 23:12:51.377023: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_145' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_145}}]]
+    2024-02-09 23:12:51.377058: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_146' with dtype float and shape [32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_146}}]]
+    2024-02-09 23:12:51.377093: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_147' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_147}}]]
+    2024-02-09 23:12:51.377128: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_148' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_148}}]]
+    2024-02-09 23:12:51.377162: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_149' with dtype float and shape [?,?,?,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_149}}]]
+    2024-02-09 23:12:51.377197: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_150' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_150}}]]
+    2024-02-09 23:12:51.377233: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_151' with dtype float and shape [?,?,?,2048]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_151}}]]
+    2024-02-09 23:12:51.377268: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_152' with dtype float and shape [?,?,?,2048]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_152}}]]
+    2024-02-09 23:12:51.377303: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_153' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_153}}]]
+    2024-02-09 23:12:51.377338: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_155' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_155}}]]
+    2024-02-09 23:12:51.377373: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_161' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_161}}]]
+    2024-02-09 23:12:51.377409: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_162' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_162}}]]
+    2024-02-09 23:12:51.377449: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_163' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_163}}]]
+    2024-02-09 23:12:51.377485: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_164' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_164}}]]
+    2024-02-09 23:12:51.377520: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_165' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_165}}]]
+    2024-02-09 23:12:51.377555: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_166' with dtype float and shape [32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_166}}]]
+    2024-02-09 23:12:51.377591: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_167' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_167}}]]
+    2024-02-09 23:12:51.377627: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_168' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_168}}]]
+    2024-02-09 23:12:51.377662: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_173' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_173}}]]
+    2024-02-09 23:12:51.377697: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_174' with dtype float and shape [32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_174}}]]
+    2024-02-09 23:12:51.377732: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_175' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_175}}]]
+    2024-02-09 23:12:51.377767: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_176' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_176}}]]
+    2024-02-09 23:12:51.377802: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_177' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_177}}]]
+    2024-02-09 23:12:51.377847: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_178' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_178}}]]
+    2024-02-09 23:12:51.377881: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_179' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_179}}]]
+    2024-02-09 23:12:51.377914: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_180' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_180}}]]
+    2024-02-09 23:12:51.377947: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_182' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_182}}]]
+    2024-02-09 23:12:51.377981: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_183' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_183}}]]
+    2024-02-09 23:12:51.378015: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_186' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_186}}]]
+    2024-02-09 23:12:51.378048: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_187' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_187}}]]
+    2024-02-09 23:12:51.378082: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_188' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_188}}]]
+    2024-02-09 23:12:51.378116: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_189' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_189}}]]
+    2024-02-09 23:12:51.378149: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_190' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_190}}]]
+    2024-02-09 23:12:51.378182: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_191' with dtype float and shape [32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_191}}]]
+    2024-02-09 23:12:51.378216: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_192' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_192}}]]
+    2024-02-09 23:12:51.378250: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_195' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_195}}]]
+    2024-02-09 23:12:51.378283: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_196' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_196}}]]
+    2024-02-09 23:12:51.378317: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_197' with dtype float and shape [32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_197}}]]
+    2024-02-09 23:12:51.378351: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_198' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_198}}]]
+    2024-02-09 23:12:51.378385: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_199' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_199}}]]
+    2024-02-09 23:12:51.378418: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_200' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_200}}]]
+    2024-02-09 23:12:51.378452: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_201' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_201}}]]
+    2024-02-09 23:12:51.378485: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_202' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_202}}]]
+    2024-02-09 23:12:51.378518: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_206' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_206}}]]
+    2024-02-09 23:12:51.378552: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_207' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_207}}]]
+    2024-02-09 23:12:51.378585: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_208' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_208}}]]
+    2024-02-09 23:12:51.378619: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_209' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_209}}]]
+    2024-02-09 23:12:51.378653: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_210' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_210}}]]
+    2024-02-09 23:12:51.378686: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_211' with dtype float and shape [32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_211}}]]
+    2024-02-09 23:12:51.378719: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_212' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_212}}]]
+    2024-02-09 23:12:51.378753: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_213' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_213}}]]
+    2024-02-09 23:12:51.378787: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_216' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_216}}]]
+    2024-02-09 23:12:51.378820: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_217' with dtype float and shape [32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_217}}]]
+    2024-02-09 23:12:51.378853: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_218' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_218}}]]
+    2024-02-09 23:12:51.378886: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_219' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_219}}]]
+    2024-02-09 23:12:51.378920: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_220' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_220}}]]
+    2024-02-09 23:12:51.378953: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_221' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_221}}]]
+    2024-02-09 23:12:51.378988: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_222' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_222}}]]
+    2024-02-09 23:12:51.379021: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_223' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_223}}]]
+    2024-02-09 23:12:51.379055: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_224' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_224}}]]
+    2024-02-09 23:12:51.379088: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_225' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_225}}]]
+    2024-02-09 23:12:51.379122: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_229' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_229}}]]
+    2024-02-09 23:12:51.379155: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_230' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_230}}]]
+    2024-02-09 23:12:51.379190: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_231' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_231}}]]
+    2024-02-09 23:12:51.379223: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_232' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_232}}]]
+    2024-02-09 23:12:51.379257: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_233' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_233}}]]
+    2024-02-09 23:12:51.379291: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_234' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_234}}]]
+    2024-02-09 23:12:51.379325: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_235' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_235}}]]
+    2024-02-09 23:12:51.379358: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_236' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_236}}]]
+    2024-02-09 23:12:51.379392: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_239' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_239}}]]
+    2024-02-09 23:12:51.379426: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_240' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_240}}]]
+    2024-02-09 23:12:51.379459: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_241' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_241}}]]
+    2024-02-09 23:12:51.379492: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_242' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_242}}]]
+    2024-02-09 23:12:51.379526: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_243' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_243}}]]
+    2024-02-09 23:12:51.379560: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_244' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_244}}]]
+    2024-02-09 23:12:51.379593: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_245' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_245}}]]
+    2024-02-09 23:12:51.379627: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_246' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_246}}]]
+    2024-02-09 23:12:51.379660: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_248' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_248}}]]
+    2024-02-09 23:12:51.379694: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_249' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_249}}]]
+    2024-02-09 23:12:51.379728: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_252' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_252}}]]
+    2024-02-09 23:12:51.379761: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_253' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_253}}]]
+    2024-02-09 23:12:51.379794: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_254' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_254}}]]
+    2024-02-09 23:12:51.379828: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_255' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_255}}]]
+    2024-02-09 23:12:51.379862: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_256' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_256}}]]
+    2024-02-09 23:12:51.379903: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_257' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_257}}]]
+    2024-02-09 23:12:51.379960: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_258' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_258}}]]
+    2024-02-09 23:12:51.379997: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_261' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_261}}]]
+    2024-02-09 23:12:51.380032: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_262' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_262}}]]
+    2024-02-09 23:12:51.380081: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_263' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_263}}]]
+    2024-02-09 23:12:51.380122: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_264' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_264}}]]
+    2024-02-09 23:12:51.380162: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_265' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_265}}]]
+    2024-02-09 23:12:51.380200: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_266' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_266}}]]
+    2024-02-09 23:12:51.380236: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_267' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_267}}]]
+    2024-02-09 23:12:51.380277: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_268' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_268}}]]
+    2024-02-09 23:12:51.380330: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_269' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_269}}]]
+    2024-02-09 23:12:51.380368: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_273' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_273}}]]
+    2024-02-09 23:12:51.380404: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_274' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_274}}]]
+    2024-02-09 23:12:51.380441: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_275' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_275}}]]
+    2024-02-09 23:12:51.380478: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_276' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_276}}]]
+    2024-02-09 23:12:51.380515: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_277' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_277}}]]
+    2024-02-09 23:12:51.380550: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_278' with dtype float and shape [32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_278}}]]
+    2024-02-09 23:12:51.380587: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_279' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_279}}]]
+    2024-02-09 23:12:51.380624: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_280' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_280}}]]
+    2024-02-09 23:12:51.380660: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_283' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_283}}]]
+    2024-02-09 23:12:51.380696: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_284' with dtype float and shape [32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_284}}]]
+    2024-02-09 23:12:51.380733: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_285' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_285}}]]
+    2024-02-09 23:12:51.380769: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_286' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_286}}]]
+    2024-02-09 23:12:51.380805: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_287' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_287}}]]
+    2024-02-09 23:12:51.380841: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_288' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_288}}]]
+    2024-02-09 23:12:51.380877: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_289' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_289}}]]
+    2024-02-09 23:12:51.380913: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_290' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_290}}]]
+    2024-02-09 23:12:51.380950: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_291' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_291}}]]
+    2024-02-09 23:12:51.380986: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_295' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_295}}]]
+    2024-02-09 23:12:51.381022: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_296' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_296}}]]
+    2024-02-09 23:12:51.381058: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_297' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_297}}]]
+    2024-02-09 23:12:51.381093: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_298' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_298}}]]
+    2024-02-09 23:12:51.381129: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_299' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_299}}]]
+    2024-02-09 23:12:51.381165: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_300' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_300}}]]
+    2024-02-09 23:12:51.381204: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_301' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_301}}]]
+    2024-02-09 23:12:51.381241: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_302' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_302}}]]
+    2024-02-09 23:12:51.381277: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_305' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_305}}]]
+    2024-02-09 23:12:51.381312: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_306' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_306}}]]
+    2024-02-09 23:12:51.381348: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_307' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_307}}]]
+    2024-02-09 23:12:51.381385: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_308' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_308}}]]
+    2024-02-09 23:12:51.381422: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_309' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_309}}]]
+    2024-02-09 23:12:51.381463: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_310' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_310}}]]
+    2024-02-09 23:12:51.381501: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_311' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_311}}]]
+    2024-02-09 23:12:51.381537: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_312' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_312}}]]
+    2024-02-09 23:12:51.381573: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_314' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_314}}]]
+    2024-02-09 23:12:51.381609: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_315' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_315}}]]
+    2024-02-09 23:12:51.381645: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_318' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_318}}]]
+    2024-02-09 23:12:51.381682: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_319' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_319}}]]
+    2024-02-09 23:12:51.381719: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_320' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_320}}]]
+    2024-02-09 23:12:51.381755: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_321' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_321}}]]
+    2024-02-09 23:12:51.381791: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_322' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_322}}]]
+    2024-02-09 23:12:51.381827: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_323' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_323}}]]
+    2024-02-09 23:12:51.381863: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_324' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_324}}]]
+    2024-02-09 23:12:51.381917: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_327' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_327}}]]
+    2024-02-09 23:12:51.381954: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_328' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_328}}]]
+    2024-02-09 23:12:51.381990: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_329' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_329}}]]
+    2024-02-09 23:12:51.382027: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_330' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_330}}]]
+    2024-02-09 23:12:51.382062: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_331' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_331}}]]
+    2024-02-09 23:12:51.382099: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_332' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_332}}]]
+    2024-02-09 23:12:51.382135: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_333' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_333}}]]
+    2024-02-09 23:12:51.382171: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_334' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_334}}]]
+    2024-02-09 23:12:51.382206: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_335' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_335}}]]
+    2024-02-09 23:12:51.382241: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_339' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_339}}]]
+    2024-02-09 23:12:51.382277: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_340' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_340}}]]
+    2024-02-09 23:12:51.382312: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_341' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_341}}]]
+    2024-02-09 23:12:51.382347: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_342' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_342}}]]
+    2024-02-09 23:12:51.382382: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_343' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_343}}]]
+    2024-02-09 23:12:51.382418: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_344' with dtype float and shape [32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_344}}]]
+    2024-02-09 23:12:51.382453: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_345' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_345}}]]
+    2024-02-09 23:12:51.382488: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_346' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_346}}]]
+    2024-02-09 23:12:51.382524: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_349' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_349}}]]
+    2024-02-09 23:12:51.382559: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_350' with dtype float and shape [32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_350}}]]
+    2024-02-09 23:12:51.382594: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_351' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_351}}]]
+    2024-02-09 23:12:51.382640: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_352' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_352}}]]
+    2024-02-09 23:12:51.382674: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_353' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_353}}]]
+    2024-02-09 23:12:51.382709: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_354' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_354}}]]
+    2024-02-09 23:12:51.382744: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_355' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_355}}]]
+    2024-02-09 23:12:51.382778: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_356' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_356}}]]
+    2024-02-09 23:12:51.382812: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_357' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_357}}]]
+    2024-02-09 23:12:51.382846: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_361' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_361}}]]
+    2024-02-09 23:12:51.382904: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_362' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_362}}]]
+    2024-02-09 23:12:51.382945: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_363' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_363}}]]
+    2024-02-09 23:12:51.382986: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_364' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_364}}]]
+    2024-02-09 23:12:51.383023: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_365' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_365}}]]
+    2024-02-09 23:12:51.383058: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_366' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_366}}]]
+    2024-02-09 23:12:51.383094: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_367' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_367}}]]
+    2024-02-09 23:12:51.383129: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_368' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_368}}]]
+    2024-02-09 23:12:51.383165: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_371' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_371}}]]
+    2024-02-09 23:12:51.383200: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_372' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_372}}]]
+    2024-02-09 23:12:51.383235: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_373' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_373}}]]
+    2024-02-09 23:12:51.383270: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_374' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_374}}]]
+    2024-02-09 23:12:51.383307: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_375' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_375}}]]
+    2024-02-09 23:12:51.383342: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_376' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_376}}]]
+    2024-02-09 23:12:51.383378: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_377' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_377}}]]
+    2024-02-09 23:12:51.383413: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_378' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_378}}]]
+    2024-02-09 23:12:51.383448: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_380' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_380}}]]
+    2024-02-09 23:12:51.383484: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_381' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_381}}]]
+    2024-02-09 23:12:51.383519: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_384' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_384}}]]
+    2024-02-09 23:12:51.383554: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_385' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_385}}]]
+    2024-02-09 23:12:51.383591: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_386' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_386}}]]
+    2024-02-09 23:12:51.383633: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_387' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_387}}]]
+    2024-02-09 23:12:51.383669: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_388' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_388}}]]
+    2024-02-09 23:12:51.383705: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_389' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_389}}]]
+    2024-02-09 23:12:51.383742: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_390' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_390}}]]
+    2024-02-09 23:12:51.383777: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_393' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_393}}]]
+    2024-02-09 23:12:51.383812: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_394' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_394}}]]
+    2024-02-09 23:12:51.383847: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_395' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_395}}]]
+    2024-02-09 23:12:51.383883: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_396' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_396}}]]
+    2024-02-09 23:12:51.383918: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_397' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_397}}]]
+    2024-02-09 23:12:51.383954: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_398' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_398}}]]
+    2024-02-09 23:12:51.384006: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_399' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_399}}]]
+    2024-02-09 23:12:51.384043: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_400' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_400}}]]
+    2024-02-09 23:12:51.384079: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_401' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_401}}]]
+    2024-02-09 23:12:51.384116: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_405' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_405}}]]
+    2024-02-09 23:12:51.384152: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_406' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_406}}]]
+    2024-02-09 23:12:51.384188: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_407' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_407}}]]
+    2024-02-09 23:12:51.384224: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_408' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_408}}]]
+    2024-02-09 23:12:51.384259: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_409' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_409}}]]
+    2024-02-09 23:12:51.384299: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_410' with dtype float and shape [32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_410}}]]
+    2024-02-09 23:12:51.384336: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_411' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_411}}]]
+    2024-02-09 23:12:51.384372: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_412' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_412}}]]
+    2024-02-09 23:12:51.384408: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_415' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_415}}]]
+    2024-02-09 23:12:51.384444: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_416' with dtype float and shape [32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_416}}]]
+    2024-02-09 23:12:51.384481: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_417' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_417}}]]
+    2024-02-09 23:12:51.384516: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_418' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_418}}]]
+    2024-02-09 23:12:51.384552: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_419' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_419}}]]
+    2024-02-09 23:12:51.384588: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_420' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_420}}]]
+    2024-02-09 23:12:51.384624: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_421' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_421}}]]
+    2024-02-09 23:12:51.384661: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_422' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_422}}]]
+    2024-02-09 23:12:51.384696: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_423' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_423}}]]
+    2024-02-09 23:12:51.384732: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_427' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_427}}]]
+    2024-02-09 23:12:51.384768: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_428' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_428}}]]
+    2024-02-09 23:12:51.384805: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_429' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_429}}]]
+    2024-02-09 23:12:51.384843: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_430' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_430}}]]
+    2024-02-09 23:12:51.384884: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_431' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_431}}]]
+    2024-02-09 23:12:51.384921: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_432' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_432}}]]
+    2024-02-09 23:12:51.384958: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_433' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_433}}]]
+    2024-02-09 23:12:51.384994: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_434' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_434}}]]
+    2024-02-09 23:12:51.385031: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_437' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_437}}]]
+    2024-02-09 23:12:51.385067: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_438' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_438}}]]
+    2024-02-09 23:12:51.385104: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_439' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_439}}]]
+    2024-02-09 23:12:51.385150: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_440' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_440}}]]
+    2024-02-09 23:12:51.385186: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_441' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_441}}]]
+    2024-02-09 23:12:51.385221: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_442' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_442}}]]
+    2024-02-09 23:12:51.385257: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_443' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_443}}]]
+    2024-02-09 23:12:51.385292: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_444' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_444}}]]
+    2024-02-09 23:12:51.385328: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_446' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_446}}]]
+    2024-02-09 23:12:51.385364: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_447' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_447}}]]
+    2024-02-09 23:12:51.385399: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_450' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_450}}]]
+    2024-02-09 23:12:51.385450: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_451' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_451}}]]
+    2024-02-09 23:12:51.385503: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_452' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_452}}]]
+    2024-02-09 23:12:51.385539: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_453' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_453}}]]
+    2024-02-09 23:12:51.385575: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_454' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_454}}]]
+    2024-02-09 23:12:51.385610: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_455' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_455}}]]
+    2024-02-09 23:12:51.385646: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_456' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_456}}]]
+    2024-02-09 23:12:51.385682: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_459' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_459}}]]
+    2024-02-09 23:12:51.385718: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_460' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_460}}]]
+    2024-02-09 23:12:51.385753: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_461' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_461}}]]
+    2024-02-09 23:12:51.385790: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_462' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_462}}]]
+    2024-02-09 23:12:51.385825: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_463' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_463}}]]
+    2024-02-09 23:12:51.385868: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_464' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_464}}]]
+    2024-02-09 23:12:51.385910: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_465' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_465}}]]
+    2024-02-09 23:12:51.385948: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_466' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_466}}]]
+    2024-02-09 23:12:51.385987: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_467' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_467}}]]
+    2024-02-09 23:12:51.386023: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_471' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_471}}]]
+    2024-02-09 23:12:51.386059: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_472' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_472}}]]
+    2024-02-09 23:12:51.386095: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_473' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_473}}]]
+    2024-02-09 23:12:51.386132: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_474' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_474}}]]
+    2024-02-09 23:12:51.386167: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_475' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_475}}]]
+    2024-02-09 23:12:51.386203: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_476' with dtype float and shape [32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_476}}]]
+    2024-02-09 23:12:51.386239: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_477' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_477}}]]
+    2024-02-09 23:12:51.386275: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_478' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_478}}]]
+    2024-02-09 23:12:51.386311: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_481' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_481}}]]
+    2024-02-09 23:12:51.386347: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_482' with dtype float and shape [32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_482}}]]
+    2024-02-09 23:12:51.386383: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_483' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_483}}]]
+    2024-02-09 23:12:51.386419: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_484' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_484}}]]
+    2024-02-09 23:12:51.386455: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_485' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_485}}]]
+    2024-02-09 23:12:51.386490: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_486' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_486}}]]
+    2024-02-09 23:12:51.386526: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_487' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_487}}]]
+    2024-02-09 23:12:51.386562: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_488' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_488}}]]
+    2024-02-09 23:12:51.386597: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_489' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_489}}]]
+    2024-02-09 23:12:51.386633: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_493' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_493}}]]
+    2024-02-09 23:12:51.386669: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_494' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_494}}]]
+    2024-02-09 23:12:51.386704: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_495' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_495}}]]
+    2024-02-09 23:12:51.386741: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_496' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_496}}]]
+    2024-02-09 23:12:51.386777: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_497' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_497}}]]
+    2024-02-09 23:12:51.386813: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_498' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_498}}]]
+    2024-02-09 23:12:51.386850: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_499' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_499}}]]
+    2024-02-09 23:12:51.386886: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_500' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_500}}]]
+    2024-02-09 23:12:51.386928: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_503' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_503}}]]
+    2024-02-09 23:12:51.386966: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_504' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_504}}]]
+    2024-02-09 23:12:51.387002: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_505' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_505}}]]
+    2024-02-09 23:12:51.387039: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_506' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_506}}]]
+    2024-02-09 23:12:51.387075: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_507' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_507}}]]
+    2024-02-09 23:12:51.387111: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_508' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_508}}]]
+    2024-02-09 23:12:51.387147: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_509' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_509}}]]
+    2024-02-09 23:12:51.387184: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_510' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_510}}]]
+    2024-02-09 23:12:51.387220: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_512' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_512}}]]
+    2024-02-09 23:12:51.387256: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_513' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_513}}]]
+    2024-02-09 23:12:51.387308: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_516' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_516}}]]
+    2024-02-09 23:12:51.387344: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_517' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_517}}]]
+    2024-02-09 23:12:51.387380: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_518' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_518}}]]
+    2024-02-09 23:12:51.387416: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_519' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_519}}]]
+    2024-02-09 23:12:51.387453: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_520' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_520}}]]
+    2024-02-09 23:12:51.387490: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_521' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_521}}]]
+    2024-02-09 23:12:51.387528: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_522' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_522}}]]
+    2024-02-09 23:12:51.387565: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_525' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_525}}]]
+    2024-02-09 23:12:51.387603: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_526' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_526}}]]
+    2024-02-09 23:12:51.387640: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_527' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_527}}]]
+    2024-02-09 23:12:51.387677: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_528' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_528}}]]
+    2024-02-09 23:12:51.387714: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_529' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_529}}]]
+    2024-02-09 23:12:51.387753: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_530' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_530}}]]
+    2024-02-09 23:12:51.387790: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_531' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_531}}]]
+    2024-02-09 23:12:51.387827: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_532' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_532}}]]
+    2024-02-09 23:12:51.387864: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_533' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_533}}]]
+    2024-02-09 23:12:51.387902: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_537' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_537}}]]
+    2024-02-09 23:12:51.387939: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_538' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_538}}]]
+    2024-02-09 23:12:51.387980: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_539' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_539}}]]
+    2024-02-09 23:12:51.388018: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_540' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_540}}]]
+    2024-02-09 23:12:51.388055: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_541' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_541}}]]
+    2024-02-09 23:12:51.388092: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_542' with dtype float and shape [32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_542}}]]
+    2024-02-09 23:12:51.388129: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_543' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_543}}]]
+    2024-02-09 23:12:51.388167: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_544' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_544}}]]
+    2024-02-09 23:12:51.388212: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_547' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_547}}]]
+    2024-02-09 23:12:51.388250: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_548' with dtype float and shape [32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_548}}]]
+    2024-02-09 23:12:51.388287: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_549' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_549}}]]
+    2024-02-09 23:12:51.388324: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_550' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_550}}]]
+    2024-02-09 23:12:51.388364: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_551' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_551}}]]
+    2024-02-09 23:12:51.388402: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_552' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_552}}]]
+    2024-02-09 23:12:51.388449: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_553' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_553}}]]
+    2024-02-09 23:12:51.388485: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_554' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_554}}]]
+    2024-02-09 23:12:51.388522: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_555' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_555}}]]
+    2024-02-09 23:12:51.388558: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_557' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_557}}]]
+    2024-02-09 23:12:51.388594: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_563' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_563}}]]
+    2024-02-09 23:12:51.388638: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_564' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_564}}]]
+    2024-02-09 23:12:51.388679: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_565' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_565}}]]
+    2024-02-09 23:12:51.388715: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_566' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_566}}]]
+    2024-02-09 23:12:51.388751: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_567' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_567}}]]
+    2024-02-09 23:12:51.388788: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_568' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_568}}]]
+    2024-02-09 23:12:51.388824: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_569' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_569}}]]
+    2024-02-09 23:12:51.388860: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_570' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_570}}]]
+    2024-02-09 23:12:51.388897: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_575' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_575}}]]
+    2024-02-09 23:12:51.388932: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_576' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_576}}]]
+    2024-02-09 23:12:51.388968: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_577' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_577}}]]
+    2024-02-09 23:12:51.389008: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_578' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_578}}]]
+    2024-02-09 23:12:51.389045: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_579' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_579}}]]
+    2024-02-09 23:12:51.389082: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_580' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_580}}]]
+    2024-02-09 23:12:51.389119: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_581' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_581}}]]
+    2024-02-09 23:12:51.389154: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_582' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_582}}]]
+    2024-02-09 23:12:51.389190: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_584' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_584}}]]
+    2024-02-09 23:12:51.389227: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_585' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_585}}]]
+    2024-02-09 23:12:51.389271: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_588' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_588}}]]
+    2024-02-09 23:12:51.389309: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_589' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_589}}]]
+    2024-02-09 23:12:51.389345: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_590' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_590}}]]
+    2024-02-09 23:12:51.389381: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_591' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_591}}]]
+    2024-02-09 23:12:51.389418: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_592' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_592}}]]
+    2024-02-09 23:12:51.389459: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_593' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_593}}]]
+    2024-02-09 23:12:51.389513: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_594' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_594}}]]
+    2024-02-09 23:12:51.389550: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_597' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_597}}]]
+    2024-02-09 23:12:51.389586: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_598' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_598}}]]
+    2024-02-09 23:12:51.389627: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_599' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_599}}]]
+    2024-02-09 23:12:51.389665: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_600' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_600}}]]
+    2024-02-09 23:12:51.389701: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_601' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_601}}]]
+    2024-02-09 23:12:51.389739: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_602' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_602}}]]
+    2024-02-09 23:12:51.389777: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_603' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_603}}]]
+    2024-02-09 23:12:51.389814: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_604' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_604}}]]
+    2024-02-09 23:12:51.389851: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_608' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_608}}]]
+    2024-02-09 23:12:51.389889: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_609' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_609}}]]
+    2024-02-09 23:12:51.389926: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_610' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_610}}]]
+    2024-02-09 23:12:51.389963: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_611' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_611}}]]
+    2024-02-09 23:12:51.390001: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_612' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_612}}]]
+    2024-02-09 23:12:51.390038: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_613' with dtype float and shape [32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_613}}]]
+    2024-02-09 23:12:51.390075: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_614' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_614}}]]
+    2024-02-09 23:12:51.390112: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_615' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_615}}]]
+    2024-02-09 23:12:51.390149: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_618' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_618}}]]
+    2024-02-09 23:12:51.390186: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_619' with dtype float and shape [32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_619}}]]
+    2024-02-09 23:12:51.390223: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_620' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_620}}]]
+    2024-02-09 23:12:51.390260: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_621' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_621}}]]
+    2024-02-09 23:12:51.390297: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_622' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_622}}]]
+    2024-02-09 23:12:51.390333: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_623' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_623}}]]
+    2024-02-09 23:12:51.390370: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_624' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_624}}]]
+    2024-02-09 23:12:51.390407: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_625' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_625}}]]
+    2024-02-09 23:12:51.390443: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_626' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_626}}]]
+    2024-02-09 23:12:51.390480: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_627' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_627}}]]
+    2024-02-09 23:12:51.390516: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_631' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_631}}]]
+    2024-02-09 23:12:51.390553: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_632' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_632}}]]
+    2024-02-09 23:12:51.390590: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_633' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_633}}]]
+    2024-02-09 23:12:51.390636: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_634' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_634}}]]
+    2024-02-09 23:12:51.390672: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_635' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_635}}]]
+    2024-02-09 23:12:51.390708: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_636' with dtype float and shape [32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_636}}]]
+    2024-02-09 23:12:51.390743: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_637' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_637}}]]
+    2024-02-09 23:12:51.390778: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_638' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_638}}]]
+    2024-02-09 23:12:51.390814: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_641' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_641}}]]
+    2024-02-09 23:12:51.390857: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_642' with dtype float and shape [32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_642}}]]
+    2024-02-09 23:12:51.390900: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_643' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_643}}]]
+    2024-02-09 23:12:51.390938: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_644' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_644}}]]
+    2024-02-09 23:12:51.390974: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_645' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_645}}]]
+    2024-02-09 23:12:51.391010: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_646' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_646}}]]
+    2024-02-09 23:12:51.391047: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_647' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_647}}]]
+    2024-02-09 23:12:51.391083: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_648' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_648}}]]
+    2024-02-09 23:12:51.391123: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_650' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_650}}]]
+    2024-02-09 23:12:51.391160: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_651' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_651}}]]
+    2024-02-09 23:12:51.391197: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_654' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_654}}]]
+    2024-02-09 23:12:51.391232: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_655' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_655}}]]
+    2024-02-09 23:12:51.391268: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_656' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_656}}]]
+    2024-02-09 23:12:51.391303: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_657' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_657}}]]
+    2024-02-09 23:12:51.391340: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_658' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_658}}]]
+    2024-02-09 23:12:51.391375: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_659' with dtype float and shape [32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_659}}]]
+    2024-02-09 23:12:51.391411: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_660' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_660}}]]
+    2024-02-09 23:12:51.391447: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_663' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_663}}]]
+    2024-02-09 23:12:51.391483: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_664' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_664}}]]
+    2024-02-09 23:12:51.391522: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_665' with dtype float and shape [32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_665}}]]
+    2024-02-09 23:12:51.391559: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_666' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_666}}]]
+    2024-02-09 23:12:51.391595: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_667' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_667}}]]
+    2024-02-09 23:12:51.391634: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_668' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_668}}]]
+    2024-02-09 23:12:51.391671: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_669' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_669}}]]
+    2024-02-09 23:12:51.391706: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_670' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_670}}]]
+    2024-02-09 23:12:51.391743: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_671' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_671}}]]
+    2024-02-09 23:12:51.391779: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_675' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_675}}]]
+    2024-02-09 23:12:51.391814: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_676' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_676}}]]
+    2024-02-09 23:12:51.391850: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_677' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_677}}]]
+    2024-02-09 23:12:51.391889: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_678' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_678}}]]
+    2024-02-09 23:12:51.391926: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_679' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_679}}]]
+    2024-02-09 23:12:51.391961: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_680' with dtype float and shape [32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_680}}]]
+    2024-02-09 23:12:51.391997: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_681' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_681}}]]
+    2024-02-09 23:12:51.392034: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_682' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_682}}]]
+    2024-02-09 23:12:51.392069: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_685' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_685}}]]
+    2024-02-09 23:12:51.392106: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_686' with dtype float and shape [32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_686}}]]
+    2024-02-09 23:12:51.392141: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_687' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_687}}]]
+    2024-02-09 23:12:51.392177: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_688' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_688}}]]
+    2024-02-09 23:12:51.392214: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_689' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_689}}]]
+    2024-02-09 23:12:51.392250: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_690' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_690}}]]
+    2024-02-09 23:12:51.392288: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_691' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_691}}]]
+    2024-02-09 23:12:51.392324: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_692' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_692}}]]
+    2024-02-09 23:12:51.392360: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_693' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_693}}]]
+    2024-02-09 23:12:51.392396: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_697' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_697}}]]
+    2024-02-09 23:12:51.392432: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_698' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_698}}]]
+    2024-02-09 23:12:51.392468: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_699' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_699}}]]
+    2024-02-09 23:12:51.392503: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_700' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_700}}]]
+    2024-02-09 23:12:51.392539: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_701' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_701}}]]
+    2024-02-09 23:12:51.392575: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_702' with dtype float and shape [32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_702}}]]
+    2024-02-09 23:12:51.392612: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_703' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_703}}]]
+    2024-02-09 23:12:51.392647: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_704' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_704}}]]
+    2024-02-09 23:12:51.392683: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_707' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_707}}]]
+    2024-02-09 23:12:51.392718: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_708' with dtype float and shape [32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_708}}]]
+    2024-02-09 23:12:51.392761: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_709' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_709}}]]
+    2024-02-09 23:12:51.392798: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_710' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_710}}]]
+    2024-02-09 23:12:51.392835: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_711' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_711}}]]
+    2024-02-09 23:12:51.392871: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_712' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_712}}]]
+    2024-02-09 23:12:51.392907: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_713' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_713}}]]
+    2024-02-09 23:12:51.392943: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_714' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_714}}]]
+    2024-02-09 23:12:51.392978: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_716' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_716}}]]
+    2024-02-09 23:12:51.393014: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_717' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_717}}]]
+    2024-02-09 23:12:51.393051: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_720' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_720}}]]
+    2024-02-09 23:12:51.393087: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_721' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_721}}]]
+    2024-02-09 23:12:51.393123: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_722' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_722}}]]
+    2024-02-09 23:12:51.393160: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_723' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_723}}]]
+    2024-02-09 23:12:51.393196: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_724' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_724}}]]
+    2024-02-09 23:12:51.393232: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_725' with dtype float and shape [32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_725}}]]
+    2024-02-09 23:12:51.393268: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_726' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_726}}]]
+    2024-02-09 23:12:51.393305: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_729' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_729}}]]
+    2024-02-09 23:12:51.393341: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_730' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_730}}]]
+    2024-02-09 23:12:51.393378: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_731' with dtype float and shape [32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_731}}]]
+    2024-02-09 23:12:51.393414: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_732' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_732}}]]
+    2024-02-09 23:12:51.393456: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_733' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_733}}]]
+    2024-02-09 23:12:51.393494: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_734' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_734}}]]
+    2024-02-09 23:12:51.393529: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_735' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_735}}]]
+    2024-02-09 23:12:51.393565: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_736' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_736}}]]
+    2024-02-09 23:12:51.393601: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_737' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_737}}]]
+    2024-02-09 23:12:51.393637: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_741' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_741}}]]
+    2024-02-09 23:12:51.393673: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_742' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_742}}]]
+    2024-02-09 23:12:51.393710: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_743' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_743}}]]
+    2024-02-09 23:12:51.393746: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_744' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_744}}]]
+    2024-02-09 23:12:51.393783: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_745' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_745}}]]
+    2024-02-09 23:12:51.393819: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_746' with dtype float and shape [32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_746}}]]
+    2024-02-09 23:12:51.393855: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_747' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_747}}]]
+    2024-02-09 23:12:51.393891: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_748' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_748}}]]
+    2024-02-09 23:12:51.393928: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_751' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_751}}]]
+    2024-02-09 23:12:51.393964: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_752' with dtype float and shape [32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_752}}]]
+    2024-02-09 23:12:51.394000: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_753' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_753}}]]
+    2024-02-09 23:12:51.394037: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_754' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_754}}]]
+    2024-02-09 23:12:51.394073: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_755' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_755}}]]
+    2024-02-09 23:12:51.394110: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_756' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_756}}]]
+    2024-02-09 23:12:51.394146: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_757' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_757}}]]
+    2024-02-09 23:12:51.394182: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_758' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_758}}]]
+    2024-02-09 23:12:51.394217: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_759' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_759}}]]
+    2024-02-09 23:12:51.394253: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_763' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_763}}]]
+    2024-02-09 23:12:51.394289: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_764' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_764}}]]
+    2024-02-09 23:12:51.394325: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_765' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_765}}]]
+    2024-02-09 23:12:51.394362: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_766' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_766}}]]
+    2024-02-09 23:12:51.394398: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_767' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_767}}]]
+    2024-02-09 23:12:51.394434: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_768' with dtype float and shape [32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_768}}]]
+    2024-02-09 23:12:51.394471: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_769' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_769}}]]
+    2024-02-09 23:12:51.394508: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_770' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_770}}]]
+    2024-02-09 23:12:51.394545: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_773' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_773}}]]
+    2024-02-09 23:12:51.394582: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_774' with dtype float and shape [32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_774}}]]
+    2024-02-09 23:12:51.394618: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_775' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_775}}]]
+    2024-02-09 23:12:51.394655: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_776' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_776}}]]
+    2024-02-09 23:12:51.394692: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_777' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_777}}]]
+    2024-02-09 23:12:51.394729: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_778' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_778}}]]
+    2024-02-09 23:12:51.394765: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_779' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_779}}]]
+    2024-02-09 23:12:51.394802: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_780' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_780}}]]
+    2024-02-09 23:12:51.394838: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_782' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_782}}]]
+    2024-02-09 23:12:51.394874: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_783' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_783}}]]
+    2024-02-09 23:12:51.394911: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_786' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_786}}]]
+    2024-02-09 23:12:51.394948: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_787' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_787}}]]
+    2024-02-09 23:12:51.394984: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_788' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_788}}]]
+    2024-02-09 23:12:51.395021: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_789' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_789}}]]
+    2024-02-09 23:12:51.395057: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_790' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_790}}]]
+    2024-02-09 23:12:51.395094: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_791' with dtype float and shape [32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_791}}]]
+    2024-02-09 23:12:51.395131: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_792' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_792}}]]
+    2024-02-09 23:12:51.395168: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_795' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_795}}]]
+    2024-02-09 23:12:51.395204: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_796' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_796}}]]
+    2024-02-09 23:12:51.395241: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_797' with dtype float and shape [32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_797}}]]
+    2024-02-09 23:12:51.395277: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_798' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_798}}]]
+    2024-02-09 23:12:51.395314: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_799' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_799}}]]
+    2024-02-09 23:12:51.395351: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_800' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_800}}]]
+    2024-02-09 23:12:51.395388: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_801' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_801}}]]
+    2024-02-09 23:12:51.395424: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_802' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_802}}]]
+    2024-02-09 23:12:51.395461: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_803' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_803}}]]
+    2024-02-09 23:12:51.395498: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_807' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_807}}]]
+    2024-02-09 23:12:51.395534: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_808' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_808}}]]
+    2024-02-09 23:12:51.395571: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_809' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_809}}]]
+    2024-02-09 23:12:51.395607: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_810' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_810}}]]
+    2024-02-09 23:12:51.395644: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_811' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_811}}]]
+    2024-02-09 23:12:51.395680: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_812' with dtype float and shape [32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_812}}]]
+    2024-02-09 23:12:51.395715: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_813' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_813}}]]
+    2024-02-09 23:12:51.395752: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_814' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_814}}]]
+    2024-02-09 23:12:51.395788: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_817' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_817}}]]
+    2024-02-09 23:12:51.395824: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_818' with dtype float and shape [32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_818}}]]
+    2024-02-09 23:12:51.395861: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_819' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_819}}]]
+    2024-02-09 23:12:51.395897: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_820' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_820}}]]
+    2024-02-09 23:12:51.395933: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_821' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_821}}]]
+    2024-02-09 23:12:51.395969: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_822' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_822}}]]
+    2024-02-09 23:12:51.396006: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_823' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_823}}]]
+    2024-02-09 23:12:51.396042: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_824' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_824}}]]
+    2024-02-09 23:12:51.396078: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_825' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_825}}]]
+    2024-02-09 23:12:51.396115: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_827' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_827}}]]
+    2024-02-09 23:12:51.396151: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_833' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_833}}]]
+    2024-02-09 23:12:51.396188: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_834' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_834}}]]
+    2024-02-09 23:12:51.396224: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_835' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_835}}]]
+    2024-02-09 23:12:51.396260: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_836' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_836}}]]
+    2024-02-09 23:12:51.396296: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_837' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_837}}]]
+    2024-02-09 23:12:51.396332: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_838' with dtype float and shape [32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_838}}]]
+    2024-02-09 23:12:51.396368: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_839' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_839}}]]
+    2024-02-09 23:12:51.396405: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_840' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_840}}]]
+    2024-02-09 23:12:51.396441: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_845' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_845}}]]
+    2024-02-09 23:12:51.396478: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_846' with dtype float and shape [32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_846}}]]
+    2024-02-09 23:12:51.396514: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_847' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_847}}]]
+    2024-02-09 23:12:51.396550: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_848' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_848}}]]
+    2024-02-09 23:12:51.396587: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_849' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_849}}]]
+    2024-02-09 23:12:51.396624: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_850' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_850}}]]
+    2024-02-09 23:12:51.396660: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_851' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_851}}]]
+    2024-02-09 23:12:51.396696: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_852' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_852}}]]
+    2024-02-09 23:12:51.396732: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_854' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_854}}]]
+    2024-02-09 23:12:51.396769: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_855' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_855}}]]
+    2024-02-09 23:12:51.396806: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_858' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_858}}]]
+    2024-02-09 23:12:51.396843: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_859' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_859}}]]
+    2024-02-09 23:12:51.396879: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_860' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_860}}]]
+    2024-02-09 23:12:51.396915: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_861' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_861}}]]
+    2024-02-09 23:12:51.396951: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_862' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_862}}]]
+    2024-02-09 23:12:51.396988: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_863' with dtype float and shape [32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_863}}]]
+    2024-02-09 23:12:51.397024: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_864' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_864}}]]
+    2024-02-09 23:12:51.397061: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_867' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_867}}]]
+    2024-02-09 23:12:51.397096: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_868' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_868}}]]
+    2024-02-09 23:12:51.397132: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_869' with dtype float and shape [32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_869}}]]
+    2024-02-09 23:12:51.397168: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_870' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_870}}]]
+    2024-02-09 23:12:51.397204: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_871' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_871}}]]
+    2024-02-09 23:12:51.397240: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_872' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_872}}]]
+    2024-02-09 23:12:51.397276: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_873' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_873}}]]
+    2024-02-09 23:12:51.397312: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_874' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_874}}]]
+    2024-02-09 23:12:51.397349: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_878' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_878}}]]
+    2024-02-09 23:12:51.397385: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_879' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_879}}]]
+    2024-02-09 23:12:51.397422: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_880' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_880}}]]
+    2024-02-09 23:12:51.397481: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_881' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_881}}]]
+    2024-02-09 23:12:51.397520: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_882' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_882}}]]
+    2024-02-09 23:12:51.397557: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_883' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_883}}]]
+    2024-02-09 23:12:51.397593: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_884' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_884}}]]
+    2024-02-09 23:12:51.397631: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_885' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_885}}]]
+    2024-02-09 23:12:51.397669: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_888' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_888}}]]
+    2024-02-09 23:12:51.397707: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_889' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_889}}]]
+    2024-02-09 23:12:51.397744: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_890' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_890}}]]
+    2024-02-09 23:12:51.397780: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_891' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_891}}]]
+    2024-02-09 23:12:51.397817: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_892' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_892}}]]
+    2024-02-09 23:12:51.397855: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_893' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_893}}]]
+    2024-02-09 23:12:51.397892: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_894' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_894}}]]
+    2024-02-09 23:12:51.397929: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_895' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_895}}]]
+    2024-02-09 23:12:51.397967: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_896' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_896}}]]
+    2024-02-09 23:12:51.398004: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_897' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_897}}]]
+    2024-02-09 23:12:51.398040: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_901' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_901}}]]
+    2024-02-09 23:12:51.398077: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_902' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_902}}]]
+    2024-02-09 23:12:51.398115: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_903' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_903}}]]
+    2024-02-09 23:12:51.398152: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_904' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_904}}]]
+    2024-02-09 23:12:51.398190: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_905' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_905}}]]
+    2024-02-09 23:12:51.398226: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_906' with dtype float and shape [32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_906}}]]
+    2024-02-09 23:12:51.398263: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_907' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_907}}]]
+    2024-02-09 23:12:51.398300: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_908' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_908}}]]
+    2024-02-09 23:12:51.398337: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_911' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_911}}]]
+    2024-02-09 23:12:51.398373: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_912' with dtype float and shape [32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_912}}]]
+    2024-02-09 23:12:51.398410: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_913' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_913}}]]
+    2024-02-09 23:12:51.398447: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_914' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_914}}]]
+    2024-02-09 23:12:51.398484: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_915' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_915}}]]
+    2024-02-09 23:12:51.398521: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_916' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_916}}]]
+    2024-02-09 23:12:51.398558: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_917' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_917}}]]
+    2024-02-09 23:12:51.398595: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_918' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_918}}]]
+    2024-02-09 23:12:51.398643: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_920' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_920}}]]
+    2024-02-09 23:12:51.398680: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_921' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_921}}]]
+    2024-02-09 23:12:51.398726: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_924' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_924}}]]
+    2024-02-09 23:12:51.398761: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_925' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_925}}]]
+    2024-02-09 23:12:51.398796: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_926' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_926}}]]
+    2024-02-09 23:12:51.398831: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_927' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_927}}]]
+    2024-02-09 23:12:51.398867: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_928' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_928}}]]
+    2024-02-09 23:12:51.398902: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_929' with dtype float and shape [32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_929}}]]
+    2024-02-09 23:12:51.398937: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_930' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_930}}]]
+    2024-02-09 23:12:51.398971: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_933' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_933}}]]
+    2024-02-09 23:12:51.399005: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_934' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_934}}]]
+    2024-02-09 23:12:51.399040: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_935' with dtype float and shape [32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_935}}]]
+    2024-02-09 23:12:51.399075: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_936' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_936}}]]
+    2024-02-09 23:12:51.399110: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_937' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_937}}]]
+    2024-02-09 23:12:51.399145: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_938' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_938}}]]
+    2024-02-09 23:12:51.399179: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_939' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_939}}]]
+    2024-02-09 23:12:51.399213: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_940' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_940}}]]
+    2024-02-09 23:12:51.399248: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_941' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_941}}]]
+    2024-02-09 23:12:51.399284: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_945' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_945}}]]
+    2024-02-09 23:12:51.399318: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_946' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_946}}]]
+    2024-02-09 23:12:51.399353: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_947' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_947}}]]
+    2024-02-09 23:12:51.399387: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_948' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_948}}]]
+    2024-02-09 23:12:51.399422: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_949' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_949}}]]
+    2024-02-09 23:12:51.399457: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_950' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_950}}]]
+    2024-02-09 23:12:51.399492: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_951' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_951}}]]
+    2024-02-09 23:12:51.399527: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_952' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_952}}]]
+    2024-02-09 23:12:51.399561: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_955' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_955}}]]
+    2024-02-09 23:12:51.399595: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_956' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_956}}]]
+    2024-02-09 23:12:51.399630: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_957' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_957}}]]
+    2024-02-09 23:12:51.399664: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_958' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_958}}]]
+    2024-02-09 23:12:51.399699: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_959' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_959}}]]
+    2024-02-09 23:12:51.399734: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_960' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_960}}]]
+    2024-02-09 23:12:51.399769: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_961' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_961}}]]
+    2024-02-09 23:12:51.399804: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_962' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_962}}]]
+    2024-02-09 23:12:51.399839: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_963' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_963}}]]
+    2024-02-09 23:12:51.399874: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_967' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_967}}]]
+    2024-02-09 23:12:51.399909: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_968' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_968}}]]
+    2024-02-09 23:12:51.399944: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_969' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_969}}]]
+    2024-02-09 23:12:51.399978: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_970' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_970}}]]
+    2024-02-09 23:12:51.400013: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_971' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_971}}]]
+    2024-02-09 23:12:51.400047: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_972' with dtype float and shape [32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_972}}]]
+    2024-02-09 23:12:51.400081: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_973' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_973}}]]
+    2024-02-09 23:12:51.400116: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_974' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_974}}]]
+    2024-02-09 23:12:51.400150: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_977' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_977}}]]
+    2024-02-09 23:12:51.400185: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_978' with dtype float and shape [32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_978}}]]
+    2024-02-09 23:12:51.400220: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_979' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_979}}]]
+    2024-02-09 23:12:51.400254: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_980' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_980}}]]
+    2024-02-09 23:12:51.400289: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_981' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_981}}]]
+    2024-02-09 23:12:51.400323: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_982' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_982}}]]
+    2024-02-09 23:12:51.400359: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_983' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_983}}]]
+    2024-02-09 23:12:51.400393: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_984' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_984}}]]
+    2024-02-09 23:12:51.400428: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_986' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_986}}]]
+    2024-02-09 23:12:51.400463: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_987' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_987}}]]
+    2024-02-09 23:12:51.400498: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_990' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_990}}]]
+    2024-02-09 23:12:51.400533: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_991' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_991}}]]
+    2024-02-09 23:12:51.400569: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_992' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_992}}]]
+    2024-02-09 23:12:51.400603: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_993' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_993}}]]
+    2024-02-09 23:12:51.400638: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_994' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_994}}]]
+    2024-02-09 23:12:51.400672: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_995' with dtype float and shape [32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_995}}]]
+    2024-02-09 23:12:51.400707: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_996' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_996}}]]
+    2024-02-09 23:12:51.400742: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_999' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_999}}]]
+    2024-02-09 23:12:51.400777: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1000' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1000}}]]
+    2024-02-09 23:12:51.400811: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1001' with dtype float and shape [32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1001}}]]
+    2024-02-09 23:12:51.400846: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1002' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1002}}]]
+    2024-02-09 23:12:51.400881: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1003' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1003}}]]
+    2024-02-09 23:12:51.400916: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1004' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1004}}]]
+    2024-02-09 23:12:51.400950: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1005' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1005}}]]
+    2024-02-09 23:12:51.400985: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1006' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1006}}]]
+    2024-02-09 23:12:51.401020: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1007' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1007}}]]
+    2024-02-09 23:12:51.401054: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1011' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1011}}]]
+    2024-02-09 23:12:51.401090: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1012' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1012}}]]
+    2024-02-09 23:12:51.401125: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1013' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1013}}]]
+    2024-02-09 23:12:51.401159: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1014' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1014}}]]
+    2024-02-09 23:12:51.401194: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1015' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1015}}]]
+    2024-02-09 23:12:51.401228: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1016' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1016}}]]
+    2024-02-09 23:12:51.401263: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1017' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1017}}]]
+    2024-02-09 23:12:51.401298: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1018' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1018}}]]
+    2024-02-09 23:12:51.401333: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1021' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1021}}]]
+    2024-02-09 23:12:51.401367: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1022' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1022}}]]
+    2024-02-09 23:12:51.401402: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1023' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1023}}]]
+    2024-02-09 23:12:51.401442: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1024' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1024}}]]
+    2024-02-09 23:12:51.401495: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1025' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1025}}]]
+    2024-02-09 23:12:51.401531: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1026' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1026}}]]
+    2024-02-09 23:12:51.401568: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1027' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1027}}]]
+    2024-02-09 23:12:51.401604: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1028' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1028}}]]
+    2024-02-09 23:12:51.401641: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1029' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1029}}]]
+    2024-02-09 23:12:51.401678: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1031' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1031}}]]
+    2024-02-09 23:12:51.401714: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1037' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1037}}]]
+    2024-02-09 23:12:51.401751: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1038' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1038}}]]
+    2024-02-09 23:12:51.401787: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1039' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1039}}]]
+    2024-02-09 23:12:51.401825: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1040' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1040}}]]
+    2024-02-09 23:12:51.401861: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1041' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1041}}]]
+    2024-02-09 23:12:51.401898: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1042' with dtype float and shape [32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1042}}]]
+    2024-02-09 23:12:51.401935: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1043' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1043}}]]
+    2024-02-09 23:12:51.401974: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1044' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1044}}]]
+    2024-02-09 23:12:51.402011: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1049' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1049}}]]
+    2024-02-09 23:12:51.402047: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1050' with dtype float and shape [32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1050}}]]
+    2024-02-09 23:12:51.402084: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1051' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1051}}]]
+    2024-02-09 23:12:51.402122: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1052' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1052}}]]
+    2024-02-09 23:12:51.402159: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1053' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1053}}]]
+    2024-02-09 23:12:51.402196: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1054' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1054}}]]
+    2024-02-09 23:12:51.402233: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1055' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1055}}]]
+    2024-02-09 23:12:51.402270: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1056' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1056}}]]
+    2024-02-09 23:12:51.402307: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1058' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1058}}]]
+    2024-02-09 23:12:51.402345: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1059' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1059}}]]
+    2024-02-09 23:12:51.402381: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1062' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1062}}]]
+    2024-02-09 23:12:51.402418: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1063' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1063}}]]
+    2024-02-09 23:12:51.402454: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1064' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1064}}]]
+    2024-02-09 23:12:51.402490: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1065' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1065}}]]
+    2024-02-09 23:12:51.402527: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1066' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1066}}]]
+    2024-02-09 23:12:51.402564: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1067' with dtype float and shape [32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1067}}]]
+    2024-02-09 23:12:51.402601: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1068' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1068}}]]
+    2024-02-09 23:12:51.402637: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1071' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1071}}]]
+    2024-02-09 23:12:51.402673: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1072' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1072}}]]
+    2024-02-09 23:12:51.402719: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1073' with dtype float and shape [32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1073}}]]
+    2024-02-09 23:12:51.402755: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1074' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1074}}]]
+    2024-02-09 23:12:51.402790: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1075' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1075}}]]
+    2024-02-09 23:12:51.402826: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1076' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1076}}]]
+    2024-02-09 23:12:51.402861: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1077' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1077}}]]
+    2024-02-09 23:12:51.402897: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1078' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1078}}]]
+    2024-02-09 23:12:51.402933: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1082' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1082}}]]
+    2024-02-09 23:12:51.402969: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1083' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1083}}]]
+    2024-02-09 23:12:51.403004: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1084' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1084}}]]
+    2024-02-09 23:12:51.403039: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1085' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1085}}]]
+    2024-02-09 23:12:51.403074: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1086' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1086}}]]
+    2024-02-09 23:12:51.403109: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1087' with dtype float and shape [32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1087}}]]
+    2024-02-09 23:12:51.403145: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1088' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1088}}]]
+    2024-02-09 23:12:51.403180: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1089' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1089}}]]
+    2024-02-09 23:12:51.403216: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1092' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1092}}]]
+    2024-02-09 23:12:51.403251: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1093' with dtype float and shape [32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1093}}]]
+    2024-02-09 23:12:51.403287: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1094' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1094}}]]
+    2024-02-09 23:12:51.403322: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1095' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1095}}]]
+    2024-02-09 23:12:51.403357: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1096' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1096}}]]
+    2024-02-09 23:12:51.403392: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1097' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1097}}]]
+    2024-02-09 23:12:51.403428: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1098' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1098}}]]
+    2024-02-09 23:12:51.403462: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1101' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1101}}]]
+    2024-02-09 23:12:51.403497: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1102' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1102}}]]
+    2024-02-09 23:12:51.403533: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1103' with dtype float and shape [?,?,?,3]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1103}}]]
+    2024-02-09 23:12:51.403569: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1105' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1105}}]]
+    2024-02-09 23:12:51.403605: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1106' with dtype float and shape [?,?,?,3]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1106}}]]
+    2024-02-09 23:12:51.403642: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1111' with dtype float and shape [?,?,?,3]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1111}}]]
+    2024-02-09 23:12:51.403678: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1112' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1112}}]]
+    2024-02-09 23:12:51.403713: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1113' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1113}}]]
+    2024-02-09 23:12:51.403749: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1114' with dtype float and shape [?,?,?,3]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1114}}]]
+
+
+.. parsed-literal::
+
+    2024-02-09 23:12:51.910039: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall' with dtype float and shape [?,?,?,?]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall}}]]
+    2024-02-09 23:12:51.910118: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1' with dtype int32 and shape [2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1}}]]
+    2024-02-09 23:12:51.910159: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_4' with dtype float and shape [?,?,?,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_4}}]]
+    2024-02-09 23:12:51.910197: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_5' with dtype float and shape [?,?,?,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_5}}]]
+    2024-02-09 23:12:51.910233: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_6' with dtype float and shape [?,1,1,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_6}}]]
+    2024-02-09 23:12:51.910269: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_7' with dtype float and shape [?,?,?,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_7}}]]
+    2024-02-09 23:12:51.910319: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_8' with dtype float and shape [?,1,1,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_8}}]]
+    2024-02-09 23:12:51.910355: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_9' with dtype float and shape [32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_9}}]]
+    2024-02-09 23:12:51.910390: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_10' with dtype float and shape [?,1,1,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_10}}]]
+    2024-02-09 23:12:51.910425: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_11' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_11}}]]
+    2024-02-09 23:12:51.910461: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_12' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_12}}]]
+    2024-02-09 23:12:51.910498: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_13' with dtype float and shape [32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_13}}]]
+    2024-02-09 23:12:51.910535: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_14' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_14}}]]
+    2024-02-09 23:12:51.910572: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_15' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_15}}]]
+    2024-02-09 23:12:51.910608: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_16' with dtype float and shape [?,?,?,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_16}}]]
+    2024-02-09 23:12:51.910644: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_17' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_17}}]]
+    2024-02-09 23:12:51.910679: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_18' with dtype float and shape [?,?,?,2048]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_18}}]]
+    2024-02-09 23:12:51.910714: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_19' with dtype float and shape [?,?,?,2048]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_19}}]]
+    2024-02-09 23:12:51.910749: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_20' with dtype float and shape [?,?,?,2048]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_20}}]]
+    2024-02-09 23:12:51.910783: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_21' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_21}}]]
+    2024-02-09 23:12:51.910819: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_25' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_25}}]]
+    2024-02-09 23:12:51.910854: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_26' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_26}}]]
+    2024-02-09 23:12:51.910891: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_27' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_27}}]]
+    2024-02-09 23:12:51.910926: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_28' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_28}}]]
+    2024-02-09 23:12:51.910965: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_29' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_29}}]]
+    2024-02-09 23:12:51.911002: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_30' with dtype float and shape [32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_30}}]]
+    2024-02-09 23:12:51.911039: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_31' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_31}}]]
+    2024-02-09 23:12:51.911077: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_32' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_32}}]]
+    2024-02-09 23:12:51.911114: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_35' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_35}}]]
+    2024-02-09 23:12:51.911152: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_36' with dtype float and shape [32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_36}}]]
+    2024-02-09 23:12:51.911190: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_37' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_37}}]]
+    2024-02-09 23:12:51.911228: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_38' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_38}}]]
+    2024-02-09 23:12:51.911266: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_39' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_39}}]]
+    2024-02-09 23:12:51.911303: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_40' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_40}}]]
+    2024-02-09 23:12:51.911340: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_41' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_41}}]]
+    2024-02-09 23:12:51.911377: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_42' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_42}}]]
+    2024-02-09 23:12:51.911414: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_44' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_44}}]]
+    2024-02-09 23:12:51.911450: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_45' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_45}}]]
+    2024-02-09 23:12:51.911488: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_48' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_48}}]]
+    2024-02-09 23:12:51.911525: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_49' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_49}}]]
+    2024-02-09 23:12:51.911561: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_50' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_50}}]]
+    2024-02-09 23:12:51.911597: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_51' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_51}}]]
+    2024-02-09 23:12:51.911634: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_52' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_52}}]]
+    2024-02-09 23:12:51.911670: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_53' with dtype float and shape [32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_53}}]]
+    2024-02-09 23:12:51.911707: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_54' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_54}}]]
+    2024-02-09 23:12:51.911744: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_57' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_57}}]]
+    2024-02-09 23:12:51.911780: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_58' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_58}}]]
+    2024-02-09 23:12:51.911817: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_59' with dtype float and shape [32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_59}}]]
+    2024-02-09 23:12:51.911854: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_60' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_60}}]]
+    2024-02-09 23:12:51.911891: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_61' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_61}}]]
+    2024-02-09 23:12:51.911940: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_62' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_62}}]]
+    2024-02-09 23:12:51.911976: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_63' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_63}}]]
+    2024-02-09 23:12:51.912011: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_64' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_64}}]]
+    2024-02-09 23:12:51.912047: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_65' with dtype float and shape [?,?,?,2048]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_65}}]]
+    2024-02-09 23:12:51.912083: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_69' with dtype float and shape [?,?,?,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_69}}]]
+    2024-02-09 23:12:51.912119: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_70' with dtype float and shape [?,?,?,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_70}}]]
+    2024-02-09 23:12:51.912154: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_71' with dtype float and shape [?,1,1,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_71}}]]
+    2024-02-09 23:12:51.912190: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_72' with dtype float and shape [?,?,?,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_72}}]]
+    2024-02-09 23:12:51.912225: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_73' with dtype float and shape [?,1,1,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_73}}]]
+    2024-02-09 23:12:51.912262: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_74' with dtype float and shape [32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_74}}]]
+    2024-02-09 23:12:51.912298: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_75' with dtype float and shape [?,1,1,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_75}}]]
+    2024-02-09 23:12:51.912333: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_76' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_76}}]]
+    2024-02-09 23:12:51.912368: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_79' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_79}}]]
+    2024-02-09 23:12:51.912403: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_80' with dtype float and shape [32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_80}}]]
+    2024-02-09 23:12:51.912439: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_81' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_81}}]]
+    2024-02-09 23:12:51.912474: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_82' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_82}}]]
+    2024-02-09 23:12:51.912510: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_83' with dtype float and shape [?,?,?,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_83}}]]
+    2024-02-09 23:12:51.912545: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_84' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_84}}]]
+    2024-02-09 23:12:51.912580: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_85' with dtype float and shape [?,?,?,2048]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_85}}]]
+    2024-02-09 23:12:51.912615: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_86' with dtype float and shape [?,?,?,2048]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_86}}]]
+    2024-02-09 23:12:51.912651: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_87' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_87}}]]
+    2024-02-09 23:12:51.912686: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_91' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_91}}]]
+    2024-02-09 23:12:51.912721: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_92' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_92}}]]
+    2024-02-09 23:12:51.912756: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_93' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_93}}]]
+    2024-02-09 23:12:51.912792: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_94' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_94}}]]
+    2024-02-09 23:12:51.912827: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_95' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_95}}]]
+    2024-02-09 23:12:51.912862: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_96' with dtype float and shape [32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_96}}]]
+    2024-02-09 23:12:51.912897: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_97' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_97}}]]
+    2024-02-09 23:12:51.912932: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_98' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_98}}]]
+    2024-02-09 23:12:51.912968: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_101' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_101}}]]
+    2024-02-09 23:12:51.913003: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_102' with dtype float and shape [32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_102}}]]
+    2024-02-09 23:12:51.913039: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_103' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_103}}]]
+    2024-02-09 23:12:51.913074: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_104' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_104}}]]
+    2024-02-09 23:12:51.913110: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_105' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_105}}]]
+    2024-02-09 23:12:51.913146: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_106' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_106}}]]
+    2024-02-09 23:12:51.913181: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_107' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_107}}]]
+    2024-02-09 23:12:51.913216: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_108' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_108}}]]
+    2024-02-09 23:12:51.913251: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_110' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_110}}]]
+    2024-02-09 23:12:51.913287: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_111' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_111}}]]
+    2024-02-09 23:12:51.913322: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_114' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_114}}]]
+    2024-02-09 23:12:51.913357: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_115' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_115}}]]
+    2024-02-09 23:12:51.913392: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_116' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_116}}]]
+    2024-02-09 23:12:51.913427: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_117' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_117}}]]
+    2024-02-09 23:12:51.913486: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_118' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_118}}]]
+    2024-02-09 23:12:51.913523: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_119' with dtype float and shape [32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_119}}]]
+    2024-02-09 23:12:51.913560: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_120' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_120}}]]
+    2024-02-09 23:12:51.913598: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_123' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_123}}]]
+    2024-02-09 23:12:51.913634: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_124' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_124}}]]
+    2024-02-09 23:12:51.913671: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_125' with dtype float and shape [32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_125}}]]
+    2024-02-09 23:12:51.913707: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_126' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_126}}]]
+    2024-02-09 23:12:51.913744: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_127' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_127}}]]
+    2024-02-09 23:12:51.913781: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_128' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_128}}]]
+    2024-02-09 23:12:51.913818: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_129' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_129}}]]
+    2024-02-09 23:12:51.913854: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_130' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_130}}]]
+    2024-02-09 23:12:51.913891: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_131' with dtype float and shape [?,?,?,2048]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_131}}]]
+    2024-02-09 23:12:51.913927: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_135' with dtype float and shape [?,?,?,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_135}}]]
+    2024-02-09 23:12:51.913964: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_136' with dtype float and shape [?,?,?,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_136}}]]
+    2024-02-09 23:12:51.914000: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_137' with dtype float and shape [?,1,1,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_137}}]]
+    2024-02-09 23:12:51.914037: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_138' with dtype float and shape [?,?,?,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_138}}]]
+    2024-02-09 23:12:51.914073: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_139' with dtype float and shape [?,1,1,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_139}}]]
+    2024-02-09 23:12:51.914110: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_140' with dtype float and shape [32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_140}}]]
+    2024-02-09 23:12:51.914146: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_141' with dtype float and shape [?,1,1,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_141}}]]
+    2024-02-09 23:12:51.914183: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_142' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_142}}]]
+    2024-02-09 23:12:51.914220: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_145' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_145}}]]
+    2024-02-09 23:12:51.914257: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_146' with dtype float and shape [32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_146}}]]
+    2024-02-09 23:12:51.914294: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_147' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_147}}]]
+    2024-02-09 23:12:51.914330: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_148' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_148}}]]
+    2024-02-09 23:12:51.914368: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_149' with dtype float and shape [?,?,?,32,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_149}}]]
+    2024-02-09 23:12:51.914404: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_150' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_150}}]]
+    2024-02-09 23:12:51.914441: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_151' with dtype float and shape [?,?,?,2048]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_151}}]]
+    2024-02-09 23:12:51.914477: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_152' with dtype float and shape [?,?,?,2048]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_152}}]]
+    2024-02-09 23:12:51.914514: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_153' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_153}}]]
+    2024-02-09 23:12:51.914550: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_155' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_155}}]]
+    2024-02-09 23:12:51.914586: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_161' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_161}}]]
+    2024-02-09 23:12:51.914623: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_162' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_162}}]]
+    2024-02-09 23:12:51.914660: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_163' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_163}}]]
+    2024-02-09 23:12:51.914696: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_164' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_164}}]]
+    2024-02-09 23:12:51.914744: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_165' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_165}}]]
+    2024-02-09 23:12:51.914779: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_166' with dtype float and shape [32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_166}}]]
+    2024-02-09 23:12:51.914814: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_167' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_167}}]]
+    2024-02-09 23:12:51.914849: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_168' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_168}}]]
+    2024-02-09 23:12:51.914884: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_173' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_173}}]]
+    2024-02-09 23:12:51.914920: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_174' with dtype float and shape [32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_174}}]]
+    2024-02-09 23:12:51.914954: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_175' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_175}}]]
+    2024-02-09 23:12:51.914990: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_176' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_176}}]]
+    2024-02-09 23:12:51.915026: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_177' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_177}}]]
+    2024-02-09 23:12:51.915061: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_178' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_178}}]]
+    2024-02-09 23:12:51.915097: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_179' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_179}}]]
+    2024-02-09 23:12:51.915133: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_180' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_180}}]]
+    2024-02-09 23:12:51.915168: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_182' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_182}}]]
+    2024-02-09 23:12:51.915204: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_183' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_183}}]]
+    2024-02-09 23:12:51.915239: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_186' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_186}}]]
+    2024-02-09 23:12:51.915274: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_187' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_187}}]]
+    2024-02-09 23:12:51.915310: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_188' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_188}}]]
+    2024-02-09 23:12:51.915345: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_189' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_189}}]]
+    2024-02-09 23:12:51.915381: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_190' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_190}}]]
+    2024-02-09 23:12:51.915433: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_191' with dtype float and shape [32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_191}}]]
+    2024-02-09 23:12:51.915470: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_192' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_192}}]]
+    2024-02-09 23:12:51.915511: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_195' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_195}}]]
+    2024-02-09 23:12:51.915547: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_196' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_196}}]]
+    2024-02-09 23:12:51.915583: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_197' with dtype float and shape [32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_197}}]]
+    2024-02-09 23:12:51.915620: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_198' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_198}}]]
+    2024-02-09 23:12:51.915657: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_199' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_199}}]]
+    2024-02-09 23:12:51.915694: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_200' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_200}}]]
+    2024-02-09 23:12:51.915731: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_201' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_201}}]]
+    2024-02-09 23:12:51.915767: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_202' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_202}}]]
+    2024-02-09 23:12:51.915804: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_206' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_206}}]]
+    2024-02-09 23:12:51.915840: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_207' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_207}}]]
+    2024-02-09 23:12:51.915878: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_208' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_208}}]]
+    2024-02-09 23:12:51.915914: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_209' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_209}}]]
+    2024-02-09 23:12:51.915950: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_210' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_210}}]]
+    2024-02-09 23:12:51.915987: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_211' with dtype float and shape [32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_211}}]]
+    2024-02-09 23:12:51.916024: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_212' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_212}}]]
+    2024-02-09 23:12:51.916061: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_213' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_213}}]]
+    2024-02-09 23:12:51.916098: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_216' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_216}}]]
+    2024-02-09 23:12:51.916135: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_217' with dtype float and shape [32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_217}}]]
+    2024-02-09 23:12:51.916171: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_218' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_218}}]]
+    2024-02-09 23:12:51.916208: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_219' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_219}}]]
+    2024-02-09 23:12:51.916246: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_220' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_220}}]]
+    2024-02-09 23:12:51.916282: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_221' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_221}}]]
+    2024-02-09 23:12:51.916319: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_222' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_222}}]]
+    2024-02-09 23:12:51.916355: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_223' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_223}}]]
+    2024-02-09 23:12:51.916393: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_224' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_224}}]]
+    2024-02-09 23:12:51.916429: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_225' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_225}}]]
+    2024-02-09 23:12:51.916466: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_229' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_229}}]]
+    2024-02-09 23:12:51.916503: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_230' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_230}}]]
+    2024-02-09 23:12:51.916540: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_231' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_231}}]]
+    2024-02-09 23:12:51.916576: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_232' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_232}}]]
+    2024-02-09 23:12:51.916623: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_233' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_233}}]]
+    2024-02-09 23:12:51.916659: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_234' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_234}}]]
+    2024-02-09 23:12:51.916695: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_235' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_235}}]]
+    2024-02-09 23:12:51.916730: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_236' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_236}}]]
+    2024-02-09 23:12:51.916766: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_239' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_239}}]]
+    2024-02-09 23:12:51.916801: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_240' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_240}}]]
+    2024-02-09 23:12:51.916838: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_241' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_241}}]]
+    2024-02-09 23:12:51.916873: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_242' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_242}}]]
+    2024-02-09 23:12:51.916909: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_243' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_243}}]]
+    2024-02-09 23:12:51.916944: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_244' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_244}}]]
+    2024-02-09 23:12:51.916979: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_245' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_245}}]]
+    2024-02-09 23:12:51.917015: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_246' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_246}}]]
+    2024-02-09 23:12:51.917051: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_248' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_248}}]]
+    2024-02-09 23:12:51.917088: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_249' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_249}}]]
+    2024-02-09 23:12:51.917123: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_252' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_252}}]]
+    2024-02-09 23:12:51.917159: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_253' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_253}}]]
+    2024-02-09 23:12:51.917195: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_254' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_254}}]]
+    2024-02-09 23:12:51.917231: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_255' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_255}}]]
+    2024-02-09 23:12:51.917266: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_256' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_256}}]]
+    2024-02-09 23:12:51.917302: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_257' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_257}}]]
+    2024-02-09 23:12:51.917338: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_258' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_258}}]]
+    2024-02-09 23:12:51.917374: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_261' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_261}}]]
+    2024-02-09 23:12:51.917410: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_262' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_262}}]]
+    2024-02-09 23:12:51.917450: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_263' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_263}}]]
+    2024-02-09 23:12:51.917505: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_264' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_264}}]]
+    2024-02-09 23:12:51.917542: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_265' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_265}}]]
+    2024-02-09 23:12:51.917580: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_266' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_266}}]]
+    2024-02-09 23:12:51.917617: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_267' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_267}}]]
+    2024-02-09 23:12:51.917655: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_268' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_268}}]]
+    2024-02-09 23:12:51.917693: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_269' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_269}}]]
+    2024-02-09 23:12:51.917731: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_273' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_273}}]]
+    2024-02-09 23:12:51.917768: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_274' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_274}}]]
+    2024-02-09 23:12:51.917805: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_275' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_275}}]]
+    2024-02-09 23:12:51.917843: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_276' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_276}}]]
+    2024-02-09 23:12:51.917880: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_277' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_277}}]]
+    2024-02-09 23:12:51.917916: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_278' with dtype float and shape [32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_278}}]]
+    2024-02-09 23:12:51.917953: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_279' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_279}}]]
+    2024-02-09 23:12:51.917991: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_280' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_280}}]]
+    2024-02-09 23:12:51.918028: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_283' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_283}}]]
+    2024-02-09 23:12:51.918064: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_284' with dtype float and shape [32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_284}}]]
+    2024-02-09 23:12:51.918102: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_285' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_285}}]]
+    2024-02-09 23:12:51.918139: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_286' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_286}}]]
+    2024-02-09 23:12:51.918176: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_287' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_287}}]]
+    2024-02-09 23:12:51.918213: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_288' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_288}}]]
+    2024-02-09 23:12:51.918250: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_289' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_289}}]]
+    2024-02-09 23:12:51.918287: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_290' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_290}}]]
+    2024-02-09 23:12:51.918324: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_291' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_291}}]]
+    2024-02-09 23:12:51.918360: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_295' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_295}}]]
+    2024-02-09 23:12:51.918397: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_296' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_296}}]]
+    2024-02-09 23:12:51.918434: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_297' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_297}}]]
+    2024-02-09 23:12:51.918472: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_298' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_298}}]]
+    2024-02-09 23:12:51.918509: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_299' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_299}}]]
+    2024-02-09 23:12:51.918547: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_300' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_300}}]]
+    2024-02-09 23:12:51.918585: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_301' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_301}}]]
+    2024-02-09 23:12:51.918622: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_302' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_302}}]]
+    2024-02-09 23:12:51.918659: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_305' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_305}}]]
+    2024-02-09 23:12:51.918706: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_306' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_306}}]]
+    2024-02-09 23:12:51.918741: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_307' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_307}}]]
+    2024-02-09 23:12:51.918778: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_308' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_308}}]]
+    2024-02-09 23:12:51.918814: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_309' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_309}}]]
+    2024-02-09 23:12:51.918850: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_310' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_310}}]]
+    2024-02-09 23:12:51.918885: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_311' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_311}}]]
+    2024-02-09 23:12:51.918920: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_312' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_312}}]]
+    2024-02-09 23:12:51.918956: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_314' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_314}}]]
+    2024-02-09 23:12:51.918991: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_315' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_315}}]]
+    2024-02-09 23:12:51.919026: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_318' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_318}}]]
+    2024-02-09 23:12:51.919062: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_319' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_319}}]]
+    2024-02-09 23:12:51.919097: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_320' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_320}}]]
+    2024-02-09 23:12:51.919133: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_321' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_321}}]]
+    2024-02-09 23:12:51.919169: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_322' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_322}}]]
+    2024-02-09 23:12:51.919204: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_323' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_323}}]]
+    2024-02-09 23:12:51.919240: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_324' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_324}}]]
+    2024-02-09 23:12:51.919275: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_327' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_327}}]]
+    2024-02-09 23:12:51.919311: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_328' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_328}}]]
+    2024-02-09 23:12:51.919347: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_329' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_329}}]]
+    2024-02-09 23:12:51.919383: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_330' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_330}}]]
+    2024-02-09 23:12:51.919418: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_331' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_331}}]]
+    2024-02-09 23:12:51.919456: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_332' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_332}}]]
+    2024-02-09 23:12:51.919492: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_333' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_333}}]]
+    2024-02-09 23:12:51.919527: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_334' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_334}}]]
+    2024-02-09 23:12:51.919563: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_335' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_335}}]]
+    2024-02-09 23:12:51.919599: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_339' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_339}}]]
+    2024-02-09 23:12:51.919634: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_340' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_340}}]]
+    2024-02-09 23:12:51.919671: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_341' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_341}}]]
+    2024-02-09 23:12:51.919707: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_342' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_342}}]]
+    2024-02-09 23:12:51.919743: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_343' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_343}}]]
+    2024-02-09 23:12:51.919779: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_344' with dtype float and shape [32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_344}}]]
+    2024-02-09 23:12:51.919814: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_345' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_345}}]]
+    2024-02-09 23:12:51.919849: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_346' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_346}}]]
+    2024-02-09 23:12:51.919884: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_349' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_349}}]]
+    2024-02-09 23:12:51.919918: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_350' with dtype float and shape [32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_350}}]]
+    2024-02-09 23:12:51.919954: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_351' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_351}}]]
+    2024-02-09 23:12:51.919989: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_352' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_352}}]]
+    2024-02-09 23:12:51.920025: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_353' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_353}}]]
+    2024-02-09 23:12:51.920061: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_354' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_354}}]]
+    2024-02-09 23:12:51.920096: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_355' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_355}}]]
+    2024-02-09 23:12:51.920132: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_356' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_356}}]]
+    2024-02-09 23:12:51.920167: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_357' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_357}}]]
+    2024-02-09 23:12:51.920203: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_361' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_361}}]]
+    2024-02-09 23:12:51.920239: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_362' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_362}}]]
+    2024-02-09 23:12:51.920274: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_363' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_363}}]]
+    2024-02-09 23:12:51.920310: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_364' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_364}}]]
+    2024-02-09 23:12:51.920346: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_365' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_365}}]]
+    2024-02-09 23:12:51.920381: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_366' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_366}}]]
+    2024-02-09 23:12:51.920415: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_367' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_367}}]]
+    2024-02-09 23:12:51.920451: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_368' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_368}}]]
+    2024-02-09 23:12:51.920487: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_371' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_371}}]]
+    2024-02-09 23:12:51.920522: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_372' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_372}}]]
+    2024-02-09 23:12:51.920557: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_373' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_373}}]]
+    2024-02-09 23:12:51.920592: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_374' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_374}}]]
+    2024-02-09 23:12:51.920628: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_375' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_375}}]]
+    2024-02-09 23:12:51.920663: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_376' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_376}}]]
+    2024-02-09 23:12:51.920699: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_377' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_377}}]]
+    2024-02-09 23:12:51.920735: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_378' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_378}}]]
+    2024-02-09 23:12:51.920771: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_380' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_380}}]]
+    2024-02-09 23:12:51.920807: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_381' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_381}}]]
+    2024-02-09 23:12:51.920842: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_384' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_384}}]]
+    2024-02-09 23:12:51.920878: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_385' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_385}}]]
+    2024-02-09 23:12:51.920914: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_386' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_386}}]]
+    2024-02-09 23:12:51.920950: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_387' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_387}}]]
+    2024-02-09 23:12:51.920985: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_388' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_388}}]]
+    2024-02-09 23:12:51.921022: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_389' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_389}}]]
+    2024-02-09 23:12:51.921057: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_390' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_390}}]]
+    2024-02-09 23:12:51.921092: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_393' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_393}}]]
+    2024-02-09 23:12:51.921128: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_394' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_394}}]]
+    2024-02-09 23:12:51.921164: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_395' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_395}}]]
+    2024-02-09 23:12:51.921199: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_396' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_396}}]]
+    2024-02-09 23:12:51.921235: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_397' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_397}}]]
+    2024-02-09 23:12:51.921271: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_398' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_398}}]]
+    2024-02-09 23:12:51.921306: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_399' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_399}}]]
+    2024-02-09 23:12:51.921341: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_400' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_400}}]]
+    2024-02-09 23:12:51.921376: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_401' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_401}}]]
+    2024-02-09 23:12:51.921412: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_405' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_405}}]]
+    2024-02-09 23:12:51.921453: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_406' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_406}}]]
+    2024-02-09 23:12:51.921507: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_407' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_407}}]]
+    2024-02-09 23:12:51.921545: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_408' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_408}}]]
+    2024-02-09 23:12:51.921582: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_409' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_409}}]]
+    2024-02-09 23:12:51.921619: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_410' with dtype float and shape [32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_410}}]]
+    2024-02-09 23:12:51.921657: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_411' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_411}}]]
+    2024-02-09 23:12:51.921694: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_412' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_412}}]]
+    2024-02-09 23:12:51.921731: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_415' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_415}}]]
+    2024-02-09 23:12:51.921768: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_416' with dtype float and shape [32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_416}}]]
+    2024-02-09 23:12:51.921806: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_417' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_417}}]]
+    2024-02-09 23:12:51.921843: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_418' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_418}}]]
+    2024-02-09 23:12:51.921881: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_419' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_419}}]]
+    2024-02-09 23:12:51.921918: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_420' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_420}}]]
+    2024-02-09 23:12:51.921956: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_421' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_421}}]]
+    2024-02-09 23:12:51.921993: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_422' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_422}}]]
+    2024-02-09 23:12:51.922030: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_423' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_423}}]]
+    2024-02-09 23:12:51.922067: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_427' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_427}}]]
+    2024-02-09 23:12:51.922104: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_428' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_428}}]]
+    2024-02-09 23:12:51.922141: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_429' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_429}}]]
+    2024-02-09 23:12:51.922178: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_430' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_430}}]]
+    2024-02-09 23:12:51.922216: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_431' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_431}}]]
+    2024-02-09 23:12:51.922252: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_432' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_432}}]]
+    2024-02-09 23:12:51.922289: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_433' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_433}}]]
+    2024-02-09 23:12:51.922325: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_434' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_434}}]]
+    2024-02-09 23:12:51.922363: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_437' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_437}}]]
+    2024-02-09 23:12:51.922399: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_438' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_438}}]]
+    2024-02-09 23:12:51.922437: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_439' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_439}}]]
+    2024-02-09 23:12:51.922473: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_440' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_440}}]]
+    2024-02-09 23:12:51.922511: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_441' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_441}}]]
+    2024-02-09 23:12:51.922550: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_442' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_442}}]]
+    2024-02-09 23:12:51.922587: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_443' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_443}}]]
+    2024-02-09 23:12:51.922624: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_444' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_444}}]]
+    2024-02-09 23:12:51.922661: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_446' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_446}}]]
+    2024-02-09 23:12:51.922698: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_447' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_447}}]]
+    2024-02-09 23:12:51.922736: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_450' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_450}}]]
+    2024-02-09 23:12:51.922774: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_451' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_451}}]]
+    2024-02-09 23:12:51.922821: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_452' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_452}}]]
+    2024-02-09 23:12:51.922858: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_453' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_453}}]]
+    2024-02-09 23:12:51.922893: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_454' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_454}}]]
+    2024-02-09 23:12:51.922928: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_455' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_455}}]]
+    2024-02-09 23:12:51.922964: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_456' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_456}}]]
+    2024-02-09 23:12:51.922999: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_459' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_459}}]]
+    2024-02-09 23:12:51.923035: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_460' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_460}}]]
+    2024-02-09 23:12:51.923071: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_461' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_461}}]]
+    2024-02-09 23:12:51.923106: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_462' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_462}}]]
+    2024-02-09 23:12:51.923142: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_463' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_463}}]]
+    2024-02-09 23:12:51.923179: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_464' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_464}}]]
+    2024-02-09 23:12:51.923214: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_465' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_465}}]]
+    2024-02-09 23:12:51.923251: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_466' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_466}}]]
+    2024-02-09 23:12:51.923286: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_467' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_467}}]]
+    2024-02-09 23:12:51.923322: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_471' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_471}}]]
+    2024-02-09 23:12:51.923358: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_472' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_472}}]]
+    2024-02-09 23:12:51.923394: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_473' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_473}}]]
+    2024-02-09 23:12:51.923429: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_474' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_474}}]]
+    2024-02-09 23:12:51.923465: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_475' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_475}}]]
+    2024-02-09 23:12:51.923501: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_476' with dtype float and shape [32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_476}}]]
+    2024-02-09 23:12:51.923537: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_477' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_477}}]]
+    2024-02-09 23:12:51.923573: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_478' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_478}}]]
+    2024-02-09 23:12:51.923609: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_481' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_481}}]]
+    2024-02-09 23:12:51.923645: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_482' with dtype float and shape [32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_482}}]]
+    2024-02-09 23:12:51.923680: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_483' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_483}}]]
+    2024-02-09 23:12:51.923716: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_484' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_484}}]]
+    2024-02-09 23:12:51.923752: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_485' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_485}}]]
+    2024-02-09 23:12:51.923788: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_486' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_486}}]]
+    2024-02-09 23:12:51.923824: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_487' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_487}}]]
+    2024-02-09 23:12:51.923860: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_488' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_488}}]]
+    2024-02-09 23:12:51.923896: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_489' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_489}}]]
+    2024-02-09 23:12:51.923932: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_493' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_493}}]]
+    2024-02-09 23:12:51.923968: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_494' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_494}}]]
+    2024-02-09 23:12:51.924004: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_495' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_495}}]]
+    2024-02-09 23:12:51.924040: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_496' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_496}}]]
+    2024-02-09 23:12:51.924076: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_497' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_497}}]]
+    2024-02-09 23:12:51.924112: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_498' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_498}}]]
+    2024-02-09 23:12:51.924148: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_499' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_499}}]]
+    2024-02-09 23:12:51.924185: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_500' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_500}}]]
+    2024-02-09 23:12:51.924221: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_503' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_503}}]]
+    2024-02-09 23:12:51.924256: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_504' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_504}}]]
+    2024-02-09 23:12:51.924292: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_505' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_505}}]]
+    2024-02-09 23:12:51.924328: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_506' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_506}}]]
+    2024-02-09 23:12:51.924365: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_507' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_507}}]]
+    2024-02-09 23:12:51.924402: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_508' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_508}}]]
+    2024-02-09 23:12:51.924438: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_509' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_509}}]]
+    2024-02-09 23:12:51.924474: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_510' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_510}}]]
+    2024-02-09 23:12:51.924510: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_512' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_512}}]]
+    2024-02-09 23:12:51.924546: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_513' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_513}}]]
+    2024-02-09 23:12:51.924581: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_516' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_516}}]]
+    2024-02-09 23:12:51.924618: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_517' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_517}}]]
+    2024-02-09 23:12:51.924654: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_518' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_518}}]]
+    2024-02-09 23:12:51.924690: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_519' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_519}}]]
+    2024-02-09 23:12:51.924726: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_520' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_520}}]]
+    2024-02-09 23:12:51.924764: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_521' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_521}}]]
+    2024-02-09 23:12:51.924800: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_522' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_522}}]]
+    2024-02-09 23:12:51.924836: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_525' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_525}}]]
+    2024-02-09 23:12:51.924872: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_526' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_526}}]]
+    2024-02-09 23:12:51.924908: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_527' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_527}}]]
+    2024-02-09 23:12:51.924945: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_528' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_528}}]]
+    2024-02-09 23:12:51.924982: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_529' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_529}}]]
+    2024-02-09 23:12:51.925019: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_530' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_530}}]]
+    2024-02-09 23:12:51.925054: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_531' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_531}}]]
+    2024-02-09 23:12:51.925091: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_532' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_532}}]]
+    2024-02-09 23:12:51.925127: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_533' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_533}}]]
+    2024-02-09 23:12:51.925164: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_537' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_537}}]]
+    2024-02-09 23:12:51.925201: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_538' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_538}}]]
+    2024-02-09 23:12:51.925237: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_539' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_539}}]]
+    2024-02-09 23:12:51.925273: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_540' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_540}}]]
+    2024-02-09 23:12:51.925309: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_541' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_541}}]]
+    2024-02-09 23:12:51.925345: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_542' with dtype float and shape [32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_542}}]]
+    2024-02-09 23:12:51.925381: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_543' with dtype float and shape [?,1,1,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_543}}]]
+    2024-02-09 23:12:51.925418: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_544' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_544}}]]
+    2024-02-09 23:12:51.925475: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_547' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_547}}]]
+    2024-02-09 23:12:51.925514: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_548' with dtype float and shape [32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_548}}]]
+    2024-02-09 23:12:51.925552: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_549' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_549}}]]
+    2024-02-09 23:12:51.925590: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_550' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_550}}]]
+    2024-02-09 23:12:51.925628: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_551' with dtype float and shape [?,?,?,32,32]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_551}}]]
+    2024-02-09 23:12:51.925666: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_552' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_552}}]]
+    2024-02-09 23:12:51.925704: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_553' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_553}}]]
+    2024-02-09 23:12:51.925744: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_554' with dtype float and shape [?,?,?,1024]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_554}}]]
+    2024-02-09 23:12:51.925781: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_555' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_555}}]]
+    2024-02-09 23:12:51.925818: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_557' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_557}}]]
+    2024-02-09 23:12:51.925855: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_563' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_563}}]]
+    2024-02-09 23:12:51.925893: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_564' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_564}}]]
+    2024-02-09 23:12:51.925929: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_565' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_565}}]]
+    2024-02-09 23:12:51.925967: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_566' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_566}}]]
+    2024-02-09 23:12:51.926005: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_567' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_567}}]]
+    2024-02-09 23:12:51.926043: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_568' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_568}}]]
+    2024-02-09 23:12:51.926081: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_569' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_569}}]]
+    2024-02-09 23:12:51.926119: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_570' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_570}}]]
+    2024-02-09 23:12:51.926156: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_575' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_575}}]]
+    2024-02-09 23:12:51.926194: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_576' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_576}}]]
+    2024-02-09 23:12:51.926232: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_577' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_577}}]]
+    2024-02-09 23:12:51.926270: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_578' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_578}}]]
+    2024-02-09 23:12:51.926307: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_579' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_579}}]]
+    2024-02-09 23:12:51.926344: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_580' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_580}}]]
+    2024-02-09 23:12:51.926382: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_581' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_581}}]]
+    2024-02-09 23:12:51.926419: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_582' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_582}}]]
+    2024-02-09 23:12:51.926456: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_584' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_584}}]]
+    2024-02-09 23:12:51.926493: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_585' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_585}}]]
+    2024-02-09 23:12:51.926531: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_588' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_588}}]]
+    2024-02-09 23:12:51.926568: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_589' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_589}}]]
+    2024-02-09 23:12:51.926606: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_590' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_590}}]]
+    2024-02-09 23:12:51.926643: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_591' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_591}}]]
+    2024-02-09 23:12:51.926691: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_592' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_592}}]]
+    2024-02-09 23:12:51.926728: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_593' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_593}}]]
+    2024-02-09 23:12:51.926764: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_594' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_594}}]]
+    2024-02-09 23:12:51.926800: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_597' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_597}}]]
+    2024-02-09 23:12:51.926836: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_598' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_598}}]]
+    2024-02-09 23:12:51.926872: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_599' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_599}}]]
+    2024-02-09 23:12:51.926909: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_600' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_600}}]]
+    2024-02-09 23:12:51.926945: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_601' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_601}}]]
+    2024-02-09 23:12:51.926981: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_602' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_602}}]]
+    2024-02-09 23:12:51.927017: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_603' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_603}}]]
+    2024-02-09 23:12:51.927053: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_604' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_604}}]]
+    2024-02-09 23:12:51.927090: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_608' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_608}}]]
+    2024-02-09 23:12:51.927127: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_609' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_609}}]]
+    2024-02-09 23:12:51.927163: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_610' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_610}}]]
+    2024-02-09 23:12:51.927199: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_611' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_611}}]]
+    2024-02-09 23:12:51.927234: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_612' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_612}}]]
+    2024-02-09 23:12:51.927270: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_613' with dtype float and shape [32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_613}}]]
+    2024-02-09 23:12:51.927306: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_614' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_614}}]]
+    2024-02-09 23:12:51.927343: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_615' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_615}}]]
+    2024-02-09 23:12:51.927379: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_618' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_618}}]]
+    2024-02-09 23:12:51.927415: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_619' with dtype float and shape [32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_619}}]]
+    2024-02-09 23:12:51.927450: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_620' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_620}}]]
+    2024-02-09 23:12:51.927486: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_621' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_621}}]]
+    2024-02-09 23:12:51.927523: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_622' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_622}}]]
+    2024-02-09 23:12:51.927559: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_623' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_623}}]]
+    2024-02-09 23:12:51.927595: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_624' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_624}}]]
+    2024-02-09 23:12:51.927631: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_625' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_625}}]]
+    2024-02-09 23:12:51.927667: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_626' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_626}}]]
+    2024-02-09 23:12:51.927703: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_627' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_627}}]]
+    2024-02-09 23:12:51.927739: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_631' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_631}}]]
+    2024-02-09 23:12:51.927775: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_632' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_632}}]]
+    2024-02-09 23:12:51.927811: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_633' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_633}}]]
+    2024-02-09 23:12:51.927847: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_634' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_634}}]]
+    2024-02-09 23:12:51.927884: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_635' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_635}}]]
+    2024-02-09 23:12:51.927919: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_636' with dtype float and shape [32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_636}}]]
+    2024-02-09 23:12:51.927955: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_637' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_637}}]]
+    2024-02-09 23:12:51.927990: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_638' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_638}}]]
+    2024-02-09 23:12:51.928026: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_641' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_641}}]]
+    2024-02-09 23:12:51.928062: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_642' with dtype float and shape [32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_642}}]]
+    2024-02-09 23:12:51.928097: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_643' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_643}}]]
+    2024-02-09 23:12:51.928133: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_644' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_644}}]]
+    2024-02-09 23:12:51.928169: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_645' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_645}}]]
+    2024-02-09 23:12:51.928204: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_646' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_646}}]]
+    2024-02-09 23:12:51.928258: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_647' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_647}}]]
+    2024-02-09 23:12:51.928296: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_648' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_648}}]]
+    2024-02-09 23:12:51.928332: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_650' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_650}}]]
+    2024-02-09 23:12:51.928370: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_651' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_651}}]]
+    2024-02-09 23:12:51.928406: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_654' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_654}}]]
+    2024-02-09 23:12:51.928444: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_655' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_655}}]]
+    2024-02-09 23:12:51.928482: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_656' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_656}}]]
+    2024-02-09 23:12:51.928519: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_657' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_657}}]]
+    2024-02-09 23:12:51.928557: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_658' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_658}}]]
+    2024-02-09 23:12:51.928593: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_659' with dtype float and shape [32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_659}}]]
+    2024-02-09 23:12:51.928630: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_660' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_660}}]]
+    2024-02-09 23:12:51.928668: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_663' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_663}}]]
+    2024-02-09 23:12:51.928706: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_664' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_664}}]]
+    2024-02-09 23:12:51.928743: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_665' with dtype float and shape [32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_665}}]]
+    2024-02-09 23:12:51.928780: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_666' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_666}}]]
+    2024-02-09 23:12:51.928818: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_667' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_667}}]]
+    2024-02-09 23:12:51.928855: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_668' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_668}}]]
+    2024-02-09 23:12:51.928893: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_669' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_669}}]]
+    2024-02-09 23:12:51.928930: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_670' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_670}}]]
+    2024-02-09 23:12:51.928967: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_671' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_671}}]]
+    2024-02-09 23:12:51.929004: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_675' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_675}}]]
+    2024-02-09 23:12:51.929041: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_676' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_676}}]]
+    2024-02-09 23:12:51.929079: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_677' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_677}}]]
+    2024-02-09 23:12:51.929116: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_678' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_678}}]]
+    2024-02-09 23:12:51.929154: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_679' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_679}}]]
+    2024-02-09 23:12:51.929191: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_680' with dtype float and shape [32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_680}}]]
+    2024-02-09 23:12:51.929228: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_681' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_681}}]]
+    2024-02-09 23:12:51.929265: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_682' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_682}}]]
+    2024-02-09 23:12:51.929303: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_685' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_685}}]]
+    2024-02-09 23:12:51.929341: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_686' with dtype float and shape [32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_686}}]]
+    2024-02-09 23:12:51.929379: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_687' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_687}}]]
+    2024-02-09 23:12:51.929416: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_688' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_688}}]]
+    2024-02-09 23:12:51.929459: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_689' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_689}}]]
+    2024-02-09 23:12:51.929497: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_690' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_690}}]]
+    2024-02-09 23:12:51.929534: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_691' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_691}}]]
+    2024-02-09 23:12:51.929571: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_692' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_692}}]]
+    2024-02-09 23:12:51.929608: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_693' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_693}}]]
+    2024-02-09 23:12:51.929645: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_697' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_697}}]]
+    2024-02-09 23:12:51.929683: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_698' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_698}}]]
+    2024-02-09 23:12:51.929721: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_699' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_699}}]]
+    2024-02-09 23:12:51.929758: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_700' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_700}}]]
+    2024-02-09 23:12:51.929794: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_701' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_701}}]]
+    2024-02-09 23:12:51.929833: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_702' with dtype float and shape [32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_702}}]]
+    2024-02-09 23:12:51.929870: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_703' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_703}}]]
+    2024-02-09 23:12:51.929908: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_704' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_704}}]]
+    2024-02-09 23:12:51.929945: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_707' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_707}}]]
+    2024-02-09 23:12:51.929983: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_708' with dtype float and shape [32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_708}}]]
+    2024-02-09 23:12:51.930020: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_709' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_709}}]]
+    2024-02-09 23:12:51.930058: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_710' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_710}}]]
+    2024-02-09 23:12:51.930097: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_711' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_711}}]]
+    2024-02-09 23:12:51.930134: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_712' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_712}}]]
+    2024-02-09 23:12:51.930172: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_713' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_713}}]]
+    2024-02-09 23:12:51.930209: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_714' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_714}}]]
+    2024-02-09 23:12:51.930246: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_716' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_716}}]]
+    2024-02-09 23:12:51.930283: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_717' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_717}}]]
+    2024-02-09 23:12:51.930321: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_720' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_720}}]]
+    2024-02-09 23:12:51.930358: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_721' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_721}}]]
+    2024-02-09 23:12:51.930395: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_722' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_722}}]]
+    2024-02-09 23:12:51.930433: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_723' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_723}}]]
+    2024-02-09 23:12:51.930470: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_724' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_724}}]]
+    2024-02-09 23:12:51.930508: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_725' with dtype float and shape [32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_725}}]]
+    2024-02-09 23:12:51.930546: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_726' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_726}}]]
+    2024-02-09 23:12:51.930584: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_729' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_729}}]]
+    2024-02-09 23:12:51.930621: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_730' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_730}}]]
+    2024-02-09 23:12:51.930659: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_731' with dtype float and shape [32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_731}}]]
+    2024-02-09 23:12:51.930706: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_732' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_732}}]]
+    2024-02-09 23:12:51.930743: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_733' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_733}}]]
+    2024-02-09 23:12:51.930780: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_734' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_734}}]]
+    2024-02-09 23:12:51.930817: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_735' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_735}}]]
+    2024-02-09 23:12:51.930853: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_736' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_736}}]]
+    2024-02-09 23:12:51.930889: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_737' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_737}}]]
+    2024-02-09 23:12:51.930926: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_741' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_741}}]]
+    2024-02-09 23:12:51.930963: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_742' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_742}}]]
+    2024-02-09 23:12:51.931000: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_743' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_743}}]]
+    2024-02-09 23:12:51.931037: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_744' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_744}}]]
+    2024-02-09 23:12:51.931073: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_745' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_745}}]]
+    2024-02-09 23:12:51.931110: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_746' with dtype float and shape [32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_746}}]]
+    2024-02-09 23:12:51.931146: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_747' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_747}}]]
+    2024-02-09 23:12:51.931183: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_748' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_748}}]]
+    2024-02-09 23:12:51.931219: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_751' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_751}}]]
+    2024-02-09 23:12:51.931256: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_752' with dtype float and shape [32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_752}}]]
+    2024-02-09 23:12:51.931292: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_753' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_753}}]]
+    2024-02-09 23:12:51.931328: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_754' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_754}}]]
+    2024-02-09 23:12:51.931364: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_755' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_755}}]]
+    2024-02-09 23:12:51.931400: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_756' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_756}}]]
+    2024-02-09 23:12:51.931437: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_757' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_757}}]]
+    2024-02-09 23:12:51.931473: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_758' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_758}}]]
+    2024-02-09 23:12:51.931510: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_759' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_759}}]]
+    2024-02-09 23:12:51.931546: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_763' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_763}}]]
+    2024-02-09 23:12:51.931582: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_764' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_764}}]]
+    2024-02-09 23:12:51.931619: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_765' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_765}}]]
+    2024-02-09 23:12:51.931656: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_766' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_766}}]]
+    2024-02-09 23:12:51.931694: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_767' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_767}}]]
+    2024-02-09 23:12:51.931730: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_768' with dtype float and shape [32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_768}}]]
+    2024-02-09 23:12:51.931766: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_769' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_769}}]]
+    2024-02-09 23:12:51.931802: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_770' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_770}}]]
+    2024-02-09 23:12:51.931838: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_773' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_773}}]]
+    2024-02-09 23:12:51.931875: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_774' with dtype float and shape [32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_774}}]]
+    2024-02-09 23:12:51.931911: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_775' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_775}}]]
+    2024-02-09 23:12:51.931948: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_776' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_776}}]]
+    2024-02-09 23:12:51.931984: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_777' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_777}}]]
+    2024-02-09 23:12:51.932021: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_778' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_778}}]]
+    2024-02-09 23:12:51.932058: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_779' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_779}}]]
+    2024-02-09 23:12:51.932095: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_780' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_780}}]]
+    2024-02-09 23:12:51.932129: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_782' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_782}}]]
+    2024-02-09 23:12:51.932165: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_783' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_783}}]]
+    2024-02-09 23:12:51.932202: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_786' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_786}}]]
+    2024-02-09 23:12:51.932239: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_787' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_787}}]]
+    2024-02-09 23:12:51.932275: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_788' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_788}}]]
+    2024-02-09 23:12:51.932308: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_789' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_789}}]]
+    2024-02-09 23:12:51.932342: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_790' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_790}}]]
+    2024-02-09 23:12:51.932378: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_791' with dtype float and shape [32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_791}}]]
+    2024-02-09 23:12:51.932414: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_792' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_792}}]]
+    2024-02-09 23:12:51.932451: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_795' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_795}}]]
+    2024-02-09 23:12:51.932488: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_796' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_796}}]]
+    2024-02-09 23:12:51.932524: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_797' with dtype float and shape [32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_797}}]]
+    2024-02-09 23:12:51.932557: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_798' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_798}}]]
+    2024-02-09 23:12:51.932594: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_799' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_799}}]]
+    2024-02-09 23:12:51.932631: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_800' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_800}}]]
+    2024-02-09 23:12:51.932667: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_801' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_801}}]]
+    2024-02-09 23:12:51.932703: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_802' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_802}}]]
+    2024-02-09 23:12:51.932739: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_803' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_803}}]]
+    2024-02-09 23:12:51.932776: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_807' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_807}}]]
+    2024-02-09 23:12:51.932812: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_808' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_808}}]]
+    2024-02-09 23:12:51.932848: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_809' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_809}}]]
+    2024-02-09 23:12:51.932885: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_810' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_810}}]]
+    2024-02-09 23:12:51.932921: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_811' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_811}}]]
+    2024-02-09 23:12:51.932959: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_812' with dtype float and shape [32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_812}}]]
+    2024-02-09 23:12:51.932992: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_813' with dtype float and shape [?,1,1,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_813}}]]
+    2024-02-09 23:12:51.933029: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_814' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_814}}]]
+    2024-02-09 23:12:51.933066: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_817' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_817}}]]
+    2024-02-09 23:12:51.933102: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_818' with dtype float and shape [32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_818}}]]
+    2024-02-09 23:12:51.933137: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_819' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_819}}]]
+    2024-02-09 23:12:51.933175: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_820' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_820}}]]
+    2024-02-09 23:12:51.933212: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_821' with dtype float and shape [?,?,?,32,16]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_821}}]]
+    2024-02-09 23:12:51.933245: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_822' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_822}}]]
+    2024-02-09 23:12:51.933279: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_823' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_823}}]]
+    2024-02-09 23:12:51.933315: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_824' with dtype float and shape [?,?,?,512]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_824}}]]
+    2024-02-09 23:12:51.933352: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_825' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_825}}]]
+    2024-02-09 23:12:51.933389: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_827' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_827}}]]
+    2024-02-09 23:12:51.933426: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_833' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_833}}]]
+    2024-02-09 23:12:51.933485: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_834' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_834}}]]
+    2024-02-09 23:12:51.933524: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_835' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_835}}]]
+    2024-02-09 23:12:51.933563: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_836' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_836}}]]
+    2024-02-09 23:12:51.933598: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_837' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_837}}]]
+    2024-02-09 23:12:51.933632: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_838' with dtype float and shape [32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_838}}]]
+    2024-02-09 23:12:51.933667: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_839' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_839}}]]
+    2024-02-09 23:12:51.933704: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_840' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_840}}]]
+    2024-02-09 23:12:51.933739: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_845' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_845}}]]
+    2024-02-09 23:12:51.933774: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_846' with dtype float and shape [32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_846}}]]
+    2024-02-09 23:12:51.933809: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_847' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_847}}]]
+    2024-02-09 23:12:51.933847: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_848' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_848}}]]
+    2024-02-09 23:12:51.933886: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_849' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_849}}]]
+    2024-02-09 23:12:51.933923: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_850' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_850}}]]
+    2024-02-09 23:12:51.933962: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_851' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_851}}]]
+    2024-02-09 23:12:51.933999: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_852' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_852}}]]
+    2024-02-09 23:12:51.934034: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_854' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_854}}]]
+    2024-02-09 23:12:51.934069: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_855' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_855}}]]
+    2024-02-09 23:12:51.934107: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_858' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_858}}]]
+    2024-02-09 23:12:51.934145: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_859' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_859}}]]
+    2024-02-09 23:12:51.934183: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_860' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_860}}]]
+    2024-02-09 23:12:51.934217: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_861' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_861}}]]
+    2024-02-09 23:12:51.934253: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_862' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_862}}]]
+    2024-02-09 23:12:51.934289: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_863' with dtype float and shape [32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_863}}]]
+    2024-02-09 23:12:51.934326: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_864' with dtype float and shape [?,1,1,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_864}}]]
+    2024-02-09 23:12:51.934364: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_867' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_867}}]]
+    2024-02-09 23:12:51.934402: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_868' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_868}}]]
+    2024-02-09 23:12:51.934441: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_869' with dtype float and shape [32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_869}}]]
+    2024-02-09 23:12:51.934476: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_870' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_870}}]]
+    2024-02-09 23:12:51.934511: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_871' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_871}}]]
+    2024-02-09 23:12:51.934549: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_872' with dtype float and shape [?,?,?,32,4]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_872}}]]
+    2024-02-09 23:12:51.934586: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_873' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_873}}]]
+    2024-02-09 23:12:51.934625: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_874' with dtype float and shape [?,?,?,128]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_874}}]]
+    2024-02-09 23:12:51.934660: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_878' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_878}}]]
+    2024-02-09 23:12:51.934705: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_879' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_879}}]]
+    2024-02-09 23:12:51.934741: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_880' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_880}}]]
+    2024-02-09 23:12:51.934778: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_881' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_881}}]]
+    2024-02-09 23:12:51.934815: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_882' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_882}}]]
+    2024-02-09 23:12:51.934851: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_883' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_883}}]]
+    2024-02-09 23:12:51.934887: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_884' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_884}}]]
+    2024-02-09 23:12:51.934923: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_885' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_885}}]]
+    2024-02-09 23:12:51.934960: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_888' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_888}}]]
+    2024-02-09 23:12:51.934996: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_889' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_889}}]]
+    2024-02-09 23:12:51.935032: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_890' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_890}}]]
+    2024-02-09 23:12:51.935069: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_891' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_891}}]]
+    2024-02-09 23:12:51.935106: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_892' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_892}}]]
+    2024-02-09 23:12:51.935140: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_893' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_893}}]]
+    2024-02-09 23:12:51.935174: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_894' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_894}}]]
+    2024-02-09 23:12:51.935210: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_895' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_895}}]]
+    2024-02-09 23:12:51.935246: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_896' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_896}}]]
+    2024-02-09 23:12:51.935283: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_897' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_897}}]]
+    2024-02-09 23:12:51.935316: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_901' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_901}}]]
+    2024-02-09 23:12:51.935351: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_902' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_902}}]]
+    2024-02-09 23:12:51.935386: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_903' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_903}}]]
+    2024-02-09 23:12:51.935423: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_904' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_904}}]]
+    2024-02-09 23:12:51.935458: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_905' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_905}}]]
+    2024-02-09 23:12:51.935494: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_906' with dtype float and shape [32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_906}}]]
+    2024-02-09 23:12:51.935530: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_907' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_907}}]]
+    2024-02-09 23:12:51.935567: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_908' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_908}}]]
+    2024-02-09 23:12:51.935603: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_911' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_911}}]]
+    2024-02-09 23:12:51.935639: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_912' with dtype float and shape [32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_912}}]]
+    2024-02-09 23:12:51.935676: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_913' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_913}}]]
+    2024-02-09 23:12:51.935712: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_914' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_914}}]]
+    2024-02-09 23:12:51.935748: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_915' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_915}}]]
+    2024-02-09 23:12:51.935784: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_916' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_916}}]]
+    2024-02-09 23:12:51.935821: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_917' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_917}}]]
+    2024-02-09 23:12:51.935854: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_918' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_918}}]]
+    2024-02-09 23:12:51.935891: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_920' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_920}}]]
+    2024-02-09 23:12:51.935927: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_921' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_921}}]]
+    2024-02-09 23:12:51.935963: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_924' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_924}}]]
+    2024-02-09 23:12:51.935999: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_925' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_925}}]]
+    2024-02-09 23:12:51.936036: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_926' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_926}}]]
+    2024-02-09 23:12:51.936072: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_927' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_927}}]]
+    2024-02-09 23:12:51.936108: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_928' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_928}}]]
+    2024-02-09 23:12:51.936145: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_929' with dtype float and shape [32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_929}}]]
+    2024-02-09 23:12:51.936182: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_930' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_930}}]]
+    2024-02-09 23:12:51.936218: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_933' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_933}}]]
+    2024-02-09 23:12:51.936252: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_934' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_934}}]]
+    2024-02-09 23:12:51.936289: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_935' with dtype float and shape [32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_935}}]]
+    2024-02-09 23:12:51.936325: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_936' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_936}}]]
+    2024-02-09 23:12:51.936361: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_937' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_937}}]]
+    2024-02-09 23:12:51.936398: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_938' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_938}}]]
+    2024-02-09 23:12:51.936435: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_939' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_939}}]]
+    2024-02-09 23:12:51.936471: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_940' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_940}}]]
+    2024-02-09 23:12:51.936504: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_941' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_941}}]]
+    2024-02-09 23:12:51.936541: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_945' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_945}}]]
+    2024-02-09 23:12:51.936576: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_946' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_946}}]]
+    2024-02-09 23:12:51.936613: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_947' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_947}}]]
+    2024-02-09 23:12:51.936649: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_948' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_948}}]]
+    2024-02-09 23:12:51.936686: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_949' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_949}}]]
+    2024-02-09 23:12:51.936722: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_950' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_950}}]]
+    2024-02-09 23:12:51.936758: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_951' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_951}}]]
+    2024-02-09 23:12:51.936794: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_952' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_952}}]]
+    2024-02-09 23:12:51.936830: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_955' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_955}}]]
+    2024-02-09 23:12:51.936867: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_956' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_956}}]]
+    2024-02-09 23:12:51.936904: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_957' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_957}}]]
+    2024-02-09 23:12:51.936941: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_958' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_958}}]]
+    2024-02-09 23:12:51.936977: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_959' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_959}}]]
+    2024-02-09 23:12:51.937014: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_960' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_960}}]]
+    2024-02-09 23:12:51.937051: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_961' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_961}}]]
+    2024-02-09 23:12:51.937088: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_962' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_962}}]]
+    2024-02-09 23:12:51.937125: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_963' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_963}}]]
+    2024-02-09 23:12:51.937161: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_967' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_967}}]]
+    2024-02-09 23:12:51.937196: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_968' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_968}}]]
+    2024-02-09 23:12:51.937232: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_969' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_969}}]]
+    2024-02-09 23:12:51.937268: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_970' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_970}}]]
+    2024-02-09 23:12:51.937305: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_971' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_971}}]]
+    2024-02-09 23:12:51.937341: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_972' with dtype float and shape [32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_972}}]]
+    2024-02-09 23:12:51.937377: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_973' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_973}}]]
+    2024-02-09 23:12:51.937413: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_974' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_974}}]]
+    2024-02-09 23:12:51.937454: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_977' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_977}}]]
+    2024-02-09 23:12:51.937509: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_978' with dtype float and shape [32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_978}}]]
+    2024-02-09 23:12:51.937548: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_979' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_979}}]]
+    2024-02-09 23:12:51.937585: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_980' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_980}}]]
+    2024-02-09 23:12:51.937624: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_981' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_981}}]]
+    2024-02-09 23:12:51.937662: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_982' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_982}}]]
+    2024-02-09 23:12:51.937700: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_983' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_983}}]]
+    2024-02-09 23:12:51.937738: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_984' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_984}}]]
+    2024-02-09 23:12:51.937775: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_986' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_986}}]]
+    2024-02-09 23:12:51.937813: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_987' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_987}}]]
+    2024-02-09 23:12:51.937851: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_990' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_990}}]]
+    2024-02-09 23:12:51.937889: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_991' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_991}}]]
+    2024-02-09 23:12:51.937928: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_992' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_992}}]]
+    2024-02-09 23:12:51.937966: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_993' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_993}}]]
+    2024-02-09 23:12:51.938004: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_994' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_994}}]]
+    2024-02-09 23:12:51.938042: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_995' with dtype float and shape [32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_995}}]]
+    2024-02-09 23:12:51.938080: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_996' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_996}}]]
+    2024-02-09 23:12:51.938117: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_999' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_999}}]]
+    2024-02-09 23:12:51.938154: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1000' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1000}}]]
+    2024-02-09 23:12:51.938193: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1001' with dtype float and shape [32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1001}}]]
+    2024-02-09 23:12:51.938231: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1002' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1002}}]]
+    2024-02-09 23:12:51.938270: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1003' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1003}}]]
+    2024-02-09 23:12:51.938308: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1004' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1004}}]]
+    2024-02-09 23:12:51.938346: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1005' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1005}}]]
+    2024-02-09 23:12:51.938384: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1006' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1006}}]]
+    2024-02-09 23:12:51.938421: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1007' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1007}}]]
+    2024-02-09 23:12:51.938459: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1011' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1011}}]]
+    2024-02-09 23:12:51.938498: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1012' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1012}}]]
+    2024-02-09 23:12:51.938536: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1013' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1013}}]]
+    2024-02-09 23:12:51.938574: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1014' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1014}}]]
+    2024-02-09 23:12:51.938612: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1015' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1015}}]]
+    2024-02-09 23:12:51.938650: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1016' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1016}}]]
+    2024-02-09 23:12:51.938697: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1017' with dtype float and shape [?,1,1,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1017}}]]
+    2024-02-09 23:12:51.938734: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1018' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1018}}]]
+    2024-02-09 23:12:51.938770: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1021' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1021}}]]
+    2024-02-09 23:12:51.938807: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1022' with dtype float and shape [32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1022}}]]
+    2024-02-09 23:12:51.938843: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1023' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1023}}]]
+    2024-02-09 23:12:51.938880: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1024' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1024}}]]
+    2024-02-09 23:12:51.938918: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1025' with dtype float and shape [?,?,?,32,8]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1025}}]]
+    2024-02-09 23:12:51.938954: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1026' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1026}}]]
+    2024-02-09 23:12:51.938991: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1027' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1027}}]]
+    2024-02-09 23:12:51.939025: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1028' with dtype float and shape [?,?,?,256]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1028}}]]
+    2024-02-09 23:12:51.939059: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1029' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1029}}]]
+    2024-02-09 23:12:51.939094: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1031' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1031}}]]
+    2024-02-09 23:12:51.939128: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1037' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1037}}]]
+    2024-02-09 23:12:51.939162: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1038' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1038}}]]
+    2024-02-09 23:12:51.939196: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1039' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1039}}]]
+    2024-02-09 23:12:51.939230: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1040' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1040}}]]
+    2024-02-09 23:12:51.939264: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1041' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1041}}]]
+    2024-02-09 23:12:51.939298: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1042' with dtype float and shape [32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1042}}]]
+    2024-02-09 23:12:51.939331: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1043' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1043}}]]
+    2024-02-09 23:12:51.939364: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1044' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1044}}]]
+    2024-02-09 23:12:51.939399: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1049' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1049}}]]
+    2024-02-09 23:12:51.939432: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1050' with dtype float and shape [32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1050}}]]
+    2024-02-09 23:12:51.939466: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1051' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1051}}]]
+    2024-02-09 23:12:51.939499: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1052' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1052}}]]
+    2024-02-09 23:12:51.939534: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1053' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1053}}]]
+    2024-02-09 23:12:51.939568: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1054' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1054}}]]
+    2024-02-09 23:12:51.939602: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1055' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1055}}]]
+    2024-02-09 23:12:51.939636: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1056' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1056}}]]
+    2024-02-09 23:12:51.939671: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1058' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1058}}]]
+    2024-02-09 23:12:51.939704: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1059' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1059}}]]
+    2024-02-09 23:12:51.939738: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1062' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1062}}]]
+    2024-02-09 23:12:51.939772: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1063' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1063}}]]
+    2024-02-09 23:12:51.939806: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1064' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1064}}]]
+    2024-02-09 23:12:51.939839: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1065' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1065}}]]
+    2024-02-09 23:12:51.939873: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1066' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1066}}]]
+    2024-02-09 23:12:51.939907: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1067' with dtype float and shape [32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1067}}]]
+    2024-02-09 23:12:51.939940: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1068' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1068}}]]
+    2024-02-09 23:12:51.939975: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1071' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1071}}]]
+    2024-02-09 23:12:51.940008: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1072' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1072}}]]
+    2024-02-09 23:12:51.940046: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1073' with dtype float and shape [32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1073}}]]
+    2024-02-09 23:12:51.940079: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1074' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1074}}]]
+    2024-02-09 23:12:51.940113: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1075' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1075}}]]
+    2024-02-09 23:12:51.940146: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1076' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1076}}]]
+    2024-02-09 23:12:51.940180: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1077' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1077}}]]
+    2024-02-09 23:12:51.940214: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1078' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1078}}]]
+    2024-02-09 23:12:51.940248: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1082' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1082}}]]
+    2024-02-09 23:12:51.940281: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1083' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1083}}]]
+    2024-02-09 23:12:51.940315: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1084' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1084}}]]
+    2024-02-09 23:12:51.940348: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1085' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1085}}]]
+    2024-02-09 23:12:51.940382: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1086' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1086}}]]
+    2024-02-09 23:12:51.940415: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1087' with dtype float and shape [32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1087}}]]
+    2024-02-09 23:12:51.940449: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1088' with dtype float and shape [?,1,1,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1088}}]]
+    2024-02-09 23:12:51.940483: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1089' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1089}}]]
+    2024-02-09 23:12:51.940516: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1092' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1092}}]]
+    2024-02-09 23:12:51.940550: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1093' with dtype float and shape [32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1093}}]]
+    2024-02-09 23:12:51.940584: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1094' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1094}}]]
+    2024-02-09 23:12:51.940618: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1095' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1095}}]]
+    2024-02-09 23:12:51.940652: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1096' with dtype float and shape [?,?,?,32,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1096}}]]
+    2024-02-09 23:12:51.940689: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1097' with dtype float and shape [?,1,1,32,1]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1097}}]]
+    2024-02-09 23:12:51.940723: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1098' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1098}}]]
+    2024-02-09 23:12:51.940757: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1101' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1101}}]]
+    2024-02-09 23:12:51.940791: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1102' with dtype float and shape [?,?,?,64]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1102}}]]
+    2024-02-09 23:12:51.940825: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1103' with dtype float and shape [?,?,?,3]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1103}}]]
+    2024-02-09 23:12:51.940859: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1105' with dtype int32 and shape [4,2]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1105}}]]
+    2024-02-09 23:12:51.940893: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1106' with dtype float and shape [?,?,?,3]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1106}}]]
+    2024-02-09 23:12:51.940927: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1111' with dtype float and shape [?,?,?,3]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1111}}]]
+    2024-02-09 23:12:51.940961: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1112' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1112}}]]
+    2024-02-09 23:12:51.940994: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1113' with dtype float
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1113}}]]
+    2024-02-09 23:12:51.941028: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1114' with dtype float and shape [?,?,?,3]
+    	 [[{{node gradients/StatefulPartitionedCall_grad/StatefulPartitionedCall_1114}}]]
+
+
+.. parsed-literal::
+
+
+  1/101 [..............................] - ETA: 45:51 - loss: 5.7132 - accuracy: 0.1797
+
+.. parsed-literal::
+
+    
+  2/101 [..............................] - ETA: 15:19 - loss: 5.3230 - accuracy: 0.1953
+
+.. parsed-literal::
+
+    
+  3/101 [..............................] - ETA: 15:06 - loss: 4.8895 - accuracy: 0.1875
+
+.. parsed-literal::
+
+    
+  4/101 [>.............................] - ETA: 14:56 - loss: 4.6401 - accuracy: 0.2012
+
+.. parsed-literal::
+
+    
+  5/101 [>.............................] - ETA: 14:47 - loss: 4.3587 - accuracy: 0.2188
+
+.. parsed-literal::
+
+    
+  6/101 [>.............................] - ETA: 14:38 - loss: 4.0658 - accuracy: 0.2409
+
+.. parsed-literal::
+
+    
+  7/101 [=>............................] - ETA: 14:29 - loss: 3.8257 - accuracy: 0.2623
+
+.. parsed-literal::
+
+    
+  8/101 [=>............................] - ETA: 14:19 - loss: 3.5840 - accuracy: 0.2920
+
+.. parsed-literal::
+
+    
+  9/101 [=>............................] - ETA: 14:10 - loss: 3.3894 - accuracy: 0.3142
+
+.. parsed-literal::
+
+    
+ 10/101 [=>............................] - ETA: 14:00 - loss: 3.1832 - accuracy: 0.3422
+
+.. parsed-literal::
+
+    
+ 11/101 [==>...........................] - ETA: 13:51 - loss: 2.9984 - accuracy: 0.3700
+
+.. parsed-literal::
+
+    
+ 12/101 [==>...........................] - ETA: 13:42 - loss: 2.8426 - accuracy: 0.3952
+
+.. parsed-literal::
+
+    
+ 13/101 [==>...........................] - ETA: 13:34 - loss: 2.6978 - accuracy: 0.4165
+
+.. parsed-literal::
+
+    
+ 14/101 [===>..........................] - ETA: 13:24 - loss: 2.5742 - accuracy: 0.4358
+
+.. parsed-literal::
+
+    
+ 15/101 [===>..........................] - ETA: 13:15 - loss: 2.4525 - accuracy: 0.4604
+
+.. parsed-literal::
+
+    
+ 16/101 [===>..........................] - ETA: 13:06 - loss: 2.3284 - accuracy: 0.4868
+
+.. parsed-literal::
+
+    
+ 17/101 [====>.........................] - ETA: 12:57 - loss: 2.2201 - accuracy: 0.5097
+
+.. parsed-literal::
+
+    
+ 18/101 [====>.........................] - ETA: 12:47 - loss: 2.1165 - accuracy: 0.5295
+
+.. parsed-literal::
+
+    
+ 19/101 [====>.........................] - ETA: 12:38 - loss: 2.0292 - accuracy: 0.5473
+
+.. parsed-literal::
+
+    
+ 20/101 [====>.........................] - ETA: 12:29 - loss: 1.9488 - accuracy: 0.5645
+
+.. parsed-literal::
+
+    
+ 21/101 [=====>........................] - ETA: 12:19 - loss: 1.8767 - accuracy: 0.5800
+
+.. parsed-literal::
+
+    
+ 22/101 [=====>........................] - ETA: 12:10 - loss: 1.8060 - accuracy: 0.5955
+
+.. parsed-literal::
+
+    
+ 23/101 [=====>........................] - ETA: 12:01 - loss: 1.7449 - accuracy: 0.6070
+
+.. parsed-literal::
+
+    
+ 24/101 [======>.......................] - ETA: 11:52 - loss: 1.6832 - accuracy: 0.6204
+
+.. parsed-literal::
+
+    
+ 25/101 [======>.......................] - ETA: 11:42 - loss: 1.6343 - accuracy: 0.6300
+
+.. parsed-literal::
+
+    
+ 26/101 [======>.......................] - ETA: 11:33 - loss: 1.5874 - accuracy: 0.6391
+
+.. parsed-literal::
+
+    
+ 27/101 [=======>......................] - ETA: 11:24 - loss: 1.5395 - accuracy: 0.6496
+
+.. parsed-literal::
+
+    
+ 28/101 [=======>......................] - ETA: 11:15 - loss: 1.4937 - accuracy: 0.6593
+
+.. parsed-literal::
+
+    
+ 29/101 [=======>......................] - ETA: 11:05 - loss: 1.4515 - accuracy: 0.6678
+
+.. parsed-literal::
+
+    
+ 30/101 [=======>......................] - ETA: 10:56 - loss: 1.4099 - accuracy: 0.6768
+
+.. parsed-literal::
+
+    
+ 31/101 [========>.....................] - ETA: 10:47 - loss: 1.3711 - accuracy: 0.6850
+
+.. parsed-literal::
+
+    
+ 32/101 [========>.....................] - ETA: 10:38 - loss: 1.3381 - accuracy: 0.6924
+
+.. parsed-literal::
+
+    
+ 33/101 [========>.....................] - ETA: 10:28 - loss: 1.3028 - accuracy: 0.7003
+
+.. parsed-literal::
+
+    
+ 34/101 [=========>....................] - ETA: 10:19 - loss: 1.2755 - accuracy: 0.7066
+
+.. parsed-literal::
+
+    
+ 35/101 [=========>....................] - ETA: 10:10 - loss: 1.2452 - accuracy: 0.7129
+
+.. parsed-literal::
+
+    
+ 36/101 [=========>....................] - ETA: 10:01 - loss: 1.2186 - accuracy: 0.7183
+
+.. parsed-literal::
+
+    
+ 37/101 [=========>....................] - ETA: 9:51 - loss: 1.1913 - accuracy: 0.7245
+
+.. parsed-literal::
+
+    
+ 38/101 [==========>...................] - ETA: 9:42 - loss: 1.1668 - accuracy: 0.7299
+
+.. parsed-literal::
+
+    
+ 39/101 [==========>...................] - ETA: 9:33 - loss: 1.1378 - accuracy: 0.7368
+
+.. parsed-literal::
+
+    
+ 40/101 [==========>...................] - ETA: 9:24 - loss: 1.1141 - accuracy: 0.7420
+
+.. parsed-literal::
+
+    
+ 41/101 [===========>..................] - ETA: 9:14 - loss: 1.0892 - accuracy: 0.7473
+
+.. parsed-literal::
+
+    
+ 42/101 [===========>..................] - ETA: 9:05 - loss: 1.0653 - accuracy: 0.7526
+
+.. parsed-literal::
+
+    
+ 43/101 [===========>..................] - ETA: 8:56 - loss: 1.0430 - accuracy: 0.7576
+
+.. parsed-literal::
+
+    
+ 44/101 [============>.................] - ETA: 8:47 - loss: 1.0243 - accuracy: 0.7617
+
+.. parsed-literal::
+
+    
+ 45/101 [============>.................] - ETA: 8:37 - loss: 1.0074 - accuracy: 0.7648
+
+.. parsed-literal::
+
+    
+ 46/101 [============>.................] - ETA: 8:28 - loss: 0.9881 - accuracy: 0.7689
+
+.. parsed-literal::
+
+    
+ 47/101 [============>.................] - ETA: 8:19 - loss: 0.9711 - accuracy: 0.7723
+
+.. parsed-literal::
+
+    
+ 48/101 [=============>................] - ETA: 8:10 - loss: 0.9529 - accuracy: 0.7765
+
+.. parsed-literal::
+
+    
+ 49/101 [=============>................] - ETA: 8:00 - loss: 0.9375 - accuracy: 0.7798
+
+.. parsed-literal::
+
+    
+ 50/101 [=============>................] - ETA: 7:51 - loss: 0.9236 - accuracy: 0.7823
+
+.. parsed-literal::
+
+    
+ 51/101 [==============>...............] - ETA: 7:42 - loss: 0.9096 - accuracy: 0.7854
+
+.. parsed-literal::
+
+    
+ 52/101 [==============>...............] - ETA: 7:33 - loss: 0.8955 - accuracy: 0.7880
+
+.. parsed-literal::
+
+    
+ 53/101 [==============>...............] - ETA: 7:23 - loss: 0.8823 - accuracy: 0.7913
+
+.. parsed-literal::
+
+    
+ 54/101 [===============>..............] - ETA: 7:14 - loss: 0.8676 - accuracy: 0.7948
+
+.. parsed-literal::
+
+    
+ 55/101 [===============>..............] - ETA: 7:05 - loss: 0.8529 - accuracy: 0.7983
+
+.. parsed-literal::
+
+    
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+
+.. parsed-literal::
+
+    
+ 57/101 [===============>..............] - ETA: 6:46 - loss: 0.8309 - accuracy: 0.8025
+
+.. parsed-literal::
+
+    
+ 58/101 [================>.............] - ETA: 6:37 - loss: 0.8184 - accuracy: 0.8051
+
+.. parsed-literal::
+
+    
+ 59/101 [================>.............] - ETA: 6:28 - loss: 0.8062 - accuracy: 0.8079
+
+.. parsed-literal::
+
+    
+ 60/101 [================>.............] - ETA: 6:19 - loss: 0.7953 - accuracy: 0.8102
+
+.. parsed-literal::
+
+    
+ 61/101 [=================>............] - ETA: 6:09 - loss: 0.7830 - accuracy: 0.8130
+
+.. parsed-literal::
+
+    
+ 62/101 [=================>............] - ETA: 6:00 - loss: 0.7715 - accuracy: 0.8157
+
+.. parsed-literal::
+
+    
+ 63/101 [=================>............] - ETA: 5:51 - loss: 0.7624 - accuracy: 0.8177
+
+.. parsed-literal::
+
+    
+ 64/101 [==================>...........] - ETA: 5:42 - loss: 0.7541 - accuracy: 0.8201
+
+.. parsed-literal::
+
+    
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+
+.. parsed-literal::
+
+    
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+
+.. parsed-literal::
+
+    
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+
+.. parsed-literal::
+
+    
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+
+.. parsed-literal::
+
+    
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+
+.. parsed-literal::
+
+    
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+
+.. parsed-literal::
+
+    
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+
+.. parsed-literal::
+
+    
+ 72/101 [====================>.........] - ETA: 4:28 - loss: 0.6889 - accuracy: 0.8345
+
+.. parsed-literal::
+
+    
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+
+.. parsed-literal::
+
+    
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+
+.. parsed-literal::
+
+    
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+
+.. parsed-literal::
+
+    
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+
+.. parsed-literal::
+
+    
+ 77/101 [=====================>........] - ETA: 3:41 - loss: 0.6537 - accuracy: 0.8422
+
+.. parsed-literal::
+
+    
+ 78/101 [======================>.......] - ETA: 3:32 - loss: 0.6460 - accuracy: 0.8442
+
+.. parsed-literal::
+
+    
+ 79/101 [======================>.......] - ETA: 3:23 - loss: 0.6388 - accuracy: 0.8458
+
+.. parsed-literal::
+
+    
+ 80/101 [======================>.......] - ETA: 3:14 - loss: 0.6318 - accuracy: 0.8474
+
+.. parsed-literal::
+
+    
+ 81/101 [=======================>......] - ETA: 3:04 - loss: 0.6246 - accuracy: 0.8491
+
+.. parsed-literal::
+
+    
+ 82/101 [=======================>......] - ETA: 2:55 - loss: 0.6179 - accuracy: 0.8506
+
+.. parsed-literal::
+
+    
+ 83/101 [=======================>......] - ETA: 2:46 - loss: 0.6120 - accuracy: 0.8519
+
+.. parsed-literal::
+
+    
+ 84/101 [=======================>......] - ETA: 2:37 - loss: 0.6050 - accuracy: 0.8536
+
+.. parsed-literal::
+
+    
+ 85/101 [========================>.....] - ETA: 2:27 - loss: 0.5985 - accuracy: 0.8551
+
+.. parsed-literal::
+
+    
+ 86/101 [========================>.....] - ETA: 2:18 - loss: 0.5934 - accuracy: 0.8564
+
+.. parsed-literal::
+
+    
+ 87/101 [========================>.....] - ETA: 2:09 - loss: 0.5879 - accuracy: 0.8575
+
+.. parsed-literal::
+
+    
+ 88/101 [=========================>....] - ETA: 2:00 - loss: 0.5820 - accuracy: 0.8588
+
+.. parsed-literal::
+
+    
+ 89/101 [=========================>....] - ETA: 1:50 - loss: 0.5760 - accuracy: 0.8601
+
+.. parsed-literal::
+
+    
+ 90/101 [=========================>....] - ETA: 1:41 - loss: 0.5715 - accuracy: 0.8612
+
+.. parsed-literal::
+
+    
+ 91/101 [==========================>...] - ETA: 1:32 - loss: 0.5654 - accuracy: 0.8626
+
+.. parsed-literal::
+
+    
+ 92/101 [==========================>...] - ETA: 1:23 - loss: 0.5595 - accuracy: 0.8640
+
+.. parsed-literal::
+
+    
+ 93/101 [==========================>...] - ETA: 1:13 - loss: 0.5544 - accuracy: 0.8653
+
+.. parsed-literal::
+
+    
+ 94/101 [==========================>...] - ETA: 1:04 - loss: 0.5514 - accuracy: 0.8661
+
+.. parsed-literal::
+
+    
+ 95/101 [===========================>..] - ETA: 55s - loss: 0.5462 - accuracy: 0.8673
+
+.. parsed-literal::
+
+    
+ 96/101 [===========================>..] - ETA: 46s - loss: 0.5411 - accuracy: 0.8685
+
+.. parsed-literal::
+
+    
+ 97/101 [===========================>..] - ETA: 36s - loss: 0.5361 - accuracy: 0.8696
+
+.. parsed-literal::
+
+    
+ 98/101 [============================>.] - ETA: 27s - loss: 0.5317 - accuracy: 0.8705
+
+.. parsed-literal::
+
+    
+ 99/101 [============================>.] - ETA: 18s - loss: 0.5282 - accuracy: 0.8714
+
+.. parsed-literal::
+
+    
+100/101 [============================>.] - ETA: 9s - loss: 0.5242 - accuracy: 0.8723
+
+.. parsed-literal::
+
+    
+101/101 [==============================] - ETA: 0s - loss: 0.5211 - accuracy: 0.8730
+
+.. parsed-literal::
+
+    2024-02-09 23:28:36.227849: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'Placeholder/_0' with dtype string and shape [1]
+    	 [[{{node Placeholder/_0}}]]
+    2024-02-09 23:28:36.228303: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'Placeholder/_1' with dtype string and shape [1]
+    	 [[{{node Placeholder/_1}}]]
+
+
+.. parsed-literal::
+
+    
+101/101 [==============================] - 966s 9s/step - loss: 0.5211 - accuracy: 0.8730 - val_loss: 0.0842 - val_accuracy: 0.9700
+
+
+.. parsed-literal::
+
+    WARNING:absl:Found untraced functions such as _update_step_xla while saving (showing 1 of 1). These functions will not be directly callable after loading.
+
+
+Perform model optimization (IR) step
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+
+
+.. code:: ipython3
+
+    ir_path = Path("./bit_ov_model/bit_m_r50x1_1.xml")
+    if not ir_path.exists():
+        print("Initiating model optimization..!!!")
+        ov_model = ov.convert_model("./bit_tf_model")
+        ov.save_model(ov_model, ir_path)
+    else:
+        print(f"IR model {ir_path} already exists.")
+
+
+.. parsed-literal::
+
+    Initiating model optimization..!!!
+
+
+Compute accuracy of the TF model
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+
+
+.. code:: ipython3
+
+    tf_model = tf.keras.models.load_model("./bit_tf_model/")
+
+    tf_predictions = []
+    gt_label = []
+
+    for _, label in validation_dataset:
+        for cls_label in label:
+            l_list = cls_label.numpy().tolist()
+            gt_label.append(l_list.index(1))
+
+    for img_batch, label_batch in validation_dataset:
+        tf_result_batch = tf_model.predict(img_batch, verbose=0)
+        for i in range(len(img_batch)):
+            tf_result = tf_result_batch[i]
+            tf_result = tf.reshape(tf_result, [-1])
+            top5_label_idx = np.argsort(tf_result)[-MAX_PREDS::][::-1]
+            tf_predictions.append(top5_label_idx)
+
+    # Convert the lists to NumPy arrays for accuracy calculation
+    tf_predictions = np.array(tf_predictions)
+    gt_label = np.array(gt_label)
+
+    tf_acc_score = accuracy_score(tf_predictions, gt_label)
+
+
+
+.. parsed-literal::
+
+    2024-02-09 23:29:14.482279: W tensorflow/core/common_runtime/graph_constructor.cc:812] Node 're_lu_48/PartitionedCall' has 1 outputs but the _output_shapes attribute specifies shapes for 2 outputs. Output shapes may be inaccurate.
+    2024-02-09 23:29:14.482323: W tensorflow/core/common_runtime/graph_constructor.cc:812] Node 'global_average_pooling2d/PartitionedCall' has 1 outputs but the _output_shapes attribute specifies shapes for 4 outputs. Output shapes may be inaccurate.
+
+
+.. parsed-literal::
+
+    2024-02-09 23:29:16.618466: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'Placeholder/_1' with dtype string and shape [1]
+    	 [[{{node Placeholder/_1}}]]
+    2024-02-09 23:29:16.618975: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'Placeholder/_4' with dtype int64 and shape [1]
+    	 [[{{node Placeholder/_4}}]]
+
+
+Compute accuracy of the OpenVINO model
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+
+
+.. code:: ipython3
+
+    ov_fp32_model = core.read_model("./bit_ov_model/bit_m_r50x1_1.xml")
+    ov_fp32_model.reshape([1, IMG_SIZE[0], IMG_SIZE[1], 3])
+
+    # Target device set to CPU (Other options Ex: AUTO/GPU/dGPU/)
+    compiled_model = ov.compile_model(ov_fp32_model)
+    output = compiled_model.outputs[0]
+
+    ov_predictions = []
+    for img_batch, _ in validation_dataset:
+        for image in img_batch:
+            image = tf.expand_dims(image, axis=0)
+            pred = compiled_model(image)[output]
+            ov_result = tf.reshape(pred, [-1])
+            top_label_idx = np.argsort(ov_result)[-MAX_PREDS::][::-1]
+            ov_predictions.append(top_label_idx)
+
+    fp32_acc_score = accuracy_score(ov_predictions, gt_label)
+
+
+Quantize OpenVINO model using NNCF
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+
+
+Model Quantization using NNCF
+
+1. Preprocessing and preparing validation samples for NNCF calibration
+2. Perform NNCF Quantization on OpenVINO FP32 model
+3. Serialize Quantized OpenVINO INT8 model
+
+.. code:: ipython3
+
+    def nncf_preprocessing(image, label):
+        image = tf.image.resize(image, IMG_SIZE)
+        image = image - MEAN_RGB
+        image = image / STDDEV_RGB
+        return image
+
+    val_ds = (validation_ds.map(nncf_preprocessing, num_parallel_calls=tf.data.experimental.AUTOTUNE)
+              .batch(1)
+              .prefetch(tf.data.experimental.AUTOTUNE))
+
+    calibration_dataset = nncf.Dataset(val_ds)
+
+    ov_fp32_model = core.read_model("./bit_ov_model/bit_m_r50x1_1.xml")
+
+    ov_int8_model = nncf.quantize(ov_fp32_model, calibration_dataset, fast_bias_correction=False)
+
+    ov.serialize(ov_int8_model, "./bit_ov_int8_model/bit_m_r50x1_1_ov_int8.xml")
+
+
+
+.. parsed-literal::
+
+    Output()
+
+
+.. parsed-literal::
+
+    2024-02-09 23:29:49.936057: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'Placeholder/_4' with dtype int64 and shape [1]
+    	 [[{{node Placeholder/_4}}]]
+    2024-02-09 23:29:49.937027: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'Placeholder/_2' with dtype string and shape [1]
+    	 [[{{node Placeholder/_2}}]]
+
+
+
+
+
+
+
+
+.. raw:: html
+
+    
+    

+
+
+
+
+.. parsed-literal::
+
+    Output()
+
+
+
+
+
+
+
+
+.. raw:: html
+
+    
+    

+
+
+
+Compute accuracy of the quantized model
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+
+
+.. code:: ipython3
+
+    nncf_quantized_model = core.read_model("./bit_ov_int8_model/bit_m_r50x1_1_ov_int8.xml")
+    nncf_quantized_model.reshape([1, IMG_SIZE[0], IMG_SIZE[1], 3])
+
+    # Target device set to CPU by default
+    compiled_model = ov.compile_model(nncf_quantized_model)
+    output = compiled_model.outputs[0]
+
+    ov_predictions = []
+    inp_tensor = nncf_quantized_model.inputs[0]
+    out_tensor = nncf_quantized_model.outputs[0]
+
+    for img_batch, _ in validation_dataset:
+        for image in img_batch:
+            image = tf.expand_dims(image, axis=0)
+            pred = compiled_model(image)[output]
+            ov_result = tf.reshape(pred, [-1])
+            top_label_idx = np.argsort(ov_result)[-MAX_PREDS::][::-1]
+            ov_predictions.append(top_label_idx)
+
+    int8_acc_score = accuracy_score(ov_predictions, gt_label)
+
+
+Compare FP32 and INT8 accuracy
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+
+
+.. code:: ipython3
+
+    print(f"Accuracy of the tensorflow model (fp32): {tf_acc_score * 100: .2f}%")
+    print(f"Accuracy of the OpenVINO optimized model (fp32): {fp32_acc_score * 100: .2f}%")
+    print(f"Accuracy of the OpenVINO quantized model (int8): {int8_acc_score * 100: .2f}%")
+    accuracy_drop = fp32_acc_score - int8_acc_score
+    print(f"Accuracy drop between OV FP32 and INT8 model: {accuracy_drop * 100:.1f}% ")
+
+
+.. parsed-literal::
+
+    Accuracy of the tensorflow model (fp32):  97.00%
+    Accuracy of the OpenVINO optimized model (fp32):  97.00%
+    Accuracy of the OpenVINO quantized model (int8):  97.00%
+    Accuracy drop between OV FP32 and INT8 model: 0.0%
+
+
+Compare inference results on one picture
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+
+
+.. code:: ipython3
+
+
+    # Accessing validation sample
+    sample_idx = 50
+    vds = datasets['validation']
+
+    if len(vds) > sample_idx:
+        sample = vds.take(sample_idx + 1).skip(sample_idx).as_numpy_iterator().next()
+    else:
+        print("Dataset does not have enough samples...!!!")
+
+    # Image data
+    sample_data = sample[0]
+
+    # Label info
+    sample_label = sample[1]
+
+    # Image data pre-processing
+    image = tf.image.resize(sample_data, IMG_SIZE)
+    image = tf.expand_dims(image, axis=0)
+    image = tf.cast(image, tf.float32) / 255.0
+
+    # OpenVINO inference
+    def ov_inference(model: ov.Model, image) -> str:
+        compiled_model = ov.compile_model(model)
+        output = compiled_model.outputs[0]
+        pred = compiled_model(image)[output]
+        ov_result = tf.reshape(pred, [-1])
+        pred_label = np.argsort(ov_result)[-MAX_PREDS::][::-1]
+        return pred_label
+
+    # OpenVINO FP32 model
+    ov_fp32_model = core.read_model("./bit_ov_model/bit_m_r50x1_1.xml")
+    ov_fp32_model.reshape([1, IMG_SIZE[0], IMG_SIZE[1], 3])
+
+    # OpenVINO INT8 model
+    ov_int8_model = core.read_model("./bit_ov_int8_model/bit_m_r50x1_1_ov_int8.xml")
+    ov_int8_model.reshape([1, IMG_SIZE[0], IMG_SIZE[1], 3])
+
+    # OpenVINO FP32 model inference
+    ov_fp32_pred_label = ov_inference(ov_fp32_model, image)
+
+    print(f"Predicted label for the sample picture by float (fp32) model: {label_func(class_idx_dict[int(ov_fp32_pred_label)])}\n")
+
+    # OpenVINO FP32 model inference
+    ov_int8_pred_label = ov_inference(ov_int8_model, image)
+    print(f"Predicted label for the sample picture by qunatized (int8) model: {label_func(class_idx_dict[int(ov_int8_pred_label)])}\n")
+
+    # Plotting the image sample with ground truth
+    plt.figure()
+    plt.imshow(sample_data)
+    plt.title(f"Ground truth: {label_func(class_idx_dict[sample_label])}")
+    plt.axis('off')
+    plt.show()
+
+
+
+.. parsed-literal::
+
+    2024-02-09 23:30:17.827051: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'Placeholder/_1' with dtype string and shape [1]
+    	 [[{{node Placeholder/_1}}]]
+    2024-02-09 23:30:17.827641: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'Placeholder/_0' with dtype string and shape [1]
+    	 [[{{node Placeholder/_0}}]]
+
+
+.. parsed-literal::
+
+    Predicted label for the sample picture by float (fp32) model: gas pump
+
+
+
+.. parsed-literal::
+
+    Predicted label for the sample picture by qunatized (int8) model: gas pump
+
+
+
+
+.. image:: 127-tensorflow-bit-image-classification-nncf-quantization-with-output_files/127-tensorflow-bit-image-classification-nncf-quantization-with-output_26_3.png
+
diff --git a/docs/notebooks/127-tensorflow-bit-image-classification-nncf-quantization-with-output_files/127-tensorflow-bit-image-classification-nncf-quantization-with-output_10_1.png b/docs/notebooks/127-tensorflow-bit-image-classification-nncf-quantization-with-output_files/127-tensorflow-bit-image-classification-nncf-quantization-with-output_10_1.png
new file mode 100644
index 00000000000000..f088ccfe15a5b5
--- /dev/null
+++ b/docs/notebooks/127-tensorflow-bit-image-classification-nncf-quantization-with-output_files/127-tensorflow-bit-image-classification-nncf-quantization-with-output_10_1.png
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:37f1a76ccf411397019d83e8344b79cdebf644f0f6ba6598141e72c6ee50c62b
+size 224517
diff --git a/docs/notebooks/127-tensorflow-bit-image-classification-nncf-quantization-with-output_files/127-tensorflow-bit-image-classification-nncf-quantization-with-output_26_3.png b/docs/notebooks/127-tensorflow-bit-image-classification-nncf-quantization-with-output_files/127-tensorflow-bit-image-classification-nncf-quantization-with-output_26_3.png
new file mode 100644
index 00000000000000..81d84c290fdeaf
--- /dev/null
+++ b/docs/notebooks/127-tensorflow-bit-image-classification-nncf-quantization-with-output_files/127-tensorflow-bit-image-classification-nncf-quantization-with-output_26_3.png
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:33f7798bd5dfbfa423dcca1d37eb7e29d0474e331105347cf0efdcfd695b850a
+size 335047
diff --git a/docs/notebooks/127-tensorflow-bit-image-classification-nncf-quantization-with-output_files/127-tensorflow-bit-image-classification-nncf-quantization-with-output_9_2.png b/docs/notebooks/127-tensorflow-bit-image-classification-nncf-quantization-with-output_files/127-tensorflow-bit-image-classification-nncf-quantization-with-output_9_2.png
new file mode 100644
index 00000000000000..93e050ce209466
--- /dev/null
+++ b/docs/notebooks/127-tensorflow-bit-image-classification-nncf-quantization-with-output_files/127-tensorflow-bit-image-classification-nncf-quantization-with-output_9_2.png
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6b354964f6b453eb9454e0e21ccb3e1275071464698af4693fc94235a1ca563e
+size 296205
diff --git a/docs/notebooks/201-vision-monodepth-with-output.rst b/docs/notebooks/201-vision-monodepth-with-output.rst
index 804b2230c8667e..233548081cb29d 100644
--- a/docs/notebooks/201-vision-monodepth-with-output.rst
+++ b/docs/notebooks/201-vision-monodepth-with-output.rst
@@ -3,7 +3,7 @@ Monodepth Estimation with OpenVINO
 
 This tutorial demonstrates Monocular Depth Estimation with MidasNet in
 OpenVINO. Model information can be found
-`here `__.
+`here `__.
 
 .. figure:: https://user-images.githubusercontent.com/36741649/127173017-a0bbcf75-db24-4d2c-81b9-616e04ab7cd9.gif
    :alt: monodepth
@@ -69,7 +69,7 @@ Install requirements
 
     %pip install -q "openvino>=2023.1.0"
     %pip install -q matplotlib opencv-python requests tqdm
-
+    
     # Fetch `notebook_utils` module
     import urllib.request
     urllib.request.urlretrieve(
@@ -92,7 +92,7 @@ Install requirements
 
 .. parsed-literal::
 
-    ('notebook_utils.py', )
+    ('notebook_utils.py', )
 
 
 
@@ -105,7 +105,7 @@ Imports
 
     import time
     from pathlib import Path
-
+    
     import cv2
     import matplotlib.cm
     import matplotlib.pyplot as plt
@@ -120,7 +120,7 @@ Imports
         display,
     )
     import openvino as ov
-
+    
     from notebook_utils import download_file, load_image
 
 Download the model
@@ -134,14 +134,14 @@ The model is in the `OpenVINO Intermediate Representation
 .. code:: ipython3
 
     model_folder = Path('model')
-
+    
     ir_model_url = 'https://storage.openvinotoolkit.org/repositories/openvino_notebooks/models/depth-estimation-midas/FP32/'
     ir_model_name_xml = 'MiDaS_small.xml'
     ir_model_name_bin = 'MiDaS_small.bin'
-
+    
     download_file(ir_model_url + ir_model_name_xml, filename=ir_model_name_xml, directory=model_folder)
     download_file(ir_model_url + ir_model_name_bin, filename=ir_model_name_bin, directory=model_folder)
-
+    
     model_xml_path = model_folder / ir_model_name_xml
 
 
@@ -167,13 +167,13 @@ Functions
     def normalize_minmax(data):
         """Normalizes the values in `data` between 0 and 1"""
         return (data - data.min()) / (data.max() - data.min())
-
-
+    
+    
     def convert_result_to_image(result, colormap="viridis"):
         """
         Convert network result of floating point numbers to an RGB image with
         integer values from 0-255 by applying a colormap.
-
+    
         `result` is expected to be a single network result in 1,H,W shape
         `colormap` is a matplotlib colormap.
         See https://matplotlib.org/stable/tutorials/colors/colormaps.html
@@ -184,8 +184,8 @@ Functions
         result = cmap(result)[:, :, :3] * 255
         result = result.astype(np.uint8)
         return result
-
-
+    
+    
     def to_rgb(image_data) -> np.ndarray:
         """
         Convert image_data from BGR to RGB
@@ -202,7 +202,7 @@ select device from dropdown list for running inference using OpenVINO
 .. code:: ipython3
 
     import ipywidgets as widgets
-
+    
     core = ov.Core()
     device = widgets.Dropdown(
         options=core.available_devices + ["AUTO"],
@@ -210,7 +210,7 @@ select device from dropdown list for running inference using OpenVINO
         description='Device:',
         disabled=False,
     )
-
+    
     device
 
 
@@ -237,10 +237,10 @@ output keys and the expected input shape for the model.
     core.set_property({'CACHE_DIR': '../cache'})
     model = core.read_model(model_xml_path)
     compiled_model = core.compile_model(model=model, device_name=device.value)
-
+    
     input_key = compiled_model.input(0)
     output_key = compiled_model.output(0)
-
+    
     network_input_shape = list(input_key.shape)
     network_image_height, network_image_width = network_input_shape[2:]
 
@@ -262,10 +262,10 @@ H=height, W=width).
 
     IMAGE_FILE = "https://storage.openvinotoolkit.org/repositories/openvino_notebooks/data/data/image/coco_bike.jpg"
     image = load_image(path=IMAGE_FILE)
-
+    
     # Resize to input shape for network.
     resized_image = cv2.resize(src=image, dsize=(network_image_height, network_image_width))
-
+    
     # Reshape the image to network input shape NCHW.
     input_image = np.expand_dims(np.transpose(resized_image, (2, 0, 1)), 0)
 
@@ -280,11 +280,11 @@ original image shape.
 .. code:: ipython3
 
     result = compiled_model([input_image])[output_key]
-
+    
     # Convert the network result of disparity map to an image that shows
     # distance as colors.
     result_image = convert_result_to_image(result=result)
-
+    
     # Resize back to original image shape. The `cv2.resize` function expects shape
     # in (width, height), [::-1] reverses the (height, width) shape to match this.
     result_image = cv2.resize(result_image, image.shape[:2][::-1])
@@ -292,7 +292,7 @@ original image shape.
 
 .. parsed-literal::
 
-    /tmp/ipykernel_809788/2076527990.py:15: MatplotlibDeprecationWarning: The get_cmap function was deprecated in Matplotlib 3.7 and will be removed two minor releases later. Use ``matplotlib.colormaps[name]`` or ``matplotlib.colormaps.get_cmap(obj)`` instead.
+    /tmp/ipykernel_2841459/2076527990.py:15: MatplotlibDeprecationWarning: The get_cmap function was deprecated in Matplotlib 3.7 and will be removed two minor releases later. Use ``matplotlib.colormaps[name]`` or ``matplotlib.colormaps.get_cmap(obj)`` instead.
       cmap = matplotlib.cm.get_cmap(colormap)
 
 
@@ -346,7 +346,7 @@ Video Settings
     # Try the `THEO` encoding if you have FFMPEG installed.
     # FOURCC = cv2.VideoWriter_fourcc(*"THEO")
     FOURCC = cv2.VideoWriter_fourcc(*"vp09")
-
+    
     # Create Path objects for the input video and the result video.
     output_directory = Path("output")
     output_directory.mkdir(exist_ok=True)
@@ -369,11 +369,11 @@ compute values for these properties for the monodepth video.
         raise ValueError(f"The video at {VIDEO_FILE} cannot be read.")
     input_fps = cap.get(cv2.CAP_PROP_FPS)
     input_video_frame_height, input_video_frame_width = image.shape[:2]
-
+    
     target_fps = input_fps / ADVANCE_FRAMES
     target_frame_height = int(input_video_frame_height * SCALE_OUTPUT)
     target_frame_width = int(input_video_frame_width * SCALE_OUTPUT)
-
+    
     cap.release()
     print(
         f"The input video has a frame width of {input_video_frame_width}, "
@@ -403,10 +403,10 @@ Do Inference on a Video and Create Monodepth Video
     input_video_frame_nr = 0
     start_time = time.perf_counter()
     total_inference_duration = 0
-
+    
     # Open the input video
     cap = cv2.VideoCapture(str(VIDEO_FILE))
-
+    
     # Create a result video.
     out_video = cv2.VideoWriter(
         str(result_video_path),
@@ -414,36 +414,36 @@ Do Inference on a Video and Create Monodepth Video
         target_fps,
         (target_frame_width * 2, target_frame_height),
     )
-
+    
     num_frames = int(NUM_SECONDS * input_fps)
     total_frames = cap.get(cv2.CAP_PROP_FRAME_COUNT) if num_frames == 0 else num_frames
     progress_bar = ProgressBar(total=total_frames)
     progress_bar.display()
-
+    
     try:
         while cap.isOpened():
             ret, image = cap.read()
             if not ret:
                 cap.release()
                 break
-
+    
             if input_video_frame_nr >= total_frames:
                 break
-
+    
             # Only process every second frame.
             # Prepare a frame for inference.
             # Resize to the input shape for network.
             resized_image = cv2.resize(src=image, dsize=(network_image_height, network_image_width))
             # Reshape the image to network input shape NCHW.
             input_image = np.expand_dims(np.transpose(resized_image, (2, 0, 1)), 0)
-
+    
             # Do inference.
             inference_start_time = time.perf_counter()
             result = compiled_model([input_image])[output_key]
             inference_stop_time = time.perf_counter()
             inference_duration = inference_stop_time - inference_start_time
             total_inference_duration += inference_duration
-
+    
             if input_video_frame_nr % (10 * ADVANCE_FRAMES) == 0:
                 clear_output(wait=True)
                 progress_bar.display()
@@ -457,7 +457,7 @@ Do Inference on a Video and Create Monodepth Video
                         f"({1/inference_duration:.2f} FPS)"
                     )
                 )
-
+    
             # Transform the network result to a RGB image.
             result_frame = to_rgb(convert_result_to_image(result))
             # Resize the image and the result to a target frame shape.
@@ -467,13 +467,13 @@ Do Inference on a Video and Create Monodepth Video
             stacked_frame = np.hstack((image, result_frame))
             # Save a frame to the video.
             out_video.write(stacked_frame)
-
+    
             input_video_frame_nr = input_video_frame_nr + ADVANCE_FRAMES
             cap.set(1, input_video_frame_nr)
-
+    
             progress_bar.progress = input_video_frame_nr
             progress_bar.update()
-
+    
     except KeyboardInterrupt:
         print("Processing interrupted.")
     finally:
@@ -483,7 +483,7 @@ Do Inference on a Video and Create Monodepth Video
         cap.release()
         end_time = time.perf_counter()
         duration = end_time - start_time
-
+    
         print(
             f"Processed {processed_frames} frames in {duration:.2f} seconds. "
             f"Total FPS (including video processing): {processed_frames/duration:.2f}."
@@ -494,7 +494,7 @@ Do Inference on a Video and Create Monodepth Video
 
 .. parsed-literal::
 
-    Processed 60 frames in 37.40 seconds. Total FPS (including video processing): 1.60.Inference FPS: 43.54
+    Processed 60 frames in 37.50 seconds. Total FPS (including video processing): 1.60.Inference FPS: 43.40 
     Monodepth Video saved to 'output/Coco%20Walking%20in%20Berkeley_monodepth.mp4'.
 
 
@@ -524,8 +524,8 @@ Display Monodepth Video
 .. parsed-literal::
 
     Showing monodepth video saved at
-    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/201-vision-monodepth/output/Coco%20Walking%20in%20Berkeley_monodepth.mp4
-    If you cannot see the video in your browser, please click on the following link to download the video
+    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/notebooks/201-vision-monodepth/output/Coco%20Walking%20in%20Berkeley_monodepth.mp4
+    If you cannot see the video in your browser, please click on the following link to download the video 
 
 
 
diff --git a/docs/notebooks/201-vision-monodepth-with-output_files/index.html.tmp b/docs/notebooks/201-vision-monodepth-with-output_files/index.html.tmp
deleted file mode 100644
index 1ee2e8baa6fdc6..00000000000000
--- a/docs/notebooks/201-vision-monodepth-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,7 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/201-vision-monodepth-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/201-vision-monodepth-with-output_files/
../
-201-vision-monodepth-with-output_18_0.png          26-Jan-2024 01:05              959858
-

-
diff --git a/docs/notebooks/202-vision-superresolution-image-with-output.rst b/docs/notebooks/202-vision-superresolution-image-with-output.rst
index 46741adcda49ec..1b2abe7d2963b5 100644
--- a/docs/notebooks/202-vision-superresolution-image-with-output.rst
+++ b/docs/notebooks/202-vision-superresolution-image-with-output.rst
@@ -5,7 +5,7 @@ Super Resolution is the process of enhancing the quality of an image by
 increasing the pixel count using deep learning. This notebook shows the
 Single Image Super Resolution (SISR) which takes just one low resolution
 image. A model called
-`single-image-super-resolution-1032 `__,
+`single-image-super-resolution-1032 `__,
 which is available in Open Model Zoo, is used in this tutorial. It is
 based on the research paper cited below.
 
@@ -774,8 +774,8 @@ as total time to process each patch.
 
 .. parsed-literal::
 
-    Processed 42 patches in 4.63 seconds. Total patches per second (including processing): 9.06.
-    Inference patches per second: 17.81 
+    Processed 42 patches in 4.64 seconds. Total patches per second (including processing): 9.05.
+    Inference patches per second: 17.92 
 
 
 Save superresolution image and the bicubic image
diff --git a/docs/notebooks/202-vision-superresolution-image-with-output_files/index.html.tmp b/docs/notebooks/202-vision-superresolution-image-with-output_files/index.html.tmp
deleted file mode 100644
index f09f6263829caa..00000000000000
--- a/docs/notebooks/202-vision-superresolution-image-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,10 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/202-vision-superresolution-image-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/202-vision-superresolution-image-with-output_files/
../
-202-vision-superresolution-image-with-output_15..> 26-Jan-2024 01:05              272963
-202-vision-superresolution-image-with-output_17..> 26-Jan-2024 01:05              356735
-202-vision-superresolution-image-with-output_23..> 26-Jan-2024 01:05             2896276
-202-vision-superresolution-image-with-output_27..> 26-Jan-2024 01:05             3207711
-

-
diff --git a/docs/notebooks/202-vision-superresolution-video-with-output.rst b/docs/notebooks/202-vision-superresolution-video-with-output.rst
index b95a0b2723ca6f..465022c097d106 100644
--- a/docs/notebooks/202-vision-superresolution-video-with-output.rst
+++ b/docs/notebooks/202-vision-superresolution-video-with-output.rst
@@ -5,7 +5,7 @@ Super Resolution is the process of enhancing the quality of an image by
 increasing the pixel count using deep learning. This notebook applies
 Single Image Super Resolution (SISR) to frames in a 360p (480×360) video
 in 360p resolution. A model called
-`single-image-super-resolution-1032 `__,
+`single-image-super-resolution-1032 `__,
 which is available in Open Model Zoo, is used in this tutorial. It is
 based on the research paper cited below.
 
@@ -81,7 +81,7 @@ Imports
 
     import time
     from pathlib import Path
-
+    
     import cv2
     import numpy as np
     from IPython.display import (
@@ -120,7 +120,7 @@ select device from dropdown list for running inference using OpenVINO
 .. code:: ipython3
 
     import ipywidgets as widgets
-
+    
     core = ov.Core()
     device = widgets.Dropdown(
         options=core.available_devices + ["AUTO"],
@@ -128,7 +128,7 @@ select device from dropdown list for running inference using OpenVINO
         description='Device:',
         disabled=False,
     )
-
+    
     device
 
 
@@ -144,20 +144,20 @@ select device from dropdown list for running inference using OpenVINO
 
     # 1032: 4x superresolution, 1033: 3x superresolution
     model_name = 'single-image-super-resolution-1032'
-
+    
     base_model_dir = Path('./model').expanduser()
-
+    
     model_xml_name = f'{model_name}.xml'
     model_bin_name = f'{model_name}.bin'
-
+    
     model_xml_path = base_model_dir / model_xml_name
     model_bin_path = base_model_dir / model_bin_name
-
+    
     if not model_xml_path.exists():
         base_url = f'https://storage.openvinotoolkit.org/repositories/open_model_zoo/2023.0/models_bin/1/{model_name}/FP16/'
         model_xml_url = base_url + model_xml_name
         model_bin_url = base_url + model_bin_name
-
+    
         download_file(model_xml_url, model_xml_path)
         download_file(model_bin_url, model_bin_path)
     else:
@@ -180,7 +180,7 @@ Functions
         """
         Convert network result of floating point numbers to image with integer
         values from 0-255. Values outside this range are clipped to 0 and 255.
-
+    
         :param result: a single superresolution network result in N,C,H,W shape
         """
         result = result.squeeze(0).transpose(1, 2, 0)
@@ -215,18 +215,18 @@ resolution version of the image in 1920x1080.
     # dictionaries.
     original_image_key, bicubic_image_key = compiled_model.inputs
     output_key = compiled_model.output(0)
-
+    
     # Get the expected input and target shape. The `.dims[2:]` function returns the height
     # and width.The `resize` function of  OpenCV expects the shape as (width, height),
     # so reverse the shape with `[::-1]` and convert it to a tuple.
     input_height, input_width = list(original_image_key.shape)[2:]
     target_height, target_width = list(bicubic_image_key.shape)[2:]
-
+    
     upsample_factor = int(target_height / input_height)
-
+    
     print(f"The network expects inputs with a width of {input_width}, " f"height of {input_height}")
     print(f"The network returns images with a width of {target_width}, " f"height of {target_height}")
-
+    
     print(
         f"The image sides are upsampled by a factor of {upsample_factor}. "
         f"The new image is {upsample_factor**2} times as large as the "
@@ -264,7 +264,7 @@ Settings
 .. code:: ipython3
 
     OUTPUT_DIR = "output"
-
+    
     Path(OUTPUT_DIR).mkdir(exist_ok=True)
     # Maximum number of frames to read from the input video. Set to 0 to read all frames.
     NUM_FRAMES = 100
@@ -290,10 +290,10 @@ Download and Prepare Video
     filename = Path(stream.default_filename.encode("ascii", "ignore").decode("ascii")).stem
     stream.download(output_path=OUTPUT_DIR, filename=filename)
     print(f"Video {filename} downloaded to {OUTPUT_DIR}")
-
+    
     # Create Path objects for the input video and the resulting videos.
     video_path = Path(stream.get_file_path(filename, OUTPUT_DIR))
-
+    
     # Path names for the result videos.
     superres_video_path = Path(f"{OUTPUT_DIR}/{video_path.stem}_superres.mp4")
     bicubic_video_path = Path(f"{OUTPUT_DIR}/{video_path.stem}_bicubic.mp4")
@@ -314,14 +314,14 @@ Download and Prepare Video
         raise ValueError(f"The video at '{video_path}' cannot be read.")
     fps = cap.get(cv2.CAP_PROP_FPS)
     frame_count = cap.get(cv2.CAP_PROP_FRAME_COUNT)
-
+    
     if NUM_FRAMES == 0:
         total_frames = frame_count
     else:
         total_frames = min(frame_count, NUM_FRAMES)
-
+    
     original_frame_height, original_frame_width = image.shape[:2]
-
+    
     cap.release()
     print(
         f"The input video has a frame width of {original_frame_width}, "
@@ -389,10 +389,10 @@ video.
     start_time = time.perf_counter()
     frame_nr = 0
     total_inference_duration = 0
-
+    
     progress_bar = ProgressBar(total=total_frames)
     progress_bar.display()
-
+    
     cap = cv2.VideoCapture(filename=str(video_path))
     try:
         while cap.isOpened():
@@ -400,22 +400,22 @@ video.
             if not ret:
                 cap.release()
                 break
-
+    
             if frame_nr >= total_frames:
                 break
-
+    
             # Resize the input image to the network shape and convert it from (H,W,C) to
             # (N,C,H,W).
             resized_image = cv2.resize(src=image, dsize=(input_width, input_height))
             input_image_original = np.expand_dims(resized_image.transpose(2, 0, 1), axis=0)
-
+    
             # Resize and reshape the image to the target shape with bicubic
             # interpolation.
             bicubic_image = cv2.resize(
                 src=image, dsize=(target_width, target_height), interpolation=cv2.INTER_CUBIC
             )
             input_image_bicubic = np.expand_dims(bicubic_image.transpose(2, 0, 1), axis=0)
-
+    
             # Do inference.
             inference_start_time = time.perf_counter()
             result = compiled_model(
@@ -427,19 +427,19 @@ video.
             inference_stop_time = time.perf_counter()
             inference_duration = inference_stop_time - inference_start_time
             total_inference_duration += inference_duration
-
+    
             # Transform the inference result into an image.
             result_frame = convert_result_to_image(result=result)
-
+    
             # Write the result image and the bicubic image to a video file.
             superres_video.write(image=result_frame)
             bicubic_video.write(image=bicubic_image)
-
+    
             stacked_frame = np.hstack((bicubic_image, result_frame))
             comparison_video.write(image=stacked_frame)
-
+    
             frame_nr = frame_nr + 1
-
+    
             # Update the progress bar and the status message.
             progress_bar.progress = frame_nr
             progress_bar.update()
@@ -453,8 +453,8 @@ video.
                         f"({1/inference_duration:.2f} FPS)"
                     )
                 )
-
-
+    
+    
     except KeyboardInterrupt:
         print("Processing interrupted.")
     finally:
@@ -480,13 +480,13 @@ video.
 
 .. parsed-literal::
 
-    Processed frame 100. Inference time: 0.05 seconds (19.51 FPS)
+    Processed frame 100. Inference time: 0.06 seconds (17.00 FPS)
 
 
 .. parsed-literal::
 
     Video's saved to output directory.
-    Processed 100 frames in 242.29 seconds. Total FPS (including video processing): 0.41. Inference FPS: 18.44.
+    Processed 100 frames in 243.08 seconds. Total FPS (including video processing): 0.41. Inference FPS: 17.69.
 
 
 Show Side-by-Side Video of Bicubic and Superresolution Version
diff --git a/docs/notebooks/203-meter-reader-with-output.rst b/docs/notebooks/203-meter-reader-with-output.rst
index 4494fc16aa0be0..771bc9c07c3e40 100644
--- a/docs/notebooks/203-meter-reader-with-output.rst
+++ b/docs/notebooks/203-meter-reader-with-output.rst
@@ -623,7 +623,7 @@ bounds of input batch size.
 
 .. parsed-literal::
 
-    
+    
 
 
 
@@ -788,7 +788,7 @@ Get the reading result on the meter picture
 .. image:: 203-meter-reader-with-output_files/203-meter-reader-with-output_24_1.png
 
 
-Try it with your meter photos
------------------------------------------------
+Try it with your meter photos!
+------------------------------
 
 
diff --git a/docs/notebooks/203-meter-reader-with-output_files/index.html.tmp b/docs/notebooks/203-meter-reader-with-output_files/index.html.tmp
deleted file mode 100644
index 31f25b738a3b21..00000000000000
--- a/docs/notebooks/203-meter-reader-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,11 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/203-meter-reader-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/203-meter-reader-with-output_files/
../
-203-meter-reader-with-output_16_1.png              26-Jan-2024 01:04              170121
-203-meter-reader-with-output_18_1.png              26-Jan-2024 01:04              190271
-203-meter-reader-with-output_20_1.png              26-Jan-2024 01:04               26914
-203-meter-reader-with-output_22_1.png              26-Jan-2024 01:04                8966
-203-meter-reader-with-output_24_1.png              26-Jan-2024 01:04              170338
-

-
diff --git a/docs/notebooks/204-segmenter-semantic-segmentation-with-output.rst b/docs/notebooks/204-segmenter-semantic-segmentation-with-output.rst
index cfd7aa7d3eae10..9447dd7c2e0d3a 100644
--- a/docs/notebooks/204-segmenter-semantic-segmentation-with-output.rst
+++ b/docs/notebooks/204-segmenter-semantic-segmentation-with-output.rst
@@ -26,20 +26,31 @@ paper: `Segmenter: Transformer for Semantic
 Segmentation `__ or in the
 `repository `__.
 
+Table of contents:
+^^^^^^^^^^^^^^^^^^
 
-**Table of contents:**
+-  `Get and prepare PyTorch model <#get-and-prepare-pytorch-model>`__
 
-- `Get and prepare PyTorch model <#get-and-prepare-pytorch-model>`__
-- `Prerequisites <#prerequisites>`__
-- `Loading PyTorch model <#loading-pytorch-model>`__
-- `Preparing preprocessing and visualization functions <#preparing-preprocessing-and-visualization-functions>`__
-- `Preprocessing <#preprocessing>`__
-- `visualization <#visualization>`__
-- `Validation of inference of original model <#validation-of-inference-of-original-model>`__
-- `Convert PyTorch model to OpenVINO Intermediate Representation (IR) <#convert-pytorch-model-to-openvino-intermediate-representation-ir>`__
-- `Verify converted model inference <#verify-converted-model-inference>`__
-- `Select inference device <#select-inference-device>`__
-- `Benchmarking performance of converted model <#benchmarking-performance-of-converted-model>`__
+   -  `Prerequisites <#prerequisites>`__
+   -  `Loading PyTorch model <#loading-pytorch-model>`__
+
+-  `Preparing preprocessing and visualization
+   functions <#preparing-preprocessing-and-visualization-functions>`__
+
+   -  `Preprocessing <#preprocessing>`__
+   -  `Visualization <#visualization>`__
+
+-  `Validation of inference of original
+   model <#validation-of-inference-of-original-model>`__
+-  `Convert PyTorch model to OpenVINO Intermediate Representation
+   (IR) <#convert-pytorch-model-to-openvino-intermediate-representation-ir>`__
+-  `Verify converted model
+   inference <#verify-converted-model-inference>`__
+
+   -  `Select inference device <#select-inference-device>`__
+
+-  `Benchmarking performance of converted
+   model <#benchmarking-performance-of-converted-model>`__
 
 .. |Segmenter diagram| image:: https://github.com/openvinotoolkit/openvino_notebooks/assets/93932510/f57979e7-fd3b-449f-bf01-afe0f965abbc
 
@@ -79,13 +90,13 @@ Prerequisites
 
     import sys
     from pathlib import Path
-
+    
     # clone Segmenter repo
     if not Path("segmenter").exists():
         !git clone https://github.com/rstrudel/segmenter
     else:
         print("Segmenter repo already cloned")
-
+    
     # include path to Segmenter repo to use its functions
     sys.path.append("./segmenter")
 
@@ -108,10 +119,7 @@ Receiving objects:   6% (17/268)
 Receiving objects:   7% (19/268)
 Receiving objects:   8% (22/268)
 Receiving objects:   9% (25/268)
-
-.. parsed-literal::
-
-    Receiving objects:  10% (27/268)
+Receiving objects:  10% (27/268)
 Receiving objects:  11% (30/268)
 Receiving objects:  12% (33/268)
 Receiving objects:  13% (35/268)
@@ -135,118 +143,122 @@ Receiving objects:  22% (59/268)
 
 .. parsed-literal::
 
-    Receiving objects:  24% (65/268), 2.55 MiB | 2.48 MiB/s
+    Receiving objects:  24% (65/268), 3.68 MiB | 3.63 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  24% (66/268), 6.21 MiB | 3.02 MiB/s
+    Receiving objects:  24% (66/268), 7.47 MiB | 3.70 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  25% (67/268), 6.21 MiB | 3.02 MiB/s
+    Receiving objects:  25% (67/268), 7.47 MiB | 3.70 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  25% (68/268), 9.88 MiB | 3.19 MiB/s
+    Receiving objects:  25% (68/268), 11.26 MiB | 3.73 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  26% (70/268), 11.71 MiB | 3.24 MiB/s
-Receiving objects:  27% (73/268), 11.71 MiB | 3.24 MiB/s
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-Receiving objects:  82% (220/268), 11.71 MiB | 3.24 MiB/s
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+    Receiving objects:  26% (70/268), 11.26 MiB | 3.73 MiB/s
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-    Receiving objects:  90% (242/268), 11.71 MiB | 3.24 MiB/s
+    Receiving objects:  90% (242/268), 11.26 MiB | 3.73 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  91% (244/268), 11.71 MiB | 3.24 MiB/s
+    Receiving objects:  91% (244/268), 11.26 MiB | 3.73 MiB/s
 
 .. parsed-literal::
 
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+    Receiving objects:  92% (247/268), 13.11 MiB | 3.72 MiB/s
+Receiving objects:  93% (250/268), 13.11 MiB | 3.72 MiB/s
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+Receiving objects:  95% (255/268), 13.11 MiB | 3.72 MiB/s
+Receiving objects:  96% (258/268), 13.11 MiB | 3.72 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  97% (260/268), 13.54 MiB | 3.28 MiB/s
-Receiving objects:  98% (263/268), 13.54 MiB | 3.28 MiB/s
-Receiving objects:  99% (266/268), 13.54 MiB | 3.28 MiB/s
+    Receiving objects:  97% (260/268), 13.11 MiB | 3.72 MiB/s
+Receiving objects:  98% (263/268), 13.11 MiB | 3.72 MiB/s
+Receiving objects:  99% (266/268), 13.11 MiB | 3.72 MiB/s
+
+.. parsed-literal::
+
+    Receiving objects:  99% (267/268), 15.03 MiB | 3.73 MiB/s
 
 .. parsed-literal::
 
     remote: Total 268 (delta 0), reused 0 (delta 0), pack-reused 268
-    Receiving objects: 100% (268/268), 15.25 MiB | 3.29 MiB/s
-Receiving objects: 100% (268/268), 15.34 MiB | 3.30 MiB/s, done.
+    Receiving objects: 100% (268/268), 15.03 MiB | 3.73 MiB/s
+Receiving objects: 100% (268/268), 15.34 MiB | 3.73 MiB/s, done.
     Resolving deltas:   0% (0/117)
 Resolving deltas:   1% (2/117)
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+Resolving deltas:   3% (4/117)
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 Resolving deltas:   8% (10/117)
@@ -254,15 +266,15 @@ Resolving deltas:   9% (11/117)
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 Resolving deltas:  81% (95/117)
+Resolving deltas:  82% (96/117)
 Resolving deltas: 100% (117/117)
 Resolving deltas: 100% (117/117), done.
 
@@ -281,9 +293,9 @@ Resolving deltas: 100% (117/117), done.
 
 .. parsed-literal::
 
-    Requirement already satisfied: torch in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from -r segmenter/requirements.txt (line 1)) (2.1.0+cpu)
-    Requirement already satisfied: click in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from -r segmenter/requirements.txt (line 2)) (8.1.7)
-    Requirement already satisfied: numpy in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from -r segmenter/requirements.txt (line 3)) (1.23.5)
+    Requirement already satisfied: torch in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from -r segmenter/requirements.txt (line 1)) (2.1.0+cpu)
+    Requirement already satisfied: click in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from -r segmenter/requirements.txt (line 2)) (8.1.7)
+    Requirement already satisfied: numpy in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from -r segmenter/requirements.txt (line 3)) (1.23.5)
 
 
 .. parsed-literal::
@@ -296,9 +308,9 @@ Resolving deltas: 100% (117/117), done.
 
     Collecting python-hostlist (from -r segmenter/requirements.txt (line 5))
       Using cached python_hostlist-1.23.0-py3-none-any.whl
-    Requirement already satisfied: tqdm in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from -r segmenter/requirements.txt (line 6)) (4.66.1)
-    Requirement already satisfied: requests in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from -r segmenter/requirements.txt (line 7)) (2.31.0)
-    Requirement already satisfied: pyyaml in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from -r segmenter/requirements.txt (line 8)) (6.0.1)
+    Requirement already satisfied: tqdm in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from -r segmenter/requirements.txt (line 6)) (4.66.1)
+    Requirement already satisfied: requests in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from -r segmenter/requirements.txt (line 7)) (2.31.0)
+    Requirement already satisfied: pyyaml in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from -r segmenter/requirements.txt (line 8)) (6.0.1)
 
 
 .. parsed-literal::
@@ -316,49 +328,57 @@ Resolving deltas: 100% (117/117), done.
 .. parsed-literal::
 
     Collecting mmsegmentation==0.14.1 (from -r segmenter/requirements.txt (line 11))
+
+
+.. parsed-literal::
+
       Using cached mmsegmentation-0.14.1-py3-none-any.whl (201 kB)
-    Requirement already satisfied: torchvision in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from timm==0.4.12->-r segmenter/requirements.txt (line 9)) (0.16.0+cpu)
-    Requirement already satisfied: addict in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from mmcv==1.3.8->-r segmenter/requirements.txt (line 10)) (2.4.0)
-    Requirement already satisfied: Pillow in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from mmcv==1.3.8->-r segmenter/requirements.txt (line 10)) (10.2.0)
+    Requirement already satisfied: torchvision in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from timm==0.4.12->-r segmenter/requirements.txt (line 9)) (0.16.0+cpu)
+    Requirement already satisfied: addict in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from mmcv==1.3.8->-r segmenter/requirements.txt (line 10)) (2.4.0)
+    Requirement already satisfied: Pillow in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from mmcv==1.3.8->-r segmenter/requirements.txt (line 10)) (10.2.0)
 
 
 .. parsed-literal::
 
     Collecting yapf (from mmcv==1.3.8->-r segmenter/requirements.txt (line 10))
+
+
+.. parsed-literal::
+
       Using cached yapf-0.40.2-py3-none-any.whl.metadata (45 kB)
-    Requirement already satisfied: matplotlib in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from mmsegmentation==0.14.1->-r segmenter/requirements.txt (line 11)) (3.7.4)
-    Requirement already satisfied: prettytable in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from mmsegmentation==0.14.1->-r segmenter/requirements.txt (line 11)) (3.9.0)
-    Requirement already satisfied: filelock in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from torch->-r segmenter/requirements.txt (line 1)) (3.13.1)
-    Requirement already satisfied: typing-extensions in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from torch->-r segmenter/requirements.txt (line 1)) (4.9.0)
-    Requirement already satisfied: sympy in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from torch->-r segmenter/requirements.txt (line 1)) (1.12)
-    Requirement already satisfied: networkx in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from torch->-r segmenter/requirements.txt (line 1)) (3.1)
-    Requirement already satisfied: jinja2 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from torch->-r segmenter/requirements.txt (line 1)) (3.1.3)
-    Requirement already satisfied: fsspec in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from torch->-r segmenter/requirements.txt (line 1)) (2023.10.0)
+    Requirement already satisfied: matplotlib in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from mmsegmentation==0.14.1->-r segmenter/requirements.txt (line 11)) (3.7.4)
+    Requirement already satisfied: prettytable in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from mmsegmentation==0.14.1->-r segmenter/requirements.txt (line 11)) (3.9.0)
+    Requirement already satisfied: filelock in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from torch->-r segmenter/requirements.txt (line 1)) (3.13.1)
+    Requirement already satisfied: typing-extensions in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from torch->-r segmenter/requirements.txt (line 1)) (4.9.0)
+    Requirement already satisfied: sympy in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from torch->-r segmenter/requirements.txt (line 1)) (1.12)
+    Requirement already satisfied: networkx in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from torch->-r segmenter/requirements.txt (line 1)) (3.1)
+    Requirement already satisfied: jinja2 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from torch->-r segmenter/requirements.txt (line 1)) (3.1.3)
+    Requirement already satisfied: fsspec in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from torch->-r segmenter/requirements.txt (line 1)) (2023.10.0)
 
 
 .. parsed-literal::
 
-    Requirement already satisfied: charset-normalizer<4,>=2 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from requests->-r segmenter/requirements.txt (line 7)) (3.3.2)
-    Requirement already satisfied: idna<4,>=2.5 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from requests->-r segmenter/requirements.txt (line 7)) (3.6)
-    Requirement already satisfied: urllib3<3,>=1.21.1 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from requests->-r segmenter/requirements.txt (line 7)) (2.1.0)
-    Requirement already satisfied: certifi>=2017.4.17 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from requests->-r segmenter/requirements.txt (line 7)) (2023.11.17)
-    Requirement already satisfied: MarkupSafe>=2.0 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from jinja2->torch->-r segmenter/requirements.txt (line 1)) (2.1.4)
+    Requirement already satisfied: charset-normalizer<4,>=2 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from requests->-r segmenter/requirements.txt (line 7)) (3.3.2)
+    Requirement already satisfied: idna<4,>=2.5 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from requests->-r segmenter/requirements.txt (line 7)) (3.6)
+    Requirement already satisfied: urllib3<3,>=1.21.1 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from requests->-r segmenter/requirements.txt (line 7)) (2.2.0)
+    Requirement already satisfied: certifi>=2017.4.17 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from requests->-r segmenter/requirements.txt (line 7)) (2024.2.2)
+    Requirement already satisfied: MarkupSafe>=2.0 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from jinja2->torch->-r segmenter/requirements.txt (line 1)) (2.1.5)
 
 
 .. parsed-literal::
 
-    Requirement already satisfied: contourpy>=1.0.1 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from matplotlib->mmsegmentation==0.14.1->-r segmenter/requirements.txt (line 11)) (1.1.1)
-    Requirement already satisfied: cycler>=0.10 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from matplotlib->mmsegmentation==0.14.1->-r segmenter/requirements.txt (line 11)) (0.12.1)
-    Requirement already satisfied: fonttools>=4.22.0 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from matplotlib->mmsegmentation==0.14.1->-r segmenter/requirements.txt (line 11)) (4.47.2)
-    Requirement already satisfied: kiwisolver>=1.0.1 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from matplotlib->mmsegmentation==0.14.1->-r segmenter/requirements.txt (line 11)) (1.4.5)
-    Requirement already satisfied: packaging>=20.0 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from matplotlib->mmsegmentation==0.14.1->-r segmenter/requirements.txt (line 11)) (23.2)
-    Requirement already satisfied: pyparsing>=2.3.1 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from matplotlib->mmsegmentation==0.14.1->-r segmenter/requirements.txt (line 11)) (3.1.1)
-    Requirement already satisfied: python-dateutil>=2.7 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from matplotlib->mmsegmentation==0.14.1->-r segmenter/requirements.txt (line 11)) (2.8.2)
-    Requirement already satisfied: importlib-resources>=3.2.0 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from matplotlib->mmsegmentation==0.14.1->-r segmenter/requirements.txt (line 11)) (6.1.1)
-    Requirement already satisfied: wcwidth in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from prettytable->mmsegmentation==0.14.1->-r segmenter/requirements.txt (line 11)) (0.2.13)
-    Requirement already satisfied: mpmath>=0.19 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from sympy->torch->-r segmenter/requirements.txt (line 1)) (1.3.0)
-    Requirement already satisfied: importlib-metadata>=6.6.0 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from yapf->mmcv==1.3.8->-r segmenter/requirements.txt (line 10)) (7.0.1)
-    Requirement already satisfied: platformdirs>=3.5.1 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from yapf->mmcv==1.3.8->-r segmenter/requirements.txt (line 10)) (4.1.0)
+    Requirement already satisfied: contourpy>=1.0.1 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from matplotlib->mmsegmentation==0.14.1->-r segmenter/requirements.txt (line 11)) (1.1.1)
+    Requirement already satisfied: cycler>=0.10 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from matplotlib->mmsegmentation==0.14.1->-r segmenter/requirements.txt (line 11)) (0.12.1)
+    Requirement already satisfied: fonttools>=4.22.0 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from matplotlib->mmsegmentation==0.14.1->-r segmenter/requirements.txt (line 11)) (4.48.1)
+    Requirement already satisfied: kiwisolver>=1.0.1 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from matplotlib->mmsegmentation==0.14.1->-r segmenter/requirements.txt (line 11)) (1.4.5)
+    Requirement already satisfied: packaging>=20.0 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from matplotlib->mmsegmentation==0.14.1->-r segmenter/requirements.txt (line 11)) (23.2)
+    Requirement already satisfied: pyparsing>=2.3.1 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from matplotlib->mmsegmentation==0.14.1->-r segmenter/requirements.txt (line 11)) (3.1.1)
+    Requirement already satisfied: python-dateutil>=2.7 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from matplotlib->mmsegmentation==0.14.1->-r segmenter/requirements.txt (line 11)) (2.8.2)
+    Requirement already satisfied: importlib-resources>=3.2.0 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from matplotlib->mmsegmentation==0.14.1->-r segmenter/requirements.txt (line 11)) (6.1.1)
+    Requirement already satisfied: wcwidth in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from prettytable->mmsegmentation==0.14.1->-r segmenter/requirements.txt (line 11)) (0.2.13)
+    Requirement already satisfied: mpmath>=0.19 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from sympy->torch->-r segmenter/requirements.txt (line 1)) (1.3.0)
+    Requirement already satisfied: importlib-metadata>=6.6.0 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from yapf->mmcv==1.3.8->-r segmenter/requirements.txt (line 10)) (7.0.1)
+    Requirement already satisfied: platformdirs>=3.5.1 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from yapf->mmcv==1.3.8->-r segmenter/requirements.txt (line 10)) (4.2.0)
 
 
 .. parsed-literal::
@@ -369,8 +389,12 @@ Resolving deltas: 100% (117/117), done.
 
 .. parsed-literal::
 
-    Requirement already satisfied: zipp>=0.5 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from importlib-metadata>=6.6.0->yapf->mmcv==1.3.8->-r segmenter/requirements.txt (line 10)) (3.17.0)
-    Requirement already satisfied: six>=1.5 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from python-dateutil>=2.7->matplotlib->mmsegmentation==0.14.1->-r segmenter/requirements.txt (line 11)) (1.16.0)
+    Requirement already satisfied: zipp>=0.5 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from importlib-metadata>=6.6.0->yapf->mmcv==1.3.8->-r segmenter/requirements.txt (line 10)) (3.17.0)
+
+
+.. parsed-literal::
+
+    Requirement already satisfied: six>=1.5 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from python-dateutil>=2.7->matplotlib->mmsegmentation==0.14.1->-r segmenter/requirements.txt (line 11)) (1.16.0)
 
 
 .. parsed-literal::
@@ -408,7 +432,7 @@ Resolving deltas: 100% (117/117), done.
 
     import numpy as np
     import yaml
-
+    
     # Fetch the notebook utils script from the openvino_notebooks repo
     import urllib.request
     urllib.request.urlretrieve(
@@ -429,13 +453,13 @@ config for our model.
     # here we use tiny model, there are also better but larger models available in repository
     WEIGHTS_LINK = "https://storage.openvinotoolkit.org/repositories/openvino_notebooks/models/segmenter/checkpoints/ade20k/seg_tiny_mask/checkpoint.pth"
     CONFIG_LINK = "https://storage.openvinotoolkit.org/repositories/openvino_notebooks/models/segmenter/checkpoints/ade20k/seg_tiny_mask/variant.yml"
-
+    
     MODEL_DIR = Path("model/")
     MODEL_DIR.mkdir(exist_ok=True)
-
+    
     download_file(WEIGHTS_LINK, directory=MODEL_DIR, show_progress=True)
     download_file(CONFIG_LINK, directory=MODEL_DIR, show_progress=True)
-
+    
     WEIGHT_PATH = MODEL_DIR / "checkpoint.pth"
     CONFIG_PATH = MODEL_DIR / "variant.yaml"
 
@@ -473,7 +497,7 @@ initialize the model.
 .. code:: ipython3
 
     from segmenter.segm.model.factory import load_model
-
+    
     pytorch_model, config = load_model(WEIGHT_PATH)
     # put model into eval mode, to set it for inference
     pytorch_model.eval()
@@ -536,12 +560,12 @@ normalized with given mean and standard deviation provided in
     from PIL import Image
     import torch
     import torchvision.transforms.functional as F
-
-
+    
+    
     def preprocess(im: Image, normalization: dict) -> torch.Tensor:
         """
         Preprocess image: scale, normalize and unsqueeze
-
+    
         :param im: input image
         :param normalization: dictionary containing normalization data from config file
         :return:
@@ -553,7 +577,7 @@ normalized with given mean and standard deviation provided in
         im = F.normalize(im, normalization["mean"], normalization["std"])
         # change dim from [C, H, W] to [1, C, H, W]
         im = im.unsqueeze(0)
-
+    
         return im
 
 Visualization
@@ -577,29 +601,29 @@ corresponding to the inferred labels.
 
     from segmenter.segm.data.utils import dataset_cat_description, seg_to_rgb
     from segmenter.segm.data.ade20k import ADE20K_CATS_PATH
-
-
+    
+    
     def apply_segmentation_mask(pil_im: Image, results: torch.Tensor) -> Image:
         """
         Combine segmentation masks with the image
-
+    
         :param pil_im: original input image
         :param results: tensor containing segmentation masks for each pixel
         :return:
                 pil_blend: image with colored segmentation masks overlay
         """
         cat_names, cat_colors = dataset_cat_description(ADE20K_CATS_PATH)
-
+    
         # 3D array, where each pixel has values for all classes, take index of max as label
         seg_map = results.argmax(0, keepdim=True)
         # transform label id to colors
         seg_rgb = seg_to_rgb(seg_map, cat_colors)
         seg_rgb = (255 * seg_rgb.cpu().numpy()).astype(np.uint8)
         pil_seg = Image.fromarray(seg_rgb[0])
-
+    
         # overlay segmentation mask over original image
         pil_blend = Image.blend(pil_im, pil_seg, 0.5).convert("RGB")
-
+    
         return pil_blend
 
 Validation of inference of original model
@@ -613,15 +637,15 @@ example image ``coco_hollywood.jpg``.
 .. code:: ipython3
 
     from segmenter.segm.model.utils import inference
-
+    
     # load image with PIL
     image = load_image("https://storage.openvinotoolkit.org/repositories/openvino_notebooks/data/data/image/coco_hollywood.jpg")
     # load_image reads the image in BGR format, [:,:,::-1] reshape transfroms it to RGB
     pil_image = Image.fromarray(image[:,:,::-1])
-
+    
     # preprocess image with normalization params loaded in previous steps
     image = preprocess(pil_image, normalization)
-
+    
     # inference function needs some meta parameters, where we specify that we don't flip images in inference mode
     im_meta = dict(flip=False)
     # perform inference with function from repository
@@ -641,7 +665,7 @@ previous steps.
 
     # combine segmentation mask with image
     blended_image = apply_segmentation_mask(pil_image, original_results)
-
+    
     # show image with segmentation mask overlay
     blended_image
 
@@ -688,15 +712,15 @@ they are not a problem.
 .. code:: ipython3
 
     import openvino as ov
-
+    
     # get input sizes from config file
     batch_size = 2
     channels = 3
     image_size = config["dataset_kwargs"]["image_size"]
-
+    
     # make dummy input with correct shapes obtained from config file
     dummy_input = torch.randn(batch_size, channels, image_size, image_size)
-
+    
     model = ov.convert_model(pytorch_model, example_input=dummy_input, input=([batch_size, channels, image_size, image_size], ))
     # serialize model for saving IR
     ov.save_model(model, MODEL_DIR / "segmenter.xml")
@@ -704,21 +728,21 @@ they are not a problem.
 
 .. parsed-literal::
 
-    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/204-segmenter-semantic-segmentation/./segmenter/segm/model/utils.py:69: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
+    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/notebooks/204-segmenter-semantic-segmentation/./segmenter/segm/model/utils.py:69: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
       if H % patch_size > 0:
-    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/204-segmenter-semantic-segmentation/./segmenter/segm/model/utils.py:71: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
+    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/notebooks/204-segmenter-semantic-segmentation/./segmenter/segm/model/utils.py:71: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
       if W % patch_size > 0:
-    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/204-segmenter-semantic-segmentation/./segmenter/segm/model/vit.py:122: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
+    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/notebooks/204-segmenter-semantic-segmentation/./segmenter/segm/model/vit.py:122: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
       if x.shape[1] != pos_embed.shape[1]:
 
 
 .. parsed-literal::
 
-    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/204-segmenter-semantic-segmentation/./segmenter/segm/model/decoder.py:100: TracerWarning: Converting a tensor to a Python integer might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
+    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/notebooks/204-segmenter-semantic-segmentation/./segmenter/segm/model/decoder.py:100: TracerWarning: Converting a tensor to a Python integer might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
       masks = rearrange(masks, "b (h w) n -> b n h w", h=int(GS))
-    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/204-segmenter-semantic-segmentation/./segmenter/segm/model/utils.py:85: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
+    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/notebooks/204-segmenter-semantic-segmentation/./segmenter/segm/model/utils.py:85: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
       if extra_h > 0:
-    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/204-segmenter-semantic-segmentation/./segmenter/segm/model/utils.py:87: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
+    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/notebooks/204-segmenter-semantic-segmentation/./segmenter/segm/model/utils.py:87: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
       if extra_w > 0:
 
 
@@ -739,7 +763,7 @@ any additional custom code required to process input.
     class SegmenterOV:
         """
         Class containing OpenVINO model with all attributes required to work with inference function.
-
+    
         :param model: compiled OpenVINO model
         :type model: CompiledModel
         :param output_blob: output blob used in inference
@@ -750,14 +774,14 @@ any additional custom code required to process input.
         :type n_cls: int
         :param normalization:
         :type normalization: dict
-
+    
         """
-
+    
         def __init__(self, model_path: Path, device:str = "CPU"):
             """
             Constructor method.
             Initializes OpenVINO model and sets all required attributes
-
+    
             :param model_path: path to model's .xml file, also containing variant.yml
             :param device: device string for selecting inference device
             """
@@ -767,23 +791,23 @@ any additional custom code required to process input.
             model_xml = core.read_model(model_path)
             self.model = core.compile_model(model_xml, device)
             self.output_blob = self.model.output(0)
-
+    
             # load model configs
             variant_path = Path(model_path).parent / "variant.yml"
             with open(variant_path, "r") as f:
                 self.config = yaml.load(f, Loader=yaml.FullLoader)
-
+    
             # load normalization specs from config
             normalization_name = self.config["dataset_kwargs"]["normalization"]
             self.normalization = STATS[normalization_name]
-
+    
             # load number of classes from config
             self.n_cls = self.config["net_kwargs"]["n_cls"]
-
+    
         def forward(self, data: torch.Tensor) -> torch.Tensor:
             """
             Perform inference on data and return the result in Tensor format
-
+    
             :param data: input data to model
             :return: data inferred by model
             """
@@ -802,7 +826,7 @@ select device from dropdown list for running inference using OpenVINO
 .. code:: ipython3
 
     import ipywidgets as widgets
-
+    
     core = ov.Core()
     device = widgets.Dropdown(
         options=core.available_devices + ["AUTO"],
@@ -810,7 +834,7 @@ select device from dropdown list for running inference using OpenVINO
         description='Device:',
         disabled=False,
     )
-
+    
     device
 
 
@@ -842,7 +866,7 @@ select device from dropdown list for running inference using OpenVINO
 
     # combine segmentation mask with image
     converted_blend = apply_segmentation_mask(pil_image, results)
-
+    
     # show image with segmentation mask overlay
     converted_blend
 
@@ -904,17 +928,17 @@ to measure the inference performance of the model.
     [ WARNING ] Default duration 120 seconds is used for unknown device AUTO
     [ INFO ] OpenVINO:
     [ INFO ] Build ................................. 2023.3.0-13775-ceeafaf64f3-releases/2023/3
-    [ INFO ]
+    [ INFO ] 
     [ INFO ] Device info:
     [ INFO ] AUTO
     [ INFO ] Build ................................. 2023.3.0-13775-ceeafaf64f3-releases/2023/3
-    [ INFO ]
-    [ INFO ]
+    [ INFO ] 
+    [ INFO ] 
     [Step 3/11] Setting device configuration
     [ WARNING ] Performance hint was not explicitly specified in command line. Device(AUTO) performance hint will be set to PerformanceMode.THROUGHPUT.
     [Step 4/11] Reading model files
     [ INFO ] Loading model files
-    [ INFO ] Read model took 22.64 ms
+    [ INFO ] Read model took 23.09 ms
     [ INFO ] Original model I/O parameters:
     [ INFO ] Model inputs:
     [ INFO ]     im (node: im) : f32 / [...] / [2,3,512,512]
@@ -932,7 +956,7 @@ to measure the inference performance of the model.
 
 .. parsed-literal::
 
-    [ INFO ] Compile model took 392.81 ms
+    [ INFO ] Compile model took 385.39 ms
     [Step 8/11] Querying optimal runtime parameters
     [ INFO ] Model:
     [ INFO ]   NETWORK_NAME: Model0
@@ -940,10 +964,6 @@ to measure the inference performance of the model.
     [ INFO ]   PERFORMANCE_HINT: PerformanceMode.THROUGHPUT
     [ INFO ]   OPTIMAL_NUMBER_OF_INFER_REQUESTS: 6
     [ INFO ]   MULTI_DEVICE_PRIORITIES: CPU
-
-
-.. parsed-literal::
-
     [ INFO ]   CPU:
     [ INFO ]     AFFINITY: Affinity.CORE
     [ INFO ]     CPU_DENORMALS_OPTIMIZATION: False
@@ -965,30 +985,30 @@ to measure the inference performance of the model.
     [ INFO ]   LOADED_FROM_CACHE: False
     [Step 9/11] Creating infer requests and preparing input tensors
     [ WARNING ] No input files were given for input 'im'!. This input will be filled with random values!
-    [ INFO ] Fill input 'im' with random values
-    [Step 10/11] Measuring performance (Start inference asynchronously, 6 inference requests, limits: 120000 ms duration)
-    [ INFO ] Benchmarking in inference only mode (inputs filling are not included in measurement loop).
+    [ INFO ] Fill input 'im' with random values 
 
 
 .. parsed-literal::
 
-    [ INFO ] First inference took 203.86 ms
+    [Step 10/11] Measuring performance (Start inference asynchronously, 6 inference requests, limits: 120000 ms duration)
+    [ INFO ] Benchmarking in inference only mode (inputs filling are not included in measurement loop).
 
 
 .. parsed-literal::
 
-    [Step 11/11] Dumping statistics report
+    [ INFO ] First inference took 210.45 ms
 
 
 .. parsed-literal::
 
+    [Step 11/11] Dumping statistics report
     [ INFO ] Execution Devices:['CPU']
-    [ INFO ] Count:            1704 iterations
-    [ INFO ] Duration:         120454.83 ms
+    [ INFO ] Count:            1686 iterations
+    [ INFO ] Duration:         120531.12 ms
     [ INFO ] Latency:
-    [ INFO ]    Median:        423.45 ms
-    [ INFO ]    Average:       423.78 ms
-    [ INFO ]    Min:           358.59 ms
-    [ INFO ]    Max:           506.30 ms
-    [ INFO ] Throughput:   28.29 FPS
+    [ INFO ]    Median:        429.25 ms
+    [ INFO ]    Average:       428.34 ms
+    [ INFO ]    Min:           354.96 ms
+    [ INFO ]    Max:           506.55 ms
+    [ INFO ] Throughput:   27.98 FPS
 
diff --git a/docs/notebooks/204-segmenter-semantic-segmentation-with-output_files/index.html.tmp b/docs/notebooks/204-segmenter-semantic-segmentation-with-output_files/index.html.tmp
deleted file mode 100644
index a10dbfe08b9521..00000000000000
--- a/docs/notebooks/204-segmenter-semantic-segmentation-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,10 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/204-segmenter-semantic-segmentation-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/204-segmenter-semantic-segmentation-with-output_files/
../
-204-segmenter-semantic-segmentation-with-output..> 26-Jan-2024 01:05               72352
-204-segmenter-semantic-segmentation-with-output..> 26-Jan-2024 01:05              909669
-204-segmenter-semantic-segmentation-with-output..> 26-Jan-2024 01:05               72372
-204-segmenter-semantic-segmentation-with-output..> 26-Jan-2024 01:05              909654
-

-
diff --git a/docs/notebooks/205-vision-background-removal-with-output.rst b/docs/notebooks/205-vision-background-removal-with-output.rst
index afaeb0e8926153..5a3e1a62dbf92e 100644
--- a/docs/notebooks/205-vision-background-removal-with-output.rst
+++ b/docs/notebooks/205-vision-background-removal-with-output.rst
@@ -24,8 +24,7 @@ Table of contents:
    -  `Settings <#settings>`__
    -  `Load the U2-Net Model <#load-the-u2-net-model>`__
 
--  `Convert PyTorch U2-Net model to OpenVINO
-   IR <#convert-pytorch-u2-net-model-to-openvino-ir>`__
+-  `Convert PyTorch U2-Net model to OpenVINO IR <#convert-pytorch-u2-net-model-to-openvino-ir>`__
 -  `Load and Pre-Process Input
    Image <#load-and-pre-process-input-image>`__
 -  `Select inference device <#select-inference-device>`__
@@ -190,52 +189,52 @@ next cell loads the model and the pre-trained weights.
 .. parsed-literal::
 
 
- 11%|█         | 524k/4.68M [00:00<00:01, 3.36MB/s]
+ 11%|█         | 524k/4.68M [00:00<00:01, 3.35MB/s]
 
 .. parsed-literal::
 
 
- 22%|██▏       | 1.05M/4.68M [00:00<00:00, 3.74MB/s]
+ 22%|██▏       | 1.05M/4.68M [00:00<00:00, 3.71MB/s]
 
 .. parsed-literal::
 
 
- 34%|███▎      | 1.57M/4.68M [00:00<00:00, 3.84MB/s]
+ 34%|███▎      | 1.57M/4.68M [00:00<00:00, 3.78MB/s]
 
 .. parsed-literal::
 
 
- 45%|████▍     | 2.10M/4.68M [00:00<00:00, 3.89MB/s]
+ 45%|████▍     | 2.10M/4.68M [00:00<00:00, 3.88MB/s]
 
 .. parsed-literal::
 
 
- 56%|█████▌    | 2.62M/4.68M [00:00<00:00, 3.92MB/s]
+ 56%|█████▌    | 2.62M/4.68M [00:00<00:00, 3.96MB/s]
 
 .. parsed-literal::
 
 
- 67%|██████▋   | 3.15M/4.68M [00:00<00:00, 3.94MB/s]
+ 67%|██████▋   | 3.15M/4.68M [00:00<00:00, 3.95MB/s]
 
 .. parsed-literal::
 
 
- 78%|███████▊  | 3.67M/4.68M [00:00<00:00, 3.95MB/s]
+ 78%|███████▊  | 3.67M/4.68M [00:00<00:00, 3.97MB/s]
 
 .. parsed-literal::
 
 
- 90%|████████▉ | 4.19M/4.68M [00:01<00:00, 3.96MB/s]
+   90%|████████▉ | 4.19M/4.68M [00:01<00:00, 4.00MB/s]
 
 .. parsed-literal::
 
 
-   100%|██████████| 4.68M/4.68M [00:01<00:00, 4.05MB/s]
+   100%|██████████| 4.68M/4.68M [00:01<00:00, 4.15MB/s]
 
 .. parsed-literal::
 
 
-   100%|██████████| 4.68M/4.68M [00:01<00:00, 3.93MB/s]
+   100%|██████████| 4.68M/4.68M [00:01<00:00, 3.96MB/s]
 
 .. parsed-literal::
 
@@ -282,7 +281,7 @@ OpenVINO IR format. Executing the following command may take a while.
 
 .. parsed-literal::
 
-    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/torch/nn/functional.py:3769: UserWarning: nn.functional.upsample is deprecated. Use nn.functional.interpolate instead.
+    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/torch/nn/functional.py:3769: UserWarning: nn.functional.upsample is deprecated. Use nn.functional.interpolate instead.
       warnings.warn("nn.functional.upsample is deprecated. Use nn.functional.interpolate instead.")
 
 
@@ -382,7 +381,7 @@ Load the OpenVINO IR model to OpenVINO Runtime and do inference.
 
 .. parsed-literal::
 
-    Inference finished. Inference time: 0.113 seconds, FPS: 8.89.
+    Inference finished. Inference time: 0.110 seconds, FPS: 9.05.
 
 
 Visualize Results
diff --git a/docs/notebooks/205-vision-background-removal-with-output_files/index.html.tmp b/docs/notebooks/205-vision-background-removal-with-output_files/index.html.tmp
deleted file mode 100644
index b21b64b5af0327..00000000000000
--- a/docs/notebooks/205-vision-background-removal-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,8 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/205-vision-background-removal-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/205-vision-background-removal-with-output_files/
../
-205-vision-background-removal-with-output_22_0.png 26-Jan-2024 01:05              279572
-205-vision-background-removal-with-output_24_0.png 26-Jan-2024 01:05              927043
-

-
diff --git a/docs/notebooks/206-vision-paddlegan-anime-with-output.rst b/docs/notebooks/206-vision-paddlegan-anime-with-output.rst
index 1fb2c84c35f9cb..cfd0f16e9b470d 100644
--- a/docs/notebooks/206-vision-paddlegan-anime-with-output.rst
+++ b/docs/notebooks/206-vision-paddlegan-anime-with-output.rst
@@ -204,7 +204,7 @@ source of the function.
 
 .. parsed-literal::
 
-    [01/25 23:27:13] ppgan INFO: Found /opt/home/k8sworker/.cache/ppgan/animeganv2_hayao.pdparams
+    [02/09 23:41:27] ppgan INFO: Found /opt/home/k8sworker/.cache/ppgan/animeganv2_hayao.pdparams
 
 
 .. code:: ipython3
@@ -345,7 +345,7 @@ succeeds, the output of the next cell will include
 
 .. parsed-literal::
 
-    2024-01-25 23:27:21 [INFO]	Static PaddlePaddle model saved in model/paddle_model_static_onnx_temp_dir.
+    2024-02-09 23:41:36 [INFO]	Static PaddlePaddle model saved in model/paddle_model_static_onnx_temp_dir.
 
 
 .. parsed-literal::
@@ -356,12 +356,12 @@ succeeds, the output of the next cell will include
     [Paddle2ONNX] Start to parsing Paddle model...
     [Paddle2ONNX] Use opset_version = 11 for ONNX export.
     [Paddle2ONNX] PaddlePaddle model is exported as ONNX format now.
-    2024-01-25 23:27:21 [INFO]	ONNX model saved in model/paddlegan_anime.onnx.
+    2024-02-09 23:41:36 [INFO]	ONNX model saved in model/paddlegan_anime.onnx.
 
 
 .. parsed-literal::
 
-    I0125 23:27:21.862668 812000 program_interpreter.cc:212] New Executor is Running.
+    I0209 23:41:36.202327 2843665 program_interpreter.cc:212] New Executor is Running.
 
 
 Convert to OpenVINO IR
@@ -643,12 +643,12 @@ measure inference on one image. For more accurate benchmarking, use
 
 .. parsed-literal::
 
-    OpenVINO IR model in OpenVINO Runtime/CPU: 0.418 seconds per image, FPS: 2.39
+    OpenVINO IR model in OpenVINO Runtime/CPU: 0.427 seconds per image, FPS: 2.34
 
 
 .. parsed-literal::
 
-    PaddleGAN model on CPU: 6.256 seconds per image, FPS: 0.16
+    PaddleGAN model on CPU: 6.182 seconds per image, FPS: 0.16
 
 
 References
diff --git a/docs/notebooks/206-vision-paddlegan-anime-with-output_files/index.html.tmp b/docs/notebooks/206-vision-paddlegan-anime-with-output_files/index.html.tmp
deleted file mode 100644
index 1c40ee150cd958..00000000000000
--- a/docs/notebooks/206-vision-paddlegan-anime-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,8 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/206-vision-paddlegan-anime-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/206-vision-paddlegan-anime-with-output_files/
../
-206-vision-paddlegan-anime-with-output_15_0.png    26-Jan-2024 01:05             1810982
-206-vision-paddlegan-anime-with-output_37_0.png    26-Jan-2024 01:05             1931637
-

-
diff --git a/docs/notebooks/207-vision-paddlegan-superresolution-with-output.rst b/docs/notebooks/207-vision-paddlegan-superresolution-with-output.rst
index b2484b18e2c49c..7236dc119c2964 100644
--- a/docs/notebooks/207-vision-paddlegan-superresolution-with-output.rst
+++ b/docs/notebooks/207-vision-paddlegan-superresolution-with-output.rst
@@ -161,7 +161,7 @@ source code.
 
 .. parsed-literal::
 
-    [01/25 23:27:55] ppgan INFO: Found /opt/home/k8sworker/.cache/ppgan/DF2K_JPEG.pdparams
+    [02/09 23:42:09] ppgan INFO: Found /opt/home/k8sworker/.cache/ppgan/DF2K_JPEG.pdparams
 
 
 .. code:: ipython3
@@ -289,12 +289,12 @@ Convert PaddlePaddle Model to ONNX
 
 .. parsed-literal::
 
-    2024-01-25 23:28:02 [INFO]	Static PaddlePaddle model saved in model/paddle_model_static_onnx_temp_dir.
+    2024-02-09 23:42:16 [INFO]	Static PaddlePaddle model saved in model/paddle_model_static_onnx_temp_dir.
 
 
 .. parsed-literal::
 
-    I0125 23:28:01.927830 812342 program_interpreter.cc:212] New Executor is Running.
+    I0209 23:42:16.006111 2843987 program_interpreter.cc:212] New Executor is Running.
 
 
 .. parsed-literal::
@@ -303,13 +303,13 @@ Convert PaddlePaddle Model to ONNX
     [Paddle2ONNX] Model file path: model/paddle_model_static_onnx_temp_dir/model.pdmodel
     [Paddle2ONNX] Paramters file path: model/paddle_model_static_onnx_temp_dir/model.pdiparams
     [Paddle2ONNX] Start to parsing Paddle model...
-    [Paddle2ONNX] Use opset_version = 13 for ONNX export.
-    [Paddle2ONNX] PaddlePaddle model is exported as ONNX format now.
 
 
 .. parsed-literal::
 
-    2024-01-25 23:28:05 [INFO]	ONNX model saved in model/paddlegan_sr.onnx.
+    [Paddle2ONNX] Use opset_version = 13 for ONNX export.
+    [Paddle2ONNX] PaddlePaddle model is exported as ONNX format now.
+    2024-02-09 23:42:19 [INFO]	ONNX model saved in model/paddlegan_sr.onnx.
 
 
 Convert ONNX Model to OpenVINO IR with `Model Conversion Python API `__
@@ -394,7 +394,7 @@ select device from dropdown list for running inference using OpenVINO
 
 .. parsed-literal::
 
-    
+    
 
 
 
@@ -423,7 +423,7 @@ select device from dropdown list for running inference using OpenVINO
 
 .. parsed-literal::
 
-    Inference duration: 3.26 seconds
+    Inference duration: 3.27 seconds
 
 
 .. code:: ipython3
@@ -446,7 +446,7 @@ select device from dropdown list for running inference using OpenVINO
 
 .. parsed-literal::
 
-    
+    
 
 
 
diff --git a/docs/notebooks/207-vision-paddlegan-superresolution-with-output_files/index.html.tmp b/docs/notebooks/207-vision-paddlegan-superresolution-with-output_files/index.html.tmp
deleted file mode 100644
index e5a474bf2efb83..00000000000000
--- a/docs/notebooks/207-vision-paddlegan-superresolution-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,9 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/207-vision-paddlegan-superresolution-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/207-vision-paddlegan-superresolution-with-output_files/
../
-207-vision-paddlegan-superresolution-with-outpu..> 26-Jan-2024 01:04              436999
-207-vision-paddlegan-superresolution-with-outpu..> 26-Jan-2024 01:04              476190
-207-vision-paddlegan-superresolution-with-outpu..> 26-Jan-2024 01:04             2835305
-

-
diff --git a/docs/notebooks/208-optical-character-recognition-with-output.rst b/docs/notebooks/208-optical-character-recognition-with-output.rst
index 19f01996769cb9..d4d12998674c16 100644
--- a/docs/notebooks/208-optical-character-recognition-with-output.rst
+++ b/docs/notebooks/208-optical-character-recognition-with-output.rst
@@ -7,9 +7,9 @@ This tutorial demonstrates how to perform optical character recognition
 tutorial, which shows only text detection.
 
 The
-`horizontal-text-detection-0001 `__
+`horizontal-text-detection-0001 `__
 and
-`text-recognition-resnet `__
+`text-recognition-resnet `__
 models are used together for text detection and then text recognition.
 
 In this tutorial, Open Model Zoo tools including Model Downloader, Model
@@ -138,50 +138,50 @@ Downloading horizontal-text-detection-0001, text-recognition-resnet-fc…
 
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     ========== Downloading model/intel/horizontal-text-detection-0001/FP16/horizontal-text-detection-0001.bin
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-    ################|| Downloading text-recognition-resnet-fc ||################
-
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-
-.. parsed-literal::
-
-    ... 1%, 7168 KB, 3382 KB/s, 2 seconds passed
-... 1%, 7200 KB, 3389 KB/s, 2 seconds passed
-... 1%, 7232 KB, 3390 KB/s, 2 seconds passed
-... 1%, 7264 KB, 3403 KB/s, 2 seconds passed
-
-.. parsed-literal::
-
-    ... 1%, 7296 KB, 3387 KB/s, 2 seconds passed
-... 1%, 7328 KB, 3393 KB/s, 2 seconds passed
-... 1%, 7360 KB, 3395 KB/s, 2 seconds passed
-... 1%, 7392 KB, 3408 KB/s, 2 seconds passed
-... 1%, 7424 KB, 3392 KB/s, 2 seconds passed
-... 1%, 7456 KB, 3397 KB/s, 2 seconds passed
-... 1%, 7488 KB, 3400 KB/s, 2 seconds passed
-
-.. parsed-literal::
-
-    ... 1%, 7520 KB, 3413 KB/s, 2 seconds passed
-... 1%, 7552 KB, 3397 KB/s, 2 seconds passed
-... 1%, 7584 KB, 3402 KB/s, 2 seconds passed
-... 1%, 7616 KB, 3405 KB/s, 2 seconds passed
-... 1%, 7648 KB, 3400 KB/s, 2 seconds passed
-
-.. parsed-literal::
-
-    ... 1%, 7680 KB, 3402 KB/s, 2 seconds passed
-... 1%, 7712 KB, 3407 KB/s, 2 seconds passed
-... 1%, 7744 KB, 3409 KB/s, 2 seconds passed
-... 1%, 7776 KB, 3405 KB/s, 2 seconds passed
-... 1%, 7808 KB, 3406 KB/s, 2 seconds passed
-... 1%, 7840 KB, 3410 KB/s, 2 seconds passed
-
-.. parsed-literal::
-
-    ... 1%, 7872 KB, 3414 KB/s, 2 seconds passed
-... 1%, 7904 KB, 3409 KB/s, 2 seconds passed
-... 1%, 7936 KB, 3410 KB/s, 2 seconds passed
-... 1%, 7968 KB, 3415 KB/s, 2 seconds passed
-... 1%, 8000 KB, 3418 KB/s, 2 seconds passed
-... 1%, 8032 KB, 3414 KB/s, 2 seconds passed
-
-.. parsed-literal::
-
-    ... 1%, 8064 KB, 3415 KB/s, 2 seconds passed
-... 1%, 8096 KB, 3419 KB/s, 2 seconds passed
-... 1%, 8128 KB, 3422 KB/s, 2 seconds passed
-... 1%, 8160 KB, 3418 KB/s, 2 seconds passed
-... 1%, 8192 KB, 3419 KB/s, 2 seconds passed
-... 1%, 8224 KB, 3422 KB/s, 2 seconds passed
-
-.. parsed-literal::
-
-    ... 1%, 8256 KB, 3427 KB/s, 2 seconds passed
-... 1%, 8288 KB, 3421 KB/s, 2 seconds passed
-... 1%, 8320 KB, 3423 KB/s, 2 seconds passed
-... 1%, 8352 KB, 3426 KB/s, 2 seconds passed
-... 1%, 8384 KB, 3430 KB/s, 2 seconds passed
-... 1%, 8416 KB, 3425 KB/s, 2 seconds passed
-
-.. parsed-literal::
-
-    ... 1%, 8448 KB, 3426 KB/s, 2 seconds passed
-... 1%, 8480 KB, 3429 KB/s, 2 seconds passed
-... 1%, 8512 KB, 3434 KB/s, 2 seconds passed
-... 1%, 8544 KB, 3429 KB/s, 2 seconds passed
-... 1%, 8576 KB, 3429 KB/s, 2 seconds passed
-... 1%, 8608 KB, 3433 KB/s, 2 seconds passed
-
-.. parsed-literal::
-
-    ... 1%, 8640 KB, 3438 KB/s, 2 seconds passed
-... 1%, 8672 KB, 3433 KB/s, 2 seconds passed
-... 1%, 8704 KB, 3433 KB/s, 2 seconds passed
-... 1%, 8736 KB, 3437 KB/s, 2 seconds passed
-... 1%, 8768 KB, 3441 KB/s, 2 seconds passed
-... 1%, 8800 KB, 3437 KB/s, 2 seconds passed
-
-.. parsed-literal::
-
-    ... 1%, 8832 KB, 3436 KB/s, 2 seconds passed
-... 1%, 8864 KB, 3440 KB/s, 2 seconds passed
-... 1%, 8896 KB, 3444 KB/s, 2 seconds passed
-... 1%, 8928 KB, 3441 KB/s, 2 seconds passed
-... 1%, 8960 KB, 3439 KB/s, 2 seconds passed
-... 1%, 8992 KB, 3441 KB/s, 2 seconds passed
-
-.. parsed-literal::
-
-    ... 1%, 9024 KB, 3447 KB/s, 2 seconds passed
-... 1%, 9056 KB, 3439 KB/s, 2 seconds passed
-... 1%, 9088 KB, 3442 KB/s, 2 seconds passed
-... 1%, 9120 KB, 3445 KB/s, 2 seconds passed
-... 1%, 9152 KB, 3450 KB/s, 2 seconds passed
-
-.. parsed-literal::
-
-    ... 1%, 9184 KB, 3442 KB/s, 2 seconds passed
-... 1%, 9216 KB, 3445 KB/s, 2 seconds passed
-... 1%, 9248 KB, 3448 KB/s, 2 seconds passed
-... 1%, 9280 KB, 3454 KB/s, 2 seconds passed
-... 1%, 9312 KB, 3445 KB/s, 2 seconds passed
-... 1%, 9344 KB, 3449 KB/s, 2 seconds passed
-
-.. parsed-literal::
-
-    ... 1%, 9376 KB, 3450 KB/s, 2 seconds passed
-... 1%, 9408 KB, 3457 KB/s, 2 seconds passed
-... 1%, 9440 KB, 3449 KB/s, 2 seconds passed
-... 1%, 9472 KB, 3452 KB/s, 2 seconds passed
-... 1%, 9504 KB, 3454 KB/s, 2 seconds passed
-... 1%, 9536 KB, 3460 KB/s, 2 seconds passed
-
-.. parsed-literal::
-
-    ... 1%, 9568 KB, 3452 KB/s, 2 seconds passed
-... 1%, 9600 KB, 3453 KB/s, 2 seconds passed
-... 1%, 9632 KB, 3457 KB/s, 2 seconds passed
-... 1%, 9664 KB, 3462 KB/s, 2 seconds passed
-... 1%, 9696 KB, 3454 KB/s, 2 seconds passed
-... 1%, 9728 KB, 3455 KB/s, 2 seconds passed
-
-.. parsed-literal::
-
-    ... 1%, 9760 KB, 3460 KB/s, 2 seconds passed
-... 1%, 9792 KB, 3465 KB/s, 2 seconds passed
-... 1%, 9824 KB, 3458 KB/s, 2 seconds passed
-... 1%, 9856 KB, 3458 KB/s, 2 seconds passed
-... 1%, 9888 KB, 3463 KB/s, 2 seconds passed
-... 1%, 9920 KB, 3469 KB/s, 2 seconds passed
-
-.. parsed-literal::
-
-    ... 1%, 9952 KB, 3460 KB/s, 2 seconds passed
-... 1%, 9984 KB, 3461 KB/s, 2 seconds passed
-... 1%, 10016 KB, 3465 KB/s, 2 seconds passed
-... 1%, 10048 KB, 3472 KB/s, 2 seconds passed
-... 1%, 10080 KB, 3463 KB/s, 2 seconds passed
-... 1%, 10112 KB, 3464 KB/s, 2 seconds passed
-
-.. parsed-literal::
-
-    ... 1%, 10144 KB, 3468 KB/s, 2 seconds passed
-... 1%, 10176 KB, 3463 KB/s, 2 seconds passed
-... 1%, 10208 KB, 3466 KB/s, 2 seconds passed
-... 1%, 10240 KB, 3466 KB/s, 2 seconds passed
-... 1%, 10272 KB, 3471 KB/s, 2 seconds passed
-
-.. parsed-literal::
-
-    ... 1%, 10304 KB, 3465 KB/s, 2 seconds passed
-... 1%, 10336 KB, 3467 KB/s, 2 seconds passed
-... 1%, 10368 KB, 3468 KB/s, 2 seconds passed
-... 1%, 10400 KB, 3473 KB/s, 2 seconds passed
-... 1%, 10432 KB, 3467 KB/s, 3 seconds passed
-... 1%, 10464 KB, 3470 KB/s, 3 seconds passed
-
-.. parsed-literal::
-
-    ... 1%, 10496 KB, 3471 KB/s, 3 seconds passed
-... 1%, 10528 KB, 3475 KB/s, 3 seconds passed
-... 1%, 10560 KB, 3470 KB/s, 3 seconds passed
-... 1%, 10592 KB, 3472 KB/s, 3 seconds passed
-... 1%, 10624 KB, 3473 KB/s, 3 seconds passed
-... 1%, 10656 KB, 3477 KB/s, 3 seconds passed
-
-.. parsed-literal::
-
-    ... 1%, 10688 KB, 3473 KB/s, 3 seconds passed
-... 1%, 10720 KB, 3475 KB/s, 3 seconds passed
-... 1%, 10752 KB, 3475 KB/s, 3 seconds passed
-... 1%, 10784 KB, 3479 KB/s, 3 seconds passed
-... 1%, 10816 KB, 3475 KB/s, 3 seconds passed
-... 1%, 10848 KB, 3478 KB/s, 3 seconds passed
-
-.. parsed-literal::
-
-    ... 1%, 10880 KB, 3478 KB/s, 3 seconds passed
-... 1%, 10912 KB, 3482 KB/s, 3 seconds passed
-... 1%, 10944 KB, 3478 KB/s, 3 seconds passed
-... 1%, 10976 KB, 3480 KB/s, 3 seconds passed
-... 1%, 11008 KB, 3481 KB/s, 3 seconds passed
-... 1%, 11040 KB, 3484 KB/s, 3 seconds passed
-
-.. parsed-literal::
-
-    ... 1%, 11072 KB, 3480 KB/s, 3 seconds passed
-... 1%, 11104 KB, 3482 KB/s, 3 seconds passed
-... 1%, 11136 KB, 3483 KB/s, 3 seconds passed
-... 1%, 11168 KB, 3487 KB/s, 3 seconds passed
-... 1%, 11200 KB, 3483 KB/s, 3 seconds passed
-... 1%, 11232 KB, 3484 KB/s, 3 seconds passed
-
-.. parsed-literal::
-
-    ... 1%, 11264 KB, 3485 KB/s, 3 seconds passed
-... 1%, 11296 KB, 3489 KB/s, 3 seconds passed
-... 1%, 11328 KB, 3485 KB/s, 3 seconds passed
-... 1%, 11360 KB, 3486 KB/s, 3 seconds passed
-... 1%, 11392 KB, 3488 KB/s, 3 seconds passed
-... 1%, 11424 KB, 3491 KB/s, 3 seconds passed
-
-.. parsed-literal::
-
-    ... 1%, 11456 KB, 3487 KB/s, 3 seconds passed
-... 1%, 11488 KB, 3488 KB/s, 3 seconds passed
-... 1%, 11520 KB, 3490 KB/s, 3 seconds passed
-... 1%, 11552 KB, 3492 KB/s, 3 seconds passed
-... 1%, 11584 KB, 3489 KB/s, 3 seconds passed
-... 1%, 11616 KB, 3490 KB/s, 3 seconds passed
-
-.. parsed-literal::
-
-    ... 1%, 11648 KB, 3492 KB/s, 3 seconds passed
-... 1%, 11680 KB, 3495 KB/s, 3 seconds passed
-... 1%, 11712 KB, 3491 KB/s, 3 seconds passed
-... 1%, 11744 KB, 3493 KB/s, 3 seconds passed
-... 1%, 11776 KB, 3494 KB/s, 3 seconds passed
-... 1%, 11808 KB, 3497 KB/s, 3 seconds passed
-
-.. parsed-literal::
-
-    ... 1%, 11840 KB, 3493 KB/s, 3 seconds passed
-... 1%, 11872 KB, 3495 KB/s, 3 seconds passed
-... 1%, 11904 KB, 3496 KB/s, 3 seconds passed
-... 1%, 11936 KB, 3499 KB/s, 3 seconds passed
-... 1%, 11968 KB, 3495 KB/s, 3 seconds passed
-... 1%, 12000 KB, 3497 KB/s, 3 seconds passed
-
-.. parsed-literal::
-
-    ... 1%, 12032 KB, 3498 KB/s, 3 seconds passed
-... 1%, 12064 KB, 3501 KB/s, 3 seconds passed
-... 1%, 12096 KB, 3497 KB/s, 3 seconds passed
-... 1%, 12128 KB, 3499 KB/s, 3 seconds passed
-... 1%, 12160 KB, 3500 KB/s, 3 seconds passed
-... 1%, 12192 KB, 3502 KB/s, 3 seconds passed
-
-.. parsed-literal::
-
-    ... 1%, 12224 KB, 3499 KB/s, 3 seconds passed
-... 1%, 12256 KB, 3501 KB/s, 3 seconds passed
-... 1%, 12288 KB, 3502 KB/s, 3 seconds passed
-... 1%, 12320 KB, 3504 KB/s, 3 seconds passed
-... 1%, 12352 KB, 3501 KB/s, 3 seconds passed
-... 1%, 12384 KB, 3503 KB/s, 3 seconds passed
-
-.. parsed-literal::
-
-    ... 1%, 12416 KB, 3504 KB/s, 3 seconds passed
-... 1%, 12448 KB, 3505 KB/s, 3 seconds passed
-... 1%, 12480 KB, 3502 KB/s, 3 seconds passed
-... 1%, 12512 KB, 3505 KB/s, 3 seconds passed
-... 1%, 12544 KB, 3505 KB/s, 3 seconds passed
-... 1%, 12576 KB, 3507 KB/s, 3 seconds passed
-
-.. parsed-literal::
-
-    ... 1%, 12608 KB, 3504 KB/s, 3 seconds passed
-... 1%, 12640 KB, 3503 KB/s, 3 seconds passed
-
-.. parsed-literal::
-
-    ... 1%, 12672 KB, 3470 KB/s, 3 seconds passed
-... 1%, 12704 KB, 3478 KB/s, 3 seconds passed
-... 1%, 12736 KB, 3486 KB/s, 3 seconds passed
-... 1%, 12768 KB, 3495 KB/s, 3 seconds passed
-... 1%, 12800 KB, 3471 KB/s, 3 seconds passed
-
-.. parsed-literal::
-
-    ... 1%, 12832 KB, 3456 KB/s, 3 seconds passed
-... 1%, 12864 KB, 3462 KB/s, 3 seconds passed
-... 1%, 12896 KB, 3467 KB/s, 3 seconds passed
-... 1%, 12928 KB, 3473 KB/s, 3 seconds passed
-
-.. parsed-literal::
-
-    ... 1%, 12960 KB, 3458 KB/s, 3 seconds passed
-... 1%, 12992 KB, 3464 KB/s, 3 seconds passed
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-... 1%, 13120 KB, 3466 KB/s, 3 seconds passed
-... 1%, 13152 KB, 3472 KB/s, 3 seconds passed
-... 1%, 13184 KB, 3477 KB/s, 3 seconds passed
-
-.. parsed-literal::
-
-    ... 1%, 13216 KB, 3461 KB/s, 3 seconds passed
-... 1%, 13248 KB, 3468 KB/s, 3 seconds passed
-... 1%, 13280 KB, 3474 KB/s, 3 seconds passed
-... 1%, 13312 KB, 3479 KB/s, 3 seconds passed
-
-.. parsed-literal::
-
-    ... 1%, 13344 KB, 3463 KB/s, 3 seconds passed
-... 1%, 13376 KB, 3469 KB/s, 3 seconds passed
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-... 1%, 13504 KB, 3471 KB/s, 3 seconds passed
-... 1%, 13536 KB, 3478 KB/s, 3 seconds passed
-... 1%, 13568 KB, 3483 KB/s, 3 seconds passed
-
-.. parsed-literal::
-
-    ... 1%, 13600 KB, 3468 KB/s, 3 seconds passed
-... 1%, 13632 KB, 3474 KB/s, 3 seconds passed
-... 1%, 13664 KB, 3480 KB/s, 3 seconds passed
-... 1%, 13696 KB, 3485 KB/s, 3 seconds passed
-
-.. parsed-literal::
-
-    ... 1%, 13728 KB, 3470 KB/s, 3 seconds passed
-... 1%, 13760 KB, 3475 KB/s, 3 seconds passed
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-... 1%, 13856 KB, 3472 KB/s, 3 seconds passed
-... 1%, 13888 KB, 3477 KB/s, 3 seconds passed
-... 2%, 13920 KB, 3484 KB/s, 3 seconds passed
-
-.. parsed-literal::
-
-    ... 2%, 13952 KB, 3489 KB/s, 3 seconds passed
-... 2%, 13984 KB, 3473 KB/s, 4 seconds passed
-... 2%, 14016 KB, 3479 KB/s, 4 seconds passed
-... 2%, 14048 KB, 3485 KB/s, 4 seconds passed
-... 2%, 14080 KB, 3491 KB/s, 4 seconds passed
-
-.. parsed-literal::
-
-    ... 2%, 14112 KB, 3475 KB/s, 4 seconds passed
-... 2%, 14144 KB, 3480 KB/s, 4 seconds passed
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-... 2%, 14208 KB, 3492 KB/s, 4 seconds passed
-... 2%, 14240 KB, 3477 KB/s, 4 seconds passed
-... 2%, 14272 KB, 3482 KB/s, 4 seconds passed
-... 2%, 14304 KB, 3488 KB/s, 4 seconds passed
-
-.. parsed-literal::
-
-    ... 2%, 14336 KB, 3494 KB/s, 4 seconds passed
-... 2%, 14368 KB, 3479 KB/s, 4 seconds passed
-... 2%, 14400 KB, 3484 KB/s, 4 seconds passed
-... 2%, 14432 KB, 3490 KB/s, 4 seconds passed
-... 2%, 14464 KB, 3496 KB/s, 4 seconds passed
-
-.. parsed-literal::
-
-    ... 2%, 14496 KB, 3480 KB/s, 4 seconds passed
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-... 2%, 14560 KB, 3491 KB/s, 4 seconds passed
-... 2%, 14592 KB, 3497 KB/s, 4 seconds passed
-... 2%, 14624 KB, 3482 KB/s, 4 seconds passed
-... 2%, 14656 KB, 3487 KB/s, 4 seconds passed
-
-.. parsed-literal::
-
-    ... 2%, 14688 KB, 3493 KB/s, 4 seconds passed
-... 2%, 14720 KB, 3499 KB/s, 4 seconds passed
-... 2%, 14752 KB, 3484 KB/s, 4 seconds passed
-... 2%, 14784 KB, 3489 KB/s, 4 seconds passed
-... 2%, 14816 KB, 3495 KB/s, 4 seconds passed
-... 2%, 14848 KB, 3500 KB/s, 4 seconds passed
-
-.. parsed-literal::
-
-    ... 2%, 14880 KB, 3485 KB/s, 4 seconds passed
-... 2%, 14912 KB, 3491 KB/s, 4 seconds passed
-... 2%, 14944 KB, 3497 KB/s, 4 seconds passed
-... 2%, 14976 KB, 3502 KB/s, 4 seconds passed
-... 2%, 15008 KB, 3487 KB/s, 4 seconds passed
-... 2%, 15040 KB, 3492 KB/s, 4 seconds passed
-
-.. parsed-literal::
-
-    ... 2%, 15072 KB, 3499 KB/s, 4 seconds passed
-... 2%, 15104 KB, 3504 KB/s, 4 seconds passed
-... 2%, 15136 KB, 3488 KB/s, 4 seconds passed
-... 2%, 15168 KB, 3494 KB/s, 4 seconds passed
-... 2%, 15200 KB, 3500 KB/s, 4 seconds passed
-... 2%, 15232 KB, 3505 KB/s, 4 seconds passed
-
-.. parsed-literal::
-
-    ... 2%, 15264 KB, 3490 KB/s, 4 seconds passed
-... 2%, 15296 KB, 3496 KB/s, 4 seconds passed
-... 2%, 15328 KB, 3501 KB/s, 4 seconds passed
-... 2%, 15360 KB, 3507 KB/s, 4 seconds passed
-... 2%, 15392 KB, 3491 KB/s, 4 seconds passed
-
-.. parsed-literal::
-
-    ... 2%, 15424 KB, 3497 KB/s, 4 seconds passed
-... 2%, 15456 KB, 3503 KB/s, 4 seconds passed
-... 2%, 15488 KB, 3509 KB/s, 4 seconds passed
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-... 2%, 15552 KB, 3498 KB/s, 4 seconds passed
-... 2%, 15584 KB, 3504 KB/s, 4 seconds passed
-... 2%, 15616 KB, 3510 KB/s, 4 seconds passed
-
-.. parsed-literal::
-
-    ... 2%, 15648 KB, 3494 KB/s, 4 seconds passed
-... 2%, 15680 KB, 3500 KB/s, 4 seconds passed
-... 2%, 15712 KB, 3506 KB/s, 4 seconds passed
-... 2%, 15744 KB, 3494 KB/s, 4 seconds passed
-
-.. parsed-literal::
-
-    ... 2%, 15776 KB, 3495 KB/s, 4 seconds passed
-... 2%, 15808 KB, 3501 KB/s, 4 seconds passed
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-... 2%, 15872 KB, 3496 KB/s, 4 seconds passed
-... 2%, 15904 KB, 3497 KB/s, 4 seconds passed
-... 2%, 15936 KB, 3503 KB/s, 4 seconds passed
-... 2%, 15968 KB, 3509 KB/s, 4 seconds passed
-
-.. parsed-literal::
-
-    ... 2%, 16000 KB, 3497 KB/s, 4 seconds passed
-... 2%, 16032 KB, 3498 KB/s, 4 seconds passed
-... 2%, 16064 KB, 3504 KB/s, 4 seconds passed
-... 2%, 16096 KB, 3510 KB/s, 4 seconds passed
-... 2%, 16128 KB, 3499 KB/s, 4 seconds passed
-
-.. parsed-literal::
-
-    ... 2%, 16160 KB, 3500 KB/s, 4 seconds passed
-... 2%, 16192 KB, 3505 KB/s, 4 seconds passed
-... 2%, 16224 KB, 3511 KB/s, 4 seconds passed
-... 2%, 16256 KB, 3500 KB/s, 4 seconds passed
-... 2%, 16288 KB, 3501 KB/s, 4 seconds passed
-... 2%, 16320 KB, 3507 KB/s, 4 seconds passed
-... 2%, 16352 KB, 3513 KB/s, 4 seconds passed
-
-.. parsed-literal::
-
-    ... 2%, 16384 KB, 3502 KB/s, 4 seconds passed
-... 2%, 16416 KB, 3503 KB/s, 4 seconds passed
-... 2%, 16448 KB, 3508 KB/s, 4 seconds passed
-... 2%, 16480 KB, 3514 KB/s, 4 seconds passed
-... 2%, 16512 KB, 3503 KB/s, 4 seconds passed
-
-.. parsed-literal::
-
-    ... 2%, 16544 KB, 3504 KB/s, 4 seconds passed
-... 2%, 16576 KB, 3510 KB/s, 4 seconds passed
-
-.. parsed-literal::
-
-    ... 2%, 16608 KB, 3466 KB/s, 4 seconds passed
-... 2%, 16640 KB, 3472 KB/s, 4 seconds passed
-... 2%, 16672 KB, 3479 KB/s, 4 seconds passed
-... 2%, 16704 KB, 3485 KB/s, 4 seconds passed
-
-.. parsed-literal::
-
-    ... 2%, 16736 KB, 3468 KB/s, 4 seconds passed
-... 2%, 16768 KB, 3472 KB/s, 4 seconds passed
-... 2%, 16800 KB, 3463 KB/s, 4 seconds passed
-... 2%, 16832 KB, 3466 KB/s, 4 seconds passed
-... 2%, 16864 KB, 3468 KB/s, 4 seconds passed
-... 2%, 16896 KB, 3473 KB/s, 4 seconds passed
-
-.. parsed-literal::
-
-    ... 2%, 16928 KB, 3464 KB/s, 4 seconds passed
-... 2%, 16960 KB, 3465 KB/s, 4 seconds passed
-... 2%, 16992 KB, 3470 KB/s, 4 seconds passed
-... 2%, 17024 KB, 3475 KB/s, 4 seconds passed
-... 2%, 17056 KB, 3465 KB/s, 4 seconds passed
-
-.. parsed-literal::
-
-    ... 2%, 17088 KB, 3466 KB/s, 4 seconds passed
-... 2%, 17120 KB, 3471 KB/s, 4 seconds passed
-... 2%, 17152 KB, 3476 KB/s, 4 seconds passed
-... 2%, 17184 KB, 3467 KB/s, 4 seconds passed
-... 2%, 17216 KB, 3468 KB/s, 4 seconds passed
-... 2%, 17248 KB, 3473 KB/s, 4 seconds passed
-... 2%, 17280 KB, 3477 KB/s, 4 seconds passed
-
-.. parsed-literal::
-
-    ... 2%, 17312 KB, 3469 KB/s, 4 seconds passed
-... 2%, 17344 KB, 3469 KB/s, 4 seconds passed
-... 2%, 17376 KB, 3474 KB/s, 5 seconds passed
-... 2%, 17408 KB, 3479 KB/s, 5 seconds passed
-... 2%, 17440 KB, 3471 KB/s, 5 seconds passed
-
-.. parsed-literal::
-
-    ... 2%, 17472 KB, 3471 KB/s, 5 seconds passed
-... 2%, 17504 KB, 3475 KB/s, 5 seconds passed
-... 2%, 17536 KB, 3480 KB/s, 5 seconds passed
-... 2%, 17568 KB, 3472 KB/s, 5 seconds passed
-... 2%, 17600 KB, 3472 KB/s, 5 seconds passed
-... 2%, 17632 KB, 3477 KB/s, 5 seconds passed
-... 2%, 17664 KB, 3482 KB/s, 5 seconds passed
-
-.. parsed-literal::
-
-    ... 2%, 17696 KB, 3474 KB/s, 5 seconds passed
-... 2%, 17728 KB, 3474 KB/s, 5 seconds passed
-... 2%, 17760 KB, 3478 KB/s, 5 seconds passed
-... 2%, 17792 KB, 3483 KB/s, 5 seconds passed
-
-.. parsed-literal::
-
-    ... 2%, 17824 KB, 3473 KB/s, 5 seconds passed
-... 2%, 17856 KB, 3475 KB/s, 5 seconds passed
-... 2%, 17888 KB, 3479 KB/s, 5 seconds passed
-... 2%, 17920 KB, 3484 KB/s, 5 seconds passed
-... 2%, 17952 KB, 3474 KB/s, 5 seconds passed
-... 2%, 17984 KB, 3476 KB/s, 5 seconds passed
-... 2%, 18016 KB, 3481 KB/s, 5 seconds passed
-... 2%, 18048 KB, 3486 KB/s, 5 seconds passed
-
-.. parsed-literal::
-
-    ... 2%, 18080 KB, 3476 KB/s, 5 seconds passed
-... 2%, 18112 KB, 3478 KB/s, 5 seconds passed
-... 2%, 18144 KB, 3482 KB/s, 5 seconds passed
-... 2%, 18176 KB, 3487 KB/s, 5 seconds passed
-
-.. parsed-literal::
-
-    ... 2%, 18208 KB, 3478 KB/s, 5 seconds passed
-... 2%, 18240 KB, 3479 KB/s, 5 seconds passed
-... 2%, 18272 KB, 3483 KB/s, 5 seconds passed
-... 2%, 18304 KB, 3488 KB/s, 5 seconds passed
-... 2%, 18336 KB, 3479 KB/s, 5 seconds passed
-... 2%, 18368 KB, 3481 KB/s, 5 seconds passed
-... 2%, 18400 KB, 3485 KB/s, 5 seconds passed
-
-.. parsed-literal::
-
-    ... 2%, 18432 KB, 3489 KB/s, 5 seconds passed
-... 2%, 18464 KB, 3480 KB/s, 5 seconds passed
-... 2%, 18496 KB, 3482 KB/s, 5 seconds passed
-... 2%, 18528 KB, 3486 KB/s, 5 seconds passed
-
-.. parsed-literal::
-
-    ... 2%, 18560 KB, 3479 KB/s, 5 seconds passed
-... 2%, 18592 KB, 3482 KB/s, 5 seconds passed
-... 2%, 18624 KB, 3484 KB/s, 5 seconds passed
-... 2%, 18656 KB, 3488 KB/s, 5 seconds passed
-... 2%, 18688 KB, 3480 KB/s, 5 seconds passed
-... 2%, 18720 KB, 3483 KB/s, 5 seconds passed
-... 2%, 18752 KB, 3485 KB/s, 5 seconds passed
-... 2%, 18784 KB, 3489 KB/s, 5 seconds passed
-
-.. parsed-literal::
-
-    ... 2%, 18816 KB, 3482 KB/s, 5 seconds passed
-... 2%, 18848 KB, 3484 KB/s, 5 seconds passed
-... 2%, 18880 KB, 3487 KB/s, 5 seconds passed
-... 2%, 18912 KB, 3490 KB/s, 5 seconds passed
-
-.. parsed-literal::
-
-    ... 2%, 18944 KB, 3483 KB/s, 5 seconds passed
-... 2%, 18976 KB, 3485 KB/s, 5 seconds passed
-... 2%, 19008 KB, 3487 KB/s, 5 seconds passed
-... 2%, 19040 KB, 3492 KB/s, 5 seconds passed
-... 2%, 19072 KB, 3484 KB/s, 5 seconds passed
-... 2%, 19104 KB, 3487 KB/s, 5 seconds passed
-... 2%, 19136 KB, 3489 KB/s, 5 seconds passed
-
-.. parsed-literal::
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+    ################|| Downloading text-recognition-resnet-fc ||################
 
-.. parsed-literal::
+    ========== Downloading model/public/text-recognition-resnet-fc/vedastr/models/__init__.py
 
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+    ========== Downloading model/public/text-recognition-resnet-fc/vedastr/models/builder.py
 
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+    ========== Downloading model/public/text-recognition-resnet-fc/vedastr/models/model.py
 
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+    ========== Downloading model/public/text-recognition-resnet-fc/vedastr/models/weight_init.py
 
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+    ========== Downloading model/public/text-recognition-resnet-fc/vedastr/models/registry.py
 
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+    ========== Downloading model/public/text-recognition-resnet-fc/vedastr/models/heads/__init__.py
 
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+    ========== Downloading model/public/text-recognition-resnet-fc/vedastr/models/heads/builder.py
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 8%, 57792 KB, 3352 KB/s, 17 seconds passed
-... 8%, 57824 KB, 3353 KB/s, 17 seconds passed
-... 8%, 57856 KB, 3351 KB/s, 17 seconds passed
-... 8%, 57888 KB, 3352 KB/s, 17 seconds passed
-... 8%, 57920 KB, 3353 KB/s, 17 seconds passed
-... 8%, 57952 KB, 3354 KB/s, 17 seconds passed
+    ... 1%, 7808 KB, 3384 KB/s, 2 seconds passed
+... 1%, 7840 KB, 3385 KB/s, 2 seconds passed
+... 1%, 7872 KB, 3398 KB/s, 2 seconds passed
+... 1%, 7904 KB, 3410 KB/s, 2 seconds passed
 
 .. parsed-literal::
 
-    ... 8%, 57984 KB, 3352 KB/s, 17 seconds passed
-... 8%, 58016 KB, 3353 KB/s, 17 seconds passed
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-... 8%, 58080 KB, 3355 KB/s, 17 seconds passed
-... 8%, 58112 KB, 3353 KB/s, 17 seconds passed
-... 8%, 58144 KB, 3353 KB/s, 17 seconds passed
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+... 1%, 8096 KB, 3393 KB/s, 2 seconds passed
+... 1%, 8128 KB, 3406 KB/s, 2 seconds passed
+... 1%, 8160 KB, 3419 KB/s, 2 seconds passed
 
 .. parsed-literal::
 
-    ... 8%, 58176 KB, 3354 KB/s, 17 seconds passed
-... 8%, 58208 KB, 3355 KB/s, 17 seconds passed
-... 8%, 58240 KB, 3353 KB/s, 17 seconds passed
-... 8%, 58272 KB, 3354 KB/s, 17 seconds passed
-... 8%, 58304 KB, 3355 KB/s, 17 seconds passed
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+... 1%, 8256 KB, 3410 KB/s, 2 seconds passed
+... 1%, 8288 KB, 3423 KB/s, 2 seconds passed
 
 .. parsed-literal::
 
-    ... 8%, 58368 KB, 3354 KB/s, 17 seconds passed
-... 8%, 58400 KB, 3355 KB/s, 17 seconds passed
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+... 1%, 8480 KB, 3407 KB/s, 2 seconds passed
+... 1%, 8512 KB, 3418 KB/s, 2 seconds passed
+... 1%, 8544 KB, 3430 KB/s, 2 seconds passed
 
 .. parsed-literal::
 
-    ... 8%, 58560 KB, 3356 KB/s, 17 seconds passed
-... 8%, 58592 KB, 3357 KB/s, 17 seconds passed
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+... 1%, 8640 KB, 3422 KB/s, 2 seconds passed
+... 1%, 8672 KB, 3434 KB/s, 2 seconds passed
 
 .. parsed-literal::
 
-    ... 8%, 58752 KB, 3356 KB/s, 17 seconds passed
-... 8%, 58784 KB, 3357 KB/s, 17 seconds passed
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-... 8%, 58880 KB, 3357 KB/s, 17 seconds passed
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+... 1%, 8864 KB, 3419 KB/s, 2 seconds passed
+... 1%, 8896 KB, 3431 KB/s, 2 seconds passed
+... 1%, 8928 KB, 3441 KB/s, 2 seconds passed
 
 .. parsed-literal::
 
-    ... 8%, 58912 KB, 3357 KB/s, 17 seconds passed
-... 8%, 58944 KB, 3358 KB/s, 17 seconds passed
-... 8%, 58976 KB, 3359 KB/s, 17 seconds passed
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-... 8%, 59072 KB, 3359 KB/s, 17 seconds passed
-... 8%, 59104 KB, 3360 KB/s, 17 seconds passed
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+... 1%, 8992 KB, 3424 KB/s, 2 seconds passed
+... 1%, 9024 KB, 3434 KB/s, 2 seconds passed
+... 1%, 9056 KB, 3445 KB/s, 2 seconds passed
 
 .. parsed-literal::
 
-    ... 8%, 59136 KB, 3358 KB/s, 17 seconds passed
-... 8%, 59168 KB, 3359 KB/s, 17 seconds passed
-... 8%, 59200 KB, 3360 KB/s, 17 seconds passed
-... 8%, 59232 KB, 3360 KB/s, 17 seconds passed
-... 8%, 59264 KB, 3359 KB/s, 17 seconds passed
+    ... 1%, 9088 KB, 3426 KB/s, 2 seconds passed
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+... 1%, 9248 KB, 3430 KB/s, 2 seconds passed
+... 1%, 9280 KB, 3441 KB/s, 2 seconds passed
+... 1%, 9312 KB, 3451 KB/s, 2 seconds passed
 
 .. parsed-literal::
 
-    ... 8%, 59296 KB, 3359 KB/s, 17 seconds passed
-... 8%, 59328 KB, 3360 KB/s, 17 seconds passed
-... 8%, 59360 KB, 3361 KB/s, 17 seconds passed
-... 8%, 59392 KB, 3359 KB/s, 17 seconds passed
-... 8%, 59424 KB, 3360 KB/s, 17 seconds passed
-... 8%, 59456 KB, 3361 KB/s, 17 seconds passed
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+... 1%, 9376 KB, 3434 KB/s, 2 seconds passed
+... 1%, 9408 KB, 3445 KB/s, 2 seconds passed
+... 1%, 9440 KB, 3455 KB/s, 2 seconds passed
 
 .. parsed-literal::
 
-    ... 8%, 59520 KB, 3360 KB/s, 17 seconds passed
-... 8%, 59552 KB, 3360 KB/s, 17 seconds passed
-... 8%, 59584 KB, 3361 KB/s, 17 seconds passed
-... 8%, 59616 KB, 3362 KB/s, 17 seconds passed
-... 8%, 59648 KB, 3361 KB/s, 17 seconds passed
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+... 1%, 9632 KB, 3439 KB/s, 2 seconds passed
+... 1%, 9664 KB, 3450 KB/s, 2 seconds passed
+... 1%, 9696 KB, 3461 KB/s, 2 seconds passed
 
 .. parsed-literal::
 
-    ... 8%, 59680 KB, 3361 KB/s, 17 seconds passed
-... 8%, 59712 KB, 3362 KB/s, 17 seconds passed
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-... 8%, 59808 KB, 3362 KB/s, 17 seconds passed
-... 8%, 59840 KB, 3363 KB/s, 17 seconds passed
-... 8%, 59872 KB, 3363 KB/s, 17 seconds passed
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+... 1%, 9792 KB, 3453 KB/s, 2 seconds passed
+... 1%, 9824 KB, 3464 KB/s, 2 seconds passed
 
 .. parsed-literal::
 
-    ... 8%, 59904 KB, 3362 KB/s, 17 seconds passed
-... 8%, 59936 KB, 3362 KB/s, 17 seconds passed
-... 8%, 59968 KB, 3363 KB/s, 17 seconds passed
-... 8%, 60000 KB, 3364 KB/s, 17 seconds passed
-... 8%, 60032 KB, 3363 KB/s, 17 seconds passed
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+... 1%, 10016 KB, 3447 KB/s, 2 seconds passed
+... 1%, 10048 KB, 3458 KB/s, 2 seconds passed
 
 .. parsed-literal::
 
-    ... 8%, 60064 KB, 3363 KB/s, 17 seconds passed
-... 8%, 60096 KB, 3364 KB/s, 17 seconds passed
-... 8%, 60128 KB, 3365 KB/s, 17 seconds passed
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-... 8%, 60192 KB, 3364 KB/s, 17 seconds passed
-... 8%, 60224 KB, 3365 KB/s, 17 seconds passed
-... 8%, 60256 KB, 3365 KB/s, 17 seconds passed
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+... 1%, 10176 KB, 3461 KB/s, 2 seconds passed
+... 1%, 10208 KB, 3454 KB/s, 2 seconds passed
 
 .. parsed-literal::
 
-    ... 8%, 60288 KB, 3364 KB/s, 17 seconds passed
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-... 8%, 60352 KB, 3365 KB/s, 17 seconds passed
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-... 8%, 60416 KB, 3365 KB/s, 17 seconds passed
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 .. parsed-literal::
 
-    ... 8%, 60448 KB, 3365 KB/s, 17 seconds passed
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+... 1%, 10592 KB, 3463 KB/s, 3 seconds passed
 
 .. parsed-literal::
 
-    ... 8%, 60672 KB, 3366 KB/s, 18 seconds passed
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 .. parsed-literal::
 
-    ... 8%, 60832 KB, 3367 KB/s, 18 seconds passed
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 .. parsed-literal::
 
-    ... 8%, 61056 KB, 3368 KB/s, 18 seconds passed
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 .. parsed-literal::
 
-    ... 8%, 61184 KB, 3368 KB/s, 18 seconds passed
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 .. parsed-literal::
 
-    ... 8%, 61408 KB, 3369 KB/s, 18 seconds passed
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 .. parsed-literal::
 
-    ... 8%, 61568 KB, 3370 KB/s, 18 seconds passed
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 .. parsed-literal::
 
-    ... 8%, 61792 KB, 3371 KB/s, 18 seconds passed
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 .. parsed-literal::
 
-    ... 8%, 61952 KB, 3372 KB/s, 18 seconds passed
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 .. parsed-literal::
 
-    ... 8%, 62176 KB, 3373 KB/s, 18 seconds passed
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+... 1%, 12288 KB, 3491 KB/s, 3 seconds passed
 
 .. parsed-literal::
 
-    ... 8%, 62336 KB, 3374 KB/s, 18 seconds passed
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+... 1%, 12448 KB, 3494 KB/s, 3 seconds passed
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 .. parsed-literal::
 
-    ... 8%, 62560 KB, 3375 KB/s, 18 seconds passed
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-... 9%, 62688 KB, 3375 KB/s, 18 seconds passed
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+... 1%, 12672 KB, 3497 KB/s, 3 seconds passed
 
 .. parsed-literal::
 
-    ... 9%, 62720 KB, 3376 KB/s, 18 seconds passed
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-... 9%, 62816 KB, 3376 KB/s, 18 seconds passed
-... 9%, 62848 KB, 3376 KB/s, 18 seconds passed
-... 9%, 62880 KB, 3377 KB/s, 18 seconds passed
+    ... 1%, 12704 KB, 3499 KB/s, 3 seconds passed
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+... 1%, 12832 KB, 3500 KB/s, 3 seconds passed
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 .. parsed-literal::
 
-    ... 9%, 62912 KB, 3378 KB/s, 18 seconds passed
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-... 9%, 62976 KB, 3377 KB/s, 18 seconds passed
-... 9%, 63008 KB, 3377 KB/s, 18 seconds passed
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+    ... 1%, 12896 KB, 3503 KB/s, 3 seconds passed
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+... 1%, 13024 KB, 3501 KB/s, 3 seconds passed
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 .. parsed-literal::
 
-    ... 9%, 63072 KB, 3377 KB/s, 18 seconds passed
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-... 9%, 63200 KB, 3378 KB/s, 18 seconds passed
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-... 9%, 63264 KB, 3378 KB/s, 18 seconds passed
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+... 1%, 13216 KB, 3505 KB/s, 3 seconds passed
 
 .. parsed-literal::
 
-    ... 9%, 63296 KB, 3379 KB/s, 18 seconds passed
-... 9%, 63328 KB, 3378 KB/s, 18 seconds passed
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-... 9%, 63392 KB, 3379 KB/s, 18 seconds passed
-... 9%, 63424 KB, 3380 KB/s, 18 seconds passed
+    ... 1%, 13248 KB, 3503 KB/s, 3 seconds passed
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+... 1%, 13376 KB, 3505 KB/s, 3 seconds passed
+... 1%, 13408 KB, 3506 KB/s, 3 seconds passed
 
 .. parsed-literal::
 
-    ... 9%, 63456 KB, 3379 KB/s, 18 seconds passed
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-... 9%, 63520 KB, 3380 KB/s, 18 seconds passed
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-... 9%, 63584 KB, 3379 KB/s, 18 seconds passed
-... 9%, 63616 KB, 3380 KB/s, 18 seconds passed
-... 9%, 63648 KB, 3380 KB/s, 18 seconds passed
+    ... 1%, 13440 KB, 3506 KB/s, 3 seconds passed
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+... 1%, 13536 KB, 3508 KB/s, 3 seconds passed
+... 1%, 13568 KB, 3508 KB/s, 3 seconds passed
+... 1%, 13600 KB, 3511 KB/s, 3 seconds passed
 
 .. parsed-literal::
 
-    ... 9%, 63680 KB, 3381 KB/s, 18 seconds passed
-... 9%, 63712 KB, 3380 KB/s, 18 seconds passed
-... 9%, 63744 KB, 3380 KB/s, 18 seconds passed
-... 9%, 63776 KB, 3381 KB/s, 18 seconds passed
-... 9%, 63808 KB, 3382 KB/s, 18 seconds passed
+    ... 1%, 13632 KB, 3509 KB/s, 3 seconds passed
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+... 1%, 13696 KB, 3509 KB/s, 3 seconds passed
+... 1%, 13728 KB, 3512 KB/s, 3 seconds passed
+... 1%, 13760 KB, 3520 KB/s, 3 seconds passed
+... 1%, 13792 KB, 3512 KB/s, 3 seconds passed
 
 .. parsed-literal::
 
-    ... 9%, 63840 KB, 3381 KB/s, 18 seconds passed
-... 9%, 63872 KB, 3381 KB/s, 18 seconds passed
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-... 9%, 63936 KB, 3382 KB/s, 18 seconds passed
-... 9%, 63968 KB, 3381 KB/s, 18 seconds passed
-... 9%, 64000 KB, 3381 KB/s, 18 seconds passed
+    ... 1%, 13824 KB, 3513 KB/s, 3 seconds passed
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+... 2%, 13920 KB, 3514 KB/s, 3 seconds passed
+... 2%, 13952 KB, 3512 KB/s, 3 seconds passed
+... 2%, 13984 KB, 3515 KB/s, 3 seconds passed
 
 .. parsed-literal::
 
-    ... 9%, 64032 KB, 3382 KB/s, 18 seconds passed
-... 9%, 64064 KB, 3383 KB/s, 18 seconds passed
-... 9%, 64096 KB, 3382 KB/s, 18 seconds passed
-... 9%, 64128 KB, 3382 KB/s, 18 seconds passed
-... 9%, 64160 KB, 3383 KB/s, 18 seconds passed
-... 9%, 64192 KB, 3383 KB/s, 18 seconds passed
+    ... 2%, 14016 KB, 3513 KB/s, 3 seconds passed
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+... 2%, 14112 KB, 3517 KB/s, 4 seconds passed
+... 2%, 14144 KB, 3515 KB/s, 4 seconds passed
+... 2%, 14176 KB, 3513 KB/s, 4 seconds passed
 
 .. parsed-literal::
 
-    ... 9%, 64224 KB, 3382 KB/s, 18 seconds passed
-... 9%, 64256 KB, 3382 KB/s, 18 seconds passed
-... 9%, 64288 KB, 3383 KB/s, 18 seconds passed
-... 9%, 64320 KB, 3384 KB/s, 19 seconds passed
-... 9%, 64352 KB, 3383 KB/s, 19 seconds passed
-... 9%, 64384 KB, 3383 KB/s, 19 seconds passed
+    ... 2%, 14208 KB, 3516 KB/s, 4 seconds passed
+... 2%, 14240 KB, 3518 KB/s, 4 seconds passed
+... 2%, 14272 KB, 3516 KB/s, 4 seconds passed
+... 2%, 14304 KB, 3514 KB/s, 4 seconds passed
+... 2%, 14336 KB, 3517 KB/s, 4 seconds passed
+... 2%, 14368 KB, 3520 KB/s, 4 seconds passed
 
 .. parsed-literal::
 
-    ... 9%, 64416 KB, 3384 KB/s, 19 seconds passed
-... 9%, 64448 KB, 3385 KB/s, 19 seconds passed
-... 9%, 64480 KB, 3383 KB/s, 19 seconds passed
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-... 9%, 64576 KB, 3385 KB/s, 19 seconds passed
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+... 2%, 14496 KB, 3522 KB/s, 4 seconds passed
+... 2%, 14528 KB, 3520 KB/s, 4 seconds passed
 
 .. parsed-literal::
 
-    ... 9%, 64608 KB, 3384 KB/s, 19 seconds passed
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+... 2%, 14752 KB, 3525 KB/s, 4 seconds passed
 
 .. parsed-literal::
 
-    ... 9%, 64800 KB, 3385 KB/s, 19 seconds passed
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+... 2%, 14912 KB, 3525 KB/s, 4 seconds passed
 
 .. parsed-literal::
 
-    ... 9%, 64992 KB, 3386 KB/s, 19 seconds passed
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+... 2%, 15136 KB, 3530 KB/s, 4 seconds passed
 
 .. parsed-literal::
 
-    ... 9%, 65184 KB, 3387 KB/s, 19 seconds passed
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 .. parsed-literal::
 
-    ... 9%, 65376 KB, 3387 KB/s, 19 seconds passed
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 .. parsed-literal::
 
-    ... 9%, 65536 KB, 3388 KB/s, 19 seconds passed
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 .. parsed-literal::
 
-    ... 9%, 65760 KB, 3389 KB/s, 19 seconds passed
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 .. parsed-literal::
 
-    ... 9%, 65920 KB, 3390 KB/s, 19 seconds passed
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 .. parsed-literal::
 
-    ... 9%, 66112 KB, 3390 KB/s, 19 seconds passed
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 .. parsed-literal::
 
-    ... 9%, 66304 KB, 3391 KB/s, 19 seconds passed
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 .. parsed-literal::
 
-    ... 9%, 66496 KB, 3392 KB/s, 19 seconds passed
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 .. parsed-literal::
 
-    ... 9%, 66688 KB, 3393 KB/s, 19 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 9%, 67648 KB, 3396 KB/s, 19 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 9%, 68576 KB, 3400 KB/s, 20 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 9%, 69312 KB, 3402 KB/s, 20 seconds passed
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 .. parsed-literal::
 
-    ... 9%, 69536 KB, 3404 KB/s, 20 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 10%, 69920 KB, 3405 KB/s, 20 seconds passed
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 .. parsed-literal::
 
-    ... 10%, 70080 KB, 3405 KB/s, 20 seconds passed
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+... 2%, 20224 KB, 3569 KB/s, 5 seconds passed
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 .. parsed-literal::
 
-    ... 10%, 70272 KB, 3407 KB/s, 20 seconds passed
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 .. parsed-literal::
 
-    ... 10%, 70432 KB, 3406 KB/s, 20 seconds passed
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+... 2%, 20576 KB, 3569 KB/s, 5 seconds passed
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 .. parsed-literal::
 
-    ... 10%, 70656 KB, 3408 KB/s, 20 seconds passed
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-... 10%, 70784 KB, 3409 KB/s, 20 seconds passed
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+... 2%, 20800 KB, 3568 KB/s, 5 seconds passed
 
 .. parsed-literal::
 
-    ... 10%, 70816 KB, 3408 KB/s, 20 seconds passed
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-... 10%, 70880 KB, 3409 KB/s, 20 seconds passed
-... 10%, 70912 KB, 3409 KB/s, 20 seconds passed
-... 10%, 70944 KB, 3408 KB/s, 20 seconds passed
-... 10%, 70976 KB, 3409 KB/s, 20 seconds passed
-... 10%, 71008 KB, 3409 KB/s, 20 seconds passed
+    ... 2%, 20832 KB, 3571 KB/s, 5 seconds passed
+... 2%, 20864 KB, 3572 KB/s, 5 seconds passed
+... 3%, 20896 KB, 3571 KB/s, 5 seconds passed
+... 3%, 20928 KB, 3570 KB/s, 5 seconds passed
+... 3%, 20960 KB, 3570 KB/s, 5 seconds passed
+... 3%, 20992 KB, 3572 KB/s, 5 seconds passed
 
 .. parsed-literal::
 
-    ... 10%, 71040 KB, 3410 KB/s, 20 seconds passed
-... 10%, 71072 KB, 3409 KB/s, 20 seconds passed
-... 10%, 71104 KB, 3409 KB/s, 20 seconds passed
-... 10%, 71136 KB, 3410 KB/s, 20 seconds passed
-... 10%, 71168 KB, 3410 KB/s, 20 seconds passed
+    ... 3%, 21024 KB, 3572 KB/s, 5 seconds passed
+... 3%, 21056 KB, 3571 KB/s, 5 seconds passed
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+... 3%, 21120 KB, 3573 KB/s, 5 seconds passed
+... 3%, 21152 KB, 3573 KB/s, 5 seconds passed
+... 3%, 21184 KB, 3572 KB/s, 5 seconds passed
 
 .. parsed-literal::
 
-    ... 10%, 71200 KB, 3409 KB/s, 20 seconds passed
-... 10%, 71232 KB, 3410 KB/s, 20 seconds passed
-... 10%, 71264 KB, 3410 KB/s, 20 seconds passed
-... 10%, 71296 KB, 3411 KB/s, 20 seconds passed
-... 10%, 71328 KB, 3410 KB/s, 20 seconds passed
-... 10%, 71360 KB, 3410 KB/s, 20 seconds passed
-... 10%, 71392 KB, 3411 KB/s, 20 seconds passed
+    ... 3%, 21216 KB, 3572 KB/s, 5 seconds passed
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+... 3%, 21280 KB, 3574 KB/s, 5 seconds passed
+... 3%, 21312 KB, 3572 KB/s, 5 seconds passed
+... 3%, 21344 KB, 3572 KB/s, 5 seconds passed
+... 3%, 21376 KB, 3574 KB/s, 5 seconds passed
 
 .. parsed-literal::
 
-    ... 10%, 71424 KB, 3411 KB/s, 20 seconds passed
-... 10%, 71456 KB, 3410 KB/s, 20 seconds passed
-... 10%, 71488 KB, 3411 KB/s, 20 seconds passed
-... 10%, 71520 KB, 3411 KB/s, 20 seconds passed
-... 10%, 71552 KB, 3412 KB/s, 20 seconds passed
+    ... 3%, 21408 KB, 3574 KB/s, 5 seconds passed
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+... 3%, 21472 KB, 3573 KB/s, 6 seconds passed
+... 3%, 21504 KB, 3575 KB/s, 6 seconds passed
+... 3%, 21536 KB, 3573 KB/s, 6 seconds passed
 
 .. parsed-literal::
 
-    ... 10%, 71584 KB, 3411 KB/s, 20 seconds passed
-... 10%, 71616 KB, 3411 KB/s, 20 seconds passed
-... 10%, 71648 KB, 3412 KB/s, 20 seconds passed
-... 10%, 71680 KB, 3412 KB/s, 21 seconds passed
-... 10%, 71712 KB, 3411 KB/s, 21 seconds passed
-... 10%, 71744 KB, 3412 KB/s, 21 seconds passed
-... 10%, 71776 KB, 3412 KB/s, 21 seconds passed
+    ... 3%, 21568 KB, 3573 KB/s, 6 seconds passed
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+... 3%, 21632 KB, 3576 KB/s, 6 seconds passed
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+... 3%, 21696 KB, 3573 KB/s, 6 seconds passed
+... 3%, 21728 KB, 3574 KB/s, 6 seconds passed
+... 3%, 21760 KB, 3577 KB/s, 6 seconds passed
 
 .. parsed-literal::
 
-    ... 10%, 71808 KB, 3413 KB/s, 21 seconds passed
-... 10%, 71840 KB, 3412 KB/s, 21 seconds passed
-... 10%, 71872 KB, 3412 KB/s, 21 seconds passed
-... 10%, 71904 KB, 3413 KB/s, 21 seconds passed
-... 10%, 71936 KB, 3413 KB/s, 21 seconds passed
+    ... 3%, 21792 KB, 3574 KB/s, 6 seconds passed
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+... 3%, 21856 KB, 3576 KB/s, 6 seconds passed
+... 3%, 21888 KB, 3578 KB/s, 6 seconds passed
+... 3%, 21920 KB, 3578 KB/s, 6 seconds passed
+... 3%, 21952 KB, 3576 KB/s, 6 seconds passed
 
 .. parsed-literal::
 
-    ... 10%, 71968 KB, 3412 KB/s, 21 seconds passed
-... 10%, 72000 KB, 3413 KB/s, 21 seconds passed
-... 10%, 72032 KB, 3413 KB/s, 21 seconds passed
-... 10%, 72064 KB, 3414 KB/s, 21 seconds passed
-... 10%, 72096 KB, 3412 KB/s, 21 seconds passed
-... 10%, 72128 KB, 3413 KB/s, 21 seconds passed
+    ... 3%, 21984 KB, 3577 KB/s, 6 seconds passed
+... 3%, 22016 KB, 3578 KB/s, 6 seconds passed
+... 3%, 22048 KB, 3575 KB/s, 6 seconds passed
+... 3%, 22080 KB, 3575 KB/s, 6 seconds passed
+... 3%, 22112 KB, 3576 KB/s, 6 seconds passed
 
 .. parsed-literal::
 
-    ... 10%, 72160 KB, 3413 KB/s, 21 seconds passed
-... 10%, 72192 KB, 3414 KB/s, 21 seconds passed
-... 10%, 72224 KB, 3413 KB/s, 21 seconds passed
-... 10%, 72256 KB, 3413 KB/s, 21 seconds passed
-... 10%, 72288 KB, 3414 KB/s, 21 seconds passed
-... 10%, 72320 KB, 3415 KB/s, 21 seconds passed
+    ... 3%, 22144 KB, 3576 KB/s, 6 seconds passed
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+... 3%, 22208 KB, 3576 KB/s, 6 seconds passed
+... 3%, 22240 KB, 3577 KB/s, 6 seconds passed
+... 3%, 22272 KB, 3577 KB/s, 6 seconds passed
+... 3%, 22304 KB, 3577 KB/s, 6 seconds passed
 
 .. parsed-literal::
 
-    ... 10%, 72352 KB, 3413 KB/s, 21 seconds passed
-... 10%, 72384 KB, 3414 KB/s, 21 seconds passed
-... 10%, 72416 KB, 3414 KB/s, 21 seconds passed
-... 10%, 72448 KB, 3415 KB/s, 21 seconds passed
-... 10%, 72480 KB, 3414 KB/s, 21 seconds passed
-... 10%, 72512 KB, 3414 KB/s, 21 seconds passed
+    ... 3%, 22336 KB, 3577 KB/s, 6 seconds passed
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+... 3%, 22432 KB, 3578 KB/s, 6 seconds passed
+... 3%, 22464 KB, 3578 KB/s, 6 seconds passed
+... 3%, 22496 KB, 3578 KB/s, 6 seconds passed
 
 .. parsed-literal::
 
-    ... 10%, 72544 KB, 3415 KB/s, 21 seconds passed
-... 10%, 72576 KB, 3416 KB/s, 21 seconds passed
-... 10%, 72608 KB, 3414 KB/s, 21 seconds passed
-... 10%, 72640 KB, 3415 KB/s, 21 seconds passed
-... 10%, 72672 KB, 3415 KB/s, 21 seconds passed
-... 10%, 72704 KB, 3416 KB/s, 21 seconds passed
+    ... 3%, 22528 KB, 3578 KB/s, 6 seconds passed
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+... 3%, 22624 KB, 3579 KB/s, 6 seconds passed
+... 3%, 22656 KB, 3579 KB/s, 6 seconds passed
+... 3%, 22688 KB, 3579 KB/s, 6 seconds passed
 
 .. parsed-literal::
 
-    ... 10%, 72736 KB, 3415 KB/s, 21 seconds passed
-... 10%, 72768 KB, 3415 KB/s, 21 seconds passed
-... 10%, 72800 KB, 3416 KB/s, 21 seconds passed
-... 10%, 72832 KB, 3417 KB/s, 21 seconds passed
-... 10%, 72864 KB, 3415 KB/s, 21 seconds passed
-... 10%, 72896 KB, 3416 KB/s, 21 seconds passed
+    ... 3%, 22720 KB, 3579 KB/s, 6 seconds passed
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+... 3%, 22816 KB, 3580 KB/s, 6 seconds passed
+... 3%, 22848 KB, 3580 KB/s, 6 seconds passed
+... 3%, 22880 KB, 3580 KB/s, 6 seconds passed
 
 .. parsed-literal::
 
-    ... 10%, 72928 KB, 3416 KB/s, 21 seconds passed
-... 10%, 72960 KB, 3417 KB/s, 21 seconds passed
-... 10%, 72992 KB, 3416 KB/s, 21 seconds passed
-... 10%, 73024 KB, 3416 KB/s, 21 seconds passed
-... 10%, 73056 KB, 3417 KB/s, 21 seconds passed
-... 10%, 73088 KB, 3417 KB/s, 21 seconds passed
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+... 3%, 23008 KB, 3581 KB/s, 6 seconds passed
+... 3%, 23040 KB, 3581 KB/s, 6 seconds passed
+... 3%, 23072 KB, 3581 KB/s, 6 seconds passed
 
 .. parsed-literal::
 
-    ... 10%, 73120 KB, 3416 KB/s, 21 seconds passed
-... 10%, 73152 KB, 3417 KB/s, 21 seconds passed
-... 10%, 73184 KB, 3417 KB/s, 21 seconds passed
-... 10%, 73216 KB, 3417 KB/s, 21 seconds passed
-... 10%, 73248 KB, 3417 KB/s, 21 seconds passed
-... 10%, 73280 KB, 3417 KB/s, 21 seconds passed
+    ... 3%, 23104 KB, 3581 KB/s, 6 seconds passed
+... 3%, 23136 KB, 3582 KB/s, 6 seconds passed
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+... 3%, 23200 KB, 3582 KB/s, 6 seconds passed
+... 3%, 23232 KB, 3582 KB/s, 6 seconds passed
+... 3%, 23264 KB, 3582 KB/s, 6 seconds passed
 
 .. parsed-literal::
 
-    ... 10%, 73312 KB, 3418 KB/s, 21 seconds passed
-... 10%, 73344 KB, 3417 KB/s, 21 seconds passed
-... 10%, 73376 KB, 3417 KB/s, 21 seconds passed
-... 10%, 73408 KB, 3418 KB/s, 21 seconds passed
-... 10%, 73440 KB, 3418 KB/s, 21 seconds passed
-... 10%, 73472 KB, 3418 KB/s, 21 seconds passed
+    ... 3%, 23296 KB, 3582 KB/s, 6 seconds passed
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+... 3%, 23392 KB, 3583 KB/s, 6 seconds passed
+... 3%, 23424 KB, 3582 KB/s, 6 seconds passed
+... 3%, 23456 KB, 3583 KB/s, 6 seconds passed
 
 .. parsed-literal::
 
-    ... 10%, 73504 KB, 3418 KB/s, 21 seconds passed
-... 10%, 73536 KB, 3418 KB/s, 21 seconds passed
-... 10%, 73568 KB, 3418 KB/s, 21 seconds passed
-... 10%, 73600 KB, 3418 KB/s, 21 seconds passed
-... 10%, 73632 KB, 3418 KB/s, 21 seconds passed
-... 10%, 73664 KB, 3419 KB/s, 21 seconds passed
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+... 3%, 23616 KB, 3583 KB/s, 6 seconds passed
+... 3%, 23648 KB, 3584 KB/s, 6 seconds passed
 
 .. parsed-literal::
 
-    ... 10%, 73696 KB, 3419 KB/s, 21 seconds passed
-... 10%, 73728 KB, 3419 KB/s, 21 seconds passed
-... 10%, 73760 KB, 3419 KB/s, 21 seconds passed
-... 10%, 73792 KB, 3419 KB/s, 21 seconds passed
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-... 10%, 73856 KB, 3419 KB/s, 21 seconds passed
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+... 3%, 23776 KB, 3584 KB/s, 6 seconds passed
+... 3%, 23808 KB, 3585 KB/s, 6 seconds passed
+... 3%, 23840 KB, 3585 KB/s, 6 seconds passed
 
 .. parsed-literal::
 
-    ... 10%, 73888 KB, 3419 KB/s, 21 seconds passed
-... 10%, 73920 KB, 3420 KB/s, 21 seconds passed
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-... 10%, 74048 KB, 3420 KB/s, 21 seconds passed
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+... 3%, 24000 KB, 3585 KB/s, 6 seconds passed
+... 3%, 24032 KB, 3585 KB/s, 6 seconds passed
 
 .. parsed-literal::
 
-    ... 10%, 74080 KB, 3420 KB/s, 21 seconds passed
-... 10%, 74112 KB, 3420 KB/s, 21 seconds passed
-... 10%, 74144 KB, 3420 KB/s, 21 seconds passed
-... 10%, 74176 KB, 3420 KB/s, 21 seconds passed
-... 10%, 74208 KB, 3421 KB/s, 21 seconds passed
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+... 3%, 24192 KB, 3587 KB/s, 6 seconds passed
+... 3%, 24224 KB, 3587 KB/s, 6 seconds passed
 
 .. parsed-literal::
 
-    ... 10%, 74240 KB, 3421 KB/s, 21 seconds passed
-... 10%, 74272 KB, 3420 KB/s, 21 seconds passed
-... 10%, 74304 KB, 3421 KB/s, 21 seconds passed
-... 10%, 74336 KB, 3421 KB/s, 21 seconds passed
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-... 10%, 74400 KB, 3421 KB/s, 21 seconds passed
-... 10%, 74432 KB, 3421 KB/s, 21 seconds passed
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+... 3%, 24384 KB, 3587 KB/s, 6 seconds passed
+... 3%, 24416 KB, 3588 KB/s, 6 seconds passed
 
 .. parsed-literal::
 
-    ... 10%, 74464 KB, 3421 KB/s, 21 seconds passed
-... 10%, 74496 KB, 3421 KB/s, 21 seconds passed
-... 10%, 74528 KB, 3421 KB/s, 21 seconds passed
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-... 10%, 74592 KB, 3422 KB/s, 21 seconds passed
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 .. parsed-literal::
 
-    ... 10%, 74624 KB, 3422 KB/s, 21 seconds passed
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-... 10%, 74720 KB, 3422 KB/s, 21 seconds passed
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 .. parsed-literal::
 
-    ... 10%, 74816 KB, 3423 KB/s, 21 seconds passed
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+... 3%, 24960 KB, 3590 KB/s, 6 seconds passed
 
 .. parsed-literal::
 
-    ... 10%, 75008 KB, 3423 KB/s, 21 seconds passed
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-... 10%, 75072 KB, 3423 KB/s, 21 seconds passed
-... 10%, 75104 KB, 3424 KB/s, 21 seconds passed
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-... 10%, 75168 KB, 3423 KB/s, 21 seconds passed
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+... 3%, 25120 KB, 3591 KB/s, 6 seconds passed
+... 3%, 25152 KB, 3590 KB/s, 7 seconds passed
 
 .. parsed-literal::
 
-    ... 10%, 75200 KB, 3424 KB/s, 21 seconds passed
-... 10%, 75232 KB, 3424 KB/s, 21 seconds passed
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-... 10%, 75296 KB, 3424 KB/s, 21 seconds passed
-... 10%, 75328 KB, 3424 KB/s, 21 seconds passed
-... 10%, 75360 KB, 3424 KB/s, 22 seconds passed
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+... 3%, 25312 KB, 3591 KB/s, 7 seconds passed
+... 3%, 25344 KB, 3592 KB/s, 7 seconds passed
 
 .. parsed-literal::
 
-    ... 10%, 75392 KB, 3425 KB/s, 22 seconds passed
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-... 10%, 75456 KB, 3425 KB/s, 22 seconds passed
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-... 10%, 75520 KB, 3425 KB/s, 22 seconds passed
-... 10%, 75552 KB, 3425 KB/s, 22 seconds passed
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+... 3%, 25536 KB, 3592 KB/s, 7 seconds passed
 
 .. parsed-literal::
 
-    ... 10%, 75584 KB, 3425 KB/s, 22 seconds passed
-... 10%, 75616 KB, 3425 KB/s, 22 seconds passed
-... 10%, 75648 KB, 3425 KB/s, 22 seconds passed
-... 10%, 75680 KB, 3425 KB/s, 22 seconds passed
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+... 3%, 25696 KB, 3593 KB/s, 7 seconds passed
+... 3%, 25728 KB, 3594 KB/s, 7 seconds passed
 
 .. parsed-literal::
 
-    ... 10%, 75776 KB, 3426 KB/s, 22 seconds passed
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-... 10%, 75936 KB, 3426 KB/s, 22 seconds passed
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+... 3%, 25888 KB, 3594 KB/s, 7 seconds passed
+... 3%, 25920 KB, 3594 KB/s, 7 seconds passed
 
 .. parsed-literal::
 
-    ... 10%, 75968 KB, 3426 KB/s, 22 seconds passed
-... 10%, 76000 KB, 3427 KB/s, 22 seconds passed
-... 10%, 76032 KB, 3427 KB/s, 22 seconds passed
-... 10%, 76064 KB, 3427 KB/s, 22 seconds passed
-... 10%, 76096 KB, 3427 KB/s, 22 seconds passed
-... 10%, 76128 KB, 3427 KB/s, 22 seconds passed
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+... 3%, 26080 KB, 3596 KB/s, 7 seconds passed
+... 3%, 26112 KB, 3595 KB/s, 7 seconds passed
 
 .. parsed-literal::
 
-    ... 10%, 76160 KB, 3427 KB/s, 22 seconds passed
-... 10%, 76192 KB, 3427 KB/s, 22 seconds passed
-... 10%, 76224 KB, 3427 KB/s, 22 seconds passed
-... 10%, 76256 KB, 3427 KB/s, 22 seconds passed
-... 10%, 76288 KB, 3427 KB/s, 22 seconds passed
-... 10%, 76320 KB, 3427 KB/s, 22 seconds passed
+    ... 3%, 26144 KB, 3595 KB/s, 7 seconds passed
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+... 3%, 26240 KB, 3596 KB/s, 7 seconds passed
+... 3%, 26272 KB, 3596 KB/s, 7 seconds passed
+... 3%, 26304 KB, 3595 KB/s, 7 seconds passed
 
 .. parsed-literal::
 
-    ... 10%, 76352 KB, 3428 KB/s, 22 seconds passed
-... 10%, 76384 KB, 3428 KB/s, 22 seconds passed
-... 10%, 76416 KB, 3427 KB/s, 22 seconds passed
-... 10%, 76448 KB, 3428 KB/s, 22 seconds passed
-... 10%, 76480 KB, 3428 KB/s, 22 seconds passed
-... 11%, 76512 KB, 3428 KB/s, 22 seconds passed
+    ... 3%, 26336 KB, 3596 KB/s, 7 seconds passed
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+... 3%, 26464 KB, 3597 KB/s, 7 seconds passed
+... 3%, 26496 KB, 3597 KB/s, 7 seconds passed
 
 .. parsed-literal::
 
-    ... 11%, 76544 KB, 3428 KB/s, 22 seconds passed
-... 11%, 76576 KB, 3428 KB/s, 22 seconds passed
-... 11%, 76608 KB, 3429 KB/s, 22 seconds passed
-... 11%, 76640 KB, 3429 KB/s, 22 seconds passed
-... 11%, 76672 KB, 3428 KB/s, 22 seconds passed
+    ... 3%, 26528 KB, 3596 KB/s, 7 seconds passed
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+... 3%, 26592 KB, 3597 KB/s, 7 seconds passed
+... 3%, 26624 KB, 3598 KB/s, 7 seconds passed
+... 3%, 26656 KB, 3596 KB/s, 7 seconds passed
 
 .. parsed-literal::
 
-    ... 11%, 76704 KB, 3429 KB/s, 22 seconds passed
-... 11%, 76736 KB, 3429 KB/s, 22 seconds passed
-... 11%, 76768 KB, 3429 KB/s, 22 seconds passed
-... 11%, 76800 KB, 3429 KB/s, 22 seconds passed
-... 11%, 76832 KB, 3429 KB/s, 22 seconds passed
-... 11%, 76864 KB, 3429 KB/s, 22 seconds passed
-... 11%, 76896 KB, 3430 KB/s, 22 seconds passed
+    ... 3%, 26688 KB, 3596 KB/s, 7 seconds passed
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+... 3%, 26816 KB, 3597 KB/s, 7 seconds passed
+... 3%, 26848 KB, 3598 KB/s, 7 seconds passed
+... 3%, 26880 KB, 3599 KB/s, 7 seconds passed
 
 .. parsed-literal::
 
-    ... 11%, 76928 KB, 3429 KB/s, 22 seconds passed
-... 11%, 76960 KB, 3430 KB/s, 22 seconds passed
-... 11%, 76992 KB, 3430 KB/s, 22 seconds passed
-... 11%, 77024 KB, 3430 KB/s, 22 seconds passed
-... 11%, 77056 KB, 3430 KB/s, 22 seconds passed
+    ... 3%, 26912 KB, 3597 KB/s, 7 seconds passed
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+... 3%, 26976 KB, 3599 KB/s, 7 seconds passed
+... 3%, 27008 KB, 3599 KB/s, 7 seconds passed
+... 3%, 27040 KB, 3597 KB/s, 7 seconds passed
 
 .. parsed-literal::
 
-    ... 11%, 77088 KB, 3430 KB/s, 22 seconds passed
-... 11%, 77120 KB, 3430 KB/s, 22 seconds passed
-... 11%, 77152 KB, 3430 KB/s, 22 seconds passed
-... 11%, 77184 KB, 3430 KB/s, 22 seconds passed
-... 11%, 77216 KB, 3430 KB/s, 22 seconds passed
-... 11%, 77248 KB, 3431 KB/s, 22 seconds passed
+    ... 3%, 27072 KB, 3598 KB/s, 7 seconds passed
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+... 3%, 27136 KB, 3600 KB/s, 7 seconds passed
+... 3%, 27168 KB, 3598 KB/s, 7 seconds passed
+... 3%, 27200 KB, 3598 KB/s, 7 seconds passed
+... 3%, 27232 KB, 3599 KB/s, 7 seconds passed
+... 3%, 27264 KB, 3600 KB/s, 7 seconds passed
 
 .. parsed-literal::
 
-    ... 11%, 77280 KB, 3431 KB/s, 22 seconds passed
-... 11%, 77312 KB, 3430 KB/s, 22 seconds passed
-... 11%, 77344 KB, 3431 KB/s, 22 seconds passed
-... 11%, 77376 KB, 3431 KB/s, 22 seconds passed
-... 11%, 77408 KB, 3431 KB/s, 22 seconds passed
-... 11%, 77440 KB, 3431 KB/s, 22 seconds passed
+    ... 3%, 27296 KB, 3598 KB/s, 7 seconds passed
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+... 3%, 27360 KB, 3599 KB/s, 7 seconds passed
+... 3%, 27392 KB, 3598 KB/s, 7 seconds passed
+... 3%, 27424 KB, 3599 KB/s, 7 seconds passed
 
 .. parsed-literal::
 
-    ... 11%, 77472 KB, 3431 KB/s, 22 seconds passed
-... 11%, 77504 KB, 3431 KB/s, 22 seconds passed
-... 11%, 77536 KB, 3432 KB/s, 22 seconds passed
-... 11%, 77568 KB, 3431 KB/s, 22 seconds passed
-... 11%, 77600 KB, 3432 KB/s, 22 seconds passed
-... 11%, 77632 KB, 3432 KB/s, 22 seconds passed
+    ... 3%, 27456 KB, 3599 KB/s, 7 seconds passed
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+... 3%, 27552 KB, 3599 KB/s, 7 seconds passed
+... 3%, 27584 KB, 3599 KB/s, 7 seconds passed
+... 3%, 27616 KB, 3600 KB/s, 7 seconds passed
 
 .. parsed-literal::
 
-    ... 11%, 77664 KB, 3432 KB/s, 22 seconds passed
-... 11%, 77696 KB, 3431 KB/s, 22 seconds passed
-... 11%, 77728 KB, 3432 KB/s, 22 seconds passed
-... 11%, 77760 KB, 3432 KB/s, 22 seconds passed
-... 11%, 77792 KB, 3432 KB/s, 22 seconds passed
-... 11%, 77824 KB, 3432 KB/s, 22 seconds passed
+    ... 3%, 27648 KB, 3599 KB/s, 7 seconds passed
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+... 3%, 27744 KB, 3601 KB/s, 7 seconds passed
+... 3%, 27776 KB, 3600 KB/s, 7 seconds passed
+... 3%, 27808 KB, 3600 KB/s, 7 seconds passed
 
 .. parsed-literal::
 
-    ... 11%, 77856 KB, 3432 KB/s, 22 seconds passed
-... 11%, 77888 KB, 3433 KB/s, 22 seconds passed
-... 11%, 77920 KB, 3433 KB/s, 22 seconds passed
-... 11%, 77952 KB, 3432 KB/s, 22 seconds passed
-... 11%, 77984 KB, 3433 KB/s, 22 seconds passed
-... 11%, 78016 KB, 3433 KB/s, 22 seconds passed
+    ... 4%, 27840 KB, 3601 KB/s, 7 seconds passed
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+... 4%, 27936 KB, 3600 KB/s, 7 seconds passed
+... 4%, 27968 KB, 3600 KB/s, 7 seconds passed
+... 4%, 28000 KB, 3602 KB/s, 7 seconds passed
 
 .. parsed-literal::
 
-    ... 11%, 78048 KB, 3433 KB/s, 22 seconds passed
-... 11%, 78080 KB, 3433 KB/s, 22 seconds passed
-... 11%, 78112 KB, 3433 KB/s, 22 seconds passed
-... 11%, 78144 KB, 3433 KB/s, 22 seconds passed
-... 11%, 78176 KB, 3433 KB/s, 22 seconds passed
-... 11%, 78208 KB, 3433 KB/s, 22 seconds passed
+    ... 4%, 28032 KB, 3601 KB/s, 7 seconds passed
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+... 4%, 28128 KB, 3602 KB/s, 7 seconds passed
+... 4%, 28160 KB, 3601 KB/s, 7 seconds passed
+... 4%, 28192 KB, 3601 KB/s, 7 seconds passed
 
 .. parsed-literal::
 
-    ... 11%, 78240 KB, 3434 KB/s, 22 seconds passed
-... 11%, 78272 KB, 3434 KB/s, 22 seconds passed
-... 11%, 78304 KB, 3434 KB/s, 22 seconds passed
-... 11%, 78336 KB, 3434 KB/s, 22 seconds passed
-... 11%, 78368 KB, 3434 KB/s, 22 seconds passed
-... 11%, 78400 KB, 3434 KB/s, 22 seconds passed
+    ... 4%, 28224 KB, 3601 KB/s, 7 seconds passed
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+... 4%, 28320 KB, 3602 KB/s, 7 seconds passed
+... 4%, 28352 KB, 3601 KB/s, 7 seconds passed
+... 4%, 28384 KB, 3603 KB/s, 7 seconds passed
 
 .. parsed-literal::
 
-    ... 11%, 78432 KB, 3434 KB/s, 22 seconds passed
-... 11%, 78464 KB, 3434 KB/s, 22 seconds passed
-... 11%, 78496 KB, 3434 KB/s, 22 seconds passed
-... 11%, 78528 KB, 3435 KB/s, 22 seconds passed
-... 11%, 78560 KB, 3434 KB/s, 22 seconds passed
+    ... 4%, 28416 KB, 3602 KB/s, 7 seconds passed
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+... 4%, 28512 KB, 3603 KB/s, 7 seconds passed
+... 4%, 28544 KB, 3602 KB/s, 7 seconds passed
+... 4%, 28576 KB, 3602 KB/s, 7 seconds passed
 
 .. parsed-literal::
 
-    ... 11%, 78592 KB, 3434 KB/s, 22 seconds passed
-... 11%, 78624 KB, 3435 KB/s, 22 seconds passed
-... 11%, 78656 KB, 3435 KB/s, 22 seconds passed
-... 11%, 78688 KB, 3435 KB/s, 22 seconds passed
-... 11%, 78720 KB, 3435 KB/s, 22 seconds passed
-... 11%, 78752 KB, 3435 KB/s, 22 seconds passed
-... 11%, 78784 KB, 3436 KB/s, 22 seconds passed
+    ... 4%, 28608 KB, 3602 KB/s, 7 seconds passed
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+... 4%, 28704 KB, 3603 KB/s, 7 seconds passed
+... 4%, 28736 KB, 3602 KB/s, 7 seconds passed
+... 4%, 28768 KB, 3603 KB/s, 7 seconds passed
 
 .. parsed-literal::
 
-    ... 11%, 78816 KB, 3435 KB/s, 22 seconds passed
-... 11%, 78848 KB, 3435 KB/s, 22 seconds passed
-... 11%, 78880 KB, 3436 KB/s, 22 seconds passed
-... 11%, 78912 KB, 3436 KB/s, 22 seconds passed
-... 11%, 78944 KB, 3435 KB/s, 22 seconds passed
+    ... 4%, 28800 KB, 3603 KB/s, 7 seconds passed
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+... 4%, 28896 KB, 3604 KB/s, 8 seconds passed
+... 4%, 28928 KB, 3603 KB/s, 8 seconds passed
+... 4%, 28960 KB, 3603 KB/s, 8 seconds passed
 
 .. parsed-literal::
 
-    ... 11%, 78976 KB, 3435 KB/s, 22 seconds passed
-... 11%, 79008 KB, 3436 KB/s, 22 seconds passed
-... 11%, 79040 KB, 3436 KB/s, 22 seconds passed
-... 11%, 79072 KB, 3436 KB/s, 23 seconds passed
-... 11%, 79104 KB, 3436 KB/s, 23 seconds passed
-... 11%, 79136 KB, 3436 KB/s, 23 seconds passed
-... 11%, 79168 KB, 3437 KB/s, 23 seconds passed
+    ... 4%, 28992 KB, 3603 KB/s, 8 seconds passed
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+... 4%, 29088 KB, 3604 KB/s, 8 seconds passed
+... 4%, 29120 KB, 3604 KB/s, 8 seconds passed
+... 4%, 29152 KB, 3605 KB/s, 8 seconds passed
 
 .. parsed-literal::
 
-    ... 11%, 79200 KB, 3436 KB/s, 23 seconds passed
-... 11%, 79232 KB, 3436 KB/s, 23 seconds passed
-... 11%, 79264 KB, 3437 KB/s, 23 seconds passed
-... 11%, 79296 KB, 3437 KB/s, 23 seconds passed
-... 11%, 79328 KB, 3437 KB/s, 23 seconds passed
+    ... 4%, 29184 KB, 3605 KB/s, 8 seconds passed
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+... 4%, 29248 KB, 3604 KB/s, 8 seconds passed
+... 4%, 29280 KB, 3605 KB/s, 8 seconds passed
+... 4%, 29312 KB, 3604 KB/s, 8 seconds passed
 
 .. parsed-literal::
 
-    ... 11%, 79360 KB, 3437 KB/s, 23 seconds passed
-... 11%, 79392 KB, 3437 KB/s, 23 seconds passed
-... 11%, 79424 KB, 3437 KB/s, 23 seconds passed
-... 11%, 79456 KB, 3437 KB/s, 23 seconds passed
-... 11%, 79488 KB, 3437 KB/s, 23 seconds passed
-... 11%, 79520 KB, 3438 KB/s, 23 seconds passed
+    ... 4%, 29344 KB, 3603 KB/s, 8 seconds passed
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+... 4%, 29440 KB, 3604 KB/s, 8 seconds passed
+... 4%, 29472 KB, 3603 KB/s, 8 seconds passed
+... 4%, 29504 KB, 3605 KB/s, 8 seconds passed
 
 .. parsed-literal::
 
-    ... 11%, 79552 KB, 3438 KB/s, 23 seconds passed
-... 11%, 79584 KB, 3438 KB/s, 23 seconds passed
-... 11%, 79616 KB, 3437 KB/s, 23 seconds passed
-... 11%, 79648 KB, 3438 KB/s, 23 seconds passed
-... 11%, 79680 KB, 3438 KB/s, 23 seconds passed
-... 11%, 79712 KB, 3438 KB/s, 23 seconds passed
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+... 4%, 29632 KB, 3605 KB/s, 8 seconds passed
+... 4%, 29664 KB, 3606 KB/s, 8 seconds passed
+... 4%, 29696 KB, 3606 KB/s, 8 seconds passed
 
 .. parsed-literal::
 
-    ... 11%, 79744 KB, 3438 KB/s, 23 seconds passed
-... 11%, 79776 KB, 3438 KB/s, 23 seconds passed
-... 11%, 79808 KB, 3439 KB/s, 23 seconds passed
-... 11%, 79840 KB, 3438 KB/s, 23 seconds passed
-... 11%, 79872 KB, 3438 KB/s, 23 seconds passed
-... 11%, 79904 KB, 3439 KB/s, 23 seconds passed
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+... 4%, 29824 KB, 3606 KB/s, 8 seconds passed
+... 4%, 29856 KB, 3605 KB/s, 8 seconds passed
+... 4%, 29888 KB, 3606 KB/s, 8 seconds passed
 
 .. parsed-literal::
 
-    ... 11%, 79936 KB, 3439 KB/s, 23 seconds passed
-... 11%, 79968 KB, 3439 KB/s, 23 seconds passed
-... 11%, 80000 KB, 3439 KB/s, 23 seconds passed
-... 11%, 80032 KB, 3439 KB/s, 23 seconds passed
-... 11%, 80064 KB, 3439 KB/s, 23 seconds passed
-... 11%, 80096 KB, 3439 KB/s, 23 seconds passed
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+... 4%, 30016 KB, 3606 KB/s, 8 seconds passed
+... 4%, 30048 KB, 3607 KB/s, 8 seconds passed
+... 4%, 30080 KB, 3607 KB/s, 8 seconds passed
 
 .. parsed-literal::
 
-    ... 11%, 80128 KB, 3439 KB/s, 23 seconds passed
-... 11%, 80160 KB, 3439 KB/s, 23 seconds passed
-... 11%, 80192 KB, 3440 KB/s, 23 seconds passed
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-... 11%, 80288 KB, 3440 KB/s, 23 seconds passed
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+... 4%, 30240 KB, 3606 KB/s, 8 seconds passed
+... 4%, 30272 KB, 3607 KB/s, 8 seconds passed
 
 .. parsed-literal::
 
-    ... 11%, 80320 KB, 3440 KB/s, 23 seconds passed
-... 11%, 80352 KB, 3440 KB/s, 23 seconds passed
-... 11%, 80384 KB, 3440 KB/s, 23 seconds passed
-... 11%, 80416 KB, 3440 KB/s, 23 seconds passed
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-... 11%, 80480 KB, 3440 KB/s, 23 seconds passed
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+... 4%, 30400 KB, 3607 KB/s, 8 seconds passed
+... 4%, 30432 KB, 3606 KB/s, 8 seconds passed
 
 .. parsed-literal::
 
-    ... 11%, 80512 KB, 3440 KB/s, 23 seconds passed
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-... 11%, 80576 KB, 3441 KB/s, 23 seconds passed
-... 11%, 80608 KB, 3441 KB/s, 23 seconds passed
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-... 11%, 80672 KB, 3441 KB/s, 23 seconds passed
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+... 4%, 30624 KB, 3607 KB/s, 8 seconds passed
+... 4%, 30656 KB, 3609 KB/s, 8 seconds passed
 
 .. parsed-literal::
 
-    ... 11%, 80704 KB, 3441 KB/s, 23 seconds passed
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-... 11%, 80768 KB, 3441 KB/s, 23 seconds passed
-... 11%, 80800 KB, 3441 KB/s, 23 seconds passed
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-... 11%, 80864 KB, 3441 KB/s, 23 seconds passed
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+... 4%, 30816 KB, 3610 KB/s, 8 seconds passed
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 .. parsed-literal::
 
-    ... 11%, 80896 KB, 3441 KB/s, 23 seconds passed
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-... 11%, 80960 KB, 3442 KB/s, 23 seconds passed
-... 11%, 80992 KB, 3442 KB/s, 23 seconds passed
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-... 11%, 81056 KB, 3442 KB/s, 23 seconds passed
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+... 4%, 30976 KB, 3609 KB/s, 8 seconds passed
+... 4%, 31008 KB, 3608 KB/s, 8 seconds passed
+... 4%, 31040 KB, 3609 KB/s, 8 seconds passed
 
 .. parsed-literal::
 
-    ... 11%, 81088 KB, 3442 KB/s, 23 seconds passed
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-... 11%, 81248 KB, 3443 KB/s, 23 seconds passed
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+... 4%, 31200 KB, 3609 KB/s, 8 seconds passed
+... 4%, 31232 KB, 3610 KB/s, 8 seconds passed
 
 .. parsed-literal::
 
-    ... 11%, 81280 KB, 3442 KB/s, 23 seconds passed
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-... 11%, 81344 KB, 3443 KB/s, 23 seconds passed
-... 11%, 81376 KB, 3443 KB/s, 23 seconds passed
-... 11%, 81408 KB, 3443 KB/s, 23 seconds passed
-... 11%, 81440 KB, 3443 KB/s, 23 seconds passed
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+... 4%, 31392 KB, 3609 KB/s, 8 seconds passed
+... 4%, 31424 KB, 3611 KB/s, 8 seconds passed
 
 .. parsed-literal::
 
-    ... 11%, 81472 KB, 3443 KB/s, 23 seconds passed
-... 11%, 81504 KB, 3443 KB/s, 23 seconds passed
-... 11%, 81536 KB, 3443 KB/s, 23 seconds passed
-... 11%, 81568 KB, 3443 KB/s, 23 seconds passed
-... 11%, 81600 KB, 3444 KB/s, 23 seconds passed
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 .. parsed-literal::
 
-    ... 11%, 81632 KB, 3444 KB/s, 23 seconds passed
-... 11%, 81664 KB, 3443 KB/s, 23 seconds passed
-... 11%, 81696 KB, 3444 KB/s, 23 seconds passed
-... 11%, 81728 KB, 3444 KB/s, 23 seconds passed
-... 11%, 81760 KB, 3444 KB/s, 23 seconds passed
-... 11%, 81792 KB, 3443 KB/s, 23 seconds passed
+    ... 4%, 31648 KB, 3610 KB/s, 8 seconds passed
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 .. parsed-literal::
 
-    ... 11%, 81824 KB, 3444 KB/s, 23 seconds passed
-... 11%, 81856 KB, 3445 KB/s, 23 seconds passed
-... 11%, 81888 KB, 3444 KB/s, 23 seconds passed
-... 11%, 81920 KB, 3444 KB/s, 23 seconds passed
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-... 11%, 81984 KB, 3445 KB/s, 23 seconds passed
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+... 4%, 31904 KB, 3611 KB/s, 8 seconds passed
+... 4%, 31936 KB, 3612 KB/s, 8 seconds passed
+... 4%, 31968 KB, 3611 KB/s, 8 seconds passed
 
 .. parsed-literal::
 
-    ... 11%, 82016 KB, 3445 KB/s, 23 seconds passed
-... 11%, 82048 KB, 3444 KB/s, 23 seconds passed
-... 11%, 82080 KB, 3445 KB/s, 23 seconds passed
-... 11%, 82112 KB, 3445 KB/s, 23 seconds passed
-... 11%, 82144 KB, 3445 KB/s, 23 seconds passed
-... 11%, 82176 KB, 3445 KB/s, 23 seconds passed
+    ... 4%, 32000 KB, 3611 KB/s, 8 seconds passed
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+... 4%, 32096 KB, 3612 KB/s, 8 seconds passed
+... 4%, 32128 KB, 3612 KB/s, 8 seconds passed
+... 4%, 32160 KB, 3612 KB/s, 8 seconds passed
 
 .. parsed-literal::
 
-    ... 11%, 82208 KB, 3445 KB/s, 23 seconds passed
-... 11%, 82240 KB, 3446 KB/s, 23 seconds passed
-... 11%, 82272 KB, 3445 KB/s, 23 seconds passed
-... 11%, 82304 KB, 3445 KB/s, 23 seconds passed
-... 11%, 82336 KB, 3446 KB/s, 23 seconds passed
-... 11%, 82368 KB, 3446 KB/s, 23 seconds passed
+    ... 4%, 32192 KB, 3612 KB/s, 8 seconds passed
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+... 4%, 32288 KB, 3611 KB/s, 8 seconds passed
+... 4%, 32320 KB, 3612 KB/s, 8 seconds passed
+... 4%, 32352 KB, 3612 KB/s, 8 seconds passed
 
 .. parsed-literal::
 
-    ... 11%, 82400 KB, 3446 KB/s, 23 seconds passed
-... 11%, 82432 KB, 3445 KB/s, 23 seconds passed
-... 11%, 82464 KB, 3446 KB/s, 23 seconds passed
-... 11%, 82496 KB, 3446 KB/s, 23 seconds passed
-... 11%, 82528 KB, 3446 KB/s, 23 seconds passed
-... 11%, 82560 KB, 3446 KB/s, 23 seconds passed
+    ... 4%, 32384 KB, 3612 KB/s, 8 seconds passed
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+... 4%, 32480 KB, 3612 KB/s, 8 seconds passed
+... 4%, 32512 KB, 3612 KB/s, 8 seconds passed
+... 4%, 32544 KB, 3612 KB/s, 9 seconds passed
 
 .. parsed-literal::
 
-    ... 11%, 82592 KB, 3446 KB/s, 23 seconds passed
-... 11%, 82624 KB, 3447 KB/s, 23 seconds passed
-... 11%, 82656 KB, 3447 KB/s, 23 seconds passed
-... 11%, 82688 KB, 3446 KB/s, 23 seconds passed
-... 11%, 82720 KB, 3447 KB/s, 23 seconds passed
-... 11%, 82752 KB, 3447 KB/s, 24 seconds passed
+    ... 4%, 32576 KB, 3613 KB/s, 9 seconds passed
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+... 4%, 32672 KB, 3612 KB/s, 9 seconds passed
+... 4%, 32704 KB, 3613 KB/s, 9 seconds passed
+... 4%, 32736 KB, 3613 KB/s, 9 seconds passed
 
 .. parsed-literal::
 
-    ... 11%, 82784 KB, 3447 KB/s, 24 seconds passed
-... 11%, 82816 KB, 3446 KB/s, 24 seconds passed
-... 11%, 82848 KB, 3447 KB/s, 24 seconds passed
-... 11%, 82880 KB, 3447 KB/s, 24 seconds passed
-... 11%, 82912 KB, 3447 KB/s, 24 seconds passed
+    ... 4%, 32768 KB, 3613 KB/s, 9 seconds passed
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+... 4%, 32864 KB, 3613 KB/s, 9 seconds passed
+... 4%, 32896 KB, 3614 KB/s, 9 seconds passed
+... 4%, 32928 KB, 3613 KB/s, 9 seconds passed
 
 .. parsed-literal::
 
-    ... 11%, 82944 KB, 3447 KB/s, 24 seconds passed
-... 11%, 82976 KB, 3447 KB/s, 24 seconds passed
-... 11%, 83008 KB, 3448 KB/s, 24 seconds passed
-... 11%, 83040 KB, 3448 KB/s, 24 seconds passed
-... 11%, 83072 KB, 3447 KB/s, 24 seconds passed
-... 11%, 83104 KB, 3448 KB/s, 24 seconds passed
-... 11%, 83136 KB, 3448 KB/s, 24 seconds passed
+    ... 4%, 32960 KB, 3614 KB/s, 9 seconds passed
+... 4%, 32992 KB, 3614 KB/s, 9 seconds passed
+... 4%, 33024 KB, 3614 KB/s, 9 seconds passed
+... 4%, 33056 KB, 3613 KB/s, 9 seconds passed
+... 4%, 33088 KB, 3615 KB/s, 9 seconds passed
+... 4%, 33120 KB, 3615 KB/s, 9 seconds passed
 
 .. parsed-literal::
 
-    ... 11%, 83168 KB, 3448 KB/s, 24 seconds passed
-... 11%, 83200 KB, 3447 KB/s, 24 seconds passed
-... 11%, 83232 KB, 3448 KB/s, 24 seconds passed
-... 11%, 83264 KB, 3448 KB/s, 24 seconds passed
-... 11%, 83296 KB, 3447 KB/s, 24 seconds passed
+    ... 4%, 33152 KB, 3615 KB/s, 9 seconds passed
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+... 4%, 33216 KB, 3614 KB/s, 9 seconds passed
+... 4%, 33248 KB, 3614 KB/s, 9 seconds passed
+... 4%, 33280 KB, 3615 KB/s, 9 seconds passed
 
 .. parsed-literal::
 
-    ... 11%, 83328 KB, 3448 KB/s, 24 seconds passed
-... 11%, 83360 KB, 3449 KB/s, 24 seconds passed
-... 11%, 83392 KB, 3449 KB/s, 24 seconds passed
-... 11%, 83424 KB, 3447 KB/s, 24 seconds passed
-... 11%, 83456 KB, 3448 KB/s, 24 seconds passed
-... 12%, 83488 KB, 3449 KB/s, 24 seconds passed
-... 12%, 83520 KB, 3449 KB/s, 24 seconds passed
+    ... 4%, 33312 KB, 3614 KB/s, 9 seconds passed
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+... 4%, 33376 KB, 3614 KB/s, 9 seconds passed
+... 4%, 33408 KB, 3615 KB/s, 9 seconds passed
+... 4%, 33440 KB, 3614 KB/s, 9 seconds passed
+... 4%, 33472 KB, 3614 KB/s, 9 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 83552 KB, 3448 KB/s, 24 seconds passed
-... 12%, 83584 KB, 3448 KB/s, 24 seconds passed
-... 12%, 83616 KB, 3449 KB/s, 24 seconds passed
-... 12%, 83648 KB, 3449 KB/s, 24 seconds passed
-... 12%, 83680 KB, 3448 KB/s, 24 seconds passed
+    ... 4%, 33504 KB, 3615 KB/s, 9 seconds passed
+... 4%, 33536 KB, 3615 KB/s, 9 seconds passed
+... 4%, 33568 KB, 3614 KB/s, 9 seconds passed
+... 4%, 33600 KB, 3615 KB/s, 9 seconds passed
+... 4%, 33632 KB, 3615 KB/s, 9 seconds passed
+... 4%, 33664 KB, 3615 KB/s, 9 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 83712 KB, 3449 KB/s, 24 seconds passed
-... 12%, 83744 KB, 3450 KB/s, 24 seconds passed
-... 12%, 83776 KB, 3450 KB/s, 24 seconds passed
-... 12%, 83808 KB, 3448 KB/s, 24 seconds passed
-... 12%, 83840 KB, 3449 KB/s, 24 seconds passed
-... 12%, 83872 KB, 3450 KB/s, 24 seconds passed
-... 12%, 83904 KB, 3450 KB/s, 24 seconds passed
+    ... 4%, 33696 KB, 3615 KB/s, 9 seconds passed
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+... 4%, 33760 KB, 3615 KB/s, 9 seconds passed
+... 4%, 33792 KB, 3616 KB/s, 9 seconds passed
+... 4%, 33824 KB, 3615 KB/s, 9 seconds passed
+... 4%, 33856 KB, 3615 KB/s, 9 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 83936 KB, 3449 KB/s, 24 seconds passed
-... 12%, 83968 KB, 3449 KB/s, 24 seconds passed
-... 12%, 84000 KB, 3450 KB/s, 24 seconds passed
-... 12%, 84032 KB, 3450 KB/s, 24 seconds passed
+    ... 4%, 33888 KB, 3616 KB/s, 9 seconds passed
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+... 4%, 33984 KB, 3616 KB/s, 9 seconds passed
+... 4%, 34016 KB, 3616 KB/s, 9 seconds passed
+... 4%, 34048 KB, 3617 KB/s, 9 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 84064 KB, 3449 KB/s, 24 seconds passed
-... 12%, 84096 KB, 3450 KB/s, 24 seconds passed
-... 12%, 84128 KB, 3451 KB/s, 24 seconds passed
-... 12%, 84160 KB, 3451 KB/s, 24 seconds passed
-... 12%, 84192 KB, 3450 KB/s, 24 seconds passed
-... 12%, 84224 KB, 3450 KB/s, 24 seconds passed
-... 12%, 84256 KB, 3451 KB/s, 24 seconds passed
+    ... 4%, 34080 KB, 3615 KB/s, 9 seconds passed
+... 4%, 34112 KB, 3616 KB/s, 9 seconds passed
+... 4%, 34144 KB, 3616 KB/s, 9 seconds passed
+... 4%, 34176 KB, 3617 KB/s, 9 seconds passed
+... 4%, 34208 KB, 3615 KB/s, 9 seconds passed
+... 4%, 34240 KB, 3616 KB/s, 9 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 84288 KB, 3451 KB/s, 24 seconds passed
-... 12%, 84320 KB, 3450 KB/s, 24 seconds passed
-... 12%, 84352 KB, 3451 KB/s, 24 seconds passed
-... 12%, 84384 KB, 3451 KB/s, 24 seconds passed
-... 12%, 84416 KB, 3452 KB/s, 24 seconds passed
+    ... 4%, 34272 KB, 3616 KB/s, 9 seconds passed
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+... 4%, 34368 KB, 3617 KB/s, 9 seconds passed
+... 4%, 34400 KB, 3617 KB/s, 9 seconds passed
+... 4%, 34432 KB, 3617 KB/s, 9 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 84448 KB, 3450 KB/s, 24 seconds passed
-... 12%, 84480 KB, 3451 KB/s, 24 seconds passed
-... 12%, 84512 KB, 3452 KB/s, 24 seconds passed
-... 12%, 84544 KB, 3452 KB/s, 24 seconds passed
-... 12%, 84576 KB, 3451 KB/s, 24 seconds passed
-... 12%, 84608 KB, 3451 KB/s, 24 seconds passed
+    ... 4%, 34464 KB, 3616 KB/s, 9 seconds passed
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+... 4%, 34560 KB, 3618 KB/s, 9 seconds passed
+... 4%, 34592 KB, 3616 KB/s, 9 seconds passed
+... 4%, 34624 KB, 3617 KB/s, 9 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 84640 KB, 3447 KB/s, 24 seconds passed
-... 12%, 84672 KB, 3448 KB/s, 24 seconds passed
-... 12%, 84704 KB, 3450 KB/s, 24 seconds passed
-... 12%, 84736 KB, 3451 KB/s, 24 seconds passed
+    ... 4%, 34656 KB, 3617 KB/s, 9 seconds passed
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+... 4%, 34752 KB, 3618 KB/s, 9 seconds passed
+... 5%, 34784 KB, 3618 KB/s, 9 seconds passed
+... 5%, 34816 KB, 3619 KB/s, 9 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 84768 KB, 3448 KB/s, 24 seconds passed
-... 12%, 84800 KB, 3444 KB/s, 24 seconds passed
-... 12%, 84832 KB, 3445 KB/s, 24 seconds passed
+    ... 5%, 34848 KB, 3617 KB/s, 9 seconds passed
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+... 5%, 34944 KB, 3619 KB/s, 9 seconds passed
+... 5%, 34976 KB, 3617 KB/s, 9 seconds passed
+... 5%, 35008 KB, 3618 KB/s, 9 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 84864 KB, 3442 KB/s, 24 seconds passed
+    ... 5%, 35040 KB, 3618 KB/s, 9 seconds passed
+... 5%, 35072 KB, 3618 KB/s, 9 seconds passed
+... 5%, 35104 KB, 3618 KB/s, 9 seconds passed
+... 5%, 35136 KB, 3619 KB/s, 9 seconds passed
+... 5%, 35168 KB, 3618 KB/s, 9 seconds passed
+... 5%, 35200 KB, 3618 KB/s, 9 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 84896 KB, 3438 KB/s, 24 seconds passed
-... 12%, 84928 KB, 3439 KB/s, 24 seconds passed
-... 12%, 84960 KB, 3436 KB/s, 24 seconds passed
-... 12%, 84992 KB, 3437 KB/s, 24 seconds passed
+    ... 5%, 35232 KB, 3618 KB/s, 9 seconds passed
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+... 5%, 35296 KB, 3619 KB/s, 9 seconds passed
+... 5%, 35328 KB, 3618 KB/s, 9 seconds passed
+... 5%, 35360 KB, 3618 KB/s, 9 seconds passed
+... 5%, 35392 KB, 3620 KB/s, 9 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 85024 KB, 3434 KB/s, 24 seconds passed
-... 12%, 85056 KB, 3435 KB/s, 24 seconds passed
+    ... 5%, 35424 KB, 3619 KB/s, 9 seconds passed
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+... 5%, 35520 KB, 3620 KB/s, 9 seconds passed
+... 5%, 35552 KB, 3620 KB/s, 9 seconds passed
+... 5%, 35584 KB, 3620 KB/s, 9 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 85088 KB, 3432 KB/s, 24 seconds passed
-... 12%, 85120 KB, 3433 KB/s, 24 seconds passed
-... 12%, 85152 KB, 3434 KB/s, 24 seconds passed
-... 12%, 85184 KB, 3431 KB/s, 24 seconds passed
-... 12%, 85216 KB, 3432 KB/s, 24 seconds passed
+    ... 5%, 35616 KB, 3619 KB/s, 9 seconds passed
+... 5%, 35648 KB, 3620 KB/s, 9 seconds passed
+... 5%, 35680 KB, 3620 KB/s, 9 seconds passed
+... 5%, 35712 KB, 3621 KB/s, 9 seconds passed
+... 5%, 35744 KB, 3619 KB/s, 9 seconds passed
+... 5%, 35776 KB, 3620 KB/s, 9 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 85248 KB, 3433 KB/s, 24 seconds passed
-... 12%, 85280 KB, 3430 KB/s, 24 seconds passed
-... 12%, 85312 KB, 3431 KB/s, 24 seconds passed
-... 12%, 85344 KB, 3432 KB/s, 24 seconds passed
+    ... 5%, 35808 KB, 3620 KB/s, 9 seconds passed
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+... 5%, 35872 KB, 3620 KB/s, 9 seconds passed
+... 5%, 35904 KB, 3621 KB/s, 9 seconds passed
+... 5%, 35936 KB, 3621 KB/s, 9 seconds passed
+... 5%, 35968 KB, 3622 KB/s, 9 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 85376 KB, 3429 KB/s, 24 seconds passed
-... 12%, 85408 KB, 3430 KB/s, 24 seconds passed
-... 12%, 85440 KB, 3431 KB/s, 24 seconds passed
-... 12%, 85472 KB, 3428 KB/s, 24 seconds passed
-... 12%, 85504 KB, 3429 KB/s, 24 seconds passed
+    ... 5%, 36000 KB, 3620 KB/s, 9 seconds passed
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+... 5%, 36064 KB, 3621 KB/s, 9 seconds passed
+... 5%, 36096 KB, 3622 KB/s, 9 seconds passed
+... 5%, 36128 KB, 3620 KB/s, 9 seconds passed
+... 5%, 36160 KB, 3621 KB/s, 9 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 85536 KB, 3430 KB/s, 24 seconds passed
-... 12%, 85568 KB, 3431 KB/s, 24 seconds passed
-... 12%, 85600 KB, 3428 KB/s, 24 seconds passed
-... 12%, 85632 KB, 3429 KB/s, 24 seconds passed
-... 12%, 85664 KB, 3430 KB/s, 24 seconds passed
-... 12%, 85696 KB, 3431 KB/s, 24 seconds passed
+    ... 5%, 36192 KB, 3621 KB/s, 9 seconds passed
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+... 5%, 36288 KB, 3621 KB/s, 10 seconds passed
+... 5%, 36320 KB, 3621 KB/s, 10 seconds passed
+... 5%, 36352 KB, 3622 KB/s, 10 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 85728 KB, 3429 KB/s, 24 seconds passed
-... 12%, 85760 KB, 3430 KB/s, 25 seconds passed
-... 12%, 85792 KB, 3431 KB/s, 25 seconds passed
-... 12%, 85824 KB, 3432 KB/s, 25 seconds passed
-... 12%, 85856 KB, 3429 KB/s, 25 seconds passed
+    ... 5%, 36384 KB, 3619 KB/s, 10 seconds passed
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+... 5%, 36448 KB, 3621 KB/s, 10 seconds passed
+... 5%, 36480 KB, 3620 KB/s, 10 seconds passed
+... 5%, 36512 KB, 3620 KB/s, 10 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 85888 KB, 3425 KB/s, 25 seconds passed
-... 12%, 85920 KB, 3427 KB/s, 25 seconds passed
-... 12%, 85952 KB, 3428 KB/s, 25 seconds passed
-... 12%, 85984 KB, 3429 KB/s, 25 seconds passed
+    ... 5%, 36544 KB, 3620 KB/s, 10 seconds passed
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+... 5%, 36608 KB, 3620 KB/s, 10 seconds passed
+... 5%, 36640 KB, 3620 KB/s, 10 seconds passed
+... 5%, 36672 KB, 3620 KB/s, 10 seconds passed
+... 5%, 36704 KB, 3621 KB/s, 10 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 86016 KB, 3421 KB/s, 25 seconds passed
+    ... 5%, 36736 KB, 3620 KB/s, 10 seconds passed
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+... 5%, 36832 KB, 3622 KB/s, 10 seconds passed
+... 5%, 36864 KB, 3620 KB/s, 10 seconds passed
+... 5%, 36896 KB, 3620 KB/s, 10 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 86048 KB, 3418 KB/s, 25 seconds passed
+    ... 5%, 36928 KB, 3621 KB/s, 10 seconds passed
+... 5%, 36960 KB, 3622 KB/s, 10 seconds passed
+... 5%, 36992 KB, 3621 KB/s, 10 seconds passed
+... 5%, 37024 KB, 3621 KB/s, 10 seconds passed
+... 5%, 37056 KB, 3621 KB/s, 10 seconds passed
+... 5%, 37088 KB, 3622 KB/s, 10 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 86080 KB, 3414 KB/s, 25 seconds passed
-... 12%, 86112 KB, 3415 KB/s, 25 seconds passed
+    ... 5%, 37120 KB, 3621 KB/s, 10 seconds passed
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+... 5%, 37184 KB, 3621 KB/s, 10 seconds passed
+... 5%, 37216 KB, 3622 KB/s, 10 seconds passed
+... 5%, 37248 KB, 3621 KB/s, 10 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 86144 KB, 3412 KB/s, 25 seconds passed
-... 12%, 86176 KB, 3409 KB/s, 25 seconds passed
+    ... 5%, 37280 KB, 3621 KB/s, 10 seconds passed
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+... 5%, 37376 KB, 3622 KB/s, 10 seconds passed
+... 5%, 37408 KB, 3622 KB/s, 10 seconds passed
+... 5%, 37440 KB, 3622 KB/s, 10 seconds passed
+... 5%, 37472 KB, 3623 KB/s, 10 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 86208 KB, 3405 KB/s, 25 seconds passed
-... 12%, 86240 KB, 3406 KB/s, 25 seconds passed
+    ... 5%, 37504 KB, 3622 KB/s, 10 seconds passed
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+... 5%, 37568 KB, 3622 KB/s, 10 seconds passed
+... 5%, 37600 KB, 3624 KB/s, 10 seconds passed
+... 5%, 37632 KB, 3623 KB/s, 10 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 86272 KB, 3403 KB/s, 25 seconds passed
-... 12%, 86304 KB, 3400 KB/s, 25 seconds passed
+    ... 5%, 37664 KB, 3622 KB/s, 10 seconds passed
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+... 5%, 37792 KB, 3623 KB/s, 10 seconds passed
+... 5%, 37824 KB, 3623 KB/s, 10 seconds passed
+... 5%, 37856 KB, 3624 KB/s, 10 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 86336 KB, 3396 KB/s, 25 seconds passed
+    ... 5%, 37888 KB, 3625 KB/s, 10 seconds passed
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+... 5%, 37952 KB, 3623 KB/s, 10 seconds passed
+... 5%, 37984 KB, 3625 KB/s, 10 seconds passed
+... 5%, 38016 KB, 3625 KB/s, 10 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 86368 KB, 3393 KB/s, 25 seconds passed
-... 12%, 86400 KB, 3390 KB/s, 25 seconds passed
+    ... 5%, 38048 KB, 3624 KB/s, 10 seconds passed
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+... 5%, 38176 KB, 3624 KB/s, 10 seconds passed
+... 5%, 38208 KB, 3624 KB/s, 10 seconds passed
+... 5%, 38240 KB, 3625 KB/s, 10 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 86432 KB, 3386 KB/s, 25 seconds passed
+    ... 5%, 38272 KB, 3623 KB/s, 10 seconds passed
+... 5%, 38304 KB, 3624 KB/s, 10 seconds passed
+... 5%, 38336 KB, 3624 KB/s, 10 seconds passed
+... 5%, 38368 KB, 3625 KB/s, 10 seconds passed
+... 5%, 38400 KB, 3624 KB/s, 10 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 86464 KB, 3383 KB/s, 25 seconds passed
-... 12%, 86496 KB, 3384 KB/s, 25 seconds passed
-... 12%, 86528 KB, 3381 KB/s, 25 seconds passed
+    ... 5%, 38432 KB, 3624 KB/s, 10 seconds passed
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+... 5%, 38528 KB, 3624 KB/s, 10 seconds passed
+... 5%, 38560 KB, 3624 KB/s, 10 seconds passed
+... 5%, 38592 KB, 3624 KB/s, 10 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 86560 KB, 3378 KB/s, 25 seconds passed
-... 12%, 86592 KB, 3378 KB/s, 25 seconds passed
+    ... 5%, 38624 KB, 3625 KB/s, 10 seconds passed
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+... 5%, 38720 KB, 3624 KB/s, 10 seconds passed
+... 5%, 38752 KB, 3625 KB/s, 10 seconds passed
+... 5%, 38784 KB, 3624 KB/s, 10 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 86624 KB, 3376 KB/s, 25 seconds passed
-... 12%, 86656 KB, 3376 KB/s, 25 seconds passed
-... 12%, 86688 KB, 3373 KB/s, 25 seconds passed
+    ... 5%, 38816 KB, 3625 KB/s, 10 seconds passed
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+... 5%, 38912 KB, 3624 KB/s, 10 seconds passed
+... 5%, 38944 KB, 3625 KB/s, 10 seconds passed
+... 5%, 38976 KB, 3625 KB/s, 10 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 86720 KB, 3371 KB/s, 25 seconds passed
-... 12%, 86752 KB, 3371 KB/s, 25 seconds passed
+    ... 5%, 39008 KB, 3626 KB/s, 10 seconds passed
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+... 5%, 39104 KB, 3625 KB/s, 10 seconds passed
+... 5%, 39136 KB, 3626 KB/s, 10 seconds passed
+... 5%, 39168 KB, 3625 KB/s, 10 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 86784 KB, 3368 KB/s, 25 seconds passed
-... 12%, 86816 KB, 3369 KB/s, 25 seconds passed
-... 12%, 86848 KB, 3366 KB/s, 25 seconds passed
-... 12%, 86880 KB, 3367 KB/s, 25 seconds passed
+    ... 5%, 39200 KB, 3625 KB/s, 10 seconds passed
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+... 5%, 39296 KB, 3625 KB/s, 10 seconds passed
+... 5%, 39328 KB, 3626 KB/s, 10 seconds passed
+... 5%, 39360 KB, 3625 KB/s, 10 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 86912 KB, 3364 KB/s, 25 seconds passed
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-... 12%, 86976 KB, 3366 KB/s, 25 seconds passed
+    ... 5%, 39392 KB, 3627 KB/s, 10 seconds passed
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+... 5%, 39488 KB, 3626 KB/s, 10 seconds passed
+... 5%, 39520 KB, 3628 KB/s, 10 seconds passed
+... 5%, 39552 KB, 3626 KB/s, 10 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 87008 KB, 3363 KB/s, 25 seconds passed
-... 12%, 87040 KB, 3363 KB/s, 25 seconds passed
-... 12%, 87072 KB, 3361 KB/s, 25 seconds passed
-... 12%, 87104 KB, 3362 KB/s, 25 seconds passed
+    ... 5%, 39584 KB, 3627 KB/s, 10 seconds passed
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+... 5%, 39680 KB, 3627 KB/s, 10 seconds passed
+... 5%, 39712 KB, 3627 KB/s, 10 seconds passed
+... 5%, 39744 KB, 3627 KB/s, 10 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 87136 KB, 3360 KB/s, 25 seconds passed
-... 12%, 87168 KB, 3360 KB/s, 25 seconds passed
-... 12%, 87200 KB, 3360 KB/s, 25 seconds passed
+    ... 5%, 39776 KB, 3628 KB/s, 10 seconds passed
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+... 5%, 39872 KB, 3627 KB/s, 10 seconds passed
+... 5%, 39904 KB, 3628 KB/s, 10 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 87232 KB, 3358 KB/s, 25 seconds passed
-... 12%, 87264 KB, 3355 KB/s, 26 seconds passed
+    ... 5%, 39936 KB, 3626 KB/s, 11 seconds passed
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+... 5%, 40032 KB, 3628 KB/s, 11 seconds passed
+... 5%, 40064 KB, 3626 KB/s, 11 seconds passed
+... 5%, 40096 KB, 3627 KB/s, 11 seconds passed
+... 5%, 40128 KB, 3627 KB/s, 11 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 87296 KB, 3355 KB/s, 26 seconds passed
-... 12%, 87328 KB, 3356 KB/s, 26 seconds passed
-... 12%, 87360 KB, 3355 KB/s, 26 seconds passed
-... 12%, 87392 KB, 3354 KB/s, 26 seconds passed
+    ... 5%, 40160 KB, 3628 KB/s, 11 seconds passed
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+... 5%, 40224 KB, 3628 KB/s, 11 seconds passed
+... 5%, 40256 KB, 3627 KB/s, 11 seconds passed
+... 5%, 40288 KB, 3629 KB/s, 11 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 87424 KB, 3352 KB/s, 26 seconds passed
-... 12%, 87456 KB, 3350 KB/s, 26 seconds passed
-... 12%, 87488 KB, 3350 KB/s, 26 seconds passed
+    ... 5%, 40320 KB, 3627 KB/s, 11 seconds passed
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+... 5%, 40384 KB, 3628 KB/s, 11 seconds passed
+... 5%, 40416 KB, 3628 KB/s, 11 seconds passed
+... 5%, 40448 KB, 3627 KB/s, 11 seconds passed
+... 5%, 40480 KB, 3628 KB/s, 11 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 87520 KB, 3348 KB/s, 26 seconds passed
-... 12%, 87552 KB, 3348 KB/s, 26 seconds passed
-... 12%, 87584 KB, 3348 KB/s, 26 seconds passed
+    ... 5%, 40512 KB, 3628 KB/s, 11 seconds passed
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+... 5%, 40576 KB, 3628 KB/s, 11 seconds passed
+... 5%, 40608 KB, 3628 KB/s, 11 seconds passed
+... 5%, 40640 KB, 3628 KB/s, 11 seconds passed
+... 5%, 40672 KB, 3629 KB/s, 11 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 87616 KB, 3346 KB/s, 26 seconds passed
-... 12%, 87648 KB, 3346 KB/s, 26 seconds passed
-... 12%, 87680 KB, 3344 KB/s, 26 seconds passed
+    ... 5%, 40704 KB, 3628 KB/s, 11 seconds passed
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+... 5%, 40768 KB, 3628 KB/s, 11 seconds passed
+... 5%, 40800 KB, 3628 KB/s, 11 seconds passed
+... 5%, 40832 KB, 3628 KB/s, 11 seconds passed
+... 5%, 40864 KB, 3628 KB/s, 11 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 87712 KB, 3344 KB/s, 26 seconds passed
-... 12%, 87744 KB, 3343 KB/s, 26 seconds passed
-... 12%, 87776 KB, 3342 KB/s, 26 seconds passed
+    ... 5%, 40896 KB, 3628 KB/s, 11 seconds passed
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+... 5%, 40960 KB, 3628 KB/s, 11 seconds passed
+... 5%, 40992 KB, 3629 KB/s, 11 seconds passed
+... 5%, 41024 KB, 3629 KB/s, 11 seconds passed
+... 5%, 41056 KB, 3629 KB/s, 11 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 87808 KB, 3341 KB/s, 26 seconds passed
-... 12%, 87840 KB, 3341 KB/s, 26 seconds passed
-... 12%, 87872 KB, 3341 KB/s, 26 seconds passed
-... 12%, 87904 KB, 3340 KB/s, 26 seconds passed
+    ... 5%, 41088 KB, 3628 KB/s, 11 seconds passed
+... 5%, 41120 KB, 3629 KB/s, 11 seconds passed
+... 5%, 41152 KB, 3629 KB/s, 11 seconds passed
+... 5%, 41184 KB, 3629 KB/s, 11 seconds passed
+... 5%, 41216 KB, 3628 KB/s, 11 seconds passed
+... 5%, 41248 KB, 3628 KB/s, 11 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 87936 KB, 3340 KB/s, 26 seconds passed
-... 12%, 87968 KB, 3338 KB/s, 26 seconds passed
-... 12%, 88000 KB, 3338 KB/s, 26 seconds passed
-... 12%, 88032 KB, 3339 KB/s, 26 seconds passed
+    ... 5%, 41280 KB, 3629 KB/s, 11 seconds passed
+... 5%, 41312 KB, 3629 KB/s, 11 seconds passed
+... 5%, 41344 KB, 3628 KB/s, 11 seconds passed
+... 5%, 41376 KB, 3628 KB/s, 11 seconds passed
+... 5%, 41408 KB, 3629 KB/s, 11 seconds passed
+... 5%, 41440 KB, 3629 KB/s, 11 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 88064 KB, 3332 KB/s, 26 seconds passed
-... 12%, 88096 KB, 3333 KB/s, 26 seconds passed
-... 12%, 88128 KB, 3334 KB/s, 26 seconds passed
-... 12%, 88160 KB, 3335 KB/s, 26 seconds passed
-... 12%, 88192 KB, 3332 KB/s, 26 seconds passed
+    ... 5%, 41472 KB, 3628 KB/s, 11 seconds passed
+... 5%, 41504 KB, 3627 KB/s, 11 seconds passed
+... 5%, 41536 KB, 3629 KB/s, 11 seconds passed
+... 5%, 41568 KB, 3627 KB/s, 11 seconds passed
+... 5%, 41600 KB, 3629 KB/s, 11 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 88224 KB, 3330 KB/s, 26 seconds passed
-... 12%, 88256 KB, 3329 KB/s, 26 seconds passed
+    ... 5%, 41632 KB, 3628 KB/s, 11 seconds passed
+... 5%, 41664 KB, 3629 KB/s, 11 seconds passed
+... 5%, 41696 KB, 3628 KB/s, 11 seconds passed
+... 5%, 41728 KB, 3629 KB/s, 11 seconds passed
+... 6%, 41760 KB, 3628 KB/s, 11 seconds passed
+... 6%, 41792 KB, 3629 KB/s, 11 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 88288 KB, 3328 KB/s, 26 seconds passed
-... 12%, 88320 KB, 3326 KB/s, 26 seconds passed
-... 12%, 88352 KB, 3326 KB/s, 26 seconds passed
+    ... 6%, 41824 KB, 3628 KB/s, 11 seconds passed
+... 6%, 41856 KB, 3629 KB/s, 11 seconds passed
+... 6%, 41888 KB, 3628 KB/s, 11 seconds passed
+... 6%, 41920 KB, 3630 KB/s, 11 seconds passed
+... 6%, 41952 KB, 3628 KB/s, 11 seconds passed
+... 6%, 41984 KB, 3630 KB/s, 11 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 88384 KB, 3324 KB/s, 26 seconds passed
-... 12%, 88416 KB, 3324 KB/s, 26 seconds passed
-... 12%, 88448 KB, 3323 KB/s, 26 seconds passed
+    ... 6%, 42016 KB, 3628 KB/s, 11 seconds passed
+... 6%, 42048 KB, 3630 KB/s, 11 seconds passed
+... 6%, 42080 KB, 3628 KB/s, 11 seconds passed
+... 6%, 42112 KB, 3630 KB/s, 11 seconds passed
+... 6%, 42144 KB, 3629 KB/s, 11 seconds passed
+... 6%, 42176 KB, 3630 KB/s, 11 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 88480 KB, 3322 KB/s, 26 seconds passed
-... 12%, 88512 KB, 3322 KB/s, 26 seconds passed
-... 12%, 88544 KB, 3320 KB/s, 26 seconds passed
-... 12%, 88576 KB, 3320 KB/s, 26 seconds passed
+    ... 6%, 42208 KB, 3629 KB/s, 11 seconds passed
+... 6%, 42240 KB, 3630 KB/s, 11 seconds passed
+... 6%, 42272 KB, 3629 KB/s, 11 seconds passed
+... 6%, 42304 KB, 3630 KB/s, 11 seconds passed
+... 6%, 42336 KB, 3629 KB/s, 11 seconds passed
+... 6%, 42368 KB, 3630 KB/s, 11 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 88608 KB, 3319 KB/s, 26 seconds passed
-... 12%, 88640 KB, 3319 KB/s, 26 seconds passed
-... 12%, 88672 KB, 3317 KB/s, 26 seconds passed
+    ... 6%, 42400 KB, 3629 KB/s, 11 seconds passed
+... 6%, 42432 KB, 3630 KB/s, 11 seconds passed
+... 6%, 42464 KB, 3629 KB/s, 11 seconds passed
+... 6%, 42496 KB, 3630 KB/s, 11 seconds passed
+... 6%, 42528 KB, 3629 KB/s, 11 seconds passed
+... 6%, 42560 KB, 3631 KB/s, 11 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 88704 KB, 3317 KB/s, 26 seconds passed
-... 12%, 88736 KB, 3317 KB/s, 26 seconds passed
-... 12%, 88768 KB, 3316 KB/s, 26 seconds passed
-... 12%, 88800 KB, 3316 KB/s, 26 seconds passed
+    ... 6%, 42592 KB, 3630 KB/s, 11 seconds passed
+... 6%, 42624 KB, 3630 KB/s, 11 seconds passed
+... 6%, 42656 KB, 3630 KB/s, 11 seconds passed
+... 6%, 42688 KB, 3631 KB/s, 11 seconds passed
+... 6%, 42720 KB, 3629 KB/s, 11 seconds passed
+... 6%, 42752 KB, 3631 KB/s, 11 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 88832 KB, 3316 KB/s, 26 seconds passed
+    ... 6%, 42784 KB, 3630 KB/s, 11 seconds passed
+... 6%, 42816 KB, 3631 KB/s, 11 seconds passed
+... 6%, 42848 KB, 3629 KB/s, 11 seconds passed
+... 6%, 42880 KB, 3631 KB/s, 11 seconds passed
+... 6%, 42912 KB, 3630 KB/s, 11 seconds passed
+... 6%, 42944 KB, 3631 KB/s, 11 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 88864 KB, 3309 KB/s, 26 seconds passed
-... 12%, 88896 KB, 3311 KB/s, 26 seconds passed
-... 12%, 88928 KB, 3312 KB/s, 26 seconds passed
-... 12%, 88960 KB, 3310 KB/s, 26 seconds passed
+    ... 6%, 42976 KB, 3630 KB/s, 11 seconds passed
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+... 6%, 43040 KB, 3630 KB/s, 11 seconds passed
+... 6%, 43072 KB, 3632 KB/s, 11 seconds passed
+... 6%, 43104 KB, 3630 KB/s, 11 seconds passed
+... 6%, 43136 KB, 3631 KB/s, 11 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 88992 KB, 3308 KB/s, 26 seconds passed
-... 12%, 89024 KB, 3307 KB/s, 26 seconds passed
+    ... 6%, 43168 KB, 3630 KB/s, 11 seconds passed
+... 6%, 43200 KB, 3632 KB/s, 11 seconds passed
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+... 6%, 43264 KB, 3631 KB/s, 11 seconds passed
+... 6%, 43296 KB, 3631 KB/s, 11 seconds passed
+... 6%, 43328 KB, 3632 KB/s, 11 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 89056 KB, 3305 KB/s, 26 seconds passed
-... 12%, 89088 KB, 3303 KB/s, 26 seconds passed
-... 12%, 89120 KB, 3302 KB/s, 26 seconds passed
+    ... 6%, 43360 KB, 3630 KB/s, 11 seconds passed
+... 6%, 43392 KB, 3631 KB/s, 11 seconds passed
+... 6%, 43424 KB, 3631 KB/s, 11 seconds passed
+... 6%, 43456 KB, 3632 KB/s, 11 seconds passed
+... 6%, 43488 KB, 3630 KB/s, 11 seconds passed
+... 6%, 43520 KB, 3632 KB/s, 11 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 89152 KB, 3301 KB/s, 27 seconds passed
+    ... 6%, 43552 KB, 3631 KB/s, 11 seconds passed
+... 6%, 43584 KB, 3632 KB/s, 11 seconds passed
+... 6%, 43616 KB, 3630 KB/s, 12 seconds passed
+... 6%, 43648 KB, 3632 KB/s, 12 seconds passed
+... 6%, 43680 KB, 3631 KB/s, 12 seconds passed
+... 6%, 43712 KB, 3632 KB/s, 12 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 89184 KB, 3295 KB/s, 27 seconds passed
-... 12%, 89216 KB, 3296 KB/s, 27 seconds passed
+    ... 6%, 43744 KB, 3630 KB/s, 12 seconds passed
+... 6%, 43776 KB, 3632 KB/s, 12 seconds passed
+... 6%, 43808 KB, 3631 KB/s, 12 seconds passed
+... 6%, 43840 KB, 3633 KB/s, 12 seconds passed
+... 6%, 43872 KB, 3631 KB/s, 12 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 89248 KB, 3293 KB/s, 27 seconds passed
-... 12%, 89280 KB, 3291 KB/s, 27 seconds passed
+    ... 6%, 43904 KB, 3630 KB/s, 12 seconds passed
+... 6%, 43936 KB, 3631 KB/s, 12 seconds passed
+... 6%, 43968 KB, 3630 KB/s, 12 seconds passed
+... 6%, 44000 KB, 3631 KB/s, 12 seconds passed
+... 6%, 44032 KB, 3630 KB/s, 12 seconds passed
+... 6%, 44064 KB, 3631 KB/s, 12 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 89312 KB, 3288 KB/s, 27 seconds passed
+    ... 6%, 44096 KB, 3630 KB/s, 12 seconds passed
+... 6%, 44128 KB, 3631 KB/s, 12 seconds passed
+... 6%, 44160 KB, 3630 KB/s, 12 seconds passed
+... 6%, 44192 KB, 3632 KB/s, 12 seconds passed
+... 6%, 44224 KB, 3633 KB/s, 12 seconds passed
+... 6%, 44256 KB, 3631 KB/s, 12 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 89344 KB, 3285 KB/s, 27 seconds passed
-... 12%, 89376 KB, 3283 KB/s, 27 seconds passed
+    ... 6%, 44288 KB, 3630 KB/s, 12 seconds passed
+... 6%, 44320 KB, 3632 KB/s, 12 seconds passed
+... 6%, 44352 KB, 3634 KB/s, 12 seconds passed
+... 6%, 44384 KB, 3631 KB/s, 12 seconds passed
+... 6%, 44416 KB, 3633 KB/s, 12 seconds passed
+... 6%, 44448 KB, 3632 KB/s, 12 seconds passed
+... 6%, 44480 KB, 3634 KB/s, 12 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 89408 KB, 3280 KB/s, 27 seconds passed
-... 12%, 89440 KB, 3277 KB/s, 27 seconds passed
+    ... 6%, 44512 KB, 3632 KB/s, 12 seconds passed
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+... 6%, 44576 KB, 3632 KB/s, 12 seconds passed
+... 6%, 44608 KB, 3634 KB/s, 12 seconds passed
+... 6%, 44640 KB, 3632 KB/s, 12 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 89472 KB, 3275 KB/s, 27 seconds passed
-... 12%, 89504 KB, 3273 KB/s, 27 seconds passed
+    ... 6%, 44672 KB, 3631 KB/s, 12 seconds passed
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+... 6%, 44768 KB, 3632 KB/s, 12 seconds passed
+... 6%, 44800 KB, 3631 KB/s, 12 seconds passed
+... 6%, 44832 KB, 3633 KB/s, 12 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 89536 KB, 3271 KB/s, 27 seconds passed
+    ... 6%, 44864 KB, 3631 KB/s, 12 seconds passed
+... 6%, 44896 KB, 3632 KB/s, 12 seconds passed
+... 6%, 44928 KB, 3631 KB/s, 12 seconds passed
+... 6%, 44960 KB, 3633 KB/s, 12 seconds passed
+... 6%, 44992 KB, 3631 KB/s, 12 seconds passed
+... 6%, 45024 KB, 3632 KB/s, 12 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 89568 KB, 3268 KB/s, 27 seconds passed
-... 12%, 89600 KB, 3265 KB/s, 27 seconds passed
+    ... 6%, 45056 KB, 3632 KB/s, 12 seconds passed
+... 6%, 45088 KB, 3633 KB/s, 12 seconds passed
+... 6%, 45120 KB, 3632 KB/s, 12 seconds passed
+... 6%, 45152 KB, 3633 KB/s, 12 seconds passed
+... 6%, 45184 KB, 3632 KB/s, 12 seconds passed
+... 6%, 45216 KB, 3633 KB/s, 12 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 89632 KB, 3264 KB/s, 27 seconds passed
-... 12%, 89664 KB, 3261 KB/s, 27 seconds passed
+    ... 6%, 45248 KB, 3632 KB/s, 12 seconds passed
+... 6%, 45280 KB, 3633 KB/s, 12 seconds passed
+... 6%, 45312 KB, 3632 KB/s, 12 seconds passed
+... 6%, 45344 KB, 3633 KB/s, 12 seconds passed
+... 6%, 45376 KB, 3632 KB/s, 12 seconds passed
+... 6%, 45408 KB, 3633 KB/s, 12 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 89696 KB, 3260 KB/s, 27 seconds passed
-... 12%, 89728 KB, 3258 KB/s, 27 seconds passed
+    ... 6%, 45440 KB, 3632 KB/s, 12 seconds passed
+... 6%, 45472 KB, 3634 KB/s, 12 seconds passed
+... 6%, 45504 KB, 3632 KB/s, 12 seconds passed
+... 6%, 45536 KB, 3633 KB/s, 12 seconds passed
+... 6%, 45568 KB, 3632 KB/s, 12 seconds passed
+... 6%, 45600 KB, 3634 KB/s, 12 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 89760 KB, 3255 KB/s, 27 seconds passed
-... 12%, 89792 KB, 3253 KB/s, 27 seconds passed
+    ... 6%, 45632 KB, 3632 KB/s, 12 seconds passed
+... 6%, 45664 KB, 3633 KB/s, 12 seconds passed
+... 6%, 45696 KB, 3633 KB/s, 12 seconds passed
+... 6%, 45728 KB, 3634 KB/s, 12 seconds passed
+... 6%, 45760 KB, 3633 KB/s, 12 seconds passed
+... 6%, 45792 KB, 3633 KB/s, 12 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 89824 KB, 3252 KB/s, 27 seconds passed
-... 12%, 89856 KB, 3250 KB/s, 27 seconds passed
+    ... 6%, 45824 KB, 3633 KB/s, 12 seconds passed
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+... 6%, 45920 KB, 3634 KB/s, 12 seconds passed
+... 6%, 45952 KB, 3633 KB/s, 12 seconds passed
+... 6%, 45984 KB, 3634 KB/s, 12 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 89888 KB, 3249 KB/s, 27 seconds passed
-... 12%, 89920 KB, 3248 KB/s, 27 seconds passed
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+... 6%, 46080 KB, 3633 KB/s, 12 seconds passed
+... 6%, 46112 KB, 3635 KB/s, 12 seconds passed
+... 6%, 46144 KB, 3633 KB/s, 12 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 89952 KB, 3246 KB/s, 27 seconds passed
-... 12%, 89984 KB, 3244 KB/s, 27 seconds passed
-... 12%, 90016 KB, 3244 KB/s, 27 seconds passed
+    ... 6%, 46176 KB, 3634 KB/s, 12 seconds passed
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+... 6%, 46304 KB, 3634 KB/s, 12 seconds passed
+... 6%, 46336 KB, 3633 KB/s, 12 seconds passed
+... 6%, 46368 KB, 3635 KB/s, 12 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 90048 KB, 3240 KB/s, 27 seconds passed
-... 12%, 90080 KB, 3241 KB/s, 27 seconds passed
+    ... 6%, 46400 KB, 3633 KB/s, 12 seconds passed
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+... 6%, 46464 KB, 3634 KB/s, 12 seconds passed
+... 6%, 46496 KB, 3635 KB/s, 12 seconds passed
+... 6%, 46528 KB, 3633 KB/s, 12 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 90112 KB, 3238 KB/s, 27 seconds passed
-... 12%, 90144 KB, 3235 KB/s, 27 seconds passed
+    ... 6%, 46560 KB, 3634 KB/s, 12 seconds passed
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+... 6%, 46656 KB, 3634 KB/s, 12 seconds passed
+... 6%, 46688 KB, 3635 KB/s, 12 seconds passed
+... 6%, 46720 KB, 3634 KB/s, 12 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 90176 KB, 3228 KB/s, 27 seconds passed
-... 12%, 90208 KB, 3227 KB/s, 27 seconds passed
+    ... 6%, 46752 KB, 3635 KB/s, 12 seconds passed
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+... 6%, 46880 KB, 3636 KB/s, 12 seconds passed
+... 6%, 46912 KB, 3635 KB/s, 12 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 90240 KB, 3223 KB/s, 27 seconds passed
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+... 6%, 47072 KB, 3636 KB/s, 12 seconds passed
+... 6%, 47104 KB, 3635 KB/s, 12 seconds passed
+... 6%, 47136 KB, 3637 KB/s, 12 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 90272 KB, 3218 KB/s, 28 seconds passed
+    ... 6%, 47168 KB, 3635 KB/s, 12 seconds passed
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+... 6%, 47232 KB, 3635 KB/s, 12 seconds passed
+... 6%, 47264 KB, 3637 KB/s, 12 seconds passed
+... 6%, 47296 KB, 3635 KB/s, 13 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 90304 KB, 3215 KB/s, 28 seconds passed
+    ... 6%, 47328 KB, 3636 KB/s, 13 seconds passed
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+... 6%, 47424 KB, 3635 KB/s, 13 seconds passed
+... 6%, 47456 KB, 3636 KB/s, 13 seconds passed
+... 6%, 47488 KB, 3635 KB/s, 13 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 90336 KB, 3210 KB/s, 28 seconds passed
+    ... 6%, 47520 KB, 3637 KB/s, 13 seconds passed
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+... 6%, 47648 KB, 3637 KB/s, 13 seconds passed
+... 6%, 47680 KB, 3636 KB/s, 13 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 90368 KB, 3208 KB/s, 28 seconds passed
-... 12%, 90400 KB, 3205 KB/s, 28 seconds passed
+    ... 6%, 47712 KB, 3636 KB/s, 13 seconds passed
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+... 6%, 47776 KB, 3637 KB/s, 13 seconds passed
+... 6%, 47808 KB, 3636 KB/s, 13 seconds passed
+... 6%, 47840 KB, 3637 KB/s, 13 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 90432 KB, 3202 KB/s, 28 seconds passed
+    ... 6%, 47872 KB, 3636 KB/s, 13 seconds passed
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+... 6%, 47968 KB, 3637 KB/s, 13 seconds passed
+... 6%, 48000 KB, 3636 KB/s, 13 seconds passed
+... 6%, 48032 KB, 3637 KB/s, 13 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 90464 KB, 3199 KB/s, 28 seconds passed
-... 13%, 90496 KB, 3197 KB/s, 28 seconds passed
+    ... 6%, 48064 KB, 3636 KB/s, 13 seconds passed
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+... 6%, 48160 KB, 3637 KB/s, 13 seconds passed
+... 6%, 48192 KB, 3636 KB/s, 13 seconds passed
+... 6%, 48224 KB, 3637 KB/s, 13 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 90528 KB, 3194 KB/s, 28 seconds passed
+    ... 6%, 48256 KB, 3636 KB/s, 13 seconds passed
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+... 6%, 48352 KB, 3637 KB/s, 13 seconds passed
+... 6%, 48384 KB, 3636 KB/s, 13 seconds passed
+... 6%, 48416 KB, 3638 KB/s, 13 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 90560 KB, 3191 KB/s, 28 seconds passed
-... 13%, 90592 KB, 3188 KB/s, 28 seconds passed
+    ... 6%, 48448 KB, 3637 KB/s, 13 seconds passed
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+... 6%, 48576 KB, 3637 KB/s, 13 seconds passed
+... 6%, 48608 KB, 3638 KB/s, 13 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 90624 KB, 3186 KB/s, 28 seconds passed
+    ... 6%, 48640 KB, 3636 KB/s, 13 seconds passed
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+... 7%, 48704 KB, 3637 KB/s, 13 seconds passed
+... 7%, 48736 KB, 3638 KB/s, 13 seconds passed
+... 7%, 48768 KB, 3637 KB/s, 13 seconds passed
+... 7%, 48800 KB, 3638 KB/s, 13 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 90656 KB, 3183 KB/s, 28 seconds passed
-... 13%, 90688 KB, 3182 KB/s, 28 seconds passed
+    ... 7%, 48832 KB, 3637 KB/s, 13 seconds passed
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+... 7%, 48928 KB, 3638 KB/s, 13 seconds passed
+... 7%, 48960 KB, 3638 KB/s, 13 seconds passed
+... 7%, 48992 KB, 3638 KB/s, 13 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 90720 KB, 3179 KB/s, 28 seconds passed
-... 13%, 90752 KB, 3176 KB/s, 28 seconds passed
+    ... 7%, 49024 KB, 3637 KB/s, 13 seconds passed
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+... 7%, 49120 KB, 3639 KB/s, 13 seconds passed
+... 7%, 49152 KB, 3637 KB/s, 13 seconds passed
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 .. parsed-literal::
 
-    ... 13%, 90784 KB, 3175 KB/s, 28 seconds passed
-... 13%, 90816 KB, 3173 KB/s, 28 seconds passed
+    ... 7%, 49216 KB, 3637 KB/s, 13 seconds passed
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+... 7%, 49312 KB, 3639 KB/s, 13 seconds passed
+... 7%, 49344 KB, 3637 KB/s, 13 seconds passed
+... 7%, 49376 KB, 3637 KB/s, 13 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 90848 KB, 3170 KB/s, 28 seconds passed
-... 13%, 90880 KB, 3169 KB/s, 28 seconds passed
+    ... 7%, 49408 KB, 3637 KB/s, 13 seconds passed
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+... 7%, 49504 KB, 3637 KB/s, 13 seconds passed
+... 7%, 49536 KB, 3638 KB/s, 13 seconds passed
+... 7%, 49568 KB, 3639 KB/s, 13 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 90912 KB, 3167 KB/s, 28 seconds passed
-... 13%, 90944 KB, 3166 KB/s, 28 seconds passed
+    ... 7%, 49600 KB, 3638 KB/s, 13 seconds passed
+... 7%, 49632 KB, 3637 KB/s, 13 seconds passed
+... 7%, 49664 KB, 3638 KB/s, 13 seconds passed
+... 7%, 49696 KB, 3639 KB/s, 13 seconds passed
+... 7%, 49728 KB, 3638 KB/s, 13 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 90976 KB, 3164 KB/s, 28 seconds passed
-... 13%, 91008 KB, 3163 KB/s, 28 seconds passed
+    ... 7%, 49760 KB, 3637 KB/s, 13 seconds passed
+... 7%, 49792 KB, 3638 KB/s, 13 seconds passed
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+... 7%, 49856 KB, 3638 KB/s, 13 seconds passed
+... 7%, 49888 KB, 3637 KB/s, 13 seconds passed
+... 7%, 49920 KB, 3638 KB/s, 13 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 91040 KB, 3161 KB/s, 28 seconds passed
-... 13%, 91072 KB, 3159 KB/s, 28 seconds passed
+    ... 7%, 49952 KB, 3638 KB/s, 13 seconds passed
+... 7%, 49984 KB, 3638 KB/s, 13 seconds passed
+... 7%, 50016 KB, 3637 KB/s, 13 seconds passed
+... 7%, 50048 KB, 3638 KB/s, 13 seconds passed
+... 7%, 50080 KB, 3638 KB/s, 13 seconds passed
+... 7%, 50112 KB, 3638 KB/s, 13 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 91104 KB, 3158 KB/s, 28 seconds passed
-... 13%, 91136 KB, 3157 KB/s, 28 seconds passed
+    ... 7%, 50144 KB, 3638 KB/s, 13 seconds passed
+... 7%, 50176 KB, 3638 KB/s, 13 seconds passed
+... 7%, 50208 KB, 3638 KB/s, 13 seconds passed
+... 7%, 50240 KB, 3639 KB/s, 13 seconds passed
+... 7%, 50272 KB, 3638 KB/s, 13 seconds passed
+... 7%, 50304 KB, 3638 KB/s, 13 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 91168 KB, 3155 KB/s, 28 seconds passed
-... 13%, 91200 KB, 3154 KB/s, 28 seconds passed
-... 13%, 91232 KB, 3153 KB/s, 28 seconds passed
+    ... 7%, 50336 KB, 3638 KB/s, 13 seconds passed
+... 7%, 50368 KB, 3639 KB/s, 13 seconds passed
+... 7%, 50400 KB, 3638 KB/s, 13 seconds passed
+... 7%, 50432 KB, 3638 KB/s, 13 seconds passed
+... 7%, 50464 KB, 3638 KB/s, 13 seconds passed
+... 7%, 50496 KB, 3639 KB/s, 13 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 91264 KB, 3152 KB/s, 28 seconds passed
-... 13%, 91296 KB, 3151 KB/s, 28 seconds passed
+    ... 7%, 50528 KB, 3638 KB/s, 13 seconds passed
+... 7%, 50560 KB, 3638 KB/s, 13 seconds passed
+... 7%, 50592 KB, 3638 KB/s, 13 seconds passed
+... 7%, 50624 KB, 3639 KB/s, 13 seconds passed
+... 7%, 50656 KB, 3638 KB/s, 13 seconds passed
+... 7%, 50688 KB, 3639 KB/s, 13 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 91328 KB, 3149 KB/s, 28 seconds passed
-... 13%, 91360 KB, 3148 KB/s, 29 seconds passed
-... 13%, 91392 KB, 3148 KB/s, 29 seconds passed
+    ... 7%, 50720 KB, 3638 KB/s, 13 seconds passed
+... 7%, 50752 KB, 3639 KB/s, 13 seconds passed
+... 7%, 50784 KB, 3638 KB/s, 13 seconds passed
+... 7%, 50816 KB, 3639 KB/s, 13 seconds passed
+... 7%, 50848 KB, 3639 KB/s, 13 seconds passed
+... 7%, 50880 KB, 3639 KB/s, 13 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 91424 KB, 3147 KB/s, 29 seconds passed
-... 13%, 91456 KB, 3146 KB/s, 29 seconds passed
-... 13%, 91488 KB, 3145 KB/s, 29 seconds passed
+    ... 7%, 50912 KB, 3638 KB/s, 13 seconds passed
+... 7%, 50944 KB, 3639 KB/s, 13 seconds passed
+... 7%, 50976 KB, 3639 KB/s, 14 seconds passed
+... 7%, 51008 KB, 3639 KB/s, 14 seconds passed
+... 7%, 51040 KB, 3639 KB/s, 14 seconds passed
+... 7%, 51072 KB, 3639 KB/s, 14 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 91520 KB, 3145 KB/s, 29 seconds passed
-... 13%, 91552 KB, 3144 KB/s, 29 seconds passed
-... 13%, 91584 KB, 3143 KB/s, 29 seconds passed
+    ... 7%, 51104 KB, 3639 KB/s, 14 seconds passed
+... 7%, 51136 KB, 3639 KB/s, 14 seconds passed
+... 7%, 51168 KB, 3639 KB/s, 14 seconds passed
+... 7%, 51200 KB, 3639 KB/s, 14 seconds passed
+... 7%, 51232 KB, 3639 KB/s, 14 seconds passed
+... 7%, 51264 KB, 3640 KB/s, 14 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 91616 KB, 3143 KB/s, 29 seconds passed
-... 13%, 91648 KB, 3142 KB/s, 29 seconds passed
-... 13%, 91680 KB, 3142 KB/s, 29 seconds passed
-... 13%, 91712 KB, 3141 KB/s, 29 seconds passed
+    ... 7%, 51296 KB, 3639 KB/s, 14 seconds passed
+... 7%, 51328 KB, 3639 KB/s, 14 seconds passed
+... 7%, 51360 KB, 3639 KB/s, 14 seconds passed
+... 7%, 51392 KB, 3640 KB/s, 14 seconds passed
+... 7%, 51424 KB, 3639 KB/s, 14 seconds passed
+... 7%, 51456 KB, 3640 KB/s, 14 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 91744 KB, 3141 KB/s, 29 seconds passed
-... 13%, 91776 KB, 3140 KB/s, 29 seconds passed
-... 13%, 91808 KB, 3140 KB/s, 29 seconds passed
+    ... 7%, 51488 KB, 3639 KB/s, 14 seconds passed
+... 7%, 51520 KB, 3640 KB/s, 14 seconds passed
+... 7%, 51552 KB, 3639 KB/s, 14 seconds passed
+... 7%, 51584 KB, 3640 KB/s, 14 seconds passed
+... 7%, 51616 KB, 3639 KB/s, 14 seconds passed
+... 7%, 51648 KB, 3640 KB/s, 14 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 91840 KB, 3136 KB/s, 29 seconds passed
-... 13%, 91872 KB, 3137 KB/s, 29 seconds passed
-... 13%, 91904 KB, 3138 KB/s, 29 seconds passed
+    ... 7%, 51680 KB, 3640 KB/s, 14 seconds passed
+... 7%, 51712 KB, 3640 KB/s, 14 seconds passed
+... 7%, 51744 KB, 3640 KB/s, 14 seconds passed
+... 7%, 51776 KB, 3640 KB/s, 14 seconds passed
+... 7%, 51808 KB, 3640 KB/s, 14 seconds passed
+... 7%, 51840 KB, 3640 KB/s, 14 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 91936 KB, 3135 KB/s, 29 seconds passed
-... 13%, 91968 KB, 3135 KB/s, 29 seconds passed
+    ... 7%, 51872 KB, 3640 KB/s, 14 seconds passed
+... 7%, 51904 KB, 3640 KB/s, 14 seconds passed
+... 7%, 51936 KB, 3640 KB/s, 14 seconds passed
+... 7%, 51968 KB, 3640 KB/s, 14 seconds passed
+... 7%, 52000 KB, 3640 KB/s, 14 seconds passed
+... 7%, 52032 KB, 3640 KB/s, 14 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 92000 KB, 3133 KB/s, 29 seconds passed
-... 13%, 92032 KB, 3131 KB/s, 29 seconds passed
+    ... 7%, 52064 KB, 3640 KB/s, 14 seconds passed
+... 7%, 52096 KB, 3640 KB/s, 14 seconds passed
+... 7%, 52128 KB, 3640 KB/s, 14 seconds passed
+... 7%, 52160 KB, 3640 KB/s, 14 seconds passed
+... 7%, 52192 KB, 3640 KB/s, 14 seconds passed
+... 7%, 52224 KB, 3640 KB/s, 14 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 92064 KB, 3128 KB/s, 29 seconds passed
-... 13%, 92096 KB, 3127 KB/s, 29 seconds passed
+    ... 7%, 52256 KB, 3640 KB/s, 14 seconds passed
+... 7%, 52288 KB, 3641 KB/s, 14 seconds passed
+... 7%, 52320 KB, 3640 KB/s, 14 seconds passed
+... 7%, 52352 KB, 3640 KB/s, 14 seconds passed
+... 7%, 52384 KB, 3640 KB/s, 14 seconds passed
+... 7%, 52416 KB, 3641 KB/s, 14 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 92128 KB, 3123 KB/s, 29 seconds passed
+    ... 7%, 52448 KB, 3640 KB/s, 14 seconds passed
+... 7%, 52480 KB, 3641 KB/s, 14 seconds passed
+... 7%, 52512 KB, 3641 KB/s, 14 seconds passed
+... 7%, 52544 KB, 3641 KB/s, 14 seconds passed
+... 7%, 52576 KB, 3641 KB/s, 14 seconds passed
+... 7%, 52608 KB, 3641 KB/s, 14 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 92160 KB, 3121 KB/s, 29 seconds passed
+    ... 7%, 52640 KB, 3641 KB/s, 14 seconds passed
+... 7%, 52672 KB, 3641 KB/s, 14 seconds passed
+... 7%, 52704 KB, 3641 KB/s, 14 seconds passed
+... 7%, 52736 KB, 3641 KB/s, 14 seconds passed
+... 7%, 52768 KB, 3641 KB/s, 14 seconds passed
+... 7%, 52800 KB, 3641 KB/s, 14 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 92192 KB, 3116 KB/s, 29 seconds passed
+    ... 7%, 52832 KB, 3641 KB/s, 14 seconds passed
+... 7%, 52864 KB, 3641 KB/s, 14 seconds passed
+... 7%, 52896 KB, 3641 KB/s, 14 seconds passed
+... 7%, 52928 KB, 3642 KB/s, 14 seconds passed
+... 7%, 52960 KB, 3641 KB/s, 14 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 92224 KB, 3113 KB/s, 29 seconds passed
+    ... 7%, 52992 KB, 3641 KB/s, 14 seconds passed
+... 7%, 53024 KB, 3641 KB/s, 14 seconds passed
+... 7%, 53056 KB, 3642 KB/s, 14 seconds passed
+... 7%, 53088 KB, 3641 KB/s, 14 seconds passed
+... 7%, 53120 KB, 3641 KB/s, 14 seconds passed
+... 7%, 53152 KB, 3641 KB/s, 14 seconds passed
+... 7%, 53184 KB, 3642 KB/s, 14 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 92256 KB, 3109 KB/s, 29 seconds passed
+    ... 7%, 53216 KB, 3641 KB/s, 14 seconds passed
+... 7%, 53248 KB, 3641 KB/s, 14 seconds passed
+... 7%, 53280 KB, 3641 KB/s, 14 seconds passed
+... 7%, 53312 KB, 3642 KB/s, 14 seconds passed
+... 7%, 53344 KB, 3641 KB/s, 14 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 92288 KB, 3104 KB/s, 29 seconds passed
-... 13%, 92320 KB, 3102 KB/s, 29 seconds passed
+    ... 7%, 53376 KB, 3642 KB/s, 14 seconds passed
+... 7%, 53408 KB, 3641 KB/s, 14 seconds passed
+... 7%, 53440 KB, 3642 KB/s, 14 seconds passed
+... 7%, 53472 KB, 3641 KB/s, 14 seconds passed
+... 7%, 53504 KB, 3642 KB/s, 14 seconds passed
+... 7%, 53536 KB, 3641 KB/s, 14 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 92352 KB, 3099 KB/s, 29 seconds passed
+    ... 7%, 53568 KB, 3640 KB/s, 14 seconds passed
+... 7%, 53600 KB, 3641 KB/s, 14 seconds passed
+... 7%, 53632 KB, 3641 KB/s, 14 seconds passed
+... 7%, 53664 KB, 3641 KB/s, 14 seconds passed
+... 7%, 53696 KB, 3640 KB/s, 14 seconds passed
+... 7%, 53728 KB, 3641 KB/s, 14 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 92384 KB, 3097 KB/s, 29 seconds passed
+    ... 7%, 53760 KB, 3642 KB/s, 14 seconds passed
+... 7%, 53792 KB, 3642 KB/s, 14 seconds passed
+... 7%, 53824 KB, 3641 KB/s, 14 seconds passed
+... 7%, 53856 KB, 3641 KB/s, 14 seconds passed
+... 7%, 53888 KB, 3642 KB/s, 14 seconds passed
+... 7%, 53920 KB, 3642 KB/s, 14 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 92416 KB, 3093 KB/s, 29 seconds passed
-... 13%, 92448 KB, 3091 KB/s, 29 seconds passed
+    ... 7%, 53952 KB, 3641 KB/s, 14 seconds passed
+... 7%, 53984 KB, 3641 KB/s, 14 seconds passed
+... 7%, 54016 KB, 3642 KB/s, 14 seconds passed
+... 7%, 54048 KB, 3642 KB/s, 14 seconds passed
+... 7%, 54080 KB, 3641 KB/s, 14 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 92480 KB, 3088 KB/s, 29 seconds passed
+    ... 7%, 54112 KB, 3641 KB/s, 14 seconds passed
+... 7%, 54144 KB, 3641 KB/s, 14 seconds passed
+... 7%, 54176 KB, 3642 KB/s, 14 seconds passed
+... 7%, 54208 KB, 3642 KB/s, 14 seconds passed
+... 7%, 54240 KB, 3642 KB/s, 14 seconds passed
+... 7%, 54272 KB, 3641 KB/s, 14 seconds passed
+... 7%, 54304 KB, 3642 KB/s, 14 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 92512 KB, 3086 KB/s, 29 seconds passed
-... 13%, 92544 KB, 3083 KB/s, 30 seconds passed
+    ... 7%, 54336 KB, 3641 KB/s, 14 seconds passed
+... 7%, 54368 KB, 3642 KB/s, 14 seconds passed
+... 7%, 54400 KB, 3642 KB/s, 14 seconds passed
+... 7%, 54432 KB, 3643 KB/s, 14 seconds passed
+... 7%, 54464 KB, 3641 KB/s, 14 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 92576 KB, 3081 KB/s, 30 seconds passed
+    ... 7%, 54496 KB, 3642 KB/s, 14 seconds passed
+... 7%, 54528 KB, 3642 KB/s, 14 seconds passed
+... 7%, 54560 KB, 3643 KB/s, 14 seconds passed
+... 7%, 54592 KB, 3642 KB/s, 14 seconds passed
+... 7%, 54624 KB, 3642 KB/s, 14 seconds passed
+... 7%, 54656 KB, 3642 KB/s, 15 seconds passed
+... 7%, 54688 KB, 3643 KB/s, 15 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 92608 KB, 3079 KB/s, 30 seconds passed
-... 13%, 92640 KB, 3077 KB/s, 30 seconds passed
+    ... 7%, 54720 KB, 3642 KB/s, 15 seconds passed
+... 7%, 54752 KB, 3642 KB/s, 15 seconds passed
+... 7%, 54784 KB, 3642 KB/s, 15 seconds passed
+... 7%, 54816 KB, 3643 KB/s, 15 seconds passed
+... 7%, 54848 KB, 3642 KB/s, 15 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 92672 KB, 3075 KB/s, 30 seconds passed
+    ... 7%, 54880 KB, 3642 KB/s, 15 seconds passed
+... 7%, 54912 KB, 3642 KB/s, 15 seconds passed
+... 7%, 54944 KB, 3643 KB/s, 15 seconds passed
+... 7%, 54976 KB, 3642 KB/s, 15 seconds passed
+... 7%, 55008 KB, 3642 KB/s, 15 seconds passed
+... 7%, 55040 KB, 3642 KB/s, 15 seconds passed
+... 7%, 55072 KB, 3643 KB/s, 15 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 92704 KB, 3072 KB/s, 30 seconds passed
-... 13%, 92736 KB, 3070 KB/s, 30 seconds passed
-... 13%, 92768 KB, 3069 KB/s, 30 seconds passed
+    ... 7%, 55104 KB, 3642 KB/s, 15 seconds passed
+... 7%, 55136 KB, 3642 KB/s, 15 seconds passed
+... 7%, 55168 KB, 3642 KB/s, 15 seconds passed
+... 7%, 55200 KB, 3643 KB/s, 15 seconds passed
+... 7%, 55232 KB, 3642 KB/s, 15 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 92800 KB, 3067 KB/s, 30 seconds passed
+    ... 7%, 55264 KB, 3642 KB/s, 15 seconds passed
+... 7%, 55296 KB, 3642 KB/s, 15 seconds passed
+... 7%, 55328 KB, 3643 KB/s, 15 seconds passed
+... 7%, 55360 KB, 3642 KB/s, 15 seconds passed
+... 7%, 55392 KB, 3642 KB/s, 15 seconds passed
+... 7%, 55424 KB, 3642 KB/s, 15 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 92832 KB, 3065 KB/s, 30 seconds passed
-... 13%, 92864 KB, 3063 KB/s, 30 seconds passed
+    ... 7%, 55456 KB, 3643 KB/s, 15 seconds passed
+... 7%, 55488 KB, 3642 KB/s, 15 seconds passed
+... 7%, 55520 KB, 3643 KB/s, 15 seconds passed
+... 7%, 55552 KB, 3643 KB/s, 15 seconds passed
+... 7%, 55584 KB, 3644 KB/s, 15 seconds passed
+... 7%, 55616 KB, 3643 KB/s, 15 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 92896 KB, 3063 KB/s, 30 seconds passed
-... 13%, 92928 KB, 3061 KB/s, 30 seconds passed
+    ... 8%, 55648 KB, 3643 KB/s, 15 seconds passed
+... 8%, 55680 KB, 3643 KB/s, 15 seconds passed
+... 8%, 55712 KB, 3644 KB/s, 15 seconds passed
+... 8%, 55744 KB, 3643 KB/s, 15 seconds passed
+... 8%, 55776 KB, 3643 KB/s, 15 seconds passed
+... 8%, 55808 KB, 3643 KB/s, 15 seconds passed
+... 8%, 55840 KB, 3644 KB/s, 15 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 92960 KB, 3060 KB/s, 30 seconds passed
-... 13%, 92992 KB, 3057 KB/s, 30 seconds passed
-... 13%, 93024 KB, 3057 KB/s, 30 seconds passed
+    ... 8%, 55872 KB, 3643 KB/s, 15 seconds passed
+... 8%, 55904 KB, 3643 KB/s, 15 seconds passed
+... 8%, 55936 KB, 3643 KB/s, 15 seconds passed
+... 8%, 55968 KB, 3644 KB/s, 15 seconds passed
+... 8%, 56000 KB, 3643 KB/s, 15 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 93056 KB, 3056 KB/s, 30 seconds passed
-... 13%, 93088 KB, 3055 KB/s, 30 seconds passed
+    ... 8%, 56032 KB, 3643 KB/s, 15 seconds passed
+... 8%, 56064 KB, 3643 KB/s, 15 seconds passed
+... 8%, 56096 KB, 3644 KB/s, 15 seconds passed
+... 8%, 56128 KB, 3643 KB/s, 15 seconds passed
+... 8%, 56160 KB, 3643 KB/s, 15 seconds passed
+... 8%, 56192 KB, 3643 KB/s, 15 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 93120 KB, 3054 KB/s, 30 seconds passed
-... 13%, 93152 KB, 3052 KB/s, 30 seconds passed
-... 13%, 93184 KB, 3052 KB/s, 30 seconds passed
+    ... 8%, 56224 KB, 3644 KB/s, 15 seconds passed
+... 8%, 56256 KB, 3643 KB/s, 15 seconds passed
+... 8%, 56288 KB, 3643 KB/s, 15 seconds passed
+... 8%, 56320 KB, 3643 KB/s, 15 seconds passed
+... 8%, 56352 KB, 3644 KB/s, 15 seconds passed
+... 8%, 56384 KB, 3643 KB/s, 15 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 93216 KB, 3050 KB/s, 30 seconds passed
-... 13%, 93248 KB, 3050 KB/s, 30 seconds passed
+    ... 8%, 56416 KB, 3644 KB/s, 15 seconds passed
+... 8%, 56448 KB, 3643 KB/s, 15 seconds passed
+... 8%, 56480 KB, 3644 KB/s, 15 seconds passed
+... 8%, 56512 KB, 3643 KB/s, 15 seconds passed
+... 8%, 56544 KB, 3644 KB/s, 15 seconds passed
+... 8%, 56576 KB, 3644 KB/s, 15 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 93280 KB, 3049 KB/s, 30 seconds passed
-... 13%, 93312 KB, 3047 KB/s, 30 seconds passed
-... 13%, 93344 KB, 3047 KB/s, 30 seconds passed
+    ... 8%, 56608 KB, 3644 KB/s, 15 seconds passed
+... 8%, 56640 KB, 3644 KB/s, 15 seconds passed
+... 8%, 56672 KB, 3644 KB/s, 15 seconds passed
+... 8%, 56704 KB, 3644 KB/s, 15 seconds passed
+... 8%, 56736 KB, 3644 KB/s, 15 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 93376 KB, 3046 KB/s, 30 seconds passed
-... 13%, 93408 KB, 3045 KB/s, 30 seconds passed
+    ... 8%, 56768 KB, 3644 KB/s, 15 seconds passed
+... 8%, 56800 KB, 3644 KB/s, 15 seconds passed
+... 8%, 56832 KB, 3644 KB/s, 15 seconds passed
+... 8%, 56864 KB, 3644 KB/s, 15 seconds passed
+... 8%, 56896 KB, 3644 KB/s, 15 seconds passed
+... 8%, 56928 KB, 3645 KB/s, 15 seconds passed
+... 8%, 56960 KB, 3644 KB/s, 15 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 93440 KB, 3044 KB/s, 30 seconds passed
-... 13%, 93472 KB, 3044 KB/s, 30 seconds passed
-... 13%, 93504 KB, 3043 KB/s, 30 seconds passed
+    ... 8%, 56992 KB, 3645 KB/s, 15 seconds passed
+... 8%, 57024 KB, 3644 KB/s, 15 seconds passed
+... 8%, 57056 KB, 3645 KB/s, 15 seconds passed
+... 8%, 57088 KB, 3644 KB/s, 15 seconds passed
+... 8%, 57120 KB, 3645 KB/s, 15 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 93536 KB, 3042 KB/s, 30 seconds passed
-... 13%, 93568 KB, 3042 KB/s, 30 seconds passed
-... 13%, 93600 KB, 3041 KB/s, 30 seconds passed
+    ... 8%, 57152 KB, 3644 KB/s, 15 seconds passed
+... 8%, 57184 KB, 3645 KB/s, 15 seconds passed
+... 8%, 57216 KB, 3644 KB/s, 15 seconds passed
+... 8%, 57248 KB, 3646 KB/s, 15 seconds passed
+... 8%, 57280 KB, 3645 KB/s, 15 seconds passed
+... 8%, 57312 KB, 3645 KB/s, 15 seconds passed
+... 8%, 57344 KB, 3645 KB/s, 15 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 93632 KB, 3040 KB/s, 30 seconds passed
-... 13%, 93664 KB, 3040 KB/s, 30 seconds passed
-... 13%, 93696 KB, 3039 KB/s, 30 seconds passed
-... 13%, 93728 KB, 3039 KB/s, 30 seconds passed
+    ... 8%, 57376 KB, 3646 KB/s, 15 seconds passed
+... 8%, 57408 KB, 3645 KB/s, 15 seconds passed
+... 8%, 57440 KB, 3645 KB/s, 15 seconds passed
+... 8%, 57472 KB, 3645 KB/s, 15 seconds passed
+... 8%, 57504 KB, 3646 KB/s, 15 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 93760 KB, 3039 KB/s, 30 seconds passed
-... 13%, 93792 KB, 3038 KB/s, 30 seconds passed
-... 13%, 93824 KB, 3038 KB/s, 30 seconds passed
+    ... 8%, 57536 KB, 3645 KB/s, 15 seconds passed
+... 8%, 57568 KB, 3645 KB/s, 15 seconds passed
+... 8%, 57600 KB, 3645 KB/s, 15 seconds passed
+... 8%, 57632 KB, 3644 KB/s, 15 seconds passed
+... 8%, 57664 KB, 3644 KB/s, 15 seconds passed
+... 8%, 57696 KB, 3644 KB/s, 15 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 93856 KB, 3038 KB/s, 30 seconds passed
-... 13%, 93888 KB, 3037 KB/s, 30 seconds passed
-... 13%, 93920 KB, 3037 KB/s, 30 seconds passed
-... 13%, 93952 KB, 3037 KB/s, 30 seconds passed
+    ... 8%, 57728 KB, 3645 KB/s, 15 seconds passed
+... 8%, 57760 KB, 3644 KB/s, 15 seconds passed
+... 8%, 57792 KB, 3644 KB/s, 15 seconds passed
+... 8%, 57824 KB, 3644 KB/s, 15 seconds passed
+... 8%, 57856 KB, 3645 KB/s, 15 seconds passed
+... 8%, 57888 KB, 3644 KB/s, 15 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 93984 KB, 3037 KB/s, 30 seconds passed
-... 13%, 94016 KB, 3036 KB/s, 30 seconds passed
-... 13%, 94048 KB, 3036 KB/s, 30 seconds passed
-... 13%, 94080 KB, 3036 KB/s, 30 seconds passed
+    ... 8%, 57920 KB, 3644 KB/s, 15 seconds passed
+... 8%, 57952 KB, 3644 KB/s, 15 seconds passed
+... 8%, 57984 KB, 3645 KB/s, 15 seconds passed
+... 8%, 58016 KB, 3645 KB/s, 15 seconds passed
+... 8%, 58048 KB, 3644 KB/s, 15 seconds passed
+... 8%, 58080 KB, 3644 KB/s, 15 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 94112 KB, 3036 KB/s, 30 seconds passed
-... 13%, 94144 KB, 3036 KB/s, 31 seconds passed
-... 13%, 94176 KB, 3035 KB/s, 31 seconds passed
-... 13%, 94208 KB, 3035 KB/s, 31 seconds passed
+    ... 8%, 58112 KB, 3645 KB/s, 15 seconds passed
+... 8%, 58144 KB, 3645 KB/s, 15 seconds passed
+... 8%, 58176 KB, 3644 KB/s, 15 seconds passed
+... 8%, 58208 KB, 3644 KB/s, 15 seconds passed
+... 8%, 58240 KB, 3645 KB/s, 15 seconds passed
+... 8%, 58272 KB, 3645 KB/s, 15 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 94240 KB, 3035 KB/s, 31 seconds passed
-... 13%, 94272 KB, 3035 KB/s, 31 seconds passed
-... 13%, 94304 KB, 3035 KB/s, 31 seconds passed
-... 13%, 94336 KB, 3035 KB/s, 31 seconds passed
-... 13%, 94368 KB, 3035 KB/s, 31 seconds passed
+    ... 8%, 58304 KB, 3644 KB/s, 15 seconds passed
+... 8%, 58336 KB, 3644 KB/s, 16 seconds passed
+... 8%, 58368 KB, 3645 KB/s, 16 seconds passed
+... 8%, 58400 KB, 3645 KB/s, 16 seconds passed
+... 8%, 58432 KB, 3645 KB/s, 16 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 94400 KB, 3035 KB/s, 31 seconds passed
-... 13%, 94432 KB, 3035 KB/s, 31 seconds passed
-... 13%, 94464 KB, 3035 KB/s, 31 seconds passed
-... 13%, 94496 KB, 3034 KB/s, 31 seconds passed
+    ... 8%, 58464 KB, 3645 KB/s, 16 seconds passed
+... 8%, 58496 KB, 3645 KB/s, 16 seconds passed
+... 8%, 58528 KB, 3645 KB/s, 16 seconds passed
+... 8%, 58560 KB, 3645 KB/s, 16 seconds passed
+... 8%, 58592 KB, 3645 KB/s, 16 seconds passed
+... 8%, 58624 KB, 3646 KB/s, 16 seconds passed
+... 8%, 58656 KB, 3645 KB/s, 16 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 94528 KB, 3034 KB/s, 31 seconds passed
-... 13%, 94560 KB, 3034 KB/s, 31 seconds passed
-... 13%, 94592 KB, 3034 KB/s, 31 seconds passed
-... 13%, 94624 KB, 3034 KB/s, 31 seconds passed
-... 13%, 94656 KB, 3034 KB/s, 31 seconds passed
+    ... 8%, 58688 KB, 3646 KB/s, 16 seconds passed
+... 8%, 58720 KB, 3646 KB/s, 16 seconds passed
+... 8%, 58752 KB, 3646 KB/s, 16 seconds passed
+... 8%, 58784 KB, 3646 KB/s, 16 seconds passed
+... 8%, 58816 KB, 3646 KB/s, 16 seconds passed
+... 8%, 58848 KB, 3646 KB/s, 16 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 94688 KB, 3034 KB/s, 31 seconds passed
-... 13%, 94720 KB, 3034 KB/s, 31 seconds passed
-... 13%, 94752 KB, 3035 KB/s, 31 seconds passed
-... 13%, 94784 KB, 3035 KB/s, 31 seconds passed
-... 13%, 94816 KB, 3035 KB/s, 31 seconds passed
-... 13%, 94848 KB, 3035 KB/s, 31 seconds passed
+    ... 8%, 58880 KB, 3646 KB/s, 16 seconds passed
+... 8%, 58912 KB, 3646 KB/s, 16 seconds passed
+... 8%, 58944 KB, 3646 KB/s, 16 seconds passed
+... 8%, 58976 KB, 3647 KB/s, 16 seconds passed
+... 8%, 59008 KB, 3646 KB/s, 16 seconds passed
+... 8%, 59040 KB, 3646 KB/s, 16 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 94880 KB, 3034 KB/s, 31 seconds passed
-... 13%, 94912 KB, 3035 KB/s, 31 seconds passed
-... 13%, 94944 KB, 3035 KB/s, 31 seconds passed
-... 13%, 94976 KB, 3035 KB/s, 31 seconds passed
+    ... 8%, 59072 KB, 3645 KB/s, 16 seconds passed
+... 8%, 59104 KB, 3645 KB/s, 16 seconds passed
+... 8%, 59136 KB, 3646 KB/s, 16 seconds passed
+... 8%, 59168 KB, 3645 KB/s, 16 seconds passed
+... 8%, 59200 KB, 3645 KB/s, 16 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 95008 KB, 3035 KB/s, 31 seconds passed
-... 13%, 95040 KB, 3035 KB/s, 31 seconds passed
-... 13%, 95072 KB, 3035 KB/s, 31 seconds passed
-... 13%, 95104 KB, 3035 KB/s, 31 seconds passed
-... 13%, 95136 KB, 3035 KB/s, 31 seconds passed
-... 13%, 95168 KB, 3035 KB/s, 31 seconds passed
+    ... 8%, 59232 KB, 3645 KB/s, 16 seconds passed
+... 8%, 59264 KB, 3646 KB/s, 16 seconds passed
+... 8%, 59296 KB, 3646 KB/s, 16 seconds passed
+... 8%, 59328 KB, 3645 KB/s, 16 seconds passed
+... 8%, 59360 KB, 3645 KB/s, 16 seconds passed
+... 8%, 59392 KB, 3646 KB/s, 16 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 95200 KB, 3035 KB/s, 31 seconds passed
-... 13%, 95232 KB, 3035 KB/s, 31 seconds passed
-... 13%, 95264 KB, 3035 KB/s, 31 seconds passed
-... 13%, 95296 KB, 3036 KB/s, 31 seconds passed
-... 13%, 95328 KB, 3036 KB/s, 31 seconds passed
+    ... 8%, 59424 KB, 3646 KB/s, 16 seconds passed
+... 8%, 59456 KB, 3646 KB/s, 16 seconds passed
+... 8%, 59488 KB, 3646 KB/s, 16 seconds passed
+... 8%, 59520 KB, 3646 KB/s, 16 seconds passed
+... 8%, 59552 KB, 3646 KB/s, 16 seconds passed
+... 8%, 59584 KB, 3646 KB/s, 16 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 95360 KB, 3036 KB/s, 31 seconds passed
-... 13%, 95392 KB, 3036 KB/s, 31 seconds passed
-... 13%, 95424 KB, 3036 KB/s, 31 seconds passed
-... 13%, 95456 KB, 3036 KB/s, 31 seconds passed
-... 13%, 95488 KB, 3036 KB/s, 31 seconds passed
-... 13%, 95520 KB, 3037 KB/s, 31 seconds passed
+    ... 8%, 59616 KB, 3646 KB/s, 16 seconds passed
+... 8%, 59648 KB, 3646 KB/s, 16 seconds passed
+... 8%, 59680 KB, 3646 KB/s, 16 seconds passed
+... 8%, 59712 KB, 3646 KB/s, 16 seconds passed
+... 8%, 59744 KB, 3646 KB/s, 16 seconds passed
+... 8%, 59776 KB, 3647 KB/s, 16 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 95552 KB, 3037 KB/s, 31 seconds passed
-... 13%, 95584 KB, 3037 KB/s, 31 seconds passed
-... 13%, 95616 KB, 3037 KB/s, 31 seconds passed
-... 13%, 95648 KB, 3037 KB/s, 31 seconds passed
-... 13%, 95680 KB, 3038 KB/s, 31 seconds passed
+    ... 8%, 59808 KB, 3646 KB/s, 16 seconds passed
+... 8%, 59840 KB, 3646 KB/s, 16 seconds passed
+... 8%, 59872 KB, 3646 KB/s, 16 seconds passed
+... 8%, 59904 KB, 3647 KB/s, 16 seconds passed
+... 8%, 59936 KB, 3646 KB/s, 16 seconds passed
+... 8%, 59968 KB, 3646 KB/s, 16 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 95712 KB, 3037 KB/s, 31 seconds passed
-... 13%, 95744 KB, 3038 KB/s, 31 seconds passed
-... 13%, 95776 KB, 3038 KB/s, 31 seconds passed
-... 13%, 95808 KB, 3038 KB/s, 31 seconds passed
-... 13%, 95840 KB, 3038 KB/s, 31 seconds passed
-... 13%, 95872 KB, 3038 KB/s, 31 seconds passed
-... 13%, 95904 KB, 3039 KB/s, 31 seconds passed
+    ... 8%, 60000 KB, 3646 KB/s, 16 seconds passed
+... 8%, 60032 KB, 3647 KB/s, 16 seconds passed
+... 8%, 60064 KB, 3646 KB/s, 16 seconds passed
+... 8%, 60096 KB, 3646 KB/s, 16 seconds passed
+... 8%, 60128 KB, 3646 KB/s, 16 seconds passed
+... 8%, 60160 KB, 3647 KB/s, 16 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 95936 KB, 3039 KB/s, 31 seconds passed
-... 13%, 95968 KB, 3039 KB/s, 31 seconds passed
-... 13%, 96000 KB, 3039 KB/s, 31 seconds passed
-... 13%, 96032 KB, 3039 KB/s, 31 seconds passed
-... 13%, 96064 KB, 3040 KB/s, 31 seconds passed
+    ... 8%, 60192 KB, 3646 KB/s, 16 seconds passed
+... 8%, 60224 KB, 3646 KB/s, 16 seconds passed
+... 8%, 60256 KB, 3646 KB/s, 16 seconds passed
+... 8%, 60288 KB, 3647 KB/s, 16 seconds passed
+... 8%, 60320 KB, 3646 KB/s, 16 seconds passed
+... 8%, 60352 KB, 3646 KB/s, 16 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 96096 KB, 3040 KB/s, 31 seconds passed
-... 13%, 96128 KB, 3040 KB/s, 31 seconds passed
-... 13%, 96160 KB, 3040 KB/s, 31 seconds passed
-... 13%, 96192 KB, 3040 KB/s, 31 seconds passed
-... 13%, 96224 KB, 3040 KB/s, 31 seconds passed
-... 13%, 96256 KB, 3041 KB/s, 31 seconds passed
+    ... 8%, 60384 KB, 3646 KB/s, 16 seconds passed
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+... 8%, 60480 KB, 3647 KB/s, 16 seconds passed
+... 8%, 60512 KB, 3647 KB/s, 16 seconds passed
+... 8%, 60544 KB, 3648 KB/s, 16 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 96288 KB, 3041 KB/s, 31 seconds passed
-... 13%, 96320 KB, 3041 KB/s, 31 seconds passed
-... 13%, 96352 KB, 3041 KB/s, 31 seconds passed
-... 13%, 96384 KB, 3041 KB/s, 31 seconds passed
-... 13%, 96416 KB, 3042 KB/s, 31 seconds passed
-... 13%, 96448 KB, 3042 KB/s, 31 seconds passed
+    ... 8%, 60576 KB, 3647 KB/s, 16 seconds passed
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+... 8%, 60672 KB, 3647 KB/s, 16 seconds passed
+... 8%, 60704 KB, 3646 KB/s, 16 seconds passed
+... 8%, 60736 KB, 3647 KB/s, 16 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 96480 KB, 3042 KB/s, 31 seconds passed
-... 13%, 96512 KB, 3042 KB/s, 31 seconds passed
-... 13%, 96544 KB, 3042 KB/s, 31 seconds passed
-... 13%, 96576 KB, 3042 KB/s, 31 seconds passed
-... 13%, 96608 KB, 3042 KB/s, 31 seconds passed
-... 13%, 96640 KB, 3043 KB/s, 31 seconds passed
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+... 8%, 60896 KB, 3647 KB/s, 16 seconds passed
+... 8%, 60928 KB, 3648 KB/s, 16 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 96672 KB, 3043 KB/s, 31 seconds passed
-... 13%, 96704 KB, 3043 KB/s, 31 seconds passed
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-... 13%, 96800 KB, 3044 KB/s, 31 seconds passed
-... 13%, 96832 KB, 3044 KB/s, 31 seconds passed
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+... 8%, 61088 KB, 3647 KB/s, 16 seconds passed
+... 8%, 61120 KB, 3647 KB/s, 16 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 96864 KB, 3044 KB/s, 31 seconds passed
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-... 13%, 96928 KB, 3044 KB/s, 31 seconds passed
-... 13%, 96960 KB, 3045 KB/s, 31 seconds passed
-... 13%, 96992 KB, 3045 KB/s, 31 seconds passed
-... 13%, 97024 KB, 3045 KB/s, 31 seconds passed
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+... 8%, 61280 KB, 3647 KB/s, 16 seconds passed
+... 8%, 61312 KB, 3648 KB/s, 16 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 97056 KB, 3045 KB/s, 31 seconds passed
-... 13%, 97088 KB, 3045 KB/s, 31 seconds passed
-... 13%, 97120 KB, 3045 KB/s, 31 seconds passed
-... 13%, 97152 KB, 3046 KB/s, 31 seconds passed
-... 13%, 97184 KB, 3046 KB/s, 31 seconds passed
-... 13%, 97216 KB, 3046 KB/s, 31 seconds passed
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+... 8%, 61472 KB, 3647 KB/s, 16 seconds passed
+... 8%, 61504 KB, 3648 KB/s, 16 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 97248 KB, 3046 KB/s, 31 seconds passed
-... 13%, 97280 KB, 3046 KB/s, 31 seconds passed
-... 13%, 97312 KB, 3047 KB/s, 31 seconds passed
-... 13%, 97344 KB, 3047 KB/s, 31 seconds passed
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-... 14%, 97408 KB, 3047 KB/s, 31 seconds passed
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+... 8%, 61664 KB, 3647 KB/s, 16 seconds passed
+... 8%, 61696 KB, 3648 KB/s, 16 seconds passed
 
 .. parsed-literal::
 
-    ... 14%, 97440 KB, 3047 KB/s, 31 seconds passed
-... 14%, 97472 KB, 3047 KB/s, 31 seconds passed
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-... 14%, 97568 KB, 3048 KB/s, 32 seconds passed
-... 14%, 97600 KB, 3048 KB/s, 32 seconds passed
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+... 8%, 61792 KB, 3648 KB/s, 16 seconds passed
+... 8%, 61824 KB, 3648 KB/s, 16 seconds passed
+... 8%, 61856 KB, 3648 KB/s, 16 seconds passed
 
 .. parsed-literal::
 
-    ... 14%, 97632 KB, 3048 KB/s, 32 seconds passed
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-... 14%, 97760 KB, 3049 KB/s, 32 seconds passed
-... 14%, 97792 KB, 3049 KB/s, 32 seconds passed
+    ... 8%, 61888 KB, 3648 KB/s, 16 seconds passed
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+... 8%, 62016 KB, 3648 KB/s, 16 seconds passed
+... 8%, 62048 KB, 3648 KB/s, 17 seconds passed
+... 8%, 62080 KB, 3648 KB/s, 17 seconds passed
 
 .. parsed-literal::
 
-    ... 14%, 97824 KB, 3049 KB/s, 32 seconds passed
-... 14%, 97856 KB, 3049 KB/s, 32 seconds passed
-... 14%, 97888 KB, 3049 KB/s, 32 seconds passed
-... 14%, 97920 KB, 3050 KB/s, 32 seconds passed
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-... 14%, 97984 KB, 3050 KB/s, 32 seconds passed
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+... 8%, 62176 KB, 3648 KB/s, 17 seconds passed
+... 8%, 62208 KB, 3649 KB/s, 17 seconds passed
+... 8%, 62240 KB, 3648 KB/s, 17 seconds passed
 
 .. parsed-literal::
 
-    ... 14%, 98016 KB, 3050 KB/s, 32 seconds passed
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-... 14%, 98080 KB, 3051 KB/s, 32 seconds passed
-... 14%, 98112 KB, 3051 KB/s, 32 seconds passed
-... 14%, 98144 KB, 3051 KB/s, 32 seconds passed
-... 14%, 98176 KB, 3051 KB/s, 32 seconds passed
+    ... 8%, 62272 KB, 3647 KB/s, 17 seconds passed
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+... 8%, 62400 KB, 3647 KB/s, 17 seconds passed
+... 8%, 62432 KB, 3648 KB/s, 17 seconds passed
 
 .. parsed-literal::
 
-    ... 14%, 98208 KB, 3051 KB/s, 32 seconds passed
-... 14%, 98240 KB, 3052 KB/s, 32 seconds passed
-... 14%, 98272 KB, 3052 KB/s, 32 seconds passed
-... 14%, 98304 KB, 3052 KB/s, 32 seconds passed
-... 14%, 98336 KB, 3052 KB/s, 32 seconds passed
-... 14%, 98368 KB, 3052 KB/s, 32 seconds passed
+    ... 8%, 62464 KB, 3648 KB/s, 17 seconds passed
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+... 8%, 62560 KB, 3648 KB/s, 17 seconds passed
+... 8%, 62592 KB, 3648 KB/s, 17 seconds passed
+... 9%, 62624 KB, 3648 KB/s, 17 seconds passed
 
 .. parsed-literal::
 
-    ... 14%, 98400 KB, 3052 KB/s, 32 seconds passed
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-... 14%, 98464 KB, 3053 KB/s, 32 seconds passed
-... 14%, 98496 KB, 3053 KB/s, 32 seconds passed
-... 14%, 98528 KB, 3053 KB/s, 32 seconds passed
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+... 9%, 62784 KB, 3649 KB/s, 17 seconds passed
+... 9%, 62816 KB, 3648 KB/s, 17 seconds passed
 
 .. parsed-literal::
 
-    ... 14%, 98560 KB, 3053 KB/s, 32 seconds passed
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 .. parsed-literal::
 
-    ... 14%, 98688 KB, 3051 KB/s, 32 seconds passed
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 .. parsed-literal::
 
-    ... 14%, 98816 KB, 3051 KB/s, 32 seconds passed
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 .. parsed-literal::
 
-    ... 14%, 98848 KB, 3046 KB/s, 32 seconds passed
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 .. parsed-literal::
 
-    ... 14%, 98880 KB, 3043 KB/s, 32 seconds passed
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 .. parsed-literal::
 
-    ... 14%, 98944 KB, 3039 KB/s, 32 seconds passed
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 .. parsed-literal::
 
-    ... 14%, 98976 KB, 3034 KB/s, 32 seconds passed
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 .. parsed-literal::
 
-    ... 14%, 99008 KB, 3031 KB/s, 32 seconds passed
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 .. parsed-literal::
 
-    ... 14%, 99040 KB, 3029 KB/s, 32 seconds passed
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+... 9%, 64480 KB, 3649 KB/s, 17 seconds passed
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 .. parsed-literal::
 
-    ... 14%, 99136 KB, 3025 KB/s, 32 seconds passed
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 .. parsed-literal::
 
-    ... 14%, 99168 KB, 3023 KB/s, 32 seconds passed
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 .. parsed-literal::
 
-    ... 14%, 99264 KB, 3020 KB/s, 32 seconds passed
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 .. parsed-literal::
 
-    ... 14%, 99296 KB, 3018 KB/s, 32 seconds passed
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 .. parsed-literal::
 
-    ... 14%, 99392 KB, 3014 KB/s, 32 seconds passed
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 .. parsed-literal::
 
-    ... 14%, 99456 KB, 3013 KB/s, 33 seconds passed
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+... 9%, 65600 KB, 3650 KB/s, 17 seconds passed
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 .. parsed-literal::
 
-    ... 14%, 99552 KB, 3010 KB/s, 33 seconds passed
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+    ... 9%, 65664 KB, 3650 KB/s, 17 seconds passed
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 .. parsed-literal::
 
-    ... 14%, 99616 KB, 3009 KB/s, 33 seconds passed
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-... 14%, 99680 KB, 3007 KB/s, 33 seconds passed
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 .. parsed-literal::
 
-    ... 14%, 99744 KB, 3006 KB/s, 33 seconds passed
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 .. parsed-literal::
 
-    ... 14%, 99808 KB, 3005 KB/s, 33 seconds passed
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-... 14%, 99872 KB, 3004 KB/s, 33 seconds passed
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+    ... 9%, 66240 KB, 3650 KB/s, 18 seconds passed
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+... 9%, 66336 KB, 3650 KB/s, 18 seconds passed
+... 9%, 66368 KB, 3650 KB/s, 18 seconds passed
+... 9%, 66400 KB, 3650 KB/s, 18 seconds passed
 
 .. parsed-literal::
 
-    ... 14%, 99936 KB, 3005 KB/s, 33 seconds passed
-... 14%, 99968 KB, 3003 KB/s, 33 seconds passed
-... 14%, 100000 KB, 3004 KB/s, 33 seconds passed
+    ... 9%, 66432 KB, 3650 KB/s, 18 seconds passed
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+... 9%, 66560 KB, 3650 KB/s, 18 seconds passed
+... 9%, 66592 KB, 3651 KB/s, 18 seconds passed
 
 .. parsed-literal::
 
-    ... 14%, 100032 KB, 3002 KB/s, 33 seconds passed
-... 14%, 100064 KB, 3003 KB/s, 33 seconds passed
-... 14%, 100096 KB, 3003 KB/s, 33 seconds passed
-... 14%, 100128 KB, 3002 KB/s, 33 seconds passed
+    ... 9%, 66624 KB, 3650 KB/s, 18 seconds passed
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+... 9%, 66752 KB, 3650 KB/s, 18 seconds passed
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 .. parsed-literal::
 
-    ... 14%, 100160 KB, 3002 KB/s, 33 seconds passed
-... 14%, 100192 KB, 3001 KB/s, 33 seconds passed
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+    ... 9%, 66816 KB, 3650 KB/s, 18 seconds passed
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+... 9%, 66944 KB, 3651 KB/s, 18 seconds passed
+... 9%, 66976 KB, 3651 KB/s, 18 seconds passed
 
 .. parsed-literal::
 
-    ... 14%, 100288 KB, 3001 KB/s, 33 seconds passed
-... 14%, 100320 KB, 3001 KB/s, 33 seconds passed
-... 14%, 100352 KB, 3001 KB/s, 33 seconds passed
-... 14%, 100384 KB, 3000 KB/s, 33 seconds passed
+    ... 9%, 67008 KB, 3651 KB/s, 18 seconds passed
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+... 9%, 67104 KB, 3651 KB/s, 18 seconds passed
+... 9%, 67136 KB, 3651 KB/s, 18 seconds passed
+... 9%, 67168 KB, 3651 KB/s, 18 seconds passed
 
 .. parsed-literal::
 
-    ... 14%, 100416 KB, 3001 KB/s, 33 seconds passed
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-... 14%, 100480 KB, 3000 KB/s, 33 seconds passed
-... 14%, 100512 KB, 3000 KB/s, 33 seconds passed
-... 14%, 100544 KB, 3001 KB/s, 33 seconds passed
+    ... 9%, 67200 KB, 3651 KB/s, 18 seconds passed
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+... 9%, 67296 KB, 3651 KB/s, 18 seconds passed
+... 9%, 67328 KB, 3651 KB/s, 18 seconds passed
+... 9%, 67360 KB, 3652 KB/s, 18 seconds passed
 
 .. parsed-literal::
 
-    ... 14%, 100576 KB, 3000 KB/s, 33 seconds passed
-... 14%, 100608 KB, 3000 KB/s, 33 seconds passed
-... 14%, 100640 KB, 3000 KB/s, 33 seconds passed
-... 14%, 100672 KB, 3000 KB/s, 33 seconds passed
+    ... 9%, 67392 KB, 3651 KB/s, 18 seconds passed
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+... 9%, 67520 KB, 3651 KB/s, 18 seconds passed
+... 9%, 67552 KB, 3651 KB/s, 18 seconds passed
 
 .. parsed-literal::
 
-    ... 14%, 100704 KB, 3000 KB/s, 33 seconds passed
-... 14%, 100736 KB, 3000 KB/s, 33 seconds passed
-... 14%, 100768 KB, 3000 KB/s, 33 seconds passed
-... 14%, 100800 KB, 3000 KB/s, 33 seconds passed
-... 14%, 100832 KB, 3000 KB/s, 33 seconds passed
+    ... 9%, 67584 KB, 3651 KB/s, 18 seconds passed
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+... 9%, 67680 KB, 3651 KB/s, 18 seconds passed
+... 9%, 67712 KB, 3651 KB/s, 18 seconds passed
+... 9%, 67744 KB, 3652 KB/s, 18 seconds passed
 
 .. parsed-literal::
 
-    ... 14%, 100864 KB, 2999 KB/s, 33 seconds passed
-... 14%, 100896 KB, 3000 KB/s, 33 seconds passed
-... 14%, 100928 KB, 3000 KB/s, 33 seconds passed
-... 14%, 100960 KB, 2999 KB/s, 33 seconds passed
+    ... 9%, 67776 KB, 3651 KB/s, 18 seconds passed
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+... 9%, 67840 KB, 3652 KB/s, 18 seconds passed
+... 9%, 67872 KB, 3652 KB/s, 18 seconds passed
+... 9%, 67904 KB, 3651 KB/s, 18 seconds passed
+... 9%, 67936 KB, 3652 KB/s, 18 seconds passed
 
 .. parsed-literal::
 
-    ... 14%, 100992 KB, 3000 KB/s, 33 seconds passed
-... 14%, 101024 KB, 3000 KB/s, 33 seconds passed
-... 14%, 101056 KB, 3001 KB/s, 33 seconds passed
-... 14%, 101088 KB, 3000 KB/s, 33 seconds passed
-... 14%, 101120 KB, 3000 KB/s, 33 seconds passed
-... 14%, 101152 KB, 3001 KB/s, 33 seconds passed
-... 14%, 101184 KB, 3001 KB/s, 33 seconds passed
+    ... 9%, 67968 KB, 3651 KB/s, 18 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 16%, 112128 KB, 2975 KB/s, 37 seconds passed
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+... 11%, 82784 KB, 3655 KB/s, 22 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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+... 11%, 83200 KB, 3656 KB/s, 22 seconds passed
 
 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 16%, 113248 KB, 2950 KB/s, 38 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 16%, 116640 KB, 2962 KB/s, 39 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 16%, 117152 KB, 2964 KB/s, 39 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 17%, 123072 KB, 2981 KB/s, 41 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 17%, 123456 KB, 2983 KB/s, 41 seconds passed
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 .. parsed-literal::
 
-    ... 17%, 123584 KB, 2984 KB/s, 41 seconds passed
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 .. parsed-literal::
 
-    ... 17%, 123808 KB, 2985 KB/s, 41 seconds passed
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-... 17%, 123872 KB, 2985 KB/s, 41 seconds passed
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+... 13%, 96768 KB, 3659 KB/s, 26 seconds passed
+... 13%, 96800 KB, 3659 KB/s, 26 seconds passed
+... 13%, 96832 KB, 3660 KB/s, 26 seconds passed
 
 .. parsed-literal::
 
-    ... 17%, 123968 KB, 2986 KB/s, 41 seconds passed
-... 17%, 124000 KB, 2986 KB/s, 41 seconds passed
-... 17%, 124032 KB, 2987 KB/s, 41 seconds passed
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-... 17%, 124096 KB, 2986 KB/s, 41 seconds passed
-... 17%, 124128 KB, 2987 KB/s, 41 seconds passed
-... 17%, 124160 KB, 2987 KB/s, 41 seconds passed
+    ... 13%, 96864 KB, 3660 KB/s, 26 seconds passed
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+... 13%, 96928 KB, 3660 KB/s, 26 seconds passed
+... 13%, 96960 KB, 3660 KB/s, 26 seconds passed
+... 13%, 96992 KB, 3660 KB/s, 26 seconds passed
 
 .. parsed-literal::
 
-    ... 17%, 124192 KB, 2986 KB/s, 41 seconds passed
-... 17%, 124224 KB, 2987 KB/s, 41 seconds passed
-... 17%, 124256 KB, 2987 KB/s, 41 seconds passed
-... 17%, 124288 KB, 2988 KB/s, 41 seconds passed
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+... 13%, 97152 KB, 3659 KB/s, 26 seconds passed
+... 13%, 97184 KB, 3660 KB/s, 26 seconds passed
+... 13%, 97216 KB, 3660 KB/s, 26 seconds passed
 
 .. parsed-literal::
 
-    ... 17%, 124320 KB, 2987 KB/s, 41 seconds passed
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-... 17%, 124384 KB, 2988 KB/s, 41 seconds passed
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-... 17%, 124448 KB, 2988 KB/s, 41 seconds passed
-... 17%, 124480 KB, 2988 KB/s, 41 seconds passed
-... 17%, 124512 KB, 2988 KB/s, 41 seconds passed
-... 17%, 124544 KB, 2989 KB/s, 41 seconds passed
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+... 13%, 97312 KB, 3660 KB/s, 26 seconds passed
+... 13%, 97344 KB, 3660 KB/s, 26 seconds passed
+... 14%, 97376 KB, 3661 KB/s, 26 seconds passed
 
 .. parsed-literal::
 
-    ... 17%, 124576 KB, 2988 KB/s, 41 seconds passed
-... 17%, 124608 KB, 2988 KB/s, 41 seconds passed
-... 17%, 124640 KB, 2989 KB/s, 41 seconds passed
-... 17%, 124672 KB, 2989 KB/s, 41 seconds passed
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+... 14%, 97536 KB, 3660 KB/s, 26 seconds passed
+... 14%, 97568 KB, 3660 KB/s, 26 seconds passed
+... 14%, 97600 KB, 3660 KB/s, 26 seconds passed
 
 .. parsed-literal::
 
-    ... 17%, 124704 KB, 2989 KB/s, 41 seconds passed
-... 17%, 124736 KB, 2989 KB/s, 41 seconds passed
-... 17%, 124768 KB, 2990 KB/s, 41 seconds passed
-... 17%, 124800 KB, 2990 KB/s, 41 seconds passed
-... 17%, 124832 KB, 2989 KB/s, 41 seconds passed
-... 17%, 124864 KB, 2990 KB/s, 41 seconds passed
-... 17%, 124896 KB, 2990 KB/s, 41 seconds passed
-... 17%, 124928 KB, 2991 KB/s, 41 seconds passed
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+... 14%, 97696 KB, 3660 KB/s, 26 seconds passed
+... 14%, 97728 KB, 3661 KB/s, 26 seconds passed
+... 14%, 97760 KB, 3661 KB/s, 26 seconds passed
 
 .. parsed-literal::
 
-    ... 17%, 124960 KB, 2990 KB/s, 41 seconds passed
-... 17%, 124992 KB, 2990 KB/s, 41 seconds passed
-... 17%, 125024 KB, 2991 KB/s, 41 seconds passed
-... 17%, 125056 KB, 2991 KB/s, 41 seconds passed
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+... 14%, 97920 KB, 3660 KB/s, 26 seconds passed
+... 14%, 97952 KB, 3660 KB/s, 26 seconds passed
+... 14%, 97984 KB, 3661 KB/s, 26 seconds passed
 
 .. parsed-literal::
 
-    ... 17%, 125088 KB, 2991 KB/s, 41 seconds passed
-... 17%, 125120 KB, 2991 KB/s, 41 seconds passed
-... 17%, 125152 KB, 2991 KB/s, 41 seconds passed
-... 17%, 125184 KB, 2992 KB/s, 41 seconds passed
-... 18%, 125216 KB, 2991 KB/s, 41 seconds passed
-... 18%, 125248 KB, 2991 KB/s, 41 seconds passed
-... 18%, 125280 KB, 2992 KB/s, 41 seconds passed
-... 18%, 125312 KB, 2992 KB/s, 41 seconds passed
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+... 14%, 98080 KB, 3660 KB/s, 26 seconds passed
+... 14%, 98112 KB, 3661 KB/s, 26 seconds passed
 
 .. parsed-literal::
 
-    ... 18%, 125344 KB, 2992 KB/s, 41 seconds passed
-... 18%, 125376 KB, 2992 KB/s, 41 seconds passed
-... 18%, 125408 KB, 2993 KB/s, 41 seconds passed
-... 18%, 125440 KB, 2993 KB/s, 41 seconds passed
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+... 14%, 98272 KB, 3661 KB/s, 26 seconds passed
+... 14%, 98304 KB, 3660 KB/s, 26 seconds passed
+... 14%, 98336 KB, 3660 KB/s, 26 seconds passed
 
 .. parsed-literal::
 
-    ... 18%, 125472 KB, 2992 KB/s, 41 seconds passed
-... 18%, 125504 KB, 2993 KB/s, 41 seconds passed
-... 18%, 125536 KB, 2993 KB/s, 41 seconds passed
-... 18%, 125568 KB, 2994 KB/s, 41 seconds passed
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+... 14%, 98432 KB, 3660 KB/s, 26 seconds passed
+... 14%, 98464 KB, 3660 KB/s, 26 seconds passed
+... 14%, 98496 KB, 3661 KB/s, 26 seconds passed
 
 .. parsed-literal::
 
-    ... 18%, 125600 KB, 2990 KB/s, 41 seconds passed
-... 18%, 125632 KB, 2991 KB/s, 41 seconds passed
-... 18%, 125664 KB, 2992 KB/s, 41 seconds passed
-... 18%, 125696 KB, 2993 KB/s, 41 seconds passed
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+... 14%, 98656 KB, 3660 KB/s, 26 seconds passed
+... 14%, 98688 KB, 3660 KB/s, 26 seconds passed
+... 14%, 98720 KB, 3660 KB/s, 26 seconds passed
 
 .. parsed-literal::
 
-    ... 18%, 125728 KB, 2991 KB/s, 42 seconds passed
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+... 14%, 98848 KB, 3660 KB/s, 27 seconds passed
+... 14%, 98880 KB, 3661 KB/s, 27 seconds passed
 
 .. parsed-literal::
 
-    ... 18%, 125760 KB, 2987 KB/s, 42 seconds passed
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+... 14%, 99040 KB, 3660 KB/s, 27 seconds passed
+... 14%, 99072 KB, 3660 KB/s, 27 seconds passed
+... 14%, 99104 KB, 3660 KB/s, 27 seconds passed
 
 .. parsed-literal::
 
-    ... 18%, 125792 KB, 2985 KB/s, 42 seconds passed
-... 18%, 125824 KB, 2986 KB/s, 42 seconds passed
-... 18%, 125856 KB, 2984 KB/s, 42 seconds passed
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+... 14%, 99200 KB, 3660 KB/s, 27 seconds passed
+... 14%, 99232 KB, 3660 KB/s, 27 seconds passed
+... 14%, 99264 KB, 3661 KB/s, 27 seconds passed
 
 .. parsed-literal::
 
-    ... 18%, 125888 KB, 2983 KB/s, 42 seconds passed
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+... 14%, 99392 KB, 3661 KB/s, 27 seconds passed
+... 14%, 99424 KB, 3660 KB/s, 27 seconds passed
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 .. parsed-literal::
 
-    ... 18%, 125920 KB, 2981 KB/s, 42 seconds passed
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+... 14%, 99616 KB, 3661 KB/s, 27 seconds passed
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 .. parsed-literal::
 
-    ... 18%, 126016 KB, 2978 KB/s, 42 seconds passed
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+... 14%, 99808 KB, 3660 KB/s, 27 seconds passed
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 .. parsed-literal::
 
-    ... 18%, 126080 KB, 2977 KB/s, 42 seconds passed
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-... 18%, 126144 KB, 2976 KB/s, 42 seconds passed
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+... 14%, 100000 KB, 3661 KB/s, 27 seconds passed
+... 14%, 100032 KB, 3661 KB/s, 27 seconds passed
 
 .. parsed-literal::
 
-    ... 18%, 126176 KB, 2975 KB/s, 42 seconds passed
-... 18%, 126208 KB, 2975 KB/s, 42 seconds passed
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+... 14%, 100192 KB, 3660 KB/s, 27 seconds passed
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 .. parsed-literal::
 
-    ... 18%, 126272 KB, 2975 KB/s, 42 seconds passed
-... 18%, 126304 KB, 2975 KB/s, 42 seconds passed
-... 18%, 126336 KB, 2974 KB/s, 42 seconds passed
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 .. parsed-literal::
 
-    ... 18%, 126400 KB, 2973 KB/s, 42 seconds passed
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 .. parsed-literal::
 
-    ... 18%, 126496 KB, 2973 KB/s, 42 seconds passed
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 .. parsed-literal::
 
-    ... 18%, 126656 KB, 2973 KB/s, 42 seconds passed
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 .. parsed-literal::
 
-    ... 18%, 126784 KB, 2972 KB/s, 42 seconds passed
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 .. parsed-literal::
 
-    ... 18%, 126976 KB, 2974 KB/s, 42 seconds passed
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 .. parsed-literal::
 
-    ... 18%, 127104 KB, 2973 KB/s, 42 seconds passed
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 .. parsed-literal::
 
-    ... 18%, 127328 KB, 2975 KB/s, 42 seconds passed
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 .. parsed-literal::
 
-    ... 18%, 127488 KB, 2974 KB/s, 42 seconds passed
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 .. parsed-literal::
 
-    ... 18%, 127680 KB, 2976 KB/s, 42 seconds passed
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 .. parsed-literal::
 
-    ... 18%, 127872 KB, 2976 KB/s, 42 seconds passed
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-... 18%, 128000 KB, 2977 KB/s, 42 seconds passed
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+... 14%, 102304 KB, 3662 KB/s, 27 seconds passed
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 .. parsed-literal::
 
-    ... 18%, 128064 KB, 2978 KB/s, 43 seconds passed
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+    ... 14%, 102368 KB, 3661 KB/s, 27 seconds passed
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 .. parsed-literal::
 
-    ... 18%, 128256 KB, 2978 KB/s, 43 seconds passed
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-... 18%, 128320 KB, 2979 KB/s, 43 seconds passed
-... 18%, 128352 KB, 2979 KB/s, 43 seconds passed
-... 18%, 128384 KB, 2978 KB/s, 43 seconds passed
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 .. parsed-literal::
 
-    ... 18%, 128416 KB, 2979 KB/s, 43 seconds passed
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-... 18%, 128480 KB, 2980 KB/s, 43 seconds passed
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-... 18%, 128576 KB, 2980 KB/s, 43 seconds passed
-... 18%, 128608 KB, 2980 KB/s, 43 seconds passed
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+... 14%, 102816 KB, 3662 KB/s, 28 seconds passed
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 .. parsed-literal::
 
-    ... 18%, 128640 KB, 2980 KB/s, 43 seconds passed
-... 18%, 128672 KB, 2980 KB/s, 43 seconds passed
-... 18%, 128704 KB, 2980 KB/s, 43 seconds passed
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-... 18%, 128768 KB, 2980 KB/s, 43 seconds passed
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+... 14%, 103008 KB, 3661 KB/s, 28 seconds passed
+... 14%, 103040 KB, 3661 KB/s, 28 seconds passed
+... 14%, 103072 KB, 3662 KB/s, 28 seconds passed
 
 .. parsed-literal::
 
-    ... 18%, 128800 KB, 2981 KB/s, 43 seconds passed
-... 18%, 128832 KB, 2981 KB/s, 43 seconds passed
-... 18%, 128864 KB, 2981 KB/s, 43 seconds passed
-... 18%, 128896 KB, 2981 KB/s, 43 seconds passed
-... 18%, 128928 KB, 2981 KB/s, 43 seconds passed
-... 18%, 128960 KB, 2982 KB/s, 43 seconds passed
-... 18%, 128992 KB, 2982 KB/s, 43 seconds passed
+    ... 14%, 103104 KB, 3661 KB/s, 28 seconds passed
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+... 14%, 103168 KB, 3661 KB/s, 28 seconds passed
+... 14%, 103200 KB, 3662 KB/s, 28 seconds passed
+... 14%, 103232 KB, 3661 KB/s, 28 seconds passed
 
 .. parsed-literal::
 
-    ... 18%, 129024 KB, 2981 KB/s, 43 seconds passed
-... 18%, 129056 KB, 2982 KB/s, 43 seconds passed
-... 18%, 129088 KB, 2982 KB/s, 43 seconds passed
-... 18%, 129120 KB, 2983 KB/s, 43 seconds passed
-... 18%, 129152 KB, 2982 KB/s, 43 seconds passed
+    ... 14%, 103264 KB, 3661 KB/s, 28 seconds passed
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+... 14%, 103392 KB, 3661 KB/s, 28 seconds passed
+... 14%, 103424 KB, 3661 KB/s, 28 seconds passed
+... 14%, 103456 KB, 3662 KB/s, 28 seconds passed
 
 .. parsed-literal::
 
-    ... 18%, 129184 KB, 2982 KB/s, 43 seconds passed
-... 18%, 129216 KB, 2983 KB/s, 43 seconds passed
-... 18%, 129248 KB, 2983 KB/s, 43 seconds passed
-... 18%, 129280 KB, 2982 KB/s, 43 seconds passed
-... 18%, 129312 KB, 2983 KB/s, 43 seconds passed
-... 18%, 129344 KB, 2983 KB/s, 43 seconds passed
-... 18%, 129376 KB, 2984 KB/s, 43 seconds passed
+    ... 14%, 103488 KB, 3661 KB/s, 28 seconds passed
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+... 14%, 103552 KB, 3661 KB/s, 28 seconds passed
+... 14%, 103584 KB, 3662 KB/s, 28 seconds passed
+... 14%, 103616 KB, 3661 KB/s, 28 seconds passed
 
 .. parsed-literal::
 
-    ... 18%, 129408 KB, 2983 KB/s, 43 seconds passed
-... 18%, 129440 KB, 2983 KB/s, 43 seconds passed
-... 18%, 129472 KB, 2984 KB/s, 43 seconds passed
-... 18%, 129504 KB, 2984 KB/s, 43 seconds passed
+    ... 14%, 103648 KB, 3661 KB/s, 28 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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-... 21%, 147712 KB, 3014 KB/s, 49 seconds passed
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+... 17%, 124384 KB, 3665 KB/s, 33 seconds passed
+... 17%, 124416 KB, 3666 KB/s, 33 seconds passed
+... 17%, 124448 KB, 3666 KB/s, 33 seconds passed
 
 .. parsed-literal::
 
-    ... 21%, 147744 KB, 3014 KB/s, 49 seconds passed
-... 21%, 147776 KB, 3015 KB/s, 49 seconds passed
-... 21%, 147808 KB, 3014 KB/s, 49 seconds passed
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-... 21%, 147872 KB, 3015 KB/s, 49 seconds passed
-... 21%, 147904 KB, 3015 KB/s, 49 seconds passed
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+... 17%, 124576 KB, 3666 KB/s, 33 seconds passed
+... 17%, 124608 KB, 3665 KB/s, 33 seconds passed
 
 .. parsed-literal::
 
-    ... 21%, 147936 KB, 3014 KB/s, 49 seconds passed
-... 21%, 147968 KB, 3015 KB/s, 49 seconds passed
-... 21%, 148000 KB, 3015 KB/s, 49 seconds passed
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+... 17%, 124800 KB, 3666 KB/s, 34 seconds passed
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 .. parsed-literal::
 
-    ... 21%, 148064 KB, 3015 KB/s, 49 seconds passed
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-... 21%, 148256 KB, 3016 KB/s, 49 seconds passed
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+... 17%, 124960 KB, 3666 KB/s, 34 seconds passed
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 .. parsed-literal::
 
-    ... 21%, 148320 KB, 3016 KB/s, 49 seconds passed
-... 21%, 148352 KB, 3016 KB/s, 49 seconds passed
-... 21%, 148384 KB, 3016 KB/s, 49 seconds passed
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 .. parsed-literal::
 
-    ... 21%, 148448 KB, 3016 KB/s, 49 seconds passed
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-... 21%, 148608 KB, 3017 KB/s, 49 seconds passed
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 .. parsed-literal::
 
-    ... 21%, 148704 KB, 3017 KB/s, 49 seconds passed
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+... 18%, 125536 KB, 3665 KB/s, 34 seconds passed
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 .. parsed-literal::
 
-    ... 21%, 148832 KB, 3018 KB/s, 49 seconds passed
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-... 21%, 148896 KB, 3018 KB/s, 49 seconds passed
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-... 21%, 148960 KB, 3018 KB/s, 49 seconds passed
-... 21%, 148992 KB, 3018 KB/s, 49 seconds passed
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+... 18%, 125696 KB, 3665 KB/s, 34 seconds passed
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 .. parsed-literal::
 
-    ... 21%, 149056 KB, 3018 KB/s, 49 seconds passed
-... 21%, 149088 KB, 3019 KB/s, 49 seconds passed
-... 21%, 149120 KB, 3019 KB/s, 49 seconds passed
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+... 18%, 125888 KB, 3665 KB/s, 34 seconds passed
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+... 18%, 125952 KB, 3665 KB/s, 34 seconds passed
 
 .. parsed-literal::
 
-    ... 21%, 149184 KB, 3019 KB/s, 49 seconds passed
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-... 21%, 149280 KB, 3020 KB/s, 49 seconds passed
-... 21%, 149312 KB, 3019 KB/s, 49 seconds passed
-... 21%, 149344 KB, 3020 KB/s, 49 seconds passed
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 .. parsed-literal::
 
-    ... 21%, 149376 KB, 3018 KB/s, 49 seconds passed
-... 21%, 149408 KB, 3018 KB/s, 49 seconds passed
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+... 18%, 126272 KB, 3665 KB/s, 34 seconds passed
+... 18%, 126304 KB, 3665 KB/s, 34 seconds passed
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 .. parsed-literal::
 
-    ... 21%, 149504 KB, 3018 KB/s, 49 seconds passed
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+... 18%, 126464 KB, 3666 KB/s, 34 seconds passed
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 .. parsed-literal::
 
-    ... 21%, 149536 KB, 3015 KB/s, 49 seconds passed
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 .. parsed-literal::
 
-    ... 21%, 149568 KB, 3013 KB/s, 49 seconds passed
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+... 18%, 126816 KB, 3666 KB/s, 34 seconds passed
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 .. parsed-literal::
 
-    ... 21%, 149632 KB, 3010 KB/s, 49 seconds passed
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 .. parsed-literal::
 
-    ... 21%, 149664 KB, 3009 KB/s, 49 seconds passed
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+... 18%, 127168 KB, 3666 KB/s, 34 seconds passed
+... 18%, 127200 KB, 3666 KB/s, 34 seconds passed
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 .. parsed-literal::
 
-    ... 21%, 149728 KB, 3006 KB/s, 49 seconds passed
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 .. parsed-literal::
 
-    ... 21%, 149760 KB, 3005 KB/s, 49 seconds passed
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 .. parsed-literal::
 
-    ... 21%, 149856 KB, 3002 KB/s, 49 seconds passed
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+... 18%, 127808 KB, 3666 KB/s, 34 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 21%, 149984 KB, 3001 KB/s, 49 seconds passed
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 .. parsed-literal::
 
-    ... 21%, 150080 KB, 2999 KB/s, 50 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 21%, 150272 KB, 2996 KB/s, 50 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 21%, 151936 KB, 2996 KB/s, 50 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 21%, 152320 KB, 2998 KB/s, 50 seconds passed
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 .. parsed-literal::
 
-    ... 21%, 152512 KB, 2999 KB/s, 50 seconds passed
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-... 21%, 152672 KB, 3000 KB/s, 50 seconds passed
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 .. parsed-literal::
 
-    ... 21%, 152704 KB, 2999 KB/s, 50 seconds passed
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-... 21%, 152800 KB, 3000 KB/s, 50 seconds passed
-... 21%, 152832 KB, 3000 KB/s, 50 seconds passed
-... 21%, 152864 KB, 3000 KB/s, 50 seconds passed
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+... 18%, 131488 KB, 3664 KB/s, 35 seconds passed
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+... 18%, 131552 KB, 3666 KB/s, 35 seconds passed
 
 .. parsed-literal::
 
-    ... 21%, 152896 KB, 3000 KB/s, 50 seconds passed
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-... 21%, 152960 KB, 3000 KB/s, 50 seconds passed
-... 21%, 152992 KB, 3000 KB/s, 50 seconds passed
-... 22%, 153024 KB, 3001 KB/s, 50 seconds passed
-... 22%, 153056 KB, 3001 KB/s, 50 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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-... 22%, 159616 KB, 3023 KB/s, 52 seconds passed
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+... 19%, 138080 KB, 3660 KB/s, 37 seconds passed
+... 19%, 138112 KB, 3661 KB/s, 37 seconds passed
+... 19%, 138144 KB, 3659 KB/s, 37 seconds passed
 
 .. parsed-literal::
 
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-... 22%, 159776 KB, 3024 KB/s, 52 seconds passed
-... 22%, 159808 KB, 3024 KB/s, 52 seconds passed
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+... 19%, 138336 KB, 3661 KB/s, 37 seconds passed
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 .. parsed-literal::
 
-    ... 22%, 159840 KB, 3024 KB/s, 52 seconds passed
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-... 22%, 159936 KB, 3024 KB/s, 52 seconds passed
-... 23%, 159968 KB, 3024 KB/s, 52 seconds passed
-... 23%, 160000 KB, 3024 KB/s, 52 seconds passed
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+... 19%, 138496 KB, 3661 KB/s, 37 seconds passed
 
 .. parsed-literal::
 
-    ... 23%, 160032 KB, 3024 KB/s, 52 seconds passed
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-... 23%, 160192 KB, 3025 KB/s, 52 seconds passed
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 .. parsed-literal::
 
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+    ... 19%, 138816 KB, 3660 KB/s, 37 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 23%, 160992 KB, 3028 KB/s, 53 seconds passed
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 .. parsed-literal::
 
-    ... 23%, 161152 KB, 3028 KB/s, 53 seconds passed
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 .. parsed-literal::
 
-    ... 23%, 161376 KB, 3029 KB/s, 53 seconds passed
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 .. parsed-literal::
 
-    ... 23%, 161536 KB, 3029 KB/s, 53 seconds passed
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 .. parsed-literal::
 
-    ... 23%, 161728 KB, 3030 KB/s, 53 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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+... 20%, 144928 KB, 3661 KB/s, 39 seconds passed
+... 20%, 144960 KB, 3662 KB/s, 39 seconds passed
+... 20%, 144992 KB, 3662 KB/s, 39 seconds passed
 
 .. parsed-literal::
 
-    ... 23%, 165440 KB, 3026 KB/s, 54 seconds passed
-... 23%, 165472 KB, 3026 KB/s, 54 seconds passed
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+... 20%, 145088 KB, 3662 KB/s, 39 seconds passed
+... 20%, 145120 KB, 3662 KB/s, 39 seconds passed
+... 20%, 145152 KB, 3661 KB/s, 39 seconds passed
 
 .. parsed-literal::
 
-    ... 23%, 165504 KB, 3025 KB/s, 54 seconds passed
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+... 20%, 145312 KB, 3661 KB/s, 39 seconds passed
+... 20%, 145344 KB, 3662 KB/s, 39 seconds passed
+... 20%, 145376 KB, 3662 KB/s, 39 seconds passed
 
 .. parsed-literal::
 
-    ... 23%, 165664 KB, 3024 KB/s, 54 seconds passed
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+... 20%, 145472 KB, 3662 KB/s, 39 seconds passed
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 .. parsed-literal::
 
-    ... 23%, 165760 KB, 3024 KB/s, 54 seconds passed
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+... 20%, 145696 KB, 3661 KB/s, 39 seconds passed
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+... 20%, 145760 KB, 3663 KB/s, 39 seconds passed
 
 .. parsed-literal::
 
-    ... 23%, 165984 KB, 3024 KB/s, 54 seconds passed
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 .. parsed-literal::
 
-    ... 23%, 166080 KB, 3024 KB/s, 54 seconds passed
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+... 21%, 146144 KB, 3663 KB/s, 39 seconds passed
 
 .. parsed-literal::
 
-    ... 23%, 166272 KB, 3025 KB/s, 54 seconds passed
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-... 23%, 166400 KB, 3026 KB/s, 54 seconds passed
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+... 21%, 146240 KB, 3662 KB/s, 39 seconds passed
+... 21%, 146272 KB, 3663 KB/s, 39 seconds passed
 
 .. parsed-literal::
 
-    ... 23%, 166432 KB, 3025 KB/s, 55 seconds passed
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-... 23%, 166592 KB, 3026 KB/s, 55 seconds passed
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 .. parsed-literal::
 
-    ... 23%, 166624 KB, 3026 KB/s, 55 seconds passed
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 .. parsed-literal::
 
-    ... 23%, 166784 KB, 3026 KB/s, 55 seconds passed
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+... 21%, 146880 KB, 3662 KB/s, 40 seconds passed
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 .. parsed-literal::
 
-    ... 24%, 166976 KB, 3027 KB/s, 55 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 24%, 167328 KB, 3027 KB/s, 55 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 24%, 170560 KB, 3037 KB/s, 56 seconds passed
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 .. parsed-literal::
 
-    ... 24%, 170720 KB, 3038 KB/s, 56 seconds passed
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 .. parsed-literal::
 
-    ... 24%, 170944 KB, 3038 KB/s, 56 seconds passed
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 .. parsed-literal::
 
-    ... 24%, 171072 KB, 3039 KB/s, 56 seconds passed
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 .. parsed-literal::
 
-    ... 24%, 171328 KB, 3040 KB/s, 56 seconds passed
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+... 21%, 151360 KB, 3663 KB/s, 41 seconds passed
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 .. parsed-literal::
 
-    ... 24%, 171456 KB, 3040 KB/s, 56 seconds passed
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-... 24%, 171616 KB, 3041 KB/s, 56 seconds passed
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-... 24%, 171680 KB, 3041 KB/s, 56 seconds passed
+    ... 21%, 151424 KB, 3662 KB/s, 41 seconds passed
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+... 21%, 151552 KB, 3662 KB/s, 41 seconds passed
+... 21%, 151584 KB, 3662 KB/s, 41 seconds passed
+... 21%, 151616 KB, 3663 KB/s, 41 seconds passed
 
 .. parsed-literal::
 
-    ... 24%, 171712 KB, 3041 KB/s, 56 seconds passed
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+... 21%, 151744 KB, 3663 KB/s, 41 seconds passed
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 .. parsed-literal::
 
-    ... 24%, 171840 KB, 3041 KB/s, 56 seconds passed
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-... 24%, 171968 KB, 3042 KB/s, 56 seconds passed
-... 24%, 172000 KB, 3042 KB/s, 56 seconds passed
-... 24%, 172032 KB, 3042 KB/s, 56 seconds passed
-... 24%, 172064 KB, 3043 KB/s, 56 seconds passed
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+... 21%, 151936 KB, 3662 KB/s, 41 seconds passed
+... 21%, 151968 KB, 3662 KB/s, 41 seconds passed
+... 21%, 152000 KB, 3663 KB/s, 41 seconds passed
 
 .. parsed-literal::
 
-    ... 24%, 172096 KB, 3042 KB/s, 56 seconds passed
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+... 21%, 152096 KB, 3663 KB/s, 41 seconds passed
+... 21%, 152128 KB, 3663 KB/s, 41 seconds passed
 
 .. parsed-literal::
 
-    ... 24%, 172224 KB, 3042 KB/s, 56 seconds passed
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-... 24%, 172448 KB, 3044 KB/s, 56 seconds passed
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+... 21%, 152352 KB, 3663 KB/s, 41 seconds passed
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 .. parsed-literal::
 
-    ... 24%, 172480 KB, 3043 KB/s, 56 seconds passed
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 .. parsed-literal::
 
-    ... 24%, 172608 KB, 3044 KB/s, 56 seconds passed
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-... 24%, 172768 KB, 3044 KB/s, 56 seconds passed
-... 24%, 172800 KB, 3045 KB/s, 56 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 24%, 172992 KB, 3045 KB/s, 56 seconds passed
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-... 24%, 173120 KB, 3045 KB/s, 56 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 24%, 173376 KB, 3046 KB/s, 56 seconds passed
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 .. parsed-literal::
 
-    ... 24%, 173568 KB, 3047 KB/s, 56 seconds passed
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-... 24%, 173696 KB, 3047 KB/s, 56 seconds passed
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 .. parsed-literal::
 
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-... 25%, 173920 KB, 3048 KB/s, 57 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 25%, 174496 KB, 3049 KB/s, 57 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 25%, 174880 KB, 3051 KB/s, 57 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 25%, 175264 KB, 3052 KB/s, 57 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 25%, 175648 KB, 3053 KB/s, 57 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 25%, 176576 KB, 3056 KB/s, 57 seconds passed
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 .. parsed-literal::
 
-    ... 25%, 176800 KB, 3056 KB/s, 57 seconds passed
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 .. parsed-literal::
 
-    ... 25%, 176960 KB, 3057 KB/s, 57 seconds passed
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 .. parsed-literal::
 
-    ... 25%, 177152 KB, 3057 KB/s, 57 seconds passed
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 .. parsed-literal::
 
-    ... 25%, 177344 KB, 3058 KB/s, 57 seconds passed
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 .. parsed-literal::
 
-    ... 25%, 177536 KB, 3058 KB/s, 58 seconds passed
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 .. parsed-literal::
 
-    ... 25%, 177728 KB, 3059 KB/s, 58 seconds passed
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-... 25%, 177856 KB, 3060 KB/s, 58 seconds passed
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+... 22%, 157792 KB, 3663 KB/s, 43 seconds passed
+... 22%, 157824 KB, 3663 KB/s, 43 seconds passed
 
 .. parsed-literal::
 
-    ... 25%, 177920 KB, 3060 KB/s, 58 seconds passed
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-... 25%, 177984 KB, 3060 KB/s, 58 seconds passed
-... 25%, 178016 KB, 3060 KB/s, 58 seconds passed
-... 25%, 178048 KB, 3060 KB/s, 58 seconds passed
-... 25%, 178080 KB, 3060 KB/s, 58 seconds passed
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+... 22%, 157920 KB, 3663 KB/s, 43 seconds passed
+... 22%, 157952 KB, 3663 KB/s, 43 seconds passed
+... 22%, 157984 KB, 3662 KB/s, 43 seconds passed
 
 .. parsed-literal::
 
-    ... 25%, 178112 KB, 3060 KB/s, 58 seconds passed
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-... 25%, 178208 KB, 3061 KB/s, 58 seconds passed
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-... 25%, 178272 KB, 3061 KB/s, 58 seconds passed
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+... 22%, 158144 KB, 3663 KB/s, 43 seconds passed
+... 22%, 158176 KB, 3663 KB/s, 43 seconds passed
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 .. parsed-literal::
 
-    ... 25%, 178304 KB, 3061 KB/s, 58 seconds passed
-... 25%, 178336 KB, 3061 KB/s, 58 seconds passed
-... 25%, 178368 KB, 3061 KB/s, 58 seconds passed
-... 25%, 178400 KB, 3061 KB/s, 58 seconds passed
-... 25%, 178432 KB, 3061 KB/s, 58 seconds passed
-... 25%, 178464 KB, 3061 KB/s, 58 seconds passed
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+... 22%, 158272 KB, 3663 KB/s, 43 seconds passed
+... 22%, 158304 KB, 3663 KB/s, 43 seconds passed
+... 22%, 158336 KB, 3663 KB/s, 43 seconds passed
 
 .. parsed-literal::
 
-    ... 25%, 178496 KB, 3062 KB/s, 58 seconds passed
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-... 25%, 178656 KB, 3062 KB/s, 58 seconds passed
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+... 22%, 158528 KB, 3663 KB/s, 43 seconds passed
+... 22%, 158560 KB, 3663 KB/s, 43 seconds passed
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 .. parsed-literal::
 
-    ... 25%, 178688 KB, 3062 KB/s, 58 seconds passed
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-... 25%, 178816 KB, 3062 KB/s, 58 seconds passed
-... 25%, 178848 KB, 3063 KB/s, 58 seconds passed
+    ... 22%, 158624 KB, 3662 KB/s, 43 seconds passed
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+... 22%, 158688 KB, 3663 KB/s, 43 seconds passed
+... 22%, 158720 KB, 3663 KB/s, 43 seconds passed
 
 .. parsed-literal::
 
-    ... 25%, 178880 KB, 3063 KB/s, 58 seconds passed
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-... 25%, 178976 KB, 3063 KB/s, 58 seconds passed
-... 25%, 179008 KB, 3063 KB/s, 58 seconds passed
-... 25%, 179040 KB, 3063 KB/s, 58 seconds passed
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+... 22%, 158912 KB, 3663 KB/s, 43 seconds passed
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 .. parsed-literal::
 
-    ... 25%, 179072 KB, 3063 KB/s, 58 seconds passed
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-... 25%, 179200 KB, 3063 KB/s, 58 seconds passed
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+... 22%, 159104 KB, 3663 KB/s, 43 seconds passed
 
 .. parsed-literal::
 
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-... 25%, 179392 KB, 3064 KB/s, 58 seconds passed
-... 25%, 179424 KB, 3064 KB/s, 58 seconds passed
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+... 22%, 159296 KB, 3663 KB/s, 43 seconds passed
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 .. parsed-literal::
 
-    ... 25%, 179456 KB, 3064 KB/s, 58 seconds passed
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-... 25%, 179584 KB, 3064 KB/s, 58 seconds passed
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+... 22%, 159456 KB, 3663 KB/s, 43 seconds passed
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 .. parsed-literal::
 
-    ... 25%, 179616 KB, 3065 KB/s, 58 seconds passed
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-... 25%, 179680 KB, 3065 KB/s, 58 seconds passed
-... 25%, 179712 KB, 3065 KB/s, 58 seconds passed
-... 25%, 179744 KB, 3065 KB/s, 58 seconds passed
-... 25%, 179776 KB, 3065 KB/s, 58 seconds passed
-... 25%, 179808 KB, 3066 KB/s, 58 seconds passed
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+... 22%, 159648 KB, 3663 KB/s, 43 seconds passed
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 .. parsed-literal::
 
-    ... 25%, 179840 KB, 3065 KB/s, 58 seconds passed
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+... 22%, 159872 KB, 3664 KB/s, 43 seconds passed
 
 .. parsed-literal::
 
-    ... 25%, 179968 KB, 3066 KB/s, 58 seconds passed
-... 25%, 180000 KB, 3066 KB/s, 58 seconds passed
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-... 25%, 180096 KB, 3066 KB/s, 58 seconds passed
-... 25%, 180128 KB, 3066 KB/s, 58 seconds passed
-... 25%, 180160 KB, 3066 KB/s, 58 seconds passed
+    ... 22%, 159904 KB, 3663 KB/s, 43 seconds passed
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+... 23%, 160032 KB, 3663 KB/s, 43 seconds passed
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 .. parsed-literal::
 
-    ... 25%, 180192 KB, 3067 KB/s, 58 seconds passed
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-... 25%, 180256 KB, 3067 KB/s, 58 seconds passed
-... 25%, 180288 KB, 3067 KB/s, 58 seconds passed
-... 25%, 180320 KB, 3067 KB/s, 58 seconds passed
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+... 23%, 160256 KB, 3664 KB/s, 43 seconds passed
 
 .. parsed-literal::
 
-    ... 25%, 180352 KB, 3067 KB/s, 58 seconds passed
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-... 25%, 180480 KB, 3067 KB/s, 58 seconds passed
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-... 25%, 180544 KB, 3068 KB/s, 58 seconds passed
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 .. parsed-literal::
 
-    ... 25%, 180576 KB, 3068 KB/s, 58 seconds passed
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 .. parsed-literal::
 
-    ... 25%, 180736 KB, 3068 KB/s, 58 seconds passed
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-... 26%, 180864 KB, 3068 KB/s, 58 seconds passed
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 .. parsed-literal::
 
-    ... 26%, 180960 KB, 3069 KB/s, 58 seconds passed
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 .. parsed-literal::
 
-    ... 26%, 181120 KB, 3069 KB/s, 59 seconds passed
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 .. parsed-literal::
 
-    ... 26%, 181344 KB, 3070 KB/s, 59 seconds passed
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 .. parsed-literal::
 
-    ... 26%, 181504 KB, 3070 KB/s, 59 seconds passed
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 .. parsed-literal::
 
-    ... 26%, 181696 KB, 3071 KB/s, 59 seconds passed
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 .. parsed-literal::
 
-    ... 26%, 181888 KB, 3071 KB/s, 59 seconds passed
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 .. parsed-literal::
 
-    ... 26%, 182080 KB, 3072 KB/s, 59 seconds passed
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 .. parsed-literal::
 
-    ... 26%, 182272 KB, 3072 KB/s, 59 seconds passed
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 .. parsed-literal::
 
-    ... 26%, 182464 KB, 3073 KB/s, 59 seconds passed
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 .. parsed-literal::
 
-    ... 26%, 182624 KB, 3073 KB/s, 59 seconds passed
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 .. parsed-literal::
 
-    ... 26%, 182848 KB, 3074 KB/s, 59 seconds passed
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 .. parsed-literal::
 
-    ... 26%, 183008 KB, 3074 KB/s, 59 seconds passed
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 .. parsed-literal::
 
-    ... 26%, 183232 KB, 3075 KB/s, 59 seconds passed
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 .. parsed-literal::
 
-    ... 26%, 183392 KB, 3075 KB/s, 59 seconds passed
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+... 23%, 163456 KB, 3663 KB/s, 44 seconds passed
 
 .. parsed-literal::
 
-    ... 26%, 183616 KB, 3076 KB/s, 59 seconds passed
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+... 23%, 163616 KB, 3664 KB/s, 44 seconds passed
+... 23%, 163648 KB, 3664 KB/s, 44 seconds passed
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 .. parsed-literal::
 
-    ... 26%, 183776 KB, 3076 KB/s, 59 seconds passed
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+... 23%, 163808 KB, 3664 KB/s, 44 seconds passed
+... 23%, 163840 KB, 3663 KB/s, 44 seconds passed
 
 .. parsed-literal::
 
-    ... 26%, 183968 KB, 3077 KB/s, 59 seconds passed
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-... 26%, 184096 KB, 3078 KB/s, 59 seconds passed
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+... 23%, 164000 KB, 3664 KB/s, 44 seconds passed
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 .. parsed-literal::
 
-    ... 26%, 184160 KB, 3077 KB/s, 59 seconds passed
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-... 26%, 184224 KB, 3078 KB/s, 59 seconds passed
-... 26%, 184256 KB, 3078 KB/s, 59 seconds passed
-... 26%, 184288 KB, 3078 KB/s, 59 seconds passed
-... 26%, 184320 KB, 3078 KB/s, 59 seconds passed
+    ... 23%, 164096 KB, 3663 KB/s, 44 seconds passed
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+... 23%, 164192 KB, 3664 KB/s, 44 seconds passed
+... 23%, 164224 KB, 3663 KB/s, 44 seconds passed
 
 .. parsed-literal::
 
-    ... 26%, 184352 KB, 3078 KB/s, 59 seconds passed
-... 26%, 184384 KB, 3078 KB/s, 59 seconds passed
-... 26%, 184416 KB, 3078 KB/s, 59 seconds passed
-... 26%, 184448 KB, 3078 KB/s, 59 seconds passed
-... 26%, 184480 KB, 3079 KB/s, 59 seconds passed
-... 26%, 184512 KB, 3079 KB/s, 59 seconds passed
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+... 23%, 164384 KB, 3664 KB/s, 44 seconds passed
+... 23%, 164416 KB, 3664 KB/s, 44 seconds passed
+... 23%, 164448 KB, 3664 KB/s, 44 seconds passed
 
 .. parsed-literal::
 
-    ... 26%, 184544 KB, 3078 KB/s, 59 seconds passed
-... 26%, 184576 KB, 3079 KB/s, 59 seconds passed
-... 26%, 184608 KB, 3079 KB/s, 59 seconds passed
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-... 26%, 184672 KB, 3079 KB/s, 59 seconds passed
-... 26%, 184704 KB, 3079 KB/s, 59 seconds passed
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+... 23%, 164512 KB, 3664 KB/s, 44 seconds passed
+... 23%, 164544 KB, 3664 KB/s, 44 seconds passed
+... 23%, 164576 KB, 3664 KB/s, 44 seconds passed
 
 .. parsed-literal::
 
-    ... 26%, 184736 KB, 3079 KB/s, 59 seconds passed
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-... 26%, 184864 KB, 3080 KB/s, 60 seconds passed
-... 26%, 184896 KB, 3080 KB/s, 60 seconds passed
+    ... 23%, 164608 KB, 3663 KB/s, 44 seconds passed
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+... 23%, 164736 KB, 3663 KB/s, 44 seconds passed
+... 23%, 164768 KB, 3664 KB/s, 44 seconds passed
+... 23%, 164800 KB, 3664 KB/s, 44 seconds passed
 
 .. parsed-literal::
 
-    ... 26%, 184928 KB, 3080 KB/s, 60 seconds passed
-... 26%, 184960 KB, 3080 KB/s, 60 seconds passed
-... 26%, 184992 KB, 3080 KB/s, 60 seconds passed
-... 26%, 185024 KB, 3080 KB/s, 60 seconds passed
-... 26%, 185056 KB, 3080 KB/s, 60 seconds passed
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+... 23%, 164896 KB, 3664 KB/s, 45 seconds passed
+... 23%, 164928 KB, 3664 KB/s, 45 seconds passed
+... 23%, 164960 KB, 3664 KB/s, 45 seconds passed
 
 .. parsed-literal::
 
-    ... 26%, 185088 KB, 3080 KB/s, 60 seconds passed
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+... 23%, 165120 KB, 3664 KB/s, 45 seconds passed
+... 23%, 165152 KB, 3664 KB/s, 45 seconds passed
+... 23%, 165184 KB, 3664 KB/s, 45 seconds passed
 
 .. parsed-literal::
 
-    ... 26%, 185312 KB, 3081 KB/s, 60 seconds passed
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+... 23%, 165280 KB, 3664 KB/s, 45 seconds passed
+... 23%, 165312 KB, 3664 KB/s, 45 seconds passed
+... 23%, 165344 KB, 3664 KB/s, 45 seconds passed
 
 .. parsed-literal::
 
-    ... 26%, 185472 KB, 3081 KB/s, 60 seconds passed
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-... 26%, 185600 KB, 3081 KB/s, 60 seconds passed
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-... 26%, 185664 KB, 3082 KB/s, 60 seconds passed
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+... 23%, 165536 KB, 3664 KB/s, 45 seconds passed
+... 23%, 165568 KB, 3664 KB/s, 45 seconds passed
 
 .. parsed-literal::
 
-    ... 26%, 185696 KB, 3082 KB/s, 60 seconds passed
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+... 23%, 165664 KB, 3664 KB/s, 45 seconds passed
+... 23%, 165696 KB, 3664 KB/s, 45 seconds passed
+... 23%, 165728 KB, 3663 KB/s, 45 seconds passed
 
 .. parsed-literal::
 
-    ... 26%, 185856 KB, 3082 KB/s, 60 seconds passed
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+... 23%, 165888 KB, 3664 KB/s, 45 seconds passed
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+... 23%, 165952 KB, 3664 KB/s, 45 seconds passed
 
 .. parsed-literal::
 
-    ... 26%, 186080 KB, 3083 KB/s, 60 seconds passed
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+... 23%, 166080 KB, 3664 KB/s, 45 seconds passed
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 .. parsed-literal::
 
-    ... 26%, 186240 KB, 3083 KB/s, 60 seconds passed
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-... 26%, 186368 KB, 3084 KB/s, 60 seconds passed
-... 26%, 186400 KB, 3084 KB/s, 60 seconds passed
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+... 23%, 166272 KB, 3664 KB/s, 45 seconds passed
+... 23%, 166304 KB, 3664 KB/s, 45 seconds passed
+... 23%, 166336 KB, 3664 KB/s, 45 seconds passed
 
 .. parsed-literal::
 
-    ... 26%, 186464 KB, 3084 KB/s, 60 seconds passed
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 .. parsed-literal::
 
-    ... 26%, 186592 KB, 3084 KB/s, 60 seconds passed
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 .. parsed-literal::
 
-    ... 26%, 186816 KB, 3085 KB/s, 60 seconds passed
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 .. parsed-literal::
 
-    ... 26%, 186976 KB, 3085 KB/s, 60 seconds passed
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 .. parsed-literal::
 
-    ... 26%, 187200 KB, 3086 KB/s, 60 seconds passed
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 .. parsed-literal::
 
-    ... 26%, 187360 KB, 3086 KB/s, 60 seconds passed
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 .. parsed-literal::
 
-    ... 26%, 187584 KB, 3087 KB/s, 60 seconds passed
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 .. parsed-literal::
 
-    ... 26%, 187744 KB, 3087 KB/s, 60 seconds passed
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 .. parsed-literal::
 
-    ... 27%, 187936 KB, 3088 KB/s, 60 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 27%, 188320 KB, 3089 KB/s, 60 seconds passed
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 .. parsed-literal::
 
-    ... 27%, 188480 KB, 3086 KB/s, 61 seconds passed
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 .. parsed-literal::
 
-    ... 27%, 188576 KB, 3084 KB/s, 61 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 27%, 188832 KB, 3082 KB/s, 61 seconds passed
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 .. parsed-literal::
 
-    ... 27%, 189024 KB, 3081 KB/s, 61 seconds passed
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 .. parsed-literal::
 
-    ... 27%, 189120 KB, 3081 KB/s, 61 seconds passed
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 .. parsed-literal::
 
-    ... 27%, 189344 KB, 3081 KB/s, 61 seconds passed
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 .. parsed-literal::
 
-    ... 27%, 189472 KB, 3082 KB/s, 61 seconds passed
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 .. parsed-literal::
 
-    ... 27%, 189696 KB, 3083 KB/s, 61 seconds passed
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 .. parsed-literal::
 
-    ... 27%, 189856 KB, 3083 KB/s, 61 seconds passed
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 .. parsed-literal::
 
-    ... 27%, 190080 KB, 3084 KB/s, 61 seconds passed
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-... 27%, 190144 KB, 3084 KB/s, 61 seconds passed
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-... 27%, 190208 KB, 3085 KB/s, 61 seconds passed
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+... 24%, 170624 KB, 3665 KB/s, 46 seconds passed
+... 24%, 170656 KB, 3665 KB/s, 46 seconds passed
 
 .. parsed-literal::
 
-    ... 27%, 190240 KB, 3084 KB/s, 61 seconds passed
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-... 27%, 190304 KB, 3085 KB/s, 61 seconds passed
-... 27%, 190336 KB, 3085 KB/s, 61 seconds passed
-... 27%, 190368 KB, 3084 KB/s, 61 seconds passed
-... 27%, 190400 KB, 3084 KB/s, 61 seconds passed
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+... 24%, 170848 KB, 3664 KB/s, 46 seconds passed
 
 .. parsed-literal::
 
-    ... 27%, 190464 KB, 3085 KB/s, 61 seconds passed
-... 27%, 190496 KB, 3084 KB/s, 61 seconds passed
-... 27%, 190528 KB, 3085 KB/s, 61 seconds passed
-... 27%, 190560 KB, 3085 KB/s, 61 seconds passed
-... 27%, 190592 KB, 3086 KB/s, 61 seconds passed
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+... 24%, 170912 KB, 3665 KB/s, 46 seconds passed
+... 24%, 170944 KB, 3665 KB/s, 46 seconds passed
+... 24%, 170976 KB, 3664 KB/s, 46 seconds passed
+... 24%, 171008 KB, 3665 KB/s, 46 seconds passed
+... 24%, 171040 KB, 3665 KB/s, 46 seconds passed
+... 24%, 171072 KB, 3665 KB/s, 46 seconds passed
 
 .. parsed-literal::
 
-    ... 27%, 190624 KB, 3085 KB/s, 61 seconds passed
-... 27%, 190656 KB, 3085 KB/s, 61 seconds passed
-... 27%, 190688 KB, 3086 KB/s, 61 seconds passed
-... 27%, 190720 KB, 3086 KB/s, 61 seconds passed
-... 27%, 190752 KB, 3085 KB/s, 61 seconds passed
-... 27%, 190784 KB, 3085 KB/s, 61 seconds passed
-... 27%, 190816 KB, 3086 KB/s, 61 seconds passed
+    ... 24%, 171104 KB, 3665 KB/s, 46 seconds passed
+... 24%, 171136 KB, 3665 KB/s, 46 seconds passed
+... 24%, 171168 KB, 3665 KB/s, 46 seconds passed
+... 24%, 171200 KB, 3665 KB/s, 46 seconds passed
+... 24%, 171232 KB, 3665 KB/s, 46 seconds passed
 
 .. parsed-literal::
 
-    ... 27%, 190848 KB, 3086 KB/s, 61 seconds passed
-... 27%, 190880 KB, 3086 KB/s, 61 seconds passed
-... 27%, 190912 KB, 3086 KB/s, 61 seconds passed
-... 27%, 190944 KB, 3086 KB/s, 61 seconds passed
-... 27%, 190976 KB, 3087 KB/s, 61 seconds passed
+    ... 24%, 171264 KB, 3665 KB/s, 46 seconds passed
+... 24%, 171296 KB, 3665 KB/s, 46 seconds passed
+... 24%, 171328 KB, 3666 KB/s, 46 seconds passed
+... 24%, 171360 KB, 3665 KB/s, 46 seconds passed
+... 24%, 171392 KB, 3665 KB/s, 46 seconds passed
+... 24%, 171424 KB, 3665 KB/s, 46 seconds passed
+... 24%, 171456 KB, 3666 KB/s, 46 seconds passed
 
 .. parsed-literal::
 
-    ... 27%, 191008 KB, 3086 KB/s, 61 seconds passed
-... 27%, 191040 KB, 3086 KB/s, 61 seconds passed
-... 27%, 191072 KB, 3087 KB/s, 61 seconds passed
-... 27%, 191104 KB, 3087 KB/s, 61 seconds passed
-... 27%, 191136 KB, 3086 KB/s, 61 seconds passed
-... 27%, 191168 KB, 3087 KB/s, 61 seconds passed
+    ... 24%, 171488 KB, 3665 KB/s, 46 seconds passed
+... 24%, 171520 KB, 3665 KB/s, 46 seconds passed
+... 24%, 171552 KB, 3665 KB/s, 46 seconds passed
+... 24%, 171584 KB, 3666 KB/s, 46 seconds passed
 
 .. parsed-literal::
 
-    ... 27%, 191200 KB, 3087 KB/s, 61 seconds passed
-... 27%, 191232 KB, 3087 KB/s, 61 seconds passed
-... 27%, 191264 KB, 3087 KB/s, 61 seconds passed
-... 27%, 191296 KB, 3087 KB/s, 61 seconds passed
-... 27%, 191328 KB, 3087 KB/s, 61 seconds passed
-... 27%, 191360 KB, 3088 KB/s, 61 seconds passed
+    ... 24%, 171616 KB, 3665 KB/s, 46 seconds passed
+... 24%, 171648 KB, 3665 KB/s, 46 seconds passed
+... 24%, 171680 KB, 3665 KB/s, 46 seconds passed
+... 24%, 171712 KB, 3666 KB/s, 46 seconds passed
+... 24%, 171744 KB, 3665 KB/s, 46 seconds passed
+... 24%, 171776 KB, 3665 KB/s, 46 seconds passed
+... 24%, 171808 KB, 3665 KB/s, 46 seconds passed
 
 .. parsed-literal::
 
-    ... 27%, 191392 KB, 3087 KB/s, 61 seconds passed
-... 27%, 191424 KB, 3087 KB/s, 61 seconds passed
-... 27%, 191456 KB, 3088 KB/s, 61 seconds passed
-... 27%, 191488 KB, 3088 KB/s, 62 seconds passed
-... 27%, 191520 KB, 3087 KB/s, 62 seconds passed
-... 27%, 191552 KB, 3088 KB/s, 62 seconds passed
+    ... 24%, 171840 KB, 3665 KB/s, 46 seconds passed
+... 24%, 171872 KB, 3665 KB/s, 46 seconds passed
+... 24%, 171904 KB, 3665 KB/s, 46 seconds passed
 
 .. parsed-literal::
 
-    ... 27%, 191584 KB, 3088 KB/s, 62 seconds passed
-... 27%, 191616 KB, 3088 KB/s, 62 seconds passed
-... 27%, 191648 KB, 3088 KB/s, 62 seconds passed
-... 27%, 191680 KB, 3088 KB/s, 62 seconds passed
-... 27%, 191712 KB, 3088 KB/s, 62 seconds passed
-... 27%, 191744 KB, 3089 KB/s, 62 seconds passed
+    ... 24%, 171936 KB, 3663 KB/s, 46 seconds passed
+... 24%, 171968 KB, 3663 KB/s, 46 seconds passed
+... 24%, 172000 KB, 3664 KB/s, 46 seconds passed
+... 24%, 172032 KB, 3665 KB/s, 46 seconds passed
+... 24%, 172064 KB, 3663 KB/s, 46 seconds passed
 
 .. parsed-literal::
 
-    ... 27%, 191776 KB, 3088 KB/s, 62 seconds passed
-... 27%, 191808 KB, 3088 KB/s, 62 seconds passed
-... 27%, 191840 KB, 3089 KB/s, 62 seconds passed
-... 27%, 191872 KB, 3089 KB/s, 62 seconds passed
-... 27%, 191904 KB, 3088 KB/s, 62 seconds passed
+    ... 24%, 172096 KB, 3661 KB/s, 47 seconds passed
+... 24%, 172128 KB, 3661 KB/s, 47 seconds passed
+... 24%, 172160 KB, 3662 KB/s, 47 seconds passed
+... 24%, 172192 KB, 3663 KB/s, 47 seconds passed
 
 .. parsed-literal::
 
-    ... 27%, 191936 KB, 3089 KB/s, 62 seconds passed
-... 27%, 191968 KB, 3089 KB/s, 62 seconds passed
-... 27%, 192000 KB, 3089 KB/s, 62 seconds passed
-... 27%, 192032 KB, 3089 KB/s, 62 seconds passed
-... 27%, 192064 KB, 3089 KB/s, 62 seconds passed
-... 27%, 192096 KB, 3089 KB/s, 62 seconds passed
-... 27%, 192128 KB, 3090 KB/s, 62 seconds passed
+    ... 24%, 172224 KB, 3661 KB/s, 47 seconds passed
+... 24%, 172256 KB, 3661 KB/s, 47 seconds passed
+... 24%, 172288 KB, 3662 KB/s, 47 seconds passed
+... 24%, 172320 KB, 3663 KB/s, 47 seconds passed
+... 24%, 172352 KB, 3661 KB/s, 47 seconds passed
+... 24%, 172384 KB, 3661 KB/s, 47 seconds passed
+... 24%, 172416 KB, 3662 KB/s, 47 seconds passed
 
 .. parsed-literal::
 
-    ... 27%, 192160 KB, 3089 KB/s, 62 seconds passed
-... 27%, 192192 KB, 3089 KB/s, 62 seconds passed
-... 27%, 192224 KB, 3090 KB/s, 62 seconds passed
-... 27%, 192256 KB, 3090 KB/s, 62 seconds passed
-... 27%, 192288 KB, 3089 KB/s, 62 seconds passed
+    ... 24%, 172448 KB, 3657 KB/s, 47 seconds passed
+... 24%, 172480 KB, 3658 KB/s, 47 seconds passed
+... 24%, 172512 KB, 3659 KB/s, 47 seconds passed
+... 24%, 172544 KB, 3659 KB/s, 47 seconds passed
+... 24%, 172576 KB, 3657 KB/s, 47 seconds passed
+... 24%, 172608 KB, 3658 KB/s, 47 seconds passed
 
 .. parsed-literal::
 
-    ... 27%, 192320 KB, 3090 KB/s, 62 seconds passed
-... 27%, 192352 KB, 3090 KB/s, 62 seconds passed
-... 27%, 192384 KB, 3090 KB/s, 62 seconds passed
-... 27%, 192416 KB, 3090 KB/s, 62 seconds passed
-... 27%, 192448 KB, 3090 KB/s, 62 seconds passed
-... 27%, 192480 KB, 3090 KB/s, 62 seconds passed
-... 27%, 192512 KB, 3091 KB/s, 62 seconds passed
+    ... 24%, 172640 KB, 3656 KB/s, 47 seconds passed
+... 24%, 172672 KB, 3657 KB/s, 47 seconds passed
+... 24%, 172704 KB, 3657 KB/s, 47 seconds passed
 
 .. parsed-literal::
 
-    ... 27%, 192544 KB, 3090 KB/s, 62 seconds passed
-... 27%, 192576 KB, 3090 KB/s, 62 seconds passed
-... 27%, 192608 KB, 3091 KB/s, 62 seconds passed
-... 27%, 192640 KB, 3091 KB/s, 62 seconds passed
-... 27%, 192672 KB, 3090 KB/s, 62 seconds passed
+    ... 24%, 172736 KB, 3655 KB/s, 47 seconds passed
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+... 24%, 172800 KB, 3657 KB/s, 47 seconds passed
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+... 24%, 172864 KB, 3656 KB/s, 47 seconds passed
+... 24%, 172896 KB, 3656 KB/s, 47 seconds passed
+... 24%, 172928 KB, 3657 KB/s, 47 seconds passed
+... 24%, 172960 KB, 3657 KB/s, 47 seconds passed
 
 .. parsed-literal::
 
-    ... 27%, 192704 KB, 3091 KB/s, 62 seconds passed
-... 27%, 192736 KB, 3091 KB/s, 62 seconds passed
-... 27%, 192768 KB, 3091 KB/s, 62 seconds passed
-... 27%, 192800 KB, 3091 KB/s, 62 seconds passed
-... 27%, 192832 KB, 3091 KB/s, 62 seconds passed
-... 27%, 192864 KB, 3091 KB/s, 62 seconds passed
-... 27%, 192896 KB, 3092 KB/s, 62 seconds passed
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+... 24%, 173056 KB, 3657 KB/s, 47 seconds passed
+... 24%, 173088 KB, 3657 KB/s, 47 seconds passed
 
 .. parsed-literal::
 
-    ... 27%, 192928 KB, 3091 KB/s, 62 seconds passed
-... 27%, 192960 KB, 3091 KB/s, 62 seconds passed
-... 27%, 192992 KB, 3092 KB/s, 62 seconds passed
-... 27%, 193024 KB, 3092 KB/s, 62 seconds passed
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+... 24%, 173280 KB, 3656 KB/s, 47 seconds passed
+... 24%, 173312 KB, 3657 KB/s, 47 seconds passed
+... 24%, 173344 KB, 3657 KB/s, 47 seconds passed
 
 .. parsed-literal::
 
-    ... 27%, 193056 KB, 3091 KB/s, 62 seconds passed
-... 27%, 193088 KB, 3092 KB/s, 62 seconds passed
-... 27%, 193120 KB, 3092 KB/s, 62 seconds passed
-... 27%, 193152 KB, 3092 KB/s, 62 seconds passed
-... 27%, 193184 KB, 3092 KB/s, 62 seconds passed
-... 27%, 193216 KB, 3092 KB/s, 62 seconds passed
-... 27%, 193248 KB, 3092 KB/s, 62 seconds passed
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+... 24%, 173440 KB, 3657 KB/s, 47 seconds passed
+... 24%, 173472 KB, 3657 KB/s, 47 seconds passed
 
 .. parsed-literal::
 
-    ... 27%, 193280 KB, 3092 KB/s, 62 seconds passed
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-... 27%, 193344 KB, 3092 KB/s, 62 seconds passed
-... 27%, 193376 KB, 3093 KB/s, 62 seconds passed
-... 27%, 193408 KB, 3092 KB/s, 62 seconds passed
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+... 24%, 173632 KB, 3656 KB/s, 47 seconds passed
+... 24%, 173664 KB, 3656 KB/s, 47 seconds passed
+... 24%, 173696 KB, 3657 KB/s, 47 seconds passed
 
 .. parsed-literal::
 
-    ... 27%, 193440 KB, 3092 KB/s, 62 seconds passed
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-... 27%, 193504 KB, 3093 KB/s, 62 seconds passed
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-... 27%, 193568 KB, 3093 KB/s, 62 seconds passed
-... 27%, 193600 KB, 3093 KB/s, 62 seconds passed
-... 27%, 193632 KB, 3093 KB/s, 62 seconds passed
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+... 24%, 173792 KB, 3656 KB/s, 47 seconds passed
+... 24%, 173824 KB, 3657 KB/s, 47 seconds passed
+... 24%, 173856 KB, 3658 KB/s, 47 seconds passed
 
 .. parsed-literal::
 
-    ... 27%, 193664 KB, 3093 KB/s, 62 seconds passed
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-... 27%, 193728 KB, 3093 KB/s, 62 seconds passed
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-... 27%, 193792 KB, 3093 KB/s, 62 seconds passed
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+... 25%, 173984 KB, 3658 KB/s, 47 seconds passed
+... 25%, 174016 KB, 3656 KB/s, 47 seconds passed
 
 .. parsed-literal::
 
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-... 27%, 193984 KB, 3094 KB/s, 62 seconds passed
-... 27%, 194016 KB, 3094 KB/s, 62 seconds passed
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+... 25%, 174176 KB, 3656 KB/s, 47 seconds passed
+... 25%, 174208 KB, 3657 KB/s, 47 seconds passed
+... 25%, 174240 KB, 3658 KB/s, 47 seconds passed
 
 .. parsed-literal::
 
-    ... 27%, 194048 KB, 3094 KB/s, 62 seconds passed
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-... 27%, 194112 KB, 3094 KB/s, 62 seconds passed
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+... 25%, 174336 KB, 3657 KB/s, 47 seconds passed
+... 25%, 174368 KB, 3658 KB/s, 47 seconds passed
+... 25%, 174400 KB, 3656 KB/s, 47 seconds passed
 
 .. parsed-literal::
 
-    ... 27%, 194208 KB, 3094 KB/s, 62 seconds passed
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-... 27%, 194336 KB, 3095 KB/s, 62 seconds passed
-... 27%, 194368 KB, 3095 KB/s, 62 seconds passed
-... 27%, 194400 KB, 3095 KB/s, 62 seconds passed
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+... 25%, 174560 KB, 3657 KB/s, 47 seconds passed
+... 25%, 174592 KB, 3657 KB/s, 47 seconds passed
+... 25%, 174624 KB, 3658 KB/s, 47 seconds passed
 
 .. parsed-literal::
 
-    ... 27%, 194432 KB, 3095 KB/s, 62 seconds passed
-... 27%, 194464 KB, 3095 KB/s, 62 seconds passed
-... 27%, 194496 KB, 3095 KB/s, 62 seconds passed
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 .. parsed-literal::
 
-    ... 27%, 194560 KB, 3095 KB/s, 62 seconds passed
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+... 25%, 174976 KB, 3657 KB/s, 47 seconds passed
+... 25%, 175008 KB, 3658 KB/s, 47 seconds passed
 
 .. parsed-literal::
 
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-... 28%, 194880 KB, 3096 KB/s, 62 seconds passed
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 .. parsed-literal::
 
-    ... 28%, 194944 KB, 3096 KB/s, 62 seconds passed
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-... 28%, 195104 KB, 3097 KB/s, 62 seconds passed
-... 28%, 195136 KB, 3097 KB/s, 62 seconds passed
-... 28%, 195168 KB, 3097 KB/s, 63 seconds passed
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+... 25%, 175296 KB, 3656 KB/s, 47 seconds passed
+... 25%, 175328 KB, 3657 KB/s, 47 seconds passed
+... 25%, 175360 KB, 3657 KB/s, 47 seconds passed
 
 .. parsed-literal::
 
-    ... 28%, 195200 KB, 3097 KB/s, 63 seconds passed
-... 28%, 195232 KB, 3097 KB/s, 63 seconds passed
-... 28%, 195264 KB, 3097 KB/s, 63 seconds passed
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 .. parsed-literal::
 
-    ... 28%, 195328 KB, 3097 KB/s, 63 seconds passed
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-... 28%, 195488 KB, 3098 KB/s, 63 seconds passed
-... 28%, 195520 KB, 3098 KB/s, 63 seconds passed
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+    ... 25%, 175520 KB, 3656 KB/s, 48 seconds passed
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+... 25%, 175744 KB, 3657 KB/s, 48 seconds passed
+... 25%, 175776 KB, 3658 KB/s, 48 seconds passed
 
 .. parsed-literal::
 
-    ... 28%, 195584 KB, 3098 KB/s, 63 seconds passed
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-... 28%, 195648 KB, 3098 KB/s, 63 seconds passed
-... 28%, 195680 KB, 3099 KB/s, 63 seconds passed
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+... 25%, 175872 KB, 3657 KB/s, 48 seconds passed
+... 25%, 175904 KB, 3658 KB/s, 48 seconds passed
 
 .. parsed-literal::
 
-    ... 28%, 195712 KB, 3098 KB/s, 63 seconds passed
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-... 28%, 195872 KB, 3099 KB/s, 63 seconds passed
-... 28%, 195904 KB, 3099 KB/s, 63 seconds passed
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+    ... 25%, 175936 KB, 3656 KB/s, 48 seconds passed
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+... 25%, 176064 KB, 3656 KB/s, 48 seconds passed
+... 25%, 176096 KB, 3657 KB/s, 48 seconds passed
+... 25%, 176128 KB, 3657 KB/s, 48 seconds passed
 
 .. parsed-literal::
 
-    ... 28%, 195968 KB, 3099 KB/s, 63 seconds passed
-... 28%, 196000 KB, 3099 KB/s, 63 seconds passed
-... 28%, 196032 KB, 3099 KB/s, 63 seconds passed
-... 28%, 196064 KB, 3100 KB/s, 63 seconds passed
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+... 25%, 176224 KB, 3657 KB/s, 48 seconds passed
+... 25%, 176256 KB, 3658 KB/s, 48 seconds passed
 
 .. parsed-literal::
 
-    ... 28%, 196096 KB, 3099 KB/s, 63 seconds passed
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-... 28%, 196224 KB, 3099 KB/s, 63 seconds passed
-... 28%, 196256 KB, 3100 KB/s, 63 seconds passed
-... 28%, 196288 KB, 3100 KB/s, 63 seconds passed
+    ... 25%, 176288 KB, 3656 KB/s, 48 seconds passed
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+... 25%, 176448 KB, 3657 KB/s, 48 seconds passed
+... 25%, 176480 KB, 3657 KB/s, 48 seconds passed
+... 25%, 176512 KB, 3658 KB/s, 48 seconds passed
 
 .. parsed-literal::
 
-    ... 28%, 196320 KB, 3100 KB/s, 63 seconds passed
-... 28%, 196352 KB, 3100 KB/s, 63 seconds passed
-... 28%, 196384 KB, 3100 KB/s, 63 seconds passed
-... 28%, 196416 KB, 3100 KB/s, 63 seconds passed
-... 28%, 196448 KB, 3101 KB/s, 63 seconds passed
+    ... 25%, 176544 KB, 3656 KB/s, 48 seconds passed
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+... 25%, 176608 KB, 3657 KB/s, 48 seconds passed
+... 25%, 176640 KB, 3658 KB/s, 48 seconds passed
 
 .. parsed-literal::
 
-    ... 28%, 196480 KB, 3100 KB/s, 63 seconds passed
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-... 28%, 196576 KB, 3101 KB/s, 63 seconds passed
-... 28%, 196608 KB, 3100 KB/s, 63 seconds passed
-... 28%, 196640 KB, 3100 KB/s, 63 seconds passed
-... 28%, 196672 KB, 3101 KB/s, 63 seconds passed
+    ... 25%, 176672 KB, 3656 KB/s, 48 seconds passed
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+... 25%, 176800 KB, 3656 KB/s, 48 seconds passed
+... 25%, 176832 KB, 3657 KB/s, 48 seconds passed
+... 25%, 176864 KB, 3657 KB/s, 48 seconds passed
+... 25%, 176896 KB, 3658 KB/s, 48 seconds passed
 
 .. parsed-literal::
 
-    ... 28%, 196704 KB, 3101 KB/s, 63 seconds passed
-... 28%, 196736 KB, 3101 KB/s, 63 seconds passed
-... 28%, 196768 KB, 3101 KB/s, 63 seconds passed
-... 28%, 196800 KB, 3101 KB/s, 63 seconds passed
-... 28%, 196832 KB, 3102 KB/s, 63 seconds passed
+    ... 25%, 176928 KB, 3656 KB/s, 48 seconds passed
+... 25%, 176960 KB, 3657 KB/s, 48 seconds passed
+... 25%, 176992 KB, 3657 KB/s, 48 seconds passed
+... 25%, 177024 KB, 3658 KB/s, 48 seconds passed
 
 .. parsed-literal::
 
-    ... 28%, 196864 KB, 3101 KB/s, 63 seconds passed
-... 28%, 196896 KB, 3101 KB/s, 63 seconds passed
-... 28%, 196928 KB, 3102 KB/s, 63 seconds passed
-... 28%, 196960 KB, 3102 KB/s, 63 seconds passed
-... 28%, 196992 KB, 3101 KB/s, 63 seconds passed
-... 28%, 197024 KB, 3101 KB/s, 63 seconds passed
-... 28%, 197056 KB, 3102 KB/s, 63 seconds passed
+    ... 25%, 177056 KB, 3656 KB/s, 48 seconds passed
+... 25%, 177088 KB, 3657 KB/s, 48 seconds passed
+... 25%, 177120 KB, 3657 KB/s, 48 seconds passed
+... 25%, 177152 KB, 3658 KB/s, 48 seconds passed
+... 25%, 177184 KB, 3656 KB/s, 48 seconds passed
+... 25%, 177216 KB, 3657 KB/s, 48 seconds passed
+... 25%, 177248 KB, 3657 KB/s, 48 seconds passed
+... 25%, 177280 KB, 3658 KB/s, 48 seconds passed
 
 .. parsed-literal::
 
-    ... 28%, 197088 KB, 3102 KB/s, 63 seconds passed
-... 28%, 197120 KB, 3102 KB/s, 63 seconds passed
-... 28%, 197152 KB, 3102 KB/s, 63 seconds passed
-... 28%, 197184 KB, 3102 KB/s, 63 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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+... 27%, 190240 KB, 3655 KB/s, 52 seconds passed
+... 27%, 190272 KB, 3655 KB/s, 52 seconds passed
+... 27%, 190304 KB, 3655 KB/s, 52 seconds passed
 
 .. parsed-literal::
 
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-... 30%, 210400 KB, 3133 KB/s, 67 seconds passed
-... 30%, 210432 KB, 3133 KB/s, 67 seconds passed
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+... 27%, 190400 KB, 3655 KB/s, 52 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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-... 30%, 210976 KB, 3134 KB/s, 67 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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-... 30%, 211520 KB, 3135 KB/s, 67 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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+... 27%, 192192 KB, 3655 KB/s, 52 seconds passed
 
 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 31%, 216128 KB, 3145 KB/s, 68 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 31%, 216512 KB, 3146 KB/s, 68 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 34%, 241696 KB, 3195 KB/s, 75 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 34%, 242080 KB, 3196 KB/s, 75 seconds passed
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 .. parsed-literal::
 
-    ... 34%, 242272 KB, 3196 KB/s, 75 seconds passed
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 .. parsed-literal::
 
-    ... 34%, 242464 KB, 3197 KB/s, 75 seconds passed
-... 34%, 242496 KB, 3197 KB/s, 75 seconds passed
-... 34%, 242528 KB, 3197 KB/s, 75 seconds passed
-... 34%, 242560 KB, 3197 KB/s, 75 seconds passed
-... 34%, 242592 KB, 3197 KB/s, 75 seconds passed
-... 34%, 242624 KB, 3197 KB/s, 75 seconds passed
+    ... 31%, 222432 KB, 3659 KB/s, 60 seconds passed
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+... 31%, 222528 KB, 3659 KB/s, 60 seconds passed
+... 31%, 222560 KB, 3659 KB/s, 60 seconds passed
+... 32%, 222592 KB, 3659 KB/s, 60 seconds passed
 
 .. parsed-literal::
 
-    ... 34%, 242656 KB, 3197 KB/s, 75 seconds passed
-... 34%, 242688 KB, 3197 KB/s, 75 seconds passed
-... 34%, 242720 KB, 3197 KB/s, 75 seconds passed
-... 34%, 242752 KB, 3197 KB/s, 75 seconds passed
-... 34%, 242784 KB, 3197 KB/s, 75 seconds passed
-... 34%, 242816 KB, 3197 KB/s, 75 seconds passed
+    ... 32%, 222624 KB, 3659 KB/s, 60 seconds passed
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+... 32%, 222720 KB, 3659 KB/s, 60 seconds passed
+... 32%, 222752 KB, 3659 KB/s, 60 seconds passed
+... 32%, 222784 KB, 3659 KB/s, 60 seconds passed
 
 .. parsed-literal::
 
-    ... 34%, 242848 KB, 3197 KB/s, 75 seconds passed
-... 34%, 242880 KB, 3198 KB/s, 75 seconds passed
-... 34%, 242912 KB, 3197 KB/s, 75 seconds passed
-... 34%, 242944 KB, 3198 KB/s, 75 seconds passed
-... 34%, 242976 KB, 3198 KB/s, 75 seconds passed
-... 34%, 243008 KB, 3198 KB/s, 75 seconds passed
+    ... 32%, 222816 KB, 3659 KB/s, 60 seconds passed
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+... 32%, 222912 KB, 3659 KB/s, 60 seconds passed
+... 32%, 222944 KB, 3660 KB/s, 60 seconds passed
+... 32%, 222976 KB, 3660 KB/s, 60 seconds passed
 
 .. parsed-literal::
 
-    ... 34%, 243040 KB, 3198 KB/s, 75 seconds passed
-... 34%, 243072 KB, 3198 KB/s, 76 seconds passed
-... 34%, 243104 KB, 3198 KB/s, 76 seconds passed
-... 34%, 243136 KB, 3198 KB/s, 76 seconds passed
-... 34%, 243168 KB, 3198 KB/s, 76 seconds passed
+    ... 32%, 223008 KB, 3659 KB/s, 60 seconds passed
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+... 32%, 223072 KB, 3660 KB/s, 60 seconds passed
+... 32%, 223104 KB, 3660 KB/s, 60 seconds passed
+... 32%, 223136 KB, 3659 KB/s, 60 seconds passed
+... 32%, 223168 KB, 3659 KB/s, 60 seconds passed
 
 .. parsed-literal::
 
-    ... 34%, 243200 KB, 3198 KB/s, 76 seconds passed
-... 34%, 243232 KB, 3198 KB/s, 76 seconds passed
-... 34%, 243264 KB, 3198 KB/s, 76 seconds passed
-... 34%, 243296 KB, 3198 KB/s, 76 seconds passed
-... 34%, 243328 KB, 3198 KB/s, 76 seconds passed
-... 34%, 243360 KB, 3198 KB/s, 76 seconds passed
-... 34%, 243392 KB, 3198 KB/s, 76 seconds passed
+    ... 32%, 223200 KB, 3660 KB/s, 60 seconds passed
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+... 32%, 223296 KB, 3659 KB/s, 61 seconds passed
+... 32%, 223328 KB, 3660 KB/s, 61 seconds passed
+... 32%, 223360 KB, 3660 KB/s, 61 seconds passed
 
 .. parsed-literal::
 
-    ... 34%, 243424 KB, 3198 KB/s, 76 seconds passed
-... 35%, 243456 KB, 3198 KB/s, 76 seconds passed
-... 35%, 243488 KB, 3199 KB/s, 76 seconds passed
-... 35%, 243520 KB, 3199 KB/s, 76 seconds passed
-... 35%, 243552 KB, 3199 KB/s, 76 seconds passed
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+... 32%, 223488 KB, 3660 KB/s, 61 seconds passed
+... 32%, 223520 KB, 3659 KB/s, 61 seconds passed
+... 32%, 223552 KB, 3659 KB/s, 61 seconds passed
 
 .. parsed-literal::
 
-    ... 35%, 243584 KB, 3199 KB/s, 76 seconds passed
-... 35%, 243616 KB, 3199 KB/s, 76 seconds passed
-... 35%, 243648 KB, 3199 KB/s, 76 seconds passed
-... 35%, 243680 KB, 3199 KB/s, 76 seconds passed
-... 35%, 243712 KB, 3199 KB/s, 76 seconds passed
-... 35%, 243744 KB, 3199 KB/s, 76 seconds passed
-... 35%, 243776 KB, 3199 KB/s, 76 seconds passed
+    ... 32%, 223584 KB, 3660 KB/s, 61 seconds passed
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+... 32%, 223680 KB, 3659 KB/s, 61 seconds passed
+... 32%, 223712 KB, 3660 KB/s, 61 seconds passed
+... 32%, 223744 KB, 3660 KB/s, 61 seconds passed
 
 .. parsed-literal::
 
-    ... 35%, 243808 KB, 3199 KB/s, 76 seconds passed
-... 35%, 243840 KB, 3199 KB/s, 76 seconds passed
-... 35%, 243872 KB, 3199 KB/s, 76 seconds passed
-... 35%, 243904 KB, 3199 KB/s, 76 seconds passed
-... 35%, 243936 KB, 3199 KB/s, 76 seconds passed
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+... 32%, 223872 KB, 3660 KB/s, 61 seconds passed
+... 32%, 223904 KB, 3660 KB/s, 61 seconds passed
+... 32%, 223936 KB, 3660 KB/s, 61 seconds passed
 
 .. parsed-literal::
 
-    ... 35%, 243968 KB, 3199 KB/s, 76 seconds passed
-... 35%, 244000 KB, 3199 KB/s, 76 seconds passed
-... 35%, 244032 KB, 3200 KB/s, 76 seconds passed
-... 35%, 244064 KB, 3199 KB/s, 76 seconds passed
-... 35%, 244096 KB, 3200 KB/s, 76 seconds passed
-... 35%, 244128 KB, 3200 KB/s, 76 seconds passed
+    ... 32%, 223968 KB, 3660 KB/s, 61 seconds passed
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+... 32%, 224064 KB, 3660 KB/s, 61 seconds passed
+... 32%, 224096 KB, 3660 KB/s, 61 seconds passed
+... 32%, 224128 KB, 3660 KB/s, 61 seconds passed
 
 .. parsed-literal::
 
-    ... 35%, 244160 KB, 3200 KB/s, 76 seconds passed
-... 35%, 244192 KB, 3200 KB/s, 76 seconds passed
-... 35%, 244224 KB, 3200 KB/s, 76 seconds passed
-... 35%, 244256 KB, 3200 KB/s, 76 seconds passed
-... 35%, 244288 KB, 3200 KB/s, 76 seconds passed
-... 35%, 244320 KB, 3200 KB/s, 76 seconds passed
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+... 32%, 224224 KB, 3660 KB/s, 61 seconds passed
+... 32%, 224256 KB, 3660 KB/s, 61 seconds passed
+... 32%, 224288 KB, 3660 KB/s, 61 seconds passed
 
 .. parsed-literal::
 
-    ... 35%, 244352 KB, 3200 KB/s, 76 seconds passed
-... 35%, 244384 KB, 3200 KB/s, 76 seconds passed
-... 35%, 244416 KB, 3200 KB/s, 76 seconds passed
-... 35%, 244448 KB, 3200 KB/s, 76 seconds passed
-... 35%, 244480 KB, 3200 KB/s, 76 seconds passed
-... 35%, 244512 KB, 3200 KB/s, 76 seconds passed
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+... 32%, 224448 KB, 3660 KB/s, 61 seconds passed
+... 32%, 224480 KB, 3660 KB/s, 61 seconds passed
+... 32%, 224512 KB, 3660 KB/s, 61 seconds passed
 
 .. parsed-literal::
 
-    ... 35%, 244544 KB, 3200 KB/s, 76 seconds passed
-... 35%, 244576 KB, 3200 KB/s, 76 seconds passed
-... 35%, 244608 KB, 3200 KB/s, 76 seconds passed
-... 35%, 244640 KB, 3201 KB/s, 76 seconds passed
-... 35%, 244672 KB, 3201 KB/s, 76 seconds passed
-... 35%, 244704 KB, 3201 KB/s, 76 seconds passed
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+... 32%, 224608 KB, 3660 KB/s, 61 seconds passed
+... 32%, 224640 KB, 3660 KB/s, 61 seconds passed
+... 32%, 224672 KB, 3660 KB/s, 61 seconds passed
 
 .. parsed-literal::
 
-    ... 35%, 244736 KB, 3201 KB/s, 76 seconds passed
-... 35%, 244768 KB, 3201 KB/s, 76 seconds passed
-... 35%, 244800 KB, 3201 KB/s, 76 seconds passed
-... 35%, 244832 KB, 3201 KB/s, 76 seconds passed
-... 35%, 244864 KB, 3201 KB/s, 76 seconds passed
-... 35%, 244896 KB, 3201 KB/s, 76 seconds passed
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+... 32%, 224832 KB, 3660 KB/s, 61 seconds passed
+... 32%, 224864 KB, 3660 KB/s, 61 seconds passed
+... 32%, 224896 KB, 3660 KB/s, 61 seconds passed
 
 .. parsed-literal::
 
-    ... 35%, 244928 KB, 3201 KB/s, 76 seconds passed
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-... 35%, 245088 KB, 3201 KB/s, 76 seconds passed
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+... 32%, 225056 KB, 3660 KB/s, 61 seconds passed
 
 .. parsed-literal::
 
-    ... 35%, 245120 KB, 3201 KB/s, 76 seconds passed
-... 35%, 245152 KB, 3201 KB/s, 76 seconds passed
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-... 35%, 245216 KB, 3201 KB/s, 76 seconds passed
-... 35%, 245248 KB, 3202 KB/s, 76 seconds passed
-... 35%, 245280 KB, 3202 KB/s, 76 seconds passed
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+... 32%, 225216 KB, 3660 KB/s, 61 seconds passed
+... 32%, 225248 KB, 3660 KB/s, 61 seconds passed
+... 32%, 225280 KB, 3660 KB/s, 61 seconds passed
 
 .. parsed-literal::
 
-    ... 35%, 245312 KB, 3202 KB/s, 76 seconds passed
-... 35%, 245344 KB, 3202 KB/s, 76 seconds passed
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-... 35%, 245408 KB, 3202 KB/s, 76 seconds passed
-... 35%, 245440 KB, 3202 KB/s, 76 seconds passed
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+... 32%, 225408 KB, 3660 KB/s, 61 seconds passed
+... 32%, 225440 KB, 3660 KB/s, 61 seconds passed
 
 .. parsed-literal::
 
-    ... 35%, 245472 KB, 3202 KB/s, 76 seconds passed
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-... 35%, 245600 KB, 3202 KB/s, 76 seconds passed
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+    ... 32%, 225472 KB, 3660 KB/s, 61 seconds passed
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+... 32%, 225600 KB, 3660 KB/s, 61 seconds passed
+... 32%, 225632 KB, 3660 KB/s, 61 seconds passed
 
 .. parsed-literal::
 
-    ... 35%, 245696 KB, 3202 KB/s, 76 seconds passed
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 .. parsed-literal::
 
-    ... 35%, 245856 KB, 3203 KB/s, 76 seconds passed
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 .. parsed-literal::
 
-    ... 35%, 246080 KB, 3203 KB/s, 76 seconds passed
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 .. parsed-literal::
 
-    ... 35%, 246240 KB, 3203 KB/s, 76 seconds passed
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 .. parsed-literal::
 
-    ... 35%, 246432 KB, 3203 KB/s, 76 seconds passed
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 .. parsed-literal::
 
-    ... 35%, 246592 KB, 3204 KB/s, 76 seconds passed
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 .. parsed-literal::
 
-    ... 35%, 246816 KB, 3204 KB/s, 77 seconds passed
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 .. parsed-literal::
 
-    ... 35%, 246976 KB, 3204 KB/s, 77 seconds passed
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 .. parsed-literal::
 
-    ... 35%, 247200 KB, 3205 KB/s, 77 seconds passed
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 .. parsed-literal::
 
-    ... 35%, 247360 KB, 3205 KB/s, 77 seconds passed
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 .. parsed-literal::
 
-    ... 35%, 247552 KB, 3206 KB/s, 77 seconds passed
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 .. parsed-literal::
 
-    ... 35%, 247744 KB, 3206 KB/s, 77 seconds passed
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 .. parsed-literal::
 
-    ... 35%, 247936 KB, 3206 KB/s, 77 seconds passed
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+... 32%, 228064 KB, 3660 KB/s, 62 seconds passed
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 .. parsed-literal::
 
-    ... 35%, 248128 KB, 3206 KB/s, 77 seconds passed
-... 35%, 248160 KB, 3206 KB/s, 77 seconds passed
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-... 35%, 248256 KB, 3207 KB/s, 77 seconds passed
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+... 32%, 228256 KB, 3660 KB/s, 62 seconds passed
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 .. parsed-literal::
 
-    ... 35%, 248320 KB, 3207 KB/s, 77 seconds passed
-... 35%, 248352 KB, 3207 KB/s, 77 seconds passed
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-... 35%, 248480 KB, 3207 KB/s, 77 seconds passed
+    ... 32%, 228320 KB, 3660 KB/s, 62 seconds passed
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 .. parsed-literal::
 
-    ... 35%, 248512 KB, 3207 KB/s, 77 seconds passed
-... 35%, 248544 KB, 3207 KB/s, 77 seconds passed
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-... 35%, 248608 KB, 3207 KB/s, 77 seconds passed
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-... 35%, 248672 KB, 3207 KB/s, 77 seconds passed
+    ... 32%, 228512 KB, 3660 KB/s, 62 seconds passed
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+... 32%, 228640 KB, 3660 KB/s, 62 seconds passed
+... 32%, 228672 KB, 3660 KB/s, 62 seconds passed
 
 .. parsed-literal::
 
-    ... 35%, 248704 KB, 3208 KB/s, 77 seconds passed
-... 35%, 248736 KB, 3207 KB/s, 77 seconds passed
-... 35%, 248768 KB, 3207 KB/s, 77 seconds passed
-... 35%, 248800 KB, 3208 KB/s, 77 seconds passed
-... 35%, 248832 KB, 3208 KB/s, 77 seconds passed
+    ... 32%, 228704 KB, 3661 KB/s, 62 seconds passed
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+... 32%, 228768 KB, 3660 KB/s, 62 seconds passed
+... 32%, 228800 KB, 3660 KB/s, 62 seconds passed
+... 32%, 228832 KB, 3660 KB/s, 62 seconds passed
 
 .. parsed-literal::
 
-    ... 35%, 248864 KB, 3208 KB/s, 77 seconds passed
-... 35%, 248896 KB, 3208 KB/s, 77 seconds passed
-... 35%, 248928 KB, 3208 KB/s, 77 seconds passed
-... 35%, 248960 KB, 3208 KB/s, 77 seconds passed
-... 35%, 248992 KB, 3208 KB/s, 77 seconds passed
-... 35%, 249024 KB, 3208 KB/s, 77 seconds passed
+    ... 32%, 228864 KB, 3660 KB/s, 62 seconds passed
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+... 32%, 228960 KB, 3661 KB/s, 62 seconds passed
+... 32%, 228992 KB, 3660 KB/s, 62 seconds passed
+... 32%, 229024 KB, 3660 KB/s, 62 seconds passed
 
 .. parsed-literal::
 
-    ... 35%, 249056 KB, 3208 KB/s, 77 seconds passed
-... 35%, 249088 KB, 3208 KB/s, 77 seconds passed
-... 35%, 249120 KB, 3208 KB/s, 77 seconds passed
-... 35%, 249152 KB, 3208 KB/s, 77 seconds passed
-... 35%, 249184 KB, 3208 KB/s, 77 seconds passed
-... 35%, 249216 KB, 3208 KB/s, 77 seconds passed
+    ... 32%, 229056 KB, 3660 KB/s, 62 seconds passed
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+... 32%, 229152 KB, 3660 KB/s, 62 seconds passed
+... 32%, 229184 KB, 3660 KB/s, 62 seconds passed
+... 32%, 229216 KB, 3660 KB/s, 62 seconds passed
 
 .. parsed-literal::
 
-    ... 35%, 249248 KB, 3208 KB/s, 77 seconds passed
-... 35%, 249280 KB, 3208 KB/s, 77 seconds passed
-... 35%, 249312 KB, 3208 KB/s, 77 seconds passed
-... 35%, 249344 KB, 3209 KB/s, 77 seconds passed
-... 35%, 249376 KB, 3209 KB/s, 77 seconds passed
-... 35%, 249408 KB, 3209 KB/s, 77 seconds passed
+    ... 32%, 229248 KB, 3660 KB/s, 62 seconds passed
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+... 32%, 229344 KB, 3660 KB/s, 62 seconds passed
+... 32%, 229376 KB, 3660 KB/s, 62 seconds passed
+... 32%, 229408 KB, 3660 KB/s, 62 seconds passed
 
 .. parsed-literal::
 
-    ... 35%, 249440 KB, 3209 KB/s, 77 seconds passed
-... 35%, 249472 KB, 3209 KB/s, 77 seconds passed
-... 35%, 249504 KB, 3209 KB/s, 77 seconds passed
-... 35%, 249536 KB, 3209 KB/s, 77 seconds passed
-... 35%, 249568 KB, 3209 KB/s, 77 seconds passed
-... 35%, 249600 KB, 3209 KB/s, 77 seconds passed
+    ... 32%, 229440 KB, 3660 KB/s, 62 seconds passed
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+... 33%, 229536 KB, 3660 KB/s, 62 seconds passed
+... 33%, 229568 KB, 3660 KB/s, 62 seconds passed
+... 33%, 229600 KB, 3660 KB/s, 62 seconds passed
 
 .. parsed-literal::
 
-    ... 35%, 249632 KB, 3209 KB/s, 77 seconds passed
-... 35%, 249664 KB, 3209 KB/s, 77 seconds passed
-... 35%, 249696 KB, 3209 KB/s, 77 seconds passed
-... 35%, 249728 KB, 3209 KB/s, 77 seconds passed
-... 35%, 249760 KB, 3209 KB/s, 77 seconds passed
-... 35%, 249792 KB, 3209 KB/s, 77 seconds passed
+    ... 33%, 229632 KB, 3660 KB/s, 62 seconds passed
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+... 33%, 229728 KB, 3660 KB/s, 62 seconds passed
+... 33%, 229760 KB, 3660 KB/s, 62 seconds passed
+... 33%, 229792 KB, 3660 KB/s, 62 seconds passed
 
 .. parsed-literal::
 
-    ... 35%, 249824 KB, 3209 KB/s, 77 seconds passed
-... 35%, 249856 KB, 3210 KB/s, 77 seconds passed
-... 35%, 249888 KB, 3209 KB/s, 77 seconds passed
-... 35%, 249920 KB, 3209 KB/s, 77 seconds passed
-... 35%, 249952 KB, 3210 KB/s, 77 seconds passed
-... 35%, 249984 KB, 3210 KB/s, 77 seconds passed
+    ... 33%, 229824 KB, 3660 KB/s, 62 seconds passed
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+... 33%, 229920 KB, 3660 KB/s, 62 seconds passed
+... 33%, 229952 KB, 3660 KB/s, 62 seconds passed
+... 33%, 229984 KB, 3660 KB/s, 62 seconds passed
 
 .. parsed-literal::
 
-    ... 35%, 250016 KB, 3210 KB/s, 77 seconds passed
-... 35%, 250048 KB, 3210 KB/s, 77 seconds passed
-... 35%, 250080 KB, 3210 KB/s, 77 seconds passed
-... 35%, 250112 KB, 3210 KB/s, 77 seconds passed
-... 35%, 250144 KB, 3210 KB/s, 77 seconds passed
-... 35%, 250176 KB, 3210 KB/s, 77 seconds passed
+    ... 33%, 230016 KB, 3660 KB/s, 62 seconds passed
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+... 33%, 230112 KB, 3660 KB/s, 62 seconds passed
+... 33%, 230144 KB, 3660 KB/s, 62 seconds passed
+... 33%, 230176 KB, 3660 KB/s, 62 seconds passed
 
 .. parsed-literal::
 
-    ... 35%, 250208 KB, 3210 KB/s, 77 seconds passed
-... 35%, 250240 KB, 3210 KB/s, 77 seconds passed
-... 35%, 250272 KB, 3210 KB/s, 77 seconds passed
-... 35%, 250304 KB, 3210 KB/s, 77 seconds passed
-... 35%, 250336 KB, 3210 KB/s, 77 seconds passed
-... 35%, 250368 KB, 3210 KB/s, 77 seconds passed
+    ... 33%, 230208 KB, 3661 KB/s, 62 seconds passed
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+... 33%, 230272 KB, 3660 KB/s, 62 seconds passed
+... 33%, 230304 KB, 3660 KB/s, 62 seconds passed
+... 33%, 230336 KB, 3661 KB/s, 62 seconds passed
 
 .. parsed-literal::
 
-    ... 36%, 250400 KB, 3210 KB/s, 77 seconds passed
-... 36%, 250432 KB, 3210 KB/s, 77 seconds passed
-... 36%, 250464 KB, 3210 KB/s, 78 seconds passed
-... 36%, 250496 KB, 3211 KB/s, 78 seconds passed
-... 36%, 250528 KB, 3211 KB/s, 78 seconds passed
-... 36%, 250560 KB, 3211 KB/s, 78 seconds passed
+    ... 33%, 230368 KB, 3660 KB/s, 62 seconds passed
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+... 33%, 230464 KB, 3661 KB/s, 62 seconds passed
+... 33%, 230496 KB, 3660 KB/s, 62 seconds passed
+... 33%, 230528 KB, 3660 KB/s, 62 seconds passed
 
 .. parsed-literal::
 
-    ... 36%, 250592 KB, 3211 KB/s, 78 seconds passed
-... 36%, 250624 KB, 3211 KB/s, 78 seconds passed
-... 36%, 250656 KB, 3211 KB/s, 78 seconds passed
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-... 36%, 250720 KB, 3211 KB/s, 78 seconds passed
-... 36%, 250752 KB, 3211 KB/s, 78 seconds passed
+    ... 33%, 230560 KB, 3660 KB/s, 62 seconds passed
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+... 33%, 230656 KB, 3660 KB/s, 63 seconds passed
+... 33%, 230688 KB, 3660 KB/s, 63 seconds passed
+... 33%, 230720 KB, 3661 KB/s, 63 seconds passed
 
 .. parsed-literal::
 
-    ... 36%, 250784 KB, 3211 KB/s, 78 seconds passed
-... 36%, 250816 KB, 3211 KB/s, 78 seconds passed
-... 36%, 250848 KB, 3211 KB/s, 78 seconds passed
-... 36%, 250880 KB, 3211 KB/s, 78 seconds passed
-... 36%, 250912 KB, 3211 KB/s, 78 seconds passed
+    ... 33%, 230752 KB, 3660 KB/s, 63 seconds passed
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+... 33%, 230848 KB, 3661 KB/s, 63 seconds passed
+... 33%, 230880 KB, 3660 KB/s, 63 seconds passed
+... 33%, 230912 KB, 3661 KB/s, 63 seconds passed
 
 .. parsed-literal::
 
-    ... 36%, 250944 KB, 3211 KB/s, 78 seconds passed
-... 36%, 250976 KB, 3211 KB/s, 78 seconds passed
-... 36%, 251008 KB, 3211 KB/s, 78 seconds passed
-... 36%, 251040 KB, 3211 KB/s, 78 seconds passed
-... 36%, 251072 KB, 3211 KB/s, 78 seconds passed
-... 36%, 251104 KB, 3212 KB/s, 78 seconds passed
-... 36%, 251136 KB, 3212 KB/s, 78 seconds passed
+    ... 33%, 230944 KB, 3660 KB/s, 63 seconds passed
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+... 33%, 231072 KB, 3660 KB/s, 63 seconds passed
+... 33%, 231104 KB, 3661 KB/s, 63 seconds passed
 
 .. parsed-literal::
 
-    ... 36%, 251168 KB, 3212 KB/s, 78 seconds passed
-... 36%, 251200 KB, 3212 KB/s, 78 seconds passed
-... 36%, 251232 KB, 3212 KB/s, 78 seconds passed
-... 36%, 251264 KB, 3212 KB/s, 78 seconds passed
-... 36%, 251296 KB, 3212 KB/s, 78 seconds passed
+    ... 33%, 231136 KB, 3660 KB/s, 63 seconds passed
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+... 33%, 231232 KB, 3661 KB/s, 63 seconds passed
+... 33%, 231264 KB, 3660 KB/s, 63 seconds passed
+... 33%, 231296 KB, 3661 KB/s, 63 seconds passed
 
 .. parsed-literal::
 
-    ... 36%, 251328 KB, 3212 KB/s, 78 seconds passed
-... 36%, 251360 KB, 3212 KB/s, 78 seconds passed
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-... 36%, 251424 KB, 3212 KB/s, 78 seconds passed
-... 36%, 251456 KB, 3212 KB/s, 78 seconds passed
-... 36%, 251488 KB, 3212 KB/s, 78 seconds passed
+    ... 33%, 231328 KB, 3661 KB/s, 63 seconds passed
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+... 33%, 231456 KB, 3661 KB/s, 63 seconds passed
+... 33%, 231488 KB, 3661 KB/s, 63 seconds passed
 
 .. parsed-literal::
 
-    ... 36%, 251520 KB, 3212 KB/s, 78 seconds passed
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-... 36%, 251616 KB, 3212 KB/s, 78 seconds passed
-... 36%, 251648 KB, 3212 KB/s, 78 seconds passed
-... 36%, 251680 KB, 3212 KB/s, 78 seconds passed
+    ... 33%, 231520 KB, 3660 KB/s, 63 seconds passed
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+... 33%, 231648 KB, 3660 KB/s, 63 seconds passed
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 .. parsed-literal::
 
-    ... 36%, 251712 KB, 3212 KB/s, 78 seconds passed
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-... 36%, 251840 KB, 3213 KB/s, 78 seconds passed
-... 36%, 251872 KB, 3213 KB/s, 78 seconds passed
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+... 33%, 231840 KB, 3661 KB/s, 63 seconds passed
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 .. parsed-literal::
 
-    ... 36%, 251904 KB, 3213 KB/s, 78 seconds passed
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 .. parsed-literal::
 
-    ... 36%, 252096 KB, 3213 KB/s, 78 seconds passed
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 .. parsed-literal::
 
-    ... 36%, 252288 KB, 3213 KB/s, 78 seconds passed
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 .. parsed-literal::
 
-    ... 36%, 252480 KB, 3214 KB/s, 78 seconds passed
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 .. parsed-literal::
 
-    ... 36%, 252672 KB, 3214 KB/s, 78 seconds passed
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 .. parsed-literal::
 
-    ... 36%, 252832 KB, 3214 KB/s, 78 seconds passed
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 .. parsed-literal::
 
-    ... 36%, 253056 KB, 3215 KB/s, 78 seconds passed
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 .. parsed-literal::
 
-    ... 36%, 253216 KB, 3215 KB/s, 78 seconds passed
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 .. parsed-literal::
 
-    ... 36%, 253440 KB, 3215 KB/s, 78 seconds passed
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 .. parsed-literal::
 
-    ... 36%, 253600 KB, 3216 KB/s, 78 seconds passed
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 .. parsed-literal::
 
-    ... 36%, 253792 KB, 3216 KB/s, 78 seconds passed
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 .. parsed-literal::
 
-    ... 36%, 253984 KB, 3216 KB/s, 78 seconds passed
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 .. parsed-literal::
 
-    ... 36%, 254144 KB, 3216 KB/s, 79 seconds passed
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-... 36%, 254304 KB, 3217 KB/s, 79 seconds passed
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+... 33%, 234304 KB, 3661 KB/s, 63 seconds passed
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 .. parsed-literal::
 
-    ... 36%, 254368 KB, 3217 KB/s, 79 seconds passed
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 .. parsed-literal::
 
-    ... 36%, 254528 KB, 3217 KB/s, 79 seconds passed
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+    ... 33%, 234560 KB, 3661 KB/s, 64 seconds passed
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+... 33%, 234720 KB, 3661 KB/s, 64 seconds passed
 
 .. parsed-literal::
 
-    ... 36%, 254752 KB, 3217 KB/s, 79 seconds passed
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+... 33%, 234880 KB, 3661 KB/s, 64 seconds passed
+... 33%, 234912 KB, 3661 KB/s, 64 seconds passed
 
 .. parsed-literal::
 
-    ... 36%, 254912 KB, 3218 KB/s, 79 seconds passed
-... 36%, 254944 KB, 3218 KB/s, 79 seconds passed
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-... 36%, 255008 KB, 3218 KB/s, 79 seconds passed
-... 36%, 255040 KB, 3218 KB/s, 79 seconds passed
-... 36%, 255072 KB, 3218 KB/s, 79 seconds passed
+    ... 33%, 234944 KB, 3661 KB/s, 64 seconds passed
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+... 33%, 235072 KB, 3661 KB/s, 64 seconds passed
+... 33%, 235104 KB, 3661 KB/s, 64 seconds passed
 
 .. parsed-literal::
 
-    ... 36%, 255104 KB, 3218 KB/s, 79 seconds passed
-... 36%, 255136 KB, 3218 KB/s, 79 seconds passed
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-... 36%, 255200 KB, 3218 KB/s, 79 seconds passed
-... 36%, 255232 KB, 3218 KB/s, 79 seconds passed
-... 36%, 255264 KB, 3218 KB/s, 79 seconds passed
+    ... 33%, 235136 KB, 3661 KB/s, 64 seconds passed
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+... 33%, 235200 KB, 3661 KB/s, 64 seconds passed
+... 33%, 235232 KB, 3661 KB/s, 64 seconds passed
+... 33%, 235264 KB, 3661 KB/s, 64 seconds passed
+... 33%, 235296 KB, 3661 KB/s, 64 seconds passed
 
 .. parsed-literal::
 
-    ... 36%, 255296 KB, 3218 KB/s, 79 seconds passed
-... 36%, 255328 KB, 3219 KB/s, 79 seconds passed
-... 36%, 255360 KB, 3218 KB/s, 79 seconds passed
-... 36%, 255392 KB, 3218 KB/s, 79 seconds passed
-... 36%, 255424 KB, 3218 KB/s, 79 seconds passed
-... 36%, 255456 KB, 3219 KB/s, 79 seconds passed
+    ... 33%, 235328 KB, 3661 KB/s, 64 seconds passed
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+... 33%, 235392 KB, 3661 KB/s, 64 seconds passed
+... 33%, 235424 KB, 3661 KB/s, 64 seconds passed
+... 33%, 235456 KB, 3661 KB/s, 64 seconds passed
 
 .. parsed-literal::
 
-    ... 36%, 255488 KB, 3219 KB/s, 79 seconds passed
-... 36%, 255520 KB, 3219 KB/s, 79 seconds passed
-... 36%, 255552 KB, 3219 KB/s, 79 seconds passed
-... 36%, 255584 KB, 3219 KB/s, 79 seconds passed
-... 36%, 255616 KB, 3219 KB/s, 79 seconds passed
-... 36%, 255648 KB, 3219 KB/s, 79 seconds passed
+    ... 33%, 235488 KB, 3661 KB/s, 64 seconds passed
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+... 33%, 235616 KB, 3661 KB/s, 64 seconds passed
+... 33%, 235648 KB, 3661 KB/s, 64 seconds passed
+... 33%, 235680 KB, 3661 KB/s, 64 seconds passed
 
 .. parsed-literal::
 
-    ... 36%, 255680 KB, 3219 KB/s, 79 seconds passed
-... 36%, 255712 KB, 3219 KB/s, 79 seconds passed
-... 36%, 255744 KB, 3219 KB/s, 79 seconds passed
-... 36%, 255776 KB, 3219 KB/s, 79 seconds passed
-... 36%, 255808 KB, 3219 KB/s, 79 seconds passed
-... 36%, 255840 KB, 3219 KB/s, 79 seconds passed
+    ... 33%, 235712 KB, 3661 KB/s, 64 seconds passed
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+... 33%, 235776 KB, 3661 KB/s, 64 seconds passed
+... 33%, 235808 KB, 3661 KB/s, 64 seconds passed
+... 33%, 235840 KB, 3661 KB/s, 64 seconds passed
 
 .. parsed-literal::
 
-    ... 36%, 255872 KB, 3219 KB/s, 79 seconds passed
-... 36%, 255904 KB, 3219 KB/s, 79 seconds passed
-... 36%, 255936 KB, 3219 KB/s, 79 seconds passed
-... 36%, 255968 KB, 3220 KB/s, 79 seconds passed
-... 36%, 256000 KB, 3219 KB/s, 79 seconds passed
-... 36%, 256032 KB, 3219 KB/s, 79 seconds passed
+    ... 33%, 235872 KB, 3661 KB/s, 64 seconds passed
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+... 33%, 236000 KB, 3661 KB/s, 64 seconds passed
+... 33%, 236032 KB, 3661 KB/s, 64 seconds passed
+... 33%, 236064 KB, 3661 KB/s, 64 seconds passed
 
 .. parsed-literal::
 
-    ... 36%, 256064 KB, 3219 KB/s, 79 seconds passed
-... 36%, 256096 KB, 3220 KB/s, 79 seconds passed
-... 36%, 256128 KB, 3220 KB/s, 79 seconds passed
-... 36%, 256160 KB, 3220 KB/s, 79 seconds passed
-... 36%, 256192 KB, 3220 KB/s, 79 seconds passed
-... 36%, 256224 KB, 3220 KB/s, 79 seconds passed
+    ... 33%, 236096 KB, 3661 KB/s, 64 seconds passed
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+... 33%, 236160 KB, 3661 KB/s, 64 seconds passed
+... 33%, 236192 KB, 3661 KB/s, 64 seconds passed
+... 33%, 236224 KB, 3661 KB/s, 64 seconds passed
 
 .. parsed-literal::
 
-    ... 36%, 256256 KB, 3220 KB/s, 79 seconds passed
-... 36%, 256288 KB, 3220 KB/s, 79 seconds passed
-... 36%, 256320 KB, 3220 KB/s, 79 seconds passed
-... 36%, 256352 KB, 3220 KB/s, 79 seconds passed
-... 36%, 256384 KB, 3220 KB/s, 79 seconds passed
-... 36%, 256416 KB, 3220 KB/s, 79 seconds passed
+    ... 33%, 236256 KB, 3661 KB/s, 64 seconds passed
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+... 33%, 236352 KB, 3661 KB/s, 64 seconds passed
+... 33%, 236384 KB, 3661 KB/s, 64 seconds passed
+... 33%, 236416 KB, 3661 KB/s, 64 seconds passed
 
 .. parsed-literal::
 
-    ... 36%, 256448 KB, 3220 KB/s, 79 seconds passed
-... 36%, 256480 KB, 3220 KB/s, 79 seconds passed
-... 36%, 256512 KB, 3220 KB/s, 79 seconds passed
-... 36%, 256544 KB, 3220 KB/s, 79 seconds passed
-... 36%, 256576 KB, 3220 KB/s, 79 seconds passed
-... 36%, 256608 KB, 3221 KB/s, 79 seconds passed
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+... 34%, 236576 KB, 3661 KB/s, 64 seconds passed
+... 34%, 236608 KB, 3661 KB/s, 64 seconds passed
 
 .. parsed-literal::
 
-    ... 36%, 256640 KB, 3220 KB/s, 79 seconds passed
-... 36%, 256672 KB, 3221 KB/s, 79 seconds passed
-... 36%, 256704 KB, 3220 KB/s, 79 seconds passed
-... 36%, 256736 KB, 3221 KB/s, 79 seconds passed
-... 36%, 256768 KB, 3221 KB/s, 79 seconds passed
-... 36%, 256800 KB, 3221 KB/s, 79 seconds passed
+    ... 34%, 236640 KB, 3661 KB/s, 64 seconds passed
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+... 34%, 236768 KB, 3661 KB/s, 64 seconds passed
+... 34%, 236800 KB, 3661 KB/s, 64 seconds passed
 
 .. parsed-literal::
 
-    ... 36%, 256832 KB, 3221 KB/s, 79 seconds passed
-... 36%, 256864 KB, 3221 KB/s, 79 seconds passed
-... 36%, 256896 KB, 3221 KB/s, 79 seconds passed
-... 36%, 256928 KB, 3221 KB/s, 79 seconds passed
-... 36%, 256960 KB, 3221 KB/s, 79 seconds passed
-... 36%, 256992 KB, 3221 KB/s, 79 seconds passed
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+... 34%, 236960 KB, 3661 KB/s, 64 seconds passed
 
 .. parsed-literal::
 
-    ... 36%, 257024 KB, 3221 KB/s, 79 seconds passed
-... 36%, 257056 KB, 3221 KB/s, 79 seconds passed
-... 36%, 257088 KB, 3221 KB/s, 79 seconds passed
-... 36%, 257120 KB, 3221 KB/s, 79 seconds passed
-... 36%, 257152 KB, 3221 KB/s, 79 seconds passed
-... 36%, 257184 KB, 3221 KB/s, 79 seconds passed
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+... 34%, 237120 KB, 3661 KB/s, 64 seconds passed
+... 34%, 237152 KB, 3661 KB/s, 64 seconds passed
+... 34%, 237184 KB, 3661 KB/s, 64 seconds passed
 
 .. parsed-literal::
 
-    ... 36%, 257216 KB, 3221 KB/s, 79 seconds passed
-... 36%, 257248 KB, 3222 KB/s, 79 seconds passed
-... 36%, 257280 KB, 3222 KB/s, 79 seconds passed
-... 36%, 257312 KB, 3221 KB/s, 79 seconds passed
-... 37%, 257344 KB, 3222 KB/s, 79 seconds passed
-... 37%, 257376 KB, 3222 KB/s, 79 seconds passed
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+... 34%, 237312 KB, 3661 KB/s, 64 seconds passed
+... 34%, 237344 KB, 3661 KB/s, 64 seconds passed
 
 .. parsed-literal::
 
-    ... 37%, 257408 KB, 3222 KB/s, 79 seconds passed
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-... 37%, 257472 KB, 3222 KB/s, 79 seconds passed
-... 37%, 257504 KB, 3222 KB/s, 79 seconds passed
-... 37%, 257536 KB, 3222 KB/s, 79 seconds passed
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+... 34%, 237536 KB, 3661 KB/s, 64 seconds passed
+... 34%, 237568 KB, 3661 KB/s, 64 seconds passed
 
 .. parsed-literal::
 
-    ... 37%, 257568 KB, 3222 KB/s, 79 seconds passed
-... 37%, 257600 KB, 3222 KB/s, 79 seconds passed
-... 37%, 257632 KB, 3222 KB/s, 79 seconds passed
-... 37%, 257664 KB, 3222 KB/s, 79 seconds passed
-... 37%, 257696 KB, 3222 KB/s, 79 seconds passed
-... 37%, 257728 KB, 3222 KB/s, 79 seconds passed
-... 37%, 257760 KB, 3222 KB/s, 79 seconds passed
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+... 34%, 237696 KB, 3661 KB/s, 64 seconds passed
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 .. parsed-literal::
 
-    ... 37%, 257792 KB, 3222 KB/s, 79 seconds passed
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-... 37%, 257920 KB, 3223 KB/s, 80 seconds passed
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 .. parsed-literal::
 
-    ... 37%, 257952 KB, 3222 KB/s, 80 seconds passed
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 .. parsed-literal::
 
-    ... 37%, 258144 KB, 3223 KB/s, 80 seconds passed
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-... 37%, 258304 KB, 3223 KB/s, 80 seconds passed
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 .. parsed-literal::
 
-    ... 37%, 258336 KB, 3223 KB/s, 80 seconds passed
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 .. parsed-literal::
 
-    ... 37%, 258528 KB, 3224 KB/s, 80 seconds passed
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 .. parsed-literal::
 
-    ... 37%, 258720 KB, 3224 KB/s, 80 seconds passed
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 .. parsed-literal::
 
-    ... 37%, 258912 KB, 3224 KB/s, 80 seconds passed
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 .. parsed-literal::
 
-    ... 37%, 259104 KB, 3224 KB/s, 80 seconds passed
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 .. parsed-literal::
 
-    ... 37%, 259264 KB, 3225 KB/s, 80 seconds passed
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 .. parsed-literal::
 
-    ... 37%, 259456 KB, 3225 KB/s, 80 seconds passed
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 .. parsed-literal::
 
-    ... 37%, 259648 KB, 3225 KB/s, 80 seconds passed
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 .. parsed-literal::
 
-    ... 37%, 259840 KB, 3226 KB/s, 80 seconds passed
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 .. parsed-literal::
 
-    ... 37%, 260032 KB, 3226 KB/s, 80 seconds passed
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 .. parsed-literal::
 
-    ... 37%, 260224 KB, 3226 KB/s, 80 seconds passed
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 .. parsed-literal::
 
-    ... 37%, 260416 KB, 3226 KB/s, 80 seconds passed
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+... 34%, 240576 KB, 3662 KB/s, 65 seconds passed
 
 .. parsed-literal::
 
-    ... 37%, 260608 KB, 3227 KB/s, 80 seconds passed
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 .. parsed-literal::
 
-    ... 37%, 260768 KB, 3227 KB/s, 80 seconds passed
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 .. parsed-literal::
 
-    ... 37%, 260992 KB, 3227 KB/s, 80 seconds passed
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 .. parsed-literal::
 
-    ... 37%, 261152 KB, 3227 KB/s, 80 seconds passed
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-... 37%, 261248 KB, 3228 KB/s, 80 seconds passed
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-... 37%, 261344 KB, 3228 KB/s, 80 seconds passed
+    ... 34%, 241184 KB, 3662 KB/s, 65 seconds passed
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+... 34%, 241344 KB, 3662 KB/s, 65 seconds passed
 
 .. parsed-literal::
 
-    ... 37%, 261376 KB, 3228 KB/s, 80 seconds passed
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-... 37%, 261440 KB, 3228 KB/s, 80 seconds passed
-... 37%, 261472 KB, 3228 KB/s, 80 seconds passed
-... 37%, 261504 KB, 3228 KB/s, 80 seconds passed
+    ... 34%, 241376 KB, 3662 KB/s, 65 seconds passed
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+... 34%, 241504 KB, 3662 KB/s, 65 seconds passed
+... 34%, 241536 KB, 3662 KB/s, 65 seconds passed
 
 .. parsed-literal::
 
-    ... 37%, 261536 KB, 3228 KB/s, 81 seconds passed
-... 37%, 261568 KB, 3228 KB/s, 81 seconds passed
-... 37%, 261600 KB, 3228 KB/s, 81 seconds passed
-... 37%, 261632 KB, 3228 KB/s, 81 seconds passed
-... 37%, 261664 KB, 3228 KB/s, 81 seconds passed
-... 37%, 261696 KB, 3228 KB/s, 81 seconds passed
-... 37%, 261728 KB, 3229 KB/s, 81 seconds passed
+    ... 34%, 241568 KB, 3662 KB/s, 65 seconds passed
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+... 34%, 241632 KB, 3662 KB/s, 65 seconds passed
+... 34%, 241664 KB, 3662 KB/s, 65 seconds passed
+... 34%, 241696 KB, 3662 KB/s, 65 seconds passed
+... 34%, 241728 KB, 3662 KB/s, 66 seconds passed
 
 .. parsed-literal::
 
-    ... 37%, 261760 KB, 3229 KB/s, 81 seconds passed
-... 37%, 261792 KB, 3228 KB/s, 81 seconds passed
-... 37%, 261824 KB, 3229 KB/s, 81 seconds passed
-... 37%, 261856 KB, 3229 KB/s, 81 seconds passed
-... 37%, 261888 KB, 3229 KB/s, 81 seconds passed
+    ... 34%, 241760 KB, 3662 KB/s, 66 seconds passed
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+... 34%, 241856 KB, 3662 KB/s, 66 seconds passed
+... 34%, 241888 KB, 3662 KB/s, 66 seconds passed
+... 34%, 241920 KB, 3662 KB/s, 66 seconds passed
 
 .. parsed-literal::
 
-    ... 37%, 261920 KB, 3229 KB/s, 81 seconds passed
-... 37%, 261952 KB, 3229 KB/s, 81 seconds passed
-... 37%, 261984 KB, 3229 KB/s, 81 seconds passed
-... 37%, 262016 KB, 3229 KB/s, 81 seconds passed
-... 37%, 262048 KB, 3229 KB/s, 81 seconds passed
-... 37%, 262080 KB, 3229 KB/s, 81 seconds passed
-... 37%, 262112 KB, 3229 KB/s, 81 seconds passed
+    ... 34%, 241952 KB, 3662 KB/s, 66 seconds passed
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+... 34%, 242048 KB, 3662 KB/s, 66 seconds passed
+... 34%, 242080 KB, 3662 KB/s, 66 seconds passed
+... 34%, 242112 KB, 3662 KB/s, 66 seconds passed
 
 .. parsed-literal::
 
-    ... 37%, 262144 KB, 3229 KB/s, 81 seconds passed
-... 37%, 262176 KB, 3229 KB/s, 81 seconds passed
-... 37%, 262208 KB, 3229 KB/s, 81 seconds passed
-... 37%, 262240 KB, 3229 KB/s, 81 seconds passed
-... 37%, 262272 KB, 3229 KB/s, 81 seconds passed
+    ... 34%, 242144 KB, 3662 KB/s, 66 seconds passed
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+... 34%, 242208 KB, 3662 KB/s, 66 seconds passed
+... 34%, 242240 KB, 3662 KB/s, 66 seconds passed
+... 34%, 242272 KB, 3662 KB/s, 66 seconds passed
 
 .. parsed-literal::
 
-    ... 37%, 262304 KB, 3229 KB/s, 81 seconds passed
-... 37%, 262336 KB, 3229 KB/s, 81 seconds passed
-... 37%, 262368 KB, 3230 KB/s, 81 seconds passed
-... 37%, 262400 KB, 3230 KB/s, 81 seconds passed
-... 37%, 262432 KB, 3229 KB/s, 81 seconds passed
-... 37%, 262464 KB, 3230 KB/s, 81 seconds passed
-... 37%, 262496 KB, 3230 KB/s, 81 seconds passed
+    ... 34%, 242304 KB, 3662 KB/s, 66 seconds passed
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+... 34%, 242368 KB, 3662 KB/s, 66 seconds passed
+... 34%, 242400 KB, 3662 KB/s, 66 seconds passed
+... 34%, 242432 KB, 3662 KB/s, 66 seconds passed
+... 34%, 242464 KB, 3662 KB/s, 66 seconds passed
 
 .. parsed-literal::
 
-    ... 37%, 262528 KB, 3230 KB/s, 81 seconds passed
-... 37%, 262560 KB, 3230 KB/s, 81 seconds passed
-... 37%, 262592 KB, 3230 KB/s, 81 seconds passed
-... 37%, 262624 KB, 3230 KB/s, 81 seconds passed
-... 37%, 262656 KB, 3230 KB/s, 81 seconds passed
+    ... 34%, 242496 KB, 3662 KB/s, 66 seconds passed
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+... 34%, 242592 KB, 3662 KB/s, 66 seconds passed
+... 34%, 242624 KB, 3662 KB/s, 66 seconds passed
+... 34%, 242656 KB, 3662 KB/s, 66 seconds passed
 
 .. parsed-literal::
 
-    ... 37%, 262688 KB, 3230 KB/s, 81 seconds passed
-... 37%, 262720 KB, 3230 KB/s, 81 seconds passed
-... 37%, 262752 KB, 3230 KB/s, 81 seconds passed
-... 37%, 262784 KB, 3230 KB/s, 81 seconds passed
-... 37%, 262816 KB, 3230 KB/s, 81 seconds passed
-... 37%, 262848 KB, 3230 KB/s, 81 seconds passed
-... 37%, 262880 KB, 3230 KB/s, 81 seconds passed
+    ... 34%, 242688 KB, 3662 KB/s, 66 seconds passed
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+... 34%, 242784 KB, 3662 KB/s, 66 seconds passed
+... 34%, 242816 KB, 3662 KB/s, 66 seconds passed
+... 34%, 242848 KB, 3662 KB/s, 66 seconds passed
 
 .. parsed-literal::
 
-    ... 37%, 262912 KB, 3230 KB/s, 81 seconds passed
-... 37%, 262944 KB, 3230 KB/s, 81 seconds passed
-... 37%, 262976 KB, 3230 KB/s, 81 seconds passed
-... 37%, 263008 KB, 3231 KB/s, 81 seconds passed
-... 37%, 263040 KB, 3231 KB/s, 81 seconds passed
+    ... 34%, 242880 KB, 3662 KB/s, 66 seconds passed
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+... 34%, 242976 KB, 3662 KB/s, 66 seconds passed
+... 34%, 243008 KB, 3662 KB/s, 66 seconds passed
+... 34%, 243040 KB, 3662 KB/s, 66 seconds passed
 
 .. parsed-literal::
 
-    ... 37%, 263072 KB, 3230 KB/s, 81 seconds passed
-... 37%, 263104 KB, 3231 KB/s, 81 seconds passed
-... 37%, 263136 KB, 3231 KB/s, 81 seconds passed
-... 37%, 263168 KB, 3231 KB/s, 81 seconds passed
-... 37%, 263200 KB, 3231 KB/s, 81 seconds passed
-... 37%, 263232 KB, 3231 KB/s, 81 seconds passed
+    ... 34%, 243072 KB, 3662 KB/s, 66 seconds passed
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+... 34%, 243168 KB, 3662 KB/s, 66 seconds passed
+... 34%, 243200 KB, 3662 KB/s, 66 seconds passed
+... 34%, 243232 KB, 3662 KB/s, 66 seconds passed
 
 .. parsed-literal::
 
-    ... 37%, 263264 KB, 3231 KB/s, 81 seconds passed
-... 37%, 263296 KB, 3231 KB/s, 81 seconds passed
-... 37%, 263328 KB, 3231 KB/s, 81 seconds passed
-... 37%, 263360 KB, 3231 KB/s, 81 seconds passed
-... 37%, 263392 KB, 3231 KB/s, 81 seconds passed
-... 37%, 263424 KB, 3231 KB/s, 81 seconds passed
+    ... 34%, 243264 KB, 3662 KB/s, 66 seconds passed
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+... 34%, 243328 KB, 3662 KB/s, 66 seconds passed
+... 34%, 243360 KB, 3662 KB/s, 66 seconds passed
+... 34%, 243392 KB, 3662 KB/s, 66 seconds passed
+... 34%, 243424 KB, 3662 KB/s, 66 seconds passed
 
 .. parsed-literal::
 
-    ... 37%, 263456 KB, 3231 KB/s, 81 seconds passed
-... 37%, 263488 KB, 3231 KB/s, 81 seconds passed
-... 37%, 263520 KB, 3231 KB/s, 81 seconds passed
-... 37%, 263552 KB, 3231 KB/s, 81 seconds passed
-... 37%, 263584 KB, 3231 KB/s, 81 seconds passed
-... 37%, 263616 KB, 3231 KB/s, 81 seconds passed
+    ... 35%, 243456 KB, 3662 KB/s, 66 seconds passed
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+... 35%, 243520 KB, 3662 KB/s, 66 seconds passed
+... 35%, 243552 KB, 3662 KB/s, 66 seconds passed
+... 35%, 243584 KB, 3662 KB/s, 66 seconds passed
 
 .. parsed-literal::
 
-    ... 37%, 263648 KB, 3232 KB/s, 81 seconds passed
-... 37%, 263680 KB, 3231 KB/s, 81 seconds passed
-... 37%, 263712 KB, 3231 KB/s, 81 seconds passed
-... 37%, 263744 KB, 3231 KB/s, 81 seconds passed
-... 37%, 263776 KB, 3232 KB/s, 81 seconds passed
+    ... 35%, 243616 KB, 3662 KB/s, 66 seconds passed
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+... 35%, 243744 KB, 3662 KB/s, 66 seconds passed
+... 35%, 243776 KB, 3662 KB/s, 66 seconds passed
+... 35%, 243808 KB, 3662 KB/s, 66 seconds passed
 
 .. parsed-literal::
 
-    ... 37%, 263808 KB, 3231 KB/s, 81 seconds passed
-... 37%, 263840 KB, 3232 KB/s, 81 seconds passed
-... 37%, 263872 KB, 3232 KB/s, 81 seconds passed
-... 37%, 263904 KB, 3232 KB/s, 81 seconds passed
-... 37%, 263936 KB, 3232 KB/s, 81 seconds passed
-... 37%, 263968 KB, 3232 KB/s, 81 seconds passed
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+... 35%, 243904 KB, 3662 KB/s, 66 seconds passed
+... 35%, 243936 KB, 3662 KB/s, 66 seconds passed
+... 35%, 243968 KB, 3662 KB/s, 66 seconds passed
 
 .. parsed-literal::
 
-    ... 37%, 264000 KB, 3232 KB/s, 81 seconds passed
-... 37%, 264032 KB, 3232 KB/s, 81 seconds passed
-... 37%, 264064 KB, 3232 KB/s, 81 seconds passed
-... 37%, 264096 KB, 3232 KB/s, 81 seconds passed
-... 37%, 264128 KB, 3232 KB/s, 81 seconds passed
-... 37%, 264160 KB, 3232 KB/s, 81 seconds passed
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+... 35%, 244128 KB, 3662 KB/s, 66 seconds passed
+... 35%, 244160 KB, 3662 KB/s, 66 seconds passed
+... 35%, 244192 KB, 3662 KB/s, 66 seconds passed
 
 .. parsed-literal::
 
-    ... 37%, 264192 KB, 3232 KB/s, 81 seconds passed
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-... 37%, 264256 KB, 3232 KB/s, 81 seconds passed
-... 37%, 264288 KB, 3232 KB/s, 81 seconds passed
-... 38%, 264320 KB, 3232 KB/s, 81 seconds passed
-... 38%, 264352 KB, 3232 KB/s, 81 seconds passed
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+... 35%, 244288 KB, 3662 KB/s, 66 seconds passed
+... 35%, 244320 KB, 3662 KB/s, 66 seconds passed
+... 35%, 244352 KB, 3662 KB/s, 66 seconds passed
 
 .. parsed-literal::
 
-    ... 38%, 264384 KB, 3232 KB/s, 81 seconds passed
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-... 38%, 264480 KB, 3233 KB/s, 81 seconds passed
-... 38%, 264512 KB, 3233 KB/s, 81 seconds passed
-... 38%, 264544 KB, 3233 KB/s, 81 seconds passed
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+... 35%, 244512 KB, 3662 KB/s, 66 seconds passed
+... 35%, 244544 KB, 3662 KB/s, 66 seconds passed
 
 .. parsed-literal::
 
-    ... 38%, 264576 KB, 3233 KB/s, 81 seconds passed
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-... 38%, 264640 KB, 3233 KB/s, 81 seconds passed
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-... 38%, 264736 KB, 3233 KB/s, 81 seconds passed
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 .. parsed-literal::
 
-    ... 38%, 264768 KB, 3233 KB/s, 81 seconds passed
-... 38%, 264800 KB, 3233 KB/s, 81 seconds passed
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-... 38%, 264928 KB, 3233 KB/s, 81 seconds passed
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+... 35%, 244896 KB, 3662 KB/s, 66 seconds passed
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 .. parsed-literal::
 
-    ... 38%, 264960 KB, 3233 KB/s, 81 seconds passed
-... 38%, 264992 KB, 3233 KB/s, 81 seconds passed
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-... 38%, 265120 KB, 3234 KB/s, 81 seconds passed
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 .. parsed-literal::
 
-    ... 38%, 265152 KB, 3234 KB/s, 81 seconds passed
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-... 38%, 265312 KB, 3234 KB/s, 82 seconds passed
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+... 35%, 245312 KB, 3662 KB/s, 66 seconds passed
 
 .. parsed-literal::
 
-    ... 38%, 265344 KB, 3234 KB/s, 82 seconds passed
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-... 38%, 265504 KB, 3234 KB/s, 82 seconds passed
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 .. parsed-literal::
 
-    ... 38%, 265536 KB, 3234 KB/s, 82 seconds passed
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-... 38%, 265600 KB, 3234 KB/s, 82 seconds passed
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 .. parsed-literal::
 
-    ... 38%, 265728 KB, 3234 KB/s, 82 seconds passed
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 .. parsed-literal::
 
-    ... 38%, 265920 KB, 3235 KB/s, 82 seconds passed
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 .. parsed-literal::
 
-    ... 38%, 266080 KB, 3235 KB/s, 82 seconds passed
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 .. parsed-literal::
 
-    ... 38%, 266272 KB, 3235 KB/s, 82 seconds passed
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-... 38%, 266400 KB, 3235 KB/s, 82 seconds passed
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 .. parsed-literal::
 
-    ... 38%, 266464 KB, 3235 KB/s, 82 seconds passed
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-... 38%, 266624 KB, 3236 KB/s, 82 seconds passed
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+... 35%, 246560 KB, 3663 KB/s, 67 seconds passed
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 .. parsed-literal::
 
-    ... 38%, 266656 KB, 3236 KB/s, 82 seconds passed
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-... 38%, 266816 KB, 3236 KB/s, 82 seconds passed
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 .. parsed-literal::
 
-    ... 38%, 266848 KB, 3236 KB/s, 82 seconds passed
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+... 35%, 247008 KB, 3663 KB/s, 67 seconds passed
 
 .. parsed-literal::
 
-    ... 38%, 267008 KB, 3236 KB/s, 82 seconds passed
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-... 38%, 267200 KB, 3237 KB/s, 82 seconds passed
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+... 35%, 247200 KB, 3662 KB/s, 67 seconds passed
 
 .. parsed-literal::
 
-    ... 38%, 267232 KB, 3237 KB/s, 82 seconds passed
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+    ... 35%, 247232 KB, 3662 KB/s, 67 seconds passed
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+... 35%, 247328 KB, 3662 KB/s, 67 seconds passed
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+... 35%, 247392 KB, 3663 KB/s, 67 seconds passed
 
 .. parsed-literal::
 
-    ... 38%, 267392 KB, 3237 KB/s, 82 seconds passed
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-... 38%, 267520 KB, 3237 KB/s, 82 seconds passed
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-... 38%, 267584 KB, 3237 KB/s, 82 seconds passed
+    ... 35%, 247424 KB, 3662 KB/s, 67 seconds passed
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+... 35%, 247520 KB, 3663 KB/s, 67 seconds passed
+... 35%, 247552 KB, 3662 KB/s, 67 seconds passed
+... 35%, 247584 KB, 3662 KB/s, 67 seconds passed
 
 .. parsed-literal::
 
-    ... 38%, 267616 KB, 3237 KB/s, 82 seconds passed
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-... 38%, 267744 KB, 3237 KB/s, 82 seconds passed
+    ... 35%, 247616 KB, 3663 KB/s, 67 seconds passed
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+... 35%, 247712 KB, 3662 KB/s, 67 seconds passed
+... 35%, 247744 KB, 3663 KB/s, 67 seconds passed
+... 35%, 247776 KB, 3662 KB/s, 67 seconds passed
 
 .. parsed-literal::
 
-    ... 38%, 267776 KB, 3237 KB/s, 82 seconds passed
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-... 38%, 267904 KB, 3238 KB/s, 82 seconds passed
-... 38%, 267936 KB, 3238 KB/s, 82 seconds passed
-... 38%, 267968 KB, 3238 KB/s, 82 seconds passed
+    ... 35%, 247808 KB, 3662 KB/s, 67 seconds passed
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+... 35%, 247904 KB, 3662 KB/s, 67 seconds passed
+... 35%, 247936 KB, 3662 KB/s, 67 seconds passed
+... 35%, 247968 KB, 3662 KB/s, 67 seconds passed
 
 .. parsed-literal::
 
-    ... 38%, 268000 KB, 3238 KB/s, 82 seconds passed
-... 38%, 268032 KB, 3238 KB/s, 82 seconds passed
-... 38%, 268064 KB, 3238 KB/s, 82 seconds passed
-... 38%, 268096 KB, 3238 KB/s, 82 seconds passed
-... 38%, 268128 KB, 3238 KB/s, 82 seconds passed
+    ... 35%, 248000 KB, 3663 KB/s, 67 seconds passed
+... 35%, 248032 KB, 3662 KB/s, 67 seconds passed
+... 35%, 248064 KB, 3662 KB/s, 67 seconds passed
+... 35%, 248096 KB, 3662 KB/s, 67 seconds passed
+... 35%, 248128 KB, 3663 KB/s, 67 seconds passed
 
 .. parsed-literal::
 
-    ... 38%, 268160 KB, 3238 KB/s, 82 seconds passed
-... 38%, 268192 KB, 3238 KB/s, 82 seconds passed
-... 38%, 268224 KB, 3238 KB/s, 82 seconds passed
-... 38%, 268256 KB, 3238 KB/s, 82 seconds passed
-... 38%, 268288 KB, 3238 KB/s, 82 seconds passed
-... 38%, 268320 KB, 3238 KB/s, 82 seconds passed
-... 38%, 268352 KB, 3238 KB/s, 82 seconds passed
+    ... 35%, 248160 KB, 3662 KB/s, 67 seconds passed
+... 35%, 248192 KB, 3663 KB/s, 67 seconds passed
+... 35%, 248224 KB, 3663 KB/s, 67 seconds passed
+... 35%, 248256 KB, 3663 KB/s, 67 seconds passed
+... 35%, 248288 KB, 3662 KB/s, 67 seconds passed
+... 35%, 248320 KB, 3663 KB/s, 67 seconds passed
+... 35%, 248352 KB, 3663 KB/s, 67 seconds passed
 
 .. parsed-literal::
 
-    ... 38%, 268384 KB, 3238 KB/s, 82 seconds passed
-... 38%, 268416 KB, 3238 KB/s, 82 seconds passed
-... 38%, 268448 KB, 3238 KB/s, 82 seconds passed
-... 38%, 268480 KB, 3239 KB/s, 82 seconds passed
-... 38%, 268512 KB, 3238 KB/s, 82 seconds passed
+    ... 35%, 248384 KB, 3663 KB/s, 67 seconds passed
+... 35%, 248416 KB, 3662 KB/s, 67 seconds passed
+... 35%, 248448 KB, 3663 KB/s, 67 seconds passed
+... 35%, 248480 KB, 3662 KB/s, 67 seconds passed
+... 35%, 248512 KB, 3663 KB/s, 67 seconds passed
 
 .. parsed-literal::
 
-    ... 38%, 268544 KB, 3239 KB/s, 82 seconds passed
-... 38%, 268576 KB, 3239 KB/s, 82 seconds passed
-... 38%, 268608 KB, 3239 KB/s, 82 seconds passed
-... 38%, 268640 KB, 3239 KB/s, 82 seconds passed
-... 38%, 268672 KB, 3239 KB/s, 82 seconds passed
-... 38%, 268704 KB, 3239 KB/s, 82 seconds passed
+    ... 35%, 248544 KB, 3662 KB/s, 67 seconds passed
+... 35%, 248576 KB, 3663 KB/s, 67 seconds passed
+... 35%, 248608 KB, 3663 KB/s, 67 seconds passed
+... 35%, 248640 KB, 3663 KB/s, 67 seconds passed
+... 35%, 248672 KB, 3662 KB/s, 67 seconds passed
+... 35%, 248704 KB, 3663 KB/s, 67 seconds passed
 
 .. parsed-literal::
 
-    ... 38%, 268736 KB, 3239 KB/s, 82 seconds passed
-... 38%, 268768 KB, 3239 KB/s, 82 seconds passed
-... 38%, 268800 KB, 3239 KB/s, 82 seconds passed
-... 38%, 268832 KB, 3239 KB/s, 82 seconds passed
-... 38%, 268864 KB, 3239 KB/s, 82 seconds passed
-... 38%, 268896 KB, 3239 KB/s, 83 seconds passed
+    ... 35%, 248736 KB, 3663 KB/s, 67 seconds passed
+... 35%, 248768 KB, 3663 KB/s, 67 seconds passed
+... 35%, 248800 KB, 3662 KB/s, 67 seconds passed
+... 35%, 248832 KB, 3663 KB/s, 67 seconds passed
+... 35%, 248864 KB, 3663 KB/s, 67 seconds passed
+... 35%, 248896 KB, 3663 KB/s, 67 seconds passed
 
 .. parsed-literal::
 
-    ... 38%, 268928 KB, 3239 KB/s, 83 seconds passed
-... 38%, 268960 KB, 3239 KB/s, 83 seconds passed
-... 38%, 268992 KB, 3239 KB/s, 83 seconds passed
-... 38%, 269024 KB, 3239 KB/s, 83 seconds passed
-... 38%, 269056 KB, 3239 KB/s, 83 seconds passed
-... 38%, 269088 KB, 3239 KB/s, 83 seconds passed
+    ... 35%, 248928 KB, 3662 KB/s, 67 seconds passed
+... 35%, 248960 KB, 3663 KB/s, 67 seconds passed
+... 35%, 248992 KB, 3663 KB/s, 67 seconds passed
+... 35%, 249024 KB, 3663 KB/s, 67 seconds passed
+... 35%, 249056 KB, 3662 KB/s, 67 seconds passed
+... 35%, 249088 KB, 3663 KB/s, 67 seconds passed
 
 .. parsed-literal::
 
-    ... 38%, 269120 KB, 3240 KB/s, 83 seconds passed
-... 38%, 269152 KB, 3239 KB/s, 83 seconds passed
-... 38%, 269184 KB, 3239 KB/s, 83 seconds passed
-... 38%, 269216 KB, 3240 KB/s, 83 seconds passed
-... 38%, 269248 KB, 3240 KB/s, 83 seconds passed
-... 38%, 269280 KB, 3240 KB/s, 83 seconds passed
+    ... 35%, 249120 KB, 3663 KB/s, 68 seconds passed
+... 35%, 249152 KB, 3663 KB/s, 68 seconds passed
+... 35%, 249184 KB, 3662 KB/s, 68 seconds passed
+... 35%, 249216 KB, 3663 KB/s, 68 seconds passed
+... 35%, 249248 KB, 3663 KB/s, 68 seconds passed
+... 35%, 249280 KB, 3663 KB/s, 68 seconds passed
 
 .. parsed-literal::
 
-    ... 38%, 269312 KB, 3240 KB/s, 83 seconds passed
-... 38%, 269344 KB, 3240 KB/s, 83 seconds passed
-... 38%, 269376 KB, 3240 KB/s, 83 seconds passed
-... 38%, 269408 KB, 3240 KB/s, 83 seconds passed
-... 38%, 269440 KB, 3240 KB/s, 83 seconds passed
-... 38%, 269472 KB, 3240 KB/s, 83 seconds passed
+    ... 35%, 249312 KB, 3663 KB/s, 68 seconds passed
+... 35%, 249344 KB, 3663 KB/s, 68 seconds passed
+... 35%, 249376 KB, 3663 KB/s, 68 seconds passed
+... 35%, 249408 KB, 3663 KB/s, 68 seconds passed
+... 35%, 249440 KB, 3663 KB/s, 68 seconds passed
+... 35%, 249472 KB, 3663 KB/s, 68 seconds passed
 
 .. parsed-literal::
 
-    ... 38%, 269504 KB, 3240 KB/s, 83 seconds passed
-... 38%, 269536 KB, 3240 KB/s, 83 seconds passed
-... 38%, 269568 KB, 3240 KB/s, 83 seconds passed
-... 38%, 269600 KB, 3240 KB/s, 83 seconds passed
-... 38%, 269632 KB, 3240 KB/s, 83 seconds passed
+    ... 35%, 249504 KB, 3663 KB/s, 68 seconds passed
+... 35%, 249536 KB, 3663 KB/s, 68 seconds passed
+... 35%, 249568 KB, 3662 KB/s, 68 seconds passed
+... 35%, 249600 KB, 3663 KB/s, 68 seconds passed
+... 35%, 249632 KB, 3663 KB/s, 68 seconds passed
+... 35%, 249664 KB, 3663 KB/s, 68 seconds passed
 
 .. parsed-literal::
 
-    ... 38%, 269664 KB, 3240 KB/s, 83 seconds passed
-... 38%, 269696 KB, 3240 KB/s, 83 seconds passed
-... 38%, 269728 KB, 3240 KB/s, 83 seconds passed
-... 38%, 269760 KB, 3241 KB/s, 83 seconds passed
-... 38%, 269792 KB, 3240 KB/s, 83 seconds passed
-... 38%, 269824 KB, 3240 KB/s, 83 seconds passed
+    ... 35%, 249696 KB, 3663 KB/s, 68 seconds passed
+... 35%, 249728 KB, 3663 KB/s, 68 seconds passed
+... 35%, 249760 KB, 3663 KB/s, 68 seconds passed
+... 35%, 249792 KB, 3663 KB/s, 68 seconds passed
+... 35%, 249824 KB, 3663 KB/s, 68 seconds passed
+... 35%, 249856 KB, 3663 KB/s, 68 seconds passed
 
 .. parsed-literal::
 
-    ... 38%, 269856 KB, 3240 KB/s, 83 seconds passed
-... 38%, 269888 KB, 3241 KB/s, 83 seconds passed
-... 38%, 269920 KB, 3241 KB/s, 83 seconds passed
-... 38%, 269952 KB, 3241 KB/s, 83 seconds passed
-... 38%, 269984 KB, 3241 KB/s, 83 seconds passed
-... 38%, 270016 KB, 3241 KB/s, 83 seconds passed
+    ... 35%, 249888 KB, 3663 KB/s, 68 seconds passed
+... 35%, 249920 KB, 3663 KB/s, 68 seconds passed
+... 35%, 249952 KB, 3663 KB/s, 68 seconds passed
+... 35%, 249984 KB, 3663 KB/s, 68 seconds passed
+... 35%, 250016 KB, 3663 KB/s, 68 seconds passed
+... 35%, 250048 KB, 3663 KB/s, 68 seconds passed
 
 .. parsed-literal::
 
-    ... 38%, 270048 KB, 3241 KB/s, 83 seconds passed
-... 38%, 270080 KB, 3241 KB/s, 83 seconds passed
-... 38%, 270112 KB, 3241 KB/s, 83 seconds passed
-... 38%, 270144 KB, 3241 KB/s, 83 seconds passed
-... 38%, 270176 KB, 3241 KB/s, 83 seconds passed
-... 38%, 270208 KB, 3241 KB/s, 83 seconds passed
+    ... 35%, 250080 KB, 3663 KB/s, 68 seconds passed
+... 35%, 250112 KB, 3663 KB/s, 68 seconds passed
+... 35%, 250144 KB, 3663 KB/s, 68 seconds passed
+... 35%, 250176 KB, 3663 KB/s, 68 seconds passed
+... 35%, 250208 KB, 3663 KB/s, 68 seconds passed
+... 35%, 250240 KB, 3663 KB/s, 68 seconds passed
 
 .. parsed-literal::
 
-    ... 38%, 270240 KB, 3241 KB/s, 83 seconds passed
-... 38%, 270272 KB, 3241 KB/s, 83 seconds passed
-... 38%, 270304 KB, 3241 KB/s, 83 seconds passed
-... 38%, 270336 KB, 3241 KB/s, 83 seconds passed
-... 38%, 270368 KB, 3241 KB/s, 83 seconds passed
-... 38%, 270400 KB, 3241 KB/s, 83 seconds passed
+    ... 35%, 250272 KB, 3663 KB/s, 68 seconds passed
+... 35%, 250304 KB, 3663 KB/s, 68 seconds passed
+... 35%, 250336 KB, 3663 KB/s, 68 seconds passed
+... 35%, 250368 KB, 3663 KB/s, 68 seconds passed
+... 36%, 250400 KB, 3663 KB/s, 68 seconds passed
+... 36%, 250432 KB, 3663 KB/s, 68 seconds passed
 
 .. parsed-literal::
 
-    ... 38%, 270432 KB, 3241 KB/s, 83 seconds passed
-... 38%, 270464 KB, 3241 KB/s, 83 seconds passed
-... 38%, 270496 KB, 3241 KB/s, 83 seconds passed
-... 38%, 270528 KB, 3242 KB/s, 83 seconds passed
-... 38%, 270560 KB, 3241 KB/s, 83 seconds passed
-... 38%, 270592 KB, 3241 KB/s, 83 seconds passed
+    ... 36%, 250464 KB, 3663 KB/s, 68 seconds passed
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+... 36%, 250528 KB, 3663 KB/s, 68 seconds passed
+... 36%, 250560 KB, 3663 KB/s, 68 seconds passed
+... 36%, 250592 KB, 3663 KB/s, 68 seconds passed
+... 36%, 250624 KB, 3663 KB/s, 68 seconds passed
 
 .. parsed-literal::
 
-    ... 38%, 270624 KB, 3242 KB/s, 83 seconds passed
-... 38%, 270656 KB, 3242 KB/s, 83 seconds passed
-... 38%, 270688 KB, 3242 KB/s, 83 seconds passed
-... 38%, 270720 KB, 3242 KB/s, 83 seconds passed
-... 38%, 270752 KB, 3242 KB/s, 83 seconds passed
-... 38%, 270784 KB, 3242 KB/s, 83 seconds passed
+    ... 36%, 250656 KB, 3663 KB/s, 68 seconds passed
+... 36%, 250688 KB, 3663 KB/s, 68 seconds passed
+... 36%, 250720 KB, 3663 KB/s, 68 seconds passed
+... 36%, 250752 KB, 3663 KB/s, 68 seconds passed
+... 36%, 250784 KB, 3663 KB/s, 68 seconds passed
+... 36%, 250816 KB, 3663 KB/s, 68 seconds passed
 
 .. parsed-literal::
 
-    ... 38%, 270816 KB, 3242 KB/s, 83 seconds passed
-... 38%, 270848 KB, 3242 KB/s, 83 seconds passed
-... 38%, 270880 KB, 3242 KB/s, 83 seconds passed
-... 38%, 270912 KB, 3242 KB/s, 83 seconds passed
-... 38%, 270944 KB, 3242 KB/s, 83 seconds passed
-... 38%, 270976 KB, 3242 KB/s, 83 seconds passed
+    ... 36%, 250848 KB, 3663 KB/s, 68 seconds passed
+... 36%, 250880 KB, 3663 KB/s, 68 seconds passed
+... 36%, 250912 KB, 3663 KB/s, 68 seconds passed
+... 36%, 250944 KB, 3663 KB/s, 68 seconds passed
+... 36%, 250976 KB, 3663 KB/s, 68 seconds passed
 
 .. parsed-literal::
 
-    ... 38%, 271008 KB, 3242 KB/s, 83 seconds passed
-... 38%, 271040 KB, 3242 KB/s, 83 seconds passed
-... 38%, 271072 KB, 3242 KB/s, 83 seconds passed
-... 38%, 271104 KB, 3242 KB/s, 83 seconds passed
-... 38%, 271136 KB, 3242 KB/s, 83 seconds passed
-... 38%, 271168 KB, 3243 KB/s, 83 seconds passed
+    ... 36%, 251008 KB, 3663 KB/s, 68 seconds passed
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+... 36%, 251072 KB, 3663 KB/s, 68 seconds passed
+... 36%, 251104 KB, 3663 KB/s, 68 seconds passed
+... 36%, 251136 KB, 3663 KB/s, 68 seconds passed
+... 36%, 251168 KB, 3663 KB/s, 68 seconds passed
+... 36%, 251200 KB, 3663 KB/s, 68 seconds passed
 
 .. parsed-literal::
 
-    ... 38%, 271200 KB, 3242 KB/s, 83 seconds passed
-... 38%, 271232 KB, 3242 KB/s, 83 seconds passed
-... 39%, 271264 KB, 3243 KB/s, 83 seconds passed
-... 39%, 271296 KB, 3243 KB/s, 83 seconds passed
-... 39%, 271328 KB, 3242 KB/s, 83 seconds passed
-... 39%, 271360 KB, 3243 KB/s, 83 seconds passed
+    ... 36%, 251232 KB, 3663 KB/s, 68 seconds passed
+... 36%, 251264 KB, 3663 KB/s, 68 seconds passed
+... 36%, 251296 KB, 3663 KB/s, 68 seconds passed
+... 36%, 251328 KB, 3663 KB/s, 68 seconds passed
+... 36%, 251360 KB, 3663 KB/s, 68 seconds passed
 
 .. parsed-literal::
 
-    ... 39%, 271392 KB, 3243 KB/s, 83 seconds passed
-... 39%, 271424 KB, 3243 KB/s, 83 seconds passed
-... 39%, 271456 KB, 3243 KB/s, 83 seconds passed
-... 39%, 271488 KB, 3243 KB/s, 83 seconds passed
-... 39%, 271520 KB, 3243 KB/s, 83 seconds passed
-... 39%, 271552 KB, 3243 KB/s, 83 seconds passed
+    ... 36%, 251392 KB, 3663 KB/s, 68 seconds passed
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+... 36%, 251456 KB, 3663 KB/s, 68 seconds passed
+... 36%, 251488 KB, 3663 KB/s, 68 seconds passed
+... 36%, 251520 KB, 3663 KB/s, 68 seconds passed
+... 36%, 251552 KB, 3663 KB/s, 68 seconds passed
+... 36%, 251584 KB, 3663 KB/s, 68 seconds passed
 
 .. parsed-literal::
 
-    ... 39%, 271584 KB, 3243 KB/s, 83 seconds passed
-... 39%, 271616 KB, 3243 KB/s, 83 seconds passed
-... 39%, 271648 KB, 3243 KB/s, 83 seconds passed
-... 39%, 271680 KB, 3243 KB/s, 83 seconds passed
-... 39%, 271712 KB, 3243 KB/s, 83 seconds passed
+    ... 36%, 251616 KB, 3663 KB/s, 68 seconds passed
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+... 36%, 251680 KB, 3663 KB/s, 68 seconds passed
+... 36%, 251712 KB, 3663 KB/s, 68 seconds passed
+... 36%, 251744 KB, 3663 KB/s, 68 seconds passed
 
 .. parsed-literal::
 
-    ... 39%, 271744 KB, 3243 KB/s, 83 seconds passed
-... 39%, 271776 KB, 3243 KB/s, 83 seconds passed
-... 39%, 271808 KB, 3243 KB/s, 83 seconds passed
-... 39%, 271840 KB, 3243 KB/s, 83 seconds passed
-... 39%, 271872 KB, 3243 KB/s, 83 seconds passed
-... 39%, 271904 KB, 3243 KB/s, 83 seconds passed
+    ... 36%, 251776 KB, 3663 KB/s, 68 seconds passed
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+... 36%, 251840 KB, 3663 KB/s, 68 seconds passed
+... 36%, 251872 KB, 3663 KB/s, 68 seconds passed
+... 36%, 251904 KB, 3663 KB/s, 68 seconds passed
+... 36%, 251936 KB, 3663 KB/s, 68 seconds passed
 
 .. parsed-literal::
 
-    ... 39%, 271936 KB, 3243 KB/s, 83 seconds passed
-... 39%, 271968 KB, 3243 KB/s, 83 seconds passed
-... 39%, 272000 KB, 3244 KB/s, 83 seconds passed
-... 39%, 272032 KB, 3244 KB/s, 83 seconds passed
-... 39%, 272064 KB, 3244 KB/s, 83 seconds passed
-... 39%, 272096 KB, 3244 KB/s, 83 seconds passed
+    ... 36%, 251968 KB, 3663 KB/s, 68 seconds passed
+... 36%, 252000 KB, 3663 KB/s, 68 seconds passed
+... 36%, 252032 KB, 3663 KB/s, 68 seconds passed
+... 36%, 252064 KB, 3663 KB/s, 68 seconds passed
+... 36%, 252096 KB, 3663 KB/s, 68 seconds passed
+... 36%, 252128 KB, 3663 KB/s, 68 seconds passed
 
 .. parsed-literal::
 
-    ... 39%, 272128 KB, 3244 KB/s, 83 seconds passed
-... 39%, 272160 KB, 3244 KB/s, 83 seconds passed
-... 39%, 272192 KB, 3244 KB/s, 83 seconds passed
-... 39%, 272224 KB, 3244 KB/s, 83 seconds passed
-... 39%, 272256 KB, 3244 KB/s, 83 seconds passed
-... 39%, 272288 KB, 3244 KB/s, 83 seconds passed
+    ... 36%, 252160 KB, 3663 KB/s, 68 seconds passed
+... 36%, 252192 KB, 3663 KB/s, 68 seconds passed
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+... 36%, 252256 KB, 3663 KB/s, 68 seconds passed
+... 36%, 252288 KB, 3663 KB/s, 68 seconds passed
+... 36%, 252320 KB, 3663 KB/s, 68 seconds passed
 
 .. parsed-literal::
 
-    ... 39%, 272320 KB, 3244 KB/s, 83 seconds passed
-... 39%, 272352 KB, 3244 KB/s, 83 seconds passed
-... 39%, 272384 KB, 3244 KB/s, 83 seconds passed
-... 39%, 272416 KB, 3244 KB/s, 83 seconds passed
-... 39%, 272448 KB, 3244 KB/s, 83 seconds passed
-... 39%, 272480 KB, 3244 KB/s, 83 seconds passed
+    ... 36%, 252352 KB, 3663 KB/s, 68 seconds passed
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+... 36%, 252416 KB, 3663 KB/s, 68 seconds passed
+... 36%, 252448 KB, 3663 KB/s, 68 seconds passed
+... 36%, 252480 KB, 3663 KB/s, 68 seconds passed
 
 .. parsed-literal::
 
-    ... 39%, 272512 KB, 3244 KB/s, 83 seconds passed
-... 39%, 272544 KB, 3244 KB/s, 83 seconds passed
-... 39%, 272576 KB, 3244 KB/s, 84 seconds passed
-... 39%, 272608 KB, 3244 KB/s, 84 seconds passed
-... 39%, 272640 KB, 3244 KB/s, 84 seconds passed
-... 39%, 272672 KB, 3245 KB/s, 84 seconds passed
+    ... 36%, 252512 KB, 3663 KB/s, 68 seconds passed
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+... 36%, 252608 KB, 3663 KB/s, 68 seconds passed
+... 36%, 252640 KB, 3663 KB/s, 68 seconds passed
+... 36%, 252672 KB, 3663 KB/s, 68 seconds passed
+... 36%, 252704 KB, 3663 KB/s, 68 seconds passed
 
 .. parsed-literal::
 
-    ... 39%, 272704 KB, 3245 KB/s, 84 seconds passed
-... 39%, 272736 KB, 3244 KB/s, 84 seconds passed
-... 39%, 272768 KB, 3245 KB/s, 84 seconds passed
-... 39%, 272800 KB, 3245 KB/s, 84 seconds passed
-... 39%, 272832 KB, 3245 KB/s, 84 seconds passed
-... 39%, 272864 KB, 3245 KB/s, 84 seconds passed
+    ... 36%, 252736 KB, 3663 KB/s, 68 seconds passed
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+... 36%, 252800 KB, 3663 KB/s, 69 seconds passed
+... 36%, 252832 KB, 3663 KB/s, 69 seconds passed
+... 36%, 252864 KB, 3663 KB/s, 69 seconds passed
 
 .. parsed-literal::
 
-    ... 39%, 272896 KB, 3245 KB/s, 84 seconds passed
-... 39%, 272928 KB, 3245 KB/s, 84 seconds passed
-... 39%, 272960 KB, 3245 KB/s, 84 seconds passed
-... 39%, 272992 KB, 3245 KB/s, 84 seconds passed
-... 39%, 273024 KB, 3245 KB/s, 84 seconds passed
-... 39%, 273056 KB, 3245 KB/s, 84 seconds passed
+    ... 36%, 252896 KB, 3663 KB/s, 69 seconds passed
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+... 36%, 252960 KB, 3663 KB/s, 69 seconds passed
+... 36%, 252992 KB, 3663 KB/s, 69 seconds passed
+... 36%, 253024 KB, 3663 KB/s, 69 seconds passed
+... 36%, 253056 KB, 3663 KB/s, 69 seconds passed
+... 36%, 253088 KB, 3663 KB/s, 69 seconds passed
 
 .. parsed-literal::
 
-    ... 39%, 273088 KB, 3245 KB/s, 84 seconds passed
-... 39%, 273120 KB, 3245 KB/s, 84 seconds passed
-... 39%, 273152 KB, 3245 KB/s, 84 seconds passed
-... 39%, 273184 KB, 3245 KB/s, 84 seconds passed
-... 39%, 273216 KB, 3245 KB/s, 84 seconds passed
-... 39%, 273248 KB, 3245 KB/s, 84 seconds passed
+    ... 36%, 253120 KB, 3663 KB/s, 69 seconds passed
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+... 36%, 253184 KB, 3663 KB/s, 69 seconds passed
+... 36%, 253216 KB, 3663 KB/s, 69 seconds passed
+... 36%, 253248 KB, 3663 KB/s, 69 seconds passed
 
 .. parsed-literal::
 
-    ... 39%, 273280 KB, 3245 KB/s, 84 seconds passed
-... 39%, 273312 KB, 3246 KB/s, 84 seconds passed
-... 39%, 273344 KB, 3246 KB/s, 84 seconds passed
-... 39%, 273376 KB, 3245 KB/s, 84 seconds passed
-... 39%, 273408 KB, 3246 KB/s, 84 seconds passed
-... 39%, 273440 KB, 3246 KB/s, 84 seconds passed
+    ... 36%, 253280 KB, 3663 KB/s, 69 seconds passed
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+... 36%, 253344 KB, 3663 KB/s, 69 seconds passed
+... 36%, 253376 KB, 3663 KB/s, 69 seconds passed
+... 36%, 253408 KB, 3663 KB/s, 69 seconds passed
+... 36%, 253440 KB, 3663 KB/s, 69 seconds passed
 
 .. parsed-literal::
 
-    ... 39%, 273472 KB, 3246 KB/s, 84 seconds passed
-... 39%, 273504 KB, 3246 KB/s, 84 seconds passed
-... 39%, 273536 KB, 3246 KB/s, 84 seconds passed
-... 39%, 273568 KB, 3246 KB/s, 84 seconds passed
-... 39%, 273600 KB, 3246 KB/s, 84 seconds passed
+    ... 36%, 253472 KB, 3663 KB/s, 69 seconds passed
+... 36%, 253504 KB, 3663 KB/s, 69 seconds passed
+... 36%, 253536 KB, 3663 KB/s, 69 seconds passed
+... 36%, 253568 KB, 3663 KB/s, 69 seconds passed
+... 36%, 253600 KB, 3663 KB/s, 69 seconds passed
+... 36%, 253632 KB, 3663 KB/s, 69 seconds passed
 
 .. parsed-literal::
 
-    ... 39%, 273632 KB, 3246 KB/s, 84 seconds passed
-... 39%, 273664 KB, 3246 KB/s, 84 seconds passed
-... 39%, 273696 KB, 3246 KB/s, 84 seconds passed
-... 39%, 273728 KB, 3246 KB/s, 84 seconds passed
-... 39%, 273760 KB, 3246 KB/s, 84 seconds passed
-... 39%, 273792 KB, 3246 KB/s, 84 seconds passed
-... 39%, 273824 KB, 3246 KB/s, 84 seconds passed
+    ... 36%, 253664 KB, 3663 KB/s, 69 seconds passed
+... 36%, 253696 KB, 3663 KB/s, 69 seconds passed
+... 36%, 253728 KB, 3663 KB/s, 69 seconds passed
+... 36%, 253760 KB, 3663 KB/s, 69 seconds passed
+... 36%, 253792 KB, 3663 KB/s, 69 seconds passed
+... 36%, 253824 KB, 3663 KB/s, 69 seconds passed
 
 .. parsed-literal::
 
-    ... 39%, 273856 KB, 3246 KB/s, 84 seconds passed
-... 39%, 273888 KB, 3246 KB/s, 84 seconds passed
-... 39%, 273920 KB, 3246 KB/s, 84 seconds passed
-... 39%, 273952 KB, 3246 KB/s, 84 seconds passed
-... 39%, 273984 KB, 3246 KB/s, 84 seconds passed
+    ... 36%, 253856 KB, 3663 KB/s, 69 seconds passed
+... 36%, 253888 KB, 3663 KB/s, 69 seconds passed
+... 36%, 253920 KB, 3663 KB/s, 69 seconds passed
+... 36%, 253952 KB, 3663 KB/s, 69 seconds passed
+... 36%, 253984 KB, 3663 KB/s, 69 seconds passed
+... 36%, 254016 KB, 3663 KB/s, 69 seconds passed
 
 .. parsed-literal::
 
-    ... 39%, 274016 KB, 3246 KB/s, 84 seconds passed
-... 39%, 274048 KB, 3247 KB/s, 84 seconds passed
-... 39%, 274080 KB, 3247 KB/s, 84 seconds passed
-... 39%, 274112 KB, 3247 KB/s, 84 seconds passed
-... 39%, 274144 KB, 3247 KB/s, 84 seconds passed
-... 39%, 274176 KB, 3247 KB/s, 84 seconds passed
-... 39%, 274208 KB, 3247 KB/s, 84 seconds passed
+    ... 36%, 254048 KB, 3663 KB/s, 69 seconds passed
+... 36%, 254080 KB, 3663 KB/s, 69 seconds passed
+... 36%, 254112 KB, 3663 KB/s, 69 seconds passed
+... 36%, 254144 KB, 3663 KB/s, 69 seconds passed
+... 36%, 254176 KB, 3663 KB/s, 69 seconds passed
+... 36%, 254208 KB, 3663 KB/s, 69 seconds passed
 
 .. parsed-literal::
 
-    ... 39%, 274240 KB, 3247 KB/s, 84 seconds passed
-... 39%, 274272 KB, 3247 KB/s, 84 seconds passed
-... 39%, 274304 KB, 3247 KB/s, 84 seconds passed
-... 39%, 274336 KB, 3247 KB/s, 84 seconds passed
-... 39%, 274368 KB, 3247 KB/s, 84 seconds passed
+    ... 36%, 254240 KB, 3663 KB/s, 69 seconds passed
+... 36%, 254272 KB, 3663 KB/s, 69 seconds passed
+... 36%, 254304 KB, 3663 KB/s, 69 seconds passed
+... 36%, 254336 KB, 3663 KB/s, 69 seconds passed
+... 36%, 254368 KB, 3663 KB/s, 69 seconds passed
+... 36%, 254400 KB, 3663 KB/s, 69 seconds passed
 
 .. parsed-literal::
 
-    ... 39%, 274400 KB, 3247 KB/s, 84 seconds passed
-... 39%, 274432 KB, 3247 KB/s, 84 seconds passed
-... 39%, 274464 KB, 3247 KB/s, 84 seconds passed
-... 39%, 274496 KB, 3247 KB/s, 84 seconds passed
-... 39%, 274528 KB, 3247 KB/s, 84 seconds passed
-... 39%, 274560 KB, 3247 KB/s, 84 seconds passed
-... 39%, 274592 KB, 3247 KB/s, 84 seconds passed
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+... 36%, 254560 KB, 3663 KB/s, 69 seconds passed
+... 36%, 254592 KB, 3663 KB/s, 69 seconds passed
 
 .. parsed-literal::
 
-    ... 39%, 274624 KB, 3247 KB/s, 84 seconds passed
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+    ... 36%, 254624 KB, 3663 KB/s, 69 seconds passed
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 .. parsed-literal::
 
-    ... 39%, 274784 KB, 3247 KB/s, 84 seconds passed
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-... 39%, 274912 KB, 3248 KB/s, 84 seconds passed
-... 39%, 274944 KB, 3248 KB/s, 84 seconds passed
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+... 36%, 254912 KB, 3663 KB/s, 69 seconds passed
+... 36%, 254944 KB, 3663 KB/s, 69 seconds passed
+... 36%, 254976 KB, 3663 KB/s, 69 seconds passed
 
 .. parsed-literal::
 
-    ... 39%, 274976 KB, 3248 KB/s, 84 seconds passed
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-... 39%, 275104 KB, 3248 KB/s, 84 seconds passed
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+... 36%, 255072 KB, 3663 KB/s, 69 seconds passed
+... 36%, 255104 KB, 3663 KB/s, 69 seconds passed
+... 36%, 255136 KB, 3663 KB/s, 69 seconds passed
 
 .. parsed-literal::
 
-    ... 39%, 275168 KB, 3248 KB/s, 84 seconds passed
-... 39%, 275200 KB, 3248 KB/s, 84 seconds passed
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-... 39%, 275296 KB, 3248 KB/s, 84 seconds passed
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+... 36%, 255296 KB, 3663 KB/s, 69 seconds passed
+... 36%, 255328 KB, 3663 KB/s, 69 seconds passed
+... 36%, 255360 KB, 3663 KB/s, 69 seconds passed
 
 .. parsed-literal::
 
-    ... 39%, 275360 KB, 3248 KB/s, 84 seconds passed
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+... 36%, 255520 KB, 3664 KB/s, 69 seconds passed
 
 .. parsed-literal::
 
-    ... 39%, 275520 KB, 3248 KB/s, 84 seconds passed
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-... 39%, 275616 KB, 3249 KB/s, 84 seconds passed
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+... 36%, 255680 KB, 3663 KB/s, 69 seconds passed
+... 36%, 255712 KB, 3663 KB/s, 69 seconds passed
 
 .. parsed-literal::
 
-    ... 39%, 275744 KB, 3249 KB/s, 84 seconds passed
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+... 36%, 255872 KB, 3663 KB/s, 69 seconds passed
+... 36%, 255904 KB, 3664 KB/s, 69 seconds passed
 
 .. parsed-literal::
 
-    ... 39%, 275904 KB, 3249 KB/s, 84 seconds passed
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-... 39%, 276000 KB, 3249 KB/s, 84 seconds passed
-... 39%, 276032 KB, 3249 KB/s, 84 seconds passed
-... 39%, 276064 KB, 3249 KB/s, 84 seconds passed
-... 39%, 276096 KB, 3249 KB/s, 84 seconds passed
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+... 36%, 256032 KB, 3664 KB/s, 69 seconds passed
+... 36%, 256064 KB, 3663 KB/s, 69 seconds passed
+... 36%, 256096 KB, 3663 KB/s, 69 seconds passed
 
 .. parsed-literal::
 
-    ... 39%, 276128 KB, 3250 KB/s, 84 seconds passed
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-... 39%, 276192 KB, 3249 KB/s, 84 seconds passed
-... 39%, 276224 KB, 3250 KB/s, 84 seconds passed
-... 39%, 276256 KB, 3250 KB/s, 84 seconds passed
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+... 36%, 256224 KB, 3663 KB/s, 69 seconds passed
+... 36%, 256256 KB, 3663 KB/s, 69 seconds passed
+... 36%, 256288 KB, 3664 KB/s, 69 seconds passed
 
 .. parsed-literal::
 
-    ... 39%, 276288 KB, 3250 KB/s, 85 seconds passed
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-... 39%, 276480 KB, 3250 KB/s, 85 seconds passed
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+... 36%, 256416 KB, 3664 KB/s, 69 seconds passed
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+... 36%, 256480 KB, 3664 KB/s, 69 seconds passed
 
 .. parsed-literal::
 
-    ... 39%, 276512 KB, 3250 KB/s, 85 seconds passed
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-... 39%, 276608 KB, 3250 KB/s, 85 seconds passed
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 .. parsed-literal::
 
-    ... 39%, 276672 KB, 3250 KB/s, 85 seconds passed
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-... 39%, 276832 KB, 3250 KB/s, 85 seconds passed
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 .. parsed-literal::
 
-    ... 39%, 276896 KB, 3251 KB/s, 85 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 40%, 280480 KB, 3256 KB/s, 86 seconds passed
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 .. parsed-literal::
 
-    ... 40%, 280672 KB, 3256 KB/s, 86 seconds passed
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 .. parsed-literal::
 
-    ... 40%, 280864 KB, 3256 KB/s, 86 seconds passed
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-... 40%, 280960 KB, 3256 KB/s, 86 seconds passed
-... 40%, 280992 KB, 3256 KB/s, 86 seconds passed
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+... 37%, 260960 KB, 3664 KB/s, 71 seconds passed
+... 37%, 260992 KB, 3664 KB/s, 71 seconds passed
+... 37%, 261024 KB, 3664 KB/s, 71 seconds passed
 
 .. parsed-literal::
 
-    ... 40%, 281024 KB, 3256 KB/s, 86 seconds passed
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-... 40%, 281088 KB, 3257 KB/s, 86 seconds passed
-... 40%, 281120 KB, 3257 KB/s, 86 seconds passed
-... 40%, 281152 KB, 3256 KB/s, 86 seconds passed
-... 40%, 281184 KB, 3256 KB/s, 86 seconds passed
-... 40%, 281216 KB, 3257 KB/s, 86 seconds passed
+    ... 37%, 261056 KB, 3664 KB/s, 71 seconds passed
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+... 37%, 261152 KB, 3664 KB/s, 71 seconds passed
+... 37%, 261184 KB, 3664 KB/s, 71 seconds passed
+... 37%, 261216 KB, 3664 KB/s, 71 seconds passed
 
 .. parsed-literal::
 
-    ... 40%, 281248 KB, 3257 KB/s, 86 seconds passed
-... 40%, 281280 KB, 3257 KB/s, 86 seconds passed
-... 40%, 281312 KB, 3257 KB/s, 86 seconds passed
-... 40%, 281344 KB, 3257 KB/s, 86 seconds passed
-... 40%, 281376 KB, 3257 KB/s, 86 seconds passed
+    ... 37%, 261248 KB, 3664 KB/s, 71 seconds passed
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+... 37%, 261344 KB, 3664 KB/s, 71 seconds passed
+... 37%, 261376 KB, 3664 KB/s, 71 seconds passed
 
 .. parsed-literal::
 
-    ... 40%, 281408 KB, 3257 KB/s, 86 seconds passed
-... 40%, 281440 KB, 3257 KB/s, 86 seconds passed
-... 40%, 281472 KB, 3257 KB/s, 86 seconds passed
-... 40%, 281504 KB, 3257 KB/s, 86 seconds passed
-... 40%, 281536 KB, 3257 KB/s, 86 seconds passed
-... 40%, 281568 KB, 3257 KB/s, 86 seconds passed
-... 40%, 281600 KB, 3257 KB/s, 86 seconds passed
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+... 37%, 261504 KB, 3664 KB/s, 71 seconds passed
+... 37%, 261536 KB, 3664 KB/s, 71 seconds passed
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 .. parsed-literal::
 
-    ... 40%, 281632 KB, 3257 KB/s, 86 seconds passed
-... 40%, 281664 KB, 3257 KB/s, 86 seconds passed
-... 40%, 281696 KB, 3257 KB/s, 86 seconds passed
-... 40%, 281728 KB, 3257 KB/s, 86 seconds passed
-... 40%, 281760 KB, 3257 KB/s, 86 seconds passed
+    ... 37%, 261600 KB, 3664 KB/s, 71 seconds passed
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+... 37%, 261696 KB, 3664 KB/s, 71 seconds passed
+... 37%, 261728 KB, 3664 KB/s, 71 seconds passed
+... 37%, 261760 KB, 3664 KB/s, 71 seconds passed
 
 .. parsed-literal::
 
-    ... 40%, 281792 KB, 3257 KB/s, 86 seconds passed
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-... 40%, 281920 KB, 3257 KB/s, 86 seconds passed
-... 40%, 281952 KB, 3258 KB/s, 86 seconds passed
-... 40%, 281984 KB, 3258 KB/s, 86 seconds passed
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+... 37%, 261920 KB, 3664 KB/s, 71 seconds passed
+... 37%, 261952 KB, 3664 KB/s, 71 seconds passed
 
 .. parsed-literal::
 
-    ... 40%, 282016 KB, 3258 KB/s, 86 seconds passed
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-... 40%, 282080 KB, 3258 KB/s, 86 seconds passed
-... 40%, 282112 KB, 3258 KB/s, 86 seconds passed
-... 40%, 282144 KB, 3258 KB/s, 86 seconds passed
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+... 37%, 262112 KB, 3664 KB/s, 71 seconds passed
+... 37%, 262144 KB, 3664 KB/s, 71 seconds passed
 
 .. parsed-literal::
 
-    ... 40%, 282176 KB, 3258 KB/s, 86 seconds passed
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-... 40%, 282304 KB, 3258 KB/s, 86 seconds passed
-... 40%, 282336 KB, 3258 KB/s, 86 seconds passed
-... 40%, 282368 KB, 3258 KB/s, 86 seconds passed
+    ... 37%, 262176 KB, 3664 KB/s, 71 seconds passed
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+... 37%, 262272 KB, 3664 KB/s, 71 seconds passed
+... 37%, 262304 KB, 3664 KB/s, 71 seconds passed
+... 37%, 262336 KB, 3664 KB/s, 71 seconds passed
 
 .. parsed-literal::
 
-    ... 40%, 282400 KB, 3258 KB/s, 86 seconds passed
-... 40%, 282432 KB, 3258 KB/s, 86 seconds passed
-... 40%, 282464 KB, 3258 KB/s, 86 seconds passed
-... 40%, 282496 KB, 3258 KB/s, 86 seconds passed
-... 40%, 282528 KB, 3258 KB/s, 86 seconds passed
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+... 37%, 262496 KB, 3664 KB/s, 71 seconds passed
+... 37%, 262528 KB, 3664 KB/s, 71 seconds passed
 
 .. parsed-literal::
 
-    ... 40%, 282560 KB, 3258 KB/s, 86 seconds passed
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-... 40%, 282688 KB, 3258 KB/s, 86 seconds passed
-... 40%, 282720 KB, 3259 KB/s, 86 seconds passed
-... 40%, 282752 KB, 3259 KB/s, 86 seconds passed
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 .. parsed-literal::
 
-    ... 40%, 282784 KB, 3259 KB/s, 86 seconds passed
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-... 40%, 282848 KB, 3259 KB/s, 86 seconds passed
-... 40%, 282880 KB, 3259 KB/s, 86 seconds passed
-... 40%, 282912 KB, 3259 KB/s, 86 seconds passed
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+... 37%, 262880 KB, 3664 KB/s, 71 seconds passed
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 .. parsed-literal::
 
-    ... 40%, 282944 KB, 3259 KB/s, 86 seconds passed
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-... 40%, 283008 KB, 3259 KB/s, 86 seconds passed
-... 40%, 283040 KB, 3259 KB/s, 86 seconds passed
-... 40%, 283072 KB, 3259 KB/s, 86 seconds passed
-... 40%, 283104 KB, 3259 KB/s, 86 seconds passed
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 .. parsed-literal::
 
-    ... 40%, 283136 KB, 3259 KB/s, 86 seconds passed
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-... 40%, 283200 KB, 3259 KB/s, 86 seconds passed
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-... 40%, 283264 KB, 3259 KB/s, 86 seconds passed
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 .. parsed-literal::
 
-    ... 40%, 283296 KB, 3259 KB/s, 86 seconds passed
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-... 40%, 283360 KB, 3259 KB/s, 86 seconds passed
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-... 40%, 283456 KB, 3260 KB/s, 86 seconds passed
-... 40%, 283488 KB, 3260 KB/s, 86 seconds passed
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 .. parsed-literal::
 
-    ... 40%, 283520 KB, 3260 KB/s, 86 seconds passed
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 .. parsed-literal::
 
-    ... 40%, 283680 KB, 3260 KB/s, 87 seconds passed
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-... 40%, 283808 KB, 3260 KB/s, 87 seconds passed
-... 40%, 283840 KB, 3260 KB/s, 87 seconds passed
-... 40%, 283872 KB, 3260 KB/s, 87 seconds passed
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 .. parsed-literal::
 
-    ... 40%, 283904 KB, 3260 KB/s, 87 seconds passed
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-... 40%, 284032 KB, 3261 KB/s, 87 seconds passed
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 .. parsed-literal::
 
-    ... 40%, 284064 KB, 3260 KB/s, 87 seconds passed
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 .. parsed-literal::
 
-    ... 40%, 284256 KB, 3261 KB/s, 87 seconds passed
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 .. parsed-literal::
 
-    ... 40%, 284448 KB, 3261 KB/s, 87 seconds passed
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 .. parsed-literal::
 
-    ... 40%, 284640 KB, 3261 KB/s, 87 seconds passed
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 .. parsed-literal::
 
-    ... 40%, 284832 KB, 3261 KB/s, 87 seconds passed
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 .. parsed-literal::
 
-    ... 40%, 285024 KB, 3262 KB/s, 87 seconds passed
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 .. parsed-literal::
 
-    ... 41%, 285216 KB, 3262 KB/s, 87 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 41%, 285600 KB, 3262 KB/s, 87 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 41%, 285952 KB, 3263 KB/s, 87 seconds passed
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 .. parsed-literal::
 
-    ... 41%, 286144 KB, 3263 KB/s, 87 seconds passed
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 .. parsed-literal::
 
-    ... 41%, 286336 KB, 3263 KB/s, 87 seconds passed
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 .. parsed-literal::
 
-    ... 41%, 286528 KB, 3264 KB/s, 87 seconds passed
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+... 38%, 266720 KB, 3665 KB/s, 72 seconds passed
 
 .. parsed-literal::
 
-    ... 41%, 286720 KB, 3264 KB/s, 87 seconds passed
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-... 41%, 286880 KB, 3264 KB/s, 87 seconds passed
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 .. parsed-literal::
 
-    ... 41%, 286912 KB, 3264 KB/s, 87 seconds passed
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 .. parsed-literal::
 
-    ... 41%, 287104 KB, 3264 KB/s, 87 seconds passed
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-... 41%, 287200 KB, 3265 KB/s, 87 seconds passed
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 .. parsed-literal::
 
-    ... 41%, 287264 KB, 3264 KB/s, 87 seconds passed
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-... 41%, 287328 KB, 3265 KB/s, 87 seconds passed
-... 41%, 287360 KB, 3265 KB/s, 88 seconds passed
-... 41%, 287392 KB, 3265 KB/s, 88 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 42%, 292960 KB, 3272 KB/s, 89 seconds passed
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 .. parsed-literal::
 
-    ... 42%, 293152 KB, 3272 KB/s, 89 seconds passed
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 .. parsed-literal::
 
-    ... 42%, 293344 KB, 3272 KB/s, 89 seconds passed
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 .. parsed-literal::
 
-    ... 42%, 293536 KB, 3273 KB/s, 89 seconds passed
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 .. parsed-literal::
 
-    ... 42%, 293728 KB, 3273 KB/s, 89 seconds passed
-... 42%, 293760 KB, 3273 KB/s, 89 seconds passed
-... 42%, 293792 KB, 3273 KB/s, 89 seconds passed
-... 42%, 293824 KB, 3273 KB/s, 89 seconds passed
-... 42%, 293856 KB, 3273 KB/s, 89 seconds passed
-... 42%, 293888 KB, 3273 KB/s, 89 seconds passed
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+... 39%, 273824 KB, 3665 KB/s, 74 seconds passed
+... 39%, 273856 KB, 3665 KB/s, 74 seconds passed
 
 .. parsed-literal::
 
-    ... 42%, 293920 KB, 3273 KB/s, 89 seconds passed
-... 42%, 293952 KB, 3273 KB/s, 89 seconds passed
-... 42%, 293984 KB, 3273 KB/s, 89 seconds passed
-... 42%, 294016 KB, 3273 KB/s, 89 seconds passed
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+... 39%, 274016 KB, 3665 KB/s, 74 seconds passed
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 .. parsed-literal::
 
-    ... 42%, 294112 KB, 3273 KB/s, 89 seconds passed
-... 42%, 294144 KB, 3273 KB/s, 89 seconds passed
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-... 42%, 294240 KB, 3273 KB/s, 89 seconds passed
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 .. parsed-literal::
 
-    ... 42%, 294272 KB, 3273 KB/s, 89 seconds passed
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-... 42%, 294464 KB, 3274 KB/s, 89 seconds passed
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+... 39%, 274432 KB, 3665 KB/s, 74 seconds passed
 
 .. parsed-literal::
 
-    ... 42%, 294496 KB, 3274 KB/s, 89 seconds passed
-... 42%, 294528 KB, 3274 KB/s, 89 seconds passed
-... 42%, 294560 KB, 3274 KB/s, 89 seconds passed
-... 42%, 294592 KB, 3274 KB/s, 89 seconds passed
-... 42%, 294624 KB, 3274 KB/s, 89 seconds passed
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 .. parsed-literal::
 
-    ... 42%, 294656 KB, 3274 KB/s, 89 seconds passed
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 .. parsed-literal::
 
-    ... 42%, 294880 KB, 3274 KB/s, 90 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 42%, 295264 KB, 3275 KB/s, 90 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 43%, 299232 KB, 3280 KB/s, 91 seconds passed
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 .. parsed-literal::
 
-    ... 43%, 299392 KB, 3280 KB/s, 91 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 43%, 299776 KB, 3280 KB/s, 91 seconds passed
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 .. parsed-literal::
 
-    ... 43%, 299968 KB, 3281 KB/s, 91 seconds passed
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 .. parsed-literal::
 
-    ... 43%, 300160 KB, 3281 KB/s, 91 seconds passed
-... 43%, 300192 KB, 3281 KB/s, 91 seconds passed
-... 43%, 300224 KB, 3281 KB/s, 91 seconds passed
-... 43%, 300256 KB, 3281 KB/s, 91 seconds passed
-... 43%, 300288 KB, 3281 KB/s, 91 seconds passed
-... 43%, 300320 KB, 3281 KB/s, 91 seconds passed
+    ... 40%, 280160 KB, 3665 KB/s, 76 seconds passed
+... 40%, 280192 KB, 3665 KB/s, 76 seconds passed
+... 40%, 280224 KB, 3666 KB/s, 76 seconds passed
+... 40%, 280256 KB, 3666 KB/s, 76 seconds passed
+... 40%, 280288 KB, 3665 KB/s, 76 seconds passed
 
 .. parsed-literal::
 
-    ... 43%, 300352 KB, 3281 KB/s, 91 seconds passed
-... 43%, 300384 KB, 3281 KB/s, 91 seconds passed
-... 43%, 300416 KB, 3281 KB/s, 91 seconds passed
-... 43%, 300448 KB, 3281 KB/s, 91 seconds passed
-... 43%, 300480 KB, 3281 KB/s, 91 seconds passed
-... 43%, 300512 KB, 3281 KB/s, 91 seconds passed
+    ... 40%, 280320 KB, 3665 KB/s, 76 seconds passed
+... 40%, 280352 KB, 3666 KB/s, 76 seconds passed
+... 40%, 280384 KB, 3666 KB/s, 76 seconds passed
+... 40%, 280416 KB, 3665 KB/s, 76 seconds passed
+... 40%, 280448 KB, 3665 KB/s, 76 seconds passed
+... 40%, 280480 KB, 3666 KB/s, 76 seconds passed
+... 40%, 280512 KB, 3666 KB/s, 76 seconds passed
 
 .. parsed-literal::
 
-    ... 43%, 300544 KB, 3281 KB/s, 91 seconds passed
-... 43%, 300576 KB, 3282 KB/s, 91 seconds passed
-... 43%, 300608 KB, 3281 KB/s, 91 seconds passed
-... 43%, 300640 KB, 3281 KB/s, 91 seconds passed
-... 43%, 300672 KB, 3281 KB/s, 91 seconds passed
-... 43%, 300704 KB, 3282 KB/s, 91 seconds passed
+    ... 40%, 280544 KB, 3665 KB/s, 76 seconds passed
+... 40%, 280576 KB, 3665 KB/s, 76 seconds passed
+... 40%, 280608 KB, 3666 KB/s, 76 seconds passed
+... 40%, 280640 KB, 3666 KB/s, 76 seconds passed
+... 40%, 280672 KB, 3665 KB/s, 76 seconds passed
 
 .. parsed-literal::
 
-    ... 43%, 300736 KB, 3282 KB/s, 91 seconds passed
-... 43%, 300768 KB, 3282 KB/s, 91 seconds passed
-... 43%, 300800 KB, 3282 KB/s, 91 seconds passed
-... 43%, 300832 KB, 3282 KB/s, 91 seconds passed
-... 43%, 300864 KB, 3282 KB/s, 91 seconds passed
-... 43%, 300896 KB, 3282 KB/s, 91 seconds passed
+    ... 40%, 280704 KB, 3665 KB/s, 76 seconds passed
+... 40%, 280736 KB, 3666 KB/s, 76 seconds passed
+... 40%, 280768 KB, 3666 KB/s, 76 seconds passed
+... 40%, 280800 KB, 3665 KB/s, 76 seconds passed
+... 40%, 280832 KB, 3665 KB/s, 76 seconds passed
+... 40%, 280864 KB, 3666 KB/s, 76 seconds passed
 
 .. parsed-literal::
 
-    ... 43%, 300928 KB, 3282 KB/s, 91 seconds passed
-... 43%, 300960 KB, 3282 KB/s, 91 seconds passed
-... 43%, 300992 KB, 3282 KB/s, 91 seconds passed
-... 43%, 301024 KB, 3282 KB/s, 91 seconds passed
-... 43%, 301056 KB, 3282 KB/s, 91 seconds passed
-... 43%, 301088 KB, 3282 KB/s, 91 seconds passed
+    ... 40%, 280896 KB, 3666 KB/s, 76 seconds passed
+... 40%, 280928 KB, 3665 KB/s, 76 seconds passed
+... 40%, 280960 KB, 3665 KB/s, 76 seconds passed
+... 40%, 280992 KB, 3666 KB/s, 76 seconds passed
+... 40%, 281024 KB, 3666 KB/s, 76 seconds passed
+... 40%, 281056 KB, 3665 KB/s, 76 seconds passed
 
 .. parsed-literal::
 
-    ... 43%, 301120 KB, 3282 KB/s, 91 seconds passed
-... 43%, 301152 KB, 3282 KB/s, 91 seconds passed
-... 43%, 301184 KB, 3282 KB/s, 91 seconds passed
-... 43%, 301216 KB, 3282 KB/s, 91 seconds passed
-... 43%, 301248 KB, 3282 KB/s, 91 seconds passed
-... 43%, 301280 KB, 3282 KB/s, 91 seconds passed
+    ... 40%, 281088 KB, 3665 KB/s, 76 seconds passed
+... 40%, 281120 KB, 3666 KB/s, 76 seconds passed
+... 40%, 281152 KB, 3666 KB/s, 76 seconds passed
+... 40%, 281184 KB, 3665 KB/s, 76 seconds passed
+... 40%, 281216 KB, 3665 KB/s, 76 seconds passed
+... 40%, 281248 KB, 3666 KB/s, 76 seconds passed
 
 .. parsed-literal::
 
-    ... 43%, 301312 KB, 3282 KB/s, 91 seconds passed
-... 43%, 301344 KB, 3282 KB/s, 91 seconds passed
-... 43%, 301376 KB, 3282 KB/s, 91 seconds passed
-... 43%, 301408 KB, 3282 KB/s, 91 seconds passed
-... 43%, 301440 KB, 3282 KB/s, 91 seconds passed
-... 43%, 301472 KB, 3283 KB/s, 91 seconds passed
+    ... 40%, 281280 KB, 3666 KB/s, 76 seconds passed
+... 40%, 281312 KB, 3665 KB/s, 76 seconds passed
+... 40%, 281344 KB, 3665 KB/s, 76 seconds passed
+... 40%, 281376 KB, 3665 KB/s, 76 seconds passed
+... 40%, 281408 KB, 3666 KB/s, 76 seconds passed
+... 40%, 281440 KB, 3665 KB/s, 76 seconds passed
 
 .. parsed-literal::
 
-    ... 43%, 301504 KB, 3283 KB/s, 91 seconds passed
-... 43%, 301536 KB, 3283 KB/s, 91 seconds passed
-... 43%, 301568 KB, 3283 KB/s, 91 seconds passed
-... 43%, 301600 KB, 3283 KB/s, 91 seconds passed
-... 43%, 301632 KB, 3283 KB/s, 91 seconds passed
+    ... 40%, 281472 KB, 3666 KB/s, 76 seconds passed
+... 40%, 281504 KB, 3666 KB/s, 76 seconds passed
+... 40%, 281536 KB, 3666 KB/s, 76 seconds passed
+... 40%, 281568 KB, 3665 KB/s, 76 seconds passed
+... 40%, 281600 KB, 3665 KB/s, 76 seconds passed
+... 40%, 281632 KB, 3665 KB/s, 76 seconds passed
 
 .. parsed-literal::
 
-    ... 43%, 301664 KB, 3283 KB/s, 91 seconds passed
-... 43%, 301696 KB, 3283 KB/s, 91 seconds passed
-... 43%, 301728 KB, 3283 KB/s, 91 seconds passed
-... 43%, 301760 KB, 3283 KB/s, 91 seconds passed
-... 43%, 301792 KB, 3283 KB/s, 91 seconds passed
-... 43%, 301824 KB, 3283 KB/s, 91 seconds passed
-... 43%, 301856 KB, 3283 KB/s, 91 seconds passed
+    ... 40%, 281664 KB, 3666 KB/s, 76 seconds passed
+... 40%, 281696 KB, 3665 KB/s, 76 seconds passed
+... 40%, 281728 KB, 3665 KB/s, 76 seconds passed
+... 40%, 281760 KB, 3665 KB/s, 76 seconds passed
+... 40%, 281792 KB, 3666 KB/s, 76 seconds passed
 
 .. parsed-literal::
 
-    ... 43%, 301888 KB, 3283 KB/s, 91 seconds passed
-... 43%, 301920 KB, 3283 KB/s, 91 seconds passed
-... 43%, 301952 KB, 3283 KB/s, 91 seconds passed
-... 43%, 301984 KB, 3283 KB/s, 91 seconds passed
-... 43%, 302016 KB, 3283 KB/s, 91 seconds passed
+    ... 40%, 281824 KB, 3665 KB/s, 76 seconds passed
+... 40%, 281856 KB, 3666 KB/s, 76 seconds passed
+... 40%, 281888 KB, 3665 KB/s, 76 seconds passed
+... 40%, 281920 KB, 3666 KB/s, 76 seconds passed
+... 40%, 281952 KB, 3666 KB/s, 76 seconds passed
+... 40%, 281984 KB, 3666 KB/s, 76 seconds passed
 
 .. parsed-literal::
 
-    ... 43%, 302048 KB, 3283 KB/s, 91 seconds passed
-... 43%, 302080 KB, 3283 KB/s, 91 seconds passed
-... 43%, 302112 KB, 3283 KB/s, 91 seconds passed
-... 43%, 302144 KB, 3283 KB/s, 92 seconds passed
-... 43%, 302176 KB, 3283 KB/s, 92 seconds passed
-... 43%, 302208 KB, 3283 KB/s, 92 seconds passed
-... 43%, 302240 KB, 3284 KB/s, 92 seconds passed
+    ... 40%, 282016 KB, 3666 KB/s, 76 seconds passed
+... 40%, 282048 KB, 3666 KB/s, 76 seconds passed
+... 40%, 282080 KB, 3666 KB/s, 76 seconds passed
+... 40%, 282112 KB, 3666 KB/s, 76 seconds passed
+... 40%, 282144 KB, 3666 KB/s, 76 seconds passed
+... 40%, 282176 KB, 3666 KB/s, 76 seconds passed
 
 .. parsed-literal::
 
-    ... 43%, 302272 KB, 3283 KB/s, 92 seconds passed
-... 43%, 302304 KB, 3283 KB/s, 92 seconds passed
-... 43%, 302336 KB, 3284 KB/s, 92 seconds passed
-... 43%, 302368 KB, 3284 KB/s, 92 seconds passed
-... 43%, 302400 KB, 3284 KB/s, 92 seconds passed
+    ... 40%, 282208 KB, 3666 KB/s, 76 seconds passed
+... 40%, 282240 KB, 3666 KB/s, 76 seconds passed
+... 40%, 282272 KB, 3666 KB/s, 76 seconds passed
+... 40%, 282304 KB, 3666 KB/s, 76 seconds passed
+... 40%, 282336 KB, 3666 KB/s, 77 seconds passed
+... 40%, 282368 KB, 3666 KB/s, 77 seconds passed
 
 .. parsed-literal::
 
-    ... 43%, 302432 KB, 3284 KB/s, 92 seconds passed
-... 43%, 302464 KB, 3284 KB/s, 92 seconds passed
-... 43%, 302496 KB, 3284 KB/s, 92 seconds passed
-... 43%, 302528 KB, 3284 KB/s, 92 seconds passed
-... 43%, 302560 KB, 3284 KB/s, 92 seconds passed
-... 43%, 302592 KB, 3284 KB/s, 92 seconds passed
+    ... 40%, 282400 KB, 3666 KB/s, 77 seconds passed
+... 40%, 282432 KB, 3666 KB/s, 77 seconds passed
+... 40%, 282464 KB, 3666 KB/s, 77 seconds passed
+... 40%, 282496 KB, 3666 KB/s, 77 seconds passed
+... 40%, 282528 KB, 3666 KB/s, 77 seconds passed
+... 40%, 282560 KB, 3666 KB/s, 77 seconds passed
 
 .. parsed-literal::
 
-    ... 43%, 302624 KB, 3284 KB/s, 92 seconds passed
-... 43%, 302656 KB, 3284 KB/s, 92 seconds passed
-... 43%, 302688 KB, 3284 KB/s, 92 seconds passed
-... 43%, 302720 KB, 3284 KB/s, 92 seconds passed
-... 43%, 302752 KB, 3284 KB/s, 92 seconds passed
-... 43%, 302784 KB, 3284 KB/s, 92 seconds passed
+    ... 40%, 282592 KB, 3666 KB/s, 77 seconds passed
+... 40%, 282624 KB, 3666 KB/s, 77 seconds passed
+... 40%, 282656 KB, 3666 KB/s, 77 seconds passed
+... 40%, 282688 KB, 3666 KB/s, 77 seconds passed
+... 40%, 282720 KB, 3666 KB/s, 77 seconds passed
+... 40%, 282752 KB, 3666 KB/s, 77 seconds passed
 
 .. parsed-literal::
 
-    ... 43%, 302816 KB, 3284 KB/s, 92 seconds passed
-... 43%, 302848 KB, 3284 KB/s, 92 seconds passed
-... 43%, 302880 KB, 3284 KB/s, 92 seconds passed
-... 43%, 302912 KB, 3284 KB/s, 92 seconds passed
-... 43%, 302944 KB, 3284 KB/s, 92 seconds passed
-... 43%, 302976 KB, 3284 KB/s, 92 seconds passed
+    ... 40%, 282784 KB, 3666 KB/s, 77 seconds passed
+... 40%, 282816 KB, 3666 KB/s, 77 seconds passed
+... 40%, 282848 KB, 3666 KB/s, 77 seconds passed
+... 40%, 282880 KB, 3666 KB/s, 77 seconds passed
+... 40%, 282912 KB, 3666 KB/s, 77 seconds passed
+... 40%, 282944 KB, 3666 KB/s, 77 seconds passed
 
 .. parsed-literal::
 
-    ... 43%, 303008 KB, 3284 KB/s, 92 seconds passed
-... 43%, 303040 KB, 3284 KB/s, 92 seconds passed
-... 43%, 303072 KB, 3284 KB/s, 92 seconds passed
-... 43%, 303104 KB, 3284 KB/s, 92 seconds passed
-... 43%, 303136 KB, 3285 KB/s, 92 seconds passed
-... 43%, 303168 KB, 3285 KB/s, 92 seconds passed
+    ... 40%, 282976 KB, 3666 KB/s, 77 seconds passed
+... 40%, 283008 KB, 3666 KB/s, 77 seconds passed
+... 40%, 283040 KB, 3666 KB/s, 77 seconds passed
+... 40%, 283072 KB, 3666 KB/s, 77 seconds passed
+... 40%, 283104 KB, 3666 KB/s, 77 seconds passed
+... 40%, 283136 KB, 3666 KB/s, 77 seconds passed
 
 .. parsed-literal::
 
-    ... 43%, 303200 KB, 3285 KB/s, 92 seconds passed
-... 43%, 303232 KB, 3285 KB/s, 92 seconds passed
-... 43%, 303264 KB, 3285 KB/s, 92 seconds passed
-... 43%, 303296 KB, 3285 KB/s, 92 seconds passed
-... 43%, 303328 KB, 3285 KB/s, 92 seconds passed
-... 43%, 303360 KB, 3285 KB/s, 92 seconds passed
+    ... 40%, 283168 KB, 3666 KB/s, 77 seconds passed
+... 40%, 283200 KB, 3666 KB/s, 77 seconds passed
+... 40%, 283232 KB, 3666 KB/s, 77 seconds passed
+... 40%, 283264 KB, 3666 KB/s, 77 seconds passed
+... 40%, 283296 KB, 3666 KB/s, 77 seconds passed
+... 40%, 283328 KB, 3666 KB/s, 77 seconds passed
 
 .. parsed-literal::
 
-    ... 43%, 303392 KB, 3285 KB/s, 92 seconds passed
-... 43%, 303424 KB, 3285 KB/s, 92 seconds passed
-... 43%, 303456 KB, 3285 KB/s, 92 seconds passed
-... 43%, 303488 KB, 3285 KB/s, 92 seconds passed
-... 43%, 303520 KB, 3285 KB/s, 92 seconds passed
-... 43%, 303552 KB, 3285 KB/s, 92 seconds passed
+    ... 40%, 283360 KB, 3666 KB/s, 77 seconds passed
+... 40%, 283392 KB, 3666 KB/s, 77 seconds passed
+... 40%, 283424 KB, 3666 KB/s, 77 seconds passed
+... 40%, 283456 KB, 3666 KB/s, 77 seconds passed
+... 40%, 283488 KB, 3666 KB/s, 77 seconds passed
+... 40%, 283520 KB, 3666 KB/s, 77 seconds passed
 
 .. parsed-literal::
 
-    ... 43%, 303584 KB, 3285 KB/s, 92 seconds passed
-... 43%, 303616 KB, 3285 KB/s, 92 seconds passed
-... 43%, 303648 KB, 3285 KB/s, 92 seconds passed
-... 43%, 303680 KB, 3285 KB/s, 92 seconds passed
-... 43%, 303712 KB, 3285 KB/s, 92 seconds passed
-... 43%, 303744 KB, 3285 KB/s, 92 seconds passed
+    ... 40%, 283552 KB, 3666 KB/s, 77 seconds passed
+... 40%, 283584 KB, 3665 KB/s, 77 seconds passed
+... 40%, 283616 KB, 3666 KB/s, 77 seconds passed
+... 40%, 283648 KB, 3666 KB/s, 77 seconds passed
+... 40%, 283680 KB, 3666 KB/s, 77 seconds passed
+... 40%, 283712 KB, 3666 KB/s, 77 seconds passed
 
 .. parsed-literal::
 
-    ... 43%, 303776 KB, 3285 KB/s, 92 seconds passed
-... 43%, 303808 KB, 3285 KB/s, 92 seconds passed
-... 43%, 303840 KB, 3285 KB/s, 92 seconds passed
-... 43%, 303872 KB, 3285 KB/s, 92 seconds passed
-... 43%, 303904 KB, 3286 KB/s, 92 seconds passed
-... 43%, 303936 KB, 3285 KB/s, 92 seconds passed
+    ... 40%, 283744 KB, 3666 KB/s, 77 seconds passed
+... 40%, 283776 KB, 3666 KB/s, 77 seconds passed
+... 40%, 283808 KB, 3666 KB/s, 77 seconds passed
+... 40%, 283840 KB, 3666 KB/s, 77 seconds passed
+... 40%, 283872 KB, 3666 KB/s, 77 seconds passed
+... 40%, 283904 KB, 3666 KB/s, 77 seconds passed
 
 .. parsed-literal::
 
-    ... 43%, 303968 KB, 3286 KB/s, 92 seconds passed
-... 43%, 304000 KB, 3286 KB/s, 92 seconds passed
-... 43%, 304032 KB, 3286 KB/s, 92 seconds passed
-... 43%, 304064 KB, 3286 KB/s, 92 seconds passed
-... 43%, 304096 KB, 3286 KB/s, 92 seconds passed
+    ... 40%, 283936 KB, 3666 KB/s, 77 seconds passed
+... 40%, 283968 KB, 3665 KB/s, 77 seconds passed
+... 40%, 284000 KB, 3666 KB/s, 77 seconds passed
+... 40%, 284032 KB, 3666 KB/s, 77 seconds passed
+... 40%, 284064 KB, 3666 KB/s, 77 seconds passed
 
 .. parsed-literal::
 
-    ... 43%, 304128 KB, 3286 KB/s, 92 seconds passed
-... 43%, 304160 KB, 3286 KB/s, 92 seconds passed
-... 43%, 304192 KB, 3286 KB/s, 92 seconds passed
-... 43%, 304224 KB, 3286 KB/s, 92 seconds passed
-... 43%, 304256 KB, 3286 KB/s, 92 seconds passed
-... 43%, 304288 KB, 3286 KB/s, 92 seconds passed
+    ... 40%, 284096 KB, 3666 KB/s, 77 seconds passed
+... 40%, 284128 KB, 3666 KB/s, 77 seconds passed
+... 40%, 284160 KB, 3666 KB/s, 77 seconds passed
+... 40%, 284192 KB, 3666 KB/s, 77 seconds passed
+... 40%, 284224 KB, 3666 KB/s, 77 seconds passed
+... 40%, 284256 KB, 3666 KB/s, 77 seconds passed
+... 40%, 284288 KB, 3666 KB/s, 77 seconds passed
 
 .. parsed-literal::
 
-    ... 43%, 304320 KB, 3286 KB/s, 92 seconds passed
-... 43%, 304352 KB, 3286 KB/s, 92 seconds passed
-... 43%, 304384 KB, 3286 KB/s, 92 seconds passed
-... 43%, 304416 KB, 3286 KB/s, 92 seconds passed
-... 43%, 304448 KB, 3286 KB/s, 92 seconds passed
-... 43%, 304480 KB, 3286 KB/s, 92 seconds passed
+    ... 40%, 284320 KB, 3666 KB/s, 77 seconds passed
+... 40%, 284352 KB, 3666 KB/s, 77 seconds passed
+... 40%, 284384 KB, 3666 KB/s, 77 seconds passed
+... 40%, 284416 KB, 3666 KB/s, 77 seconds passed
+... 40%, 284448 KB, 3666 KB/s, 77 seconds passed
+... 40%, 284480 KB, 3666 KB/s, 77 seconds passed
 
 .. parsed-literal::
 
-    ... 43%, 304512 KB, 3286 KB/s, 92 seconds passed
-... 43%, 304544 KB, 3286 KB/s, 92 seconds passed
-... 43%, 304576 KB, 3286 KB/s, 92 seconds passed
-... 43%, 304608 KB, 3286 KB/s, 92 seconds passed
-... 43%, 304640 KB, 3286 KB/s, 92 seconds passed
-... 43%, 304672 KB, 3286 KB/s, 92 seconds passed
+    ... 40%, 284512 KB, 3666 KB/s, 77 seconds passed
+... 40%, 284544 KB, 3666 KB/s, 77 seconds passed
+... 40%, 284576 KB, 3666 KB/s, 77 seconds passed
+... 40%, 284608 KB, 3666 KB/s, 77 seconds passed
+... 40%, 284640 KB, 3666 KB/s, 77 seconds passed
+... 40%, 284672 KB, 3666 KB/s, 77 seconds passed
 
 .. parsed-literal::
 
-    ... 43%, 304704 KB, 3286 KB/s, 92 seconds passed
-... 43%, 304736 KB, 3286 KB/s, 92 seconds passed
-... 43%, 304768 KB, 3286 KB/s, 92 seconds passed
-... 43%, 304800 KB, 3286 KB/s, 92 seconds passed
-... 43%, 304832 KB, 3286 KB/s, 92 seconds passed
-... 43%, 304864 KB, 3287 KB/s, 92 seconds passed
+    ... 40%, 284704 KB, 3666 KB/s, 77 seconds passed
+... 40%, 284736 KB, 3666 KB/s, 77 seconds passed
+... 40%, 284768 KB, 3666 KB/s, 77 seconds passed
+... 40%, 284800 KB, 3666 KB/s, 77 seconds passed
+... 40%, 284832 KB, 3666 KB/s, 77 seconds passed
 
 .. parsed-literal::
 
-    ... 43%, 304896 KB, 3287 KB/s, 92 seconds passed
-... 43%, 304928 KB, 3287 KB/s, 92 seconds passed
-... 43%, 304960 KB, 3287 KB/s, 92 seconds passed
-... 43%, 304992 KB, 3287 KB/s, 92 seconds passed
-... 43%, 305024 KB, 3287 KB/s, 92 seconds passed
-... 43%, 305056 KB, 3287 KB/s, 92 seconds passed
+    ... 40%, 284864 KB, 3666 KB/s, 77 seconds passed
+... 40%, 284896 KB, 3666 KB/s, 77 seconds passed
+... 40%, 284928 KB, 3666 KB/s, 77 seconds passed
+... 40%, 284960 KB, 3666 KB/s, 77 seconds passed
+... 40%, 284992 KB, 3666 KB/s, 77 seconds passed
+... 40%, 285024 KB, 3666 KB/s, 77 seconds passed
 
 .. parsed-literal::
 
-    ... 43%, 305088 KB, 3287 KB/s, 92 seconds passed
-... 43%, 305120 KB, 3287 KB/s, 92 seconds passed
-... 43%, 305152 KB, 3287 KB/s, 92 seconds passed
-... 43%, 305184 KB, 3287 KB/s, 92 seconds passed
-... 43%, 305216 KB, 3287 KB/s, 92 seconds passed
-... 43%, 305248 KB, 3287 KB/s, 92 seconds passed
+    ... 40%, 285056 KB, 3666 KB/s, 77 seconds passed
+... 40%, 285088 KB, 3666 KB/s, 77 seconds passed
+... 40%, 285120 KB, 3666 KB/s, 77 seconds passed
+... 40%, 285152 KB, 3666 KB/s, 77 seconds passed
+... 41%, 285184 KB, 3666 KB/s, 77 seconds passed
+... 41%, 285216 KB, 3666 KB/s, 77 seconds passed
 
 .. parsed-literal::
 
-    ... 43%, 305280 KB, 3287 KB/s, 92 seconds passed
-... 43%, 305312 KB, 3287 KB/s, 92 seconds passed
-... 43%, 305344 KB, 3287 KB/s, 92 seconds passed
-... 43%, 305376 KB, 3287 KB/s, 92 seconds passed
-... 43%, 305408 KB, 3287 KB/s, 92 seconds passed
-... 43%, 305440 KB, 3287 KB/s, 92 seconds passed
+    ... 41%, 285248 KB, 3666 KB/s, 77 seconds passed
+... 41%, 285280 KB, 3666 KB/s, 77 seconds passed
+... 41%, 285312 KB, 3666 KB/s, 77 seconds passed
+... 41%, 285344 KB, 3666 KB/s, 77 seconds passed
+... 41%, 285376 KB, 3666 KB/s, 77 seconds passed
+... 41%, 285408 KB, 3666 KB/s, 77 seconds passed
 
 .. parsed-literal::
 
-    ... 43%, 305472 KB, 3287 KB/s, 92 seconds passed
-... 43%, 305504 KB, 3287 KB/s, 92 seconds passed
-... 43%, 305536 KB, 3287 KB/s, 92 seconds passed
-... 43%, 305568 KB, 3287 KB/s, 92 seconds passed
-... 43%, 305600 KB, 3287 KB/s, 92 seconds passed
-... 43%, 305632 KB, 3288 KB/s, 92 seconds passed
+    ... 41%, 285440 KB, 3666 KB/s, 77 seconds passed
+... 41%, 285472 KB, 3666 KB/s, 77 seconds passed
+... 41%, 285504 KB, 3666 KB/s, 77 seconds passed
+... 41%, 285536 KB, 3666 KB/s, 77 seconds passed
+... 41%, 285568 KB, 3666 KB/s, 77 seconds passed
+... 41%, 285600 KB, 3666 KB/s, 77 seconds passed
 
 .. parsed-literal::
 
-    ... 43%, 305664 KB, 3287 KB/s, 92 seconds passed
-... 43%, 305696 KB, 3287 KB/s, 92 seconds passed
-... 43%, 305728 KB, 3287 KB/s, 92 seconds passed
-... 43%, 305760 KB, 3287 KB/s, 92 seconds passed
-... 43%, 305792 KB, 3288 KB/s, 92 seconds passed
+    ... 41%, 285632 KB, 3666 KB/s, 77 seconds passed
+... 41%, 285664 KB, 3666 KB/s, 77 seconds passed
+... 41%, 285696 KB, 3666 KB/s, 77 seconds passed
+... 41%, 285728 KB, 3666 KB/s, 77 seconds passed
+... 41%, 285760 KB, 3666 KB/s, 77 seconds passed
+... 41%, 285792 KB, 3666 KB/s, 77 seconds passed
 
 .. parsed-literal::
 
-    ... 43%, 305824 KB, 3287 KB/s, 93 seconds passed
-... 43%, 305856 KB, 3288 KB/s, 93 seconds passed
-... 43%, 305888 KB, 3288 KB/s, 93 seconds passed
-... 43%, 305920 KB, 3288 KB/s, 93 seconds passed
-... 43%, 305952 KB, 3288 KB/s, 93 seconds passed
-... 43%, 305984 KB, 3288 KB/s, 93 seconds passed
+    ... 41%, 285824 KB, 3666 KB/s, 77 seconds passed
+... 41%, 285856 KB, 3666 KB/s, 77 seconds passed
+... 41%, 285888 KB, 3666 KB/s, 77 seconds passed
+... 41%, 285920 KB, 3666 KB/s, 77 seconds passed
+... 41%, 285952 KB, 3666 KB/s, 77 seconds passed
+... 41%, 285984 KB, 3666 KB/s, 77 seconds passed
 
 .. parsed-literal::
 
-    ... 43%, 306016 KB, 3288 KB/s, 93 seconds passed
-... 44%, 306048 KB, 3288 KB/s, 93 seconds passed
-... 44%, 306080 KB, 3288 KB/s, 93 seconds passed
-... 44%, 306112 KB, 3288 KB/s, 93 seconds passed
-... 44%, 306144 KB, 3288 KB/s, 93 seconds passed
-... 44%, 306176 KB, 3288 KB/s, 93 seconds passed
+    ... 41%, 286016 KB, 3666 KB/s, 78 seconds passed
+... 41%, 286048 KB, 3666 KB/s, 78 seconds passed
+... 41%, 286080 KB, 3666 KB/s, 78 seconds passed
+... 41%, 286112 KB, 3666 KB/s, 78 seconds passed
+... 41%, 286144 KB, 3666 KB/s, 78 seconds passed
+... 41%, 286176 KB, 3666 KB/s, 78 seconds passed
 
 .. parsed-literal::
 
-    ... 44%, 306208 KB, 3288 KB/s, 93 seconds passed
-... 44%, 306240 KB, 3288 KB/s, 93 seconds passed
-... 44%, 306272 KB, 3288 KB/s, 93 seconds passed
-... 44%, 306304 KB, 3288 KB/s, 93 seconds passed
-... 44%, 306336 KB, 3288 KB/s, 93 seconds passed
-... 44%, 306368 KB, 3288 KB/s, 93 seconds passed
+    ... 41%, 286208 KB, 3666 KB/s, 78 seconds passed
+... 41%, 286240 KB, 3666 KB/s, 78 seconds passed
+... 41%, 286272 KB, 3666 KB/s, 78 seconds passed
+... 41%, 286304 KB, 3666 KB/s, 78 seconds passed
+... 41%, 286336 KB, 3666 KB/s, 78 seconds passed
+... 41%, 286368 KB, 3666 KB/s, 78 seconds passed
 
 .. parsed-literal::
 
-    ... 44%, 306400 KB, 3288 KB/s, 93 seconds passed
-... 44%, 306432 KB, 3288 KB/s, 93 seconds passed
-... 44%, 306464 KB, 3288 KB/s, 93 seconds passed
-... 44%, 306496 KB, 3288 KB/s, 93 seconds passed
-... 44%, 306528 KB, 3288 KB/s, 93 seconds passed
-... 44%, 306560 KB, 3288 KB/s, 93 seconds passed
+    ... 41%, 286400 KB, 3666 KB/s, 78 seconds passed
+... 41%, 286432 KB, 3666 KB/s, 78 seconds passed
+... 41%, 286464 KB, 3666 KB/s, 78 seconds passed
+... 41%, 286496 KB, 3666 KB/s, 78 seconds passed
+... 41%, 286528 KB, 3666 KB/s, 78 seconds passed
 
 .. parsed-literal::
 
-    ... 44%, 306592 KB, 3288 KB/s, 93 seconds passed
-... 44%, 306624 KB, 3288 KB/s, 93 seconds passed
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+... 41%, 286720 KB, 3666 KB/s, 78 seconds passed
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 .. parsed-literal::
 
-    ... 44%, 306784 KB, 3289 KB/s, 93 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 44%, 307328 KB, 3289 KB/s, 93 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 44%, 307936 KB, 3290 KB/s, 93 seconds passed
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 .. parsed-literal::
 
-    ... 44%, 308096 KB, 3290 KB/s, 93 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 44%, 308480 KB, 3291 KB/s, 93 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 44%, 311680 KB, 3294 KB/s, 94 seconds passed
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 .. parsed-literal::
 
-    ... 44%, 311904 KB, 3295 KB/s, 94 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 44%, 312288 KB, 3295 KB/s, 94 seconds passed
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 .. parsed-literal::
 
-    ... 44%, 312448 KB, 3295 KB/s, 94 seconds passed
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 .. parsed-literal::
 
-    ... 44%, 312640 KB, 3295 KB/s, 94 seconds passed
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 .. parsed-literal::
 
-    ... 44%, 312832 KB, 3296 KB/s, 94 seconds passed
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 .. parsed-literal::
 
-    ... 45%, 313024 KB, 3296 KB/s, 94 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 45%, 318688 KB, 3302 KB/s, 96 seconds passed
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 .. parsed-literal::
 
-    ... 45%, 318912 KB, 3302 KB/s, 96 seconds passed
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 .. parsed-literal::
 
-    ... 45%, 319072 KB, 3302 KB/s, 96 seconds passed
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 .. parsed-literal::
 
-    ... 45%, 319264 KB, 3303 KB/s, 96 seconds passed
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+... 43%, 299424 KB, 3667 KB/s, 81 seconds passed
 
 .. parsed-literal::
 
-    ... 45%, 319456 KB, 3303 KB/s, 96 seconds passed
-... 45%, 319488 KB, 3303 KB/s, 96 seconds passed
-... 45%, 319520 KB, 3303 KB/s, 96 seconds passed
-... 45%, 319552 KB, 3303 KB/s, 96 seconds passed
-... 45%, 319584 KB, 3303 KB/s, 96 seconds passed
-... 45%, 319616 KB, 3303 KB/s, 96 seconds passed
+    ... 43%, 299456 KB, 3667 KB/s, 81 seconds passed
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+... 43%, 299552 KB, 3667 KB/s, 81 seconds passed
+... 43%, 299584 KB, 3667 KB/s, 81 seconds passed
+... 43%, 299616 KB, 3667 KB/s, 81 seconds passed
 
 .. parsed-literal::
 
-    ... 45%, 319648 KB, 3303 KB/s, 96 seconds passed
-... 45%, 319680 KB, 3303 KB/s, 96 seconds passed
-... 45%, 319712 KB, 3303 KB/s, 96 seconds passed
-... 45%, 319744 KB, 3303 KB/s, 96 seconds passed
-... 45%, 319776 KB, 3303 KB/s, 96 seconds passed
-... 45%, 319808 KB, 3303 KB/s, 96 seconds passed
+    ... 43%, 299648 KB, 3667 KB/s, 81 seconds passed
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+... 43%, 299776 KB, 3667 KB/s, 81 seconds passed
+... 43%, 299808 KB, 3667 KB/s, 81 seconds passed
 
 .. parsed-literal::
 
-    ... 45%, 319840 KB, 3303 KB/s, 96 seconds passed
-... 45%, 319872 KB, 3303 KB/s, 96 seconds passed
-... 45%, 319904 KB, 3303 KB/s, 96 seconds passed
-... 46%, 319936 KB, 3304 KB/s, 96 seconds passed
-... 46%, 319968 KB, 3303 KB/s, 96 seconds passed
-... 46%, 320000 KB, 3304 KB/s, 96 seconds passed
+    ... 43%, 299840 KB, 3667 KB/s, 81 seconds passed
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+... 43%, 299904 KB, 3667 KB/s, 81 seconds passed
+... 43%, 299936 KB, 3667 KB/s, 81 seconds passed
+... 43%, 299968 KB, 3667 KB/s, 81 seconds passed
 
 .. parsed-literal::
 
-    ... 46%, 320032 KB, 3304 KB/s, 96 seconds passed
-... 46%, 320064 KB, 3304 KB/s, 96 seconds passed
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-... 46%, 320128 KB, 3304 KB/s, 96 seconds passed
-... 46%, 320160 KB, 3304 KB/s, 96 seconds passed
-... 46%, 320192 KB, 3304 KB/s, 96 seconds passed
+    ... 43%, 300000 KB, 3667 KB/s, 81 seconds passed
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+... 43%, 300128 KB, 3667 KB/s, 81 seconds passed
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+... 43%, 300192 KB, 3667 KB/s, 81 seconds passed
 
 .. parsed-literal::
 
-    ... 46%, 320224 KB, 3304 KB/s, 96 seconds passed
-... 46%, 320256 KB, 3304 KB/s, 96 seconds passed
-... 46%, 320288 KB, 3304 KB/s, 96 seconds passed
-... 46%, 320320 KB, 3304 KB/s, 96 seconds passed
-... 46%, 320352 KB, 3304 KB/s, 96 seconds passed
-... 46%, 320384 KB, 3304 KB/s, 96 seconds passed
+    ... 43%, 300224 KB, 3667 KB/s, 81 seconds passed
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+... 43%, 300320 KB, 3667 KB/s, 81 seconds passed
+... 43%, 300352 KB, 3667 KB/s, 81 seconds passed
+... 43%, 300384 KB, 3667 KB/s, 81 seconds passed
 
 .. parsed-literal::
 
-    ... 46%, 320416 KB, 3304 KB/s, 96 seconds passed
-... 46%, 320448 KB, 3304 KB/s, 96 seconds passed
-... 46%, 320480 KB, 3304 KB/s, 96 seconds passed
-... 46%, 320512 KB, 3304 KB/s, 96 seconds passed
-... 46%, 320544 KB, 3304 KB/s, 96 seconds passed
-... 46%, 320576 KB, 3304 KB/s, 97 seconds passed
+    ... 43%, 300416 KB, 3667 KB/s, 81 seconds passed
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+... 43%, 300480 KB, 3667 KB/s, 81 seconds passed
+... 43%, 300512 KB, 3667 KB/s, 81 seconds passed
+... 43%, 300544 KB, 3667 KB/s, 81 seconds passed
 
 .. parsed-literal::
 
-    ... 46%, 320608 KB, 3304 KB/s, 97 seconds passed
-... 46%, 320640 KB, 3304 KB/s, 97 seconds passed
-... 46%, 320672 KB, 3304 KB/s, 97 seconds passed
-... 46%, 320704 KB, 3304 KB/s, 97 seconds passed
-... 46%, 320736 KB, 3304 KB/s, 97 seconds passed
-... 46%, 320768 KB, 3304 KB/s, 97 seconds passed
+    ... 43%, 300576 KB, 3667 KB/s, 81 seconds passed
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+... 43%, 300672 KB, 3667 KB/s, 81 seconds passed
+... 43%, 300704 KB, 3667 KB/s, 81 seconds passed
+... 43%, 300736 KB, 3667 KB/s, 81 seconds passed
 
 .. parsed-literal::
 
-    ... 46%, 320800 KB, 3304 KB/s, 97 seconds passed
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-... 46%, 320896 KB, 3305 KB/s, 97 seconds passed
-... 46%, 320928 KB, 3305 KB/s, 97 seconds passed
-... 46%, 320960 KB, 3305 KB/s, 97 seconds passed
+    ... 43%, 300768 KB, 3667 KB/s, 82 seconds passed
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+... 43%, 300896 KB, 3667 KB/s, 82 seconds passed
+... 43%, 300928 KB, 3667 KB/s, 82 seconds passed
 
 .. parsed-literal::
 
-    ... 46%, 320992 KB, 3305 KB/s, 97 seconds passed
-... 46%, 321024 KB, 3305 KB/s, 97 seconds passed
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-... 46%, 321088 KB, 3305 KB/s, 97 seconds passed
-... 46%, 321120 KB, 3305 KB/s, 97 seconds passed
-... 46%, 321152 KB, 3305 KB/s, 97 seconds passed
+    ... 43%, 300960 KB, 3667 KB/s, 82 seconds passed
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+... 43%, 301056 KB, 3667 KB/s, 82 seconds passed
+... 43%, 301088 KB, 3667 KB/s, 82 seconds passed
+... 43%, 301120 KB, 3667 KB/s, 82 seconds passed
 
 .. parsed-literal::
 
-    ... 46%, 321184 KB, 3305 KB/s, 97 seconds passed
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-... 46%, 321248 KB, 3305 KB/s, 97 seconds passed
-... 46%, 321280 KB, 3305 KB/s, 97 seconds passed
-... 46%, 321312 KB, 3305 KB/s, 97 seconds passed
-... 46%, 321344 KB, 3305 KB/s, 97 seconds passed
+    ... 43%, 301152 KB, 3667 KB/s, 82 seconds passed
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+... 43%, 301280 KB, 3667 KB/s, 82 seconds passed
+... 43%, 301312 KB, 3667 KB/s, 82 seconds passed
 
 .. parsed-literal::
 
-    ... 46%, 321376 KB, 3305 KB/s, 97 seconds passed
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-... 46%, 321472 KB, 3305 KB/s, 97 seconds passed
-... 46%, 321504 KB, 3305 KB/s, 97 seconds passed
-... 46%, 321536 KB, 3305 KB/s, 97 seconds passed
+    ... 43%, 301344 KB, 3667 KB/s, 82 seconds passed
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+... 43%, 301472 KB, 3667 KB/s, 82 seconds passed
+... 43%, 301504 KB, 3667 KB/s, 82 seconds passed
 
 .. parsed-literal::
 
-    ... 46%, 321568 KB, 3305 KB/s, 97 seconds passed
-... 46%, 321600 KB, 3305 KB/s, 97 seconds passed
-... 46%, 321632 KB, 3305 KB/s, 97 seconds passed
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-... 46%, 321696 KB, 3305 KB/s, 97 seconds passed
+    ... 43%, 301536 KB, 3667 KB/s, 82 seconds passed
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+... 43%, 301600 KB, 3667 KB/s, 82 seconds passed
+... 43%, 301632 KB, 3667 KB/s, 82 seconds passed
+... 43%, 301664 KB, 3667 KB/s, 82 seconds passed
 
 .. parsed-literal::
 
-    ... 46%, 321728 KB, 3305 KB/s, 97 seconds passed
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-... 46%, 321792 KB, 3306 KB/s, 97 seconds passed
-... 46%, 321824 KB, 3306 KB/s, 97 seconds passed
-... 46%, 321856 KB, 3306 KB/s, 97 seconds passed
-... 46%, 321888 KB, 3306 KB/s, 97 seconds passed
+    ... 43%, 301696 KB, 3667 KB/s, 82 seconds passed
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 .. parsed-literal::
 
-    ... 46%, 321920 KB, 3306 KB/s, 97 seconds passed
-... 46%, 321952 KB, 3306 KB/s, 97 seconds passed
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-... 46%, 322048 KB, 3306 KB/s, 97 seconds passed
-... 46%, 322080 KB, 3306 KB/s, 97 seconds passed
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 .. parsed-literal::
 
-    ... 46%, 322112 KB, 3306 KB/s, 97 seconds passed
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-... 46%, 322272 KB, 3306 KB/s, 97 seconds passed
+    ... 43%, 302080 KB, 3667 KB/s, 82 seconds passed
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+... 43%, 302240 KB, 3667 KB/s, 82 seconds passed
+... 43%, 302272 KB, 3667 KB/s, 82 seconds passed
 
 .. parsed-literal::
 
-    ... 46%, 322304 KB, 3306 KB/s, 97 seconds passed
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-... 46%, 322400 KB, 3306 KB/s, 97 seconds passed
-... 46%, 322432 KB, 3306 KB/s, 97 seconds passed
-... 46%, 322464 KB, 3306 KB/s, 97 seconds passed
+    ... 43%, 302304 KB, 3667 KB/s, 82 seconds passed
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+... 43%, 302400 KB, 3667 KB/s, 82 seconds passed
+... 43%, 302432 KB, 3667 KB/s, 82 seconds passed
 
 .. parsed-literal::
 
-    ... 46%, 322496 KB, 3306 KB/s, 97 seconds passed
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+... 43%, 302560 KB, 3667 KB/s, 82 seconds passed
+... 43%, 302592 KB, 3667 KB/s, 82 seconds passed
+... 43%, 302624 KB, 3667 KB/s, 82 seconds passed
 
 .. parsed-literal::
 
-    ... 46%, 322688 KB, 3307 KB/s, 97 seconds passed
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 .. parsed-literal::
 
-    ... 46%, 322880 KB, 3307 KB/s, 97 seconds passed
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 .. parsed-literal::
 
-    ... 46%, 323072 KB, 3307 KB/s, 97 seconds passed
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 .. parsed-literal::
 
-    ... 46%, 323264 KB, 3306 KB/s, 97 seconds passed
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 .. parsed-literal::
 
-    ... 46%, 323392 KB, 3306 KB/s, 97 seconds passed
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 .. parsed-literal::
 
-    ... 46%, 323488 KB, 3306 KB/s, 97 seconds passed
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 .. parsed-literal::
 
-    ... 46%, 323712 KB, 3306 KB/s, 97 seconds passed
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 .. parsed-literal::
 
-    ... 46%, 323840 KB, 3306 KB/s, 97 seconds passed
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 .. parsed-literal::
 
-    ... 46%, 324096 KB, 3306 KB/s, 98 seconds passed
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 .. parsed-literal::
 
-    ... 46%, 324224 KB, 3306 KB/s, 98 seconds passed
-... 46%, 324256 KB, 3307 KB/s, 98 seconds passed
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 .. parsed-literal::
 
-    ... 46%, 324480 KB, 3307 KB/s, 98 seconds passed
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-... 46%, 324544 KB, 3307 KB/s, 98 seconds passed
-s passed
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 .. parsed-literal::
 
-    ... 46%, 324608 KB, 3307 KB/s, 98 seconds passed
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-... 46%, 324832 KB, 3308 KB/s, 98 seconds passed
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+... 43%, 304832 KB, 3667 KB/s, 83 seconds passed
+... 43%, 304864 KB, 3667 KB/s, 83 seconds passed
 
 .. parsed-literal::
 
-    ... 46%, 324864 KB, 3307 KB/s, 98 seconds passed
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-... 46%, 324960 KB, 3308 KB/s, 98 seconds passed
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+... 43%, 305056 KB, 3667 KB/s, 83 seconds passed
+... 43%, 305088 KB, 3667 KB/s, 83 seconds passed
 
 .. parsed-literal::
 
-    ... 46%, 324992 KB, 3307 KB/s, 98 seconds passed
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+... 43%, 305248 KB, 3667 KB/s, 83 seconds passed
 
 .. parsed-literal::
 
-    ... 46%, 325216 KB, 3308 KB/s, 98 seconds passed
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-... 46%, 325280 KB, 3308 KB/s, 98 seconds passed
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-... 46%, 325344 KB, 3308 KB/s, 98 seconds passed
+    ... 43%, 305280 KB, 3667 KB/s, 83 seconds passed
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+... 43%, 305408 KB, 3667 KB/s, 83 seconds passed
+... 43%, 305440 KB, 3667 KB/s, 83 seconds passed
+... 43%, 305472 KB, 3667 KB/s, 83 seconds passed
 
 .. parsed-literal::
 
-    ... 46%, 325376 KB, 3308 KB/s, 98 seconds passed
-... 46%, 325408 KB, 3308 KB/s, 98 seconds passed
-... 46%, 325440 KB, 3308 KB/s, 98 seconds passed
-... 46%, 325472 KB, 3308 KB/s, 98 seconds passed
-... 46%, 325504 KB, 3308 KB/s, 98 seconds passed
-... 46%, 325536 KB, 3308 KB/s, 98 seconds passed
+    ... 43%, 305504 KB, 3667 KB/s, 83 seconds passed
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+... 43%, 305600 KB, 3667 KB/s, 83 seconds passed
+... 43%, 305632 KB, 3667 KB/s, 83 seconds passed
 
 .. parsed-literal::
 
-    ... 46%, 325568 KB, 3308 KB/s, 98 seconds passed
-... 46%, 325600 KB, 3309 KB/s, 98 seconds passed
-s passed
-... 46%, 325664 KB, 3308 KB/s, 98 seconds passed
-... 46%, 325696 KB, 3308 KB/s, 98 seconds passed
-... 46%, 325728 KB, 3309 KB/s, 98 seconds passed
+    ... 43%, 305664 KB, 3667 KB/s, 83 seconds passed
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+... 43%, 305760 KB, 3667 KB/s, 83 seconds passed
+... 43%, 305792 KB, 3667 KB/s, 83 seconds passed
+... 43%, 305824 KB, 3667 KB/s, 83 seconds passed
 
 .. parsed-literal::
 
-    ... 46%, 325760 KB, 3308 KB/s, 98 seconds passed
-... 46%, 325792 KB, 3308 KB/s, 98 seconds passed
-... 46%, 325824 KB, 3309 KB/s, 98 seconds passed
-... 46%, 325856 KB, 3308 KB/s, 98 seconds passed
-... 46%, 325888 KB, 3308 KB/s, 98 seconds passed
+    ... 43%, 305856 KB, 3667 KB/s, 83 seconds passed
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+... 43%, 305952 KB, 3667 KB/s, 83 seconds passed
+... 43%, 305984 KB, 3667 KB/s, 83 seconds passed
+... 43%, 306016 KB, 3667 KB/s, 83 seconds passed
 
 .. parsed-literal::
 
-    ... 46%, 325920 KB, 3308 KB/s, 98 seconds passed
-... 46%, 325952 KB, 3309 KB/s, 98 seconds passed
-... 46%, 325984 KB, 3308 KB/s, 98 seconds passed
-... 46%, 326016 KB, 3308 KB/s, 98 seconds passed
-... 46%, 326048 KB, 3309 KB/s, 98 seconds passed
-... 46%, 326080 KB, 3309 KB/s, 98 seconds passed
+    ... 44%, 306048 KB, 3667 KB/s, 83 seconds passed
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+... 44%, 306144 KB, 3667 KB/s, 83 seconds passed
+... 44%, 306176 KB, 3667 KB/s, 83 seconds passed
+... 44%, 306208 KB, 3667 KB/s, 83 seconds passed
 
 .. parsed-literal::
 
-    ... 46%, 326112 KB, 3308 KB/s, 98 seconds passed
-... 46%, 326144 KB, 3308 KB/s, 98 seconds passed
-... 46%, 326176 KB, 3309 KB/s, 98 seconds passed
-... 46%, 326208 KB, 3309 KB/s, 98 seconds passed
-s passed
-... 46%, 326272 KB, 3309 KB/s, 98 seconds passed
+    ... 44%, 306240 KB, 3667 KB/s, 83 seconds passed
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+... 44%, 306336 KB, 3667 KB/s, 83 seconds passed
+... 44%, 306368 KB, 3667 KB/s, 83 seconds passed
+... 44%, 306400 KB, 3667 KB/s, 83 seconds passed
 
 .. parsed-literal::
 
-    ... 46%, 326304 KB, 3309 KB/s, 98 seconds passed
-... 46%, 326336 KB, 3309 KB/s, 98 seconds passed
-... 46%, 326368 KB, 3308 KB/s, 98 seconds passed
-... 46%, 326400 KB, 3309 KB/s, 98 seconds passed
-... 46%, 326432 KB, 3309 KB/s, 98 seconds passed
-... 46%, 326464 KB, 3309 KB/s, 98 seconds passed
+    ... 44%, 306432 KB, 3667 KB/s, 83 seconds passed
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+... 44%, 306528 KB, 3667 KB/s, 83 seconds passed
+... 44%, 306560 KB, 3667 KB/s, 83 seconds passed
+... 44%, 306592 KB, 3668 KB/s, 83 seconds passed
 
 .. parsed-literal::
 
-    ... 46%, 326496 KB, 3309 KB/s, 98 seconds passed
-... 46%, 326528 KB, 3309 KB/s, 98 seconds passed
-... 46%, 326560 KB, 3309 KB/s, 98 seconds passed
-s passed
-... 46%, 326624 KB, 3309 KB/s, 98 seconds passed
+    ... 44%, 306624 KB, 3667 KB/s, 83 seconds passed
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+... 44%, 306720 KB, 3668 KB/s, 83 seconds passed
+... 44%, 306752 KB, 3667 KB/s, 83 seconds passed
+... 44%, 306784 KB, 3667 KB/s, 83 seconds passed
 
 .. parsed-literal::
 
-    ... 46%, 326656 KB, 3309 KB/s, 98 seconds passed
-... 46%, 326688 KB, 3309 KB/s, 98 seconds passed
-... 46%, 326720 KB, 3309 KB/s, 98 seconds passed
-... 46%, 326752 KB, 3309 KB/s, 98 seconds passed
-... 46%, 326784 KB, 3309 KB/s, 98 seconds passed
+    ... 44%, 306816 KB, 3667 KB/s, 83 seconds passed
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+... 44%, 306944 KB, 3667 KB/s, 83 seconds passed
+... 44%, 306976 KB, 3668 KB/s, 83 seconds passed
 
 .. parsed-literal::
 
-    ... 46%, 326816 KB, 3308 KB/s, 98 seconds passed
-... 46%, 326848 KB, 3309 KB/s, 98 seconds passed
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-... 47%, 326912 KB, 3309 KB/s, 98 seconds passed
-... 47%, 326944 KB, 3309 KB/s, 98 seconds passed
-... 47%, 326976 KB, 3309 KB/s, 98 seconds passed
+    ... 44%, 307008 KB, 3667 KB/s, 83 seconds passed
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+... 44%, 307104 KB, 3668 KB/s, 83 seconds passed
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+... 44%, 307168 KB, 3667 KB/s, 83 seconds passed
 
 .. parsed-literal::
 
-    ... 47%, 327008 KB, 3309 KB/s, 98 seconds passed
-... 47%, 327040 KB, 3309 KB/s, 98 seconds passed
-... 47%, 327072 KB, 3309 KB/s, 98 seconds passed
-... 47%, 327104 KB, 3309 KB/s, 98 seconds passed
-... 47%, 327136 KB, 3309 KB/s, 98 seconds passed
-... 47%, 327168 KB, 3309 KB/s, 98 seconds passed
+    ... 44%, 307200 KB, 3667 KB/s, 83 seconds passed
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+... 44%, 307296 KB, 3668 KB/s, 83 seconds passed
+... 44%, 307328 KB, 3667 KB/s, 83 seconds passed
+... 44%, 307360 KB, 3668 KB/s, 83 seconds passed
 
 .. parsed-literal::
 
-    ... 47%, 327200 KB, 3309 KB/s, 98 seconds passed
-... 47%, 327232 KB, 3309 KB/s, 98 seconds passed
-... 47%, 327264 KB, 3309 KB/s, 98 seconds passed
-... 47%, 327296 KB, 3309 KB/s, 98 seconds passed
+    ... 44%, 307392 KB, 3667 KB/s, 83 seconds passed
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+... 44%, 307520 KB, 3667 KB/s, 83 seconds passed
+... 44%, 307552 KB, 3668 KB/s, 83 seconds passed
 
 .. parsed-literal::
 
-    ... 47%, 327328 KB, 3309 KB/s, 98 seconds passed
-... 47%, 327360 KB, 3309 KB/s, 98 seconds passed
-... 47%, 327392 KB, 3310 KB/s, 98 seconds passed
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-... 47%, 327520 KB, 3310 KB/s, 98 seconds passed
-... 47%, 327552 KB, 3310 KB/s, 98 seconds passed
+    ... 44%, 307584 KB, 3667 KB/s, 83 seconds passed
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+... 44%, 307712 KB, 3667 KB/s, 83 seconds passed
+... 44%, 307744 KB, 3668 KB/s, 83 seconds passed
 
 .. parsed-literal::
 
-    ... 47%, 327584 KB, 3309 KB/s, 98 seconds passed
-... 47%, 327616 KB, 3310 KB/s, 98 seconds passed
-... 47%, 327648 KB, 3310 KB/s, 98 seconds passed
-... 47%, 327680 KB, 3310 KB/s, 98 seconds passed
+    ... 44%, 307776 KB, 3667 KB/s, 83 seconds passed
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+... 44%, 307936 KB, 3668 KB/s, 83 seconds passed
 
 .. parsed-literal::
 
-    ... 47%, 327712 KB, 3309 KB/s, 99 seconds passed
-... 47%, 327744 KB, 3310 KB/s, 99 seconds passed
-... 47%, 327776 KB, 3310 KB/s, 99 seconds passed
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-... 47%, 327872 KB, 3310 KB/s, 99 seconds passed
-... 47%, 327904 KB, 3310 KB/s, 99 seconds passed
-... 47%, 327936 KB, 3310 KB/s, 99 seconds passed
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+... 44%, 308128 KB, 3668 KB/s, 84 seconds passed
 
 .. parsed-literal::
 
-    ... 47%, 327968 KB, 3310 KB/s, 99 seconds passed
-... 47%, 328000 KB, 3310 KB/s, 99 seconds passed
-... 47%, 328032 KB, 3310 KB/s, 99 seconds passed
-... 47%, 328064 KB, 3310 KB/s, 99 seconds passed
+    ... 44%, 308160 KB, 3667 KB/s, 84 seconds passed
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+... 44%, 308256 KB, 3668 KB/s, 84 seconds passed
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+... 44%, 308320 KB, 3668 KB/s, 84 seconds passed
 
 .. parsed-literal::
 
-    ... 47%, 328096 KB, 3310 KB/s, 99 seconds passed
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-... 47%, 328192 KB, 3310 KB/s, 99 seconds passed
-... 47%, 328224 KB, 3310 KB/s, 99 seconds passed
-s passed
-... 47%, 328288 KB, 3310 KB/s, 99 seconds passed
-... 47%, 328320 KB, 3311 KB/s, 99 seconds passed
+    ... 44%, 308352 KB, 3667 KB/s, 84 seconds passed
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+... 44%, 308480 KB, 3667 KB/s, 84 seconds passed
 
 .. parsed-literal::
 
-    ... 47%, 328352 KB, 3310 KB/s, 99 seconds passed
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 .. parsed-literal::
 
-    ... 47%, 328480 KB, 3310 KB/s, 99 seconds passed
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-... 47%, 328576 KB, 3311 KB/s, 99 seconds passed
-... 47%, 328608 KB, 3310 KB/s, 99 seconds passed
-... 47%, 328640 KB, 3311 KB/s, 99 seconds passed
-s passed
-... 47%, 328704 KB, 3311 KB/s, 99 seconds passed
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 .. parsed-literal::
 
-    ... 47%, 328736 KB, 3310 KB/s, 99 seconds passed
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 .. parsed-literal::
 
-    ... 47%, 328864 KB, 3311 KB/s, 99 seconds passed
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 .. parsed-literal::
 
-    ... 47%, 329120 KB, 3311 KB/s, 99 seconds passed
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 .. parsed-literal::
 
-    ... 47%, 329248 KB, 3311 KB/s, 99 seconds passed
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 .. parsed-literal::
 
-    ... 47%, 329504 KB, 3311 KB/s, 99 seconds passed
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 .. parsed-literal::
 
-    conds passed
-    ... 47%, 329664 KB, 3312 KB/s, 99 seconds passed
-    ... 47%, 329696 KB, 3312 KB/s, 99 seconds passed
-    ... 47%, 329728 KB, 3312 KB/s, 99 seconds passed
-    ... 47%, 329760 KB, 3312 KB/s, 99 seconds passed
-    s passed
-    ... 47%, 329824 KB, 3312 KB/s, 99 seconds passed
-    ... 47%, 329856 KB, 3312 KB/s, 99 seconds passed
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 .. parsed-literal::
 
-    ... 47%, 329888 KB, 3312 KB/s, 99 seconds passed
-    ... 47%, 329920 KB, 3312 KB/s, 99 seconds passed
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 .. parsed-literal::
 
-    ... 47%, 330016 KB, 3312 KB/s, 99 seconds passed
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-    ... 47%, 330112 KB, 3312 KB/s, 99 seconds passed
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-    s passed
-    ... 47%, 330208 KB, 3312 KB/s, 99 seconds passed
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 .. parsed-literal::
 
-    ... 47%, 330240 KB, 3313 KB/s, 99 seconds passed
-    ... 47%, 330272 KB, 3312 KB/s, 99 seconds passed
-    ... 47%, 330304 KB, 3312 KB/s, 99 seconds passed
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-    ... 47%, 330368 KB, 3313 KB/s, 99 seconds passed
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 .. parsed-literal::
 
-    ... 47%, 330400 KB, 3312 KB/s, 99 seconds passed
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 .. parsed-literal::
 
-    ... 47%, 330624 KB, 3313 KB/s, 99 seconds passed
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 .. parsed-literal::
 
-    ... 47%, 330784 KB, 3313 KB/s, 99 seconds passed
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 .. parsed-literal::
 
-    ... 47%, 331008 KB, 3313 KB/s, 99 seconds passed
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 .. parsed-literal::
 
-    ... 47%, 331168 KB, 3313 KB/s, 99 seconds passed
-... 47%, 331200 KB, 3313 KB/s, 99 seconds passed
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-... 47%, 331264 KB, 3314 KB/s, 99 seconds passed
-... 47%, 331296 KB, 3313 KB/s, 99 seconds passed
-... 47%, 331328 KB, 3313 KB/s, 99 seconds passed
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 .. parsed-literal::
 
-    ... 47%, 331360 KB, 3314 KB/s, 99 seconds passed
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-... 47%, 331424 KB, 3313 KB/s, 100 seconds passed
-... 47%, 331456 KB, 3314 KB/s, 100 seconds passed
-... 47%, 331488 KB, 3314 KB/s, 100 seconds passed
-ds passed
+    ... 44%, 311520 KB, 3667 KB/s, 84 seconds passed
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 .. parsed-literal::
 
-    ... 47%, 331552 KB, 3313 KB/s, 100 seconds passed
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-... 47%, 331712 KB, 3314 KB/s, 100 seconds passed
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 .. parsed-literal::
 
-    ... 47%, 331744 KB, 3314 KB/s, 100 seconds passed
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+... 44%, 312064 KB, 3668 KB/s, 85 seconds passed
 
 .. parsed-literal::
 
-    ... 47%, 331936 KB, 3314 KB/s, 100 seconds passed
-... 47%, 331968 KB, 3314 KB/s, 100 seconds passed
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-... 47%, 332096 KB, 3314 KB/s, 100 seconds passed
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+... 44%, 312192 KB, 3667 KB/s, 85 seconds passed
+... 44%, 312224 KB, 3668 KB/s, 85 seconds passed
+... 44%, 312256 KB, 3668 KB/s, 85 seconds passed
 
 .. parsed-literal::
 
-    ... 47%, 332128 KB, 3314 KB/s, 100 seconds passed
-... 47%, 332160 KB, 3315 KB/s, 100 seconds passed
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-... 47%, 332256 KB, 3315 KB/s, 100 seconds passed
-... 47%, 332288 KB, 3315 KB/s, 100 seconds passed
+    ... 44%, 312288 KB, 3668 KB/s, 85 seconds passed
+... 44%, 312320 KB, 3668 KB/s, 85 seconds passed
+... 44%, 312352 KB, 3668 KB/s, 85 seconds passed
+... 44%, 312384 KB, 3668 KB/s, 85 seconds passed
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 .. parsed-literal::
 
-    ... 47%, 332320 KB, 3314 KB/s, 100 seconds passed
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-... 47%, 332480 KB, 3315 KB/s, 100 seconds passed
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 .. parsed-literal::
 
-    ... 47%, 332512 KB, 3315 KB/s, 100 seconds passed
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 .. parsed-literal::
 
-    ... 47%, 332704 KB, 3315 KB/s, 100 seconds passed
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 .. parsed-literal::
 
-    ... 47%, 332832 KB, 3314 KB/s, 100 seconds passed
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 .. parsed-literal::
 
-    ... 47%, 332960 KB, 3314 KB/s, 100 seconds passed
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 .. parsed-literal::
 
-    ... 47%, 333024 KB, 3313 KB/s, 100 seconds passed
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 .. parsed-literal::
 
-    ... 47%, 333184 KB, 3313 KB/s, 100 seconds passed
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 .. parsed-literal::
 
-    ... 47%, 333312 KB, 3313 KB/s, 100 seconds passed
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 .. parsed-literal::
 
-    ... 47%, 333568 KB, 3313 KB/s, 100 seconds passed
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 .. parsed-literal::
 
-    ... 47%, 333696 KB, 3313 KB/s, 100 seconds passed
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 .. parsed-literal::
 
-    ... 48%, 333952 KB, 3313 KB/s, 100 seconds passed
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 .. parsed-literal::
 
-    ... 48%, 334080 KB, 3313 KB/s, 100 seconds passed
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-... 48%, 334176 KB, 3314 KB/s, 100 seconds passed
-... 48%, 334208 KB, 3314 KB/s, 100 seconds passed
-... 48%, 334240 KB, 3314 KB/s, 100 seconds passed
-... 48%, 334272 KB, 3314 KB/s, 100 seconds passed
-... 48%, 334304 KB, 3314 KB/s, 100 seconds passed
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 .. parsed-literal::
 
-    ... 48%, 334336 KB, 3314 KB/s, 100 seconds passed
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 .. parsed-literal::
 
-    ... 48%, 334464 KB, 3314 KB/s, 100 seconds passed
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 .. parsed-literal::
 
-    ... 48%, 334720 KB, 3314 KB/s, 100 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 48%, 335104 KB, 3313 KB/s, 101 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 48%, 335456 KB, 3311 KB/s, 101 seconds passed
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 .. parsed-literal::
 
-    ... 48%, 335584 KB, 3311 KB/s, 101 seconds passed
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 .. parsed-literal::
 
-    ... 48%, 335808 KB, 3311 KB/s, 101 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 48%, 336192 KB, 3312 KB/s, 101 seconds passed
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 .. parsed-literal::
 
-    ... 48%, 336320 KB, 3312 KB/s, 101 seconds passed
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 .. parsed-literal::
 
-    ... 48%, 336576 KB, 3312 KB/s, 101 seconds passed
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 .. parsed-literal::
 
-    ... 48%, 336704 KB, 3312 KB/s, 101 seconds passed
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 .. parsed-literal::
 
-    ... 48%, 336928 KB, 3313 KB/s, 101 seconds passed
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 .. parsed-literal::
 
-    ... 48%, 337088 KB, 3313 KB/s, 101 seconds passed
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 .. parsed-literal::
 
-    ... 48%, 337312 KB, 3312 KB/s, 101 seconds passed
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 .. parsed-literal::
 
-    ... 48%, 337440 KB, 3313 KB/s, 101 seconds passed
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 .. parsed-literal::
 
-    ... 48%, 337472 KB, 3312 KB/s, 101 seconds passed
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 .. parsed-literal::
 
-    ... 48%, 337536 KB, 3310 KB/s, 101 seconds passed
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 .. parsed-literal::
 
-    ... 48%, 337568 KB, 3309 KB/s, 101 seconds passed
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 .. parsed-literal::
 
-    ... 48%, 337664 KB, 3308 KB/s, 102 seconds passed
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 .. parsed-literal::
 
-    ... 48%, 337728 KB, 3308 KB/s, 102 seconds passed
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-... 48%, 337792 KB, 3307 KB/s, 102 seconds passed
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-... 48%, 337856 KB, 3308 KB/s, 102 seconds passed
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+... 45%, 319200 KB, 3667 KB/s, 87 seconds passed
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 .. parsed-literal::
 
-    ... 48%, 337888 KB, 3307 KB/s, 102 seconds passed
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-... 48%, 337952 KB, 3307 KB/s, 102 seconds passed
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+... 45%, 319424 KB, 3668 KB/s, 87 seconds passed
 
 .. parsed-literal::
 
-    ... 48%, 337984 KB, 3307 KB/s, 102 seconds passed
-... 48%, 338016 KB, 3307 KB/s, 102 seconds passed
-... 48%, 338048 KB, 3307 KB/s, 102 seconds passed
-... 48%, 338080 KB, 3307 KB/s, 102 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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-... 50%, 350400 KB, 3308 KB/s, 105 seconds passed
-... 50%, 350432 KB, 3308 KB/s, 105 seconds passed
+    ... 47%, 332864 KB, 3668 KB/s, 90 seconds passed
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+... 47%, 332960 KB, 3668 KB/s, 90 seconds passed
+... 47%, 332992 KB, 3668 KB/s, 90 seconds passed
+... 47%, 333024 KB, 3668 KB/s, 90 seconds passed
 
 .. parsed-literal::
 
-    ... 50%, 350464 KB, 3307 KB/s, 105 seconds passed
-... 50%, 350496 KB, 3308 KB/s, 105 seconds passed
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-... 50%, 350592 KB, 3307 KB/s, 105 seconds passed
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+... 47%, 333152 KB, 3668 KB/s, 90 seconds passed
+... 47%, 333184 KB, 3668 KB/s, 90 seconds passed
+... 47%, 333216 KB, 3668 KB/s, 90 seconds passed
 
 .. parsed-literal::
 
-    ... 50%, 350624 KB, 3308 KB/s, 105 seconds passed
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-... 50%, 350784 KB, 3308 KB/s, 106 seconds passed
-... 50%, 350816 KB, 3308 KB/s, 106 seconds passed
+    ... 47%, 333248 KB, 3668 KB/s, 90 seconds passed
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+... 47%, 333344 KB, 3668 KB/s, 90 seconds passed
+... 47%, 333376 KB, 3668 KB/s, 90 seconds passed
+... 47%, 333408 KB, 3668 KB/s, 90 seconds passed
 
 .. parsed-literal::
 
-    ... 50%, 350848 KB, 3308 KB/s, 106 seconds passed
-... 50%, 350880 KB, 3308 KB/s, 106 seconds passed
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+... 47%, 333568 KB, 3668 KB/s, 90 seconds passed
+... 47%, 333600 KB, 3668 KB/s, 90 seconds passed
 
 .. parsed-literal::
 
-    ... 50%, 351008 KB, 3308 KB/s, 106 seconds passed
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-... 50%, 351200 KB, 3308 KB/s, 106 seconds passed
+    ... 47%, 333632 KB, 3668 KB/s, 90 seconds passed
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+... 47%, 333760 KB, 3668 KB/s, 90 seconds passed
+... 47%, 333792 KB, 3669 KB/s, 90 seconds passed
 
 .. parsed-literal::
 
-    ... 50%, 351232 KB, 3308 KB/s, 106 seconds passed
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+... 48%, 333984 KB, 3668 KB/s, 91 seconds passed
 
 .. parsed-literal::
 
-    ... 50%, 351360 KB, 3308 KB/s, 106 seconds passed
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-... 50%, 351520 KB, 3309 KB/s, 106 seconds passed
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 .. parsed-literal::
 
-    ... 50%, 351616 KB, 3308 KB/s, 106 seconds passed
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 .. parsed-literal::
 
-    ... 50%, 351744 KB, 3309 KB/s, 106 seconds passed
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 .. parsed-literal::
 
-    ... 50%, 351968 KB, 3309 KB/s, 106 seconds passed
-... 50%, 352000 KB, 3309 KB/s, 106 seconds passed
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-... 50%, 352096 KB, 3309 KB/s, 106 seconds passed
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+... 48%, 334720 KB, 3668 KB/s, 91 seconds passed
 
 .. parsed-literal::
 
-    ... 50%, 352128 KB, 3309 KB/s, 106 seconds passed
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 .. parsed-literal::
 
-    ... 50%, 352352 KB, 3309 KB/s, 106 seconds passed
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+... 48%, 335104 KB, 3668 KB/s, 91 seconds passed
 
 .. parsed-literal::
 
-    ... 50%, 352512 KB, 3309 KB/s, 106 seconds passed
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-... 50%, 352704 KB, 3310 KB/s, 106 seconds passed
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 .. parsed-literal::
 
-    ... 50%, 352736 KB, 3309 KB/s, 106 seconds passed
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 .. parsed-literal::
 
-    ... 50%, 352864 KB, 3310 KB/s, 106 seconds passed
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 .. parsed-literal::
 
-    ... 50%, 353120 KB, 3310 KB/s, 106 seconds passed
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 .. parsed-literal::
 
-    ... 50%, 353248 KB, 3310 KB/s, 106 seconds passed
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 .. parsed-literal::
 
-    ... 50%, 353504 KB, 3310 KB/s, 106 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 50%, 353888 KB, 3311 KB/s, 106 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 50%, 354272 KB, 3311 KB/s, 106 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 50%, 354624 KB, 3312 KB/s, 107 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 51%, 355392 KB, 3312 KB/s, 107 seconds passed
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 .. parsed-literal::
 
-    ... 51%, 355552 KB, 3312 KB/s, 107 seconds passed
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 .. parsed-literal::
 
-    ... 51%, 355776 KB, 3313 KB/s, 107 seconds passed
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 .. parsed-literal::
 
-    ... 51%, 355936 KB, 3313 KB/s, 107 seconds passed
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 .. parsed-literal::
 
-    ... 51%, 356160 KB, 3313 KB/s, 107 seconds passed
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 .. parsed-literal::
 
-    ... 51%, 356320 KB, 3313 KB/s, 107 seconds passed
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 .. parsed-literal::
 
-    ... 51%, 356544 KB, 3314 KB/s, 107 seconds passed
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 .. parsed-literal::
 
-    ... 51%, 356704 KB, 3313 KB/s, 107 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 53%, 369536 KB, 3325 KB/s, 111 seconds passed
-... 53%, 369568 KB, 3324 KB/s, 111 seconds passed
-... 53%, 369600 KB, 3325 KB/s, 111 seconds passed
-... 53%, 369632 KB, 3325 KB/s, 111 seconds passed
-... 53%, 369664 KB, 3325 KB/s, 111 seconds passed
+    ... 50%, 352128 KB, 3669 KB/s, 95 seconds passed
+... 50%, 352160 KB, 3669 KB/s, 95 seconds passed
+... 50%, 352192 KB, 3670 KB/s, 95 seconds passed
+... 50%, 352224 KB, 3670 KB/s, 95 seconds passed
+... 50%, 352256 KB, 3669 KB/s, 95 seconds passed
+... 50%, 352288 KB, 3669 KB/s, 95 seconds passed
+... 50%, 352320 KB, 3670 KB/s, 95 seconds passed
 
 .. parsed-literal::
 
-    ... 53%, 369696 KB, 3325 KB/s, 111 seconds passed
-... 53%, 369728 KB, 3325 KB/s, 111 seconds passed
-... 53%, 369760 KB, 3325 KB/s, 111 seconds passed
-... 53%, 369792 KB, 3325 KB/s, 111 seconds passed
-... 53%, 369824 KB, 3325 KB/s, 111 seconds passed
-... 53%, 369856 KB, 3325 KB/s, 111 seconds passed
+    ... 50%, 352352 KB, 3670 KB/s, 96 seconds passed
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+... 50%, 352416 KB, 3669 KB/s, 96 seconds passed
+... 50%, 352448 KB, 3669 KB/s, 96 seconds passed
+... 50%, 352480 KB, 3670 KB/s, 96 seconds passed
 
 .. parsed-literal::
 
-    ... 53%, 369888 KB, 3325 KB/s, 111 seconds passed
-... 53%, 369920 KB, 3325 KB/s, 111 seconds passed
-... 53%, 369952 KB, 3325 KB/s, 111 seconds passed
-... 53%, 369984 KB, 3325 KB/s, 111 seconds passed
-... 53%, 370016 KB, 3325 KB/s, 111 seconds passed
+    ... 50%, 352512 KB, 3669 KB/s, 96 seconds passed
+... 50%, 352544 KB, 3669 KB/s, 96 seconds passed
+... 50%, 352576 KB, 3670 KB/s, 96 seconds passed
+... 50%, 352608 KB, 3670 KB/s, 96 seconds passed
+... 50%, 352640 KB, 3669 KB/s, 96 seconds passed
+... 50%, 352672 KB, 3669 KB/s, 96 seconds passed
+... 50%, 352704 KB, 3669 KB/s, 96 seconds passed
 
 .. parsed-literal::
 
-    ... 53%, 370048 KB, 3325 KB/s, 111 seconds passed
-... 53%, 370080 KB, 3325 KB/s, 111 seconds passed
-... 53%, 370112 KB, 3325 KB/s, 111 seconds passed
-... 53%, 370144 KB, 3325 KB/s, 111 seconds passed
-... 53%, 370176 KB, 3325 KB/s, 111 seconds passed
-... 53%, 370208 KB, 3325 KB/s, 111 seconds passed
-... 53%, 370240 KB, 3325 KB/s, 111 seconds passed
+    ... 50%, 352736 KB, 3670 KB/s, 96 seconds passed
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+... 50%, 352800 KB, 3669 KB/s, 96 seconds passed
+... 50%, 352832 KB, 3669 KB/s, 96 seconds passed
+... 50%, 352864 KB, 3670 KB/s, 96 seconds passed
 
 .. parsed-literal::
 
-    ... 53%, 370272 KB, 3325 KB/s, 111 seconds passed
-... 53%, 370304 KB, 3325 KB/s, 111 seconds passed
-... 53%, 370336 KB, 3325 KB/s, 111 seconds passed
-... 53%, 370368 KB, 3325 KB/s, 111 seconds passed
-... 53%, 370400 KB, 3326 KB/s, 111 seconds passed
+    ... 50%, 352896 KB, 3669 KB/s, 96 seconds passed
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+... 50%, 352960 KB, 3670 KB/s, 96 seconds passed
+... 50%, 352992 KB, 3670 KB/s, 96 seconds passed
+... 50%, 353024 KB, 3669 KB/s, 96 seconds passed
+... 50%, 353056 KB, 3669 KB/s, 96 seconds passed
 
 .. parsed-literal::
 
-    ... 53%, 370432 KB, 3325 KB/s, 111 seconds passed
-... 53%, 370464 KB, 3325 KB/s, 111 seconds passed
-... 53%, 370496 KB, 3325 KB/s, 111 seconds passed
-... 53%, 370528 KB, 3326 KB/s, 111 seconds passed
-... 53%, 370560 KB, 3325 KB/s, 111 seconds passed
-... 53%, 370592 KB, 3325 KB/s, 111 seconds passed
-... 53%, 370624 KB, 3326 KB/s, 111 seconds passed
+    ... 50%, 353088 KB, 3669 KB/s, 96 seconds passed
+... 50%, 353120 KB, 3670 KB/s, 96 seconds passed
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+... 50%, 353184 KB, 3669 KB/s, 96 seconds passed
+... 50%, 353216 KB, 3669 KB/s, 96 seconds passed
+... 50%, 353248 KB, 3670 KB/s, 96 seconds passed
 
 .. parsed-literal::
 
-    ... 53%, 370656 KB, 3326 KB/s, 111 seconds passed
-... 53%, 370688 KB, 3325 KB/s, 111 seconds passed
-... 53%, 370720 KB, 3325 KB/s, 111 seconds passed
-... 53%, 370752 KB, 3326 KB/s, 111 seconds passed
-... 53%, 370784 KB, 3326 KB/s, 111 seconds passed
+    ... 50%, 353280 KB, 3669 KB/s, 96 seconds passed
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+... 50%, 353344 KB, 3670 KB/s, 96 seconds passed
+... 50%, 353376 KB, 3670 KB/s, 96 seconds passed
+... 50%, 353408 KB, 3669 KB/s, 96 seconds passed
+... 50%, 353440 KB, 3669 KB/s, 96 seconds passed
 
 .. parsed-literal::
 
-    ... 53%, 370816 KB, 3326 KB/s, 111 seconds passed
-... 53%, 370848 KB, 3326 KB/s, 111 seconds passed
-... 53%, 370880 KB, 3326 KB/s, 111 seconds passed
-... 53%, 370912 KB, 3326 KB/s, 111 seconds passed
-... 53%, 370944 KB, 3326 KB/s, 111 seconds passed
-... 53%, 370976 KB, 3326 KB/s, 111 seconds passed
+    ... 50%, 353472 KB, 3670 KB/s, 96 seconds passed
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+... 50%, 353568 KB, 3669 KB/s, 96 seconds passed
+... 50%, 353600 KB, 3670 KB/s, 96 seconds passed
+... 50%, 353632 KB, 3670 KB/s, 96 seconds passed
 
 .. parsed-literal::
 
-    ... 53%, 371008 KB, 3326 KB/s, 111 seconds passed
-... 53%, 371040 KB, 3326 KB/s, 111 seconds passed
-... 53%, 371072 KB, 3326 KB/s, 111 seconds passed
-... 53%, 371104 KB, 3326 KB/s, 111 seconds passed
-... 53%, 371136 KB, 3326 KB/s, 111 seconds passed
-... 53%, 371168 KB, 3326 KB/s, 111 seconds passed
+    ... 50%, 353664 KB, 3669 KB/s, 96 seconds passed
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+... 50%, 353728 KB, 3670 KB/s, 96 seconds passed
+... 50%, 353760 KB, 3670 KB/s, 96 seconds passed
+... 50%, 353792 KB, 3669 KB/s, 96 seconds passed
+... 50%, 353824 KB, 3669 KB/s, 96 seconds passed
+... 50%, 353856 KB, 3670 KB/s, 96 seconds passed
 
 .. parsed-literal::
 
-    ... 53%, 371200 KB, 3326 KB/s, 111 seconds passed
-... 53%, 371232 KB, 3326 KB/s, 111 seconds passed
-... 53%, 371264 KB, 3326 KB/s, 111 seconds passed
-... 53%, 371296 KB, 3326 KB/s, 111 seconds passed
-... 53%, 371328 KB, 3326 KB/s, 111 seconds passed
+    ... 50%, 353888 KB, 3670 KB/s, 96 seconds passed
+... 50%, 353920 KB, 3669 KB/s, 96 seconds passed
+... 50%, 353952 KB, 3669 KB/s, 96 seconds passed
+... 50%, 353984 KB, 3670 KB/s, 96 seconds passed
 
 .. parsed-literal::
 
-    ... 53%, 371360 KB, 3326 KB/s, 111 seconds passed
-... 53%, 371392 KB, 3326 KB/s, 111 seconds passed
-... 53%, 371424 KB, 3326 KB/s, 111 seconds passed
-... 53%, 371456 KB, 3326 KB/s, 111 seconds passed
-... 53%, 371488 KB, 3326 KB/s, 111 seconds passed
-... 53%, 371520 KB, 3326 KB/s, 111 seconds passed
-... 53%, 371552 KB, 3327 KB/s, 111 seconds passed
+    ... 50%, 354016 KB, 3669 KB/s, 96 seconds passed
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+... 50%, 354112 KB, 3670 KB/s, 96 seconds passed
+... 50%, 354144 KB, 3669 KB/s, 96 seconds passed
+... 50%, 354176 KB, 3669 KB/s, 96 seconds passed
+... 50%, 354208 KB, 3670 KB/s, 96 seconds passed
 
 .. parsed-literal::
 
-    ... 53%, 371584 KB, 3326 KB/s, 111 seconds passed
-... 53%, 371616 KB, 3326 KB/s, 111 seconds passed
-... 53%, 371648 KB, 3327 KB/s, 111 seconds passed
-... 53%, 371680 KB, 3327 KB/s, 111 seconds passed
-... 53%, 371712 KB, 3326 KB/s, 111 seconds passed
+    ... 50%, 354240 KB, 3670 KB/s, 96 seconds passed
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+... 50%, 354304 KB, 3669 KB/s, 96 seconds passed
+... 50%, 354336 KB, 3670 KB/s, 96 seconds passed
+... 50%, 354368 KB, 3670 KB/s, 96 seconds passed
+... 50%, 354400 KB, 3670 KB/s, 96 seconds passed
 
 .. parsed-literal::
 
-    ... 53%, 371744 KB, 3326 KB/s, 111 seconds passed
-... 53%, 371776 KB, 3327 KB/s, 111 seconds passed
-... 53%, 371808 KB, 3327 KB/s, 111 seconds passed
-... 53%, 371840 KB, 3326 KB/s, 111 seconds passed
-... 53%, 371872 KB, 3327 KB/s, 111 seconds passed
-... 53%, 371904 KB, 3327 KB/s, 111 seconds passed
-... 53%, 371936 KB, 3327 KB/s, 111 seconds passed
+    ... 50%, 354432 KB, 3669 KB/s, 96 seconds passed
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+... 50%, 354528 KB, 3670 KB/s, 96 seconds passed
+... 50%, 354560 KB, 3669 KB/s, 96 seconds passed
+... 50%, 354592 KB, 3670 KB/s, 96 seconds passed
 
 .. parsed-literal::
 
-    ... 53%, 371968 KB, 3327 KB/s, 111 seconds passed
-... 53%, 372000 KB, 3327 KB/s, 111 seconds passed
-... 53%, 372032 KB, 3327 KB/s, 111 seconds passed
-... 53%, 372064 KB, 3327 KB/s, 111 seconds passed
-... 53%, 372096 KB, 3327 KB/s, 111 seconds passed
+    ... 50%, 354624 KB, 3670 KB/s, 96 seconds passed
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+... 51%, 354720 KB, 3669 KB/s, 96 seconds passed
+... 51%, 354752 KB, 3670 KB/s, 96 seconds passed
+... 51%, 354784 KB, 3670 KB/s, 96 seconds passed
 
 .. parsed-literal::
 
-    ... 53%, 372128 KB, 3327 KB/s, 111 seconds passed
-... 53%, 372160 KB, 3327 KB/s, 111 seconds passed
-... 53%, 372192 KB, 3327 KB/s, 111 seconds passed
-... 53%, 372224 KB, 3327 KB/s, 111 seconds passed
-... 53%, 372256 KB, 3327 KB/s, 111 seconds passed
-... 53%, 372288 KB, 3327 KB/s, 111 seconds passed
-... 53%, 372320 KB, 3327 KB/s, 111 seconds passed
+    ... 51%, 354816 KB, 3669 KB/s, 96 seconds passed
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+... 51%, 354880 KB, 3670 KB/s, 96 seconds passed
+... 51%, 354912 KB, 3669 KB/s, 96 seconds passed
+... 51%, 354944 KB, 3669 KB/s, 96 seconds passed
 
 .. parsed-literal::
 
-    ... 53%, 372352 KB, 3327 KB/s, 111 seconds passed
-... 53%, 372384 KB, 3327 KB/s, 111 seconds passed
-... 53%, 372416 KB, 3327 KB/s, 111 seconds passed
-... 53%, 372448 KB, 3327 KB/s, 111 seconds passed
-... 53%, 372480 KB, 3327 KB/s, 111 seconds passed
+    ... 51%, 354976 KB, 3669 KB/s, 96 seconds passed
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+... 51%, 355072 KB, 3669 KB/s, 96 seconds passed
+... 51%, 355104 KB, 3670 KB/s, 96 seconds passed
+... 51%, 355136 KB, 3670 KB/s, 96 seconds passed
 
 .. parsed-literal::
 
-    ... 53%, 372512 KB, 3327 KB/s, 111 seconds passed
-... 53%, 372544 KB, 3327 KB/s, 111 seconds passed
-... 53%, 372576 KB, 3327 KB/s, 111 seconds passed
-... 53%, 372608 KB, 3327 KB/s, 111 seconds passed
-... 53%, 372640 KB, 3327 KB/s, 111 seconds passed
-... 53%, 372672 KB, 3327 KB/s, 111 seconds passed
-... 53%, 372704 KB, 3328 KB/s, 111 seconds passed
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+... 51%, 355264 KB, 3670 KB/s, 96 seconds passed
+... 51%, 355296 KB, 3669 KB/s, 96 seconds passed
+... 51%, 355328 KB, 3669 KB/s, 96 seconds passed
 
 .. parsed-literal::
 
-    ... 53%, 372736 KB, 3327 KB/s, 112 seconds passed
-... 53%, 372768 KB, 3327 KB/s, 112 seconds passed
-... 53%, 372800 KB, 3328 KB/s, 112 seconds passed
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-... 53%, 372864 KB, 3327 KB/s, 112 seconds passed
+    ... 51%, 355360 KB, 3669 KB/s, 96 seconds passed
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+... 51%, 355488 KB, 3669 KB/s, 96 seconds passed
+... 51%, 355520 KB, 3670 KB/s, 96 seconds passed
 
 .. parsed-literal::
 
-    ... 53%, 372896 KB, 3327 KB/s, 112 seconds passed
-... 53%, 372928 KB, 3328 KB/s, 112 seconds passed
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-... 53%, 373056 KB, 3328 KB/s, 112 seconds passed
-... 53%, 373088 KB, 3328 KB/s, 112 seconds passed
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+... 51%, 355712 KB, 3669 KB/s, 96 seconds passed
 
 .. parsed-literal::
 
-    ... 53%, 373120 KB, 3328 KB/s, 112 seconds passed
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-... 53%, 373216 KB, 3328 KB/s, 112 seconds passed
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 .. parsed-literal::
 
-    ... 53%, 373248 KB, 3328 KB/s, 112 seconds passed
-... 53%, 373280 KB, 3328 KB/s, 112 seconds passed
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-... 53%, 373440 KB, 3328 KB/s, 112 seconds passed
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 .. parsed-literal::
 
-    ... 53%, 373472 KB, 3328 KB/s, 112 seconds passed
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-... 53%, 373600 KB, 3328 KB/s, 112 seconds passed
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 .. parsed-literal::
 
-    ... 53%, 373632 KB, 3328 KB/s, 112 seconds passed
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-... 53%, 373760 KB, 3328 KB/s, 112 seconds passed
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-... 53%, 373824 KB, 3328 KB/s, 112 seconds passed
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+... 51%, 356448 KB, 3669 KB/s, 97 seconds passed
+... 51%, 356480 KB, 3670 KB/s, 97 seconds passed
 
 .. parsed-literal::
 
-    ... 53%, 373856 KB, 3328 KB/s, 112 seconds passed
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 .. parsed-literal::
 
-    ... 53%, 374016 KB, 3328 KB/s, 112 seconds passed
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-... 53%, 374208 KB, 3329 KB/s, 112 seconds passed
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 .. parsed-literal::
 
-    ... 53%, 374240 KB, 3328 KB/s, 112 seconds passed
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+    ... 51%, 356896 KB, 3670 KB/s, 97 seconds passed
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 .. parsed-literal::
 
-    ... 53%, 374400 KB, 3329 KB/s, 112 seconds passed
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-... 53%, 374592 KB, 3329 KB/s, 112 seconds passed
+    ... 51%, 357088 KB, 3669 KB/s, 97 seconds passed
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 .. parsed-literal::
 
-    ... 53%, 374624 KB, 3329 KB/s, 112 seconds passed
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+... 51%, 357344 KB, 3669 KB/s, 97 seconds passed
 
 .. parsed-literal::
 
-    ... 53%, 374784 KB, 3329 KB/s, 112 seconds passed
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+    ... 51%, 357376 KB, 3668 KB/s, 97 seconds passed
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+... 51%, 357472 KB, 3669 KB/s, 97 seconds passed
 
 .. parsed-literal::
 
-    ... 53%, 375008 KB, 3329 KB/s, 112 seconds passed
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-... 53%, 375072 KB, 3329 KB/s, 112 seconds passed
-... 53%, 375104 KB, 3330 KB/s, 112 seconds passed
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+    ... 51%, 357504 KB, 3668 KB/s, 97 seconds passed
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+... 51%, 357728 KB, 3669 KB/s, 97 seconds passed
+... 51%, 357760 KB, 3669 KB/s, 97 seconds passed
 
 .. parsed-literal::
 
-    ... 53%, 375168 KB, 3329 KB/s, 112 seconds passed
-... 53%, 375200 KB, 3329 KB/s, 112 seconds passed
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-... 53%, 375296 KB, 3329 KB/s, 112 seconds passed
-... 53%, 375328 KB, 3330 KB/s, 112 seconds passed
-... 53%, 375360 KB, 3330 KB/s, 112 seconds passed
+    ... 51%, 357792 KB, 3668 KB/s, 97 seconds passed
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+... 51%, 357856 KB, 3669 KB/s, 97 seconds passed
 
 .. parsed-literal::
 
-    ... 53%, 375392 KB, 3329 KB/s, 112 seconds passed
-... 53%, 375424 KB, 3330 KB/s, 112 seconds passed
-... 53%, 375456 KB, 3330 KB/s, 112 seconds passed
-... 53%, 375488 KB, 3330 KB/s, 112 seconds passed
+    ... 51%, 357888 KB, 3668 KB/s, 97 seconds passed
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+... 51%, 358080 KB, 3669 KB/s, 97 seconds passed
+... 51%, 358112 KB, 3669 KB/s, 97 seconds passed
 
 .. parsed-literal::
 
-    ... 53%, 375520 KB, 3330 KB/s, 112 seconds passed
-... 53%, 375552 KB, 3330 KB/s, 112 seconds passed
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-... 54%, 375616 KB, 3330 KB/s, 112 seconds passed
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-... 54%, 375680 KB, 3330 KB/s, 112 seconds passed
-... 54%, 375712 KB, 3330 KB/s, 112 seconds passed
-... 54%, 375744 KB, 3330 KB/s, 112 seconds passed
+    ... 51%, 358144 KB, 3668 KB/s, 97 seconds passed
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+... 51%, 358208 KB, 3669 KB/s, 97 seconds passed
+... 51%, 358240 KB, 3669 KB/s, 97 seconds passed
 
 .. parsed-literal::
 
-    ... 54%, 375776 KB, 3330 KB/s, 112 seconds passed
-... 54%, 375808 KB, 3330 KB/s, 112 seconds passed
-... 54%, 375840 KB, 3330 KB/s, 112 seconds passed
-... 54%, 375872 KB, 3330 KB/s, 112 seconds passed
+    ... 51%, 358272 KB, 3668 KB/s, 97 seconds passed
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+... 51%, 358464 KB, 3669 KB/s, 97 seconds passed
+... 51%, 358496 KB, 3669 KB/s, 97 seconds passed
+... 51%, 358528 KB, 3669 KB/s, 97 seconds passed
 
 .. parsed-literal::
 
-    ... 54%, 375904 KB, 3330 KB/s, 112 seconds passed
-... 54%, 375936 KB, 3330 KB/s, 112 seconds passed
-... 54%, 375968 KB, 3330 KB/s, 112 seconds passed
-... 54%, 376000 KB, 3330 KB/s, 112 seconds passed
-... 54%, 376032 KB, 3330 KB/s, 112 seconds passed
-... 54%, 376064 KB, 3330 KB/s, 112 seconds passed
-... 54%, 376096 KB, 3330 KB/s, 112 seconds passed
-... 54%, 376128 KB, 3330 KB/s, 112 seconds passed
+    ... 51%, 358560 KB, 3668 KB/s, 97 seconds passed
+... 51%, 358592 KB, 3669 KB/s, 97 seconds passed
+... 51%, 358624 KB, 3669 KB/s, 97 seconds passed
+... 51%, 358656 KB, 3669 KB/s, 97 seconds passed
 
 .. parsed-literal::
 
-    ... 54%, 376160 KB, 3330 KB/s, 112 seconds passed
-... 54%, 376192 KB, 3330 KB/s, 112 seconds passed
-... 54%, 376224 KB, 3330 KB/s, 112 seconds passed
-... 54%, 376256 KB, 3331 KB/s, 112 seconds passed
+    ... 51%, 358688 KB, 3668 KB/s, 97 seconds passed
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+... 51%, 358816 KB, 3668 KB/s, 97 seconds passed
+... 51%, 358848 KB, 3669 KB/s, 97 seconds passed
+... 51%, 358880 KB, 3669 KB/s, 97 seconds passed
 
 .. parsed-literal::
 
-    ... 54%, 376288 KB, 3330 KB/s, 112 seconds passed
-... 54%, 376320 KB, 3330 KB/s, 112 seconds passed
-... 54%, 376352 KB, 3330 KB/s, 112 seconds passed
-... 54%, 376384 KB, 3331 KB/s, 112 seconds passed
-... 54%, 376416 KB, 3330 KB/s, 113 seconds passed
-... 54%, 376448 KB, 3330 KB/s, 113 seconds passed
-... 54%, 376480 KB, 3331 KB/s, 113 seconds passed
+    ... 51%, 358912 KB, 3668 KB/s, 97 seconds passed
+... 51%, 358944 KB, 3668 KB/s, 97 seconds passed
+... 51%, 358976 KB, 3669 KB/s, 97 seconds passed
+... 51%, 359008 KB, 3669 KB/s, 97 seconds passed
 
 .. parsed-literal::
 
-    ... 54%, 376512 KB, 3331 KB/s, 113 seconds passed
-... 54%, 376544 KB, 3330 KB/s, 113 seconds passed
-... 54%, 376576 KB, 3331 KB/s, 113 seconds passed
-... 54%, 376608 KB, 3331 KB/s, 113 seconds passed
-... 54%, 376640 KB, 3331 KB/s, 113 seconds passed
+    ... 51%, 359040 KB, 3668 KB/s, 97 seconds passed
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+... 51%, 359200 KB, 3669 KB/s, 97 seconds passed
+... 51%, 359232 KB, 3669 KB/s, 97 seconds passed
+... 51%, 359264 KB, 3669 KB/s, 97 seconds passed
 
 .. parsed-literal::
 
-    ... 54%, 376672 KB, 3331 KB/s, 113 seconds passed
-... 54%, 376704 KB, 3331 KB/s, 113 seconds passed
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-... 54%, 376800 KB, 3331 KB/s, 113 seconds passed
-... 54%, 376832 KB, 3331 KB/s, 113 seconds passed
+    ... 51%, 359296 KB, 3668 KB/s, 97 seconds passed
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+... 51%, 359360 KB, 3669 KB/s, 97 seconds passed
+... 51%, 359392 KB, 3669 KB/s, 97 seconds passed
 
 .. parsed-literal::
 
-    ... 54%, 376864 KB, 3331 KB/s, 113 seconds passed
-... 54%, 376896 KB, 3331 KB/s, 113 seconds passed
-... 54%, 376928 KB, 3331 KB/s, 113 seconds passed
-... 54%, 376960 KB, 3331 KB/s, 113 seconds passed
-... 54%, 376992 KB, 3331 KB/s, 113 seconds passed
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+    ... 51%, 359424 KB, 3668 KB/s, 97 seconds passed
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+... 51%, 359520 KB, 3669 KB/s, 97 seconds passed
+... 51%, 359552 KB, 3668 KB/s, 98 seconds passed
+... 51%, 359584 KB, 3669 KB/s, 98 seconds passed
 
 .. parsed-literal::
 
-    ... 54%, 377056 KB, 3331 KB/s, 113 seconds passed
-... 54%, 377088 KB, 3331 KB/s, 113 seconds passed
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-... 54%, 377152 KB, 3331 KB/s, 113 seconds passed
-... 54%, 377184 KB, 3331 KB/s, 113 seconds passed
-... 54%, 377216 KB, 3331 KB/s, 113 seconds passed
+    ... 51%, 359616 KB, 3669 KB/s, 98 seconds passed
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+... 51%, 359744 KB, 3669 KB/s, 98 seconds passed
+... 51%, 359776 KB, 3669 KB/s, 98 seconds passed
 
 .. parsed-literal::
 
-    ... 54%, 377248 KB, 3331 KB/s, 113 seconds passed
-... 54%, 377280 KB, 3331 KB/s, 113 seconds passed
-... 54%, 377312 KB, 3331 KB/s, 113 seconds passed
-... 54%, 377344 KB, 3331 KB/s, 113 seconds passed
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-... 54%, 377408 KB, 3332 KB/s, 113 seconds passed
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+... 51%, 359904 KB, 3669 KB/s, 98 seconds passed
+... 51%, 359936 KB, 3668 KB/s, 98 seconds passed
 
 .. parsed-literal::
 
-    ... 54%, 377440 KB, 3331 KB/s, 113 seconds passed
-... 54%, 377472 KB, 3331 KB/s, 113 seconds passed
-... 54%, 377504 KB, 3331 KB/s, 113 seconds passed
-... 54%, 377536 KB, 3332 KB/s, 113 seconds passed
-... 54%, 377568 KB, 3331 KB/s, 113 seconds passed
-... 54%, 377600 KB, 3331 KB/s, 113 seconds passed
+    ... 51%, 359968 KB, 3669 KB/s, 98 seconds passed
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+... 51%, 360096 KB, 3669 KB/s, 98 seconds passed
+... 51%, 360128 KB, 3669 KB/s, 98 seconds passed
+... 51%, 360160 KB, 3669 KB/s, 98 seconds passed
 
 .. parsed-literal::
 
-    ... 54%, 377632 KB, 3332 KB/s, 113 seconds passed
-... 54%, 377664 KB, 3332 KB/s, 113 seconds passed
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-... 54%, 377728 KB, 3332 KB/s, 113 seconds passed
-... 54%, 377760 KB, 3332 KB/s, 113 seconds passed
-... 54%, 377792 KB, 3332 KB/s, 113 seconds passed
+    ... 51%, 360192 KB, 3668 KB/s, 98 seconds passed
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+... 51%, 360256 KB, 3669 KB/s, 98 seconds passed
+... 51%, 360288 KB, 3669 KB/s, 98 seconds passed
+... 51%, 360320 KB, 3668 KB/s, 98 seconds passed
 
 .. parsed-literal::
 
-    ... 54%, 377824 KB, 3331 KB/s, 113 seconds passed
-... 54%, 377856 KB, 3332 KB/s, 113 seconds passed
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-... 54%, 377920 KB, 3332 KB/s, 113 seconds passed
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-... 54%, 377984 KB, 3332 KB/s, 113 seconds passed
+    ... 51%, 360352 KB, 3669 KB/s, 98 seconds passed
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+... 51%, 360512 KB, 3669 KB/s, 98 seconds passed
+... 51%, 360544 KB, 3669 KB/s, 98 seconds passed
 
 .. parsed-literal::
 
-    ... 54%, 378016 KB, 3332 KB/s, 113 seconds passed
-... 54%, 378048 KB, 3332 KB/s, 113 seconds passed
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-... 54%, 378112 KB, 3332 KB/s, 113 seconds passed
-... 54%, 378144 KB, 3332 KB/s, 113 seconds passed
-... 54%, 378176 KB, 3332 KB/s, 113 seconds passed
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+... 51%, 360672 KB, 3669 KB/s, 98 seconds passed
 
 .. parsed-literal::
 
-    ... 54%, 378208 KB, 3332 KB/s, 113 seconds passed
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-... 54%, 378272 KB, 3332 KB/s, 113 seconds passed
-... 54%, 378304 KB, 3332 KB/s, 113 seconds passed
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-... 54%, 378368 KB, 3332 KB/s, 113 seconds passed
+    ... 51%, 360704 KB, 3668 KB/s, 98 seconds passed
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+... 51%, 360896 KB, 3669 KB/s, 98 seconds passed
+... 51%, 360928 KB, 3669 KB/s, 98 seconds passed
 
 .. parsed-literal::
 
-    ... 54%, 378400 KB, 3332 KB/s, 113 seconds passed
-... 54%, 378432 KB, 3332 KB/s, 113 seconds passed
-... 54%, 378464 KB, 3332 KB/s, 113 seconds passed
-... 54%, 378496 KB, 3332 KB/s, 113 seconds passed
-... 54%, 378528 KB, 3332 KB/s, 113 seconds passed
-... 54%, 378560 KB, 3333 KB/s, 113 seconds passed
+    ... 51%, 360960 KB, 3668 KB/s, 98 seconds passed
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+... 51%, 361024 KB, 3669 KB/s, 98 seconds passed
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 .. parsed-literal::
 
-    ... 54%, 378592 KB, 3332 KB/s, 113 seconds passed
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-... 54%, 378656 KB, 3332 KB/s, 113 seconds passed
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+... 51%, 361280 KB, 3669 KB/s, 98 seconds passed
+... 51%, 361312 KB, 3669 KB/s, 98 seconds passed
 
 .. parsed-literal::
 
-    ... 54%, 378752 KB, 3332 KB/s, 113 seconds passed
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-... 54%, 378880 KB, 3333 KB/s, 113 seconds passed
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+    ... 51%, 361344 KB, 3668 KB/s, 98 seconds passed
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+... 51%, 361440 KB, 3669 KB/s, 98 seconds passed
 
 .. parsed-literal::
 
-    ... 54%, 378976 KB, 3332 KB/s, 113 seconds passed
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-... 54%, 379104 KB, 3333 KB/s, 113 seconds passed
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 .. parsed-literal::
 
-    ... 54%, 379136 KB, 3333 KB/s, 113 seconds passed
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 .. parsed-literal::
 
-    ... 54%, 379328 KB, 3333 KB/s, 113 seconds passed
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 .. parsed-literal::
 
-    ... 54%, 379488 KB, 3333 KB/s, 113 seconds passed
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+    ... 52%, 362112 KB, 3669 KB/s, 98 seconds passed
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 .. parsed-literal::
 
-    ... 54%, 379712 KB, 3333 KB/s, 113 seconds passed
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 .. parsed-literal::
 
-    ... 54%, 379872 KB, 3333 KB/s, 113 seconds passed
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 .. parsed-literal::
 
-    ... 54%, 380096 KB, 3333 KB/s, 114 seconds passed
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 .. parsed-literal::
 
-    ... 54%, 380256 KB, 3334 KB/s, 114 seconds passed
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 .. parsed-literal::
 
-    ... 54%, 380480 KB, 3334 KB/s, 114 seconds passed
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 .. parsed-literal::
 
-    ... 54%, 380608 KB, 3334 KB/s, 114 seconds passed
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 .. parsed-literal::
 
-    ... 54%, 380864 KB, 3334 KB/s, 114 seconds passed
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 .. parsed-literal::
 
-    ... 54%, 380992 KB, 3334 KB/s, 114 seconds passed
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 .. parsed-literal::
 
-    ... 54%, 381248 KB, 3334 KB/s, 114 seconds passed
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 .. parsed-literal::
 
-    ... 54%, 381376 KB, 3334 KB/s, 114 seconds passed
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 .. parsed-literal::
 
-    ... 54%, 381600 KB, 3335 KB/s, 114 seconds passed
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+... 52%, 364288 KB, 3669 KB/s, 99 seconds passed
+... 52%, 364320 KB, 3669 KB/s, 99 seconds passed
+... 52%, 364352 KB, 3669 KB/s, 99 seconds passed
 
 .. parsed-literal::
 
-    ... 54%, 381760 KB, 3335 KB/s, 114 seconds passed
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-... 54%, 381952 KB, 3335 KB/s, 114 seconds passed
+    ... 52%, 364384 KB, 3669 KB/s, 99 seconds passed
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+... 52%, 364448 KB, 3669 KB/s, 99 seconds passed
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 .. parsed-literal::
 
-    ... 54%, 381984 KB, 3335 KB/s, 114 seconds passed
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-... 54%, 382048 KB, 3335 KB/s, 114 seconds passed
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-... 54%, 382112 KB, 3335 KB/s, 114 seconds passed
+    ... 52%, 364512 KB, 3669 KB/s, 99 seconds passed
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+... 52%, 364672 KB, 3669 KB/s, 99 seconds passed
+... 52%, 364704 KB, 3669 KB/s, 99 seconds passed
 
 .. parsed-literal::
 
-    ... 54%, 382144 KB, 3335 KB/s, 114 seconds passed
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-... 54%, 382272 KB, 3335 KB/s, 114 seconds passed
-... 54%, 382304 KB, 3335 KB/s, 114 seconds passed
-... 54%, 382336 KB, 3335 KB/s, 114 seconds passed
+    ... 52%, 364736 KB, 3669 KB/s, 99 seconds passed
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+... 52%, 364800 KB, 3669 KB/s, 99 seconds passed
+... 52%, 364832 KB, 3669 KB/s, 99 seconds passed
+... 52%, 364864 KB, 3669 KB/s, 99 seconds passed
 
 .. parsed-literal::
 
-    ... 54%, 382368 KB, 3336 KB/s, 114 seconds passed
-... 54%, 382400 KB, 3335 KB/s, 114 seconds passed
-... 54%, 382432 KB, 3335 KB/s, 114 seconds passed
-... 54%, 382464 KB, 3336 KB/s, 114 seconds passed
+    ... 52%, 364896 KB, 3669 KB/s, 99 seconds passed
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+... 52%, 365056 KB, 3669 KB/s, 99 seconds passed
+... 52%, 365088 KB, 3669 KB/s, 99 seconds passed
 
 .. parsed-literal::
 
-    ... 54%, 382496 KB, 3335 KB/s, 114 seconds passed
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-... 55%, 382656 KB, 3335 KB/s, 114 seconds passed
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+... 52%, 365216 KB, 3669 KB/s, 99 seconds passed
+... 52%, 365248 KB, 3669 KB/s, 99 seconds passed
 
 .. parsed-literal::
 
-    ... 55%, 382752 KB, 3335 KB/s, 114 seconds passed
-... 55%, 382784 KB, 3336 KB/s, 114 seconds passed
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+    ... 52%, 365280 KB, 3669 KB/s, 99 seconds passed
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+... 52%, 365408 KB, 3669 KB/s, 99 seconds passed
+... 52%, 365440 KB, 3669 KB/s, 99 seconds passed
 
 .. parsed-literal::
 
-    ... 55%, 382880 KB, 3336 KB/s, 114 seconds passed
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+    ... 52%, 365472 KB, 3669 KB/s, 99 seconds passed
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+... 52%, 365600 KB, 3669 KB/s, 99 seconds passed
+... 52%, 365632 KB, 3669 KB/s, 99 seconds passed
 
 .. parsed-literal::
 
-    ... 55%, 383104 KB, 3336 KB/s, 114 seconds passed
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+... 52%, 365792 KB, 3669 KB/s, 99 seconds passed
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 .. parsed-literal::
 
-    ... 55%, 383264 KB, 3336 KB/s, 114 seconds passed
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+... 52%, 366016 KB, 3669 KB/s, 99 seconds passed
 
 .. parsed-literal::
 
-    ... 55%, 383488 KB, 3336 KB/s, 114 seconds passed
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+... 52%, 366208 KB, 3669 KB/s, 99 seconds passed
 
 .. parsed-literal::
 
-    ... 55%, 383648 KB, 3336 KB/s, 114 seconds passed
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+... 52%, 366368 KB, 3669 KB/s, 99 seconds passed
+... 52%, 366400 KB, 3669 KB/s, 99 seconds passed
 
 .. parsed-literal::
 
-    ... 55%, 383872 KB, 3337 KB/s, 115 seconds passed
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+... 52%, 366560 KB, 3669 KB/s, 99 seconds passed
+... 52%, 366592 KB, 3669 KB/s, 99 seconds passed
 
 .. parsed-literal::
 
-    ... 55%, 384032 KB, 3336 KB/s, 115 seconds passed
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 .. parsed-literal::
 
-    ... 55%, 384256 KB, 3337 KB/s, 115 seconds passed
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+... 52%, 366912 KB, 3669 KB/s, 100 seconds passed
+... 52%, 366944 KB, 3669 KB/s, 100 seconds passed
 
 .. parsed-literal::
 
-    ... 55%, 384416 KB, 3337 KB/s, 115 seconds passed
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 .. parsed-literal::
 
-    ... 55%, 384608 KB, 3337 KB/s, 115 seconds passed
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 .. parsed-literal::
 
-    ... 55%, 384768 KB, 3337 KB/s, 115 seconds passed
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 .. parsed-literal::
 
-    ... 55%, 384992 KB, 3338 KB/s, 115 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 55%, 385728 KB, 3338 KB/s, 115 seconds passed
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 .. parsed-literal::
 
-    ... 55%, 385920 KB, 3338 KB/s, 115 seconds passed
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 .. parsed-literal::
 
-    ... 55%, 386080 KB, 3338 KB/s, 115 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 55%, 386432 KB, 3338 KB/s, 115 seconds passed
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 .. parsed-literal::
 
-    ... 55%, 386688 KB, 3338 KB/s, 115 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 55%, 387072 KB, 3339 KB/s, 115 seconds passed
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 .. parsed-literal::
 
-    ... 55%, 387200 KB, 3339 KB/s, 115 seconds passed
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 .. parsed-literal::
 
-    ... 55%, 387424 KB, 3339 KB/s, 116 seconds passed
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 .. parsed-literal::
 
-    ... 55%, 387552 KB, 3339 KB/s, 116 seconds passed
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 .. parsed-literal::
 
-    ... 55%, 387808 KB, 3339 KB/s, 116 seconds passed
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 .. parsed-literal::
 
-    ... 55%, 387936 KB, 3339 KB/s, 116 seconds passed
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 .. parsed-literal::
 
-    ... 55%, 388192 KB, 3340 KB/s, 116 seconds passed
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 .. parsed-literal::
 
-    ... 55%, 388320 KB, 3340 KB/s, 116 seconds passed
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 .. parsed-literal::
 
-    ... 55%, 388576 KB, 3340 KB/s, 116 seconds passed
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 .. parsed-literal::
 
-    ... 55%, 388704 KB, 3340 KB/s, 116 seconds passed
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-... 55%, 388768 KB, 3340 KB/s, 116 seconds passed
-... 55%, 388800 KB, 3341 KB/s, 116 seconds passed
-... 55%, 388832 KB, 3340 KB/s, 116 seconds passed
-... 55%, 388864 KB, 3340 KB/s, 116 seconds passed
-... 55%, 388896 KB, 3341 KB/s, 116 seconds passed
-... 55%, 388928 KB, 3341 KB/s, 116 seconds passed
+    ... 53%, 371392 KB, 3669 KB/s, 101 seconds passed
+... 53%, 371424 KB, 3669 KB/s, 101 seconds passed
+... 53%, 371456 KB, 3669 KB/s, 101 seconds passed
+... 53%, 371488 KB, 3670 KB/s, 101 seconds passed
 
 .. parsed-literal::
 
-    ... 55%, 388960 KB, 3340 KB/s, 116 seconds passed
-... 55%, 388992 KB, 3340 KB/s, 116 seconds passed
-... 55%, 389024 KB, 3341 KB/s, 116 seconds passed
-... 55%, 389056 KB, 3341 KB/s, 116 seconds passed
+    ... 53%, 371520 KB, 3669 KB/s, 101 seconds passed
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+... 53%, 371680 KB, 3669 KB/s, 101 seconds passed
+... 53%, 371712 KB, 3669 KB/s, 101 seconds passed
+... 53%, 371744 KB, 3670 KB/s, 101 seconds passed
 
 .. parsed-literal::
 
-    ... 55%, 389088 KB, 3340 KB/s, 116 seconds passed
-... 55%, 389120 KB, 3340 KB/s, 116 seconds passed
-... 55%, 389152 KB, 3341 KB/s, 116 seconds passed
-... 55%, 389184 KB, 3341 KB/s, 116 seconds passed
-... 55%, 389216 KB, 3340 KB/s, 116 seconds passed
-... 55%, 389248 KB, 3341 KB/s, 116 seconds passed
-... 55%, 389280 KB, 3341 KB/s, 116 seconds passed
-... 55%, 389312 KB, 3341 KB/s, 116 seconds passed
+    ... 53%, 371776 KB, 3669 KB/s, 101 seconds passed
+... 53%, 371808 KB, 3669 KB/s, 101 seconds passed
+... 53%, 371840 KB, 3669 KB/s, 101 seconds passed
 
 .. parsed-literal::
 
-    ... 55%, 389344 KB, 3340 KB/s, 116 seconds passed
-... 55%, 389376 KB, 3341 KB/s, 116 seconds passed
-... 55%, 389408 KB, 3341 KB/s, 116 seconds passed
-... 55%, 389440 KB, 3341 KB/s, 116 seconds passed
+    ... 53%, 371872 KB, 3669 KB/s, 101 seconds passed
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+... 53%, 372064 KB, 3669 KB/s, 101 seconds passed
+... 53%, 372096 KB, 3669 KB/s, 101 seconds passed
 
 .. parsed-literal::
 
-    ... 55%, 389472 KB, 3341 KB/s, 116 seconds passed
-... 56%, 389504 KB, 3341 KB/s, 116 seconds passed
-... 56%, 389536 KB, 3341 KB/s, 116 seconds passed
-... 56%, 389568 KB, 3341 KB/s, 116 seconds passed
-... 56%, 389600 KB, 3341 KB/s, 116 seconds passed
-... 56%, 389632 KB, 3341 KB/s, 116 seconds passed
-... 56%, 389664 KB, 3341 KB/s, 116 seconds passed
-... 56%, 389696 KB, 3341 KB/s, 116 seconds passed
+    ... 53%, 372128 KB, 3670 KB/s, 101 seconds passed
+... 53%, 372160 KB, 3669 KB/s, 101 seconds passed
+... 53%, 372192 KB, 3669 KB/s, 101 seconds passed
+... 53%, 372224 KB, 3669 KB/s, 101 seconds passed
 
 .. parsed-literal::
 
-    ... 56%, 389728 KB, 3341 KB/s, 116 seconds passed
-... 56%, 389760 KB, 3341 KB/s, 116 seconds passed
-... 56%, 389792 KB, 3341 KB/s, 116 seconds passed
-... 56%, 389824 KB, 3341 KB/s, 116 seconds passed
+    ... 53%, 372256 KB, 3669 KB/s, 101 seconds passed
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+... 53%, 372416 KB, 3669 KB/s, 101 seconds passed
+... 53%, 372448 KB, 3669 KB/s, 101 seconds passed
+... 53%, 372480 KB, 3669 KB/s, 101 seconds passed
 
 .. parsed-literal::
 
-    ... 56%, 389856 KB, 3341 KB/s, 116 seconds passed
-... 56%, 389888 KB, 3341 KB/s, 116 seconds passed
-... 56%, 389920 KB, 3341 KB/s, 116 seconds passed
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-... 56%, 389984 KB, 3341 KB/s, 116 seconds passed
-... 56%, 390016 KB, 3341 KB/s, 116 seconds passed
-... 56%, 390048 KB, 3341 KB/s, 116 seconds passed
-... 56%, 390080 KB, 3342 KB/s, 116 seconds passed
+    ... 53%, 372512 KB, 3670 KB/s, 101 seconds passed
+... 53%, 372544 KB, 3669 KB/s, 101 seconds passed
+... 53%, 372576 KB, 3669 KB/s, 101 seconds passed
+... 53%, 372608 KB, 3669 KB/s, 101 seconds passed
 
 .. parsed-literal::
 
-    ... 56%, 390112 KB, 3341 KB/s, 116 seconds passed
-... 56%, 390144 KB, 3341 KB/s, 116 seconds passed
-... 56%, 390176 KB, 3342 KB/s, 116 seconds passed
-... 56%, 390208 KB, 3342 KB/s, 116 seconds passed
+    ... 53%, 372640 KB, 3669 KB/s, 101 seconds passed
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+... 53%, 372768 KB, 3669 KB/s, 101 seconds passed
+... 53%, 372800 KB, 3669 KB/s, 101 seconds passed
+... 53%, 372832 KB, 3669 KB/s, 101 seconds passed
 
 .. parsed-literal::
 
-    ... 56%, 390240 KB, 3341 KB/s, 116 seconds passed
-... 56%, 390272 KB, 3341 KB/s, 116 seconds passed
-... 56%, 390304 KB, 3342 KB/s, 116 seconds passed
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-... 56%, 390400 KB, 3342 KB/s, 116 seconds passed
-... 56%, 390432 KB, 3342 KB/s, 116 seconds passed
+    ... 53%, 372864 KB, 3669 KB/s, 101 seconds passed
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+... 53%, 372928 KB, 3669 KB/s, 101 seconds passed
+... 53%, 372960 KB, 3669 KB/s, 101 seconds passed
+... 53%, 372992 KB, 3669 KB/s, 101 seconds passed
 
 .. parsed-literal::
 
-    ... 56%, 390464 KB, 3342 KB/s, 116 seconds passed
-... 56%, 390496 KB, 3341 KB/s, 116 seconds passed
-... 56%, 390528 KB, 3342 KB/s, 116 seconds passed
-... 56%, 390560 KB, 3342 KB/s, 116 seconds passed
-... 56%, 390592 KB, 3342 KB/s, 116 seconds passed
+    ... 53%, 373024 KB, 3669 KB/s, 101 seconds passed
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+... 53%, 373120 KB, 3669 KB/s, 101 seconds passed
+... 53%, 373152 KB, 3669 KB/s, 101 seconds passed
+... 53%, 373184 KB, 3669 KB/s, 101 seconds passed
 
 .. parsed-literal::
 
-    ... 56%, 390624 KB, 3342 KB/s, 116 seconds passed
-... 56%, 390656 KB, 3342 KB/s, 116 seconds passed
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-... 56%, 390784 KB, 3342 KB/s, 116 seconds passed
-... 56%, 390816 KB, 3342 KB/s, 116 seconds passed
+    ... 53%, 373216 KB, 3669 KB/s, 101 seconds passed
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+... 53%, 373312 KB, 3669 KB/s, 101 seconds passed
+... 53%, 373344 KB, 3669 KB/s, 101 seconds passed
+... 53%, 373376 KB, 3669 KB/s, 101 seconds passed
 
 .. parsed-literal::
 
-    ... 56%, 390848 KB, 3342 KB/s, 116 seconds passed
-... 56%, 390880 KB, 3342 KB/s, 116 seconds passed
-... 56%, 390912 KB, 3342 KB/s, 116 seconds passed
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-... 56%, 390976 KB, 3342 KB/s, 116 seconds passed
+    ... 53%, 373408 KB, 3669 KB/s, 101 seconds passed
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+... 53%, 373536 KB, 3669 KB/s, 101 seconds passed
+... 53%, 373568 KB, 3669 KB/s, 101 seconds passed
 
 .. parsed-literal::
 
-    ... 56%, 391008 KB, 3342 KB/s, 116 seconds passed
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-... 56%, 391168 KB, 3342 KB/s, 117 seconds passed
+    ... 53%, 373600 KB, 3669 KB/s, 101 seconds passed
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+... 53%, 373728 KB, 3669 KB/s, 101 seconds passed
+... 53%, 373760 KB, 3670 KB/s, 101 seconds passed
 
 .. parsed-literal::
 
-    ... 56%, 391200 KB, 3342 KB/s, 117 seconds passed
-... 56%, 391232 KB, 3343 KB/s, 117 seconds passed
-... 56%, 391264 KB, 3342 KB/s, 117 seconds passed
-... 56%, 391296 KB, 3342 KB/s, 117 seconds passed
-... 56%, 391328 KB, 3342 KB/s, 117 seconds passed
-... 56%, 391360 KB, 3343 KB/s, 117 seconds passed
+    ... 53%, 373792 KB, 3669 KB/s, 101 seconds passed
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+... 53%, 373920 KB, 3669 KB/s, 101 seconds passed
+... 53%, 373952 KB, 3669 KB/s, 101 seconds passed
 
 .. parsed-literal::
 
-    ... 56%, 391392 KB, 3342 KB/s, 117 seconds passed
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+    ... 53%, 373984 KB, 3669 KB/s, 101 seconds passed
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+... 53%, 374112 KB, 3669 KB/s, 101 seconds passed
+... 53%, 374144 KB, 3670 KB/s, 101 seconds passed
 
 .. parsed-literal::
 
-    ... 56%, 391584 KB, 3343 KB/s, 117 seconds passed
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-... 56%, 391680 KB, 3343 KB/s, 117 seconds passed
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+... 53%, 374272 KB, 3670 KB/s, 101 seconds passed
+... 53%, 374304 KB, 3669 KB/s, 102 seconds passed
 
 .. parsed-literal::
 
-    ... 56%, 391776 KB, 3342 KB/s, 117 seconds passed
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+... 53%, 374496 KB, 3669 KB/s, 102 seconds passed
+... 53%, 374528 KB, 3670 KB/s, 102 seconds passed
 
 .. parsed-literal::
 
-    ... 56%, 391936 KB, 3343 KB/s, 117 seconds passed
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+... 53%, 374656 KB, 3670 KB/s, 102 seconds passed
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 .. parsed-literal::
 
-    ... 56%, 392160 KB, 3343 KB/s, 117 seconds passed
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+... 53%, 374880 KB, 3669 KB/s, 102 seconds passed
+... 53%, 374912 KB, 3670 KB/s, 102 seconds passed
 
 .. parsed-literal::
 
-    ... 56%, 392320 KB, 3343 KB/s, 117 seconds passed
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+... 53%, 375040 KB, 3670 KB/s, 102 seconds passed
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 .. parsed-literal::
 
-    ... 56%, 392544 KB, 3343 KB/s, 117 seconds passed
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 .. parsed-literal::
 
-    ... 56%, 392672 KB, 3343 KB/s, 117 seconds passed
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 .. parsed-literal::
 
-    ... 56%, 392928 KB, 3343 KB/s, 117 seconds passed
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 .. parsed-literal::
 
-    ... 56%, 393056 KB, 3344 KB/s, 117 seconds passed
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 .. parsed-literal::
 
-    ... 56%, 393280 KB, 3344 KB/s, 117 seconds passed
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 .. parsed-literal::
 
-    ... 56%, 393440 KB, 3344 KB/s, 117 seconds passed
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 .. parsed-literal::
 
-    ... 56%, 393664 KB, 3344 KB/s, 117 seconds passed
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+... 54%, 376416 KB, 3670 KB/s, 102 seconds passed
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 .. parsed-literal::
 
-    ... 56%, 393824 KB, 3344 KB/s, 117 seconds passed
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+    ... 54%, 376480 KB, 3669 KB/s, 102 seconds passed
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+... 54%, 376544 KB, 3670 KB/s, 102 seconds passed
+... 54%, 376576 KB, 3670 KB/s, 102 seconds passed
 
 .. parsed-literal::
 
-    ... 56%, 394048 KB, 3344 KB/s, 117 seconds passed
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+    ... 54%, 376608 KB, 3669 KB/s, 102 seconds passed
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+... 54%, 376800 KB, 3670 KB/s, 102 seconds passed
+... 54%, 376832 KB, 3670 KB/s, 102 seconds passed
 
 .. parsed-literal::
 
-    ... 56%, 394208 KB, 3344 KB/s, 117 seconds passed
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+    ... 54%, 376864 KB, 3669 KB/s, 102 seconds passed
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+... 54%, 376928 KB, 3670 KB/s, 102 seconds passed
+... 54%, 376960 KB, 3670 KB/s, 102 seconds passed
 
 .. parsed-literal::
 
-    ... 56%, 394432 KB, 3345 KB/s, 117 seconds passed
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+    ... 54%, 376992 KB, 3669 KB/s, 102 seconds passed
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+... 54%, 377152 KB, 3669 KB/s, 102 seconds passed
+... 54%, 377184 KB, 3670 KB/s, 102 seconds passed
+... 54%, 377216 KB, 3670 KB/s, 102 seconds passed
 
 .. parsed-literal::
 
-    ... 56%, 394592 KB, 3345 KB/s, 117 seconds passed
-... 56%, 394624 KB, 3345 KB/s, 117 seconds passed
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+    ... 54%, 377248 KB, 3669 KB/s, 102 seconds passed
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+... 54%, 377312 KB, 3670 KB/s, 102 seconds passed
+... 54%, 377344 KB, 3670 KB/s, 102 seconds passed
 
 .. parsed-literal::
 
-    ... 56%, 394816 KB, 3345 KB/s, 118 seconds passed
-... 56%, 394848 KB, 3345 KB/s, 118 seconds passed
-... 56%, 394880 KB, 3345 KB/s, 118 seconds passed
-... 56%, 394912 KB, 3345 KB/s, 118 seconds passed
+    ... 54%, 377376 KB, 3669 KB/s, 102 seconds passed
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+... 54%, 377568 KB, 3670 KB/s, 102 seconds passed
+... 54%, 377600 KB, 3670 KB/s, 102 seconds passed
 
 .. parsed-literal::
 
-    ... 56%, 394944 KB, 3345 KB/s, 118 seconds passed
-... 56%, 394976 KB, 3345 KB/s, 118 seconds passed
-... 56%, 395008 KB, 3345 KB/s, 118 seconds passed
-... 56%, 395040 KB, 3345 KB/s, 118 seconds passed
-... 56%, 395072 KB, 3345 KB/s, 118 seconds passed
-... 56%, 395104 KB, 3345 KB/s, 118 seconds passed
-... 56%, 395136 KB, 3345 KB/s, 118 seconds passed
-... 56%, 395168 KB, 3346 KB/s, 118 seconds passed
+    ... 54%, 377632 KB, 3669 KB/s, 102 seconds passed
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+... 54%, 377696 KB, 3670 KB/s, 102 seconds passed
+... 54%, 377728 KB, 3670 KB/s, 102 seconds passed
 
 .. parsed-literal::
 
-    ... 56%, 395200 KB, 3345 KB/s, 118 seconds passed
-... 56%, 395232 KB, 3345 KB/s, 118 seconds passed
-... 56%, 395264 KB, 3345 KB/s, 118 seconds passed
-... 56%, 395296 KB, 3346 KB/s, 118 seconds passed
+    ... 54%, 377760 KB, 3669 KB/s, 102 seconds passed
+... 54%, 377792 KB, 3670 KB/s, 102 seconds passed
+... 54%, 377824 KB, 3670 KB/s, 102 seconds passed
+... 54%, 377856 KB, 3670 KB/s, 102 seconds passed
+... 54%, 377888 KB, 3669 KB/s, 102 seconds passed
+... 54%, 377920 KB, 3670 KB/s, 102 seconds passed
+... 54%, 377952 KB, 3670 KB/s, 102 seconds passed
+... 54%, 377984 KB, 3670 KB/s, 102 seconds passed
 
 .. parsed-literal::
 
-    ... 56%, 395328 KB, 3345 KB/s, 118 seconds passed
-... 56%, 395360 KB, 3345 KB/s, 118 seconds passed
-... 56%, 395392 KB, 3346 KB/s, 118 seconds passed
-... 56%, 395424 KB, 3346 KB/s, 118 seconds passed
-... 56%, 395456 KB, 3345 KB/s, 118 seconds passed
-... 56%, 395488 KB, 3346 KB/s, 118 seconds passed
-... 56%, 395520 KB, 3346 KB/s, 118 seconds passed
-... 56%, 395552 KB, 3346 KB/s, 118 seconds passed
+    ... 54%, 378016 KB, 3669 KB/s, 103 seconds passed
+... 54%, 378048 KB, 3670 KB/s, 103 seconds passed
+... 54%, 378080 KB, 3670 KB/s, 103 seconds passed
+... 54%, 378112 KB, 3669 KB/s, 103 seconds passed
 
 .. parsed-literal::
 
-    ... 56%, 395584 KB, 3346 KB/s, 118 seconds passed
-... 56%, 395616 KB, 3346 KB/s, 118 seconds passed
-... 56%, 395648 KB, 3346 KB/s, 118 seconds passed
-... 56%, 395680 KB, 3346 KB/s, 118 seconds passed
+    ... 54%, 378144 KB, 3669 KB/s, 103 seconds passed
+... 54%, 378176 KB, 3670 KB/s, 103 seconds passed
+... 54%, 378208 KB, 3670 KB/s, 103 seconds passed
+... 54%, 378240 KB, 3669 KB/s, 103 seconds passed
+... 54%, 378272 KB, 3669 KB/s, 103 seconds passed
+... 54%, 378304 KB, 3670 KB/s, 103 seconds passed
+... 54%, 378336 KB, 3670 KB/s, 103 seconds passed
 
 .. parsed-literal::
 
-    ... 56%, 395712 KB, 3346 KB/s, 118 seconds passed
-... 56%, 395744 KB, 3346 KB/s, 118 seconds passed
-... 56%, 395776 KB, 3346 KB/s, 118 seconds passed
-... 56%, 395808 KB, 3346 KB/s, 118 seconds passed
-... 56%, 395840 KB, 3346 KB/s, 118 seconds passed
-... 56%, 395872 KB, 3346 KB/s, 118 seconds passed
-... 56%, 395904 KB, 3346 KB/s, 118 seconds passed
-... 56%, 395936 KB, 3346 KB/s, 118 seconds passed
+    ... 54%, 378368 KB, 3669 KB/s, 103 seconds passed
+... 54%, 378400 KB, 3669 KB/s, 103 seconds passed
+... 54%, 378432 KB, 3670 KB/s, 103 seconds passed
+... 54%, 378464 KB, 3670 KB/s, 103 seconds passed
 
 .. parsed-literal::
 
-    ... 56%, 395968 KB, 3346 KB/s, 118 seconds passed
-... 56%, 396000 KB, 3346 KB/s, 118 seconds passed
-... 56%, 396032 KB, 3346 KB/s, 118 seconds passed
-... 56%, 396064 KB, 3346 KB/s, 118 seconds passed
+    ... 54%, 378496 KB, 3669 KB/s, 103 seconds passed
+... 54%, 378528 KB, 3669 KB/s, 103 seconds passed
+... 54%, 378560 KB, 3670 KB/s, 103 seconds passed
+... 54%, 378592 KB, 3670 KB/s, 103 seconds passed
+... 54%, 378624 KB, 3669 KB/s, 103 seconds passed
+... 54%, 378656 KB, 3669 KB/s, 103 seconds passed
+... 54%, 378688 KB, 3670 KB/s, 103 seconds passed
+... 54%, 378720 KB, 3670 KB/s, 103 seconds passed
 
 .. parsed-literal::
 
-    ... 56%, 396096 KB, 3346 KB/s, 118 seconds passed
-... 56%, 396128 KB, 3346 KB/s, 118 seconds passed
-... 56%, 396160 KB, 3346 KB/s, 118 seconds passed
-... 56%, 396192 KB, 3346 KB/s, 118 seconds passed
-... 56%, 396224 KB, 3346 KB/s, 118 seconds passed
-... 56%, 396256 KB, 3346 KB/s, 118 seconds passed
-... 56%, 396288 KB, 3346 KB/s, 118 seconds passed
+    ... 54%, 378752 KB, 3669 KB/s, 103 seconds passed
+... 54%, 378784 KB, 3669 KB/s, 103 seconds passed
+... 54%, 378816 KB, 3670 KB/s, 103 seconds passed
+... 54%, 378848 KB, 3670 KB/s, 103 seconds passed
 
 .. parsed-literal::
 
-    ... 56%, 396320 KB, 3346 KB/s, 118 seconds passed
-... 56%, 396352 KB, 3346 KB/s, 118 seconds passed
-... 56%, 396384 KB, 3346 KB/s, 118 seconds passed
-... 56%, 396416 KB, 3346 KB/s, 118 seconds passed
-... 57%, 396448 KB, 3347 KB/s, 118 seconds passed
+    ... 54%, 378880 KB, 3669 KB/s, 103 seconds passed
+... 54%, 378912 KB, 3669 KB/s, 103 seconds passed
+... 54%, 378944 KB, 3670 KB/s, 103 seconds passed
+... 54%, 378976 KB, 3670 KB/s, 103 seconds passed
+... 54%, 379008 KB, 3669 KB/s, 103 seconds passed
+... 54%, 379040 KB, 3669 KB/s, 103 seconds passed
+... 54%, 379072 KB, 3670 KB/s, 103 seconds passed
+... 54%, 379104 KB, 3670 KB/s, 103 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 396480 KB, 3346 KB/s, 118 seconds passed
-... 57%, 396512 KB, 3346 KB/s, 118 seconds passed
-... 57%, 396544 KB, 3347 KB/s, 118 seconds passed
-... 57%, 396576 KB, 3347 KB/s, 118 seconds passed
-... 57%, 396608 KB, 3346 KB/s, 118 seconds passed
-... 57%, 396640 KB, 3346 KB/s, 118 seconds passed
-... 57%, 396672 KB, 3347 KB/s, 118 seconds passed
+    ... 54%, 379136 KB, 3669 KB/s, 103 seconds passed
+... 54%, 379168 KB, 3669 KB/s, 103 seconds passed
+... 54%, 379200 KB, 3670 KB/s, 103 seconds passed
+... 54%, 379232 KB, 3670 KB/s, 103 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 396704 KB, 3346 KB/s, 118 seconds passed
-... 57%, 396736 KB, 3346 KB/s, 118 seconds passed
-... 57%, 396768 KB, 3347 KB/s, 118 seconds passed
-... 57%, 396800 KB, 3347 KB/s, 118 seconds passed
+    ... 54%, 379264 KB, 3670 KB/s, 103 seconds passed
+... 54%, 379296 KB, 3669 KB/s, 103 seconds passed
+... 54%, 379328 KB, 3670 KB/s, 103 seconds passed
+... 54%, 379360 KB, 3670 KB/s, 103 seconds passed
+... 54%, 379392 KB, 3670 KB/s, 103 seconds passed
+... 54%, 379424 KB, 3669 KB/s, 103 seconds passed
+... 54%, 379456 KB, 3670 KB/s, 103 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 396832 KB, 3346 KB/s, 118 seconds passed
-... 57%, 396864 KB, 3346 KB/s, 118 seconds passed
-... 57%, 396896 KB, 3347 KB/s, 118 seconds passed
+    ... 54%, 379488 KB, 3670 KB/s, 103 seconds passed
+... 54%, 379520 KB, 3670 KB/s, 103 seconds passed
+... 54%, 379552 KB, 3669 KB/s, 103 seconds passed
+... 54%, 379584 KB, 3670 KB/s, 103 seconds passed
+... 54%, 379616 KB, 3670 KB/s, 103 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 396928 KB, 3344 KB/s, 118 seconds passed
-... 57%, 396960 KB, 3344 KB/s, 118 seconds passed
-... 57%, 396992 KB, 3344 KB/s, 118 seconds passed
+    ... 54%, 379648 KB, 3670 KB/s, 103 seconds passed
+... 54%, 379680 KB, 3669 KB/s, 103 seconds passed
+... 54%, 379712 KB, 3670 KB/s, 103 seconds passed
+... 54%, 379744 KB, 3670 KB/s, 103 seconds passed
+... 54%, 379776 KB, 3670 KB/s, 103 seconds passed
+... 54%, 379808 KB, 3669 KB/s, 103 seconds passed
+... 54%, 379840 KB, 3670 KB/s, 103 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 397024 KB, 3344 KB/s, 118 seconds passed
-... 57%, 397056 KB, 3344 KB/s, 118 seconds passed
-... 57%, 397088 KB, 3343 KB/s, 118 seconds passed
-... 57%, 397120 KB, 3343 KB/s, 118 seconds passed
-... 57%, 397152 KB, 3344 KB/s, 118 seconds passed
+    ... 54%, 379872 KB, 3670 KB/s, 103 seconds passed
+... 54%, 379904 KB, 3670 KB/s, 103 seconds passed
+... 54%, 379936 KB, 3669 KB/s, 103 seconds passed
+... 54%, 379968 KB, 3670 KB/s, 103 seconds passed
+... 54%, 380000 KB, 3670 KB/s, 103 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 397184 KB, 3343 KB/s, 118 seconds passed
-... 57%, 397216 KB, 3343 KB/s, 118 seconds passed
-... 57%, 397248 KB, 3344 KB/s, 118 seconds passed
+    ... 54%, 380032 KB, 3670 KB/s, 103 seconds passed
+... 54%, 380064 KB, 3669 KB/s, 103 seconds passed
+... 54%, 380096 KB, 3669 KB/s, 103 seconds passed
+... 54%, 380128 KB, 3670 KB/s, 103 seconds passed
+... 54%, 380160 KB, 3669 KB/s, 103 seconds passed
+... 54%, 380192 KB, 3669 KB/s, 103 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 397280 KB, 3343 KB/s, 118 seconds passed
-... 57%, 397312 KB, 3343 KB/s, 118 seconds passed
-... 57%, 397344 KB, 3343 KB/s, 118 seconds passed
-... 57%, 397376 KB, 3344 KB/s, 118 seconds passed
-... 57%, 397408 KB, 3343 KB/s, 118 seconds passed
-... 57%, 397440 KB, 3343 KB/s, 118 seconds passed
-... 57%, 397472 KB, 3344 KB/s, 118 seconds passed
-... 57%, 397504 KB, 3344 KB/s, 118 seconds passed
+    ... 54%, 380224 KB, 3669 KB/s, 103 seconds passed
+... 54%, 380256 KB, 3669 KB/s, 103 seconds passed
+... 54%, 380288 KB, 3669 KB/s, 103 seconds passed
+... 54%, 380320 KB, 3669 KB/s, 103 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 397536 KB, 3343 KB/s, 118 seconds passed
-... 57%, 397568 KB, 3343 KB/s, 118 seconds passed
-... 57%, 397600 KB, 3344 KB/s, 118 seconds passed
-... 57%, 397632 KB, 3344 KB/s, 118 seconds passed
+    ... 54%, 380352 KB, 3669 KB/s, 103 seconds passed
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+... 54%, 380416 KB, 3669 KB/s, 103 seconds passed
+... 54%, 380448 KB, 3670 KB/s, 103 seconds passed
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+... 54%, 380512 KB, 3669 KB/s, 103 seconds passed
+... 54%, 380544 KB, 3669 KB/s, 103 seconds passed
+... 54%, 380576 KB, 3670 KB/s, 103 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 397664 KB, 3343 KB/s, 118 seconds passed
-... 57%, 397696 KB, 3343 KB/s, 118 seconds passed
-... 57%, 397728 KB, 3344 KB/s, 118 seconds passed
-... 57%, 397760 KB, 3344 KB/s, 118 seconds passed
-... 57%, 397792 KB, 3343 KB/s, 118 seconds passed
-... 57%, 397824 KB, 3344 KB/s, 118 seconds passed
-... 57%, 397856 KB, 3344 KB/s, 118 seconds passed
-... 57%, 397888 KB, 3344 KB/s, 118 seconds passed
+    ... 54%, 380608 KB, 3669 KB/s, 103 seconds passed
+... 54%, 380640 KB, 3669 KB/s, 103 seconds passed
+... 54%, 380672 KB, 3669 KB/s, 103 seconds passed
+... 54%, 380704 KB, 3670 KB/s, 103 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 397920 KB, 3343 KB/s, 118 seconds passed
-... 57%, 397952 KB, 3344 KB/s, 118 seconds passed
-... 57%, 397984 KB, 3344 KB/s, 118 seconds passed
-... 57%, 398016 KB, 3344 KB/s, 119 seconds passed
+    ... 54%, 380736 KB, 3669 KB/s, 103 seconds passed
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+... 54%, 380800 KB, 3669 KB/s, 103 seconds passed
+... 54%, 380832 KB, 3670 KB/s, 103 seconds passed
+... 54%, 380864 KB, 3669 KB/s, 103 seconds passed
+... 54%, 380896 KB, 3669 KB/s, 103 seconds passed
+... 54%, 380928 KB, 3669 KB/s, 103 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 398048 KB, 3344 KB/s, 119 seconds passed
-... 57%, 398080 KB, 3344 KB/s, 119 seconds passed
-... 57%, 398112 KB, 3344 KB/s, 119 seconds passed
-... 57%, 398144 KB, 3344 KB/s, 119 seconds passed
-... 57%, 398176 KB, 3344 KB/s, 119 seconds passed
-... 57%, 398208 KB, 3344 KB/s, 119 seconds passed
-... 57%, 398240 KB, 3344 KB/s, 119 seconds passed
-... 57%, 398272 KB, 3344 KB/s, 119 seconds passed
+    ... 54%, 380960 KB, 3670 KB/s, 103 seconds passed
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+... 54%, 381024 KB, 3669 KB/s, 103 seconds passed
+... 54%, 381056 KB, 3669 KB/s, 103 seconds passed
+... 54%, 381088 KB, 3670 KB/s, 103 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 398304 KB, 3344 KB/s, 119 seconds passed
-... 57%, 398336 KB, 3344 KB/s, 119 seconds passed
-... 57%, 398368 KB, 3344 KB/s, 119 seconds passed
-... 57%, 398400 KB, 3344 KB/s, 119 seconds passed
+    ... 54%, 381120 KB, 3669 KB/s, 103 seconds passed
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+... 54%, 381216 KB, 3670 KB/s, 103 seconds passed
+... 54%, 381248 KB, 3669 KB/s, 103 seconds passed
+... 54%, 381280 KB, 3669 KB/s, 103 seconds passed
+... 54%, 381312 KB, 3669 KB/s, 103 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 398432 KB, 3344 KB/s, 119 seconds passed
-... 57%, 398464 KB, 3344 KB/s, 119 seconds passed
-... 57%, 398496 KB, 3344 KB/s, 119 seconds passed
-... 57%, 398528 KB, 3344 KB/s, 119 seconds passed
-... 57%, 398560 KB, 3344 KB/s, 119 seconds passed
-... 57%, 398592 KB, 3344 KB/s, 119 seconds passed
-... 57%, 398624 KB, 3344 KB/s, 119 seconds passed
-... 57%, 398656 KB, 3345 KB/s, 119 seconds passed
+    ... 54%, 381344 KB, 3670 KB/s, 103 seconds passed
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+... 54%, 381408 KB, 3669 KB/s, 103 seconds passed
+... 54%, 381440 KB, 3669 KB/s, 103 seconds passed
+... 54%, 381472 KB, 3670 KB/s, 103 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 398688 KB, 3344 KB/s, 119 seconds passed
-... 57%, 398720 KB, 3344 KB/s, 119 seconds passed
-... 57%, 398752 KB, 3344 KB/s, 119 seconds passed
-... 57%, 398784 KB, 3345 KB/s, 119 seconds passed
+    ... 54%, 381504 KB, 3669 KB/s, 103 seconds passed
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+... 54%, 381632 KB, 3669 KB/s, 103 seconds passed
+... 54%, 381664 KB, 3669 KB/s, 104 seconds passed
+... 54%, 381696 KB, 3669 KB/s, 104 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 398816 KB, 3344 KB/s, 119 seconds passed
-... 57%, 398848 KB, 3344 KB/s, 119 seconds passed
-... 57%, 398880 KB, 3345 KB/s, 119 seconds passed
-... 57%, 398912 KB, 3345 KB/s, 119 seconds passed
-... 57%, 398944 KB, 3344 KB/s, 119 seconds passed
-... 57%, 398976 KB, 3345 KB/s, 119 seconds passed
-... 57%, 399008 KB, 3345 KB/s, 119 seconds passed
+    ... 54%, 381728 KB, 3670 KB/s, 104 seconds passed
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+... 54%, 381792 KB, 3669 KB/s, 104 seconds passed
+... 54%, 381824 KB, 3669 KB/s, 104 seconds passed
+... 54%, 381856 KB, 3670 KB/s, 104 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 399040 KB, 3345 KB/s, 119 seconds passed
-... 57%, 399072 KB, 3344 KB/s, 119 seconds passed
-... 57%, 399104 KB, 3345 KB/s, 119 seconds passed
-... 57%, 399136 KB, 3345 KB/s, 119 seconds passed
-... 57%, 399168 KB, 3345 KB/s, 119 seconds passed
+    ... 54%, 381888 KB, 3669 KB/s, 104 seconds passed
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+... 54%, 381952 KB, 3670 KB/s, 104 seconds passed
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+... 54%, 382016 KB, 3669 KB/s, 104 seconds passed
+... 54%, 382048 KB, 3669 KB/s, 104 seconds passed
+... 54%, 382080 KB, 3670 KB/s, 104 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 399200 KB, 3345 KB/s, 119 seconds passed
-... 57%, 399232 KB, 3345 KB/s, 119 seconds passed
-... 57%, 399264 KB, 3345 KB/s, 119 seconds passed
-... 57%, 399296 KB, 3345 KB/s, 119 seconds passed
-... 57%, 399328 KB, 3345 KB/s, 119 seconds passed
-... 57%, 399360 KB, 3345 KB/s, 119 seconds passed
-... 57%, 399392 KB, 3345 KB/s, 119 seconds passed
+    ... 54%, 382112 KB, 3670 KB/s, 104 seconds passed
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+... 54%, 382176 KB, 3669 KB/s, 104 seconds passed
+... 54%, 382208 KB, 3670 KB/s, 104 seconds passed
+... 54%, 382240 KB, 3670 KB/s, 104 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 399424 KB, 3345 KB/s, 119 seconds passed
-... 57%, 399456 KB, 3345 KB/s, 119 seconds passed
-... 57%, 399488 KB, 3345 KB/s, 119 seconds passed
+    ... 54%, 382272 KB, 3669 KB/s, 104 seconds passed
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+... 54%, 382400 KB, 3669 KB/s, 104 seconds passed
+... 54%, 382432 KB, 3669 KB/s, 104 seconds passed
+... 54%, 382464 KB, 3670 KB/s, 104 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 399520 KB, 3344 KB/s, 119 seconds passed
-... 57%, 399552 KB, 3344 KB/s, 119 seconds passed
-... 57%, 399584 KB, 3345 KB/s, 119 seconds passed
-... 57%, 399616 KB, 3345 KB/s, 119 seconds passed
+    ... 54%, 382496 KB, 3670 KB/s, 104 seconds passed
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+... 55%, 382560 KB, 3669 KB/s, 104 seconds passed
+... 55%, 382592 KB, 3670 KB/s, 104 seconds passed
+... 55%, 382624 KB, 3670 KB/s, 104 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 399648 KB, 3343 KB/s, 119 seconds passed
+    ... 55%, 382656 KB, 3669 KB/s, 104 seconds passed
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+... 55%, 382720 KB, 3670 KB/s, 104 seconds passed
+... 55%, 382752 KB, 3670 KB/s, 104 seconds passed
+... 55%, 382784 KB, 3669 KB/s, 104 seconds passed
+... 55%, 382816 KB, 3669 KB/s, 104 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 399680 KB, 3343 KB/s, 119 seconds passed
-... 57%, 399712 KB, 3342 KB/s, 119 seconds passed
+    ... 55%, 382848 KB, 3670 KB/s, 104 seconds passed
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+... 55%, 382912 KB, 3669 KB/s, 104 seconds passed
+... 55%, 382944 KB, 3669 KB/s, 104 seconds passed
+... 55%, 382976 KB, 3670 KB/s, 104 seconds passed
+... 55%, 383008 KB, 3670 KB/s, 104 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 399744 KB, 3341 KB/s, 119 seconds passed
-... 57%, 399776 KB, 3341 KB/s, 119 seconds passed
+    ... 55%, 383040 KB, 3669 KB/s, 104 seconds passed
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+... 55%, 383104 KB, 3670 KB/s, 104 seconds passed
+... 55%, 383136 KB, 3670 KB/s, 104 seconds passed
+... 55%, 383168 KB, 3669 KB/s, 104 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 399808 KB, 3341 KB/s, 119 seconds passed
-... 57%, 399840 KB, 3340 KB/s, 119 seconds passed
-... 57%, 399872 KB, 3340 KB/s, 119 seconds passed
+    ... 55%, 383200 KB, 3669 KB/s, 104 seconds passed
+... 55%, 383232 KB, 3670 KB/s, 104 seconds passed
+... 55%, 383264 KB, 3669 KB/s, 104 seconds passed
+... 55%, 383296 KB, 3669 KB/s, 104 seconds passed
+... 55%, 383328 KB, 3669 KB/s, 104 seconds passed
+... 55%, 383360 KB, 3670 KB/s, 104 seconds passed
+... 55%, 383392 KB, 3670 KB/s, 104 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 399904 KB, 3340 KB/s, 119 seconds passed
-... 57%, 399936 KB, 3340 KB/s, 119 seconds passed
-... 57%, 399968 KB, 3340 KB/s, 119 seconds passed
+    ... 55%, 383424 KB, 3669 KB/s, 104 seconds passed
+... 55%, 383456 KB, 3669 KB/s, 104 seconds passed
+... 55%, 383488 KB, 3670 KB/s, 104 seconds passed
+... 55%, 383520 KB, 3670 KB/s, 104 seconds passed
+... 55%, 383552 KB, 3669 KB/s, 104 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 400000 KB, 3340 KB/s, 119 seconds passed
-... 57%, 400032 KB, 3340 KB/s, 119 seconds passed
-... 57%, 400064 KB, 3339 KB/s, 119 seconds passed
+    ... 55%, 383584 KB, 3669 KB/s, 104 seconds passed
+... 55%, 383616 KB, 3670 KB/s, 104 seconds passed
+... 55%, 383648 KB, 3669 KB/s, 104 seconds passed
+... 55%, 383680 KB, 3669 KB/s, 104 seconds passed
+... 55%, 383712 KB, 3669 KB/s, 104 seconds passed
+... 55%, 383744 KB, 3670 KB/s, 104 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 400096 KB, 3339 KB/s, 119 seconds passed
-... 57%, 400128 KB, 3340 KB/s, 119 seconds passed
-... 57%, 400160 KB, 3339 KB/s, 119 seconds passed
-... 57%, 400192 KB, 3339 KB/s, 119 seconds passed
-... 57%, 400224 KB, 3339 KB/s, 119 seconds passed
+    ... 55%, 383776 KB, 3669 KB/s, 104 seconds passed
+... 55%, 383808 KB, 3669 KB/s, 104 seconds passed
+... 55%, 383840 KB, 3669 KB/s, 104 seconds passed
+... 55%, 383872 KB, 3670 KB/s, 104 seconds passed
+... 55%, 383904 KB, 3669 KB/s, 104 seconds passed
+... 55%, 383936 KB, 3669 KB/s, 104 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 400256 KB, 3339 KB/s, 119 seconds passed
-... 57%, 400288 KB, 3339 KB/s, 119 seconds passed
-... 57%, 400320 KB, 3339 KB/s, 119 seconds passed
-... 57%, 400352 KB, 3339 KB/s, 119 seconds passed
+    ... 55%, 383968 KB, 3669 KB/s, 104 seconds passed
+... 55%, 384000 KB, 3670 KB/s, 104 seconds passed
+... 55%, 384032 KB, 3669 KB/s, 104 seconds passed
+... 55%, 384064 KB, 3669 KB/s, 104 seconds passed
+... 55%, 384096 KB, 3669 KB/s, 104 seconds passed
+... 55%, 384128 KB, 3670 KB/s, 104 seconds passed
+... 55%, 384160 KB, 3670 KB/s, 104 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 400384 KB, 3339 KB/s, 119 seconds passed
-... 57%, 400416 KB, 3339 KB/s, 119 seconds passed
-... 57%, 400448 KB, 3339 KB/s, 119 seconds passed
-... 57%, 400480 KB, 3339 KB/s, 119 seconds passed
-... 57%, 400512 KB, 3339 KB/s, 119 seconds passed
-... 57%, 400544 KB, 3339 KB/s, 119 seconds passed
-... 57%, 400576 KB, 3339 KB/s, 119 seconds passed
+    ... 55%, 384192 KB, 3669 KB/s, 104 seconds passed
+... 55%, 384224 KB, 3669 KB/s, 104 seconds passed
+... 55%, 384256 KB, 3670 KB/s, 104 seconds passed
+... 55%, 384288 KB, 3670 KB/s, 104 seconds passed
+... 55%, 384320 KB, 3669 KB/s, 104 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 400608 KB, 3339 KB/s, 119 seconds passed
-... 57%, 400640 KB, 3339 KB/s, 119 seconds passed
-... 57%, 400672 KB, 3339 KB/s, 119 seconds passed
-... 57%, 400704 KB, 3339 KB/s, 119 seconds passed
+    ... 55%, 384352 KB, 3669 KB/s, 104 seconds passed
+... 55%, 384384 KB, 3670 KB/s, 104 seconds passed
+... 55%, 384416 KB, 3670 KB/s, 104 seconds passed
+... 55%, 384448 KB, 3669 KB/s, 104 seconds passed
+... 55%, 384480 KB, 3670 KB/s, 104 seconds passed
+... 55%, 384512 KB, 3670 KB/s, 104 seconds passed
+... 55%, 384544 KB, 3670 KB/s, 104 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 400736 KB, 3339 KB/s, 120 seconds passed
-... 57%, 400768 KB, 3339 KB/s, 120 seconds passed
-... 57%, 400800 KB, 3339 KB/s, 120 seconds passed
-... 57%, 400832 KB, 3340 KB/s, 120 seconds passed
-... 57%, 400864 KB, 3339 KB/s, 120 seconds passed
-... 57%, 400896 KB, 3339 KB/s, 120 seconds passed
-... 57%, 400928 KB, 3339 KB/s, 120 seconds passed
-... 57%, 400960 KB, 3340 KB/s, 120 seconds passed
+    ... 55%, 384576 KB, 3669 KB/s, 104 seconds passed
+... 55%, 384608 KB, 3670 KB/s, 104 seconds passed
+... 55%, 384640 KB, 3670 KB/s, 104 seconds passed
+... 55%, 384672 KB, 3670 KB/s, 104 seconds passed
+... 55%, 384704 KB, 3669 KB/s, 104 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 400992 KB, 3339 KB/s, 120 seconds passed
-... 57%, 401024 KB, 3339 KB/s, 120 seconds passed
-... 57%, 401056 KB, 3340 KB/s, 120 seconds passed
-... 57%, 401088 KB, 3340 KB/s, 120 seconds passed
+    ... 55%, 384736 KB, 3670 KB/s, 104 seconds passed
+... 55%, 384768 KB, 3670 KB/s, 104 seconds passed
+... 55%, 384800 KB, 3670 KB/s, 104 seconds passed
+... 55%, 384832 KB, 3669 KB/s, 104 seconds passed
+... 55%, 384864 KB, 3670 KB/s, 104 seconds passed
+... 55%, 384896 KB, 3670 KB/s, 104 seconds passed
+... 55%, 384928 KB, 3670 KB/s, 104 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 401120 KB, 3339 KB/s, 120 seconds passed
-... 57%, 401152 KB, 3339 KB/s, 120 seconds passed
-... 57%, 401184 KB, 3340 KB/s, 120 seconds passed
-... 57%, 401216 KB, 3340 KB/s, 120 seconds passed
-... 57%, 401248 KB, 3339 KB/s, 120 seconds passed
-... 57%, 401280 KB, 3340 KB/s, 120 seconds passed
-... 57%, 401312 KB, 3340 KB/s, 120 seconds passed
-... 57%, 401344 KB, 3340 KB/s, 120 seconds passed
+    ... 55%, 384960 KB, 3669 KB/s, 104 seconds passed
+... 55%, 384992 KB, 3670 KB/s, 104 seconds passed
+... 55%, 385024 KB, 3670 KB/s, 104 seconds passed
+... 55%, 385056 KB, 3670 KB/s, 104 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 401376 KB, 3339 KB/s, 120 seconds passed
-... 57%, 401408 KB, 3340 KB/s, 120 seconds passed
-... 57%, 401440 KB, 3340 KB/s, 120 seconds passed
-... 57%, 401472 KB, 3340 KB/s, 120 seconds passed
+    ... 55%, 385088 KB, 3669 KB/s, 104 seconds passed
+... 55%, 385120 KB, 3670 KB/s, 104 seconds passed
+... 55%, 385152 KB, 3670 KB/s, 104 seconds passed
+... 55%, 385184 KB, 3670 KB/s, 104 seconds passed
+... 55%, 385216 KB, 3669 KB/s, 104 seconds passed
+... 55%, 385248 KB, 3670 KB/s, 104 seconds passed
+... 55%, 385280 KB, 3670 KB/s, 104 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 401504 KB, 3340 KB/s, 120 seconds passed
-... 57%, 401536 KB, 3340 KB/s, 120 seconds passed
-... 57%, 401568 KB, 3340 KB/s, 120 seconds passed
-... 57%, 401600 KB, 3340 KB/s, 120 seconds passed
-... 57%, 401632 KB, 3340 KB/s, 120 seconds passed
-... 57%, 401664 KB, 3340 KB/s, 120 seconds passed
-... 57%, 401696 KB, 3340 KB/s, 120 seconds passed
-... 57%, 401728 KB, 3340 KB/s, 120 seconds passed
+    ... 55%, 385312 KB, 3669 KB/s, 104 seconds passed
+... 55%, 385344 KB, 3669 KB/s, 104 seconds passed
+... 55%, 385376 KB, 3670 KB/s, 105 seconds passed
+... 55%, 385408 KB, 3670 KB/s, 105 seconds passed
+... 55%, 385440 KB, 3669 KB/s, 105 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 401760 KB, 3340 KB/s, 120 seconds passed
-... 57%, 401792 KB, 3340 KB/s, 120 seconds passed
-... 57%, 401824 KB, 3340 KB/s, 120 seconds passed
-... 57%, 401856 KB, 3340 KB/s, 120 seconds passed
+    ... 55%, 385472 KB, 3669 KB/s, 105 seconds passed
+... 55%, 385504 KB, 3670 KB/s, 105 seconds passed
+... 55%, 385536 KB, 3670 KB/s, 105 seconds passed
+... 55%, 385568 KB, 3669 KB/s, 105 seconds passed
+... 55%, 385600 KB, 3669 KB/s, 105 seconds passed
+... 55%, 385632 KB, 3670 KB/s, 105 seconds passed
+... 55%, 385664 KB, 3670 KB/s, 105 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 401888 KB, 3340 KB/s, 120 seconds passed
-... 57%, 401920 KB, 3340 KB/s, 120 seconds passed
-... 57%, 401952 KB, 3340 KB/s, 120 seconds passed
-... 57%, 401984 KB, 3340 KB/s, 120 seconds passed
-... 57%, 402016 KB, 3340 KB/s, 120 seconds passed
-... 57%, 402048 KB, 3340 KB/s, 120 seconds passed
-... 57%, 402080 KB, 3340 KB/s, 120 seconds passed
-... 57%, 402112 KB, 3341 KB/s, 120 seconds passed
+    ... 55%, 385696 KB, 3669 KB/s, 105 seconds passed
+... 55%, 385728 KB, 3669 KB/s, 105 seconds passed
+... 55%, 385760 KB, 3670 KB/s, 105 seconds passed
+... 55%, 385792 KB, 3670 KB/s, 105 seconds passed
+... 55%, 385824 KB, 3669 KB/s, 105 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 402144 KB, 3340 KB/s, 120 seconds passed
-... 57%, 402176 KB, 3340 KB/s, 120 seconds passed
-... 57%, 402208 KB, 3340 KB/s, 120 seconds passed
+    ... 55%, 385856 KB, 3669 KB/s, 105 seconds passed
+... 55%, 385888 KB, 3670 KB/s, 105 seconds passed
+... 55%, 385920 KB, 3670 KB/s, 105 seconds passed
+... 55%, 385952 KB, 3669 KB/s, 105 seconds passed
+... 55%, 385984 KB, 3670 KB/s, 105 seconds passed
+... 55%, 386016 KB, 3670 KB/s, 105 seconds passed
+... 55%, 386048 KB, 3670 KB/s, 105 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 402240 KB, 3340 KB/s, 120 seconds passed
-... 57%, 402272 KB, 3340 KB/s, 120 seconds passed
-... 57%, 402304 KB, 3340 KB/s, 120 seconds passed
-... 57%, 402336 KB, 3341 KB/s, 120 seconds passed
-... 57%, 402368 KB, 3340 KB/s, 120 seconds passed
-... 57%, 402400 KB, 3340 KB/s, 120 seconds passed
-... 57%, 402432 KB, 3340 KB/s, 120 seconds passed
-... 57%, 402464 KB, 3341 KB/s, 120 seconds passed
+    ... 55%, 386080 KB, 3669 KB/s, 105 seconds passed
+... 55%, 386112 KB, 3670 KB/s, 105 seconds passed
+... 55%, 386144 KB, 3670 KB/s, 105 seconds passed
+... 55%, 386176 KB, 3670 KB/s, 105 seconds passed
+... 55%, 386208 KB, 3669 KB/s, 105 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 402496 KB, 3340 KB/s, 120 seconds passed
-... 57%, 402528 KB, 3340 KB/s, 120 seconds passed
-... 57%, 402560 KB, 3341 KB/s, 120 seconds passed
-... 57%, 402592 KB, 3341 KB/s, 120 seconds passed
+    ... 55%, 386240 KB, 3670 KB/s, 105 seconds passed
+... 55%, 386272 KB, 3670 KB/s, 105 seconds passed
+... 55%, 386304 KB, 3670 KB/s, 105 seconds passed
+... 55%, 386336 KB, 3669 KB/s, 105 seconds passed
+... 55%, 386368 KB, 3670 KB/s, 105 seconds passed
+... 55%, 386400 KB, 3670 KB/s, 105 seconds passed
+... 55%, 386432 KB, 3670 KB/s, 105 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 402624 KB, 3340 KB/s, 120 seconds passed
-... 57%, 402656 KB, 3341 KB/s, 120 seconds passed
-... 57%, 402688 KB, 3341 KB/s, 120 seconds passed
-... 57%, 402720 KB, 3341 KB/s, 120 seconds passed
-... 57%, 402752 KB, 3340 KB/s, 120 seconds passed
-... 57%, 402784 KB, 3341 KB/s, 120 seconds passed
-... 57%, 402816 KB, 3341 KB/s, 120 seconds passed
-... 57%, 402848 KB, 3341 KB/s, 120 seconds passed
+    ... 55%, 386464 KB, 3669 KB/s, 105 seconds passed
+... 55%, 386496 KB, 3670 KB/s, 105 seconds passed
+... 55%, 386528 KB, 3670 KB/s, 105 seconds passed
+... 55%, 386560 KB, 3670 KB/s, 105 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 402880 KB, 3341 KB/s, 120 seconds passed
-... 57%, 402912 KB, 3341 KB/s, 120 seconds passed
-... 57%, 402944 KB, 3341 KB/s, 120 seconds passed
-... 57%, 402976 KB, 3341 KB/s, 120 seconds passed
+    ... 55%, 386592 KB, 3669 KB/s, 105 seconds passed
+... 55%, 386624 KB, 3670 KB/s, 105 seconds passed
+... 55%, 386656 KB, 3670 KB/s, 105 seconds passed
+... 55%, 386688 KB, 3670 KB/s, 105 seconds passed
+... 55%, 386720 KB, 3669 KB/s, 105 seconds passed
+... 55%, 386752 KB, 3670 KB/s, 105 seconds passed
+... 55%, 386784 KB, 3670 KB/s, 105 seconds passed
+... 55%, 386816 KB, 3670 KB/s, 105 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 403008 KB, 3341 KB/s, 120 seconds passed
-... 57%, 403040 KB, 3341 KB/s, 120 seconds passed
-... 57%, 403072 KB, 3341 KB/s, 120 seconds passed
-... 57%, 403104 KB, 3341 KB/s, 120 seconds passed
-... 57%, 403136 KB, 3341 KB/s, 120 seconds passed
-... 57%, 403168 KB, 3341 KB/s, 120 seconds passed
-... 57%, 403200 KB, 3341 KB/s, 120 seconds passed
-... 57%, 403232 KB, 3341 KB/s, 120 seconds passed
+    ... 55%, 386848 KB, 3669 KB/s, 105 seconds passed
+... 55%, 386880 KB, 3670 KB/s, 105 seconds passed
+... 55%, 386912 KB, 3670 KB/s, 105 seconds passed
+... 55%, 386944 KB, 3670 KB/s, 105 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 403264 KB, 3341 KB/s, 120 seconds passed
-... 57%, 403296 KB, 3341 KB/s, 120 seconds passed
-... 57%, 403328 KB, 3341 KB/s, 120 seconds passed
-... 57%, 403360 KB, 3341 KB/s, 120 seconds passed
+    ... 55%, 386976 KB, 3669 KB/s, 105 seconds passed
+... 55%, 387008 KB, 3670 KB/s, 105 seconds passed
+... 55%, 387040 KB, 3670 KB/s, 105 seconds passed
+... 55%, 387072 KB, 3670 KB/s, 105 seconds passed
+... 55%, 387104 KB, 3669 KB/s, 105 seconds passed
+... 55%, 387136 KB, 3670 KB/s, 105 seconds passed
+... 55%, 387168 KB, 3670 KB/s, 105 seconds passed
+... 55%, 387200 KB, 3670 KB/s, 105 seconds passed
 
 .. parsed-literal::
 
-    ... 57%, 403392 KB, 3341 KB/s, 120 seconds passed
-... 58%, 403424 KB, 3341 KB/s, 120 seconds passed
-... 58%, 403456 KB, 3341 KB/s, 120 seconds passed
-... 58%, 403488 KB, 3341 KB/s, 120 seconds passed
-... 58%, 403520 KB, 3341 KB/s, 120 seconds passed
-... 58%, 403552 KB, 3341 KB/s, 120 seconds passed
-... 58%, 403584 KB, 3341 KB/s, 120 seconds passed
-... 58%, 403616 KB, 3342 KB/s, 120 seconds passed
+    ... 55%, 387232 KB, 3669 KB/s, 105 seconds passed
+... 55%, 387264 KB, 3670 KB/s, 105 seconds passed
+... 55%, 387296 KB, 3670 KB/s, 105 seconds passed
+... 55%, 387328 KB, 3670 KB/s, 105 seconds passed
 
 .. parsed-literal::
 
-    ... 58%, 403648 KB, 3341 KB/s, 120 seconds passed
-... 58%, 403680 KB, 3341 KB/s, 120 seconds passed
-... 58%, 403712 KB, 3341 KB/s, 120 seconds passed
-... 58%, 403744 KB, 3342 KB/s, 120 seconds passed
+    ... 55%, 387360 KB, 3669 KB/s, 105 seconds passed
+... 55%, 387392 KB, 3670 KB/s, 105 seconds passed
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+... 55%, 387456 KB, 3670 KB/s, 105 seconds passed
+... 55%, 387488 KB, 3669 KB/s, 105 seconds passed
+... 55%, 387520 KB, 3670 KB/s, 105 seconds passed
+... 55%, 387552 KB, 3670 KB/s, 105 seconds passed
+... 55%, 387584 KB, 3670 KB/s, 105 seconds passed
 
 .. parsed-literal::
 
-    ... 58%, 403776 KB, 3341 KB/s, 120 seconds passed
-... 58%, 403808 KB, 3341 KB/s, 120 seconds passed
-... 58%, 403840 KB, 3342 KB/s, 120 seconds passed
-... 58%, 403872 KB, 3342 KB/s, 120 seconds passed
-... 58%, 403904 KB, 3341 KB/s, 120 seconds passed
-... 58%, 403936 KB, 3342 KB/s, 120 seconds passed
-... 58%, 403968 KB, 3342 KB/s, 120 seconds passed
+    ... 55%, 387616 KB, 3669 KB/s, 105 seconds passed
+... 55%, 387648 KB, 3670 KB/s, 105 seconds passed
+... 55%, 387680 KB, 3670 KB/s, 105 seconds passed
+... 55%, 387712 KB, 3670 KB/s, 105 seconds passed
 
 .. parsed-literal::
 
-    ... 58%, 404000 KB, 3342 KB/s, 120 seconds passed
-... 58%, 404032 KB, 3341 KB/s, 120 seconds passed
-... 58%, 404064 KB, 3342 KB/s, 120 seconds passed
-... 58%, 404096 KB, 3342 KB/s, 120 seconds passed
-... 58%, 404128 KB, 3342 KB/s, 120 seconds passed
+    ... 55%, 387744 KB, 3669 KB/s, 105 seconds passed
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+... 55%, 387808 KB, 3670 KB/s, 105 seconds passed
+... 55%, 387840 KB, 3670 KB/s, 105 seconds passed
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+... 55%, 387904 KB, 3670 KB/s, 105 seconds passed
+... 55%, 387936 KB, 3670 KB/s, 105 seconds passed
+... 55%, 387968 KB, 3670 KB/s, 105 seconds passed
 
 .. parsed-literal::
 
-    ... 58%, 404160 KB, 3342 KB/s, 120 seconds passed
-... 58%, 404192 KB, 3342 KB/s, 120 seconds passed
-... 58%, 404224 KB, 3342 KB/s, 120 seconds passed
-... 58%, 404256 KB, 3342 KB/s, 120 seconds passed
-... 58%, 404288 KB, 3342 KB/s, 120 seconds passed
-... 58%, 404320 KB, 3342 KB/s, 120 seconds passed
-... 58%, 404352 KB, 3342 KB/s, 120 seconds passed
+    ... 55%, 388000 KB, 3669 KB/s, 105 seconds passed
+... 55%, 388032 KB, 3670 KB/s, 105 seconds passed
+... 55%, 388064 KB, 3670 KB/s, 105 seconds passed
+... 55%, 388096 KB, 3670 KB/s, 105 seconds passed
 
 .. parsed-literal::
 
-    ... 58%, 404384 KB, 3342 KB/s, 120 seconds passed
-... 58%, 404416 KB, 3342 KB/s, 121 seconds passed
-... 58%, 404448 KB, 3342 KB/s, 121 seconds passed
-... 58%, 404480 KB, 3342 KB/s, 121 seconds passed
+    ... 55%, 388128 KB, 3670 KB/s, 105 seconds passed
+... 55%, 388160 KB, 3670 KB/s, 105 seconds passed
+... 55%, 388192 KB, 3670 KB/s, 105 seconds passed
+... 55%, 388224 KB, 3670 KB/s, 105 seconds passed
+... 55%, 388256 KB, 3670 KB/s, 105 seconds passed
+... 55%, 388288 KB, 3670 KB/s, 105 seconds passed
+... 55%, 388320 KB, 3670 KB/s, 105 seconds passed
+... 55%, 388352 KB, 3670 KB/s, 105 seconds passed
 
 .. parsed-literal::
 
-    ... 58%, 404512 KB, 3342 KB/s, 121 seconds passed
-... 58%, 404544 KB, 3342 KB/s, 121 seconds passed
-... 58%, 404576 KB, 3342 KB/s, 121 seconds passed
-... 58%, 404608 KB, 3342 KB/s, 121 seconds passed
-... 58%, 404640 KB, 3342 KB/s, 121 seconds passed
-... 58%, 404672 KB, 3342 KB/s, 121 seconds passed
-... 58%, 404704 KB, 3342 KB/s, 121 seconds passed
+    ... 55%, 388384 KB, 3670 KB/s, 105 seconds passed
+... 55%, 388416 KB, 3670 KB/s, 105 seconds passed
+... 55%, 388448 KB, 3670 KB/s, 105 seconds passed
+... 55%, 388480 KB, 3670 KB/s, 105 seconds passed
 
 .. parsed-literal::
 
-    ... 58%, 404736 KB, 3342 KB/s, 121 seconds passed
-... 58%, 404768 KB, 3342 KB/s, 121 seconds passed
-... 58%, 404800 KB, 3342 KB/s, 121 seconds passed
-... 58%, 404832 KB, 3342 KB/s, 121 seconds passed
-... 58%, 404864 KB, 3342 KB/s, 121 seconds passed
+    ... 55%, 388512 KB, 3670 KB/s, 105 seconds passed
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+... 55%, 388576 KB, 3670 KB/s, 105 seconds passed
+... 55%, 388608 KB, 3670 KB/s, 105 seconds passed
+... 55%, 388640 KB, 3670 KB/s, 105 seconds passed
+... 55%, 388672 KB, 3670 KB/s, 105 seconds passed
+... 55%, 388704 KB, 3670 KB/s, 105 seconds passed
 
 .. parsed-literal::
 
-    ... 58%, 404896 KB, 3342 KB/s, 121 seconds passed
-... 58%, 404928 KB, 3342 KB/s, 121 seconds passed
-... 58%, 404960 KB, 3342 KB/s, 121 seconds passed
-... 58%, 404992 KB, 3342 KB/s, 121 seconds passed
-... 58%, 405024 KB, 3342 KB/s, 121 seconds passed
-... 58%, 405056 KB, 3342 KB/s, 121 seconds passed
+    ... 55%, 388736 KB, 3670 KB/s, 105 seconds passed
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+... 55%, 388800 KB, 3670 KB/s, 105 seconds passed
+... 55%, 388832 KB, 3670 KB/s, 105 seconds passed
+... 55%, 388864 KB, 3670 KB/s, 105 seconds passed
 
 .. parsed-literal::
 
-    ... 58%, 405088 KB, 3342 KB/s, 121 seconds passed
-... 58%, 405120 KB, 3343 KB/s, 121 seconds passed
-... 58%, 405152 KB, 3342 KB/s, 121 seconds passed
-... 58%, 405184 KB, 3342 KB/s, 121 seconds passed
-... 58%, 405216 KB, 3342 KB/s, 121 seconds passed
-... 58%, 405248 KB, 3343 KB/s, 121 seconds passed
+    ... 55%, 388896 KB, 3670 KB/s, 105 seconds passed
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+... 55%, 388992 KB, 3670 KB/s, 105 seconds passed
+... 55%, 389024 KB, 3670 KB/s, 105 seconds passed
+... 55%, 389056 KB, 3670 KB/s, 106 seconds passed
 
 .. parsed-literal::
 
-    ... 58%, 405280 KB, 3342 KB/s, 121 seconds passed
-... 58%, 405312 KB, 3342 KB/s, 121 seconds passed
-... 58%, 405344 KB, 3343 KB/s, 121 seconds passed
-... 58%, 405376 KB, 3343 KB/s, 121 seconds passed
-... 58%, 405408 KB, 3342 KB/s, 121 seconds passed
-... 58%, 405440 KB, 3343 KB/s, 121 seconds passed
+    ... 55%, 389088 KB, 3670 KB/s, 106 seconds passed
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+... 55%, 389184 KB, 3670 KB/s, 106 seconds passed
+... 55%, 389216 KB, 3670 KB/s, 106 seconds passed
+... 55%, 389248 KB, 3670 KB/s, 106 seconds passed
 
 .. parsed-literal::
 
-    ... 58%, 405472 KB, 3343 KB/s, 121 seconds passed
-... 58%, 405504 KB, 3343 KB/s, 121 seconds passed
-... 58%, 405536 KB, 3342 KB/s, 121 seconds passed
-... 58%, 405568 KB, 3343 KB/s, 121 seconds passed
-... 58%, 405600 KB, 3343 KB/s, 121 seconds passed
-... 58%, 405632 KB, 3343 KB/s, 121 seconds passed
+    ... 55%, 389280 KB, 3670 KB/s, 106 seconds passed
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+... 55%, 389344 KB, 3670 KB/s, 106 seconds passed
+... 55%, 389376 KB, 3670 KB/s, 106 seconds passed
+... 55%, 389408 KB, 3670 KB/s, 106 seconds passed
+... 55%, 389440 KB, 3670 KB/s, 106 seconds passed
 
 .. parsed-literal::
 
-    ... 58%, 405664 KB, 3343 KB/s, 121 seconds passed
-... 58%, 405696 KB, 3343 KB/s, 121 seconds passed
-... 58%, 405728 KB, 3343 KB/s, 121 seconds passed
-... 58%, 405760 KB, 3343 KB/s, 121 seconds passed
-... 58%, 405792 KB, 3343 KB/s, 121 seconds passed
-... 58%, 405824 KB, 3343 KB/s, 121 seconds passed
+    ... 55%, 389472 KB, 3670 KB/s, 106 seconds passed
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+... 56%, 389568 KB, 3670 KB/s, 106 seconds passed
+... 56%, 389600 KB, 3670 KB/s, 106 seconds passed
+... 56%, 389632 KB, 3670 KB/s, 106 seconds passed
 
 .. parsed-literal::
 
-    ... 58%, 405856 KB, 3343 KB/s, 121 seconds passed
-... 58%, 405888 KB, 3343 KB/s, 121 seconds passed
-... 58%, 405920 KB, 3343 KB/s, 121 seconds passed
-... 58%, 405952 KB, 3343 KB/s, 121 seconds passed
-... 58%, 405984 KB, 3343 KB/s, 121 seconds passed
-... 58%, 406016 KB, 3343 KB/s, 121 seconds passed
+    ... 56%, 389664 KB, 3670 KB/s, 106 seconds passed
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+... 56%, 389760 KB, 3670 KB/s, 106 seconds passed
+... 56%, 389792 KB, 3670 KB/s, 106 seconds passed
+... 56%, 389824 KB, 3670 KB/s, 106 seconds passed
 
 .. parsed-literal::
 
-    ... 58%, 406048 KB, 3343 KB/s, 121 seconds passed
-... 58%, 406080 KB, 3343 KB/s, 121 seconds passed
-... 58%, 406112 KB, 3343 KB/s, 121 seconds passed
-... 58%, 406144 KB, 3343 KB/s, 121 seconds passed
-... 58%, 406176 KB, 3343 KB/s, 121 seconds passed
-... 58%, 406208 KB, 3343 KB/s, 121 seconds passed
+    ... 56%, 389856 KB, 3670 KB/s, 106 seconds passed
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+... 56%, 389952 KB, 3670 KB/s, 106 seconds passed
+... 56%, 389984 KB, 3670 KB/s, 106 seconds passed
+... 56%, 390016 KB, 3670 KB/s, 106 seconds passed
 
 .. parsed-literal::
 
-    ... 58%, 406240 KB, 3343 KB/s, 121 seconds passed
-... 58%, 406272 KB, 3343 KB/s, 121 seconds passed
-... 58%, 406304 KB, 3343 KB/s, 121 seconds passed
-... 58%, 406336 KB, 3343 KB/s, 121 seconds passed
-... 58%, 406368 KB, 3343 KB/s, 121 seconds passed
-... 58%, 406400 KB, 3344 KB/s, 121 seconds passed
+    ... 56%, 390048 KB, 3670 KB/s, 106 seconds passed
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+... 56%, 390144 KB, 3670 KB/s, 106 seconds passed
+... 56%, 390176 KB, 3670 KB/s, 106 seconds passed
+... 56%, 390208 KB, 3670 KB/s, 106 seconds passed
 
 .. parsed-literal::
 
-    ... 58%, 406432 KB, 3343 KB/s, 121 seconds passed
-... 58%, 406464 KB, 3343 KB/s, 121 seconds passed
-... 58%, 406496 KB, 3343 KB/s, 121 seconds passed
-... 58%, 406528 KB, 3344 KB/s, 121 seconds passed
-... 58%, 406560 KB, 3343 KB/s, 121 seconds passed
-... 58%, 406592 KB, 3343 KB/s, 121 seconds passed
+    ... 56%, 390240 KB, 3670 KB/s, 106 seconds passed
+... 56%, 390272 KB, 3670 KB/s, 106 seconds passed
+... 56%, 390304 KB, 3670 KB/s, 106 seconds passed
+... 56%, 390336 KB, 3670 KB/s, 106 seconds passed
+... 56%, 390368 KB, 3670 KB/s, 106 seconds passed
+... 56%, 390400 KB, 3670 KB/s, 106 seconds passed
 
 .. parsed-literal::
 
-    ... 58%, 406624 KB, 3344 KB/s, 121 seconds passed
-... 58%, 406656 KB, 3344 KB/s, 121 seconds passed
-... 58%, 406688 KB, 3343 KB/s, 121 seconds passed
-... 58%, 406720 KB, 3344 KB/s, 121 seconds passed
-... 58%, 406752 KB, 3344 KB/s, 121 seconds passed
-... 58%, 406784 KB, 3344 KB/s, 121 seconds passed
+    ... 56%, 390432 KB, 3670 KB/s, 106 seconds passed
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+... 56%, 390496 KB, 3670 KB/s, 106 seconds passed
+... 56%, 390528 KB, 3670 KB/s, 106 seconds passed
+... 56%, 390560 KB, 3670 KB/s, 106 seconds passed
 
 .. parsed-literal::
 
-    ... 58%, 406816 KB, 3343 KB/s, 121 seconds passed
-... 58%, 406848 KB, 3344 KB/s, 121 seconds passed
-... 58%, 406880 KB, 3344 KB/s, 121 seconds passed
-... 58%, 406912 KB, 3344 KB/s, 121 seconds passed
-... 58%, 406944 KB, 3344 KB/s, 121 seconds passed
+    ... 56%, 390592 KB, 3670 KB/s, 106 seconds passed
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+... 56%, 390656 KB, 3670 KB/s, 106 seconds passed
+... 56%, 390688 KB, 3670 KB/s, 106 seconds passed
+... 56%, 390720 KB, 3670 KB/s, 106 seconds passed
+... 56%, 390752 KB, 3670 KB/s, 106 seconds passed
 
 .. parsed-literal::
 
-    ... 58%, 406976 KB, 3344 KB/s, 121 seconds passed
-... 58%, 407008 KB, 3344 KB/s, 121 seconds passed
-... 58%, 407040 KB, 3344 KB/s, 121 seconds passed
-... 58%, 407072 KB, 3344 KB/s, 121 seconds passed
-... 58%, 407104 KB, 3344 KB/s, 121 seconds passed
-... 58%, 407136 KB, 3344 KB/s, 121 seconds passed
+    ... 56%, 390784 KB, 3670 KB/s, 106 seconds passed
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+... 56%, 390848 KB, 3670 KB/s, 106 seconds passed
+... 56%, 390880 KB, 3670 KB/s, 106 seconds passed
+... 56%, 390912 KB, 3670 KB/s, 106 seconds passed
+... 56%, 390944 KB, 3670 KB/s, 106 seconds passed
 
 .. parsed-literal::
 
-    ... 58%, 407168 KB, 3344 KB/s, 121 seconds passed
-... 58%, 407200 KB, 3344 KB/s, 121 seconds passed
-... 58%, 407232 KB, 3344 KB/s, 121 seconds passed
-... 58%, 407264 KB, 3344 KB/s, 121 seconds passed
-... 58%, 407296 KB, 3344 KB/s, 121 seconds passed
+    ... 56%, 390976 KB, 3670 KB/s, 106 seconds passed
+... 56%, 391008 KB, 3670 KB/s, 106 seconds passed
+... 56%, 391040 KB, 3670 KB/s, 106 seconds passed
+... 56%, 391072 KB, 3670 KB/s, 106 seconds passed
+... 56%, 391104 KB, 3670 KB/s, 106 seconds passed
+... 56%, 391136 KB, 3670 KB/s, 106 seconds passed
 
 .. parsed-literal::
 
-    ... 58%, 407328 KB, 3344 KB/s, 121 seconds passed
-... 58%, 407360 KB, 3344 KB/s, 121 seconds passed
-... 58%, 407392 KB, 3344 KB/s, 121 seconds passed
-... 58%, 407424 KB, 3344 KB/s, 121 seconds passed
-... 58%, 407456 KB, 3344 KB/s, 121 seconds passed
-... 58%, 407488 KB, 3344 KB/s, 121 seconds passed
-... 58%, 407520 KB, 3344 KB/s, 121 seconds passed
+    ... 56%, 391168 KB, 3670 KB/s, 106 seconds passed
+... 56%, 391200 KB, 3670 KB/s, 106 seconds passed
+... 56%, 391232 KB, 3670 KB/s, 106 seconds passed
+... 56%, 391264 KB, 3670 KB/s, 106 seconds passed
+... 56%, 391296 KB, 3670 KB/s, 106 seconds passed
+... 56%, 391328 KB, 3670 KB/s, 106 seconds passed
 
 .. parsed-literal::
 
-    ... 58%, 407552 KB, 3344 KB/s, 121 seconds passed
-... 58%, 407584 KB, 3344 KB/s, 121 seconds passed
-... 58%, 407616 KB, 3344 KB/s, 121 seconds passed
-... 58%, 407648 KB, 3344 KB/s, 121 seconds passed
-... 58%, 407680 KB, 3344 KB/s, 121 seconds passed
+    ... 56%, 391360 KB, 3670 KB/s, 106 seconds passed
+... 56%, 391392 KB, 3670 KB/s, 106 seconds passed
+... 56%, 391424 KB, 3670 KB/s, 106 seconds passed
+... 56%, 391456 KB, 3670 KB/s, 106 seconds passed
+... 56%, 391488 KB, 3670 KB/s, 106 seconds passed
+... 56%, 391520 KB, 3670 KB/s, 106 seconds passed
 
 .. parsed-literal::
 
-    ... 58%, 407712 KB, 3344 KB/s, 121 seconds passed
-... 58%, 407744 KB, 3344 KB/s, 121 seconds passed
-... 58%, 407776 KB, 3344 KB/s, 121 seconds passed
-... 58%, 407808 KB, 3344 KB/s, 121 seconds passed
-... 58%, 407840 KB, 3344 KB/s, 121 seconds passed
-... 58%, 407872 KB, 3344 KB/s, 121 seconds passed
-... 58%, 407904 KB, 3345 KB/s, 121 seconds passed
+    ... 56%, 391552 KB, 3670 KB/s, 106 seconds passed
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+... 56%, 391616 KB, 3670 KB/s, 106 seconds passed
+... 56%, 391648 KB, 3670 KB/s, 106 seconds passed
+... 56%, 391680 KB, 3670 KB/s, 106 seconds passed
+... 56%, 391712 KB, 3670 KB/s, 106 seconds passed
 
 .. parsed-literal::
 
-    ... 58%, 407936 KB, 3344 KB/s, 121 seconds passed
-... 58%, 407968 KB, 3344 KB/s, 121 seconds passed
-... 58%, 408000 KB, 3345 KB/s, 121 seconds passed
-... 58%, 408032 KB, 3345 KB/s, 121 seconds passed
-... 58%, 408064 KB, 3344 KB/s, 121 seconds passed
+    ... 56%, 391744 KB, 3670 KB/s, 106 seconds passed
+... 56%, 391776 KB, 3670 KB/s, 106 seconds passed
+... 56%, 391808 KB, 3670 KB/s, 106 seconds passed
+... 56%, 391840 KB, 3670 KB/s, 106 seconds passed
+... 56%, 391872 KB, 3670 KB/s, 106 seconds passed
+... 56%, 391904 KB, 3670 KB/s, 106 seconds passed
 
 .. parsed-literal::
 
-    ... 58%, 408096 KB, 3344 KB/s, 122 seconds passed
-... 58%, 408128 KB, 3345 KB/s, 122 seconds passed
-... 58%, 408160 KB, 3345 KB/s, 122 seconds passed
-... 58%, 408192 KB, 3344 KB/s, 122 seconds passed
-... 58%, 408224 KB, 3345 KB/s, 122 seconds passed
-... 58%, 408256 KB, 3345 KB/s, 122 seconds passed
-... 58%, 408288 KB, 3345 KB/s, 122 seconds passed
+    ... 56%, 391936 KB, 3670 KB/s, 106 seconds passed
+... 56%, 391968 KB, 3670 KB/s, 106 seconds passed
+... 56%, 392000 KB, 3670 KB/s, 106 seconds passed
+... 56%, 392032 KB, 3670 KB/s, 106 seconds passed
+... 56%, 392064 KB, 3670 KB/s, 106 seconds passed
+... 56%, 392096 KB, 3670 KB/s, 106 seconds passed
 
 .. parsed-literal::
 
-    ... 58%, 408320 KB, 3345 KB/s, 122 seconds passed
-... 58%, 408352 KB, 3345 KB/s, 122 seconds passed
-... 58%, 408384 KB, 3345 KB/s, 122 seconds passed
-... 58%, 408416 KB, 3345 KB/s, 122 seconds passed
-... 58%, 408448 KB, 3345 KB/s, 122 seconds passed
+    ... 56%, 392128 KB, 3670 KB/s, 106 seconds passed
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+... 56%, 392224 KB, 3670 KB/s, 106 seconds passed
+... 56%, 392256 KB, 3670 KB/s, 106 seconds passed
+... 56%, 392288 KB, 3670 KB/s, 106 seconds passed
 
 .. parsed-literal::
 
-    ... 58%, 408480 KB, 3345 KB/s, 122 seconds passed
-... 58%, 408512 KB, 3345 KB/s, 122 seconds passed
-... 58%, 408544 KB, 3344 KB/s, 122 seconds passed
-... 58%, 408576 KB, 3344 KB/s, 122 seconds passed
-... 58%, 408608 KB, 3345 KB/s, 122 seconds passed
-... 58%, 408640 KB, 3345 KB/s, 122 seconds passed
+    ... 56%, 392320 KB, 3670 KB/s, 106 seconds passed
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+... 56%, 392384 KB, 3670 KB/s, 106 seconds passed
+... 56%, 392416 KB, 3670 KB/s, 106 seconds passed
+... 56%, 392448 KB, 3670 KB/s, 106 seconds passed
 
 .. parsed-literal::
 
-    ... 58%, 408672 KB, 3344 KB/s, 122 seconds passed
+    ... 56%, 392480 KB, 3670 KB/s, 106 seconds passed
+... 56%, 392512 KB, 3670 KB/s, 106 seconds passed
+... 56%, 392544 KB, 3670 KB/s, 106 seconds passed
+... 56%, 392576 KB, 3670 KB/s, 106 seconds passed
+... 56%, 392608 KB, 3670 KB/s, 106 seconds passed
+... 56%, 392640 KB, 3670 KB/s, 106 seconds passed
+... 56%, 392672 KB, 3670 KB/s, 106 seconds passed
 
 .. parsed-literal::
 
-    ... 58%, 408704 KB, 3344 KB/s, 122 seconds passed
-... 58%, 408736 KB, 3343 KB/s, 122 seconds passed
+    ... 56%, 392704 KB, 3670 KB/s, 106 seconds passed
+... 56%, 392736 KB, 3670 KB/s, 107 seconds passed
+... 56%, 392768 KB, 3670 KB/s, 107 seconds passed
+... 56%, 392800 KB, 3670 KB/s, 107 seconds passed
+... 56%, 392832 KB, 3670 KB/s, 107 seconds passed
 
 .. parsed-literal::
 
-    ... 58%, 408768 KB, 3342 KB/s, 122 seconds passed
+    ... 56%, 392864 KB, 3670 KB/s, 107 seconds passed
+... 56%, 392896 KB, 3670 KB/s, 107 seconds passed
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+... 56%, 392960 KB, 3670 KB/s, 107 seconds passed
+... 56%, 392992 KB, 3670 KB/s, 107 seconds passed
+... 56%, 393024 KB, 3670 KB/s, 107 seconds passed
+... 56%, 393056 KB, 3670 KB/s, 107 seconds passed
 
 .. parsed-literal::
 
-    ... 58%, 408800 KB, 3341 KB/s, 122 seconds passed
-... 58%, 408832 KB, 3342 KB/s, 122 seconds passed
-... 58%, 408864 KB, 3341 KB/s, 122 seconds passed
+    ... 56%, 393088 KB, 3670 KB/s, 107 seconds passed
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+... 56%, 393152 KB, 3670 KB/s, 107 seconds passed
+... 56%, 393184 KB, 3670 KB/s, 107 seconds passed
+... 56%, 393216 KB, 3670 KB/s, 107 seconds passed
 
 .. parsed-literal::
 
-    ... 58%, 408896 KB, 3341 KB/s, 122 seconds passed
-... 58%, 408928 KB, 3341 KB/s, 122 seconds passed
-... 58%, 408960 KB, 3341 KB/s, 122 seconds passed
+    ... 56%, 393248 KB, 3670 KB/s, 107 seconds passed
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+... 56%, 393376 KB, 3670 KB/s, 107 seconds passed
+... 56%, 393408 KB, 3670 KB/s, 107 seconds passed
+... 56%, 393440 KB, 3670 KB/s, 107 seconds passed
 
 .. parsed-literal::
 
-    ... 58%, 408992 KB, 3340 KB/s, 122 seconds passed
-... 58%, 409024 KB, 3340 KB/s, 122 seconds passed
-... 58%, 409056 KB, 3341 KB/s, 122 seconds passed
-... 58%, 409088 KB, 3340 KB/s, 122 seconds passed
+    ... 56%, 393472 KB, 3670 KB/s, 107 seconds passed
+... 56%, 393504 KB, 3670 KB/s, 107 seconds passed
+... 56%, 393536 KB, 3670 KB/s, 107 seconds passed
+... 56%, 393568 KB, 3670 KB/s, 107 seconds passed
 
 .. parsed-literal::
 
-    ... 58%, 409120 KB, 3340 KB/s, 122 seconds passed
-... 58%, 409152 KB, 3340 KB/s, 122 seconds passed
-... 58%, 409184 KB, 3340 KB/s, 122 seconds passed
-... 58%, 409216 KB, 3340 KB/s, 122 seconds passed
-... 58%, 409248 KB, 3340 KB/s, 122 seconds passed
+    ... 56%, 393600 KB, 3670 KB/s, 107 seconds passed
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+... 56%, 393760 KB, 3670 KB/s, 107 seconds passed
+... 56%, 393792 KB, 3670 KB/s, 107 seconds passed
+... 56%, 393824 KB, 3670 KB/s, 107 seconds passed
 
 .. parsed-literal::
 
-    ... 58%, 409280 KB, 3340 KB/s, 122 seconds passed
-... 58%, 409312 KB, 3340 KB/s, 122 seconds passed
-... 58%, 409344 KB, 3340 KB/s, 122 seconds passed
-... 58%, 409376 KB, 3340 KB/s, 122 seconds passed
+    ... 56%, 393856 KB, 3670 KB/s, 107 seconds passed
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+... 56%, 393920 KB, 3670 KB/s, 107 seconds passed
+... 56%, 393952 KB, 3670 KB/s, 107 seconds passed
 
 .. parsed-literal::
 
-    ... 58%, 409408 KB, 3340 KB/s, 122 seconds passed
-... 58%, 409440 KB, 3340 KB/s, 122 seconds passed
-... 58%, 409472 KB, 3340 KB/s, 122 seconds passed
-... 58%, 409504 KB, 3340 KB/s, 122 seconds passed
-... 58%, 409536 KB, 3340 KB/s, 122 seconds passed
-... 58%, 409568 KB, 3340 KB/s, 122 seconds passed
-... 58%, 409600 KB, 3340 KB/s, 122 seconds passed
+    ... 56%, 393984 KB, 3670 KB/s, 107 seconds passed
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+... 56%, 394112 KB, 3670 KB/s, 107 seconds passed
+... 56%, 394144 KB, 3670 KB/s, 107 seconds passed
+... 56%, 394176 KB, 3670 KB/s, 107 seconds passed
 
 .. parsed-literal::
 
-    ... 58%, 409632 KB, 3340 KB/s, 122 seconds passed
-... 58%, 409664 KB, 3340 KB/s, 122 seconds passed
-... 58%, 409696 KB, 3340 KB/s, 122 seconds passed
-... 58%, 409728 KB, 3340 KB/s, 122 seconds passed
+    ... 56%, 394208 KB, 3670 KB/s, 107 seconds passed
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+... 56%, 394272 KB, 3670 KB/s, 107 seconds passed
+... 56%, 394304 KB, 3670 KB/s, 107 seconds passed
+... 56%, 394336 KB, 3670 KB/s, 107 seconds passed
 
 .. parsed-literal::
 
-    ... 58%, 409760 KB, 3340 KB/s, 122 seconds passed
-... 58%, 409792 KB, 3340 KB/s, 122 seconds passed
-... 58%, 409824 KB, 3340 KB/s, 122 seconds passed
-... 58%, 409856 KB, 3340 KB/s, 122 seconds passed
-... 58%, 409888 KB, 3340 KB/s, 122 seconds passed
-... 58%, 409920 KB, 3340 KB/s, 122 seconds passed
-... 58%, 409952 KB, 3340 KB/s, 122 seconds passed
-... 58%, 409984 KB, 3341 KB/s, 122 seconds passed
+    ... 56%, 394368 KB, 3670 KB/s, 107 seconds passed
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+... 56%, 394496 KB, 3670 KB/s, 107 seconds passed
+... 56%, 394528 KB, 3670 KB/s, 107 seconds passed
+... 56%, 394560 KB, 3670 KB/s, 107 seconds passed
 
 .. parsed-literal::
 
-    ... 58%, 410016 KB, 3340 KB/s, 122 seconds passed
-... 58%, 410048 KB, 3340 KB/s, 122 seconds passed
-... 58%, 410080 KB, 3340 KB/s, 122 seconds passed
-... 58%, 410112 KB, 3341 KB/s, 122 seconds passed
+    ... 56%, 394592 KB, 3670 KB/s, 107 seconds passed
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+... 56%, 394656 KB, 3670 KB/s, 107 seconds passed
+... 56%, 394688 KB, 3670 KB/s, 107 seconds passed
+... 56%, 394720 KB, 3670 KB/s, 107 seconds passed
 
 .. parsed-literal::
 
-    ... 58%, 410144 KB, 3340 KB/s, 122 seconds passed
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-... 58%, 410208 KB, 3341 KB/s, 122 seconds passed
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-... 58%, 410272 KB, 3340 KB/s, 122 seconds passed
-... 58%, 410304 KB, 3340 KB/s, 122 seconds passed
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-... 59%, 410368 KB, 3341 KB/s, 122 seconds passed
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+... 56%, 394880 KB, 3670 KB/s, 107 seconds passed
+... 56%, 394912 KB, 3670 KB/s, 107 seconds passed
+... 56%, 394944 KB, 3670 KB/s, 107 seconds passed
 
 .. parsed-literal::
 
-    ... 59%, 410400 KB, 3340 KB/s, 122 seconds passed
-... 59%, 410432 KB, 3341 KB/s, 122 seconds passed
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-... 59%, 410496 KB, 3341 KB/s, 122 seconds passed
+    ... 56%, 394976 KB, 3670 KB/s, 107 seconds passed
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+... 56%, 395104 KB, 3670 KB/s, 107 seconds passed
 
 .. parsed-literal::
 
-    ... 59%, 410528 KB, 3341 KB/s, 122 seconds passed
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-... 59%, 410752 KB, 3341 KB/s, 122 seconds passed
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+... 56%, 395328 KB, 3670 KB/s, 107 seconds passed
 
 .. parsed-literal::
 
-    ... 59%, 410784 KB, 3341 KB/s, 122 seconds passed
-... 59%, 410816 KB, 3341 KB/s, 122 seconds passed
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 .. parsed-literal::
 
-    ... 59%, 410912 KB, 3341 KB/s, 122 seconds passed
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+    ... 56%, 395520 KB, 3670 KB/s, 107 seconds passed
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 .. parsed-literal::
 
-    ... 59%, 411072 KB, 3340 KB/s, 123 seconds passed
-... 59%, 411104 KB, 3340 KB/s, 123 seconds passed
-... 59%, 411136 KB, 3341 KB/s, 123 seconds passed
-... 59%, 411168 KB, 3341 KB/s, 123 seconds passed
+    ... 56%, 395712 KB, 3670 KB/s, 107 seconds passed
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 .. parsed-literal::
 
-    ... 59%, 411200 KB, 3339 KB/s, 123 seconds passed
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+... 56%, 396064 KB, 3670 KB/s, 107 seconds passed
 
 .. parsed-literal::
 
-    ... 59%, 411232 KB, 3339 KB/s, 123 seconds passed
-... 59%, 411264 KB, 3339 KB/s, 123 seconds passed
+    ... 56%, 396096 KB, 3670 KB/s, 107 seconds passed
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+... 56%, 396224 KB, 3670 KB/s, 107 seconds passed
 
 .. parsed-literal::
 
-    ... 59%, 411296 KB, 3338 KB/s, 123 seconds passed
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+    ... 56%, 396256 KB, 3670 KB/s, 107 seconds passed
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+... 57%, 396448 KB, 3670 KB/s, 108 seconds passed
 
 .. parsed-literal::
 
-    ... 59%, 411392 KB, 3337 KB/s, 123 seconds passed
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+    ... 57%, 396480 KB, 3670 KB/s, 108 seconds passed
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+... 57%, 396608 KB, 3670 KB/s, 108 seconds passed
 
 .. parsed-literal::
 
-    ... 59%, 411456 KB, 3337 KB/s, 123 seconds passed
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-... 59%, 411520 KB, 3336 KB/s, 123 seconds passed
+    ... 57%, 396640 KB, 3670 KB/s, 108 seconds passed
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+... 57%, 396800 KB, 3670 KB/s, 108 seconds passed
+... 57%, 396832 KB, 3670 KB/s, 108 seconds passed
 
 .. parsed-literal::
 
-    ... 59%, 411552 KB, 3336 KB/s, 123 seconds passed
-... 59%, 411584 KB, 3336 KB/s, 123 seconds passed
+    ... 57%, 396864 KB, 3670 KB/s, 108 seconds passed
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+... 57%, 396960 KB, 3670 KB/s, 108 seconds passed
+... 57%, 396992 KB, 3670 KB/s, 108 seconds passed
 
 .. parsed-literal::
 
-    ... 59%, 411616 KB, 3335 KB/s, 123 seconds passed
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-... 59%, 411680 KB, 3335 KB/s, 123 seconds passed
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+    ... 57%, 397024 KB, 3670 KB/s, 108 seconds passed
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+... 57%, 397152 KB, 3670 KB/s, 108 seconds passed
+... 57%, 397184 KB, 3670 KB/s, 108 seconds passed
+... 57%, 397216 KB, 3670 KB/s, 108 seconds passed
 
 .. parsed-literal::
 
-    ... 59%, 411776 KB, 3335 KB/s, 123 seconds passed
-... 59%, 411808 KB, 3335 KB/s, 123 seconds passed
+    ... 57%, 397248 KB, 3670 KB/s, 108 seconds passed
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+... 57%, 397344 KB, 3670 KB/s, 108 seconds passed
+... 57%, 397376 KB, 3670 KB/s, 108 seconds passed
 
 .. parsed-literal::
 
-    ... 59%, 411840 KB, 3334 KB/s, 123 seconds passed
-... 59%, 411872 KB, 3334 KB/s, 123 seconds passed
-... 59%, 411904 KB, 3335 KB/s, 123 seconds passed
-... 59%, 411936 KB, 3334 KB/s, 123 seconds passed
-... 59%, 411968 KB, 3334 KB/s, 123 seconds passed
+    ... 57%, 397408 KB, 3670 KB/s, 108 seconds passed
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+... 57%, 397536 KB, 3670 KB/s, 108 seconds passed
+... 57%, 397568 KB, 3670 KB/s, 108 seconds passed
+... 57%, 397600 KB, 3670 KB/s, 108 seconds passed
 
 .. parsed-literal::
 
-    ... 59%, 412000 KB, 3334 KB/s, 123 seconds passed
-... 59%, 412032 KB, 3334 KB/s, 123 seconds passed
-... 59%, 412064 KB, 3334 KB/s, 123 seconds passed
+    ... 57%, 397632 KB, 3670 KB/s, 108 seconds passed
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+... 57%, 397696 KB, 3670 KB/s, 108 seconds passed
+... 57%, 397728 KB, 3670 KB/s, 108 seconds passed
+... 57%, 397760 KB, 3670 KB/s, 108 seconds passed
 
 .. parsed-literal::
 
-    ... 59%, 412096 KB, 3334 KB/s, 123 seconds passed
-... 59%, 412128 KB, 3334 KB/s, 123 seconds passed
-... 59%, 412160 KB, 3334 KB/s, 123 seconds passed
-... 59%, 412192 KB, 3334 KB/s, 123 seconds passed
-... 59%, 412224 KB, 3334 KB/s, 123 seconds passed
-... 59%, 412256 KB, 3334 KB/s, 123 seconds passed
+    ... 57%, 397792 KB, 3670 KB/s, 108 seconds passed
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+... 57%, 397888 KB, 3670 KB/s, 108 seconds passed
+... 57%, 397920 KB, 3670 KB/s, 108 seconds passed
+... 57%, 397952 KB, 3670 KB/s, 108 seconds passed
 
 .. parsed-literal::
 
-    ... 59%, 412288 KB, 3334 KB/s, 123 seconds passed
-... 59%, 412320 KB, 3333 KB/s, 123 seconds passed
-... 59%, 412352 KB, 3334 KB/s, 123 seconds passed
-... 59%, 412384 KB, 3334 KB/s, 123 seconds passed
+    ... 57%, 397984 KB, 3670 KB/s, 108 seconds passed
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+... 57%, 398112 KB, 3670 KB/s, 108 seconds passed
+... 57%, 398144 KB, 3670 KB/s, 108 seconds passed
 
 .. parsed-literal::
 
-    ... 59%, 412416 KB, 3333 KB/s, 123 seconds passed
-... 59%, 412448 KB, 3334 KB/s, 123 seconds passed
-... 59%, 412480 KB, 3334 KB/s, 123 seconds passed
-... 59%, 412512 KB, 3334 KB/s, 123 seconds passed
-... 59%, 412544 KB, 3333 KB/s, 123 seconds passed
-... 59%, 412576 KB, 3334 KB/s, 123 seconds passed
+    ... 57%, 398176 KB, 3670 KB/s, 108 seconds passed
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+... 57%, 398240 KB, 3670 KB/s, 108 seconds passed
+... 57%, 398272 KB, 3670 KB/s, 108 seconds passed
+... 57%, 398304 KB, 3670 KB/s, 108 seconds passed
+... 57%, 398336 KB, 3670 KB/s, 108 seconds passed
 
 .. parsed-literal::
 
-    ... 59%, 412608 KB, 3334 KB/s, 123 seconds passed
-... 59%, 412640 KB, 3334 KB/s, 123 seconds passed
-... 59%, 412672 KB, 3334 KB/s, 123 seconds passed
-... 59%, 412704 KB, 3334 KB/s, 123 seconds passed
-... 59%, 412736 KB, 3334 KB/s, 123 seconds passed
-... 59%, 412768 KB, 3334 KB/s, 123 seconds passed
+    ... 57%, 398368 KB, 3670 KB/s, 108 seconds passed
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+... 57%, 398464 KB, 3670 KB/s, 108 seconds passed
+... 57%, 398496 KB, 3670 KB/s, 108 seconds passed
+... 57%, 398528 KB, 3670 KB/s, 108 seconds passed
 
 .. parsed-literal::
 
-    ... 59%, 412800 KB, 3334 KB/s, 123 seconds passed
-... 59%, 412832 KB, 3334 KB/s, 123 seconds passed
-... 59%, 412864 KB, 3334 KB/s, 123 seconds passed
-... 59%, 412896 KB, 3334 KB/s, 123 seconds passed
-... 59%, 412928 KB, 3334 KB/s, 123 seconds passed
+    ... 57%, 398560 KB, 3670 KB/s, 108 seconds passed
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+... 57%, 398656 KB, 3670 KB/s, 108 seconds passed
+... 57%, 398688 KB, 3670 KB/s, 108 seconds passed
+... 57%, 398720 KB, 3670 KB/s, 108 seconds passed
 
 .. parsed-literal::
 
-    ... 59%, 412960 KB, 3334 KB/s, 123 seconds passed
-... 59%, 412992 KB, 3334 KB/s, 123 seconds passed
-... 59%, 413024 KB, 3334 KB/s, 123 seconds passed
-... 59%, 413056 KB, 3334 KB/s, 123 seconds passed
-... 59%, 413088 KB, 3334 KB/s, 123 seconds passed
-... 59%, 413120 KB, 3334 KB/s, 123 seconds passed
-... 59%, 413152 KB, 3334 KB/s, 123 seconds passed
+    ... 57%, 398752 KB, 3670 KB/s, 108 seconds passed
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+... 57%, 398848 KB, 3670 KB/s, 108 seconds passed
+... 57%, 398880 KB, 3670 KB/s, 108 seconds passed
+... 57%, 398912 KB, 3670 KB/s, 108 seconds passed
 
 .. parsed-literal::
 
-    ... 59%, 413184 KB, 3334 KB/s, 123 seconds passed
-... 59%, 413216 KB, 3334 KB/s, 123 seconds passed
-... 59%, 413248 KB, 3334 KB/s, 123 seconds passed
-... 59%, 413280 KB, 3334 KB/s, 123 seconds passed
-... 59%, 413312 KB, 3334 KB/s, 123 seconds passed
+    ... 57%, 398944 KB, 3670 KB/s, 108 seconds passed
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+... 57%, 399008 KB, 3670 KB/s, 108 seconds passed
+... 57%, 399040 KB, 3670 KB/s, 108 seconds passed
+... 57%, 399072 KB, 3670 KB/s, 108 seconds passed
 
 .. parsed-literal::
 
-    ... 59%, 413344 KB, 3334 KB/s, 123 seconds passed
-... 59%, 413376 KB, 3334 KB/s, 123 seconds passed
-... 59%, 413408 KB, 3334 KB/s, 123 seconds passed
-... 59%, 413440 KB, 3334 KB/s, 123 seconds passed
-... 59%, 413472 KB, 3334 KB/s, 123 seconds passed
-... 59%, 413504 KB, 3334 KB/s, 123 seconds passed
+    ... 57%, 399104 KB, 3670 KB/s, 108 seconds passed
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+... 57%, 399232 KB, 3670 KB/s, 108 seconds passed
+... 57%, 399264 KB, 3670 KB/s, 108 seconds passed
+... 57%, 399296 KB, 3670 KB/s, 108 seconds passed
 
 .. parsed-literal::
 
-    ... 59%, 413536 KB, 3334 KB/s, 124 seconds passed
-... 59%, 413568 KB, 3334 KB/s, 124 seconds passed
-... 59%, 413600 KB, 3334 KB/s, 124 seconds passed
-... 59%, 413632 KB, 3334 KB/s, 124 seconds passed
-... 59%, 413664 KB, 3334 KB/s, 124 seconds passed
-... 59%, 413696 KB, 3334 KB/s, 124 seconds passed
+    ... 57%, 399328 KB, 3670 KB/s, 108 seconds passed
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+... 57%, 399392 KB, 3670 KB/s, 108 seconds passed
+... 57%, 399424 KB, 3670 KB/s, 108 seconds passed
+... 57%, 399456 KB, 3670 KB/s, 108 seconds passed
 
 .. parsed-literal::
 
-    ... 59%, 413728 KB, 3334 KB/s, 124 seconds passed
-... 59%, 413760 KB, 3335 KB/s, 124 seconds passed
-... 59%, 413792 KB, 3334 KB/s, 124 seconds passed
-... 59%, 413824 KB, 3334 KB/s, 124 seconds passed
-... 59%, 413856 KB, 3335 KB/s, 124 seconds passed
-... 59%, 413888 KB, 3335 KB/s, 124 seconds passed
+    ... 57%, 399488 KB, 3670 KB/s, 108 seconds passed
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+... 57%, 399616 KB, 3670 KB/s, 108 seconds passed
+... 57%, 399648 KB, 3670 KB/s, 108 seconds passed
+... 57%, 399680 KB, 3670 KB/s, 108 seconds passed
 
 .. parsed-literal::
 
-    ... 59%, 413920 KB, 3334 KB/s, 124 seconds passed
-... 59%, 413952 KB, 3335 KB/s, 124 seconds passed
-... 59%, 413984 KB, 3335 KB/s, 124 seconds passed
-... 59%, 414016 KB, 3335 KB/s, 124 seconds passed
-... 59%, 414048 KB, 3335 KB/s, 124 seconds passed
+    ... 57%, 399712 KB, 3670 KB/s, 108 seconds passed
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+... 57%, 399776 KB, 3670 KB/s, 108 seconds passed
+... 57%, 399808 KB, 3670 KB/s, 108 seconds passed
+... 57%, 399840 KB, 3670 KB/s, 108 seconds passed
 
 .. parsed-literal::
 
-    ... 59%, 414080 KB, 3335 KB/s, 124 seconds passed
-... 59%, 414112 KB, 3335 KB/s, 124 seconds passed
-... 59%, 414144 KB, 3335 KB/s, 124 seconds passed
-... 59%, 414176 KB, 3335 KB/s, 124 seconds passed
-... 59%, 414208 KB, 3335 KB/s, 124 seconds passed
-... 59%, 414240 KB, 3335 KB/s, 124 seconds passed
-... 59%, 414272 KB, 3335 KB/s, 124 seconds passed
+    ... 57%, 399872 KB, 3670 KB/s, 108 seconds passed
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+... 57%, 399968 KB, 3670 KB/s, 108 seconds passed
+... 57%, 400000 KB, 3670 KB/s, 108 seconds passed
+... 57%, 400032 KB, 3670 KB/s, 108 seconds passed
 
 .. parsed-literal::
 
-    ... 59%, 414304 KB, 3335 KB/s, 124 seconds passed
-... 59%, 414336 KB, 3335 KB/s, 124 seconds passed
-... 59%, 414368 KB, 3335 KB/s, 124 seconds passed
-... 59%, 414400 KB, 3335 KB/s, 124 seconds passed
-... 59%, 414432 KB, 3335 KB/s, 124 seconds passed
+    ... 57%, 400064 KB, 3670 KB/s, 108 seconds passed
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+... 57%, 400160 KB, 3670 KB/s, 109 seconds passed
+... 57%, 400192 KB, 3670 KB/s, 109 seconds passed
+... 57%, 400224 KB, 3670 KB/s, 109 seconds passed
 
 .. parsed-literal::
 
-    ... 59%, 414464 KB, 3335 KB/s, 124 seconds passed
-... 59%, 414496 KB, 3335 KB/s, 124 seconds passed
-... 59%, 414528 KB, 3335 KB/s, 124 seconds passed
-... 59%, 414560 KB, 3335 KB/s, 124 seconds passed
-... 59%, 414592 KB, 3335 KB/s, 124 seconds passed
-... 59%, 414624 KB, 3335 KB/s, 124 seconds passed
-... 59%, 414656 KB, 3335 KB/s, 124 seconds passed
+    ... 57%, 400256 KB, 3670 KB/s, 109 seconds passed
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+... 57%, 400352 KB, 3670 KB/s, 109 seconds passed
+... 57%, 400384 KB, 3670 KB/s, 109 seconds passed
+... 57%, 400416 KB, 3670 KB/s, 109 seconds passed
 
 .. parsed-literal::
 
-    ... 59%, 414688 KB, 3335 KB/s, 124 seconds passed
-... 59%, 414720 KB, 3335 KB/s, 124 seconds passed
-... 59%, 414752 KB, 3335 KB/s, 124 seconds passed
-... 59%, 414784 KB, 3335 KB/s, 124 seconds passed
-... 59%, 414816 KB, 3335 KB/s, 124 seconds passed
+    ... 57%, 400448 KB, 3670 KB/s, 109 seconds passed
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+... 57%, 400512 KB, 3670 KB/s, 109 seconds passed
+... 57%, 400544 KB, 3670 KB/s, 109 seconds passed
+... 57%, 400576 KB, 3670 KB/s, 109 seconds passed
 
 .. parsed-literal::
 
-    ... 59%, 414848 KB, 3335 KB/s, 124 seconds passed
-... 59%, 414880 KB, 3335 KB/s, 124 seconds passed
-... 59%, 414912 KB, 3335 KB/s, 124 seconds passed
-... 59%, 414944 KB, 3335 KB/s, 124 seconds passed
-... 59%, 414976 KB, 3335 KB/s, 124 seconds passed
-... 59%, 415008 KB, 3335 KB/s, 124 seconds passed
-... 59%, 415040 KB, 3336 KB/s, 124 seconds passed
+    ... 57%, 400608 KB, 3670 KB/s, 109 seconds passed
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+... 57%, 400736 KB, 3670 KB/s, 109 seconds passed
+... 57%, 400768 KB, 3670 KB/s, 109 seconds passed
+... 57%, 400800 KB, 3670 KB/s, 109 seconds passed
 
 .. parsed-literal::
 
-    ... 59%, 415072 KB, 3335 KB/s, 124 seconds passed
-... 59%, 415104 KB, 3335 KB/s, 124 seconds passed
-... 59%, 415136 KB, 3336 KB/s, 124 seconds passed
-... 59%, 415168 KB, 3336 KB/s, 124 seconds passed
-... 59%, 415200 KB, 3335 KB/s, 124 seconds passed
+    ... 57%, 400832 KB, 3670 KB/s, 109 seconds passed
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+... 57%, 400896 KB, 3670 KB/s, 109 seconds passed
+... 57%, 400928 KB, 3670 KB/s, 109 seconds passed
+... 57%, 400960 KB, 3670 KB/s, 109 seconds passed
 
 .. parsed-literal::
 
-    ... 59%, 415232 KB, 3336 KB/s, 124 seconds passed
-... 59%, 415264 KB, 3336 KB/s, 124 seconds passed
-... 59%, 415296 KB, 3336 KB/s, 124 seconds passed
-... 59%, 415328 KB, 3336 KB/s, 124 seconds passed
-... 59%, 415360 KB, 3336 KB/s, 124 seconds passed
-... 59%, 415392 KB, 3336 KB/s, 124 seconds passed
-... 59%, 415424 KB, 3336 KB/s, 124 seconds passed
+    ... 57%, 400992 KB, 3670 KB/s, 109 seconds passed
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+... 57%, 401120 KB, 3670 KB/s, 109 seconds passed
+... 57%, 401152 KB, 3670 KB/s, 109 seconds passed
+... 57%, 401184 KB, 3670 KB/s, 109 seconds passed
 
 .. parsed-literal::
 
-    ... 59%, 415456 KB, 3336 KB/s, 124 seconds passed
-... 59%, 415488 KB, 3336 KB/s, 124 seconds passed
-... 59%, 415520 KB, 3336 KB/s, 124 seconds passed
-... 59%, 415552 KB, 3336 KB/s, 124 seconds passed
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+... 57%, 401312 KB, 3670 KB/s, 109 seconds passed
+... 57%, 401344 KB, 3670 KB/s, 109 seconds passed
 
 .. parsed-literal::
 
-    ... 59%, 415584 KB, 3336 KB/s, 124 seconds passed
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-... 59%, 415712 KB, 3336 KB/s, 124 seconds passed
-... 59%, 415744 KB, 3336 KB/s, 124 seconds passed
-... 59%, 415776 KB, 3336 KB/s, 124 seconds passed
-... 59%, 415808 KB, 3336 KB/s, 124 seconds passed
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+... 57%, 401536 KB, 3670 KB/s, 109 seconds passed
+... 57%, 401568 KB, 3670 KB/s, 109 seconds passed
 
 .. parsed-literal::
 
-    ... 59%, 415840 KB, 3336 KB/s, 124 seconds passed
-... 59%, 415872 KB, 3336 KB/s, 124 seconds passed
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-... 59%, 415936 KB, 3336 KB/s, 124 seconds passed
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+... 57%, 401728 KB, 3670 KB/s, 109 seconds passed
 
 .. parsed-literal::
 
-    ... 59%, 415968 KB, 3336 KB/s, 124 seconds passed
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-... 59%, 416128 KB, 3336 KB/s, 124 seconds passed
-... 59%, 416160 KB, 3336 KB/s, 124 seconds passed
+    ... 57%, 401760 KB, 3670 KB/s, 109 seconds passed
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+... 57%, 401952 KB, 3670 KB/s, 109 seconds passed
 
 .. parsed-literal::
 
-    ... 59%, 416192 KB, 3336 KB/s, 124 seconds passed
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-... 59%, 416256 KB, 3336 KB/s, 124 seconds passed
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+    ... 57%, 401984 KB, 3670 KB/s, 109 seconds passed
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+... 57%, 402112 KB, 3670 KB/s, 109 seconds passed
 
 .. parsed-literal::
 
-    ... 59%, 416352 KB, 3336 KB/s, 124 seconds passed
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+    ... 57%, 402144 KB, 3670 KB/s, 109 seconds passed
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+... 57%, 402304 KB, 3670 KB/s, 109 seconds passed
 
 .. parsed-literal::
 
-    ... 59%, 416576 KB, 3337 KB/s, 124 seconds passed
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-... 59%, 416672 KB, 3337 KB/s, 124 seconds passed
-... 59%, 416704 KB, 3337 KB/s, 124 seconds passed
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+... 57%, 402464 KB, 3671 KB/s, 109 seconds passed
 
 .. parsed-literal::
 
-    ... 59%, 416736 KB, 3337 KB/s, 124 seconds passed
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 .. parsed-literal::
 
-    ... 59%, 416960 KB, 3337 KB/s, 124 seconds passed
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+... 57%, 402848 KB, 3671 KB/s, 109 seconds passed
 
 .. parsed-literal::
 
-    ... 59%, 417120 KB, 3337 KB/s, 124 seconds passed
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+    ... 57%, 402880 KB, 3670 KB/s, 109 seconds passed
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+... 57%, 403008 KB, 3670 KB/s, 109 seconds passed
+... 57%, 403040 KB, 3670 KB/s, 109 seconds passed
+... 57%, 403072 KB, 3670 KB/s, 109 seconds passed
 
 .. parsed-literal::
 
-    ... 60%, 417312 KB, 3337 KB/s, 125 seconds passed
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-... 60%, 417472 KB, 3337 KB/s, 125 seconds passed
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+... 57%, 403200 KB, 3671 KB/s, 109 seconds passed
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 .. parsed-literal::
 
-    ... 60%, 417504 KB, 3337 KB/s, 125 seconds passed
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-... 60%, 417664 KB, 3337 KB/s, 125 seconds passed
+    ... 57%, 403264 KB, 3670 KB/s, 109 seconds passed
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+... 58%, 403456 KB, 3671 KB/s, 109 seconds passed
 
 .. parsed-literal::
 
-    ... 60%, 417696 KB, 3338 KB/s, 125 seconds passed
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-... 60%, 417792 KB, 3337 KB/s, 125 seconds passed
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-... 60%, 417856 KB, 3338 KB/s, 125 seconds passed
+    ... 58%, 403488 KB, 3671 KB/s, 109 seconds passed
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+... 58%, 403584 KB, 3671 KB/s, 109 seconds passed
+... 58%, 403616 KB, 3671 KB/s, 109 seconds passed
 
 .. parsed-literal::
 
-    ... 60%, 417888 KB, 3337 KB/s, 125 seconds passed
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-... 60%, 418016 KB, 3338 KB/s, 125 seconds passed
-... 60%, 418048 KB, 3338 KB/s, 125 seconds passed
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+... 58%, 403776 KB, 3670 KB/s, 109 seconds passed
+... 58%, 403808 KB, 3670 KB/s, 110 seconds passed
+... 58%, 403840 KB, 3671 KB/s, 110 seconds passed
 
 .. parsed-literal::
 
-    ... 60%, 418080 KB, 3338 KB/s, 125 seconds passed
-... 60%, 418112 KB, 3338 KB/s, 125 seconds passed
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-... 60%, 418176 KB, 3338 KB/s, 125 seconds passed
-... 60%, 418208 KB, 3338 KB/s, 125 seconds passed
-... 60%, 418240 KB, 3338 KB/s, 125 seconds passed
+    ... 58%, 403872 KB, 3671 KB/s, 110 seconds passed
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+... 58%, 403968 KB, 3671 KB/s, 110 seconds passed
+... 58%, 404000 KB, 3670 KB/s, 110 seconds passed
 
 .. parsed-literal::
 
-    ... 60%, 418272 KB, 3338 KB/s, 125 seconds passed
-... 60%, 418304 KB, 3338 KB/s, 125 seconds passed
-... 60%, 418336 KB, 3338 KB/s, 125 seconds passed
-... 60%, 418368 KB, 3338 KB/s, 125 seconds passed
-... 60%, 418400 KB, 3338 KB/s, 125 seconds passed
+    ... 58%, 404032 KB, 3670 KB/s, 110 seconds passed
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+... 58%, 404128 KB, 3670 KB/s, 110 seconds passed
+... 58%, 404160 KB, 3670 KB/s, 110 seconds passed
+... 58%, 404192 KB, 3670 KB/s, 110 seconds passed
 
 .. parsed-literal::
 
-    ... 60%, 418432 KB, 3338 KB/s, 125 seconds passed
-... 60%, 418464 KB, 3338 KB/s, 125 seconds passed
-... 60%, 418496 KB, 3338 KB/s, 125 seconds passed
-... 60%, 418528 KB, 3338 KB/s, 125 seconds passed
-... 60%, 418560 KB, 3338 KB/s, 125 seconds passed
-... 60%, 418592 KB, 3338 KB/s, 125 seconds passed
-... 60%, 418624 KB, 3338 KB/s, 125 seconds passed
+    ... 58%, 404224 KB, 3671 KB/s, 110 seconds passed
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+... 58%, 404320 KB, 3670 KB/s, 110 seconds passed
+... 58%, 404352 KB, 3671 KB/s, 110 seconds passed
+... 58%, 404384 KB, 3671 KB/s, 110 seconds passed
 
 .. parsed-literal::
 
-    ... 60%, 418656 KB, 3338 KB/s, 125 seconds passed
-... 60%, 418688 KB, 3338 KB/s, 125 seconds passed
-... 60%, 418720 KB, 3338 KB/s, 125 seconds passed
-... 60%, 418752 KB, 3338 KB/s, 125 seconds passed
-... 60%, 418784 KB, 3338 KB/s, 125 seconds passed
+    ... 58%, 404416 KB, 3670 KB/s, 110 seconds passed
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+... 58%, 404480 KB, 3671 KB/s, 110 seconds passed
+... 58%, 404512 KB, 3671 KB/s, 110 seconds passed
+... 58%, 404544 KB, 3670 KB/s, 110 seconds passed
+... 58%, 404576 KB, 3670 KB/s, 110 seconds passed
 
 .. parsed-literal::
 
-    ... 60%, 418816 KB, 3338 KB/s, 125 seconds passed
-... 60%, 418848 KB, 3338 KB/s, 125 seconds passed
-... 60%, 418880 KB, 3339 KB/s, 125 seconds passed
-... 60%, 418912 KB, 3338 KB/s, 125 seconds passed
-... 60%, 418944 KB, 3338 KB/s, 125 seconds passed
-... 60%, 418976 KB, 3339 KB/s, 125 seconds passed
+    ... 58%, 404608 KB, 3671 KB/s, 110 seconds passed
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+... 58%, 404672 KB, 3670 KB/s, 110 seconds passed
+... 58%, 404704 KB, 3670 KB/s, 110 seconds passed
+... 58%, 404736 KB, 3671 KB/s, 110 seconds passed
 
 .. parsed-literal::
 
-    ... 60%, 419008 KB, 3338 KB/s, 125 seconds passed
-... 60%, 419040 KB, 3338 KB/s, 125 seconds passed
-... 60%, 419072 KB, 3338 KB/s, 125 seconds passed
-... 60%, 419104 KB, 3339 KB/s, 125 seconds passed
-... 60%, 419136 KB, 3338 KB/s, 125 seconds passed
-... 60%, 419168 KB, 3338 KB/s, 125 seconds passed
+    ... 58%, 404768 KB, 3670 KB/s, 110 seconds passed
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+... 58%, 404864 KB, 3671 KB/s, 110 seconds passed
+... 58%, 404896 KB, 3670 KB/s, 110 seconds passed
+... 58%, 404928 KB, 3670 KB/s, 110 seconds passed
+... 58%, 404960 KB, 3670 KB/s, 110 seconds passed
 
 .. parsed-literal::
 
-    ... 60%, 419200 KB, 3339 KB/s, 125 seconds passed
-... 60%, 419232 KB, 3339 KB/s, 125 seconds passed
-... 60%, 419264 KB, 3339 KB/s, 125 seconds passed
-... 60%, 419296 KB, 3339 KB/s, 125 seconds passed
-... 60%, 419328 KB, 3339 KB/s, 125 seconds passed
-... 60%, 419360 KB, 3339 KB/s, 125 seconds passed
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+... 58%, 405088 KB, 3670 KB/s, 110 seconds passed
+... 58%, 405120 KB, 3671 KB/s, 110 seconds passed
 
 .. parsed-literal::
 
-    ... 60%, 419392 KB, 3339 KB/s, 125 seconds passed
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-... 60%, 419456 KB, 3339 KB/s, 125 seconds passed
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-... 60%, 419520 KB, 3339 KB/s, 125 seconds passed
-... 60%, 419552 KB, 3339 KB/s, 125 seconds passed
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+... 58%, 405248 KB, 3671 KB/s, 110 seconds passed
+... 58%, 405280 KB, 3670 KB/s, 110 seconds passed
+... 58%, 405312 KB, 3670 KB/s, 110 seconds passed
 
 .. parsed-literal::
 
-    ... 60%, 419584 KB, 3339 KB/s, 125 seconds passed
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-... 60%, 419648 KB, 3339 KB/s, 125 seconds passed
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-... 60%, 419712 KB, 3339 KB/s, 125 seconds passed
-... 60%, 419744 KB, 3339 KB/s, 125 seconds passed
+    ... 58%, 405344 KB, 3670 KB/s, 110 seconds passed
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+... 58%, 405472 KB, 3670 KB/s, 110 seconds passed
+... 58%, 405504 KB, 3671 KB/s, 110 seconds passed
 
 .. parsed-literal::
 
-    ... 60%, 419776 KB, 3339 KB/s, 125 seconds passed
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-... 60%, 419840 KB, 3339 KB/s, 125 seconds passed
-... 60%, 419872 KB, 3339 KB/s, 125 seconds passed
-... 60%, 419904 KB, 3339 KB/s, 125 seconds passed
-... 60%, 419936 KB, 3339 KB/s, 125 seconds passed
+    ... 58%, 405536 KB, 3670 KB/s, 110 seconds passed
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+... 58%, 405632 KB, 3671 KB/s, 110 seconds passed
+... 58%, 405664 KB, 3670 KB/s, 110 seconds passed
+... 58%, 405696 KB, 3670 KB/s, 110 seconds passed
 
 .. parsed-literal::
 
-    ... 60%, 419968 KB, 3339 KB/s, 125 seconds passed
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-... 60%, 420128 KB, 3339 KB/s, 125 seconds passed
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+... 58%, 405856 KB, 3671 KB/s, 110 seconds passed
+... 58%, 405888 KB, 3671 KB/s, 110 seconds passed
 
 .. parsed-literal::
 
-    ... 60%, 420160 KB, 3339 KB/s, 125 seconds passed
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-... 60%, 420320 KB, 3339 KB/s, 125 seconds passed
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+... 58%, 406080 KB, 3671 KB/s, 110 seconds passed
+... 58%, 406112 KB, 3671 KB/s, 110 seconds passed
 
 .. parsed-literal::
 
-    ... 60%, 420352 KB, 3339 KB/s, 125 seconds passed
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-... 60%, 420512 KB, 3340 KB/s, 125 seconds passed
+    ... 58%, 406144 KB, 3671 KB/s, 110 seconds passed
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+... 58%, 406272 KB, 3671 KB/s, 110 seconds passed
 
 .. parsed-literal::
 
-    ... 60%, 420544 KB, 3340 KB/s, 125 seconds passed
-... 60%, 420576 KB, 3340 KB/s, 125 seconds passed
-... 60%, 420608 KB, 3340 KB/s, 125 seconds passed
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-... 60%, 420672 KB, 3340 KB/s, 125 seconds passed
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+... 58%, 406400 KB, 3671 KB/s, 110 seconds passed
+... 58%, 406432 KB, 3670 KB/s, 110 seconds passed
+... 58%, 406464 KB, 3670 KB/s, 110 seconds passed
 
 .. parsed-literal::
 
-    ... 60%, 420704 KB, 3340 KB/s, 125 seconds passed
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-... 60%, 420800 KB, 3340 KB/s, 125 seconds passed
-... 60%, 420832 KB, 3340 KB/s, 125 seconds passed
-... 60%, 420864 KB, 3340 KB/s, 125 seconds passed
-... 60%, 420896 KB, 3340 KB/s, 125 seconds passed
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+... 58%, 406592 KB, 3670 KB/s, 110 seconds passed
+... 58%, 406624 KB, 3671 KB/s, 110 seconds passed
+... 58%, 406656 KB, 3671 KB/s, 110 seconds passed
 
 .. parsed-literal::
 
-    ... 60%, 420928 KB, 3340 KB/s, 126 seconds passed
-... 60%, 420960 KB, 3340 KB/s, 126 seconds passed
-... 60%, 420992 KB, 3340 KB/s, 126 seconds passed
-... 60%, 421024 KB, 3340 KB/s, 126 seconds passed
-... 60%, 421056 KB, 3340 KB/s, 126 seconds passed
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+... 58%, 406752 KB, 3671 KB/s, 110 seconds passed
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+... 58%, 406816 KB, 3670 KB/s, 110 seconds passed
 
 .. parsed-literal::
 
-    ... 60%, 421088 KB, 3340 KB/s, 126 seconds passed
-... 60%, 421120 KB, 3340 KB/s, 126 seconds passed
-... 60%, 421152 KB, 3340 KB/s, 126 seconds passed
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-... 60%, 421216 KB, 3340 KB/s, 126 seconds passed
-... 60%, 421248 KB, 3340 KB/s, 126 seconds passed
+    ... 58%, 406848 KB, 3670 KB/s, 110 seconds passed
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+... 58%, 406976 KB, 3670 KB/s, 110 seconds passed
+... 58%, 407008 KB, 3671 KB/s, 110 seconds passed
+... 58%, 407040 KB, 3671 KB/s, 110 seconds passed
 
 .. parsed-literal::
 
-    ... 60%, 421280 KB, 3340 KB/s, 126 seconds passed
-... 60%, 421312 KB, 3340 KB/s, 126 seconds passed
-... 60%, 421344 KB, 3340 KB/s, 126 seconds passed
-... 60%, 421376 KB, 3340 KB/s, 126 seconds passed
-... 60%, 421408 KB, 3340 KB/s, 126 seconds passed
-... 60%, 421440 KB, 3340 KB/s, 126 seconds passed
+    ... 58%, 407072 KB, 3671 KB/s, 110 seconds passed
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+... 58%, 407200 KB, 3671 KB/s, 110 seconds passed
+... 58%, 407232 KB, 3671 KB/s, 110 seconds passed
 
 .. parsed-literal::
 
-    ... 60%, 421472 KB, 3340 KB/s, 126 seconds passed
-... 60%, 421504 KB, 3340 KB/s, 126 seconds passed
-... 60%, 421536 KB, 3340 KB/s, 126 seconds passed
-... 60%, 421568 KB, 3340 KB/s, 126 seconds passed
-... 60%, 421600 KB, 3340 KB/s, 126 seconds passed
-... 60%, 421632 KB, 3340 KB/s, 126 seconds passed
+    ... 58%, 407264 KB, 3671 KB/s, 110 seconds passed
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+... 58%, 407392 KB, 3671 KB/s, 110 seconds passed
+... 58%, 407424 KB, 3671 KB/s, 110 seconds passed
 
 .. parsed-literal::
 
-    ... 60%, 421664 KB, 3340 KB/s, 126 seconds passed
-... 60%, 421696 KB, 3340 KB/s, 126 seconds passed
-... 60%, 421728 KB, 3340 KB/s, 126 seconds passed
-... 60%, 421760 KB, 3340 KB/s, 126 seconds passed
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-... 60%, 421824 KB, 3340 KB/s, 126 seconds passed
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+... 58%, 407584 KB, 3670 KB/s, 111 seconds passed
 
 .. parsed-literal::
 
-    ... 60%, 421856 KB, 3341 KB/s, 126 seconds passed
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 .. parsed-literal::
 
-    ... 60%, 422048 KB, 3341 KB/s, 126 seconds passed
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 .. parsed-literal::
 
-    ... 60%, 422240 KB, 3341 KB/s, 126 seconds passed
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 .. parsed-literal::
 
-    ... 60%, 422432 KB, 3341 KB/s, 126 seconds passed
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 .. parsed-literal::
 
-    ... 60%, 422592 KB, 3341 KB/s, 126 seconds passed
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 .. parsed-literal::
 
-    ... 60%, 422816 KB, 3341 KB/s, 126 seconds passed
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 .. parsed-literal::
 
-    ... 60%, 422976 KB, 3341 KB/s, 126 seconds passed
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 .. parsed-literal::
 
-    ... 60%, 423168 KB, 3341 KB/s, 126 seconds passed
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 .. parsed-literal::
 
-    ... 60%, 423360 KB, 3342 KB/s, 126 seconds passed
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 .. parsed-literal::
 
-    ... 60%, 423552 KB, 3342 KB/s, 126 seconds passed
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 .. parsed-literal::
 
-    ... 60%, 423744 KB, 3342 KB/s, 126 seconds passed
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 .. parsed-literal::
 
-    ... 60%, 423936 KB, 3342 KB/s, 126 seconds passed
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 .. parsed-literal::
 
-    ... 60%, 424096 KB, 3342 KB/s, 126 seconds passed
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 .. parsed-literal::
 
-    ... 61%, 424288 KB, 3342 KB/s, 126 seconds passed
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 .. parsed-literal::
 
-    ... 61%, 424480 KB, 3342 KB/s, 126 seconds passed
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 .. parsed-literal::
 
-    ... 61%, 424672 KB, 3343 KB/s, 127 seconds passed
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 .. parsed-literal::
 
-    ... 61%, 424864 KB, 3343 KB/s, 127 seconds passed
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 .. parsed-literal::
 
-    ... 61%, 425056 KB, 3343 KB/s, 127 seconds passed
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 .. parsed-literal::
 
-    ... 61%, 425248 KB, 3343 KB/s, 127 seconds passed
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+... 59%, 411200 KB, 3671 KB/s, 112 seconds passed
 
 .. parsed-literal::
 
-    ... 61%, 425440 KB, 3343 KB/s, 127 seconds passed
-... 61%, 425472 KB, 3343 KB/s, 127 seconds passed
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-... 61%, 425600 KB, 3343 KB/s, 127 seconds passed
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+... 59%, 411328 KB, 3671 KB/s, 112 seconds passed
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 .. parsed-literal::
 
-    ... 61%, 425632 KB, 3343 KB/s, 127 seconds passed
-... 61%, 425664 KB, 3343 KB/s, 127 seconds passed
-... 61%, 425696 KB, 3343 KB/s, 127 seconds passed
-... 61%, 425728 KB, 3343 KB/s, 127 seconds passed
-... 61%, 425760 KB, 3343 KB/s, 127 seconds passed
-... 61%, 425792 KB, 3343 KB/s, 127 seconds passed
+    ... 59%, 411392 KB, 3671 KB/s, 112 seconds passed
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+... 59%, 411520 KB, 3671 KB/s, 112 seconds passed
+... 59%, 411552 KB, 3671 KB/s, 112 seconds passed
+... 59%, 411584 KB, 3671 KB/s, 112 seconds passed
 
 .. parsed-literal::
 
-    ... 61%, 425824 KB, 3343 KB/s, 127 seconds passed
-... 61%, 425856 KB, 3343 KB/s, 127 seconds passed
-... 61%, 425888 KB, 3343 KB/s, 127 seconds passed
-... 61%, 425920 KB, 3343 KB/s, 127 seconds passed
-... 61%, 425952 KB, 3343 KB/s, 127 seconds passed
-... 61%, 425984 KB, 3343 KB/s, 127 seconds passed
+    ... 59%, 411616 KB, 3671 KB/s, 112 seconds passed
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+... 59%, 411680 KB, 3671 KB/s, 112 seconds passed
+... 59%, 411712 KB, 3671 KB/s, 112 seconds passed
+... 59%, 411744 KB, 3671 KB/s, 112 seconds passed
 
 .. parsed-literal::
 
-    ... 61%, 426016 KB, 3344 KB/s, 127 seconds passed
-... 61%, 426048 KB, 3344 KB/s, 127 seconds passed
-... 61%, 426080 KB, 3344 KB/s, 127 seconds passed
-... 61%, 426112 KB, 3344 KB/s, 127 seconds passed
-... 61%, 426144 KB, 3344 KB/s, 127 seconds passed
+    ... 59%, 411776 KB, 3671 KB/s, 112 seconds passed
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+... 59%, 411904 KB, 3671 KB/s, 112 seconds passed
+... 59%, 411936 KB, 3671 KB/s, 112 seconds passed
+... 59%, 411968 KB, 3671 KB/s, 112 seconds passed
 
 .. parsed-literal::
 
-    ... 61%, 426176 KB, 3344 KB/s, 127 seconds passed
-... 61%, 426208 KB, 3344 KB/s, 127 seconds passed
-... 61%, 426240 KB, 3344 KB/s, 127 seconds passed
-... 61%, 426272 KB, 3344 KB/s, 127 seconds passed
-... 61%, 426304 KB, 3344 KB/s, 127 seconds passed
-... 61%, 426336 KB, 3344 KB/s, 127 seconds passed
+    ... 59%, 412000 KB, 3671 KB/s, 112 seconds passed
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+... 59%, 412064 KB, 3671 KB/s, 112 seconds passed
+... 59%, 412096 KB, 3671 KB/s, 112 seconds passed
+... 59%, 412128 KB, 3671 KB/s, 112 seconds passed
 
 .. parsed-literal::
 
-    ... 61%, 426368 KB, 3344 KB/s, 127 seconds passed
-... 61%, 426400 KB, 3344 KB/s, 127 seconds passed
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-... 61%, 426464 KB, 3344 KB/s, 127 seconds passed
-... 61%, 426496 KB, 3344 KB/s, 127 seconds passed
-... 61%, 426528 KB, 3344 KB/s, 127 seconds passed
+    ... 59%, 412160 KB, 3671 KB/s, 112 seconds passed
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+... 59%, 412288 KB, 3671 KB/s, 112 seconds passed
+... 59%, 412320 KB, 3671 KB/s, 112 seconds passed
+... 59%, 412352 KB, 3671 KB/s, 112 seconds passed
 
 .. parsed-literal::
 
-    ... 61%, 426560 KB, 3344 KB/s, 127 seconds passed
-... 61%, 426592 KB, 3344 KB/s, 127 seconds passed
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-... 61%, 426656 KB, 3344 KB/s, 127 seconds passed
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-... 61%, 426720 KB, 3344 KB/s, 127 seconds passed
+    ... 59%, 412384 KB, 3671 KB/s, 112 seconds passed
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+... 59%, 412448 KB, 3671 KB/s, 112 seconds passed
+... 59%, 412480 KB, 3671 KB/s, 112 seconds passed
+... 59%, 412512 KB, 3671 KB/s, 112 seconds passed
 
 .. parsed-literal::
 
-    ... 61%, 426752 KB, 3344 KB/s, 127 seconds passed
-... 61%, 426784 KB, 3344 KB/s, 127 seconds passed
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-... 61%, 426848 KB, 3344 KB/s, 127 seconds passed
-... 61%, 426880 KB, 3344 KB/s, 127 seconds passed
-... 61%, 426912 KB, 3344 KB/s, 127 seconds passed
+    ... 59%, 412544 KB, 3671 KB/s, 112 seconds passed
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+... 59%, 412640 KB, 3671 KB/s, 112 seconds passed
+... 59%, 412672 KB, 3671 KB/s, 112 seconds passed
+... 59%, 412704 KB, 3671 KB/s, 112 seconds passed
 
 .. parsed-literal::
 
-    ... 61%, 426944 KB, 3344 KB/s, 127 seconds passed
-... 61%, 426976 KB, 3344 KB/s, 127 seconds passed
-... 61%, 427008 KB, 3344 KB/s, 127 seconds passed
-... 61%, 427040 KB, 3344 KB/s, 127 seconds passed
-... 61%, 427072 KB, 3344 KB/s, 127 seconds passed
-... 61%, 427104 KB, 3344 KB/s, 127 seconds passed
+    ... 59%, 412736 KB, 3671 KB/s, 112 seconds passed
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+... 59%, 412800 KB, 3671 KB/s, 112 seconds passed
+... 59%, 412832 KB, 3671 KB/s, 112 seconds passed
+... 59%, 412864 KB, 3671 KB/s, 112 seconds passed
 
 .. parsed-literal::
 
-    ... 61%, 427136 KB, 3344 KB/s, 127 seconds passed
-... 61%, 427168 KB, 3344 KB/s, 127 seconds passed
-... 61%, 427200 KB, 3344 KB/s, 127 seconds passed
-... 61%, 427232 KB, 3344 KB/s, 127 seconds passed
-... 61%, 427264 KB, 3344 KB/s, 127 seconds passed
-... 61%, 427296 KB, 3344 KB/s, 127 seconds passed
+    ... 59%, 412896 KB, 3671 KB/s, 112 seconds passed
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+... 59%, 413024 KB, 3671 KB/s, 112 seconds passed
+... 59%, 413056 KB, 3671 KB/s, 112 seconds passed
+... 59%, 413088 KB, 3671 KB/s, 112 seconds passed
 
 .. parsed-literal::
 
-    ... 61%, 427328 KB, 3344 KB/s, 127 seconds passed
-... 61%, 427360 KB, 3344 KB/s, 127 seconds passed
-... 61%, 427392 KB, 3345 KB/s, 127 seconds passed
-... 61%, 427424 KB, 3345 KB/s, 127 seconds passed
-... 61%, 427456 KB, 3345 KB/s, 127 seconds passed
-... 61%, 427488 KB, 3345 KB/s, 127 seconds passed
+    ... 59%, 413120 KB, 3671 KB/s, 112 seconds passed
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+... 59%, 413184 KB, 3671 KB/s, 112 seconds passed
+... 59%, 413216 KB, 3671 KB/s, 112 seconds passed
+... 59%, 413248 KB, 3671 KB/s, 112 seconds passed
 
 .. parsed-literal::
 
-    ... 61%, 427520 KB, 3345 KB/s, 127 seconds passed
-... 61%, 427552 KB, 3345 KB/s, 127 seconds passed
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-... 61%, 427616 KB, 3345 KB/s, 127 seconds passed
-... 61%, 427648 KB, 3345 KB/s, 127 seconds passed
-... 61%, 427680 KB, 3345 KB/s, 127 seconds passed
+    ... 59%, 413280 KB, 3671 KB/s, 112 seconds passed
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+... 59%, 413408 KB, 3671 KB/s, 112 seconds passed
+... 59%, 413440 KB, 3671 KB/s, 112 seconds passed
+... 59%, 413472 KB, 3671 KB/s, 112 seconds passed
 
 .. parsed-literal::
 
-    ... 61%, 427712 KB, 3345 KB/s, 127 seconds passed
-... 61%, 427744 KB, 3345 KB/s, 127 seconds passed
-... 61%, 427776 KB, 3345 KB/s, 127 seconds passed
-... 61%, 427808 KB, 3345 KB/s, 127 seconds passed
-... 61%, 427840 KB, 3345 KB/s, 127 seconds passed
-... 61%, 427872 KB, 3345 KB/s, 127 seconds passed
+    ... 59%, 413504 KB, 3671 KB/s, 112 seconds passed
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+... 59%, 413568 KB, 3671 KB/s, 112 seconds passed
+... 59%, 413600 KB, 3671 KB/s, 112 seconds passed
+... 59%, 413632 KB, 3671 KB/s, 112 seconds passed
 
 .. parsed-literal::
 
-    ... 61%, 427904 KB, 3345 KB/s, 127 seconds passed
-... 61%, 427936 KB, 3345 KB/s, 127 seconds passed
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-... 61%, 428000 KB, 3345 KB/s, 127 seconds passed
-... 61%, 428032 KB, 3345 KB/s, 127 seconds passed
-... 61%, 428064 KB, 3345 KB/s, 127 seconds passed
+    ... 59%, 413664 KB, 3671 KB/s, 112 seconds passed
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+... 59%, 413792 KB, 3671 KB/s, 112 seconds passed
+... 59%, 413824 KB, 3671 KB/s, 112 seconds passed
+... 59%, 413856 KB, 3671 KB/s, 112 seconds passed
 
 .. parsed-literal::
 
-    ... 61%, 428096 KB, 3345 KB/s, 127 seconds passed
-... 61%, 428128 KB, 3345 KB/s, 127 seconds passed
-... 61%, 428160 KB, 3345 KB/s, 127 seconds passed
-... 61%, 428192 KB, 3345 KB/s, 127 seconds passed
-... 61%, 428224 KB, 3345 KB/s, 127 seconds passed
+    ... 59%, 413888 KB, 3671 KB/s, 112 seconds passed
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+... 59%, 414016 KB, 3671 KB/s, 112 seconds passed
 
 .. parsed-literal::
 
-    ... 61%, 428256 KB, 3345 KB/s, 128 seconds passed
-... 61%, 428288 KB, 3345 KB/s, 128 seconds passed
-... 61%, 428320 KB, 3345 KB/s, 128 seconds passed
-... 61%, 428352 KB, 3345 KB/s, 128 seconds passed
-... 61%, 428384 KB, 3345 KB/s, 128 seconds passed
-... 61%, 428416 KB, 3345 KB/s, 128 seconds passed
-... 61%, 428448 KB, 3345 KB/s, 128 seconds passed
+    ... 59%, 414048 KB, 3671 KB/s, 112 seconds passed
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+... 59%, 414176 KB, 3671 KB/s, 112 seconds passed
+... 59%, 414208 KB, 3671 KB/s, 112 seconds passed
+... 59%, 414240 KB, 3671 KB/s, 112 seconds passed
 
 .. parsed-literal::
 
-    ... 61%, 428480 KB, 3345 KB/s, 128 seconds passed
-... 61%, 428512 KB, 3345 KB/s, 128 seconds passed
-... 61%, 428544 KB, 3345 KB/s, 128 seconds passed
-... 61%, 428576 KB, 3345 KB/s, 128 seconds passed
-... 61%, 428608 KB, 3345 KB/s, 128 seconds passed
+    ... 59%, 414272 KB, 3671 KB/s, 112 seconds passed
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+... 59%, 414336 KB, 3671 KB/s, 112 seconds passed
+... 59%, 414368 KB, 3671 KB/s, 112 seconds passed
+... 59%, 414400 KB, 3671 KB/s, 112 seconds passed
 
 .. parsed-literal::
 
-    ... 61%, 428640 KB, 3345 KB/s, 128 seconds passed
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-... 61%, 428832 KB, 3346 KB/s, 128 seconds passed
+    ... 59%, 414432 KB, 3671 KB/s, 112 seconds passed
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+... 59%, 414528 KB, 3671 KB/s, 112 seconds passed
+... 59%, 414560 KB, 3671 KB/s, 112 seconds passed
+... 59%, 414592 KB, 3671 KB/s, 112 seconds passed
 
 .. parsed-literal::
 
-    ... 61%, 428864 KB, 3346 KB/s, 128 seconds passed
-... 61%, 428896 KB, 3346 KB/s, 128 seconds passed
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-... 61%, 428992 KB, 3346 KB/s, 128 seconds passed
+    ... 59%, 414624 KB, 3671 KB/s, 112 seconds passed
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 .. parsed-literal::
 
-    ... 61%, 429024 KB, 3346 KB/s, 128 seconds passed
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+    ... 59%, 414816 KB, 3671 KB/s, 112 seconds passed
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 .. parsed-literal::
 
-    ... 61%, 429216 KB, 3346 KB/s, 128 seconds passed
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+    ... 59%, 415008 KB, 3671 KB/s, 113 seconds passed
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 .. parsed-literal::
 
-    ... 61%, 429408 KB, 3346 KB/s, 128 seconds passed
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+    ... 59%, 415200 KB, 3671 KB/s, 113 seconds passed
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+... 59%, 415296 KB, 3671 KB/s, 113 seconds passed
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 .. parsed-literal::
 
-    ... 61%, 429600 KB, 3346 KB/s, 128 seconds passed
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-... 61%, 429696 KB, 3346 KB/s, 128 seconds passed
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 .. parsed-literal::
 
-    ... 61%, 429792 KB, 3346 KB/s, 128 seconds passed
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-... 61%, 429888 KB, 3346 KB/s, 128 seconds passed
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+    ... 59%, 415584 KB, 3671 KB/s, 113 seconds passed
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 .. parsed-literal::
 
-    ... 61%, 429984 KB, 3346 KB/s, 128 seconds passed
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+    ... 59%, 415776 KB, 3671 KB/s, 113 seconds passed
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+... 59%, 415936 KB, 3671 KB/s, 113 seconds passed
 
 .. parsed-literal::
 
-    ... 61%, 430176 KB, 3347 KB/s, 128 seconds passed
-... 61%, 430208 KB, 3347 KB/s, 128 seconds passed
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+... 59%, 416096 KB, 3671 KB/s, 113 seconds passed
 
 .. parsed-literal::
 
-    ... 61%, 430368 KB, 3347 KB/s, 128 seconds passed
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-... 61%, 430528 KB, 3347 KB/s, 128 seconds passed
+    ... 59%, 416128 KB, 3671 KB/s, 113 seconds passed
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 .. parsed-literal::
 
-    ... 61%, 430560 KB, 3347 KB/s, 128 seconds passed
-... 61%, 430592 KB, 3347 KB/s, 128 seconds passed
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+    ... 59%, 416320 KB, 3671 KB/s, 113 seconds passed
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+... 59%, 416448 KB, 3671 KB/s, 113 seconds passed
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 .. parsed-literal::
 
-    ... 61%, 430720 KB, 3347 KB/s, 128 seconds passed
-... 61%, 430752 KB, 3347 KB/s, 128 seconds passed
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-... 61%, 430816 KB, 3347 KB/s, 128 seconds passed
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-... 61%, 430880 KB, 3347 KB/s, 128 seconds passed
+    ... 59%, 416512 KB, 3671 KB/s, 113 seconds passed
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+... 59%, 416608 KB, 3671 KB/s, 113 seconds passed
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+... 59%, 416672 KB, 3671 KB/s, 113 seconds passed
 
 .. parsed-literal::
 
-    ... 61%, 430912 KB, 3347 KB/s, 128 seconds passed
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-... 61%, 431008 KB, 3347 KB/s, 128 seconds passed
-... 61%, 431040 KB, 3347 KB/s, 128 seconds passed
-... 61%, 431072 KB, 3347 KB/s, 128 seconds passed
+    ... 59%, 416704 KB, 3671 KB/s, 113 seconds passed
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+... 59%, 416800 KB, 3671 KB/s, 113 seconds passed
+... 59%, 416832 KB, 3671 KB/s, 113 seconds passed
+... 59%, 416864 KB, 3671 KB/s, 113 seconds passed
 
 .. parsed-literal::
 
-    ... 61%, 431104 KB, 3347 KB/s, 128 seconds passed
-... 61%, 431136 KB, 3347 KB/s, 128 seconds passed
-... 61%, 431168 KB, 3347 KB/s, 128 seconds passed
-... 61%, 431200 KB, 3347 KB/s, 128 seconds passed
-... 62%, 431232 KB, 3347 KB/s, 128 seconds passed
-... 62%, 431264 KB, 3347 KB/s, 128 seconds passed
+    ... 59%, 416896 KB, 3671 KB/s, 113 seconds passed
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+... 59%, 416992 KB, 3671 KB/s, 113 seconds passed
+... 59%, 417024 KB, 3671 KB/s, 113 seconds passed
+... 59%, 417056 KB, 3671 KB/s, 113 seconds passed
 
 .. parsed-literal::
 
-    ... 62%, 431296 KB, 3347 KB/s, 128 seconds passed
-... 62%, 431328 KB, 3347 KB/s, 128 seconds passed
-... 62%, 431360 KB, 3347 KB/s, 128 seconds passed
-... 62%, 431392 KB, 3347 KB/s, 128 seconds passed
-... 62%, 431424 KB, 3348 KB/s, 128 seconds passed
-... 62%, 431456 KB, 3348 KB/s, 128 seconds passed
+    ... 59%, 417088 KB, 3671 KB/s, 113 seconds passed
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+... 59%, 417184 KB, 3671 KB/s, 113 seconds passed
+... 59%, 417216 KB, 3671 KB/s, 113 seconds passed
+... 59%, 417248 KB, 3671 KB/s, 113 seconds passed
 
 .. parsed-literal::
 
-    ... 62%, 431488 KB, 3348 KB/s, 128 seconds passed
-... 62%, 431520 KB, 3348 KB/s, 128 seconds passed
-... 62%, 431552 KB, 3348 KB/s, 128 seconds passed
-... 62%, 431584 KB, 3348 KB/s, 128 seconds passed
-... 62%, 431616 KB, 3348 KB/s, 128 seconds passed
-... 62%, 431648 KB, 3348 KB/s, 128 seconds passed
+    ... 59%, 417280 KB, 3671 KB/s, 113 seconds passed
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+... 60%, 417376 KB, 3671 KB/s, 113 seconds passed
+... 60%, 417408 KB, 3671 KB/s, 113 seconds passed
+... 60%, 417440 KB, 3671 KB/s, 113 seconds passed
 
 .. parsed-literal::
 
-    ... 62%, 431680 KB, 3348 KB/s, 128 seconds passed
-... 62%, 431712 KB, 3348 KB/s, 128 seconds passed
-... 62%, 431744 KB, 3348 KB/s, 128 seconds passed
-... 62%, 431776 KB, 3348 KB/s, 128 seconds passed
-... 62%, 431808 KB, 3348 KB/s, 128 seconds passed
-... 62%, 431840 KB, 3348 KB/s, 128 seconds passed
+    ... 60%, 417472 KB, 3671 KB/s, 113 seconds passed
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+... 60%, 417568 KB, 3671 KB/s, 113 seconds passed
+... 60%, 417600 KB, 3671 KB/s, 113 seconds passed
+... 60%, 417632 KB, 3671 KB/s, 113 seconds passed
 
 .. parsed-literal::
 
-    ... 62%, 431872 KB, 3348 KB/s, 128 seconds passed
-... 62%, 431904 KB, 3348 KB/s, 128 seconds passed
-... 62%, 431936 KB, 3348 KB/s, 128 seconds passed
-... 62%, 431968 KB, 3348 KB/s, 129 seconds passed
-... 62%, 432000 KB, 3348 KB/s, 129 seconds passed
-... 62%, 432032 KB, 3348 KB/s, 129 seconds passed
+    ... 60%, 417664 KB, 3671 KB/s, 113 seconds passed
+... 60%, 417696 KB, 3671 KB/s, 113 seconds passed
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+... 60%, 417760 KB, 3671 KB/s, 113 seconds passed
+... 60%, 417792 KB, 3671 KB/s, 113 seconds passed
+... 60%, 417824 KB, 3671 KB/s, 113 seconds passed
 
 .. parsed-literal::
 
-    ... 62%, 432064 KB, 3348 KB/s, 129 seconds passed
-... 62%, 432096 KB, 3348 KB/s, 129 seconds passed
-... 62%, 432128 KB, 3348 KB/s, 129 seconds passed
-... 62%, 432160 KB, 3348 KB/s, 129 seconds passed
-... 62%, 432192 KB, 3348 KB/s, 129 seconds passed
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+    ... 60%, 417856 KB, 3671 KB/s, 113 seconds passed
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+... 60%, 417984 KB, 3671 KB/s, 113 seconds passed
+... 60%, 418016 KB, 3671 KB/s, 113 seconds passed
 
 .. parsed-literal::
 
-    ... 62%, 432256 KB, 3348 KB/s, 129 seconds passed
-... 62%, 432288 KB, 3348 KB/s, 129 seconds passed
-... 62%, 432320 KB, 3348 KB/s, 129 seconds passed
-... 62%, 432352 KB, 3348 KB/s, 129 seconds passed
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-... 62%, 432416 KB, 3348 KB/s, 129 seconds passed
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+... 60%, 418144 KB, 3671 KB/s, 113 seconds passed
+... 60%, 418176 KB, 3671 KB/s, 113 seconds passed
+... 60%, 418208 KB, 3671 KB/s, 113 seconds passed
 
 .. parsed-literal::
 
-    ... 62%, 432448 KB, 3348 KB/s, 129 seconds passed
-... 62%, 432480 KB, 3348 KB/s, 129 seconds passed
-... 62%, 432512 KB, 3348 KB/s, 129 seconds passed
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-... 62%, 432576 KB, 3348 KB/s, 129 seconds passed
-... 62%, 432608 KB, 3348 KB/s, 129 seconds passed
+    ... 60%, 418240 KB, 3671 KB/s, 113 seconds passed
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+... 60%, 418304 KB, 3671 KB/s, 113 seconds passed
+... 60%, 418336 KB, 3671 KB/s, 113 seconds passed
+... 60%, 418368 KB, 3671 KB/s, 113 seconds passed
 
 .. parsed-literal::
 
-    ... 62%, 432640 KB, 3348 KB/s, 129 seconds passed
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-... 62%, 432800 KB, 3348 KB/s, 129 seconds passed
+    ... 60%, 418400 KB, 3671 KB/s, 113 seconds passed
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+... 60%, 418560 KB, 3671 KB/s, 113 seconds passed
+... 60%, 418592 KB, 3671 KB/s, 114 seconds passed
 
 .. parsed-literal::
 
-    ... 62%, 432832 KB, 3348 KB/s, 129 seconds passed
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-... 62%, 432896 KB, 3349 KB/s, 129 seconds passed
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 .. parsed-literal::
 
-    ... 62%, 432992 KB, 3349 KB/s, 129 seconds passed
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+... 60%, 418944 KB, 3671 KB/s, 114 seconds passed
+... 60%, 418976 KB, 3671 KB/s, 114 seconds passed
 
 .. parsed-literal::
 
-    ... 62%, 433216 KB, 3349 KB/s, 129 seconds passed
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+... 60%, 419104 KB, 3671 KB/s, 114 seconds passed
 
 .. parsed-literal::
 
-    ... 62%, 433376 KB, 3349 KB/s, 129 seconds passed
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+... 60%, 419360 KB, 3671 KB/s, 114 seconds passed
 
 .. parsed-literal::
 
-    ... 62%, 433568 KB, 3349 KB/s, 129 seconds passed
-... 62%, 433600 KB, 3349 KB/s, 129 seconds passed
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-... 62%, 433696 KB, 3349 KB/s, 129 seconds passed
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 .. parsed-literal::
 
-    ... 62%, 433760 KB, 3349 KB/s, 129 seconds passed
-... 62%, 433792 KB, 3349 KB/s, 129 seconds passed
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-... 62%, 433856 KB, 3349 KB/s, 129 seconds passed
-... 62%, 433888 KB, 3349 KB/s, 129 seconds passed
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 .. parsed-literal::
 
-    ... 62%, 433952 KB, 3349 KB/s, 129 seconds passed
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-... 62%, 434112 KB, 3349 KB/s, 129 seconds passed
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+... 60%, 419872 KB, 3671 KB/s, 114 seconds passed
 
 .. parsed-literal::
 
-    ... 62%, 434144 KB, 3349 KB/s, 129 seconds passed
-... 62%, 434176 KB, 3349 KB/s, 129 seconds passed
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-... 62%, 434240 KB, 3350 KB/s, 129 seconds passed
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-... 62%, 434304 KB, 3350 KB/s, 129 seconds passed
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+... 60%, 420064 KB, 3671 KB/s, 114 seconds passed
+... 60%, 420096 KB, 3671 KB/s, 114 seconds passed
 
 .. parsed-literal::
 
-    ... 62%, 434336 KB, 3350 KB/s, 129 seconds passed
-... 62%, 434368 KB, 3350 KB/s, 129 seconds passed
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-... 62%, 434496 KB, 3350 KB/s, 129 seconds passed
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 .. parsed-literal::
 
-    ... 62%, 434528 KB, 3350 KB/s, 129 seconds passed
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 .. parsed-literal::
 
-    ... 62%, 434720 KB, 3350 KB/s, 129 seconds passed
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 .. parsed-literal::
 
-    ... 62%, 434912 KB, 3350 KB/s, 129 seconds passed
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 .. parsed-literal::
 
-    ... 62%, 435104 KB, 3350 KB/s, 129 seconds passed
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 .. parsed-literal::
 
-    ... 62%, 435296 KB, 3350 KB/s, 129 seconds passed
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 .. parsed-literal::
 
-    ... 62%, 435488 KB, 3350 KB/s, 129 seconds passed
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 .. parsed-literal::
 
-    ... 62%, 435680 KB, 3351 KB/s, 130 seconds passed
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 .. parsed-literal::
 
-    ... 62%, 435872 KB, 3351 KB/s, 130 seconds passed
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 .. parsed-literal::
 
-    ... 62%, 436032 KB, 3351 KB/s, 130 seconds passed
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 .. parsed-literal::
 
-    ... 62%, 436224 KB, 3351 KB/s, 130 seconds passed
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 .. parsed-literal::
 
-    ... 62%, 436416 KB, 3351 KB/s, 130 seconds passed
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 .. parsed-literal::
 
-    ... 62%, 436608 KB, 3351 KB/s, 130 seconds passed
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 .. parsed-literal::
 
-    ... 62%, 436800 KB, 3351 KB/s, 130 seconds passed
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 .. parsed-literal::
 
-    ... 62%, 436992 KB, 3351 KB/s, 130 seconds passed
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 .. parsed-literal::
 
-    ... 62%, 437152 KB, 3351 KB/s, 130 seconds passed
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 .. parsed-literal::
 
-    ... 62%, 437376 KB, 3352 KB/s, 130 seconds passed
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 .. parsed-literal::
 
-    ... 62%, 437536 KB, 3352 KB/s, 130 seconds passed
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 .. parsed-literal::
 
-    ... 62%, 437760 KB, 3352 KB/s, 130 seconds passed
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 .. parsed-literal::
 
-    ... 62%, 437920 KB, 3352 KB/s, 130 seconds passed
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 .. parsed-literal::
 
-    ... 62%, 438144 KB, 3352 KB/s, 130 seconds passed
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-... 63%, 438208 KB, 3352 KB/s, 130 seconds passed
-... 63%, 438240 KB, 3352 KB/s, 130 seconds passed
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 .. parsed-literal::
 
-    ... 63%, 438304 KB, 3352 KB/s, 130 seconds passed
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-... 63%, 438400 KB, 3352 KB/s, 130 seconds passed
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+... 60%, 424224 KB, 3671 KB/s, 115 seconds passed
+... 60%, 424256 KB, 3671 KB/s, 115 seconds passed
 
 .. parsed-literal::
 
-    ... 63%, 438496 KB, 3352 KB/s, 130 seconds passed
-... 63%, 438528 KB, 3353 KB/s, 130 seconds passed
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 .. parsed-literal::
 
-    ... 63%, 438688 KB, 3353 KB/s, 130 seconds passed
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 .. parsed-literal::
 
-    ... 63%, 438880 KB, 3353 KB/s, 130 seconds passed
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 .. parsed-literal::
 
-    ... 63%, 439072 KB, 3353 KB/s, 130 seconds passed
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 .. parsed-literal::
 
-    ... 63%, 439264 KB, 3353 KB/s, 130 seconds passed
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 .. parsed-literal::
 
-    ... 63%, 439456 KB, 3353 KB/s, 131 seconds passed
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 .. parsed-literal::
 
-    ... 63%, 439648 KB, 3353 KB/s, 131 seconds passed
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 .. parsed-literal::
 
-    ... 63%, 439840 KB, 3353 KB/s, 131 seconds passed
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 .. parsed-literal::
 
-    ... 63%, 440032 KB, 3354 KB/s, 131 seconds passed
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 .. parsed-literal::
 
-    ... 63%, 440192 KB, 3354 KB/s, 131 seconds passed
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 .. parsed-literal::
 
-    ... 63%, 440416 KB, 3354 KB/s, 131 seconds passed
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 .. parsed-literal::
 
-    ... 63%, 440576 KB, 3354 KB/s, 131 seconds passed
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 .. parsed-literal::
 
-    ... 63%, 440800 KB, 3354 KB/s, 131 seconds passed
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 .. parsed-literal::
 
-    ... 63%, 440960 KB, 3354 KB/s, 131 seconds passed
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 .. parsed-literal::
 
-    ... 63%, 441152 KB, 3354 KB/s, 131 seconds passed
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 .. parsed-literal::
 
-    ... 63%, 441344 KB, 3354 KB/s, 131 seconds passed
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 .. parsed-literal::
 
-    ... 63%, 441536 KB, 3355 KB/s, 131 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 63%, 442496 KB, 3355 KB/s, 131 seconds passed
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 .. parsed-literal::
 
-    ... 63%, 442656 KB, 3355 KB/s, 131 seconds passed
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 .. parsed-literal::
 
-    ... 63%, 442848 KB, 3356 KB/s, 131 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 63%, 443616 KB, 3356 KB/s, 132 seconds passed
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 .. parsed-literal::
 
-    ... 63%, 443808 KB, 3356 KB/s, 132 seconds passed
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 .. parsed-literal::
 
-    ... 63%, 444000 KB, 3356 KB/s, 132 seconds passed
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 .. parsed-literal::
 
-    ... 63%, 444160 KB, 3356 KB/s, 132 seconds passed
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 .. parsed-literal::
 
-    ... 63%, 444384 KB, 3356 KB/s, 132 seconds passed
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 .. parsed-literal::
 
-    ... 63%, 444544 KB, 3357 KB/s, 132 seconds passed
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 .. parsed-literal::
 
-    ... 63%, 444736 KB, 3357 KB/s, 132 seconds passed
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 .. parsed-literal::
 
-    ... 63%, 444928 KB, 3357 KB/s, 132 seconds passed
-... 63%, 444960 KB, 3356 KB/s, 132 seconds passed
-... 63%, 444992 KB, 3356 KB/s, 132 seconds passed
-... 63%, 445024 KB, 3357 KB/s, 132 seconds passed
-... 63%, 445056 KB, 3357 KB/s, 132 seconds passed
+    ... 61%, 430688 KB, 3671 KB/s, 117 seconds passed
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+... 61%, 430816 KB, 3671 KB/s, 117 seconds passed
+... 61%, 430848 KB, 3671 KB/s, 117 seconds passed
+... 61%, 430880 KB, 3671 KB/s, 117 seconds passed
 
 .. parsed-literal::
 
-    ... 63%, 445088 KB, 3356 KB/s, 132 seconds passed
+    ... 61%, 430912 KB, 3672 KB/s, 117 seconds passed
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+... 61%, 430976 KB, 3671 KB/s, 117 seconds passed
+... 61%, 431008 KB, 3671 KB/s, 117 seconds passed
+... 61%, 431040 KB, 3672 KB/s, 117 seconds passed
 
 .. parsed-literal::
 
-    ... 63%, 445120 KB, 3355 KB/s, 132 seconds passed
-... 64%, 445152 KB, 3355 KB/s, 132 seconds passed
+    ... 61%, 431072 KB, 3671 KB/s, 117 seconds passed
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+... 61%, 431168 KB, 3672 KB/s, 117 seconds passed
+... 61%, 431200 KB, 3671 KB/s, 117 seconds passed
+... 62%, 431232 KB, 3671 KB/s, 117 seconds passed
 
 .. parsed-literal::
 
-    ... 64%, 445184 KB, 3354 KB/s, 132 seconds passed
+    ... 62%, 431264 KB, 3671 KB/s, 117 seconds passed
+... 62%, 431296 KB, 3672 KB/s, 117 seconds passed
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+... 62%, 431360 KB, 3671 KB/s, 117 seconds passed
+... 62%, 431392 KB, 3671 KB/s, 117 seconds passed
+... 62%, 431424 KB, 3672 KB/s, 117 seconds passed
 
 .. parsed-literal::
 
-    ... 64%, 445216 KB, 3354 KB/s, 132 seconds passed
-... 64%, 445248 KB, 3354 KB/s, 132 seconds passed
-... 64%, 445280 KB, 3353 KB/s, 132 seconds passed
-... 64%, 445312 KB, 3353 KB/s, 132 seconds passed
+    ... 62%, 431456 KB, 3671 KB/s, 117 seconds passed
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+... 62%, 431552 KB, 3672 KB/s, 117 seconds passed
+... 62%, 431584 KB, 3671 KB/s, 117 seconds passed
+... 62%, 431616 KB, 3671 KB/s, 117 seconds passed
 
 .. parsed-literal::
 
-    ... 64%, 445344 KB, 3353 KB/s, 132 seconds passed
-... 64%, 445376 KB, 3353 KB/s, 132 seconds passed
+    ... 62%, 431648 KB, 3671 KB/s, 117 seconds passed
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+... 62%, 431744 KB, 3671 KB/s, 117 seconds passed
+... 62%, 431776 KB, 3671 KB/s, 117 seconds passed
+... 62%, 431808 KB, 3672 KB/s, 117 seconds passed
 
 .. parsed-literal::
 
-    ... 64%, 445408 KB, 3353 KB/s, 132 seconds passed
-... 64%, 445440 KB, 3353 KB/s, 132 seconds passed
-... 64%, 445472 KB, 3353 KB/s, 132 seconds passed
-... 64%, 445504 KB, 3352 KB/s, 132 seconds passed
-... 64%, 445536 KB, 3353 KB/s, 132 seconds passed
-... 64%, 445568 KB, 3353 KB/s, 132 seconds passed
+    ... 62%, 431840 KB, 3671 KB/s, 117 seconds passed
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+... 62%, 431936 KB, 3672 KB/s, 117 seconds passed
+... 62%, 431968 KB, 3671 KB/s, 117 seconds passed
+... 62%, 432000 KB, 3672 KB/s, 117 seconds passed
 
 .. parsed-literal::
 
-    ... 64%, 445600 KB, 3352 KB/s, 132 seconds passed
-... 64%, 445632 KB, 3352 KB/s, 132 seconds passed
-... 64%, 445664 KB, 3353 KB/s, 132 seconds passed
+    ... 62%, 432032 KB, 3672 KB/s, 117 seconds passed
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+... 62%, 432128 KB, 3672 KB/s, 117 seconds passed
+... 62%, 432160 KB, 3672 KB/s, 117 seconds passed
+... 62%, 432192 KB, 3672 KB/s, 117 seconds passed
 
 .. parsed-literal::
 
-    ... 64%, 445696 KB, 3352 KB/s, 132 seconds passed
-... 64%, 445728 KB, 3352 KB/s, 132 seconds passed
-... 64%, 445760 KB, 3352 KB/s, 132 seconds passed
-... 64%, 445792 KB, 3353 KB/s, 132 seconds passed
-... 64%, 445824 KB, 3352 KB/s, 132 seconds passed
-... 64%, 445856 KB, 3352 KB/s, 132 seconds passed
-... 64%, 445888 KB, 3353 KB/s, 132 seconds passed
+    ... 62%, 432224 KB, 3671 KB/s, 117 seconds passed
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+... 62%, 432320 KB, 3672 KB/s, 117 seconds passed
+... 62%, 432352 KB, 3671 KB/s, 117 seconds passed
+... 62%, 432384 KB, 3672 KB/s, 117 seconds passed
 
 .. parsed-literal::
 
-    ... 64%, 445920 KB, 3353 KB/s, 132 seconds passed
-... 64%, 445952 KB, 3352 KB/s, 133 seconds passed
-... 64%, 445984 KB, 3352 KB/s, 133 seconds passed
-... 64%, 446016 KB, 3353 KB/s, 133 seconds passed
-... 64%, 446048 KB, 3353 KB/s, 133 seconds passed
+    ... 62%, 432416 KB, 3672 KB/s, 117 seconds passed
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+... 62%, 432512 KB, 3672 KB/s, 117 seconds passed
+... 62%, 432544 KB, 3672 KB/s, 117 seconds passed
+... 62%, 432576 KB, 3672 KB/s, 117 seconds passed
 
 .. parsed-literal::
 
-    ... 64%, 446080 KB, 3352 KB/s, 133 seconds passed
-... 64%, 446112 KB, 3353 KB/s, 133 seconds passed
-... 64%, 446144 KB, 3353 KB/s, 133 seconds passed
-... 64%, 446176 KB, 3353 KB/s, 133 seconds passed
-... 64%, 446208 KB, 3352 KB/s, 133 seconds passed
-... 64%, 446240 KB, 3353 KB/s, 133 seconds passed
+    ... 62%, 432608 KB, 3671 KB/s, 117 seconds passed
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+... 62%, 432704 KB, 3672 KB/s, 117 seconds passed
+... 62%, 432736 KB, 3671 KB/s, 117 seconds passed
+... 62%, 432768 KB, 3672 KB/s, 117 seconds passed
 
 .. parsed-literal::
 
-    ... 64%, 446272 KB, 3353 KB/s, 133 seconds passed
-... 64%, 446304 KB, 3353 KB/s, 133 seconds passed
-... 64%, 446336 KB, 3353 KB/s, 133 seconds passed
-... 64%, 446368 KB, 3353 KB/s, 133 seconds passed
-... 64%, 446400 KB, 3353 KB/s, 133 seconds passed
-... 64%, 446432 KB, 3353 KB/s, 133 seconds passed
+    ... 62%, 432800 KB, 3672 KB/s, 117 seconds passed
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+... 62%, 432896 KB, 3672 KB/s, 117 seconds passed
+... 62%, 432928 KB, 3672 KB/s, 117 seconds passed
+... 62%, 432960 KB, 3672 KB/s, 117 seconds passed
 
 .. parsed-literal::
 
-    ... 64%, 446464 KB, 3353 KB/s, 133 seconds passed
-... 64%, 446496 KB, 3353 KB/s, 133 seconds passed
-... 64%, 446528 KB, 3353 KB/s, 133 seconds passed
-... 64%, 446560 KB, 3353 KB/s, 133 seconds passed
-... 64%, 446592 KB, 3353 KB/s, 133 seconds passed
-... 64%, 446624 KB, 3353 KB/s, 133 seconds passed
+    ... 62%, 432992 KB, 3671 KB/s, 117 seconds passed
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+... 62%, 433088 KB, 3672 KB/s, 117 seconds passed
+... 62%, 433120 KB, 3671 KB/s, 117 seconds passed
+... 62%, 433152 KB, 3672 KB/s, 117 seconds passed
 
 .. parsed-literal::
 
-    ... 64%, 446656 KB, 3353 KB/s, 133 seconds passed
-... 64%, 446688 KB, 3353 KB/s, 133 seconds passed
-... 64%, 446720 KB, 3353 KB/s, 133 seconds passed
-... 64%, 446752 KB, 3353 KB/s, 133 seconds passed
-... 64%, 446784 KB, 3353 KB/s, 133 seconds passed
-... 64%, 446816 KB, 3353 KB/s, 133 seconds passed
+    ... 62%, 433184 KB, 3672 KB/s, 117 seconds passed
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+... 62%, 433280 KB, 3672 KB/s, 117 seconds passed
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+... 62%, 433344 KB, 3672 KB/s, 118 seconds passed
 
 .. parsed-literal::
 
-    ... 64%, 446848 KB, 3353 KB/s, 133 seconds passed
-... 64%, 446880 KB, 3353 KB/s, 133 seconds passed
-... 64%, 446912 KB, 3353 KB/s, 133 seconds passed
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-... 64%, 446976 KB, 3353 KB/s, 133 seconds passed
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+... 62%, 433504 KB, 3672 KB/s, 118 seconds passed
 
 .. parsed-literal::
 
-    ... 64%, 447008 KB, 3353 KB/s, 133 seconds passed
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-... 64%, 447072 KB, 3354 KB/s, 133 seconds passed
-... 64%, 447104 KB, 3353 KB/s, 133 seconds passed
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-... 64%, 447168 KB, 3353 KB/s, 133 seconds passed
-... 64%, 447200 KB, 3354 KB/s, 133 seconds passed
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 .. parsed-literal::
 
-    ... 64%, 447232 KB, 3353 KB/s, 133 seconds passed
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-... 64%, 447296 KB, 3353 KB/s, 133 seconds passed
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 .. parsed-literal::
 
-    ... 64%, 447392 KB, 3353 KB/s, 133 seconds passed
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+    ... 62%, 433920 KB, 3671 KB/s, 118 seconds passed
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 .. parsed-literal::
 
-    ... 64%, 447616 KB, 3353 KB/s, 133 seconds passed
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 .. parsed-literal::
 
-    ... 64%, 447776 KB, 3354 KB/s, 133 seconds passed
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 .. parsed-literal::
 
-    ... 64%, 448000 KB, 3354 KB/s, 133 seconds passed
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 .. parsed-literal::
 
-    ... 64%, 448128 KB, 3354 KB/s, 133 seconds passed
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 .. parsed-literal::
 
-    ... 64%, 448384 KB, 3354 KB/s, 133 seconds passed
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 .. parsed-literal::
 
-    ... 64%, 448512 KB, 3354 KB/s, 133 seconds passed
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-... 64%, 448672 KB, 3354 KB/s, 133 seconds passed
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+... 62%, 435200 KB, 3672 KB/s, 118 seconds passed
 
 .. parsed-literal::
 
-    ... 64%, 448768 KB, 3354 KB/s, 133 seconds passed
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 .. parsed-literal::
 
-    ... 64%, 448896 KB, 3354 KB/s, 133 seconds passed
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 .. parsed-literal::
 
-    ... 64%, 449152 KB, 3355 KB/s, 133 seconds passed
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 .. parsed-literal::
 
-    ... 64%, 449248 KB, 3354 KB/s, 133 seconds passed
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-... 64%, 449472 KB, 3355 KB/s, 133 seconds passed
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 .. parsed-literal::
 
-    ... 64%, 449504 KB, 3355 KB/s, 133 seconds passed
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-... 64%, 449600 KB, 3355 KB/s, 133 seconds passed
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+... 62%, 436128 KB, 3672 KB/s, 118 seconds passed
+... 62%, 436160 KB, 3672 KB/s, 118 seconds passed
 
 .. parsed-literal::
 
-    ... 64%, 449632 KB, 3355 KB/s, 134 seconds passed
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-... 64%, 449792 KB, 3355 KB/s, 134 seconds passed
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-... 64%, 449856 KB, 3355 KB/s, 134 seconds passed
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+... 62%, 436288 KB, 3672 KB/s, 118 seconds passed
+... 62%, 436320 KB, 3672 KB/s, 118 seconds passed
+... 62%, 436352 KB, 3672 KB/s, 118 seconds passed
 
 .. parsed-literal::
 
-    ... 64%, 449888 KB, 3355 KB/s, 134 seconds passed
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+    ... 62%, 436384 KB, 3672 KB/s, 118 seconds passed
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+... 62%, 436480 KB, 3672 KB/s, 118 seconds passed
+... 62%, 436512 KB, 3672 KB/s, 118 seconds passed
 
 .. parsed-literal::
 
-    ... 64%, 450016 KB, 3355 KB/s, 134 seconds passed
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-... 64%, 450208 KB, 3355 KB/s, 134 seconds passed
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+... 62%, 436672 KB, 3672 KB/s, 118 seconds passed
+... 62%, 436704 KB, 3672 KB/s, 118 seconds passed
+... 62%, 436736 KB, 3672 KB/s, 118 seconds passed
 
 .. parsed-literal::
 
-    ... 64%, 450240 KB, 3355 KB/s, 134 seconds passed
-... 64%, 450272 KB, 3355 KB/s, 134 seconds passed
-... 64%, 450304 KB, 3355 KB/s, 134 seconds passed
-... 64%, 450336 KB, 3355 KB/s, 134 seconds passed
-... 64%, 450368 KB, 3356 KB/s, 134 seconds passed
+    ... 62%, 436768 KB, 3672 KB/s, 118 seconds passed
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+... 62%, 436832 KB, 3672 KB/s, 118 seconds passed
+... 62%, 436864 KB, 3672 KB/s, 118 seconds passed
+... 62%, 436896 KB, 3672 KB/s, 118 seconds passed
 
 .. parsed-literal::
 
-    ... 64%, 450400 KB, 3355 KB/s, 134 seconds passed
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-... 64%, 450592 KB, 3356 KB/s, 134 seconds passed
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+... 62%, 437088 KB, 3672 KB/s, 119 seconds passed
+... 62%, 437120 KB, 3672 KB/s, 119 seconds passed
 
 .. parsed-literal::
 
-    ... 64%, 450624 KB, 3356 KB/s, 134 seconds passed
-... 64%, 450656 KB, 3355 KB/s, 134 seconds passed
-... 64%, 450688 KB, 3356 KB/s, 134 seconds passed
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-... 64%, 450752 KB, 3356 KB/s, 134 seconds passed
+    ... 62%, 437152 KB, 3672 KB/s, 119 seconds passed
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+... 62%, 437216 KB, 3672 KB/s, 119 seconds passed
+... 62%, 437248 KB, 3672 KB/s, 119 seconds passed
+... 62%, 437280 KB, 3671 KB/s, 119 seconds passed
 
 .. parsed-literal::
 
-    ... 64%, 450784 KB, 3356 KB/s, 134 seconds passed
-... 64%, 450816 KB, 3356 KB/s, 134 seconds passed
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-... 64%, 450912 KB, 3356 KB/s, 134 seconds passed
-... 64%, 450944 KB, 3356 KB/s, 134 seconds passed
-... 64%, 450976 KB, 3356 KB/s, 134 seconds passed
+    ... 62%, 437312 KB, 3672 KB/s, 119 seconds passed
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+... 62%, 437408 KB, 3672 KB/s, 119 seconds passed
+... 62%, 437440 KB, 3672 KB/s, 119 seconds passed
+... 62%, 437472 KB, 3672 KB/s, 119 seconds passed
+... 62%, 437504 KB, 3672 KB/s, 119 seconds passed
 
 .. parsed-literal::
 
-    ... 64%, 451008 KB, 3356 KB/s, 134 seconds passed
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 .. parsed-literal::
 
-    ... 64%, 451168 KB, 3356 KB/s, 134 seconds passed
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-... 64%, 451360 KB, 3356 KB/s, 134 seconds passed
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 .. parsed-literal::
 
-    ... 64%, 451392 KB, 3356 KB/s, 134 seconds passed
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 .. parsed-literal::
 
-    ... 64%, 451552 KB, 3356 KB/s, 134 seconds passed
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 .. parsed-literal::
 
-    ... 64%, 451744 KB, 3356 KB/s, 134 seconds passed
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 .. parsed-literal::
 
-    ... 64%, 451936 KB, 3356 KB/s, 134 seconds passed
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 .. parsed-literal::
 
-    ... 65%, 452128 KB, 3357 KB/s, 134 seconds passed
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 .. parsed-literal::
 
-    ... 65%, 452320 KB, 3357 KB/s, 134 seconds passed
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+... 63%, 439008 KB, 3672 KB/s, 119 seconds passed
 
 .. parsed-literal::
 
-    ... 65%, 452512 KB, 3357 KB/s, 134 seconds passed
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 .. parsed-literal::
 
-    ... 65%, 452704 KB, 3357 KB/s, 134 seconds passed
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-... 65%, 452800 KB, 3357 KB/s, 134 seconds passed
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 .. parsed-literal::
 
-    ... 65%, 452896 KB, 3357 KB/s, 134 seconds passed
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 .. parsed-literal::
 
-    ... 65%, 453088 KB, 3357 KB/s, 134 seconds passed
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 .. parsed-literal::
 
-    ... 65%, 453280 KB, 3357 KB/s, 134 seconds passed
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 .. parsed-literal::
 
-    ... 65%, 453472 KB, 3357 KB/s, 135 seconds passed
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 .. parsed-literal::
 
-    ... 65%, 453664 KB, 3358 KB/s, 135 seconds passed
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 .. parsed-literal::
 
-    ... 65%, 453824 KB, 3358 KB/s, 135 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 65%, 454976 KB, 3358 KB/s, 135 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 65%, 455744 KB, 3359 KB/s, 135 seconds passed
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 .. parsed-literal::
 
-    ... 65%, 455904 KB, 3359 KB/s, 135 seconds passed
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 .. parsed-literal::
 
-    ... 65%, 456128 KB, 3359 KB/s, 135 seconds passed
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 .. parsed-literal::
 
-    ... 65%, 456288 KB, 3359 KB/s, 135 seconds passed
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 .. parsed-literal::
 
-    ... 65%, 456512 KB, 3359 KB/s, 135 seconds passed
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 .. parsed-literal::
 
-    ... 65%, 456672 KB, 3360 KB/s, 135 seconds passed
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 .. parsed-literal::
 
-    ... 65%, 456864 KB, 3360 KB/s, 135 seconds passed
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 .. parsed-literal::
 
-    ... 65%, 457056 KB, 3360 KB/s, 136 seconds passed
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 .. parsed-literal::
 
-    ... 65%, 457248 KB, 3360 KB/s, 136 seconds passed
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+    ... 63%, 443776 KB, 3672 KB/s, 120 seconds passed
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+... 63%, 443840 KB, 3672 KB/s, 120 seconds passed
+... 63%, 443872 KB, 3672 KB/s, 120 seconds passed
+... 63%, 443904 KB, 3672 KB/s, 120 seconds passed
+... 63%, 443936 KB, 3672 KB/s, 120 seconds passed
 
 .. parsed-literal::
 
-    ... 65%, 457408 KB, 3360 KB/s, 136 seconds passed
-... 65%, 457440 KB, 3360 KB/s, 136 seconds passed
-... 65%, 457472 KB, 3360 KB/s, 136 seconds passed
-... 65%, 457504 KB, 3360 KB/s, 136 seconds passed
-... 65%, 457536 KB, 3360 KB/s, 136 seconds passed
-... 65%, 457568 KB, 3360 KB/s, 136 seconds passed
-... 65%, 457600 KB, 3360 KB/s, 136 seconds passed
+    ... 63%, 443968 KB, 3672 KB/s, 120 seconds passed
+... 63%, 444000 KB, 3672 KB/s, 120 seconds passed
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+... 63%, 444064 KB, 3672 KB/s, 120 seconds passed
+... 63%, 444096 KB, 3672 KB/s, 120 seconds passed
+... 63%, 444128 KB, 3672 KB/s, 120 seconds passed
 
 .. parsed-literal::
 
-    ... 65%, 457632 KB, 3360 KB/s, 136 seconds passed
-... 65%, 457664 KB, 3360 KB/s, 136 seconds passed
-... 65%, 457696 KB, 3360 KB/s, 136 seconds passed
-... 65%, 457728 KB, 3360 KB/s, 136 seconds passed
-... 65%, 457760 KB, 3360 KB/s, 136 seconds passed
+    ... 63%, 444160 KB, 3672 KB/s, 120 seconds passed
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+... 63%, 444256 KB, 3672 KB/s, 120 seconds passed
+... 63%, 444288 KB, 3672 KB/s, 120 seconds passed
+... 63%, 444320 KB, 3672 KB/s, 120 seconds passed
 
 .. parsed-literal::
 
-    ... 65%, 457792 KB, 3360 KB/s, 136 seconds passed
-... 65%, 457824 KB, 3360 KB/s, 136 seconds passed
-... 65%, 457856 KB, 3360 KB/s, 136 seconds passed
-... 65%, 457888 KB, 3360 KB/s, 136 seconds passed
-... 65%, 457920 KB, 3360 KB/s, 136 seconds passed
-... 65%, 457952 KB, 3360 KB/s, 136 seconds passed
-... 65%, 457984 KB, 3360 KB/s, 136 seconds passed
+    ... 63%, 444352 KB, 3672 KB/s, 120 seconds passed
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+... 63%, 444448 KB, 3672 KB/s, 121 seconds passed
+... 63%, 444480 KB, 3672 KB/s, 121 seconds passed
+... 63%, 444512 KB, 3672 KB/s, 121 seconds passed
 
 .. parsed-literal::
 
-    ... 65%, 458016 KB, 3360 KB/s, 136 seconds passed
-... 65%, 458048 KB, 3360 KB/s, 136 seconds passed
-... 65%, 458080 KB, 3360 KB/s, 136 seconds passed
-... 65%, 458112 KB, 3361 KB/s, 136 seconds passed
-... 65%, 458144 KB, 3360 KB/s, 136 seconds passed
+    ... 63%, 444544 KB, 3672 KB/s, 121 seconds passed
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+... 63%, 444608 KB, 3672 KB/s, 121 seconds passed
+... 63%, 444640 KB, 3672 KB/s, 121 seconds passed
+... 63%, 444672 KB, 3672 KB/s, 121 seconds passed
 
 .. parsed-literal::
 
-    ... 65%, 458176 KB, 3360 KB/s, 136 seconds passed
-... 65%, 458208 KB, 3360 KB/s, 136 seconds passed
-... 65%, 458240 KB, 3361 KB/s, 136 seconds passed
-... 65%, 458272 KB, 3361 KB/s, 136 seconds passed
-... 65%, 458304 KB, 3361 KB/s, 136 seconds passed
-... 65%, 458336 KB, 3361 KB/s, 136 seconds passed
-... 65%, 458368 KB, 3361 KB/s, 136 seconds passed
+    ... 63%, 444704 KB, 3672 KB/s, 121 seconds passed
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+... 63%, 444832 KB, 3672 KB/s, 121 seconds passed
+... 63%, 444864 KB, 3672 KB/s, 121 seconds passed
+... 63%, 444896 KB, 3672 KB/s, 121 seconds passed
 
 .. parsed-literal::
 
-    ... 65%, 458400 KB, 3361 KB/s, 136 seconds passed
-... 65%, 458432 KB, 3361 KB/s, 136 seconds passed
-... 65%, 458464 KB, 3361 KB/s, 136 seconds passed
-... 65%, 458496 KB, 3361 KB/s, 136 seconds passed
-... 65%, 458528 KB, 3361 KB/s, 136 seconds passed
+    ... 63%, 444928 KB, 3672 KB/s, 121 seconds passed
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+... 63%, 444992 KB, 3672 KB/s, 121 seconds passed
+... 63%, 445024 KB, 3672 KB/s, 121 seconds passed
+... 63%, 445056 KB, 3672 KB/s, 121 seconds passed
 
 .. parsed-literal::
 
-    ... 65%, 458560 KB, 3361 KB/s, 136 seconds passed
-... 65%, 458592 KB, 3361 KB/s, 136 seconds passed
-... 65%, 458624 KB, 3361 KB/s, 136 seconds passed
-... 65%, 458656 KB, 3361 KB/s, 136 seconds passed
-... 65%, 458688 KB, 3361 KB/s, 136 seconds passed
-... 65%, 458720 KB, 3361 KB/s, 136 seconds passed
+    ... 63%, 445088 KB, 3672 KB/s, 121 seconds passed
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+... 64%, 445184 KB, 3672 KB/s, 121 seconds passed
+... 64%, 445216 KB, 3672 KB/s, 121 seconds passed
+... 64%, 445248 KB, 3672 KB/s, 121 seconds passed
 
 .. parsed-literal::
 
-    ... 65%, 458752 KB, 3361 KB/s, 136 seconds passed
-... 65%, 458784 KB, 3361 KB/s, 136 seconds passed
-... 65%, 458816 KB, 3361 KB/s, 136 seconds passed
-... 65%, 458848 KB, 3361 KB/s, 136 seconds passed
-... 65%, 458880 KB, 3361 KB/s, 136 seconds passed
-... 65%, 458912 KB, 3361 KB/s, 136 seconds passed
+    ... 64%, 445280 KB, 3672 KB/s, 121 seconds passed
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+... 64%, 445376 KB, 3672 KB/s, 121 seconds passed
+... 64%, 445408 KB, 3672 KB/s, 121 seconds passed
+... 64%, 445440 KB, 3672 KB/s, 121 seconds passed
 
 .. parsed-literal::
 
-    ... 65%, 458944 KB, 3361 KB/s, 136 seconds passed
-... 65%, 458976 KB, 3361 KB/s, 136 seconds passed
-... 65%, 459008 KB, 3361 KB/s, 136 seconds passed
-... 66%, 459040 KB, 3361 KB/s, 136 seconds passed
-... 66%, 459072 KB, 3361 KB/s, 136 seconds passed
-... 66%, 459104 KB, 3361 KB/s, 136 seconds passed
+    ... 64%, 445472 KB, 3672 KB/s, 121 seconds passed
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+... 64%, 445568 KB, 3672 KB/s, 121 seconds passed
+... 64%, 445600 KB, 3672 KB/s, 121 seconds passed
+... 64%, 445632 KB, 3672 KB/s, 121 seconds passed
 
 .. parsed-literal::
 
-    ... 66%, 459136 KB, 3361 KB/s, 136 seconds passed
-... 66%, 459168 KB, 3361 KB/s, 136 seconds passed
-... 66%, 459200 KB, 3361 KB/s, 136 seconds passed
-... 66%, 459232 KB, 3361 KB/s, 136 seconds passed
-... 66%, 459264 KB, 3361 KB/s, 136 seconds passed
+    ... 64%, 445664 KB, 3672 KB/s, 121 seconds passed
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+... 64%, 445728 KB, 3672 KB/s, 121 seconds passed
+... 64%, 445760 KB, 3672 KB/s, 121 seconds passed
+... 64%, 445792 KB, 3672 KB/s, 121 seconds passed
 
 .. parsed-literal::
 
-    ... 66%, 459296 KB, 3361 KB/s, 136 seconds passed
-... 66%, 459328 KB, 3361 KB/s, 136 seconds passed
-... 66%, 459360 KB, 3361 KB/s, 136 seconds passed
-... 66%, 459392 KB, 3361 KB/s, 136 seconds passed
-... 66%, 459424 KB, 3361 KB/s, 136 seconds passed
-... 66%, 459456 KB, 3361 KB/s, 136 seconds passed
-... 66%, 459488 KB, 3361 KB/s, 136 seconds passed
+    ... 64%, 445824 KB, 3672 KB/s, 121 seconds passed
+... 64%, 445856 KB, 3672 KB/s, 121 seconds passed
+... 64%, 445888 KB, 3672 KB/s, 121 seconds passed
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+... 64%, 445952 KB, 3672 KB/s, 121 seconds passed
+... 64%, 445984 KB, 3672 KB/s, 121 seconds passed
+... 64%, 446016 KB, 3672 KB/s, 121 seconds passed
 
 .. parsed-literal::
 
-    ... 66%, 459520 KB, 3361 KB/s, 136 seconds passed
-... 66%, 459552 KB, 3361 KB/s, 136 seconds passed
-... 66%, 459584 KB, 3361 KB/s, 136 seconds passed
-... 66%, 459616 KB, 3361 KB/s, 136 seconds passed
-... 66%, 459648 KB, 3362 KB/s, 136 seconds passed
+    ... 64%, 446048 KB, 3672 KB/s, 121 seconds passed
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+... 64%, 446112 KB, 3672 KB/s, 121 seconds passed
+... 64%, 446144 KB, 3672 KB/s, 121 seconds passed
+... 64%, 446176 KB, 3672 KB/s, 121 seconds passed
 
 .. parsed-literal::
 
-    ... 66%, 459680 KB, 3361 KB/s, 136 seconds passed
-... 66%, 459712 KB, 3361 KB/s, 136 seconds passed
-... 66%, 459744 KB, 3362 KB/s, 136 seconds passed
-... 66%, 459776 KB, 3362 KB/s, 136 seconds passed
-... 66%, 459808 KB, 3362 KB/s, 136 seconds passed
-... 66%, 459840 KB, 3362 KB/s, 136 seconds passed
+    ... 64%, 446208 KB, 3672 KB/s, 121 seconds passed
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+... 64%, 446336 KB, 3672 KB/s, 121 seconds passed
+... 64%, 446368 KB, 3672 KB/s, 121 seconds passed
+... 64%, 446400 KB, 3672 KB/s, 121 seconds passed
 
 .. parsed-literal::
 
-    ... 66%, 459872 KB, 3362 KB/s, 136 seconds passed
-... 66%, 459904 KB, 3362 KB/s, 136 seconds passed
-... 66%, 459936 KB, 3362 KB/s, 136 seconds passed
-... 66%, 459968 KB, 3362 KB/s, 136 seconds passed
-... 66%, 460000 KB, 3362 KB/s, 136 seconds passed
-... 66%, 460032 KB, 3362 KB/s, 136 seconds passed
+    ... 64%, 446432 KB, 3672 KB/s, 121 seconds passed
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+... 64%, 446496 KB, 3672 KB/s, 121 seconds passed
+... 64%, 446528 KB, 3672 KB/s, 121 seconds passed
+... 64%, 446560 KB, 3672 KB/s, 121 seconds passed
 
 .. parsed-literal::
 
-    ... 66%, 460064 KB, 3362 KB/s, 136 seconds passed
-... 66%, 460096 KB, 3362 KB/s, 136 seconds passed
-... 66%, 460128 KB, 3362 KB/s, 136 seconds passed
-... 66%, 460160 KB, 3362 KB/s, 136 seconds passed
-... 66%, 460192 KB, 3362 KB/s, 136 seconds passed
-... 66%, 460224 KB, 3362 KB/s, 136 seconds passed
+    ... 64%, 446592 KB, 3672 KB/s, 121 seconds passed
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+... 64%, 446720 KB, 3672 KB/s, 121 seconds passed
+... 64%, 446752 KB, 3672 KB/s, 121 seconds passed
+... 64%, 446784 KB, 3672 KB/s, 121 seconds passed
 
 .. parsed-literal::
 
-    ... 66%, 460256 KB, 3362 KB/s, 136 seconds passed
-... 66%, 460288 KB, 3362 KB/s, 136 seconds passed
-... 66%, 460320 KB, 3362 KB/s, 136 seconds passed
-... 66%, 460352 KB, 3362 KB/s, 136 seconds passed
-... 66%, 460384 KB, 3362 KB/s, 136 seconds passed
-... 66%, 460416 KB, 3362 KB/s, 136 seconds passed
+    ... 64%, 446816 KB, 3672 KB/s, 121 seconds passed
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+... 64%, 446880 KB, 3672 KB/s, 121 seconds passed
+... 64%, 446912 KB, 3672 KB/s, 121 seconds passed
+... 64%, 446944 KB, 3672 KB/s, 121 seconds passed
 
 .. parsed-literal::
 
-    ... 66%, 460448 KB, 3362 KB/s, 136 seconds passed
-... 66%, 460480 KB, 3362 KB/s, 136 seconds passed
-... 66%, 460512 KB, 3362 KB/s, 136 seconds passed
-... 66%, 460544 KB, 3362 KB/s, 136 seconds passed
-... 66%, 460576 KB, 3362 KB/s, 136 seconds passed
-... 66%, 460608 KB, 3362 KB/s, 136 seconds passed
+    ... 64%, 446976 KB, 3672 KB/s, 121 seconds passed
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+... 64%, 447104 KB, 3672 KB/s, 121 seconds passed
+... 64%, 447136 KB, 3672 KB/s, 121 seconds passed
+... 64%, 447168 KB, 3672 KB/s, 121 seconds passed
 
 .. parsed-literal::
 
-    ... 66%, 460640 KB, 3362 KB/s, 136 seconds passed
-... 66%, 460672 KB, 3362 KB/s, 136 seconds passed
-... 66%, 460704 KB, 3362 KB/s, 137 seconds passed
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-... 66%, 460768 KB, 3362 KB/s, 137 seconds passed
-... 66%, 460800 KB, 3362 KB/s, 137 seconds passed
+    ... 64%, 447200 KB, 3672 KB/s, 121 seconds passed
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+... 64%, 447264 KB, 3672 KB/s, 121 seconds passed
+... 64%, 447296 KB, 3672 KB/s, 121 seconds passed
+... 64%, 447328 KB, 3672 KB/s, 121 seconds passed
 
 .. parsed-literal::
 
-    ... 66%, 460832 KB, 3362 KB/s, 137 seconds passed
-... 66%, 460864 KB, 3362 KB/s, 137 seconds passed
-... 66%, 460896 KB, 3362 KB/s, 137 seconds passed
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-... 66%, 460992 KB, 3362 KB/s, 137 seconds passed
+    ... 64%, 447360 KB, 3672 KB/s, 121 seconds passed
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+... 64%, 447520 KB, 3672 KB/s, 121 seconds passed
 
 .. parsed-literal::
 
-    ... 66%, 461024 KB, 3362 KB/s, 137 seconds passed
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-... 66%, 461120 KB, 3362 KB/s, 137 seconds passed
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-... 66%, 461184 KB, 3363 KB/s, 137 seconds passed
+    ... 64%, 447552 KB, 3672 KB/s, 121 seconds passed
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 .. parsed-literal::
 
-    ... 66%, 461216 KB, 3362 KB/s, 137 seconds passed
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-... 66%, 461312 KB, 3363 KB/s, 137 seconds passed
-... 66%, 461344 KB, 3363 KB/s, 137 seconds passed
-... 66%, 461376 KB, 3363 KB/s, 137 seconds passed
+    ... 64%, 447712 KB, 3672 KB/s, 121 seconds passed
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+... 64%, 447872 KB, 3672 KB/s, 121 seconds passed
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 .. parsed-literal::
 
-    ... 66%, 461408 KB, 3363 KB/s, 137 seconds passed
-... 66%, 461440 KB, 3363 KB/s, 137 seconds passed
-... 66%, 461472 KB, 3363 KB/s, 137 seconds passed
-... 66%, 461504 KB, 3363 KB/s, 137 seconds passed
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-... 66%, 461568 KB, 3363 KB/s, 137 seconds passed
+    ... 64%, 447936 KB, 3672 KB/s, 121 seconds passed
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+... 64%, 448000 KB, 3672 KB/s, 121 seconds passed
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+... 64%, 448064 KB, 3672 KB/s, 121 seconds passed
 
 .. parsed-literal::
 
-    ... 66%, 461600 KB, 3363 KB/s, 137 seconds passed
-... 66%, 461632 KB, 3363 KB/s, 137 seconds passed
-... 66%, 461664 KB, 3363 KB/s, 137 seconds passed
-... 66%, 461696 KB, 3363 KB/s, 137 seconds passed
-... 66%, 461728 KB, 3363 KB/s, 137 seconds passed
-... 66%, 461760 KB, 3363 KB/s, 137 seconds passed
+    ... 64%, 448096 KB, 3672 KB/s, 122 seconds passed
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+... 64%, 448256 KB, 3672 KB/s, 122 seconds passed
+... 64%, 448288 KB, 3672 KB/s, 122 seconds passed
 
 .. parsed-literal::
 
-    ... 66%, 461792 KB, 3363 KB/s, 137 seconds passed
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-... 66%, 461856 KB, 3363 KB/s, 137 seconds passed
-... 66%, 461888 KB, 3363 KB/s, 137 seconds passed
+    ... 64%, 448320 KB, 3672 KB/s, 122 seconds passed
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+... 64%, 448384 KB, 3672 KB/s, 122 seconds passed
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+... 64%, 448448 KB, 3672 KB/s, 122 seconds passed
 
 .. parsed-literal::
 
-    ... 66%, 461920 KB, 3362 KB/s, 137 seconds passed
-... 66%, 461952 KB, 3362 KB/s, 137 seconds passed
-... 66%, 461984 KB, 3363 KB/s, 137 seconds passed
-... 66%, 462016 KB, 3363 KB/s, 137 seconds passed
+    ... 64%, 448480 KB, 3672 KB/s, 122 seconds passed
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+... 64%, 448608 KB, 3672 KB/s, 122 seconds passed
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+... 64%, 448672 KB, 3672 KB/s, 122 seconds passed
 
 .. parsed-literal::
 
-    ... 66%, 462048 KB, 3362 KB/s, 137 seconds passed
-... 66%, 462080 KB, 3362 KB/s, 137 seconds passed
+    ... 64%, 448704 KB, 3672 KB/s, 122 seconds passed
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 .. parsed-literal::
 
-    ... 66%, 462112 KB, 3361 KB/s, 137 seconds passed
+    ... 64%, 448864 KB, 3672 KB/s, 122 seconds passed
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+... 64%, 448992 KB, 3672 KB/s, 122 seconds passed
+... 64%, 449024 KB, 3672 KB/s, 122 seconds passed
+... 64%, 449056 KB, 3672 KB/s, 122 seconds passed
 
 .. parsed-literal::
 
-    ... 66%, 462144 KB, 3360 KB/s, 137 seconds passed
-... 66%, 462176 KB, 3361 KB/s, 137 seconds passed
-... 66%, 462208 KB, 3360 KB/s, 137 seconds passed
-... 66%, 462240 KB, 3360 KB/s, 137 seconds passed
+    ... 64%, 449088 KB, 3672 KB/s, 122 seconds passed
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+... 64%, 449152 KB, 3672 KB/s, 122 seconds passed
+... 64%, 449184 KB, 3672 KB/s, 122 seconds passed
+... 64%, 449216 KB, 3672 KB/s, 122 seconds passed
 
 .. parsed-literal::
 
-    ... 66%, 462272 KB, 3360 KB/s, 137 seconds passed
-... 66%, 462304 KB, 3360 KB/s, 137 seconds passed
-... 66%, 462336 KB, 3360 KB/s, 137 seconds passed
+    ... 64%, 449248 KB, 3672 KB/s, 122 seconds passed
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+... 64%, 449344 KB, 3672 KB/s, 122 seconds passed
+... 64%, 449376 KB, 3672 KB/s, 122 seconds passed
+... 64%, 449408 KB, 3672 KB/s, 122 seconds passed
 
 .. parsed-literal::
 
-    ... 66%, 462368 KB, 3359 KB/s, 137 seconds passed
-... 66%, 462400 KB, 3360 KB/s, 137 seconds passed
-... 66%, 462432 KB, 3359 KB/s, 137 seconds passed
-... 66%, 462464 KB, 3359 KB/s, 137 seconds passed
-... 66%, 462496 KB, 3359 KB/s, 137 seconds passed
+    ... 64%, 449440 KB, 3672 KB/s, 122 seconds passed
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+... 64%, 449536 KB, 3672 KB/s, 122 seconds passed
+... 64%, 449568 KB, 3672 KB/s, 122 seconds passed
+... 64%, 449600 KB, 3672 KB/s, 122 seconds passed
 
 .. parsed-literal::
 
-    ... 66%, 462528 KB, 3359 KB/s, 137 seconds passed
-... 66%, 462560 KB, 3359 KB/s, 137 seconds passed
-... 66%, 462592 KB, 3359 KB/s, 137 seconds passed
+    ... 64%, 449632 KB, 3672 KB/s, 122 seconds passed
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+... 64%, 449760 KB, 3672 KB/s, 122 seconds passed
+... 64%, 449792 KB, 3672 KB/s, 122 seconds passed
 
 .. parsed-literal::
 
-    ... 66%, 462624 KB, 3359 KB/s, 137 seconds passed
-... 66%, 462656 KB, 3359 KB/s, 137 seconds passed
-... 66%, 462688 KB, 3359 KB/s, 137 seconds passed
-... 66%, 462720 KB, 3359 KB/s, 137 seconds passed
-... 66%, 462752 KB, 3359 KB/s, 137 seconds passed
-... 66%, 462784 KB, 3359 KB/s, 137 seconds passed
-... 66%, 462816 KB, 3359 KB/s, 137 seconds passed
+    ... 64%, 449824 KB, 3672 KB/s, 122 seconds passed
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+... 64%, 449920 KB, 3672 KB/s, 122 seconds passed
+... 64%, 449952 KB, 3672 KB/s, 122 seconds passed
+... 64%, 449984 KB, 3672 KB/s, 122 seconds passed
 
 .. parsed-literal::
 
-    ... 66%, 462848 KB, 3359 KB/s, 137 seconds passed
-... 66%, 462880 KB, 3359 KB/s, 137 seconds passed
-... 66%, 462912 KB, 3359 KB/s, 137 seconds passed
-... 66%, 462944 KB, 3359 KB/s, 137 seconds passed
-... 66%, 462976 KB, 3360 KB/s, 137 seconds passed
+    ... 64%, 450016 KB, 3672 KB/s, 122 seconds passed
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+... 64%, 450112 KB, 3672 KB/s, 122 seconds passed
+... 64%, 450144 KB, 3672 KB/s, 122 seconds passed
+... 64%, 450176 KB, 3672 KB/s, 122 seconds passed
 
 .. parsed-literal::
 
-    ... 66%, 463008 KB, 3359 KB/s, 137 seconds passed
-... 66%, 463040 KB, 3359 KB/s, 137 seconds passed
-... 66%, 463072 KB, 3359 KB/s, 137 seconds passed
-... 66%, 463104 KB, 3359 KB/s, 137 seconds passed
-... 66%, 463136 KB, 3359 KB/s, 137 seconds passed
-... 66%, 463168 KB, 3359 KB/s, 137 seconds passed
-... 66%, 463200 KB, 3359 KB/s, 137 seconds passed
+    ... 64%, 450208 KB, 3672 KB/s, 122 seconds passed
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+... 64%, 450304 KB, 3672 KB/s, 122 seconds passed
+... 64%, 450336 KB, 3672 KB/s, 122 seconds passed
+... 64%, 450368 KB, 3672 KB/s, 122 seconds passed
 
 .. parsed-literal::
 
-    ... 66%, 463232 KB, 3359 KB/s, 137 seconds passed
-... 66%, 463264 KB, 3359 KB/s, 137 seconds passed
-... 66%, 463296 KB, 3359 KB/s, 137 seconds passed
-... 66%, 463328 KB, 3360 KB/s, 137 seconds passed
+    ... 64%, 450400 KB, 3672 KB/s, 122 seconds passed
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+... 64%, 450496 KB, 3672 KB/s, 122 seconds passed
+... 64%, 450528 KB, 3672 KB/s, 122 seconds passed
+... 64%, 450560 KB, 3672 KB/s, 122 seconds passed
 
 .. parsed-literal::
 
-    ... 66%, 463360 KB, 3359 KB/s, 137 seconds passed
-... 66%, 463392 KB, 3359 KB/s, 137 seconds passed
-... 66%, 463424 KB, 3359 KB/s, 137 seconds passed
-... 66%, 463456 KB, 3360 KB/s, 137 seconds passed
-... 66%, 463488 KB, 3359 KB/s, 137 seconds passed
-... 66%, 463520 KB, 3359 KB/s, 137 seconds passed
-... 66%, 463552 KB, 3360 KB/s, 137 seconds passed
+    ... 64%, 450592 KB, 3672 KB/s, 122 seconds passed
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+... 64%, 450720 KB, 3672 KB/s, 122 seconds passed
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 .. parsed-literal::
 
-    ... 66%, 463584 KB, 3360 KB/s, 137 seconds passed
-... 66%, 463616 KB, 3359 KB/s, 137 seconds passed
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 .. parsed-literal::
 
-    ... 66%, 463744 KB, 3359 KB/s, 138 seconds passed
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 .. parsed-literal::
 
-    ... 66%, 463936 KB, 3360 KB/s, 138 seconds passed
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 .. parsed-literal::
 
-    ... 66%, 464128 KB, 3360 KB/s, 138 seconds passed
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 .. parsed-literal::
 
-    ... 66%, 464320 KB, 3360 KB/s, 138 seconds passed
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+... 64%, 451680 KB, 3672 KB/s, 122 seconds passed
 
 .. parsed-literal::
 
-    ... 66%, 464480 KB, 3360 KB/s, 138 seconds passed
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 .. parsed-literal::
 
-    ... 66%, 464672 KB, 3360 KB/s, 138 seconds passed
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 .. parsed-literal::
 
-    ... 66%, 464864 KB, 3360 KB/s, 138 seconds passed
-... 66%, 464896 KB, 3360 KB/s, 138 seconds passed
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+... 65%, 452256 KB, 3672 KB/s, 123 seconds passed
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 .. parsed-literal::
 
-    ... 66%, 465056 KB, 3360 KB/s, 138 seconds passed
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 .. parsed-literal::
 
-    ... 66%, 465248 KB, 3360 KB/s, 138 seconds passed
-... 66%, 465280 KB, 3360 KB/s, 138 seconds passed
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 .. parsed-literal::
 
-    ... 66%, 465408 KB, 3360 KB/s, 138 seconds passed
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 .. parsed-literal::
 
-    ... 66%, 465632 KB, 3360 KB/s, 138 seconds passed
-... 66%, 465664 KB, 3361 KB/s, 138 seconds passed
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 .. parsed-literal::
 
-    ... 66%, 465760 KB, 3361 KB/s, 138 seconds passed
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 .. parsed-literal::
 
-    ... 67%, 466016 KB, 3361 KB/s, 138 seconds passed
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 .. parsed-literal::
 
-    ... 67%, 466144 KB, 3361 KB/s, 138 seconds passed
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 .. parsed-literal::
 
-    ... 67%, 466400 KB, 3361 KB/s, 138 seconds passed
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 .. parsed-literal::
 
-    ... 67%, 466528 KB, 3361 KB/s, 138 seconds passed
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 .. parsed-literal::
 
-    ... 67%, 466784 KB, 3361 KB/s, 138 seconds passed
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 .. parsed-literal::
 
-    ... 67%, 466848 KB, 3361 KB/s, 138 seconds passed
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 .. parsed-literal::
 
-    ... 67%, 467104 KB, 3361 KB/s, 138 seconds passed
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 .. parsed-literal::
 
-    ... 67%, 467232 KB, 3361 KB/s, 138 seconds passed
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 .. parsed-literal::
 
-    ... 67%, 467488 KB, 3361 KB/s, 139 seconds passed
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 .. parsed-literal::
 
-    ... 67%, 467616 KB, 3361 KB/s, 139 seconds passed
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 .. parsed-literal::
 
-    ... 67%, 467872 KB, 3362 KB/s, 139 seconds passed
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 .. parsed-literal::
 
-    ... 67%, 468000 KB, 3362 KB/s, 139 seconds passed
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 .. parsed-literal::
 
-    ... 67%, 468256 KB, 3362 KB/s, 139 seconds passed
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 .. parsed-literal::
 
-    ... 67%, 468384 KB, 3362 KB/s, 139 seconds passed
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 .. parsed-literal::
 
-    ... 67%, 468608 KB, 3362 KB/s, 139 seconds passed
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 .. parsed-literal::
 
-    ... 67%, 468768 KB, 3362 KB/s, 139 seconds passed
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 .. parsed-literal::
 
-    ... 67%, 468992 KB, 3363 KB/s, 139 seconds passed
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 .. parsed-literal::
 
-    ... 67%, 469152 KB, 3362 KB/s, 139 seconds passed
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 .. parsed-literal::
 
-    ... 67%, 469344 KB, 3363 KB/s, 139 seconds passed
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 .. parsed-literal::
 
-    ... 67%, 469504 KB, 3363 KB/s, 139 seconds passed
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 .. parsed-literal::
 
-    ... 67%, 469728 KB, 3363 KB/s, 139 seconds passed
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-... 67%, 469856 KB, 3363 KB/s, 139 seconds passed
+    ... 65%, 456992 KB, 3672 KB/s, 124 seconds passed
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+... 65%, 457088 KB, 3672 KB/s, 124 seconds passed
+... 65%, 457120 KB, 3672 KB/s, 124 seconds passed
 
 .. parsed-literal::
 
-    ... 67%, 469888 KB, 3363 KB/s, 139 seconds passed
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-... 67%, 470080 KB, 3363 KB/s, 139 seconds passed
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+... 65%, 457344 KB, 3672 KB/s, 124 seconds passed
 
 .. parsed-literal::
 
-    ... 67%, 470112 KB, 3363 KB/s, 139 seconds passed
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-... 67%, 470208 KB, 3363 KB/s, 139 seconds passed
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+... 65%, 457504 KB, 3672 KB/s, 124 seconds passed
 
 .. parsed-literal::
 
-    ... 67%, 470272 KB, 3363 KB/s, 139 seconds passed
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-... 67%, 470432 KB, 3363 KB/s, 139 seconds passed
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 .. parsed-literal::
 
-    ... 67%, 470496 KB, 3363 KB/s, 139 seconds passed
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-... 67%, 470624 KB, 3364 KB/s, 139 seconds passed
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 .. parsed-literal::
 
-    ... 67%, 470656 KB, 3363 KB/s, 139 seconds passed
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 .. parsed-literal::
 
-    ... 67%, 470880 KB, 3364 KB/s, 139 seconds passed
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+... 65%, 458240 KB, 3673 KB/s, 124 seconds passed
 
 .. parsed-literal::
 
-    ... 67%, 471040 KB, 3364 KB/s, 140 seconds passed
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+... 65%, 458496 KB, 3673 KB/s, 124 seconds passed
 
 .. parsed-literal::
 
-    ... 67%, 471232 KB, 3364 KB/s, 140 seconds passed
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-... 67%, 471296 KB, 3364 KB/s, 140 seconds passed
-... 67%, 471328 KB, 3364 KB/s, 140 seconds passed
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 .. parsed-literal::
 
-    ... 67%, 471424 KB, 3364 KB/s, 140 seconds passed
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 .. parsed-literal::
 
-    ... 67%, 471616 KB, 3364 KB/s, 140 seconds passed
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-... 67%, 471776 KB, 3364 KB/s, 140 seconds passed
+    ... 65%, 458912 KB, 3672 KB/s, 124 seconds passed
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+... 65%, 459008 KB, 3673 KB/s, 124 seconds passed
 
 .. parsed-literal::
 
-    ... 67%, 471808 KB, 3364 KB/s, 140 seconds passed
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-... 67%, 471936 KB, 3364 KB/s, 140 seconds passed
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 .. parsed-literal::
 
-    ... 67%, 471968 KB, 3364 KB/s, 140 seconds passed
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 .. parsed-literal::
 
-    ... 67%, 472192 KB, 3364 KB/s, 140 seconds passed
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 .. parsed-literal::
 
-    ... 67%, 472352 KB, 3364 KB/s, 140 seconds passed
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 .. parsed-literal::
 
-    ... 67%, 472576 KB, 3364 KB/s, 140 seconds passed
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 .. parsed-literal::
 
-    ... 67%, 472736 KB, 3365 KB/s, 140 seconds passed
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 .. parsed-literal::
 
-    ... 68%, 472960 KB, 3365 KB/s, 140 seconds passed
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 .. parsed-literal::
 
-    ... 68%, 473120 KB, 3365 KB/s, 140 seconds passed
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 .. parsed-literal::
 
-    ... 68%, 473344 KB, 3365 KB/s, 140 seconds passed
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 .. parsed-literal::
 
-    ... 68%, 473472 KB, 3365 KB/s, 140 seconds passed
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 .. parsed-literal::
 
-    ... 68%, 473696 KB, 3365 KB/s, 140 seconds passed
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 .. parsed-literal::
 
-    ... 68%, 473856 KB, 3365 KB/s, 140 seconds passed
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 .. parsed-literal::
 
-    ... 68%, 474016 KB, 3365 KB/s, 140 seconds passed
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 .. parsed-literal::
 
-    ... 68%, 474048 KB, 3364 KB/s, 140 seconds passed
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 .. parsed-literal::
 
-    ... 68%, 474112 KB, 3363 KB/s, 140 seconds passed
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 .. parsed-literal::
 
-    ... 68%, 474144 KB, 3362 KB/s, 140 seconds passed
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 .. parsed-literal::
 
-    ... 68%, 474272 KB, 3362 KB/s, 141 seconds passed
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 .. parsed-literal::
 
-    ... 68%, 474336 KB, 3361 KB/s, 141 seconds passed
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 .. parsed-literal::
 
-    ... 68%, 474496 KB, 3361 KB/s, 141 seconds passed
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 .. parsed-literal::
 
-    ... 68%, 474592 KB, 3361 KB/s, 141 seconds passed
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 .. parsed-literal::
 
-    ... 68%, 474784 KB, 3360 KB/s, 141 seconds passed
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 .. parsed-literal::
 
-    ... 68%, 474912 KB, 3360 KB/s, 141 seconds passed
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 .. parsed-literal::
 
-    ... 68%, 475104 KB, 3361 KB/s, 141 seconds passed
-... 68%, 475136 KB, 3361 KB/s, 141 seconds passed
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-... 68%, 475200 KB, 3361 KB/s, 141 seconds passed
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+... 66%, 463296 KB, 3672 KB/s, 126 seconds passed
+... 66%, 463328 KB, 3673 KB/s, 126 seconds passed
+... 66%, 463360 KB, 3672 KB/s, 126 seconds passed
 
 .. parsed-literal::
 
-    ... 68%, 475296 KB, 3361 KB/s, 141 seconds passed
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 .. parsed-literal::
 
-    ... 68%, 475488 KB, 3361 KB/s, 141 seconds passed
-... 68%, 475520 KB, 3361 KB/s, 141 seconds passed
-... 68%, 475552 KB, 3361 KB/s, 141 seconds passed
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-... 68%, 475648 KB, 3361 KB/s, 141 seconds passed
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+... 66%, 463744 KB, 3672 KB/s, 126 seconds passed
 
 .. parsed-literal::
 
-    ... 68%, 475680 KB, 3361 KB/s, 141 seconds passed
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-... 68%, 475744 KB, 3361 KB/s, 141 seconds passed
-... 68%, 475776 KB, 3361 KB/s, 141 seconds passed
-... 68%, 475808 KB, 3361 KB/s, 141 seconds passed
+    ... 66%, 463776 KB, 3672 KB/s, 126 seconds passed
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+... 66%, 463904 KB, 3672 KB/s, 126 seconds passed
+... 66%, 463936 KB, 3673 KB/s, 126 seconds passed
+... 66%, 463968 KB, 3673 KB/s, 126 seconds passed
 
 .. parsed-literal::
 
-    ... 68%, 475840 KB, 3361 KB/s, 141 seconds passed
-... 68%, 475872 KB, 3361 KB/s, 141 seconds passed
-... 68%, 475904 KB, 3361 KB/s, 141 seconds passed
-... 68%, 475936 KB, 3361 KB/s, 141 seconds passed
-... 68%, 475968 KB, 3361 KB/s, 141 seconds passed
-... 68%, 476000 KB, 3361 KB/s, 141 seconds passed
+    ... 66%, 464000 KB, 3672 KB/s, 126 seconds passed
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+... 66%, 464064 KB, 3673 KB/s, 126 seconds passed
+... 66%, 464096 KB, 3673 KB/s, 126 seconds passed
+... 66%, 464128 KB, 3672 KB/s, 126 seconds passed
 
 .. parsed-literal::
 
-    ... 68%, 476032 KB, 3361 KB/s, 141 seconds passed
-... 68%, 476064 KB, 3361 KB/s, 141 seconds passed
-... 68%, 476096 KB, 3361 KB/s, 141 seconds passed
-... 68%, 476128 KB, 3361 KB/s, 141 seconds passed
-... 68%, 476160 KB, 3361 KB/s, 141 seconds passed
-... 68%, 476192 KB, 3361 KB/s, 141 seconds passed
+    ... 66%, 464160 KB, 3672 KB/s, 126 seconds passed
+... 66%, 464192 KB, 3673 KB/s, 126 seconds passed
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+... 66%, 464256 KB, 3672 KB/s, 126 seconds passed
+... 66%, 464288 KB, 3672 KB/s, 126 seconds passed
+... 66%, 464320 KB, 3673 KB/s, 126 seconds passed
+... 66%, 464352 KB, 3673 KB/s, 126 seconds passed
 
 .. parsed-literal::
 
-    ... 68%, 476224 KB, 3361 KB/s, 141 seconds passed
-... 68%, 476256 KB, 3361 KB/s, 141 seconds passed
-... 68%, 476288 KB, 3361 KB/s, 141 seconds passed
-... 68%, 476320 KB, 3361 KB/s, 141 seconds passed
-... 68%, 476352 KB, 3361 KB/s, 141 seconds passed
-... 68%, 476384 KB, 3362 KB/s, 141 seconds passed
+    ... 66%, 464384 KB, 3672 KB/s, 126 seconds passed
+... 66%, 464416 KB, 3672 KB/s, 126 seconds passed
+... 66%, 464448 KB, 3673 KB/s, 126 seconds passed
+... 66%, 464480 KB, 3673 KB/s, 126 seconds passed
 
 .. parsed-literal::
 
-    ... 68%, 476416 KB, 3361 KB/s, 141 seconds passed
-... 68%, 476448 KB, 3361 KB/s, 141 seconds passed
-... 68%, 476480 KB, 3361 KB/s, 141 seconds passed
-... 68%, 476512 KB, 3362 KB/s, 141 seconds passed
-... 68%, 476544 KB, 3361 KB/s, 141 seconds passed
-... 68%, 476576 KB, 3361 KB/s, 141 seconds passed
+    ... 66%, 464512 KB, 3672 KB/s, 126 seconds passed
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+... 66%, 464640 KB, 3672 KB/s, 126 seconds passed
+... 66%, 464672 KB, 3672 KB/s, 126 seconds passed
+... 66%, 464704 KB, 3673 KB/s, 126 seconds passed
 
 .. parsed-literal::
 
-    ... 68%, 476608 KB, 3362 KB/s, 141 seconds passed
-... 68%, 476640 KB, 3362 KB/s, 141 seconds passed
-... 68%, 476672 KB, 3361 KB/s, 141 seconds passed
-... 68%, 476704 KB, 3361 KB/s, 141 seconds passed
-... 68%, 476736 KB, 3362 KB/s, 141 seconds passed
-... 68%, 476768 KB, 3362 KB/s, 141 seconds passed
+    ... 66%, 464736 KB, 3673 KB/s, 126 seconds passed
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+... 66%, 464800 KB, 3672 KB/s, 126 seconds passed
+... 66%, 464832 KB, 3673 KB/s, 126 seconds passed
+... 66%, 464864 KB, 3673 KB/s, 126 seconds passed
 
 .. parsed-literal::
 
-    ... 68%, 476800 KB, 3361 KB/s, 141 seconds passed
-... 68%, 476832 KB, 3362 KB/s, 141 seconds passed
-... 68%, 476864 KB, 3362 KB/s, 141 seconds passed
-... 68%, 476896 KB, 3362 KB/s, 141 seconds passed
-... 68%, 476928 KB, 3361 KB/s, 141 seconds passed
+    ... 66%, 464896 KB, 3673 KB/s, 126 seconds passed
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+... 66%, 464992 KB, 3673 KB/s, 126 seconds passed
+... 66%, 465024 KB, 3673 KB/s, 126 seconds passed
+... 66%, 465056 KB, 3672 KB/s, 126 seconds passed
 
 .. parsed-literal::
 
-    ... 68%, 476960 KB, 3362 KB/s, 141 seconds passed
-... 68%, 476992 KB, 3362 KB/s, 141 seconds passed
-... 68%, 477024 KB, 3362 KB/s, 141 seconds passed
-... 68%, 477056 KB, 3362 KB/s, 141 seconds passed
-... 68%, 477088 KB, 3362 KB/s, 141 seconds passed
-... 68%, 477120 KB, 3362 KB/s, 141 seconds passed
-... 68%, 477152 KB, 3362 KB/s, 141 seconds passed
+    ... 66%, 465088 KB, 3673 KB/s, 126 seconds passed
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+... 66%, 465184 KB, 3672 KB/s, 126 seconds passed
+... 66%, 465216 KB, 3673 KB/s, 126 seconds passed
+... 66%, 465248 KB, 3672 KB/s, 126 seconds passed
 
 .. parsed-literal::
 
-    ... 68%, 477184 KB, 3362 KB/s, 141 seconds passed
-... 68%, 477216 KB, 3362 KB/s, 141 seconds passed
-... 68%, 477248 KB, 3362 KB/s, 141 seconds passed
-... 68%, 477280 KB, 3362 KB/s, 141 seconds passed
-... 68%, 477312 KB, 3362 KB/s, 141 seconds passed
+    ... 66%, 465280 KB, 3673 KB/s, 126 seconds passed
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+... 66%, 465376 KB, 3672 KB/s, 126 seconds passed
+... 66%, 465408 KB, 3673 KB/s, 126 seconds passed
+... 66%, 465440 KB, 3672 KB/s, 126 seconds passed
 
 .. parsed-literal::
 
-    ... 68%, 477344 KB, 3362 KB/s, 141 seconds passed
-... 68%, 477376 KB, 3362 KB/s, 141 seconds passed
-... 68%, 477408 KB, 3362 KB/s, 141 seconds passed
-... 68%, 477440 KB, 3362 KB/s, 141 seconds passed
-... 68%, 477472 KB, 3362 KB/s, 142 seconds passed
-... 68%, 477504 KB, 3362 KB/s, 142 seconds passed
-... 68%, 477536 KB, 3362 KB/s, 142 seconds passed
+    ... 66%, 465472 KB, 3673 KB/s, 126 seconds passed
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+... 66%, 465536 KB, 3673 KB/s, 126 seconds passed
+... 66%, 465568 KB, 3672 KB/s, 126 seconds passed
+... 66%, 465600 KB, 3673 KB/s, 126 seconds passed
 
 .. parsed-literal::
 
-    ... 68%, 477568 KB, 3362 KB/s, 142 seconds passed
-... 68%, 477600 KB, 3362 KB/s, 142 seconds passed
-... 68%, 477632 KB, 3362 KB/s, 142 seconds passed
-... 68%, 477664 KB, 3362 KB/s, 142 seconds passed
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+... 66%, 465760 KB, 3673 KB/s, 126 seconds passed
+... 66%, 465792 KB, 3673 KB/s, 126 seconds passed
+... 66%, 465824 KB, 3673 KB/s, 126 seconds passed
 
 .. parsed-literal::
 
-    ... 68%, 477696 KB, 3362 KB/s, 142 seconds passed
-... 68%, 477728 KB, 3362 KB/s, 142 seconds passed
-... 68%, 477760 KB, 3362 KB/s, 142 seconds passed
-... 68%, 477792 KB, 3362 KB/s, 142 seconds passed
-... 68%, 477824 KB, 3362 KB/s, 142 seconds passed
-... 68%, 477856 KB, 3362 KB/s, 142 seconds passed
-... 68%, 477888 KB, 3362 KB/s, 142 seconds passed
-... 68%, 477920 KB, 3362 KB/s, 142 seconds passed
+    ... 66%, 465856 KB, 3673 KB/s, 126 seconds passed
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+... 66%, 465952 KB, 3672 KB/s, 126 seconds passed
+... 66%, 465984 KB, 3673 KB/s, 126 seconds passed
 
 .. parsed-literal::
 
-    ... 68%, 477952 KB, 3362 KB/s, 142 seconds passed
-... 68%, 477984 KB, 3362 KB/s, 142 seconds passed
-... 68%, 478016 KB, 3362 KB/s, 142 seconds passed
-... 68%, 478048 KB, 3363 KB/s, 142 seconds passed
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+... 67%, 466176 KB, 3672 KB/s, 126 seconds passed
 
 .. parsed-literal::
 
-    ... 68%, 478080 KB, 3362 KB/s, 142 seconds passed
-... 68%, 478112 KB, 3362 KB/s, 142 seconds passed
-... 68%, 478144 KB, 3363 KB/s, 142 seconds passed
-... 68%, 478176 KB, 3363 KB/s, 142 seconds passed
-... 68%, 478208 KB, 3362 KB/s, 142 seconds passed
-... 68%, 478240 KB, 3362 KB/s, 142 seconds passed
-... 68%, 478272 KB, 3363 KB/s, 142 seconds passed
-... 68%, 478304 KB, 3363 KB/s, 142 seconds passed
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+... 67%, 466304 KB, 3672 KB/s, 126 seconds passed
+... 67%, 466336 KB, 3673 KB/s, 126 seconds passed
+... 67%, 466368 KB, 3673 KB/s, 126 seconds passed
 
 .. parsed-literal::
 
-    ... 68%, 478336 KB, 3362 KB/s, 142 seconds passed
-... 68%, 478368 KB, 3362 KB/s, 142 seconds passed
-... 68%, 478400 KB, 3363 KB/s, 142 seconds passed
-... 68%, 478432 KB, 3363 KB/s, 142 seconds passed
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 .. parsed-literal::
 
-    ... 68%, 478464 KB, 3362 KB/s, 142 seconds passed
-... 68%, 478496 KB, 3363 KB/s, 142 seconds passed
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-... 68%, 478624 KB, 3363 KB/s, 142 seconds passed
-... 68%, 478656 KB, 3363 KB/s, 142 seconds passed
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+... 67%, 466720 KB, 3673 KB/s, 127 seconds passed
+... 67%, 466752 KB, 3673 KB/s, 127 seconds passed
 
 .. parsed-literal::
 
-    ... 68%, 478720 KB, 3363 KB/s, 142 seconds passed
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+... 67%, 466912 KB, 3672 KB/s, 127 seconds passed
+... 67%, 466944 KB, 3672 KB/s, 127 seconds passed
 
 .. parsed-literal::
 
-    ... 68%, 478848 KB, 3362 KB/s, 142 seconds passed
-... 68%, 478880 KB, 3362 KB/s, 142 seconds passed
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-... 68%, 478944 KB, 3363 KB/s, 142 seconds passed
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+... 67%, 467104 KB, 3673 KB/s, 127 seconds passed
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 .. parsed-literal::
 
-    ... 68%, 478976 KB, 3361 KB/s, 142 seconds passed
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 .. parsed-literal::
 
-    ... 68%, 479040 KB, 3360 KB/s, 142 seconds passed
+    ... 67%, 467360 KB, 3673 KB/s, 127 seconds passed
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+... 67%, 467520 KB, 3673 KB/s, 127 seconds passed
 
 .. parsed-literal::
 
-    ... 68%, 479072 KB, 3359 KB/s, 142 seconds passed
-... 68%, 479104 KB, 3359 KB/s, 142 seconds passed
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 .. parsed-literal::
 
-    ... 68%, 479136 KB, 3358 KB/s, 142 seconds passed
-... 68%, 479168 KB, 3358 KB/s, 142 seconds passed
+    ... 67%, 467744 KB, 3673 KB/s, 127 seconds passed
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 .. parsed-literal::
 
-    ... 68%, 479200 KB, 3358 KB/s, 142 seconds passed
-... 68%, 479232 KB, 3358 KB/s, 142 seconds passed
-... 68%, 479264 KB, 3358 KB/s, 142 seconds passed
+    ... 67%, 467936 KB, 3673 KB/s, 127 seconds passed
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 .. parsed-literal::
 
-    ... 68%, 479296 KB, 3357 KB/s, 142 seconds passed
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+    ... 67%, 468096 KB, 3673 KB/s, 127 seconds passed
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 .. parsed-literal::
 
-    ... 68%, 479360 KB, 3357 KB/s, 142 seconds passed
-... 68%, 479392 KB, 3357 KB/s, 142 seconds passed
-... 68%, 479424 KB, 3356 KB/s, 142 seconds passed
-... 68%, 479456 KB, 3356 KB/s, 142 seconds passed
-... 68%, 479488 KB, 3357 KB/s, 142 seconds passed
+    ... 67%, 468320 KB, 3673 KB/s, 127 seconds passed
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 .. parsed-literal::
 
-    ... 68%, 479520 KB, 3356 KB/s, 142 seconds passed
-... 68%, 479552 KB, 3356 KB/s, 142 seconds passed
+    ... 67%, 468480 KB, 3673 KB/s, 127 seconds passed
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 .. parsed-literal::
 
-    ... 68%, 479584 KB, 3356 KB/s, 142 seconds passed
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-... 68%, 479648 KB, 3355 KB/s, 142 seconds passed
-... 68%, 479680 KB, 3356 KB/s, 142 seconds passed
-... 68%, 479712 KB, 3356 KB/s, 142 seconds passed
+    ... 67%, 468704 KB, 3673 KB/s, 127 seconds passed
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 .. parsed-literal::
 
-    ... 68%, 479744 KB, 3355 KB/s, 142 seconds passed
-... 68%, 479776 KB, 3355 KB/s, 142 seconds passed
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+    ... 67%, 468864 KB, 3673 KB/s, 127 seconds passed
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 .. parsed-literal::
 
-    ... 68%, 479840 KB, 3355 KB/s, 142 seconds passed
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-... 69%, 480000 KB, 3355 KB/s, 143 seconds passed
+    ... 67%, 469088 KB, 3673 KB/s, 127 seconds passed
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 .. parsed-literal::
 
-    ... 69%, 480032 KB, 3355 KB/s, 143 seconds passed
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-... 69%, 480096 KB, 3355 KB/s, 143 seconds passed
+    ... 67%, 469248 KB, 3673 KB/s, 127 seconds passed
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+... 67%, 469376 KB, 3673 KB/s, 127 seconds passed
+... 67%, 469408 KB, 3673 KB/s, 127 seconds passed
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 .. parsed-literal::
 
-    ... 69%, 480128 KB, 3355 KB/s, 143 seconds passed
-... 69%, 480160 KB, 3355 KB/s, 143 seconds passed
-... 69%, 480192 KB, 3355 KB/s, 143 seconds passed
-... 69%, 480224 KB, 3355 KB/s, 143 seconds passed
-... 69%, 480256 KB, 3355 KB/s, 143 seconds passed
-... 69%, 480288 KB, 3355 KB/s, 143 seconds passed
-... 69%, 480320 KB, 3355 KB/s, 143 seconds passed
+    ... 67%, 469472 KB, 3673 KB/s, 127 seconds passed
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+... 67%, 469568 KB, 3673 KB/s, 127 seconds passed
+... 67%, 469600 KB, 3673 KB/s, 127 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 480352 KB, 3355 KB/s, 143 seconds passed
-... 69%, 480384 KB, 3355 KB/s, 143 seconds passed
-... 69%, 480416 KB, 3355 KB/s, 143 seconds passed
-... 69%, 480448 KB, 3355 KB/s, 143 seconds passed
+    ... 67%, 469632 KB, 3673 KB/s, 127 seconds passed
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 .. parsed-literal::
 
-    ... 69%, 480480 KB, 3355 KB/s, 143 seconds passed
-... 69%, 480512 KB, 3355 KB/s, 143 seconds passed
-... 69%, 480544 KB, 3355 KB/s, 143 seconds passed
-... 69%, 480576 KB, 3355 KB/s, 143 seconds passed
-... 69%, 480608 KB, 3355 KB/s, 143 seconds passed
-... 69%, 480640 KB, 3355 KB/s, 143 seconds passed
-... 69%, 480672 KB, 3355 KB/s, 143 seconds passed
+    ... 67%, 469856 KB, 3673 KB/s, 127 seconds passed
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+... 67%, 469920 KB, 3673 KB/s, 127 seconds passed
+... 67%, 469952 KB, 3673 KB/s, 127 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 480704 KB, 3355 KB/s, 143 seconds passed
-... 69%, 480736 KB, 3355 KB/s, 143 seconds passed
-... 69%, 480768 KB, 3355 KB/s, 143 seconds passed
-... 69%, 480800 KB, 3355 KB/s, 143 seconds passed
-... 69%, 480832 KB, 3355 KB/s, 143 seconds passed
+    ... 67%, 469984 KB, 3672 KB/s, 127 seconds passed
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+... 67%, 470112 KB, 3672 KB/s, 127 seconds passed
+... 67%, 470144 KB, 3673 KB/s, 127 seconds passed
+... 67%, 470176 KB, 3673 KB/s, 127 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 480864 KB, 3355 KB/s, 143 seconds passed
-... 69%, 480896 KB, 3355 KB/s, 143 seconds passed
-... 69%, 480928 KB, 3355 KB/s, 143 seconds passed
-... 69%, 480960 KB, 3355 KB/s, 143 seconds passed
-... 69%, 480992 KB, 3355 KB/s, 143 seconds passed
-... 69%, 481024 KB, 3355 KB/s, 143 seconds passed
-... 69%, 481056 KB, 3355 KB/s, 143 seconds passed
+    ... 67%, 470208 KB, 3673 KB/s, 128 seconds passed
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+... 67%, 470272 KB, 3673 KB/s, 128 seconds passed
+... 67%, 470304 KB, 3673 KB/s, 128 seconds passed
+... 67%, 470336 KB, 3673 KB/s, 128 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 481088 KB, 3355 KB/s, 143 seconds passed
-... 69%, 481120 KB, 3355 KB/s, 143 seconds passed
-... 69%, 481152 KB, 3355 KB/s, 143 seconds passed
-... 69%, 481184 KB, 3355 KB/s, 143 seconds passed
-... 69%, 481216 KB, 3356 KB/s, 143 seconds passed
+    ... 67%, 470368 KB, 3673 KB/s, 128 seconds passed
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+... 67%, 470496 KB, 3673 KB/s, 128 seconds passed
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+... 67%, 470560 KB, 3673 KB/s, 128 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 481248 KB, 3355 KB/s, 143 seconds passed
-... 69%, 481280 KB, 3355 KB/s, 143 seconds passed
-... 69%, 481312 KB, 3356 KB/s, 143 seconds passed
-... 69%, 481344 KB, 3356 KB/s, 143 seconds passed
-... 69%, 481376 KB, 3355 KB/s, 143 seconds passed
-... 69%, 481408 KB, 3355 KB/s, 143 seconds passed
-... 69%, 481440 KB, 3356 KB/s, 143 seconds passed
+    ... 67%, 470592 KB, 3673 KB/s, 128 seconds passed
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+... 67%, 470720 KB, 3673 KB/s, 128 seconds passed
+... 67%, 470752 KB, 3673 KB/s, 128 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 481472 KB, 3356 KB/s, 143 seconds passed
-... 69%, 481504 KB, 3355 KB/s, 143 seconds passed
-... 69%, 481536 KB, 3356 KB/s, 143 seconds passed
-... 69%, 481568 KB, 3356 KB/s, 143 seconds passed
-... 69%, 481600 KB, 3356 KB/s, 143 seconds passed
+    ... 67%, 470784 KB, 3673 KB/s, 128 seconds passed
+... 67%, 470816 KB, 3673 KB/s, 128 seconds passed
+... 67%, 470848 KB, 3673 KB/s, 128 seconds passed
+... 67%, 470880 KB, 3673 KB/s, 128 seconds passed
+... 67%, 470912 KB, 3673 KB/s, 128 seconds passed
+... 67%, 470944 KB, 3673 KB/s, 128 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 481632 KB, 3355 KB/s, 143 seconds passed
-... 69%, 481664 KB, 3356 KB/s, 143 seconds passed
-... 69%, 481696 KB, 3356 KB/s, 143 seconds passed
-... 69%, 481728 KB, 3356 KB/s, 143 seconds passed
-... 69%, 481760 KB, 3356 KB/s, 143 seconds passed
-... 69%, 481792 KB, 3356 KB/s, 143 seconds passed
+    ... 67%, 470976 KB, 3673 KB/s, 128 seconds passed
+... 67%, 471008 KB, 3673 KB/s, 128 seconds passed
+... 67%, 471040 KB, 3673 KB/s, 128 seconds passed
+... 67%, 471072 KB, 3673 KB/s, 128 seconds passed
+... 67%, 471104 KB, 3673 KB/s, 128 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 481824 KB, 3356 KB/s, 143 seconds passed
-... 69%, 481856 KB, 3356 KB/s, 143 seconds passed
-... 69%, 481888 KB, 3356 KB/s, 143 seconds passed
-... 69%, 481920 KB, 3356 KB/s, 143 seconds passed
-... 69%, 481952 KB, 3356 KB/s, 143 seconds passed
-... 69%, 481984 KB, 3356 KB/s, 143 seconds passed
+    ... 67%, 471136 KB, 3673 KB/s, 128 seconds passed
+... 67%, 471168 KB, 3673 KB/s, 128 seconds passed
+... 67%, 471200 KB, 3673 KB/s, 128 seconds passed
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+... 67%, 471264 KB, 3673 KB/s, 128 seconds passed
+... 67%, 471296 KB, 3673 KB/s, 128 seconds passed
+... 67%, 471328 KB, 3673 KB/s, 128 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 482016 KB, 3356 KB/s, 143 seconds passed
-... 69%, 482048 KB, 3356 KB/s, 143 seconds passed
-... 69%, 482080 KB, 3356 KB/s, 143 seconds passed
-... 69%, 482112 KB, 3356 KB/s, 143 seconds passed
-... 69%, 482144 KB, 3356 KB/s, 143 seconds passed
-... 69%, 482176 KB, 3356 KB/s, 143 seconds passed
+    ... 67%, 471360 KB, 3673 KB/s, 128 seconds passed
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+... 67%, 471424 KB, 3673 KB/s, 128 seconds passed
+... 67%, 471456 KB, 3673 KB/s, 128 seconds passed
+... 67%, 471488 KB, 3673 KB/s, 128 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 482208 KB, 3356 KB/s, 143 seconds passed
-... 69%, 482240 KB, 3356 KB/s, 143 seconds passed
-... 69%, 482272 KB, 3356 KB/s, 143 seconds passed
-... 69%, 482304 KB, 3356 KB/s, 143 seconds passed
-... 69%, 482336 KB, 3356 KB/s, 143 seconds passed
-... 69%, 482368 KB, 3356 KB/s, 143 seconds passed
+    ... 67%, 471520 KB, 3673 KB/s, 128 seconds passed
+... 67%, 471552 KB, 3673 KB/s, 128 seconds passed
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+... 67%, 471648 KB, 3673 KB/s, 128 seconds passed
+... 67%, 471680 KB, 3673 KB/s, 128 seconds passed
+... 67%, 471712 KB, 3673 KB/s, 128 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 482400 KB, 3356 KB/s, 143 seconds passed
-... 69%, 482432 KB, 3356 KB/s, 143 seconds passed
-... 69%, 482464 KB, 3356 KB/s, 143 seconds passed
-... 69%, 482496 KB, 3356 KB/s, 143 seconds passed
-... 69%, 482528 KB, 3356 KB/s, 143 seconds passed
-... 69%, 482560 KB, 3356 KB/s, 143 seconds passed
+    ... 67%, 471744 KB, 3673 KB/s, 128 seconds passed
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+... 67%, 471808 KB, 3673 KB/s, 128 seconds passed
+... 67%, 471840 KB, 3673 KB/s, 128 seconds passed
+... 67%, 471872 KB, 3673 KB/s, 128 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 482592 KB, 3356 KB/s, 143 seconds passed
-... 69%, 482624 KB, 3356 KB/s, 143 seconds passed
-... 69%, 482656 KB, 3356 KB/s, 143 seconds passed
-... 69%, 482688 KB, 3356 KB/s, 143 seconds passed
-... 69%, 482720 KB, 3356 KB/s, 143 seconds passed
-... 69%, 482752 KB, 3357 KB/s, 143 seconds passed
+    ... 67%, 471904 KB, 3673 KB/s, 128 seconds passed
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+... 67%, 472000 KB, 3673 KB/s, 128 seconds passed
+... 67%, 472032 KB, 3673 KB/s, 128 seconds passed
+... 67%, 472064 KB, 3673 KB/s, 128 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 482784 KB, 3356 KB/s, 143 seconds passed
-... 69%, 482816 KB, 3356 KB/s, 143 seconds passed
-... 69%, 482848 KB, 3356 KB/s, 143 seconds passed
-... 69%, 482880 KB, 3357 KB/s, 143 seconds passed
-... 69%, 482912 KB, 3356 KB/s, 143 seconds passed
+    ... 67%, 472096 KB, 3673 KB/s, 128 seconds passed
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+... 67%, 472160 KB, 3673 KB/s, 128 seconds passed
+... 67%, 472192 KB, 3673 KB/s, 128 seconds passed
+... 67%, 472224 KB, 3673 KB/s, 128 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 482944 KB, 3356 KB/s, 143 seconds passed
-... 69%, 482976 KB, 3357 KB/s, 143 seconds passed
-... 69%, 483008 KB, 3356 KB/s, 143 seconds passed
-... 69%, 483040 KB, 3356 KB/s, 143 seconds passed
-... 69%, 483072 KB, 3356 KB/s, 143 seconds passed
+    ... 67%, 472256 KB, 3673 KB/s, 128 seconds passed
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+... 67%, 472352 KB, 3673 KB/s, 128 seconds passed
+... 67%, 472384 KB, 3673 KB/s, 128 seconds passed
+... 67%, 472416 KB, 3673 KB/s, 128 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 483104 KB, 3356 KB/s, 143 seconds passed
-... 69%, 483136 KB, 3356 KB/s, 143 seconds passed
-... 69%, 483168 KB, 3356 KB/s, 143 seconds passed
-... 69%, 483200 KB, 3356 KB/s, 143 seconds passed
-... 69%, 483232 KB, 3356 KB/s, 143 seconds passed
-... 69%, 483264 KB, 3356 KB/s, 143 seconds passed
-... 69%, 483296 KB, 3357 KB/s, 143 seconds passed
+    ... 67%, 472448 KB, 3673 KB/s, 128 seconds passed
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+... 67%, 472544 KB, 3673 KB/s, 128 seconds passed
+... 67%, 472576 KB, 3673 KB/s, 128 seconds passed
+... 67%, 472608 KB, 3673 KB/s, 128 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 483328 KB, 3357 KB/s, 143 seconds passed
-... 69%, 483360 KB, 3356 KB/s, 143 seconds passed
-... 69%, 483392 KB, 3356 KB/s, 143 seconds passed
-... 69%, 483424 KB, 3357 KB/s, 144 seconds passed
-... 69%, 483456 KB, 3357 KB/s, 144 seconds passed
+    ... 67%, 472640 KB, 3673 KB/s, 128 seconds passed
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+... 67%, 472704 KB, 3673 KB/s, 128 seconds passed
+... 67%, 472736 KB, 3673 KB/s, 128 seconds passed
+... 67%, 472768 KB, 3673 KB/s, 128 seconds passed
+... 67%, 472800 KB, 3673 KB/s, 128 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 483488 KB, 3356 KB/s, 144 seconds passed
-... 69%, 483520 KB, 3357 KB/s, 144 seconds passed
-... 69%, 483552 KB, 3357 KB/s, 144 seconds passed
-... 69%, 483584 KB, 3357 KB/s, 144 seconds passed
-... 69%, 483616 KB, 3356 KB/s, 144 seconds passed
-... 69%, 483648 KB, 3357 KB/s, 144 seconds passed
+    ... 67%, 472832 KB, 3673 KB/s, 128 seconds passed
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+... 67%, 472896 KB, 3673 KB/s, 128 seconds passed
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+... 68%, 472960 KB, 3673 KB/s, 128 seconds passed
+... 68%, 472992 KB, 3673 KB/s, 128 seconds passed
+... 68%, 473024 KB, 3673 KB/s, 128 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 483680 KB, 3357 KB/s, 144 seconds passed
-... 69%, 483712 KB, 3357 KB/s, 144 seconds passed
-... 69%, 483744 KB, 3357 KB/s, 144 seconds passed
-... 69%, 483776 KB, 3357 KB/s, 144 seconds passed
-... 69%, 483808 KB, 3357 KB/s, 144 seconds passed
-... 69%, 483840 KB, 3357 KB/s, 144 seconds passed
+    ... 68%, 473056 KB, 3673 KB/s, 128 seconds passed
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+... 68%, 473152 KB, 3673 KB/s, 128 seconds passed
+... 68%, 473184 KB, 3673 KB/s, 128 seconds passed
+... 68%, 473216 KB, 3673 KB/s, 128 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 483872 KB, 3357 KB/s, 144 seconds passed
-... 69%, 483904 KB, 3357 KB/s, 144 seconds passed
-... 69%, 483936 KB, 3357 KB/s, 144 seconds passed
-... 69%, 483968 KB, 3357 KB/s, 144 seconds passed
-... 69%, 484000 KB, 3357 KB/s, 144 seconds passed
+    ... 68%, 473248 KB, 3673 KB/s, 128 seconds passed
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+... 68%, 473312 KB, 3673 KB/s, 128 seconds passed
+... 68%, 473344 KB, 3673 KB/s, 128 seconds passed
+... 68%, 473376 KB, 3673 KB/s, 128 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 484032 KB, 3357 KB/s, 144 seconds passed
-... 69%, 484064 KB, 3357 KB/s, 144 seconds passed
-... 69%, 484096 KB, 3357 KB/s, 144 seconds passed
-... 69%, 484128 KB, 3357 KB/s, 144 seconds passed
+    ... 68%, 473408 KB, 3673 KB/s, 128 seconds passed
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+... 68%, 473504 KB, 3673 KB/s, 128 seconds passed
+... 68%, 473536 KB, 3673 KB/s, 128 seconds passed
+... 68%, 473568 KB, 3673 KB/s, 128 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 484160 KB, 3356 KB/s, 144 seconds passed
-... 69%, 484192 KB, 3356 KB/s, 144 seconds passed
-... 69%, 484224 KB, 3357 KB/s, 144 seconds passed
-... 69%, 484256 KB, 3357 KB/s, 144 seconds passed
+    ... 68%, 473600 KB, 3673 KB/s, 128 seconds passed
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+... 68%, 473696 KB, 3673 KB/s, 128 seconds passed
+... 68%, 473728 KB, 3673 KB/s, 128 seconds passed
+... 68%, 473760 KB, 3673 KB/s, 128 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 484288 KB, 3356 KB/s, 144 seconds passed
+    ... 68%, 473792 KB, 3673 KB/s, 128 seconds passed
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+... 68%, 473856 KB, 3673 KB/s, 129 seconds passed
+... 68%, 473888 KB, 3673 KB/s, 129 seconds passed
+... 68%, 473920 KB, 3673 KB/s, 129 seconds passed
+... 68%, 473952 KB, 3673 KB/s, 129 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 484320 KB, 3355 KB/s, 144 seconds passed
+    ... 68%, 473984 KB, 3673 KB/s, 129 seconds passed
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+... 68%, 474080 KB, 3673 KB/s, 129 seconds passed
+... 68%, 474112 KB, 3673 KB/s, 129 seconds passed
+... 68%, 474144 KB, 3673 KB/s, 129 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 484352 KB, 3354 KB/s, 144 seconds passed
-... 69%, 484384 KB, 3354 KB/s, 144 seconds passed
-... 69%, 484416 KB, 3354 KB/s, 144 seconds passed
+    ... 68%, 474176 KB, 3673 KB/s, 129 seconds passed
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+... 68%, 474272 KB, 3673 KB/s, 129 seconds passed
+... 68%, 474304 KB, 3673 KB/s, 129 seconds passed
+... 68%, 474336 KB, 3673 KB/s, 129 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 484448 KB, 3353 KB/s, 144 seconds passed
+    ... 68%, 474368 KB, 3673 KB/s, 129 seconds passed
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+... 68%, 474464 KB, 3673 KB/s, 129 seconds passed
+... 68%, 474496 KB, 3673 KB/s, 129 seconds passed
+... 68%, 474528 KB, 3673 KB/s, 129 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 484480 KB, 3353 KB/s, 144 seconds passed
-... 69%, 484512 KB, 3352 KB/s, 144 seconds passed
-... 69%, 484544 KB, 3352 KB/s, 144 seconds passed
+    ... 68%, 474560 KB, 3673 KB/s, 129 seconds passed
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+... 68%, 474656 KB, 3673 KB/s, 129 seconds passed
+... 68%, 474688 KB, 3673 KB/s, 129 seconds passed
+... 68%, 474720 KB, 3673 KB/s, 129 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 484576 KB, 3352 KB/s, 144 seconds passed
-... 69%, 484608 KB, 3352 KB/s, 144 seconds passed
+    ... 68%, 474752 KB, 3673 KB/s, 129 seconds passed
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+... 68%, 474880 KB, 3673 KB/s, 129 seconds passed
+... 68%, 474912 KB, 3673 KB/s, 129 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 484640 KB, 3351 KB/s, 144 seconds passed
-... 69%, 484672 KB, 3351 KB/s, 144 seconds passed
-... 69%, 484704 KB, 3351 KB/s, 144 seconds passed
+    ... 68%, 474944 KB, 3673 KB/s, 129 seconds passed
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+... 68%, 475072 KB, 3673 KB/s, 129 seconds passed
+... 68%, 475104 KB, 3673 KB/s, 129 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 484736 KB, 3351 KB/s, 144 seconds passed
-... 69%, 484768 KB, 3351 KB/s, 144 seconds passed
+    ... 68%, 475136 KB, 3673 KB/s, 129 seconds passed
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+... 68%, 475200 KB, 3673 KB/s, 129 seconds passed
+... 68%, 475232 KB, 3673 KB/s, 129 seconds passed
+... 68%, 475264 KB, 3673 KB/s, 129 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 484800 KB, 3350 KB/s, 144 seconds passed
-... 69%, 484832 KB, 3350 KB/s, 144 seconds passed
-... 69%, 484864 KB, 3350 KB/s, 144 seconds passed
-... 69%, 484896 KB, 3350 KB/s, 144 seconds passed
+    ... 68%, 475296 KB, 3673 KB/s, 129 seconds passed
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+... 68%, 475392 KB, 3673 KB/s, 129 seconds passed
+... 68%, 475424 KB, 3673 KB/s, 129 seconds passed
+... 68%, 475456 KB, 3673 KB/s, 129 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 484928 KB, 3349 KB/s, 144 seconds passed
-... 69%, 484960 KB, 3350 KB/s, 144 seconds passed
-... 69%, 484992 KB, 3350 KB/s, 144 seconds passed
+    ... 68%, 475488 KB, 3673 KB/s, 129 seconds passed
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+... 68%, 475616 KB, 3673 KB/s, 129 seconds passed
+... 68%, 475648 KB, 3673 KB/s, 129 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 485024 KB, 3349 KB/s, 144 seconds passed
-... 69%, 485056 KB, 3349 KB/s, 144 seconds passed
-... 69%, 485088 KB, 3349 KB/s, 144 seconds passed
-... 69%, 485120 KB, 3349 KB/s, 144 seconds passed
-... 69%, 485152 KB, 3349 KB/s, 144 seconds passed
+    ... 68%, 475680 KB, 3673 KB/s, 129 seconds passed
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+... 68%, 475776 KB, 3673 KB/s, 129 seconds passed
+... 68%, 475808 KB, 3673 KB/s, 129 seconds passed
+... 68%, 475840 KB, 3673 KB/s, 129 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 485184 KB, 3349 KB/s, 144 seconds passed
-... 69%, 485216 KB, 3349 KB/s, 144 seconds passed
-... 69%, 485248 KB, 3349 KB/s, 144 seconds passed
+    ... 68%, 475872 KB, 3673 KB/s, 129 seconds passed
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+... 68%, 476000 KB, 3673 KB/s, 129 seconds passed
+... 68%, 476032 KB, 3673 KB/s, 129 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 485280 KB, 3349 KB/s, 144 seconds passed
-... 69%, 485312 KB, 3349 KB/s, 144 seconds passed
-... 69%, 485344 KB, 3349 KB/s, 144 seconds passed
-... 69%, 485376 KB, 3349 KB/s, 144 seconds passed
-... 69%, 485408 KB, 3349 KB/s, 144 seconds passed
-... 69%, 485440 KB, 3349 KB/s, 144 seconds passed
+    ... 68%, 476064 KB, 3673 KB/s, 129 seconds passed
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+... 68%, 476160 KB, 3673 KB/s, 129 seconds passed
+... 68%, 476192 KB, 3673 KB/s, 129 seconds passed
+... 68%, 476224 KB, 3673 KB/s, 129 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 485472 KB, 3348 KB/s, 144 seconds passed
-... 69%, 485504 KB, 3349 KB/s, 144 seconds passed
-... 69%, 485536 KB, 3349 KB/s, 144 seconds passed
+    ... 68%, 476256 KB, 3673 KB/s, 129 seconds passed
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+... 68%, 476352 KB, 3673 KB/s, 129 seconds passed
+... 68%, 476384 KB, 3673 KB/s, 129 seconds passed
+... 68%, 476416 KB, 3673 KB/s, 129 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 485568 KB, 3348 KB/s, 144 seconds passed
-... 69%, 485600 KB, 3348 KB/s, 145 seconds passed
-... 69%, 485632 KB, 3349 KB/s, 145 seconds passed
-... 69%, 485664 KB, 3349 KB/s, 145 seconds passed
-... 69%, 485696 KB, 3348 KB/s, 145 seconds passed
-... 69%, 485728 KB, 3348 KB/s, 145 seconds passed
-... 69%, 485760 KB, 3349 KB/s, 145 seconds passed
+    ... 68%, 476448 KB, 3673 KB/s, 129 seconds passed
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+... 68%, 476512 KB, 3673 KB/s, 129 seconds passed
+... 68%, 476544 KB, 3673 KB/s, 129 seconds passed
+... 68%, 476576 KB, 3673 KB/s, 129 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 485792 KB, 3348 KB/s, 145 seconds passed
-... 69%, 485824 KB, 3348 KB/s, 145 seconds passed
-... 69%, 485856 KB, 3348 KB/s, 145 seconds passed
-... 69%, 485888 KB, 3349 KB/s, 145 seconds passed
+    ... 68%, 476608 KB, 3673 KB/s, 129 seconds passed
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+... 68%, 476768 KB, 3673 KB/s, 129 seconds passed
+... 68%, 476800 KB, 3673 KB/s, 129 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 485920 KB, 3348 KB/s, 145 seconds passed
-... 69%, 485952 KB, 3348 KB/s, 145 seconds passed
-... 69%, 485984 KB, 3349 KB/s, 145 seconds passed
-... 69%, 486016 KB, 3349 KB/s, 145 seconds passed
-... 69%, 486048 KB, 3348 KB/s, 145 seconds passed
-... 69%, 486080 KB, 3349 KB/s, 145 seconds passed
-... 69%, 486112 KB, 3349 KB/s, 145 seconds passed
+    ... 68%, 476832 KB, 3673 KB/s, 129 seconds passed
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+... 68%, 476928 KB, 3673 KB/s, 129 seconds passed
+... 68%, 476960 KB, 3673 KB/s, 129 seconds passed
+... 68%, 476992 KB, 3673 KB/s, 129 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 486144 KB, 3349 KB/s, 145 seconds passed
-... 69%, 486176 KB, 3348 KB/s, 145 seconds passed
-... 69%, 486208 KB, 3349 KB/s, 145 seconds passed
-... 69%, 486240 KB, 3349 KB/s, 145 seconds passed
-... 69%, 486272 KB, 3349 KB/s, 145 seconds passed
+    ... 68%, 477024 KB, 3673 KB/s, 129 seconds passed
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+... 68%, 477120 KB, 3673 KB/s, 129 seconds passed
+... 68%, 477152 KB, 3673 KB/s, 129 seconds passed
+... 68%, 477184 KB, 3673 KB/s, 129 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 486304 KB, 3349 KB/s, 145 seconds passed
-... 69%, 486336 KB, 3349 KB/s, 145 seconds passed
-... 69%, 486368 KB, 3349 KB/s, 145 seconds passed
-... 69%, 486400 KB, 3349 KB/s, 145 seconds passed
-... 69%, 486432 KB, 3349 KB/s, 145 seconds passed
-... 69%, 486464 KB, 3349 KB/s, 145 seconds passed
+    ... 68%, 477216 KB, 3673 KB/s, 129 seconds passed
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+... 68%, 477312 KB, 3673 KB/s, 129 seconds passed
+... 68%, 477344 KB, 3673 KB/s, 129 seconds passed
+... 68%, 477376 KB, 3673 KB/s, 129 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 486496 KB, 3349 KB/s, 145 seconds passed
-... 69%, 486528 KB, 3349 KB/s, 145 seconds passed
-... 69%, 486560 KB, 3349 KB/s, 145 seconds passed
-... 69%, 486592 KB, 3349 KB/s, 145 seconds passed
-... 69%, 486624 KB, 3349 KB/s, 145 seconds passed
-... 69%, 486656 KB, 3349 KB/s, 145 seconds passed
+    ... 68%, 477408 KB, 3673 KB/s, 129 seconds passed
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+... 68%, 477504 KB, 3673 KB/s, 129 seconds passed
+... 68%, 477536 KB, 3673 KB/s, 129 seconds passed
+... 68%, 477568 KB, 3673 KB/s, 130 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 486688 KB, 3349 KB/s, 145 seconds passed
-... 69%, 486720 KB, 3349 KB/s, 145 seconds passed
-... 69%, 486752 KB, 3349 KB/s, 145 seconds passed
-... 69%, 486784 KB, 3349 KB/s, 145 seconds passed
-... 69%, 486816 KB, 3349 KB/s, 145 seconds passed
-... 69%, 486848 KB, 3349 KB/s, 145 seconds passed
+    ... 68%, 477600 KB, 3673 KB/s, 130 seconds passed
+... 68%, 477632 KB, 3673 KB/s, 130 seconds passed
+... 68%, 477664 KB, 3673 KB/s, 130 seconds passed
+... 68%, 477696 KB, 3673 KB/s, 130 seconds passed
+... 68%, 477728 KB, 3673 KB/s, 130 seconds passed
+... 68%, 477760 KB, 3673 KB/s, 130 seconds passed
 
 .. parsed-literal::
 
-    ... 70%, 486880 KB, 3349 KB/s, 145 seconds passed
-... 70%, 486912 KB, 3349 KB/s, 145 seconds passed
-... 70%, 486944 KB, 3349 KB/s, 145 seconds passed
-... 70%, 486976 KB, 3349 KB/s, 145 seconds passed
-... 70%, 487008 KB, 3349 KB/s, 145 seconds passed
+    ... 68%, 477792 KB, 3673 KB/s, 130 seconds passed
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+... 68%, 477856 KB, 3673 KB/s, 130 seconds passed
+... 68%, 477888 KB, 3673 KB/s, 130 seconds passed
+... 68%, 477920 KB, 3673 KB/s, 130 seconds passed
+... 68%, 477952 KB, 3673 KB/s, 130 seconds passed
 
 .. parsed-literal::
 
-    ... 70%, 487040 KB, 3349 KB/s, 145 seconds passed
-... 70%, 487072 KB, 3349 KB/s, 145 seconds passed
-... 70%, 487104 KB, 3349 KB/s, 145 seconds passed
-... 70%, 487136 KB, 3349 KB/s, 145 seconds passed
-... 70%, 487168 KB, 3349 KB/s, 145 seconds passed
-... 70%, 487200 KB, 3349 KB/s, 145 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 70%, 487424 KB, 3349 KB/s, 145 seconds passed
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 .. parsed-literal::
 
-    ... 70%, 487648 KB, 3350 KB/s, 145 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 70%, 488192 KB, 3350 KB/s, 145 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 70%, 489120 KB, 3350 KB/s, 145 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 70%, 489504 KB, 3351 KB/s, 146 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 70%, 491360 KB, 3352 KB/s, 146 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 70%, 492096 KB, 3352 KB/s, 146 seconds passed
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 .. parsed-literal::
 
-    ... 70%, 492288 KB, 3352 KB/s, 146 seconds passed
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 .. parsed-literal::
 
-    ... 70%, 492448 KB, 3352 KB/s, 146 seconds passed
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 .. parsed-literal::
 
-    ... 70%, 492672 KB, 3352 KB/s, 146 seconds passed
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 .. parsed-literal::
 
-    ... 70%, 492832 KB, 3352 KB/s, 146 seconds passed
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 .. parsed-literal::
 
-    ... 70%, 493056 KB, 3352 KB/s, 147 seconds passed
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 .. parsed-literal::
 
-    ... 70%, 493216 KB, 3352 KB/s, 147 seconds passed
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 .. parsed-literal::
 
-    ... 70%, 493440 KB, 3353 KB/s, 147 seconds passed
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-... 70%, 493536 KB, 3353 KB/s, 147 seconds passed
-... 70%, 493568 KB, 3353 KB/s, 147 seconds passed
+    ... 69%, 484416 KB, 3673 KB/s, 131 seconds passed
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+... 69%, 484512 KB, 3673 KB/s, 131 seconds passed
+... 69%, 484544 KB, 3673 KB/s, 131 seconds passed
+... 69%, 484576 KB, 3673 KB/s, 131 seconds passed
 
 .. parsed-literal::
 
-    ... 70%, 493600 KB, 3353 KB/s, 147 seconds passed
-... 70%, 493632 KB, 3353 KB/s, 147 seconds passed
-... 70%, 493664 KB, 3353 KB/s, 147 seconds passed
-... 70%, 493696 KB, 3353 KB/s, 147 seconds passed
-... 70%, 493728 KB, 3353 KB/s, 147 seconds passed
-... 70%, 493760 KB, 3353 KB/s, 147 seconds passed
-... 70%, 493792 KB, 3353 KB/s, 147 seconds passed
+    ... 69%, 484608 KB, 3673 KB/s, 131 seconds passed
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+... 69%, 484704 KB, 3673 KB/s, 131 seconds passed
+... 69%, 484736 KB, 3673 KB/s, 131 seconds passed
+... 69%, 484768 KB, 3673 KB/s, 131 seconds passed
 
 .. parsed-literal::
 
-    ... 71%, 493824 KB, 3353 KB/s, 147 seconds passed
-... 71%, 493856 KB, 3353 KB/s, 147 seconds passed
-... 71%, 493888 KB, 3353 KB/s, 147 seconds passed
-... 71%, 493920 KB, 3353 KB/s, 147 seconds passed
-... 71%, 493952 KB, 3353 KB/s, 147 seconds passed
+    ... 69%, 484800 KB, 3673 KB/s, 131 seconds passed
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+... 69%, 484864 KB, 3673 KB/s, 131 seconds passed
+... 69%, 484896 KB, 3673 KB/s, 131 seconds passed
+... 69%, 484928 KB, 3673 KB/s, 132 seconds passed
 
 .. parsed-literal::
 
-    ... 71%, 493984 KB, 3353 KB/s, 147 seconds passed
-... 71%, 494016 KB, 3353 KB/s, 147 seconds passed
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-... 71%, 494112 KB, 3353 KB/s, 147 seconds passed
-... 71%, 494144 KB, 3353 KB/s, 147 seconds passed
-... 71%, 494176 KB, 3353 KB/s, 147 seconds passed
+    ... 69%, 484960 KB, 3673 KB/s, 132 seconds passed
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+... 69%, 485056 KB, 3673 KB/s, 132 seconds passed
+... 69%, 485088 KB, 3673 KB/s, 132 seconds passed
+... 69%, 485120 KB, 3673 KB/s, 132 seconds passed
 
 .. parsed-literal::
 
-    ... 71%, 494208 KB, 3353 KB/s, 147 seconds passed
-... 71%, 494240 KB, 3353 KB/s, 147 seconds passed
-... 71%, 494272 KB, 3353 KB/s, 147 seconds passed
-... 71%, 494304 KB, 3353 KB/s, 147 seconds passed
-... 71%, 494336 KB, 3353 KB/s, 147 seconds passed
+    ... 69%, 485152 KB, 3673 KB/s, 132 seconds passed
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+... 69%, 485280 KB, 3673 KB/s, 132 seconds passed
+... 69%, 485312 KB, 3673 KB/s, 132 seconds passed
 
 .. parsed-literal::
 
-    ... 71%, 494368 KB, 3353 KB/s, 147 seconds passed
-... 71%, 494400 KB, 3353 KB/s, 147 seconds passed
-... 71%, 494432 KB, 3353 KB/s, 147 seconds passed
-... 71%, 494464 KB, 3353 KB/s, 147 seconds passed
-... 71%, 494496 KB, 3353 KB/s, 147 seconds passed
-... 71%, 494528 KB, 3353 KB/s, 147 seconds passed
-... 71%, 494560 KB, 3353 KB/s, 147 seconds passed
+    ... 69%, 485344 KB, 3673 KB/s, 132 seconds passed
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+... 69%, 485472 KB, 3673 KB/s, 132 seconds passed
+... 69%, 485504 KB, 3673 KB/s, 132 seconds passed
 
 .. parsed-literal::
 
-    ... 71%, 494592 KB, 3353 KB/s, 147 seconds passed
-... 71%, 494624 KB, 3353 KB/s, 147 seconds passed
-... 71%, 494656 KB, 3353 KB/s, 147 seconds passed
-... 71%, 494688 KB, 3354 KB/s, 147 seconds passed
-... 71%, 494720 KB, 3353 KB/s, 147 seconds passed
+    ... 69%, 485536 KB, 3673 KB/s, 132 seconds passed
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+... 69%, 485632 KB, 3673 KB/s, 132 seconds passed
+... 69%, 485664 KB, 3673 KB/s, 132 seconds passed
+... 69%, 485696 KB, 3673 KB/s, 132 seconds passed
 
 .. parsed-literal::
 
-    ... 71%, 494752 KB, 3353 KB/s, 147 seconds passed
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-... 71%, 494848 KB, 3354 KB/s, 147 seconds passed
-... 71%, 494880 KB, 3353 KB/s, 147 seconds passed
-... 71%, 494912 KB, 3354 KB/s, 147 seconds passed
+    ... 69%, 485728 KB, 3673 KB/s, 132 seconds passed
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+... 69%, 485824 KB, 3673 KB/s, 132 seconds passed
+... 69%, 485856 KB, 3673 KB/s, 132 seconds passed
+... 69%, 485888 KB, 3673 KB/s, 132 seconds passed
 
 .. parsed-literal::
 
-    ... 71%, 494944 KB, 3354 KB/s, 147 seconds passed
-... 71%, 494976 KB, 3354 KB/s, 147 seconds passed
-... 71%, 495008 KB, 3353 KB/s, 147 seconds passed
-... 71%, 495040 KB, 3354 KB/s, 147 seconds passed
-... 71%, 495072 KB, 3354 KB/s, 147 seconds passed
-... 71%, 495104 KB, 3354 KB/s, 147 seconds passed
+    ... 69%, 485920 KB, 3673 KB/s, 132 seconds passed
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+... 69%, 486016 KB, 3673 KB/s, 132 seconds passed
+... 69%, 486048 KB, 3673 KB/s, 132 seconds passed
+... 69%, 486080 KB, 3673 KB/s, 132 seconds passed
 
 .. parsed-literal::
 
-    ... 71%, 495136 KB, 3354 KB/s, 147 seconds passed
-... 71%, 495168 KB, 3354 KB/s, 147 seconds passed
-... 71%, 495200 KB, 3354 KB/s, 147 seconds passed
-... 71%, 495232 KB, 3354 KB/s, 147 seconds passed
-... 71%, 495264 KB, 3354 KB/s, 147 seconds passed
-... 71%, 495296 KB, 3354 KB/s, 147 seconds passed
+    ... 69%, 486112 KB, 3673 KB/s, 132 seconds passed
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+... 69%, 486208 KB, 3673 KB/s, 132 seconds passed
+... 69%, 486240 KB, 3673 KB/s, 132 seconds passed
+... 69%, 486272 KB, 3673 KB/s, 132 seconds passed
 
 .. parsed-literal::
 
-    ... 71%, 495328 KB, 3354 KB/s, 147 seconds passed
-... 71%, 495360 KB, 3354 KB/s, 147 seconds passed
-... 71%, 495392 KB, 3354 KB/s, 147 seconds passed
-... 71%, 495424 KB, 3354 KB/s, 147 seconds passed
-... 71%, 495456 KB, 3354 KB/s, 147 seconds passed
+    ... 69%, 486304 KB, 3673 KB/s, 132 seconds passed
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+... 69%, 486400 KB, 3673 KB/s, 132 seconds passed
+... 69%, 486432 KB, 3673 KB/s, 132 seconds passed
+... 69%, 486464 KB, 3673 KB/s, 132 seconds passed
 
 .. parsed-literal::
 
-    ... 71%, 495488 KB, 3354 KB/s, 147 seconds passed
-... 71%, 495520 KB, 3354 KB/s, 147 seconds passed
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-... 71%, 495616 KB, 3354 KB/s, 147 seconds passed
-... 71%, 495648 KB, 3354 KB/s, 147 seconds passed
-... 71%, 495680 KB, 3354 KB/s, 147 seconds passed
+    ... 69%, 486496 KB, 3673 KB/s, 132 seconds passed
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+... 69%, 486592 KB, 3673 KB/s, 132 seconds passed
+... 69%, 486624 KB, 3673 KB/s, 132 seconds passed
+... 69%, 486656 KB, 3673 KB/s, 132 seconds passed
 
 .. parsed-literal::
 
-    ... 71%, 495712 KB, 3354 KB/s, 147 seconds passed
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-... 71%, 495776 KB, 3354 KB/s, 147 seconds passed
-... 71%, 495808 KB, 3354 KB/s, 147 seconds passed
-... 71%, 495840 KB, 3354 KB/s, 147 seconds passed
+    ... 69%, 486688 KB, 3673 KB/s, 132 seconds passed
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+... 69%, 486816 KB, 3673 KB/s, 132 seconds passed
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 .. parsed-literal::
 
-    ... 71%, 495872 KB, 3354 KB/s, 147 seconds passed
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-... 71%, 496032 KB, 3354 KB/s, 147 seconds passed
+    ... 70%, 486880 KB, 3673 KB/s, 132 seconds passed
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+... 70%, 486976 KB, 3673 KB/s, 132 seconds passed
+... 70%, 487008 KB, 3673 KB/s, 132 seconds passed
 
 .. parsed-literal::
 
-    ... 71%, 496064 KB, 3354 KB/s, 147 seconds passed
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+    ... 70%, 487040 KB, 3673 KB/s, 132 seconds passed
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+... 70%, 487200 KB, 3673 KB/s, 132 seconds passed
 
 .. parsed-literal::
 
-    ... 71%, 496256 KB, 3354 KB/s, 147 seconds passed
-... 71%, 496288 KB, 3354 KB/s, 147 seconds passed
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-... 71%, 496352 KB, 3354 KB/s, 147 seconds passed
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-... 71%, 496416 KB, 3354 KB/s, 147 seconds passed
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+... 70%, 487392 KB, 3673 KB/s, 132 seconds passed
 
 .. parsed-literal::
 
-    ... 71%, 496448 KB, 3355 KB/s, 147 seconds passed
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-... 71%, 496608 KB, 3355 KB/s, 148 seconds passed
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 .. parsed-literal::
 
-    ... 71%, 496640 KB, 3354 KB/s, 148 seconds passed
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 .. parsed-literal::
 
-    ... 71%, 496800 KB, 3355 KB/s, 148 seconds passed
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 .. parsed-literal::
 
-    ... 71%, 497024 KB, 3355 KB/s, 148 seconds passed
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 .. parsed-literal::
 
-    ... 71%, 497184 KB, 3355 KB/s, 148 seconds passed
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 .. parsed-literal::
 
-    ... 71%, 497408 KB, 3355 KB/s, 148 seconds passed
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 .. parsed-literal::
 
-    ... 71%, 497568 KB, 3355 KB/s, 148 seconds passed
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 .. parsed-literal::
 
-    ... 71%, 497792 KB, 3355 KB/s, 148 seconds passed
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 .. parsed-literal::
 
-    ... 71%, 497952 KB, 3355 KB/s, 148 seconds passed
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 .. parsed-literal::
 
-    ... 71%, 498176 KB, 3355 KB/s, 148 seconds passed
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 .. parsed-literal::
 
-    ... 71%, 498304 KB, 3355 KB/s, 148 seconds passed
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 .. parsed-literal::
 
-    ... 71%, 498528 KB, 3356 KB/s, 148 seconds passed
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 .. parsed-literal::
 
-    ... 71%, 498688 KB, 3356 KB/s, 148 seconds passed
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+... 70%, 489856 KB, 3673 KB/s, 133 seconds passed
 
 .. parsed-literal::
 
-    ... 71%, 498912 KB, 3356 KB/s, 148 seconds passed
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 .. parsed-literal::
 
-    ... 71%, 499072 KB, 3356 KB/s, 148 seconds passed
-... 71%, 499104 KB, 3356 KB/s, 148 seconds passed
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-... 71%, 499200 KB, 3356 KB/s, 148 seconds passed
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+    ... 70%, 490080 KB, 3673 KB/s, 133 seconds passed
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+... 70%, 490208 KB, 3673 KB/s, 133 seconds passed
+... 70%, 490240 KB, 3673 KB/s, 133 seconds passed
 
 .. parsed-literal::
 
-    ... 71%, 499296 KB, 3356 KB/s, 148 seconds passed
-... 71%, 499328 KB, 3356 KB/s, 148 seconds passed
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-... 71%, 499392 KB, 3356 KB/s, 148 seconds passed
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 .. parsed-literal::
 
-    ... 71%, 499456 KB, 3356 KB/s, 148 seconds passed
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+    ... 70%, 490432 KB, 3673 KB/s, 133 seconds passed
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+... 70%, 490624 KB, 3673 KB/s, 133 seconds passed
 
 .. parsed-literal::
 
-    ... 71%, 499680 KB, 3357 KB/s, 148 seconds passed
-... 71%, 499712 KB, 3356 KB/s, 148 seconds passed
-... 71%, 499744 KB, 3356 KB/s, 148 seconds passed
-... 71%, 499776 KB, 3357 KB/s, 148 seconds passed
-... 71%, 499808 KB, 3357 KB/s, 148 seconds passed
+    ... 70%, 490656 KB, 3673 KB/s, 133 seconds passed
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 .. parsed-literal::
 
-    ... 71%, 499840 KB, 3356 KB/s, 148 seconds passed
-... 71%, 499872 KB, 3356 KB/s, 148 seconds passed
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-... 71%, 499936 KB, 3357 KB/s, 148 seconds passed
-... 71%, 499968 KB, 3357 KB/s, 148 seconds passed
-... 71%, 500000 KB, 3357 KB/s, 148 seconds passed
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+... 70%, 490976 KB, 3673 KB/s, 133 seconds passed
+... 70%, 491008 KB, 3673 KB/s, 133 seconds passed
 
 .. parsed-literal::
 
-    ... 71%, 500064 KB, 3357 KB/s, 148 seconds passed
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+... 70%, 491200 KB, 3673 KB/s, 133 seconds passed
 
 .. parsed-literal::
 
-    ... 71%, 500224 KB, 3357 KB/s, 149 seconds passed
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+    ... 70%, 491232 KB, 3673 KB/s, 133 seconds passed
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+... 70%, 491360 KB, 3673 KB/s, 133 seconds passed
+... 70%, 491392 KB, 3673 KB/s, 133 seconds passed
 
 .. parsed-literal::
 
-    ... 71%, 500448 KB, 3357 KB/s, 149 seconds passed
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 .. parsed-literal::
 
-    ... 71%, 500608 KB, 3357 KB/s, 149 seconds passed
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 .. parsed-literal::
 
-    ... 72%, 500800 KB, 3357 KB/s, 149 seconds passed
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+... 70%, 491936 KB, 3673 KB/s, 133 seconds passed
 
 .. parsed-literal::
 
-    ... 72%, 500992 KB, 3357 KB/s, 149 seconds passed
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 .. parsed-literal::
 
-    ... 72%, 501184 KB, 3357 KB/s, 149 seconds passed
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 .. parsed-literal::
 
-    ... 72%, 501344 KB, 3357 KB/s, 149 seconds passed
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 .. parsed-literal::
 
-    ... 72%, 501568 KB, 3358 KB/s, 149 seconds passed
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 .. parsed-literal::
 
-    ... 72%, 501728 KB, 3358 KB/s, 149 seconds passed
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 .. parsed-literal::
 
-    ... 72%, 501920 KB, 3357 KB/s, 149 seconds passed
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 .. parsed-literal::
 
-    ... 72%, 502048 KB, 3357 KB/s, 149 seconds passed
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 .. parsed-literal::
 
-    ... 72%, 502112 KB, 3356 KB/s, 149 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 72%, 502208 KB, 3355 KB/s, 149 seconds passed
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 .. parsed-literal::
 
-    ... 72%, 502272 KB, 3354 KB/s, 149 seconds passed
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 .. parsed-literal::
 
-    ... 72%, 502368 KB, 3354 KB/s, 149 seconds passed
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 .. parsed-literal::
 
-    ... 72%, 502496 KB, 3353 KB/s, 149 seconds passed
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 .. parsed-literal::
 
-    ... 72%, 502560 KB, 3353 KB/s, 149 seconds passed
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 .. parsed-literal::
 
-    ... 72%, 502752 KB, 3353 KB/s, 149 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 72%, 503424 KB, 3352 KB/s, 150 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 72%, 504160 KB, 3353 KB/s, 150 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 72%, 504544 KB, 3353 KB/s, 150 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 72%, 504928 KB, 3353 KB/s, 150 seconds passed
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 .. parsed-literal::
 
-    ... 72%, 505056 KB, 3353 KB/s, 150 seconds passed
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 .. parsed-literal::
 
-    ... 72%, 505280 KB, 3354 KB/s, 150 seconds passed
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 .. parsed-literal::
 
-    ... 72%, 505440 KB, 3353 KB/s, 150 seconds passed
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 .. parsed-literal::
 
-    ... 72%, 505664 KB, 3354 KB/s, 150 seconds passed
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+    ... 71%, 497664 KB, 3674 KB/s, 135 seconds passed
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+... 71%, 497728 KB, 3674 KB/s, 135 seconds passed
+... 71%, 497760 KB, 3674 KB/s, 135 seconds passed
+... 71%, 497792 KB, 3674 KB/s, 135 seconds passed
 
 .. parsed-literal::
 
-    ... 72%, 505824 KB, 3354 KB/s, 150 seconds passed
-... 72%, 505856 KB, 3354 KB/s, 150 seconds passed
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-... 72%, 505920 KB, 3354 KB/s, 150 seconds passed
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+    ... 71%, 497824 KB, 3673 KB/s, 135 seconds passed
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+... 71%, 497952 KB, 3673 KB/s, 135 seconds passed
+... 71%, 497984 KB, 3674 KB/s, 135 seconds passed
+... 71%, 498016 KB, 3674 KB/s, 135 seconds passed
 
 .. parsed-literal::
 
-    ... 72%, 506016 KB, 3354 KB/s, 150 seconds passed
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-... 72%, 506080 KB, 3354 KB/s, 150 seconds passed
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-... 72%, 506176 KB, 3354 KB/s, 150 seconds passed
+    ... 71%, 498048 KB, 3674 KB/s, 135 seconds passed
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+... 71%, 498112 KB, 3674 KB/s, 135 seconds passed
+... 71%, 498144 KB, 3674 KB/s, 135 seconds passed
+... 71%, 498176 KB, 3674 KB/s, 135 seconds passed
 
 .. parsed-literal::
 
-    ... 72%, 506208 KB, 3354 KB/s, 150 seconds passed
-... 72%, 506240 KB, 3354 KB/s, 150 seconds passed
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-... 72%, 506368 KB, 3354 KB/s, 150 seconds passed
+    ... 71%, 498208 KB, 3673 KB/s, 135 seconds passed
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+... 71%, 498336 KB, 3673 KB/s, 135 seconds passed
+... 71%, 498368 KB, 3674 KB/s, 135 seconds passed
+... 71%, 498400 KB, 3674 KB/s, 135 seconds passed
 
 .. parsed-literal::
 
-    ... 72%, 506400 KB, 3354 KB/s, 150 seconds passed
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-... 72%, 506496 KB, 3354 KB/s, 150 seconds passed
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-... 72%, 506560 KB, 3355 KB/s, 150 seconds passed
+    ... 71%, 498432 KB, 3673 KB/s, 135 seconds passed
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+... 71%, 498496 KB, 3674 KB/s, 135 seconds passed
+... 71%, 498528 KB, 3674 KB/s, 135 seconds passed
 
 .. parsed-literal::
 
-    ... 72%, 506592 KB, 3354 KB/s, 151 seconds passed
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-... 72%, 506720 KB, 3354 KB/s, 151 seconds passed
+    ... 71%, 498560 KB, 3673 KB/s, 135 seconds passed
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+... 71%, 498720 KB, 3673 KB/s, 135 seconds passed
+... 71%, 498752 KB, 3674 KB/s, 135 seconds passed
+... 71%, 498784 KB, 3674 KB/s, 135 seconds passed
 
 .. parsed-literal::
 
-    ... 72%, 506752 KB, 3354 KB/s, 151 seconds passed
-... 72%, 506784 KB, 3355 KB/s, 151 seconds passed
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+... 71%, 498880 KB, 3674 KB/s, 135 seconds passed
+... 71%, 498912 KB, 3674 KB/s, 135 seconds passed
 
 .. parsed-literal::
 
-    ... 72%, 506976 KB, 3354 KB/s, 151 seconds passed
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-... 72%, 507104 KB, 3354 KB/s, 151 seconds passed
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+... 71%, 499104 KB, 3673 KB/s, 135 seconds passed
+... 71%, 499136 KB, 3674 KB/s, 135 seconds passed
 
 .. parsed-literal::
 
-    ... 72%, 507136 KB, 3355 KB/s, 151 seconds passed
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-... 72%, 507296 KB, 3355 KB/s, 151 seconds passed
-... 72%, 507328 KB, 3355 KB/s, 151 seconds passed
+    ... 71%, 499168 KB, 3674 KB/s, 135 seconds passed
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+... 71%, 499264 KB, 3674 KB/s, 135 seconds passed
+... 71%, 499296 KB, 3674 KB/s, 135 seconds passed
 
 .. parsed-literal::
 
-    ... 72%, 507360 KB, 3355 KB/s, 151 seconds passed
-... 72%, 507392 KB, 3355 KB/s, 151 seconds passed
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-... 72%, 507488 KB, 3355 KB/s, 151 seconds passed
+    ... 71%, 499328 KB, 3673 KB/s, 135 seconds passed
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+... 71%, 499488 KB, 3673 KB/s, 135 seconds passed
+... 71%, 499520 KB, 3674 KB/s, 135 seconds passed
 
 .. parsed-literal::
 
-    ... 72%, 507520 KB, 3355 KB/s, 151 seconds passed
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-... 72%, 507680 KB, 3355 KB/s, 151 seconds passed
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+... 71%, 499648 KB, 3674 KB/s, 135 seconds passed
+... 71%, 499680 KB, 3674 KB/s, 135 seconds passed
 
 .. parsed-literal::
 
-    ... 72%, 507712 KB, 3355 KB/s, 151 seconds passed
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-... 73%, 507872 KB, 3355 KB/s, 151 seconds passed
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+... 71%, 499872 KB, 3673 KB/s, 136 seconds passed
 
 .. parsed-literal::
 
-    ... 73%, 507904 KB, 3355 KB/s, 151 seconds passed
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-... 73%, 507968 KB, 3355 KB/s, 151 seconds passed
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-... 73%, 508032 KB, 3355 KB/s, 151 seconds passed
-... 73%, 508064 KB, 3355 KB/s, 151 seconds passed
+    ... 71%, 499904 KB, 3674 KB/s, 136 seconds passed
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+... 71%, 500000 KB, 3673 KB/s, 136 seconds passed
+... 71%, 500032 KB, 3674 KB/s, 136 seconds passed
+... 71%, 500064 KB, 3674 KB/s, 136 seconds passed
 
 .. parsed-literal::
 
-    ... 73%, 508096 KB, 3355 KB/s, 151 seconds passed
-... 73%, 508128 KB, 3355 KB/s, 151 seconds passed
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+... 71%, 500256 KB, 3673 KB/s, 136 seconds passed
 
 .. parsed-literal::
 
-    ... 73%, 508256 KB, 3355 KB/s, 151 seconds passed
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 .. parsed-literal::
 
-    ... 73%, 508480 KB, 3355 KB/s, 151 seconds passed
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 .. parsed-literal::
 
-    ... 73%, 508640 KB, 3355 KB/s, 151 seconds passed
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 .. parsed-literal::
 
-    ... 73%, 508864 KB, 3356 KB/s, 151 seconds passed
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 .. parsed-literal::
 
-    ... 73%, 509024 KB, 3356 KB/s, 151 seconds passed
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 .. parsed-literal::
 
-    ... 73%, 509248 KB, 3356 KB/s, 151 seconds passed
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 .. parsed-literal::
 
-    ... 73%, 509408 KB, 3356 KB/s, 151 seconds passed
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 .. parsed-literal::
 
-    ... 73%, 509632 KB, 3356 KB/s, 151 seconds passed
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 .. parsed-literal::
 
-    ... 73%, 509792 KB, 3356 KB/s, 151 seconds passed
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 .. parsed-literal::
 
-    ... 73%, 510016 KB, 3356 KB/s, 151 seconds passed
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 .. parsed-literal::
 
-    ... 73%, 510176 KB, 3356 KB/s, 151 seconds passed
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 .. parsed-literal::
 
-    ... 73%, 510400 KB, 3357 KB/s, 152 seconds passed
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 .. parsed-literal::
 
-    ... 73%, 510528 KB, 3357 KB/s, 152 seconds passed
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 .. parsed-literal::
 
-    ... 73%, 510752 KB, 3357 KB/s, 152 seconds passed
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 .. parsed-literal::
 
-    ... 73%, 510912 KB, 3357 KB/s, 152 seconds passed
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 .. parsed-literal::
 
-    ... 73%, 511136 KB, 3357 KB/s, 152 seconds passed
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+    ... 72%, 503168 KB, 3673 KB/s, 136 seconds passed
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 .. parsed-literal::
 
-    ... 73%, 511296 KB, 3357 KB/s, 152 seconds passed
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 .. parsed-literal::
 
-    ... 73%, 511488 KB, 3357 KB/s, 152 seconds passed
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 .. parsed-literal::
 
-    ... 73%, 511680 KB, 3357 KB/s, 152 seconds passed
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+... 72%, 503872 KB, 3674 KB/s, 137 seconds passed
+... 72%, 503904 KB, 3674 KB/s, 137 seconds passed
 
 .. parsed-literal::
 
-    ... 73%, 511872 KB, 3357 KB/s, 152 seconds passed
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-... 73%, 512000 KB, 3358 KB/s, 152 seconds passed
-... 73%, 512032 KB, 3358 KB/s, 152 seconds passed
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+... 72%, 504000 KB, 3674 KB/s, 137 seconds passed
+... 72%, 504032 KB, 3674 KB/s, 137 seconds passed
 
 .. parsed-literal::
 
-    ... 73%, 512064 KB, 3358 KB/s, 152 seconds passed
-... 73%, 512096 KB, 3357 KB/s, 152 seconds passed
-... 73%, 512128 KB, 3358 KB/s, 152 seconds passed
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-... 73%, 512224 KB, 3358 KB/s, 152 seconds passed
+    ... 72%, 504064 KB, 3674 KB/s, 137 seconds passed
+... 72%, 504096 KB, 3674 KB/s, 137 seconds passed
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+... 72%, 504192 KB, 3674 KB/s, 137 seconds passed
+... 72%, 504224 KB, 3674 KB/s, 137 seconds passed
+... 72%, 504256 KB, 3674 KB/s, 137 seconds passed
 
 .. parsed-literal::
 
-    ... 73%, 512256 KB, 3358 KB/s, 152 seconds passed
-... 73%, 512288 KB, 3358 KB/s, 152 seconds passed
-... 73%, 512320 KB, 3358 KB/s, 152 seconds passed
-... 73%, 512352 KB, 3358 KB/s, 152 seconds passed
-... 73%, 512384 KB, 3358 KB/s, 152 seconds passed
+    ... 72%, 504288 KB, 3674 KB/s, 137 seconds passed
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+... 72%, 504352 KB, 3674 KB/s, 137 seconds passed
+... 72%, 504384 KB, 3674 KB/s, 137 seconds passed
 
 .. parsed-literal::
 
-    ... 73%, 512416 KB, 3358 KB/s, 152 seconds passed
-... 73%, 512448 KB, 3358 KB/s, 152 seconds passed
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-... 73%, 512544 KB, 3358 KB/s, 152 seconds passed
-... 73%, 512576 KB, 3358 KB/s, 152 seconds passed
-... 73%, 512608 KB, 3358 KB/s, 152 seconds passed
+    ... 72%, 504416 KB, 3674 KB/s, 137 seconds passed
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+... 72%, 504576 KB, 3674 KB/s, 137 seconds passed
+... 72%, 504608 KB, 3674 KB/s, 137 seconds passed
+... 72%, 504640 KB, 3674 KB/s, 137 seconds passed
 
 .. parsed-literal::
 
-    ... 73%, 512640 KB, 3358 KB/s, 152 seconds passed
-... 73%, 512672 KB, 3358 KB/s, 152 seconds passed
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-... 73%, 512768 KB, 3358 KB/s, 152 seconds passed
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+... 72%, 504768 KB, 3674 KB/s, 137 seconds passed
 
 .. parsed-literal::
 
-    ... 73%, 512800 KB, 3358 KB/s, 152 seconds passed
-... 73%, 512832 KB, 3358 KB/s, 152 seconds passed
-... 73%, 512864 KB, 3358 KB/s, 152 seconds passed
-... 73%, 512896 KB, 3358 KB/s, 152 seconds passed
-... 73%, 512928 KB, 3358 KB/s, 152 seconds passed
-... 73%, 512960 KB, 3358 KB/s, 152 seconds passed
+    ... 72%, 504800 KB, 3674 KB/s, 137 seconds passed
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+... 72%, 504960 KB, 3674 KB/s, 137 seconds passed
+... 72%, 504992 KB, 3674 KB/s, 137 seconds passed
 
 .. parsed-literal::
 
-    ... 73%, 512992 KB, 3358 KB/s, 152 seconds passed
-... 73%, 513024 KB, 3357 KB/s, 152 seconds passed
-... 73%, 513056 KB, 3358 KB/s, 152 seconds passed
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-... 73%, 513120 KB, 3358 KB/s, 152 seconds passed
+    ... 72%, 505024 KB, 3674 KB/s, 137 seconds passed
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+... 72%, 505120 KB, 3674 KB/s, 137 seconds passed
+... 72%, 505152 KB, 3674 KB/s, 137 seconds passed
 
 .. parsed-literal::
 
-    ... 73%, 513152 KB, 3358 KB/s, 152 seconds passed
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+... 72%, 505280 KB, 3674 KB/s, 137 seconds passed
+... 72%, 505312 KB, 3674 KB/s, 137 seconds passed
+... 72%, 505344 KB, 3674 KB/s, 137 seconds passed
 
 .. parsed-literal::
 
-    ... 73%, 513184 KB, 3356 KB/s, 152 seconds passed
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+... 72%, 505536 KB, 3674 KB/s, 137 seconds passed
 
 .. parsed-literal::
 
-    ... 73%, 513216 KB, 3356 KB/s, 152 seconds passed
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+... 72%, 505696 KB, 3674 KB/s, 137 seconds passed
+... 72%, 505728 KB, 3674 KB/s, 137 seconds passed
 
 .. parsed-literal::
 
-    ... 73%, 513248 KB, 3355 KB/s, 152 seconds passed
-... 73%, 513280 KB, 3355 KB/s, 152 seconds passed
-... 73%, 513312 KB, 3355 KB/s, 152 seconds passed
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+... 72%, 505856 KB, 3674 KB/s, 137 seconds passed
+... 72%, 505888 KB, 3674 KB/s, 137 seconds passed
+... 72%, 505920 KB, 3674 KB/s, 137 seconds passed
 
 .. parsed-literal::
 
-    ... 73%, 513344 KB, 3354 KB/s, 153 seconds passed
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+... 72%, 506016 KB, 3674 KB/s, 137 seconds passed
+... 72%, 506048 KB, 3674 KB/s, 137 seconds passed
+... 72%, 506080 KB, 3674 KB/s, 137 seconds passed
 
 .. parsed-literal::
 
-    ... 73%, 513376 KB, 3354 KB/s, 153 seconds passed
-... 73%, 513408 KB, 3354 KB/s, 153 seconds passed
-... 73%, 513440 KB, 3353 KB/s, 153 seconds passed
-... 73%, 513472 KB, 3353 KB/s, 153 seconds passed
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+... 72%, 506240 KB, 3674 KB/s, 137 seconds passed
+... 72%, 506272 KB, 3674 KB/s, 137 seconds passed
+... 72%, 506304 KB, 3674 KB/s, 137 seconds passed
 
 .. parsed-literal::
 
-    ... 73%, 513504 KB, 3353 KB/s, 153 seconds passed
-... 73%, 513536 KB, 3353 KB/s, 153 seconds passed
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+... 72%, 506432 KB, 3674 KB/s, 137 seconds passed
+... 72%, 506464 KB, 3674 KB/s, 137 seconds passed
 
 .. parsed-literal::
 
-    ... 73%, 513568 KB, 3353 KB/s, 153 seconds passed
-... 73%, 513600 KB, 3353 KB/s, 153 seconds passed
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-... 73%, 513664 KB, 3352 KB/s, 153 seconds passed
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+... 72%, 506656 KB, 3674 KB/s, 137 seconds passed
+... 72%, 506688 KB, 3674 KB/s, 137 seconds passed
 
 .. parsed-literal::
 
-    ... 73%, 513696 KB, 3352 KB/s, 153 seconds passed
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-... 73%, 513760 KB, 3352 KB/s, 153 seconds passed
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+... 72%, 506848 KB, 3674 KB/s, 137 seconds passed
 
 .. parsed-literal::
 
-    ... 73%, 513792 KB, 3352 KB/s, 153 seconds passed
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-... 73%, 513856 KB, 3352 KB/s, 153 seconds passed
-... 73%, 513888 KB, 3352 KB/s, 153 seconds passed
-... 73%, 513920 KB, 3352 KB/s, 153 seconds passed
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+... 72%, 507008 KB, 3674 KB/s, 137 seconds passed
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 .. parsed-literal::
 
-    ... 73%, 513952 KB, 3351 KB/s, 153 seconds passed
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 .. parsed-literal::
 
-    ... 73%, 514048 KB, 3351 KB/s, 153 seconds passed
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 .. parsed-literal::
 
-    ... 73%, 514272 KB, 3351 KB/s, 153 seconds passed
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 .. parsed-literal::
 
-    ... 73%, 514368 KB, 3351 KB/s, 153 seconds passed
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 .. parsed-literal::
 
-    ... 73%, 514592 KB, 3351 KB/s, 153 seconds passed
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 .. parsed-literal::
 
-    ... 74%, 514720 KB, 3351 KB/s, 153 seconds passed
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 .. parsed-literal::
 
-    ... 74%, 514944 KB, 3352 KB/s, 153 seconds passed
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 .. parsed-literal::
 
-    ... 74%, 515104 KB, 3351 KB/s, 153 seconds passed
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 .. parsed-literal::
 
-    ... 74%, 515328 KB, 3352 KB/s, 153 seconds passed
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 .. parsed-literal::
 
-    ... 74%, 515488 KB, 3352 KB/s, 153 seconds passed
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 .. parsed-literal::
 
-    ... 74%, 515680 KB, 3352 KB/s, 153 seconds passed
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 .. parsed-literal::
 
-    ... 74%, 515872 KB, 3352 KB/s, 153 seconds passed
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 .. parsed-literal::
 
-    ... 74%, 516064 KB, 3352 KB/s, 153 seconds passed
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 .. parsed-literal::
 
-    ... 74%, 516256 KB, 3352 KB/s, 153 seconds passed
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 .. parsed-literal::
 
-    ... 74%, 516416 KB, 3352 KB/s, 154 seconds passed
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 .. parsed-literal::
 
-    ... 74%, 516640 KB, 3352 KB/s, 154 seconds passed
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 .. parsed-literal::
 
-    ... 74%, 516800 KB, 3353 KB/s, 154 seconds passed
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 .. parsed-literal::
 
-    ... 74%, 516992 KB, 3353 KB/s, 154 seconds passed
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 .. parsed-literal::
 
-    ... 74%, 517184 KB, 3353 KB/s, 154 seconds passed
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 .. parsed-literal::
 
-    ... 74%, 517376 KB, 3353 KB/s, 154 seconds passed
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 .. parsed-literal::
 
-    ... 74%, 517568 KB, 3353 KB/s, 154 seconds passed
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+... 73%, 511008 KB, 3674 KB/s, 139 seconds passed
+... 73%, 511040 KB, 3674 KB/s, 139 seconds passed
 
 .. parsed-literal::
 
-    ... 74%, 517760 KB, 3353 KB/s, 154 seconds passed
-... 74%, 517792 KB, 3353 KB/s, 154 seconds passed
-... 74%, 517824 KB, 3353 KB/s, 154 seconds passed
-... 74%, 517856 KB, 3353 KB/s, 154 seconds passed
-... 74%, 517888 KB, 3353 KB/s, 154 seconds passed
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+... 73%, 511200 KB, 3674 KB/s, 139 seconds passed
 
 .. parsed-literal::
 
-    ... 74%, 517920 KB, 3353 KB/s, 154 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 75%, 523584 KB, 3352 KB/s, 156 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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+... 74%, 518144 KB, 3674 KB/s, 141 seconds passed
+... 74%, 518176 KB, 3674 KB/s, 141 seconds passed
+... 74%, 518208 KB, 3674 KB/s, 141 seconds passed
 
 .. parsed-literal::
 
-    ... 75%, 523872 KB, 3351 KB/s, 156 seconds passed
-... 75%, 523904 KB, 3350 KB/s, 156 seconds passed
-... 75%, 523936 KB, 3350 KB/s, 156 seconds passed
+    ... 74%, 518240 KB, 3674 KB/s, 141 seconds passed
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+... 74%, 518304 KB, 3674 KB/s, 141 seconds passed
+... 74%, 518336 KB, 3674 KB/s, 141 seconds passed
+... 74%, 518368 KB, 3674 KB/s, 141 seconds passed
+... 74%, 518400 KB, 3674 KB/s, 141 seconds passed
 
 .. parsed-literal::
 
-    ... 75%, 523968 KB, 3350 KB/s, 156 seconds passed
-... 75%, 524000 KB, 3350 KB/s, 156 seconds passed
-... 75%, 524032 KB, 3350 KB/s, 156 seconds passed
-... 75%, 524064 KB, 3350 KB/s, 156 seconds passed
-... 75%, 524096 KB, 3350 KB/s, 156 seconds passed
+    ... 74%, 518432 KB, 3674 KB/s, 141 seconds passed
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+... 74%, 518496 KB, 3674 KB/s, 141 seconds passed
+... 74%, 518528 KB, 3674 KB/s, 141 seconds passed
+... 74%, 518560 KB, 3674 KB/s, 141 seconds passed
+... 74%, 518592 KB, 3674 KB/s, 141 seconds passed
 
 .. parsed-literal::
 
-    ... 75%, 524128 KB, 3350 KB/s, 156 seconds passed
-... 75%, 524160 KB, 3350 KB/s, 156 seconds passed
-... 75%, 524192 KB, 3350 KB/s, 156 seconds passed
-... 75%, 524224 KB, 3350 KB/s, 156 seconds passed
+    ... 74%, 518624 KB, 3674 KB/s, 141 seconds passed
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+... 74%, 518720 KB, 3674 KB/s, 141 seconds passed
+... 74%, 518752 KB, 3674 KB/s, 141 seconds passed
+... 74%, 518784 KB, 3674 KB/s, 141 seconds passed
 
 .. parsed-literal::
 
-    ... 75%, 524256 KB, 3349 KB/s, 156 seconds passed
-... 75%, 524288 KB, 3350 KB/s, 156 seconds passed
-... 75%, 524320 KB, 3350 KB/s, 156 seconds passed
-... 75%, 524352 KB, 3349 KB/s, 156 seconds passed
-... 75%, 524384 KB, 3349 KB/s, 156 seconds passed
+    ... 74%, 518816 KB, 3674 KB/s, 141 seconds passed
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+... 74%, 518912 KB, 3674 KB/s, 141 seconds passed
+... 74%, 518944 KB, 3674 KB/s, 141 seconds passed
+... 74%, 518976 KB, 3674 KB/s, 141 seconds passed
 
 .. parsed-literal::
 
-    ... 75%, 524416 KB, 3350 KB/s, 156 seconds passed
-... 75%, 524448 KB, 3349 KB/s, 156 seconds passed
-... 75%, 524480 KB, 3349 KB/s, 156 seconds passed
-... 75%, 524512 KB, 3349 KB/s, 156 seconds passed
-... 75%, 524544 KB, 3350 KB/s, 156 seconds passed
+    ... 74%, 519008 KB, 3674 KB/s, 141 seconds passed
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+... 74%, 519104 KB, 3674 KB/s, 141 seconds passed
+... 74%, 519136 KB, 3674 KB/s, 141 seconds passed
+... 74%, 519168 KB, 3674 KB/s, 141 seconds passed
 
 .. parsed-literal::
 
-    ... 75%, 524576 KB, 3349 KB/s, 156 seconds passed
-... 75%, 524608 KB, 3349 KB/s, 156 seconds passed
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-... 75%, 524672 KB, 3350 KB/s, 156 seconds passed
-... 75%, 524704 KB, 3349 KB/s, 156 seconds passed
+    ... 74%, 519200 KB, 3674 KB/s, 141 seconds passed
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+... 74%, 519296 KB, 3674 KB/s, 141 seconds passed
+... 74%, 519328 KB, 3674 KB/s, 141 seconds passed
+... 74%, 519360 KB, 3674 KB/s, 141 seconds passed
 
 .. parsed-literal::
 
-    ... 75%, 524736 KB, 3349 KB/s, 156 seconds passed
-... 75%, 524768 KB, 3350 KB/s, 156 seconds passed
-... 75%, 524800 KB, 3350 KB/s, 156 seconds passed
-... 75%, 524832 KB, 3349 KB/s, 156 seconds passed
-... 75%, 524864 KB, 3349 KB/s, 156 seconds passed
-... 75%, 524896 KB, 3350 KB/s, 156 seconds passed
-... 75%, 524928 KB, 3350 KB/s, 156 seconds passed
+    ... 74%, 519392 KB, 3674 KB/s, 141 seconds passed
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+... 74%, 519488 KB, 3674 KB/s, 141 seconds passed
+... 74%, 519520 KB, 3674 KB/s, 141 seconds passed
+... 74%, 519552 KB, 3674 KB/s, 141 seconds passed
 
 .. parsed-literal::
 
-    ... 75%, 524960 KB, 3349 KB/s, 156 seconds passed
-... 75%, 524992 KB, 3350 KB/s, 156 seconds passed
-... 75%, 525024 KB, 3350 KB/s, 156 seconds passed
-... 75%, 525056 KB, 3350 KB/s, 156 seconds passed
-... 75%, 525088 KB, 3350 KB/s, 156 seconds passed
+    ... 74%, 519584 KB, 3674 KB/s, 141 seconds passed
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+... 74%, 519648 KB, 3674 KB/s, 141 seconds passed
+... 74%, 519680 KB, 3674 KB/s, 141 seconds passed
+... 74%, 519712 KB, 3674 KB/s, 141 seconds passed
 
 .. parsed-literal::
 
-    ... 75%, 525120 KB, 3350 KB/s, 156 seconds passed
-... 75%, 525152 KB, 3350 KB/s, 156 seconds passed
-... 75%, 525184 KB, 3349 KB/s, 156 seconds passed
-... 75%, 525216 KB, 3350 KB/s, 156 seconds passed
-... 75%, 525248 KB, 3350 KB/s, 156 seconds passed
-... 75%, 525280 KB, 3350 KB/s, 156 seconds passed
+    ... 74%, 519744 KB, 3674 KB/s, 141 seconds passed
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+... 74%, 519872 KB, 3674 KB/s, 141 seconds passed
+... 74%, 519904 KB, 3674 KB/s, 141 seconds passed
+... 74%, 519936 KB, 3674 KB/s, 141 seconds passed
 
 .. parsed-literal::
 
-    ... 75%, 525312 KB, 3350 KB/s, 156 seconds passed
-... 75%, 525344 KB, 3350 KB/s, 156 seconds passed
-... 75%, 525376 KB, 3350 KB/s, 156 seconds passed
-... 75%, 525408 KB, 3350 KB/s, 156 seconds passed
-... 75%, 525440 KB, 3350 KB/s, 156 seconds passed
+    ... 74%, 519968 KB, 3674 KB/s, 141 seconds passed
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+... 74%, 520032 KB, 3674 KB/s, 141 seconds passed
+... 74%, 520064 KB, 3674 KB/s, 141 seconds passed
+... 74%, 520096 KB, 3674 KB/s, 141 seconds passed
 
 .. parsed-literal::
 
-    ... 75%, 525472 KB, 3350 KB/s, 156 seconds passed
-... 75%, 525504 KB, 3350 KB/s, 156 seconds passed
-... 75%, 525536 KB, 3350 KB/s, 156 seconds passed
-... 75%, 525568 KB, 3350 KB/s, 156 seconds passed
-... 75%, 525600 KB, 3350 KB/s, 156 seconds passed
-... 75%, 525632 KB, 3350 KB/s, 156 seconds passed
-... 75%, 525664 KB, 3350 KB/s, 156 seconds passed
+    ... 74%, 520128 KB, 3674 KB/s, 141 seconds passed
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+... 74%, 520256 KB, 3674 KB/s, 141 seconds passed
+... 74%, 520288 KB, 3674 KB/s, 141 seconds passed
+... 74%, 520320 KB, 3674 KB/s, 141 seconds passed
 
 .. parsed-literal::
 
-    ... 75%, 525696 KB, 3350 KB/s, 156 seconds passed
-... 75%, 525728 KB, 3350 KB/s, 156 seconds passed
-... 75%, 525760 KB, 3350 KB/s, 156 seconds passed
-... 75%, 525792 KB, 3350 KB/s, 156 seconds passed
-... 75%, 525824 KB, 3350 KB/s, 156 seconds passed
+    ... 74%, 520352 KB, 3674 KB/s, 141 seconds passed
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+... 74%, 520416 KB, 3674 KB/s, 141 seconds passed
+... 74%, 520448 KB, 3674 KB/s, 141 seconds passed
+... 74%, 520480 KB, 3674 KB/s, 141 seconds passed
 
 .. parsed-literal::
 
-    ... 75%, 525856 KB, 3350 KB/s, 156 seconds passed
-... 75%, 525888 KB, 3350 KB/s, 156 seconds passed
-... 75%, 525920 KB, 3350 KB/s, 156 seconds passed
-... 75%, 525952 KB, 3350 KB/s, 156 seconds passed
-... 75%, 525984 KB, 3350 KB/s, 156 seconds passed
-... 75%, 526016 KB, 3350 KB/s, 156 seconds passed
-... 75%, 526048 KB, 3350 KB/s, 156 seconds passed
+    ... 74%, 520512 KB, 3674 KB/s, 141 seconds passed
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+... 74%, 520640 KB, 3674 KB/s, 141 seconds passed
+... 74%, 520672 KB, 3674 KB/s, 141 seconds passed
+... 74%, 520704 KB, 3674 KB/s, 141 seconds passed
 
 .. parsed-literal::
 
-    ... 75%, 526080 KB, 3350 KB/s, 157 seconds passed
-... 75%, 526112 KB, 3350 KB/s, 157 seconds passed
-... 75%, 526144 KB, 3350 KB/s, 157 seconds passed
-... 75%, 526176 KB, 3350 KB/s, 157 seconds passed
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+... 74%, 520800 KB, 3674 KB/s, 141 seconds passed
+... 74%, 520832 KB, 3674 KB/s, 141 seconds passed
+... 74%, 520864 KB, 3674 KB/s, 141 seconds passed
 
 .. parsed-literal::
 
-    ... 75%, 526208 KB, 3350 KB/s, 157 seconds passed
-... 75%, 526240 KB, 3350 KB/s, 157 seconds passed
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-... 75%, 526304 KB, 3350 KB/s, 157 seconds passed
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-... 75%, 526368 KB, 3350 KB/s, 157 seconds passed
-... 75%, 526400 KB, 3350 KB/s, 157 seconds passed
-... 75%, 526432 KB, 3351 KB/s, 157 seconds passed
+    ... 74%, 520896 KB, 3674 KB/s, 141 seconds passed
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+... 74%, 520992 KB, 3674 KB/s, 141 seconds passed
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+... 74%, 521056 KB, 3674 KB/s, 141 seconds passed
 
 .. parsed-literal::
 
-    ... 75%, 526464 KB, 3350 KB/s, 157 seconds passed
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+... 74%, 521216 KB, 3674 KB/s, 141 seconds passed
 
 .. parsed-literal::
 
-    ... 75%, 526592 KB, 3350 KB/s, 157 seconds passed
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-... 75%, 526816 KB, 3351 KB/s, 157 seconds passed
+    ... 74%, 521248 KB, 3674 KB/s, 141 seconds passed
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+... 74%, 521408 KB, 3674 KB/s, 141 seconds passed
+... 74%, 521440 KB, 3674 KB/s, 141 seconds passed
 
 .. parsed-literal::
 
-    ... 75%, 526848 KB, 3350 KB/s, 157 seconds passed
-... 75%, 526880 KB, 3351 KB/s, 157 seconds passed
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+... 74%, 521600 KB, 3674 KB/s, 141 seconds passed
 
 .. parsed-literal::
 
-    ... 75%, 526976 KB, 3351 KB/s, 157 seconds passed
-... 75%, 527008 KB, 3351 KB/s, 157 seconds passed
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-... 75%, 527200 KB, 3351 KB/s, 157 seconds passed
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 .. parsed-literal::
 
-    ... 75%, 527232 KB, 3351 KB/s, 157 seconds passed
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 .. parsed-literal::
 
-    ... 75%, 527360 KB, 3351 KB/s, 157 seconds passed
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 .. parsed-literal::
 
-    ... 75%, 527616 KB, 3351 KB/s, 157 seconds passed
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 .. parsed-literal::
 
-    ... 75%, 527744 KB, 3351 KB/s, 157 seconds passed
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 .. parsed-literal::
 
-    ... 75%, 528000 KB, 3351 KB/s, 157 seconds passed
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 .. parsed-literal::
 
-    ... 75%, 528128 KB, 3351 KB/s, 157 seconds passed
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 .. parsed-literal::
 
-    ... 75%, 528352 KB, 3352 KB/s, 157 seconds passed
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 .. parsed-literal::
 
-    ... 75%, 528512 KB, 3351 KB/s, 157 seconds passed
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 .. parsed-literal::
 
-    ... 76%, 528736 KB, 3352 KB/s, 157 seconds passed
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 .. parsed-literal::
 
-    ... 76%, 528896 KB, 3352 KB/s, 157 seconds passed
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 .. parsed-literal::
 
-    ... 76%, 529120 KB, 3352 KB/s, 157 seconds passed
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-... 76%, 529184 KB, 3352 KB/s, 157 seconds passed
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-... 76%, 529248 KB, 3352 KB/s, 157 seconds passed
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 .. parsed-literal::
 
-    ... 76%, 529280 KB, 3352 KB/s, 157 seconds passed
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-... 76%, 529376 KB, 3352 KB/s, 157 seconds passed
-... 76%, 529408 KB, 3352 KB/s, 157 seconds passed
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+    ... 75%, 523904 KB, 3674 KB/s, 142 seconds passed
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+... 75%, 524064 KB, 3674 KB/s, 142 seconds passed
+... 75%, 524096 KB, 3674 KB/s, 142 seconds passed
 
 .. parsed-literal::
 
-    ... 76%, 529472 KB, 3352 KB/s, 157 seconds passed
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+... 75%, 524224 KB, 3674 KB/s, 142 seconds passed
+... 75%, 524256 KB, 3674 KB/s, 142 seconds passed
 
 .. parsed-literal::
 
-    ... 76%, 529632 KB, 3352 KB/s, 157 seconds passed
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-... 76%, 529760 KB, 3352 KB/s, 158 seconds passed
-... 76%, 529792 KB, 3352 KB/s, 158 seconds passed
-... 76%, 529824 KB, 3352 KB/s, 158 seconds passed
+    ... 75%, 524288 KB, 3674 KB/s, 142 seconds passed
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+... 75%, 524384 KB, 3674 KB/s, 142 seconds passed
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+... 75%, 524448 KB, 3674 KB/s, 142 seconds passed
 
 .. parsed-literal::
 
-    ... 76%, 529856 KB, 3352 KB/s, 158 seconds passed
-... 76%, 529888 KB, 3352 KB/s, 158 seconds passed
-... 76%, 529920 KB, 3352 KB/s, 158 seconds passed
-... 76%, 529952 KB, 3352 KB/s, 158 seconds passed
-... 76%, 529984 KB, 3353 KB/s, 158 seconds passed
+    ... 75%, 524480 KB, 3674 KB/s, 142 seconds passed
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+... 75%, 524576 KB, 3674 KB/s, 142 seconds passed
+... 75%, 524608 KB, 3674 KB/s, 142 seconds passed
+... 75%, 524640 KB, 3674 KB/s, 142 seconds passed
 
 .. parsed-literal::
 
-    ... 76%, 530016 KB, 3352 KB/s, 158 seconds passed
-... 76%, 530048 KB, 3352 KB/s, 158 seconds passed
-... 76%, 530080 KB, 3352 KB/s, 158 seconds passed
-... 76%, 530112 KB, 3353 KB/s, 158 seconds passed
-... 76%, 530144 KB, 3352 KB/s, 158 seconds passed
-... 76%, 530176 KB, 3352 KB/s, 158 seconds passed
+    ... 75%, 524672 KB, 3674 KB/s, 142 seconds passed
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+... 75%, 524800 KB, 3674 KB/s, 142 seconds passed
+... 75%, 524832 KB, 3674 KB/s, 142 seconds passed
 
 .. parsed-literal::
 
-    ... 76%, 530208 KB, 3353 KB/s, 158 seconds passed
-... 76%, 530240 KB, 3353 KB/s, 158 seconds passed
-... 76%, 530272 KB, 3352 KB/s, 158 seconds passed
-... 76%, 530304 KB, 3352 KB/s, 158 seconds passed
-... 76%, 530336 KB, 3353 KB/s, 158 seconds passed
-... 76%, 530368 KB, 3353 KB/s, 158 seconds passed
+    ... 75%, 524864 KB, 3674 KB/s, 142 seconds passed
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+... 75%, 524960 KB, 3674 KB/s, 142 seconds passed
+... 75%, 524992 KB, 3674 KB/s, 142 seconds passed
+... 75%, 525024 KB, 3674 KB/s, 142 seconds passed
 
 .. parsed-literal::
 
-    ... 76%, 530400 KB, 3353 KB/s, 158 seconds passed
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-... 76%, 530464 KB, 3353 KB/s, 158 seconds passed
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-... 76%, 530560 KB, 3353 KB/s, 158 seconds passed
+    ... 75%, 525056 KB, 3674 KB/s, 142 seconds passed
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+... 75%, 525152 KB, 3674 KB/s, 142 seconds passed
+... 75%, 525184 KB, 3674 KB/s, 142 seconds passed
+... 75%, 525216 KB, 3674 KB/s, 142 seconds passed
 
 .. parsed-literal::
 
-    ... 76%, 530592 KB, 3353 KB/s, 158 seconds passed
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-... 76%, 530720 KB, 3353 KB/s, 158 seconds passed
-... 76%, 530752 KB, 3353 KB/s, 158 seconds passed
+    ... 75%, 525248 KB, 3674 KB/s, 142 seconds passed
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+... 75%, 525344 KB, 3674 KB/s, 142 seconds passed
+... 75%, 525376 KB, 3674 KB/s, 142 seconds passed
+... 75%, 525408 KB, 3674 KB/s, 142 seconds passed
 
 .. parsed-literal::
 
-    ... 76%, 530784 KB, 3353 KB/s, 158 seconds passed
-... 76%, 530816 KB, 3353 KB/s, 158 seconds passed
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-... 76%, 530880 KB, 3353 KB/s, 158 seconds passed
-... 76%, 530912 KB, 3353 KB/s, 158 seconds passed
-... 76%, 530944 KB, 3353 KB/s, 158 seconds passed
+    ... 75%, 525440 KB, 3674 KB/s, 142 seconds passed
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+... 75%, 525568 KB, 3674 KB/s, 143 seconds passed
+... 75%, 525600 KB, 3674 KB/s, 143 seconds passed
 
 .. parsed-literal::
 
-    ... 76%, 530976 KB, 3353 KB/s, 158 seconds passed
-... 76%, 531008 KB, 3353 KB/s, 158 seconds passed
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-... 76%, 531104 KB, 3353 KB/s, 158 seconds passed
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+    ... 75%, 525632 KB, 3674 KB/s, 143 seconds passed
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+... 75%, 525760 KB, 3674 KB/s, 143 seconds passed
+... 75%, 525792 KB, 3674 KB/s, 143 seconds passed
 
 .. parsed-literal::
 
-    ... 76%, 531168 KB, 3353 KB/s, 158 seconds passed
-... 76%, 531200 KB, 3353 KB/s, 158 seconds passed
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-... 76%, 531296 KB, 3353 KB/s, 158 seconds passed
+    ... 75%, 525824 KB, 3674 KB/s, 143 seconds passed
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+... 75%, 525952 KB, 3674 KB/s, 143 seconds passed
 
 .. parsed-literal::
 
-    ... 76%, 531328 KB, 3353 KB/s, 158 seconds passed
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-... 76%, 531392 KB, 3353 KB/s, 158 seconds passed
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-... 76%, 531456 KB, 3353 KB/s, 158 seconds passed
-... 76%, 531488 KB, 3353 KB/s, 158 seconds passed
-... 76%, 531520 KB, 3353 KB/s, 158 seconds passed
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+... 75%, 526176 KB, 3674 KB/s, 143 seconds passed
 
 .. parsed-literal::
 
-    ... 76%, 531552 KB, 3353 KB/s, 158 seconds passed
-... 76%, 531584 KB, 3353 KB/s, 158 seconds passed
-... 76%, 531616 KB, 3353 KB/s, 158 seconds passed
-... 76%, 531648 KB, 3353 KB/s, 158 seconds passed
-... 76%, 531680 KB, 3353 KB/s, 158 seconds passed
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+... 75%, 526272 KB, 3674 KB/s, 143 seconds passed
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+... 75%, 526336 KB, 3674 KB/s, 143 seconds passed
 
 .. parsed-literal::
 
-    ... 76%, 531712 KB, 3353 KB/s, 158 seconds passed
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-... 76%, 531840 KB, 3353 KB/s, 158 seconds passed
-... 76%, 531872 KB, 3354 KB/s, 158 seconds passed
-... 76%, 531904 KB, 3354 KB/s, 158 seconds passed
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+... 75%, 526528 KB, 3674 KB/s, 143 seconds passed
+... 75%, 526560 KB, 3674 KB/s, 143 seconds passed
 
 .. parsed-literal::
 
-    ... 76%, 531936 KB, 3353 KB/s, 158 seconds passed
-... 76%, 531968 KB, 3353 KB/s, 158 seconds passed
-... 76%, 532000 KB, 3354 KB/s, 158 seconds passed
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-... 76%, 532064 KB, 3353 KB/s, 158 seconds passed
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+... 75%, 526720 KB, 3674 KB/s, 143 seconds passed
 
 .. parsed-literal::
 
-    ... 76%, 532096 KB, 3354 KB/s, 158 seconds passed
-... 76%, 532128 KB, 3354 KB/s, 158 seconds passed
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-... 76%, 532256 KB, 3354 KB/s, 158 seconds passed
-... 76%, 532288 KB, 3354 KB/s, 158 seconds passed
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+... 75%, 526944 KB, 3674 KB/s, 143 seconds passed
 
 .. parsed-literal::
 
-    ... 76%, 532320 KB, 3354 KB/s, 158 seconds passed
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 .. parsed-literal::
 
-    ... 76%, 532480 KB, 3354 KB/s, 158 seconds passed
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 .. parsed-literal::
 
-    ... 76%, 532672 KB, 3354 KB/s, 158 seconds passed
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 .. parsed-literal::
 
-    ... 76%, 532864 KB, 3354 KB/s, 158 seconds passed
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 .. parsed-literal::
 
-    ... 76%, 533024 KB, 3354 KB/s, 158 seconds passed
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 .. parsed-literal::
 
-    ... 76%, 533216 KB, 3354 KB/s, 158 seconds passed
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 .. parsed-literal::
 
-    ... 76%, 533408 KB, 3354 KB/s, 159 seconds passed
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 .. parsed-literal::
 
-    ... 76%, 533600 KB, 3354 KB/s, 159 seconds passed
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 .. parsed-literal::
 
-    ... 76%, 533792 KB, 3354 KB/s, 159 seconds passed
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 .. parsed-literal::
 
-    ... 76%, 533984 KB, 3355 KB/s, 159 seconds passed
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 .. parsed-literal::
 
-    ... 76%, 534144 KB, 3355 KB/s, 159 seconds passed
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 .. parsed-literal::
 
-    ... 76%, 534336 KB, 3355 KB/s, 159 seconds passed
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 .. parsed-literal::
 
-    ... 76%, 534528 KB, 3355 KB/s, 159 seconds passed
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 .. parsed-literal::
 
-    ... 76%, 534720 KB, 3355 KB/s, 159 seconds passed
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 .. parsed-literal::
 
-    ... 76%, 534912 KB, 3355 KB/s, 159 seconds passed
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 .. parsed-literal::
 
-    ... 76%, 535072 KB, 3355 KB/s, 159 seconds passed
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 .. parsed-literal::
 
-    ... 76%, 535296 KB, 3355 KB/s, 159 seconds passed
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 .. parsed-literal::
 
-    ... 76%, 535456 KB, 3355 KB/s, 159 seconds passed
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 .. parsed-literal::
 
-    ... 77%, 535680 KB, 3355 KB/s, 159 seconds passed
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+... 76%, 530496 KB, 3675 KB/s, 144 seconds passed
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 .. parsed-literal::
 
-    ... 77%, 535808 KB, 3355 KB/s, 159 seconds passed
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+    ... 76%, 530560 KB, 3674 KB/s, 144 seconds passed
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+... 76%, 530656 KB, 3674 KB/s, 144 seconds passed
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+... 76%, 530720 KB, 3674 KB/s, 144 seconds passed
 
 .. parsed-literal::
 
-    ... 77%, 536064 KB, 3355 KB/s, 159 seconds passed
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+... 76%, 530880 KB, 3675 KB/s, 144 seconds passed
 
 .. parsed-literal::
 
-    ... 77%, 536192 KB, 3355 KB/s, 159 seconds passed
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-... 77%, 536288 KB, 3356 KB/s, 159 seconds passed
-... 77%, 536320 KB, 3356 KB/s, 159 seconds passed
-... 77%, 536352 KB, 3356 KB/s, 159 seconds passed
-... 77%, 536384 KB, 3356 KB/s, 159 seconds passed
-... 77%, 536416 KB, 3356 KB/s, 159 seconds passed
+    ... 76%, 530912 KB, 3674 KB/s, 144 seconds passed
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+... 76%, 531104 KB, 3674 KB/s, 144 seconds passed
 
 .. parsed-literal::
 
-    ... 77%, 536448 KB, 3356 KB/s, 159 seconds passed
-... 77%, 536480 KB, 3356 KB/s, 159 seconds passed
-... 77%, 536512 KB, 3356 KB/s, 159 seconds passed
-... 77%, 536544 KB, 3356 KB/s, 159 seconds passed
+    ... 76%, 531136 KB, 3675 KB/s, 144 seconds passed
+... 76%, 531168 KB, 3674 KB/s, 144 seconds passed
+... 76%, 531200 KB, 3674 KB/s, 144 seconds passed
+... 76%, 531232 KB, 3674 KB/s, 144 seconds passed
+... 76%, 531264 KB, 3675 KB/s, 144 seconds passed
 
 .. parsed-literal::
 
-    ... 77%, 536576 KB, 3356 KB/s, 159 seconds passed
-... 77%, 536608 KB, 3356 KB/s, 159 seconds passed
-... 77%, 536640 KB, 3356 KB/s, 159 seconds passed
-... 77%, 536672 KB, 3356 KB/s, 159 seconds passed
-... 77%, 536704 KB, 3356 KB/s, 159 seconds passed
-... 77%, 536736 KB, 3356 KB/s, 159 seconds passed
-... 77%, 536768 KB, 3356 KB/s, 159 seconds passed
-... 77%, 536800 KB, 3356 KB/s, 159 seconds passed
+    ... 76%, 531296 KB, 3674 KB/s, 144 seconds passed
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+... 76%, 531360 KB, 3674 KB/s, 144 seconds passed
+... 76%, 531392 KB, 3675 KB/s, 144 seconds passed
+... 76%, 531424 KB, 3674 KB/s, 144 seconds passed
+... 76%, 531456 KB, 3674 KB/s, 144 seconds passed
 
 .. parsed-literal::
 
-    ... 77%, 536832 KB, 3356 KB/s, 159 seconds passed
-... 77%, 536864 KB, 3356 KB/s, 159 seconds passed
-... 77%, 536896 KB, 3356 KB/s, 159 seconds passed
-... 77%, 536928 KB, 3356 KB/s, 159 seconds passed
+    ... 76%, 531488 KB, 3674 KB/s, 144 seconds passed
+... 76%, 531520 KB, 3675 KB/s, 144 seconds passed
+... 76%, 531552 KB, 3674 KB/s, 144 seconds passed
+... 76%, 531584 KB, 3674 KB/s, 144 seconds passed
+... 76%, 531616 KB, 3674 KB/s, 144 seconds passed
+... 76%, 531648 KB, 3675 KB/s, 144 seconds passed
 
 .. parsed-literal::
 
-    ... 77%, 536960 KB, 3356 KB/s, 159 seconds passed
-... 77%, 536992 KB, 3356 KB/s, 159 seconds passed
-... 77%, 537024 KB, 3356 KB/s, 159 seconds passed
-... 77%, 537056 KB, 3356 KB/s, 159 seconds passed
-... 77%, 537088 KB, 3356 KB/s, 160 seconds passed
-... 77%, 537120 KB, 3356 KB/s, 160 seconds passed
-... 77%, 537152 KB, 3356 KB/s, 160 seconds passed
-... 77%, 537184 KB, 3356 KB/s, 160 seconds passed
+    ... 76%, 531680 KB, 3674 KB/s, 144 seconds passed
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+... 76%, 531744 KB, 3674 KB/s, 144 seconds passed
+... 76%, 531776 KB, 3675 KB/s, 144 seconds passed
+... 76%, 531808 KB, 3674 KB/s, 144 seconds passed
+... 76%, 531840 KB, 3674 KB/s, 144 seconds passed
 
 .. parsed-literal::
 
-    ... 77%, 537216 KB, 3356 KB/s, 160 seconds passed
-... 77%, 537248 KB, 3356 KB/s, 160 seconds passed
-... 77%, 537280 KB, 3356 KB/s, 160 seconds passed
-... 77%, 537312 KB, 3356 KB/s, 160 seconds passed
+    ... 76%, 531872 KB, 3674 KB/s, 144 seconds passed
+... 76%, 531904 KB, 3675 KB/s, 144 seconds passed
+... 76%, 531936 KB, 3674 KB/s, 144 seconds passed
+... 76%, 531968 KB, 3674 KB/s, 144 seconds passed
+... 76%, 532000 KB, 3674 KB/s, 144 seconds passed
+... 76%, 532032 KB, 3675 KB/s, 144 seconds passed
 
 .. parsed-literal::
 
-    ... 77%, 537344 KB, 3356 KB/s, 160 seconds passed
-... 77%, 537376 KB, 3356 KB/s, 160 seconds passed
-... 77%, 537408 KB, 3356 KB/s, 160 seconds passed
-... 77%, 537440 KB, 3356 KB/s, 160 seconds passed
-... 77%, 537472 KB, 3356 KB/s, 160 seconds passed
-... 77%, 537504 KB, 3356 KB/s, 160 seconds passed
-... 77%, 537536 KB, 3357 KB/s, 160 seconds passed
+    ... 76%, 532064 KB, 3674 KB/s, 144 seconds passed
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+... 76%, 532128 KB, 3674 KB/s, 144 seconds passed
+... 76%, 532160 KB, 3674 KB/s, 144 seconds passed
+... 76%, 532192 KB, 3674 KB/s, 144 seconds passed
+... 76%, 532224 KB, 3674 KB/s, 144 seconds passed
 
 .. parsed-literal::
 
-    ... 77%, 537568 KB, 3357 KB/s, 160 seconds passed
-... 77%, 537600 KB, 3356 KB/s, 160 seconds passed
-... 77%, 537632 KB, 3356 KB/s, 160 seconds passed
-... 77%, 537664 KB, 3357 KB/s, 160 seconds passed
-... 77%, 537696 KB, 3357 KB/s, 160 seconds passed
+    ... 76%, 532256 KB, 3674 KB/s, 144 seconds passed
+... 76%, 532288 KB, 3675 KB/s, 144 seconds passed
+... 76%, 532320 KB, 3674 KB/s, 144 seconds passed
+... 76%, 532352 KB, 3674 KB/s, 144 seconds passed
+... 76%, 532384 KB, 3674 KB/s, 144 seconds passed
+... 76%, 532416 KB, 3675 KB/s, 144 seconds passed
 
 .. parsed-literal::
 
-    ... 77%, 537728 KB, 3356 KB/s, 160 seconds passed
-... 77%, 537760 KB, 3357 KB/s, 160 seconds passed
-... 77%, 537792 KB, 3357 KB/s, 160 seconds passed
-... 77%, 537824 KB, 3357 KB/s, 160 seconds passed
-... 77%, 537856 KB, 3356 KB/s, 160 seconds passed
-... 77%, 537888 KB, 3357 KB/s, 160 seconds passed
-... 77%, 537920 KB, 3357 KB/s, 160 seconds passed
+    ... 76%, 532448 KB, 3674 KB/s, 144 seconds passed
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+... 76%, 532512 KB, 3674 KB/s, 144 seconds passed
+... 76%, 532544 KB, 3675 KB/s, 144 seconds passed
+... 76%, 532576 KB, 3674 KB/s, 144 seconds passed
+... 76%, 532608 KB, 3674 KB/s, 144 seconds passed
 
 .. parsed-literal::
 
-    ... 77%, 537952 KB, 3357 KB/s, 160 seconds passed
-... 77%, 537984 KB, 3357 KB/s, 160 seconds passed
-... 77%, 538016 KB, 3357 KB/s, 160 seconds passed
-... 77%, 538048 KB, 3357 KB/s, 160 seconds passed
-... 77%, 538080 KB, 3357 KB/s, 160 seconds passed
+    ... 76%, 532640 KB, 3674 KB/s, 144 seconds passed
+... 76%, 532672 KB, 3674 KB/s, 144 seconds passed
+... 76%, 532704 KB, 3674 KB/s, 144 seconds passed
+... 76%, 532736 KB, 3674 KB/s, 144 seconds passed
+... 76%, 532768 KB, 3674 KB/s, 144 seconds passed
+... 76%, 532800 KB, 3674 KB/s, 144 seconds passed
 
 .. parsed-literal::
 
-    ... 77%, 538112 KB, 3357 KB/s, 160 seconds passed
-... 77%, 538144 KB, 3357 KB/s, 160 seconds passed
-... 77%, 538176 KB, 3357 KB/s, 160 seconds passed
-... 77%, 538208 KB, 3357 KB/s, 160 seconds passed
-... 77%, 538240 KB, 3357 KB/s, 160 seconds passed
-... 77%, 538272 KB, 3357 KB/s, 160 seconds passed
-... 77%, 538304 KB, 3357 KB/s, 160 seconds passed
+    ... 76%, 532832 KB, 3674 KB/s, 144 seconds passed
+... 76%, 532864 KB, 3674 KB/s, 144 seconds passed
+... 76%, 532896 KB, 3674 KB/s, 145 seconds passed
+... 76%, 532928 KB, 3674 KB/s, 145 seconds passed
+... 76%, 532960 KB, 3674 KB/s, 145 seconds passed
+... 76%, 532992 KB, 3674 KB/s, 145 seconds passed
 
 .. parsed-literal::
 
-    ... 77%, 538336 KB, 3357 KB/s, 160 seconds passed
-... 77%, 538368 KB, 3357 KB/s, 160 seconds passed
-... 77%, 538400 KB, 3357 KB/s, 160 seconds passed
-... 77%, 538432 KB, 3357 KB/s, 160 seconds passed
-... 77%, 538464 KB, 3357 KB/s, 160 seconds passed
+    ... 76%, 533024 KB, 3675 KB/s, 145 seconds passed
+... 76%, 533056 KB, 3674 KB/s, 145 seconds passed
+... 76%, 533088 KB, 3674 KB/s, 145 seconds passed
+... 76%, 533120 KB, 3674 KB/s, 145 seconds passed
+... 76%, 533152 KB, 3675 KB/s, 145 seconds passed
+... 76%, 533184 KB, 3674 KB/s, 145 seconds passed
 
 .. parsed-literal::
 
-    ... 77%, 538496 KB, 3357 KB/s, 160 seconds passed
-... 77%, 538528 KB, 3357 KB/s, 160 seconds passed
-... 77%, 538560 KB, 3357 KB/s, 160 seconds passed
-... 77%, 538592 KB, 3357 KB/s, 160 seconds passed
-... 77%, 538624 KB, 3357 KB/s, 160 seconds passed
-... 77%, 538656 KB, 3357 KB/s, 160 seconds passed
-... 77%, 538688 KB, 3357 KB/s, 160 seconds passed
+    ... 76%, 533216 KB, 3674 KB/s, 145 seconds passed
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+... 76%, 533280 KB, 3675 KB/s, 145 seconds passed
+... 76%, 533312 KB, 3674 KB/s, 145 seconds passed
+... 76%, 533344 KB, 3674 KB/s, 145 seconds passed
+... 76%, 533376 KB, 3674 KB/s, 145 seconds passed
 
 .. parsed-literal::
 
-    ... 77%, 538720 KB, 3357 KB/s, 160 seconds passed
-... 77%, 538752 KB, 3357 KB/s, 160 seconds passed
-... 77%, 538784 KB, 3357 KB/s, 160 seconds passed
-... 77%, 538816 KB, 3357 KB/s, 160 seconds passed
-... 77%, 538848 KB, 3357 KB/s, 160 seconds passed
+    ... 76%, 533408 KB, 3675 KB/s, 145 seconds passed
+... 76%, 533440 KB, 3674 KB/s, 145 seconds passed
+... 76%, 533472 KB, 3674 KB/s, 145 seconds passed
+... 76%, 533504 KB, 3675 KB/s, 145 seconds passed
+... 76%, 533536 KB, 3675 KB/s, 145 seconds passed
 
 .. parsed-literal::
 
-    ... 77%, 538880 KB, 3357 KB/s, 160 seconds passed
-... 77%, 538912 KB, 3357 KB/s, 160 seconds passed
-... 77%, 538944 KB, 3357 KB/s, 160 seconds passed
-... 77%, 538976 KB, 3357 KB/s, 160 seconds passed
-... 77%, 539008 KB, 3357 KB/s, 160 seconds passed
-... 77%, 539040 KB, 3357 KB/s, 160 seconds passed
+    ... 76%, 533568 KB, 3674 KB/s, 145 seconds passed
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+... 76%, 533664 KB, 3675 KB/s, 145 seconds passed
+... 76%, 533696 KB, 3674 KB/s, 145 seconds passed
+... 76%, 533728 KB, 3674 KB/s, 145 seconds passed
 
 .. parsed-literal::
 
-    ... 77%, 539072 KB, 3357 KB/s, 160 seconds passed
-... 77%, 539104 KB, 3357 KB/s, 160 seconds passed
-... 77%, 539136 KB, 3357 KB/s, 160 seconds passed
-... 77%, 539168 KB, 3357 KB/s, 160 seconds passed
-... 77%, 539200 KB, 3357 KB/s, 160 seconds passed
-... 77%, 539232 KB, 3357 KB/s, 160 seconds passed
+    ... 76%, 533760 KB, 3674 KB/s, 145 seconds passed
+... 76%, 533792 KB, 3675 KB/s, 145 seconds passed
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+... 76%, 533856 KB, 3674 KB/s, 145 seconds passed
+... 76%, 533888 KB, 3674 KB/s, 145 seconds passed
+... 76%, 533920 KB, 3675 KB/s, 145 seconds passed
 
 .. parsed-literal::
 
-    ... 77%, 539264 KB, 3357 KB/s, 160 seconds passed
-... 77%, 539296 KB, 3357 KB/s, 160 seconds passed
-... 77%, 539328 KB, 3358 KB/s, 160 seconds passed
-... 77%, 539360 KB, 3358 KB/s, 160 seconds passed
-... 77%, 539392 KB, 3357 KB/s, 160 seconds passed
-... 77%, 539424 KB, 3357 KB/s, 160 seconds passed
+    ... 76%, 533952 KB, 3674 KB/s, 145 seconds passed
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+... 76%, 534048 KB, 3675 KB/s, 145 seconds passed
+... 76%, 534080 KB, 3674 KB/s, 145 seconds passed
+... 76%, 534112 KB, 3674 KB/s, 145 seconds passed
 
 .. parsed-literal::
 
-    ... 77%, 539456 KB, 3358 KB/s, 160 seconds passed
-... 77%, 539488 KB, 3358 KB/s, 160 seconds passed
-... 77%, 539520 KB, 3357 KB/s, 160 seconds passed
-... 77%, 539552 KB, 3358 KB/s, 160 seconds passed
-... 77%, 539584 KB, 3358 KB/s, 160 seconds passed
+    ... 76%, 534144 KB, 3675 KB/s, 145 seconds passed
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+... 76%, 534208 KB, 3675 KB/s, 145 seconds passed
+... 76%, 534240 KB, 3674 KB/s, 145 seconds passed
+... 76%, 534272 KB, 3674 KB/s, 145 seconds passed
+... 76%, 534304 KB, 3675 KB/s, 145 seconds passed
 
 .. parsed-literal::
 
-    ... 77%, 539616 KB, 3357 KB/s, 160 seconds passed
-... 77%, 539648 KB, 3358 KB/s, 160 seconds passed
-... 77%, 539680 KB, 3358 KB/s, 160 seconds passed
-... 77%, 539712 KB, 3358 KB/s, 160 seconds passed
-... 77%, 539744 KB, 3358 KB/s, 160 seconds passed
-... 77%, 539776 KB, 3358 KB/s, 160 seconds passed
-... 77%, 539808 KB, 3358 KB/s, 160 seconds passed
+    ... 76%, 534336 KB, 3674 KB/s, 145 seconds passed
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+... 76%, 534432 KB, 3675 KB/s, 145 seconds passed
+... 76%, 534464 KB, 3674 KB/s, 145 seconds passed
+... 76%, 534496 KB, 3674 KB/s, 145 seconds passed
 
 .. parsed-literal::
 
-    ... 77%, 539840 KB, 3358 KB/s, 160 seconds passed
-... 77%, 539872 KB, 3358 KB/s, 160 seconds passed
-... 77%, 539904 KB, 3358 KB/s, 160 seconds passed
-... 77%, 539936 KB, 3358 KB/s, 160 seconds passed
-... 77%, 539968 KB, 3358 KB/s, 160 seconds passed
+    ... 76%, 534528 KB, 3674 KB/s, 145 seconds passed
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+... 76%, 534592 KB, 3674 KB/s, 145 seconds passed
+... 76%, 534624 KB, 3674 KB/s, 145 seconds passed
+... 76%, 534656 KB, 3674 KB/s, 145 seconds passed
+... 76%, 534688 KB, 3675 KB/s, 145 seconds passed
 
 .. parsed-literal::
 
-    ... 77%, 540000 KB, 3358 KB/s, 160 seconds passed
-... 77%, 540032 KB, 3358 KB/s, 160 seconds passed
-... 77%, 540064 KB, 3358 KB/s, 160 seconds passed
-... 77%, 540096 KB, 3358 KB/s, 160 seconds passed
-... 77%, 540128 KB, 3358 KB/s, 160 seconds passed
-... 77%, 540160 KB, 3358 KB/s, 160 seconds passed
+    ... 76%, 534720 KB, 3674 KB/s, 145 seconds passed
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+... 76%, 534816 KB, 3675 KB/s, 145 seconds passed
+... 76%, 534848 KB, 3674 KB/s, 145 seconds passed
+... 76%, 534880 KB, 3674 KB/s, 145 seconds passed
 
 .. parsed-literal::
 
-    ... 77%, 540192 KB, 3358 KB/s, 160 seconds passed
-... 77%, 540224 KB, 3358 KB/s, 160 seconds passed
-... 77%, 540256 KB, 3358 KB/s, 160 seconds passed
-... 77%, 540288 KB, 3358 KB/s, 160 seconds passed
-... 77%, 540320 KB, 3358 KB/s, 160 seconds passed
-... 77%, 540352 KB, 3358 KB/s, 160 seconds passed
+    ... 76%, 534912 KB, 3675 KB/s, 145 seconds passed
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+... 76%, 534976 KB, 3674 KB/s, 145 seconds passed
+... 76%, 535008 KB, 3674 KB/s, 145 seconds passed
+... 76%, 535040 KB, 3675 KB/s, 145 seconds passed
+... 76%, 535072 KB, 3675 KB/s, 145 seconds passed
 
 .. parsed-literal::
 
-    ... 77%, 540384 KB, 3358 KB/s, 160 seconds passed
-... 77%, 540416 KB, 3358 KB/s, 160 seconds passed
-... 77%, 540448 KB, 3358 KB/s, 160 seconds passed
-... 77%, 540480 KB, 3358 KB/s, 160 seconds passed
-... 77%, 540512 KB, 3358 KB/s, 160 seconds passed
-... 77%, 540544 KB, 3358 KB/s, 160 seconds passed
+    ... 76%, 535104 KB, 3674 KB/s, 145 seconds passed
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+... 76%, 535200 KB, 3675 KB/s, 145 seconds passed
+... 76%, 535232 KB, 3674 KB/s, 145 seconds passed
+... 76%, 535264 KB, 3675 KB/s, 145 seconds passed
 
 .. parsed-literal::
 
-    ... 77%, 540576 KB, 3358 KB/s, 160 seconds passed
-... 77%, 540608 KB, 3358 KB/s, 160 seconds passed
-... 77%, 540640 KB, 3358 KB/s, 160 seconds passed
-... 77%, 540672 KB, 3358 KB/s, 160 seconds passed
-... 77%, 540704 KB, 3358 KB/s, 160 seconds passed
-... 77%, 540736 KB, 3358 KB/s, 160 seconds passed
+    ... 76%, 535296 KB, 3675 KB/s, 145 seconds passed
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+... 76%, 535392 KB, 3674 KB/s, 145 seconds passed
+... 76%, 535424 KB, 3675 KB/s, 145 seconds passed
+... 76%, 535456 KB, 3675 KB/s, 145 seconds passed
 
 .. parsed-literal::
 
-    ... 77%, 540768 KB, 3358 KB/s, 161 seconds passed
-... 77%, 540800 KB, 3358 KB/s, 161 seconds passed
-... 77%, 540832 KB, 3358 KB/s, 161 seconds passed
-... 77%, 540864 KB, 3358 KB/s, 161 seconds passed
-... 77%, 540896 KB, 3358 KB/s, 161 seconds passed
-... 77%, 540928 KB, 3358 KB/s, 161 seconds passed
+    ... 76%, 535488 KB, 3674 KB/s, 145 seconds passed
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+... 77%, 535552 KB, 3675 KB/s, 145 seconds passed
+... 77%, 535584 KB, 3675 KB/s, 145 seconds passed
+... 77%, 535616 KB, 3674 KB/s, 145 seconds passed
 
 .. parsed-literal::
 
-    ... 77%, 540960 KB, 3358 KB/s, 161 seconds passed
-... 77%, 540992 KB, 3358 KB/s, 161 seconds passed
-... 77%, 541024 KB, 3358 KB/s, 161 seconds passed
-... 77%, 541056 KB, 3358 KB/s, 161 seconds passed
-... 77%, 541088 KB, 3358 KB/s, 161 seconds passed
-... 77%, 541120 KB, 3358 KB/s, 161 seconds passed
+    ... 77%, 535648 KB, 3675 KB/s, 145 seconds passed
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+... 77%, 535776 KB, 3675 KB/s, 145 seconds passed
+... 77%, 535808 KB, 3675 KB/s, 145 seconds passed
+... 77%, 535840 KB, 3675 KB/s, 145 seconds passed
 
 .. parsed-literal::
 
-    ... 77%, 541152 KB, 3358 KB/s, 161 seconds passed
-... 77%, 541184 KB, 3358 KB/s, 161 seconds passed
-... 77%, 541216 KB, 3358 KB/s, 161 seconds passed
-... 77%, 541248 KB, 3359 KB/s, 161 seconds passed
-... 77%, 541280 KB, 3358 KB/s, 161 seconds passed
-... 77%, 541312 KB, 3358 KB/s, 161 seconds passed
+    ... 77%, 535872 KB, 3675 KB/s, 145 seconds passed
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+... 77%, 535936 KB, 3675 KB/s, 145 seconds passed
+... 77%, 535968 KB, 3675 KB/s, 145 seconds passed
+... 77%, 536000 KB, 3675 KB/s, 145 seconds passed
 
 .. parsed-literal::
 
-    ... 77%, 541344 KB, 3359 KB/s, 161 seconds passed
-... 77%, 541376 KB, 3359 KB/s, 161 seconds passed
-... 77%, 541408 KB, 3358 KB/s, 161 seconds passed
-... 77%, 541440 KB, 3359 KB/s, 161 seconds passed
-... 77%, 541472 KB, 3359 KB/s, 161 seconds passed
-... 77%, 541504 KB, 3359 KB/s, 161 seconds passed
+    ... 77%, 536032 KB, 3675 KB/s, 145 seconds passed
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+... 77%, 536128 KB, 3675 KB/s, 145 seconds passed
+... 77%, 536160 KB, 3675 KB/s, 145 seconds passed
+... 77%, 536192 KB, 3675 KB/s, 145 seconds passed
+... 77%, 536224 KB, 3675 KB/s, 145 seconds passed
 
 .. parsed-literal::
 
-    ... 77%, 541536 KB, 3359 KB/s, 161 seconds passed
-... 77%, 541568 KB, 3359 KB/s, 161 seconds passed
-... 77%, 541600 KB, 3359 KB/s, 161 seconds passed
-... 77%, 541632 KB, 3359 KB/s, 161 seconds passed
-... 77%, 541664 KB, 3359 KB/s, 161 seconds passed
+    ... 77%, 536256 KB, 3675 KB/s, 145 seconds passed
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+... 77%, 536320 KB, 3675 KB/s, 145 seconds passed
+... 77%, 536352 KB, 3675 KB/s, 145 seconds passed
+... 77%, 536384 KB, 3675 KB/s, 145 seconds passed
 
 .. parsed-literal::
 
-    ... 77%, 541696 KB, 3359 KB/s, 161 seconds passed
-... 77%, 541728 KB, 3359 KB/s, 161 seconds passed
-... 77%, 541760 KB, 3359 KB/s, 161 seconds passed
-... 77%, 541792 KB, 3359 KB/s, 161 seconds passed
-... 77%, 541824 KB, 3359 KB/s, 161 seconds passed
-... 77%, 541856 KB, 3359 KB/s, 161 seconds passed
-... 77%, 541888 KB, 3359 KB/s, 161 seconds passed
+    ... 77%, 536416 KB, 3675 KB/s, 145 seconds passed
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+... 77%, 536480 KB, 3675 KB/s, 145 seconds passed
+... 77%, 536512 KB, 3675 KB/s, 145 seconds passed
+... 77%, 536544 KB, 3675 KB/s, 145 seconds passed
+... 77%, 536576 KB, 3675 KB/s, 146 seconds passed
+... 77%, 536608 KB, 3675 KB/s, 146 seconds passed
 
 .. parsed-literal::
 
-    ... 77%, 541920 KB, 3359 KB/s, 161 seconds passed
-... 77%, 541952 KB, 3359 KB/s, 161 seconds passed
-... 77%, 541984 KB, 3359 KB/s, 161 seconds passed
-... 77%, 542016 KB, 3359 KB/s, 161 seconds passed
-... 77%, 542048 KB, 3359 KB/s, 161 seconds passed
+    ... 77%, 536640 KB, 3675 KB/s, 146 seconds passed
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+... 77%, 536704 KB, 3675 KB/s, 146 seconds passed
+... 77%, 536736 KB, 3675 KB/s, 146 seconds passed
+... 77%, 536768 KB, 3675 KB/s, 146 seconds passed
 
 .. parsed-literal::
 
-    ... 77%, 542080 KB, 3359 KB/s, 161 seconds passed
-... 77%, 542112 KB, 3359 KB/s, 161 seconds passed
-... 77%, 542144 KB, 3359 KB/s, 161 seconds passed
-... 77%, 542176 KB, 3359 KB/s, 161 seconds passed
-... 77%, 542208 KB, 3359 KB/s, 161 seconds passed
-... 77%, 542240 KB, 3359 KB/s, 161 seconds passed
-... 77%, 542272 KB, 3359 KB/s, 161 seconds passed
+    ... 77%, 536800 KB, 3675 KB/s, 146 seconds passed
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+... 77%, 536864 KB, 3675 KB/s, 146 seconds passed
+... 77%, 536896 KB, 3674 KB/s, 146 seconds passed
+... 77%, 536928 KB, 3675 KB/s, 146 seconds passed
+... 77%, 536960 KB, 3675 KB/s, 146 seconds passed
 
 .. parsed-literal::
 
-    ... 77%, 542304 KB, 3359 KB/s, 161 seconds passed
-... 77%, 542336 KB, 3359 KB/s, 161 seconds passed
-... 77%, 542368 KB, 3359 KB/s, 161 seconds passed
-... 77%, 542400 KB, 3359 KB/s, 161 seconds passed
-... 77%, 542432 KB, 3359 KB/s, 161 seconds passed
+    ... 77%, 536992 KB, 3675 KB/s, 146 seconds passed
+... 77%, 537024 KB, 3674 KB/s, 146 seconds passed
+... 77%, 537056 KB, 3675 KB/s, 146 seconds passed
+... 77%, 537088 KB, 3675 KB/s, 146 seconds passed
+... 77%, 537120 KB, 3675 KB/s, 146 seconds passed
 
 .. parsed-literal::
 
-    ... 77%, 542464 KB, 3359 KB/s, 161 seconds passed
-... 78%, 542496 KB, 3359 KB/s, 161 seconds passed
-... 78%, 542528 KB, 3359 KB/s, 161 seconds passed
-... 78%, 542560 KB, 3359 KB/s, 161 seconds passed
-... 78%, 542592 KB, 3359 KB/s, 161 seconds passed
-... 78%, 542624 KB, 3359 KB/s, 161 seconds passed
-... 78%, 542656 KB, 3359 KB/s, 161 seconds passed
+    ... 77%, 537152 KB, 3674 KB/s, 146 seconds passed
+... 77%, 537184 KB, 3675 KB/s, 146 seconds passed
+... 77%, 537216 KB, 3675 KB/s, 146 seconds passed
+... 77%, 537248 KB, 3675 KB/s, 146 seconds passed
+... 77%, 537280 KB, 3675 KB/s, 146 seconds passed
+... 77%, 537312 KB, 3675 KB/s, 146 seconds passed
+... 77%, 537344 KB, 3675 KB/s, 146 seconds passed
 
 .. parsed-literal::
 
-    ... 78%, 542688 KB, 3359 KB/s, 161 seconds passed
-... 78%, 542720 KB, 3359 KB/s, 161 seconds passed
-... 78%, 542752 KB, 3359 KB/s, 161 seconds passed
-... 78%, 542784 KB, 3359 KB/s, 161 seconds passed
+    ... 77%, 537376 KB, 3675 KB/s, 146 seconds passed
+... 77%, 537408 KB, 3675 KB/s, 146 seconds passed
+... 77%, 537440 KB, 3675 KB/s, 146 seconds passed
+... 77%, 537472 KB, 3675 KB/s, 146 seconds passed
+... 77%, 537504 KB, 3675 KB/s, 146 seconds passed
 
 .. parsed-literal::
 
-    ... 78%, 542816 KB, 3359 KB/s, 161 seconds passed
-... 78%, 542848 KB, 3359 KB/s, 161 seconds passed
-... 78%, 542880 KB, 3359 KB/s, 161 seconds passed
-... 78%, 542912 KB, 3359 KB/s, 161 seconds passed
-... 78%, 542944 KB, 3359 KB/s, 161 seconds passed
-... 78%, 542976 KB, 3359 KB/s, 161 seconds passed
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 .. parsed-literal::
 
-    ... 78%, 543040 KB, 3359 KB/s, 161 seconds passed
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 .. parsed-literal::
 
-    ... 78%, 543200 KB, 3359 KB/s, 161 seconds passed
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 .. parsed-literal::
 
-    ... 78%, 543424 KB, 3360 KB/s, 161 seconds passed
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 .. parsed-literal::
 
-    ... 78%, 543584 KB, 3360 KB/s, 161 seconds passed
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 .. parsed-literal::
 
-    ... 78%, 543808 KB, 3360 KB/s, 161 seconds passed
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 .. parsed-literal::
 
-    ... 78%, 543968 KB, 3360 KB/s, 161 seconds passed
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 .. parsed-literal::
 
-    ... 78%, 544160 KB, 3360 KB/s, 161 seconds passed
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 .. parsed-literal::
 
-    ... 78%, 544352 KB, 3360 KB/s, 161 seconds passed
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 .. parsed-literal::
 
-    ... 78%, 544544 KB, 3360 KB/s, 162 seconds passed
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 .. parsed-literal::
 
-    ... 78%, 544704 KB, 3360 KB/s, 162 seconds passed
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 .. parsed-literal::
 
-    ... 78%, 544928 KB, 3361 KB/s, 162 seconds passed
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 .. parsed-literal::
 
-    ... 78%, 545088 KB, 3360 KB/s, 162 seconds passed
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 .. parsed-literal::
 
-    ... 78%, 545312 KB, 3361 KB/s, 162 seconds passed
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 .. parsed-literal::
 
-    ... 78%, 545472 KB, 3361 KB/s, 162 seconds passed
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 .. parsed-literal::
 
-    ... 78%, 545664 KB, 3361 KB/s, 162 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 78%, 547200 KB, 3362 KB/s, 162 seconds passed
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 .. parsed-literal::
 
-    ... 78%, 547360 KB, 3362 KB/s, 162 seconds passed
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 .. parsed-literal::
 
-    ... 78%, 547552 KB, 3362 KB/s, 162 seconds passed
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 .. parsed-literal::
 
-    ... 78%, 547744 KB, 3362 KB/s, 162 seconds passed
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 .. parsed-literal::
 
-    ... 78%, 547936 KB, 3362 KB/s, 162 seconds passed
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 .. parsed-literal::
 
-    ... 78%, 548128 KB, 3362 KB/s, 163 seconds passed
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 .. parsed-literal::
 
-    ... 78%, 548320 KB, 3362 KB/s, 163 seconds passed
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 .. parsed-literal::
 
-    ... 78%, 548512 KB, 3362 KB/s, 163 seconds passed
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 .. parsed-literal::
 
-    ... 78%, 548704 KB, 3362 KB/s, 163 seconds passed
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 .. parsed-literal::
 
-    ... 78%, 548896 KB, 3363 KB/s, 163 seconds passed
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 .. parsed-literal::
 
-    ... 78%, 549088 KB, 3363 KB/s, 163 seconds passed
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 .. parsed-literal::
 
-    ... 78%, 549280 KB, 3363 KB/s, 163 seconds passed
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 .. parsed-literal::
 
-    ... 79%, 549472 KB, 3363 KB/s, 163 seconds passed
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 .. parsed-literal::
 
-    ... 79%, 549664 KB, 3363 KB/s, 163 seconds passed
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 .. parsed-literal::
 
-    ... 79%, 549824 KB, 3363 KB/s, 163 seconds passed
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 .. parsed-literal::
 
-    ... 79%, 550048 KB, 3363 KB/s, 163 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 79%, 550400 KB, 3363 KB/s, 163 seconds passed
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 .. parsed-literal::
 
-    ... 79%, 550592 KB, 3363 KB/s, 163 seconds passed
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 .. parsed-literal::
 
-    ... 79%, 550784 KB, 3364 KB/s, 163 seconds passed
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 .. parsed-literal::
 
-    ... 79%, 550976 KB, 3364 KB/s, 163 seconds passed
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 .. parsed-literal::
 
-    ... 79%, 551168 KB, 3364 KB/s, 163 seconds passed
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 .. parsed-literal::
 
-    ... 79%, 551360 KB, 3364 KB/s, 163 seconds passed
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 .. parsed-literal::
 
-    ... 79%, 551552 KB, 3364 KB/s, 163 seconds passed
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 .. parsed-literal::
 
-    ... 79%, 551744 KB, 3364 KB/s, 163 seconds passed
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 .. parsed-literal::
 
-    ... 79%, 551936 KB, 3364 KB/s, 164 seconds passed
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 .. parsed-literal::
 
-    ... 79%, 552128 KB, 3364 KB/s, 164 seconds passed
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 .. parsed-literal::
 
-    ... 79%, 552288 KB, 3364 KB/s, 164 seconds passed
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 .. parsed-literal::
 
-    ... 79%, 552480 KB, 3365 KB/s, 164 seconds passed
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 .. parsed-literal::
 
-    ... 79%, 552672 KB, 3365 KB/s, 164 seconds passed
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 .. parsed-literal::
 
-    ... 79%, 552864 KB, 3365 KB/s, 164 seconds passed
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 .. parsed-literal::
 
-    ... 79%, 553056 KB, 3365 KB/s, 164 seconds passed
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 .. parsed-literal::
 
-    ... 79%, 553248 KB, 3365 KB/s, 164 seconds passed
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 .. parsed-literal::
 
-    ... 79%, 553440 KB, 3365 KB/s, 164 seconds passed
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 .. parsed-literal::
 
-    ... 79%, 553632 KB, 3365 KB/s, 164 seconds passed
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 .. parsed-literal::
 
-    ... 79%, 553824 KB, 3365 KB/s, 164 seconds passed
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 .. parsed-literal::
 
-    ... 79%, 553984 KB, 3365 KB/s, 164 seconds passed
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 .. parsed-literal::
 
-    ... 79%, 554176 KB, 3365 KB/s, 164 seconds passed
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 .. parsed-literal::
 
-    ... 79%, 554368 KB, 3365 KB/s, 164 seconds passed
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 .. parsed-literal::
 
-    ... 79%, 554560 KB, 3366 KB/s, 164 seconds passed
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 .. parsed-literal::
 
-    ... 79%, 554752 KB, 3366 KB/s, 164 seconds passed
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 .. parsed-literal::
 
-    ... 79%, 554944 KB, 3366 KB/s, 164 seconds passed
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 .. parsed-literal::
 
-    ... 79%, 555136 KB, 3366 KB/s, 164 seconds passed
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 .. parsed-literal::
 
-    ... 79%, 555328 KB, 3366 KB/s, 164 seconds passed
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 .. parsed-literal::
 
-    ... 79%, 555520 KB, 3366 KB/s, 165 seconds passed
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+... 79%, 550400 KB, 3675 KB/s, 149 seconds passed
 
 .. parsed-literal::
 
-    ... 79%, 555712 KB, 3366 KB/s, 165 seconds passed
-... 79%, 555744 KB, 3366 KB/s, 165 seconds passed
-... 79%, 555776 KB, 3366 KB/s, 165 seconds passed
-... 79%, 555808 KB, 3366 KB/s, 165 seconds passed
-... 79%, 555840 KB, 3366 KB/s, 165 seconds passed
-... 79%, 555872 KB, 3366 KB/s, 165 seconds passed
+    ... 79%, 550432 KB, 3675 KB/s, 149 seconds passed
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+... 79%, 550528 KB, 3675 KB/s, 149 seconds passed
+... 79%, 550560 KB, 3675 KB/s, 149 seconds passed
+... 79%, 550592 KB, 3675 KB/s, 149 seconds passed
 
 .. parsed-literal::
 
-    ... 79%, 555904 KB, 3366 KB/s, 165 seconds passed
-... 79%, 555936 KB, 3366 KB/s, 165 seconds passed
-... 79%, 555968 KB, 3366 KB/s, 165 seconds passed
-... 79%, 556000 KB, 3366 KB/s, 165 seconds passed
-... 79%, 556032 KB, 3366 KB/s, 165 seconds passed
-... 79%, 556064 KB, 3366 KB/s, 165 seconds passed
+    ... 79%, 550624 KB, 3675 KB/s, 149 seconds passed
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+... 79%, 550688 KB, 3675 KB/s, 149 seconds passed
+... 79%, 550720 KB, 3675 KB/s, 149 seconds passed
+... 79%, 550752 KB, 3675 KB/s, 149 seconds passed
 
 .. parsed-literal::
 
-    ... 79%, 556096 KB, 3366 KB/s, 165 seconds passed
-... 79%, 556128 KB, 3366 KB/s, 165 seconds passed
-... 79%, 556160 KB, 3366 KB/s, 165 seconds passed
-... 79%, 556192 KB, 3367 KB/s, 165 seconds passed
-... 79%, 556224 KB, 3367 KB/s, 165 seconds passed
-... 79%, 556256 KB, 3367 KB/s, 165 seconds passed
+    ... 79%, 550784 KB, 3675 KB/s, 149 seconds passed
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+... 79%, 550912 KB, 3675 KB/s, 149 seconds passed
+... 79%, 550944 KB, 3675 KB/s, 149 seconds passed
+... 79%, 550976 KB, 3675 KB/s, 149 seconds passed
 
 .. parsed-literal::
 
-    ... 79%, 556288 KB, 3367 KB/s, 165 seconds passed
-... 79%, 556320 KB, 3367 KB/s, 165 seconds passed
-... 79%, 556352 KB, 3367 KB/s, 165 seconds passed
-... 79%, 556384 KB, 3367 KB/s, 165 seconds passed
-... 80%, 556416 KB, 3367 KB/s, 165 seconds passed
-... 80%, 556448 KB, 3367 KB/s, 165 seconds passed
+    ... 79%, 551008 KB, 3675 KB/s, 149 seconds passed
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+... 79%, 551072 KB, 3675 KB/s, 149 seconds passed
+... 79%, 551104 KB, 3675 KB/s, 149 seconds passed
+... 79%, 551136 KB, 3675 KB/s, 149 seconds passed
 
 .. parsed-literal::
 
-    ... 80%, 556480 KB, 3367 KB/s, 165 seconds passed
-... 80%, 556512 KB, 3367 KB/s, 165 seconds passed
-... 80%, 556544 KB, 3367 KB/s, 165 seconds passed
-... 80%, 556576 KB, 3367 KB/s, 165 seconds passed
-... 80%, 556608 KB, 3367 KB/s, 165 seconds passed
-... 80%, 556640 KB, 3367 KB/s, 165 seconds passed
+    ... 79%, 551168 KB, 3675 KB/s, 149 seconds passed
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+... 79%, 551264 KB, 3675 KB/s, 149 seconds passed
+... 79%, 551296 KB, 3675 KB/s, 149 seconds passed
+... 79%, 551328 KB, 3675 KB/s, 149 seconds passed
 
 .. parsed-literal::
 
-    ... 80%, 556672 KB, 3367 KB/s, 165 seconds passed
-... 80%, 556704 KB, 3367 KB/s, 165 seconds passed
-... 80%, 556736 KB, 3367 KB/s, 165 seconds passed
-... 80%, 556768 KB, 3367 KB/s, 165 seconds passed
-... 80%, 556800 KB, 3367 KB/s, 165 seconds passed
-... 80%, 556832 KB, 3367 KB/s, 165 seconds passed
+    ... 79%, 551360 KB, 3675 KB/s, 150 seconds passed
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+... 79%, 551456 KB, 3675 KB/s, 150 seconds passed
+... 79%, 551488 KB, 3675 KB/s, 150 seconds passed
+... 79%, 551520 KB, 3675 KB/s, 150 seconds passed
 
 .. parsed-literal::
 
-    ... 80%, 556864 KB, 3367 KB/s, 165 seconds passed
-... 80%, 556896 KB, 3367 KB/s, 165 seconds passed
-... 80%, 556928 KB, 3367 KB/s, 165 seconds passed
-... 80%, 556960 KB, 3367 KB/s, 165 seconds passed
-... 80%, 556992 KB, 3367 KB/s, 165 seconds passed
-... 80%, 557024 KB, 3367 KB/s, 165 seconds passed
+    ... 79%, 551552 KB, 3675 KB/s, 150 seconds passed
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+... 79%, 551680 KB, 3675 KB/s, 150 seconds passed
+... 79%, 551712 KB, 3675 KB/s, 150 seconds passed
+... 79%, 551744 KB, 3675 KB/s, 150 seconds passed
 
 .. parsed-literal::
 
-    ... 80%, 557056 KB, 3367 KB/s, 165 seconds passed
-... 80%, 557088 KB, 3367 KB/s, 165 seconds passed
-... 80%, 557120 KB, 3367 KB/s, 165 seconds passed
-... 80%, 557152 KB, 3367 KB/s, 165 seconds passed
-... 80%, 557184 KB, 3367 KB/s, 165 seconds passed
+    ... 79%, 551776 KB, 3675 KB/s, 150 seconds passed
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+... 79%, 551840 KB, 3675 KB/s, 150 seconds passed
+... 79%, 551872 KB, 3675 KB/s, 150 seconds passed
+... 79%, 551904 KB, 3675 KB/s, 150 seconds passed
 
 .. parsed-literal::
 
-    ... 80%, 557216 KB, 3367 KB/s, 165 seconds passed
-... 80%, 557248 KB, 3367 KB/s, 165 seconds passed
-... 80%, 557280 KB, 3367 KB/s, 165 seconds passed
-... 80%, 557312 KB, 3367 KB/s, 165 seconds passed
-... 80%, 557344 KB, 3367 KB/s, 165 seconds passed
-... 80%, 557376 KB, 3367 KB/s, 165 seconds passed
+    ... 79%, 551936 KB, 3675 KB/s, 150 seconds passed
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+... 79%, 552032 KB, 3675 KB/s, 150 seconds passed
+... 79%, 552064 KB, 3675 KB/s, 150 seconds passed
+... 79%, 552096 KB, 3675 KB/s, 150 seconds passed
 
 .. parsed-literal::
 
-    ... 80%, 557408 KB, 3367 KB/s, 165 seconds passed
-... 80%, 557440 KB, 3367 KB/s, 165 seconds passed
-... 80%, 557472 KB, 3367 KB/s, 165 seconds passed
-... 80%, 557504 KB, 3367 KB/s, 165 seconds passed
-... 80%, 557536 KB, 3367 KB/s, 165 seconds passed
-... 80%, 557568 KB, 3367 KB/s, 165 seconds passed
+    ... 79%, 552128 KB, 3675 KB/s, 150 seconds passed
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+... 79%, 552224 KB, 3675 KB/s, 150 seconds passed
+... 79%, 552256 KB, 3675 KB/s, 150 seconds passed
+... 79%, 552288 KB, 3675 KB/s, 150 seconds passed
 
 .. parsed-literal::
 
-    ... 80%, 557600 KB, 3367 KB/s, 165 seconds passed
-... 80%, 557632 KB, 3367 KB/s, 165 seconds passed
-... 80%, 557664 KB, 3367 KB/s, 165 seconds passed
-... 80%, 557696 KB, 3367 KB/s, 165 seconds passed
-... 80%, 557728 KB, 3367 KB/s, 165 seconds passed
-... 80%, 557760 KB, 3367 KB/s, 165 seconds passed
+    ... 79%, 552320 KB, 3675 KB/s, 150 seconds passed
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+... 79%, 552416 KB, 3675 KB/s, 150 seconds passed
+... 79%, 552448 KB, 3675 KB/s, 150 seconds passed
+... 79%, 552480 KB, 3675 KB/s, 150 seconds passed
 
 .. parsed-literal::
 
-    ... 80%, 557792 KB, 3367 KB/s, 165 seconds passed
-... 80%, 557824 KB, 3367 KB/s, 165 seconds passed
-... 80%, 557856 KB, 3367 KB/s, 165 seconds passed
-... 80%, 557888 KB, 3367 KB/s, 165 seconds passed
-... 80%, 557920 KB, 3367 KB/s, 165 seconds passed
-... 80%, 557952 KB, 3367 KB/s, 165 seconds passed
+    ... 79%, 552512 KB, 3675 KB/s, 150 seconds passed
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+... 79%, 552608 KB, 3675 KB/s, 150 seconds passed
+... 79%, 552640 KB, 3675 KB/s, 150 seconds passed
+... 79%, 552672 KB, 3675 KB/s, 150 seconds passed
 
 .. parsed-literal::
 
-    ... 80%, 557984 KB, 3367 KB/s, 165 seconds passed
-... 80%, 558016 KB, 3367 KB/s, 165 seconds passed
-... 80%, 558048 KB, 3368 KB/s, 165 seconds passed
-... 80%, 558080 KB, 3367 KB/s, 165 seconds passed
-... 80%, 558112 KB, 3368 KB/s, 165 seconds passed
-... 80%, 558144 KB, 3368 KB/s, 165 seconds passed
+    ... 79%, 552704 KB, 3675 KB/s, 150 seconds passed
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+... 79%, 552800 KB, 3675 KB/s, 150 seconds passed
+... 79%, 552832 KB, 3675 KB/s, 150 seconds passed
+... 79%, 552864 KB, 3675 KB/s, 150 seconds passed
 
 .. parsed-literal::
 
-    ... 80%, 558176 KB, 3368 KB/s, 165 seconds passed
-... 80%, 558208 KB, 3368 KB/s, 165 seconds passed
-... 80%, 558240 KB, 3368 KB/s, 165 seconds passed
-... 80%, 558272 KB, 3368 KB/s, 165 seconds passed
-... 80%, 558304 KB, 3368 KB/s, 165 seconds passed
-... 80%, 558336 KB, 3368 KB/s, 165 seconds passed
+    ... 79%, 552896 KB, 3675 KB/s, 150 seconds passed
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+... 79%, 553056 KB, 3675 KB/s, 150 seconds passed
 
 .. parsed-literal::
 
-    ... 80%, 558368 KB, 3368 KB/s, 165 seconds passed
-... 80%, 558400 KB, 3368 KB/s, 165 seconds passed
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-... 80%, 558464 KB, 3368 KB/s, 165 seconds passed
-... 80%, 558496 KB, 3368 KB/s, 165 seconds passed
-... 80%, 558528 KB, 3368 KB/s, 165 seconds passed
+    ... 79%, 553088 KB, 3675 KB/s, 150 seconds passed
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+... 79%, 553248 KB, 3675 KB/s, 150 seconds passed
 
 .. parsed-literal::
 
-    ... 80%, 558560 KB, 3368 KB/s, 165 seconds passed
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-... 80%, 558656 KB, 3368 KB/s, 165 seconds passed
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-... 80%, 558720 KB, 3368 KB/s, 165 seconds passed
+    ... 79%, 553280 KB, 3675 KB/s, 150 seconds passed
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+... 79%, 553408 KB, 3675 KB/s, 150 seconds passed
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 .. parsed-literal::
 
-    ... 80%, 558752 KB, 3368 KB/s, 165 seconds passed
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-... 80%, 558880 KB, 3368 KB/s, 165 seconds passed
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+    ... 79%, 553472 KB, 3675 KB/s, 150 seconds passed
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+... 79%, 553600 KB, 3675 KB/s, 150 seconds passed
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 .. parsed-literal::
 
-    ... 80%, 558944 KB, 3368 KB/s, 165 seconds passed
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-... 80%, 559072 KB, 3368 KB/s, 165 seconds passed
-... 80%, 559104 KB, 3368 KB/s, 165 seconds passed
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 .. parsed-literal::
 
-    ... 80%, 559136 KB, 3368 KB/s, 165 seconds passed
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-... 80%, 559200 KB, 3368 KB/s, 166 seconds passed
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 .. parsed-literal::
 
-    ... 80%, 559328 KB, 3368 KB/s, 166 seconds passed
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 .. parsed-literal::
 
-    ... 80%, 559520 KB, 3368 KB/s, 166 seconds passed
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 .. parsed-literal::
 
-    ... 80%, 559712 KB, 3368 KB/s, 166 seconds passed
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 .. parsed-literal::
 
-    ... 80%, 559872 KB, 3368 KB/s, 166 seconds passed
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 .. parsed-literal::
 
-    ... 80%, 560064 KB, 3369 KB/s, 166 seconds passed
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 .. parsed-literal::
 
-    ... 80%, 560256 KB, 3369 KB/s, 166 seconds passed
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 .. parsed-literal::
 
-    ... 80%, 560448 KB, 3369 KB/s, 166 seconds passed
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-... 80%, 560608 KB, 3369 KB/s, 166 seconds passed
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 .. parsed-literal::
 
-    ... 80%, 560640 KB, 3369 KB/s, 166 seconds passed
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 .. parsed-literal::
 
-    ... 80%, 560832 KB, 3369 KB/s, 166 seconds passed
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 .. parsed-literal::
 
-    ... 80%, 560992 KB, 3369 KB/s, 166 seconds passed
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 .. parsed-literal::
 
-    ... 80%, 561216 KB, 3369 KB/s, 166 seconds passed
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 .. parsed-literal::
 
-    ... 80%, 561376 KB, 3369 KB/s, 166 seconds passed
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 .. parsed-literal::
 
-    ... 80%, 561568 KB, 3369 KB/s, 166 seconds passed
-... 80%, 561600 KB, 3369 KB/s, 166 seconds passed
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-... 80%, 561728 KB, 3369 KB/s, 166 seconds passed
+    ... 79%, 556256 KB, 3674 KB/s, 151 seconds passed
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 .. parsed-literal::
 
-    ... 80%, 561760 KB, 3369 KB/s, 166 seconds passed
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-... 80%, 561920 KB, 3370 KB/s, 166 seconds passed
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+... 80%, 556576 KB, 3675 KB/s, 151 seconds passed
+... 80%, 556608 KB, 3675 KB/s, 151 seconds passed
 
 .. parsed-literal::
 
-    ... 80%, 561952 KB, 3370 KB/s, 166 seconds passed
-... 80%, 561984 KB, 3370 KB/s, 166 seconds passed
-... 80%, 562016 KB, 3370 KB/s, 166 seconds passed
-... 80%, 562048 KB, 3370 KB/s, 166 seconds passed
-... 80%, 562080 KB, 3370 KB/s, 166 seconds passed
-... 80%, 562112 KB, 3370 KB/s, 166 seconds passed
+    ... 80%, 556640 KB, 3674 KB/s, 151 seconds passed
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+... 80%, 556704 KB, 3675 KB/s, 151 seconds passed
+... 80%, 556736 KB, 3675 KB/s, 151 seconds passed
 
 .. parsed-literal::
 
-    ... 80%, 562144 KB, 3370 KB/s, 166 seconds passed
-... 80%, 562176 KB, 3370 KB/s, 166 seconds passed
-... 80%, 562208 KB, 3370 KB/s, 166 seconds passed
-... 80%, 562240 KB, 3370 KB/s, 166 seconds passed
-... 80%, 562272 KB, 3370 KB/s, 166 seconds passed
-... 80%, 562304 KB, 3370 KB/s, 166 seconds passed
+    ... 80%, 556768 KB, 3674 KB/s, 151 seconds passed
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+... 80%, 556832 KB, 3675 KB/s, 151 seconds passed
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+... 80%, 556928 KB, 3675 KB/s, 151 seconds passed
+... 80%, 556960 KB, 3675 KB/s, 151 seconds passed
+... 80%, 556992 KB, 3675 KB/s, 151 seconds passed
 
 .. parsed-literal::
 
-    ... 80%, 562336 KB, 3370 KB/s, 166 seconds passed
-... 80%, 562368 KB, 3370 KB/s, 166 seconds passed
-... 80%, 562400 KB, 3370 KB/s, 166 seconds passed
-... 80%, 562432 KB, 3370 KB/s, 166 seconds passed
-... 80%, 562464 KB, 3370 KB/s, 166 seconds passed
-... 80%, 562496 KB, 3370 KB/s, 166 seconds passed
+    ... 80%, 557024 KB, 3674 KB/s, 151 seconds passed
+... 80%, 557056 KB, 3675 KB/s, 151 seconds passed
+... 80%, 557088 KB, 3675 KB/s, 151 seconds passed
+... 80%, 557120 KB, 3675 KB/s, 151 seconds passed
 
 .. parsed-literal::
 
-    ... 80%, 562528 KB, 3370 KB/s, 166 seconds passed
-... 80%, 562560 KB, 3370 KB/s, 166 seconds passed
-... 80%, 562592 KB, 3370 KB/s, 166 seconds passed
-... 80%, 562624 KB, 3370 KB/s, 166 seconds passed
-... 80%, 562656 KB, 3370 KB/s, 166 seconds passed
-... 80%, 562688 KB, 3370 KB/s, 166 seconds passed
+    ... 80%, 557152 KB, 3674 KB/s, 151 seconds passed
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+... 80%, 557280 KB, 3674 KB/s, 151 seconds passed
+... 80%, 557312 KB, 3675 KB/s, 151 seconds passed
+... 80%, 557344 KB, 3675 KB/s, 151 seconds passed
 
 .. parsed-literal::
 
-    ... 80%, 562720 KB, 3370 KB/s, 166 seconds passed
-... 80%, 562752 KB, 3370 KB/s, 166 seconds passed
-... 80%, 562784 KB, 3370 KB/s, 166 seconds passed
-... 80%, 562816 KB, 3370 KB/s, 166 seconds passed
-... 80%, 562848 KB, 3370 KB/s, 166 seconds passed
+    ... 80%, 557376 KB, 3674 KB/s, 151 seconds passed
+... 80%, 557408 KB, 3674 KB/s, 151 seconds passed
+... 80%, 557440 KB, 3675 KB/s, 151 seconds passed
+... 80%, 557472 KB, 3675 KB/s, 151 seconds passed
 
 .. parsed-literal::
 
-    ... 80%, 562880 KB, 3370 KB/s, 167 seconds passed
-... 80%, 562912 KB, 3370 KB/s, 167 seconds passed
-... 80%, 562944 KB, 3370 KB/s, 167 seconds passed
-... 80%, 562976 KB, 3370 KB/s, 167 seconds passed
-... 80%, 563008 KB, 3370 KB/s, 167 seconds passed
-... 80%, 563040 KB, 3370 KB/s, 167 seconds passed
+    ... 80%, 557504 KB, 3674 KB/s, 151 seconds passed
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+... 80%, 557664 KB, 3674 KB/s, 151 seconds passed
+... 80%, 557696 KB, 3675 KB/s, 151 seconds passed
+... 80%, 557728 KB, 3675 KB/s, 151 seconds passed
 
 .. parsed-literal::
 
-    ... 80%, 563072 KB, 3370 KB/s, 167 seconds passed
-... 80%, 563104 KB, 3370 KB/s, 167 seconds passed
-... 80%, 563136 KB, 3370 KB/s, 167 seconds passed
-... 80%, 563168 KB, 3370 KB/s, 167 seconds passed
-... 80%, 563200 KB, 3370 KB/s, 167 seconds passed
-... 80%, 563232 KB, 3370 KB/s, 167 seconds passed
+    ... 80%, 557760 KB, 3674 KB/s, 151 seconds passed
+... 80%, 557792 KB, 3674 KB/s, 151 seconds passed
+... 80%, 557824 KB, 3675 KB/s, 151 seconds passed
+... 80%, 557856 KB, 3675 KB/s, 151 seconds passed
 
 .. parsed-literal::
 
-    ... 80%, 563264 KB, 3370 KB/s, 167 seconds passed
-... 80%, 563296 KB, 3370 KB/s, 167 seconds passed
-... 80%, 563328 KB, 3370 KB/s, 167 seconds passed
-... 80%, 563360 KB, 3370 KB/s, 167 seconds passed
-... 81%, 563392 KB, 3370 KB/s, 167 seconds passed
-... 81%, 563424 KB, 3370 KB/s, 167 seconds passed
+    ... 80%, 557888 KB, 3674 KB/s, 151 seconds passed
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+... 80%, 558016 KB, 3675 KB/s, 151 seconds passed
+... 80%, 558048 KB, 3674 KB/s, 151 seconds passed
+... 80%, 558080 KB, 3675 KB/s, 151 seconds passed
 
 .. parsed-literal::
 
-    ... 81%, 563456 KB, 3370 KB/s, 167 seconds passed
-... 81%, 563488 KB, 3370 KB/s, 167 seconds passed
-... 81%, 563520 KB, 3370 KB/s, 167 seconds passed
-... 81%, 563552 KB, 3370 KB/s, 167 seconds passed
-... 81%, 563584 KB, 3370 KB/s, 167 seconds passed
-... 81%, 563616 KB, 3370 KB/s, 167 seconds passed
+    ... 80%, 558112 KB, 3675 KB/s, 151 seconds passed
+... 80%, 558144 KB, 3674 KB/s, 151 seconds passed
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+... 80%, 558208 KB, 3675 KB/s, 151 seconds passed
+... 80%, 558240 KB, 3675 KB/s, 151 seconds passed
+... 80%, 558272 KB, 3675 KB/s, 151 seconds passed
 
 .. parsed-literal::
 
-    ... 81%, 563648 KB, 3370 KB/s, 167 seconds passed
-... 81%, 563680 KB, 3370 KB/s, 167 seconds passed
-... 81%, 563712 KB, 3370 KB/s, 167 seconds passed
-... 81%, 563744 KB, 3370 KB/s, 167 seconds passed
-... 81%, 563776 KB, 3370 KB/s, 167 seconds passed
-... 81%, 563808 KB, 3370 KB/s, 167 seconds passed
+    ... 80%, 558304 KB, 3674 KB/s, 151 seconds passed
+... 80%, 558336 KB, 3675 KB/s, 151 seconds passed
+... 80%, 558368 KB, 3675 KB/s, 151 seconds passed
+... 80%, 558400 KB, 3674 KB/s, 151 seconds passed
 
 .. parsed-literal::
 
-    ... 81%, 563840 KB, 3370 KB/s, 167 seconds passed
-... 81%, 563872 KB, 3371 KB/s, 167 seconds passed
-... 81%, 563904 KB, 3370 KB/s, 167 seconds passed
-... 81%, 563936 KB, 3370 KB/s, 167 seconds passed
-... 81%, 563968 KB, 3371 KB/s, 167 seconds passed
-... 81%, 564000 KB, 3371 KB/s, 167 seconds passed
+    ... 80%, 558432 KB, 3674 KB/s, 151 seconds passed
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+... 80%, 558592 KB, 3675 KB/s, 151 seconds passed
+... 80%, 558624 KB, 3675 KB/s, 151 seconds passed
+... 80%, 558656 KB, 3675 KB/s, 151 seconds passed
 
 .. parsed-literal::
 
-    ... 81%, 564032 KB, 3370 KB/s, 167 seconds passed
-... 81%, 564064 KB, 3371 KB/s, 167 seconds passed
-... 81%, 564096 KB, 3371 KB/s, 167 seconds passed
-... 81%, 564128 KB, 3371 KB/s, 167 seconds passed
-... 81%, 564160 KB, 3371 KB/s, 167 seconds passed
-... 81%, 564192 KB, 3371 KB/s, 167 seconds passed
+    ... 80%, 558688 KB, 3674 KB/s, 152 seconds passed
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+... 80%, 558752 KB, 3675 KB/s, 152 seconds passed
+... 80%, 558784 KB, 3674 KB/s, 152 seconds passed
+... 80%, 558816 KB, 3674 KB/s, 152 seconds passed
 
 .. parsed-literal::
 
-    ... 81%, 564224 KB, 3371 KB/s, 167 seconds passed
-... 81%, 564256 KB, 3371 KB/s, 167 seconds passed
-... 81%, 564288 KB, 3371 KB/s, 167 seconds passed
-... 81%, 564320 KB, 3371 KB/s, 167 seconds passed
-... 81%, 564352 KB, 3371 KB/s, 167 seconds passed
-... 81%, 564384 KB, 3371 KB/s, 167 seconds passed
+    ... 80%, 558848 KB, 3675 KB/s, 152 seconds passed
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+... 80%, 558944 KB, 3674 KB/s, 152 seconds passed
+... 80%, 558976 KB, 3675 KB/s, 152 seconds passed
+... 80%, 559008 KB, 3675 KB/s, 152 seconds passed
 
 .. parsed-literal::
 
-    ... 81%, 564416 KB, 3371 KB/s, 167 seconds passed
-... 81%, 564448 KB, 3371 KB/s, 167 seconds passed
-... 81%, 564480 KB, 3371 KB/s, 167 seconds passed
-... 81%, 564512 KB, 3371 KB/s, 167 seconds passed
-... 81%, 564544 KB, 3371 KB/s, 167 seconds passed
-... 81%, 564576 KB, 3371 KB/s, 167 seconds passed
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+... 80%, 559104 KB, 3675 KB/s, 152 seconds passed
+... 80%, 559136 KB, 3675 KB/s, 152 seconds passed
+... 80%, 559168 KB, 3674 KB/s, 152 seconds passed
 
 .. parsed-literal::
 
-    ... 81%, 564608 KB, 3371 KB/s, 167 seconds passed
-... 81%, 564640 KB, 3371 KB/s, 167 seconds passed
-... 81%, 564672 KB, 3371 KB/s, 167 seconds passed
-... 81%, 564704 KB, 3371 KB/s, 167 seconds passed
-... 81%, 564736 KB, 3371 KB/s, 167 seconds passed
-... 81%, 564768 KB, 3371 KB/s, 167 seconds passed
+    ... 80%, 559200 KB, 3674 KB/s, 152 seconds passed
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+... 80%, 559360 KB, 3675 KB/s, 152 seconds passed
+... 80%, 559392 KB, 3675 KB/s, 152 seconds passed
 
 .. parsed-literal::
 
-    ... 81%, 564800 KB, 3371 KB/s, 167 seconds passed
-... 81%, 564832 KB, 3371 KB/s, 167 seconds passed
-... 81%, 564864 KB, 3371 KB/s, 167 seconds passed
-... 81%, 564896 KB, 3371 KB/s, 167 seconds passed
-... 81%, 564928 KB, 3371 KB/s, 167 seconds passed
+    ... 80%, 559424 KB, 3674 KB/s, 152 seconds passed
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+... 80%, 559520 KB, 3675 KB/s, 152 seconds passed
+... 80%, 559552 KB, 3674 KB/s, 152 seconds passed
 
 .. parsed-literal::
 
-    ... 81%, 564960 KB, 3371 KB/s, 167 seconds passed
-... 81%, 564992 KB, 3371 KB/s, 167 seconds passed
-... 81%, 565024 KB, 3371 KB/s, 167 seconds passed
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-... 81%, 565088 KB, 3371 KB/s, 167 seconds passed
-... 81%, 565120 KB, 3371 KB/s, 167 seconds passed
-... 81%, 565152 KB, 3371 KB/s, 167 seconds passed
+    ... 80%, 559584 KB, 3674 KB/s, 152 seconds passed
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+... 80%, 559744 KB, 3675 KB/s, 152 seconds passed
+... 80%, 559776 KB, 3675 KB/s, 152 seconds passed
 
 .. parsed-literal::
 
-    ... 81%, 565184 KB, 3371 KB/s, 167 seconds passed
-... 81%, 565216 KB, 3371 KB/s, 167 seconds passed
-... 81%, 565248 KB, 3371 KB/s, 167 seconds passed
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+... 80%, 559936 KB, 3674 KB/s, 152 seconds passed
 
 .. parsed-literal::
 
-    ... 81%, 565344 KB, 3371 KB/s, 167 seconds passed
-... 81%, 565376 KB, 3371 KB/s, 167 seconds passed
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+    ... 80%, 559968 KB, 3674 KB/s, 152 seconds passed
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+... 80%, 560160 KB, 3675 KB/s, 152 seconds passed
 
 .. parsed-literal::
 
-    ... 81%, 565568 KB, 3371 KB/s, 167 seconds passed
-... 81%, 565600 KB, 3371 KB/s, 167 seconds passed
-... 81%, 565632 KB, 3371 KB/s, 167 seconds passed
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-... 81%, 565696 KB, 3371 KB/s, 167 seconds passed
+    ... 80%, 560192 KB, 3674 KB/s, 152 seconds passed
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 .. parsed-literal::
 
-    ... 81%, 565728 KB, 3371 KB/s, 167 seconds passed
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-... 81%, 565856 KB, 3371 KB/s, 167 seconds passed
-... 81%, 565888 KB, 3372 KB/s, 167 seconds passed
-... 81%, 565920 KB, 3372 KB/s, 167 seconds passed
+    ... 80%, 560320 KB, 3674 KB/s, 152 seconds passed
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+... 80%, 560512 KB, 3675 KB/s, 152 seconds passed
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 .. parsed-literal::
 
-    ... 81%, 565952 KB, 3371 KB/s, 167 seconds passed
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-... 81%, 566016 KB, 3372 KB/s, 167 seconds passed
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+    ... 80%, 560576 KB, 3674 KB/s, 152 seconds passed
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 .. parsed-literal::
 
-    ... 81%, 566112 KB, 3372 KB/s, 167 seconds passed
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-... 81%, 566208 KB, 3372 KB/s, 167 seconds passed
-... 81%, 566240 KB, 3372 KB/s, 167 seconds passed
-... 81%, 566272 KB, 3372 KB/s, 167 seconds passed
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 .. parsed-literal::
 
-    ... 81%, 566304 KB, 3372 KB/s, 167 seconds passed
-... 81%, 566336 KB, 3372 KB/s, 167 seconds passed
-... 81%, 566368 KB, 3372 KB/s, 167 seconds passed
-... 81%, 566400 KB, 3372 KB/s, 167 seconds passed
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+    ... 80%, 560960 KB, 3674 KB/s, 152 seconds passed
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 .. parsed-literal::
 
-    ... 81%, 566496 KB, 3372 KB/s, 167 seconds passed
-... 81%, 566528 KB, 3372 KB/s, 167 seconds passed
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-... 81%, 566592 KB, 3372 KB/s, 168 seconds passed
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+    ... 80%, 561088 KB, 3674 KB/s, 152 seconds passed
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 .. parsed-literal::
 
-    ... 81%, 566688 KB, 3372 KB/s, 168 seconds passed
-... 81%, 566720 KB, 3372 KB/s, 168 seconds passed
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-... 81%, 566816 KB, 3372 KB/s, 168 seconds passed
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+    ... 80%, 561344 KB, 3674 KB/s, 152 seconds passed
+... 80%, 561376 KB, 3675 KB/s, 152 seconds passed
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 .. parsed-literal::
 
-    ... 81%, 566880 KB, 3372 KB/s, 168 seconds passed
-... 81%, 566912 KB, 3372 KB/s, 168 seconds passed
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-... 81%, 566976 KB, 3372 KB/s, 168 seconds passed
-... 81%, 567008 KB, 3372 KB/s, 168 seconds passed
-... 81%, 567040 KB, 3372 KB/s, 168 seconds passed
+    ... 80%, 561472 KB, 3674 KB/s, 152 seconds passed
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+... 80%, 561664 KB, 3675 KB/s, 152 seconds passed
+... 80%, 561696 KB, 3675 KB/s, 152 seconds passed
 
 .. parsed-literal::
 
-    ... 81%, 567072 KB, 3372 KB/s, 168 seconds passed
-... 81%, 567104 KB, 3372 KB/s, 168 seconds passed
-... 81%, 567136 KB, 3372 KB/s, 168 seconds passed
-... 81%, 567168 KB, 3372 KB/s, 168 seconds passed
-... 81%, 567200 KB, 3372 KB/s, 168 seconds passed
+    ... 80%, 561728 KB, 3674 KB/s, 152 seconds passed
+... 80%, 561760 KB, 3675 KB/s, 152 seconds passed
+... 80%, 561792 KB, 3675 KB/s, 152 seconds passed
+... 80%, 561824 KB, 3675 KB/s, 152 seconds passed
 
 .. parsed-literal::
 
-    ... 81%, 567232 KB, 3372 KB/s, 168 seconds passed
-... 81%, 567264 KB, 3372 KB/s, 168 seconds passed
-... 81%, 567296 KB, 3372 KB/s, 168 seconds passed
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-... 81%, 567392 KB, 3372 KB/s, 168 seconds passed
-... 81%, 567424 KB, 3372 KB/s, 168 seconds passed
+    ... 80%, 561856 KB, 3674 KB/s, 152 seconds passed
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+... 80%, 562016 KB, 3675 KB/s, 152 seconds passed
+... 80%, 562048 KB, 3675 KB/s, 152 seconds passed
+... 80%, 562080 KB, 3675 KB/s, 152 seconds passed
 
 .. parsed-literal::
 
-    ... 81%, 567456 KB, 3372 KB/s, 168 seconds passed
-... 81%, 567488 KB, 3372 KB/s, 168 seconds passed
-... 81%, 567520 KB, 3372 KB/s, 168 seconds passed
-... 81%, 567552 KB, 3372 KB/s, 168 seconds passed
-... 81%, 567584 KB, 3372 KB/s, 168 seconds passed
+    ... 80%, 562112 KB, 3674 KB/s, 152 seconds passed
+... 80%, 562144 KB, 3675 KB/s, 152 seconds passed
+... 80%, 562176 KB, 3675 KB/s, 152 seconds passed
+... 80%, 562208 KB, 3675 KB/s, 152 seconds passed
 
 .. parsed-literal::
 
-    ... 81%, 567616 KB, 3372 KB/s, 168 seconds passed
-... 81%, 567648 KB, 3372 KB/s, 168 seconds passed
-... 81%, 567680 KB, 3372 KB/s, 168 seconds passed
-... 81%, 567712 KB, 3372 KB/s, 168 seconds passed
-... 81%, 567744 KB, 3372 KB/s, 168 seconds passed
-... 81%, 567776 KB, 3372 KB/s, 168 seconds passed
+    ... 80%, 562240 KB, 3674 KB/s, 152 seconds passed
+... 80%, 562272 KB, 3675 KB/s, 152 seconds passed
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+... 80%, 562400 KB, 3675 KB/s, 153 seconds passed
+... 80%, 562432 KB, 3675 KB/s, 153 seconds passed
+... 80%, 562464 KB, 3675 KB/s, 153 seconds passed
 
 .. parsed-literal::
 
-    ... 81%, 567808 KB, 3373 KB/s, 168 seconds passed
-... 81%, 567840 KB, 3373 KB/s, 168 seconds passed
-... 81%, 567872 KB, 3372 KB/s, 168 seconds passed
-... 81%, 567904 KB, 3373 KB/s, 168 seconds passed
-... 81%, 567936 KB, 3373 KB/s, 168 seconds passed
-... 81%, 567968 KB, 3373 KB/s, 168 seconds passed
+    ... 80%, 562496 KB, 3674 KB/s, 153 seconds passed
+... 80%, 562528 KB, 3675 KB/s, 153 seconds passed
+... 80%, 562560 KB, 3675 KB/s, 153 seconds passed
 
 .. parsed-literal::
 
-    ... 81%, 568000 KB, 3373 KB/s, 168 seconds passed
-... 81%, 568032 KB, 3373 KB/s, 168 seconds passed
-... 81%, 568064 KB, 3373 KB/s, 168 seconds passed
-... 81%, 568096 KB, 3373 KB/s, 168 seconds passed
-... 81%, 568128 KB, 3373 KB/s, 168 seconds passed
-... 81%, 568160 KB, 3373 KB/s, 168 seconds passed
+    ... 80%, 562592 KB, 3674 KB/s, 153 seconds passed
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+... 80%, 562656 KB, 3675 KB/s, 153 seconds passed
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+... 80%, 562752 KB, 3674 KB/s, 153 seconds passed
+... 80%, 562784 KB, 3675 KB/s, 153 seconds passed
+... 80%, 562816 KB, 3675 KB/s, 153 seconds passed
 
 .. parsed-literal::
 
-    ... 81%, 568192 KB, 3373 KB/s, 168 seconds passed
-... 81%, 568224 KB, 3373 KB/s, 168 seconds passed
-... 81%, 568256 KB, 3373 KB/s, 168 seconds passed
-... 81%, 568288 KB, 3373 KB/s, 168 seconds passed
-... 81%, 568320 KB, 3373 KB/s, 168 seconds passed
-... 81%, 568352 KB, 3373 KB/s, 168 seconds passed
+    ... 80%, 562848 KB, 3674 KB/s, 153 seconds passed
+... 80%, 562880 KB, 3674 KB/s, 153 seconds passed
+... 80%, 562912 KB, 3675 KB/s, 153 seconds passed
+... 80%, 562944 KB, 3675 KB/s, 153 seconds passed
 
 .. parsed-literal::
 
-    ... 81%, 568384 KB, 3373 KB/s, 168 seconds passed
-... 81%, 568416 KB, 3373 KB/s, 168 seconds passed
-... 81%, 568448 KB, 3373 KB/s, 168 seconds passed
-... 81%, 568480 KB, 3373 KB/s, 168 seconds passed
-... 81%, 568512 KB, 3373 KB/s, 168 seconds passed
-... 81%, 568544 KB, 3373 KB/s, 168 seconds passed
+    ... 80%, 562976 KB, 3674 KB/s, 153 seconds passed
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+... 80%, 563040 KB, 3675 KB/s, 153 seconds passed
+... 80%, 563072 KB, 3675 KB/s, 153 seconds passed
+... 80%, 563104 KB, 3674 KB/s, 153 seconds passed
+... 80%, 563136 KB, 3674 KB/s, 153 seconds passed
+... 80%, 563168 KB, 3675 KB/s, 153 seconds passed
+... 80%, 563200 KB, 3675 KB/s, 153 seconds passed
 
 .. parsed-literal::
 
-    ... 81%, 568576 KB, 3373 KB/s, 168 seconds passed
-... 81%, 568608 KB, 3373 KB/s, 168 seconds passed
-... 81%, 568640 KB, 3373 KB/s, 168 seconds passed
-... 81%, 568672 KB, 3373 KB/s, 168 seconds passed
-... 81%, 568704 KB, 3373 KB/s, 168 seconds passed
-... 81%, 568736 KB, 3373 KB/s, 168 seconds passed
+    ... 80%, 563232 KB, 3674 KB/s, 153 seconds passed
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+... 80%, 563296 KB, 3675 KB/s, 153 seconds passed
+... 80%, 563328 KB, 3675 KB/s, 153 seconds passed
+... 80%, 563360 KB, 3675 KB/s, 153 seconds passed
 
 .. parsed-literal::
 
-    ... 81%, 568768 KB, 3373 KB/s, 168 seconds passed
-... 81%, 568800 KB, 3373 KB/s, 168 seconds passed
-... 81%, 568832 KB, 3373 KB/s, 168 seconds passed
-... 81%, 568864 KB, 3373 KB/s, 168 seconds passed
-... 81%, 568896 KB, 3373 KB/s, 168 seconds passed
-... 81%, 568928 KB, 3373 KB/s, 168 seconds passed
+    ... 81%, 563392 KB, 3675 KB/s, 153 seconds passed
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+... 81%, 563520 KB, 3675 KB/s, 153 seconds passed
+... 81%, 563552 KB, 3675 KB/s, 153 seconds passed
+... 81%, 563584 KB, 3675 KB/s, 153 seconds passed
 
 .. parsed-literal::
 
-    ... 81%, 568960 KB, 3373 KB/s, 168 seconds passed
-... 81%, 568992 KB, 3373 KB/s, 168 seconds passed
-... 81%, 569024 KB, 3373 KB/s, 168 seconds passed
-... 81%, 569056 KB, 3373 KB/s, 168 seconds passed
-... 81%, 569088 KB, 3373 KB/s, 168 seconds passed
-... 81%, 569120 KB, 3373 KB/s, 168 seconds passed
+    ... 81%, 563616 KB, 3674 KB/s, 153 seconds passed
+... 81%, 563648 KB, 3675 KB/s, 153 seconds passed
+... 81%, 563680 KB, 3675 KB/s, 153 seconds passed
+... 81%, 563712 KB, 3675 KB/s, 153 seconds passed
 
 .. parsed-literal::
 
-    ... 81%, 569152 KB, 3373 KB/s, 168 seconds passed
-... 81%, 569184 KB, 3373 KB/s, 168 seconds passed
-... 81%, 569216 KB, 3373 KB/s, 168 seconds passed
-... 81%, 569248 KB, 3373 KB/s, 168 seconds passed
-... 81%, 569280 KB, 3373 KB/s, 168 seconds passed
-... 81%, 569312 KB, 3373 KB/s, 168 seconds passed
+    ... 81%, 563744 KB, 3674 KB/s, 153 seconds passed
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+... 81%, 563904 KB, 3675 KB/s, 153 seconds passed
+... 81%, 563936 KB, 3675 KB/s, 153 seconds passed
+... 81%, 563968 KB, 3675 KB/s, 153 seconds passed
 
 .. parsed-literal::
 
-    ... 81%, 569344 KB, 3373 KB/s, 168 seconds passed
-... 81%, 569376 KB, 3373 KB/s, 168 seconds passed
-... 81%, 569408 KB, 3373 KB/s, 168 seconds passed
-... 81%, 569440 KB, 3373 KB/s, 168 seconds passed
-... 81%, 569472 KB, 3373 KB/s, 168 seconds passed
-... 81%, 569504 KB, 3373 KB/s, 168 seconds passed
+    ... 81%, 564000 KB, 3675 KB/s, 153 seconds passed
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+... 81%, 564064 KB, 3675 KB/s, 153 seconds passed
+... 81%, 564096 KB, 3675 KB/s, 153 seconds passed
 
 .. parsed-literal::
 
-    ... 81%, 569536 KB, 3373 KB/s, 168 seconds passed
-... 81%, 569568 KB, 3373 KB/s, 168 seconds passed
-... 81%, 569600 KB, 3373 KB/s, 168 seconds passed
-... 81%, 569632 KB, 3373 KB/s, 168 seconds passed
-... 81%, 569664 KB, 3373 KB/s, 168 seconds passed
-... 81%, 569696 KB, 3373 KB/s, 168 seconds passed
+    ... 81%, 564128 KB, 3675 KB/s, 153 seconds passed
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+... 81%, 564256 KB, 3675 KB/s, 153 seconds passed
+... 81%, 564288 KB, 3675 KB/s, 153 seconds passed
+... 81%, 564320 KB, 3675 KB/s, 153 seconds passed
 
 .. parsed-literal::
 
-    ... 81%, 569728 KB, 3373 KB/s, 168 seconds passed
-... 81%, 569760 KB, 3373 KB/s, 168 seconds passed
-... 81%, 569792 KB, 3373 KB/s, 168 seconds passed
-... 81%, 569824 KB, 3374 KB/s, 168 seconds passed
-... 81%, 569856 KB, 3374 KB/s, 168 seconds passed
-... 81%, 569888 KB, 3374 KB/s, 168 seconds passed
+    ... 81%, 564352 KB, 3675 KB/s, 153 seconds passed
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+... 81%, 564416 KB, 3675 KB/s, 153 seconds passed
+... 81%, 564448 KB, 3675 KB/s, 153 seconds passed
+... 81%, 564480 KB, 3675 KB/s, 153 seconds passed
 
 .. parsed-literal::
 
-    ... 81%, 569920 KB, 3374 KB/s, 168 seconds passed
-... 81%, 569952 KB, 3374 KB/s, 168 seconds passed
-... 81%, 569984 KB, 3374 KB/s, 168 seconds passed
-... 81%, 570016 KB, 3374 KB/s, 168 seconds passed
-... 81%, 570048 KB, 3374 KB/s, 168 seconds passed
+    ... 81%, 564512 KB, 3675 KB/s, 153 seconds passed
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+... 81%, 564608 KB, 3675 KB/s, 153 seconds passed
+... 81%, 564640 KB, 3675 KB/s, 153 seconds passed
+... 81%, 564672 KB, 3675 KB/s, 153 seconds passed
 
 .. parsed-literal::
 
-    ... 81%, 570080 KB, 3374 KB/s, 168 seconds passed
-... 81%, 570112 KB, 3374 KB/s, 168 seconds passed
-... 81%, 570144 KB, 3374 KB/s, 168 seconds passed
-... 81%, 570176 KB, 3374 KB/s, 168 seconds passed
-... 81%, 570208 KB, 3374 KB/s, 168 seconds passed
-... 81%, 570240 KB, 3374 KB/s, 168 seconds passed
+    ... 81%, 564704 KB, 3675 KB/s, 153 seconds passed
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+... 81%, 564800 KB, 3675 KB/s, 153 seconds passed
+... 81%, 564832 KB, 3675 KB/s, 153 seconds passed
+... 81%, 564864 KB, 3675 KB/s, 153 seconds passed
 
 .. parsed-literal::
 
-    ... 81%, 570272 KB, 3374 KB/s, 169 seconds passed
-... 81%, 570304 KB, 3374 KB/s, 169 seconds passed
-... 82%, 570336 KB, 3374 KB/s, 169 seconds passed
-... 82%, 570368 KB, 3374 KB/s, 169 seconds passed
-... 82%, 570400 KB, 3374 KB/s, 169 seconds passed
-... 82%, 570432 KB, 3374 KB/s, 169 seconds passed
+    ... 81%, 564896 KB, 3675 KB/s, 153 seconds passed
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+... 81%, 564992 KB, 3675 KB/s, 153 seconds passed
+... 81%, 565024 KB, 3675 KB/s, 153 seconds passed
+... 81%, 565056 KB, 3675 KB/s, 153 seconds passed
 
 .. parsed-literal::
 
-    ... 82%, 570464 KB, 3374 KB/s, 169 seconds passed
-... 82%, 570496 KB, 3374 KB/s, 169 seconds passed
-... 82%, 570528 KB, 3374 KB/s, 169 seconds passed
-... 82%, 570560 KB, 3374 KB/s, 169 seconds passed
-... 82%, 570592 KB, 3374 KB/s, 169 seconds passed
-... 82%, 570624 KB, 3374 KB/s, 169 seconds passed
+    ... 81%, 565088 KB, 3675 KB/s, 153 seconds passed
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+... 81%, 565184 KB, 3675 KB/s, 153 seconds passed
+... 81%, 565216 KB, 3675 KB/s, 153 seconds passed
+... 81%, 565248 KB, 3675 KB/s, 153 seconds passed
 
 .. parsed-literal::
 
-    ... 82%, 570656 KB, 3374 KB/s, 169 seconds passed
-... 82%, 570688 KB, 3374 KB/s, 169 seconds passed
-... 82%, 570720 KB, 3374 KB/s, 169 seconds passed
-... 82%, 570752 KB, 3374 KB/s, 169 seconds passed
-... 82%, 570784 KB, 3374 KB/s, 169 seconds passed
-... 82%, 570816 KB, 3374 KB/s, 169 seconds passed
+    ... 81%, 565280 KB, 3675 KB/s, 153 seconds passed
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+... 81%, 565344 KB, 3675 KB/s, 153 seconds passed
+... 81%, 565376 KB, 3675 KB/s, 153 seconds passed
+... 81%, 565408 KB, 3675 KB/s, 153 seconds passed
 
 .. parsed-literal::
 
-    ... 82%, 570848 KB, 3374 KB/s, 169 seconds passed
-... 82%, 570880 KB, 3374 KB/s, 169 seconds passed
-... 82%, 570912 KB, 3374 KB/s, 169 seconds passed
-... 82%, 570944 KB, 3374 KB/s, 169 seconds passed
-... 82%, 570976 KB, 3374 KB/s, 169 seconds passed
-... 82%, 571008 KB, 3374 KB/s, 169 seconds passed
+    ... 81%, 565440 KB, 3675 KB/s, 153 seconds passed
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+... 81%, 565568 KB, 3675 KB/s, 153 seconds passed
+... 81%, 565600 KB, 3675 KB/s, 153 seconds passed
+... 81%, 565632 KB, 3675 KB/s, 153 seconds passed
 
 .. parsed-literal::
 
-    ... 82%, 571040 KB, 3374 KB/s, 169 seconds passed
-... 82%, 571072 KB, 3374 KB/s, 169 seconds passed
-... 82%, 571104 KB, 3374 KB/s, 169 seconds passed
-... 82%, 571136 KB, 3374 KB/s, 169 seconds passed
-... 82%, 571168 KB, 3374 KB/s, 169 seconds passed
-... 82%, 571200 KB, 3374 KB/s, 169 seconds passed
+    ... 81%, 565664 KB, 3675 KB/s, 153 seconds passed
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+... 81%, 565760 KB, 3675 KB/s, 153 seconds passed
+... 81%, 565792 KB, 3675 KB/s, 153 seconds passed
 
 .. parsed-literal::
 
-    ... 82%, 571232 KB, 3374 KB/s, 169 seconds passed
-... 82%, 571264 KB, 3374 KB/s, 169 seconds passed
-... 82%, 571296 KB, 3374 KB/s, 169 seconds passed
-... 82%, 571328 KB, 3374 KB/s, 169 seconds passed
-... 82%, 571360 KB, 3374 KB/s, 169 seconds passed
-... 82%, 571392 KB, 3374 KB/s, 169 seconds passed
+    ... 81%, 565824 KB, 3675 KB/s, 153 seconds passed
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+... 81%, 565984 KB, 3675 KB/s, 153 seconds passed
+... 81%, 566016 KB, 3675 KB/s, 153 seconds passed
 
 .. parsed-literal::
 
-    ... 82%, 571424 KB, 3374 KB/s, 169 seconds passed
-... 82%, 571456 KB, 3374 KB/s, 169 seconds passed
-... 82%, 571488 KB, 3374 KB/s, 169 seconds passed
-... 82%, 571520 KB, 3374 KB/s, 169 seconds passed
-... 82%, 571552 KB, 3374 KB/s, 169 seconds passed
-... 82%, 571584 KB, 3374 KB/s, 169 seconds passed
+    ... 81%, 566048 KB, 3675 KB/s, 154 seconds passed
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+... 81%, 566112 KB, 3675 KB/s, 154 seconds passed
+... 81%, 566144 KB, 3675 KB/s, 154 seconds passed
+... 81%, 566176 KB, 3675 KB/s, 154 seconds passed
 
 .. parsed-literal::
 
-    ... 82%, 571616 KB, 3374 KB/s, 169 seconds passed
-... 82%, 571648 KB, 3375 KB/s, 169 seconds passed
-... 82%, 571680 KB, 3375 KB/s, 169 seconds passed
-... 82%, 571712 KB, 3374 KB/s, 169 seconds passed
-... 82%, 571744 KB, 3375 KB/s, 169 seconds passed
-... 82%, 571776 KB, 3375 KB/s, 169 seconds passed
+    ... 81%, 566208 KB, 3675 KB/s, 154 seconds passed
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+... 81%, 566336 KB, 3675 KB/s, 154 seconds passed
+... 81%, 566368 KB, 3675 KB/s, 154 seconds passed
+... 81%, 566400 KB, 3675 KB/s, 154 seconds passed
 
 .. parsed-literal::
 
-    ... 82%, 571808 KB, 3375 KB/s, 169 seconds passed
-... 82%, 571840 KB, 3375 KB/s, 169 seconds passed
-... 82%, 571872 KB, 3375 KB/s, 169 seconds passed
-... 82%, 571904 KB, 3375 KB/s, 169 seconds passed
-... 82%, 571936 KB, 3375 KB/s, 169 seconds passed
-... 82%, 571968 KB, 3375 KB/s, 169 seconds passed
+    ... 81%, 566432 KB, 3675 KB/s, 154 seconds passed
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+... 81%, 566528 KB, 3675 KB/s, 154 seconds passed
+... 81%, 566560 KB, 3675 KB/s, 154 seconds passed
 
 .. parsed-literal::
 
-    ... 82%, 572000 KB, 3375 KB/s, 169 seconds passed
-... 82%, 572032 KB, 3375 KB/s, 169 seconds passed
-... 82%, 572064 KB, 3375 KB/s, 169 seconds passed
-... 82%, 572096 KB, 3375 KB/s, 169 seconds passed
-... 82%, 572128 KB, 3375 KB/s, 169 seconds passed
-... 82%, 572160 KB, 3375 KB/s, 169 seconds passed
+    ... 81%, 566592 KB, 3675 KB/s, 154 seconds passed
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+... 81%, 566720 KB, 3675 KB/s, 154 seconds passed
+... 81%, 566752 KB, 3675 KB/s, 154 seconds passed
+... 81%, 566784 KB, 3675 KB/s, 154 seconds passed
 
 .. parsed-literal::
 
-    ... 82%, 572192 KB, 3375 KB/s, 169 seconds passed
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-... 82%, 572256 KB, 3375 KB/s, 169 seconds passed
-... 82%, 572288 KB, 3375 KB/s, 169 seconds passed
-... 82%, 572320 KB, 3375 KB/s, 169 seconds passed
+    ... 81%, 566816 KB, 3675 KB/s, 154 seconds passed
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+... 81%, 566944 KB, 3675 KB/s, 154 seconds passed
 
 .. parsed-literal::
 
-    ... 82%, 572352 KB, 3375 KB/s, 169 seconds passed
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-... 82%, 572448 KB, 3375 KB/s, 169 seconds passed
-... 82%, 572480 KB, 3375 KB/s, 169 seconds passed
-... 82%, 572512 KB, 3375 KB/s, 169 seconds passed
-... 82%, 572544 KB, 3375 KB/s, 169 seconds passed
+    ... 81%, 566976 KB, 3675 KB/s, 154 seconds passed
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+... 81%, 567104 KB, 3675 KB/s, 154 seconds passed
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 .. parsed-literal::
 
-    ... 82%, 572576 KB, 3375 KB/s, 169 seconds passed
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-... 82%, 572640 KB, 3375 KB/s, 169 seconds passed
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+    ... 81%, 567200 KB, 3675 KB/s, 154 seconds passed
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+... 81%, 567328 KB, 3675 KB/s, 154 seconds passed
 
 .. parsed-literal::
 
-    ... 82%, 572736 KB, 3375 KB/s, 169 seconds passed
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-... 82%, 572800 KB, 3375 KB/s, 169 seconds passed
-... 82%, 572832 KB, 3375 KB/s, 169 seconds passed
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-... 82%, 572896 KB, 3375 KB/s, 169 seconds passed
+    ... 81%, 567360 KB, 3675 KB/s, 154 seconds passed
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+... 81%, 567520 KB, 3675 KB/s, 154 seconds passed
+... 81%, 567552 KB, 3675 KB/s, 154 seconds passed
 
 .. parsed-literal::
 
-    ... 82%, 572928 KB, 3375 KB/s, 169 seconds passed
-... 82%, 572960 KB, 3375 KB/s, 169 seconds passed
-... 82%, 572992 KB, 3375 KB/s, 169 seconds passed
-... 82%, 573024 KB, 3375 KB/s, 169 seconds passed
-... 82%, 573056 KB, 3375 KB/s, 169 seconds passed
-... 82%, 573088 KB, 3375 KB/s, 169 seconds passed
+    ... 81%, 567584 KB, 3675 KB/s, 154 seconds passed
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+... 81%, 567680 KB, 3675 KB/s, 154 seconds passed
+... 81%, 567712 KB, 3675 KB/s, 154 seconds passed
 
 .. parsed-literal::
 
-    ... 82%, 573120 KB, 3375 KB/s, 169 seconds passed
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-... 82%, 573280 KB, 3375 KB/s, 169 seconds passed
+    ... 81%, 567744 KB, 3675 KB/s, 154 seconds passed
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+... 81%, 567904 KB, 3675 KB/s, 154 seconds passed
+... 81%, 567936 KB, 3675 KB/s, 154 seconds passed
 
 .. parsed-literal::
 
-    ... 82%, 573312 KB, 3375 KB/s, 169 seconds passed
-... 82%, 573344 KB, 3375 KB/s, 169 seconds passed
-... 82%, 573376 KB, 3375 KB/s, 169 seconds passed
-... 82%, 573408 KB, 3375 KB/s, 169 seconds passed
-... 82%, 573440 KB, 3375 KB/s, 169 seconds passed
-... 82%, 573472 KB, 3375 KB/s, 169 seconds passed
+    ... 81%, 567968 KB, 3675 KB/s, 154 seconds passed
+... 81%, 568000 KB, 3675 KB/s, 154 seconds passed
+... 81%, 568032 KB, 3675 KB/s, 154 seconds passed
+... 81%, 568064 KB, 3675 KB/s, 154 seconds passed
 
 .. parsed-literal::
 
-    ... 82%, 573504 KB, 3375 KB/s, 169 seconds passed
-... 82%, 573536 KB, 3375 KB/s, 169 seconds passed
-... 82%, 573568 KB, 3375 KB/s, 169 seconds passed
-... 82%, 573600 KB, 3375 KB/s, 169 seconds passed
-... 82%, 573632 KB, 3375 KB/s, 169 seconds passed
-... 82%, 573664 KB, 3376 KB/s, 169 seconds passed
+    ... 81%, 568096 KB, 3675 KB/s, 154 seconds passed
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+... 81%, 568256 KB, 3675 KB/s, 154 seconds passed
+... 81%, 568288 KB, 3675 KB/s, 154 seconds passed
+... 81%, 568320 KB, 3675 KB/s, 154 seconds passed
 
 .. parsed-literal::
 
-    ... 82%, 573696 KB, 3376 KB/s, 169 seconds passed
-... 82%, 573728 KB, 3376 KB/s, 169 seconds passed
-... 82%, 573760 KB, 3376 KB/s, 169 seconds passed
-... 82%, 573792 KB, 3376 KB/s, 169 seconds passed
-... 82%, 573824 KB, 3376 KB/s, 169 seconds passed
-... 82%, 573856 KB, 3376 KB/s, 169 seconds passed
+    ... 81%, 568352 KB, 3675 KB/s, 154 seconds passed
+... 81%, 568384 KB, 3675 KB/s, 154 seconds passed
+... 81%, 568416 KB, 3675 KB/s, 154 seconds passed
+... 81%, 568448 KB, 3675 KB/s, 154 seconds passed
 
 .. parsed-literal::
 
-    ... 82%, 573888 KB, 3376 KB/s, 169 seconds passed
-... 82%, 573920 KB, 3376 KB/s, 169 seconds passed
-... 82%, 573952 KB, 3376 KB/s, 170 seconds passed
-... 82%, 573984 KB, 3376 KB/s, 170 seconds passed
-... 82%, 574016 KB, 3376 KB/s, 170 seconds passed
-... 82%, 574048 KB, 3376 KB/s, 170 seconds passed
+    ... 81%, 568480 KB, 3675 KB/s, 154 seconds passed
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+... 81%, 568608 KB, 3675 KB/s, 154 seconds passed
+... 81%, 568640 KB, 3675 KB/s, 154 seconds passed
+... 81%, 568672 KB, 3675 KB/s, 154 seconds passed
 
 .. parsed-literal::
 
-    ... 82%, 574080 KB, 3376 KB/s, 170 seconds passed
-... 82%, 574112 KB, 3376 KB/s, 170 seconds passed
-... 82%, 574144 KB, 3376 KB/s, 170 seconds passed
-... 82%, 574176 KB, 3376 KB/s, 170 seconds passed
-... 82%, 574208 KB, 3376 KB/s, 170 seconds passed
-... 82%, 574240 KB, 3376 KB/s, 170 seconds passed
+    ... 81%, 568704 KB, 3675 KB/s, 154 seconds passed
+... 81%, 568736 KB, 3675 KB/s, 154 seconds passed
+... 81%, 568768 KB, 3675 KB/s, 154 seconds passed
+... 81%, 568800 KB, 3675 KB/s, 154 seconds passed
 
 .. parsed-literal::
 
-    ... 82%, 574272 KB, 3376 KB/s, 170 seconds passed
-... 82%, 574304 KB, 3376 KB/s, 170 seconds passed
-... 82%, 574336 KB, 3376 KB/s, 170 seconds passed
-... 82%, 574368 KB, 3376 KB/s, 170 seconds passed
-... 82%, 574400 KB, 3376 KB/s, 170 seconds passed
-... 82%, 574432 KB, 3376 KB/s, 170 seconds passed
+    ... 81%, 568832 KB, 3675 KB/s, 154 seconds passed
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+... 81%, 568960 KB, 3675 KB/s, 154 seconds passed
+... 81%, 568992 KB, 3675 KB/s, 154 seconds passed
+... 81%, 569024 KB, 3675 KB/s, 154 seconds passed
+... 81%, 569056 KB, 3675 KB/s, 154 seconds passed
 
 .. parsed-literal::
 
-    ... 82%, 574464 KB, 3376 KB/s, 170 seconds passed
-... 82%, 574496 KB, 3376 KB/s, 170 seconds passed
-... 82%, 574528 KB, 3376 KB/s, 170 seconds passed
-... 82%, 574560 KB, 3376 KB/s, 170 seconds passed
-... 82%, 574592 KB, 3376 KB/s, 170 seconds passed
-... 82%, 574624 KB, 3376 KB/s, 170 seconds passed
+    ... 81%, 569088 KB, 3675 KB/s, 154 seconds passed
+... 81%, 569120 KB, 3675 KB/s, 154 seconds passed
+... 81%, 569152 KB, 3675 KB/s, 154 seconds passed
+... 81%, 569184 KB, 3675 KB/s, 154 seconds passed
 
 .. parsed-literal::
 
-    ... 82%, 574656 KB, 3376 KB/s, 170 seconds passed
-... 82%, 574688 KB, 3376 KB/s, 170 seconds passed
-... 82%, 574720 KB, 3376 KB/s, 170 seconds passed
-... 82%, 574752 KB, 3376 KB/s, 170 seconds passed
-... 82%, 574784 KB, 3376 KB/s, 170 seconds passed
-... 82%, 574816 KB, 3376 KB/s, 170 seconds passed
+    ... 81%, 569216 KB, 3675 KB/s, 154 seconds passed
+... 81%, 569248 KB, 3675 KB/s, 154 seconds passed
+... 81%, 569280 KB, 3675 KB/s, 154 seconds passed
+... 81%, 569312 KB, 3675 KB/s, 154 seconds passed
+... 81%, 569344 KB, 3675 KB/s, 154 seconds passed
+... 81%, 569376 KB, 3675 KB/s, 154 seconds passed
+... 81%, 569408 KB, 3675 KB/s, 154 seconds passed
+... 81%, 569440 KB, 3675 KB/s, 154 seconds passed
 
 .. parsed-literal::
 
-    ... 82%, 574848 KB, 3376 KB/s, 170 seconds passed
-... 82%, 574880 KB, 3376 KB/s, 170 seconds passed
-... 82%, 574912 KB, 3376 KB/s, 170 seconds passed
-... 82%, 574944 KB, 3376 KB/s, 170 seconds passed
-... 82%, 574976 KB, 3376 KB/s, 170 seconds passed
-... 82%, 575008 KB, 3376 KB/s, 170 seconds passed
+    ... 81%, 569472 KB, 3675 KB/s, 154 seconds passed
+... 81%, 569504 KB, 3675 KB/s, 154 seconds passed
+... 81%, 569536 KB, 3675 KB/s, 154 seconds passed
+... 81%, 569568 KB, 3675 KB/s, 154 seconds passed
 
 .. parsed-literal::
 
-    ... 82%, 575040 KB, 3376 KB/s, 170 seconds passed
-... 82%, 575072 KB, 3376 KB/s, 170 seconds passed
-... 82%, 575104 KB, 3376 KB/s, 170 seconds passed
-... 82%, 575136 KB, 3376 KB/s, 170 seconds passed
-... 82%, 575168 KB, 3376 KB/s, 170 seconds passed
+    ... 81%, 569600 KB, 3675 KB/s, 154 seconds passed
+... 81%, 569632 KB, 3675 KB/s, 154 seconds passed
+... 81%, 569664 KB, 3675 KB/s, 154 seconds passed
+... 81%, 569696 KB, 3675 KB/s, 155 seconds passed
+... 81%, 569728 KB, 3675 KB/s, 155 seconds passed
+... 81%, 569760 KB, 3675 KB/s, 155 seconds passed
+... 81%, 569792 KB, 3675 KB/s, 155 seconds passed
+... 81%, 569824 KB, 3675 KB/s, 155 seconds passed
 
 .. parsed-literal::
 
-    ... 82%, 575200 KB, 3376 KB/s, 170 seconds passed
-... 82%, 575232 KB, 3376 KB/s, 170 seconds passed
-... 82%, 575264 KB, 3376 KB/s, 170 seconds passed
-... 82%, 575296 KB, 3376 KB/s, 170 seconds passed
-... 82%, 575328 KB, 3376 KB/s, 170 seconds passed
-... 82%, 575360 KB, 3376 KB/s, 170 seconds passed
+    ... 81%, 569856 KB, 3675 KB/s, 155 seconds passed
+... 81%, 569888 KB, 3675 KB/s, 155 seconds passed
+... 81%, 569920 KB, 3675 KB/s, 155 seconds passed
+... 81%, 569952 KB, 3675 KB/s, 155 seconds passed
 
 .. parsed-literal::
 
-    ... 82%, 575392 KB, 3376 KB/s, 170 seconds passed
-... 82%, 575424 KB, 3376 KB/s, 170 seconds passed
-... 82%, 575456 KB, 3376 KB/s, 170 seconds passed
-... 82%, 575488 KB, 3376 KB/s, 170 seconds passed
-... 82%, 575520 KB, 3376 KB/s, 170 seconds passed
-... 82%, 575552 KB, 3376 KB/s, 170 seconds passed
+    ... 81%, 569984 KB, 3675 KB/s, 155 seconds passed
+... 81%, 570016 KB, 3675 KB/s, 155 seconds passed
+... 81%, 570048 KB, 3675 KB/s, 155 seconds passed
+... 81%, 570080 KB, 3675 KB/s, 155 seconds passed
+... 81%, 570112 KB, 3675 KB/s, 155 seconds passed
+... 81%, 570144 KB, 3675 KB/s, 155 seconds passed
+... 81%, 570176 KB, 3675 KB/s, 155 seconds passed
 
 .. parsed-literal::
 
-    ... 82%, 575584 KB, 3376 KB/s, 170 seconds passed
-... 82%, 575616 KB, 3376 KB/s, 170 seconds passed
-... 82%, 575648 KB, 3377 KB/s, 170 seconds passed
-... 82%, 575680 KB, 3377 KB/s, 170 seconds passed
+    ... 81%, 570208 KB, 3675 KB/s, 155 seconds passed
+... 81%, 570240 KB, 3675 KB/s, 155 seconds passed
+... 81%, 570272 KB, 3675 KB/s, 155 seconds passed
+... 81%, 570304 KB, 3675 KB/s, 155 seconds passed
+... 82%, 570336 KB, 3675 KB/s, 155 seconds passed
 
 .. parsed-literal::
 
-    ... 82%, 575712 KB, 3376 KB/s, 170 seconds passed
-... 82%, 575744 KB, 3376 KB/s, 170 seconds passed
-... 82%, 575776 KB, 3376 KB/s, 170 seconds passed
-... 82%, 575808 KB, 3377 KB/s, 170 seconds passed
+    ... 82%, 570368 KB, 3675 KB/s, 155 seconds passed
+... 82%, 570400 KB, 3675 KB/s, 155 seconds passed
+... 82%, 570432 KB, 3675 KB/s, 155 seconds passed
+... 82%, 570464 KB, 3675 KB/s, 155 seconds passed
+... 82%, 570496 KB, 3675 KB/s, 155 seconds passed
+... 82%, 570528 KB, 3675 KB/s, 155 seconds passed
+... 82%, 570560 KB, 3675 KB/s, 155 seconds passed
 
 .. parsed-literal::
 
-    ... 82%, 575840 KB, 3375 KB/s, 170 seconds passed
-... 82%, 575872 KB, 3376 KB/s, 170 seconds passed
+    ... 82%, 570592 KB, 3675 KB/s, 155 seconds passed
+... 82%, 570624 KB, 3675 KB/s, 155 seconds passed
+... 82%, 570656 KB, 3675 KB/s, 155 seconds passed
+... 82%, 570688 KB, 3675 KB/s, 155 seconds passed
+... 82%, 570720 KB, 3675 KB/s, 155 seconds passed
 
 .. parsed-literal::
 
-    ... 82%, 575904 KB, 3375 KB/s, 170 seconds passed
-... 82%, 575936 KB, 3375 KB/s, 170 seconds passed
-... 82%, 575968 KB, 3375 KB/s, 170 seconds passed
+    ... 82%, 570752 KB, 3675 KB/s, 155 seconds passed
+... 82%, 570784 KB, 3675 KB/s, 155 seconds passed
+... 82%, 570816 KB, 3675 KB/s, 155 seconds passed
+... 82%, 570848 KB, 3675 KB/s, 155 seconds passed
+... 82%, 570880 KB, 3675 KB/s, 155 seconds passed
+... 82%, 570912 KB, 3675 KB/s, 155 seconds passed
 
 .. parsed-literal::
 
-    ... 82%, 576000 KB, 3374 KB/s, 170 seconds passed
-... 82%, 576032 KB, 3374 KB/s, 170 seconds passed
+    ... 82%, 570944 KB, 3675 KB/s, 155 seconds passed
+... 82%, 570976 KB, 3675 KB/s, 155 seconds passed
+... 82%, 571008 KB, 3675 KB/s, 155 seconds passed
+... 82%, 571040 KB, 3675 KB/s, 155 seconds passed
+... 82%, 571072 KB, 3675 KB/s, 155 seconds passed
+... 82%, 571104 KB, 3675 KB/s, 155 seconds passed
 
 .. parsed-literal::
 
-    ... 82%, 576064 KB, 3374 KB/s, 170 seconds passed
-... 82%, 576096 KB, 3374 KB/s, 170 seconds passed
-... 82%, 576128 KB, 3374 KB/s, 170 seconds passed
-... 82%, 576160 KB, 3374 KB/s, 170 seconds passed
-... 82%, 576192 KB, 3374 KB/s, 170 seconds passed
+    ... 82%, 571136 KB, 3675 KB/s, 155 seconds passed
+... 82%, 571168 KB, 3675 KB/s, 155 seconds passed
+... 82%, 571200 KB, 3675 KB/s, 155 seconds passed
+... 82%, 571232 KB, 3675 KB/s, 155 seconds passed
+... 82%, 571264 KB, 3675 KB/s, 155 seconds passed
+... 82%, 571296 KB, 3675 KB/s, 155 seconds passed
 
 .. parsed-literal::
 
-    ... 82%, 576224 KB, 3374 KB/s, 170 seconds passed
-... 82%, 576256 KB, 3374 KB/s, 170 seconds passed
-... 82%, 576288 KB, 3374 KB/s, 170 seconds passed
+    ... 82%, 571328 KB, 3675 KB/s, 155 seconds passed
+... 82%, 571360 KB, 3675 KB/s, 155 seconds passed
+... 82%, 571392 KB, 3675 KB/s, 155 seconds passed
+... 82%, 571424 KB, 3675 KB/s, 155 seconds passed
+... 82%, 571456 KB, 3675 KB/s, 155 seconds passed
+... 82%, 571488 KB, 3675 KB/s, 155 seconds passed
 
 .. parsed-literal::
 
-    ... 82%, 576320 KB, 3373 KB/s, 170 seconds passed
-... 82%, 576352 KB, 3374 KB/s, 170 seconds passed
-... 82%, 576384 KB, 3374 KB/s, 170 seconds passed
-... 82%, 576416 KB, 3373 KB/s, 170 seconds passed
-... 82%, 576448 KB, 3373 KB/s, 170 seconds passed
+    ... 82%, 571520 KB, 3675 KB/s, 155 seconds passed
+... 82%, 571552 KB, 3675 KB/s, 155 seconds passed
+... 82%, 571584 KB, 3675 KB/s, 155 seconds passed
+... 82%, 571616 KB, 3675 KB/s, 155 seconds passed
+... 82%, 571648 KB, 3675 KB/s, 155 seconds passed
+... 82%, 571680 KB, 3675 KB/s, 155 seconds passed
 
 .. parsed-literal::
 
-    ... 82%, 576480 KB, 3374 KB/s, 170 seconds passed
-... 82%, 576512 KB, 3374 KB/s, 170 seconds passed
-... 82%, 576544 KB, 3373 KB/s, 170 seconds passed
-... 82%, 576576 KB, 3374 KB/s, 170 seconds passed
-... 82%, 576608 KB, 3374 KB/s, 170 seconds passed
-... 82%, 576640 KB, 3374 KB/s, 170 seconds passed
+    ... 82%, 571712 KB, 3675 KB/s, 155 seconds passed
+... 82%, 571744 KB, 3675 KB/s, 155 seconds passed
+... 82%, 571776 KB, 3675 KB/s, 155 seconds passed
+... 82%, 571808 KB, 3675 KB/s, 155 seconds passed
+... 82%, 571840 KB, 3675 KB/s, 155 seconds passed
+... 82%, 571872 KB, 3675 KB/s, 155 seconds passed
 
 .. parsed-literal::
 
-    ... 82%, 576672 KB, 3373 KB/s, 170 seconds passed
-... 82%, 576704 KB, 3374 KB/s, 170 seconds passed
-... 82%, 576736 KB, 3374 KB/s, 170 seconds passed
-... 82%, 576768 KB, 3374 KB/s, 170 seconds passed
+    ... 82%, 571904 KB, 3675 KB/s, 155 seconds passed
+... 82%, 571936 KB, 3675 KB/s, 155 seconds passed
+... 82%, 571968 KB, 3675 KB/s, 155 seconds passed
+... 82%, 572000 KB, 3675 KB/s, 155 seconds passed
+... 82%, 572032 KB, 3675 KB/s, 155 seconds passed
+... 82%, 572064 KB, 3675 KB/s, 155 seconds passed
 
 .. parsed-literal::
 
-    ... 82%, 576800 KB, 3373 KB/s, 170 seconds passed
-... 82%, 576832 KB, 3374 KB/s, 170 seconds passed
-... 82%, 576864 KB, 3374 KB/s, 170 seconds passed
-... 82%, 576896 KB, 3374 KB/s, 170 seconds passed
-... 82%, 576928 KB, 3374 KB/s, 170 seconds passed
-... 82%, 576960 KB, 3374 KB/s, 170 seconds passed
-... 82%, 576992 KB, 3374 KB/s, 170 seconds passed
-... 82%, 577024 KB, 3374 KB/s, 170 seconds passed
+    ... 82%, 572096 KB, 3675 KB/s, 155 seconds passed
+... 82%, 572128 KB, 3675 KB/s, 155 seconds passed
+... 82%, 572160 KB, 3675 KB/s, 155 seconds passed
+... 82%, 572192 KB, 3675 KB/s, 155 seconds passed
+... 82%, 572224 KB, 3675 KB/s, 155 seconds passed
+... 82%, 572256 KB, 3675 KB/s, 155 seconds passed
 
 .. parsed-literal::
 
-    ... 82%, 577056 KB, 3374 KB/s, 171 seconds passed
-... 82%, 577088 KB, 3374 KB/s, 171 seconds passed
-... 82%, 577120 KB, 3374 KB/s, 171 seconds passed
-... 82%, 577152 KB, 3374 KB/s, 171 seconds passed
+    ... 82%, 572288 KB, 3675 KB/s, 155 seconds passed
+... 82%, 572320 KB, 3675 KB/s, 155 seconds passed
+... 82%, 572352 KB, 3675 KB/s, 155 seconds passed
+... 82%, 572384 KB, 3675 KB/s, 155 seconds passed
+... 82%, 572416 KB, 3675 KB/s, 155 seconds passed
 
 .. parsed-literal::
 
-    ... 82%, 577184 KB, 3374 KB/s, 171 seconds passed
-... 82%, 577216 KB, 3374 KB/s, 171 seconds passed
-... 82%, 577248 KB, 3374 KB/s, 171 seconds passed
-... 83%, 577280 KB, 3374 KB/s, 171 seconds passed
-... 83%, 577312 KB, 3374 KB/s, 171 seconds passed
-... 83%, 577344 KB, 3374 KB/s, 171 seconds passed
-... 83%, 577376 KB, 3374 KB/s, 171 seconds passed
-... 83%, 577408 KB, 3374 KB/s, 171 seconds passed
+    ... 82%, 572448 KB, 3675 KB/s, 155 seconds passed
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+... 82%, 572576 KB, 3675 KB/s, 155 seconds passed
+... 82%, 572608 KB, 3675 KB/s, 155 seconds passed
+... 82%, 572640 KB, 3675 KB/s, 155 seconds passed
 
 .. parsed-literal::
 
-    ... 83%, 577440 KB, 3374 KB/s, 171 seconds passed
-... 83%, 577472 KB, 3374 KB/s, 171 seconds passed
-... 83%, 577504 KB, 3374 KB/s, 171 seconds passed
+    ... 82%, 572672 KB, 3675 KB/s, 155 seconds passed
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+... 82%, 572736 KB, 3675 KB/s, 155 seconds passed
+... 82%, 572768 KB, 3675 KB/s, 155 seconds passed
+... 82%, 572800 KB, 3675 KB/s, 155 seconds passed
 
 .. parsed-literal::
 
-    ... 83%, 577536 KB, 3374 KB/s, 171 seconds passed
-... 83%, 577568 KB, 3374 KB/s, 171 seconds passed
-... 83%, 577600 KB, 3374 KB/s, 171 seconds passed
-... 83%, 577632 KB, 3374 KB/s, 171 seconds passed
-... 83%, 577664 KB, 3374 KB/s, 171 seconds passed
-... 83%, 577696 KB, 3374 KB/s, 171 seconds passed
-... 83%, 577728 KB, 3374 KB/s, 171 seconds passed
-... 83%, 577760 KB, 3374 KB/s, 171 seconds passed
+    ... 82%, 572832 KB, 3675 KB/s, 155 seconds passed
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+... 82%, 572928 KB, 3675 KB/s, 155 seconds passed
+... 82%, 572960 KB, 3675 KB/s, 155 seconds passed
+... 82%, 572992 KB, 3675 KB/s, 155 seconds passed
 
 .. parsed-literal::
 
-    ... 83%, 577792 KB, 3374 KB/s, 171 seconds passed
-... 83%, 577824 KB, 3374 KB/s, 171 seconds passed
-... 83%, 577856 KB, 3374 KB/s, 171 seconds passed
-... 83%, 577888 KB, 3374 KB/s, 171 seconds passed
+    ... 82%, 573024 KB, 3675 KB/s, 155 seconds passed
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+... 82%, 573088 KB, 3675 KB/s, 155 seconds passed
+... 82%, 573120 KB, 3675 KB/s, 155 seconds passed
+... 82%, 573152 KB, 3675 KB/s, 155 seconds passed
 
 .. parsed-literal::
 
-    ... 83%, 577920 KB, 3374 KB/s, 171 seconds passed
-... 83%, 577952 KB, 3374 KB/s, 171 seconds passed
-... 83%, 577984 KB, 3374 KB/s, 171 seconds passed
-... 83%, 578016 KB, 3374 KB/s, 171 seconds passed
-... 83%, 578048 KB, 3374 KB/s, 171 seconds passed
-... 83%, 578080 KB, 3374 KB/s, 171 seconds passed
-... 83%, 578112 KB, 3374 KB/s, 171 seconds passed
-... 83%, 578144 KB, 3374 KB/s, 171 seconds passed
+    ... 82%, 573184 KB, 3675 KB/s, 155 seconds passed
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+... 82%, 573312 KB, 3675 KB/s, 155 seconds passed
+... 82%, 573344 KB, 3675 KB/s, 155 seconds passed
+... 82%, 573376 KB, 3675 KB/s, 156 seconds passed
 
 .. parsed-literal::
 
-    ... 83%, 578176 KB, 3374 KB/s, 171 seconds passed
-... 83%, 578208 KB, 3374 KB/s, 171 seconds passed
-... 83%, 578240 KB, 3374 KB/s, 171 seconds passed
-... 83%, 578272 KB, 3374 KB/s, 171 seconds passed
+    ... 82%, 573408 KB, 3675 KB/s, 156 seconds passed
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+... 82%, 573472 KB, 3675 KB/s, 156 seconds passed
+... 82%, 573504 KB, 3675 KB/s, 156 seconds passed
+... 82%, 573536 KB, 3675 KB/s, 156 seconds passed
 
 .. parsed-literal::
 
-    ... 83%, 578304 KB, 3374 KB/s, 171 seconds passed
-... 83%, 578336 KB, 3374 KB/s, 171 seconds passed
-... 83%, 578368 KB, 3374 KB/s, 171 seconds passed
-... 83%, 578400 KB, 3375 KB/s, 171 seconds passed
-... 83%, 578432 KB, 3374 KB/s, 171 seconds passed
-... 83%, 578464 KB, 3374 KB/s, 171 seconds passed
-... 83%, 578496 KB, 3374 KB/s, 171 seconds passed
-... 83%, 578528 KB, 3375 KB/s, 171 seconds passed
+    ... 82%, 573568 KB, 3675 KB/s, 156 seconds passed
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+... 82%, 573696 KB, 3675 KB/s, 156 seconds passed
+... 82%, 573728 KB, 3675 KB/s, 156 seconds passed
+... 82%, 573760 KB, 3675 KB/s, 156 seconds passed
 
 .. parsed-literal::
 
-    ... 83%, 578560 KB, 3374 KB/s, 171 seconds passed
-... 83%, 578592 KB, 3374 KB/s, 171 seconds passed
-... 83%, 578624 KB, 3375 KB/s, 171 seconds passed
-... 83%, 578656 KB, 3375 KB/s, 171 seconds passed
+    ... 82%, 573792 KB, 3675 KB/s, 156 seconds passed
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+... 82%, 573856 KB, 3675 KB/s, 156 seconds passed
+... 82%, 573888 KB, 3675 KB/s, 156 seconds passed
+... 82%, 573920 KB, 3675 KB/s, 156 seconds passed
 
 .. parsed-literal::
 
-    ... 83%, 578688 KB, 3374 KB/s, 171 seconds passed
-... 83%, 578720 KB, 3374 KB/s, 171 seconds passed
-... 83%, 578752 KB, 3375 KB/s, 171 seconds passed
-... 83%, 578784 KB, 3375 KB/s, 171 seconds passed
-... 83%, 578816 KB, 3374 KB/s, 171 seconds passed
-... 83%, 578848 KB, 3375 KB/s, 171 seconds passed
-... 83%, 578880 KB, 3375 KB/s, 171 seconds passed
-... 83%, 578912 KB, 3375 KB/s, 171 seconds passed
+    ... 82%, 573952 KB, 3675 KB/s, 156 seconds passed
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+... 82%, 574080 KB, 3675 KB/s, 156 seconds passed
+... 82%, 574112 KB, 3675 KB/s, 156 seconds passed
+... 82%, 574144 KB, 3675 KB/s, 156 seconds passed
 
 .. parsed-literal::
 
-    ... 83%, 578944 KB, 3374 KB/s, 171 seconds passed
-... 83%, 578976 KB, 3375 KB/s, 171 seconds passed
-... 83%, 579008 KB, 3375 KB/s, 171 seconds passed
-... 83%, 579040 KB, 3375 KB/s, 171 seconds passed
+    ... 82%, 574176 KB, 3675 KB/s, 156 seconds passed
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+... 82%, 574240 KB, 3675 KB/s, 156 seconds passed
+... 82%, 574272 KB, 3675 KB/s, 156 seconds passed
 
 .. parsed-literal::
 
-    ... 83%, 579072 KB, 3375 KB/s, 171 seconds passed
-... 83%, 579104 KB, 3375 KB/s, 171 seconds passed
-... 83%, 579136 KB, 3375 KB/s, 171 seconds passed
-... 83%, 579168 KB, 3375 KB/s, 171 seconds passed
-... 83%, 579200 KB, 3375 KB/s, 171 seconds passed
-... 83%, 579232 KB, 3375 KB/s, 171 seconds passed
-... 83%, 579264 KB, 3375 KB/s, 171 seconds passed
-... 83%, 579296 KB, 3375 KB/s, 171 seconds passed
+    ... 82%, 574304 KB, 3675 KB/s, 156 seconds passed
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+... 82%, 574464 KB, 3675 KB/s, 156 seconds passed
+... 82%, 574496 KB, 3675 KB/s, 156 seconds passed
+... 82%, 574528 KB, 3675 KB/s, 156 seconds passed
 
 .. parsed-literal::
 
-    ... 83%, 579328 KB, 3375 KB/s, 171 seconds passed
-... 83%, 579360 KB, 3375 KB/s, 171 seconds passed
-... 83%, 579392 KB, 3375 KB/s, 171 seconds passed
-... 83%, 579424 KB, 3375 KB/s, 171 seconds passed
+    ... 82%, 574560 KB, 3675 KB/s, 156 seconds passed
+... 82%, 574592 KB, 3675 KB/s, 156 seconds passed
+... 82%, 574624 KB, 3675 KB/s, 156 seconds passed
+... 82%, 574656 KB, 3675 KB/s, 156 seconds passed
 
 .. parsed-literal::
 
-    ... 83%, 579456 KB, 3375 KB/s, 171 seconds passed
-... 83%, 579488 KB, 3375 KB/s, 171 seconds passed
-... 83%, 579520 KB, 3375 KB/s, 171 seconds passed
-... 83%, 579552 KB, 3375 KB/s, 171 seconds passed
-... 83%, 579584 KB, 3375 KB/s, 171 seconds passed
-... 83%, 579616 KB, 3375 KB/s, 171 seconds passed
-... 83%, 579648 KB, 3375 KB/s, 171 seconds passed
-... 83%, 579680 KB, 3375 KB/s, 171 seconds passed
+    ... 82%, 574688 KB, 3675 KB/s, 156 seconds passed
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+... 82%, 574816 KB, 3675 KB/s, 156 seconds passed
+... 82%, 574848 KB, 3675 KB/s, 156 seconds passed
+... 82%, 574880 KB, 3675 KB/s, 156 seconds passed
+... 82%, 574912 KB, 3675 KB/s, 156 seconds passed
 
 .. parsed-literal::
 
-    ... 83%, 579712 KB, 3375 KB/s, 171 seconds passed
-... 83%, 579744 KB, 3375 KB/s, 171 seconds passed
-... 83%, 579776 KB, 3375 KB/s, 171 seconds passed
-... 83%, 579808 KB, 3375 KB/s, 171 seconds passed
+    ... 82%, 574944 KB, 3675 KB/s, 156 seconds passed
+... 82%, 574976 KB, 3675 KB/s, 156 seconds passed
+... 82%, 575008 KB, 3675 KB/s, 156 seconds passed
+... 82%, 575040 KB, 3675 KB/s, 156 seconds passed
 
 .. parsed-literal::
 
-    ... 83%, 579840 KB, 3375 KB/s, 171 seconds passed
-... 83%, 579872 KB, 3375 KB/s, 171 seconds passed
-... 83%, 579904 KB, 3375 KB/s, 171 seconds passed
-... 83%, 579936 KB, 3375 KB/s, 171 seconds passed
-... 83%, 579968 KB, 3375 KB/s, 171 seconds passed
-... 83%, 580000 KB, 3375 KB/s, 171 seconds passed
-... 83%, 580032 KB, 3375 KB/s, 171 seconds passed
-... 83%, 580064 KB, 3375 KB/s, 171 seconds passed
+    ... 82%, 575072 KB, 3675 KB/s, 156 seconds passed
+... 82%, 575104 KB, 3675 KB/s, 156 seconds passed
+... 82%, 575136 KB, 3675 KB/s, 156 seconds passed
+... 82%, 575168 KB, 3675 KB/s, 156 seconds passed
+... 82%, 575200 KB, 3675 KB/s, 156 seconds passed
+... 82%, 575232 KB, 3675 KB/s, 156 seconds passed
+... 82%, 575264 KB, 3675 KB/s, 156 seconds passed
+... 82%, 575296 KB, 3675 KB/s, 156 seconds passed
 
 .. parsed-literal::
 
-    ... 83%, 580096 KB, 3375 KB/s, 171 seconds passed
-... 83%, 580128 KB, 3375 KB/s, 171 seconds passed
-... 83%, 580160 KB, 3375 KB/s, 171 seconds passed
-... 83%, 580192 KB, 3375 KB/s, 171 seconds passed
+    ... 82%, 575328 KB, 3675 KB/s, 156 seconds passed
+... 82%, 575360 KB, 3675 KB/s, 156 seconds passed
+... 82%, 575392 KB, 3675 KB/s, 156 seconds passed
+... 82%, 575424 KB, 3675 KB/s, 156 seconds passed
 
 .. parsed-literal::
 
-    ... 83%, 580224 KB, 3375 KB/s, 171 seconds passed
-... 83%, 580256 KB, 3375 KB/s, 171 seconds passed
-... 83%, 580288 KB, 3375 KB/s, 171 seconds passed
-... 83%, 580320 KB, 3376 KB/s, 171 seconds passed
-... 83%, 580352 KB, 3375 KB/s, 171 seconds passed
-... 83%, 580384 KB, 3375 KB/s, 171 seconds passed
-... 83%, 580416 KB, 3375 KB/s, 171 seconds passed
-... 83%, 580448 KB, 3376 KB/s, 171 seconds passed
+    ... 82%, 575456 KB, 3675 KB/s, 156 seconds passed
+... 82%, 575488 KB, 3675 KB/s, 156 seconds passed
+... 82%, 575520 KB, 3675 KB/s, 156 seconds passed
+... 82%, 575552 KB, 3675 KB/s, 156 seconds passed
+... 82%, 575584 KB, 3675 KB/s, 156 seconds passed
+... 82%, 575616 KB, 3675 KB/s, 156 seconds passed
+... 82%, 575648 KB, 3675 KB/s, 156 seconds passed
+... 82%, 575680 KB, 3675 KB/s, 156 seconds passed
 
 .. parsed-literal::
 
-    ... 83%, 580480 KB, 3375 KB/s, 171 seconds passed
-... 83%, 580512 KB, 3375 KB/s, 171 seconds passed
-... 83%, 580544 KB, 3376 KB/s, 171 seconds passed
-... 83%, 580576 KB, 3376 KB/s, 171 seconds passed
+    ... 82%, 575712 KB, 3675 KB/s, 156 seconds passed
+... 82%, 575744 KB, 3675 KB/s, 156 seconds passed
+... 82%, 575776 KB, 3675 KB/s, 156 seconds passed
+... 82%, 575808 KB, 3675 KB/s, 156 seconds passed
 
 .. parsed-literal::
 
-    ... 83%, 580608 KB, 3375 KB/s, 171 seconds passed
-... 83%, 580640 KB, 3375 KB/s, 171 seconds passed
-... 83%, 580672 KB, 3376 KB/s, 171 seconds passed
-... 83%, 580704 KB, 3376 KB/s, 171 seconds passed
-... 83%, 580736 KB, 3375 KB/s, 172 seconds passed
-... 83%, 580768 KB, 3376 KB/s, 172 seconds passed
-... 83%, 580800 KB, 3376 KB/s, 172 seconds passed
-... 83%, 580832 KB, 3376 KB/s, 172 seconds passed
+    ... 82%, 575840 KB, 3675 KB/s, 156 seconds passed
+... 82%, 575872 KB, 3675 KB/s, 156 seconds passed
+... 82%, 575904 KB, 3675 KB/s, 156 seconds passed
+... 82%, 575936 KB, 3675 KB/s, 156 seconds passed
+... 82%, 575968 KB, 3675 KB/s, 156 seconds passed
+... 82%, 576000 KB, 3675 KB/s, 156 seconds passed
+... 82%, 576032 KB, 3675 KB/s, 156 seconds passed
+... 82%, 576064 KB, 3675 KB/s, 156 seconds passed
 
 .. parsed-literal::
 
-    ... 83%, 580864 KB, 3375 KB/s, 172 seconds passed
-... 83%, 580896 KB, 3376 KB/s, 172 seconds passed
-... 83%, 580928 KB, 3376 KB/s, 172 seconds passed
-... 83%, 580960 KB, 3376 KB/s, 172 seconds passed
+    ... 82%, 576096 KB, 3675 KB/s, 156 seconds passed
+... 82%, 576128 KB, 3675 KB/s, 156 seconds passed
+... 82%, 576160 KB, 3675 KB/s, 156 seconds passed
+... 82%, 576192 KB, 3675 KB/s, 156 seconds passed
 
 .. parsed-literal::
 
-    ... 83%, 580992 KB, 3375 KB/s, 172 seconds passed
-... 83%, 581024 KB, 3376 KB/s, 172 seconds passed
-... 83%, 581056 KB, 3376 KB/s, 172 seconds passed
-... 83%, 581088 KB, 3376 KB/s, 172 seconds passed
-... 83%, 581120 KB, 3376 KB/s, 172 seconds passed
-... 83%, 581152 KB, 3376 KB/s, 172 seconds passed
-... 83%, 581184 KB, 3376 KB/s, 172 seconds passed
+    ... 82%, 576224 KB, 3675 KB/s, 156 seconds passed
+... 82%, 576256 KB, 3675 KB/s, 156 seconds passed
+... 82%, 576288 KB, 3675 KB/s, 156 seconds passed
+... 82%, 576320 KB, 3675 KB/s, 156 seconds passed
+... 82%, 576352 KB, 3675 KB/s, 156 seconds passed
+... 82%, 576384 KB, 3675 KB/s, 156 seconds passed
+... 82%, 576416 KB, 3675 KB/s, 156 seconds passed
 
 .. parsed-literal::
 
-    ... 83%, 581216 KB, 3376 KB/s, 172 seconds passed
-... 83%, 581248 KB, 3376 KB/s, 172 seconds passed
-... 83%, 581280 KB, 3376 KB/s, 172 seconds passed
-... 83%, 581312 KB, 3376 KB/s, 172 seconds passed
+    ... 82%, 576448 KB, 3675 KB/s, 156 seconds passed
+... 82%, 576480 KB, 3675 KB/s, 156 seconds passed
+... 82%, 576512 KB, 3675 KB/s, 156 seconds passed
+... 82%, 576544 KB, 3675 KB/s, 156 seconds passed
+... 82%, 576576 KB, 3675 KB/s, 156 seconds passed
 
 .. parsed-literal::
 
-    ... 83%, 581344 KB, 3376 KB/s, 172 seconds passed
-... 83%, 581376 KB, 3376 KB/s, 172 seconds passed
-... 83%, 581408 KB, 3376 KB/s, 172 seconds passed
-... 83%, 581440 KB, 3376 KB/s, 172 seconds passed
-... 83%, 581472 KB, 3376 KB/s, 172 seconds passed
-... 83%, 581504 KB, 3376 KB/s, 172 seconds passed
-... 83%, 581536 KB, 3376 KB/s, 172 seconds passed
+    ... 82%, 576608 KB, 3675 KB/s, 156 seconds passed
+... 82%, 576640 KB, 3675 KB/s, 156 seconds passed
+... 82%, 576672 KB, 3675 KB/s, 156 seconds passed
+... 82%, 576704 KB, 3675 KB/s, 156 seconds passed
+... 82%, 576736 KB, 3675 KB/s, 156 seconds passed
+... 82%, 576768 KB, 3675 KB/s, 156 seconds passed
+... 82%, 576800 KB, 3675 KB/s, 156 seconds passed
 
 .. parsed-literal::
 
-    ... 83%, 581568 KB, 3376 KB/s, 172 seconds passed
-... 83%, 581600 KB, 3376 KB/s, 172 seconds passed
-... 83%, 581632 KB, 3376 KB/s, 172 seconds passed
-... 83%, 581664 KB, 3376 KB/s, 172 seconds passed
-... 83%, 581696 KB, 3376 KB/s, 172 seconds passed
+    ... 82%, 576832 KB, 3675 KB/s, 156 seconds passed
+... 82%, 576864 KB, 3675 KB/s, 156 seconds passed
+... 82%, 576896 KB, 3675 KB/s, 156 seconds passed
+... 82%, 576928 KB, 3675 KB/s, 156 seconds passed
 
 .. parsed-literal::
 
-    ... 83%, 581728 KB, 3376 KB/s, 172 seconds passed
-... 83%, 581760 KB, 3376 KB/s, 172 seconds passed
-... 83%, 581792 KB, 3376 KB/s, 172 seconds passed
-... 83%, 581824 KB, 3376 KB/s, 172 seconds passed
-... 83%, 581856 KB, 3376 KB/s, 172 seconds passed
-... 83%, 581888 KB, 3376 KB/s, 172 seconds passed
-... 83%, 581920 KB, 3376 KB/s, 172 seconds passed
+    ... 82%, 576960 KB, 3675 KB/s, 156 seconds passed
+... 82%, 576992 KB, 3675 KB/s, 156 seconds passed
+... 82%, 577024 KB, 3675 KB/s, 156 seconds passed
+... 82%, 577056 KB, 3675 KB/s, 156 seconds passed
+... 82%, 577088 KB, 3675 KB/s, 157 seconds passed
+... 82%, 577120 KB, 3675 KB/s, 157 seconds passed
+... 82%, 577152 KB, 3675 KB/s, 157 seconds passed
+... 82%, 577184 KB, 3675 KB/s, 157 seconds passed
 
 .. parsed-literal::
 
-    ... 83%, 581952 KB, 3376 KB/s, 172 seconds passed
-... 83%, 581984 KB, 3376 KB/s, 172 seconds passed
-... 83%, 582016 KB, 3376 KB/s, 172 seconds passed
-... 83%, 582048 KB, 3376 KB/s, 172 seconds passed
-... 83%, 582080 KB, 3376 KB/s, 172 seconds passed
+    ... 82%, 577216 KB, 3675 KB/s, 157 seconds passed
+... 82%, 577248 KB, 3675 KB/s, 157 seconds passed
+... 83%, 577280 KB, 3675 KB/s, 157 seconds passed
+... 83%, 577312 KB, 3675 KB/s, 157 seconds passed
 
 .. parsed-literal::
 
-    ... 83%, 582112 KB, 3376 KB/s, 172 seconds passed
-... 83%, 582144 KB, 3376 KB/s, 172 seconds passed
-... 83%, 582176 KB, 3376 KB/s, 172 seconds passed
-... 83%, 582208 KB, 3376 KB/s, 172 seconds passed
-... 83%, 582240 KB, 3376 KB/s, 172 seconds passed
+    ... 83%, 577344 KB, 3675 KB/s, 157 seconds passed
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+... 83%, 577408 KB, 3675 KB/s, 157 seconds passed
+... 83%, 577440 KB, 3675 KB/s, 157 seconds passed
+... 83%, 577472 KB, 3675 KB/s, 157 seconds passed
+... 83%, 577504 KB, 3675 KB/s, 157 seconds passed
+... 83%, 577536 KB, 3675 KB/s, 157 seconds passed
+... 83%, 577568 KB, 3675 KB/s, 157 seconds passed
 
 .. parsed-literal::
 
-    ... 83%, 582272 KB, 3376 KB/s, 172 seconds passed
-... 83%, 582304 KB, 3376 KB/s, 172 seconds passed
-... 83%, 582336 KB, 3376 KB/s, 172 seconds passed
-... 83%, 582368 KB, 3376 KB/s, 172 seconds passed
-... 83%, 582400 KB, 3376 KB/s, 172 seconds passed
-... 83%, 582432 KB, 3376 KB/s, 172 seconds passed
-... 83%, 582464 KB, 3376 KB/s, 172 seconds passed
+    ... 83%, 577600 KB, 3675 KB/s, 157 seconds passed
+... 83%, 577632 KB, 3675 KB/s, 157 seconds passed
+... 83%, 577664 KB, 3675 KB/s, 157 seconds passed
+... 83%, 577696 KB, 3675 KB/s, 157 seconds passed
+... 83%, 577728 KB, 3675 KB/s, 157 seconds passed
 
 .. parsed-literal::
 
-    ... 83%, 582496 KB, 3376 KB/s, 172 seconds passed
-... 83%, 582528 KB, 3376 KB/s, 172 seconds passed
-... 83%, 582560 KB, 3376 KB/s, 172 seconds passed
-... 83%, 582592 KB, 3377 KB/s, 172 seconds passed
-... 83%, 582624 KB, 3376 KB/s, 172 seconds passed
+    ... 83%, 577760 KB, 3675 KB/s, 157 seconds passed
+... 83%, 577792 KB, 3675 KB/s, 157 seconds passed
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+... 83%, 577856 KB, 3675 KB/s, 157 seconds passed
+... 83%, 577888 KB, 3675 KB/s, 157 seconds passed
+... 83%, 577920 KB, 3675 KB/s, 157 seconds passed
+... 83%, 577952 KB, 3675 KB/s, 157 seconds passed
 
 .. parsed-literal::
 
-    ... 83%, 582656 KB, 3376 KB/s, 172 seconds passed
-... 83%, 582688 KB, 3376 KB/s, 172 seconds passed
-... 83%, 582720 KB, 3377 KB/s, 172 seconds passed
-... 83%, 582752 KB, 3376 KB/s, 172 seconds passed
-... 83%, 582784 KB, 3376 KB/s, 172 seconds passed
-... 83%, 582816 KB, 3377 KB/s, 172 seconds passed
-... 83%, 582848 KB, 3377 KB/s, 172 seconds passed
+    ... 83%, 577984 KB, 3675 KB/s, 157 seconds passed
+... 83%, 578016 KB, 3675 KB/s, 157 seconds passed
+... 83%, 578048 KB, 3675 KB/s, 157 seconds passed
+... 83%, 578080 KB, 3675 KB/s, 157 seconds passed
 
 .. parsed-literal::
 
-    ... 83%, 582880 KB, 3376 KB/s, 172 seconds passed
-... 83%, 582912 KB, 3376 KB/s, 172 seconds passed
-... 83%, 582944 KB, 3377 KB/s, 172 seconds passed
-... 83%, 582976 KB, 3377 KB/s, 172 seconds passed
-... 83%, 583008 KB, 3376 KB/s, 172 seconds passed
+    ... 83%, 578112 KB, 3675 KB/s, 157 seconds passed
+... 83%, 578144 KB, 3675 KB/s, 157 seconds passed
+... 83%, 578176 KB, 3675 KB/s, 157 seconds passed
+... 83%, 578208 KB, 3675 KB/s, 157 seconds passed
+... 83%, 578240 KB, 3675 KB/s, 157 seconds passed
+... 83%, 578272 KB, 3675 KB/s, 157 seconds passed
+... 83%, 578304 KB, 3675 KB/s, 157 seconds passed
 
 .. parsed-literal::
 
-    ... 83%, 583040 KB, 3377 KB/s, 172 seconds passed
-... 83%, 583072 KB, 3377 KB/s, 172 seconds passed
-... 83%, 583104 KB, 3377 KB/s, 172 seconds passed
-... 83%, 583136 KB, 3376 KB/s, 172 seconds passed
-... 83%, 583168 KB, 3377 KB/s, 172 seconds passed
-... 83%, 583200 KB, 3377 KB/s, 172 seconds passed
-... 83%, 583232 KB, 3377 KB/s, 172 seconds passed
+    ... 83%, 578336 KB, 3675 KB/s, 157 seconds passed
+... 83%, 578368 KB, 3675 KB/s, 157 seconds passed
+... 83%, 578400 KB, 3675 KB/s, 157 seconds passed
+... 83%, 578432 KB, 3675 KB/s, 157 seconds passed
+... 83%, 578464 KB, 3675 KB/s, 157 seconds passed
 
 .. parsed-literal::
 
-    ... 83%, 583264 KB, 3377 KB/s, 172 seconds passed
-... 83%, 583296 KB, 3377 KB/s, 172 seconds passed
-... 83%, 583328 KB, 3377 KB/s, 172 seconds passed
-... 83%, 583360 KB, 3377 KB/s, 172 seconds passed
+    ... 83%, 578496 KB, 3675 KB/s, 157 seconds passed
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+... 83%, 578560 KB, 3675 KB/s, 157 seconds passed
+... 83%, 578592 KB, 3675 KB/s, 157 seconds passed
+... 83%, 578624 KB, 3675 KB/s, 157 seconds passed
+... 83%, 578656 KB, 3675 KB/s, 157 seconds passed
+... 83%, 578688 KB, 3675 KB/s, 157 seconds passed
 
 .. parsed-literal::
 
-    ... 83%, 583392 KB, 3377 KB/s, 172 seconds passed
-... 83%, 583424 KB, 3377 KB/s, 172 seconds passed
-... 83%, 583456 KB, 3377 KB/s, 172 seconds passed
-... 83%, 583488 KB, 3377 KB/s, 172 seconds passed
-... 83%, 583520 KB, 3377 KB/s, 172 seconds passed
-... 83%, 583552 KB, 3377 KB/s, 172 seconds passed
-... 83%, 583584 KB, 3377 KB/s, 172 seconds passed
-... 83%, 583616 KB, 3377 KB/s, 172 seconds passed
+    ... 83%, 578720 KB, 3675 KB/s, 157 seconds passed
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+... 83%, 578784 KB, 3675 KB/s, 157 seconds passed
+... 83%, 578816 KB, 3675 KB/s, 157 seconds passed
+... 83%, 578848 KB, 3675 KB/s, 157 seconds passed
 
 .. parsed-literal::
 
-    ... 83%, 583648 KB, 3377 KB/s, 172 seconds passed
-... 83%, 583680 KB, 3377 KB/s, 172 seconds passed
-... 83%, 583712 KB, 3377 KB/s, 172 seconds passed
-... 83%, 583744 KB, 3377 KB/s, 172 seconds passed
+    ... 83%, 578880 KB, 3675 KB/s, 157 seconds passed
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+... 83%, 578976 KB, 3675 KB/s, 157 seconds passed
+... 83%, 579008 KB, 3675 KB/s, 157 seconds passed
+... 83%, 579040 KB, 3675 KB/s, 157 seconds passed
 
 .. parsed-literal::
 
-    ... 83%, 583776 KB, 3377 KB/s, 172 seconds passed
-... 83%, 583808 KB, 3377 KB/s, 172 seconds passed
-... 83%, 583840 KB, 3377 KB/s, 172 seconds passed
-... 83%, 583872 KB, 3377 KB/s, 172 seconds passed
-... 83%, 583904 KB, 3377 KB/s, 172 seconds passed
-... 83%, 583936 KB, 3377 KB/s, 172 seconds passed
-... 83%, 583968 KB, 3377 KB/s, 172 seconds passed
+    ... 83%, 579072 KB, 3675 KB/s, 157 seconds passed
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+... 83%, 579168 KB, 3675 KB/s, 157 seconds passed
+... 83%, 579200 KB, 3675 KB/s, 157 seconds passed
+... 83%, 579232 KB, 3675 KB/s, 157 seconds passed
 
 .. parsed-literal::
 
-    ... 83%, 584000 KB, 3377 KB/s, 172 seconds passed
-... 83%, 584032 KB, 3377 KB/s, 172 seconds passed
-... 83%, 584064 KB, 3377 KB/s, 172 seconds passed
-... 83%, 584096 KB, 3377 KB/s, 172 seconds passed
-... 83%, 584128 KB, 3377 KB/s, 172 seconds passed
+    ... 83%, 579264 KB, 3675 KB/s, 157 seconds passed
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+... 83%, 579392 KB, 3675 KB/s, 157 seconds passed
+... 83%, 579424 KB, 3675 KB/s, 157 seconds passed
+... 83%, 579456 KB, 3675 KB/s, 157 seconds passed
 
 .. parsed-literal::
 
-    ... 83%, 584160 KB, 3377 KB/s, 172 seconds passed
-... 83%, 584192 KB, 3377 KB/s, 172 seconds passed
-... 83%, 584224 KB, 3377 KB/s, 172 seconds passed
-... 84%, 584256 KB, 3377 KB/s, 172 seconds passed
-... 84%, 584288 KB, 3377 KB/s, 172 seconds passed
-... 84%, 584320 KB, 3377 KB/s, 172 seconds passed
-... 84%, 584352 KB, 3377 KB/s, 172 seconds passed
+    ... 83%, 579488 KB, 3675 KB/s, 157 seconds passed
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+... 83%, 579552 KB, 3675 KB/s, 157 seconds passed
+... 83%, 579584 KB, 3675 KB/s, 157 seconds passed
+... 83%, 579616 KB, 3675 KB/s, 157 seconds passed
 
 .. parsed-literal::
 
-    ... 84%, 584384 KB, 3377 KB/s, 173 seconds passed
-... 84%, 584416 KB, 3377 KB/s, 173 seconds passed
-... 84%, 584448 KB, 3377 KB/s, 173 seconds passed
-... 84%, 584480 KB, 3377 KB/s, 173 seconds passed
-... 84%, 584512 KB, 3377 KB/s, 173 seconds passed
+    ... 83%, 579648 KB, 3675 KB/s, 157 seconds passed
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+... 83%, 579744 KB, 3675 KB/s, 157 seconds passed
+... 83%, 579776 KB, 3675 KB/s, 157 seconds passed
+... 83%, 579808 KB, 3675 KB/s, 157 seconds passed
 
 .. parsed-literal::
 
-    ... 84%, 584544 KB, 3377 KB/s, 173 seconds passed
-... 84%, 584576 KB, 3377 KB/s, 173 seconds passed
-... 84%, 584608 KB, 3377 KB/s, 173 seconds passed
-... 84%, 584640 KB, 3377 KB/s, 173 seconds passed
-... 84%, 584672 KB, 3377 KB/s, 173 seconds passed
-... 84%, 584704 KB, 3377 KB/s, 173 seconds passed
-... 84%, 584736 KB, 3377 KB/s, 173 seconds passed
+    ... 83%, 579840 KB, 3675 KB/s, 157 seconds passed
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+... 83%, 579936 KB, 3675 KB/s, 157 seconds passed
+... 83%, 579968 KB, 3675 KB/s, 157 seconds passed
+... 83%, 580000 KB, 3675 KB/s, 157 seconds passed
 
 .. parsed-literal::
 
-    ... 84%, 584768 KB, 3377 KB/s, 173 seconds passed
-... 84%, 584800 KB, 3377 KB/s, 173 seconds passed
-... 84%, 584832 KB, 3377 KB/s, 173 seconds passed
-... 84%, 584864 KB, 3378 KB/s, 173 seconds passed
-... 84%, 584896 KB, 3377 KB/s, 173 seconds passed
+    ... 83%, 580032 KB, 3675 KB/s, 157 seconds passed
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+... 83%, 580096 KB, 3675 KB/s, 157 seconds passed
+... 83%, 580128 KB, 3675 KB/s, 157 seconds passed
+... 83%, 580160 KB, 3675 KB/s, 157 seconds passed
 
 .. parsed-literal::
 
-    ... 84%, 584928 KB, 3377 KB/s, 173 seconds passed
-... 84%, 584960 KB, 3377 KB/s, 173 seconds passed
-... 84%, 584992 KB, 3378 KB/s, 173 seconds passed
-... 84%, 585024 KB, 3377 KB/s, 173 seconds passed
-... 84%, 585056 KB, 3377 KB/s, 173 seconds passed
-... 84%, 585088 KB, 3378 KB/s, 173 seconds passed
-... 84%, 585120 KB, 3378 KB/s, 173 seconds passed
+    ... 83%, 580192 KB, 3675 KB/s, 157 seconds passed
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+... 83%, 580288 KB, 3675 KB/s, 157 seconds passed
+... 83%, 580320 KB, 3675 KB/s, 157 seconds passed
+... 83%, 580352 KB, 3675 KB/s, 157 seconds passed
+... 83%, 580384 KB, 3675 KB/s, 157 seconds passed
 
 .. parsed-literal::
 
-    ... 84%, 585152 KB, 3377 KB/s, 173 seconds passed
-... 84%, 585184 KB, 3377 KB/s, 173 seconds passed
-... 84%, 585216 KB, 3378 KB/s, 173 seconds passed
-... 84%, 585248 KB, 3378 KB/s, 173 seconds passed
+    ... 83%, 580416 KB, 3675 KB/s, 157 seconds passed
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+... 83%, 580480 KB, 3675 KB/s, 157 seconds passed
+... 83%, 580512 KB, 3675 KB/s, 157 seconds passed
+... 83%, 580544 KB, 3675 KB/s, 157 seconds passed
 
 .. parsed-literal::
 
-    ... 84%, 585280 KB, 3377 KB/s, 173 seconds passed
-... 84%, 585312 KB, 3377 KB/s, 173 seconds passed
-... 84%, 585344 KB, 3378 KB/s, 173 seconds passed
-... 84%, 585376 KB, 3378 KB/s, 173 seconds passed
-... 84%, 585408 KB, 3378 KB/s, 173 seconds passed
-... 84%, 585440 KB, 3378 KB/s, 173 seconds passed
-... 84%, 585472 KB, 3378 KB/s, 173 seconds passed
-... 84%, 585504 KB, 3378 KB/s, 173 seconds passed
+    ... 83%, 580576 KB, 3675 KB/s, 157 seconds passed
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+... 83%, 580704 KB, 3675 KB/s, 157 seconds passed
+... 83%, 580736 KB, 3675 KB/s, 157 seconds passed
+... 83%, 580768 KB, 3675 KB/s, 158 seconds passed
 
 .. parsed-literal::
 
-    ... 84%, 585536 KB, 3378 KB/s, 173 seconds passed
-... 84%, 585568 KB, 3378 KB/s, 173 seconds passed
-... 84%, 585600 KB, 3378 KB/s, 173 seconds passed
-... 84%, 585632 KB, 3378 KB/s, 173 seconds passed
+    ... 83%, 580800 KB, 3675 KB/s, 158 seconds passed
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+... 83%, 580864 KB, 3675 KB/s, 158 seconds passed
+... 83%, 580896 KB, 3675 KB/s, 158 seconds passed
+... 83%, 580928 KB, 3675 KB/s, 158 seconds passed
 
 .. parsed-literal::
 
-    ... 84%, 585664 KB, 3378 KB/s, 173 seconds passed
-... 84%, 585696 KB, 3378 KB/s, 173 seconds passed
-... 84%, 585728 KB, 3378 KB/s, 173 seconds passed
-... 84%, 585760 KB, 3378 KB/s, 173 seconds passed
-... 84%, 585792 KB, 3378 KB/s, 173 seconds passed
-... 84%, 585824 KB, 3378 KB/s, 173 seconds passed
-... 84%, 585856 KB, 3378 KB/s, 173 seconds passed
-... 84%, 585888 KB, 3378 KB/s, 173 seconds passed
+    ... 83%, 580960 KB, 3675 KB/s, 158 seconds passed
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+... 83%, 581088 KB, 3675 KB/s, 158 seconds passed
+... 83%, 581120 KB, 3675 KB/s, 158 seconds passed
+... 83%, 581152 KB, 3675 KB/s, 158 seconds passed
 
 .. parsed-literal::
 
-    ... 84%, 585920 KB, 3378 KB/s, 173 seconds passed
-... 84%, 585952 KB, 3378 KB/s, 173 seconds passed
-... 84%, 585984 KB, 3378 KB/s, 173 seconds passed
-... 84%, 586016 KB, 3378 KB/s, 173 seconds passed
+    ... 83%, 581184 KB, 3675 KB/s, 158 seconds passed
+... 83%, 581216 KB, 3675 KB/s, 158 seconds passed
+... 83%, 581248 KB, 3675 KB/s, 158 seconds passed
+... 83%, 581280 KB, 3675 KB/s, 158 seconds passed
 
 .. parsed-literal::
 
-    ... 84%, 586048 KB, 3378 KB/s, 173 seconds passed
-... 84%, 586080 KB, 3378 KB/s, 173 seconds passed
-... 84%, 586112 KB, 3378 KB/s, 173 seconds passed
-... 84%, 586144 KB, 3378 KB/s, 173 seconds passed
-... 84%, 586176 KB, 3378 KB/s, 173 seconds passed
-... 84%, 586208 KB, 3378 KB/s, 173 seconds passed
-... 84%, 586240 KB, 3378 KB/s, 173 seconds passed
-... 84%, 586272 KB, 3378 KB/s, 173 seconds passed
+    ... 83%, 581312 KB, 3675 KB/s, 158 seconds passed
+... 83%, 581344 KB, 3675 KB/s, 158 seconds passed
+... 83%, 581376 KB, 3675 KB/s, 158 seconds passed
+... 83%, 581408 KB, 3675 KB/s, 158 seconds passed
+... 83%, 581440 KB, 3675 KB/s, 158 seconds passed
+... 83%, 581472 KB, 3675 KB/s, 158 seconds passed
+... 83%, 581504 KB, 3675 KB/s, 158 seconds passed
 
 .. parsed-literal::
 
-    ... 84%, 586304 KB, 3378 KB/s, 173 seconds passed
-... 84%, 586336 KB, 3378 KB/s, 173 seconds passed
-... 84%, 586368 KB, 3378 KB/s, 173 seconds passed
-... 84%, 586400 KB, 3378 KB/s, 173 seconds passed
+    ... 83%, 581536 KB, 3675 KB/s, 158 seconds passed
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+... 83%, 581600 KB, 3675 KB/s, 158 seconds passed
+... 83%, 581632 KB, 3675 KB/s, 158 seconds passed
+... 83%, 581664 KB, 3675 KB/s, 158 seconds passed
 
 .. parsed-literal::
 
-    ... 84%, 586432 KB, 3378 KB/s, 173 seconds passed
-... 84%, 586464 KB, 3378 KB/s, 173 seconds passed
-... 84%, 586496 KB, 3378 KB/s, 173 seconds passed
-... 84%, 586528 KB, 3378 KB/s, 173 seconds passed
-... 84%, 586560 KB, 3378 KB/s, 173 seconds passed
-... 84%, 586592 KB, 3378 KB/s, 173 seconds passed
-... 84%, 586624 KB, 3378 KB/s, 173 seconds passed
+    ... 83%, 581696 KB, 3675 KB/s, 158 seconds passed
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+... 83%, 581760 KB, 3675 KB/s, 158 seconds passed
+... 83%, 581792 KB, 3675 KB/s, 158 seconds passed
+... 83%, 581824 KB, 3675 KB/s, 158 seconds passed
+... 83%, 581856 KB, 3675 KB/s, 158 seconds passed
+... 83%, 581888 KB, 3675 KB/s, 158 seconds passed
+... 83%, 581920 KB, 3675 KB/s, 158 seconds passed
 
 .. parsed-literal::
 
-    ... 84%, 586656 KB, 3378 KB/s, 173 seconds passed
-... 84%, 586688 KB, 3378 KB/s, 173 seconds passed
-... 84%, 586720 KB, 3378 KB/s, 173 seconds passed
-... 84%, 586752 KB, 3378 KB/s, 173 seconds passed
-... 84%, 586784 KB, 3378 KB/s, 173 seconds passed
+    ... 83%, 581952 KB, 3675 KB/s, 158 seconds passed
+... 83%, 581984 KB, 3675 KB/s, 158 seconds passed
+... 83%, 582016 KB, 3675 KB/s, 158 seconds passed
+... 83%, 582048 KB, 3675 KB/s, 158 seconds passed
 
 .. parsed-literal::
 
-    ... 84%, 586816 KB, 3378 KB/s, 173 seconds passed
-... 84%, 586848 KB, 3378 KB/s, 173 seconds passed
-... 84%, 586880 KB, 3378 KB/s, 173 seconds passed
-... 84%, 586912 KB, 3379 KB/s, 173 seconds passed
-... 84%, 586944 KB, 3378 KB/s, 173 seconds passed
-... 84%, 586976 KB, 3378 KB/s, 173 seconds passed
+    ... 83%, 582080 KB, 3675 KB/s, 158 seconds passed
+... 83%, 582112 KB, 3675 KB/s, 158 seconds passed
+... 83%, 582144 KB, 3675 KB/s, 158 seconds passed
+... 83%, 582176 KB, 3675 KB/s, 158 seconds passed
+... 83%, 582208 KB, 3675 KB/s, 158 seconds passed
+... 83%, 582240 KB, 3675 KB/s, 158 seconds passed
+... 83%, 582272 KB, 3675 KB/s, 158 seconds passed
+... 83%, 582304 KB, 3675 KB/s, 158 seconds passed
 
 .. parsed-literal::
 
-    ... 84%, 587008 KB, 3378 KB/s, 173 seconds passed
-... 84%, 587040 KB, 3379 KB/s, 173 seconds passed
-... 84%, 587072 KB, 3378 KB/s, 173 seconds passed
-... 84%, 587104 KB, 3378 KB/s, 173 seconds passed
-... 84%, 587136 KB, 3378 KB/s, 173 seconds passed
-... 84%, 587168 KB, 3379 KB/s, 173 seconds passed
+    ... 83%, 582336 KB, 3675 KB/s, 158 seconds passed
+... 83%, 582368 KB, 3675 KB/s, 158 seconds passed
+... 83%, 582400 KB, 3675 KB/s, 158 seconds passed
+... 83%, 582432 KB, 3675 KB/s, 158 seconds passed
 
 .. parsed-literal::
 
-    ... 84%, 587200 KB, 3378 KB/s, 173 seconds passed
-... 84%, 587232 KB, 3378 KB/s, 173 seconds passed
-... 84%, 587264 KB, 3379 KB/s, 173 seconds passed
-... 84%, 587296 KB, 3379 KB/s, 173 seconds passed
-... 84%, 587328 KB, 3378 KB/s, 173 seconds passed
+    ... 83%, 582464 KB, 3675 KB/s, 158 seconds passed
+... 83%, 582496 KB, 3675 KB/s, 158 seconds passed
+... 83%, 582528 KB, 3675 KB/s, 158 seconds passed
+... 83%, 582560 KB, 3675 KB/s, 158 seconds passed
+... 83%, 582592 KB, 3675 KB/s, 158 seconds passed
+... 83%, 582624 KB, 3675 KB/s, 158 seconds passed
+... 83%, 582656 KB, 3675 KB/s, 158 seconds passed
 
 .. parsed-literal::
 
-    ... 84%, 587360 KB, 3378 KB/s, 173 seconds passed
-... 84%, 587392 KB, 3379 KB/s, 173 seconds passed
-... 84%, 587424 KB, 3379 KB/s, 173 seconds passed
-... 84%, 587456 KB, 3379 KB/s, 173 seconds passed
-... 84%, 587488 KB, 3379 KB/s, 173 seconds passed
-... 84%, 587520 KB, 3379 KB/s, 173 seconds passed
-... 84%, 587552 KB, 3379 KB/s, 173 seconds passed
+    ... 83%, 582688 KB, 3675 KB/s, 158 seconds passed
+... 83%, 582720 KB, 3675 KB/s, 158 seconds passed
+... 83%, 582752 KB, 3675 KB/s, 158 seconds passed
+... 83%, 582784 KB, 3675 KB/s, 158 seconds passed
 
 .. parsed-literal::
 
-    ... 84%, 587584 KB, 3379 KB/s, 173 seconds passed
-... 84%, 587616 KB, 3379 KB/s, 173 seconds passed
-... 84%, 587648 KB, 3379 KB/s, 173 seconds passed
-... 84%, 587680 KB, 3379 KB/s, 173 seconds passed
-... 84%, 587712 KB, 3379 KB/s, 173 seconds passed
+    ... 83%, 582816 KB, 3675 KB/s, 158 seconds passed
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+... 83%, 582976 KB, 3675 KB/s, 158 seconds passed
+... 83%, 583008 KB, 3675 KB/s, 158 seconds passed
+... 83%, 583040 KB, 3675 KB/s, 158 seconds passed
 
 .. parsed-literal::
 
-    ... 84%, 587744 KB, 3379 KB/s, 173 seconds passed
-... 84%, 587776 KB, 3379 KB/s, 173 seconds passed
-... 84%, 587808 KB, 3379 KB/s, 173 seconds passed
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-... 84%, 587872 KB, 3379 KB/s, 173 seconds passed
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-... 84%, 587936 KB, 3379 KB/s, 173 seconds passed
+    ... 83%, 583072 KB, 3675 KB/s, 158 seconds passed
+... 83%, 583104 KB, 3675 KB/s, 158 seconds passed
+... 83%, 583136 KB, 3675 KB/s, 158 seconds passed
+... 83%, 583168 KB, 3675 KB/s, 158 seconds passed
 
 .. parsed-literal::
 
-    ... 84%, 587968 KB, 3379 KB/s, 173 seconds passed
-... 84%, 588000 KB, 3379 KB/s, 174 seconds passed
-... 84%, 588032 KB, 3379 KB/s, 174 seconds passed
-... 84%, 588064 KB, 3379 KB/s, 174 seconds passed
-... 84%, 588096 KB, 3379 KB/s, 174 seconds passed
+    ... 83%, 583200 KB, 3675 KB/s, 158 seconds passed
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+... 83%, 583360 KB, 3675 KB/s, 158 seconds passed
+... 83%, 583392 KB, 3675 KB/s, 158 seconds passed
+... 83%, 583424 KB, 3675 KB/s, 158 seconds passed
 
 .. parsed-literal::
 
-    ... 84%, 588128 KB, 3379 KB/s, 174 seconds passed
-... 84%, 588160 KB, 3379 KB/s, 174 seconds passed
-... 84%, 588192 KB, 3379 KB/s, 174 seconds passed
-... 84%, 588224 KB, 3379 KB/s, 174 seconds passed
-... 84%, 588256 KB, 3379 KB/s, 174 seconds passed
-... 84%, 588288 KB, 3379 KB/s, 174 seconds passed
-... 84%, 588320 KB, 3379 KB/s, 174 seconds passed
+    ... 83%, 583456 KB, 3675 KB/s, 158 seconds passed
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+... 83%, 583520 KB, 3675 KB/s, 158 seconds passed
+... 83%, 583552 KB, 3675 KB/s, 158 seconds passed
 
 .. parsed-literal::
 
-    ... 84%, 588352 KB, 3379 KB/s, 174 seconds passed
-... 84%, 588384 KB, 3379 KB/s, 174 seconds passed
-... 84%, 588416 KB, 3379 KB/s, 174 seconds passed
-... 84%, 588448 KB, 3379 KB/s, 174 seconds passed
-... 84%, 588480 KB, 3379 KB/s, 174 seconds passed
+    ... 83%, 583584 KB, 3675 KB/s, 158 seconds passed
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+... 83%, 583744 KB, 3675 KB/s, 158 seconds passed
+... 83%, 583776 KB, 3675 KB/s, 158 seconds passed
+... 83%, 583808 KB, 3675 KB/s, 158 seconds passed
 
 .. parsed-literal::
 
-    ... 84%, 588512 KB, 3379 KB/s, 174 seconds passed
-... 84%, 588544 KB, 3379 KB/s, 174 seconds passed
-... 84%, 588576 KB, 3379 KB/s, 174 seconds passed
-... 84%, 588608 KB, 3379 KB/s, 174 seconds passed
-... 84%, 588640 KB, 3379 KB/s, 174 seconds passed
-... 84%, 588672 KB, 3379 KB/s, 174 seconds passed
-... 84%, 588704 KB, 3379 KB/s, 174 seconds passed
+    ... 83%, 583840 KB, 3675 KB/s, 158 seconds passed
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+... 83%, 583904 KB, 3675 KB/s, 158 seconds passed
+... 83%, 583936 KB, 3675 KB/s, 158 seconds passed
 
 .. parsed-literal::
 
-    ... 84%, 588736 KB, 3379 KB/s, 174 seconds passed
-... 84%, 588768 KB, 3379 KB/s, 174 seconds passed
-... 84%, 588800 KB, 3379 KB/s, 174 seconds passed
-... 84%, 588832 KB, 3379 KB/s, 174 seconds passed
-... 84%, 588864 KB, 3379 KB/s, 174 seconds passed
+    ... 83%, 583968 KB, 3675 KB/s, 158 seconds passed
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+... 83%, 584096 KB, 3675 KB/s, 158 seconds passed
+... 83%, 584128 KB, 3675 KB/s, 158 seconds passed
+... 83%, 584160 KB, 3675 KB/s, 158 seconds passed
+... 83%, 584192 KB, 3675 KB/s, 158 seconds passed
 
 .. parsed-literal::
 
-    ... 84%, 588896 KB, 3379 KB/s, 174 seconds passed
-... 84%, 588928 KB, 3379 KB/s, 174 seconds passed
-... 84%, 588960 KB, 3380 KB/s, 174 seconds passed
-... 84%, 588992 KB, 3379 KB/s, 174 seconds passed
-... 84%, 589024 KB, 3379 KB/s, 174 seconds passed
-... 84%, 589056 KB, 3379 KB/s, 174 seconds passed
-... 84%, 589088 KB, 3380 KB/s, 174 seconds passed
+    ... 83%, 584224 KB, 3675 KB/s, 158 seconds passed
+... 84%, 584256 KB, 3675 KB/s, 158 seconds passed
+... 84%, 584288 KB, 3675 KB/s, 158 seconds passed
+... 84%, 584320 KB, 3675 KB/s, 158 seconds passed
 
 .. parsed-literal::
 
-    ... 84%, 589120 KB, 3379 KB/s, 174 seconds passed
-... 84%, 589152 KB, 3379 KB/s, 174 seconds passed
-... 84%, 589184 KB, 3379 KB/s, 174 seconds passed
-... 84%, 589216 KB, 3380 KB/s, 174 seconds passed
-... 84%, 589248 KB, 3379 KB/s, 174 seconds passed
+    ... 84%, 584352 KB, 3675 KB/s, 158 seconds passed
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+... 84%, 584512 KB, 3675 KB/s, 159 seconds passed
+... 84%, 584544 KB, 3675 KB/s, 159 seconds passed
+... 84%, 584576 KB, 3675 KB/s, 159 seconds passed
 
 .. parsed-literal::
 
-    ... 84%, 589280 KB, 3379 KB/s, 174 seconds passed
-... 84%, 589312 KB, 3380 KB/s, 174 seconds passed
-... 84%, 589344 KB, 3380 KB/s, 174 seconds passed
-... 84%, 589376 KB, 3379 KB/s, 174 seconds passed
-... 84%, 589408 KB, 3379 KB/s, 174 seconds passed
-... 84%, 589440 KB, 3380 KB/s, 174 seconds passed
-... 84%, 589472 KB, 3380 KB/s, 174 seconds passed
+    ... 84%, 584608 KB, 3675 KB/s, 159 seconds passed
+... 84%, 584640 KB, 3675 KB/s, 159 seconds passed
+... 84%, 584672 KB, 3675 KB/s, 159 seconds passed
+... 84%, 584704 KB, 3675 KB/s, 159 seconds passed
 
 .. parsed-literal::
 
-    ... 84%, 589504 KB, 3380 KB/s, 174 seconds passed
-... 84%, 589536 KB, 3380 KB/s, 174 seconds passed
-... 84%, 589568 KB, 3380 KB/s, 174 seconds passed
-... 84%, 589600 KB, 3380 KB/s, 174 seconds passed
-... 84%, 589632 KB, 3380 KB/s, 174 seconds passed
+    ... 84%, 584736 KB, 3675 KB/s, 159 seconds passed
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+... 84%, 584896 KB, 3675 KB/s, 159 seconds passed
+... 84%, 584928 KB, 3675 KB/s, 159 seconds passed
+... 84%, 584960 KB, 3675 KB/s, 159 seconds passed
 
 .. parsed-literal::
 
-    ... 84%, 589664 KB, 3380 KB/s, 174 seconds passed
-... 84%, 589696 KB, 3380 KB/s, 174 seconds passed
-... 84%, 589728 KB, 3380 KB/s, 174 seconds passed
-... 84%, 589760 KB, 3380 KB/s, 174 seconds passed
-... 84%, 589792 KB, 3380 KB/s, 174 seconds passed
-... 84%, 589824 KB, 3380 KB/s, 174 seconds passed
+    ... 84%, 584992 KB, 3675 KB/s, 159 seconds passed
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+... 84%, 585056 KB, 3675 KB/s, 159 seconds passed
+... 84%, 585088 KB, 3675 KB/s, 159 seconds passed
 
 .. parsed-literal::
 
-    ... 84%, 589856 KB, 3380 KB/s, 174 seconds passed
-... 84%, 589888 KB, 3380 KB/s, 174 seconds passed
-... 84%, 589920 KB, 3380 KB/s, 174 seconds passed
-... 84%, 589952 KB, 3380 KB/s, 174 seconds passed
-... 84%, 589984 KB, 3380 KB/s, 174 seconds passed
+    ... 84%, 585120 KB, 3675 KB/s, 159 seconds passed
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+... 84%, 585248 KB, 3675 KB/s, 159 seconds passed
+... 84%, 585280 KB, 3675 KB/s, 159 seconds passed
+... 84%, 585312 KB, 3675 KB/s, 159 seconds passed
 
 .. parsed-literal::
 
-    ... 84%, 590016 KB, 3380 KB/s, 174 seconds passed
-... 84%, 590048 KB, 3380 KB/s, 174 seconds passed
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-... 84%, 590144 KB, 3380 KB/s, 174 seconds passed
-... 84%, 590176 KB, 3380 KB/s, 174 seconds passed
-... 84%, 590208 KB, 3380 KB/s, 174 seconds passed
+    ... 84%, 585344 KB, 3675 KB/s, 159 seconds passed
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+... 84%, 585408 KB, 3675 KB/s, 159 seconds passed
+... 84%, 585440 KB, 3675 KB/s, 159 seconds passed
+... 84%, 585472 KB, 3675 KB/s, 159 seconds passed
 
 .. parsed-literal::
 
-    ... 84%, 590240 KB, 3380 KB/s, 174 seconds passed
-... 84%, 590272 KB, 3380 KB/s, 174 seconds passed
-... 84%, 590304 KB, 3380 KB/s, 174 seconds passed
-... 84%, 590336 KB, 3380 KB/s, 174 seconds passed
-... 84%, 590368 KB, 3380 KB/s, 174 seconds passed
+    ... 84%, 585504 KB, 3675 KB/s, 159 seconds passed
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+... 84%, 585600 KB, 3675 KB/s, 159 seconds passed
+... 84%, 585632 KB, 3675 KB/s, 159 seconds passed
+... 84%, 585664 KB, 3675 KB/s, 159 seconds passed
 
 .. parsed-literal::
 
-    ... 84%, 590400 KB, 3380 KB/s, 174 seconds passed
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-... 84%, 590496 KB, 3380 KB/s, 174 seconds passed
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-... 84%, 590560 KB, 3380 KB/s, 174 seconds passed
+    ... 84%, 585696 KB, 3675 KB/s, 159 seconds passed
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+... 84%, 585856 KB, 3675 KB/s, 159 seconds passed
 
 .. parsed-literal::
 
-    ... 84%, 590592 KB, 3379 KB/s, 174 seconds passed
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 .. parsed-literal::
 
-    ... 84%, 590624 KB, 3379 KB/s, 174 seconds passed
-... 84%, 590656 KB, 3379 KB/s, 174 seconds passed
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+    ... 84%, 586080 KB, 3675 KB/s, 159 seconds passed
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+... 84%, 586176 KB, 3675 KB/s, 159 seconds passed
+... 84%, 586208 KB, 3675 KB/s, 159 seconds passed
+... 84%, 586240 KB, 3675 KB/s, 159 seconds passed
 
 .. parsed-literal::
 
-    ... 84%, 590784 KB, 3379 KB/s, 174 seconds passed
-... 84%, 590816 KB, 3379 KB/s, 174 seconds passed
-... 84%, 590848 KB, 3379 KB/s, 174 seconds passed
+    ... 84%, 586272 KB, 3675 KB/s, 159 seconds passed
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+... 84%, 586400 KB, 3675 KB/s, 159 seconds passed
+... 84%, 586432 KB, 3675 KB/s, 159 seconds passed
 
 .. parsed-literal::
 
-    ... 84%, 590880 KB, 3378 KB/s, 174 seconds passed
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-... 84%, 590976 KB, 3378 KB/s, 174 seconds passed
+    ... 84%, 586464 KB, 3675 KB/s, 159 seconds passed
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+... 84%, 586560 KB, 3675 KB/s, 159 seconds passed
+... 84%, 586592 KB, 3675 KB/s, 159 seconds passed
+... 84%, 586624 KB, 3675 KB/s, 159 seconds passed
 
 .. parsed-literal::
 
-    ... 84%, 591008 KB, 3378 KB/s, 174 seconds passed
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-... 84%, 591104 KB, 3378 KB/s, 174 seconds passed
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-... 84%, 591168 KB, 3379 KB/s, 174 seconds passed
+    ... 84%, 586656 KB, 3675 KB/s, 159 seconds passed
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+... 84%, 586784 KB, 3675 KB/s, 159 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 591200 KB, 3378 KB/s, 174 seconds passed
-... 85%, 591232 KB, 3378 KB/s, 174 seconds passed
-... 85%, 591264 KB, 3379 KB/s, 174 seconds passed
-... 85%, 591296 KB, 3379 KB/s, 174 seconds passed
-... 85%, 591328 KB, 3378 KB/s, 175 seconds passed
+    ... 84%, 586816 KB, 3675 KB/s, 159 seconds passed
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+... 84%, 586976 KB, 3675 KB/s, 159 seconds passed
+... 84%, 587008 KB, 3675 KB/s, 159 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 591360 KB, 3378 KB/s, 175 seconds passed
-... 85%, 591392 KB, 3379 KB/s, 175 seconds passed
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-... 85%, 591488 KB, 3379 KB/s, 175 seconds passed
-... 85%, 591520 KB, 3379 KB/s, 175 seconds passed
-... 85%, 591552 KB, 3379 KB/s, 175 seconds passed
+    ... 84%, 587040 KB, 3675 KB/s, 159 seconds passed
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+... 84%, 587104 KB, 3675 KB/s, 159 seconds passed
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+... 84%, 587168 KB, 3675 KB/s, 159 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 591584 KB, 3379 KB/s, 175 seconds passed
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-... 85%, 591648 KB, 3379 KB/s, 175 seconds passed
-... 85%, 591680 KB, 3379 KB/s, 175 seconds passed
-... 85%, 591712 KB, 3379 KB/s, 175 seconds passed
+    ... 84%, 587200 KB, 3675 KB/s, 159 seconds passed
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+... 84%, 587392 KB, 3675 KB/s, 159 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 591744 KB, 3379 KB/s, 175 seconds passed
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-... 85%, 591872 KB, 3379 KB/s, 175 seconds passed
-... 85%, 591904 KB, 3379 KB/s, 175 seconds passed
-... 85%, 591936 KB, 3379 KB/s, 175 seconds passed
+    ... 84%, 587424 KB, 3675 KB/s, 159 seconds passed
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+... 84%, 587488 KB, 3675 KB/s, 159 seconds passed
+... 84%, 587520 KB, 3675 KB/s, 159 seconds passed
+... 84%, 587552 KB, 3675 KB/s, 159 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 591968 KB, 3379 KB/s, 175 seconds passed
-... 85%, 592000 KB, 3379 KB/s, 175 seconds passed
-... 85%, 592032 KB, 3379 KB/s, 175 seconds passed
-... 85%, 592064 KB, 3379 KB/s, 175 seconds passed
-... 85%, 592096 KB, 3379 KB/s, 175 seconds passed
+    ... 84%, 587584 KB, 3675 KB/s, 159 seconds passed
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+... 84%, 587744 KB, 3675 KB/s, 159 seconds passed
+... 84%, 587776 KB, 3675 KB/s, 159 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 592128 KB, 3379 KB/s, 175 seconds passed
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-... 85%, 592256 KB, 3379 KB/s, 175 seconds passed
-... 85%, 592288 KB, 3379 KB/s, 175 seconds passed
-... 85%, 592320 KB, 3379 KB/s, 175 seconds passed
+    ... 84%, 587808 KB, 3675 KB/s, 159 seconds passed
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+... 84%, 587872 KB, 3675 KB/s, 159 seconds passed
+... 84%, 587904 KB, 3675 KB/s, 159 seconds passed
+... 84%, 587936 KB, 3675 KB/s, 159 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 592352 KB, 3379 KB/s, 175 seconds passed
-... 85%, 592384 KB, 3379 KB/s, 175 seconds passed
-... 85%, 592416 KB, 3379 KB/s, 175 seconds passed
-... 85%, 592448 KB, 3379 KB/s, 175 seconds passed
+    ... 84%, 587968 KB, 3675 KB/s, 159 seconds passed
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+... 84%, 588096 KB, 3675 KB/s, 159 seconds passed
+... 84%, 588128 KB, 3675 KB/s, 160 seconds passed
+... 84%, 588160 KB, 3675 KB/s, 160 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 592480 KB, 3379 KB/s, 175 seconds passed
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-... 85%, 592576 KB, 3379 KB/s, 175 seconds passed
-... 85%, 592608 KB, 3379 KB/s, 175 seconds passed
-... 85%, 592640 KB, 3379 KB/s, 175 seconds passed
-... 85%, 592672 KB, 3379 KB/s, 175 seconds passed
-... 85%, 592704 KB, 3379 KB/s, 175 seconds passed
+    ... 84%, 588192 KB, 3675 KB/s, 160 seconds passed
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+... 84%, 588256 KB, 3675 KB/s, 160 seconds passed
+... 84%, 588288 KB, 3675 KB/s, 160 seconds passed
+... 84%, 588320 KB, 3675 KB/s, 160 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 592736 KB, 3379 KB/s, 175 seconds passed
-... 85%, 592768 KB, 3379 KB/s, 175 seconds passed
-... 85%, 592800 KB, 3379 KB/s, 175 seconds passed
-... 85%, 592832 KB, 3379 KB/s, 175 seconds passed
+    ... 84%, 588352 KB, 3675 KB/s, 160 seconds passed
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+... 84%, 588448 KB, 3675 KB/s, 160 seconds passed
+... 84%, 588480 KB, 3675 KB/s, 160 seconds passed
+... 84%, 588512 KB, 3675 KB/s, 160 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 592864 KB, 3379 KB/s, 175 seconds passed
-... 85%, 592896 KB, 3379 KB/s, 175 seconds passed
-... 85%, 592928 KB, 3379 KB/s, 175 seconds passed
-... 85%, 592960 KB, 3379 KB/s, 175 seconds passed
-... 85%, 592992 KB, 3379 KB/s, 175 seconds passed
-... 85%, 593024 KB, 3379 KB/s, 175 seconds passed
+    ... 84%, 588544 KB, 3675 KB/s, 160 seconds passed
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+... 84%, 588608 KB, 3675 KB/s, 160 seconds passed
+... 84%, 588640 KB, 3675 KB/s, 160 seconds passed
+... 84%, 588672 KB, 3675 KB/s, 160 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 593056 KB, 3379 KB/s, 175 seconds passed
+    ... 84%, 588704 KB, 3675 KB/s, 160 seconds passed
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+... 84%, 588768 KB, 3675 KB/s, 160 seconds passed
+... 84%, 588800 KB, 3675 KB/s, 160 seconds passed
+... 84%, 588832 KB, 3675 KB/s, 160 seconds passed
+... 84%, 588864 KB, 3675 KB/s, 160 seconds passed
+... 84%, 588896 KB, 3675 KB/s, 160 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 593088 KB, 3378 KB/s, 175 seconds passed
+    ... 84%, 588928 KB, 3675 KB/s, 160 seconds passed
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+... 84%, 588992 KB, 3675 KB/s, 160 seconds passed
+... 84%, 589024 KB, 3675 KB/s, 160 seconds passed
+... 84%, 589056 KB, 3675 KB/s, 160 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 593120 KB, 3377 KB/s, 175 seconds passed
+    ... 84%, 589088 KB, 3675 KB/s, 160 seconds passed
+... 84%, 589120 KB, 3675 KB/s, 160 seconds passed
+... 84%, 589152 KB, 3675 KB/s, 160 seconds passed
+... 84%, 589184 KB, 3675 KB/s, 160 seconds passed
+... 84%, 589216 KB, 3675 KB/s, 160 seconds passed
+... 84%, 589248 KB, 3675 KB/s, 160 seconds passed
+... 84%, 589280 KB, 3675 KB/s, 160 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 593152 KB, 3377 KB/s, 175 seconds passed
-... 85%, 593184 KB, 3377 KB/s, 175 seconds passed
-... 85%, 593216 KB, 3376 KB/s, 175 seconds passed
+    ... 84%, 589312 KB, 3675 KB/s, 160 seconds passed
+... 84%, 589344 KB, 3675 KB/s, 160 seconds passed
+... 84%, 589376 KB, 3675 KB/s, 160 seconds passed
+... 84%, 589408 KB, 3675 KB/s, 160 seconds passed
+... 84%, 589440 KB, 3675 KB/s, 160 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 593248 KB, 3376 KB/s, 175 seconds passed
+    ... 84%, 589472 KB, 3675 KB/s, 160 seconds passed
+... 84%, 589504 KB, 3675 KB/s, 160 seconds passed
+... 84%, 589536 KB, 3675 KB/s, 160 seconds passed
+... 84%, 589568 KB, 3675 KB/s, 160 seconds passed
+... 84%, 589600 KB, 3675 KB/s, 160 seconds passed
+... 84%, 589632 KB, 3675 KB/s, 160 seconds passed
+... 84%, 589664 KB, 3675 KB/s, 160 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 593280 KB, 3375 KB/s, 175 seconds passed
-... 85%, 593312 KB, 3376 KB/s, 175 seconds passed
-... 85%, 593344 KB, 3375 KB/s, 175 seconds passed
-... 85%, 593376 KB, 3375 KB/s, 175 seconds passed
+    ... 84%, 589696 KB, 3675 KB/s, 160 seconds passed
+... 84%, 589728 KB, 3675 KB/s, 160 seconds passed
+... 84%, 589760 KB, 3675 KB/s, 160 seconds passed
+... 84%, 589792 KB, 3675 KB/s, 160 seconds passed
+... 84%, 589824 KB, 3675 KB/s, 160 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 593408 KB, 3375 KB/s, 175 seconds passed
-... 85%, 593440 KB, 3375 KB/s, 175 seconds passed
+    ... 84%, 589856 KB, 3675 KB/s, 160 seconds passed
+... 84%, 589888 KB, 3675 KB/s, 160 seconds passed
+... 84%, 589920 KB, 3675 KB/s, 160 seconds passed
+... 84%, 589952 KB, 3675 KB/s, 160 seconds passed
+... 84%, 589984 KB, 3675 KB/s, 160 seconds passed
+... 84%, 590016 KB, 3675 KB/s, 160 seconds passed
+... 84%, 590048 KB, 3675 KB/s, 160 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 593472 KB, 3375 KB/s, 175 seconds passed
-... 85%, 593504 KB, 3375 KB/s, 175 seconds passed
-... 85%, 593536 KB, 3375 KB/s, 175 seconds passed
-... 85%, 593568 KB, 3374 KB/s, 175 seconds passed
-... 85%, 593600 KB, 3375 KB/s, 175 seconds passed
+    ... 84%, 590080 KB, 3675 KB/s, 160 seconds passed
+... 84%, 590112 KB, 3675 KB/s, 160 seconds passed
+... 84%, 590144 KB, 3675 KB/s, 160 seconds passed
+... 84%, 590176 KB, 3675 KB/s, 160 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 593632 KB, 3374 KB/s, 175 seconds passed
-... 85%, 593664 KB, 3374 KB/s, 175 seconds passed
-... 85%, 593696 KB, 3374 KB/s, 175 seconds passed
+    ... 84%, 590208 KB, 3675 KB/s, 160 seconds passed
+... 84%, 590240 KB, 3675 KB/s, 160 seconds passed
+... 84%, 590272 KB, 3675 KB/s, 160 seconds passed
+... 84%, 590304 KB, 3675 KB/s, 160 seconds passed
+... 84%, 590336 KB, 3675 KB/s, 160 seconds passed
+... 84%, 590368 KB, 3675 KB/s, 160 seconds passed
+... 84%, 590400 KB, 3675 KB/s, 160 seconds passed
+... 84%, 590432 KB, 3675 KB/s, 160 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 593728 KB, 3374 KB/s, 175 seconds passed
-... 85%, 593760 KB, 3374 KB/s, 175 seconds passed
-... 85%, 593792 KB, 3374 KB/s, 175 seconds passed
-... 85%, 593824 KB, 3374 KB/s, 175 seconds passed
+    ... 84%, 590464 KB, 3675 KB/s, 160 seconds passed
+... 84%, 590496 KB, 3675 KB/s, 160 seconds passed
+... 84%, 590528 KB, 3675 KB/s, 160 seconds passed
+... 84%, 590560 KB, 3675 KB/s, 160 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 593856 KB, 3374 KB/s, 175 seconds passed
-... 85%, 593888 KB, 3374 KB/s, 176 seconds passed
-... 85%, 593920 KB, 3374 KB/s, 176 seconds passed
-... 85%, 593952 KB, 3374 KB/s, 176 seconds passed
-... 85%, 593984 KB, 3374 KB/s, 176 seconds passed
+    ... 84%, 590592 KB, 3675 KB/s, 160 seconds passed
+... 84%, 590624 KB, 3675 KB/s, 160 seconds passed
+... 84%, 590656 KB, 3675 KB/s, 160 seconds passed
+... 84%, 590688 KB, 3675 KB/s, 160 seconds passed
+... 84%, 590720 KB, 3675 KB/s, 160 seconds passed
+... 84%, 590752 KB, 3675 KB/s, 160 seconds passed
+... 84%, 590784 KB, 3675 KB/s, 160 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 594016 KB, 3374 KB/s, 176 seconds passed
-... 85%, 594048 KB, 3374 KB/s, 176 seconds passed
-... 85%, 594080 KB, 3374 KB/s, 176 seconds passed
-... 85%, 594112 KB, 3374 KB/s, 176 seconds passed
-... 85%, 594144 KB, 3374 KB/s, 176 seconds passed
+    ... 84%, 590816 KB, 3675 KB/s, 160 seconds passed
+... 84%, 590848 KB, 3675 KB/s, 160 seconds passed
+... 84%, 590880 KB, 3675 KB/s, 160 seconds passed
+... 84%, 590912 KB, 3675 KB/s, 160 seconds passed
+... 84%, 590944 KB, 3675 KB/s, 160 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 594176 KB, 3374 KB/s, 176 seconds passed
-... 85%, 594208 KB, 3374 KB/s, 176 seconds passed
-... 85%, 594240 KB, 3374 KB/s, 176 seconds passed
-... 85%, 594272 KB, 3374 KB/s, 176 seconds passed
-... 85%, 594304 KB, 3374 KB/s, 176 seconds passed
-... 85%, 594336 KB, 3374 KB/s, 176 seconds passed
+    ... 84%, 590976 KB, 3675 KB/s, 160 seconds passed
+... 84%, 591008 KB, 3675 KB/s, 160 seconds passed
+... 84%, 591040 KB, 3675 KB/s, 160 seconds passed
+... 84%, 591072 KB, 3675 KB/s, 160 seconds passed
+... 84%, 591104 KB, 3675 KB/s, 160 seconds passed
+... 84%, 591136 KB, 3675 KB/s, 160 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 594368 KB, 3374 KB/s, 176 seconds passed
-... 85%, 594400 KB, 3374 KB/s, 176 seconds passed
-... 85%, 594432 KB, 3374 KB/s, 176 seconds passed
-... 85%, 594464 KB, 3374 KB/s, 176 seconds passed
-... 85%, 594496 KB, 3374 KB/s, 176 seconds passed
+    ... 84%, 591168 KB, 3675 KB/s, 160 seconds passed
+... 85%, 591200 KB, 3675 KB/s, 160 seconds passed
+... 85%, 591232 KB, 3675 KB/s, 160 seconds passed
+... 85%, 591264 KB, 3675 KB/s, 160 seconds passed
+... 85%, 591296 KB, 3675 KB/s, 160 seconds passed
+... 85%, 591328 KB, 3675 KB/s, 160 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 594528 KB, 3374 KB/s, 176 seconds passed
-... 85%, 594560 KB, 3374 KB/s, 176 seconds passed
-... 85%, 594592 KB, 3374 KB/s, 176 seconds passed
-... 85%, 594624 KB, 3374 KB/s, 176 seconds passed
-... 85%, 594656 KB, 3374 KB/s, 176 seconds passed
-... 85%, 594688 KB, 3374 KB/s, 176 seconds passed
+    ... 85%, 591360 KB, 3675 KB/s, 160 seconds passed
+... 85%, 591392 KB, 3675 KB/s, 160 seconds passed
+... 85%, 591424 KB, 3675 KB/s, 160 seconds passed
+... 85%, 591456 KB, 3675 KB/s, 160 seconds passed
+... 85%, 591488 KB, 3675 KB/s, 160 seconds passed
+... 85%, 591520 KB, 3675 KB/s, 160 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 594720 KB, 3374 KB/s, 176 seconds passed
-... 85%, 594752 KB, 3374 KB/s, 176 seconds passed
-... 85%, 594784 KB, 3374 KB/s, 176 seconds passed
-... 85%, 594816 KB, 3374 KB/s, 176 seconds passed
-... 85%, 594848 KB, 3374 KB/s, 176 seconds passed
+    ... 85%, 591552 KB, 3675 KB/s, 160 seconds passed
+... 85%, 591584 KB, 3675 KB/s, 160 seconds passed
+... 85%, 591616 KB, 3675 KB/s, 160 seconds passed
+... 85%, 591648 KB, 3675 KB/s, 160 seconds passed
+... 85%, 591680 KB, 3675 KB/s, 160 seconds passed
+... 85%, 591712 KB, 3675 KB/s, 160 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 594880 KB, 3374 KB/s, 176 seconds passed
-... 85%, 594912 KB, 3374 KB/s, 176 seconds passed
-... 85%, 594944 KB, 3374 KB/s, 176 seconds passed
-... 85%, 594976 KB, 3374 KB/s, 176 seconds passed
-... 85%, 595008 KB, 3374 KB/s, 176 seconds passed
-... 85%, 595040 KB, 3374 KB/s, 176 seconds passed
-... 85%, 595072 KB, 3374 KB/s, 176 seconds passed
+    ... 85%, 591744 KB, 3675 KB/s, 160 seconds passed
+... 85%, 591776 KB, 3675 KB/s, 160 seconds passed
+... 85%, 591808 KB, 3675 KB/s, 161 seconds passed
+... 85%, 591840 KB, 3675 KB/s, 161 seconds passed
+... 85%, 591872 KB, 3675 KB/s, 161 seconds passed
+... 85%, 591904 KB, 3675 KB/s, 161 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 595104 KB, 3374 KB/s, 176 seconds passed
-... 85%, 595136 KB, 3374 KB/s, 176 seconds passed
-... 85%, 595168 KB, 3374 KB/s, 176 seconds passed
-... 85%, 595200 KB, 3374 KB/s, 176 seconds passed
-... 85%, 595232 KB, 3374 KB/s, 176 seconds passed
+    ... 85%, 591936 KB, 3675 KB/s, 161 seconds passed
+... 85%, 591968 KB, 3675 KB/s, 161 seconds passed
+... 85%, 592000 KB, 3675 KB/s, 161 seconds passed
+... 85%, 592032 KB, 3675 KB/s, 161 seconds passed
+... 85%, 592064 KB, 3675 KB/s, 161 seconds passed
+... 85%, 592096 KB, 3675 KB/s, 161 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 595264 KB, 3374 KB/s, 176 seconds passed
-... 85%, 595296 KB, 3374 KB/s, 176 seconds passed
-... 85%, 595328 KB, 3374 KB/s, 176 seconds passed
-... 85%, 595360 KB, 3374 KB/s, 176 seconds passed
-... 85%, 595392 KB, 3374 KB/s, 176 seconds passed
-... 85%, 595424 KB, 3374 KB/s, 176 seconds passed
-... 85%, 595456 KB, 3374 KB/s, 176 seconds passed
+    ... 85%, 592128 KB, 3675 KB/s, 161 seconds passed
+... 85%, 592160 KB, 3675 KB/s, 161 seconds passed
+... 85%, 592192 KB, 3675 KB/s, 161 seconds passed
+... 85%, 592224 KB, 3675 KB/s, 161 seconds passed
+... 85%, 592256 KB, 3675 KB/s, 161 seconds passed
+... 85%, 592288 KB, 3675 KB/s, 161 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 595488 KB, 3374 KB/s, 176 seconds passed
-... 85%, 595520 KB, 3374 KB/s, 176 seconds passed
-... 85%, 595552 KB, 3374 KB/s, 176 seconds passed
-... 85%, 595584 KB, 3374 KB/s, 176 seconds passed
-... 85%, 595616 KB, 3374 KB/s, 176 seconds passed
+    ... 85%, 592320 KB, 3675 KB/s, 161 seconds passed
+... 85%, 592352 KB, 3675 KB/s, 161 seconds passed
+... 85%, 592384 KB, 3675 KB/s, 161 seconds passed
+... 85%, 592416 KB, 3675 KB/s, 161 seconds passed
+... 85%, 592448 KB, 3675 KB/s, 161 seconds passed
+... 85%, 592480 KB, 3675 KB/s, 161 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 595648 KB, 3374 KB/s, 176 seconds passed
-... 85%, 595680 KB, 3374 KB/s, 176 seconds passed
-... 85%, 595712 KB, 3375 KB/s, 176 seconds passed
-... 85%, 595744 KB, 3374 KB/s, 176 seconds passed
-... 85%, 595776 KB, 3374 KB/s, 176 seconds passed
-... 85%, 595808 KB, 3374 KB/s, 176 seconds passed
-... 85%, 595840 KB, 3375 KB/s, 176 seconds passed
+    ... 85%, 592512 KB, 3675 KB/s, 161 seconds passed
+... 85%, 592544 KB, 3675 KB/s, 161 seconds passed
+... 85%, 592576 KB, 3675 KB/s, 161 seconds passed
+... 85%, 592608 KB, 3675 KB/s, 161 seconds passed
+... 85%, 592640 KB, 3675 KB/s, 161 seconds passed
+... 85%, 592672 KB, 3675 KB/s, 161 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 595872 KB, 3374 KB/s, 176 seconds passed
-... 85%, 595904 KB, 3374 KB/s, 176 seconds passed
-... 85%, 595936 KB, 3375 KB/s, 176 seconds passed
-... 85%, 595968 KB, 3375 KB/s, 176 seconds passed
+    ... 85%, 592704 KB, 3675 KB/s, 161 seconds passed
+... 85%, 592736 KB, 3675 KB/s, 161 seconds passed
+... 85%, 592768 KB, 3675 KB/s, 161 seconds passed
+... 85%, 592800 KB, 3675 KB/s, 161 seconds passed
+... 85%, 592832 KB, 3675 KB/s, 161 seconds passed
+... 85%, 592864 KB, 3675 KB/s, 161 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 596000 KB, 3374 KB/s, 176 seconds passed
-... 85%, 596032 KB, 3374 KB/s, 176 seconds passed
-... 85%, 596064 KB, 3375 KB/s, 176 seconds passed
-... 85%, 596096 KB, 3375 KB/s, 176 seconds passed
-... 85%, 596128 KB, 3374 KB/s, 176 seconds passed
-... 85%, 596160 KB, 3375 KB/s, 176 seconds passed
-... 85%, 596192 KB, 3375 KB/s, 176 seconds passed
-... 85%, 596224 KB, 3375 KB/s, 176 seconds passed
+    ... 85%, 592896 KB, 3675 KB/s, 161 seconds passed
+... 85%, 592928 KB, 3675 KB/s, 161 seconds passed
+... 85%, 592960 KB, 3675 KB/s, 161 seconds passed
+... 85%, 592992 KB, 3675 KB/s, 161 seconds passed
+... 85%, 593024 KB, 3675 KB/s, 161 seconds passed
+... 85%, 593056 KB, 3675 KB/s, 161 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 596256 KB, 3374 KB/s, 176 seconds passed
-... 85%, 596288 KB, 3375 KB/s, 176 seconds passed
-... 85%, 596320 KB, 3375 KB/s, 176 seconds passed
-... 85%, 596352 KB, 3375 KB/s, 176 seconds passed
+    ... 85%, 593088 KB, 3675 KB/s, 161 seconds passed
+... 85%, 593120 KB, 3675 KB/s, 161 seconds passed
+... 85%, 593152 KB, 3675 KB/s, 161 seconds passed
+... 85%, 593184 KB, 3675 KB/s, 161 seconds passed
+... 85%, 593216 KB, 3675 KB/s, 161 seconds passed
+... 85%, 593248 KB, 3675 KB/s, 161 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 596384 KB, 3375 KB/s, 176 seconds passed
-... 85%, 596416 KB, 3375 KB/s, 176 seconds passed
-... 85%, 596448 KB, 3375 KB/s, 176 seconds passed
-... 85%, 596480 KB, 3375 KB/s, 176 seconds passed
-... 85%, 596512 KB, 3375 KB/s, 176 seconds passed
-... 85%, 596544 KB, 3375 KB/s, 176 seconds passed
-... 85%, 596576 KB, 3375 KB/s, 176 seconds passed
-... 85%, 596608 KB, 3375 KB/s, 176 seconds passed
+    ... 85%, 593280 KB, 3675 KB/s, 161 seconds passed
+... 85%, 593312 KB, 3675 KB/s, 161 seconds passed
+... 85%, 593344 KB, 3675 KB/s, 161 seconds passed
+... 85%, 593376 KB, 3675 KB/s, 161 seconds passed
+... 85%, 593408 KB, 3675 KB/s, 161 seconds passed
+... 85%, 593440 KB, 3675 KB/s, 161 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 596640 KB, 3375 KB/s, 176 seconds passed
-... 85%, 596672 KB, 3375 KB/s, 176 seconds passed
-... 85%, 596704 KB, 3375 KB/s, 176 seconds passed
-... 85%, 596736 KB, 3375 KB/s, 176 seconds passed
+    ... 85%, 593472 KB, 3675 KB/s, 161 seconds passed
+... 85%, 593504 KB, 3675 KB/s, 161 seconds passed
+... 85%, 593536 KB, 3675 KB/s, 161 seconds passed
+... 85%, 593568 KB, 3675 KB/s, 161 seconds passed
+... 85%, 593600 KB, 3675 KB/s, 161 seconds passed
+... 85%, 593632 KB, 3675 KB/s, 161 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 596768 KB, 3375 KB/s, 176 seconds passed
-... 85%, 596800 KB, 3375 KB/s, 176 seconds passed
-... 85%, 596832 KB, 3375 KB/s, 176 seconds passed
-... 85%, 596864 KB, 3375 KB/s, 176 seconds passed
-... 85%, 596896 KB, 3375 KB/s, 176 seconds passed
-... 85%, 596928 KB, 3375 KB/s, 176 seconds passed
-... 85%, 596960 KB, 3375 KB/s, 176 seconds passed
-... 85%, 596992 KB, 3375 KB/s, 176 seconds passed
+    ... 85%, 593664 KB, 3675 KB/s, 161 seconds passed
+... 85%, 593696 KB, 3675 KB/s, 161 seconds passed
+... 85%, 593728 KB, 3675 KB/s, 161 seconds passed
+... 85%, 593760 KB, 3675 KB/s, 161 seconds passed
+... 85%, 593792 KB, 3675 KB/s, 161 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 597024 KB, 3375 KB/s, 176 seconds passed
-... 85%, 597056 KB, 3375 KB/s, 176 seconds passed
-... 85%, 597088 KB, 3375 KB/s, 176 seconds passed
-... 85%, 597120 KB, 3375 KB/s, 176 seconds passed
+    ... 85%, 593824 KB, 3675 KB/s, 161 seconds passed
+... 85%, 593856 KB, 3675 KB/s, 161 seconds passed
+... 85%, 593888 KB, 3675 KB/s, 161 seconds passed
+... 85%, 593920 KB, 3675 KB/s, 161 seconds passed
+... 85%, 593952 KB, 3675 KB/s, 161 seconds passed
+... 85%, 593984 KB, 3675 KB/s, 161 seconds passed
+... 85%, 594016 KB, 3676 KB/s, 161 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 597152 KB, 3375 KB/s, 176 seconds passed
-... 85%, 597184 KB, 3375 KB/s, 176 seconds passed
-... 85%, 597216 KB, 3375 KB/s, 176 seconds passed
-... 85%, 597248 KB, 3375 KB/s, 176 seconds passed
-... 85%, 597280 KB, 3375 KB/s, 176 seconds passed
-... 85%, 597312 KB, 3375 KB/s, 176 seconds passed
-... 85%, 597344 KB, 3375 KB/s, 176 seconds passed
-... 85%, 597376 KB, 3375 KB/s, 176 seconds passed
+    ... 85%, 594048 KB, 3675 KB/s, 161 seconds passed
+... 85%, 594080 KB, 3675 KB/s, 161 seconds passed
+... 85%, 594112 KB, 3675 KB/s, 161 seconds passed
+... 85%, 594144 KB, 3676 KB/s, 161 seconds passed
+... 85%, 594176 KB, 3675 KB/s, 161 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 597408 KB, 3375 KB/s, 176 seconds passed
-... 85%, 597440 KB, 3375 KB/s, 176 seconds passed
-... 85%, 597472 KB, 3375 KB/s, 176 seconds passed
-... 85%, 597504 KB, 3375 KB/s, 176 seconds passed
+    ... 85%, 594208 KB, 3675 KB/s, 161 seconds passed
+... 85%, 594240 KB, 3675 KB/s, 161 seconds passed
+... 85%, 594272 KB, 3676 KB/s, 161 seconds passed
+... 85%, 594304 KB, 3675 KB/s, 161 seconds passed
+... 85%, 594336 KB, 3675 KB/s, 161 seconds passed
+... 85%, 594368 KB, 3675 KB/s, 161 seconds passed
+... 85%, 594400 KB, 3676 KB/s, 161 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 597536 KB, 3375 KB/s, 177 seconds passed
-... 85%, 597568 KB, 3375 KB/s, 177 seconds passed
-... 85%, 597600 KB, 3375 KB/s, 177 seconds passed
-... 85%, 597632 KB, 3375 KB/s, 177 seconds passed
-... 85%, 597664 KB, 3375 KB/s, 177 seconds passed
-... 85%, 597696 KB, 3375 KB/s, 177 seconds passed
-... 85%, 597728 KB, 3375 KB/s, 177 seconds passed
-... 85%, 597760 KB, 3376 KB/s, 177 seconds passed
+    ... 85%, 594432 KB, 3675 KB/s, 161 seconds passed
+... 85%, 594464 KB, 3675 KB/s, 161 seconds passed
+... 85%, 594496 KB, 3675 KB/s, 161 seconds passed
+... 85%, 594528 KB, 3675 KB/s, 161 seconds passed
+... 85%, 594560 KB, 3675 KB/s, 161 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 597792 KB, 3375 KB/s, 177 seconds passed
-... 85%, 597824 KB, 3375 KB/s, 177 seconds passed
-... 85%, 597856 KB, 3375 KB/s, 177 seconds passed
-... 85%, 597888 KB, 3376 KB/s, 177 seconds passed
+    ... 85%, 594592 KB, 3675 KB/s, 161 seconds passed
+... 85%, 594624 KB, 3675 KB/s, 161 seconds passed
+... 85%, 594656 KB, 3675 KB/s, 161 seconds passed
+... 85%, 594688 KB, 3675 KB/s, 161 seconds passed
+... 85%, 594720 KB, 3675 KB/s, 161 seconds passed
+... 85%, 594752 KB, 3675 KB/s, 161 seconds passed
 
 .. parsed-literal::
 
-    ... 85%, 597920 KB, 3375 KB/s, 177 seconds passed
-... 85%, 597952 KB, 3375 KB/s, 177 seconds passed
-... 85%, 597984 KB, 3376 KB/s, 177 seconds passed
-... 85%, 598016 KB, 3376 KB/s, 177 seconds passed
-... 85%, 598048 KB, 3375 KB/s, 177 seconds passed
-... 85%, 598080 KB, 3375 KB/s, 177 seconds passed
-... 85%, 598112 KB, 3376 KB/s, 177 seconds passed
-... 86%, 598144 KB, 3376 KB/s, 177 seconds passed
+    ... 85%, 594784 KB, 3675 KB/s, 161 seconds passed
+... 85%, 594816 KB, 3675 KB/s, 161 seconds passed
+... 85%, 594848 KB, 3675 KB/s, 161 seconds passed
+... 85%, 594880 KB, 3675 KB/s, 161 seconds passed
+... 85%, 594912 KB, 3675 KB/s, 161 seconds passed
+... 85%, 594944 KB, 3675 KB/s, 161 seconds passed
 
 .. parsed-literal::
 
-    ... 86%, 598176 KB, 3375 KB/s, 177 seconds passed
-... 86%, 598208 KB, 3376 KB/s, 177 seconds passed
-... 86%, 598240 KB, 3376 KB/s, 177 seconds passed
+    ... 85%, 594976 KB, 3675 KB/s, 161 seconds passed
+... 85%, 595008 KB, 3675 KB/s, 161 seconds passed
+... 85%, 595040 KB, 3675 KB/s, 161 seconds passed
+... 85%, 595072 KB, 3675 KB/s, 161 seconds passed
+... 85%, 595104 KB, 3675 KB/s, 161 seconds passed
+... 85%, 595136 KB, 3675 KB/s, 161 seconds passed
 
 .. parsed-literal::
 
-    ... 86%, 598272 KB, 3375 KB/s, 177 seconds passed
-... 86%, 598304 KB, 3375 KB/s, 177 seconds passed
-... 86%, 598336 KB, 3376 KB/s, 177 seconds passed
-... 86%, 598368 KB, 3376 KB/s, 177 seconds passed
-... 86%, 598400 KB, 3375 KB/s, 177 seconds passed
-... 86%, 598432 KB, 3376 KB/s, 177 seconds passed
-... 86%, 598464 KB, 3376 KB/s, 177 seconds passed
-... 86%, 598496 KB, 3376 KB/s, 177 seconds passed
+    ... 85%, 595168 KB, 3675 KB/s, 161 seconds passed
+... 85%, 595200 KB, 3675 KB/s, 161 seconds passed
+... 85%, 595232 KB, 3675 KB/s, 161 seconds passed
+... 85%, 595264 KB, 3675 KB/s, 161 seconds passed
+... 85%, 595296 KB, 3675 KB/s, 161 seconds passed
+... 85%, 595328 KB, 3675 KB/s, 161 seconds passed
 
 .. parsed-literal::
 
-    ... 86%, 598528 KB, 3375 KB/s, 177 seconds passed
-... 86%, 598560 KB, 3376 KB/s, 177 seconds passed
-... 86%, 598592 KB, 3376 KB/s, 177 seconds passed
-... 86%, 598624 KB, 3376 KB/s, 177 seconds passed
+    ... 85%, 595360 KB, 3675 KB/s, 161 seconds passed
+... 85%, 595392 KB, 3675 KB/s, 161 seconds passed
+... 85%, 595424 KB, 3675 KB/s, 161 seconds passed
+... 85%, 595456 KB, 3675 KB/s, 161 seconds passed
+... 85%, 595488 KB, 3675 KB/s, 162 seconds passed
+... 85%, 595520 KB, 3675 KB/s, 162 seconds passed
 
 .. parsed-literal::
 
-    ... 86%, 598656 KB, 3376 KB/s, 177 seconds passed
-... 86%, 598688 KB, 3376 KB/s, 177 seconds passed
-... 86%, 598720 KB, 3376 KB/s, 177 seconds passed
-... 86%, 598752 KB, 3376 KB/s, 177 seconds passed
-... 86%, 598784 KB, 3376 KB/s, 177 seconds passed
-... 86%, 598816 KB, 3376 KB/s, 177 seconds passed
-... 86%, 598848 KB, 3376 KB/s, 177 seconds passed
+    ... 85%, 595552 KB, 3675 KB/s, 162 seconds passed
+... 85%, 595584 KB, 3675 KB/s, 162 seconds passed
+... 85%, 595616 KB, 3675 KB/s, 162 seconds passed
+... 85%, 595648 KB, 3675 KB/s, 162 seconds passed
+... 85%, 595680 KB, 3675 KB/s, 162 seconds passed
 
 .. parsed-literal::
 
-    ... 86%, 598880 KB, 3376 KB/s, 177 seconds passed
-... 86%, 598912 KB, 3376 KB/s, 177 seconds passed
-... 86%, 598944 KB, 3376 KB/s, 177 seconds passed
-... 86%, 598976 KB, 3376 KB/s, 177 seconds passed
-... 86%, 599008 KB, 3376 KB/s, 177 seconds passed
+    ... 85%, 595712 KB, 3675 KB/s, 162 seconds passed
+... 85%, 595744 KB, 3675 KB/s, 162 seconds passed
+... 85%, 595776 KB, 3675 KB/s, 162 seconds passed
+... 85%, 595808 KB, 3675 KB/s, 162 seconds passed
+... 85%, 595840 KB, 3675 KB/s, 162 seconds passed
+... 85%, 595872 KB, 3675 KB/s, 162 seconds passed
+... 85%, 595904 KB, 3675 KB/s, 162 seconds passed
 
 .. parsed-literal::
 
-    ... 86%, 599040 KB, 3376 KB/s, 177 seconds passed
-... 86%, 599072 KB, 3376 KB/s, 177 seconds passed
-... 86%, 599104 KB, 3376 KB/s, 177 seconds passed
-... 86%, 599136 KB, 3376 KB/s, 177 seconds passed
-... 86%, 599168 KB, 3376 KB/s, 177 seconds passed
-... 86%, 599200 KB, 3376 KB/s, 177 seconds passed
-... 86%, 599232 KB, 3376 KB/s, 177 seconds passed
+    ... 85%, 595936 KB, 3675 KB/s, 162 seconds passed
+... 85%, 595968 KB, 3675 KB/s, 162 seconds passed
+... 85%, 596000 KB, 3675 KB/s, 162 seconds passed
+... 85%, 596032 KB, 3675 KB/s, 162 seconds passed
+... 85%, 596064 KB, 3675 KB/s, 162 seconds passed
 
 .. parsed-literal::
 
-    ... 86%, 599264 KB, 3376 KB/s, 177 seconds passed
-... 86%, 599296 KB, 3376 KB/s, 177 seconds passed
-... 86%, 599328 KB, 3376 KB/s, 177 seconds passed
-... 86%, 599360 KB, 3376 KB/s, 177 seconds passed
-... 86%, 599392 KB, 3376 KB/s, 177 seconds passed
+    ... 85%, 596096 KB, 3675 KB/s, 162 seconds passed
+... 85%, 596128 KB, 3675 KB/s, 162 seconds passed
+... 85%, 596160 KB, 3675 KB/s, 162 seconds passed
+... 85%, 596192 KB, 3675 KB/s, 162 seconds passed
+... 85%, 596224 KB, 3675 KB/s, 162 seconds passed
+... 85%, 596256 KB, 3675 KB/s, 162 seconds passed
+... 85%, 596288 KB, 3675 KB/s, 162 seconds passed
 
 .. parsed-literal::
 
-    ... 86%, 599424 KB, 3376 KB/s, 177 seconds passed
-... 86%, 599456 KB, 3376 KB/s, 177 seconds passed
-... 86%, 599488 KB, 3376 KB/s, 177 seconds passed
-... 86%, 599520 KB, 3376 KB/s, 177 seconds passed
-... 86%, 599552 KB, 3376 KB/s, 177 seconds passed
-... 86%, 599584 KB, 3376 KB/s, 177 seconds passed
-... 86%, 599616 KB, 3376 KB/s, 177 seconds passed
+    ... 85%, 596320 KB, 3675 KB/s, 162 seconds passed
+... 85%, 596352 KB, 3675 KB/s, 162 seconds passed
+... 85%, 596384 KB, 3675 KB/s, 162 seconds passed
+... 85%, 596416 KB, 3675 KB/s, 162 seconds passed
+... 85%, 596448 KB, 3675 KB/s, 162 seconds passed
 
 .. parsed-literal::
 
-    ... 86%, 599648 KB, 3376 KB/s, 177 seconds passed
-... 86%, 599680 KB, 3376 KB/s, 177 seconds passed
-... 86%, 599712 KB, 3376 KB/s, 177 seconds passed
-... 86%, 599744 KB, 3376 KB/s, 177 seconds passed
-... 86%, 599776 KB, 3376 KB/s, 177 seconds passed
+    ... 85%, 596480 KB, 3675 KB/s, 162 seconds passed
+... 85%, 596512 KB, 3675 KB/s, 162 seconds passed
+... 85%, 596544 KB, 3675 KB/s, 162 seconds passed
+... 85%, 596576 KB, 3675 KB/s, 162 seconds passed
+... 85%, 596608 KB, 3675 KB/s, 162 seconds passed
+... 85%, 596640 KB, 3675 KB/s, 162 seconds passed
 
 .. parsed-literal::
 
-    ... 86%, 599808 KB, 3376 KB/s, 177 seconds passed
-... 86%, 599840 KB, 3376 KB/s, 177 seconds passed
-... 86%, 599872 KB, 3376 KB/s, 177 seconds passed
-... 86%, 599904 KB, 3376 KB/s, 177 seconds passed
-... 86%, 599936 KB, 3376 KB/s, 177 seconds passed
-... 86%, 599968 KB, 3376 KB/s, 177 seconds passed
+    ... 85%, 596672 KB, 3675 KB/s, 162 seconds passed
+... 85%, 596704 KB, 3675 KB/s, 162 seconds passed
+... 85%, 596736 KB, 3675 KB/s, 162 seconds passed
+... 85%, 596768 KB, 3675 KB/s, 162 seconds passed
+... 85%, 596800 KB, 3675 KB/s, 162 seconds passed
+... 85%, 596832 KB, 3675 KB/s, 162 seconds passed
 
 .. parsed-literal::
 
-    ... 86%, 600000 KB, 3376 KB/s, 177 seconds passed
-... 86%, 600032 KB, 3376 KB/s, 177 seconds passed
-... 86%, 600064 KB, 3376 KB/s, 177 seconds passed
-... 86%, 600096 KB, 3376 KB/s, 177 seconds passed
-... 86%, 600128 KB, 3376 KB/s, 177 seconds passed
-... 86%, 600160 KB, 3377 KB/s, 177 seconds passed
+    ... 85%, 596864 KB, 3675 KB/s, 162 seconds passed
+... 85%, 596896 KB, 3675 KB/s, 162 seconds passed
+... 85%, 596928 KB, 3675 KB/s, 162 seconds passed
+... 85%, 596960 KB, 3675 KB/s, 162 seconds passed
+... 85%, 596992 KB, 3675 KB/s, 162 seconds passed
+... 85%, 597024 KB, 3675 KB/s, 162 seconds passed
+... 85%, 597056 KB, 3675 KB/s, 162 seconds passed
 
 .. parsed-literal::
 
-    ... 86%, 600192 KB, 3376 KB/s, 177 seconds passed
-... 86%, 600224 KB, 3376 KB/s, 177 seconds passed
-... 86%, 600256 KB, 3377 KB/s, 177 seconds passed
-... 86%, 600288 KB, 3377 KB/s, 177 seconds passed
-... 86%, 600320 KB, 3376 KB/s, 177 seconds passed
-... 86%, 600352 KB, 3376 KB/s, 177 seconds passed
+    ... 85%, 597088 KB, 3675 KB/s, 162 seconds passed
+... 85%, 597120 KB, 3675 KB/s, 162 seconds passed
+... 85%, 597152 KB, 3675 KB/s, 162 seconds passed
+... 85%, 597184 KB, 3675 KB/s, 162 seconds passed
 
 .. parsed-literal::
 
-    ... 86%, 600384 KB, 3377 KB/s, 177 seconds passed
-... 86%, 600416 KB, 3377 KB/s, 177 seconds passed
-... 86%, 600448 KB, 3376 KB/s, 177 seconds passed
-... 86%, 600480 KB, 3377 KB/s, 177 seconds passed
-... 86%, 600512 KB, 3377 KB/s, 177 seconds passed
-... 86%, 600544 KB, 3377 KB/s, 177 seconds passed
+    ... 85%, 597216 KB, 3675 KB/s, 162 seconds passed
+... 85%, 597248 KB, 3675 KB/s, 162 seconds passed
+... 85%, 597280 KB, 3675 KB/s, 162 seconds passed
+... 85%, 597312 KB, 3676 KB/s, 162 seconds passed
+... 85%, 597344 KB, 3675 KB/s, 162 seconds passed
+... 85%, 597376 KB, 3675 KB/s, 162 seconds passed
+... 85%, 597408 KB, 3675 KB/s, 162 seconds passed
 
 .. parsed-literal::
 
-    ... 86%, 600576 KB, 3376 KB/s, 177 seconds passed
-... 86%, 600608 KB, 3377 KB/s, 177 seconds passed
-... 86%, 600640 KB, 3377 KB/s, 177 seconds passed
-... 86%, 600672 KB, 3377 KB/s, 177 seconds passed
-... 86%, 600704 KB, 3377 KB/s, 177 seconds passed
+    ... 85%, 597440 KB, 3675 KB/s, 162 seconds passed
+... 85%, 597472 KB, 3675 KB/s, 162 seconds passed
+... 85%, 597504 KB, 3675 KB/s, 162 seconds passed
+... 85%, 597536 KB, 3675 KB/s, 162 seconds passed
+... 85%, 597568 KB, 3675 KB/s, 162 seconds passed
 
 .. parsed-literal::
 
-    ... 86%, 600736 KB, 3377 KB/s, 177 seconds passed
-... 86%, 600768 KB, 3377 KB/s, 177 seconds passed
-... 86%, 600800 KB, 3377 KB/s, 177 seconds passed
-... 86%, 600832 KB, 3377 KB/s, 177 seconds passed
-... 86%, 600864 KB, 3377 KB/s, 177 seconds passed
-... 86%, 600896 KB, 3377 KB/s, 177 seconds passed
-... 86%, 600928 KB, 3377 KB/s, 177 seconds passed
+    ... 85%, 597600 KB, 3675 KB/s, 162 seconds passed
+... 85%, 597632 KB, 3675 KB/s, 162 seconds passed
+... 85%, 597664 KB, 3675 KB/s, 162 seconds passed
+... 85%, 597696 KB, 3675 KB/s, 162 seconds passed
+... 85%, 597728 KB, 3675 KB/s, 162 seconds passed
+... 85%, 597760 KB, 3675 KB/s, 162 seconds passed
+... 85%, 597792 KB, 3675 KB/s, 162 seconds passed
 
 .. parsed-literal::
 
-    ... 86%, 600960 KB, 3377 KB/s, 177 seconds passed
-... 86%, 600992 KB, 3377 KB/s, 177 seconds passed
-... 86%, 601024 KB, 3377 KB/s, 177 seconds passed
-... 86%, 601056 KB, 3377 KB/s, 177 seconds passed
-... 86%, 601088 KB, 3377 KB/s, 177 seconds passed
+    ... 85%, 597824 KB, 3675 KB/s, 162 seconds passed
+... 85%, 597856 KB, 3675 KB/s, 162 seconds passed
+... 85%, 597888 KB, 3675 KB/s, 162 seconds passed
+... 85%, 597920 KB, 3675 KB/s, 162 seconds passed
+... 85%, 597952 KB, 3675 KB/s, 162 seconds passed
 
 .. parsed-literal::
 
-    ... 86%, 601120 KB, 3377 KB/s, 177 seconds passed
-... 86%, 601152 KB, 3377 KB/s, 177 seconds passed
-... 86%, 601184 KB, 3377 KB/s, 177 seconds passed
-... 86%, 601216 KB, 3377 KB/s, 178 seconds passed
-... 86%, 601248 KB, 3377 KB/s, 178 seconds passed
-... 86%, 601280 KB, 3377 KB/s, 178 seconds passed
-... 86%, 601312 KB, 3377 KB/s, 178 seconds passed
+    ... 85%, 597984 KB, 3675 KB/s, 162 seconds passed
+... 85%, 598016 KB, 3675 KB/s, 162 seconds passed
+... 85%, 598048 KB, 3675 KB/s, 162 seconds passed
+... 85%, 598080 KB, 3675 KB/s, 162 seconds passed
+... 85%, 598112 KB, 3675 KB/s, 162 seconds passed
+... 86%, 598144 KB, 3675 KB/s, 162 seconds passed
 
 .. parsed-literal::
 
-    ... 86%, 601344 KB, 3377 KB/s, 178 seconds passed
-... 86%, 601376 KB, 3377 KB/s, 178 seconds passed
-... 86%, 601408 KB, 3377 KB/s, 178 seconds passed
-... 86%, 601440 KB, 3377 KB/s, 178 seconds passed
-... 86%, 601472 KB, 3377 KB/s, 178 seconds passed
+    ... 86%, 598176 KB, 3675 KB/s, 162 seconds passed
+... 86%, 598208 KB, 3675 KB/s, 162 seconds passed
+... 86%, 598240 KB, 3675 KB/s, 162 seconds passed
+... 86%, 598272 KB, 3675 KB/s, 162 seconds passed
+... 86%, 598304 KB, 3675 KB/s, 162 seconds passed
+... 86%, 598336 KB, 3676 KB/s, 162 seconds passed
 
 .. parsed-literal::
 
-    ... 86%, 601504 KB, 3377 KB/s, 178 seconds passed
-... 86%, 601536 KB, 3377 KB/s, 178 seconds passed
-... 86%, 601568 KB, 3377 KB/s, 178 seconds passed
-... 86%, 601600 KB, 3377 KB/s, 178 seconds passed
-... 86%, 601632 KB, 3377 KB/s, 178 seconds passed
-... 86%, 601664 KB, 3377 KB/s, 178 seconds passed
+    ... 86%, 598368 KB, 3675 KB/s, 162 seconds passed
+... 86%, 598400 KB, 3675 KB/s, 162 seconds passed
+... 86%, 598432 KB, 3675 KB/s, 162 seconds passed
+... 86%, 598464 KB, 3676 KB/s, 162 seconds passed
+... 86%, 598496 KB, 3675 KB/s, 162 seconds passed
+... 86%, 598528 KB, 3675 KB/s, 162 seconds passed
 
 .. parsed-literal::
 
-    ... 86%, 601696 KB, 3377 KB/s, 178 seconds passed
-... 86%, 601728 KB, 3377 KB/s, 178 seconds passed
-... 86%, 601760 KB, 3377 KB/s, 178 seconds passed
-... 86%, 601792 KB, 3377 KB/s, 178 seconds passed
-... 86%, 601824 KB, 3377 KB/s, 178 seconds passed
+    ... 86%, 598560 KB, 3675 KB/s, 162 seconds passed
+... 86%, 598592 KB, 3676 KB/s, 162 seconds passed
+... 86%, 598624 KB, 3675 KB/s, 162 seconds passed
+... 86%, 598656 KB, 3675 KB/s, 162 seconds passed
+... 86%, 598688 KB, 3675 KB/s, 162 seconds passed
+... 86%, 598720 KB, 3676 KB/s, 162 seconds passed
 
 .. parsed-literal::
 
-    ... 86%, 601856 KB, 3377 KB/s, 178 seconds passed
-... 86%, 601888 KB, 3377 KB/s, 178 seconds passed
-... 86%, 601920 KB, 3377 KB/s, 178 seconds passed
-... 86%, 601952 KB, 3377 KB/s, 178 seconds passed
-... 86%, 601984 KB, 3377 KB/s, 178 seconds passed
-... 86%, 602016 KB, 3377 KB/s, 178 seconds passed
-... 86%, 602048 KB, 3377 KB/s, 178 seconds passed
+    ... 86%, 598752 KB, 3675 KB/s, 162 seconds passed
+... 86%, 598784 KB, 3675 KB/s, 162 seconds passed
+... 86%, 598816 KB, 3675 KB/s, 162 seconds passed
+... 86%, 598848 KB, 3676 KB/s, 162 seconds passed
+... 86%, 598880 KB, 3675 KB/s, 162 seconds passed
+... 86%, 598912 KB, 3675 KB/s, 162 seconds passed
 
 .. parsed-literal::
 
-    ... 86%, 602080 KB, 3377 KB/s, 178 seconds passed
-... 86%, 602112 KB, 3377 KB/s, 178 seconds passed
-... 86%, 602144 KB, 3377 KB/s, 178 seconds passed
-... 86%, 602176 KB, 3377 KB/s, 178 seconds passed
-... 86%, 602208 KB, 3377 KB/s, 178 seconds passed
+    ... 86%, 598944 KB, 3675 KB/s, 162 seconds passed
+... 86%, 598976 KB, 3676 KB/s, 162 seconds passed
+... 86%, 599008 KB, 3675 KB/s, 162 seconds passed
+... 86%, 599040 KB, 3675 KB/s, 162 seconds passed
+... 86%, 599072 KB, 3675 KB/s, 162 seconds passed
+... 86%, 599104 KB, 3676 KB/s, 162 seconds passed
 
 .. parsed-literal::
 
-    ... 86%, 602240 KB, 3377 KB/s, 178 seconds passed
-... 86%, 602272 KB, 3377 KB/s, 178 seconds passed
-... 86%, 602304 KB, 3377 KB/s, 178 seconds passed
-... 86%, 602336 KB, 3377 KB/s, 178 seconds passed
-... 86%, 602368 KB, 3377 KB/s, 178 seconds passed
-... 86%, 602400 KB, 3377 KB/s, 178 seconds passed
-... 86%, 602432 KB, 3378 KB/s, 178 seconds passed
+    ... 86%, 599136 KB, 3675 KB/s, 162 seconds passed
+... 86%, 599168 KB, 3675 KB/s, 162 seconds passed
+... 86%, 599200 KB, 3675 KB/s, 163 seconds passed
+... 86%, 599232 KB, 3676 KB/s, 163 seconds passed
+... 86%, 599264 KB, 3675 KB/s, 163 seconds passed
+... 86%, 599296 KB, 3675 KB/s, 163 seconds passed
 
 .. parsed-literal::
 
-    ... 86%, 602464 KB, 3377 KB/s, 178 seconds passed
-... 86%, 602496 KB, 3377 KB/s, 178 seconds passed
-... 86%, 602528 KB, 3377 KB/s, 178 seconds passed
-... 86%, 602560 KB, 3378 KB/s, 178 seconds passed
+    ... 86%, 599328 KB, 3675 KB/s, 163 seconds passed
+... 86%, 599360 KB, 3676 KB/s, 163 seconds passed
+... 86%, 599392 KB, 3675 KB/s, 163 seconds passed
+... 86%, 599424 KB, 3675 KB/s, 163 seconds passed
+... 86%, 599456 KB, 3675 KB/s, 163 seconds passed
+... 86%, 599488 KB, 3676 KB/s, 163 seconds passed
 
 .. parsed-literal::
 
-    ... 86%, 602592 KB, 3377 KB/s, 178 seconds passed
-... 86%, 602624 KB, 3377 KB/s, 178 seconds passed
-... 86%, 602656 KB, 3378 KB/s, 178 seconds passed
-... 86%, 602688 KB, 3378 KB/s, 178 seconds passed
-... 86%, 602720 KB, 3377 KB/s, 178 seconds passed
-... 86%, 602752 KB, 3378 KB/s, 178 seconds passed
-... 86%, 602784 KB, 3378 KB/s, 178 seconds passed
-... 86%, 602816 KB, 3378 KB/s, 178 seconds passed
+    ... 86%, 599520 KB, 3675 KB/s, 163 seconds passed
+... 86%, 599552 KB, 3675 KB/s, 163 seconds passed
+... 86%, 599584 KB, 3675 KB/s, 163 seconds passed
+... 86%, 599616 KB, 3676 KB/s, 163 seconds passed
+... 86%, 599648 KB, 3675 KB/s, 163 seconds passed
+... 86%, 599680 KB, 3675 KB/s, 163 seconds passed
 
 .. parsed-literal::
 
-    ... 86%, 602848 KB, 3377 KB/s, 178 seconds passed
-... 86%, 602880 KB, 3378 KB/s, 178 seconds passed
-... 86%, 602912 KB, 3378 KB/s, 178 seconds passed
-... 86%, 602944 KB, 3378 KB/s, 178 seconds passed
+    ... 86%, 599712 KB, 3675 KB/s, 163 seconds passed
+... 86%, 599744 KB, 3676 KB/s, 163 seconds passed
+... 86%, 599776 KB, 3675 KB/s, 163 seconds passed
+... 86%, 599808 KB, 3675 KB/s, 163 seconds passed
+... 86%, 599840 KB, 3675 KB/s, 163 seconds passed
+... 86%, 599872 KB, 3676 KB/s, 163 seconds passed
 
 .. parsed-literal::
 
-    ... 86%, 602976 KB, 3378 KB/s, 178 seconds passed
-... 86%, 603008 KB, 3378 KB/s, 178 seconds passed
-... 86%, 603040 KB, 3378 KB/s, 178 seconds passed
-... 86%, 603072 KB, 3378 KB/s, 178 seconds passed
-... 86%, 603104 KB, 3378 KB/s, 178 seconds passed
-... 86%, 603136 KB, 3378 KB/s, 178 seconds passed
-... 86%, 603168 KB, 3378 KB/s, 178 seconds passed
-... 86%, 603200 KB, 3378 KB/s, 178 seconds passed
+    ... 86%, 599904 KB, 3675 KB/s, 163 seconds passed
+... 86%, 599936 KB, 3675 KB/s, 163 seconds passed
+... 86%, 599968 KB, 3675 KB/s, 163 seconds passed
+... 86%, 600000 KB, 3676 KB/s, 163 seconds passed
+... 86%, 600032 KB, 3675 KB/s, 163 seconds passed
+... 86%, 600064 KB, 3675 KB/s, 163 seconds passed
 
 .. parsed-literal::
 
-    ... 86%, 603232 KB, 3378 KB/s, 178 seconds passed
-... 86%, 603264 KB, 3378 KB/s, 178 seconds passed
-... 86%, 603296 KB, 3378 KB/s, 178 seconds passed
-... 86%, 603328 KB, 3378 KB/s, 178 seconds passed
+    ... 86%, 600096 KB, 3675 KB/s, 163 seconds passed
+... 86%, 600128 KB, 3676 KB/s, 163 seconds passed
+... 86%, 600160 KB, 3675 KB/s, 163 seconds passed
+... 86%, 600192 KB, 3675 KB/s, 163 seconds passed
+... 86%, 600224 KB, 3675 KB/s, 163 seconds passed
+... 86%, 600256 KB, 3676 KB/s, 163 seconds passed
 
 .. parsed-literal::
 
-    ... 86%, 603360 KB, 3378 KB/s, 178 seconds passed
-... 86%, 603392 KB, 3378 KB/s, 178 seconds passed
-... 86%, 603424 KB, 3378 KB/s, 178 seconds passed
-... 86%, 603456 KB, 3378 KB/s, 178 seconds passed
-... 86%, 603488 KB, 3378 KB/s, 178 seconds passed
-... 86%, 603520 KB, 3378 KB/s, 178 seconds passed
-... 86%, 603552 KB, 3378 KB/s, 178 seconds passed
-... 86%, 603584 KB, 3378 KB/s, 178 seconds passed
+    ... 86%, 600288 KB, 3675 KB/s, 163 seconds passed
+... 86%, 600320 KB, 3675 KB/s, 163 seconds passed
+... 86%, 600352 KB, 3675 KB/s, 163 seconds passed
+... 86%, 600384 KB, 3676 KB/s, 163 seconds passed
+... 86%, 600416 KB, 3675 KB/s, 163 seconds passed
+... 86%, 600448 KB, 3676 KB/s, 163 seconds passed
 
 .. parsed-literal::
 
-    ... 86%, 603616 KB, 3378 KB/s, 178 seconds passed
-... 86%, 603648 KB, 3378 KB/s, 178 seconds passed
-... 86%, 603680 KB, 3378 KB/s, 178 seconds passed
-... 86%, 603712 KB, 3378 KB/s, 178 seconds passed
+    ... 86%, 600480 KB, 3676 KB/s, 163 seconds passed
+... 86%, 600512 KB, 3675 KB/s, 163 seconds passed
+... 86%, 600544 KB, 3675 KB/s, 163 seconds passed
+... 86%, 600576 KB, 3675 KB/s, 163 seconds passed
+... 86%, 600608 KB, 3676 KB/s, 163 seconds passed
+... 86%, 600640 KB, 3676 KB/s, 163 seconds passed
 
 .. parsed-literal::
 
-    ... 86%, 603744 KB, 3378 KB/s, 178 seconds passed
-... 86%, 603776 KB, 3378 KB/s, 178 seconds passed
-... 86%, 603808 KB, 3378 KB/s, 178 seconds passed
-... 86%, 603840 KB, 3378 KB/s, 178 seconds passed
-... 86%, 603872 KB, 3378 KB/s, 178 seconds passed
-... 86%, 603904 KB, 3378 KB/s, 178 seconds passed
-... 86%, 603936 KB, 3378 KB/s, 178 seconds passed
+    ... 86%, 600672 KB, 3675 KB/s, 163 seconds passed
+... 86%, 600704 KB, 3675 KB/s, 163 seconds passed
+... 86%, 600736 KB, 3676 KB/s, 163 seconds passed
+... 86%, 600768 KB, 3676 KB/s, 163 seconds passed
+... 86%, 600800 KB, 3675 KB/s, 163 seconds passed
+... 86%, 600832 KB, 3676 KB/s, 163 seconds passed
 
 .. parsed-literal::
 
-    ... 86%, 603968 KB, 3378 KB/s, 178 seconds passed
-... 86%, 604000 KB, 3378 KB/s, 178 seconds passed
-... 86%, 604032 KB, 3378 KB/s, 178 seconds passed
-... 86%, 604064 KB, 3378 KB/s, 178 seconds passed
-... 86%, 604096 KB, 3378 KB/s, 178 seconds passed
+    ... 86%, 600864 KB, 3676 KB/s, 163 seconds passed
+... 86%, 600896 KB, 3675 KB/s, 163 seconds passed
+... 86%, 600928 KB, 3675 KB/s, 163 seconds passed
+... 86%, 600960 KB, 3675 KB/s, 163 seconds passed
+... 86%, 600992 KB, 3676 KB/s, 163 seconds passed
 
 .. parsed-literal::
 
-    ... 86%, 604128 KB, 3378 KB/s, 178 seconds passed
-... 86%, 604160 KB, 3378 KB/s, 178 seconds passed
-... 86%, 604192 KB, 3378 KB/s, 178 seconds passed
-... 86%, 604224 KB, 3378 KB/s, 178 seconds passed
-... 86%, 604256 KB, 3378 KB/s, 178 seconds passed
-... 86%, 604288 KB, 3378 KB/s, 178 seconds passed
-... 86%, 604320 KB, 3378 KB/s, 178 seconds passed
+    ... 86%, 601024 KB, 3675 KB/s, 163 seconds passed
+... 86%, 601056 KB, 3675 KB/s, 163 seconds passed
+... 86%, 601088 KB, 3675 KB/s, 163 seconds passed
+... 86%, 601120 KB, 3676 KB/s, 163 seconds passed
+... 86%, 601152 KB, 3675 KB/s, 163 seconds passed
+... 86%, 601184 KB, 3675 KB/s, 163 seconds passed
 
 .. parsed-literal::
 
-    ... 86%, 604352 KB, 3378 KB/s, 178 seconds passed
-... 86%, 604384 KB, 3378 KB/s, 178 seconds passed
-... 86%, 604416 KB, 3378 KB/s, 178 seconds passed
-... 86%, 604448 KB, 3378 KB/s, 178 seconds passed
+    ... 86%, 601216 KB, 3675 KB/s, 163 seconds passed
+... 86%, 601248 KB, 3676 KB/s, 163 seconds passed
+... 86%, 601280 KB, 3675 KB/s, 163 seconds passed
+... 86%, 601312 KB, 3675 KB/s, 163 seconds passed
+... 86%, 601344 KB, 3675 KB/s, 163 seconds passed
+... 86%, 601376 KB, 3676 KB/s, 163 seconds passed
 
 .. parsed-literal::
 
-    ... 86%, 604480 KB, 3378 KB/s, 178 seconds passed
-... 86%, 604512 KB, 3378 KB/s, 178 seconds passed
-... 86%, 604544 KB, 3378 KB/s, 178 seconds passed
-... 86%, 604576 KB, 3378 KB/s, 178 seconds passed
-... 86%, 604608 KB, 3378 KB/s, 178 seconds passed
-... 86%, 604640 KB, 3378 KB/s, 178 seconds passed
-... 86%, 604672 KB, 3378 KB/s, 178 seconds passed
-... 86%, 604704 KB, 3379 KB/s, 178 seconds passed
+    ... 86%, 601408 KB, 3675 KB/s, 163 seconds passed
+... 86%, 601440 KB, 3675 KB/s, 163 seconds passed
+... 86%, 601472 KB, 3675 KB/s, 163 seconds passed
+... 86%, 601504 KB, 3676 KB/s, 163 seconds passed
+... 86%, 601536 KB, 3675 KB/s, 163 seconds passed
+... 86%, 601568 KB, 3675 KB/s, 163 seconds passed
 
 .. parsed-literal::
 
-    ... 86%, 604736 KB, 3378 KB/s, 178 seconds passed
-... 86%, 604768 KB, 3378 KB/s, 178 seconds passed
-... 86%, 604800 KB, 3378 KB/s, 178 seconds passed
-... 86%, 604832 KB, 3379 KB/s, 178 seconds passed
+    ... 86%, 601600 KB, 3675 KB/s, 163 seconds passed
+... 86%, 601632 KB, 3676 KB/s, 163 seconds passed
+... 86%, 601664 KB, 3675 KB/s, 163 seconds passed
+... 86%, 601696 KB, 3675 KB/s, 163 seconds passed
+... 86%, 601728 KB, 3675 KB/s, 163 seconds passed
+... 86%, 601760 KB, 3676 KB/s, 163 seconds passed
 
 .. parsed-literal::
 
-    ... 86%, 604864 KB, 3378 KB/s, 179 seconds passed
-... 86%, 604896 KB, 3378 KB/s, 179 seconds passed
-... 86%, 604928 KB, 3379 KB/s, 179 seconds passed
-... 86%, 604960 KB, 3379 KB/s, 179 seconds passed
-... 86%, 604992 KB, 3378 KB/s, 179 seconds passed
-... 86%, 605024 KB, 3378 KB/s, 179 seconds passed
-... 86%, 605056 KB, 3379 KB/s, 179 seconds passed
+    ... 86%, 601792 KB, 3675 KB/s, 163 seconds passed
+... 86%, 601824 KB, 3675 KB/s, 163 seconds passed
+... 86%, 601856 KB, 3675 KB/s, 163 seconds passed
+... 86%, 601888 KB, 3676 KB/s, 163 seconds passed
+... 86%, 601920 KB, 3675 KB/s, 163 seconds passed
+... 86%, 601952 KB, 3675 KB/s, 163 seconds passed
 
 .. parsed-literal::
 
-    ... 86%, 605088 KB, 3379 KB/s, 179 seconds passed
-... 87%, 605120 KB, 3378 KB/s, 179 seconds passed
-... 87%, 605152 KB, 3379 KB/s, 179 seconds passed
-... 87%, 605184 KB, 3379 KB/s, 179 seconds passed
-... 87%, 605216 KB, 3379 KB/s, 179 seconds passed
+    ... 86%, 601984 KB, 3675 KB/s, 163 seconds passed
+... 86%, 602016 KB, 3676 KB/s, 163 seconds passed
+... 86%, 602048 KB, 3675 KB/s, 163 seconds passed
+... 86%, 602080 KB, 3675 KB/s, 163 seconds passed
+... 86%, 602112 KB, 3676 KB/s, 163 seconds passed
+... 86%, 602144 KB, 3676 KB/s, 163 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 605248 KB, 3379 KB/s, 179 seconds passed
-... 87%, 605280 KB, 3379 KB/s, 179 seconds passed
-... 87%, 605312 KB, 3379 KB/s, 179 seconds passed
-... 87%, 605344 KB, 3379 KB/s, 179 seconds passed
-... 87%, 605376 KB, 3379 KB/s, 179 seconds passed
-... 87%, 605408 KB, 3379 KB/s, 179 seconds passed
-... 87%, 605440 KB, 3379 KB/s, 179 seconds passed
+    ... 86%, 602176 KB, 3675 KB/s, 163 seconds passed
+... 86%, 602208 KB, 3675 KB/s, 163 seconds passed
+... 86%, 602240 KB, 3675 KB/s, 163 seconds passed
+... 86%, 602272 KB, 3676 KB/s, 163 seconds passed
+... 86%, 602304 KB, 3675 KB/s, 163 seconds passed
+... 86%, 602336 KB, 3675 KB/s, 163 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 605472 KB, 3379 KB/s, 179 seconds passed
-... 87%, 605504 KB, 3379 KB/s, 179 seconds passed
-... 87%, 605536 KB, 3379 KB/s, 179 seconds passed
-... 87%, 605568 KB, 3379 KB/s, 179 seconds passed
-... 87%, 605600 KB, 3379 KB/s, 179 seconds passed
+    ... 86%, 602368 KB, 3676 KB/s, 163 seconds passed
+... 86%, 602400 KB, 3676 KB/s, 163 seconds passed
+... 86%, 602432 KB, 3675 KB/s, 163 seconds passed
+... 86%, 602464 KB, 3676 KB/s, 163 seconds passed
+... 86%, 602496 KB, 3676 KB/s, 163 seconds passed
+... 86%, 602528 KB, 3676 KB/s, 163 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 605632 KB, 3379 KB/s, 179 seconds passed
-... 87%, 605664 KB, 3379 KB/s, 179 seconds passed
-... 87%, 605696 KB, 3379 KB/s, 179 seconds passed
-... 87%, 605728 KB, 3379 KB/s, 179 seconds passed
-... 87%, 605760 KB, 3379 KB/s, 179 seconds passed
-... 87%, 605792 KB, 3379 KB/s, 179 seconds passed
+    ... 86%, 602560 KB, 3675 KB/s, 163 seconds passed
+... 86%, 602592 KB, 3676 KB/s, 163 seconds passed
+... 86%, 602624 KB, 3676 KB/s, 163 seconds passed
+... 86%, 602656 KB, 3676 KB/s, 163 seconds passed
+... 86%, 602688 KB, 3675 KB/s, 163 seconds passed
+... 86%, 602720 KB, 3676 KB/s, 163 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 605824 KB, 3378 KB/s, 179 seconds passed
-... 87%, 605856 KB, 3379 KB/s, 179 seconds passed
-... 87%, 605888 KB, 3379 KB/s, 179 seconds passed
-... 87%, 605920 KB, 3379 KB/s, 179 seconds passed
+    ... 86%, 602752 KB, 3676 KB/s, 163 seconds passed
+... 86%, 602784 KB, 3676 KB/s, 163 seconds passed
+... 86%, 602816 KB, 3675 KB/s, 163 seconds passed
+... 86%, 602848 KB, 3676 KB/s, 163 seconds passed
+... 86%, 602880 KB, 3676 KB/s, 164 seconds passed
+... 86%, 602912 KB, 3676 KB/s, 164 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 605952 KB, 3378 KB/s, 179 seconds passed
+    ... 86%, 602944 KB, 3675 KB/s, 164 seconds passed
+... 86%, 602976 KB, 3676 KB/s, 164 seconds passed
+... 86%, 603008 KB, 3676 KB/s, 164 seconds passed
+... 86%, 603040 KB, 3676 KB/s, 164 seconds passed
+... 86%, 603072 KB, 3675 KB/s, 164 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 605984 KB, 3377 KB/s, 179 seconds passed
+    ... 86%, 603104 KB, 3676 KB/s, 164 seconds passed
+... 86%, 603136 KB, 3676 KB/s, 164 seconds passed
+... 86%, 603168 KB, 3676 KB/s, 164 seconds passed
+... 86%, 603200 KB, 3675 KB/s, 164 seconds passed
+... 86%, 603232 KB, 3676 KB/s, 164 seconds passed
+... 86%, 603264 KB, 3676 KB/s, 164 seconds passed
+... 86%, 603296 KB, 3676 KB/s, 164 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 606016 KB, 3377 KB/s, 179 seconds passed
+    ... 86%, 603328 KB, 3675 KB/s, 164 seconds passed
+... 86%, 603360 KB, 3676 KB/s, 164 seconds passed
+... 86%, 603392 KB, 3676 KB/s, 164 seconds passed
+... 86%, 603424 KB, 3676 KB/s, 164 seconds passed
+... 86%, 603456 KB, 3675 KB/s, 164 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 606048 KB, 3376 KB/s, 179 seconds passed
-... 87%, 606080 KB, 3376 KB/s, 179 seconds passed
-... 87%, 606112 KB, 3376 KB/s, 179 seconds passed
+    ... 86%, 603488 KB, 3676 KB/s, 164 seconds passed
+... 86%, 603520 KB, 3676 KB/s, 164 seconds passed
+... 86%, 603552 KB, 3676 KB/s, 164 seconds passed
+... 86%, 603584 KB, 3676 KB/s, 164 seconds passed
+... 86%, 603616 KB, 3676 KB/s, 164 seconds passed
+... 86%, 603648 KB, 3676 KB/s, 164 seconds passed
+... 86%, 603680 KB, 3676 KB/s, 164 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 606144 KB, 3376 KB/s, 179 seconds passed
-... 87%, 606176 KB, 3375 KB/s, 179 seconds passed
+    ... 86%, 603712 KB, 3675 KB/s, 164 seconds passed
+... 86%, 603744 KB, 3676 KB/s, 164 seconds passed
+... 86%, 603776 KB, 3676 KB/s, 164 seconds passed
+... 86%, 603808 KB, 3676 KB/s, 164 seconds passed
+... 86%, 603840 KB, 3675 KB/s, 164 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 606208 KB, 3375 KB/s, 179 seconds passed
-... 87%, 606240 KB, 3375 KB/s, 179 seconds passed
-... 87%, 606272 KB, 3375 KB/s, 179 seconds passed
+    ... 86%, 603872 KB, 3676 KB/s, 164 seconds passed
+... 86%, 603904 KB, 3676 KB/s, 164 seconds passed
+... 86%, 603936 KB, 3676 KB/s, 164 seconds passed
+... 86%, 603968 KB, 3675 KB/s, 164 seconds passed
+... 86%, 604000 KB, 3676 KB/s, 164 seconds passed
+... 86%, 604032 KB, 3676 KB/s, 164 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 606304 KB, 3375 KB/s, 179 seconds passed
-... 87%, 606336 KB, 3375 KB/s, 179 seconds passed
+    ... 86%, 604064 KB, 3676 KB/s, 164 seconds passed
+... 86%, 604096 KB, 3676 KB/s, 164 seconds passed
+... 86%, 604128 KB, 3676 KB/s, 164 seconds passed
+... 86%, 604160 KB, 3676 KB/s, 164 seconds passed
+... 86%, 604192 KB, 3676 KB/s, 164 seconds passed
+... 86%, 604224 KB, 3676 KB/s, 164 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 606368 KB, 3374 KB/s, 179 seconds passed
-... 87%, 606400 KB, 3374 KB/s, 179 seconds passed
-... 87%, 606432 KB, 3374 KB/s, 179 seconds passed
-... 87%, 606464 KB, 3374 KB/s, 179 seconds passed
-... 87%, 606496 KB, 3374 KB/s, 179 seconds passed
+    ... 86%, 604256 KB, 3676 KB/s, 164 seconds passed
+... 86%, 604288 KB, 3676 KB/s, 164 seconds passed
+... 86%, 604320 KB, 3676 KB/s, 164 seconds passed
+... 86%, 604352 KB, 3676 KB/s, 164 seconds passed
+... 86%, 604384 KB, 3676 KB/s, 164 seconds passed
+... 86%, 604416 KB, 3676 KB/s, 164 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 606528 KB, 3374 KB/s, 179 seconds passed
-... 87%, 606560 KB, 3374 KB/s, 179 seconds passed
+    ... 86%, 604448 KB, 3676 KB/s, 164 seconds passed
+... 86%, 604480 KB, 3676 KB/s, 164 seconds passed
+... 86%, 604512 KB, 3676 KB/s, 164 seconds passed
+... 86%, 604544 KB, 3676 KB/s, 164 seconds passed
+... 86%, 604576 KB, 3676 KB/s, 164 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 606592 KB, 3374 KB/s, 179 seconds passed
-... 87%, 606624 KB, 3374 KB/s, 179 seconds passed
-... 87%, 606656 KB, 3374 KB/s, 179 seconds passed
-... 87%, 606688 KB, 3373 KB/s, 179 seconds passed
-... 87%, 606720 KB, 3374 KB/s, 179 seconds passed
-... 87%, 606752 KB, 3374 KB/s, 179 seconds passed
+    ... 86%, 604608 KB, 3676 KB/s, 164 seconds passed
+... 86%, 604640 KB, 3676 KB/s, 164 seconds passed
+... 86%, 604672 KB, 3676 KB/s, 164 seconds passed
+... 86%, 604704 KB, 3676 KB/s, 164 seconds passed
+... 86%, 604736 KB, 3676 KB/s, 164 seconds passed
+... 86%, 604768 KB, 3676 KB/s, 164 seconds passed
+... 86%, 604800 KB, 3676 KB/s, 164 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 606784 KB, 3373 KB/s, 179 seconds passed
-... 87%, 606816 KB, 3373 KB/s, 179 seconds passed
-... 87%, 606848 KB, 3374 KB/s, 179 seconds passed
+    ... 86%, 604832 KB, 3676 KB/s, 164 seconds passed
+... 86%, 604864 KB, 3676 KB/s, 164 seconds passed
+... 86%, 604896 KB, 3676 KB/s, 164 seconds passed
+... 86%, 604928 KB, 3676 KB/s, 164 seconds passed
+... 86%, 604960 KB, 3676 KB/s, 164 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 606880 KB, 3373 KB/s, 179 seconds passed
-... 87%, 606912 KB, 3373 KB/s, 179 seconds passed
-... 87%, 606944 KB, 3373 KB/s, 179 seconds passed
-... 87%, 606976 KB, 3373 KB/s, 179 seconds passed
-... 87%, 607008 KB, 3373 KB/s, 179 seconds passed
-... 87%, 607040 KB, 3373 KB/s, 179 seconds passed
-... 87%, 607072 KB, 3373 KB/s, 179 seconds passed
+    ... 86%, 604992 KB, 3676 KB/s, 164 seconds passed
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+... 86%, 605056 KB, 3676 KB/s, 164 seconds passed
+... 86%, 605088 KB, 3676 KB/s, 164 seconds passed
+... 87%, 605120 KB, 3676 KB/s, 164 seconds passed
+... 87%, 605152 KB, 3676 KB/s, 164 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 607104 KB, 3373 KB/s, 179 seconds passed
-... 87%, 607136 KB, 3373 KB/s, 179 seconds passed
-... 87%, 607168 KB, 3373 KB/s, 179 seconds passed
-... 87%, 607200 KB, 3373 KB/s, 179 seconds passed
+    ... 87%, 605184 KB, 3676 KB/s, 164 seconds passed
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+... 87%, 605248 KB, 3676 KB/s, 164 seconds passed
+... 87%, 605280 KB, 3676 KB/s, 164 seconds passed
+... 87%, 605312 KB, 3676 KB/s, 164 seconds passed
+... 87%, 605344 KB, 3676 KB/s, 164 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 607232 KB, 3373 KB/s, 179 seconds passed
-... 87%, 607264 KB, 3373 KB/s, 179 seconds passed
-... 87%, 607296 KB, 3373 KB/s, 179 seconds passed
-... 87%, 607328 KB, 3374 KB/s, 179 seconds passed
-... 87%, 607360 KB, 3373 KB/s, 180 seconds passed
-... 87%, 607392 KB, 3373 KB/s, 180 seconds passed
-... 87%, 607424 KB, 3374 KB/s, 180 seconds passed
-... 87%, 607456 KB, 3374 KB/s, 180 seconds passed
+    ... 87%, 605376 KB, 3676 KB/s, 164 seconds passed
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+... 87%, 605472 KB, 3675 KB/s, 164 seconds passed
+... 87%, 605504 KB, 3676 KB/s, 164 seconds passed
+... 87%, 605536 KB, 3676 KB/s, 164 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 607488 KB, 3373 KB/s, 180 seconds passed
-... 87%, 607520 KB, 3373 KB/s, 180 seconds passed
-... 87%, 607552 KB, 3374 KB/s, 180 seconds passed
-... 87%, 607584 KB, 3374 KB/s, 180 seconds passed
+    ... 87%, 605568 KB, 3676 KB/s, 164 seconds passed
+... 87%, 605600 KB, 3675 KB/s, 164 seconds passed
+... 87%, 605632 KB, 3676 KB/s, 164 seconds passed
+... 87%, 605664 KB, 3676 KB/s, 164 seconds passed
+... 87%, 605696 KB, 3676 KB/s, 164 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 607616 KB, 3373 KB/s, 180 seconds passed
-... 87%, 607648 KB, 3373 KB/s, 180 seconds passed
-... 87%, 607680 KB, 3374 KB/s, 180 seconds passed
-... 87%, 607712 KB, 3374 KB/s, 180 seconds passed
-... 87%, 607744 KB, 3373 KB/s, 180 seconds passed
-... 87%, 607776 KB, 3374 KB/s, 180 seconds passed
-... 87%, 607808 KB, 3374 KB/s, 180 seconds passed
-... 87%, 607840 KB, 3374 KB/s, 180 seconds passed
+    ... 87%, 605728 KB, 3675 KB/s, 164 seconds passed
+... 87%, 605760 KB, 3676 KB/s, 164 seconds passed
+... 87%, 605792 KB, 3676 KB/s, 164 seconds passed
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+... 87%, 605856 KB, 3675 KB/s, 164 seconds passed
+... 87%, 605888 KB, 3676 KB/s, 164 seconds passed
+... 87%, 605920 KB, 3676 KB/s, 164 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 607872 KB, 3374 KB/s, 180 seconds passed
-... 87%, 607904 KB, 3374 KB/s, 180 seconds passed
-... 87%, 607936 KB, 3374 KB/s, 180 seconds passed
+    ... 87%, 605952 KB, 3676 KB/s, 164 seconds passed
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+... 87%, 606016 KB, 3676 KB/s, 164 seconds passed
+... 87%, 606048 KB, 3676 KB/s, 164 seconds passed
+... 87%, 606080 KB, 3676 KB/s, 164 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 607968 KB, 3373 KB/s, 180 seconds passed
-... 87%, 608000 KB, 3374 KB/s, 180 seconds passed
-... 87%, 608032 KB, 3374 KB/s, 180 seconds passed
-... 87%, 608064 KB, 3374 KB/s, 180 seconds passed
-... 87%, 608096 KB, 3374 KB/s, 180 seconds passed
-... 87%, 608128 KB, 3374 KB/s, 180 seconds passed
-... 87%, 608160 KB, 3374 KB/s, 180 seconds passed
-... 87%, 608192 KB, 3374 KB/s, 180 seconds passed
+    ... 87%, 606112 KB, 3676 KB/s, 164 seconds passed
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+... 87%, 606208 KB, 3676 KB/s, 164 seconds passed
+... 87%, 606240 KB, 3675 KB/s, 164 seconds passed
+... 87%, 606272 KB, 3676 KB/s, 164 seconds passed
+... 87%, 606304 KB, 3676 KB/s, 164 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 608224 KB, 3374 KB/s, 180 seconds passed
-... 87%, 608256 KB, 3374 KB/s, 180 seconds passed
-... 87%, 608288 KB, 3374 KB/s, 180 seconds passed
-... 87%, 608320 KB, 3374 KB/s, 180 seconds passed
+    ... 87%, 606336 KB, 3676 KB/s, 164 seconds passed
+... 87%, 606368 KB, 3675 KB/s, 164 seconds passed
+... 87%, 606400 KB, 3676 KB/s, 164 seconds passed
+... 87%, 606432 KB, 3676 KB/s, 164 seconds passed
+... 87%, 606464 KB, 3676 KB/s, 164 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 608352 KB, 3374 KB/s, 180 seconds passed
-... 87%, 608384 KB, 3374 KB/s, 180 seconds passed
-... 87%, 608416 KB, 3374 KB/s, 180 seconds passed
-... 87%, 608448 KB, 3374 KB/s, 180 seconds passed
-... 87%, 608480 KB, 3374 KB/s, 180 seconds passed
-... 87%, 608512 KB, 3374 KB/s, 180 seconds passed
-... 87%, 608544 KB, 3374 KB/s, 180 seconds passed
-... 87%, 608576 KB, 3374 KB/s, 180 seconds passed
+    ... 87%, 606496 KB, 3675 KB/s, 164 seconds passed
+... 87%, 606528 KB, 3676 KB/s, 164 seconds passed
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+... 87%, 606592 KB, 3676 KB/s, 165 seconds passed
+... 87%, 606624 KB, 3675 KB/s, 165 seconds passed
+... 87%, 606656 KB, 3676 KB/s, 165 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 608608 KB, 3374 KB/s, 180 seconds passed
-... 87%, 608640 KB, 3374 KB/s, 180 seconds passed
-... 87%, 608672 KB, 3374 KB/s, 180 seconds passed
-... 87%, 608704 KB, 3374 KB/s, 180 seconds passed
+    ... 87%, 606688 KB, 3676 KB/s, 165 seconds passed
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+... 87%, 606752 KB, 3675 KB/s, 165 seconds passed
+... 87%, 606784 KB, 3676 KB/s, 165 seconds passed
+... 87%, 606816 KB, 3676 KB/s, 165 seconds passed
+... 87%, 606848 KB, 3676 KB/s, 165 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 608736 KB, 3374 KB/s, 180 seconds passed
-... 87%, 608768 KB, 3374 KB/s, 180 seconds passed
-... 87%, 608800 KB, 3374 KB/s, 180 seconds passed
-... 87%, 608832 KB, 3374 KB/s, 180 seconds passed
-... 87%, 608864 KB, 3374 KB/s, 180 seconds passed
-... 87%, 608896 KB, 3374 KB/s, 180 seconds passed
-... 87%, 608928 KB, 3374 KB/s, 180 seconds passed
-... 87%, 608960 KB, 3374 KB/s, 180 seconds passed
+    ... 87%, 606880 KB, 3676 KB/s, 165 seconds passed
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+... 87%, 606976 KB, 3676 KB/s, 165 seconds passed
+... 87%, 607008 KB, 3676 KB/s, 165 seconds passed
+... 87%, 607040 KB, 3676 KB/s, 165 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 608992 KB, 3374 KB/s, 180 seconds passed
-... 87%, 609024 KB, 3374 KB/s, 180 seconds passed
-... 87%, 609056 KB, 3374 KB/s, 180 seconds passed
-... 87%, 609088 KB, 3374 KB/s, 180 seconds passed
+    ... 87%, 607072 KB, 3676 KB/s, 165 seconds passed
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+... 87%, 607136 KB, 3675 KB/s, 165 seconds passed
+... 87%, 607168 KB, 3676 KB/s, 165 seconds passed
+... 87%, 607200 KB, 3676 KB/s, 165 seconds passed
+... 87%, 607232 KB, 3675 KB/s, 165 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 609120 KB, 3374 KB/s, 180 seconds passed
-... 87%, 609152 KB, 3374 KB/s, 180 seconds passed
-... 87%, 609184 KB, 3374 KB/s, 180 seconds passed
-... 87%, 609216 KB, 3374 KB/s, 180 seconds passed
-... 87%, 609248 KB, 3374 KB/s, 180 seconds passed
-... 87%, 609280 KB, 3374 KB/s, 180 seconds passed
-... 87%, 609312 KB, 3374 KB/s, 180 seconds passed
+    ... 87%, 607264 KB, 3676 KB/s, 165 seconds passed
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+... 87%, 607328 KB, 3676 KB/s, 165 seconds passed
+... 87%, 607360 KB, 3676 KB/s, 165 seconds passed
+... 87%, 607392 KB, 3676 KB/s, 165 seconds passed
+... 87%, 607424 KB, 3676 KB/s, 165 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 609344 KB, 3374 KB/s, 180 seconds passed
-... 87%, 609376 KB, 3374 KB/s, 180 seconds passed
-... 87%, 609408 KB, 3374 KB/s, 180 seconds passed
-... 87%, 609440 KB, 3374 KB/s, 180 seconds passed
-... 87%, 609472 KB, 3374 KB/s, 180 seconds passed
+    ... 87%, 607456 KB, 3676 KB/s, 165 seconds passed
+... 87%, 607488 KB, 3676 KB/s, 165 seconds passed
+... 87%, 607520 KB, 3676 KB/s, 165 seconds passed
+... 87%, 607552 KB, 3676 KB/s, 165 seconds passed
+... 87%, 607584 KB, 3676 KB/s, 165 seconds passed
+... 87%, 607616 KB, 3676 KB/s, 165 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 609504 KB, 3374 KB/s, 180 seconds passed
-... 87%, 609536 KB, 3374 KB/s, 180 seconds passed
-... 87%, 609568 KB, 3374 KB/s, 180 seconds passed
-... 87%, 609600 KB, 3375 KB/s, 180 seconds passed
-... 87%, 609632 KB, 3374 KB/s, 180 seconds passed
-... 87%, 609664 KB, 3374 KB/s, 180 seconds passed
-... 87%, 609696 KB, 3374 KB/s, 180 seconds passed
+    ... 87%, 607648 KB, 3676 KB/s, 165 seconds passed
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+... 87%, 607712 KB, 3676 KB/s, 165 seconds passed
+... 87%, 607744 KB, 3676 KB/s, 165 seconds passed
+... 87%, 607776 KB, 3676 KB/s, 165 seconds passed
+... 87%, 607808 KB, 3676 KB/s, 165 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 609728 KB, 3375 KB/s, 180 seconds passed
-... 87%, 609760 KB, 3374 KB/s, 180 seconds passed
-... 87%, 609792 KB, 3374 KB/s, 180 seconds passed
-... 87%, 609824 KB, 3375 KB/s, 180 seconds passed
-... 87%, 609856 KB, 3375 KB/s, 180 seconds passed
+    ... 87%, 607840 KB, 3676 KB/s, 165 seconds passed
+... 87%, 607872 KB, 3676 KB/s, 165 seconds passed
+... 87%, 607904 KB, 3676 KB/s, 165 seconds passed
+... 87%, 607936 KB, 3676 KB/s, 165 seconds passed
+... 87%, 607968 KB, 3676 KB/s, 165 seconds passed
+... 87%, 608000 KB, 3676 KB/s, 165 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 609888 KB, 3374 KB/s, 180 seconds passed
-... 87%, 609920 KB, 3374 KB/s, 180 seconds passed
-... 87%, 609952 KB, 3375 KB/s, 180 seconds passed
-... 87%, 609984 KB, 3375 KB/s, 180 seconds passed
-... 87%, 610016 KB, 3374 KB/s, 180 seconds passed
-... 87%, 610048 KB, 3375 KB/s, 180 seconds passed
-... 87%, 610080 KB, 3375 KB/s, 180 seconds passed
+    ... 87%, 608032 KB, 3676 KB/s, 165 seconds passed
+... 87%, 608064 KB, 3676 KB/s, 165 seconds passed
+... 87%, 608096 KB, 3676 KB/s, 165 seconds passed
+... 87%, 608128 KB, 3676 KB/s, 165 seconds passed
+... 87%, 608160 KB, 3676 KB/s, 165 seconds passed
+... 87%, 608192 KB, 3676 KB/s, 165 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 610112 KB, 3375 KB/s, 180 seconds passed
-... 87%, 610144 KB, 3375 KB/s, 180 seconds passed
-... 87%, 610176 KB, 3375 KB/s, 180 seconds passed
-... 87%, 610208 KB, 3375 KB/s, 180 seconds passed
-... 87%, 610240 KB, 3375 KB/s, 180 seconds passed
+    ... 87%, 608224 KB, 3676 KB/s, 165 seconds passed
+... 87%, 608256 KB, 3676 KB/s, 165 seconds passed
+... 87%, 608288 KB, 3676 KB/s, 165 seconds passed
+... 87%, 608320 KB, 3676 KB/s, 165 seconds passed
+... 87%, 608352 KB, 3676 KB/s, 165 seconds passed
+... 87%, 608384 KB, 3676 KB/s, 165 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 610272 KB, 3375 KB/s, 180 seconds passed
-... 87%, 610304 KB, 3375 KB/s, 180 seconds passed
-... 87%, 610336 KB, 3375 KB/s, 180 seconds passed
-... 87%, 610368 KB, 3375 KB/s, 180 seconds passed
-... 87%, 610400 KB, 3375 KB/s, 180 seconds passed
-... 87%, 610432 KB, 3375 KB/s, 180 seconds passed
-... 87%, 610464 KB, 3375 KB/s, 180 seconds passed
+    ... 87%, 608416 KB, 3676 KB/s, 165 seconds passed
+... 87%, 608448 KB, 3676 KB/s, 165 seconds passed
+... 87%, 608480 KB, 3676 KB/s, 165 seconds passed
+... 87%, 608512 KB, 3676 KB/s, 165 seconds passed
+... 87%, 608544 KB, 3676 KB/s, 165 seconds passed
+... 87%, 608576 KB, 3676 KB/s, 165 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 610496 KB, 3375 KB/s, 180 seconds passed
-... 87%, 610528 KB, 3375 KB/s, 180 seconds passed
-... 87%, 610560 KB, 3375 KB/s, 180 seconds passed
-... 87%, 610592 KB, 3375 KB/s, 180 seconds passed
-... 87%, 610624 KB, 3375 KB/s, 180 seconds passed
+    ... 87%, 608608 KB, 3676 KB/s, 165 seconds passed
+... 87%, 608640 KB, 3676 KB/s, 165 seconds passed
+... 87%, 608672 KB, 3676 KB/s, 165 seconds passed
+... 87%, 608704 KB, 3676 KB/s, 165 seconds passed
+... 87%, 608736 KB, 3676 KB/s, 165 seconds passed
+... 87%, 608768 KB, 3676 KB/s, 165 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 610656 KB, 3375 KB/s, 180 seconds passed
-... 87%, 610688 KB, 3375 KB/s, 180 seconds passed
-... 87%, 610720 KB, 3375 KB/s, 180 seconds passed
-... 87%, 610752 KB, 3375 KB/s, 180 seconds passed
-... 87%, 610784 KB, 3375 KB/s, 180 seconds passed
-... 87%, 610816 KB, 3375 KB/s, 180 seconds passed
+    ... 87%, 608800 KB, 3676 KB/s, 165 seconds passed
+... 87%, 608832 KB, 3676 KB/s, 165 seconds passed
+... 87%, 608864 KB, 3676 KB/s, 165 seconds passed
+... 87%, 608896 KB, 3676 KB/s, 165 seconds passed
+... 87%, 608928 KB, 3676 KB/s, 165 seconds passed
+... 87%, 608960 KB, 3676 KB/s, 165 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 610848 KB, 3375 KB/s, 180 seconds passed
-... 87%, 610880 KB, 3375 KB/s, 180 seconds passed
-... 87%, 610912 KB, 3375 KB/s, 180 seconds passed
-... 87%, 610944 KB, 3375 KB/s, 180 seconds passed
-... 87%, 610976 KB, 3375 KB/s, 180 seconds passed
-... 87%, 611008 KB, 3375 KB/s, 181 seconds passed
+    ... 87%, 608992 KB, 3676 KB/s, 165 seconds passed
+... 87%, 609024 KB, 3676 KB/s, 165 seconds passed
+... 87%, 609056 KB, 3676 KB/s, 165 seconds passed
+... 87%, 609088 KB, 3676 KB/s, 165 seconds passed
+... 87%, 609120 KB, 3676 KB/s, 165 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 611040 KB, 3375 KB/s, 181 seconds passed
-... 87%, 611072 KB, 3375 KB/s, 181 seconds passed
-... 87%, 611104 KB, 3375 KB/s, 181 seconds passed
-... 87%, 611136 KB, 3375 KB/s, 181 seconds passed
-... 87%, 611168 KB, 3375 KB/s, 181 seconds passed
-... 87%, 611200 KB, 3375 KB/s, 181 seconds passed
+    ... 87%, 609152 KB, 3676 KB/s, 165 seconds passed
+... 87%, 609184 KB, 3676 KB/s, 165 seconds passed
+... 87%, 609216 KB, 3676 KB/s, 165 seconds passed
+... 87%, 609248 KB, 3676 KB/s, 165 seconds passed
+... 87%, 609280 KB, 3676 KB/s, 165 seconds passed
+... 87%, 609312 KB, 3676 KB/s, 165 seconds passed
+... 87%, 609344 KB, 3676 KB/s, 165 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 611232 KB, 3375 KB/s, 181 seconds passed
-... 87%, 611264 KB, 3375 KB/s, 181 seconds passed
-... 87%, 611296 KB, 3375 KB/s, 181 seconds passed
-... 87%, 611328 KB, 3375 KB/s, 181 seconds passed
-... 87%, 611360 KB, 3375 KB/s, 181 seconds passed
-... 87%, 611392 KB, 3375 KB/s, 181 seconds passed
+    ... 87%, 609376 KB, 3676 KB/s, 165 seconds passed
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+... 87%, 609440 KB, 3676 KB/s, 165 seconds passed
+... 87%, 609472 KB, 3676 KB/s, 165 seconds passed
+... 87%, 609504 KB, 3676 KB/s, 165 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 611424 KB, 3375 KB/s, 181 seconds passed
-... 87%, 611456 KB, 3375 KB/s, 181 seconds passed
-... 87%, 611488 KB, 3375 KB/s, 181 seconds passed
-... 87%, 611520 KB, 3375 KB/s, 181 seconds passed
-... 87%, 611552 KB, 3375 KB/s, 181 seconds passed
+    ... 87%, 609536 KB, 3676 KB/s, 165 seconds passed
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+... 87%, 609600 KB, 3676 KB/s, 165 seconds passed
+... 87%, 609632 KB, 3676 KB/s, 165 seconds passed
+... 87%, 609664 KB, 3676 KB/s, 165 seconds passed
+... 87%, 609696 KB, 3676 KB/s, 165 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 611584 KB, 3375 KB/s, 181 seconds passed
-... 87%, 611616 KB, 3375 KB/s, 181 seconds passed
-... 87%, 611648 KB, 3376 KB/s, 181 seconds passed
-... 87%, 611680 KB, 3375 KB/s, 181 seconds passed
-... 87%, 611712 KB, 3375 KB/s, 181 seconds passed
-... 87%, 611744 KB, 3375 KB/s, 181 seconds passed
-... 87%, 611776 KB, 3376 KB/s, 181 seconds passed
+    ... 87%, 609728 KB, 3676 KB/s, 165 seconds passed
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+... 87%, 609824 KB, 3676 KB/s, 165 seconds passed
+... 87%, 609856 KB, 3676 KB/s, 165 seconds passed
+... 87%, 609888 KB, 3676 KB/s, 165 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 611808 KB, 3375 KB/s, 181 seconds passed
-... 87%, 611840 KB, 3375 KB/s, 181 seconds passed
-... 87%, 611872 KB, 3376 KB/s, 181 seconds passed
-... 87%, 611904 KB, 3376 KB/s, 181 seconds passed
-... 87%, 611936 KB, 3375 KB/s, 181 seconds passed
+    ... 87%, 609920 KB, 3676 KB/s, 165 seconds passed
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+... 87%, 610016 KB, 3676 KB/s, 165 seconds passed
+... 87%, 610048 KB, 3676 KB/s, 165 seconds passed
+... 87%, 610080 KB, 3676 KB/s, 165 seconds passed
 
 .. parsed-literal::
 
-    ... 87%, 611968 KB, 3375 KB/s, 181 seconds passed
-... 87%, 612000 KB, 3376 KB/s, 181 seconds passed
-... 87%, 612032 KB, 3376 KB/s, 181 seconds passed
-... 88%, 612064 KB, 3375 KB/s, 181 seconds passed
-... 88%, 612096 KB, 3376 KB/s, 181 seconds passed
-... 88%, 612128 KB, 3376 KB/s, 181 seconds passed
-... 88%, 612160 KB, 3376 KB/s, 181 seconds passed
+    ... 87%, 610112 KB, 3676 KB/s, 165 seconds passed
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+... 87%, 610208 KB, 3676 KB/s, 165 seconds passed
+... 87%, 610240 KB, 3676 KB/s, 165 seconds passed
+... 87%, 610272 KB, 3676 KB/s, 166 seconds passed
 
 .. parsed-literal::
 
-    ... 88%, 612192 KB, 3375 KB/s, 181 seconds passed
-... 88%, 612224 KB, 3376 KB/s, 181 seconds passed
-... 88%, 612256 KB, 3376 KB/s, 181 seconds passed
-... 88%, 612288 KB, 3376 KB/s, 181 seconds passed
-... 88%, 612320 KB, 3376 KB/s, 181 seconds passed
+    ... 87%, 610304 KB, 3676 KB/s, 166 seconds passed
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+... 87%, 610400 KB, 3676 KB/s, 166 seconds passed
+... 87%, 610432 KB, 3676 KB/s, 166 seconds passed
+... 87%, 610464 KB, 3676 KB/s, 166 seconds passed
 
 .. parsed-literal::
 
-    ... 88%, 612352 KB, 3376 KB/s, 181 seconds passed
-... 88%, 612384 KB, 3376 KB/s, 181 seconds passed
-... 88%, 612416 KB, 3376 KB/s, 181 seconds passed
-... 88%, 612448 KB, 3376 KB/s, 181 seconds passed
-... 88%, 612480 KB, 3376 KB/s, 181 seconds passed
-... 88%, 612512 KB, 3376 KB/s, 181 seconds passed
-... 88%, 612544 KB, 3376 KB/s, 181 seconds passed
+    ... 87%, 610496 KB, 3676 KB/s, 166 seconds passed
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+... 87%, 610592 KB, 3676 KB/s, 166 seconds passed
+... 87%, 610624 KB, 3676 KB/s, 166 seconds passed
+... 87%, 610656 KB, 3676 KB/s, 166 seconds passed
 
 .. parsed-literal::
 
-    ... 88%, 612576 KB, 3376 KB/s, 181 seconds passed
-... 88%, 612608 KB, 3376 KB/s, 181 seconds passed
-... 88%, 612640 KB, 3376 KB/s, 181 seconds passed
-... 88%, 612672 KB, 3376 KB/s, 181 seconds passed
-... 88%, 612704 KB, 3376 KB/s, 181 seconds passed
+    ... 87%, 610688 KB, 3676 KB/s, 166 seconds passed
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+... 87%, 610752 KB, 3676 KB/s, 166 seconds passed
+... 87%, 610784 KB, 3676 KB/s, 166 seconds passed
+... 87%, 610816 KB, 3676 KB/s, 166 seconds passed
 
 .. parsed-literal::
 
-    ... 88%, 612736 KB, 3376 KB/s, 181 seconds passed
-... 88%, 612768 KB, 3376 KB/s, 181 seconds passed
-... 88%, 612800 KB, 3376 KB/s, 181 seconds passed
-... 88%, 612832 KB, 3376 KB/s, 181 seconds passed
-... 88%, 612864 KB, 3376 KB/s, 181 seconds passed
-... 88%, 612896 KB, 3376 KB/s, 181 seconds passed
+    ... 87%, 610848 KB, 3676 KB/s, 166 seconds passed
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+... 87%, 610976 KB, 3676 KB/s, 166 seconds passed
+... 87%, 611008 KB, 3676 KB/s, 166 seconds passed
+... 87%, 611040 KB, 3676 KB/s, 166 seconds passed
 
 .. parsed-literal::
 
-    ... 88%, 612928 KB, 3376 KB/s, 181 seconds passed
-... 88%, 612960 KB, 3376 KB/s, 181 seconds passed
-... 88%, 612992 KB, 3376 KB/s, 181 seconds passed
-... 88%, 613024 KB, 3376 KB/s, 181 seconds passed
-... 88%, 613056 KB, 3376 KB/s, 181 seconds passed
+    ... 87%, 611072 KB, 3676 KB/s, 166 seconds passed
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+... 87%, 611136 KB, 3676 KB/s, 166 seconds passed
+... 87%, 611168 KB, 3676 KB/s, 166 seconds passed
+... 87%, 611200 KB, 3676 KB/s, 166 seconds passed
 
 .. parsed-literal::
 
-    ... 88%, 613088 KB, 3376 KB/s, 181 seconds passed
-... 88%, 613120 KB, 3376 KB/s, 181 seconds passed
-... 88%, 613152 KB, 3376 KB/s, 181 seconds passed
-... 88%, 613184 KB, 3376 KB/s, 181 seconds passed
-... 88%, 613216 KB, 3376 KB/s, 181 seconds passed
-... 88%, 613248 KB, 3376 KB/s, 181 seconds passed
-... 88%, 613280 KB, 3376 KB/s, 181 seconds passed
+    ... 87%, 611232 KB, 3676 KB/s, 166 seconds passed
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+... 87%, 611328 KB, 3676 KB/s, 166 seconds passed
+... 87%, 611360 KB, 3676 KB/s, 166 seconds passed
+... 87%, 611392 KB, 3676 KB/s, 166 seconds passed
+... 87%, 611424 KB, 3676 KB/s, 166 seconds passed
 
 .. parsed-literal::
 
-    ... 88%, 613312 KB, 3376 KB/s, 181 seconds passed
-... 88%, 613344 KB, 3376 KB/s, 181 seconds passed
-... 88%, 613376 KB, 3376 KB/s, 181 seconds passed
-... 88%, 613408 KB, 3376 KB/s, 181 seconds passed
-... 88%, 613440 KB, 3376 KB/s, 181 seconds passed
+    ... 87%, 611456 KB, 3676 KB/s, 166 seconds passed
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+... 87%, 611520 KB, 3676 KB/s, 166 seconds passed
+... 87%, 611552 KB, 3676 KB/s, 166 seconds passed
+... 87%, 611584 KB, 3676 KB/s, 166 seconds passed
 
 .. parsed-literal::
 
-    ... 88%, 613472 KB, 3376 KB/s, 181 seconds passed
-... 88%, 613504 KB, 3376 KB/s, 181 seconds passed
-... 88%, 613536 KB, 3376 KB/s, 181 seconds passed
-... 88%, 613568 KB, 3376 KB/s, 181 seconds passed
-... 88%, 613600 KB, 3376 KB/s, 181 seconds passed
-... 88%, 613632 KB, 3376 KB/s, 181 seconds passed
-... 88%, 613664 KB, 3376 KB/s, 181 seconds passed
+    ... 87%, 611616 KB, 3676 KB/s, 166 seconds passed
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+... 87%, 611744 KB, 3676 KB/s, 166 seconds passed
+... 87%, 611776 KB, 3676 KB/s, 166 seconds passed
+... 87%, 611808 KB, 3676 KB/s, 166 seconds passed
 
 .. parsed-literal::
 
-    ... 88%, 613696 KB, 3376 KB/s, 181 seconds passed
-... 88%, 613728 KB, 3376 KB/s, 181 seconds passed
-... 88%, 613760 KB, 3376 KB/s, 181 seconds passed
-... 88%, 613792 KB, 3376 KB/s, 181 seconds passed
-... 88%, 613824 KB, 3376 KB/s, 181 seconds passed
+    ... 87%, 611840 KB, 3676 KB/s, 166 seconds passed
+... 87%, 611872 KB, 3676 KB/s, 166 seconds passed
+... 87%, 611904 KB, 3676 KB/s, 166 seconds passed
+... 87%, 611936 KB, 3676 KB/s, 166 seconds passed
 
 .. parsed-literal::
 
-    ... 88%, 613856 KB, 3376 KB/s, 181 seconds passed
-... 88%, 613888 KB, 3376 KB/s, 181 seconds passed
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-... 88%, 613952 KB, 3376 KB/s, 181 seconds passed
-... 88%, 613984 KB, 3376 KB/s, 181 seconds passed
-... 88%, 614016 KB, 3376 KB/s, 181 seconds passed
-... 88%, 614048 KB, 3377 KB/s, 181 seconds passed
+    ... 87%, 611968 KB, 3676 KB/s, 166 seconds passed
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+... 88%, 612128 KB, 3676 KB/s, 166 seconds passed
+... 88%, 612160 KB, 3676 KB/s, 166 seconds passed
+... 88%, 612192 KB, 3676 KB/s, 166 seconds passed
 
 .. parsed-literal::
 
-    ... 88%, 614080 KB, 3376 KB/s, 181 seconds passed
-... 88%, 614112 KB, 3376 KB/s, 181 seconds passed
-... 88%, 614144 KB, 3376 KB/s, 181 seconds passed
-... 88%, 614176 KB, 3377 KB/s, 181 seconds passed
-... 88%, 614208 KB, 3376 KB/s, 181 seconds passed
+    ... 88%, 612224 KB, 3676 KB/s, 166 seconds passed
+... 88%, 612256 KB, 3676 KB/s, 166 seconds passed
+... 88%, 612288 KB, 3676 KB/s, 166 seconds passed
+... 88%, 612320 KB, 3676 KB/s, 166 seconds passed
 
 .. parsed-literal::
 
-    ... 88%, 614240 KB, 3376 KB/s, 181 seconds passed
-... 88%, 614272 KB, 3377 KB/s, 181 seconds passed
-... 88%, 614304 KB, 3377 KB/s, 181 seconds passed
-... 88%, 614336 KB, 3376 KB/s, 181 seconds passed
-... 88%, 614368 KB, 3377 KB/s, 181 seconds passed
-... 88%, 614400 KB, 3377 KB/s, 181 seconds passed
-... 88%, 614432 KB, 3377 KB/s, 181 seconds passed
+    ... 88%, 612352 KB, 3676 KB/s, 166 seconds passed
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+... 88%, 612544 KB, 3676 KB/s, 166 seconds passed
+... 88%, 612576 KB, 3676 KB/s, 166 seconds passed
 
 .. parsed-literal::
 
-    ... 88%, 614464 KB, 3377 KB/s, 181 seconds passed
-... 88%, 614496 KB, 3377 KB/s, 181 seconds passed
-... 88%, 614528 KB, 3377 KB/s, 181 seconds passed
-... 88%, 614560 KB, 3377 KB/s, 181 seconds passed
+    ... 88%, 612608 KB, 3676 KB/s, 166 seconds passed
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+... 88%, 612672 KB, 3676 KB/s, 166 seconds passed
+... 88%, 612704 KB, 3676 KB/s, 166 seconds passed
 
 .. parsed-literal::
 
-    ... 88%, 614592 KB, 3377 KB/s, 181 seconds passed
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-... 88%, 614752 KB, 3377 KB/s, 182 seconds passed
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-... 88%, 614816 KB, 3377 KB/s, 182 seconds passed
+    ... 88%, 612736 KB, 3676 KB/s, 166 seconds passed
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+... 88%, 612896 KB, 3676 KB/s, 166 seconds passed
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 .. parsed-literal::
 
-    ... 88%, 614848 KB, 3377 KB/s, 182 seconds passed
-... 88%, 614880 KB, 3377 KB/s, 182 seconds passed
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+    ... 88%, 612960 KB, 3676 KB/s, 166 seconds passed
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+... 88%, 613056 KB, 3676 KB/s, 166 seconds passed
+... 88%, 613088 KB, 3676 KB/s, 166 seconds passed
 
 .. parsed-literal::
 
-    ... 88%, 614976 KB, 3377 KB/s, 182 seconds passed
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-... 88%, 615072 KB, 3377 KB/s, 182 seconds passed
-... 88%, 615104 KB, 3377 KB/s, 182 seconds passed
-... 88%, 615136 KB, 3377 KB/s, 182 seconds passed
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-... 88%, 615200 KB, 3377 KB/s, 182 seconds passed
+    ... 88%, 613120 KB, 3676 KB/s, 166 seconds passed
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+... 88%, 613248 KB, 3676 KB/s, 166 seconds passed
+... 88%, 613280 KB, 3676 KB/s, 166 seconds passed
+... 88%, 613312 KB, 3676 KB/s, 166 seconds passed
 
 .. parsed-literal::
 
-    ... 88%, 615232 KB, 3377 KB/s, 182 seconds passed
-... 88%, 615264 KB, 3377 KB/s, 182 seconds passed
-... 88%, 615296 KB, 3377 KB/s, 182 seconds passed
-... 88%, 615328 KB, 3377 KB/s, 182 seconds passed
+    ... 88%, 613344 KB, 3676 KB/s, 166 seconds passed
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+... 88%, 613408 KB, 3676 KB/s, 166 seconds passed
+... 88%, 613440 KB, 3676 KB/s, 166 seconds passed
+... 88%, 613472 KB, 3676 KB/s, 166 seconds passed
 
 .. parsed-literal::
 
-    ... 88%, 615360 KB, 3377 KB/s, 182 seconds passed
-... 88%, 615392 KB, 3377 KB/s, 182 seconds passed
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-... 88%, 615456 KB, 3377 KB/s, 182 seconds passed
-... 88%, 615488 KB, 3377 KB/s, 182 seconds passed
-... 88%, 615520 KB, 3377 KB/s, 182 seconds passed
-... 88%, 615552 KB, 3377 KB/s, 182 seconds passed
+    ... 88%, 613504 KB, 3676 KB/s, 166 seconds passed
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+... 88%, 613600 KB, 3676 KB/s, 166 seconds passed
+... 88%, 613632 KB, 3676 KB/s, 166 seconds passed
+... 88%, 613664 KB, 3676 KB/s, 166 seconds passed
 
 .. parsed-literal::
 
-    ... 88%, 615584 KB, 3377 KB/s, 182 seconds passed
-... 88%, 615616 KB, 3377 KB/s, 182 seconds passed
-... 88%, 615648 KB, 3377 KB/s, 182 seconds passed
-... 88%, 615680 KB, 3377 KB/s, 182 seconds passed
-... 88%, 615712 KB, 3377 KB/s, 182 seconds passed
+    ... 88%, 613696 KB, 3676 KB/s, 166 seconds passed
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+... 88%, 613792 KB, 3676 KB/s, 166 seconds passed
+... 88%, 613824 KB, 3676 KB/s, 166 seconds passed
+... 88%, 613856 KB, 3676 KB/s, 166 seconds passed
 
 .. parsed-literal::
 
-    ... 88%, 615744 KB, 3377 KB/s, 182 seconds passed
-... 88%, 615776 KB, 3377 KB/s, 182 seconds passed
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-... 88%, 615840 KB, 3377 KB/s, 182 seconds passed
-... 88%, 615872 KB, 3377 KB/s, 182 seconds passed
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-... 88%, 615936 KB, 3377 KB/s, 182 seconds passed
+    ... 88%, 613888 KB, 3676 KB/s, 166 seconds passed
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+... 88%, 613984 KB, 3676 KB/s, 167 seconds passed
+... 88%, 614016 KB, 3676 KB/s, 167 seconds passed
+... 88%, 614048 KB, 3676 KB/s, 167 seconds passed
 
 .. parsed-literal::
 
-    ... 88%, 615968 KB, 3377 KB/s, 182 seconds passed
-... 88%, 616000 KB, 3377 KB/s, 182 seconds passed
-... 88%, 616032 KB, 3377 KB/s, 182 seconds passed
-... 88%, 616064 KB, 3377 KB/s, 182 seconds passed
-... 88%, 616096 KB, 3378 KB/s, 182 seconds passed
+    ... 88%, 614080 KB, 3676 KB/s, 167 seconds passed
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+... 88%, 614176 KB, 3676 KB/s, 167 seconds passed
+... 88%, 614208 KB, 3676 KB/s, 167 seconds passed
+... 88%, 614240 KB, 3676 KB/s, 167 seconds passed
 
 .. parsed-literal::
 
-    ... 88%, 616128 KB, 3377 KB/s, 182 seconds passed
-... 88%, 616160 KB, 3377 KB/s, 182 seconds passed
-... 88%, 616192 KB, 3377 KB/s, 182 seconds passed
-... 88%, 616224 KB, 3378 KB/s, 182 seconds passed
-... 88%, 616256 KB, 3377 KB/s, 182 seconds passed
-... 88%, 616288 KB, 3377 KB/s, 182 seconds passed
+    ... 88%, 614272 KB, 3676 KB/s, 167 seconds passed
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+... 88%, 614368 KB, 3676 KB/s, 167 seconds passed
+... 88%, 614400 KB, 3676 KB/s, 167 seconds passed
+... 88%, 614432 KB, 3676 KB/s, 167 seconds passed
 
 .. parsed-literal::
 
-    ... 88%, 616320 KB, 3378 KB/s, 182 seconds passed
-... 88%, 616352 KB, 3378 KB/s, 182 seconds passed
-... 88%, 616384 KB, 3377 KB/s, 182 seconds passed
-... 88%, 616416 KB, 3378 KB/s, 182 seconds passed
-... 88%, 616448 KB, 3378 KB/s, 182 seconds passed
-... 88%, 616480 KB, 3378 KB/s, 182 seconds passed
+    ... 88%, 614464 KB, 3676 KB/s, 167 seconds passed
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+... 88%, 614560 KB, 3676 KB/s, 167 seconds passed
+... 88%, 614592 KB, 3676 KB/s, 167 seconds passed
+... 88%, 614624 KB, 3676 KB/s, 167 seconds passed
 
 .. parsed-literal::
 
-    ... 88%, 616512 KB, 3378 KB/s, 182 seconds passed
-... 88%, 616544 KB, 3378 KB/s, 182 seconds passed
-... 88%, 616576 KB, 3378 KB/s, 182 seconds passed
-... 88%, 616608 KB, 3378 KB/s, 182 seconds passed
-... 88%, 616640 KB, 3378 KB/s, 182 seconds passed
-... 88%, 616672 KB, 3378 KB/s, 182 seconds passed
+    ... 88%, 614656 KB, 3676 KB/s, 167 seconds passed
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+... 88%, 614752 KB, 3676 KB/s, 167 seconds passed
+... 88%, 614784 KB, 3676 KB/s, 167 seconds passed
+... 88%, 614816 KB, 3676 KB/s, 167 seconds passed
 
 .. parsed-literal::
 
-    ... 88%, 616704 KB, 3378 KB/s, 182 seconds passed
-... 88%, 616736 KB, 3378 KB/s, 182 seconds passed
-... 88%, 616768 KB, 3378 KB/s, 182 seconds passed
-... 88%, 616800 KB, 3378 KB/s, 182 seconds passed
-... 88%, 616832 KB, 3378 KB/s, 182 seconds passed
-... 88%, 616864 KB, 3378 KB/s, 182 seconds passed
+    ... 88%, 614848 KB, 3676 KB/s, 167 seconds passed
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+... 88%, 614912 KB, 3676 KB/s, 167 seconds passed
+... 88%, 614944 KB, 3676 KB/s, 167 seconds passed
+... 88%, 614976 KB, 3676 KB/s, 167 seconds passed
 
 .. parsed-literal::
 
-    ... 88%, 616896 KB, 3378 KB/s, 182 seconds passed
-... 88%, 616928 KB, 3378 KB/s, 182 seconds passed
-... 88%, 616960 KB, 3378 KB/s, 182 seconds passed
-... 88%, 616992 KB, 3378 KB/s, 182 seconds passed
-... 88%, 617024 KB, 3378 KB/s, 182 seconds passed
-... 88%, 617056 KB, 3378 KB/s, 182 seconds passed
+    ... 88%, 615008 KB, 3676 KB/s, 167 seconds passed
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+... 88%, 615072 KB, 3676 KB/s, 167 seconds passed
+... 88%, 615104 KB, 3676 KB/s, 167 seconds passed
+... 88%, 615136 KB, 3676 KB/s, 167 seconds passed
+... 88%, 615168 KB, 3676 KB/s, 167 seconds passed
+... 88%, 615200 KB, 3676 KB/s, 167 seconds passed
 
 .. parsed-literal::
 
-    ... 88%, 617088 KB, 3378 KB/s, 182 seconds passed
-... 88%, 617120 KB, 3378 KB/s, 182 seconds passed
-... 88%, 617152 KB, 3378 KB/s, 182 seconds passed
-... 88%, 617184 KB, 3378 KB/s, 182 seconds passed
-... 88%, 617216 KB, 3378 KB/s, 182 seconds passed
-... 88%, 617248 KB, 3378 KB/s, 182 seconds passed
+    ... 88%, 615232 KB, 3676 KB/s, 167 seconds passed
+... 88%, 615264 KB, 3676 KB/s, 167 seconds passed
+... 88%, 615296 KB, 3676 KB/s, 167 seconds passed
+... 88%, 615328 KB, 3676 KB/s, 167 seconds passed
+... 88%, 615360 KB, 3676 KB/s, 167 seconds passed
 
 .. parsed-literal::
 
-    ... 88%, 617280 KB, 3378 KB/s, 182 seconds passed
-... 88%, 617312 KB, 3378 KB/s, 182 seconds passed
-... 88%, 617344 KB, 3378 KB/s, 182 seconds passed
-... 88%, 617376 KB, 3378 KB/s, 182 seconds passed
-... 88%, 617408 KB, 3378 KB/s, 182 seconds passed
-... 88%, 617440 KB, 3378 KB/s, 182 seconds passed
+    ... 88%, 615392 KB, 3676 KB/s, 167 seconds passed
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+... 88%, 615456 KB, 3676 KB/s, 167 seconds passed
+... 88%, 615488 KB, 3676 KB/s, 167 seconds passed
+... 88%, 615520 KB, 3676 KB/s, 167 seconds passed
+... 88%, 615552 KB, 3676 KB/s, 167 seconds passed
+... 88%, 615584 KB, 3676 KB/s, 167 seconds passed
 
 .. parsed-literal::
 
-    ... 88%, 617472 KB, 3378 KB/s, 182 seconds passed
-... 88%, 617504 KB, 3378 KB/s, 182 seconds passed
-... 88%, 617536 KB, 3378 KB/s, 182 seconds passed
-... 88%, 617568 KB, 3378 KB/s, 182 seconds passed
-... 88%, 617600 KB, 3378 KB/s, 182 seconds passed
-... 88%, 617632 KB, 3378 KB/s, 182 seconds passed
+    ... 88%, 615616 KB, 3676 KB/s, 167 seconds passed
+... 88%, 615648 KB, 3676 KB/s, 167 seconds passed
+... 88%, 615680 KB, 3676 KB/s, 167 seconds passed
+... 88%, 615712 KB, 3676 KB/s, 167 seconds passed
+... 88%, 615744 KB, 3676 KB/s, 167 seconds passed
 
 .. parsed-literal::
 
-    ... 88%, 617664 KB, 3378 KB/s, 182 seconds passed
-... 88%, 617696 KB, 3378 KB/s, 182 seconds passed
-... 88%, 617728 KB, 3378 KB/s, 182 seconds passed
-... 88%, 617760 KB, 3378 KB/s, 182 seconds passed
-... 88%, 617792 KB, 3378 KB/s, 182 seconds passed
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+... 88%, 615936 KB, 3676 KB/s, 167 seconds passed
+... 88%, 615968 KB, 3676 KB/s, 167 seconds passed
 
 .. parsed-literal::
 
-    ... 88%, 617856 KB, 3378 KB/s, 182 seconds passed
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-... 88%, 617920 KB, 3378 KB/s, 182 seconds passed
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-... 88%, 617984 KB, 3378 KB/s, 182 seconds passed
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+... 88%, 616128 KB, 3676 KB/s, 167 seconds passed
 
 .. parsed-literal::
 
-    ... 88%, 618016 KB, 3378 KB/s, 182 seconds passed
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+... 88%, 616320 KB, 3676 KB/s, 167 seconds passed
 
 .. parsed-literal::
 
-    ... 88%, 618208 KB, 3378 KB/s, 182 seconds passed
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+... 88%, 616480 KB, 3676 KB/s, 167 seconds passed
 
 .. parsed-literal::
 
-    ... 88%, 618400 KB, 3378 KB/s, 183 seconds passed
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 .. parsed-literal::
 
-    ... 88%, 618592 KB, 3379 KB/s, 183 seconds passed
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 .. parsed-literal::
 
-    ... 88%, 618784 KB, 3379 KB/s, 183 seconds passed
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+... 88%, 617088 KB, 3676 KB/s, 167 seconds passed
 
 .. parsed-literal::
 
-    ... 88%, 618976 KB, 3379 KB/s, 183 seconds passed
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+... 88%, 617280 KB, 3676 KB/s, 167 seconds passed
 
 .. parsed-literal::
 
-    ... 89%, 619168 KB, 3379 KB/s, 183 seconds passed
-... 89%, 619200 KB, 3379 KB/s, 183 seconds passed
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-... 89%, 619296 KB, 3379 KB/s, 183 seconds passed
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+    ... 88%, 617312 KB, 3676 KB/s, 167 seconds passed
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+... 88%, 617472 KB, 3676 KB/s, 167 seconds passed
 
 .. parsed-literal::
 
-    ... 89%, 619360 KB, 3379 KB/s, 183 seconds passed
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-... 89%, 619520 KB, 3379 KB/s, 183 seconds passed
+    ... 88%, 617504 KB, 3676 KB/s, 167 seconds passed
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+... 88%, 617600 KB, 3676 KB/s, 167 seconds passed
+... 88%, 617632 KB, 3676 KB/s, 168 seconds passed
 
 .. parsed-literal::
 
-    ... 89%, 619552 KB, 3379 KB/s, 183 seconds passed
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+    ... 88%, 617664 KB, 3676 KB/s, 168 seconds passed
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+... 88%, 617792 KB, 3676 KB/s, 168 seconds passed
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 .. parsed-literal::
 
-    ... 89%, 619744 KB, 3379 KB/s, 183 seconds passed
-... 89%, 619776 KB, 3379 KB/s, 183 seconds passed
-... 89%, 619808 KB, 3379 KB/s, 183 seconds passed
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-... 89%, 619872 KB, 3379 KB/s, 183 seconds passed
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+... 88%, 618016 KB, 3676 KB/s, 168 seconds passed
 
 .. parsed-literal::
 
-    ... 89%, 619936 KB, 3379 KB/s, 183 seconds passed
-... 89%, 619968 KB, 3379 KB/s, 183 seconds passed
-... 89%, 620000 KB, 3379 KB/s, 183 seconds passed
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+    ... 88%, 618048 KB, 3676 KB/s, 168 seconds passed
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 .. parsed-literal::
 
-    ... 89%, 620096 KB, 3379 KB/s, 183 seconds passed
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-... 89%, 620224 KB, 3379 KB/s, 183 seconds passed
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-... 89%, 620288 KB, 3379 KB/s, 183 seconds passed
+    ... 88%, 618240 KB, 3676 KB/s, 168 seconds passed
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 .. parsed-literal::
 
-    ... 89%, 620320 KB, 3379 KB/s, 183 seconds passed
-... 89%, 620352 KB, 3379 KB/s, 183 seconds passed
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+    ... 88%, 618432 KB, 3676 KB/s, 168 seconds passed
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 .. parsed-literal::
 
-    ... 89%, 620480 KB, 3379 KB/s, 183 seconds passed
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 .. parsed-literal::
 
-    ... 89%, 620704 KB, 3379 KB/s, 183 seconds passed
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+    ... 88%, 618816 KB, 3676 KB/s, 168 seconds passed
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 .. parsed-literal::
 
-    ... 89%, 620864 KB, 3380 KB/s, 183 seconds passed
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+    ... 89%, 619008 KB, 3676 KB/s, 168 seconds passed
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 .. parsed-literal::
 
-    ... 89%, 621088 KB, 3380 KB/s, 183 seconds passed
-... 89%, 621120 KB, 3380 KB/s, 183 seconds passed
-... 89%, 621152 KB, 3380 KB/s, 183 seconds passed
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+    ... 89%, 619200 KB, 3676 KB/s, 168 seconds passed
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 .. parsed-literal::
 
-    ... 89%, 621248 KB, 3380 KB/s, 183 seconds passed
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-... 89%, 621408 KB, 3380 KB/s, 183 seconds passed
+    ... 89%, 619360 KB, 3676 KB/s, 168 seconds passed
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 .. parsed-literal::
 
-    ... 89%, 621440 KB, 3380 KB/s, 183 seconds passed
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-... 89%, 621504 KB, 3380 KB/s, 183 seconds passed
-... 89%, 621536 KB, 3380 KB/s, 183 seconds passed
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+    ... 89%, 619584 KB, 3676 KB/s, 168 seconds passed
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 .. parsed-literal::
 
-    ... 89%, 621600 KB, 3380 KB/s, 183 seconds passed
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-... 89%, 621792 KB, 3380 KB/s, 183 seconds passed
+    ... 89%, 619744 KB, 3676 KB/s, 168 seconds passed
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 .. parsed-literal::
 
-    ... 89%, 621824 KB, 3380 KB/s, 183 seconds passed
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-... 89%, 621920 KB, 3380 KB/s, 183 seconds passed
-... 89%, 621952 KB, 3380 KB/s, 183 seconds passed
+    ... 89%, 619968 KB, 3676 KB/s, 168 seconds passed
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 .. parsed-literal::
 
-    ... 89%, 621984 KB, 3380 KB/s, 183 seconds passed
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-... 89%, 622112 KB, 3380 KB/s, 184 seconds passed
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+    ... 89%, 620128 KB, 3676 KB/s, 168 seconds passed
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 .. parsed-literal::
 
-    ... 89%, 622208 KB, 3380 KB/s, 184 seconds passed
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-... 89%, 622272 KB, 3380 KB/s, 184 seconds passed
-... 89%, 622304 KB, 3380 KB/s, 184 seconds passed
-... 89%, 622336 KB, 3380 KB/s, 184 seconds passed
+    ... 89%, 620352 KB, 3676 KB/s, 168 seconds passed
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 .. parsed-literal::
 
-    ... 89%, 622368 KB, 3380 KB/s, 184 seconds passed
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-... 89%, 622528 KB, 3380 KB/s, 184 seconds passed
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+    ... 89%, 620480 KB, 3676 KB/s, 168 seconds passed
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 .. parsed-literal::
 
-    ... 89%, 622592 KB, 3380 KB/s, 184 seconds passed
-... 89%, 622624 KB, 3380 KB/s, 184 seconds passed
+    ... 89%, 620704 KB, 3676 KB/s, 168 seconds passed
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 .. parsed-literal::
 
-    ... 89%, 622656 KB, 3380 KB/s, 184 seconds passed
-... 89%, 622688 KB, 3380 KB/s, 184 seconds passed
-... 89%, 622720 KB, 3380 KB/s, 184 seconds passed
-... 89%, 622752 KB, 3380 KB/s, 184 seconds passed
+    ... 89%, 620864 KB, 3676 KB/s, 168 seconds passed
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+... 89%, 620992 KB, 3676 KB/s, 168 seconds passed
+... 89%, 621024 KB, 3676 KB/s, 168 seconds passed
+... 89%, 621056 KB, 3676 KB/s, 168 seconds passed
 
 .. parsed-literal::
 
-    ... 89%, 622784 KB, 3379 KB/s, 184 seconds passed
+    ... 89%, 621088 KB, 3676 KB/s, 168 seconds passed
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+... 89%, 621152 KB, 3676 KB/s, 168 seconds passed
+... 89%, 621184 KB, 3676 KB/s, 168 seconds passed
+... 89%, 621216 KB, 3676 KB/s, 168 seconds passed
 
 .. parsed-literal::
 
-    ... 89%, 622816 KB, 3379 KB/s, 184 seconds passed
-... 89%, 622848 KB, 3378 KB/s, 184 seconds passed
-... 89%, 622880 KB, 3378 KB/s, 184 seconds passed
+    ... 89%, 621248 KB, 3676 KB/s, 168 seconds passed
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+... 89%, 621376 KB, 3676 KB/s, 169 seconds passed
+... 89%, 621408 KB, 3676 KB/s, 169 seconds passed
+... 89%, 621440 KB, 3676 KB/s, 169 seconds passed
 
 .. parsed-literal::
 
-    ... 89%, 622912 KB, 3378 KB/s, 184 seconds passed
+    ... 89%, 621472 KB, 3676 KB/s, 169 seconds passed
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+... 89%, 621600 KB, 3676 KB/s, 169 seconds passed
 
 .. parsed-literal::
 
-    ... 89%, 622944 KB, 3378 KB/s, 184 seconds passed
-... 89%, 622976 KB, 3378 KB/s, 184 seconds passed
-... 89%, 623008 KB, 3377 KB/s, 184 seconds passed
-... 89%, 623040 KB, 3377 KB/s, 184 seconds passed
+    ... 89%, 621632 KB, 3676 KB/s, 169 seconds passed
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+... 89%, 621792 KB, 3676 KB/s, 169 seconds passed
+... 89%, 621824 KB, 3676 KB/s, 169 seconds passed
 
 .. parsed-literal::
 
-    ... 89%, 623072 KB, 3377 KB/s, 184 seconds passed
-... 89%, 623104 KB, 3377 KB/s, 184 seconds passed
+    ... 89%, 621856 KB, 3676 KB/s, 169 seconds passed
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+... 89%, 621920 KB, 3676 KB/s, 169 seconds passed
+... 89%, 621952 KB, 3676 KB/s, 169 seconds passed
+... 89%, 621984 KB, 3676 KB/s, 169 seconds passed
 
 .. parsed-literal::
 
-    ... 89%, 623136 KB, 3377 KB/s, 184 seconds passed
-... 89%, 623168 KB, 3377 KB/s, 184 seconds passed
-... 89%, 623200 KB, 3377 KB/s, 184 seconds passed
-... 89%, 623232 KB, 3377 KB/s, 184 seconds passed
-... 89%, 623264 KB, 3377 KB/s, 184 seconds passed
+    ... 89%, 622016 KB, 3676 KB/s, 169 seconds passed
+... 89%, 622048 KB, 3676 KB/s, 169 seconds passed
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+... 89%, 622112 KB, 3676 KB/s, 169 seconds passed
+... 89%, 622144 KB, 3676 KB/s, 169 seconds passed
+... 89%, 622176 KB, 3676 KB/s, 169 seconds passed
+... 89%, 622208 KB, 3676 KB/s, 169 seconds passed
 
 .. parsed-literal::
 
-    ... 89%, 623296 KB, 3377 KB/s, 184 seconds passed
-... 89%, 623328 KB, 3376 KB/s, 184 seconds passed
-... 89%, 623360 KB, 3377 KB/s, 184 seconds passed
-... 89%, 623392 KB, 3377 KB/s, 184 seconds passed
+    ... 89%, 622240 KB, 3676 KB/s, 169 seconds passed
+... 89%, 622272 KB, 3676 KB/s, 169 seconds passed
+... 89%, 622304 KB, 3676 KB/s, 169 seconds passed
+... 89%, 622336 KB, 3676 KB/s, 169 seconds passed
 
 .. parsed-literal::
 
-    ... 89%, 623424 KB, 3376 KB/s, 184 seconds passed
-... 89%, 623456 KB, 3376 KB/s, 184 seconds passed
-... 89%, 623488 KB, 3377 KB/s, 184 seconds passed
-... 89%, 623520 KB, 3377 KB/s, 184 seconds passed
-... 89%, 623552 KB, 3376 KB/s, 184 seconds passed
-... 89%, 623584 KB, 3377 KB/s, 184 seconds passed
+    ... 89%, 622368 KB, 3676 KB/s, 169 seconds passed
+... 89%, 622400 KB, 3676 KB/s, 169 seconds passed
+... 89%, 622432 KB, 3676 KB/s, 169 seconds passed
+... 89%, 622464 KB, 3676 KB/s, 169 seconds passed
+... 89%, 622496 KB, 3676 KB/s, 169 seconds passed
+... 89%, 622528 KB, 3676 KB/s, 169 seconds passed
+... 89%, 622560 KB, 3676 KB/s, 169 seconds passed
 
 .. parsed-literal::
 
-    ... 89%, 623616 KB, 3377 KB/s, 184 seconds passed
-... 89%, 623648 KB, 3376 KB/s, 184 seconds passed
-... 89%, 623680 KB, 3376 KB/s, 184 seconds passed
-... 89%, 623712 KB, 3377 KB/s, 184 seconds passed
-... 89%, 623744 KB, 3377 KB/s, 184 seconds passed
+    ... 89%, 622592 KB, 3676 KB/s, 169 seconds passed
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+... 89%, 622688 KB, 3676 KB/s, 169 seconds passed
+... 89%, 622720 KB, 3676 KB/s, 169 seconds passed
 
 .. parsed-literal::
 
-    ... 89%, 623776 KB, 3376 KB/s, 184 seconds passed
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-... 89%, 623872 KB, 3377 KB/s, 184 seconds passed
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-... 89%, 623936 KB, 3377 KB/s, 184 seconds passed
+    ... 89%, 622752 KB, 3676 KB/s, 169 seconds passed
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+... 89%, 622880 KB, 3676 KB/s, 169 seconds passed
+... 89%, 622912 KB, 3676 KB/s, 169 seconds passed
+... 89%, 622944 KB, 3676 KB/s, 169 seconds passed
 
 .. parsed-literal::
 
-    ... 89%, 623968 KB, 3377 KB/s, 184 seconds passed
-... 89%, 624000 KB, 3377 KB/s, 184 seconds passed
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-... 89%, 624096 KB, 3377 KB/s, 184 seconds passed
-... 89%, 624128 KB, 3377 KB/s, 184 seconds passed
+    ... 89%, 622976 KB, 3676 KB/s, 169 seconds passed
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+... 89%, 623072 KB, 3676 KB/s, 169 seconds passed
+... 89%, 623104 KB, 3676 KB/s, 169 seconds passed
 
 .. parsed-literal::
 
-    ... 89%, 624160 KB, 3377 KB/s, 184 seconds passed
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-... 89%, 624256 KB, 3377 KB/s, 184 seconds passed
-... 89%, 624288 KB, 3377 KB/s, 184 seconds passed
+    ... 89%, 623136 KB, 3676 KB/s, 169 seconds passed
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+... 89%, 623296 KB, 3676 KB/s, 169 seconds passed
+... 89%, 623328 KB, 3676 KB/s, 169 seconds passed
 
 .. parsed-literal::
 
-    ... 89%, 624320 KB, 3377 KB/s, 184 seconds passed
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-... 89%, 624448 KB, 3377 KB/s, 184 seconds passed
+    ... 89%, 623360 KB, 3676 KB/s, 169 seconds passed
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+... 89%, 623456 KB, 3676 KB/s, 169 seconds passed
+... 89%, 623488 KB, 3676 KB/s, 169 seconds passed
 
 .. parsed-literal::
 
-    ... 89%, 624480 KB, 3376 KB/s, 184 seconds passed
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-... 89%, 624544 KB, 3377 KB/s, 184 seconds passed
-... 89%, 624576 KB, 3377 KB/s, 184 seconds passed
-... 89%, 624608 KB, 3376 KB/s, 184 seconds passed
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+... 89%, 623680 KB, 3676 KB/s, 169 seconds passed
+... 89%, 623712 KB, 3676 KB/s, 169 seconds passed
 
 .. parsed-literal::
 
-    ... 89%, 624640 KB, 3377 KB/s, 184 seconds passed
-... 89%, 624672 KB, 3377 KB/s, 184 seconds passed
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-... 89%, 624768 KB, 3377 KB/s, 184 seconds passed
-... 89%, 624800 KB, 3377 KB/s, 185 seconds passed
-... 89%, 624832 KB, 3377 KB/s, 185 seconds passed
+    ... 89%, 623744 KB, 3676 KB/s, 169 seconds passed
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+... 89%, 623840 KB, 3676 KB/s, 169 seconds passed
+... 89%, 623872 KB, 3676 KB/s, 169 seconds passed
+... 89%, 623904 KB, 3676 KB/s, 169 seconds passed
 
 .. parsed-literal::
 
-    ... 89%, 624864 KB, 3377 KB/s, 185 seconds passed
-... 89%, 624896 KB, 3377 KB/s, 185 seconds passed
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-... 89%, 624960 KB, 3377 KB/s, 185 seconds passed
+    ... 89%, 623936 KB, 3676 KB/s, 169 seconds passed
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+... 89%, 624064 KB, 3676 KB/s, 169 seconds passed
+... 89%, 624096 KB, 3676 KB/s, 169 seconds passed
 
 .. parsed-literal::
 
-    ... 89%, 624992 KB, 3377 KB/s, 185 seconds passed
-... 89%, 625024 KB, 3377 KB/s, 185 seconds passed
-... 89%, 625056 KB, 3377 KB/s, 185 seconds passed
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-... 89%, 625152 KB, 3377 KB/s, 185 seconds passed
-... 89%, 625184 KB, 3377 KB/s, 185 seconds passed
-... 89%, 625216 KB, 3377 KB/s, 185 seconds passed
+    ... 89%, 624128 KB, 3676 KB/s, 169 seconds passed
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+... 89%, 624192 KB, 3676 KB/s, 169 seconds passed
+... 89%, 624224 KB, 3676 KB/s, 169 seconds passed
+... 89%, 624256 KB, 3676 KB/s, 169 seconds passed
 
 .. parsed-literal::
 
-    ... 89%, 625248 KB, 3377 KB/s, 185 seconds passed
-... 89%, 625280 KB, 3377 KB/s, 185 seconds passed
-... 89%, 625312 KB, 3377 KB/s, 185 seconds passed
-... 89%, 625344 KB, 3377 KB/s, 185 seconds passed
+    ... 89%, 624288 KB, 3676 KB/s, 169 seconds passed
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+... 89%, 624416 KB, 3676 KB/s, 169 seconds passed
+... 89%, 624448 KB, 3676 KB/s, 169 seconds passed
+... 89%, 624480 KB, 3676 KB/s, 169 seconds passed
 
 .. parsed-literal::
 
-    ... 89%, 625376 KB, 3377 KB/s, 185 seconds passed
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-... 89%, 625440 KB, 3377 KB/s, 185 seconds passed
-... 89%, 625472 KB, 3377 KB/s, 185 seconds passed
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-... 89%, 625536 KB, 3377 KB/s, 185 seconds passed
-... 89%, 625568 KB, 3377 KB/s, 185 seconds passed
-... 89%, 625600 KB, 3377 KB/s, 185 seconds passed
+    ... 89%, 624512 KB, 3676 KB/s, 169 seconds passed
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+... 89%, 624576 KB, 3676 KB/s, 169 seconds passed
+... 89%, 624608 KB, 3676 KB/s, 169 seconds passed
+... 89%, 624640 KB, 3676 KB/s, 169 seconds passed
 
 .. parsed-literal::
 
-    ... 89%, 625632 KB, 3377 KB/s, 185 seconds passed
-... 89%, 625664 KB, 3377 KB/s, 185 seconds passed
-... 89%, 625696 KB, 3377 KB/s, 185 seconds passed
-... 89%, 625728 KB, 3377 KB/s, 185 seconds passed
+    ... 89%, 624672 KB, 3676 KB/s, 169 seconds passed
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+... 89%, 624800 KB, 3676 KB/s, 169 seconds passed
+... 89%, 624832 KB, 3676 KB/s, 169 seconds passed
+... 89%, 624864 KB, 3676 KB/s, 169 seconds passed
 
 .. parsed-literal::
 
-    ... 89%, 625760 KB, 3377 KB/s, 185 seconds passed
-... 89%, 625792 KB, 3377 KB/s, 185 seconds passed
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-... 89%, 625856 KB, 3377 KB/s, 185 seconds passed
-... 89%, 625888 KB, 3377 KB/s, 185 seconds passed
-... 89%, 625920 KB, 3377 KB/s, 185 seconds passed
-... 89%, 625952 KB, 3377 KB/s, 185 seconds passed
-... 90%, 625984 KB, 3377 KB/s, 185 seconds passed
+    ... 89%, 624896 KB, 3676 KB/s, 169 seconds passed
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+... 89%, 624960 KB, 3676 KB/s, 169 seconds passed
+... 89%, 624992 KB, 3676 KB/s, 169 seconds passed
+... 89%, 625024 KB, 3676 KB/s, 170 seconds passed
 
 .. parsed-literal::
 
-    ... 90%, 626016 KB, 3377 KB/s, 185 seconds passed
-... 90%, 626048 KB, 3377 KB/s, 185 seconds passed
-... 90%, 626080 KB, 3377 KB/s, 185 seconds passed
-... 90%, 626112 KB, 3377 KB/s, 185 seconds passed
+    ... 89%, 625056 KB, 3676 KB/s, 170 seconds passed
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+... 89%, 625184 KB, 3676 KB/s, 170 seconds passed
+... 89%, 625216 KB, 3676 KB/s, 170 seconds passed
+... 89%, 625248 KB, 3676 KB/s, 170 seconds passed
 
 .. parsed-literal::
 
-    ... 90%, 626144 KB, 3377 KB/s, 185 seconds passed
-... 90%, 626176 KB, 3377 KB/s, 185 seconds passed
-... 90%, 626208 KB, 3377 KB/s, 185 seconds passed
-... 90%, 626240 KB, 3377 KB/s, 185 seconds passed
-... 90%, 626272 KB, 3377 KB/s, 185 seconds passed
-... 90%, 626304 KB, 3377 KB/s, 185 seconds passed
-... 90%, 626336 KB, 3377 KB/s, 185 seconds passed
+    ... 89%, 625280 KB, 3676 KB/s, 170 seconds passed
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+... 89%, 625344 KB, 3676 KB/s, 170 seconds passed
+... 89%, 625376 KB, 3676 KB/s, 170 seconds passed
+... 89%, 625408 KB, 3676 KB/s, 170 seconds passed
 
 .. parsed-literal::
 
-    ... 90%, 626368 KB, 3377 KB/s, 185 seconds passed
-... 90%, 626400 KB, 3377 KB/s, 185 seconds passed
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-... 90%, 626464 KB, 3377 KB/s, 185 seconds passed
+    ... 89%, 625440 KB, 3676 KB/s, 170 seconds passed
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+... 89%, 625536 KB, 3676 KB/s, 170 seconds passed
+... 89%, 625568 KB, 3676 KB/s, 170 seconds passed
+... 89%, 625600 KB, 3676 KB/s, 170 seconds passed
 
 .. parsed-literal::
 
-    ... 90%, 626496 KB, 3377 KB/s, 185 seconds passed
-... 90%, 626528 KB, 3377 KB/s, 185 seconds passed
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-... 90%, 626656 KB, 3377 KB/s, 185 seconds passed
-... 90%, 626688 KB, 3378 KB/s, 185 seconds passed
-... 90%, 626720 KB, 3378 KB/s, 185 seconds passed
+    ... 89%, 625632 KB, 3676 KB/s, 170 seconds passed
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+... 89%, 625696 KB, 3676 KB/s, 170 seconds passed
+... 89%, 625728 KB, 3676 KB/s, 170 seconds passed
+... 89%, 625760 KB, 3676 KB/s, 170 seconds passed
 
 .. parsed-literal::
 
-    ... 90%, 626752 KB, 3377 KB/s, 185 seconds passed
-... 90%, 626784 KB, 3377 KB/s, 185 seconds passed
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+    ... 89%, 625792 KB, 3676 KB/s, 170 seconds passed
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+... 89%, 625920 KB, 3676 KB/s, 170 seconds passed
+... 89%, 625952 KB, 3676 KB/s, 170 seconds passed
+... 90%, 625984 KB, 3676 KB/s, 170 seconds passed
 
 .. parsed-literal::
 
-    ... 90%, 626880 KB, 3377 KB/s, 185 seconds passed
-... 90%, 626912 KB, 3378 KB/s, 185 seconds passed
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-... 90%, 627040 KB, 3378 KB/s, 185 seconds passed
-... 90%, 627072 KB, 3378 KB/s, 185 seconds passed
-... 90%, 627104 KB, 3378 KB/s, 185 seconds passed
+    ... 90%, 626016 KB, 3676 KB/s, 170 seconds passed
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+... 90%, 626080 KB, 3676 KB/s, 170 seconds passed
+... 90%, 626112 KB, 3676 KB/s, 170 seconds passed
+... 90%, 626144 KB, 3676 KB/s, 170 seconds passed
 
 .. parsed-literal::
 
-    ... 90%, 627136 KB, 3378 KB/s, 185 seconds passed
-... 90%, 627168 KB, 3378 KB/s, 185 seconds passed
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-... 90%, 627232 KB, 3378 KB/s, 185 seconds passed
+    ... 90%, 626176 KB, 3676 KB/s, 170 seconds passed
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+... 90%, 626304 KB, 3676 KB/s, 170 seconds passed
+... 90%, 626336 KB, 3676 KB/s, 170 seconds passed
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 .. parsed-literal::
 
-    ... 90%, 627264 KB, 3378 KB/s, 185 seconds passed
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-... 90%, 627360 KB, 3378 KB/s, 185 seconds passed
-... 90%, 627392 KB, 3378 KB/s, 185 seconds passed
-... 90%, 627424 KB, 3378 KB/s, 185 seconds passed
-... 90%, 627456 KB, 3378 KB/s, 185 seconds passed
+    ... 90%, 626400 KB, 3676 KB/s, 170 seconds passed
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+... 90%, 626496 KB, 3676 KB/s, 170 seconds passed
+... 90%, 626528 KB, 3676 KB/s, 170 seconds passed
 
 .. parsed-literal::
 
-    ... 90%, 627488 KB, 3378 KB/s, 185 seconds passed
-... 90%, 627520 KB, 3378 KB/s, 185 seconds passed
-... 90%, 627552 KB, 3378 KB/s, 185 seconds passed
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-... 90%, 627616 KB, 3378 KB/s, 185 seconds passed
+    ... 90%, 626560 KB, 3676 KB/s, 170 seconds passed
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+... 90%, 626656 KB, 3676 KB/s, 170 seconds passed
+... 90%, 626688 KB, 3676 KB/s, 170 seconds passed
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 .. parsed-literal::
 
-    ... 90%, 627648 KB, 3378 KB/s, 185 seconds passed
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-... 90%, 627712 KB, 3378 KB/s, 185 seconds passed
-... 90%, 627744 KB, 3378 KB/s, 185 seconds passed
-... 90%, 627776 KB, 3378 KB/s, 185 seconds passed
-... 90%, 627808 KB, 3378 KB/s, 185 seconds passed
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+    ... 90%, 626752 KB, 3676 KB/s, 170 seconds passed
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+... 90%, 626880 KB, 3676 KB/s, 170 seconds passed
+... 90%, 626912 KB, 3676 KB/s, 170 seconds passed
 
 .. parsed-literal::
 
-    ... 90%, 627872 KB, 3378 KB/s, 185 seconds passed
-... 90%, 627904 KB, 3378 KB/s, 185 seconds passed
-... 90%, 627936 KB, 3378 KB/s, 185 seconds passed
-... 90%, 627968 KB, 3378 KB/s, 185 seconds passed
-... 90%, 628000 KB, 3378 KB/s, 185 seconds passed
+    ... 90%, 626944 KB, 3676 KB/s, 170 seconds passed
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+... 90%, 627040 KB, 3676 KB/s, 170 seconds passed
+... 90%, 627072 KB, 3676 KB/s, 170 seconds passed
+... 90%, 627104 KB, 3676 KB/s, 170 seconds passed
 
 .. parsed-literal::
 
-    ... 90%, 628032 KB, 3378 KB/s, 185 seconds passed
-... 90%, 628064 KB, 3378 KB/s, 185 seconds passed
-... 90%, 628096 KB, 3378 KB/s, 185 seconds passed
-... 90%, 628128 KB, 3378 KB/s, 185 seconds passed
-... 90%, 628160 KB, 3378 KB/s, 185 seconds passed
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-... 90%, 628224 KB, 3378 KB/s, 185 seconds passed
+    ... 90%, 627136 KB, 3676 KB/s, 170 seconds passed
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+... 90%, 627232 KB, 3676 KB/s, 170 seconds passed
+... 90%, 627264 KB, 3676 KB/s, 170 seconds passed
+... 90%, 627296 KB, 3676 KB/s, 170 seconds passed
 
 .. parsed-literal::
 
-    ... 90%, 628256 KB, 3378 KB/s, 185 seconds passed
-... 90%, 628288 KB, 3378 KB/s, 185 seconds passed
-... 90%, 628320 KB, 3378 KB/s, 185 seconds passed
-... 90%, 628352 KB, 3378 KB/s, 185 seconds passed
-... 90%, 628384 KB, 3378 KB/s, 185 seconds passed
+    ... 90%, 627328 KB, 3676 KB/s, 170 seconds passed
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+... 90%, 627392 KB, 3676 KB/s, 170 seconds passed
+... 90%, 627424 KB, 3676 KB/s, 170 seconds passed
+... 90%, 627456 KB, 3676 KB/s, 170 seconds passed
 
 .. parsed-literal::
 
-    ... 90%, 628416 KB, 3378 KB/s, 185 seconds passed
-... 90%, 628448 KB, 3378 KB/s, 186 seconds passed
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-... 90%, 628512 KB, 3378 KB/s, 186 seconds passed
-... 90%, 628544 KB, 3378 KB/s, 186 seconds passed
-... 90%, 628576 KB, 3378 KB/s, 186 seconds passed
-... 90%, 628608 KB, 3378 KB/s, 186 seconds passed
+    ... 90%, 627488 KB, 3676 KB/s, 170 seconds passed
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+... 90%, 627648 KB, 3676 KB/s, 170 seconds passed
+... 90%, 627680 KB, 3676 KB/s, 170 seconds passed
 
 .. parsed-literal::
 
-    ... 90%, 628640 KB, 3378 KB/s, 186 seconds passed
-... 90%, 628672 KB, 3378 KB/s, 186 seconds passed
-... 90%, 628704 KB, 3378 KB/s, 186 seconds passed
-... 90%, 628736 KB, 3378 KB/s, 186 seconds passed
-... 90%, 628768 KB, 3379 KB/s, 186 seconds passed
+    ... 90%, 627712 KB, 3676 KB/s, 170 seconds passed
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+... 90%, 627776 KB, 3676 KB/s, 170 seconds passed
+... 90%, 627808 KB, 3676 KB/s, 170 seconds passed
+... 90%, 627840 KB, 3676 KB/s, 170 seconds passed
 
 .. parsed-literal::
 
-    ... 90%, 628800 KB, 3378 KB/s, 186 seconds passed
-... 90%, 628832 KB, 3378 KB/s, 186 seconds passed
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-... 90%, 628896 KB, 3379 KB/s, 186 seconds passed
-... 90%, 628928 KB, 3378 KB/s, 186 seconds passed
-... 90%, 628960 KB, 3378 KB/s, 186 seconds passed
-... 90%, 628992 KB, 3379 KB/s, 186 seconds passed
+    ... 90%, 627872 KB, 3676 KB/s, 170 seconds passed
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+... 90%, 628000 KB, 3676 KB/s, 170 seconds passed
+... 90%, 628032 KB, 3676 KB/s, 170 seconds passed
+... 90%, 628064 KB, 3676 KB/s, 170 seconds passed
 
 .. parsed-literal::
 
-    ... 90%, 629024 KB, 3379 KB/s, 186 seconds passed
-... 90%, 629056 KB, 3378 KB/s, 186 seconds passed
-... 90%, 629088 KB, 3379 KB/s, 186 seconds passed
-... 90%, 629120 KB, 3379 KB/s, 186 seconds passed
-... 90%, 629152 KB, 3379 KB/s, 186 seconds passed
+    ... 90%, 628096 KB, 3676 KB/s, 170 seconds passed
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+... 90%, 628160 KB, 3676 KB/s, 170 seconds passed
+... 90%, 628192 KB, 3676 KB/s, 170 seconds passed
+... 90%, 628224 KB, 3676 KB/s, 170 seconds passed
 
 .. parsed-literal::
 
-    ... 90%, 629184 KB, 3378 KB/s, 186 seconds passed
-... 90%, 629216 KB, 3379 KB/s, 186 seconds passed
-... 90%, 629248 KB, 3379 KB/s, 186 seconds passed
-... 90%, 629280 KB, 3379 KB/s, 186 seconds passed
-... 90%, 629312 KB, 3379 KB/s, 186 seconds passed
-... 90%, 629344 KB, 3379 KB/s, 186 seconds passed
+    ... 90%, 628256 KB, 3676 KB/s, 170 seconds passed
+... 90%, 628288 KB, 3676 KB/s, 170 seconds passed
+... 90%, 628320 KB, 3676 KB/s, 170 seconds passed
+... 90%, 628352 KB, 3676 KB/s, 170 seconds passed
+... 90%, 628384 KB, 3676 KB/s, 170 seconds passed
+... 90%, 628416 KB, 3676 KB/s, 170 seconds passed
+... 90%, 628448 KB, 3676 KB/s, 170 seconds passed
 
 .. parsed-literal::
 
-    ... 90%, 629376 KB, 3379 KB/s, 186 seconds passed
-... 90%, 629408 KB, 3379 KB/s, 186 seconds passed
-... 90%, 629440 KB, 3379 KB/s, 186 seconds passed
-... 90%, 629472 KB, 3379 KB/s, 186 seconds passed
-... 90%, 629504 KB, 3379 KB/s, 186 seconds passed
-... 90%, 629536 KB, 3379 KB/s, 186 seconds passed
+    ... 90%, 628480 KB, 3676 KB/s, 170 seconds passed
+... 90%, 628512 KB, 3676 KB/s, 170 seconds passed
+... 90%, 628544 KB, 3676 KB/s, 170 seconds passed
+... 90%, 628576 KB, 3676 KB/s, 170 seconds passed
+... 90%, 628608 KB, 3676 KB/s, 170 seconds passed
 
 .. parsed-literal::
 
-    ... 90%, 629568 KB, 3379 KB/s, 186 seconds passed
-... 90%, 629600 KB, 3379 KB/s, 186 seconds passed
-... 90%, 629632 KB, 3379 KB/s, 186 seconds passed
-... 90%, 629664 KB, 3379 KB/s, 186 seconds passed
-... 90%, 629696 KB, 3379 KB/s, 186 seconds passed
-... 90%, 629728 KB, 3379 KB/s, 186 seconds passed
+    ... 90%, 628640 KB, 3676 KB/s, 170 seconds passed
+... 90%, 628672 KB, 3676 KB/s, 170 seconds passed
+... 90%, 628704 KB, 3676 KB/s, 170 seconds passed
+... 90%, 628736 KB, 3676 KB/s, 171 seconds passed
+... 90%, 628768 KB, 3676 KB/s, 171 seconds passed
+... 90%, 628800 KB, 3676 KB/s, 171 seconds passed
+... 90%, 628832 KB, 3676 KB/s, 171 seconds passed
 
 .. parsed-literal::
 
-    ... 90%, 629760 KB, 3379 KB/s, 186 seconds passed
-... 90%, 629792 KB, 3379 KB/s, 186 seconds passed
-... 90%, 629824 KB, 3379 KB/s, 186 seconds passed
-... 90%, 629856 KB, 3379 KB/s, 186 seconds passed
-... 90%, 629888 KB, 3379 KB/s, 186 seconds passed
-... 90%, 629920 KB, 3379 KB/s, 186 seconds passed
+    ... 90%, 628864 KB, 3676 KB/s, 171 seconds passed
+... 90%, 628896 KB, 3676 KB/s, 171 seconds passed
+... 90%, 628928 KB, 3676 KB/s, 171 seconds passed
+... 90%, 628960 KB, 3676 KB/s, 171 seconds passed
 
 .. parsed-literal::
 
-    ... 90%, 629952 KB, 3379 KB/s, 186 seconds passed
-... 90%, 629984 KB, 3379 KB/s, 186 seconds passed
-... 90%, 630016 KB, 3379 KB/s, 186 seconds passed
-... 90%, 630048 KB, 3379 KB/s, 186 seconds passed
-... 90%, 630080 KB, 3379 KB/s, 186 seconds passed
+    ... 90%, 628992 KB, 3676 KB/s, 171 seconds passed
+... 90%, 629024 KB, 3676 KB/s, 171 seconds passed
+... 90%, 629056 KB, 3676 KB/s, 171 seconds passed
+... 90%, 629088 KB, 3676 KB/s, 171 seconds passed
+... 90%, 629120 KB, 3676 KB/s, 171 seconds passed
+... 90%, 629152 KB, 3676 KB/s, 171 seconds passed
+... 90%, 629184 KB, 3676 KB/s, 171 seconds passed
+... 90%, 629216 KB, 3676 KB/s, 171 seconds passed
 
 .. parsed-literal::
 
-    ... 90%, 630112 KB, 3379 KB/s, 186 seconds passed
-... 90%, 630144 KB, 3379 KB/s, 186 seconds passed
-... 90%, 630176 KB, 3379 KB/s, 186 seconds passed
-... 90%, 630208 KB, 3379 KB/s, 186 seconds passed
-... 90%, 630240 KB, 3379 KB/s, 186 seconds passed
-... 90%, 630272 KB, 3379 KB/s, 186 seconds passed
-... 90%, 630304 KB, 3379 KB/s, 186 seconds passed
+    ... 90%, 629248 KB, 3676 KB/s, 171 seconds passed
+... 90%, 629280 KB, 3676 KB/s, 171 seconds passed
+... 90%, 629312 KB, 3676 KB/s, 171 seconds passed
+... 90%, 629344 KB, 3676 KB/s, 171 seconds passed
+... 90%, 629376 KB, 3676 KB/s, 171 seconds passed
 
 .. parsed-literal::
 
-    ... 90%, 630336 KB, 3379 KB/s, 186 seconds passed
-... 90%, 630368 KB, 3379 KB/s, 186 seconds passed
-... 90%, 630400 KB, 3379 KB/s, 186 seconds passed
-... 90%, 630432 KB, 3379 KB/s, 186 seconds passed
-... 90%, 630464 KB, 3379 KB/s, 186 seconds passed
+    ... 90%, 629408 KB, 3676 KB/s, 171 seconds passed
+... 90%, 629440 KB, 3676 KB/s, 171 seconds passed
+... 90%, 629472 KB, 3676 KB/s, 171 seconds passed
+... 90%, 629504 KB, 3676 KB/s, 171 seconds passed
+... 90%, 629536 KB, 3676 KB/s, 171 seconds passed
+... 90%, 629568 KB, 3676 KB/s, 171 seconds passed
+... 90%, 629600 KB, 3676 KB/s, 171 seconds passed
 
 .. parsed-literal::
 
-    ... 90%, 630496 KB, 3379 KB/s, 186 seconds passed
-... 90%, 630528 KB, 3379 KB/s, 186 seconds passed
-... 90%, 630560 KB, 3379 KB/s, 186 seconds passed
-... 90%, 630592 KB, 3379 KB/s, 186 seconds passed
-... 90%, 630624 KB, 3379 KB/s, 186 seconds passed
-... 90%, 630656 KB, 3379 KB/s, 186 seconds passed
-... 90%, 630688 KB, 3379 KB/s, 186 seconds passed
+    ... 90%, 629632 KB, 3676 KB/s, 171 seconds passed
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+... 90%, 629696 KB, 3676 KB/s, 171 seconds passed
+... 90%, 629728 KB, 3676 KB/s, 171 seconds passed
+... 90%, 629760 KB, 3676 KB/s, 171 seconds passed
 
 .. parsed-literal::
 
-    ... 90%, 630720 KB, 3379 KB/s, 186 seconds passed
-... 90%, 630752 KB, 3379 KB/s, 186 seconds passed
-... 90%, 630784 KB, 3379 KB/s, 186 seconds passed
-... 90%, 630816 KB, 3379 KB/s, 186 seconds passed
-... 90%, 630848 KB, 3379 KB/s, 186 seconds passed
+    ... 90%, 629792 KB, 3676 KB/s, 171 seconds passed
+... 90%, 629824 KB, 3676 KB/s, 171 seconds passed
+... 90%, 629856 KB, 3676 KB/s, 171 seconds passed
+... 90%, 629888 KB, 3676 KB/s, 171 seconds passed
+... 90%, 629920 KB, 3676 KB/s, 171 seconds passed
+... 90%, 629952 KB, 3676 KB/s, 171 seconds passed
+... 90%, 629984 KB, 3676 KB/s, 171 seconds passed
 
 .. parsed-literal::
 
-    ... 90%, 630880 KB, 3379 KB/s, 186 seconds passed
-... 90%, 630912 KB, 3379 KB/s, 186 seconds passed
-... 90%, 630944 KB, 3379 KB/s, 186 seconds passed
-... 90%, 630976 KB, 3379 KB/s, 186 seconds passed
-... 90%, 631008 KB, 3379 KB/s, 186 seconds passed
-... 90%, 631040 KB, 3380 KB/s, 186 seconds passed
+    ... 90%, 630016 KB, 3676 KB/s, 171 seconds passed
+... 90%, 630048 KB, 3676 KB/s, 171 seconds passed
+... 90%, 630080 KB, 3676 KB/s, 171 seconds passed
+... 90%, 630112 KB, 3676 KB/s, 171 seconds passed
 
 .. parsed-literal::
 
-    ... 90%, 631072 KB, 3379 KB/s, 186 seconds passed
-... 90%, 631104 KB, 3379 KB/s, 186 seconds passed
-... 90%, 631136 KB, 3379 KB/s, 186 seconds passed
-... 90%, 631168 KB, 3380 KB/s, 186 seconds passed
-... 90%, 631200 KB, 3379 KB/s, 186 seconds passed
-... 90%, 631232 KB, 3379 KB/s, 186 seconds passed
+    ... 90%, 630144 KB, 3676 KB/s, 171 seconds passed
+... 90%, 630176 KB, 3676 KB/s, 171 seconds passed
+... 90%, 630208 KB, 3676 KB/s, 171 seconds passed
+... 90%, 630240 KB, 3676 KB/s, 171 seconds passed
+... 90%, 630272 KB, 3676 KB/s, 171 seconds passed
+... 90%, 630304 KB, 3676 KB/s, 171 seconds passed
+... 90%, 630336 KB, 3676 KB/s, 171 seconds passed
+... 90%, 630368 KB, 3676 KB/s, 171 seconds passed
 
 .. parsed-literal::
 
-    ... 90%, 631264 KB, 3380 KB/s, 186 seconds passed
-... 90%, 631296 KB, 3380 KB/s, 186 seconds passed
-... 90%, 631328 KB, 3379 KB/s, 186 seconds passed
-... 90%, 631360 KB, 3379 KB/s, 186 seconds passed
-... 90%, 631392 KB, 3380 KB/s, 186 seconds passed
-... 90%, 631424 KB, 3380 KB/s, 186 seconds passed
+    ... 90%, 630400 KB, 3676 KB/s, 171 seconds passed
+... 90%, 630432 KB, 3676 KB/s, 171 seconds passed
+... 90%, 630464 KB, 3676 KB/s, 171 seconds passed
+... 90%, 630496 KB, 3676 KB/s, 171 seconds passed
 
 .. parsed-literal::
 
-    ... 90%, 631456 KB, 3380 KB/s, 186 seconds passed
-... 90%, 631488 KB, 3380 KB/s, 186 seconds passed
-... 90%, 631520 KB, 3380 KB/s, 186 seconds passed
-... 90%, 631552 KB, 3380 KB/s, 186 seconds passed
-... 90%, 631584 KB, 3380 KB/s, 186 seconds passed
+    ... 90%, 630528 KB, 3676 KB/s, 171 seconds passed
+... 90%, 630560 KB, 3676 KB/s, 171 seconds passed
+... 90%, 630592 KB, 3676 KB/s, 171 seconds passed
+... 90%, 630624 KB, 3676 KB/s, 171 seconds passed
+... 90%, 630656 KB, 3676 KB/s, 171 seconds passed
+... 90%, 630688 KB, 3676 KB/s, 171 seconds passed
+... 90%, 630720 KB, 3676 KB/s, 171 seconds passed
 
 .. parsed-literal::
 
-    ... 90%, 631616 KB, 3380 KB/s, 186 seconds passed
-... 90%, 631648 KB, 3380 KB/s, 186 seconds passed
-... 90%, 631680 KB, 3380 KB/s, 186 seconds passed
-... 90%, 631712 KB, 3380 KB/s, 186 seconds passed
-... 90%, 631744 KB, 3380 KB/s, 186 seconds passed
-... 90%, 631776 KB, 3380 KB/s, 186 seconds passed
-... 90%, 631808 KB, 3380 KB/s, 186 seconds passed
+    ... 90%, 630752 KB, 3676 KB/s, 171 seconds passed
+... 90%, 630784 KB, 3676 KB/s, 171 seconds passed
+... 90%, 630816 KB, 3676 KB/s, 171 seconds passed
+... 90%, 630848 KB, 3676 KB/s, 171 seconds passed
+... 90%, 630880 KB, 3676 KB/s, 171 seconds passed
 
 .. parsed-literal::
 
-    ... 90%, 631840 KB, 3380 KB/s, 186 seconds passed
-... 90%, 631872 KB, 3380 KB/s, 186 seconds passed
-... 90%, 631904 KB, 3380 KB/s, 186 seconds passed
-... 90%, 631936 KB, 3380 KB/s, 186 seconds passed
-... 90%, 631968 KB, 3380 KB/s, 186 seconds passed
+    ... 90%, 630912 KB, 3676 KB/s, 171 seconds passed
+... 90%, 630944 KB, 3676 KB/s, 171 seconds passed
+... 90%, 630976 KB, 3676 KB/s, 171 seconds passed
+... 90%, 631008 KB, 3676 KB/s, 171 seconds passed
+... 90%, 631040 KB, 3676 KB/s, 171 seconds passed
+... 90%, 631072 KB, 3676 KB/s, 171 seconds passed
+... 90%, 631104 KB, 3676 KB/s, 171 seconds passed
 
 .. parsed-literal::
 
-    ... 90%, 632000 KB, 3380 KB/s, 186 seconds passed
-... 90%, 632032 KB, 3380 KB/s, 186 seconds passed
-... 90%, 632064 KB, 3380 KB/s, 186 seconds passed
-... 90%, 632096 KB, 3380 KB/s, 186 seconds passed
-... 90%, 632128 KB, 3380 KB/s, 187 seconds passed
-... 90%, 632160 KB, 3380 KB/s, 187 seconds passed
-... 90%, 632192 KB, 3380 KB/s, 187 seconds passed
+    ... 90%, 631136 KB, 3676 KB/s, 171 seconds passed
+... 90%, 631168 KB, 3676 KB/s, 171 seconds passed
+... 90%, 631200 KB, 3676 KB/s, 171 seconds passed
+... 90%, 631232 KB, 3676 KB/s, 171 seconds passed
+... 90%, 631264 KB, 3676 KB/s, 171 seconds passed
 
 .. parsed-literal::
 
-    ... 90%, 632224 KB, 3380 KB/s, 187 seconds passed
-... 90%, 632256 KB, 3380 KB/s, 187 seconds passed
-... 90%, 632288 KB, 3380 KB/s, 187 seconds passed
-... 90%, 632320 KB, 3380 KB/s, 187 seconds passed
-... 90%, 632352 KB, 3380 KB/s, 187 seconds passed
+    ... 90%, 631296 KB, 3676 KB/s, 171 seconds passed
+... 90%, 631328 KB, 3676 KB/s, 171 seconds passed
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+... 90%, 631392 KB, 3676 KB/s, 171 seconds passed
+... 90%, 631424 KB, 3676 KB/s, 171 seconds passed
+... 90%, 631456 KB, 3676 KB/s, 171 seconds passed
+... 90%, 631488 KB, 3676 KB/s, 171 seconds passed
 
 .. parsed-literal::
 
-    ... 90%, 632384 KB, 3380 KB/s, 187 seconds passed
-... 90%, 632416 KB, 3380 KB/s, 187 seconds passed
-... 90%, 632448 KB, 3380 KB/s, 187 seconds passed
-... 90%, 632480 KB, 3380 KB/s, 187 seconds passed
-... 90%, 632512 KB, 3380 KB/s, 187 seconds passed
-... 90%, 632544 KB, 3380 KB/s, 187 seconds passed
-... 90%, 632576 KB, 3380 KB/s, 187 seconds passed
+    ... 90%, 631520 KB, 3676 KB/s, 171 seconds passed
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+... 90%, 631584 KB, 3676 KB/s, 171 seconds passed
+... 90%, 631616 KB, 3676 KB/s, 171 seconds passed
+... 90%, 631648 KB, 3676 KB/s, 171 seconds passed
 
 .. parsed-literal::
 
-    ... 90%, 632608 KB, 3380 KB/s, 187 seconds passed
-... 90%, 632640 KB, 3380 KB/s, 187 seconds passed
-... 90%, 632672 KB, 3380 KB/s, 187 seconds passed
-... 90%, 632704 KB, 3380 KB/s, 187 seconds passed
-... 90%, 632736 KB, 3380 KB/s, 187 seconds passed
+    ... 90%, 631680 KB, 3676 KB/s, 171 seconds passed
+... 90%, 631712 KB, 3676 KB/s, 171 seconds passed
+... 90%, 631744 KB, 3676 KB/s, 171 seconds passed
+... 90%, 631776 KB, 3676 KB/s, 171 seconds passed
+... 90%, 631808 KB, 3676 KB/s, 171 seconds passed
+... 90%, 631840 KB, 3676 KB/s, 171 seconds passed
 
 .. parsed-literal::
 
-    ... 90%, 632768 KB, 3380 KB/s, 187 seconds passed
-... 90%, 632800 KB, 3380 KB/s, 187 seconds passed
-... 90%, 632832 KB, 3380 KB/s, 187 seconds passed
-... 90%, 632864 KB, 3380 KB/s, 187 seconds passed
-... 90%, 632896 KB, 3380 KB/s, 187 seconds passed
-... 91%, 632928 KB, 3380 KB/s, 187 seconds passed
-... 91%, 632960 KB, 3380 KB/s, 187 seconds passed
+    ... 90%, 631872 KB, 3676 KB/s, 171 seconds passed
+... 90%, 631904 KB, 3676 KB/s, 171 seconds passed
+... 90%, 631936 KB, 3676 KB/s, 171 seconds passed
+... 90%, 631968 KB, 3676 KB/s, 171 seconds passed
+... 90%, 632000 KB, 3676 KB/s, 171 seconds passed
 
 .. parsed-literal::
 
-    ... 91%, 632992 KB, 3380 KB/s, 187 seconds passed
-... 91%, 633024 KB, 3380 KB/s, 187 seconds passed
-... 91%, 633056 KB, 3380 KB/s, 187 seconds passed
-... 91%, 633088 KB, 3380 KB/s, 187 seconds passed
-... 91%, 633120 KB, 3380 KB/s, 187 seconds passed
+    ... 90%, 632032 KB, 3676 KB/s, 171 seconds passed
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+... 90%, 632096 KB, 3676 KB/s, 171 seconds passed
+... 90%, 632128 KB, 3676 KB/s, 171 seconds passed
+... 90%, 632160 KB, 3676 KB/s, 171 seconds passed
+... 90%, 632192 KB, 3676 KB/s, 171 seconds passed
 
 .. parsed-literal::
 
-    ... 91%, 633152 KB, 3380 KB/s, 187 seconds passed
-... 91%, 633184 KB, 3380 KB/s, 187 seconds passed
-... 91%, 633216 KB, 3381 KB/s, 187 seconds passed
-... 91%, 633248 KB, 3380 KB/s, 187 seconds passed
-... 91%, 633280 KB, 3380 KB/s, 187 seconds passed
-... 91%, 633312 KB, 3380 KB/s, 187 seconds passed
-... 91%, 633344 KB, 3381 KB/s, 187 seconds passed
+    ... 90%, 632224 KB, 3676 KB/s, 171 seconds passed
+... 90%, 632256 KB, 3676 KB/s, 171 seconds passed
+... 90%, 632288 KB, 3676 KB/s, 171 seconds passed
+... 90%, 632320 KB, 3676 KB/s, 171 seconds passed
+... 90%, 632352 KB, 3676 KB/s, 171 seconds passed
+... 90%, 632384 KB, 3676 KB/s, 171 seconds passed
 
 .. parsed-literal::
 
-    ... 91%, 633376 KB, 3380 KB/s, 187 seconds passed
-... 91%, 633408 KB, 3380 KB/s, 187 seconds passed
-... 91%, 633440 KB, 3380 KB/s, 187 seconds passed
-... 91%, 633472 KB, 3381 KB/s, 187 seconds passed
+    ... 90%, 632416 KB, 3676 KB/s, 172 seconds passed
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+... 90%, 632480 KB, 3676 KB/s, 172 seconds passed
+... 90%, 632512 KB, 3676 KB/s, 172 seconds passed
+... 90%, 632544 KB, 3676 KB/s, 172 seconds passed
+... 90%, 632576 KB, 3676 KB/s, 172 seconds passed
+... 90%, 632608 KB, 3676 KB/s, 172 seconds passed
 
 .. parsed-literal::
 
-    ... 91%, 633504 KB, 3380 KB/s, 187 seconds passed
-... 91%, 633536 KB, 3380 KB/s, 187 seconds passed
-... 91%, 633568 KB, 3381 KB/s, 187 seconds passed
-... 91%, 633600 KB, 3381 KB/s, 187 seconds passed
-... 91%, 633632 KB, 3380 KB/s, 187 seconds passed
-... 91%, 633664 KB, 3381 KB/s, 187 seconds passed
-... 91%, 633696 KB, 3381 KB/s, 187 seconds passed
-... 91%, 633728 KB, 3381 KB/s, 187 seconds passed
+    ... 90%, 632640 KB, 3676 KB/s, 172 seconds passed
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+... 90%, 632704 KB, 3676 KB/s, 172 seconds passed
+... 90%, 632736 KB, 3676 KB/s, 172 seconds passed
+... 90%, 632768 KB, 3676 KB/s, 172 seconds passed
 
 .. parsed-literal::
 
-    ... 91%, 633760 KB, 3381 KB/s, 187 seconds passed
-... 91%, 633792 KB, 3381 KB/s, 187 seconds passed
-... 91%, 633824 KB, 3381 KB/s, 187 seconds passed
-... 91%, 633856 KB, 3381 KB/s, 187 seconds passed
+    ... 90%, 632800 KB, 3676 KB/s, 172 seconds passed
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+... 90%, 632896 KB, 3676 KB/s, 172 seconds passed
+... 91%, 632928 KB, 3676 KB/s, 172 seconds passed
+... 91%, 632960 KB, 3676 KB/s, 172 seconds passed
 
 .. parsed-literal::
 
-    ... 91%, 633888 KB, 3381 KB/s, 187 seconds passed
-... 91%, 633920 KB, 3381 KB/s, 187 seconds passed
-... 91%, 633952 KB, 3381 KB/s, 187 seconds passed
-... 91%, 633984 KB, 3381 KB/s, 187 seconds passed
-... 91%, 634016 KB, 3381 KB/s, 187 seconds passed
-... 91%, 634048 KB, 3381 KB/s, 187 seconds passed
-... 91%, 634080 KB, 3381 KB/s, 187 seconds passed
+    ... 91%, 632992 KB, 3676 KB/s, 172 seconds passed
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+... 91%, 633088 KB, 3676 KB/s, 172 seconds passed
+... 91%, 633120 KB, 3676 KB/s, 172 seconds passed
+... 91%, 633152 KB, 3676 KB/s, 172 seconds passed
 
 .. parsed-literal::
 
-    ... 91%, 634112 KB, 3381 KB/s, 187 seconds passed
-... 91%, 634144 KB, 3381 KB/s, 187 seconds passed
-... 91%, 634176 KB, 3381 KB/s, 187 seconds passed
-... 91%, 634208 KB, 3381 KB/s, 187 seconds passed
-... 91%, 634240 KB, 3381 KB/s, 187 seconds passed
+    ... 91%, 633184 KB, 3676 KB/s, 172 seconds passed
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+... 91%, 633280 KB, 3676 KB/s, 172 seconds passed
+... 91%, 633312 KB, 3676 KB/s, 172 seconds passed
+... 91%, 633344 KB, 3676 KB/s, 172 seconds passed
 
 .. parsed-literal::
 
-    ... 91%, 634272 KB, 3381 KB/s, 187 seconds passed
-... 91%, 634304 KB, 3381 KB/s, 187 seconds passed
-... 91%, 634336 KB, 3381 KB/s, 187 seconds passed
-... 91%, 634368 KB, 3381 KB/s, 187 seconds passed
-... 91%, 634400 KB, 3381 KB/s, 187 seconds passed
-... 91%, 634432 KB, 3381 KB/s, 187 seconds passed
-... 91%, 634464 KB, 3381 KB/s, 187 seconds passed
+    ... 91%, 633376 KB, 3676 KB/s, 172 seconds passed
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+... 91%, 633472 KB, 3676 KB/s, 172 seconds passed
+... 91%, 633504 KB, 3676 KB/s, 172 seconds passed
+... 91%, 633536 KB, 3676 KB/s, 172 seconds passed
 
 .. parsed-literal::
 
-    ... 91%, 634496 KB, 3381 KB/s, 187 seconds passed
-... 91%, 634528 KB, 3381 KB/s, 187 seconds passed
-... 91%, 634560 KB, 3381 KB/s, 187 seconds passed
-... 91%, 634592 KB, 3381 KB/s, 187 seconds passed
-... 91%, 634624 KB, 3381 KB/s, 187 seconds passed
+    ... 91%, 633568 KB, 3676 KB/s, 172 seconds passed
+... 91%, 633600 KB, 3676 KB/s, 172 seconds passed
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+... 91%, 633664 KB, 3676 KB/s, 172 seconds passed
+... 91%, 633696 KB, 3676 KB/s, 172 seconds passed
+... 91%, 633728 KB, 3676 KB/s, 172 seconds passed
 
 .. parsed-literal::
 
-    ... 91%, 634656 KB, 3381 KB/s, 187 seconds passed
-... 91%, 634688 KB, 3381 KB/s, 187 seconds passed
-... 91%, 634720 KB, 3381 KB/s, 187 seconds passed
-... 91%, 634752 KB, 3381 KB/s, 187 seconds passed
-... 91%, 634784 KB, 3381 KB/s, 187 seconds passed
-... 91%, 634816 KB, 3381 KB/s, 187 seconds passed
+    ... 91%, 633760 KB, 3676 KB/s, 172 seconds passed
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+... 91%, 633856 KB, 3676 KB/s, 172 seconds passed
+... 91%, 633888 KB, 3676 KB/s, 172 seconds passed
+... 91%, 633920 KB, 3676 KB/s, 172 seconds passed
 
 .. parsed-literal::
 
-    ... 91%, 634848 KB, 3381 KB/s, 187 seconds passed
-... 91%, 634880 KB, 3381 KB/s, 187 seconds passed
-... 91%, 634912 KB, 3381 KB/s, 187 seconds passed
-... 91%, 634944 KB, 3381 KB/s, 187 seconds passed
-... 91%, 634976 KB, 3381 KB/s, 187 seconds passed
-... 91%, 635008 KB, 3381 KB/s, 187 seconds passed
+    ... 91%, 633952 KB, 3676 KB/s, 172 seconds passed
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+... 91%, 634016 KB, 3676 KB/s, 172 seconds passed
+... 91%, 634048 KB, 3676 KB/s, 172 seconds passed
+... 91%, 634080 KB, 3676 KB/s, 172 seconds passed
 
 .. parsed-literal::
 
-    ... 91%, 635040 KB, 3381 KB/s, 187 seconds passed
-... 91%, 635072 KB, 3381 KB/s, 187 seconds passed
-... 91%, 635104 KB, 3381 KB/s, 187 seconds passed
-... 91%, 635136 KB, 3381 KB/s, 187 seconds passed
-... 91%, 635168 KB, 3381 KB/s, 187 seconds passed
-... 91%, 635200 KB, 3381 KB/s, 187 seconds passed
+    ... 91%, 634112 KB, 3676 KB/s, 172 seconds passed
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+... 91%, 634176 KB, 3676 KB/s, 172 seconds passed
+... 91%, 634208 KB, 3676 KB/s, 172 seconds passed
+... 91%, 634240 KB, 3676 KB/s, 172 seconds passed
+... 91%, 634272 KB, 3676 KB/s, 172 seconds passed
+... 91%, 634304 KB, 3676 KB/s, 172 seconds passed
 
 .. parsed-literal::
 
-    ... 91%, 635232 KB, 3381 KB/s, 187 seconds passed
-... 91%, 635264 KB, 3381 KB/s, 187 seconds passed
-... 91%, 635296 KB, 3381 KB/s, 187 seconds passed
-... 91%, 635328 KB, 3381 KB/s, 187 seconds passed
-... 91%, 635360 KB, 3381 KB/s, 187 seconds passed
-... 91%, 635392 KB, 3381 KB/s, 187 seconds passed
+    ... 91%, 634336 KB, 3676 KB/s, 172 seconds passed
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+... 91%, 634400 KB, 3676 KB/s, 172 seconds passed
+... 91%, 634432 KB, 3676 KB/s, 172 seconds passed
+... 91%, 634464 KB, 3676 KB/s, 172 seconds passed
 
 .. parsed-literal::
 
-    ... 91%, 635424 KB, 3381 KB/s, 187 seconds passed
-... 91%, 635456 KB, 3381 KB/s, 187 seconds passed
-... 91%, 635488 KB, 3381 KB/s, 187 seconds passed
-... 91%, 635520 KB, 3382 KB/s, 187 seconds passed
-... 91%, 635552 KB, 3381 KB/s, 187 seconds passed
-... 91%, 635584 KB, 3381 KB/s, 187 seconds passed
+    ... 91%, 634496 KB, 3676 KB/s, 172 seconds passed
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+... 91%, 634560 KB, 3676 KB/s, 172 seconds passed
+... 91%, 634592 KB, 3676 KB/s, 172 seconds passed
+... 91%, 634624 KB, 3676 KB/s, 172 seconds passed
+... 91%, 634656 KB, 3676 KB/s, 172 seconds passed
 
 .. parsed-literal::
 
-    ... 91%, 635616 KB, 3381 KB/s, 187 seconds passed
-... 91%, 635648 KB, 3382 KB/s, 187 seconds passed
-... 91%, 635680 KB, 3381 KB/s, 187 seconds passed
-... 91%, 635712 KB, 3381 KB/s, 187 seconds passed
-... 91%, 635744 KB, 3382 KB/s, 187 seconds passed
-... 91%, 635776 KB, 3382 KB/s, 187 seconds passed
+    ... 91%, 634688 KB, 3676 KB/s, 172 seconds passed
+... 91%, 634720 KB, 3676 KB/s, 172 seconds passed
+... 91%, 634752 KB, 3676 KB/s, 172 seconds passed
+... 91%, 634784 KB, 3676 KB/s, 172 seconds passed
+... 91%, 634816 KB, 3676 KB/s, 172 seconds passed
+... 91%, 634848 KB, 3676 KB/s, 172 seconds passed
 
 .. parsed-literal::
 
-    ... 91%, 635808 KB, 3381 KB/s, 188 seconds passed
-... 91%, 635840 KB, 3381 KB/s, 188 seconds passed
-... 91%, 635872 KB, 3382 KB/s, 188 seconds passed
-... 91%, 635904 KB, 3382 KB/s, 188 seconds passed
-... 91%, 635936 KB, 3381 KB/s, 188 seconds passed
+    ... 91%, 634880 KB, 3676 KB/s, 172 seconds passed
+... 91%, 634912 KB, 3676 KB/s, 172 seconds passed
+... 91%, 634944 KB, 3676 KB/s, 172 seconds passed
+... 91%, 634976 KB, 3676 KB/s, 172 seconds passed
+... 91%, 635008 KB, 3676 KB/s, 172 seconds passed
+... 91%, 635040 KB, 3676 KB/s, 172 seconds passed
+... 91%, 635072 KB, 3676 KB/s, 172 seconds passed
 
 .. parsed-literal::
 
-    ... 91%, 635968 KB, 3382 KB/s, 188 seconds passed
-... 91%, 636000 KB, 3382 KB/s, 188 seconds passed
-... 91%, 636032 KB, 3382 KB/s, 188 seconds passed
-... 91%, 636064 KB, 3382 KB/s, 188 seconds passed
-... 91%, 636096 KB, 3382 KB/s, 188 seconds passed
-... 91%, 636128 KB, 3382 KB/s, 188 seconds passed
-... 91%, 636160 KB, 3382 KB/s, 188 seconds passed
+    ... 91%, 635104 KB, 3676 KB/s, 172 seconds passed
+... 91%, 635136 KB, 3676 KB/s, 172 seconds passed
+... 91%, 635168 KB, 3676 KB/s, 172 seconds passed
+... 91%, 635200 KB, 3676 KB/s, 172 seconds passed
+... 91%, 635232 KB, 3676 KB/s, 172 seconds passed
 
 .. parsed-literal::
 
-    ... 91%, 636192 KB, 3382 KB/s, 188 seconds passed
-... 91%, 636224 KB, 3382 KB/s, 188 seconds passed
-... 91%, 636256 KB, 3382 KB/s, 188 seconds passed
-... 91%, 636288 KB, 3382 KB/s, 188 seconds passed
-... 91%, 636320 KB, 3382 KB/s, 188 seconds passed
+    ... 91%, 635264 KB, 3676 KB/s, 172 seconds passed
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+... 91%, 635360 KB, 3676 KB/s, 172 seconds passed
+... 91%, 635392 KB, 3676 KB/s, 172 seconds passed
+... 91%, 635424 KB, 3676 KB/s, 172 seconds passed
 
 .. parsed-literal::
 
-    ... 91%, 636352 KB, 3382 KB/s, 188 seconds passed
-... 91%, 636384 KB, 3382 KB/s, 188 seconds passed
-... 91%, 636416 KB, 3382 KB/s, 188 seconds passed
-... 91%, 636448 KB, 3382 KB/s, 188 seconds passed
-... 91%, 636480 KB, 3382 KB/s, 188 seconds passed
-... 91%, 636512 KB, 3382 KB/s, 188 seconds passed
-... 91%, 636544 KB, 3382 KB/s, 188 seconds passed
+    ... 91%, 635456 KB, 3676 KB/s, 172 seconds passed
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+... 91%, 635584 KB, 3676 KB/s, 172 seconds passed
+... 91%, 635616 KB, 3676 KB/s, 172 seconds passed
 
 .. parsed-literal::
 
-    ... 91%, 636576 KB, 3382 KB/s, 188 seconds passed
-... 91%, 636608 KB, 3382 KB/s, 188 seconds passed
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-... 91%, 636704 KB, 3382 KB/s, 188 seconds passed
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+... 91%, 635776 KB, 3676 KB/s, 172 seconds passed
+... 91%, 635808 KB, 3676 KB/s, 172 seconds passed
 
 .. parsed-literal::
 
-    ... 91%, 636736 KB, 3382 KB/s, 188 seconds passed
-... 91%, 636768 KB, 3382 KB/s, 188 seconds passed
-... 91%, 636800 KB, 3382 KB/s, 188 seconds passed
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-... 91%, 636896 KB, 3382 KB/s, 188 seconds passed
+    ... 91%, 635840 KB, 3676 KB/s, 172 seconds passed
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+... 91%, 635936 KB, 3676 KB/s, 172 seconds passed
+... 91%, 635968 KB, 3676 KB/s, 172 seconds passed
 
 .. parsed-literal::
 
-    ... 91%, 636928 KB, 3382 KB/s, 188 seconds passed
-... 91%, 636960 KB, 3382 KB/s, 188 seconds passed
-... 91%, 636992 KB, 3382 KB/s, 188 seconds passed
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+    ... 91%, 636000 KB, 3676 KB/s, 172 seconds passed
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+... 91%, 636128 KB, 3676 KB/s, 173 seconds passed
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+... 91%, 636192 KB, 3676 KB/s, 173 seconds passed
 
 .. parsed-literal::
 
-    ... 91%, 637088 KB, 3382 KB/s, 188 seconds passed
-... 91%, 637120 KB, 3382 KB/s, 188 seconds passed
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-... 91%, 637216 KB, 3382 KB/s, 188 seconds passed
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+    ... 91%, 636224 KB, 3676 KB/s, 173 seconds passed
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+... 91%, 636320 KB, 3676 KB/s, 173 seconds passed
+... 91%, 636352 KB, 3676 KB/s, 173 seconds passed
 
 .. parsed-literal::
 
-    ... 91%, 637312 KB, 3382 KB/s, 188 seconds passed
-... 91%, 637344 KB, 3382 KB/s, 188 seconds passed
-... 91%, 637376 KB, 3382 KB/s, 188 seconds passed
-... 91%, 637408 KB, 3382 KB/s, 188 seconds passed
-... 91%, 637440 KB, 3382 KB/s, 188 seconds passed
+    ... 91%, 636384 KB, 3676 KB/s, 173 seconds passed
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+... 91%, 636512 KB, 3676 KB/s, 173 seconds passed
+... 91%, 636544 KB, 3676 KB/s, 173 seconds passed
+... 91%, 636576 KB, 3676 KB/s, 173 seconds passed
 
 .. parsed-literal::
 
-    ... 91%, 637472 KB, 3382 KB/s, 188 seconds passed
-... 91%, 637504 KB, 3382 KB/s, 188 seconds passed
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-... 91%, 637600 KB, 3382 KB/s, 188 seconds passed
-... 91%, 637632 KB, 3382 KB/s, 188 seconds passed
-... 91%, 637664 KB, 3382 KB/s, 188 seconds passed
+    ... 91%, 636608 KB, 3676 KB/s, 173 seconds passed
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+... 91%, 636736 KB, 3676 KB/s, 173 seconds passed
 
 .. parsed-literal::
 
-    ... 91%, 637696 KB, 3382 KB/s, 188 seconds passed
-... 91%, 637728 KB, 3382 KB/s, 188 seconds passed
-... 91%, 637760 KB, 3382 KB/s, 188 seconds passed
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-... 91%, 637824 KB, 3382 KB/s, 188 seconds passed
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+... 91%, 636928 KB, 3676 KB/s, 173 seconds passed
+... 91%, 636960 KB, 3676 KB/s, 173 seconds passed
 
 .. parsed-literal::
 
-    ... 91%, 637856 KB, 3382 KB/s, 188 seconds passed
-... 91%, 637888 KB, 3382 KB/s, 188 seconds passed
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-... 91%, 637984 KB, 3382 KB/s, 188 seconds passed
-... 91%, 638016 KB, 3382 KB/s, 188 seconds passed
-... 91%, 638048 KB, 3383 KB/s, 188 seconds passed
+    ... 91%, 636992 KB, 3676 KB/s, 173 seconds passed
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+... 91%, 637088 KB, 3676 KB/s, 173 seconds passed
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 .. parsed-literal::
 
-    ... 91%, 638080 KB, 3383 KB/s, 188 seconds passed
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-... 91%, 638208 KB, 3383 KB/s, 188 seconds passed
+    ... 91%, 637152 KB, 3676 KB/s, 173 seconds passed
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+... 91%, 637312 KB, 3676 KB/s, 173 seconds passed
+... 91%, 637344 KB, 3676 KB/s, 173 seconds passed
 
 .. parsed-literal::
 
-    ... 91%, 638240 KB, 3382 KB/s, 188 seconds passed
-... 91%, 638272 KB, 3383 KB/s, 188 seconds passed
-... 91%, 638304 KB, 3383 KB/s, 188 seconds passed
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-... 91%, 638400 KB, 3383 KB/s, 188 seconds passed
-... 91%, 638432 KB, 3383 KB/s, 188 seconds passed
+    ... 91%, 637376 KB, 3676 KB/s, 173 seconds passed
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+... 91%, 637472 KB, 3676 KB/s, 173 seconds passed
+... 91%, 637504 KB, 3676 KB/s, 173 seconds passed
 
 .. parsed-literal::
 
-    ... 91%, 638464 KB, 3383 KB/s, 188 seconds passed
-... 91%, 638496 KB, 3383 KB/s, 188 seconds passed
-... 91%, 638528 KB, 3383 KB/s, 188 seconds passed
-... 91%, 638560 KB, 3383 KB/s, 188 seconds passed
-... 91%, 638592 KB, 3383 KB/s, 188 seconds passed
+    ... 91%, 637536 KB, 3676 KB/s, 173 seconds passed
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 .. parsed-literal::
 
-    ... 91%, 638624 KB, 3383 KB/s, 188 seconds passed
-... 91%, 638656 KB, 3383 KB/s, 188 seconds passed
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-... 91%, 638784 KB, 3383 KB/s, 188 seconds passed
-... 91%, 638816 KB, 3383 KB/s, 188 seconds passed
+    ... 91%, 637760 KB, 3676 KB/s, 173 seconds passed
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+... 91%, 637856 KB, 3676 KB/s, 173 seconds passed
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 .. parsed-literal::
 
-    ... 91%, 638848 KB, 3383 KB/s, 188 seconds passed
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 .. parsed-literal::
 
-    ... 91%, 639008 KB, 3383 KB/s, 188 seconds passed
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-... 91%, 639136 KB, 3383 KB/s, 188 seconds passed
-... 91%, 639168 KB, 3383 KB/s, 188 seconds passed
-... 91%, 639200 KB, 3383 KB/s, 188 seconds passed
+    ... 91%, 638144 KB, 3676 KB/s, 173 seconds passed
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+... 91%, 638208 KB, 3676 KB/s, 173 seconds passed
+... 91%, 638240 KB, 3676 KB/s, 173 seconds passed
+... 91%, 638272 KB, 3676 KB/s, 173 seconds passed
 
 .. parsed-literal::
 
-    ... 91%, 639232 KB, 3383 KB/s, 188 seconds passed
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-... 91%, 639296 KB, 3383 KB/s, 188 seconds passed
-... 91%, 639328 KB, 3383 KB/s, 188 seconds passed
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 .. parsed-literal::
 
-    ... 91%, 639392 KB, 3383 KB/s, 188 seconds passed
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 .. parsed-literal::
 
-    ... 91%, 639552 KB, 3383 KB/s, 189 seconds passed
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 .. parsed-literal::
 
-    ... 91%, 639776 KB, 3383 KB/s, 189 seconds passed
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 .. parsed-literal::
 
-    ... 92%, 639936 KB, 3383 KB/s, 189 seconds passed
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-... 92%, 640000 KB, 3383 KB/s, 189 seconds passed
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-... 92%, 640096 KB, 3383 KB/s, 189 seconds passed
+    ... 91%, 639040 KB, 3676 KB/s, 173 seconds passed
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+... 91%, 639200 KB, 3676 KB/s, 173 seconds passed
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 .. parsed-literal::
 
-    ... 92%, 640128 KB, 3383 KB/s, 189 seconds passed
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 .. parsed-literal::
 
-    ... 92%, 640320 KB, 3383 KB/s, 189 seconds passed
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 .. parsed-literal::
 
-    ... 92%, 640512 KB, 3383 KB/s, 189 seconds passed
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 .. parsed-literal::
 
-    ... 92%, 640704 KB, 3384 KB/s, 189 seconds passed
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+... 92%, 640000 KB, 3676 KB/s, 174 seconds passed
 
 .. parsed-literal::
 
-    ... 92%, 640896 KB, 3384 KB/s, 189 seconds passed
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-... 92%, 640992 KB, 3384 KB/s, 189 seconds passed
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+    ... 92%, 640032 KB, 3676 KB/s, 174 seconds passed
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 .. parsed-literal::
 
-    ... 92%, 641088 KB, 3384 KB/s, 189 seconds passed
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-... 92%, 641216 KB, 3384 KB/s, 189 seconds passed
-... 92%, 641248 KB, 3384 KB/s, 189 seconds passed
+    ... 92%, 640192 KB, 3676 KB/s, 174 seconds passed
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 .. parsed-literal::
 
-    ... 92%, 641280 KB, 3384 KB/s, 189 seconds passed
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-... 92%, 641408 KB, 3384 KB/s, 189 seconds passed
+    ... 92%, 640384 KB, 3676 KB/s, 174 seconds passed
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 .. parsed-literal::
 
-    ... 92%, 641440 KB, 3384 KB/s, 189 seconds passed
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-... 92%, 641600 KB, 3384 KB/s, 189 seconds passed
+    ... 92%, 640576 KB, 3676 KB/s, 174 seconds passed
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+... 92%, 640704 KB, 3676 KB/s, 174 seconds passed
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 .. parsed-literal::
 
-    ... 92%, 641632 KB, 3384 KB/s, 189 seconds passed
-... 92%, 641664 KB, 3384 KB/s, 189 seconds passed
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-... 92%, 641728 KB, 3384 KB/s, 189 seconds passed
-... 92%, 641760 KB, 3384 KB/s, 189 seconds passed
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+    ... 92%, 640768 KB, 3676 KB/s, 174 seconds passed
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+... 92%, 640896 KB, 3676 KB/s, 174 seconds passed
 
 .. parsed-literal::
 
-    ... 92%, 641824 KB, 3384 KB/s, 189 seconds passed
-... 92%, 641856 KB, 3384 KB/s, 189 seconds passed
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-... 92%, 641920 KB, 3384 KB/s, 189 seconds passed
-... 92%, 641952 KB, 3384 KB/s, 189 seconds passed
-... 92%, 641984 KB, 3384 KB/s, 189 seconds passed
+    ... 92%, 640928 KB, 3676 KB/s, 174 seconds passed
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+... 92%, 641024 KB, 3676 KB/s, 174 seconds passed
+... 92%, 641056 KB, 3676 KB/s, 174 seconds passed
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 .. parsed-literal::
 
-    ... 92%, 642016 KB, 3384 KB/s, 189 seconds passed
-... 92%, 642048 KB, 3384 KB/s, 189 seconds passed
-... 92%, 642080 KB, 3384 KB/s, 189 seconds passed
-... 92%, 642112 KB, 3384 KB/s, 189 seconds passed
-... 92%, 642144 KB, 3384 KB/s, 189 seconds passed
-... 92%, 642176 KB, 3384 KB/s, 189 seconds passed
+    ... 92%, 641120 KB, 3676 KB/s, 174 seconds passed
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+... 92%, 641216 KB, 3676 KB/s, 174 seconds passed
+... 92%, 641248 KB, 3676 KB/s, 174 seconds passed
+... 92%, 641280 KB, 3676 KB/s, 174 seconds passed
 
 .. parsed-literal::
 
-    ... 92%, 642208 KB, 3384 KB/s, 189 seconds passed
-... 92%, 642240 KB, 3384 KB/s, 189 seconds passed
-... 92%, 642272 KB, 3384 KB/s, 189 seconds passed
-... 92%, 642304 KB, 3384 KB/s, 189 seconds passed
-... 92%, 642336 KB, 3384 KB/s, 189 seconds passed
-... 92%, 642368 KB, 3384 KB/s, 189 seconds passed
+    ... 92%, 641312 KB, 3676 KB/s, 174 seconds passed
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+... 92%, 641440 KB, 3676 KB/s, 174 seconds passed
+... 92%, 641472 KB, 3676 KB/s, 174 seconds passed
+... 92%, 641504 KB, 3676 KB/s, 174 seconds passed
 
 .. parsed-literal::
 
-    ... 92%, 642400 KB, 3384 KB/s, 189 seconds passed
-... 92%, 642432 KB, 3384 KB/s, 189 seconds passed
-... 92%, 642464 KB, 3384 KB/s, 189 seconds passed
-... 92%, 642496 KB, 3384 KB/s, 189 seconds passed
-... 92%, 642528 KB, 3384 KB/s, 189 seconds passed
+    ... 92%, 641536 KB, 3676 KB/s, 174 seconds passed
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+... 92%, 641600 KB, 3676 KB/s, 174 seconds passed
+... 92%, 641632 KB, 3676 KB/s, 174 seconds passed
+... 92%, 641664 KB, 3676 KB/s, 174 seconds passed
+... 92%, 641696 KB, 3676 KB/s, 174 seconds passed
 
 .. parsed-literal::
 
-    ... 92%, 642560 KB, 3384 KB/s, 189 seconds passed
-... 92%, 642592 KB, 3384 KB/s, 189 seconds passed
-... 92%, 642624 KB, 3384 KB/s, 189 seconds passed
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-... 92%, 642688 KB, 3384 KB/s, 189 seconds passed
-... 92%, 642720 KB, 3384 KB/s, 189 seconds passed
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+... 92%, 641856 KB, 3676 KB/s, 174 seconds passed
 
 .. parsed-literal::
 
-    ... 92%, 642752 KB, 3384 KB/s, 189 seconds passed
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-... 92%, 642816 KB, 3384 KB/s, 189 seconds passed
-... 92%, 642848 KB, 3384 KB/s, 189 seconds passed
-... 92%, 642880 KB, 3384 KB/s, 189 seconds passed
-... 92%, 642912 KB, 3384 KB/s, 189 seconds passed
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+... 92%, 642048 KB, 3676 KB/s, 174 seconds passed
 
 .. parsed-literal::
 
-    ... 92%, 642944 KB, 3384 KB/s, 189 seconds passed
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-... 92%, 643104 KB, 3385 KB/s, 189 seconds passed
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 .. parsed-literal::
 
-    ... 92%, 643136 KB, 3385 KB/s, 189 seconds passed
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 .. parsed-literal::
 
-    ... 92%, 643328 KB, 3385 KB/s, 190 seconds passed
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 .. parsed-literal::
 
-    ... 92%, 643520 KB, 3385 KB/s, 190 seconds passed
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+... 92%, 642784 KB, 3676 KB/s, 174 seconds passed
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 .. parsed-literal::
 
-    ... 92%, 643712 KB, 3385 KB/s, 190 seconds passed
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 .. parsed-literal::
 
-    ... 92%, 643904 KB, 3385 KB/s, 190 seconds passed
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 .. parsed-literal::
 
-    ... 92%, 644096 KB, 3385 KB/s, 190 seconds passed
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 .. parsed-literal::
 
-    ... 92%, 644288 KB, 3385 KB/s, 190 seconds passed
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 .. parsed-literal::
 
-    ... 92%, 644480 KB, 3385 KB/s, 190 seconds passed
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 .. parsed-literal::
 
-    ... 92%, 644672 KB, 3385 KB/s, 190 seconds passed
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 .. parsed-literal::
 
-    ... 92%, 644832 KB, 3385 KB/s, 190 seconds passed
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 .. parsed-literal::
 
-    ... 92%, 645024 KB, 3385 KB/s, 190 seconds passed
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 .. parsed-literal::
 
-    ... 92%, 645216 KB, 3385 KB/s, 190 seconds passed
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 .. parsed-literal::
 
-    ... 92%, 645408 KB, 3386 KB/s, 190 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 92%, 645792 KB, 3386 KB/s, 190 seconds passed
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 .. parsed-literal::
 
-    ... 92%, 645984 KB, 3386 KB/s, 190 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 92%, 646368 KB, 3386 KB/s, 190 seconds passed
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 .. parsed-literal::
 
-    ... 92%, 646560 KB, 3386 KB/s, 190 seconds passed
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 .. parsed-literal::
 
-    ... 92%, 646720 KB, 3386 KB/s, 190 seconds passed
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 .. parsed-literal::
 
-    ... 93%, 646944 KB, 3386 KB/s, 191 seconds passed
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 .. parsed-literal::
 
-    ... 93%, 647104 KB, 3386 KB/s, 191 seconds passed
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 .. parsed-literal::
 
-    ... 93%, 647296 KB, 3386 KB/s, 191 seconds passed
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 .. parsed-literal::
 
-    ... 93%, 647488 KB, 3386 KB/s, 191 seconds passed
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 .. parsed-literal::
 
-    ... 93%, 647680 KB, 3387 KB/s, 191 seconds passed
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 .. parsed-literal::
 
-    ... 93%, 647872 KB, 3387 KB/s, 191 seconds passed
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 .. parsed-literal::
 
-    ... 93%, 648064 KB, 3387 KB/s, 191 seconds passed
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 .. parsed-literal::
 
-    ... 93%, 648256 KB, 3387 KB/s, 191 seconds passed
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 .. parsed-literal::
 
-    ... 93%, 648448 KB, 3387 KB/s, 191 seconds passed
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-... 93%, 648608 KB, 3387 KB/s, 191 seconds passed
+    ... 93%, 647552 KB, 3676 KB/s, 176 seconds passed
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 .. parsed-literal::
 
-    ... 93%, 648640 KB, 3387 KB/s, 191 seconds passed
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+    ... 93%, 647776 KB, 3676 KB/s, 176 seconds passed
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 .. parsed-literal::
 
-    ... 93%, 648800 KB, 3387 KB/s, 191 seconds passed
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-... 93%, 648864 KB, 3387 KB/s, 191 seconds passed
-... 93%, 648896 KB, 3387 KB/s, 191 seconds passed
-... 93%, 648928 KB, 3387 KB/s, 191 seconds passed
-... 93%, 648960 KB, 3387 KB/s, 191 seconds passed
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+... 93%, 648096 KB, 3676 KB/s, 176 seconds passed
+... 93%, 648128 KB, 3676 KB/s, 176 seconds passed
 
 .. parsed-literal::
 
-    ... 93%, 648992 KB, 3387 KB/s, 191 seconds passed
-... 93%, 649024 KB, 3387 KB/s, 191 seconds passed
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 .. parsed-literal::
 
-    ... 93%, 649184 KB, 3387 KB/s, 191 seconds passed
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-... 93%, 649344 KB, 3387 KB/s, 191 seconds passed
+    ... 93%, 648320 KB, 3676 KB/s, 176 seconds passed
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+... 93%, 648512 KB, 3676 KB/s, 176 seconds passed
 
 .. parsed-literal::
 
-    ... 93%, 649376 KB, 3387 KB/s, 191 seconds passed
-... 93%, 649408 KB, 3387 KB/s, 191 seconds passed
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 .. parsed-literal::
 
-    ... 93%, 649568 KB, 3387 KB/s, 191 seconds passed
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 .. parsed-literal::
 
-    ... 93%, 649760 KB, 3387 KB/s, 191 seconds passed
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-... 93%, 649920 KB, 3387 KB/s, 191 seconds passed
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 .. parsed-literal::
 
-    ... 93%, 649952 KB, 3387 KB/s, 191 seconds passed
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+    ... 93%, 649088 KB, 3676 KB/s, 176 seconds passed
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+... 93%, 649216 KB, 3676 KB/s, 176 seconds passed
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 .. parsed-literal::
 
-    ... 93%, 650144 KB, 3388 KB/s, 191 seconds passed
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-... 93%, 650208 KB, 3388 KB/s, 191 seconds passed
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+    ... 93%, 649280 KB, 3676 KB/s, 176 seconds passed
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 .. parsed-literal::
 
-    ... 93%, 650336 KB, 3388 KB/s, 191 seconds passed
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+    ... 93%, 649472 KB, 3676 KB/s, 176 seconds passed
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+... 93%, 649600 KB, 3676 KB/s, 176 seconds passed
+... 93%, 649632 KB, 3676 KB/s, 176 seconds passed
 
 .. parsed-literal::
 
-    ... 93%, 650528 KB, 3388 KB/s, 191 seconds passed
-... 93%, 650560 KB, 3388 KB/s, 192 seconds passed
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+    ... 93%, 649664 KB, 3676 KB/s, 176 seconds passed
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+... 93%, 649792 KB, 3676 KB/s, 176 seconds passed
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 .. parsed-literal::
 
-    ... 93%, 650720 KB, 3388 KB/s, 192 seconds passed
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+... 93%, 649984 KB, 3676 KB/s, 176 seconds passed
+... 93%, 650016 KB, 3676 KB/s, 176 seconds passed
 
 .. parsed-literal::
 
-    ... 93%, 650912 KB, 3388 KB/s, 192 seconds passed
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-... 93%, 650976 KB, 3388 KB/s, 192 seconds passed
-... 93%, 651008 KB, 3388 KB/s, 192 seconds passed
-... 93%, 651040 KB, 3388 KB/s, 192 seconds passed
+    ... 93%, 650048 KB, 3676 KB/s, 176 seconds passed
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+... 93%, 650176 KB, 3676 KB/s, 176 seconds passed
+... 93%, 650208 KB, 3677 KB/s, 176 seconds passed
 
 .. parsed-literal::
 
-    ... 93%, 651072 KB, 3388 KB/s, 192 seconds passed
-... 93%, 651104 KB, 3388 KB/s, 192 seconds passed
-... 93%, 651136 KB, 3388 KB/s, 192 seconds passed
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-... 93%, 651200 KB, 3388 KB/s, 192 seconds passed
-... 93%, 651232 KB, 3388 KB/s, 192 seconds passed
-... 93%, 651264 KB, 3388 KB/s, 192 seconds passed
+    ... 93%, 650240 KB, 3676 KB/s, 176 seconds passed
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+... 93%, 650336 KB, 3677 KB/s, 176 seconds passed
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 .. parsed-literal::
 
-    ... 93%, 651296 KB, 3388 KB/s, 192 seconds passed
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-... 93%, 651424 KB, 3388 KB/s, 192 seconds passed
+    ... 93%, 650400 KB, 3676 KB/s, 176 seconds passed
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 .. parsed-literal::
 
-    ... 93%, 651456 KB, 3388 KB/s, 192 seconds passed
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 .. parsed-literal::
 
-    ... 93%, 651648 KB, 3388 KB/s, 192 seconds passed
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-... 93%, 651808 KB, 3388 KB/s, 192 seconds passed
+    ... 93%, 650784 KB, 3676 KB/s, 176 seconds passed
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 .. parsed-literal::
 
-    ... 93%, 651840 KB, 3388 KB/s, 192 seconds passed
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-... 93%, 651936 KB, 3388 KB/s, 192 seconds passed
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 .. parsed-literal::
 
-    ... 93%, 652032 KB, 3388 KB/s, 192 seconds passed
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 .. parsed-literal::
 
-    ... 93%, 652224 KB, 3388 KB/s, 192 seconds passed
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+    ... 93%, 651392 KB, 3676 KB/s, 177 seconds passed
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 .. parsed-literal::
 
-    ... 93%, 652416 KB, 3389 KB/s, 192 seconds passed
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 .. parsed-literal::
 
-    ... 93%, 652608 KB, 3389 KB/s, 192 seconds passed
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+    ... 93%, 651776 KB, 3676 KB/s, 177 seconds passed
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 .. parsed-literal::
 
-    ... 93%, 652800 KB, 3389 KB/s, 192 seconds passed
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 .. parsed-literal::
 
-    ... 93%, 652992 KB, 3389 KB/s, 192 seconds passed
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 .. parsed-literal::
 
-    ... 93%, 653184 KB, 3389 KB/s, 192 seconds passed
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 .. parsed-literal::
 
-    ... 93%, 653376 KB, 3389 KB/s, 192 seconds passed
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 .. parsed-literal::
 
-    ... 93%, 653568 KB, 3389 KB/s, 192 seconds passed
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-... 93%, 653696 KB, 3389 KB/s, 192 seconds passed
+    ... 93%, 652672 KB, 3677 KB/s, 177 seconds passed
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 .. parsed-literal::
 
-    ... 93%, 653728 KB, 3389 KB/s, 192 seconds passed
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+    ... 93%, 652896 KB, 3676 KB/s, 177 seconds passed
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 .. parsed-literal::
 
-    ... 94%, 653920 KB, 3389 KB/s, 192 seconds passed
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+    ... 93%, 653056 KB, 3676 KB/s, 177 seconds passed
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 .. parsed-literal::
 
-    ... 94%, 654016 KB, 3389 KB/s, 192 seconds passed
-... 94%, 654048 KB, 3389 KB/s, 192 seconds passed
-... 94%, 654080 KB, 3389 KB/s, 192 seconds passed
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+    ... 93%, 653248 KB, 3677 KB/s, 177 seconds passed
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+... 93%, 653408 KB, 3676 KB/s, 177 seconds passed
 
 .. parsed-literal::
 
-    ... 94%, 654144 KB, 3388 KB/s, 193 seconds passed
+    ... 93%, 653440 KB, 3676 KB/s, 177 seconds passed
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 .. parsed-literal::
 
-    ... 94%, 654176 KB, 3388 KB/s, 193 seconds passed
-... 94%, 654208 KB, 3387 KB/s, 193 seconds passed
+    ... 93%, 653632 KB, 3677 KB/s, 177 seconds passed
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 .. parsed-literal::
 
-    ... 94%, 654240 KB, 3387 KB/s, 193 seconds passed
-... 94%, 654272 KB, 3387 KB/s, 193 seconds passed
+    ... 94%, 653792 KB, 3676 KB/s, 177 seconds passed
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+... 94%, 653984 KB, 3677 KB/s, 177 seconds passed
 
 .. parsed-literal::
 
-    ... 94%, 654304 KB, 3387 KB/s, 193 seconds passed
-... 94%, 654336 KB, 3387 KB/s, 193 seconds passed
-... 94%, 654368 KB, 3386 KB/s, 193 seconds passed
-... 94%, 654400 KB, 3386 KB/s, 193 seconds passed
+    ... 94%, 654016 KB, 3677 KB/s, 177 seconds passed
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+... 94%, 654144 KB, 3677 KB/s, 177 seconds passed
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 .. parsed-literal::
 
-    ... 94%, 654432 KB, 3386 KB/s, 193 seconds passed
-... 94%, 654464 KB, 3386 KB/s, 193 seconds passed
-... 94%, 654496 KB, 3386 KB/s, 193 seconds passed
+    ... 94%, 654208 KB, 3677 KB/s, 177 seconds passed
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+... 94%, 654336 KB, 3677 KB/s, 177 seconds passed
+... 94%, 654368 KB, 3677 KB/s, 177 seconds passed
+... 94%, 654400 KB, 3677 KB/s, 177 seconds passed
 
 .. parsed-literal::
 
-    ... 94%, 654528 KB, 3386 KB/s, 193 seconds passed
-... 94%, 654560 KB, 3386 KB/s, 193 seconds passed
-... 94%, 654592 KB, 3386 KB/s, 193 seconds passed
-... 94%, 654624 KB, 3386 KB/s, 193 seconds passed
-... 94%, 654656 KB, 3386 KB/s, 193 seconds passed
+    ... 94%, 654432 KB, 3677 KB/s, 177 seconds passed
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+... 94%, 654528 KB, 3677 KB/s, 178 seconds passed
+... 94%, 654560 KB, 3677 KB/s, 178 seconds passed
 
 .. parsed-literal::
 
-    ... 94%, 654688 KB, 3386 KB/s, 193 seconds passed
-... 94%, 654720 KB, 3386 KB/s, 193 seconds passed
-... 94%, 654752 KB, 3386 KB/s, 193 seconds passed
+    ... 94%, 654592 KB, 3677 KB/s, 178 seconds passed
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+... 94%, 654720 KB, 3677 KB/s, 178 seconds passed
+... 94%, 654752 KB, 3677 KB/s, 178 seconds passed
 
 .. parsed-literal::
 
-    ... 94%, 654784 KB, 3385 KB/s, 193 seconds passed
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 .. parsed-literal::
 
-    ... 94%, 655008 KB, 3385 KB/s, 193 seconds passed
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 .. parsed-literal::
 
-    ... 94%, 655104 KB, 3385 KB/s, 193 seconds passed
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 .. parsed-literal::
 
-    ... 94%, 655360 KB, 3385 KB/s, 193 seconds passed
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 .. parsed-literal::
 
-    ... 94%, 655488 KB, 3385 KB/s, 193 seconds passed
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 .. parsed-literal::
 
-    ... 94%, 655712 KB, 3386 KB/s, 193 seconds passed
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 .. parsed-literal::
 
-    ... 94%, 655872 KB, 3386 KB/s, 193 seconds passed
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 .. parsed-literal::
 
-    ... 94%, 656096 KB, 3386 KB/s, 193 seconds passed
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 .. parsed-literal::
 
-    ... 94%, 656256 KB, 3386 KB/s, 193 seconds passed
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 .. parsed-literal::
 
-    ... 94%, 656480 KB, 3386 KB/s, 193 seconds passed
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 .. parsed-literal::
 
-    ... 94%, 656640 KB, 3386 KB/s, 193 seconds passed
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 .. parsed-literal::
 
-    ... 94%, 656832 KB, 3386 KB/s, 193 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 94%, 660064 KB, 3387 KB/s, 194 seconds passed
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 .. parsed-literal::
 
-    ... 94%, 660192 KB, 3387 KB/s, 194 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 95%, 660800 KB, 3388 KB/s, 195 seconds passed
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 .. parsed-literal::
 
-    ... 95%, 660960 KB, 3388 KB/s, 195 seconds passed
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-... 95%, 661152 KB, 3388 KB/s, 195 seconds passed
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+... 95%, 661120 KB, 3677 KB/s, 179 seconds passed
+... 95%, 661152 KB, 3677 KB/s, 179 seconds passed
 
 .. parsed-literal::
 
-    ... 95%, 661184 KB, 3388 KB/s, 195 seconds passed
-... 95%, 661216 KB, 3388 KB/s, 195 seconds passed
-... 95%, 661248 KB, 3388 KB/s, 195 seconds passed
-... 95%, 661280 KB, 3388 KB/s, 195 seconds passed
+    ... 95%, 661184 KB, 3677 KB/s, 179 seconds passed
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+... 95%, 661312 KB, 3677 KB/s, 179 seconds passed
+... 95%, 661344 KB, 3677 KB/s, 179 seconds passed
+... 95%, 661376 KB, 3677 KB/s, 179 seconds passed
 
 .. parsed-literal::
 
-    ... 95%, 661312 KB, 3388 KB/s, 195 seconds passed
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-... 95%, 661504 KB, 3388 KB/s, 195 seconds passed
+    ... 95%, 661408 KB, 3677 KB/s, 179 seconds passed
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+... 95%, 661504 KB, 3677 KB/s, 179 seconds passed
+... 95%, 661536 KB, 3677 KB/s, 179 seconds passed
+... 95%, 661568 KB, 3677 KB/s, 179 seconds passed
 
 .. parsed-literal::
 
-    ... 95%, 661536 KB, 3388 KB/s, 195 seconds passed
-... 95%, 661568 KB, 3388 KB/s, 195 seconds passed
-... 95%, 661600 KB, 3388 KB/s, 195 seconds passed
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+    ... 95%, 661600 KB, 3677 KB/s, 179 seconds passed
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+... 95%, 661696 KB, 3677 KB/s, 179 seconds passed
+... 95%, 661728 KB, 3677 KB/s, 179 seconds passed
+... 95%, 661760 KB, 3677 KB/s, 179 seconds passed
 
 .. parsed-literal::
 
-    ... 95%, 661696 KB, 3388 KB/s, 195 seconds passed
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-... 95%, 661824 KB, 3388 KB/s, 195 seconds passed
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-... 95%, 661888 KB, 3388 KB/s, 195 seconds passed
+    ... 95%, 661792 KB, 3677 KB/s, 179 seconds passed
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+... 95%, 661856 KB, 3677 KB/s, 179 seconds passed
+... 95%, 661888 KB, 3677 KB/s, 179 seconds passed
+... 95%, 661920 KB, 3677 KB/s, 180 seconds passed
 
 .. parsed-literal::
 
-    ... 95%, 661920 KB, 3388 KB/s, 195 seconds passed
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+... 95%, 662080 KB, 3677 KB/s, 180 seconds passed
+... 95%, 662112 KB, 3677 KB/s, 180 seconds passed
+... 95%, 662144 KB, 3677 KB/s, 180 seconds passed
 
 .. parsed-literal::
 
-    ... 95%, 662080 KB, 3388 KB/s, 195 seconds passed
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+... 95%, 662272 KB, 3677 KB/s, 180 seconds passed
+... 95%, 662304 KB, 3677 KB/s, 180 seconds passed
 
 .. parsed-literal::
 
-    ... 95%, 662304 KB, 3388 KB/s, 195 seconds passed
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+... 95%, 662464 KB, 3677 KB/s, 180 seconds passed
+... 95%, 662496 KB, 3677 KB/s, 180 seconds passed
+... 95%, 662528 KB, 3677 KB/s, 180 seconds passed
 
 .. parsed-literal::
 
-    ... 95%, 662464 KB, 3388 KB/s, 195 seconds passed
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+... 95%, 662656 KB, 3677 KB/s, 180 seconds passed
+... 95%, 662688 KB, 3677 KB/s, 180 seconds passed
 
 .. parsed-literal::
 
-    ... 95%, 662688 KB, 3389 KB/s, 195 seconds passed
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+... 95%, 662848 KB, 3677 KB/s, 180 seconds passed
+... 95%, 662880 KB, 3677 KB/s, 180 seconds passed
 
 .. parsed-literal::
 
-    ... 95%, 662848 KB, 3388 KB/s, 195 seconds passed
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-... 95%, 663008 KB, 3389 KB/s, 195 seconds passed
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+... 95%, 663008 KB, 3677 KB/s, 180 seconds passed
+... 95%, 663040 KB, 3677 KB/s, 180 seconds passed
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 .. parsed-literal::
 
-    ... 95%, 663040 KB, 3389 KB/s, 195 seconds passed
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+... 95%, 663200 KB, 3677 KB/s, 180 seconds passed
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+... 95%, 663264 KB, 3677 KB/s, 180 seconds passed
 
 .. parsed-literal::
 
-    ... 95%, 663232 KB, 3389 KB/s, 195 seconds passed
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 .. parsed-literal::
 
-    ... 95%, 663392 KB, 3389 KB/s, 195 seconds passed
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 .. parsed-literal::
 
-    ... 95%, 663616 KB, 3389 KB/s, 195 seconds passed
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 .. parsed-literal::
 
-    ... 95%, 663776 KB, 3389 KB/s, 195 seconds passed
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 .. parsed-literal::
 
-    ... 95%, 664000 KB, 3389 KB/s, 195 seconds passed
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 .. parsed-literal::
 
-    ... 95%, 664160 KB, 3389 KB/s, 195 seconds passed
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 .. parsed-literal::
 
-    ... 95%, 664384 KB, 3389 KB/s, 196 seconds passed
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 .. parsed-literal::
 
-    ... 95%, 664544 KB, 3389 KB/s, 196 seconds passed
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 .. parsed-literal::
 
-    ... 95%, 664768 KB, 3389 KB/s, 196 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 95%, 665120 KB, 3389 KB/s, 196 seconds passed
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 .. parsed-literal::
 
-    ... 95%, 665280 KB, 3389 KB/s, 196 seconds passed
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 .. parsed-literal::
 
-    ... 95%, 665504 KB, 3390 KB/s, 196 seconds passed
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 .. parsed-literal::
 
-    ... 95%, 665664 KB, 3390 KB/s, 196 seconds passed
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 .. parsed-literal::
 
-    ... 95%, 665888 KB, 3390 KB/s, 196 seconds passed
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 .. parsed-literal::
 
-    ... 95%, 666048 KB, 3390 KB/s, 196 seconds passed
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 .. parsed-literal::
 
-    ... 95%, 666272 KB, 3390 KB/s, 196 seconds passed
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 .. parsed-literal::
 
-    ... 95%, 666432 KB, 3390 KB/s, 196 seconds passed
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+... 95%, 666656 KB, 3677 KB/s, 181 seconds passed
 
 .. parsed-literal::
 
-    ... 95%, 666656 KB, 3390 KB/s, 196 seconds passed
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+    ... 95%, 666688 KB, 3677 KB/s, 181 seconds passed
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+... 95%, 666848 KB, 3677 KB/s, 181 seconds passed
+... 95%, 666880 KB, 3677 KB/s, 181 seconds passed
 
 .. parsed-literal::
 
-    ... 95%, 666816 KB, 3390 KB/s, 196 seconds passed
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-... 95%, 667008 KB, 3390 KB/s, 196 seconds passed
+    ... 95%, 666912 KB, 3677 KB/s, 181 seconds passed
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+... 95%, 667008 KB, 3677 KB/s, 181 seconds passed
+... 95%, 667040 KB, 3677 KB/s, 181 seconds passed
 
 .. parsed-literal::
 
-    ... 95%, 667040 KB, 3390 KB/s, 196 seconds passed
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-... 95%, 667104 KB, 3390 KB/s, 196 seconds passed
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+    ... 95%, 667072 KB, 3677 KB/s, 181 seconds passed
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+... 95%, 667200 KB, 3677 KB/s, 181 seconds passed
+... 95%, 667232 KB, 3677 KB/s, 181 seconds passed
+... 95%, 667264 KB, 3677 KB/s, 181 seconds passed
 
 .. parsed-literal::
 
-    ... 95%, 667168 KB, 3390 KB/s, 196 seconds passed
-... 95%, 667200 KB, 3390 KB/s, 196 seconds passed
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-... 95%, 667296 KB, 3390 KB/s, 196 seconds passed
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+    ... 95%, 667296 KB, 3677 KB/s, 181 seconds passed
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+... 95%, 667360 KB, 3677 KB/s, 181 seconds passed
+... 95%, 667392 KB, 3677 KB/s, 181 seconds passed
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 .. parsed-literal::
 
-    ... 95%, 667392 KB, 3390 KB/s, 196 seconds passed
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+... 95%, 667616 KB, 3677 KB/s, 181 seconds passed
 
 .. parsed-literal::
 
-    ... 95%, 667552 KB, 3390 KB/s, 196 seconds passed
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-... 95%, 667680 KB, 3390 KB/s, 196 seconds passed
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 .. parsed-literal::
 
-    ... 96%, 667776 KB, 3391 KB/s, 196 seconds passed
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+... 96%, 667968 KB, 3677 KB/s, 181 seconds passed
+... 96%, 668000 KB, 3677 KB/s, 181 seconds passed
 
 .. parsed-literal::
 
-    ... 96%, 667936 KB, 3391 KB/s, 196 seconds passed
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 .. parsed-literal::
 
-    ... 96%, 668128 KB, 3391 KB/s, 197 seconds passed
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 .. parsed-literal::
 
-    ... 96%, 668320 KB, 3391 KB/s, 197 seconds passed
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+... 96%, 668544 KB, 3677 KB/s, 181 seconds passed
 
 .. parsed-literal::
 
-    ... 96%, 668512 KB, 3391 KB/s, 197 seconds passed
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 .. parsed-literal::
 
-    ... 96%, 668704 KB, 3391 KB/s, 197 seconds passed
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+... 96%, 668928 KB, 3677 KB/s, 181 seconds passed
 
 .. parsed-literal::
 
-    ... 96%, 668896 KB, 3391 KB/s, 197 seconds passed
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 .. parsed-literal::
 
-    ... 96%, 669088 KB, 3391 KB/s, 197 seconds passed
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+... 96%, 669280 KB, 3677 KB/s, 181 seconds passed
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 .. parsed-literal::
 
-    ... 96%, 669280 KB, 3391 KB/s, 197 seconds passed
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 .. parsed-literal::
 
-    ... 96%, 669472 KB, 3391 KB/s, 197 seconds passed
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 .. parsed-literal::
 
-    ... 96%, 669664 KB, 3391 KB/s, 197 seconds passed
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 .. parsed-literal::
 
-    ... 96%, 669856 KB, 3391 KB/s, 197 seconds passed
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 .. parsed-literal::
 
-    ... 96%, 670048 KB, 3391 KB/s, 197 seconds passed
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 .. parsed-literal::
 
-    ... 96%, 670240 KB, 3391 KB/s, 197 seconds passed
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 .. parsed-literal::
 
-    ... 96%, 670400 KB, 3392 KB/s, 197 seconds passed
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 .. parsed-literal::
 
-    ... 96%, 670624 KB, 3392 KB/s, 197 seconds passed
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 .. parsed-literal::
 
-    ... 96%, 670784 KB, 3392 KB/s, 197 seconds passed
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 .. parsed-literal::
 
-    ... 96%, 670976 KB, 3392 KB/s, 197 seconds passed
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 .. parsed-literal::
 
-    ... 96%, 671168 KB, 3392 KB/s, 197 seconds passed
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 .. parsed-literal::
 
-    ... 96%, 671360 KB, 3392 KB/s, 197 seconds passed
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 .. parsed-literal::
 
-    ... 96%, 671552 KB, 3392 KB/s, 197 seconds passed
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 .. parsed-literal::
 
-    ... 96%, 671744 KB, 3392 KB/s, 197 seconds passed
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 .. parsed-literal::
 
-    ... 96%, 671936 KB, 3392 KB/s, 198 seconds passed
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 .. parsed-literal::
 
-    ... 96%, 672128 KB, 3392 KB/s, 198 seconds passed
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 .. parsed-literal::
 
-    ... 96%, 672288 KB, 3392 KB/s, 198 seconds passed
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 .. parsed-literal::
 
-    ... 96%, 672512 KB, 3392 KB/s, 198 seconds passed
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 .. parsed-literal::
 
-    ... 96%, 672672 KB, 3392 KB/s, 198 seconds passed
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 .. parsed-literal::
 
-    ... 96%, 672896 KB, 3393 KB/s, 198 seconds passed
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 .. parsed-literal::
 
-    ... 96%, 673056 KB, 3393 KB/s, 198 seconds passed
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 .. parsed-literal::
 
-    ... 96%, 673280 KB, 3393 KB/s, 198 seconds passed
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 .. parsed-literal::
 
-    ... 96%, 673440 KB, 3393 KB/s, 198 seconds passed
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-... 96%, 673536 KB, 3393 KB/s, 198 seconds passed
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+    ... 96%, 673504 KB, 3677 KB/s, 183 seconds passed
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+... 96%, 673632 KB, 3677 KB/s, 183 seconds passed
+... 96%, 673664 KB, 3677 KB/s, 183 seconds passed
 
 .. parsed-literal::
 
-    ... 96%, 673632 KB, 3393 KB/s, 198 seconds passed
-... 96%, 673664 KB, 3393 KB/s, 198 seconds passed
-... 96%, 673696 KB, 3393 KB/s, 198 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 96%, 674400 KB, 3393 KB/s, 198 seconds passed
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 .. parsed-literal::
 
-    ... 96%, 674560 KB, 3393 KB/s, 198 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 97%, 675168 KB, 3394 KB/s, 198 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 97%, 678944 KB, 3395 KB/s, 199 seconds passed
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 .. parsed-literal::
 
-    ... 97%, 679136 KB, 3395 KB/s, 200 seconds passed
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 .. parsed-literal::
 
-    ... 97%, 679296 KB, 3395 KB/s, 200 seconds passed
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 .. parsed-literal::
 
-    ... 97%, 679488 KB, 3395 KB/s, 200 seconds passed
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 .. parsed-literal::
 
-    ... 97%, 679680 KB, 3395 KB/s, 200 seconds passed
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 .. parsed-literal::
 
-    ... 97%, 679872 KB, 3395 KB/s, 200 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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@@ -34428,7 +33554,7 @@ ds passed
 
 .. parsed-literal::
 
-    ... 100%, 3 KB, 14284 KB/s, 0 seconds passed
+    ... 100%, 3 KB, 13660 KB/s, 0 seconds passed
 
 
     ========== Replacing text in model/public/text-recognition-resnet-fc/vedastr/models/heads/__init__.py
@@ -34500,7 +33626,7 @@ Converting text-recognition-resnet-fc…
 .. parsed-literal::
 
     ========== Converting text-recognition-resnet-fc to ONNX
-    Conversion to ONNX command: /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/bin/python -- /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/openvino/model_zoo/internal_scripts/pytorch_to_onnx.py --model-path=/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/openvino/model_zoo/models/public/text-recognition-resnet-fc --model-path=model/public/text-recognition-resnet-fc --model-name=get_model --import-module=model '--model-param=file_config=r"model/public/text-recognition-resnet-fc/vedastr/configs/resnet_fc.py"' '--model-param=weights=r"model/public/text-recognition-resnet-fc/vedastr/ckpt/resnet_fc.pth"' --input-shape=1,1,32,100 --input-names=input --output-names=output --output-file=model/public/text-recognition-resnet-fc/resnet_fc.onnx
+    Conversion to ONNX command: /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/bin/python -- /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/openvino/model_zoo/internal_scripts/pytorch_to_onnx.py --model-path=/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/openvino/model_zoo/models/public/text-recognition-resnet-fc --model-path=model/public/text-recognition-resnet-fc --model-name=get_model --import-module=model '--model-param=file_config=r"model/public/text-recognition-resnet-fc/vedastr/configs/resnet_fc.py"' '--model-param=weights=r"model/public/text-recognition-resnet-fc/vedastr/ckpt/resnet_fc.pth"' --input-shape=1,1,32,100 --input-names=input --output-names=output --output-file=model/public/text-recognition-resnet-fc/resnet_fc.onnx
 
 
 
@@ -34513,7 +33639,7 @@ Converting text-recognition-resnet-fc…
 
 
     ========== Converting text-recognition-resnet-fc to IR (FP16)
-    Conversion command: /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/bin/python -- /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/bin/mo --framework=onnx --output_dir=model/public/text-recognition-resnet-fc/FP16 --model_name=text-recognition-resnet-fc --input=input '--mean_values=input[127.5]' '--scale_values=input[127.5]' --output=output --input_model=model/public/text-recognition-resnet-fc/resnet_fc.onnx '--layout=input(NCHW)' '--input_shape=[1, 1, 32, 100]' --compress_to_fp16=True
+    Conversion command: /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/bin/python -- /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/bin/mo --framework=onnx --output_dir=model/public/text-recognition-resnet-fc/FP16 --model_name=text-recognition-resnet-fc --input=input '--mean_values=input[127.5]' '--scale_values=input[127.5]' --output=output --input_model=model/public/text-recognition-resnet-fc/resnet_fc.onnx '--layout=input(NCHW)' '--input_shape=[1, 1, 32, 100]' --compress_to_fp16=True
 
 
 
@@ -34530,8 +33656,9 @@ Converting text-recognition-resnet-fc…
 .. parsed-literal::
 
     [ SUCCESS ] Generated IR version 11 model.
-    [ SUCCESS ] XML file: /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/208-optical-character-recognition/model/public/text-recognition-resnet-fc/FP16/text-recognition-resnet-fc.xml
-    [ SUCCESS ] BIN file: /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/208-optical-character-recognition/model/public/text-recognition-resnet-fc/FP16/text-recognition-resnet-fc.bin
+    [ SUCCESS ] XML file: /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/notebooks/208-optical-character-recognition/model/public/text-recognition-resnet-fc/FP16/text-recognition-resnet-fc.xml
+    [ SUCCESS ] BIN file: /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/notebooks/208-optical-character-recognition/model/public/text-recognition-resnet-fc/FP16/text-recognition-resnet-fc.bin
+
 
 
 Select inference device
diff --git a/docs/notebooks/208-optical-character-recognition-with-output_files/index.html.tmp b/docs/notebooks/208-optical-character-recognition-with-output_files/index.html.tmp
deleted file mode 100644
index 06c0119681f1ab..00000000000000
--- a/docs/notebooks/208-optical-character-recognition-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,20 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/208-optical-character-recognition-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/208-optical-character-recognition-with-output_files/
../
-208-optical-character-recognition-with-output_1..> 26-Jan-2024 01:05              305482
-208-optical-character-recognition-with-output_2..> 26-Jan-2024 01:05              923631
-208-optical-character-recognition-with-output_2..> 26-Jan-2024 01:05                1996
-208-optical-character-recognition-with-output_2..> 26-Jan-2024 01:05               11367
-208-optical-character-recognition-with-output_2..> 26-Jan-2024 01:05                1990
-208-optical-character-recognition-with-output_2..> 26-Jan-2024 01:05               11142
-208-optical-character-recognition-with-output_2..> 26-Jan-2024 01:05                1630
-208-optical-character-recognition-with-output_2..> 26-Jan-2024 01:05                8428
-208-optical-character-recognition-with-output_2..> 26-Jan-2024 01:05                 949
-208-optical-character-recognition-with-output_2..> 26-Jan-2024 01:05                2274
-208-optical-character-recognition-with-output_2..> 26-Jan-2024 01:05                 817
-208-optical-character-recognition-with-output_2..> 26-Jan-2024 01:05                1559
-208-optical-character-recognition-with-output_2..> 26-Jan-2024 01:05                 838
-208-optical-character-recognition-with-output_2..> 26-Jan-2024 01:05                1487
-

-
diff --git a/docs/notebooks/209-handwritten-ocr-with-output.rst b/docs/notebooks/209-handwritten-ocr-with-output.rst
index 4f0d55e4a8101c..5812496245a1ce 100644
--- a/docs/notebooks/209-handwritten-ocr-with-output.rst
+++ b/docs/notebooks/209-handwritten-ocr-with-output.rst
@@ -8,9 +8,9 @@ Latin alphabet is available in `notebook
 This model is capable of processing only one line of symbols at a time.
 
 The models used in this notebook are
-`handwritten-japanese-recognition-0001 `__
+`handwritten-japanese-recognition-0001 `__
 and
-`handwritten-simplified-chinese-0001 `__.
+`handwritten-simplified-chinese-0001 `__.
 To decode model outputs as readable text
 `kondate_nakayosi `__
 and
@@ -62,12 +62,12 @@ Imports
 
     from collections import namedtuple
     from itertools import groupby
-    
+
     import cv2
     import matplotlib.pyplot as plt
     import numpy as np
     import openvino as ov
-    
+
     # Fetch `notebook_utils` module
     import urllib.request
     urllib.request.urlretrieve(
@@ -89,7 +89,7 @@ Set up all constants and folders used in this notebook
     base_models_dir = "models"
     data_folder = "data"
     charlist_folder = f"{data_folder}/text"
-    
+
     # Precision used by the model.
     precision = "FP16"
 
@@ -127,9 +127,9 @@ If you want to perform OCR on a text in Japanese, set
 
     # Select the language by using either language="chinese" or language="japanese".
     language = "chinese"
-    
+
     languages = {"chinese": chinese_files, "japanese": japanese_files}
-    
+
     selected_language = languages.get(language)
 
 Download the Model
@@ -196,14 +196,14 @@ select device from dropdown list for running inference using OpenVINO
 .. code:: ipython3
 
     import ipywidgets as widgets
-    
+
     device = widgets.Dropdown(
         options=core.available_devices + ["AUTO"],
         value='AUTO',
         description='Device:',
         disabled=False,
     )
-    
+
     device
 
 
@@ -252,32 +252,32 @@ keep letters proportional and meet input shape.
         "https://storage.openvinotoolkit.org/repositories/openvino_notebooks/data/data/image/" + selected_language.demo_image_name,
         directory=data_folder
     )
-    
+
     # Text detection models expect an image in grayscale format.
     # IMPORTANT! This model enables reading only one line at time.
-    
+
     # Read the image.
     image = cv2.imread(filename=str(file_name), flags=cv2.IMREAD_GRAYSCALE)
-    
+
     # Fetch the shape.
     image_height, _ = image.shape
-    
+
     # B,C,H,W = batch size, number of channels, height, width.
     _, _, H, W = recognition_input_layer.shape
-    
+
     # Calculate scale ratio between the input shape height and image height to resize the image.
     scale_ratio = H / image_height
-    
+
     # Resize the image to expected input sizes.
     resized_image = cv2.resize(
         image, None, fx=scale_ratio, fy=scale_ratio, interpolation=cv2.INTER_AREA
     )
-    
+
     # Pad the image to match input size, without changing aspect ratio.
     resized_image = np.pad(
         resized_image, ((0, 0), (0, W - resized_image.shape[1])), mode="edge"
     )
-    
+
     # Reshape to network input shape.
     input_image = resized_image[None, None, :, :]
 
@@ -335,10 +335,10 @@ Chinese and Japanese models.
 
     # Get a dictionary to encode the output, based on model documentation.
     used_charlist = selected_language.charlist_name
-    
+
     # With both models, there should be blank symbol added at index 0 of each charlist.
     blank_char = "~"
-    
+
     with used_charlist_file.open(mode="r", encoding="utf-8") as charlist:
         letters = blank_char + "".join(line.strip() for line in charlist)
 
@@ -380,7 +380,7 @@ Finally, get the symbols from corresponding indexes in the charlist.
 
     # Remove a batch dimension.
     predictions = np.squeeze(predictions)
-    
+
     # Run the `argmax` function to pick the symbols with the highest probability.
     predictions_indexes = np.argmax(predictions, axis=1)
 
@@ -388,13 +388,13 @@ Finally, get the symbols from corresponding indexes in the charlist.
 
     # Use the `groupby` function to remove concurrent letters, as required by CTC greedy decoding.
     output_text_indexes = list(groupby(predictions_indexes))
-    
+
     # Remove grouper objects.
     output_text_indexes, _ = np.transpose(output_text_indexes, (1, 0))
-    
+
     # Remove blank symbols.
     output_text_indexes = output_text_indexes[output_text_indexes != 0]
-    
+
     # Assign letters to indexes from the output array.
     output_text = [letters[letter_index] for letter_index in output_text_indexes]
 
@@ -411,7 +411,7 @@ the image with predicted text printed below.
     plt.figure(figsize=(20, 1))
     plt.axis("off")
     plt.imshow(resized_image, cmap="gray", vmin=0, vmax=255)
-    
+
     print("".join(output_text))
 
 
diff --git a/docs/notebooks/209-handwritten-ocr-with-output_files/index.html.tmp b/docs/notebooks/209-handwritten-ocr-with-output_files/index.html.tmp
deleted file mode 100644
index 6c47e2eb382649..00000000000000
--- a/docs/notebooks/209-handwritten-ocr-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,8 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/209-handwritten-ocr-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/209-handwritten-ocr-with-output_files/
../
-209-handwritten-ocr-with-output_22_0.png           26-Jan-2024 01:05               53571
-209-handwritten-ocr-with-output_32_1.png           26-Jan-2024 01:05               53571
-

-
diff --git a/docs/notebooks/210-slowfast-video-recognition-with-output.rst b/docs/notebooks/210-slowfast-video-recognition-with-output.rst
index 3b46e142a5397e..0c9edf604cabf2 100644
--- a/docs/notebooks/210-slowfast-video-recognition-with-output.rst
+++ b/docs/notebooks/210-slowfast-video-recognition-with-output.rst
@@ -87,7 +87,7 @@ Imports and Settings
     from typing import Any, List, Dict
     from IPython.display import Video
     import openvino as ov
-
+    
     sys.path.append("../utils")
     from notebook_utils import download_file
 
@@ -111,15 +111,15 @@ each action. Read more about the dataset and the paper
     MODEL_NAME = "slowfast_r50"
     MODEL_REPOSITORY = "facebookresearch/pytorchvideo"
     DEVICE = "cpu"
-
+    
     # load the pretrained model from the repository
     model = torch.hub.load(
         repo_or_dir=MODEL_REPOSITORY, model=MODEL_NAME, pretrained=True, skip_validation=True
     )
-
+    
     # set the device to allocate tensors to. for example, "cpu" or "cuda"
     model.to(DEVICE)
-
+    
     # set the model to eval mode
     model.eval()
 
@@ -471,13 +471,13 @@ mapping to a dict for later use.
         "https://dl.fbaipublicfiles.com/pyslowfast/dataset/class_names/kinetics_classnames.json"
     )
     CLASSNAMES_FILE = "kinetics_classnames.json"
-
+    
     download_file(url=CLASSNAMES_SOURCE, directory=DATA_DIR, show_progress=True)
-
+    
     # load from json
     with open(DATA_DIR / CLASSNAMES_FILE, "r") as f:
         kinetics_classnames = json.load(f)
-
+    
     # load dict of id to class label mapping
     kinetics_id_to_classname = {}
     for k, v in kinetics_classnames.items():
@@ -498,7 +498,7 @@ the downloaded video.
     VIDEO_SOURCE = "https://dl.fbaipublicfiles.com/pytorchvideo/projects/archery.mp4"
     VIDEO_NAME = "archery.mp4"
     VIDEO_PATH = DATA_DIR / VIDEO_NAME
-
+    
     download_file(url=VIDEO_SOURCE, directory=DATA_DIR, show_progress=True)
     Video(VIDEO_PATH, embed=True)
 
@@ -550,8 +550,8 @@ helper functions to implement the preprocessing steps.
             new_width = int(math.floor((float(width) / height) * size))
         scaled = cv2.resize(frame, (new_width, new_height), interpolation=cv2.INTER_LINEAR)
         return scaled.astype(np.float32)
-
-
+    
+    
     def center_crop(size: int, frame: np.ndarray) -> np.ndarray:
         """
         Center crop the input frame to size.
@@ -564,8 +564,8 @@ helper functions to implement the preprocessing steps.
         assert cropped.shape[0] == size, "Image height not cropped properly"
         assert cropped.shape[1] == size, "Image width not cropped properly"
         return cropped
-
-
+    
+    
     def normalize(array: np.ndarray, mean: List[float], std: List[float]) -> np.ndarray:
         """
         Normalize a given array by subtracting the mean and dividing the std.
@@ -578,8 +578,8 @@ helper functions to implement the preprocessing steps.
         array = array - mean
         array = array / std
         return array
-
-
+    
+    
     def pack_pathway_output(frames: np.ndarray, alpha: int = 4) -> List[np.ndarray]:
         """
         Prepare output as a list of arrays, each corresponding
@@ -594,8 +594,8 @@ helper functions to implement the preprocessing steps.
         )
         frame_list = [slow_pathway, fast_pathway]
         return frame_list
-
-
+    
+    
     def process_inputs(
         frames: List[np.ndarray],
         num_frames: int,
@@ -661,7 +661,7 @@ model.
         inputs = process_inputs(
             frames=frames, num_frames=num_frames, crop_size=crop_size, mean=mean, std=std
         )
-
+    
         if isinstance(model, ov.CompiledModel):
             # openvino compiled model
             output_blob = model.output(0)
@@ -670,17 +670,17 @@ model.
             # pytorch model
             predictions = model([torch.from_numpy(inp) for inp in inputs])
             predictions = predictions.detach().cpu().numpy()
-
+    
         def softmax(x):
             return (np.exp(x) / np.exp(x).sum(axis=None))
-
+    
         # apply activation
         predictions = softmax(predictions)
-
+    
         # top k predicted class IDs
         topk = 5
         pred_classes = np.argsort(-1 * predictions, axis=1)[:, :topk]
-
+    
         # Map the predicted classes to the label names
         pred_class_names = [id_to_label_mapping[int(i)] for i in pred_classes[0]]
         return pred_class_names
@@ -696,7 +696,7 @@ inference using the same. The top 5 predictions can be seen below.
     MEAN = [0.45, 0.45, 0.45]
     STD = [0.225, 0.225, 0.225]
     TOP_K = 5
-
+    
     predictions = run_inference(
         model=model,
         video_path=str(VIDEO_PATH),
@@ -708,7 +708,7 @@ inference using the same. The top 5 predictions can be seen below.
         mean=MEAN,
         std=STD,
     )
-
+    
     print(f"Predicted labels: {', '.join(predictions)}")
 
 
@@ -737,18 +737,18 @@ either be compiled and inferred or serialized.
         def __init__(self, model):
             super().__init__()
             self.model = model
-
+    
         def forward(self, input):
             return model(list(input))
-
-
+    
+    
     dummy_input = [torch.randn((1, 3, 8, 256, 256)), torch.randn([1, 3, 32, 256, 256])]
-
+    
     model = ov.convert_model(ModelWrapper(model), example_input=(dummy_input,))
     IR_PATH = MODEL_DIR / "slowfast-r50.xml"
-
-
-
+    
+    
+    
     # serialize model for saving IR
     ov.save_model(model=model, output_model=str(IR_PATH), compress_to_fp16=False)
 
@@ -761,7 +761,7 @@ using the ``weights`` parameter.
 .. code:: ipython3
 
     core = ov.Core()
-
+    
     # read converted model
     conv_model = core.read_model(str(IR_PATH))
 
@@ -775,14 +775,14 @@ select device from dropdown list for running inference using OpenVINO
 .. code:: ipython3
 
     import ipywidgets as widgets
-
+    
     device = widgets.Dropdown(
         options=core.available_devices + ["AUTO"],
         value='AUTO',
         description='Device:',
         disabled=False,
     )
-
+    
     device
 
 
diff --git a/docs/notebooks/211-speech-to-text-with-output_files/index.html.tmp b/docs/notebooks/211-speech-to-text-with-output_files/index.html.tmp
deleted file mode 100644
index d4ffc5e7480bc8..00000000000000
--- a/docs/notebooks/211-speech-to-text-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,10 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/211-speech-to-text-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/211-speech-to-text-with-output_files/
../
-211-speech-to-text-with-output_20_0.png            26-Jan-2024 01:05               21796
-211-speech-to-text-with-output_20_2.png            26-Jan-2024 01:05               85260
-211-speech-to-text-with-output_28_0.png            26-Jan-2024 01:05               50178
-211-speech-to-text-with-output_28_1.png            26-Jan-2024 01:05               10083
-

-
diff --git a/docs/notebooks/212-pyannote-speaker-diarization-with-output.rst b/docs/notebooks/212-pyannote-speaker-diarization-with-output.rst
index 5cca20600a54a6..2003edf24b3c74 100644
--- a/docs/notebooks/212-pyannote-speaker-diarization-with-output.rst
+++ b/docs/notebooks/212-pyannote-speaker-diarization-with-output.rst
@@ -42,8 +42,6 @@ Table of contents:
 
 -  `Prerequisites <#prerequisites>`__
 -  `Prepare pipeline <#prepare-pipeline>`__
--  `login to huggingfacehub to get access to pre-trained
-   model <#login-to-huggingfacehub-to-get-access-to-pre-trained-model>`__
 -  `Load test audio file <#load-test-audio-file>`__
 -  `Run inference pipeline <#run-inference-pipeline>`__
 -  `Convert model to OpenVINO Intermediate Representation
@@ -66,18 +64,20 @@ Prerequisites
 
 .. parsed-literal::
 
-    DEPRECATION: pytorch-lightning 1.6.5 has a non-standard dependency specifier torch>=1.8.*. pip 24.0 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of pytorch-lightning or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063
+    DEPRECATION: pytorch-lightning 1.6.5 has a non-standard dependency specifier torch>=1.8.*. pip 24.1 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of pytorch-lightning or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063
 
 
 .. parsed-literal::
 
     ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
+    googleapis-common-protos 1.62.0 requires protobuf!=3.20.0,!=3.20.1,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0.dev0,>=3.19.5, but you have protobuf 3.20.1 which is incompatible.
     onnx 1.15.0 requires protobuf>=3.20.2, but you have protobuf 3.20.1 which is incompatible.
     paddlepaddle 2.6.0 requires protobuf>=3.20.2; platform_system != "Windows", but you have protobuf 3.20.1 which is incompatible.
     ppgan 2.1.0 requires imageio==2.9.0, but you have imageio 2.33.1 which is incompatible.
     ppgan 2.1.0 requires librosa==0.8.1, but you have librosa 0.9.2 which is incompatible.
     ppgan 2.1.0 requires opencv-python<=4.6.0.66, but you have opencv-python 4.9.0.80 which is incompatible.
     tensorflow 2.12.0 requires protobuf!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.20.3, but you have protobuf 3.20.1 which is incompatible.
+    tensorflow-metadata 1.14.0 requires protobuf<4.21,>=3.20.3, but you have protobuf 3.20.1 which is incompatible.
 
 
 .. parsed-literal::
@@ -130,14 +130,14 @@ method by providing a path to the directory with pipeline configuration
 or identification from `HuggingFace
 hub `__.
 
-   **Note**: This tutorial uses a non-official version of model
+   **NOTE**: This tutorial uses a non-official version of model
    ``philschmid/pyannote-speaker-diarization-endpoint``, provided only
    for demo purposes. The original model
    (``pyannote/speaker-diarization``) requires you to accept the model
    license before downloading or using its weights, visit the
    `pyannote/speaker-diarization `__
    to read accept the license before you proceed. To use this model, you
-   must be a registered user in 🤗 Hugging Face Hub. You will need to use
+   must be a registered user in Hugging Face Hub. You will need to use
    an access token for the code below to run. For more information on
    access tokens, please refer to `this section of the
    documentation `__.
@@ -148,6 +148,7 @@ hub `__.
 
 
    ## login to huggingfacehub to get access to pre-trained model
+
    from huggingface_hub import notebook_login, whoami
 
    try:
@@ -244,7 +245,7 @@ pipeline
 
 .. parsed-literal::
 
-    Diarization pipeline took 15.77 s
+    Diarization pipeline took 15.72 s
 
 
 The result of running the pipeline can be represented as a diagram
@@ -403,7 +404,7 @@ Run speaker diarization with OpenVINO
 
 .. parsed-literal::
 
-    Diarization pipeline took 15.03 s
+    Diarization pipeline took 15.12 s
 
 
 .. code:: ipython3
diff --git a/docs/notebooks/212-pyannote-speaker-diarization-with-output_files/index.html.tmp b/docs/notebooks/212-pyannote-speaker-diarization-with-output_files/index.html.tmp
deleted file mode 100644
index 0e283d3c9b8c99..00000000000000
--- a/docs/notebooks/212-pyannote-speaker-diarization-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,9 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/212-pyannote-speaker-diarization-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/212-pyannote-speaker-diarization-with-output_files/
../
-212-pyannote-speaker-diarization-with-output_14..> 26-Jan-2024 01:05                7969
-212-pyannote-speaker-diarization-with-output_27..> 26-Jan-2024 01:05                7969
-212-pyannote-speaker-diarization-with-output_9_..> 26-Jan-2024 01:05               43095
-

-
diff --git a/docs/notebooks/213-question-answering-with-output.rst b/docs/notebooks/213-question-answering-with-output.rst
index 35a06d7d34668b..559bece7fda0b4 100644
--- a/docs/notebooks/213-question-answering-with-output.rst
+++ b/docs/notebooks/213-question-answering-with-output.rst
@@ -9,23 +9,27 @@ larger BERT-large model. The model comes from `Open Model
 Zoo `__. Final part
 of this notebook provides live inference results from your inputs.
 
+Table of contents:
+^^^^^^^^^^^^^^^^^^
 
-**Table of contents:**
+-  `Imports <#imports>`__
+-  `The model <#the-model>`__
 
+   -  `Download the model <#download-the-model>`__
+   -  `Load the model <#load-the-model>`__
 
-- `Imports <#imports>`__
-- `The model <#the-model>`__
-- `Download the model <#download-the-model>`__
-- `Load the model <#load-the-model>`__
-- `Select inference device <#select-inference-device>`__
-- `Processing <#processing>`__
-- `Preprocessing <#preprocessing>`__
-- `Postprocessing <#postprocessing>`__
-- `Main Processing Function <#main-processing-function>`__
-- `Run <#run>`__
-- `Run on local paragraphs <#run-on-local-paragraphs>`__
-- `Run on websites <#run-on-websites>`__
+      -  `Select inference device <#select-inference-device>`__
 
+-  `Processing <#processing>`__
+
+   -  `Preprocessing <#preprocessing>`__
+   -  `Postprocessing <#postprocessing>`__
+   -  `Main Processing Function <#main-processing-function>`__
+
+-  `Run <#run>`__
+
+   -  `Run on local paragraphs <#run-on-local-paragraphs>`__
+   -  `Run on websites <#run-on-websites>`__
 
 .. code:: ipython3
 
@@ -34,8 +38,8 @@ of this notebook provides live inference results from your inputs.
 
 .. parsed-literal::
 
-    DEPRECATION: pytorch-lightning 1.6.5 has a non-standard dependency specifier torch>=1.8.*. pip 24.0 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of pytorch-lightning or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063
-
+    DEPRECATION: pytorch-lightning 1.6.5 has a non-standard dependency specifier torch>=1.8.*. pip 24.1 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of pytorch-lightning or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063
+    
 
 .. parsed-literal::
 
@@ -55,7 +59,7 @@ Imports
         url='https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/main/notebooks/utils/notebook_utils.py',
         filename='notebook_utils.py'
     )
-
+    
     from notebook_utils import download_file
 
 .. code:: ipython3
@@ -64,17 +68,17 @@ Imports
     import time
     from urllib import parse
     from pathlib import Path
-
+    
     import numpy as np
     import openvino as ov
-
-
+    
+    
     download_file(
         url='https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/main/notebooks/213-question-answering/html_reader.py',
         filename='html_reader.py'
     )
     import html_reader as reader
-
+    
     download_file(
         url='https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/main/notebooks/213-question-answering/tokens_bert.py',
         filename='tokens_bert.py'
@@ -121,13 +125,13 @@ converted to OpenVINO Intermediate Representation (OpenVINO IR).
 
     MODEL_DIR = Path("model")
     MODEL_DIR.mkdir(exist_ok=True)
-
+    
     model_xml_url = "https://storage.openvinotoolkit.org/repositories/open_model_zoo/2023.0/models_bin/1/bert-small-uncased-whole-word-masking-squad-int8-0002/FP16-INT8/bert-small-uncased-whole-word-masking-squad-int8-0002.xml"
     model_bin_url = "https://storage.openvinotoolkit.org/repositories/open_model_zoo/2023.0/models_bin/1/bert-small-uncased-whole-word-masking-squad-int8-0002/FP16-INT8/bert-small-uncased-whole-word-masking-squad-int8-0002.bin"
-
+    
     download_file(model_xml_url, model_xml_url.split("/")[-1], MODEL_DIR)
     download_file(model_bin_url, model_bin_url.split("/")[-1], MODEL_DIR)
-
+    
     model_path = MODEL_DIR / model_xml_url.split("/")[-1]
 
 
@@ -185,16 +189,16 @@ select device from dropdown list for running inference using OpenVINO
 .. code:: ipython3
 
     import ipywidgets as widgets
-
+    
     core = ov.Core()
-
+    
     device = widgets.Dropdown(
         options=core.available_devices + ["AUTO"],
         value='AUTO',
         description='Device:',
         disabled=False,
     )
-
+    
     device
 
 
@@ -209,11 +213,11 @@ select device from dropdown list for running inference using OpenVINO
 .. code:: ipython3
 
     compiled_model = core.compile_model(model=model, device_name=device.value)
-
+    
     # Get input and output names of nodes.
     input_keys = list(compiled_model.inputs)
     output_keys = list(compiled_model.outputs)
-
+    
     # Get the network input size.
     input_size = compiled_model.input(0).shape[1]
 
@@ -253,16 +257,16 @@ content from provided URLs.
         "https://storage.openvinotoolkit.org/repositories/openvino_notebooks/data/data/text/bert-uncased/vocab.txt",
         directory="data"
     )
-
+    
     # Create a dictionary with words and their indices.
     vocab = tokens.load_vocab_file(str(vocab_file_path))
-
+    
     # Define special tokens.
     cls_token = vocab["[CLS]"]
     pad_token = vocab["[PAD]"]
     sep_token = vocab["[SEP]"]
-
-
+    
+    
     # A function to load text from given urls.
     def load_context(sources):
         input_urls = []
@@ -273,7 +277,7 @@ content from provided URLs.
                 input_urls.append(source)
             else:
                 paragraphs.append(source)
-
+    
         paragraphs.extend(reader.get_paragraphs(input_urls))
         # Produce one big context string.
         return "\n".join(paragraphs)
@@ -322,10 +326,10 @@ documentation  0:
             # Add padding to all the inputs.
             input_ids = input_ids + [pad_token] * diff_input_size
             attention_mask = attention_mask + [0] * diff_input_size
             token_type_ids = token_type_ids + [0] * diff_input_size
-
+    
         return (input_ids, attention_mask, token_type_ids), diff_input_size
 
 Postprocessing
@@ -384,33 +388,33 @@ the context range for the answer.
 
     # Based on https://github.com/openvinotoolkit/open_model_zoo/blob/bf03f505a650bafe8da03d2747a8b55c5cb2ef16/demos/common/python/openvino/model_zoo/model_api/models/bert.py#L163
     def postprocess(output_start, output_end, question_tokens, context_tokens_start_end, padding, start_idx):
-
+    
         def get_score(logits):
             out = np.exp(logits)
             return out / out.sum(axis=-1)
-
+    
         # Get start-end scores for the context.
         score_start = get_score(output_start)
         score_end = get_score(output_end)
-
+    
         # An index of the first context token in a tensor.
         context_start_idx = len(question_tokens) + 2
         # An index of the last+1 context token in a tensor.
         context_end_idx = input_size - padding - 1
-
+    
         # Find product of all start-end combinations to find the best one.
         max_score, max_start, max_end = find_best_answer_window(start_score=score_start,
                                                                 end_score=score_end,
                                                                 context_start_idx=context_start_idx,
                                                                 context_end_idx=context_end_idx)
-
+    
         # Convert to context text start-end index.
         max_start = context_tokens_start_end[max_start + start_idx][0]
         max_end = context_tokens_start_end[max_end + start_idx][1]
-
+    
         return max_score, max_start, max_end
-
-
+    
+    
     # Based on https://github.com/openvinotoolkit/open_model_zoo/blob/bf03f505a650bafe8da03d2747a8b55c5cb2ef16/demos/common/python/openvino/model_zoo/model_api/models/bert.py#L188
     def find_best_answer_window(start_score, end_score, context_start_idx, context_end_idx):
         context_len = context_end_idx - context_start_idx
@@ -425,7 +429,7 @@ the context range for the answer.
         # Find the best start-end pair.
         max_s, max_e = divmod(score_mat.flatten().argmax(), score_mat.shape[1])
         max_score = score_mat[max_s, max_e]
-
+    
         return max_score, max_s, max_e
 
 First, create a list of tokens from the context and the question. Then,
@@ -440,7 +444,7 @@ answer should come with the highest score.
                                                                          vocab=vocab)
         # Convert the question string to tokens.
         question_tokens, _ = tokens.text_to_tokens(text=question.lower(), vocab=vocab)
-
+    
         results = []
         # Iterate through different parts of the context.
         for network_input, padding, start_idx in prepare_input(question_tokens=question_tokens,
@@ -448,7 +452,7 @@ answer should come with the highest score.
             # Get output layers.
             output_start_key = compiled_model.output("output_s")
             output_end_key = compiled_model.output("output_e")
-
+    
             # OpenVINO inference.
             result = compiled_model(network_input)
             # Postprocess the result, getting the score and context range for the answer.
@@ -459,7 +463,7 @@ answer should come with the highest score.
                                           padding=padding,
                                           start_idx=start_idx)
             results.append(score_start_end)
-
+    
         # Find the highest score.
         answer = max(results, key=operator.itemgetter(0))
         # Return the part of the context, which is already an answer.
@@ -478,16 +482,16 @@ iterate through the questions.
     def run_question_answering(sources, example_question=None):
         print(f"Context: {sources}", flush=True)
         context = load_context(sources)
-
+    
         if len(context) == 0:
             print("Error: Empty context or outside paragraphs")
             return
-
+    
         if example_question is not None:
             start_time = time.perf_counter()
             answer, score = get_best_answer(question=example_question, context=context)
             end_time = time.perf_counter()
-
+    
             print(f"Question: {example_question}")
             print(f"Answer: {answer}")
             print(f"Score: {score:.2f}")
@@ -498,12 +502,12 @@ iterate through the questions.
                 # if no question - break
                 if question == "":
                     break
-
+    
                 # measure processing time
                 start_time = time.perf_counter()
                 answer, score = get_best_answer(question=question, context=context)
                 end_time = time.perf_counter()
-
+    
                 print(f"Question: {question}")
                 print(f"Answer: {answer}")
                 print(f"Score: {score:.2f}")
@@ -553,9 +557,9 @@ questions in the box.**
                "and relating those classes to each other. A computational problem is understood to be a task that "
                "is in principle amenable to being solved by a computer, which is equivalent to stating that the "
                "problem may be solved by mechanical application of mathematical steps, such as an algorithm."]
-
+    
     question = "What is the term for a task that generally lends itself to being solved by a computer?"
-
+    
     run_question_answering(sources, example_question=question)
 
 
@@ -569,7 +573,7 @@ questions in the box.**
     Question: What is the term for a task that generally lends itself to being solved by a computer?
     Answer: A computational problem
     Score: 0.53
-    Time: 0.04s
+    Time: 0.03s
 
 
 Run on websites
@@ -599,9 +603,9 @@ questions in the box.**
 .. code:: ipython3
 
     sources = ["https://en.wikipedia.org/wiki/OpenVINO"]
-
+    
     question = "What does OpenVINO mean?"
-
+    
     run_question_answering(sources, example_question=question)
 
 
@@ -613,7 +617,7 @@ questions in the box.**
 .. parsed-literal::
 
     Question: What does OpenVINO mean?
-    Answer: Open Visual Inference and Neural network Optimization
-    Score: 0.95
+    Answer: open-source software toolkit for optimizing and deploying deep learning models
+    Score: 0.06
     Time: 0.06s
 
diff --git a/docs/notebooks/214-grammar-correction-with-output.rst b/docs/notebooks/214-grammar-correction-with-output.rst
index 47273f6b0444bf..9d67d48f770814 100644
--- a/docs/notebooks/214-grammar-correction-with-output.rst
+++ b/docs/notebooks/214-grammar-correction-with-output.rst
@@ -595,14 +595,15 @@ some time to complete.
 
 
 
-.. raw:: html
 
-    

 
 
 
 
+.. raw:: html
 
+    
+    

 
 
 
@@ -613,14 +614,15 @@ some time to complete.
 
 
 
-.. raw:: html
 
-    

 
 
 
 
+.. raw:: html
 
+    
+    

 
 
 
@@ -631,14 +633,15 @@ some time to complete.
 
 
 
-.. raw:: html
 
-    

 
 
 
 
+.. raw:: html
 
+    
+    

 
 
 
@@ -809,5 +812,5 @@ Interactive demo
 
 .. .. raw:: html
 
-..     

+..    

 
diff --git a/docs/notebooks/215-image-inpainting-with-output.rst b/docs/notebooks/215-image-inpainting-with-output.rst
index 931833feacc7d5..f6ce5d5d06c4aa 100644
--- a/docs/notebooks/215-image-inpainting-with-output.rst
+++ b/docs/notebooks/215-image-inpainting-with-output.rst
@@ -63,7 +63,7 @@ Download ``gmcnn-places2-tf``\ model (this step will be skipped if the
 model is already downloaded) and then unzip it. Downloaded model stored
 in TensorFlow frozen graph format. The steps how this frozen graph can
 be obtained from original model checkpoint can be found in this
-`instruction `__
+`instruction `__
 
 .. code:: ipython3
 
diff --git a/docs/notebooks/215-image-inpainting-with-output_files/index.html.tmp b/docs/notebooks/215-image-inpainting-with-output_files/index.html.tmp
deleted file mode 100644
index fbeb5bde43da2a..00000000000000
--- a/docs/notebooks/215-image-inpainting-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,10 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/215-image-inpainting-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/215-image-inpainting-with-output_files/
../
-215-image-inpainting-with-output_15_0.png          26-Jan-2024 01:05               16186
-215-image-inpainting-with-output_17_0.png          26-Jan-2024 01:05              544222
-215-image-inpainting-with-output_19_0.png          26-Jan-2024 01:05              492981
-215-image-inpainting-with-output_23_0.png          26-Jan-2024 01:05              593391
-

-
diff --git a/docs/notebooks/216-attention-center-with-output.rst b/docs/notebooks/216-attention-center-with-output.rst
index d2a2eee3d2a236..6ef7808432b0ad 100644
--- a/docs/notebooks/216-attention-center-with-output.rst
+++ b/docs/notebooks/216-attention-center-with-output.rst
@@ -73,14 +73,14 @@ Table of contents:
 
 .. parsed-literal::
 
-    Requirement already satisfied: openvino>=2023.2.0 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (2023.3.0)
-    Requirement already satisfied: numpy>=1.16.6 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from openvino>=2023.2.0) (1.23.5)
-    Requirement already satisfied: openvino-telemetry>=2023.2.1 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from openvino>=2023.2.0) (2023.2.1)
+    Requirement already satisfied: openvino>=2023.2.0 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (2023.3.0)
+    Requirement already satisfied: numpy>=1.16.6 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from openvino>=2023.2.0) (1.23.5)
+    Requirement already satisfied: openvino-telemetry>=2023.2.1 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from openvino>=2023.2.0) (2023.2.1)
 
 
 .. parsed-literal::
 
-    DEPRECATION: pytorch-lightning 1.6.5 has a non-standard dependency specifier torch>=1.8.*. pip 24.0 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of pytorch-lightning or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063
+    DEPRECATION: pytorch-lightning 1.6.5 has a non-standard dependency specifier torch>=1.8.*. pip 24.1 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of pytorch-lightning or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063
     
 
 .. parsed-literal::
@@ -107,14 +107,14 @@ Imports
 
 .. parsed-literal::
 
-    2024-01-25 23:35:29.422785: I tensorflow/core/util/port.cc:110] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
-    2024-01-25 23:35:29.457116: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+    2024-02-09 23:49:23.781601: I tensorflow/core/util/port.cc:110] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
+    2024-02-09 23:49:23.815218: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
     To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
 
 
 .. parsed-literal::
 
-    2024-01-25 23:35:29.986390: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+    2024-02-09 23:49:24.361080: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
 
 
 Download the attention-center model
@@ -209,7 +209,10 @@ remote: Counting objects:  65% (110/168)
 remote: Counting objects:  66% (111/168)
 remote: Counting objects:  67% (113/168)
 remote: Counting objects:  68% (115/168)
-remote: Counting objects:  69% (116/168)
+
+.. parsed-literal::
+
+    remote: Counting objects:  69% (116/168)
 remote: Counting objects:  70% (118/168)
 remote: Counting objects:  71% (120/168)
 remote: Counting objects:  72% (121/168)
@@ -231,10 +234,7 @@ remote: Counting objects:  87% (147/168)
 remote: Counting objects:  88% (148/168)
 remote: Counting objects:  89% (150/168)
 remote: Counting objects:  90% (152/168)
-
-.. parsed-literal::
-
-    remote: Counting objects:  91% (153/168)
+remote: Counting objects:  91% (153/168)
 remote: Counting objects:  92% (155/168)
 remote: Counting objects:  93% (157/168)
 remote: Counting objects:  94% (158/168)
@@ -254,19 +254,19 @@ remote: Compressing objects:   5% (7/132)
 remote: Compressing objects:   6% (8/132)
 remote: Compressing objects:   7% (10/132)
 remote: Compressing objects:   8% (11/132)
-remote: Compressing objects:   9% (12/132)
-remote: Compressing objects:  10% (14/132)
 
 .. parsed-literal::
 
-    remote: Compressing objects:  11% (15/132)
+    remote: Compressing objects:   9% (12/132)
+remote: Compressing objects:  10% (14/132)
+remote: Compressing objects:  11% (15/132)
 remote: Compressing objects:  12% (16/132)
 remote: Compressing objects:  13% (18/132)
-remote: Compressing objects:  14% (19/132)
 
 .. parsed-literal::
 
-    remote: Compressing objects:  15% (20/132)
+    remote: Compressing objects:  14% (19/132)
+remote: Compressing objects:  15% (20/132)
 remote: Compressing objects:  16% (22/132)
 
 .. parsed-literal::
@@ -289,7 +289,10 @@ remote: Compressing objects:  24% (32/132)
 .. parsed-literal::
 
     remote: Compressing objects:  25% (33/132)
-remote: Compressing objects:  26% (35/132)
+
+.. parsed-literal::
+
+    remote: Compressing objects:  26% (35/132)
 remote: Compressing objects:  27% (36/132)
 remote: Compressing objects:  28% (37/132)
 remote: Compressing objects:  29% (39/132)
@@ -365,10 +368,6 @@ remote: Compressing objects:  98% (130/132)
 remote: Compressing objects:  99% (131/132)
 remote: Compressing objects: 100% (132/132)
 remote: Compressing objects: 100% (132/132), done.
-
-
-.. parsed-literal::
-
     Receiving objects:   0% (1/168)
 Receiving objects:   1% (2/168)
 Receiving objects:   2% (4/168)
@@ -408,151 +407,151 @@ Receiving objects:  32% (54/168)
 
 .. parsed-literal::
 
-    Receiving objects:  33% (56/168), 1.79 MiB | 3.52 MiB/s
+    Receiving objects:  33% (56/168), 1.46 MiB | 2.90 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  34% (58/168), 1.79 MiB | 3.52 MiB/s
-Receiving objects:  35% (59/168), 1.79 MiB | 3.52 MiB/s
+    Receiving objects:  34% (58/168), 1.46 MiB | 2.90 MiB/s
+Receiving objects:  35% (59/168), 1.46 MiB | 2.90 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  35% (59/168), 3.69 MiB | 3.66 MiB/s
+    Receiving objects:  35% (59/168), 3.15 MiB | 3.13 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  36% (61/168), 5.57 MiB | 3.69 MiB/s
+    Receiving objects:  35% (60/168), 6.50 MiB | 3.23 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  36% (61/168), 7.48 MiB | 3.72 MiB/s
+    Receiving objects:  36% (61/168), 6.50 MiB | 3.23 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  37% (63/168), 9.36 MiB | 3.72 MiB/s
+    Receiving objects:  36% (62/168), 9.93 MiB | 3.27 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  38% (64/168), 9.36 MiB | 3.72 MiB/s
+    Receiving objects:  37% (63/168), 9.93 MiB | 3.27 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  39% (66/168), 11.27 MiB | 3.74 MiB/s
+    Receiving objects:  38% (64/168), 9.93 MiB | 3.27 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  40% (68/168), 11.27 MiB | 3.74 MiB/s
+    Receiving objects:  39% (66/168), 11.62 MiB | 3.29 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  41% (69/168), 13.15 MiB | 3.74 MiB/s
+    Receiving objects:  40% (68/168), 11.62 MiB | 3.29 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  42% (71/168), 13.15 MiB | 3.74 MiB/s
-Receiving objects:  43% (73/168), 13.15 MiB | 3.74 MiB/s
-Receiving objects:  44% (74/168), 13.15 MiB | 3.74 MiB/s
-Receiving objects:  45% (76/168), 13.15 MiB | 3.74 MiB/s
-Receiving objects:  46% (78/168), 13.15 MiB | 3.74 MiB/s
-Receiving objects:  47% (79/168), 13.15 MiB | 3.74 MiB/s
-Receiving objects:  48% (81/168), 13.15 MiB | 3.74 MiB/s
+    Receiving objects:  40% (68/168), 13.29 MiB | 3.29 MiB/s
+Receiving objects:  41% (69/168), 13.29 MiB | 3.29 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  49% (83/168), 13.15 MiB | 3.74 MiB/s
-Receiving objects:  50% (84/168), 13.15 MiB | 3.74 MiB/s
-Receiving objects:  51% (86/168), 13.15 MiB | 3.74 MiB/s
+    Receiving objects:  42% (71/168), 13.29 MiB | 3.29 MiB/s
+Receiving objects:  43% (73/168), 13.29 MiB | 3.29 MiB/s
+Receiving objects:  44% (74/168), 13.29 MiB | 3.29 MiB/s
+Receiving objects:  45% (76/168), 13.29 MiB | 3.29 MiB/s
+Receiving objects:  46% (78/168), 13.29 MiB | 3.29 MiB/s
+Receiving objects:  47% (79/168), 13.29 MiB | 3.29 MiB/s
+Receiving objects:  48% (81/168), 13.29 MiB | 3.29 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  52% (88/168), 13.15 MiB | 3.74 MiB/s
-Receiving objects:  53% (90/168), 13.15 MiB | 3.74 MiB/s
-Receiving objects:  54% (91/168), 13.15 MiB | 3.74 MiB/s
-Receiving objects:  55% (93/168), 13.15 MiB | 3.74 MiB/s
-Receiving objects:  56% (95/168), 13.15 MiB | 3.74 MiB/s
-Receiving objects:  57% (96/168), 13.15 MiB | 3.74 MiB/s
-Receiving objects:  58% (98/168), 13.15 MiB | 3.74 MiB/s
-Receiving objects:  59% (100/168), 13.15 MiB | 3.74 MiB/s
-Receiving objects:  60% (101/168), 13.15 MiB | 3.74 MiB/s
-Receiving objects:  61% (103/168), 13.15 MiB | 3.74 MiB/s
+    Receiving objects:  49% (83/168), 13.29 MiB | 3.29 MiB/s
+Receiving objects:  50% (84/168), 13.29 MiB | 3.29 MiB/s
+Receiving objects:  51% (86/168), 13.29 MiB | 3.29 MiB/s
+Receiving objects:  52% (88/168), 13.29 MiB | 3.29 MiB/s
+Receiving objects:  53% (90/168), 13.29 MiB | 3.29 MiB/s
+Receiving objects:  54% (91/168), 13.29 MiB | 3.29 MiB/s
+Receiving objects:  55% (93/168), 13.29 MiB | 3.29 MiB/s
+Receiving objects:  56% (95/168), 13.29 MiB | 3.29 MiB/s
+Receiving objects:  57% (96/168), 13.29 MiB | 3.29 MiB/s
+Receiving objects:  58% (98/168), 13.29 MiB | 3.29 MiB/s
+Receiving objects:  59% (100/168), 13.29 MiB | 3.29 MiB/s
+Receiving objects:  60% (101/168), 13.29 MiB | 3.29 MiB/s
+Receiving objects:  61% (103/168), 13.29 MiB | 3.29 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  61% (104/168), 15.07 MiB | 3.75 MiB/s
+    Receiving objects:  61% (104/168), 16.65 MiB | 3.34 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  61% (104/168), 18.84 MiB | 3.78 MiB/s
+    Receiving objects:  61% (104/168), 20.00 MiB | 3.34 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  61% (104/168), 22.65 MiB | 3.78 MiB/s
+    Receiving objects:  61% (104/168), 23.32 MiB | 3.33 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  62% (105/168), 24.51 MiB | 3.77 MiB/s
+    Receiving objects:  62% (105/168), 23.32 MiB | 3.33 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  63% (106/168), 24.51 MiB | 3.77 MiB/s
+    Receiving objects:  63% (106/168), 24.84 MiB | 3.29 MiB/s
 
 .. parsed-literal::
 
     remote: Total 168 (delta 73), reused 114 (delta 28), pack-reused 0
-    Receiving objects:  64% (108/168), 24.51 MiB | 3.77 MiB/s
-Receiving objects:  65% (110/168), 24.51 MiB | 3.77 MiB/s
-Receiving objects:  66% (111/168), 24.51 MiB | 3.77 MiB/s
-Receiving objects:  67% (113/168), 24.51 MiB | 3.77 MiB/s
-Receiving objects:  68% (115/168), 24.51 MiB | 3.77 MiB/s
-Receiving objects:  69% (116/168), 24.51 MiB | 3.77 MiB/s
-Receiving objects:  70% (118/168), 24.51 MiB | 3.77 MiB/s
-Receiving objects:  71% (120/168), 24.51 MiB | 3.77 MiB/s
-Receiving objects:  72% (121/168), 24.51 MiB | 3.77 MiB/s
-Receiving objects:  73% (123/168), 24.51 MiB | 3.77 MiB/s
-Receiving objects:  74% (125/168), 24.51 MiB | 3.77 MiB/s
-Receiving objects:  75% (126/168), 24.51 MiB | 3.77 MiB/s
-Receiving objects:  76% (128/168), 24.51 MiB | 3.77 MiB/s
-Receiving objects:  77% (130/168), 24.51 MiB | 3.77 MiB/s
-Receiving objects:  78% (132/168), 24.51 MiB | 3.77 MiB/s
-Receiving objects:  79% (133/168), 24.51 MiB | 3.77 MiB/s
-Receiving objects:  80% (135/168), 24.51 MiB | 3.77 MiB/s
-Receiving objects:  81% (137/168), 24.51 MiB | 3.77 MiB/s
-Receiving objects:  82% (138/168), 24.51 MiB | 3.77 MiB/s
-Receiving objects:  83% (140/168), 24.51 MiB | 3.77 MiB/s
-Receiving objects:  84% (142/168), 24.51 MiB | 3.77 MiB/s
-Receiving objects:  85% (143/168), 24.51 MiB | 3.77 MiB/s
-Receiving objects:  86% (145/168), 24.51 MiB | 3.77 MiB/s
-Receiving objects:  87% (147/168), 24.51 MiB | 3.77 MiB/s
-Receiving objects:  88% (148/168), 24.51 MiB | 3.77 MiB/s
-Receiving objects:  89% (150/168), 24.51 MiB | 3.77 MiB/s
-Receiving objects:  90% (152/168), 24.51 MiB | 3.77 MiB/s
-Receiving objects:  91% (153/168), 24.51 MiB | 3.77 MiB/s
-Receiving objects:  92% (155/168), 24.51 MiB | 3.77 MiB/s
-Receiving objects:  93% (157/168), 24.51 MiB | 3.77 MiB/s
-Receiving objects:  94% (158/168), 24.51 MiB | 3.77 MiB/s
-Receiving objects:  95% (160/168), 24.51 MiB | 3.77 MiB/s
-Receiving objects:  96% (162/168), 24.51 MiB | 3.77 MiB/s
-Receiving objects:  97% (163/168), 24.51 MiB | 3.77 MiB/s
-Receiving objects:  98% (165/168), 24.51 MiB | 3.77 MiB/s
-Receiving objects:  99% (167/168), 24.51 MiB | 3.77 MiB/s
-Receiving objects: 100% (168/168), 24.51 MiB | 3.77 MiB/s
-Receiving objects: 100% (168/168), 26.22 MiB | 3.76 MiB/s, done.
+    Receiving objects:  64% (108/168), 24.84 MiB | 3.29 MiB/s
+Receiving objects:  65% (110/168), 24.84 MiB | 3.29 MiB/s
+Receiving objects:  66% (111/168), 24.84 MiB | 3.29 MiB/s
+Receiving objects:  67% (113/168), 24.84 MiB | 3.29 MiB/s
+Receiving objects:  68% (115/168), 24.84 MiB | 3.29 MiB/s
+Receiving objects:  69% (116/168), 24.84 MiB | 3.29 MiB/s
+Receiving objects:  70% (118/168), 24.84 MiB | 3.29 MiB/s
+Receiving objects:  71% (120/168), 24.84 MiB | 3.29 MiB/s
+Receiving objects:  72% (121/168), 24.84 MiB | 3.29 MiB/s
+Receiving objects:  73% (123/168), 24.84 MiB | 3.29 MiB/s
+Receiving objects:  74% (125/168), 24.84 MiB | 3.29 MiB/s
+Receiving objects:  75% (126/168), 24.84 MiB | 3.29 MiB/s
+Receiving objects:  76% (128/168), 24.84 MiB | 3.29 MiB/s
+Receiving objects:  77% (130/168), 24.84 MiB | 3.29 MiB/s
+Receiving objects:  78% (132/168), 24.84 MiB | 3.29 MiB/s
+Receiving objects:  79% (133/168), 24.84 MiB | 3.29 MiB/s
+Receiving objects:  80% (135/168), 24.84 MiB | 3.29 MiB/s
+Receiving objects:  81% (137/168), 24.84 MiB | 3.29 MiB/s
+Receiving objects:  82% (138/168), 24.84 MiB | 3.29 MiB/s
+Receiving objects:  83% (140/168), 24.84 MiB | 3.29 MiB/s
+Receiving objects:  84% (142/168), 24.84 MiB | 3.29 MiB/s
+Receiving objects:  85% (143/168), 24.84 MiB | 3.29 MiB/s
+Receiving objects:  86% (145/168), 24.84 MiB | 3.29 MiB/s
+Receiving objects:  87% (147/168), 24.84 MiB | 3.29 MiB/s
+Receiving objects:  88% (148/168), 24.84 MiB | 3.29 MiB/s
+Receiving objects:  89% (150/168), 24.84 MiB | 3.29 MiB/s
+Receiving objects:  90% (152/168), 24.84 MiB | 3.29 MiB/s
+Receiving objects:  91% (153/168), 24.84 MiB | 3.29 MiB/s
+Receiving objects:  92% (155/168), 24.84 MiB | 3.29 MiB/s
+Receiving objects:  93% (157/168), 24.84 MiB | 3.29 MiB/s
+Receiving objects:  94% (158/168), 24.84 MiB | 3.29 MiB/s
+Receiving objects:  95% (160/168), 24.84 MiB | 3.29 MiB/s
+Receiving objects:  96% (162/168), 24.84 MiB | 3.29 MiB/s
+Receiving objects:  97% (163/168), 24.84 MiB | 3.29 MiB/s
+Receiving objects:  98% (165/168), 24.84 MiB | 3.29 MiB/s
+Receiving objects:  99% (167/168), 24.84 MiB | 3.29 MiB/s
+Receiving objects: 100% (168/168), 24.84 MiB | 3.29 MiB/s
+Receiving objects: 100% (168/168), 26.22 MiB | 3.29 MiB/s, done.
     Resolving deltas:   0% (0/73)
-Resolving deltas:   1% (1/73)
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@@ -734,12 +733,12 @@ Upload input image using file loading button
 
 .. parsed-literal::
 
-    2024-01-25 23:35:43.537386: E tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:266] failed call to cuInit: CUDA_ERROR_COMPAT_NOT_SUPPORTED_ON_DEVICE: forward compatibility was attempted on non supported HW
-    2024-01-25 23:35:43.537423: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:168] retrieving CUDA diagnostic information for host: iotg-dev-workstation-07
-    2024-01-25 23:35:43.537428: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:175] hostname: iotg-dev-workstation-07
-    2024-01-25 23:35:43.537586: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:199] libcuda reported version is: 470.223.2
-    2024-01-25 23:35:43.537603: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:203] kernel reported version is: 470.182.3
-    2024-01-25 23:35:43.537606: E tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:312] kernel version 470.182.3 does not match DSO version 470.223.2 -- cannot find working devices in this configuration
+    2024-02-09 23:49:38.816368: E tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:266] failed call to cuInit: CUDA_ERROR_COMPAT_NOT_SUPPORTED_ON_DEVICE: forward compatibility was attempted on non supported HW
+    2024-02-09 23:49:38.816405: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:168] retrieving CUDA diagnostic information for host: iotg-dev-workstation-07
+    2024-02-09 23:49:38.816409: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:175] hostname: iotg-dev-workstation-07
+    2024-02-09 23:49:38.816551: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:199] libcuda reported version is: 470.223.2
+    2024-02-09 23:49:38.816566: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:203] kernel reported version is: 470.182.3
+    2024-02-09 23:49:38.816569: E tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:312] kernel version 470.182.3 does not match DSO version 470.223.2 -- cannot find working devices in this configuration
 
 
 
diff --git a/docs/notebooks/216-attention-center-with-output_files/index.html.tmp b/docs/notebooks/216-attention-center-with-output_files/index.html.tmp
deleted file mode 100644
index a1ca9e4cf619b7..00000000000000
--- a/docs/notebooks/216-attention-center-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,8 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/216-attention-center-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/216-attention-center-with-output_files/
../
-216-attention-center-with-output_15_1.png          26-Jan-2024 01:05              387941
-216-attention-center-with-output_17_1.png          26-Jan-2024 01:05              387905
-

-
diff --git a/docs/notebooks/217-vision-deblur-with-output.rst b/docs/notebooks/217-vision-deblur-with-output.rst
deleted file mode 100644
index 2f41249b1b6759..00000000000000
--- a/docs/notebooks/217-vision-deblur-with-output.rst
+++ /dev/null
@@ -1,1074 +0,0 @@
-Deblur Photos with DeblurGAN-v2 and OpenVINO™
-=============================================
-
-Table of contents:
-^^^^^^^^^^^^^^^^^^
-
--  `What is deblurring? <#what-is-deblurring>`__
--  `Preparations <#preparations>`__
-
-   -  `Imports <#imports>`__
-   -  `Settings <#settings>`__
-   -  `Select inference device <#select-inference-device>`__
-   -  `Download DeblurGAN-v2 Model <#download-deblurgan-v2-model>`__
-   -  `Prepare model <#prepare-model>`__
-   -  `Convert DeblurGAN-v2 Model to OpenVINO IR
-      format <#convert-deblurgan-v2-model-to-openvino-ir-format>`__
-
--  `Load the Model <#load-the-model>`__
--  `Deblur Image <#deblur-image>`__
-
-   -  `Load, resize and reshape input
-      image <#load-resize-and-reshape-input-image>`__
-   -  `Do Inference on the Input
-      Image <#do-inference-on-the-input-image>`__
-   -  `Display results <#display-results>`__
-   -  `Save the deblurred image <#save-the-deblurred-image>`__
-
-This tutorial demonstrates Single Image Motion Deblurring with
-DeblurGAN-v2 in OpenVINO, by first converting the
-`VITA-Group/DeblurGANv2 `__
-model to OpenVINO Intermediate Representation (OpenVINO IR) format. For
-more information about the model, see the
-`documentation `__.
-
-What is deblurring?
-~~~~~~~~~~~~~~~~~~~
-
-
-
-Deblurring is the task of removing motion blurs that usually occur in
-photos shot with hand-held cameras when there are moving objects in the
-scene. Blurs not only reduce the human perception about the quality of
-the image, but also complicate computer vision analyses.
-
-For more information, refer to the following research paper:
-
-Kupyn, O., Martyniuk, T., Wu, J., & Wang, Z. (2019). `DeblurGAN-v2:
-Deblurring (orders-of-magnitude) faster and
-better. `__
-In Proceedings of the IEEE/CVF International Conference on Computer
-Vision (pp. 8878-8887).
-
-Preparations
-------------
-
-
-
-.. code:: ipython3
-
-    %pip install -q "openvino-dev>=2023.1.0"
-
-
-.. parsed-literal::
-
-    DEPRECATION: pytorch-lightning 1.6.5 has a non-standard dependency specifier torch>=1.8.*. pip 24.0 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of pytorch-lightning or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063
-    
-
-.. parsed-literal::
-
-    Note: you may need to restart the kernel to use updated packages.
-
-
-Imports
-~~~~~~~
-
-
-
-.. code:: ipython3
-
-    import sys
-    from pathlib import Path
-    
-    import cv2
-    import matplotlib.pyplot as plt
-    import numpy as np
-    from IPython.display import Markdown, display
-    import openvino as ov
-    
-    sys.path.append("../utils")
-    from notebook_utils import load_image
-
-Settings
-~~~~~~~~
-
-
-
-.. code:: ipython3
-
-    # A directory where the model will be downloaded.
-    model_dir = Path("model")
-    model_dir.mkdir(exist_ok=True)
-    
-    # The name of the model from Open Model Zoo.
-    model_name = "deblurgan-v2"
-    model_xml_path = model_dir / f"{model_name}.xml"
-    ov_model = None
-    
-    precision = "FP16"
-
-Select inference device
-~~~~~~~~~~~~~~~~~~~~~~~
-
-
-
-select device from dropdown list for running inference using OpenVINO
-
-.. code:: ipython3
-
-    import ipywidgets as widgets
-    
-    core = ov.Core()
-    
-    device = widgets.Dropdown(
-        options=core.available_devices + ["AUTO"],
-        value='AUTO',
-        description='Device:',
-        disabled=False,
-    )
-    
-    device
-
-
-
-
-.. parsed-literal::
-
-    Dropdown(description='Device:', index=1, options=('CPU', 'AUTO'), value='AUTO')
-
-
-
-Download DeblurGAN-v2 Model
-~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-
-
-Model defined in
-`VITA-Group/DeblurGANv2 `__
-repository. For converting model we should clone this repo and install
-its dependencies. To reduce conversion step, we will use OMZ downloader
-for downloading model weights. After downloading is finished, model
-related code will be saved in ``model/public/deblurgan-v2/models/``
-directory and weights in ``public/deblurgan-v2/ckpt/fpn_mobilenet.h5``
-
-.. code:: ipython3
-
-    download_command = (
-        f"omz_downloader --name {model_name} --output_dir"
-        f" {model_dir} --cache_dir {model_dir}"
-    )
-    display(Markdown(f"Download command: `{download_command}`"))
-    display(Markdown(f"Downloading {model_name}..."))
-    ! $download_command
-
-
-
-Download command:
-``omz_downloader --name deblurgan-v2 --output_dir model --cache_dir model``
-
-
-
-Downloading deblurgan-v2…
-
-
-.. parsed-literal::
-
-    ################|| Downloading deblurgan-v2 ||################
-    
-    ========== Downloading model/public/deblurgan-v2/models/__init__.py
-
-
-.. parsed-literal::
-
-    
-    
-    ========== Downloading model/public/deblurgan-v2/models/fpn_mobilenet.py
-
-
-.. parsed-literal::
-
-    ... 100%, 5 KB, 15440 KB/s, 0 seconds passed
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-    
-    ========== Downloading model/public/deblurgan-v2/models/mobilenet_v2.py
-
-
-.. parsed-literal::
-
-    ... 100%, 4 KB, 14928 KB/s, 0 seconds passed
-
-    
-    ========== Downloading model/public/deblurgan-v2/models/networks.py
-
-
-.. parsed-literal::
-
-    ... 100%, 12 KB, 36702 KB/s, 0 seconds passed
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-    
-    ========== Downloading model/public/deblurgan-v2/ckpt/fpn_mobilenet.h5
-
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-
-    
-    ========== Replacing text in model/public/deblurgan-v2/models/networks.py
-    ========== Replacing text in model/public/deblurgan-v2/models/fpn_mobilenet.py
-    ========== Replacing text in model/public/deblurgan-v2/models/fpn_mobilenet.py
-    
-
-
-Prepare model
-~~~~~~~~~~~~~
-
-
-
-DeblurGAN-v2 is PyTorch model for converting it to OpenVINO Intermediate
-Representation format, we should first instantiate model class and load
-checkpoint weights.
-
-.. code:: ipython3
-
-    sys.path.append("model/public/deblurgan-v2")
-    
-    import torch
-    
-    from models.networks import get_generator
-    
-    
-    class DeblurV2(torch.nn.Module):
-        def __init__(self, weights, model_name):
-            super().__init__()
-    
-            parameters = {'g_name': model_name, 'norm_layer': 'instance'}
-            self.impl = get_generator(parameters)
-            checkpoint = torch.load(weights, map_location='cpu')['model']
-            self.impl.load_state_dict(checkpoint)
-            self.impl.train(True)
-    
-        def forward(self, image):
-            out = self.impl(image)
-            # convert out to [0, 1] range
-            out = (out + 1) / 2
-            return out
-
-Convert DeblurGAN-v2 Model to OpenVINO IR format
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-
-
-For best results with OpenVINO, it is recommended to convert the model
-to OpenVINO IR format. To convert the PyTorch model, we will use model
-conversion Python API. The ``ov.convert_model`` Python function returns
-an OpenVINO model ready to load on a device and start making
-predictions. We can save the model on the disk for next usage with
-``ov.save_model``. For more information about model conversion Python
-API, see this
-`page `__.
-
-Model conversion may take a while.
-
-.. code:: ipython3
-
-    deblur_gan_model = DeblurV2("model/public/deblurgan-v2/ckpt/fpn_mobilenet.h5", "fpn_mobilenet")
-    
-    with torch.no_grad():
-        deblur_gan_model.eval()
-        ov_model = ov.convert_model(deblur_gan_model, example_input=torch.ones((1,3,736,1312), dtype=torch.float32), input=[[1,3,736,1312]])
-        ov.save_model(ov_model, model_xml_path, compress_to_fp16=(precision == "FP16"))
-
-Load the Model
---------------
-
-
-
-Load and compile the DeblurGAN-v2 model in the OpenVINO Runtime with
-``core.read_model`` and compile it for the specified device with
-``core.compile_model``. Get input and output keys and the expected input
-shape for the model.
-
-.. code:: ipython3
-
-    model = core.read_model(model=model_xml_path)
-    compiled_model = core.compile_model(model=model, device_name=device.value)
-
-.. code:: ipython3
-
-    model_input_layer = compiled_model.input(0)
-    model_output_layer = compiled_model.output(0)
-
-.. code:: ipython3
-
-    model_input_layer
-
-
-
-
-.. parsed-literal::
-
-    
-
-
-
-.. code:: ipython3
-
-    model_output_layer
-
-
-
-
-.. parsed-literal::
-
-    
-
-
-
-Deblur Image
-------------
-
-
-
-Load, resize and reshape input image
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-
-
-The input image is read by using the default ``load_image`` function
-from ``notebooks.utils``. Then, resized to meet the network expected
-input sizes, and reshaped to ``(N, C, H, W)``, where ``N`` is a number
-of images in the batch, ``C`` is a number of channels, ``H`` is the
-height, and ``W`` is the width.
-
-.. code:: ipython3
-
-    # Image filename (local path or URL)
-    filename = "https://raw.githubusercontent.com/VITA-Group/DeblurGANv2/master/test_img/000027.png"
-
-.. code:: ipython3
-
-    # Load the input image.
-    # Load image returns image in BGR format
-    image = load_image(filename)
-    
-    # Convert the image to expected by model RGB format
-    if image.shape[2] == 4:
-        image = cv2.cvtColor(image, cv2.COLOR_BGRA2BGR)
-    image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
-    
-    # N,C,H,W = batch size, number of channels, height, width.
-    N, C, H, W = model_input_layer.shape
-    
-    # Resize the image to meet network expected input sizes.
-    resized_image = cv2.resize(image, (W, H))
-    
-    # Convert image to float32 precision anf normalize in [-1, 1] range
-    input_image = (resized_image.astype(np.float32) - 127.5) / 127.5
-    
-    # Add batch dimension to input image tensor
-    input_image = np.expand_dims(input_image.transpose(2, 0, 1), 0) 
-
-.. code:: ipython3
-
-    plt.imshow(image);
-
-
-
-.. image:: 217-vision-deblur-with-output_files/217-vision-deblur-with-output_25_0.png
-
-
-Do Inference on the Input Image
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-
-
-Do the inference, convert the result to an image shape and resize it to
-the original image size.
-
-.. code:: ipython3
-
-    # Inference.
-    result = compiled_model([input_image])[model_output_layer]
-    
-    # Convert the result to an image shape and [0, 255] range
-    result_image = result[0].transpose((1, 2, 0)) * 255
-    
-    h, w = image.shape[:2]
-    
-    # Resize to the original image size and convert to original u8 precision
-    resized_result_image = cv2.resize(result_image, (w, h)).astype(np.uint8)
-
-.. code:: ipython3
-
-    plt.imshow(resized_result_image);
-
-
-
-.. image:: 217-vision-deblur-with-output_files/217-vision-deblur-with-output_28_0.png
-
-
-Display results
-~~~~~~~~~~~~~~~
-
-
-
-.. code:: ipython3
-
-    # Create subplot(r,c) by providing the no. of rows (r),
-    # number of columns (c) and figure size.
-    f, ax = plt.subplots(1, 2, figsize=(20, 20))
-    
-    # Use the created array and display the images horizontally.
-    ax[0].set_title("Blurred")
-    ax[0].imshow(image)
-    
-    ax[1].set_title("DeblurGAN-v2")
-    ax[1].imshow(resized_result_image);
-
-
-
-.. image:: 217-vision-deblur-with-output_files/217-vision-deblur-with-output_30_0.png
-
-
-Save the deblurred image
-~~~~~~~~~~~~~~~~~~~~~~~~
-
-
-
-Save the output image of the DeblurGAN-v2 model in the current
-directory.
-
-.. code:: ipython3
-
-    savename = "deblurred.png"
-    cv2.imwrite(savename, resized_result_image);
diff --git a/docs/notebooks/217-vision-deblur-with-output_files/217-vision-deblur-with-output_25_0.png b/docs/notebooks/217-vision-deblur-with-output_files/217-vision-deblur-with-output_25_0.png
deleted file mode 100644
index f328f8e480fb0c..00000000000000
--- a/docs/notebooks/217-vision-deblur-with-output_files/217-vision-deblur-with-output_25_0.png
+++ /dev/null
@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:83003e456cf4415bf49fabaae1a3a3e850e66884ab30a40872fd4f625cc682fe
-size 220275
diff --git a/docs/notebooks/217-vision-deblur-with-output_files/217-vision-deblur-with-output_28_0.png b/docs/notebooks/217-vision-deblur-with-output_files/217-vision-deblur-with-output_28_0.png
deleted file mode 100644
index e7e598bb0b3e70..00000000000000
--- a/docs/notebooks/217-vision-deblur-with-output_files/217-vision-deblur-with-output_28_0.png
+++ /dev/null
@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:287e7d9a789efab3ee5929511adcde4d58d460d348acc64b216f10b26f0daf3f
-size 223298
diff --git a/docs/notebooks/217-vision-deblur-with-output_files/217-vision-deblur-with-output_30_0.png b/docs/notebooks/217-vision-deblur-with-output_files/217-vision-deblur-with-output_30_0.png
deleted file mode 100644
index 81595c231e9812..00000000000000
--- a/docs/notebooks/217-vision-deblur-with-output_files/217-vision-deblur-with-output_30_0.png
+++ /dev/null
@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:a289317a43457fedb53230af290a7f91036be77fa57631382c01096d78d8386f
-size 768439
diff --git a/docs/notebooks/217-vision-deblur-with-output_files/index.html.tmp b/docs/notebooks/217-vision-deblur-with-output_files/index.html.tmp
deleted file mode 100644
index 3796a74c9ae06c..00000000000000
--- a/docs/notebooks/217-vision-deblur-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,9 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/217-vision-deblur-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/217-vision-deblur-with-output_files/
../
-217-vision-deblur-with-output_25_0.png             26-Jan-2024 01:05              220275
-217-vision-deblur-with-output_28_0.png             26-Jan-2024 01:05              223298
-217-vision-deblur-with-output_30_0.png             26-Jan-2024 01:05              768439
-

-
diff --git a/docs/notebooks/218-vehicle-detection-and-recognition-with-output.rst b/docs/notebooks/218-vehicle-detection-and-recognition-with-output.rst
index 2ca8e99cc29c58..02a1014dcab97d 100644
--- a/docs/notebooks/218-vehicle-detection-and-recognition-with-output.rst
+++ b/docs/notebooks/218-vehicle-detection-and-recognition-with-output.rst
@@ -54,8 +54,8 @@ Import the required modules.
 
 .. parsed-literal::
 
-    DEPRECATION: pytorch-lightning 1.6.5 has a non-standard dependency specifier torch>=1.8.*. pip 24.0 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of pytorch-lightning or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063
-    
+    DEPRECATION: pytorch-lightning 1.6.5 has a non-standard dependency specifier torch>=1.8.*. pip 24.1 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of pytorch-lightning or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063
+
 
 .. parsed-literal::
 
@@ -68,12 +68,12 @@ Import the required modules.
     import sys
     from pathlib import Path
     from typing import Tuple
-    
+
     import cv2
     import numpy as np
     import matplotlib.pyplot as plt
     import openvino as ov
-    
+
     sys.path.append("../utils")
     import notebook_utils as utils
 
@@ -86,7 +86,7 @@ Download pretrained models from
 https://storage.openvinotoolkit.org/repositories/open_model_zoo. If the
 model is already downloaded, this step is skipped.
 
-   **Note**: To change the model, replace the name of the model in the
+   **NOTE**: To change the model, replace the name of the model in the
    code below, for example to ``"vehicle-detection-0201"`` or
    ``"vehicle-detection-0202"``. Keep in mind that they support
    different image input sizes in detection. Also, you can change the
@@ -106,9 +106,9 @@ model is already downloaded, this step is skipped.
     recognition_model_name = "vehicle-attributes-recognition-barrier-0039"
     # Selected precision (FP32, FP16, FP16-INT8)
     precision = "FP32"
-    
+
     base_model_url = "https://storage.openvinotoolkit.org/repositories/open_model_zoo/2023.0/models_bin/1"
-    
+
     # Check if the model exists.
     detection_model_url = (
         f"{base_model_url}/{detection_model_name}/{precision}/{detection_model_name}.xml"
@@ -118,7 +118,7 @@ model is already downloaded, this step is skipped.
     )
     detection_model_path = (base_model_dir / detection_model_name).with_suffix('.xml')
     recognition_model_path = (base_model_dir / recognition_model_name).with_suffix('.xml')
-    
+
     # Download the detection model.
     if not detection_model_path.exists():
         utils.download_file(detection_model_url, detection_model_name + '.xml', base_model_dir)
@@ -167,16 +167,16 @@ specified device.
 .. code:: ipython3
 
     import ipywidgets as widgets
-    
+
     core = ov.Core()
-    
+
     device = widgets.Dropdown(
         options=core.available_devices + ["AUTO"],
         value='AUTO',
         description='Device:',
         disabled=False,
     )
-    
+
     device
 
 
@@ -192,13 +192,13 @@ specified device.
 
     # Initialize OpenVINO Runtime runtime.
     core = ov.Core()
-    
-    
+
+
     def model_init(model_path: str) -> Tuple:
         """
         Read the network and weights from file, load the
         model on the CPU and get input and output names of nodes
-    
+
         :param: model: model architecture path *.xml
         :retuns:
                 input_key: Input node network
@@ -206,7 +206,7 @@ specified device.
                 exec_net: Encoder model network
                 net: Model network
         """
-    
+
         # Read the network and corresponding weights from a file.
         model = core.read_model(model=model_path)
         compiled_model = core.compile_model(model=model, device_name=device.value)
@@ -230,7 +230,7 @@ Use ``input_keys.shape`` to get data shapes.
     input_key_de, output_keys_de, compiled_model_de = model_init(detection_model_path)
     # Recognition model initialization.
     input_key_re, output_keys_re, compiled_model_re = model_init(recognition_model_path)
-    
+
     # Get input size - Detection.
     height_de, width_de = list(input_key_de.shape)[2:]
     # Get input size - Recognition.
@@ -249,7 +249,7 @@ The ``plt_show()`` function is used to show image.
         """
         Use matplot to show image inline
         raw_image: input image
-    
+
         :param: raw_image:image array
         """
         plt.figure(figsize=(10, 6))
@@ -275,7 +275,7 @@ channel with ``expand_dims`` function.
         url, filename=filename, directory=directory, show_progress=False, silent=True,timeout=30
     )
     assert Path(image_file).exists()
-    
+
     # Read the image.
     image_de = cv2.imread("data/cars.jpg")
     # Resize it to [3, 256, 256].
@@ -337,7 +337,7 @@ the image and filter out low-confidence results.
     def crop_images(bgr_image, resized_image, boxes, threshold=0.6) -> np.ndarray:
         """
         Use bounding boxes from detection model to find the absolute car position
-        
+
         :param: bgr_image: raw image
         :param: resized_image: resized image
         :param: boxes: detection model returns rectangle position
@@ -347,7 +347,7 @@ the image and filter out low-confidence results.
         # Fetch image shapes to calculate ratio
         (real_y, real_x), (resized_y, resized_x) = bgr_image.shape[:2], resized_image.shape[:2]
         ratio_x, ratio_y = real_x / resized_x, real_y / resized_y
-    
+
         # Find the boxes ratio
         boxes = boxes[:, 2:]
         # Store the vehicle's position
@@ -358,16 +358,16 @@ the image and filter out low-confidence results.
             conf = box[0]
             if conf > threshold:
                 # Convert float to int and multiply corner position of each box by x and y ratio
-                # In case that bounding box is found at the top of the image, 
-                # upper box  bar should be positioned a little bit lower to make it visible on image 
+                # In case that bounding box is found at the top of the image,
+                # upper box  bar should be positioned a little bit lower to make it visible on image
                 (x_min, y_min, x_max, y_max) = [
-                    int(max(corner_position * ratio_y * resized_y, 10)) if idx % 2 
+                    int(max(corner_position * ratio_y * resized_y, 10)) if idx % 2
                     else int(corner_position * ratio_x * resized_x)
                     for idx, corner_position in enumerate(box[1:])
                 ]
-                
+
                 car_position.append([x_min, y_min, x_max, y_max])
-                
+
         return car_position
 
 .. code:: ipython3
@@ -415,7 +415,7 @@ determine the maximum probability as the result.
     def vehicle_recognition(compiled_model_re, input_size, raw_image):
         """
         Vehicle attributes recognition, input a single vehicle, return attributes
-        :param: compiled_model_re: recognition net 
+        :param: compiled_model_re: recognition net
         :param: input_size: recognition input size
         :param: raw_image: single vehicle image
         :returns: attr_color: predicted color
@@ -424,11 +424,11 @@ determine the maximum probability as the result.
         # An attribute of a vehicle.
         colors = ['White', 'Gray', 'Yellow', 'Red', 'Green', 'Blue', 'Black']
         types = ['Car', 'Bus', 'Truck', 'Van']
-        
+
         # Resize the image to input size.
         resized_image_re = cv2.resize(raw_image, input_size)
         input_image_re = np.expand_dims(resized_image_re.transpose(2, 0, 1), 0)
-        
+
         # Run inference.
         # Predict result.
         predict_colors = compiled_model_re([input_image_re])[compiled_model_re.output(1)]
@@ -436,7 +436,7 @@ determine the maximum probability as the result.
         predict_colors = np.squeeze(predict_colors, (2, 3))
         predict_types = compiled_model_re([input_image_re])[compiled_model_re.output(0)]
         predict_types = np.squeeze(predict_types, (2, 3))
-    
+
         attr_color, attr_type = (colors[np.argmax(predict_colors)],
                                  types[np.argmax(predict_types)])
         return attr_color, attr_type
@@ -464,7 +464,7 @@ image with a vehicle and recognize the attributes of a vehicle.
     def convert_result_to_image(compiled_model_re, bgr_image, resized_image, boxes, threshold=0.6):
         """
         Use Detection model boxes to draw rectangles and plot the result
-        
+
         :param: compiled_model_re: recognition net
         :param: input_key_re: recognition input key
         :param: bgr_image: raw image
@@ -475,29 +475,29 @@ image with a vehicle and recognize the attributes of a vehicle.
         """
         # Define colors for boxes and descriptions.
         colors = {"red": (255, 0, 0), "green": (0, 255, 0)}
-        
+
         # Convert the base image from BGR to RGB format.
         rgb_image = cv2.cvtColor(bgr_image, cv2.COLOR_BGR2RGB)
-        
+
         # Find positions of cars.
         car_position = crop_images(image_de, resized_image, boxes)
-        
+
         for x_min, y_min, x_max, y_max in car_position:
             # Run vehicle recognition inference.
-            attr_color, attr_type = vehicle_recognition(compiled_model_re, (72, 72), 
+            attr_color, attr_type = vehicle_recognition(compiled_model_re, (72, 72),
                                                         image_de[y_min:y_max, x_min:x_max])
-    
+
             # Close the window with a vehicle.
             plt.close()
-    
+
             # Draw a bounding box based on position.
             # Parameters in the `rectangle` function are: image, start_point, end_point, color, thickness.
             rgb_image = cv2.rectangle(rgb_image, (x_min, y_min), (x_max, y_max), colors["red"], 2)
-    
-            # Print the attributes of a vehicle. 
+
+            # Print the attributes of a vehicle.
             # Parameters in the `putText` function are: img, text, org, fontFace, fontScale, color, thickness, lineType.
             rgb_image = cv2.putText(
-                rgb_image, 
+                rgb_image,
                 f"{attr_color} {attr_type}",
                 (x_min, y_min - 10),
                 cv2.FONT_HERSHEY_SIMPLEX,
@@ -506,7 +506,7 @@ image with a vehicle and recognize the attributes of a vehicle.
                 10,
                 cv2.LINE_AA
             )
-    
+
         return rgb_image
 
 .. code:: ipython3
diff --git a/docs/notebooks/218-vehicle-detection-and-recognition-with-output_files/index.html.tmp b/docs/notebooks/218-vehicle-detection-and-recognition-with-output_files/index.html.tmp
deleted file mode 100644
index 2dbbf713779465..00000000000000
--- a/docs/notebooks/218-vehicle-detection-and-recognition-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,9 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/218-vehicle-detection-and-recognition-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/218-vehicle-detection-and-recognition-with-output_files/
../
-218-vehicle-detection-and-recognition-with-outp..> 26-Jan-2024 01:05              172680
-218-vehicle-detection-and-recognition-with-outp..> 26-Jan-2024 01:05               19599
-218-vehicle-detection-and-recognition-with-outp..> 26-Jan-2024 01:05              175941
-

-
diff --git a/docs/notebooks/219-knowledge-graphs-conve-with-output.rst b/docs/notebooks/219-knowledge-graphs-conve-with-output.rst
index 4e180ea7004f37..00226d02f2317e 100644
--- a/docs/notebooks/219-knowledge-graphs-conve-with-output.rst
+++ b/docs/notebooks/219-knowledge-graphs-conve-with-output.rst
@@ -16,26 +16,38 @@ Knowledge Graph Embeddings” (https://arxiv.org/abs/1707.01476). The
 sample dataset can be downloaded from:
 https://github.com/TimDettmers/ConvE/tree/master/countries/countries_S1
 
-
-**Table of contents:**
-
-
-- `Windows specific settings <#windows-specific-settings>`__
-- `Import the packages needed for successful execution <#import-the-packages-needed-for-successful-execution>`__
-- `Settings: Including path to the serialized model files and input data files <#settings-including-path-to-the-serialized-model-files-and-input-data-files>`__
-- `Download Model Checkpoint <#download-model-checkpoint>`__
-- `Defining the ConvE model class <#defining-the-conve-model-class>`__
-- `Defining the dataloader <#defining-the-dataloader>`__
-- `Evaluate the trained ConvE model <#evaluate-the-trained-conve-model>`__
-- `Prediction on the Knowledge graph. <#prediction-on-the-knowledge-graph>`__
-- `Convert the trained PyTorch model to IR format for OpenVINO inference <#convert-the-trained-pytorch-model-to-ir-format-for-openvino-inference>`__
-- `Evaluate the model performance with OpenVINO <#evaluate-the-model-performance-with-openvino>`__
-- `Select inference device <#select-inference-device>`__
-- `Determine the platform specific speedup obtained through OpenVINO graph optimizations <#determine-the-platform-specific-speedup-obtained-through-openvino-graph-optimizations>`__
-- `Benchmark the converted OpenVINO model using benchmark app <#benchmark-the-converted-openvino-model-using-benchmark-app>`__
-- `Conclusions <#conclusions>`__
-- `References <#references>`__
-
+Table of contents:
+^^^^^^^^^^^^^^^^^^
+
+-  `Windows specific settings <#windows-specific-settings>`__
+-  `Import the packages needed for successful
+   execution <#import-the-packages-needed-for-successful-execution>`__
+
+   -  `Settings: Including path to the serialized model files and input
+      data
+      files <#settings-including-path-to-the-serialized-model-files-and-input-data-files>`__
+   -  `Download Model Checkpoint <#download-model-checkpoint>`__
+   -  `Defining the ConvE model
+      class <#defining-the-conve-model-class>`__
+   -  `Defining the dataloader <#defining-the-dataloader>`__
+   -  `Evaluate the trained ConvE
+      model <#evaluate-the-trained-conve-model>`__
+   -  `Prediction on the Knowledge
+      graph. <#prediction-on-the-knowledge-graph->`__
+   -  `Convert the trained PyTorch model to IR format for OpenVINO
+      inference <#convert-the-trained-pytorch-model-to-ir-format-for-openvino-inference>`__
+   -  `Evaluate the model performance with
+      OpenVINO <#evaluate-the-model-performance-with-openvino>`__
+
+-  `Select inference device <#select-inference-device>`__
+
+   -  `Determine the platform specific speedup obtained through OpenVINO
+      graph
+      optimizations <#determine-the-platform-specific-speedup-obtained-through-openvino-graph-optimizations>`__
+   -  `Benchmark the converted OpenVINO model using benchmark
+      app <#benchmark-the-converted-openvino-model-using-benchmark-app>`__
+   -  `Conclusions <#conclusions>`__
+   -  `References <#references>`__
 
 .. code:: ipython3
 
@@ -44,7 +56,7 @@ https://github.com/TimDettmers/ConvE/tree/master/countries/countries_S1
 
 .. parsed-literal::
 
-    DEPRECATION: pytorch-lightning 1.6.5 has a non-standard dependency specifier torch>=1.8.*. pip 24.0 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of pytorch-lightning or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063
+    DEPRECATION: pytorch-lightning 1.6.5 has a non-standard dependency specifier torch>=1.8.*. pip 24.1 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of pytorch-lightning or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063
 
 
 .. parsed-literal::
@@ -213,7 +225,7 @@ Download Model Checkpoint
 
 .. parsed-literal::
 
-    PosixPath('/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/219-knowledge-graphs-conve/models/conve.pt')
+    PosixPath('/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/notebooks/219-knowledge-graphs-conve/models/conve.pt')
 
 
 
@@ -375,7 +387,7 @@ typical to use metrics such as Mean Reciprocal Rank, Hits@10 etc.
 
 .. parsed-literal::
 
-    Average time taken for inference: 0.706791877746582 ms
+    Average time taken for inference: 0.7827480634053549 ms
     Mean accuracy of the model on the test dataset: 0.875
 
 
@@ -448,7 +460,7 @@ Evaluate the model performance with OpenVINO
 Now, we evaluate the model performance with the OpenVINO framework. In
 order to do so, make three main API calls:
 
-1. Initialize the Inference engine with ``Core()``
+1. Initialize the OpenVINO with ``Core()``
 2. Load the model with ``read_model()``
 3. Compile the model with ``compile_model()``
 
@@ -519,7 +531,7 @@ select device from dropdown list for running inference using OpenVINO
 
 .. parsed-literal::
 
-    Average time taken for inference: 0.8750458558400472 ms
+    Average time taken for inference: 0.9586711724599203 ms
     Mean accuracy of the model on the test dataset: 0.10416666666666667
 
 
@@ -538,7 +550,7 @@ Determine the platform specific speedup obtained through OpenVINO graph optimiza
 
 .. parsed-literal::
 
-    Speedup with OpenVINO optimizations: 0.81 X
+    Speedup with OpenVINO optimizations: 0.82 X
 
 
 Benchmark the converted OpenVINO model using benchmark app
@@ -587,7 +599,7 @@ inference can also be obtained by looking at the benchmark app results.
     [ WARNING ] Performance hint was not explicitly specified in command line. Device(CPU) performance hint will be set to PerformanceMode.THROUGHPUT.
     [Step 4/11] Reading model files
     [ INFO ] Loading model files
-    [ INFO ] Read model took 12.67 ms
+    [ INFO ] Read model took 4.18 ms
     [ INFO ] Original model I/O parameters:
     [ INFO ] Model inputs:
     [ INFO ]     e1 (node: e1) : i64 / [...] / []
@@ -607,7 +619,7 @@ inference can also be obtained by looking at the benchmark app results.
 
 .. parsed-literal::
 
-    [ INFO ] Compile model took 73.17 ms
+    [ INFO ] Compile model took 53.83 ms
     [Step 8/11] Querying optimal runtime parameters
     [ INFO ] Model:
     [ INFO ]   NETWORK_NAME: Model0
@@ -633,21 +645,21 @@ inference can also be obtained by looking at the benchmark app results.
     [ INFO ] Fill input 'rel' with random values
     [Step 10/11] Measuring performance (Start inference asynchronously, 12 inference requests, limits: 10000 ms duration)
     [ INFO ] Benchmarking in inference only mode (inputs filling are not included in measurement loop).
-    [ INFO ] First inference took 5.21 ms
+    [ INFO ] First inference took 3.90 ms
 
 
 .. parsed-literal::
 
     [Step 11/11] Dumping statistics report
     [ INFO ] Execution Devices:['CPU']
-    [ INFO ] Count:            105636 iterations
-    [ INFO ] Duration:         10001.35 ms
+    [ INFO ] Count:            104112 iterations
+    [ INFO ] Duration:         10001.51 ms
     [ INFO ] Latency:
     [ INFO ]    Median:        0.95 ms
-    [ INFO ]    Average:       0.98 ms
-    [ INFO ]    Min:           0.52 ms
-    [ INFO ]    Max:           8.65 ms
-    [ INFO ] Throughput:   10562.17 FPS
+    [ INFO ]    Average:       0.97 ms
+    [ INFO ]    Min:           0.53 ms
+    [ INFO ]    Max:           8.98 ms
+    [ INFO ] Throughput:   10409.63 FPS
 
 
 Conclusions
diff --git a/docs/notebooks/220-cross-lingual-books-alignment-with-output.rst b/docs/notebooks/220-cross-lingual-books-alignment-with-output.rst
index 0f7e778b095601..eb00d5b5ca63f9 100644
--- a/docs/notebooks/220-cross-lingual-books-alignment-with-output.rst
+++ b/docs/notebooks/220-cross-lingual-books-alignment-with-output.rst
@@ -22,7 +22,7 @@ The notebook guides you through the entire process of creating a
 parallel book: from obtaining raw texts to building a visualization of
 aligned sentences. Here is the pipeline diagram:
 
-|image01|
+|image0|
 
 Visualizing the result allows you to identify areas for improvement in
 the pipeline steps, as indicated in the diagram.
@@ -37,8 +37,8 @@ Prerequisites
 -  ``seaborn`` - for alignment matrix visualization
 -  ``ipywidgets`` - for displaying HTML and JS output in the notebook
 
-
-**Table of contents:**
+Table of contents:
+^^^^^^^^^^^^^^^^^^
 
 -  `Get Books <#get-books>`__
 -  `Clean Text <#clean-text>`__
@@ -54,8 +54,7 @@ Prerequisites
 -  `Speed up Embeddings
    Computation <#speed-up-embeddings-computation>`__
 
-
-.. |image01| image:: https://user-images.githubusercontent.com/51917466/254582697-18f3ab38-e264-4b2c-a088-8e54b855c1b2.png
+.. |image0| image:: https://user-images.githubusercontent.com/51917466/254582697-18f3ab38-e264-4b2c-a088-8e54b855c1b2.png
 
 .. code:: ipython3
 
@@ -113,7 +112,7 @@ Let’s check that we got the right books by showing a part of the texts:
 
 .. parsed-literal::
 
-    The Project Gutenberg eBook of Anna Karenina
+    The Project Gutenberg eBook of Anna Karenina
 
     This ebook is for the use of anyone anywhere in the United States and
     most other parts of the world at no cost and with almost no restrictions
@@ -401,12 +400,12 @@ languages. It has the same architecture as the BERT model but has been
 trained on a different task: to produce identical embeddings for
 translation pairs.
 
-|image0|
+|image01|
 
 This makes LaBSE a great choice for our task and it can be reused for
 different language pairs still producing good results.
 
-.. |image0| image:: https://user-images.githubusercontent.com/51917466/254582913-51531880-373b-40cb-bbf6-1965859df2eb.png%22
+.. |image01| image:: https://user-images.githubusercontent.com/51917466/254582913-51531880-373b-40cb-bbf6-1965859df2eb.png
 
 .. code:: ipython3
 
@@ -855,17 +854,15 @@ Speed up Embeddings Computation
 Let’s see how we can speed up the most computationally complex part of
 the pipeline - getting embeddings. You might wonder why, when using
 OpenVINO, you need to compile the model after reading it. There are two
-main reasons for this:
-
-1. Compatibility with different devices. The
+main reasons for this: 1. Compatibility with different devices. The
 model can be compiled to run on a `specific
-device `__,
-like CPU, GPU. Each device may work with different data types,
+device `__,
+like CPU, GPU or GNA. Each device may work with different data types,
 support different features, and gain performance by changing the neural
 network for a specific computing model. With OpenVINO, you do not need
 to store multiple copies of the network with optimized for different
-hardware. A universal OpenVINO model representation is enough.
-2. Optimization for different scenarios. For example, one scenario
+hardware. A universal OpenVINO model representation is enough. 1.
+Optimization for different scenarios. For example, one scenario
 prioritizes minimizing the *time between starting and finishing model
 inference* (`latency-oriented
 optimization `__).
@@ -937,7 +934,7 @@ advance and fill it in as the inference requests are executed.
 
 Let’s compare the models and plot the results.
 
-   **Note**: To get a more accurate benchmark, use the `Benchmark Python
+   **NOTE**: To get a more accurate benchmark, use the `Benchmark Python
    Tool `__
 
 .. code:: ipython3
@@ -1046,8 +1043,9 @@ Async mode with throughput hint, we get ×3.21 (or 221%) performance
 boost.
 
 Here are useful links with information about the techniques used in this
-notebook:
-
-- `OpenVINO performance hints `__
-- `OpenVINO Async API `__
-- `Throughput Optimizations `__
+notebook: - `OpenVINO performance
+hints `__
+- `OpenVINO Async
+API `__
+- `Throughput
+Optimizations `__
diff --git a/docs/notebooks/220-cross-lingual-books-alignment-with-output_files/index.html.tmp b/docs/notebooks/220-cross-lingual-books-alignment-with-output_files/index.html.tmp
deleted file mode 100644
index bec185bbcceec2..00000000000000
--- a/docs/notebooks/220-cross-lingual-books-alignment-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,8 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/220-cross-lingual-books-alignment-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/220-cross-lingual-books-alignment-with-output_files/
../
-220-cross-lingual-books-alignment-with-output_3..> 26-Jan-2024 01:05               24464
-220-cross-lingual-books-alignment-with-output_4..> 26-Jan-2024 01:05               29527
-

-
diff --git a/docs/notebooks/221-machine-translation-with-output.rst b/docs/notebooks/221-machine-translation-with-output.rst
index 0a5f6eb62471e7..c7431e9770701f 100644
--- a/docs/notebooks/221-machine-translation-with-output.rst
+++ b/docs/notebooks/221-machine-translation-with-output.rst
@@ -37,7 +37,7 @@ Table of contents:
 
 .. parsed-literal::
 
-    DEPRECATION: pytorch-lightning 1.6.5 has a non-standard dependency specifier torch>=1.8.*. pip 24.0 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of pytorch-lightning or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063
+    DEPRECATION: pytorch-lightning 1.6.5 has a non-standard dependency specifier torch>=1.8.*. pip 24.1 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of pytorch-lightning or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063
     
 
 .. parsed-literal::
@@ -47,7 +47,7 @@ Table of contents:
 
 .. parsed-literal::
 
-    DEPRECATION: pytorch-lightning 1.6.5 has a non-standard dependency specifier torch>=1.8.*. pip 24.0 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of pytorch-lightning or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063
+    DEPRECATION: pytorch-lightning 1.6.5 has a non-standard dependency specifier torch>=1.8.*. pip 24.1 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of pytorch-lightning or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063
     
 
 .. parsed-literal::
diff --git a/docs/notebooks/222-vision-image-colorization-with-output.rst b/docs/notebooks/222-vision-image-colorization-with-output.rst
index 6a07ece5881872..87a39a51abba11 100644
--- a/docs/notebooks/222-vision-image-colorization-with-output.rst
+++ b/docs/notebooks/222-vision-image-colorization-with-output.rst
@@ -42,18 +42,21 @@ About Colorization-siggraph
 See the `colorization `__
 repository for more details.
 
-**Table of contents:**
+Table of contents:
+^^^^^^^^^^^^^^^^^^
 
+-  `Imports <#imports>`__
+-  `Configurations <#configurations>`__
 
-- `Imports <#imports>`__
-- `Configurations <#configurations>`__
-- `Select inference device <#select-inference-device>`__
-- `Download the model <#download-the-model>`__
-- `Convert the model to OpenVINO IR <#convert-the-model-to-openvino-ir>`__
-- `Loading the Model <#loading-the-model>`__
-- `Utility Functions <#utility-functions>`__
-- `Load the Image <#load-the-image>`__
-- `Display Colorized Image <#display-colorized-image>`__
+   -  `Select inference device <#select-inference-device>`__
+
+-  `Download the model <#download-the-model>`__
+-  `Convert the model to OpenVINO
+   IR <#convert-the-model-to-openvino-ir>`__
+-  `Loading the Model <#loading-the-model>`__
+-  `Utility Functions <#utility-functions>`__
+-  `Load the Image <#load-the-image>`__
+-  `Display Colorized Image <#display-colorized-image>`__
 
 .. code:: ipython3
 
@@ -62,38 +65,34 @@ repository for more details.
 
 .. parsed-literal::
 
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-
-
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+    Requirement already satisfied: openvino-dev>=2023.1.0 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (2023.3.0)
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+    Requirement already satisfied: numpy>=1.16.6 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from openvino-dev>=2023.1.0) (1.23.5)
+    Requirement already satisfied: opencv-python in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from openvino-dev>=2023.1.0) (4.9.0.80)
+    Requirement already satisfied: openvino-telemetry>=2022.1.0 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from openvino-dev>=2023.1.0) (2023.2.1)
+    Requirement already satisfied: pillow>=8.1.2 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from openvino-dev>=2023.1.0) (10.2.0)
+    Requirement already satisfied: pyyaml>=5.4.1 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from openvino-dev>=2023.1.0) (6.0.1)
+    Requirement already satisfied: requests>=2.25.1 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from openvino-dev>=2023.1.0) (2.31.0)
+    Requirement already satisfied: scipy>=1.8 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from openvino-dev>=2023.1.0) (1.10.1)
+    Requirement already satisfied: texttable>=1.6.3 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from openvino-dev>=2023.1.0) (1.7.0)
 
 
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+    Requirement already satisfied: openvino==2023.3.0 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from openvino-dev>=2023.1.0) (2023.3.0)
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+    Requirement already satisfied: idna<4,>=2.5 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from requests>=2.25.1->openvino-dev>=2023.1.0) (3.6)
+    Requirement already satisfied: urllib3<3,>=1.21.1 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from requests>=2.25.1->openvino-dev>=2023.1.0) (2.2.0)
+    Requirement already satisfied: certifi>=2017.4.17 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from requests>=2.25.1->openvino-dev>=2023.1.0) (2024.2.2)
 
 
 .. parsed-literal::
 
-    DEPRECATION: pytorch-lightning 1.6.5 has a non-standard dependency specifier torch>=1.8.*. pip 24.0 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of pytorch-lightning or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063
+    DEPRECATION: pytorch-lightning 1.6.5 has a non-standard dependency specifier torch>=1.8.*. pip 24.1 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of pytorch-lightning or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063
 
 
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 .. parsed-literal::
 
-    ... 2%, 3264 KB, 3229 KB/s, 1 seconds passed
-... 2%, 3296 KB, 3254 KB/s, 1 seconds passed
-... 2%, 3328 KB, 3284 KB/s, 1 seconds passed
-... 2%, 3360 KB, 3238 KB/s, 1 seconds passed
-... 2%, 3392 KB, 3236 KB/s, 1 seconds passed
-... 2%, 3424 KB, 3261 KB/s, 1 seconds passed
-... 2%, 3456 KB, 3288 KB/s, 1 seconds passed
+    ... 1%, 1984 KB, 3260 KB/s, 0 seconds passed
+... 1%, 2016 KB, 3304 KB/s, 0 seconds passed
+... 1%, 2048 KB, 3354 KB/s, 0 seconds passed
+... 1%, 2080 KB, 3295 KB/s, 0 seconds passed
+... 1%, 2112 KB, 3285 KB/s, 0 seconds passed
+... 1%, 2144 KB, 3326 KB/s, 0 seconds passed
+... 1%, 2176 KB, 3373 KB/s, 0 seconds passed
 
 .. parsed-literal::
 
-    ... 2%, 3488 KB, 3243 KB/s, 1 seconds passed
-... 2%, 3520 KB, 3242 KB/s, 1 seconds passed
-... 2%, 3552 KB, 3269 KB/s, 1 seconds passed
-... 2%, 3584 KB, 3285 KB/s, 1 seconds passed
+    ... 1%, 2208 KB, 3317 KB/s, 0 seconds passed
+... 1%, 2240 KB, 3305 KB/s, 0 seconds passed
+... 1%, 2272 KB, 3345 KB/s, 0 seconds passed
+... 1%, 2304 KB, 3389 KB/s, 0 seconds passed
+... 1%, 2336 KB, 3335 KB/s, 0 seconds passed
 
 .. parsed-literal::
 
-    ... 2%, 3616 KB, 3252 KB/s, 1 seconds passed
-... 2%, 3648 KB, 3251 KB/s, 1 seconds passed
-... 2%, 3680 KB, 3277 KB/s, 1 seconds passed
-... 2%, 3712 KB, 3304 KB/s, 1 seconds passed
-... 2%, 3744 KB, 3260 KB/s, 1 seconds passed
-... 2%, 3776 KB, 3259 KB/s, 1 seconds passed
-... 3%, 3808 KB, 3285 KB/s, 1 seconds passed
-... 3%, 3840 KB, 3310 KB/s, 1 seconds passed
+    ... 1%, 2368 KB, 3323 KB/s, 0 seconds passed
+... 1%, 2400 KB, 3361 KB/s, 0 seconds passed
+... 1%, 2432 KB, 3403 KB/s, 0 seconds passed
+... 1%, 2464 KB, 3306 KB/s, 0 seconds passed
+... 1%, 2496 KB, 3339 KB/s, 0 seconds passed
+... 2%, 2528 KB, 3375 KB/s, 0 seconds passed
+... 2%, 2560 KB, 3415 KB/s, 0 seconds passed
 
 .. parsed-literal::
 
-    ... 3%, 3872 KB, 3269 KB/s, 1 seconds passed
-... 3%, 3904 KB, 3267 KB/s, 1 seconds passed
-... 3%, 3936 KB, 3291 KB/s, 1 seconds passed
-... 3%, 3968 KB, 3317 KB/s, 1 seconds passed
+    ... 2%, 2592 KB, 3324 KB/s, 0 seconds passed
+... 2%, 2624 KB, 3355 KB/s, 0 seconds passed
+... 2%, 2656 KB, 3390 KB/s, 0 seconds passed
+... 2%, 2688 KB, 3428 KB/s, 0 seconds passed
 
 .. parsed-literal::
 
-    ... 3%, 4000 KB, 3255 KB/s, 1 seconds passed
-... 3%, 4032 KB, 3273 KB/s, 1 seconds passed
-... 3%, 4064 KB, 3297 KB/s, 1 seconds passed
-... 3%, 4096 KB, 3311 KB/s, 1 seconds passed
+    ... 2%, 2720 KB, 3341 KB/s, 0 seconds passed
+... 2%, 2752 KB, 3370 KB/s, 0 seconds passed
+... 2%, 2784 KB, 3403 KB/s, 0 seconds passed
+... 2%, 2816 KB, 3440 KB/s, 0 seconds passed
+... 2%, 2848 KB, 3355 KB/s, 0 seconds passed
+... 2%, 2880 KB, 3383 KB/s, 0 seconds passed
+... 2%, 2912 KB, 3414 KB/s, 0 seconds passed
+... 2%, 2944 KB, 3450 KB/s, 0 seconds passed
 
 .. parsed-literal::
 
-    ... 3%, 4128 KB, 3263 KB/s, 1 seconds passed
-... 3%, 4160 KB, 3279 KB/s, 1 seconds passed
-... 3%, 4192 KB, 3303 KB/s, 1 seconds passed
-... 3%, 4224 KB, 3326 KB/s, 1 seconds passed
-... 3%, 4256 KB, 3287 KB/s, 1 seconds passed
-... 3%, 4288 KB, 3286 KB/s, 1 seconds passed
-... 3%, 4320 KB, 3309 KB/s, 1 seconds passed
-... 3%, 4352 KB, 3332 KB/s, 1 seconds passed
+    ... 2%, 2976 KB, 3368 KB/s, 0 seconds passed
+... 2%, 3008 KB, 3396 KB/s, 0 seconds passed
+... 2%, 3040 KB, 3427 KB/s, 0 seconds passed
+... 2%, 3072 KB, 3460 KB/s, 0 seconds passed
 
 .. parsed-literal::
 
-    ... 3%, 4384 KB, 3293 KB/s, 1 seconds passed
-... 3%, 4416 KB, 3292 KB/s, 1 seconds passed
-... 3%, 4448 KB, 3314 KB/s, 1 seconds passed
-... 3%, 4480 KB, 3336 KB/s, 1 seconds passed
+    ... 2%, 3104 KB, 3382 KB/s, 0 seconds passed
+... 2%, 3136 KB, 3409 KB/s, 0 seconds passed
+... 2%, 3168 KB, 3439 KB/s, 0 seconds passed
+... 2%, 3200 KB, 3470 KB/s, 0 seconds passed
+... 2%, 3232 KB, 3431 KB/s, 0 seconds passed
+... 2%, 3264 KB, 3421 KB/s, 0 seconds passed
+... 2%, 3296 KB, 3449 KB/s, 0 seconds passed
+... 2%, 3328 KB, 3478 KB/s, 0 seconds passed
 
 .. parsed-literal::
 
-    ... 3%, 4512 KB, 3298 KB/s, 1 seconds passed
-... 3%, 4544 KB, 3298 KB/s, 1 seconds passed
-... 3%, 4576 KB, 3319 KB/s, 1 seconds passed
-... 3%, 4608 KB, 3341 KB/s, 1 seconds passed
-... 3%, 4640 KB, 3305 KB/s, 1 seconds passed
-... 3%, 4672 KB, 3302 KB/s, 1 seconds passed
-... 3%, 4704 KB, 3323 KB/s, 1 seconds passed
+    ... 2%, 3360 KB, 3441 KB/s, 0 seconds passed
+... 2%, 3392 KB, 3430 KB/s, 0 seconds passed
+... 2%, 3424 KB, 3458 KB/s, 0 seconds passed
+... 2%, 3456 KB, 3487 KB/s, 0 seconds passed
+... 2%, 3488 KB, 3451 KB/s, 1 seconds passed
 
 .. parsed-literal::
 
-    ... 3%, 4736 KB, 3337 KB/s, 1 seconds passed
-... 3%, 4768 KB, 3308 KB/s, 1 seconds passed
-... 3%, 4800 KB, 3306 KB/s, 1 seconds passed
-... 3%, 4832 KB, 3327 KB/s, 1 seconds passed
+    ... 2%, 3520 KB, 3442 KB/s, 1 seconds passed
+... 2%, 3552 KB, 3467 KB/s, 1 seconds passed
+... 2%, 3584 KB, 3493 KB/s, 1 seconds passed
+... 2%, 3616 KB, 3423 KB/s, 1 seconds passed
+... 2%, 3648 KB, 3447 KB/s, 1 seconds passed
+... 2%, 3680 KB, 3472 KB/s, 1 seconds passed
+... 2%, 3712 KB, 3500 KB/s, 1 seconds passed
 
 .. parsed-literal::
 
-    ... 3%, 4864 KB, 3299 KB/s, 1 seconds passed
-... 3%, 4896 KB, 3298 KB/s, 1 seconds passed
-... 3%, 4928 KB, 3312 KB/s, 1 seconds passed
-... 3%, 4960 KB, 3331 KB/s, 1 seconds passed
-... 3%, 4992 KB, 3346 KB/s, 1 seconds passed
-... 3%, 5024 KB, 3318 KB/s, 1 seconds passed
+    ... 2%, 3744 KB, 3434 KB/s, 1 seconds passed
+... 2%, 3776 KB, 3457 KB/s, 1 seconds passed
+... 3%, 3808 KB, 3482 KB/s, 1 seconds passed
+... 3%, 3840 KB, 3507 KB/s, 1 seconds passed
 
 .. parsed-literal::
 
-    ... 4%, 5056 KB, 3317 KB/s, 1 seconds passed
-... 4%, 5088 KB, 3336 KB/s, 1 seconds passed
-... 4%, 5120 KB, 3356 KB/s, 1 seconds passed
-... 4%, 5152 KB, 3323 KB/s, 1 seconds passed
-... 4%, 5184 KB, 3321 KB/s, 1 seconds passed
-... 4%, 5216 KB, 3340 KB/s, 1 seconds passed
-... 4%, 5248 KB, 3359 KB/s, 1 seconds passed
+    ... 3%, 3872 KB, 3442 KB/s, 1 seconds passed
+... 3%, 3904 KB, 3464 KB/s, 1 seconds passed
+... 3%, 3936 KB, 3488 KB/s, 1 seconds passed
+... 3%, 3968 KB, 3513 KB/s, 1 seconds passed
+... 3%, 4000 KB, 3449 KB/s, 1 seconds passed
+... 3%, 4032 KB, 3471 KB/s, 1 seconds passed
+... 3%, 4064 KB, 3496 KB/s, 1 seconds passed
+... 3%, 4096 KB, 3520 KB/s, 1 seconds passed
 
 .. parsed-literal::
 
-    ... 4%, 5280 KB, 3326 KB/s, 1 seconds passed
-... 4%, 5312 KB, 3326 KB/s, 1 seconds passed
-... 4%, 5344 KB, 3343 KB/s, 1 seconds passed
-... 4%, 5376 KB, 3317 KB/s, 1 seconds passed
+    ... 3%, 4128 KB, 3458 KB/s, 1 seconds passed
+... 3%, 4160 KB, 3480 KB/s, 1 seconds passed
+... 3%, 4192 KB, 3503 KB/s, 1 seconds passed
+... 3%, 4224 KB, 3525 KB/s, 1 seconds passed
+... 3%, 4256 KB, 3495 KB/s, 1 seconds passed
 
 .. parsed-literal::
 
-    ... 4%, 5408 KB, 3317 KB/s, 1 seconds passed
-... 4%, 5440 KB, 3328 KB/s, 1 seconds passed
-... 4%, 5472 KB, 3346 KB/s, 1 seconds passed
-... 4%, 5504 KB, 3321 KB/s, 1 seconds passed
-... 4%, 5536 KB, 3321 KB/s, 1 seconds passed
-... 4%, 5568 KB, 3331 KB/s, 1 seconds passed
-... 4%, 5600 KB, 3349 KB/s, 1 seconds passed
+    ... 3%, 4288 KB, 3487 KB/s, 1 seconds passed
+... 3%, 4320 KB, 3509 KB/s, 1 seconds passed
+... 3%, 4352 KB, 3531 KB/s, 1 seconds passed
+... 3%, 4384 KB, 3501 KB/s, 1 seconds passed
+... 3%, 4416 KB, 3493 KB/s, 1 seconds passed
+... 3%, 4448 KB, 3515 KB/s, 1 seconds passed
+... 3%, 4480 KB, 3536 KB/s, 1 seconds passed
 
 .. parsed-literal::
 
-    ... 4%, 5632 KB, 3325 KB/s, 1 seconds passed
-... 4%, 5664 KB, 3324 KB/s, 1 seconds passed
-... 4%, 5696 KB, 3334 KB/s, 1 seconds passed
-... 4%, 5728 KB, 3352 KB/s, 1 seconds passed
+    ... 3%, 4512 KB, 3507 KB/s, 1 seconds passed
+... 3%, 4544 KB, 3498 KB/s, 1 seconds passed
+... 3%, 4576 KB, 3519 KB/s, 1 seconds passed
+... 3%, 4608 KB, 3540 KB/s, 1 seconds passed
+... 3%, 4640 KB, 3512 KB/s, 1 seconds passed
 
 .. parsed-literal::
 
-    ... 4%, 5760 KB, 3329 KB/s, 1 seconds passed
-... 4%, 5792 KB, 3327 KB/s, 1 seconds passed
-... 4%, 5824 KB, 3338 KB/s, 1 seconds passed
-... 4%, 5856 KB, 3355 KB/s, 1 seconds passed
-... 4%, 5888 KB, 3333 KB/s, 1 seconds passed
-... 4%, 5920 KB, 3333 KB/s, 1 seconds passed
+    ... 3%, 4672 KB, 3503 KB/s, 1 seconds passed
+... 3%, 4704 KB, 3523 KB/s, 1 seconds passed
+... 3%, 4736 KB, 3542 KB/s, 1 seconds passed
+... 3%, 4768 KB, 3488 KB/s, 1 seconds passed
+... 3%, 4800 KB, 3507 KB/s, 1 seconds passed
+... 3%, 4832 KB, 3527 KB/s, 1 seconds passed
+... 3%, 4864 KB, 3545 KB/s, 1 seconds passed
 
 .. parsed-literal::
 
-    ... 4%, 5952 KB, 3343 KB/s, 1 seconds passed
-... 4%, 5984 KB, 3358 KB/s, 1 seconds passed
-... 4%, 6016 KB, 3335 KB/s, 1 seconds passed
-... 4%, 6048 KB, 3335 KB/s, 1 seconds passed
-... 4%, 6080 KB, 3346 KB/s, 1 seconds passed
-... 4%, 6112 KB, 3360 KB/s, 1 seconds passed
+    ... 3%, 4896 KB, 3494 KB/s, 1 seconds passed
+... 3%, 4928 KB, 3511 KB/s, 1 seconds passed
+... 3%, 4960 KB, 3531 KB/s, 1 seconds passed
+... 3%, 4992 KB, 3506 KB/s, 1 seconds passed
 
 .. parsed-literal::
 
-    ... 4%, 6144 KB, 3338 KB/s, 1 seconds passed
-... 4%, 6176 KB, 3337 KB/s, 1 seconds passed
-... 4%, 6208 KB, 3347 KB/s, 1 seconds passed
-... 4%, 6240 KB, 3363 KB/s, 1 seconds passed
-... 4%, 6272 KB, 3341 KB/s, 1 seconds passed
+    ... 3%, 5024 KB, 3498 KB/s, 1 seconds passed
+... 4%, 5056 KB, 3515 KB/s, 1 seconds passed
+... 4%, 5088 KB, 3534 KB/s, 1 seconds passed
+... 4%, 5120 KB, 3510 KB/s, 1 seconds passed
+... 4%, 5152 KB, 3502 KB/s, 1 seconds passed
+... 4%, 5184 KB, 3519 KB/s, 1 seconds passed
+... 4%, 5216 KB, 3539 KB/s, 1 seconds passed
 
 .. parsed-literal::
 
-    ... 5%, 6304 KB, 3340 KB/s, 1 seconds passed
-... 5%, 6336 KB, 3351 KB/s, 1 seconds passed
-... 5%, 6368 KB, 3366 KB/s, 1 seconds passed
-... 5%, 6400 KB, 3345 KB/s, 1 seconds passed
-... 5%, 6432 KB, 3344 KB/s, 1 seconds passed
-... 5%, 6464 KB, 3354 KB/s, 1 seconds passed
-... 5%, 6496 KB, 3369 KB/s, 1 seconds passed
+    ... 4%, 5248 KB, 3514 KB/s, 1 seconds passed
+... 4%, 5280 KB, 3507 KB/s, 1 seconds passed
+... 4%, 5312 KB, 3524 KB/s, 1 seconds passed
+... 4%, 5344 KB, 3543 KB/s, 1 seconds passed
+... 4%, 5376 KB, 3519 KB/s, 1 seconds passed
 
 .. parsed-literal::
 
-    ... 5%, 6528 KB, 3348 KB/s, 1 seconds passed
-... 5%, 6560 KB, 3347 KB/s, 1 seconds passed
-... 5%, 6592 KB, 3357 KB/s, 1 seconds passed
-... 5%, 6624 KB, 3371 KB/s, 1 seconds passed
+    ... 4%, 5408 KB, 3512 KB/s, 1 seconds passed
+... 4%, 5440 KB, 3528 KB/s, 1 seconds passed
+... 4%, 5472 KB, 3546 KB/s, 1 seconds passed
+... 4%, 5504 KB, 3523 KB/s, 1 seconds passed
+... 4%, 5536 KB, 3516 KB/s, 1 seconds passed
+... 4%, 5568 KB, 3532 KB/s, 1 seconds passed
+... 4%, 5600 KB, 3550 KB/s, 1 seconds passed
 
 .. parsed-literal::
 
-    ... 5%, 6656 KB, 3351 KB/s, 1 seconds passed
-... 5%, 6688 KB, 3350 KB/s, 1 seconds passed
-... 5%, 6720 KB, 3359 KB/s, 2 seconds passed
-... 5%, 6752 KB, 3374 KB/s, 2 seconds passed
-... 5%, 6784 KB, 3354 KB/s, 2 seconds passed
-... 5%, 6816 KB, 3352 KB/s, 2 seconds passed
+    ... 4%, 5632 KB, 3527 KB/s, 1 seconds passed
+... 4%, 5664 KB, 3520 KB/s, 1 seconds passed
+... 4%, 5696 KB, 3536 KB/s, 1 seconds passed
+... 4%, 5728 KB, 3553 KB/s, 1 seconds passed
+... 4%, 5760 KB, 3530 KB/s, 1 seconds passed
 
 .. parsed-literal::
 
-    ... 5%, 6848 KB, 3362 KB/s, 2 seconds passed
-... 5%, 6880 KB, 3376 KB/s, 2 seconds passed
-... 5%, 6912 KB, 3356 KB/s, 2 seconds passed
-... 5%, 6944 KB, 3355 KB/s, 2 seconds passed
-... 5%, 6976 KB, 3364 KB/s, 2 seconds passed
-... 5%, 7008 KB, 3373 KB/s, 2 seconds passed
+    ... 4%, 5792 KB, 3523 KB/s, 1 seconds passed
+... 4%, 5824 KB, 3539 KB/s, 1 seconds passed
+... 4%, 5856 KB, 3556 KB/s, 1 seconds passed
+... 4%, 5888 KB, 3532 KB/s, 1 seconds passed
+... 4%, 5920 KB, 3529 KB/s, 1 seconds passed
+... 4%, 5952 KB, 3543 KB/s, 1 seconds passed
+... 4%, 5984 KB, 3560 KB/s, 1 seconds passed
 
 .. parsed-literal::
 
-    ... 5%, 7040 KB, 3358 KB/s, 2 seconds passed
-... 5%, 7072 KB, 3357 KB/s, 2 seconds passed
-... 5%, 7104 KB, 3367 KB/s, 2 seconds passed
-... 5%, 7136 KB, 3375 KB/s, 2 seconds passed
-... 5%, 7168 KB, 3361 KB/s, 2 seconds passed
+    ... 4%, 6016 KB, 3536 KB/s, 1 seconds passed
+... 4%, 6048 KB, 3533 KB/s, 1 seconds passed
+... 4%, 6080 KB, 3546 KB/s, 1 seconds passed
+... 4%, 6112 KB, 3563 KB/s, 1 seconds passed
+... 4%, 6144 KB, 3579 KB/s, 1 seconds passed
 
 .. parsed-literal::
 
-    ... 5%, 7200 KB, 3360 KB/s, 2 seconds passed
-... 5%, 7232 KB, 3369 KB/s, 2 seconds passed
-... 5%, 7264 KB, 3377 KB/s, 2 seconds passed
-... 5%, 7296 KB, 3363 KB/s, 2 seconds passed
-... 5%, 7328 KB, 3361 KB/s, 2 seconds passed
-... 5%, 7360 KB, 3372 KB/s, 2 seconds passed
-... 5%, 7392 KB, 3380 KB/s, 2 seconds passed
+    ... 4%, 6176 KB, 3537 KB/s, 1 seconds passed
+... 4%, 6208 KB, 3551 KB/s, 1 seconds passed
+... 4%, 6240 KB, 3566 KB/s, 1 seconds passed
+... 4%, 6272 KB, 3546 KB/s, 1 seconds passed
+... 5%, 6304 KB, 3540 KB/s, 1 seconds passed
+... 5%, 6336 KB, 3554 KB/s, 1 seconds passed
+... 5%, 6368 KB, 3568 KB/s, 1 seconds passed
 
 .. parsed-literal::
 
-    ... 5%, 7424 KB, 3365 KB/s, 2 seconds passed
-... 5%, 7456 KB, 3363 KB/s, 2 seconds passed
-... 5%, 7488 KB, 3368 KB/s, 2 seconds passed
-... 5%, 7520 KB, 3381 KB/s, 2 seconds passed
+    ... 5%, 6400 KB, 3546 KB/s, 1 seconds passed
+... 5%, 6432 KB, 3541 KB/s, 1 seconds passed
+... 5%, 6464 KB, 3555 KB/s, 1 seconds passed
+... 5%, 6496 KB, 3570 KB/s, 1 seconds passed
 
 .. parsed-literal::
 
-    ... 5%, 7552 KB, 3367 KB/s, 2 seconds passed
-... 6%, 7584 KB, 3365 KB/s, 2 seconds passed
-... 6%, 7616 KB, 3370 KB/s, 2 seconds passed
-... 6%, 7648 KB, 3383 KB/s, 2 seconds passed
-... 6%, 7680 KB, 3370 KB/s, 2 seconds passed
-... 6%, 7712 KB, 3368 KB/s, 2 seconds passed
+    ... 5%, 6528 KB, 3548 KB/s, 1 seconds passed
+... 5%, 6560 KB, 3544 KB/s, 1 seconds passed
+... 5%, 6592 KB, 3558 KB/s, 1 seconds passed
+... 5%, 6624 KB, 3573 KB/s, 1 seconds passed
+... 5%, 6656 KB, 3551 KB/s, 1 seconds passed
+... 5%, 6688 KB, 3547 KB/s, 1 seconds passed
+... 5%, 6720 KB, 3561 KB/s, 1 seconds passed
 
 .. parsed-literal::
 
-    ... 6%, 7744 KB, 3373 KB/s, 2 seconds passed
-... 6%, 7776 KB, 3385 KB/s, 2 seconds passed
-... 6%, 7808 KB, 3372 KB/s, 2 seconds passed
-... 6%, 7840 KB, 3370 KB/s, 2 seconds passed
-... 6%, 7872 KB, 3375 KB/s, 2 seconds passed
-... 6%, 7904 KB, 3387 KB/s, 2 seconds passed
+    ... 5%, 6752 KB, 3575 KB/s, 1 seconds passed
+... 5%, 6784 KB, 3554 KB/s, 1 seconds passed
+... 5%, 6816 KB, 3552 KB/s, 1 seconds passed
+... 5%, 6848 KB, 3565 KB/s, 1 seconds passed
+... 5%, 6880 KB, 3578 KB/s, 1 seconds passed
 
 .. parsed-literal::
 
-    ... 6%, 7936 KB, 3375 KB/s, 2 seconds passed
-... 6%, 7968 KB, 3375 KB/s, 2 seconds passed
-... 6%, 8000 KB, 3383 KB/s, 2 seconds passed
-... 6%, 8032 KB, 3389 KB/s, 2 seconds passed
-... 6%, 8064 KB, 3376 KB/s, 2 seconds passed
+    ... 5%, 6912 KB, 3557 KB/s, 1 seconds passed
+... 5%, 6944 KB, 3554 KB/s, 1 seconds passed
+... 5%, 6976 KB, 3568 KB/s, 1 seconds passed
+... 5%, 7008 KB, 3580 KB/s, 1 seconds passed
+... 5%, 7040 KB, 3560 KB/s, 1 seconds passed
+... 5%, 7072 KB, 3559 KB/s, 1 seconds passed
+... 5%, 7104 KB, 3570 KB/s, 1 seconds passed
 
 .. parsed-literal::
 
-    ... 6%, 8096 KB, 3374 KB/s, 2 seconds passed
-... 6%, 8128 KB, 3378 KB/s, 2 seconds passed
-... 6%, 8160 KB, 3390 KB/s, 2 seconds passed
-... 6%, 8192 KB, 3377 KB/s, 2 seconds passed
-... 6%, 8224 KB, 3376 KB/s, 2 seconds passed
-... 6%, 8256 KB, 3380 KB/s, 2 seconds passed
-... 6%, 8288 KB, 3391 KB/s, 2 seconds passed
+    ... 5%, 7136 KB, 3584 KB/s, 1 seconds passed
+... 5%, 7168 KB, 3565 KB/s, 2 seconds passed
+... 5%, 7200 KB, 3561 KB/s, 2 seconds passed
+... 5%, 7232 KB, 3572 KB/s, 2 seconds passed
+... 5%, 7264 KB, 3586 KB/s, 2 seconds passed
 
 .. parsed-literal::
 
-    ... 6%, 8320 KB, 3379 KB/s, 2 seconds passed
-... 6%, 8352 KB, 3377 KB/s, 2 seconds passed
-... 6%, 8384 KB, 3381 KB/s, 2 seconds passed
-... 6%, 8416 KB, 3393 KB/s, 2 seconds passed
+    ... 5%, 7296 KB, 3566 KB/s, 2 seconds passed
+... 5%, 7328 KB, 3561 KB/s, 2 seconds passed
+... 5%, 7360 KB, 3574 KB/s, 2 seconds passed
+... 5%, 7392 KB, 3586 KB/s, 2 seconds passed
+... 5%, 7424 KB, 3567 KB/s, 2 seconds passed
+... 5%, 7456 KB, 3563 KB/s, 2 seconds passed
 
 .. parsed-literal::
 
-    ... 6%, 8448 KB, 3381 KB/s, 2 seconds passed
-... 6%, 8480 KB, 3380 KB/s, 2 seconds passed
-... 6%, 8512 KB, 3383 KB/s, 2 seconds passed
-... 6%, 8544 KB, 3395 KB/s, 2 seconds passed
-... 6%, 8576 KB, 3383 KB/s, 2 seconds passed
-... 6%, 8608 KB, 3381 KB/s, 2 seconds passed
+    ... 5%, 7488 KB, 3575 KB/s, 2 seconds passed
+... 5%, 7520 KB, 3588 KB/s, 2 seconds passed
+... 5%, 7552 KB, 3569 KB/s, 2 seconds passed
+... 6%, 7584 KB, 3567 KB/s, 2 seconds passed
+... 6%, 7616 KB, 3579 KB/s, 2 seconds passed
+... 6%, 7648 KB, 3591 KB/s, 2 seconds passed
 
 .. parsed-literal::
 
-    ... 6%, 8640 KB, 3385 KB/s, 2 seconds passed
-... 6%, 8672 KB, 3397 KB/s, 2 seconds passed
-... 6%, 8704 KB, 3385 KB/s, 2 seconds passed
-... 6%, 8736 KB, 3383 KB/s, 2 seconds passed
-... 6%, 8768 KB, 3386 KB/s, 2 seconds passed
-... 6%, 8800 KB, 3398 KB/s, 2 seconds passed
+    ... 6%, 7680 KB, 3572 KB/s, 2 seconds passed
+... 6%, 7712 KB, 3569 KB/s, 2 seconds passed
+... 6%, 7744 KB, 3581 KB/s, 2 seconds passed
+... 6%, 7776 KB, 3593 KB/s, 2 seconds passed
+... 6%, 7808 KB, 3574 KB/s, 2 seconds passed
+... 6%, 7840 KB, 3571 KB/s, 2 seconds passed
 
 .. parsed-literal::
 
-    ... 7%, 8832 KB, 3387 KB/s, 2 seconds passed
-... 7%, 8864 KB, 3384 KB/s, 2 seconds passed
-... 7%, 8896 KB, 3387 KB/s, 2 seconds passed
-... 7%, 8928 KB, 3399 KB/s, 2 seconds passed
-... 7%, 8960 KB, 3388 KB/s, 2 seconds passed
+    ... 6%, 7872 KB, 3583 KB/s, 2 seconds passed
+... 6%, 7904 KB, 3595 KB/s, 2 seconds passed
+... 6%, 7936 KB, 3577 KB/s, 2 seconds passed
+... 6%, 7968 KB, 3575 KB/s, 2 seconds passed
+... 6%, 8000 KB, 3585 KB/s, 2 seconds passed
+... 6%, 8032 KB, 3597 KB/s, 2 seconds passed
 
 .. parsed-literal::
 
-    ... 7%, 8992 KB, 3387 KB/s, 2 seconds passed
-... 7%, 9024 KB, 3390 KB/s, 2 seconds passed
-... 7%, 9056 KB, 3400 KB/s, 2 seconds passed
-... 7%, 9088 KB, 3390 KB/s, 2 seconds passed
-... 7%, 9120 KB, 3388 KB/s, 2 seconds passed
-... 7%, 9152 KB, 3391 KB/s, 2 seconds passed
-... 7%, 9184 KB, 3402 KB/s, 2 seconds passed
+    ... 6%, 8064 KB, 3578 KB/s, 2 seconds passed
+... 6%, 8096 KB, 3577 KB/s, 2 seconds passed
+... 6%, 8128 KB, 3587 KB/s, 2 seconds passed
+... 6%, 8160 KB, 3599 KB/s, 2 seconds passed
+... 6%, 8192 KB, 3568 KB/s, 2 seconds passed
 
 .. parsed-literal::
 
-    ... 7%, 9216 KB, 3384 KB/s, 2 seconds passed
-... 7%, 9248 KB, 3389 KB/s, 2 seconds passed
-... 7%, 9280 KB, 3392 KB/s, 2 seconds passed
-... 7%, 9312 KB, 3403 KB/s, 2 seconds passed
+    ... 6%, 8224 KB, 3575 KB/s, 2 seconds passed
+... 6%, 8256 KB, 3588 KB/s, 2 seconds passed
+... 6%, 8288 KB, 3599 KB/s, 2 seconds passed
+... 6%, 8320 KB, 3571 KB/s, 2 seconds passed
+... 6%, 8352 KB, 3577 KB/s, 2 seconds passed
+... 6%, 8384 KB, 3590 KB/s, 2 seconds passed
+... 6%, 8416 KB, 3601 KB/s, 2 seconds passed
 
 .. parsed-literal::
 
-    ... 7%, 9344 KB, 3386 KB/s, 2 seconds passed
-... 7%, 9376 KB, 3391 KB/s, 2 seconds passed
-... 7%, 9408 KB, 3394 KB/s, 2 seconds passed
-... 7%, 9440 KB, 3404 KB/s, 2 seconds passed
-... 7%, 9472 KB, 3394 KB/s, 2 seconds passed
-... 7%, 9504 KB, 3392 KB/s, 2 seconds passed
+    ... 6%, 8448 KB, 3583 KB/s, 2 seconds passed
+... 6%, 8480 KB, 3579 KB/s, 2 seconds passed
+... 6%, 8512 KB, 3591 KB/s, 2 seconds passed
+... 6%, 8544 KB, 3602 KB/s, 2 seconds passed
+... 6%, 8576 KB, 3575 KB/s, 2 seconds passed
 
 .. parsed-literal::
 
-    ... 7%, 9536 KB, 3395 KB/s, 2 seconds passed
-... 7%, 9568 KB, 3405 KB/s, 2 seconds passed
-... 7%, 9600 KB, 3396 KB/s, 2 seconds passed
-... 7%, 9632 KB, 3393 KB/s, 2 seconds passed
-... 7%, 9664 KB, 3397 KB/s, 2 seconds passed
-... 7%, 9696 KB, 3407 KB/s, 2 seconds passed
+    ... 6%, 8608 KB, 3581 KB/s, 2 seconds passed
+... 6%, 8640 KB, 3593 KB/s, 2 seconds passed
+... 6%, 8672 KB, 3603 KB/s, 2 seconds passed
+... 6%, 8704 KB, 3576 KB/s, 2 seconds passed
+... 6%, 8736 KB, 3583 KB/s, 2 seconds passed
+... 6%, 8768 KB, 3594 KB/s, 2 seconds passed
+... 6%, 8800 KB, 3604 KB/s, 2 seconds passed
 
 .. parsed-literal::
 
-    ... 7%, 9728 KB, 3398 KB/s, 2 seconds passed
-... 7%, 9760 KB, 3395 KB/s, 2 seconds passed
-... 7%, 9792 KB, 3398 KB/s, 2 seconds passed
-... 7%, 9824 KB, 3408 KB/s, 2 seconds passed
-... 7%, 9856 KB, 3399 KB/s, 2 seconds passed
+    ... 7%, 8832 KB, 3578 KB/s, 2 seconds passed
+... 7%, 8864 KB, 3584 KB/s, 2 seconds passed
+... 7%, 8896 KB, 3596 KB/s, 2 seconds passed
+... 7%, 8928 KB, 3606 KB/s, 2 seconds passed
+... 7%, 8960 KB, 3579 KB/s, 2 seconds passed
 
 .. parsed-literal::
 
-    ... 7%, 9888 KB, 3396 KB/s, 2 seconds passed
-... 7%, 9920 KB, 3399 KB/s, 2 seconds passed
-... 7%, 9952 KB, 3393 KB/s, 2 seconds passed
-... 7%, 9984 KB, 3393 KB/s, 2 seconds passed
-... 7%, 10016 KB, 3397 KB/s, 2 seconds passed
-... 7%, 10048 KB, 3400 KB/s, 2 seconds passed
-... 8%, 10080 KB, 3410 KB/s, 2 seconds passed
+    ... 7%, 8992 KB, 3586 KB/s, 2 seconds passed
+... 7%, 9024 KB, 3597 KB/s, 2 seconds passed
+... 7%, 9056 KB, 3607 KB/s, 2 seconds passed
+... 7%, 9088 KB, 3581 KB/s, 2 seconds passed
+... 7%, 9120 KB, 3588 KB/s, 2 seconds passed
+... 7%, 9152 KB, 3599 KB/s, 2 seconds passed
+... 7%, 9184 KB, 3608 KB/s, 2 seconds passed
 
 .. parsed-literal::
 
-    ... 8%, 10112 KB, 3395 KB/s, 2 seconds passed
-... 8%, 10144 KB, 3399 KB/s, 2 seconds passed
-... 8%, 10176 KB, 3402 KB/s, 2 seconds passed
-... 8%, 10208 KB, 3411 KB/s, 2 seconds passed
+    ... 7%, 9216 KB, 3583 KB/s, 2 seconds passed
+... 7%, 9248 KB, 3589 KB/s, 2 seconds passed
+... 7%, 9280 KB, 3600 KB/s, 2 seconds passed
+... 7%, 9312 KB, 3609 KB/s, 2 seconds passed
+... 7%, 9344 KB, 3596 KB/s, 2 seconds passed
 
 .. parsed-literal::
 
-    ... 8%, 10240 KB, 3396 KB/s, 3 seconds passed
-... 8%, 10272 KB, 3400 KB/s, 3 seconds passed
-... 8%, 10304 KB, 3403 KB/s, 3 seconds passed
-... 8%, 10336 KB, 3412 KB/s, 3 seconds passed
-... 8%, 10368 KB, 3397 KB/s, 3 seconds passed
-... 8%, 10400 KB, 3401 KB/s, 3 seconds passed
+    ... 7%, 9376 KB, 3593 KB/s, 2 seconds passed
+... 7%, 9408 KB, 3602 KB/s, 2 seconds passed
+... 7%, 9440 KB, 3612 KB/s, 2 seconds passed
+... 7%, 9472 KB, 3597 KB/s, 2 seconds passed
+... 7%, 9504 KB, 3594 KB/s, 2 seconds passed
+... 7%, 9536 KB, 3603 KB/s, 2 seconds passed
+... 7%, 9568 KB, 3613 KB/s, 2 seconds passed
 
 .. parsed-literal::
 
-    ... 8%, 10432 KB, 3404 KB/s, 3 seconds passed
-... 8%, 10464 KB, 3413 KB/s, 3 seconds passed
-... 8%, 10496 KB, 3396 KB/s, 3 seconds passed
-... 8%, 10528 KB, 3401 KB/s, 3 seconds passed
-... 8%, 10560 KB, 3405 KB/s, 3 seconds passed
+    ... 7%, 9600 KB, 3588 KB/s, 2 seconds passed
+... 7%, 9632 KB, 3595 KB/s, 2 seconds passed
+... 7%, 9664 KB, 3605 KB/s, 2 seconds passed
+... 7%, 9696 KB, 3614 KB/s, 2 seconds passed
 
 .. parsed-literal::
 
-    ... 8%, 10592 KB, 3399 KB/s, 3 seconds passed
-... 8%, 10624 KB, 3397 KB/s, 3 seconds passed
-... 8%, 10656 KB, 3399 KB/s, 3 seconds passed
-... 8%, 10688 KB, 3406 KB/s, 3 seconds passed
-... 8%, 10720 KB, 3401 KB/s, 3 seconds passed
-... 8%, 10752 KB, 3401 KB/s, 3 seconds passed
+    ... 7%, 9728 KB, 3590 KB/s, 2 seconds passed
+... 7%, 9760 KB, 3596 KB/s, 2 seconds passed
+... 7%, 9792 KB, 3606 KB/s, 2 seconds passed
+... 7%, 9824 KB, 3615 KB/s, 2 seconds passed
+... 7%, 9856 KB, 3591 KB/s, 2 seconds passed
+... 7%, 9888 KB, 3597 KB/s, 2 seconds passed
+... 7%, 9920 KB, 3607 KB/s, 2 seconds passed
+... 7%, 9952 KB, 3616 KB/s, 2 seconds passed
 
 .. parsed-literal::
 
-    ... 8%, 10784 KB, 3404 KB/s, 3 seconds passed
-... 8%, 10816 KB, 3407 KB/s, 3 seconds passed
-... 8%, 10848 KB, 3416 KB/s, 3 seconds passed
-... 8%, 10880 KB, 3400 KB/s, 3 seconds passed
-... 8%, 10912 KB, 3405 KB/s, 3 seconds passed
-... 8%, 10944 KB, 3408 KB/s, 3 seconds passed
+    ... 7%, 9984 KB, 3592 KB/s, 2 seconds passed
+... 7%, 10016 KB, 3598 KB/s, 2 seconds passed
+... 7%, 10048 KB, 3608 KB/s, 2 seconds passed
+... 8%, 10080 KB, 3616 KB/s, 2 seconds passed
 
 .. parsed-literal::
 
-    ... 8%, 10976 KB, 3402 KB/s, 3 seconds passed
-... 8%, 11008 KB, 3401 KB/s, 3 seconds passed
-... 8%, 11040 KB, 3403 KB/s, 3 seconds passed
-... 8%, 11072 KB, 3410 KB/s, 3 seconds passed
-... 8%, 11104 KB, 3418 KB/s, 3 seconds passed
+    ... 8%, 10112 KB, 3593 KB/s, 2 seconds passed
+... 8%, 10144 KB, 3599 KB/s, 2 seconds passed
+... 8%, 10176 KB, 3609 KB/s, 2 seconds passed
+... 8%, 10208 KB, 3617 KB/s, 2 seconds passed
+... 8%, 10240 KB, 3596 KB/s, 2 seconds passed
+... 8%, 10272 KB, 3602 KB/s, 2 seconds passed
+... 8%, 10304 KB, 3611 KB/s, 2 seconds passed
+... 8%, 10336 KB, 3620 KB/s, 2 seconds passed
 
 .. parsed-literal::
 
-    ... 8%, 11136 KB, 3401 KB/s, 3 seconds passed
-... 8%, 11168 KB, 3403 KB/s, 3 seconds passed
-... 8%, 11200 KB, 3410 KB/s, 3 seconds passed
-... 8%, 11232 KB, 3404 KB/s, 3 seconds passed
-... 8%, 11264 KB, 3403 KB/s, 3 seconds passed
+    ... 8%, 10368 KB, 3598 KB/s, 2 seconds passed
+... 8%, 10400 KB, 3602 KB/s, 2 seconds passed
+... 8%, 10432 KB, 3612 KB/s, 2 seconds passed
+... 8%, 10464 KB, 3620 KB/s, 2 seconds passed
 
 .. parsed-literal::
 
-    ... 8%, 11296 KB, 3405 KB/s, 3 seconds passed
-... 8%, 11328 KB, 3411 KB/s, 3 seconds passed
-... 9%, 11360 KB, 3407 KB/s, 3 seconds passed
-... 9%, 11392 KB, 3406 KB/s, 3 seconds passed
-... 9%, 11424 KB, 3405 KB/s, 3 seconds passed
-... 9%, 11456 KB, 3412 KB/s, 3 seconds passed
+    ... 8%, 10496 KB, 3598 KB/s, 2 seconds passed
+... 8%, 10528 KB, 3603 KB/s, 2 seconds passed
+... 8%, 10560 KB, 3614 KB/s, 2 seconds passed
+... 8%, 10592 KB, 3622 KB/s, 2 seconds passed
+... 8%, 10624 KB, 3600 KB/s, 2 seconds passed
+... 8%, 10656 KB, 3605 KB/s, 2 seconds passed
+... 8%, 10688 KB, 3615 KB/s, 2 seconds passed
+... 8%, 10720 KB, 3623 KB/s, 2 seconds passed
 
 .. parsed-literal::
 
-    ... 9%, 11488 KB, 3406 KB/s, 3 seconds passed
-... 9%, 11520 KB, 3405 KB/s, 3 seconds passed
-... 9%, 11552 KB, 3408 KB/s, 3 seconds passed
-... 9%, 11584 KB, 3413 KB/s, 3 seconds passed
-... 9%, 11616 KB, 3409 KB/s, 3 seconds passed
-... 9%, 11648 KB, 3406 KB/s, 3 seconds passed
+    ... 8%, 10752 KB, 3601 KB/s, 2 seconds passed
+... 8%, 10784 KB, 3606 KB/s, 2 seconds passed
+... 8%, 10816 KB, 3616 KB/s, 2 seconds passed
+... 8%, 10848 KB, 3623 KB/s, 2 seconds passed
 
 .. parsed-literal::
 
-    ... 9%, 11680 KB, 3409 KB/s, 3 seconds passed
-... 9%, 11712 KB, 3414 KB/s, 3 seconds passed
-... 9%, 11744 KB, 3409 KB/s, 3 seconds passed
-... 9%, 11776 KB, 3407 KB/s, 3 seconds passed
-... 9%, 11808 KB, 3409 KB/s, 3 seconds passed
-... 9%, 11840 KB, 3415 KB/s, 3 seconds passed
+    ... 8%, 10880 KB, 3602 KB/s, 3 seconds passed
+... 8%, 10912 KB, 3607 KB/s, 3 seconds passed
+... 8%, 10944 KB, 3617 KB/s, 3 seconds passed
+... 8%, 10976 KB, 3624 KB/s, 3 seconds passed
+... 8%, 11008 KB, 3603 KB/s, 3 seconds passed
+... 8%, 11040 KB, 3608 KB/s, 3 seconds passed
+... 8%, 11072 KB, 3617 KB/s, 3 seconds passed
 
 .. parsed-literal::
 
-    ... 9%, 11872 KB, 3409 KB/s, 3 seconds passed
-... 9%, 11904 KB, 3408 KB/s, 3 seconds passed
-... 9%, 11936 KB, 3410 KB/s, 3 seconds passed
-... 9%, 11968 KB, 3416 KB/s, 3 seconds passed
-... 9%, 12000 KB, 3411 KB/s, 3 seconds passed
+    ... 8%, 11104 KB, 3606 KB/s, 3 seconds passed
+... 8%, 11136 KB, 3603 KB/s, 3 seconds passed
+... 8%, 11168 KB, 3608 KB/s, 3 seconds passed
+... 8%, 11200 KB, 3618 KB/s, 3 seconds passed
+... 8%, 11232 KB, 3607 KB/s, 3 seconds passed
 
 .. parsed-literal::
 
-    ... 9%, 12032 KB, 3409 KB/s, 3 seconds passed
-... 9%, 12064 KB, 3411 KB/s, 3 seconds passed
-... 9%, 12096 KB, 3416 KB/s, 3 seconds passed
-... 9%, 12128 KB, 3412 KB/s, 3 seconds passed
-... 9%, 12160 KB, 3410 KB/s, 3 seconds passed
-... 9%, 12192 KB, 3412 KB/s, 3 seconds passed
+    ... 8%, 11264 KB, 3605 KB/s, 3 seconds passed
+... 8%, 11296 KB, 3610 KB/s, 3 seconds passed
+... 8%, 11328 KB, 3619 KB/s, 3 seconds passed
+... 9%, 11360 KB, 3611 KB/s, 3 seconds passed
+... 9%, 11392 KB, 3605 KB/s, 3 seconds passed
+... 9%, 11424 KB, 3611 KB/s, 3 seconds passed
+... 9%, 11456 KB, 3620 KB/s, 3 seconds passed
 
 .. parsed-literal::
 
-    ... 9%, 12224 KB, 3417 KB/s, 3 seconds passed
-... 9%, 12256 KB, 3413 KB/s, 3 seconds passed
-... 9%, 12288 KB, 3411 KB/s, 3 seconds passed
-... 9%, 12320 KB, 3412 KB/s, 3 seconds passed
-... 9%, 12352 KB, 3418 KB/s, 3 seconds passed
+    ... 9%, 11488 KB, 3608 KB/s, 3 seconds passed
+... 9%, 11520 KB, 3602 KB/s, 3 seconds passed
+... 9%, 11552 KB, 3611 KB/s, 3 seconds passed
+... 9%, 11584 KB, 3620 KB/s, 3 seconds passed
+... 9%, 11616 KB, 3609 KB/s, 3 seconds passed
 
 .. parsed-literal::
 
-    ... 9%, 12384 KB, 3413 KB/s, 3 seconds passed
-... 9%, 12416 KB, 3412 KB/s, 3 seconds passed
-... 9%, 12448 KB, 3413 KB/s, 3 seconds passed
-... 9%, 12480 KB, 3418 KB/s, 3 seconds passed
-... 9%, 12512 KB, 3414 KB/s, 3 seconds passed
-... 9%, 12544 KB, 3413 KB/s, 3 seconds passed
+    ... 9%, 11648 KB, 3604 KB/s, 3 seconds passed
+... 9%, 11680 KB, 3613 KB/s, 3 seconds passed
+... 9%, 11712 KB, 3621 KB/s, 3 seconds passed
+... 9%, 11744 KB, 3611 KB/s, 3 seconds passed
+... 9%, 11776 KB, 3605 KB/s, 3 seconds passed
+... 9%, 11808 KB, 3614 KB/s, 3 seconds passed
+... 9%, 11840 KB, 3622 KB/s, 3 seconds passed
 
 .. parsed-literal::
 
-    ... 9%, 12576 KB, 3413 KB/s, 3 seconds passed
-... 10%, 12608 KB, 3419 KB/s, 3 seconds passed
-... 10%, 12640 KB, 3415 KB/s, 3 seconds passed
-... 10%, 12672 KB, 3412 KB/s, 3 seconds passed
-... 10%, 12704 KB, 3414 KB/s, 3 seconds passed
-... 10%, 12736 KB, 3420 KB/s, 3 seconds passed
+    ... 9%, 11872 KB, 3612 KB/s, 3 seconds passed
+... 9%, 11904 KB, 3605 KB/s, 3 seconds passed
+... 9%, 11936 KB, 3615 KB/s, 3 seconds passed
+... 9%, 11968 KB, 3623 KB/s, 3 seconds passed
+... 9%, 12000 KB, 3612 KB/s, 3 seconds passed
 
 .. parsed-literal::
 
-    ... 10%, 12768 KB, 3415 KB/s, 3 seconds passed
-... 10%, 12800 KB, 3413 KB/s, 3 seconds passed
-... 10%, 12832 KB, 3415 KB/s, 3 seconds passed
-... 10%, 12864 KB, 3420 KB/s, 3 seconds passed
-... 10%, 12896 KB, 3416 KB/s, 3 seconds passed
+    ... 9%, 12032 KB, 3607 KB/s, 3 seconds passed
+... 9%, 12064 KB, 3615 KB/s, 3 seconds passed
+... 9%, 12096 KB, 3624 KB/s, 3 seconds passed
+... 9%, 12128 KB, 3613 KB/s, 3 seconds passed
+... 9%, 12160 KB, 3607 KB/s, 3 seconds passed
+... 9%, 12192 KB, 3616 KB/s, 3 seconds passed
+... 9%, 12224 KB, 3624 KB/s, 3 seconds passed
 
 .. parsed-literal::
 
-    ... 10%, 12928 KB, 3414 KB/s, 3 seconds passed
-... 10%, 12960 KB, 3415 KB/s, 3 seconds passed
-... 10%, 12992 KB, 3421 KB/s, 3 seconds passed
-... 10%, 13024 KB, 3417 KB/s, 3 seconds passed
-... 10%, 13056 KB, 3415 KB/s, 3 seconds passed
+    ... 9%, 12256 KB, 3614 KB/s, 3 seconds passed
+... 9%, 12288 KB, 3608 KB/s, 3 seconds passed
+... 9%, 12320 KB, 3617 KB/s, 3 seconds passed
+... 9%, 12352 KB, 3625 KB/s, 3 seconds passed
+... 9%, 12384 KB, 3615 KB/s, 3 seconds passed
 
 .. parsed-literal::
 
-    ... 10%, 13088 KB, 3416 KB/s, 3 seconds passed
-... 10%, 13120 KB, 3422 KB/s, 3 seconds passed
-... 10%, 13152 KB, 3420 KB/s, 3 seconds passed
-... 10%, 13184 KB, 3418 KB/s, 3 seconds passed
-... 10%, 13216 KB, 3420 KB/s, 3 seconds passed
-... 10%, 13248 KB, 3424 KB/s, 3 seconds passed
-... 10%, 13280 KB, 3421 KB/s, 3 seconds passed
+    ... 9%, 12416 KB, 3609 KB/s, 3 seconds passed
+... 9%, 12448 KB, 3618 KB/s, 3 seconds passed
+... 9%, 12480 KB, 3625 KB/s, 3 seconds passed
+... 9%, 12512 KB, 3615 KB/s, 3 seconds passed
+... 9%, 12544 KB, 3610 KB/s, 3 seconds passed
+... 9%, 12576 KB, 3619 KB/s, 3 seconds passed
+... 10%, 12608 KB, 3626 KB/s, 3 seconds passed
 
 .. parsed-literal::
 
-    ... 10%, 13312 KB, 3419 KB/s, 3 seconds passed
-... 10%, 13344 KB, 3421 KB/s, 3 seconds passed
-... 10%, 13376 KB, 3423 KB/s, 3 seconds passed
-... 10%, 13408 KB, 3419 KB/s, 3 seconds passed
-... 10%, 13440 KB, 3417 KB/s, 3 seconds passed
+    ... 10%, 12640 KB, 3616 KB/s, 3 seconds passed
+... 10%, 12672 KB, 3611 KB/s, 3 seconds passed
+... 10%, 12704 KB, 3619 KB/s, 3 seconds passed
+... 10%, 12736 KB, 3628 KB/s, 3 seconds passed
+... 10%, 12768 KB, 3619 KB/s, 3 seconds passed
 
 .. parsed-literal::
 
-    ... 10%, 13472 KB, 3418 KB/s, 3 seconds passed
-... 10%, 13504 KB, 3424 KB/s, 3 seconds passed
-... 10%, 13536 KB, 3420 KB/s, 3 seconds passed
-... 10%, 13568 KB, 3418 KB/s, 3 seconds passed
-... 10%, 13600 KB, 3419 KB/s, 3 seconds passed
-... 10%, 13632 KB, 3425 KB/s, 3 seconds passed
+    ... 10%, 12800 KB, 3613 KB/s, 3 seconds passed
+... 10%, 12832 KB, 3620 KB/s, 3 seconds passed
+... 10%, 12864 KB, 3629 KB/s, 3 seconds passed
+... 10%, 12896 KB, 3618 KB/s, 3 seconds passed
+... 10%, 12928 KB, 3614 KB/s, 3 seconds passed
+... 10%, 12960 KB, 3621 KB/s, 3 seconds passed
+... 10%, 12992 KB, 3629 KB/s, 3 seconds passed
 
 .. parsed-literal::
 
-    ... 10%, 13664 KB, 3421 KB/s, 3 seconds passed
-... 10%, 13696 KB, 3419 KB/s, 4 seconds passed
-... 10%, 13728 KB, 3421 KB/s, 4 seconds passed
-... 10%, 13760 KB, 3426 KB/s, 4 seconds passed
-... 10%, 13792 KB, 3422 KB/s, 4 seconds passed
+    ... 10%, 13024 KB, 3619 KB/s, 3 seconds passed
+... 10%, 13056 KB, 3615 KB/s, 3 seconds passed
+... 10%, 13088 KB, 3622 KB/s, 3 seconds passed
+... 10%, 13120 KB, 3630 KB/s, 3 seconds passed
 
 .. parsed-literal::
 
-    ... 10%, 13824 KB, 3420 KB/s, 4 seconds passed
-... 11%, 13856 KB, 3421 KB/s, 4 seconds passed
-... 11%, 13888 KB, 3426 KB/s, 4 seconds passed
-... 11%, 13920 KB, 3416 KB/s, 4 seconds passed
-... 11%, 13952 KB, 3420 KB/s, 4 seconds passed
+    ... 10%, 13152 KB, 3620 KB/s, 3 seconds passed
+... 10%, 13184 KB, 3616 KB/s, 3 seconds passed
+... 10%, 13216 KB, 3622 KB/s, 3 seconds passed
+... 10%, 13248 KB, 3630 KB/s, 3 seconds passed
+... 10%, 13280 KB, 3613 KB/s, 3 seconds passed
+... 10%, 13312 KB, 3615 KB/s, 3 seconds passed
+... 10%, 13344 KB, 3623 KB/s, 3 seconds passed
 
 .. parsed-literal::
 
-    ... 11%, 13984 KB, 3421 KB/s, 4 seconds passed
-... 11%, 14016 KB, 3427 KB/s, 4 seconds passed
-... 11%, 14048 KB, 3423 KB/s, 4 seconds passed
-... 11%, 14080 KB, 3421 KB/s, 4 seconds passed
-... 11%, 14112 KB, 3422 KB/s, 4 seconds passed
-... 11%, 14144 KB, 3428 KB/s, 4 seconds passed
+    ... 10%, 13376 KB, 3630 KB/s, 3 seconds passed
+... 10%, 13408 KB, 3614 KB/s, 3 seconds passed
+... 10%, 13440 KB, 3616 KB/s, 3 seconds passed
+... 10%, 13472 KB, 3624 KB/s, 3 seconds passed
+... 10%, 13504 KB, 3632 KB/s, 3 seconds passed
 
 .. parsed-literal::
 
-    ... 11%, 14176 KB, 3418 KB/s, 4 seconds passed
-... 11%, 14208 KB, 3422 KB/s, 4 seconds passed
-... 11%, 14240 KB, 3423 KB/s, 4 seconds passed
-... 11%, 14272 KB, 3429 KB/s, 4 seconds passed
-... 11%, 14304 KB, 3424 KB/s, 4 seconds passed
-... 11%, 14336 KB, 3422 KB/s, 4 seconds passed
+    ... 10%, 13536 KB, 3615 KB/s, 3 seconds passed
+... 10%, 13568 KB, 3617 KB/s, 3 seconds passed
+... 10%, 13600 KB, 3625 KB/s, 3 seconds passed
+... 10%, 13632 KB, 3632 KB/s, 3 seconds passed
+... 10%, 13664 KB, 3616 KB/s, 3 seconds passed
+... 10%, 13696 KB, 3618 KB/s, 3 seconds passed
+... 10%, 13728 KB, 3625 KB/s, 3 seconds passed
 
 .. parsed-literal::
 
-    ... 11%, 14368 KB, 3424 KB/s, 4 seconds passed
-... 11%, 14400 KB, 3430 KB/s, 4 seconds passed
-... 11%, 14432 KB, 3425 KB/s, 4 seconds passed
-... 11%, 14464 KB, 3423 KB/s, 4 seconds passed
-... 11%, 14496 KB, 3425 KB/s, 4 seconds passed
-... 11%, 14528 KB, 3430 KB/s, 4 seconds passed
+    ... 10%, 13760 KB, 3633 KB/s, 3 seconds passed
+... 10%, 13792 KB, 3617 KB/s, 3 seconds passed
+... 10%, 13824 KB, 3619 KB/s, 3 seconds passed
+... 11%, 13856 KB, 3626 KB/s, 3 seconds passed
+... 11%, 13888 KB, 3633 KB/s, 3 seconds passed
 
 .. parsed-literal::
 
-    ... 11%, 14560 KB, 3426 KB/s, 4 seconds passed
-... 11%, 14592 KB, 3423 KB/s, 4 seconds passed
-... 11%, 14624 KB, 3424 KB/s, 4 seconds passed
-... 11%, 14656 KB, 3430 KB/s, 4 seconds passed
+    ... 11%, 13920 KB, 3617 KB/s, 3 seconds passed
+... 11%, 13952 KB, 3620 KB/s, 3 seconds passed
+... 11%, 13984 KB, 3627 KB/s, 3 seconds passed
+... 11%, 14016 KB, 3635 KB/s, 3 seconds passed
+... 11%, 14048 KB, 3618 KB/s, 3 seconds passed
+... 11%, 14080 KB, 3621 KB/s, 3 seconds passed
 
 .. parsed-literal::
 
-    ... 11%, 14688 KB, 3420 KB/s, 4 seconds passed
-... 11%, 14720 KB, 3424 KB/s, 4 seconds passed
-... 11%, 14752 KB, 3425 KB/s, 4 seconds passed
-... 11%, 14784 KB, 3431 KB/s, 4 seconds passed
-... 11%, 14816 KB, 3421 KB/s, 4 seconds passed
-... 11%, 14848 KB, 3425 KB/s, 4 seconds passed
-... 11%, 14880 KB, 3426 KB/s, 4 seconds passed
+    ... 11%, 14112 KB, 3628 KB/s, 3 seconds passed
+... 11%, 14144 KB, 3635 KB/s, 3 seconds passed
+... 11%, 14176 KB, 3619 KB/s, 3 seconds passed
+... 11%, 14208 KB, 3621 KB/s, 3 seconds passed
+... 11%, 14240 KB, 3628 KB/s, 3 seconds passed
+... 11%, 14272 KB, 3636 KB/s, 3 seconds passed
 
 .. parsed-literal::
 
-    ... 11%, 14912 KB, 3432 KB/s, 4 seconds passed
-... 11%, 14944 KB, 3422 KB/s, 4 seconds passed
-... 11%, 14976 KB, 3426 KB/s, 4 seconds passed
-... 11%, 15008 KB, 3427 KB/s, 4 seconds passed
-... 11%, 15040 KB, 3433 KB/s, 4 seconds passed
+    ... 11%, 14304 KB, 3619 KB/s, 3 seconds passed
+... 11%, 14336 KB, 3622 KB/s, 3 seconds passed
+... 11%, 14368 KB, 3629 KB/s, 3 seconds passed
+... 11%, 14400 KB, 3636 KB/s, 3 seconds passed
+... 11%, 14432 KB, 3620 KB/s, 3 seconds passed
+... 11%, 14464 KB, 3623 KB/s, 3 seconds passed
 
 .. parsed-literal::
 
-    ... 11%, 15072 KB, 3428 KB/s, 4 seconds passed
-... 11%, 15104 KB, 3427 KB/s, 4 seconds passed
-... 12%, 15136 KB, 3428 KB/s, 4 seconds passed
-... 12%, 15168 KB, 3433 KB/s, 4 seconds passed
-... 12%, 15200 KB, 3429 KB/s, 4 seconds passed
-... 12%, 15232 KB, 3426 KB/s, 4 seconds passed
+    ... 11%, 14496 KB, 3630 KB/s, 3 seconds passed
+... 11%, 14528 KB, 3637 KB/s, 3 seconds passed
+... 11%, 14560 KB, 3629 KB/s, 4 seconds passed
+... 11%, 14592 KB, 3624 KB/s, 4 seconds passed
+... 11%, 14624 KB, 3630 KB/s, 4 seconds passed
+... 11%, 14656 KB, 3637 KB/s, 4 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 15264 KB, 3428 KB/s, 4 seconds passed
-... 12%, 15296 KB, 3426 KB/s, 4 seconds passed
-... 12%, 15328 KB, 3423 KB/s, 4 seconds passed
-... 12%, 15360 KB, 3427 KB/s, 4 seconds passed
-... 12%, 15392 KB, 3429 KB/s, 4 seconds passed
+    ... 11%, 14688 KB, 3621 KB/s, 4 seconds passed
+... 11%, 14720 KB, 3624 KB/s, 4 seconds passed
+... 11%, 14752 KB, 3630 KB/s, 4 seconds passed
+... 11%, 14784 KB, 3638 KB/s, 4 seconds passed
+... 11%, 14816 KB, 3622 KB/s, 4 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 15424 KB, 3427 KB/s, 4 seconds passed
-... 12%, 15456 KB, 3424 KB/s, 4 seconds passed
-... 12%, 15488 KB, 3428 KB/s, 4 seconds passed
-... 12%, 15520 KB, 3429 KB/s, 4 seconds passed
-... 12%, 15552 KB, 3427 KB/s, 4 seconds passed
+    ... 11%, 14848 KB, 3624 KB/s, 4 seconds passed
+... 11%, 14880 KB, 3631 KB/s, 4 seconds passed
+... 11%, 14912 KB, 3638 KB/s, 4 seconds passed
+... 11%, 14944 KB, 3623 KB/s, 4 seconds passed
+... 11%, 14976 KB, 3625 KB/s, 4 seconds passed
+... 11%, 15008 KB, 3632 KB/s, 4 seconds passed
+... 11%, 15040 KB, 3639 KB/s, 4 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 15584 KB, 3425 KB/s, 4 seconds passed
-... 12%, 15616 KB, 3429 KB/s, 4 seconds passed
-... 12%, 15648 KB, 3429 KB/s, 4 seconds passed
-... 12%, 15680 KB, 3428 KB/s, 4 seconds passed
-... 12%, 15712 KB, 3426 KB/s, 4 seconds passed
-... 12%, 15744 KB, 3429 KB/s, 4 seconds passed
-... 12%, 15776 KB, 3429 KB/s, 4 seconds passed
+    ... 11%, 15072 KB, 3623 KB/s, 4 seconds passed
+... 11%, 15104 KB, 3625 KB/s, 4 seconds passed
+... 12%, 15136 KB, 3633 KB/s, 4 seconds passed
+... 12%, 15168 KB, 3639 KB/s, 4 seconds passed
+... 12%, 15200 KB, 3624 KB/s, 4 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 15808 KB, 3429 KB/s, 4 seconds passed
-... 12%, 15840 KB, 3425 KB/s, 4 seconds passed
-... 12%, 15872 KB, 3429 KB/s, 4 seconds passed
-... 12%, 15904 KB, 3430 KB/s, 4 seconds passed
-... 12%, 15936 KB, 3429 KB/s, 4 seconds passed
+    ... 12%, 15232 KB, 3626 KB/s, 4 seconds passed
+... 12%, 15264 KB, 3633 KB/s, 4 seconds passed
+... 12%, 15296 KB, 3639 KB/s, 4 seconds passed
+... 12%, 15328 KB, 3624 KB/s, 4 seconds passed
+... 12%, 15360 KB, 3627 KB/s, 4 seconds passed
+... 12%, 15392 KB, 3634 KB/s, 4 seconds passed
+... 12%, 15424 KB, 3641 KB/s, 4 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 15968 KB, 3426 KB/s, 4 seconds passed
-... 12%, 16000 KB, 3430 KB/s, 4 seconds passed
-... 12%, 16032 KB, 3431 KB/s, 4 seconds passed
-... 12%, 16064 KB, 3430 KB/s, 4 seconds passed
-... 12%, 16096 KB, 3426 KB/s, 4 seconds passed
-... 12%, 16128 KB, 3430 KB/s, 4 seconds passed
+    ... 12%, 15456 KB, 3626 KB/s, 4 seconds passed
+... 12%, 15488 KB, 3629 KB/s, 4 seconds passed
+... 12%, 15520 KB, 3634 KB/s, 4 seconds passed
+... 12%, 15552 KB, 3641 KB/s, 4 seconds passed
+... 12%, 15584 KB, 3625 KB/s, 4 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 16160 KB, 3431 KB/s, 4 seconds passed
-... 12%, 16192 KB, 3430 KB/s, 4 seconds passed
-... 12%, 16224 KB, 3427 KB/s, 4 seconds passed
-... 12%, 16256 KB, 3431 KB/s, 4 seconds passed
-... 12%, 16288 KB, 3432 KB/s, 4 seconds passed
+    ... 12%, 15616 KB, 3628 KB/s, 4 seconds passed
+... 12%, 15648 KB, 3634 KB/s, 4 seconds passed
+... 12%, 15680 KB, 3630 KB/s, 4 seconds passed
+... 12%, 15712 KB, 3626 KB/s, 4 seconds passed
+... 12%, 15744 KB, 3628 KB/s, 4 seconds passed
+... 12%, 15776 KB, 3635 KB/s, 4 seconds passed
 
 .. parsed-literal::
 
-    ... 12%, 16320 KB, 3431 KB/s, 4 seconds passed
-... 12%, 16352 KB, 3427 KB/s, 4 seconds passed
-... 13%, 16384 KB, 3431 KB/s, 4 seconds passed
-... 13%, 16416 KB, 3432 KB/s, 4 seconds passed
-... 13%, 16448 KB, 3431 KB/s, 4 seconds passed
+    ... 12%, 15808 KB, 3631 KB/s, 4 seconds passed
+... 12%, 15840 KB, 3627 KB/s, 4 seconds passed
+... 12%, 15872 KB, 3629 KB/s, 4 seconds passed
+... 12%, 15904 KB, 3636 KB/s, 4 seconds passed
+... 12%, 15936 KB, 3634 KB/s, 4 seconds passed
+... 12%, 15968 KB, 3628 KB/s, 4 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 16480 KB, 3428 KB/s, 4 seconds passed
-... 13%, 16512 KB, 3432 KB/s, 4 seconds passed
-... 13%, 16544 KB, 3432 KB/s, 4 seconds passed
-... 13%, 16576 KB, 3432 KB/s, 4 seconds passed
-... 13%, 16608 KB, 3428 KB/s, 4 seconds passed
-... 13%, 16640 KB, 3433 KB/s, 4 seconds passed
-... 13%, 16672 KB, 3434 KB/s, 4 seconds passed
+    ... 12%, 16000 KB, 3630 KB/s, 4 seconds passed
+... 12%, 16032 KB, 3636 KB/s, 4 seconds passed
+... 12%, 16064 KB, 3632 KB/s, 4 seconds passed
+... 12%, 16096 KB, 3628 KB/s, 4 seconds passed
+... 12%, 16128 KB, 3630 KB/s, 4 seconds passed
+... 12%, 16160 KB, 3637 KB/s, 4 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 16704 KB, 3432 KB/s, 4 seconds passed
-... 13%, 16736 KB, 3429 KB/s, 4 seconds passed
-... 13%, 16768 KB, 3433 KB/s, 4 seconds passed
-... 13%, 16800 KB, 3434 KB/s, 4 seconds passed
-... 13%, 16832 KB, 3433 KB/s, 4 seconds passed
+    ... 12%, 16192 KB, 3632 KB/s, 4 seconds passed
+... 12%, 16224 KB, 3629 KB/s, 4 seconds passed
+... 12%, 16256 KB, 3631 KB/s, 4 seconds passed
+... 12%, 16288 KB, 3637 KB/s, 4 seconds passed
+... 12%, 16320 KB, 3633 KB/s, 4 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 16864 KB, 3430 KB/s, 4 seconds passed
-... 13%, 16896 KB, 3434 KB/s, 4 seconds passed
-... 13%, 16928 KB, 3434 KB/s, 4 seconds passed
-... 13%, 16960 KB, 3432 KB/s, 4 seconds passed
-... 13%, 16992 KB, 3430 KB/s, 4 seconds passed
-... 13%, 17024 KB, 3433 KB/s, 4 seconds passed
+    ... 12%, 16352 KB, 3629 KB/s, 4 seconds passed
+... 13%, 16384 KB, 3631 KB/s, 4 seconds passed
+... 13%, 16416 KB, 3637 KB/s, 4 seconds passed
+... 13%, 16448 KB, 3633 KB/s, 4 seconds passed
+... 13%, 16480 KB, 3630 KB/s, 4 seconds passed
+... 13%, 16512 KB, 3632 KB/s, 4 seconds passed
+... 13%, 16544 KB, 3638 KB/s, 4 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 17056 KB, 3434 KB/s, 4 seconds passed
-... 13%, 17088 KB, 3433 KB/s, 4 seconds passed
-... 13%, 17120 KB, 3430 KB/s, 4 seconds passed
-... 13%, 17152 KB, 3435 KB/s, 4 seconds passed
-... 13%, 17184 KB, 3435 KB/s, 5 seconds passed
+    ... 13%, 16576 KB, 3633 KB/s, 4 seconds passed
+... 13%, 16608 KB, 3630 KB/s, 4 seconds passed
+... 13%, 16640 KB, 3632 KB/s, 4 seconds passed
+... 13%, 16672 KB, 3638 KB/s, 4 seconds passed
+... 13%, 16704 KB, 3635 KB/s, 4 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 17216 KB, 3435 KB/s, 5 seconds passed
-... 13%, 17248 KB, 3431 KB/s, 5 seconds passed
-... 13%, 17280 KB, 3435 KB/s, 5 seconds passed
-... 13%, 17312 KB, 3435 KB/s, 5 seconds passed
-... 13%, 17344 KB, 3435 KB/s, 5 seconds passed
+    ... 13%, 16736 KB, 3631 KB/s, 4 seconds passed
+... 13%, 16768 KB, 3633 KB/s, 4 seconds passed
+... 13%, 16800 KB, 3639 KB/s, 4 seconds passed
+... 13%, 16832 KB, 3635 KB/s, 4 seconds passed
+... 13%, 16864 KB, 3631 KB/s, 4 seconds passed
+... 13%, 16896 KB, 3633 KB/s, 4 seconds passed
+... 13%, 16928 KB, 3639 KB/s, 4 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 17376 KB, 3431 KB/s, 5 seconds passed
-... 13%, 17408 KB, 3436 KB/s, 5 seconds passed
-... 13%, 17440 KB, 3436 KB/s, 5 seconds passed
-... 13%, 17472 KB, 3436 KB/s, 5 seconds passed
-... 13%, 17504 KB, 3432 KB/s, 5 seconds passed
-... 13%, 17536 KB, 3436 KB/s, 5 seconds passed
-... 13%, 17568 KB, 3437 KB/s, 5 seconds passed
+    ... 13%, 16960 KB, 3636 KB/s, 4 seconds passed
+... 13%, 16992 KB, 3632 KB/s, 4 seconds passed
+... 13%, 17024 KB, 3635 KB/s, 4 seconds passed
+... 13%, 17056 KB, 3640 KB/s, 4 seconds passed
+... 13%, 17088 KB, 3637 KB/s, 4 seconds passed
 
 .. parsed-literal::
 
-    ... 13%, 17600 KB, 3429 KB/s, 5 seconds passed
-... 13%, 17632 KB, 3432 KB/s, 5 seconds passed
-... 14%, 17664 KB, 3434 KB/s, 5 seconds passed
-... 14%, 17696 KB, 3436 KB/s, 5 seconds passed
+    ... 13%, 17120 KB, 3633 KB/s, 4 seconds passed
+... 13%, 17152 KB, 3634 KB/s, 4 seconds passed
+... 13%, 17184 KB, 3640 KB/s, 4 seconds passed
+... 13%, 17216 KB, 3636 KB/s, 4 seconds passed
+... 13%, 17248 KB, 3632 KB/s, 4 seconds passed
+... 13%, 17280 KB, 3635 KB/s, 4 seconds passed
+... 13%, 17312 KB, 3641 KB/s, 4 seconds passed
 
 .. parsed-literal::
 
-    ... 14%, 17728 KB, 3430 KB/s, 5 seconds passed
-... 14%, 17760 KB, 3433 KB/s, 5 seconds passed
-... 14%, 17792 KB, 3434 KB/s, 5 seconds passed
-... 14%, 17824 KB, 3437 KB/s, 5 seconds passed
-... 14%, 17856 KB, 3435 KB/s, 5 seconds passed
-... 14%, 17888 KB, 3433 KB/s, 5 seconds passed
-... 14%, 17920 KB, 3435 KB/s, 5 seconds passed
+    ... 13%, 17344 KB, 3629 KB/s, 4 seconds passed
+... 13%, 17376 KB, 3633 KB/s, 4 seconds passed
+... 13%, 17408 KB, 3635 KB/s, 4 seconds passed
+... 13%, 17440 KB, 3641 KB/s, 4 seconds passed
+... 13%, 17472 KB, 3637 KB/s, 4 seconds passed
 
 .. parsed-literal::
 
-    ... 14%, 17952 KB, 3437 KB/s, 5 seconds passed
-... 14%, 17984 KB, 3435 KB/s, 5 seconds passed
-... 14%, 18016 KB, 3434 KB/s, 5 seconds passed
-... 14%, 18048 KB, 3438 KB/s, 5 seconds passed
-... 14%, 18080 KB, 3438 KB/s, 5 seconds passed
+    ... 13%, 17504 KB, 3634 KB/s, 4 seconds passed
+... 13%, 17536 KB, 3635 KB/s, 4 seconds passed
+... 13%, 17568 KB, 3642 KB/s, 4 seconds passed
+... 13%, 17600 KB, 3637 KB/s, 4 seconds passed
+... 13%, 17632 KB, 3634 KB/s, 4 seconds passed
+... 14%, 17664 KB, 3637 KB/s, 4 seconds passed
+... 14%, 17696 KB, 3642 KB/s, 4 seconds passed
 
 .. parsed-literal::
 
-    ... 14%, 18112 KB, 3436 KB/s, 5 seconds passed
-... 14%, 18144 KB, 3434 KB/s, 5 seconds passed
-... 14%, 18176 KB, 3438 KB/s, 5 seconds passed
-... 14%, 18208 KB, 3438 KB/s, 5 seconds passed
-... 14%, 18240 KB, 3436 KB/s, 5 seconds passed
+    ... 14%, 17728 KB, 3638 KB/s, 4 seconds passed
+... 14%, 17760 KB, 3635 KB/s, 4 seconds passed
+... 14%, 17792 KB, 3636 KB/s, 4 seconds passed
+... 14%, 17824 KB, 3642 KB/s, 4 seconds passed
 
 .. parsed-literal::
 
-    ... 14%, 18272 KB, 3435 KB/s, 5 seconds passed
-... 14%, 18304 KB, 3436 KB/s, 5 seconds passed
-... 14%, 18336 KB, 3438 KB/s, 5 seconds passed
-... 14%, 18368 KB, 3432 KB/s, 5 seconds passed
-... 14%, 18400 KB, 3435 KB/s, 5 seconds passed
-... 14%, 18432 KB, 3437 KB/s, 5 seconds passed
-... 14%, 18464 KB, 3439 KB/s, 5 seconds passed
+    ... 14%, 17856 KB, 3631 KB/s, 4 seconds passed
+... 14%, 17888 KB, 3635 KB/s, 4 seconds passed
+... 14%, 17920 KB, 3637 KB/s, 4 seconds passed
+... 14%, 17952 KB, 3643 KB/s, 4 seconds passed
+... 14%, 17984 KB, 3632 KB/s, 4 seconds passed
+... 14%, 18016 KB, 3635 KB/s, 4 seconds passed
+... 14%, 18048 KB, 3637 KB/s, 4 seconds passed
+... 14%, 18080 KB, 3643 KB/s, 4 seconds passed
 
 .. parsed-literal::
 
-    ... 14%, 18496 KB, 3433 KB/s, 5 seconds passed
-... 14%, 18528 KB, 3435 KB/s, 5 seconds passed
-... 14%, 18560 KB, 3437 KB/s, 5 seconds passed
-... 14%, 18592 KB, 3439 KB/s, 5 seconds passed
+    ... 14%, 18112 KB, 3632 KB/s, 4 seconds passed
+... 14%, 18144 KB, 3636 KB/s, 4 seconds passed
+... 14%, 18176 KB, 3637 KB/s, 4 seconds passed
+... 14%, 18208 KB, 3643 KB/s, 4 seconds passed
 
 .. parsed-literal::
 
-    ... 14%, 18624 KB, 3433 KB/s, 5 seconds passed
-... 14%, 18656 KB, 3436 KB/s, 5 seconds passed
-... 14%, 18688 KB, 3438 KB/s, 5 seconds passed
-... 14%, 18720 KB, 3440 KB/s, 5 seconds passed
-... 14%, 18752 KB, 3433 KB/s, 5 seconds passed
-... 14%, 18784 KB, 3436 KB/s, 5 seconds passed
-... 14%, 18816 KB, 3438 KB/s, 5 seconds passed
+    ... 14%, 18240 KB, 3633 KB/s, 5 seconds passed
+... 14%, 18272 KB, 3636 KB/s, 5 seconds passed
+... 14%, 18304 KB, 3638 KB/s, 5 seconds passed
+... 14%, 18336 KB, 3644 KB/s, 5 seconds passed
+... 14%, 18368 KB, 3633 KB/s, 5 seconds passed
+... 14%, 18400 KB, 3637 KB/s, 5 seconds passed
+... 14%, 18432 KB, 3638 KB/s, 5 seconds passed
+... 14%, 18464 KB, 3644 KB/s, 5 seconds passed
 
 .. parsed-literal::
 
-    ... 14%, 18848 KB, 3441 KB/s, 5 seconds passed
-... 14%, 18880 KB, 3439 KB/s, 5 seconds passed
-... 15%, 18912 KB, 3437 KB/s, 5 seconds passed
-... 15%, 18944 KB, 3441 KB/s, 5 seconds passed
-... 15%, 18976 KB, 3441 KB/s, 5 seconds passed
+    ... 14%, 18496 KB, 3633 KB/s, 5 seconds passed
+... 14%, 18528 KB, 3637 KB/s, 5 seconds passed
+... 14%, 18560 KB, 3638 KB/s, 5 seconds passed
+... 14%, 18592 KB, 3644 KB/s, 5 seconds passed
+... 14%, 18624 KB, 3642 KB/s, 5 seconds passed
 
 .. parsed-literal::
 
-    ... 15%, 19008 KB, 3434 KB/s, 5 seconds passed
-... 15%, 19040 KB, 3437 KB/s, 5 seconds passed
-... 15%, 19072 KB, 3439 KB/s, 5 seconds passed
-... 15%, 19104 KB, 3441 KB/s, 5 seconds passed
-... 15%, 19136 KB, 3435 KB/s, 5 seconds passed
-... 15%, 19168 KB, 3438 KB/s, 5 seconds passed
+    ... 14%, 18656 KB, 3639 KB/s, 5 seconds passed
+... 14%, 18688 KB, 3641 KB/s, 5 seconds passed
+... 14%, 18720 KB, 3645 KB/s, 5 seconds passed
+... 14%, 18752 KB, 3642 KB/s, 5 seconds passed
+... 14%, 18784 KB, 3639 KB/s, 5 seconds passed
+... 14%, 18816 KB, 3640 KB/s, 5 seconds passed
+... 14%, 18848 KB, 3645 KB/s, 5 seconds passed
 
 .. parsed-literal::
 
-    ... 15%, 19200 KB, 3439 KB/s, 5 seconds passed
-... 15%, 19232 KB, 3441 KB/s, 5 seconds passed
-... 15%, 19264 KB, 3435 KB/s, 5 seconds passed
-... 15%, 19296 KB, 3438 KB/s, 5 seconds passed
-... 15%, 19328 KB, 3440 KB/s, 5 seconds passed
-... 15%, 19360 KB, 3442 KB/s, 5 seconds passed
+    ... 14%, 18880 KB, 3635 KB/s, 5 seconds passed
+... 15%, 18912 KB, 3639 KB/s, 5 seconds passed
+... 15%, 18944 KB, 3640 KB/s, 5 seconds passed
+... 15%, 18976 KB, 3645 KB/s, 5 seconds passed
 
 .. parsed-literal::
 
-    ... 15%, 19392 KB, 3435 KB/s, 5 seconds passed
-... 15%, 19424 KB, 3438 KB/s, 5 seconds passed
-... 15%, 19456 KB, 3440 KB/s, 5 seconds passed
-... 15%, 19488 KB, 3442 KB/s, 5 seconds passed
+    ... 15%, 19008 KB, 3635 KB/s, 5 seconds passed
+... 15%, 19040 KB, 3640 KB/s, 5 seconds passed
+... 15%, 19072 KB, 3641 KB/s, 5 seconds passed
+... 15%, 19104 KB, 3646 KB/s, 5 seconds passed
+... 15%, 19136 KB, 3637 KB/s, 5 seconds passed
+... 15%, 19168 KB, 3640 KB/s, 5 seconds passed
+... 15%, 19200 KB, 3640 KB/s, 5 seconds passed
+... 15%, 19232 KB, 3646 KB/s, 5 seconds passed
 
 .. parsed-literal::
 
-    ... 15%, 19520 KB, 3436 KB/s, 5 seconds passed
-... 15%, 19552 KB, 3439 KB/s, 5 seconds passed
-... 15%, 19584 KB, 3440 KB/s, 5 seconds passed
-... 15%, 19616 KB, 3442 KB/s, 5 seconds passed
-... 15%, 19648 KB, 3436 KB/s, 5 seconds passed
-... 15%, 19680 KB, 3439 KB/s, 5 seconds passed
-... 15%, 19712 KB, 3441 KB/s, 5 seconds passed
+    ... 15%, 19264 KB, 3636 KB/s, 5 seconds passed
+... 15%, 19296 KB, 3640 KB/s, 5 seconds passed
+... 15%, 19328 KB, 3641 KB/s, 5 seconds passed
+... 15%, 19360 KB, 3646 KB/s, 5 seconds passed
 
 .. parsed-literal::
 
-    ... 15%, 19744 KB, 3442 KB/s, 5 seconds passed
-... 15%, 19776 KB, 3436 KB/s, 5 seconds passed
-... 15%, 19808 KB, 3439 KB/s, 5 seconds passed
-... 15%, 19840 KB, 3441 KB/s, 5 seconds passed
-... 15%, 19872 KB, 3443 KB/s, 5 seconds passed
+    ... 15%, 19392 KB, 3637 KB/s, 5 seconds passed
+... 15%, 19424 KB, 3641 KB/s, 5 seconds passed
+... 15%, 19456 KB, 3641 KB/s, 5 seconds passed
+... 15%, 19488 KB, 3646 KB/s, 5 seconds passed
+... 15%, 19520 KB, 3637 KB/s, 5 seconds passed
+... 15%, 19552 KB, 3640 KB/s, 5 seconds passed
 
 .. parsed-literal::
 
-    ... 15%, 19904 KB, 3437 KB/s, 5 seconds passed
-... 15%, 19936 KB, 3440 KB/s, 5 seconds passed
-... 15%, 19968 KB, 3441 KB/s, 5 seconds passed
-... 15%, 20000 KB, 3443 KB/s, 5 seconds passed
-... 15%, 20032 KB, 3437 KB/s, 5 seconds passed
-... 15%, 20064 KB, 3440 KB/s, 5 seconds passed
+    ... 15%, 19584 KB, 3641 KB/s, 5 seconds passed
+... 15%, 19616 KB, 3641 KB/s, 5 seconds passed
+... 15%, 19648 KB, 3637 KB/s, 5 seconds passed
+... 15%, 19680 KB, 3640 KB/s, 5 seconds passed
+... 15%, 19712 KB, 3641 KB/s, 5 seconds passed
+... 15%, 19744 KB, 3647 KB/s, 5 seconds passed
 
 .. parsed-literal::
 
-    ... 15%, 20096 KB, 3441 KB/s, 5 seconds passed
-... 15%, 20128 KB, 3444 KB/s, 5 seconds passed
-... 16%, 20160 KB, 3438 KB/s, 5 seconds passed
-... 16%, 20192 KB, 3441 KB/s, 5 seconds passed
-... 16%, 20224 KB, 3442 KB/s, 5 seconds passed
-... 16%, 20256 KB, 3445 KB/s, 5 seconds passed
+    ... 15%, 19776 KB, 3638 KB/s, 5 seconds passed
+... 15%, 19808 KB, 3641 KB/s, 5 seconds passed
+... 15%, 19840 KB, 3642 KB/s, 5 seconds passed
+... 15%, 19872 KB, 3647 KB/s, 5 seconds passed
+... 15%, 19904 KB, 3639 KB/s, 5 seconds passed
+... 15%, 19936 KB, 3641 KB/s, 5 seconds passed
 
 .. parsed-literal::
 
-    ... 16%, 20288 KB, 3438 KB/s, 5 seconds passed
-... 16%, 20320 KB, 3441 KB/s, 5 seconds passed
-... 16%, 20352 KB, 3442 KB/s, 5 seconds passed
-... 16%, 20384 KB, 3444 KB/s, 5 seconds passed
+    ... 15%, 19968 KB, 3642 KB/s, 5 seconds passed
+... 15%, 20000 KB, 3648 KB/s, 5 seconds passed
+... 15%, 20032 KB, 3639 KB/s, 5 seconds passed
+... 15%, 20064 KB, 3642 KB/s, 5 seconds passed
+... 15%, 20096 KB, 3643 KB/s, 5 seconds passed
+... 15%, 20128 KB, 3648 KB/s, 5 seconds passed
 
 .. parsed-literal::
 
-    ... 16%, 20416 KB, 3438 KB/s, 5 seconds passed
-... 16%, 20448 KB, 3441 KB/s, 5 seconds passed
-... 16%, 20480 KB, 3442 KB/s, 5 seconds passed
-... 16%, 20512 KB, 3444 KB/s, 5 seconds passed
-... 16%, 20544 KB, 3438 KB/s, 5 seconds passed
-... 16%, 20576 KB, 3442 KB/s, 5 seconds passed
-... 16%, 20608 KB, 3443 KB/s, 5 seconds passed
+    ... 16%, 20160 KB, 3640 KB/s, 5 seconds passed
+... 16%, 20192 KB, 3642 KB/s, 5 seconds passed
+... 16%, 20224 KB, 3643 KB/s, 5 seconds passed
+... 16%, 20256 KB, 3649 KB/s, 5 seconds passed
+... 16%, 20288 KB, 3640 KB/s, 5 seconds passed
+... 16%, 20320 KB, 3643 KB/s, 5 seconds passed
 
 .. parsed-literal::
 
-    ... 16%, 20640 KB, 3444 KB/s, 5 seconds passed
-... 16%, 20672 KB, 3439 KB/s, 6 seconds passed
-... 16%, 20704 KB, 3442 KB/s, 6 seconds passed
-... 16%, 20736 KB, 3443 KB/s, 6 seconds passed
-... 16%, 20768 KB, 3445 KB/s, 6 seconds passed
+    ... 16%, 20352 KB, 3644 KB/s, 5 seconds passed
+... 16%, 20384 KB, 3648 KB/s, 5 seconds passed
+... 16%, 20416 KB, 3640 KB/s, 5 seconds passed
+... 16%, 20448 KB, 3643 KB/s, 5 seconds passed
+... 16%, 20480 KB, 3643 KB/s, 5 seconds passed
+... 16%, 20512 KB, 3644 KB/s, 5 seconds passed
 
 .. parsed-literal::
 
-    ... 16%, 20800 KB, 3439 KB/s, 6 seconds passed
-... 16%, 20832 KB, 3443 KB/s, 6 seconds passed
-... 16%, 20864 KB, 3443 KB/s, 6 seconds passed
-... 16%, 20896 KB, 3446 KB/s, 6 seconds passed
-... 16%, 20928 KB, 3440 KB/s, 6 seconds passed
-... 16%, 20960 KB, 3443 KB/s, 6 seconds passed
+    ... 16%, 20544 KB, 3641 KB/s, 5 seconds passed
+... 16%, 20576 KB, 3643 KB/s, 5 seconds passed
+... 16%, 20608 KB, 3643 KB/s, 5 seconds passed
+... 16%, 20640 KB, 3645 KB/s, 5 seconds passed
+... 16%, 20672 KB, 3641 KB/s, 5 seconds passed
+... 16%, 20704 KB, 3643 KB/s, 5 seconds passed
 
 .. parsed-literal::
 
-    ... 16%, 20992 KB, 3443 KB/s, 6 seconds passed
-... 16%, 21024 KB, 3446 KB/s, 6 seconds passed
-... 16%, 21056 KB, 3440 KB/s, 6 seconds passed
-... 16%, 21088 KB, 3443 KB/s, 6 seconds passed
-... 16%, 21120 KB, 3444 KB/s, 6 seconds passed
-... 16%, 21152 KB, 3446 KB/s, 6 seconds passed
+    ... 16%, 20736 KB, 3644 KB/s, 5 seconds passed
+... 16%, 20768 KB, 3645 KB/s, 5 seconds passed
+... 16%, 20800 KB, 3641 KB/s, 5 seconds passed
+... 16%, 20832 KB, 3643 KB/s, 5 seconds passed
+... 16%, 20864 KB, 3644 KB/s, 5 seconds passed
+... 16%, 20896 KB, 3645 KB/s, 5 seconds passed
 
 .. parsed-literal::
 
-    ... 16%, 21184 KB, 3440 KB/s, 6 seconds passed
-... 16%, 21216 KB, 3443 KB/s, 6 seconds passed
-... 16%, 21248 KB, 3444 KB/s, 6 seconds passed
-... 16%, 21280 KB, 3447 KB/s, 6 seconds passed
+    ... 16%, 20928 KB, 3641 KB/s, 5 seconds passed
+... 16%, 20960 KB, 3644 KB/s, 5 seconds passed
+... 16%, 20992 KB, 3644 KB/s, 5 seconds passed
+... 16%, 21024 KB, 3645 KB/s, 5 seconds passed
+... 16%, 21056 KB, 3642 KB/s, 5 seconds passed
+... 16%, 21088 KB, 3644 KB/s, 5 seconds passed
 
 .. parsed-literal::
 
-    ... 16%, 21312 KB, 3441 KB/s, 6 seconds passed
-... 16%, 21344 KB, 3444 KB/s, 6 seconds passed
-... 16%, 21376 KB, 3445 KB/s, 6 seconds passed
-... 16%, 21408 KB, 3447 KB/s, 6 seconds passed
-... 17%, 21440 KB, 3441 KB/s, 6 seconds passed
-... 17%, 21472 KB, 3444 KB/s, 6 seconds passed
-... 17%, 21504 KB, 3445 KB/s, 6 seconds passed
+    ... 16%, 21120 KB, 3644 KB/s, 5 seconds passed
+... 16%, 21152 KB, 3645 KB/s, 5 seconds passed
+... 16%, 21184 KB, 3642 KB/s, 5 seconds passed
+... 16%, 21216 KB, 3645 KB/s, 5 seconds passed
+... 16%, 21248 KB, 3645 KB/s, 5 seconds passed
+... 16%, 21280 KB, 3646 KB/s, 5 seconds passed
 
 .. parsed-literal::
 
-    ... 17%, 21536 KB, 3444 KB/s, 6 seconds passed
-... 17%, 21568 KB, 3441 KB/s, 6 seconds passed
-... 17%, 21600 KB, 3444 KB/s, 6 seconds passed
-... 17%, 21632 KB, 3445 KB/s, 6 seconds passed
-... 17%, 21664 KB, 3444 KB/s, 6 seconds passed
+    ... 16%, 21312 KB, 3642 KB/s, 5 seconds passed
+... 16%, 21344 KB, 3645 KB/s, 5 seconds passed
+... 16%, 21376 KB, 3645 KB/s, 5 seconds passed
+... 16%, 21408 KB, 3646 KB/s, 5 seconds passed
+... 17%, 21440 KB, 3643 KB/s, 5 seconds passed
+... 17%, 21472 KB, 3646 KB/s, 5 seconds passed
 
 .. parsed-literal::
 
-    ... 17%, 21696 KB, 3442 KB/s, 6 seconds passed
-... 17%, 21728 KB, 3445 KB/s, 6 seconds passed
-... 17%, 21760 KB, 3445 KB/s, 6 seconds passed
-... 17%, 21792 KB, 3448 KB/s, 6 seconds passed
-... 17%, 21824 KB, 3442 KB/s, 6 seconds passed
-... 17%, 21856 KB, 3445 KB/s, 6 seconds passed
+    ... 17%, 21504 KB, 3645 KB/s, 5 seconds passed
+... 17%, 21536 KB, 3647 KB/s, 5 seconds passed
+... 17%, 21568 KB, 3643 KB/s, 5 seconds passed
+... 17%, 21600 KB, 3646 KB/s, 5 seconds passed
+... 17%, 21632 KB, 3647 KB/s, 5 seconds passed
+... 17%, 21664 KB, 3649 KB/s, 5 seconds passed
 
 .. parsed-literal::
 
-    ... 17%, 21888 KB, 3446 KB/s, 6 seconds passed
-... 17%, 21920 KB, 3448 KB/s, 6 seconds passed
-... 17%, 21952 KB, 3443 KB/s, 6 seconds passed
-... 17%, 21984 KB, 3445 KB/s, 6 seconds passed
-... 17%, 22016 KB, 3446 KB/s, 6 seconds passed
-... 17%, 22048 KB, 3449 KB/s, 6 seconds passed
+    ... 17%, 21696 KB, 3644 KB/s, 5 seconds passed
+... 17%, 21728 KB, 3647 KB/s, 5 seconds passed
+... 17%, 21760 KB, 3647 KB/s, 5 seconds passed
+... 17%, 21792 KB, 3649 KB/s, 5 seconds passed
+... 17%, 21824 KB, 3645 KB/s, 5 seconds passed
+... 17%, 21856 KB, 3648 KB/s, 5 seconds passed
 
 .. parsed-literal::
 
-    ... 17%, 22080 KB, 3443 KB/s, 6 seconds passed
-... 17%, 22112 KB, 3446 KB/s, 6 seconds passed
-... 17%, 22144 KB, 3447 KB/s, 6 seconds passed
-... 17%, 22176 KB, 3449 KB/s, 6 seconds passed
-... 17%, 22208 KB, 3443 KB/s, 6 seconds passed
+    ... 17%, 21888 KB, 3648 KB/s, 5 seconds passed
+... 17%, 21920 KB, 3641 KB/s, 6 seconds passed
+... 17%, 21952 KB, 3644 KB/s, 6 seconds passed
+... 17%, 21984 KB, 3647 KB/s, 6 seconds passed
+... 17%, 22016 KB, 3647 KB/s, 6 seconds passed
 
 .. parsed-literal::
 
-    ... 17%, 22240 KB, 3446 KB/s, 6 seconds passed
-... 17%, 22272 KB, 3447 KB/s, 6 seconds passed
-... 17%, 22304 KB, 3445 KB/s, 6 seconds passed
-... 17%, 22336 KB, 3443 KB/s, 6 seconds passed
-... 17%, 22368 KB, 3446 KB/s, 6 seconds passed
-... 17%, 22400 KB, 3447 KB/s, 6 seconds passed
+    ... 17%, 22048 KB, 3642 KB/s, 6 seconds passed
+... 17%, 22080 KB, 3644 KB/s, 6 seconds passed
+... 17%, 22112 KB, 3647 KB/s, 6 seconds passed
+... 17%, 22144 KB, 3647 KB/s, 6 seconds passed
+... 17%, 22176 KB, 3642 KB/s, 6 seconds passed
+... 17%, 22208 KB, 3645 KB/s, 6 seconds passed
 
 .. parsed-literal::
 
-    ... 17%, 22432 KB, 3446 KB/s, 6 seconds passed
-... 17%, 22464 KB, 3444 KB/s, 6 seconds passed
-... 17%, 22496 KB, 3446 KB/s, 6 seconds passed
-... 17%, 22528 KB, 3447 KB/s, 6 seconds passed
-... 17%, 22560 KB, 3446 KB/s, 6 seconds passed
+    ... 17%, 22240 KB, 3647 KB/s, 6 seconds passed
+... 17%, 22272 KB, 3647 KB/s, 6 seconds passed
+... 17%, 22304 KB, 3643 KB/s, 6 seconds passed
+... 17%, 22336 KB, 3645 KB/s, 6 seconds passed
+... 17%, 22368 KB, 3647 KB/s, 6 seconds passed
+... 17%, 22400 KB, 3648 KB/s, 6 seconds passed
 
 .. parsed-literal::
 
-    ... 17%, 22592 KB, 3444 KB/s, 6 seconds passed
-... 17%, 22624 KB, 3447 KB/s, 6 seconds passed
-... 17%, 22656 KB, 3448 KB/s, 6 seconds passed
-... 18%, 22688 KB, 3446 KB/s, 6 seconds passed
-... 18%, 22720 KB, 3444 KB/s, 6 seconds passed
-... 18%, 22752 KB, 3447 KB/s, 6 seconds passed
+    ... 17%, 22432 KB, 3649 KB/s, 6 seconds passed
+... 17%, 22464 KB, 3646 KB/s, 6 seconds passed
+... 17%, 22496 KB, 3648 KB/s, 6 seconds passed
+... 17%, 22528 KB, 3648 KB/s, 6 seconds passed
+... 17%, 22560 KB, 3643 KB/s, 6 seconds passed
+... 17%, 22592 KB, 3646 KB/s, 6 seconds passed
 
 .. parsed-literal::
 
-    ... 18%, 22784 KB, 3448 KB/s, 6 seconds passed
-... 18%, 22816 KB, 3447 KB/s, 6 seconds passed
-... 18%, 22848 KB, 3445 KB/s, 6 seconds passed
-... 18%, 22880 KB, 3447 KB/s, 6 seconds passed
-... 18%, 22912 KB, 3448 KB/s, 6 seconds passed
+    ... 17%, 22624 KB, 3649 KB/s, 6 seconds passed
+... 17%, 22656 KB, 3648 KB/s, 6 seconds passed
+... 18%, 22688 KB, 3650 KB/s, 6 seconds passed
+... 18%, 22720 KB, 3646 KB/s, 6 seconds passed
+... 18%, 22752 KB, 3649 KB/s, 6 seconds passed
+... 18%, 22784 KB, 3649 KB/s, 6 seconds passed
 
 .. parsed-literal::
 
-    ... 18%, 22944 KB, 3447 KB/s, 6 seconds passed
-... 18%, 22976 KB, 3445 KB/s, 6 seconds passed
-... 18%, 23008 KB, 3447 KB/s, 6 seconds passed
-... 18%, 23040 KB, 3448 KB/s, 6 seconds passed
-... 18%, 23072 KB, 3443 KB/s, 6 seconds passed
+    ... 18%, 22816 KB, 3650 KB/s, 6 seconds passed
+... 18%, 22848 KB, 3644 KB/s, 6 seconds passed
+... 18%, 22880 KB, 3648 KB/s, 6 seconds passed
+... 18%, 22912 KB, 3649 KB/s, 6 seconds passed
 
 .. parsed-literal::
 
-    ... 18%, 23104 KB, 3445 KB/s, 6 seconds passed
-... 18%, 23136 KB, 3447 KB/s, 6 seconds passed
-... 18%, 23168 KB, 3448 KB/s, 6 seconds passed
-... 18%, 23200 KB, 3443 KB/s, 6 seconds passed
-... 18%, 23232 KB, 3445 KB/s, 6 seconds passed
-... 18%, 23264 KB, 3448 KB/s, 6 seconds passed
-... 18%, 23296 KB, 3449 KB/s, 6 seconds passed
+    ... 18%, 22944 KB, 3636 KB/s, 6 seconds passed
+... 18%, 22976 KB, 3641 KB/s, 6 seconds passed
+... 18%, 23008 KB, 3645 KB/s, 6 seconds passed
+... 18%, 23040 KB, 3649 KB/s, 6 seconds passed
+... 18%, 23072 KB, 3636 KB/s, 6 seconds passed
+... 18%, 23104 KB, 3641 KB/s, 6 seconds passed
+... 18%, 23136 KB, 3646 KB/s, 6 seconds passed
+... 18%, 23168 KB, 3650 KB/s, 6 seconds passed
 
 .. parsed-literal::
 
-    ... 18%, 23328 KB, 3443 KB/s, 6 seconds passed
-... 18%, 23360 KB, 3447 KB/s, 6 seconds passed
-... 18%, 23392 KB, 3449 KB/s, 6 seconds passed
-... 18%, 23424 KB, 3450 KB/s, 6 seconds passed
-... 18%, 23456 KB, 3449 KB/s, 6 seconds passed
+    ... 18%, 23200 KB, 3637 KB/s, 6 seconds passed
+... 18%, 23232 KB, 3641 KB/s, 6 seconds passed
+... 18%, 23264 KB, 3646 KB/s, 6 seconds passed
+... 18%, 23296 KB, 3650 KB/s, 6 seconds passed
+... 18%, 23328 KB, 3652 KB/s, 6 seconds passed
 
 .. parsed-literal::
 
-    ... 18%, 23488 KB, 3447 KB/s, 6 seconds passed
-... 18%, 23520 KB, 3449 KB/s, 6 seconds passed
-... 18%, 23552 KB, 3449 KB/s, 6 seconds passed
-... 18%, 23584 KB, 3443 KB/s, 6 seconds passed
-... 18%, 23616 KB, 3446 KB/s, 6 seconds passed
-... 18%, 23648 KB, 3447 KB/s, 6 seconds passed
+    ... 18%, 23360 KB, 3642 KB/s, 6 seconds passed
+... 18%, 23392 KB, 3646 KB/s, 6 seconds passed
+... 18%, 23424 KB, 3651 KB/s, 6 seconds passed
+... 18%, 23456 KB, 3652 KB/s, 6 seconds passed
+... 18%, 23488 KB, 3642 KB/s, 6 seconds passed
+... 18%, 23520 KB, 3647 KB/s, 6 seconds passed
+... 18%, 23552 KB, 3651 KB/s, 6 seconds passed
 
 .. parsed-literal::
 
-    ... 18%, 23680 KB, 3449 KB/s, 6 seconds passed
-... 18%, 23712 KB, 3444 KB/s, 6 seconds passed
-... 18%, 23744 KB, 3446 KB/s, 6 seconds passed
-... 18%, 23776 KB, 3449 KB/s, 6 seconds passed
-... 18%, 23808 KB, 3450 KB/s, 6 seconds passed
+    ... 18%, 23584 KB, 3653 KB/s, 6 seconds passed
+... 18%, 23616 KB, 3642 KB/s, 6 seconds passed
+... 18%, 23648 KB, 3647 KB/s, 6 seconds passed
+... 18%, 23680 KB, 3651 KB/s, 6 seconds passed
 
 .. parsed-literal::
 
-    ... 18%, 23840 KB, 3444 KB/s, 6 seconds passed
-... 18%, 23872 KB, 3446 KB/s, 6 seconds passed
-... 18%, 23904 KB, 3450 KB/s, 6 seconds passed
-... 19%, 23936 KB, 3451 KB/s, 6 seconds passed
-... 19%, 23968 KB, 3450 KB/s, 6 seconds passed
-... 19%, 24000 KB, 3447 KB/s, 6 seconds passed
+    ... 18%, 23712 KB, 3638 KB/s, 6 seconds passed
+... 18%, 23744 KB, 3643 KB/s, 6 seconds passed
+... 18%, 23776 KB, 3647 KB/s, 6 seconds passed
+... 18%, 23808 KB, 3651 KB/s, 6 seconds passed
+... 18%, 23840 KB, 3638 KB/s, 6 seconds passed
+... 18%, 23872 KB, 3643 KB/s, 6 seconds passed
+... 18%, 23904 KB, 3647 KB/s, 6 seconds passed
+... 19%, 23936 KB, 3651 KB/s, 6 seconds passed
 
 .. parsed-literal::
 
-    ... 19%, 24032 KB, 3450 KB/s, 6 seconds passed
-... 19%, 24064 KB, 3451 KB/s, 6 seconds passed
-... 19%, 24096 KB, 3444 KB/s, 6 seconds passed
-... 19%, 24128 KB, 3447 KB/s, 6 seconds passed
-... 19%, 24160 KB, 3448 KB/s, 7 seconds passed
-... 19%, 24192 KB, 3450 KB/s, 7 seconds passed
+    ... 19%, 23968 KB, 3639 KB/s, 6 seconds passed
+... 19%, 24000 KB, 3643 KB/s, 6 seconds passed
+... 19%, 24032 KB, 3648 KB/s, 6 seconds passed
+... 19%, 24064 KB, 3652 KB/s, 6 seconds passed
 
 .. parsed-literal::
 
-    ... 19%, 24224 KB, 3445 KB/s, 7 seconds passed
-... 19%, 24256 KB, 3447 KB/s, 7 seconds passed
-... 19%, 24288 KB, 3449 KB/s, 7 seconds passed
-... 19%, 24320 KB, 3451 KB/s, 7 seconds passed
+    ... 19%, 24096 KB, 3639 KB/s, 6 seconds passed
+... 19%, 24128 KB, 3644 KB/s, 6 seconds passed
+... 19%, 24160 KB, 3648 KB/s, 6 seconds passed
+... 19%, 24192 KB, 3652 KB/s, 6 seconds passed
+... 19%, 24224 KB, 3639 KB/s, 6 seconds passed
+... 19%, 24256 KB, 3644 KB/s, 6 seconds passed
+... 19%, 24288 KB, 3648 KB/s, 6 seconds passed
+... 19%, 24320 KB, 3652 KB/s, 6 seconds passed
 
 .. parsed-literal::
 
-    ... 19%, 24352 KB, 3445 KB/s, 7 seconds passed
-... 19%, 24384 KB, 3448 KB/s, 7 seconds passed
-... 19%, 24416 KB, 3449 KB/s, 7 seconds passed
-... 19%, 24448 KB, 3451 KB/s, 7 seconds passed
-... 19%, 24480 KB, 3446 KB/s, 7 seconds passed
-... 19%, 24512 KB, 3448 KB/s, 7 seconds passed
-... 19%, 24544 KB, 3449 KB/s, 7 seconds passed
+    ... 19%, 24352 KB, 3639 KB/s, 6 seconds passed
+... 19%, 24384 KB, 3644 KB/s, 6 seconds passed
+... 19%, 24416 KB, 3648 KB/s, 6 seconds passed
+... 19%, 24448 KB, 3652 KB/s, 6 seconds passed
 
 .. parsed-literal::
 
-    ... 19%, 24576 KB, 3451 KB/s, 7 seconds passed
-... 19%, 24608 KB, 3446 KB/s, 7 seconds passed
-... 19%, 24640 KB, 3448 KB/s, 7 seconds passed
-... 19%, 24672 KB, 3450 KB/s, 7 seconds passed
-... 19%, 24704 KB, 3452 KB/s, 7 seconds passed
+    ... 19%, 24480 KB, 3639 KB/s, 6 seconds passed
+... 19%, 24512 KB, 3644 KB/s, 6 seconds passed
+... 19%, 24544 KB, 3648 KB/s, 6 seconds passed
+... 19%, 24576 KB, 3652 KB/s, 6 seconds passed
+... 19%, 24608 KB, 3640 KB/s, 6 seconds passed
+... 19%, 24640 KB, 3644 KB/s, 6 seconds passed
+... 19%, 24672 KB, 3649 KB/s, 6 seconds passed
+... 19%, 24704 KB, 3653 KB/s, 6 seconds passed
 
 .. parsed-literal::
 
-    ... 19%, 24736 KB, 3447 KB/s, 7 seconds passed
-... 19%, 24768 KB, 3449 KB/s, 7 seconds passed
-... 19%, 24800 KB, 3450 KB/s, 7 seconds passed
-... 19%, 24832 KB, 3451 KB/s, 7 seconds passed
-... 19%, 24864 KB, 3446 KB/s, 7 seconds passed
-... 19%, 24896 KB, 3449 KB/s, 7 seconds passed
+    ... 19%, 24736 KB, 3642 KB/s, 6 seconds passed
+... 19%, 24768 KB, 3644 KB/s, 6 seconds passed
+... 19%, 24800 KB, 3649 KB/s, 6 seconds passed
+... 19%, 24832 KB, 3653 KB/s, 6 seconds passed
 
 .. parsed-literal::
 
-    ... 19%, 24928 KB, 3450 KB/s, 7 seconds passed
-... 19%, 24960 KB, 3451 KB/s, 7 seconds passed
-... 19%, 24992 KB, 3446 KB/s, 7 seconds passed
-... 19%, 25024 KB, 3449 KB/s, 7 seconds passed
-... 19%, 25056 KB, 3450 KB/s, 7 seconds passed
-... 19%, 25088 KB, 3451 KB/s, 7 seconds passed
+    ... 19%, 24864 KB, 3642 KB/s, 6 seconds passed
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+... 19%, 24928 KB, 3649 KB/s, 6 seconds passed
+... 19%, 24960 KB, 3654 KB/s, 6 seconds passed
+... 19%, 24992 KB, 3642 KB/s, 6 seconds passed
+... 19%, 25024 KB, 3645 KB/s, 6 seconds passed
 
 .. parsed-literal::
 
-    ... 19%, 25120 KB, 3447 KB/s, 7 seconds passed
-... 19%, 25152 KB, 3449 KB/s, 7 seconds passed
-... 19%, 25184 KB, 3451 KB/s, 7 seconds passed
-... 20%, 25216 KB, 3452 KB/s, 7 seconds passed
+    ... 19%, 25056 KB, 3649 KB/s, 6 seconds passed
+... 19%, 25088 KB, 3654 KB/s, 6 seconds passed
+... 19%, 25120 KB, 3641 KB/s, 6 seconds passed
+... 19%, 25152 KB, 3645 KB/s, 6 seconds passed
+... 19%, 25184 KB, 3649 KB/s, 6 seconds passed
+... 20%, 25216 KB, 3654 KB/s, 6 seconds passed
 
 .. parsed-literal::
 
-    ... 20%, 25248 KB, 3447 KB/s, 7 seconds passed
-... 20%, 25280 KB, 3450 KB/s, 7 seconds passed
-... 20%, 25312 KB, 3451 KB/s, 7 seconds passed
-... 20%, 25344 KB, 3452 KB/s, 7 seconds passed
-... 20%, 25376 KB, 3447 KB/s, 7 seconds passed
-... 20%, 25408 KB, 3450 KB/s, 7 seconds passed
-... 20%, 25440 KB, 3451 KB/s, 7 seconds passed
+    ... 20%, 25248 KB, 3641 KB/s, 6 seconds passed
+... 20%, 25280 KB, 3645 KB/s, 6 seconds passed
+... 20%, 25312 KB, 3650 KB/s, 6 seconds passed
+... 20%, 25344 KB, 3654 KB/s, 6 seconds passed
+... 20%, 25376 KB, 3642 KB/s, 6 seconds passed
 
 .. parsed-literal::
 
-    ... 20%, 25472 KB, 3452 KB/s, 7 seconds passed
-... 20%, 25504 KB, 3448 KB/s, 7 seconds passed
-... 20%, 25536 KB, 3450 KB/s, 7 seconds passed
-... 20%, 25568 KB, 3452 KB/s, 7 seconds passed
-... 20%, 25600 KB, 3452 KB/s, 7 seconds passed
+    ... 20%, 25408 KB, 3646 KB/s, 6 seconds passed
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+... 20%, 25504 KB, 3642 KB/s, 7 seconds passed
+... 20%, 25536 KB, 3646 KB/s, 7 seconds passed
+... 20%, 25568 KB, 3650 KB/s, 7 seconds passed
+... 20%, 25600 KB, 3654 KB/s, 7 seconds passed
 
 .. parsed-literal::
 
-    ... 20%, 25632 KB, 3448 KB/s, 7 seconds passed
-... 20%, 25664 KB, 3450 KB/s, 7 seconds passed
-... 20%, 25696 KB, 3452 KB/s, 7 seconds passed
-... 20%, 25728 KB, 3452 KB/s, 7 seconds passed
-... 20%, 25760 KB, 3448 KB/s, 7 seconds passed
-... 20%, 25792 KB, 3450 KB/s, 7 seconds passed
+    ... 20%, 25632 KB, 3642 KB/s, 7 seconds passed
+... 20%, 25664 KB, 3646 KB/s, 7 seconds passed
+... 20%, 25696 KB, 3650 KB/s, 7 seconds passed
+... 20%, 25728 KB, 3655 KB/s, 7 seconds passed
 
 .. parsed-literal::
 
-    ... 20%, 25824 KB, 3452 KB/s, 7 seconds passed
-... 20%, 25856 KB, 3453 KB/s, 7 seconds passed
-... 20%, 25888 KB, 3449 KB/s, 7 seconds passed
-... 20%, 25920 KB, 3450 KB/s, 7 seconds passed
-... 20%, 25952 KB, 3452 KB/s, 7 seconds passed
-... 20%, 25984 KB, 3453 KB/s, 7 seconds passed
+    ... 20%, 25760 KB, 3642 KB/s, 7 seconds passed
+... 20%, 25792 KB, 3646 KB/s, 7 seconds passed
+... 20%, 25824 KB, 3651 KB/s, 7 seconds passed
+... 20%, 25856 KB, 3655 KB/s, 7 seconds passed
+... 20%, 25888 KB, 3644 KB/s, 7 seconds passed
+... 20%, 25920 KB, 3647 KB/s, 7 seconds passed
+... 20%, 25952 KB, 3651 KB/s, 7 seconds passed
+... 20%, 25984 KB, 3655 KB/s, 7 seconds passed
 
 .. parsed-literal::
 
-    ... 20%, 26016 KB, 3449 KB/s, 7 seconds passed
-... 20%, 26048 KB, 3451 KB/s, 7 seconds passed
-... 20%, 26080 KB, 3452 KB/s, 7 seconds passed
-... 20%, 26112 KB, 3453 KB/s, 7 seconds passed
+    ... 20%, 26016 KB, 3643 KB/s, 7 seconds passed
+... 20%, 26048 KB, 3647 KB/s, 7 seconds passed
+... 20%, 26080 KB, 3651 KB/s, 7 seconds passed
+... 20%, 26112 KB, 3655 KB/s, 7 seconds passed
 
 .. parsed-literal::
 
-    ... 20%, 26144 KB, 3449 KB/s, 7 seconds passed
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-... 20%, 26208 KB, 3453 KB/s, 7 seconds passed
-... 20%, 26240 KB, 3453 KB/s, 7 seconds passed
-... 20%, 26272 KB, 3449 KB/s, 7 seconds passed
-... 20%, 26304 KB, 3451 KB/s, 7 seconds passed
-... 20%, 26336 KB, 3453 KB/s, 7 seconds passed
+    ... 20%, 26144 KB, 3643 KB/s, 7 seconds passed
+... 20%, 26176 KB, 3647 KB/s, 7 seconds passed
+... 20%, 26208 KB, 3651 KB/s, 7 seconds passed
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+... 20%, 26272 KB, 3644 KB/s, 7 seconds passed
+... 20%, 26304 KB, 3647 KB/s, 7 seconds passed
+... 20%, 26336 KB, 3652 KB/s, 7 seconds passed
+... 20%, 26368 KB, 3656 KB/s, 7 seconds passed
 
 .. parsed-literal::
 
-    ... 20%, 26368 KB, 3453 KB/s, 7 seconds passed
-... 20%, 26400 KB, 3449 KB/s, 7 seconds passed
-... 20%, 26432 KB, 3452 KB/s, 7 seconds passed
-... 21%, 26464 KB, 3453 KB/s, 7 seconds passed
-... 21%, 26496 KB, 3454 KB/s, 7 seconds passed
+    ... 20%, 26400 KB, 3644 KB/s, 7 seconds passed
+... 20%, 26432 KB, 3648 KB/s, 7 seconds passed
+... 21%, 26464 KB, 3652 KB/s, 7 seconds passed
+... 21%, 26496 KB, 3656 KB/s, 7 seconds passed
 
 .. parsed-literal::
 
-    ... 21%, 26528 KB, 3450 KB/s, 7 seconds passed
-... 21%, 26560 KB, 3452 KB/s, 7 seconds passed
-... 21%, 26592 KB, 3453 KB/s, 7 seconds passed
-... 21%, 26624 KB, 3454 KB/s, 7 seconds passed
-... 21%, 26656 KB, 3450 KB/s, 7 seconds passed
-... 21%, 26688 KB, 3452 KB/s, 7 seconds passed
+    ... 21%, 26528 KB, 3644 KB/s, 7 seconds passed
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+... 21%, 26592 KB, 3652 KB/s, 7 seconds passed
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+... 21%, 26656 KB, 3645 KB/s, 7 seconds passed
+... 21%, 26688 KB, 3648 KB/s, 7 seconds passed
+... 21%, 26720 KB, 3652 KB/s, 7 seconds passed
+... 21%, 26752 KB, 3656 KB/s, 7 seconds passed
 
 .. parsed-literal::
 
-    ... 21%, 26720 KB, 3453 KB/s, 7 seconds passed
-... 21%, 26752 KB, 3454 KB/s, 7 seconds passed
-... 21%, 26784 KB, 3450 KB/s, 7 seconds passed
-... 21%, 26816 KB, 3452 KB/s, 7 seconds passed
-... 21%, 26848 KB, 3453 KB/s, 7 seconds passed
-... 21%, 26880 KB, 3454 KB/s, 7 seconds passed
+    ... 21%, 26784 KB, 3645 KB/s, 7 seconds passed
+... 21%, 26816 KB, 3648 KB/s, 7 seconds passed
+... 21%, 26848 KB, 3653 KB/s, 7 seconds passed
+... 21%, 26880 KB, 3657 KB/s, 7 seconds passed
 
 .. parsed-literal::
 
-    ... 21%, 26912 KB, 3450 KB/s, 7 seconds passed
-... 21%, 26944 KB, 3453 KB/s, 7 seconds passed
-... 21%, 26976 KB, 3455 KB/s, 7 seconds passed
-... 21%, 27008 KB, 3455 KB/s, 7 seconds passed
+    ... 21%, 26912 KB, 3645 KB/s, 7 seconds passed
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+... 21%, 26976 KB, 3653 KB/s, 7 seconds passed
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+... 21%, 27072 KB, 3649 KB/s, 7 seconds passed
+... 21%, 27104 KB, 3653 KB/s, 7 seconds passed
+... 21%, 27136 KB, 3657 KB/s, 7 seconds passed
 
 .. parsed-literal::
 
-    ... 21%, 27040 KB, 3451 KB/s, 7 seconds passed
-... 21%, 27072 KB, 3452 KB/s, 7 seconds passed
-... 21%, 27104 KB, 3454 KB/s, 7 seconds passed
-... 21%, 27136 KB, 3453 KB/s, 7 seconds passed
-... 21%, 27168 KB, 3450 KB/s, 7 seconds passed
-... 21%, 27200 KB, 3452 KB/s, 7 seconds passed
-... 21%, 27232 KB, 3454 KB/s, 7 seconds passed
+    ... 21%, 27168 KB, 3645 KB/s, 7 seconds passed
+... 21%, 27200 KB, 3649 KB/s, 7 seconds passed
+... 21%, 27232 KB, 3653 KB/s, 7 seconds passed
+... 21%, 27264 KB, 3657 KB/s, 7 seconds passed
 
 .. parsed-literal::
 
-    ... 21%, 27264 KB, 3454 KB/s, 7 seconds passed
-... 21%, 27296 KB, 3451 KB/s, 7 seconds passed
-... 21%, 27328 KB, 3453 KB/s, 7 seconds passed
-... 21%, 27360 KB, 3454 KB/s, 7 seconds passed
-... 21%, 27392 KB, 3454 KB/s, 7 seconds passed
+    ... 21%, 27296 KB, 3645 KB/s, 7 seconds passed
+... 21%, 27328 KB, 3649 KB/s, 7 seconds passed
+... 21%, 27360 KB, 3653 KB/s, 7 seconds passed
+... 21%, 27392 KB, 3658 KB/s, 7 seconds passed
+... 21%, 27424 KB, 3647 KB/s, 7 seconds passed
+... 21%, 27456 KB, 3650 KB/s, 7 seconds passed
+... 21%, 27488 KB, 3654 KB/s, 7 seconds passed
+... 21%, 27520 KB, 3658 KB/s, 7 seconds passed
 
 .. parsed-literal::
 
-    ... 21%, 27424 KB, 3451 KB/s, 7 seconds passed
-... 21%, 27456 KB, 3453 KB/s, 7 seconds passed
-... 21%, 27488 KB, 3454 KB/s, 7 seconds passed
-... 21%, 27520 KB, 3455 KB/s, 7 seconds passed
-... 21%, 27552 KB, 3451 KB/s, 7 seconds passed
-... 21%, 27584 KB, 3454 KB/s, 7 seconds passed
+    ... 21%, 27552 KB, 3647 KB/s, 7 seconds passed
+... 21%, 27584 KB, 3650 KB/s, 7 seconds passed
+... 21%, 27616 KB, 3654 KB/s, 7 seconds passed
+... 21%, 27648 KB, 3645 KB/s, 7 seconds passed
 
 .. parsed-literal::
 
-    ... 21%, 27616 KB, 3455 KB/s, 7 seconds passed
-... 21%, 27648 KB, 3455 KB/s, 8 seconds passed
-... 21%, 27680 KB, 3451 KB/s, 8 seconds passed
-... 22%, 27712 KB, 3453 KB/s, 8 seconds passed
-... 22%, 27744 KB, 3455 KB/s, 8 seconds passed
-... 22%, 27776 KB, 3455 KB/s, 8 seconds passed
+    ... 21%, 27680 KB, 3646 KB/s, 7 seconds passed
+... 22%, 27712 KB, 3650 KB/s, 7 seconds passed
+... 22%, 27744 KB, 3654 KB/s, 7 seconds passed
+... 22%, 27776 KB, 3645 KB/s, 7 seconds passed
+... 22%, 27808 KB, 3646 KB/s, 7 seconds passed
+... 22%, 27840 KB, 3650 KB/s, 7 seconds passed
+... 22%, 27872 KB, 3654 KB/s, 7 seconds passed
+... 22%, 27904 KB, 3658 KB/s, 7 seconds passed
 
 .. parsed-literal::
 
-    ... 22%, 27808 KB, 3451 KB/s, 8 seconds passed
-... 22%, 27840 KB, 3454 KB/s, 8 seconds passed
-... 22%, 27872 KB, 3455 KB/s, 8 seconds passed
-... 22%, 27904 KB, 3455 KB/s, 8 seconds passed
+    ... 22%, 27936 KB, 3647 KB/s, 7 seconds passed
+... 22%, 27968 KB, 3651 KB/s, 7 seconds passed
+... 22%, 28000 KB, 3654 KB/s, 7 seconds passed
+... 22%, 28032 KB, 3658 KB/s, 7 seconds passed
 
 .. parsed-literal::
 
-    ... 22%, 27936 KB, 3452 KB/s, 8 seconds passed
-... 22%, 27968 KB, 3454 KB/s, 8 seconds passed
-... 22%, 28000 KB, 3455 KB/s, 8 seconds passed
-... 22%, 28032 KB, 3455 KB/s, 8 seconds passed
-... 22%, 28064 KB, 3452 KB/s, 8 seconds passed
-... 22%, 28096 KB, 3454 KB/s, 8 seconds passed
-... 22%, 28128 KB, 3456 KB/s, 8 seconds passed
+    ... 22%, 28064 KB, 3647 KB/s, 7 seconds passed
+... 22%, 28096 KB, 3651 KB/s, 7 seconds passed
+... 22%, 28128 KB, 3655 KB/s, 7 seconds passed
+... 22%, 28160 KB, 3646 KB/s, 7 seconds passed
+... 22%, 28192 KB, 3647 KB/s, 7 seconds passed
+... 22%, 28224 KB, 3651 KB/s, 7 seconds passed
+... 22%, 28256 KB, 3655 KB/s, 7 seconds passed
 
 .. parsed-literal::
 
-    ... 22%, 28160 KB, 3456 KB/s, 8 seconds passed
-... 22%, 28192 KB, 3452 KB/s, 8 seconds passed
-... 22%, 28224 KB, 3455 KB/s, 8 seconds passed
-... 22%, 28256 KB, 3456 KB/s, 8 seconds passed
-... 22%, 28288 KB, 3456 KB/s, 8 seconds passed
+    ... 22%, 28288 KB, 3647 KB/s, 7 seconds passed
+... 22%, 28320 KB, 3648 KB/s, 7 seconds passed
+... 22%, 28352 KB, 3651 KB/s, 7 seconds passed
+... 22%, 28384 KB, 3655 KB/s, 7 seconds passed
 
 .. parsed-literal::
 
-    ... 22%, 28320 KB, 3452 KB/s, 8 seconds passed
-... 22%, 28352 KB, 3455 KB/s, 8 seconds passed
-... 22%, 28384 KB, 3456 KB/s, 8 seconds passed
-... 22%, 28416 KB, 3457 KB/s, 8 seconds passed
-... 22%, 28448 KB, 3453 KB/s, 8 seconds passed
-... 22%, 28480 KB, 3454 KB/s, 8 seconds passed
+    ... 22%, 28416 KB, 3647 KB/s, 7 seconds passed
+... 22%, 28448 KB, 3648 KB/s, 7 seconds passed
+... 22%, 28480 KB, 3652 KB/s, 7 seconds passed
+... 22%, 28512 KB, 3655 KB/s, 7 seconds passed
+... 22%, 28544 KB, 3647 KB/s, 7 seconds passed
+... 22%, 28576 KB, 3648 KB/s, 7 seconds passed
+... 22%, 28608 KB, 3652 KB/s, 7 seconds passed
+... 22%, 28640 KB, 3656 KB/s, 7 seconds passed
 
 .. parsed-literal::
 
-    ... 22%, 28512 KB, 3456 KB/s, 8 seconds passed
-... 22%, 28544 KB, 3456 KB/s, 8 seconds passed
-... 22%, 28576 KB, 3453 KB/s, 8 seconds passed
-... 22%, 28608 KB, 3455 KB/s, 8 seconds passed
-... 22%, 28640 KB, 3455 KB/s, 8 seconds passed
-... 22%, 28672 KB, 3456 KB/s, 8 seconds passed
+    ... 22%, 28672 KB, 3648 KB/s, 7 seconds passed
+... 22%, 28704 KB, 3648 KB/s, 7 seconds passed
+... 22%, 28736 KB, 3652 KB/s, 7 seconds passed
+... 22%, 28768 KB, 3656 KB/s, 7 seconds passed
 
 .. parsed-literal::
 
-    ... 22%, 28704 KB, 3453 KB/s, 8 seconds passed
-... 22%, 28736 KB, 3455 KB/s, 8 seconds passed
-... 22%, 28768 KB, 3457 KB/s, 8 seconds passed
-... 22%, 28800 KB, 3457 KB/s, 8 seconds passed
+    ... 22%, 28800 KB, 3648 KB/s, 7 seconds passed
+... 22%, 28832 KB, 3649 KB/s, 7 seconds passed
+... 22%, 28864 KB, 3652 KB/s, 7 seconds passed
+... 22%, 28896 KB, 3656 KB/s, 7 seconds passed
+... 22%, 28928 KB, 3648 KB/s, 7 seconds passed
+... 22%, 28960 KB, 3649 KB/s, 7 seconds passed
+... 23%, 28992 KB, 3652 KB/s, 7 seconds passed
+... 23%, 29024 KB, 3656 KB/s, 7 seconds passed
 
 .. parsed-literal::
 
-    ... 22%, 28832 KB, 3453 KB/s, 8 seconds passed
-... 22%, 28864 KB, 3456 KB/s, 8 seconds passed
-... 22%, 28896 KB, 3457 KB/s, 8 seconds passed
-... 22%, 28928 KB, 3457 KB/s, 8 seconds passed
-... 22%, 28960 KB, 3454 KB/s, 8 seconds passed
-... 23%, 28992 KB, 3456 KB/s, 8 seconds passed
-... 23%, 29024 KB, 3457 KB/s, 8 seconds passed
+    ... 23%, 29056 KB, 3648 KB/s, 7 seconds passed
+... 23%, 29088 KB, 3649 KB/s, 7 seconds passed
+... 23%, 29120 KB, 3653 KB/s, 7 seconds passed
+... 23%, 29152 KB, 3656 KB/s, 7 seconds passed
 
 .. parsed-literal::
 
-    ... 23%, 29056 KB, 3457 KB/s, 8 seconds passed
-... 23%, 29088 KB, 3454 KB/s, 8 seconds passed
-... 23%, 29120 KB, 3455 KB/s, 8 seconds passed
-... 23%, 29152 KB, 3456 KB/s, 8 seconds passed
+    ... 23%, 29184 KB, 3647 KB/s, 8 seconds passed
+... 23%, 29216 KB, 3649 KB/s, 8 seconds passed
+... 23%, 29248 KB, 3653 KB/s, 8 seconds passed
+... 23%, 29280 KB, 3657 KB/s, 8 seconds passed
+... 23%, 29312 KB, 3648 KB/s, 8 seconds passed
+... 23%, 29344 KB, 3649 KB/s, 8 seconds passed
+... 23%, 29376 KB, 3653 KB/s, 8 seconds passed
+... 23%, 29408 KB, 3657 KB/s, 8 seconds passed
 
 .. parsed-literal::
 
-    ... 23%, 29184 KB, 3453 KB/s, 8 seconds passed
-... 23%, 29216 KB, 3454 KB/s, 8 seconds passed
-... 23%, 29248 KB, 3456 KB/s, 8 seconds passed
-... 23%, 29280 KB, 3456 KB/s, 8 seconds passed
-... 23%, 29312 KB, 3453 KB/s, 8 seconds passed
-... 23%, 29344 KB, 3454 KB/s, 8 seconds passed
-... 23%, 29376 KB, 3456 KB/s, 8 seconds passed
+    ... 23%, 29440 KB, 3648 KB/s, 8 seconds passed
+... 23%, 29472 KB, 3649 KB/s, 8 seconds passed
+... 23%, 29504 KB, 3653 KB/s, 8 seconds passed
+... 23%, 29536 KB, 3657 KB/s, 8 seconds passed
 
 .. parsed-literal::
 
-    ... 23%, 29408 KB, 3456 KB/s, 8 seconds passed
-... 23%, 29440 KB, 3453 KB/s, 8 seconds passed
-... 23%, 29472 KB, 3454 KB/s, 8 seconds passed
-... 23%, 29504 KB, 3456 KB/s, 8 seconds passed
-... 23%, 29536 KB, 3456 KB/s, 8 seconds passed
+    ... 23%, 29568 KB, 3648 KB/s, 8 seconds passed
+... 23%, 29600 KB, 3650 KB/s, 8 seconds passed
+... 23%, 29632 KB, 3653 KB/s, 8 seconds passed
+... 23%, 29664 KB, 3657 KB/s, 8 seconds passed
+... 23%, 29696 KB, 3648 KB/s, 8 seconds passed
+... 23%, 29728 KB, 3650 KB/s, 8 seconds passed
+... 23%, 29760 KB, 3654 KB/s, 8 seconds passed
+... 23%, 29792 KB, 3657 KB/s, 8 seconds passed
 
 .. parsed-literal::
 
-    ... 23%, 29568 KB, 3453 KB/s, 8 seconds passed
-... 23%, 29600 KB, 3454 KB/s, 8 seconds passed
-... 23%, 29632 KB, 3456 KB/s, 8 seconds passed
-... 23%, 29664 KB, 3456 KB/s, 8 seconds passed
-... 23%, 29696 KB, 3453 KB/s, 8 seconds passed
+    ... 23%, 29824 KB, 3648 KB/s, 8 seconds passed
+... 23%, 29856 KB, 3650 KB/s, 8 seconds passed
+... 23%, 29888 KB, 3654 KB/s, 8 seconds passed
+... 23%, 29920 KB, 3657 KB/s, 8 seconds passed
 
 .. parsed-literal::
 
-    ... 23%, 29728 KB, 3454 KB/s, 8 seconds passed
-... 23%, 29760 KB, 3456 KB/s, 8 seconds passed
-... 23%, 29792 KB, 3456 KB/s, 8 seconds passed
-... 23%, 29824 KB, 3453 KB/s, 8 seconds passed
-... 23%, 29856 KB, 3454 KB/s, 8 seconds passed
-... 23%, 29888 KB, 3456 KB/s, 8 seconds passed
+    ... 23%, 29952 KB, 3649 KB/s, 8 seconds passed
+... 23%, 29984 KB, 3650 KB/s, 8 seconds passed
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+... 23%, 30080 KB, 3649 KB/s, 8 seconds passed
+... 23%, 30112 KB, 3651 KB/s, 8 seconds passed
+... 23%, 30144 KB, 3654 KB/s, 8 seconds passed
+... 23%, 30176 KB, 3658 KB/s, 8 seconds passed
 
 .. parsed-literal::
 
-    ... 23%, 29920 KB, 3457 KB/s, 8 seconds passed
-... 23%, 29952 KB, 3453 KB/s, 8 seconds passed
-... 23%, 29984 KB, 3454 KB/s, 8 seconds passed
-... 23%, 30016 KB, 3456 KB/s, 8 seconds passed
-... 23%, 30048 KB, 3457 KB/s, 8 seconds passed
+    ... 23%, 30208 KB, 3648 KB/s, 8 seconds passed
+... 24%, 30240 KB, 3651 KB/s, 8 seconds passed
+... 24%, 30272 KB, 3654 KB/s, 8 seconds passed
+... 24%, 30304 KB, 3658 KB/s, 8 seconds passed
 
 .. parsed-literal::
 
-    ... 23%, 30080 KB, 3454 KB/s, 8 seconds passed
-... 23%, 30112 KB, 3455 KB/s, 8 seconds passed
-... 23%, 30144 KB, 3457 KB/s, 8 seconds passed
-... 23%, 30176 KB, 3457 KB/s, 8 seconds passed
-... 23%, 30208 KB, 3454 KB/s, 8 seconds passed
-... 24%, 30240 KB, 3455 KB/s, 8 seconds passed
-... 24%, 30272 KB, 3457 KB/s, 8 seconds passed
+    ... 24%, 30336 KB, 3649 KB/s, 8 seconds passed
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+... 24%, 30464 KB, 3649 KB/s, 8 seconds passed
+... 24%, 30496 KB, 3651 KB/s, 8 seconds passed
+... 24%, 30528 KB, 3655 KB/s, 8 seconds passed
+... 24%, 30560 KB, 3658 KB/s, 8 seconds passed
 
 .. parsed-literal::
 
-    ... 24%, 30304 KB, 3457 KB/s, 8 seconds passed
-... 24%, 30336 KB, 3455 KB/s, 8 seconds passed
-... 24%, 30368 KB, 3456 KB/s, 8 seconds passed
-... 24%, 30400 KB, 3458 KB/s, 8 seconds passed
-... 24%, 30432 KB, 3458 KB/s, 8 seconds passed
+    ... 24%, 30592 KB, 3649 KB/s, 8 seconds passed
+... 24%, 30624 KB, 3651 KB/s, 8 seconds passed
+... 24%, 30656 KB, 3655 KB/s, 8 seconds passed
+... 24%, 30688 KB, 3658 KB/s, 8 seconds passed
 
 .. parsed-literal::
 
-    ... 24%, 30464 KB, 3455 KB/s, 8 seconds passed
-... 24%, 30496 KB, 3455 KB/s, 8 seconds passed
-... 24%, 30528 KB, 3457 KB/s, 8 seconds passed
-... 24%, 30560 KB, 3457 KB/s, 8 seconds passed
-... 24%, 30592 KB, 3454 KB/s, 8 seconds passed
+    ... 24%, 30720 KB, 3650 KB/s, 8 seconds passed
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+... 24%, 30816 KB, 3658 KB/s, 8 seconds passed
+... 24%, 30848 KB, 3651 KB/s, 8 seconds passed
+... 24%, 30880 KB, 3653 KB/s, 8 seconds passed
 
 .. parsed-literal::
 
-    ... 24%, 30624 KB, 3455 KB/s, 8 seconds passed
-... 24%, 30656 KB, 3457 KB/s, 8 seconds passed
-... 24%, 30688 KB, 3458 KB/s, 8 seconds passed
-... 24%, 30720 KB, 3455 KB/s, 8 seconds passed
-... 24%, 30752 KB, 3456 KB/s, 8 seconds passed
-... 24%, 30784 KB, 3458 KB/s, 8 seconds passed
-... 24%, 30816 KB, 3458 KB/s, 8 seconds passed
+    ... 24%, 30912 KB, 3655 KB/s, 8 seconds passed
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+... 24%, 31008 KB, 3653 KB/s, 8 seconds passed
+... 24%, 31040 KB, 3655 KB/s, 8 seconds passed
+... 24%, 31072 KB, 3659 KB/s, 8 seconds passed
 
 .. parsed-literal::
 
-    ... 24%, 30848 KB, 3456 KB/s, 8 seconds passed
-... 24%, 30880 KB, 3457 KB/s, 8 seconds passed
-... 24%, 30912 KB, 3458 KB/s, 8 seconds passed
-... 24%, 30944 KB, 3458 KB/s, 8 seconds passed
-... 24%, 30976 KB, 3456 KB/s, 8 seconds passed
+    ... 24%, 31104 KB, 3651 KB/s, 8 seconds passed
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+... 24%, 31168 KB, 3655 KB/s, 8 seconds passed
+... 24%, 31200 KB, 3659 KB/s, 8 seconds passed
+... 24%, 31232 KB, 3650 KB/s, 8 seconds passed
 
 .. parsed-literal::
 
-    ... 24%, 31008 KB, 3457 KB/s, 8 seconds passed
-... 24%, 31040 KB, 3459 KB/s, 8 seconds passed
-... 24%, 31072 KB, 3459 KB/s, 8 seconds passed
-... 24%, 31104 KB, 3456 KB/s, 8 seconds passed
-... 24%, 31136 KB, 3456 KB/s, 9 seconds passed
-... 24%, 31168 KB, 3458 KB/s, 9 seconds passed
+    ... 24%, 31264 KB, 3652 KB/s, 8 seconds passed
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+... 24%, 31328 KB, 3659 KB/s, 8 seconds passed
+... 24%, 31360 KB, 3650 KB/s, 8 seconds passed
+... 24%, 31392 KB, 3653 KB/s, 8 seconds passed
+... 24%, 31424 KB, 3656 KB/s, 8 seconds passed
+... 24%, 31456 KB, 3659 KB/s, 8 seconds passed
 
 .. parsed-literal::
 
-    ... 24%, 31200 KB, 3458 KB/s, 9 seconds passed
-... 24%, 31232 KB, 3454 KB/s, 9 seconds passed
-... 24%, 31264 KB, 3456 KB/s, 9 seconds passed
-... 24%, 31296 KB, 3458 KB/s, 9 seconds passed
-... 24%, 31328 KB, 3459 KB/s, 9 seconds passed
+    ... 24%, 31488 KB, 3651 KB/s, 8 seconds passed
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+... 25%, 31552 KB, 3656 KB/s, 8 seconds passed
+... 25%, 31584 KB, 3659 KB/s, 8 seconds passed
+... 25%, 31616 KB, 3651 KB/s, 8 seconds passed
 
 .. parsed-literal::
 
-    ... 24%, 31360 KB, 3455 KB/s, 9 seconds passed
-... 24%, 31392 KB, 3456 KB/s, 9 seconds passed
-... 24%, 31424 KB, 3459 KB/s, 9 seconds passed
-... 24%, 31456 KB, 3459 KB/s, 9 seconds passed
-... 24%, 31488 KB, 3456 KB/s, 9 seconds passed
-... 25%, 31520 KB, 3458 KB/s, 9 seconds passed
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+... 25%, 31776 KB, 3654 KB/s, 8 seconds passed
+... 25%, 31808 KB, 3656 KB/s, 8 seconds passed
+... 25%, 31840 KB, 3660 KB/s, 8 seconds passed
 
 .. parsed-literal::
 
-    ... 25%, 31552 KB, 3459 KB/s, 9 seconds passed
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-... 25%, 31616 KB, 3455 KB/s, 9 seconds passed
-... 25%, 31648 KB, 3457 KB/s, 9 seconds passed
-... 25%, 31680 KB, 3458 KB/s, 9 seconds passed
-... 25%, 31712 KB, 3459 KB/s, 9 seconds passed
+    ... 25%, 31872 KB, 3651 KB/s, 8 seconds passed
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+... 25%, 31936 KB, 3656 KB/s, 8 seconds passed
+... 25%, 31968 KB, 3660 KB/s, 8 seconds passed
+... 25%, 32000 KB, 3652 KB/s, 8 seconds passed
 
 .. parsed-literal::
 
-    ... 25%, 31744 KB, 3455 KB/s, 9 seconds passed
-... 25%, 31776 KB, 3457 KB/s, 9 seconds passed
-... 25%, 31808 KB, 3458 KB/s, 9 seconds passed
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+    ... 25%, 32032 KB, 3654 KB/s, 8 seconds passed
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+... 25%, 32128 KB, 3652 KB/s, 8 seconds passed
+... 25%, 32160 KB, 3654 KB/s, 8 seconds passed
+... 25%, 32192 KB, 3657 KB/s, 8 seconds passed
+... 25%, 32224 KB, 3660 KB/s, 8 seconds passed
 
 .. parsed-literal::
 
-    ... 25%, 31872 KB, 3455 KB/s, 9 seconds passed
-... 25%, 31904 KB, 3457 KB/s, 9 seconds passed
-... 25%, 31936 KB, 3459 KB/s, 9 seconds passed
-... 25%, 31968 KB, 3460 KB/s, 9 seconds passed
-... 25%, 32000 KB, 3456 KB/s, 9 seconds passed
-... 25%, 32032 KB, 3457 KB/s, 9 seconds passed
-... 25%, 32064 KB, 3460 KB/s, 9 seconds passed
+    ... 25%, 32256 KB, 3652 KB/s, 8 seconds passed
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+... 25%, 32320 KB, 3657 KB/s, 8 seconds passed
+... 25%, 32352 KB, 3660 KB/s, 8 seconds passed
+... 25%, 32384 KB, 3652 KB/s, 8 seconds passed
 
 .. parsed-literal::
 
-    ... 25%, 32096 KB, 3460 KB/s, 9 seconds passed
-... 25%, 32128 KB, 3457 KB/s, 9 seconds passed
-... 25%, 32160 KB, 3458 KB/s, 9 seconds passed
-... 25%, 32192 KB, 3460 KB/s, 9 seconds passed
-... 25%, 32224 KB, 3460 KB/s, 9 seconds passed
+    ... 25%, 32416 KB, 3655 KB/s, 8 seconds passed
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+... 25%, 32576 KB, 3657 KB/s, 8 seconds passed
 
 .. parsed-literal::
 
-    ... 25%, 32256 KB, 3456 KB/s, 9 seconds passed
-... 25%, 32288 KB, 3458 KB/s, 9 seconds passed
-... 25%, 32320 KB, 3459 KB/s, 9 seconds passed
-... 25%, 32352 KB, 3459 KB/s, 9 seconds passed
-... 25%, 32384 KB, 3456 KB/s, 9 seconds passed
+    ... 25%, 32608 KB, 3653 KB/s, 8 seconds passed
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+... 25%, 32736 KB, 3653 KB/s, 8 seconds passed
 
 .. parsed-literal::
 
-    ... 25%, 32416 KB, 3458 KB/s, 9 seconds passed
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-... 25%, 32512 KB, 3457 KB/s, 9 seconds passed
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-... 25%, 32576 KB, 3460 KB/s, 9 seconds passed
+    ... 26%, 32768 KB, 3652 KB/s, 8 seconds passed
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+... 26%, 32928 KB, 3655 KB/s, 9 seconds passed
+... 26%, 32960 KB, 3658 KB/s, 9 seconds passed
 
 .. parsed-literal::
 
-    ... 25%, 32608 KB, 3460 KB/s, 9 seconds passed
-... 25%, 32640 KB, 3457 KB/s, 9 seconds passed
-... 25%, 32672 KB, 3458 KB/s, 9 seconds passed
-... 25%, 32704 KB, 3460 KB/s, 9 seconds passed
-... 25%, 32736 KB, 3460 KB/s, 9 seconds passed
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+... 26%, 33056 KB, 3655 KB/s, 9 seconds passed
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 .. parsed-literal::
 
-    ... 26%, 32768 KB, 3457 KB/s, 9 seconds passed
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-... 26%, 32960 KB, 3460 KB/s, 9 seconds passed
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+... 26%, 33312 KB, 3655 KB/s, 9 seconds passed
+... 26%, 33344 KB, 3658 KB/s, 9 seconds passed
 
 .. parsed-literal::
 
-    ... 26%, 32992 KB, 3460 KB/s, 9 seconds passed
-... 26%, 33024 KB, 3457 KB/s, 9 seconds passed
-... 26%, 33056 KB, 3459 KB/s, 9 seconds passed
-... 26%, 33088 KB, 3461 KB/s, 9 seconds passed
-... 26%, 33120 KB, 3460 KB/s, 9 seconds passed
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+... 26%, 33472 KB, 3659 KB/s, 9 seconds passed
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 .. parsed-literal::
 
-    ... 26%, 33152 KB, 3457 KB/s, 9 seconds passed
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-... 26%, 33248 KB, 3460 KB/s, 9 seconds passed
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 .. parsed-literal::
 
-    ... 26%, 33344 KB, 3461 KB/s, 9 seconds passed
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-... 26%, 33440 KB, 3459 KB/s, 9 seconds passed
-... 26%, 33472 KB, 3459 KB/s, 9 seconds passed
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+... 26%, 33856 KB, 3659 KB/s, 9 seconds passed
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 .. parsed-literal::
 
-    ... 26%, 33504 KB, 3456 KB/s, 9 seconds passed
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-... 26%, 33568 KB, 3459 KB/s, 9 seconds passed
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+... 27%, 34112 KB, 3660 KB/s, 9 seconds passed
 
 .. parsed-literal::
 
-    ... 26%, 33664 KB, 3456 KB/s, 9 seconds passed
-... 26%, 33696 KB, 3459 KB/s, 9 seconds passed
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-... 26%, 33760 KB, 3456 KB/s, 9 seconds passed
-... 26%, 33792 KB, 3457 KB/s, 9 seconds passed
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-... 26%, 33856 KB, 3461 KB/s, 9 seconds passed
+    ... 27%, 34144 KB, 3656 KB/s, 9 seconds passed
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+... 27%, 34208 KB, 3657 KB/s, 9 seconds passed
+... 27%, 34240 KB, 3660 KB/s, 9 seconds passed
 
 .. parsed-literal::
 
-    ... 26%, 33888 KB, 3456 KB/s, 9 seconds passed
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-... 26%, 33952 KB, 3460 KB/s, 9 seconds passed
-... 26%, 33984 KB, 3461 KB/s, 9 seconds passed
-... 27%, 34016 KB, 3461 KB/s, 9 seconds passed
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+... 27%, 34464 KB, 3657 KB/s, 9 seconds passed
+... 27%, 34496 KB, 3660 KB/s, 9 seconds passed
 
 .. parsed-literal::
 
-    ... 27%, 34048 KB, 3457 KB/s, 9 seconds passed
-... 27%, 34080 KB, 3460 KB/s, 9 seconds passed
-... 27%, 34112 KB, 3462 KB/s, 9 seconds passed
-... 27%, 34144 KB, 3461 KB/s, 9 seconds passed
-... 27%, 34176 KB, 3457 KB/s, 9 seconds passed
-... 27%, 34208 KB, 3460 KB/s, 9 seconds passed
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+... 27%, 34592 KB, 3658 KB/s, 9 seconds passed
+... 27%, 34624 KB, 3660 KB/s, 9 seconds passed
+... 27%, 34656 KB, 3655 KB/s, 9 seconds passed
 
 .. parsed-literal::
 
-    ... 27%, 34240 KB, 3460 KB/s, 9 seconds passed
-... 27%, 34272 KB, 3457 KB/s, 9 seconds passed
-... 27%, 34304 KB, 3457 KB/s, 9 seconds passed
-... 27%, 34336 KB, 3460 KB/s, 9 seconds passed
-... 27%, 34368 KB, 3460 KB/s, 9 seconds passed
+    ... 27%, 34688 KB, 3656 KB/s, 9 seconds passed
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+... 27%, 34816 KB, 3656 KB/s, 9 seconds passed
+... 27%, 34848 KB, 3658 KB/s, 9 seconds passed
+... 27%, 34880 KB, 3661 KB/s, 9 seconds passed
 
 .. parsed-literal::
 
-    ... 27%, 34400 KB, 3457 KB/s, 9 seconds passed
-... 27%, 34432 KB, 3457 KB/s, 9 seconds passed
-... 27%, 34464 KB, 3460 KB/s, 9 seconds passed
-... 27%, 34496 KB, 3461 KB/s, 9 seconds passed
-... 27%, 34528 KB, 3458 KB/s, 9 seconds passed
+    ... 27%, 34912 KB, 3656 KB/s, 9 seconds passed
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+... 27%, 35008 KB, 3661 KB/s, 9 seconds passed
+... 27%, 35040 KB, 3656 KB/s, 9 seconds passed
 
 .. parsed-literal::
 
-    ... 27%, 34560 KB, 3458 KB/s, 9 seconds passed
-... 27%, 34592 KB, 3460 KB/s, 9 seconds passed
-... 27%, 34624 KB, 3462 KB/s, 10 seconds passed
-... 27%, 34656 KB, 3457 KB/s, 10 seconds passed
-... 27%, 34688 KB, 3458 KB/s, 10 seconds passed
-... 27%, 34720 KB, 3461 KB/s, 10 seconds passed
-... 27%, 34752 KB, 3462 KB/s, 10 seconds passed
+    ... 27%, 35072 KB, 3656 KB/s, 9 seconds passed
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+... 27%, 35200 KB, 3656 KB/s, 9 seconds passed
+... 27%, 35232 KB, 3658 KB/s, 9 seconds passed
+... 27%, 35264 KB, 3661 KB/s, 9 seconds passed
 
 .. parsed-literal::
 
-    ... 27%, 34784 KB, 3458 KB/s, 10 seconds passed
-... 27%, 34816 KB, 3458 KB/s, 10 seconds passed
-... 27%, 34848 KB, 3461 KB/s, 10 seconds passed
-... 27%, 34880 KB, 3461 KB/s, 10 seconds passed
+    ... 28%, 35296 KB, 3656 KB/s, 9 seconds passed
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+... 28%, 35360 KB, 3659 KB/s, 9 seconds passed
+... 28%, 35392 KB, 3662 KB/s, 9 seconds passed
+... 28%, 35424 KB, 3656 KB/s, 9 seconds passed
 
 .. parsed-literal::
 
-    ... 27%, 34912 KB, 3455 KB/s, 10 seconds passed
-... 27%, 34944 KB, 3458 KB/s, 10 seconds passed
-... 27%, 34976 KB, 3461 KB/s, 10 seconds passed
-... 27%, 35008 KB, 3461 KB/s, 10 seconds passed
-... 27%, 35040 KB, 3455 KB/s, 10 seconds passed
-... 27%, 35072 KB, 3458 KB/s, 10 seconds passed
-... 27%, 35104 KB, 3461 KB/s, 10 seconds passed
+    ... 28%, 35456 KB, 3657 KB/s, 9 seconds passed
+... 28%, 35488 KB, 3659 KB/s, 9 seconds passed
+... 28%, 35520 KB, 3662 KB/s, 9 seconds passed
+... 28%, 35552 KB, 3656 KB/s, 9 seconds passed
+... 28%, 35584 KB, 3657 KB/s, 9 seconds passed
+... 28%, 35616 KB, 3659 KB/s, 9 seconds passed
+... 28%, 35648 KB, 3662 KB/s, 9 seconds passed
 
 .. parsed-literal::
 
-    ... 27%, 35136 KB, 3461 KB/s, 10 seconds passed
-... 27%, 35168 KB, 3455 KB/s, 10 seconds passed
-... 27%, 35200 KB, 3458 KB/s, 10 seconds passed
-... 27%, 35232 KB, 3461 KB/s, 10 seconds passed
-... 27%, 35264 KB, 3461 KB/s, 10 seconds passed
+    ... 28%, 35680 KB, 3656 KB/s, 9 seconds passed
+... 28%, 35712 KB, 3657 KB/s, 9 seconds passed
+... 28%, 35744 KB, 3659 KB/s, 9 seconds passed
+... 28%, 35776 KB, 3662 KB/s, 9 seconds passed
 
 .. parsed-literal::
 
-    ... 28%, 35296 KB, 3458 KB/s, 10 seconds passed
-... 28%, 35328 KB, 3459 KB/s, 10 seconds passed
-... 28%, 35360 KB, 3461 KB/s, 10 seconds passed
-... 28%, 35392 KB, 3462 KB/s, 10 seconds passed
+    ... 28%, 35808 KB, 3656 KB/s, 9 seconds passed
+... 28%, 35840 KB, 3657 KB/s, 9 seconds passed
+... 28%, 35872 KB, 3659 KB/s, 9 seconds passed
+... 28%, 35904 KB, 3662 KB/s, 9 seconds passed
+... 28%, 35936 KB, 3656 KB/s, 9 seconds passed
+... 28%, 35968 KB, 3657 KB/s, 9 seconds passed
+... 28%, 36000 KB, 3659 KB/s, 9 seconds passed
+... 28%, 36032 KB, 3662 KB/s, 9 seconds passed
 
 .. parsed-literal::
 
-    ... 28%, 35424 KB, 3456 KB/s, 10 seconds passed
-... 28%, 35456 KB, 3459 KB/s, 10 seconds passed
-... 28%, 35488 KB, 3461 KB/s, 10 seconds passed
-... 28%, 35520 KB, 3462 KB/s, 10 seconds passed
-... 28%, 35552 KB, 3456 KB/s, 10 seconds passed
-... 28%, 35584 KB, 3459 KB/s, 10 seconds passed
-... 28%, 35616 KB, 3461 KB/s, 10 seconds passed
-... 28%, 35648 KB, 3462 KB/s, 10 seconds passed
+    ... 28%, 36064 KB, 3656 KB/s, 9 seconds passed
+... 28%, 36096 KB, 3657 KB/s, 9 seconds passed
+... 28%, 36128 KB, 3659 KB/s, 9 seconds passed
+... 28%, 36160 KB, 3662 KB/s, 9 seconds passed
 
 .. parsed-literal::
 
-    ... 28%, 35680 KB, 3456 KB/s, 10 seconds passed
-... 28%, 35712 KB, 3459 KB/s, 10 seconds passed
-... 28%, 35744 KB, 3462 KB/s, 10 seconds passed
-... 28%, 35776 KB, 3462 KB/s, 10 seconds passed
+    ... 28%, 36192 KB, 3656 KB/s, 9 seconds passed
+... 28%, 36224 KB, 3657 KB/s, 9 seconds passed
+... 28%, 36256 KB, 3659 KB/s, 9 seconds passed
+... 28%, 36288 KB, 3662 KB/s, 9 seconds passed
+... 28%, 36320 KB, 3656 KB/s, 9 seconds passed
+... 28%, 36352 KB, 3658 KB/s, 9 seconds passed
+... 28%, 36384 KB, 3659 KB/s, 9 seconds passed
+... 28%, 36416 KB, 3662 KB/s, 9 seconds passed
 
 .. parsed-literal::
 
-    ... 28%, 35808 KB, 3457 KB/s, 10 seconds passed
-... 28%, 35840 KB, 3459 KB/s, 10 seconds passed
-... 28%, 35872 KB, 3462 KB/s, 10 seconds passed
-... 28%, 35904 KB, 3462 KB/s, 10 seconds passed
-... 28%, 35936 KB, 3457 KB/s, 10 seconds passed
-... 28%, 35968 KB, 3459 KB/s, 10 seconds passed
-... 28%, 36000 KB, 3462 KB/s, 10 seconds passed
+    ... 28%, 36448 KB, 3657 KB/s, 9 seconds passed
+... 28%, 36480 KB, 3657 KB/s, 9 seconds passed
+... 28%, 36512 KB, 3659 KB/s, 9 seconds passed
+... 29%, 36544 KB, 3662 KB/s, 9 seconds passed
 
 .. parsed-literal::
 
-    ... 28%, 36032 KB, 3462 KB/s, 10 seconds passed
-... 28%, 36064 KB, 3457 KB/s, 10 seconds passed
-... 28%, 36096 KB, 3459 KB/s, 10 seconds passed
-... 28%, 36128 KB, 3462 KB/s, 10 seconds passed
-... 28%, 36160 KB, 3462 KB/s, 10 seconds passed
+    ... 29%, 36576 KB, 3656 KB/s, 10 seconds passed
+... 29%, 36608 KB, 3658 KB/s, 10 seconds passed
+... 29%, 36640 KB, 3659 KB/s, 10 seconds passed
+... 29%, 36672 KB, 3662 KB/s, 10 seconds passed
+... 29%, 36704 KB, 3656 KB/s, 10 seconds passed
+... 29%, 36736 KB, 3658 KB/s, 10 seconds passed
+... 29%, 36768 KB, 3660 KB/s, 10 seconds passed
 
 .. parsed-literal::
 
-    ... 28%, 36192 KB, 3457 KB/s, 10 seconds passed
-... 28%, 36224 KB, 3460 KB/s, 10 seconds passed
-... 28%, 36256 KB, 3462 KB/s, 10 seconds passed
-... 28%, 36288 KB, 3463 KB/s, 10 seconds passed
+    ... 29%, 36800 KB, 3663 KB/s, 10 seconds passed
+... 29%, 36832 KB, 3656 KB/s, 10 seconds passed
+... 29%, 36864 KB, 3658 KB/s, 10 seconds passed
+... 29%, 36896 KB, 3660 KB/s, 10 seconds passed
+... 29%, 36928 KB, 3663 KB/s, 10 seconds passed
 
 .. parsed-literal::
 
-    ... 28%, 36320 KB, 3458 KB/s, 10 seconds passed
-... 28%, 36352 KB, 3460 KB/s, 10 seconds passed
-... 28%, 36384 KB, 3462 KB/s, 10 seconds passed
-... 28%, 36416 KB, 3463 KB/s, 10 seconds passed
-... 28%, 36448 KB, 3457 KB/s, 10 seconds passed
-... 28%, 36480 KB, 3460 KB/s, 10 seconds passed
-... 28%, 36512 KB, 3462 KB/s, 10 seconds passed
-... 29%, 36544 KB, 3463 KB/s, 10 seconds passed
+    ... 29%, 36960 KB, 3657 KB/s, 10 seconds passed
+... 29%, 36992 KB, 3658 KB/s, 10 seconds passed
+... 29%, 37024 KB, 3660 KB/s, 10 seconds passed
+... 29%, 37056 KB, 3663 KB/s, 10 seconds passed
+... 29%, 37088 KB, 3657 KB/s, 10 seconds passed
+... 29%, 37120 KB, 3658 KB/s, 10 seconds passed
 
 .. parsed-literal::
 
-    ... 29%, 36576 KB, 3457 KB/s, 10 seconds passed
-... 29%, 36608 KB, 3460 KB/s, 10 seconds passed
-... 29%, 36640 KB, 3463 KB/s, 10 seconds passed
-... 29%, 36672 KB, 3463 KB/s, 10 seconds passed
+    ... 29%, 37152 KB, 3660 KB/s, 10 seconds passed
+... 29%, 37184 KB, 3663 KB/s, 10 seconds passed
+... 29%, 37216 KB, 3657 KB/s, 10 seconds passed
+... 29%, 37248 KB, 3658 KB/s, 10 seconds passed
+... 29%, 37280 KB, 3660 KB/s, 10 seconds passed
+... 29%, 37312 KB, 3663 KB/s, 10 seconds passed
 
 .. parsed-literal::
 
-    ... 29%, 36704 KB, 3458 KB/s, 10 seconds passed
-... 29%, 36736 KB, 3460 KB/s, 10 seconds passed
-... 29%, 36768 KB, 3463 KB/s, 10 seconds passed
-... 29%, 36800 KB, 3463 KB/s, 10 seconds passed
-... 29%, 36832 KB, 3458 KB/s, 10 seconds passed
-... 29%, 36864 KB, 3460 KB/s, 10 seconds passed
-... 29%, 36896 KB, 3463 KB/s, 10 seconds passed
+    ... 29%, 37344 KB, 3657 KB/s, 10 seconds passed
+... 29%, 37376 KB, 3659 KB/s, 10 seconds passed
+... 29%, 37408 KB, 3661 KB/s, 10 seconds passed
+... 29%, 37440 KB, 3663 KB/s, 10 seconds passed
+... 29%, 37472 KB, 3658 KB/s, 10 seconds passed
+... 29%, 37504 KB, 3659 KB/s, 10 seconds passed
 
 .. parsed-literal::
 
-    ... 29%, 36928 KB, 3463 KB/s, 10 seconds passed
-... 29%, 36960 KB, 3458 KB/s, 10 seconds passed
-... 29%, 36992 KB, 3460 KB/s, 10 seconds passed
-... 29%, 37024 KB, 3463 KB/s, 10 seconds passed
-... 29%, 37056 KB, 3463 KB/s, 10 seconds passed
+    ... 29%, 37536 KB, 3661 KB/s, 10 seconds passed
+... 29%, 37568 KB, 3664 KB/s, 10 seconds passed
+... 29%, 37600 KB, 3658 KB/s, 10 seconds passed
+... 29%, 37632 KB, 3659 KB/s, 10 seconds passed
+... 29%, 37664 KB, 3661 KB/s, 10 seconds passed
+... 29%, 37696 KB, 3664 KB/s, 10 seconds passed
 
 .. parsed-literal::
 
-    ... 29%, 37088 KB, 3458 KB/s, 10 seconds passed
-... 29%, 37120 KB, 3460 KB/s, 10 seconds passed
-... 29%, 37152 KB, 3463 KB/s, 10 seconds passed
-... 29%, 37184 KB, 3463 KB/s, 10 seconds passed
+    ... 29%, 37728 KB, 3658 KB/s, 10 seconds passed
+... 29%, 37760 KB, 3659 KB/s, 10 seconds passed
+... 30%, 37792 KB, 3661 KB/s, 10 seconds passed
+... 30%, 37824 KB, 3664 KB/s, 10 seconds passed
+... 30%, 37856 KB, 3658 KB/s, 10 seconds passed
+... 30%, 37888 KB, 3660 KB/s, 10 seconds passed
 
 .. parsed-literal::
 
-    ... 29%, 37216 KB, 3458 KB/s, 10 seconds passed
-... 29%, 37248 KB, 3460 KB/s, 10 seconds passed
-... 29%, 37280 KB, 3463 KB/s, 10 seconds passed
-... 29%, 37312 KB, 3463 KB/s, 10 seconds passed
-... 29%, 37344 KB, 3458 KB/s, 10 seconds passed
-... 29%, 37376 KB, 3461 KB/s, 10 seconds passed
-... 29%, 37408 KB, 3463 KB/s, 10 seconds passed
-... 29%, 37440 KB, 3463 KB/s, 10 seconds passed
+    ... 30%, 37920 KB, 3661 KB/s, 10 seconds passed
+... 30%, 37952 KB, 3664 KB/s, 10 seconds passed
+... 30%, 37984 KB, 3658 KB/s, 10 seconds passed
+... 30%, 38016 KB, 3660 KB/s, 10 seconds passed
+... 30%, 38048 KB, 3661 KB/s, 10 seconds passed
+... 30%, 38080 KB, 3664 KB/s, 10 seconds passed
 
 .. parsed-literal::
 
-    ... 29%, 37472 KB, 3458 KB/s, 10 seconds passed
-... 29%, 37504 KB, 3461 KB/s, 10 seconds passed
-... 29%, 37536 KB, 3463 KB/s, 10 seconds passed
-... 29%, 37568 KB, 3464 KB/s, 10 seconds passed
+    ... 30%, 38112 KB, 3658 KB/s, 10 seconds passed
+... 30%, 38144 KB, 3660 KB/s, 10 seconds passed
+... 30%, 38176 KB, 3661 KB/s, 10 seconds passed
+... 30%, 38208 KB, 3658 KB/s, 10 seconds passed
+... 30%, 38240 KB, 3658 KB/s, 10 seconds passed
+... 30%, 38272 KB, 3660 KB/s, 10 seconds passed
 
 .. parsed-literal::
 
-    ... 29%, 37600 KB, 3458 KB/s, 10 seconds passed
-... 29%, 37632 KB, 3461 KB/s, 10 seconds passed
-... 29%, 37664 KB, 3464 KB/s, 10 seconds passed
-... 29%, 37696 KB, 3464 KB/s, 10 seconds passed
-... 29%, 37728 KB, 3458 KB/s, 10 seconds passed
-... 29%, 37760 KB, 3461 KB/s, 10 seconds passed
-... 30%, 37792 KB, 3464 KB/s, 10 seconds passed
+    ... 30%, 38304 KB, 3661 KB/s, 10 seconds passed
+... 30%, 38336 KB, 3664 KB/s, 10 seconds passed
+... 30%, 38368 KB, 3659 KB/s, 10 seconds passed
+... 30%, 38400 KB, 3660 KB/s, 10 seconds passed
+... 30%, 38432 KB, 3662 KB/s, 10 seconds passed
+... 30%, 38464 KB, 3664 KB/s, 10 seconds passed
 
 .. parsed-literal::
 
-    ... 30%, 37824 KB, 3464 KB/s, 10 seconds passed
-... 30%, 37856 KB, 3459 KB/s, 10 seconds passed
-... 30%, 37888 KB, 3461 KB/s, 10 seconds passed
-... 30%, 37920 KB, 3464 KB/s, 10 seconds passed
-... 30%, 37952 KB, 3464 KB/s, 10 seconds passed
+    ... 30%, 38496 KB, 3659 KB/s, 10 seconds passed
+... 30%, 38528 KB, 3660 KB/s, 10 seconds passed
+... 30%, 38560 KB, 3662 KB/s, 10 seconds passed
+... 30%, 38592 KB, 3664 KB/s, 10 seconds passed
+... 30%, 38624 KB, 3659 KB/s, 10 seconds passed
 
 .. parsed-literal::
 
-    ... 30%, 37984 KB, 3459 KB/s, 10 seconds passed
-... 30%, 38016 KB, 3461 KB/s, 10 seconds passed
-... 30%, 38048 KB, 3463 KB/s, 10 seconds passed
-... 30%, 38080 KB, 3459 KB/s, 11 seconds passed
+    ... 30%, 38656 KB, 3660 KB/s, 10 seconds passed
+... 30%, 38688 KB, 3662 KB/s, 10 seconds passed
+... 30%, 38720 KB, 3665 KB/s, 10 seconds passed
+... 30%, 38752 KB, 3659 KB/s, 10 seconds passed
+... 30%, 38784 KB, 3660 KB/s, 10 seconds passed
+... 30%, 38816 KB, 3662 KB/s, 10 seconds passed
 
 .. parsed-literal::
 
-    ... 30%, 38112 KB, 3459 KB/s, 11 seconds passed
-... 30%, 38144 KB, 3461 KB/s, 11 seconds passed
-... 30%, 38176 KB, 3463 KB/s, 11 seconds passed
-... 30%, 38208 KB, 3460 KB/s, 11 seconds passed
-... 30%, 38240 KB, 3459 KB/s, 11 seconds passed
-... 30%, 38272 KB, 3461 KB/s, 11 seconds passed
-... 30%, 38304 KB, 3464 KB/s, 11 seconds passed
+    ... 30%, 38848 KB, 3660 KB/s, 10 seconds passed
+... 30%, 38880 KB, 3659 KB/s, 10 seconds passed
+... 30%, 38912 KB, 3660 KB/s, 10 seconds passed
+... 30%, 38944 KB, 3662 KB/s, 10 seconds passed
+... 30%, 38976 KB, 3660 KB/s, 10 seconds passed
+... 30%, 39008 KB, 3659 KB/s, 10 seconds passed
 
 .. parsed-literal::
 
-    ... 30%, 38336 KB, 3460 KB/s, 11 seconds passed
-... 30%, 38368 KB, 3459 KB/s, 11 seconds passed
-... 30%, 38400 KB, 3462 KB/s, 11 seconds passed
-... 30%, 38432 KB, 3464 KB/s, 11 seconds passed
-... 30%, 38464 KB, 3460 KB/s, 11 seconds passed
+    ... 30%, 39040 KB, 3661 KB/s, 10 seconds passed
+... 31%, 39072 KB, 3662 KB/s, 10 seconds passed
+... 31%, 39104 KB, 3659 KB/s, 10 seconds passed
+... 31%, 39136 KB, 3659 KB/s, 10 seconds passed
+... 31%, 39168 KB, 3660 KB/s, 10 seconds passed
+... 31%, 39200 KB, 3662 KB/s, 10 seconds passed
 
 .. parsed-literal::
 
-    ... 30%, 38496 KB, 3459 KB/s, 11 seconds passed
-... 30%, 38528 KB, 3462 KB/s, 11 seconds passed
-... 30%, 38560 KB, 3464 KB/s, 11 seconds passed
-... 30%, 38592 KB, 3465 KB/s, 11 seconds passed
-... 30%, 38624 KB, 3459 KB/s, 11 seconds passed
-... 30%, 38656 KB, 3462 KB/s, 11 seconds passed
-... 30%, 38688 KB, 3464 KB/s, 11 seconds passed
+    ... 31%, 39232 KB, 3659 KB/s, 10 seconds passed
+... 31%, 39264 KB, 3659 KB/s, 10 seconds passed
+... 31%, 39296 KB, 3661 KB/s, 10 seconds passed
+... 31%, 39328 KB, 3662 KB/s, 10 seconds passed
+... 31%, 39360 KB, 3660 KB/s, 10 seconds passed
+... 31%, 39392 KB, 3660 KB/s, 10 seconds passed
 
 .. parsed-literal::
 
-    ... 30%, 38720 KB, 3460 KB/s, 11 seconds passed
-... 30%, 38752 KB, 3460 KB/s, 11 seconds passed
-... 30%, 38784 KB, 3462 KB/s, 11 seconds passed
-... 30%, 38816 KB, 3465 KB/s, 11 seconds passed
-... 30%, 38848 KB, 3465 KB/s, 11 seconds passed
+    ... 31%, 39424 KB, 3661 KB/s, 10 seconds passed
+... 31%, 39456 KB, 3662 KB/s, 10 seconds passed
+... 31%, 39488 KB, 3660 KB/s, 10 seconds passed
+... 31%, 39520 KB, 3660 KB/s, 10 seconds passed
+... 31%, 39552 KB, 3661 KB/s, 10 seconds passed
+... 31%, 39584 KB, 3662 KB/s, 10 seconds passed
+... 31%, 39616 KB, 3665 KB/s, 10 seconds passed
 
 .. parsed-literal::
 
-    ... 30%, 38880 KB, 3460 KB/s, 11 seconds passed
-... 30%, 38912 KB, 3462 KB/s, 11 seconds passed
-... 30%, 38944 KB, 3464 KB/s, 11 seconds passed
-... 30%, 38976 KB, 3465 KB/s, 11 seconds passed
+    ... 31%, 39648 KB, 3660 KB/s, 10 seconds passed
+... 31%, 39680 KB, 3661 KB/s, 10 seconds passed
+... 31%, 39712 KB, 3663 KB/s, 10 seconds passed
+... 31%, 39744 KB, 3661 KB/s, 10 seconds passed
+... 31%, 39776 KB, 3660 KB/s, 10 seconds passed
 
 .. parsed-literal::
 
-    ... 30%, 39008 KB, 3460 KB/s, 11 seconds passed
-... 30%, 39040 KB, 3462 KB/s, 11 seconds passed
-... 31%, 39072 KB, 3464 KB/s, 11 seconds passed
-... 31%, 39104 KB, 3461 KB/s, 11 seconds passed
-... 31%, 39136 KB, 3460 KB/s, 11 seconds passed
-... 31%, 39168 KB, 3462 KB/s, 11 seconds passed
-... 31%, 39200 KB, 3464 KB/s, 11 seconds passed
+    ... 31%, 39808 KB, 3661 KB/s, 10 seconds passed
+... 31%, 39840 KB, 3663 KB/s, 10 seconds passed
+... 31%, 39872 KB, 3660 KB/s, 10 seconds passed
+... 31%, 39904 KB, 3660 KB/s, 10 seconds passed
+... 31%, 39936 KB, 3661 KB/s, 10 seconds passed
+... 31%, 39968 KB, 3663 KB/s, 10 seconds passed
 
 .. parsed-literal::
 
-    ... 31%, 39232 KB, 3461 KB/s, 11 seconds passed
-... 31%, 39264 KB, 3460 KB/s, 11 seconds passed
-... 31%, 39296 KB, 3462 KB/s, 11 seconds passed
-... 31%, 39328 KB, 3465 KB/s, 11 seconds passed
-... 31%, 39360 KB, 3461 KB/s, 11 seconds passed
+    ... 31%, 40000 KB, 3660 KB/s, 10 seconds passed
+... 31%, 40032 KB, 3660 KB/s, 10 seconds passed
+... 31%, 40064 KB, 3661 KB/s, 10 seconds passed
+... 31%, 40096 KB, 3663 KB/s, 10 seconds passed
+... 31%, 40128 KB, 3660 KB/s, 10 seconds passed
 
 .. parsed-literal::
 
-    ... 31%, 39392 KB, 3460 KB/s, 11 seconds passed
-... 31%, 39424 KB, 3462 KB/s, 11 seconds passed
-... 31%, 39456 KB, 3465 KB/s, 11 seconds passed
-... 31%, 39488 KB, 3461 KB/s, 11 seconds passed
-... 31%, 39520 KB, 3460 KB/s, 11 seconds passed
-... 31%, 39552 KB, 3462 KB/s, 11 seconds passed
-... 31%, 39584 KB, 3465 KB/s, 11 seconds passed
+    ... 31%, 40160 KB, 3660 KB/s, 10 seconds passed
+... 31%, 40192 KB, 3661 KB/s, 10 seconds passed
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+... 31%, 40256 KB, 3660 KB/s, 10 seconds passed
+... 31%, 40288 KB, 3660 KB/s, 11 seconds passed
+... 32%, 40320 KB, 3662 KB/s, 11 seconds passed
+... 32%, 40352 KB, 3663 KB/s, 11 seconds passed
 
 .. parsed-literal::
 
-    ... 31%, 39616 KB, 3461 KB/s, 11 seconds passed
-... 31%, 39648 KB, 3460 KB/s, 11 seconds passed
-... 31%, 39680 KB, 3462 KB/s, 11 seconds passed
-... 31%, 39712 KB, 3465 KB/s, 11 seconds passed
+    ... 32%, 40384 KB, 3660 KB/s, 11 seconds passed
+... 32%, 40416 KB, 3660 KB/s, 11 seconds passed
+... 32%, 40448 KB, 3662 KB/s, 11 seconds passed
+... 32%, 40480 KB, 3663 KB/s, 11 seconds passed
+... 32%, 40512 KB, 3660 KB/s, 11 seconds passed
 
 .. parsed-literal::
 
-    ... 31%, 39744 KB, 3461 KB/s, 11 seconds passed
-... 31%, 39776 KB, 3460 KB/s, 11 seconds passed
-... 31%, 39808 KB, 3463 KB/s, 11 seconds passed
-... 31%, 39840 KB, 3465 KB/s, 11 seconds passed
-... 31%, 39872 KB, 3461 KB/s, 11 seconds passed
+    ... 32%, 40544 KB, 3660 KB/s, 11 seconds passed
+... 32%, 40576 KB, 3662 KB/s, 11 seconds passed
+... 32%, 40608 KB, 3663 KB/s, 11 seconds passed
+... 32%, 40640 KB, 3660 KB/s, 11 seconds passed
+... 32%, 40672 KB, 3660 KB/s, 11 seconds passed
+... 32%, 40704 KB, 3662 KB/s, 11 seconds passed
+... 32%, 40736 KB, 3663 KB/s, 11 seconds passed
 
 .. parsed-literal::
 
-    ... 31%, 39904 KB, 3460 KB/s, 11 seconds passed
-... 31%, 39936 KB, 3463 KB/s, 11 seconds passed
-... 31%, 39968 KB, 3465 KB/s, 11 seconds passed
-... 31%, 40000 KB, 3460 KB/s, 11 seconds passed
-... 31%, 40032 KB, 3460 KB/s, 11 seconds passed
-... 31%, 40064 KB, 3463 KB/s, 11 seconds passed
-... 31%, 40096 KB, 3464 KB/s, 11 seconds passed
+    ... 32%, 40768 KB, 3660 KB/s, 11 seconds passed
+... 32%, 40800 KB, 3660 KB/s, 11 seconds passed
+... 32%, 40832 KB, 3662 KB/s, 11 seconds passed
+... 32%, 40864 KB, 3664 KB/s, 11 seconds passed
+... 32%, 40896 KB, 3661 KB/s, 11 seconds passed
 
 .. parsed-literal::
 
-    ... 31%, 40128 KB, 3460 KB/s, 11 seconds passed
-... 31%, 40160 KB, 3460 KB/s, 11 seconds passed
-... 31%, 40192 KB, 3463 KB/s, 11 seconds passed
-... 31%, 40224 KB, 3465 KB/s, 11 seconds passed
+    ... 32%, 40928 KB, 3661 KB/s, 11 seconds passed
+... 32%, 40960 KB, 3662 KB/s, 11 seconds passed
+... 32%, 40992 KB, 3664 KB/s, 11 seconds passed
+... 32%, 41024 KB, 3661 KB/s, 11 seconds passed
+... 32%, 41056 KB, 3661 KB/s, 11 seconds passed
+... 32%, 41088 KB, 3662 KB/s, 11 seconds passed
+... 32%, 41120 KB, 3664 KB/s, 11 seconds passed
 
 .. parsed-literal::
 
-    ... 31%, 40256 KB, 3460 KB/s, 11 seconds passed
-... 31%, 40288 KB, 3460 KB/s, 11 seconds passed
-... 32%, 40320 KB, 3463 KB/s, 11 seconds passed
-... 32%, 40352 KB, 3465 KB/s, 11 seconds passed
-... 32%, 40384 KB, 3462 KB/s, 11 seconds passed
-... 32%, 40416 KB, 3461 KB/s, 11 seconds passed
-... 32%, 40448 KB, 3463 KB/s, 11 seconds passed
-... 32%, 40480 KB, 3465 KB/s, 11 seconds passed
+    ... 32%, 41152 KB, 3661 KB/s, 11 seconds passed
+... 32%, 41184 KB, 3661 KB/s, 11 seconds passed
+... 32%, 41216 KB, 3662 KB/s, 11 seconds passed
+... 32%, 41248 KB, 3664 KB/s, 11 seconds passed
+... 32%, 41280 KB, 3661 KB/s, 11 seconds passed
 
 .. parsed-literal::
 
-    ... 32%, 40512 KB, 3462 KB/s, 11 seconds passed
-... 32%, 40544 KB, 3461 KB/s, 11 seconds passed
-... 32%, 40576 KB, 3463 KB/s, 11 seconds passed
-... 32%, 40608 KB, 3465 KB/s, 11 seconds passed
+    ... 32%, 41312 KB, 3661 KB/s, 11 seconds passed
+... 32%, 41344 KB, 3662 KB/s, 11 seconds passed
+... 32%, 41376 KB, 3664 KB/s, 11 seconds passed
+... 32%, 41408 KB, 3661 KB/s, 11 seconds passed
+... 32%, 41440 KB, 3661 KB/s, 11 seconds passed
+... 32%, 41472 KB, 3662 KB/s, 11 seconds passed
+... 32%, 41504 KB, 3664 KB/s, 11 seconds passed
 
 .. parsed-literal::
 
-    ... 32%, 40640 KB, 3459 KB/s, 11 seconds passed
-... 32%, 40672 KB, 3461 KB/s, 11 seconds passed
-... 32%, 40704 KB, 3463 KB/s, 11 seconds passed
-... 32%, 40736 KB, 3465 KB/s, 11 seconds passed
-... 32%, 40768 KB, 3460 KB/s, 11 seconds passed
+    ... 32%, 41536 KB, 3661 KB/s, 11 seconds passed
+... 33%, 41568 KB, 3661 KB/s, 11 seconds passed
+... 33%, 41600 KB, 3663 KB/s, 11 seconds passed
+... 33%, 41632 KB, 3664 KB/s, 11 seconds passed
+... 33%, 41664 KB, 3661 KB/s, 11 seconds passed
 
 .. parsed-literal::
 
-    ... 32%, 40800 KB, 3461 KB/s, 11 seconds passed
-... 32%, 40832 KB, 3463 KB/s, 11 seconds passed
-... 32%, 40864 KB, 3465 KB/s, 11 seconds passed
-... 32%, 40896 KB, 3460 KB/s, 11 seconds passed
-... 32%, 40928 KB, 3461 KB/s, 11 seconds passed
-... 32%, 40960 KB, 3463 KB/s, 11 seconds passed
-... 32%, 40992 KB, 3465 KB/s, 11 seconds passed
+    ... 33%, 41696 KB, 3661 KB/s, 11 seconds passed
+... 33%, 41728 KB, 3663 KB/s, 11 seconds passed
+... 33%, 41760 KB, 3665 KB/s, 11 seconds passed
+... 33%, 41792 KB, 3661 KB/s, 11 seconds passed
+... 33%, 41824 KB, 3661 KB/s, 11 seconds passed
+... 33%, 41856 KB, 3663 KB/s, 11 seconds passed
+... 33%, 41888 KB, 3665 KB/s, 11 seconds passed
 
 .. parsed-literal::
 
-    ... 32%, 41024 KB, 3460 KB/s, 11 seconds passed
-... 32%, 41056 KB, 3461 KB/s, 11 seconds passed
-... 32%, 41088 KB, 3464 KB/s, 11 seconds passed
-... 32%, 41120 KB, 3465 KB/s, 11 seconds passed
+    ... 33%, 41920 KB, 3661 KB/s, 11 seconds passed
+... 33%, 41952 KB, 3661 KB/s, 11 seconds passed
+... 33%, 41984 KB, 3663 KB/s, 11 seconds passed
+... 33%, 42016 KB, 3665 KB/s, 11 seconds passed
 
 .. parsed-literal::
 
-    ... 32%, 41152 KB, 3461 KB/s, 11 seconds passed
-... 32%, 41184 KB, 3461 KB/s, 11 seconds passed
-... 32%, 41216 KB, 3464 KB/s, 11 seconds passed
-... 32%, 41248 KB, 3466 KB/s, 11 seconds passed
-... 32%, 41280 KB, 3461 KB/s, 11 seconds passed
-... 32%, 41312 KB, 3461 KB/s, 11 seconds passed
-... 32%, 41344 KB, 3464 KB/s, 11 seconds passed
-... 32%, 41376 KB, 3466 KB/s, 11 seconds passed
+    ... 33%, 42048 KB, 3661 KB/s, 11 seconds passed
+... 33%, 42080 KB, 3661 KB/s, 11 seconds passed
+... 33%, 42112 KB, 3663 KB/s, 11 seconds passed
+... 33%, 42144 KB, 3665 KB/s, 11 seconds passed
+... 33%, 42176 KB, 3661 KB/s, 11 seconds passed
+... 33%, 42208 KB, 3661 KB/s, 11 seconds passed
+... 33%, 42240 KB, 3663 KB/s, 11 seconds passed
+... 33%, 42272 KB, 3665 KB/s, 11 seconds passed
 
 .. parsed-literal::
 
-    ... 32%, 41408 KB, 3461 KB/s, 11 seconds passed
-... 32%, 41440 KB, 3462 KB/s, 11 seconds passed
-... 32%, 41472 KB, 3464 KB/s, 11 seconds passed
-... 32%, 41504 KB, 3466 KB/s, 11 seconds passed
+    ... 33%, 42304 KB, 3661 KB/s, 11 seconds passed
+... 33%, 42336 KB, 3661 KB/s, 11 seconds passed
+... 33%, 42368 KB, 3663 KB/s, 11 seconds passed
+... 33%, 42400 KB, 3665 KB/s, 11 seconds passed
 
 .. parsed-literal::
 
-    ... 32%, 41536 KB, 3461 KB/s, 11 seconds passed
-... 33%, 41568 KB, 3462 KB/s, 12 seconds passed
-... 33%, 41600 KB, 3464 KB/s, 12 seconds passed
-... 33%, 41632 KB, 3466 KB/s, 12 seconds passed
-... 33%, 41664 KB, 3461 KB/s, 12 seconds passed
+    ... 33%, 42432 KB, 3662 KB/s, 11 seconds passed
+... 33%, 42464 KB, 3663 KB/s, 11 seconds passed
+... 33%, 42496 KB, 3664 KB/s, 11 seconds passed
+... 33%, 42528 KB, 3665 KB/s, 11 seconds passed
+... 33%, 42560 KB, 3662 KB/s, 11 seconds passed
+... 33%, 42592 KB, 3663 KB/s, 11 seconds passed
+... 33%, 42624 KB, 3664 KB/s, 11 seconds passed
+... 33%, 42656 KB, 3665 KB/s, 11 seconds passed
 
 .. parsed-literal::
 
-    ... 33%, 41696 KB, 3462 KB/s, 12 seconds passed
-... 33%, 41728 KB, 3464 KB/s, 12 seconds passed
-... 33%, 41760 KB, 3466 KB/s, 12 seconds passed
-... 33%, 41792 KB, 3461 KB/s, 12 seconds passed
-... 33%, 41824 KB, 3462 KB/s, 12 seconds passed
-... 33%, 41856 KB, 3464 KB/s, 12 seconds passed
-... 33%, 41888 KB, 3466 KB/s, 12 seconds passed
+    ... 33%, 42688 KB, 3662 KB/s, 11 seconds passed
+... 33%, 42720 KB, 3663 KB/s, 11 seconds passed
+... 33%, 42752 KB, 3663 KB/s, 11 seconds passed
+... 33%, 42784 KB, 3662 KB/s, 11 seconds passed
 
 .. parsed-literal::
 
-    ... 33%, 41920 KB, 3461 KB/s, 12 seconds passed
-... 33%, 41952 KB, 3462 KB/s, 12 seconds passed
-... 33%, 41984 KB, 3464 KB/s, 12 seconds passed
-... 33%, 42016 KB, 3466 KB/s, 12 seconds passed
+    ... 33%, 42816 KB, 3662 KB/s, 11 seconds passed
+... 34%, 42848 KB, 3663 KB/s, 11 seconds passed
+... 34%, 42880 KB, 3664 KB/s, 11 seconds passed
+... 34%, 42912 KB, 3666 KB/s, 11 seconds passed
+... 34%, 42944 KB, 3662 KB/s, 11 seconds passed
+... 34%, 42976 KB, 3663 KB/s, 11 seconds passed
+... 34%, 43008 KB, 3664 KB/s, 11 seconds passed
+... 34%, 43040 KB, 3666 KB/s, 11 seconds passed
 
 .. parsed-literal::
 
-    ... 33%, 42048 KB, 3461 KB/s, 12 seconds passed
-... 33%, 42080 KB, 3462 KB/s, 12 seconds passed
-... 33%, 42112 KB, 3464 KB/s, 12 seconds passed
-... 33%, 42144 KB, 3466 KB/s, 12 seconds passed
-... 33%, 42176 KB, 3461 KB/s, 12 seconds passed
-... 33%, 42208 KB, 3462 KB/s, 12 seconds passed
-... 33%, 42240 KB, 3465 KB/s, 12 seconds passed
-... 33%, 42272 KB, 3466 KB/s, 12 seconds passed
+    ... 34%, 43072 KB, 3662 KB/s, 11 seconds passed
+... 34%, 43104 KB, 3662 KB/s, 11 seconds passed
+... 34%, 43136 KB, 3664 KB/s, 11 seconds passed
+... 34%, 43168 KB, 3662 KB/s, 11 seconds passed
 
 .. parsed-literal::
 
-    ... 33%, 42304 KB, 3461 KB/s, 12 seconds passed
-... 33%, 42336 KB, 3462 KB/s, 12 seconds passed
-... 33%, 42368 KB, 3465 KB/s, 12 seconds passed
-... 33%, 42400 KB, 3466 KB/s, 12 seconds passed
+    ... 34%, 43200 KB, 3662 KB/s, 11 seconds passed
+... 34%, 43232 KB, 3662 KB/s, 11 seconds passed
+... 34%, 43264 KB, 3664 KB/s, 11 seconds passed
+... 34%, 43296 KB, 3666 KB/s, 11 seconds passed
+... 34%, 43328 KB, 3662 KB/s, 11 seconds passed
+... 34%, 43360 KB, 3663 KB/s, 11 seconds passed
+... 34%, 43392 KB, 3664 KB/s, 11 seconds passed
 
 .. parsed-literal::
 
-    ... 33%, 42432 KB, 3462 KB/s, 12 seconds passed
-... 33%, 42464 KB, 3463 KB/s, 12 seconds passed
-... 33%, 42496 KB, 3465 KB/s, 12 seconds passed
-... 33%, 42528 KB, 3467 KB/s, 12 seconds passed
-... 33%, 42560 KB, 3461 KB/s, 12 seconds passed
+    ... 34%, 43424 KB, 3666 KB/s, 11 seconds passed
+... 34%, 43456 KB, 3663 KB/s, 11 seconds passed
+... 34%, 43488 KB, 3663 KB/s, 11 seconds passed
+... 34%, 43520 KB, 3665 KB/s, 11 seconds passed
+... 34%, 43552 KB, 3666 KB/s, 11 seconds passed
 
 .. parsed-literal::
 
-    ... 33%, 42592 KB, 3462 KB/s, 12 seconds passed
-... 33%, 42624 KB, 3465 KB/s, 12 seconds passed
-... 33%, 42656 KB, 3462 KB/s, 12 seconds passed
-... 33%, 42688 KB, 3462 KB/s, 12 seconds passed
-... 33%, 42720 KB, 3463 KB/s, 12 seconds passed
-... 33%, 42752 KB, 3465 KB/s, 12 seconds passed
+    ... 34%, 43584 KB, 3663 KB/s, 11 seconds passed
+... 34%, 43616 KB, 3663 KB/s, 11 seconds passed
+... 34%, 43648 KB, 3664 KB/s, 11 seconds passed
+... 34%, 43680 KB, 3662 KB/s, 11 seconds passed
+... 34%, 43712 KB, 3662 KB/s, 11 seconds passed
+... 34%, 43744 KB, 3663 KB/s, 11 seconds passed
 
 .. parsed-literal::
 
-    ... 33%, 42784 KB, 3463 KB/s, 12 seconds passed
-... 33%, 42816 KB, 3462 KB/s, 12 seconds passed
-... 34%, 42848 KB, 3463 KB/s, 12 seconds passed
-... 34%, 42880 KB, 3465 KB/s, 12 seconds passed
-... 34%, 42912 KB, 3463 KB/s, 12 seconds passed
+    ... 34%, 43776 KB, 3664 KB/s, 11 seconds passed
+... 34%, 43808 KB, 3662 KB/s, 11 seconds passed
+... 34%, 43840 KB, 3663 KB/s, 11 seconds passed
+... 34%, 43872 KB, 3663 KB/s, 11 seconds passed
+... 34%, 43904 KB, 3664 KB/s, 11 seconds passed
 
 .. parsed-literal::
 
-    ... 34%, 42944 KB, 3462 KB/s, 12 seconds passed
-... 34%, 42976 KB, 3463 KB/s, 12 seconds passed
-... 34%, 43008 KB, 3465 KB/s, 12 seconds passed
-... 34%, 43040 KB, 3463 KB/s, 12 seconds passed
-... 34%, 43072 KB, 3462 KB/s, 12 seconds passed
-... 34%, 43104 KB, 3463 KB/s, 12 seconds passed
-... 34%, 43136 KB, 3465 KB/s, 12 seconds passed
+    ... 34%, 43936 KB, 3662 KB/s, 11 seconds passed
+... 34%, 43968 KB, 3663 KB/s, 12 seconds passed
+... 34%, 44000 KB, 3663 KB/s, 12 seconds passed
+... 34%, 44032 KB, 3665 KB/s, 12 seconds passed
+... 34%, 44064 KB, 3663 KB/s, 12 seconds passed
+... 35%, 44096 KB, 3663 KB/s, 12 seconds passed
+... 35%, 44128 KB, 3663 KB/s, 12 seconds passed
 
 .. parsed-literal::
 
-    ... 34%, 43168 KB, 3462 KB/s, 12 seconds passed
-... 34%, 43200 KB, 3462 KB/s, 12 seconds passed
-... 34%, 43232 KB, 3463 KB/s, 12 seconds passed
-... 34%, 43264 KB, 3465 KB/s, 12 seconds passed
+    ... 35%, 44160 KB, 3665 KB/s, 12 seconds passed
+... 35%, 44192 KB, 3663 KB/s, 12 seconds passed
+... 35%, 44224 KB, 3663 KB/s, 12 seconds passed
+... 35%, 44256 KB, 3663 KB/s, 12 seconds passed
+... 35%, 44288 KB, 3665 KB/s, 12 seconds passed
+... 35%, 44320 KB, 3663 KB/s, 12 seconds passed
 
 .. parsed-literal::
 
-    ... 34%, 43296 KB, 3462 KB/s, 12 seconds passed
-... 34%, 43328 KB, 3462 KB/s, 12 seconds passed
-... 34%, 43360 KB, 3463 KB/s, 12 seconds passed
-... 34%, 43392 KB, 3465 KB/s, 12 seconds passed
-... 34%, 43424 KB, 3462 KB/s, 12 seconds passed
-... 34%, 43456 KB, 3462 KB/s, 12 seconds passed
+    ... 35%, 44352 KB, 3663 KB/s, 12 seconds passed
+... 35%, 44384 KB, 3664 KB/s, 12 seconds passed
+... 35%, 44416 KB, 3665 KB/s, 12 seconds passed
+... 35%, 44448 KB, 3663 KB/s, 12 seconds passed
+... 35%, 44480 KB, 3663 KB/s, 12 seconds passed
+... 35%, 44512 KB, 3664 KB/s, 12 seconds passed
 
 .. parsed-literal::
 
-    ... 34%, 43488 KB, 3463 KB/s, 12 seconds passed
-... 34%, 43520 KB, 3465 KB/s, 12 seconds passed
-... 34%, 43552 KB, 3461 KB/s, 12 seconds passed
-... 34%, 43584 KB, 3462 KB/s, 12 seconds passed
-... 34%, 43616 KB, 3463 KB/s, 12 seconds passed
-... 34%, 43648 KB, 3465 KB/s, 12 seconds passed
+    ... 35%, 44544 KB, 3665 KB/s, 12 seconds passed
+... 35%, 44576 KB, 3663 KB/s, 12 seconds passed
+... 35%, 44608 KB, 3663 KB/s, 12 seconds passed
+... 35%, 44640 KB, 3664 KB/s, 12 seconds passed
+... 35%, 44672 KB, 3665 KB/s, 12 seconds passed
 
 .. parsed-literal::
 
-    ... 34%, 43680 KB, 3461 KB/s, 12 seconds passed
-... 34%, 43712 KB, 3462 KB/s, 12 seconds passed
-... 34%, 43744 KB, 3463 KB/s, 12 seconds passed
-... 34%, 43776 KB, 3465 KB/s, 12 seconds passed
-... 34%, 43808 KB, 3467 KB/s, 12 seconds passed
+    ... 35%, 44704 KB, 3663 KB/s, 12 seconds passed
+... 35%, 44736 KB, 3664 KB/s, 12 seconds passed
+... 35%, 44768 KB, 3664 KB/s, 12 seconds passed
+... 35%, 44800 KB, 3666 KB/s, 12 seconds passed
+... 35%, 44832 KB, 3663 KB/s, 12 seconds passed
+... 35%, 44864 KB, 3664 KB/s, 12 seconds passed
+... 35%, 44896 KB, 3664 KB/s, 12 seconds passed
 
 .. parsed-literal::
 
-    ... 34%, 43840 KB, 3463 KB/s, 12 seconds passed
-... 34%, 43872 KB, 3464 KB/s, 12 seconds passed
-... 34%, 43904 KB, 3466 KB/s, 12 seconds passed
-... 34%, 43936 KB, 3467 KB/s, 12 seconds passed
-... 34%, 43968 KB, 3463 KB/s, 12 seconds passed
-... 34%, 44000 KB, 3464 KB/s, 12 seconds passed
-... 34%, 44032 KB, 3466 KB/s, 12 seconds passed
+    ... 35%, 44928 KB, 3665 KB/s, 12 seconds passed
+... 35%, 44960 KB, 3663 KB/s, 12 seconds passed
+... 35%, 44992 KB, 3664 KB/s, 12 seconds passed
+... 35%, 45024 KB, 3664 KB/s, 12 seconds passed
+... 35%, 45056 KB, 3666 KB/s, 12 seconds passed
 
 .. parsed-literal::
 
-    ... 34%, 44064 KB, 3464 KB/s, 12 seconds passed
-... 35%, 44096 KB, 3463 KB/s, 12 seconds passed
-... 35%, 44128 KB, 3464 KB/s, 12 seconds passed
-... 35%, 44160 KB, 3466 KB/s, 12 seconds passed
-... 35%, 44192 KB, 3464 KB/s, 12 seconds passed
+    ... 35%, 45088 KB, 3663 KB/s, 12 seconds passed
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+... 35%, 45184 KB, 3666 KB/s, 12 seconds passed
+... 35%, 45216 KB, 3663 KB/s, 12 seconds passed
+... 35%, 45248 KB, 3664 KB/s, 12 seconds passed
 
 .. parsed-literal::
 
-    ... 35%, 44224 KB, 3463 KB/s, 12 seconds passed
-... 35%, 44256 KB, 3464 KB/s, 12 seconds passed
-... 35%, 44288 KB, 3466 KB/s, 12 seconds passed
-... 35%, 44320 KB, 3468 KB/s, 12 seconds passed
-... 35%, 44352 KB, 3463 KB/s, 12 seconds passed
+    ... 35%, 45280 KB, 3664 KB/s, 12 seconds passed
+... 35%, 45312 KB, 3666 KB/s, 12 seconds passed
+... 36%, 45344 KB, 3663 KB/s, 12 seconds passed
+... 36%, 45376 KB, 3664 KB/s, 12 seconds passed
+... 36%, 45408 KB, 3664 KB/s, 12 seconds passed
+... 36%, 45440 KB, 3666 KB/s, 12 seconds passed
 
 .. parsed-literal::
 
-    ... 35%, 44384 KB, 3464 KB/s, 12 seconds passed
-... 35%, 44416 KB, 3466 KB/s, 12 seconds passed
-... 35%, 44448 KB, 3468 KB/s, 12 seconds passed
-... 35%, 44480 KB, 3463 KB/s, 12 seconds passed
-... 35%, 44512 KB, 3464 KB/s, 12 seconds passed
-... 35%, 44544 KB, 3466 KB/s, 12 seconds passed
+    ... 36%, 45472 KB, 3663 KB/s, 12 seconds passed
+... 36%, 45504 KB, 3664 KB/s, 12 seconds passed
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+... 36%, 45568 KB, 3666 KB/s, 12 seconds passed
+... 36%, 45600 KB, 3663 KB/s, 12 seconds passed
+... 36%, 45632 KB, 3664 KB/s, 12 seconds passed
 
 .. parsed-literal::
 
-    ... 35%, 44576 KB, 3462 KB/s, 12 seconds passed
-... 35%, 44608 KB, 3463 KB/s, 12 seconds passed
-... 35%, 44640 KB, 3464 KB/s, 12 seconds passed
-... 35%, 44672 KB, 3466 KB/s, 12 seconds passed
-... 35%, 44704 KB, 3462 KB/s, 12 seconds passed
+    ... 36%, 45664 KB, 3664 KB/s, 12 seconds passed
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+... 36%, 45760 KB, 3664 KB/s, 12 seconds passed
+... 36%, 45792 KB, 3665 KB/s, 12 seconds passed
+... 36%, 45824 KB, 3666 KB/s, 12 seconds passed
 
 .. parsed-literal::
 
-    ... 35%, 44736 KB, 3463 KB/s, 12 seconds passed
-... 35%, 44768 KB, 3464 KB/s, 12 seconds passed
-... 35%, 44800 KB, 3466 KB/s, 12 seconds passed
-... 35%, 44832 KB, 3462 KB/s, 12 seconds passed
-... 35%, 44864 KB, 3464 KB/s, 12 seconds passed
-... 35%, 44896 KB, 3464 KB/s, 12 seconds passed
-... 35%, 44928 KB, 3466 KB/s, 12 seconds passed
+    ... 36%, 45856 KB, 3664 KB/s, 12 seconds passed
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+... 36%, 45952 KB, 3666 KB/s, 12 seconds passed
+... 36%, 45984 KB, 3664 KB/s, 12 seconds passed
+... 36%, 46016 KB, 3665 KB/s, 12 seconds passed
 
 .. parsed-literal::
 
-    ... 35%, 44960 KB, 3462 KB/s, 12 seconds passed
-... 35%, 44992 KB, 3464 KB/s, 12 seconds passed
-... 35%, 45024 KB, 3465 KB/s, 12 seconds passed
-... 35%, 45056 KB, 3466 KB/s, 12 seconds passed
-... 35%, 45088 KB, 3464 KB/s, 13 seconds passed
+    ... 36%, 46048 KB, 3665 KB/s, 12 seconds passed
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+... 36%, 46144 KB, 3665 KB/s, 12 seconds passed
+... 36%, 46176 KB, 3665 KB/s, 12 seconds passed
+... 36%, 46208 KB, 3666 KB/s, 12 seconds passed
 
 .. parsed-literal::
 
-    ... 35%, 45120 KB, 3464 KB/s, 13 seconds passed
-... 35%, 45152 KB, 3465 KB/s, 13 seconds passed
-... 35%, 45184 KB, 3466 KB/s, 13 seconds passed
-... 35%, 45216 KB, 3462 KB/s, 13 seconds passed
-... 35%, 45248 KB, 3463 KB/s, 13 seconds passed
+    ... 36%, 46240 KB, 3663 KB/s, 12 seconds passed
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+... 36%, 46336 KB, 3667 KB/s, 12 seconds passed
+... 36%, 46368 KB, 3663 KB/s, 12 seconds passed
+... 36%, 46400 KB, 3664 KB/s, 12 seconds passed
 
 .. parsed-literal::
 
-    ... 35%, 45280 KB, 3465 KB/s, 13 seconds passed
-... 35%, 45312 KB, 3466 KB/s, 13 seconds passed
-... 36%, 45344 KB, 3463 KB/s, 13 seconds passed
-... 36%, 45376 KB, 3464 KB/s, 13 seconds passed
-... 36%, 45408 KB, 3465 KB/s, 13 seconds passed
-... 36%, 45440 KB, 3467 KB/s, 13 seconds passed
+    ... 36%, 46432 KB, 3665 KB/s, 12 seconds passed
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+... 36%, 46528 KB, 3665 KB/s, 12 seconds passed
+... 36%, 46560 KB, 3666 KB/s, 12 seconds passed
+... 36%, 46592 KB, 3667 KB/s, 12 seconds passed
 
 .. parsed-literal::
 
-    ... 36%, 45472 KB, 3463 KB/s, 13 seconds passed
-... 36%, 45504 KB, 3464 KB/s, 13 seconds passed
-... 36%, 45536 KB, 3465 KB/s, 13 seconds passed
-... 36%, 45568 KB, 3467 KB/s, 13 seconds passed
-... 36%, 45600 KB, 3463 KB/s, 13 seconds passed
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+... 37%, 46720 KB, 3667 KB/s, 12 seconds passed
+... 37%, 46752 KB, 3663 KB/s, 12 seconds passed
+... 37%, 46784 KB, 3665 KB/s, 12 seconds passed
 
 .. parsed-literal::
 
-    ... 36%, 45632 KB, 3464 KB/s, 13 seconds passed
-... 36%, 45664 KB, 3465 KB/s, 13 seconds passed
-... 36%, 45696 KB, 3467 KB/s, 13 seconds passed
-... 36%, 45728 KB, 3465 KB/s, 13 seconds passed
-... 36%, 45760 KB, 3465 KB/s, 13 seconds passed
-... 36%, 45792 KB, 3465 KB/s, 13 seconds passed
-... 36%, 45824 KB, 3467 KB/s, 13 seconds passed
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+... 37%, 46944 KB, 3666 KB/s, 12 seconds passed
+... 37%, 46976 KB, 3667 KB/s, 12 seconds passed
 
 .. parsed-literal::
 
-    ... 36%, 45856 KB, 3465 KB/s, 13 seconds passed
-... 36%, 45888 KB, 3464 KB/s, 13 seconds passed
-... 36%, 45920 KB, 3465 KB/s, 13 seconds passed
-... 36%, 45952 KB, 3467 KB/s, 13 seconds passed
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+... 37%, 47104 KB, 3664 KB/s, 12 seconds passed
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 .. parsed-literal::
 
-    ... 36%, 45984 KB, 3463 KB/s, 13 seconds passed
-... 36%, 46016 KB, 3464 KB/s, 13 seconds passed
-... 36%, 46048 KB, 3465 KB/s, 13 seconds passed
-... 36%, 46080 KB, 3467 KB/s, 13 seconds passed
-... 36%, 46112 KB, 3463 KB/s, 13 seconds passed
-... 36%, 46144 KB, 3464 KB/s, 13 seconds passed
+    ... 37%, 47200 KB, 3666 KB/s, 12 seconds passed
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+... 37%, 47296 KB, 3665 KB/s, 12 seconds passed
+... 37%, 47328 KB, 3666 KB/s, 12 seconds passed
+... 37%, 47360 KB, 3668 KB/s, 12 seconds passed
 
 .. parsed-literal::
 
-    ... 36%, 46176 KB, 3465 KB/s, 13 seconds passed
-... 36%, 46208 KB, 3467 KB/s, 13 seconds passed
-... 36%, 46240 KB, 3463 KB/s, 13 seconds passed
-... 36%, 46272 KB, 3464 KB/s, 13 seconds passed
-... 36%, 46304 KB, 3465 KB/s, 13 seconds passed
-... 36%, 46336 KB, 3467 KB/s, 13 seconds passed
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+... 37%, 47488 KB, 3668 KB/s, 12 seconds passed
+... 37%, 47520 KB, 3664 KB/s, 12 seconds passed
+... 37%, 47552 KB, 3666 KB/s, 12 seconds passed
 
 .. parsed-literal::
 
-    ... 36%, 46368 KB, 3463 KB/s, 13 seconds passed
-... 36%, 46400 KB, 3464 KB/s, 13 seconds passed
-... 36%, 46432 KB, 3466 KB/s, 13 seconds passed
-... 36%, 46464 KB, 3467 KB/s, 13 seconds passed
-... 36%, 46496 KB, 3463 KB/s, 13 seconds passed
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+... 37%, 47680 KB, 3666 KB/s, 13 seconds passed
+... 37%, 47712 KB, 3666 KB/s, 13 seconds passed
+... 37%, 47744 KB, 3668 KB/s, 13 seconds passed
 
 .. parsed-literal::
 
-    ... 36%, 46528 KB, 3464 KB/s, 13 seconds passed
-... 36%, 46560 KB, 3466 KB/s, 13 seconds passed
-... 36%, 46592 KB, 3467 KB/s, 13 seconds passed
-... 37%, 46624 KB, 3463 KB/s, 13 seconds passed
-... 37%, 46656 KB, 3464 KB/s, 13 seconds passed
-... 37%, 46688 KB, 3466 KB/s, 13 seconds passed
-... 37%, 46720 KB, 3467 KB/s, 13 seconds passed
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+... 37%, 47840 KB, 3666 KB/s, 13 seconds passed
+... 38%, 47872 KB, 3668 KB/s, 13 seconds passed
+... 38%, 47904 KB, 3664 KB/s, 13 seconds passed
 
 .. parsed-literal::
 
-    ... 37%, 46752 KB, 3463 KB/s, 13 seconds passed
-... 37%, 46784 KB, 3465 KB/s, 13 seconds passed
-... 37%, 46816 KB, 3466 KB/s, 13 seconds passed
-... 37%, 46848 KB, 3467 KB/s, 13 seconds passed
+    ... 38%, 47936 KB, 3666 KB/s, 13 seconds passed
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+... 38%, 48064 KB, 3666 KB/s, 13 seconds passed
+... 38%, 48096 KB, 3666 KB/s, 13 seconds passed
+... 38%, 48128 KB, 3668 KB/s, 13 seconds passed
 
 .. parsed-literal::
 
-    ... 37%, 46880 KB, 3464 KB/s, 13 seconds passed
-... 37%, 46912 KB, 3465 KB/s, 13 seconds passed
-... 37%, 46944 KB, 3466 KB/s, 13 seconds passed
-... 37%, 46976 KB, 3468 KB/s, 13 seconds passed
-... 37%, 47008 KB, 3464 KB/s, 13 seconds passed
-... 37%, 47040 KB, 3465 KB/s, 13 seconds passed
-... 37%, 47072 KB, 3466 KB/s, 13 seconds passed
+    ... 38%, 48160 KB, 3664 KB/s, 13 seconds passed
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+... 38%, 48224 KB, 3667 KB/s, 13 seconds passed
+... 38%, 48256 KB, 3668 KB/s, 13 seconds passed
+... 38%, 48288 KB, 3665 KB/s, 13 seconds passed
 
 .. parsed-literal::
 
-    ... 37%, 47104 KB, 3468 KB/s, 13 seconds passed
-... 37%, 47136 KB, 3464 KB/s, 13 seconds passed
-... 37%, 47168 KB, 3465 KB/s, 13 seconds passed
-... 37%, 47200 KB, 3466 KB/s, 13 seconds passed
-... 37%, 47232 KB, 3468 KB/s, 13 seconds passed
+    ... 38%, 48320 KB, 3666 KB/s, 13 seconds passed
+... 38%, 48352 KB, 3667 KB/s, 13 seconds passed
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+... 38%, 48448 KB, 3666 KB/s, 13 seconds passed
+... 38%, 48480 KB, 3667 KB/s, 13 seconds passed
+... 38%, 48512 KB, 3668 KB/s, 13 seconds passed
 
 .. parsed-literal::
 
-    ... 37%, 47264 KB, 3464 KB/s, 13 seconds passed
-... 37%, 47296 KB, 3465 KB/s, 13 seconds passed
-... 37%, 47328 KB, 3467 KB/s, 13 seconds passed
-... 37%, 47360 KB, 3468 KB/s, 13 seconds passed
-... 37%, 47392 KB, 3464 KB/s, 13 seconds passed
+    ... 38%, 48544 KB, 3665 KB/s, 13 seconds passed
+... 38%, 48576 KB, 3666 KB/s, 13 seconds passed
+... 38%, 48608 KB, 3667 KB/s, 13 seconds passed
+... 38%, 48640 KB, 3668 KB/s, 13 seconds passed
+... 38%, 48672 KB, 3665 KB/s, 13 seconds passed
 
 .. parsed-literal::
 
-    ... 37%, 47424 KB, 3465 KB/s, 13 seconds passed
-... 37%, 47456 KB, 3466 KB/s, 13 seconds passed
-... 37%, 47488 KB, 3469 KB/s, 13 seconds passed
-... 37%, 47520 KB, 3464 KB/s, 13 seconds passed
-... 37%, 47552 KB, 3465 KB/s, 13 seconds passed
-... 37%, 47584 KB, 3467 KB/s, 13 seconds passed
-... 37%, 47616 KB, 3468 KB/s, 13 seconds passed
+    ... 38%, 48704 KB, 3667 KB/s, 13 seconds passed
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+... 38%, 48768 KB, 3665 KB/s, 13 seconds passed
+... 38%, 48800 KB, 3665 KB/s, 13 seconds passed
+... 38%, 48832 KB, 3667 KB/s, 13 seconds passed
+... 38%, 48864 KB, 3667 KB/s, 13 seconds passed
+... 38%, 48896 KB, 3669 KB/s, 13 seconds passed
 
 .. parsed-literal::
 
-    ... 37%, 47648 KB, 3464 KB/s, 13 seconds passed
-... 37%, 47680 KB, 3465 KB/s, 13 seconds passed
-... 37%, 47712 KB, 3467 KB/s, 13 seconds passed
-... 37%, 47744 KB, 3469 KB/s, 13 seconds passed
+    ... 38%, 48928 KB, 3665 KB/s, 13 seconds passed
+... 38%, 48960 KB, 3666 KB/s, 13 seconds passed
+... 38%, 48992 KB, 3667 KB/s, 13 seconds passed
+... 38%, 49024 KB, 3664 KB/s, 13 seconds passed
 
 .. parsed-literal::
 
-    ... 37%, 47776 KB, 3465 KB/s, 13 seconds passed
-... 37%, 47808 KB, 3465 KB/s, 13 seconds passed
-... 37%, 47840 KB, 3467 KB/s, 13 seconds passed
-... 38%, 47872 KB, 3468 KB/s, 13 seconds passed
-... 38%, 47904 KB, 3464 KB/s, 13 seconds passed
-... 38%, 47936 KB, 3466 KB/s, 13 seconds passed
-... 38%, 47968 KB, 3467 KB/s, 13 seconds passed
+    ... 38%, 49056 KB, 3665 KB/s, 13 seconds passed
+... 38%, 49088 KB, 3666 KB/s, 13 seconds passed
+... 38%, 49120 KB, 3667 KB/s, 13 seconds passed
+... 39%, 49152 KB, 3664 KB/s, 13 seconds passed
+... 39%, 49184 KB, 3665 KB/s, 13 seconds passed
+... 39%, 49216 KB, 3666 KB/s, 13 seconds passed
+... 39%, 49248 KB, 3667 KB/s, 13 seconds passed
 
 .. parsed-literal::
 
-    ... 38%, 48000 KB, 3469 KB/s, 13 seconds passed
-... 38%, 48032 KB, 3465 KB/s, 13 seconds passed
-... 38%, 48064 KB, 3466 KB/s, 13 seconds passed
-... 38%, 48096 KB, 3467 KB/s, 13 seconds passed
-... 38%, 48128 KB, 3469 KB/s, 13 seconds passed
+    ... 39%, 49280 KB, 3664 KB/s, 13 seconds passed
+... 39%, 49312 KB, 3665 KB/s, 13 seconds passed
+... 39%, 49344 KB, 3666 KB/s, 13 seconds passed
+... 39%, 49376 KB, 3668 KB/s, 13 seconds passed
+... 39%, 49408 KB, 3665 KB/s, 13 seconds passed
 
 .. parsed-literal::
 
-    ... 38%, 48160 KB, 3464 KB/s, 13 seconds passed
-... 38%, 48192 KB, 3466 KB/s, 13 seconds passed
-... 38%, 48224 KB, 3467 KB/s, 13 seconds passed
-... 38%, 48256 KB, 3469 KB/s, 13 seconds passed
-... 38%, 48288 KB, 3464 KB/s, 13 seconds passed
+    ... 39%, 49440 KB, 3665 KB/s, 13 seconds passed
+... 39%, 49472 KB, 3666 KB/s, 13 seconds passed
+... 39%, 49504 KB, 3668 KB/s, 13 seconds passed
+... 39%, 49536 KB, 3665 KB/s, 13 seconds passed
+... 39%, 49568 KB, 3665 KB/s, 13 seconds passed
+... 39%, 49600 KB, 3666 KB/s, 13 seconds passed
+... 39%, 49632 KB, 3668 KB/s, 13 seconds passed
 
 .. parsed-literal::
 
-    ... 38%, 48320 KB, 3466 KB/s, 13 seconds passed
-... 38%, 48352 KB, 3467 KB/s, 13 seconds passed
-... 38%, 48384 KB, 3469 KB/s, 13 seconds passed
-... 38%, 48416 KB, 3464 KB/s, 13 seconds passed
-... 38%, 48448 KB, 3466 KB/s, 13 seconds passed
-... 38%, 48480 KB, 3467 KB/s, 13 seconds passed
-... 38%, 48512 KB, 3469 KB/s, 13 seconds passed
+    ... 39%, 49664 KB, 3665 KB/s, 13 seconds passed
+... 39%, 49696 KB, 3666 KB/s, 13 seconds passed
+... 39%, 49728 KB, 3666 KB/s, 13 seconds passed
+... 39%, 49760 KB, 3668 KB/s, 13 seconds passed
+... 39%, 49792 KB, 3665 KB/s, 13 seconds passed
 
 .. parsed-literal::
 
-    ... 38%, 48544 KB, 3465 KB/s, 14 seconds passed
-... 38%, 48576 KB, 3466 KB/s, 14 seconds passed
-... 38%, 48608 KB, 3467 KB/s, 14 seconds passed
-... 38%, 48640 KB, 3469 KB/s, 14 seconds passed
+    ... 39%, 49824 KB, 3666 KB/s, 13 seconds passed
+... 39%, 49856 KB, 3666 KB/s, 13 seconds passed
+... 39%, 49888 KB, 3668 KB/s, 13 seconds passed
+... 39%, 49920 KB, 3665 KB/s, 13 seconds passed
+... 39%, 49952 KB, 3666 KB/s, 13 seconds passed
+... 39%, 49984 KB, 3666 KB/s, 13 seconds passed
+... 39%, 50016 KB, 3668 KB/s, 13 seconds passed
 
 .. parsed-literal::
 
-    ... 38%, 48672 KB, 3465 KB/s, 14 seconds passed
-... 38%, 48704 KB, 3466 KB/s, 14 seconds passed
-... 38%, 48736 KB, 3467 KB/s, 14 seconds passed
-... 38%, 48768 KB, 3469 KB/s, 14 seconds passed
-... 38%, 48800 KB, 3465 KB/s, 14 seconds passed
-... 38%, 48832 KB, 3466 KB/s, 14 seconds passed
-... 38%, 48864 KB, 3467 KB/s, 14 seconds passed
+    ... 39%, 50048 KB, 3665 KB/s, 13 seconds passed
+... 39%, 50080 KB, 3666 KB/s, 13 seconds passed
+... 39%, 50112 KB, 3666 KB/s, 13 seconds passed
+... 39%, 50144 KB, 3668 KB/s, 13 seconds passed
+... 39%, 50176 KB, 3665 KB/s, 13 seconds passed
 
 .. parsed-literal::
 
-    ... 38%, 48896 KB, 3469 KB/s, 14 seconds passed
-... 38%, 48928 KB, 3465 KB/s, 14 seconds passed
-... 38%, 48960 KB, 3466 KB/s, 14 seconds passed
-... 38%, 48992 KB, 3468 KB/s, 14 seconds passed
+    ... 39%, 50208 KB, 3666 KB/s, 13 seconds passed
+... 39%, 50240 KB, 3666 KB/s, 13 seconds passed
+... 39%, 50272 KB, 3668 KB/s, 13 seconds passed
+... 39%, 50304 KB, 3665 KB/s, 13 seconds passed
+... 39%, 50336 KB, 3666 KB/s, 13 seconds passed
+... 39%, 50368 KB, 3666 KB/s, 13 seconds passed
+... 40%, 50400 KB, 3668 KB/s, 13 seconds passed
 
 .. parsed-literal::
 
-    ... 38%, 49024 KB, 3465 KB/s, 14 seconds passed
-... 38%, 49056 KB, 3465 KB/s, 14 seconds passed
-... 38%, 49088 KB, 3466 KB/s, 14 seconds passed
-... 38%, 49120 KB, 3468 KB/s, 14 seconds passed
-... 39%, 49152 KB, 3469 KB/s, 14 seconds passed
-... 39%, 49184 KB, 3465 KB/s, 14 seconds passed
+    ... 40%, 50432 KB, 3665 KB/s, 13 seconds passed
+... 40%, 50464 KB, 3666 KB/s, 13 seconds passed
+... 40%, 50496 KB, 3666 KB/s, 13 seconds passed
+... 40%, 50528 KB, 3668 KB/s, 13 seconds passed
 
 .. parsed-literal::
 
-    ... 39%, 49216 KB, 3466 KB/s, 14 seconds passed
-... 39%, 49248 KB, 3468 KB/s, 14 seconds passed
-... 39%, 49280 KB, 3465 KB/s, 14 seconds passed
-... 39%, 49312 KB, 3465 KB/s, 14 seconds passed
-... 39%, 49344 KB, 3466 KB/s, 14 seconds passed
-... 39%, 49376 KB, 3468 KB/s, 14 seconds passed
+    ... 40%, 50560 KB, 3665 KB/s, 13 seconds passed
+... 40%, 50592 KB, 3666 KB/s, 13 seconds passed
+... 40%, 50624 KB, 3666 KB/s, 13 seconds passed
+... 40%, 50656 KB, 3668 KB/s, 13 seconds passed
+... 40%, 50688 KB, 3665 KB/s, 13 seconds passed
+... 40%, 50720 KB, 3666 KB/s, 13 seconds passed
+... 40%, 50752 KB, 3667 KB/s, 13 seconds passed
+... 40%, 50784 KB, 3668 KB/s, 13 seconds passed
 
 .. parsed-literal::
 
-    ... 39%, 49408 KB, 3467 KB/s, 14 seconds passed
-... 39%, 49440 KB, 3465 KB/s, 14 seconds passed
-... 39%, 49472 KB, 3467 KB/s, 14 seconds passed
-... 39%, 49504 KB, 3468 KB/s, 14 seconds passed
-... 39%, 49536 KB, 3467 KB/s, 14 seconds passed
+    ... 40%, 50816 KB, 3666 KB/s, 13 seconds passed
+... 40%, 50848 KB, 3666 KB/s, 13 seconds passed
+... 40%, 50880 KB, 3667 KB/s, 13 seconds passed
+... 40%, 50912 KB, 3668 KB/s, 13 seconds passed
 
 .. parsed-literal::
 
-    ... 39%, 49568 KB, 3465 KB/s, 14 seconds passed
-... 39%, 49600 KB, 3467 KB/s, 14 seconds passed
-... 39%, 49632 KB, 3468 KB/s, 14 seconds passed
-... 39%, 49664 KB, 3464 KB/s, 14 seconds passed
-... 39%, 49696 KB, 3465 KB/s, 14 seconds passed
-... 39%, 49728 KB, 3467 KB/s, 14 seconds passed
-... 39%, 49760 KB, 3468 KB/s, 14 seconds passed
+    ... 40%, 50944 KB, 3666 KB/s, 13 seconds passed
+... 40%, 50976 KB, 3666 KB/s, 13 seconds passed
+... 40%, 51008 KB, 3667 KB/s, 13 seconds passed
+... 40%, 51040 KB, 3668 KB/s, 13 seconds passed
+... 40%, 51072 KB, 3666 KB/s, 13 seconds passed
+... 40%, 51104 KB, 3666 KB/s, 13 seconds passed
+... 40%, 51136 KB, 3667 KB/s, 13 seconds passed
+... 40%, 51168 KB, 3668 KB/s, 13 seconds passed
 
 .. parsed-literal::
 
-    ... 39%, 49792 KB, 3464 KB/s, 14 seconds passed
-... 39%, 49824 KB, 3465 KB/s, 14 seconds passed
-... 39%, 49856 KB, 3467 KB/s, 14 seconds passed
-... 39%, 49888 KB, 3468 KB/s, 14 seconds passed
+    ... 40%, 51200 KB, 3665 KB/s, 13 seconds passed
+... 40%, 51232 KB, 3666 KB/s, 13 seconds passed
+... 40%, 51264 KB, 3667 KB/s, 13 seconds passed
+... 40%, 51296 KB, 3668 KB/s, 13 seconds passed
 
 .. parsed-literal::
 
-    ... 39%, 49920 KB, 3464 KB/s, 14 seconds passed
-... 39%, 49952 KB, 3465 KB/s, 14 seconds passed
-... 39%, 49984 KB, 3467 KB/s, 14 seconds passed
-... 39%, 50016 KB, 3468 KB/s, 14 seconds passed
-... 39%, 50048 KB, 3466 KB/s, 14 seconds passed
-... 39%, 50080 KB, 3466 KB/s, 14 seconds passed
+    ... 40%, 51328 KB, 3665 KB/s, 14 seconds passed
+... 40%, 51360 KB, 3666 KB/s, 14 seconds passed
+... 40%, 51392 KB, 3667 KB/s, 14 seconds passed
+... 40%, 51424 KB, 3669 KB/s, 14 seconds passed
+... 40%, 51456 KB, 3665 KB/s, 14 seconds passed
+... 40%, 51488 KB, 3667 KB/s, 14 seconds passed
+... 40%, 51520 KB, 3667 KB/s, 14 seconds passed
 
 .. parsed-literal::
 
-    ... 39%, 50112 KB, 3467 KB/s, 14 seconds passed
-... 39%, 50144 KB, 3468 KB/s, 14 seconds passed
-... 39%, 50176 KB, 3466 KB/s, 14 seconds passed
-... 39%, 50208 KB, 3466 KB/s, 14 seconds passed
-... 39%, 50240 KB, 3467 KB/s, 14 seconds passed
-... 39%, 50272 KB, 3468 KB/s, 14 seconds passed
+    ... 40%, 51552 KB, 3669 KB/s, 14 seconds passed
+... 40%, 51584 KB, 3666 KB/s, 14 seconds passed
+... 40%, 51616 KB, 3667 KB/s, 14 seconds passed
+... 41%, 51648 KB, 3667 KB/s, 14 seconds passed
+... 41%, 51680 KB, 3669 KB/s, 14 seconds passed
 
 .. parsed-literal::
 
-    ... 39%, 50304 KB, 3467 KB/s, 14 seconds passed
-... 39%, 50336 KB, 3466 KB/s, 14 seconds passed
-... 39%, 50368 KB, 3467 KB/s, 14 seconds passed
-... 40%, 50400 KB, 3469 KB/s, 14 seconds passed
+    ... 41%, 51712 KB, 3666 KB/s, 14 seconds passed
+... 41%, 51744 KB, 3666 KB/s, 14 seconds passed
+... 41%, 51776 KB, 3667 KB/s, 14 seconds passed
+... 41%, 51808 KB, 3665 KB/s, 14 seconds passed
+... 41%, 51840 KB, 3665 KB/s, 14 seconds passed
+... 41%, 51872 KB, 3666 KB/s, 14 seconds passed
+... 41%, 51904 KB, 3667 KB/s, 14 seconds passed
 
 .. parsed-literal::
 
-    ... 40%, 50432 KB, 3464 KB/s, 14 seconds passed
-... 40%, 50464 KB, 3466 KB/s, 14 seconds passed
-... 40%, 50496 KB, 3467 KB/s, 14 seconds passed
-... 40%, 50528 KB, 3468 KB/s, 14 seconds passed
-... 40%, 50560 KB, 3465 KB/s, 14 seconds passed
-... 40%, 50592 KB, 3466 KB/s, 14 seconds passed
-... 40%, 50624 KB, 3467 KB/s, 14 seconds passed
-... 40%, 50656 KB, 3469 KB/s, 14 seconds passed
+    ... 41%, 51936 KB, 3665 KB/s, 14 seconds passed
+... 41%, 51968 KB, 3666 KB/s, 14 seconds passed
+... 41%, 52000 KB, 3666 KB/s, 14 seconds passed
+... 41%, 52032 KB, 3667 KB/s, 14 seconds passed
 
 .. parsed-literal::
 
-    ... 40%, 50688 KB, 3465 KB/s, 14 seconds passed
-... 40%, 50720 KB, 3466 KB/s, 14 seconds passed
-... 40%, 50752 KB, 3467 KB/s, 14 seconds passed
-... 40%, 50784 KB, 3469 KB/s, 14 seconds passed
+    ... 41%, 52064 KB, 3665 KB/s, 14 seconds passed
+... 41%, 52096 KB, 3666 KB/s, 14 seconds passed
+... 41%, 52128 KB, 3666 KB/s, 14 seconds passed
+... 41%, 52160 KB, 3667 KB/s, 14 seconds passed
+... 41%, 52192 KB, 3665 KB/s, 14 seconds passed
+... 41%, 52224 KB, 3666 KB/s, 14 seconds passed
+... 41%, 52256 KB, 3667 KB/s, 14 seconds passed
+... 41%, 52288 KB, 3668 KB/s, 14 seconds passed
 
 .. parsed-literal::
 
-    ... 40%, 50816 KB, 3465 KB/s, 14 seconds passed
-... 40%, 50848 KB, 3466 KB/s, 14 seconds passed
-... 40%, 50880 KB, 3467 KB/s, 14 seconds passed
-... 40%, 50912 KB, 3469 KB/s, 14 seconds passed
-... 40%, 50944 KB, 3467 KB/s, 14 seconds passed
-... 40%, 50976 KB, 3466 KB/s, 14 seconds passed
+    ... 41%, 52320 KB, 3665 KB/s, 14 seconds passed
+... 41%, 52352 KB, 3666 KB/s, 14 seconds passed
+... 41%, 52384 KB, 3667 KB/s, 14 seconds passed
+... 41%, 52416 KB, 3668 KB/s, 14 seconds passed
+... 41%, 52448 KB, 3667 KB/s, 14 seconds passed
 
 .. parsed-literal::
 
-    ... 40%, 51008 KB, 3467 KB/s, 14 seconds passed
-... 40%, 51040 KB, 3469 KB/s, 14 seconds passed
-... 40%, 51072 KB, 3467 KB/s, 14 seconds passed
-... 40%, 51104 KB, 3466 KB/s, 14 seconds passed
-... 40%, 51136 KB, 3467 KB/s, 14 seconds passed
-... 40%, 51168 KB, 3469 KB/s, 14 seconds passed
+    ... 41%, 52480 KB, 3666 KB/s, 14 seconds passed
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+... 41%, 52576 KB, 3665 KB/s, 14 seconds passed
+... 41%, 52608 KB, 3666 KB/s, 14 seconds passed
+... 41%, 52640 KB, 3667 KB/s, 14 seconds passed
 
 .. parsed-literal::
 
-    ... 40%, 51200 KB, 3465 KB/s, 14 seconds passed
-... 40%, 51232 KB, 3466 KB/s, 14 seconds passed
-... 40%, 51264 KB, 3467 KB/s, 14 seconds passed
-... 40%, 51296 KB, 3469 KB/s, 14 seconds passed
+    ... 41%, 52672 KB, 3668 KB/s, 14 seconds passed
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+... 41%, 52736 KB, 3666 KB/s, 14 seconds passed
+... 41%, 52768 KB, 3667 KB/s, 14 seconds passed
+... 41%, 52800 KB, 3668 KB/s, 14 seconds passed
 
 .. parsed-literal::
 
-    ... 40%, 51328 KB, 3465 KB/s, 14 seconds passed
-... 40%, 51360 KB, 3467 KB/s, 14 seconds passed
-... 40%, 51392 KB, 3468 KB/s, 14 seconds passed
-... 40%, 51424 KB, 3469 KB/s, 14 seconds passed
-... 40%, 51456 KB, 3465 KB/s, 14 seconds passed
-... 40%, 51488 KB, 3467 KB/s, 14 seconds passed
-... 40%, 51520 KB, 3468 KB/s, 14 seconds passed
-... 40%, 51552 KB, 3469 KB/s, 14 seconds passed
+    ... 41%, 52832 KB, 3665 KB/s, 14 seconds passed
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+... 41%, 52896 KB, 3667 KB/s, 14 seconds passed
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+... 42%, 52960 KB, 3665 KB/s, 14 seconds passed
+... 42%, 52992 KB, 3667 KB/s, 14 seconds passed
+... 42%, 53024 KB, 3667 KB/s, 14 seconds passed
 
 .. parsed-literal::
 
-    ... 40%, 51584 KB, 3466 KB/s, 14 seconds passed
-... 40%, 51616 KB, 3467 KB/s, 14 seconds passed
-... 41%, 51648 KB, 3468 KB/s, 14 seconds passed
-... 41%, 51680 KB, 3469 KB/s, 14 seconds passed
+    ... 42%, 53056 KB, 3668 KB/s, 14 seconds passed
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+... 42%, 53120 KB, 3667 KB/s, 14 seconds passed
+... 42%, 53152 KB, 3668 KB/s, 14 seconds passed
+... 42%, 53184 KB, 3668 KB/s, 14 seconds passed
 
 .. parsed-literal::
 
-    ... 41%, 51712 KB, 3465 KB/s, 14 seconds passed
-... 41%, 51744 KB, 3467 KB/s, 14 seconds passed
-... 41%, 51776 KB, 3468 KB/s, 14 seconds passed
-... 41%, 51808 KB, 3469 KB/s, 14 seconds passed
-... 41%, 51840 KB, 3465 KB/s, 14 seconds passed
-... 41%, 51872 KB, 3467 KB/s, 14 seconds passed
+    ... 42%, 53216 KB, 3666 KB/s, 14 seconds passed
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+... 42%, 53344 KB, 3666 KB/s, 14 seconds passed
+... 42%, 53376 KB, 3667 KB/s, 14 seconds passed
+... 42%, 53408 KB, 3667 KB/s, 14 seconds passed
 
 .. parsed-literal::
 
-    ... 41%, 51904 KB, 3468 KB/s, 14 seconds passed
-... 41%, 51936 KB, 3469 KB/s, 14 seconds passed
-... 41%, 51968 KB, 3465 KB/s, 14 seconds passed
-... 41%, 52000 KB, 3467 KB/s, 14 seconds passed
-... 41%, 52032 KB, 3468 KB/s, 15 seconds passed
-... 41%, 52064 KB, 3470 KB/s, 15 seconds passed
+    ... 42%, 53440 KB, 3668 KB/s, 14 seconds passed
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+... 42%, 53504 KB, 3667 KB/s, 14 seconds passed
+... 42%, 53536 KB, 3667 KB/s, 14 seconds passed
+... 42%, 53568 KB, 3668 KB/s, 14 seconds passed
 
 .. parsed-literal::
 
-    ... 41%, 52096 KB, 3465 KB/s, 15 seconds passed
-... 41%, 52128 KB, 3467 KB/s, 15 seconds passed
-... 41%, 52160 KB, 3468 KB/s, 15 seconds passed
-... 41%, 52192 KB, 3470 KB/s, 15 seconds passed
+    ... 42%, 53600 KB, 3665 KB/s, 14 seconds passed
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+... 42%, 53696 KB, 3668 KB/s, 14 seconds passed
+... 42%, 53728 KB, 3666 KB/s, 14 seconds passed
+... 42%, 53760 KB, 3667 KB/s, 14 seconds passed
 
 .. parsed-literal::
 
-    ... 41%, 52224 KB, 3466 KB/s, 15 seconds passed
-... 41%, 52256 KB, 3467 KB/s, 15 seconds passed
-... 41%, 52288 KB, 3468 KB/s, 15 seconds passed
-... 41%, 52320 KB, 3467 KB/s, 15 seconds passed
-... 41%, 52352 KB, 3465 KB/s, 15 seconds passed
-... 41%, 52384 KB, 3467 KB/s, 15 seconds passed
-... 41%, 52416 KB, 3468 KB/s, 15 seconds passed
+    ... 42%, 53792 KB, 3667 KB/s, 14 seconds passed
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+... 42%, 53920 KB, 3667 KB/s, 14 seconds passed
+... 42%, 53952 KB, 3669 KB/s, 14 seconds passed
 
 .. parsed-literal::
 
-    ... 41%, 52448 KB, 3467 KB/s, 15 seconds passed
-... 41%, 52480 KB, 3466 KB/s, 15 seconds passed
-... 41%, 52512 KB, 3467 KB/s, 15 seconds passed
-... 41%, 52544 KB, 3468 KB/s, 15 seconds passed
-... 41%, 52576 KB, 3470 KB/s, 15 seconds passed
+    ... 42%, 53984 KB, 3666 KB/s, 14 seconds passed
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+... 42%, 54080 KB, 3668 KB/s, 14 seconds passed
+... 42%, 54112 KB, 3666 KB/s, 14 seconds passed
+... 42%, 54144 KB, 3667 KB/s, 14 seconds passed
 
 .. parsed-literal::
 
-    ... 41%, 52608 KB, 3466 KB/s, 15 seconds passed
-... 41%, 52640 KB, 3467 KB/s, 15 seconds passed
-... 41%, 52672 KB, 3468 KB/s, 15 seconds passed
-... 41%, 52704 KB, 3470 KB/s, 15 seconds passed
-... 41%, 52736 KB, 3466 KB/s, 15 seconds passed
-... 41%, 52768 KB, 3468 KB/s, 15 seconds passed
-... 41%, 52800 KB, 3468 KB/s, 15 seconds passed
+    ... 43%, 54176 KB, 3668 KB/s, 14 seconds passed
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+... 43%, 54272 KB, 3667 KB/s, 14 seconds passed
+... 43%, 54304 KB, 3668 KB/s, 14 seconds passed
+... 43%, 54336 KB, 3668 KB/s, 14 seconds passed
 
 .. parsed-literal::
 
-    ... 41%, 52832 KB, 3470 KB/s, 15 seconds passed
-... 41%, 52864 KB, 3466 KB/s, 15 seconds passed
-... 41%, 52896 KB, 3468 KB/s, 15 seconds passed
-... 42%, 52928 KB, 3469 KB/s, 15 seconds passed
-... 42%, 52960 KB, 3470 KB/s, 15 seconds passed
+    ... 43%, 54368 KB, 3666 KB/s, 14 seconds passed
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+... 43%, 54464 KB, 3669 KB/s, 14 seconds passed
+... 43%, 54496 KB, 3666 KB/s, 14 seconds passed
+... 43%, 54528 KB, 3668 KB/s, 14 seconds passed
 
 .. parsed-literal::
 
-    ... 42%, 52992 KB, 3466 KB/s, 15 seconds passed
-... 42%, 53024 KB, 3468 KB/s, 15 seconds passed
-... 42%, 53056 KB, 3469 KB/s, 15 seconds passed
-... 42%, 53088 KB, 3470 KB/s, 15 seconds passed
-... 42%, 53120 KB, 3466 KB/s, 15 seconds passed
+    ... 43%, 54560 KB, 3668 KB/s, 14 seconds passed
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+... 43%, 54624 KB, 3666 KB/s, 14 seconds passed
+... 43%, 54656 KB, 3668 KB/s, 14 seconds passed
+... 43%, 54688 KB, 3668 KB/s, 14 seconds passed
+... 43%, 54720 KB, 3668 KB/s, 14 seconds passed
 
 .. parsed-literal::
 
-    ... 42%, 53152 KB, 3468 KB/s, 15 seconds passed
-... 42%, 53184 KB, 3469 KB/s, 15 seconds passed
-... 42%, 53216 KB, 3470 KB/s, 15 seconds passed
-... 42%, 53248 KB, 3466 KB/s, 15 seconds passed
-... 42%, 53280 KB, 3468 KB/s, 15 seconds passed
-... 42%, 53312 KB, 3469 KB/s, 15 seconds passed
-... 42%, 53344 KB, 3470 KB/s, 15 seconds passed
+    ... 43%, 54752 KB, 3666 KB/s, 14 seconds passed
+... 43%, 54784 KB, 3668 KB/s, 14 seconds passed
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+... 43%, 54848 KB, 3669 KB/s, 14 seconds passed
+... 43%, 54880 KB, 3666 KB/s, 14 seconds passed
+... 43%, 54912 KB, 3668 KB/s, 14 seconds passed
 
 .. parsed-literal::
 
-    ... 42%, 53376 KB, 3466 KB/s, 15 seconds passed
-... 42%, 53408 KB, 3468 KB/s, 15 seconds passed
-... 42%, 53440 KB, 3469 KB/s, 15 seconds passed
-... 42%, 53472 KB, 3471 KB/s, 15 seconds passed
+    ... 43%, 54944 KB, 3668 KB/s, 14 seconds passed
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+... 43%, 55008 KB, 3667 KB/s, 15 seconds passed
+... 43%, 55040 KB, 3668 KB/s, 15 seconds passed
+... 43%, 55072 KB, 3668 KB/s, 15 seconds passed
+... 43%, 55104 KB, 3669 KB/s, 15 seconds passed
 
 .. parsed-literal::
 
-    ... 42%, 53504 KB, 3466 KB/s, 15 seconds passed
-... 42%, 53536 KB, 3468 KB/s, 15 seconds passed
-... 42%, 53568 KB, 3469 KB/s, 15 seconds passed
-... 42%, 53600 KB, 3471 KB/s, 15 seconds passed
-... 42%, 53632 KB, 3466 KB/s, 15 seconds passed
-... 42%, 53664 KB, 3468 KB/s, 15 seconds passed
-... 42%, 53696 KB, 3469 KB/s, 15 seconds passed
+    ... 43%, 55136 KB, 3666 KB/s, 15 seconds passed
+... 43%, 55168 KB, 3668 KB/s, 15 seconds passed
+... 43%, 55200 KB, 3668 KB/s, 15 seconds passed
+... 43%, 55232 KB, 3669 KB/s, 15 seconds passed
+... 43%, 55264 KB, 3666 KB/s, 15 seconds passed
+... 43%, 55296 KB, 3668 KB/s, 15 seconds passed
 
 .. parsed-literal::
 
-    ... 42%, 53728 KB, 3471 KB/s, 15 seconds passed
-... 42%, 53760 KB, 3466 KB/s, 15 seconds passed
-... 42%, 53792 KB, 3468 KB/s, 15 seconds passed
-... 42%, 53824 KB, 3469 KB/s, 15 seconds passed
-... 42%, 53856 KB, 3471 KB/s, 15 seconds passed
+    ... 43%, 55328 KB, 3668 KB/s, 15 seconds passed
+... 43%, 55360 KB, 3669 KB/s, 15 seconds passed
+... 43%, 55392 KB, 3666 KB/s, 15 seconds passed
+... 44%, 55424 KB, 3668 KB/s, 15 seconds passed
+... 44%, 55456 KB, 3668 KB/s, 15 seconds passed
 
 .. parsed-literal::
 
-    ... 42%, 53888 KB, 3466 KB/s, 15 seconds passed
-... 42%, 53920 KB, 3468 KB/s, 15 seconds passed
-... 42%, 53952 KB, 3469 KB/s, 15 seconds passed
-... 42%, 53984 KB, 3471 KB/s, 15 seconds passed
+    ... 44%, 55488 KB, 3667 KB/s, 15 seconds passed
+... 44%, 55520 KB, 3667 KB/s, 15 seconds passed
+... 44%, 55552 KB, 3668 KB/s, 15 seconds passed
+... 44%, 55584 KB, 3669 KB/s, 15 seconds passed
+... 44%, 55616 KB, 3669 KB/s, 15 seconds passed
+... 44%, 55648 KB, 3667 KB/s, 15 seconds passed
+... 44%, 55680 KB, 3668 KB/s, 15 seconds passed
 
 .. parsed-literal::
 
-    ... 42%, 54016 KB, 3466 KB/s, 15 seconds passed
-... 42%, 54048 KB, 3468 KB/s, 15 seconds passed
-... 42%, 54080 KB, 3469 KB/s, 15 seconds passed
-... 42%, 54112 KB, 3471 KB/s, 15 seconds passed
-... 42%, 54144 KB, 3466 KB/s, 15 seconds passed
-... 43%, 54176 KB, 3468 KB/s, 15 seconds passed
-... 43%, 54208 KB, 3470 KB/s, 15 seconds passed
-... 43%, 54240 KB, 3471 KB/s, 15 seconds passed
+    ... 44%, 55712 KB, 3669 KB/s, 15 seconds passed
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+... 44%, 55776 KB, 3667 KB/s, 15 seconds passed
+... 44%, 55808 KB, 3669 KB/s, 15 seconds passed
+... 44%, 55840 KB, 3669 KB/s, 15 seconds passed
+... 44%, 55872 KB, 3669 KB/s, 15 seconds passed
 
 .. parsed-literal::
 
-    ... 43%, 54272 KB, 3466 KB/s, 15 seconds passed
-... 43%, 54304 KB, 3468 KB/s, 15 seconds passed
-... 43%, 54336 KB, 3469 KB/s, 15 seconds passed
+    ... 44%, 55904 KB, 3667 KB/s, 15 seconds passed
+... 44%, 55936 KB, 3669 KB/s, 15 seconds passed
+... 44%, 55968 KB, 3669 KB/s, 15 seconds passed
+... 44%, 56000 KB, 3667 KB/s, 15 seconds passed
+... 44%, 56032 KB, 3667 KB/s, 15 seconds passed
+... 44%, 56064 KB, 3669 KB/s, 15 seconds passed
 
 .. parsed-literal::
 
-    ... 43%, 54368 KB, 3465 KB/s, 15 seconds passed
-... 43%, 54400 KB, 3466 KB/s, 15 seconds passed
-... 43%, 54432 KB, 3468 KB/s, 15 seconds passed
-... 43%, 54464 KB, 3469 KB/s, 15 seconds passed
-... 43%, 54496 KB, 3465 KB/s, 15 seconds passed
-... 43%, 54528 KB, 3466 KB/s, 15 seconds passed
-... 43%, 54560 KB, 3468 KB/s, 15 seconds passed
-... 43%, 54592 KB, 3469 KB/s, 15 seconds passed
+    ... 44%, 56096 KB, 3669 KB/s, 15 seconds passed
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+... 44%, 56192 KB, 3669 KB/s, 15 seconds passed
+... 44%, 56224 KB, 3669 KB/s, 15 seconds passed
+... 44%, 56256 KB, 3670 KB/s, 15 seconds passed
 
 .. parsed-literal::
 
-    ... 43%, 54624 KB, 3468 KB/s, 15 seconds passed
-... 43%, 54656 KB, 3467 KB/s, 15 seconds passed
-... 43%, 54688 KB, 3468 KB/s, 15 seconds passed
-... 43%, 54720 KB, 3469 KB/s, 15 seconds passed
+    ... 44%, 56288 KB, 3667 KB/s, 15 seconds passed
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+... 44%, 56384 KB, 3670 KB/s, 15 seconds passed
+... 44%, 56416 KB, 3667 KB/s, 15 seconds passed
+... 44%, 56448 KB, 3669 KB/s, 15 seconds passed
 
 .. parsed-literal::
 
-    ... 43%, 54752 KB, 3466 KB/s, 15 seconds passed
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-... 43%, 54880 KB, 3466 KB/s, 15 seconds passed
+    ... 44%, 56480 KB, 3669 KB/s, 15 seconds passed
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+... 44%, 56576 KB, 3669 KB/s, 15 seconds passed
+... 44%, 56608 KB, 3669 KB/s, 15 seconds passed
+... 44%, 56640 KB, 3670 KB/s, 15 seconds passed
 
 .. parsed-literal::
 
-    ... 43%, 54912 KB, 3467 KB/s, 15 seconds passed
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-... 43%, 54976 KB, 3470 KB/s, 15 seconds passed
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-... 43%, 55104 KB, 3470 KB/s, 15 seconds passed
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+... 45%, 56736 KB, 3669 KB/s, 15 seconds passed
+... 45%, 56768 KB, 3670 KB/s, 15 seconds passed
+... 45%, 56800 KB, 3667 KB/s, 15 seconds passed
 
 .. parsed-literal::
 
-    ... 43%, 55136 KB, 3468 KB/s, 15 seconds passed
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-... 43%, 55200 KB, 3469 KB/s, 15 seconds passed
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+... 45%, 56960 KB, 3668 KB/s, 15 seconds passed
+... 45%, 56992 KB, 3669 KB/s, 15 seconds passed
 
 .. parsed-literal::
 
-    ... 43%, 55296 KB, 3467 KB/s, 15 seconds passed
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+... 45%, 57152 KB, 3667 KB/s, 15 seconds passed
 
 .. parsed-literal::
 
-    ... 44%, 55520 KB, 3468 KB/s, 16 seconds passed
-... 44%, 55552 KB, 3467 KB/s, 16 seconds passed
-... 44%, 55584 KB, 3469 KB/s, 16 seconds passed
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+... 45%, 57344 KB, 3668 KB/s, 15 seconds passed
+... 45%, 57376 KB, 3670 KB/s, 15 seconds passed
 
 .. parsed-literal::
 
-    ... 44%, 55648 KB, 3466 KB/s, 16 seconds passed
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+... 45%, 57504 KB, 3670 KB/s, 15 seconds passed
+... 45%, 57536 KB, 3667 KB/s, 15 seconds passed
 
 .. parsed-literal::
 
-    ... 44%, 55840 KB, 3469 KB/s, 16 seconds passed
-... 44%, 55872 KB, 3470 KB/s, 16 seconds passed
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-... 44%, 56000 KB, 3470 KB/s, 16 seconds passed
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+... 45%, 57696 KB, 3668 KB/s, 15 seconds passed
+... 45%, 57728 KB, 3669 KB/s, 15 seconds passed
+... 45%, 57760 KB, 3670 KB/s, 15 seconds passed
 
 .. parsed-literal::
 
-    ... 44%, 56032 KB, 3466 KB/s, 16 seconds passed
-... 44%, 56064 KB, 3467 KB/s, 16 seconds passed
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-... 44%, 56128 KB, 3470 KB/s, 16 seconds passed
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+... 45%, 57888 KB, 3670 KB/s, 15 seconds passed
+... 45%, 57920 KB, 3667 KB/s, 15 seconds passed
 
 .. parsed-literal::
 
-    ... 44%, 56160 KB, 3467 KB/s, 16 seconds passed
-... 44%, 56192 KB, 3468 KB/s, 16 seconds passed
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-... 44%, 56256 KB, 3470 KB/s, 16 seconds passed
-... 44%, 56288 KB, 3467 KB/s, 16 seconds passed
-... 44%, 56320 KB, 3468 KB/s, 16 seconds passed
-... 44%, 56352 KB, 3469 KB/s, 16 seconds passed
-... 44%, 56384 KB, 3470 KB/s, 16 seconds passed
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+... 46%, 58112 KB, 3669 KB/s, 15 seconds passed
+... 46%, 58144 KB, 3670 KB/s, 15 seconds passed
 
 .. parsed-literal::
 
-    ... 44%, 56416 KB, 3467 KB/s, 16 seconds passed
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+... 46%, 58304 KB, 3667 KB/s, 15 seconds passed
 
 .. parsed-literal::
 
-    ... 44%, 56544 KB, 3467 KB/s, 16 seconds passed
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-... 44%, 56672 KB, 3467 KB/s, 16 seconds passed
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 .. parsed-literal::
 
-    ... 45%, 56768 KB, 3471 KB/s, 16 seconds passed
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 .. parsed-literal::
 
-    ... 45%, 56928 KB, 3467 KB/s, 16 seconds passed
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 .. parsed-literal::
 
-    ... 45%, 57056 KB, 3467 KB/s, 16 seconds passed
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 .. parsed-literal::
 
-    ... 45%, 57312 KB, 3467 KB/s, 16 seconds passed
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 .. parsed-literal::
 
-    ... 45%, 57440 KB, 3467 KB/s, 16 seconds passed
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 .. parsed-literal::
 
-    ... 45%, 57664 KB, 3469 KB/s, 16 seconds passed
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 .. parsed-literal::
 
-    ... 45%, 57824 KB, 3467 KB/s, 16 seconds passed
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 .. parsed-literal::
 
-    ... 46%, 57952 KB, 3467 KB/s, 16 seconds passed
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 .. parsed-literal::
 
-    ... 46%, 58208 KB, 3468 KB/s, 16 seconds passed
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 .. parsed-literal::
 
-    ... 46%, 58336 KB, 3468 KB/s, 16 seconds passed
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 .. parsed-literal::
 
-    ... 46%, 58560 KB, 3472 KB/s, 16 seconds passed
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 .. parsed-literal::
 
-    ... 46%, 58720 KB, 3468 KB/s, 16 seconds passed
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 .. parsed-literal::
 
-    ... 46%, 58880 KB, 3469 KB/s, 16 seconds passed
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 .. parsed-literal::
 
-    ... 46%, 59072 KB, 3467 KB/s, 17 seconds passed
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 .. parsed-literal::
 
-    ... 47%, 59200 KB, 3467 KB/s, 17 seconds passed
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 .. parsed-literal::
 
-    ... 47%, 59456 KB, 3469 KB/s, 17 seconds passed
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-
-
-
-    ... 47%, 59584 KB, 3467 KB/s, 17 seconds passed
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 .. parsed-literal::
 
-    ... 47%, 59776 KB, 3469 KB/s, 17 seconds passed
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 .. parsed-literal::
 
-    ... 47%, 59968 KB, 3467 KB/s, 17 seconds passed
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 .. parsed-literal::
 
-    ... 47%, 60096 KB, 3467 KB/s, 17 seconds passed
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 .. parsed-literal::
 
-    ... 47%, 60352 KB, 3467 KB/s, 17 seconds passed
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 .. parsed-literal::
 
-    ... 48%, 60480 KB, 3468 KB/s, 17 seconds passed
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-... 48%, 60608 KB, 3468 KB/s, 17 seconds passed
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 .. parsed-literal::
 
-    ... 48%, 60672 KB, 3470 KB/s, 17 seconds passed
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-... 48%, 60800 KB, 3470 KB/s, 17 seconds passed
-... 48%, 60832 KB, 3471 KB/s, 17 seconds passed
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+... 49%, 62624 KB, 3670 KB/s, 17 seconds passed
 
 .. parsed-literal::
 
-    ... 48%, 60864 KB, 3468 KB/s, 17 seconds passed
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-... 48%, 60928 KB, 3470 KB/s, 17 seconds passed
-... 48%, 60960 KB, 3472 KB/s, 17 seconds passed
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+... 49%, 62720 KB, 3669 KB/s, 17 seconds passed
+... 49%, 62752 KB, 3670 KB/s, 17 seconds passed
+... 49%, 62784 KB, 3667 KB/s, 17 seconds passed
+... 49%, 62816 KB, 3667 KB/s, 17 seconds passed
+... 49%, 62848 KB, 3669 KB/s, 17 seconds passed
 
 .. parsed-literal::
 
-    ... 48%, 60992 KB, 3468 KB/s, 17 seconds passed
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+    ... 49%, 62880 KB, 3670 KB/s, 17 seconds passed
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+... 49%, 62976 KB, 3669 KB/s, 17 seconds passed
+... 50%, 63008 KB, 3670 KB/s, 17 seconds passed
 
 .. parsed-literal::
 
-    ... 48%, 61248 KB, 3468 KB/s, 17 seconds passed
-   ... 48%, 61280 KB, 3469 KB/s, 17 seconds passed
-   ... 48%, 61312 KB, 3471 KB/s, 17 seconds passed
-    passed
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+... 50%, 63200 KB, 3667 KB/s, 17 seconds passed
 
 .. parsed-literal::
 
-    ... 48%, 61376 KB, 3468 KB/s, 17 seconds passed
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+    ... 50%, 63232 KB, 3669 KB/s, 17 seconds passed
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+... 50%, 63328 KB, 3667 KB/s, 17 seconds passed
+... 50%, 63360 KB, 3669 KB/s, 17 seconds passed
+... 50%, 63392 KB, 3670 KB/s, 17 seconds passed
 
 .. parsed-literal::
 
-    ... 48%, 61568 KB, 3470 KB/s, 17 seconds passed
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+... 50%, 63520 KB, 3670 KB/s, 17 seconds passed
+... 50%, 63552 KB, 3668 KB/s, 17 seconds passed
 
 .. parsed-literal::
 
-    ... 49%, 61760 KB, 3468 KB/s, 17 seconds passed
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+... 50%, 63744 KB, 3669 KB/s, 17 seconds passed
+... 50%, 63776 KB, 3670 KB/s, 17 seconds passed
 
 .. parsed-literal::
 
-    ... 49%, 61888 KB, 3468 KB/s, 17 seconds passed
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+... 50%, 63904 KB, 3669 KB/s, 17 seconds passed
+... 50%, 63936 KB, 3668 KB/s, 17 seconds passed
 
 .. parsed-literal::
 
-    ... 49%, 62144 KB, 3468 KB/s, 17 seconds passed
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+... 50%, 64128 KB, 3669 KB/s, 17 seconds passed
+... 50%, 64160 KB, 3670 KB/s, 17 seconds passed
 
 .. parsed-literal::
 
-    ... 49%, 62272 KB, 3469 KB/s, 17 seconds passed
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+... 51%, 64288 KB, 3670 KB/s, 17 seconds passed
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 .. parsed-literal::
 
-    ... 49%, 62464 KB, 3471 KB/s, 17 seconds passed
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+... 51%, 64480 KB, 3668 KB/s, 17 seconds passed
+... 51%, 64512 KB, 3669 KB/s, 17 seconds passed
+... 51%, 64544 KB, 3670 KB/s, 17 seconds passed
 
 .. parsed-literal::
 
-    ... 49%, 62656 KB, 3469 KB/s, 18 seconds passed
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 .. parsed-literal::
 
-    ... 49%, 62784 KB, 3469 KB/s, 18 seconds passed
-    ... 49%, 62816 KB, 3470 KB/s, 18 seconds passed
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-    ... 49%, 62912 KB, 3469 KB/s, 18 seconds passed
-    ... 49%, 62944 KB, 3470 KB/s, 18 seconds passed
-    ... 49%, 62976 KB, 3471 KB/s, 18 seconds passed
-     passed
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 .. parsed-literal::
 
-    ... 50%, 63040 KB, 3469 KB/s, 18 seconds passed
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 .. parsed-literal::
 
-    ... 50%, 63168 KB, 3469 KB/s, 18 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 52%, 66080 KB, 3469 KB/s, 19 seconds passed
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 .. parsed-literal::
 
-    ... 52%, 66208 KB, 3469 KB/s, 19 seconds passed
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 .. parsed-literal::
 
-    ... 52%, 66400 KB, 3471 KB/s, 19 seconds passed
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 .. parsed-literal::
 
-    ... 52%, 66592 KB, 3470 KB/s, 19 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 53%, 66976 KB, 3470 KB/s, 19 seconds passed
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 .. parsed-literal::
 
-    ... 53%, 67104 KB, 3470 KB/s, 19 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 58%, 73568 KB, 3473 KB/s, 21 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 62%, 78944 KB, 3473 KB/s, 22 seconds passed
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 .. parsed-literal::
 
-    ... 62%, 79104 KB, 3473 KB/s, 22 seconds passed
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 .. parsed-literal::
 
-    ... 62%, 79264 KB, 3473 KB/s, 22 seconds passed
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 .. parsed-literal::
 
-    ... 63%, 79456 KB, 3472 KB/s, 22 seconds passed
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 .. parsed-literal::
 
-    ... 63%, 79616 KB, 3473 KB/s, 22 seconds passed
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-... 63%, 79776 KB, 3473 KB/s, 22 seconds passed
+    ... 65%, 82496 KB, 3671 KB/s, 22 seconds passed
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+... 65%, 82624 KB, 3671 KB/s, 22 seconds passed
+... 65%, 82656 KB, 3672 KB/s, 22 seconds passed
+... 65%, 82688 KB, 3672 KB/s, 22 seconds passed
 
 .. parsed-literal::
 
-    ... 63%, 79808 KB, 3472 KB/s, 22 seconds passed
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-... 63%, 79872 KB, 3473 KB/s, 22 seconds passed
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-... 63%, 79936 KB, 3473 KB/s, 23 seconds passed
+    ... 65%, 82720 KB, 3671 KB/s, 22 seconds passed
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+... 65%, 82784 KB, 3672 KB/s, 22 seconds passed
+... 65%, 82816 KB, 3672 KB/s, 22 seconds passed
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 .. parsed-literal::
 
-    ... 63%, 79968 KB, 3473 KB/s, 23 seconds passed
-... 63%, 80000 KB, 3473 KB/s, 23 seconds passed
-... 63%, 80032 KB, 3473 KB/s, 23 seconds passed
-... 63%, 80064 KB, 3473 KB/s, 23 seconds passed
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-... 63%, 80128 KB, 3473 KB/s, 23 seconds passed
+    ... 65%, 82880 KB, 3671 KB/s, 22 seconds passed
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+... 65%, 83008 KB, 3671 KB/s, 22 seconds passed
+... 65%, 83040 KB, 3672 KB/s, 22 seconds passed
+... 65%, 83072 KB, 3672 KB/s, 22 seconds passed
 
 .. parsed-literal::
 
-    ... 63%, 80160 KB, 3473 KB/s, 23 seconds passed
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-... 63%, 80256 KB, 3473 KB/s, 23 seconds passed
-... 63%, 80288 KB, 3473 KB/s, 23 seconds passed
+    ... 65%, 83104 KB, 3671 KB/s, 22 seconds passed
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+... 66%, 83168 KB, 3672 KB/s, 22 seconds passed
+... 66%, 83200 KB, 3672 KB/s, 22 seconds passed
 
 .. parsed-literal::
 
-    ... 63%, 80320 KB, 3473 KB/s, 23 seconds passed
-... 63%, 80352 KB, 3473 KB/s, 23 seconds passed
-... 63%, 80384 KB, 3473 KB/s, 23 seconds passed
-... 63%, 80416 KB, 3473 KB/s, 23 seconds passed
-... 63%, 80448 KB, 3473 KB/s, 23 seconds passed
-... 63%, 80480 KB, 3473 KB/s, 23 seconds passed
+    ... 66%, 83232 KB, 3671 KB/s, 22 seconds passed
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+... 66%, 83360 KB, 3671 KB/s, 22 seconds passed
+... 66%, 83392 KB, 3671 KB/s, 22 seconds passed
+... 66%, 83424 KB, 3672 KB/s, 22 seconds passed
 
 .. parsed-literal::
 
-    ... 63%, 80512 KB, 3473 KB/s, 23 seconds passed
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-... 63%, 80576 KB, 3473 KB/s, 23 seconds passed
-... 63%, 80608 KB, 3473 KB/s, 23 seconds passed
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-... 64%, 80672 KB, 3473 KB/s, 23 seconds passed
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+... 66%, 83552 KB, 3672 KB/s, 22 seconds passed
+... 66%, 83584 KB, 3672 KB/s, 22 seconds passed
 
 .. parsed-literal::
 
-    ... 64%, 80704 KB, 3473 KB/s, 23 seconds passed
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-... 64%, 80768 KB, 3473 KB/s, 23 seconds passed
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-... 64%, 80832 KB, 3473 KB/s, 23 seconds passed
+    ... 66%, 83616 KB, 3671 KB/s, 22 seconds passed
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+... 66%, 83776 KB, 3671 KB/s, 22 seconds passed
+... 66%, 83808 KB, 3672 KB/s, 22 seconds passed
 
 .. parsed-literal::
 
-    ... 64%, 80864 KB, 3473 KB/s, 23 seconds passed
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-... 64%, 80992 KB, 3473 KB/s, 23 seconds passed
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+... 66%, 83936 KB, 3673 KB/s, 22 seconds passed
+... 66%, 83968 KB, 3673 KB/s, 22 seconds passed
 
 .. parsed-literal::
 
-    ... 64%, 81056 KB, 3474 KB/s, 23 seconds passed
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-... 64%, 81120 KB, 3473 KB/s, 23 seconds passed
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+... 66%, 84128 KB, 3671 KB/s, 22 seconds passed
+... 66%, 84160 KB, 3671 KB/s, 22 seconds passed
+... 66%, 84192 KB, 3672 KB/s, 22 seconds passed
 
 .. parsed-literal::
 
-    ... 64%, 81216 KB, 3473 KB/s, 23 seconds passed
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-... 64%, 81312 KB, 3474 KB/s, 23 seconds passed
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-... 64%, 81376 KB, 3473 KB/s, 23 seconds passed
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+... 66%, 84288 KB, 3671 KB/s, 22 seconds passed
+... 66%, 84320 KB, 3672 KB/s, 22 seconds passed
+... 66%, 84352 KB, 3673 KB/s, 22 seconds passed
 
 .. parsed-literal::
 
-    ... 64%, 81408 KB, 3473 KB/s, 23 seconds passed
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-... 64%, 81472 KB, 3473 KB/s, 23 seconds passed
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-... 64%, 81568 KB, 3474 KB/s, 23 seconds passed
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+... 67%, 84512 KB, 3671 KB/s, 23 seconds passed
+... 67%, 84544 KB, 3672 KB/s, 23 seconds passed
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 .. parsed-literal::
 
-    ... 64%, 81600 KB, 3473 KB/s, 23 seconds passed
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-... 64%, 81696 KB, 3474 KB/s, 23 seconds passed
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 .. parsed-literal::
 
-    ... 64%, 81760 KB, 3473 KB/s, 23 seconds passed
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+... 67%, 84928 KB, 3672 KB/s, 23 seconds passed
+... 67%, 84960 KB, 3672 KB/s, 23 seconds passed
 
 .. parsed-literal::
 
-    ... 65%, 81952 KB, 3474 KB/s, 23 seconds passed
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 .. parsed-literal::
 
-    ... 65%, 82112 KB, 3473 KB/s, 23 seconds passed
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 .. parsed-literal::
 
-    ... 65%, 82304 KB, 3473 KB/s, 23 seconds passed
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 .. parsed-literal::
 
-    ... 65%, 82496 KB, 3473 KB/s, 23 seconds passed
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 .. parsed-literal::
 
-    ... 65%, 82656 KB, 3473 KB/s, 23 seconds passed
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 .. parsed-literal::
 
-    ... 65%, 82848 KB, 3474 KB/s, 23 seconds passed
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 .. parsed-literal::
 
-    ... 65%, 83008 KB, 3473 KB/s, 23 seconds passed
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 .. parsed-literal::
 
-    ... 66%, 83200 KB, 3474 KB/s, 23 seconds passed
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 .. parsed-literal::
 
-    ... 66%, 83392 KB, 3473 KB/s, 24 seconds passed
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 .. parsed-literal::
 
-    ... 66%, 83552 KB, 3474 KB/s, 24 seconds passed
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 .. parsed-literal::
 
-    ... 66%, 83776 KB, 3473 KB/s, 24 seconds passed
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 .. parsed-literal::
 
-    ... 66%, 83904 KB, 3473 KB/s, 24 seconds passed
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 .. parsed-literal::
 
-    ... 66%, 84096 KB, 3474 KB/s, 24 seconds passed
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 .. parsed-literal::
 
-    ... 66%, 84288 KB, 3473 KB/s, 24 seconds passed
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 .. parsed-literal::
 
-    ... 67%, 84480 KB, 3474 KB/s, 24 seconds passed
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 .. parsed-literal::
 
-    ... 67%, 84672 KB, 3474 KB/s, 24 seconds passed
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 .. parsed-literal::
 
-    ... 67%, 84800 KB, 3473 KB/s, 24 seconds passed
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+    ... 69%, 88000 KB, 3673 KB/s, 23 seconds passed
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 .. parsed-literal::
 
-    ... 67%, 84992 KB, 3474 KB/s, 24 seconds passed
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 .. parsed-literal::
 
-    ... 67%, 85184 KB, 3474 KB/s, 24 seconds passed
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 .. parsed-literal::
 
-    ... 67%, 85376 KB, 3474 KB/s, 24 seconds passed
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-... 67%, 85440 KB, 3474 KB/s, 24 seconds passed
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-... 67%, 85504 KB, 3474 KB/s, 24 seconds passed
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 .. parsed-literal::
 
-    ... 67%, 85536 KB, 3473 KB/s, 24 seconds passed
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+    ... 70%, 88736 KB, 3672 KB/s, 24 seconds passed
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 .. parsed-literal::
 
-    ... 68%, 85696 KB, 3474 KB/s, 24 seconds passed
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-... 68%, 85760 KB, 3474 KB/s, 24 seconds passed
-... 68%, 85792 KB, 3473 KB/s, 24 seconds passed
-... 68%, 85824 KB, 3474 KB/s, 24 seconds passed
-... 68%, 85856 KB, 3474 KB/s, 24 seconds passed
+    ... 70%, 88928 KB, 3671 KB/s, 24 seconds passed
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+... 70%, 89024 KB, 3673 KB/s, 24 seconds passed
+... 70%, 89056 KB, 3671 KB/s, 24 seconds passed
+... 70%, 89088 KB, 3672 KB/s, 24 seconds passed
 
 .. parsed-literal::
 
-    ... 68%, 85888 KB, 3474 KB/s, 24 seconds passed
-... 68%, 85920 KB, 3474 KB/s, 24 seconds passed
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-... 68%, 85984 KB, 3474 KB/s, 24 seconds passed
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+... 70%, 89248 KB, 3672 KB/s, 24 seconds passed
+... 70%, 89280 KB, 3673 KB/s, 24 seconds passed
 
 .. parsed-literal::
 
-    ... 68%, 86080 KB, 3474 KB/s, 24 seconds passed
-... 68%, 86112 KB, 3474 KB/s, 24 seconds passed
-... 68%, 86144 KB, 3474 KB/s, 24 seconds passed
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+... 70%, 89408 KB, 3673 KB/s, 24 seconds passed
+... 71%, 89440 KB, 3672 KB/s, 24 seconds passed
+... 71%, 89472 KB, 3672 KB/s, 24 seconds passed
 
 .. parsed-literal::
 
-    ... 68%, 86240 KB, 3474 KB/s, 24 seconds passed
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-... 68%, 86400 KB, 3475 KB/s, 24 seconds passed
+    ... 71%, 89504 KB, 3672 KB/s, 24 seconds passed
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+... 71%, 89600 KB, 3672 KB/s, 24 seconds passed
+... 71%, 89632 KB, 3672 KB/s, 24 seconds passed
+... 71%, 89664 KB, 3673 KB/s, 24 seconds passed
 
 .. parsed-literal::
 
-    ... 68%, 86432 KB, 3474 KB/s, 24 seconds passed
-... 68%, 86464 KB, 3474 KB/s, 24 seconds passed
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+... 71%, 89760 KB, 3672 KB/s, 24 seconds passed
+... 71%, 89792 KB, 3673 KB/s, 24 seconds passed
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 .. parsed-literal::
 
-    ... 68%, 86592 KB, 3474 KB/s, 24 seconds passed
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-... 68%, 86656 KB, 3475 KB/s, 24 seconds passed
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-... 68%, 86784 KB, 3475 KB/s, 24 seconds passed
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 .. parsed-literal::
 
-    ... 68%, 86816 KB, 3474 KB/s, 24 seconds passed
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-... 68%, 86880 KB, 3474 KB/s, 25 seconds passed
-... 69%, 86912 KB, 3475 KB/s, 25 seconds passed
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+... 71%, 90176 KB, 3673 KB/s, 24 seconds passed
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 .. parsed-literal::
 
-    ... 69%, 86944 KB, 3474 KB/s, 25 seconds passed
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-... 69%, 87104 KB, 3474 KB/s, 25 seconds passed
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+... 71%, 90400 KB, 3673 KB/s, 24 seconds passed
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 .. parsed-literal::
 
-    ... 69%, 87136 KB, 3474 KB/s, 25 seconds passed
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-... 69%, 87200 KB, 3474 KB/s, 25 seconds passed
-... 69%, 87232 KB, 3474 KB/s, 25 seconds passed
-... 69%, 87264 KB, 3474 KB/s, 25 seconds passed
-... 69%, 87296 KB, 3475 KB/s, 25 seconds passed
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+... 71%, 90560 KB, 3674 KB/s, 24 seconds passed
+... 71%, 90592 KB, 3672 KB/s, 24 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 87328 KB, 3474 KB/s, 25 seconds passed
-... 69%, 87360 KB, 3474 KB/s, 25 seconds passed
-... 69%, 87392 KB, 3474 KB/s, 25 seconds passed
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+... 72%, 90784 KB, 3673 KB/s, 24 seconds passed
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 .. parsed-literal::
 
-    ... 69%, 87488 KB, 3474 KB/s, 25 seconds passed
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-... 69%, 87680 KB, 3475 KB/s, 25 seconds passed
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+... 72%, 90944 KB, 3674 KB/s, 24 seconds passed
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 .. parsed-literal::
 
-    ... 69%, 87712 KB, 3474 KB/s, 25 seconds passed
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 .. parsed-literal::
 
-    ... 69%, 87872 KB, 3474 KB/s, 25 seconds passed
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+... 72%, 91360 KB, 3672 KB/s, 24 seconds passed
 
 .. parsed-literal::
 
-    ... 69%, 88032 KB, 3475 KB/s, 25 seconds passed
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-... 69%, 88096 KB, 3474 KB/s, 25 seconds passed
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-... 70%, 88192 KB, 3475 KB/s, 25 seconds passed
+    ... 72%, 91392 KB, 3672 KB/s, 24 seconds passed
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 .. parsed-literal::
 
-    ... 70%, 88224 KB, 3474 KB/s, 25 seconds passed
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+    ... 72%, 91584 KB, 3673 KB/s, 24 seconds passed
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 .. parsed-literal::
 
-    ... 70%, 88384 KB, 3474 KB/s, 25 seconds passed
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 .. parsed-literal::
 
-    ... 70%, 88608 KB, 3474 KB/s, 25 seconds passed
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 .. parsed-literal::
 
-    ... 70%, 88736 KB, 3474 KB/s, 25 seconds passed
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 .. parsed-literal::
 
-    ... 70%, 88928 KB, 3475 KB/s, 25 seconds passed
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 .. parsed-literal::
 
-    ... 70%, 89120 KB, 3474 KB/s, 25 seconds passed
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 .. parsed-literal::
 
-    ... 70%, 89312 KB, 3475 KB/s, 25 seconds passed
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 .. parsed-literal::
 
-    ... 71%, 89472 KB, 3474 KB/s, 25 seconds passed
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 .. parsed-literal::
 
-    ... 71%, 89632 KB, 3474 KB/s, 25 seconds passed
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 .. parsed-literal::
 
-    ... 71%, 89824 KB, 3475 KB/s, 25 seconds passed
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 .. parsed-literal::
 
-    ... 71%, 90016 KB, 3474 KB/s, 25 seconds passed
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 .. parsed-literal::
 
-    ... 71%, 90208 KB, 3475 KB/s, 25 seconds passed
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 .. parsed-literal::
 
-    ... 71%, 90368 KB, 3474 KB/s, 26 seconds passed
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 .. parsed-literal::
 
-    ... 71%, 90528 KB, 3474 KB/s, 26 seconds passed
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 .. parsed-literal::
 
-    ... 72%, 90720 KB, 3475 KB/s, 26 seconds passed
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 .. parsed-literal::
 
-    ... 72%, 90880 KB, 3474 KB/s, 26 seconds passed
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 .. parsed-literal::
 
-    ... 72%, 91072 KB, 3475 KB/s, 26 seconds passed
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 .. parsed-literal::
 
-    ... 72%, 91264 KB, 3474 KB/s, 26 seconds passed
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 .. parsed-literal::
 
-    ... 72%, 91424 KB, 3474 KB/s, 26 seconds passed
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 .. parsed-literal::
 
-    ... 72%, 91616 KB, 3475 KB/s, 26 seconds passed
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-... 72%, 91680 KB, 3474 KB/s, 26 seconds passed
-... 72%, 91712 KB, 3475 KB/s, 26 seconds passed
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 .. parsed-literal::
 
-    ... 72%, 91776 KB, 3474 KB/s, 26 seconds passed
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-... 72%, 91904 KB, 3474 KB/s, 26 seconds passed
-... 72%, 91936 KB, 3474 KB/s, 26 seconds passed
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+... 75%, 95520 KB, 3673 KB/s, 26 seconds passed
 
 .. parsed-literal::
 
-    ... 73%, 91968 KB, 3475 KB/s, 26 seconds passed
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-... 73%, 92032 KB, 3474 KB/s, 26 seconds passed
-... 73%, 92064 KB, 3474 KB/s, 26 seconds passed
-... 73%, 92096 KB, 3475 KB/s, 26 seconds passed
-... 73%, 92128 KB, 3475 KB/s, 26 seconds passed
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+... 75%, 95616 KB, 3673 KB/s, 26 seconds passed
+... 75%, 95648 KB, 3673 KB/s, 26 seconds passed
+... 75%, 95680 KB, 3672 KB/s, 26 seconds passed
 
 .. parsed-literal::
 
-    ... 73%, 92160 KB, 3474 KB/s, 26 seconds passed
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-... 73%, 92224 KB, 3475 KB/s, 26 seconds passed
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+... 76%, 95872 KB, 3673 KB/s, 26 seconds passed
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 .. parsed-literal::
 
-    ... 73%, 92320 KB, 3475 KB/s, 26 seconds passed
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 .. parsed-literal::
 
-    ... 73%, 92512 KB, 3475 KB/s, 26 seconds passed
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-... 73%, 92576 KB, 3475 KB/s, 26 seconds passed
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+... 76%, 96256 KB, 3673 KB/s, 26 seconds passed
 
 .. parsed-literal::
 
-    ... 73%, 92672 KB, 3474 KB/s, 26 seconds passed
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 .. parsed-literal::
 
-    ... 73%, 92864 KB, 3475 KB/s, 26 seconds passed
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 .. parsed-literal::
 
-    ... 73%, 93056 KB, 3475 KB/s, 26 seconds passed
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 .. parsed-literal::
 
-    ... 74%, 93216 KB, 3475 KB/s, 26 seconds passed
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+... 77%, 96992 KB, 3672 KB/s, 26 seconds passed
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 .. parsed-literal::
 
-    ... 74%, 93408 KB, 3475 KB/s, 26 seconds passed
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 .. parsed-literal::
 
-    ... 74%, 93568 KB, 3474 KB/s, 26 seconds passed
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 .. parsed-literal::
 
-    ... 74%, 93760 KB, 3475 KB/s, 26 seconds passed
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 .. parsed-literal::
 
-    ... 74%, 93952 KB, 3475 KB/s, 27 seconds passed
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 .. parsed-literal::
 
-    ... 74%, 94112 KB, 3475 KB/s, 27 seconds passed
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 .. parsed-literal::
 
-    ... 74%, 94304 KB, 3476 KB/s, 27 seconds passed
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 .. parsed-literal::
 
-    ... 74%, 94464 KB, 3475 KB/s, 27 seconds passed
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 .. parsed-literal::
 
-    ... 75%, 94656 KB, 3475 KB/s, 27 seconds passed
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 .. parsed-literal::
 
-    ... 75%, 94816 KB, 3474 KB/s, 27 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 75%, 95200 KB, 3474 KB/s, 27 seconds passed
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 .. parsed-literal::
 
-    ... 75%, 95360 KB, 3475 KB/s, 27 seconds passed
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 .. parsed-literal::
 
-    ... 75%, 95552 KB, 3475 KB/s, 27 seconds passed
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 .. parsed-literal::
 
-    ... 75%, 95712 KB, 3475 KB/s, 27 seconds passed
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 .. parsed-literal::
 
-    ... 76%, 95904 KB, 3475 KB/s, 27 seconds passed
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 .. parsed-literal::
 
-    ... 76%, 96096 KB, 3475 KB/s, 27 seconds passed
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 .. parsed-literal::
 
-    ... 76%, 96256 KB, 3475 KB/s, 27 seconds passed
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 .. parsed-literal::
 
-    ... 76%, 96448 KB, 3476 KB/s, 27 seconds passed
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 .. parsed-literal::
 
-    ... 76%, 96608 KB, 3475 KB/s, 27 seconds passed
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 .. parsed-literal::
 
-    ... 76%, 96800 KB, 3476 KB/s, 27 seconds passed
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 .. parsed-literal::
 
-    ... 77%, 96992 KB, 3475 KB/s, 27 seconds passed
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 .. parsed-literal::
 
-    ... 77%, 97152 KB, 3475 KB/s, 27 seconds passed
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 .. parsed-literal::
 
-    ... 77%, 97344 KB, 3476 KB/s, 28 seconds passed
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 .. parsed-literal::
 
-    ... 77%, 97504 KB, 3475 KB/s, 28 seconds passed
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 .. parsed-literal::
 
-    ... 77%, 97696 KB, 3475 KB/s, 28 seconds passed
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 .. parsed-literal::
 
-    ... 77%, 97888 KB, 3475 KB/s, 28 seconds passed
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 .. parsed-literal::
 
-    ... 77%, 98048 KB, 3475 KB/s, 28 seconds passed
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-... 77%, 98144 KB, 3475 KB/s, 28 seconds passed
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+... 81%, 102080 KB, 3673 KB/s, 27 seconds passed
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 .. parsed-literal::
 
-    ... 77%, 98240 KB, 3476 KB/s, 28 seconds passed
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-... 78%, 98304 KB, 3475 KB/s, 28 seconds passed
-... 78%, 98336 KB, 3475 KB/s, 28 seconds passed
-... 78%, 98368 KB, 3476 KB/s, 28 seconds passed
+    ... 81%, 102144 KB, 3672 KB/s, 27 seconds passed
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+... 81%, 102208 KB, 3673 KB/s, 27 seconds passed
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+... 81%, 102272 KB, 3673 KB/s, 27 seconds passed
 
 .. parsed-literal::
 
-    ... 78%, 98400 KB, 3475 KB/s, 28 seconds passed
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-... 78%, 98560 KB, 3475 KB/s, 28 seconds passed
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 .. parsed-literal::
 
-    ... 78%, 98592 KB, 3475 KB/s, 28 seconds passed
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 .. parsed-literal::
 
-    ... 78%, 98784 KB, 3475 KB/s, 28 seconds passed
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 .. parsed-literal::
 
-    ... 78%, 98944 KB, 3476 KB/s, 28 seconds passed
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 .. parsed-literal::
 
-    ... 78%, 99136 KB, 3476 KB/s, 28 seconds passed
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 .. parsed-literal::
 
-    ... 78%, 99296 KB, 3476 KB/s, 28 seconds passed
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 .. parsed-literal::
 
-    ... 78%, 99488 KB, 3476 KB/s, 28 seconds passed
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+... 82%, 103648 KB, 3674 KB/s, 28 seconds passed
 
 .. parsed-literal::
 
-    ... 79%, 99680 KB, 3476 KB/s, 28 seconds passed
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 .. parsed-literal::
 
-    ... 79%, 99840 KB, 3476 KB/s, 28 seconds passed
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-... 79%, 100000 KB, 3476 KB/s, 28 seconds passed
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+... 82%, 104000 KB, 3673 KB/s, 28 seconds passed
 
 .. parsed-literal::
 
-    ... 79%, 100032 KB, 3475 KB/s, 28 seconds passed
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 .. parsed-literal::
 
-    ... 79%, 100192 KB, 3476 KB/s, 28 seconds passed
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 .. parsed-literal::
 
-    ... 79%, 100384 KB, 3476 KB/s, 28 seconds passed
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 .. parsed-literal::
 
-    ... 79%, 100544 KB, 3475 KB/s, 28 seconds passed
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 .. parsed-literal::
 
-    ... 79%, 100736 KB, 3476 KB/s, 28 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 80%, 101088 KB, 3476 KB/s, 29 seconds passed
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 .. parsed-literal::
 
-    ... 80%, 101280 KB, 3476 KB/s, 29 seconds passed
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 .. parsed-literal::
 
-    ... 80%, 101440 KB, 3475 KB/s, 29 seconds passed
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 .. parsed-literal::
 
-    ... 80%, 101632 KB, 3476 KB/s, 29 seconds passed
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 .. parsed-literal::
 
-    ... 80%, 101824 KB, 3475 KB/s, 29 seconds passed
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 .. parsed-literal::
 
-    ... 80%, 101984 KB, 3476 KB/s, 29 seconds passed
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 .. parsed-literal::
 
-    ... 81%, 102176 KB, 3476 KB/s, 29 seconds passed
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 .. parsed-literal::
 
-    ... 81%, 102336 KB, 3475 KB/s, 29 seconds passed
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 .. parsed-literal::
 
-    ... 81%, 102528 KB, 3476 KB/s, 29 seconds passed
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 .. parsed-literal::
 
-    ... 81%, 102720 KB, 3476 KB/s, 29 seconds passed
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 .. parsed-literal::
 
-    ... 81%, 102880 KB, 3476 KB/s, 29 seconds passed
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 .. parsed-literal::
 
-    ... 81%, 103040 KB, 3476 KB/s, 29 seconds passed
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 .. parsed-literal::
 
-    ... 81%, 103232 KB, 3476 KB/s, 29 seconds passed
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 .. parsed-literal::
 
-    ... 82%, 103424 KB, 3476 KB/s, 29 seconds passed
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 .. parsed-literal::
 
-    ... 82%, 103616 KB, 3476 KB/s, 29 seconds passed
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 .. parsed-literal::
 
-    ... 82%, 103776 KB, 3476 KB/s, 29 seconds passed
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 .. parsed-literal::
 
-    ... 82%, 103968 KB, 3476 KB/s, 29 seconds passed
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+... 86%, 108320 KB, 3673 KB/s, 29 seconds passed
+... 86%, 108352 KB, 3674 KB/s, 29 seconds passed
 
 .. parsed-literal::
 
-    ... 82%, 104128 KB, 3476 KB/s, 29 seconds passed
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-... 82%, 104224 KB, 3476 KB/s, 29 seconds passed
-... 82%, 104256 KB, 3476 KB/s, 29 seconds passed
-... 82%, 104288 KB, 3476 KB/s, 29 seconds passed
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+... 86%, 108480 KB, 3674 KB/s, 29 seconds passed
 
 .. parsed-literal::
 
-    ... 82%, 104320 KB, 3476 KB/s, 30 seconds passed
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 .. parsed-literal::
 
-    ... 82%, 104480 KB, 3476 KB/s, 30 seconds passed
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-... 83%, 104576 KB, 3476 KB/s, 30 seconds passed
-... 83%, 104608 KB, 3476 KB/s, 30 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
-    ... 86%, 109504 KB, 3476 KB/s, 31 seconds passed
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 .. parsed-literal::
 
-    ... 87%, 109664 KB, 3477 KB/s, 31 seconds passed
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 .. parsed-literal::
 
-    ... 87%, 109856 KB, 3477 KB/s, 31 seconds passed
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 .. parsed-literal::
 
-    ... 87%, 110016 KB, 3476 KB/s, 31 seconds passed
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 .. parsed-literal::
 
-    ... 87%, 110208 KB, 3476 KB/s, 31 seconds passed
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-... 87%, 110304 KB, 3477 KB/s, 31 seconds passed
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 .. parsed-literal::
 
-    ... 87%, 110400 KB, 3476 KB/s, 31 seconds passed
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 .. parsed-literal::
 
-    ... 87%, 110592 KB, 3476 KB/s, 31 seconds passed
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-... 87%, 110656 KB, 3477 KB/s, 31 seconds passed
-... 87%, 110688 KB, 3477 KB/s, 31 seconds passed
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 .. parsed-literal::
 
-    ... 87%, 110752 KB, 3477 KB/s, 31 seconds passed
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-... 87%, 110816 KB, 3477 KB/s, 31 seconds passed
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+... 91%, 115456 KB, 3673 KB/s, 31 seconds passed
+... 91%, 115488 KB, 3674 KB/s, 31 seconds passed
 
 .. parsed-literal::
 
-    ... 88%, 110912 KB, 3476 KB/s, 31 seconds passed
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-... 88%, 110976 KB, 3477 KB/s, 31 seconds passed
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-... 88%, 111040 KB, 3477 KB/s, 31 seconds passed
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+... 91%, 115680 KB, 3672 KB/s, 31 seconds passed
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 .. parsed-literal::
 
-    ... 88%, 111104 KB, 3476 KB/s, 31 seconds passed
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-... 88%, 111168 KB, 3476 KB/s, 31 seconds passed
-... 88%, 111200 KB, 3477 KB/s, 31 seconds passed
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 .. parsed-literal::
 
-    ... 88%, 111296 KB, 3476 KB/s, 32 seconds passed
-... 88%, 111328 KB, 3477 KB/s, 32 seconds passed
-... 88%, 111360 KB, 3476 KB/s, 32 seconds passed
-... 88%, 111392 KB, 3477 KB/s, 32 seconds passed
-... 88%, 111424 KB, 3476 KB/s, 32 seconds passed
-... 88%, 111456 KB, 3477 KB/s, 32 seconds passed
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+... 92%, 116000 KB, 3674 KB/s, 31 seconds passed
+... 92%, 116032 KB, 3672 KB/s, 31 seconds passed
+... 92%, 116064 KB, 3673 KB/s, 31 seconds passed
 
 .. parsed-literal::
 
-    ... 88%, 111488 KB, 3476 KB/s, 32 seconds passed
-... 88%, 111520 KB, 3477 KB/s, 32 seconds passed
-... 88%, 111552 KB, 3477 KB/s, 32 seconds passed
-... 88%, 111584 KB, 3477 KB/s, 32 seconds passed
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+... 92%, 116256 KB, 3674 KB/s, 31 seconds passed
 
 .. parsed-literal::
 
-    ... 88%, 111616 KB, 3476 KB/s, 32 seconds passed
-... 88%, 111648 KB, 3477 KB/s, 32 seconds passed
-... 88%, 111680 KB, 3477 KB/s, 32 seconds passed
-... 88%, 111712 KB, 3477 KB/s, 32 seconds passed
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 .. parsed-literal::
 
-    ... 88%, 111808 KB, 3477 KB/s, 32 seconds passed
-... 88%, 111840 KB, 3477 KB/s, 32 seconds passed
-... 88%, 111872 KB, 3476 KB/s, 32 seconds passed
-... 88%, 111904 KB, 3477 KB/s, 32 seconds passed
-... 88%, 111936 KB, 3477 KB/s, 32 seconds passed
-... 88%, 111968 KB, 3477 KB/s, 32 seconds passed
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+... 92%, 116608 KB, 3673 KB/s, 31 seconds passed
+... 92%, 116640 KB, 3674 KB/s, 31 seconds passed
 
 .. parsed-literal::
 
-    ... 88%, 112000 KB, 3476 KB/s, 32 seconds passed
-... 88%, 112032 KB, 3477 KB/s, 32 seconds passed
-... 88%, 112064 KB, 3477 KB/s, 32 seconds passed
-... 88%, 112096 KB, 3477 KB/s, 32 seconds passed
-... 89%, 112128 KB, 3476 KB/s, 32 seconds passed
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+... 92%, 116800 KB, 3672 KB/s, 31 seconds passed
 
 .. parsed-literal::
 
-    ... 89%, 112160 KB, 3476 KB/s, 32 seconds passed
-... 89%, 112192 KB, 3477 KB/s, 32 seconds passed
-... 89%, 112224 KB, 3477 KB/s, 32 seconds passed
-... 89%, 112256 KB, 3476 KB/s, 32 seconds passed
-... 89%, 112288 KB, 3477 KB/s, 32 seconds passed
-... 89%, 112320 KB, 3477 KB/s, 32 seconds passed
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+... 92%, 116960 KB, 3673 KB/s, 31 seconds passed
+... 92%, 116992 KB, 3674 KB/s, 31 seconds passed
+... 92%, 117024 KB, 3674 KB/s, 31 seconds passed
 
 .. parsed-literal::
 
-    ... 89%, 112352 KB, 3477 KB/s, 32 seconds passed
-... 89%, 112384 KB, 3477 KB/s, 32 seconds passed
-... 89%, 112416 KB, 3477 KB/s, 32 seconds passed
-... 89%, 112448 KB, 3477 KB/s, 32 seconds passed
-... 89%, 112480 KB, 3477 KB/s, 32 seconds passed
-... 89%, 112512 KB, 3477 KB/s, 32 seconds passed
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+... 93%, 117152 KB, 3674 KB/s, 31 seconds passed
+... 93%, 117184 KB, 3672 KB/s, 31 seconds passed
 
 .. parsed-literal::
 
-    ... 89%, 112544 KB, 3477 KB/s, 32 seconds passed
-... 89%, 112576 KB, 3477 KB/s, 32 seconds passed
-... 89%, 112608 KB, 3477 KB/s, 32 seconds passed
-... 89%, 112640 KB, 3477 KB/s, 32 seconds passed
-... 89%, 112672 KB, 3477 KB/s, 32 seconds passed
-... 89%, 112704 KB, 3477 KB/s, 32 seconds passed
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+... 93%, 117344 KB, 3673 KB/s, 31 seconds passed
+... 93%, 117376 KB, 3674 KB/s, 31 seconds passed
+... 93%, 117408 KB, 3674 KB/s, 31 seconds passed
 
 .. parsed-literal::
 
-    ... 89%, 112736 KB, 3477 KB/s, 32 seconds passed
-... 89%, 112768 KB, 3477 KB/s, 32 seconds passed
-... 89%, 112800 KB, 3477 KB/s, 32 seconds passed
-... 89%, 112832 KB, 3477 KB/s, 32 seconds passed
-... 89%, 112864 KB, 3477 KB/s, 32 seconds passed
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+... 93%, 117536 KB, 3674 KB/s, 31 seconds passed
+... 93%, 117568 KB, 3673 KB/s, 32 seconds passed
 
 .. parsed-literal::
 
-    ... 89%, 112896 KB, 3477 KB/s, 32 seconds passed
-... 89%, 112928 KB, 3477 KB/s, 32 seconds passed
-... 89%, 112960 KB, 3477 KB/s, 32 seconds passed
-... 89%, 112992 KB, 3477 KB/s, 32 seconds passed
-... 89%, 113024 KB, 3477 KB/s, 32 seconds passed
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+... 93%, 117728 KB, 3673 KB/s, 32 seconds passed
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+... 93%, 117792 KB, 3674 KB/s, 32 seconds passed
 
 .. parsed-literal::
 
-    ... 89%, 113056 KB, 3477 KB/s, 32 seconds passed
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-... 89%, 113120 KB, 3477 KB/s, 32 seconds passed
-... 89%, 113152 KB, 3477 KB/s, 32 seconds passed
-... 89%, 113184 KB, 3477 KB/s, 32 seconds passed
-... 89%, 113216 KB, 3477 KB/s, 32 seconds passed
-... 89%, 113248 KB, 3477 KB/s, 32 seconds passed
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+... 93%, 117920 KB, 3674 KB/s, 32 seconds passed
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 .. parsed-literal::
 
-    ... 89%, 113280 KB, 3477 KB/s, 32 seconds passed
-... 89%, 113312 KB, 3477 KB/s, 32 seconds passed
-... 89%, 113344 KB, 3477 KB/s, 32 seconds passed
-... 90%, 113376 KB, 3476 KB/s, 32 seconds passed
-... 90%, 113408 KB, 3477 KB/s, 32 seconds passed
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+... 93%, 118176 KB, 3674 KB/s, 32 seconds passed
 
 .. parsed-literal::
 
-    ... 90%, 113440 KB, 3477 KB/s, 32 seconds passed
-... 90%, 113472 KB, 3477 KB/s, 32 seconds passed
-... 90%, 113504 KB, 3477 KB/s, 32 seconds passed
-... 90%, 113536 KB, 3477 KB/s, 32 seconds passed
-... 90%, 113568 KB, 3477 KB/s, 32 seconds passed
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+... 93%, 118304 KB, 3672 KB/s, 32 seconds passed
 
 .. parsed-literal::
 
-    ... 90%, 113600 KB, 3477 KB/s, 32 seconds passed
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-... 90%, 113664 KB, 3477 KB/s, 32 seconds passed
-... 90%, 113696 KB, 3477 KB/s, 32 seconds passed
-... 90%, 113728 KB, 3477 KB/s, 32 seconds passed
-... 90%, 113760 KB, 3477 KB/s, 32 seconds passed
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 .. parsed-literal::
 
-    ... 90%, 113792 KB, 3477 KB/s, 32 seconds passed
-... 90%, 113824 KB, 3477 KB/s, 32 seconds passed
-... 90%, 113856 KB, 3477 KB/s, 32 seconds passed
-... 90%, 113888 KB, 3477 KB/s, 32 seconds passed
-... 90%, 113920 KB, 3477 KB/s, 32 seconds passed
-... 90%, 113952 KB, 3477 KB/s, 32 seconds passed
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 .. parsed-literal::
 
-    ... 90%, 113984 KB, 3477 KB/s, 32 seconds passed
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-... 90%, 114080 KB, 3477 KB/s, 32 seconds passed
-... 90%, 114112 KB, 3477 KB/s, 32 seconds passed
-... 90%, 114144 KB, 3477 KB/s, 32 seconds passed
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 .. parsed-literal::
 
-    ... 90%, 114176 KB, 3477 KB/s, 32 seconds passed
-... 90%, 114208 KB, 3477 KB/s, 32 seconds passed
-... 90%, 114240 KB, 3477 KB/s, 32 seconds passed
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-... 90%, 114304 KB, 3477 KB/s, 32 seconds passed
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 .. parsed-literal::
 
-    ... 90%, 114336 KB, 3477 KB/s, 32 seconds passed
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-... 90%, 114400 KB, 3477 KB/s, 32 seconds passed
-... 90%, 114432 KB, 3477 KB/s, 32 seconds passed
-... 90%, 114464 KB, 3477 KB/s, 32 seconds passed
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 .. parsed-literal::
 
-    ... 90%, 114496 KB, 3477 KB/s, 32 seconds passed
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-... 90%, 114592 KB, 3477 KB/s, 32 seconds passed
-... 91%, 114624 KB, 3477 KB/s, 32 seconds passed
-... 91%, 114656 KB, 3477 KB/s, 32 seconds passed
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 .. parsed-literal::
 
-    ... 91%, 114688 KB, 3477 KB/s, 32 seconds passed
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-... 91%, 114752 KB, 3477 KB/s, 32 seconds passed
-... 91%, 114784 KB, 3477 KB/s, 33 seconds passed
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 .. parsed-literal::
 
-    ... 91%, 114848 KB, 3477 KB/s, 33 seconds passed
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 .. parsed-literal::
 
-    ... 91%, 115040 KB, 3477 KB/s, 33 seconds passed
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-... 91%, 115104 KB, 3477 KB/s, 33 seconds passed
-... 91%, 115136 KB, 3477 KB/s, 33 seconds passed
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-... 91%, 115200 KB, 3477 KB/s, 33 seconds passed
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+... 95%, 120000 KB, 3672 KB/s, 32 seconds passed
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 .. parsed-literal::
 
-    ... 91%, 115232 KB, 3477 KB/s, 33 seconds passed
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-... 91%, 115296 KB, 3477 KB/s, 33 seconds passed
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 .. parsed-literal::
 
-    ... 91%, 115392 KB, 3477 KB/s, 33 seconds passed
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-... 91%, 115456 KB, 3477 KB/s, 33 seconds passed
-... 91%, 115488 KB, 3477 KB/s, 33 seconds passed
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+... 95%, 120416 KB, 3673 KB/s, 32 seconds passed
 
 .. parsed-literal::
 
-    ... 91%, 115584 KB, 3477 KB/s, 33 seconds passed
-... 91%, 115616 KB, 3477 KB/s, 33 seconds passed
-... 91%, 115648 KB, 3477 KB/s, 33 seconds passed
-... 91%, 115680 KB, 3477 KB/s, 33 seconds passed
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+... 95%, 120576 KB, 3673 KB/s, 32 seconds passed
 
 .. parsed-literal::
 
-    ... 91%, 115744 KB, 3477 KB/s, 33 seconds passed
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-... 91%, 115808 KB, 3476 KB/s, 33 seconds passed
-... 91%, 115840 KB, 3477 KB/s, 33 seconds passed
-... 91%, 115872 KB, 3477 KB/s, 33 seconds passed
-... 92%, 115904 KB, 3477 KB/s, 33 seconds passed
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+... 95%, 120768 KB, 3673 KB/s, 32 seconds passed
+... 95%, 120800 KB, 3673 KB/s, 32 seconds passed
 
 .. parsed-literal::
 
-    ... 92%, 115936 KB, 3476 KB/s, 33 seconds passed
-... 92%, 115968 KB, 3477 KB/s, 33 seconds passed
-... 92%, 116000 KB, 3477 KB/s, 33 seconds passed
-... 92%, 116032 KB, 3477 KB/s, 33 seconds passed
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+... 96%, 120960 KB, 3674 KB/s, 32 seconds passed
 
 .. parsed-literal::
 
-    ... 92%, 116128 KB, 3477 KB/s, 33 seconds passed
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-... 92%, 116192 KB, 3477 KB/s, 33 seconds passed
-... 92%, 116224 KB, 3477 KB/s, 33 seconds passed
-... 92%, 116256 KB, 3477 KB/s, 33 seconds passed
+    ... 96%, 120992 KB, 3673 KB/s, 32 seconds passed
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 .. parsed-literal::
 
-    ... 92%, 116288 KB, 3477 KB/s, 33 seconds passed
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-... 92%, 116352 KB, 3477 KB/s, 33 seconds passed
-... 92%, 116384 KB, 3477 KB/s, 33 seconds passed
-... 92%, 116416 KB, 3477 KB/s, 33 seconds passed
-... 92%, 116448 KB, 3477 KB/s, 33 seconds passed
+    ... 96%, 121216 KB, 3673 KB/s, 32 seconds passed
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+... 96%, 121280 KB, 3673 KB/s, 33 seconds passed
+... 96%, 121312 KB, 3673 KB/s, 33 seconds passed
+... 96%, 121344 KB, 3674 KB/s, 33 seconds passed
 
 .. parsed-literal::
 
-    ... 92%, 116480 KB, 3477 KB/s, 33 seconds passed
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-... 92%, 116544 KB, 3477 KB/s, 33 seconds passed
-... 92%, 116576 KB, 3477 KB/s, 33 seconds passed
-... 92%, 116608 KB, 3477 KB/s, 33 seconds passed
-... 92%, 116640 KB, 3477 KB/s, 33 seconds passed
+    ... 96%, 121376 KB, 3672 KB/s, 33 seconds passed
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+... 96%, 121472 KB, 3673 KB/s, 33 seconds passed
+... 96%, 121504 KB, 3672 KB/s, 33 seconds passed
+... 96%, 121536 KB, 3673 KB/s, 33 seconds passed
 
 .. parsed-literal::
 
-    ... 92%, 116672 KB, 3477 KB/s, 33 seconds passed
-... 92%, 116704 KB, 3477 KB/s, 33 seconds passed
-... 92%, 116736 KB, 3477 KB/s, 33 seconds passed
-... 92%, 116768 KB, 3477 KB/s, 33 seconds passed
-... 92%, 116800 KB, 3477 KB/s, 33 seconds passed
+    ... 96%, 121568 KB, 3674 KB/s, 33 seconds passed
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+... 96%, 121664 KB, 3673 KB/s, 33 seconds passed
+... 96%, 121696 KB, 3674 KB/s, 33 seconds passed
+... 96%, 121728 KB, 3673 KB/s, 33 seconds passed
 
 .. parsed-literal::
 
-    ... 92%, 116832 KB, 3477 KB/s, 33 seconds passed
-... 92%, 116864 KB, 3477 KB/s, 33 seconds passed
-... 92%, 116896 KB, 3477 KB/s, 33 seconds passed
-... 92%, 116928 KB, 3477 KB/s, 33 seconds passed
-... 92%, 116960 KB, 3477 KB/s, 33 seconds passed
-... 92%, 116992 KB, 3477 KB/s, 33 seconds passed
+    ... 96%, 121760 KB, 3672 KB/s, 33 seconds passed
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+... 96%, 121824 KB, 3674 KB/s, 33 seconds passed
+... 96%, 121856 KB, 3674 KB/s, 33 seconds passed
+... 96%, 121888 KB, 3672 KB/s, 33 seconds passed
 
 .. parsed-literal::
 
-    ... 92%, 117024 KB, 3477 KB/s, 33 seconds passed
-... 92%, 117056 KB, 3477 KB/s, 33 seconds passed
-... 92%, 117088 KB, 3477 KB/s, 33 seconds passed
-... 92%, 117120 KB, 3477 KB/s, 33 seconds passed
-... 93%, 117152 KB, 3477 KB/s, 33 seconds passed
+    ... 96%, 121920 KB, 3673 KB/s, 33 seconds passed
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+... 96%, 122048 KB, 3673 KB/s, 33 seconds passed
+... 96%, 122080 KB, 3674 KB/s, 33 seconds passed
+... 96%, 122112 KB, 3673 KB/s, 33 seconds passed
 
 .. parsed-literal::
 
-    ... 93%, 117184 KB, 3477 KB/s, 33 seconds passed
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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 .. parsed-literal::
 
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-
-.. parsed-literal::
-
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-
-.. parsed-literal::
-
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-
-.. parsed-literal::
-
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-
-.. parsed-literal::
-
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-
-.. parsed-literal::
-
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-
-.. parsed-literal::
-
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-
-.. parsed-literal::
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-
-.. parsed-literal::
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-
-.. parsed-literal::
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-
-.. parsed-literal::
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-
-.. parsed-literal::
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-
-.. parsed-literal::
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-
-.. parsed-literal::
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-
-.. parsed-literal::
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-
-.. parsed-literal::
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-
-.. parsed-literal::
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-
-.. parsed-literal::
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-
-.. parsed-literal::
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-
-.. parsed-literal::
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-
-.. parsed-literal::
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-
-.. parsed-literal::
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-
-.. parsed-literal::
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-
-.. parsed-literal::
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-
-.. parsed-literal::
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-
-.. parsed-literal::
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-
-.. parsed-literal::
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-
-.. parsed-literal::
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-
-.. parsed-literal::
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-... 99%, 125824 KB, 3478 KB/s, 36 seconds passed
-... 99%, 125856 KB, 3477 KB/s, 36 seconds passed
-... 99%, 125888 KB, 3478 KB/s, 36 seconds passed
-... 99%, 125920 KB, 3477 KB/s, 36 seconds passed
-
-.. parsed-literal::
-
-    ... 99%, 125952 KB, 3478 KB/s, 36 seconds passed
-... 100%, 125953 KB, 3478 KB/s, 36 seconds passed
+    ... 99%, 125888 KB, 3673 KB/s, 34 seconds passed
+... 99%, 125920 KB, 3674 KB/s, 34 seconds passed
+... 99%, 125952 KB, 3673 KB/s, 34 seconds passed
+... 100%, 125953 KB, 3673 KB/s, 34 seconds passed
 
 
 
@@ -6276,7 +6161,7 @@ above.
 
 .. parsed-literal::
 
-    ... 100%, 0 KB, 301 KB/s, 0 seconds passed
+    ... 100%, 0 KB, 283 KB/s, 0 seconds passed
 
 
     ========== Downloading models/public/colorization-v2/model/base_color.py
@@ -6284,11 +6169,7 @@ above.
 
 .. parsed-literal::
 
-    ... 100%, 0 KB, 1783 KB/s, 0 seconds passed
-
-
-
-.. parsed-literal::
+    ... 100%, 0 KB, 1753 KB/s, 0 seconds passed
 
 
     ========== Downloading models/public/colorization-v2/model/eccv16.py
@@ -6296,7 +6177,7 @@ above.
 
 .. parsed-literal::
 
-    ... 100%, 4 KB, 15965 KB/s, 0 seconds passed
+    ... 100%, 4 KB, 17370 KB/s, 0 seconds passed
 
 
     ========== Replacing text in models/public/colorization-v2/model/__init__.py
@@ -6333,7 +6214,7 @@ respectively
 .. parsed-literal::
 
     ========== Converting colorization-v2 to ONNX
-    Conversion to ONNX command: /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/bin/python -- /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/openvino/model_zoo/internal_scripts/pytorch_to_onnx.py --model-path=models/public/colorization-v2 --model-name=ECCVGenerator --weights=models/public/colorization-v2/ckpt/colorization-v2-eccv16.pth --import-module=model --input-shape=1,1,256,256 --output-file=models/public/colorization-v2/colorization-v2-eccv16.onnx --input-names=data_l --output-names=color_ab
+    Conversion to ONNX command: /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/bin/python -- /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/openvino/model_zoo/internal_scripts/pytorch_to_onnx.py --model-path=models/public/colorization-v2 --model-name=ECCVGenerator --weights=models/public/colorization-v2/ckpt/colorization-v2-eccv16.pth --import-module=model --input-shape=1,1,256,256 --output-file=models/public/colorization-v2/colorization-v2-eccv16.onnx --input-names=data_l --output-names=color_ab
 
 
 
@@ -6346,7 +6227,7 @@ respectively
 
 
     ========== Converting colorization-v2 to IR (FP16)
-    Conversion command: /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/bin/python -- /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/bin/mo --framework=onnx --output_dir=models/public/colorization-v2/FP16 --model_name=colorization-v2 --input=data_l --output=color_ab --input_model=models/public/colorization-v2/colorization-v2-eccv16.onnx '--layout=data_l(NCHW)' '--input_shape=[1, 1, 256, 256]' --compress_to_fp16=True
+    Conversion command: /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/bin/python -- /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/bin/mo --framework=onnx --output_dir=models/public/colorization-v2/FP16 --model_name=colorization-v2 --input=data_l --output=color_ab --input_model=models/public/colorization-v2/colorization-v2-eccv16.onnx '--layout=data_l(NCHW)' '--input_shape=[1, 1, 256, 256]' --compress_to_fp16=True
 
 
 
@@ -6363,8 +6244,10 @@ respectively
 .. parsed-literal::
 
     [ SUCCESS ] Generated IR version 11 model.
-    [ SUCCESS ] XML file: /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/222-vision-image-colorization/models/public/colorization-v2/FP16/colorization-v2.xml
-    [ SUCCESS ] BIN file: /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/222-vision-image-colorization/models/public/colorization-v2/FP16/colorization-v2.bin
+    [ SUCCESS ] XML file: /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/notebooks/222-vision-image-colorization/models/public/colorization-v2/FP16/colorization-v2.xml
+    [ SUCCESS ] BIN file: /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/notebooks/222-vision-image-colorization/models/public/colorization-v2/FP16/colorization-v2.bin
+
+
 
 
 Loading the Model
diff --git a/docs/notebooks/222-vision-image-colorization-with-output_files/index.html.tmp b/docs/notebooks/222-vision-image-colorization-with-output_files/index.html.tmp
deleted file mode 100644
index 9ae7b3db88fc14..00000000000000
--- a/docs/notebooks/222-vision-image-colorization-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,8 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/222-vision-image-colorization-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/222-vision-image-colorization-with-output_files/
../
-222-vision-image-colorization-with-output_21_0.png 26-Jan-2024 01:05              415784
-222-vision-image-colorization-with-output_22_0.png 26-Jan-2024 01:05              284968
-

-
diff --git a/docs/notebooks/223-text-prediction-with-output.rst b/docs/notebooks/223-text-prediction-with-output.rst
index 82be66bd9493da..cbfcc1655da4be 100644
--- a/docs/notebooks/223-text-prediction-with-output.rst
+++ b/docs/notebooks/223-text-prediction-with-output.rst
@@ -115,7 +115,7 @@ used for text generation whereas PersonaGPT is used for Conversation.
 
 .. parsed-literal::
 
-    DEPRECATION: pytorch-lightning 1.6.5 has a non-standard dependency specifier torch>=1.8.*. pip 24.0 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of pytorch-lightning or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063
+    DEPRECATION: pytorch-lightning 1.6.5 has a non-standard dependency specifier torch>=1.8.*. pip 24.1 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of pytorch-lightning or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063
 
 
 .. parsed-literal::
@@ -125,7 +125,7 @@ used for text generation whereas PersonaGPT is used for Conversation.
 
 .. parsed-literal::
 
-    DEPRECATION: pytorch-lightning 1.6.5 has a non-standard dependency specifier torch>=1.8.*. pip 24.0 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of pytorch-lightning or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063
+    DEPRECATION: pytorch-lightning 1.6.5 has a non-standard dependency specifier torch>=1.8.*. pip 24.1 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of pytorch-lightning or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063
 
 
 .. parsed-literal::
@@ -135,7 +135,7 @@ used for text generation whereas PersonaGPT is used for Conversation.
 
 .. parsed-literal::
 
-    DEPRECATION: pytorch-lightning 1.6.5 has a non-standard dependency specifier torch>=1.8.*. pip 24.0 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of pytorch-lightning or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063
+    DEPRECATION: pytorch-lightning 1.6.5 has a non-standard dependency specifier torch>=1.8.*. pip 24.1 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of pytorch-lightning or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063
 
 
 .. parsed-literal::
@@ -231,7 +231,7 @@ consumption.
 
 .. parsed-literal::
 
-    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/transformers/models/gpt2/modeling_gpt2.py:801: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
+    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/transformers/models/gpt2/modeling_gpt2.py:801: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
       if batch_size <= 0:
 
 
@@ -341,14 +341,14 @@ at later stage.
 
 .. parsed-literal::
 
-    2024-01-25 23:39:48.601059: I tensorflow/core/util/port.cc:110] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
-    2024-01-25 23:39:48.632782: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+    2024-02-09 23:53:22.771432: I tensorflow/core/util/port.cc:110] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
+    2024-02-09 23:53:22.804649: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
     To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
 
 
 .. parsed-literal::
 
-    2024-01-25 23:39:49.202605: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+    2024-02-09 23:53:23.373829: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
 
 
 Define Softmax layer
@@ -695,59 +695,59 @@ The style of inference can be selected in the next cell.
 .. parsed-literal::
 
     Person: Hi,How are you?
-    PersonaGPT: i am good. how are you?
+    PersonaGPT: i am alright. do you have any siblings?
 
 
 .. parsed-literal::
 
     Person: What are you doing?
-    PersonaGPT: i'm fine, just getting ready to go for my daily walk. what do you do for fun?
+    PersonaGPT: i am busy with school. do you like to read?
 
 
 .. parsed-literal::
 
     Person: I like to dance,do you?
-    PersonaGPT: i love dancing! what kind of dance do you do?
+    PersonaGPT: i do not. are you a professional dancer?
 
 
 .. parsed-literal::
 
     Person: Can you recommend me some books?
-    PersonaGPT: do you like to read?
+    PersonaGPT: i think the bible is a good starting point
 
 
 .. parsed-literal::
 
     Person: Hi,How are you?
-    PersonaGPT: good, i just came back from a walk
+    PersonaGPT: i'm okay thanks for asking.
 
 
 .. parsed-literal::
 
     Person: What are you doing?
-    PersonaGPT: i'm going to the park soon
+    PersonaGPT: i'm just reading.
 
 
 .. parsed-literal::
 
     Person: I like to dance,do you?
-    PersonaGPT: i love dancing. where do you live?
+    PersonaGPT: i do not but i like reading.
 
 
 .. parsed-literal::
 
     Person: Can you recommend me some books?
-    PersonaGPT: what do you like to read?
+    PersonaGPT: i guess not. i don't have any siblings.
 
 
 .. parsed-literal::
 
     Person: Hi,How are you?
-    PersonaGPT: i like to read too. do you want to get married some day?
+    PersonaGPT: i'm good thanks for asking.
 
 
 .. parsed-literal::
 
     Person: What are you doing?
-    PersonaGPT: going to check some books out right now.
+    PersonaGPT: i am practicing my dance moves.
 
diff --git a/docs/notebooks/224-3D-segmentation-point-clouds-with-output.rst b/docs/notebooks/224-3D-segmentation-point-clouds-with-output.rst
index 36a59f446492c1..d0299a5b08aa74 100644
--- a/docs/notebooks/224-3D-segmentation-point-clouds-with-output.rst
+++ b/docs/notebooks/224-3D-segmentation-point-clouds-with-output.rst
@@ -40,7 +40,7 @@ Table of contents:
 
 .. parsed-literal::
 
-    DEPRECATION: pytorch-lightning 1.6.5 has a non-standard dependency specifier torch>=1.8.*. pip 24.0 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of pytorch-lightning or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063
+    DEPRECATION: pytorch-lightning 1.6.5 has a non-standard dependency specifier torch>=1.8.*. pip 24.1 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of pytorch-lightning or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063
     
 
 .. parsed-literal::
@@ -209,7 +209,7 @@ chair for example.
 
 .. parsed-literal::
 
-    /tmp/ipykernel_817728/2347079344.py:12: UserWarning: No data for colormapping provided via 'c'. Parameters 'cmap' will be ignored
+    /tmp/ipykernel_2848921/2347079344.py:12: UserWarning: No data for colormapping provided via 'c'. Parameters 'cmap' will be ignored
       ax.scatter3D(X, Y, Z, s=5, cmap="jet", marker="o", label='chair')
 
 
@@ -310,7 +310,7 @@ select device from dropdown list for running inference using OpenVINO
 
 .. parsed-literal::
 
-    /tmp/ipykernel_817728/68687822.py:23: UserWarning: No data for colormapping provided via 'c'. Parameters 'cmap' will be ignored
+    /tmp/ipykernel_2848921/68687822.py:23: UserWarning: No data for colormapping provided via 'c'. Parameters 'cmap' will be ignored
       ax.scatter(XCur, YCur, ZCur, s=5, cmap="jet", marker="o", label=classes[i])
 
 
diff --git a/docs/notebooks/224-3D-segmentation-point-clouds-with-output_files/index.html.tmp b/docs/notebooks/224-3D-segmentation-point-clouds-with-output_files/index.html.tmp
deleted file mode 100644
index 102395be00360d..00000000000000
--- a/docs/notebooks/224-3D-segmentation-point-clouds-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,8 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/224-3D-segmentation-point-clouds-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/224-3D-segmentation-point-clouds-with-output_files/
../
-224-3D-segmentation-point-clouds-with-output_11..> 26-Jan-2024 01:05              207243
-224-3D-segmentation-point-clouds-with-output_16..> 26-Jan-2024 01:05              220281
-

-
diff --git a/docs/notebooks/225-stable-diffusion-text-to-image-with-output.rst b/docs/notebooks/225-stable-diffusion-text-to-image-with-output.rst
index 171314d5d347d2..fb64064fa000f3 100644
--- a/docs/notebooks/225-stable-diffusion-text-to-image-with-output.rst
+++ b/docs/notebooks/225-stable-diffusion-text-to-image-with-output.rst
@@ -68,12 +68,12 @@ Prerequisites
 **The following is needed only if you want to use the original model. If
 not, you do not have to do anything. Just run the notebook.**
 
-   **Note**: The original model (for example, ``stable-diffusion-v1-4``)
+   **NOTE**: The original model (for example, ``stable-diffusion-v1-4``)
    requires you to accept the model license before downloading or using
    its weights. Visit the `stable-diffusion-v1-4
    card `__ to
    read and accept the license before you proceed. To use this diffusion
-   model, you must be a registered user in 🤗 Hugging Face Hub. You will
+   model, you must be a registered user in Hugging Face Hub. You will
    need to use an access token for the code below to run. For more
    information on access tokens, refer to `this section of the
    documentation `__.
@@ -1100,7 +1100,7 @@ Now, you can define a text prompt for image generation and run inference
 pipeline. Optionally, you can also change the random generator seed for
 latent state initialization and number of steps.
 
-   **Note**: Consider increasing ``steps`` to get more precise results.
+   **NOTE**: Consider increasing ``steps`` to get more precise results.
    A suggested value is ``50``, but it will take longer time to process.
 
 .. code:: ipython3
diff --git a/docs/notebooks/225-stable-diffusion-text-to-image-with-output_files/index.html.tmp b/docs/notebooks/225-stable-diffusion-text-to-image-with-output_files/index.html.tmp
deleted file mode 100644
index 475c322b6be4de..00000000000000
--- a/docs/notebooks/225-stable-diffusion-text-to-image-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,9 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/225-stable-diffusion-text-to-image-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/225-stable-diffusion-text-to-image-with-output_files/
../
-225-stable-diffusion-text-to-image-with-output_..> 26-Jan-2024 01:05              372482
-225-stable-diffusion-text-to-image-with-output_..> 26-Jan-2024 01:05              928958
-225-stable-diffusion-text-to-image-with-output_..> 26-Jan-2024 01:05              726871
-

-
diff --git a/docs/notebooks/226-yolov7-optimization-with-output.rst b/docs/notebooks/226-yolov7-optimization-with-output.rst
index c4e7fe7d312279..1bae731eaf8d35 100644
--- a/docs/notebooks/226-yolov7-optimization-with-output.rst
+++ b/docs/notebooks/226-yolov7-optimization-with-output.rst
@@ -100,7 +100,7 @@ Prerequisites
 
 .. parsed-literal::
 
-    DEPRECATION: pytorch-lightning 1.6.5 has a non-standard dependency specifier torch>=1.8.*. pip 24.0 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of pytorch-lightning or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063
+    DEPRECATION: pytorch-lightning 1.6.5 has a non-standard dependency specifier torch>=1.8.*. pip 24.1 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of pytorch-lightning or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063
 
 
 .. parsed-literal::
@@ -140,13 +140,13 @@ Receiving objects:   5% (60/1197)
 Receiving objects:   6% (72/1197)
 Receiving objects:   7% (84/1197)
 Receiving objects:   8% (96/1197)
-Receiving objects:   9% (108/1197)
-Receiving objects:  10% (120/1197)
-Receiving objects:  11% (132/1197)
 
 .. parsed-literal::
 
-    Receiving objects:  12% (144/1197)
+    Receiving objects:   9% (108/1197)
+Receiving objects:  10% (120/1197)
+Receiving objects:  11% (132/1197)
+Receiving objects:  12% (144/1197)
 Receiving objects:  13% (156/1197)
 Receiving objects:  14% (168/1197)
 Receiving objects:  15% (180/1197)
@@ -167,211 +167,223 @@ Receiving objects:  25% (300/1197)
 
 .. parsed-literal::
 
-    Receiving objects:  26% (322/1197), 3.57 MiB | 3.47 MiB/s
+    Receiving objects:  26% (322/1197), 3.61 MiB | 3.50 MiB/s
+
+.. parsed-literal::
+
+    Receiving objects:  27% (324/1197), 3.61 MiB | 3.50 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  27% (324/1197), 3.57 MiB | 3.47 MiB/s
+    Receiving objects:  27% (334/1197), 7.27 MiB | 3.52 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  27% (334/1197), 7.24 MiB | 3.51 MiB/s
+    Receiving objects:  27% (334/1197), 10.93 MiB | 3.53 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  27% (334/1197), 10.90 MiB | 3.52 MiB/s
+    Receiving objects:  28% (336/1197), 10.93 MiB | 3.53 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  28% (336/1197), 10.90 MiB | 3.52 MiB/s
+    Receiving objects:  28% (338/1197), 14.60 MiB | 3.53 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  28% (338/1197), 14.57 MiB | 3.53 MiB/s
+    Receiving objects:  28% (339/1197), 18.26 MiB | 3.55 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  28% (339/1197), 18.23 MiB | 3.55 MiB/s
+    Receiving objects:  28% (339/1197), 21.92 MiB | 3.55 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  28% (339/1197), 21.89 MiB | 3.55 MiB/s
+    Receiving objects:  28% (340/1197), 23.75 MiB | 3.55 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  28% (340/1197), 23.73 MiB | 3.55 MiB/s
+    Receiving objects:  28% (343/1197), 29.25 MiB | 3.55 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  28% (343/1197), 29.20 MiB | 3.54 MiB/s
+    Receiving objects:  28% (345/1197), 31.09 MiB | 3.55 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  28% (345/1197), 31.06 MiB | 3.55 MiB/s
+    Receiving objects:  28% (347/1197), 34.76 MiB | 3.55 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  28% (346/1197), 35.67 MiB | 3.35 MiB/s
+    Receiving objects:  29% (348/1197), 38.43 MiB | 3.55 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  29% (348/1197), 37.50 MiB | 3.35 MiB/s
+    Receiving objects:  29% (350/1197), 38.43 MiB | 3.55 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  30% (360/1197), 39.33 MiB | 3.35 MiB/s
-Receiving objects:  31% (372/1197), 39.33 MiB | 3.35 MiB/s
-Receiving objects:  32% (384/1197), 39.33 MiB | 3.35 MiB/s
-Receiving objects:  33% (396/1197), 39.33 MiB | 3.35 MiB/s
+    Receiving objects:  30% (360/1197), 38.43 MiB | 3.55 MiB/s
+Receiving objects:  31% (372/1197), 38.43 MiB | 3.55 MiB/s
+Receiving objects:  32% (384/1197), 38.43 MiB | 3.55 MiB/s
+Receiving objects:  33% (396/1197), 38.43 MiB | 3.55 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  34% (407/1197), 39.33 MiB | 3.35 MiB/s
-Receiving objects:  35% (419/1197), 39.33 MiB | 3.35 MiB/s
-Receiving objects:  36% (431/1197), 39.33 MiB | 3.35 MiB/s
-Receiving objects:  37% (443/1197), 39.33 MiB | 3.35 MiB/s
+    Receiving objects:  34% (407/1197), 38.43 MiB | 3.55 MiB/s
+Receiving objects:  35% (419/1197), 38.43 MiB | 3.55 MiB/s
+Receiving objects:  36% (431/1197), 38.43 MiB | 3.55 MiB/s
+Receiving objects:  37% (443/1197), 38.43 MiB | 3.55 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  38% (455/1197), 39.33 MiB | 3.35 MiB/s
-Receiving objects:  39% (467/1197), 39.33 MiB | 3.35 MiB/s
-Receiving objects:  40% (479/1197), 39.33 MiB | 3.35 MiB/s
-Receiving objects:  41% (491/1197), 39.33 MiB | 3.35 MiB/s
-Receiving objects:  42% (503/1197), 39.33 MiB | 3.35 MiB/s
-Receiving objects:  43% (515/1197), 39.33 MiB | 3.35 MiB/s
+    Receiving objects:  38% (455/1197), 40.26 MiB | 3.55 MiB/s
+Receiving objects:  39% (467/1197), 40.26 MiB | 3.55 MiB/s
+Receiving objects:  40% (479/1197), 40.26 MiB | 3.55 MiB/s
+Receiving objects:  41% (491/1197), 40.26 MiB | 3.55 MiB/s
+Receiving objects:  42% (503/1197), 40.26 MiB | 3.55 MiB/s
+Receiving objects:  43% (515/1197), 40.26 MiB | 3.55 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  43% (523/1197), 41.16 MiB | 3.35 MiB/s
-Receiving objects:  44% (527/1197), 41.16 MiB | 3.35 MiB/s
-Receiving objects:  45% (539/1197), 41.16 MiB | 3.35 MiB/s
-Receiving objects:  46% (551/1197), 41.16 MiB | 3.35 MiB/s
-Receiving objects:  47% (563/1197), 41.16 MiB | 3.35 MiB/s
-Receiving objects:  48% (575/1197), 41.16 MiB | 3.35 MiB/s
-Receiving objects:  49% (587/1197), 41.16 MiB | 3.35 MiB/s
-Receiving objects:  50% (599/1197), 41.16 MiB | 3.35 MiB/s
-Receiving objects:  51% (611/1197), 41.16 MiB | 3.35 MiB/s
-Receiving objects:  52% (623/1197), 41.16 MiB | 3.35 MiB/s
-Receiving objects:  53% (635/1197), 41.16 MiB | 3.35 MiB/s
-Receiving objects:  54% (647/1197), 41.16 MiB | 3.35 MiB/s
-Receiving objects:  55% (659/1197), 41.16 MiB | 3.35 MiB/s
-Receiving objects:  56% (671/1197), 41.16 MiB | 3.35 MiB/s
-Receiving objects:  57% (683/1197), 41.16 MiB | 3.35 MiB/s
-Receiving objects:  58% (695/1197), 41.16 MiB | 3.35 MiB/s
+    Receiving objects:  44% (527/1197), 42.10 MiB | 3.55 MiB/s
+Receiving objects:  45% (539/1197), 42.10 MiB | 3.55 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  59% (707/1197), 41.16 MiB | 3.35 MiB/s
+    Receiving objects:  46% (551/1197), 42.10 MiB | 3.55 MiB/s
+Receiving objects:  47% (563/1197), 42.10 MiB | 3.55 MiB/s
+Receiving objects:  48% (575/1197), 42.10 MiB | 3.55 MiB/s
+Receiving objects:  49% (587/1197), 42.10 MiB | 3.55 MiB/s
+Receiving objects:  50% (599/1197), 42.10 MiB | 3.55 MiB/s
+Receiving objects:  51% (611/1197), 42.10 MiB | 3.55 MiB/s
+Receiving objects:  52% (623/1197), 42.10 MiB | 3.55 MiB/s
+Receiving objects:  53% (635/1197), 42.10 MiB | 3.55 MiB/s
+Receiving objects:  54% (647/1197), 42.10 MiB | 3.55 MiB/s
+Receiving objects:  55% (659/1197), 42.10 MiB | 3.55 MiB/s
+Receiving objects:  56% (671/1197), 42.10 MiB | 3.55 MiB/s
+Receiving objects:  57% (683/1197), 42.10 MiB | 3.55 MiB/s
+Receiving objects:  58% (695/1197), 42.10 MiB | 3.55 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  59% (715/1197), 46.64 MiB | 3.34 MiB/s
+    Receiving objects:  58% (700/1197), 42.10 MiB | 3.55 MiB/s
+Receiving objects:  59% (707/1197), 42.10 MiB | 3.55 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  59% (715/1197), 50.32 MiB | 3.54 MiB/s
+    Receiving objects:  59% (715/1197), 47.60 MiB | 3.55 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  59% (715/1197), 53.98 MiB | 3.54 MiB/s
+    Receiving objects:  59% (715/1197), 51.26 MiB | 3.55 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  59% (715/1197), 55.80 MiB | 3.54 MiB/s
+    Receiving objects:  59% (715/1197), 54.93 MiB | 3.55 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  60% (719/1197), 57.63 MiB | 3.54 MiB/s
-Receiving objects:  61% (731/1197), 57.63 MiB | 3.54 MiB/s
+    Receiving objects:  59% (715/1197), 56.75 MiB | 3.55 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  62% (743/1197), 57.63 MiB | 3.54 MiB/s
-Receiving objects:  63% (755/1197), 57.63 MiB | 3.54 MiB/s
-Receiving objects:  64% (767/1197), 57.63 MiB | 3.54 MiB/s
-Receiving objects:  65% (779/1197), 57.63 MiB | 3.54 MiB/s
-Receiving objects:  66% (791/1197), 57.63 MiB | 3.54 MiB/s
-Receiving objects:  67% (802/1197), 57.63 MiB | 3.54 MiB/s
-Receiving objects:  68% (814/1197), 57.63 MiB | 3.54 MiB/s
-Receiving objects:  69% (826/1197), 57.63 MiB | 3.54 MiB/s
+    Receiving objects:  60% (719/1197), 56.75 MiB | 3.55 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  70% (838/1197), 57.63 MiB | 3.54 MiB/s
-Receiving objects:  71% (850/1197), 57.63 MiB | 3.54 MiB/s
-Receiving objects:  72% (862/1197), 57.63 MiB | 3.54 MiB/s
+    Receiving objects:  61% (731/1197), 56.75 MiB | 3.55 MiB/s
+Receiving objects:  62% (743/1197), 58.59 MiB | 3.55 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  72% (872/1197), 57.63 MiB | 3.54 MiB/s
-Receiving objects:  73% (874/1197), 57.63 MiB | 3.54 MiB/s
-Receiving objects:  74% (886/1197), 59.46 MiB | 3.54 MiB/s
-Receiving objects:  75% (898/1197), 59.46 MiB | 3.54 MiB/s
-Receiving objects:  76% (910/1197), 59.46 MiB | 3.54 MiB/s
-Receiving objects:  77% (922/1197), 59.46 MiB | 3.54 MiB/s
-Receiving objects:  78% (934/1197), 59.46 MiB | 3.54 MiB/s
-Receiving objects:  79% (946/1197), 59.46 MiB | 3.54 MiB/s
-Receiving objects:  80% (958/1197), 59.46 MiB | 3.54 MiB/s
+    Receiving objects:  63% (755/1197), 58.59 MiB | 3.55 MiB/s
+Receiving objects:  64% (767/1197), 58.59 MiB | 3.55 MiB/s
+Receiving objects:  65% (779/1197), 58.59 MiB | 3.55 MiB/s
+Receiving objects:  66% (791/1197), 58.59 MiB | 3.55 MiB/s
+Receiving objects:  67% (802/1197), 58.59 MiB | 3.55 MiB/s
+Receiving objects:  68% (814/1197), 58.59 MiB | 3.55 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  81% (970/1197), 59.46 MiB | 3.54 MiB/s
-Receiving objects:  82% (982/1197), 59.46 MiB | 3.54 MiB/s
-Receiving objects:  83% (994/1197), 59.46 MiB | 3.54 MiB/s
-Receiving objects:  84% (1006/1197), 59.46 MiB | 3.54 MiB/s
+    Receiving objects:  69% (826/1197), 58.59 MiB | 3.55 MiB/s
+Receiving objects:  70% (838/1197), 58.59 MiB | 3.55 MiB/s
+Receiving objects:  71% (850/1197), 58.59 MiB | 3.55 MiB/s
+Receiving objects:  72% (862/1197), 58.59 MiB | 3.55 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  85% (1018/1197), 59.46 MiB | 3.54 MiB/s
-Receiving objects:  86% (1030/1197), 59.46 MiB | 3.54 MiB/s
-Receiving objects:  87% (1042/1197), 59.46 MiB | 3.54 MiB/s
-Receiving objects:  88% (1054/1197), 59.46 MiB | 3.54 MiB/s
-Receiving objects:  89% (1066/1197), 59.46 MiB | 3.54 MiB/s
-Receiving objects:  90% (1078/1197), 59.46 MiB | 3.54 MiB/s
-Receiving objects:  91% (1090/1197), 59.46 MiB | 3.54 MiB/s
-Receiving objects:  92% (1102/1197), 59.46 MiB | 3.54 MiB/s
-Receiving objects:  93% (1114/1197), 59.46 MiB | 3.54 MiB/s
-Receiving objects:  94% (1126/1197), 59.46 MiB | 3.54 MiB/s
-Receiving objects:  95% (1138/1197), 59.46 MiB | 3.54 MiB/s
-Receiving objects:  96% (1150/1197), 59.46 MiB | 3.54 MiB/s
-Receiving objects:  97% (1162/1197), 59.46 MiB | 3.54 MiB/s
+    Receiving objects:  73% (874/1197), 58.59 MiB | 3.55 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  97% (1172/1197), 63.14 MiB | 3.55 MiB/s
+    Receiving objects:  74% (886/1197), 58.59 MiB | 3.55 MiB/s
+Receiving objects:  75% (898/1197), 58.59 MiB | 3.55 MiB/s
+Receiving objects:  76% (910/1197), 58.59 MiB | 3.55 MiB/s
+Receiving objects:  77% (922/1197), 58.59 MiB | 3.55 MiB/s
+Receiving objects:  78% (934/1197), 58.59 MiB | 3.55 MiB/s
+Receiving objects:  79% (946/1197), 58.59 MiB | 3.55 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  97% (1172/1197), 66.80 MiB | 3.55 MiB/s
+    Receiving objects:  80% (958/1197), 58.59 MiB | 3.55 MiB/s
+Receiving objects:  81% (970/1197), 58.59 MiB | 3.55 MiB/s
+Receiving objects:  82% (982/1197), 58.59 MiB | 3.55 MiB/s
+Receiving objects:  83% (994/1197), 58.59 MiB | 3.55 MiB/s
+Receiving objects:  84% (1006/1197), 58.59 MiB | 3.55 MiB/s
+Receiving objects:  85% (1018/1197), 58.59 MiB | 3.55 MiB/s
+Receiving objects:  86% (1030/1197), 58.59 MiB | 3.55 MiB/s
+Receiving objects:  87% (1042/1197), 58.59 MiB | 3.55 MiB/s
+Receiving objects:  88% (1054/1197), 58.59 MiB | 3.55 MiB/s
+Receiving objects:  89% (1066/1197), 58.59 MiB | 3.55 MiB/s
+Receiving objects:  90% (1078/1197), 58.59 MiB | 3.55 MiB/s
+Receiving objects:  91% (1090/1197), 58.59 MiB | 3.55 MiB/s
+Receiving objects:  92% (1102/1197), 58.59 MiB | 3.55 MiB/s
+Receiving objects:  93% (1114/1197), 58.59 MiB | 3.55 MiB/s
+Receiving objects:  94% (1126/1197), 58.59 MiB | 3.55 MiB/s
+Receiving objects:  95% (1138/1197), 58.59 MiB | 3.55 MiB/s
+Receiving objects:  96% (1150/1197), 58.59 MiB | 3.55 MiB/s
+Receiving objects:  97% (1162/1197), 58.59 MiB | 3.55 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  97% (1172/1197), 70.46 MiB | 3.55 MiB/s
+    Receiving objects:  97% (1172/1197), 60.42 MiB | 3.55 MiB/s
 
 .. parsed-literal::
 
-    Receiving objects:  97% (1172/1197), 74.13 MiB | 3.55 MiB/s
-remote: Total 1197 (delta 0), reused 0 (delta 0), pack-reused 1197
-    Receiving objects:  98% (1174/1197), 74.13 MiB | 3.55 MiB/s
-Receiving objects:  99% (1186/1197), 74.13 MiB | 3.55 MiB/s
-Receiving objects: 100% (1197/1197), 74.13 MiB | 3.55 MiB/s
-Receiving objects: 100% (1197/1197), 74.23 MiB | 3.50 MiB/s, done.
+    Receiving objects:  97% (1172/1197), 64.08 MiB | 3.55 MiB/s
+
+.. parsed-literal::
+
+    Receiving objects:  97% (1172/1197), 67.75 MiB | 3.55 MiB/s
+
+.. parsed-literal::
+
+    Receiving objects:  97% (1172/1197), 71.41 MiB | 3.55 MiB/s
+
+.. parsed-literal::
+
+    remote: Total 1197 (delta 0), reused 0 (delta 0), pack-reused 1197
+    Receiving objects:  98% (1174/1197), 73.25 MiB | 3.55 MiB/s
+Receiving objects:  99% (1186/1197), 73.25 MiB | 3.55 MiB/s
+Receiving objects: 100% (1197/1197), 73.25 MiB | 3.55 MiB/s
+Receiving objects: 100% (1197/1197), 74.23 MiB | 3.54 MiB/s, done.
     Resolving deltas:   0% (0/520)
-Resolving deltas:   1% (8/520)
+Resolving deltas:   1% (9/520)
 Resolving deltas:   2% (15/520)
-Resolving deltas:   3% (17/520)
+
+.. parsed-literal::
+
+    Resolving deltas:   3% (17/520)
 Resolving deltas:   4% (21/520)
 Resolving deltas:   5% (26/520)
-Resolving deltas:   6% (33/520)
+Resolving deltas:   6% (32/520)
 Resolving deltas:   8% (42/520)
 Resolving deltas:   9% (50/520)
 Resolving deltas:  10% (52/520)
 Resolving deltas:  11% (58/520)
 Resolving deltas:  13% (68/520)
-
-.. parsed-literal::
-
-    Resolving deltas:  14% (73/520)
+Resolving deltas:  14% (73/520)
 Resolving deltas:  16% (87/520)
 Resolving deltas:  17% (91/520)
 Resolving deltas:  21% (113/520)
@@ -401,36 +413,34 @@ Resolving deltas:  71% (371/520)
 Resolving deltas:  72% (375/520)
 Resolving deltas:  73% (380/520)
 Resolving deltas:  74% (385/520)
-Resolving deltas:  75% (391/520)
+Resolving deltas:  75% (394/520)
 Resolving deltas:  76% (396/520)
 Resolving deltas:  77% (401/520)
 Resolving deltas:  78% (406/520)
-Resolving deltas:  79% (414/520)
+Resolving deltas:  80% (416/520)
 Resolving deltas:  81% (424/520)
-Resolving deltas:  82% (429/520)
-Resolving deltas:  83% (433/520)
+Resolving deltas:  83% (436/520)
 Resolving deltas:  84% (437/520)
-Resolving deltas:  85% (443/520)
-Resolving deltas:  86% (448/520)
-Resolving deltas:  87% (453/520)
-Resolving deltas:  88% (458/520)
-Resolving deltas:  89% (465/520)
+Resolving deltas:  85% (442/520)
+Resolving deltas:  86% (450/520)
+Resolving deltas:  87% (454/520)
+Resolving deltas:  89% (463/520)
 Resolving deltas:  90% (469/520)
-Resolving deltas:  91% (474/520)
-Resolving deltas:  92% (482/520)
-Resolving deltas:  93% (486/520)
+Resolving deltas:  91% (477/520)
+Resolving deltas:  93% (488/520)
 Resolving deltas:  94% (489/520)
 Resolving deltas:  95% (494/520)
-Resolving deltas:  96% (500/520)
-Resolving deltas:  97% (505/520)
-Resolving deltas:  99% (519/520)
+Resolving deltas:  96% (502/520)
+Resolving deltas:  97% (507/520)
+Resolving deltas:  98% (514/520)
+Resolving deltas:  99% (515/520)
 Resolving deltas: 100% (520/520)
 Resolving deltas: 100% (520/520), done.
 
 
 .. parsed-literal::
 
-    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/226-yolov7-optimization/yolov7
+    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/notebooks/226-yolov7-optimization/yolov7
 
 
 .. code:: ipython3
@@ -455,7 +465,7 @@ Resolving deltas: 100% (520/520), done.
 
 .. parsed-literal::
 
-    PosixPath('/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/notebooks/226-yolov7-optimization/yolov7/model/yolov7-tiny.pt')
+    PosixPath('/opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/notebooks/226-yolov7-optimization/yolov7/model/yolov7-tiny.pt')
 
 
 
@@ -475,10 +485,6 @@ result,
 .. parsed-literal::
 
     Namespace(agnostic_nms=False, augment=False, classes=None, conf_thres=0.25, device='', exist_ok=False, img_size=640, iou_thres=0.45, name='exp', no_trace=False, nosave=False, project='runs/detect', save_conf=False, save_txt=False, source='inference/images/horses.jpg', update=False, view_img=False, weights=['model/yolov7-tiny.pt'])
-
-
-.. parsed-literal::
-
     YOLOR 🚀 v0.1-128-ga207844 torch 1.13.1+cpu CPU
 
 
@@ -503,9 +509,13 @@ result,
 
 .. parsed-literal::
 
-    5 horses, Done. (69.8ms) Inference, (0.8ms) NMS
+    5 horses, Done. (70.4ms) Inference, (0.8ms) NMS
+
+
+.. parsed-literal::
+
      The image with the result is saved in: runs/detect/exp/horses.jpg
-    Done. (0.083s)
+    Done. (0.084s)
 
 
 .. code:: ipython3
@@ -607,10 +617,6 @@ an end2end ONNX model, you can check this
 
     YOLOR 🚀 v0.1-128-ga207844 torch 1.13.1+cpu CPU
 
-
-
-.. parsed-literal::
-
     Fusing layers...
 
 
@@ -644,7 +650,7 @@ an end2end ONNX model, you can check this
 
     ONNX export success, saved as model/yolov7-tiny.onnx
 
-    Export complete (2.38s). Visualize with https://github.com/lutzroeder/netron.
+    Export complete (2.36s). Visualize with https://github.com/lutzroeder/netron.
 
 
 Convert ONNX Model to OpenVINO Intermediate Representation (IR)
@@ -977,92 +983,93 @@ Create dataloader
 .. parsed-literal::
 
 
-   Scanning images:   0%|          | 0/5000 [00:00
 
 
 
 
+.. raw:: html
+
+    
+    

 
 
 
 
 .. parsed-literal::
 
-    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/nncf/experimental/tensor/tensor.py:84: RuntimeWarning: invalid value encountered in multiply
-      return Tensor(self.data * unwrap_tensor_data(other))
-
+    Output()
 
 
 .. parsed-literal::
 
-    Output()
+    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/nncf/experimental/tensor/tensor.py:84: RuntimeWarning: invalid value encountered in multiply
+      return Tensor(self.data * unwrap_tensor_data(other))
 
 
 
-.. raw:: html
 
-    

 
 
 
 
+.. raw:: html
 
+    
+    

 
 
 
@@ -1478,7 +1487,7 @@ models.
     [ WARNING ] Performance hint was not explicitly specified in command line. Device(AUTO) performance hint will be set to PerformanceMode.THROUGHPUT.
     [Step 4/11] Reading model files
     [ INFO ] Loading model files
-    [ INFO ] Read model took 13.23 ms
+    [ INFO ] Read model took 13.39 ms
     [ INFO ] Original model I/O parameters:
     [ INFO ] Model inputs:
     [ INFO ]     images (node: images) : f32 / [...] / [1,3,640,640]
@@ -1496,7 +1505,7 @@ models.
 
 .. parsed-literal::
 
-    [ INFO ] Compile model took 292.99 ms
+    [ INFO ] Compile model took 272.70 ms
     [Step 8/11] Querying optimal runtime parameters
     [ INFO ] Model:
     [ INFO ]   NETWORK_NAME: torch_jit
@@ -1532,25 +1541,21 @@ models.
 
     [Step 10/11] Measuring performance (Start inference asynchronously, 6 inference requests, limits: 120000 ms duration)
     [ INFO ] Benchmarking in inference only mode (inputs filling are not included in measurement loop).
-
-
-.. parsed-literal::
-
-    [ INFO ] First inference took 43.08 ms
+    [ INFO ] First inference took 43.02 ms
 
 
 .. parsed-literal::
 
     [Step 11/11] Dumping statistics report
     [ INFO ] Execution Devices:['CPU']
-    [ INFO ] Count:            11622 iterations
-    [ INFO ] Duration:         120099.01 ms
+    [ INFO ] Count:            11586 iterations
+    [ INFO ] Duration:         120047.32 ms
     [ INFO ] Latency:
-    [ INFO ]    Median:        61.70 ms
-    [ INFO ]    Average:       61.87 ms
-    [ INFO ]    Min:           39.98 ms
-    [ INFO ]    Max:           89.36 ms
-    [ INFO ] Throughput:   96.77 FPS
+    [ INFO ]    Median:        61.86 ms
+    [ INFO ]    Average:       62.03 ms
+    [ INFO ]    Min:           44.24 ms
+    [ INFO ]    Max:           86.89 ms
+    [ INFO ] Throughput:   96.51 FPS
 
 
 .. code:: ipython3
@@ -1577,7 +1582,7 @@ models.
     [ WARNING ] Performance hint was not explicitly specified in command line. Device(AUTO) performance hint will be set to PerformanceMode.THROUGHPUT.
     [Step 4/11] Reading model files
     [ INFO ] Loading model files
-    [ INFO ] Read model took 21.77 ms
+    [ INFO ] Read model took 22.28 ms
     [ INFO ] Original model I/O parameters:
     [ INFO ] Model inputs:
     [ INFO ]     images (node: images) : f32 / [...] / [1,3,640,640]
@@ -1595,7 +1600,7 @@ models.
 
 .. parsed-literal::
 
-    [ INFO ] Compile model took 472.19 ms
+    [ INFO ] Compile model took 489.58 ms
     [Step 8/11] Querying optimal runtime parameters
     [ INFO ] Model:
     [ INFO ]   NETWORK_NAME: torch_jit
@@ -1625,25 +1630,25 @@ models.
     [Step 9/11] Creating infer requests and preparing input tensors
     [ WARNING ] No input files were given for input 'images'!. This input will be filled with random values!
     [ INFO ] Fill input 'images' with random values
-    [Step 10/11] Measuring performance (Start inference asynchronously, 6 inference requests, limits: 120000 ms duration)
-    [ INFO ] Benchmarking in inference only mode (inputs filling are not included in measurement loop).
 
 
 .. parsed-literal::
 
-    [ INFO ] First inference took 24.62 ms
+    [Step 10/11] Measuring performance (Start inference asynchronously, 6 inference requests, limits: 120000 ms duration)
+    [ INFO ] Benchmarking in inference only mode (inputs filling are not included in measurement loop).
+    [ INFO ] First inference took 25.89 ms
 
 
 .. parsed-literal::
 
     [Step 11/11] Dumping statistics report
     [ INFO ] Execution Devices:['CPU']
-    [ INFO ] Count:            33126 iterations
-    [ INFO ] Duration:         120024.58 ms
+    [ INFO ] Count:            33210 iterations
+    [ INFO ] Duration:         120019.44 ms
     [ INFO ] Latency:
-    [ INFO ]    Median:        21.54 ms
-    [ INFO ]    Average:       21.62 ms
-    [ INFO ]    Min:           15.29 ms
-    [ INFO ]    Max:           42.94 ms
-    [ INFO ] Throughput:   275.99 FPS
+    [ INFO ]    Median:        21.49 ms
+    [ INFO ]    Average:       21.57 ms
+    [ INFO ]    Min:           15.74 ms
+    [ INFO ]    Max:           43.27 ms
+    [ INFO ] Throughput:   276.71 FPS
 
diff --git a/docs/notebooks/226-yolov7-optimization-with-output_files/226-yolov7-optimization-with-output_10_0.jpg b/docs/notebooks/226-yolov7-optimization-with-output_files/226-yolov7-optimization-with-output_10_0.jpg
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+++ b/docs/notebooks/226-yolov7-optimization-with-output_files/226-yolov7-optimization-with-output_10_0.jpg
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+++ b/docs/notebooks/226-yolov7-optimization-with-output_files/226-yolov7-optimization-with-output_10_0.png
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+++ b/docs/notebooks/226-yolov7-optimization-with-output_files/226-yolov7-optimization-with-output_27_0.jpg
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+++ b/docs/notebooks/226-yolov7-optimization-with-output_files/226-yolov7-optimization-with-output_44_0.png
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diff --git a/docs/notebooks/226-yolov7-optimization-with-output_files/index.html.tmp b/docs/notebooks/226-yolov7-optimization-with-output_files/index.html.tmp
deleted file mode 100644
index 665744b896e552..00000000000000
--- a/docs/notebooks/226-yolov7-optimization-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,12 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/226-yolov7-optimization-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/226-yolov7-optimization-with-output_files/
../
-226-yolov7-optimization-with-output_10_0.jpg       26-Jan-2024 01:04               63540
-226-yolov7-optimization-with-output_10_0.png       26-Jan-2024 01:04              565687
-226-yolov7-optimization-with-output_27_0.jpg       26-Jan-2024 01:04               62771
-226-yolov7-optimization-with-output_27_0.png       26-Jan-2024 01:04              572556
-226-yolov7-optimization-with-output_44_0.jpg       26-Jan-2024 01:04               62806
-226-yolov7-optimization-with-output_44_0.png       26-Jan-2024 01:04              572217
-

-
diff --git a/docs/notebooks/227-whisper-convert-with-output.rst b/docs/notebooks/227-whisper-convert-with-output.rst
index 0c4e6c896b5a7e..b427377f942c93 100644
--- a/docs/notebooks/227-whisper-convert-with-output.rst
+++ b/docs/notebooks/227-whisper-convert-with-output.rst
@@ -19,10 +19,12 @@ card `__ and
 GitHub `repository `__.
 
 In this notebook, we will use Whisper with OpenVINO to generate
-subtitles in a sample video. Notebook contains the following steps: 1.
-Download the model. 2. Instantiate the PyTorch model pipeline. 3.
-Convert model to OpenVINO IR, using model conversion API. 4. Run the
-Whisper pipeline with OpenVINO models.
+subtitles in a sample video. Notebook contains the following steps:
+
+1. Download the model.
+2. Instantiate the PyTorch model pipeline.
+3. Convert model to OpenVINO IR, using model conversion API.
+4. Run the Whisper pipeline with OpenVINO models.
 
 Table of contents:
 ^^^^^^^^^^^^^^^^^^
@@ -320,8 +322,7 @@ To run the PyTorch Whisper model, we just need to call the
 original model pipeline for audio transcribing after replacing the
 original models with OpenVINO IR versions.
 
-Select inference device
---------------------------
+### Select inference device
 
 select device from dropdown list for running inference using OpenVINO
 
@@ -565,7 +566,7 @@ Interactive demo
 
 .. .. raw:: html
 
-..     

+..    

 
 
 .. parsed-literal::
diff --git a/docs/notebooks/227-whisper-nncf-quantize-with-output.rst b/docs/notebooks/227-whisper-nncf-quantize-with-output.rst
index 57bb04a89190f9..30317d9cc17dfb 100644
--- a/docs/notebooks/227-whisper-nncf-quantize-with-output.rst
+++ b/docs/notebooks/227-whisper-nncf-quantize-with-output.rst
@@ -23,12 +23,10 @@ Table of contents:
 ^^^^^^^^^^^^^^^^^^
 
 -  `Prerequisites <#prerequisites>`__
--  `Create and initialize quantization
-    <#create-and-initialize-quantization-#0>`__
+-  `Create and initialize quantization <#create-and-initialize-quantization-#0>`__
 
    -  `Prepare calibration datasets <#prepare-calibration-datasets>`__
-   -  `Quantize Whisper encoder and decoder
-      models <#quantize-whisper-encoder-and-decoder-models>`__
+   -  `Quantize Whisper encoder and decoder models <#quantize-whisper-encoder-and-decoder-models>`__
 
 -  `Transcribe video with quantized OpenVINO
    model <#transcribe-video-with-quantized-openvino-model>`__
@@ -137,7 +135,7 @@ Select the task for the model:
 
 
 Create and initialize quantization
-------------------------------------
+----------------------------------
 
 `NNCF `__ enables
 post-training quantization by adding the quantization layers into the
@@ -345,6 +343,8 @@ and save the quantized IRs after that.
 
 
 
+
+
 Transcribe video with quantized OpenVINO model
 ----------------------------------------------
 
diff --git a/docs/notebooks/228-clip-zero-shot-convert-with-output_files/index.html.tmp b/docs/notebooks/228-clip-zero-shot-convert-with-output_files/index.html.tmp
deleted file mode 100644
index 6a6b3614bccc8c..00000000000000
--- a/docs/notebooks/228-clip-zero-shot-convert-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,8 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/228-clip-zero-shot-convert-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/228-clip-zero-shot-convert-with-output_files/
../
-228-clip-zero-shot-convert-with-output_12_0.png    26-Jan-2024 01:05              464100
-228-clip-zero-shot-convert-with-output_5_0.png     26-Jan-2024 01:05              464100
-

-
diff --git a/docs/notebooks/228-clip-zero-shot-quantize-with-output_files/index.html.tmp b/docs/notebooks/228-clip-zero-shot-quantize-with-output_files/index.html.tmp
deleted file mode 100644
index 321fcdbf811511..00000000000000
--- a/docs/notebooks/228-clip-zero-shot-quantize-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,7 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/228-clip-zero-shot-quantize-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/228-clip-zero-shot-quantize-with-output_files/
../
-228-clip-zero-shot-quantize-with-output_16_0.png   26-Jan-2024 01:05              464748
-

-
diff --git a/docs/notebooks/229-distilbert-sequence-classification-with-output.rst b/docs/notebooks/229-distilbert-sequence-classification-with-output.rst
index d9b584d9685636..62dbb164e01724 100644
--- a/docs/notebooks/229-distilbert-sequence-classification-with-output.rst
+++ b/docs/notebooks/229-distilbert-sequence-classification-with-output.rst
@@ -36,42 +36,46 @@ Imports
 .. parsed-literal::
 
     Looking in indexes: https://pypi.org/simple, https://download.pytorch.org/whl/cpu
-    Requirement already satisfied: openvino>=2023.1.0 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (2023.3.0)
-    Requirement already satisfied: transformers in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (4.37.1)
-    Requirement already satisfied: numpy>=1.16.6 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from openvino>=2023.1.0) (1.23.5)
-    Requirement already satisfied: openvino-telemetry>=2023.2.1 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from openvino>=2023.1.0) (2023.2.1)
+    Requirement already satisfied: openvino>=2023.1.0 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (2023.3.0)
+    Requirement already satisfied: transformers in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (4.37.2)
+    Requirement already satisfied: numpy>=1.16.6 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from openvino>=2023.1.0) (1.23.5)
+    Requirement already satisfied: openvino-telemetry>=2023.2.1 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from openvino>=2023.1.0) (2023.2.1)
 
 
 .. parsed-literal::
 
-    Requirement already satisfied: filelock in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from transformers) (3.13.1)
-    Requirement already satisfied: huggingface-hub<1.0,>=0.19.3 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from transformers) (0.20.3)
-    Requirement already satisfied: packaging>=20.0 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from transformers) (23.2)
-    Requirement already satisfied: pyyaml>=5.1 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from transformers) (6.0.1)
-    Requirement already satisfied: regex!=2019.12.17 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from transformers) (2023.12.25)
-    Requirement already satisfied: requests in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from transformers) (2.31.0)
-    Requirement already satisfied: tokenizers<0.19,>=0.14 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from transformers) (0.15.1)
-    Requirement already satisfied: safetensors>=0.3.1 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from transformers) (0.4.2)
-    Requirement already satisfied: tqdm>=4.27 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from transformers) (4.66.1)
+    Requirement already satisfied: filelock in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from transformers) (3.13.1)
+    Requirement already satisfied: huggingface-hub<1.0,>=0.19.3 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from transformers) (0.20.3)
+    Requirement already satisfied: packaging>=20.0 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from transformers) (23.2)
+    Requirement already satisfied: pyyaml>=5.1 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from transformers) (6.0.1)
 
 
 .. parsed-literal::
 
-    Requirement already satisfied: fsspec>=2023.5.0 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from huggingface-hub<1.0,>=0.19.3->transformers) (2023.10.0)
-    Requirement already satisfied: typing-extensions>=3.7.4.3 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from huggingface-hub<1.0,>=0.19.3->transformers) (4.9.0)
+    Requirement already satisfied: regex!=2019.12.17 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from transformers) (2023.12.25)
+    Requirement already satisfied: requests in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from transformers) (2.31.0)
+    Requirement already satisfied: tokenizers<0.19,>=0.14 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from transformers) (0.15.1)
+    Requirement already satisfied: safetensors>=0.4.1 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from transformers) (0.4.2)
+    Requirement already satisfied: tqdm>=4.27 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from transformers) (4.66.1)
 
 
 .. parsed-literal::
 
-    Requirement already satisfied: charset-normalizer<4,>=2 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from requests->transformers) (3.3.2)
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-    Requirement already satisfied: urllib3<3,>=1.21.1 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from requests->transformers) (2.1.0)
-    Requirement already satisfied: certifi>=2017.4.17 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from requests->transformers) (2023.11.17)
+    Requirement already satisfied: fsspec>=2023.5.0 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from huggingface-hub<1.0,>=0.19.3->transformers) (2023.10.0)
+    Requirement already satisfied: typing-extensions>=3.7.4.3 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from huggingface-hub<1.0,>=0.19.3->transformers) (4.9.0)
 
 
 .. parsed-literal::
 
-    DEPRECATION: pytorch-lightning 1.6.5 has a non-standard dependency specifier torch>=1.8.*. pip 24.0 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of pytorch-lightning or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063
+    Requirement already satisfied: charset-normalizer<4,>=2 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from requests->transformers) (3.3.2)
+    Requirement already satisfied: idna<4,>=2.5 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from requests->transformers) (3.6)
+    Requirement already satisfied: urllib3<3,>=1.21.1 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from requests->transformers) (2.2.0)
+    Requirement already satisfied: certifi>=2017.4.17 in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (from requests->transformers) (2024.2.2)
+
+
+.. parsed-literal::
+
+    DEPRECATION: pytorch-lightning 1.6.5 has a non-standard dependency specifier torch>=1.8.*. pip 24.1 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of pytorch-lightning or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063
     
 
 .. parsed-literal::
@@ -159,7 +163,7 @@ optimal execution on end-point target devices.
 
 .. parsed-literal::
 
-    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/transformers/models/distilbert/modeling_distilbert.py:246: TracerWarning: torch.tensor results are registered as constants in the trace. You can safely ignore this warning if you use this function to create tensors out of constant variables that would be the same every time you call this function. In any other case, this might cause the trace to be incorrect.
+    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/transformers/models/distilbert/modeling_distilbert.py:246: TracerWarning: torch.tensor results are registered as constants in the trace. You can safely ignore this warning if you use this function to create tensors out of constant variables that would be the same every time you call this function. In any other case, this might cause the trace to be incorrect.
       mask, torch.tensor(torch.finfo(scores.dtype).min)
 
 
diff --git a/docs/notebooks/230-yolov8-instance-segmentation-with-output.rst b/docs/notebooks/230-yolov8-instance-segmentation-with-output.rst
index 19e3406f643b14..a1ae017a36e936 100644
--- a/docs/notebooks/230-yolov8-instance-segmentation-with-output.rst
+++ b/docs/notebooks/230-yolov8-instance-segmentation-with-output.rst
@@ -599,7 +599,7 @@ in the YOLOv8 repo, we also need to download annotations in the format
 used by the author of the model, for use with the original model
 evaluation function.
 
-   **Note**: The initial dataset download may take a few minutes to
+   **NOTE**: The initial dataset download may take a few minutes to
    complete. The download speed will vary depending on the quality of
    your internet connection.
 
@@ -760,13 +760,13 @@ validator class instance.
 After definition test function and validator creation, we are ready for
 getting accuracy metrics.
 
-**Note**: Model evaluation is time consuming
-process and can take several minutes, depending on the hardware. For
-reducing calculation time, we define ``num_samples`` parameter with
-evaluation subset size, but in this case, accuracy can be noncomparable
-with originally reported by the authors of the model, due to validation
-subset difference. *To validate the models on the full dataset set
-``NUM_TEST_SAMPLES = None``.*
+   **NOTE**: Model evaluation is time consuming
+   process and can take several minutes, depending on the hardware. For
+   reducing calculation time, we define ``num_samples`` parameter with
+   evaluation subset size, but in this case, accuracy can be noncomparable
+   with originally reported by the authors of the model, due to validation
+   subset difference. *To validate the models on the full dataset set
+   ``NUM_TEST_SAMPLES = None``.*
 
 .. code:: ipython3
 
@@ -871,7 +871,7 @@ asymmetric quantization of activations. For more accurate results, we
 should keep the operation in the postprocessing subgraph in floating
 point precision, using the ``ignored_scope`` parameter.
 
-   **Note**: Model post-training quantization is time-consuming process.
+   **NOTE**: Model post-training quantization is time-consuming process.
    Be patient, it can take several minutes depending on your hardware.
 
 .. code:: ipython3
@@ -993,7 +993,7 @@ Tool `__
 to measure the inference performance of the ``FP32`` and ``INT8``
 models.
 
-   **Note**: For more accurate performance, it is recommended to run
+   **NOTE**: For more accurate performance, it is recommended to run
    ``benchmark_app`` in a terminal/command prompt after closing other
    applications. Run
    ``benchmark_app -m  -d CPU -shape ""`` to
diff --git a/docs/notebooks/230-yolov8-instance-segmentation-with-output_files/index.html.tmp b/docs/notebooks/230-yolov8-instance-segmentation-with-output_files/index.html.tmp
deleted file mode 100644
index 487e53a89be868..00000000000000
--- a/docs/notebooks/230-yolov8-instance-segmentation-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,13 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/230-yolov8-instance-segmentation-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/230-yolov8-instance-segmentation-with-output_files/
../
-230-yolov8-instance-segmentation-with-output_11..> 26-Jan-2024 01:05               81079
-230-yolov8-instance-segmentation-with-output_11..> 26-Jan-2024 01:05              790288
-230-yolov8-instance-segmentation-with-output_22..> 26-Jan-2024 01:05              104433
-230-yolov8-instance-segmentation-with-output_22..> 26-Jan-2024 01:05              919053
-230-yolov8-instance-segmentation-with-output_44..> 26-Jan-2024 01:05              103935
-230-yolov8-instance-segmentation-with-output_44..> 26-Jan-2024 01:05              918316
-230-yolov8-instance-segmentation-with-output_60..> 26-Jan-2024 01:05              495438
-

-
diff --git a/docs/notebooks/230-yolov8-keypoint-detection-with-output.rst b/docs/notebooks/230-yolov8-keypoint-detection-with-output.rst
index 9395ad299379de..8728bc40966051 100644
--- a/docs/notebooks/230-yolov8-keypoint-detection-with-output.rst
+++ b/docs/notebooks/230-yolov8-keypoint-detection-with-output.rst
@@ -588,7 +588,7 @@ in the YOLOv8 repo, we also need to download annotations in the format
 used by the author of the model, for use with the original model
 evaluation function.
 
-   **Note**: The initial dataset download may take a few minutes to
+   **NOTE**: The initial dataset download may take a few minutes to
    complete. The download speed will vary depending on the quality of
    your internet connection.
 
@@ -750,13 +750,13 @@ validator class instance.
 After definition test function and validator creation, we are ready for
 getting accuracy metrics.
 
-**Note**: Model evaluation is time consuming
-process and can take several minutes, depending on the hardware. For
-reducing calculation time, we define ``num_samples`` parameter with
-evaluation subset size, but in this case, accuracy can be noncomparable
-with originally reported by the authors of the model, due to validation
-subset difference. *To validate the models on the full dataset set
-``NUM_TEST_SAMPLES = None``.*
+   **NOTE**: Model evaluation is time consuming
+   process and can take several minutes, depending on the hardware. For
+   reducing calculation time, we define ``num_samples`` parameter with
+   evaluation subset size, but in this case, accuracy can be noncomparable
+   with originally reported by the authors of the model, due to validation
+   subset difference. *To validate the models on the full dataset set
+   ``NUM_TEST_SAMPLES = None``.*
 
 .. code:: ipython3
 
@@ -859,7 +859,7 @@ asymmetric quantization of activations. For more accurate results, we
 should keep the operation in the postprocessing subgraph in floating
 point precision, using the ``ignored_scope`` parameter.
 
-   **Note**: Model post-training quantization is time-consuming process.
+   **NOTE**: Model post-training quantization is time-consuming process.
    Be patient, it can take several minutes depending on your hardware.
 
 .. code:: ipython3
@@ -985,7 +985,7 @@ Tool `__
 to measure the inference performance of the ``FP32`` and ``INT8``
 models.
 
-   **Note**: For more accurate performance, it is recommended to run
+   **NOTE**: For more accurate performance, it is recommended to run
    ``benchmark_app`` in a terminal/command prompt after closing other
    applications. Run
    ``benchmark_app -m  -d CPU -shape ""`` to
diff --git a/docs/notebooks/230-yolov8-keypoint-detection-with-output_files/index.html.tmp b/docs/notebooks/230-yolov8-keypoint-detection-with-output_files/index.html.tmp
deleted file mode 100644
index a5b738fdce3f0f..00000000000000
--- a/docs/notebooks/230-yolov8-keypoint-detection-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,13 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/230-yolov8-keypoint-detection-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/230-yolov8-keypoint-detection-with-output_files/
../
-230-yolov8-keypoint-detection-with-output_11_1.jpg 26-Jan-2024 01:05               58622
-230-yolov8-keypoint-detection-with-output_11_1.png 26-Jan-2024 01:05              581068
-230-yolov8-keypoint-detection-with-output_22_0.jpg 26-Jan-2024 01:05               58280
-230-yolov8-keypoint-detection-with-output_22_0.png 26-Jan-2024 01:04              584143
-230-yolov8-keypoint-detection-with-output_46_0.jpg 26-Jan-2024 01:05               58058
-230-yolov8-keypoint-detection-with-output_46_0.png 26-Jan-2024 01:05              584051
-230-yolov8-keypoint-detection-with-output_62_0.png 26-Jan-2024 01:05              490879
-

-
diff --git a/docs/notebooks/230-yolov8-object-detection-with-output.rst b/docs/notebooks/230-yolov8-object-detection-with-output.rst
index fb874bcecd6ba9..9558abba9422c8 100644
--- a/docs/notebooks/230-yolov8-object-detection-with-output.rst
+++ b/docs/notebooks/230-yolov8-object-detection-with-output.rst
@@ -567,7 +567,7 @@ in the YOLOv8 repo, we also need to download annotations in the format
 used by the author of the model, for use with the original model
 evaluation function.
 
-   **Note**: The initial dataset download may take a few minutes to
+   **NOTE**: The initial dataset download may take a few minutes to
    complete. The download speed will vary depending on the quality of
    your internet connection.
 
@@ -724,13 +724,13 @@ validator class instance.
 After definition test function and validator creation, we are ready for
 getting accuracy metrics.
 
-**Note**: Model evaluation is time consuming
-process and can take several minutes, depending on the hardware. For
-reducing calculation time, we define ``num_samples`` parameter with
-evaluation subset size, but in this case, accuracy can be noncomparable
-with originally reported by the authors of the model, due to validation
-subset difference. *To validate the models on the full dataset set
-``NUM_TEST_SAMPLES = None``.*
+   **NOTE**: Model evaluation is time consuming
+   process and can take several minutes, depending on the hardware. For
+   reducing calculation time, we define ``num_samples`` parameter with
+   evaluation subset size, but in this case, accuracy can be noncomparable
+   with originally reported by the authors of the model, due to validation
+   subset difference. *To validate the models on the full dataset set
+   ``NUM_TEST_SAMPLES = None``.*
 
 .. code:: ipython3
 
@@ -833,7 +833,7 @@ asymmetric quantization of activations. For more accurate results, we
 should keep the operation in the postprocessing subgraph in floating
 point precision, using the ``ignored_scope`` parameter.
 
-   **Note**: Model post-training quantization is time-consuming process.
+   **NOTE**: Model post-training quantization is time-consuming process.
    Be patient, it can take several minutes depending on your hardware.
 
 .. code:: ipython3
@@ -955,7 +955,7 @@ Tool `__
 to measure the inference performance of the ``FP32`` and ``INT8``
 models.
 
-   **Note**: For more accurate performance, it is recommended to run
+   **NOTE**: For more accurate performance, it is recommended to run
    ``benchmark_app`` in a terminal/command prompt after closing other
    applications. Run
    ``benchmark_app -m  -d CPU -shape ""`` to
diff --git a/docs/notebooks/230-yolov8-object-detection-with-output_files/index.html.tmp b/docs/notebooks/230-yolov8-object-detection-with-output_files/index.html.tmp
deleted file mode 100644
index 04236a86fd95c3..00000000000000
--- a/docs/notebooks/230-yolov8-object-detection-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,15 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/230-yolov8-object-detection-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/230-yolov8-object-detection-with-output_files/
../
-230-yolov8-object-detection-with-output_11_1.jpg   26-Jan-2024 01:05              110998
-230-yolov8-object-detection-with-output_11_1.png   26-Jan-2024 01:05              910454
-230-yolov8-object-detection-with-output_22_0.jpg   26-Jan-2024 01:05              110022
-230-yolov8-object-detection-with-output_22_0.png   26-Jan-2024 01:05              929067
-230-yolov8-object-detection-with-output_45_0.jpg   26-Jan-2024 01:05              110900
-230-yolov8-object-detection-with-output_45_0.png   26-Jan-2024 01:05              929911
-230-yolov8-object-detection-with-output_68_0.jpg   26-Jan-2024 01:05              110900
-230-yolov8-object-detection-with-output_68_0.png   26-Jan-2024 01:05              929911
-230-yolov8-object-detection-with-output_74_0.png   26-Jan-2024 01:05              491904
-

-
diff --git a/docs/notebooks/231-instruct-pix2pix-image-editing-with-output.rst b/docs/notebooks/231-instruct-pix2pix-image-editing-with-output.rst
index 9b8b9877d3dc2b..1021ebf27736a1 100644
--- a/docs/notebooks/231-instruct-pix2pix-image-editing-with-output.rst
+++ b/docs/notebooks/231-instruct-pix2pix-image-editing-with-output.rst
@@ -70,8 +70,7 @@ Create Pytorch Models pipeline
 
 ``StableDiffusionInstructPix2PixPipeline`` is an end-to-end inference
 pipeline that you can use to edit images from text instructions with
-just a few lines of code provided as part
-🤗🧨\ `diffusers `__ library.
+just a few lines of code provided as part of `diffusers `__ library.
 
 First, we load the pre-trained weights of all components of the model.
 
@@ -92,7 +91,7 @@ First, we load the pre-trained weights of all components of the model.
     unet.eval()
     vae = pipe.vae
     vae.eval()
-    
+
     del pipe
 
 Convert Models to OpenVINO IR
@@ -146,11 +145,11 @@ hidden states.
     from pathlib import Path
     import openvino as ov
     import gc
-    
+
     core = ov.Core()
-    
+
     TEXT_ENCODER_OV_PATH = Path("text_encoder.xml")
-    
+
     def cleanup_torchscript_cache():
         """
         Helper for removing cached model representation
@@ -158,13 +157,13 @@ hidden states.
         torch._C._jit_clear_class_registry()
         torch.jit._recursive.concrete_type_store = torch.jit._recursive.ConcreteTypeStore()
         torch.jit._state._clear_class_state()
-    
-    
+
+
     def convert_encoder(text_encoder: torch.nn.Module, ir_path:Path):
         """
-        Convert Text Encoder mode. 
-        Function accepts text encoder model, and prepares example inputs for conversion, 
-        Parameters: 
+        Convert Text Encoder mode.
+        Function accepts text encoder model, and prepares example inputs for conversion,
+        Parameters:
             text_encoder (torch.nn.Module): text_encoder model from Stable Diffusion pipeline
             ir_path (Path): File for storing model
         Returns:
@@ -173,7 +172,7 @@ hidden states.
         input_ids = torch.ones((1, 77), dtype=torch.long)
         # switch model to inference mode
         text_encoder.eval()
-    
+
         # disable gradients calculation for reducing memory consumption
         with torch.no_grad():
             # Export model to IR format
@@ -182,13 +181,13 @@ hidden states.
         del ov_model
         cleanup_torchscript_cache()
         print(f'Text Encoder successfully converted to IR and saved to {ir_path}')
-        
-    
+
+
     if not TEXT_ENCODER_OV_PATH.exists():
         convert_encoder(text_encoder, TEXT_ENCODER_OV_PATH)
     else:
         print(f"Text encoder will be loaded from {TEXT_ENCODER_OV_PATH}")
-    
+
     del text_encoder
     gc.collect()
 
@@ -228,14 +227,14 @@ into two independent models.
 .. code:: ipython3
 
     VAE_ENCODER_OV_PATH = Path("vae_encoder.xml")
-    
+
     def convert_vae_encoder(vae: torch.nn.Module, ir_path: Path):
         """
-        Convert VAE model for encoding to IR format. 
-        Function accepts vae model, creates wrapper class for export only necessary for inference part, 
-        prepares example inputs for conversion, 
-        Parameters: 
-            vae (torch.nn.Module): VAE model from StableDiffusio pipeline 
+        Convert VAE model for encoding to IR format.
+        Function accepts vae model, creates wrapper class for export only necessary for inference part,
+        prepares example inputs for conversion,
+        Parameters:
+            vae (torch.nn.Module): VAE model from StableDiffusio pipeline
             ir_path (Path): File for storing model
         Returns:
             None
@@ -244,7 +243,7 @@ into two independent models.
             def __init__(self, vae):
                 super().__init__()
                 self.vae = vae
-    
+
             def forward(self, image):
                 return self.vae.encode(x=image)["latent_dist"].sample()
         vae_encoder = VAEEncoderWrapper(vae)
@@ -256,21 +255,21 @@ into two independent models.
         del ov_model
         cleanup_torchscript_cache()
         print(f'VAE encoder successfully converted to IR and saved to {ir_path}')
-    
-    
+
+
     if not VAE_ENCODER_OV_PATH.exists():
         convert_vae_encoder(vae, VAE_ENCODER_OV_PATH)
     else:
         print(f"VAE encoder will be loaded from {VAE_ENCODER_OV_PATH}")
-    
+
     VAE_DECODER_OV_PATH = Path('vae_decoder.xml')
-    
+
     def convert_vae_decoder(vae: torch.nn.Module, ir_path: Path):
         """
-        Convert VAE model for decoding to IR format. 
-        Function accepts vae model, creates wrapper class for export only necessary for inference part, 
-        prepares example inputs for conversion, 
-        Parameters: 
+        Convert VAE model for decoding to IR format.
+        Function accepts vae model, creates wrapper class for export only necessary for inference part,
+        prepares example inputs for conversion,
+        Parameters:
             vae (torch.nn.Module): VAE model frm StableDiffusion pipeline
             ir_path (Path): File for storing model
         Returns:
@@ -280,13 +279,13 @@ into two independent models.
             def __init__(self, vae):
                 super().__init__()
                 self.vae = vae
-    
+
             def forward(self, latents):
                 return self.vae.decode(latents)
-        
+
         vae_decoder = VAEDecoderWrapper(vae)
         latents = torch.zeros((1, 4, 64, 64))
-    
+
         vae_decoder.eval()
         with torch.no_grad():
             ov_model = ov.convert_model(vae_decoder, example_input=latents, input=[((1,4,64,64),)])
@@ -294,13 +293,13 @@ into two independent models.
         del ov_model
         cleanup_torchscript_cache()
         print(f'VAE decoder successfully converted to IR and saved to {ir_path}')
-    
-    
+
+
     if not VAE_DECODER_OV_PATH.exists():
         convert_vae_decoder(vae, VAE_DECODER_OV_PATH)
     else:
         print(f"VAE decoder will be loaded from {VAE_DECODER_OV_PATH}")
-    
+
     del vae
     gc.collect()
 
@@ -337,20 +336,20 @@ Model predicts the ``sample`` state for the next step.
 .. code:: ipython3
 
     import numpy as np
-    
+
     UNET_OV_PATH = Path("unet.xml")
-    
+
     dtype_mapping = {
         torch.float32: ov.Type.f32,
         torch.float64: ov.Type.f64
     }
-    
-    
+
+
     def convert_unet(unet:torch.nn.Module, ir_path:Path):
         """
-        Convert U-net model to IR format. 
-        Function accepts unet model, prepares example inputs for conversion, 
-        Parameters: 
+        Convert U-net model to IR format.
+        Function accepts unet model, prepares example inputs for conversion,
+        Parameters:
             unet (StableDiffusionPipeline): unet from Stable Diffusion pipeline
             ir_path (Path): File for storing model
         Returns:
@@ -367,7 +366,7 @@ Model predicts the ``sample`` state for the next step.
             shape = ov.PartialShape(tuple(input_tensor.shape))
             element_type = dtype_mapping[input_tensor.dtype]
             input_info.append((shape, element_type))
-    
+
         unet.eval()
         with torch.no_grad():
             ov_model = ov.convert_model(unet, example_input=dummy_inputs, input=input_info)
@@ -375,8 +374,8 @@ Model predicts the ``sample`` state for the next step.
         del ov_model
         cleanup_torchscript_cache()
         print(f'Unet successfully converted to IR and saved to {ir_path}')
-    
-    
+
+
     if not UNET_OV_PATH.exists():
         convert_unet(unet, UNET_OV_PATH)
         gc.collect()
@@ -435,13 +434,13 @@ decoder part of the variational auto encoder.
     from typing import Union, List, Optional, Tuple
     import PIL
     import cv2
-    
-    
+
+
     def scale_fit_to_window(dst_width:int, dst_height:int, image_width:int, image_height:int):
         """
-        Preprocessing helper function for calculating image size for resize with peserving original aspect ratio 
+        Preprocessing helper function for calculating image size for resize with peserving original aspect ratio
         and fitting image to specific window size
-        
+
         Parameters:
           dst_width (int): destination window width
           dst_height (int): destination window height
@@ -453,15 +452,15 @@ decoder part of the variational auto encoder.
         """
         im_scale = min(dst_height / image_height, dst_width / image_width)
         return int(im_scale * image_width), int(im_scale * image_height)
-    
-    
+
+
     def preprocess(image: PIL.Image.Image):
         """
         Image preprocessing function. Takes image in PIL.Image format, resizes it to keep aspect ration and fits to model input window 512x512,
         then converts it to np.ndarray and adds padding with zeros on right or bottom side of image (depends from aspect ratio), after that
         converts data to float32 data type and change range of values from [0, 255] to [-1, 1], finally, converts data layout from planar NHWC to NCHW.
         The function returns preprocessed input tensor and padding size, which can be used in postprocessing.
-        
+
         Parameters:
           image (PIL.Image.Image): input image
         Returns:
@@ -481,15 +480,15 @@ decoder part of the variational auto encoder.
         image = 2.0 * image - 1.0
         image = image.transpose(0, 3, 1, 2)
         return image, pad
-    
-    
+
+
     def randn_tensor(
         shape: Union[Tuple, List],
         dtype: Optional[np.dtype] = np.float32,
     ):
         """
         Helper function for generation random values tensor with given shape and data type
-        
+
         Parameters:
           shape (Union[Tuple, List]): shape for filling random values
           dtype (np.dtype, *optiona*, np.float32): data type for result
@@ -497,10 +496,10 @@ decoder part of the variational auto encoder.
           latents (np.ndarray): tensor with random values with given data type and shape (usually represents noise in latent space)
         """
         latents = np.random.randn(*shape).astype(dtype)
-    
+
         return latents
-    
-    
+
+
     class OVInstructPix2PixPipeline(DiffusionPipeline):
         """
         OpenVINO inference pipeline for InstructPix2Pix
@@ -522,11 +521,11 @@ decoder part of the variational auto encoder.
             self.scheduler = scheduler
             self.load_models(core, device, text_encoder,
                              vae_encoder, unet, vae_decoder)
-    
+
         def load_models(self, core: ov.Core, device: str, text_encoder: ov.Model, vae_encoder: ov.Model, unet: ov.Model, vae_decoder: ov.Model):
             """
             Function for loading models on device using OpenVINO
-            
+
             Parameters:
               core (Core): OpenVINO runtime Core class instance
               device (str): inference device
@@ -547,7 +546,7 @@ decoder part of the variational auto encoder.
             self.unet_out = self.unet.output(0)
             self.vae_decoder = core.compile_model(vae_decoder, device, ov_config)
             self.vae_decoder_out = self.vae_decoder.output(0)
-    
+
         def __call__(
             self,
             prompt: Union[str, List[str]],
@@ -561,7 +560,7 @@ decoder part of the variational auto encoder.
         ):
             """
             Function invoked when calling the pipeline for generation.
-    
+
             Parameters:
                 prompt (`str` or `List[str]`):
                     The prompt or prompts to guide the image generation.
@@ -590,9 +589,9 @@ decoder part of the variational auto encoder.
                     [PIL](https://pillow.readthedocs.io/en/stable/): `PIL.Image.Image` or `np.array`.
             Returns:
                 image ([List[Union[np.ndarray, PIL.Image.Image]]): generaited images
-                
+
             """
-    
+
             # 1. Define call parameters
             batch_size = 1 if isinstance(prompt, str) else len(prompt)
             # here `guidance_scale` is defined analog to the guidance weight `w` of equation (2)
@@ -601,25 +600,25 @@ decoder part of the variational auto encoder.
             do_classifier_free_guidance = guidance_scale > 1.0 and image_guidance_scale >= 1.0
             # check if scheduler is in sigmas space
             scheduler_is_in_sigma_space = hasattr(self.scheduler, "sigmas")
-    
+
             # 2. Encode input prompt
             text_embeddings = self._encode_prompt(prompt)
-    
+
             # 3. Preprocess image
             orig_width, orig_height = image.size
             image, pad = preprocess(image)
             height, width = image.shape[-2:]
-    
+
             # 4. set timesteps
             self.scheduler.set_timesteps(num_inference_steps)
             timesteps = self.scheduler.timesteps
-    
+
             # 5. Prepare Image latents
             image_latents = self.prepare_image_latents(
                 image,
                 do_classifier_free_guidance=do_classifier_free_guidance,
             )
-    
+
             # 6. Prepare latent variables
             num_channels_latents = 4
             latents = self.prepare_latents(
@@ -630,7 +629,7 @@ decoder part of the variational auto encoder.
                 text_embeddings.dtype,
                 latents,
             )
-    
+
             # 7. Denoising loop
             num_warmup_steps = len(timesteps) - num_inference_steps * self.scheduler.order
             with self.progress_bar(total=num_inference_steps) as progress_bar:
@@ -640,17 +639,17 @@ decoder part of the variational auto encoder.
                     # is applied for both the text and the input image.
                     latent_model_input = np.concatenate(
                         [latents] * 3) if do_classifier_free_guidance else latents
-    
+
                     # concat latents, image_latents in the channel dimension
                     scaled_latent_model_input = self.scheduler.scale_model_input(
                         latent_model_input, t)
                     scaled_latent_model_input = np.concatenate(
                         [scaled_latent_model_input, image_latents], axis=1)
-    
+
                     # predict the noise residual
                     noise_pred = self.unet([scaled_latent_model_input, t, text_embeddings])[
                         self.unet_out]
-    
+
                     # Hack:
                     # For karras style schedulers the model does classifier free guidance using the
                     # predicted_original_sample instead of the noise_pred. So we need to compute the
@@ -659,7 +658,7 @@ decoder part of the variational auto encoder.
                         step_index = (self.scheduler.timesteps == t).nonzero().item()
                         sigma = self.scheduler.sigmas[step_index].numpy()
                         noise_pred = latent_model_input - sigma * noise_pred
-    
+
                     # perform guidance
                     if do_classifier_free_guidance:
                         noise_pred_text, noise_pred_image, noise_pred_uncond = noise_pred[
@@ -667,7 +666,7 @@ decoder part of the variational auto encoder.
                         noise_pred = (
                             noise_pred_uncond + guidance_scale * (noise_pred_text - noise_pred_image) + image_guidance_scale * (noise_pred_image - noise_pred_uncond)
                         )
-    
+
                     # For karras style schedulers the model does classifier free guidance using the
                     # predicted_original_sample instead of the noise_pred. But the scheduler.step function
                     # expects the noise_pred and computes the predicted_original_sample internally. So we
@@ -675,17 +674,17 @@ decoder part of the variational auto encoder.
                     # predicted_original_sample is correct.
                     if scheduler_is_in_sigma_space:
                         noise_pred = (noise_pred - latents) / (-sigma)
-    
+
                     # compute the previous noisy sample x_t -> x_t-1
                     latents = self.scheduler.step(torch.from_numpy(noise_pred), t, torch.from_numpy(latents)).prev_sample.numpy()
-    
+
                     # call the callback, if provided
                     if i == len(timesteps) - 1 or ((i + 1) > num_warmup_steps and (i + 1) % self.scheduler.order == 0):
                         progress_bar.update()
-    
+
             # 8. Post-processing
             image = self.decode_latents(latents, pad)
-    
+
             # 9. Convert to PIL
             if output_type == "pil":
                 image = self.numpy_to_pil(image)
@@ -694,13 +693,13 @@ decoder part of the variational auto encoder.
             else:
                 image = [cv2.resize(img, (orig_width, orig_width))
                          for img in image]
-    
+
             return image
-    
+
         def _encode_prompt(self, prompt:Union[str, List[str]], num_images_per_prompt:int = 1, do_classifier_free_guidance:bool = True):
             """
             Encodes the prompt into text encoder hidden states.
-    
+
             Parameters:
                 prompt (str or list(str)): prompt to be encoded
                 num_images_per_prompt (int): number of images that should be generated per prompt
@@ -709,7 +708,7 @@ decoder part of the variational auto encoder.
                 text_embeddings (np.ndarray): text encoder hidden states
             """
             batch_size = len(prompt) if isinstance(prompt, list) else 1
-    
+
             # tokenize input prompts
             text_inputs = self.tokenizer(
                 prompt,
@@ -719,10 +718,10 @@ decoder part of the variational auto encoder.
                 return_tensors="np",
             )
             text_input_ids = text_inputs.input_ids
-    
+
             text_embeddings = self.text_encoder(
                 text_input_ids)[self.text_encoder_out]
-    
+
             # duplicate text embeddings for each generation per prompt, using mps friendly method
             if num_images_per_prompt != 1:
                 bs_embed, seq_len, _ = text_embeddings.shape
@@ -730,7 +729,7 @@ decoder part of the variational auto encoder.
                     text_embeddings, (1, num_images_per_prompt, 1))
                 text_embeddings = np.reshape(
                     text_embeddings, (bs_embed * num_images_per_prompt, seq_len, -1))
-    
+
             # get unconditional embeddings for classifier free guidance
             if do_classifier_free_guidance:
                 uncond_tokens: List[str]
@@ -743,31 +742,31 @@ decoder part of the variational auto encoder.
                     truncation=True,
                     return_tensors="np",
                 )
-    
+
                 uncond_embeddings = self.text_encoder(uncond_input.input_ids)[
                     self.text_encoder_out]
-    
+
                 # duplicate unconditional embeddings for each generation per prompt, using mps friendly method
                 seq_len = uncond_embeddings.shape[1]
                 uncond_embeddings = np.tile(
                     uncond_embeddings, (1, num_images_per_prompt, 1))
                 uncond_embeddings = np.reshape(
                     uncond_embeddings, (batch_size * num_images_per_prompt, seq_len, -1))
-    
+
                 # For classifier free guidance, you need to do two forward passes.
                 # Here, you concatenate the unconditional and text embeddings into a single batch
                 # to avoid doing two forward passes
                 text_embeddings = np.concatenate(
                     [text_embeddings, uncond_embeddings, uncond_embeddings])
-    
+
             return text_embeddings
-    
+
         def prepare_image_latents(
             self, image, batch_size=1, num_images_per_prompt=1, do_classifier_free_guidance=True
         ):
             """
             Encodes input image to latent space using VAE Encoder
-            
+
             Parameters:
                image (np.ndarray): input image tensor
                num_image_per_prompt (int, *optional*, 1): number of image generated for promt
@@ -775,12 +774,12 @@ decoder part of the variational auto encoder.
             Returns:
                image_latents: image encoded to latent space
             """
-    
+
             image = image.astype(np.float32)
-    
+
             batch_size = batch_size * num_images_per_prompt
             image_latents = self.vae_encoder(image)[self.vae_encoder_out]
-    
+
             if batch_size > image_latents.shape[0] and batch_size % image_latents.shape[0] == 0:
                 # expand image_latents for batch_size
                 additional_image_per_prompt = batch_size // image_latents.shape[0]
@@ -792,18 +791,18 @@ decoder part of the variational auto encoder.
                 )
             else:
                 image_latents = np.concatenate([image_latents], axis=0)
-    
+
             if do_classifier_free_guidance:
                 uncond_image_latents = np.zeros_like(image_latents)
                 image_latents = np.concatenate([image_latents, image_latents, uncond_image_latents], axis=0)
-    
+
             return image_latents
-    
+
         def prepare_latents(self, batch_size:int, num_channels_latents:int, height:int, width:int, dtype:np.dtype = np.float32, latents:np.ndarray = None):
             """
-            Preparing noise to image generation. If initial latents are not provided, they will be generated randomly, 
+            Preparing noise to image generation. If initial latents are not provided, they will be generated randomly,
             then prepared latents scaled by the standard deviation required by the scheduler
-            
+
             Parameters:
                batch_size (int): input batch size
                num_channels_latents (int): number of channels for noise generation
@@ -819,15 +818,15 @@ decoder part of the variational auto encoder.
                 latents = randn_tensor(shape, dtype=dtype)
             else:
                 latents = latents
-    
+
             # scale the initial noise by the standard deviation required by the scheduler
             latents = latents * self.scheduler.init_noise_sigma.numpy()
             return latents
-    
+
         def decode_latents(self, latents:np.array, pad:Tuple[int]):
             """
             Decode predicted image from latent space using VAE Decoder and unpad image result
-            
+
             Parameters:
                latents (np.ndarray): image encoded in diffusion latent space
                pad (Tuple[int]): each side padding sizes obtained on preprocessing step
@@ -848,12 +847,12 @@ decoder part of the variational auto encoder.
 .. code:: ipython3
 
     import matplotlib.pyplot as plt
-    
-    
+
+
     def visualize_results(orig_img:PIL.Image.Image, processed_img:PIL.Image.Image, img1_title:str, img2_title:str):
         """
         Helper function for results visualization
-        
+
         Parameters:
            orig_img (PIL.Image.Image): original image
            processed_img (PIL.Image.Image): processed image after editing
@@ -876,7 +875,7 @@ decoder part of the variational auto encoder.
             a.grid(False)
         list_axes[0].imshow(np.array(orig_img))
         list_axes[1].imshow(np.array(processed_img))
-        list_axes[0].set_title(img1_title, fontsize=20) 
+        list_axes[0].set_title(img1_title, fontsize=20)
         list_axes[1].set_title(img2_title, fontsize=20)
         fig.subplots_adjust(wspace=0.0 if is_horizontal else 0.01 , hspace=0.01 if is_horizontal else 0.0)
         fig.tight_layout()
@@ -890,14 +889,14 @@ can provide device selecting one from available in dropdown list.
 .. code:: ipython3
 
     import ipywidgets as widgets
-    
+
     device = widgets.Dropdown(
         options=core.available_devices + ["AUTO"],
         value='AUTO',
         description='Device:',
         disabled=False,
     )
-    
+
     device
 
 
@@ -912,10 +911,10 @@ can provide device selecting one from available in dropdown list.
 .. code:: ipython3
 
     from transformers import CLIPTokenizer
-    
+
     tokenizer = CLIPTokenizer.from_pretrained('openai/clip-vit-large-patch14')
     scheduler = EulerAncestralDiscreteScheduler.from_config(scheduler_config)
-    
+
     ov_pipe = OVInstructPix2PixPipeline(tokenizer, scheduler, core, TEXT_ENCODER_OV_PATH, VAE_ENCODER_OV_PATH, UNET_OV_PATH, VAE_DECODER_OV_PATH, device=device.value)
 
 
@@ -932,7 +931,7 @@ by the model on this
 need inspiration. Optionally, you can also change the random generator
 seed for latent state initialization and number of steps.
 
-   **Note**: Consider increasing ``steps`` to get more precise results.
+   **NOTE**: Consider increasing ``steps`` to get more precise results.
    A suggested value is ``100``, but it will take more time to process.
 
 .. code:: ipython3
@@ -958,14 +957,14 @@ seed for latent state initialization and number of steps.
 
 
 
-   **Note**: Diffusion process can take some time, depending on what
+   **NOTE**: Diffusion process can take some time, depending on what
    hardware you select.
 
 .. code:: ipython3
 
     import io
     import requests
-    
+
     default_url = "https://user-images.githubusercontent.com/29454499/223343459-4ac944f0-502e-4acf-9813-8e9f0abc8a16.jpg"
     # read uploaded image
     image = PIL.Image.open(io.BytesIO(image_widget.value[-1]['content']) if image_widget.value else requests.get(default_url, stream=True).raw)
@@ -1042,7 +1041,7 @@ improve model inference speed.
         description='Quantization',
         disabled=False,
     )
-    
+
     to_quantize
 
 
@@ -1061,7 +1060,7 @@ Let’s load ``skip magic`` extension to skip quantization if
 
     import sys
     sys.path.append("../utils")
-    
+
     %load_ext skip_kernel_extension
 
 Prepare calibration dataset
@@ -1077,29 +1076,29 @@ model inputs for calibration we should customize ``CompiledModel``.
 .. code:: ipython3
 
     %%skip not $to_quantize.value
-    
+
     import datasets
     from tqdm.notebook import tqdm
     from transformers import Pipeline
     from typing import Any, Dict, List
-    
+
     class CompiledModelDecorator(ov.CompiledModel):
         def __init__(self, compiled_model, prob: float, data_cache: List[Any] = None):
             super().__init__(compiled_model)
             self.data_cache = data_cache if data_cache else []
             self.prob = np.clip(prob, 0, 1)
-    
+
         def __call__(self, *args, **kwargs):
             if np.random.rand() >= self.prob:
                 self.data_cache.append(*args)
             return super().__call__(*args, **kwargs)
-    
+
     def collect_calibration_data(pix2pix_pipeline: Pipeline, subset_size: int) -> List[Dict]:
         original_unet = pix2pix_pipeline.unet
         pix2pix_pipeline.unet = CompiledModelDecorator(original_unet, prob=0.3)
         dataset = datasets.load_dataset("fusing/instructpix2pix-1000-samples", split="train", streaming=True).shuffle(seed=42)
         pix2pix_pipeline.set_progress_bar_config(disable=True)
-    
+
         # Run inference for data collection
         pbar = tqdm(total=subset_size)
         diff = 0
@@ -1113,7 +1112,7 @@ model inputs for calibration we should customize ``CompiledModel``.
                 break
             pbar.update(collected_subset_size - diff)
             diff = collected_subset_size
-    
+
         calibration_dataset = pix2pix_pipeline.unet.data_cache
         pix2pix_pipeline.set_progress_bar_config(disable=False)
         pix2pix_pipeline.unet = original_unet
@@ -1122,7 +1121,7 @@ model inputs for calibration we should customize ``CompiledModel``.
 .. code:: ipython3
 
     %%skip not $to_quantize.value
-    
+
     UNET_INT8_OV_PATH = Path("unet_int8.xml")
     if not UNET_INT8_OV_PATH.exists():
         subset_size = 300
@@ -1154,9 +1153,9 @@ Create a quantized model from the pre-trained converted OpenVINO model.
 .. code:: ipython3
 
     %%skip not $to_quantize.value
-    
+
     import nncf
-    
+
     if UNET_INT8_OV_PATH.exists():
         print("Loading quantized model")
         quantized_unet = core.read_model(UNET_INT8_OV_PATH)
@@ -1199,16 +1198,16 @@ data.
 .. code:: ipython3
 
     %%skip not $to_quantize.value
-    
+
     print('Pipeline settings')
     print(f'Input text: {text_prompt.value}')
     print(f'Seed: {seed.value}')
     print(f'Number of steps: {num_steps.value}')
     np.random.seed(seed.value)
-    
+
     int8_pipe = OVInstructPix2PixPipeline(tokenizer, scheduler, core, TEXT_ENCODER_OV_PATH, VAE_ENCODER_OV_PATH, UNET_INT8_OV_PATH, VAE_DECODER_OV_PATH, device=device.value)
     int8_processed_image = int8_pipe(text_prompt.value, image, num_steps.value)
-    
+
     fig = visualize_results(processed_image[0], int8_processed_image[0], img1_title="FP16 result", img2_title="INT8 result")
 
 
@@ -1245,9 +1244,9 @@ models, we use median inference time on calibration subset.
 .. code:: ipython3
 
     %%skip not $to_quantize.value
-    
+
     import time
-    
+
     calibration_dataset = datasets.load_dataset("fusing/instructpix2pix-1000-samples", split="train", streaming=True)
     validation_data = []
     validation_size = 10
@@ -1256,7 +1255,7 @@ models, we use median inference time on calibration subset.
         prompt = batch["edit_prompt"]
         input_image = batch["input_image"].convert("RGB")
         validation_data.append((prompt, input_image))
-    
+
     def calculate_inference_time(pix2pix_pipeline, calibration_dataset, size=10):
         inference_time = []
         pix2pix_pipeline.set_progress_bar_config(disable=True)
@@ -1271,7 +1270,7 @@ models, we use median inference time on calibration subset.
 .. code:: ipython3
 
     %%skip not $to_quantize.value
-    
+
     fp_latency = calculate_inference_time(ov_pipe, validation_data)
     int8_latency = calculate_inference_time(int8_pipe, validation_data)
     print(f"Performance speed up: {fp_latency / int8_latency:.3f}")
@@ -1287,7 +1286,7 @@ Interactive demo with Gradio
 
 
 
-   **Note**: Diffusion process can take some time, depending on what
+   **NOTE**: Diffusion process can take some time, depending on what
    hardware you select.
 
 .. code:: ipython3
@@ -1298,7 +1297,7 @@ Interactive demo with Gradio
         description='Precision:',
         disabled=False,
     )
-    
+
     pipe_precision
 
 
@@ -1316,22 +1315,22 @@ Interactive demo with Gradio
     from urllib.request import urlretrieve
     from pathlib import Path
     import numpy as np
-    
+
     default_url = "https://user-images.githubusercontent.com/29454499/223343459-4ac944f0-502e-4acf-9813-8e9f0abc8a16.jpg"
     path = Path("data/example.jpg")
     path.parent.mkdir(parents=True, exist_ok=True)
     urlretrieve(default_url, path)
-    
+
     pipeline = int8_pipe if pipe_precision.value == "INT8" else ov_pipe
-    
+
     def generate(img, text, seed, num_steps, _=gr.Progress(track_tqdm=True)):
         if img is None:
             raise gr.Error("Please upload an image or choose one from the examples list")
         np.random.seed(seed)
         result = pipeline(text, img, num_steps)[0]
         return result
-    
-    
+
+
     demo = gr.Interface(
         generate,
         [
@@ -1349,7 +1348,7 @@ Interactive demo with Gradio
         gr.Image(label="Result"),
         examples=[[path, "Make it in galaxy"]],
     )
-    
+
     try:
         demo.queue().launch(debug=False)
     except Exception:
diff --git a/docs/notebooks/231-instruct-pix2pix-image-editing-with-output_files/index.html.tmp b/docs/notebooks/231-instruct-pix2pix-image-editing-with-output_files/index.html.tmp
deleted file mode 100644
index b8e9b431a1ec4b..00000000000000
--- a/docs/notebooks/231-instruct-pix2pix-image-editing-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,8 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/231-instruct-pix2pix-image-editing-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/231-instruct-pix2pix-image-editing-with-output_files/
../
-231-instruct-pix2pix-image-editing-with-output_..> 26-Jan-2024 01:05             3699096
-231-instruct-pix2pix-image-editing-with-output_..> 26-Jan-2024 01:05             3646410
-

-
diff --git a/docs/notebooks/232-clip-language-saliency-map-with-output.rst b/docs/notebooks/232-clip-language-saliency-map-with-output.rst
index 6b78d2ced7a328..5a33e362877c89 100644
--- a/docs/notebooks/232-clip-language-saliency-map-with-output.rst
+++ b/docs/notebooks/232-clip-language-saliency-map-with-output.rst
@@ -79,8 +79,8 @@ used to build the saliency map. Here is how it can be done:
 5. Update the corresponding region on the ``saliency map``.
 6. Repeat steps 2-5 multiple times (``n_iters``).
 
-**Table of contents:**
----
+Table of contents:
+^^^^^^^^^^^^^^^^^^
 
 -  `Initial Implementation with Transformers and
    Pytorch <#initial-implementation-with-transformers-and-pytorch>`__
@@ -96,8 +96,7 @@ used to build the saliency map. Here is how it can be done:
    AsyncInferQueue <#accelerate-inference-with-asyncinferqueue>`__
 -  `Pack the Pipeline into a
    Function <#pack-the-pipeline-into-a-function>`__
--  `Interactive demo with
-   Gradio <#interactive-demo-with-gradio>`__
+-  `Interactive demo with Gradio <#interactive-demo-with-gradio>`__
 -  `What To Do Next <#what-to-do-next>`__
 
 .. |image0| image:: https://user-images.githubusercontent.com/29454499/218967961-9858efd5-fff2-4eb0-bde9-60852f4b31cb.JPG
diff --git a/docs/notebooks/232-clip-language-saliency-map-with-output_files/index.html.tmp b/docs/notebooks/232-clip-language-saliency-map-with-output_files/index.html.tmp
deleted file mode 100644
index fe168105c01ed2..00000000000000
--- a/docs/notebooks/232-clip-language-saliency-map-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,11 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/232-clip-language-saliency-map-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/232-clip-language-saliency-map-with-output_files/
../
-232-clip-language-saliency-map-with-output_15_0..> 26-Jan-2024 01:05               74041
-232-clip-language-saliency-map-with-output_17_0..> 26-Jan-2024 01:05              473017
-232-clip-language-saliency-map-with-output_19_1..> 26-Jan-2024 01:05              472958
-232-clip-language-saliency-map-with-output_29_1..> 26-Jan-2024 01:05              475731
-232-clip-language-saliency-map-with-output_35_1..> 26-Jan-2024 01:05              471008
-

-
diff --git a/docs/notebooks/233-blip-convert-with-output_files/index.html.tmp b/docs/notebooks/233-blip-convert-with-output_files/index.html.tmp
deleted file mode 100644
index 0a00ff0f6e23a2..00000000000000
--- a/docs/notebooks/233-blip-convert-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,9 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/233-blip-convert-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/233-blip-convert-with-output_files/
../
-233-blip-convert-with-output_25_0.png              26-Jan-2024 01:05              206940
-233-blip-convert-with-output_27_0.png              26-Jan-2024 01:05              210551
-233-blip-convert-with-output_7_0.png               26-Jan-2024 01:05              210551
-

-
diff --git a/docs/notebooks/233-blip-optimize-with-output.rst b/docs/notebooks/233-blip-optimize-with-output.rst
index feb81a1cee22da..5410fe51c33c10 100644
--- a/docs/notebooks/233-blip-optimize-with-output.rst
+++ b/docs/notebooks/233-blip-optimize-with-output.rst
@@ -55,18 +55,18 @@ Prerequisites
 .. code:: ipython3
 
     from pathlib import Path
-
+    
     VISION_MODEL_OV = Path("blip_vision_model.xml")
     TEXT_ENCODER_OV = Path("blip_text_encoder.xml")
     TEXT_DECODER_OV = Path("blip_text_decoder_with_past.xml")
-
+    
     if not (VISION_MODEL_OV.exists() and TEXT_ENCODER_OV.exists() and TEXT_DECODER_OV.exists()):
         raise RuntimeError('This notebook should be run after 233-blip-convert notebook')
 
 .. code:: ipython3
 
     from transformers import BlipProcessor
-
+    
     processor = BlipProcessor.from_pretrained("Salesforce/blip-vqa-base")
 
 Quantize
@@ -107,7 +107,7 @@ understanding of vision, language and commonsense knowledge to answer.
     import numpy as np
     from datasets import load_dataset
     from tqdm.notebook import tqdm
-
+    
     def preprocess_batch(batch, vision_model, inputs_info):
         """
         Preprocesses a dataset batch by loading and transforming image and text data.
@@ -128,14 +128,14 @@ understanding of vision, language and commonsense knowledge to answer.
                 "encoder_hidden_states": encoder_hidden_states,
                 "text_encoder_inputs": []
             }
-
+    
         text_encoder_inputs = {
             "input_ids": inputs["input_ids"],
             "attention_mask": inputs["attention_mask"]
         }
         inputs_info[image_id]["text_encoder_inputs"].append(text_encoder_inputs)
-
-
+    
+    
     def prepare_input_data(dataloader, vision_model, opt_init_steps):
         """
         Store calibration subset in List to reduce quantization time.
@@ -143,7 +143,7 @@ understanding of vision, language and commonsense knowledge to answer.
         inputs_info = {}
         for batch in tqdm(dataloader, total=opt_init_steps, desc="Prepare calibration data"):
             preprocess_batch(batch, vision_model, inputs_info)
-
+    
         calibration_subset = []
         for image_id in inputs_info:
             pixel_values = inputs_info[image_id]["pixel_values"]
@@ -158,8 +158,8 @@ understanding of vision, language and commonsense knowledge to answer.
                 }
                 calibration_subset.append(blip_inputs)
         return calibration_subset
-
-
+    
+    
     def prepare_dataset(vision_model, opt_init_steps=300, streaming=True):
         """
         Prepares a vision-text dataset for quantization.
@@ -176,7 +176,7 @@ time and depends on your internet connection.
 
     import nncf
     import openvino as ov
-
+    
     comp_vision_model = ov.compile_model(VISION_MODEL_OV)
     calibration_data = prepare_dataset(comp_vision_model)
 
@@ -205,17 +205,17 @@ Vision model
 .. code:: ipython3
 
     VISION_MODEL_OV_INT8 = Path(str(VISION_MODEL_OV).replace(".xml", "_int8.xml"))
-
+    
     core = ov.Core()
     ov_vision_model = core.read_model(VISION_MODEL_OV)
     vision_dataset = nncf.Dataset(calibration_data, lambda x: x["vision_model_inputs"])
-
+    
     quantized_model = nncf.quantize(
         model=ov_vision_model,
         calibration_dataset=vision_dataset,
         model_type=nncf.ModelType.TRANSFORMER
     )
-
+    
     ov.save_model(quantized_model, VISION_MODEL_OV_INT8)
 
 
@@ -244,7 +244,7 @@ Text encoder
 .. code:: ipython3
 
     TEXT_ENCODER_OV_INT8 = Path(str(TEXT_ENCODER_OV).replace(".xml", "_int8.xml"))
-
+    
     text_encoder_dataset = nncf.Dataset(calibration_data, lambda x: x["text_encoder_inputs"])
     ov_text_encoder = core.read_model(TEXT_ENCODER_OV)
     quantized_model = nncf.quantize(
@@ -290,7 +290,7 @@ The optimization process contains the following steps:
 .. code:: ipython3
 
     TEXT_DECODER_OV_INT8 = Path(str(TEXT_DECODER_OV).replace(".xml", "_int8.xml"))
-
+    
     text_decoder = core.read_model(TEXT_DECODER_OV)
     compressed_text_decoder = nncf.compress_weights(text_decoder)
     ov.save_model(compressed_text_decoder, str(TEXT_DECODER_OV_INT8))
@@ -303,7 +303,7 @@ Run optimized OpenVINO model
 The steps for making predictions with the optimized OpenVINO BLIP model
 are similar to the PyTorch model. Let us check the model result using
 the same input data from the `first
-notebook <233-blip-convert-with-output-with-output.html>`__.
+notebook <233-blip-convert-with-output.html>`__.
 
 .. code:: ipython3
 
@@ -316,18 +316,18 @@ notebook <233-blip-convert-with-output-with-output.html>`__.
     from functools import partial
     from transformers import BlipForQuestionAnswering
     from blip_model import OVBlipModel, text_decoder_forward
-
+    
     model = BlipForQuestionAnswering.from_pretrained("Salesforce/blip-vqa-base")
     text_decoder = model.text_decoder
     text_decoder.eval()
-
+    
     text_decoder.forward = partial(text_decoder_forward, ov_text_decoder_with_past=q_ov_text_decoder_with_past)
     int8_model = OVBlipModel(model.config, model.decoder_start_token_id, q_ov_vision_model, q_ov_text_encoder, text_decoder)
 
 .. code:: ipython3
 
     from PIL import Image
-
+    
     raw_image = Image.open("demo.jpg").convert('RGB')
     question = "how many dogs are in the picture?"
     # preprocess input data
@@ -341,7 +341,7 @@ Image Captioning
 .. code:: ipython3
 
     from utils import visualize_results
-
+    
     out = int8_model.generate_caption(inputs["pixel_values"], max_length=20)
     caption = processor.decode(out[0], skip_special_tokens=True)
     fig = visualize_results(raw_image, caption)
@@ -423,14 +423,14 @@ quantized models.
 
     import time
     import torch
-
+    
     def calculate_inference_time(blip_model, calibration_data, generate_caption):
         inference_time = []
         for inputs in calibration_data:
             pixel_values = torch.from_numpy(inputs["vision_model_inputs"]["pixel_values"])
             input_ids = torch.from_numpy(inputs["text_encoder_inputs"]["input_ids"])
             attention_mask = torch.from_numpy(inputs["text_encoder_inputs"]["attention_mask"])
-
+    
             start = time.perf_counter()
             if generate_caption:
                 _ = blip_model.generate_caption(pixel_values, max_length=20)
@@ -446,7 +446,7 @@ quantized models.
     fp_original_model = BlipForQuestionAnswering.from_pretrained("Salesforce/blip-vqa-base")
     fp_text_decoder = fp_original_model.text_decoder
     fp_text_decoder.eval()
-
+    
     comp_text_encoder = ov.compile_model(TEXT_ENCODER_OV)
     comp_text_decoder_with_past = ov.compile_model(TEXT_DECODER_OV)
     fp_text_decoder.forward = partial(text_decoder_forward, ov_text_decoder_with_past=comp_text_decoder_with_past)
@@ -455,10 +455,10 @@ quantized models.
 .. code:: ipython3
 
     validation_data = calibration_data[:100]
-
+    
     int8_caption_latency = calculate_inference_time(int8_model, validation_data, generate_caption=True)
     fp16_caption_latency = calculate_inference_time(fp16_model, validation_data, generate_caption=True)
-
+    
     print(f"Image Captioning speed up: {fp16_caption_latency / int8_caption_latency:.3f}")
 
 .. code:: ipython3
diff --git a/docs/notebooks/233-blip-optimize-with-output_files/index.html.tmp b/docs/notebooks/233-blip-optimize-with-output_files/index.html.tmp
deleted file mode 100644
index 1525b69dcb9207..00000000000000
--- a/docs/notebooks/233-blip-optimize-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,8 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/233-blip-optimize-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/233-blip-optimize-with-output_files/
../
-233-blip-optimize-with-output_23_0.png             26-Jan-2024 01:05              206216
-233-blip-optimize-with-output_25_0.png             26-Jan-2024 01:05              210551
-

-
diff --git a/docs/notebooks/234-encodec-audio-compression-with-output.rst b/docs/notebooks/234-encodec-audio-compression-with-output.rst
index 04704e8717e146..33481a2b6a12e7 100644
--- a/docs/notebooks/234-encodec-audio-compression-with-output.rst
+++ b/docs/notebooks/234-encodec-audio-compression-with-output.rst
@@ -61,14 +61,14 @@ Install required dependencies:
 
 .. parsed-literal::
 
-    DEPRECATION: pytorch-lightning 1.6.5 has a non-standard dependency specifier torch>=1.8.*. pip 24.0 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of pytorch-lightning or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063
+    DEPRECATION: pytorch-lightning 1.6.5 has a non-standard dependency specifier torch>=1.8.*. pip 24.1 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of pytorch-lightning or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063
 
 
 .. parsed-literal::
 
     ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
-    pyannote-audio 2.0.1 requires torchaudio<1.0,>=0.10, but you have torchaudio 2.1.2+cpu which is incompatible.
-    torchvision 0.14.1+cpu requires torch==1.13.1, but you have torch 2.1.2+cpu which is incompatible.
+    pyannote-audio 2.0.1 requires torchaudio<1.0,>=0.10, but you have torchaudio 2.2.0+cpu which is incompatible.
+    torchvision 0.14.1+cpu requires torch==1.13.1, but you have torch 2.2.0+cpu which is incompatible.
 
 
 .. parsed-literal::
@@ -141,7 +141,7 @@ bandwidth.
 
 .. parsed-literal::
 
-    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/torch/nn/utils/weight_norm.py:30: UserWarning: torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.
+    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/torch/nn/utils/weight_norm.py:28: UserWarning: torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.
       warnings.warn("torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.")
 
 
@@ -296,7 +296,7 @@ similar as possible to the original.
 
 .. parsed-literal::
 
-    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/torch/nn/utils/weight_norm.py:30: UserWarning: torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.
+    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/torch/nn/utils/weight_norm.py:28: UserWarning: torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.
       warnings.warn("torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.")
 
 
@@ -324,7 +324,7 @@ audio.
 
 
     
 
@@ -396,13 +396,13 @@ with ``ov.save_model``.
 
 .. parsed-literal::
 
-    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/encodec/modules/conv.py:60: TracerWarning: Converting a tensor to a Python float might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
+    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/encodec/modules/conv.py:60: TracerWarning: Converting a tensor to a Python float might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
       ideal_length = (math.ceil(n_frames) - 1) * stride + (kernel_size - padding_total)
-    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/encodec/modules/conv.py:85: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
+    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/encodec/modules/conv.py:85: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
       assert padding_left >= 0 and padding_right >= 0, (padding_left, padding_right)
-    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/encodec/modules/conv.py:87: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
+    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/encodec/modules/conv.py:87: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
       max_pad = max(padding_left, padding_right)
-    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/encodec/modules/conv.py:89: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
+    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/encodec/modules/conv.py:89: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
       if length <= max_pad:
 
 
@@ -418,11 +418,11 @@ with ``ov.save_model``.
 
 .. parsed-literal::
 
-    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/encodec/quantization/core_vq.py:358: TracerWarning: torch.tensor results are registered as constants in the trace. You can safely ignore this warning if you use this function to create tensors out of constant variables that would be the same every time you call this function. In any other case, this might cause the trace to be incorrect.
+    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/encodec/quantization/core_vq.py:358: TracerWarning: torch.tensor results are registered as constants in the trace. You can safely ignore this warning if you use this function to create tensors out of constant variables that would be the same every time you call this function. In any other case, this might cause the trace to be incorrect.
       quantized_out = torch.tensor(0.0, device=q_indices.device)
-    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/encodec/quantization/core_vq.py:359: TracerWarning: Iterating over a tensor might cause the trace to be incorrect. Passing a tensor of different shape won't change the number of iterations executed (and might lead to errors or silently give incorrect results).
+    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/encodec/quantization/core_vq.py:359: TracerWarning: Iterating over a tensor might cause the trace to be incorrect. Passing a tensor of different shape won't change the number of iterations executed (and might lead to errors or silently give incorrect results).
       for i, indices in enumerate(q_indices):
-    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-598/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/encodec/modules/conv.py:103: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
+    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-609/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/encodec/modules/conv.py:103: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
       assert (padding_left + padding_right) <= x.shape[-1]
 
 
diff --git a/docs/notebooks/234-encodec-audio-compression-with-output_files/234-encodec-audio-compression-with-output_19_1.png b/docs/notebooks/234-encodec-audio-compression-with-output_files/234-encodec-audio-compression-with-output_19_1.png
index 4d1f7be941887e..26cbb3e458c909 100644
--- a/docs/notebooks/234-encodec-audio-compression-with-output_files/234-encodec-audio-compression-with-output_19_1.png
+++ b/docs/notebooks/234-encodec-audio-compression-with-output_files/234-encodec-audio-compression-with-output_19_1.png
@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:c99a97c7779acef829103435a9de148f7d7ec1dea72b09b694e6c039f2737c45
-size 44357
+oid sha256:4c3aedb7f986fef32f6226adcbe0c5fa7dbdb4f76314db58f6570e6ebeff8015
+size 44362
diff --git a/docs/notebooks/234-encodec-audio-compression-with-output_files/index.html.tmp b/docs/notebooks/234-encodec-audio-compression-with-output_files/index.html.tmp
deleted file mode 100644
index 6037fdb836bf03..00000000000000
--- a/docs/notebooks/234-encodec-audio-compression-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,9 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/234-encodec-audio-compression-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/234-encodec-audio-compression-with-output_files/
../
-234-encodec-audio-compression-with-output_19_1.png 26-Jan-2024 01:04               44357
-234-encodec-audio-compression-with-output_38_1.png 26-Jan-2024 01:04               44353
-234-encodec-audio-compression-with-output_6_2.png  26-Jan-2024 01:04               45005
-

-
diff --git a/docs/notebooks/235-controlnet-stable-diffusion-with-output_files/index.html.tmp b/docs/notebooks/235-controlnet-stable-diffusion-with-output_files/index.html.tmp
deleted file mode 100644
index f2cb308852e3dc..00000000000000
--- a/docs/notebooks/235-controlnet-stable-diffusion-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,10 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/235-controlnet-stable-diffusion-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/235-controlnet-stable-diffusion-with-output_files/
../
-235-controlnet-stable-diffusion-with-output_17_..> 26-Jan-2024 01:05              498463
-235-controlnet-stable-diffusion-with-output_34_..> 26-Jan-2024 01:05               30487
-235-controlnet-stable-diffusion-with-output_34_..> 26-Jan-2024 01:05              464375
-235-controlnet-stable-diffusion-with-output_8_0..> 26-Jan-2024 01:05              498463
-

-
diff --git a/docs/notebooks/236-stable-diffusion-v2-optimum-demo-comparison-with-output_files/index.html.tmp b/docs/notebooks/236-stable-diffusion-v2-optimum-demo-comparison-with-output_files/index.html.tmp
deleted file mode 100644
index 68638e78682f3d..00000000000000
--- a/docs/notebooks/236-stable-diffusion-v2-optimum-demo-comparison-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,8 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/236-stable-diffusion-v2-optimum-demo-comparison-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/236-stable-diffusion-v2-optimum-demo-comparison-with-output_files/
../
-236-stable-diffusion-v2-optimum-demo-comparison..> 26-Jan-2024 01:04              573225
-236-stable-diffusion-v2-optimum-demo-comparison..> 26-Jan-2024 01:04              466925
-

-
diff --git a/docs/notebooks/236-stable-diffusion-v2-optimum-demo-with-output_files/index.html.tmp b/docs/notebooks/236-stable-diffusion-v2-optimum-demo-with-output_files/index.html.tmp
deleted file mode 100644
index 9f48592491f038..00000000000000
--- a/docs/notebooks/236-stable-diffusion-v2-optimum-demo-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,7 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/236-stable-diffusion-v2-optimum-demo-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/236-stable-diffusion-v2-optimum-demo-with-output_files/
../
-236-stable-diffusion-v2-optimum-demo-with-outpu..> 26-Jan-2024 01:05              451596
-

-
diff --git a/docs/notebooks/236-stable-diffusion-v2-text-to-image-demo-with-output.rst b/docs/notebooks/236-stable-diffusion-v2-text-to-image-demo-with-output.rst
index 20d6a22adb4a8d..9b862a14f976e6 100644
--- a/docs/notebooks/236-stable-diffusion-v2-text-to-image-demo-with-output.rst
+++ b/docs/notebooks/236-stable-diffusion-v2-text-to-image-demo-with-output.rst
@@ -21,17 +21,28 @@ like to see the full implementation of stable diffusion for text to
 image, please visit
 `236-stable-diffusion-v2-text-to-image `__.
 
+Table of contents:
+^^^^^^^^^^^^^^^^^^
 
-**Table of contents:**
+-  `Step 0: Install and import
+   prerequisites <#step-0-install-and-import-prerequisites>`__
+-  `Step 1: Stable Diffusion v2 Fundamental
+   components <#step-1-stable-diffusion-v2-fundamental-components>`__
 
-- `Step 0: Install and import prerequisites <#step-0-install-and-import-prerequisites>`__
-- `Step 1: Stable Diffusion v2 Fundamental components <#step-1-stable-diffusion-v2-fundamental-components>`__
-- `Step 1.1: Retrieve components from HuggingFace <#step-1-1-retrieve-components-from-huggingface>`__
-- `Step 2: Convert the models to OpenVINO <#step-2-convert-the-models-to-openvino>`__
-- `Step 3: Text-to-Image Generation Inference Pipeline <#step-3-text-to-image-generation-inference-pipeline>`__
-- `Step 3.1: Load and Understand Text to Image OpenVINO models <#step-3-1-load-and-understand-text-to-image-openvino-models>`__
-- `Step 3.2: Select inference device <#step-3-2-select-inference-device>`__
-- `Step 3.3: Run Text-to-Image generation <#step-3-3-run-text-to-image-generation>`__
+   -  `Step 1.1: Retrieve components from
+      HuggingFace <#step-1-1-retrieve-components-from-huggingface>`__
+
+-  `Step 2: Convert the models to
+   OpenVINO <#step-2-convert-the-models-to-openvino>`__
+-  `Step 3: Text-to-Image Generation Inference
+   Pipeline <#step-3-text-to-image-generation-inference-pipeline>`__
+
+   -  `Step 3.1: Load and Understand Text to Image OpenVINO
+      models <#step-3-1-load-and-understand-text-to-image-openvino-models>`__
+   -  `Step 3.2: Select inference
+      device <#step-3-2-select-inference-device>`__
+   -  `Step 3.3: Run Text-to-Image
+      generation <#step-3-3-run-text-to-image-generation>`__
 
 Step 0: Install and import prerequisites
 ----------------------------------------
@@ -59,7 +70,7 @@ pipelines `__.
     WARNING: Ignoring invalid distribution -orch (/home/ea/work/ov_venv/lib/python3.8/site-packages)
     WARNING: Ignoring invalid distribution -orch (/home/ea/work/ov_venv/lib/python3.8/site-packages)
     WARNING: Ignoring invalid distribution -orch (/home/ea/work/ov_venv/lib/python3.8/site-packages)
-
+    
     [notice] A new release of pip available: 22.3 -> 23.2.1
     [notice] To update, run: pip install --upgrade pip
     Note: you may need to restart the kernel to use updated packages.
@@ -96,9 +107,9 @@ using ``stable-diffusion-2-1``.
 
     # Retrieve the Text to Image Stable Diffusion pipeline components
     from diffusers import StableDiffusionPipeline
-
+    
     pipe = StableDiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-2-1-base").to("cpu")
-
+    
     # for reducing memory consumption get all components from pipeline independently
     text_encoder = pipe.text_encoder
     text_encoder.eval()
@@ -106,9 +117,9 @@ using ``stable-diffusion-2-1``.
     unet.eval()
     vae = pipe.vae
     vae.eval()
-
+    
     conf = pipe.scheduler.config
-
+    
     del pipe
 
 
@@ -153,15 +164,15 @@ pipelines in OpenVINO on our own data!
 .. code:: ipython3
 
     from pathlib import Path
-
+    
     # Define a dir to save text-to-image models
     txt2img_model_dir = Path("sd2.1")
     txt2img_model_dir.mkdir(exist_ok=True)
 
 .. code:: ipython3
 
-    from implementation.conversion_helper_utils import convert_encoder, convert_unet, convert_vae_decoder, convert_vae_encoder
-
+    from implementation.conversion_helper_utils import convert_encoder, convert_unet, convert_vae_decoder, convert_vae_encoder 
+    
     # Convert the Text-to-Image models from PyTorch -> Onnx -> OpenVINO
     # 1. Convert the Text Encoder
     txt_encoder_ov_path = txt2img_model_dir / "text_encoder.xml"
@@ -197,16 +208,16 @@ select device from dropdown list for running inference using OpenVINO
 
     import ipywidgets as widgets
     from openvino.runtime import Core
-
+    
     core = Core()
-
+    
     device = widgets.Dropdown(
         options=core.available_devices + ["AUTO"],
         value='AUTO',
         description='Device:',
         disabled=False,
     )
-
+    
     device
 
 
@@ -259,10 +270,10 @@ As part of the ``OVStableDiffusionPipeline()`` class:
     from diffusers.schedulers import LMSDiscreteScheduler
     from transformers import CLIPTokenizer
     from implementation.ov_stable_diffusion_pipeline import OVStableDiffusionPipeline
-
+    
     scheduler = LMSDiscreteScheduler.from_config(conf)
     tokenizer = CLIPTokenizer.from_pretrained('openai/clip-vit-large-patch14')
-
+    
     ov_pipe = OVStableDiffusionPipeline(
         tokenizer=tokenizer,
         text_encoder=text_enc,
@@ -310,7 +321,7 @@ explanation of how it works can be found in this
 .. code:: ipython3
 
     import ipywidgets as widgets
-
+    
     text_prompt = widgets.Textarea(value="valley in the Alps at sunset, epic vista, beautiful landscape, 4k, 8k", description='positive prompt', layout=widgets.Layout(width="auto"))
     negative_prompt = widgets.Textarea(value="frames, borderline, text, charachter, duplicate, error, out of frame, watermark, low quality, ugly, deformed, blur", description='negative prompt', layout=widgets.Layout(width="auto"))
     num_steps = widgets.IntSlider(min=1, max=50, value=25, description='steps:')
@@ -329,7 +340,7 @@ explanation of how it works can be found in this
 .. code:: ipython3
 
     # Run inference pipeline
-    result = ov_pipe(text_prompt.value, negative_prompt=negative_prompt.value, num_inference_steps=num_steps.value,
+    result = ov_pipe(text_prompt.value, negative_prompt=negative_prompt.value, num_inference_steps=num_steps.value, 
                      seed=seed.value)
 
 
diff --git a/docs/notebooks/236-stable-diffusion-v2-text-to-image-demo-with-output_files/index.html.tmp b/docs/notebooks/236-stable-diffusion-v2-text-to-image-demo-with-output_files/index.html.tmp
deleted file mode 100644
index d449e9b176c92e..00000000000000
--- a/docs/notebooks/236-stable-diffusion-v2-text-to-image-demo-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,8 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/236-stable-diffusion-v2-text-to-image-demo-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/236-stable-diffusion-v2-text-to-image-demo-with-output_files/
../
-236-stable-diffusion-v2-text-to-image-demo-with..> 26-Jan-2024 01:05              100414
-236-stable-diffusion-v2-text-to-image-demo-with..> 26-Jan-2024 01:05             1057851
-

-
diff --git a/docs/notebooks/236-stable-diffusion-v2-text-to-image-with-output.rst b/docs/notebooks/236-stable-diffusion-v2-text-to-image-with-output.rst
index 57d88c70e0ee85..346fa1b0a03432 100644
--- a/docs/notebooks/236-stable-diffusion-v2-text-to-image-with-output.rst
+++ b/docs/notebooks/236-stable-diffusion-v2-text-to-image-with-output.rst
@@ -950,7 +950,7 @@ Now, you can define a text prompts for image generation and run
 inference pipeline. Optionally, you can also change the random generator
 seed for latent state initialization and number of steps.
 
-   **Note**: Consider increasing ``steps`` to get more precise results.
+   **NOTE**: Consider increasing ``steps`` to get more precise results.
    A suggested value is ``50``, but it will take longer time to process.
 
 .. code:: ipython3
diff --git a/docs/notebooks/237-segment-anything-with-output.rst b/docs/notebooks/237-segment-anything-with-output.rst
index eda857209e557a..bcfc646f5c91e4 100644
--- a/docs/notebooks/237-segment-anything-with-output.rst
+++ b/docs/notebooks/237-segment-anything-with-output.rst
@@ -1413,7 +1413,7 @@ result, we will use a ``mixed`` quantization preset. It provides
 symmetric quantization of weights and asymmetric quantization of
 activations.
 
-   **Note**: Model post-training quantization is time-consuming process.
+   **NOTE**: Model post-training quantization is time-consuming process.
    Be patient, it can take several minutes depending on your hardware.
 
 .. code:: ipython3
@@ -1451,6 +1451,8 @@ activations.
 
     model quantization finished
 
+
+
 .. code:: ipython3
 
     ov_encoder_path_int8 = "sam_image_encoder_int8.xml"
diff --git a/docs/notebooks/237-segment-anything-with-output_files/index.html.tmp b/docs/notebooks/237-segment-anything-with-output_files/index.html.tmp
deleted file mode 100644
index 7cf50b3b95b86f..00000000000000
--- a/docs/notebooks/237-segment-anything-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,18 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/237-segment-anything-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/237-segment-anything-with-output_files/
../
-237-segment-anything-with-output_21_0.png          26-Jan-2024 01:04              467418
-237-segment-anything-with-output_28_0.png          26-Jan-2024 01:04              468529
-237-segment-anything-with-output_35_0.png          26-Jan-2024 01:04              469443
-237-segment-anything-with-output_39_0.png          26-Jan-2024 01:04              470668
-237-segment-anything-with-output_44_0.png          26-Jan-2024 01:04              468092
-237-segment-anything-with-output_48_0.png          26-Jan-2024 01:04              468088
-237-segment-anything-with-output_53_0.png          26-Jan-2024 01:04              472756
-237-segment-anything-with-output_68_1.jpg          26-Jan-2024 01:04              262203
-237-segment-anything-with-output_68_1.png          26-Jan-2024 01:04             2409333
-237-segment-anything-with-output_80_0.png          26-Jan-2024 01:04              469432
-237-segment-anything-with-output_82_1.jpg          26-Jan-2024 01:04              262535
-237-segment-anything-with-output_82_1.png          26-Jan-2024 01:04             2397126
-

-
diff --git a/docs/notebooks/238-deep-floyd-if-convert-with-output_files/index.html.tmp b/docs/notebooks/238-deep-floyd-if-convert-with-output_files/index.html.tmp
deleted file mode 100644
index c821a457bcecf0..00000000000000
--- a/docs/notebooks/238-deep-floyd-if-convert-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,9 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/238-deep-floyd-if-convert-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/238-deep-floyd-if-convert-with-output_files/
../
-238-deep-floyd-if-convert-with-output_29_3.png     26-Jan-2024 01:05               10887
-238-deep-floyd-if-convert-with-output_31_3.png     26-Jan-2024 01:05              129741
-238-deep-floyd-if-convert-with-output_41_0.png     26-Jan-2024 01:05             1349882
-

-
diff --git a/docs/notebooks/238-deep-floyd-if-optimize-with-output_files/index.html.tmp b/docs/notebooks/238-deep-floyd-if-optimize-with-output_files/index.html.tmp
deleted file mode 100644
index 353fd8146fabec..00000000000000
--- a/docs/notebooks/238-deep-floyd-if-optimize-with-output_files/index.html.tmp
+++ /dev/null
@@ -1,12 +0,0 @@
-
-Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/238-deep-floyd-if-optimize-with-output_files/
-
-
Index of /projects/ov-notebook/0.1.0-latest/20240125220808/dist/rst_files/238-deep-floyd-if-optimize-with-output_files/
../
-238-deep-floyd-if-optimize-with-output_23_6.jpg    26-Jan-2024 01:05                2577
-238-deep-floyd-if-optimize-with-output_23_6.png    26-Jan-2024 01:05               11369
-238-deep-floyd-if-optimize-with-output_24_5.jpg    26-Jan-2024 01:05               23341
-238-deep-floyd-if-optimize-with-output_24_5.png    26-Jan-2024 01:05              164221
-238-deep-floyd-if-optimize-with-output_25_1.jpg    26-Jan-2024 01:05              210327
-238-deep-floyd-if-optimize-with-output_25_1.png    26-Jan-2024 01:05             1937722
-

-
diff --git a/docs/notebooks/239-image-bind-convert-with-output.rst b/docs/notebooks/239-image-bind-convert-with-output.rst
index 8a6f25798bb364..d2974d5fa106a3 100644
--- a/docs/notebooks/239-image-bind-convert-with-output.rst
+++ b/docs/notebooks/239-image-bind-convert-with-output.rst
@@ -95,28 +95,28 @@ Prerequisites
 .. code:: ipython3
 
     import sys
-
+    
     %pip install -q soundfile pytorchvideo ftfy "timm>=0.6.7" einops fvcore "openvino>=2023.1.0" numpy scipy matplotlib --extra-index-url https://download.pytorch.org/whl/cpu
-
+    
     if sys.version_info.minor < 8:
         %pip install -q "decord"
     else:
         %pip install -q "eva-decord"
-
+    
     if sys.platform != "linux":
-        %pip install -q "torch>=2.0.1" "torchvision>=0.15.2" "torchaudio>=2.0.2"
+        %pip install -q "torch>=2.0.1" "torchvision>=0.15.2,<0.17.0" "torchaudio>=2.0.2"
     else:
-        %pip install -q "torch>=2.0.1" "torchvision>=0.15.2" "torchaudio>=2.0.2" --index-url https://download.pytorch.org/whl/cpu
+        %pip install -q "torch>=2.0.1" "torchvision>=0.15.2,<0.17.0" "torchaudio>=2.0.2" --index-url https://download.pytorch.org/whl/cpu
 
 .. code:: ipython3
 
     from pathlib import Path
-
+    
     repo_dir = Path("ImageBind")
-
+    
     if not repo_dir.exists():
         !git clone https://github.com/facebookresearch/ImageBind.git
-
+    
     %cd {repo_dir}
 
 
@@ -147,7 +147,7 @@ card `__.
     import torch
     from imagebind.models import imagebind_model
     from imagebind.models.imagebind_model import ModalityType
-
+    
     # Instantiate model
     model = imagebind_model.imagebind_huge(pretrained=True)
     model.eval();
@@ -186,11 +186,11 @@ data reading and preprocessing for each modality.
 .. code:: ipython3
 
     # Prepare inputs
-
+    
     text_list = ["A car", "A bird", "A dog"]
     image_paths = [".assets/dog_image.jpg", ".assets/car_image.jpg", ".assets/bird_image.jpg"]
     audio_paths = [".assets/dog_audio.wav", ".assets/bird_audio.wav", ".assets/car_audio.wav"]
-
+    
     inputs = {
         ModalityType.TEXT: data.load_and_transform_text(text_list, "cpu"),
         ModalityType.VISION: data.load_and_transform_vision_data(image_paths, "cpu"),
@@ -223,14 +223,14 @@ embeddings.
             super().__init__()
             self.model = model
             self.modality = modality
-
+        
         def forward(self, data):
             return self.model({self.modality: data})
 
 .. code:: ipython3
 
     import openvino as ov
-
+    
     core = ov.Core()
 
 Select inference device
@@ -243,14 +243,14 @@ select device from dropdown list for running inference using OpenVINO
 .. code:: ipython3
 
     import ipywidgets as widgets
-
+    
     device = widgets.Dropdown(
         options=core.available_devices + ["AUTO"],
         value='AUTO',
         description='Device:',
         disabled=False,
     )
-
+    
     device
 
 
@@ -265,7 +265,7 @@ select device from dropdown list for running inference using OpenVINO
 .. code:: ipython3
 
     ov_modality_models = {}
-
+    
     modalities = [ModalityType.TEXT, ModalityType.VISION, ModalityType.AUDIO]
     for modality in modalities:
         export_dir = Path(f"image-bind-{modality}")
@@ -347,17 +347,17 @@ they represent the same object.
     import matplotlib.pyplot as plt
     import numpy as np
     from scipy.special import softmax
-
-
+    
+    
     def visualize_prob_matrix(matrix, x_label, y_label):
         fig, ax = plt.subplots()
         ax.matshow(matrix, cmap='winter')
-
+    
         for (i, j), z in np.ndenumerate(matrix):
             ax.text(j, i, '{:0.3f}'.format(z), ha='center', va='center')
             ax.set_xticks(range(len(x_label)), x_label)
             ax.set_yticks(range(len(y_label)), y_label)
-
+    
     image_list = [img.split('/')[-1] for img in image_paths]
     audio_list = [audio.split('/')[-1] for audio in audio_paths]
 
@@ -369,7 +369,7 @@ Text-Image classification
 .. code:: ipython3
 
     text_vision_scores = softmax(embeddings[ModalityType.VISION] @ embeddings[ModalityType.TEXT].T, axis=-1)
-
+    
     visualize_prob_matrix(text_vision_scores, text_list, image_list)
 
 
@@ -385,7 +385,7 @@ Text-Audio classification
 .. code:: ipython3
 
     text_audio_scores = softmax(embeddings[ModalityType.AUDIO] @ embeddings[ModalityType.TEXT].T, axis=-1)
-
+    
     visualize_prob_matrix(text_audio_scores, text_list, audio_list)
 
 
@@ -401,7 +401,7 @@ Image-Audio classification
 .. code:: ipython3
 
     audio_vision_scores = softmax(embeddings[ModalityType.VISION] @ embeddings[ModalityType.AUDIO].T, axis=-1)
-
+    
     visualize_prob_matrix(audio_vision_scores, image_list, audio_list)
 
 
@@ -424,7 +424,7 @@ Putting all together, we can match text, image, and sound for our data.
 
 .. parsed-literal::
 
-    Predicted label: A car
+    Predicted label: A car 
     probability for image - 1.000
     probability for audio - 1.000
 
@@ -437,7 +437,7 @@ Putting all together, we can match text, image, and sound for our data.
 
 .. raw:: html
 
-
+