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Commits on May 7, 2020
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Gluon data 2.0: c++ dataloader and built-in image/bbox transforms (#1…
…7841) * c++ dataloader and built-in image/bbox * update * fix error * fix import error * fix ci build * fix vs openmp loop type * fix warning as error with sign/unsign comp * sign/unsign comp * update to pytest * remove nose * fix tear_down * address comments * thread safe dataset * address comments * address comments * fix * serial pytest for data download
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* fix the error message of reshape() * Fixing issue #16655 reshape() error message Co-authored-by: Ubuntu <[email protected]>
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Change include to relative in nvvm_to_onnx.cc (#18249)
Signed-off-by: Serge Panev <[email protected]>
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fixed overwrite of args/aux variables (#18232)
* fixed overwrite of args/aux variables * fixed spacing
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Commits on May 8, 2020
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fix when clicking version dropdown it jumps to top of the page (#18238)
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Commits on May 9, 2020
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Commits on May 10, 2020
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Change LC_NUMERIC for CentOS CI jobs to verify locale invariance (#18097
) * Load the user's locale before performing tests * Change the locale for the CentOS CI jobs to weed out locale-related bugs * Mark tests that fail due to the decimal point with xfail * Run localedef when generating the CentOS CI image * Cancel some Scala tests when C locale uses a non-standard decimal sep. * Rename xfail helper to xfail_when_nonstandard_decimal_separator * Fix scalastyle errors * Disable more Python tests that fail due to locale-related issues * Move assumeStandardDecimalSeparator into separate object to fix scaladoc * Disable the "symbol pow" test when running with non-standard decimal sep * Disable new tests that fail due to locale-related issues
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Fix interleave matmul doc (#18260)
* fix doc * fix doc * fix axis Co-authored-by: Lin <[email protected]>
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Commits on May 11, 2020
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CI: Update Android, ARM build and ARM test containers (#18264)
* Android build containers * ARM build containers * ARM test containers * Fix naming scheme * Set WORKDIR at correct location
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[Numpy] Port nd.random.multinomial to npx.sample_categorical (#18272)
* port nd.multinomial to npx.sample_categorical * move to npx.random
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[Numpy] New FFIs for Operator: squeeze, repeat, around, round, diagfl…
…at (#18263) * FFI new feature * Feature ffi x 5 * Fix pylint error * Fix pylint error * Fix around error * repeat modified
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Commits on May 12, 2020
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Update unix gpu toolchain (#18186)
* update nvidiadocker command & remove cuda compat * replace cu101 with cuda since compat is no longer to be used * skip flaky tests * get rid of ubuntu_build_cuda and point ubuntu_cu101 to base gpu instead of cuda compat * Revert "skip flaky tests" This reverts commit 1c720fa. * revert removal of ubuntu_build_cuda * add linux gpu g4 node to all steps using g3 in unix-gpu pipeline
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Co-authored-by: Lin <[email protected]>
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Commits on May 13, 2020
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Revert PR 17767 for fixing GPU memory usage regression (#18283)
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Commits on May 14, 2020
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Fix LSTM and GRU layers gradient calculations (#18203)
* Fix input gradient calculation for bidirectional LSTM For bidiractional LSTM with number of layers > 2 input gradient calculation was incorrect. Reason of wrong calculations was overwriting y derivative (dy) tensor by calculated x derivative (dx) tensor before right2left layer could use dy for own gradient calculations. Propsed fix uses additional space to avoid overwriting. * Fix gradient calculation for GRU For GRU with number of layers > 2 i2h_weight gradient for layers in the middle (all except last and first) was incorrect. Wrong caluculations were caused by assigning output pointer to input instead of calculating new input pointer. * Enable tests for GRU and LSTM gradients * Fix comments * Change loop iteration deduction * Add more test cases for fused rnn layers
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Changes to mxnet.metric (#18083)
* finish 5 changes * move metric.py to gluon, replace mx.metric with mx.gluon.metric in python/mxnet/ * fix importError * replace mx.metric with mx.gluon.metric in tests/python * remove global support * remove macro support * rewrite BinaryAccuracy * extend F1 to multiclass/multilabel * add tests for new F1, remove global tests * use mxnet.numpy instead of numpy * fix sanity * rewrite ce and ppl, improve some details * use mxnet.numpy.float64 * remove sklearn * remove reset_local() and get_global in other files * fix test_mlp * replace mx.metric with mx.gluon.metric in example * fix context difference * Disable -DUSE_TVM_OP on GPU builds * Fix disable tvm op for gpu runs * use label.ctx in metric.py; remove gluoncv dependency in test_cvnets * fix sanity * fix importError * remove nose Co-authored-by: Ubuntu <[email protected]> Co-authored-by: Leonard Lausen <[email protected]>
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Reenable test_amp_conversion (#18292)
TVMOP feature is now disabled on GPU builds, which caused this test to fail previously
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Commits on May 15, 2020
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Fix memory leaks in Gluon (#18328)
Fix leak of ndarray objects in the frontend due to reference cycle.
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Commits on May 16, 2020
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Add a timeout to the storage profiler in case mem_counters_ is not ye…
…t initialized (#18306) * avoid race condition in profiler init * Update storage_profiler.h Co-authored-by: Ubuntu <[email protected]>
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Commits on May 17, 2020
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[CI] run operator tests with naive engine (#18252)
* run operator tests with naive engine * fix take tests * update skip mark * fix cuda error reset * adjust tests * disable parallel testing and naive engine for mkl/mkldnn #18244
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[numpy] add dlpack functions to npx (#18342)
* add dlpack functions to npx * improve tests * further improve test * fix comment
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Commits on May 18, 2020
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[BUGFIX] Remove Profiler from the runtime feature list, since its alw…
…ays built (#18308) * remove Profiler from the runtime feature list, since its always built * Update libinfo.cc * Update RunTime.pm Co-authored-by: Lin <[email protected]>
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Commits on May 19, 2020
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Include lib/libopenblas.so.0 on CD (#18356)
The cmake staticbuild script doesn't link openblas statically, but rather provides the so file to be included in the distribution. This is intentional, as it simplifies the build script, but update of Jenkinsifle was missed when switching the CD to rely on cmake.
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cmake: check compiler supports C++17 sufficiently (#18354)
By default cmake accepts any compiler that supports at least some part of C++17. In practice this leads to hard to understand error messages at later stages during compilation, as for example gcc5 supports part of C++17 but does not support C++17 sufficiently to compile MXNet.
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Disable test_sequential_rnn_cells (#18360)
* Disable test_sequential_rnn_cells * Disable test_np_mixed_precision_binary_funcs * Disable test_rnn_forward_backward
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[Numpy] FFI: max/min/amax/amin (#17824)
* ffi_min_max * pylint fix Co-authored-by: Hao Jin <[email protected]>
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Include all mkldnn headers in CD builds (#18355)
* Fix cmake mkldnn install target. Previously mkldnn headers are installed to CMAKE_INSTALL_INCLUDEDIR instead of CMAKE_INSTALL_INCLUDEDIR/mkldnn * Fix pypi_package.sh pip/setup.py for mkldnn builds
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Website global search feature (#18288)
* init global search ui * add hover effect to icon and refactor js * add search bar ui styles * fix search UI's effect on navbar height * add fade in/out effect to search ui and navbar * update search trigger to click and add x button for close * add version select for search * fix version typo * update dropdown * fix hitsperpage reset after change version * fix nav trigger not show * update search border css class name * make dropdown style consistent * global search mobile&tablet UI * adjust mobile search result width * extract global search related styles to a seperate scss * restore formatting to existing code * format & coding style * fix caret height bug * add mobile compatible UI * add license header to js files and update dropdown width * put docsearch css before main to overrides * update search result panel height * dynamically generate version dropdown * use more accurate selector over search result * use vh for height * add comments to scss * move versions to Jekyll global variable * remove redundant version key * make global search default version the same as website version Co-authored-by: Yang Shi <[email protected]>
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Commits on May 20, 2020
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replace google CDN with JQuery's own CDN (#18369)
Co-authored-by: Yang Shi <[email protected]>
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[Website 2.0] Artifact URL Adjustment (#18340)
* Testing new S3 bucket without publish step * Adding publish step & restricted nodes for prod * Drop restricted on primary node for testing' * Revert to restricted nodes with publishing
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Fix races in block scope (#17749)
* Add tests * Fix block_scope Co-authored-by: Haibin Lin <[email protected]> Co-authored-by: Lin <[email protected]>
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Commits on May 21, 2020
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Fix race condition in unittest by pytest temp_dir fixtures (#18323)
* serial tests * pytest fixture temp_dir * address comments
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[Numpy] Fix gluon activations (#18370)
* fix activation numpy bug * Update test_numpy_gluon.py * fix
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Commits on May 22, 2020
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Fix FInferShape for some ops to support partial type inference (#18348)
* Fix FInferShape for some ops to support partial type inference Signed-off-by: Serge Panev <[email protected]> * Add missing ndim check in in matrix_op-inl.h Signed-off-by: Serge Panev <[email protected]>
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Fix binary scalar dtype and add bool support (#18277)
* add boolean support for concatenate (#18213) * fix binary scalar logic dtype (#16964) * common_expr test remove * binary scalar op support scalar dtype Co-Authored-By: Wentao Xu <[email protected]> * test_error_fix Co-authored-by: Wentao Xu <[email protected]>
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Fix reference leak in Block._children and enable reference leak tests…
… universally (#18376) * Fix reference leak in Block._children * Activate everywhere * Disable on CentOS * Fix
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Introduce MXNET_BUILD_SHARED_LIBS to specify build type of libmxnet (#…
…18365) * Consider BUILD_SHARED_LIBS flag * Use MXNET_BUILD_SHARED_LIBS
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Commits on May 23, 2020
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Commits on May 24, 2020
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[numpy] Fix mean, prod with input of empty array (#18286)
* prod * mean * nan * sanity * change kernel * include Co-authored-by: Ubuntu <[email protected]>
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Commits on May 25, 2020
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Fix Win Environ "PATH" does not exists Bug (#18402)
When "PATH" are not in the environment, we will get error when reading os.environ['PATH']. Change to os.environ.get('PATH', '') to fix it.
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Add docs about default dtype (#18399)
* add doc about default dtype * fix sanity error
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Commits on May 26, 2020
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Commits on May 27, 2020
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Remove references to MXNet convenience binaries on Maven (#18410)
* Remove references to MXNet convenience releases on Maven These convenience binaries redistributed Category-X binaries in violation of ASF policies. References: - https://www.apache.org/legal/resolved.html#category-x - https://lists.apache.org/thread.html/rad2fbedc0ae3d0ab9e6f9f453d2b4000f6a318939c7b92783d9e5693%40%3Cdev.mxnet.apache.org%3E - https://lists.apache.org/thread.html/r738c102492649c754f49e2195985bc765df07df3c8a1e06942e8872f%40%3Cdev.mxnet.apache.org%3E * Update get_started page
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change _Pragma to #pragma (#18379)
* change _Pragma to #pragma._Pragma not work with msvc * new plan * fix lint * add arg * fix * fix lint * fix
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Fix CD failure due to illegal instruction in OpenBLAS (#18408)
* Update to OpenBlas 0.3.10 pre-release Includes OpenMathLib/OpenBLAS#2527 * Enable support for older architectures in OpenBLAS dynamic architecture feature
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Commits on May 28, 2020
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remove mx.model.FeedForward API (#18394)
* Remove mx.model.FeedForward API * remove more tests * remove tools depending on FeedForward * Update model.py Co-authored-by: Ubuntu <[email protected]> Co-authored-by: Lin <[email protected]>
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Commits on May 30, 2020
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CI: Prime docker cache in "Docker cache build" job (#18438)
Cache priming was previously only handled when using the ./ci/build.py or ./ci/docker_cache.py script. The former is used during most CI jobs. The latter is used for containers not declared in docker-compose.yml during the "Docker cache build" job. More and more containers are declared in docker-compose.yml now, but prior to this commit their cache wasn't primed in the "Docker cache build" job.
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[website] Redirect Chinese visitors to Apache Chinese CDN provider PA…
…RT 1 (#18431) * website - redirect Chinese visitors to Apache Chinese CDN provider * switch to mod_geoip for most accurate redirecting Co-authored-by: Yang Shi <[email protected]>
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Commits on May 31, 2020
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Update basic_layers.py fix fix Update basic_layers.py fix bug
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Commits on Jun 1, 2020
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Improve log_softmax op performance by using DNNL support (#18320)
* Improve log_softmax performance by OneDNN library * Adapt tests for MKLDNN log_softmax * Fix lint errors * Fix indent and comments
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Update nccl installation in Dockerfile.build.centos7 (#18441)
By moving the NCCL installation before the COPY runtime_functions.sh statement, users will not suffer from cache invalidation due to the COPY and don't have to repeat the nccl installation locally as there will be a cache hit.
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Commits on Jun 2, 2020
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More clear description to
transform_first
(#18444)* More clear description to `transform_first` After teaching an MLU-CV class, some students feel confused when they are using the `transform_first` function. So I modified it a bit to make it more clear. :) * remove space Co-authored-by: JackieWu <[email protected]>
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Add npx op 'index_add' (#18089)
* part cpu * index_add forward & test * fix wrong doc * fix index_add_sanity_error * index_update_test * remove index_update & implement index_add backward * fix sanity error * reduce code length * depart into two file * test CI compiler * test CI * test CI * reduce mshadow & allow more dtype * fix sanity error * fix conflict * reduce fwd macro code * reduce bwd macro code * fix compile error * tensor ind * remove cudaMalloc/cudaFree * fix windows compile error * fix compile error * use value instead of references * remove pragma * fix naive engine error * try to pass CI * fix sanity error * depart gradient into three node * resolve comment & initialize mshadow::Shape * fix werror Co-authored-by: Ubuntu <[email protected]> Co-authored-by: Ubuntu <[email protected]> Co-authored-by: Xingjian Shi <[email protected]>
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stop running test_conv.py script as it no longer exists (#18455)
* stop running test_conv.py script as it no longer exists * revert adding mkldnn test for cu* builds
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redirect visitors based on geolocation - update host condition (#18457)
Co-authored-by: Yang Shi <[email protected]>
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[Numpy] [Operator] Fix __neg__ (#18467)
* fix negation * support boolean type * Update elemwise_unary_op.h * Update test_numpy_op.py
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Commits on Jun 3, 2020
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Julia: fix 7z path on Win. (#18461)
* Julia has changed the folder of 7z.exe. * Update julia/deps/build.jl 7z.exe folder issue resolved Co-authored-by: Iblis Lin <[email protected]> Co-authored-by: Iblis Lin <[email protected]>
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Dynamically Generate Version Dropdown (#18473)
* dynamically generate general version dropdown * dynamic generate installation guide version dropdown * fix type * use var Co-authored-by: Yang Shi <[email protected]>
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[Numpy]Fix einsum issue #18102 (#18419)
* * Fix einsum Bug * * Fix sanity * * Fix one dim start bug * * Fix test case gt
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Commits on Jun 4, 2020
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Add Developer Guide Docs to MXNet Website (#18474)
* init dev guide * move dev guide above FAQ * update format and images * hoist git docs and fix styles * use relative urls * remove useless code block * use consistent url and file name * update heading * add apache license header * init dev guide * move dev guide above FAQ * update format and images * hoist git docs and fix styles * use relative urls * remove useless code block * use consistent url and file name * update heading * add apache license header * update doc - git clone recursive * reviewing the dev guide - proof reading and text edits Co-authored-by: Yang Shi <[email protected]> Co-authored-by: Talia Chopra <[email protected]>
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BytePS trainer + tests (#18032)
* [MXNET-#16795] Byteps-KVStore: Intergrate Byteps into mxnet as new type of kvstore backend (#17555) * Add Byteps backend for kvstore * Add a temp launcher for byteps backend * make the test fit for byteps kvstore. * final workable test * Remove trashy print and logs * correct comment * add hostfile for ci test * add ci test for byteps kvstore * add visibile devices for byteps-kvstore ci test * add licenses for tools/byteps_launcher.py * syntax error * pylint error (remove unused import like logging) * pylint error * pylint error * enable launching without hostfile (local byteps) * 1. rename byteps_kvstore.py to byteps.py; 2. shorten the launch option to ; 3. add instruction for -H and -SH options for launch; 4. add documentation for byteps kvstore in kvstore/base.py: create(name='local') * edit documentation of KVStoreBase::is_capable(capability); reture fasle for BytePS(KVStoreBase):is_capable(any). * pylint error * remove an error of arg.byteps * use --env option to set workers' environment * error in byteps-launcher.py * remove the unpurposed editing mistake in runtime_functions.sh * disable cpu support for byteps kvstore. * 1. format the document to avoid julia doc build error; 2. little change to nightly test; 3. add byteps copy right declararation in byteps_launcher.py 4. if args.byteps == True ===> if args.byteps * remove the --scheduler_ip and --scheduler_port options in launch.py * 1. maintain the origin value of broadcast and pushpull 2. optimize when out = value or [out]=value 3. add some missing documentation to avoid doc building error. * Add bytePS to CI * add dependency * +integrationtest_ubuntu_gpu_byteps * add byteps pipeline * disable a few tests * remove more tests * fix permission * remove apt-get * fix python path * improve logging * fix printns * add back CI Co-authored-by: Ubuntu <[email protected]> Co-authored-by: Piyush Ghai <[email protected]> Co-authored-by: eric-haibin-lin <[email protected]> Co-authored-by: eric-haibin-lin <--global> Co-authored-by: Lin <[email protected]> * fix byteps logging and declare tensor * check exceptions and return -1 * print logging in CI * Update byteps.py * Update runtime_functions.sh * add numa dependency * pin dependency * Update runtime_functions.sh * Update Dockerfile.build.ubuntu * Update runtime_functions.sh * Update runtime_functions.sh * Update runtime_functions.sh * Update runtime_functions.sh * Update Jenkins_steps.groovy * remove launcher. use bpslauncher instead. Co-authored-by: Chaokun Chang <[email protected]> Co-authored-by: Ubuntu <[email protected]> Co-authored-by: Piyush Ghai <[email protected]> Co-authored-by: Lin <[email protected]> Co-authored-by: Ubuntu <[email protected]> Co-authored-by: EC2 Default User <[email protected]> Co-authored-by: Ubuntu <[email protected]>
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Commits on Jun 5, 2020
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Revert installation dropdown change (#18488)
This broke the version selector. Co-authored-by: Yang Shi <[email protected]>
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Add image classification tutorial for jetson (#18434)
* add image classification tutorial for jetson * update code to use gluon model zoo; update doc * referencing MXNet official website for Jetson installation guide
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Update Jetson installation guide (#18485)
* add config Makefile for jetson * modify jetson install guide
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Fix tests for ONNX version 1.5.0 bump (#18054)
* implement onnx translation helpers * bump onnx version to 1.5 * add export only test cases for topk and slice_axis
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Commits on Jun 6, 2020
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Commits on Jun 8, 2020
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remove tools dependent on mx.module APIs (#18508)
* remove tools depending on mx.module * remove caffe converter and coreml tools Co-authored-by: Lin <[email protected]>
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* remove mx.rnn APIs * fix test * update test Co-authored-by: Ubuntu <[email protected]> Co-authored-by: Lin <[email protected]>
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[Bug Fixed] Fix batch norm when grad_req is
add
(#18500)* fix batch norm when fix_gamma is True * support gradient accumulation for batch norm * mkldnn batchnorm support grad add * unittest for bn * fix bn arg * fix lint * fix mkldnn * fix mkldnn bn * fix grad when fixing gamma * fix naive gpu bn * fix lint * fix cudnn bn * fix flag * fix lint * fix testcase * fix * use @pytest.mark.parametrize * combination * remove redundant test in batchnorm * npx.batch_norm test * try to fix test * reduce the number of tests for batchnorm * fix
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Drop list support in optimize_for (#18483)
* initial commit * fixed typos * changed warning to exception * updated subgraph_op unittests
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Commits on Jun 9, 2020
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[numpy] fix op repeat with list input (#18371)
* except .h * except storage * repeat * change fwd * delete * codecov Co-authored-by: Ubuntu <[email protected]>
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Commits on Jun 10, 2020
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Consolidate installation instructions on website and add disclaimer f…
…or non-ASF ressources (#18487) * Update website with disclaimer for non-ASF ressources * Integrate Windows instructions to build_from_source.md * Remove master version from selector * Update Download links * Update get_started/download.md per Release Download Page policy
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Add backward Type inference to main NN operators (#18378)
* Add backward Type inference to main DNN operators Signed-off-by: Serge Panev <[email protected]> * Add comments Signed-off-by: Serge Panev <[email protected]>
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Commits on Jun 11, 2020
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remove mx.module.* APIs for MXNet 2.0 (#18525)
* remove Module tests * remove APIs relying on module * remove docs and tools using mx.module * remove executor manager * remove ssd and ncf examples * add back grad compression api doc * fix lint * add back cpredict exmaple * fix resnet memory test * remove tests * remove tests/python/tensorrt/test_tensorrt_lenet5.py since it depends on a model traiend by mx.Module * skip flaky test * fix quantization test * remove subgraph tests Co-authored-by: EC2 Default User <[email protected]> Co-authored-by: Lin <[email protected]>
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revert changes causing cd failures (#18533)
Reverting the following changes to cd_unittest_ubuntu causing CD pipeline failures: The first change was using Naive Engine for operator tests, which causes timeout failures in CD Added here: 10b6b48 Second change was running integrationtest_ubuntu_gpu_byteps as part of cu* CD tests, added here: e28e9fe
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Fix Slow Site Loading Speed part2 (#18512)
* host JQuery locally * defer time consuming scripts * defer more render-blocking script * move general version dropdown css from head to scss * update quotation mark * add cache control * add licenses info to jquery * remove jquery from github # Conflicts: # docs/static_site/src/assets/js/jquery-3.3.1.min.js * load jquery based on env * update wget jquery command Co-authored-by: Yang Shi <[email protected]>
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Commits on Jun 12, 2020
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Remove XXOutput loss operators (#18531)
* remove xxOutput operators used in Module * remove SVMOutput * remove RegressionOutput in language binding * remove more examples * fix scala, perl * remove spark examples * remove softmaxoutput op * remove more tests * remove more SoftmaxOutput related code * remove MAERegression * remove symbol.Softmax * fix perl test count * fix failing tests * remove mlp cpu test * fix scala test * remove tests/examples relying on imagenet-1k pretrained symbolic models * fix scala build * remove MultiTaskSuite for scala * fix cpp build * fix scale, clojure test * fix scala and python test * fix scala and clojure test * remove clojure test * remove clojure test * remove test_forward for python * remove clj viz test * remove viz tests * remove clj tutorail test * remove bert test * remove clj tests * remove clj multi-label test * remove module mlp test for clh * remove module test for clj * rm ./contrib/clojure-package/test/org/apache/clojure_mxnet/ndarray_api_test.clj * remove clj tests * rm test_mkldnn_model Co-authored-by: EC2 Default User <[email protected]> Co-authored-by: Lin <[email protected]>
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Commits on Jun 13, 2020
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Remove the deprecated BatchNorm_v1 op (#18538)
* remove batchnorm_v1 * fix gpu build Co-authored-by: EC2 Default User <[email protected]> Co-authored-by: Lin <[email protected]>
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Commits on Jun 14, 2020
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remove dependency on train_mnist.py script (#18550)
* remove dependency on train_mnist.py script * remove image classification tests from nightly
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Commits on Jun 15, 2020
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Add options for stackoverflow and discuss to issue_template & disable blank issue
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[OpPerf] Add example of using opperf with internal op locally (#18324)
* add example of using opperf with internal op locally * split diff to old and new code for readability * mx.nd.copyto doesnt exist & website title shows ndarray instead of symbol * Revert "mx.nd.copyto doesnt exist & website title shows ndarray instead of symbol" This reverts commit 118b090.
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Commits on Jun 16, 2020
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Julia: fix deprecation in visualize.jl (#18515)
* Update visualize.jl matchall has been deprecated as of Julia 1.3. Changes made to fix. * Cleaned * Update julia/src/visualize.jl * Update julia/src/visualize.jl Co-authored-by: Iblis Lin <[email protected]>
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add op npx.index_update (#18545)
* add op npx.index_update * remove debug comment * change eps * fix stupid error * add blank line in docs * gpu temporary space request alignment * fix test error Co-authored-by: Ubuntu <[email protected]>
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Test CD mxnet_lib/static and python/pypi stages on CI (#18559)
* add cd mxnet_lib/static stages to ci * add cd pypi packaging stage to ci * removing existing cmake static compile stages in favor of other added stages * pass mxnet_variant correctly
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Commits on Jun 17, 2020
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add FAQ redirect rules (#18552)
Co-authored-by: Yang Shi <[email protected]>
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fix contribute page anchor position shifted (#18571)
Co-authored-by: Yang Shi <[email protected]>
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Commits on Jun 18, 2020
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fix misbehave of KLDivLoss (#18423)
* fix misbehave of KLDivLoss In the current version of KLDivLoss, the return value is not the same value calculated by SoftmaxCrossEntropyLoss, which is not documented. It may due to the incorrect settings which using mean rather than sum dealing with the return value. I provide a fix of this setting, which will keep the return value of `KLDivLoss` and SoftmaxCrossEntropyLoss` almost the same when `from_logits=False` and `sparse_label=False` are set to these functions seperately. Now, the behave of KLDivLoss is exactly the same to what the document say. ``` import mxnet as mx a=mx.nd.array([[-1,1],[1,-1]]) b=mx.nd.array([1,0]).one_hot(2) TrueLoss=mx.gluon.loss.SoftmaxCrossEntropyLoss(sparse_label=False) FalseLoss=mx.gluon.loss.KLDivLoss(from_logits=False) c=TrueLoss(a,b) d=FalseLoss(a,b)*a.shape[-1] assert((c-d).abs().sum()==0 and a.shape[-1]==2) ``` * update sdml loss the current version of SDMLLoss told us to `multiply for the number of labels` but actually it `multiply batch_size`. After this PR, it is no need to `multiply batch_size` or `multiply the number of labels` any more. * remove outdated comment
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[Numpy] Bugfix of slice operator export (MXNet to ONNX) v2 (#18535)
* fixed get_inputs() for onnx slice operator export * added unit test for onnx slice operator export * implement get_inputs with_shapes helper * update slice ops to use with_shapes * added verbose parameter for get_outputs() Co-authored-by: Andrey Stotskiy <[email protected]>
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Update cmake/upstream/FindCUDAToolkit.cmake (#18528)
Previously MXNet includes a hotfix for a cross-compiling bug in upstream FindCUDAToolkit.cmake. Upstream has fixed the bug now in their master branch. Replace MXNet's fix by the upstream fix to avoid diverging from upstream. See https://gitlab.kitware.com/cmake/cmake/-/issues/20572
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Commits on Jun 19, 2020
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Simplify mxnet.gluon Block APIs (#18413)
## Motivations Currently the implementation of mxnet.gluon.block is not so pythonic and there are many redundancies ### 1. overlaps between Block._params and Block._reg_params when we want to self-define a model, we currently need to use the code as follows: ``` class Net(nn.HybridBlock): def __init__(self, **kwargs): super(HybridNet, self).__init__(**kwargs) with self.name_scope(): self.hidden1 = nn.Dense(256, activation='relu') self.a=self.params.get('a', shape=(1, )) ``` There are several shortcomings when using this form of registration: a. adding parameter ‘a’ will lead to double recordings in both self._params and self._reg_params, which is a redundancy. And there is also a discrepancy in Block: i. In the method “collect_params”, we use “_params” to get all parameters ii. while in the method “_collect_params_with_prefix” (and methods “load_parameters” accordingly), we use “_reg_params” to get all parameters. b. Currently if we do not use “with self.name_scope():” for children blocks, it will lead to wrong name scopes. For the following example, we actually can not get the parameters of self.hidden1 from the result of collect_params ``` class HybridNet(nn.HybridBlock): def __init__(self, **kwargs): super(HybridNet, self).__init__(**kwargs) self.hidden1 = nn.Dense(256, activation='relu') with self.name_scope(): self.hidden2 = nn.Dense(10, activation='relu') def hybrid_forward(self, F, x): x = self.hidden2(self.hidden1(x)) return x >>> net = HybridNet() >>> net.initialize() >>> print(net.collect_params()) hybridnet0_ ( Parameter dense0_weight (shape=(256, -1), dtype=float32) Parameter dense0_bias (shape=(256,), dtype=float32) Parameter hybridnet0_dense0_weight (shape=(10, -1), dtype=float32) Parameter hybridnet0_dense0_bias (shape=(10,), dtype=float32) ) ``` From the above example we can also find that the parameter names are not related to the attributes’ names, which is not straightforward. In all, we find that using name_scope and ParameterDict is not user-friendly. Thus we plan to remove such redundancies and simplify the definitions of children blocks and parameters, like: ``` class Net(nn.HybridBlock): def __init__(self, **kwargs): super(HybridNet, self).__init__(**kwargs) self.hidden1 = nn.Dense(256, activation='relu') self.a=gluon.parameter.Parameter(name="a", shape=(1, )) ``` ### 2. parameter sharing Currently, we use parameter “params” in the definition of Block for parameter sharing. It means before the __init__ of Block, shared parameters already recorded in self._params.shared. And currently Block forbids overriding parameters. We think that this is not convenient. A most common way to share parameter is like what Pytorch does, like ``` self.hidden1.weight=self.hidden2.weight ``` But note that in the case where we have a HybridBlock and the block has been hybridized, then we shouldn't allow overriding the parameter but ask the user to unhybridize the Block first. To further allow sharing parameters recursively, we plan to add an API: ``` def share_parameters(self, params : Dict): ``` We plan to use the structured based form (like what is used in “_collect_params_with_prefix()”) to represent each parameter recursively. For example, we denote “self.hidden1.weight” as “hidden_weight” In all, we plan to make the following improvements: 1. remove parameters “prefix” and “params” in the “\_\_init\_\_" function. 2. remove the use of self._params(ParameterDict) in Block 3. allow parameter attribute overriding in non-hydridization case. 4. add the method “share_parameters" to recursively share parameters in children blocks. ## Parameter naming Once a parameter is created, `param.name` would not be changed in the following operations. It is in the form of `param_{uuid4}_{name}`, where `name` is from `__init __` parameter. Here `name` is optional, default `weight`. It is mainly used to denote which default initialization should be used. We use `param.name` as the name of a parameter's symbol representation. ## collect_params() It returns a `dict`, where the keys are structural names of parameters, like `{'hidden1.weight': Parameter (shape=(3, -1), dtype=float32), 'hidden1.bias': Parameter (shape=(3,), dtype=float32)}` Note that we use `.` as the linking character again because the structured based naming scheme is no longer used in the symbol representation. ## Save and Load For `HybridBlock`, there are two ways to save and load parameters: ### save_parameters() and load_parameters() In `save_parameters()`, we use `structural name` to save parameters, and they should be loaded by `load_parameters()`, which loads parameters based on a model's structure. ### HybridBlock.export and SymbolBlock.imports In `export`, we only save parameters using `param.name` without `structural name`. The param file should be loaded in SymbolBlock.imports. ## SymbolBlock When using `SymbolBlock.imports`, keys in `self.param` would be the loaded parameters' names `param.name`. While in `SymbolBlock(outputs, inputs, params=None)`, if you provide like `params=net.collect_params()`, keys in `self.param` would be structural names of `net`'s parameters (keys in net.collect_params() ). It is often used in this situation that a `SymbolBlock` is a children block of another `HybridBlock`. Otherwise, keys in `self.param` would be the loaded parameters' names `param.name`.
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Link GluonCV object detection tutorial for Jetson (#18530)
* add object detection tutorial for Jetson * adding GluonCV in title * cross reference gluoncv turorial
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[MXNET-889] Implement ONNX export for gluon LSTM. (#17734)
* implement onnx translations for _full type nodes * implement onnx translations for _rnn_param_concat * implement onnx translations for RNN (LSTM mode) * implement node export unittest for gluon.LSTM
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cmake: x86 options only on x86 and remove manual specification on CI (#…
…18588) Use CMAKE_SYSTEM_PROCESSOR to detect target architecture and make x86 related options available only when compiling for x86. Remove the code turning these options manually off on CI. Remove ANDROID cmake option which was used to decide if -lpthread needs to be specified explicitly (on most Linux systems) or not (on Android). Instead auto-detect the behavior.
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Commits on Jun 20, 2020
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Switch to cached op in the testing suite (#18579)
* add default ctx to cachedop fwd * add test * perl fix * initial commit * update sparse tests * add aux_states * fix aux-state type * fix some tests * fix check symbolic forwrad/backward * fix symbolic grad check * arg_dict fixes * support init ops * support forward only graph * fix check symbolic backward stype * add missing file * replace extension test bind * replace bind with _bind * simplify backward_mul implementation * small fix * drop contrib.sparseembedding * remove simple_bind in test sparse ops * use simple_bind * replave simple bind in quantization * fix aux index * update amp simple_bind calls * drop ifft * fix a bug found in subgraph op * add aux_array method * replace symbols * minor fix * fix executor default context * fix import * bug fix for nd.where * add subgraph test * fix forward grad req * fix batch dot dtype * remove unused code * fix slice dtype * fix attach grad * remove tests for non-existing sparse ops * MXCachedOpGetOptimizedSymbol * fix foreach test * enhance err msg * skip failed test * add docs * add docs * fix lint * fix lint, remove quantization * fix lint * fix lint * fix lint * fix build and import * fix import * fix perl call * fix test * remove perl binding * remove reshape test * fix profiler, trt * remove tensorrt test * remove quantization tests * fix import * fix conflcit * fix lint * skip buggy test Co-authored-by: EC2 Default User <[email protected]> Co-authored-by: Lin <[email protected]>
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Commits on Jun 22, 2020
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graph executor c api removal (#18598)
* add default ctx to cachedop fwd * add test * perl fix * initial commit * update sparse tests * add aux_states * fix aux-state type * fix some tests * fix check symbolic forwrad/backward * fix symbolic grad check * arg_dict fixes * support init ops * support forward only graph * fix check symbolic backward stype * add missing file * replace extension test bind * replace bind with _bind * simplify backward_mul implementation * small fix * drop contrib.sparseembedding * remove simple_bind in test sparse ops * use simple_bind * replave simple bind in quantization * fix aux index * update amp simple_bind calls * drop ifft * fix a bug found in subgraph op * add aux_array method * replace symbols * minor fix * fix executor default context * fix import * bug fix for nd.where * add subgraph test * fix forward grad req * fix batch dot dtype * remove unused code * fix slice dtype * fix attach grad * remove tests for non-existing sparse ops * MXCachedOpGetOptimizedSymbol * fix foreach test * enhance err msg * skip failed test * add docs * add docs * fix lint * fix lint, remove quantization * fix lint * fix lint * fix lint * fix build and import * fix import * remove scala, R, julia, perl bindings * remove cpp, matlab bindings * fix perl call * fix test * remove perl binding * remove reshape test * fix profiler, trt * remove tensorrt test * remove quantization tests * fix import * fix conflcit * fix lint * skip buggy test * remove clojure * remove executor c api * remove amalgamation * fix build * move executor folder * fix import * fix lint * fix cpp pcakge * fix predict cpp * fix cpp make * remove jnilint * remove cpp package tset * remove julia test pipeline * disable numpy tests * disable compat test for delete Co-authored-by: EC2 Default User <[email protected]> Co-authored-by: Lin <[email protected]>
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Commits on Jun 23, 2020
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redirect api reference on v-master to v1.6 (#18607)
* redirect api reference on v-master to v1.6 * update R docs
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Allow input reordering duing Gluon / CachedOp graph transformations (#…
…17949) * Initial commit of input reordering in Gluon * Add test for Gluon input reorder * Fix backward in CachedOp for input reordering * Fix test_input_reorder for backward pass * Fix merge error in NaiveCachedOp * Include correct header for std::iota Co-authored-by: Vladimir Cherepanov <[email protected]>
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Commits on Jun 24, 2020
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Update docs according to new Block APIs (#18413)
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Commits on Jun 25, 2020
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add epsilon to adamax (#18532)
Co-authored-by: Ubuntu <[email protected]>
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Commits on Jun 26, 2020
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Commits on Jun 27, 2020
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* add lans optimizer * fix * fix Co-authored-by: Zheng <[email protected]>
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Commits on Jun 29, 2020
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Improve performance of broadcast_axis on CPU (#17882)
* adding comments explaining code optimizations * fixing broadcast_axis kernel to int32 * fixing slice_axis kernel to int32 * combining CPU and GPU implementation method signatures and cleaned up code * adding new broadcast_axis to np_matmul Co-authored-by: Rohit Kumar Srivastava <[email protected]>
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Commits on Jun 30, 2020
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[Numpy] FFI: tril_indices (#18546)
* add numpy tril_indices ffi * Update src/api/operator/numpy/np_matrix_op.cc Co-authored-by: Haozheng Fan <[email protected]> Co-authored-by: Haozheng Fan <[email protected]>
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Commits on Jul 1, 2020
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Fix BatchNorm backward synchronization (#18644)
* Add test for BatchNorm running variables synchronization * Fix BatchNorm backward synchronization It fixes issue #18610
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Fix softmax, logsoftmax failed on empty ndarray (#18602)
* Fix failing empty array (log_)softmax * Modify test for npx (log_)softmax
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Commits on Jul 2, 2020
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* refactor clipboard * make lang getter more extensible * trigger ci
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Commits on Jul 3, 2020
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Add --no-pull option which disables overwriting the local docker cache based on CI docker cache. It is useful when locally changing Dockerfiles.
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[numpy] FFI flip, rollaxis, stack (#18614)
* flip * rollaxis * stack * fixed * retrigger ci Co-authored-by: Ubuntu <[email protected]>
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Commits on Jul 4, 2020
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[numpy] Fix less/greater bug with scalar input (#18642)
* fix ffi * fix less/greater error * back * submodule * fixed Co-authored-by: Ubuntu <[email protected]>
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Commits on Jul 7, 2020
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* user feedback widget implementation * add user feedback widget to python docs site * update margin * add apache license * one more license * turn off feedback widget on python site * update copy * format * add event value field * turn on widget on Python site
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* package created * mvn WIP * normal wip, to be tested * update * docstring added, normal mostly done * add test file * Bernoulli WIP * bernoulli wip * bernoulli doc done * dense variational WIP * add kl infra * implement normal kl method * refactor kl * add not implemented handling, rename kl_storage * add abstract method and Categorical class * rewrite logit2prob prob2logit for multiclass support * normal broadcast_to implemented * categorical mostly done * update distributions/utils.py * add dot ahead of import * fix normal F * bernoulli, normal brief tests implemented * add hybridize tests * transformation infras done * affine transformation, implemented tested * add tests cases * add sum_right_most * fix get F bug * compose transform implemented, tested * fix * add event_dim * fetch mvn from upstremm * clean code, implement normal cdf and tests * constraint in bernoulli done * fix constraint * finish half normal * add cached_property * add test on cached_property * add more features to distribution and constratins * change constraint * fix bernoulli * add independent * add independent tests * update naming of cached_property * revert * add constraints * add Cat * add Stack for imperative mode * add Stack for imperative mode * add bernoulli entropy * categorical WIP * categorical sampling implemented * finish categorical log_prob, sampling * enumerate_support finished * polish StochasticBlock, add test * add test for stochastic sequential * clean loss list in __call__ * fix affine, implement sigmoid, softmax * add gumbel, relaxed bernoulli * relaxed one-hot sampling implemented * gamma done * gamma, dirichlet implemented * beta done * gumbel softmax log-likelihood implemented * refactor tests, implement exponential, fix compose transform * weibull implemented, transformed distribution cdf icdf added * pareto implemented * uniform wip * uniform done * rewrite lgamma, implement chi2 * fix chi2 scale * F distributiion done * t implemented * fix tiny problem * cauchy done * add half cauchy * multinomial done, tests to be added * add multinomial test * MVN done, tests todo * mvn polished * fix a few precison issues * add erf, erfinv unified api and learnable transform * fix mvn attribute check * MVN done * poisson done * hack poisson for size support * geometric finished * negative binomial done * binomial done * implement some kl * add more kl * refactor kl test * add more kl * binomial kl todo * change constraint logical op implement * implement gamma entropy * finish beta dirchlet entropy * finishi all entropy * kl finished * add constraint test * domain map done * remove bayesian dense * fix tiny problems * add kl uniform normal * add kl tests * acquire patch from upstream * add some doc * finish doc * refactor kl test(WIP) * add more kl, fix float32 underflow issue * make sampling more stable * handle inconsistent mode * replace boolean idx with np.where * fix file name * add more doc * add constraint check * add half_normal/cauchy pdf cdf support check * fix import problem * change nosetest to pytest * remove buggy lines * change alias register path * attempt to fix ci * fix lint, change a few tests * fix lint * modify hybrid sequential * fix lint * change import order * add test gluon probability v2 * fix hybridize flag * change implementation of stochastic block * fix lint * fix comments * fix block * modify domain map * add raises for improper add_loss * add raises for improper add_loss * add extra cases * change collectLoss decorator to mandatory * skip stochastic block tests * remove test cases * put gpu tests back * add test_gluon_stochastic_block back * remove export test * put a test back * tiny refactor * add memory leak flag * small changes Co-authored-by: Zheng <[email protected]>
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