From 4394ca9e82b467a0876cd286748fcf1d306c1ac6 Mon Sep 17 00:00:00 2001 From: Karol Blaszczak Date: Mon, 26 Aug 2024 09:59:25 +0200 Subject: [PATCH 1/5] Docs merging conformance articles 24.3 (#26222) --- .../compatibility-and-support.rst | 17 +- .../supported-devices.rst | 37 +- ...upported-operations-framework-frontend.rst | 1107 - ...supported-operations-inference-devices.rst | 180 - .../supported-operations.rst | 444 + .../[legacy]-model-optimizer-faq.rst | 2 +- .../[legacy]-convert-onnx.rst | 2 +- .../[legacy]-convert-paddle.rst | 2 +- .../[legacy]-convert-tensorflow-lite.rst | 4 +- .../[legacy]-convert-tensorflow.rst | 2 +- .../documentation/openvino-extensibility.rst | 2 +- .../model-preparation/convert-model-onnx.rst | 9 +- .../convert-model-paddle.rst | 9 +- .../convert-model-tensorflow-lite.rst | 4 +- .../convert-model-tensorflow.rst | 18 +- .../opset_report_omz_dynamic.html | 160 + .../opset_report_omz_static.html | 4815 +++++ .../template/chosen.jquery.min.js | 0 .../conformance_reports/template/filters.js | 0 .../template/highlight_tables_template.html | 0 .../template/report_template.html | 0 .../conformance_reports/template/style.css | 0 .../conformance_files/paddlepaddle_ops.csv | 106 + .../_static/conformance_files/pytorch_ops.csv | 408 + .../conformance_files/tensorflow_ops.csv | 1400 ++ .../opset_report_omz_dynamic.html | 14351 ------------- .../opset_report_omz_static.html | 16624 ---------------- 27 files changed, 7384 insertions(+), 32319 deletions(-) delete mode 100644 docs/articles_en/about-openvino/compatibility-and-support/supported-operations-framework-frontend.rst delete mode 100644 docs/articles_en/about-openvino/compatibility-and-support/supported-operations-inference-devices.rst create mode 100644 docs/articles_en/about-openvino/compatibility-and-support/supported-operations.rst create mode 100644 docs/sphinx_setup/_static/conformance_files/conformance_reports/opset_report_omz_dynamic.html create mode 100644 docs/sphinx_setup/_static/conformance_files/conformance_reports/opset_report_omz_static.html rename docs/sphinx_setup/_static/{download => conformance_files}/conformance_reports/template/chosen.jquery.min.js (100%) rename docs/sphinx_setup/_static/{download => conformance_files}/conformance_reports/template/filters.js (100%) rename docs/sphinx_setup/_static/{download => conformance_files}/conformance_reports/template/highlight_tables_template.html (100%) rename docs/sphinx_setup/_static/{download => conformance_files}/conformance_reports/template/report_template.html (100%) rename docs/sphinx_setup/_static/{download => conformance_files}/conformance_reports/template/style.css (100%) create mode 100644 docs/sphinx_setup/_static/conformance_files/paddlepaddle_ops.csv create mode 100644 docs/sphinx_setup/_static/conformance_files/pytorch_ops.csv create mode 100644 docs/sphinx_setup/_static/conformance_files/tensorflow_ops.csv delete mode 100644 docs/sphinx_setup/_static/download/conformance_reports/opset_report_omz_dynamic.html delete mode 100644 docs/sphinx_setup/_static/download/conformance_reports/opset_report_omz_static.html diff --git a/docs/articles_en/about-openvino/compatibility-and-support.rst b/docs/articles_en/about-openvino/compatibility-and-support.rst index f9ea2b2b34ba90..f46a180b23ef07 100644 --- a/docs/articles_en/about-openvino/compatibility-and-support.rst +++ b/docs/articles_en/about-openvino/compatibility-and-support.rst @@ -7,18 +7,17 @@ Compatibility and Support :hidden: compatibility-and-support/supported-devices + compatibility-and-support/supported-operations compatibility-and-support/supported-models - compatibility-and-support/supported-operations-inference-devices - compatibility-and-support/supported-operations-framework-frontend -:doc:`Supported Devices ` - compatibility information for supported hardware accelerators. - -:doc:`Supported Models ` - a list of selected models confirmed to work with given hardware. - -:doc:`Supported Operations ` - a listing of framework layers supported by OpenVINO. - -:doc:`Supported Operations ` - a listing of layers supported by OpenVINO inference devices. +| :doc:`Supported Devices `: +| compatibility information for supported hardware accelerators. +| :doc:`Supported Operations `: +| a listing of operations supported by OpenVINO, based on device and frontend conformance. +| :doc:`AI Models verified for OpenVINO™ `: +| a list of selected models confirmed to work with Intel® Core Ultra™ Processors with the + OpenVINO™ toolkit. 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 index 890d48bcf75502..b9f15bbe12cccc 100644 --- a/docs/articles_en/about-openvino/compatibility-and-support/supported-devices.rst +++ b/docs/articles_en/about-openvino/compatibility-and-support/supported-devices.rst @@ -1,12 +1,12 @@ -Supported Inference Devices -============================ +Supported Devices +=============================================================================================== .. 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 +The OpenVINO™ runtime enables you to use the following devices to run your deep learning models: :doc:`CPU <../../openvino-workflow/running-inference/inference-devices-and-modes/cpu-device>`, :doc:`GPU <../../openvino-workflow/running-inference/inference-devices-and-modes/gpu-device>`, @@ -18,16 +18,20 @@ deep learning models: Beside running inference with a specific device, OpenVINO offers the option of running automated inference with the following inference modes: -* :doc:`Automatic Device Selection <../../openvino-workflow/running-inference/inference-devices-and-modes/auto-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 <../../openvino-workflow/running-inference/inference-devices-and-modes/hetero-execution>` - enables splitting inference among several devices - automatically, for example, if one device doesn't support certain operations. -* :doc:`(LEGACY) Multi-device Inference <./../../documentation/legacy-features/multi-device>` - executes inference on multiple devices. - Currently, this mode is considered a legacy solution. Using Automatic Device Selection is advised. -* :doc:`Automatic Batching <../../openvino-workflow/running-inference/inference-devices-and-modes/automatic-batching>` - automatically groups inference requests to improve - device utilization. +| :doc:`Automatic Device Selection <../../openvino-workflow/running-inference/inference-devices-and-modes/auto-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 <../../openvino-workflow/running-inference/inference-devices-and-modes/hetero-execution>`: +| enables splitting inference among several devices automatically, for example, if one device + doesn't support certain operations. +| :doc:`Automatic Batching <../../openvino-workflow/running-inference/inference-devices-and-modes/automatic-batching>`: +| automatically groups inference requests to improve device utilization. + +| :doc:`(LEGACY) Multi-device Inference <./../../documentation/legacy-features/multi-device>`: +| executes inference on multiple devices. Currently, this mode is considered a legacy + solution. Using Automatic Device Selection instead is advised. Feature Support and API Coverage @@ -36,16 +40,17 @@ Feature Support and API Coverage ======================================================================================================================================== ======= ========== =========== Supported Feature CPU GPU NPU ======================================================================================================================================== ======= ========== =========== + :doc:`Automatic Device Selection <../../openvino-workflow/running-inference/inference-devices-and-modes/auto-device-selection>` Yes Yes Partial :doc:`Heterogeneous execution <../../openvino-workflow/running-inference/inference-devices-and-modes/hetero-execution>` Yes Yes No - :doc:`(LEGACY) Multi-device execution <./../../documentation/legacy-features/multi-device>` Yes Yes Partial :doc:`Automatic batching <../../openvino-workflow/running-inference/inference-devices-and-modes/automatic-batching>` No Yes No :doc:`Multi-stream execution <../../openvino-workflow/running-inference/optimize-inference/optimizing-throughput>` Yes Yes No - :doc:`Models caching <../../openvino-workflow/running-inference/optimize-inference/optimizing-latency/model-caching-overview>` Yes Partial Yes + :doc:`Model caching <../../openvino-workflow/running-inference/optimize-inference/optimizing-latency/model-caching-overview>` Yes Partial Yes :doc:`Dynamic shapes <../../openvino-workflow/running-inference/dynamic-shapes>` Yes Partial No :doc:`Import/Export <../../documentation/openvino-ecosystem>` Yes Yes Yes :doc:`Preprocessing acceleration <../../openvino-workflow/running-inference/optimize-inference/optimize-preprocessing>` Yes Yes No :doc:`Stateful models <../../openvino-workflow/running-inference/stateful-models>` Yes Yes Yes :doc:`Extensibility <../../documentation/openvino-extensibility>` Yes Yes No + :doc:`(LEGACY) Multi-device execution <./../../documentation/legacy-features/multi-device>` Yes Yes Partial ======================================================================================================================================== ======= ========== =========== @@ -80,10 +85,10 @@ topic (step 3 "Configure input and output"). .. note:: - With OpenVINO 2024.0 release, support for GNA has been discontinued. To keep using it + With the 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: + With the 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™ 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 7fb2774447537d..00000000000000 --- a/docs/articles_en/about-openvino/compatibility-and-support/supported-operations-framework-frontend.rst +++ /dev/null @@ -1,1107 +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::_pack_padded_sequence - aten::_pad_packed_sequence - aten::_set_item - aten::_shape_as_tensor - aten::_unique2 - aten::_upsample_bicubic2d_aa - aten::_upsample_bilinear2d_aa - aten::_weight_norm - aten::abs - 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::bucketize - aten::cat - aten::cdist - aten::ceil - aten::ceil_ - aten::celu - aten::celu_ - 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::dot - aten::dropout - aten::dropout_ - aten::einsum Supported in limited set of patterns - aten::elu - 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::expm1 - aten::expm1_ - 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::floor_divide_ - aten::floordiv - aten::fmod - aten::frobenius_norm - aten::full - aten::full_like - aten::gather - aten::gcd - aten::ge - aten::gelu - aten::glu - aten::grid_sampler - aten::group_norm - aten::gru - aten::gt - aten::hardsigmoid - 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_add - aten::index_add_ - aten::index_copy_ - aten::index_put_ - aten::index_select - aten::instance_norm - aten::Int - aten::IntImplicit - aten::inverse - 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_inv - 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_sigmoid - 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::mish - aten::mish_ - aten::mm - aten::movedim - aten::mul - aten::mul_ - aten::multinomial - aten::multiply - aten::multiply_ - aten::mv - 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::reciprocal_ - aten::reflection_pad2d Supported in limited set of patterns - aten::relu - aten::relu6 - 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::max Supported in limited set of patterns - prim::min Supported in limited set of patterns - 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 deleted file mode 100644 index 339ed4520a0f0c..00000000000000 --- a/docs/articles_en/about-openvino/compatibility-and-support/supported-operations-inference-devices.rst +++ /dev/null @@ -1,180 +0,0 @@ -.. {#openvino_resources_supported_operations} - -Supported Operations - by Inference Devices -=========================================== - - -This page presents operations supported by OpenVINO inference devices. The table presents general information, -for a more detailed and most recent listing of operations that are implemented and tested: - - -.. button-link:: ../../_static/download/conformance_reports/opset_report_omz_static.html - :color: primary - :outline: - - See the full conformance report table (static) - -.. button-link:: ../../_static/download/conformance_reports/opset_report_omz_dynamic.html - :color: primary - :outline: - - See the full conformance report table (dynamic) - - - -================================= =============== ============== ================== - Operations CPU (x86) GPU CPU (Arm®) -================================= =============== ============== ================== - Abs Supported** Supported Supported - Acos Supported** Supported Supported**** - Acosh Supported** Supported Supported**** - Activation-Clamp Supported*** Supported Supported - Activation-ELU Supported*** Supported Supported - Activation-Exp Supported*** Supported Supported - Activation-Leaky ReLU Supported*** Supported Not Supported - Activation-Not Supported*** Supported Not Supported - Activation-PReLU Supported*** Supported Supported - Activation-ReLU Supported*** Supported Supported - Activation-ReLU6 Supported*** Supported Not Supported - Activation-Sigmoid/Logistic Supported*** Supported Supported - Activation-TanH Supported*** Supported Supported - ArgMax Supported** Supported Not Supported - Asin Supported** Supported Supported**** - Asinh Supported** Supported Supported**** - Atan Supported** Supported Supported**** - Atanh Supported** Supported Supported**** - BatchNormalization Supported Supported Supported - BinaryConvolution Supported Supported Not Supported - Broadcast Supported** Supported Supported - Ceil Supported** Supported Supported - Concat Supported*** Supported Supported - Const Supported Supported Supported - Convolution-Dilated Supported Supported Supported - Convolution-Dilated 3D Supported Supported Not Supported - Convolution-Grouped Supported Supported Supported - Convolution-Grouped 3D Supported Supported Not Supported - Convolution-Ordinary Supported Supported Supported - Convolution-Ordinary 3D Supported Supported Not Supported - Cos Supported** Supported Supported**** - Cosh Supported** Supported Supported**** - Crop Supported Supported Not Supported - CTCGreedyDecoder Supported** Supported** Supported**** - Deconvolution Supported Supported Not Supported - Deconvolution 3D Supported Supported Not Supported - DeformableConvolution Supported Supported Not Supported - DepthToSpace Supported** Supported Supported* - DetectionOutput Supported** Supported Supported**** - Eltwise-And Supported*** Supported Supported - Eltwise-Add Supported*** Supported Supported - Eltwise-Div Supported*** Supported Supported - Eltwise-Equal Supported*** Supported Supported* - Eltwise-FloorMod Supported*** Supported Supported**** - Eltwise-Greater Supported*** Supported Supported - Eltwise-GreaterEqual Supported*** Supported Supported - Eltwise-Less Supported*** Supported Supported* - Eltwise-LessEqual Supported*** Supported Supported* - Eltwise-LogicalAnd Supported*** Supported Supported - Eltwise-LogicalOr Supported*** Supported Supported - Eltwise-LogicalXor Supported*** Supported Supported - Eltwise-Max Supported*** Supported Supported - Eltwise-Min Supported*** Supported Supported - Eltwise-Mul Supported*** Supported Supported - Eltwise-NotEqual Supported*** Supported Supported* - Eltwise-Pow Supported*** Supported Supported - Eltwise-Prod Supported*** Supported Not Supported - Eltwise-SquaredDiff Supported*** Supported Supported - Eltwise-Sub Supported*** Supported Supported - Eltwise-Sum Supported*** Supported Supported**** - Erf Supported** Supported Supported**** - Exp Supported Supported Supported - FakeQuantize Supported Not Supported Supported* - Fill Supported** Not Supported Not Supported - Flatten Supported Supported Not Supported - Floor Supported** Supported Supported - FullyConnected (Inner Product) Supported*** Supported Supported - Gather Supported** Supported Supported* - GatherTree Supported** Not Supported Supported**** - Gemm Supported Supported Not Supported - GRN Supported** Supported** Supported - HardSigmoid Supported** Supported Supported**** - Interp Supported** Supported** Supported* - Log Supported** Supported Supported - LRN (Norm) Supported Supported Supported* - LSTMCell Supported Supported Supported - GRUCell Supported Supported Supported - RNNCell Supported Supported Supported - LSTMSequence Supported Supported Supported**** - GRUSequence Supported Supported Supported**** - RNNSequence Supported Supported Supported**** - LogSoftmax Supported** Supported Supported - Memory Supported Not Supported Not Supported - MVN Supported** Supported Supported* - Neg Supported** Supported Supported - NonMaxSuppression Supported** Not Supported Supported**** - Normalize Supported** Supported Supported* - OneHot Supported** Supported Supported**** - Pad Supported** Supported Supported* - Permute Supported Supported Not Supported - Pooling(AVG,MAX) Supported Supported Supported - Pooling(AVG,MAX) 3D Supported Supported Supported* - Power Supported** Supported Supported - PowerFile Supported** Not Supported Not Supported - PriorBox Supported** Supported Supported - PriorBoxClustered Supported** Supported** Supported - Proposal Supported** Supported Supported**** - PSROIPooling Supported** Supported Supported**** - Range Supported** Not Supported Not Supported - Reciprocal Supported** Supported Not Supported - ReduceAnd Supported** Supported Supported**** - ReduceL1 Supported** Supported Supported - ReduceL2 Supported** Supported Supported - ReduceLogSum Supported** Supported Supported - ReduceLogSumExp Supported** Supported Not Supported - ReduceMax Supported** Supported Supported - ReduceMean Supported** Supported Supported - ReduceMin Supported** Supported Supported - ReduceOr Supported** Supported Supported**** - ReduceProd Supported** Supported Supported - ReduceSum Supported** Supported Supported - ReduceSumSquare Supported** Supported Not Supported - RegionYolo Supported** Supported Supported**** - ReorgYolo Supported** Supported Supported - Resample Supported** Supported Not Supported - Reshape Supported*** Supported Supported - ReverseSequence Supported** Supported Supported**** - RNN Supported Not Supported Supported - ROIPooling Supported Supported* Supported**** - ScaleShift Supported*** Supported Not Supported - ScatterUpdate Supported** Not Supported Not Supported - Select Supported Supported Supported - Selu Supported** Supported Supported**** - ShuffleChannels Supported** Supported Supported - Sign Supported** Supported Supported - Sin Supported** Supported Supported - Sinh Supported** Supported Supported**** - SimplerNMS Supported** Supported Not Supported - Slice Supported*** Supported Not Supported - SoftMax Supported*** Supported Supported - Softplus Supported** Supported Supported - Softsign Supported** Supported Not Supported - SpaceToDepth Supported** Not Supported Supported* - SpatialTransformer Supported** Not Supported Not Supported - Split Supported*** Supported Supported - Squeeze Supported** Supported Supported - StridedSlice Supported** Supported Supported* - Tan Supported** Supported Supported**** - TensorIterator Supported Not Supported Supported - Tile Supported*** Supported** Supported - TopK Supported** Supported Supported**** - Unpooling Not Supported Supported Not Supported - Unsqueeze Supported** Supported Supported - Upsampling Not Supported Supported Not Supported -================================= =============== ============== ================== - -| `*` - support is limited to the specific parameters. -| `**` - support is implemented via :doc:`Extensibility mechanism <../../documentation/openvino-extensibility>`. -| `***` - supports NCDHW layout. -| `****` - support is implemented via runtime reference. - - - diff --git a/docs/articles_en/about-openvino/compatibility-and-support/supported-operations.rst b/docs/articles_en/about-openvino/compatibility-and-support/supported-operations.rst new file mode 100644 index 00000000000000..5bd414776784ce --- /dev/null +++ b/docs/articles_en/about-openvino/compatibility-and-support/supported-operations.rst @@ -0,0 +1,444 @@ +Supported Operations +=============================================================================================== + +.. meta:: + :description: Check the operations supported by OpenVINO. + + +Here, you will find comprehensive information on operations supported by OpenVINO. The +conformance reports provide operation coverage for inference devices, while the tables list +operations available for all OpenVINO framework frontends. + +**Device-operation conformance reports:** + +.. grid:: 1 1 2 2 + :gutter: 4 + + .. grid-item:: + + .. button-link:: ../../_static/conformance_files/conformance_reports/opset_report_omz_static.html + :color: primary + :outline: + :expand: + + ops with static shapes only + + .. grid-item:: + + .. button-link:: ../../_static/conformance_files/conformance_reports/opset_report_omz_dynamic.html + :color: primary + :outline: + :expand: + + ops including dynamic inputs + +**Operations supported by OpenVINO frontend Frameworks:** + +.. tab-set:: + + .. tab-item:: PyTorch + + .. csv-table:: + :class: modeldata stripe + :name: TensorFlow ops + :header-rows: 1 + :file: ../../_static/conformance_files/pytorch_ops.csv + + .. tab-item:: TensorFlow + + .. csv-table:: + :class: modeldata stripe + :name: TensorFlow ops + :header-rows: 1 + :file: ../../_static/conformance_files/tensorflow_ops.csv + + .. tab-item:: PaddlePaddle + + .. csv-table:: + :class: modeldata stripe + :name: Paddle ops + :header-rows: 1 + :file: ../../_static/conformance_files/paddlepaddle_ops.csv + + .. 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:: 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/legacy-features/transition-legacy-conversion-api/legacy-conversion-api/[legacy]-model-optimizer-faq.rst b/docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api/[legacy]-model-optimizer-faq.rst index fb7e3004258253..ae64f8fdbd40fb 100644 --- a/docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api/[legacy]-model-optimizer-faq.rst +++ b/docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api/[legacy]-model-optimizer-faq.rst @@ -81,7 +81,7 @@ Q3. What does the message "[ ERROR ]: Unable to create ports for node with id" m **A:** Most likely, Model Optimizer does not know how to infer output shapes of some layers in the given topology. To lessen the scope, compile the list of layers that are custom for Model Optimizer: present in the topology, -absent in the :doc:`list of supported operations <../../../../about-openvino/compatibility-and-support/supported-operations-framework-frontend>` for the target framework. +absent in the :doc:`list of supported operations <../../../../about-openvino/compatibility-and-support/supported-operations>` for the target framework. Then, refer to available options in the corresponding section in the :doc:`[Legacy] Custom Layers in Model Optimizer <../legacy-model-optimizer-extensibility>` page. .. _question-7: diff --git a/docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api/[legacy]-supported-model-formats/[legacy]-convert-onnx.rst b/docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api/[legacy]-supported-model-formats/[legacy]-convert-onnx.rst index 9e7ab98cf1f2f9..9c7ee67c58d553 100644 --- a/docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api/[legacy]-supported-model-formats/[legacy]-convert-onnx.rst +++ b/docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api/[legacy]-supported-model-formats/[legacy]-convert-onnx.rst @@ -58,7 +58,7 @@ There are no ONNX-specific parameters, so only framework-agnostic parameters are Supported ONNX Layers ##################### -For the list of supported standard layers, refer to the :doc:`Supported Operations <../../../../../about-openvino/compatibility-and-support/supported-operations-framework-frontend>` page. +For the list of supported standard layers, refer to the :doc:`Supported Operations <../../../../../about-openvino/compatibility-and-support/supported-operations>` page. Additional Resources #################### diff --git a/docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api/[legacy]-supported-model-formats/[legacy]-convert-paddle.rst b/docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api/[legacy]-supported-model-formats/[legacy]-convert-paddle.rst index 9b58030bb2d8cc..47598ecaeadca5 100644 --- a/docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api/[legacy]-supported-model-formats/[legacy]-convert-paddle.rst +++ b/docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api/[legacy]-supported-model-formats/[legacy]-convert-paddle.rst @@ -126,7 +126,7 @@ When you convert certain PaddlePaddle models, you may need to set the ``example_ Supported PaddlePaddle Layers ############################# -For the list of supported standard layers, refer to the :doc:`Supported Operations <../../../../../about-openvino/compatibility-and-support/supported-operations-framework-frontend>` page. +For the list of supported standard layers, refer to the :doc:`Supported Operations <../../../../../about-openvino/compatibility-and-support/supported-operations>` page. Frequently Asked Questions (FAQ) ################################ diff --git a/docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api/[legacy]-supported-model-formats/[legacy]-convert-tensorflow-lite.rst b/docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api/[legacy]-supported-model-formats/[legacy]-convert-tensorflow-lite.rst index 738893ddd7454b..a0d6d1cd866eba 100644 --- a/docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api/[legacy]-supported-model-formats/[legacy]-convert-tensorflow-lite.rst +++ b/docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api/[legacy]-supported-model-formats/[legacy]-convert-tensorflow-lite.rst @@ -5,7 +5,7 @@ .. meta:: - :description: Learn how to convert a model from a + :description: Learn how to convert a model from a TensorFlow Lite format to the OpenVINO Intermediate Representation. .. danger:: @@ -29,7 +29,7 @@ TensorFlow Lite models are supported via FrontEnd API. You may skip conversion t Supported TensorFlow Lite Layers ################################### -For the list of supported standard layers, refer to the :doc:`Supported Operations <../../../../../about-openvino/compatibility-and-support/supported-operations-framework-frontend>` page. +For the list of supported standard layers, refer to the :doc:`Supported Operations <../../../../../about-openvino/compatibility-and-support/supported-operations>` page. Supported TensorFlow Lite Models ################################### diff --git a/docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api/[legacy]-supported-model-formats/[legacy]-convert-tensorflow.rst b/docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api/[legacy]-supported-model-formats/[legacy]-convert-tensorflow.rst index 8dd124fbc3726f..b1a7a997a6b785 100644 --- a/docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api/[legacy]-supported-model-formats/[legacy]-convert-tensorflow.rst +++ b/docs/articles_en/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api/[legacy]-supported-model-formats/[legacy]-convert-tensorflow.rst @@ -333,7 +333,7 @@ Model conversion API supports passing TensorFlow/TensorFlow2 models directly fro Supported TensorFlow and TensorFlow 2 Keras Layers ################################################## -For the list of supported standard layers, refer to the :doc:`Supported Operations <../../../../../about-openvino/compatibility-and-support/supported-operations-framework-frontend>` page. +For the list of supported standard layers, refer to the :doc:`Supported Operations <../../../../../about-openvino/compatibility-and-support/supported-operations>` page. Frequently Asked Questions (FAQ) ################################ diff --git a/docs/articles_en/documentation/openvino-extensibility.rst b/docs/articles_en/documentation/openvino-extensibility.rst index b276a713f6f6de..4beb8c54f7cd2c 100644 --- a/docs/articles_en/documentation/openvino-extensibility.rst +++ b/docs/articles_en/documentation/openvino-extensibility.rst @@ -27,7 +27,7 @@ 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. 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 <../about-openvino/compatibility-and-support/supported-operations-framework-frontend>`. +To see the operations supported by your framework, refer to :doc:`Supported Framework Operations <../about-openvino/compatibility-and-support/supported-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: diff --git a/docs/articles_en/openvino-workflow/model-preparation/convert-model-onnx.rst b/docs/articles_en/openvino-workflow/model-preparation/convert-model-onnx.rst index 9c903388a5c3bd..9d1f0a3e0d754a 100644 --- a/docs/articles_en/openvino-workflow/model-preparation/convert-model-onnx.rst +++ b/docs/articles_en/openvino-workflow/model-preparation/convert-model-onnx.rst @@ -1,5 +1,3 @@ -.. {#openvino_docs_OV_Converter_UG_prepare_model_convert_model_Convert_Model_From_ONNX} - Converting an ONNX Model ======================== @@ -63,10 +61,13 @@ OpenVINO model conversion API supports ONNX models with external data representa Supported ONNX Layers ##################### -For the list of supported standard layers, refer to the :doc:`Supported Operations <../../about-openvino/compatibility-and-support/supported-operations-framework-frontend>` page. +For the list of supported standard layers, refer to the +:doc:`Supported Operations <../../about-openvino/compatibility-and-support/supported-operations>` +page. Additional Resources #################### -Check out more examples of model conversion in :doc:`interactive Python tutorials <../../learn-openvino/interactive-tutorials-python>`. +Check out more examples of model conversion in +:doc:`interactive Python tutorials <../../learn-openvino/interactive-tutorials-python>`. diff --git a/docs/articles_en/openvino-workflow/model-preparation/convert-model-paddle.rst b/docs/articles_en/openvino-workflow/model-preparation/convert-model-paddle.rst index 97c968bc4a7692..b91af11c012566 100644 --- a/docs/articles_en/openvino-workflow/model-preparation/convert-model-paddle.rst +++ b/docs/articles_en/openvino-workflow/model-preparation/convert-model-paddle.rst @@ -1,5 +1,3 @@ -.. {#openvino_docs_OV_Converter_UG_prepare_model_convert_model_Convert_Model_From_Paddle} - Converting a PaddlePaddle Model =============================== @@ -153,11 +151,14 @@ Some PaddlePaddle models may require setting ``example_input`` or ``output`` for Supported PaddlePaddle Layers ############################# -For the list of supported standard layers, refer to the :doc:`Supported Operations <../../about-openvino/compatibility-and-support/supported-operations-framework-frontend>` page. +For the list of supported standard layers, refer to the +:doc:`Supported Operations <../../about-openvino/compatibility-and-support/supported-operations>` +page. Additional Resources #################### -Check out more examples of model conversion in :doc:`interactive Python tutorials <../../learn-openvino/interactive-tutorials-python>`. +Check out more examples of model conversion in +:doc:`interactive Python tutorials <../../learn-openvino/interactive-tutorials-python>`. diff --git a/docs/articles_en/openvino-workflow/model-preparation/convert-model-tensorflow-lite.rst b/docs/articles_en/openvino-workflow/model-preparation/convert-model-tensorflow-lite.rst index 93738f48f1d39f..28792770f58f41 100644 --- a/docs/articles_en/openvino-workflow/model-preparation/convert-model-tensorflow-lite.rst +++ b/docs/articles_en/openvino-workflow/model-preparation/convert-model-tensorflow-lite.rst @@ -1,5 +1,3 @@ -.. {#convert-model-tensorflow_Lite} - Converting a TensorFlow Lite Model ================================== @@ -44,7 +42,7 @@ Supported TensorFlow Lite Layers ################################### For the list of supported standard layers, refer to the -:doc:`Supported Operations <../../about-openvino/compatibility-and-support/supported-operations-framework-frontend>` +:doc:`Supported Operations <../../about-openvino/compatibility-and-support/supported-operations>` page. Supported TensorFlow Lite Models diff --git a/docs/articles_en/openvino-workflow/model-preparation/convert-model-tensorflow.rst b/docs/articles_en/openvino-workflow/model-preparation/convert-model-tensorflow.rst index e66a5a87c48cd3..5012a8c9f70736 100644 --- a/docs/articles_en/openvino-workflow/model-preparation/convert-model-tensorflow.rst +++ b/docs/articles_en/openvino-workflow/model-preparation/convert-model-tensorflow.rst @@ -1,5 +1,3 @@ -.. {#openvino_docs_OV_Converter_UG_prepare_model_convert_model_Convert_Model_From_TensorFlow} - Converting a TensorFlow Model ============================= @@ -38,9 +36,9 @@ or `Hugging Face `__. .. note:: - Examples below that convert TensorFlow models from a file, do not require any version - of TensorFlow to be installed on the system, except in cases when the ``tensorflow`` - module is imported explicitly. + The examples converting TensorFlow models from a file do not require any version + of TensorFlow installed on the system, unless the ``tensorflow`` module is imported + explicitly. Converting TensorFlow 2 Models ############################## @@ -385,15 +383,7 @@ Supported TensorFlow and TensorFlow 2 Keras Layers ################################################## For the list of supported standard layers, refer to the -:doc:`Supported Operations <../../about-openvino/compatibility-and-support/supported-operations-framework-frontend>` +:doc:`Supported Operations <../../about-openvino/compatibility-and-support/supported-operations>` page. -Summary -####### - -In this document, you learned: - -* Basic information about how the model conversion API works with TensorFlow models. -* Which TensorFlow models are supported. -* How to freeze a TensorFlow model. diff --git a/docs/sphinx_setup/_static/conformance_files/conformance_reports/opset_report_omz_dynamic.html b/docs/sphinx_setup/_static/conformance_files/conformance_reports/opset_report_omz_dynamic.html new file mode 100644 index 00000000000000..a3a0a3e4ebfeed --- /dev/null +++ b/docs/sphinx_setup/_static/conformance_files/conformance_reports/opset_report_omz_dynamic.html @@ -0,0 +1,160 @@ + + + + + + + + + + + + + + + Report + + + +
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Operations coverage summary: Tag: Conformance_report__omz_dynamic_opset | Version: master_2024.4.0-16305-eb736518857-refs/pull/3613/head | Time: None

+
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+ Passrates are based on relative weights each subgraphs! You can check absolute value in `General passrate` row! +
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+ + + + \ No newline at end of file diff --git a/docs/sphinx_setup/_static/conformance_files/conformance_reports/opset_report_omz_static.html b/docs/sphinx_setup/_static/conformance_files/conformance_reports/opset_report_omz_static.html new file mode 100644 index 00000000000000..22427c316e99aa --- /dev/null +++ b/docs/sphinx_setup/_static/conformance_files/conformance_reports/opset_report_omz_static.html @@ -0,0 +1,4815 @@ + + + + + + + + + + + + + + + Report + + + +
+

Operations coverage summary: Tag: Conformance_report__omz_static_opset | Version: master_2024.4.0-16305-eb736518857-refs/pull/3613/head | Time: 08-08-2024 14:33:45

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+ Collected statistic info +
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+
+ P:1815 + F:1248 + S:0 + C:8 + H:0 +
+
+ + 		NOT RUN
ConvolutionBackpropData-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 54.84 %
+
+
+ P:15 + F:13 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
Cos-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 100.0 %
+
+
+ P:9 + F:0 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
Cosh-1 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
CumSum-3 NOT RUN NOT RUN NOT RUN NOT RUN + + 75.4 %
+
+
+ P:8 + F:1 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
DFT-7 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
DeformableConvolution-1 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
DeformableConvolution-8 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
DeformablePSROIPooling-1 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
DepthToSpace-1 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
DetectionOutput-1 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
DetectionOutput-8 NOT RUN NOT RUN NOT RUN NOT RUN + + 64.72 %
+
+
+ P:12 + F:11 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
Divide-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 85.43 %
+
+
+ P:123 + F:48 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
Einsum-7 NOT RUN NOT RUN NOT RUN NOT RUN + + 91.93 %
+
+
+ P:20 + F:1 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
Elu-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 99.97 %
+
+
+ P:19 + F:2 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
EmbeddingBagOffsets-15 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
EmbeddingBagOffsetsSum-3 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
EmbeddingBagPacked-15 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
EmbeddingBagPackedSum-3 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
EmbeddingSegmentsSum-3 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
Equal-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 50.0 %
+
+
+ P:6 + F:6 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
Erf-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 70.67 %
+
+
+ P:15 + F:4 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
Exp-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 66.66 %
+
+
+ P:4 + F:2 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
ExperimentalDetectronDetectionOutput-6 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
ExperimentalDetectronGenerateProposalsSingleImage-6 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
ExperimentalDetectronPriorGridGenerator-6 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
ExperimentalDetectronROIFeatureExtractor-6 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
ExperimentalDetectronTopKROIs-6 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
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Eye-9 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
FakeConvert-13 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
FakeQuantize-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 34.52 %
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+
+ + 		NOT RUN
Floor-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 56.18 %
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+
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+ P:11 + F:4 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
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GRUCell-3 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
GRUSequence-5 NOT RUN NOT RUN NOT RUN NOT RUN + + 63.41 %
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+
+ P:9 + F:7 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
Gather-1 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
Gather-7 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
Gather-8 NOT RUN NOT RUN NOT RUN NOT RUN + + 67.32 %
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+
+ + 		NOT RUN
GatherElements-6 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
GatherND-5 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
GatherND-8 NOT RUN NOT RUN NOT RUN NOT RUN + + 100.0 %
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+ P:3 + F:0 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
GatherTree-1 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
Gelu-2 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
Gelu-7 NOT RUN NOT RUN NOT RUN NOT RUN + + 67.89 %
+
+
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+
+ + 		NOT RUN
GenerateProposals-9 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
Greater-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 24.99 %
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+ P:2 + F:6 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
GreaterEqual-1 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
GridSample-9 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
GroupConvolution-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 42.81 %
+
+
+ P:528 + F:255 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
GroupConvolutionBackpropData-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 82.21 %
+
+
+ P:7 + F:7 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
GroupNormalization-12 NOT RUN NOT RUN NOT RUN NOT RUN + + 0.0 %
+
+
+ P:0 + F:55 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
HSigmoid-5 NOT RUN NOT RUN NOT RUN NOT RUN + + 96.75 %
+
+
+ P:30 + F:9 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
HSwish-4 NOT RUN NOT RUN NOT RUN NOT RUN + + 96.27 %
+
+
+ P:94 + F:41 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
HardSigmoid-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 98.52 %
+
+
+ P:59 + F:10 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
I420toBGR-8 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
I420toRGB-8 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
IDFT-7 NOT RUN NOT RUN NOT RUN NOT RUN + + 100.0 %
+
+
+ P:3 + F:0 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
IRDFT-9 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
If-8 NOT RUN NOT RUN NOT RUN NOT RUN + + 100.0 %
+
+
+ P:6 + F:0 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
Interpolate-1 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
Interpolate-11 NOT RUN NOT RUN NOT RUN NOT RUN + + 84.08 %
+
+
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+
+ + 		NOT RUN
Interpolate-4 NOT RUN NOT RUN NOT RUN NOT RUN + + 35.1 %
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+
+ P:20 + F:29 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
Inverse-14 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
IsFinite-10 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
IsInf-10 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
IsNaN-10 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
LRN-1 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
LSTMCell-1 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
LSTMCell-4 NOT RUN NOT RUN NOT RUN NOT RUN + + 100.0 %
+
+
+ P:6 + F:0 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
LSTMSequence-1 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
LSTMSequence-5 NOT RUN NOT RUN NOT RUN NOT RUN + + 71.74 %
+
+
+ P:12 + F:5 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
Less-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 50.0 %
+
+
+ P:4 + F:4 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
LessEqual-1 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
Log-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 100.0 %
+
+
+ P:3 + F:0 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
LogSoftmax-5 NOT RUN NOT RUN NOT RUN NOT RUN + + 66.66 %
+
+
+ P:2 + F:1 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
LogicalAnd-1 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
LogicalNot-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 57.54 %
+
+
+ P:5 + F:2 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
LogicalOr-1 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
LogicalXor-2 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
Loop-5 NOT RUN NOT RUN NOT RUN NOT RUN + + 25.0 %
+
+
+ P:2 + F:6 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
MVN-2 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
MVN-6 NOT RUN NOT RUN NOT RUN NOT RUN + + 83.8 %
+
+
+ P:64 + F:48 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
MatMul-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 89.49 %
+
+
+ P:420 + F:124 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
MatrixNms-8 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
MaxPool-1 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
MaxPool-14 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
MaxPool-8 NOT RUN NOT RUN NOT RUN NOT RUN + + 0.0 %
+
+
+ P:0 + F:250 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
Maximum-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 68.05 %
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+
+ P:21 + F:7 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
Minimum-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 66.15 %
+
+
+ P:13 + F:10 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
Mish-4 NOT RUN NOT RUN NOT RUN NOT RUN + + 68.43 %
+
+
+ P:122 + F:28 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
Mod-1 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
MulticlassNms-8 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
MulticlassNms-9 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
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Multiply-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 72.29 %
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+
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+
+ + 		NOT RUN
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NV12toBGR-8 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
NV12toRGB-8 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
Negative-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 100.0 %
+
+
+ P:3 + F:0 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
NonMaxSuppression-1 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
NonMaxSuppression-3 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
NonMaxSuppression-4 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
NonMaxSuppression-5 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
NonMaxSuppression-9 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
NonZero-3 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
NormalizeL2-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 100.0 %
+
+
+ P:6 + F:0 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
NotEqual-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 50.0 %
+
+
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+
+ + 		NOT RUN
OneHot-1 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
PRelu-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 75.7 %
+
+
+ P:130 + F:179 + S:0 + C:1 + H:0 +
+
+ + 		NOT RUN
PSROIPooling-1 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
Pad-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 68.44 %
+
+
+ P:30 + F:17 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
Pad-12 NOT RUN NOT RUN NOT RUN NOT RUN + + 26.22 %
+
+
+ P:18 + F:22 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
Parameter-1 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
Power-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 78.77 %
+
+
+ P:60 + F:16 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
PriorBox-1 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
PriorBox-8 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
PriorBoxClustered-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 99.99 %
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+
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+
+ + 		NOT RUN
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Proposal-4 NOT RUN NOT RUN NOT RUN NOT RUN + + 66.66 %
+
+
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+
+ + 		NOT RUN
RDFT-9 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
RNNCell-1 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
RNNSequence-5 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
ROIAlign-3 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
ROIAlign-9 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
ROIAlignRotated-15 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
ROIPooling-2 NOT RUN NOT RUN NOT RUN NOT RUN + + 66.66 %
+
+
+ P:30 + F:15 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
RandomUniform-8 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
Range-1 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
Range-4 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
ReadValue-3 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
ReadValue-6 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
ReduceL1-4 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
ReduceL2-4 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
ReduceLogicalAnd-1 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
ReduceLogicalOr-1 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
ReduceMax-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 100.0 %
+
+
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+
+ + 		NOT RUN
ReduceMean-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 84.11 %
+
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+
+ + 		NOT RUN
ReduceMin-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 100.0 %
+
+
+ P:6 + F:0 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
ReduceProd-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 100.0 %
+
+
+ P:114 + F:0 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
ReduceSum-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 99.9 %
+
+
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+
+ + 		NOT RUN
RegionYolo-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 100.0 %
+
+
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+
+ + 		NOT RUN
Relu-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 47.94 %
+
+
+ P:611 + F:763 + S:0 + C:2 + H:0 +
+
+ + 		NOT RUN
ReorgYolo-2 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
Reshape-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 89.32 %
+
+
+ P:963 + F:246 + S:0 + C:1 + H:0 +
+
+ + 		NOT RUN
Result-1 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
Reverse-1 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
ReverseSequence-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 100.0 %
+
+
+ P:6 + F:0 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
Roll-7 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
Round-5 NOT RUN NOT RUN NOT RUN NOT RUN + + 100.0 %
+
+
+ P:3 + F:0 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
ScaledDotProductAttention-13 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
ScatterElementsUpdate-12 NOT RUN NOT RUN NOT RUN NOT RUN + + 100.0 %
+
+
+ P:6 + F:0 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
ScatterElementsUpdate-3 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
ScatterNDUpdate-15 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
ScatterNDUpdate-4 NOT RUN NOT RUN NOT RUN NOT RUN + + 72.84 %
+
+
+ P:16 + F:1 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
ScatterUpdate-3 NOT RUN NOT RUN NOT RUN NOT RUN + + 100.0 %
+
+
+ P:9 + F:0 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
Select-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 25.63 %
+
+
+ P:5 + F:10 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
Selu-1 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
ShapeOf-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 100.0 %
+
+
+ P:60 + F:0 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
ShapeOf-3 NOT RUN NOT RUN NOT RUN NOT RUN + + 74.69 %
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+
+ P:378 + F:57 + S:0 + C:1 + H:0 +
+
+ + 		NOT RUN
ShuffleChannels-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 100.0 %
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+ P:3 + F:0 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
Sigmoid-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 94.57 %
+
+
+ P:71 + F:25 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
Sign-1 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
Sin-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 100.0 %
+
+
+ P:12 + F:0 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
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Slice-8 NOT RUN NOT RUN NOT RUN NOT RUN + + 75.81 %
+
+
+ P:85 + F:20 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
SoftPlus-4 NOT RUN NOT RUN NOT RUN NOT RUN + + 66.66 %
+
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+ P:4 + F:2 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
SoftSign-9 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
Softmax-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 100.0 %
+
+
+ P:3 + F:0 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
Softmax-8 NOT RUN NOT RUN NOT RUN NOT RUN + + 92.46 %
+
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+ P:76 + F:17 + S:0 + C:1 + H:0 +
+
+ + 		NOT RUN
SpaceToBatch-2 NOT RUN NOT RUN NOT RUN NOT RUN + + 69.49 %
+
+
+ P:7 + F:2 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
SpaceToDepth-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 66.66 %
+
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+ P:2 + F:1 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
Split-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 70.51 %
+
+
+ P:18 + F:6 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
Sqrt-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 86.25 %
+
+
+ P:35 + F:11 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
SquaredDifference-1 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
Squeeze-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 69.78 %
+
+
+ P:72 + F:17 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
StridedSlice-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 69.8 %
+
+
+ P:486 + F:118 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
Subtract-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 72.22 %
+
+
+ P:124 + F:18 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
Swish-4 NOT RUN NOT RUN NOT RUN NOT RUN + + 43.89 %
+
+
+ P:109 + F:108 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
Tan-1 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
Tanh-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 95.95 %
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+
+ P:19 + F:2 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
TensorIterator-1 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
Tile-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 99.79 %
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+
+ P:11 + F:1 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
TopK-1 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
TopK-11 NOT RUN NOT RUN NOT RUN NOT RUN + + 66.66 %
+
+
+ P:6 + F:3 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
TopK-3 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
Transpose-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 71.98 %
+
+
+ P:361 + F:108 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
Unique-10 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
Unsqueeze-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 69.91 %
+
+
+ P:279 + F:56 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
VariadicSplit-1 NOT RUN NOT RUN NOT RUN NOT RUN + + 99.62 %
+
+
+ P:78 + F:6 + S:0 + C:0 + H:0 +
+
+ + 		NOT RUN
Xor-1 NOT RUN NOT RUN NOT RUN NOT RUNN/A NOT RUN
+ + + + \ No newline at end of file diff --git a/docs/sphinx_setup/_static/download/conformance_reports/template/chosen.jquery.min.js b/docs/sphinx_setup/_static/conformance_files/conformance_reports/template/chosen.jquery.min.js similarity index 100% rename from docs/sphinx_setup/_static/download/conformance_reports/template/chosen.jquery.min.js rename to docs/sphinx_setup/_static/conformance_files/conformance_reports/template/chosen.jquery.min.js diff --git a/docs/sphinx_setup/_static/download/conformance_reports/template/filters.js b/docs/sphinx_setup/_static/conformance_files/conformance_reports/template/filters.js similarity index 100% rename from docs/sphinx_setup/_static/download/conformance_reports/template/filters.js rename to docs/sphinx_setup/_static/conformance_files/conformance_reports/template/filters.js diff --git a/docs/sphinx_setup/_static/download/conformance_reports/template/highlight_tables_template.html b/docs/sphinx_setup/_static/conformance_files/conformance_reports/template/highlight_tables_template.html similarity index 100% rename from docs/sphinx_setup/_static/download/conformance_reports/template/highlight_tables_template.html rename to docs/sphinx_setup/_static/conformance_files/conformance_reports/template/highlight_tables_template.html diff --git a/docs/sphinx_setup/_static/download/conformance_reports/template/report_template.html b/docs/sphinx_setup/_static/conformance_files/conformance_reports/template/report_template.html similarity index 100% rename from docs/sphinx_setup/_static/download/conformance_reports/template/report_template.html rename to docs/sphinx_setup/_static/conformance_files/conformance_reports/template/report_template.html diff --git a/docs/sphinx_setup/_static/download/conformance_reports/template/style.css b/docs/sphinx_setup/_static/conformance_files/conformance_reports/template/style.css similarity index 100% rename from docs/sphinx_setup/_static/download/conformance_reports/template/style.css rename to docs/sphinx_setup/_static/conformance_files/conformance_reports/template/style.css diff --git a/docs/sphinx_setup/_static/conformance_files/paddlepaddle_ops.csv b/docs/sphinx_setup/_static/conformance_files/paddlepaddle_ops.csv new file mode 100644 index 00000000000000..0ee06e48c3b587 --- /dev/null +++ b/docs/sphinx_setup/_static/conformance_files/paddlepaddle_ops.csv @@ -0,0 +1,106 @@ +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, diff --git a/docs/sphinx_setup/_static/conformance_files/pytorch_ops.csv b/docs/sphinx_setup/_static/conformance_files/pytorch_ops.csv new file mode 100644 index 00000000000000..a5836fb9b1f946 --- /dev/null +++ b/docs/sphinx_setup/_static/conformance_files/pytorch_ops.csv @@ -0,0 +1,408 @@ +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::_pack_padded_sequence, +aten::_pad_packed_sequence, +aten::_set_item, +aten::_shape_as_tensor, +aten::_unique2, +aten::_upsample_bicubic2d_aa, +aten::_upsample_bilinear2d_aa, +aten::_weight_norm, +aten::abs, +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::aminmax, +aten::any, +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::bucketize, +aten::cat, +aten::cdist, +aten::ceil, +aten::ceil_, +aten::celu, +aten::celu_, +aten::channel_shuffle, +aten::chunk , Supported in limited set of patterns +aten::clamp, +aten::clamp_, +aten::clamp_max, +aten::clamp_max_, +aten::clamp_min, +aten::clamp_min_, +aten::clip, +aten::clip_, +aten::clone, +aten::col2im, +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::dot, +aten::dropout, +aten::dropout_, +aten::einsum , Supported in limited set of patterns +aten::elu, +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::expm1, +aten::expm1_, +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::floor_divide_, +aten::floordiv, +aten::fmod, +aten::frobenius_norm, +aten::full, +aten::full_like, +aten::gather, +aten::gcd, +aten::ge, +aten::gelu, +aten::glu, +aten::grid_sampler, +aten::group_norm, +aten::gru, +aten::gt, +aten::hann_window, +aten::hardsigmoid, +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_add, +aten::index_add_, +aten::index_copy_, +aten::index_put_, +aten::index_select, +aten::instance_norm, +aten::Int, +aten::IntImplicit, +aten::inverse, +aten::is_grad_enabled, +aten::is_nonzero, +aten::isfinite, +aten::isinf, +aten::isnan, +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_inv, +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_sigmoid, +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::mish, +aten::mish_, +aten::mm, +aten::movedim, +aten::mul, +aten::mul_, +aten::multinomial, +aten::multiply, +aten::multiply_, +aten::mv, +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::reciprocal_, +aten::reflection_pad2d , Supported in limited set of patterns +aten::relu, +aten::relu6, +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::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::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, +ov_ext::conv1d, +ov_ext::embedding, +ov_ext::linear, +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::max , Supported in limited set of patterns +prim::min , Supported in limited set of patterns +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, diff --git a/docs/sphinx_setup/_static/conformance_files/tensorflow_ops.csv b/docs/sphinx_setup/_static/conformance_files/tensorflow_ops.csv new file mode 100644 index 00000000000000..2ae67c460064a4 --- /dev/null +++ b/docs/sphinx_setup/_static/conformance_files/tensorflow_ops.csv @@ -0,0 +1,1400 @@ +Operation Name,Supported,Limitation +Abort,NO, +Abs,YES, +AccumulateNV2,NO, +AccumulatorApplyGradient,NO, +AccumulatorNumAccumulated,NO, +AccumulatorSetGlobalStep,NO, +AccumulatorTakeGradient,NO, +Acos,YES, +Acosh,YES, +Add,YES, +AddManySparseToTensorsMap,NO, +AddN,YES, +AddSparseToTensorsMap,NO, +AddV2,YES, +AdjustContrast,NO, +AdjustContrastv2,YES, +AdjustHueNEW,YES, +AdjustSaturationNEW,YES, +All,YES, +AllCandidateSampler,NO, +AllToAll,NO, +Angle,YES, +AnonymousHashTable,NO, +AnonymousIterator,NO, +AnonymousIteratorV2,NO, +AnonymousIteratorV3,NO, +AnonymousMemoryCache,NO, +AnonymousMultiDeviceIterator,NO, +AnonymousMultiDeviceIteratorV3,NO, +AnonymousMutableDenseHashTable,NO, +AnonymousMutableHashTable,NO, +AnonymousMutableHashTableOfTensors,NO, +AnonymousRandomSeedGenerator,NO, +AnonymousSeedGenerator,NO, +Any,YES, +ApplyAdaMax,NO, +ApplyAdadelta,NO, +ApplyAdagrad,NO, +ApplyAdagradDA,NO, +ApplyAdagradV2,NO, +ApplyAdam,NO, +ApplyAddSign,NO, +ApplyCenteredRMSProp,NO, +ApplyFtrl,NO, +ApplyFtrlV2,NO, +ApplyGradientDescent,NO, +ApplyMomentum,NO, +ApplyPowerSign,NO, +ApplyProximalAdagrad,NO, +ApplyProximalGradientDescent,NO, +ApplyRMSProp,NO, +ApproxTopK,NO, +ApproximateEqual,YES, +ArgMax,YES, +ArgMin,YES, +AsString,NO, +Asin,YES, +Asinh,YES, +Assert,YES, +AssertCardinalityDataset,NO, +AssertNextDataset,NO, +AssertPrevDataset,NO, +Assign,YES, +AssignAdd,YES, +AssignAddVariableOp,YES, +AssignSub,YES, +AssignSubVariableOp,YES, +AssignVariableOp,YES, +AssignVariableXlaConcatND,NO, +Atan,YES, +Atan2,YES, +Atanh,YES, +AudioSpectrogram,NO, +AudioSummary,NO, +AudioSummaryV2,NO, +AutoShardDataset,NO, +AvgPool,YES, +AvgPool3D,YES, +AvgPool3DGrad,NO, +AvgPoolGrad,NO, +BandedTriangularSolve,NO, +Barrier,NO, +BarrierClose,NO, +BarrierIncompleteSize,NO, +BarrierInsertMany,NO, +BarrierReadySize,NO, +BarrierTakeMany,NO, +Batch,NO, +BatchCholesky,NO, +BatchCholeskyGrad,NO, +BatchDataset,NO, +BatchDatasetV2,NO, +BatchFFT,NO, +BatchFFT2D,NO, +BatchFFT3D,NO, +BatchFunction,NO, +BatchIFFT,NO, +BatchIFFT2D,NO, +BatchIFFT3D,NO, +BatchMatMul,YES, +BatchMatMulV2,YES, +BatchMatMulV3,YES, +BatchMatrixBandPart,NO, +BatchMatrixDeterminant,NO, +BatchMatrixDiag,NO, +BatchMatrixDiagPart,NO, +BatchMatrixInverse,NO, +BatchMatrixSetDiag,NO, +BatchMatrixSolve,NO, +BatchMatrixSolveLs,NO, +BatchMatrixTriangularSolve,NO, +BatchNormWithGlobalNormalization,NO, +BatchNormWithGlobalNormalizationGrad,NO, +BatchSelfAdjointEig,NO, +BatchSelfAdjointEigV2,NO, +BatchSvd,NO, +BatchToSpace,NO, +BatchToSpaceND,YES, +BesselI0,NO, +BesselI0e,NO, +BesselI1,NO, +BesselI1e,NO, +BesselJ0,NO, +BesselJ1,NO, +BesselK0,NO, +BesselK0e,NO, +BesselK1,NO, +BesselK1e,NO, +BesselY0,NO, +BesselY1,NO, +Betainc,NO, +BiasAdd,YES, +BiasAddGrad,NO, +BiasAddV1,NO, +Bincount,YES, +Bitcast,NO, +BitwiseAnd,YES, +BitwiseOr,YES, +BitwiseXor,YES, +BlockLSTM,YES, +BlockLSTMGrad,NO, +BlockLSTMGradV2,NO, +BlockLSTMV2,NO, +BoostedTreesAggregateStats,NO, +BoostedTreesBucketize,NO, +BoostedTreesCalculateBestFeatureSplit,NO, +BoostedTreesCalculateBestFeatureSplitV2,NO, +BoostedTreesCalculateBestGainsPerFeature,NO, +BoostedTreesCenterBias,NO, +BoostedTreesCreateEnsemble,NO, +BoostedTreesCreateQuantileStreamResource,NO, +BoostedTreesDeserializeEnsemble,NO, +BoostedTreesEnsembleResourceHandleOp,NO, +BoostedTreesExampleDebugOutputs,NO, +BoostedTreesFlushQuantileSummaries,NO, +BoostedTreesGetEnsembleStates,NO, +BoostedTreesMakeQuantileSummaries,NO, +BoostedTreesMakeStatsSummary,NO, +BoostedTreesPredict,NO, +BoostedTreesQuantileStreamResourceAddSummaries,NO, +BoostedTreesQuantileStreamResourceDeserialize,NO, +BoostedTreesQuantileStreamResourceFlush,NO, +BoostedTreesQuantileStreamResourceGetBucketBoundaries,NO, +BoostedTreesQuantileStreamResourceHandleOp,NO, +BoostedTreesSerializeEnsemble,NO, +BoostedTreesSparseAggregateStats,NO, +BoostedTreesSparseCalculateBestFeatureSplit,NO, +BoostedTreesTrainingPredict,NO, +BoostedTreesUpdateEnsemble,NO, +BoostedTreesUpdateEnsembleV2,NO, +BroadcastArgs,YES, +BroadcastGradientArgs,NO, +BroadcastTo,YES, +Bucketize,YES, +BytesProducedStatsDataset,NO, +CSRSparseMatrixComponents,NO, +CSRSparseMatrixToDense,NO, +CSRSparseMatrixToSparseTensor,NO, +CSVDataset,NO, +CSVDatasetV2,NO, +CTCBeamSearchDecoder,NO, +CTCGreedyDecoder,YES, +CTCLoss,YES, +CTCLossV2,NO, +CacheDataset,NO, +CacheDatasetV2,NO, +Case,NO, +Cast,YES, +Ceil,YES, +CheckNumerics,YES, +CheckNumericsV2,YES, +Cholesky,NO, +CholeskyGrad,NO, +ChooseFastestBranchDataset,NO, +ChooseFastestDataset,NO, +ClipByValue,YES, +CloseSummaryWriter,NO, +CollectiveAllToAllV2,NO, +CollectiveAllToAllV3,NO, +CollectiveAssignGroupV2,NO, +CollectiveBcastRecv,NO, +CollectiveBcastRecvV2,NO, +CollectiveBcastSend,NO, +CollectiveBcastSendV2,NO, +CollectiveGather,NO, +CollectiveGatherV2,NO, +CollectiveInitializeCommunicator,NO, +CollectivePermute,NO, +CollectiveReduce,NO, +CollectiveReduceScatterV2,NO, +CollectiveReduceV2,NO, +CollectiveReduceV3,NO, +CombinedNonMaxSuppression,NO, +Complex,YES, +ComplexAbs,YES, +CompositeTensorVariantFromComponents,NO, +CompositeTensorVariantToComponents,NO, +CompressElement,NO, +ComputeAccidentalHits,NO, +ComputeBatchSize,NO, +Concat,YES, +ConcatOffset,NO, +ConcatV2,YES, +ConcatenateDataset,NO, +ConditionalAccumulator,NO, +ConfigureDistributedTPU,NO, +ConfigureTPUEmbedding,NO, +Conj,YES, +ConjugateTranspose,YES, +Const,YES, +ConsumeMutexLock,NO, +ControlTrigger,NO, +Conv,NO, +Conv2D,YES, +Conv2DBackpropFilter,NO, +Conv2DBackpropFilterV2,NO, +Conv2DBackpropInput,YES, +Conv2DBackpropInputV2,NO, +Conv3D,YES, +Conv3DBackpropFilter,NO, +Conv3DBackpropFilterV2,NO, +Conv3DBackpropInput,NO, +Conv3DBackpropInputV2,YES, +Copy,NO, +CopyHost,NO, +Cos,YES, +Cosh,YES, +CountUpTo,NO, +CreateSummaryDbWriter,NO, +CreateSummaryFileWriter,NO, +CropAndResize,YES, +CropAndResizeGradBoxes,NO, +CropAndResizeGradImage,NO, +Cross,NO, +CrossReplicaSum,NO, +CudnnRNN,NO, +CudnnRNNBackprop,NO, +CudnnRNNBackpropV2,NO, +CudnnRNNBackpropV3,NO, +CudnnRNNCanonicalToParams,NO, +CudnnRNNCanonicalToParamsV2,NO, +CudnnRNNParamsSize,NO, +CudnnRNNParamsToCanonical,NO, +CudnnRNNParamsToCanonicalV2,NO, +CudnnRNNV2,NO, +CudnnRNNV3,NO, +Cumprod,NO, +Cumsum,YES, +CumulativeLogsumexp,NO, +DataFormatDimMap,NO, +DataFormatVecPermute,NO, +DataServiceDataset,NO, +DataServiceDatasetV2,NO, +DataServiceDatasetV3,NO, +DataServiceDatasetV4,NO, +DatasetCardinality,NO, +DatasetFromGraph,NO, +DatasetToGraph,NO, +DatasetToGraphV2,NO, +DatasetToSingleElement,NO, +DatasetToTFRecord,NO, +Dawsn,NO, +DebugGradientIdentity,NO, +DebugGradientRefIdentity,NO, +DebugIdentity,NO, +DebugIdentityV2,NO, +DebugIdentityV3,NO, +DebugNanCount,NO, +DebugNumericSummary,NO, +DebugNumericSummaryV2,NO, +DecodeAndCropJpeg,NO, +DecodeBase64,NO, +DecodeBmp,NO, +DecodeCSV,NO, +DecodeCompressed,NO, +DecodeGif,NO, +DecodeImage,NO, +DecodeJSONExample,NO, +DecodeJpeg,NO, +DecodePaddedRaw,NO, +DecodePng,NO, +DecodeProtoV2,NO, +DecodeRaw,NO, +DecodeWav,NO, +DeepCopy,NO, +DeleteIterator,NO, +DeleteMemoryCache,NO, +DeleteMultiDeviceIterator,NO, +DeleteRandomSeedGenerator,NO, +DeleteSeedGenerator,NO, +DeleteSessionTensor,NO, +DenseBincount,NO, +DenseCountSparseOutput,NO, +DenseToCSRSparseMatrix,NO, +DenseToDenseSetOperation,NO, +DenseToSparseBatchDataset,NO, +DenseToSparseSetOperation,NO, +DepthToSpace,YES, +DepthwiseConv2dNative,YES, +DepthwiseConv2dNativeBackpropFilter,NO, +DepthwiseConv2dNativeBackpropInput,NO, +Dequantize,NO, +DeserializeIterator,NO, +DeserializeManySparse,NO, +DeserializeSparse,NO, +DestroyResourceOp,NO, +DestroyTemporaryVariable,NO, +DeviceIndex,NO, +Diag,NO, +DiagPart,NO, +Digamma,NO, +Dilation2D,NO, +Dilation2DBackpropFilter,NO, +Dilation2DBackpropInput,NO, +DirectedInterleaveDataset,NO, +DisableCopyOnRead,NO, +DistributedSave,NO, +Div,YES, +DivNoNan,YES, +DrawBoundingBoxes,NO, +DrawBoundingBoxesV2,NO, +DummyIterationCounter,NO, +DummyMemoryCache,NO, +DummySeedGenerator,NO, +DynamicEnqueueTPUEmbeddingArbitraryTensorBatch,NO, +DynamicPartition,YES, +DynamicStitch,YES, +EagerPyFunc,NO, +EditDistance,NO, +Eig,NO, +Einsum,YES, +Elu,YES, +EluGrad,NO, +Empty,NO, +EmptyTensorList,YES, +EncodeBase64,NO, +EncodeJpeg,NO, +EncodeJpegVariableQuality,NO, +EncodePng,NO, +EncodeProto,NO, +EncodeWav,NO, +EnqueueTPUEmbeddingArbitraryTensorBatch,NO, +EnqueueTPUEmbeddingIntegerBatch,NO, +EnqueueTPUEmbeddingRaggedTensorBatch,NO, +EnqueueTPUEmbeddingSparseBatch,NO, +EnqueueTPUEmbeddingSparseTensorBatch,NO, +EnsureShape,YES, +Enter,YES, +Equal,YES, +Erf,YES, +Erfc,NO, +Erfinv,NO, +EuclideanNorm,YES, +Exit,YES, +Exp,YES, +ExpandDims,YES, +ExperimentalAssertNextDataset,NO, +ExperimentalAutoShardDataset,NO, +ExperimentalBytesProducedStatsDataset,NO, +ExperimentalCSVDataset,NO, +ExperimentalChooseFastestDataset,NO, +ExperimentalDatasetCardinality,NO, +ExperimentalDatasetToTFRecord,NO, +ExperimentalDenseToSparseBatchDataset,NO, +ExperimentalDirectedInterleaveDataset,NO, +ExperimentalGroupByReducerDataset,NO, +ExperimentalGroupByWindowDataset,NO, +ExperimentalIgnoreErrorsDataset,NO, +ExperimentalIteratorGetDevice,NO, +ExperimentalLMDBDataset,NO, +ExperimentalLatencyStatsDataset,NO, +ExperimentalMapAndBatchDataset,NO, +ExperimentalMapDataset,NO, +ExperimentalMatchingFilesDataset,NO, +ExperimentalMaxIntraOpParallelismDataset,NO, +ExperimentalNonSerializableDataset,NO, +ExperimentalParallelInterleaveDataset,NO, +ExperimentalParseExampleDataset,NO, +ExperimentalPrivateThreadPoolDataset,NO, +ExperimentalRandomDataset,NO, +ExperimentalRebatchDataset,NO, +ExperimentalScanDataset,NO, +ExperimentalSetStatsAggregatorDataset,NO, +ExperimentalSleepDataset,NO, +ExperimentalSlidingWindowDataset,NO, +ExperimentalSqlDataset,NO, +ExperimentalStatsAggregatorHandle,NO, +ExperimentalStatsAggregatorSummary,NO, +ExperimentalTakeWhileDataset,NO, +ExperimentalThreadPoolDataset,NO, +ExperimentalThreadPoolHandle,NO, +ExperimentalUnbatchDataset,NO, +ExperimentalUniqueDataset,NO, +Expint,NO, +Expm1,NO, +ExtractGlimpse,NO, +ExtractGlimpseV2,NO, +ExtractImagePatches,YES, +ExtractJpegShape,NO, +ExtractVolumePatches,NO, +FFT,YES, +FFT2D,YES, +FFT3D,YES, +FIFOQueue,YES, +FIFOQueueV2,YES, +Fact,NO, +FakeParam,NO, +FakeQuantWithMinMaxArgs,YES, +FakeQuantWithMinMaxArgsGradient,NO, +FakeQuantWithMinMaxVars,YES, +FakeQuantWithMinMaxVarsGradient,NO, +FakeQuantWithMinMaxVarsPerChannel,YES, +FakeQuantWithMinMaxVarsPerChannelGradient,NO, +FakeQueue,NO, +Fill,YES, +FilterByLastComponentDataset,NO, +FilterDataset,NO, +FinalizeDataset,NO, +Fingerprint,NO, +FixedLengthRecordDataset,NO, +FixedLengthRecordDatasetV2,NO, +FixedLengthRecordReader,NO, +FixedLengthRecordReaderV2,NO, +FixedUnigramCandidateSampler,NO, +FlatMapDataset,NO, +Floor,YES, +FloorDiv,YES, +FloorMod,YES, +FlushSummaryWriter,NO, +For,NO, +FractionalAvgPool,NO, +FractionalAvgPoolGrad,NO, +FractionalMaxPool,NO, +FractionalMaxPoolGrad,NO, +FresnelCos,NO, +FresnelSin,NO, +FusedBatchNorm,YES, +FusedBatchNormGrad,NO, +FusedBatchNormGradV2,NO, +FusedBatchNormGradV3,NO, +FusedBatchNormV2,YES, +FusedBatchNormV3,YES, +FusedPadConv2D,NO, +FusedResizeAndPadConv2D,NO, +GRUBlockCell,YES, +GRUBlockCellGrad,NO, +Gather,YES, +GatherNd,YES, +GatherV2,YES, +GenerateBoundingBoxProposals,NO, +GenerateVocabRemapping,NO, +GeneratorDataset,NO, +GetElementAtIndex,NO, +GetOptions,NO, +GetSessionHandle,NO, +GetSessionHandleV2,NO, +GetSessionTensor,NO, +Greater,YES, +GreaterEqual,YES, +GroupByReducerDataset,NO, +GroupByWindowDataset,NO, +GuaranteeConst,NO, +HSVToRGBNEW,YES, +HashTable,YES, +HashTableV2,YES, +HistogramFixedWidth,NO, +HistogramSummary,NO, +IFFT,YES, +IFFT2D,YES, +IFFT3D,YES, +IRFFT,YES, +IRFFT2D,YES, +IRFFT3D,YES, +Identity,YES, +IdentityN,YES, +IdentityReader,NO, +IdentityReaderV2,NO, +If,YES, +Igamma,NO, +IgammaGradA,NO, +Igammac,NO, +IgnoreErrorsDataset,NO, +Imag,YES, +ImageProjectiveTransformV2,NO, +ImageProjectiveTransformV3,NO, +ImageSummary,NO, +ImmutableConst,NO, +ImportEvent,NO, +InTopK,NO, +InTopKV2,NO, +InfeedDequeue,NO, +InfeedDequeueTuple,NO, +InfeedEnqueue,NO, +InfeedEnqueuePrelinearizedBuffer,NO, +InfeedEnqueueTuple,NO, +InitializeTable,NO, +InitializeTableFromDataset,NO, +InitializeTableFromTextFile,NO, +InitializeTableFromTextFileV2,NO, +InitializeTableV2,NO, +InplaceAdd,NO, +InplaceSub,NO, +InplaceUpdate,NO, +InterleaveDataset,NO, +Inv,YES, +InvGrad,NO, +Invert,YES, +InvertPermutation,YES, +IsBoostedTreesEnsembleInitialized,NO, +IsBoostedTreesQuantileStreamResourceInitialized,NO, +IsFinite,YES, +IsInf,YES, +IsNan,YES, +IsTPUEmbeddingInitialized,NO, +IsVariableInitialized,YES, +IsotonicRegression,NO, +Iterator,YES, +IteratorFromStringHandle,NO, +IteratorFromStringHandleV2,NO, +IteratorGetDevice,NO, +IteratorGetNext,YES, +IteratorGetNextAsOptional,NO, +IteratorGetNextSync,NO, +IteratorToStringHandle,NO, +IteratorV2,YES, +L2Loss,YES, +LMDBDataset,NO, +LMDBReader,NO, +LRN,YES, +LRNGrad,NO, +LSTMBlockCell,NO, +LSTMBlockCellGrad,NO, +LatencyStatsDataset,NO, +LeakyRelu,YES, +LeakyReluGrad,NO, +LearnedUnigramCandidateSampler,NO, +LeftShift,NO, +LegacyParallelInterleaveDatasetV2,NO, +Less,YES, +LessEqual,YES, +Lgamma,NO, +LinSpace,YES, +ListDataset,NO, +ListDiff,YES, +LoadAndRemapMatrix,NO, +LoadDataset,NO, +LoadTPUEmbeddingADAMParameters,NO, +LoadTPUEmbeddingAdadeltaParameters,NO, +LoadTPUEmbeddingAdagradMomentumParameters,NO, +LoadTPUEmbeddingAdagradParameters,NO, +LoadTPUEmbeddingCenteredRMSPropParameters,NO, +LoadTPUEmbeddingFTRLParameters,NO, +LoadTPUEmbeddingFrequencyEstimatorParameters,NO, +LoadTPUEmbeddingMDLAdagradLightParameters,NO, +LoadTPUEmbeddingMomentumParameters,NO, +LoadTPUEmbeddingProximalAdagradParameters,NO, +LoadTPUEmbeddingProximalYogiParameters,NO, +LoadTPUEmbeddingRMSPropParameters,NO, +LoadTPUEmbeddingStochasticGradientDescentParameters,NO, +Log,YES, +Log1p,YES, +LogMatrixDeterminant,NO, +LogSoftmax,YES, +LogUniformCandidateSampler,NO, +LogicalAnd,YES, +LogicalNot,YES, +LogicalOr,YES, +LookupTableExport,NO, +LookupTableExportV2,NO, +LookupTableFind,YES, +LookupTableFindV2,YES, +LookupTableImport,YES, +LookupTableImportV2,YES, +LookupTableInsert,YES, +LookupTableInsertV2,YES, +LookupTableRemoveV2,NO, +LookupTableSize,NO, +LookupTableSizeV2,NO, +LoopCond,YES, +LowerBound,NO, +Lu,NO, +MakeIterator,NO, +MapAndBatchDataset,NO, +MapClear,NO, +MapDataset,NO, +MapDefun,NO, +MapIncompleteSize,NO, +MapPeek,NO, +MapSize,NO, +MapStage,NO, +MapUnstage,NO, +MapUnstageNoKey,NO, +MatMul,YES, +MatchingFiles,NO, +MatchingFilesDataset,NO, +MatrixBandPart,YES, +MatrixDeterminant,NO, +MatrixDiag,YES, +MatrixDiagPart,NO, +MatrixDiagPartV2,NO, +MatrixDiagPartV3,NO, +MatrixDiagV2,NO, +MatrixDiagV3,NO, +MatrixExponential,NO, +MatrixInverse,YES, +MatrixLogarithm,NO, +MatrixSetDiag,NO, +MatrixSetDiagV2,NO, +MatrixSetDiagV3,NO, +MatrixSolve,NO, +MatrixSolveLs,NO, +MatrixSquareRoot,NO, +MatrixTriangularSolve,NO, +Max,YES, +MaxIntraOpParallelismDataset,NO, +MaxPool,YES, +MaxPool3D,YES, +MaxPool3DGrad,NO, +MaxPool3DGradGrad,NO, +MaxPoolGrad,NO, +MaxPoolGradGrad,NO, +MaxPoolGradGradV2,NO, +MaxPoolGradGradWithArgmax,NO, +MaxPoolGradV2,NO, +MaxPoolGradWithArgmax,NO, +MaxPoolV2,YES, +MaxPoolWithArgmax,YES, +Maximum,YES, +Mean,YES, +Merge,YES, +MergeSummary,NO, +MergeV2Checkpoints,YES, +Mfcc,NO, +Min,YES, +Minimum,YES, +MirrorPad,YES, +MirrorPadGrad,NO, +Mod,YES, +ModelDataset,NO, +Mul,YES, +MulNoNan,YES, +MultiDeviceIterator,NO, +MultiDeviceIteratorFromStringHandle,NO, +MultiDeviceIteratorGetNextFromShard,NO, +MultiDeviceIteratorInit,NO, +MultiDeviceIteratorToStringHandle,NO, +Multinomial,YES, +MutableDenseHashTable,NO, +MutableDenseHashTableV2,NO, +MutableHashTable,YES, +MutableHashTableOfTensors,NO, +MutableHashTableOfTensorsV2,NO, +MutableHashTableV2,YES, +MutexLock,NO, +MutexV2,NO, +NcclAllReduce,NO, +NcclBroadcast,NO, +NcclReduce,NO, +Ndtri,NO, +Neg,YES, +NextAfter,NO, +NextIteration,YES, +NoOp,YES, +NonDeterministicInts,NO, +NonMaxSuppression,YES, +NonMaxSuppressionV2,YES, +NonMaxSuppressionV3,YES, +NonMaxSuppressionV4,YES, +NonMaxSuppressionV5,YES, +NonMaxSuppressionWithOverlaps,NO, +NonSerializableDataset,NO, +NotEqual,YES, +NthElement,NO, +OneHot,YES, +OneShotIterator,YES, +OnesLike,YES, +OptimizeDataset,NO, +OptimizeDatasetV2,NO, +OptionalFromValue,NO, +OptionalGetValue,NO, +OptionalHasValue,NO, +OptionalNone,NO, +OptionsDataset,NO, +OrderedMapClear,NO, +OrderedMapIncompleteSize,NO, +OrderedMapPeek,NO, +OrderedMapSize,NO, +OrderedMapStage,NO, +OrderedMapUnstage,NO, +OrderedMapUnstageNoKey,NO, +OutfeedDequeue,NO, +OutfeedDequeueTuple,NO, +OutfeedDequeueTupleV2,NO, +OutfeedDequeueV2,NO, +OutfeedEnqueue,NO, +OutfeedEnqueueTuple,NO, +Pack,YES, +Pad,YES, +PadV2,YES, +PaddedBatchDataset,NO, +PaddedBatchDatasetV2,NO, +PaddingFIFOQueue,NO, +PaddingFIFOQueueV2,NO, +ParallelBatchDataset,NO, +ParallelConcat,NO, +ParallelDynamicStitch,YES, +ParallelFilterDataset,NO, +ParallelInterleaveDataset,NO, +ParallelInterleaveDatasetV2,NO, +ParallelInterleaveDatasetV3,NO, +ParallelInterleaveDatasetV4,NO, +ParallelMapDataset,NO, +ParallelMapDatasetV2,NO, +ParameterizedTruncatedNormal,NO, +ParseExample,NO, +ParseExampleDataset,NO, +ParseExampleDatasetV2,NO, +ParseExampleV2,NO, +ParseSequenceExample,NO, +ParseSequenceExampleV2,NO, +ParseSingleExample,NO, +ParseSingleSequenceExample,NO, +ParseTensor,NO, +PartitionedCall,YES, +Placeholder,YES, +PlaceholderV2,NO, +PlaceholderWithDefault,YES, +Polygamma,NO, +PopulationCount,NO, +Pow,YES, +PrefetchDataset,NO, +Prelinearize,NO, +PrelinearizeTuple,NO, +PreventGradient,YES, +Print,NO, +PrintV2,NO, +PriorityQueue,NO, +PriorityQueueV2,NO, +PrivateThreadPoolDataset,NO, +Prod,YES, +PyFunc,NO, +PyFuncStateless,NO, +Qr,NO, +QuantizeAndDequantize,NO, +QuantizeAndDequantizeV2,NO, +QuantizeAndDequantizeV3,NO, +QuantizeAndDequantizeV4,NO, +QuantizeAndDequantizeV4Grad,NO, +QuantizeDownAndShrinkRange,NO, +QuantizeV2,NO, +QuantizedAdd,NO, +QuantizedAvgPool,NO, +QuantizedBatchNormWithGlobalNormalization,NO, +QuantizedBiasAdd,NO, +QuantizedConcat,NO, +QuantizedConv2D,NO, +QuantizedConv2DAndRelu,NO, +QuantizedConv2DAndReluAndRequantize,NO, +QuantizedConv2DAndRequantize,NO, +QuantizedConv2DPerChannel,NO, +QuantizedConv2DWithBias,NO, +QuantizedConv2DWithBiasAndRelu,NO, +QuantizedConv2DWithBiasAndReluAndRequantize,NO, +QuantizedConv2DWithBiasAndRequantize,NO, +QuantizedConv2DWithBiasSignedSumAndReluAndRequantize,NO, +QuantizedConv2DWithBiasSumAndRelu,NO, +QuantizedConv2DWithBiasSumAndReluAndRequantize,NO, +QuantizedDepthwiseConv2D,NO, +QuantizedDepthwiseConv2DWithBias,NO, +QuantizedDepthwiseConv2DWithBiasAndRelu,NO, +QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize,NO, +QuantizedInstanceNorm,NO, +QuantizedMatMul,NO, +QuantizedMatMulWithBias,NO, +QuantizedMatMulWithBiasAndDequantize,NO, +QuantizedMatMulWithBiasAndRelu,NO, +QuantizedMatMulWithBiasAndReluAndRequantize,NO, +QuantizedMatMulWithBiasAndRequantize,NO, +QuantizedMaxPool,NO, +QuantizedMul,NO, +QuantizedRelu,NO, +QuantizedRelu6,NO, +QuantizedReluX,NO, +QuantizedReshape,NO, +QuantizedResizeBilinear,NO, +QueueClose,NO, +QueueCloseV2,NO, +QueueDequeue,YES, +QueueDequeueMany,YES, +QueueDequeueManyV2,NO, +QueueDequeueUpTo,YES, +QueueDequeueUpToV2,YES, +QueueDequeueV2,YES, +QueueEnqueue,NO, +QueueEnqueueMany,NO, +QueueEnqueueManyV2,NO, +QueueEnqueueV2,NO, +QueueIsClosed,NO, +QueueIsClosedV2,NO, +QueueSize,NO, +QueueSizeV2,NO, +RFFT,YES, +RFFT2D,YES, +RFFT3D,YES, +RGBToHSV,NO, +RaggedBincount,NO, +RaggedCountSparseOutput,NO, +RaggedCross,NO, +RaggedFillEmptyRows,NO, +RaggedFillEmptyRowsGrad,NO, +RaggedGather,NO, +RaggedRange,NO, +RaggedTensorFromVariant,NO, +RaggedTensorToSparse,YES,openvino-tokenizers required +RaggedTensorToTensor,YES,openvino-tokenizers required +RaggedTensorToVariant,NO, +RaggedTensorToVariantGradient,NO, +RandomCrop,NO, +RandomDataset,NO, +RandomDatasetV2,NO, +RandomGamma,NO, +RandomGammaGrad,NO, +RandomIndexShuffle,NO, +RandomPoisson,NO, +RandomPoissonV2,NO, +RandomShuffle,NO, +RandomShuffleQueue,NO, +RandomShuffleQueueV2,NO, +RandomStandardNormal,NO, +RandomUniform,YES, +RandomUniformInt,YES, +Range,YES, +RangeDataset,NO, +Rank,YES, +ReadFile,NO, +ReadVariableOp,YES, +ReadVariableXlaSplitND,NO, +ReaderNumRecordsProduced,NO, +ReaderNumRecordsProducedV2,NO, +ReaderNumWorkUnitsCompleted,NO, +ReaderNumWorkUnitsCompletedV2,NO, +ReaderRead,NO, +ReaderReadUpTo,NO, +ReaderReadUpToV2,NO, +ReaderReadV2,NO, +ReaderReset,NO, +ReaderResetV2,NO, +ReaderRestoreState,NO, +ReaderRestoreStateV2,NO, +ReaderSerializeState,NO, +ReaderSerializeStateV2,NO, +Real,YES, +RealDiv,YES, +RebatchDataset,NO, +RebatchDatasetV2,NO, +Reciprocal,YES, +ReciprocalGrad,NO, +RecordInput,NO, +Recv,NO, +RecvTPUEmbeddingActivations,NO, +ReduceDataset,NO, +ReduceJoin,NO, +RefEnter,NO, +RefExit,NO, +RefIdentity,NO, +RefMerge,NO, +RefNextIteration,NO, +RefSelect,NO, +RefSwitch,NO, +RegexFullMatch,NO, +RegexReplace,NO, +RegisterDataset,NO, +RegisterDatasetV2,NO, +Relu,YES, +Relu6,YES, +Relu6Grad,NO, +ReluGrad,NO, +RemoteCall,NO, +RepeatDataset,NO, +RequantizationRange,NO, +RequantizationRangePerChannel,NO, +Requantize,NO, +RequantizePerChannel,NO, +Reshape,YES, +ResizeArea,NO, +ResizeBicubic,NO, +ResizeBicubicGrad,NO, +ResizeBilinear,YES, +ResizeBilinearGrad,NO, +ResizeNearestNeighbor,YES, +ResizeNearestNeighborGrad,NO, +ResourceAccumulatorApplyGradient,NO, +ResourceAccumulatorNumAccumulated,NO, +ResourceAccumulatorSetGlobalStep,NO, +ResourceAccumulatorTakeGradient,NO, +ResourceApplyAdaMax,NO, +ResourceApplyAdadelta,NO, +ResourceApplyAdagrad,NO, +ResourceApplyAdagradDA,NO, +ResourceApplyAdagradV2,NO, +ResourceApplyAdam,NO, +ResourceApplyAdamWithAmsgrad,NO, +ResourceApplyAddSign,NO, +ResourceApplyCenteredRMSProp,NO, +ResourceApplyFtrl,NO, +ResourceApplyFtrlV2,NO, +ResourceApplyGradientDescent,NO, +ResourceApplyKerasMomentum,NO, +ResourceApplyMomentum,NO, +ResourceApplyPowerSign,NO, +ResourceApplyProximalAdagrad,NO, +ResourceApplyProximalGradientDescent,NO, +ResourceApplyRMSProp,NO, +ResourceConditionalAccumulator,NO, +ResourceCountUpTo,NO, +ResourceGather,YES, +ResourceGatherNd,NO, +ResourceScatterAdd,NO, +ResourceScatterDiv,NO, +ResourceScatterMax,NO, +ResourceScatterMin,NO, +ResourceScatterMul,NO, +ResourceScatterNdAdd,NO, +ResourceScatterNdMax,NO, +ResourceScatterNdMin,NO, +ResourceScatterNdSub,NO, +ResourceScatterNdUpdate,NO, +ResourceScatterSub,NO, +ResourceScatterUpdate,NO, +ResourceSparseApplyAdadelta,NO, +ResourceSparseApplyAdagrad,NO, +ResourceSparseApplyAdagradDA,NO, +ResourceSparseApplyAdagradV2,NO, +ResourceSparseApplyCenteredRMSProp,NO, +ResourceSparseApplyFtrl,NO, +ResourceSparseApplyFtrlV2,NO, +ResourceSparseApplyKerasMomentum,NO, +ResourceSparseApplyMomentum,NO, +ResourceSparseApplyProximalAdagrad,NO, +ResourceSparseApplyProximalGradientDescent,NO, +ResourceSparseApplyRMSProp,NO, +ResourceStridedSliceAssign,NO, +Restore,NO, +RestoreSlice,NO, +RestoreV2,YES, +RetrieveTPUEmbeddingADAMParameters,NO, +RetrieveTPUEmbeddingAdadeltaParameters,NO, +RetrieveTPUEmbeddingAdagradMomentumParameters,NO, +RetrieveTPUEmbeddingAdagradParameters,NO, +RetrieveTPUEmbeddingCenteredRMSPropParameters,NO, +RetrieveTPUEmbeddingFTRLParameters,NO, +RetrieveTPUEmbeddingFrequencyEstimatorParameters,NO, +RetrieveTPUEmbeddingMDLAdagradLightParameters,NO, +RetrieveTPUEmbeddingMomentumParameters,NO, +RetrieveTPUEmbeddingProximalAdagradParameters,NO, +RetrieveTPUEmbeddingProximalYogiParameters,NO, +RetrieveTPUEmbeddingRMSPropParameters,NO, +RetrieveTPUEmbeddingStochasticGradientDescentParameters,NO, +Reverse,YES, +ReverseSequence,YES, +ReverseV2,YES, +RewriteDataset,NO, +RightShift,NO, +Rint,YES, +RngReadAndSkip,NO, +RngSkip,NO, +Roll,YES, +Round,YES, +Rsqrt,YES, +RsqrtGrad,NO, +SampleDistortedBoundingBox,NO, +SampleDistortedBoundingBoxV2,NO, +SamplingDataset,NO, +Save,NO, +SaveDataset,NO, +SaveDatasetV2,NO, +SaveSlices,NO, +SaveV2,YES, +ScalarSummary,NO, +ScaleAndTranslate,NO, +ScaleAndTranslateGrad,NO, +ScanDataset,NO, +ScatterAdd,NO, +ScatterDiv,NO, +ScatterMax,NO, +ScatterMin,NO, +ScatterMul,NO, +ScatterNd,YES, +ScatterNdAdd,NO, +ScatterNdMax,NO, +ScatterNdMin,NO, +ScatterNdNonAliasingAdd,NO, +ScatterNdSub,NO, +ScatterNdUpdate,NO, +ScatterSub,NO, +ScatterUpdate,NO, +SdcaFprint,NO, +SdcaOptimizer,NO, +SdcaOptimizerV2,NO, +SdcaShrinkL1,NO, +SegmentMax,NO, +SegmentMaxV2,NO, +SegmentMean,NO, +SegmentMin,NO, +SegmentMinV2,NO, +SegmentProd,NO, +SegmentProdV2,NO, +SegmentSum,YES, +SegmentSumV2,NO, +Select,YES, +SelectV2,YES, +SelfAdjointEig,NO, +SelfAdjointEigV2,NO, +Selu,YES, +SeluGrad,NO, +Send,NO, +SendTPUEmbeddingGradients,NO, +SerializeIterator,NO, +SerializeManySparse,NO, +SerializeSparse,NO, +SerializeTensor,NO, +SetSize,NO, +SetStatsAggregatorDataset,NO, +Shape,YES, +ShapeN,YES, +ShardDataset,NO, +ShardedFilename,YES, +ShardedFilespec,NO, +ShuffleAndRepeatDataset,NO, +ShuffleAndRepeatDatasetV2,NO, +ShuffleDataset,NO, +ShuffleDatasetV2,NO, +ShuffleDatasetV3,NO, +ShutdownDistributedTPU,NO, +Sigmoid,YES, +SigmoidGrad,NO, +Sign,YES, +Sin,YES, +Sinh,YES, +Size,YES, +SkipDataset,NO, +SleepDataset,NO, +Slice,YES, +SlidingWindowDataset,NO, +Snapshot,YES, +SnapshotChunkDataset,NO, +SnapshotDataset,NO, +SnapshotDatasetReader,NO, +SnapshotDatasetV2,NO, +SnapshotNestedDatasetReader,NO, +SobolSample,NO, +Softmax,YES, +SoftmaxCrossEntropyWithLogits,NO, +Softplus,YES, +SoftplusGrad,NO, +Softsign,YES, +SoftsignGrad,NO, +SpaceToBatch,NO, +SpaceToBatchND,YES, +SpaceToDepth,YES, +SparseAccumulatorApplyGradient,NO, +SparseAccumulatorTakeGradient,NO, +SparseAdd,NO, +SparseAddGrad,NO, +SparseApplyAdadelta,NO, +SparseApplyAdagrad,NO, +SparseApplyAdagradDA,NO, +SparseApplyAdagradV2,NO, +SparseApplyCenteredRMSProp,NO, +SparseApplyFtrl,NO, +SparseApplyFtrlV2,NO, +SparseApplyMomentum,NO, +SparseApplyProximalAdagrad,NO, +SparseApplyProximalGradientDescent,NO, +SparseApplyRMSProp,NO, +SparseBincount,NO, +SparseConcat,NO, +SparseConditionalAccumulator,NO, +SparseCountSparseOutput,NO, +SparseCross,NO, +SparseCrossHashed,NO, +SparseCrossV2,NO, +SparseDenseCwiseAdd,NO, +SparseDenseCwiseDiv,NO, +SparseDenseCwiseMul,NO, +SparseFillEmptyRows,YES, +SparseFillEmptyRowsGrad,NO, +SparseMatMul,NO, +SparseMatrixAdd,NO, +SparseMatrixMatMul,NO, +SparseMatrixMul,NO, +SparseMatrixNNZ,NO, +SparseMatrixOrderingAMD,NO, +SparseMatrixSoftmax,NO, +SparseMatrixSoftmaxGrad,NO, +SparseMatrixSparseCholesky,NO, +SparseMatrixSparseMatMul,NO, +SparseMatrixTranspose,NO, +SparseMatrixZeros,NO, +SparseReduceMax,NO, +SparseReduceMaxSparse,NO, +SparseReduceSum,NO, +SparseReduceSumSparse,NO, +SparseReorder,NO, +SparseReshape,YES, +SparseSegmentMean,NO, +SparseSegmentMeanGrad,NO, +SparseSegmentMeanGradV2,NO, +SparseSegmentMeanWithNumSegments,NO, +SparseSegmentSqrtN,NO, +SparseSegmentSqrtNGrad,NO, +SparseSegmentSqrtNGradV2,NO, +SparseSegmentSqrtNWithNumSegments,NO, +SparseSegmentSum,YES, +SparseSegmentSumGrad,NO, +SparseSegmentSumGradV2,NO, +SparseSegmentSumWithNumSegments,NO, +SparseSlice,NO, +SparseSliceGrad,NO, +SparseSoftmax,NO, +SparseSoftmaxCrossEntropyWithLogits,NO, +SparseSparseMaximum,NO, +SparseSparseMinimum,NO, +SparseSplit,NO, +SparseTensorDenseAdd,NO, +SparseTensorDenseMatMul,NO, +SparseTensorSliceDataset,NO, +SparseTensorToCSRSparseMatrix,NO, +SparseToDense,YES, +SparseToSparseSetOperation,NO, +Spence,NO, +Split,YES, +SplitV,YES, +SqlDataset,NO, +Sqrt,YES, +SqrtGrad,NO, +Square,YES, +SquaredDifference,YES, +Squeeze,YES, +Stack,NO, +StackClose,NO, +StackCloseV2,NO, +StackPop,NO, +StackPopV2,NO, +StackPush,NO, +StackPushV2,NO, +StackV2,NO, +Stage,NO, +StageClear,NO, +StagePeek,NO, +StageSize,NO, +StatefulPartitionedCall,YES, +StatefulRandomBinomial,NO, +StatefulStandardNormal,NO, +StatefulStandardNormalV2,NO, +StatefulTruncatedNormal,NO, +StatefulUniform,NO, +StatefulUniformFullInt,NO, +StatefulUniformInt,NO, +StatelessCase,NO, +StatelessIf,YES, +StatelessMultinomial,NO, +StatelessParameterizedTruncatedNormal,NO, +StatelessRandomBinomial,NO, +StatelessRandomGammaV2,NO, +StatelessRandomGammaV3,NO, +StatelessRandomGetAlg,NO, +StatelessRandomGetKeyCounter,NO, +StatelessRandomGetKeyCounterAlg,NO, +StatelessRandomNormal,NO, +StatelessRandomNormalV2,NO, +StatelessRandomPoisson,NO, +StatelessRandomUniform,NO, +StatelessRandomUniformFullInt,NO, +StatelessRandomUniformFullIntV2,NO, +StatelessRandomUniformInt,NO, +StatelessRandomUniformIntV2,NO, +StatelessRandomUniformV2,NO, +StatelessSampleDistortedBoundingBox,NO, +StatelessShuffle,NO, +StatelessTruncatedNormal,NO, +StatelessTruncatedNormalV2,NO, +StatelessWhile,YES, +StaticRegexFullMatch,YES, +StaticRegexReplace,YES,openvino-tokenizers required +StatsAggregatorHandle,NO, +StatsAggregatorHandleV2,NO, +StatsAggregatorSetSummaryWriter,NO, +StatsAggregatorSummary,NO, 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+WriteRawProtoSummary,NO, +WriteScalarSummary,NO, +WriteSummary,NO, +Xdivy,YES, +XlaConcatND,NO, +XlaSplitND,NO, +Xlog1py,YES, +Xlogy,YES, +ZerosLike,YES, +Zeta,NO, +ZipDataset,NO, \ No newline at end of file diff --git a/docs/sphinx_setup/_static/download/conformance_reports/opset_report_omz_dynamic.html b/docs/sphinx_setup/_static/download/conformance_reports/opset_report_omz_dynamic.html deleted file mode 100644 index 6116ec813a2c13..00000000000000 --- a/docs/sphinx_setup/_static/download/conformance_reports/opset_report_omz_dynamic.html +++ /dev/null @@ -1,14351 +0,0 @@ - - - - - - - - - - - - - - - Report - - - -
-

Operations coverage summary: Tag: Conformance_report__omz_dynamic_opset | Version: releases/2023/3_2023.3.0-13788-d19307ba138-releases/2023/3 | Time: 25-01-2024 15:27:23

-
-
- Collected statistic info -
-
- N/ANo Tests -
-
- Passrates are based on relative weights each subgraphs! You can check absolute value in `General passrate` row! -
-
- Relative Passrate could be from 0 to 100% (Inference only)! Relative weight of operation is calculated once for current set of models, but there are more then one tests per model. -
-
- Status: - P:85Passed - F:0Failed - S:2Skipped - C:0Crashed - H:0Hanged -
-
- Plugin operation implementation status: -
Implemented
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Not implemented
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Operation ({OpName}-{FirstOpsetNumberContainsOp})CPUDGPUGPUTEMPLATE
Total: 219 52 52 107 52
Trusted op (passrate=100%):69.23 %51.92 %0.0 %75.0 %
AVG passrate (=sum_pass_rates/covered_ops_num):93.83 %86.5 %0.0 %94.7 %
General passrate (=passed_tests/all_tests):93.03 %80.42 %0.0 %94.82 %
Abs-1 - - ---
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-
- - 		- - ---
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-
-
- - 		- - 0.0 %
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- P:0 - F:6 - S:0 - C:0 - H:0 -
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- - 		- - ---
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- -
Acos-1 - - ---
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- - 		- - ---
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- - 		N/A - - ---
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Acosh-4 - - ---
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-
- - 		- - ---
-
-
-
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- - 		N/A - - ---
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- -
AdaptiveAvgPool-8 - - ---
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-
- - 		- - ---
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- - 		N/A - - ---
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- -
AdaptiveMaxPool-8 - - ---
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-
- - 		- - ---
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-
-
-
- - 		N/A - - ---
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- -
Add-1 - - 100.0 %
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-
- P:56 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
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-
- P:56 - F:0 - S:0 - C:1 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:156 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
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-
- P:56 - F:0 - S:0 - C:0 - H:0 -
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- -
Asin-1 - - ---
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-
- - 		- - ---
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- - 		N/A - - ---
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Asinh-4 - - ---
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- - 		- - ---
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- - 		N/A - - ---
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- -
Assign-3 - - ---
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- - 		- - ---
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- - 		N/A - - ---
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Assign-6 - - ---
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-
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-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
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-
-
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- -
Atan-1 - - ---
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-
-
-
- - 		- - ---
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-
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- - 		N/A - - ---
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- -
Atanh-4 - - ---
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-
-
- - 		- - ---
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-
-
- - 		N/A - - ---
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-
-
- -
AvgPool-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:93 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
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-
- -
BatchNormInference-1 - - ---
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- - 		- - ---
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- - 		N/A - - ---
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- -
BatchNormInference-5 - - 100.0 %
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-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
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-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 0.0 %
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-
- P:0 - F:9 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
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-
- P:3 - F:0 - S:0 - C:0 - H:0 -
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- -
BatchToSpace-2 - - ---
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-
- - 		- - ---
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-
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- - 		- - 0.0 %
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- P:0 - F:3 - S:0 - C:0 - H:0 -
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- - 		- - ---
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- -
BinaryConvolution-1 - - ---
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- - 		- - ---
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- - 		N/A - - ---
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BitwiseAnd-13 - - ---
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-
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-
- - 		- - ---
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-
-
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- - 		N/A - - ---
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-
-
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- -
BitwiseNot-13 - - ---
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-
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-
- - 		- - ---
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- - 		N/A - - ---
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- -
BitwiseOr-13 - - ---
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-
- - 		- - ---
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-
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- - 		N/A - - ---
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BitwiseXor-13 - - ---
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- - 		- - ---
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- - 		N/A - - ---
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-
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- -
Broadcast-1 - - ---
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-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
Broadcast-3 - - 98.33 %
-
-
- P:7 - F:0 - S:0 - C:1 - H:0 -
-
- - 		- - 83.81 %
-
-
- P:7 - F:0 - S:0 - C:1 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:72 - S:0 - C:0 - H:0 -
-
- - 		- - 82.63 %
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-
- P:7 - F:0 - S:0 - C:2 - H:0 -
-
- -
Bucketize-3 - - ---
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-
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-
- - 		- - ---
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- - 		N/A - - ---
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- -
CTCGreedyDecoder-1 - - ---
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-
-
-
- - 		- - ---
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-
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- - 		N/A - - ---
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- -
CTCGreedyDecoderSeqLen-6 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
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-
- P:0 - F:3 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
CTCLoss-4 - - ---
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- - 		- - ---
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- - 		N/A - - ---
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-
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- -
Ceiling-1 - - ---
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-
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-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
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-
- P:0 - F:6 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
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-
- -
Clamp-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:15 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
Concat-1 - - 100.0 %
-
-
- P:14 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 95.5 %
-
-
- P:14 - F:0 - S:0 - C:1 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:234 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:13 - F:0 - S:0 - C:0 - H:0 -
-
- -
Constant-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
Convert-1 - - 70.42 %
-
-
- P:29 - F:1 - S:0 - C:0 - H:0 -
-
- - 		- - 70.42 %
-
-
- P:29 - F:1 - S:0 - C:0 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:129 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:30 - F:0 - S:0 - C:0 - H:0 -
-
- -
ConvertLike-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
Convolution-1 - - 99.64 %
-
-
- P:37 - F:0 - S:0 - C:3 - H:0 -
-
- - 		- - 88.98 %
-
-
- P:37 - F:2 - S:0 - C:2 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:714 - S:0 - C:0 - H:0 -
-
- - 		- - 99.69 %
-
-
- P:38 - F:0 - S:0 - C:2 - H:0 -
-
- -
ConvolutionBackpropData-1 - - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:27 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- -
Cos-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:3 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
Cosh-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
CumSum-3 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:3 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
DFT-7 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
DeformableConvolution-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
DeformableConvolution-8 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
DeformablePSROIPooling-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
DepthToSpace-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
DetectionOutput-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
DetectionOutput-8 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:27 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
Divide-1 - - 100.0 %
-
-
- P:12 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:12 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:69 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:12 - F:0 - S:0 - C:0 - H:0 -
-
- -
Einsum-7 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:15 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
Elu-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:3 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
EmbeddingBagOffsetsSum-3 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
EmbeddingBagPackedSum-3 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
EmbeddingSegmentsSum-3 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
Equal-1 - - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:9 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- -
Erf-1 - - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:9 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- -
Exp-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:6 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
ExperimentalDetectronDetectionOutput-6 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
ExperimentalDetectronGenerateProposalsSingleImage-6 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
ExperimentalDetectronPriorGridGenerator-6 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
ExperimentalDetectronROIFeatureExtractor-6 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
ExperimentalDetectronTopKROIs-6 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
ExtractImagePatches-3 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
Eye-9 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
FakeConvert-13 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
FakeQuantize-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:12 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
Floor-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:3 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
FloorMod-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:3 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
GRN-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
GRUCell-3 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
GRUSequence-5 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:12 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
Gather-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
Gather-7 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
Gather-8 - - 98.76 %
-
-
- P:23 - F:0 - S:0 - C:1 - H:0 -
-
- - 		- - 95.04 %
-
-
- P:21 - F:2 - S:0 - C:1 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:90 - S:0 - C:0 - H:0 -
-
- - 		- - 98.76 %
-
-
- P:23 - F:0 - S:0 - C:1 - H:0 -
-
- -
GatherElements-6 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
GatherND-5 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
GatherND-8 - - 66.67 %
-
-
- P:2 - F:1 - S:0 - C:0 - H:0 -
-
- - 		- - 66.67 %
-
-
- P:2 - F:1 - S:0 - C:0 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:6 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- -
GatherTree-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
Gelu-2 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
Gelu-7 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:6 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
GenerateProposals-9 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
Greater-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:6 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
GreaterEqual-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
GridSample-9 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
GroupConvolution-1 - - 100.0 %
-
-
- P:24 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 99.6 %
-
-
- P:23 - F:1 - S:0 - C:0 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:258 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:24 - F:0 - S:0 - C:0 - H:0 -
-
- -
GroupConvolutionBackpropData-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:12 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
GroupNormalization-12 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:6 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
HSigmoid-5 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:9 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
HSwish-4 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:9 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
HardSigmoid-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:12 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
I420toBGR-8 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
I420toRGB-8 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
IDFT-7 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:3 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
IRDFT-9 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
If-8 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:6 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
Interpolate-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
Interpolate-11 - - 97.95 %
-
-
- P:7 - F:0 - S:0 - C:2 - H:0 -
-
- - 		- - 98.88 %
-
-
- P:8 - F:0 - S:0 - C:1 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:51 - S:0 - C:0 - H:0 -
-
- - 		- - 98.88 %
-
-
- P:8 - F:0 - S:0 - C:1 - H:0 -
-
- -
Interpolate-4 - - 66.67 %
-
-
- P:2 - F:0 - S:0 - C:1 - H:0 -
-
- - 		- - 66.67 %
-
-
- P:2 - F:0 - S:0 - C:1 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:21 - S:0 - C:0 - H:0 -
-
- - 		- - 66.67 %
-
-
- P:2 - F:0 - S:0 - C:1 - H:0 -
-
- -
IsFinite-10 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
IsInf-10 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
IsNaN-10 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
LRN-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:3 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
LSTMCell-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
LSTMCell-4 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
LSTMSequence-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
LSTMSequence-5 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:12 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
Less-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:6 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
LessEqual-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
Log-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:3 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
LogSoftmax-5 - - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:6 - S:0 - C:0 - H:0 -
-
- - 		- - 50.0 %
-
-
- P:2 - F:2 - S:0 - C:0 - H:0 -
-
- -
LogicalAnd-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
LogicalNot-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:3 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
LogicalOr-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
LogicalXor-2 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
Loop-5 - - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 66.67 %
-
-
- P:2 - F:1 - S:0 - C:0 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:9 - S:0 - C:0 - H:0 -
-
- - 		- - 50.0 %
-
-
- P:2 - F:2 - S:0 - C:0 - H:0 -
-
- -
MVN-2 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
MVN-6 - - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:21 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- -
MatMul-1 - - 100.0 %
-
-
- P:23 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 99.94 %
-
-
- P:23 - F:1 - S:0 - C:0 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:84 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:22 - F:0 - S:0 - C:0 - H:0 -
-
- -
MatrixNms-8 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
MaxPool-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
MaxPool-8 - - 96.85 %
-
-
- P:7 - F:0 - S:0 - C:1 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:15 - S:0 - C:0 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:108 - S:0 - C:0 - H:0 -
-
- - 		- - 96.85 %
-
-
- P:7 - F:0 - S:0 - C:1 - H:0 -
-
- -
Maximum-1 - - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:27 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- -
Minimum-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:12 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
Mish-4 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:3 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
Mod-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
MulticlassNms-8 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
MulticlassNms-9 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
Multinomial-13 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
Multiply-1 - - 100.0 %
-
-
- P:50 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:50 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:153 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:50 - F:0 - S:0 - C:0 - H:0 -
-
- -
NMSRotated-13 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
NV12toBGR-8 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
NV12toRGB-8 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
Negative-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:3 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
NonMaxSuppression-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
NonMaxSuppression-3 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
NonMaxSuppression-4 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
NonMaxSuppression-5 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
NonMaxSuppression-9 - - 50.0 %
-
-
- P:4 - F:4 - S:0 - C:0 - H:0 -
-
- - 		- - 66.67 %
-
-
- P:4 - F:2 - S:0 - C:0 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:6 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- -
NonZero-3 - - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:6 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- -
NormalizeL2-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:9 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
NotEqual-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:3 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
OneHot-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
PRelu-1 - - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 66.67 %
-
-
- P:2 - F:1 - S:0 - C:0 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:33 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- -
PSROIPooling-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
Pad-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:9 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
Pad-12 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:18 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
Parameter-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
Power-1 - - 100.0 %
-
-
- P:18 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:18 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:54 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:18 - F:0 - S:0 - C:0 - H:0 -
-
- -
PriorBox-1 - - 91.3 %
-
-
- P:50 - F:0 - S:0 - C:7 - H:0 -
-
- - 		- - 78.75 %
-
-
- P:50 - F:0 - S:0 - C:16 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:75 - S:0 - C:0 - H:0 -
-
- - 		- - 93.66 %
-
-
- P:50 - F:0 - S:0 - C:5 - H:0 -
-
- -
PriorBox-8 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
PriorBoxClustered-1 - - 66.67 %
-
-
- P:34 - F:0 - S:0 - C:17 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:85 - S:0 - C:0 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:51 - S:0 - C:0 - H:0 -
-
- - 		- - 69.16 %
-
-
- P:34 - F:0 - S:0 - C:13 - H:0 -
-
- -
Proposal-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
Proposal-4 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:9 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
RDFT-9 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
RNNCell-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
RNNSequence-5 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
ROIAlign-3 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
ROIAlign-9 - - 66.67 %
-
-
- P:2 - F:0 - S:0 - C:1 - H:0 -
-
- - 		- - 66.67 %
-
-
- P:2 - F:1 - S:0 - C:0 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:3 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- -
ROIPooling-2 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:9 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
RandomUniform-8 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
Range-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
Range-4 - - 80.63 %
-
-
- P:8 - F:1 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:9 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:9 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:9 - F:0 - S:0 - C:0 - H:0 -
-
- -
ReadValue-3 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
ReadValue-6 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
ReduceL1-4 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
ReduceL2-4 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
ReduceLogicalAnd-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
ReduceLogicalOr-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
ReduceMax-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:6 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
ReduceMean-1 - - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:27 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- -
ReduceMin-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:6 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
ReduceProd-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:9 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
ReduceSum-1 - - 100.0 %
-
-
- P:13 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:14 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:39 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:13 - F:0 - S:0 - C:0 - H:0 -
-
- -
RegionYolo-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:39 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
Relu-1 - - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 66.67 %
-
-
- P:2 - F:1 - S:0 - C:0 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:15 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- -
ReorgYolo-2 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
Reshape-1 - - 95.37 %
-
-
- P:44 - F:0 - S:0 - C:6 - H:0 -
-
- - 		- - 84.39 %
-
-
- P:44 - F:0 - S:0 - C:5 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:219 - S:0 - C:0 - H:0 -
-
- - 		- - 84.62 %
-
-
- P:44 - F:0 - S:0 - C:4 - H:0 -
-
- -
Result-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
Reverse-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
ReverseSequence-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:6 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
Roll-7 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
Round-5 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:3 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
ScaledDotProductAttention-13 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
ScatterElementsUpdate-12 - - 66.67 %
-
-
- P:2 - F:1 - S:0 - C:0 - H:0 -
-
- - 		- - 66.67 %
-
-
- P:2 - F:1 - S:0 - C:0 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:9 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- -
ScatterElementsUpdate-3 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
ScatterNDUpdate-4 - - 66.67 %
-
-
- P:2 - F:0 - S:0 - C:1 - H:0 -
-
- - 		- - 66.67 %
-
-
- P:2 - F:0 - S:0 - C:1 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:12 - S:0 - C:0 - H:0 -
-
- - 		- - 66.67 %
-
-
- P:2 - F:0 - S:0 - C:1 - H:0 -
-
- -
ScatterUpdate-3 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:9 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
Select-1 - - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:18 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- -
Selu-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
ShapeOf-1 - - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:9 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- -
ShapeOf-3 - - 100.0 %
-
-
- P:24 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:24 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:63 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:24 - F:0 - S:0 - C:0 - H:0 -
-
- -
ShuffleChannels-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:3 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
Sigmoid-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:12 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
Sign-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
Sin-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:3 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
Sinh-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
Slice-8 - - 100.0 %
-
-
- P:15 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:15 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:30 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:15 - F:0 - S:0 - C:0 - H:0 -
-
- -
SoftPlus-4 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:3 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
SoftSign-9 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
Softmax-1 - - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 66.67 %
-
-
- P:2 - F:1 - S:0 - C:0 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:9 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- -
Softmax-8 - - 100.0 %
-
-
- P:9 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 69.33 %
-
-
- P:8 - F:1 - S:0 - C:0 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:36 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:9 - F:0 - S:0 - C:0 - H:0 -
-
- -
SpaceToBatch-2 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:3 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
SpaceToDepth-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:3 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
Split-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:18 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
Sqrt-1 - - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:15 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- -
SquaredDifference-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
Squeeze-1 - - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:45 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- -
StridedSlice-1 - - 100.0 %
-
-
- P:9 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:9 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:99 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:9 - F:0 - S:0 - C:0 - H:0 -
-
- -
Subtract-1 - - 100.0 %
-
-
- P:12 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:12 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:69 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:12 - F:0 - S:0 - C:0 - H:0 -
-
- -
Swish-4 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:3 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
Tan-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
Tanh-1 - - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:12 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- -
TensorIterator-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
Tile-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - 0.0 %
-
-
- P:0 - F:18 - S:0 - C:0 - H:0 -
-
- - 		- - ---
-
-
-
-
- -
TopK-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
TopK-11 - - 100.0 %
-
-
- P:2 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:2 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:12 - S:0 - C:0 - H:0 -
-
- - 		- - 66.67 %
-
-
- P:2 - F:0 - S:0 - C:1 - H:0 -
-
- -
TopK-3 - - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 66.67 %
-
-
- P:2 - F:0 - S:0 - C:1 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:6 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- -
Transpose-1 - - 100.0 %
-
-
- P:12 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:12 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:39 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:12 - F:0 - S:0 - C:0 - H:0 -
-
- -
Unique-10 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
Unsqueeze-1 - - 100.0 %
-
-
- P:29 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:30 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:99 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:29 - F:0 - S:0 - C:0 - H:0 -
-
- -
VariadicSplit-1 - - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 0.0 %
-
-
- P:0 - F:36 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- -
Xor-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		N/A - - ---
-
-
-
-
- -
- - - - \ No newline at end of file diff --git a/docs/sphinx_setup/_static/download/conformance_reports/opset_report_omz_static.html b/docs/sphinx_setup/_static/download/conformance_reports/opset_report_omz_static.html deleted file mode 100644 index 28fddfc3266e1d..00000000000000 --- a/docs/sphinx_setup/_static/download/conformance_reports/opset_report_omz_static.html +++ /dev/null @@ -1,16624 +0,0 @@ - - - - - - - - - - - - - - - Report - - - -
-

Operations coverage summary: Tag: Conformance_report__omz_static_opset | Version: releases/2023/3_2023.3.0-13788-d19307ba138-releases/2023/3 | Time: 25-01-2024 15:09:51

-
-
- Collected statistic info -
-
- N/ANo Tests -
-
- Passrates are based on relative weights each subgraphs! You can check absolute value in `General passrate` row! -
-
- Relative Passrate could be from 0 to 100% (Inference only)! Relative weight of operation is calculated once for current set of models, but there are more then one tests per model. -
-
- Status: - P:85Passed - F:0Failed - S:2Skipped - C:0Crashed - H:0Hanged -
-
- Plugin operation implementation status: -
Implemented
-
Not implemented
-
-
-
- -
-
-
- - -
-
- - -
-
- - -
-
- - -
-
- - -
- - -
-
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Operation ({OpName}-{FirstOpsetNumberContainsOp})CPUDGPUGPUTEMPLATE
Total: 219 101 101 101 101
Trusted op (passrate=100%):93.07 %75.25 %76.24 %90.1 %
AVG passrate (=sum_pass_rates/covered_ops_num):99.35 %94.12 %95.18 %96.17 %
General passrate (=passed_tests/all_tests):99.44 %93.36 %93.77 %98.67 %
Abs-1 - - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- -
Acos-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
Acosh-4 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
AdaptiveAvgPool-8 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
AdaptiveMaxPool-8 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
Add-1 - - 100.0 %
-
-
- P:99 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:99 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:99 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:99 - F:0 - S:0 - C:0 - H:0 -
-
- -
Asin-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
Asinh-4 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
Assign-3 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
Assign-6 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
Atan-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
Atanh-4 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
AvgPool-1 - - 100.0 %
-
-
- P:93 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:93 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:93 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:93 - F:0 - S:0 - C:0 - H:0 -
-
- -
BatchNormInference-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
BatchNormInference-5 - - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- -
BatchToSpace-2 - - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- -
BinaryConvolution-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
BitwiseAnd-13 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
BitwiseNot-13 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
BitwiseOr-13 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
BitwiseXor-13 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
Broadcast-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
Broadcast-3 - - 100.0 %
-
-
- P:63 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:63 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:63 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:63 - F:0 - S:0 - C:0 - H:0 -
-
- -
Bucketize-3 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
CTCGreedyDecoder-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
CTCGreedyDecoderSeqLen-6 - - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 50.0 %
-
-
- P:2 - F:2 - S:0 - C:0 - H:0 -
-
- -
CTCLoss-4 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
Ceiling-1 - - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- -
Clamp-1 - - 100.0 %
-
-
- P:15 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 67.19 %
-
-
- P:12 - F:3 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:15 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:15 - F:0 - S:0 - C:0 - H:0 -
-
- -
Concat-1 - - 100.0 %
-
-
- P:219 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:219 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:219 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:219 - F:0 - S:0 - C:0 - H:0 -
-
- -
Constant-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
Convert-1 - - 99.95 %
-
-
- P:96 - F:3 - S:0 - C:0 - H:0 -
-
- - 		- - 99.95 %
-
-
- P:96 - F:3 - S:0 - C:0 - H:0 -
-
- - 		- - 99.95 %
-
-
- P:96 - F:3 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:99 - F:0 - S:0 - C:0 - H:0 -
-
- -
ConvertLike-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
Convolution-1 - - 100.0 %
-
-
- P:672 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 96.45 %
-
-
- P:654 - F:27 - S:0 - C:0 - H:0 -
-
- - 		- - 99.56 %
-
-
- P:611 - F:70 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:672 - F:0 - S:0 - C:0 - H:0 -
-
- -
ConvolutionBackpropData-1 - - 100.0 %
-
-
- P:24 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 66.73 %
-
-
- P:21 - F:4 - S:0 - C:0 - H:0 -
-
- - 		- - 53.94 %
-
-
- P:17 - F:8 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:24 - F:0 - S:0 - C:0 - H:0 -
-
- -
Cos-1 - - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- -
Cosh-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
CumSum-3 - - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- -
DFT-7 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
DeformableConvolution-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
DeformableConvolution-8 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
DeformablePSROIPooling-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
DepthToSpace-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
DetectionOutput-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
DetectionOutput-8 - - 100.0 %
-
-
- P:27 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 93.02 %
-
-
- P:21 - F:6 - S:0 - C:0 - H:0 -
-
- - 		- - 94.22 %
-
-
- P:22 - F:5 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:27 - F:0 - S:0 - C:0 - H:0 -
-
- -
Divide-1 - - 100.0 %
-
-
- P:57 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 99.93 %
-
-
- P:56 - F:1 - S:0 - C:0 - H:0 -
-
- - 		- - 99.93 %
-
-
- P:56 - F:1 - S:0 - C:0 - H:0 -
-
- - 		- - 96.73 %
-
-
- P:53 - F:8 - S:0 - C:0 - H:0 -
-
- -
Einsum-7 - - 100.0 %
-
-
- P:15 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:15 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 91.92 %
-
-
- P:14 - F:1 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:15 - F:0 - S:0 - C:0 - H:0 -
-
- -
Elu-1 - - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- -
EmbeddingBagOffsetsSum-3 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
EmbeddingBagPackedSum-3 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
EmbeddingSegmentsSum-3 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
Equal-1 - - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- -
Erf-1 - - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- -
Exp-1 - - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 66.67 %
-
-
- P:4 - F:2 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- -
ExperimentalDetectronDetectionOutput-6 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
ExperimentalDetectronGenerateProposalsSingleImage-6 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
ExperimentalDetectronPriorGridGenerator-6 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
ExperimentalDetectronROIFeatureExtractor-6 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
ExperimentalDetectronTopKROIs-6 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
ExtractImagePatches-3 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
Eye-9 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
FakeConvert-13 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
FakeQuantize-1 - - 100.0 %
-
-
- P:12 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:12 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:12 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:12 - F:0 - S:0 - C:0 - H:0 -
-
- -
Floor-1 - - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- -
FloorMod-1 - - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- -
GRN-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
GRUCell-3 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
GRUSequence-5 - - 100.0 %
-
-
- P:12 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 66.67 %
-
-
- P:8 - F:0 - S:0 - C:4 - H:0 -
-
- - 		- - 66.67 %
-
-
- P:8 - F:0 - S:0 - C:4 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:12 - F:0 - S:0 - C:0 - H:0 -
-
- -
Gather-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
Gather-7 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
Gather-8 - - 100.0 %
-
-
- P:66 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 99.96 %
-
-
- P:62 - F:1 - S:0 - C:3 - H:0 -
-
- - 		- - 99.96 %
-
-
- P:62 - F:1 - S:0 - C:3 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:66 - F:0 - S:0 - C:0 - H:0 -
-
- -
GatherElements-6 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
GatherND-5 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
GatherND-8 - - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- -
GatherTree-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
Gelu-2 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
Gelu-7 - - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 50.0 %
-
-
- P:4 - F:4 - S:0 - C:0 - H:0 -
-
- -
GenerateProposals-9 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
Greater-1 - - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- -
GreaterEqual-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
GridSample-9 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
GroupConvolution-1 - - 100.0 %
-
-
- P:234 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 70.1 %
-
-
- P:161 - F:109 - S:0 - C:0 - H:0 -
-
- - 		- - 86.81 %
-
-
- P:188 - F:54 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:234 - F:0 - S:0 - C:0 - H:0 -
-
- -
GroupConvolutionBackpropData-1 - - 100.0 %
-
-
- P:12 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:12 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:12 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:12 - F:0 - S:0 - C:0 - H:0 -
-
- -
GroupNormalization-12 - - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 50.0 %
-
-
- P:4 - F:4 - S:0 - C:0 - H:0 -
-
- -
HSigmoid-5 - - 100.0 %
-
-
- P:9 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:9 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:9 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 50.0 %
-
-
- P:6 - F:6 - S:0 - C:0 - H:0 -
-
- -
HSwish-4 - - 100.0 %
-
-
- P:9 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:9 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:9 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 50.0 %
-
-
- P:6 - F:6 - S:0 - C:0 - H:0 -
-
- -
HardSigmoid-1 - - 67.1 %
-
-
- P:6 - F:10 - S:0 - C:0 - H:0 -
-
- - 		- - 67.1 %
-
-
- P:6 - F:10 - S:0 - C:0 - H:0 -
-
- - 		- - 67.1 %
-
-
- P:6 - F:10 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:12 - F:0 - S:0 - C:0 - H:0 -
-
- -
I420toBGR-8 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
I420toRGB-8 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
IDFT-7 - - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 66.67 %
-
-
- P:2 - F:1 - S:0 - C:0 - H:0 -
-
- - 		- - 66.67 %
-
-
- P:2 - F:1 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- -
IRDFT-9 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
If-8 - - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- -
Interpolate-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
Interpolate-11 - - 99.95 %
-
-
- P:41 - F:0 - S:0 - C:1 - H:0 -
-
- - 		- - 99.95 %
-
-
- P:41 - F:0 - S:0 - C:1 - H:0 -
-
- - 		- - 99.95 %
-
-
- P:41 - F:0 - S:0 - C:1 - H:0 -
-
- - 		- - 99.95 %
-
-
- P:41 - F:0 - S:0 - C:1 - H:0 -
-
- -
Interpolate-4 - - 100.0 %
-
-
- P:18 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:18 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:18 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:18 - F:0 - S:0 - C:0 - H:0 -
-
- -
IsFinite-10 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
IsInf-10 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
IsNaN-10 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
LRN-1 - - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- -
LSTMCell-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
LSTMCell-4 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
LSTMSequence-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
LSTMSequence-5 - - 100.0 %
-
-
- P:12 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 66.67 %
-
-
- P:8 - F:0 - S:0 - C:4 - H:0 -
-
- - 		- - 66.67 %
-
-
- P:8 - F:0 - S:0 - C:4 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:12 - F:0 - S:0 - C:0 - H:0 -
-
- -
Less-1 - - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- -
LessEqual-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
Log-1 - - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- -
LogSoftmax-5 - - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 50.0 %
-
-
- P:2 - F:2 - S:0 - C:0 - H:0 -
-
- -
LogicalAnd-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
LogicalNot-1 - - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- -
LogicalOr-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
LogicalXor-2 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
Loop-5 - - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 39.97 %
-
-
- P:3 - F:5 - S:0 - C:0 - H:0 -
-
- - 		- - 26.65 %
-
-
- P:2 - F:6 - S:0 - C:0 - H:0 -
-
- - 		- - 66.67 %
-
-
- P:4 - F:0 - S:0 - C:2 - H:0 -
-
- -
MVN-2 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
MVN-6 - - 100.0 %
-
-
- P:18 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:18 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:18 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:18 - F:0 - S:0 - C:0 - H:0 -
-
- -
MatMul-1 - - 100.0 %
-
-
- P:60 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:60 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 94.55 %
-
-
- P:58 - F:2 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:60 - F:0 - S:0 - C:0 - H:0 -
-
- -
MatrixNms-8 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
MaxPool-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
MaxPool-8 - - 100.0 %
-
-
- P:99 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 99.63 %
-
-
- P:96 - F:3 - S:0 - C:0 - H:0 -
-
- - 		- - 99.63 %
-
-
- P:96 - F:3 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:99 - F:0 - S:0 - C:0 - H:0 -
-
- -
Maximum-1 - - 100.0 %
-
-
- P:21 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:21 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:21 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:21 - F:0 - S:0 - C:0 - H:0 -
-
- -
Minimum-1 - - 100.0 %
-
-
- P:12 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:12 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:12 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 50.0 %
-
-
- P:8 - F:8 - S:0 - C:0 - H:0 -
-
- -
Mish-4 - - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- -
Mod-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
MulticlassNms-8 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
MulticlassNms-9 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
Multinomial-13 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
Multiply-1 - - 100.0 %
-
-
- P:102 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:102 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:102 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:102 - F:0 - S:0 - C:0 - H:0 -
-
- -
NMSRotated-13 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
NV12toBGR-8 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
NV12toRGB-8 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
Negative-1 - - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- -
NonMaxSuppression-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
NonMaxSuppression-3 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
NonMaxSuppression-4 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
NonMaxSuppression-5 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
NonMaxSuppression-9 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
NonZero-3 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
NormalizeL2-1 - - 100.0 %
-
-
- P:9 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:9 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:9 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:9 - F:0 - S:0 - C:0 - H:0 -
-
- -
NotEqual-1 - - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- -
OneHot-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
PRelu-1 - - 100.0 %
-
-
- P:30 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 80.09 %
-
-
- P:21 - F:13 - S:0 - C:0 - H:0 -
-
- - 		- - 80.09 %
-
-
- P:21 - F:13 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:30 - F:0 - S:0 - C:0 - H:0 -
-
- -
PSROIPooling-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
Pad-1 - - 99.99 %
-
-
- P:8 - F:1 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:9 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:9 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:9 - F:0 - S:0 - C:0 - H:0 -
-
- -
Pad-12 - - 99.81 %
-
-
- P:17 - F:1 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:18 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:18 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:18 - F:0 - S:0 - C:0 - H:0 -
-
- -
Parameter-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
Power-1 - - 100.0 %
-
-
- P:36 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:36 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:36 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:36 - F:0 - S:0 - C:0 - H:0 -
-
- -
PriorBox-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
PriorBox-8 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
PriorBoxClustered-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
Proposal-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
Proposal-4 - - 100.0 %
-
-
- P:9 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 66.67 %
-
-
- P:6 - F:3 - S:0 - C:0 - H:0 -
-
- - 		- - 66.67 %
-
-
- P:6 - F:3 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:9 - F:0 - S:0 - C:0 - H:0 -
-
- -
RDFT-9 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
RNNCell-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
RNNSequence-5 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
ROIAlign-3 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
ROIAlign-9 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
ROIPooling-2 - - 100.0 %
-
-
- P:9 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 66.67 %
-
-
- P:6 - F:3 - S:0 - C:0 - H:0 -
-
- - 		- - 66.67 %
-
-
- P:6 - F:3 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:9 - F:0 - S:0 - C:0 - H:0 -
-
- -
RandomUniform-8 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
Range-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
Range-4 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
ReadValue-3 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
ReadValue-6 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
ReduceL1-4 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
ReduceL2-4 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
ReduceLogicalAnd-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
ReduceLogicalOr-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
ReduceMax-1 - - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- -
ReduceMean-1 - - 100.0 %
-
-
- P:24 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:24 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:24 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:24 - F:0 - S:0 - C:0 - H:0 -
-
- -
ReduceMin-1 - - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- -
ReduceProd-1 - - 100.0 %
-
-
- P:9 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:9 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:9 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:9 - F:0 - S:0 - C:0 - H:0 -
-
- -
ReduceSum-1 - - 100.0 %
-
-
- P:24 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:24 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:24 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:24 - F:0 - S:0 - C:0 - H:0 -
-
- -
RegionYolo-1 - - 100.0 %
-
-
- P:39 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:39 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:39 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:39 - F:0 - S:0 - C:0 - H:0 -
-
- -
Relu-1 - - 100.0 %
-
-
- P:12 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 66.69 %
-
-
- P:9 - F:3 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:12 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:12 - F:0 - S:0 - C:0 - H:0 -
-
- -
ReorgYolo-2 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
Reshape-1 - - 100.0 %
-
-
- P:168 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:168 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:168 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:168 - F:0 - S:0 - C:0 - H:0 -
-
- -
Result-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
Reverse-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
ReverseSequence-1 - - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- -
Roll-7 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
Round-5 - - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- -
ScaledDotProductAttention-13 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
ScatterElementsUpdate-12 - - 84.86 %
-
-
- P:5 - F:1 - S:0 - C:0 - H:0 -
-
- - 		- - 66.67 %
-
-
- P:4 - F:2 - S:0 - C:0 - H:0 -
-
- - 		- - 66.67 %
-
-
- P:4 - F:2 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- -
ScatterElementsUpdate-3 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
ScatterNDUpdate-4 - - 100.0 %
-
-
- P:9 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:9 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:9 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:9 - F:0 - S:0 - C:0 - H:0 -
-
- -
ScatterUpdate-3 - - 100.0 %
-
-
- P:9 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 79.42 %
-
-
- P:8 - F:1 - S:0 - C:0 - H:0 -
-
- - 		- - 79.42 %
-
-
- P:8 - F:1 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:9 - F:0 - S:0 - C:0 - H:0 -
-
- -
Select-1 - - 100.0 %
-
-
- P:12 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:12 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:12 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:12 - F:0 - S:0 - C:0 - H:0 -
-
- -
Selu-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
ShapeOf-1 - - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- -
ShapeOf-3 - - 100.0 %
-
-
- P:39 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:39 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:39 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:39 - F:0 - S:0 - C:0 - H:0 -
-
- -
ShuffleChannels-1 - - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- -
Sigmoid-1 - - 100.0 %
-
-
- P:12 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:12 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:12 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:12 - F:0 - S:0 - C:0 - H:0 -
-
- -
Sign-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
Sin-1 - - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- -
Sinh-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
Slice-8 - - 100.0 %
-
-
- P:15 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:15 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:15 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:15 - F:0 - S:0 - C:0 - H:0 -
-
- -
SoftPlus-4 - - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- -
SoftSign-9 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
Softmax-1 - - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:6 - F:0 - S:0 - C:0 - H:0 -
-
- -
Softmax-8 - - 100.0 %
-
-
- P:27 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 90.0 %
-
-
- P:26 - F:1 - S:0 - C:0 - H:0 -
-
- - 		- - 90.0 %
-
-
- P:26 - F:1 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:27 - F:0 - S:0 - C:0 - H:0 -
-
- -
SpaceToBatch-2 - - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- -
SpaceToDepth-1 - - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- -
Split-1 - - 100.0 %
-
-
- P:18 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:18 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:18 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:18 - F:0 - S:0 - C:0 - H:0 -
-
- -
Sqrt-1 - - 100.0 %
-
-
- P:12 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:12 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:12 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:12 - F:0 - S:0 - C:0 - H:0 -
-
- -
SquaredDifference-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
Squeeze-1 - - 100.0 %
-
-
- P:39 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:39 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:39 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:39 - F:0 - S:0 - C:0 - H:0 -
-
- -
StridedSlice-1 - - 100.0 %
-
-
- P:90 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:90 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:90 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:90 - F:0 - S:0 - C:0 - H:0 -
-
- -
Subtract-1 - - 100.0 %
-
-
- P:57 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:57 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:57 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:57 - F:0 - S:0 - C:0 - H:0 -
-
- -
Swish-4 - - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- -
Tan-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
Tanh-1 - - 100.0 %
-
-
- P:9 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:9 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:9 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:9 - F:0 - S:0 - C:0 - H:0 -
-
- -
TensorIterator-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
Tile-1 - - 100.0 %
-
-
- P:18 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:18 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:18 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:18 - F:0 - S:0 - C:0 - H:0 -
-
- -
TopK-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
TopK-11 - - 83.01 %
-
-
- P:8 - F:1 - S:0 - C:0 - H:0 -
-
- - 		- - 56.43 %
-
-
- P:7 - F:3 - S:0 - C:0 - H:0 -
-
- - 		- - 83.01 %
-
-
- P:8 - F:1 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:9 - F:0 - S:0 - C:0 - H:0 -
-
- -
TopK-3 - - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 66.67 %
-
-
- P:2 - F:0 - S:0 - C:1 - H:0 -
-
- - 		- - 66.67 %
-
-
- P:2 - F:0 - S:0 - C:1 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:3 - F:0 - S:0 - C:0 - H:0 -
-
- -
Transpose-1 - - 100.0 %
-
-
- P:27 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:27 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:27 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:27 - F:0 - S:0 - C:0 - H:0 -
-
- -
Unique-10 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
Unsqueeze-1 - - 100.0 %
-
-
- P:69 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:69 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:69 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:69 - F:0 - S:0 - C:0 - H:0 -
-
- -
VariadicSplit-1 - - 100.0 %
-
-
- P:33 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:33 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:33 - F:0 - S:0 - C:0 - H:0 -
-
- - 		- - 100.0 %
-
-
- P:33 - F:0 - S:0 - C:0 - H:0 -
-
- -
Xor-1 - - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- - 		- - ---
-
-
-
-
- -
- - - - \ No newline at end of file From d5c468a91e488cb56042daef5e9ebc4b0b3b92b3 Mon Sep 17 00:00:00 2001 From: Karol Blaszczak Date: Mon, 26 Aug 2024 10:02:30 +0200 Subject: [PATCH 2/5] [DOCS] benchmark update 24.3-port (#26126) (#26223) port: https://github.com/openvinotoolkit/openvino/pull/26126 Co-authored-by: Michael Frank Hansen --- .../about-openvino/performance-benchmarks.rst | 3 +- .../OV-2024.3-Performance-Data.xlsx | Bin 302284 -> 305774 bytes .../OV-2024.3-platform_list.pdf | Bin 242429 -> 239931 bytes .../OV-2024.3-system-info-detailed.xlsx | Bin 78255 -> 78345 bytes .../benchmarks_files/OVMS-benchmark-data.csv | 156 +++++++++--------- 5 files changed, 79 insertions(+), 80 deletions(-) diff --git a/docs/articles_en/about-openvino/performance-benchmarks.rst b/docs/articles_en/about-openvino/performance-benchmarks.rst index 96ddcff022e237..7f838d62b18f1c 100644 --- a/docs/articles_en/about-openvino/performance-benchmarks.rst +++ b/docs/articles_en/about-openvino/performance-benchmarks.rst @@ -206,12 +206,11 @@ You can also test performance for your system yourself, following the guide on

Disclaimers

- * Intel® Distribution of OpenVINO™ toolkit performance results are based on release 2024.3, as of July 31, 2024. * OpenVINO Model Server performance results are based on release - 2024.2, as of June 28, 2024. + 2024.3, as of Aug. 19, 2024. The results may not reflect all publicly available updates. Intel technologies' features and benefits depend on system configuration and may require enabled hardware, software, or service diff --git a/docs/sphinx_setup/_static/benchmarks_files/OV-2024.3-Performance-Data.xlsx b/docs/sphinx_setup/_static/benchmarks_files/OV-2024.3-Performance-Data.xlsx index e89b5991029ad6317a8d401d3bf1e03e171bc9bb..05de7365749228b3ec06d971cf0adca40da9f32b 100644 GIT binary patch delta 111680 zcmYJab95(7^9LH+w(X7WjcwbulW%O>_QrOyv2AZ`n>Wwg>#@i{0QT!lXrb4Xmjd~lat0_Z zHCa;LbGGxvc7GPHAlo7W!VSb*-XE`z!MGI{QCB^qmh)ilCm8Q$acFqY0_Du}v(!gtz(H0IA(+@5lK0A}nN3_xdc(gJt8|qrV z#?!|zjfSQq087Fh_GVJGZLao@*-O0ockKpi9zKIky4;05 zD9at88NuD7i-pWv`B`c)n+di?W{S&4LDp}y!ADsu0PSY3t2o*)2H0P12kT!)v@32; z3iaM4X&h4Y;`WfIG_tgF7DLjn$JH5Md%n?P-~t%uT?2ameYgz1Bd%*#3r&4_OJKU2vJT%{o*?AtSr*3T9#QvM zHa}M9Z4_w#NDkLp<9)BXdK#(;__@h*z)qeU%G;Fv$QZwy4NSBc2y2`b6Uo6zdw z8!=Y7V>Ew3&aR?>~7$pzEXz~UE7^SJoHP#?+s8bvP1voUo+!X2? z%Bmo(k-0PoY^oxW=Y^Q>ps~Fm-3)=1Rwk7>IY-*~jSDH8&Xh_#ZMeyWh*NW1B(uXD 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CPU-only,,484.765,486.962,181.829,179.94 -bert-base-cased,OV-2024.2,xeon,Intel® Xeon® Gold 6238M CPU-only,,430.151,434.276,157.835,158.277 -bert-base-cased,OV-2024.2,core,Intel® Core™ i9-11900K CPU-only,,101.044,102.838,35.727,36.57 -bert-base-cased,OV-2024.2,core,Intel® Core™ i7-11700K CPU-only,,100.741,103.322,35.046,36.607 -bert-base-cased,OV-2024.2,core,Intel® Core™ i3-10100 CPU-only,,26.124,26.329,17.155,17.387 -end_rec,,,,,,,, -begin_rec,,,,,,,, -bert-large-uncased,OV-2024.2,xeon,Intel® Xeon® 8260M CPU-only,,41.302,41.994,14.937,14.482 -bert-large-uncased,OV-2024.2,xeon,Intel® Xeon® Gold 6238M CPU-only,,36.595,37.1,13.114,13.03 -bert-large-uncased,OV-2024.2,core,Intel® Core™ i9-11900K CPU-only,,10.076,10.145,3.267,3.246 -bert-large-uncased,OV-2024.2,core,Intel® Core™ i7-11700K CPU-only,,10.161,10.203,3.287,3.26 -bert-large-uncased,OV-2024.2,core,Intel® Core™ i3-10100 CPU-only,,2.422,2.424,1.447,1.427 -end_rec,,,,,,,, -begin_rec,,,,,,,, -Efficientdet-D0,OV-2024.2,xeon,Intel® Xeon® 8260M CPU-only,,433.166,479.055,285.65,287.547 -Efficientdet-D0,OV-2024.2,xeon,Intel® Xeon® Gold 6238M CPU-only,,367.395,407,251.401,257.516 -Efficientdet-D0,OV-2024.2,core,Intel® Core™ i9-11900K CPU-only,,132.153,149.424,57.682,61.811 -Efficientdet-D0,OV-2024.2,core,Intel® Core™ i7-11700K CPU-only,,124.984,142.514,50.265,53.089 -Efficientdet-D0,OV-2024.2,core,Intel® Core™ i3-10100 CPU-only,,47.048,50.328,30.026,31.473 -end_rec,,,,,,,, -begin_rec,,,,,,,, -mask_rcnn_resnet50_atrous_coco,OV-2024.2,xeon,Intel® Xeon® 8260M CPU-only,,6.323,6.488,1.978,1.868 -mask_rcnn_resnet50_atrous_coco,OV-2024.2,xeon,Intel® Xeon® Gold 6238M CPU-only,,5.637,5.742,1.715,1.633 -mask_rcnn_resnet50_atrous_coco,OV-2024.2,core,Intel® Core™ i9-11900K CPU-only,,1.302,1.276,0.396,0.373 -mask_rcnn_resnet50_atrous_coco,OV-2024.2,core,Intel® Core™ i7-11700K CPU-only,,1.307,1.28,0.374,0.36 -mask_rcnn_resnet50_atrous_coco,OV-2024.2,core,Intel® Core™ i3-10100 CPU-only,,0.381,0.35,0.181,0.15 -end_rec,,,,,,,, -begin_rec,,,,,,,, -Mobilenet-V2 ,OV-2024.2,xeon,Intel® Xeon® 8260M CPU-only,,7578.115,12346.3,3354.203,3938.523 -Mobilenet-V2 ,OV-2024.2,xeon,Intel® Xeon® Gold 6238M CPU-only,,7513.034,10367.947,2915.906,3349.306 -Mobilenet-V2 ,OV-2024.2,core,Intel® Core™ i9-11900K CPU-only,,2152.015,2740.691,745.81,882.839 -Mobilenet-V2 ,OV-2024.2,core,Intel® Core™ i7-11700K CPU-only,,2093.311,2822.613,667.391,795.616 -Mobilenet-V2 ,OV-2024.2,core,Intel® Core™ i3-10100 CPU-only,,615.392,719.715,381.686,454.574 -end_rec,,,,,,,, -begin_rec,,,,,,,, -Resnet-50,OV-2024.2,xeon,Intel® Xeon® 8260M CPU-only,,2354.173,2482.832,639.577,645.443 -Resnet-50,OV-2024.2,xeon,Intel® Xeon® Gold 6238M CPU-only,,2070.726,2177.751,571.252,575.778 -Resnet-50,OV-2024.2,core,Intel® Core™ i9-11900K CPU-only,,440.402,458.622,114.169,116.577 -Resnet-50,OV-2024.2,core,Intel® Core™ i7-11700K CPU-only,,448.464,470.586,111.785,114.628 -Resnet-50,OV-2024.2,core,Intel® Core™ i3-10100 CPU-only,,114.267,118.502,57.29,58.233 -end_rec,,,,,,,, -begin_rec,,,,,,,, -SSD-Resnet34-1200 ,OV-2024.2,xeon,Intel® Xeon® 8260M CPU-only,,44.587,47.293,12.111,12.248 -SSD-Resnet34-1200 ,OV-2024.2,xeon,Intel® Xeon® Gold 6238M CPU-only,,38.784,40.602,10.521,10.613 -SSD-Resnet34-1200 ,OV-2024.2,core,Intel® Core™ i9-11900K CPU-only,,7.736,7.821,2.034,2.011 -SSD-Resnet34-1200 ,OV-2024.2,core,Intel® Core™ i7-11700K CPU-only,,7.953,8.033,2.083,2.058 -SSD-Resnet34-1200 ,OV-2024.2,core,Intel® Core™ i3-10100 CPU-only,,1.951,1.936,1.04,1.014 -end_rec,,,,,,,, -begin_rec,,,,,,,, -SSD_Mobilenet_V1_Coco,OV-2024.2,xeon,Intel® Xeon® 8260M CPU-only,,4753.674,4933.241,1370.423,1379.026 -SSD_Mobilenet_V1_Coco,OV-2024.2,xeon,Intel® Xeon® Gold 6238M CPU-only,,4165.318,4276.949,1197.151,1222.112 -SSD_Mobilenet_V1_Coco,OV-2024.2,core,Intel® Core™ i9-11900K CPU-only,,920.957,1001.56,270.597,281.293 -SSD_Mobilenet_V1_Coco,OV-2024.2,core,Intel® Core™ i7-11700K CPU-only,,941.323,1030.464,256.649,266.715 -SSD_Mobilenet_V1_Coco,OV-2024.2,core,Intel® Core™ i3-10100 CPU-only,,256.291,266.245,129.84,135.453 -end_rec,,,,,,,, -begin_rec,,,,,,,, -Unet-Camvid--0001 ,OV-2024.2,xeon,Intel® Xeon® 8260M CPU-only,,73.871,78.016,18.23,18.374 -Unet-Camvid--0001 ,OV-2024.2,xeon,Intel® Xeon® Gold 6238M CPU-only,,64.573,67.713,15.815,16.023 -Unet-Camvid--0001 ,OV-2024.2,core,Intel® Core™ i9-11900K CPU-only,,12.572,12.669,3.28,3.254 -Unet-Camvid--0001 ,OV-2024.2,core,Intel® Core™ i7-11700K CPU-only,,12.779,12.894,3.315,3.299 -Unet-Camvid--0001 ,OV-2024.2,core,Intel® Core™ i3-10100 CPU-only,,2.99,2.971,1.549,1.542 -end_rec,,,,,,,, -begin_rec,,,,,,,, -Yolo_V3_Tiny,OV-2024.2,xeon,Intel® Xeon® 8260M CPU-only,,1863.229,2344.128,775.001,786.09 -Yolo_V3_Tiny,OV-2024.2,xeon,Intel® Xeon® Gold 6238M CPU-only,,1669.35,2066.437,675.625,703.203 -Yolo_V3_Tiny,OV-2024.2,core,Intel® Core™ i9-11900K CPU-only,,430.441,505.532,146.284,151.09 -Yolo_V3_Tiny,OV-2024.2,core,Intel® Core™ i7-11700K CPU-only,,419.347,513.112,142.009,148.117 -Yolo_V3_Tiny,OV-2024.2,core,Intel® Core™ i3-10100 CPU-only,,117.889,133.312,63.598,69.377 -end_rec,,,,,,,, -begin_rec,,,,,,,, -Yolo_V8n,OV-2024.2,xeon,Intel® Xeon® 8260M CPU-only,,705.714,845.484,316.319,388.763 -Yolo_V8n,OV-2024.2,xeon,Intel® Xeon® Gold 6238M CPU-only,,641.815,746.965,278.824,338.806 -Yolo_V8n,OV-2024.2,core,Intel® Core™ i9-11900K CPU-only,,154.54,205.294,67.744,75.634 -Yolo_V8n,OV-2024.2,core,Intel® Core™ i7-11700K CPU-only,,149.289,199.997,65.243,72.677 -Yolo_V8n,OV-2024.2,core,Intel® Core™ i3-10100 CPU-only,,55.999,68.155,34.454,38.544 -end_rec,,,,,,,, \ No newline at end of file +Network model,Release,IE-Type,Platform name,Throughput-OVMS-INT8,Throughput-OV-INT8,Throughput-OVMS-FP32,Throughput-OV-FP32,UOM_T +begin_rec,,,,,,,, +bert-base-cased,OV-2024.3,xeon,Intel® Xeon® 8260M CPU-only,479.649,482.878,180.7,179.541,FPS +bert-base-cased,OV-2024.3,xeon,Intel® Xeon® Gold 6238M CPU-only,428.173,430.397,156.73,159.276,FPS +bert-base-cased,OV-2024.3,core,Intel® Core™ i9-11900K CPU-only,100.783,101.983,35.711,36.35,FPS +bert-base-cased,OV-2024.3,core,Intel® Core™ i7-11700K CPU-only,98.441,102.62,34.303,36.096,FPS +bert-base-cased,OV-2024.3,core,Intel® Core™ i3-10100 CPU-only,26.185,26.436,17.108,17.395,FPS +end_rec,,,,,,,, +begin_rec,,,,,,,, +bert-large-uncased,OV-2024.3,xeon,Intel® Xeon® 8260M CPU-only,41.872,42.401,14.949,14.473,FPS +bert-large-uncased,OV-2024.3,xeon,Intel® Xeon® Gold 6238M CPU-only,37.05,37.864,13.075,13.031,FPS +bert-large-uncased,OV-2024.3,core,Intel® Core™ i9-11900K CPU-only,10.047,10.111,3.259,3.237,FPS +bert-large-uncased,OV-2024.3,core,Intel® Core™ i7-11700K CPU-only,9.961,10.167,3.236,3.224,FPS +bert-large-uncased,OV-2024.3,core,Intel® Core™ i3-10100 CPU-only,2.43,2.427,1.447,1.428,FPS +end_rec,,,,,,,, +begin_rec,,,,,,,, +Efficientdet-D0,OV-2024.3,xeon,Intel® Xeon® 8260M CPU-only,439.435,485.287,274.772,272.856,FPS +Efficientdet-D0,OV-2024.3,xeon,Intel® Xeon® Gold 6238M CPU-only,376.1,415.275,253.829,259.188,FPS +Efficientdet-D0,OV-2024.3,core,Intel® Core™ i9-11900K CPU-only,131.735,148.558,57.036,59.907,FPS +Efficientdet-D0,OV-2024.3,core,Intel® Core™ i7-11700K CPU-only,119.798,140.129,,,FPS +Efficientdet-D0,OV-2024.3,core,Intel® Core™ i3-10100 CPU-only,47.382,50.573,30.226,31.492,FPS +end_rec,,,,,,,, +begin_rec,,,,,,,, +mask_rcnn_resnet50_atrous_coco,OV-2024.3,xeon,Intel® Xeon® 8260M CPU-only,6.306,6.364,1.96,1.868,FPS +mask_rcnn_resnet50_atrous_coco,OV-2024.3,xeon,Intel® Xeon® Gold 6238M CPU-only,5.652,5.771,1.714,1.639,FPS +mask_rcnn_resnet50_atrous_coco,OV-2024.3,core,Intel® Core™ i9-11900K CPU-only,1.309,1.267,0.396,0.371,FPS +mask_rcnn_resnet50_atrous_coco,OV-2024.3,core,Intel® Core™ i7-11700K CPU-only,1.293,1.271,0.355,0.346,FPS +mask_rcnn_resnet50_atrous_coco,OV-2024.3,core,Intel® Core™ i3-10100 CPU-only,0.38,0.352,0.182,0.151,FPS +end_rec,,,,,,,, +begin_rec,,,,,,,, +Mobilenet-V2 ,OV-2024.3,xeon,Intel® Xeon® 8260M CPU-only,7563.199,12406.597,3336.015,3972.673,FPS +Mobilenet-V2 ,OV-2024.3,xeon,Intel® Xeon® Gold 6238M CPU-only,7475.62,10373.146,2934.976,3381.725,FPS +Mobilenet-V2 ,OV-2024.3,core,Intel® Core™ i9-11900K CPU-only,2158.818,2742.363,740.988,874.037,FPS +Mobilenet-V2 ,OV-2024.3,core,Intel® Core™ i7-11700K CPU-only,2042.633,2809.471,631.59,759.984,FPS +Mobilenet-V2 ,OV-2024.3,core,Intel® Core™ i3-10100 CPU-only,614.174,718.416,381.882,455.793,FPS +end_rec,,,,,,,, +begin_rec,,,,,,,, +Resnet-50,OV-2024.3,xeon,Intel® Xeon® 8260M CPU-only,2356.238,2483.3,628.616,635.411,FPS +Resnet-50,OV-2024.3,xeon,Intel® Xeon® Gold 6238M CPU-only,2071.836,2202.317,568.945,575.057,FPS +Resnet-50,OV-2024.3,core,Intel® Core™ i9-11900K CPU-only,440.533,458.665,113.442,116.116,FPS +Resnet-50,OV-2024.3,core,Intel® Core™ i7-11700K CPU-only,441.7,469.848,107.395,113.605,FPS +Resnet-50,OV-2024.3,core,Intel® Core™ i3-10100 CPU-only,114.045,118.024,57.165,58.366,FPS +end_rec,,,,,,,, +begin_rec,,,,,,,, +SSD-Resnet34-1200 ,OV-2024.3,xeon,Intel® Xeon® 8260M CPU-only,44.499,47.251,12.074,12.167,FPS +SSD-Resnet34-1200 ,OV-2024.3,xeon,Intel® Xeon® Gold 6238M CPU-only,38.714,40.662,10.504,10.653,FPS +SSD-Resnet34-1200 ,OV-2024.3,core,Intel® Core™ i9-11900K CPU-only,7.756,7.818,2.029,2.005,FPS +SSD-Resnet34-1200 ,OV-2024.3,core,Intel® Core™ i7-11700K CPU-only,7.929,8.032,2.072,2.054,FPS +SSD-Resnet34-1200 ,OV-2024.3,core,Intel® Core™ i3-10100 CPU-only,1.947,1.937,1.037,1.008,FPS +end_rec,,,,,,,, +begin_rec,,,,,,,, +SSD_Mobilenet_V1_Coco,OV-2024.3,xeon,Intel® Xeon® 8260M CPU-only,4732.691,4875.291,1362.268,1375.237,FPS +SSD_Mobilenet_V1_Coco,OV-2024.3,xeon,Intel® Xeon® Gold 6238M CPU-only,4168.575,4279.825,1199.883,1226.189,FPS +SSD_Mobilenet_V1_Coco,OV-2024.3,core,Intel® Core™ i9-11900K CPU-only,921.041,1001.672,268.066,280.987,FPS +SSD_Mobilenet_V1_Coco,OV-2024.3,core,Intel® Core™ i7-11700K CPU-only,915.4,1028.233,244.534,260.822,FPS +SSD_Mobilenet_V1_Coco,OV-2024.3,core,Intel® Core™ i3-10100 CPU-only,256.018,266.401,129.917,135.312,FPS +end_rec,,,,,,,, +begin_rec,,,,,,,, +Unet-Camvid--0001 ,OV-2024.3,xeon,Intel® Xeon® 8260M CPU-only,73.429,77.693,18.104,17.938,FPS +Unet-Camvid--0001 ,OV-2024.3,xeon,Intel® Xeon® Gold 6238M CPU-only,64.29,67.517,15.777,15.927,FPS +Unet-Camvid--0001 ,OV-2024.3,core,Intel® Core™ i9-11900K CPU-only,12.574,12.628,3.267,3.253,FPS +Unet-Camvid--0001 ,OV-2024.3,core,Intel® Core™ i7-11700K CPU-only,12.718,12.881,3.272,3.297,FPS +Unet-Camvid--0001 ,OV-2024.3,core,Intel® Core™ i3-10100 CPU-only,2.995,2.976,1.555,1.53,FPS +end_rec,,,,,,,, +begin_rec,,,,,,,, +Yolo_V3_Tiny,OV-2024.3,xeon,Intel® Xeon® 8260M CPU-only,1842.129,2317.052,755.451,777.681,FPS +Yolo_V3_Tiny,OV-2024.3,xeon,Intel® Xeon® Gold 6238M CPU-only,1667.812,2056.27,675.447,704.412,FPS +Yolo_V3_Tiny,OV-2024.3,core,Intel® Core™ i9-11900K CPU-only,431.387,504.093,145.92,151.499,FPS +Yolo_V3_Tiny,OV-2024.3,core,Intel® Core™ i7-11700K CPU-only,409.268,516.794,139.903,147.235,FPS +Yolo_V3_Tiny,OV-2024.3,core,Intel® Core™ i3-10100 CPU-only,117.276,133.578,65.341,69.29,FPS +end_rec,,,,,,,, +begin_rec,,,,,,,, +Yolo_V8n,OV-2024.3,xeon,Intel® Xeon® 8260M CPU-only,,,314.652,386.299,FPS +Yolo_V8n,OV-2024.34,xeon,Intel® Xeon® Gold 6238M CPU-only,,,282.302,340.845,FPS +Yolo_V8n,OV-2024.65,core,Intel® Core™ i9-11900K CPU-only,153.817,204.691,67.421,74.996,FPS +Yolo_V8n,OV-2024.96,core,Intel® Core™ i7-11700K CPU-only,143.19,197.409,62.948,70.913,FPS +Yolo_V8n,OV-2024.127,core,Intel® Core™ i3-10100 CPU-only,56.244,67.968,34.396,38.576,FPS +end_rec,,,,,,,, From 513058c469e435ef4a787f08044ce18bd01e8606 Mon Sep 17 00:00:00 2001 From: Maciej Smyk Date: Mon, 26 Aug 2024 11:55:15 +0200 Subject: [PATCH 3/5] [DOCS] Changes in Security article in docs for 24.3 (#26227) Port from https://github.com/openvinotoolkit/openvino/pull/26206 * Moved content from the Encrypted Models article to the main OpenVINO Security article. * Changed name of the "Intermediate Representation Suitable for INT8 Inference" article to "Low Precision IR (INT8 Inference)". --- ...rmediate-representation-int8-inference.rst | 4 +- .../documentation/openvino-security.rst | 79 ++++++++++++++++--- .../openvino-encrypted-models.rst | 56 ------------- ...tegrate-openvino-with-your-application.rst | 2 +- 4 files changed, 69 insertions(+), 72 deletions(-) delete mode 100644 docs/articles_en/documentation/openvino-security/openvino-encrypted-models.rst diff --git a/docs/articles_en/documentation/openvino-ir-format/intermediate-representation-int8-inference.rst b/docs/articles_en/documentation/openvino-ir-format/intermediate-representation-int8-inference.rst index 4c9c3ab6f05c76..ac35537fa54c1a 100644 --- a/docs/articles_en/documentation/openvino-ir-format/intermediate-representation-int8-inference.rst +++ b/docs/articles_en/documentation/openvino-ir-format/intermediate-representation-int8-inference.rst @@ -1,6 +1,4 @@ -.. {#openvino_docs_MO_DG_prepare_model_convert_model_IR_suitable_for_INT8_inference} - -Intermediate Representation Suitable for INT8 Inference +Low Precision IR (INT8 Inference) ======================================================= diff --git a/docs/articles_en/documentation/openvino-security.rst b/docs/articles_en/documentation/openvino-security.rst index da8a4427c2162c..2deebbc320f285 100644 --- a/docs/articles_en/documentation/openvino-security.rst +++ b/docs/articles_en/documentation/openvino-security.rst @@ -1,21 +1,76 @@ -.. {#openvino_docs_security_guide_introduction} - OpenVINO Security -================= +=================================================== +Deploying deep learning models for OpenVINO may raise security and privacy issues. +Trained models are often valuable intellectual property and you may choose to protect them +with encryption or other security tools. -.. toctree:: - :maxdepth: 1 - :hidden: +Actual security and privacy requirements depend on your unique deployment scenario. +This section provides general guidance on using OpenVINO tools and libraries securely. +The main security measure for OpenVINO is its +:doc:`Security Add-on `. You can find its description +in the Ecosystem section. - openvino-security/openvino-encrypted-models +.. _encrypted-models: +Using Encrypted Models with OpenVINO +############################################## -Deploying deep learning models for OpenVINO may raise security and privacy issues. -Trained models are often valuable intellectual property and you may choose to protect them with encryption or other security tools. +Deploying deep-learning capabilities to edge devices can present security challenges like ensuring +inference integrity, or providing copyright protection of your deep-learning models. -Actual security and privacy requirements depend on your unique deployment scenario. -This section provides general guidance on using OpenVINO tools and libraries securely. -The main security measure for OpenVINO is its :doc:`Security Add-on `. You can find its description in the Ecosystem section. +One possible solution is to use cryptography to protect models as they are deployed and stored +on edge devices. Model encryption, decryption and authentication are not provided by OpenVINO +but can be implemented with third-party tools (i.e., OpenSSL). While implementing encryption, +ensure that the latest versions of tools are used and follow cryptography best practices. + +This guide presents how to use OpenVINO securely with protected models. + +Secure Model Deployment ++++++++++++++++++++++++++++++++++++ + +After a model is optimized by model conversion API, it's deployed to target devices in the +OpenVINO Intermediate Representation (OpenVINO IR) format. An optimized model is stored on edge +device and is executed by the OpenVINO Runtime. TensorFlow, TensorFlow Lite, ONNX and PaddlePaddle +models can be read natively by OpenVINO Runtime as well. + +Encrypting and optimizing model before deploying it to the edge device can be used to protect +deep-learning models. The edge device should keep the stored model protected all the time +and have the model decrypted **in runtime only** for use by the OpenVINO Runtime. + +.. image:: ../assets/images/deploy_encrypted_model.svg + +Loading Encrypted Models ++++++++++++++++++++++++++++++++++++ + +The OpenVINO Runtime requires model decryption before loading. Allocate a temporary memory block +for model decryption and use the ``ov::Core::read_model`` method to load the model from a memory +buffer. For more information, see the ``ov::Core`` Class Reference Documentation. + +.. doxygensnippet:: docs/articles_en/assets/snippets/protecting_model_guide.cpp + :language: cpp + :fragment: part0 + +Hardware-based protection such as Intel Software Guard Extensions (Intel SGX) can be used to protect +decryption operation secrets and bind them to a device. For more information, see +the `Intel Software Guard Extensions `__. + +Use the ``ov::Core::read_model`` to set model representations and weights respectively. + +Currently there is no way to read external weights from memory for ONNX models. +The ``ov::Core::read_model(const std::string& model, const Tensor& weights)`` method +should be called with ``weights`` passed as an empty ``ov::Tensor``. + +.. doxygensnippet:: docs/articles_en/assets/snippets/protecting_model_guide.cpp + :language: cpp + :fragment: part1 +Additional Resources +#################### +- Intel® Distribution of OpenVINO™ toolkit `home page `__. +- :doc:`Convert a Model `. +- :doc:`OpenVINO™ Runtime User Guide <../openvino-workflow/running-inference>`. +- For more information on Sample Applications, see the :doc:`OpenVINO Samples Overview <../learn-openvino/openvino-samples>` +- For information on a set of pre-trained models, see the :doc:`Overview of OpenVINO™ Toolkit Pre-Trained Models <../omz_models_group_intel>`. +- For IoT Libraries and Code Samples, see the `Intel® IoT Developer Kit `__. diff --git a/docs/articles_en/documentation/openvino-security/openvino-encrypted-models.rst b/docs/articles_en/documentation/openvino-security/openvino-encrypted-models.rst deleted file mode 100644 index 1a5d7261440c5e..00000000000000 --- a/docs/articles_en/documentation/openvino-security/openvino-encrypted-models.rst +++ /dev/null @@ -1,56 +0,0 @@ -.. {#openvino_docs_OV_UG_protecting_model_guide} - -Using Encrypted Models with OpenVINO -==================================== - - -.. meta:: - :description: Learn how to encrypt and optimize a model before its deployment - to the edge device to ensure inference integrity and - provide copyright protection. - -Deploying deep-learning capabilities to edge devices can present security challenges like ensuring inference integrity, or providing copyright protection of your deep-learning models. - -One possible solution is to use cryptography to protect models as they are deployed and stored on edge devices. Model encryption, decryption and authentication are not provided by OpenVINO but can be implemented with third-party tools (i.e., OpenSSL). While implementing encryption, ensure that the latest versions of tools are used and follow cryptography best practices. - -This guide presents how to use OpenVINO securely with protected models. - -Secure Model Deployment -####################### - -After a model is optimized by model conversion API, it's deployed to target devices in the OpenVINO Intermediate Representation (OpenVINO IR) format. An optimized model is stored on edge device and is executed by the OpenVINO Runtime. TensorFlow, TensorFlow Lite, ONNX and PaddlePaddle models can be read natively by OpenVINO Runtime as well. - -Encrypting and optimizing model before deploying it to the edge device can be used to protect deep-learning models. The edge device should keep the stored model protected all the time and have the model decrypted **in runtime only** for use by the OpenVINO Runtime. - -.. image:: ../../assets/images/deploy_encrypted_model.svg - -Loading Encrypted Models -######################## - -The OpenVINO Runtime requires model decryption before loading. Allocate a temporary memory block for model decryption and use the ``ov::Core::read_model`` method to load the model from a memory buffer. For more information, see the ``ov::Core`` Class Reference Documentation. - -.. doxygensnippet:: docs/articles_en/assets/snippets/protecting_model_guide.cpp - :language: cpp - :fragment: part0 - -Hardware-based protection such as Intel Software Guard Extensions (Intel SGX) can be used to protect decryption operation secrets and bind them to a device. For more information, see the `Intel Software Guard Extensions `__. - -Use the ``ov::Core::read_model`` to set model representations and weights respectively. - -Currently there is no way to read external weights from memory for ONNX models. The ``ov::Core::read_model(const std::string& model, const Tensor& weights)`` method should be called with ``weights`` passed as an empty ``ov::Tensor``. - -.. doxygensnippet:: docs/articles_en/assets/snippets/protecting_model_guide.cpp - :language: cpp - :fragment: part1 - -Additional Resources -#################### - -- Intel® Distribution of OpenVINO™ toolkit `home page `__. -- :doc:`Convert a Model <../legacy-features/transition-legacy-conversion-api/legacy-conversion-api>`. -- :doc:`OpenVINO™ Runtime User Guide <../../openvino-workflow/running-inference>`. -- For more information on Sample Applications, see the :doc:`OpenVINO Samples Overview <../../learn-openvino/openvino-samples>` -- For information on a set of pre-trained models, see the :doc:`Overview of OpenVINO™ Toolkit Pre-Trained Models <../../omz_models_group_intel>`. -- For IoT Libraries and Code Samples, see the `Intel® IoT Developer Kit `__. - - diff --git a/docs/articles_en/openvino-workflow/running-inference/integrate-openvino-with-your-application.rst b/docs/articles_en/openvino-workflow/running-inference/integrate-openvino-with-your-application.rst index 4829d75cd07127..12d8d41c39b7ff 100644 --- a/docs/articles_en/openvino-workflow/running-inference/integrate-openvino-with-your-application.rst +++ b/docs/articles_en/openvino-workflow/running-inference/integrate-openvino-with-your-application.rst @@ -439,5 +439,5 @@ Additional Resources * Models in the OpenVINO IR format on `Hugging Face `__. * :doc:`OpenVINO™ Runtime Preprocessing ` * :doc:`String Tensors ` -* :doc:`Using Encrypted Models with OpenVINO <../../documentation/openvino-security/openvino-encrypted-models>` +* :ref:`Using Encrypted Models with OpenVINO ` From 439951db4d3b7215ca614894feae71da12893433 Mon Sep 17 00:00:00 2001 From: Sebastian Golebiewski Date: Mon, 26 Aug 2024 12:06:53 +0200 Subject: [PATCH 4/5] [DOCS] Reorganize conda forge installation article for 24.3 (#26229) Porting: https://github.com/openvinotoolkit/openvino/pull/26225 --- .../install-openvino-conda.rst | 72 +++++++++---------- 1 file changed, 35 insertions(+), 37 deletions(-) diff --git a/docs/articles_en/get-started/install-openvino/install-openvino-conda.rst b/docs/articles_en/get-started/install-openvino/install-openvino-conda.rst index c810ad1ddad974..ce77ddba8a53b8 100644 --- a/docs/articles_en/get-started/install-openvino/install-openvino-conda.rst +++ b/docs/articles_en/get-started/install-openvino/install-openvino-conda.rst @@ -71,6 +71,41 @@ need to install additional components. Check the description below, as well as t :doc:`list of additional configurations <../configurations>` to see if your case needs any of them. +Enabling GPU device for inference ++++++++++++++++++++++++++++++++++ + +To use a GPU device for OpenVINO inference on Linux, you must install OpenCL ICD: + +.. code-block:: sh + + conda install ocl-icd-system + +This step is not required on Windows, as Intel® Graphics Compute Runtime for +OpenCL™ Driver is included with the Intel® Graphics Driver package. + +Compiling with OpenVINO Runtime from Conda-Forge on Linux ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ + +When linking OpenVINO libraries from Conda on Linux, ensure that you have the necessary Conda compilers installed and Conda standard libraries are used. +To do so, run the following command in your Conda environment: + +.. code-block:: sh + + conda install cmake c-compiler cxx-compiler make + conda env config vars set LD_LIBRARY_PATH=$CONDA_PREFIX/lib:$LD_LIBRARY_PATH + +It is crucial to reactivate your Conda environment after installing the compilers. +This step ensures that all the environment variables are set correctly for successful linkage. + +To reactivate your Conda environment, execute the following command: + +.. code-block:: sh + + conda activate py310 + +Once you have reactivated your Conda environment, make sure that all the necessary environment +variables are properly set and proceed with linking the OpenVINO libraries. + Installing specific components of OpenVINO from Conda Forge +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ @@ -112,43 +147,6 @@ For multiple components, use: conda install conda-forge::libopenvino-intel-cpu-plugin conda-forge::libopenvino-arm-cpu-plugin conda-forge::libopenvino-intel-npu-plugin conda-forge::libopenvino-intel-gpu-plugin - -Compiling with OpenVINO Runtime from Conda-Forge on Linux -+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ - -When linking OpenVINO libraries from Conda on Linux, ensure that you have the necessary Conda compilers installed and Conda standard libraries are used. -To do so, run the following command in your Conda environment: - -.. code-block:: sh - - conda install cmake c-compiler cxx-compiler make - conda env config vars set LD_LIBRARY_PATH=$CONDA_PREFIX/lib:$LD_LIBRARY_PATH - -It is crucial to reactivate your Conda environment after installing the compilers. -This step ensures that all the environment variables are set correctly for successful linkage. - -To reactivate your Conda environment, execute the following command: - -.. code-block:: sh - - conda activate py310 - -Once you have reactivated your Conda environment, make sure that all the necessary environment -variables are properly set and proceed with linking the OpenVINO libraries. - -Enabling GPU device for inference -+++++++++++++++++++++++++++++++++ - -To use a GPU device for OpenVINO inference on Linux, you must install OpenCL ICD: - -.. code-block:: sh - - conda install ocl-icd-system - -This step is not required on Windows, as Intel® Graphics Compute Runtime for -OpenCL™ Driver is included with the Intel® Graphics Driver package. - - Uninstalling OpenVINO™ Runtime ########################################################### From df88c5cba93dd9f5794cf9ff45e9d6b3802bb7db Mon Sep 17 00:00:00 2001 From: Sebastian Golebiewski Date: Mon, 26 Aug 2024 13:32:33 +0200 Subject: [PATCH 5/5] [DOCS] Bump zipp in docs for 24.3 (#26230) Porting: https://github.com/openvinotoolkit/openvino/pull/26179 --- docs/requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/requirements.txt b/docs/requirements.txt index 98328772f48c60..e300ff860536ad 100644 --- a/docs/requirements.txt +++ b/docs/requirements.txt @@ -46,4 +46,4 @@ sphinxcontrib-qthelp==1.0.3 sphinxcontrib-serializinghtml==1.1.9 toml==0.10.2 urllib3==1.26.18 -zipp==3.4.1 \ No newline at end of file +zipp==3.19.1 \ No newline at end of file