From 71a601ea0e81746b2e20de74c96bd968957538f0 Mon Sep 17 00:00:00 2001 From: Abhishek Gola Date: Thu, 27 Aug 2026 11:57:22 +0530 Subject: [PATCH] Merge pull request #29783 from abhishek-gola:extended_onnx_coverage Added GridSample BiCubic, Dropout support - #29783 Updated ONNX coverage after this PR: 74.8% ### Pull Request Readiness Checklist See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [x] The PR is proposed to the proper branch - [x] There is a reference to the original bug report and related work - [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [x] The feature is well documented and sample code can be built with the project CMake --- .../dnn/include/opencv2/dnn/all_layers.hpp | 7 + .../misc/python/test/test_onnx_conformance.py | 1 + modules/dnn/src/init.cpp | 1 + .../cpu_kernels/gridsample_kernels.simd.hpp | 16 - modules/dnn/src/layers/det_layer.cpp | 16 +- modules/dnn/src/layers/dropout_mask_layer.cpp | 74 ++ modules/dnn/src/layers/gridsample_layer.cpp | 20 +- modules/dnn/src/layers/size_layer.cpp | 5 +- modules/dnn/src/onnx/onnx_importer2.cpp | 13 +- modules/dnn/test/test_onnx_conformance.cpp | 14 +- ...conformance_layer_filter__openvino.inl.hpp | 32 +- ...yer_filter_opencv_classic_denylist.inl.hpp | 961 ------------------ ..._conformance_layer_parser_denylist.inl.hpp | 23 - 13 files changed, 137 insertions(+), 1046 deletions(-) create mode 100644 modules/dnn/src/layers/dropout_mask_layer.cpp delete mode 100644 modules/dnn/test/test_onnx_conformance_layer_filter_opencv_classic_denylist.inl.hpp diff --git a/modules/dnn/include/opencv2/dnn/all_layers.hpp b/modules/dnn/include/opencv2/dnn/all_layers.hpp index df8b3f4409..e55bceb40a 100644 --- a/modules/dnn/include/opencv2/dnn/all_layers.hpp +++ b/modules/dnn/include/opencv2/dnn/all_layers.hpp @@ -1701,6 +1701,13 @@ CV__DNN_INLINE_NS_BEGIN static Ptr create(const LayerParams ¶ms); }; + /** @brief ONNX Dropout in eval mode: passes input through, mask output is all-true. */ + class CV_EXPORTS DropoutMaskLayer : public Layer + { + public: + static Ptr create(const LayerParams ¶ms); + }; + class CV_EXPORTS EyeLikeLayer : public Layer { public: diff --git a/modules/dnn/misc/python/test/test_onnx_conformance.py b/modules/dnn/misc/python/test/test_onnx_conformance.py index 991f9d3616..fbada05287 100644 --- a/modules/dnn/misc/python/test/test_onnx_conformance.py +++ b/modules/dnn/misc/python/test/test_onnx_conformance.py @@ -31,6 +31,7 @@ TOLERANCE_OVERRIDES = { "test_flexattention_fp16_expanded_ver26": (0.0002, 0.001), "test_gelu_tanh_1": (0.00011, 0.00016), "test_gelu_tanh_2": (9e-05, 0.0005), + "test_gridsample_bicubic": (4e-05, 0.0001), "test_linear_attention_fp16": (0.0002, 0.001), "test_linear_attention_fp16_expanded": (0.0002, 0.001), "test_nllloss_NCd1d2_reduction_sum_expanded": (2e-05, 0.0001), diff --git a/modules/dnn/src/init.cpp b/modules/dnn/src/init.cpp index 44e8c30883..bb9567ebcd 100644 --- a/modules/dnn/src/init.cpp +++ b/modules/dnn/src/init.cpp @@ -218,6 +218,7 @@ void initializeLayerFactory() CV_DNN_REGISTER_LAYER_CLASS(BatchNorm2, BatchNorm2Layer); CV_DNN_REGISTER_LAYER_CLASS(MaxUnpool, MaxUnpoolLayer); CV_DNN_REGISTER_LAYER_CLASS(Dropout, BlankLayer); + CV_DNN_REGISTER_LAYER_CLASS(DropoutMask, DropoutMaskLayer); CV_DNN_REGISTER_LAYER_CLASS(Identity, BlankLayer); CV_DNN_REGISTER_LAYER_CLASS(Silence, BlankLayer); CV_DNN_REGISTER_LAYER_CLASS(Const, ConstLayer); diff --git a/modules/dnn/src/layers/cpu_kernels/gridsample_kernels.simd.hpp b/modules/dnn/src/layers/cpu_kernels/gridsample_kernels.simd.hpp index 7198638756..9d43af83c7 100644 --- a/modules/dnn/src/layers/cpu_kernels/gridsample_kernels.simd.hpp +++ b/modules/dnn/src/layers/cpu_kernels/gridsample_kernels.simd.hpp @@ -347,7 +347,6 @@ static inline void bicubic2D(const float* X, const float* G, float* Y, } } v_float32 row0, row1, row2, row3; - v_float32 mn, mx; { v_float32 c0 = vx_load_aligned(a[0]); v_float32 c1 = vx_load_aligned(a[1]); @@ -355,8 +354,6 @@ static inline void bicubic2D(const float* X, const float* G, float* Y, v_float32 c3 = vx_load_aligned(a[3]); row0 = v_add(v_add(v_mul(c0, vwx0), v_mul(c1, vwx1)), v_add(v_mul(c2, vwx2), v_mul(c3, vwx3))); - mn = v_min(v_min(c0, c1), v_min(c2, c3)); - mx = v_max(v_max(c0, c1), v_max(c2, c3)); } { v_float32 c0 = vx_load_aligned(a[4]); @@ -365,8 +362,6 @@ static inline void bicubic2D(const float* X, const float* G, float* Y, v_float32 c3 = vx_load_aligned(a[7]); row1 = v_add(v_add(v_mul(c0, vwx0), v_mul(c1, vwx1)), v_add(v_mul(c2, vwx2), v_mul(c3, vwx3))); - mn = v_min(mn, v_min(v_min(c0, c1), v_min(c2, c3))); - mx = v_max(mx, v_max(v_max(c0, c1), v_max(c2, c3))); } { v_float32 c0 = vx_load_aligned(a[8]); @@ -375,8 +370,6 @@ static inline void bicubic2D(const float* X, const float* G, float* Y, v_float32 c3 = vx_load_aligned(a[11]); row2 = v_add(v_add(v_mul(c0, vwx0), v_mul(c1, vwx1)), v_add(v_mul(c2, vwx2), v_mul(c3, vwx3))); - mn = v_min(mn, v_min(v_min(c0, c1), v_min(c2, c3))); - mx = v_max(mx, v_max(v_max(c0, c1), v_max(c2, c3))); } { v_float32 c0 = vx_load_aligned(a[12]); @@ -385,12 +378,9 @@ static inline void bicubic2D(const float* X, const float* G, float* Y, v_float32 c3 = vx_load_aligned(a[15]); row3 = v_add(v_add(v_mul(c0, vwx0), v_mul(c1, vwx1)), v_add(v_mul(c2, vwx2), v_mul(c3, vwx3))); - mn = v_min(mn, v_min(v_min(c0, c1), v_min(c2, c3))); - mx = v_max(mx, v_max(v_max(c0, c1), v_max(c2, c3))); } v_float32 R = v_add(v_add(v_mul(row0, vwy0), v_mul(row1, vwy1)), v_add(v_mul(row2, vwy2), v_mul(row3, vwy3))); - R = v_max(mn, v_min(R, mx)); v_store_aligned(bo, R); for (int k = 0; k < L; k++) { outBase[(size_t)(c + k) * yCStride + (size_t)w] = bo[k]; @@ -401,7 +391,6 @@ static inline void bicubic2D(const float* X, const float* G, float* Y, for (; c < C; c++) { const float* baseNC = baseN + (size_t)c * xCStride; float a[4][4]; - float minv = FLT_MAX, maxv = -FLT_MAX; if (interior) { const float* p = baseNC + (size_t)(y1 - 1) * xHStride + (size_t)(x1 - 1); for (int j = 0; j < 4; j++) { @@ -419,13 +408,8 @@ static inline void bicubic2D(const float* X, const float* G, float* Y, float rowv[4]; for (int j = 0; j < 4; j++) { rowv[j] = a[j][0] * wx[0] + a[j][1] * wx[1] + a[j][2] * wx[2] + a[j][3] * wx[3]; - for (int i = 0; i < 4; i++) { - minv = std::min(minv, a[j][i]); - maxv = std::max(maxv, a[j][i]); - } } float outv = rowv[0] * wy[0] + rowv[1] * wy[1] + rowv[2] * wy[2] + rowv[3] * wy[3]; - outv = std::max(minv, std::min(outv, maxv)); outBase[(size_t)c * yCStride + (size_t)w] = outv; } } diff --git a/modules/dnn/src/layers/det_layer.cpp b/modules/dnn/src/layers/det_layer.cpp index 7131318c64..182f107093 100644 --- a/modules/dnn/src/layers/det_layer.cpp +++ b/modules/dnn/src/layers/det_layer.cpp @@ -45,7 +45,7 @@ public: if (in.size() > 2) out.assign(in.begin(), in.end() - 2); else - out = MatShape({1}); + out = MatShape::scalar(); outputs.assign(1, out); return false; @@ -83,19 +83,13 @@ public: size_t batch = X.total() / (X.size[X.dims - 2] * X.size[X.dims - 1]); - int outDims; - std::vector outSizes; if (X.dims > 2) { - outDims = X.dims - 2; - outSizes.assign(X.size.p, X.size.p + outDims); + int outDims = X.dims - 2; + std::vector outSizes(X.size.p, X.size.p + outDims); + outputs[0].create(outDims, outSizes.data(), X.type()); } - else - { - outDims = 1; - outSizes = {1}; - } - outputs[0].create(outDims, outSizes.data(), X.type()); + // else: scalar output is pre-allocated by the engine; create() would detach it. const int type = X.type(); const size_t elemSz = X.elemSize(); diff --git a/modules/dnn/src/layers/dropout_mask_layer.cpp b/modules/dnn/src/layers/dropout_mask_layer.cpp new file mode 100644 index 0000000000..e4cce6feef --- /dev/null +++ b/modules/dnn/src/layers/dropout_mask_layer.cpp @@ -0,0 +1,74 @@ +// This file is part of OpenCV project. +// It is subject to the license terms in the LICENSE file found in the top-level directory +// of this distribution and at http://opencv.org/license.html. +// Copyright (C) 2026, BigVision LLC, all rights reserved. +// Third party copyrights are property of their respective owners. + +#include "../precomp.hpp" +#include "layers_common.hpp" + +namespace cv { +namespace dnn { + +class DropoutMaskLayerImpl CV_FINAL : public DropoutMaskLayer +{ +public: + DropoutMaskLayerImpl(const LayerParams& params) + { + setParamsFrom(params); + } + + bool supportBackend(int backendId) CV_OVERRIDE + { + return backendId == DNN_BACKEND_OPENCV; + } + + bool getMemoryShapes(const std::vector& inputs, + const int requiredOutputs, + std::vector& outputs, + std::vector& internals) const CV_OVERRIDE + { + CV_Assert(!inputs.empty() && requiredOutputs >= 2); + outputs.assign(requiredOutputs, inputs[0]); + internals.clear(); + return true; + } + + void getTypes(const std::vector& inputs, + const int requiredOutputs, + const int /*requiredInternals*/, + std::vector& outputs, + std::vector& internals) const CV_OVERRIDE + { + CV_Assert(!inputs.empty() && requiredOutputs >= 2); + outputs.assign(requiredOutputs, MatType(CV_Bool)); + outputs[0] = inputs[0]; + internals.clear(); + } + + void forward(InputArrayOfArrays inputs_arr, + OutputArrayOfArrays outputs_arr, + OutputArrayOfArrays /*internals_arr*/) CV_OVERRIDE + { + std::vector inputs, outputs; + inputs_arr.getMatVector(inputs); + outputs_arr.getMatVector(outputs); + + CV_Assert(!inputs.empty() && outputs.size() >= 2); + const Mat& x = inputs[0]; + if (outputs[0].data != x.data) + x.copyTo(outputs[0]); + + for (size_t i = 1; i < outputs.size(); ++i) + { + outputs[i].setTo(true); + } + } +}; + +Ptr DropoutMaskLayer::create(const LayerParams& params) +{ + return Ptr(new DropoutMaskLayerImpl(params)); +} + +}} diff --git a/modules/dnn/src/layers/gridsample_layer.cpp b/modules/dnn/src/layers/gridsample_layer.cpp index 57ff465e88..a467ef7c74 100644 --- a/modules/dnn/src/layers/gridsample_layer.cpp +++ b/modules/dnn/src/layers/gridsample_layer.cpp @@ -192,48 +192,30 @@ static inline void gridSampleComputeRows( const T* p = baseNC + (size_t)(y1 - 1) * xHStride + (x1 - 1); float v00 = (float)p[0], v01 = (float)p[1], v02 = (float)p[2], v03 = (float)p[3]; float rowv0 = v00 * wx[0] + v01 * wx[1] + v02 * wx[2] + v03 * wx[3]; - float minv = std::min(std::min(v00, v01), std::min(v02, v03)); - float maxv = std::max(std::max(v00, v01), std::max(v02, v03)); p += xHStride; float v10 = (float)p[0], v11 = (float)p[1], v12 = (float)p[2], v13 = (float)p[3]; float rowv1 = v10 * wx[0] + v11 * wx[1] + v12 * wx[2] + v13 * wx[3]; - minv = std::min(minv, std::min(std::min(v10, v11), std::min(v12, v13))); - maxv = std::max(maxv, std::max(std::max(v10, v11), std::max(v12, v13))); p += xHStride; float v20 = (float)p[0], v21 = (float)p[1], v22 = (float)p[2], v23 = (float)p[3]; float rowv2 = v20 * wx[0] + v21 * wx[1] + v22 * wx[2] + v23 * wx[3]; - minv = std::min(minv, std::min(std::min(v20, v21), std::min(v22, v23))); - maxv = std::max(maxv, std::max(std::max(v20, v21), std::max(v22, v23))); p += xHStride; float v30 = (float)p[0], v31 = (float)p[1], v32 = (float)p[2], v33 = (float)p[3]; float rowv3 = v30 * wx[0] + v31 * wx[1] + v32 * wx[2] + v33 * wx[3]; - minv = std::min(minv, std::min(std::min(v30, v31), std::min(v32, v33))); - maxv = std::max(maxv, std::max(std::max(v30, v31), std::max(v32, v33))); outv = rowv0 * wy[0] + rowv1 * wy[1] + rowv2 * wy[2] + rowv3 * wy[3]; - outv = std::max(minv, std::min(outv, maxv)); } else { float a00 = fetch(baseNC, y1 - 1, x1 - 1), a01 = fetch(baseNC, y1 - 1, x1 ), a02 = fetch(baseNC, y1 - 1, x1 + 1), a03 = fetch(baseNC, y1 - 1, x1 + 2); float rowv0 = a00 * wx[0] + a01 * wx[1] + a02 * wx[2] + a03 * wx[3]; - float minv = std::min(std::min(a00, a01), std::min(a02, a03)); - float maxv = std::max(std::max(a00, a01), std::max(a02, a03)); float b00 = fetch(baseNC, y1, x1 - 1), b01 = fetch(baseNC, y1, x1 ), b02 = fetch(baseNC, y1, x1 + 1), b03 = fetch(baseNC, y1, x1 + 2); float rowv1 = b00 * wx[0] + b01 * wx[1] + b02 * wx[2] + b03 * wx[3]; - minv = std::min(minv, std::min(std::min(b00, b01), std::min(b02, b03))); - maxv = std::max(maxv, std::max(std::max(b00, b01), std::max(b02, b03))); float c00 = fetch(baseNC, y1 + 1, x1 - 1), c01 = fetch(baseNC, y1 + 1, x1 ), c02 = fetch(baseNC, y1 + 1, x1 + 1), c03 = fetch(baseNC, y1 + 1, x1 + 2); float rowv2 = c00 * wx[0] + c01 * wx[1] + c02 * wx[2] + c03 * wx[3]; - minv = std::min(minv, std::min(std::min(c00, c01), std::min(c02, c03))); - maxv = std::max(maxv, std::max(std::max(c00, c01), std::max(c02, c03))); float d00 = fetch(baseNC, y1 + 2, x1 - 1), d01 = fetch(baseNC, y1 + 2, x1 ), d02 = fetch(baseNC, y1 + 2, x1 + 1), d03 = fetch(baseNC, y1 + 2, x1 + 2); float rowv3 = d00 * wx[0] + d01 * wx[1] + d02 * wx[2] + d03 * wx[3]; - minv = std::min(minv, std::min(std::min(d00, d01), std::min(d02, d03))); - maxv = std::max(maxv, std::max(std::max(d00, d01), std::max(d02, d03))); outv = rowv0 * wy[0] + rowv1 * wy[1] + rowv2 * wy[2] + rowv3 * wy[3]; - outv = std::max(minv, std::min(outv, maxv)); } } Yptr[yRowBase + w] = saturate_cast(outv); @@ -470,7 +452,7 @@ public: cubic_alpha = params.get("cubic_coeff_a", -0.75f); if (m == "nearest") mode = M_NEAREST; - else if (m == "bicubic") mode = M_BICUBIC; + else if (m == "bicubic" || m == "cubic") mode = M_BICUBIC; else mode = M_BILINEAR; if (p == "border") padding = P_BORDER; diff --git a/modules/dnn/src/layers/size_layer.cpp b/modules/dnn/src/layers/size_layer.cpp index 266e67002d..a358b31b6d 100644 --- a/modules/dnn/src/layers/size_layer.cpp +++ b/modules/dnn/src/layers/size_layer.cpp @@ -29,7 +29,7 @@ public: std::vector& outputs, std::vector& internals) const CV_OVERRIDE { - outputs.assign(1, MatShape({1})); + outputs.assign(1, MatShape::scalar()); return false; } @@ -57,8 +57,7 @@ public: const MatShape xShape = shape(x); int64_t totalElems = static_cast(total(xShape)); - outputs[0].create(1, 1, CV_64S); - outputs[0].at(0) = totalElems; + outputs[0].ptr()[0] = totalElems; } }; diff --git a/modules/dnn/src/onnx/onnx_importer2.cpp b/modules/dnn/src/onnx/onnx_importer2.cpp index c2e386aa14..5d1af7e2e1 100644 --- a/modules/dnn/src/onnx/onnx_importer2.cpp +++ b/modules/dnn/src/onnx/onnx_importer2.cpp @@ -259,6 +259,7 @@ protected: void parseReshape (LayerParams& layerParams, const opencv_onnx::NodeProto& node_proto); void parseScatter (LayerParams& layerParams, const opencv_onnx::NodeProto& node_proto); void parseShape (LayerParams& layerParams, const opencv_onnx::NodeProto& node_proto); + void parseDropout (LayerParams& layerParams, const opencv_onnx::NodeProto& node_proto); void parseSimpleLayers (LayerParams& layerParams, const opencv_onnx::NodeProto& node_proto); void parseSlice (LayerParams& layerParams, const opencv_onnx::NodeProto& node_proto); void parseSoftMax (LayerParams& layerParams, const opencv_onnx::NodeProto& node_proto); @@ -2333,6 +2334,15 @@ void ONNXImporter2::parseSimpleLayers(LayerParams& layerParams, const opencv_onn addLayer(layerParams, node_proto); } +// Passthrough Dropout (eval mode) with an optional 2nd "mask" output. BlankLayer handles the +// 1-output case; the 2-output case needs a deterministic all-true mask, so route it to DropoutMask. +void ONNXImporter2::parseDropout(LayerParams& layerParams, const opencv_onnx::NodeProto& node_proto) +{ + if (node_proto.output_size() > 1) + layerParams.type = "DropoutMask"; + addLayer(layerParams, node_proto); +} + void ONNXImporter2::parseEinsum(LayerParams& layerParams, const opencv_onnx::NodeProto& node_proto) { // Check if of equation is valid @@ -3157,7 +3167,7 @@ void ONNXImporter2::buildDispatchMap_ONNX_AI() std::vector simpleLayers { "Acos", "Acosh", "Asin", "Asinh", "Atan", "Atanh", "Ceil", "Celu", "Cos", - "Cosh", "Dropout", "Erf", "Exp", "Floor", "HardSigmoid", "HardSwish", + "Cosh", "Erf", "Exp", "Floor", "HardSigmoid", "HardSwish", "Identity", "Log", "Not", "Round", "Reciprocal", "Selu", "Sign", "Sigmoid", "Sin", "Sinh", "Softplus", "Softsign", "Shrink", "Sqrt", "Tan", "ThresholdedRelu", "Gelu", "GeluApproximation" @@ -3166,6 +3176,7 @@ void ONNXImporter2::buildDispatchMap_ONNX_AI() { dispatch[name] = &ONNXImporter2::parseSimpleLayers; } + dispatch["Dropout"] = &ONNXImporter2::parseDropout; // BUG: https://github.com/opencv/opencv/issues/26310 // ai.onnx: opset 10+ diff --git a/modules/dnn/test/test_onnx_conformance.cpp b/modules/dnn/test/test_onnx_conformance.cpp index 9132fe55f4..93e9b396c9 100644 --- a/modules/dnn/test/test_onnx_conformance.cpp +++ b/modules/dnn/test/test_onnx_conformance.cpp @@ -1866,7 +1866,6 @@ public: static std::set global_deny_list; static std::set opencl_fp16_deny_list; static std::set opencl_deny_list; - static std::set classic_deny_list; #ifdef HAVE_HALIDE static std::set halide_deny_list; #endif @@ -1965,7 +1964,6 @@ std::set Test_ONNX_conformance::parser_deny_list; std::set Test_ONNX_conformance::global_deny_list; std::set Test_ONNX_conformance::opencl_fp16_deny_list; std::set Test_ONNX_conformance::opencl_deny_list; -std::set Test_ONNX_conformance::classic_deny_list; #ifdef HAVE_HALIDE std::set Test_ONNX_conformance::halide_deny_list; #endif @@ -1991,12 +1989,6 @@ TEST_P(Test_ONNX_conformance, Layer_Test) applyTestTag(CV_TEST_TAG_DNN_SKIP_PARSER, CV_TEST_TAG_DNN_SKIP_ONNX_CONFORMANCE); } - // SKIP some more if we are in the 'classic engine' mode, where we don't support certain layers. - if (classic_deny_list.find(name) != classic_deny_list.end()) - { - applyTestTag(CV_TEST_TAG_DNN_SKIP_PARSER, CV_TEST_TAG_DNN_SKIP_ONNX_CONFORMANCE); - } - // SKIP when the test case is in the global deny list. if (global_deny_list.find(name) != global_deny_list.end()) { @@ -2044,6 +2036,9 @@ TEST_P(Test_ONNX_conformance, Layer_Test) if (name == "test_nllloss_NCd1d2d3d4d5_mean_weight_expanded") { default_l1 = 2e-5; // Expected: (normL1) <= (l1), actual: 1.06394e-05 vs 1e-05 } + if (name == "test_gridsample_bicubic") { + default_l1 = 4e-5; // Expected: (normL1) <= (l1), actual: 3.61577e-05 vs 1e-05 + } // fp16 Attention models retain fp16 accumulation precision (~9e-5 L1, ~2.4e-4 Inf) // even when executed on an fp32 target. if (name == "test_attention_4d_fp16" || @@ -2132,6 +2127,9 @@ TEST_P(Test_ONNX_conformance, Layer_Test) if (name == "test_roialign_aligned_false" || name == "test_roialign_aligned_true") { default_l1 = 3e-5; } + if (name == "test_gridsample_bicubic") { + default_l1 = 4e-5; // GridSample falls back to CPU; same actual: 3.61577e-05 vs 1e-05 as the OpenCV backend + } // fp16 Attention models retain fp16 accumulation precision (~9e-5 L1, ~2.4e-4 Inf) // even when executed on an fp32 target (the layer falls back to the CPU path). if (name == "test_attention_4d_fp16" || diff --git a/modules/dnn/test/test_onnx_conformance_layer_filter__openvino.inl.hpp b/modules/dnn/test/test_onnx_conformance_layer_filter__openvino.inl.hpp index e19d882e1e..b9b7a45e01 100644 --- a/modules/dnn/test/test_onnx_conformance_layer_filter__openvino.inl.hpp +++ b/modules/dnn/test/test_onnx_conformance_layer_filter__openvino.inl.hpp @@ -476,12 +476,20 @@ CASE(test_clip_default_min_expanded) SKIP; CASE(test_clip_example) SKIP; +CASE(test_clip_example_expanded) + SKIP; +CASE(test_clip_expanded) + SKIP; CASE(test_clip_inbounds) SKIP; CASE(test_clip_inbounds_expanded) SKIP; +CASE(test_clip_min_greater_than_max_expanded) + SKIP; CASE(test_clip_outbounds) SKIP; +CASE(test_clip_outbounds_expanded) + SKIP; CASE(test_clip_splitbounds) SKIP; CASE(test_clip_splitbounds_expanded) @@ -524,6 +532,10 @@ CASE(test_constant) SKIP; CASE(test_constant_pad) SKIP; +CASE(test_constant_pad_axes) + SKIP; +CASE(test_constant_pad_negative_axes) + SKIP; CASE(test_constantofshape_float_ones) SKIP; CASE(test_constantofshape_int_shape_zero) @@ -663,9 +675,9 @@ CASE(test_div_uint8) CASE(test_dropout_default) // no filter CASE(test_dropout_default_mask) - // no filter + SKIP; CASE(test_dropout_default_mask_ratio) - // no filter + SKIP; CASE(test_dropout_default_old) // no filter CASE(test_dropout_default_ratio) @@ -901,7 +913,11 @@ CASE(test_gridsample) CASE(test_gridsample_aligncorners_true) SKIP; CASE(test_gridsample_bicubic) - // no filter + SKIP; +CASE(test_gridsample_bicubic_align_corners_0_additional_1) + SKIP; +CASE(test_gridsample_bicubic_align_corners_1_additional_1) + SKIP; CASE(test_gridsample_bilinear) SKIP; CASE(test_gridsample_border_padding) @@ -1244,6 +1260,8 @@ CASE(test_l1normalization_axis_1) SKIP; CASE(test_l1normalization_axis_last) SKIP; +CASE(test_l2normalization_axis_0) + SKIP; CASE(test_l2normalization_axis_1) SKIP; CASE(test_layer_normalization_2d_axis0) @@ -1496,6 +1514,8 @@ CASE(test_lppool_2d_dilations) SKIP; CASE(test_lppool_2d_pads) SKIP; +CASE(test_lppool_2d_same_lower) + SKIP; CASE(test_lppool_2d_same_upper) SKIP; CASE(test_lppool_2d_strides) @@ -1558,6 +1578,8 @@ CASE(test_maxpool_2d_ceil) #if SKIP_SET_1 SKIP_MYRIAD; #endif +CASE(test_maxpool_2d_ceil_output_size_reduce_by_one) + SKIP; CASE(test_maxpool_2d_default) #if SKIP_SET_1 SKIP_MYRIAD; @@ -2932,7 +2954,7 @@ CASE(test_training_dropout_mask) CASE(test_training_dropout_zero_ratio) SKIP; CASE(test_training_dropout_zero_ratio_mask) - // no filter + SKIP; CASE(test_transpose_all_permutations_0) // no filter CASE(test_transpose_all_permutations_1) @@ -2983,6 +3005,8 @@ CASE(test_triu_square_neg) SKIP; CASE(test_triu_zero) SKIP; +CASE(test_unique_length_1) + SKIP; CASE(test_unique_not_sorted_without_axis) SKIP; CASE(test_unique_sorted_with_axis) diff --git a/modules/dnn/test/test_onnx_conformance_layer_filter_opencv_classic_denylist.inl.hpp b/modules/dnn/test/test_onnx_conformance_layer_filter_opencv_classic_denylist.inl.hpp deleted file mode 100644 index c5804ba1cc..0000000000 --- a/modules/dnn/test/test_onnx_conformance_layer_filter_opencv_classic_denylist.inl.hpp +++ /dev/null @@ -1,961 +0,0 @@ -"test_if", -"test_top_k", // Issue:: K being input is not compatible with the current engine -"test_top_k_negative_axis", // same as above -"test_top_k_smallest", // same as above -"test_expand_dim_changed", -"test_expand_dim_unchanged", -"test_gemm_all_attributes", -"test_gemm_alpha", -"test_gemm_beta", -"test_gemm_default_scalar_bias", -"test_gemm_default_single_elem_vector_bias", -"test_gemm_default_vector_bias", -"test_gemm_default_zero_bias", -"test_gemm_transposeA", -"test_gemm_transposeB", -"test_range_float_type_positive_delta", -"test_range_int32_type_negative_delta", -"test_reshape_extended_dims", -"test_reshape_negative_dim", -"test_reshape_negative_extended_dims", -"test_reshape_one_dim", -"test_reshape_reduced_dims", -"test_reshape_reordered_all_dims", -"test_reshape_reordered_last_dims", -"test_reshape_zero_and_negative_dim", -"test_reshape_zero_dim", -"test_shape", -"test_shape_clip_end", -"test_shape_clip_start", -"test_shape_end_1", -"test_shape_end_negative_1", -"test_shape_example", -"test_shape_start_1", -"test_shape_start_1_end_2", -"test_shape_start_1_end_negative_1", -"test_shape_start_negative_1", -"test_slice", -"test_slice_default_axes", -"test_slice_default_steps", -"test_slice_end_out_of_bounds", -"test_slice_neg", -"test_slice_neg_steps", -"test_slice_negative_axes", -"test_split_variable_parts_1d", -"test_split_variable_parts_2d", -"test_split_variable_parts_default_axis", -"test_squeeze", -"test_squeeze_negative_axes", -"test_tile", -"test_tile_precomputed", -"test_unsqueeze_axis_0", -"test_unsqueeze_axis_1", -"test_unsqueeze_axis_2", -"test_unsqueeze_negative_axes", -"test_unsqueeze_three_axes", -"test_unsqueeze_two_axes", -"test_unsqueeze_unsorted_axes", -"test_clip", -"test_clip_default_inbounds", -"test_clip_default_int8_inbounds", -"test_clip_default_int8_max", -"test_clip_default_int8_min", -"test_clip_default_max", -"test_clip_default_min", -"test_clip_example", -"test_clip_inbounds", -"test_clip_outbounds", -"test_clip_splitbounds", -"test_size", -"test_size_example", -"test_mean_example", -"test_mean_one_input", -"test_mean_two_inputs", -"test_isnan", -"test_isinf", -"test_isinf_negative", -"test_isinf_positive", -"test_tril", -"test_tril_neg", -"test_tril_one_row_neg", -"test_tril_out_neg", -"test_tril_out_pos", -"test_tril_pos", -"test_tril_square", -"test_tril_square_neg", -"test_triu", -"test_triu_neg", -"test_triu_one_row", -"test_triu_out_neg_out", -"test_triu_out_pos", -"test_triu_pos", -"test_triu_square", -"test_triu_square_neg", -"test_det_2d", -"test_det_nd", -"test_max_int16", -"test_max_uint16", -"test_max_uint32", -"test_max_uint64", -"test_min_int16", -"test_min_uint16", -"test_min_uint32", -"test_min_uint64", -"test_mod_mixed_sign_int16", -"test_mod_uint16", -"test_mod_uint32", -"test_mod_uint64", -"test_bitshift_left_uint16", -"test_bitshift_left_uint32", -"test_bitshift_left_uint64", -"test_bitshift_left_uint8", -"test_bitshift_right_uint16", -"test_bitshift_right_uint32", -"test_bitshift_right_uint64", -"test_bitshift_right_uint8", -"test_gridsample", -"test_gridsample_aligncorners_true", -"test_gridsample_bilinear", -"test_gridsample_border_padding", -"test_gridsample_reflection_padding", -"test_gridsample_zeros_padding", -"test_gridsample_nearest", -"test_edge_pad", -"test_lstm_batchwise", -"test_lstm_defaults", -"test_lstm_with_initial_bias", -"test_lstm_with_peepholes", -"test_pow_types_float", -"test_pow_types_float32_int32", -"test_pow_types_float32_int64", -"test_pow_types_float32_uint32", -"test_pow_types_float32_uint64", -"test_pow_types_int", -"test_pow_types_int32_float32", -"test_pow_types_int32_int32", -"test_pow_types_int64_float32", -"test_reflect_pad", -"test_constant", -"test_constant_pad", -"test_constantofshape_float_ones", -"test_constantofshape_int_zeros", -"test_nonzero_example", -"test_unique_not_sorted_without_axis", -"test_unique_sorted_with_axis", -"test_unique_sorted_with_axis_3d", -"test_unique_sorted_with_negative_axis", -"test_unique_sorted_without_axis", -"test_resize_downsample_scales_nearest", -"test_resize_downsample_sizes_cubic", -"test_resize_downsample_sizes_nearest", -"test_resize_upsample_scales_cubic", -"test_resize_upsample_scales_cubic_A_n0p5_exclude_outside", -"test_resize_upsample_scales_cubic_align_corners", -"test_resize_upsample_scales_cubic_asymmetric", -"test_resize_upsample_scales_linear", -"test_resize_upsample_scales_linear_align_corners", -"test_resize_upsample_scales_nearest", -"test_resize_upsample_sizes_cubic", -"test_resize_upsample_sizes_nearest", -"test_resize_upsample_sizes_nearest_ceil_half_pixel", -"test_resize_upsample_sizes_nearest_floor_align_corners", -"test_resize_upsample_sizes_nearest_round_prefer_ceil_asymmetric", -"test_resize_downsample_scales_cubic", -"test_resize_downsample_scales_cubic_A_n0p5_exclude_outside", -"test_resize_downsample_scales_linear", -"test_resize_downsample_sizes_linear_pytorch_half_pixel", -"test_resize_downsample_sizes_nearest_tf_half_pixel_for_nn", -"test_resize_tf_crop_and_resize", -"test_nonmaxsuppression_center_point_box_format", -"test_nonmaxsuppression_flipped_coordinates", -"test_nonmaxsuppression_identical_boxes", -"test_nonmaxsuppression_limit_output_size", -"test_nonmaxsuppression_single_box", -"test_nonmaxsuppression_suppress_by_IOU", -"test_nonmaxsuppression_suppress_by_IOU_and_scores", -"test_nonmaxsuppression_two_batches", -"test_nonmaxsuppression_two_classes", -"test_add_int16", -"test_add_int8", -"test_add_uint16", -"test_add_uint32", -"test_add_uint64", -"test_clip_default_inbounds_expanded", -"test_clip_default_int8_inbounds_expanded", -"test_clip_default_int8_max_expanded", -"test_clip_default_int8_min_expanded", -"test_clip_default_max_expanded", -"test_clip_default_min_expanded", -"test_clip_inbounds_expanded", -"test_clip_splitbounds_expanded", -"test_equal_int16", -"test_equal_int8", -"test_equal_uint16", -"test_equal_uint32", -"test_equal_uint64", -"test_equal_uint8", -"test_isinf_float16", -"test_isnan_float16", -"test_logsoftmax_axis_0_expanded_ver18", -"test_logsoftmax_axis_1_expanded_ver18", -"test_logsoftmax_axis_2_expanded_ver18", -"test_logsoftmax_default_axis_expanded_ver18", -"test_logsoftmax_example_1_expanded_ver18", -"test_logsoftmax_large_number_expanded_ver18", -"test_logsoftmax_negative_axis_expanded_ver18", -"test_mul_int16", -"test_mul_int8", -"test_mul_uint16", -"test_mul_uint32", -"test_mul_uint64", -"test_softmax_axis_0_expanded_ver18", -"test_softmax_axis_1_expanded_ver18", -"test_softmax_axis_2_expanded_ver18", -"test_softmax_default_axis_expanded_ver18", -"test_softmax_example_expanded_ver18", -"test_softmax_large_number_expanded_ver18", -"test_softmax_negative_axis_expanded_ver18", -"test_swish", -"test_greater_equal_int16", -"test_greater_equal_int16_expanded", -"test_greater_equal_int8", -"test_greater_equal_int8_expanded", -"test_greater_equal_uint16", -"test_greater_equal_uint16_expanded", -"test_greater_equal_uint32", -"test_greater_equal_uint32_expanded", -"test_greater_equal_uint64", -"test_greater_equal_uint64_expanded", -"test_greater_equal_uint8", -"test_greater_equal_uint8_expanded", -"test_greater_int16", -"test_greater_int8", -"test_greater_uint16", -"test_greater_uint32", -"test_greater_uint64", -"test_greater_uint8", -"test_less_equal_int16", -"test_less_equal_int16_expanded", -"test_less_equal_int8", -"test_less_equal_int8_expanded", -"test_less_equal_uint16", -"test_less_equal_uint16_expanded", -"test_less_equal_uint32", -"test_less_equal_uint32_expanded", -"test_less_equal_uint64", -"test_less_equal_uint64_expanded", -"test_less_equal_uint8", -"test_less_equal_uint8_expanded", -"test_less_int16", -"test_less_int8", -"test_less_uint16", -"test_less_uint32", -"test_less_uint64", -"test_less_uint8", -"test_lpnormalization_default", -"test_resize_upsample_scales_nearest_axes_2_3", -"test_resize_upsample_sizes_nearest_axes_2_3", -"test_split_equal_parts_2d_opset13", -"test_split_variable_parts_1d_opset13", -"test_split_variable_parts_1d_opset18", -"test_split_variable_parts_2d_opset13", -"test_split_variable_parts_2d_opset18", -"test_split_variable_parts_default_axis_opset13", -"test_split_variable_parts_default_axis_opset18", -"test_sub_int16", -"test_sub_int8", -"test_sub_uint16", -"test_sub_uint32", -"test_sub_uint64", -"test_top_k_same_values", //type mismatch -"test_top_k_same_values_2d", -"test_top_k_same_values_largest", -"test_top_k_uint64", -"test_training_dropout_zero_ratio", -"test_wrap_pad", -"test_div_int16", -"test_div_uint8", -"test_div_int8", -"test_div_uint16", -"test_div_uint32", -"test_div_uint64", -"test_cumsum_1d_int32_exclusive", -"test_cumsum_2d_int32", -"test_cast_BFLOAT16_to_FLOAT", -"test_cast_DOUBLE_to_FLOAT16", -"test_cast_FLOAT16_to_DOUBLE", -"test_cast_FLOAT16_to_FLOAT", -"test_cast_FLOAT_to_BFLOAT16", -"test_cast_FLOAT_to_DOUBLE", -"test_cast_FLOAT_to_FLOAT16", -"test_castlike_BFLOAT16_to_FLOAT", -"test_castlike_BFLOAT16_to_FLOAT_expanded", -"test_castlike_DOUBLE_to_FLOAT", -"test_castlike_DOUBLE_to_FLOAT16", -"test_castlike_DOUBLE_to_FLOAT16_expanded", -"test_castlike_DOUBLE_to_FLOAT_expanded", -"test_castlike_FLOAT16_to_DOUBLE", -"test_castlike_FLOAT16_to_DOUBLE_expanded", -"test_castlike_FLOAT16_to_FLOAT", -"test_castlike_FLOAT16_to_FLOAT_expanded", -"test_castlike_FLOAT_to_BFLOAT16", -"test_castlike_FLOAT_to_BFLOAT16_expanded", -"test_castlike_FLOAT_to_DOUBLE", -"test_castlike_FLOAT_to_DOUBLE_expanded", -"test_castlike_FLOAT_to_FLOAT16", -"test_castlike_FLOAT_to_FLOAT16_expanded", -"test_gelu_default_1_expanded", -"test_gelu_default_2_expanded", -"test_gelu_tanh_1_expanded", -"test_gelu_tanh_2_expanded", -"test_bitwise_and_i16_3d", -"test_bitwise_and_i32_2d", -"test_bitwise_and_ui64_bcast_3v1d", -"test_bitwise_and_ui8_bcast_4v3d", -"test_bitwise_not_2d", -"test_bitwise_not_3d", -"test_bitwise_not_4d", -"test_bitwise_or_i16_4d", -"test_bitwise_or_i32_2d", -"test_bitwise_or_ui64_bcast_3v1d", -"test_bitwise_or_ui8_bcast_4v3d", -"test_bitwise_xor_i16_3d", -"test_bitwise_xor_i32_2d", -"test_bitwise_xor_ui64_bcast_3v1d", -"test_bitwise_xor_ui8_bcast_4v3d", -"test_reduce_sum_default_axes_keepdims_example", -"test_reduce_sum_do_not_keepdims_example", -"test_reduce_sum_do_not_keepdims_random", -"test_reduce_sum_empty_axes_input_noop_example", -"test_reduce_sum_empty_axes_input_noop_random", -"test_reduce_sum_keepdims_example", -"test_reduce_sum_keepdims_random", -"test_reduce_sum_negative_axes_keepdims_example", -"test_reduce_sum_negative_axes_keepdims_random", -"test_reduce_sum_default_axes_keepdims_random", -"test_reduce_l1_default_axes_keepdims_example_expanded", -"test_reduce_l1_default_axes_keepdims_random_expanded", -"test_reduce_l1_do_not_keepdims_example_expanded", -"test_reduce_l1_do_not_keepdims_random_expanded", -"test_reduce_l1_keep_dims_example_expanded", -"test_reduce_l1_keep_dims_random_expanded", -"test_reduce_l1_negative_axes_keep_dims_example_expanded", -"test_reduce_l1_negative_axes_keep_dims_random_expanded", -"test_reduce_log_sum_asc_axes_expanded", -"test_reduce_log_sum_default_expanded", -"test_reduce_log_sum_desc_axes_expanded", -"test_reduce_log_sum_negative_axes_expanded", -"test_reduce_max_bool_inputs", -"test_reduce_min_bool_inputs", -"test_reduce_sum_square_default_axes_keepdims_example_expanded", -"test_reduce_sum_square_default_axes_keepdims_random_expanded", -"test_reduce_sum_square_do_not_keepdims_example_expanded", -"test_reduce_sum_square_do_not_keepdims_random_expanded", -"test_reduce_sum_square_keepdims_example_expanded", -"test_reduce_sum_square_keepdims_random_expanded", -"test_reduce_sum_square_negative_axes_keepdims_example_expanded", -"test_reduce_sum_square_negative_axes_keepdims_random_expanded", -"test_reduce_sum_empty_axes_input_noop", -"test_reduce_l1_default_axes_keepdims_example", -"test_reduce_l1_default_axes_keepdims_random", -"test_reduce_l1_do_not_keepdims_example", -"test_reduce_l1_do_not_keepdims_random", -"test_reduce_l1_keep_dims_example", -"test_reduce_l1_keep_dims_random", -"test_reduce_l1_negative_axes_keep_dims_example", -"test_reduce_l1_negative_axes_keep_dims_random", -"test_reduce_l2_default_axes_keepdims_example", -"test_reduce_l2_default_axes_keepdims_example_expanded", -"test_reduce_l2_default_axes_keepdims_random", -"test_reduce_l2_default_axes_keepdims_random_expanded", -"test_reduce_l2_do_not_keepdims_example", -"test_reduce_l2_do_not_keepdims_example_expanded", -"test_reduce_l2_do_not_keepdims_random", -"test_reduce_l2_do_not_keepdims_random_expanded", -"test_reduce_l2_keep_dims_example", -"test_reduce_l2_keep_dims_example_expanded", -"test_reduce_l2_keep_dims_random", -"test_reduce_l2_keep_dims_random_expanded", -"test_reduce_l2_negative_axes_keep_dims_example", -"test_reduce_l2_negative_axes_keep_dims_example_expanded", -"test_reduce_l2_negative_axes_keep_dims_random", -"test_reduce_l2_negative_axes_keep_dims_random_expanded", -"test_reduce_log_sum_asc_axes", -"test_reduce_log_sum_default", -"test_reduce_log_sum_desc_axes", -"test_reduce_log_sum_exp_default_axes_keepdims_example", -"test_reduce_log_sum_exp_default_axes_keepdims_example_expanded", -"test_reduce_log_sum_exp_default_axes_keepdims_random", -"test_reduce_log_sum_exp_default_axes_keepdims_random_expanded", -"test_reduce_log_sum_exp_do_not_keepdims_example", -"test_reduce_log_sum_exp_do_not_keepdims_example_expanded", -"test_reduce_log_sum_exp_do_not_keepdims_random", -"test_reduce_log_sum_exp_do_not_keepdims_random_expanded", -"test_reduce_log_sum_exp_keepdims_example", -"test_reduce_log_sum_exp_keepdims_example_expanded", -"test_reduce_log_sum_exp_keepdims_random", -"test_reduce_log_sum_exp_keepdims_random_expanded", -"test_reduce_log_sum_exp_negative_axes_keepdims_example", -"test_reduce_log_sum_exp_negative_axes_keepdims_example_expanded", -"test_reduce_log_sum_exp_negative_axes_keepdims_random", -"test_reduce_log_sum_exp_negative_axes_keepdims_random_expanded", -"test_reduce_log_sum_negative_axes", -"test_reduce_max_do_not_keepdims_example", -"test_reduce_max_do_not_keepdims_random", -"test_reduce_max_keepdims_example", -"test_reduce_max_keepdims_random", -"test_reduce_max_negative_axes_keepdims_example", -"test_reduce_max_negative_axes_keepdims_random", -"test_reduce_mean_default_axes_keepdims_example", -"test_reduce_mean_default_axes_keepdims_random", -"test_reduce_mean_do_not_keepdims_example", -"test_reduce_mean_do_not_keepdims_random", -"test_reduce_mean_keepdims_example", -"test_reduce_mean_keepdims_random", -"test_reduce_mean_negative_axes_keepdims_example", -"test_reduce_mean_negative_axes_keepdims_random", -"test_reduce_min_do_not_keepdims_example", -"test_reduce_min_do_not_keepdims_random", -"test_reduce_min_keepdims_example", -"test_reduce_min_keepdims_random", -"test_reduce_min_negative_axes_keepdims_example", -"test_reduce_min_negative_axes_keepdims_random", -"test_reduce_prod_do_not_keepdims_example", -"test_reduce_prod_do_not_keepdims_random", -"test_reduce_prod_keepdims_example", -"test_reduce_prod_keepdims_random", -"test_reduce_prod_negative_axes_keepdims_example", -"test_reduce_prod_negative_axes_keepdims_random", -"test_reduce_sum_square_default_axes_keepdims_example", -"test_reduce_sum_square_default_axes_keepdims_random", -"test_reduce_sum_square_do_not_keepdims_example", -"test_reduce_sum_square_do_not_keepdims_random", -"test_reduce_sum_square_keepdims_example", -"test_reduce_sum_square_keepdims_random", -"test_reduce_sum_square_negative_axes_keepdims_example", -"test_reduce_sum_square_negative_axes_keepdims_random", -"test_elu_default_expanded_ver18", -"test_elu_example_expanded_ver18", -"test_elu_expanded_ver18", -"test_thresholdedrelu_default_expanded_ver18", -"test_thresholdedrelu_example_expanded_ver18", -"test_thresholdedrelu_expanded_ver18", -"test_selu_default_expanded_ver18", -"test_selu_example_expanded_ver18", -"test_selu_expanded_ver18", -"test_hardsigmoid_default_expanded_ver18", -"test_hardsigmoid_example_expanded_ver18", -"test_hardsigmoid_expanded_ver18", -"test_softplus_example_expanded_ver18", -"test_softplus_expanded_ver18", -"test_softsign_example_expanded_ver18", -"test_softsign_expanded_ver18", -"test_shrink_hard_expanded_ver18", -"test_shrink_soft_expanded_ver18", -"test_relu_expanded_ver18", -"test_prelu_broadcast_expanded", -"test_prelu_example_expanded", -"test_leakyrelu_default_expanded", -"test_leakyrelu_example_expanded", -"test_leakyrelu_expanded", -"test_sce_NCd1_mean_weight_negative_ii", -"test_sce_NCd1_mean_weight_negative_ii_expanded", -"test_sce_NCd1_mean_weight_negative_ii_log_prob", -"test_sce_NCd1_mean_weight_negative_ii_log_prob_expanded", -"test_sce_NCd1d2d3_none_no_weight_negative_ii", -"test_sce_NCd1d2d3_none_no_weight_negative_ii_expanded", -"test_sce_NCd1d2d3_none_no_weight_negative_ii_log_prob", -"test_sce_NCd1d2d3_none_no_weight_negative_ii_log_prob_expanded", -"test_sce_NCd1d2d3_sum_weight_high_ii", -"test_sce_NCd1d2d3_sum_weight_high_ii_expanded", -"test_sce_NCd1d2d3_sum_weight_high_ii_log_prob", -"test_sce_NCd1d2d3_sum_weight_high_ii_log_prob_expanded", -"test_sce_NCd1d2d3d4d5_mean_weight", -"test_sce_NCd1d2d3d4d5_mean_weight_expanded", -"test_sce_NCd1d2d3d4d5_mean_weight_log_prob", -"test_sce_NCd1d2d3d4d5_mean_weight_log_prob_expanded", -"test_sce_NCd1d2d3d4d5_none_no_weight", -"test_sce_NCd1d2d3d4d5_none_no_weight_expanded", -"test_sce_NCd1d2d3d4d5_none_no_weight_log_prob", -"test_sce_NCd1d2d3d4d5_none_no_weight_log_prob_expanded", -"test_sce_mean", -"test_sce_mean_3d", -"test_sce_mean_3d_expanded", -"test_sce_mean_3d_log_prob", -"test_sce_mean_3d_log_prob_expanded", -"test_sce_mean_expanded", -"test_sce_mean_log_prob", -"test_sce_mean_log_prob_expanded", -"test_sce_mean_no_weight_ii", -"test_sce_mean_no_weight_ii_3d", -"test_sce_mean_no_weight_ii_3d_expanded", -"test_sce_mean_no_weight_ii_3d_log_prob", -"test_sce_mean_no_weight_ii_3d_log_prob_expanded", -"test_sce_mean_no_weight_ii_4d", -"test_sce_mean_no_weight_ii_4d_expanded", -"test_sce_mean_no_weight_ii_4d_log_prob", -"test_sce_mean_no_weight_ii_4d_log_prob_expanded", -"test_sce_mean_no_weight_ii_expanded", -"test_sce_mean_no_weight_ii_log_prob", -"test_sce_mean_no_weight_ii_log_prob_expanded", -"test_sce_mean_weight", -"test_sce_mean_weight_expanded", -"test_sce_mean_weight_ii", -"test_sce_mean_weight_ii_3d", -"test_sce_mean_weight_ii_3d_expanded", -"test_sce_mean_weight_ii_3d_log_prob", -"test_sce_mean_weight_ii_3d_log_prob_expanded", -"test_sce_mean_weight_ii_4d", -"test_sce_mean_weight_ii_4d_expanded", -"test_sce_mean_weight_ii_4d_log_prob", -"test_sce_mean_weight_ii_4d_log_prob_expanded", -"test_sce_mean_weight_ii_expanded", -"test_sce_mean_weight_ii_log_prob", -"test_sce_mean_weight_ii_log_prob_expanded", -"test_sce_mean_weight_log_prob", -"test_sce_mean_weight_log_prob_expanded", -"test_sce_none", -"test_sce_none_expanded", -"test_sce_none_log_prob", -"test_sce_none_log_prob_expanded", -"test_sce_none_weights", -"test_sce_none_weights_expanded", -"test_sce_none_weights_log_prob", -"test_sce_none_weights_log_prob_expanded", -"test_sce_sum", -"test_sce_sum_expanded", -"test_sce_sum_log_prob", -"test_sce_sum_log_prob_expanded", -"test_nllloss_NC", -"test_nllloss_NCd1", -"test_nllloss_NCd1_ii", -"test_nllloss_NCd1_ii_expanded", -"test_nllloss_NCd1_mean_weight_negative_ii", -"test_nllloss_NCd1_mean_weight_negative_ii_expanded", -"test_nllloss_NCd1_weight", -"test_nllloss_NCd1_weight_ii", -"test_nllloss_NCd1_weight_ii_expanded", -"test_nllloss_NCd1d2", -"test_nllloss_NCd1d2_no_weight_reduction_mean_ii", -"test_nllloss_NCd1d2_no_weight_reduction_mean_ii_expanded", -"test_nllloss_NCd1d2_reduction_mean", -"test_nllloss_NCd1d2_reduction_mean_expanded", -"test_nllloss_NCd1d2_reduction_sum", -"test_nllloss_NCd1d2_with_weight", -"test_nllloss_NCd1d2_with_weight_reduction_mean", -"test_nllloss_NCd1d2_with_weight_reduction_sum", -"test_nllloss_NCd1d2_with_weight_reduction_sum_expanded", -"test_nllloss_NCd1d2_with_weight_reduction_sum_ii", -"test_nllloss_NCd1d2_with_weight_reduction_sum_ii_expanded", -"test_nllloss_NCd1d2d3_none_no_weight_negative_ii", -"test_nllloss_NCd1d2d3_none_no_weight_negative_ii_expanded", -"test_nllloss_NCd1d2d3_sum_weight_high_ii", -"test_nllloss_NCd1d2d3_sum_weight_high_ii_expanded", -"test_nllloss_NCd1d2d3d4d5_mean_weight", -"test_nllloss_NCd1d2d3d4d5_none_no_weight", -"test_center_crop_pad_crop", -"test_center_crop_pad_crop_and_pad", -"test_center_crop_pad_crop_and_pad_expanded", -"test_center_crop_pad_crop_axes_chw", -"test_center_crop_pad_crop_axes_chw_expanded", -"test_center_crop_pad_crop_axes_hwc", -"test_center_crop_pad_crop_axes_hwc_expanded", -"test_center_crop_pad_crop_expanded", -"test_center_crop_pad_crop_negative_axes_hwc", -"test_center_crop_pad_crop_negative_axes_hwc_expanded", -"test_center_crop_pad_pad", -"test_center_crop_pad_pad_expanded", -"test_gridsample_bilinear_align_corners_0_additional_1", -"test_gridsample_bilinear_align_corners_1_additional_1", -"test_gridsample_nearest_align_corners_0_additional_1", -"test_gridsample_nearest_align_corners_1_additional_1", -"test_gridsample_volumetric_bilinear_align_corners_0", -"test_gridsample_volumetric_bilinear_align_corners_1", -"test_gridsample_volumetric_nearest_align_corners_0", -"test_gridsample_volumetric_nearest_align_corners_1", -"test_onehot_negative_indices", -"test_onehot_with_axis", -"test_onehot_with_negative_axis", -"test_onehot_without_axis", -"test_dft", -"test_dft_axis_opset19", -"test_dft_inverse", -"test_dft_inverse_opset19", -"test_dft_opset19", -"test_affine_grid_3d", -"test_affine_grid_3d_align_corners", -"test_affine_grid_2d", -"test_affine_grid_2d_align_corners", -"test_rotary_embedding", //type mismatch -"test_rotary_embedding_3d_input", -"test_rotary_embedding_3d_input_expanded", -"test_rotary_embedding_expanded", -"test_rotary_embedding_interleaved", -"test_rotary_embedding_interleaved_expanded", -"test_rotary_embedding_no_position_ids", -"test_rotary_embedding_no_position_ids_expanded", -"test_rotary_embedding_no_position_ids_interleaved", -"test_rotary_embedding_no_position_ids_interleaved_expanded", -"test_rotary_embedding_no_position_ids_rotary_dim", -"test_rotary_embedding_no_position_ids_rotary_dim_expanded", -"test_rotary_embedding_with_interleaved_rotary_dim", -"test_rotary_embedding_with_interleaved_rotary_dim_expanded", -"test_rotary_embedding_with_rotary_dim", -"test_rotary_embedding_with_rotary_dim_expanded", -"test_attention_3d", -"test_attention_3d_attn_mask", -"test_attention_3d_causal", -"test_attention_3d_diff_heads_sizes", -"test_attention_3d_diff_heads_sizes_attn_mask", -"test_attention_3d_diff_heads_sizes_causal", -"test_attention_3d_diff_heads_sizes_softcap", -"test_attention_3d_diff_heads_sizes_scaled", -"test_attention_3d_gqa", -"test_attention_3d_gqa_attn_mask", -"test_attention_3d_gqa_causal", -"test_attention_3d_gqa_scaled", -"test_attention_3d_gqa_softcap", -"test_attention_3d_scaled", -"test_attention_3d_softcap", -"test_attention_3d_transpose_verification", -"test_attention_4d", -"test_attention_4d_attn_mask", -"test_attention_4d_attn_mask_3d", -"test_attention_4d_attn_mask_3d_causal", -"test_attention_4d_attn_mask_4d", -"test_attention_4d_attn_mask_4d_causal", -"test_attention_4d_attn_mask_bool", -"test_attention_4d_attn_mask_bool_4d", -"test_attention_4d_causal", -"test_attention_4d_diff_heads_sizes", -"test_attention_4d_diff_heads_sizes_attn_mask", -"test_attention_4d_diff_heads_sizes_causal", -"test_attention_4d_diff_heads_sizes_scaled", -"test_attention_4d_diff_heads_sizes_softcap", -"test_attention_4d_gqa", -"test_attention_4d_gqa_attn_mask", -"test_attention_4d_gqa_causal", -"test_attention_4d_gqa_scaled", -"test_attention_4d_gqa_softcap", -"test_attention_4d_scaled", -"test_attention_4d_softcap", -"test_attention_4d_attn_mask_bool", -"test_attention_4d_attn_mask_bool_4d", -"test_rotary_embedding_with_rotary_dim_expanded", -"test_hammingwindow", -"test_hammingwindow_expanded", -"test_hammingwindow_symmetric", -"test_hammingwindow_symmetric_expanded", -"test_hannwindow", -"test_hannwindow_expanded", -"test_hannwindow_symmetric", -"test_hannwindow_symmetric_expanded", -"test_blackmanwindow", -"test_blackmanwindow_expanded", -"test_blackmanwindow_symmetric", -"test_blackmanwindow_symmetric_expanded", -"test_layer_normalization_2d_axis0", -"test_layer_normalization_2d_axis0_expanded", -"test_layer_normalization_2d_axis0_expanded_ver18", -"test_layer_normalization_2d_axis1", -"test_layer_normalization_2d_axis1_expanded", -"test_layer_normalization_2d_axis1_expanded_ver18", -"test_layer_normalization_2d_axis_negative_1", -"test_layer_normalization_2d_axis_negative_1_expanded", -"test_layer_normalization_2d_axis_negative_1_expanded_ver18", -"test_layer_normalization_2d_axis_negative_2", -"test_layer_normalization_2d_axis_negative_2_expanded", -"test_layer_normalization_2d_axis_negative_2_expanded_ver18", -"test_layer_normalization_3d_axis0_epsilon", -"test_layer_normalization_3d_axis0_epsilon_expanded", -"test_layer_normalization_3d_axis0_epsilon_expanded_ver18", -"test_layer_normalization_3d_axis1_epsilon", -"test_layer_normalization_3d_axis1_epsilon_expanded", -"test_layer_normalization_3d_axis1_epsilon_expanded_ver18", -"test_layer_normalization_3d_axis2_epsilon", -"test_layer_normalization_3d_axis2_epsilon_expanded", -"test_layer_normalization_3d_axis2_epsilon_expanded_ver18", -"test_layer_normalization_3d_axis_negative_1_epsilon", -"test_layer_normalization_3d_axis_negative_1_epsilon_expanded", -"test_layer_normalization_3d_axis_negative_1_epsilon_expanded_ver18", -"test_layer_normalization_3d_axis_negative_2_epsilon", -"test_layer_normalization_3d_axis_negative_2_epsilon_expanded", -"test_layer_normalization_3d_axis_negative_2_epsilon_expanded_ver18", -"test_layer_normalization_3d_axis_negative_3_epsilon", -"test_layer_normalization_3d_axis_negative_3_epsilon_expanded", -"test_layer_normalization_3d_axis_negative_3_epsilon_expanded_ver18", -"test_layer_normalization_4d_axis0", -"test_layer_normalization_4d_axis0_expanded", -"test_layer_normalization_4d_axis0_expanded_ver18", -"test_layer_normalization_4d_axis1", -"test_layer_normalization_4d_axis1_expanded", -"test_layer_normalization_4d_axis1_expanded_ver18", -"test_layer_normalization_4d_axis2", -"test_layer_normalization_4d_axis2_expanded", -"test_layer_normalization_4d_axis2_expanded_ver18", -"test_layer_normalization_4d_axis3", -"test_layer_normalization_4d_axis3_expanded", -"test_layer_normalization_4d_axis3_expanded_ver18", -"test_layer_normalization_4d_axis_negative_1", -"test_layer_normalization_4d_axis_negative_1_expanded", -"test_layer_normalization_4d_axis_negative_1_expanded_ver18", -"test_layer_normalization_4d_axis_negative_2", -"test_layer_normalization_4d_axis_negative_2_expanded", -"test_layer_normalization_4d_axis_negative_2_expanded_ver18", -"test_layer_normalization_4d_axis_negative_3", -"test_layer_normalization_4d_axis_negative_3_expanded", -"test_layer_normalization_4d_axis_negative_3_expanded_ver18", -"test_layer_normalization_4d_axis_negative_4", -"test_layer_normalization_4d_axis_negative_4_expanded", -"test_layer_normalization_4d_axis_negative_4_expanded_ver18", -"test_layer_normalization_default_axis", -"test_layer_normalization_default_axis_expanded", -"test_layer_normalization_default_axis_expanded_ver18", -"test_roialign_aligned_false", -"test_roialign_aligned_true", -"test_roialign_mode_max", -"test_batchnorm_example", -"test_batchnorm_epsilon", -"test_gru_batchwise", -"test_gru_defaults", -"test_gru_seq_length", -"test_gru_with_initial_bias", -"test_reduce_l1_empty_set", -"test_reduce_l1_empty_set_expanded", -"test_reduce_l2_empty_set", -"test_reduce_l2_empty_set_expanded", -"test_reduce_log_sum_empty_set", -"test_reduce_log_sum_empty_set_expanded", -"test_reduce_log_sum_exp_empty_set", -"test_reduce_max_empty_set", -"test_reduce_min_empty_set", -"test_reduce_prod_empty_set", -"test_reduce_sum_empty_set", -"test_reduce_sum_empty_set_non_reduced_axis_zero", -"test_reduce_sum_square_empty_set", -"test_reduce_sum_square_empty_set_expanded", -"test_reduce_log_sum_exp_empty_set_expanded", -"test_loop11", -"test_scan9_multi_state", // Scan supported only by the new graph engine -"test_scan9_scalar", // ---- same as above --- -"test_scan9_sum", // ---- same as above --- -"test_eyelike_populate_off_main_diagonal", -"test_eyelike_with_dtype", -"test_eyelike_without_dtype", -"test_qlinearconv", -"test_qlinearmatmul_2D", -"test_qlinearmatmul_3D", -"test_convtranspose", -"test_convtranspose_1d", -"test_convtranspose_3d", -"test_convtranspose_dilations", -"test_convtranspose_group_2", -"test_convtranspose_group_2_image_3", -"test_convtranspose_kernel_shape", -"test_convtranspose_output_shape", -"test_convtranspose_pad", -"test_convtranspose_pads", -"test_convtranspose_with_kernel", -"test_lppool_1d_default", -"test_lppool_2d_default", -"test_lppool_2d_dilations", -"test_lppool_2d_pads", -"test_lppool_2d_same_upper", -"test_lppool_2d_strides", -"test_lppool_3d_default", -"test_maxpool_3d_dilations", -"test_maxpool_3d_dilations_use_ref_impl", -"test_maxpool_3d_dilations_use_ref_impl_large", -"test_einsum_inner_prod", -"test_einsum_scalar", -"test_averagepool_2d_ceil_last_window_starts_on_pad", -"test_averagepool_2d_dilations", -"test_averagepool_3d_dilations_large_count_include_pad_is_0_ceil_mode_is_False", -"test_averagepool_3d_dilations_large_count_include_pad_is_0_ceil_mode_is_True", -"test_averagepool_3d_dilations_large_count_include_pad_is_1_ceil_mode_is_False", -"test_averagepool_3d_dilations_large_count_include_pad_is_1_ceil_mode_is_True", -"test_averagepool_3d_dilations_small", -"test_constantofshape_int_shape_zero", -"test_l1normalization_axis_0", -"test_l1normalization_axis_1", -"test_l1normalization_axis_last", -"test_l2normalization_axis_1", -"test_nllloss_NCd1d2d3d4d5_mean_weight_expanded", -"test_nllloss_NCd1d2_reduction_sum_expanded", -"test_rms_normalization_2d_axis0_expanded", -"test_rms_normalization_2d_axis1_expanded", -"test_rms_normalization_2d_axis_negative_1_expanded", -"test_rms_normalization_2d_axis_negative_2_expanded", -"test_rms_normalization_3d_axis0_epsilon_expanded", -"test_rms_normalization_3d_axis1_epsilon_expanded", -"test_rms_normalization_3d_axis2_epsilon_expanded", -"test_rms_normalization_3d_axis_negative_1_epsilon_expanded", -"test_rms_normalization_3d_axis_negative_2_epsilon_expanded", -"test_rms_normalization_3d_axis_negative_3_epsilon_expanded", -"test_rms_normalization_4d_axis0_expanded", -"test_rms_normalization_4d_axis1_expanded", -"test_rms_normalization_4d_axis2_expanded", -"test_rms_normalization_4d_axis3_expanded", -"test_rms_normalization_4d_axis_negative_1_expanded", -"test_rms_normalization_4d_axis_negative_2_expanded", -"test_rms_normalization_4d_axis_negative_3_expanded", -"test_rms_normalization_4d_axis_negative_4_expanded", -"test_rms_normalization_default_axis_expanded", -"test_split_1d_uneven_split_opset18", -"test_split_2d_uneven_split_opset18", -"test_split_equal_parts_1d_opset13", -"test_split_equal_parts_1d_opset18", -"test_split_equal_parts_default_axis_opset13", -"test_split_equal_parts_default_axis_opset18", -"test_split_zero_size_splits", -"test_split_zero_size_splits_opset13", -"test_split_zero_size_splits_opset18", -"test_swish_expanded", -"test_tril_zero", -"test_triu_zero", -"test_resize_downsample_scales_cubic_align_corners", -"test_resize_downsample_scales_cubic_antialias", -"test_resize_downsample_scales_linear_align_corners", -"test_resize_downsample_scales_linear_antialias", -"test_resize_downsample_scales_linear_half_pixel_symmetric", -"test_resize_downsample_sizes_cubic_antialias", -"test_resize_downsample_sizes_linear_antialias", -"test_resize_downsample_sizes_nearest_not_larger", -"test_resize_downsample_sizes_nearest_not_smaller", -"test_resize_tf_crop_and_resize_axes_2_3", -"test_resize_tf_crop_and_resize_axes_3_2", -"test_resize_tf_crop_and_resize_extrapolation_value", -"test_resize_upsample_scales_linear_half_pixel_symmetric", -"test_resize_upsample_scales_nearest_axes_3_2", -"test_resize_upsample_sizes_nearest_axes_3_2", -"test_resize_upsample_sizes_nearest_not_larger", -"test_resize_upsample_sizes_nearest_not_smaller", -"test_dynamicquantizelinear", -"test_dynamicquantizelinear_expanded", -"test_dynamicquantizelinear_max_adjusted", -"test_dynamicquantizelinear_max_adjusted_expanded", -"test_dynamicquantizelinear_min_adjusted", -"test_dynamicquantizelinear_min_adjusted_expanded", -"test_attention_3d_expanded", -"test_attention_3d_attn_mask_expanded", -"test_attention_3d_diff_heads_sizes_attn_mask_expanded", -"test_attention_3d_scaled_expanded", -"test_attention_3d_gqa_attn_mask_expanded", -"test_attention_3d_diff_heads_sizes_expanded", -"test_attention_3d_transpose_verification_expanded", -"test_attention_3d_softcap_expanded", -"test_attention_3d_gqa_scaled_expanded", -"test_attention_3d_with_past_and_present_qk_matmul_softmax_expanded", -"test_attention_3d_with_past_and_present_qk_matmul_bias_expanded", -"test_attention_3d_with_past_and_present_qk_matmul_expanded", -"test_attention_3d_with_past_and_present_expanded", -"test_attention_3d_gqa_with_past_and_present_expanded", -"test_attention_3d_causal_expanded", -"test_attention_3d_diff_heads_sizes_causal_expanded", -"test_attention_3d_diff_heads_sizes_scaled_expanded", -"test_attention_3d_diff_heads_sizes_softcap", -"test_attention_3d_diff_heads_sizes_softcap_expanded", -"test_attention_3d_diff_heads_with_past_and_present", -"test_attention_3d_diff_heads_with_past_and_present_expanded", -"test_attention_3d_gqa_causal_expanded", -"test_attention_3d_gqa_expanded", -"test_attention_3d_gqa_softcap_expanded", -"test_attention_4d_attn_mask_3d_causal_expanded", -"test_attention_4d_attn_mask_3d_expanded", -"test_attention_4d_causal_expanded", -"test_attention_4d_diff_heads_sizes_attn_mask_expanded", -"test_attention_4d_diff_heads_mask4d_padded_kv_expanded", -"test_attention_4d_attn_mask_4d_causal_expanded", -"test_attention_4d_attn_mask_4d_expanded", -"test_attention_4d_attn_mask_bool_4d_expanded", -"test_attention_4d_attn_mask_bool_expanded", -"test_attention_4d_attn_mask_expanded", -"test_attention_4d_diff_heads_sizes_causal_expanded", -"test_attention_4d_diff_heads_sizes_expanded", -"test_attention_4d_diff_heads_sizes_scaled_expanded", -"test_attention_4d_diff_heads_sizes_softcap_expanded", -"test_attention_4d_expanded", -"test_attention_3d_gqa_with_past_and_present", -"test_attention_3d_with_past_and_present", -"test_attention_3d_with_past_and_present_qk_matmul", -"test_attention_3d_with_past_and_present_qk_matmul_bias", -"test_attention_4d_diff_heads_with_past_and_present", -"test_attention_4d_diff_heads_with_past_and_present_expanded", -"test_attention_4d_diff_heads_with_past_and_present_mask3d", -"test_attention_4d_diff_heads_with_past_and_present_mask3d_expanded", -"test_attention_4d_diff_heads_with_past_and_present_mask4d", -"test_attention_4d_diff_heads_with_past_and_present_mask4d_expanded", -"test_attention_4d_fp16_expanded", -"test_attention_4d_gqa_attn_mask_expanded", -"test_attention_4d_gqa_causal_expanded", -"test_attention_4d_gqa_expanded", -"test_attention_4d_gqa_scaled_expanded", -"test_attention_4d_gqa_softcap_expanded", -"test_attention_3d_with_past_and_present_qk_matmul_softmax", -"test_attention_4d_fp16", -"test_attention_4d_gqa_with_past_and_present", -"test_attention_4d_gqa_with_past_and_present_expanded", -"test_attention_4d_gqa_with_past_and_present_fp16", -"test_attention_4d_gqa_with_past_and_present_fp16_expanded", -"test_attention_4d_scaled_expanded", -"test_attention_4d_softcap_expanded", -"test_attention_4d_with_past_and_present", -"test_attention_4d_with_past_and_present_expanded", -"test_attention_4d_with_past_and_present_qk_matmul", -"test_attention_4d_with_past_and_present_qk_matmul_bias", -"test_attention_4d_with_past_and_present_qk_matmul_bias_3d_mask", -"test_attention_4d_with_past_and_present_qk_matmul_bias_3d_mask_causal", -"test_attention_4d_with_past_and_present_qk_matmul_bias_3d_mask_causal_expanded", -"test_attention_4d_with_past_and_present_qk_matmul_bias_3d_mask_expanded", -"test_attention_4d_with_past_and_present_qk_matmul_bias_4d_mask", -"test_attention_4d_with_past_and_present_qk_matmul_bias_4d_mask_causal", -"test_attention_4d_with_past_and_present_qk_matmul_bias_4d_mask_causal_expanded", -"test_attention_4d_with_past_and_present_qk_matmul_bias_4d_mask_expanded", -"test_attention_4d_with_past_and_present_qk_matmul_bias_expanded", -"test_attention_4d_with_past_and_present_qk_matmul_expanded", -"test_attention_4d_with_qk_matmul", -"test_attention_4d_with_qk_matmul_bias", -"test_attention_4d_with_qk_matmul_bias_expanded", -"test_attention_4d_with_qk_matmul_expanded", -"test_attention_4d_with_qk_matmul_softmax", -"test_attention_4d_with_qk_matmul_softmax_expanded", -"test_dft_rfft", -"test_nonmaxsuppression_iou_threshold_boundary", -"test_attention_4d_softcap_neginf_mask_expanded", -"test_attention_4d_softcap_neginf_mask_poison_expanded", -"test_causal_conv_with_state_b1_c1_degenerate_expanded", -"test_causal_conv_with_state_basic_expanded", -"test_causal_conv_with_state_decode_step_expanded", -"test_causal_conv_with_state_kernel_size_one_expanded", -"test_causal_conv_with_state_short_input_no_past_state_expanded", -"test_causal_conv_with_state_silu_expanded", -"test_causal_conv_with_state_silu_with_past_state_expanded", -"test_causal_conv_with_state_swish_alias_expanded", -"test_causal_conv_with_state_with_bias_and_past_state_expanded", -"test_causal_conv_with_state_with_bias_expanded", -"test_causal_conv_with_state_with_past_state_expanded", -"test_causal_conv_with_state_b1_c1_degenerate", -"test_causal_conv_with_state_basic", -"test_causal_conv_with_state_decode_step", -"test_causal_conv_with_state_fp16", -"test_causal_conv_with_state_kernel_size_one", -"test_causal_conv_with_state_short_input_no_past_state", -"test_causal_conv_with_state_silu", -"test_causal_conv_with_state_silu_fp16", -"test_causal_conv_with_state_silu_with_past_state", -"test_causal_conv_with_state_swish_alias", -"test_causal_conv_with_state_with_bias", -"test_causal_conv_with_state_with_bias_and_past_state", -"test_causal_conv_with_state_with_past_state", -"test_cumprod_1d", -"test_cumprod_1d_exclusive", -"test_cumprod_1d_int32_exclusive", -"test_cumprod_1d_reverse", -"test_cumprod_1d_reverse_exclusive", -"test_cumprod_2d_axis_0", -"test_cumprod_2d_axis_1", -"test_cumprod_2d_int32", -"test_cumprod_2d_negative_axis", -"test_flexattention_scaled_expanded_ver26", -"test_range_bfloat16_type_positive_delta", -"test_range_float16_type_positive_delta", diff --git a/modules/dnn/test/test_onnx_conformance_layer_parser_denylist.inl.hpp b/modules/dnn/test/test_onnx_conformance_layer_parser_denylist.inl.hpp index d59a7d8876..54a7832101 100644 --- a/modules/dnn/test/test_onnx_conformance_layer_parser_denylist.inl.hpp +++ b/modules/dnn/test/test_onnx_conformance_layer_parser_denylist.inl.hpp @@ -157,11 +157,7 @@ "test_castlike_no_saturate_FLOAT_to_FLOAT8E5M2FNUZ", "test_castlike_no_saturate_FLOAT_to_FLOAT8E5M2FNUZ_expanded", "test_castlike_no_saturate_FLOAT_to_FLOAT8E5M2_expanded", -"test_clip_example_expanded", //wrong output -"test_clip_expanded", "test_clip_min_greater_than_max", -"test_clip_min_greater_than_max_expanded", -"test_clip_outbounds_expanded", "test_col2im", "test_col2im_5d", "test_col2im_dilations", @@ -171,8 +167,6 @@ "test_compress_1", // ---- same as above --- "test_compress_default_axis", // ---- same as above --- "test_compress_negative_axis", // ---- same as above --- -"test_constant_pad_axes", //type mismatch -"test_constant_pad_negative_axes", "test_convinteger_with_padding", // Issues::Layer::Can't create layer "onnx_node_output_0!y" of type "ConvInteger" in function 'getLayerInstance' "test_convinteger_without_padding", //Issues::Layer::Can't create layer "onnx_node_output_0!y" of type "ConvInteger" in function 'getLayerInstance' "test_convtranspose_autopad_same", @@ -188,32 +182,17 @@ "test_dequantizelinear_uint16", "test_dequantizelinear_uint4", "test_dft_axis", -"test_dropout_default_mask", // Issue::cvtest::norm::wrong data type -"test_dropout_default_mask_ratio", // ---- same as above --- "test_equal_string", "test_equal_string_broadcast", -"test_gridsample_bicubic", // ---- same as above --- -"test_gridsample_bicubic_align_corners_0_additional_1", -"test_gridsample_bicubic_align_corners_1_additional_1", "test_group_normalization_epsilon_expanded", "test_group_normalization_example_expanded", "test_identity_opt", // 23221 illegal hardware instruction "test_identity_sequence", // Issue:: Unkonwn error "test_if_opt", // Issue::Failed to allocate 17059022683624350 bytes in function 'OutOfMemoryError' "test_if_seq", // Issue::typeProto.has_tensor_type() in function 'dumpValueInfoProto' -"test_l2normalization_axis_0", //nan "test_loop13_seq", // Loop with tensor sequences output, not yet supported in OpenCV "test_loop16_seq_none", // Loop with optional tensor sequences, not yet supported in OpenCV -"test_lppool_1d_default", -"test_lppool_2d_default", -"test_lppool_2d_dilations", -"test_lppool_2d_pads", -"test_lppool_2d_same_lower", -"test_lppool_2d_same_upper", -"test_lppool_2d_strides", -"test_lppool_3d_default", "test_matmulinteger", // Issues::Layer does not exist. Can't create layer "onnx_node_output_0!Y" of type "MatMulInteger" in function 'getLayerInstance' -"test_maxpool_2d_ceil_output_size_reduce_by_one", "test_melweightmatrix", "test_momentum", // Issues::Layer does not exist. Can't create layer "onnx_node_output_0!X1_new" of type "ai.onnx.preview.training.Momentum" in function 'getLayerInstance' "test_momentum_multiple", // ---- same as above --- @@ -319,8 +298,6 @@ "test_training_dropout_default", // ---- same as above --- type mismatch "test_training_dropout_default_mask", // ---- same as above --- "test_training_dropout_mask", // ---- same as above --- -"test_training_dropout_zero_ratio_mask", // ---- same as above --- -"test_unique_length_1", //incorrect output // ===== ONNX 1.22 additions: ops/dtypes not yet supported by the importer ===== // BitCast op not supported by the ONNX importer