mirror of https://github.com/opencv/opencv.git
Open Source Computer Vision Library
https://opencv.org/
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
2302 lines
91 KiB
2302 lines
91 KiB
// 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) 2018-2019, Intel Corporation, all rights reserved. |
|
// Third party copyrights are property of their respective owners. |
|
|
|
|
|
#include "test_precomp.hpp" |
|
#include "npy_blob.hpp" |
|
#include <opencv2/dnn/shape_utils.hpp> |
|
namespace opencv_test { namespace { |
|
|
|
template<typename TString> |
|
static std::string _tf(TString filename, bool required = true) |
|
{ |
|
return findDataFile(std::string("dnn/onnx/") + filename, required); |
|
} |
|
|
|
class Test_ONNX_layers : public DNNTestLayer |
|
{ |
|
public: |
|
bool required; |
|
|
|
Test_ONNX_layers() : required(true) { } |
|
|
|
enum Extension |
|
{ |
|
npy, |
|
pb |
|
}; |
|
|
|
void testONNXModels(const String& basename, const Extension ext = npy, |
|
const double l1 = 0, const float lInf = 0, const bool useSoftmax = false, |
|
bool checkNoFallbacks = true, int numInps = 1) |
|
{ |
|
String onnxmodel = _tf("models/" + basename + ".onnx", required); |
|
std::vector<Mat> inps(numInps); |
|
Mat ref; |
|
if (ext == npy) { |
|
for (int i = 0; i < numInps; ++i) |
|
inps[i] = blobFromNPY(_tf("data/input_" + basename + (numInps > 1 ? format("_%d", i) : "") + ".npy")); |
|
ref = blobFromNPY(_tf("data/output_" + basename + ".npy")); |
|
} |
|
else if (ext == pb) { |
|
for (int i = 0; i < numInps; ++i) |
|
inps[i] = readTensorFromONNX(_tf("data/input_" + basename + (numInps > 1 ? format("_%d", i) : "") + ".pb")); |
|
ref = readTensorFromONNX(_tf("data/output_" + basename + ".pb")); |
|
} |
|
else |
|
CV_Error(Error::StsUnsupportedFormat, "Unsupported extension"); |
|
|
|
checkBackend(&inps[0], &ref); |
|
Net net = readNetFromONNX(onnxmodel); |
|
ASSERT_FALSE(net.empty()); |
|
|
|
net.setPreferableBackend(backend); |
|
net.setPreferableTarget(target); |
|
|
|
std::vector<String> inputNames; |
|
for (int i = 0; i < numInps; ++i) |
|
inputNames.push_back(format("%d", i)); |
|
net.setInputsNames(inputNames); |
|
|
|
for (int i = 0; i < numInps; ++i) |
|
net.setInput(inps[i], inputNames[i]); |
|
Mat out = net.forward(""); |
|
|
|
if (useSoftmax) |
|
{ |
|
LayerParams lp; |
|
Net netSoftmax; |
|
netSoftmax.addLayerToPrev("softmaxLayer", "Softmax", lp); |
|
netSoftmax.setPreferableBackend(DNN_BACKEND_OPENCV); |
|
|
|
netSoftmax.setInput(out); |
|
out = netSoftmax.forward(); |
|
|
|
netSoftmax.setInput(ref); |
|
ref = netSoftmax.forward(); |
|
} |
|
normAssert(ref, out, "", l1 ? l1 : default_l1, lInf ? lInf : default_lInf); |
|
if (checkNoFallbacks) |
|
expectNoFallbacksFromIE(net); |
|
} |
|
}; |
|
|
|
TEST_P(Test_ONNX_layers, InstanceNorm) |
|
{ |
|
if(backend == DNN_BACKEND_CUDA) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_CUDA); /* MVN is not supported */ |
|
|
|
if (target == DNN_TARGET_MYRIAD) |
|
testONNXModels("instancenorm", npy, 0, 0, false, false); |
|
else |
|
testONNXModels("instancenorm", npy); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, MaxPooling) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2020020000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
#endif |
|
testONNXModels("maxpooling", npy, 0, 0, false, false); |
|
} |
|
TEST_P(Test_ONNX_layers, MaxPooling_2) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000) |
|
// IE exception: Cannot get memory! |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
#endif |
|
|
|
testONNXModels("two_maxpooling", npy, 0, 0, false, false); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Convolution) |
|
{ |
|
testONNXModels("convolution"); |
|
testONNXModels("conv_asymmetric_pads"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Convolution_variable_weight) |
|
{ |
|
if ((backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH || |
|
backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) && target == DNN_TARGET_MYRIAD) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
|
|
if (backend == DNN_BACKEND_CUDA) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_CUDA); // not supported |
|
if (backend == DNN_BACKEND_VKCOM) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_VULKAN); // not supported |
|
String basename = "conv_variable_w"; |
|
Net net = readNetFromONNX(_tf("models/" + basename + ".onnx")); |
|
ASSERT_FALSE(net.empty()); |
|
|
|
net.setPreferableBackend(backend); |
|
net.setPreferableTarget(target); |
|
|
|
for (int i = 0; i < 2; i++) |
|
{ |
|
Mat input = blobFromNPY(_tf("data/input_" + basename + format("_%d", i) + "_0.npy")); |
|
Mat weights = blobFromNPY(_tf("data/input_" + basename + format("_%d", i) + "_1.npy")); |
|
Mat ref = blobFromNPY(_tf("data/output_" + basename + format("_%d", i) + ".npy")); |
|
|
|
net.setInput(input, "0"); |
|
net.setInput(weights, "1"); |
|
|
|
Mat out = net.forward(); |
|
normAssert(ref, out, "", default_l1, default_lInf); |
|
} |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Convolution_variable_weight_bias) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000) |
|
// openvino/src/plugins/intel_myriad/common/src/ngraph/transformations/extract_dynamic_batch/slice_convolution.cpp:14 Expecting operation v1::GroupConvolution GroupConvolution_6904725 (Reshape_17[0]:f32{1,4,5,5}, Reshape_6904719[0]:f32{4,1,1,2,2}) -> (f32{1,4,4,4}) to have constant kernel, got Reshape_6904719[0]:f32{4,1,1,2,2} |
|
// openvino\src\plugins\intel_myriad\common\src\ngraph\transformations\extract_dynamic_batch\slice_convolution.cpp:15 Expecting operation v1::GroupConvolution GroupConvolution_6904692 (Reshape_17[0]:f32{1,4,5,5}, Reshape_6904686[0]:f32{4,1,1,2,2}) -> (f32{1,4,4,4}) to have constant kernel, got Reshape_6904686[0]:f32{4,1,1,2,2} |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
// accuracy (depends on OpenCL version / HW) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16)) |
|
applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, |
|
CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION |
|
); |
|
#elif defined(INF_ENGINE_RELEASE) |
|
if ((backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH || |
|
backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) && target == DNN_TARGET_MYRIAD) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
|
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU && |
|
getInferenceEngineCPUType() == CV_DNN_INFERENCE_ENGINE_CPU_TYPE_ARM_COMPUTE) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_ARM_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
#endif |
|
|
|
if (backend == DNN_BACKEND_CUDA) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_CUDA); // supports only <= 2 inputs |
|
|
|
if (backend == DNN_BACKEND_VKCOM) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_VULKAN); // not supported |
|
|
|
String basename = "conv_variable_wb"; |
|
Net net = readNetFromONNX(_tf("models/" + basename + ".onnx")); |
|
ASSERT_FALSE(net.empty()); |
|
|
|
net.setPreferableBackend(backend); |
|
net.setPreferableTarget(target); |
|
|
|
for (int i = 0; i < 2; i++) |
|
{ |
|
Mat input = blobFromNPY(_tf("data/input_" + basename + format("_%d", i) + "_0.npy")); |
|
Mat weights = blobFromNPY(_tf("data/input_" + basename + format("_%d", i) + "_1.npy")); |
|
Mat bias = blobFromNPY(_tf("data/input_" + basename + format("_%d", i) + "_2.npy")); |
|
Mat ref = blobFromNPY(_tf("data/output_" + basename + format("_%d", i) + ".npy")); |
|
|
|
net.setInput(input, "0"); |
|
net.setInput(weights, "1"); |
|
net.setInput(bias, "bias"); |
|
|
|
Mat out = net.forward(); |
|
normAssert(ref, out, "", default_l1, default_lInf); |
|
} |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Gather) |
|
{ |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 && target == DNN_TARGET_MYRIAD) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
testONNXModels("gather"); |
|
// GPU plugin unsupported slice for constant |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16)) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL, CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
testONNXModels("gather_scalar", npy, 0, 0, false, false); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Convolution3D) |
|
{ |
|
testONNXModels("conv3d"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Convolution3D_bias) |
|
{ |
|
testONNXModels("conv3d_bias"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Two_convolution) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 && target == DNN_TARGET_MYRIAD |
|
&& getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X |
|
) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD_X, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
#endif |
|
// Reference output values are in range [-0.855, 0.611] |
|
testONNXModels("two_convolution"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Deconvolution) |
|
{ |
|
testONNXModels("deconvolution", npy, 0, 0, false, false); |
|
testONNXModels("two_deconvolution", npy, 0, 0, false, false); |
|
testONNXModels("deconvolution_group", npy, 0, 0, false, false); |
|
testONNXModels("deconvolution_output_shape", npy, 0, 0, false, false); |
|
if (target != DNN_TARGET_CUDA_FP16) // bug |
|
testONNXModels("deconv_adjpad_2d", npy, 0, 0, false, false); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Deconvolution3D) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
{ |
|
// [ GENERAL_ERROR ] openvino/src/plugins/intel_myriad/graph_transformer/src/frontend/frontend.cpp:592 Failed to compile layer "2": |
|
// [ GENERAL_ERROR ] openvino/src/plugins/intel_myriad/graph_transformer/src/model/model.cpp:198 duplicateData error: while duplicating 2@weights Const data got different desc and content byte sizes (162 and 486 respectively) |
|
if (target == DNN_TARGET_MYRIAD) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
} |
|
#elif defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2021040000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
{ |
|
// [ GENERAL_ERROR ] vpu/graph_transformer/src/frontend/frontend.cpp:439 Failed to compile layer "2": |
|
// [ GENERAL_ERROR ] vpu/graph_transformer/src/model/model.cpp:198 duplicateData error: while duplicating 2@weights Const data got different desc and content byte sizes (162 and 486 respectively) |
|
if (target == DNN_TARGET_MYRIAD) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
} |
|
#endif |
|
|
|
if (backend == DNN_BACKEND_OPENCV) |
|
throw SkipTestException("OpenCV backend is not supported"); // FIXIT use tags |
|
|
|
if (backend == DNN_BACKEND_VKCOM) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_VULKAN); |
|
|
|
testONNXModels("deconv3d"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Deconvolution3D_bias) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
{ |
|
// [ GENERAL_ERROR ] openvino/src/plugins/intel_myriad/graph_transformer/src/frontend/frontend.cpp:592 Failed to compile layer "3": |
|
// [ GENERAL_ERROR ] openvino/src/plugins/intel_myriad/graph_transformer/src/model/model.cpp:198 duplicateData error: while duplicating 3@weights Const data got different desc and content byte sizes (270 and 810 respectively) |
|
if (target == DNN_TARGET_MYRIAD) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
} |
|
#elif defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2021040000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
{ |
|
// [ GENERAL_ERROR ] vpu/graph_transformer/src/frontend/frontend.cpp:439 Failed to compile layer "2": |
|
// [ GENERAL_ERROR ] vpu/graph_transformer/src/model/model.cpp:198 duplicateData error: while duplicating 2@weights Const data got different desc and content byte sizes (162 and 486 respectively) |
|
if (target == DNN_TARGET_MYRIAD) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
} |
|
#endif |
|
|
|
if (backend == DNN_BACKEND_OPENCV) |
|
throw SkipTestException("OpenCV backend is not supported"); // FIXIT use tags |
|
|
|
if (backend == DNN_BACKEND_VKCOM) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_VULKAN); |
|
|
|
testONNXModels("deconv3d_bias"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Deconvolution3D_pad) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
{ |
|
// [ GENERAL_ERROR ] openvino/src/plugins/intel_myriad/graph_transformer/src/frontend/frontend.cpp:592 Failed to compile layer "3": |
|
// [ GENERAL_ERROR ] openvino/src/plugins/intel_myriad/graph_transformer/src/model/model.cpp:198 duplicateData error: while duplicating 3@weights Const data got different desc and content byte sizes (108 and 432 respectively) |
|
if (target == DNN_TARGET_MYRIAD) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
} |
|
#elif defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2021040000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
{ |
|
// [ GENERAL_ERROR ] vpu/graph_transformer/src/frontend/frontend.cpp:439 Failed to compile layer "2": |
|
// [ GENERAL_ERROR ] vpu/graph_transformer/src/model/model.cpp:198 duplicateData error: while duplicating 2@weights Const data got different desc and content byte sizes (162 and 486 respectively) |
|
if (target == DNN_TARGET_MYRIAD) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
} |
|
#endif |
|
|
|
if (backend == DNN_BACKEND_OPENCV) |
|
throw SkipTestException("OpenCV backend is not supported"); // FIXIT use tags |
|
|
|
if (backend == DNN_BACKEND_VKCOM) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_VULKAN); |
|
|
|
testONNXModels("deconv3d_pad"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Deconvolution3D_adjpad) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
{ |
|
// [ GENERAL_ERROR ] openvino/src/plugins/intel_myriad/graph_transformer/src/frontend/frontend.cpp:592 Failed to compile layer "3": |
|
// [ GENERAL_ERROR ] openvino/src/plugins/intel_myriad/graph_transformer/src/model/model.cpp:198 duplicateData error: while duplicating 3@weights Const data got different desc and content byte sizes (90 and 180 respectively) |
|
if (target == DNN_TARGET_MYRIAD) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
} |
|
#elif defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2021040000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
{ |
|
// [ GENERAL_ERROR ] vpu/graph_transformer/src/frontend/frontend.cpp:439 Failed to compile layer "2": |
|
// [ GENERAL_ERROR ] vpu/graph_transformer/src/model/model.cpp:198 duplicateData error: while duplicating 2@weights Const data got different desc and content byte sizes (162 and 486 respectively) |
|
if (target == DNN_TARGET_MYRIAD) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
} |
|
#endif |
|
|
|
if (backend == DNN_BACKEND_OPENCV) |
|
throw SkipTestException("OpenCV backend is not supported"); // FIXIT use tags |
|
|
|
if (backend == DNN_BACKEND_VKCOM) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_VULKAN); |
|
|
|
testONNXModels("deconv3d_adjpad"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Dropout) |
|
{ |
|
testONNXModels("dropout"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Linear) |
|
{ |
|
if (backend == DNN_BACKEND_OPENCV && target == DNN_TARGET_OPENCL_FP16) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL_FP16); |
|
testONNXModels("linear"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, ReLU) |
|
{ |
|
testONNXModels("ReLU"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, PReLU) |
|
{ |
|
testONNXModels("PReLU_slope"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Clip) |
|
{ |
|
testONNXModels("clip", npy); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Shape) |
|
{ |
|
testONNXModels("shape_of_constant"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, ReduceMean) |
|
{ |
|
testONNXModels("reduce_mean"); |
|
testONNXModels("reduce_mean_axis1"); |
|
testONNXModels("reduce_mean_axis2"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, ReduceSum) |
|
{ |
|
testONNXModels("reduce_sum"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, ReduceMax) |
|
{ |
|
testONNXModels("reduce_max"); |
|
} |
|
TEST_P(Test_ONNX_layers, ReduceMax_axis_0) |
|
{ |
|
testONNXModels("reduce_max_axis_0"); |
|
} |
|
TEST_P(Test_ONNX_layers, ReduceMax_axis_1) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2021040000) |
|
// [ GENERAL_ERROR ] AssertionFailed: !out.networkInputs.empty() |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
#endif |
|
testONNXModels("reduce_max_axis_1"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Min) |
|
{ |
|
testONNXModels("min", npy, 0, 0, false, true, 2); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, ArgLayer) |
|
{ |
|
if (backend != DNN_BACKEND_OPENCV || target != DNN_TARGET_CPU) |
|
throw SkipTestException("Only CPU is supported"); // FIXIT use tags |
|
|
|
testONNXModels("argmax"); |
|
testONNXModels("argmin"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Scale) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000) |
|
// accuracy (inf/nan) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
#elif defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2021040000) |
|
// accuracy |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
// IE exception: mkldnn_node.cpp:238 Ngraph operation Reshape with name ReduceMean_0 has dynamic output shape on 0 port, but CPU plug-in supports only static shape |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16)) |
|
applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, |
|
CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION |
|
); |
|
#elif defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2021040000) |
|
// Ngraph operation Reshape with name ReduceMean_0 has dynamic output shape on 0 port, but CPU plug-in supports only static shape |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_OPENCL) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_OPENCL_FP16) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
#endif |
|
testONNXModels("scale"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Scale_broadcast) |
|
{ |
|
if (backend == DNN_BACKEND_CUDA) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_CUDA); // doesn't support broadcasting |
|
testONNXModels("scale_broadcast", npy, 0, 0, false, true, 3); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Scale_broadcast_mid) |
|
{ |
|
if (backend == DNN_BACKEND_CUDA) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_CUDA); // doesn't support broadcasting |
|
testONNXModels("scale_broadcast_mid", npy, 0, 0, false, true, 2); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, ReduceMean3D) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LT(2021040000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 && target != DNN_TARGET_CPU) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); // Only CPU on DLIE backend is supported |
|
else if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target != DNN_TARGET_CPU) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); // Only CPU on DLIE backend is supported |
|
#endif |
|
if (backend == DNN_BACKEND_OPENCV && target != DNN_TARGET_CPU) |
|
throw SkipTestException("Only CPU is supported"); // FIXIT use tags |
|
|
|
if (backend == DNN_BACKEND_VKCOM) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_VULKAN); |
|
|
|
testONNXModels("reduce_mean3d"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, MaxPooling_Sigmoid) |
|
{ |
|
testONNXModels("maxpooling_sigmoid"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Cast) |
|
{ |
|
testONNXModels("cast"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Power) |
|
{ |
|
testONNXModels("pow2", npy, 0, 0, false, false); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Exp) |
|
{ |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
testONNXModels("exp"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Elementwise_Ceil) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LT(2021040000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
#endif |
|
testONNXModels("ceil"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Elementwise_Floor) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LT(2021040000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
#endif |
|
testONNXModels("floor"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Elementwise_Log) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LT(2021040000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
#endif |
|
testONNXModels("log"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Elementwise_Round) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LT(2021040000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
#endif |
|
testONNXModels("round"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Elementwise_Sqrt) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LT(2021040000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
testONNXModels("sqrt"); |
|
#endif |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Elementwise_not) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000) |
|
// Cannot get memory! |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
// Cannot get memory! |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16)) |
|
applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, |
|
CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION |
|
); |
|
// Cannot get memory! |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
#elif defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LT(2021040000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
#endif |
|
testONNXModels("not"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Compare_EQ) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000) |
|
// Cannot get memory! |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
#elif defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2021040000) |
|
// IE exception: Function contains several inputs and outputs with one friendly name! |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16)) |
|
applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, |
|
CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION |
|
); |
|
// IE exception: Function contains several inputs and outputs with one friendly name! |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
#elif defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LT(2021040000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
#endif |
|
|
|
testONNXModels("equal"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Compare_GT) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000) |
|
// Cannot get memory! |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
#elif defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2021040000) |
|
// IE exception: Function contains several inputs and outputs with one friendly name! |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16)) |
|
applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, |
|
CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION |
|
); |
|
// IE exception: Function contains several inputs and outputs with one friendly name! |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
#elif defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LT(2021040000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
#endif |
|
|
|
testONNXModels("greater"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Compare_LT) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000) |
|
// Cannot get memory! |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
#elif defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2021040000) |
|
// IE exception: Function contains several inputs and outputs with one friendly name! |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16)) |
|
applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, |
|
CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION |
|
); |
|
// IE exception: Function contains several inputs and outputs with one friendly name! |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
#elif defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LT(2021040000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
#endif |
|
|
|
testONNXModels("less"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, CompareSameDims_EQ) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000) |
|
// Cannot get memory! |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
#elif defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2021040000) |
|
// IE exception: Function contains several inputs and outputs with one friendly name! |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16)) |
|
applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, |
|
CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION |
|
); |
|
// IE exception: Function contains several inputs and outputs with one friendly name! |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
#elif defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LT(2021040000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
#endif |
|
|
|
testONNXModels("equal_same_dims", npy, 0, 0, false, true, 2); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, CompareSameDims_GT) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000) |
|
// Cannot get memory! |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
#elif defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2021040000) |
|
// IE exception: Function contains several inputs and outputs with one friendly name! |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16)) |
|
applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, |
|
CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION |
|
); |
|
// IE exception: Function contains several inputs and outputs with one friendly name! |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
#elif defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LT(2021040000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
#endif |
|
|
|
testONNXModels("greater_same_dims", npy, 0, 0, false, true, 2); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, CompareSameDims_LT) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000) |
|
// Cannot get memory! |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
#elif defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2021040000) |
|
// IE exception: Function contains several inputs and outputs with one friendly name! |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16)) |
|
applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, |
|
CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION |
|
); |
|
// IE exception: Function contains several inputs and outputs with one friendly name! |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
#elif defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LT(2021040000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
#endif |
|
|
|
testONNXModels("less_same_dims", npy, 0, 0, false, true, 2); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Concatenation) |
|
{ |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
{ |
|
if (target == DNN_TARGET_OPENCL_FP16) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
if (target == DNN_TARGET_OPENCL) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
} |
|
testONNXModels("concatenation"); |
|
testONNXModels("concat_const_blobs"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Eltwise3D) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LT(2021040000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 && target != DNN_TARGET_CPU) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); // Only CPU on DLIE backend is supported |
|
else if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target != DNN_TARGET_CPU) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); // Only CPU on DLIE backend is supported |
|
#endif |
|
testONNXModels("eltwise3d"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, AveragePooling) |
|
{ |
|
testONNXModels("average_pooling"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, MaxPooling3D) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
{ |
|
// accuracy |
|
if (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16) |
|
applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, |
|
CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION |
|
); |
|
// IE exception: [ GENERAL_ERROR ] AssertionFailed: !expired() |
|
if (target == DNN_TARGET_MYRIAD) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
} |
|
#elif defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2021040000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
{ |
|
// accuracy |
|
if (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16) |
|
applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, |
|
CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION |
|
); |
|
// IE exception: [ GENERAL_ERROR ] AssertionFailed: !expired() |
|
if (target == DNN_TARGET_MYRIAD) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
} |
|
#endif |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LT(2021040000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 && target != DNN_TARGET_CPU) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); // Only CPU on DLIE backend is supported |
|
else if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target != DNN_TARGET_CPU) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); // Only CPU on DLIE backend is supported |
|
#endif |
|
if (backend == DNN_BACKEND_OPENCV && target != DNN_TARGET_CPU) |
|
throw SkipTestException("Only CPU is supported"); // FIXIT use tags |
|
|
|
if (backend == DNN_BACKEND_VKCOM) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_VULKAN); |
|
|
|
testONNXModels("max_pool3d", npy, 0, 0, false, false); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, AvePooling3D) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LT(2021040000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 && target != DNN_TARGET_CPU) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); // Only CPU on DLIE backend is supported |
|
else if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target != DNN_TARGET_CPU) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); // Only CPU on DLIE backend is supported |
|
#endif |
|
if (backend == DNN_BACKEND_OPENCV && target != DNN_TARGET_CPU) |
|
throw SkipTestException("Only CPU is supported"); // FIXIT use tags |
|
|
|
if (backend == DNN_BACKEND_VKCOM) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_VULKAN); |
|
|
|
testONNXModels("ave_pool3d"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, PoolConv3D) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LT(2021040000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 && target != DNN_TARGET_CPU) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); // Only CPU on DLIE backend is supported |
|
else if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target != DNN_TARGET_CPU) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); // Only CPU on DLIE backend is supported |
|
#endif |
|
if (backend == DNN_BACKEND_OPENCV && target != DNN_TARGET_CPU) |
|
throw SkipTestException("Only CPU is supported"); // FIXIT use tags |
|
|
|
if (backend == DNN_BACKEND_VKCOM) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_VULKAN); |
|
|
|
testONNXModels("pool_conv_3d"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, BatchNormalization) |
|
{ |
|
testONNXModels("batch_norm"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, BatchNormalization3D) |
|
{ |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
{ |
|
if (target == DNN_TARGET_OPENCL_FP16) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
if (target == DNN_TARGET_OPENCL) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
} |
|
testONNXModels("batch_norm_3d"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, BatchNormalizationUnfused) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2021030000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); // exception |
|
#endif |
|
testONNXModels("frozenBatchNorm2d"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, BatchNormalizationSubgraph) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2021030000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); // exception |
|
#endif |
|
testONNXModels("batch_norm_subgraph"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, NormalizeFusionSubgraph) |
|
{ |
|
testONNXModels("normalize_fusion"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Transpose) |
|
{ |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
{ |
|
if (target == DNN_TARGET_OPENCL_FP16) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
if (target == DNN_TARGET_OPENCL) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
} |
|
testONNXModels("transpose"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Multiplication) |
|
{ |
|
if (backend == DNN_BACKEND_OPENCV && target == DNN_TARGET_OPENCL_FP16) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL_FP16); |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 && target == DNN_TARGET_MYRIAD) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
testONNXModels("mul"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, MatMul) |
|
{ |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
|
|
testONNXModels("matmul_2d"); |
|
testONNXModels("matmul_3d"); |
|
testONNXModels("matmul_4d"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, MatMulAdd) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000) |
|
// accuracy |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
#elif defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LT(2021010000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
#endif |
|
if (backend == DNN_BACKEND_OPENCV && target == DNN_TARGET_OPENCL_FP16) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL_FP16); |
|
testONNXModels("matmul_add"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Expand) |
|
{ |
|
testONNXModels("expand"); |
|
testONNXModels("expand_identity"); |
|
testONNXModels("expand_batch"); |
|
testONNXModels("expand_channels"); |
|
testONNXModels("expand_neg_batch"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, ExpandHW) |
|
{ |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
testONNXModels("expand_hw"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Constant) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2018050000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 && target == DNN_TARGET_MYRIAD |
|
&& getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD_X, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
#endif |
|
testONNXModels("constant"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Padding) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LT(2019010000) |
|
testONNXModels("padding", npy, 0, 0, false, false); |
|
#else |
|
testONNXModels("padding"); |
|
#endif |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Resize) |
|
{ |
|
testONNXModels("resize_nearest"); |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
testONNXModels("resize_bilinear"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, ResizeUnfused) |
|
{ |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
testONNXModels("upsample_unfused_torch1.2"); |
|
testONNXModels("upsample_unfused_opset9_torch1.4"); |
|
testONNXModels("resize_nearest_unfused_opset11_torch1.4"); |
|
testONNXModels("resize_nearest_unfused_opset11_torch1.3"); |
|
testONNXModels("resize_bilinear_unfused_opset11_torch1.4"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, ResizeUnfusedTwoInputs) |
|
{ |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
testONNXModels("upsample_unfused_two_inputs_opset9_torch1.4", npy, 0, 0, false, true, 2); |
|
testONNXModels("upsample_unfused_two_inputs_opset11_torch1.4", npy, 0, 0, false, true, 2); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, MultyInputs) |
|
{ |
|
testONNXModels("multy_inputs", npy, 0, 0, false, true, 2); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Broadcast) |
|
{ |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
testONNXModels("channel_broadcast", npy, 0, 0, false, true, 2); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, DynamicResize) |
|
{ |
|
testONNXModels("dynamic_resize_9", npy, 0, 0, false, true, 2); |
|
testONNXModels("dynamic_resize_10", npy, 0, 0, false, true, 2); |
|
testONNXModels("dynamic_resize_11", npy, 0, 0, false, true, 2); |
|
testONNXModels("dynamic_resize_13", npy, 0, 0, false, true, 2); |
|
testONNXModels("dynamic_resize_scale_9", npy, 0, 0, false, true, 2); |
|
testONNXModels("dynamic_resize_scale_10", npy, 0, 0, false, true, 2); |
|
testONNXModels("dynamic_resize_scale_11", npy, 0, 0, false, true, 2); |
|
testONNXModels("dynamic_resize_scale_13", npy, 0, 0, false, true, 2); |
|
|
|
testONNXModels("resize_size_opset11"); |
|
testONNXModels("resize_size_opset13"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Resize_HumanSeg) |
|
{ |
|
testONNXModels("resize_humanseg"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Div) |
|
{ |
|
const String model = _tf("models/div.onnx"); |
|
Net net = readNetFromONNX(model); |
|
ASSERT_FALSE(net.empty()); |
|
|
|
net.setPreferableBackend(backend); |
|
net.setPreferableTarget(target); |
|
|
|
// Reference output values range is -68.80928, 2.991873. So to avoid computational |
|
// difference for FP16 we'll perform reversed division (just swap inputs). |
|
Mat inp1 = blobFromNPY(_tf("data/input_div_1.npy")); |
|
Mat inp2 = blobFromNPY(_tf("data/input_div_0.npy")); |
|
Mat ref = blobFromNPY(_tf("data/output_div.npy")); |
|
cv::divide(1.0, ref, ref); |
|
checkBackend(&inp1, &ref); |
|
|
|
net.setInput(inp1, "0"); |
|
net.setInput(inp2, "1"); |
|
Mat out = net.forward(); |
|
|
|
normAssert(ref, out, "", default_l1, default_lInf); |
|
expectNoFallbacksFromIE(net); |
|
expectNoFallbacksFromCUDA(net); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, DynamicReshape) |
|
{ |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
|
|
testONNXModels("dynamic_reshape"); |
|
testONNXModels("dynamic_reshape_opset_11"); |
|
testONNXModels("flatten_by_prod"); |
|
testONNXModels("flatten_const"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Reshape) |
|
{ |
|
testONNXModels("unsqueeze"); |
|
testONNXModels("unsqueeze_opset_13"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Squeeze) |
|
{ |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 && target == DNN_TARGET_MYRIAD) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
testONNXModels("squeeze"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, ReduceL2) |
|
{ |
|
testONNXModels("reduceL2"); |
|
testONNXModels("reduceL2_subgraph"); |
|
testONNXModels("reduceL2_subgraph_2"); |
|
testONNXModels("reduceL2_subgraph2_2"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Split) |
|
{ |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
testONNXModels("split_1"); |
|
testONNXModels("split_2"); |
|
testONNXModels("split_3"); |
|
testONNXModels("split_4"); |
|
testONNXModels("split_sizes"); |
|
testONNXModels("split_neg_axis"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Slice) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LT(2019010000) |
|
testONNXModels("slice", npy, 0, 0, false, false); |
|
#else |
|
testONNXModels("slice"); |
|
testONNXModels("slice_neg_starts"); |
|
testONNXModels("slice_opset_11"); |
|
#endif |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Slice_Steps_2DInput) |
|
{ |
|
testONNXModels("slice_opset_11_steps_2d"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Slice_Steps_3DInput) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000) |
|
// Cannot get memory! |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
// IE exception: Cannot get memory! |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16)) |
|
applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, |
|
CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION |
|
); |
|
#endif |
|
|
|
testONNXModels("slice_opset_11_steps_3d"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Slice_Steps_4DInput) |
|
{ |
|
testONNXModels("slice_opset_11_steps_4d"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Slice_Steps_5DInput) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000) |
|
// Cannot get memory! |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
// IE exception: Cannot get memory! |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16)) |
|
applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, |
|
CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION |
|
); |
|
// Cannot get memory! |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
#endif |
|
|
|
testONNXModels("slice_opset_11_steps_5d"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Softmax) |
|
{ |
|
testONNXModels("softmax"); |
|
testONNXModels("log_softmax", npy, 0, 0, false, false); |
|
testONNXModels("softmax_unfused"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Split_EltwiseMax) |
|
{ |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
testONNXModels("split_max"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, LSTM_Activations) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000) |
|
// Cannot get memory! |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
// IE exception: Node Block1326/lstm/reshape_0/permute was not assigned on any pointed device |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16)) |
|
applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, |
|
CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION |
|
); |
|
#elif defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2021040000) |
|
// IE Exception: Ngraph operation Reshape with name Block1237_Output_0_before_reshape has dynamic output shape on 0 port, but CPU plug-in supports only static shape |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16)) |
|
applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, |
|
CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION |
|
); |
|
#endif |
|
|
|
testONNXModels("lstm_cntk_tanh", pb, 0, 0, false, false); |
|
} |
|
|
|
// disabled due to poor handling of 1-d mats |
|
TEST_P(Test_ONNX_layers, DISABLED_LSTM) |
|
{ |
|
testONNXModels("lstm", npy, 0, 0, false, false); |
|
} |
|
|
|
// disabled due to poor handling of 1-d mats |
|
TEST_P(Test_ONNX_layers, DISABLED_LSTM_bidirectional) |
|
{ |
|
testONNXModels("lstm_bidirectional", npy, 0, 0, false, false); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, LSTM_hidden) |
|
{ |
|
testONNXModels("hidden_lstm", npy, 0, 0, false, false); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, LSTM_hidden_bidirectional) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000) |
|
// Cannot get memory! |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
// IE exception: Node Transpose_45 was not assigned on any pointed device. |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16)) |
|
applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, |
|
CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION |
|
); |
|
#endif |
|
|
|
testONNXModels("hidden_lstm_bi", npy, 0, 0, false, false); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, GRU) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000) |
|
// Cannot get memory! |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
// IE exception: Node GRU_22 was not assigned on any pointed device |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16)) |
|
applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, |
|
CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION |
|
); |
|
#endif |
|
testONNXModels("gru", npy, 0, 0, false, false); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, GRU_bidirectional) |
|
{ |
|
testONNXModels("gru_bi", npy, 0, 0, false, false); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, LSTM_cell_forward) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000) |
|
// accuracy! |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
#elif defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2021040000) |
|
// Ngraph operation Reshape with name LSTM_16/lstm_y/reshape has dynamic output shape on 0 port, but CPU plug-in supports only static shape |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_OPENCL) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_OPENCL_FP16) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
#endif |
|
testONNXModels("lstm_cell_forward", npy, 0, 0, false, false); |
|
} |
|
TEST_P(Test_ONNX_layers, LSTM_cell_bidirectional) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000) |
|
// Cannot get memory! |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
#elif defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2021040000) |
|
// Ngraph operation Reshape with name LSTM_16/lstm_y/reshape has dynamic output shape on 0 port, but CPU plug-in supports only static shape |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_OPENCL) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_OPENCL_FP16) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
#endif |
|
testONNXModels("lstm_cell_bidirectional", npy, 0, 0, false, false); |
|
} |
|
TEST_P(Test_ONNX_layers, LSTM_cell_with_peepholes) |
|
{ |
|
testONNXModels("lstm_cell_with_peepholes", npy, 0, 0, false, false); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Pad2d_Unfused) |
|
{ |
|
testONNXModels("ReflectionPad2d"); |
|
testONNXModels("ZeroPad2d"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, LinearWithConstant) |
|
{ |
|
if (backend == DNN_BACKEND_OPENCV && target == DNN_TARGET_OPENCL_FP16) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL_FP16); |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LT(2020040000) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE); |
|
#endif |
|
if (backend == DNN_BACKEND_CUDA) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_CUDA); |
|
testONNXModels("lin_with_constant"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, MatmulWithTwoInputs) |
|
{ |
|
if (backend == DNN_BACKEND_OPENCV && target == DNN_TARGET_OPENCL_FP16) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL_FP16); |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LT(2020040000) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE); |
|
#endif |
|
testONNXModels("matmul_with_two_inputs"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, ResizeOpset11_Torch1_6) |
|
{ |
|
testONNXModels("resize_opset11_torch1.6"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Mish) |
|
{ |
|
testONNXModels("mish"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, CalculatePads) |
|
{ |
|
testONNXModels("calc_pads"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Conv1d) |
|
{ |
|
testONNXModels("conv1d"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Conv1d_bias) |
|
{ |
|
testONNXModels("conv1d_bias"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Conv1d_variable_weight) |
|
{ |
|
if (backend == DNN_BACKEND_CUDA) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_CUDA); // not supported |
|
if (backend == DNN_BACKEND_VKCOM) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_VULKAN); // not supported |
|
String basename = "conv1d_variable_w"; |
|
Net net = readNetFromONNX(_tf("models/" + basename + ".onnx")); |
|
ASSERT_FALSE(net.empty()); |
|
|
|
net.setPreferableBackend(backend); |
|
net.setPreferableTarget(target); |
|
|
|
Mat input = blobFromNPY(_tf("data/input_" + basename + "_0.npy")); |
|
Mat weights = blobFromNPY(_tf("data/input_" + basename + "_1.npy")); |
|
Mat ref = blobFromNPY(_tf("data/output_" + basename + ".npy")); |
|
|
|
net.setInput(input, "0"); |
|
net.setInput(weights, "1"); |
|
|
|
Mat out = net.forward(); |
|
normAssert(ref, out, "", default_l1, default_lInf); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Conv1d_variable_weight_bias) |
|
{ |
|
if (backend == DNN_BACKEND_CUDA) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_CUDA); // not supported |
|
if (backend == DNN_BACKEND_VKCOM) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_VULKAN); // not supported |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
{ |
|
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
if (target == DNN_TARGET_CPU && getInferenceEngineCPUType() == CV_DNN_INFERENCE_ENGINE_CPU_TYPE_ARM_COMPUTE) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_ARM_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
} |
|
String basename = "conv1d_variable_wb"; |
|
Net net = readNetFromONNX(_tf("models/" + basename + ".onnx")); |
|
ASSERT_FALSE(net.empty()); |
|
|
|
net.setPreferableBackend(backend); |
|
net.setPreferableTarget(target); |
|
|
|
Mat input = blobFromNPY(_tf("data/input_" + basename + "_0.npy")); |
|
Mat weights = blobFromNPY(_tf("data/input_" + basename + "_1.npy")); |
|
Mat bias = blobFromNPY(_tf("data/input_" + basename + "_2.npy")); |
|
Mat ref = blobFromNPY(_tf("data/output_" + basename + ".npy")); |
|
|
|
net.setInput(input, "0"); |
|
net.setInput(weights, "1"); |
|
net.setInput(bias, "bias"); |
|
|
|
Mat out = net.forward(); |
|
normAssert(ref, out, "", default_l1, default_lInf); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, GatherMultiOutput) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2021040000) |
|
// IE Exception: Ngraph operation Reshape with name 6 has dynamic output shape on 0 port, but CPU plug-in supports only static shape |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16)) |
|
applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, |
|
CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION |
|
); |
|
#endif |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2021030000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_OPENCL) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); // exception |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_OPENCL_FP16) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); // exception |
|
#endif |
|
|
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LE(2021030000) |
|
if (target == DNN_TARGET_MYRIAD) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE); |
|
#endif |
|
|
|
testONNXModels("gather_multi_output"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, DynamicAxes_squeeze_and_conv) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
{ |
|
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
} |
|
#if INF_ENGINE_VER_MAJOR_LT(2021000000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
{ |
|
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
} |
|
#endif |
|
#endif |
|
testONNXModels("squeeze_and_conv_dynamic_axes"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, DynamicAxes_unsqueeze_and_conv) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
{ |
|
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
} |
|
#if INF_ENGINE_VER_MAJOR_LT(2021000000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
{ |
|
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
} |
|
#endif |
|
#endif |
|
testONNXModels("unsqueeze_and_conv_dynamic_axes"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, DynamicAxes_gather) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
{ |
|
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
} |
|
#if INF_ENGINE_VER_MAJOR_LT(2021000000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
{ |
|
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
} |
|
#endif |
|
#endif |
|
testONNXModels("gather_dynamic_axes"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, DynamicAxes_gather_scalar) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000) |
|
// accuracy |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16)) |
|
applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, |
|
CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION |
|
); |
|
#elif defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2021040000) |
|
// accuracy |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16)) |
|
applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, |
|
CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION |
|
); |
|
#elif defined(INF_ENGINE_RELEASE) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
{ |
|
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
} |
|
#if INF_ENGINE_VER_MAJOR_LT(2021000000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
{ |
|
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
} |
|
#endif |
|
#endif |
|
testONNXModels("gather_scalar_dynamic_axes"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, DynamicAxes_slice) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
{ |
|
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
} |
|
#if INF_ENGINE_VER_MAJOR_LT(2021000000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
{ |
|
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
} |
|
#endif |
|
#endif |
|
testONNXModels("slice_dynamic_axes"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, DynamicAxes_slice_opset_11) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
{ |
|
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
} |
|
#if INF_ENGINE_VER_MAJOR_LT(2021000000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
{ |
|
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
} |
|
#endif |
|
#endif |
|
testONNXModels("slice_opset_11_dynamic_axes"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, DynamicAxes_resize_opset11_torch16) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
{ |
|
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
} |
|
#if INF_ENGINE_VER_MAJOR_LT(2021000000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
{ |
|
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
} |
|
#endif |
|
#endif |
|
testONNXModels("resize_opset11_torch1.6_dynamic_axes"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, DynamicAxes_average_pooling) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
{ |
|
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
} |
|
#if INF_ENGINE_VER_MAJOR_LT(2021000000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
{ |
|
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
} |
|
#endif |
|
#endif |
|
testONNXModels("average_pooling_dynamic_axes"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, DynamicAxes_maxpooling_sigmoid) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
{ |
|
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
} |
|
#if INF_ENGINE_VER_MAJOR_LT(2021000000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
{ |
|
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
} |
|
#endif |
|
#endif |
|
testONNXModels("maxpooling_sigmoid_dynamic_axes"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, DynamicAxes_dynamic_batch) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
{ |
|
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
} |
|
#if INF_ENGINE_VER_MAJOR_LT(2021000000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
{ |
|
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
} |
|
#endif |
|
#endif |
|
testONNXModels("dynamic_batch"); |
|
} |
|
|
|
|
|
TEST_P(Test_ONNX_layers, MaxPool1d) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LT(2021040000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
{ |
|
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
} |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
{ |
|
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
} |
|
#endif |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2021040000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD) |
|
{ |
|
// 2021.4: [ GENERAL_ERROR ] AssertionFailed: !expired() |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
} |
|
#endif |
|
testONNXModels("maxpooling_1d"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, MaxPoolSigmoid1d) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
#elif defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LT(2021040000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
{ |
|
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
} |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
{ |
|
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
} |
|
#endif |
|
testONNXModels("maxpooling_sigmoid_1d"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, MaxPool1d_Twise) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000) |
|
// Cannot get memory! |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
// Cannot get memory! |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16)) |
|
applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, |
|
CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION |
|
); |
|
#elif defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LT(2021040000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
{ |
|
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
} |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
{ |
|
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
} |
|
#endif |
|
testONNXModels("two_maxpooling_1d"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, AvePool1d) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000) |
|
// Cannot get memory! |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
#elif defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LT(2021040000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
{ |
|
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
} |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
{ |
|
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
} |
|
#endif |
|
testONNXModels("average_pooling_1d"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, PoolConv1d) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000) |
|
// Cannot get memory! |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
// Cannot get memory! |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
// Cannot get memory! |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16)) |
|
applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, |
|
CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION |
|
); |
|
#elif defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LT(2021040000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
{ |
|
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
} |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
{ |
|
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
} |
|
#endif |
|
testONNXModels("pool_conv_1d"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, ConvResizePool1d) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2021040000) |
|
// IE Exception: Ngraph operation Reshape with name 15 has dynamic output shape on 0 port, but CPU plug-in supports only static shape |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16)) |
|
applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, |
|
CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION |
|
); |
|
#endif |
|
#if defined(INF_ENGINE_RELEASE) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
{ |
|
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
} |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
{ |
|
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
#if INF_ENGINE_VER_MAJOR_EQ(2021030000) |
|
if (target == DNN_TARGET_OPENCL) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); // exception |
|
if (target == DNN_TARGET_OPENCL_FP16) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); // exception |
|
#endif |
|
} |
|
#endif |
|
testONNXModels("conv_resize_pool_1d"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, SubFromConst) |
|
{ |
|
testONNXModels("sub_from_const1"); |
|
testONNXModels("sub_from_const_eltwise"); |
|
testONNXModels("sub_from_const_broadcast"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, DivConst) |
|
{ |
|
testONNXModels("div_const"); |
|
} |
|
|
|
|
|
TEST_P(Test_ONNX_layers, Quantized_Convolution) |
|
{ |
|
testONNXModels("quantized_conv_uint8_weights", npy, 0.004, 0.02); |
|
testONNXModels("quantized_conv_int8_weights", npy, 0.03, 0.5); |
|
testONNXModels("quantized_conv_per_channel_weights", npy, 0.06, 0.4); |
|
|
|
testONNXModels("quantized_conv_asymmetric_pads_int8_weights"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Quantized_MatMul) |
|
{ |
|
testONNXModels("quantized_matmul_uint8_weights", npy, 0.005, 0.007); |
|
testONNXModels("quantized_matmul_int8_weights", npy, 0.06, 0.2); |
|
testONNXModels("quantized_matmul_per_channel_weights", npy, 0.06, 0.22); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Quantized_MatMul_Variable_Weights) |
|
{ |
|
// Unsupported |
|
EXPECT_THROW( |
|
{ |
|
testONNXModels("quantized_matmul_variable_inputs"); |
|
}, cv::Exception); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Quantized_Eltwise) |
|
{ |
|
testONNXModels("quantized_eltwise"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Quantized_Eltwise_Scalar) |
|
{ |
|
testONNXModels("quantized_eltwise_scalar"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Quantized_Eltwise_Broadcast) |
|
{ |
|
testONNXModels("quantized_eltwise_broadcast"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Quantized_LeakyReLU) |
|
{ |
|
testONNXModels("quantized_leaky_relu"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Quantized_Sigmoid) |
|
{ |
|
testONNXModels("quantized_sigmoid"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Quantized_MaxPool) |
|
{ |
|
testONNXModels("quantized_maxpool"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Quantized_AvgPool) |
|
{ |
|
testONNXModels("quantized_avgpool"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Quantized_Split) |
|
{ |
|
testONNXModels("quantized_split"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Quantized_Pad) |
|
{ |
|
testONNXModels("quantized_padding"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Quantized_Reshape) |
|
{ |
|
testONNXModels("quantized_reshape"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Quantized_Transpose) |
|
{ |
|
testONNXModels("quantized_transpose"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Quantized_Squeeze) |
|
{ |
|
testONNXModels("quantized_squeeze"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Quantized_Unsqueeze) |
|
{ |
|
testONNXModels("quantized_unsqueeze"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Quantized_Resize) |
|
{ |
|
testONNXModels("quantized_resize_nearest"); |
|
testONNXModels("quantized_resize_bilinear", npy, 2e-4, 0.003); |
|
testONNXModels("quantized_resize_bilinear_align", npy, 3e-4, 0.003); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Quantized_Concat) |
|
{ |
|
testONNXModels("quantized_concat"); |
|
testONNXModels("quantized_concat_const_blob"); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, Quantized_Constant) |
|
{ |
|
testONNXModels("quantized_constant", npy, 0.002, 0.008); |
|
} |
|
|
|
INSTANTIATE_TEST_CASE_P(/*nothing*/, Test_ONNX_layers, dnnBackendsAndTargets()); |
|
|
|
class Test_ONNX_nets : public Test_ONNX_layers |
|
{ |
|
public: |
|
Test_ONNX_nets() { required = false; } |
|
}; |
|
|
|
TEST_P(Test_ONNX_nets, Alexnet) |
|
{ |
|
#if defined(OPENCV_32BIT_CONFIGURATION) && (defined(HAVE_OPENCL) || defined(_WIN32)) |
|
applyTestTag(CV_TEST_TAG_MEMORY_2GB); |
|
#else |
|
applyTestTag(target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_512MB : CV_TEST_TAG_MEMORY_1GB); |
|
#endif |
|
|
|
const String model = _tf("models/alexnet.onnx", false); |
|
|
|
Net net = readNetFromONNX(model); |
|
ASSERT_FALSE(net.empty()); |
|
|
|
net.setPreferableBackend(backend); |
|
net.setPreferableTarget(target); |
|
|
|
Mat inp = imread(_tf("../grace_hopper_227.png")); |
|
Mat ref = blobFromNPY(_tf("../caffe_alexnet_prob.npy")); |
|
checkBackend(&inp, &ref); |
|
|
|
net.setInput(blobFromImage(inp, 1.0f, Size(227, 227), Scalar(), false)); |
|
ASSERT_FALSE(net.empty()); |
|
Mat out = net.forward(); |
|
|
|
normAssert(out, ref, "", default_l1, default_lInf); |
|
expectNoFallbacksFromIE(net); |
|
} |
|
|
|
TEST_P(Test_ONNX_nets, Squeezenet) |
|
{ |
|
testONNXModels("squeezenet", pb); |
|
} |
|
|
|
TEST_P(Test_ONNX_nets, Googlenet) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000) |
|
// accuracy |
|
if (target == DNN_TARGET_MYRIAD) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
#elif defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2021040000) |
|
// accuracy |
|
if (target == DNN_TARGET_MYRIAD) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
#elif defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LT(2021040000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
|
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
#endif |
|
|
|
const String model = _tf("models/googlenet.onnx", false); |
|
|
|
Net net = readNetFromONNX(model); |
|
ASSERT_FALSE(net.empty()); |
|
|
|
net.setPreferableBackend(backend); |
|
net.setPreferableTarget(target); |
|
|
|
std::vector<Mat> images; |
|
images.push_back( imread(_tf("../googlenet_0.png")) ); |
|
images.push_back( imread(_tf("../googlenet_1.png")) ); |
|
Mat inp = blobFromImages(images, 1.0f, Size(), Scalar(), false); |
|
Mat ref = blobFromNPY(_tf("../googlenet_prob.npy")); |
|
checkBackend(&inp, &ref); |
|
|
|
net.setInput(inp); |
|
ASSERT_FALSE(net.empty()); |
|
Mat out = net.forward(); |
|
|
|
normAssert(ref, out, "", default_l1, default_lInf); |
|
expectNoFallbacksFromIE(net); |
|
} |
|
|
|
TEST_P(Test_ONNX_nets, CaffeNet) |
|
{ |
|
#if defined(OPENCV_32BIT_CONFIGURATION) && (defined(HAVE_OPENCL) || defined(_WIN32)) |
|
applyTestTag(CV_TEST_TAG_MEMORY_2GB); |
|
#else |
|
applyTestTag(target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_512MB : CV_TEST_TAG_MEMORY_1GB); |
|
#endif |
|
|
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2019030000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 && target == DNN_TARGET_MYRIAD |
|
&& getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD_X, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
#endif |
|
testONNXModels("caffenet", pb); |
|
} |
|
|
|
TEST_P(Test_ONNX_nets, RCNN_ILSVRC13) |
|
{ |
|
#if defined(OPENCV_32BIT_CONFIGURATION) && (defined(HAVE_OPENCL) || defined(_WIN32)) |
|
applyTestTag(CV_TEST_TAG_MEMORY_2GB); |
|
#else |
|
applyTestTag(target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_512MB : CV_TEST_TAG_MEMORY_1GB); |
|
#endif |
|
|
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2019030000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 && target == DNN_TARGET_MYRIAD |
|
&& getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD_X, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
#endif |
|
// Reference output values are in range [-4.992, -1.161] |
|
testONNXModels("rcnn_ilsvrc13", pb, 0.0046); |
|
} |
|
|
|
TEST_P(Test_ONNX_nets, VGG16_bn) |
|
{ |
|
applyTestTag(CV_TEST_TAG_MEMORY_6GB); // > 2.3Gb |
|
|
|
// output range: [-16; 27], after Softmax [0; 0.67] |
|
const double lInf = (target == DNN_TARGET_MYRIAD) ? 0.038 : default_lInf; |
|
testONNXModels("vgg16-bn", pb, default_l1, lInf, true); |
|
} |
|
|
|
TEST_P(Test_ONNX_nets, ZFNet) |
|
{ |
|
applyTestTag(CV_TEST_TAG_MEMORY_2GB); |
|
testONNXModels("zfnet512", pb); |
|
} |
|
|
|
TEST_P(Test_ONNX_nets, ResNet18v1) |
|
{ |
|
applyTestTag(CV_TEST_TAG_MEMORY_512MB); |
|
|
|
// output range: [-16; 22], after Softmax [0, 0.51] |
|
testONNXModels("resnet18v1", pb, default_l1, default_lInf, true, target != DNN_TARGET_MYRIAD); |
|
} |
|
|
|
TEST_P(Test_ONNX_nets, ResNet50v1) |
|
{ |
|
applyTestTag(CV_TEST_TAG_MEMORY_512MB); |
|
|
|
// output range: [-67; 75], after Softmax [0, 0.98] |
|
testONNXModels("resnet50v1", pb, default_l1, default_lInf, true, target != DNN_TARGET_MYRIAD); |
|
} |
|
|
|
TEST_P(Test_ONNX_nets, ResNet50_Int8) |
|
{ |
|
testONNXModels("resnet50_int8", pb, default_l1, default_lInf, true); |
|
} |
|
|
|
TEST_P(Test_ONNX_nets, ResNet101_DUC_HDC) |
|
{ |
|
applyTestTag(CV_TEST_TAG_VERYLONG); |
|
|
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019010000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
#endif |
|
#if defined(INF_ENGINE_RELEASE) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 && target == DNN_TARGET_MYRIAD) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
#endif |
|
if (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_OPENCL) |
|
{ |
|
if (backend == DNN_BACKEND_OPENCV) |
|
applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_OPENCL : CV_TEST_TAG_DNN_SKIP_OPENCL_FP16); |
|
throw SkipTestException("Test is disabled for OpenCL targets"); |
|
} |
|
testONNXModels("resnet101_duc_hdc", pb); |
|
} |
|
|
|
TEST_P(Test_ONNX_nets, TinyYolov2) |
|
{ |
|
applyTestTag(CV_TEST_TAG_MEMORY_512MB); |
|
|
|
if (cvtest::skipUnstableTests) |
|
throw SkipTestException("Skip unstable test"); |
|
#if defined(INF_ENGINE_RELEASE) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 |
|
&& (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16) |
|
) |
|
applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
|
|
if (target == DNN_TARGET_MYRIAD && getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X |
|
) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD_X, |
|
backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 ? |
|
CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER : |
|
CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
#endif |
|
|
|
// output range: [-11; 8] |
|
double l1 = default_l1, lInf = default_lInf; |
|
if (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) |
|
{ |
|
l1 = 0.02; |
|
lInf = 0.2; |
|
} |
|
else if (target == DNN_TARGET_CUDA_FP16) |
|
{ |
|
l1 = 0.018; |
|
lInf = 0.16; |
|
} |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2020040000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_OPENCL_FP16) |
|
{ |
|
l1 = 0.018f; lInf = 0.16f; |
|
} |
|
#endif |
|
|
|
testONNXModels("tiny_yolo2", pb, l1, lInf); |
|
} |
|
|
|
TEST_P(Test_ONNX_nets, CNN_MNIST) |
|
{ |
|
// output range: [-1952; 6574], after Softmax [0; 1] |
|
testONNXModels("cnn_mnist", pb, default_l1, default_lInf, true); |
|
} |
|
|
|
TEST_P(Test_ONNX_nets, MobileNet_v2) |
|
{ |
|
// output range: [-166; 317], after Softmax [0; 1] |
|
testONNXModels("mobilenetv2", pb, default_l1, default_lInf, true); |
|
} |
|
|
|
TEST_P(Test_ONNX_nets, LResNet100E_IR) |
|
{ |
|
applyTestTag( |
|
#if defined(OPENCV_32BIT_CONFIGURATION) && defined(HAVE_OPENCL) |
|
CV_TEST_TAG_MEMORY_2GB, |
|
#else |
|
(target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_512MB : CV_TEST_TAG_MEMORY_1GB), |
|
#endif |
|
CV_TEST_TAG_DEBUG_LONG |
|
); |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
{ |
|
if (target == DNN_TARGET_OPENCL_FP16) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
if (target == DNN_TARGET_OPENCL) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
} |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
{ |
|
if (target == DNN_TARGET_OPENCL_FP16) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
if (target == DNN_TARGET_OPENCL) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
} |
|
|
|
double l1 = default_l1, lInf = default_lInf; |
|
// output range: [-3; 3] |
|
if (backend == DNN_BACKEND_OPENCV && target == DNN_TARGET_OPENCL_FP16) |
|
{ |
|
l1 = 0.009; |
|
lInf = 0.035; |
|
} |
|
else if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 && target == DNN_TARGET_CPU) |
|
{ |
|
l1 = 4.6e-5; |
|
lInf = 1.9e-4; |
|
} |
|
else if (target == DNN_TARGET_CUDA_FP16) |
|
{ |
|
l1 = 0.008; |
|
lInf = 0.04; |
|
} |
|
testONNXModels("LResNet100E_IR", pb, l1, lInf); |
|
} |
|
|
|
TEST_P(Test_ONNX_nets, Emotion_ferplus) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) |
|
if (target == DNN_TARGET_MYRIAD && getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD_X, |
|
backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 ? |
|
CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER : |
|
CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); |
|
#endif |
|
|
|
double l1 = default_l1; |
|
double lInf = default_lInf; |
|
|
|
// Output values are in range [-2.011, 2.111] |
|
if ((backend == DNN_BACKEND_OPENCV && target == DNN_TARGET_OPENCL_FP16) || (target == DNN_TARGET_CUDA_FP16)) |
|
l1 = 0.007; |
|
else if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 && target == DNN_TARGET_OPENCL_FP16) |
|
{ |
|
l1 = 0.021; |
|
lInf = 0.034; |
|
} |
|
else if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 && (target == DNN_TARGET_CPU || target == DNN_TARGET_OPENCL)) { |
|
l1 = 2.4e-4; |
|
lInf = 6e-4; |
|
} |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2020040000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_OPENCL_FP16) |
|
{ |
|
l1 = 0.013f; lInf = 0.035f; |
|
} |
|
#endif |
|
|
|
testONNXModels("emotion_ferplus", pb, l1, lInf); |
|
} |
|
|
|
TEST_P(Test_ONNX_nets, Inception_v2) |
|
{ |
|
testONNXModels("inception_v2", pb, default_l1, default_lInf, true); |
|
} |
|
|
|
TEST_P(Test_ONNX_nets, DenseNet121) |
|
{ |
|
applyTestTag(CV_TEST_TAG_MEMORY_512MB); |
|
|
|
// output range: [-87; 138], after Softmax [0; 1] |
|
testONNXModels("densenet121", pb, default_l1, default_lInf, true, target != DNN_TARGET_MYRIAD); |
|
} |
|
|
|
TEST_P(Test_ONNX_nets, Inception_v1) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LT(2021040000) |
|
if ((backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 || |
|
backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) && target == DNN_TARGET_MYRIAD) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD); |
|
#endif |
|
testONNXModels("inception_v1", pb); |
|
} |
|
|
|
TEST_P(Test_ONNX_nets, Shufflenet) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LT(2021040000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) |
|
{ |
|
if (target == DNN_TARGET_OPENCL_FP16) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
if (target == DNN_TARGET_OPENCL) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); |
|
} |
|
#endif |
|
testONNXModels("shufflenet", pb); |
|
} |
|
|
|
TEST_P(Test_ONNX_nets, Resnet34_kinetics) |
|
{ |
|
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000) |
|
// IE exception: Failed to allocate graph: MYRIAD device is not opened |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
// accuracy |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16)) |
|
applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, |
|
CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION |
|
); |
|
#elif defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2021040000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) |
|
{ |
|
// IE exception: Function contains several inputs and outputs with one friendly name! |
|
if (target == DNN_TARGET_MYRIAD) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); |
|
} |
|
#elif defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LT(2021040000) |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 && target != DNN_TARGET_CPU) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); // Only CPU on DLIE backend is supported |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target != DNN_TARGET_CPU) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); // Only CPU on DLIE backend is supported |
|
#endif |
|
if (backend == DNN_BACKEND_OPENCV && target != DNN_TARGET_CPU) |
|
throw SkipTestException("Only CPU is supported"); // FIXIT use tags |
|
|
|
if (backend == DNN_BACKEND_VKCOM) |
|
applyTestTag(CV_TEST_TAG_DNN_SKIP_VULKAN); |
|
|
|
String onnxmodel = findDataFile("dnn/resnet-34_kinetics.onnx", false); |
|
Mat image0 = imread(findDataFile("dnn/dog416.png")); |
|
Mat image1 = imread(findDataFile("dnn/street.png")); |
|
|
|
Mat ref0 = blobFromNPY(_tf("data/output_kinetics0.npy")); |
|
Mat ref1 = blobFromNPY(_tf("data/output_kinetics1.npy")); |
|
|
|
std::vector<Mat> images_0(16, image0); |
|
std::vector<Mat> images_1(16, image1); |
|
Mat blob0 = blobFromImages(images_0, 1.0, Size(112, 112), Scalar(114.7748, 107.7354, 99.4750), true, true); |
|
Mat blob1 = blobFromImages(images_1, 1.0, Size(112, 112), Scalar(114.7748, 107.7354, 99.4750), true, true); |
|
|
|
Net permute; |
|
LayerParams lp; |
|
int order[] = {1, 0, 2, 3}; |
|
lp.set("order", DictValue::arrayInt<int*>(&order[0], 4)); |
|
permute.addLayerToPrev("perm", "Permute", lp); |
|
|
|
permute.setPreferableBackend(backend); |
|
permute.setPreferableTarget(target); |
|
|
|
permute.setInput(blob0); |
|
Mat input0 = permute.forward().clone(); |
|
|
|
permute.setInput(blob1); |
|
Mat input1 = permute.forward().clone(); |
|
|
|
int dims[] = {1, 3, 16, 112, 112}; |
|
input0 = input0.reshape(0, 5, &dims[0]); |
|
input1 = input1.reshape(0, 5, &dims[0]); |
|
|
|
Net net = readNetFromONNX(onnxmodel); |
|
ASSERT_FALSE(net.empty()); |
|
net.setPreferableBackend(backend); |
|
net.setPreferableTarget(target); |
|
|
|
// output range [-5, 11] |
|
float l1 = 0.0013; |
|
float lInf = 0.009; |
|
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_OPENCL_FP16) |
|
{ |
|
l1 = 0.02; |
|
lInf = 0.07; |
|
} |
|
if (target == DNN_TARGET_CUDA_FP16) |
|
{ |
|
l1 = 0.01; |
|
lInf = 0.06; |
|
} |
|
|
|
checkBackend(&input0, &ref0); |
|
net.setInput(input0); |
|
Mat out = net.forward().clone(); |
|
normAssert(ref0, out, "", l1, lInf); |
|
|
|
checkBackend(&input1, &ref1); |
|
net.setInput(input1); |
|
out = net.forward().clone(); |
|
normAssert(ref1, out, "", l1, lInf); |
|
|
|
expectNoFallbacksFromIE(net); |
|
} |
|
|
|
TEST_P(Test_ONNX_layers, CumSum) |
|
{ |
|
testONNXModels("cumsum_1d_exclusive_1"); |
|
testONNXModels("cumsum_1d_reverse"); |
|
testONNXModels("cumsum_1d_exclusive_1_reverse"); |
|
testONNXModels("cumsum_2d_dim_1"); |
|
testONNXModels("cumsum_3d_dim_2"); |
|
} |
|
|
|
INSTANTIATE_TEST_CASE_P(/**/, Test_ONNX_nets, dnnBackendsAndTargets()); |
|
|
|
}} // namespace
|
|
|