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Make Inference Engine R3 as a minimal supported version

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pull/13884/head
Dmitry Kurtaev 6 years ago
parent 1db5d82b7f
commit ed710eaa1c
10 changed files with 3 additions and 89 deletions
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  1. 24
      modules/dnn/perf/perf_net.cpp
  2. 3
      modules/dnn/src/layers/convolution_layer.cpp
  3. 2
      modules/dnn/src/op_inf_engine.cpp
  4. 2
      modules/dnn/src/op_inf_engine.hpp
  5. 2
      modules/dnn/test/test_backends.cpp
  6. 20
      modules/dnn/test/test_common.hpp
  7. 5
      modules/dnn/test/test_halide_layers.cpp
  8. 8
      modules/dnn/test/test_layers.cpp
  9. 24
      modules/dnn/test/test_tf_importer.cpp
  10. 2
      modules/dnn/test/test_torch_importer.cpp

24
modules/dnn/perf/perf_net.cpp
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@ -162,24 +162,6 @@ PERF_TEST_P_(DNNTestNetwork, DenseNet_121)
Mat(cv::Size(224, 224), CV_32FC3));
}
PERF_TEST_P_(DNNTestNetwork, OpenPose_pose_coco)
{
if (backend == DNN_BACKEND_HALIDE ||
(backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD))
throw SkipTestException("");
processNet("dnn/openpose_pose_coco.caffemodel", "dnn/openpose_pose_coco.prototxt", "",
Mat(cv::Size(368, 368), CV_32FC3));
}
PERF_TEST_P_(DNNTestNetwork, OpenPose_pose_mpi)
{
if (backend == DNN_BACKEND_HALIDE ||
(backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD))
throw SkipTestException("");
processNet("dnn/openpose_pose_mpi.caffemodel", "dnn/openpose_pose_mpi.prototxt", "",
Mat(cv::Size(368, 368), CV_32FC3));
}
PERF_TEST_P_(DNNTestNetwork, OpenPose_pose_mpi_faster_4_stages)
{
if (backend == DNN_BACKEND_HALIDE ||
@ -219,11 +201,7 @@ PERF_TEST_P_(DNNTestNetwork, YOLOv3)
PERF_TEST_P_(DNNTestNetwork, EAST_text_detection)
{
if (backend == DNN_BACKEND_HALIDE
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_RELEASE < 2018030000
|| (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
#endif
)
if (backend == DNN_BACKEND_HALIDE)
throw SkipTestException("");
processNet("dnn/frozen_east_text_detection.pb", "", "", Mat(cv::Size(320, 320), CV_32FC3));
}

3
modules/dnn/src/layers/convolution_layer.cpp
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@ -1161,10 +1161,7 @@ public:
const int group = numOutput / outGroupCn;
if (group != 1)
{
#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2018R3)
return preferableTarget == DNN_TARGET_CPU;
#endif
return false;
}
if (preferableTarget == DNN_TARGET_OPENCL || preferableTarget == DNN_TARGET_OPENCL_FP16)
return dilation.width == 1 && dilation.height == 1;

2
modules/dnn/src/op_inf_engine.cpp
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@ -541,7 +541,6 @@ size_t InfEngineBackendNet::getBatchSize() const noexcept
return batchSize;
}
#if INF_ENGINE_VER_MAJOR_GT(INF_ENGINE_RELEASE_2018R2)
InferenceEngine::StatusCode InfEngineBackendNet::AddExtension(const InferenceEngine::IShapeInferExtensionPtr &extension, InferenceEngine::ResponseDesc *resp) noexcept
{
CV_Error(Error::StsNotImplemented, "");
@ -553,7 +552,6 @@ InferenceEngine::StatusCode InfEngineBackendNet::reshape(const InferenceEngine::
CV_Error(Error::StsNotImplemented, "");
return InferenceEngine::StatusCode::OK;
}
#endif
void InfEngineBackendNet::init(int targetId)
{

2
modules/dnn/src/op_inf_engine.hpp
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@ -22,8 +22,6 @@
//#pragma GCC diagnostic pop
#endif
#define INF_ENGINE_RELEASE_2018R1 2018010000
#define INF_ENGINE_RELEASE_2018R2 2018020000
#define INF_ENGINE_RELEASE_2018R3 2018030000
#define INF_ENGINE_RELEASE_2018R4 2018040000
#define INF_ENGINE_RELEASE_2018R5 2018050000

2
modules/dnn/test/test_backends.cpp
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@ -250,7 +250,7 @@ TEST_P(DNNTestNetwork, OpenPose_pose_mpi_faster_4_stages)
TEST_P(DNNTestNetwork, OpenFace)
{
#if defined(INF_ENGINE_RELEASE)
#if (INF_ENGINE_RELEASE < 2018030000 || INF_ENGINE_RELEASE == 2018050000)
#if INF_ENGINE_RELEASE == 2018050000
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
throw SkipTestException("");
#elif INF_ENGINE_RELEASE < 2018040000

20
modules/dnn/test/test_common.hpp
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@ -285,29 +285,9 @@ public:
{
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_RELEASE < 2018030000
if (inp && ref && inp->size[0] != 1)
{
// Myriad plugin supports only batch size 1. Slice a single sample.
if (inp->size[0] == ref->size[0])
{
std::vector<cv::Range> range(inp->dims, Range::all());
range[0] = Range(0, 1);
*inp = inp->operator()(range);
range = std::vector<cv::Range>(ref->dims, Range::all());
range[0] = Range(0, 1);
*ref = ref->operator()(range);
}
else
throw SkipTestException("Myriad plugin supports only batch size 1");
}
#else
if (inp && ref && inp->dims == 4 && ref->dims == 4 &&
inp->size[0] != 1 && inp->size[0] != ref->size[0])
throw SkipTestException("Inconsistent batch size of input and output blobs for Myriad plugin");
#endif
}
}

5
modules/dnn/test/test_halide_layers.cpp
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@ -93,11 +93,6 @@ TEST_P(Convolution, Accuracy)
Backend backendId = get<0>(get<7>(GetParam()));
Target targetId = get<1>(get<7>(GetParam()));
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_RELEASE < 2018030000
if (backendId == DNN_BACKEND_INFERENCE_ENGINE && targetId == DNN_TARGET_MYRIAD)
throw SkipTestException("Test is enabled starts from OpenVINO 2018R3");
#endif
bool skipCheck = false;
int sz[] = {outChannels, inChannels / group, kernel.height, kernel.width};

8
modules/dnn/test/test_layers.cpp
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@ -220,10 +220,6 @@ TEST(Layer_Test_Reshape, Accuracy)
TEST_P(Test_Caffe_layers, BatchNorm)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_RELEASE < 2018030000
if (backend == DNN_BACKEND_INFERENCE_ENGINE)
throw SkipTestException("Test is enabled starts from OpenVINO 2018R3");
#endif
testLayerUsingCaffeModels("layer_batch_norm", true);
testLayerUsingCaffeModels("layer_batch_norm_local_stats", true, false);
}
@ -741,10 +737,6 @@ INSTANTIATE_TEST_CASE_P(Layer_Test, Crop, Combine(
// into the normalization area.
TEST_P(Test_Caffe_layers, Average_pooling_kernel_area)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_RELEASE < 2018030000
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
throw SkipTestException("Test is enabled starts from OpenVINO 2018R3");
#endif
LayerParams lp;
lp.name = "testAvePool";
lp.type = "Pooling";

24
modules/dnn/test/test_tf_importer.cpp
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@ -147,10 +147,6 @@ TEST_P(Test_TensorFlow_layers, eltwise)
TEST_P(Test_TensorFlow_layers, pad_and_concat)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_RELEASE < 2018030000
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
throw SkipTestException("Test is enabled starts from OpenVINO 2018R3");
#endif
runTensorFlowNet("pad_and_concat");
}
@ -185,10 +181,6 @@ TEST_P(Test_TensorFlow_layers, pooling)
// TODO: fix tests and replace to pooling
TEST_P(Test_TensorFlow_layers, ave_pool_same)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_RELEASE < 2018030000
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
throw SkipTestException("Test is enabled starts from OpenVINO 2018R3");
#endif
runTensorFlowNet("ave_pool_same");
}
@ -453,11 +445,6 @@ TEST_P(Test_TensorFlow_nets, opencv_face_detector_uint8)
TEST_P(Test_TensorFlow_nets, EAST_text_detection)
{
checkBackend();
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_RELEASE < 2018030000
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
throw SkipTestException("Test is enabled starts from OpenVINO 2018R3");
#endif
std::string netPath = findDataFile("dnn/frozen_east_text_detection.pb", false);
std::string imgPath = findDataFile("cv/ximgproc/sources/08.png", false);
std::string refScoresPath = findDataFile("dnn/east_text_detection.scores.npy", false);
@ -516,17 +503,6 @@ TEST_P(Test_TensorFlow_layers, fp16_weights)
runTensorFlowNet("fp16_max_pool_odd_valid", false, l1, lInf);
runTensorFlowNet("fp16_max_pool_even", false, l1, lInf);
runTensorFlowNet("fp16_padding_same", false, l1, lInf);
}
// TODO: fix pad_and_concat and add this test case to fp16_weights
TEST_P(Test_TensorFlow_layers, fp16_pad_and_concat)
{
const float l1 = 0.00071;
const float lInf = 0.012;
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_RELEASE < 2018030000
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
throw SkipTestException("Test is enabled starts from OpenVINO 2018R3");
#endif
runTensorFlowNet("fp16_pad_and_concat", false, l1, lInf);
}

2
modules/dnn/test/test_torch_importer.cpp
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@ -272,7 +272,7 @@ class Test_Torch_nets : public DNNTestLayer {};
TEST_P(Test_Torch_nets, OpenFace_accuracy)
{
#if defined(INF_ENGINE_RELEASE) && (INF_ENGINE_RELEASE < 2018030000 || INF_ENGINE_RELEASE == 2018050000)
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_RELEASE == 2018050000
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
throw SkipTestException("");
#endif

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