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dnn: use OpenVINO 2019R1 defines

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This commit is contained in:
Alexander Alekhin 2019-04-01 15:00:25 +03:00
parent d4a96b699e
commit 8483801eab
11 changed files with 28 additions and 27 deletions
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4
cmake/OpenCVDetectInferenceEngine.cmake
View File

@ -87,9 +87,9 @@ endif()
if(INF_ENGINE_TARGET)
if(NOT INF_ENGINE_RELEASE)
message(WARNING "InferenceEngine version have not been set, 2018R5 will be used by default. Set INF_ENGINE_RELEASE variable if you experience build errors.")
message(WARNING "InferenceEngine version have not been set, 2019R1 will be used by default. Set INF_ENGINE_RELEASE variable if you experience build errors.")
endif()
set(INF_ENGINE_RELEASE "2018050000" CACHE STRING "Force IE version, should be in form YYYYAABBCC (e.g. 2018R2.0.2 -> 2018020002)")
set(INF_ENGINE_RELEASE "2019010000" CACHE STRING "Force IE version, should be in form YYYYAABBCC (e.g. 2018R2.0.2 -> 2018020002)")
set_target_properties(${INF_ENGINE_TARGET} PROPERTIES
INTERFACE_COMPILE_DEFINITIONS "HAVE_INF_ENGINE=1;INF_ENGINE_RELEASE=${INF_ENGINE_RELEASE}"
)

2
modules/dnn/src/dnn.cpp
View File

@ -1637,7 +1637,7 @@ struct Net::Impl
preferableTarget == DNN_TARGET_MYRIAD ||
preferableTarget == DNN_TARGET_FPGA) && !fused)
{
#if INF_ENGINE_VER_MAJOR_GT(INF_ENGINE_RELEASE_2018R5)
#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2019R1)
for (const std::string& name : {"weights", "biases"})
{
auto it = ieNode->layer.getParameters().find(name);

2
modules/dnn/src/layers/normalize_bbox_layer.cpp
View File

@ -290,7 +290,7 @@ public:
weights = wrapToInfEngineBlob(blobs[0], {(size_t)numChannels}, InferenceEngine::Layout::C);
l.getParameters()["channel_shared"] = blobs[0].total() == 1;
}
#if INF_ENGINE_VER_MAJOR_GT(INF_ENGINE_RELEASE_2018R5)
#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2019R1)
l.getParameters()["weights"] = weights;
#else
l.addConstantData("weights", weights);

8
modules/dnn/src/op_inf_engine.cpp
View File

@ -130,7 +130,7 @@ void InfEngineBackendNet::init(int targetId)
for (int id : unconnectedLayersIds)
{
InferenceEngine::Builder::OutputLayer outLayer("myconv1");
#if INF_ENGINE_VER_MAJOR_GT(INF_ENGINE_RELEASE_2018R5)
#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2019R1)
// Inference Engine determines network precision by ports.
InferenceEngine::Precision p = (targetId == DNN_TARGET_MYRIAD ||
targetId == DNN_TARGET_OPENCL_FP16) ?
@ -188,7 +188,7 @@ void InfEngineBackendNet::init(int targetId)
void InfEngineBackendNet::addLayer(InferenceEngine::Builder::Layer& layer)
{
#if INF_ENGINE_VER_MAJOR_GT(INF_ENGINE_RELEASE_2018R5)
#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2019R1)
// Add weights to network and connect them after input blobs.
std::map<std::string, InferenceEngine::Parameter>& params = layer.getParameters();
std::vector<int> blobsIds;
@ -229,7 +229,7 @@ void InfEngineBackendNet::addLayer(InferenceEngine::Builder::Layer& layer)
CV_Assert(layers.insert({layerName, id}).second);
unconnectedLayersIds.insert(id);
#if INF_ENGINE_VER_MAJOR_GT(INF_ENGINE_RELEASE_2018R5)
#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2019R1)
// By default, all the weights are connected to last ports ids.
for (int i = 0; i < blobsIds.size(); ++i)
{
@ -903,7 +903,7 @@ InferenceEngine::Blob::Ptr convertFp16(const InferenceEngine::Blob::Ptr& blob)
void addConstantData(const std::string& name, InferenceEngine::Blob::Ptr data,
InferenceEngine::Builder::Layer& l)
{
#if INF_ENGINE_VER_MAJOR_GT(INF_ENGINE_RELEASE_2018R5)
#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2019R1)
l.getParameters()[name] = data;
#else
l.addConstantData(name, data);

5
modules/dnn/src/op_inf_engine.hpp
View File

@ -27,10 +27,11 @@
#define INF_ENGINE_RELEASE_2018R3 2018030000
#define INF_ENGINE_RELEASE_2018R4 2018040000
#define INF_ENGINE_RELEASE_2018R5 2018050000
#define INF_ENGINE_RELEASE_2019R1 2019010000
#ifndef INF_ENGINE_RELEASE
#warning("IE version have not been provided via command-line. Using 2018R5 by default")
#define INF_ENGINE_RELEASE INF_ENGINE_RELEASE_2018R5
#warning("IE version have not been provided via command-line. Using 2019R1 by default")
#define INF_ENGINE_RELEASE INF_ENGINE_RELEASE_2019R1
#endif
#define INF_ENGINE_VER_MAJOR_GT(ver) (((INF_ENGINE_RELEASE) / 10000) > ((ver) / 10000))

2
modules/dnn/test/test_backends.cpp
View File

@ -289,7 +289,7 @@ TEST_P(DNNTestNetwork, OpenFace)
#if INF_ENGINE_VER_MAJOR_EQ(2018050000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
throw SkipTestException("Test is disabled for Myriad targets");
#elif INF_ENGINE_VER_MAJOR_GT(2018050000)
#elif INF_ENGINE_VER_MAJOR_GE(2019010000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD
&& getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X
)

2
modules/dnn/test/test_darknet_importer.cpp
View File

@ -267,7 +267,7 @@ public:
TEST_P(Test_Darknet_nets, YoloVoc)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2018050000)
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019010000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_OPENCL_FP16)
throw SkipTestException("Test is disabled");
#endif

12
modules/dnn/test/test_halide_layers.cpp
View File

@ -169,7 +169,7 @@ TEST_P(Deconvolution, Accuracy)
throw SkipTestException("Test is disabled for OpenVINO 2018R4");
#endif
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2018050000)
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019010000)
if (backendId == DNN_BACKEND_INFERENCE_ENGINE && targetId == DNN_TARGET_MYRIAD
&& getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X
&& inChannels == 6 && outChannels == 4 && group == 1
@ -351,7 +351,7 @@ TEST_P(MaxPooling, Accuracy)
throw SkipTestException("Problems with output dimension in OpenVINO 2018R5");
#endif
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2018050000)
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019010000)
if (backendId == DNN_BACKEND_INFERENCE_ENGINE && targetId == DNN_TARGET_MYRIAD
&& getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X
&& (stride == Size(1, 1) || stride == Size(2, 2))
@ -561,7 +561,7 @@ TEST_P(ReLU, Accuracy)
float negativeSlope = get<0>(GetParam());
Backend backendId = get<0>(get<1>(GetParam()));
Target targetId = get<1>(get<1>(GetParam()));
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2018050000)
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019010000)
if (backendId == DNN_BACKEND_INFERENCE_ENGINE
&& negativeSlope < 0
)
@ -589,7 +589,7 @@ TEST_P(NoParamActivation, Accuracy)
LayerParams lp;
lp.type = get<0>(GetParam());
lp.name = "testLayer";
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2018050000)
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019010000)
if (backendId == DNN_BACKEND_INFERENCE_ENGINE
&& lp.type == "AbsVal"
)
@ -688,7 +688,7 @@ TEST_P(Concat, Accuracy)
throw SkipTestException("Test is disabled for Myriad target"); // crash
#endif
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2018050000)
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019010000)
if (backendId == DNN_BACKEND_INFERENCE_ENGINE && targetId == DNN_TARGET_CPU
&& inSize == Vec3i(1, 4, 5) && numChannels == Vec3i(1, 6, 2)
)
@ -769,7 +769,7 @@ TEST_P(Eltwise, Accuracy)
throw SkipTestException("Test is disabled for Myriad target");
#endif
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2018050000)
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019010000)
if (backendId == DNN_BACKEND_INFERENCE_ENGINE && numConv > 1)
throw SkipTestException("Test is disabled for DLIE backend");
#endif

4
modules/dnn/test/test_layers.cpp
View File

@ -236,7 +236,7 @@ TEST_P(Test_Caffe_layers, Dropout)
TEST_P(Test_Caffe_layers, Concat)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2018050000)
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019010000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
throw SkipTestException("Test is disabled for Myriad targets");
#endif
@ -247,7 +247,7 @@ TEST_P(Test_Caffe_layers, Concat)
TEST_P(Test_Caffe_layers, Fused_Concat)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2018050000)
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019010000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE)
throw SkipTestException("Test is disabled for DLIE due negative_slope parameter");
#endif

2
modules/dnn/test/test_onnx_importer.cpp
View File

@ -319,7 +319,7 @@ TEST_P(Test_ONNX_nets, ResNet50v1)
TEST_P(Test_ONNX_nets, ResNet101_DUC_HDC)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2018050000)
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019010000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE)
throw SkipTestException("Test is disabled for DLIE targets");
#endif

12
modules/dnn/test/test_tf_importer.cpp
View File

@ -140,7 +140,7 @@ TEST_P(Test_TensorFlow_layers, padding)
TEST_P(Test_TensorFlow_layers, padding_same)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2018050000)
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019010000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE)
throw SkipTestException("Test is disabled for DLIE");
#endif
@ -197,7 +197,7 @@ TEST_P(Test_TensorFlow_layers, pooling)
TEST_P(Test_TensorFlow_layers, ave_pool_same)
{
// Reference output values are in range [-0.519531, 0.112976]
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2018050000)
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019010000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD
&& getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X
)
@ -241,7 +241,7 @@ TEST_P(Test_TensorFlow_layers, reshape)
TEST_P(Test_TensorFlow_layers, flatten)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2018050000)
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019010000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE)
throw SkipTestException("Test is disabled for DLIE");
#endif
@ -257,7 +257,7 @@ TEST_P(Test_TensorFlow_layers, flatten)
TEST_P(Test_TensorFlow_layers, unfused_flatten)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2018050000)
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019010000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE)
throw SkipTestException("Test is disabled for DLIE");
#endif
@ -279,7 +279,7 @@ TEST_P(Test_TensorFlow_layers, leaky_relu)
TEST_P(Test_TensorFlow_layers, l2_normalize)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2018050000)
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019010000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD
&& getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X
)
@ -587,7 +587,7 @@ TEST_P(Test_TensorFlow_layers, fp16_weights)
TEST_P(Test_TensorFlow_layers, fp16_padding_same)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2018050000)
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019010000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE)
throw SkipTestException("Test is disabled for DLIE");
#endif