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Merge pull request #15184 from l-bat:IE_R2

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Support new IE API (#15184)

* Add support OpenVINO R2 for layers

* Add Core API

* Fix tests

* Fix expectNoFallbacksFromIE for ONNX nets

* Remove deprecated API

* Remove td

* Remove TargetDevice

* Fix Async

* Add test

* Fix detectMyriadX

* Fix test

* Fix warning
This commit is contained in:
Lubov Batanina
2019-08-06 22:20:26 +03:00
committed by Alexander Alekhin
parent cf93a05d2d
commit 0e1ef8f8e1
13 changed files with 247 additions and 130 deletions
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modules/dnn/test/test_ie_models.cpp
+27 -13
View File
@@ -136,13 +136,10 @@ static const std::vector<std::string> getOpenVINOTestModelsList()
static inline void genData(const std::vector<size_t>& dims, Mat& m, Blob::Ptr& dataPtr)
{
std::vector<int> reversedDims(dims.begin(), dims.end());
std::reverse(reversedDims.begin(), reversedDims.end());
m.create(reversedDims, CV_32F);
m.create(std::vector<int>(dims.begin(), dims.end()), CV_32F);
randu(m, -1, 1);
dataPtr = make_shared_blob<float>(Precision::FP32, dims, (float*)m.data);
dataPtr = make_shared_blob<float>({Precision::FP32, dims, Layout::ANY}, (float*)m.data);
}
void runIE(Target target, const std::string& xmlPath, const std::string& binPath,
@@ -154,32 +151,42 @@ void runIE(Target target, const std::string& xmlPath, const std::string& binPath
CNNNetwork net = reader.getNetwork();
std::string device_name;
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2019010000)
Core ie;
#else
InferenceEnginePluginPtr enginePtr;
InferencePlugin plugin;
#endif
ExecutableNetwork netExec;
InferRequest infRequest;
try
{
auto dispatcher = InferenceEngine::PluginDispatcher({""});
switch (target)
{
case DNN_TARGET_CPU:
enginePtr = dispatcher.getSuitablePlugin(TargetDevice::eCPU);
device_name = "CPU";
break;
case DNN_TARGET_OPENCL:
case DNN_TARGET_OPENCL_FP16:
enginePtr = dispatcher.getSuitablePlugin(TargetDevice::eGPU);
device_name = "GPU";
break;
case DNN_TARGET_MYRIAD:
enginePtr = dispatcher.getSuitablePlugin(TargetDevice::eMYRIAD);
device_name = "MYRIAD";
break;
case DNN_TARGET_FPGA:
enginePtr = dispatcher.getPluginByDevice("HETERO:FPGA,CPU");
device_name = "FPGA";
break;
default:
CV_Error(Error::StsNotImplemented, "Unknown target");
};
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LE(2019010000)
auto dispatcher = InferenceEngine::PluginDispatcher({""});
enginePtr = dispatcher.getPluginByDevice(device_name);
#endif
if (target == DNN_TARGET_CPU || target == DNN_TARGET_FPGA)
{
std::string suffixes[] = {"_avx2", "_sse4", ""};
@@ -202,16 +209,23 @@ void runIE(Target target, const std::string& xmlPath, const std::string& binPath
try
{
IExtensionPtr extension = make_so_pointer<IExtension>(libName);
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2019010000)
ie.AddExtension(extension, device_name);
#else
enginePtr->AddExtension(extension, 0);
#endif
break;
}
catch(...) {}
}
// Some of networks can work without a library of extra layers.
}
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2019010000)
netExec = ie.LoadNetwork(net, device_name);
#else
plugin = InferencePlugin(enginePtr);
netExec = plugin.LoadNetwork(net, {});
#endif
infRequest = netExec.CreateInferRequest();
}
catch (const std::exception& ex)
@@ -224,7 +238,7 @@ void runIE(Target target, const std::string& xmlPath, const std::string& binPath
BlobMap inputBlobs;
for (auto& it : net.getInputsInfo())
{
genData(it.second->getDims(), inputsMap[it.first], inputBlobs[it.first]);
genData(it.second->getTensorDesc().getDims(), inputsMap[it.first], inputBlobs[it.first]);
}
infRequest.SetInput(inputBlobs);
@@ -233,7 +247,7 @@ void runIE(Target target, const std::string& xmlPath, const std::string& binPath
BlobMap outputBlobs;
for (auto& it : net.getOutputsInfo())
{
genData(it.second->dims, outputsMap[it.first], outputBlobs[it.first]);
genData(it.second->getTensorDesc().getDims(), outputsMap[it.first], outputBlobs[it.first]);
}
infRequest.SetOutput(outputBlobs);
modules/dnn/test/test_misc.cpp
+36
View File
@@ -467,6 +467,42 @@ INSTANTIATE_TEST_CASE_P(/**/, Async, Combine(
Values(CV_32F, CV_8U),
testing::ValuesIn(getAvailableTargets(DNN_BACKEND_INFERENCE_ENGINE))
));
typedef testing::TestWithParam<Target> Test_Model_Optimizer;
TEST_P(Test_Model_Optimizer, forward_two_nets)
{
const int target = GetParam();
const std::string suffix = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? "_fp16" : "";
const std::string& model = findDataFile("dnn/layers/layer_convolution" + suffix + ".bin");
const std::string& proto = findDataFile("dnn/layers/layer_convolution" + suffix + ".xml");
Net net0 = readNet(model, proto);
net0.setPreferableTarget(target);
Net net1 = readNet(model, proto);
net1.setPreferableTarget(target);
// Generate inputs.
int blobSize[] = {2, 6, 75, 113};
Mat input(4, &blobSize[0], CV_32F);
randu(input, 0, 255);
net0.setInput(input);
Mat ref0 = net0.forward().clone();
net1.setInput(input);
Mat ref1 = net1.forward();
net0.setInput(input);
Mat ref2 = net0.forward();
normAssert(ref0, ref2, 0, 0);
}
INSTANTIATE_TEST_CASE_P(/**/, Test_Model_Optimizer,
testing::ValuesIn(getAvailableTargets(DNN_BACKEND_INFERENCE_ENGINE))
);
#endif // HAVE_INF_ENGINE
}} // namespace