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Enable some dnn tests according to the new Intel's Inference Engine release (R4)

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This commit is contained in:
Dmitry Kurtaev
2018-11-26 12:09:50 +03:00
parent ca5455c592
commit 84ce2cc211
5 changed files with 46 additions and 28 deletions
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modules/dnn/src/layers/elementwise_layers.cpp
+15 -7
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@@ -700,7 +700,8 @@ struct AbsValFunctor
bool supportBackend(int backendId, int)
{
return backendId == DNN_BACKEND_OPENCV || backendId == DNN_BACKEND_HALIDE;
return backendId == DNN_BACKEND_OPENCV || backendId == DNN_BACKEND_HALIDE ||
backendId == DNN_BACKEND_INFERENCE_ENGINE;
}
void apply(const float* srcptr, float* dstptr, int len, size_t planeSize, int cn0, int cn1) const
@@ -754,8 +755,11 @@ struct AbsValFunctor
#ifdef HAVE_INF_ENGINE
InferenceEngine::CNNLayerPtr initInfEngine(InferenceEngine::LayerParams& lp)
{
CV_Error(Error::StsNotImplemented, "Abs");
return InferenceEngine::CNNLayerPtr();
lp.type = "ReLU";
std::shared_ptr<InferenceEngine::ReLULayer> ieLayer(new InferenceEngine::ReLULayer(lp));
ieLayer->negative_slope = -1;
ieLayer->params["negative_slope"] = "-1.0";
return ieLayer;
}
#endif // HAVE_INF_ENGINE
@@ -832,7 +836,7 @@ struct PowerFunctor
bool supportBackend(int backendId, int targetId)
{
if (backendId == DNN_BACKEND_INFERENCE_ENGINE)
return (targetId != DNN_TARGET_OPENCL && targetId != DNN_TARGET_OPENCL_FP16) || power == 1.0;
return (targetId != DNN_TARGET_OPENCL && targetId != DNN_TARGET_OPENCL_FP16) || power == 1.0 || power == 0.5;
else
return backendId == DNN_BACKEND_OPENCV || backendId == DNN_BACKEND_HALIDE;
}
@@ -978,7 +982,8 @@ struct ChannelsPReLUFunctor
bool supportBackend(int backendId, int)
{
return backendId == DNN_BACKEND_OPENCV || backendId == DNN_BACKEND_HALIDE;
return backendId == DNN_BACKEND_OPENCV || backendId == DNN_BACKEND_HALIDE ||
backendId == DNN_BACKEND_INFERENCE_ENGINE;
}
void apply(const float* srcptr, float* dstptr, int len, size_t planeSize, int cn0, int cn1) const
@@ -1064,8 +1069,11 @@ struct ChannelsPReLUFunctor
#ifdef HAVE_INF_ENGINE
InferenceEngine::CNNLayerPtr initInfEngine(InferenceEngine::LayerParams& lp)
{
CV_Error(Error::StsNotImplemented, "PReLU");
return InferenceEngine::CNNLayerPtr();
lp.type = "PReLU";
std::shared_ptr<InferenceEngine::PReLULayer> ieLayer(new InferenceEngine::PReLULayer(lp));
const size_t numChannels = scale.total();
ieLayer->_weights = wrapToInfEngineBlob(scale, {numChannels}, InferenceEngine::Layout::C);
return ieLayer;
}
#endif // HAVE_INF_ENGINE