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Code Packages Releases Wiki Activity

Move Inference Engine to new API

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This commit is contained in:
Dmitry Kurtaev
2019-01-14 09:55:44 +03:00
parent 4ced27e149
commit f0ddf302b2
34 changed files with 852 additions and 80 deletions
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modules/dnn/src/layers/elementwise_layers.cpp
+74
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@@ -152,10 +152,16 @@ public:
virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> >&) CV_OVERRIDE
{
#ifdef HAVE_INF_ENGINE
#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2018R5)
InferenceEngine::Builder::Layer ieLayer = func.initInfEngineBuilderAPI();
ieLayer.setName(this->name);
return Ptr<BackendNode>(new InfEngineBackendNode(ieLayer));
#else
InferenceEngine::LayerParams lp;
lp.name = this->name;
lp.precision = InferenceEngine::Precision::FP32;
return Ptr<BackendNode>(new InfEngineBackendNode(func.initInfEngine(lp)));
#endif
#endif // HAVE_INF_ENGINE
return Ptr<BackendNode>();
}
@@ -345,6 +351,12 @@ struct ReLUFunctor
#endif // HAVE_HALIDE
#ifdef HAVE_INF_ENGINE
#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2018R5)
InferenceEngine::Builder::Layer initInfEngineBuilderAPI()
{
return InferenceEngine::Builder::ReLULayer("").setNegativeSlope(slope);
}
#else
InferenceEngine::CNNLayerPtr initInfEngine(InferenceEngine::LayerParams& lp)
{
lp.type = "ReLU";
@@ -353,6 +365,7 @@ struct ReLUFunctor
ieLayer->params["negative_slope"] = format("%f", slope);
return ieLayer;
}
#endif
#endif // HAVE_INF_ENGINE
bool tryFuse(Ptr<dnn::Layer>&) { return false; }
@@ -452,6 +465,12 @@ struct ReLU6Functor
#endif // HAVE_HALIDE
#ifdef HAVE_INF_ENGINE
#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2018R5)
InferenceEngine::Builder::Layer initInfEngineBuilderAPI()
{
return InferenceEngine::Builder::ClampLayer("").setMinValue(minValue).setMaxValue(maxValue);
}
#else
InferenceEngine::CNNLayerPtr initInfEngine(InferenceEngine::LayerParams& lp)
{
lp.type = "Clamp";
@@ -462,6 +481,7 @@ struct ReLU6Functor
ieLayer->params["max"] = format("%f", maxValue);
return ieLayer;
}
#endif
#endif // HAVE_INF_ENGINE
bool tryFuse(Ptr<dnn::Layer>&) { return false; }
@@ -530,12 +550,19 @@ struct TanHFunctor
#endif // HAVE_HALIDE
#ifdef HAVE_INF_ENGINE
#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2018R5)
InferenceEngine::Builder::Layer initInfEngineBuilderAPI()
{
return InferenceEngine::Builder::TanHLayer("");
}
#else
InferenceEngine::CNNLayerPtr initInfEngine(InferenceEngine::LayerParams& lp)
{
lp.type = "TanH";
std::shared_ptr<InferenceEngine::CNNLayer> ieLayer(new InferenceEngine::CNNLayer(lp));
return ieLayer;
}
#endif
#endif // HAVE_INF_ENGINE
bool tryFuse(Ptr<dnn::Layer>&) { return false; }
@@ -604,12 +631,19 @@ struct SigmoidFunctor
#endif // HAVE_HALIDE
#ifdef HAVE_INF_ENGINE
#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2018R5)
InferenceEngine::Builder::Layer initInfEngineBuilderAPI()
{
return InferenceEngine::Builder::SigmoidLayer("");
}
#else
InferenceEngine::CNNLayerPtr initInfEngine(InferenceEngine::LayerParams& lp)
{
lp.type = "Sigmoid";
std::shared_ptr<InferenceEngine::CNNLayer> ieLayer(new InferenceEngine::CNNLayer(lp));
return ieLayer;
}
#endif
#endif // HAVE_INF_ENGINE
bool tryFuse(Ptr<dnn::Layer>&) { return false; }
@@ -680,11 +714,18 @@ struct ELUFunctor
#endif // HAVE_HALIDE
#ifdef HAVE_INF_ENGINE
#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2018R5)
InferenceEngine::Builder::Layer initInfEngineBuilderAPI()
{
return InferenceEngine::Builder::ELULayer("");
}
#else
InferenceEngine::CNNLayerPtr initInfEngine(InferenceEngine::LayerParams& lp)
{
lp.type = "ELU";
return InferenceEngine::CNNLayerPtr(new InferenceEngine::CNNLayer(lp));
}
#endif
#endif // HAVE_INF_ENGINE
bool tryFuse(Ptr<dnn::Layer>&) { return false; }
@@ -753,6 +794,12 @@ struct AbsValFunctor
#endif // HAVE_HALIDE
#ifdef HAVE_INF_ENGINE
#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2018R5)
InferenceEngine::Builder::Layer initInfEngineBuilderAPI()
{
return InferenceEngine::Builder::ReLULayer("").setNegativeSlope(-1);
}
#else
InferenceEngine::CNNLayerPtr initInfEngine(InferenceEngine::LayerParams& lp)
{
lp.type = "ReLU";
@@ -761,6 +808,7 @@ struct AbsValFunctor
ieLayer->params["negative_slope"] = "-1.0";
return ieLayer;
}
#endif
#endif // HAVE_INF_ENGINE
bool tryFuse(Ptr<dnn::Layer>&) { return false; }
@@ -808,11 +856,18 @@ struct BNLLFunctor
#endif // HAVE_HALIDE
#ifdef HAVE_INF_ENGINE
#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2018R5)
InferenceEngine::Builder::Layer initInfEngineBuilderAPI()
{
CV_Error(Error::StsNotImplemented, "");
}
#else
InferenceEngine::CNNLayerPtr initInfEngine(InferenceEngine::LayerParams& lp)
{
CV_Error(Error::StsNotImplemented, "BNLL");
return InferenceEngine::CNNLayerPtr();
}
#endif
#endif // HAVE_INF_ENGINE
bool tryFuse(Ptr<dnn::Layer>&) { return false; }
@@ -917,6 +972,14 @@ struct PowerFunctor
#endif // HAVE_HALIDE
#ifdef HAVE_INF_ENGINE
#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2018R5)
InferenceEngine::Builder::Layer initInfEngineBuilderAPI()
{
return InferenceEngine::Builder::PowerLayer("").setPower(power)
.setScale(scale)
.setShift(shift);
}
#else
InferenceEngine::CNNLayerPtr initInfEngine(InferenceEngine::LayerParams& lp)
{
if (power == 1.0f && scale == 1.0f && shift == 0.0f)
@@ -936,6 +999,7 @@ struct PowerFunctor
return ieLayer;
}
}
#endif
#endif // HAVE_INF_ENGINE
bool tryFuse(Ptr<dnn::Layer>& top)
@@ -1067,6 +1131,15 @@ struct ChannelsPReLUFunctor
#endif // HAVE_HALIDE
#ifdef HAVE_INF_ENGINE
#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2018R5)
InferenceEngine::Builder::Layer initInfEngineBuilderAPI()
{
InferenceEngine::Builder::PReLULayer ieLayer("");
const size_t numChannels = scale.total();
ieLayer.setWeights(wrapToInfEngineBlob(scale, {numChannels}, InferenceEngine::Layout::C));
return ieLayer;
}
#else
InferenceEngine::CNNLayerPtr initInfEngine(InferenceEngine::LayerParams& lp)
{
lp.type = "PReLU";
@@ -1075,6 +1148,7 @@ struct ChannelsPReLUFunctor
ieLayer->_weights = wrapToInfEngineBlob(scale, {numChannels}, InferenceEngine::Layout::C);
return ieLayer;
}
#endif
#endif // HAVE_INF_ENGINE
bool tryFuse(Ptr<dnn::Layer>&) { return false; }