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dnn: use inheritance for OpenVINO net impl

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This commit is contained in:
Alexander Alekhin
2022-03-07 22:26:20 +00:00
parent b26fc6f31b
commit ca7f964104
14 changed files with 413 additions and 133 deletions
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79
modules/dnn/src/net_impl.cpp
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@@ -30,6 +30,12 @@ std::string detail::NetImplBase::getDumpFileNameBase() const
}
Net::Impl::~Impl()
{
// nothing
}
Net::Impl::Impl()
{
// allocate fake net input layer
@@ -46,9 +52,8 @@ Net::Impl::Impl()
netWasQuantized = false;
fusion = true;
isAsync = false;
preferableBackend = DNN_BACKEND_DEFAULT;
preferableBackend = (Backend)getParam_DNN_BACKEND_DEFAULT();
preferableTarget = DNN_TARGET_CPU;
skipInfEngineInit = false;
hasDynamicShapes = false;
}
@@ -86,22 +91,10 @@ void Net::Impl::clear()
}
void Net::Impl::setUpNet(const std::vector<LayerPin>& blobsToKeep_)
void Net::Impl::validateBackendAndTarget()
{
CV_TRACE_FUNCTION();
if (dumpLevel && networkDumpCounter == 0)
{
dumpNetworkToFile();
}
if (preferableBackend == DNN_BACKEND_DEFAULT)
preferableBackend = (Backend)getParam_DNN_BACKEND_DEFAULT();
#ifdef HAVE_INF_ENGINE
if (preferableBackend == DNN_BACKEND_INFERENCE_ENGINE)
preferableBackend = DNN_BACKEND_INFERENCE_ENGINE_NGRAPH; // = getInferenceEngineBackendTypeParam();
#endif
CV_Assert(preferableBackend != DNN_BACKEND_OPENCV ||
preferableTarget == DNN_TARGET_CPU ||
preferableTarget == DNN_TARGET_OPENCL ||
@@ -109,19 +102,6 @@ void Net::Impl::setUpNet(const std::vector<LayerPin>& blobsToKeep_)
CV_Assert(preferableBackend != DNN_BACKEND_HALIDE ||
preferableTarget == DNN_TARGET_CPU ||
preferableTarget == DNN_TARGET_OPENCL);
#ifdef HAVE_INF_ENGINE
if (preferableBackend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH)
{
CV_Assert(
(preferableTarget == DNN_TARGET_CPU && (!isArmComputePlugin() || preferableBackend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH)) ||
preferableTarget == DNN_TARGET_OPENCL ||
preferableTarget == DNN_TARGET_OPENCL_FP16 ||
preferableTarget == DNN_TARGET_MYRIAD ||
preferableTarget == DNN_TARGET_HDDL ||
preferableTarget == DNN_TARGET_FPGA
);
}
#endif
#ifdef HAVE_WEBNN
if (preferableBackend == DNN_BACKEND_WEBNN)
{
@@ -136,6 +116,20 @@ void Net::Impl::setUpNet(const std::vector<LayerPin>& blobsToKeep_)
CV_Assert(preferableBackend != DNN_BACKEND_TIMVX ||
preferableTarget == DNN_TARGET_NPU);
CV_Assert(preferableBackend != DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && "Inheritance internal error");
}
void Net::Impl::setUpNet(const std::vector<LayerPin>& blobsToKeep_)
{
CV_TRACE_FUNCTION();
if (dumpLevel && networkDumpCounter == 0)
{
dumpNetworkToFile();
}
validateBackendAndTarget();
if (!netWasAllocated || this->blobsToKeep != blobsToKeep_)
{
if (preferableBackend == DNN_BACKEND_OPENCV && IS_DNN_OPENCL_TARGET(preferableTarget))
@@ -813,12 +807,10 @@ void Net::Impl::forwardLayer(LayerData& ld)
{
forwardHalide(ld.outputBlobsWrappers, node);
}
#ifdef HAVE_INF_ENGINE
else if (preferableBackend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH)
{
forwardNgraph(ld.outputBlobsWrappers, node, isAsync);
CV_Assert(preferableBackend != DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && "Inheritance internal error");
}
#endif
else if (preferableBackend == DNN_BACKEND_WEBNN)
{
forwardWebnn(ld.outputBlobsWrappers, node, isAsync);
@@ -844,7 +836,7 @@ void Net::Impl::forwardLayer(LayerData& ld)
#endif
else
{
CV_Error(Error::StsNotImplemented, "Unknown backend identifier");
CV_Error(Error::StsNotImplemented, cv::format("Unknown backend identifier: %d", preferableBackend));
}
}
@@ -1369,30 +1361,7 @@ Mat Net::Impl::getBlob(String outputName) const
AsyncArray Net::Impl::getBlobAsync(const LayerPin& pin)
{
CV_TRACE_FUNCTION();
#ifdef HAVE_INF_ENGINE
if (!pin.valid())
CV_Error(Error::StsObjectNotFound, "Requested blob not found");
LayerData& ld = layers[pin.lid];
if ((size_t)pin.oid >= ld.outputBlobs.size())
{
CV_Error(Error::StsOutOfRange, format("Layer \"%s\" produce only %d outputs, "
"the #%d was requested",
ld.name.c_str(), (int)ld.outputBlobs.size(), (int)pin.oid));
}
if (preferableTarget != DNN_TARGET_CPU)
{
CV_Assert(!ld.outputBlobsWrappers.empty() && !ld.outputBlobsWrappers[pin.oid].empty());
// Transfer data to CPU if it's require.
ld.outputBlobsWrappers[pin.oid]->copyToHost();
}
CV_Assert(preferableBackend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH);
Ptr<NgraphBackendWrapper> wrapper = ld.outputBlobsWrappers[pin.oid].dynamicCast<NgraphBackendWrapper>();
return std::move(wrapper->futureMat);
#else
CV_Error(Error::StsNotImplemented, "DNN: OpenVINO/nGraph backend is required");
#endif // HAVE_INF_ENGINE
}