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dnn(ocl4dnn): fuseLayer() use umat_input/outputBlobs for OpenCL target

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Also, fix bug when use OPENCL target but no OpenCL runtime

Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com>
pull/10164/head
Wu Zhiwen 7 years ago committed by Li Peng
parent a47fbd2610
commit 1f465a0ef9
1 changed files with 17 additions and 7 deletions
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  1. 24
      modules/dnn/src/dnn.cpp

24
modules/dnn/src/dnn.cpp
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@ -1196,7 +1196,8 @@ struct Net::Impl
// some other layers. // some other layers.
// TODO: OpenCL target support more fusion styles. // TODO: OpenCL target support more fusion styles.
if ( preferableTarget == DNN_TARGET_OPENCL && ld.layerInstance->type.compare("Convolution") ) if ( preferableTarget == DNN_TARGET_OPENCL &&
(!cv::ocl::useOpenCL() || ld.layerInstance->type.compare("Convolution")) )
continue; continue;
Ptr<Layer>& currLayer = ld.layerInstance; Ptr<Layer>& currLayer = ld.layerInstance;
@ -1214,7 +1215,10 @@ struct Net::Impl
{ {
printf_(("\tfused with %s\n", nextBNormLayer->name.c_str())); printf_(("\tfused with %s\n", nextBNormLayer->name.c_str()));
bnormData->skipFlags[DNN_BACKEND_DEFAULT] = true; bnormData->skipFlags[DNN_BACKEND_DEFAULT] = true;
ld.outputBlobs = layers[lpNext.lid].outputBlobs; if ( preferableTarget == DNN_TARGET_OPENCL )
ld.umat_outputBlobs = layers[lpNext.lid].umat_outputBlobs;
else
ld.outputBlobs = layers[lpNext.lid].outputBlobs;
if( bnormData->consumers.size() == 1 ) if( bnormData->consumers.size() == 1 )
{ {
nextData = &layers[bnormData->consumers[0].lid]; nextData = &layers[bnormData->consumers[0].lid];
@ -1234,7 +1238,10 @@ struct Net::Impl
{ {
printf_(("\tfused with %s\n", nextScaleLayer->name.c_str())); printf_(("\tfused with %s\n", nextScaleLayer->name.c_str()));
scaleData->skipFlags[DNN_BACKEND_DEFAULT] = true; scaleData->skipFlags[DNN_BACKEND_DEFAULT] = true;
ld.outputBlobs = layers[lpNext.lid].outputBlobs; if ( preferableTarget == DNN_TARGET_OPENCL )
ld.umat_outputBlobs = layers[lpNext.lid].umat_outputBlobs;
else
ld.outputBlobs = layers[lpNext.lid].outputBlobs;
if( scaleData->consumers.size() == 1 ) if( scaleData->consumers.size() == 1 )
{ {
nextData = &layers[scaleData->consumers[0].lid]; nextData = &layers[scaleData->consumers[0].lid];
@ -1263,7 +1270,10 @@ struct Net::Impl
LayerData *activData = nextData; LayerData *activData = nextData;
printf_(("\tfused with %s\n", nextActivLayer->name.c_str())); printf_(("\tfused with %s\n", nextActivLayer->name.c_str()));
activData->skipFlags[DNN_BACKEND_DEFAULT] = true; activData->skipFlags[DNN_BACKEND_DEFAULT] = true;
ld.outputBlobs = layers[lpNext.lid].outputBlobs; if ( preferableTarget == DNN_TARGET_OPENCL )
ld.umat_outputBlobs = layers[lpNext.lid].umat_outputBlobs;
else
ld.outputBlobs = layers[lpNext.lid].outputBlobs;
if ( preferableTarget == DNN_TARGET_OPENCL ) if ( preferableTarget == DNN_TARGET_OPENCL )
{ {
@ -1325,13 +1335,13 @@ struct Net::Impl
!nextData->type.compare("Power")) && !nextData->type.compare("Power")) &&
currLayer->setActivation(nextActivLayer) ) currLayer->setActivation(nextActivLayer) )
{ {
CV_Assert(firstConvLayerData->outputBlobs.size() == 1 && ld.inputBlobs.size() == 1); CV_Assert(firstConvLayerData->umat_outputBlobs.size() == 1 && ld.umat_inputBlobs.size() == 1);
ld.inputBlobs.push_back(&firstConvLayerData->outputBlobs[0]); ld.umat_inputBlobs.push_back(firstConvLayerData->umat_outputBlobs[0]);
printf_(("\tfused with %s\n", nextEltwiseLayer->name.c_str())); printf_(("\tfused with %s\n", nextEltwiseLayer->name.c_str()));
printf_(("\tfused with %s\n", nextActivLayer->name.c_str())); printf_(("\tfused with %s\n", nextActivLayer->name.c_str()));
eltwiseData->skipFlags[DNN_BACKEND_DEFAULT] = true; eltwiseData->skipFlags[DNN_BACKEND_DEFAULT] = true;
nextData->skipFlags[DNN_BACKEND_DEFAULT] = true; nextData->skipFlags[DNN_BACKEND_DEFAULT] = true;
ld.outputBlobs = layers[lpNext.lid].outputBlobs; ld.umat_outputBlobs = layers[lpNext.lid].umat_outputBlobs;
} }
} }
} }

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