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Merge pull request #10164 from pengli:dnn

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This commit is contained in:
Alexander Alekhin
2017-11-29 12:05:10 +00:00
parent f5dba12762 1f465a0ef9
commit cc2ee923e4
4 changed files with 219 additions and 7 deletions
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modules/dnn/src/dnn.cpp
+17 -7
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@@ -1196,7 +1196,8 @@ struct Net::Impl
// some other layers.
// 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;
Ptr<Layer>& currLayer = ld.layerInstance;
@@ -1214,7 +1215,10 @@ struct Net::Impl
{
printf_(("\tfused with %s\n", nextBNormLayer->name.c_str()));
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 )
{
nextData = &layers[bnormData->consumers[0].lid];
@@ -1234,7 +1238,10 @@ struct Net::Impl
{
printf_(("\tfused with %s\n", nextScaleLayer->name.c_str()));
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 )
{
nextData = &layers[scaleData->consumers[0].lid];
@@ -1263,7 +1270,10 @@ struct Net::Impl
LayerData *activData = nextData;
printf_(("\tfused with %s\n", nextActivLayer->name.c_str()));
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 )
{
@@ -1325,13 +1335,13 @@ struct Net::Impl
!nextData->type.compare("Power")) &&
currLayer->setActivation(nextActivLayer) )
{
CV_Assert(firstConvLayerData->outputBlobs.size() == 1 && ld.inputBlobs.size() == 1);
ld.inputBlobs.push_back(&firstConvLayerData->outputBlobs[0]);
CV_Assert(firstConvLayerData->umat_outputBlobs.size() == 1 && ld.umat_inputBlobs.size() == 1);
ld.umat_inputBlobs.push_back(firstConvLayerData->umat_outputBlobs[0]);
printf_(("\tfused with %s\n", nextEltwiseLayer->name.c_str()));
printf_(("\tfused with %s\n", nextActivLayer->name.c_str()));
eltwiseData->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;
}
}
}