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dnn(opencl): bypass unsupported fusion cases 2

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This commit is contained in:
Alexander Alekhin 2020-10-09 16:33:48 +00:00
parent 083727b0a6
commit cdcf7e62f3
3 changed files with 50 additions and 19 deletions
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59
modules/dnn/src/dnn.cpp
View File

@ -2413,14 +2413,42 @@ struct Net::Impl : public detail::NetImplBase
}
// fuse convolution layer followed by eltwise + relu
if ( IS_DNN_OPENCL_TARGET(preferableTarget) && ld.layerInstance->type == "Convolution" )
while (nextData && IS_DNN_OPENCL_TARGET(preferableTarget) && ld.layerInstance->type == "Convolution") // semantic of 'if'
{
Ptr<EltwiseLayer> nextEltwiseLayer;
if( nextData )
nextEltwiseLayer = nextData->layerInstance.dynamicCast<EltwiseLayer>();
Ptr<EltwiseLayer> nextEltwiseLayer = nextData->layerInstance.dynamicCast<EltwiseLayer>();
if (nextEltwiseLayer.empty())
break;
if (pinsToKeep.count(lpNext) != 0)
break;
if (nextData->inputBlobsId.size() != 2)
break;
if (!nextData->params.has("operation") || nextData->params.get<String>("operation").toLowerCase() == "sum")
{
if (nextData->params.has("coeff"))
{
DictValue paramCoeff = nextData->params.get("coeff");
int n = paramCoeff.size();
bool isCoeffOneOne = (n == 2);
for (int i = 0; isCoeffOneOne && i < n; i++)
{
float c = paramCoeff.get<float>(i);
isCoeffOneOne &= (c == 1.0f);
}
if (!isCoeffOneOne)
{
CV_LOG_DEBUG(NULL, "DNN/OpenCL: fusion of 'Sum' without coeffs (or {1.0, 1.0}) is supported only");
break;
}
}
}
else
{
CV_LOG_DEBUG(NULL, "DNN/OpenCL: fusion with eltwise operation is not supported: " << nextData->params.get<String>("operation"));
break;
}
if( !nextEltwiseLayer.empty() && pinsToKeep.count(lpNext) == 0 &&
nextData && nextData->inputBlobsId.size() == 2 )
{
LayerData *eltwiseData = nextData;
@ -2517,6 +2545,8 @@ struct Net::Impl : public detail::NetImplBase
}
}
}
break;
}
}
@ -2698,11 +2728,11 @@ struct Net::Impl : public detail::NetImplBase
Ptr<Layer> layer = ld.layerInstance;
TickMeter tm;
tm.start();
if( !ld.skip )
{
TickMeter tm;
tm.start();
std::map<int, Ptr<BackendNode> >::iterator it = ld.backendNodes.find(preferableBackend);
if (preferableBackend == DNN_BACKEND_OPENCV || it == ld.backendNodes.end() || it->second.empty())
{
@ -2881,12 +2911,15 @@ struct Net::Impl : public detail::NetImplBase
CV_Error(Error::StsNotImplemented, "Unknown backend identifier");
}
}
tm.stop();
int64 t = tm.getTimeTicks();
layersTimings[ld.id] = (t > 0) ? t : t + 1; // zero for skipped layers only
}
else
tm.reset();
tm.stop();
layersTimings[ld.id] = tm.getTimeTicks();
{
layersTimings[ld.id] = 0;
}
ld.flag = 1;
}

2
modules/dnn/src/layers/convolution_layer.cpp
View File

@ -376,7 +376,7 @@ public:
if (activ_power->scale != 1.0f) // not supported well by implementation, #17964
{
// FIXIT no way to check number of blobs (like, eltwise input)
CV_LOG_INFO(NULL, "DNN/OpenCL: can't configure Power activation (scale != 1.0f)");
CV_LOG_DEBUG(NULL, "DNN/OpenCL: can't configure Power activation (scale != 1.0f)");
activ.release();
newActiv = false;
return false;

8
modules/dnn/test/test_layers.cpp
View File

@ -2341,10 +2341,6 @@ TEST_P(ConvolutionEltwiseActivationFusion, Accuracy)
Backend backendId = get<0>(get<4>(GetParam()));
Target targetId = get<1>(get<4>(GetParam()));
// bug: https://github.com/opencv/opencv/issues/17945
if ((eltwiseOp != "sum" || weightedEltwise) && backendId == DNN_BACKEND_OPENCV && (targetId == DNN_TARGET_OPENCL || targetId == DNN_TARGET_OPENCL_FP16))
applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL);
Net net;
int convId = net.addLayer(convParams.name, convParams.type, convParams);
int eltwiseId = net.addLayer(eltwiseParams.name, eltwiseParams.type, eltwiseParams);
@ -2361,7 +2357,9 @@ TEST_P(ConvolutionEltwiseActivationFusion, Accuracy)
expectedFusedLayers.push_back(activId); // activation is fused with eltwise layer
else if (targetId == DNN_TARGET_OPENCL || targetId == DNN_TARGET_OPENCL_FP16)
{
if (actType == "ReLU" || actType == "ChannelsPReLU" /*|| actType == "Power"*/)
if (eltwiseOp == "sum" && !weightedEltwise &&
(actType == "ReLU" || actType == "ChannelsPReLU" /*|| actType == "Power"*/)
)
{
expectedFusedLayers.push_back(eltwiseId);
expectedFusedLayers.push_back(activId);