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fp16 ocl support for googlenet

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Signed-off-by: Li Peng <peng.li@intel.com>
This commit is contained in:
Li Peng
2018-04-26 19:22:29 +08:00
parent 329abb5b64
commit 3dd916882a
32 changed files with 2480 additions and 303 deletions
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modules/dnn/src/layers/convolution_layer.cpp
+9 -4
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@@ -94,7 +94,7 @@ public:
CV_Assert(blobs[0].dims == 4 && blobs[0].size[3] == kernel.width && blobs[0].size[2] == kernel.height);
const Mat &input = *inputs[0];
CV_Assert(input.dims == 4 && (input.type() == CV_32F || input.type() == CV_64F));
CV_Assert(input.dims == 4 && (input.type() == CV_32F || input.type() == CV_64F || input.type() == CV_16S));
for (size_t i = 0; i < inputs.size(); i++)
{
CV_Assert(inputs[i]->type() == input.type());
@@ -288,7 +288,7 @@ public:
newActiv = true;
activType = OCL4DNN_CONV_FUSED_ACTIV_NONE;
if (preferableTarget == DNN_TARGET_OPENCL)
if (IS_DNN_OPENCL_TARGET(preferableTarget))
{
Ptr<PowerLayer> activ_power = activ.dynamicCast<PowerLayer>();
if (!activ_power.empty())
@@ -842,6 +842,7 @@ public:
std::vector<UMat> inputs;
std::vector<UMat> outputs;
bool use_half = (inps.depth() == CV_16S);
inps.getUMatVector(inputs);
outs.getUMatVector(outputs);
@@ -860,6 +861,7 @@ public:
config.dilation = dilation;
config.group = inputs[0].size[1] / umat_blobs[0].size[1];
config.bias_term = (hasBias()) ? true : false;
config.use_half = use_half;
convolutionOp = Ptr<OCL4DNNConvSpatial<float> >(new OCL4DNNConvSpatial<float>(config));
}
@@ -964,7 +966,7 @@ public:
CV_TRACE_FUNCTION();
CV_TRACE_ARG_VALUE(name, "name", name.c_str());
CV_OCL_RUN((preferableTarget == DNN_TARGET_OPENCL) &&
CV_OCL_RUN(IS_DNN_OPENCL_TARGET(preferableTarget) &&
OCL_PERFORMANCE_CHECK(ocl::Device::getDefault().isIntel()),
forward_ocl(inputs_arr, outputs_arr, internals_arr))
@@ -1360,6 +1362,9 @@ public:
std::vector<UMat> outputs;
std::vector<UMat> internals;
if (inputs_.depth() == CV_16S)
return false;
inputs_.getUMatVector(inputs);
outputs_.getUMatVector(outputs);
internals_.getUMatVector(internals);
@@ -1450,7 +1455,7 @@ public:
CV_TRACE_FUNCTION();
CV_TRACE_ARG_VALUE(name, "name", name.c_str());
CV_OCL_RUN((preferableTarget == DNN_TARGET_OPENCL) &&
CV_OCL_RUN(IS_DNN_OPENCL_TARGET(preferableTarget) &&
OCL_PERFORMANCE_CHECK(ocl::Device::getDefault().isIntel()),
forward_ocl(inputs_arr, outputs_arr, internals_arr))