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Fallback for "SAME" padMode in ocl convolution and pooling

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It fixes tensorflow ocl testcase of MobileNetSSD and Inception_v2_SSD

Signed-off-by: Li Peng <peng.li@intel.com>
This commit is contained in:
Li Peng
2018-02-19 20:56:40 +08:00
parent 203ac0f818
commit c524f669c7
4 changed files with 40 additions and 12 deletions
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modules/dnn/src/layers/convolution_layer.cpp
+2 -8
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@@ -824,15 +824,9 @@ public:
for (int i = 0; i < inputs.size(); ++i)
CV_Assert(inputs[i].u != outputs[0].u);
int inpH = inputs[0].size[2];
int inpW = inputs[0].size[3];
int out_h = (inpH + 2 * pad.height - (dilation.height * (kernel.height - 1) + 1)) / stride.height + 1;
int out_w = (inpW + 2 * pad.width - (dilation.width * (kernel.width - 1) + 1)) / stride.width + 1;
if (out_h != outputs[0].size[2] || out_w != outputs[0].size[3])
if (padMode == "SAME")
return false;
int group = inputs[0].size[1] / umat_blobs[0].size[1];
if (convolutionOp.empty())
{
OCL4DNNConvConfig config;
@@ -842,7 +836,7 @@ public:
config.pad = pad;
config.stride = stride;
config.dilation = dilation;
config.group = group;
config.group = inputs[0].size[1] / umat_blobs[0].size[1];
config.bias_term = (hasBias()) ? true : false;
convolutionOp = Ptr<OCL4DNNConvSpatial<float> >(new OCL4DNNConvSpatial<float>(config));