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Add CenterNet based on Resnet101, TensorRT not implemented.

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Signed-off-by: Davide Sapienza <sapienza.dav@gmail.com>
This commit is contained in:
Davide Sapienza
2019-12-18 18:59:54 +01:00
parent 44b2bce3ff
commit df888a3457
13 changed files with 773 additions and 11 deletions
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src/Conv2d.cpp
+6 -5
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@@ -44,7 +44,8 @@ void Conv2d::initCUDNN(bool back) {
convDesc, srcTensor, filterDesc,
&tmpdim.n, &tmpdim.c, &tmpdim.h, &tmpdim.w) );
if(odim.n != tmpdim.n || odim.c != tmpdim.c || odim.h != tmpdim.h || odim.w != tmpdim.w) {
std::cout<<"tkdim: "; odim.print();
std::cout<<"tkdim input: "; idim.print();
std::cout<<"tkdim output: "; odim.print();
std::cout<<"cudnndim: "; tmpdim.print();
FatalError("Eror conv dimension mismatch");
}
@@ -107,12 +108,12 @@ void Conv2d::inferCUDNN(dnnType* srcData, bool back) {
} else {
alpha = dnnType(1);
beta = dnnType(0);
cudnnBatchNormalizationForwardInference(net->cudnnHandle,
checkCUDNN( cudnnBatchNormalizationForwardInference(net->cudnnHandle,
CUDNN_BATCHNORM_SPATIAL, &alpha, &beta,
dstTensorDesc, dstData, dstTensorDesc,
dstData, biasTensorDesc, //same tensor descriptor as bias
scales_d, bias_d, mean_d, variance_d,
CUDNN_BN_MIN_EPSILON);
CUDNN_BN_MIN_EPSILON) );
}
}
@@ -140,8 +141,8 @@ Conv2d::Conv2d( Network *net, int out_ch, int kernelH, int kernelW,
} else {
output_dim.n = input_dim.n;
output_dim.c = out_ch;
output_dim.h = (input_dim.h * strideH) - 2*paddingH + kernelH -1;
output_dim.w = (input_dim.w * strideW) - 2*paddingW + kernelW -1;
output_dim.h = ((input_dim.h-1) * strideH) - 2*paddingH + kernelH;
output_dim.w = ((input_dim.w-1) * strideW) - 2*paddingW + kernelW;
output_dim.l = 1;
}
initCUDNN(deConv);