mmr/tkDNN
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Merge with master, works with Jetpack 4.3

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Signed-off-by: xavier <micaelaverucchi@gmail.com>
This commit is contained in:
xavier
2020-01-15 19:24:19 +01:00
parent 23a1365dc4 c32a0be257
commit 0f0c8c28e1
10 changed files with 59 additions and 35 deletions
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src/Conv2d.cpp
+1 -1
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@@ -113,7 +113,7 @@ void Conv2d::inferCUDNN(dnnType* srcData, bool back) {
dstTensorDesc, dstData, dstTensorDesc,
dstData, biasTensorDesc, //same tensor descriptor as bias
scales_d, bias_d, mean_d, variance_d,
CUDNN_BN_MIN_EPSILON) );
TKDNN_BN_MIN_EPSILON) );
}
}
src/DeformConv2d.cpp
+1 -1
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@@ -124,7 +124,7 @@ dnnType* DeformConv2d::infer(dataDim_t &dim, dnnType* srcData) {
dstTensorDesc, dstData, dstTensorDesc,
dstData, biasTensorDesc, //same tensor descriptor as bias
scales_d, bias_d, mean_d, variance_d,
CUDNN_BN_MIN_EPSILON) );
TKDNN_BN_MIN_EPSILON) );
}
//update data dimensions
src/LayerWgs.cpp
+1 -1
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@@ -35,7 +35,7 @@ LayerWgs::LayerWgs(Network *net, int inputs, int outputs,
seek += outputs;
readBinaryFile(weights_path.c_str(), outputs, &variance_h, &variance_d, seek, net->dontLoadWeights);
float eps = CUDNN_BN_MIN_EPSILON;
float eps = TKDNN_BN_MIN_EPSILON;
power_h = new dnnType[outputs];
for(int i=0; i<outputs; i++) power_h[i] = 1.0f;
src/Network.cpp
+5 -4
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@@ -18,10 +18,6 @@ Network::Network(dataDim_t input_dim) {
dataType = CUDNN_DATA_FLOAT;
tensorFormat = CUDNN_TENSOR_NCHW;
dontLoadWeights = false;
checkCUDNN( cudnnCreate(&cudnnHandle) );
checkERROR( cublasCreate(&cublasHandle) );
num_layers = 0;
fp16 = false;
@@ -39,6 +35,11 @@ Network::Network(dataDim_t input_dim) {
std::cout<<COL_REDB<<"!! FP16 INERENCE ENABLED !!"<<COL_END<<"\n";
if(dla)
std::cout<<COL_GREENB<<"!! DLA INERENCE ENABLED !!"<<COL_END<<"\n";
checkCUDNN( cudnnCreate(&cudnnHandle) );
checkERROR( cublasCreate(&cublasHandle) );
}
Network::~Network() {