mmr/tkDNN
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opencv viz

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Francesco Gatti
2017-08-10 16:22:17 +02:00
parent b75fa637cb
commit 266330009c
31 changed files with 211 additions and 152 deletions
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src/NetworkRT.cpp
+5 -5
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@@ -81,9 +81,9 @@ NetworkRT::NetworkRT(Network *net) {
std::cout<<"input idex = "<<buf_input_idx<<" -> output index = "<<buf_output_idx<<"\n";
// create GPU buffers and a stream
checkCuda(cudaMalloc(&buffersRT[buf_input_idx], dim.tot()*sizeof(value_type)));
checkCuda(cudaMalloc(&buffersRT[buf_output_idx], output_dim.tot()*sizeof(value_type)));
checkCuda(cudaMalloc(&output, output_dim.tot()*sizeof(value_type)));
checkCuda(cudaMalloc(&buffersRT[buf_input_idx], dim.tot()*sizeof(dnnType)));
checkCuda(cudaMalloc(&buffersRT[buf_output_idx], output_dim.tot()*sizeof(dnnType)));
checkCuda(cudaMalloc(&output, output_dim.tot()*sizeof(dnnType)));
checkCuda(cudaStreamCreate(&stream));
}
@@ -91,7 +91,7 @@ NetworkRT::~NetworkRT() {
}
value_type* NetworkRT::infer(dataDim_t &dim, value_type* data) {
dnnType* NetworkRT::infer(dataDim_t &dim, dnnType* data) {
checkCuda(cudaMemcpyAsync(buffersRT[buf_input_idx], data, dim.tot()*sizeof(float), cudaMemcpyDeviceToDevice, stream));
contextRT->enqueue(1, buffersRT, stream, nullptr);
@@ -161,7 +161,7 @@ ITensor* NetworkRT::convert_layer(ITensor *input, Conv2d *l) {
float eps = CUDNN_BN_MIN_EPSILON;
//make power array of ones
value_type *power_h = new value_type[l->outputs];
dnnType *power_h = new dnnType[l->outputs];
for(int i=0; i<l->outputs; i++) power_h[i] = 1.0f;
//convert mean