ResNet working
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@@ -20,13 +20,6 @@ LayerWgs::LayerWgs(Network *net, int inputs, int outputs,
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seek += inputs*outputs*kh*kw*kl;
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readBinaryFile(weights_path.c_str(), outputs, &bias_h, &bias_d, seek);
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std::cout<<"w:\n";
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printDeviceVector(64, data_d, true);
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std::cout<<"b:\n";
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printDeviceVector(64, bias_d, true);
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std::cout<<"step----------------------------------------\n";
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this->batchnorm = batchnorm;
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if(batchnorm) {
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seek += outputs;
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@@ -36,17 +29,6 @@ std::cout<<"step----------------------------------------\n";
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seek += outputs;
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readBinaryFile(weights_path.c_str(), outputs, &variance_h, &variance_d, seek);
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std::cout<<"s:\n";
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printDeviceVector(64, scales_d, true);
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std::cout<<"m:\n";
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printDeviceVector(64, mean_d, true);
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std::cout<<"v:\n";
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printDeviceVector(64, variance_d, true);
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std::cout<<"END----------------------------------------\n";
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float eps = CUDNN_BN_MIN_EPSILON;
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power_h = new dnnType[outputs];
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+7
-1
@@ -263,10 +263,16 @@ ILayer* NetworkRT::convert_layer(ITensor *input, Conv2d *l) {
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ILayer* NetworkRT::convert_layer(ITensor *input, Pooling *l) {
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//std::cout<<"convert Pooling\n";
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PoolingType ptype;
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if(l->pool_mode == tkdnnPoolingMode_t::POOLING_MAX) ptype = PoolingType::kMAX;
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if(l->pool_mode == tkdnnPoolingMode_t::POOLING_AVERAGE) ptype = PoolingType::kAVERAGE;
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if(l->pool_mode == tkdnnPoolingMode_t::POOLING_AVERAGE_EXCLUDE_PADDING) ptype = PoolingType::kMAX_AVERAGE_BLEND;
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IPoolingLayer *lRT = networkRT->addPooling(*input,
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PoolingType::kMAX, DimsHW{l->winH, l->winW});
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ptype, DimsHW{l->winH, l->winW});
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checkNULL(lRT);
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lRT->setStride(DimsHW{l->strideH, l->strideW});
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lRT->setPadding(DimsHW{l->paddingH, l->paddingW});
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return lRT;
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}
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+5
-2
@@ -7,9 +7,12 @@ namespace tk { namespace dnn {
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Route::Route(Network *net, Layer **layers, int layers_n) : Layer(net) {
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this->layers = layers;
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this->layers_n = layers_n;
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if(layers_n > MAX_INPUT_LAYERS)
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FatalError("Route: MAX INPUT LAYERS overload");
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for(int i=0; i<layers_n; i++)
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this->layers[i] = layers[i];
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//get dims
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output_dim.l = 1;
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output_dim.c = 0;
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