| | |
| | | #include "blas.h" |
| | | } |
| | | |
| | | #ifdef OPENCV |
| | | #include "opencv2/highgui/highgui_c.h" |
| | | #endif |
| | | |
| | | float * get_network_output_gpu_layer(network net, int i); |
| | | float * get_network_delta_gpu_layer(network net, int i); |
| | | float * get_network_output_gpu(network net); |
| | |
| | | fill_ongpu(l.outputs * l.batch, 0, l.delta_gpu, 1); |
| | | } |
| | | l.forward_gpu(l, state); |
| | | if(net.wait_stream) |
| | | cudaStreamSynchronize(get_cuda_stream()); |
| | | if(net.wait_stream) |
| | | cudaStreamSynchronize(get_cuda_stream()); |
| | | state.input = l.output_gpu; |
| | | /* |
| | | cuda_pull_array(l.output_gpu, l.output, l.batch*l.outputs); |
| | | if (l.out_w >= 0 && l.out_h >= 1 && l.c >= 3) { |
| | | int j; |
| | | for (j = 0; j < l.out_c; ++j) { |
| | | image img = make_image(l.out_w, l.out_h, 3); |
| | | memcpy(img.data, l.output+ l.out_w*l.out_h*j, l.out_w*l.out_h * 1 * sizeof(float)); |
| | | char buff[256]; |
| | | sprintf(buff, "layer-%d slice-%d", i, j); |
| | | show_image(img, buff); |
| | | } |
| | | cvWaitKey(0); // wait press-key in console |
| | | cvDestroyAllWindows(); |
| | | } |
| | | */ |
| | | } |
| | | } |
| | | |
| | |
| | | state.truth = *net.truth_gpu; |
| | | state.train = 1; |
| | | #ifdef CUDNN_HALF |
| | | int i; |
| | | for (i = 0; i < net.n; ++i) { |
| | | layer l = net.layers[i]; |
| | | cuda_convert_f32_to_f16(l.weights_gpu, l.c*l.n*l.size*l.size, (half *)l.weights_gpu16); |
| | | } |
| | | int i; |
| | | for (i = 0; i < net.n; ++i) { |
| | | layer l = net.layers[i]; |
| | | cuda_convert_f32_to_f16(l.weights_gpu, l.c*l.n*l.size*l.size, l.weights_gpu16); |
| | | } |
| | | #endif |
| | | forward_network_gpu(net, state); |
| | | cudaStreamSynchronize(get_cuda_stream()); |
| | | //cudaStreamSynchronize(get_cuda_stream()); |
| | | backward_network_gpu(net, state); |
| | | } |
| | | |
| | |
| | | |
| | | float *network_predict_gpu(network net, float *input) |
| | | { |
| | | if (net.gpu_index != cuda_get_device()) |
| | | cuda_set_device(net.gpu_index); |
| | | if (net.gpu_index != cuda_get_device()) |
| | | cuda_set_device(net.gpu_index); |
| | | int size = get_network_input_size(net) * net.batch; |
| | | network_state state; |
| | | state.index = 0; |