| | |
| | | l.workspace_size = get_workspace_size(l); |
| | | l.activation = activation; |
| | | |
| | | fprintf(stderr, "Convolutional Layer: %d x %d x %d image, %d filters -> %d x %d x %d image\n", h,w,c,n, out_h, out_w, n); |
| | | fprintf(stderr, "conv %5d %2d x%2d /%2d %4d x%4d x%4d -> %4d x%4d x%4d\n", n, size, size, stride, w, h, c, l.out_w, l.out_h, l.out_c); |
| | | |
| | | return l; |
| | | } |
| | |
| | | |
| | | l->delta_gpu = cuda_make_array(l->delta, l->batch*out_h*out_w*l->n); |
| | | l->output_gpu = cuda_make_array(l->output, l->batch*out_h*out_w*l->n); |
| | | |
| | | if(l->batch_normalize){ |
| | | cuda_free(l->x_gpu); |
| | | cuda_free(l->x_norm_gpu); |
| | | |
| | | l->x_gpu = cuda_make_array(l->output, l->batch*l->outputs); |
| | | l->x_norm_gpu = cuda_make_array(l->output, l->batch*l->outputs); |
| | | } |
| | | #ifdef CUDNN |
| | | cudnn_convolutional_setup(l); |
| | | #endif |