| | |
| | | return float_to_image(w,h,c,l.delta); |
| | | } |
| | | |
| | | maxpool_layer make_maxpool_layer(int batch, int h, int w, int c, int size, int stride) |
| | | maxpool_layer make_maxpool_layer(int batch, int h, int w, int c, int size, int stride, int padding) |
| | | { |
| | | fprintf(stderr, "Maxpool Layer: %d x %d x %d image, %d size, %d stride\n", h,w,c,size,stride); |
| | | maxpool_layer l = {0}; |
| | |
| | | l.h = h; |
| | | l.w = w; |
| | | l.c = c; |
| | | l.out_w = (w-1)/stride + 1; |
| | | l.out_h = (h-1)/stride + 1; |
| | | l.pad = padding; |
| | | l.out_w = (w + 2*padding - size + 1)/stride + 1; |
| | | l.out_h = (h + 2*padding - size + 1)/stride + 1; |
| | | l.out_c = c; |
| | | l.outputs = l.out_h * l.out_w * l.out_c; |
| | | l.inputs = h*w*c; |
| | |
| | | l.indexes = calloc(output_size, sizeof(int)); |
| | | l.output = calloc(output_size, sizeof(float)); |
| | | l.delta = calloc(output_size, sizeof(float)); |
| | | l.forward = forward_maxpool_layer; |
| | | l.backward = backward_maxpool_layer; |
| | | #ifdef GPU |
| | | l.forward_gpu = forward_maxpool_layer_gpu; |
| | | l.backward_gpu = backward_maxpool_layer_gpu; |
| | | l.indexes_gpu = cuda_make_int_array(output_size); |
| | | l.output_gpu = cuda_make_array(l.output, output_size); |
| | | l.delta_gpu = cuda_make_array(l.delta, output_size); |
| | |
| | | |
| | | void resize_maxpool_layer(maxpool_layer *l, int w, int h) |
| | | { |
| | | int stride = l->stride; |
| | | l->h = h; |
| | | l->w = w; |
| | | l->inputs = h*w*l->c; |
| | | |
| | | l->out_w = (w-1)/stride + 1; |
| | | l->out_h = (h-1)/stride + 1; |
| | | l->out_w = (w + 2*l->pad - l->size + 1)/l->stride + 1; |
| | | l->out_h = (h + 2*l->pad - l->size + 1)/l->stride + 1; |
| | | l->outputs = l->out_w * l->out_h * l->c; |
| | | int output_size = l->outputs * l->batch; |
| | | |
| | |
| | | cuda_free(l->output_gpu); |
| | | cuda_free(l->delta_gpu); |
| | | l->indexes_gpu = cuda_make_int_array(output_size); |
| | | l->output_gpu = cuda_make_array(0, output_size); |
| | | l->delta_gpu = cuda_make_array(0, output_size); |
| | | l->output_gpu = cuda_make_array(l->output, output_size); |
| | | l->delta_gpu = cuda_make_array(l->delta, output_size); |
| | | #endif |
| | | } |
| | | |
| | | void forward_maxpool_layer(const maxpool_layer l, network_state state) |
| | | { |
| | | int b,i,j,k,m,n; |
| | | int w_offset = (-l.size-1)/2 + 1; |
| | | int h_offset = (-l.size-1)/2 + 1; |
| | | int w_offset = -l.pad; |
| | | int h_offset = -l.pad; |
| | | |
| | | int h = (l.h-1)/l.stride + 1; |
| | | int w = (l.w-1)/l.stride + 1; |
| | | int h = l.out_h; |
| | | int w = l.out_w; |
| | | int c = l.c; |
| | | |
| | | for(b = 0; b < l.batch; ++b){ |
| | |
| | | void backward_maxpool_layer(const maxpool_layer l, network_state state) |
| | | { |
| | | int i; |
| | | int h = (l.h-1)/l.stride + 1; |
| | | int w = (l.w-1)/l.stride + 1; |
| | | int h = l.out_h; |
| | | int w = l.out_w; |
| | | int c = l.c; |
| | | memset(state.delta, 0, l.batch*l.h*l.w*l.c*sizeof(float)); |
| | | for(i = 0; i < h*w*c*l.batch; ++i){ |
| | | int index = l.indexes[i]; |
| | | state.delta[index] += l.delta[i]; |