#include "maxpool_layer.h" #include "cuda.h" #include image get_maxpool_image(maxpool_layer l) { int h = l.out_h; int w = l.out_w; int c = l.c; return float_to_image(w,h,c,l.output); } image get_maxpool_delta(maxpool_layer l) { int h = l.out_h; int w = l.out_w; int c = l.c; 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) { 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.type = MAXPOOL; l.batch = batch; l.h = h; l.w = w; l.c = c; l.out_w = (w-1)/stride + 1; l.out_h = (h-1)/stride + 1; l.out_c = c; l.outputs = l.out_h * l.out_w * l.out_c; l.inputs = h*w*c; l.size = size; l.stride = stride; int output_size = l.out_h * l.out_w * l.out_c * batch; l.indexes = calloc(output_size, sizeof(int)); l.output = calloc(output_size, sizeof(float)); l.delta = calloc(output_size, sizeof(float)); #ifdef 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); #endif return l; } void resize_maxpool_layer(maxpool_layer *l, int w, int h) { int stride = l->stride; l->h = h; l->w = w; l->out_w = (w-1)/stride + 1; l->out_h = (h-1)/stride + 1; l->outputs = l->out_w * l->out_h * l->c; int output_size = l->outputs * l->batch; l->indexes = realloc(l->indexes, output_size * sizeof(int)); l->output = realloc(l->output, output_size * sizeof(float)); l->delta = realloc(l->delta, output_size * sizeof(float)); #ifdef GPU cuda_free((float *)l->indexes_gpu); 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); #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 h = (l.h-1)/l.stride + 1; int w = (l.w-1)/l.stride + 1; int c = l.c; for(b = 0; b < l.batch; ++b){ for(k = 0; k < c; ++k){ for(i = 0; i < h; ++i){ for(j = 0; j < w; ++j){ int out_index = j + w*(i + h*(k + c*b)); float max = -FLT_MAX; int max_i = -1; for(n = 0; n < l.size; ++n){ for(m = 0; m < l.size; ++m){ int cur_h = h_offset + i*l.stride + n; int cur_w = w_offset + j*l.stride + m; int index = cur_w + l.w*(cur_h + l.h*(k + b*l.c)); int valid = (cur_h >= 0 && cur_h < l.h && cur_w >= 0 && cur_w < l.w); float val = (valid != 0) ? state.input[index] : -FLT_MAX; max_i = (val > max) ? index : max_i; max = (val > max) ? val : max; } } l.output[out_index] = max; l.indexes[out_index] = max_i; } } } } } 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 c = l.c; for(i = 0; i < h*w*c*l.batch; ++i){ int index = l.indexes[i]; state.delta[index] += l.delta[i]; } }