mirror of https://github.com/pjreddie/darknet.git
128 lines
3.9 KiB
C
128 lines
3.9 KiB
C
#include "maxpool_layer.h"
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#include "cuda.h"
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#include <stdio.h>
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image get_maxpool_image(maxpool_layer l)
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{
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int h = l.out_h;
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int w = l.out_w;
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int c = l.c;
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return float_to_image(w,h,c,l.output);
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}
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image get_maxpool_delta(maxpool_layer l)
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{
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int h = l.out_h;
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int w = l.out_w;
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int c = l.c;
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return float_to_image(w,h,c,l.delta);
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}
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maxpool_layer make_maxpool_layer(int batch, int h, int w, int c, int size, int stride, int padding)
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{
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maxpool_layer l = {0};
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l.type = MAXPOOL;
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l.batch = batch;
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l.h = h;
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l.w = w;
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l.c = c;
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l.pad = padding;
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l.out_w = (w + padding - size)/stride + 1;
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l.out_h = (h + padding - size)/stride + 1;
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l.out_c = c;
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l.outputs = l.out_h * l.out_w * l.out_c;
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l.inputs = h*w*c;
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l.size = size;
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l.stride = stride;
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int output_size = l.out_h * l.out_w * l.out_c * batch;
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l.indexes = calloc(output_size, sizeof(int));
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l.output = calloc(output_size, sizeof(float));
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l.delta = calloc(output_size, sizeof(float));
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l.forward = forward_maxpool_layer;
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l.backward = backward_maxpool_layer;
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#ifdef GPU
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l.forward_gpu = forward_maxpool_layer_gpu;
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l.backward_gpu = backward_maxpool_layer_gpu;
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l.indexes_gpu = cuda_make_int_array(0, output_size);
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l.output_gpu = cuda_make_array(l.output, output_size);
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l.delta_gpu = cuda_make_array(l.delta, output_size);
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#endif
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fprintf(stderr, "max %d x %d / %d %4d x%4d x%4d -> %4d x%4d x%4d\n", size, size, stride, w, h, c, l.out_w, l.out_h, l.out_c);
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return l;
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}
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void resize_maxpool_layer(maxpool_layer *l, int w, int h)
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{
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l->h = h;
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l->w = w;
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l->inputs = h*w*l->c;
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l->out_w = (w + l->pad - l->size)/l->stride + 1;
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l->out_h = (h + l->pad - l->size)/l->stride + 1;
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l->outputs = l->out_w * l->out_h * l->c;
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int output_size = l->outputs * l->batch;
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l->indexes = realloc(l->indexes, output_size * sizeof(int));
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l->output = realloc(l->output, output_size * sizeof(float));
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l->delta = realloc(l->delta, output_size * sizeof(float));
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#ifdef GPU
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cuda_free((float *)l->indexes_gpu);
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cuda_free(l->output_gpu);
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cuda_free(l->delta_gpu);
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l->indexes_gpu = cuda_make_int_array(0, output_size);
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l->output_gpu = cuda_make_array(l->output, output_size);
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l->delta_gpu = cuda_make_array(l->delta, output_size);
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#endif
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}
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void forward_maxpool_layer(const maxpool_layer l, network net)
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{
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int b,i,j,k,m,n;
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int w_offset = -l.pad/2;
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int h_offset = -l.pad/2;
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int h = l.out_h;
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int w = l.out_w;
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int c = l.c;
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for(b = 0; b < l.batch; ++b){
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for(k = 0; k < c; ++k){
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for(i = 0; i < h; ++i){
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for(j = 0; j < w; ++j){
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int out_index = j + w*(i + h*(k + c*b));
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float max = -FLT_MAX;
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int max_i = -1;
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for(n = 0; n < l.size; ++n){
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for(m = 0; m < l.size; ++m){
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int cur_h = h_offset + i*l.stride + n;
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int cur_w = w_offset + j*l.stride + m;
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int index = cur_w + l.w*(cur_h + l.h*(k + b*l.c));
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int valid = (cur_h >= 0 && cur_h < l.h &&
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cur_w >= 0 && cur_w < l.w);
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float val = (valid != 0) ? net.input[index] : -FLT_MAX;
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max_i = (val > max) ? index : max_i;
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max = (val > max) ? val : max;
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}
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}
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l.output[out_index] = max;
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l.indexes[out_index] = max_i;
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}
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}
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}
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}
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}
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void backward_maxpool_layer(const maxpool_layer l, network net)
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{
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int i;
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int h = l.out_h;
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int w = l.out_w;
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int c = l.c;
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for(i = 0; i < h*w*c*l.batch; ++i){
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int index = l.indexes[i];
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net.delta[index] += l.delta[i];
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}
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}
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