mirror of https://github.com/pjreddie/darknet.git
107 lines
3.2 KiB
C
107 lines
3.2 KiB
C
#include "upsample_layer.h"
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#include "cuda.h"
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#include "blas.h"
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#include <stdio.h>
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layer make_upsample_layer(int batch, int w, int h, int c, int stride)
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{
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layer l = {0};
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l.type = UPSAMPLE;
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l.batch = batch;
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l.w = w;
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l.h = h;
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l.c = c;
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l.out_w = w*stride;
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l.out_h = h*stride;
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l.out_c = c;
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if(stride < 0){
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stride = -stride;
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l.reverse=1;
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l.out_w = w/stride;
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l.out_h = h/stride;
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}
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l.stride = stride;
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l.outputs = l.out_w*l.out_h*l.out_c;
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l.inputs = l.w*l.h*l.c;
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l.delta = calloc(l.outputs*batch, sizeof(float));
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l.output = calloc(l.outputs*batch, sizeof(float));;
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l.forward = forward_upsample_layer;
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l.backward = backward_upsample_layer;
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#ifdef GPU
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l.forward_gpu = forward_upsample_layer_gpu;
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l.backward_gpu = backward_upsample_layer_gpu;
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l.delta_gpu = cuda_make_array(l.delta, l.outputs*batch);
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l.output_gpu = cuda_make_array(l.output, l.outputs*batch);
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#endif
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if(l.reverse) fprintf(stderr, "downsample %2dx %4d x%4d x%4d -> %4d x%4d x%4d\n", stride, w, h, c, l.out_w, l.out_h, l.out_c);
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else fprintf(stderr, "upsample %2dx %4d x%4d x%4d -> %4d x%4d x%4d\n", 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_upsample_layer(layer *l, int w, int h)
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{
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l->w = w;
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l->h = h;
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l->out_w = w*l->stride;
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l->out_h = h*l->stride;
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if(l->reverse){
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l->out_w = w/l->stride;
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l->out_h = h/l->stride;
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}
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l->outputs = l->out_w*l->out_h*l->out_c;
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l->inputs = l->h*l->w*l->c;
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l->delta = realloc(l->delta, l->outputs*l->batch*sizeof(float));
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l->output = realloc(l->output, l->outputs*l->batch*sizeof(float));
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#ifdef GPU
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cuda_free(l->output_gpu);
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cuda_free(l->delta_gpu);
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l->output_gpu = cuda_make_array(l->output, l->outputs*l->batch);
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l->delta_gpu = cuda_make_array(l->delta, l->outputs*l->batch);
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#endif
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}
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void forward_upsample_layer(const layer l, network net)
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{
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fill_cpu(l.outputs*l.batch, 0, l.output, 1);
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if(l.reverse){
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upsample_cpu(l.output, l.out_w, l.out_h, l.c, l.batch, l.stride, 0, l.scale, net.input);
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}else{
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upsample_cpu(net.input, l.w, l.h, l.c, l.batch, l.stride, 1, l.scale, l.output);
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}
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}
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void backward_upsample_layer(const layer l, network net)
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{
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if(l.reverse){
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upsample_cpu(l.delta, l.out_w, l.out_h, l.c, l.batch, l.stride, 1, l.scale, net.delta);
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}else{
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upsample_cpu(net.delta, l.w, l.h, l.c, l.batch, l.stride, 0, l.scale, l.delta);
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}
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}
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#ifdef GPU
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void forward_upsample_layer_gpu(const layer l, network net)
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{
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fill_gpu(l.outputs*l.batch, 0, l.output_gpu, 1);
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if(l.reverse){
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upsample_gpu(l.output_gpu, l.out_w, l.out_h, l.c, l.batch, l.stride, 0, l.scale, net.input_gpu);
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}else{
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upsample_gpu(net.input_gpu, l.w, l.h, l.c, l.batch, l.stride, 1, l.scale, l.output_gpu);
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}
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}
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void backward_upsample_layer_gpu(const layer l, network net)
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{
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if(l.reverse){
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upsample_gpu(l.delta_gpu, l.out_w, l.out_h, l.c, l.batch, l.stride, 1, l.scale, net.delta_gpu);
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}else{
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upsample_gpu(net.delta_gpu, l.w, l.h, l.c, l.batch, l.stride, 0, l.scale, l.delta_gpu);
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}
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}
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#endif
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