#include "reorg_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_reorg_layer(int batch, int h, int w, int c, int stride, int reverse)
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{
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layer l = {0};
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l.type = REORG;
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l.batch = batch;
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l.stride = stride;
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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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if(reverse){
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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/(stride*stride);
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}else{
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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*(stride*stride);
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}
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l.reverse = reverse;
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fprintf(stderr, "Reorg Layer: %d x %d x %d image -> %d x %d x %d image, \n", w,h,c,l.out_w, l.out_h, l.out_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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int output_size = l.out_h * l.out_w * l.out_c * batch;
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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_reorg_layer;
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l.backward = backward_reorg_layer;
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#ifdef GPU
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l.forward_gpu = forward_reorg_layer_gpu;
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l.backward_gpu = backward_reorg_layer_gpu;
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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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return l;
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}
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void resize_reorg_layer(layer *l, int w, int h)
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{
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int stride = l->stride;
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int c = l->c;
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l->h = h;
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l->w = w;
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if(l->reverse){
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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/(stride*stride);
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}else{
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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*(stride*stride);
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}
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l->outputs = l->out_h * l->out_w * l->out_c;
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l->inputs = l->outputs;
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int output_size = l->outputs * l->batch;
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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(l->output_gpu);
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cuda_free(l->delta_gpu);
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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_reorg_layer(const layer l, network_state state)
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{
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int b,i,j,k;
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for(b = 0; b < l.batch; ++b){
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for(k = 0; k < l.c; ++k){
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for(j = 0; j < l.h; ++j){
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for(i = 0; i < l.w; ++i){
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int in_index = i + l.w*(j + l.h*(k + l.c*b));
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int c2 = k % l.out_c;
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int offset = k / l.out_c;
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int w2 = i*l.stride + offset % l.stride;
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int h2 = j*l.stride + offset / l.stride;
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int out_index = w2 + l.out_w*(h2 + l.out_h*(c2 + l.out_c*b));
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l.output[out_index] = state.input[in_index];
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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_reorg_layer(const layer l, network_state state)
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{
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int b,i,j,k;
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for(b = 0; b < l.batch; ++b){
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for(k = 0; k < l.c; ++k){
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for(j = 0; j < l.h; ++j){
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for(i = 0; i < l.w; ++i){
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int in_index = i + l.w*(j + l.h*(k + l.c*b));
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int c2 = k % l.out_c;
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int offset = k / l.out_c;
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int w2 = i*l.stride + offset % l.stride;
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int h2 = j*l.stride + offset / l.stride;
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int out_index = w2 + l.out_w*(h2 + l.out_h*(c2 + l.out_c*b));
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state.delta[in_index] = l.delta[out_index];
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}
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}
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}
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}
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}
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#ifdef GPU
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void forward_reorg_layer_gpu(layer l, network_state state)
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{
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if(l.reverse){
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reorg_ongpu(state.input, l.w, l.h, l.c, l.batch, l.stride, 1, l.output_gpu);
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}else {
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reorg_ongpu(state.input, l.w, l.h, l.c, l.batch, l.stride, 0, l.output_gpu);
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}
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}
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void backward_reorg_layer_gpu(layer l, network_state state)
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{
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if(l.reverse){
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reorg_ongpu(l.delta_gpu, l.w, l.h, l.c, l.batch, l.stride, 0, state.delta);
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}else{
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reorg_ongpu(l.delta_gpu, l.w, l.h, l.c, l.batch, l.stride, 1, state.delta);
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}
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}
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#endif
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