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| #include "reorg_layer.h"
| #include "cuda.h"
| #include "blas.h"
| #include <stdio.h>
|
|
| layer make_reorg_layer(int batch, int w, int h, int c, int stride, int reverse)
| {
| layer l = {0};
| l.type = REORG;
| l.batch = batch;
| l.stride = stride;
| l.h = h;
| l.w = w;
| l.c = c;
| if(reverse){
| l.out_w = w*stride;
| l.out_h = h*stride;
| l.out_c = c/(stride*stride);
| }else{
| l.out_w = w/stride;
| l.out_h = h/stride;
| l.out_c = c*(stride*stride);
| }
| l.reverse = reverse;
| fprintf(stderr, "reorg /%2d %4d x%4d x%4d -> %4d x%4d x%4d\n", stride, w, h, c, l.out_w, l.out_h, l.out_c);
| l.outputs = l.out_h * l.out_w * l.out_c;
| l.inputs = h*w*c;
| int output_size = l.out_h * l.out_w * l.out_c * batch;
| l.output = calloc(output_size, sizeof(float));
| l.delta = calloc(output_size, sizeof(float));
|
| l.forward = forward_reorg_layer;
| l.backward = backward_reorg_layer;
| #ifdef GPU
| l.forward_gpu = forward_reorg_layer_gpu;
| l.backward_gpu = backward_reorg_layer_gpu;
|
| 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_reorg_layer(layer *l, int w, int h)
| {
| int stride = l->stride;
| int c = l->c;
|
| l->h = h;
| l->w = w;
|
| if(l->reverse){
| l->out_w = w*stride;
| l->out_h = h*stride;
| l->out_c = c/(stride*stride);
| }else{
| l->out_w = w/stride;
| l->out_h = h/stride;
| l->out_c = c*(stride*stride);
| }
|
| l->outputs = l->out_h * l->out_w * l->out_c;
| l->inputs = l->outputs;
| int output_size = l->outputs * l->batch;
|
| l->output = realloc(l->output, output_size * sizeof(float));
| l->delta = realloc(l->delta, output_size * sizeof(float));
|
| #ifdef GPU
| cuda_free(l->output_gpu);
| cuda_free(l->delta_gpu);
| l->output_gpu = cuda_make_array(l->output, output_size);
| l->delta_gpu = cuda_make_array(l->delta, output_size);
| #endif
| }
|
| void forward_reorg_layer(const layer l, network_state state)
| {
| if (l.reverse) {
| reorg_cpu(state.input, l.out_w, l.out_h, l.out_c, l.batch, l.stride, 1, l.output);
| }
| else {
| reorg_cpu(state.input, l.out_w, l.out_h, l.out_c, l.batch, l.stride, 0, l.output);
| }
| }
|
| void backward_reorg_layer(const layer l, network_state state)
| {
| if (l.reverse) {
| reorg_cpu(l.delta, l.out_w, l.out_h, l.out_c, l.batch, l.stride, 0, state.delta);
| }
| else {
| reorg_cpu(l.delta, l.out_w, l.out_h, l.out_c, l.batch, l.stride, 1, state.delta);
| }
| }
|
| #ifdef GPU
| void forward_reorg_layer_gpu(layer l, network_state state)
| {
| if (l.reverse) {
| reorg_ongpu(state.input, l.out_w, l.out_h, l.out_c, l.batch, l.stride, 1, l.output_gpu);
| }
| else {
| reorg_ongpu(state.input, l.out_w, l.out_h, l.out_c, l.batch, l.stride, 0, l.output_gpu);
| }
| }
|
| void backward_reorg_layer_gpu(layer l, network_state state)
| {
| if (l.reverse) {
| reorg_ongpu(l.delta_gpu, l.out_w, l.out_h, l.out_c, l.batch, l.stride, 0, state.delta);
| }
| else {
| reorg_ongpu(l.delta_gpu, l.out_w, l.out_h, l.out_c, l.batch, l.stride, 1, state.delta);
| }
| }
| #endif
|
|
