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| #include "shortcut_layer.h"
| #include "cuda.h"
| #include "blas.h"
| #include <stdio.h>
| #include <assert.h>
|
| layer make_shortcut_layer(int batch, int index, int w, int h, int c, int w2, int h2, int c2)
| {
| fprintf(stderr,"Shortcut Layer: %d\n", index);
| layer l = {0};
| l.type = SHORTCUT;
| l.batch = batch;
| l.w = w2;
| l.h = h2;
| l.c = c2;
| l.out_w = w;
| l.out_h = h;
| l.out_c = c;
| l.outputs = w*h*c;
| l.inputs = l.outputs;
|
| l.index = index;
|
| l.delta = calloc(l.outputs*batch, sizeof(float));
| l.output = calloc(l.outputs*batch, sizeof(float));;
|
| l.forward = forward_shortcut_layer;
| l.backward = backward_shortcut_layer;
| #ifdef GPU
| l.forward_gpu = forward_shortcut_layer_gpu;
| l.backward_gpu = backward_shortcut_layer_gpu;
|
| l.delta_gpu = cuda_make_array(l.delta, l.outputs*batch);
| l.output_gpu = cuda_make_array(l.output, l.outputs*batch);
| #endif
| return l;
| }
|
| void resize_shortcut_layer(layer *l, int w, int h)
| {
| //assert(l->w == l->out_w);
| //assert(l->h == l->out_h);
| l->w = l->out_w = w;
| l->h = l->out_h = h;
| l->outputs = w*h*l->out_c;
| l->inputs = l->outputs;
| l->delta = realloc(l->delta, l->outputs*l->batch * sizeof(float));
| l->output = realloc(l->output, l->outputs*l->batch * sizeof(float));
|
| #ifdef GPU
| cuda_free(l->output_gpu);
| cuda_free(l->delta_gpu);
| l->output_gpu = cuda_make_array(l->output, l->outputs*l->batch);
| l->delta_gpu = cuda_make_array(l->delta, l->outputs*l->batch);
| #endif
|
| }
|
| void forward_shortcut_layer(const layer l, network_state state)
| {
| copy_cpu(l.outputs*l.batch, state.input, 1, l.output, 1);
| shortcut_cpu(l.batch, l.w, l.h, l.c, state.net.layers[l.index].output, l.out_w, l.out_h, l.out_c, l.output);
| activate_array(l.output, l.outputs*l.batch, l.activation);
| }
|
| void backward_shortcut_layer(const layer l, network_state state)
| {
| gradient_array(l.output, l.outputs*l.batch, l.activation, l.delta);
| axpy_cpu(l.outputs*l.batch, 1, l.delta, 1, state.delta, 1);
| shortcut_cpu(l.batch, l.out_w, l.out_h, l.out_c, l.delta, l.w, l.h, l.c, state.net.layers[l.index].delta);
| }
|
| #ifdef GPU
| void forward_shortcut_layer_gpu(const layer l, network_state state)
| {
| copy_ongpu(l.outputs*l.batch, state.input, 1, l.output_gpu, 1);
| shortcut_gpu(l.batch, l.w, l.h, l.c, state.net.layers[l.index].output_gpu, l.out_w, l.out_h, l.out_c, l.output_gpu);
| activate_array_ongpu(l.output_gpu, l.outputs*l.batch, l.activation);
| }
|
| void backward_shortcut_layer_gpu(const layer l, network_state state)
| {
| gradient_array_ongpu(l.output_gpu, l.outputs*l.batch, l.activation, l.delta_gpu);
| axpy_ongpu(l.outputs*l.batch, 1, l.delta_gpu, 1, state.delta, 1);
| shortcut_gpu(l.batch, l.out_w, l.out_h, l.out_c, l.delta_gpu, l.w, l.h, l.c, state.net.layers[l.index].delta_gpu);
| }
| #endif
|
|
