darknet/src/route_layer.c
2015-05-11 13:46:49 -07:00

94 lines
2.6 KiB
C

#include "route_layer.h"
#include "cuda.h"
#include "blas.h"
#include <stdio.h>
route_layer make_route_layer(int batch, int n, int *input_layers, int *input_sizes)
{
fprintf(stderr,"Route Layer:");
route_layer l = {0};
l.type = ROUTE;
l.batch = batch;
l.n = n;
l.input_layers = input_layers;
l.input_sizes = input_sizes;
int i;
int outputs = 0;
for(i = 0; i < n; ++i){
fprintf(stderr," %d", input_layers[i]);
outputs += input_sizes[i];
}
fprintf(stderr, "\n");
l.outputs = outputs;
l.inputs = outputs;
l.delta = calloc(outputs*batch, sizeof(float));
l.output = calloc(outputs*batch, sizeof(float));;
#ifdef GPU
l.delta_gpu = cuda_make_array(0, outputs*batch);
l.output_gpu = cuda_make_array(0, outputs*batch);
#endif
return l;
}
void forward_route_layer(const route_layer l, network net)
{
int i, j;
int offset = 0;
for(i = 0; i < l.n; ++i){
int index = l.input_layers[i];
float *input = net.layers[index].output;
int input_size = l.input_sizes[i];
for(j = 0; j < l.batch; ++j){
copy_cpu(input_size, input + j*input_size, 1, l.output + offset + j*l.outputs, 1);
}
offset += input_size;
}
}
void backward_route_layer(const route_layer l, network net)
{
int i, j;
int offset = 0;
for(i = 0; i < l.n; ++i){
int index = l.input_layers[i];
float *delta = net.layers[index].delta;
int input_size = l.input_sizes[i];
for(j = 0; j < l.batch; ++j){
copy_cpu(input_size, l.delta + offset + j*l.outputs, 1, delta + j*input_size, 1);
}
offset += input_size;
}
}
#ifdef GPU
void forward_route_layer_gpu(const route_layer l, network net)
{
int i, j;
int offset = 0;
for(i = 0; i < l.n; ++i){
int index = l.input_layers[i];
float *input = net.layers[index].output_gpu;
int input_size = l.input_sizes[i];
for(j = 0; j < l.batch; ++j){
copy_ongpu(input_size, input + j*input_size, 1, l.output_gpu + offset + j*l.outputs, 1);
}
offset += input_size;
}
}
void backward_route_layer_gpu(const route_layer l, network net)
{
int i, j;
int offset = 0;
for(i = 0; i < l.n; ++i){
int index = l.input_layers[i];
float *delta = net.layers[index].delta_gpu;
int input_size = l.input_sizes[i];
for(j = 0; j < l.batch; ++j){
copy_ongpu(input_size, l.delta_gpu + offset + j*l.outputs, 1, delta + j*input_size, 1);
}
offset += input_size;
}
}
#endif