mirror of
https://github.com/pjreddie/darknet.git
synced 2023-08-10 21:13:14 +03:00
94 lines
2.6 KiB
C
94 lines
2.6 KiB
C
#include "route_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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route_layer make_route_layer(int batch, int n, int *input_layers, int *input_sizes)
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{
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fprintf(stderr,"Route Layer:");
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route_layer l = {0};
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l.type = ROUTE;
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l.batch = batch;
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l.n = n;
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l.input_layers = input_layers;
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l.input_sizes = input_sizes;
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int i;
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int outputs = 0;
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for(i = 0; i < n; ++i){
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fprintf(stderr," %d", input_layers[i]);
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outputs += input_sizes[i];
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}
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fprintf(stderr, "\n");
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l.outputs = outputs;
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l.inputs = outputs;
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l.delta = calloc(outputs*batch, sizeof(float));
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l.output = calloc(outputs*batch, sizeof(float));;
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#ifdef GPU
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l.delta_gpu = cuda_make_array(0, outputs*batch);
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l.output_gpu = cuda_make_array(0, outputs*batch);
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#endif
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return l;
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}
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void forward_route_layer(const route_layer l, network net)
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{
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int i, j;
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int offset = 0;
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for(i = 0; i < l.n; ++i){
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int index = l.input_layers[i];
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float *input = net.layers[index].output;
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int input_size = l.input_sizes[i];
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for(j = 0; j < l.batch; ++j){
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copy_cpu(input_size, input + j*input_size, 1, l.output + offset + j*l.outputs, 1);
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}
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offset += input_size;
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}
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}
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void backward_route_layer(const route_layer l, network net)
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{
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int i, j;
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int offset = 0;
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for(i = 0; i < l.n; ++i){
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int index = l.input_layers[i];
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float *delta = net.layers[index].delta;
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int input_size = l.input_sizes[i];
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for(j = 0; j < l.batch; ++j){
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copy_cpu(input_size, l.delta + offset + j*l.outputs, 1, delta + j*input_size, 1);
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}
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offset += input_size;
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}
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}
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#ifdef GPU
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void forward_route_layer_gpu(const route_layer l, network net)
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{
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int i, j;
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int offset = 0;
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for(i = 0; i < l.n; ++i){
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int index = l.input_layers[i];
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float *input = net.layers[index].output_gpu;
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int input_size = l.input_sizes[i];
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for(j = 0; j < l.batch; ++j){
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copy_ongpu(input_size, input + j*input_size, 1, l.output_gpu + offset + j*l.outputs, 1);
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}
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offset += input_size;
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}
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}
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void backward_route_layer_gpu(const route_layer l, network net)
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{
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int i, j;
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int offset = 0;
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for(i = 0; i < l.n; ++i){
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int index = l.input_layers[i];
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float *delta = net.layers[index].delta_gpu;
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int input_size = l.input_sizes[i];
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for(j = 0; j < l.batch; ++j){
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copy_ongpu(input_size, l.delta_gpu + offset + j*l.outputs, 1, delta + j*input_size, 1);
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}
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offset += input_size;
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}
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}
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#endif
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