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

58 lines
1.4 KiB
C

#include "dropout_layer.h"
#include "params.h"
#include "utils.h"
#include "cuda.h"
#include <stdlib.h>
#include <stdio.h>
dropout_layer make_dropout_layer(int batch, int inputs, float probability)
{
fprintf(stderr, "Dropout Layer: %d inputs, %f probability\n", inputs, probability);
dropout_layer l = {0};
l.type = DROPOUT;
l.probability = probability;
l.inputs = inputs;
l.outputs = inputs;
l.batch = batch;
l.rand = calloc(inputs*batch, sizeof(float));
l.scale = 1./(1.-probability);
#ifdef GPU
l.rand_gpu = cuda_make_array(l.rand, inputs*batch);
#endif
return l;
}
void resize_dropout_layer(dropout_layer *l, int inputs)
{
l->rand = realloc(l->rand, l->inputs*l->batch*sizeof(float));
#ifdef GPU
cuda_free(l->rand_gpu);
l->rand_gpu = cuda_make_array(l->rand, inputs*l->batch);
#endif
}
void forward_dropout_layer(dropout_layer l, network_state state)
{
int i;
if (!state.train) return;
for(i = 0; i < l.batch * l.inputs; ++i){
float r = rand_uniform();
l.rand[i] = r;
if(r < l.probability) state.input[i] = 0;
else state.input[i] *= l.scale;
}
}
void backward_dropout_layer(dropout_layer l, network_state state)
{
int i;
if(!state.delta) return;
for(i = 0; i < l.batch * l.inputs; ++i){
float r = l.rand[i];
if(r < l.probability) state.delta[i] = 0;
else state.delta[i] *= l.scale;
}
}