mirror of https://github.com/pjreddie/darknet.git
61 lines
1.6 KiB
C
61 lines
1.6 KiB
C
#include "dropout_layer.h"
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#include "utils.h"
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#include "cuda.h"
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#include <stdlib.h>
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#include <stdio.h>
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dropout_layer make_dropout_layer(int batch, int inputs, float probability)
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{
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dropout_layer l = {0};
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l.type = DROPOUT;
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l.probability = probability;
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l.inputs = inputs;
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l.outputs = inputs;
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l.batch = batch;
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l.rand = calloc(inputs*batch, sizeof(float));
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l.scale = 1./(1.-probability);
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l.forward = forward_dropout_layer;
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l.backward = backward_dropout_layer;
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#ifdef GPU
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l.forward_gpu = forward_dropout_layer_gpu;
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l.backward_gpu = backward_dropout_layer_gpu;
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l.rand_gpu = cuda_make_array(l.rand, inputs*batch);
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#endif
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fprintf(stderr, "dropout p = %.2f %4d -> %4d\n", probability, inputs, inputs);
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return l;
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}
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void resize_dropout_layer(dropout_layer *l, int inputs)
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{
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l->rand = realloc(l->rand, l->inputs*l->batch*sizeof(float));
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#ifdef GPU
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cuda_free(l->rand_gpu);
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l->rand_gpu = cuda_make_array(l->rand, inputs*l->batch);
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#endif
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}
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void forward_dropout_layer(dropout_layer l, network net)
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{
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int i;
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if (!net.train) return;
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for(i = 0; i < l.batch * l.inputs; ++i){
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float r = rand_uniform(0, 1);
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l.rand[i] = r;
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if(r < l.probability) net.input[i] = 0;
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else net.input[i] *= l.scale;
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}
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}
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void backward_dropout_layer(dropout_layer l, network net)
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{
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int i;
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if(!net.delta) return;
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for(i = 0; i < l.batch * l.inputs; ++i){
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float r = l.rand[i];
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if(r < l.probability) net.delta[i] = 0;
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else net.delta[i] *= l.scale;
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}
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}
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