mirror of https://github.com/AlexeyAB/darknet.git
89 lines
2.9 KiB
C
89 lines
2.9 KiB
C
#include "dropout_layer.h"
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#include "utils.h"
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#include "dark_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, int dropblock, float dropblock_size_rel, int dropblock_size_abs, int w, int h, int c)
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{
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dropout_layer l = { (LAYER_TYPE)0 };
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l.type = DROPOUT;
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l.probability = probability;
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l.dropblock = dropblock;
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l.dropblock_size_rel = dropblock_size_rel;
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l.dropblock_size_abs = dropblock_size_abs;
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if (l.dropblock) {
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l.out_w = l.w = w;
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l.out_h = l.h = h;
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l.out_c = l.c = c;
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if (l.w <= 0 || l.h <= 0 || l.c <= 0) {
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printf(" Error: DropBlock - there must be positive values for: l.w=%d, l.h=%d, l.c=%d \n", l.w, l.h, l.c);
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exit(0);
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}
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}
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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 = (float*)xcalloc(inputs * batch, sizeof(float));
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l.scale = 1./(1.0 - 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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if (l.dropblock) {
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l.drop_blocks_scale = cuda_make_array_pinned(l.rand, l.batch);
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l.drop_blocks_scale_gpu = cuda_make_array(l.rand, l.batch);
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}
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#endif
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if (l.dropblock) {
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if(l.dropblock_size_abs) fprintf(stderr, "dropblock p = %.3f l.dropblock_size_abs = %d %4d -> %4d\n", probability, l.dropblock_size_abs, inputs, inputs);
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else fprintf(stderr, "dropblock p = %.3f l.dropblock_size_rel = %.2f %4d -> %4d\n", probability, l.dropblock_size_rel, inputs, inputs);
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}
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else fprintf(stderr, "dropout p = %.3f %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->inputs = l->outputs = inputs;
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l->rand = (float*)xrealloc(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, l->inputs*l->batch);
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if (l->dropblock) {
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cudaFreeHost(l->drop_blocks_scale);
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l->drop_blocks_scale = cuda_make_array_pinned(l->rand, l->batch);
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cuda_free(l->drop_blocks_scale_gpu);
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l->drop_blocks_scale_gpu = cuda_make_array(l->rand, l->batch);
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}
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#endif
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}
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void forward_dropout_layer(dropout_layer l, network_state state)
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{
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int i;
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if (!state.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) state.input[i] = 0;
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else state.input[i] *= l.scale;
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}
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}
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void backward_dropout_layer(dropout_layer l, network_state state)
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{
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int i;
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if(!state.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) state.delta[i] = 0;
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else state.delta[i] *= l.scale;
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}
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}
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