text: #include "dropout_layer.h"
  #include "utils.h"
  #include "cuda.h"
  #include <stdlib.h>
  #include <stdio.h>
  
  dropout_layer make_dropout_layer(int batch, int inputs, float 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);
      l.forward = forward_dropout_layer;
      l.backward = backward_dropout_layer;
      #ifdef GPU
      l.forward_gpu = forward_dropout_layer_gpu;
      l.backward_gpu = backward_dropout_layer_gpu;
      l.rand_gpu = cuda_make_array(l.rand, inputs*batch);
      #endif
      fprintf(stderr, "dropout       p = %.2f               %4d  ->  %4d\n", probability, inputs, inputs);
      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 net)
  {
      int i;
      if (!net.train) return;
      for(i = 0; i < l.batch * l.inputs; ++i){
          float r = rand_uniform(0, 1);
          l.rand[i] = r;
          if(r < l.probability) net.input[i] = 0;
          else net.input[i] *= l.scale;
      }
  }
  
  void backward_dropout_layer(dropout_layer l, network net)
  {
      int i;
      if(!net.delta) return;
      for(i = 0; i < l.batch * l.inputs; ++i){
          float r = l.rand[i];
          if(r < l.probability) net.delta[i] = 0;
          else net.delta[i] *= l.scale;
      }
  }
  
  