From e92f7d301c971b4d27aa3dcd1e4047e94f04b3fc Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@gmail.com>
Date: Wed, 25 Mar 2015 01:27:12 +0000
Subject: [PATCH] smaller gridsize in bias
---
src/dropout_layer.c | 21 +++++++++------------
1 files changed, 9 insertions(+), 12 deletions(-)
diff --git a/src/dropout_layer.c b/src/dropout_layer.c
index 32a3408..7fbf8ff 100644
--- a/src/dropout_layer.c
+++ b/src/dropout_layer.c
@@ -1,4 +1,5 @@
#include "dropout_layer.h"
+#include "params.h"
#include "utils.h"
#include "cuda.h"
#include <stdlib.h>
@@ -11,11 +12,9 @@
layer->probability = probability;
layer->inputs = inputs;
layer->batch = batch;
- layer->output = calloc(inputs*batch, sizeof(float));
layer->rand = calloc(inputs*batch, sizeof(float));
layer->scale = 1./(1.-probability);
#ifdef GPU
- layer->output_gpu = cuda_make_array(layer->output, inputs*batch);
layer->rand_gpu = cuda_make_array(layer->rand, inputs*batch);
#endif
return layer;
@@ -23,36 +22,34 @@
void resize_dropout_layer(dropout_layer *layer, int inputs)
{
- layer->output = realloc(layer->output, layer->inputs*layer->batch*sizeof(float));
layer->rand = realloc(layer->rand, layer->inputs*layer->batch*sizeof(float));
#ifdef GPU
- cuda_free(layer->output_gpu);
cuda_free(layer->rand_gpu);
- layer->output_gpu = cuda_make_array(layer->output, inputs*layer->batch);
layer->rand_gpu = cuda_make_array(layer->rand, inputs*layer->batch);
#endif
}
-void forward_dropout_layer(dropout_layer layer, float *input)
+void forward_dropout_layer(dropout_layer layer, network_state state)
{
int i;
+ if (!state.train) return;
for(i = 0; i < layer.batch * layer.inputs; ++i){
float r = rand_uniform();
layer.rand[i] = r;
- if(r < layer.probability) layer.output[i] = 0;
- else layer.output[i] = input[i]*layer.scale;
+ if(r < layer.probability) state.input[i] = 0;
+ else state.input[i] *= layer.scale;
}
}
-void backward_dropout_layer(dropout_layer layer, float *delta)
+void backward_dropout_layer(dropout_layer layer, network_state state)
{
int i;
- if(!delta) return;
+ if(!state.delta) return;
for(i = 0; i < layer.batch * layer.inputs; ++i){
float r = layer.rand[i];
- if(r < layer.probability) delta[i] = 0;
- else delta[i] *= layer.scale;
+ if(r < layer.probability) state.delta[i] = 0;
+ else state.delta[i] *= layer.scale;
}
}
--
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