From 76ee68f96d864a27312c9aa09856ddda559a5cd9 Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@gmail.com>
Date: Thu, 28 Aug 2014 02:11:46 +0000
Subject: [PATCH] Trying some stuff w/ dropout
---
src/network.c | 53 ++++++-----------------------------------------------
1 files changed, 6 insertions(+), 47 deletions(-)
diff --git a/src/network.c b/src/network.c
index 292bba0..3761bf9 100644
--- a/src/network.c
+++ b/src/network.c
@@ -28,25 +28,16 @@
}
#ifdef GPU
-void forward_network(network net, float *input, int train)
+void forward_network_gpu(network net, cl_mem input_cl, int train)
{
- cl_setup();
- size_t size = get_network_input_size(net);
- if(!net.input_cl){
- net.input_cl = clCreateBuffer(cl.context,
- CL_MEM_READ_WRITE, size*sizeof(float), 0, &cl.error);
- check_error(cl);
- }
- cl_write_array(net.input_cl, input, size);
- cl_mem input_cl = net.input_cl;
int i;
for(i = 0; i < net.n; ++i){
if(net.types[i] == CONVOLUTIONAL){
convolutional_layer layer = *(convolutional_layer *)net.layers[i];
forward_convolutional_layer_gpu(layer, input_cl);
input_cl = layer.output_cl;
- input = layer.output;
}
+ /*
else if(net.types[i] == CONNECTED){
connected_layer layer = *(connected_layer *)net.layers[i];
forward_connected_layer(layer, input, train);
@@ -72,10 +63,11 @@
forward_normalization_layer(layer, input);
input = layer.output;
}
+ */
}
}
-#else
+#endif
void forward_network(network net, float *input, int train)
{
@@ -118,7 +110,6 @@
}
}
}
-#endif
void update_network(network net)
{
@@ -275,45 +266,13 @@
float *X = calloc(batch*d.X.cols, sizeof(float));
float *y = calloc(batch*d.y.cols, sizeof(float));
- int i,j;
+ int i;
float sum = 0;
- int index = 0;
for(i = 0; i < n; ++i){
- for(j = 0; j < batch; ++j){
- index = rand()%d.X.rows;
- memcpy(X+j*d.X.cols, d.X.vals[index], d.X.cols*sizeof(float));
- memcpy(y+j*d.y.cols, d.y.vals[index], d.y.cols*sizeof(float));
- }
-
+ get_batch(d, batch, X, y);
float err = train_network_datum(net, X, y);
sum += err;
- //train_network_datum(net, X, y);
- /*
- float *y = d.y.vals[index];
- int class = get_predicted_class_network(net);
- correct += (y[class]?1:0);
- */
-
-/*
- for(j = 0; j < d.y.cols*batch; ++j){
- printf("%6.3f ", y[j]);
- }
- printf("\n");
- for(j = 0; j < d.y.cols*batch; ++j){
- printf("%6.3f ", get_network_output(net)[j]);
- }
- printf("\n");
- printf("\n");
- */
-
-
- //printf("%d %f %f\n", i,net.output[0], d.y.vals[index][0]);
- //if((i+1)%10 == 0){
- // printf("%d: %f\n", (i+1), (float)correct/(i+1));
- //}
}
- //printf("Accuracy: %f\n",(float) correct/n);
- //show_image(float_to_image(32,32,3,X), "Orig");
free(X);
free(y);
return (float)sum/(n*batch);
--
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