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/cnn.c | 55 +++++++++++++++++++++++++++++++++++++++++++++++++++----
1 files changed, 51 insertions(+), 4 deletions(-)
diff --git a/src/cnn.c b/src/cnn.c
index 72ad4a1..0cd6da3 100644
--- a/src/cnn.c
+++ b/src/cnn.c
@@ -32,6 +32,51 @@
show_image_layers(edge, "Test Convolve");
}
+#ifdef GPU
+
+void test_convolutional_layer()
+{
+ int i;
+ image dog = load_image("data/dog.jpg",256,256);
+ network net = parse_network_cfg("cfg/convolutional.cfg");
+// data test = load_cifar10_data("data/cifar10/test_batch.bin");
+// float *X = calloc(net.batch*test.X.cols, sizeof(float));
+// float *y = calloc(net.batch*test.y.cols, sizeof(float));
+ int in_size = get_network_input_size(net)*net.batch;
+ int size = get_network_output_size(net)*net.batch;
+float *X = calloc(in_size, sizeof(float));
+ for(i = 0; i < in_size; ++i){
+ X[i] = dog.data[i%get_network_input_size(net)];
+ }
+// get_batch(test, net.batch, X, y);
+ clock_t start, end;
+ cl_mem input_cl = cl_make_array(X, in_size);
+
+ forward_network_gpu(net, input_cl, 1);
+ start = clock();
+ forward_network_gpu(net, input_cl, 1);
+ end = clock();
+ float gpu_sec = (float)(end-start)/CLOCKS_PER_SEC;
+ float *gpu_out = calloc(size, sizeof(float));
+ memcpy(gpu_out, get_network_output(net), size*sizeof(float));
+
+ start = clock();
+ forward_network(net, X, 1);
+ end = clock();
+ float cpu_sec = (float)(end-start)/CLOCKS_PER_SEC;
+ float *cpu_out = calloc(size, sizeof(float));
+ memcpy(cpu_out, get_network_output(net), size*sizeof(float));
+
+ float sum = 0;
+ for(i = 0; i < size; ++i) {
+ //printf("%f, %f\n", gpu_out[i], cpu_out[i]);
+ sum += pow(gpu_out[i] - cpu_out[i], 2);
+ }
+ printf("gpu: %f sec, cpu: %f sec, diff: %f, size: %d\n", gpu_sec, cpu_sec, sum, size);
+}
+
+#endif
+
void test_convolve_matrix()
{
image dog = load_image("dog.jpg",300,400);
@@ -325,7 +370,7 @@
void train_nist()
{
srand(222222);
- network net = parse_network_cfg("cfg/nist_final.cfg");
+ network net = parse_network_cfg("cfg/nist.cfg");
data train = load_categorical_data_csv("data/mnist/mnist_train.csv", 0, 10);
data test = load_categorical_data_csv("data/mnist/mnist_test.csv",0,10);
translate_data_rows(train, -144);
@@ -349,7 +394,7 @@
mean_array(get_network_output_layer(net,3), 100),
mean_array(get_network_output_layer(net,4), 100));
*/
- save_network(net, "cfg/nist_final2.cfg");
+ //save_network(net, "cfg/nist_final2.cfg");
//printf("%5d Training Loss: %lf, Params: %f %f %f, ",count*1000, loss, lr, momentum, decay);
//end = clock();
@@ -798,7 +843,7 @@
{
//train_full();
//test_distribution();
- feenableexcept(FE_DIVBYZERO | FE_INVALID | FE_OVERFLOW);
+ //feenableexcept(FE_DIVBYZERO | FE_INVALID | FE_OVERFLOW);
//test_blas();
//test_visualize();
@@ -809,7 +854,9 @@
//test_split();
//test_ensemble();
//test_nist_single();
- test_nist();
+ //test_nist();
+ train_nist();
+ //test_convolutional_layer();
//test_cifar10();
//train_cifar10();
//test_vince();
--
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