Maybe some stuff changed

src/cnn.c

@@ -957,59 +957,8 @@ void test_distribution()
 
 int main(int argc, char *argv[])
 {
-    test_gpu_blas();
-    //test_blas();
-    //train_assira();
-	//test_visualize();
-    //test_distribution();
-    //feenableexcept(FE_DIVBYZERO | FE_INVALID | FE_OVERFLOW);
-    //train_imagenet();
-    //test_imagenet();
-
-    //test_blas();
-    //test_visualize();
     //test_gpu_blas();
-    //test_blas();
-    //test_convolve_matrix();
-    //    test_im2row();
-    //test_split();
-    //test_ensemble();
-    //test_nist_single();
-    //test_nist();
-    //train_nist();
-    //test_convolutional_layer();
-    //test_col2im();
-    //test_cifar10();
-    //train_cifar10();
-    //test_vince();
-    //test_full();
-    //tune_VOC();
-    //features_VOC_image(argv[1], argv[2], argv[3], 0);
-    //features_VOC_image(argv[1], argv[2], argv[3], 1);
-    //train_VOC();
-    //features_VOC_image(argv[1], argv[2], argv[3], 0, 4);
-    //features_VOC_image(argv[1], argv[2], argv[3], 1, 4);
-    //features_VOC_image_size(argv[1], atoi(argv[2]), atoi(argv[3]));
-    //visualize_imagenet_features("data/assira/train.list");
-    //visualize_imagenet_topk("data/VOC2012.list");
-    //visualize_cat();
-    //flip_network();
-    //test_visualize();
-    //test_parser();
+    train_imagenet();
     fprintf(stderr, "Success!\n");
-    //test_random_preprocess();
-    //test_random_classify();
-    //test_parser();
-    //test_backpropagate();
-    //test_ann();
-    //test_convolve();
-    //test_upsample();
-    //test_rotate();
-    //test_load();
-    //test_network();
-    //test_convolutional_layer();
-    //verify_convolutional_layer();
-    //test_color();
-    //cvWaitKey(0);
     return 0;
 }

src/convolutional_layer.c

@@ -342,7 +342,7 @@ void bias_output_gpu(const convolutional_layer layer)
     check_error(cl);
 }
 
-//#define TIMEIT
+#define TIMEIT
 
 void forward_convolutional_layer_gpu(convolutional_layer layer, cl_mem in)
 {

src/gemm.c

@@ -176,14 +176,12 @@ void gemm_ongpu(int TA, int TB, int M, int N, int K, float ALPHA,
         float BETA,
         cl_mem C_gpu, int ldc)
 {
-    /*
     cl_setup();
     cl_command_queue queue = cl.queue;
     cl_event event;
     cl.error = clblasSgemm(clblasRowMajor, TA?clblasTrans:clblasNoTrans, TB?clblasTrans:clblasNoTrans,M, N, K,ALPHA, A_gpu, 0, lda,B_gpu, 0, ldb,BETA, C_gpu, 0, ldc,1, &queue, 0, NULL, &event);
-    */
 
-    gemm_ongpu_new(TA, TB, M, N, K, ALPHA, A_gpu, lda, B_gpu, ldb, BETA, C_gpu, ldc);
+    //gemm_ongpu_new(TA, TB, M, N, K, ALPHA, A_gpu, lda, B_gpu, ldb, BETA, C_gpu, ldc);
 }
 
 void gemm_ongpu_new(int TA, int TB, int M, int N, int K, float ALPHA, 
@@ -327,7 +325,7 @@ void time_gpu_random_matrix(int TA, int TB, int m, int k, int n)
 
 void time_ongpu(int TA, int TB, int m, int k, int n)
 {
-    int iter = 100;
+    int iter = 128;
     float *a = random_matrix(m,k);
     float *b = random_matrix(k,n);
 
@@ -345,10 +343,10 @@ void time_ongpu(int TA, int TB, int m, int k, int n)
     for(i = 0; i<iter; ++i){
         gemm_ongpu(TA,TB,m,n,k,1,a_cl,lda,b_cl,ldb,1,c_cl,n);
     }
-    int flop = m*n*(2*k+3)*iter;
-    float gflop = flop/pow(10., 9);
+    double flop = m*n*(2.*k+3.)*iter;
+    double gflop = flop/pow(10., 9);
     end = clock();
-    float seconds = sec(end-start);
+    double seconds = sec(end-start);
     printf("Matrix Multiplication %dx%d * %dx%d, TA=%d, TB=%d: %lf s, %lf GFLOPS\n",m,k,k,n, TA, TB, seconds, gflop/seconds);
     clReleaseMemObject(a_cl);
     clReleaseMemObject(b_cl);

src/network.c

@@ -38,6 +38,7 @@ void forward_network_gpu(network net, cl_mem input, cl_mem truth, int train)
     //printf("start\n");
     int i;
     for(i = 0; i < net.n; ++i){
+        clock_t time = clock();
         if(net.types[i] == CONVOLUTIONAL){
             convolutional_layer layer = *(convolutional_layer *)net.layers[i];
             forward_convolutional_layer_gpu(layer, input);
@@ -62,6 +63,7 @@ void forward_network_gpu(network net, cl_mem input, cl_mem truth, int train)
             forward_softmax_layer_gpu(layer, input);
             input = layer.output_cl;
         }
+        printf("%d %f\n", i, sec(clock()-time));
         /*
            else if(net.types[i] == CROP){
            crop_layer layer = *(crop_layer *)net.layers[i];