Optimized resizing of network for random=1

src/convolutional_layer.c

@@ -359,6 +359,8 @@ void test_convolutional_layer()
 
 void resize_convolutional_layer(convolutional_layer *l, int w, int h)
 {
+	int old_w = l->w;
+	int old_h = l->h;
     l->w = w;
     l->h = h;
     int out_w = convolutional_out_width(*l);
@@ -378,19 +380,21 @@ void resize_convolutional_layer(convolutional_layer *l, int w, int h)
     }
 
 #ifdef GPU
-    cuda_free(l->delta_gpu);
-    cuda_free(l->output_gpu);
+	if (old_w < w || old_h < h) {
+		cuda_free(l->delta_gpu);
+		cuda_free(l->output_gpu);
 
-    l->delta_gpu =  cuda_make_array(l->delta,  l->batch*l->outputs);
-    l->output_gpu = cuda_make_array(l->output, l->batch*l->outputs);
+		l->delta_gpu = cuda_make_array(l->delta, l->batch*l->outputs);
+		l->output_gpu = cuda_make_array(l->output, l->batch*l->outputs);
 
-    if(l->batch_normalize){
-        cuda_free(l->x_gpu);
-        cuda_free(l->x_norm_gpu);
+		if (l->batch_normalize) {
+			cuda_free(l->x_gpu);
+			cuda_free(l->x_norm_gpu);
 
-        l->x_gpu = cuda_make_array(l->output, l->batch*l->outputs);
-        l->x_norm_gpu = cuda_make_array(l->output, l->batch*l->outputs);
-    }
+			l->x_gpu = cuda_make_array(l->output, l->batch*l->outputs);
+			l->x_norm_gpu = cuda_make_array(l->output, l->batch*l->outputs);
+		}
+	}
 #ifdef CUDNN
     cudnn_convolutional_setup(l);
 #endif

src/network.c

@@ -328,6 +328,12 @@ int resize_network(network *net, int w, int h)
     cuda_set_device(net->gpu_index);
     if(gpu_index >= 0){
         cuda_free(net->workspace);
+		if (net->input_gpu) {
+			cuda_free(*net->input_gpu);
+			*net->input_gpu = 0;
+			cuda_free(*net->truth_gpu);
+			*net->truth_gpu = 0;
+		}
     }
 #endif
     int i;
@@ -340,6 +346,7 @@ int resize_network(network *net, int w, int h)
     //fflush(stderr);
     for (i = 0; i < net->n; ++i){
         layer l = net->layers[i];
+		printf(" %d: layer = %d,", i, l.type);
         if(l.type == CONVOLUTIONAL){
             resize_convolutional_layer(&l, w, h);
         }else if(l.type == CROP){
@@ -371,13 +378,8 @@ int resize_network(network *net, int w, int h)
     }
 #ifdef GPU
     if(gpu_index >= 0){
-        if(net->input_gpu) {
-            cuda_free(*net->input_gpu);
-            *net->input_gpu = 0;
-            cuda_free(*net->truth_gpu);
-            *net->truth_gpu = 0;
-        }
         net->workspace = cuda_make_array(0, (workspace_size-1)/sizeof(float)+1);
+		printf(" CUDA allocate done! \n");
     }else {
         free(net->workspace);
         net->workspace = calloc(1, workspace_size);