fix error quantize_image's result type.

fix warning printf params, in backward_network_gpu.

include/darknet.h

@@ -960,7 +960,7 @@ LIB_API void optimize_picture(network *net, image orig, int max_layer, float sca
 LIB_API void make_image_red(image im);
 LIB_API image make_attention_image(int img_size, float *original_delta_cpu, float *original_input_cpu, int w, int h, int c);
 LIB_API image resize_image(image im, int w, int h);
-LIB_API image quantize_image(image im);
+LIB_API void quantize_image(image im);
 LIB_API void copy_image_from_bytes(image im, char *pdata);
 LIB_API image letterbox_image(image im, int w, int h);
 LIB_API void rgbgr_image(image im);

src/image.c

@@ -1303,7 +1303,7 @@ float bilinear_interpolate(image im, float x, float y, int c)
     return val;
 }
 
-image quantize_image(image im)
+void quantize_image(image im)
 {
     int size = im.c * im.w * im.h;
     int i;

src/network_kernels.cu

@@ -246,7 +246,7 @@ void backward_network_gpu(network net, network_state state)
     if (net.adversarial) {
         int x_size = get_network_input_size(net)*net.batch;
         printf(" x_size = %d, original_delta = %p, original_input = %p, net.learning_rate = %d \n",
-            x_size, original_delta, original_input, x_size, net.learning_rate);
+            x_size, original_delta, original_input, net.learning_rate);
         axpy_ongpu(x_size, net.learning_rate, original_delta, 1, original_input, 1);
         constrain_min_max_ongpu(x_size, 0, 1, original_input, 1);
     }