snapshot...

modules/deeplearning/srcnn_l1b_l2.py

@@ -216,10 +216,10 @@ class SRCNN:
 
         data_norm = []
         for k, param in enumerate(data_params):
-            data = data[:, k, 3:131:2, 3:131:2]
-            data = resample(y_64, x_64, data, s, t)
-            data = normalize(data, param, mean_std_dct, add_noise=add_noise, noise_scale=noise_scale)
-            data_norm.append(data)
+            tmp = data[:, k, 3:131:2, 3:131:2]
+            tmp = resample(y_64, x_64, tmp, s, t)
+            tmp = normalize(tmp, param, mean_std_dct, add_noise=add_noise, noise_scale=noise_scale)
+            data_norm.append(tmp)
         data = np.stack(data_norm, axis=3)
         data = data.astype(np.float32)