snapshot...

modules/deeplearning/srcnn_l1b_l2.py

@@ -515,9 +515,7 @@ class SRCNN:
         self.test_loss(t_loss)
         self.test_accuracy(labels, pred)
 
-    def predict(self, mini_batch):
-        inputs = [mini_batch[0]]
-        labels = mini_batch[1]
+    def predict(self, inputs, labels):
         pred = self.model([inputs], training=False)
         t_loss = self.loss(labels, pred)
 
@@ -659,7 +657,7 @@ class SRCNN:
             ds = tf.data.Dataset.from_tensor_slices((data, label))
             ds = ds.batch(BATCH_SIZE)
             for mini_batch_test in ds:
-                self.predict(mini_batch_test)
+                self.predict(mini_batch_test[0], mini_batch_test[1])
 
         print('loss, acc: ', self.test_loss.result().numpy(), self.test_accuracy.result().numpy())