snapshot...

modules/deeplearning/srcnn_l1b_l2.py

@@ -411,12 +411,12 @@ class SRCNN:
 
         input_2d = self.inputs[0]
         print('input: ', input_2d.shape)
-        input_2d = tf.keras.layers.Conv2D(num_filters, kernel_size=3, strides=1, padding='VALID', activation=None)(input_2d)
+        ##input_2d = tf.keras.layers.Conv2D(num_filters, kernel_size=3, strides=1, padding='VALID', activation=None)(input_2d)
         # conv = input_2d
         # print('input: ', conv.shape)
         print('input: ', input_2d.shape)
 
-        conv = conv_b = tf.keras.layers.Conv2D(num_filters, kernel_size=3, kernel_initializer='he_uniform', activation=activation, padding='SAME')(input_2d)
+        conv = conv_b = tf.keras.layers.Conv2D(num_filters, kernel_size=3, kernel_initializer='he_uniform', activation=activation, padding='VALID')(input_2d)
         print(conv.shape)
 
         if NOISE_TRAINING: