test...

modules/deeplearning/espcn.py

@@ -357,18 +357,18 @@ class ESPCN:
 
         conv_b = build_residual_conv2d_block(conv_b, num_filters, 'Residual_Block_1')
 
-        conv_b = build_residual_conv2d_block(conv_b, num_filters, 'Residual_Block_2')
-
-        conv_b = build_residual_conv2d_block(conv_b, num_filters, 'Residual_Block_3')
-
-        conv_b = build_residual_conv2d_block(conv_b, num_filters, 'Residual_Block_4')
+        # conv_b = build_residual_conv2d_block(conv_b, num_filters, 'Residual_Block_2')
+        #
+        # conv_b = build_residual_conv2d_block(conv_b, num_filters, 'Residual_Block_3')
+        #
+        # conv_b = build_residual_conv2d_block(conv_b, num_filters, 'Residual_Block_4')
 
         conv_b = tf.keras.layers.Conv2D(num_filters, kernel_size=3, strides=1, padding=padding)(conv_b)
 
         conv = conv + conv_b
         print(conv.shape)
 
-        conv = tf.keras.layers.Conv2D(num_filters * (factor ** 2), 3, padding='same')(conv)
+        #conv = tf.keras.layers.Conv2D(num_filters * (factor ** 2), 3, padding='same')(conv)
         # conv = tf.keras.layers.Conv2D((factor ** 2), 3, padding='same')(conv)
         print(conv.shape)