snapshot...

modules/deeplearning/cnn_cld_frac.py

@@ -458,14 +458,13 @@ class CNN:
         if NOISE_TRAINING:
             conv = conv_b = tf.keras.layers.GaussianNoise(stddev=NOISE_STDDEV)(conv)
 
-        conv_b = build_residual_block_1x1(conv_b, num_filters, activation, 'Residual_Block_1')
+        conv = build_residual_block_1x1(conv, num_filters, activation, 'Residual_Block_1')
 
-        conv_b = build_residual_block_1x1(conv_b, num_filters, activation, 'Residual_Block_2')
+        conv = build_residual_block_1x1(conv, num_filters, activation, 'Residual_Block_2')
 
-        conv_b = build_residual_block_1x1(conv_b, num_filters, activation, 'Residual_Block_3')
+        conv = build_residual_block_1x1(conv, num_filters, activation, 'Residual_Block_3')
 
         # conv = conv + conv_b
-        conv = conv_b
         print(conv.shape)
 
         self.logits = tf.keras.layers.Conv2D(NumLogits, kernel_size=1, strides=1, padding=padding, name='regression')(conv)