snapshot...

modules/deeplearning/icing_fcn.py

@@ -571,12 +571,13 @@ class IcingIntensityFCN:
         num_filters = len(self.train_params) * 16
 
         input_2d = self.inputs[0]
-        conv = tf.keras.layers.Conv2D(num_filters, kernel_size=5, strides=1, padding=padding, activation=None)(input_2d)
-        print(conv.shape)
-        skip = conv
 
         if NOISE_TRAINING:
-            conv = tf.keras.layers.GaussianNoise(stddev=NOISE_STDDEV)(conv)
+            conv = tf.keras.layers.GaussianNoise(stddev=NOISE_STDDEV)(input_2d)
+
+        conv = tf.keras.layers.Conv2D(num_filters, kernel_size=5, strides=1, padding=padding, activation=activation)(conv)
+        print(conv.shape)
+        skip = conv
 
         conv = tf.keras.layers.Conv2D(num_filters, kernel_size=5, strides=1, padding=padding, activation=activation)(conv)
         conv = tf.keras.layers.MaxPool2D(padding=padding)(conv)