option to use GaussianNoise as input to CNN_2D

modules/deeplearning/icing_cnn.py

@@ -535,7 +535,12 @@ class IcingIntensityNN:
 
         num_filters = len(train_params) * 2
 
-        conv = tf.keras.layers.Conv2D(num_filters, 5, strides=[1, 1], padding=padding, activation=activation)(self.inputs[0])
+        if NOISE_TRAINING:
+            input_2d = tf.keras.layers.GaussianNoise(stddev=NOISE_STDDEV)(self.inputs[0])
+        else:
+            input_2d = self.inputs[0]
+
+        conv = tf.keras.layers.Conv2D(num_filters, 5, strides=[1, 1], padding=padding, activation=activation)(input_2d)
         conv = tf.keras.layers.MaxPool2D(padding=padding)(conv)
         conv = tf.keras.layers.BatchNormalization()(conv)
         print(conv.shape)