minor...

modules/deeplearning/icing_cnn.py

@@ -215,25 +215,6 @@ class IcingIntensityNN:
         label = label.astype(np.int32)
         label = np.where(label == -1, 0, label)
 
-        # # Augmentation, TODO: work into Dataset.map (efficiency)
-        # data_aug = []
-        # label_aug = []
-        # for k in range(label.shape[0]):
-        #     if label[k] == 3 or label[k] == 4 or label[k] == 5 or label[k] == 6:
-        #         data_aug.append(tf.image.flip_up_down(data[k,]).numpy())
-        #         data_aug.append(tf.image.flip_left_right(data[k,]).numpy())
-        #         data_aug.append(tf.image.rot90(data[k,]).numpy())
-        #         label_aug.append(label[k])
-        #         label_aug.append(label[k])
-        #         label_aug.append(label[k])
-        #
-        # data_aug = np.stack(data_aug)
-        # label_aug = np.stack(label_aug)
-        #
-        # data = np.concatenate([data, data_aug])
-        # label = np.concatenate([label, label_aug])
-        # # --------------------------------------------------------
-
         # binary, two class
         if NumClasses == 2:
             label = np.where(label != 0, 1, label)