Start adding unsupervised train loop

unsupervised/models.py

@@ -9,8 +9,8 @@ def wrap_mobilenet_nnconv5_for_utrain(model):
 
     This just exposes the lower disparity layers as outputs, so they can be used to train at different scales/image
     resolutions.
-    :param model:
-    :return:
+    :param model: Fast Depth model to wrap
+    :return: Keras model that takes same input as model and outputs the model output plus 3 disparity layers
     """
     input = model.input
     disp_1 = model.get_layer('conv_pw_%d_relu' % 15).output