code: def propose_layers_with_shapes(model):
      proposed_layers = propose_layers(model.graph_def)
      with tf.Graph().as_default(), tf.Session() as sess:
          t_input = tf.placeholder(tf.float32, [1] + model.image_shape)
          T = render.import_model(model, t_input, t_input)
          t_shapes = [
              tf.shape(T(node.name))[1:] for node in proposed_layers
          ]
          shapes = sess.run(
              t_shapes, {t_input: np.zeros([1] + model.image_shape)}
          )
      return zip(proposed_layers, shapes)
  
imports: import lucid.optvis.render
label_desc: Use image node_id 4 for calling a global function with example usage: propose_layers_with_shapes(model) and returns: zip