def optimistic_restore()

in utils.py [0:0]

• 21 lines of code
• 6 McCabe index (conditional complexity)

def optimistic_restore(session, save_file, v_prefix=None):
    reader = tf.train.NewCheckpointReader(save_file)
    saved_shapes = reader.get_variable_to_shape_map()

    var_names = sorted([(var.name, var.name.split(':')[0]) for var in tf.get_collection(
        tf.GraphKeys.GLOBAL_VARIABLES) if var.name.split(':')[0] in saved_shapes])
    restore_vars = []
    with tf.variable_scope('', reuse=True):
        for var_name, saved_var_name in var_names:
            try:
                curr_var = tf.get_variable(saved_var_name)
            except Exception as e:
                print(e)
                continue
            var_shape = curr_var.get_shape().as_list()
            if var_shape == saved_shapes[saved_var_name]:
                restore_vars.append(curr_var)
            else:
                print(var_name)
                print(var_shape, saved_shapes[saved_var_name])

    saver = tf.train.Saver(restore_vars)
    saver.restore(session, save_file)