def dist(a, b):
    return sum((i-j)**2 for i, j in zip(a, b))
def _model_variable_scope(self):
    """Returns a variable scope that the model should be created under.

    If self.dtype is a castable type, model variable will be created in fp32
    then cast to self.dtype before being used.

    Returns:
      A variable scope for the model.
    """

    return tf.compat.v1.variable_scope(
        'resnet_model',
        custom_getter=self._custom_dtype_getter,
        reuse=tf.AUTO_REUSE)