code: def _layer_norm_with_affine_ref(axis, epsilon, X, gamma, beta):
      Y, mean, std = _layer_norm_ref(axis, epsilon, X)
      Y = Y * gamma + beta
      return (Y, mean, std)
  
imports: from caffe2.python import brew, core, workspace
  from caffe2.python.model_helper import ModelHelper
  from functools import partial
  from hypothesis import given, settings
  from typing import Optional, Tuple
  import caffe2.python.hypothesis_test_util
  import caffe2.python.serialized_test.serialized_test_util
  import hypothesis.strategies
  import numpy
  import torch
  import unittest
  from ._utils import assert_allclose
label_desc: Use image node_id 2 for calling a global function with example usage: _layer_norm_with_affine_ref(axis, epsilon, X, gamma, beta) and returns: Y,  mean,  std