code: def test_layer_norm_brew_wrapper(self, X, gc, dc):
      axis = np.random.randint(0, len(X.shape))
      scale_dim = [1] * np.ndim(X)
      scale_dim[axis] = X.shape[axis]
  
      self.ws.create_blob("input").feed(X)
  
      model = ModelHelper(name="test_layer_norm_brew_wrapper")
      brew.layer_norm(
          model,
          "input",
          "output",
          dim_in=X.shape[axis:],
          axis=axis,
          epsilon=1e-4,
      )
  
      self.ws.create_net(model.param_init_net).run()
      self.ws.create_net(model.net).run()
  
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 9 for calling the TestLayerNormOp obj's underlying member method code with example usage: obj.test_layer_norm_brew_wrapper(X, gc, dc) without return types