code: def test_layernorm(dshape):
      layer = nn.LayerNorm(in_channels=10)
      print("checking layer {}\nshape: {}.".format(layer, dshape))
      layer.initialize()
      x = mx.np.ones(shape=dshape)
      x.attach_grad()
      with mx.autograd.record():
          out = layer(x)
      out.backward()
  
      np_out = out.asnumpy()
      np_dx = x.grad.asnumpy()
  
      layer.hybridize()
  
      x = mx.np.ones(shape=dshape)
      x.attach_grad()
      with mx.autograd.record():
          out = layer(x)
      out.backward()
  
      mx.test_utils.assert_almost_equal(
          np_out, out.asnumpy(), rtol=1e-5, atol=1e-6
      )
      mx.test_utils.assert_almost_equal(
          np_dx, x.grad.asnumpy(), rtol=1e-5, atol=1e-6
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  import os
  from uuid import uuid4
  import numpy
  import mxnet
  from mxnet import gluon, autograd, np, npx
  from mxnet.test_utils import use_np, assert_almost_equal, check_gluon_hybridize_consistency, assert_allclose
  from mxnet.gluon import nn
  from mxnet.base import MXNetError
  import random
  import pytest
label_desc: Use image node_id 27 for calling a global function with example usage: test_layernorm(dshape) without return types