code: def test_layer_norm(self):
      def layer_norm(x, weight, bias):
          dim = -1
          eps = 1e-5
          mean = torch.mean(x, dim, keepdim=True)
          centered = x - mean
          var = torch.sum(
              centered * centered, dim, keepdim=True
          ) / x.size(-1)
          rvar = 1.0 / torch.sqrt(var + eps)
          normed = (x - mean) * rvar
          return normed * weight + bias
  
      bs = 10
      ln_size = 16
      layer_norm_inps = [(bs, ln_size), (ln_size,), (ln_size,)]
      run_and_compare_activation(self, layer_norm, layer_norm_inps)
  
imports: import torch
  import torch.nn
  import torch.fx
  from functorch import make_fx
  from torch.nn import functional
  from functorch.compile import memory_efficient_fusion
  from torch._functorch.compile_utils import fx_graph_cse
  from torch.testing._internal.common_utils import TestCase, run_tests
  import inspect
  import random
  from typing import Callable
  import unittest
label_desc: Use image node_id 6 for calling the TestMemoryEfficientOpAuthoring obj's underlying member method code with example usage: obj.test_layer_norm() and returns: unknown