code: def layer_norm(
      input: Tensor,
      normalized_shape: ShapeType,
      weight: Optional[Tensor] = None,
      bias: Optional[Tensor] = None,
      eps: float = 1e-5,
  ) -> Tensor:
      """
      Reference implementation of :func:`torch.nn.functional.layer_norm`.
      """
      return torch.native_layer_norm(
          input, normalized_shape, weight, bias, eps
      )[0]
  
imports: import math
  from functools import wraps
  from typing import Callable, Optional, Union
  import torch
  import torch._prims
  import torch._prims_common
  import torch._refs
  from torch._decomp import register_decomposition
  from torch._prims_common import ELEMENTWISE_TYPE_PROMOTION_KIND, NumberType, ShapeType, TensorLike, TensorLikeType
  from torch._prims_common.wrappers import elementwise_type_promotion_wrapper, elementwise_unary_scalar_wrapper, out_wrapper
  from torch._refs import _make_inplace
label_desc: Use image node_id 9 for calling a global function with example usage: layer_norm(input, normalized_shape, weight, bias, eps) and returns: torch