code: def __init__(
      self,
      normalized_shape: Union[int, Tuple[int, ...]],
      eps: float = 1e-5,
      elementwise_affine: bool = True,
  ):
      self.normalized_shape = (
          (normalized_shape,)
          if isinstance(normalized_shape, int)
          else tuple(normalized_shape)
      )
      self.axis, self.eps, self.elementwise_affine = (
          tuple(-1 - i for i in range(len(self.normalized_shape))),
          eps,
          elementwise_affine,
      )
      self.weight, self.bias = (
          (
              Tensor.ones(*self.normalized_shape),
              Tensor.zeros(*self.normalized_shape),
          )
          if elementwise_affine
          else (None, None)
      )
  
imports: import math
  from typing import Optional, Union, Tuple, cast
  from tinygrad.tensor import Tensor
  from tinygrad.helpers import prod
  from tinygrad.nn import optim, state
label_desc: Use image node_id 1 to create a new LayerNorm object  with example: obj = LayerNorm(normalized_shape, eps, elementwise_affine)