code: def __call__(self, x: Tensor):
      assert (
          self.normalized_shape
          == x.shape[-len(self.normalized_shape) :]
      ), f"last dimensions of {x.shape} must match {self.normalized_shape}"
      x = x.layernorm(eps=self.eps, axis=self.axis)
      if not self.elementwise_affine:
          return x
      return x * self.weight + self.bias
  
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 2 for calling the LayerNorm obj's underlying member method code with example usage: obj.__call__(x) and returns: unknown, x