code: def __call__(self, x: Tensor):
      x = (
          x.reshape(x.shape[0], self.num_features, -1)
          .layernorm(eps=self.eps)
          .reshape(x.shape)
      )
      if self.weight is None or self.bias is None:
          return x
      return x * self.weight.reshape(
          1, -1, *[1] * (len(x.shape) - 2)
      ) + self.bias.reshape(1, -1, *[1] * (len(x.shape) - 2))
  
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 InstanceNorm obj's underlying member method code with example usage: obj.__call__(x) and returns: unknown, x