code: def meta_ln_backward(
      dY: torch.Tensor,
      input: torch.Tensor,
      normalized_shape,
      mean,
      rstd,
      weight,
      bias,
      grad_input_mask,
  ):
      dX = torch.empty_like(input)
      dgamma = torch.empty_like(weight)
      dbeta = torch.empty_like(bias)
      return dX, dgamma, dbeta
  
imports: from typing import List, Optional, Union
  import torch
  from torch.utils._pytree import tree_map
label_desc: Use image node_id 19 for calling a global function with example usage: meta_ln_backward(dY, input, normalized_shape, mean, rstd, weight, bias, grad_input_mask) and returns: dX,  dgamma,  dbeta