code: def __init__(
      self,
      normalized_shape,
      eps=1e-6,
      data_format=torch.contiguous_format,
  ):
      super().__init__()
      self.weight = nn.Parameter(torch.ones(normalized_shape))
      self.bias = nn.Parameter(torch.zeros(normalized_shape))
      self.eps = eps
      self.data_format = data_format
      if self.data_format not in [torch.contiguous_format]:
          raise NotImplementedError
      self.normalized_shape = (normalized_shape,)
  
imports: import os
  import time
  import torch
  import torch.distributed
  import torch.multiprocessing
  import torch.nn
  from torch.distributed._tensor import DeviceMesh, distribute_module, distribute_tensor, Replicate, Shard
label_desc: Use image node_id 1 to create a new LayerNorm object from inherited base classes: nn with example: obj = LayerNorm(normalized_shape, eps, data_format)