code: def __init__(
      self,
      normalized_shape,
      eps=1e-05,
      weight=True,
      dtype=None,
      device=None,
  ):
      super().__init__(
          normalized_shape=normalized_shape,
          eps=eps,
          weight=weight,
          dtype=dtype,
          device=device,
      )
  
imports: import math
  import os
  import warnings
  from typing import List, Optional, Tuple, Union
  import torch
  import torch.nn
  import torch.nn.functional
  from transformers import PreTrainedModel, PreTrainedTokenizer, PreTrainedTokenizerFast
  from transformers.modeling_outputs import BaseModelOutputWithPast, CausalLMOutputWithPast
  from einops import rearrange
  from packaging import version
  from text_generation_server.utils.layers import TensorParallelEmbedding, TensorParallelColumnLinear, TensorParallelRowLinear, TensorParallelHead, get_linear
label_desc: Use image node_id 1 to create a new LPRMSNorm object from inherited base classes: RMSNorm with example: obj = LPRMSNorm(normalized_shape, eps, weight, dtype, device)