code: def __init__(self, ori_emebedding, additional_size):
      super().__init__()
      self.ori_emb = ori_emebedding
  
      orig_emb_std, orig_emb_mean = torch.std_mean(
          ori_emebedding.weight
      )
      self.add_emb = torch.nn.Embedding(
          additional_size, ori_emebedding.embedding_dim
      )
      torch.nn.init.normal_(
          self.add_emb.weight,
          orig_emb_mean.item(),
          orig_emb_std.item(),
      )
      self.num_embeddings = (
          ori_emebedding.num_embeddings + additional_size
      )
  
file_path: espnet/espnet2/asr/decoder/whisper_decoder.py
imports: import copy
  from typing import Any, List, Tuple
  import torch
  from typeguard import check_argument_types
  from espnet2.asr.decoder.abs_decoder import AbsDecoder
  from espnet.nets.scorer_interface import BatchScorerInterface
label_desc: Use image node_id 1 to create a new ExpandedTokenEmbedding object from inherited base classes: torch.nn with example: obj = ExpandedTokenEmbedding(ori_emebedding, additional_size)