class_docstr: Maps individual tokens to sequences of character ids, compatible with ELMo.
  To be consistent with previously trained models, we include it here as special of existing
  character indexers.
  
  We allow to add optional additional special tokens with designated
  character ids with `tokens_to_add`.
class_docstr_tok: ["Maps","individual","tokens","to","sequences","of","character","ids",",","compatible","with","ELMo",".","To","be","consistent","with","previously","trained","models",",","we","include","it","here","as","special","of","existing","character","indexers",".","We","allow","to","add","optional","additional","special","tokens","with","designated","character","ids","with","`","tokens_to_add","`","."]
code: def __init__(self, tokens_to_add: Dict[str, int] = None) -> None:
      self.tokens_to_add = tokens_to_add or {}
  
file_path: allennlp/allennlp/data/token_indexers/elmo_indexer.py
imports: from typing import Dict, List
  import torch
  from allennlp.common.util import pad_sequence_to_length
  from allennlp.data.tokenizers import Token
  from allennlp.data.token_indexers.token_indexer import TokenIndexer, IndexedTokenList
  from allennlp.data.vocabulary import Vocabulary
label_desc: Use image node_id 1 to create a new ELMoCharacterMapper object  with example: obj = ELMoCharacterMapper(tokens_to_add)