code: def _lookup_tokens(
      self,
      tokens: List[Tuple[str, int, int]],
      max_seq_len: Optional[int] = None,
  ) -> Tuple[List[int], List[int], List[int]]:
      if max_seq_len is None:
          max_seq_len = self.max_seq_len
  
      return self.vocab_lookup(
          tokens,
          bos_idx=self.vocab.eos_idx,
          eos_idx=self.vocab.eos_idx,
          use_eos_token_for_bos=True,
          max_seq_len=max_seq_len,
      )
  
imports: from typing import Any, Dict, List, Optional, Tuple
  import torch
  from fairseq.data.legacy.masked_lm_dictionary import MaskedLMDictionary
  from pytext.common.constants import SpecialTokens
  from pytext.config.component import ComponentType, create_component
  from pytext.data.bert_tensorizer import BERTTensorizerBase, BERTTensorizerBaseScriptImpl, build_fairseq_vocab
  from pytext.data.tokenizers import Tokenizer
  from pytext.data.utils import Vocabulary
  from pytext.data.xlm_constants import LANG2ID_15
  from pytext.torchscript.utils import ScriptBatchInput
  from pytext.torchscript.vocab import ScriptVocabulary
  from pytext.utils.file_io import PathManager
  from pytext.utils.lazy import lazy_property
label_desc: Use image node_id 2 for calling the XLMTensorizerScriptImpl obj's underlying member method code with example usage: obj._lookup_tokens(tokens, max_seq_len) and returns: self