code: def __init__(
      self,
      tokenizer: Tokenizer,
      vocab: Vocabulary,
      max_seq_len: int,
      language_vocab: List[str],
      default_language: str,
  ):
      super().__init__(tokenizer, vocab, max_seq_len)
      self.language_vocab = ScriptVocabulary(language_vocab)
      self.default_language = torch.jit.Attribute(default_language, str)
  
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 1 to create a new XLMTensorizerScriptImpl object from inherited base classes: BERTTensorizerBaseScriptImpl with example: obj = XLMTensorizerScriptImpl(tokenizer, vocab, max_seq_len, language_vocab, default_language)