code: def __init__(
      self, tokenizer: Tokenizer, vocab: Vocabulary, max_seq_len: int
  ):
      super().__init__()
      self.tokenizer = tokenizer
      self.vocab = ScriptVocabulary(
          list(vocab),
          pad_idx=vocab.get_pad_index(),
          bos_idx=vocab.get_bos_index(-1),
          eos_idx=vocab.get_eos_index(-1),
          unk_idx=vocab.get_unk_index(),
      )
      self.vocab_lookup = VocabLookup(self.vocab)
      self.max_seq_len = max_seq_len
  
imports: from typing import Any, Dict, List, Optional, Tuple
  import torch
  from fairseq.data.dictionary import Dictionary
  from fairseq.data.legacy.masked_lm_dictionary import BertDictionary
  from pytext import resources
  from pytext.common.constants import Token
  from pytext.config.component import ComponentType, create_component
  from pytext.data.tensorizers import Tensorizer, TensorizerScriptImpl
  from pytext.data.tokenizers import Tokenizer, WordPieceTokenizer
  from pytext.data.utils import BOS, EOS, MASK, PAD, UNK, Vocabulary
  from pytext.torchscript.tensorizer.tensorizer import VocabLookup
  from pytext.torchscript.utils import pad_2d_mask, ScriptBatchInput
  from pytext.torchscript.vocab import ScriptVocabulary
  from pytext.utils.file_io import PathManager
  from pytext.utils.lazy import lazy_property
  from pytorch.text.fb.utils.transform_utils import pad_2d
label_desc: Use image node_id 1 to create a new BERTTensorizerBaseScriptImpl object from inherited base classes: TensorizerScriptImpl with example: obj = BERTTensorizerBaseScriptImpl(tokenizer, vocab, max_seq_len)