code: def get_tokens_by_index(
      self, tokens: Optional[List[List[List[str]]]], index: int
  ) -> Optional[List[str]]:
      if tokens is None or len(tokens) == 0:
          return None
  
      # TokenTensorizer only works with a single text per row, stick with that
      return tokens[index][0]
  
imports: from typing import List, Optional, Tuple
  import torch
  from pytext.config.component import ComponentType, create_component
  from pytext.data.tensorizers import TensorizerScriptImpl
  from pytext.data.tokenizers import Tokenizer
  from pytext.torchscript.tensorizer.tensorizer import VocabLookup
  from pytext.torchscript.tokenizer import ScriptDoNothingTokenizer
  from pytext.torchscript.utils import ScriptBatchInput
  from pytext.torchscript.vocab import ScriptVocabulary
  from pytext.utils import cuda
  from pytext.utils.file_io import PathManager
  from pytext.utils.lazy import lazy_property
  from pytorch.text.fb.utils.transform_utils import pad_2d
  from .tensorizers import Tensorizer, tokenize, VocabConfig
  from .utils import VocabBuilder, Vocabulary
label_desc: Use image node_id 3 for calling the TokenTensorizerScriptImpl obj's underlying member method code with example usage: obj.get_tokens_by_index(tokens, index) and returns: tokens, None