code: def __call__(self, item: Dict[str, Any]):
      output = get_pair_text_tokens(item, self)
      output["text"] = output["tokens_masked"]
      output["tokens"] = output["tokens_masked"]
      if "is_correct" in item:
          output["is_correct"] = torch.tensor(
              item.get("is_correct", True), dtype=torch.long
          )
      return output
  
imports: import copy
  import random
  from typing import Any, Dict, List, Optional, Tuple, Union
  import torch
  from mmf.common.registry import registry
  from mmf.common.sample import Sample, SampleList
  from mmf.datasets.processors.processors import BaseProcessor
label_desc: Use image node_id 2 for calling the UNITERTextTokenizer obj's underlying member method code with example usage: obj.__call__(item) and returns: output