code: def __call__(self, item: Dict[str, Any]) -> Dict[str, torch.Tensor]:
      output = get_pair_text_tokens(item, self)
      output["text"] = output["tokens_masked"]
      output["tokens"] = output["tokens_masked"]
  
      if self._corrupt_prob > 0:
          (
              contrastive_label,
              corrupt_output,
          ) = self._get_contrastive_output(item)
          output["input_ids_corrupt"] = corrupt_output["input_ids"]
          output["segment_ids_corrupt"] = corrupt_output["segment_ids"]
          output["input_mask_corrupt"] = corrupt_output["input_mask"]
          output["contrastive_label"] = contrastive_label
      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 VinVLTextTokenizer obj's underlying member method code with example usage: obj.__call__(item) and returns: output