code: def test_caption_processor(self):
      config = self._get_config(
          "../../../mmf/configs/datasets/coco/defaults.yaml"
      )
      captioning_config = config.dataset_config.coco
      caption_processor_config = (
          captioning_config.processors.caption_processor
      )
  
      vocab_path = os.path.join(
          os.path.abspath(__file__), "..", "..", "data", "vocab.txt"
      )
      caption_processor_config.params.vocab.type = "random"
      caption_processor_config.params.vocab.vocab_file = (
          os.path.abspath(vocab_path)
      )
      caption_processor = CaptionProcessor(
          caption_processor_config.params
      )
  
      tokens = [1, 4, 5, 6, 4, 7, 8, 2, 0, 0, 0]
      caption = caption_processor(tokens)
  
      # Test start, stop, pad are removed
      self.assertNotIn("<s>", caption["tokens"])
      self.assertNotIn("</s>", caption["tokens"])
      self.assertNotIn("<pad>", caption["tokens"])
  
      # Test caption is correct
      self.assertEqual(caption["caption"], "a man with a red helmet")
  
imports: import os
  import tempfile
  import unittest
  import torch
  from mmf.datasets.processors.image_processors import VILTImageProcessor
  from mmf.datasets.processors.processors import CaptionProcessor, EvalAIAnswerProcessor, MultiClassFromFile, MultiHotAnswerFromVocabProcessor, Processor, TransformerBboxProcessor
  from mmf.datasets.processors.video_processors import VideoTransforms
  from mmf.utils.configuration import load_yaml
  from omegaconf import OmegaConf
  from tests.test_utils import compare_tensors, skip_if_no_pytorchvideo
label_desc: Use image node_id 2 for calling the TestDatasetProcessors obj's underlying member method code with example usage: obj.test_caption_processor() without return types