code: def test_evalai_answer_processor(self):
      evalai_answer_processor = EvalAIAnswerProcessor()
  
      # Test number
      processed = evalai_answer_processor("two")
      expected = "2"
      self.assertEqual(processed, expected)
  
      # Test article
      processed = evalai_answer_processor("a building")
      expected = "building"
      self.assertEqual(processed, expected)
  
      # Test tokenize
      processed = evalai_answer_processor("snow, mountain")
      expected = "snow mountain"
      self.assertEqual(processed, expected)
  
      # Test contractions
      processed = evalai_answer_processor("isnt")
      expected = "isn't"
      self.assertEqual(processed, expected)
  
      # Test processor
      processed = evalai_answer_processor("the two mountain's \t \n   ")
      expected = "2 mountain 's"
      self.assertEqual(processed, expected)
  
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 4 for calling the TestDatasetProcessors obj's underlying member method code with example usage: obj.test_evalai_answer_processor() without return types