class_docstr: Checks that pre-trained Transresnet Multimodal model gives the correct results.
docstr: Test pretrained model.
docstr_tok: ["Test","pretrained","model","."]
code: def test_transresnet(self):
      """
      Test pretrained model.
      """
      _, test = testing_utils.eval_model(MODEL_OPTIONS, skip_valid=True)
  
      # Overall
      self.assertAlmostEqual(test["accuracy"], 0.3667, places=4)
      self.assertAlmostEqual(test["hits@5"], 0.6333, places=4)
      self.assertAlmostEqual(test["hits@10"], 0.7667, places=4)
  
      # First round
      self.assertAlmostEqual(
          test["first_round/hits@1/100"], 0.2, places=4
      )
  
      # Second round
      self.assertAlmostEqual(
          test["second_round/hits@1/100"], 0.5, places=4
      )
  
      # Third round
      self.assertAlmostEqual(
          test["third_round+/hits@1/100"], 0.4, places=4
      )
  
imports: import unittest
  import parlai.scripts.display_data
  import parlai.utils.testing
label_desc: Use image node_id 2 for calling the TestTransresnet obj's underlying member method code with example usage: obj.test_transresnet() without return types