code: def test_multi_data_preprocessor(self):
      processor = MultiBranchDataPreprocessor(self.data_preprocessor)
      # test processing multi_data when training
      multi_data = processor(self.multi_data, training=True)
      self.assertEqual(
          multi_data["inputs"]["sup"].shape, (1, 3, 224, 224)
      )
      self.assertEqual(
          multi_data["inputs"]["unsup_teacher"].shape, (2, 3, 608, 608)
      )
      self.assertEqual(
          multi_data["inputs"]["unsup_student"].shape, (2, 3, 704, 704)
      )
      self.assertEqual(len(multi_data["data_samples"]["sup"]), 1)
      self.assertEqual(
          len(multi_data["data_samples"]["unsup_teacher"]), 2
      )
      self.assertEqual(
          len(multi_data["data_samples"]["unsup_student"]), 2
      )
      # test processing data when testing
      data = processor(self.data)
      self.assertEqual(data["inputs"].shape, (1, 3, 224, 224))
      self.assertEqual(len(data["data_samples"]), 1)
  
file_path: mmdetection/tests/test_models/test_data_preprocessors/test_data_preprocessor.py
imports: from unittest import TestCase
  import torch
  from mmengine.logging import MessageHub
  from mmdet.models.data_preprocessors import BatchFixedSizePad, BatchSyncRandomResize, DetDataPreprocessor, MultiBranchDataPreprocessor
  from mmdet.structures import DetDataSample
  from mmdet.testing import demo_mm_inputs
label_desc: Use image node_id 2 for calling the TestMultiBranchDataPreprocessor obj's underlying member method code with example usage: obj.test_multi_data_preprocessor() without return types