code: def preprocess(self, data):
      self.micro_batch_idx_set.add(self.handle.get_micro_batch_idx())
      return super().preprocess(data)
  
imports: import json
  import math
  import random
  import sys
  from pathlib import Path
  import pytest
  from torchvision.models.resnet import ResNet18_Weights
  from ts.handler_utils.micro_batching import MicroBatching
  from ts.torch_handler.image_classifier import ImageClassifier
  from ts.torch_handler.unit_tests.test_utils.mock_context import MockContext
  from ts.torch_handler.unit_tests.test_utils.model_dir import copy_files, download_model
label_desc: Use image node_id 2 for calling the MicroBatchingTestHandler obj's underlying member method code with example usage: obj.preprocess(data) and returns: super