code: def handler(context, request):
      handler = MicroBatchingTestHandler(micro_batch_size=request.param)
      handler.initialize(context)
      handler.handle.parallelism = context.model_yaml_config[
          "mb_parallelism"
      ]
  
      yield handler
  
      handler.handle.shutdown()
  
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 7 for calling a global function with example usage: handler(context, request) without return types