code: def verify_micro_batch_idx_set(
      micro_batch_idx_set, test_data_size, micro_batch_size
  ):
      assert micro_batch_idx_set == set(
          [
              val
              for val in range(
                  0, math.ceil(test_data_size / micro_batch_size)
              )
          ]
      )
  
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 9 for calling a global function with example usage: verify_micro_batch_idx_set(micro_batch_idx_set, test_data_size, micro_batch_size) without return types