code: def test_handle(context, mixed_batch, handler):
      test_data, labels = mixed_batch
      results = handler.handle(test_data, context)
      assert len(results) == len(labels)
      for l, r in zip(labels, results):
          assert l in r
  
      verify_micro_batch_idx_set(
          handler.micro_batch_idx_set,
          len(test_data),
          handler.handle.micro_batch_size,
      )
      handler.micro_batch_idx_set.clear()
  
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 10 for calling a global function with example usage: test_handle(context, mixed_batch, handler) without return types