code: def test_handler(monkeypatch, mocker, file, expected_result):
      """
      Test dlrm handler as standalone entity with specified test cases
      """
      monkeypatch.syspath_prepend(EXAMPLE_ROOT_DIR)
  
      handler = ImageClassifier()
      ctx = MockContext(
          model_pt_file=REPO_ROOT_DIR.joinpath(
              MODEL_PTH_FILE
          ).as_posix(),
          model_dir=EXAMPLE_ROOT_DIR.as_posix(),
          model_file="model.py",
      )
  
      torch.manual_seed(42 * 42)
      handler.initialize(ctx)
      data = {}
      # Batch size 2
      with open(Path(CURR_FILE_PATH) / "test_data" / file, "rb") as f:
          data["data"] = f
          data = f.read()
  
      x = mocker.Mock(get=lambda x: data)
  
      x = handler.preprocess([x])
      x = handler.inference(x)
      x = handler.postprocess(x)
      labels = list(x[0].keys())
  
      assert labels == expected_result
  
file_path: serve/test/pytest/test_example_near_real_time_video.py
imports: import json
  import os
  import shutil
  from pathlib import Path
  import pytest
  import requests
  import test_utils
  import torch
  from model_archiver import ModelArchiverConfig
  from ts.torch_handler.image_classifier import ImageClassifier
  from ts.torch_handler.unit_tests.test_utils.mock_context import MockContext
label_desc: Use image node_id 4 for calling a global function with example usage: test_handler(monkeypatch, mocker, file, expected_result) without return types