code: def test_wheel_download_works(tmp_path):
      simple_dependency = "cloudpickle"
      requirements_file = os.path.join(tmp_path, "req.txt")
      wheel_dir = os.path.join(tmp_path, "wheels")
      with open(requirements_file, "w") as req_file:
          req_file.write(simple_dependency)
  
      WheeledModel._download_wheels(requirements_file, wheel_dir)
      wheels = os.listdir(wheel_dir)
      assert len(wheels) == 1  # Only a single wheel is downloaded
      assert wheels[0].endswith(".whl")  # Type is wheel
      assert simple_dependency in wheels[0]
  
imports: import json
  import os
  import random
  import re
  from collections import namedtuple
  import numpy
  import pandas
  import pytest
  import sklearn.neighbors
  import yaml
  from sklearn import datasets
  import mlflow
  import mlflow.pyfunc.scoring_server
  from mlflow.exceptions import MlflowException
  from mlflow.models.wheeled_model import _WHEELS_FOLDER_NAME, WheeledModel
  from mlflow.pyfunc.model import MLMODEL_FILE_NAME, Model
  from mlflow.store.artifact.utils.models import _improper_model_uri_msg
  from mlflow.tracking.artifact_utils import _download_artifact_from_uri
  from mlflow.utils.environment import _CONDA_ENV_FILE_NAME, _REQUIREMENTS_FILE_NAME, _is_pip_deps, _mlflow_conda_env
  from tests.helper_functions import _is_available_on_pypi, _mlflow_major_version_string, pyfunc_serve_and_score_model
label_desc: Use image node_id 16 for calling a global function with example usage: test_wheel_download_works(tmp_path) without return types