code: def test_serving_wheeled_model(sklearn_knn_model):
      model_name = f"wheels-test-{random_int()}"
      model_uri = f"models:/{model_name}/1"
      wheeled_model_uri = f"models:/{model_name}/2"
      artifact_path = "model"
      (model, inference_data) = sklearn_knn_model
  
      # Log a model
      with mlflow.start_run():
          mlflow.sklearn.log_model(
              sk_model=model,
              artifact_path=artifact_path,
              registered_model_name=model_name,
          )
  
      # Re-log with wheels
      with mlflow.start_run():
          WheeledModel.log_model(model_uri=model_uri)
  
      data = json.dumps(
          {
              "dataframe_split": pd.DataFrame(inference_data).to_dict(
                  orient="split"
              )
          }
      )
      resp = pyfunc_serve_and_score_model(
          wheeled_model_uri,
          data=data,
          content_type=pyfunc_scoring_server.CONTENT_TYPE_JSON,
          extra_args=EXTRA_PYFUNC_SERVING_TEST_ARGS,
      )
      scores = pd.read_json(
          resp.content.decode("utf-8"), orient="records"
      ).values.squeeze()
      np.testing.assert_array_almost_equal(
          scores, model.predict(inference_data)
      )
  
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 15 for calling a global function with example usage: test_serving_wheeled_model(sklearn_knn_model) without return types