code: def test_run_name(
      tmpdir: py.path.local, run_name: Optional[str], expected: str
  ) -> None:
      tracking_uri = f"file:{tmpdir}"
  
      mlflow_kwargs = {"run_name": run_name}
      mlflc = MLflowCallback(
          tracking_uri=tracking_uri, mlflow_kwargs=mlflow_kwargs
      )
      study = optuna.create_study()
      study.optimize(_objective_func, n_trials=1, callbacks=[mlflc])
  
      mlfl_client = MlflowClient(tracking_uri)
      experiment = mlfl_client.search_experiments()[0]
      run = mlfl_client.search_runs(experiment.experiment_id)[0]
      tags = run.data.tags
      assert tags["mlflow.runName"] == expected
  
imports: from typing import Callable
  from typing import List
  from typing import Optional
  from typing import Tuple
  from typing import Union
  import numpy
  import py
  import pytest
  import optuna
  from optuna._imports import try_import
  from optuna.integration.mlflow import MLflowCallback
label_desc: Use image node_id 9 for calling a global function with example usage: test_run_name(tmpdir, run_name, expected) without return types