code: def test_log_mlflow_tags(tmpdir: py.path.local) -> None:
      tracking_uri = f"file:{tmpdir}"
      expected_tags = {"foo": 0, "bar": 1}
      mlflow_kwargs = {"tags": expected_tags}
  
      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 all([k in tags.keys() for k in expected_tags.keys()])
      assert all(
          [
              tags[key] == str(value)
              for key, value in expected_tags.items()
          ]
      )
  
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 17 for calling a global function with example usage: test_log_mlflow_tags(tmpdir) without return types