code: def test_tuner_api_kwargs(shutdown_only, params_expected):
      tuner_params, assertion = params_expected
  
      tuner = Tuner(lambda config: 1, **tuner_params)
  
      caught_kwargs = {}
  
      class MockExperimentAnalysis:
          trials = []
  
      def catch_kwargs(**kwargs):
          caught_kwargs.update(kwargs)
          return MockExperimentAnalysis()
  
      with patch("ray.tune.impl.tuner_internal.run", catch_kwargs):
          tuner.fit()
  
      assert assertion(caught_kwargs)
  
imports: import os
  from pathlib import Path
  from unittest.mock import patch
  import pytest
  import unittest
  from typing import Optional
  from sklearn.datasets import load_breast_cancer
  from sklearn.utils import shuffle
  import ray
  from ray import train, tune
  from ray.train import CheckpointConfig, RunConfig, ScalingConfig
  from ray.train.constants import RAY_CHDIR_TO_TRIAL_DIR
  from ray.train.examples.pytorch.torch_linear_example import train_func
  from ray.data import Dataset, Datasource, ReadTask, from_pandas, read_datasource
  from ray.data.block import BlockMetadata
  from ray.train.data_parallel_trainer import DataParallelTrainer
  from ray.train.torch import TorchTrainer
  from ray.train.trainer import BaseTrainer
  from ray.train.xgboost import XGBoostTrainer
  from ray.tune import Callback, CLIReporter
  from ray.tune.tune_config import TuneConfig
  from ray.tune.tuner import Tuner
label_desc: Use image node_id 5 for calling a global function with example usage: test_tuner_api_kwargs(shutdown_only, params_expected) and returns: MockExperimentAnalysis