code: def test_run_config_in_param_space():
      trainer = DataParallelTrainer(
          lambda config: None,
          backend_config=TestConfig(),
          scaling_config=ScalingConfig(num_workers=1),
      )
      with pytest.raises(ValueError):
          Tuner(
              trainer,
              param_space={"run_config": RunConfig(name="ignored")},
          )
  
imports: import logging
  import pytest
  import ray
  from ray import train, tune
  from ray.air.constants import TRAINING_ITERATION
  from ray.train import FailureConfig, RunConfig, ScalingConfig
  from ray.train._internal.worker_group import WorkerGroup
  from ray.train.backend import Backend, BackendConfig
  from ray.train.data_parallel_trainer import DataParallelTrainer
  from ray.train.examples.pytorch.torch_fashion_mnist_example import train_func_per_worker
  from ray.train.examples.tf.tensorflow_mnist_example import train_func
  from ray.train.tensorflow.tensorflow_trainer import TensorflowTrainer
  from ray.train.tests.util import create_dict_checkpoint, load_dict_checkpoint
  from ray.train.torch.torch_trainer import TorchTrainer
  from ray.tune.tune_config import TuneConfig
  from ray.tune.tuner import Tuner
label_desc: Use image node_id 13 for calling a global function with example usage: test_run_config_in_param_space() without return types