code: def test_train_with_config_remote(
      fs_protocol, bucket, test_data_tabular_large, ray_cluster_2cpu
  ):
      backend = {
          "type": "local",
          "credentials": {
              "artifacts": minio_test_creds(),
          },
      }
  
      with remote_tmpdir(fs_protocol, bucket) as tmpdir:
          _run_train_with_config(
              200, test_data_tabular_large, tmpdir, backend=backend
          )
  
imports: import os
  import tempfile
  from typing import List, Set
  from unittest import mock
  import numpy
  import pandas
  import pytest
  from ludwig.api import LudwigModel
  from ludwig.constants import COLUMN, ENCODER, INPUT_FEATURES, NAME, OUTPUT_FEATURES, PREPROCESSING, SPLIT, TYPE
  from ludwig.schema.model_types.base import ModelConfig
  from ludwig.types import FeatureConfigDict, ModelConfigDict
  from ludwig.utils.misc_utils import merge_dict
  from tests.integration_tests.utils import binary_feature, category_feature, generate_data, image_feature, minio_test_creds, number_feature, private_param, remote_tmpdir, text_feature
  import dask.dataframe
  from ray.tune.experiment.trial import Trial
  from ludwig.automl import auto_train, create_auto_config, train_with_config
  from ludwig.automl.automl import OUTPUT_DIR
  from ludwig.hyperopt.execution import RayTuneExecutor
label_desc: Use image node_id 17 for calling a global function with example usage: test_train_with_config_remote(fs_protocol, bucket, test_data_tabular_large, ray_cluster_2cpu) without return types