code: def test_invalid_data_config():
      # facets included in input dataset
      with pytest.raises(ValueError, match=r"^Invalid dataset_type"):
          DataConfig(
              s3_data_input_path="s3://bucket/inputpath",
              s3_output_path="s3://bucket/outputpath",
              dataset_type="whatnot_type",
          )
      # facets NOT included in input dataset
      error_msg = r"^The parameter 'predicted_label' is not supported for dataset_type"
      with pytest.raises(ValueError, match=error_msg):
          DataConfig(
              s3_data_input_path="s3://bucket/inputpath",
              s3_output_path="s3://bucket/outputpath",
              dataset_type="application/x-image",
              predicted_label="label",
          )
      error_msg = r"^The parameter 'excluded_columns' is not supported for dataset_type"
      with pytest.raises(ValueError, match=error_msg):
          DataConfig(
              s3_data_input_path="s3://bucket/inputpath",
              s3_output_path="s3://bucket/outputpath",
              dataset_type="application/x-image",
              excluded_columns="excluded",
          )
      error_msg = r"^The parameters 'facet_dataset_uri' and 'facet_headers' are not supported for dataset_type"  # noqa E501  # pylint: disable=c0301
      with pytest.raises(ValueError, match=error_msg):
          DataConfig(
              s3_data_input_path="s3://bucket/inputpath",
              s3_output_path="s3://bucket/outputpath",
              dataset_type="application/x-image",
              facet_dataset_uri="facet_dataset/URI",
              facet_headers="facet",
          )
      error_msg = r"^The parameters 'predicted_label_dataset_uri' and 'predicted_label_headers' are not supported for dataset_type"  # noqa E501  # pylint: disable=c0301
      with pytest.raises(ValueError, match=error_msg):
          DataConfig(
              s3_data_input_path="s3://bucket/inputpath",
              s3_output_path="s3://bucket/outputpath",
              dataset_type="application/jsonlines",
              predicted_label_dataset_uri="pred_dataset/URI",
              predicted_label_headers="prediction",
          )
  
imports: from __future__ import absolute_import, print_function
  import copy
  import pytest
  from mock import MagicMock, Mock, patch
  from sagemaker import Processor, image_uris
  from sagemaker.clarify import BiasConfig, DataConfig, ModelConfig, ModelPredictedLabelConfig, PDPConfig, SageMakerClarifyProcessor, SHAPConfig, TextConfig, ImageConfig, _AnalysisConfigGenerator, DatasetType, ProcessingOutputHandler, SegmentationConfig
label_desc: Use image node_id 4 for calling a global function with example usage: test_invalid_data_config() without return types