code: def data_config():
      return DataConfig(
          s3_data_input_path=_S3_INPUT_PATH,
          s3_output_path=_S3_OUTPUT_PATH,
          label="fraud",
          dataset_type="text/csv",
      )
  
imports: from __future__ import absolute_import
  import json
  import re
  import pytest
  from sagemaker.clarify import DataConfig, BiasConfig, ModelConfig, ModelPredictedLabelConfig, SHAPConfig
  from sagemaker.workflow.clarify_check_step import DataBiasCheckConfig, ClarifyCheckStep, ModelBiasCheckConfig, ModelExplainabilityCheckConfig, ClarifyCheckConfig, _EXPLAINABILITY_MONITORING_CFG_BASE_NAME, _BIAS_MONITORING_CFG_BASE_NAME
  from sagemaker.model_monitor.model_monitoring import _MODEL_MONITOR_S3_PATH
  from sagemaker.workflow.parameters import ParameterString
  from sagemaker.workflow.pipeline import Pipeline
  from sagemaker.workflow.pipeline import PipelineDefinitionConfig
  from sagemaker.workflow.steps import CacheConfig
  from sagemaker.workflow.check_job_config import CheckJobConfig
label_desc: Use image node_id 3 for calling a global function with example usage: data_config() and returns: DataConfig