docs: def transform_config(transformer, data, data_type='S3Prefix', content_type=None, compression_type=None,
                       split_type=None, job_name=None):
      """Export Airflow transform config from a SageMaker transformer
  
      Args:
          transformer (sagemaker.transformer.Transformer): The SageMaker transformer to export Airflow
              config from.
          data (str): Input data location in S3.
          data_type (str): What the S3 location defines (default: 'S3Prefix'). Valid values:
  
              * 'S3Prefix' - the S3 URI defines a key name prefix. All objects with this prefix will be used as
                  inputs for the transform job.
              * 'ManifestFile' - the S3 URI points to a single manifest file listing each S3 object to use as
                  an input for the transform job.
  
          content_type (str): MIME type of the input data (default: None).
          compression_type (str): Compression type of the input data, if compressed (default: None).
              Valid values: 'Gzip', None.
          split_type (str): The record delimiter for the input object (default: 'None').
              Valid values: 'None', 'Line', 'RecordIO', and 'TFRecord'.
          job_name (str): job name (default: None). If not specified, one will be generated.
  
      Returns:
          dict: Transform config that can be directly used by SageMakerTransformOperator in Airflow.
      """
      if job_name is not None:
          transformer._current_job_name = job_name
      else:
          base_name = transformer.base_transform_job_name
          transformer._current_job_name = utils.name_from_base(base_name) \
              if base_name is not None else transformer.model_name
  
      if transformer.output_path is None:
          transformer.output_path = 's3://{}/{}'.format(
              transformer.sagemaker_session.default_bucket(), transformer._current_job_name)
  
      job_config = sagemaker.transformer._TransformJob._load_config(
          data, data_type, content_type, compression_type, split_type, transformer)
  
      config = {
          'TransformJobName': transformer._current_job_name,
          'ModelName': transformer.model_name,
          'TransformInput': job_config['input_config'],
          'TransformOutput': job_config['output_config'],
          'TransformResources': job_config['resource_config'],
      }
  
      if transformer.strategy is not None:
          config['BatchStrategy'] = transformer.strategy
  
      if transformer.max_concurrent_transforms is not None:
          config['MaxConcurrentTransforms'] = transformer.max_concurrent_transforms
  
      if transformer.max_payload is not None:
          config['MaxPayloadInMB'] = transformer.max_payload
  
      if transformer.env is not None:
          config['Environment'] = transformer.env
  
      if transformer.tags is not None:
          config['Tags'] = transformer.tags
  
      return config