old_contents: import os
  
  from autosklearn.data.competition_data_manager import CompetitionDataManager
  from autosklearn.data.arff_data_manager import ARFFDataManager
  
  from autosklearn.constants import *
  
  
  
  def get_data_manager(namespace, encode_labels=False):
      """Get a dataset from a argparse.Namespace.
  
      Parameters
      ----------
      namespace : argparse.Namespace
          The return value of ArgumentParser.parse_args()
  
      encode_labels : bool (default=False)
          Whether to perform 1HotEncoding for Categorical data.
  
      Returns
      -------
      DataManager
          Loaded dataset.
      """
      data_format = namespace.data_format
      data_format_ = data_format.lower()
      data_format_ = data_format_.replace('-', '').replace('_', '')
  
      if data_format_ == 'arff':
          return ARFFDataManager(namespace.dataset, namespace.task,
                                 namespace.metric, namespace.target,
                                 encode_labels=encode_labels)
      elif data_format_ == 'automlcompetitionformat':
          return CompetitionDataManager(namespace.dataset,
                                        encode_labels=encode_labels)
      else:
          raise NotImplemented('Data format %s not supported.' % data_format)
  
  
  def populate_argparse_with_data_options(parser):
      # Support different parsers for different data types
  
      parser.add_argument('--data-format', type=str, required=True,
                          choices=["automl-competition-format", "arff"])
      parser.add_argument('--dataset', type=str, required=True,
                          help='Unique identifier of the dataset.')
      parser.add_argument('--task', choices=TASK_TYPES_TO_STRING.values(),
                          help='Task to execute on the dataset. Only necessary '
                               'for data in arff format.')
      parser.add_argument('--metric', choices=list(STRING_TO_METRIC.keys()),
                          help='Loss function to optimize for. Only necessary '
                               'for data in arff format.')
      parser.add_argument('--target', type=str,
                          help='Target attribute. Only necessary for data in '
                               'arff format.')
  
      return parser
  
new_contents: import os
  
  from autosklearn.data.competition_data_manager import CompetitionDataManager
  from autosklearn.data.arff_data_manager import ARFFDataManager
  
  from autosklearn.constants import *
  
  
  
  def get_data_manager(namespace, encode_labels=False):
      """Get a dataset from a argparse.Namespace.
  
      Parameters
      ----------
      namespace : argparse.Namespace
          The return value of ArgumentParser.parse_args()
  
      encode_labels : bool (default=False)
          Whether to perform 1HotEncoding for Categorical data.
  
      Returns
      -------
      DataManager
          Loaded dataset.
      """
      data_format = namespace.data_format
      data_format_ = data_format.lower()
      data_format_ = data_format_.replace('-', '').replace('_', '')
  
      if data_format_ == 'arff':
          return ARFFDataManager(namespace.dataset, namespace.task,
                                 namespace.metric, namespace.target,
                                 encode_labels=encode_labels)
      elif data_format_ == 'automlcompetitionformat':
          return CompetitionDataManager(namespace.dataset,
                                        encode_labels=encode_labels)
      else:
          raise NotImplementedError('Data format %s not supported.' % data_format)
  
  
  def populate_argparse_with_data_options(parser):
      # Support different parsers for different data types
  
      parser.add_argument('--data-format', type=str, required=True,
                          choices=["automl-competition-format", "arff"])
      parser.add_argument('--dataset', type=str, required=True,
                          help='Unique identifier of the dataset.')
      parser.add_argument('--task', choices=TASK_TYPES_TO_STRING.values(),
                          help='Task to execute on the dataset. Only necessary '
                               'for data in arff format.')
      parser.add_argument('--metric', choices=list(STRING_TO_METRIC.keys()),
                          help='Loss function to optimize for. Only necessary '
                               'for data in arff format.')
      parser.add_argument('--target', type=str,
                          help='Target attribute. Only necessary for data in '
                               'arff format.')
  
      return parser
  
subject: FIX raising right exception