(name, split_name, dataset_dir, file_pattern=None, reader=None)
return datasets_map[name].get_split(
      split_name,
      dataset_dir,
      file_pattern,
      reader)
Given a dataset name and a split_name returns a Dataset.

  Args:
    name: String, the name of the dataset.
    split_name: A train/test split name.
    dataset_dir: The directory where the dataset files are stored.
    file_pattern: The file pattern to use for matching the dataset source files.
    reader: The subclass of tf.ReaderBase. If left as `None`, then the default
      reader defined by each dataset is used.

  Returns:
    A `Dataset` class.

  Raises:
    ValueError: If the dataset `name` is unknown.
Given a dataset name and a split_name returns a Dataset.
Given a dataset name and a split_name returns a Dataset .
def get_dataset(name, split_name, dataset_dir, file_pattern=None, reader=None):
  """Given a dataset name and a split_name returns a Dataset.

  Args:
    name: String, the name of the dataset.
    split_name: A train/test split name.
    dataset_dir: The directory where the dataset files are stored.
    file_pattern: The file pattern to use for matching the dataset source files.
    reader: The subclass of tf.ReaderBase. If left as `None`, then the default
      reader defined by each dataset is used.

  Returns:
    A `Dataset` class.

  Raises:
    ValueError: If the dataset `name` is unknown.
  """
  if name not in datasets_map:
    raise ValueError('Name of dataset unknown %s' % name)
  return datasets_map[name].get_split(
      split_name,
      dataset_dir,
      file_pattern,
      reader)
def get_dataset ( name , split_name , dataset_dir , file_pattern = None , reader = None ) : if name not in datasets_map : raise ValueError ( 'Name of dataset unknown %s' % name ) return datasets_map [ name ] . get_split ( split_name , dataset_dir , file_pattern , reader )