(split_name, dataset_dir, image_preprocessing_fn, dataset_name, file_pattern=None, reader=None, **kwargs)
return dataset_common.get_split(split_name, dataset_dir,
                                      file_pattern, reader,
                                      image_preprocessing_fn,
                                      dataset_name,
                                      SPLITS_TO_SIZES,
                                      ITEMS_TO_DESCRIPTIONS,
                                      NUM_CLASSES,
                                      **kwargs)
Gets a dataset tuple with instructions for reading ImageNet.

    Args:
      split_name: A train/test split name.
      dataset_dir: The base directory of the dataset sources.
      file_pattern: The file pattern to use when matching the dataset sources.
        It is assumed that the pattern contains a '%s' string so that the split
        name can be inserted.
      reader: The TensorFlow reader type.

    Returns:
      A `Dataset` namedtuple.

    Raises:
        ValueError: if `split_name` is not a valid train/test split.
Gets a dataset tuple with instructions for reading ImageNet.
Gets a dataset tuple with instructions for reading ImageNet .
def get_split(split_name, dataset_dir, image_preprocessing_fn, dataset_name, file_pattern=None, reader=None, **kwargs):
    """Gets a dataset tuple with instructions for reading ImageNet.

    Args:
      split_name: A train/test split name.
      dataset_dir: The base directory of the dataset sources.
      file_pattern: The file pattern to use when matching the dataset sources.
        It is assumed that the pattern contains a '%s' string so that the split
        name can be inserted.
      reader: The TensorFlow reader type.

    Returns:
      A `Dataset` namedtuple.

    Raises:
        ValueError: if `split_name` is not a valid train/test split.
    """
    if not file_pattern:
        file_pattern = FILE_PATTERN
    return dataset_common.get_split(split_name, dataset_dir,
                                      file_pattern, reader,
                                      image_preprocessing_fn,
                                      dataset_name,
                                      SPLITS_TO_SIZES,
                                      ITEMS_TO_DESCRIPTIONS,
                                      NUM_CLASSES,
                                      **kwargs)
def get_split ( split_name , dataset_dir , image_preprocessing_fn , dataset_name , file_pattern = None , reader = None , * * kwargs ) : if not file_pattern : file_pattern = FILE_PATTERN return dataset_common . get_split ( split_name , dataset_dir , file_pattern , reader , image_preprocessing_fn , dataset_name , SPLITS_TO_SIZES , ITEMS_TO_DESCRIPTIONS , NUM_CLASSES , * * kwargs )