(self)
Implements DatasetConverter.create_dataset_specification_and_records.

    If no split file is provided, and the default location for Quickdraw splits
    does not contain a split file, splits are randomly created in this
    function using 70%, 15%, and 15% of the data for training, validation and
    testing, respectively, and then stored in that default location.

    The splits for this dataset are represented as a dictionary mapping each of
    'train', 'valid', and 'test' to a list of class names. For example the value
    associated with the key 'train' may be ['angel', 'clock', ...].
Implements DatasetConverter.create_dataset_specification_and_records.
Implements DatasetConverter . create_dataset_specification_and_records .
def create_dataset_specification_and_records(self):
    """Implements DatasetConverter.create_dataset_specification_and_records.

    If no split file is provided, and the default location for Quickdraw splits
    does not contain a split file, splits are randomly created in this
    function using 70%, 15%, and 15% of the data for training, validation and
    testing, respectively, and then stored in that default location.

    The splits for this dataset are represented as a dictionary mapping each of
    'train', 'valid', and 'test' to a list of class names. For example the value
    associated with the key 'train' may be ['angel', 'clock', ...].
    """

    splits = self.get_splits()
    # Get the names of the classes assigned to each split.
    train_classes = splits['train']
    valid_classes = splits['valid']
    test_classes = splits['test']

    self.parse_split_data(learning_spec.Split.TRAIN, train_classes)
    self.parse_split_data(learning_spec.Split.VALID, valid_classes)
    self.parse_split_data(learning_spec.Split.TEST, test_classes)
def create_dataset_specification_and_records ( self ) : splits = self . get_splits ( ) # Get the names of the classes assigned to each split. train_classes = splits [ 'train' ] valid_classes = splits [ 'valid' ] test_classes = splits [ 'test' ] self . parse_split_data ( learning_spec . Split . TRAIN , train_classes ) self . parse_split_data ( learning_spec . Split . VALID , valid_classes ) self . parse_split_data ( learning_spec . Split . TEST , test_classes )