def create_combined_augmenter(
    lower_level: float,
    orth_level: float,
    orth_variants: Optional[Dict[str, List[Dict]]],
    whitespace_level: float,
    whitespace_per_token: float,
    whitespace_variants: Optional[List[str]],
) -> Callable[["Language", Example], Iterator[Example]]:
    """Create a data augmentation callback that uses orth-variant replacement.
    The callback can be added to a corpus or other data iterator during training.

    lower_level (float): The percentage of texts that will be lowercased.
    orth_level (float): The percentage of texts that will be augmented.
    orth_variants (Optional[Dict[str, List[Dict]]]): A dictionary containing the
        single and paired orth variants. Typically loaded from a JSON file.
    whitespace_level (float): The percentage of texts that will have whitespace
        tokens inserted.
    whitespace_per_token (float): The number of whitespace tokens to insert in
        the modified doc as a percentage of the doc length.
    whitespace_variants (Optional[List[str]]): The whitespace token texts.
    RETURNS (Callable[[Language, Example], Iterator[Example]]): The augmenter.
    """
    return partial(
        combined_augmenter,
        lower_level=lower_level,
        orth_level=orth_level,
        orth_variants=orth_variants,
        whitespace_level=whitespace_level,
        whitespace_per_token=whitespace_per_token,
        whitespace_variants=whitespace_variants,
    )
Create a data augmentation callback that uses orth-variant replacement.
    The callback can be added to a corpus or other data iterator during training.

    lower_level (float): The percentage of texts that will be lowercased.
    orth_level (float): The percentage of texts that will be augmented.
    orth_variants (Optional[Dict[str, List[Dict]]]): A dictionary containing the
        single and paired orth variants. Typically loaded from a JSON file.
    whitespace_level (float): The percentage of texts that will have whitespace
        tokens inserted.
    whitespace_per_token (float): The number of whitespace tokens to insert in
        the modified doc as a percentage of the doc length.
    whitespace_variants (Optional[List[str]]): The whitespace token texts.
    RETURNS (Callable[[Language, Example], Iterator[Example]]): The augmenter.
    
spacy/training/augment.py