Class Augmenter

textattack/augmentation/augmenter.py:15–251

A class for performing data augmentation using TextAttack. Returns all possible transformations for a given string. Currently only supports transformations which are word swaps. Args: transformation (textattack.Transformation): the transformation that suggests n

class Augmenter:
    """A class for performing data augmentation using TextAttack.

    Returns all possible transformations for a given string. Currently only
        supports transformations which are word swaps.

    Args:
        transformation (textattack.Transformation): the transformation
            that suggests new texts from an input.
        constraints: (list(textattack.Constraint)): constraints
            that each transformation must meet
        pct_words_to_swap: (float): [0., 1.], percentage of words to swap per augmented example
        transformations_per_example: (int): Maximum number of augmentations
            per input
        high_yield: Whether to return a set of augmented texts that will be relatively similar, or to return only a
            single one.
        fast_augment: Stops additional transformation runs when number of successful augmentations reaches
            transformations_per_example
        advanced_metrics: return perplexity and USE Score of augmentation

    Example::
        >>> from textattack.transformations import WordSwapRandomCharacterDeletion, WordSwapQWERTY, CompositeTransformation
        >>> from textattack.constraints.pre_transformation import RepeatModification, StopwordModification
        >>> from textattack.augmentation import Augmenter

        >>> transformation = CompositeTransformation([WordSwapRandomCharacterDeletion(), WordSwapQWERTY()])
        >>> constraints = [RepeatModification(), StopwordModification()]

        >>> # initiate augmenter
        >>> augmenter = Augmenter(
        ...     transformation=transformation,
        ...     constraints=constraints,
        ...     pct_words_to_swap=0.5,
        ...     transformations_per_example=3
        ... )

        >>> # additional parameters can be modified if not during initiation
        >>> augmenter.enable_advanced_metrics = True
        >>> augmenter.fast_augment = True
        >>> augmenter.high_yield = True

        >>> s = 'What I cannot create, I do not understand.'
        >>> results = augmenter.augment(s)

        >>> augmentations = results[0]
        >>> perplexity_score = results[1]
        >>> use_score = results[2]
    """

    def __init__(
        self,
        transformation,
        constraints=[],
        pct_words_to_swap=0.1,
        transformations_per_example=1,
        high_yield=False,
        fast_augment=False,
        enable_advanced_metrics=False,