aac_metrics.classes.rouge_l module

class ROUGEL(return_all_scores: bool = True, *, beta: float = 1.2, tokenizer: ~typing.Callable[[str], list[str]] = <method 'split' of 'str' objects>)

Bases: AACMetric[tuple[ROUGELScores, ROUGELScores] | Tensor]

Recall-Oriented Understudy for Gisting Evaluation class.

• Paper: https://aclanthology.org/W04-1013.pdf

For more information, see rouge_l().

compute() → tuple[ROUGELScores, ROUGELScores] | Tensor

extra_repr() → str

Return the extra representation of the module.

To print customized extra information, you should re-implement this method in your own modules. Both single-line and multi-line strings are acceptable.

full_state_update: ClassVar[bool | None] = False

get_output_names() → tuple[str, ...]

higher_is_better: ClassVar[bool | None] = True

is_differentiable: ClassVar[bool | None] = False

max_value: ClassVar[float] = 1.0

min_value: ClassVar[float] = 0.0

reset() → None

training: bool

update(

candidates: list[str],

mult_references: list[list[str]],

) → None