aac_metrics.classes.bleu module

class BLEU(return_all_scores: bool = True, *, n: int = 4, option: ~typing.Literal['shortest', 'average', 'closest'] = 'closest', verbose: int = 0, tokenizer: ~typing.Callable[[str], list[str]] = <method 'split' of 'str' objects>)

Bases: AACMetric[tuple[dict[str, Tensor], dict[str, Tensor]] | Tensor]

BiLingual Evaluation Understudy metric class.

• Paper: https://www.aclweb.org/anthology/P02-1040.pdf

For more information, see bleu().

compute() → tuple[dict[str, Tensor], dict[str, Tensor]] | 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

class BLEU1(return_all_scores: bool = True, option: ~typing.Literal['shortest', 'average', 'closest'] = 'closest', verbose: int = 0, tokenizer: ~typing.Callable[[str], list[str]] = <method 'split' of 'str' objects>)

Bases: BLEU

class BLEU2(return_all_scores: bool = True, option: ~typing.Literal['shortest', 'average', 'closest'] = 'closest', verbose: int = 0, tokenizer: ~typing.Callable[[str], list[str]] = <method 'split' of 'str' objects>)

Bases: BLEU

class BLEU3(return_all_scores: bool = True, option: ~typing.Literal['shortest', 'average', 'closest'] = 'closest', verbose: int = 0, tokenizer: ~typing.Callable[[str], list[str]] = <method 'split' of 'str' objects>)

Bases: BLEU

class BLEU4(return_all_scores: bool = True, option: ~typing.Literal['shortest', 'average', 'closest'] = 'closest', verbose: int = 0, tokenizer: ~typing.Callable[[str], list[str]] = <method 'split' of 'str' objects>)

Bases: BLEU