Request: More unsafe fixes for custom-type-var-return-type/PYI019

[Avasam]

Description

This is a direct follow-up to #14183, which was closed by #14238 but there are still cases that I think can be autofixed. Namely, when other method params than self/cls are typed.

For example, as of Ruff 0.9.3:

This is currently autofixed

class _BaseHeterogeneousEnsemble(MetaEstimatorMixin, _BaseComposition, metaclass=ABCMeta):
    def set_params(self: _BaseHeterogeneousEnsemble_Self, **params) -> _BaseHeterogeneousEnsemble_Self: ...

But these aren't:

class _SigmoidCalibration(RegressorMixin, BaseEstimator):
    def fit(
        self: _SigmoidCalibration_Self,
        X: ArrayLike,
        y: ArrayLike,
        sample_weight: None | ArrayLike = None,
    ) -> _SigmoidCalibration_Self: ...


class _PLS(
    ClassNamePrefixFeaturesOutMixin,
    TransformerMixin,
    RegressorMixin,
    MultiOutputMixin,
    BaseEstimator,
    metaclass=ABCMeta,
):
    def fit(self: _PLS_Self, X: MatrixLike, Y: MatrixLike | ArrayLike) -> _PLS_Self: ...


class _BaseNMF(ClassNamePrefixFeaturesOutMixin, TransformerMixin, BaseEstimator, ABC):
    def fit(self: _BaseNMF_Self, X: MatrixLike | ArrayLike, y: Any = None, **params) -> _BaseNMF_Self: ...


class _BinMapper(TransformerMixin, BaseEstimator):
    def fit(self: _BinMapper_Self, X: MatrixLike, y=None) -> _BinMapper_Self: ...


class _BaseFilter(SelectorMixin, BaseEstimator):
    def fit(self: _BaseFilter_Self, X: MatrixLike, y: ArrayLike) -> _BaseFilter_Self: ...


class _BinaryGaussianProcessClassifierLaplace(BaseEstimator):
    def fit(
        self: _BinaryGaussianProcessClassifierLaplace_Self,
        X: MatrixLike | ArrayLike,
        y: ArrayLike,
    ) -> _BinaryGaussianProcessClassifierLaplace_Self: ...


class _GeneralizedLinearRegressor(RegressorMixin, BaseEstimator):
    def fit(
        self: _GeneralizedLinearRegressor_Self,
        X: MatrixLike | ArrayLike,
        y: ArrayLike,
        sample_weight: None | ArrayLike = None,
    ) -> _GeneralizedLinearRegressor_Self: ...


class _RidgeGCV(LinearModel):
    def fit(
        self: _RidgeGCV_Self,
        X: MatrixLike,
        y: MatrixLike | ArrayLike,
        sample_weight: float | None | ArrayLike = None,
    ) -> _RidgeGCV_Self: ...


class _MultiOutputEstimator(MetaEstimatorMixin, BaseEstimator, metaclass=ABCMeta):
    def partial_fit(
        self: _MultiOutputEstimator_Self,
        X: MatrixLike | ArrayLike,
        y: MatrixLike,
        classes: Sequence[ArrayLike] | None = None,
        sample_weight: None | ArrayLike = None,
    ) -> _MultiOutputEstimator_Self: ...

(examples taken from #14183 (comment) and microsoft/python-type-stubs#340)