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authorS. Solomon Darnell2025-03-28 21:52:21 -0500
committerS. Solomon Darnell2025-03-28 21:52:21 -0500
commit4a52a71956a8d46fcb7294ac71734504bb09bcc2 (patch)
treeee3dc5af3b6313e921cd920906356f5d4febc4ed /.venv/lib/python3.12/site-packages/numpy/_typing/_ufunc.pyi
parentcc961e04ba734dd72309fb548a2f97d67d578813 (diff)
downloadgn-ai-master.tar.gz
two version of R2R are hereHEADmaster
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+"""A module with private type-check-only `numpy.ufunc` subclasses.
+
+The signatures of the ufuncs are too varied to reasonably type
+with a single class. So instead, `ufunc` has been expanded into
+four private subclasses, one for each combination of
+`~ufunc.nin` and `~ufunc.nout`.
+
+"""
+
+from typing import (
+ Any,
+ Generic,
+ overload,
+ TypeVar,
+ Literal,
+ SupportsIndex,
+ Protocol,
+)
+
+from numpy import ufunc, _CastingKind, _OrderKACF
+from numpy.typing import NDArray
+
+from ._shape import _ShapeLike
+from ._scalars import _ScalarLike_co
+from ._array_like import ArrayLike, _ArrayLikeBool_co, _ArrayLikeInt_co
+from ._dtype_like import DTypeLike
+
+_T = TypeVar("_T")
+_2Tuple = tuple[_T, _T]
+_3Tuple = tuple[_T, _T, _T]
+_4Tuple = tuple[_T, _T, _T, _T]
+
+_NTypes = TypeVar("_NTypes", bound=int)
+_IDType = TypeVar("_IDType", bound=Any)
+_NameType = TypeVar("_NameType", bound=str)
+
+
+class _SupportsArrayUFunc(Protocol):
+ def __array_ufunc__(
+ self,
+ ufunc: ufunc,
+ method: Literal["__call__", "reduce", "reduceat", "accumulate", "outer", "inner"],
+ *inputs: Any,
+ **kwargs: Any,
+ ) -> Any: ...
+
+
+# NOTE: In reality `extobj` should be a length of list 3 containing an
+# int, an int, and a callable, but there's no way to properly express
+# non-homogenous lists.
+# Use `Any` over `Union` to avoid issues related to lists invariance.
+
+# NOTE: `reduce`, `accumulate`, `reduceat` and `outer` raise a ValueError for
+# ufuncs that don't accept two input arguments and return one output argument.
+# In such cases the respective methods are simply typed as `None`.
+
+# NOTE: Similarly, `at` won't be defined for ufuncs that return
+# multiple outputs; in such cases `at` is typed as `None`
+
+# NOTE: If 2 output types are returned then `out` must be a
+# 2-tuple of arrays. Otherwise `None` or a plain array are also acceptable
+
+class _UFunc_Nin1_Nout1(ufunc, Generic[_NameType, _NTypes, _IDType]): # type: ignore[misc]
+ @property
+ def __name__(self) -> _NameType: ...
+ @property
+ def ntypes(self) -> _NTypes: ...
+ @property
+ def identity(self) -> _IDType: ...
+ @property
+ def nin(self) -> Literal[1]: ...
+ @property
+ def nout(self) -> Literal[1]: ...
+ @property
+ def nargs(self) -> Literal[2]: ...
+ @property
+ def signature(self) -> None: ...
+ @property
+ def reduce(self) -> None: ...
+ @property
+ def accumulate(self) -> None: ...
+ @property
+ def reduceat(self) -> None: ...
+ @property
+ def outer(self) -> None: ...
+
+ @overload
+ def __call__(
+ self,
+ __x1: _ScalarLike_co,
+ out: None = ...,
+ *,
+ where: None | _ArrayLikeBool_co = ...,
+ casting: _CastingKind = ...,
+ order: _OrderKACF = ...,
+ dtype: DTypeLike = ...,
+ subok: bool = ...,
+ signature: str | _2Tuple[None | str] = ...,
+ extobj: list[Any] = ...,
+ ) -> Any: ...
+ @overload
+ def __call__(
+ self,
+ __x1: ArrayLike,
+ out: None | NDArray[Any] | tuple[NDArray[Any]] = ...,
+ *,
+ where: None | _ArrayLikeBool_co = ...,
+ casting: _CastingKind = ...,
+ order: _OrderKACF = ...,
+ dtype: DTypeLike = ...,
+ subok: bool = ...,
+ signature: str | _2Tuple[None | str] = ...,
+ extobj: list[Any] = ...,
+ ) -> NDArray[Any]: ...
+ @overload
+ def __call__(
+ self,
+ __x1: _SupportsArrayUFunc,
+ out: None | NDArray[Any] | tuple[NDArray[Any]] = ...,
+ *,
+ where: None | _ArrayLikeBool_co = ...,
+ casting: _CastingKind = ...,
+ order: _OrderKACF = ...,
+ dtype: DTypeLike = ...,
+ subok: bool = ...,
+ signature: str | _2Tuple[None | str] = ...,
+ extobj: list[Any] = ...,
+ ) -> Any: ...
+
+ def at(
+ self,
+ a: _SupportsArrayUFunc,
+ indices: _ArrayLikeInt_co,
+ /,
+ ) -> None: ...
+
+class _UFunc_Nin2_Nout1(ufunc, Generic[_NameType, _NTypes, _IDType]): # type: ignore[misc]
+ @property
+ def __name__(self) -> _NameType: ...
+ @property
+ def ntypes(self) -> _NTypes: ...
+ @property
+ def identity(self) -> _IDType: ...
+ @property
+ def nin(self) -> Literal[2]: ...
+ @property
+ def nout(self) -> Literal[1]: ...
+ @property
+ def nargs(self) -> Literal[3]: ...
+ @property
+ def signature(self) -> None: ...
+
+ @overload
+ def __call__(
+ self,
+ __x1: _ScalarLike_co,
+ __x2: _ScalarLike_co,
+ out: None = ...,
+ *,
+ where: None | _ArrayLikeBool_co = ...,
+ casting: _CastingKind = ...,
+ order: _OrderKACF = ...,
+ dtype: DTypeLike = ...,
+ subok: bool = ...,
+ signature: str | _3Tuple[None | str] = ...,
+ extobj: list[Any] = ...,
+ ) -> Any: ...
+ @overload
+ def __call__(
+ self,
+ __x1: ArrayLike,
+ __x2: ArrayLike,
+ out: None | NDArray[Any] | tuple[NDArray[Any]] = ...,
+ *,
+ where: None | _ArrayLikeBool_co = ...,
+ casting: _CastingKind = ...,
+ order: _OrderKACF = ...,
+ dtype: DTypeLike = ...,
+ subok: bool = ...,
+ signature: str | _3Tuple[None | str] = ...,
+ extobj: list[Any] = ...,
+ ) -> NDArray[Any]: ...
+
+ def at(
+ self,
+ a: NDArray[Any],
+ indices: _ArrayLikeInt_co,
+ b: ArrayLike,
+ /,
+ ) -> None: ...
+
+ def reduce(
+ self,
+ array: ArrayLike,
+ axis: None | _ShapeLike = ...,
+ dtype: DTypeLike = ...,
+ out: None | NDArray[Any] = ...,
+ keepdims: bool = ...,
+ initial: Any = ...,
+ where: _ArrayLikeBool_co = ...,
+ ) -> Any: ...
+
+ def accumulate(
+ self,
+ array: ArrayLike,
+ axis: SupportsIndex = ...,
+ dtype: DTypeLike = ...,
+ out: None | NDArray[Any] = ...,
+ ) -> NDArray[Any]: ...
+
+ def reduceat(
+ self,
+ array: ArrayLike,
+ indices: _ArrayLikeInt_co,
+ axis: SupportsIndex = ...,
+ dtype: DTypeLike = ...,
+ out: None | NDArray[Any] = ...,
+ ) -> NDArray[Any]: ...
+
+ # Expand `**kwargs` into explicit keyword-only arguments
+ @overload
+ def outer(
+ self,
+ A: _ScalarLike_co,
+ B: _ScalarLike_co,
+ /, *,
+ out: None = ...,
+ where: None | _ArrayLikeBool_co = ...,
+ casting: _CastingKind = ...,
+ order: _OrderKACF = ...,
+ dtype: DTypeLike = ...,
+ subok: bool = ...,
+ signature: str | _3Tuple[None | str] = ...,
+ extobj: list[Any] = ...,
+ ) -> Any: ...
+ @overload
+ def outer( # type: ignore[misc]
+ self,
+ A: ArrayLike,
+ B: ArrayLike,
+ /, *,
+ out: None | NDArray[Any] | tuple[NDArray[Any]] = ...,
+ where: None | _ArrayLikeBool_co = ...,
+ casting: _CastingKind = ...,
+ order: _OrderKACF = ...,
+ dtype: DTypeLike = ...,
+ subok: bool = ...,
+ signature: str | _3Tuple[None | str] = ...,
+ extobj: list[Any] = ...,
+ ) -> NDArray[Any]: ...
+
+class _UFunc_Nin1_Nout2(ufunc, Generic[_NameType, _NTypes, _IDType]): # type: ignore[misc]
+ @property
+ def __name__(self) -> _NameType: ...
+ @property
+ def ntypes(self) -> _NTypes: ...
+ @property
+ def identity(self) -> _IDType: ...
+ @property
+ def nin(self) -> Literal[1]: ...
+ @property
+ def nout(self) -> Literal[2]: ...
+ @property
+ def nargs(self) -> Literal[3]: ...
+ @property
+ def signature(self) -> None: ...
+ @property
+ def at(self) -> None: ...
+ @property
+ def reduce(self) -> None: ...
+ @property
+ def accumulate(self) -> None: ...
+ @property
+ def reduceat(self) -> None: ...
+ @property
+ def outer(self) -> None: ...
+
+ @overload
+ def __call__(
+ self,
+ __x1: _ScalarLike_co,
+ __out1: None = ...,
+ __out2: None = ...,
+ *,
+ where: None | _ArrayLikeBool_co = ...,
+ casting: _CastingKind = ...,
+ order: _OrderKACF = ...,
+ dtype: DTypeLike = ...,
+ subok: bool = ...,
+ signature: str | _3Tuple[None | str] = ...,
+ extobj: list[Any] = ...,
+ ) -> _2Tuple[Any]: ...
+ @overload
+ def __call__(
+ self,
+ __x1: ArrayLike,
+ __out1: None | NDArray[Any] = ...,
+ __out2: None | NDArray[Any] = ...,
+ *,
+ out: _2Tuple[NDArray[Any]] = ...,
+ where: None | _ArrayLikeBool_co = ...,
+ casting: _CastingKind = ...,
+ order: _OrderKACF = ...,
+ dtype: DTypeLike = ...,
+ subok: bool = ...,
+ signature: str | _3Tuple[None | str] = ...,
+ extobj: list[Any] = ...,
+ ) -> _2Tuple[NDArray[Any]]: ...
+ @overload
+ def __call__(
+ self,
+ __x1: _SupportsArrayUFunc,
+ __out1: None | NDArray[Any] = ...,
+ __out2: None | NDArray[Any] = ...,
+ *,
+ out: _2Tuple[NDArray[Any]] = ...,
+ where: None | _ArrayLikeBool_co = ...,
+ casting: _CastingKind = ...,
+ order: _OrderKACF = ...,
+ dtype: DTypeLike = ...,
+ subok: bool = ...,
+ signature: str | _3Tuple[None | str] = ...,
+ extobj: list[Any] = ...,
+ ) -> _2Tuple[Any]: ...
+
+class _UFunc_Nin2_Nout2(ufunc, Generic[_NameType, _NTypes, _IDType]): # type: ignore[misc]
+ @property
+ def __name__(self) -> _NameType: ...
+ @property
+ def ntypes(self) -> _NTypes: ...
+ @property
+ def identity(self) -> _IDType: ...
+ @property
+ def nin(self) -> Literal[2]: ...
+ @property
+ def nout(self) -> Literal[2]: ...
+ @property
+ def nargs(self) -> Literal[4]: ...
+ @property
+ def signature(self) -> None: ...
+ @property
+ def at(self) -> None: ...
+ @property
+ def reduce(self) -> None: ...
+ @property
+ def accumulate(self) -> None: ...
+ @property
+ def reduceat(self) -> None: ...
+ @property
+ def outer(self) -> None: ...
+
+ @overload
+ def __call__(
+ self,
+ __x1: _ScalarLike_co,
+ __x2: _ScalarLike_co,
+ __out1: None = ...,
+ __out2: None = ...,
+ *,
+ where: None | _ArrayLikeBool_co = ...,
+ casting: _CastingKind = ...,
+ order: _OrderKACF = ...,
+ dtype: DTypeLike = ...,
+ subok: bool = ...,
+ signature: str | _4Tuple[None | str] = ...,
+ extobj: list[Any] = ...,
+ ) -> _2Tuple[Any]: ...
+ @overload
+ def __call__(
+ self,
+ __x1: ArrayLike,
+ __x2: ArrayLike,
+ __out1: None | NDArray[Any] = ...,
+ __out2: None | NDArray[Any] = ...,
+ *,
+ out: _2Tuple[NDArray[Any]] = ...,
+ where: None | _ArrayLikeBool_co = ...,
+ casting: _CastingKind = ...,
+ order: _OrderKACF = ...,
+ dtype: DTypeLike = ...,
+ subok: bool = ...,
+ signature: str | _4Tuple[None | str] = ...,
+ extobj: list[Any] = ...,
+ ) -> _2Tuple[NDArray[Any]]: ...
+
+class _GUFunc_Nin2_Nout1(ufunc, Generic[_NameType, _NTypes, _IDType]): # type: ignore[misc]
+ @property
+ def __name__(self) -> _NameType: ...
+ @property
+ def ntypes(self) -> _NTypes: ...
+ @property
+ def identity(self) -> _IDType: ...
+ @property
+ def nin(self) -> Literal[2]: ...
+ @property
+ def nout(self) -> Literal[1]: ...
+ @property
+ def nargs(self) -> Literal[3]: ...
+
+ # NOTE: In practice the only gufunc in the main namespace is `matmul`,
+ # so we can use its signature here
+ @property
+ def signature(self) -> Literal["(n?,k),(k,m?)->(n?,m?)"]: ...
+ @property
+ def reduce(self) -> None: ...
+ @property
+ def accumulate(self) -> None: ...
+ @property
+ def reduceat(self) -> None: ...
+ @property
+ def outer(self) -> None: ...
+ @property
+ def at(self) -> None: ...
+
+ # Scalar for 1D array-likes; ndarray otherwise
+ @overload
+ def __call__(
+ self,
+ __x1: ArrayLike,
+ __x2: ArrayLike,
+ out: None = ...,
+ *,
+ casting: _CastingKind = ...,
+ order: _OrderKACF = ...,
+ dtype: DTypeLike = ...,
+ subok: bool = ...,
+ signature: str | _3Tuple[None | str] = ...,
+ extobj: list[Any] = ...,
+ axes: list[_2Tuple[SupportsIndex]] = ...,
+ ) -> Any: ...
+ @overload
+ def __call__(
+ self,
+ __x1: ArrayLike,
+ __x2: ArrayLike,
+ out: NDArray[Any] | tuple[NDArray[Any]],
+ *,
+ casting: _CastingKind = ...,
+ order: _OrderKACF = ...,
+ dtype: DTypeLike = ...,
+ subok: bool = ...,
+ signature: str | _3Tuple[None | str] = ...,
+ extobj: list[Any] = ...,
+ axes: list[_2Tuple[SupportsIndex]] = ...,
+ ) -> NDArray[Any]: ...