BUG: vecdot signature

numpy/__init__.pyi

@@ -364,7 +364,6 @@ from numpy._core.numeric import (
     convolve as convolve,
     outer as outer,
     tensordot as tensordot,
-    vecdot as vecdot,
     roll as roll,
     rollaxis as rollaxis,
     moveaxis as moveaxis,
@@ -3321,7 +3320,7 @@ logical_and: _UFunc_Nin2_Nout1[L['logical_and'], L[20], L[True]]
 logical_not: _UFunc_Nin1_Nout1[L['logical_not'], L[20], None]
 logical_or: _UFunc_Nin2_Nout1[L['logical_or'], L[20], L[False]]
 logical_xor: _UFunc_Nin2_Nout1[L['logical_xor'], L[19], L[False]]
-matmul: _GUFunc_Nin2_Nout1[L['matmul'], L[19], None]
+matmul: _GUFunc_Nin2_Nout1[L['matmul'], L[19], None, L["(n?,k),(k,m?)->(n?,m?)"]]
 maximum: _UFunc_Nin2_Nout1[L['maximum'], L[21], None]
 minimum: _UFunc_Nin2_Nout1[L['minimum'], L[21], None]
 mod: _UFunc_Nin2_Nout1[L['remainder'], L[16], None]
@@ -3350,7 +3349,7 @@ tan: _UFunc_Nin1_Nout1[L['tan'], L[8], None]
 tanh: _UFunc_Nin1_Nout1[L['tanh'], L[8], None]
 true_divide: _UFunc_Nin2_Nout1[L['true_divide'], L[11], None]
 trunc: _UFunc_Nin1_Nout1[L['trunc'], L[7], None]
-vecdot: _GUFunc_Nin2_Nout1[L['vecdot'], L[19], None]
+vecdot: _GUFunc_Nin2_Nout1[L['vecdot'], L[19], None, L["(n),(n)->()"]]
 
 abs = absolute
 acos = arccos

numpy/_core/multiarray.py

@@ -42,7 +42,7 @@
     'set_legacy_print_mode',
     'set_typeDict', 'shares_memory', 'typeinfo',
     'unpackbits', 'unravel_index', 'vdot', 'where', 'zeros',
-    '_get_promotion_state', '_set_promotion_state']
+    '_get_promotion_state', '_set_promotion_state', 'vecdot']
 
 # For backward compatibility, make sure pickle imports 
 # these functions from here

numpy/_core/numeric.py

@@ -18,7 +18,7 @@
     fromstring, inner, lexsort, matmul, may_share_memory, min_scalar_type,
     ndarray, nditer, nested_iters, promote_types, putmask, result_type,
     shares_memory, vdot, where, zeros, normalize_axis_index,
-    _get_promotion_state, _set_promotion_state
+    _get_promotion_state, _set_promotion_state, vecdot
 )
 
 from . import overrides
@@ -53,7 +53,7 @@
     'identity', 'allclose', 'putmask',
     'flatnonzero', 'inf', 'nan', 'False_', 'True_', 'bitwise_not',
     'full', 'full_like', 'matmul', 'shares_memory', 'may_share_memory',
-    '_get_promotion_state', '_set_promotion_state']
+    '_get_promotion_state', '_set_promotion_state', 'vecdot']
 
 
 def _zeros_like_dispatcher(

numpy/_core/numeric.pyi

@@ -497,39 +497,6 @@ def tensordot(
     axes: int | tuple[_ShapeLike, _ShapeLike] = ...,
 ) -> NDArray[object_]: ...
 
-@overload
-def vecdot(
-    x1: _ArrayLikeUnknown, x2: _ArrayLikeUnknown, axis: int = ...
-) -> NDArray[Any]: ...
-@overload
-def vecdot(
-    x1: _ArrayLikeBool_co, x2: _ArrayLikeBool_co, axis: int = ...
-) -> NDArray[np.bool]: ...
-@overload
-def vecdot(
-    x1: _ArrayLikeUInt_co, x2: _ArrayLikeUInt_co, axis: int = ...
-) -> NDArray[unsignedinteger[Any]]: ...
-@overload
-def vecdot(
-    x1: _ArrayLikeInt_co, x2: _ArrayLikeInt_co, axis: int = ...
-) -> NDArray[signedinteger[Any]]: ...
-@overload
-def vecdot(
-    x1: _ArrayLikeFloat_co, x2: _ArrayLikeFloat_co, axis: int = ...
-) -> NDArray[floating[Any]]: ...
-@overload
-def vecdot(
-    x1: _ArrayLikeComplex_co, x2: _ArrayLikeComplex_co, axis: int = ...
-) -> NDArray[complexfloating[Any, Any]]: ...
-@overload
-def vecdot(
-    x1: _ArrayLikeTD64_co, x2: _ArrayLikeTD64_co, axis: int = ...
-) -> NDArray[timedelta64]: ...
-@overload
-def vecdot(
-    x1: _ArrayLikeObject_co, x2: _ArrayLikeObject_co, axis: int = ...
-) -> NDArray[object_]: ...
-
 @overload
 def roll(
     a: _ArrayLike[_SCT],

numpy/_core/umath.py

@@ -37,4 +37,4 @@
     'multiply', 'negative', 'nextafter', 'not_equal', 'pi', 'positive',
     'power', 'rad2deg', 'radians', 'reciprocal', 'remainder', 'right_shift',
     'rint', 'sign', 'signbit', 'sin', 'sinh', 'spacing', 'sqrt', 'square',
-    'subtract', 'tan', 'tanh', 'true_divide', 'trunc', 'vecdot']
+    'subtract', 'tan', 'tanh', 'true_divide', 'trunc']

numpy/_typing/_ufunc.pyi

@@ -33,6 +33,7 @@ _4Tuple = tuple[_T, _T, _T, _T]
 _NTypes = TypeVar("_NTypes", bound=int)
 _IDType = TypeVar("_IDType", bound=Any)
 _NameType = TypeVar("_NameType", bound=str)
+_Signature = TypeVar("_Signature", bound=str)
 
 
 class _SupportsArrayUFunc(Protocol):
@@ -366,7 +367,7 @@ class _UFunc_Nin2_Nout2(ufunc, Generic[_NameType, _NTypes, _IDType]):  # type: i
         signature: str | _4Tuple[None | str] = ...,
     ) -> _2Tuple[NDArray[Any]]: ...
 
-class _GUFunc_Nin2_Nout1(ufunc, Generic[_NameType, _NTypes, _IDType]):  # type: ignore[misc]
+class _GUFunc_Nin2_Nout1(ufunc, Generic[_NameType, _NTypes, _IDType, _Signature]):  # type: ignore[misc]
     @property
     def __name__(self) -> _NameType: ...
     @property
@@ -379,11 +380,8 @@ class _GUFunc_Nin2_Nout1(ufunc, Generic[_NameType, _NTypes, _IDType]):  # type:
     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?)"]: ...
+    def signature(self) -> _Signature: ...
     @property
     def reduce(self) -> None: ...
     @property

numpy/typing/tests/data/reveal/numeric.pyi

@@ -91,12 +91,6 @@ assert_type(np.tensordot(AR_i8, AR_c16), npt.NDArray[np.complexfloating[Any, Any
 assert_type(np.tensordot(AR_i8, AR_m), npt.NDArray[np.timedelta64])
 assert_type(np.tensordot(AR_O, AR_O), npt.NDArray[np.object_])
 
-assert_type(np.vecdot(AR_i8, AR_i8), npt.NDArray[np.signedinteger[Any]])
-assert_type(np.vecdot(AR_b, AR_b), npt.NDArray[np.bool])
-assert_type(np.vecdot(AR_b, AR_u8), npt.NDArray[np.unsignedinteger[Any]])
-assert_type(np.vecdot(AR_i8, AR_b), npt.NDArray[np.signedinteger[Any]])
-assert_type(np.vecdot(AR_i8, AR_f8), npt.NDArray[np.floating[Any]])
-
 assert_type(np.isscalar(i8), bool)
 assert_type(np.isscalar(AR_i8), bool)
 assert_type(np.isscalar(B), bool)

numpy/typing/tests/data/reveal/ufuncs.pyi

@@ -76,6 +76,16 @@ assert_type(np.matmul.identity, None)
 assert_type(np.matmul(AR_f8, AR_f8), Any)
 assert_type(np.matmul(AR_f8, AR_f8, axes=[(0, 1), (0, 1), (0, 1)]), Any)
 
+assert_type(np.vecdot.__name__, Literal["vecdot"])
+assert_type(np.vecdot.ntypes, Literal[19])
+assert_type(np.vecdot.identity, None)
+assert_type(np.vecdot.nin, Literal[2])
+assert_type(np.vecdot.nout, Literal[1])
+assert_type(np.vecdot.nargs, Literal[3])
+assert_type(np.vecdot.signature, Literal["(n),(n)->()"])
+assert_type(np.vecdot.identity, None)
+assert_type(np.vecdot(AR_f8, AR_f8), Any)
+
 assert_type(np.bitwise_count.__name__, Literal['bitwise_count'])
 assert_type(np.bitwise_count.ntypes, Literal[11])
 assert_type(np.bitwise_count.identity, None)

tools/ci/array-api-skips.txt

@@ -13,7 +13,3 @@ array_api_tests/test_signatures.py::test_func_signature[reshape]
 # missing 'descending' keyword arguments
 array_api_tests/test_signatures.py::test_func_signature[argsort]
 array_api_tests/test_signatures.py::test_func_signature[sort]
-
-# TODO: check why in CI `inspect.signature(np.vecdot)` returns (*arg, **kwarg)
-#       instead of raising ValueError. mtsokol: couldn't reproduce locally
-array_api_tests/test_signatures.py::test_func_signature[vecdot]