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from collections.abc import Sequence
from typing import TypeVar, Any, overload, Union, Literal
from numpy import (
ndarray,
dtype,
bool_,
unsignedinteger,
signedinteger,
floating,
complexfloating,
number,
_OrderKACF,
)
from numpy._typing import (
_ArrayLikeBool_co,
_ArrayLikeUInt_co,
_ArrayLikeInt_co,
_ArrayLikeFloat_co,
_ArrayLikeComplex_co,
_DTypeLikeBool,
_DTypeLikeUInt,
_DTypeLikeInt,
_DTypeLikeFloat,
_DTypeLikeComplex,
_DTypeLikeComplex_co,
)
_ArrayType = TypeVar(
"_ArrayType",
bound=ndarray[Any, dtype[Union[bool_, number[Any]]]],
)
_OptimizeKind = None | bool | Literal["greedy", "optimal"] | Sequence[Any]
_CastingSafe = Literal["no", "equiv", "safe", "same_kind"]
_CastingUnsafe = Literal["unsafe"]
__all__: list[str]
# TODO: Properly handle the `casting`-based combinatorics
# TODO: We need to evaluate the content `__subscripts` in order
# to identify whether or an array or scalar is returned. At a cursory
# glance this seems like something that can quite easily be done with
# a mypy plugin.
# Something like `is_scalar = bool(__subscripts.partition("->")[-1])`
@overload
def einsum(
subscripts: str | _ArrayLikeInt_co,
/,
*operands: _ArrayLikeBool_co,
out: None = ...,
dtype: None | _DTypeLikeBool = ...,
order: _OrderKACF = ...,
casting: _CastingSafe = ...,
optimize: _OptimizeKind = ...,
) -> Any: ...
@overload
def einsum(
subscripts: str | _ArrayLikeInt_co,
/,
*operands: _ArrayLikeUInt_co,
out: None = ...,
dtype: None | _DTypeLikeUInt = ...,
order: _OrderKACF = ...,
casting: _CastingSafe = ...,
optimize: _OptimizeKind = ...,
) -> Any: ...
@overload
def einsum(
subscripts: str | _ArrayLikeInt_co,
/,
*operands: _ArrayLikeInt_co,
out: None = ...,
dtype: None | _DTypeLikeInt = ...,
order: _OrderKACF = ...,
casting: _CastingSafe = ...,
optimize: _OptimizeKind = ...,
) -> Any: ...
@overload
def einsum(
subscripts: str | _ArrayLikeInt_co,
/,
*operands: _ArrayLikeFloat_co,
out: None = ...,
dtype: None | _DTypeLikeFloat = ...,
order: _OrderKACF = ...,
casting: _CastingSafe = ...,
optimize: _OptimizeKind = ...,
) -> Any: ...
@overload
def einsum(
subscripts: str | _ArrayLikeInt_co,
/,
*operands: _ArrayLikeComplex_co,
out: None = ...,
dtype: None | _DTypeLikeComplex = ...,
order: _OrderKACF = ...,
casting: _CastingSafe = ...,
optimize: _OptimizeKind = ...,
) -> Any: ...
@overload
def einsum(
subscripts: str | _ArrayLikeInt_co,
/,
*operands: Any,
casting: _CastingUnsafe,
dtype: None | _DTypeLikeComplex_co = ...,
out: None = ...,
order: _OrderKACF = ...,
optimize: _OptimizeKind = ...,
) -> Any: ...
@overload
def einsum(
subscripts: str | _ArrayLikeInt_co,
/,
*operands: _ArrayLikeComplex_co,
out: _ArrayType,
dtype: None | _DTypeLikeComplex_co = ...,
order: _OrderKACF = ...,
casting: _CastingSafe = ...,
optimize: _OptimizeKind = ...,
) -> _ArrayType: ...
@overload
def einsum(
subscripts: str | _ArrayLikeInt_co,
/,
*operands: Any,
out: _ArrayType,
casting: _CastingUnsafe,
dtype: None | _DTypeLikeComplex_co = ...,
order: _OrderKACF = ...,
optimize: _OptimizeKind = ...,
) -> _ArrayType: ...
# NOTE: `einsum_call` is a hidden kwarg unavailable for public use.
# It is therefore excluded from the signatures below.
# NOTE: In practice the list consists of a `str` (first element)
# and a variable number of integer tuples.
def einsum_path(
subscripts: str | _ArrayLikeInt_co,
/,
*operands: _ArrayLikeComplex_co,
optimize: _OptimizeKind = ...,
) -> tuple[list[Any], str]: ...
|
