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Edit File: einsumfunc.pyi
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]: ...