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112 lines
3.4 KiB
112 lines
3.4 KiB
import abc
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from threading import Lock
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from collections.abc import Callable, Mapping, Sequence
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from typing import (
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Any,
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NamedTuple,
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TypedDict,
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TypeVar,
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Union,
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overload,
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Literal,
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)
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from numpy import dtype, ndarray, uint32, uint64
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from numpy._typing import _ArrayLikeInt_co, _ShapeLike, _SupportsDType, _UInt32Codes, _UInt64Codes
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_T = TypeVar("_T")
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_DTypeLikeUint32 = Union[
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dtype[uint32],
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_SupportsDType[dtype[uint32]],
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type[uint32],
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_UInt32Codes,
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]
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_DTypeLikeUint64 = Union[
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dtype[uint64],
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_SupportsDType[dtype[uint64]],
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type[uint64],
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_UInt64Codes,
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]
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class _SeedSeqState(TypedDict):
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entropy: None | int | Sequence[int]
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spawn_key: tuple[int, ...]
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pool_size: int
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n_children_spawned: int
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class _Interface(NamedTuple):
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state_address: Any
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state: Any
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next_uint64: Any
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next_uint32: Any
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next_double: Any
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bit_generator: Any
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class ISeedSequence(abc.ABC):
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@abc.abstractmethod
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def generate_state(
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self, n_words: int, dtype: _DTypeLikeUint32 | _DTypeLikeUint64 = ...
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) -> ndarray[Any, dtype[uint32 | uint64]]: ...
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class ISpawnableSeedSequence(ISeedSequence):
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@abc.abstractmethod
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def spawn(self: _T, n_children: int) -> list[_T]: ...
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class SeedlessSeedSequence(ISpawnableSeedSequence):
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def generate_state(
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self, n_words: int, dtype: _DTypeLikeUint32 | _DTypeLikeUint64 = ...
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) -> ndarray[Any, dtype[uint32 | uint64]]: ...
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def spawn(self: _T, n_children: int) -> list[_T]: ...
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class SeedSequence(ISpawnableSeedSequence):
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entropy: None | int | Sequence[int]
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spawn_key: tuple[int, ...]
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pool_size: int
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n_children_spawned: int
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pool: ndarray[Any, dtype[uint32]]
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def __init__(
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self,
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entropy: None | int | Sequence[int] | _ArrayLikeInt_co = ...,
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*,
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spawn_key: Sequence[int] = ...,
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pool_size: int = ...,
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n_children_spawned: int = ...,
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) -> None: ...
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def __repr__(self) -> str: ...
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@property
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def state(
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self,
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) -> _SeedSeqState: ...
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def generate_state(
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self, n_words: int, dtype: _DTypeLikeUint32 | _DTypeLikeUint64 = ...
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) -> ndarray[Any, dtype[uint32 | uint64]]: ...
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def spawn(self, n_children: int) -> list[SeedSequence]: ...
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class BitGenerator(abc.ABC):
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lock: Lock
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def __init__(self, seed: None | _ArrayLikeInt_co | SeedSequence = ...) -> None: ...
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def __getstate__(self) -> dict[str, Any]: ...
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def __setstate__(self, state: dict[str, Any]) -> None: ...
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def __reduce__(
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self,
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) -> tuple[Callable[[str], BitGenerator], tuple[str], tuple[dict[str, Any]]]: ...
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@abc.abstractmethod
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@property
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def state(self) -> Mapping[str, Any]: ...
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@state.setter
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def state(self, value: Mapping[str, Any]) -> None: ...
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@property
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def seed_seq(self) -> ISeedSequence: ...
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def spawn(self, n_children: int) -> list[BitGenerator]: ...
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@overload
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def random_raw(self, size: None = ..., output: Literal[True] = ...) -> int: ... # type: ignore[misc]
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@overload
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def random_raw(self, size: _ShapeLike = ..., output: Literal[True] = ...) -> ndarray[Any, dtype[uint64]]: ... # type: ignore[misc]
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@overload
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def random_raw(self, size: None | _ShapeLike = ..., output: Literal[False] = ...) -> None: ... # type: ignore[misc]
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def _benchmark(self, cnt: int, method: str = ...) -> None: ...
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@property
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def ctypes(self) -> _Interface: ...
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@property
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def cffi(self) -> _Interface: ...
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