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Direktori : /proc/thread-self/root/opt/cloudlinux/venv/lib64/python3.11/site-packages/numpy/core/ |
Current File : //proc/thread-self/root/opt/cloudlinux/venv/lib64/python3.11/site-packages/numpy/core/_internal.pyi |
from typing import Any, TypeVar, overload, Generic import ctypes as ct from numpy import ndarray from numpy.ctypeslib import c_intp _CastT = TypeVar("_CastT", bound=ct._CanCastTo) # Copied from `ctypes.cast` _CT = TypeVar("_CT", bound=ct._CData) _PT = TypeVar("_PT", bound=None | int) # TODO: Let the likes of `shape_as` and `strides_as` return `None` # for 0D arrays once we've got shape-support class _ctypes(Generic[_PT]): @overload def __new__(cls, array: ndarray[Any, Any], ptr: None = ...) -> _ctypes[None]: ... @overload def __new__(cls, array: ndarray[Any, Any], ptr: _PT) -> _ctypes[_PT]: ... @property def data(self) -> _PT: ... @property def shape(self) -> ct.Array[c_intp]: ... @property def strides(self) -> ct.Array[c_intp]: ... @property def _as_parameter_(self) -> ct.c_void_p: ... def data_as(self, obj: type[_CastT]) -> _CastT: ... def shape_as(self, obj: type[_CT]) -> ct.Array[_CT]: ... def strides_as(self, obj: type[_CT]) -> ct.Array[_CT]: ...