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80 lines
1.7 KiB
80 lines
1.7 KiB
from collections.abc import Iterable
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from typing import Any, TypeVar, overload, SupportsIndex
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from numpy import generic
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from numpy._typing import (
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NDArray,
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ArrayLike,
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_ShapeLike,
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_Shape,
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_ArrayLike
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)
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_SCT = TypeVar("_SCT", bound=generic)
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__all__: list[str]
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class DummyArray:
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__array_interface__: dict[str, Any]
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base: None | NDArray[Any]
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def __init__(
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self,
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interface: dict[str, Any],
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base: None | NDArray[Any] = ...,
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) -> None: ...
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@overload
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def as_strided(
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x: _ArrayLike[_SCT],
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shape: None | Iterable[int] = ...,
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strides: None | Iterable[int] = ...,
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subok: bool = ...,
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writeable: bool = ...,
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) -> NDArray[_SCT]: ...
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@overload
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def as_strided(
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x: ArrayLike,
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shape: None | Iterable[int] = ...,
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strides: None | Iterable[int] = ...,
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subok: bool = ...,
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writeable: bool = ...,
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) -> NDArray[Any]: ...
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@overload
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def sliding_window_view(
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x: _ArrayLike[_SCT],
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window_shape: int | Iterable[int],
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axis: None | SupportsIndex = ...,
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*,
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subok: bool = ...,
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writeable: bool = ...,
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) -> NDArray[_SCT]: ...
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@overload
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def sliding_window_view(
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x: ArrayLike,
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window_shape: int | Iterable[int],
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axis: None | SupportsIndex = ...,
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*,
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subok: bool = ...,
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writeable: bool = ...,
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) -> NDArray[Any]: ...
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@overload
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def broadcast_to(
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array: _ArrayLike[_SCT],
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shape: int | Iterable[int],
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subok: bool = ...,
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) -> NDArray[_SCT]: ...
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@overload
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def broadcast_to(
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array: ArrayLike,
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shape: int | Iterable[int],
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subok: bool = ...,
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) -> NDArray[Any]: ...
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def broadcast_shapes(*args: _ShapeLike) -> _Shape: ...
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def broadcast_arrays(
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*args: ArrayLike,
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subok: bool = ...,
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) -> list[NDArray[Any]]: ...
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