55 lines
1.6 KiB
Python
55 lines
1.6 KiB
Python
from __future__ import annotations
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from typing import cast, Callable, Generic, Type, TypeVar
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import torch
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__all__ = ['Await']
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W = TypeVar("W")
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class _PyAwaitMeta(type(torch._C._Await), type(Generic)): # type: ignore[misc, no-redef]
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pass
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class _Await(torch._C._Await, Generic[W], metaclass=_PyAwaitMeta):
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r"""
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Wrapper around a ``torch._C.Await`` which encapsulates delayed execution
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of a callable. All manipulations happen with functions ``torch.jit._awaitable``,
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``torch.jit._awaitable_wait``, ``torch.jit._awaitable_nowait``.
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Torch scriptable manipulations:
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``torch.jit._awaitable(func, *args)``
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Creates ``Await[W]`` object, where W is return type of func.
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Returns:
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``torch.jit._awaitable_wait(Await[W])``
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Returns the result of the function, specified at ``_awaitable``, with specified arguments.
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Returns:
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The result of type ``W`` of the function call. The result is owned by ``Await[W]``
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and returned on all following ``_awaitable_wait`` calls.
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``torch.jit._awaitable_nowait(W)``
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Returns:
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Trivial ``Await[W]`` with specified result.
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Only in eager mode:
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``fn() -> Callable[Tuple[Any], W]``
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Returns:
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Specified at ``_awaitable`` python function ``func``.
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``args() -> Tuple[Any]``
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Returns:
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Specified at ``_awaitable`` python args.
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``is_nowait() -> _bool``
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Returns:
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``True`` if this object was created via ``_awaitable_nowait`` call (trivial `Await[W]`).
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In eager mode ``Await[W]`` can be used as ``W`` i.e. attributes of W can be called on ``Await[W]``,
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``_awaitable_wait()`` call will be transparently added.
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"""
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pass
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