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