Adding torch.futures to API docs (#40051)

Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/40051

Test Plan: Imported from OSS

Differential Revision: D22055031

Pulled By: mrshenli

fbshipit-source-id: ce8a79ba4ffdc7dbed6d4c62b1c33b96764c89e7

docs/source/futures.rst

@@ -0,0 +1,24 @@
+.. currentmodule:: torch.futures
+
+.. _futures-docs:
+
+torch.futures
+=============
+
+.. warning::
+  The ``torch.futures`` package is experimental and subject to change.
+
+
+This package provides a :class:`~torch.futures.Future` type that encapsulates
+an asynchronous execution and a set of utility functions to simplify operations
+on :class:`~torch.futures.Future` objects. Currently, the
+:class:`~torch.futures.Future` type is primarily used by the
+:ref:`distributed-rpc-framework`.
+
+.. automodule:: torch.futures
+
+.. autoclass:: Future
+    :members:
+
+.. autofunction:: collect_all
+.. autofunction:: wait_all

docs/source/index.rst

@@ -39,6 +39,7 @@ PyTorch is an optimized tensor library for deep learning using GPUs and CPUs.
    torch.cuda.amp <amp>
    torch.distributed <distributed>
    torch.distributions <distributions>
+   futures
    torch.hub <hub>
    torch.jit <jit>
    nn.init
@@ -64,7 +65,7 @@ PyTorch is an optimized tensor library for deep learning using GPUs and CPUs.
 .. toctree::
    :maxdepth: 1
    :caption: Libraries
-   
+
    torchaudio <https://pytorch.org/audio>
    torchtext <https://pytorch.org/text>
    torchvision/index

torch/futures/__init__.py

@@ -1,7 +1,3 @@
-"""
-The ``torch.futures`` package contains a ``Future`` type and corresponding
-utility functions.
-"""
 import torch
 
 
@@ -10,9 +6,6 @@ class Future(torch._C.Future):
     Wrapper around a ``torch._C.Future`` which encapsulates an asynchronous
     execution of a callable, e.g. :meth:`~torch.distributed.rpc.rpc_async`. It
     also exposes a set of APIs to add callback functions and set results.
-
-    .. warning::
-        The ``torch.futures.Future`` is experimental and subject to change.
     """
     def __new__(cls):
         return super(Future, cls).__new__(cls)