pytorch · brianjo · Oct 27, 2020 · Oct 27, 2020
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diff --git a/docs/1.7.0/torchvision/_sources/datasets.rst.txt b/docs/1.7.0/torchvision/_sources/datasets.rst.txt
@@ -0,0 +1,233 @@
+torchvision.datasets
+====================
+
+All datasets are subclasses of :class:`torch.utils.data.Dataset`
+i.e, they have ``__getitem__`` and ``__len__`` methods implemented.
+Hence, they can all be passed to a :class:`torch.utils.data.DataLoader`
+which can load multiple samples parallelly using ``torch.multiprocessing`` workers.
+For example: ::
+
+    imagenet_data = torchvision.datasets.ImageNet('path/to/imagenet_root/')
+    data_loader = torch.utils.data.DataLoader(imagenet_data,
+                                              batch_size=4,
+                                              shuffle=True,
+                                              num_workers=args.nThreads)
+
+The following datasets are available:
+
+.. contents:: Datasets
+    :local:
+
+All the datasets have almost similar API. They all have two common arguments:
+``transform`` and  ``target_transform`` to transform the input and target respectively.
+
+
+.. currentmodule:: torchvision.datasets
+
+CelebA
+~~~~~~
+
+.. autoclass:: CelebA
+  :members: __getitem__
+  :special-members:
+
+CIFAR
+~~~~~
+
+.. autoclass:: CIFAR10
+  :members: __getitem__
+  :special-members:
+
+.. autoclass:: CIFAR100
+
+Cityscapes
+~~~~~~~~~~
+
+.. note ::
+    Requires Cityscape to be downloaded.
+
+.. autoclass:: Cityscapes
+  :members: __getitem__
+  :special-members:
+
+COCO
+~~~~
+
+.. note ::
+    These require the `COCO API to be installed`_
+
+.. _COCO API to be installed: https://github.com/pdollar/coco/tree/master/PythonAPI
+
+
+Captions
+^^^^^^^^
+
+.. autoclass:: CocoCaptions
+  :members: __getitem__
+  :special-members:
+
+
+Detection
+^^^^^^^^^
+
+.. autoclass:: CocoDetection
+  :members: __getitem__
+  :special-members:
+
+DatasetFolder
+~~~~~~~~~~~~~
+
+.. autoclass:: DatasetFolder
+  :members: __getitem__
+  :special-members:
+
+
+EMNIST
+~~~~~~
+
+.. autoclass:: EMNIST
+
+FakeData
+~~~~~~~~
+
+.. autoclass:: FakeData
+
+Fashion-MNIST
+~~~~~~~~~~~~~
+
+.. autoclass:: FashionMNIST
+
+Flickr
+~~~~~~
+
+.. autoclass:: Flickr8k
+  :members: __getitem__
+  :special-members:
+
+.. autoclass:: Flickr30k
+  :members: __getitem__
+  :special-members:
+
+HMDB51
+~~~~~~~
+
+.. autoclass:: HMDB51
+  :members: __getitem__
+  :special-members:
+
+ImageFolder
+~~~~~~~~~~~
+
+.. autoclass:: ImageFolder
+  :members: __getitem__
+  :special-members:
+
+ImageNet
+~~~~~~~~~~~
+
+.. autoclass:: ImageNet
+
+.. note ::
+    This requires `scipy` to be installed
+
+Kinetics-400
+~~~~~~~~~~~~
+
+.. autoclass:: Kinetics400
+  :members: __getitem__
+  :special-members:
+
+KMNIST
+~~~~~~~~~~~~~
+
+.. autoclass:: KMNIST
+
+LSUN
+~~~~
+
+.. autoclass:: LSUN
+  :members: __getitem__
+  :special-members:
+
+MNIST
+~~~~~
+
+.. autoclass:: MNIST
+
+Omniglot
+~~~~~~
+
+.. autoclass:: Omniglot
+
+PhotoTour
+~~~~~~~~~
+
+.. autoclass:: PhotoTour
+  :members: __getitem__
+  :special-members:
+
+Places365
+~~~~~~~~~
+
+.. autoclass:: Places365
+  :members: __getitem__
+  :special-members:
+
+QMNIST
+~~~~~~
+
+.. autoclass:: QMNIST
+
+SBD
+~~~~~~
+
+.. autoclass:: SBDataset
+  :members: __getitem__
+  :special-members:
+
+SBU
+~~~
+
+.. autoclass:: SBU
+  :members: __getitem__
+  :special-members:
+
+STL10
+~~~~~
+
+.. autoclass:: STL10
+  :members: __getitem__
+  :special-members:
+
+SVHN
+~~~~~
+
+.. autoclass:: SVHN
+  :members: __getitem__
+  :special-members:
+
+UCF101
+~~~~~~~
+
+.. autoclass:: UCF101
+  :members: __getitem__
+  :special-members:
+
+USPS
+~~~~~
+
+.. autoclass:: USPS
+  :members: __getitem__
+  :special-members:
+
+VOC
+~~~~~~
+
+.. autoclass:: VOCSegmentation
+  :members: __getitem__
+  :special-members:
+
+.. autoclass:: VOCDetection
+  :members: __getitem__
+  :special-members:
+
diff --git a/docs/1.7.0/torchvision/_sources/index.rst.txt b/docs/1.7.0/torchvision/_sources/index.rst.txt
@@ -0,0 +1,54 @@
+torchvision
+===========
+This library is part of the `PyTorch
+<http://pytorch.org/>`_ project. PyTorch is an open source
+machine learning framework.
+
+Features described in this documentation are classified by release status:
+
+  *Stable:*  These features will be maintained long-term and there should generally
+  be no major performance limitations or gaps in documentation.
+  We also expect to maintain backwards compatibility (although
+  breaking changes can happen and notice will be given one release ahead
+  of time).
+
+  *Beta:*  Features are tagged as Beta because the API may change based on
+  user feedback, because the performance needs to improve, or because
+  coverage across operators is not yet complete. For Beta features, we are
+  committing to seeing the feature through to the Stable classification.
+  We are not, however, committing to backwards compatibility.
+
+  *Prototype:*  These features are typically not available as part of
+  binary distributions like PyPI or Conda, except sometimes behind run-time
+  flags, and are at an early stage for feedback and testing.
+
+
+
+The :mod:`torchvision` package consists of popular datasets, model
+architectures, and common image transformations for computer vision.
+
+.. toctree::
+   :maxdepth: 2
+   :caption: Package Reference
+
+   datasets
+   io
+   models
+   ops
+   transforms
+   utils
+
+.. automodule:: torchvision
+   :members:
+
+.. toctree::
+   :maxdepth: 1
+   :caption: PyTorch Libraries
+
+   PyTorch <https://pytorch.org/docs>
+   torchaudio <https://pytorch.org/audio>
+   torchtext <https://pytorch.org/text>
+   torchvision <https://pytorch.org/vision>
+   TorchElastic <https://pytorch.org/elastic/>
+   TorchServe <https://pytorch.org/serve>
+   PyTorch on XLA Devices <http://pytorch.org/xla/>
diff --git a/docs/1.7.0/torchvision/_sources/io.rst.txt b/docs/1.7.0/torchvision/_sources/io.rst.txt
@@ -0,0 +1,72 @@
+torchvision.io
+==============
+
+.. currentmodule:: torchvision.io
+
+The :mod:`torchvision.io` package provides functions for performing IO
+operations. They are currently specific to reading and writing video and
+images.
+
+Video
+-----
+
+.. autofunction:: read_video
+
+.. autofunction:: read_video_timestamps
+
+.. autofunction:: write_video
+
+
+Fine-grained video API
+-------------------
+
+In addition to the :mod:`read_video` function, we provide a high-performance 
+lower-level API for more fine-grained control compared to the :mod:`read_video` function.
+It does all this whilst fully supporting torchscript.
+
+.. autoclass:: VideoReader
+    :members: __next__, get_metadata, set_current_stream, seek
+
+
+Example of inspecting a video:
+
+.. code:: python
+
+    import torchvision
+    video_path = "path to a test video"
+    # Constructor allocates memory and a threaded decoder
+    # instance per video. At the momet it takes two arguments:
+    # path to the video file, and a wanted stream.
+    reader = torchvision.io.VideoReader(video_path, "video")
+
+    # The information about the video can be retrieved using the 
+    # `get_metadata()` method. It returns a dictionary for every stream, with
+    # duration and other relevant metadata (often frame rate)
+    reader_md = reader.get_metadata()
+
+    # metadata is structured as a dict of dicts with following structure
+    # {"stream_type": {"attribute": [attribute per stream]}}
+    #
+    # following would print out the list of frame rates for every present video stream
+    print(reader_md["video"]["fps"])
+
+    # we explicitly select the stream we would like to operate on. In
+    # the constructor we select a default video stream, but
+    # in practice, we can set whichever stream we would like 
+    video.set_current_stream("video:0")
+
+
+Image
+-----
+
+.. autofunction:: read_image
+
+.. autofunction:: decode_image
+
+.. autofunction:: encode_jpeg
+
+.. autofunction:: write_jpeg
+
+.. autofunction:: encode_png
+
+.. autofunction:: write_png