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torchvision.datasets
====================
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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.ImageFolder('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 


MNIST
~~~~~

.. autoclass:: MNIST

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:

LSUN
~~~~

.. autoclass:: LSUN
  :members: __getitem__
  :special-members:

ImageFolder
~~~~~~~~~~~

.. autoclass:: ImageFolder
  :members: __getitem__
  :special-members:


Imagenet-12
~~~~~~~~~~~

This should simply be implemented with an ``ImageFolder`` dataset.
The data is preprocessed `as described
here <https://github.com/facebook/fb.resnet.torch/blob/master/INSTALL.md#download-the-imagenet-dataset>`__

`Here is an
example <https://github.com/pytorch/examples/blob/27e2a46c1d1505324032b1d94fc6ce24d5b67e97/imagenet/main.py#L48-L62>`__.

CIFAR
~~~~~

.. autoclass:: CIFAR10
  :members: __getitem__
  :special-members:
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.. autoclass:: CIFAR100
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STL10
~~~~~


.. autoclass:: STL10
  :members: __getitem__
  :special-members:

SVHN
~~~~~


.. autoclass:: SVHN
  :members: __getitem__
  :special-members:

PhotoTour
~~~~~~~~~


.. autoclass:: PhotoTour
  :members: __getitem__
  :special-members: