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* Removed unnecessary class variables.

* The integrity of dataset files is now being checked right after the download finished. Thus making sure that a corrupt file is not being extracted. In case of corruption we throw a RuntimeError.

* Added missing md5 hashes to MNIST, FashionMNIST, KMNIST, EMNIST and QMNIST datasets.

* Removed printing of error message when integrity check failed.
Reformulated error message.

* Reformatted code to be lint conform.

* Fixed formatting in utils.py

* fix url

* update comment

* introduced function to verify str arguments

* flake8

* added FIXME to VOC

* Fixed error message

* added test for verify_str_arg

* cleanup todos

* added option for custom error message

* fix VOC

* fixed Caltech

* fixed call to the VisionDataset constructor

* change call from keyword arguments to positional

* changed order of arguments

* removed transforms argument once again

* Fixed call to constructor of parent class

* fixed LSUN

* fixed Caltech256

* Added general reader for sn3 tensors in "pascalvincent" format

* Added class QMNIST into mnist.py

* QMNIST dataset: make some pt files smaller

* Change request from fmassa.

* read_sn3_pascalvincent_tensor: cse

* read_sn3_pascalvincent_tensor: check file size (when strict!=False)

* Fix lint

* More lint

* Add documentation and expose QMNIST to dataset namespace

* added fake data

* fixed fake data

* renamed extract and download methods and added functionality

* added raw fake data

* refactored imagenet and added test

* flake8

* added fake devkit and mocked download_url

* reversed uncommenting

* added mock to CI

* fixed tests for imagefolder

* flake8

* WIP

* WIP: minor improvements

* Add tests

* Fix typo

* Use download_and_extract on caltech, cifar and omniglot

* Add a print message during extraction

* Remove EMNIST from test

* introduced new super class for all vision datasets

* Removed root from repr if dataset has no root

* reverted some overly-ambitious autoformatting

* reverted some overly-ambitious autoformatting

* added split attribute to repr of STL10 dataset

* made Python2 friendly and more robust

* Fixed call of the superclass constructor

* moved transform and target_transform back to the base classes

* added check if transforms are present before printing to avoid setting them within the constructor

* added missing transforms and target_transforms to base classes

* fixed linter error

* Update URL for EMNIST

Update the dataset and download URL for EMNIST to the url from the updated arxiv version.

* Update mnist.py

* Add KMNIST

* Add documentation

* Add KMNIST to module's __all__ list

* Revert "move area calculation out of loop (#641)"

This reverts commit 62cbf0bf.

* Revert "Fix FashionMNIST loading MNIST (#640)"

This reverts commit 36215690.

Before this would lead FashionMNIST to contain mnist data:

```
MNIST(root, download=True)
FashionMNIST(root, download=True)
```

As MNIST and FashionMNIST are the same classes, the processed
outputs actual ended up to be the same files. This commit now
stores them at different files and also stores the class name when
saving them. I also added md5 sums.

* cast mnist targer to int

* fix unused variables

* fix syntax in tests

* remove # noqa; rename l variable to line_split; use except OSError

* add W504

* add W504

* add W503,W504 tox.ini

* MNIST and FashionMNIST now have their own 'raw' and 'processed' folders

* mkdir exist_ok

* Add classes metadata to MNIST and FashionMNIST

* Add `targets` property to MNIST and FashionMNIST

* Add class metadata to CIFAR10/CIFAR100

* Add `targets` property to CIFAR10/CIFAR100

* Add targets attribute to DatasetFolder

The URL to download EMNIST seems to have changed. I fixed this.

* add __repr__ for datasets

* fix lint

* EMNIST dataset + speedup *MNIST preprocessing

* added FashionMNIST dataset

* documentation

* fixed formatting

* fixed formatting

* enable ~ expression in datasets

* fixed root in __init__ to self.root

* Add documentation for transforms

* document and remove unused imports in mnist.py

* document lsun, mscoco datasets

* rest of the datasets documented

* Clean up the documentation in other functions

* Add links for datasets

* Add more documentation

* pep8 fix

    git ls-files | grep '\.py$' | xargs -n1 -P`nproc` autopep8 -i