GitLab

* added separate checks for dimensionality in to_pil_image and added tests

* updated to_pil_image to use both 2D ndarrays and tensors, as well as refactored the tests

* 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

Improve `test_pad_with_non_constant_padding_modes` to avoid data multiplication in `transforms.ToPILImage()` on float data:
```python
img = torch.zeros(3, 27, 27)  # Float32
img[:, :, 0] = 1   # we add 1 and not 255
img = transforms.ToPILImage()(img)  # This converts 1 to 255 due to [pic = pic.mul(255).byte()](https://github.com/pytorch/vision/blob/master/torchvision/transforms/functional.py#L107)
```
and thus test's correct values are [..., 200, 1, 0]

Remove test with variables

* Add case in test_to_tensor for PIL Images mode '1'

* Add support in ToTensor for PIL Images mode '1'

* Fix pep8 issues

* Made transorms.RandomCrop tolerate images smaller than the given size.

* Extended the tescase for transforms.RandomCrop

* Made the testcase test for owidth=width+1

* Fixed the one pixel pading and the testcase

* Fixed minor lintint errors. flake8 passes.

* Added reflect, symmetric and edge padding

* Updated padding docs, added tests

* Adding tests to ImageFolder

* Adding DatasetFolder class

* Fix tests for pytest and code for lint checker

* Adding mock to requirements for ImageFolder tests

* Remove mocks from requirements

This reverts commit ab03dc43.

* Adding tests to ImageFolder

* Adding DatasetFolder class

* Fix tests for pytest and code for lint checker

* Adding mock to requirements for ImageFolder tests

* Add random affine transformation

* Rewrite __repr__

* Refactor affine transform and update tests

* Add RandomApply, RandomChoice, RandomOrder transformations

* Rename argument `proba` to `p`

* Set probability as configuration parameter in RandomHorizontalFlip and RandomHorizontalFlip (#414)

* Fix documentation

* add __repr__ for all transform objects

* add tests for __repr__

* add to_grayscale + randomGrayscale

add rotate and RandomRotation to transforms

* refactor transforms and add transforms/functional.py

* add __all__ to transforms.py

* add assert for byte tensor to_pil_image

* add mode param to ToPILImage

* add some more tests

* fix formatiing on error messages

* added tests for to_pil_image with mode param

* flake8 fixes

expands coverage on test_to_tensor to 1 and 4 image channels

* added Whiten transform and relative section in README

* added Whiten transform and its section in README

* fixed lint

* fixed lint again

* added linear transformation and whitening test unitary covariance

* fixed lint and test

* commit before rebasing

* before rebase

* added assertion to check matrix size

* fix readme

* added space around operator

* replace assert with raise ValueError, fix spaces and readme

* increase num_samples, reduce alpha and fix seed for hflip and vflip tests

* flake8 fixes

* Add adjust_hue and adjust_saturation

* Add adjust_brightness, adjust_contrast

Also
* Change adjust_saturation to use pillow implementation
* Documentation made clear

* Add adjust_gamma

* Add ColorJitter

* Address review comments

* Fix documentation for ColorJitter

* Address review comments 2

* Fallback to adjust_hue in case of BW images

* Add tests

* fix dtype

rename scaled_crop -> resized_crop + rename RandomSizedCrop -> RandomResizedCrop

TenCrop and FiveCrop refactored

add FiveCrop and TenCrop

add RandomVerticalFlip transform

make size param of Scale (h,w) not (w,h)