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TenCrop and FiveCrop refactored

add FiveCrop and TenCrop

add RandomVerticalFlip transform

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

This reverts commit 36849429.

* load densenet tensors onto cpu

* fix docs for size param in random + center crop

* revert incorrect commit

(cherry picked from commit 71afec427baca8e37cd9e10d98812bc586e9a4ac)

isinstance(padding, tuple) is added to the padding assertion to be able to pass a sequence.

Wrong order of dimensions In transforms.CenterCrop and transforms.RandomCrop:
Documentation says it should be (w, h), but it actually is (h, w).
Fixing docs to match the code

* 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

It can be enabled by calling torchvision.set_image_backend('accimage')

* Fixed border missing on bottom and right side using make_grid

* Add support for Transforms.Scale([h, w]) with specific height and width

if self.size is a int then scale the image with the shorter side,
otherwise if self.size is a list then scale the image to self.size
directly

* Add assert of size and doc for README

Add assert of size and doc for README

* Fix linter problem

Fix linter problem

* Add test for Scale

Add test for Scale

* Add both tuple and list support for Scale.size

Add both tuple and list support for Scale.size

* Add order of Scale.size in document and test case for list type of Scale.size

Add order of Scale.size in document and test case for list type of
Scale.size

* fix for to_tensor when input is np.ndarray of shape [H,W,C]. Issue #48 pytorch/vision

* update cifar datasets to transpose images from CHW -> HWC

* fix flake8 issue on test_transforms.py

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

Previous assertion only allows numbers for `fill`, which rules out the possibility to pad multi-channel colors. For example, now fill=(255,255,255) or fill="white" can be used to achieve white padding for rgb inputs.

YCbCr breaks the code without warning. Changed the code to make `ToTensor()` cope with all PIL image types.