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

First dimension is batch size, channel is the second

* add pad_value argument

* add argument to save_image

* fix space

* requested change of order

* update docs

* 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

I have made some performance improvements to the model, and testing them now.  If results turn out good, I will submit a separate PR.

Using python2 style '/' will convert int type to float in python3 which will cause the following error when creating FloatTensor:

TypeError: torch.FloatTensor constructor received an invalid combination of arguments - got (float, int, int, int), but expected one of:
 * no arguments
 * (int ...)
      didn't match because some of the arguments have invalid types: (float, int, int, int)

* clipping values, and replacing transposes with permute

Without clipping, any values larger than 255 will be replaced with
int(v mod 256) by byte(), which results in high freq noise in image.

* replaced clip with clamp

This reverts commit 2f579d58.

Without clipping, any values larger than 255 will be replaced with
int(v mod 256) by byte(), which results in high freq noise in image.

In python2, calling `make_grid` won't display the last images if the number of images doesn't divide `nrow`.
Int division...

This should fix that!

* 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