GitLab

added CIFAR100 autoclass in docs

update SVHN docs to note label change for digit 0

According to the comment, this should be 1MB which is 1024*1024 bytes.

* added FashionMNIST dataset

* documentation

* fixed formatting

* fixed formatting

* enable ~ expression in datasets

* fixed root in __init__ to self.root

Make the labels be 1d tensors of type `np.int64`.
Assign label `0`  to data samples of digit 0. The original dataset assigns them label `10`.

* 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

See https://github.com/python-pillow/Pillow/issues/835

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

* 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

tgz_mdf should be changed to tgz_md5 to make it work