Python 3..6 & Google Colab support

This minor release introduces Python 3.6 compatibility hence the library can now be freely used on Google's Colab.

Additional changes:

• Improved related section in documentation
• Introduced official library alias (td, import torchdata as td) throughout documentation
• Redesign of README & example of torchvision integration.

Minor bug fixes

Up to this point only single bug was found (torchdata.WrapDataset performing infinite recursion).

This is probably the last 0.1.x release, next version (0.2.0) will focus on improvements of pipeline related minor issues, naming and finishing documentation.

Necessary extensions

This release was focused on missing functionalities, only minor improvements (beside documentation) and coverage this time.

This is the last pre-release before releasing for wider audience.

Major Features and Improvements:

• Refactor concrete datasets into torchdata.datasets module (only torchdata.Dataset and torchdata.Iterable are now available inside torchdata main namespace)
• torchdata.Iterable got apply (just like torchdata.Dataset) and filter abilities
• Add torchdata.datasets.WrapDataset and torchdata.datasets.WrapIterable, which act as a proxy between existing torch.utils.data.Dataset / torch.utils.data.IterableDataset and torchdata counterparts. Using those classes, one can easily transform torchvision datasets or any other pre-made and use map, cache and a-like on them.
• torchdata.Dataset got reduce operation

Bug fixes:

• Minor test coverage improvements in uncertain places

Bug fixes and test coverage

Another pre-release focused mainly on bug fixing and maintenance of current functionality. All changes are breaking at this point and API should be considered unstable.

Major Features and Improvements:

• Added torchdata.modifiers.Lambda (arbitrary function can modify any cacher)
• Made torchdata.cacher.Pickle work as a context manager (cleaning cache directory after block)
• Function arguments come first unless varargs have to be specified. Mainly changes torchdata.modifiers module
• torchdata.maps.Drop and torchdata.maps.Select return single element instead of single element tuple

Fixes

• Added modifiers to __init__
• Fix incorrect OverSampler and UnderSampler behaviour
• Fix torchdata.cacher.Pickle to use correct binary format
• Minor fixes dictated by unit tests (see appropriate commits)

Initial release

Hello 😄 ,

This is initial release of torchdata library, which currently should be considered as alpha.

To see what it's all about, check README.md.

To get in-depth info, check documentation.

Hope you will have more fun with data and PyTorch from now on, cheers 💯