v0.1.5

======

Fixed
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* Fix setup.py for windows installs.

v0.1.4

======

Added
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* `FilteredMetaDatasest` filter the classes used to sample tasks.
* `UnionMetaDatasest` to get the union of multiple MetaDatasets.
* Alias `MiniImageNetCNN` to `CNN4` and add `embedding_size` argument.
* Optional data augmentation schemes for vision benchmarks.
* `l2l.vision.models.ResNet12`
* `l2l.vision.datasets.DescribableTextures`
* `l2l.vision.datasets.Quickdraw`
* `l2l.vision.datasets.FGVCFungi`
* Add `labels_to_indices` and `indices_to_labels` as optional arguments to `l2l.data.MetaDataset`.

Changed
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* Updated reference for citations.

Added

=====

* `l2l.vision.datasets.CUBirds200`.

Changed
-------

* Optimization transforms can be accessed directly through `l2l.optim`, e.g. `l2l.optim.KroneckerTransform`.
* All vision models adhere to the `.features` and `.classifier` interface.

Fixed
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* Fix `clone_module` for Modules whose submodules share parameters.

v0.1.2

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Added
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* New example: [Meta-World](https://github.com/rlworkgroup/metaworld) example with MAML-TRPO with it's own env wrapper. (@[Kostis-S-Z](https://github.com/Kostis-S-Z))
* `l2l.vision.benchmarks` interface.
* Differentiable optimization utilities in `l2l.optim`. (including `l2l.optim.LearnableOptimizer` for meta-descent)
* General gradient-based meta-learning wrapper in `l2l.algorithms.GBML`.
* Various `nn.Modules` in `l2l.nn`.
* `l2l.update_module` as a more general alternative to `l2l.algorithms.maml_update`.

Fixed
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* clone_module supports non-Module objects.
* VGG flowers now relies on tarfile.open() instead of tarfile.TarFile().

v0.1.1

======

Added
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* New tutorial: 'Feature Reuse with ANIL'. (@ewinapun)

Changed
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* Mujoco imports optional for docs: the import error is postponed to first method call.

Fixed
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* `MAML()` and `clone_module` support for RNN modules.

v0.1.0.1

========

Fixed
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* Remove Cython dependency when installing from PyPI and clean up package distribution.

Added

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* A CHANGELOG.md file.
* New vision datasets: FC100, tiered-Imagenet, FGVCAircraft, VGGFlowers102.
* New vision examples: Reptile & ANIL.
* Extensive benchmarks of all vision examples.

Changed
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* Re-wrote TaskDataset and task transforms in Cython, for a 20x speed-up.
* Travis testing with different versions of Python (3.6, 3.7), torch (1.1, 1.2, 1.3, 1.4), and torchvision (0.3, 0.4, 0.5).
* New Material doc theme with links to changelog and examples.

Fixed
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* Support for `RandomClassRotation` with newer versions of torchvision.
* Various minor fixes in the examples.
* Add Dropbox download if GDrive fails for FC100.

First public release.