v0.2.1

======

Changed
-------

* Make qpth dependency optional.

MetaModules, TasksetSampler, Adapters & LoRA, more examples and

tutorials.

v0.1.7

======

Added
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* Bounding box cropping for Aircraft and CUB200.
* Pretrained weights for vision models with: `l2l.vision.models.get_pretrained_backbone()`.
* Add `keep_requires_grad` flag to `detach_module`. ([Zhaofeng Wu](https://github.com/ZhaofengWu))

Fixed
-----

* Fix arguments when instantiating `l2l.nn.Scale`.
* Fix `train_loss` logging in `LightningModule` implementations with PyTorch-Lightning 1.5.
* Fix `RandomClassRotation` ([#283](#283)) to incorporate multi-channelled inputs. ([Varad Pimpalkhute](https://github.com/nightlessbaron/))
* Fix memory leak in `maml.py` and `meta-sgd.py` and add tests to `maml_test.py` and `metasgd_test.py` to check for possible future memory leaks. ([#284] (#284)) ([Kevin Zhang] (https://github.com/kzhang2))

v0.1.6

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Added
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* PyTorch Lightning interface to MAML, ANIL, ProtoNet, MetaOptNet.
* Automatic batcher for Lightning: `l2l.data.EpisodicBatcher`.
* `l2l.nn.PrototypicalClassifier` and `l2l.nn.SVMClassifier`.
* Add `l2l.vision.models.WRN28`.
* Separate modules for `CNN4Backbone`, `ResNet12Backbone`, `WRN28Backbones` w/ pretrained weights.
* Add `l2l.data.OnDeviceDataset` and implement `device` parameter for benchmarks.
* (Beta) Add `l2l.data.partition_task` and `l2l.data.InfiniteIterator`.

Changed
-------

* Renamed and clarify dropout parameters for `ResNet12`.

Fixed
-----

* Improved support for 1D inputs in `l2l.nn.KroneckerLinear`. (@timweiland)

v0.1.5

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Fixed
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* Fix setup.py for windows installs.

v0.1.4

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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
-------

* 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
-----

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

v0.1.2

======

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
-----

* 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
-------

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

Fixed
-----

* `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.