CHANGELOG.md

Changelog

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

[Unreleased]

Added

Changed

Fixed

v0.1.6

Added

• 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

Fixed

• Fix setup.py for windows installs.

v0.1.4

Added

• 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.

v0.1.3

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

• New example: Meta-World example with MAML-TRPO with it's own env wrapper. (@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.

Changed

Fixed

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

v0.1.1

Added

• 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

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

v0.1.0

Added

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

Changed

• 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

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