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CHANGELOG.md

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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

v0.2.1

Changed

  • Make qpth dependency optional.

v0.2.0

Added

  • New vision example: MAML++. (@Theo Morales)
  • Add tutorial: "Demystifying Task Transforms", (Varad Pimpalkhute)
  • Add l2l.nn.MetaModule and l2l.nn.ParameterTransform for parameter-efficient finetuning.
  • Add l2l.nn.freezeand l2l.nn.unfreeze.
  • Add Adapters and LoRA examples.
  • Add TasksetSampler, compatible with PyTorch's Dataloaders.

Changed

  • Documentation: uses mkdocstrings instead of pydoc-markdown.
  • Remove text/news_topic_classification.py example.
  • Rename TaskDataset to Taskset.

Fixed

  • MAML Toy example. (@Theo Morales)
  • Example for detach_module. (Nimish Sanghi)
  • Loading duplicate FGVC Aircraft images.
  • Move vision datasets to Zenodo. (mini-ImageNet, tiered-ImageNet, FC100, CIFAR-FS, CUB200)
  • mini-ImageNet targets are now ints (not np.float64).
  • Swap family for variants in FGVCAircraft, as in MetaDataset.

v0.1.7

Added

  • 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)

Changed

Fixed

  • Fix arguments when instantiating l2l.nn.Scale.
  • Fix train_loss logging in LightningModule implementations with PyTorch-Lightning 1.5.
  • Fix RandomClassRotation (#283) to incorporate multi-channelled inputs. (Varad Pimpalkhute)
  • 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) (Kevin Zhang)

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.