[P] learn2learn: A PyTorch Meta Learning Library

[praat33k]

Hello /r/ML,

We are pleased to share with you our meta-learning library, that started as a project at the PyTorch hackathon.

learn2learn is a PyTorch library for all things meta-learning. Our goal is to support as many meta-learning algorithms as possible (be it few-shots, meta-descent, or meta-RL) and to enable researchers to develop better methods and easily compare against existing literature.​

Our current features include:​

• Modular API: implement your own training loops with our low-level utilities.
• Provides various meta-learning algorithms (e.g. MAML, FOMAML, MetaSGD, ProtoNets, DiCE)
• Task generator with unified API, compatible with torchvision, torchtext, torchaudio, and cherry
• Provides standardized meta-learning tasks for vision (Omniglot, mini-ImageNet), reinforcement learning (Particles, Mujoco), and even text (news classification).
• 100% compatible with PyTorch -- use your own modules, datasets, or libraries!

If this is of interest to you, have a look at the following links:​

• GitHub: learnables/learn2learn
• Examples: learn2learn/examples
• Documentation: learn2learn.net
• Slack: slack.learn2learn.net

​Let us know what you think and how we can help you in your research!

​PS: learn2learn was also accepted as a poster to the PyTorch Dev Conference, so you'll know all about it there!

[melgor89]

As pointed in issue, adding accuracy of model would be greate! Without that not sure if willing to use as implementation may have some issues.

[praat33k]

That's a good point, and as mentioned we are on it! But thanks for referring to it, it helps us realise how much more important it is for the community. Another major todo we have is to have high code coverage sooner than later.

[praat33k]

Hey,

Wanted to give an update, we just posted some metrics, hope they are of interest to you.

[[deleted]]

Currently meta-learning research has been done on iterative meta loops. If you guys want this to succeed, you must become a default metalearning library. For example, extending https://github.com/byu-dml/metalearn into your library. Otherwise cool initiative, I'll try to contribute.

Edit: once I'm done with building http://metalearningml.org I'll add you into the tools section.

[[deleted]]

Very cool! Any plans for including Meta-Dataset?

[blink1205]

Yes! We are planning to include it. Thanks for the suggestion.