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[P] learn2learn: A PyTorch Meta Learning Library

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:​

​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!

submitted by /u/praat33k
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.