crashmoon / MAML-Pytorch-Multi-GPUs

pytorch maml with Multi-GPUs, fast and simplest implementation

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MAML-Pytorch-Multi-GPUs

It is a reproduced version of maml, which is implemented with PyTorch 1.6.0 and support Multi-GPUs both in Meta-training phase and Meta-testing phase.

All the hyper-parameters and tricks, e.g. gradient clip, are strictly consistent with the original paper Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks HERE and its Tensorflow Implementation HERE.

Platform

  • python: 3.7
  • Pytorch: 1.6.0

Howto

  1. Downloading MiniImagenet dataset
  2. Changing dataset_dir in run_meta.py with your own root of the MiniImagenet dataset
  3. python run_meta.py

Comparison to original MAML implementation for miniImageNet

5-way 1-shot 5-way 5-shot
MAML 48.7% 63.1%
Ours 48.9% #TODO#

meta_loss

reference

https://github.com/cbfinn/maml

https://github.com/dragen1860/MAML-Pytorch

https://github.com/jik0730/MAML-in-pytorch

https://arxiv.org/abs/1703.03400

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pytorch maml with Multi-GPUs, fast and simplest implementation


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