PyTorch-MAML
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fmu2
A PyTorch implementation of Model Agnostic Meta-Learning (MAML) that faithfully reproduces the results from the original paper.
Hi Fangzhou, Thank you for your excellent work. The codebase is well-organized and easy to follow. When I tried to train `mini-imagenet` using either 2 - 8 GPUs by the...
when i set the encoder_args: bn_args: track_running_stats: True the train will not converge?
May i ask what's your format of CUB200 csv file and how to get the csv file ? Thanks
Hi, I think bringing up the inductive bias of MAML method is very interesting. How exactly could we get the results of MAML in the inductive setting using your implementation?...
Hi. Thanks for publishing this. I have always had a really hard time reproducing the results of the MAML paper and I have to get to the bottom of it...
Hi, do you have any MAML checkpoints that do get the 63% acc the original paper got?
I saw other implementations loading images from the train/val/test folders as the preprocessing step. https://github.com/yaoyao-liu/mini-imagenet-tools I am just curious if using pickle to load the data all at once is...
