starting to think that going back to your settatrr approach might be better X’D…

  
    
    
    Implement a meta-trainable step size 
  
  
    I want to implement a (meta) trainable step size. I tried it with this post: 


and with the higher library (https://github.com/facebookresearch/higher) with no luck… 
I tried: 
eta = torch.tensor([0.5], requires_grad=True).view(1)
inner_opt = torch.optim.Adam(child_model.parameters(), lr=eta)
#meta_params = itertools.chain(child_model.parameters(),eta.parameters())
meta_params = itertools.chain(child_model.parameters())
meta_opt = torch.optim.Adam(meta_params, lr=1e-3)
# do meta-training/outer …