PCC-pytorch

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Hey I first wanted to say that this is great work. I also wanted to point out that in the non-amortized curvature loss if you look at the shapes:

grad_z is [batchsize x latent_dim] grad_u is [batchsize x action_dim]

when I think in the paper grad_u should be [batchsize x latent_dim].

So, I think right now the way the curvature loss is formatted it is non-sensical dimensionally since if action_dim ≠ latent_dim or action_dim ≠ 1 then you'd get a dimension mismatch. Let me know if you have any questions.