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I'm porting JAX code that I've been writing for research projects into more production-ready code in Pytorch. I want to use Pytorch Lightning to streamline the process but I'm not sure how well it accomodates with e.g. torch.vmap, torch.func.grad etc. Does it optimize through these operators correctly ? In particular I have some autoencoder where the encoder is a based on Langevin diffusion and Monte Carlo estimation.
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Hi all,
I'm porting JAX code that I've been writing for research projects into more production-ready code in Pytorch. I want to use Pytorch Lightning to streamline the process but I'm not sure how well it accomodates with e.g.
torch.vmap,torch.func.gradetc. Does it optimize through these operators correctly ? In particular I have some autoencoder where the encoder is a based on Langevin diffusion and Monte Carlo estimation.Thanks in advance!
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