Comments (2)
jbegaint
commented on August 22, 2024
1
Hi, can you try setting torch.backends.cudnn.deterministic = True in your main script?
They were some updates in pytorch 1.8 that produces undeterministic behavior in some convolution ops. Usually the NaN are caused by the hyperprior decoding, the scales prediction need to be 100% reproducible otherwise the entropy decoding fails to decode the correct latent values.
A better solution would be to have a quantized hyperprior decoder for the scales. We'll release a model soon.
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MarineCao
commented on August 22, 2024
1
Thanks for your reply!
I set torch.backends.cudnn.deterministic = True, and it works.
Thanks!
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