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Now Tin and Tube are subclasses of torch.nn.Module and they can have learnable parameters in the form of values in Taichi fields. However, now these values cannot be optimized by PyTorch optimizers, since they are not PyTorch-compatible. One way to make them to be PyTorch-compatible is to use a proxy torch.nn.Parameter and sync the values of torch.nn.Parameter with those in the corresponding Taichi field.
If anyone come up with a better solution, discussions and PRs are always welcomed.
The text was updated successfully, but these errors were encountered:
Now
Tin
andTube
are subclasses oftorch.nn.Module
and they can have learnable parameters in the form of values in Taichi fields. However, now these values cannot be optimized by PyTorch optimizers, since they are not PyTorch-compatible. One way to make them to be PyTorch-compatible is to use a proxytorch.nn.Parameter
and sync the values oftorch.nn.Parameter
with those in the corresponding Taichi field.If anyone come up with a better solution, discussions and PRs are always welcomed.
The text was updated successfully, but these errors were encountered: