updating core/ml models #131
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…t cache the activation function
…verting back to previous implementation
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Heads-up: you'll need to pull dev into the PR to enable the updated automated checks. |
cedriclim1
approved these changes
Jan 20, 2026
gvarnavi
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Jan 20, 2026
| dev = torch.device( | ||
| "cuda" if torch.cuda.is_available() else "mps" if torch.mps.is_available() else "cpu" | ||
| ) | ||
| elif isinstance(dev, str) and dev.lower() == "gpu": |
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@arthurmccray @cedriclim1 Why did we drop device='gpu' support?
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ah shoot, that's a mistake! Didn't realize that wasn't in the tutorial notebook that i had used for testing. I'll make a hotfix branch and fix that along with adding a proper pytest so it can't happen again.
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This PR expands on the neural networks included in /core/ml, and generally cleans up that code with docstrings, linter fixes, etc. This is also associated with updated tutorial notebooks in draft PR at quantem-tutorials and which will be pulled into main there when done.
In general this adds some new models and refactors a few things, but I think everything should backwards-compatible and non-breaking. I also removed the
Finermodel because I think we are wanting folks to useHSirenfor INRs in general.