Fix missing pretrained weight fallback#179
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Summary
Reimplements the behavior proposed in #125 against the current codebase.
When L2-SP regularization is configured but the pretrained weights directory does not contain weights for the selected model architecture,
get_regularization_loss()currently raisesKeyErrorbefore reaching its existing fallback path. This changes the lookup to treat a missing model/architecture as no pretrained file found, so the existing L2 fallback is used.Credit to @antortjim for the original report and fix idea in #125.
Testing
uv run pytest -q tests/test_losses.pyuv run pytest -q-> 29 passed, 5 deselectedSupersedes #125.