Allow non-strict decoder checkpoint loading#62
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| Analyzer | Status | Updated (UTC) | Details |
|---|---|---|---|
| Python | Jun 1, 2026 10:56a.m. | Review ↗ |
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Co-authored-by: mkofler96 <18218171+mkofler96@users.noreply.github.com>
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[WIP] Update decoder load_state_dict calls to allow unexpected keys
Allow non-strict decoder checkpoint loading
Jun 1, 2026
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Pull request overview
This PR makes decoder checkpoint loading tolerant to extra/unexpected keys by passing strict=False to decoder.load_state_dict(...), aiming to prevent load failures when checkpoints contain additional entries.
Changes:
- Set
strict=Falsewhen loading decoder parameters inload_model_parameters(). - Set
strict=Falseon the primary decoder load path inload_trained_model(). - Set
strict=Falseon the fallback decoder load path inload_trained_model().
| data = torch.load(filename, map_location=device, weights_only=True) | ||
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| decoder.load_state_dict(data["model_state_dict"]) | ||
| decoder.load_state_dict(data["model_state_dict"], strict=False) |
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| try: | ||
| decoder.load_state_dict(data["model_state_dict"]) | ||
| decoder.load_state_dict(data["model_state_dict"], strict=False) | ||
| except RuntimeError: | ||
| state_dict = {} | ||
| for k, v in data["model_state_dict"].items(): |
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Checkpoint loading previously required an exact state-dict key match, causing failures when extra/unexpected keys were present. This change makes decoder checkpoint loading tolerant to such keys in both direct and fallback load paths.
Decoder load behavior
decoder.load_state_dict(...)to passstrict=Falsein:load_model_parameters()load_trained_model()primary loadload_trained_model()RuntimeError fallback load (aftermodule.prefix normalization)Scope
DeepSDFStruct/deep_sdf/workspace.pyOriginal prompt
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