Error to loading pre-trained model with torchsparse backend
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Description
Error
RuntimeError: Error(s) in loading state_dict for SLatMeshDecoder:
Missing key(s) in state_dict: "upsample.0.out_layers.0.conv.kernel", "upsample.0.out_layers.3.conv.kernel", "upsample.0.skip_connection.conv.kernel", "upsample.1.out_layers.0.conv.kernel", "upsample.1.out_layers.3.conv.kernel", "upsample.1.skip_connection.conv.kernel".
Unexpected key(s) in state_dict: "upsample.0.out_layers.0.conv.weight", "upsample.0.out_layers.3.conv.weight", "upsample.0.skip_connection.conv.weight", "upsample.1.out_layers.0.conv.weight", "upsample.1.out_layers.3.conv.weight", "upsample.1.skip_connection.conv.weight".
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reproducing the pretrained-model load with the torchsparse backend and inspect the SLatMeshDecoder state_dict mismatch. Trace where the checkpoint and decoder define the listed kernel and weight keys. Done means the model loads without the reported missing and unexpected-key errors.
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Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100