Lightning-AI / Lightning-AI/pytorch-lightning
Help PyG to support convertig homogenous LightningModule GNNs into heterogenous ones
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- Dominant language
- Python
- Stars
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- Avg merge
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Description
Description & Motivation
Currentlly it's not possible to use the internal to_hetero() conversion from PyG to turn a homogenous GNN into a heterogenous one, if the GNN is based on LightningModule .
If the PyG team decides it's worth supporting Lightning in that case, probably your help would be appreciated in that matter.
Pitch
No response
Alternatives
Provide an own wrapper utility to turn the GraphModule returned by PyG's to_hetero() back into a LightningModule.
Additional context
PyG issue: https://github.com/pyg-team/pytorch_geometric/issues/10653
cc @lantiga
Contributor guide
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 reading the linked PyG issue 10653 and the interaction between LightningModule-based GNNs and PyG's internal to_hetero() conversion. A complete contribution would need an agreed approach and documented support or wrapper behavior, with validation that homogeneous LightningModule GNNs can be converted to heterogeneous ones.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Quiet
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100