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We want to push changes to build Graphium 3.0, which will enable faster and more memory-efficient training and inference while also removing some of the codebase's "uglier" parts and version constraints. - Current constraints about `cuda-version=11.2` make the package not really usable. - The point above is due to `torchmetrics >=0.7.0,<0.11` constraint. That constraint needs to be relaxed, which requires to remove the file `ipu_metrics.py` and to change from functional metrics to class metrics. - Moving to a C++ molecular featurization for super-fast at-dataloading featurization of molecules. The caching will be optimized and only contain the labels. - Support for multi-gpu, and making sure the metrics and loss sync correctly across devices. - Standardizing `pre-nn` and `pre-nn-edges` to be part of the `MLPEncoder` and `EncoderManager` - Fix the issue with multiple node ordering coming from multiple tasks that require different orders (nodes, edges, etc.)
Overdue by 1 year(s)•Due by July 26, 2024•1/6 issues closedImprovements to the [muTransfer paper](https://www.microsoft.com/en-us/research/blog/%C2%B5transfer-a-technique-for-hyperparameter-tuning-of-enormous-neural-networks/).
No due date•2/3 issues closed