Hi everyone, I am Princy Chahal currently studying Machine Learning at George Brown College, Toronto, Canada. I have been working with the Deepchem community since February 2022. During this time I have trained models using Deepchem and have also contributed pull requests to
deepchem related to the pytorch lightning usage with deepchem.
I am really excited to work on building out deepchem’s integration with pytorch lightning this summer.
Project: Deepchem - Pytorch Lightning
Pytorch Lightning provides a framework and functionalities for building and training
pytorch models. If integrated with deepchem, pytorch-lightning will reduce the workload of
implementing ML model functionalities for the deepchem library and will also enable useful
functionalities like distributed training, easy model configuration and experimentation.
Below are three specific aspects we would like to showcase through the pytorch-lightning
integration for deepchem:
- Multi-GPU training for current set of deepchem models compatible with the lightning
integration. The multi-GPU training would be done by building on top of the lightning
distributed training functionalities.
- Leveraging the lightning integration to showcase improvements in training. Two models
in which improvement can be showcased are the Protein Transformer model and the
MPNNMOdel (Message Passing Neural Network).
- Hydra config management to track model configuration and experiments easily with
the lightning integration.