pytorch-lightning

Congrats on the launch! This looks interesting, however I feel like this space is quite crowded. You mentioned that your most important feature is the fact that you are open-source, but off the top of my head I can think of several projects: * Kubeflow: https://github.com/kubeflow/kubeflow * MLFlow: https://github.com/mlflow/mlflow * Pachyderm: https://github.com/pachyderm/pachyderm * DVC: https://github.com/iterative/dvc * Polyaxon: https://github.com/polyaxon/polyaxon * Sacred: https://github.com/IDSIA/sacred * pytorch-lightning + grid: https://github.com/PyTorchLightning/pytorch-lightning * DeterminedAI: https://github.com/determined-ai/determined * Metaflow: https://github.com/Netflix/metaflow * Aim: https://github.com/aimhubio/aim * And so many more... In addition to this list, several other hosted platform offer experiments trackin

Hi William -- we have absolutely not copied any of Lightning's APIs. In fact, our PyTorch API makes some significantly different design choices than Lightning does -- e.g., we require users to step optimizers and run the backward pass explicitly, which is a bit lower-level but allows for more flexibility when using the API. For instance, here is an example of a GAN using our PyTorch API: https://github.com/determined-ai/determined/blob/master/exam... This is a port of this PyTorch Lightning example: https://github.com/PyTorchLightning/pytorch-lightning/blob/m... Despite the former being a port of the latter, there are significant differences between the two APIs. More broadly, we welcome competition in this space and think there's a lot that we can all learn from one another.

We currently have google engineers training on TPU pods with PyTorch Lightning. TPU support is VERY real... but yes, sometimes it breaks but PyTorch and Google are working very hard to bridge that gap. But we have dedicated partners at Google on the TPU team working to get Lightning working seamlessly on pods. Check out the discussions here: https://github.com/PyTorchLightning/pytorch-lightning/issues...

So this is the endgame of pytorch-lightning, which was always a mystery to me. (if you haven't used it, it's strongly recommended if you use PyTorch: https://github.com/PyTorchLightning/pytorch-lightning ) IMO, open source is at its best when it's supported by a SaaS as it provides a strong incentive to keep the project up-to-date, and the devs of PL have been very proactive.

Hi, great work! Have you heard of PyTorch Lightning (https://github.com/PyTorchLightning/pytorch-lightning) and there conference seed repo (https://github.com/PyTorchLightning/pytorch-lightning-confer...)? Maybe it would make sense to join forces.

Thanks for taking a look. 1) GPU acceleration and AWS VPC deployments are only available in the private beta (free tier is hosted on our private infrastructure). Apply here and we can set up a meeting with you asap: https://modelzoo.typeform.com/to/Y8U9Lw. 2) We've started with TensorFlow and Hugging Face Transformers. We're currently working on scikit-learn and PyTorch support (via https://github.com/PyTorchLightning/pytorch-lightning). What kind of frameworks do you use?