pytorch-lightning

One thing that makes me wonder is that there are 4 security issues raised and all of them were automatically commented and closed by some bot called `pl-ghost` [1][2][3][4]. In the end, only this one [4] properly handled, and all bot comments are deleted. You can see the bot comments in another report [5], which is more informative than the OP one. [1] https://github.com/Lightning-AI/pytorch-lightning/issues/216... [2] https://github.com/Lightning-AI/pytorch-lightning/issues/216... [3] https://github.com/Lightning-AI/pytorch-lightning/issues/216... [4] https://github.com/Lightning-AI/pytorch-lightning/issues/216... [5] https://socket.dev/blog/lightning-pypi-package-compromised

On GitHub, I saw this message from April 20, and I’m a bit confused. "deependujha hi @thebaptiste, thanks for inquiring. Release of 2.6.2 is blocked due to some internal reasons. Will notify once release is made. " I'd hate it if they knew of the problem that long ago and didn't warn until now. If someone has more info and can clarify I'd be thankful. https://github.com/Lightning-AI/pytorch-lightning/issues/216...

Thanks to the community for reporting the security issues with PyTorch Lightning 2.6.2 and 2.6.3 - we're actively looking into it. In the meantime, please use 2.6.1 until we publish 2.6.4. For more details: https://github.com/Lightning-AI/pytorch-lightning/security/a...

Advisory, fresh from the owen https://github.com/Lightning-AI/pytorch-lightning/security/a...

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?

It’s not that they don’t know how to be engineers, it’s that politically they all want to own their “thing” in TF. This type of exchange is pretty much what happens all the time: https://github.com/williamFalcon/pytorch-lightning/issues/35 There is no reason why two things can’t be merged together for better UX and functionality, but two humans have egos, want to lead projects, and be in charge, so things remain separate.

I suppose the reason why PyTorch doesn't implement this boiler plate for you is due to all of these quirky edge cases :) I think Pytorch Lightning might be worth taking a look at: https://github.com/williamFalcon/pytorch-lightning