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Save log data on disk in addition to online logging
Dear Comet ML Team,
Thank you for offering such a great product. I am using it daily for my research and recommended it to my colleagues.
I am working on a cluster. Sometimes the internet gets disconnected for whatever reason. In this case it would be great to have a backup of the data while disconnected, instead of losing it completely. When trying to do a workaround by running online and offline simultaneously, the run will just end the other instance.
Describe the solution you'd like
A flag that enables saving the data on the local disk in addition to logging it to Comet ML online. e.g.
experiment = Experiment(save_to_dir="./comet")
by default save_to_dir=None won't save anything on the disk as currently.
After the run ended, being able to upload the saved data to the same run online.
Describe alternatives you've considered
Allow Experiment and OfflineExperiment run simultaneously as a workaround.
PS: I am working mostly with Pytorch Lightning, so an integration with Lightning would be great, though I guess it's not in your hands.
Thank you for the kind words @DeepOzean. Currently, we do not support running OfflineExperiment and Experiment simultaneously. Let me see if I can create a workaround for your use case. I will update you here if I make any progress.
Also, we do have an integration with Pytorch Lightning! Here is the documentation to help you get started. https://pytorch-lightning.readthedocs.io/en/latest/api/pytorch_lightning.loggers.comet.html
Please let me know if you have any more questions!
Hi Dhruv, is there an update on the workaround? Thanks again for your time!
I believe allowing Experiment and OfflineExperiment to run simultaneously will be helpful since sometimes I exceeded the rate limit so some experiments can't be logged correctly.
Comet now uses an offline fallback mechanism. For more information see: https://research.dev.comet.com/docs/v2/api-and-sdk/python-sdk/advanced/fallback-to-offline/