cool!
Sometimes (<10%) we use two registrars with different task_names (in terms of ClearML) to display the same indicators but for different models that do different logic. And in such cases, we made two tb versions of / task and wrote in parallel.
And I wanted to know if it is possible here as well.
Of course, now I thought about the fact that maybe we need to write everything in one place, but with different names, but different metrics are used there. I'm not very well versed in ClearML yet and may just not be completely familiar with the functionality.
we made two tb versions of / task and wrote in parallel.
And I wanted to know if it is possible here as well.
Basically you will have different series (based on the TB log file) on the same graph so you can compare 🙂 all automatically
I thought about the fact that maybe we need to write everything in one place
It will be in the same place, under the main Task
Should work out of the box
Do you accidentally know if there are any plans for an implementation with the logger variable, so that in case of something it would be possible to write to different tables?
CheerfulGorilla72 what do you mean "an implementation with the logger variable" ? pytorch-lighting defaults to the TB logger, which clearml will automatically catch and log into the clearml-server, you can always add additional logs with clearml interface Logger.current_logger().report_???
What am I missing ?
It's all? 😯 🪄 😀
without assigning a logger variable?
Do you accidentally know if there are any plans for an implementation with the logger variable, so that in case of something it would be possible to write to different tables?
BTW: Basically just call Task.init(...) the rest is magic 🙂
Hi CheerfulGorilla72 ,
Sure there are:
https://github.com/allegroai/clearml/tree/master/examples/frameworks/pytorch-lightning