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16 × Eureka!Thanks for the reply ! I am using the enterprise version, do you have a link to some docs for the autoscaler ? On the orchestration tab I can see AWS and GCP but not Azure. (also, I was previously able to see Clearml GPUs, but it looks like they're not available anymore ?)
Oh, wow for some reason I thought I read somewhere in the documentation that the sync was taking care of upload and finalize. Or maybe that was for the CLI ? Anyway that's what I was missing, thank you !
Great, thanks a lot for the help !
okay I'll look into it, thanks !
@<1537605940121964544:profile|EnthusiasticShrimp49> A follow up question about metrics - My pytorch (lightning) experiments are logging to tensorboard and ClearML is automatically picking this up and uploading scalars and debug_images. If I use the set_default_upload_destination
that you mentionned, would that still properly use my URI even though I am not calling Logger.current_logger().report_image
directly ?
Also, I reset than deleted ~80% of the experiment that I had 2 days ago...
No ! The way I delete those is like so:
Experiment view -> Reset (one or more) experiment -> expriment is now in draft
Archive experiment
Open archive -> Delete
I get no feedback at all from the operation, but I can see the experiments are no longer available on clearml
okay cool, I'm currently trying to migrate our stack to run from the git repository and using ClearML Datasets. I am still having an issue with relative imports in python, we were previously modifying PYTHONPATH
in the container, but now I need to modify it manually on the host. I saw there is some documentation about that here , but I'm not sure I understand that correctly since it do...
That's correct, I'm on the community server for now. What about for the SDK and CLI ? If they have their own credentials, can they also use clearml-data
and clearml.Dataset.get()
to access my dataset ?
It feels a bit off at the moment to have all the pipelines / tasks / datasets that we will use under "Anthony Courchesne's Workspace" (even though I saw I can rename it)
@<1523701070390366208:profile|CostlyOstrich36> Is there a way to migrate datasets and experiments to another workspace ?
I mean I'm hosting it myself, it's on app.clear.ml
also, I see that clearml-serving support pytorch, is there any chance for support for TensorRT ?
I made sure to delete them from the archived tab
okay ! Right now in my workflow, I have upload, finalize and publish all happening one after the other without extra logic. From my tests it also looks like I can use a finalized but unpublished dataset without any problem. Should I be handling this differently ?
Thanks, that is exactly the kind of info I was looking for ! If debug images are counting in the metrics quota that would explain how we reached the limit so quickly.
ah, okay that make sense, I'll look more into the difference between pro / enterprise. Thanks for the info !