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29 × Eureka!I ran into something similar, for me I'd actually cloned the repository using the address without the git@ (something made it work). ClearML read it from the remote repository URL and used it. When I updated the URL of the remote repository in my git client it then worked.
I realise I made a mistake and hadn't actually used connect_configuration !
I think the issue is the bandwidth yeah, for example when I doubled the number of CPUs (which doubles the allowed egress) the time taken to upload halved. It is puzzling because as you say it's not that much to upload.
For now I've whittled down the number of entries to a more select but useful few and that has solved the issue. If it crops up again I will try connect_configuration properly.
Thanks for ...
Hi CostlyOstrich36 thanks for the response and makes sense.
What sort of problems could happen, would it just be the corruption of the data that is being written or could it be more breaking?
For context, I’m currently backing up the server (spinning it down) every night but now need to run tasks over night and don’t want to have any missed logs/artifacts when the server is shutdown.
That said, maybe the connect dict is not the best solution for thousand key dictionary
Seems like it isn't haha!
What is the difference with connect_configuration ? The nice thing about it not being an artifact is that we can use the gui to see which hashes have changed (which admittedly when there are a few thousand is tricky anyway)
I think a note about the fileserver should be added to the https://clear.ml/docs/latest/docs/deploying_clearml/clearml_server_security page!
CumbersomeCormorant74 just to confirm in my case the file's aren't actually deleted - I have to manually delete them from the fileserver via a terminal
I've tracked down our messages when this occurred and I think we had a different error to you, sorry.
In case it helps our problem was when the below command was run in the repository:$ git remote -vReturned the https address rather than the ssh address.
Then clearml tried to convert this to the ssh address, which looked like<org>/<repo>/rather than:<org>/<repo>.git(Which is possible a separate bug?)
From my limited understanding of it, I think it's the client that does the saving and communicating to the fileserver not the server, whereas deletion is done by the GUI/server which I guess could have different permissions somehow?
Ah apologies for getting the wrong end of the stick a bit!
Not sure if it helps you or not, but when the link to an artifact didn't work for me it was because the URL being used was internal to the server (I had an agent that had access to internal endpoints). In my case setting the agent fileserver url to the public domain solved my issue.
When you generate new credentials in the GUI, it comes up with a section to copy and paste into either clearml-init or ~/clearml.conf . I want the files server displayed here to be a GCP address
I think you should open a github feature request since there is currently no way to do this via UI
Will do. Is there a way to do it no via the UI? E.g. in the server configuration (I'm running a self hosted server)?
OK that's great, thanks for the info SuccessfulKoala55 👍
Yep GCP. I wonder if it's something to do with Container-Opimized OS, which is how I'm running the agents
Shards that I can see are using a lot of disk space are
events-training_stats_scalarevents-log- And then various
worker_stats_*
And what is the difference in behaviour betweenTask.init(..., output_uri=True) and Task.init(..., output_uri=None) ?
And regarding the first question - Edit your
~/clearml.conf
That would change what file server is used by me locally or an agent yes, but I want to change what is shown by the GUI so that would need to be a setting on the server itself?
Ok, thanks Jake!
task.get_parameters and task.get_parameters_as_dict have the keyword argument cast which attempts to convert values back to their original type, but interestingly doesn't seem to work for properties:
` task = Task.init()
task.set_user_properties(x=5)
task.connect({"a":5})
task.get_parameters_as_dict(cast=True)
{'General': {'a': 5}, 'properties': {'x': '5'}} Hopefully would be a relatively easy extension of get_user_properties ` !
Maybe it was the load on the server? meaning dealing with multiple requests at the same time delayed the requests?!
Possibly but I think the server was fine as I could run the same task locally and it took a few seconds (rather than 75) to upload. The egress limit on the agent was 32 Gbps which seems much larger than what I though I was sending but I don't have a good idea of what that limit actually means in practice!
CostlyOstrich36 I use the GCP disk image to launch a Compute Engine instance which sits behind an HTTP load balancer
Is the GCP disk image released for it? I get access denied with this link: https://storage.googleapis.com/allegro-files/clearml-server/clearml-server-1-3-0.tar.gz
Cheers!
Thanks @<1523701087100473344:profile|SuccessfulKoala55> , I’ve taken a look and is this force merging you’re referring to? Do you know how often ES is configured to merge in clearml server?