Yep can do 👍

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?

FrothyDog40 https://github.com/allegroai/clearml-docs/pull/235

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!

Yep GCP. I wonder if it's something to do with Container-Opimized OS, which is how I'm running the agents

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'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?)

OK that's great, thanks for the info SuccessfulKoala55 👍

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?

Thanks CumbersomeCormorant74

Ok, thanks Jake!

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)

https://github.com/allegroai/clearml/pull/737

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?

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.

Another option would be to do
task.close() task.reset()And then execute an agent to pick up that task, but I don’t think reset is part of the public API. Is this risky?

It seems to be an issue that a few people are having problems with: https://github.com/allegroai/clearml-server/issues/112

I think a note about the fileserver should be added to the https://clear.ml/docs/latest/docs/deploying_clearml/clearml_server_security page!

Yeah it's strange isn't it!

Hi CostlyOstrich36 , thanks for getting back to me!

I want to launch multiple tasks from one python process to be run by multiple agents simultaneously.

My current process for launching one task remotely is to use task.execute_remotely , and then I separately spin up a VM and execute a ClearML agent on that VM with the task ID.

Ideally, I would like to create multiple tasks in this way - so do Task.init(…) , set up some configuration, and then task.execute_remotely in a l...

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)?

Updating the server has solved the issue 👍

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 ` !

Tasks are running locally and recording to our self deployed server, no output in my task log that indicates an issue. This is all of the console output:

2023-01-09 12:53:22 ClearML Task: created new task id=7f94e231d8a04a8c9592026dea89463a ClearML results page: 2023-01-09 12:53:24 ClearML Monitor: GPU monitoring failed getting GPU reading, switching off GPU monitoringAre there any logs in the server I can check? The server is running v1.3.1 and the issue I’m see is with version 1....

Thanks for confirming, I can make a PR if that would be helpful?

CostlyOstrich36 thanks for getting back to me!

yes!

That's great! Please can you let me know how to do it/how to set the default files server?

However it would be advisable to also add the following argument to your code :

That's useful thanks, I didn't know about this kwarg

Perhaps linked to https://github.com/allegroai/clearml-server/issues/112 ?

Could well be the same as https://github.com/allegroai/clearml-server/issues/112 which is also discussed https://clearml.slack.com/archives/CTK20V944/p1648547056095859 🙂

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

Shards that I can see are using a lot of disk space are

• events-training_stats_scalar
• events-log
• And then various worker_stats_*