Hi SkinnyPanda43
Are you trying to access the same Task or an external one ?

Sure set os environment 'CLEARML_NO_DEFAULT_SERVER=1`

When is clearml-deploy coming to the open source release?

Currently available under clearml-serving (more features are being worked on, i.e. additional stats and backends)
https://github.com/allegroai/clearml-serving

And command is a list instead of a single str

"command list", you mean the command argument ?

if executed remotely...

You mean cloning the local execution, sending to the agent, then when running on the agent the Args/command is updated to a list ?

Just to make sure I understand, running locally creates the Args/command correctly, then when actually executed on the remote machine (i.e. execute_remotely creates the correct Args/command But when the agent actually executes it) it updates back the Args/command as a list. Is that a correct description ?

ElegantKangaroo44 what do you think?

MysteriousBee56 yes, please change the trains code!!! Wee pee, if you think someone else can benefit, feel free to PR :)
Regrading the double entry, that seems like an odd bug, how can I reproduce it?

Hi PompousBeetle71
Could you test the latest RC, I think the warning were fixed:
pip install trains==0.16.2rc0Let me know...

Hi AstonishingSwan80 , what do you mean by "ec2 API"?

Thanks DilapidatedDucks58 ! We ❤ suggestions for improvements 🙂

Did you try to print a page using the browser (I think that they can all store it as pdf these days) Yes I agree, it would 🙂 we have some thoughts on creating plugins for the system, I think this could be a good use-case. Wait a week or two ;)

And what is exactly missing from the "installed packages" ? Is "help_models" an additional wheel you have to install ?
Just making sure here, but remember that if your original code did not have a git repo, the only thing that is "copied" to the trains-server is the initial script, so any accompanying scripts will be missing in the trains-agent environment

Hmm, and when you zoom out, still cropped ?

PlainSquid19 Trains will analyze the entire repository if this is a git repo code, and a single script file if there is no repository found.

It will not analyze an entire folder if it is not in a git repository, because it will not be able to recreate this folder anyhow. Make sense ?

MysteriousBee56 I would do Task.create()
you can get the full Task internal representation with task.data
Then call task._edit(script={'repo': ...}) to edit/update all the Task entries.
You can check the dull details of the task object here: https://github.com/allegroai/trains/blob/master/trains/backend_api/services/v2_8/tasks.py#L954
BTW: when you have a sample script working, consider PR-ing it, I'm sure it will be useful for others 🙂 (also a great way to get us involved with debuggin...

With pleasure

Check here:
https://github.com/allegroai/trains/blob/master/docs/trains.conf#L78

You can configure credentials based on the bucket name. Should work for Azure as well

Also there was a truck that worked in the previous big, could you zoom out in the browser, and see if you suddenly get the plot?

Hi WackyRabbit7 ,
Regrading git credentials, see here in the trains.conf https://github.com/allegroai/trains-agent/blob/master/docs/trains.conf#L18

Trains assumes one of two (almost three) possible setups
Your code/script is in a git repository. Then when executing manually all the git references incl` uncommitted changes are stored. Then when executing with the trains-agent, it will clone the code based on these references apply the uncommitted changes and run your code. To do that the ...

This is odd because the screen grab point to CUDA 10.2 ...

OddAlligator72 sure thing 🙂
This should sort it out:
Task.init('examples', 'train', continue_last_task=True)If you want to continue a specific Task:
continue_last_task='task_id_here'Getting the previous model:
last_checkopoint = task.models['output'][-1]What do you think?

I was unable to reproduce, but I added a few safety checks. I'll make sure they are available on the master in a few minutes, could maybe rerun after?

🤞

LazyLeopard18 nice. maybe we should add it in the FAQ / Install. Could you send the exact docker-compose you used and command line, I'll ask the guys to add it 🙂

Hmm I see what you mean. It is on the roadmap (ETA the next version 0.17, 0.16 is due in a week or so) to add multiple models per Task so it is easier to see the connections in the UI. I'm assuming this will solve the problem?

StaleKangaroo85 check https://demoapp.trains.allegro.ai/projects/0e152d03acf94ae4bb1f3787e293a9f5/experiments/193ac2bced184c49a57658fceb4bd7f9/info-output/metrics/plots?columns=type&columns=name&columns=status&columns=project.name&columns=user.name&columns=started&columns=last_update&columns=last_iteration&order=last_update on the demo server, seems okay to me...

Hi TrickyRaccoon92
BTW: checkout the HP optimization example, it might make things even easier 🙂 https://github.com/allegroai/trains/blob/master/examples/optimization/hyper-parameter-optimization/hyper_parameter_optimizer.py

Hi PompousParrot44
Well this kind of control is tricky. If you don't mind processes "fighting over cpu" you can just spin two trains-agents in cpu-mode. It will work as long as they have a different TRAINS_WORKER_NAME
The other option (might be a bit of an overkill) is to use K8s, which will set the CPU % for the entire agent.
What do you think?

CloudyHamster42 what's the trains-server version ?

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