That was also my feeling! But I though that spawning the trains-agent from a conda env would isolate me from cuda drivers on the system

--- /data ---------- 48.4 GiB [##########] /elastic_7 1.8 GiB [ ] /shared 879.1 MiB [ ] /fileserver . 163.5 MiB [ ] /clearml_cache . 38.6 MiB [ ] /mongo 8.0 KiB [ ] /redis

BTW, is there any specific reason for not upgrading to clearml?

I just didn't have time so far 🙂

trains-agent-1: runs an experiment for a long time (>12h). Picks a new experiment on top of the long one running trains-agent-2: runs only one experiment at a time, normal trains-agent-3: runs only one experiment at a time, normalIn total: 4 experiments running for 3 agents

awesome! Unfortunately, calling artifact["foo"].get() gave me:
Could not retrieve a local copy of artifact foo, failed downloading file:///checkpoints/test_task/test_2.fgjeo3b9f5b44ca193a68011c62841bf/artifacts/foo/foo.json
It tries to get it from the local storage, but the json is stored in s3 (it does exists) and I did create both tasks specifying the correct output_uri (to s3)

from the ClearML UI

Thanks SuccessfulKoala55 😁

and in the logs:
`
agent.worker_name = worker1
agent.force_git_ssh_protocol = false
agent.python_binary =
agent.package_manager.type = pip
agent.package_manager.pip_version = ==20.2.3
agent.package_manager.system_site_packages = true
agent.package_manager.force_upgrade = false
agent.package_manager.conda_channels.0 = pytorch
agent.package_manager.conda_channels.1 = conda-forge
agent.package_manager.conda_channels.2 = defaults
agent.package_manager.torch_nightly = false
agent.venvs_dir = /...

I’m not too fond of many user configurations, it’s confusing.

100% agree, nevertheless, how much is too many? Currently, there are only two settings in the user preferences category, so one more wouldn’t hurt?

however, clearml is open source, nothing stops you from adding the code and sending a PR

I’d be super happy to contribute yes! Nevertheless, I am not sure where to start: clearml-server repo? clearml-web repo?

In the comparison the problem will be the same, right? If I choose last/min/max values, it won’t tell me the corresponding values for others metrics. I could switch to graphs, group by metric and look manually for the corresponding values, but that becomes quickly cumbersome as the number of experiments compared grow

super, thanks SuccessfulKoala55 !

I am looking for a way to gracefully stop the task (clean up artifacts, shutdown backend service) on the agent

I tested by installing flask in the default env -> which was installed in the ~/.local/lib/python3.6/site-packages folder. Then I created a venv with flag --system-site-packages . I activated the venv and flask was indeed available

Could you please share the stacktrace?

I was able to fix by applying for a license and registering it

Oof now I cannot start the second controller in the services queue on the same second machine, it fails with
` Processing /tmp/build/80754af9/cffi_1605538068321/work
ERROR: Could not install packages due to an EnvironmentError: [Errno 2] No such file or directory: '/tmp/build/80754af9/cffi_1605538068321/work'
clearml_agent: ERROR: Could not install task requirements!
Command '['/home/machine/.clearml/venvs-builds.1.3/3.6/bin/python', '-m', 'pip', '--disable-pip-version-check', 'install', '-r'...

Which commit corresponds to RC version? So far we tested with latest commit on master (9a7850b23d2b0e1f2098ab051de58ce806143fff)

I also would like to avoid any copy of these artifacts on s3 (to avoid double costs, since some folders might be big)

should I try to roll back to clearml-server 1.0.2? I am very anxious now…

Alright SuccessfulKoala55 I was able to make it work by downgrading clearml-agent to 0.17.2

AgitatedDove14 yes but I don't see in the docs how to attach it to the logger of the earlystopping handler

I guess I’ll get used to it 😄

Nice, thanks!

might be worth documenting 😄

Will it freeze/crash/break/stop the ongoing experiments?

AgitatedDove14 I am actually considering rolling back to 1.1.0, so 1.3.0 is not really an option for now

yes what happens in the case of the installation with pip wheels files?

When installed with http://get.docker.com , it works

as it's also based on pytorch-ignite!

I am not sure to understand, what is the link with pytorch-ignite?

We're in the brainstorming phase of what are the best approaches to integrate, we might pick your brain later on

Awesome, I'd be happy to help!

AnxiousSeal95 Any update on this topic? I am very excited to see where this can go 🤩