when i run this one clearml-agent --config-file ~/clearml-iris.conf it output the help info

I can comment it on the github issue

oh i see, i’m trying it now

i’m not sure if i use the command correctly

yes

yes, that’s the error i got

but the solution in the answer doesn’t help cause when i do reverse with -R the server couldn’t be brought up

Do you think the local agent will be supported someday in the future?

but basically i create it by init and rename it

i tried to add environment right before importing clearml, but it doesn’t work as expected
os.environ['CLEARML_CONFIG_FILE'] = str(Path.home()/f"clearml-{socket.getfqdn()}.conf") from clearml import Task Task.init(project_name="Alfred", task_name="finalized", auto_connect_frameworks={'pytorch': False})

I have two laptop, one is running ubuntu 20.04 and one is macos, both are running in my local network. I installed the server on ubuntu and ssh from mac to it to bring up the server then build up a tunnel using ssh -L

seems the not logging problem is back

No sure, here is the code

working very well actually

So what if i want three tasks running in parallel, should i Task.init in the main process and change the task name in the sub process?

and one experiment takes 40 hours to run, so i let them run in parallel

Or can I enable agent in this kind of local mode?

before i renamed it, i can log the experiment successfully, i basically add task.init to the python script then just run that script

i can only see the init log

Oh this is one line missing on the above code

yeah sure

btw, i’m running the code with multiprocessing, so the log is duplicated 3 times

Guess my best chance is to check out the agent source code right?

I tried from clearml.backend_api.session import client no luck

i tired to run trains-compose without -d to say the log,
trains-agent-services | trains_agent: ERROR: Connection Error: it seems api_server is misconfigured. Is this the TRAINS API server http://apiserver:8008 ?
trains-agent-services | http://192.5.53.86:8081 http://192.5.53.86:8080 http://apiserver:8008
I didn’t assign anything to TRAINS_HOST_IP, not sure if the apiserver:8008 caused the problem

is there any document for this?

Yes, i think trains might wrap the torch.load function, but the thing is that i need to load some part of the dataset using torch.load, so this error shows up many time during training, I found i can use this line:
task = Task.init(project_name="Alfred", task_name="trains_plot", auto_connect_frameworks={'pytorch': False})but does it mean i cannot monitor torch.load function any more?

How can I do to help extend it?