namely, I'm very interested in testing this unmerged feature, will be trying to leverage it as soon as possible
None

credentials for the server to do things with s3 will be in /opt/clearml/apiserver.conf.

Might be under examples

oh i see. you're talking about the agent-services, not a separate agent in a container.
yup, I've got the same thing going there.
fwiw...
for me, HOST_IP is 0.0.0.0 and the other "HOSTS" env vars don't contain "http" in them.
and my server is publicly reachable, not sure if that matter either.

you could also take the route of NOT specifying num_layers, and instead write your own code to create a set of viable layer designs to choose from and pass that as a parameter, so optuna selects from a countable set instead of suggesting integer values .

the downside of this is the lack of gradient information in the optimization process

I believe pipe.connect_configuration is what you're looking for?

I think you’d have to run the cleanup service. That’s what seems to be what is controlling deletion based on archived status and some other temporal filters

I tried mounting a config file (in the structure of the one on github but with just the relevant s3 section) into the agent-services container at /root/clearml.conf and after restarting the container, it seems to have had an impact. thank you!

When I inspect the console of the task I'm trying to run, I see there's a call to cp /tmp/clearml.conf ~/default_clearml.conf in the docker command and that the volume /tmp/clearml.conf is picked up from the host at some custom-named file ...

@<1541954607595393024:profile|BattyCrocodile47> put together None

you can put task.execute_remotely() to create it in draft mode. I've taken to configuring defaults to run things very quickly just in case i forget though (e.g. placeholder string for dataset, bail out early if not changed… or just do one epoch on a small subset of samples, etc).

Yup if you scroll through the logs in the console, near the top (post config dump), you’ll see a git clone and checkout to the specific hash.

PS You can actually change this parameter in an experiment’s configuration if it is in draft mode.

For reproducibility, it kind of makes sense though. The existence of the file is contingent on the worker cloning the source code. I'm sure things can be done to maintain state differently but I personally adapted to the git-based workflow for managing files pretty quickly.

though yes I will admit I had the same thought first: why must I run it each time?

Beware: squash merges will ruin the ability to reproduce the experiment at that time since the git commit will be lost (presuming th...

I'm guessing this is done through code-server?

I'm currently rolling a JupyterHub instance (multiuser, with codeserver inside) on the same machine as clearml-server. That’s where tasks are executed etc. so, all browser dev env.

It sounds like there’s an option to basically bypass this latter step and just use clearml’s credentialing to accomplish much the same thing? Am I understanding clearml-session correctly?

i think we may have found the frankenbug?

the argument to the dataset name was not being overridden correctly (mistyped), so the default value of an empty string (instead of a placeholder like "CHANGE_ME") in the parent task caused the dataset to basically get created with an empty name, and somehow that hid the whole project, despite hundreds of existing tasks in it.

and no way to un-hide it as far as I can tell?

didnt disappear this time.

the clearml github, search for a file named cleanup service dot py (or something to that effect)

I ran into something similar during deployment. Hopefully this helps with your debugging: if the agent was launched separately from the rest of the stack, it may not have proper docker-DNS resolution to None . (e.g. if in the same docker-compose, perhaps you didnt add the backend network field, or if it was launched separately through docker run without an explicit external network defined)

if the agent's on the same machine, try docker network connect to add...

youre basically asking to sample from a distribution where not all parameters are mutually independent .

the short answer is no- this is not directly supported . optuna needs each hyperparam to be independent, so its up to you to handle the dependencies between parameters yourself unfortunately .

your solution of defining them independently and then using num_layers to potentially ignore other parameters is a valid one .

maybe an important note: I mounted the same cache directory for the agents.

👀 following.
I have much the same issue, and it's mission-critical that I resolve it soon.

thank you!
I'll add a volume mount to the services-agent container, and from what I understand that will become the template it uses?

is this the structure of the file?
None

or is it the "dot" syntax (like what shows up in the console when the task executes / your snippet)?

probably, but the syntax would be in that of a git diff, so it’d be a touch clunky if you asked me
Are you trying to avoid local development?

ah, thank you for the clarity. A quarterly release schedule makes sense, it's about what I've observed.
Let me know if I can be of any assistance in early testing!

If you can hit the endpoint with curl, you for sure can hook it up to many frontend frameworks.

Personal recs: gradio, streamlit

Abstract the interaction into a function call, and wrap it all in some UI elements using python.

and now its gone.

i will attempt to start that now.

Weird . I recently implemented a function that talked to this exact endpoint and found it had to exclude the version and api paths . Is there some sort of redirect that happens?

Can vouch, this works well. Had my server hard reboot (maybe bc of clearml? maybe bc of hardware, maybe both… haven’t figured it out), and busy remote workers still managed to update the backend once it came back up.

Re: backups… what would happen if zipped while running but no work was being performed? Still an issue potentially?

and what happens if docker compose down is run while there’s work in the services queue? Will it be restored? What are the implications if a backup is perform...

one note is that it happened after I tried deploying a set of workers to a new queue, which she tried to use to run the tasks in parallel instead of our default queue which is only serviced by one worker (a container i built)

but isnt that just the same as running agent in daemon mode? thats what i was hoping James could do