ReassuredTiger98

Can you explain what you meant by 

entropy point file?

There is no need to specify entry point file.
It is automatically detected when you run the Code manually on your machine.
My assumption was that the file "src/run_task.py" (based on your log) is just a test file, and hence was not added top the repository. So the agent failed to actually restore it from the git (files that are not added are not considered part of the git diff, this is usually git behavio...

Thanks ContemplativePuppy11 !

How would you pass data/args between one step of the pipeline to another ?
Or are you saying the pipeline class itself stores all the components ?

GreasyPenguin66 Nice !!!
Very cool setup, and kudos on making it work with multiple users!
Quick question, shouldn't the JUPYTERHUB_API_TOKEN env variable be enough to gain access to the server? Why did you need to add it to the 'nbserver-x.json' as well?

PleasantOwl46 any chance there are subprojects under the requested project?

does this mean that Task stores --args (and propagates these further through the code as CLI arguments) somewhere where i can get and manipulate them from my code?

Yes it changes the actual argparse object and pushes the new values in runtime, basically you args.parse() will return the values from the UI (backend)

Yes this is definitely the issue, the agent assume the docker user is "root".
Let me check something

I started a last one to confirm!

You mean a second run, just to make sure ?

😞 It's working as expected for me...
That said I tested on Linux & pip,
Any specific req to test with? from the log I see this is conda on windows, are you using the base conda env or a venv inside conda?

Hi RoundMosquito25
How did you spin the agent (whats the cmd line? is it in docker mode or venv mode?)
From the console it seems the pip installation inside the container (based on the log this is what I assume) seems like it is stuck ?!

Hi SubstantialElk6 I believe you just need to use clearml 1.0.5 , and make sure you rae passing the correct OS environment to the agent

Maybe it's the Azure upload that has a weird size bug?!

hmm, yes it should create the queue if it's missing (btw you could work around that and create it in the UI). Any chance you can open a github issue in the clearml helm chart repo so we do not forget ?

this topic is about the issue with reporting a configuration with a string inside a tuple that has backslash

So the encoding itself is done YAML style, and based on your example \b Has to be encoded to \b because this is string encoding, like \n will become "new line"
Make sense ?

Hi @<1797800418953138176:profile|ScrawnyCrocodile51>

Will the docker container / disk space (really I am more interested about the dataset that download by the task) get automatically clean up?

Yes, the agent is running the container with --rm 🙂

No, I think the default version already supports cuda 117

if they're mission critical, but rather the clearml cache folder?

hmmm... they are important, but only when starting the process. any specific suggestion ?
(and they are deleted after the Task is done, so they are temp)

Hurray!

LOL I see it now 🙂

Verified and fix, should be deployed soon in RC 🙂

Okay let me check

My internet traffic looks wierd.I think this is because tensorboard logs too much data on each batch and ClearML send it to server. How can i fix it? My training speed decreased by 5-6 times.

BTW: ComfortableShark77 the network is being sent in background process, it should not effect the processing time, no?

DeliciousBluewhale87 out of curiosity , what do you mean by "deployment functionality" ? is it model serving ?

HandsomeCrow5 Seems like the right place would be in the artifacts, as a summary of the experiment (as opposed to on going reporting), is that the case?
If it is then in the Artifacts tab clicking on the artifact should open another tab with your summary, which sounds like what you were looking for (with the exception of the preview thumbnail 🙂

In the main pipeline I want to work with the secondary pipeline and other functions decorated with 

PipelineDecorator

. Does ClearMl allow this? I have not been able to get it to work.

Usually when we think about pipelines or pipelines, the nested pipeline is just another Task you are running in the DAG (where the target queue is the services queue).
When you say nested pipelines with decorators, what exactly do you have in mind ?

DeliciousBluewhale87 and is it working?

Sure thing, and I agree it seems unlikely to be an issue 🙂

So how do I solve the problem? Should I just relaunch the agents? Because they can't execute jobs now

Are you running in docker mode ?
If so you can actually delete mapped files (they will still be available inside the docker), just make sure you delete them X hours after they were created, and you should be fine.
wdyt?

Worker just installs by name from pip, and it installs not my package!

Oh dear ...
Did you configure additional pip repositories in the Agent's clearml.conf ? https://github.com/allegroai/clearml-agent/blob/178af0dee84e22becb9eec8f81f343b9f2022630/docs/clearml.conf#L77 It might be that (1) is not enough, as pip will first try to search the package in the pip repository, and only then in the private one. To avoid that, in your code you can point directly to an https of your package` Ta...

Hmm that is odd.
Can you verify with the latest from GitHub?
Is this reproducible with the pipeline example code?

Hi @<1571308003204796416:profile|HollowPeacock58>
I'm assuming this is the arm support (i,e, you are running on new mac) fix we released in one one of the last clearml-agent versions. could you update to the latest clearml-agent?

pip3 install clearml-agent==1.6.0rc2