Can you post here the actual line? seems like we can fix it to also support this scenario (if we could test it)

reproduced with matplotlib 3.1

one of them has been named incorrectly and now I'm trying to remove it and it's not running anywhere,

Oh I see, meaning until it "times out".
You could search for it in the UI (based on the session ID) and abort/archive it

Hi DeliciousBluewhale87
When you say "workflow orchestration", do you mean like a pipeline automation ?

I would like to use ClearML together with Hydra multirun sweeps, but I’m having some difficulties with the configuration of tasks.

Hi SoreHorse95
In theory that should work out of the box, why do you need to manually create a Task (as opposed to just have Task.init call inside the code) ?

AstonishingWorm64
You can turn on the venv cache , it will just handle it's own full env caching 🙂
See here:
https://github.com/allegroai/clearml-agent/blob/4f7407084d1900a79d455570c573e60f40208742/docs/clearml.conf#L100

SteadyFox10 I suspect you are correct 🙂
CourageousLizard33 see also section (4) here:
https://github.com/allegroai/trains-server/blob/master/docs/install_linux_mac.md#launching-the-trains-server-docker-in-linux-or-macos

(or woman or in between, we are supportive as long as code is working 🙂 )

Hi @<1570583227918192640:profile|FloppySwallow46>

Hey I have a question, Can you monitor the time for one pipeline,

you mean to see the start / end time of the pipeline?
Click on the details link on the right hand side and you will have all the details on the pipeline task, including running time

Yes, that sounds like the issue, is the file actually there ?

I put two models in the same endpoint, then only one was running,

without providing version number, you are overriding the models (because this is the same endpoint)

I started another docker container having a different port number and then the curls with the new model endpoint (with the new port) started working

Seems like misconfiguration on the first one?

, which apparently I can't specify when I establish the model endpoint but I need to re compose the docker container by...

Hi FierceHamster54
Are you saying the pipeline component is a standalone script?
If this is the case then you are correct, it should not need to, I think you can specify it in the decorator.
I think this might work 🤞
@PipelineDecorator.component(..., repo=False)

Hmm yes, @<1570220858075516928:profile|SlipperySheep79> I think you are right in your case it make sense to do add this option.
Could you add GH issue with the feature request? it should be fairly easy to add and we use GH to make sure we track those requests
wdyt?

BTW: CloudyHamster42 I think this issue was discussed on GitHub, and the final "verdict" was we should have an option to split/combine graphs on the UI side (i.e. similar to the "smoothing" or wall-time axis etc.)

How would one do this? Do I just share a link to the experiment, like

See "Share" in the right click menu on the experiment

To store all the debug samples, also it can store all the models (if you configure the output_uri=' http://file_server_here:8081 ') Yes: instead of the file server have 's3://<ip_of_minio>:9000/bucket' make sure you add the credentials for the minio in the trains.conf Yes, basically once you have the creendtials in the trains.conf, you could do StorageManager.get_local_copy('s3://<minio>:9000/bucket/file') (also upload of course 🙂 )

Yey!

https://github.com/allegroai/trains/blob/master/docs/trains.conf#L47

Hi CheerfulGorilla72
the "installed packages" section is used as "requirements.txt for the agent.
Are you saying the autodetection fails to detect all packages? You can specify in "manual execution" (i.e not when the agent is running the code), to just take the requirements.txt locally:` Task.force_requirements_env_freeze(requirements_file="./requirements.txt")

notice the above call should be executed Before Task.init

task = Task.init(...) `3. If you clear all the "installed packages" se...

Hi RoughTiger69

One quirk I found was that even with this flag on, the agent decides to install whatever is in the requirements.txt

Whats the clearml-agent you are using?

I just noticed that even when I clear the list of installed packages in the UI, upon startup, clearml agent still picks up the requirements.txt (after checking out the code) and tries to install it.

It can also just skip the entire Python installation with:
CLEARML_AGENT_SKIP_PYTHON_ENV_INSTALL=1

(this is the part that is not in the background, so if the epoch is short it might have an effect)

Can you send the full log? This is odd, it will by default use the python executable it (the agent) is running with.
Regardless you can specify the python executable to be used here:
https://github.com/allegroai/clearml-agent/blob/bd411a19843fbb1e063b131e830a4515233bdf04/docs/clearml.conf#L44

Hi DeliciousKoala34

Happened when cloning and running a task on an agent on a different machine. I

sounds like torch internal issue, can you send the full log of the remote Task ?

My pleasure 💗

which was trained on jupyter notebook.

Hmm that might be the issue, it assumes a local script running, let me verify that

clearml_agent: ERROR: Can not run task without repository or literalscript in script.diff

This is odd ...

OutrageousSheep60 when you launch clearml-session it tells you the session ID (which is also a Task ID), can you look for it in the UI and check there is something in the repo/uncommitted-changes section ?

Hmm, what's the clearml-agent version ?

then when we triggered a inference deploy it failed

How would you control it? Is it based on a Task ? like a property "match python version" ?

🤔

I think there was an issue with the entire .ml domain name (at least for some dns providers)