Would it suffice to provide the git credentials ...

That should be enough, basically this is where they should be:
https://github.com/allegroai/clearml-agent/blob/0462af6a3d3ef6f2bc54fd08f0eb88f53a70724c/docs/clearml.conf#L18

SoggyBeetle95 is this secret a per Task secret, or is it for the agent itself (I.e. for all Tasks the agent will spin)?

Maybe the ~= is breaking the conda "magic" version resolver

seems like pip 20.1.1 has the issue, but >= 22.2.2 do not.

Notice we changed the value there, it now has two versions, pne for python 3.10 < and one for python 3.10>=
The main reason is that pip changed their resolving algorithm, and the new one can break its own dependencies (i.e. pip freeze > requirements.txt -> pip install might not actually work)
None

Can you see it on the console ?

I update my-private-dep to 1.8.0

Not sure how this is connected with the venv, could you expand ?

JitteryCoyote63 next week is the Trains next release with upgrade to ES 7, do you want to wait or sort a solution for this one ?
(BTW: I think that you can mount a license file or delete one, and it should be okay, I'll ask the backend guys regradless)

JitteryCoyote63 nice hack 😄
how come it is not automatically logged as console output ?

Hi DeterminedToad86
I just verified on a clean sagemaker instance everything should just work, see here: https://demoapp.demo.clear.ml/projects/0e919ea1cc5c499b99e1ab85004b6e97/experiments/887edef09d4549e88b829a34c87d4d5b/output/execution Yes if you have more than one file (either notebook or python script) than you must have a git repo, in order to run the task using the Agent.

It seems like the configuration is cached in a way even when you change the CLI parameters.

@<1523704461418041344:profile|EnormousCormorant39> nice!
Yes the configuration is cached so that after you set it once you can just call clearml-session again without all the arguments
What was the actual issue ? Should we add something to the printout?

. Is there any known issue with amazon sagemaker and ClearML

On the contrary it actually works better on Sagemaker...

Here is what I did on sage maker, created:
created a new sagemaker instance opened jupyter notebook Started a new notebook conda_python3 / conda_py3_pytorchIn then I just did "!pip install clearml" and Task.init
Is there any difference ?

I think I was not able to fully express my point. Let me try again.
When you are running the pipeline Fully locally (both logic and components) the assumption is this is for debugging purposes.
This means that the code of each component is locally available, could that be a reason?

Well it is there, do you have it in your docker-compose as well?
https://github.com/allegroai/trains-server/blob/master/docker-compose.yml#L55

@<1523701099620470784:profile|ElegantCoyote26> what's the target upload? also how come you are uploading a local file and auto deleting it, and then uploading the same one as artifact ?

I think poetry should somehow return error if toml is "empty" then we can detect it...

JitteryCoyote63 Is this an Ignite feature ? what is the expectation ? (I guess the ClearML Logger just inherits from the base ignite logger)

BTW: from the instance name it seems like it is a VM with preinstalled pytorch, why don't you add system site packages, so the venv will inherit all the preinstalled packages, it might also save some space 🙂
DeterminedToad86 see here:
https://github.com/allegroai/clearml-agent/blob/0462af6a3d3ef6f2bc54fd08f0eb88f53a70724c/docs/clearml.conf#L55
Change it on the agent's conf file to:
system_site_packages: true

Seems like a okay clearml.conf file
Notice this is the error:
404can you curl to this address ? are you sure you have httpS and not http ? was the dns configured ?

That was the idea behind the feature (and BTW any feedback on usability and debugging will be appreciated here, pipelines are notorious to debug 🙂 )

the ability to exexute without an agent i was just talking about thia functionality the other day in the community channel

What would be the use case ? (actually the infrastructure now supports it)

Thanks @<1523701868901961728:profile|ReassuredTiger98>
From the log this is what conda is installing, it should have worked

/tmp/conda_env1991w09m.yml:
channels:
- defaults
- conda-forge
- pytorch
dependencies:
- blas~=1.0
- bzip2~=1.0.8
- ca-certificates~=2020.10.14
- certifi~=2020.6.20
- cloudpickle~=1.6.0
- cudatoolkit~=11.1.1
- cycler~=0.10.0
- cytoolz~=0.11.0
- dask-core~=2021.2.0
- decorator~=4.4.2
- ffmpeg~=4.3
- freetype~=2.10.4
- gmp~=6.2.1
- gnutls~=3.6.13
- imageio~=2.9.0
-...

yes, I do, I added a

auxiliary_cfg

and I saw it immediately both in CLI and in the web ui

How many Tasks do you see in the UI in DevOps project with the system Tag SERVING-CONTROL-PLANE ?

TBH our Preprocess class has an import in it that points to a file that is not part of the preprocess.py so I have no idea how you think this can work.

ConvolutedSealion94 actually you can add an entire folder as preprocessing, including multiple files
See example des...

actually the issue is that the packages are not being detected 😞
what happens if you do the following?
Task.add_requirements("tensorflow") task = Task.init(...)

In venv mode yes, in docker mode you can pass them by setting the -e flag on the docker_extra_flags
https://github.com/allegroai/trains-agent/blob/121dec2a62022ddcbb0478ded467a7260cb60195/docs/trains.conf#L98

AntsyElk37

and when i try to use --output-uri i can't pass true because obviously i can't pass a boolean only strings

hmm, that sounds right, I think we should fix that so when using --output-uri true the value that is passed is actually True, not the string "true".
Regrading the issue itself:
are you saying --skip-task-init is being ignored ? and it always adds the Task.init call? you can also pass --output-uri https://files.clear.ml (which is the same as True) ,...

@<1595587997728772096:profile|MuddyRobin9> are you sure it was able to spin the EC2 instance ? which clearml version autoscaler are you running ?

What's the "working dir" ? (where in the repo the script is executed from)

Hmm that is odd, let me see if I can reproduce it.
What's the clearml version you are using ?

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 🙂

replace it with:
git+No need for the repository name, this will ensure you always reinstall it (again pip feature)

Woot woot, will do!