Yes including this. (There was a fix to an issue with trains-agent and disabling frameworks, it is already part of 0.16.3 )

Hi RipeGoose2
I think it "should" take of uploading the artifacts as well (they are included in the zip file created by the offline package)
Notice that the "default_output_uri" on the remote machine is meaningless as it stored them locally anyhow. It will only have an effect on the machine that actually imports the offline session.
Make sense ?

ShakyOstrich31

I am reusing an old task ...

Which means that the old Task stores the requirements on the Task itself (see "Installed Packages" section), Notice it also stores the exact git commit to use.
When you are cloning the Task (i.e. in the pipeline), you should probably:
set the commit / branch to the latest in the branch clear the "installed packages" section, which would cause the agent to use the "requirements.txt" stored in the git repo itself.As far as I understand this s...

So inside the pipeline logic you can do Task.current_task().id
Or inside a component Task.current_task().parent

Is this per Task or for all the Tasks always ?

Hi VexedCat68
Check this example:
https://github.com/allegroai/clearml/blob/4f9aaa69ed2d5b8ea68ebee5508610d0b1935d5f/examples/scheduler/trigger_example.py#L44

I am writing quite a bit of documentation on the topic of pipelines. I am happy to share the article here, once my questions are answered and we can make a pull request for the official documentation out of it.

Amazing please share once done, I will make sure we merge it into the docs!

Does this mean that within component or add_function_step I cannot use any code of my current directories code base, only code from external packages that are imported - unless I add my code with ...

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

,

remote_execute

kills the thread so the multirun stops at the first sub-task.

Hmm

task = Task.init(...)
# config some stuff
task.remote_execute(queue_name_here, exit_process=False)
# this means that the local execution will stop but when running on the remote agent it will be skipped
if Task.running_locally():
  return

Hmm okay let me check that, I think I understand the issue

Hi @<1624941407783358464:profile|GrievingTiger47>
I think you should try to contact the sales guys here: None

this results at the end of an experiment in an object to be saved under a given name regardless if it was dynamic or not?

Yes, at the end the name of the artifact is what it will be stored under (obviously if you reuse the name you basically overwrites the artifact)

Hi @<1523706645840924672:profile|VirtuousFish83>
Hmm so generally I think the answer is no... I mean you can download all scalars and re-report them with a different title/series, but I think you will not be able to delete a specific set, and the only way would be to reset the entire Task.
I'm curious what's the scenario here? is it like a typo you want to fix?

Hi ExasperatedCrocodile76
This is quite the hack, but doable 🙂
`
file_path = task.connect_configuration(name = 'augmentations', configuration = 'augmentations.py')

import importlib

module_name = 'augmentations'

spec = importlib.util.spec_from_file_location(module_name, file_path)
module = importlib.util.module_from_spec(spec)
spec.loader.exec_module(module) `
https://stackoverflow.com/a/54956419

Thanks! PR merged 🚀

Shouldn't this be a real value and not a template

you mean value being pulled to the pod that failed ?

@<1587253076522176512:profile|HollowPeacock33>
Is this a commercial ad? this seems like out of scope for this channel
Can you expand?

Hi SpicyLion54
the -f flag is not very stabe for pip (and cannot be added in requirements.txt). ClearML agent mwill automatically find the correct torch (from the torch repository) based on the cuda it detects in runtime.
This means it automatically translates torch==1.8.1 and will pull form the correct repo based on torch support table.

at the end it's just another env var

It should work GIT_SSH_COMMAND is used by pip

Hi SubstantialElk6
I can't see that is was removed, could you send the full log ?

Hi @<1529633468214939648:profile|CostlyElephant1>
what seems to be the issue? I could not locate anything in the log

"Environment setup completed successfully
Starting Task Execution:"

Do you mean it takes a long time to setup the environment inside the container?

CLEARML_AGENT_SKIP_PIP_VENV_INSTALL and CLEARML_AGENT_SKIP_PYTHON_ENV_INSTALL,

It seems to be working, as you can see no virtual environment is created, the only thing that is installed is the cleartml-agent that i...

@<1523722618576834560:profile|ShaggyElk85> nice !
I think that in theory you can run the DBs arm64 images no?

Notice that the actual configuration that is used is the https://github.com/allegroai/clearml/blob/b21e93272682af99fffc861224f38d65b42c2354/clearml/backend_config/bucket_config.py#L23
But it is created here:
https://github.com/allegroai/clearml/blob/b21e93272682af99fffc861224f38d65b42c2354/clearml/backend_config/bucket_config.py#L199

By the way, will downloading still happen if the datasets is available in the cache folder?

If it is cached, then there is no need to re-download 🙂

Happy new year @<1618780810947596288:profile|ExuberantLion50>

• Is this the right place to mention such bugs?Definitely the right place to discuss them, usually if verified we ask to also add in github for easier traceability / visibility

m (i.e. there's two plots shown side-by-side but they're actually both just the first experiment that was selected). This is happening across all experiments, all my workspaces, and all the browsers I've tried.

Can you share a screenshot? is this r...

This is so odd,
could you add prints right after the Task.init?
Also could you verify it still gets stuck with the latest RC

clearml==1.16.3rc2

Basically the links to the file server are saved in both mongo and elastic, so as long as these are host:ip based, at least in theory it should work

GreasyPenguin14 GrittyKangaroo27 the new release contains a fix, could you verify it solves the issue in your scenario as well (there is now a smart timeout to detect the inconsistent state, that means the close/exit procedure might be delayed (10sec) instead of hanging in these specific rare scenarios)

GreasyPenguin14 I think this is what you are looking for
Task.get_project_id('project_name')

quick update 1.0.2 will be ready in an hour, apologies 😞