Would be very cool if you could include this use case!

I totally think we should, any chance you can open an Issue, so this feature is not lost?

Quick update Nexus supports direct http upload, which means that as CostlyOstrich36 mentioned, just pointing to the Nexus http upload endpoint would work:
output_uri="http://<nexus>:<port>/repository/something/"See docs:
https://support.sonatype.com/hc/en-us/articles/115006744008-How-can-I-programmatically-upload-files-into-Nexus-3-

So it sounds as if for some reason calling Task.init inide a notebook on your jupyterhub is not detecting the notebook.
Is there anything special about the jupyterhub deployment ? how is it deployed ? is it password protected ? is this reproducible ?

Sure thing, my pleasure 🙂

If the manual execution (i.e. pycharm) was working it should have stored it on the Pipeline Task.

It completed after the max_job limit (10)

Yep this is optuna "testing the water"

DefeatedCrab47 If I remember correctly v1+ has their arguments coming from argparse .
Are you using this feature ? 2. How do you set the TB HParam ? Currently Trains does not support TB HParams, the reason is the set of HParams needs to match a single experiment. Is that your case?

The upload itself is in the background.
It should not take long to prepare the plot for sending. Are you experiencing a major delay ?

Error 101 : Inconsistent data encountered in document: document=Output, field=model

Okay this point to a migration issue from 0.17 to 1.0
First try to upgrade to 1.0 then to 1.0.2
(I would also upgrade a single apiserver instance, once it is done, then you can spin the rest)
Make sense ?

You can change it the CWD folder, if you put . in working dir it will be the root git repo, but you can do any subfolder, obviously you need to change the script path to match the folder, e.g. ./folder/script.py etc.

Yes, because when a container is executed, the agent creates a new venv and inherits from the system wide installed packages, but it cannot inherit or "understand" there is an existing venv, and where it is.

Hmm that is odd, but at least we have a workaround 🙂
What's the matplotlib backend ?

WickedElephant66 is this issue the same as this one?
https://clearml.slack.com/archives/CTK20V944/p1656537337804619?thread_ts=1656446563.854059&cid=CTK20V944

I'm not, not sure about WickedElephant66 / DefiantHippopotamus88

is that what you want to happen ?

. I’m using the default operation mode which uses kubectl run. Should I use templates and specify a service in there to be able to connect to the pods?

Ohh the default "kubectl run" does not support the "ports-mode" 😞

There’s a static number of pod which services are created for…

You got it! 🙂

DeliciousBluewhale87 basically any solution that is compliant with S3 protocol will work. An example:
output_uri=" :PORT/bucket/folder"Are you sure Nexus supports this protocol ?
I "think" nexus sits on top of a storage solution (like am object storage), meaning we can use the same storage solution Nexus is using.
Just to clarify we do not support the artifactory protocol Nexus provides for storing models/artifacts. But we do support it as a source for python packages used by the a...

If this is the case I would do:

` # Add the collector steps (i.e. the 10 Tasks
pipe.add_task(...
post_execute_callback=Collector.collect_me
)

pipe.start()
pipe.wait()
Collector.process_results(pipe) `wdyt?

integer

I wonder if using our own containers which should have most the deps will work better than a simpler container.

Why not, it's transparent, just run in --docker mode and provide a default docker image if the Task doesn't specify one.

Hi ColossalDeer61 ,

Xxx is the module where my main experiment script resides.

So I think there are two options,
Assuming you have a similar folder structure-main_folder
--package_folder
--script_folder
---script.py
Then if you set the "working directory" in the execution section to "." and the entry point to "script_folder/script.py", then your code could do:
from package_folder import ABC
2. After cloning the original experiment, you can edit the "installed packages", and ad...

Hi @<1523701066867150848:profile|JitteryCoyote63>

Hi, how does

agent.enable_git_ask_pass

works

basically it pushes the pass through stdin to git when it asks (it is a git feature)

DilapidatedDucks58

is there any way to post Slack alerts for the frozen experiments?

The latest RC should solve the PyTorch data loader, do you want to test it?
pip install clearml==0.17.5rc2

Exactly !

Hi @<1686547344096497664:profile|ContemplativeArcticwolf43>

In the 2nd 'Getting Started' tutorial,

Could you send a link to the specific notebook?

. But whenever a task is picked, it fails for the following

You mean after the Task.init call?

BattyLion34 is this running with an agent ?
What's the comparison with a previously working Task (in terms of python packages) ?

but DS in order for models to be uploaded,
you still have to set:

output_uri=True

in the

No, if you set the default_output_uri, there is no need to pass output_uri=True in the Task.init() 🙂
It is basically setting it for you, make sense ?

I am thinking about just installing this manually on the worker ...

If you install them system wide (i.e. with sudo) and add agent.package_manager.system_site_packages then they will always be available for you 🙂

And then also use 

priority_optional_packages: ["carla"]

This actually means that it will always try to install the package clara first, but if it fails, it will no raise an error.

BTW: this would be a good use case for dockers, just saying :w...

Let me check if we can reproduce it

Hi @<1603198134261911552:profile|ColossalReindeer77>

Hello! does anyone know how to do

HPO

when your parameters are in a

Hydra

Basically hydra parameters are overridden with "Hydra/param"
(this is equivalent to the "override" option of hydra in CLI)