I mean what is the actual link?
File:// is a path to a file.
If your machine cannot access that path you get an error.
For example:
file:///home/user/file.bin
translates to /home/user/file.bin
If you do not have the file /home/user/file.bin on your machine you get an error.
GrievingTurkey78 make sense ?
Note that by default trains / clearml will not upload your weights file anywhere , only if you set "output_uri" to a specific location it will do that .

On all Agents

RobustSnake79 this one seems like scalar type graph + summary table, correct?
BTW: I'm not sure how to include the "Recommendation" part 🙂

VivaciousWalrus99
Yes this is odd:
1608392232071 spectralab:gpu0 DEBUG New python executable in /cs/usr/gal.hyams/.trains/venvs-builds/3.7/bin/python2So it thinks it has python v3.7 but it is using python2 in the venv...
In your trains.conf file, set agent.python_binary to the python3.7 binary. It should be something like:
agent.python_binary=/path/to/python/python3.7

RipeGoose2 That sounds familiar. Could you test with the latest RC?
pip install trains==0.16.4rc0

YEY 🙂

Hi RipeGoose2
So the http://app.community.clear.ml already contains it.
Next release of the standalone server (a.k.a clearml-server) will include it as well.
I think the ETA is end of the year (i.e. 2 weeks), but I'm not sure on the exact timeframe.
Sounds good ?

Hi SmoothSheep78
Do you need to import the previous state of the trains-server, or are you starting from scratch ?

SmugOx94 Yes, we just introduced it 🙂 with 0.16.3
Discussion was here (I'll make sure to update the issue that the version is out)
https://github.com/allegroai/trains/issues/222
In your trains.conf add the following line:
sdk.development.store_code_diff_from_remote = trueIt will store the diff from the remote HEAD instead of the local one.

Funny this was mentioned just today 🙂
https://clearml.slack.com/archives/CTK20V944/p1620664770492400

Basically if you want to always ignore the "installed packages" in your clearml.conf, put:
agent.package_manager.force_repo_requirements_txt = true

What happens when you call:

from clearml.backend_interface.task.repo import ScriptInfo

print(ScriptInfo._ScriptInfo__legacy_jupyter_notebook_server_json_parsing(None))

Hi @<1540142641931358208:profile|FancyBaldeagle86>
You mean in the UI? i.e. clone an experiment hover over the Configuration / Hyperparameter section and clicking edit ?

print(os.environ)

@<1523701079223570432:profile|ReassuredOwl55>

Hey, here’s a quickie – is it possible to specify different “types” of input parameters (“Args/…“) such that they are handled nicely on the front end?

You me cast / checked in the UI ?

. I'm thinking it's generically a kernel gateway issue, but I'm not sure if other platforms are using that yet

The odd thing is that you can access the notebook, but it returns zero kernels ..

what's the clearml package version and clearml-session version ?

Hi TroubledJellyfish71
What do you have listed on the Task's execution "installed packages" section ? (of the original Task) ?
How did it end up with an http link of pytorch ?
Usually it would be torch==1.11 ...
EDIT:
I'm assuming the original Task was executed on a Mac M1, what are you getting when calling pip freeze ?
And where is the agent running ? (and is it venv or docker mode?)

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 HappyDove3
task.set_script is a great way to add the info (assuming the .git is missing)
Are you running it using PyCharm? (If so use the clearml pycharm plugin, it basically passes the info from your local git to the remote machine via OS environment)

Oh that makes sense! I'll pass it to the documentation guys 🙏

Hi @<1523704667563888640:profile|CooperativeOtter46>

Is there a way to set the name/path of the

requirements.txt

file the agent uses to install packages?

When the agent is installing packages it takes it from the "Onstalled Packages" section of the Task. Only if it is empty it will revert to "requirements.txt" from the git repository

That said, if you can Add the following to your "Installed Pacakges"

-r my_other_requirements.txt

And the agent will `my_...

I'm trying to figure if this is reproducible...

WickedGoat98 what's the clearml version you are using?

potential sources of slow down in the training code

Is there one?

My pleasure 🙂

Wow, thank you very much. And how would I bind my code to task?

you mean the code that creates pipeline Tasks ?
(remember the pipeline itself is a Task in the system, basically if your pipeline code is a single script it will pack the entire thing )

I think that what you need is to create an OutputModel , then call update weights file when you have the better model, this will also allow you to tag the model object. Would that help? Or would it make sense to use Task.models and count on the auto logging?

I get what you're saying. Only problem is in the case of AutoLogging, I don't have the model id, for the model being saved.

Task.models['output'] should return all the model objects the autologging created

SparklingElephant70 , let me make sure I understand, the idea is to make sure the pipeline will launch a specific commit/branch, and that you can control it? Also are you using the pipeline add_step function or are you decorating a function with PipelineDecorator ?

It's in my local conda environment though.

Meaning this is a wheel installed manually in conda? or is it a folder inside the conda environment ?