Is it possible to get the folder with the artifacts/models? (edited)

You can directly get the artifacts/models url then deduce the folder
task = Task.get_task('my_task_id') print(task.artifacts['my artifact'].url)

LOL

Let me chech

. It is not possible to specify the full output destination right?

Correct 😞

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 ?

so it would be better just to use the original code files and the same conda env. if possible…

Hmm you can actually run your code in "agent mode" assuming you have everything else setup.
This basically means you set a few environment variables prior to launching the code:
Basically:
export CLEARML_TASK_ID=<The_task_id_to_run> export CLEARML_LOG_TASK_TO_BACKEND=1 export CLEARML_SIMULATE_REMOTE_TASK=1 python my_script_here.py

HighOtter69 inside the legend click on the color rectangle next to the series name, you can change the color of the series on the graph. This property is stored so it will always remember your color preferences (yes even logging from another machine 🙂 )

Basically it gives it direct access to the host, this is why it is considered less safe (access on other levels as well, like network)

DeliciousBluewhale87
You could also just upload the data (i.e do not call close). Then you will be able to change it later obviously, this will make in intractable.
BTW: the clearml-data stores delta changes, so if you only change a few files it will only store those.

Okay that actually makes sense, let me check I think I know what's going on

Hope you don’t mind linking to that repo

LOL 😄

btw: any specific reason to call current_task after you closed the main Task ?

Hi! I was wondering why ClearML recognize Scikit-learn scalers as Input Models...

Hi GiganticTurtle0
any joblib.load/save is logged by clearml (it cannot actually differentiate what it is used for ...)
You can of course disable it with Task.init(..., auto_connect_frameworks={'joblib': False})

Hi CurvedHedgehog15
Yes you are correct, plots are displayed side-by-side in the ui. The reason is that since they are very generic, it is very challenging to actually be able to merge / overlay two arbitrary plots.
I can see two options

1. To allow user to combine two plots in the ui (this way the responsibility is on the user to understand this is possible
2. Maybe add programmatic interface to more easily access the raw data?
   Wdyt?

now, I need to pass a variable to the Preprocess class

you mean for the construction ?

How did you add the args? Is it argparser? If so the help is automatically picked so you can see it in yhe UI. BTW, the ability to provide a list of options is a really cool feature to have, I'll make sure to pass ot to product 😀

Docker would recognise that image locally and just use it right? I won’t need to update that image often anyway

Correct 🙂

LOL can't wait to see that

Are you using zsh by any chance?

WickedGoat98 sorry, I missed the thread...

that the trains.conf has to be located on the node running the trains-agent.

Correct 🙂
The easiest way to check is to see if you can curl to the ip:port from the docker.
If you fail it is probably the wrong IP.
the IP you need to use is the IP of the machine running the docker-compose (not the IP of the docker inside that machine).
Make sense ?

I mean, can you install it with something like ?
pip install git+Basically the agent will install main repository, and any git submodules. But it cannot install multiple repositories, as the directory structure might be too much.
wdyt?

What's the trains-server version ?
You can see it if you go to the profile page

Sure thing, my pleasure 🙂

Hmm good question, I'm actually not sure if you can pass 24GB (this is not a limit on the GPU memory, this affects the memblock size, I think)

Yes, it's a bit confusing, the gist of it is that we wanted to have the ability to have diff configurations for diff buckets

that clearml-agent needs to be installed from system python mentioned anywhere in the docs, if not I suggest it gets added.

You are right, I will check and fix if not 🙂

Thank you so much for helping.

My pleasure

Yep, that would do it ...
You can disable it with:
Task.init(..., auto_connect_frameworks={'scikit': False})

Yep this will work. BTW check the new pipeline it might have a more flexible solution
https://github.com/allegroai/clearml/blob/master/examples/pipeline/full_custom_pipeline.py

Yes

IrritableOwl63 in the profile page, look at the bottom right corner