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?

How can I ensure that additional tasks aren’t created for a notebook unless I really want to?

TrickySheep9 are you saying two Tasks are created in the same notebook without you closing one of them ?
(Also, how is the git diff warning there with the latest clearml, I think there was some fix related to that)

Hi QuaintJellyfish58

like we want set using UI but limited option on dropdown list

You mean like limit the ability of users to choose specific values? (so they do not mess things up?)

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})

I'm having another problem now because I am using the OptunaOptimizer.

Hmm let me check a sec

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

One last thing make sure you spin the pod container with privileged mode, because the trains-agent docker will spin a sibling docker for your actual experiment.

I'm assuming some package imports absl (the TF define package) and that's the reason you see the TF defines). Does that make sense?

Task.init(..., output_uri='s3://...')

Yes 🙂 https://discuss.pytorch.org/t/shm-error-in-docker/22755
add either "--ipc=host" or "--shm-size= 8g " to the docker args (on the Task or globally in the clearml.conf extra_docker_args)
notice the 8g depends on the GPU

I created my own docker image with a newer python and the error disappeared

I'm not sure I understand how that solved it?!

It is for storing the predictions a trained model makes, so two different models do create slightly different images

That actually makes sense.
So how would you create exactly the same file (i.e. why do you need to manually control the upload folder, wouldn't creating a new unique folder suffice ?)

Thanks LethalDolphin75 ! ❤

This is awesome, thank you!

try:
None

docker_install_opencv_libs: true

I know there is a aux cfg with key value pairs but how can use it in the python code?

This is actually for helping to configure Triton services, you cannot (I think) easily access it from the code

Hi @<1529633468214939648:profile|CostlyElephant1>

Is it possible to get user ID of the current user

On the Task.data object itself there should be a filed named " user " that's the user ID of the owner (creator) of the Task.
You can filter based on this id with

Tasks.get_tasks(..., task_filter={'user': ["user-id-here"]})

wdyt?

Because submodules inside a git are basically a requirement for a git repo to run. Skipping over a few or selecting manually will break the agent. That said maybe shallow clone might be easier or faster. Regardless it should be an environment passed per Task. Feel free to add a GH issue request, if this is not a unique edge case we will add it

OddShrimp85 you can see the full configuration at the top of the Task log. What do you have there? Also what is the clearml python version?

How can I add additional information, e.g. debug samples, or scalar to the data to be shown in the UI?  Logger.current_logger() is not working

Yes 🙂
dataset.get_logger() to the rescue

WackyRabbit7 This is a json representation of the entire plot (basically how plotly sees it).
What you are after is:
full_json[0]['cells']['values']Which is a list of lists (row order) in the table

LazyLeopard18 nice. maybe we should add it in the FAQ / Install. Could you send the exact docker-compose you used and command line, I'll ask the guys to add it 🙂

could one also limit the number of CPU cores available?

If you are running in docker mode you can add:
--cpus=<value>see ref here: https://docs.docker.com/config/containers/resource_constraints/

Just add it to extra_docker_arguments :
https://github.com/allegroai/clearml-agent/blob/2cb452b1c21191f17635bcb6222fa8bfd82afe29/docs/clearml.conf#L142