2. solves it. I did not know this is possible.

Do you know how I can get this version?

Well, I guess no hurdles vs. safety is inherently no solvable. I am all for hurdles, if it is clear how to overcome it. And in my opinion referring to clearml-init is something which makes sense from a developer and a user perspective.

Hey Martin, thank you for answering!
I see your point, however in my opinion this is really unexpected behavior. Sure, I can do some work to make it "safe", but shouldn't that be default. So throw an error without clearml.conf and expect CLEARML_USE_DEFAULT_SERVER=1 ` .

The current behavior is not fail safe.

Is this really working for you guys? I have no clue what's wrong. Seems so unlikely that my code works with artifacts, datasets, but not logging...

Log

Is this not something completely different?
This will just change the way to local repository is analyzed, but nothing about the agent.

Latest version for everything. I will message you again, if I encounter this problem again.

So I suppose there is a bug in ClearML.

One more thing: The cuda_version that clearml finds automatically is wrong.

Thank you, perfect! I did not try yet, but wil do now.

Thanks a lot. But even for a user, I can not set a default for all projects, right?

mytask.get_logger().current_logger().set_default_upload_destination(" s3://ip:9000/clearml ") this is what I do. Do you do the same?

AgitatedDove14 I have to problem that "debug samples" are not shown anymore after running many iterations. What's appropriate to use here: A colleague told me increasing task_log_buffer_capacity worked. Is this the right way? What is the difference to file_history_size ?

Haha, fortunately I have a good job already. Just wanted to know how many people are actively working on clearml.

Thank you very much!!!

Hi @<1523701070390366208:profile|CostlyOstrich36>
Thanks a lot. It seems there is no such option in clearml-data CLI, right?

Anyways, from my google search it seems that this is not something that is intuitive to fix.
Is there any progress on this: https://github.com/allegroai/clearml-agent/issues/45 ? This works on all my machines 🙂

Okay, thank you anyways. I was just asking because I thought I had seen such a setting before. Must have been something different.

# This file may be used to create an environment using:
# $ conda create --name <env> --file <this file>
# platform: linux-64
_libgcc_mutex=0.1=conda_forge
_openmp_mutex=4.5=1_llvm
absl-py=0.12.0=pypi_0
aiostream=0.4.2=pypi_0
attrs=20.3.0=pypi_0
blas=1.0=mkl
bzip2=1.0.8=h7b6447c_0
ca-certificates=2020.10.14=0
cached-property=1.5.2=pypi_0
cachetools=4.2.1=pypi_0
certifi=2020.6.20=py37_0
chardet=4.0.0=pypi_0
clearml=0.17.4=pypi_0
cloudpickle=1.6.0=py_0
cudatoolkit=11.1.1=h6406543_8
cycler...

Not for the logger, I just tested it.

So I have to specify it on every clearml-agent in the respective clearml.conf?

TRAINS_LOG_ENVIRONMENT=MYENVVAR works. Thank you!

Thank you. The reports feature is super cool! Greetings to the team. One of the best features for educational use!

Interesting. Will probably only matter for very small experiments or experiments, where validation is run very infrequently.

Ok. I just wanted to make sure I have configured my agent properly. Just want to make sure I have to set it on all agents.

When you say it is an SDK parameter this means that I only have to specify it on the computer where I start the task from, right? So an clearml-agent would read this parameter from the task itself.

Thank you very much, good to know!

For me this does not work (at least with nested tqdm bars, did not try single ones yet).