Don't know whether I do something wrong. Locally it works, but when executed via queue I get:

` File "run_task.py", line 14, in <module>
main()
File "run_task.py", line 9, in main
printme = importlib.import_module("some_package.file_to_import").printme
File "/home/tim/.clearml/venvs-builds/3.7/lib/python3.7/importlib/init.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "<frozen importlib._bootstrap>", line 1006, in _gcd...

Thank you very much, gonna try that!

btw: why is agent.package_manager and agent attribute. Imo it does not make sense because conda can install pip packages, but pip cannot install conda packages which can lead to install failures, right?

Now I get:

ollecting package metadata (repodata.json): done
Solving environment: - 
Found conflicts! Looking for incompatible packages.
This can take several minutes.  Press CTRL-C to abort.
failed                                                                                                                                                                         
                                                                                                                            ...

So I just updated the env that clearml-agent created (and where pytorch cpu is installed) with my local environment.yml and now the correct version is installed, so most probably the `/tmp/conda_envaz1ne897.yml`` is the problem here

Same error 😕

@<1523701994743664640:profile|AppetizingMouse58> Thank you very much. I forgot the volume mapping.
So can I just add the config to the async_delete container and mirror the directory structure from github?

volumes:
    - /opt/clearml/config:/opt/clearml/config
    - /opt/clearml/logs:/var/log/clearml

It works! Thank you very much 🙂

Hi @<1523701087100473344:profile|SuccessfulKoala55> Thank you very much.
Is there some way to verify the server uses the correct configuration files? (E.g. see it in the logs/web ui). I Just tried it does not work.
At least I can see the async_delete service complains about a missing secret, so I can start debugging there. I am using the same config as for my agents, but somehow for async_delete it does not work...

And the files that I see on github are the default configuration of the server, even if I do not have these files in my installation, right?

It seems like this is a bug however or is something like this to be expected? There shouldn't be files that are not shown in the WebUI..?

It is now looking for conflicts.

You mean I should have opencv/ffmpeg available on the clearml-server machine?

AgitatedDove14 https://github.com/allegroai/clearml/pull/372

I guess this is the current way to do it: https://github.com/tensorflow/tensorboard/issues/39#issuecomment-568917607 so I would say: Yes, it supports gif.

Based on https://github.com/lanpa/tensorboardX/blob/34d1616c035faaa0f3f7c9d19cb8bb4425f19939/tensorboardX/summary.py#L355 I would guess that it is already encoded before added to the tensorboard summary.

pytorch.tensorboard is the same as tensorboardx https://github.com/pytorch/pytorch/blob/6d45d7a6c331ddb856ac34a76bcd3613aa05185b/torch/utils/tensorboard/summary.py#L461

Yea, tensorboardX is using moviepy.

The task already contains this

Thanks a lot. To summarize: To me clearml is a framework, but I would rather have it be a library.
Other than that I am very happy with clearml and it is probably my favorite machine learning related package of the last two years! 🙂 And thanks for taking so much time to talk to me!

I am still trying to solve the add_requirements + importlib combo. If I use detect_with_freeze I can not use add_requirements and if I use automatic code analysis it will not find all packages because of importlib .
For now I come to the conclusion, that keeping a requirements.txt and making clearml parse the requirements from there should be the most robust solution. Unfortunately, there seems to be no way to do this with Task.init .

Or alternatively I just saw that Task.create takes a requirements.txt as an argument. This would also be fine for me, however I am not sure whether I should use Task.create ?

AlertBlackbird30 Thanks for asking. Just take everything with I grain of salt I say, because I am also not sure whether I do machine learning the correct way 😄

I think you got the right idea. I actually do reinforcement learning (RL), so I have multiple RL-environments and RL-agents. However, while the code for the agents differs between the agents, the glue code is the same. So what I do is I call python run_experiment.py --agent http://myproject.agents.my ` _agent --environm...

But you can manually add them with Task.add_requirements, no?

In my opinion an ugly solution. I would have to keep track of which requirements are missing. Then I would rather just add all requirements manually.

name: core
channels:
  - pytorch
  - conda-forge
  - defaults
dependencies:
  - _libgcc_mutex=0.1
  - _openmp_mutex=4.5
  - blas=1.0
  - bzip2=1.0.8
  - ca-certificates=2020.12.5
  - certifi=2020.12.5
  - cudatoolkit=11.1.1
  - ffmpeg=4.3
  - freetype=2.10.4
  - gmp=6.2.1
  - gnutls=3.6.13
  - jpeg=9b
  - lame=3.100
  - lcms2=2.11
  - ld_impl_linux-64=2.33.1
  - libedit=3.1.20191231
  - libffi=3.3
  - libgcc-ng=9.3.0
  - libiconv=1.16
  - libpng=1.6.37
  - libstdcxx-ng=9.3.0
  - libtiff...

drwxr-xr-x 10 root root 4096 Jul 31  2020 .
drwxr-xr-x 14 root root 4096 Jul 31  2020 ..
drwxr-xr-x  2 root root 4096 Feb  4 13:52 bin
drwxr-xr-x  2 root root 4096 Jul 31  2020 etc
drwxr-xr-x  2 root root 4096 Jul 31  2020 games
drwxr-xr-x  2 root root 4096 Jul 31  2020 include
drwxr-xr-x  4 root root 4096 Feb  3 13:40 lib
lrwxrwxrwx  1 root root    9 Dez 10 14:29 man -> share/man
drwxr-xr-x  2 root root 4096 Jul 31  2020 sbin
drwxr-xr-x  7 root root 4096 Jul 31  2020 share
drwxr-xr-x  ...

Same error.

One question: Does clearml resolve the CUDA Version from driver or conda?

Okay. It works now. I don't know what went wrong before. Probably a user error 😅

sure.