And the one with the CPU version? is it with "~=" or "="?
btw: I also tested the clearml-agent running on a different machine and with python 3.8 and I get the same problems.
==> 2021-03-11 12:50:38 <==
# cmd: /home/tim/miniconda3/condabin/conda create --yes --mkdir --prefix /home/tim/.clearml/venvs-builds/3.8 python=3.8
--
==> 2021-03-11 12:50:40 <==
# cmd: /home/tim/miniconda3/condabin/conda install -p /home/tim/.clearml/venvs-builds/3.8 -c defaults -c conda-forge -c pytorch cudatoolkit=11.0 --quiet --json
--
==> 2021-03-11 12:50:43 <==
# cmd: /home/tim/miniconda3/condabin/conda install -p /home/tim/.clearml/venvs-builds/3.8 -c defaults -c conda-forge -c pytorch pip<20.2 --quiet --json
--
==> 2021-03-11 12:51:17 <==
# cmd: /home/tim/miniconda3/bin/conda-env update -p /home/tim/.clearml/venvs-builds/3.8 --file /tmp/conda_envaz1ne897.yml --quiet --json
@<1523701868901961728:profile|ReassuredTiger98> it works on my machine 😞
@<1523701868901961728:profile|ReassuredTiger98> what are you getting with:
nvidia-smi
And here:
ls -la /usr/local/
The problem is that clearml installsÂ
cudatoolkit=11.0
 butÂ
cudatoolkit=11.1
 is needed.
You suggested this fix earlier, but I am not sure why it didnt work then.
Hmm , could you test with the clearml-agent 0.17.2 ? making surethis actually solves the problem
Do you know how I can get this version?
Hi @<1523701868901961728:profile|ReassuredTiger98> when you get to it...
please download the wheel, then install it with
pip3 install -U clearml_agent-0.17.3rc0-py3-none-any.whl
Then run the daemon with the additional --debug argument, basically:
clearml-agent --debug daemon --foreground ...
Once the agent is running please send the Task's log from your console 🙂
Okay found it 🙂 it returns 11020 instead of 112
You suggested this fix earlier, but I am not sure why it didnt work then.
Thu Mar 11 17:52:45 2021
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 460.56 Driver Version: 460.56 CUDA Version: 11.2 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 GeForce RTX 3090 Off | 00000000:01:00.0 Off | N/A |
| 61% 63C P2 296W / 350W | 8318MiB / 24268MiB | 74% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 1 GeForce RTX 3090 Off | 00000000:21:00.0 Off | N/A |
| 30% 29C P8 20W / 350W | 1MiB / 24268MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| 0 N/A N/A 133165 C+G ...s-builds.1/3.7/bin/python 8314MiB |
+-----------------------------------------------------------------------------+
I mean the version which it bases the PyTorch installation on.
I just tried to envrionment setup steps that clearml-agent is doing locally, but with my environment.yml instead of the one that clearml generates.
channels:
- pytorch
- conda-forge
- defaults
dependencies:
- cudatoolkit~=11.1.1
- pytorch~=1.8.0
Works fine
Type "help", "copyright", "credits" or "license" for more information.
>>> from clearml_agent.helper.gpu.gpustat import get_driver_cuda_version
>>> get_driver_cuda_version()
'110'
Hurray conda.
Notice it does include cudatoolkit , but conda ignores it
cudatoolkit~=11.1.1
Can you test the same one only serach and replace ~= with == ?
So only short update for today: I did not yet start a run with conda 4.7.12.
But one question: Actually conda can not be at fault here, right? I can install pytorch just fine locally on the agent, when I do not use clearml(-agent)
I try it one more time just to make sure
I do not have a global cuda install on this machine. Everything except for the driver is installed via conda.