@<1523701070390366208:profile|CostlyOstrich36> I'm now running the agent with --docker , and I'm using task.create(docker="nvidia/cuda:11.0.3-cudnn8-runtime-ubuntu20.04")

within a docker

ERROR: This container was built for NVIDIA Driver Release 530.30 or later, but
       version 460.32.03 was detected and compatibility mode is UNAVAILABLE.

       [[System has unsupported display driver / cuda driver combination (CUDA_ERROR_SYSTEM_DRIVER_MISMATCH) cuInit()=803]]

This has been resolved now! Thank you for your help @<1523701070390366208:profile|CostlyOstrich36>

unrelated to the agent itself

Thank you

It means that there is an issue with the drivers. I suggest trying this docker image - nvcr.io/nvidia/pytorch:23.04-py3

to achieve running both the agent and the deployment on the same machine, adding --network=host to the run arguments solved it!

What I dont understand is how to tell clearml to install this version of pytorch and torchvision, with cu118

Thank you for getting back to me

agent.cuda_version="11.2"

In the config file it should be something like this: agent.cuda_version="11.2" I think

or cu11x

It seems to find a cuda 11, then it installs cuda 12

Torch CUDA 111 index page found, adding `

`
PyTorch: Adding index `

` and installing `torch ==2.4.0.*`
Looking in indexes: 

, 

, 

Collecting torch==2.4.0.*
  Using cached torch-2.4.0-cp310-cp310-manylinux1_x86_64.whl (797.2 MB)
2024-08-12 12:40:37
Collecting clearml
  Using cached clearml-1.16.3-py2.py3-none-any.whl (1.2 MB)
Collecting triton==3.0.0
  Using cached 

 (209.4 MB)
2024-08-12 12:40:42
Collecting nvidia-nccl-cu12==2.20.5
  Using cached nvidia_nccl_cu12-2.20.5-py3-none-manylinux2014_x86_64.whl (176.2 MB)
Collecting nvidia-curand-cu12==10.3.2.106

CUDA is the driver itself. The agent doesn't install CUDA but installs a compatible torch assuming that CUDA is properly installed.

Hi @<1523701070390366208:profile|CostlyOstrich36> I am not specifying a version 🙂

I am trying task.create like so:

task = Task.create(
    script="test_gpu.py",
    packages=["torch"],
)

@<1523701070390366208:profile|CostlyOstrich36> do you have any ideas?

Collecting pip<20.2
Using cached pip-20.1.1-py2.py3-none-any.whl (1.5 MB)
Installing collected packages: pip
Attempting uninstall: pip
Found existing installation: pip 20.0.2
Not uninstalling pip at /usr/lib/python3/dist-packages, outside environment /usr
Can't uninstall 'pip'. No files were found to uninstall.

I can install the correct torch version with this command:
pip install --pre torchvision --force-reinstall --index-url ` None ```

Just to make sure, run the code on the machine itself to verify that python can actually detect the driver

Isn't the problem that CUDA 12 is being installed?

I think it tries to get the latest one. Are you using the agent in docker mode? you can also control this via clearml.conf with agent.cuda_version

pip install --pre torchvision --force-reinstall --index-url None

OK, then just try the docker image I suggested 🙂

@<1523701070390366208:profile|CostlyOstrich36> same error now 😞

Environment setup completed successfully
Starting Task Execution:
/root/.clearml/venvs-builds/3.8/lib/python3.8/site-packages/torch/cuda/__init__.py:128: UserWarning: CUDA initialization: The NVIDIA driver on your system is too old (found version 11020). Please update your GPU driver by downloading and installing a new version from the URL: 

 Alternatively, go to: 

 to install a PyTorch version that has been compiled with your version of the CUDA driver. (Triggered internally at ../c10/cuda/CUDAFunctions.cpp:108.)
  return torch._C._cuda_getDeviceCount() > 0
False
Traceback (most recent call last):
  File "facility_classifier/test_gpu.py", line 8, in <module>
    assert torch.cuda.is_available()
AssertionError

I am running the agent with clearml-agent daemon --queue training

Just try as is first with this docker image + verify that the code can access cuda driver unrelated to the agent

Thank you I will try that

I can install on the server with this command