I am trying task.create like so:

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

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

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

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

Thank you

It's hanging at

Installing collected packages: zipp, importlib-resources, rpds-py, pkgutil-resolve-name, attrs, referencing, jsonschema-specifications, jsonschema, certifi, urllib3, idna, charset-normalizer, requests, pyparsing, PyYAML, six, pathlib2, orderedmultidict, furl, pyjwt, psutil, python-dateutil, platformdirs, distlib, filelock, virtualenv, clearml-agent
Successfully installed PyYAML-6.0.2 attrs-23.2.0 certifi-2024.7.4 charset-normalizer-3.3.2 clearml-agent-1.8.1 distlib-0.3.8 filelock-3.15.4 furl-2.1.3 idna-3.7 importlib-resources-6.4.0 jsonschema-4.23.0 jsonschema-specifications-2023.12.1 orderedmultidict-1.0.1 pathlib2-2.3.7.post1 pkgutil-resolve-name-1.3.10 platformdirs-4.2.2 psutil-5.9.8 pyjwt-2.8.0 pyparsing-3.1.2 python-dateutil-2.8.2 referencing-0.35.1 requests-2.31.0 rpds-py-0.20.0 six-1.16.0 urllib3-1.26.19 virtualenv-20.26.3 zipp-3.20.0
WARNING: You are using pip version 20.1.1; however, version 24.2 is available.
You should consider upgrading via the '/usr/bin/python3 -m pip install --upgrade pip' command.

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

docker="nvidia/cuda:11.8.0-base-ubuntu20.04"

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

Hi @<1734020162731905024:profile|RattyBluewhale45> , what version of pytorch are you specifying?

Thank you for getting back to me

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

If I run nvidia-smi it returns valid output and it says the CUDA version is 11.2

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

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

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

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.

or cu11x

within a docker

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

Solved that by setting docker_args=["--privileged", "--network=host"]

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

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

Thank you I will try that

unrelated to the agent itself

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

I have set agent.package_manager.pip_version="" which resolved that message

agent.cuda_version="11.2"

@<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

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