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.
Just try as is first with this docker image + verify that the code can access cuda driver unrelated to the agent
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
Solved that by setting docker_args=["--privileged", "--network=host"]
I am trying task.create like so:
task = Task.create(
script="test_gpu.py",
packages=["torch"],
)
If I run nvidia-smi it returns valid output and it says the CUDA version is 11.2
I can install on the server with this command
@<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 have set agent.package_manager.pip_version="" which resolved that message