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

Thank you for getting back to me

Thank you

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

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....

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

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]]

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 

...

@<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")

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

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

Thank you I will try that

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

I can install on the server with this command

I have set agent{cuda_version: 11.2}

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

or cu11x

@<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 PyTo...

How are you getting:

beautifulsoup4 @ file:///croot/beautifulsoup4-split_1681493039619/work

This comes with the docker image ultralytics/ultralytics:latest

As I get a bunch of these warnings in both of the clones that failed

Resetting and enqueuing task which has built successfully also fails 😞

Task log

agent.package_manager.pip_version=""

Docker mode

DEBUG   Installing build dependencies ... [?25l- \ | / - done
[?25h  Getting requirements to build wheel ... [?25l- error
  [1;31merror[0m: [1msubprocess-exited-with-error[0m
  
  [31m×[0m [32mGetting requirements to build wheel[0m did not run successfully.
  [31m│[0m exit code: [1;36m1[0m
  [31m╰─>[0m [31m[21 lines of output][0m
  [31m   [0m Traceback (most recent call last):
  [31m   [0m   File "/root/.clearml/venvs-builds/3.8/lib/python3.8/site-packages/pip/_vendor/pyproject_hooks/_i...

Setting agent.venvs_cache path back to ~/.clearml/venvs-cache seems to have done the trick!

The original run completes successfully, it's only the runs cloned from the GUI which fail

In a cloned run with new container ultralytics/ultralytics:latest I get this error:

clearml_agent: ERROR: Could not install task requirements!
Command '['/root/.clearml/venvs-builds/3.10/bin/python', '-m', 'pip', '--disable-pip-version-check', 'install', '-r', '/tmp/cached-reqs7171xfem.txt', '--extra-index-url', '

', '--extra-index-url', '

 returned non-zero exit status 1.

"Original PIP" is empty as for this task we can rely on the docker image to provide the python packages

Container nvcr.io/nvidia/pytorch:22.12-py3