Hi @<1523701070390366208:profile|CostlyOstrich36> I am not specifying a version 🙂
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
In the config file it should be something like this: agent.cuda_version="11.2" I think
to achieve running both the agent and the deployment on the same machine, adding --network=host to the run arguments solved it!
@<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")
This has been resolved now! Thank you for your help @<1523701070390366208:profile|CostlyOstrich36>