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ROCm 5.7, PyTorch 2.3, Torchvision 0.18 with AMD GFX803 aka AMD Polaris aka AMD RX570/RX580/RX590

This repo provides a docker buildfile based on the original ROCm-Dockerimage to compile PyTorch and Torchvision for the AMD RX570/RX580/RX590 generation. PyTorch and Torchvision are not compiled to use the GPU-Polaris generation in the original PIP repository. And of course not compiled too in the official ROCm-PyTorch Dockerfile. However, if Polaris 20/21 GPU support is to be used in ComfyUI or A1111 StableDiffusion, there is no way around newly compiled pyTorch and Torvision whl/wheel python files. That what this Docker Buildfile will do for you.

ROCm-5.7.0 in a Dockerfile

OS linux Python ROCm PyTorch Torchvision GPU
Ubuntu-22.04.2 5.19 3.10.10 5.7.0 2.3.0 0.18.0 RX570/580/590 aka Polaris 20/21 aka GCN 4
  • It is not necessary to install the entire ROCm-Stack on the host system. Unless you want to use something to optimize your GPU via rocm-smi. In my case, I need the rocm stuff to reduce the power consumption of my RX570 GPU to 145 watts with rocm-smi --setpoweroverdrive 145 && watch -n2 rocm-smi every time I restart the container.
  1. install the docker-subsystem / docker.io on your linux system
  2. download the latest file version of this github
  3. build your Docker image via docker build . -t 'rocm57_pt23:v1'
  4. start the container via:
  5. docker run -it --device=/dev/kfd --device=/dev/dri --group-add=video --ipc=host \ --cap-add=SYS_PTRACE --security-opt seccomp=unconfined -p 8188:8188 rocm57_pt23:v1
  6. install ComfyUI and download a Model or map an Directory on your Host-Computer
  7. After installing ComfyUI reinstall pytorch and torchvision wheels into your ComfyUI-Python-Environment. you find the Polaris compiled Python-Wheel-Files into the "/pytorch/dist" and "/torchvision/dist" Directory

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