l1naforever/stable-diffusion-rocm repository overview

⁠Stable Diffusion ROCm (Radeon OpenCompute) Dockerfile

Go from docker pull; docker run; txt2img on a Radeon ✨.

Provides a Dockerfile that packages the basujindal optimized Stable Diffusion⁠ repository, preconfigured with dependencies to run on AMD Radeon GPUs (particularly 5xxx/6xxx desktop-class GPUs) via AMD's ROCm platform⁠.

⁠Requirements

• A compatible Radeon card (VEGA 56/64, Radeon RX 67XX/68XX/69XX). Other cards may also function at some capacity.
• Modern Linux kernel with ROCM module (Kernel 5.10+)
• Docker

⁠Usage

First, pull the Docker image locally:

    docker pull l1naforever/stable-diffusion-rocm:latest

Now, create an alias which will be used to run the Docker container. This normally goes in your ~/.zshrc or ~/.bashrc:

    alias drun='sudo docker run -it --network=host --device=/dev/kfd --device=/dev/dri --group-add=video --ipc=host --cap-add=SYS_PTRACE --security-opt seccomp=unconfined -v $(pwd):/pwd' ​

Finally, run the container:

    drun --name stable-diffusion l1naforever/stable-diffusion-rocm:latest

This will place you in a shell that can immediately be used to invoke the optimizedSD/optimized_txt2img.py and optimizedSD/optimized_img2img.py scripts, generating outputs within the output directory:

    python optimizedSD/optimized_txt2img.py --prompt "a beautiful landscape with sugar trees in autumn colors by studio ghibli, highly detailed, photorealistic forest, with orange and red leaves falling, fall colors, dynamic lighting, beautif_ul, trending on artstation artgerm pixiv twitter, dream" --ddim_steps 50 

If the provided drun alias above was used, the container will have your current working directory mounted at /pwd, which you can use to copy inputs and outputs from the container. For example, to copy the outputs generated within the container to your host's working directory:

    # Run from within the container:
    cp -r outputs /pwd