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Build Docker Environment and use with GPU Support

Before you can use this Docker environment, you need to have the following:

  • Docker installed on your system
  • NVIDIA drivers installed on your system
  • NVIDIA Container Toolkit installed on your system

Change the GPU architecture in Dockerfile

You shold change the TORCH_CUDA_ARCH_LIST accoording to your GPU Compute Capability in Dockerfile before building the image. For example, if you are using an NVIDIA V100 GPU, you should set the TORCH_CUDA_ARCH_LIST environment variable in Dockerfile to the following value:

export TORCH_CUDA_ARCH_LIST=7.0+PTX

Build and Run

  1. Build docker image: 
    docker build -t Sin3DGen:latest .
  2. Start the docker container: 
    docker run --gpus all -it Sin3DGen:latest /bin/bash
  3. Clone the repository: 
    git clone git@github.com:wyysf-98/Sin3DGen.git

Troubleshooting

If you encounter any issues with the Docker environment with GPU support, please check the following:

  • Make sure that you have installed the NVIDIA drivers and NVIDIA Container Toolkit on your system.
  • Make sure that you have specified the --gpus all option when starting the Docker container.
  • Make sure that your deep learning application is configured to use the GPU.