* change docs from 1.x to main * bump version * update readme status info and highlights * revert version change * fix dead links * fix script * fix docs * fix building status * fix md lint error * upgrade to ubuntu20.04 for github ci * Revert "upgrade to ubuntu20.04 for github ci" This reverts commit 9c598f4857633dfb96b116ca9fb9a5d15b5fa6b4. * update codebase md files * upgrade to ubuntu20.04 for github ci * fix * fix requirements * fix * fix ci * bump version * fix * fix pplnn torchscript * fix building status * fix ncnn * fix * remove circileci hold * fix pytorch image
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Use Docker Image
We provide two dockerfiles for CPU and GPU respectively. For CPU users, we install MMDeploy with ONNXRuntime, ncnn and OpenVINO backends. For GPU users, we install MMDeploy with TensorRT backend. Besides, users can install mmdeploy with different versions when building the docker image.
Build docker image
For CPU users, we can build the docker image with the latest MMDeploy through:
cd mmdeploy
docker build docker/CPU/ -t mmdeploy:master-cpu
For GPU users, we can build the docker image with the latest MMDeploy through:
cd mmdeploy
docker build docker/GPU/ -t mmdeploy:master-gpu
For installing MMDeploy with a specific version, we can append --build-arg VERSION=${VERSION}
to build command. GPU for example:
cd mmdeploy
docker build docker/GPU/ -t mmdeploy:0.1.0 --build-arg VERSION=0.1.0
For installing libs with the aliyun source, we can append --build-arg USE_SRC_INSIDE=${USE_SRC_INSIDE}
to build command.
# GPU for example
cd mmdeploy
docker build docker/GPU/ -t mmdeploy:inside --build-arg USE_SRC_INSIDE=true
# CPU for example
cd mmdeploy
docker build docker/CPU/ -t mmdeploy:inside --build-arg USE_SRC_INSIDE=true
Run docker container
After building the docker image succeed, we can use docker run
to launch the docker service. GPU docker image for example:
docker run --gpus all -it mmdeploy:master-gpu
FAQs
-
CUDA error: the provided PTX was compiled with an unsupported toolchain:
As described here, update the GPU driver to the latest one for your GPU.
-
docker: Error response from daemon: could not select device driver "" with capabilities: [gpu].
# Add the package repositories distribution=$(. /etc/os-release;echo $ID$VERSION_ID) curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add - curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list sudo apt-get update && sudo apt-get install -y nvidia-container-toolkit sudo systemctl restart docker