c6a171b776
Co-authored-by: jirka <jirka.borovec@seznam.cz> |
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.. | ||
base-conda | ||
base-cuda | ||
base-xla | ||
nvidia | ||
release | ||
tpu-tests | ||
README.md |
README.md
Docker images
Builds images form attached Dockerfiles
You can build it on your own, note it takes lots of time, be prepared.
git clone <git-repository>
docker image build -t pytorch-lightning:latest -f dockers/conda/Dockerfile .
or with specific arguments
git clone <git-repository>
docker image build \
-t pytorch-lightning:py3.8-pt1.6 \
-f dockers/base-cuda/Dockerfile \
--build-arg PYTHON_VERSION=3.8 \
--build-arg PYTORCH_VERSION=1.6 \
.
or nightly version from Coda
git clone <git-repository>
docker image build \
-t pytorch-lightning:py3.7-pt1.8 \
-f dockers/base-conda/Dockerfile \
--build-arg PYTHON_VERSION=3.7 \
--build-arg PYTORCH_VERSION=1.8 \
.
To run your docker use
docker image list
docker run --rm -it pytorch-lightning:latest bash
and if you do not need it anymore, just clean it:
docker image list
docker image rm pytorch-lightning:latest
Run docker image with GPUs
To run docker image with access to you GPUs you need to install
# 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
and later run the docker image with --gpus all
so for example
docker run --rm -it --gpus all pytorchlightning/pytorch_lightning:base-cuda-py3.7-torch1.6
Run Jupyter server
Inspiration comes from https://u.group/thinking/how-to-put-jupyter-notebooks-in-a-dockerfile
- Build the docker image:
docker image build \ -t pytorch-lightning:v1.2.9 \ -f dockers/nvidia/Dockerfile \ --build-arg LIGHTNING_VERSION=1.2.9 \ .
- start the server and map ports:
docker run --rm -it --runtime=nvidia -e NVIDIA_VISIBLE_DEVICES=all -p 8888:8888 pytorch-lightning:v1.2.9
- Connect in local browser:
- copy the generated path e.g.
http://hostname:8888/?token=0719fa7e1729778b0cec363541a608d5003e26d4910983c6
- replace the
hostname
bylocalhost
- copy the generated path e.g.