lightning/dockers/README.md

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# Docker images
## Builds images form attached Dockerfiles
You can build it on your own, note it takes lots of time, be prepared.
```bash
git clone <git-repository>
docker image build -t pytorch-lightning:latest -f dockers/conda/Dockerfile .
```
or with specific arguments
```bash
git clone <git-repository>
docker image build \
-t pytorch-lightning:base-cuda-py3.7-pt1.8 \
-f dockers/base-cuda/Dockerfile \
--build-arg PYTHON_VERSION=3.7 \
--build-arg PYTORCH_VERSION=1.8 \
.
```
or nightly version from Conda
```bash
git clone <git-repository>
docker image build \
-t pytorch-lightning:base-conda-py3.9-pt1.11 \
-f dockers/base-conda/Dockerfile \
--build-arg PYTHON_VERSION=3.9 \
--build-arg PYTORCH_VERSION=1.11 \
.
```
To run your docker use
```bash
docker image list
docker run --rm -it pytorch-lightning:latest bash
```
and if you do not need it anymore, just clean it:
```bash
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
```bash
# 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
1. Build the docker image:
```bash
docker image build \
-t pytorch-lightning:v1.3.1 \
-f dockers/nvidia/Dockerfile \
--build-arg LIGHTNING_VERSION=1.3.1 \
.
```
1. start the server and map ports:
```bash
docker run --rm -it --runtime=nvidia -e NVIDIA_VISIBLE_DEVICES=all -p 8888:8888 pytorch-lightning:v1.3.1
```
1. Connect in local browser:
- copy the generated path e.g. `http://hostname:8888/?token=0719fa7e1729778b0cec363541a608d5003e26d4910983c6`
- replace the `hostname` by `localhost`