This repo constitutes a skeleton for a typical ML/DS project. Docker is a first class citizen and can be customized by editing the provided Dockerfile
.
When starting a new project, please do the following:
- On GitHub, create your own repository from this template by clicking the "Use this template" button
- Update
DOCKER_IMAGE_NAME
instart.sh
- Build and start a docker container:
./start.sh [--gpu] [--notebook] [--tensorboard] [-v|--mount /host/path:/container/path] [--detach]
- Start a development container in VS Code:
There are two ways this can be done.
- Attach to the already running container (preferred when container is running on remote host)
- In VS Code, install the
Remote-Containers
extention - Run
Remote-Containers: Attach to Running Container...
(F1). Select the newly created container - In the Explorer pane, click
Open Folder
and type the workspace directory (by default mounted to/workspace
)
- In VS Code, install the
- Let VS Code manage the container (preferred for local development)
- In VS Code, install the
Remote-Containers
extention - Update
name
in.devcontainer/devcontainer.json
to the value ofDOCKER_IMAGE_NAME
- Run
Remote-Containers: Reopen in container
(F1). Select the newly created container
- In VS Code, install the
- Attach to the already running container (preferred when container is running on remote host)