LightGBM/docker

Using LightGBM via Docker

This directory contains Dockerfiles to make it easy to build and run LightGBM via Docker.

Installing Docker

Follow the general installation instructions on the Docker site:

• macOS
• Ubuntu
• Windows

Using CLI Version of LightGBM via Docker

Build a Docker image with LightGBM CLI:

mkdir lightgbm-docker
cd lightgbm-docker
wget https://raw.githubusercontent.com/Microsoft/LightGBM/master/docker/dockerfile-cli
docker build -t lightgbm-cli -f dockerfile-cli .

where lightgbm-cli is the desired Docker image name.

Run the CLI from the container:

docker run --rm -it \
--volume $HOME/lgbm.conf:/lgbm.conf \
--volume $HOME/model.txt:/model.txt \
--volume $HOME/tmp:/out \
lightgbm-cli \
config=lgbm.conf

In the above example, three volumes are mounted from the host machine to the Docker container:

• lgbm.conf - task config, for example

app=multiclass
num_class=3
task=convert_model
input_model=model.txt
convert_model=/out/predict.cpp
convert_model_language=cpp

• model.txt - an input file for the task, could be training data or, in this case, a pre-trained model.
• out - a directory to store the output of the task, notice that convert_model in the task config is using it.

config=lgbm.conf is a command-line argument passed to the lightgbm executable, more arguments can be passed if required.

Running the Python-package Сontainer

Build the container, for Python users:

mkdir lightgbm-docker
cd lightgbm-docker
wget https://raw.githubusercontent.com/Microsoft/LightGBM/master/docker/dockerfile-python
docker build -t lightgbm -f dockerfile-python .

After build finished, run the container:

docker run --rm -it lightgbm

Running the R-package Сontainer

Build the container based on the verse Rocker image, for R users:

mkdir lightgbm-docker
cd lightgbm-docker
wget https://raw.githubusercontent.com/Microsoft/LightGBM/master/docker/dockerfile-r
docker build -t lightgbm-r -f dockerfile-r .

After the build is finished you have two options to run the container:

1. Start RStudio, an interactive development environment, so that you can develop your analysis using LightGBM or simply try out the R package. You can open RStudio in your web browser.
2. Start a regular R session.

In both cases you can simply call

library("lightgbm")

to load the installed LightGBM R package.

RStudio

docker run --rm -it -e PASSWORD=lightgbm -p 8787:8787 lightgbm-r

Open the browser at http://localhost:8787 and log in. See the rocker/rstudio image documentation for further configuration options.

Regular R

If you just want a vanilla R process, change the executable of the container:

docker run --rm -it lightgbm-r R