optuna-dashboard

Real-time dashboard for Optuna. Code files were originally taken from Goptuna.

Getting Started

You can install optuna-dashboard via PyPI or Anaconda Cloud.

$ pip install optuna-dashboard

And you can also install following optional dependencies to make optuna-dashboard faster.

$ pip install optuna-fast-fanova gunicorn

Then please execute optuna-dashboard command with Optuna storage URL.

$ optuna-dashboard sqlite:///db.sqlite3
Listening on http://localhost:8080/
Hit Ctrl-C to quit.

$ optuna-dashboard -h
usage: optuna-dashboard [-h] [--port PORT] [--host HOST] [--version] [--quiet] storage

Real-time dashboard for Optuna.

positional arguments:
  storage        DB URL (e.g. sqlite:///example.db)

optional arguments:
  -h, --help            show this help message and exit
  --port PORT           port number (default: 8080)
  --host HOST           hostname (default: 127.0.0.1)
  --server {wsgiref,gunicorn}
                        server (default: auto)
  --version, -v         show program's version number and exit
  --quiet, -q           quiet

Using an official Docker image

You can also use an official Docker image instead of setting up your Python environment. The Docker image only supports SQLite3, MySQL(PyMySQL), and PostgreSQL(Psycopg2).

$ docker run -it --rm -p 8080:8080 -v `pwd`:/app -w /app \
> ghcr.io/optuna/optuna-dashboard sqlite:///db.sqlite3

$ docker run -it --rm -p 8080:8080 ghcr.io/optuna/optuna-dashboard mysql+pymysql://username:password@hostname:3306/dbname

$ docker run -it --rm -p 8080:8080 ghcr.io/optuna/optuna-dashboard postgresql+psycopg2://username:password@hostname:5432/dbname

Features

Manage Studies

You can create and delete studies from Dashboard.

Visualize with Interactive Graphs & Rich Trials Data Grid

You can check the optimization history, hyperparameter importances, etc. in graphs and tables.

Submitting patches

If you want to contribute, please check Developers Guide.