optuna-dashboard

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

Installation

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

$ pip install optuna-dashboard

Getting Started

First, please specify the storage URL to persistent your study using the RDB backend.

import optuna

def objective(trial):
    x = trial.suggest_float("x", -100, 100)
    y = trial.suggest_categorical("y", [-1, 0, 1])
    return x**2 + y

if __name__ == "__main__":
    study = optuna.create_study(
        storage="sqlite:///db.sqlite3",  # Specify the storage URL here.
        study_name="quadratic-simple"
    )
    study.optimize(objective, n_trials=100)
    print(f"Best value: {study.best_value} (params: {study.best_params})")

After running the above script, please execute the optuna-dashboard command with Optuna storage URL.

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

Please check out our documentation for more details.

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.