Optuna Examples

This page contains a list of example codes written with Optuna.

The simplest codeblock looks like this:

import optuna


def objective(trial):
    x = trial.suggest_float("x", -100, 100)
    return x ** 2


if __name__ == "__main__":
    study = optuna.create_study()
    # The optimization finishes after evaluating 1000 times or 3 seconds.
    study.optimize(objective, n_trials=1000, timeout=3)
    print(f"Best params is {study.best_params} with value {study.best_value}")

The examples below provide codeblocks similar to the example above for various different scenarios.

Simple Black-box Optimization

Examples with ML Libraries

An example of Optuna Dashboard

The following example demonstrates how to use Optuna Dashboard.

Starting Optuna Dashboard with in-memory storage

An example where an objective function uses additional arguments

The following example demonstrates how to implement an objective function that uses additional arguments other than trial.

Scikit-learn (callable class version)

Examples of Pruning

The following example demonstrates how to implement pruning logic with Optuna.

Simple pruning (scikit-learn)

In addition, integration modules are available for the following libraries, providing simpler interfaces to utilize pruning.

Examples of Samplers

Warm Starting CMA-ES

Examples of User-Defined Sampler

SimulatedAnnealingSampler

Examples of Terminator

Examples of Multi-Objective Optimization

Examples of Visualization

Examples of Distributed Optimization

Examples of Reinforcement Learning

Optimization of Hyperparameters for Stable-Baslines Agent

External projects using Optuna

PRs to add additional projects welcome!

Running with Optuna's Docker images?

You can use our docker images with the tag ending with -dev to run most of the examples. For example, you can run PyTorch Simple via docker run --rm -v $(pwd):/prj -w /prj optuna/optuna:py3.7-dev python pytorch/pytorch_simple.py. Also, you can try our visualization example in Jupyter Notebook by opening localhost:8888 in your browser after executing this:

docker run -p 8888:8888 --rm optuna/optuna:py3.7-dev jupyter notebook --allow-root --no-browser --port 8888 --ip 0.0.0.0 --NotebookApp.token='' --NotebookApp.password=''

nzw0301/optuna-examples