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.
The following example demonstrates how to use Optuna Dashboard.
The following example demonstrates how to implement an objective function that uses additional arguments other than trial
.
The following example demonstrates how to implement pruning logic with Optuna.
In addition, integration modules are available for the following libraries, providing simpler interfaces to utilize pruning.
PRs to add additional projects welcome!
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=''