v0.9.0b4

Human-in-the-loop Optimization

$ pip install Pillow optuna==3.1.0 optuna-dashboard==0.9.0b4

from __future__ import annotations

import os
import textwrap
import threading
import time
from typing import NoReturn
from wsgiref.simple_server import make_server

import optuna
from PIL import Image
from optuna.trial import TrialState

from optuna_dashboard import ObjectiveChoiceWidget, save_note, ObjectiveSliderWidget
from optuna_dashboard import register_objective_form_widgets
from optuna_dashboard import set_objective_names
from optuna_dashboard import wsgi
from optuna_dashboard.artifact import upload_artifact
from optuna_dashboard.artifact.file_system import FileSystemBackend


storage = optuna.storages.InMemoryStorage()
base_path = os.path.join(os.path.dirname(__file__), "artifact")
artifact_backend = FileSystemBackend(base_path=base_path)


def suggest_and_generate_image(study: optuna.Study) -> None:
    # Ask new parameters
    trial = study.ask()
    r = trial.suggest_int("r", 0, 255)
    g = trial.suggest_int("g", 0, 255)
    b = trial.suggest_int("b", 0, 255)

    # Generate image
    image_path = f"tmp/sample-{trial.number}.png"
    image = Image.new("RGB", (320, 240), color=(r,g,b))
    image.save(image_path)

    # Upload Artifact
    artifact_id = upload_artifact(artifact_backend, trial, image_path)

    # Save Note
    note = textwrap.dedent(f'''\
    ## Trial {trial.number}
    
    ![generated-image](/artifacts/{study._study_id}/{trial._trial_id}/{artifact_id})
    ''')
    save_note(trial, note)


def start_preferential_optimization() -> NoReturn:
    # Create Study
    study = optuna.create_study(
        study_name="Human-in-the-loop Optimization",
        storage=storage,
        directions=["minimize", "maximize"]
    )
    set_objective_names(study, ["Human Perception Score", "Looks Yellow?"])
    register_objective_form_widgets(study, widgets=[
        ObjectiveChoiceWidget(
            choices=["Good 👍", "Bad 👎"],
            values=[-1, 1],
            description="Please input your score!",
        ),
        ObjectiveSliderWidget(
            min=1,
            max=10,
            step=1,
            description="Higher is better.",
        ),
    ])

    # Start Human-in-the-loop Optimization
    n_batch = 3
    while True:
        running_trials = study.get_trials(deepcopy=False, states=(TrialState.RUNNING,))
        if len(running_trials) >= n_batch:
            time.sleep(5)
            continue
        suggest_and_generate_image(study)


def main() -> None:
    if not os.path.exists(base_path):
        os.mkdir(base_path)

    # Start Dashboard server on background
    app = wsgi(storage, artifact_backend=artifact_backend)
    httpd = make_server("127.0.0.1", 8080, app)
    thread = threading.Thread(target=httpd.serve_forever)
    thread.start()

    # Run optimize loop
    try:
        start_preferential_optimization()
    except KeyboardInterrupt:
        httpd.shutdown()
        httpd.server_close()
        thread.join()


if __name__ == "__main__":
    main()

What's Changed

• Fix bug of custom user widgets and enhance artifact support. by @c-bata in #375
• Update best trials when state is updated by @c-bata in #376
• Bump the version up to v0.9.0b4 by @c-bata in #377

Full Changelog: v0.9.0b3...v0.9.0b4