mirror of
https://github.com/wassname/optuna-dashboard.git
synced 2026-09-20 13:00:32 +08:00
127 lines
3.5 KiB
Python
127 lines
3.5 KiB
Python
import asyncio
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import os
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import threading
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import time
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from typing import List
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from typing import Tuple
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from wsgiref.simple_server import make_server
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import optuna
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from pyppeteer import launch
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from optuna_dashboard.app import create_app
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host = "127.0.0.1"
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port = 8080
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output_dir = "tmp"
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def create_optuna_storage() -> optuna.storages.InMemoryStorage:
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storage = optuna.storages.InMemoryStorage()
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# Single-objective study
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study = optuna.create_study(study_name="single-objective", storage=storage)
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def objective_single(trial: optuna.Trial) -> float:
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x1 = trial.suggest_float("x1", 0, 10)
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x2 = trial.suggest_float("x2", 0, 10)
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return (x1 - 2) ** 2 + (x2 - 5) ** 2
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study.optimize(objective_single, n_trials=50)
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# Single-objective study with 1 parameter
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study = optuna.create_study(
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study_name="single-objective-1-param", storage=storage, direction="maximize"
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)
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def objective_single_with_1param(trial: optuna.Trial) -> float:
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x1 = trial.suggest_float("x1", 0, 10)
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return -((x1 - 2) ** 2)
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study.optimize(objective_single_with_1param, n_trials=50)
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# Multi-objective study
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study = optuna.create_study(
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study_name="multi-objective",
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storage=storage,
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directions=["minimize", "minimize"],
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)
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def objective_multi(trial: optuna.Trial) -> Tuple[float, float]:
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x = trial.suggest_float("x", 0, 5)
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y = trial.suggest_float("y", 0, 3)
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v0 = 4 * x ** 2 + 4 * y ** 2
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v1 = (x - 5) ** 2 + (y - 5) ** 2
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return v0, v1
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study.optimize(objective_multi, n_trials=50)
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# Pruning with no intermediate values
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study = optuna.create_study(
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study_name="binh-korn-function-with-constraints", storage=storage
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)
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def objective_prune_with_no_trials(trial: optuna.Trial) -> float:
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x = trial.suggest_float("x", -15, 30)
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y = trial.suggest_float("y", -15, 30)
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v = x ** 2 + y ** 2
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if v > 100:
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raise optuna.TrialPruned()
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return v
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study.optimize(objective_prune_with_no_trials, n_trials=100)
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# No trials single-objective study
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optuna.create_study(
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study_name="single-objective study with no trials", storage=storage
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)
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# No trials multi-objective study
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optuna.create_study(
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study_name="multi-objective study with no trials",
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storage=storage,
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directions=["minimize", "maximize"],
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)
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return storage
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async def take_screenshots(study_ids: List[int]) -> None:
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browser = await launch()
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page = await browser.newPage()
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await page.setViewport({"width": 1000, "height": 3000})
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await page.goto(f"http://{host}:{port}/dashboard/")
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time.sleep(1)
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await page.screenshot({"path": os.path.join(output_dir, "study-list.png")})
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for study_id in study_ids:
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await page.goto(f"http://{host}:{port}/dashboard/studies/{study_id}")
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time.sleep(10)
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await page.screenshot(
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{"path": os.path.join(output_dir, f"study-{study_id}.png")}
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)
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await browser.close()
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def main() -> None:
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os.makedirs(output_dir, exist_ok=True)
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storage = create_optuna_storage()
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app = create_app(storage)
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httpd = make_server(host, port, app)
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thread = threading.Thread(target=httpd.serve_forever)
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thread.start()
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study_ids = [s._study_id for s in storage.get_all_study_summaries()]
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loop = asyncio.get_event_loop()
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loop.run_until_complete(take_screenshots(study_ids))
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httpd.shutdown()
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httpd.server_close()
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thread.join()
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if __name__ == "__main__":
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main()
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