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