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# docker run -d --rm -p 3306:3306 -e MYSQL_USER=optuna -e MYSQL_DATABASE=optuna -e MYSQL_PASSWORD=password -e MYSQL_ALLOW_EMPTY_PASSWORD=yes --name optuna-mysql mysql:8.0 | |
from __future__ import annotations | |
import math | |
import threading | |
import time | |
from sqlalchemy import event | |
from sqlalchemy.engine.base import Engine | |
import optuna | |
optuna.logging.set_verbosity(optuna.logging.ERROR) | |
storage_url = "mysql+pymysql://optuna:password@127.0.0.1:3306/optuna" | |
storage = optuna.storages.RDBStorage(storage_url) | |
sql_queries_lock = threading.Lock() | |
sql_queries: dict[str, tuple[int, list[float]]] = {} | |
n_studies = 50 | |
n_trials = 100 | |
n_params = 10 | |
class EngineProfiler: | |
def __init__(self, engine: Engine) -> None: | |
self.engine = engine | |
self.query_start_time = time.perf_counter() | |
def register(self) -> None: | |
event.listen(self.engine, "before_cursor_execute", self.before_cursor_execute) | |
event.listen(self.engine, "after_cursor_execute", self.after_cursor_execute) | |
def before_cursor_execute( # type: ignore | |
self, conn, cursor, statement, parameters, context, executemany | |
) -> None: | |
self.query_start_time = time.perf_counter() | |
def after_cursor_execute( # type: ignore | |
self, conn, cursor, stmt, parameters, context, executemany | |
) -> None: | |
global sql_queries, sql_queries_lock | |
duration = time.perf_counter() - self.query_start_time | |
with sql_queries_lock: | |
registered = stmt in sql_queries | |
sql_queries[stmt] = ( | |
sql_queries[stmt][0] + 1 if registered else 1, | |
sql_queries[stmt][1] + [duration] if registered else [duration], | |
) | |
def objective(trial: optuna.Trial) -> float: | |
return sum([ | |
math.sin(trial.suggest_float('param-{}'.format(i), 0, math.pi * 2)) | |
for i in range(n_params) | |
]) | |
def main(): | |
global sql_queries, sql_queries_lock | |
# Create trials | |
if len(storage.get_all_studies()) == 0: | |
for i in range(n_studies): | |
study = optuna.create_study(storage=storage) | |
study.optimize(lambda trial: objective(trial), n_trials=n_trials, n_jobs=8) | |
# Profile storage.get_all_trials() | |
EngineProfiler(storage.engine).register() | |
start = time.time() | |
for i in range(100): | |
storage.get_all_trials(study_id=1) | |
elapsed = time.time() - start | |
print(f"Elapsed: {elapsed:.4f}s ({n_trials=} {n_params=})") | |
# Show profiler stats | |
summary = [ | |
(stmt, count, f"{sum(durations):.4f}", sum(durations)) | |
for stmt, (count, durations) in sql_queries.items() | |
] | |
sort_by_total = sorted(summary, key=lambda r: r[3], reverse=True) | |
print("") | |
print("Sort by Total:") | |
print("Total Time(s)\tQuery Count\tStatement") | |
for q in sort_by_total[:5]: | |
print(f"{q[2]}\t{q[1]}\t{q[0]}") | |
if __name__ == '__main__': | |
main() |
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