| from __future__ import annotations | |
| import json | |
| import random | |
| from pathlib import Path | |
| from typing import Any | |
| import numpy as np | |
| def seed_everything(seed: int) -> None: | |
| random.seed(seed) | |
| np.random.seed(seed) | |
| try: | |
| import torch | |
| torch.manual_seed(seed) | |
| torch.cuda.manual_seed_all(seed) | |
| torch.backends.cudnn.benchmark = True | |
| except Exception: | |
| pass | |
| def ensure_dir(path: str | Path) -> Path: | |
| path = Path(path) | |
| path.mkdir(parents=True, exist_ok=True) | |
| return path | |
| def write_json(obj: dict[str, Any], path: str | Path) -> None: | |
| path = Path(path) | |
| path.parent.mkdir(parents=True, exist_ok=True) | |
| with path.open("w", encoding="utf-8") as f: | |
| json.dump(obj, f, indent=2) | |
| def count_parameters(model: Any) -> int: | |
| return sum(p.numel() for p in model.parameters() if p.requires_grad) | |
| def get_device(name: str): | |
| import torch | |
| if name.startswith("cuda") and torch.cuda.is_available(): | |
| return torch.device(name) | |
| return torch.device("cpu") | |