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| from __future__ import annotations | |
| import json | |
| import random | |
| from contextlib import nullcontext | |
| from pathlib import Path | |
| from typing import Any | |
| import numpy as np | |
| import torch | |
| def seed_everything(seed: int) -> None: | |
| random.seed(seed) | |
| np.random.seed(seed) | |
| torch.manual_seed(seed) | |
| if torch.cuda.is_available(): | |
| torch.cuda.manual_seed_all(seed) | |
| def get_device(prefer_mps: bool = True, requested_device: str = "auto") -> torch.device: | |
| if requested_device != "auto": | |
| if requested_device == "cuda": | |
| if not torch.cuda.is_available(): | |
| raise RuntimeError("CUDA was requested but is not available.") | |
| return torch.device("cuda") | |
| if requested_device == "mps": | |
| if not torch.backends.mps.is_available(): | |
| raise RuntimeError("MPS was requested but is not available.") | |
| return torch.device("mps") | |
| if requested_device == "cpu": | |
| return torch.device("cpu") | |
| raise ValueError(f"Unsupported device: {requested_device}") | |
| if torch.cuda.is_available(): | |
| return torch.device("cuda") | |
| if prefer_mps and torch.backends.mps.is_available(): | |
| return torch.device("mps") | |
| return torch.device("cpu") | |
| def get_autocast(device: torch.device, enabled: bool): | |
| if not enabled: | |
| return nullcontext() | |
| if device.type == "cuda": | |
| return torch.autocast(device_type="cuda", dtype=torch.float16) | |
| return nullcontext() | |
| def dump_json(path: str | Path, payload: dict[str, Any]) -> None: | |
| path = Path(path) | |
| path.parent.mkdir(parents=True, exist_ok=True) | |
| with path.open("w", encoding="utf-8") as handle: | |
| json.dump(payload, handle, indent=2) | |
| def load_json(path: str | Path) -> dict[str, Any]: | |
| with Path(path).open("r", encoding="utf-8") as handle: | |
| return json.load(handle) | |