| """Torch device probe used by every training script.""" | |
| from __future__ import annotations | |
| from typing import Any | |
| def probe_torch() -> dict[str, Any]: | |
| info: dict[str, Any] = { | |
| "torch_imported": False, | |
| "version": None, | |
| "cuda_compiled": None, | |
| "cuda_available": False, | |
| "device": "cpu", | |
| "gpu_name": None, | |
| "error": None, | |
| } | |
| try: | |
| import torch | |
| except Exception as exc: # pragma: no cover - environment dependent | |
| info["error"] = f"{type(exc).__name__}: {exc}" | |
| return info | |
| info["torch_imported"] = True | |
| info["version"] = torch.__version__ | |
| info["cuda_compiled"] = torch.version.cuda | |
| info["cuda_available"] = bool(torch.cuda.is_available()) | |
| if info["cuda_available"]: | |
| info["device"] = "cuda" | |
| info["gpu_name"] = torch.cuda.get_device_name(0) | |
| return info | |
| def torch_device(): | |
| import torch | |
| return torch.device("cuda" if torch.cuda.is_available() else "cpu") | |