Traktor/myenv/Lib/site-packages/torch/distributed/checkpoint/api.py
2024-05-26 05:12:46 +02:00

42 lines
1.4 KiB
Python

import traceback as tb
from typing import Any, Dict, Tuple
WRAPPED_EXCEPTION = Tuple[BaseException, tb.StackSummary]
__all__ = ["CheckpointException"]
def _wrap_exception(exc: BaseException) -> WRAPPED_EXCEPTION:
return (exc, tb.extract_tb(exc.__traceback__))
def _is_wrapped_exception(obj: Any) -> bool:
if not isinstance(obj, tuple):
return False
if len(obj) != 2:
return False
return isinstance(obj[0], BaseException) and isinstance(obj[1], tb.StackSummary)
class CheckpointException(BaseException):
"""Exception raised if failure was detected as part of a checkpoint load or save."""
def __init__(self, msg: str, failures: Dict[int, WRAPPED_EXCEPTION]):
super().__init__(msg, failures)
self._failures = failures
@property
def failures(self) -> Dict[int, WRAPPED_EXCEPTION]:
"""Return a dictionary mapping node ranks to their associated exceptions in case of failure."""
return self._failures
def __str__(self):
str = f"CheckpointException ranks:{self._failures.keys()}\n"
for rank, exc_pair in self._failures.items():
exc, trace = exc_pair
str += f"Traceback (most recent call last): (RANK {rank})\n"
if trace is not None:
str += "".join(tb.format_list(trace))
str += "".join(tb.format_exception_only(type(exc), value=exc))
return str