MLPY/Lib/site-packages/torch/distributed/checkpoint/api.py

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