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Source code for torch.distributed.elastic.events

#!/usr/bin/env/python3

# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.

"""
Module contains events processing mechanisms that are integrated with the standard python logging.

Example of usage:

::

  from torch.distributed.elastic import events
  event = events.Event(name="test_event", source=events.EventSource.WORKER, metadata={...})
  events.get_logging_handler(destination="console").info(event)

"""

import inspect
import logging
import os
import socket
import traceback
from enum import Enum
from typing import Dict, Optional

from torch.distributed.elastic.events.handlers import get_logging_handler

from .api import (  # noqa: F401
    Event,
    EventMetadataValue,
    EventSource,
    NodeState,
    RdzvEvent,
)

_events_loggers: Dict[str, logging.Logger] = {}

def _get_or_create_logger(destination: str = "null") -> logging.Logger:
    """
    Constructs python logger based on the destination type or extends if provided.
    Available destination could be found in ``handlers.py`` file.
    The constructed logger does not propagate messages to the upper level loggers,
    e.g. root logger. This makes sure that a single event can be processed once.

    Args:
        destination: The string representation of the event handler.
            Available handlers found in ``handlers`` module
    """
    global _events_loggers

    if destination not in _events_loggers:
        _events_logger = logging.getLogger(f"torchelastic-events-{destination}")
        _events_logger.setLevel(os.environ.get("LOGLEVEL", "INFO"))
        # Do not propagate message to the root logger
        _events_logger.propagate = False

        logging_handler = get_logging_handler(destination)
        _events_logger.addHandler(logging_handler)

        # Add the logger to the global dictionary
        _events_loggers[destination] = _events_logger

    return _events_loggers[destination]


[docs]def record(event: Event, destination: str = "null") -> None: _get_or_create_logger(destination).info(event.serialize())
def record_rdzv_event(event: RdzvEvent) -> None: _get_or_create_logger("dynamic_rendezvous").info(event.serialize()) def construct_and_record_rdzv_event( run_id: str, message: str, node_state: NodeState, name: str = "", hostname: str = "", pid: Optional[int] = None, master_endpoint: str = "", local_id: Optional[int] = None, rank: Optional[int] = None, ) -> None: # We don't want to perform an extra computation if not needed. if isinstance(get_logging_handler("dynamic_rendezvous"), logging.NullHandler): return # Set up parameters. if not hostname: hostname = socket.getfqdn() if not pid: pid = os.getpid() # Determines which file called this function. callstack = inspect.stack() filename = "no_file" if len(callstack) > 1: stack_depth_1 = callstack[1] filename = os.path.basename(stack_depth_1.filename) if not name: name = stack_depth_1.function # Delete the callstack variable. If kept, this can mess with python's # garbage collector as we are holding on to stack frame information in # the inspect module. del callstack # Set up error trace if this is an exception if node_state == NodeState.FAILED: error_trace = traceback.format_exc() else: error_trace = "" # Initialize event object event = RdzvEvent( name=f"{filename}:{name}", run_id=run_id, message=message, hostname=hostname, pid=pid, node_state=node_state, master_endpoint=master_endpoint, rank=rank, local_id=local_id, error_trace=error_trace, ) # Finally, record the event. record_rdzv_event(event)

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