class_docstr: Represent the failed process result. When the worker process fails, it may record failure root cause into the file.
  
  Tries to read the failure timestamp from the provided ``error_file``,
  if the ``error_file`` does not exist, the timestamp is the current
  timestamp (seconds since epoch).
  
  The ``message`` field is a concise explanation of the failure. If
  the error file exists then the message is obtained from the error file.
  Otherwise one is generated based on the failure signature.
  
  .. note:: It is assumed that the ``error_file`` is written by
            ``torch.distributed.elastic.multiprocessing.errors.error_handler.ErrorHandler``.
            Otherwise the behavior is undefined.
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code: def _get_error_data(
      self, error_file_data: Dict[str, Any]
  ) -> Tuple[str, int]:
      message = error_file_data["message"]
      if isinstance(message, str):
          timestamp = int(error_file_data.get("timestamp", 0))
      else:
          timestamp = int(message["extraInfo"]["timestamp"])
      return (message, timestamp)
  
imports: import json
  import os
  import signal
  import socket
  import time
  import warnings
  from dataclasses import dataclass, field
  from datetime import datetime
  from functools import wraps
  from string import Template
  from typing import Any, Callable, Dict, List, Optional, Tuple, TypeVar
  from torch.distributed.elastic.utils.logging import get_logger
  from .error_handler import ErrorHandler
  from .handlers import get_error_handler
label_desc: Use image node_id 2 for calling the ProcessFailure obj's underlying member method code with example usage: obj._get_error_data(error_file_data) and returns: message,  timestamp