class_docstr: Write the provided exception object along with some other metadata about
  the error in a structured way in JSON format to an error file specified by the
  environment variable: ``TORCHELASTIC_ERROR_FILE``. If this environment
  variable is not set, then simply logs the contents of what would have been
  written to the error file.
  
  This handler may be subclassed to customize the handling of the error.
  Subclasses should override ``initialize()`` and ``record_exception()``.
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code: def _rm(self, my_error_file):
      if os.path.isfile(my_error_file):
          # Log the contents of the original file.
          with open(my_error_file) as fp:
              try:
                  original = json.dumps(json.load(fp), indent=2)
                  log.warning(
                      "%s already exists"
                      " and will be overwritten."
                      " Original contents:\n%s",
                      my_error_file,
                      original,
                  )
              except json.decoder.JSONDecodeError as err:
                  log.warning(
                      "%s already exists"
                      " and will be overwritten."
                      " Unable to load original contents:\n",
                      my_error_file,
                  )
          os.remove(my_error_file)
  
file_path: pytorch/torch/distributed/elastic/multiprocessing/errors/error_handler.py
imports: import faulthandler
  import json
  import logging
  import os
  import time
  import traceback
  import warnings
  from typing import Any, Dict, Optional
label_desc: Use image node_id 7 for calling the ErrorHandler obj's underlying member method code with example usage: obj._rm(my_error_file) without return types