class_docstr: Configuration related to failure handling of each training/tuning run.
  
  Args:
      max_failures: Tries to recover a run at least this many times.
          Will recover from the latest checkpoint if present.
          Setting to -1 will lead to infinite recovery retries.
          Setting to 0 will disable retries. Defaults to 0.
      fail_fast: Whether to fail upon the first error.
          If fail_fast='raise' provided, the original error during training will be
          immediately raised. fail_fast='raise' can easily leak resources and
          should be used with caution.
code: def __repr__(self):
      return _repr_dataclass(self)
  
imports: import logging
  from collections import defaultdict
  from dataclasses import _MISSING_TYPE, dataclass, fields
  from pathlib import Path
  from typing import TYPE_CHECKING, Any, Callable, Dict, List, Mapping, Optional, Union, Tuple
  import pyarrow.fs
  from ray._private.thirdparty.tabulate.tabulate import tabulate
  from ray.util.annotations import PublicAPI, Deprecated
  from ray.widgets import Template, make_table_html_repr
  from ray.data.preprocessor import Preprocessor
label_desc: Use image node_id 2 for calling the FailureConfig obj's underlying member method code with example usage: obj.__repr__() and returns: _repr_dataclass