class_docstr: Runtime configuration for training and tuning runs.
  
  Upon resuming from a training or tuning run checkpoint,
  Ray Train/Tune will automatically apply the RunConfig from
  the previously checkpointed run.
  
  Args:
      name: Name of the trial or experiment. If not provided, will be deduced
          from the Trainable.
      storage_path: [Beta] Path to store results at. Can be a local directory or
          a destination on cloud storage. If Ray storage is set up,
          defaults to the storage location. Otherwise, this defaults to
          the local ``~/ray_results`` directory.
      failure_config: Failure mode configuration.
      checkpoint_config: Checkpointing configuration.
      sync_config: Configuration object for syncing. See train.SyncConfig.
      verbose: 0, 1, or 2. Verbosity mode.
          0 = silent, 1 = default, 2 = verbose. Defaults to 1.
          If the ``RAY_AIR_NEW_OUTPUT=1`` environment variable is set,
          uses the old verbosity settings:
          0 = silent, 1 = only status updates, 2 = status and brief
          results, 3 = status and detailed results.
      stop: Stop conditions to consider. Refer to ray.tune.stopper.Stopper
          for more info. Stoppers should be serializable.
      callbacks: [DeveloperAPI] Callbacks to invoke.
          Refer to ray.tune.callback.Callback for more info.
          Callbacks should be serializable.
          Currently only stateless callbacks are supported for resumed runs.
          (any state of the callback will not be checkpointed by Tune
          and thus will not take effect in resumed runs).
      progress_reporter: [DeveloperAPI] Progress reporter for reporting
          intermediate experiment progress. Defaults to CLIReporter if
          running in command-line, or JupyterNotebookReporter if running in
          a Jupyter notebook.
      log_to_file: [DeveloperAPI] Log stdout and stderr to files in
          trial directories. If this is `False` (default), no files
          are written. If `true`, outputs are written to `trialdir/stdout`
          and `trialdir/stderr`, respectively. If this is a single string,
          this is interpreted as a file relative to the trialdir, to which
          both streams are written. If this is a Sequence (e.g. a Tuple),
          it has to have length 2 and the elements indicate the files to
          which stdout and stderr are written, respectively.
code: def __post_init__(self):
      from ray.train import SyncConfig
      from ray.tune.experimental.output import (
          AirVerbosity,
          get_air_verbosity,
      )
  
      if not self.failure_config:
          self.failure_config = FailureConfig()
  
      if not self.sync_config:
          self.sync_config = SyncConfig()
  
      if not self.checkpoint_config:
          self.checkpoint_config = CheckpointConfig()
  
      if self.verbose is None:
          # Default `verbose` value. For new output engine,
          # this is AirVerbosity.DEFAULT.
          # For old output engine, this is Verbosity.V3_TRIAL_DETAILS
          # Todo (krfricke): Currently uses number to pass test_configs::test_repr
          self.verbose = get_air_verbosity(AirVerbosity.DEFAULT) or 3
  
      # Convert Paths to strings
      if isinstance(self.local_dir, Path):
          self.local_dir = self.local_dir.as_posix()
  
      if isinstance(self.storage_path, Path):
          self.storage_path = self.storage_path.as_posix()
  
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 1 for calling the RunConfig obj's underlying member method code with example usage: obj.__post_init__() without return types