class_docstr: Analyze results from a Ray Train/Tune experiment.
  
  To use this class, the run must store the history of reported metrics
  in log files (e.g., `result.json` and `progress.csv`).
  This is the default behavior, unless default loggers are explicitly excluded
  with the `TUNE_DISABLE_AUTO_CALLBACK_LOGGERS=1` environment variable.
  
  Parameters:
      experiment_checkpoint_path: Path to an `experiment_state.json` file,
          or a directory that contains an `experiment_state.json` file.
      default_metric: Default metric for comparing results. Can be
          overwritten with the ``metric`` parameter in the respective
          functions.
      default_mode: Default mode for comparing results. Has to be one
          of [min, max]. Can be overwritten with the ``mode`` parameter
          in the respective functions.
      trials: List of trials that can be accessed via `analysis.trials`.
code: def _validate_metric(self, metric: str) -> str:
      if not metric and not self.default_metric:
          raise ValueError(
              "No `metric` has been passed and  `default_metric` has "
              "not been set. Please specify the `metric` parameter."
          )
      return metric or self.default_metric
  
imports: import copy
  import fnmatch
  import io
  import json
  import logging
  from numbers import Number
  import os
  from pathlib import Path
  from typing import Any, Dict, List, Optional, Tuple, Union
  import pyarrow.fs
  from ray.util.annotations import PublicAPI
  from ray.air.constants import EXPR_PROGRESS_FILE, EXPR_RESULT_FILE, TRAINING_ITERATION
  from ray.train import Checkpoint
  from ray.train._internal.storage import _list_at_fs_path, _exists_at_fs_path, get_fs_and_path
  from ray.tune.execution.tune_controller import TuneController
  from ray.tune.experiment import Trial
  from ray.tune.result import DEFAULT_METRIC, CONFIG_PREFIX
  from ray.tune.utils import flatten_dict
  from ray.tune.utils.serialization import TuneFunctionDecoder
  from ray.tune.utils.util import is_nan_or_inf, is_nan, unflattened_lookup
label_desc: Use image node_id 24 for calling the ExperimentAnalysis obj's underlying member method code with example usage: obj._validate_metric(metric) and returns: unknown