docstr: Ensure the provided parameters are valid and properly formatted
docstr_tok: ["Ensure","the","provided","parameters","are","valid","and","properly","formatted"]
code: def validate_parameters(self):
      """Ensure the provided parameters are valid and properly formatted"""
      #################### metrics_params/metrics ####################
      if (self.metrics is not None) and (
          "metrics" in self.metrics_params.keys()
      ):
          raise ValueError(
              "`metrics` may be provided as a kwarg, or as a `metrics_params` key, but NOT BOTH. Received: "
              + f"\n `metrics`={self.metrics}\n `metrics_params`={self.metrics_params}"
          )
      else:
          _metrics_alias = "metrics"
          if self.metrics is None:
              try:
                  self.metrics = self.metrics_params["metrics"]
              except KeyError:
                  self.metrics = self.metrics_params["metrics_map"]
                  _metrics_alias = "metrics_map"
          self.metrics = format_metrics(self.metrics)
          self.metrics_params = {
              **{_metrics_alias: self.metrics},
              **self.metrics_params,
          }
  
imports: from hyperparameter_hunter.callbacks.bases import BaseCallback
  from hyperparameter_hunter.i_o.reporting import ReportingHandler
  from hyperparameter_hunter.keys.makers import CrossExperimentKeyMaker
  from hyperparameter_hunter.metrics import format_metrics
  from hyperparameter_hunter.sentinels import DatasetSentinel
  from hyperparameter_hunter.settings import G, ASSETS_DIRNAME, RESULT_FILE_SUB_DIR_PATHS
  from hyperparameter_hunter.utils.boltons_utils import remap
  from hyperparameter_hunter.utils.file_utils import make_dirs, ParametersFromFile
  from hyperparameter_hunter.utils.general_utils import Alias
  from hyperparameter_hunter.utils.result_utils import format_predictions, default_do_full_save
  from inspect import signature, isclass
  import numpy
  import os.path
  import pandas
  from pandas.api.types import is_numeric_dtype
  from typing import List, Optional, Tuple, Union
  from sklearn.model_selection import _split
label_desc: Use image node_id 26 for calling the Environment obj's underlying member method code with example usage: obj.validate_parameters() without return types