class_docstr: Generates trials to be passed to the TrialRunner.
  
  Uses the provided ``searcher`` object to generate trials. This class
  transparently handles repeating trials with score aggregation
  without embedding logic into the Searcher.
  
  Args:
      searcher: Search object that subclasses the Searcher base class. This
          is then used for generating new hyperparameter samples.
docstr: Registers experiment specifications.
  
  Arguments:
      experiments: Experiments to run.
docstr_tok: ["Registers","experiment","specifications",".","Arguments",":","experiments",":","Experiments","to","run","."]
code: def add_configurations(
      self,
      experiments: Union[Experiment, List[Experiment], Dict[str, Dict]],
  ):
      """Registers experiment specifications.
  
      Arguments:
          experiments: Experiments to run.
      """
      assert not self._experiment
      logger.debug("added configurations")
      experiment_list = _convert_to_experiment_list(experiments)
      assert (
          len(experiment_list) == 1
      ), "SearchAlgorithms can only support 1 experiment at a time."
      self._experiment = experiment_list[0]
      experiment_spec = self._experiment.spec
      self._total_samples = self._experiment.spec.get("num_samples", 1)
  
      _warn_on_repeater(self.searcher, self._total_samples)
      if "run" not in experiment_spec:
          raise TuneError(
              "Must specify `run` in {}".format(experiment_spec)
          )
  
imports: import copy
  import logging
  from typing import Dict, List, Optional, Union
  from ray.tune.error import TuneError
  from ray.tune.experiment import Experiment, _convert_to_experiment_list
  from ray.tune.experiment.config_parser import _make_parser, _create_trial_from_spec
  from ray.tune.search.search_algorithm import SearchAlgorithm
  from ray.tune.search import Searcher
  from ray.tune.search.util import _set_search_properties_backwards_compatible
  from ray.tune.search.variant_generator import format_vars, _resolve_nested_dict
  from ray.tune.experiment import Trial
  from ray.tune.utils.util import flatten_dict, merge_dicts, _atomic_save, _load_newest_checkpoint
  from ray.util.annotations import DeveloperAPI
label_desc: Use image node_id 5 for calling the SearchGenerator obj's underlying member method code with example usage: obj.add_configurations(experiments) without return types