ray.tune.search.Searcher.restore_from_dir#
- Searcher.restore_from_dir(checkpoint_dir: str)[source]#
Restores the state of a searcher from a given checkpoint_dir.
Typically, you should use this function to restore from an experiment directory such as
~/ray_results/trainable
.tuner = tune.Tuner( cost, run_config=train.RunConfig( name=self.experiment_name, storage_path="~/my_results", ), tune_config=tune.TuneConfig( search_alg=search_alg, num_samples=5 ), param_space=config ) tuner.fit() search_alg2 = Searcher() search_alg2.restore_from_dir( os.path.join("~/my_results", self.experiment_name)