class_docstr: Searcher which randomly samples configurations to try next.
class_docstr_tok: ["Searcher","which","randomly","samples","configurations","to","try","next","."]
code: def __init__(self, *, first_is_default=True, random_seed=0, **kwargs):
      super().__init__(**kwargs)
      self._first_is_default = first_is_default
      # We use an explicit random_state here, in order to better support checkpoint and resume
      self.random_state = np.random.RandomState(random_seed)
      self._params_space = self._get_params_space()
      self._num_configs = self._get_num_configs()
  
file_path: autogluon/core/src/autogluon/core/searcher/local_random_searcher.py
imports: import logging
  import numpy
  from sklearn.model_selection import ParameterSampler
  from autogluon.common import space
  from .exceptions import ExhaustedSearchSpaceError
  from .local_searcher import LocalSearcher
label_desc: Use image node_id 1 to create a new LocalRandomSearcher object from inherited base classes: LocalSearcher with example: obj = LocalRandomSearcher()