class_docstr: Searcher which randomly samples configurations to try next.
class_docstr_tok: ["Searcher","which","randomly","samples","configurations","to","try","next","."]
code: def _sample_config(self) -> dict:
      params = list(
          ParameterSampler(
              self._params_space,
              n_iter=1,
              random_state=self.random_state,
          )
      )[0]
      for key in params:
          if isinstance(params[key], np.float64):
              # Fix error in FastAI, can't handle np.float64
              params[key] = float(params[key])
      params.update(self._params_static)
      return params
  
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 4 for calling the LocalRandomSearcher obj's underlying member method code with example usage: obj._sample_config() and returns: params