class_docstr: Hyper Parameter Searcher. A Tuner-like class.
class_docstr_tok: ["Hyper","Parameter","Searcher",".","A","Tuner-like","class","."]
docstr: A wrapper to test optimization latency multiple times after training.
docstr_tok: ["A","wrapper","to","test","optimization","latency","multiple","times","after","training","."]
code: def _validate(self, *args: Any, **kwargs: Any) -> None:
      """A wrapper to test optimization latency multiple times after training."""
      self.trainer.validate_loop = CustomEvaluationLoop()
      self.trainer.state.fn = TrainerFn.VALIDATING
      self.trainer.training = False
      self.trainer.testing = False
      self.trainer.validate(*args, **kwargs)
  
imports: from typing import Any
  import pytorch_lightning
  import copy
  import math
  from pytorch_lightning.trainer.states import TrainerFn, TrainerStatus
  from bigdl.nano.utils.common import invalidInputError
  from bigdl.nano.automl.hpo.backend import create_hpo_backend, SamplerType
  from .objective import Objective
  from ._helper import ResetCallback, CustomEvaluationLoop
  from bigdl.nano.automl.utils.parallel import run_parallel
  from bigdl.nano.automl.hpo.search import _search_summary, _end_search, _create_study, _validate_args, _prepare_args
label_desc: Use image node_id 9 for calling the HPOSearcher obj's underlying member method code with example usage: obj._validate() without return types