class_docstr: Example:
      >>> auto_est = AutoEstimator.from_torch(model_creator=model_creator,
                                              optimizer=get_optimizer,
                                              loss=nn.BCELoss(),
                                              logs_dir="/tmp/zoo_automl_logs",
                                              resources_per_trial={"cpu": 2},
                                              name="test_fit")
      >>> auto_est.fit(data=data,
                       validation_data=validation_data,
                       search_space=create_linear_search_space(),
                       n_sampling=4,
                       epochs=1,
                       metric="accuracy")
      >>> best_model = auto_est.get_best_model()
class_docstr_tok: ["Example",":",">",">",">","auto_est","=","AutoEstimator.from_torch","(","model_creator=model_creator",",","optimizer=get_optimizer",",","loss=nn.BCELoss","(",")",",","logs_dir=","''","\/tmp\/zoo_automl_logs","''",",","resources_per_trial=","{","``","cpu","''",":","2","}",",","name=","''","test_fit","''",")",">",">",">","auto_est.fit","(","data=data",",","validation_data=validation_data",",","search_space=create_linear_search_space","(",")",",","n_sampling=4",",","epochs=1",",","metric=","''","accuracy","''",")",">",">",">","best_model","=","auto_est.get_best_model","(",")"]
docstr: This is for internal use only.
  Return the best automl model found by the AutoEstimator
  
  :return: an automl base model instance
docstr_tok: ["This","is","for","internal","use","only",".","Return","the","best","automl","model","found","by","the","AutoEstimator",":","return",":","an","automl","base","model","instance"]
code: def _get_best_automl_model(self):
      """
      This is for internal use only.
      Return the best automl model found by the AutoEstimator
  
      :return: an automl base model instance
      """
      if not self.best_trial:
          self.best_trial = self.searcher.get_best_trial()
      best_model_path = self.best_trial.model_path
      best_config = self.best_trial.config
      best_automl_model = self.model_builder.build(best_config)
      best_automl_model.restore(best_model_path)
      return best_automl_model
  
file_path: BigDL/python/orca/src/bigdl/orca/automl/auto_estimator.py
imports: from bigdl.orca.automl.search import SearchEngineFactory
  from bigdl.dllib.utils.log4Error import *
  from bigdl.dllib.utils.log4Error import invalidInputError
  from numpy import ndarray
  from typing import TYPE_CHECKING, Callable, Dict, List, Optional, Tuple, Union, Any
label_desc: Use image node_id 7 for calling the AutoEstimator obj's underlying member method code with example usage: obj._get_best_automl_model() and returns: best_automl_model