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","(",")"]
code: def __init__(
      self,
      model_builder: "ModelBuilder",
      logs_dir: str = "/tmp/auto_estimator_logs",
      resources_per_trial: Optional[Dict[str, int]] = None,
      remote_dir: Optional[str] = None,
      name: Optional[str] = None,
  ) -> None:
      self.model_builder = model_builder
      self.searcher = SearchEngineFactory.create_engine(
          backend="ray",
          logs_dir=logs_dir,
          resources_per_trial=resources_per_trial,
          remote_dir=remote_dir,
          name=name,
      )
      self._fitted = False
      self.best_trial = None
  
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 1 to create a new AutoEstimator object  with example: obj = AutoEstimator(model_builder, logs_dir, resources_per_trial, remote_dir, name)