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()
docstr: Create an AutoEstimator for tensorflow keras.
  
  :param model_creator: Tensorflow keras model creator function.
  :param logs_dir: Local directory to save logs and results. It defaults to
      "/tmp/auto_estimator_logs"
  :param resources_per_trial: Dict. resources for each trial. e.g. {"cpu": 2}.
  :param name: Name of the auto estimator. It defaults to "auto_keras_estimator"
  :param remote_dir: String. Remote directory to sync training results and checkpoints. It
      defaults to None and doesn't take effects while running in local. While running in
      cluster, it defaults to "hdfs:///tmp/{name}".
  
  :return: an AutoEstimator object.
code: def from_keras(
      *,
      model_creator,
      logs_dir="/tmp/auto_estimator_logs",
      resources_per_trial=None,
      name="auto_keras_estimator",
      remote_dir=None,
  ):
      """
      Create an AutoEstimator for tensorflow keras.
  
      :param model_creator: Tensorflow keras model creator function.
      :param logs_dir: Local directory to save logs and results. It defaults to
          "/tmp/auto_estimator_logs"
      :param resources_per_trial: Dict. resources for each trial. e.g. {"cpu": 2}.
      :param name: Name of the auto estimator. It defaults to "auto_keras_estimator"
      :param remote_dir: String. Remote directory to sync training results and checkpoints. It
          defaults to None and doesn't take effects while running in local. While running in
          cluster, it defaults to "hdfs:///tmp/{name}".
  
      :return: an AutoEstimator object.
      """
      from zoo.orca.automl.model.base_keras_model import (
          KerasModelBuilder,
      )
  
      model_builder = KerasModelBuilder(model_creator=model_creator)
      return AutoEstimator(
          model_builder=model_builder,
          logs_dir=logs_dir,
          resources_per_trial=resources_per_trial,
          remote_dir=remote_dir,
          name=name,
      )
  
file_path: analytics-zoo/pyzoo/zoo/orca/automl/auto_estimator.py
imports: from zoo.orca.automl.search import SearchEngineFactory
label_desc: Use image node_id 3 for calling the AutoEstimator obj's underlying member method code with example usage: obj.from_keras() and returns: AutoEstimator