docstr: Returns the learned model.
  
  :return: the learned model.
code: def get_model(
      self, sample_input: Optional["Tensor"] = None
  ) -> "Model":
      """
      Returns the learned model.
  
      :return: the learned model.
      """
      state_refs = [w.get_state.remote() for w in self.remote_workers]
      state = ray.get(state_refs[0])
      return self._get_model_from_state(
          state, sample_input=sample_input
      )
  
imports: import os
  import types
  from bigdl.orca.common import SafePickle
  import shutil
  import tempfile
  import logging
  import ray
  from bigdl.dllib.utils import log4Error
  from bigdl.dllib.utils.file_utils import is_local_path
  from bigdl.orca.data.file import enable_multi_fs_save, enable_multi_fs_load
  from bigdl.orca.data.ray_xshards import RayXShards
  from bigdl.orca.learn.dl_cluster import RayDLCluster
  from bigdl.orca.learn.tf2.tf_runner import TFRunner
  from bigdl.orca.learn.ray_estimator import Estimator
  from bigdl.orca.learn.utils import maybe_dataframe_to_xshards, dataframe_to_xshards, convert_predict_xshards_to_dataframe, update_predict_xshards, process_xshards_of_pandas_dataframe, make_data_creator, add_predict_to_pd_xshards
  from bigdl.orca.data.file import get_remote_file_to_local, get_remote_dir_to_local, is_file
  from bigdl.orca.data.utils import process_spark_xshards
  from bigdl.dllib.utils.log4Error import invalidInputError
  from bigdl.orca.ray import OrcaRayContext
  from typing import TYPE_CHECKING, Dict, List, Callable, Union, Optional
label_desc: Use image node_id 9 for calling the TensorFlow2Estimator obj's underlying member method code with example usage: obj.get_model(sample_input) and returns: self