code: def _predict_spark_xshards(self, xshards, params):
      ray_xshards = RayXShards.from_spark_xshards(xshards)
  
      def transform_func(worker, shards_ref):
          params["data_creator"] = make_data_creator(shards_ref)
          return worker.predict.remote(**params)
  
      pred_shards = ray_xshards.transform_shards_with_actors(
          self.remote_workers, transform_func
      )
      spark_xshards = pred_shards.to_spark_xshards()
      return spark_xshards
  
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 7 for calling the TensorFlow2Estimator obj's underlying member method code with example usage: obj._predict_spark_xshards(xshards, params) and returns: spark_xshards, worker