code: def test_openvino_predict_xshards(self):
      self.load_resnet()
      input_data_list = [
          np.array([self.input] * 4),
          np.concatenate(
              [np.array([self.input] * 2), np.zeros([1, 3, 224, 224])]
          ),
      ]
      sc = init_nncontext()
      rdd = sc.parallelize(input_data_list, numSlices=2)
      shards = SparkXShards(rdd)
  
      def pre_processing(images):
          return {"x": images}
  
      shards = shards.transform_shard(pre_processing)
      result = self.est.predict(shards)
      result_c = result.collect()
      assert isinstance(result, SparkXShards)
      assert result_c[0].shape == (4, 1000)
      assert result_c[1].shape == (3, 1000)
      assert self.check_result(result_c[0], 4)
      assert self.check_result(result_c[1], 2)
      assert not self.check_result(result_c[1][2:], 1)
  
imports: import os
  import tarfile
  import tempfile
  import shutil
  from unittest import TestCase
  import numpy
  from bigdl.dllib.feature.dataset.base import maybe_download
  from bigdl.dllib.nncontext import init_nncontext
  from bigdl.orca.data import SparkXShards
  from bigdl.orca.learn.openvino import Estimator
label_desc: Use image node_id 9 for calling the TestEstimatorForOpenVINO obj's underlying member method code with example usage: obj.test_openvino_predict_xshards() and returns: dict