code: def test_predict(self):
      orca_estimator = get_estimator(workers_per_node=2)
      train_dataset = train_data_creator()
      result_shards = orca_estimator.predict(
          data=train_dataset, feature_cols=["y"]
      )
      print("Finished Training:", result_shards)
      result_shards.show()
      assert isinstance(result_shards, ray.data.Dataset)
  
imports: import pytest
  import logging
  from unittest import TestCase
  import ray
  from ray.data import Dataset
  import torch.nn
  import torch.optim
  from bigdl.orca import init_orca_context, stop_orca_context
  from bigdl.orca.learn.pytorch import Estimator
  from bigdl.orca.learn.metrics import MSE
label_desc: Use image node_id 4 for calling the TestPytorchEstimator obj's underlying member method code with example usage: obj.test_predict() without return types