code: def test_predict_with_entry_point(
      tfs_predictor_with_model_and_entry_point_same_tar,
  ):
      input_data = {"instances": [1.0, 2.0, 5.0]}
      expected_result = {"predictions": [4.0, 4.5, 6.0]}
  
      result = (
          tfs_predictor_with_model_and_entry_point_same_tar.predict(
              input_data
          )
      )
      assert expected_result == result
  
imports: from __future__ import absolute_import
  import tarfile
  import botocore.exceptions
  import os
  import pytest
  import sagemaker
  import sagemaker.predictor
  import sagemaker.utils
  import tests.integ
  import tests.integ.timeout
  from sagemaker.deserializers import JSONDeserializer
  from sagemaker.tensorflow.model import TensorFlowModel, TensorFlowPredictor
  from sagemaker.serializers import CSVSerializer, IdentitySerializer
label_desc: Use image node_id 8 for calling a global function with example usage: test_predict_with_entry_point(tfs_predictor_with_model_and_entry_point_same_tar) without return types