code: def test_tfs_model_with_entry_point(
      repack_model,
      model_code_key_prefix,
      sagemaker_session,
      tensorflow_inference_version,
  ):
      model = TensorFlowModel(
          "s3://some/data.tar.gz",
          entry_point="train.py",
          role=ROLE,
          framework_version=tensorflow_inference_version,
          image_uri="my-image",
          sagemaker_session=sagemaker_session,
          model_kms_key="kms-key",
      )
  
      model.prepare_container_def(INSTANCE_TYPE)
  
      model_code_key_prefix.assert_called_with(
          model.key_prefix, model.name, model.image_uri
      )
  
      repack_model.assert_called_with(
          "train.py",
          None,
          [],
          "s3://some/data.tar.gz",
          "s3://my_bucket/key-prefix/model.tar.gz",
          sagemaker_session,
          kms_key="kms-key",
      )
  
imports: from __future__ import absolute_import
  import io
  import json
  import logging
  import mock
  import pytest
  from mock import Mock, patch, ANY
  from sagemaker.serializers import CSVSerializer, IdentitySerializer
  from sagemaker.tensorflow import TensorFlow, TensorFlowModel, TensorFlowPredictor
label_desc: Use image node_id 8 for calling a global function with example usage: test_tfs_model_with_entry_point(repack_model, model_code_key_prefix, sagemaker_session, tensorflow_inference_version) without return types