code: def test_tfs_model_accelerator(
      retrieve_image_uri, sagemaker_session, tensorflow_eia_version
  ):
      model = TensorFlowModel(
          "s3://some/data.tar.gz",
          role=ROLE,
          framework_version=tensorflow_eia_version,
          sagemaker_session=sagemaker_session,
      )
      cdef = model.prepare_container_def(
          INSTANCE_TYPE, accelerator_type=ACCELERATOR_TYPE
      )
      retrieve_image_uri.assert_called_with(
          "tensorflow",
          REGION,
          version=tensorflow_eia_version,
          instance_type=INSTANCE_TYPE,
          accelerator_type=ACCELERATOR_TYPE,
          image_scope="inference",
          serverless_inference_config=None,
      )
      assert IMAGE == cdef["Image"]
  
      predictor = model.deploy(INSTANCE_COUNT, INSTANCE_TYPE)
      assert isinstance(predictor, TensorFlowPredictor)
  
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 4 for calling a global function with example usage: test_tfs_model_accelerator(retrieve_image_uri, sagemaker_session, tensorflow_eia_version) without return types