code: def test_create_model(
      name_from_base,
      sagemaker_session,
      tensorflow_inference_version,
      tensorflow_inference_py_version,
  ):
      if version.Version(
          tensorflow_inference_version
      ) < version.Version("1.11"):
          pytest.skip(
              "Legacy TF version requires explicit image URI, and "
              "this logic is tested in test_create_model_with_custom_image."
          )
  
      container_log_level = '"logging.INFO"'
      base_job_name = "job"
      tf = TensorFlow(
          entry_point=SCRIPT_PATH,
          source_dir="s3://mybucket/source",
          framework_version=tensorflow_inference_version,
          py_version=tensorflow_inference_py_version,
          role=ROLE,
          sagemaker_session=sagemaker_session,
          instance_count=INSTANCE_COUNT,
          instance_type=INSTANCE_TYPE,
          container_log_level=container_log_level,
          base_job_name=base_job_name,
          enable_network_isolation=True,
          output_path="s3://mybucket/output",
      )
  
      tf._current_job_name = "doing something"
  
      model_name = "doing something else"
      name_from_base.return_value = model_name
      model = tf.create_model()
  
      name_from_base.assert_called_with("job")
  
      assert model.sagemaker_session == sagemaker_session
      assert model.framework_version == tensorflow_inference_version
      assert model.entry_point is None
      assert model.role == ROLE
      assert model.name == model_name
      assert model._container_log_level == container_log_level
      assert model.source_dir is None
      assert model.vpc_config is None
      assert model.enable_network_isolation()
  
imports: from __future__ import absolute_import
  import json
  import logging
  import os
  from mock import patch, Mock, MagicMock
  from packaging import version
  import pytest
  from sagemaker.estimator import _TrainingJob
  from sagemaker.session_settings import SessionSettings
  from sagemaker.tensorflow import TensorFlow
  from sagemaker.instance_group import InstanceGroup
  from sagemaker.workflow.parameters import ParameterString, ParameterBoolean
  from tests.unit import DATA_DIR
label_desc: Use image node_id 6 for calling a global function with example usage: test_create_model(name_from_base, sagemaker_session, tensorflow_inference_version, tensorflow_inference_py_version) without return types