code: def _build_tf(
      sagemaker_session,
      framework_version=None,
      py_version=None,
      instance_type=None,
      base_job_name=None,
      **kwargs,
  ):
      return TensorFlow(
          entry_point=SCRIPT_PATH,
          framework_version=framework_version,
          py_version=py_version,
          role=ROLE,
          sagemaker_session=sagemaker_session,
          instance_count=INSTANCE_COUNT,
          instance_type=instance_type
          if instance_type
          else INSTANCE_TYPE,
          base_job_name=base_job_name,
          **kwargs,
      )
  
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 5 for calling a global function with example usage: _build_tf(sagemaker_session, framework_version, py_version, instance_type, base_job_name) and returns: TensorFlow