code: def test_create_model_with_custom_image(sagemaker_session):
      container_log_level = '"logging.INFO"'
      source_dir = "s3://mybucket/source"
      custom_image = "tensorflow:1.0"
      tf = TensorFlow(
          entry_point=SCRIPT_PATH,
          role=ROLE,
          sagemaker_session=sagemaker_session,
          instance_count=INSTANCE_COUNT,
          instance_type=INSTANCE_TYPE,
          image_uri=custom_image,
          container_log_level=container_log_level,
          base_job_name="job",
          source_dir=source_dir,
      )
  
      job_name = "doing something"
      tf.fit(inputs="s3://mybucket/train", job_name=job_name)
      model = tf.create_model()
  
      assert model.image_uri == custom_image
  
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 8 for calling a global function with example usage: test_create_model_with_custom_image(sagemaker_session) without return types