code: def test_deploy(sagemaker_session):
      estimator = TensorFlow(
          entry_point=SCRIPT,
          source_dir=SOURCE_DIR,
          role=ROLE,
          framework_version="2.3.0",
          py_version="py37",
          instance_count=2,
          instance_type=INSTANCE_TYPE_CPU,
          sagemaker_session=sagemaker_session,
          base_job_name="test-cifar",
      )
  
      estimator.fit("s3://mybucket/train")
  
      estimator.deploy(
          initial_instance_count=1, instance_type=INSTANCE_TYPE_CPU
      )
      image = IMAGE_URI_FORMAT_STRING.format(
          REGION, REPOSITORY, "2.3.0", PROCESSOR
      )
      sagemaker_session.create_model.assert_called_with(
          ANY,
          ROLE,
          {
              "Image": image,
              "Environment": {"SAGEMAKER_TFS_NGINX_LOGLEVEL": "info"},
              "ModelDataUrl": "s3://m/m.tar.gz",
          },
          vpc_config=None,
          enable_network_isolation=False,
          tags=None,
      )
  
imports: from __future__ import absolute_import
  import pytest
  from mock import Mock, ANY
  from sagemaker.tensorflow import TensorFlow
label_desc: Use image node_id 3 for calling a global function with example usage: test_deploy(sagemaker_session) without return types