code: def test_hvd_gpu(
      sagemaker_session,
      tensorflow_training_latest_version,
      tensorflow_training_latest_py_version,
      tmpdir,
      **kwargs,
  ):
      if (
          Version(tensorflow_training_latest_version) >= Version("2.12")
          and kwargs["instance_type"] == "ml.p2.xlarge"
      ):
          pytest.skip(
              "P2 instances have been deprecated for sagemaker jobs starting TensorFlow 2.12"
          )
      if Version(tensorflow_training_latest_version) >= Version("2.13"):
          pytest.skip(
              "Horovod is deprecated in TensorFlow 2.13 and above"
          )
  
      _create_and_fit_estimator(
          sagemaker_session,
          tensorflow_training_latest_version,
          tensorflow_training_latest_py_version,
          kwargs["instance_type"],
          tmpdir,
      )
  
file_path: sagemaker-python-sdk/tests/integ/test_horovod.py
imports: from __future__ import absolute_import
  import json
  import os
  import pytest
  import sagemaker.utils
  import tests.integ
  from tests.integ.s3_utils import extract_files_from_s3
  from tests.integ.utils import gpu_list, retry_with_instance_list
  from sagemaker.tensorflow import TensorFlow
  from tests.integ import timeout
  from packaging.version import Version
label_desc: Use image node_id 2 for calling a global function with example usage: test_hvd_gpu(sagemaker_session, tensorflow_training_latest_version, tensorflow_training_latest_py_version, tmpdir) without return types