code: def test_log_and_load_model_persists_and_restores_model_successfully(
      tmp_path, monkeypatch
  ):
      mlflow.set_tracking_uri(tmp_path.joinpath("mlruns").as_uri())
      monkeypatch.chdir(tmp_path)
      model_data_info = save_or_log_tf_model_by_mlflow128(
          tmp_path, "iris", "log_model"
      )
      model_uri = f"runs:/{model_data_info.run_id}/model"
      mlflow.tensorflow.load_model(model_uri=model_uri)
  
imports: import collections
  import json
  import os
  import iris_data_utils
  import numpy
  import pandas
  import pandas.testing
  import pytest
  import tensorflow
  import mlflow
  import mlflow.pyfunc.scoring_server
  from mlflow import pyfunc
  from mlflow.store.artifact.s3_artifact_repo import S3ArtifactRepository
  from mlflow.tensorflow import _TF2Wrapper
  from mlflow.utils.conda import get_or_create_conda_env
  from mlflow.utils.environment import _mlflow_conda_env
  from tests.helper_functions import assert_array_almost_equal, pyfunc_serve_and_score_model
label_desc: Use image node_id 6 for calling a global function with example usage: test_log_and_load_model_persists_and_restores_model_successfully(tmp_path, monkeypatch) without return types