code: def temp_mlflow_env_root(tmp_path, monkeypatch):
      env_root = tmp_path / "envs"
      env_root.mkdir(exist_ok=True)
      monkeypatch.setenv(MLFLOW_ENV_ROOT.name, str(env_root))
      return env_root
  
imports: import os
  import sys
  from collections import namedtuple
  from io import BytesIO
  from pathlib import Path
  from stat import S_IRGRP, S_IROTH, S_IRUSR, S_IXGRP, S_IXOTH, S_IXUSR
  import numpy
  import pandas
  import pytest
  import sklearn
  from sklearn.datasets import load_iris
  from sklearn.linear_model import LogisticRegression
  import mlflow
  from mlflow.environment_variables import MLFLOW_ENV_ROOT
  from mlflow.pyfunc.scoring_server import CONTENT_TYPE_JSON
  from mlflow.utils.environment import _PYTHON_ENV_FILE_NAME, _REQUIREMENTS_FILE_NAME
  from mlflow.utils.virtualenv import _is_pyenv_available, _is_virtualenv_available
  from tests.helper_functions import pyfunc_serve_and_score_model
label_desc: Use image node_id 3 for calling a global function with example usage: temp_mlflow_env_root(tmp_path, monkeypatch) and returns: env_root