code: def _read_registered_model_meta(model_path):
      model_meta = {}
      if os.path.isfile(
          os.path.join(model_path, REGISTERED_MODEL_META_FILE_NAME)
      ):
          model_meta = read_yaml(
              model_path, REGISTERED_MODEL_META_FILE_NAME
          )
  
      return model_meta
  
imports: import logging
  import multiprocessing
  import os
  import shutil
  import signal
  import sys
  from pathlib import Path
  from subprocess import Popen, check_call
  import mlflow
  import mlflow.version
  from mlflow import mleap, pyfunc
  from mlflow.environment_variables import MLFLOW_DEPLOYMENT_FLAVOR_NAME, MLFLOW_DISABLE_ENV_CREATION
  from mlflow.models import Model
  from mlflow.models.model import MLMODEL_FILE_NAME
  from mlflow.pyfunc import _extract_conda_env, mlserver, scoring_server
  from mlflow.store.artifact.models_artifact_repo import REGISTERED_MODEL_META_FILE_NAME
  from mlflow.utils import env_manager
  from mlflow.utils.file_utils import read_yaml
  from mlflow.utils.virtualenv import _get_or_create_virtualenv
  from mlflow.version import VERSION
label_desc: Use image node_id 5 for calling a global function with example usage: _read_registered_model_meta(model_path) and returns: model_meta