code: def get_model_version_from_model_uri(model_uri):
      """
      Helper function to fetch a model version from a model uri of the form
      models:/<model_name>/<model_version/stage/latest>.
      """
      import mlflow
      from mlflow import MlflowClient
  
      databricks_profile_uri = (
          get_databricks_profile_uri_from_artifact_uri(model_uri)
          or mlflow.get_registry_uri()
      )
      client = MlflowClient(registry_uri=databricks_profile_uri)
      (name, version) = get_model_name_and_version(client, model_uri)
      return client.get_model_version(name, version)
  
imports: import datetime
  import decimal
  import json
  import logging
  import os
  from copy import deepcopy
  from typing import Any, Dict, List, Optional, Union
  import numpy
  import pandas
  from mlflow.exceptions import INVALID_PARAMETER_VALUE, MlflowException
  from mlflow.models import Model
  from mlflow.store.artifact.utils.models import get_model_name_and_version
  from mlflow.types import DataType, ParamSchema, ParamSpec, Schema, TensorSpec
  from mlflow.types.schema import Array, Object, Property
  from mlflow.types.utils import TensorsNotSupportedException, _infer_param_schema, clean_tensor_type
  from mlflow.utils.annotations import experimental
  from mlflow.utils.proto_json_utils import NumpyEncoder, dataframe_from_parsed_json, parse_tf_serving_input
  from mlflow.utils.uri import get_databricks_profile_uri_from_artifact_uri
label_desc: Use image node_id 22 for calling a global function with example usage: get_model_version_from_model_uri(model_uri) and returns: client