class_docstr: The metadata of a logged MLflow Model.
class_docstr_tok: ["The","metadata","of","a","logged","MLflow","Model","."]
docstr: The ``model_uri`` of the logged model in the format ``'runs:/<run_id>/<artifact_path>'``.
  
  :getter: Gets the uri path of the logged model from the uri `runs:/<run_id>` path
      encapsulation
  :type: str
docstr_tok: ["The","``","model_uri","``","of","the","logged","model","in","the","format","``","'runs",":","\/","<","run_id",">","\/","<","artifact_path",">","'","``",".",":","getter",":","Gets","the","uri","path","of","the","logged","model","from","the","uri","`","runs",":","\/","<","run_id",">","`","path","encapsulation",":","type",":","str"]
code: def model_uri(self):
      """
      The ``model_uri`` of the logged model in the format ``'runs:/<run_id>/<artifact_path>'``.
  
      :getter: Gets the uri path of the logged model from the uri `runs:/<run_id>` path
          encapsulation
      :type: str
      """
      return self._model_uri
  
imports: import json
  import logging
  import os
  import uuid
  import warnings
  from datetime import datetime
  from typing import Any, Callable, Dict, Optional, Union
  import yaml
  import mlflow
  from mlflow.artifacts import download_artifacts
  from mlflow.exceptions import MlflowException
  from mlflow.tracking._model_registry import DEFAULT_AWAIT_MAX_SLEEP_SECONDS
  from mlflow.tracking._tracking_service.utils import _resolve_tracking_uri
  from mlflow.utils.annotations import experimental
  from mlflow.utils.databricks_utils import get_databricks_runtime
  from mlflow.utils.file_utils import TempDir
  from mlflow.utils.uri import get_uri_scheme
label_desc: Use image node_id 4 for calling the ModelInfo obj's underlying member method code with example usage: obj.model_uri() and returns: self