class_docstr: Util class for setting up and logging to MLflow.
  
  Use this util for any library that needs MLflow logging/tracking logic
  such as Ray Tune or Ray Train.
class_docstr_tok: ["Util","class","for","setting","up","and","logging","to","MLflow",".","Use","this","util","for","any","library","that","needs","MLflow","logging\/tracking","logic","such","as","Ray","Tune","or","Ray","Train","."]
docstr: Check if run with the provided id exists.
docstr_tok: ["Check","if","run","with","the","provided","id","exists","."]
code: def _run_exists(self, run_id: str) -> bool:
      """Check if run with the provided id exists."""
      from mlflow.exceptions import MlflowException
  
      try:
          self._mlflow.get_run(run_id=run_id)
          return True
      except MlflowException:
          return False
  
file_path: ray/python/ray/air/_internal/mlflow.py
imports: import logging
  import os
  from packaging import version
  from copy import deepcopy
  from typing import TYPE_CHECKING, Dict, Optional
  from ray._private.dict import flatten_dict
label_desc: Use image node_id 7 for calling the _MLflowLoggerUtil obj's underlying member method code with example usage: obj._run_exists(run_id) and returns: True, False