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","."]
code: def __init__(self):
      import mlflow
  
      self._mlflow = mlflow
      self.experiment_id = None
  
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 1 to create a new _MLflowLoggerUtil object  with example: obj = _MLflowLoggerUtil()