code: def prepare_ray_tune(self, train_fn, tune_config, tune_callbacks):
      from ray.tune.integration.mlflow import mlflow_mixin
  
      return mlflow_mixin(train_fn), {
          **tune_config,
          "mlflow": {
              "experiment_id": self.experiment_id,
              "experiment_name": self.experiment_name,
              "tracking_uri": mlflow.get_tracking_uri(),
          },
      }
  
imports: import logging
  import os
  import queue
  import threading
  from ludwig.api_annotations import DeveloperAPI, PublicAPI
  from ludwig.callbacks import Callback
  from ludwig.constants import TRAINER
  from ludwig.globals import MODEL_HYPERPARAMETERS_FILE_NAME, TRAIN_SET_METADATA_FILE_NAME
  from ludwig.types import TrainingSetMetadataDict
  from ludwig.utils.data_utils import chunk_dict, flatten_dict, save_json, to_json_dict
  from ludwig.utils.package_utils import LazyLoader
label_desc: Use image node_id 14 for calling the MlflowCallback obj's underlying member method code with example usage: obj.prepare_ray_tune(train_fn, tune_config, tune_callbacks) and returns: mlflow_mixin,  dict