code: def __init__(
      self,
      bagged_ensemble_model,
      X: DataFrame,
      y: Series,
      sample_weight,
      time_limit: float,
      time_start: float,
      models: list,
      oof_pred_proba: ndarray,
      oof_pred_model_repeats: ndarray,
      save_folds: bool,
  ):
      super().__init__(
          bagged_ensemble_model,
          X,
          y,
          sample_weight,
          time_limit,
          time_start,
          models,
          oof_pred_proba,
          oof_pred_model_repeats,
          save_folds,
      )
      # ray.util.connect("localhost:10001")
      # ray.init(address='auto')
      print("init")
      ray.init()
  
file_path: autogluon/core/src/autogluon/core/models/ensemble/ray_parallel_fold_fitting_strategy.py
imports: import time
  import ray
  from numpy import ndarray
  from pandas import DataFrame, Series
  from ray.util import placement_group, placement_group_table
  from autogluon.core.models.ensemble.fold_fitting_strategy import SequentialLocalFoldFittingStrategy
label_desc: Use image node_id 1 to create a new RayParallelFitter object from inherited base classes: SequentialLocalFoldFittingStrategy with example: obj = RayParallelFitter(bagged_ensemble_model, X, y, sample_weight, time_limit, time_start, models, oof_pred_proba, oof_pred_model_repeats, save_folds)