code: def _get_mc_dropout_modules(self) -> set:
      def recurse_children(children, acc):
          for module in children:
              if isinstance(module, MonteCarloDropout):
                  acc.add(module)
              acc = recurse_children(module.children(), acc)
          return acc
  
      return recurse_children(self.children(), set())
  
imports: from abc import ABC, abstractmethod
  from functools import wraps
  from typing import Any, Dict, Optional, Sequence, Tuple, Union
  import pytorch_lightning
  import torch
  import torch.nn
  import torchmetrics
  from joblib import Parallel, delayed
  from darts.logging import get_logger, raise_if, raise_log
  from darts.models.components.layer_norm_variants import RINorm
  from darts.timeseries import TimeSeries
  from darts.utils.likelihood_models import Likelihood
  from darts.utils.timeseries_generation import _build_forecast_series
  from darts.utils.torch import MonteCarloDropout
label_desc: Use image node_id 14 for calling the PLForecastingModule obj's underlying member method code with example usage: obj._get_mc_dropout_modules() and returns: recurse_children, acc