class_docstr: Ensemble class that uses bagging for ensembling intent-slot models.
  
  Args:
      config (Config): Configuration object specifying all the
          parameters of BaggingIntentSlotEnsemble.
      models (List[Model]): List of intent-slot model objects.
  
  Attributes:
      use_crf (bool): Whether to use CRF for word tagging task.
      output_layer (IntentSlotOutputLayer): Output layer of intent-slot
          model responsible for computing loss and predictions.
code: def __init__(
      self, config: Config, models: List[Model], *args, **kwargs
  ) -> None:
      super().__init__(config, models)
      self.use_crf = isinstance(
          self.output_layer.word_output, CRFOutputLayer
      )
      log_class_usage(__class__)
  
file_path: pytext/pytext/models/ensembles/bagging_intent_slot_ensemble.py
imports: from typing import Dict, List, Tuple
  import torch
  from pytext.models.joint_model import IntentSlotModel
  from pytext.models.model import Model
  from pytext.models.output_layers import CRFOutputLayer
  from pytext.utils.usage import log_class_usage
  from .ensemble import EnsembleModel
label_desc: Use image node_id 1 to create a new BaggingIntentSlotEnsembleModel object from inherited base classes: EnsembleModel with example: obj = BaggingIntentSlotEnsembleModel(config, models)