class_docstr: A wrapper around an ensemble of models.
class_docstr_tok: ["A","wrapper","around","an","ensemble","of","models","."]
code: def __init__(self, models):
      super().__init__()
      self.models = torch.nn.ModuleList(models)
      self.bos = self.models[0].decoder.dictionary.bos()
      self.eos = self.models[0].decoder.dictionary.eos()
      self.pad = self.models[0].decoder.dictionary.pad()
      self.unk = self.models[0].decoder.dictionary.unk()
      self.encoder = _EnsembleModelEncoder(self.models)
  
imports: import math
  import torch
  import torch.nn.functional
  from fairseq.models.nat import _apply_del_words, _apply_ins_masks, _apply_ins_words, _fill, _skip, _skip_encoder_out
label_desc: Use image node_id 1 to create a new BasicEnsembleModel object from inherited base classes: torch.nn with example: obj = BasicEnsembleModel(models)