class_docstr: Multilingual decoder.
class_docstr_tok: ["Multilingual","decoder","."]
code: def __init__(
      self, dictionary, decoders, hidden_dim, rescale_grads=False
  ):
      super().__init__(dictionary)
      self.decoders = nn.ModuleList(decoders)
      self.hidden_dim = hidden_dim
      self.max_vocab_size = len(dictionary)
      if rescale_grads and len(decoders) > 1:
          register_hooks(self, decoders)
  
imports: import torch
  import torch.nn
  from fairseq.models import FairseqEncoder, FairseqIncrementalDecoder
  from pytorch_translate import utils
  from pytorch_translate.data import data
label_desc: Use image node_id 1 to create a new MultilingualDecoder object from inherited base classes: FairseqIncrementalDecoder with example: obj = MultilingualDecoder(dictionary, decoders, hidden_dim, rescale_grads)