class_docstr: Multilingual encoder.
  
  This encoder consists of n separate encoders. A language token ID at the
  begin of the source sentence selects the encoder to use.
class_docstr_tok: ["Multilingual","encoder",".","This","encoder","consists","of","n","separate","encoders",".","A","language","token","ID","at","the","begin","of","the","source","sentence","selects","the","encoder","to","use","."]
docstr: Maximum input length supported by the encoder.
docstr_tok: ["Maximum","input","length","supported","by","the","encoder","."]
code: def max_positions(self):
      """Maximum input length supported by the encoder."""
      return int(1e5)
  
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 4 for calling the MultilingualEncoder obj's underlying member method code with example usage: obj.max_positions() and returns: int