class_docstr: A language pair dataset with multiple source sentences for
  each target sentence.
class_docstr_tok: ["A","language","pair","dataset","with","multiple","source","sentences","for","each","target","sentence","."]
code: def collater(self, samples):
      return MultisourceLanguagePairDataset.collate(
          samples,
          self.src_dict.pad(),
          self.src_dict.eos(),
          self.tgt is not None,
          self.left_pad_source,
          self.left_pad_target,
      )
  
file_path: translate/pytorch_translate/research/multisource/multisource_data.py
imports: import numpy
  import torch
  from fairseq import data
label_desc: Use image node_id 2 for calling the MultisourceLanguagePairDataset obj's underlying member method code with example usage: obj.collater(samples) and returns: MultisourceLanguagePairDataset