class_docstr: Extension of fairseq.data.BacktranslationDataset where each example
  has a weight in [0.0, 1.0], which will be used to weigh the loss.
  
  Args:
      weights (list): list of per example weight values; each example
      has a weight in [0.0, 1.0]. Alternatively, when weights consists of a
      single value, that value is broadcast as weight to all examples. [0.0]
      gives 0 weight to all examples.
code: def __getattr__(self, attr):
      if attr in self.__dict__:
          return getattr(self, attr)
      return getattr(self.dataset, attr)
  
imports: import torch
  from fairseq import data
label_desc: Use image node_id 2 for calling the WeightedBacktranslationDataset obj's underlying member method code with example usage: obj.__getattr__(attr) and returns: getattr, getattr