class_docstr: A wrapper around TokenBlockDataset for BART dataset.
  
  Args:
      dataset (TokenBlockDataset): dataset to wrap
      sizes (List[int]): sentence lengths
      vocab (~fairseq.data.Dictionary): vocabulary
      mask_idx (int): dictionary index used for masked token
      mask_whole_words: only mask whole words. This should be a byte mask
          over vocab indices, indicating whether it is the beginning of a
          word. We will extend any mask to encompass the whole word.
      shuffle (bool, optional): shuffle the elements before batching.
        Default: ``True``
      seed: Seed for random number generator for reproducibility.
class_docstr_tok: ["A","wrapper","around","TokenBlockDataset","for","BART","dataset",".","Args",":","dataset","(","TokenBlockDataset",")",":","dataset","to","wrap","sizes","(","List","[","int","]",")",":","sentence","lengths","vocab","(","~fairseq.data.Dictionary",")",":","vocabulary","mask_idx","(","int",")",":","dictionary","index","used","for","masked","token","mask_whole_words",":","only","mask","whole","words",".","This","should","be","a","byte","mask","over","vocab","indices",",","indicating","whether","it","is","the","beginning","of","a","word",".","We","will","extend","any","mask","to","encompass","the","whole","word",".","shuffle","(","bool",",","optional",")",":","shuffle","the","elements","before","batching",".","Default",":","``","True","``","seed",":","Seed","for","random","number","generator","for","reproducibility","."]
docstr: Return an example's size as a float or tuple. This value is used when
  filtering a dataset with ``--max-positions``.
docstr_tok: ["Return","an","example","'s","size","as","a","float","or","tuple",".","This","value","is","used","when","filtering","a","dataset","with","``","--","max-positions","``","."]
code: def size(self, index):
      """Return an example's size as a float or tuple. This value is used when
      filtering a dataset with ``--max-positions``."""
      return self.sizes[index]
  
imports: import math
  import numpy
  import torch
  from .None import FairseqDataset, data_utils
label_desc: Use image node_id 14 for calling the DenoisingDataset obj's underlying member method code with example usage: obj.size(index) and returns: self