class_docstr: Shuffle words by no more than k positions.
class_docstr_tok: ["Shuffle","words","by","no","more","than","k","positions","."]
code: def __init__(
      self,
      dictionary,
      default_max_shuffle_distance=3,
      bpe_cont_marker="@@",
      bpe_end_marker=None,
  ):
      super().__init__(dictionary, bpe_cont_marker, bpe_end_marker)
      self.default_max_shuffle_distance = 3
  
imports: import numpy
  import torch
  from fairseq.data import data_utils
label_desc: Use image node_id 1 to create a new WordShuffle object from inherited base classes: WordNoising with example: obj = WordShuffle(dictionary, default_max_shuffle_distance, bpe_cont_marker, bpe_end_marker)