class_docstr: Denoising task for applying sequence to sequence denoising. (ie. BART)
docstr: Return the source :class:`~fairseq.data.Dictionary`.
docstr_tok: ["Return","the","source",":","class",":","`","~fairseq.data.Dictionary","`","."]
code: def source_dictionary(self):
      """Return the source :class:`~fairseq.data.Dictionary`."""
      return self.dictionary
  
imports: import logging
  import os
  from dataclasses import dataclass, field
  from typing import Any, Optional
  import numpy
  from omegaconf import II, MISSING
  from fairseq import utils
  from fairseq.data import AppendTokenDataset, DenoisingDataset, Dictionary, IdDataset, NestedDictionaryDataset, NumelDataset, PadDataset, PrependTokenDataset, StripTokenDataset, TokenBlockDataset, data_utils
  from fairseq.data.encoders.utils import get_whole_word_mask
  from fairseq.data.shorten_dataset import maybe_shorten_dataset
  from fairseq.dataclass import ChoiceEnum, FairseqDataclass
  from fairseq.tasks import FairseqTask, register_task
  from ..data.indexed_dataset import get_available_dataset_impl
label_desc: Use image node_id 7 for calling the DenoisingTask obj's underlying member method code with example usage: obj.source_dictionary() and returns: self