code: def __init__(
      self,
      cfg,
      trainer,
      tokenizer,
      name,
      indexed_dataset,
      data_prefix,
      num_epochs,
      max_num_samples,
      max_seq_length,
      seed,
      masked_lm_prob=0.15,
      short_seq_prob=0.1,
      max_ngram_size=10,
      mean_ngram_size=None,
      geometric_dist=True,
      permutation=False,
      whole_word_masking=True,
      favor_long_ngrams=False,
      delete_mask_prob=0,
      respect_document_boundaries=True,
      documents=None,
  ):
      super().__init__(
          cfg=cfg,
          trainer=trainer,
          tokenizer=tokenizer,
          name=name,
          indexed_dataset=indexed_dataset,
          data_prefix=data_prefix,
          num_epochs=num_epochs,
          max_num_samples=max_num_samples,
          max_seq_length=max_seq_length,
          max_seq_length_dec=None,
          seed=seed,
          masked_lm_prob=masked_lm_prob,
          short_seq_prob=short_seq_prob,
          max_ngram_size=max_ngram_size,
          mean_ngram_size=mean_ngram_size,
          geometric_dist=geometric_dist,
          permutation=permutation,
          whole_word_masking=whole_word_masking,
          favor_long_ngrams=favor_long_ngrams,
          respect_document_boundaries=respect_document_boundaries,
          documents=documents,
      )
  
      # Params to store.
      self.delete_mask_prob = delete_mask_prob
  
file_path: NeMo/nemo/collections/nlp/data/language_modeling/megatron/bart_dataset.py
imports: import numpy
  from nemo.collections.nlp.data.language_modeling.megatron.dataset_utils import create_masked_lm_predictions, get_samples_mapping
  from nemo.collections.nlp.data.language_modeling.megatron.t5_dataset import T5Dataset
label_desc: Use image node_id 1 to create a new BARTDataset object from inherited base classes: T5Dataset with example: obj = BARTDataset(cfg, trainer, tokenizer, name, indexed_dataset, data_prefix, num_epochs, max_num_samples, max_seq_length, seed, masked_lm_prob, short_seq_prob, max_ngram_size, mean_ngram_size, geometric_dist, permutation, whole_word_masking, favor_long_ngrams, delete_mask_prob, respect_document_boundaries, documents)