class_docstr: Dataset containing sentences and their blocks for an inverse cloze task.
class_docstr_tok: ["Dataset","containing","sentences","and","their","blocks","for","an","inverse","cloze","task","."]
docstr: Get empty block and title - used in REALM pretraining
docstr_tok: ["Get","empty","block","and","title","-","used","in","REALM","pretraining"]
code: def get_null_block(self):
      """Get empty block and title - used in REALM pretraining"""
      block, title = [], []
      block_tokens, block_pad_mask = self.concat_and_pad_tokens(
          block, title
      )
  
      return block_tokens, block_pad_mask
  
file_path: colossalai/examples/tutorial/sequence_parallel/data/datasets/ict_dataset.py
imports: import itertools
  import random
  import numpy
  from megatron import get_args, get_tokenizer
  from megatron.data.dataset_utils import get_indexed_dataset_
  from megatron.data.realm_dataset_utils import get_block_samples_mapping
  from torch.utils.data import Dataset
label_desc: Use image node_id 5 for calling the ICTDataset obj's underlying member method code with example usage: obj.get_null_block() and returns: block_tokens,  block_pad_mask