class_docstr: GLUE Dataset in a text-to-text format.
code: def make_history_mask_3d(self, block):
      batch, length = block.shape
      arange = np.arange(length)
      history_mask = (arange[None,] <= arange[:, None])[None,]
      history_mask = np.repeat(history_mask, batch, 0)
      return history_mask
  
imports: import os
  import pickle
  from typing import Dict, List, Optional, Union
  import numpy
  import torch
  from nemo.collections.common.tokenizers.tokenizer_spec import TokenizerSpec
  from nemo.collections.nlp.data.glue_benchmark.data_processors import ColaProcessor, MnliMismatchedProcessor, MnliProcessor, MrpcProcessor, QnliProcessor, QqpProcessor, RteProcessor, Sst2Processor, StsbProcessor, WnliProcessor, XNLIProcessor
  from nemo.core.classes import Dataset
  from nemo.core.neural_types import CategoricalValuesType, ChannelType, MaskType, NeuralType, RegressionValuesType
  from nemo.utils import logging
label_desc: Use image node_id 6 for calling the TextToTextGLUEDataset obj's underlying member method code with example usage: obj.make_history_mask_3d(block) and returns: history_mask