class_docstr: GLUE Dataset in a text-to-text format.
docstr: Processes GLUE datasets
  Args:
      file_name: path to file
      task_name: GLUE task name
      tokenizer: such as AutoTokenizer
      max_seq_length: max sequence length minus 2 for [CLS] and [SEP]
      use_cache: whether to use data cache
      prefix_override: if you want to override default prompt for this task specify this via a string.
      pad_to_max_length: If true, pad to the maximum length.
docstr_tok: ["Processes","GLUE","datasets","Args",":","file_name",":","path","to","file","task_name",":","GLUE","task","name","tokenizer",":","such","as","AutoTokenizer","max_seq_length",":","max","sequence","length","minus","2","for","[","CLS","]","and","[","SEP","]","use_cache",":","whether","to","use","data","cache","prefix_override",":","if","you","want","to","override","default","prompt","for","this","task","specify","this","via","a","string",".","pad_to_max_length",":","If","true",",","pad","to","the","maximum","length","."]
code: def __init__(
      self,
      file_name: str,
      task_name: str,
      tokenizer: TokenizerSpec,
      max_seq_length: int,
      max_seq_length_decoder: int = 128,
      use_cache: bool = True,
      prefix_override: str = None,
      pad_to_max_length: bool = True,
  ):
      """
      Processes GLUE datasets
      Args:
          file_name: path to file
          task_name: GLUE task name
          tokenizer: such as AutoTokenizer
          max_seq_length: max sequence length minus 2 for [CLS] and [SEP]
          use_cache: whether to use data cache
          prefix_override: if you want to override default prompt for this task specify this via a string.
          pad_to_max_length: If true, pad to the maximum length.
      """
      super().__init__(
          file_name,
          task_name,
          tokenizer,
          max_seq_length,
          use_cache,
          compute_features=False,
      )
      self.max_seq_length = max_seq_length
      self.max_seq_length_decoder = max_seq_length_decoder
      self.pad_to_max_length = pad_to_max_length
      self.processor = processors[self.task_name]()
      self.prefix_override = prefix_override
      self.features = self.convert_examples_to_features()
  
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 2 to create a new TextToTextGLUEDataset object from inherited base classes: GLUEDataset with example: obj = TextToTextGLUEDataset(file_name, task_name, tokenizer, max_seq_length, max_seq_length_decoder, use_cache, prefix_override, pad_to_max_length)