class_docstr: Sequence to Sequence Dataset in memory.
  Similar to SequenceToSequenceDataset but with the same input format as GPTSFTDataset
class_docstr_tok: ["Sequence","to","Sequence","Dataset","in","memory",".","Similar","to","SequenceToSequenceDataset","but","with","the","same","input","format","as","GPTSFTDataset"]
code: def __len__(self):
      return len(self.indexed_dataset)
  
file_path: NeMo/nemo/collections/nlp/data/language_modeling/megatron/t5_sft_dataset.py
imports: import json
  import os
  from typing import Optional
  import numpy
  import torch
  from datasets import load_dataset
  from nemo.collections.common.tokenizers.tokenizer_spec import TokenizerSpec
  from nemo.collections.nlp.data.language_modeling.text_memmap_dataset import JSONLMemMapDataset
  from nemo.core.classes import Dataset
  from nemo.utils import logging
label_desc: Use image node_id 4 for calling the T5SFTDataset obj's underlying member method code with example usage: obj.__len__() and returns: len