code: def __init__(self, request: Dict, tokenizer) -> None:
      super().__init__()
      self.request = request
      self.tokenizer = tokenizer
      self.add_eos_to_encoder_input = self.request[
          "add_eos_to_encoder_input"
      ]
  
      # tokenize prompt
      self.request["tokenized_prompt"] = " ".join(
          self.tokenizer.text_to_tokens(request["prompt"])
      )
      tokens = self.tokenizer.text_to_ids(request["prompt"])
      self.request["tokens"] = torch.tensor(tokens)
      self.mask_prompt(self.request["prompt"])
  
file_path: NeMo/nemo/collections/nlp/data/language_modeling/megatron/request_dataset.py
imports: from typing import Dict, List
  import torch
  from torch.utils.data.dataset import Dataset
label_desc: Use image node_id 1 to create a new T5RequestDataset object from inherited base classes: Dataset with example: obj = T5RequestDataset(request, tokenizer)