class_docstr: Dataset that returns tokenized prompts from a stream of text files.
      Args:
          prompt_tokenizer (PromptTokenizingStrategy): The prompt tokenizing method for processing the data.
          dataset (dataset.Dataset): Dataset with text files.
code: def __init__(  # pylint: disable=super-init-not-called
      self,
      prompt_tokenizer: PromptTokenizingStrategy,
      dataset: IterableDataset,
      process_count: Optional[int] = None,
      **kwargs,
  ):
      self.prompt_tokenizer = prompt_tokenizer
      self.process_count = process_count
      super().__init__(self.process(dataset).data, **kwargs)
  
file_path: axolotl/src/axolotl/datasets.py
imports: import logging
  import os
  from typing import List, Optional
  import torch
  from datasets import Dataset, IterableDataset
  from .prompt_tokenizers import PromptTokenizingStrategy
label_desc: Use image node_id 1 to create a new TokenizedPromptDataset object from inherited base classes: Dataset with example: obj = TokenizedPromptDataset(prompt_tokenizer, dataset, process_count)