class_docstr: Args:
      dataset_path: the path to the jsonl file
code: def __init__(
      self,
      dataset_path: str,
      nougat_model: PreTrainedModel,
      max_length: int,
      split: str = "train",
      root_name: str = "arxiv",
  ):
      super().__init__()
      self.nougat_model = nougat_model
      self.max_length = max_length
      self.split = split
      self.perturb = (
          "NOUGAT_PERTURB" in os.environ
          and os.environ["NOUGAT_PERTURB"]
      )
      # TODO improve naming conventions
      template = "%s"
      self.dataset = SciPDFDataset(
          dataset_path,
          split=self.split,
          template=template,
          root_name=root_name,
      )
      self.dataset_length = len(self.dataset)
  
imports: import logging
  import os
  from math import prod
  from pathlib import Path
  from functools import partial
  import random
  from typing import Dict, Tuple, Callable
  from PIL import Image, UnidentifiedImageError
  from typing import List, Optional
  import torch
  import pypdf
  import orjson
  from torch.utils.data import Dataset
  from transformers.modeling_utils import PreTrainedModel
  from nougat.dataset.rasterize import rasterize_paper
label_desc: Use image node_id 1 to create a new NougatDataset object from inherited base classes: Dataset with example: obj = NougatDataset(dataset_path, nougat_model, max_length, split, root_name)