class_docstr: :class:`SequentialDataset` is based on :class:`~recbole.data.dataset.dataset.Dataset`,
  and provides augmentation interface to adapt to Sequential Recommendation,
  which can accelerate the data loader.
  
  Attributes:
      max_item_list_len (int): Max length of historical item list.
      item_list_length_field (str): Field name for item lists' length.
code: def __init__(self, config):
      self.max_item_list_len = config["MAX_ITEM_LIST_LENGTH"]
      self.item_list_length_field = config["ITEM_LIST_LENGTH_FIELD"]
      super().__init__(config)
      if config["benchmark_filename"] is not None:
          self._benchmark_presets()
  
file_path: RecBole/recbole/data/dataset/sequential_dataset.py
imports: import numpy
  import torch
  from recbole.data.dataset import Dataset
  from recbole.data.interaction import Interaction
  from recbole.utils.enum_type import FeatureType, FeatureSource
label_desc: Use image node_id 1 to create a new SequentialDataset object from inherited base classes: Dataset with example: obj = SequentialDataset(config)