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.
docstr: Change feat format from :class:`pandas.DataFrame` to :class:`Interaction`,
  then perform data augmentation.
docstr_tok: ["Change","feat","format","from",":","class",":","`","pandas.DataFrame","`","to",":","class",":","`","Interaction","`",",","then","perform","data","augmentation","."]
code: def _change_feat_format(self):
      """Change feat format from :class:`pandas.DataFrame` to :class:`Interaction`,
      then perform data augmentation.
      """
      super()._change_feat_format()
  
      if self.config["benchmark_filename"] is not None:
          return
      self.logger.debug("Augmentation for sequential recommendation.")
      self.data_augmentation()
  
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 2 for calling the SequentialDataset obj's underlying member method code with example usage: obj._change_feat_format() without return types