code: def fit(self, dataset):
      dataset = copy.deepcopy(dataset)
      with torch.no_grad():
          for i, data in enumerate(dataset):
              dataset[i] = self.__postprocess(
                  self._postprocess(
                      self._fit(
                          self._preprocess(self.__preprocess(data))
                      )
                  )
              )
      return dataset
  
file_path: AutoGL/autogl/module/feature/_base_feature_engineer/_base_feature_engineer_dgl.py
imports: import copy
  import torch
  import typing
  import dgl
  from autogl.data.graph import GeneralStaticGraph
  import autogl.data.graph.utils.conversion
  from .None import _base_feature_engineer
label_desc: Use image node_id 3 for calling the BaseFeatureEngineer obj's underlying member method code with example usage: obj.fit(dataset) and returns: dataset