code: def fit_transform(self, dataset, inplace: bool = True):
      if not inplace:
          dataset = copy.deepcopy(dataset)
      with torch.no_grad():
          for i, data in enumerate(dataset):
              dataset[i] = self._postprocess(
                  self._transform(self._fit(self._preprocess(data)))
              )
      return dataset
  
imports: import copy
  import torch
  import typing
  import autogl.data.graph
label_desc: Use image node_id 3 for calling the DataPreprocessor obj's underlying member method code with example usage: obj.fit_transform(dataset, inplace) and returns: dataset