code: def _process(self):
      path = os.path.join(self._raw_directory, f"{self.__name}.mat")
      mat = scipy.io.loadmat(path)
      adj_matrix, group = mat["network"], mat["group"]
  
      y = torch.from_numpy(group.todense()).to(torch.float)
  
      row_ind, col_ind = adj_matrix.nonzero()
      edge_index = torch.stack(
          [torch.tensor(row_ind), torch.tensor(col_ind)], dim=0
      )
      edge_attr = torch.tensor(adj_matrix[row_ind, col_ind])
      data = Data(
          edge_index=edge_index, edge_attr=edge_attr, x=None, y=y
      )
      torch.save(data, list(self._processed_file_paths)[0])
  
imports: import itertools
  import os
  import scipy.io
  import torch
  import typing
  from autogl.data import Data, download_url, InMemoryStaticGraphSet
  from autogl.data.graph import GeneralStaticGraphGenerator
  from ._dataset_registry import DatasetUniversalRegistry
  from ._data_source import OnlineDataSource
  from ..None import backend
label_desc: Use image node_id 4 for calling the _MATLABMatrix obj's underlying member method code with example usage: obj._process() without return types