code: def __init__(
      self,
      root,
      transform=None,
      pre_transform=None,
      pre_filter=None,
      split="train",
  ):
      self.split = split
      self.root = root
  
      super(FOLDdataset, self).__init__(
          root, transform, pre_transform, pre_filter
      )
  
      self.transform, self.pre_transform, self.pre_filter = (
          transform,
          pre_transform,
          pre_filter,
      )
      self.data, self.slices = torch.load(self.processed_paths[0])
  
imports: import os.path
  import h5py
  import numpy
  import warnings
  from tqdm import tqdm
  import torch
  import torch.nn.functional
  from torch_geometric.data import Data
  from torch_geometric.data import InMemoryDataset
label_desc: Use image node_id 1 to create a new FOLDdataset object from inherited base classes: InMemoryDataset with example: obj = FOLDdataset(root, transform, pre_transform, pre_filter, split)