code: def __init__(self):
      super().__init__()
      self.conv1 = MixHopConv(
          dataset.num_features, 60, powers=[0, 1, 2]
      )
      self.norm1 = BatchNorm(3 * 60)
  
      self.conv2 = MixHopConv(3 * 60, 60, powers=[0, 1, 2])
      self.norm2 = BatchNorm(3 * 60)
  
      self.conv3 = MixHopConv(3 * 60, 60, powers=[0, 1, 2])
      self.norm3 = BatchNorm(3 * 60)
  
      self.lin = Linear(3 * 60, dataset.num_classes)
  
file_path: pytorch_geometric/examples/mixhop.py
imports: import os.path
  import torch
  import torch.nn.functional
  from torch_geometric.datasets import Planetoid
  from torch_geometric.nn import BatchNorm, Linear, MixHopConv
label_desc: Use image node_id 1 to create a new MixHop object from inherited base classes: torch.nn with example: obj = MixHop()