code: def __init__(self, layer_sizes, batch_norm_mm=0.99):
      super(GCN, self).__init__()
  
      self.layers = nn.ModuleList()
      for in_dim, out_dim in zip(layer_sizes[:-1], layer_sizes[1:]):
          self.layers.append(GraphConv(in_dim, out_dim))
          self.layers.append(
              BatchNorm1d(out_dim, momentum=batch_norm_mm)
          )
          self.layers.append(nn.PReLU())
  
imports: import copy
  import dgl
  import torch
  from dgl.nn.pytorch.conv import GraphConv, SAGEConv
  from torch import nn
  from torch.nn import BatchNorm1d, Parameter
  from torch.nn.init import ones_, zeros_
label_desc: Use image node_id 1 to create a new GCN object from inherited base classes: nn with example: obj = GCN(layer_sizes, batch_norm_mm)