code: def __init__(self, in_feats, out_feats, radius):
      super(LGNNCore, self).__init__()
      self.out_feats = out_feats
      self.radius = radius
  
      self.linear_prev = nn.Linear(in_feats, out_feats)
      self.linear_deg = nn.Linear(in_feats, out_feats)
      self.linear_radius = nn.ModuleList(
          [nn.Linear(in_feats, out_feats) for i in range(radius)]
      )
      self.linear_fuse = nn.Linear(in_feats, out_feats)
      self.bn = nn.BatchNorm1d(out_feats)
  
imports: import os
  import dgl
  import torch
  import torch
  import torch.nn
  import torch.nn.functional
  from dgl.data import citation_graph
  import matplotlib.pyplot
  import networkx
  import dgl.function
  from torch.utils.data import DataLoader
label_desc: Use image node_id 1 to create a new LGNNCore object from inherited base classes: nn with example: obj = LGNNCore(in_feats, out_feats, radius)