code: def __init__(self, in_size, out_size):
      super().__init__()
      self.out_size = out_size
      self.weight = nn.Linear(in_size, out_size, bias=False)
  
file_path: dgl/examples/sparse/gcnii.py
imports: import math
  import dgl.sparse
  import torch
  import torch.nn
  import torch.nn.functional
  from dgl.data import CoraGraphDataset
  from torch.optim import Adam
label_desc: Use image node_id 1 to create a new GCNIIConvolution object from inherited base classes: nn with example: obj = GCNIIConvolution(in_size, out_size)