Function normalize_adjacency_matrix

code/utils.py:450–471

(data,args)

def normalize_adjacency_matrix(data,args):
    edge_index = data.data.edge_index
    num_nodes = data.data.x.shape[0]

    
    edge_index_self_loops = torch.stack([torch.arange(num_nodes), torch.arange(num_nodes)], dim=0)
    edge_index = torch.cat([edge_index, edge_index_self_loops], dim=1)

  
    adj = torch.sparse_coo_tensor(edge_index, torch.ones(edge_index.shape[1]), (num_nodes, num_nodes))

    
    deg = torch.sparse.sum(adj, dim=1).to_dense()
    deg_inv_sqrt = deg.pow(-0.5)
    deg_inv_sqrt[deg_inv_sqrt == float('inf')] = 0

    
    adj_normalized = adj.coalesce()  
    deg_inv_sqrt_mat = torch.sparse_coo_tensor(torch.arange(num_nodes).unsqueeze(0).repeat(2, 1), deg_inv_sqrt, (num_nodes, num_nodes))
    adj_normalized = torch.sparse.mm(deg_inv_sqrt_mat, torch.sparse.mm(adj_normalized, deg_inv_sqrt_mat))

    return adj_normalized