直接for循环,吧edge index里面的位置填充1: import torch def edge_index_to_adjacency_matrix(edge_index, num_nodes): # 创建大小为 (num_nodes, num_nodes) 的二维张量 adjacency_matrix = torch.zeros(num_nodes, num_nodes) # 根据边索引填充邻接矩阵的元素 for i, j in zip(*edge_index): adjacency...
import torch # 假设你的边索引是这样的 edge_index = torch.tensor([[0, 1, 2], [1, 0, 3]]) # 计算邻接矩阵 adj_matrix = torch.sparse.FloatTensor(edge_index, torch.ones(edge_index.size(1)), torch.Size([num_nodes, num_nodes])).to(device) # 将邻接矩阵转换为密集格式 adj_matrix =...