def forward(self, edge_subgraph, x): with edge_subgraph.local_scope(): edge_subgraph.ndata['x'] = x for etype in edge_subgraph.canonical_etypes: edge_subgraph.apply_edges(self.apply_edges, etype=etype) return edge_subgraph.edata['score'] class Model(nn.Module): def __init__(self...
predictor(edge_subgraph, x) 6 实例化模型,并定义预测函数 device = th.device("cuda" if th.cuda.is_available() else "cpu") print("device: {}".format(device)) model = MyModel(64, args.num_hidden, args.num_hidden, 18, g.num_nodes()) model = model.to(device) loss_fcn = nn....
edata_schemes={})>>># Node IDs>>>print(g.nodes()) tensor([0,1,2,3])>>># Edge end nodes>>>print(g.edges()) (tensor([0,0,0,1]), tensor([1,2,3,3]))>>>print(g.edges(form='all'))# 打印边的源和目的节点,以及边的序号(tensor([0,0,0,1]), tensor([1,2,3,3]), ...
dgl.node_subgraph, dgl.edge_subgraph, dgl.in_subgraph 和dgl.out_subgraph都增加一个relabel_nodes参数,以允许图形压缩 dgl.node_subgraph,dgl.edge_subgraph,dgl.in_subgraphanddgl.out_subgraphall have arelabel_nodesargument to allow graph compaction (i.e. removing the nodes with no edges). (#2929)...
BatchedDGLGraph 和 DGLSubGraph 类合并进去 DGLGraph 类。 构建DGLGraph 时不再需要 is_multigraph 参数。 DGL | 基于深度学习框架DGL的分子图初探 DGL | 基于深度图学习框架DGL的分子图生成 DGL | 基于JTNN可视化给定分子的邻居分子 DGL&RDKit|基于GCN与基于3D描述符的分子溶解度预测模型对比 ...
each subgraph is stored as aDGLGraphobject. The original node/edge IDs before reshuffling are stored in the field of ‘orig_id’ in the node/edge data of the subgraphs. The node data dgl.NID and the edge data dgl.EID of the subgraphs store new node/edge IDs of the full graph after ...
在dgl.nn 下的所有 GNN modules 现在都支持 Homogeneous Graph 和 Bipartite Graph。 DGLHeteroGraph 有了更快的 pickling/unpickling 实现。 实现了新的加载和存储 DGLHeteroGraph 的 API。 BatchedDGLGraph 和 DGLSubGraph 类合并进去 DGLGraph 类。 构建DGLGraph 时不再需要 is_multigraph 参数。
each subgraph is stored as aDGLGraphobject. The original node/edge IDs before reshuffling are stored in the field of ‘orig_id’ in the node/edge data of the subgraphs. The node data dgl.NID and the edge data dgl.EID of the subgraphs store new node/edge IDs of the full graph after ...
1、创建图 1.1、同质图 1.1.1、图表示 dgl创建图的时候,使用两组节点列表表示边,其中每组节点对应位置的节点表示边的两个端点,例如: 在没有明确指定节点的情况下,d...
https://pytorch-geometric.readthedocs.io/en/latest/modules/utils.html#torch_geometric.utils.subgraph ️ 2 Author Ziyang-Yu commented Nov 22, 2024 Thanks for your reply. I have looked into it. But it only returns (edge_index, edge_attr), which seems missing node features.Sign...