hetero_graph.nodes['user'].data['train_mask'] = torch.zeros(unique_userid_count, dtype=torch.bool).bernoulli(1.0)all_userid_idx = torch.nonzero(hetero_graph.nodes['user'].data['train_mask'], as_tuple=False).squeeze()user_loader = dgl.dataloading.NodeDataLoader(hetero_graph, {"user"...
4)fromdgl.data.utilsimportsave_graphsgraph_labels={"glabel":torch.tensor([0,1])}save_graphs("...
sampler import Uniformimport numpy as npimport pandas as pdimport itertoolsimport osimport tqdmfrom dgl import save_graphs, load_graphsimport dgl.function as fnimport torchimport dglimport torch.nn.functional as Ffrom dgl.nn.pytorch import GraphConv, SAGEConv, HeteroGraphConvfrom dgl.utils import ...
fromdgl.data.utilsimportdownload,check_sha1defdownload(self):# 存储文件的路径,请确保使用与原始文件名相同的后缀gz_file_path=os.path.join(self.raw_dir,self.name+'.csv.gz')# 下载文件download(self.url,path=gz_file_path)# 检查 SHA-1ifnotcheck_sha1(gz_file_path,self._sha1_str):raiseUserW...
from dgl import save_graphs, load_graphsimport dgl.function as fnimport torchimport dglimport torch.nn.functional as Ffrom dgl.nn.pytorch import GraphConv, SAGEConv, HeteroGraphConvfrom dgl.utils import expand_as_pairimport tqdmfrom collections import defaultdictimport torch as thimport dgl.nn as...
edata_schemes={}) 也可以使用save_graphs和load_graphs api来保存和加载DGL二进制图文件。 1.5 异构图 在DGL中每条关系使用三元组来表示(source node type, edge type, destination node type) >>>importdgl>>>importtorchasth>>># Create a heterograph with 3 node types and 3 edges types.>>>graph_da...
save_graphs, load_graphsimport dgl.function as fnimport torchimport dglimport torch.nn.functional as Ffrom dgl.nn.pytorch import GraphConv, SAGEConv, HeteroGraphConvfrom dgl.utils import expand_as_pairimport tqdmfrom collections import defaultdictimport torch as thimport dgl.nn as dglnnfrom dgl....
from dgl.dataloading import MultiLayerFullNeighborSampler, EdgeDataLoaderfrom dgl.dataloading.negative_sampler import Uniformimport numpy as npimport pandas as pdimport itertoolsimport osimport tqdmfrom dgl import save_graphs, load_graphsimport dgl.function as fnimport torchimport dglimport torch.nn....
save_graphs, load_graphsimport dgl.function as fnimport torchimport dglimport torch.nn.functional as Ffrom dgl.nn.pytorch import GraphConv, SAGEConv, HeteroGraphConvfrom dgl.utils import expand_as_pairimport tqdmfrom collections import defaultdictimport torch as thimport dgl.nn as dglnnfrom dgl....
Utils for measuring homophily of a graph (#5376,#5382,@mufeili) EdgeGATConv (#5282,@schmidt-ju) CuGraphGATConv (#5168,@tingyu66) CuGraphSAGEConv (#5137,@tingyu66) SubgraphX (#5315,@kunmukh) SubgraphX for heterogeneous graphs (#5530,@ndbaker1,@kunmukh) ...