from dgl.data.utils import makedirs, save_info, load_infofrom sklearn.metrics import roc_auc_scoreimport gcgc.collect() 推荐一个工具,tqdm 很好用 哦,结合 dataloading接口, 可以看到模型训练以及数据处理执行的进度,赶紧用起来吧～ 这里的 sklearn 工具 的导入,仅仅是为了调用他来进行分类模型的离线指标...
import 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 expand_as_pairimport...
import 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 expand_as_pairimport...
# Save graphsdgl.save_graphs('graph.dgl',g)dgl.save_graphs('graphs.dgl',[g,sg1,sg2])# Load graphs(g,),_=dgl.load_graphs('graph.dgl')print(g)(g,sg1,sg2),_=dgl.load_graphs('graphs.dgl')print(g)print(sg1)print(sg2)
data.utilsimportsave_graphsgraph_labels={"glabel":torch.tensor([0,1])}save_graphs("./data....
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) ...
如果数据集是一个 zip 文件,可以直接继承 dgl.data.DGLBuiltinDataset 类。后者支持解压缩 zip 文件。 否则用户需要自己实现 download() importosfromdgl.data.utilsimportdownloaddefdownload(self):# 存储文件的路径file_path=os.path.join(self.raw_dir,self.name+'.mat')# 下载文件download(self.url,path=fi...
ndata_schemes={} 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...
Amazon Neptune ML: a new capability of Neptune that uses Graph Neural Networks (GNNs), a machine learning technique purpose-built for graphs, to make easy, fast, and more accurate predictions using graph data.https://aws.amazon.com/cn/neptune/machine-learning/ ...
nn.functional as F from dgl import DGLGraph from dgl.data import register_data_args, load_data...