A bug

[11051911]

When I brought my own data into the experiment, it basically ran out, but the methods involving cross-entropy loss reported this error. May I ask the author what the problem may be? Have you encountered it before?
C:\cb\pytorch_1000000000000\work\aten\src\ATen\native\cuda\Loss.cu:106: block: [32,0,0], thread: [126,0,0] Assertion target_val >= zero && target_val <= onefailed. C:\cb\pytorch_1000000000000\work\aten\src\ATen\native\cuda\Loss.cu:106: block: [4255,0,0], thread: [62,0,0] Assertiontarget_val >= zero && target_val <= onefailed. File "E:\最新聚类论文代码\A-Unified-Framework-for-Deep-Attribute-Graph-Clustering-main\main.py", line 53, in <module> result = train(args, data, logger) File "E:\最新聚类论文代码\A-Unified-Framework-for-Deep-Attribute-Graph-Clustering-main\model\pretrain_gat_for_efrdgc\train.py", line 48, in train loss = F.binary_cross_entropy(A_pred.view(-1), adj_label.view(-1))