ISDA-for-Deep-Networks
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RuntimeError: copy_if failed to synchronize: device-side assert triggered
weight_CV: tensor([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]],
[[nan, nan, nan, ..., nan, nan, nan],
[nan, nan, nan, ..., nan, nan, nan],
[nan, nan, nan, ..., nan, nan, nan],
...,
[nan, nan, nan, ..., nan, nan, nan],
[nan, nan, nan, ..., nan, nan, nan],
[nan, nan, nan, ..., nan, nan, nan]],
训练自己的数据的时候报错了,weight_cv一直都是NAN 我尝试过以下这些方案解决,结果不行: 1、调整学习率 2、对FC权重和特征进行归一化
我的分类数是3000多类,我看代码weight_cv,是对label的一个onehot转换。按理应该不会出现这种错误才对。 希望作者能指点一下,谢谢
补充一下:不过二分类好像没问题,