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您好 我们想在您的基础上训练一个分类网络,但细节的地方有两个位置不太理解,能不能麻烦解释一下,万分感谢。 第一个是results为什么后面还要torch.cat一个torch.ones_like results = torch.cat([torch.sigmoid(results), torch.ones_like(results[:, :1]).float().cuda() * 0.5], 1) 第二个是这里为什么要乘以16 out = self.fc(global_feat) * 16
The text was updated successfully, but these errors were encountered:
因为我对特征做了一个归一化,值都会比较小,同时也不想让参数的范围过大,所以就乘了一个系数
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您好 我们想在您的基础上训练一个分类网络,但细节的地方有两个位置不太理解,能不能麻烦解释一下,万分感谢。
第一个是results为什么后面还要torch.cat一个torch.ones_like
results = torch.cat([torch.sigmoid(results), torch.ones_like(results[:, :1]).float().cuda() * 0.5], 1)
第二个是这里为什么要乘以16
out = self.fc(global_feat) * 16
The text was updated successfully, but these errors were encountered: