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在net.py和resnet.py中,请问forward函数的最后为什么要加入x = torch.sigmoid(x) ?,这里之后return x应该和标签值求损失函数然后反向传播,sigmoid之后相当于归一化,明显与标签值不匹配吧
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这是为了将网络的输出约束到0-1范围内 softmax函数才是归一化
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在net.py和resnet.py中,请问forward函数的最后为什么要加入x = torch.sigmoid(x) ?,这里之后return x应该和标签值求损失函数然后反向传播,sigmoid之后相当于归一化,明显与标签值不匹配吧
The text was updated successfully, but these errors were encountered: