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@xiaolonw if(tloss1 > 0) { for(int k = 0; k < dim; k ++) { fori_diff[k] += (fneg[k] - fpos[k]); // / (pairNum * 1.0 - 2.0); fpos_diff[k] += -fori[k]; // / (pairNum * 1.0 - 2.0); fneg_diff[k] += fori[k]; } } if(tloss2 > 0) { for(int k = 0; k < dim; k ++) { fori_diff[k] += -fpos[k]; // / (pairNum * 1.0 - 2.0); fpos_diff[k] += fneg[k]-fori[k]; // / (pairNum * 1.0 - 2.0); fneg_diff[k] += fpos[k]; } } 为什么loss1与loss2大于0时,计算梯度的方式不一致呢? loss = f(a).f(n)-f(a).f(p) 那求偏导后,loss1>0是,diff的计算与上述loss相同,loss2>0时的计算公式是怎么得来呢? 多谢啦
The text was updated successfully, but these errors were encountered:
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@xiaolonw
if(tloss1 > 0)
{
for(int k = 0; k < dim; k ++)
{
fori_diff[k] += (fneg[k] - fpos[k]); // / (pairNum * 1.0 - 2.0);
fpos_diff[k] += -fori[k]; // / (pairNum * 1.0 - 2.0);
fneg_diff[k] += fori[k];
}
}
if(tloss2 > 0)
{
for(int k = 0; k < dim; k ++)
{
fori_diff[k] += -fpos[k]; // / (pairNum * 1.0 - 2.0);
fpos_diff[k] += fneg[k]-fori[k]; // / (pairNum * 1.0 - 2.0);
fneg_diff[k] += fpos[k];
}
}
为什么loss1与loss2大于0时,计算梯度的方式不一致呢?
loss = f(a).f(n)-f(a).f(p)
那求偏导后,loss1>0是,diff的计算与上述loss相同,loss2>0时的计算公式是怎么得来呢?
多谢啦
The text was updated successfully, but these errors were encountered: