首页
学习
活动
专区
圈层
工具
发布
社区首页 >专栏 >something about softmax

something about softmax

作者头像
caoqi95
发布2019-06-20 11:29:00
发布2019-06-20 11:29:00
6240
举报

[1]. Softmax vs. Softmax-Loss: Numerical Stability

代码语言:javascript
复制
function softmax(z)
  #z = z - maximum(z)
  o = exp(z)
  return o / sum(o)
end
function gradient_together(z, y)
  o = softmax(z)
  o[y] -= 1.0
  return o
end
function gradient_separated(z, y)
  o = softmax(z)
  ∂o_∂z = diagm(o) - o*o'
  ∂f_∂o = zeros(size(o))
  ∂f_∂o[y] = -1.0 / o[y]
  return ∂o_∂z * ∂f_∂o
end

[2]. PyTorch - VGG output layer - no softmax?

The reason why this is done is because you only need the softmax layer at the time of inferencing. While training, to calculate the loss you don’t need to softmax and just calculate loss without it. This way the number of computations get reduced!

本文参与 腾讯云自媒体同步曝光计划,分享自作者个人站点/博客。
原始发表:2019.06.20 ,如有侵权请联系 cloudcommunity@tencent.com 删除
目录
  • [1]. Softmax vs. Softmax-Loss: Numerical Stability
  • [2]. PyTorch - VGG output layer - no softmax?
问题归档专栏文章快讯文章归档关键词归档开发者手册归档开发者手册 Section 归档