python logsumexp示例

pytorch 和python代码：

      import numpy as np
      import torch as t
      te = t.tensor([[-1.0000e+12, -1.0000e+02,  0.0000e+00],
                     [-2.0000e+00, -1.0000e+12,  0.0000e+00]])
      print(te) # [2,3]
      logumsexp0= t.logsumexp(te,dim=0) # 两行之间列分别计算log (sum(...)) 值
      print(logumsexp0)
      res = t.logsumexp(te,dim=1) # 一般都是最后一个维度计算
      print(res)
      res = t.sum(res)
      print(res)
      res_0=np.log(np.sum(np.exp(te.numpy()[0])))
      res_1=np.log(np.sum(np.exp(te.numpy()[1])))
      print(res_0)
      print(res_1)
  
 

如果数据改为：

      import numpy as np
      import torch as t
      te = t.tensor([[-1000, -1000,  1000],
                     [-2.0000e+00, -1.0000e+12,  0.0000e+00]])
  
 

res_0=np.log(np.sum(np.exp(te.numpy()[0])))

这个代码会报错：

RuntimeWarning: overflow encountered in exp

这个不报错：

      import numpy as np
      import torch as t
      from scipy.special import logsumexp
      sci_0= logsumexp(te.numpy()[0])
      print("sci_0",sci_0)
      sci_0= logsumexp(te.numpy()[1])
      print("sci_1",sci_0)
  
 

文章来源: blog.csdn.net，作者：AI视觉网奇，版权归原作者所有，如需转载，请联系作者。

原文链接：blog.csdn.net/jacke121/article/details/122994935