python logsumexp示例

x33g5p2x  于2022-02-18 转载在 Python  
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  1. pytorch python代码:
  1. import numpy as np
  2. import torch as t
  3. te = t.tensor([[-1.0000e+12, -1.0000e+02, 0.0000e+00],
  4. [-2.0000e+00, -1.0000e+12, 0.0000e+00]])
  5. print(te) # [2,3]
  6. logumsexp0= t.logsumexp(te,dim=0) # 两行之间列分别计算log (sum(...)) 值
  7. print(logumsexp0)
  8. res = t.logsumexp(te,dim=1) # 一般都是最后一个维度计算
  9. print(res)
  10. res = t.sum(res)
  11. print(res)
  12. res_0=np.log(np.sum(np.exp(te.numpy()[0])))
  13. res_1=np.log(np.sum(np.exp(te.numpy()[1])))
  14. print(res_0)
  15. print(res_1)

如果数据改为:

  1. import numpy as np
  2. import torch as t
  3. te = t.tensor([[-1000, -1000, 1000],
  4. [-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:

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

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