softmax

import torch
import torch.autograd as autograd
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
import numpy as np


data=autograd.Variable(torch.FloatTensor([1.0,2.0,3.0]))
log_softmax=F.log_softmax(data,dim=0)
print("log_softmax",log_softmax)

softmax=F.softmax(data,dim=0)
print("softmax",softmax)

np_softmax=softmax.data.numpy()
log_np_softmax=np.log(np_softmax)
print("log_np_softmax",log_np_softmax)

'''

                  1                     2                   3
exp           2.718281828        7.389056099         20.08553692       30.19287485
softmax       0.090030573        0.244728471         0.665240956
log_softmax   -2.407605964       -1.407605964        -0.407605964
 
0.090030573=2.718281828/30.19287485
-2.407605964=ln(0.090030573)


log_softmax tensor([-2.4076, -1.4076, -0.4076])  
softmax tensor([0.0900, 0.2447, 0.6652])  
log_np_softmax [-2.407606   -1.4076059  -0.40760598]

'''