'''
torch.nn torch.nn.functional (F)
CrossEntropyLoss cross_entropy
LogSoftmax log_softmax
NLLLoss nll_loss
'''
import torch
import torch.nn.functional as F
input=torch.randn(3,4)
label=torch.tensor([0,2,1])
print("input",input)
softmax=F.softmax(input,dim=1)
print("softmax",softmax)
log_softmax=F.log_softmax(input,dim=1)
print("log_softmax",log_softmax)
loss_nll=F.nll_loss(log_softmax,label)
print("loss_nll",loss_nll)
loss_cross=F.cross_entropy(input,label)
print("loss_cross",loss_cross)
'''
input tensor([[ 0.0363, 0.1419, 2.1639, 1.5429],
[-0.6606, -0.0991, -0.6160, -2.4418],
[-1.1279, -1.5333, -0.2142, 0.8669]])
softmax tensor([[0.0666, 0.0740, 0.5590, 0.3004],
[0.2521, 0.4419, 0.2636, 0.0425],
[0.0869, 0.0579, 0.2166, 0.6386]])
log_softmax tensor([[-2.7092, -2.6036, -0.5816, -1.2026],
[-1.3781, -0.8166, -1.3335, -3.1592],
[-2.4433, -2.8488, -1.5296, -0.4485]])
loss_nll tensor(1.4971)
loss_cross tensor(1.4971)
0.0363 0.1419 2.1639 1.5429
-0.6606 -0.0991 -0.616 -2.4418
-1.1279 -1.5333 -0.2142 0.8669
dim=0
exp sum
1.0370 1.1525 8.7050 4.6781 15.57258663
0.5165 0.9057 0.5401 0.0870 2.049298083
0.3237 0.2158 0.8072 2.3795 3.726244435
softmax
0.0666 0.0740 0.5590 0.3004
0.2521 0.4419 0.2636 0.0425
0.0869 0.0579 0.2166 0.6386
log_softmax
-2.7092 -2.6036 -0.5816 -1.2026
-1.3781 -0.8166 -1.3335 -3.1593
-2.4433 -2.8487 -1.5296 -0.4485
1.0370=exp(0.0363)
0.0666=1.0370/15.57258663
-2.7092=ln(0.0666)
1.497070103=abs(-2.7092-1.3335-0.44850/3
'''
