About LayerNormLayer

[lonelywm]

in forward function, x = torch.inverse(...)

tensor = torch.FloatTensor([[1,2],[3,4]])
t_out = torch.inverse(tensor)
t_o = 1/tensor
print(tensor)
print(t_out)
print(t_o)
==========>
1 2
3 4
[torch.FloatTensor of size 2x2]

-2.0000 1.0000
1.5000 -0.5000
[torch.FloatTensor of size 2x2]

1.0000 0.5000
0.3333 0.2500
============>
or what we need is t_o
in theano T.inv===1/T
as has been mentioned in the paper

[github-pengge]

My bad. Now it's fixed.