Is there any indexing method in pytorch?
I'm studying about pytorch recently.
But this problem is so weird..
x=np.arrage(24)
ft=torch.FloatTensor(x)
print(floatT.view([@1])[@2])

Answer = tensor([[13., 16.], [19., 22.]])
Can there be indexing methods @1 and @2 that satisfy the Answer?

by viewing ft as a tensor with 6 columns:
ft.view(-1, 6)
Out[]:
tensor([[ 0.,  1.,  2.,  3.,  4.,  5.],
        [ 6.,  7.,  8.,  9., 10., 11.],
        [12., 13., 14., 15., 16., 17.],
        [18., 19., 20., 21., 22., 23.]])

you place the elements (13, 19), and (16, 22) on top of each other.
Now you only need to pick them up from the right rows/columns:
.view(-1, 6)[2:, (1, 4)]
Out[]:
tensor([[13., 16.],
        [19., 22.]])

