Best way to do a 2d cross product

I have a tensor with the following shape B x C x 2 x NrVerticies x 2
and now I want to do a cross product for the last dim. I found the function
however, this function only supports 3D vectors, so I was wondering what would be the torch way to handle the cross product in 2D.

I think you might misunderstand the docs, as the specified dim should have the size 3 and you can use multiple dimensions as seen here:

a = torch.randn(4, 5, 6, 7, 8, 3)
b = torch.randn(4, 5, 6, 7, 8, 3)
torch.cross(a, b, dim=5)

For your example it won’t work, since your last dimension has a size of 2.

Thanks for the feedback. I understood the docs, but I wanted to use the cross product in 2D.
Finally, I ended up doing this, if someone is having the same issue.

 # pad the last dim to have 3D vector 
s_pad = F.pad(s, (0, 1))
# compute the cross product 
A = torch.cross(s_pad[:, index_list], s_pad[:, index_list_plus], dim=2)
# use the last dim which is the same as if the cross product would be done in 2D
A = A[..., 2]