no no, I want to represent each of these numbers as vectors, if I represent each of these numbers as vector of size 10, then n would be 10.
so a number would be represented as
6 -> [0.01, 0.2, 0.5, -0.2, 0.6, 0.2, 0.7, 0.3, 0.02, 0.5]

similarly for 4, 9, 8
finally I want a matrix of size [4x10]
representing 40 parameters, 10 for each of 6, 4, 9, 8
if my tensor was
torch.tensor([2., 4., 6.], requires_grad=True)

then I want a matrix of size [3x10]
representing 30 parameters, 10 for each of 2, 4, 6
I think embedding is not the correct way to do this