I'm wondering how to get functionality similar to numpy.einsum in Julia.
Specifically, I have a 3rd order tensor that I'm looking to multiply by a 2nd tensor (matrix), contracting both of the dimensions to yield a 1st order tensor (vector).
Currently, I'm using PyCall so that I can use the numpy.einsum function like so:
using PyCall
@pyimport numpy as np
a = rand(5,4,3)
b = rand(5,4)
c = np.einsum("ijk,ij", a,b)
size(c) == (3,)
It feels kind of silly to rely on calling python in order to do tensor math. I also imagine that a julia implementation would have speed advantages. However, I haven't any function for this in julia, and the brute force summation is 1-2 orders of magnitude slower. What functions can I use?
Doesn't sum(a.*b,(1,2)) do what you want?