Numpy: Multiplying a matrix with a 3d tensor — Suggestion

Question

I have a matrix P with shape MxN and a 3d tensor T with shape KxNxR. I want to multiply P with every N

Answer 1

You could also use Einstein summation notation:

P = numpy.random.randint(1,10,(5,3))
P.shape
T = numpy.random.randint(1,10,(2,3,4))
T.shape

numpy.einsum('ij,kjl->kil',P,T)

which should give you the same results as:

P.dot(T).transpose(1,0,2)

Answer 2

scipy.tensordot(P, T, axes=[1,1]).swapaxes(0,1)