python - Speed up multilple matrix products with numpy -


in python have 2 3 dimensional arrays:

t size (n,n,n)

u size (k,n,n)

t , u can seen many 2-d arrays 1 next other. need multiply matrices, ie have perform following operation:

for in range(n):         h[:,:,i] =  u[:,:,i].dot(t[:,:,i]).dot(u[:,:,i].t)

as n might big wondering if operation in way speed numpy.

carefully looking iterators , how involved in dot product reductions, translate of 1 np.einsum implementation -

h = np.einsum('ijk,jlk,mlk->imk',u,t,u)

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