问题
I have a matrix A with size (5,7,3) and a matrix B with size (5,3,8). I want to multiply them C = A.B, and the size of C is (5,7,8).
It means that one 2D submatrix with size (7,3) in matrix A will be multiplied with one 2D submatrix with size (3,8) in matrix B respectively. So I have to multiply 5 times.
The simplest way is using a loop and numpy:
for u in range(5):
C[u] = numpy.dot(A[u],B[u])
Is there any way to do this without using a loop? Is there any equivalent method in Theano to do this without using scan?
回答1:
Can be done pretty simply with np.einsum in numpy.
C = numpy.einsum('ijk,ikl->ijl', A, B)
It can also simply be:
C = numpy.matmul(A,B)
Since the docs state:
If either argument is N-D, N > 2, it is treated as a stack of matrices residing in the last two indexes and broadcast accordingly
Theano has similar functionaly of batched_dot so it would be
C = theano.tensor.batched_dot(A, B)
来源：https://stackoverflow.com/questions/45565369/3d-matrix-multiplication-in-numpy-and-theano