Eigendecomposition for asymmetric matrix

i want to compute the eigenvalues and eigenvectors of a hidden layer using mxnet, 
i have seen mxnet.ndarray.linalg.syevd ,but it only support the symmetric matrix, if the matrix is asymmetric how to solve?

i resolved this problem by using “.asnumpy()”, and then using " .eig(T)" support by numpy ,but i found it run really slow.Does anyone has any good idea to solve it?
thank u very much