本文介绍了PyTorch中复杂矩阵的行列式的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
有没有一种方法可以计算PyTroch中复杂矩阵的行列式?
Is there a way to calculate the determinant of a complex matrix in PyTroch?
torch.det
推荐答案
很遗憾,当前尚未实现.一种方法是实现您自己的版本,或仅使用 np.linalg.det
.这是一个简短的函数,用于计算使用LU分解编写的复杂矩阵的行列式:
Unfortunately it's not implemented currently. One way would be to implement your own version or simply use np.linalg.det
.Here is a short function which computes the determinant of a complex matrix that I wrote using LU-decomposition:
def complex_det(A):
def complex_diag(A):
return torch.view_as_complex(torch.stack((A.real.diag(), A.imag.diag()),dim=1))
#Perform LU decomposition to matrix A:
A_LU, pivots = A.lu()
P, A_L, A_U = torch.lu_unpack(A_LU, pivots)
#Det. of multiplied matrices is multiplcation of det.:
det = torch.prod(complex_diag(A_L)) * torch.prod(complex_diag(A_U)) * torch.det(P.real) #Could probably calculate det(P) [which is +-1] efficiently using Sylvester's determinant identity
return det
#Test it:
A = torch.view_as_complex(torch.randn(3,3,2))
complex_det(A)
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