PyTorch torch.slogdet Function
PyTorch torch Reference Manual
torch.slogdetIt is a function in PyTorch used to compute the sign and logarithm of the determinant of a matrix. It is more numerically stable for cases where the determinant is very large or very small.
Function Definition
torch.slogdet(input, out=None)
Parameters:
input(Tensor): Input square matrix.out(tuple, optional): Output tuple.
Return Value:
tuple: Returns a tuple of (sign, log value).
Usage Example
Example
import torch
# Create a square matrix
A = torch.tensor([[1.0, 2.0, 3.0],
[0.0, 4.0, 5.0],
[0.0, 0.0, 6.0]])
# Compute the sign and logarithm of the determinant
sign, logdet = torch.slogdet(A)
print("Matrix A:")
print(A)
print("nDeterminant sign:", sign)
print("Log determinant:", logdet)
print("Determinant:", sign * torch.exp(logdet))
# Create a square matrix
A = torch.tensor([[1.0, 2.0, 3.0],
[0.0, 4.0, 5.0],
[0.0, 0.0, 6.0]])
# Compute the sign and logarithm of the determinant
sign, logdet = torch.slogdet(A)
print("Matrix A:")
print(A)
print("nDeterminant sign:", sign)
print("Log determinant:", logdet)
print("Determinant:", sign * torch.exp(logdet))
The output is:
矩阵 A:
tensor([[1., 2., 3.],
[0., 4., 5.],
[0., 0., 6.]])
行列式符号: tensor(1.)
行列式对数: tensor(3.5835)
行列式: tensor(24.)
Other Extensions