torch / torch
torch.matrix_exp¶
-
torch.
matrix_exp
()¶ matrix_power(input) -> Tensor
Returns the matrix exponential. Supports batched input. For a matrix
A
, the matrix exponential is defined asThe implementation is based on: Bader, P.; Blanes, S.; Casas, F. Computing the Matrix Exponential with an Optimized Taylor Polynomial Approximation. Mathematics 2019, 7, 1174.
- Parameters
input (Tensor) – the input tensor.
Example:
>>> a = torch.randn(2, 2, 2) >>> a[0, :, :] = torch.eye(2, 2) >>> a[1, :, :] = 2 * torch.eye(2, 2) >>> a tensor([[[1., 0.], [0., 1.]], [[2., 0.], [0., 2.]]]) >>> torch.matrix_exp(a) tensor([[[2.7183, 0.0000], [0.0000, 2.7183]], [[7.3891, 0.0000], [0.0000, 7.3891]]]) >>> import math >>> x = torch.tensor([[0, math.pi/3], [-math.pi/3, 0]]) >>> x.matrix_exp() # should be [[cos(pi/3), sin(pi/3)], [-sin(pi/3), cos(pi/3)]] tensor([[ 0.5000, 0.8660], [-0.8660, 0.5000]])
此页内容是否对您有帮助