torch_matrix_exp: Matrix_exp

In torch: Tensors and Neural Networks with 'GPU' Acceleration

Matrix_exp

Description

Matrix_exp

Usage

torch_matrix_exp(self)

Arguments

self	(Tensor) the input tensor.

matrix_power(input) -> Tensor

Returns the matrix exponential. Supports batched input. For a matrix A, the matrix exponential is defined as

\exp^A = \sum_{k=0}^\infty A^k / k!.

The implementation is based on: Bader, P.; Blanes, S.; Casas, F. Computing the Matrix Exponential with an Optimized Taylor Polynomial Approximation. Mathematics 2019, 7, 1174.

Examples

if (torch_is_installed()) {

a <- torch_randn(c(2, 2, 2))
a[1, , ] <- torch_eye(2, 2)
a[2, , ] <- 2 * torch_eye(2, 2)
a
torch_matrix_exp(a)

x <- torch_tensor(rbind(c(0, pi/3), c(-pi/3, 0)))
x$matrix_exp() # should be [[cos(pi/3), sin(pi/3)], [-sin(pi/3), cos(pi/3)]]
}

torch documentation built on June 7, 2023, 6:19 p.m.