torch_eig

Provides functionality to define and train neural networks similar to
'PyTorch' by Paszke et al (2019) <doi:10.48550/arXiv.1912.01703> but written entirely in R
using the 'libtorch' library. Also supports low-level tensor operations and
'GPU' acceleration.

Daniel Falbel

torch

Tensors and Neural Networks with 'GPU' Acceleration

Javier Luraschi

Dmitriy Selivanov

Athos Damiani

Christophe Regouby

Krzysztof Joachimiak

Hamada S. Badr

Sebastian Fischer

Maximilian Pichler

 RStudio

torch_eig function

<dl><dt>self</dt>
<dd>(Tensor) the square matrix of shape \((n \times n)\) for which the eigenvalues and eigenvectors will be computed</dd>
<dt>eigenvectors</dt>
<dd>(bool) <code>TRUE</code> to compute both eigenvalues and eigenvectors; otherwise, only eigenvalues will be computed</dd></dl>

Arguments

Computes the eigenvalues and eigenvectors of a real square matrix.

eig(input, eigenvectors=False, out=NULL) -&gt; (Tensor, Tensor) 

Eig — torch_eig

<dl>

<dt>self</dt>
<dd>(Tensor) the square matrix of shape \((n \times n)\) for which the eigenvalues and eigenvectors will be computed</dd>


<dt>eigenvectors</dt>
<dd>(bool) <code>TRUE</code> to compute both eigenvalues and eigenvectors; otherwise, only eigenvalues will be computed</dd>

</dl>

Computes the eigenvalues and eigenvectors of a real square matrix.

torch_eig: Eig

Description

Arguments

eig(input, eigenvectors=False, out=NULL) -> (Tensor, Tensor)

Description

Arguments

eig(input, eigenvectors=False, out=NULL) -&gt; (Tensor, Tensor)

eig(input, eigenvectors=False, out=NULL) -> (Tensor, Tensor)