torch_conj

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_conj function

<dl><dt>self</dt>
<dd>(Tensor) the input tensor.</dd></dl>

Arguments

Computes the element-wise conjugate of the given <code>input</code> tensor.
$$
 \mbox{out}_{i} = conj(\mbox{input}_{i})
$$

conj(input) -&gt; Tensor 

Conj — torch_conj

<dl>

<dt>self</dt>
<dd>(Tensor) the input tensor.</dd>

</dl>

Computes the element-wise conjugate of the given <code>input</code> tensor.
$$
 \mbox{out}_{i} = conj(\mbox{input}_{i})
$$

Last chance! 50% off unlimited learning

torch_conj: Conj

Description

Usage

Arguments

conj(input) -> Tensor

Examples

Last chance! 50% off unlimited learning

Description

Usage

Arguments

conj(input) -&gt; Tensor

Examples

conj(input) -> Tensor