nnf_log_softmax

Applies a softmax followed by a logarithm.

Provides functionality to define and train neural networks similar to
'PyTorch' by Paszke et al (2019) <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

 RStudio

nnf_log_softmax function

<dl><dt>input</dt>
<dd>(Tensor) input</dd>
<dt>dim</dt>
<dd>(int) A dimension along which log_softmax will be computed.</dd>
<dt>dtype</dt>
<dd>(<code>torch.dtype</code>, optional) the desired data type of returned tensor.
If specified, the input tensor is casted to <code>dtype</code> before the operation
is performed. This is useful for preventing data type overflows.
Default: <code>NULL</code>.</dd></dl>

Arguments

Log_softmax — nnf_log_softmax

<dl>

<dt>input</dt>
<dd>(Tensor) input</dd>


<dt>dim</dt>
<dd>(int) A dimension along which log_softmax will be computed.</dd>


<dt>dtype</dt>
<dd>(<code>torch.dtype</code>, optional) the desired data type of returned tensor.
If specified, the input tensor is casted to <code>dtype</code> before the operation
is performed. This is useful for preventing data type overflows.
Default: <code>NULL</code>.</dd>

</dl>

nnf_log_softmax: Log_softmax

Description

Usage

Arguments

Details