print.nn_arch

Display <code>nn_arch()</code> configuration

internal

Provides a higher-level interface to the 'torch' package for defining,
training, and fine-tuning neural networks, including its depth, powered by code generation.
This package supports few to several architectures, including feedforward (multi-layer perceptron)
and recurrent neural networks (Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU)),
while also reduces boilerplate 'torch' code while enabling seamless integration with 'torch'. The model methods
to train neural networks from this package also bridges to titanic ML frameworks in R, namely
'tidymodels' ecosystem, which enables the 'parsnip' model specifications, workflows, recipes,
and tuning tools.

Joshua Marie

kindling

Higher-Level Interface of 'torch' Package to Auto-Train Neural
Networks

Antoine Soetewey

print.nn_arch function

<dl><dt>x</dt>
<dd>An object of class "nn_arch"</dd>
<dt>...</dt>
<dd>Additional arguments (unused)</dd></dl>

Arguments

Display nn_arch() configuration — print.nn_arch

<dl>

<dt>x</dt>
<dd>An object of class "nn_arch"</dd>


<dt>...</dt>
<dd>Additional arguments (unused)</dd>

</dl>

print.nn_arch: Display `nn_arch()` configuration

Description

Usage

Value

Arguments