args

Type-safe helper to specify parameters for activation functions.
All parameters must be named and match the formal arguments of the
corresponding <code>torch</code> activation function.

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 currently supports few to several architectures, namely 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

args function

<dl><dt>...</dt>
<dd>Named arguments for the activation function.</dd></dl>

Arguments

Activation Function Arguments Helper — args

<dl>

<dt>...</dt>
<dd>Named arguments for the activation function.</dd>

</dl>

args: Activation Function Arguments Helper

Description

Usage

Value

Arguments