validate_device

Check if requested device is available. And auto-detect available GPU device
or fallback to CPU.

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 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

validate_device function

<dl><dt>device</dt>
<dd>Character. Requested device.</dd></dl>

Arguments

Validate device and get default device — validate_device

<dl>

<dt>device</dt>
<dd>Character. Requested device.</dd>

</dl>

validate_device: Validate device and get default device

Description

Usage

Value

Arguments