Title: Higher-Level Interface of ‘torch’ Package to Auto-Train Neural Networks
Whether you’re generating neural network architecture expressions or
directly fitting/training models, {kindling} minimizes boilerplate
code while preserving {torch}. Since this package uses {torch} as
its backend, GPU acceleration is supported.
{kindling} also bridges the gap between {torch} and {tidymodels}.
It works seamlessly with {parsnip}, {recipes}, and {workflows} to
bring deep learning into your existing {tidymodels} modeling pipeline.
This enables a streamlined interface for building, training, and tuning
deep learning models within the familiar {tidymodels} ecosystem.
-
Code generation of
{torch}expression -
Multiple architectures available
- Base models interface: feedforward networks (MLP/DNN/FFNN) and recurrent variants (RNN, LSTM, GRU)
- Generalized neural network trainer that has the same topology as MLPs
-
Native support for R ML workflows and pipelines (currently
{tidymodels};{mlr3}planned) -
Fine-grained control over network depth, layer sizes, and activation functions
-
GPU acceleration support via
{torch}tensors
You can install {kindling} on CRAN:
install.packages('kindling')Or install the development version from GitHub:
# install.packages("pak")
pak::pak("joshuamarie/kindling")
## devtools::install_github("joshuamarie/kindling")- Getting Started with kindling
- Tuning Capabilities
- Custom Activation Function
- Special Cases: Linear and Logistic Regression
- Similar Packages and Comparison
Falbel D, Luraschi J (2023). torch: Tensors and Neural Networks with ‘GPU’ Acceleration. R package version 0.13.0, https://torch.mlverse.org, https://github.com/mlverse/torch.
Wickham H (2019). Advanced R, 2nd edition. Chapman and Hall/CRC. ISBN 978-0815384571, https://adv-r.hadley.nz/.
Goodfellow I, Bengio Y, Courville A (2016). Deep Learning. MIT Press. https://www.deeplearningbook.org/.
If you use {kindling} in a publication, please cite it. Run
citation("kindling") in R to get the current citation, or see the
CITATION
file.
MIT + file LICENSE
Please note that the kindling project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
