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

v0.3.0 · Mar 2, 2026 · MIT + file LICENSE

Description

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.

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OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026

Dependency Network

Dependencies Reverse dependencies purrr torch rlang cli glue vctrs parsnip tibble tidyr dplyr NeuralNetTools vip ggplot2 tune dials +3 more dependencies kindling

Version History

new 0.3.0 Mar 9, 2026