attention: Self-Attention Algorithm

Self-Attention algorithm helper functions and demonstration vignettes of increasing depth on how to construct the Self-Attention algorithm, this is based on Vaswani et al. (2017) <doi:10.48550/arXiv.1706.03762>, Dan Jurafsky and James H. Martin (2022, ISBN:978-0131873216) <https://web.stanford.edu/~jurafsky/slp3/> "Speech and Language Processing (3rd ed.)" and Alex Graves (2020) <https://www.youtube.com/watch?v=AIiwuClvH6k> "Attention and Memory in Deep Learning".

Version:	0.4.0
Suggests:	covr, knitr, rmarkdown, testthat (≥ 3.0.0)
Published:	2023-11-10
DOI:	10.32614/CRAN.package.attention
Author:	Bastiaan Quast [aut, cre]
Maintainer:	Bastiaan Quast <bquast at gmail.com>
License:	GPL (≥ 3)
NeedsCompilation:	no
Materials:	README NEWS
CRAN checks:	attention results

Documentation:

Reference manual:	attention.pdf
Vignettes:	Complete Self-Attention from Scratch Simple Self-Attention from Scratch

Downloads:

Package source:	attention_0.4.0.tar.gz
Windows binaries:	r-devel: attention_0.4.0.zip, r-release: attention_0.4.0.zip, r-oldrel: attention_0.4.0.zip
macOS binaries:	r-release (arm64): attention_0.4.0.tgz, r-oldrel (arm64): attention_0.4.0.tgz, r-release (x86_64): attention_0.4.0.tgz, r-oldrel (x86_64): attention_0.4.0.tgz
Old sources:	attention archive

Reverse dependencies:

Reverse imports:

rnn, transformer

Linking:

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