From ab6f36e8b6bdd736b9c2383252789012c5cb0605 Mon Sep 17 00:00:00 2001 From: chengchingwen Date: Thu, 21 Dec 2023 16:31:45 +0800 Subject: [PATCH] update readme --- README.md | 30 +++++++++++++++++++++++++++++- docs/src/assets/overview.md | Bin 0 -> 154066 bytes 2 files changed, 29 insertions(+), 1 deletion(-) create mode 100644 docs/src/assets/overview.md diff --git a/README.md b/README.md index 54f38a3..ed28a5e 100644 --- a/README.md +++ b/README.md @@ -5,4 +5,32 @@ [![Build Status](https://github.com/chengchingwen/NeuralAttentionlib.jl/workflows/CI/badge.svg)](https://github.com/chengchingwen/NeuralAttentionlib.jl/actions) [![Coverage](https://codecov.io/gh/chengchingwen/NeuralAttentionlib.jl/branch/master/graph/badge.svg)](https://codecov.io/gh/chengchingwen/NeuralAttentionlib.jl) -Reusable functionality for defining custom attention/transformer layers. +Reusable functionality for defining custom attention/transformer layers. See [document](https://chengchingwen.github.io/NeuralAttentionlib.jl/dev) for more information. + +# Design + +
NeuralAttentionlib_Overview
+ +The core idea of this package is to make the attention operation composable, so that most of the attention variants can + be easily defined without rewriting other parts. For example, normal attention use `softmax` on the attention score to + normalize weight of each entries. If you want to replace `softmax` with other normalization function, such as L2-norm, + there is a problem that they require different ways to mask specific entries such as paddings. With this package, we + can easily do this by providing a different `AbstractMaskOp` to `masked_score`, so no copy-paste is needed. For another + example, some position embeddings are adding values to the attention scores, with this package, you can directly chain + the position embedding function (or use `biased_score`) with other score functions. Moreover, the same definition can + be used directly for high dimensional attentions, such as image or video. + + +This package contain 3 submodules: `MatMul`, `Masks`, and `Functional`. + +1. `Matmul` defines an Array wrapper `CollapsedDimsArray{T}(array, ni::Integer, nj::Integer)` which treat n-dimensional + array as 3-dimensional array while preserving the original shape. By explicitly specifying which dimensions should be + the "batch" and "length" dimensions, the implementations of attention do not need to worry about the input dimensions. +2. `Masks` provides an interface to define non-allocating masks with support for both CPU and GPU (using Julia's + broadcast interface) and many pre-defined masks. For example, `CausalMask()` is just a Julia object and it would + NOT allocate a `n^2` attention score mask either on CPU or GPU. These masks are also composable, you can use `&`/`|` + to combine, for example, causal mask and padding mask without extra allocation or the need to write extra code. +3. `Functional` contains the implementation for the "attention score"s, "mixing"s, and "attention operation"s. The + interface of "attention score"s allow you to chain different score function together, such as `normalized_score`, + `masked_score`, and `biased_score`. And the interface of "attention operation"s allow you to provide different + score functions and mixing functions. The other part, such as reshaping for multi-head, are automatically handled. diff --git a/docs/src/assets/overview.md b/docs/src/assets/overview.md new file mode 100644 index 0000000000000000000000000000000000000000..7ad87ce88e1758ad144a54d102401b49dd5435d0 GIT binary patch literal 154066 zcmeFZc~p*j_&(Z3*byR?k|H!0jfy0iOY^8XnpK+9NXbw_nlul3(;O-Wc5XZYu|*Rn<4=XpM#&wbz5b=}wf+*47Kp`@UvAR{BAl#`WI zBP07ehm33s#r9436Yg r)i?Qw14GvJKLIiDl11$;g<=t~m4ndwBHyIXkGB4>Bw6wK%S=-nYSlec|pViVU(6rgVXTL@7=50j_Z~wZx zy;`O7(cprNA#eFo+`hM;&Yf5*-EcP?su9bH-MKtiWWeXtP^PjKh=fcka_3t-iI?VD(|9wNowTGbc zKi|>ZRb%^~?{-MCQ~&qf4f2=l|6W2xUxOq3d=eXxi;V0<-pGihz5V3lhD~p5ZfO2r z`{-n9(whJIdb3HD0#EnPm+{U22cG2rzZ_|G|8F`L|EtBkDlhu)!OOi<8_Byd+oG(h zsv6FrIoee)7RIg~8yhPx%KmkZhMson(Bt<}SO6VrC+9Z|C zwqtRd{~QQKwJ!@p9N~evttLEU9k~go9Fpfd?ol!bopBk}SepK!aDww|fslFKlZuUX zz0-W|Q(qrF+H^ypD`b~&e(_V!mUW9{mxiZAl= zI6L1Prx}#E%8e!ZF^~6^#i*ruSr>?&IpfumdhyO~rgGnn@&+MSSJ!O4!k^uRlTS`w z&d|zU4&;BInQz~JHtyHvZM$$OGN+_}BIt(c3$LYVtCrMzelf!KyLRv1O+kU@FwU>5 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