AccelerateHS / AccelerateHS/accelerate

Support Automatic Differentiation

未關閉
#398 29 則留言 4 個 reaction 已指派 0 人 在 GitHub 檢視
library/ecosystem
主要語言
Haskell
星號
1k
分支
135
PR 合併指標
30 天內沒有已合併 PR

描述

If we had AD, Accelerate would be ready for creating Deep Learning frameworks on top of it.

I've found a [very nice post](https://rufflewind.com/2016-12-30/reverse-mode-automatic-differentiation) explaining a way of implementing it in Rust and Python.

The thing is, if we implement it _inside_ Accelerate it would be great, as all programs could be passed through AD.

The source for the obsolete `rad` package created by Edward Kmett is quite simple, and might be trivial to implement. (http://hackage.haskell.org/package/rad-0.1.6.3/docs/src/Numeric-RAD.html)

貢獻指南

這個儲存庫沒有索引到貢獻指南

評估

這個 Issue 還沒有評估資料。

把新 issue 寄到你的電子郵件信箱

精選適合新手參與的 GitHub issue 摘要。