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Nesting Forward-mode Ad In A Functional Framework

机译:在功能框架中嵌套前向广告

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We discuss the augmentation of a functional-programming language with a derivative-taking operator implemented with forward-mode automatic differentiation (AD). The primary technical difficulty in doing so lies in ensuring correctness in the face of nested invocation of that operator, due to the need to distinguish perturbations introduced by distinct invocations. We exhibit a series of implementations of a referentially-transparent forward-mode-AD derivative-taking operator, each of which uses a different non-referentially-transparent mechanism to distinguish perturbations. Even though the forward-mode-AD derivative-taking operator is itself referentially transparent, we hypothesize that one cannot correctly formulate this operator as a function definition in current pure dialects of Haskell.
机译:我们讨论了使用正向自动微分(AD)实现的衍生工具运算符对功能编程语言的扩充。这样做的主要技术困难在于,由于需要区分不同调用所引起的扰动,因此在面对该操作员的嵌套调用时要确保正确性。我们展示了一系列参照透明的前向AD导数取算符的实现,每个实现都使用不同的非参照透明的机制来区分扰动。即使正向AD导数取整运算符本身是参照透明的,我们仍假设无法正确地将此运算符公式化为当前Haskell纯方言中的函数定义。

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