Test Linearity
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- 难度
- 4/5
- 预计耗时
- 3-5 天
- 新手友好度
- 25/100
- Issue 类型
- 功能
- 描述清晰度
- 基本清楚
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- 停滞
- 技术栈
- julia
- 领域
- testing-qa
调研方向
未指定文件路径或测试路径。先阅读现有的 rand_tangent、rrule 和 frule 测试工具,然后确定应如何检查 pushforward 和 pullback 的线性。完成标准是添加关于零和标量行为的已达成一致的测试;只有在现有的微分生成机制支持加法性的情况下,才将其包括在内。
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描述
Pushforwards and pullbacks are requred to be linear operators.
Which formally is defined as φ(𝛼x) = 𝛼φ(x) and φ(a+b) = φ(a) + φ(b) for a,b,x differentials/vector space elements, and 𝛼 being a scalar.
A important collory of that is φ(0) = 0 where two 0s are the additive identity for the relivent vector spaces.
Which we can test with iszero(φ(zero(d)), since we always have access to a differential d, and all differentials must define zero and iszero.
Similarly we can test φ(𝛼x) = 𝛼φ(x) via φ(2d) == 2φ(d) since all differnetial define multiplication with a scalar. and we have one provided d.
We can't easily test φ(a+b) = φ(a) + φ(b) though, as we only have one differential.
We can test φ(d+d) = φ(d) + φ(d) but that is less interesting.
If we are generating them using rand_tangent we can easily generate another.
Though perhaps we should be insisting that things define the addition of there natural differentials with the structural differentials that rand_tangent will most often provide (though sometimes rand_tangent's structural differential will have extra nondifferentiable fields so we can't trust it, unless we insist the user does actually overload it).
Or we could avoid direct additon and do (primal + rand_tangent(d)) + d) though this is getting off-topic..
Possibly just skip that in initial implementation of this
The linear pullback can be extracted from the rrule via (f,primal...) -> (ds...) -> last(rrule(f, primal...))(ds...) (or equiv: (f,primal) -> last(rrule(f, primal)))
The linear pushforward can be extracted from frulevia(f,primal) -> (ds...) -> frule(ds..., f, primal...)`
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