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Getting an rrule from an frule in ChainRules.jl
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# rrule from frule (transposition) | |
using Zygote | |
using ChainRulesCore | |
using LinearAlgebra | |
function f(x) | |
a = sin.(x) | |
b = sum(a) | |
c = b * a | |
return c | |
end | |
function ChainRulesCore.frule((Δself, Δx,), ::typeof(f), x) | |
a, ȧ = sin.(x), cos.(x) .* Δx | |
b, ḃ = sum(a), sum(ȧ) | |
c, ċ = b * a, ḃ * a + b * ȧ | |
return c, ċ | |
end | |
function ChainRulesCore.rrule(config::RuleConfig{>:HasReverseMode}, ::typeof(f), x) | |
pushforward(Δfx...) = frule(Δfx, f, x)[2] | |
_, back = rrule_via_ad(config, pushforward, f, x) | |
f_pullback(Δy) = back(Δy)[2:end] | |
return f(x), f_pullback | |
end | |
let x = rand(3) | |
v = randn(3) | |
w = randn(3) | |
jvp(f, x, v) = frule((NoTangent(), v), f, x)[2] | |
vjp(f, x, w) = rrule_via_ad(Zygote.ZygoteRuleConfig(), f, x)[2](w)[2] | |
dot(w, jvp(f, x, v)) ≈ dot(vjp(f, x, w), v) | |
end |
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This is inspired by JAX's approach to decomposing reverse-mode into (forward-mode) linearization + transposition (where transposition only needs rules for linear primitives)