add again changes made on website which got lost in a local rebase without checking first because I forgot about this for ages

Author: mcabbott

Project.toml

@@ -13,7 +13,7 @@ Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 [compat]
 ChainRulesCore = "1"
 Functors = "0.3"
-Yota = "0.7.3"
+Yota = "0.8.1"
 Zygote = "0.6.40"
 julia = "1.6"
 

test/destructure.jl

@@ -106,16 +106,15 @@ end
   end
 
   @testset "using Yota" begin
-    @test_broken Yota_gradient(m -> destructure(m)[1][1], m1)[1] == [1,0,0]  # Unexpected expression: $(Expr(:static_parameter, 1))
-    # These are all broken!
+    @test Yota_gradient(m -> destructure(m)[1][1], m1)[1] == [1,0,0]
     @test Yota_gradient(m -> destructure(m)[1][2], m2)[1] == ([0,1,0], [0,0,0])
-    @test Yota_gradient(m -> destructure(m)[1][3], (m1, m1))[1] == ([0,0,1], ZeroTangent())
-    @test Yota_gradient(m -> destructure(m)[1][1], m3)[1] == (x = [1,0,0], y = ZeroTangent(), z = [0,0,0])
-    @test Yota_gradient(m -> destructure(m)[1][2], m4)[1] == (x = [0,1,0], y = ZeroTangent(), z = [0,0,0])
+    @test Yota_gradient(m -> destructure(m)[1][3], (m1, m1))[1] == ([0,0,1], nothing)
+    @test Yota_gradient(m -> destructure(m)[1][1], m3)[1] == (x = [1,0,0], y = nothing, z = [0,0,0])
+    @test Yota_gradient(m -> destructure(m)[1][2], m4)[1] == (x = [0,1,0], y = nothing, z = [0,0,0])
 
     g5 = Yota_gradient(m -> destructure(m)[1][3], m5)[1]
     @test g5.a[1].x == [0,0,1]
-    @test g5.a[2] === ZeroTangent()
+    @test g5.a[2] === nothing
 
     g6 = Yota_gradient(m -> imag(destructure(m)[1][4]), m6)[1]
     @test g6.a == [0,0,0]
@@ -128,7 +127,7 @@ end
     @test g8[3] == [[10.0]]
 
     g9 = Yota_gradient(m -> sum(sqrt, destructure(m)[1]), m9)[1]
-    @test g9.c === ZeroTangent()
+    @test g9.c === nothing
   end
 end
 
@@ -199,11 +198,11 @@ end
     @test Yota_gradient(x -> re7(x).c[2][1], rand(3))[1] == [0,0,0]
 
     v8, re8 = destructure(m8)
-    @test_broken Yota_gradient(x -> sum(abs2, re8(x)[1].y), v8)[1] == [2,4,6,0,0]  # MethodError: no method matching zero(::Type{Any})
-    @test_broken Yota_gradient(x -> only(sum(re8(x)[3]))^2, v8)[1] == [0,0,0,0,10]  # MethodError: no method matching !(::Expr)
+    @test Yota_gradient(x -> sum(abs2, re8(x)[1].y), v8)[1] == [2,4,6,0,0]
+    @test Yota_gradient(x -> only(sum(re8(x)[3]))^2, v8)[1] == [0,0,0,0,10]
 
     re9 = destructure(m9)[2]
-    @test_broken Yota_gradient(x -> sum(abs2, re9(x).c[1]), 1:7)[1] == [0,0,0, 8,10,12,14]  # MethodError: no method matching zero(::Type{Array})
+    @test Yota_gradient(x -> sum(abs2, re9(x).c[1]), 1:7)[1] == [0,0,0, 8,10,12,14]
   end
 end
 

test/runtests.jl

@@ -39,7 +39,10 @@ end
 
 # Make Yota's output look like Zygote's:
 
-Yota_gradient(f, xs...) = Base.tail(Yota.grad(f, xs...)[2])
+Yota_gradient(f, xs...) = map(y2z, Base.tail(Yota.grad(f, xs...)[2]))
+y2z(::AbstractZero) = nothing  # we don't care about different flavours of zero
+y2z(t::Tangent) = map(y2z, ChainRulesCore.backing(canonicalize(t)))  # namedtuples!
+y2z(x) = x
 
 @testset verbose=true "Optimisers.jl" begin
   @testset verbose=true "Features" begin