replace append! with reduce(vcat, ...)

Author: mcabbott

src/destructure.jl

@@ -3,10 +3,10 @@ using ChainRulesCore: ChainRulesCore, NoTangent, ProjectTo
 const NoT = NoTangent()
 
 """
-    destructure([T], model) -> vector, reconstructor
+    destructure(model) -> vector, reconstructor
 
 Copies all [`trainable`](@ref), [`isnumeric`](@ref) parameters in the model
-to a `Vector{T}`, and returns also a function which reverses this transformation.
+to a vector, and returns also a function which reverses this transformation.
 Differentiable.
 
 # Example
@@ -18,8 +18,8 @@ julia> re([10,20,30])
 (x = [10.0, 20.0], y = (sin, [30.0]))
 ```
 """
-function destructure(::Type{T}, x) where T
-  flat, off, len = alpha!(x, T[])
+function destructure(x)
+  flat, off, len = alpha(x)
   flat, Restucture(x, off, len)
 end
 
@@ -32,19 +32,22 @@ end
 Base.show(io::IO, re::Restucture{T}) where T = print(io, "Restructure(", T.name.name, ", ..., ", re.length, ")")
 
 # This flattens a model, and returns a web of offsets for later use:
-function alpha!(x, flat::AbstractVector)
-  isempty(flat) || error("this won't work")
-  isnumeric(x) && return append!(flat, x), 0  # trivial case
+function alpha(x)
+  isnumeric(x) && return vcat(vec(x)), 0, length(x)  # trivial case
+  arrays = AbstractVector[]
+  len = Ref(0)
   off = fmap(x; exclude = isnumeric, walk = (f, z) -> map(f, _trainable(z))) do y
-    append!(flat, y)
-    length(flat) - length(y)
+    push!(arrays, vec(y))
+    o = len[]
+    len[] = o + length(y)
+    o
   end
-  flat, off, length(flat)
+  reduce(vcat, arrays), off, len[]
 end
 
-function ChainRulesCore.rrule(::typeof(alpha!), x, flat)
-  flat′, off, len = alpha!(x, flat)
-  alpha_back((dflat, _)) = (NoT, beta(x, off, dflat; walk = _Tangent_biwalk, prune = NoT, len), NoT)
+function ChainRulesCore.rrule(::typeof(alpha), x)
+  flat, off, len = alpha(x)
+  alpha_back((dflat, _)) = (NoT, beta(x, off, dflat; walk = _Tangent_biwalk, prune = NoT, len))
   (flat, off, len), alpha_back
 end
 
@@ -100,14 +103,3 @@ function gamma!(x, dx, off::Integer, flat::AbstractVector)
 end
 gamma!(x, dx::Zero, off, flat::AbstractVector) = nothing
 gamma!(x, dx::Zero, off::Integer, flat::AbstractVector) = nothing  # ambiguity
-
-# Least importantly, this infers the eltype if one is not given:
-destructure(x) = destructure(omega(x), x)
-function omega(x)
-  T = Bool
-  fmap(x; exclude = isnumeric, walk = (f, z) -> foreach(f, _trainable(z))) do y
-    T = promote_type(T, eltype(y))
-  end
-  T
-end
-ChainRulesCore.@non_differentiable omega(::Any)

test/destructure.jl

@@ -8,9 +8,7 @@ m6 = (a = m1, b = [4.0 + im], c = m1)
 m7 = TwoThirds((sin, collect(1:3.0)), (cos, collect(4:6.0)), (tan, collect(7:9.0)))
 
 @testset "flatten & restore" begin
-  @test destructure(Int, m1)[1] isa Vector{Int}
   @test destructure(m1)[1] isa Vector{Float64}
-
   @test destructure(m1)[1] == 1:3
   @test destructure(m2)[1] == 1:6
   @test destructure(m3)[1] == 1:6