import Base: * toarray(xs::AbstractArray, ys::AbstractArray) = ys toarray(xs::AbstractArray, y) = similar(xs, typeof(y), ()) .= y unarray(xs) = xs unarray(xs::AbstractArray{T,0} where T) = xs[] Base.getindex(xs::TrackedArray, i...) = TrackedArray(Call(getindex, xs, i...), toarray(xs.x, xs.x[i...])) function back!(::typeof(getindex), Δ, xs::TrackedArray, i...) Δ′ = zeros(xs.x) Δ′[i...] = unarray(Δ) @back!(xs, Δ′) end Base.:-(xs::TrackedArray) = TrackedArray(Call(-, xs)) back!(::typeof(-), Δ, xs::TrackedArray) = back!(xs, -Δ) Base.transpose(xs::TrackedArray) = TrackedArray(Call(transpose, xs)) Base.ctranspose(xs::TrackedArray) = TrackedArray(Call(ctranspose, xs)) back!(::typeof(transpose), Δ, xs) = @back!(xs, trim(xs, Δ.')) back!(::typeof(ctranspose), Δ, xs) = @back!(xs, trim(xs, Δ')) Base.vcat(a::TrackedVector, b::TrackedVector) = TrackedArray(Call(vcat, a, b)) Base.vcat(a::TrackedVector, b::AbstractVector) = TrackedArray(Call(vcat, a, b)) Base.vcat(a::AbstractVector, b::TrackedVector) = TrackedArray(Call(vcat, a, b)) Base.vcat(a::TrackedArray, b::TrackedArray) = TrackedArray(Call(vcat, a, b)) Base.vcat(a::TrackedArray, b::AbstractArray) = TrackedArray(Call(vcat, a, b)) Base.vcat(a::AbstractArray, b::TrackedArray) = TrackedArray(Call(vcat, a, b)) function back!(::typeof(vcat), Δ, xs, ys) i = Base.tail(map(_ -> :, size(Δ))) @back!(xs, Δ[1:size(xs,1), i...]) @back!(ys, Δ[size(xs,1)+1:end, i...]) end # Reductions Base.sum(xs::TrackedArray, dim) = TrackedArray(Call(sum, xs, dim)) Base.sum(xs::TrackedArray) = TrackedArray(Call(sum, xs), toarray(xs.x, sum(xs.x))) Base.sum(xs::TrackedScalar, dim...) = xs back!(::typeof(sum), Δ, xs::TrackedArray, dim...) = back!(xs, similar(xs.x) .= Δ) Base.maximum(xs::TrackedArray, args...) = maximum(xs.x, args...) Base.findfirst(xs::TrackedArray, args...) = findfirst(xs.x, args...) # BLAS a::TrackedMatrix * b::TrackedMatrix = TrackedArray(Call(*, a, b)) a::TrackedMatrix * b::AbstractMatrix = TrackedArray(Call(*, a, b)) a::AbstractMatrix * b::TrackedMatrix = TrackedArray(Call(*, a, b)) a::TrackedMatrix * b::TrackedVector = TrackedArray(Call(*, a, b)) a::TrackedMatrix * b::AbstractVector = TrackedArray(Call(*, a, b)) a::AbstractMatrix * b::TrackedVector = TrackedArray(Call(*, a, b)) function back!(::typeof(*), Δ, a::AbstractMatrix, b::AbstractVecOrMat) @back!(a, A_mul_Bt(Δ, data(b))) @back!(b, At_mul_B(data(a), Δ)) end # NNlib import NNlib: softmax, ∇softmax softmax(xs::TrackedArray) = TrackedArray(Call(softmax, xs)) back!(::typeof(softmax), Δ, xs) = @back!(xs, ∇softmax(Δ, data(xs))) # Broadcasting using ForwardDiff: Dual, partials struct Broadcasted{T} data::T end (b::Broadcasted)(xs...) = map(x -> x.value, b.data) dualify(xs, n) = xs dualify(xs::TrackedArray, ps) = map(x -> Dual(x, ps), data(xs)) function tracked_broadcast(f, args::Vararg{Any,N}) where N dargs = map((x,i) -> dualify(x, ntuple(j -> i==j, Val{N})), args, ntuple(identity, Val{N})) # TrackedArray(Call(Broadcasted(broadcast(f, dargs...)), args...)) # Works around a 0.6 type inference issue b = Broadcasted(broadcast(f, dargs...)) TrackedArray(Call(b, args...), b()) end trim(x, Δ) = reshape(Δ, ntuple(i -> size(Δ, i), Val{ndims(x)})) unbroadcast(x, Δ) = size(x) == size(Δ) ? Δ : trim(x, sum(Δ, filter(n -> size(x, n) == 1, 1:ndims(Δ)))) function getpartial(Δ, x, i) @inbounds p = getindex(partials(x), i) return Δ * p end function back!(b::Broadcasted, Δ, args::Vararg{Any,N}) where N Δargs = ntuple(i -> getpartial.(Δ, b.data, i), Val{N}) foreach((x, Δ) -> @back!(x, unbroadcast(x, Δ)), args, Δargs) end Base.Broadcast._containertype(::Type{<:TrackedArray}) = TrackedArray Base.Broadcast.promote_containertype(::Type{TrackedArray}, ::Type{TrackedArray}) = TrackedArray Base.Broadcast.promote_containertype(::Type{Array}, ::Type{TrackedArray}) = TrackedArray Base.Broadcast.promote_containertype(::Type{TrackedArray}, ::Type{Array}) = TrackedArray Base.Broadcast.promote_containertype(::Type{TrackedArray}, ct) = TrackedArray Base.Broadcast.promote_containertype(ct, ::Type{TrackedArray}) = TrackedArray Base.Broadcast.broadcast_indices(::Type{TrackedArray}, A::Ref) = () Base.Broadcast.broadcast_indices(::Type{TrackedArray}, A) = indices(A) Base.Broadcast.broadcast_c(f, ::Type{TrackedArray}, A, Bs...) = tracked_broadcast(f, A, Bs...)