Zygote DiffEq Integration (Pun Intended) about zygote.jl HOT 4 OPEN

MethodError: no method matching Float64(::ForwardDiff.Dual{Nothing,Float64,2})
  ...
Stacktrace:
 [1] convert(::Type{Float64}, ::ForwardDiff.Dual{Nothing,Float64,2}) at ./number.jl:7
 [2] (::getfield(Zygote, Symbol("##819#822")){typeof(convert)})(::Type, ::Float64) at /home/stefan/.julia/packages/Zygote/Ohw1K/src/lib/broadcast.jl:113

f(x,p,t) = p*x
t = 0:0.1:1
function sol(a)
    pr = ODEProblem(f,1.,(0.,1.),a)
    s = solve(pr,Euler(),dt=0.01, saveat=t)
    s.u
end
Zygote.gradient(a->sum(sol(a)),1.)

Compiling Tuple{getfield(DiffEqBase, Symbol("##solve#442")),Base.Iterators.Pairs{Symbol,Any,Tuple{Symbol,Symbol},NamedTuple{(:dt, :saveat),Tuple{Float64,StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}}}},typeof(solve),ODEProblem{Float64,Tuple{Float64,Float64},false,Float64,ODEFunction{false,typeof(f),LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Nothing,DiffEqBase.StandardODEProblem},Euler}: BoundsError: attempt to access 0-element UnitRange{Int64} at index [1]

Stacktrace:
 [1] throw_boundserror(::UnitRange{Int64}, ::Int64) at ./abstractarray.jl:484
 [2] getindex at ./range.jl:597 [inlined]
 [3] getindex at /home/stefan/.julia/packages/IRTools/Y9ACs/src/ir/wrap.jl:23 [inlined]
 [4] first at ./abstractarray.jl:270 [inlined]

using DiffEqSensitivity, OrdinaryDiffEq, Zygote

function fiip(du,u,p,t)
  du[1] = dx = p[1]*u[1] - p[2]*u[1]*u[2]
  du[2] = dy = -p[3]*u[2] + p[4]*u[1]*u[2]
end
function foop(u,p,t)
  dx = p[1]*u[1] - p[2]*u[1]*u[2]
  dy = -p[3]*u[2] + p[4]*u[1]*u[2]
  [dx,dy]
end

p = [1.5,1.0,3.0,1.0]; u0 = [1.0;1.0]
prob = ODEProblem(fiip,u0,(0.0,10.0),p)
proboop = ODEProblem(foop,u0,(0.0,10.0),p)

Zygote.gradient((u0,p)->sum(solve(proboop,Tsit5(),u0=u0,p=p,abstol=1e-14,reltol=1e-14,saveat=0.1,sensealg=ZygoteAdjoint())),u0,p)
Zygote.gradient((u0,p)->sum(solve(proboop,Tsit5(),u0=u0,p=p,abstol=1e-14,reltol=1e-14,saveat=0.1,sensealg=SensitivityADPassThrough())),u0,p)

# Harder!
Zygote.gradient((u0,p)->sum(solve(proboop,Tsit5(),u0=u0,p=p,abstol=1e-14,reltol=1e-14,saveat=0.1,sensealg=ZygoteAdjoint())),u0,p)
Zygote.gradient((u0,p)->sum(solve(proboop,Tsit5(),u0=u0,p=p,abstol=1e-14,reltol=1e-14,saveat=0.1,sensealg=SensitivityADPassThrough())),u0,p)