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SciML / DiffEqFlux.jl

Pre-built implicit layer architectures with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods
https://docs.sciml.ai/DiffEqFlux/stable
MIT License
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Error when running example on README #63

Closed ranjanan closed 5 years ago

ranjanan commented 5 years ago 
using DifferentialEquations
function lotka_volterra(du,u,p,t)
  x, y = u
  α, β, δ, γ = p
  du[1] = dx = α*x - β*x*y
  du[2] = dy = -δ*y + γ*x*y
end
u0 = [1.0,1.0]
tspan = (0.0,10.0)
p = [1.5,1.0,3.0,1.0]
prob = ODEProblem(lotka_volterra,u0,tspan,p)
sol = solve(prob,Tsit5())

using Flux, DiffEqFlux
p = param([2.2, 1.0, 2.0, 0.4]) # Initial Parameter Vector
params = Flux.Params([p])

function predict_adjoint() # Our 1-layer neural network
  Tracker.collect(diffeq_adjoint(p,prob,Tsit5(),saveat=0.1))
end
loss_adjoint() = sum(abs2,x-1 for x in predict_adjoint())

data = Iterators.repeated((), 100)
opt = ADAM(0.1)
cb = function () #callback function to observe training
  display(loss_adjoint())
  # using `remake` to re-create our `prob` with current parameters `p`
  display(plot(solve(remake(prob,p=Flux.data(p)),Tsit5(),saveat=0.1),ylim=(0,6)))
end

# Display the ODE with the initial parameter values.
cb()

Flux.train!(loss_adjoint, params, data, opt, cb = cb)

Error: 

julia> Flux.train!(loss_adjoint, params, data, opt, cb = cb)
ERROR: BoundsError: attempt to access 0-element StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}} at index [0]
Stacktrace:
 [1] throw_boundserror(::StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}, ::Tuple{Int64}) at ./abstractarray.jl:484
 [2] checkbounds at ./abstractarray.jl:449 [inlined]
 [3] getindex at ./range.jl:638 [inlined]
 [4] tstop_saveat_disc_handling at /homes/anantharaman/.julia/packages/OrdinaryDiffEq/qdrLN/src/solve.jl:408 [inlined]
 [5] #__init#334(::Float64, ::Array{Float64,1}, ::Array{Float64,1}, ::Nothing, ::Bool, ::Bool, ::Bool, ::Bool, ::Nothing, ::Bool, ::Bool, ::Float64, ::Float64, ::Float64, ::Bool, ::Bool, ::Rational{Int64}, ::Float64, ::Float64, ::Rational{Int64}, ::Int64, ::Int64, ::Int64, ::Rational{Int64}, ::Bool, ::Int64, ::Nothing, ::Nothing, ::Int64, ::typeof(DiffEqBase.ODE_DEFAULT_NORM), ::typeof(LinearAlgebra.opnorm), ::typeof(DiffEqBase.ODE_DEFAULT_ISOUTOFDOMAIN), ::typeof(DiffEqBase.ODE_DEFAULT_UNSTABLE_CHECK), ::Bool, ::Bool, ::Bool, ::Bool, ::Bool, ::Bool, ::Bool, ::Int64, ::String, ::typeof(DiffEqBase.ODE_DEFAULT_PROG_MESSAGE), ::Nothing, ::Bool, ::Bool, ::Bool, ::Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{,Tuple{}}}, ::typeof(DiffEqBase.__init), ::ODEProblem{Array{Float64,1},Tuple{Float64,Float64},true,Array{Float64,1},ODEFunction{true,DiffEqSensitivity.ODEAdjointSensitivityFunction{Array{Float64,1},Array{Float64,1},Array{Float64,1},Nothing,Nothing,Nothing,Nothing,Nothing,DiffEqSensitivity.SensitivityAlg{0,true,Val{:central}},Nothing,Nothing,Nothing,Nothing,Array{Float64,1},ODESolution{Float64,2,Array{Array{Float64,1},1},Nothing,Nothing,Array{Float64,1},Array{Array{Array{Float64,1},1},1},ODEProblem{Array{Float64,1},Tuple{Float64,Float64},true,Array{Float64,1},ODEFunction{true,typeof(lotka_volterra),LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Nothing,DiffEqBase.StandardODEProblem},Tsit5,OrdinaryDiffEq.InterpolationData{ODEFunction{true,typeof(lotka_volterra),LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Array{Array{Float64,1},1},Array{Float64,1},Array{Array{Array{Float64,1},1},1},OrdinaryDiffEq.Tsit5Cache{Array{Float64,1},Array{Float64,1},Array{Float64,1},OrdinaryDiffEq.Tsit5ConstantCache{Float64,Float64}}},DiffEqBase.DEStats},Nothing},LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},CallbackSet{Tuple{},Tuple{DiscreteCallback{getfield(DiffEqCallbacks, Symbol("##31#34")){Base.RefValue{Union{Nothing, Float64}}},getfield(DiffEqCallbacks, Symbol("##32#35")){getfield(DiffEqSensitivity, Symbol("#time_choice#20")){Array{Float64,1},Base.RefValue{Int64}},getfield(DiffEqSensitivity, Symbol("##19#21")){getfield(DiffEqFlux, Symbol("#df#27")),Bool,Array{Float64,1},Array{Float64,1},Base.RefValue{Int64},Int64},Base.RefValue{Union{Nothing, Float64}}},getfield(DiffEqCallbacks, Symbol("##33#36")){typeof(DiffEqBase.INITIALIZE_DEFAULT),Bool,getfield(DiffEqSensitivity, Symbol("#time_choice#20")){Array{Float64,1},Base.RefValue{Int64}},Base.RefValue{Union{Nothing, Float64}},getfield(DiffEqCallbacks, Symbol("##32#35")){getfield(DiffEqSensitivity, Symbol("#time_choice#20")){Array{Float64,1},Base.RefValue{Int64}},getfield(DiffEqSensitivity, Symbol("##19#21")){getfield(DiffEqFlux, Symbol("#df#27")),Bool,Array{Float64,1},Array{Float64,1},Base.RefValue{Int64},Int64},Base.RefValue{Union{Nothing, Float64}}}}}}},DiffEqBase.StandardODEProblem}, ::Tsit5, ::Array{Array{Float64,1},1}, ::Array{Float64,1}, ::Array{Any,1}, ::Type{Val{true}}) at /homes/anantharaman/.julia/packages/OrdinaryDiffEq/qdrLN/src/solve.jl:154
 [6] (::getfield(DiffEqBase, Symbol("#kw##__init")))(::NamedTuple{(:abstol, :reltol, :save_everystep, :save_start, :saveat),Tuple{Float64,Float64,Bool,Bool,Float64}}, ::typeof(DiffEqBase.__init), ::ODEProblem{Array{Float64,1},Tuple{Float64,Float64},true,Array{Float64,1},ODEFunction{true,DiffEqSensitivity.ODEAdjointSensitivityFunction{Array{Float64,1},Array{Float64,1},Array{Float64,1},Nothing,Nothing,Nothing,Nothing,Nothing,DiffEqSensitivity.SensitivityAlg{0,true,Val{:central}},Nothing,Nothing,Nothing,Nothing,Array{Float64,1},ODESolution{Float64,2,Array{Array{Float64,1},1},Nothing,Nothing,Array{Float64,1},Array{Array{Array{Float64,1},1},1},ODEProblem{Array{Float64,1},Tuple{Float64,Float64},true,Array{Float64,1},ODEFunction{true,typeof(lotka_volterra),LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Nothing,DiffEqBase.StandardODEProblem},Tsit5,OrdinaryDiffEq.InterpolationData{ODEFunction{true,typeof(lotka_volterra),LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Array{Array{Float64,1},1},Array{Float64,1},Array{Array{Array{Float64,1},1},1},OrdinaryDiffEq.Tsit5Cache{Array{Float64,1},Array{Float64,1},Array{Float64,1},OrdinaryDiffEq.Tsit5ConstantCache{Float64,Float64}}},DiffEqBase.DEStats},Nothing},LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},CallbackSet{Tuple{},Tuple{DiscreteCallback{getfield(DiffEqCallbacks, Symbol("##31#34")){Base.RefValue{Union{Nothing, Float64}}},getfield(DiffEqCallbacks, Symbol("##32#35")){getfield(DiffEqSensitivity, Symbol("#time_choice#20")){Array{Float64,1},Base.RefValue{Int64}},getfield(DiffEqSensitivity, Symbol("##19#21")){getfield(DiffEqFlux, Symbol("#df#27")),Bool,Array{Float64,1},Array{Float64,1},Base.RefValue{Int64},Int64},Base.RefValue{Union{Nothing, Float64}}},getfield(DiffEqCallbacks, Symbol("##33#36")){typeof(DiffEqBase.INITIALIZE_DEFAULT),Bool,getfield(DiffEqSensitivity, Symbol("#time_choice#20")){Array{Float64,1},Base.RefValue{Int64}},Base.RefValue{Union{Nothing, Float64}},getfield(DiffEqCallbacks, Symbol("##32#35")){getfield(DiffEqSensitivity, Symbol("#time_choice#20")){Array{Float64,1},Base.RefValue{Int64}},getfield(DiffEqSensitivity, Symbol("##19#21")){getfield(DiffEqFlux, Symbol("#df#27")),Bool,Array{Float64,1},Array{Float64,1},Base.RefValue{Int64},Int64},Base.RefValue{Union{Nothing, Float64}}}}}}},DiffEqBase.StandardODEProblem}, ::Tsit5, ::Array{Array{Float64,1},1}, ::Array{Float64,1}, ::Array{Any,1}, ::Type{Val{true}}) at ./none:0 (repeats 5 times)
 [7] #__solve#333(::Base.Iterators.Pairs{Symbol,Real,NTuple{5,Symbol},NamedTuple{(:abstol, :reltol, :save_everystep, :save_start, :saveat),Tuple{Float64,Float64,Bool,Bool,Float64}}}, ::Function, ::ODEProblem{Array{Float64,1},Tuple{Float64,Float64},true,Array{Float64,1},ODEFunction{true,DiffEqSensitivity.ODEAdjointSensitivityFunction{Array{Float64,1},Array{Float64,1},Array{Float64,1},Nothing,Nothing,Nothing,Nothing,Nothing,DiffEqSensitivity.SensitivityAlg{0,true,Val{:central}},Nothing,Nothing,Nothing,Nothing,Array{Float64,1},ODESolution{Float64,2,Array{Array{Float64,1},1},Nothing,Nothing,Array{Float64,1},Array{Array{Array{Float64,1},1},1},ODEProblem{Array{Float64,1},Tuple{Float64,Float64},true,Array{Float64,1},ODEFunction{true,typeof(lotka_volterra),LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Nothing,DiffEqBase.StandardODEProblem},Tsit5,OrdinaryDiffEq.InterpolationData{ODEFunction{true,typeof(lotka_volterra),LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Array{Array{Float64,1},1},Array{Float64,1},Array{Array{Array{Float64,1},1},1},OrdinaryDiffEq.Tsit5Cache{Array{Float64,1},Array{Float64,1},Array{Float64,1},OrdinaryDiffEq.Tsit5ConstantCache{Float64,Float64}}},DiffEqBase.DEStats},Nothing},LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},CallbackSet{Tuple{},Tuple{DiscreteCallback{getfield(DiffEqCallbacks, Symbol("##31#34")){Base.RefValue{Union{Nothing, Float64}}},getfield(DiffEqCallbacks, Symbol("##32#35")){getfield(DiffEqSensitivity, Symbol("#time_choice#20")){Array{Float64,1},Base.RefValue{Int64}},getfield(DiffEqSensitivity, Symbol("##19#21")){getfield(DiffEqFlux, Symbol("#df#27")),Bool,Array{Float64,1},Array{Float64,1},Base.RefValue{Int64},Int64},Base.RefValue{Union{Nothing, Float64}}},getfield(DiffEqCallbacks, Symbol("##33#36")){typeof(DiffEqBase.INITIALIZE_DEFAULT),Bool,getfield(DiffEqSensitivity, Symbol("#time_choice#20")){Array{Float64,1},Base.RefValue{Int64}},Base.RefValue{Union{Nothing, Float64}},getfield(DiffEqCallbacks, Symbol("##32#35")){getfield(DiffEqSensitivity, Symbol("#time_choice#20")){Array{Float64,1},Base.RefValue{Int64}},getfield(DiffEqSensitivity, Symbol("##19#21")){getfield(DiffEqFlux, Symbol("#df#27")),Bool,Array{Float64,1},Array{Float64,1},Base.RefValue{Int64},Int64},Base.RefValue{Union{Nothing, Float64}}}}}}},DiffEqBase.StandardODEProblem}, ::Tsit5) at /homes/anantharaman/.julia/packages/OrdinaryDiffEq/qdrLN/src/solve.jl:4
 [8] #__solve at ./none:0 [inlined]
 [9] #solve#381 at /homes/anantharaman/.julia/packages/DiffEqBase/hia0S/src/solve.jl:39 [inlined]
 [10] (::getfield(DiffEqBase, Symbol("#kw##solve")))(::NamedTuple{(:abstol, :reltol, :save_everystep, :save_start, :saveat),Tuple{Float64,Float64,Bool,Bool,Float64}}, ::typeof(solve), ::ODEProblem{Array{Float64,1},Tuple{Float64,Float64},true,Array{Float64,1},ODEFunction{true,DiffEqSensitivity.ODEAdjointSensitivityFunction{Array{Float64,1},Array{Float64,1},Array{Float64,1},Nothing,Nothing,Nothing,Nothing,Nothing,DiffEqSensitivity.SensitivityAlg{0,true,Val{:central}},Nothing,Nothing,Nothing,Nothing,Array{Float64,1},ODESolution{Float64,2,Array{Array{Float64,1},1},Nothing,Nothing,Array{Float64,1},Array{Array{Array{Float64,1},1},1},ODEProblem{Array{Float64,1},Tuple{Float64,Float64},true,Array{Float64,1},ODEFunction{true,typeof(lotka_volterra),LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Nothing,DiffEqBase.StandardODEProblem},Tsit5,OrdinaryDiffEq.InterpolationData{ODEFunction{true,typeof(lotka_volterra),LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Array{Array{Float64,1},1},Array{Float64,1},Array{Array{Array{Float64,1},1},1},OrdinaryDiffEq.Tsit5Cache{Array{Float64,1},Array{Float64,1},Array{Float64,1},OrdinaryDiffEq.Tsit5ConstantCache{Float64,Float64}}},DiffEqBase.DEStats},Nothing},LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},CallbackSet{Tuple{},Tuple{DiscreteCallback{getfield(DiffEqCallbacks, Symbol("##31#34")){Base.RefValue{Union{Nothing, Float64}}},getfield(DiffEqCallbacks, Symbol("##32#35")){getfield(DiffEqSensitivity, Symbol("#time_choice#20")){Array{Float64,1},Base.RefValue{Int64}},getfield(DiffEqSensitivity, Symbol("##19#21")){getfield(DiffEqFlux, Symbol("#df#27")),Bool,Array{Float64,1},Array{Float64,1},Base.RefValue{Int64},Int64},Base.RefValue{Union{Nothing, Float64}}},getfield(DiffEqCallbacks, Symbol("##33#36")){typeof(DiffEqBase.INITIALIZE_DEFAULT),Bool,getfield(DiffEqSensitivity, Symbol("#time_choice#20")){Array{Float64,1},Base.RefValue{Int64}},Base.RefValue{Union{Nothing, Float64}},getfield(DiffEqCallbacks, Symbol("##32#35")){getfield(DiffEqSensitivity, Symbol("#time_choice#20")){Array{Float64,1},Base.RefValue{Int64}},getfield(DiffEqSensitivity, Symbol("##19#21")){getfield(DiffEqFlux, Symbol("#df#27")),Bool,Array{Float64,1},Array{Float64,1},Base.RefValue{Int64},Int64},Base.RefValue{Union{Nothing, Float64}}}}}}},DiffEqBase.StandardODEProblem}, ::Tsit5) at ./none:0
 [11] #adjoint_sensitivities_u0#24(::Float64, ::Float64, ::Float64, ::Float64, ::DiffEqSensitivity.SensitivityAlg{0,true,Val{:central}}, ::Array{Float64,1}, ::Base.Iterators.Pairs{Symbol,Float64,Tuple{Symbol},NamedTuple{(:saveat,),Tuple{Float64}}}, ::Function, ::ODESolution{Float64,2,Array{Array{Float64,1},1},Nothing,Nothing,Array{Float64,1},Array{Array{Array{Float64,1},1},1},ODEProblem{Array{Float64,1},Tuple{Float64,Float64},true,Array{Float64,1},ODEFunction{true,typeof(lotka_volterra),LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Nothing,DiffEqBase.StandardODEProblem},Tsit5,OrdinaryDiffEq.InterpolationData{ODEFunction{true,typeof(lotka_volterra),LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Array{Array{Float64,1},1},Array{Float64,1},Array{Array{Array{Float64,1},1},1},OrdinaryDiffEq.Tsit5Cache{Array{Float64,1},Array{Float64,1},Array{Float64,1},OrdinaryDiffEq.Tsit5ConstantCache{Float64,Float64}}},DiffEqBase.DEStats}, ::Tsit5, ::getfield(DiffEqFlux, Symbol("#df#27")), ::Array{Float64,1}, ::Nothing) at /homes/anantharaman/.julia/packages/DiffEqSensitivity/GkTme/src/adjoint_sensitivity.jl:326
 [12] (::getfield(DiffEqSensitivity, Symbol("#kw##adjoint_sensitivities_u0")))(::NamedTuple{(:sensealg, :saveat),Tuple{DiffEqSensitivity.SensitivityAlg{0,true,Val{:central}},Float64}}, ::typeof(DiffEqSensitivity.adjoint_sensitivities_u0), ::ODESolution{Float64,2,Array{Array{Float64,1},1},Nothing,Nothing,Array{Float64,1},Array{Array{Array{Float64,1},1},1},ODEProblem{Array{Float64,1},Tuple{Float64,Float64},true,Array{Float64,1},ODEFunction{true,typeof(lotka_volterra),LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Nothing,DiffEqBase.StandardODEProblem},Tsit5,OrdinaryDiffEq.InterpolationData{ODEFunction{true,typeof(lotka_volterra),LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Array{Array{Float64,1},1},Array{Float64,1},Array{Array{Array{Float64,1},1},1},OrdinaryDiffEq.Tsit5Cache{Array{Float64,1},Array{Float64,1},Array{Float64,1},OrdinaryDiffEq.Tsit5ConstantCache{Float64,Float64}}},DiffEqBase.DEStats}, ::Tsit5, ::Function, ::Array{Float64,1}, ::Nothing) at ./none:0 (repeats 2 times)
 [13] (::getfield(DiffEqFlux, Symbol("##24#26")){DiffEqSensitivity.SensitivityAlg{0,true,Val{:central}},Base.Iterators.Pairs{Symbol,Float64,Tuple{Symbol},NamedTuple{(:saveat,),Tuple{Float64}}},Array{Float64,1},Tuple{Tsit5},ODESolution{Float64,2,Array{Array{Float64,1},1},Nothing,Nothing,Array{Float64,1},Array{Array{Array{Float64,1},1},1},ODEProblem{Array{Float64,1},Tuple{Float64,Float64},true,Array{Float64,1},ODEFunction{true,typeof(lotka_volterra),LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Nothing,DiffEqBase.StandardODEProblem},Tsit5,OrdinaryDiffEq.InterpolationData{ODEFunction{true,typeof(lotka_volterra),LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Array{Array{Float64,1},1},Array{Float64,1},Array{Array{Array{Float64,1},1},1},OrdinaryDiffEq.Tsit5Cache{Array{Float64,1},Array{Float64,1},Array{Float64,1},OrdinaryDiffEq.Tsit5ConstantCache{Float64,Float64}}},DiffEqBase.DEStats}})(::Array{Float64,2}) at /homes/anantharaman/.julia/packages/DiffEqFlux/RFBjh/src/Flux/layers.jl:100
 [14] back_(::Tracker.Call{getfield(DiffEqFlux, Symbol("##24#26")){DiffEqSensitivity.SensitivityAlg{0,true,Val{:central}},Base.Iterators.Pairs{Symbol,Float64,Tuple{Symbol},NamedTuple{(:saveat,),Tuple{Float64}}},Array{Float64,1},Tuple{Tsit5},ODESolution{Float64,2,Array{Array{Float64,1},1},Nothing,Nothing,Array{Float64,1},Array{Array{Array{Float64,1},1},1},ODEProblem{Array{Float64,1},Tuple{Float64,Float64},true,Array{Float64,1},ODEFunction{true,typeof(lotka_volterra),LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Nothing,DiffEqBase.StandardODEProblem},Tsit5,OrdinaryDiffEq.InterpolationData{ODEFunction{true,typeof(lotka_volterra),LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Array{Array{Float64,1},1},Array{Float64,1},Array{Array{Array{Float64,1},1},1},OrdinaryDiffEq.Tsit5Cache{Array{Float64,1},Array{Float64,1},Array{Float64,1},OrdinaryDiffEq.Tsit5ConstantCache{Float64,Float64}}},DiffEqBase.DEStats}},Tuple{Tracker.Tracked{Array{Float64,1}},Nothing,Nothing,Nothing}}, ::Array{Float64,2}, ::Bool) at /homes/anantharaman/.julia/packages/Tracker/RRYy6/src/back.jl:35
 [15] back(::Tracker.Tracked{Array{Float64,2}}, ::Array{Float64,2}, ::Bool) at /homes/anantharaman/.julia/packages/Tracker/RRYy6/src/back.jl:58
 [16] #13 at /homes/anantharaman/.julia/packages/Tracker/RRYy6/src/back.jl:38 [inlined]
 [17] foreach at ./abstractarray.jl:1867 [inlined]
 [18] back_(::Tracker.Call{getfield(Tracker, Symbol("##372#374")){Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{,Tuple{}}},TrackedArray{…,Array{Float64,2}},Tuple{CartesianIndex{2}}},Tuple{Tracker.Tracked{Array{Float64,2}},Nothing}}, ::Float64, ::Bool) at /homes/anantharaman/.julia/packages/Tracker/RRYy6/src/back.jl:38
 [19] back(::Tracker.Tracked{Float64}, ::Float64, ::Bool) at /homes/anantharaman/.julia/packages/Tracker/RRYy6/src/back.jl:58
 [20] #13 at /homes/anantharaman/.julia/packages/Tracker/RRYy6/src/back.jl:38 [inlined]
 [21] foreach at ./abstractarray.jl:1867 [inlined]
 [22] back_(::Tracker.Call{getfield(Tracker, Symbol("##344#347")){Int64},Tuple{Tracker.Tracked{Float64},Nothing}}, ::Float64, ::Bool) at /homes/anantharaman/.julia/packages/Tracker/RRYy6/src/back.jl:38
 [23] back(::Tracker.Tracked{Float64}, ::Float64, ::Bool) at /homes/anantharaman/.julia/packages/Tracker/RRYy6/src/back.jl:58
 [24] foreach at /homes/anantharaman/.julia/packages/Tracker/RRYy6/src/back.jl:38 [inlined]
 [25] back_(::Tracker.Call{getfield(Tracker, Symbol("##73#74")){Tracker.TrackedReal{Float64}},Tuple{Tracker.Tracked{Float64}}}, ::Float64, ::Bool) at /homes/anantharaman/.julia/packages/Tracker/RRYy6/src/back.jl:38
 [26] back(::Tracker.Tracked{Float64}, ::Float64, ::Bool) at /homes/anantharaman/.julia/packages/Tracker/RRYy6/src/back.jl:58
 [27] #13 at /homes/anantharaman/.julia/packages/Tracker/RRYy6/src/back.jl:38 [inlined]
 [28] foreach at ./abstractarray.jl:1867 [inlined]
 [29] back_(::Tracker.Call{getfield(Tracker, Symbol("##253#256")),Tuple{Tracker.Tracked{Float64},Tracker.Tracked{Float64}}}, ::Float64, ::Bool) at /homes/anantharaman/.julia/packages/Tracker/RRYy6/src/back.jl:38
 [30] back(::Tracker.Tracked{Float64}, ::Int64, ::Bool) at /homes/anantharaman/.julia/packages/Tracker/RRYy6/src/back.jl:58
 [31] #back!#15 at /homes/anantharaman/.julia/packages/Tracker/RRYy6/src/back.jl:77 [inlined]
 [32] #back! at ./none:0 [inlined]
 [33] #back!#32 at /homes/anantharaman/.julia/packages/Tracker/RRYy6/src/lib/real.jl:16 [inlined]
 [34] back!(::Tracker.TrackedReal{Float64}) at /homes/anantharaman/.julia/packages/Tracker/RRYy6/src/lib/real.jl:14
 [35] gradient_(::getfield(Flux.Optimise, Symbol("##14#20")){typeof(loss_adjoint)}, ::Tracker.Params) at /homes/anantharaman/.julia/packages/Tracker/RRYy6/src/back.jl:4
 [36] #gradient#24(::Bool, ::Function, ::Function, ::Tracker.Params) at /homes/anantharaman/.julia/packages/Tracker/RRYy6/src/back.jl:164
 [37] gradient at /homes/anantharaman/.julia/packages/Tracker/RRYy6/src/back.jl:164 [inlined]
 [38] macro expansion at /homes/anantharaman/.julia/packages/Flux/qXNjB/src/optimise/train.jl:71 [inlined]
 [39] macro expansion at /homes/anantharaman/.julia/packages/Juno/TfNYn/src/progress.jl:124 [inlined]
 [40] #train!#12(::getfield(Main, Symbol("##59#60")), ::Function, ::Function, ::Tracker.Params, ::Base.Iterators.Take{Base.Iterators.Repeated{Tuple{}}}, ::ADAM) at /homes/anantharaman/.julia/packages/Flux/qXNjB/src/optimise/train.jl:69
 [41] (::getfield(Flux.Optimise, Symbol("#kw##train!")))(::NamedTuple{(:cb,),Tuple{getfield(Main, Symbol("##59#60"))}}, ::typeof(Flux.Optimise.train!), ::Function, ::Tracker.Params, ::Base.Iterators.Take{Base.Iterators.Repeated{Tuple{}}}, ::ADAM) at ./none:0
 [42] top-level scope at none:0

Status: 

    Status `~/Work/Training/Project.toml`
  [aae7a2af] DiffEqFlux v0.5.2
  [0c46a032] DifferentialEquations v6.6.0
  [587475ba] Flux v0.8.3
  [f6369f11] ForwardDiff v0.10.3
  [1dea7af3] OrdinaryDiffEq v5.12.0
  [37e2e3b7] ReverseDiff v0.3.1
  [c3572dad] Sundials v3.6.1
ranjanan commented 5 years ago

Dup of #12