DiffEqFlux.sciml_train giving UndefVarError: ProgressLogging not defined

General Usage
1

When running the Optimization of Ordinary Differential Equations tutorial in the DiffEqFlux documentation, I get the following error

ERROR: LoadError: UndefVarError: ProgressLogging not defined
Stacktrace:
 [1] default_logger(::Atom.Progress.JunoProgressLogger) at C:\Users\jmurp\.julia\packages\DiffEqBase\VoY3t\src\utils.jl:262
 [2] sciml_train(::Function, ::Array{Float64,1}, ::ADAM, ::Base.Iterators.Cycle{Tuple{DiffEqFlux.NullData}}; cb::Function, maxiters::Int64, progress::Bool, save_best::Bool) at C:\Users\jmurp\.julia\packages\DiffEqFlux\FZMwP\src\train.jl:42
 [3] top-level scope at C:\Users\jmurp\OneDrive\Desktop\Research\AstroML\Julia\DiffEqFluxTutorials.jl:45
 [4] include_string(::Function, ::Module, ::String, ::String) at .\loading.jl:1088
in expression starting at C:\Users\jmurp\OneDrive\Desktop\Research\AstroML\Julia\DiffEqFluxTutorials.jl:45

My code is identical to the tutorial

using DifferentialEquations, Flux, Optim, DiffEqFlux, DiffEqSensitivity, Plots

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

# Initial Condition
u0 = [1.0, 1.0]

# Simulation Interval and Intermediary Points
tspan = (0.0, 10.0)
tsteps = 0.0:0.1:10.0

# LV parameter p = [α, β, δ, γ]
p = [1.5, 1.0, 3.0, 1.0]

# Setup and Solve the ODE Problem
prob = ODEProblem(lotka_volterra!, u0, tspan, p)
sol = solve(prob, Tsit5())

# Plot the Solution
plot(sol)
savefig("LV_ode.png")

function loss(p)
    sol = solve(prob, Tsit5(), p = p, saveat = tsteps)
    loss = sum(abs2, sol .- 1)
    return loss, sol
end

callback = function (p, l, pred)
    display(l)
    plt = plot(pred, ylim = (0, 6))
    display(plt)
    # Tell sciml_train to not halt the optimization. If return true, then
    # optimization stops.
    return false
end

result_ode = DiffEqFlux.sciml_train(loss, p,
                                    ADAM(0.1),
                                    cb = callback,
                                    maxiters = 100)

My code is runniing on Julia 1.5.0 and my package statuses are :
DifferentialEquations v6.15.0
Flux v0.10.4
Optim v0.21.0
DiffEqFlux v1.17.0
DiffEqSensitivity v6.31.1
Plots v1.6.0

I’ve tried restarting Julia and Atom and building ProgressLogging locally.

2

This was an error in the latest release. Sorry. I fixed this up with the release of DiffEqFlux v1.21.0

3

Got the same error. when I try to download the lastest version of DiffEqFlux i get this compatibility issue…

(@JuliaPro_v1.5.0-1) pkg> add https://github.com/SciML/DiffEqFlux.jl
Updating git-repo https://github.com/SciML/DiffEqFlux.jl
Resolving package versions…
ERROR: Unsatisfiable requirements detected for package Adapt [79e6a3ab]:
Adapt [79e6a3ab] log:
├─possible versions are: [0.3.0-0.3.1, 0.4.0-0.4.2, 1.0.0-1.0.1, 1.1.0, 2.0.0-2.0.2] or uninstalled
├─restricted to versions 1-2 by DiffEqFlux [aae7a2af], leaving only versions [1.0.0-1.0.1, 1.1.0, 2.0.0-2.0.2]
│ └─DiffEqFlux [aae7a2af] log:
│ ├─possible versions are: 1.21.0 or uninstalled
│ └─DiffEqFlux [aae7a2af] is fixed to version 1.21.0
├─restricted by compatibility requirements with CuArrays [3a865a2d] to versions: [1.0.0-1.0.1, 1.1.0]
│ └─CuArrays [3a865a2d] log:
│ ├─possible versions are: [0.2.1, 0.3.0, 0.4.0, 0.5.0, 0.6.0-0.6.2, 0.7.0-0.7.3, 0.8.0-0.8.1, 0.9.0-0.9.1, 1.0.0-1.0.2, 1.1.0, 1.2.0-1.2.1, 1.3.0, 1.4.0-1.4.7, 1.5.0, 1.6.0, 1.7.0-1.7.3, 2.0.0-2.0.1, 2.1.0, 2.2.0-2.2.2] or uninstalled
│ ├─restricted to versions * by an explicit requirement, leaving only versions [0.2.1, 0.3.0, 0.4.0, 0.5.0, 0.6.0-0.6.2, 0.7.0-0.7.3, 0.8.0-0.8.1, 0.9.0-0.9.1, 1.0.0-1.0.2, 1.1.0, 1.2.0-1.2.1, 1.3.0, 1.4.0-1.4.7, 1.5.0, 1.6.0, 1.7.0-1.7.3, 2.0.0-2.0.1, 2.1.0, 2.2.0-2.2.2]
│ ├─restricted by compatibility requirements with GPUArrays [0c68f7d7] to versions: [0.2.1, 2.0.0-2.0.1, 2.1.0, 2.2.0-2.2.2] or uninstalled, leaving only versions: [0.2.1, 2.0.0-2.0.1, 2.1.0, 2.2.0-2.2.2]
│ │ └─GPUArrays [0c68f7d7] log:
│ │ ├─possible versions are: [0.3.0-0.3.4, 0.4.0-0.4.2, 0.5.0, 0.6.0-0.6.1, 0.7.0-0.7.2, 1.0.0-1.0.4, 2.0.0-2.0.1, 3.0.0-3.0.1, 3.1.0, 3.2.0, 3.3.0, 3.4.0-3.4.1, 4.0.0-4.0.1, 5.0.0, 5.1.0] or uninstalled
│ │ ├─restricted to versions * by an explicit requirement, leaving only versions [0.3.0-0.3.4, 0.4.0-0.4.2, 0.5.0, 0.6.0-0.6.1, 0.7.0-0.7.2, 1.0.0-1.0.4, 2.0.0-2.0.1, 3.0.0-3.0.1, 3.1.0, 3.2.0, 3.3.0, 3.4.0-3.4.1, 4.0.0-4.0.1, 5.0.0, 5.1.0]
│ │ ├─restricted by compatibility requirements with CUDA [052768ef] to versions: [3.4.0-3.4.1, 4.0.0-4.0.1, 5.0.0, 5.1.0]
│ │ │ └─CUDA [052768ef] log:
│ │ │ ├─possible versions are: [0.1.0, 1.0.0-1.0.2, 1.1.0, 1.2.0-1.2.1, 1.3.0-1.3.3] or uninstalled
│ │ │ ├─restricted to versions * by an explicit requirement, leaving only versions [0.1.0, 1.0.0-1.0.2, 1.1.0, 1.2.0-1.2.1, 1.3.0-1.3.3]
│ │ │ └─restricted by compatibility requirements with Flux [587475ba] to versions: [1.0.0-1.0.2, 1.1.0, 1.2.0-1.2.1, 1.3.0-1.3.3]
│ │ │ └─Flux [587475ba] log:
│ │ │ ├─possible versions are: [0.4.1, 0.5.0-0.5.4, 0.6.0-0.6.10, 0.7.0-0.7.3, 0.8.0-0.8.3, 0.9.0, 0.10.0-0.10.4, 0.11.0-0.11.1] or uninstalled
│ │ │ └─restricted to versions 0.11 by DiffEqFlux [aae7a2af], leaving only versions 0.11.0-0.11.1
│ │ │ └─DiffEqFlux [aae7a2af] log: see above
│ │ └─restricted by compatibility requirements with CuArrays [3a865a2d] to versions: [3.1.0, 3.2.0, 3.3.0, 3.4.0-3.4.1], leaving only versions: 3.4.0-3.4.1
│ │ └─CuArrays [3a865a2d] log: see above
│ └─restricted by compatibility requirements with CUDAdrv [c5f51814] to versions: [0.4.0, 0.5.0, 0.6.0-0.6.2, 0.7.0-0.7.3, 0.8.0-0.8.1, 1.0.2, 1.1.0, 1.2.0-1.2.1, 1.3.0, 1.4.0-1.4.7, 1.5.0, 1.6.0, 1.7.0-1.7.3, 2.0.0-2.0.1, 2.1.0, 2.2.0-2.2.2] or uninstalled, leaving only versions: [2.0.0-2.0.1, 2.1.0, 2.2.0-2.2.2]
│ └─CUDAdrv [c5f51814] log:
│ ├─possible versions are: [0.8.0-0.8.6, 0.9.0, 1.0.0-1.0.1, 2.0.0, 3.0.0-3.0.1, 3.1.0, 4.0.0-4.0.4, 5.0.0-5.0.1, 5.1.0, 6.0.0-6.0.1, 6.1.0, 6.2.0-6.2.3, 6.3.0] or uninstalled
│ ├─restricted to versions * by an explicit requirement, leaving only versions [0.8.0-0.8.6, 0.9.0, 1.0.0-1.0.1, 2.0.0, 3.0.0-3.0.1, 3.1.0, 4.0.0-4.0.4, 5.0.0-5.0.1, 5.1.0, 6.0.0-6.0.1, 6.1.0, 6.2.0-6.2.3, 6.3.0]
│ ├─restricted by compatibility requirements with CUDAnative [be33ccc6] to versions: [0.8.0-0.8.6, 3.0.0-3.0.1, 3.1.0, 4.0.1-4.0.4, 5.0.0-5.0.1, 5.1.0, 6.0.0-6.0.1, 6.1.0, 6.2.0-6.2.3, 6.3.0]
│ │ └─CUDAnative [be33ccc6] log:
│ │ ├─possible versions are: [0.7.0, 0.8.0-0.8.10, 0.9.0-0.9.1, 0.10.0-0.10.1, 1.0.0-1.0.1, 2.0.0-2.0.1, 2.1.0-2.1.3, 2.2.0-2.2.1, 2.3.0-2.3.1, 2.4.0, 2.5.0-2.5.5, 2.6.0, 2.7.0, 2.8.0-2.8.1, 2.9.0-2.9.1, 2.10.0-2.10.2, 3.0.0-3.0.4, 3.1.0, 3.2.0] or uninstalled
│ │ ├─restricted to versions * by an explicit requirement, leaving only versions [0.7.0, 0.8.0-0.8.10, 0.9.0-0.9.1, 0.10.0-0.10.1, 1.0.0-1.0.1, 2.0.0-2.0.1, 2.1.0-2.1.3, 2.2.0-2.2.1, 2.3.0-2.3.1, 2.4.0, 2.5.0-2.5.5, 2.6.0, 2.7.0, 2.8.0-2.8.1, 2.9.0-2.9.1, 2.10.0-2.10.2, 3.0.0-3.0.4, 3.1.0, 3.2.0]
│ │ ├─restricted by compatibility requirements with Adapt [79e6a3ab] to versions: [0.7.0, 0.8.0-0.8.10, 0.9.0-0.9.1, 2.2.1, 2.3.0-2.3.1, 2.4.0, 2.5.0-2.5.5, 2.6.0, 2.7.0, 2.8.0-2.8.1, 2.9.0-2.9.1, 2.10.0-2.10.2, 3.0.0-3.0.4, 3.1.0, 3.2.0] or uninstalled, leaving only versions: [0.7.0, 0.8.0-0.8.10, 0.9.0-0.9.1, 2.2.1, 2.3.0-2.3.1, 2.4.0, 2.5.0-2.5.5, 2.6.0, 2.7.0, 2.8.0-2.8.1, 2.9.0-2.9.1, 2.10.0-2.10.2, 3.0.0-3.0.4, 3.1.0, 3.2.0]
│ │ │ └─Adapt [79e6a3ab] log: see above
│ │ └─restricted by compatibility requirements with CuArrays [3a865a2d] to versions: [3.0.0-3.0.4, 3.1.0, 3.2.0]
│ │ └─CuArrays [3a865a2d] log: see above
│ ├─restricted by compatibility requirements with CUDAapi [3895d2a7] to versions: [0.8.2-0.8.6, 0.9.0, 1.0.0-1.0.1, 2.0.0,
3.0.0-3.0.1, 3.1.0, 4.0.0-4.0.4, 5.0.0-5.0.1, 5.1.0, 6.0.0-6.0.1, 6.1.0, 6.2.0-6.2.3, 6.3.0] or uninstalled, leaving only versions: [0.8.2-0.8.6, 3.0.0-3.0.1, 3.1.0, 4.0.1-4.0.4, 5.0.0-5.0.1, 5.1.0, 6.0.0-6.0.1, 6.1.0, 6.2.0-6.2.3, 6.3.0]
│ │ └─CUDAapi [3895d2a7] log:
│ │ ├─possible versions are: [0.5.0-0.5.4, 0.6.0-0.6.3, 1.0.0-1.0.1, 1.1.0, 1.2.0, 2.0.0, 2.1.0, 3.0.0, 3.1.0, 4.0.0] or
uninstalled
│ │ ├─restricted to versions * by an explicit requirement, leaving only versions [0.5.0-0.5.4, 0.6.0-0.6.3, 1.0.0-1.0.1,
1.1.0, 1.2.0, 2.0.0, 2.1.0, 3.0.0, 3.1.0, 4.0.0]
│ │ └─restricted by compatibility requirements with CuArrays [3a865a2d] to versions: [3.0.0, 3.1.0, 4.0.0]
│ │ └─CuArrays [3a865a2d] log: see above
│ └─restricted by compatibility requirements with CuArrays [3a865a2d] to versions: [6.0.1, 6.1.0, 6.2.0-6.2.3, 6.3.0]
│ └─CuArrays [3a865a2d] log: see above
└─restricted by compatibility requirements with CUDA [052768ef] to versions: 2.0.0-2.0.2 — no versions left
└─CUDA [052768ef] log: see above

4

That’s because CuArrays was replaced by CUDA.jl

5

Hello, I’m using Juno’s debugger in DiffEqFlux.sciml_train and I get the same error:

debug> ERROR: UndefVarError: ProgressLogging not defined
Stacktrace:
[1] evaluate_call_recurse!(::Any, ::JuliaInterpreter.Frame, ::Expr; enter_generated::Bool) at C:\Users\Sebas.julia\packages\JuliaInterpreter\kDn3E\src\interpret.jl:212
[2] evaluate_call_recurse! at C:\Users\Sebas.julia\packages\JuliaInterpreter\kDn3E\src\interpret.jl:201
[inlined]
[3] eval_rhs(::Any, ::JuliaInterpreter.Frame, ::Expr) at C:\Users\Sebas.julia\packages\JuliaInterpreter\kDn3E\src\interpret.jl:388
[4] step_expr!(::Any, ::JuliaInterpreter.Frame, ::Any, ::Bool) at C:\Users\Sebas.julia\packages\JuliaInterpreter\kDn3E\src\interpret.jl:531
[5] step_expr!(::Any, ::JuliaInterpreter.Frame, ::Bool) at C:\Users\Sebas.julia\packages\JuliaInterpreter\kDn3E\src\interpret.jl:581
[6] finish!(::Any, ::JuliaInterpreter.Frame, ::Bool) at C:\Users\Sebas.julia\packages\JuliaInterpreter\kDn3E\src\commands.jl:14
[7] finish_and_return! at C:\Users\Sebas.julia\packages\JuliaInterpreter\kDn3E\src\commands.jl:29 [inlined]
[8] evaluate_call_recurse!(::Any, ::JuliaInterpreter.Frame, ::Expr; enter_generated::Bool) at C:\Users\Sebas.julia\packages\JuliaInterpreter\kDn3E\src\interpret.jl:239
… (the last 7 lines are repeated 5 more times)
[44] evaluate_call_recurse! at C:\Users\Sebas.julia\packages\JuliaInterpreter\kDn3E\src\interpret.jl:201 [inlined]
[45] eval_rhs(::Any, ::JuliaInterpreter.Frame, ::Expr) at C:\Users\Sebas.julia\packages\JuliaInterpreter\kDn3E\src\interpret.jl:388
[46] step_expr!(::Any, ::JuliaInterpreter.Frame, ::Any, ::Bool) at C:\Users\Sebas.julia\packages\JuliaInterpreter\kDn3E\src\interpret.jl:526
[47] step_expr!(::Any, ::JuliaInterpreter.Frame, ::Bool) at C:\Users\Sebas.julia\packages\JuliaInterpreter\kDn3E\src\interpret.jl:581
[48] finish!(::Any, ::JuliaInterpreter.Frame, ::Bool) at C:\Users\Sebas.julia\packages\JuliaInterpreter\kDn3E\src\commands.jl:14
[49] finish_and_return!(::Any, ::JuliaInterpreter.Frame, ::Bool) at C:\Users\Sebas.julia\packages\JuliaInterpreter\kDn3E\src\commands.jl:29
[50] finish_stack!(::Any, ::JuliaInterpreter.Frame, ::Bool) at C:\Users\Sebas.julia\packages\JuliaInterpreter\kDn3E\src\commands.jl:59
[51] debug_command(::Any, ::JuliaInterpreter.Frame, ::Symbol, ::Bool; line::Nothing) at C:\Users\Sebas.julia\packages\JuliaInterpreter\kDn3E\src\commands.jl:473
[52] debug_command(::Any, ::JuliaInterpreter.Frame, ::Symbol, ::Bool) at C:\Users\Sebas.julia\packages\JuliaInterpreter\kDn3E\src\commands.jl:415
[53] (::Atom.JunoDebugger.var"#54#56"{Bool,Bool,Bool})() at C:\Users\Sebas.julia\packages\Atom\MxsDb\src\debugger\stepper.jl:159
[54] evalscope(::Atom.JunoDebugger.var"#54#56"{Bool,Bool,Bool}) at C:\Users\Sebas.julia\packages\Atom\MxsDb\src\debugger\stepper.jl:392
[55] startdebugging(::JuliaInterpreter.Frame, ::Bool; istoplevel::Bool, toggle_ui::Bool) at C:\Users\Sebas.julia\packages\Atom\MxsDb\src\debugger\stepper.jl:157
[56] (::Base.var"#inner#2"{Base.Iterators.Pairs{Symbol,Bool,Tuple{Symbol,Symbol},NamedTuple{(:istoplevel, :toggle_ui),Tuple{Bool,Bool}}},typeof(Atom.JunoDebugger.startdebugging),Tuple{JuliaInterpreter.Frame,Bool}})() at .\essentials.jl:713
[57] #invokelatest#1 at .\essentials.jl:714 [inlined]
[58] (::Atom.JunoDebugger.var"#48#51"{String,String,Bool,Int64})() at C:\Users\Sebas.julia\packages\Atom\MxsDb\src\debugger\stepper.jl:119
[59] hideprompt(::Atom.JunoDebugger.var"#48#51"{String,String,Bool,Int64}) at C:\Users\Sebas.julia\packages\Atom\MxsDb\src\repl.jl:127
[60] #47 at C:\Users\Sebas.julia\packages\Atom\MxsDb\src\debugger\stepper.jl:84 [inlined]
[61] task_local_storage(::Atom.JunoDebugger.var"#47#50"{String,String,Bool,Int64}, ::Symbol, ::String) at .\task.jl:226
[62] debug_file(::String, ::String, ::String, ::Bool, ::Int64) at C:\Users\Sebas.julia\packages\Atom\MxsDb\src\debugger\stepper.jl:83
[63] debug_file(::String, ::String, ::String, ::Bool) at C:\Users\Sebas.julia\packages\Atom\MxsDb\src\debugger\stepper.jl:81
[64] handlemsg(::Dict{String,Any}, ::String, ::Vararg{Any,N} where N) at C:\Users\Sebas.julia\packages\Atom\MxsDb\src\comm.jl:169

The version of DiffEqFlux is 1.24.0

Does the debugger have any limitation in DiffEqFlux? Or should it works?

Thanks!!

6

@pfitzseb is there some weird interaction between the debugger and ProgressLogging?

7

Not as far as I’m aware. Do you have a MWE I can try, @junsebas97?

8

For example, in the following code:


using Flux, DiffEqFlux, DifferentialEquations

# Data: Lotka-Volterra simulation
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]               # initial Condition
tspan = (0.0, 15.0)              # integration interval
Δt    = 0.01
p     = [1.5, 1.0, 3.0, 1.0]     # system parameters
prob   = ODEProblem(lotka_volterra, u0, tspan, p)
sol    = solve(prob, Tsit5(), saveat = Δt)
y_real = sol[2, :]    # label


# ML model:
ANN    = FastChain(FastDense(2,  5, tanh), FastDense(5,  2))
params = initial_params(ANN)
function model(du, u, p, t)
    du[1] = dx = ANN(u, p)[1]
    du[2] = dy = ANN(u, p)[2]
end

function prediction(θ)
    problem = ODEProblem(model, u0, tspan, θ)
    solve(problem, Tsit5(), saveat = Δt)
end

function loss(θ)
    pred   = prediction(θ)
    y_pred = pred[2, :]
    sum(abs2, y_real - y_pred)
end
loss(params)

function callback(p, loss_val)
    println(loss_val)
    false
end

sol = DiffEqFlux.sciml_train(loss, params, ADAM(0.05), cb = callback, maxiters = 50)

When I put a breakpoint inside the loss function (y_pred = pred[2, :]) and it’s called by DiffEqFlux.sciml_train, i get the ProgressLogging error.