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GPU example do not run #959

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skycolt opened this issue Jan 3, 2025 · 7 comments
Open

GPU example do not run #959

skycolt opened this issue Jan 3, 2025 · 7 comments
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bug Something isn't working

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@skycolt
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skycolt commented Jan 3, 2025

Describe the bug 🐞

I tried to run the ODE on GPU example but encountered error

Expected behavior

expect the example code to run without problem:

Minimal Reproducible Example 👇

using OrdinaryDiffEq, Lux, LuxCUDA, SciMLSensitivity, ComponentArrays, Random
rng = Xoshiro(0)

const cdev = cpu_device()
const gdev = gpu_device()

model = Chain(Dense(2, 50, tanh), Dense(50, 2))
ps, st = Lux.setup(rng, model)
ps = ps |> ComponentArray |> gdev
st = st |> gdev
dudt(u, p, t) = model(u, p, st)[1]

# Simulation interval and intermediary points
tspan = (0.0f0, 10.0f0)
tsteps = 0.0f0:1.0f-1:10.0f0

u0 = Float32[2.0; 0.0] |> gdev
prob_gpu = ODEProblem(dudt, u0, tspan, ps)

# Runs on a GPU
sol_gpu = solve(prob_gpu, Tsit5(); saveat = tsteps)

Error & Stacktrace ⚠️

ERROR: Not implemented

Stacktrace:
[1] error(s::String)
@ Base .\error.jl:35
[2] runtime_module(job::GPUCompiler.CompilerJob)
@ GPUCompiler C:\Users\maw48.julia\packages\GPUCompiler\2CW9L\src\interface.jl:176
[3] build_runtime(job::GPUCompiler.CompilerJob)
@ GPUCompiler C:\Users\maw48.julia\packages\GPUCompiler\2CW9L\src\rtlib.jl:106
[4] (::GPUCompiler.var"#168#170"{GPUCompiler.CompilerJob{GPUCompiler.PTXCompilerTarget, CUDA.CUDACompilerParams}})()
@ GPUCompiler C:\Users\maw48.julia\packages\GPUCompiler\2CW9L\src\rtlib.jl:152
[5] lock(f::GPUCompiler.var"#168#170"{GPUCompiler.CompilerJob{GPUCompiler.PTXCompilerTarget, CUDA.CUDACompilerParams}}, l::ReentrantLock)
@ Base .\lock.jl:232
[6] macro expansion
@ C:\Users\maw48.julia\packages\GPUCompiler\2CW9L\src\rtlib.jl:130 [inlined]
[7] load_runtime(job::GPUCompiler.CompilerJob)
@ GPUCompiler C:\Users\maw48.julia\packages\GPUCompiler\2CW9L\src\utils.jl:108
[8] macro expansion
@ C:\Users\maw48.julia\packages\GPUCompiler\2CW9L\src\driver.jl:264 [inlined]
[9] emit_llvm(job::GPUCompiler.CompilerJob; toplevel::Bool, libraries::Bool, optimize::Bool, cleanup::Bool, validate::Bool, only_entry::Bool)
@ GPUCompiler C:\Users\maw48.julia\packages\GPUCompiler\2CW9L\src\utils.jl:108
[10] emit_llvm
@ C:\Users\maw48.julia\packages\GPUCompiler\2CW9L\src\utils.jl:106 [inlined]
[11] codegen(output::Symbol, job::GPUCompiler.CompilerJob; toplevel::Bool, libraries::Bool, optimize::Bool, cleanup::Bool, validate::Bool, strip::Bool, only_entry::Bool, parent_job::Nothing)
@ GPUCompiler C:\Users\maw48.julia\packages\GPUCompiler\2CW9L\src\driver.jl:100
[12] codegen(output::Symbol, job::GPUCompiler.CompilerJob)
@ GPUCompiler C:\Users\maw48.julia\packages\GPUCompiler\2CW9L\src\driver.jl:82
[13] compile(target::Symbol, job::GPUCompiler.CompilerJob; kwargs::@kwargs{})
@ GPUCompiler C:\Users\maw48.julia\packages\GPUCompiler\2CW9L\src\driver.jl:79
[14] compile
@ C:\Users\maw48.julia\packages\GPUCompiler\2CW9L\src\driver.jl:74 [inlined]
[15] #1145
@ C:\Users\maw48.julia\packages\CUDA\2kjXI\src\compiler\compilation.jl:250 [inlined]
[16] JuliaContext(f::CUDA.var"#1145#1148"{GPUCompiler.CompilerJob{GPUCompiler.PTXCompilerTarget, CUDA.CUDACompilerParams}}; kwargs::@kwargs{})
@ GPUCompiler C:\Users\maw48.julia\packages\GPUCompiler\2CW9L\src\driver.jl:34
[17] JuliaContext(f::Function)
@ GPUCompiler C:\Users\maw48.julia\packages\GPUCompiler\2CW9L\src\driver.jl:25
[18] compile(job::GPUCompiler.CompilerJob)
@ CUDA C:\Users\maw48.julia\packages\CUDA\2kjXI\src\compiler\compilation.jl:249
[19] actual_compilation(cache::Dict{Any, CuFunction}, src::Core.MethodInstance, world::UInt64, cfg::GPUCompiler.CompilerConfig{GPUCompiler.PTXCompilerTarget, CUDA.CUDACompilerParams}, compiler::typeof(CUDA.compile), linker::typeof(CUDA.link))
@ GPUCompiler C:\Users\maw48.julia\packages\GPUCompiler\2CW9L\src\execution.jl:237
[20] cached_compilation(cache::Dict{Any, CuFunction}, src::Core.MethodInstance, cfg::GPUCompiler.CompilerConfig{GPUCompiler.PTXCompilerTarget, CUDA.CUDACompilerParams}, compiler::Function, linker::Function)
@ GPUCompiler C:\Users\maw48.julia\packages\GPUCompiler\2CW9L\src\execution.jl:151
[21] macro expansion
@ C:\Users\maw48.julia\packages\CUDA\2kjXI\src\compiler\execution.jl:380 [inlined]
[22] macro expansion
@ .\lock.jl:273 [inlined]
[23] cufunction(f::typeof(CUDA.partial_mapreduce_grid), tt::Type{Tuple{typeof(identity), typeof(Base.add_sum), Float32, CartesianIndices{1, Tuple{Base.OneTo{Int64}}}, CartesianIndices{1, Tuple{Base.OneTo{Int64}}}, Val{true}, CuDeviceMatrix{Float32, 1}, Base.Broadcast.Broadcasted{CUDA.CuArrayStyle{1, CUDA.DeviceMemory}, Tuple{Base.OneTo{Int64}}, typeof(DiffEqBase.sse), Tuple{CuDeviceVector{Float32, 1}}}}}; kwargs::@kwargs{})
@ CUDA C:\Users\maw48.julia\packages\CUDA\2kjXI\src\compiler\execution.jl:375
[24] cufunction
@ C:\Users\maw48.julia\packages\CUDA\2kjXI\src\compiler\execution.jl:372 [inlined]
[25] macro expansion
@ C:\Users\maw48.julia\packages\CUDA\2kjXI\src\compiler\execution.jl:112 [inlined]
[26] mapreducedim!(f::typeof(identity), op::typeof(Base.add_sum), R::CuArray{Float32, 1, CUDA.DeviceMemory}, A::Base.Broadcast.Broadcasted{CUDA.CuArrayStyle{1, CUDA.DeviceMemory}, Tuple{Base.OneTo{Int64}}, typeof(DiffEqBase.sse), Tuple{CuArray{Float32, 1, CUDA.DeviceMemory}}}; init::Float32)
@ CUDA C:\Users\maw48.julia\packages\CUDA\2kjXI\src\mapreduce.jl:234
[27] mapreducedim!
@ C:\Users\maw48.julia\packages\CUDA\2kjXI\src\mapreduce.jl:169 [inlined]
[28] _mapreduce(f::typeof(DiffEqBase.sse), op::typeof(Base.add_sum), As::CuArray{Float32, 1, CUDA.DeviceMemory}; dims::Colon, init::Float32)
@ GPUArrays C:\Users\maw48.julia\packages\GPUArrays\qt4ax\src\host\mapreduce.jl:67
[29] _mapreduce
@ C:\Users\maw48.julia\packages\GPUArrays\qt4ax\src\host\mapreduce.jl:33 [inlined]
[30] mapreduce
@ C:\Users\maw48.julia\packages\GPUArrays\qt4ax\src\host\mapreduce.jl:28 [inlined]
[31] _sum
@ .\reducedim.jl:987 [inlined]
[32] sum
@ .\reducedim.jl:983 [inlined]
[33] ODE_DEFAULT_NORM
@ C:\Users\maw48.julia\packages\DiffEqBase\R2Vjs\ext\DiffEqBaseCUDAExt.jl:7 [inlined]
[34] __init(prob::ODEProblem{CuArray{Float32, 1, CUDA.DeviceMemory}, Tuple{Float32, Float32}, false, ComponentVector{Float32, CuArray{Float32, 1, CUDA.DeviceMemory}, Tuple{Axis{(layer_1 = 1:0, layer_2 = ViewAxis(1:150, Axis(weight = ViewAxis(1:100, ShapedAxis((50, 2))), bias = 101:150)), layer_3 = ViewAxis(151:252, Axis(weight = ViewAxis(1:100, ShapedAxis((2, 50))), bias = 101:102)))}}}, ODEFunction{false, SciMLBase.FullSpecialize, DiffEqFlux.var"#dudt#17"{StatefulLuxLayer{Static.True, Chain{@NamedTuple{layer_1::WrappedFunction{var"#1#2"}, layer_2::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}, layer_3::Dense{typeof(identity), Int64, Int64, Nothing, Nothing, Static.True}}, Nothing}, Nothing, @NamedTuple{layer_1::@NamedTuple{}, layer_2::@NamedTuple{}, layer_3::@NamedTuple{}}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, typeof(DiffEqFlux.basic_tgrad), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing, Nothing}, @kwargs{}, SciMLBase.StandardODEProblem}, alg::Tsit5{typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!), Static.False}, timeseries_init::Tuple{}, ts_init::Tuple{}, ks_init::Tuple{}, recompile::Type{Val{true}}; saveat::Tuple{}, tstops::Tuple{}, d_discontinuities::Tuple{}, save_idxs::Nothing, save_everystep::Bool, save_on::Bool, save_start::Bool, save_end::Bool, callback::Nothing, dense::Bool, calck::Bool, dt::Float32, dtmin::Float32, dtmax::Float32, force_dtmin::Bool, adaptive::Bool, gamma::Rational{Int64}, abstol::Nothing, reltol::Nothing, qmin::Rational{Int64}, qmax::Int64, qsteady_min::Int64, qsteady_max::Int64, beta1::Nothing, beta2::Nothing, qoldinit::Rational{Int64}, controller::Nothing, fullnormalize::Bool, failfactor::Int64, maxiters::Int64, internalnorm::typeof(DiffEqBase.ODE_DEFAULT_NORM), internalopnorm::typeof(LinearAlgebra.opnorm), isoutofdomain::typeof(DiffEqBase.ODE_DEFAULT_ISOUTOFDOMAIN), unstable_check::typeof(DiffEqBase.ODE_DEFAULT_UNSTABLE_CHECK), verbose::Bool, timeseries_errors::Bool, dense_errors::Bool, advance_to_tstop::Bool, stop_at_next_tstop::Bool, initialize_save::Bool, progress::Bool, progress_steps::Int64, progress_name::String, progress_message::typeof(DiffEqBase.ODE_DEFAULT_PROG_MESSAGE), progress_id::Symbol, userdata::Nothing, allow_extrapolation::Bool, initialize_integrator::Bool, alias::ODEAliasSpecifier, initializealg::OrdinaryDiffEqCore.DefaultInit, kwargs::@kwargs{save_noise::Bool})
@ OrdinaryDiffEqCore C:\Users\maw48.julia\packages\OrdinaryDiffEqCore\3Talm\src\solve.jl:383
[35] __init (repeats 5 times)
@ C:\Users\maw48.julia\packages\OrdinaryDiffEqCore\3Talm\src\solve.jl:11 [inlined]
[36] #__solve#62
@ C:\Users\maw48.julia\packages\OrdinaryDiffEqCore\3Talm\src\solve.jl:6 [inlined]
[37] __solve
@ C:\Users\maw48.julia\packages\OrdinaryDiffEqCore\3Talm\src\solve.jl:1 [inlined]
[38] solve_call(_prob::ODEProblem{CuArray{Float32, 1, CUDA.DeviceMemory}, Tuple{Float32, Float32}, false, ComponentVector{Float32, CuArray{Float32, 1, CUDA.DeviceMemory}, Tuple{Axis{(layer_1 = 1:0, layer_2 = ViewAxis(1:150, Axis(weight = ViewAxis(1:100, ShapedAxis((50, 2))), bias = 101:150)), layer_3 = ViewAxis(151:252, Axis(weight = ViewAxis(1:100, ShapedAxis((2, 50))), bias = 101:102)))}}}, ODEFunction{false, SciMLBase.FullSpecialize, DiffEqFlux.var"#dudt#17"{StatefulLuxLayer{Static.True, Chain{@NamedTuple{layer_1::WrappedFunction{var"#1#2"}, layer_2::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}, layer_3::Dense{typeof(identity), Int64, Int64, Nothing, Nothing, Static.True}}, Nothing}, Nothing, @NamedTuple{layer_1::@NamedTuple{}, layer_2::@NamedTuple{}, layer_3::@NamedTuple{}}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, typeof(DiffEqFlux.basic_tgrad), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing, Nothing}, @kwargs{}, SciMLBase.StandardODEProblem}, args::Tsit5{typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!), Static.False}; merge_callbacks::Bool, kwargshandle::Nothing, kwargs::@kwargs{save_noise::Bool, save_start::Bool, save_end::Bool})
@ DiffEqBase C:\Users\maw48.julia\packages\DiffEqBase\R2Vjs\src\solve.jl:634
[39] solve_call
@ C:\Users\maw48.julia\packages\DiffEqBase\R2Vjs\src\solve.jl:591 [inlined]
[40] #solve_up#53
@ C:\Users\maw48.julia\packages\DiffEqBase\R2Vjs\src\solve.jl:1122 [inlined]
[41] solve_up
@ C:\Users\maw48.julia\packages\DiffEqBase\R2Vjs\src\solve.jl:1101 [inlined]
[42] #solve#51
@ C:\Users\maw48.julia\packages\DiffEqBase\R2Vjs\src\solve.jl:1038 [inlined]
[43] _concrete_solve_adjoint(::ODEProblem{CuArray{Float32, 1, CUDA.DeviceMemory}, Tuple{Float32, Float32}, false, ComponentVector{Float32, CuArray{Float32, 1, CUDA.DeviceMemory}, Tuple{Axis{(layer_1 = 1:0, layer_2 = ViewAxis(1:150, Axis(weight = ViewAxis(1:100, ShapedAxis((50, 2))), bias = 101:150)), layer_3 = ViewAxis(151:252, Axis(weight = ViewAxis(1:100, ShapedAxis((2, 50))), bias = 101:102)))}}}, ODEFunction{false, SciMLBase.FullSpecialize, DiffEqFlux.var"#dudt#17"{StatefulLuxLayer{Static.True, Chain{@NamedTuple{layer_1::WrappedFunction{var"#1#2"}, layer_2::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}, layer_3::Dense{typeof(identity), Int64, Int64, Nothing, Nothing, Static.True}}, Nothing}, Nothing, @NamedTuple{layer_1::@NamedTuple{}, layer_2::@NamedTuple{}, layer_3::@NamedTuple{}}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, typeof(DiffEqFlux.basic_tgrad), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing, Nothing}, @kwargs{}, SciMLBase.StandardODEProblem}, ::Tsit5{typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!), Static.False}, ::InterpolatingAdjoint{0, true, Val{:central}, ZygoteVJP}, ::CuArray{Float32, 1, CUDA.DeviceMemory}, ::ComponentVector{Float32, CuArray{Float32, 1, CUDA.DeviceMemory}, Tuple{Axis{(layer_1 = 1:0, layer_2 = ViewAxis(1:150, Axis(weight = ViewAxis(1:100, ShapedAxis((50, 2))), bias = 101:150)), layer_3 = ViewAxis(151:252, Axis(weight = ViewAxis(1:100, ShapedAxis((2, 50))), bias = 101:102)))}}}, ::SciMLBase.ChainRulesOriginator; save_start::Bool, save_end::Bool, saveat::StepRangeLen{Float32, Float64, Float64, Int64}, save_idxs::Nothing, kwargs::@kwargs{})
@ SciMLSensitivity C:\Users\maw48.julia\packages\SciMLSensitivity\RQ8Av\src\concrete_solve.jl:424
[44] _concrete_solve_adjoint
@ C:\Users\maw48.julia\packages\SciMLSensitivity\RQ8Av\src\concrete_solve.jl:361 [inlined]
[45] #_solve_adjoint#75
@ C:\Users\maw48.julia\packages\DiffEqBase\R2Vjs\src\solve.jl:1585 [inlined]
[46] _solve_adjoint
@ C:\Users\maw48.julia\packages\DiffEqBase\R2Vjs\src\solve.jl:1558 [inlined]
[47] #rrule#4
@ C:\Users\maw48.julia\packages\DiffEqBase\R2Vjs\ext\DiffEqBaseChainRulesCoreExt.jl:26 [inlined]
[48] rrule
@ C:\Users\maw48.julia\packages\DiffEqBase\R2Vjs\ext\DiffEqBaseChainRulesCoreExt.jl:22 [inlined]
[49] rrule
@ C:\Users\maw48.julia\packages\ChainRulesCore\U6wNx\src\rules.jl:144 [inlined]
[50] chain_rrule_kw
@ C:\Users\maw48.julia\packages\Zygote\TWpme\src\compiler\chainrules.jl:236 [inlined]
[51] macro expansion
@ C:\Users\maw48.julia\packages\Zygote\TWpme\src\compiler\interface2.jl:0 [inlined]
[52] _pullback
@ C:\Users\maw48.julia\packages\Zygote\TWpme\src\compiler\interface2.jl:91 [inlined]
[53] _apply
@ .\boot.jl:946 [inlined]
[54] adjoint
@ C:\Users\maw48.julia\packages\Zygote\TWpme\src\lib\lib.jl:202 [inlined]
[55] _pullback
@ C:\Users\maw48.julia\packages\ZygoteRules\M4xmc\src\adjoint.jl:67 [inlined]
[56] #solve#51
@ C:\Users\maw48.julia\packages\DiffEqBase\R2Vjs\src\solve.jl:1038 [inlined]
[57] _pullback(::Zygote.Context{false}, ::DiffEqBase.var"##solve#51", ::InterpolatingAdjoint{0, true, Val{:central}, ZygoteVJP}, ::Nothing, ::Nothing, ::Val{true}, ::@kwargs{saveat::StepRangeLen{Float32, Float64, Float64, Int64}}, ::typeof(solve), ::ODEProblem{CuArray{Float32, 1, CUDA.DeviceMemory}, Tuple{Float32, Float32}, false, ComponentVector{Float32, CuArray{Float32, 1, CUDA.DeviceMemory}, Tuple{Axis{(layer_1 = 1:0, layer_2 = ViewAxis(1:150, Axis(weight = ViewAxis(1:100, ShapedAxis((50, 2))), bias = 101:150)), layer_3 = ViewAxis(151:252, Axis(weight = ViewAxis(1:100, ShapedAxis((2, 50))), bias = 101:102)))}}}, ODEFunction{false, SciMLBase.FullSpecialize, DiffEqFlux.var"#dudt#17"{StatefulLuxLayer{Static.True, Chain{@NamedTuple{layer_1::WrappedFunction{var"#1#2"}, layer_2::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}, layer_3::Dense{typeof(identity), Int64, Int64, Nothing, Nothing, Static.True}}, Nothing}, Nothing, @NamedTuple{layer_1::@NamedTuple{}, layer_2::@NamedTuple{}, layer_3::@NamedTuple{}}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, typeof(DiffEqFlux.basic_tgrad), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing, Nothing}, @kwargs{}, SciMLBase.StandardODEProblem}, ::Tsit5{typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!), Static.False})
@ Zygote C:\Users\maw48.julia\packages\Zygote\TWpme\src\compiler\interface2.jl:0
[58] _apply
@ .\boot.jl:946 [inlined]
[59] adjoint
@ C:\Users\maw48.julia\packages\Zygote\TWpme\src\lib\lib.jl:202 [inlined]
[60] _pullback
@ C:\Users\maw48.julia\packages\ZygoteRules\M4xmc\src\adjoint.jl:67 [inlined]
[61] solve
@ C:\Users\maw48.julia\packages\DiffEqBase\R2Vjs\src\solve.jl:1028 [inlined]
[62] _pullback(::Zygote.Context{false}, ::typeof(Core.kwcall), ::@NamedTuple{sensealg::InterpolatingAdjoint{0, true, Val{:central}, ZygoteVJP}, saveat::StepRangeLen{Float32, Float64, Float64, Int64}}, ::typeof(solve), ::ODEProblem{CuArray{Float32, 1, CUDA.DeviceMemory}, Tuple{Float32, Float32}, false, ComponentVector{Float32, CuArray{Float32, 1, CUDA.DeviceMemory}, Tuple{Axis{(layer_1 = 1:0, layer_2 = ViewAxis(1:150, Axis(weight = ViewAxis(1:100, ShapedAxis((50, 2))), bias = 101:150)), layer_3 = ViewAxis(151:252, Axis(weight = ViewAxis(1:100, ShapedAxis((2, 50))), bias = 101:102)))}}}, ODEFunction{false, SciMLBase.FullSpecialize, DiffEqFlux.var"#dudt#17"{StatefulLuxLayer{Static.True, Chain{@NamedTuple{layer_1::WrappedFunction{var"#1#2"}, layer_2::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}, layer_3::Dense{typeof(identity), Int64, Int64, Nothing, Nothing, Static.True}}, Nothing}, Nothing, @NamedTuple{layer_1::@NamedTuple{}, layer_2::@NamedTuple{}, layer_3::@NamedTuple{}}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, typeof(DiffEqFlux.basic_tgrad), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing, Nothing}, @kwargs{}, SciMLBase.StandardODEProblem}, ::Tsit5{typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!), Static.False})
@ Zygote C:\Users\maw48.julia\packages\Zygote\TWpme\src\compiler\interface2.jl:0
[63] _apply(::Function, ::Vararg{Any})
@ Core .\boot.jl:946
[64] adjoint
@ C:\Users\maw48.julia\packages\Zygote\TWpme\src\lib\lib.jl:202 [inlined]
[65] _pullback
@ C:\Users\maw48.julia\packages\ZygoteRules\M4xmc\src\adjoint.jl:67 [inlined]
[66] NeuralODE
@ C:\Users\maw48.julia\packages\DiffEqFlux\lXF4l\src\neural_de.jl:54 [inlined]
[67] _pullback(::Zygote.Context{false}, ::NeuralODE{Chain{@NamedTuple{layer_1::WrappedFunction{var"#1#2"}, layer_2::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}, layer_3::Dense{typeof(identity), Int64, Int64, Nothing, Nothing, Static.True}}, Nothing}, Tuple{Float32, Float32}, Tuple{Tsit5{typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!), Static.False}}, @kwargs{saveat::StepRangeLen{Float32, Float64, Float64, Int64}}}, ::CuArray{Float32, 1, CUDA.DeviceMemory}, ::ComponentVector{Float32, CuArray{Float32, 1, CUDA.DeviceMemory}, Tuple{Axis{(layer_1 = 1:0, layer_2 = ViewAxis(1:150, Axis(weight = ViewAxis(1:100, ShapedAxis((50, 2))), bias = 101:150)), layer_3 = ViewAxis(151:252, Axis(weight = ViewAxis(1:100, ShapedAxis((2, 50))), bias = 101:102)))}}}, ::@NamedTuple{layer_1::@NamedTuple{}, layer_2::@NamedTuple{}, layer_3::@NamedTuple{}})
@ Zygote C:\Users\maw48.julia\packages\Zygote\TWpme\src\compiler\interface2.jl:0
[68] predict_neuralode
@ .\In[3]:31 [inlined]
[69] _pullback(ctx::Zygote.Context{false}, f::typeof(predict_neuralode), args::ComponentVector{Float32, CuArray{Float32, 1, CUDA.DeviceMemory}, Tuple{Axis{(layer_1 = 1:0, layer_2 = ViewAxis(1:150, Axis(weight = ViewAxis(1:100, ShapedAxis((50, 2))), bias = 101:150)), layer_3 = ViewAxis(151:252, Axis(weight = ViewAxis(1:100, ShapedAxis((2, 50))), bias = 101:102)))}}})
@ Zygote C:\Users\maw48.julia\packages\Zygote\TWpme\src\compiler\interface2.jl:0
[70] loss_neuralode
@ .\In[3]:33 [inlined]
[71] _pullback(ctx::Zygote.Context{false}, f::typeof(loss_neuralode), args::ComponentVector{Float32, CuArray{Float32, 1, CUDA.DeviceMemory}, Tuple{Axis{(layer_1 = 1:0, layer_2 = ViewAxis(1:150, Axis(weight = ViewAxis(1:100, ShapedAxis((50, 2))), bias = 101:150)), layer_3 = ViewAxis(151:252, Axis(weight = ViewAxis(1:100, ShapedAxis((2, 50))), bias = 101:102)))}}})
@ Zygote C:\Users\maw48.julia\packages\Zygote\TWpme\src\compiler\interface2.jl:0
[72] #6
@ .\In[3]:58 [inlined]
[73] _pullback(::Zygote.Context{false}, ::var"#6#7", ::ComponentVector{Float32, CuArray{Float32, 1, CUDA.DeviceMemory}, Tuple{Axis{(layer_1 = 1:0, layer_2 = ViewAxis(1:150, Axis(weight = ViewAxis(1:100, ShapedAxis((50, 2))), bias = 101:150)), layer_3 = ViewAxis(151:252, Axis(weight = ViewAxis(1:100, ShapedAxis((2, 50))), bias = 101:102)))}}}, ::SciMLBase.NullParameters)
@ Zygote C:\Users\maw48.julia\packages\Zygote\TWpme\src\compiler\interface2.jl:0
[74] pullback(::Function, ::Zygote.Context{false}, ::ComponentVector{Float32, CuArray{Float32, 1, CUDA.DeviceMemory}, Tuple{Axis{(layer_1 = 1:0, layer_2 = ViewAxis(1:150, Axis(weight = ViewAxis(1:100, ShapedAxis((50, 2))), bias = 101:150)), layer_3 = ViewAxis(151:252, Axis(weight = ViewAxis(1:100, ShapedAxis((2, 50))), bias = 101:102)))}}}, ::Vararg{Any})
@ Zygote C:\Users\maw48.julia\packages\Zygote\TWpme\src\compiler\interface.jl:90
[75] pullback(::Function, ::ComponentVector{Float32, CuArray{Float32, 1, CUDA.DeviceMemory}, Tuple{Axis{(layer_1 = 1:0, layer_2 = ViewAxis(1:150, Axis(weight = ViewAxis(1:100, ShapedAxis((50, 2))), bias = 101:150)), layer_3 = ViewAxis(151:252, Axis(weight = ViewAxis(1:100, ShapedAxis((2, 50))), bias = 101:102)))}}}, ::SciMLBase.NullParameters)
@ Zygote C:\Users\maw48.julia\packages\Zygote\TWpme\src\compiler\interface.jl:88
[76] withgradient(::Function, ::ComponentVector{Float32, CuArray{Float32, 1, CUDA.DeviceMemory}, Tuple{Axis{(layer_1 = 1:0, layer_2 = ViewAxis(1:150, Axis(weight = ViewAxis(1:100, ShapedAxis((50, 2))), bias = 101:150)), layer_3 = ViewAxis(151:252, Axis(weight = ViewAxis(1:100, ShapedAxis((2, 50))), bias = 101:102)))}}}, ::Vararg{Any})
@ Zygote C:\Users\maw48.julia\packages\Zygote\TWpme\src\compiler\interface.jl:205
[77] value_and_gradient
@ C:\Users\maw48.julia\packages\DifferentiationInterface\6QHLL\ext\DifferentiationInterfaceZygoteExt\DifferentiationInterfaceZygoteExt.jl:97 [inlined]
[78] value_and_gradient!(f::Function, grad::ComponentVector{Float32, CuArray{Float32, 1, CUDA.DeviceMemory}, Tuple{Axis{(layer_1 = 1:0, layer_2 = ViewAxis(1:150, Axis(weight = ViewAxis(1:100, ShapedAxis((50, 2))), bias = 101:150)), layer_3 = ViewAxis(151:252, Axis(weight = ViewAxis(1:100, ShapedAxis((2, 50))), bias = 101:102)))}}}, prep::DifferentiationInterface.NoGradientPrep, backend::AutoZygote, x::ComponentVector{Float32, CuArray{Float32, 1, CUDA.DeviceMemory}, Tuple{Axis{(layer_1 = 1:0, layer_2 = ViewAxis(1:150, Axis(weight = ViewAxis(1:100, ShapedAxis((50, 2))), bias = 101:150)), layer_3 = ViewAxis(151:252, Axis(weight = ViewAxis(1:100, ShapedAxis((2, 50))), bias = 101:102)))}}}, contexts::DifferentiationInterface.Constant{SciMLBase.NullParameters})
@ DifferentiationInterfaceZygoteExt C:\Users\maw48.julia\packages\DifferentiationInterface\6QHLL\ext\DifferentiationInterfaceZygoteExt\DifferentiationInterfaceZygoteExt.jl:119
[79] (::OptimizationZygoteExt.var"#fg!#16"{SciMLBase.NullParameters, OptimizationFunction{true, AutoZygote, var"#6#7", Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED_NO_TIME), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, AutoZygote})(res::ComponentVector{Float32, CuArray{Float32, 1, CUDA.DeviceMemory}, Tuple{Axis{(layer_1 = 1:0, layer_2 = ViewAxis(1:150, Axis(weight = ViewAxis(1:100, ShapedAxis((50, 2))), bias = 101:150)), layer_3 = ViewAxis(151:252, Axis(weight = ViewAxis(1:100, ShapedAxis((2, 50))), bias = 101:102)))}}}, θ::ComponentVector{Float32, CuArray{Float32, 1, CUDA.DeviceMemory}, Tuple{Axis{(layer_1 = 1:0, layer_2 = ViewAxis(1:150, Axis(weight = ViewAxis(1:100, ShapedAxis((50, 2))), bias = 101:150)), layer_3 = ViewAxis(151:252, Axis(weight = ViewAxis(1:100, ShapedAxis((2, 50))), bias = 101:102)))}}})
@ OptimizationZygoteExt C:\Users\maw48.julia\packages\OptimizationBase\gvXsf\ext\OptimizationZygoteExt.jl:53
[80] macro expansion
@ C:\Users\maw48.julia\packages\OptimizationOptimisers\i6VZS\src\OptimizationOptimisers.jl:101 [inlined]
[81] macro expansion
@ C:\Users\maw48.julia\packages\Optimization\cfp9i\src\utils.jl:32 [inlined]
[82] __solve(cache::OptimizationCache{OptimizationFunction{true, AutoZygote, var"#6#7", OptimizationZygoteExt.var"#grad#14"{SciMLBase.NullParameters, OptimizationFunction{true, AutoZygote, var"#6#7", Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED_NO_TIME), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, AutoZygote}, OptimizationZygoteExt.var"#fg!#16"{SciMLBase.NullParameters, OptimizationFunction{true, AutoZygote, var"#6#7", Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED_NO_TIME), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, AutoZygote}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED_NO_TIME), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, OptimizationBase.ReInitCache{ComponentVector{Float32, CuArray{Float32, 1, CUDA.DeviceMemory}, Tuple{Axis{(layer_1 = 1:0, layer_2 = ViewAxis(1:150, Axis(weight = ViewAxis(1:100, ShapedAxis((50, 2))), bias = 101:150)), layer_3 = ViewAxis(151:252, Axis(weight = ViewAxis(1:100, ShapedAxis((2, 50))), bias = 101:102)))}}}, SciMLBase.NullParameters}, Nothing, Nothing, Nothing, Nothing, Nothing, Adam, Bool, var"#3#5", Nothing})
@ OptimizationOptimisers C:\Users\maw48.julia\packages\OptimizationOptimisers\i6VZS\src\OptimizationOptimisers.jl:83
[83] solve!(cache::OptimizationCache{OptimizationFunction{true, AutoZygote, var"#6#7", OptimizationZygoteExt.var"#grad#14"{SciMLBase.NullParameters, OptimizationFunction{true, AutoZygote, var"#6#7", Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED_NO_TIME), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, AutoZygote}, OptimizationZygoteExt.var"#fg!#16"{SciMLBase.NullParameters, OptimizationFunction{true, AutoZygote, var"#6#7", Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED_NO_TIME), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, AutoZygote}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED_NO_TIME), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, OptimizationBase.ReInitCache{ComponentVector{Float32, CuArray{Float32, 1, CUDA.DeviceMemory}, Tuple{Axis{(layer_1 = 1:0, layer_2 = ViewAxis(1:150, Axis(weight = ViewAxis(1:100, ShapedAxis((50, 2))), bias = 101:150)), layer_3 = ViewAxis(151:252, Axis(weight = ViewAxis(1:100, ShapedAxis((2, 50))), bias = 101:102)))}}}, SciMLBase.NullParameters}, Nothing, Nothing, Nothing, Nothing, Nothing, Adam, Bool, var"#3#5", Nothing})
@ SciMLBase C:\Users\maw48.julia\packages\SciMLBase\XzPx0\src\solve.jl:186
[84] solve(::OptimizationProblem{true, OptimizationFunction{true, AutoZygote, var"#6#7", Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED_NO_TIME), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, ComponentVector{Float32, CuArray{Float32, 1, CUDA.DeviceMemory}, Tuple{Axis{(layer_1 = 1:0, layer_2 = ViewAxis(1:150, Axis(weight = ViewAxis(1:100, ShapedAxis((50, 2))), bias = 101:150)), layer_3 = ViewAxis(151:252, Axis(weight = ViewAxis(1:100, ShapedAxis((2, 50))), bias = 101:102)))}}}, SciMLBase.NullParameters, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, @kwargs{}}, ::Adam; kwargs::@kwargs{callback::var"#3#5", maxiters::Int64})
@ SciMLBase C:\Users\maw48.julia\packages\SciMLBase\XzPx0\src\solve.jl:94

Environment (please complete the following information):

  • Output of using Pkg; Pkg.status()
Status `C:\Users\maw48\.julia\environments\v1.11\Project.toml`
  [cbdf2221] AlgebraOfGraphics v0.8.13
  [336ed68f] CSV v0.10.15
  [052768ef] CUDA v5.5.2
  [13f3f980] CairoMakie v0.12.18
  [479239e8] Catalyst v14.4.1
  [324d7699] CategoricalArrays v0.10.8
  [8be319e6] Chain v0.6.0
  [b0b7db55] ComponentArrays v0.15.20
  [a93c6f00] DataFrames v1.7.0
  [1313f7d8] DataFramesMeta v0.15.4
  [82cc6244] DataInterpolations v6.6.0
  [aae7a2af] DiffEqFlux v4.1.0
  [0c46a032] DifferentialEquations v7.15.0
  [31c24e10] Distributions v0.25.115
  [e1fe09cc] ExpectationMaximization v0.2.3
  [1a297f60] FillArrays v1.13.0
  [f6369f11] ForwardDiff v0.10.38
  [c43c736e] Genie v5.31.1
  [a59fdf5c] GenieFramework v2.7.0
  [af5da776] GlobalSensitivity v2.7.0
  [7073ff75] IJulia v1.26.0
  [a98d9a8b] Interpolations v0.15.1
  [033835bb] JLD2 v0.5.10
  [98e50ef6] JuliaFormatter v1.0.62
  [ccbc3e58] JumpProcesses v9.14.0
  [2fda8390] LsqFit v0.15.0
  [b2108857] Lux v1.4.4
  [d0bbae9a] LuxCUDA v0.3.3
  [bb33d45b] LuxCore v1.2.1
  [add582a8] MLJ v0.20.7
  [961ee093] ModelingToolkit v9.59.0
  [76087f3c] NLopt v1.1.1
  [429524aa] Optim v1.10.0
  [3bd65402] Optimisers v0.4.2
  [7f7a1694] Optimization v4.0.5
  [36348300] OptimizationOptimJL v0.4.1
  [42dfb2eb] OptimizationOptimisers v0.3.6
  [1dea7af3] OrdinaryDiffEq v6.90.1
  [d96e819e] Parameters v0.12.3
  [a03496cd] PlotlyBase v0.8.19
  [91a5bcdd] Plots v1.40.9
  [e6cf234a] RandomNumbers v1.6.0
  [37e2e3b7] ReverseDiff v1.15.3
  [0bca4576] SciMLBase v2.70.0
  [e9a6253c] SciMLNLSolve v0.1.9
  [1ed8b502] SciMLSensitivity v7.72.0
  [2913bbd2] StatsBase v0.34.4
  [4c63d2b9] StatsFuns v1.3.2
  [f3b207a7] StatsPlots v0.15.7
⌅ [4acbeb90] Stipple v0.28.22
⌅ [ec984513] StipplePlotly v0.13.16
⌅ [a3c5d34a] StippleUI v0.23.5
  [a2db99b7] TextAnalysis v0.8.2
  [fce5fe82] Turing v0.35.5
  [e88e6eb3] Zygote v0.6.75
  [37e2e46d] LinearAlgebra v1.11.0
  [9a3f8284] Random v1.11.0
  • Output of using Pkg; Pkg.status(; mode = PKGMODE_MANIFEST)
Status `C:\Users\maw48\.julia\environments\v1.11\Manifest.toml`
  [47edcb42] ADTypes v1.11.0
  [da404889] ARFFFiles v1.5.0
  [621f4979] AbstractFFTs v1.5.0
  [80f14c24] AbstractMCMC v5.6.0
⌅ [7a57a42e] AbstractPPL v0.9.0
  [1520ce14] AbstractTrees v0.4.5
  [7d9f7c33] Accessors v0.1.39
  [79e6a3ab] Adapt v4.1.1
  [35492f91] AdaptivePredicates v1.2.0
  [0bf59076] AdvancedHMC v0.6.4
  [5b7e9947] AdvancedMH v0.8.5
  [576499cb] AdvancedPS v0.6.0
⌅ [b5ca4192] AdvancedVI v0.2.11
  [cbdf2221] AlgebraOfGraphics v0.8.13
  [66dad0bd] AliasTables v1.1.3
  [27a7e980] Animations v0.4.2
  [dce04be8] ArgCheck v2.4.0
  [c7e460c6] ArgParse v1.2.0
  [ec485272] ArnoldiMethod v0.4.0
  [7d9fca2a] Arpack v0.5.4
  [4fba245c] ArrayInterface v7.18.0
  [4c555306] ArrayLayouts v1.11.0
  [a9b6321e] Atomix v1.0.1
  [67c07d97] Automa v1.1.0
  [13072b0f] AxisAlgorithms v1.1.0
  [39de3d68] AxisArrays v0.4.7
  [ab4f0b2a] BFloat16s v0.5.0
  [aae01518] BandedMatrices v1.9.0
  [198e06fe] BangBang v0.4.3
  [9718e550] Baselet v0.1.1
  [e2ed5e7c] Bijections v0.1.9
  [76274a88] Bijectors v0.15.2
  [d1d4a3ce] BitFlags v0.1.9
  [62783981] BitTwiddlingConvenienceFunctions v0.1.6
  [8e7c35d0] BlockArrays v1.3.0
  [4544d5e4] Boltz v1.1.0
  [764a87c0] BoundaryValueDiffEq v5.12.0
  [56b672f2] BoundaryValueDiffEqCore v1.2.0
  [85d9eb09] BoundaryValueDiffEqFIRK v1.2.0
  [1a22d4ce] BoundaryValueDiffEqMIRK v1.2.0
  [ed55bfe0] BoundaryValueDiffEqShooting v1.2.0
  [fa961155] CEnum v0.5.0
  [2a0fbf3d] CPUSummary v0.2.6
  [96374032] CRlibm v1.0.1
  [00ebfdb7] CSTParser v3.4.3
  [336ed68f] CSV v0.10.15
  [052768ef] CUDA v5.5.2
  [1af6417a] CUDA_Runtime_Discovery v0.3.5
  [159f3aea] Cairo v1.1.1
  [13f3f980] CairoMakie v0.12.18
  [7057c7e9] Cassette v0.3.14
  [479239e8] Catalyst v14.4.1
  [324d7699] CategoricalArrays v0.10.8
  [af321ab8] CategoricalDistributions v0.1.15
  [8be319e6] Chain v0.6.0
  [082447d4] ChainRules v1.72.2
  [d360d2e6] ChainRulesCore v1.25.1
  [9e997f8a] ChangesOfVariables v0.1.9
  [fb6a15b2] CloseOpenIntervals v0.1.13
  [aaaa29a8] Clustering v0.15.7
  [da1fd8a2] CodeTracking v1.3.6
  [944b1d66] CodecZlib v0.7.6
  [a2cac450] ColorBrewer v0.4.0
  [35d6a980] ColorSchemes v3.27.1
⌅ [3da002f7] ColorTypes v0.11.5
⌃ [c3611d14] ColorVectorSpace v0.10.0
⌅ [5ae59095] Colors v0.12.11
  [861a8166] Combinatorics v1.0.2
  [a80b9123] CommonMark v0.8.15
  [38540f10] CommonSolve v0.2.4
  [bbf7d656] CommonSubexpressions v0.3.1
  [f70d9fcc] CommonWorldInvalidations v1.0.0
  [34da2185] Compat v4.16.0
  [ab4b797d] ComplexityMeasures v3.8.0
  [b0b7db55] ComponentArrays v0.15.20
  [b152e2b5] CompositeTypes v0.1.4
  [a33af91c] CompositionsBase v0.1.2
  [ed09eef8] ComputationalResources v0.3.2
  [2569d6c7] ConcreteStructs v0.2.3
  [f0e56b4a] ConcurrentUtilities v2.4.3
  [8f4d0f93] Conda v1.10.2
  [5218b696] Configurations v0.17.6
  [88cd18e8] ConsoleProgressMonitor v0.1.2
  [187b0558] ConstructionBase v1.5.8
  [6add18c4] ContextVariablesX v0.1.3
  [d38c429a] Contour v0.6.3
  [ae264745] Copulas v0.1.26
  [adafc99b] CpuId v0.3.1
  [a8cc5b0e] Crayons v4.1.1
⌅ [717857b8] DSP v0.7.10
  [9a962f9c] DataAPI v1.16.0
  [124859b0] DataDeps v0.7.13
  [a93c6f00] DataFrames v1.7.0
  [1313f7d8] DataFramesMeta v0.15.4
  [82cc6244] DataInterpolations v6.6.0
  [864edb3b] DataStructures v0.18.20
  [e2d170a0] DataValueInterfaces v1.0.0
  [244e2a9f] DefineSingletons v0.1.2
  [927a84f5] DelaunayTriangulation v1.6.3
  [bcd4f6db] DelayDiffEq v5.52.0
  [5732040d] DelayEmbeddings v2.8.0
  [8bb1440f] DelimitedFiles v1.9.1
  [b429d917] DensityInterface v0.4.0
  [85a47980] Dictionaries v0.4.3
  [2b5f629d] DiffEqBase v6.161.0
  [459566f4] DiffEqCallbacks v4.2.2
  [aae7a2af] DiffEqFlux v4.1.0
  [77a26b50] DiffEqNoiseProcess v5.24.0
  [163ba53b] DiffResults v1.1.0
  [b552c78f] DiffRules v1.15.1
  [0c46a032] DifferentialEquations v7.15.0
  [a0c0ee7d] DifferentiationInterface v0.6.28
  [8d63f2c5] DispatchDoctor v0.4.19
  [b4f34e82] Distances v0.10.12
  [31c24e10] Distributions v0.25.115
  [ced4e74d] DistributionsAD v0.6.57
  [ffbed154] DocStringExtensions v0.9.3
  [5b8099bc] DomainSets v0.7.14
  [4dc1fcf4] DotEnv v1.0.0
  [366bfd00] DynamicPPL v0.32.2
  [7c1d4256] DynamicPolynomials v0.6.1
  [06fc5a27] DynamicQuantities v1.4.0
  [792122b4] EarlyStopping v0.3.0
  [cad2338a] EllipticalSliceSampling v2.0.0
  [4e289a0a] EnumX v1.0.4
  [7da242da] Enzyme v0.13.27
  [f151be2c] EnzymeCore v0.8.8
  [90fa49ef] ErrorfreeArithmetic v0.5.2
⌃ [429591f6] ExactPredicates v2.2.5
  [460bff9d] ExceptionUnwrapping v0.1.11
  [e1fe09cc] ExpectationMaximization v0.2.3
  [d4d017d3] ExponentialUtilities v1.27.0
  [e2ba6199] ExprTools v0.1.10
⌅ [6b7a57c9] Expronicon v0.8.5
  [55351af7] ExproniconLite v0.10.13
  [411431e0] Extents v0.1.4
  [8f5d6c58] EzXML v1.2.0
  [c87230d0] FFMPEG v0.4.2
  [7a1cc6ca] FFTW v1.8.0
  [cc61a311] FLoops v0.2.2
  [b9860ae5] FLoopsBase v0.1.1
  [9d29842c] FastAlmostBandedMatrices v0.1.4
  [7034ab61] FastBroadcast v0.3.5
  [9aa1b823] FastClosures v0.3.2
  [442a2c76] FastGaussQuadrature v1.0.2
  [29a986be] FastLapackInterface v2.0.4
  [a4df4552] FastPower v1.1.1
  [fa42c844] FastRounding v0.3.1
  [33837fe5] FeatureSelection v0.2.2
  [5789e2e9] FileIO v1.16.6
  [8fc22ac5] FilePaths v0.8.3
  [48062228] FilePathsBase v0.9.22
  [1a297f60] FillArrays v1.13.0
  [64ca27bc] FindFirstFunctions v1.4.1
  [6a86dc24] FiniteDiff v2.26.2
  [53c48c17] FixedPointNumbers v0.8.5
  [1fa38f19] Format v1.3.7
  [f6369f11] ForwardDiff v0.10.38
  [b38be410] FreeType v4.1.1
  [663a7486] FreeTypeAbstraction v0.10.6
  [f62d2435] FunctionProperties v0.1.2
  [069b7b12] FunctionWrappers v1.1.3
  [77dc65aa] FunctionWrappersWrappers v0.1.3
  [d9f16b24] Functors v0.5.2
  [38e38edf] GLM v1.9.0
⌅ [0c68f7d7] GPUArrays v10.3.1
⌅ [46192b85] GPUArraysCore v0.1.6
⌅ [61eb1bfa] GPUCompiler v0.27.8
⌃ [28b8d3ca] GR v0.73.5
  [b0ab02a7] GarishPrint v0.5.1
  [c145ed77] GenericSchur v0.5.4
  [c43c736e] Genie v5.31.1
  [c6228e60] GenieAutoReload v2.2.5
  [4e5d9629] GenieDevTools v2.12.0
  [a59fdf5c] GenieFramework v2.7.0
  [3bdcc7f3] GeniePackageManager v1.1.0
  [03cc5b98] GenieSession v1.1.2
  [5c4fdc26] GenieSessionFileSession v1.1.0
  [68eda718] GeoFormatTypes v0.4.2
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⌅ [5c1252a2] GeometryBasics v0.4.11
  [c27321d9] Glob v1.3.1
  [af5da776] GlobalSensitivity v2.7.0
  [a2bd30eb] Graphics v1.1.3
  [86223c79] Graphs v1.12.0
  [3955a311] GridLayoutBase v0.11.1
  [42e2da0e] Grisu v1.0.2
  [19dc6840] HCubature v1.7.0
  [7693890a] HTML_Entities v1.0.1
  [cd3eb016] HTTP v1.10.15
  [3e5b6fbb] HostCPUFeatures v0.1.17
  [77172c1b] HttpCommon v0.5.0
  [0e44f5e4] Hwloc v3.3.0
  [34004b35] HypergeometricFunctions v0.3.25
  [7073ff75] IJulia v1.26.0
  [7869d1d1] IRTools v0.4.14
  [615f187c] IfElse v0.1.1
  [2803e5a7] ImageAxes v0.6.12
  [c817782e] ImageBase v0.1.7
  [a09fc81d] ImageCore v0.10.5
  [82e4d734] ImageIO v0.6.9
  [bc367c6b] ImageMetadata v0.9.10
  [313cdc1a] Indexing v1.1.1
  [9b13fd28] IndirectArrays v1.0.0
  [d25df0c9] Inflate v0.1.5
  [6d011eab] Inflector v1.1.0
  [22cec73e] InitialValues v0.3.1
  [842dd82b] InlineStrings v1.4.2
  [505f98c9] InplaceOps v0.3.0
  [18e54dd8] IntegerMathUtils v0.1.2
  [a98d9a8b] Interpolations v0.15.1
⌅ [d1acc4aa] IntervalArithmetic v0.20.9
  [8197267c] IntervalSets v0.7.10
  [3587e190] InverseFunctions v0.1.17
  [41ab1584] InvertedIndices v1.3.1
  [92d709cd] IrrationalConstants v0.2.2
  [f1662d9f] Isoband v0.1.1
  [c8e1da08] IterTools v1.10.0
  [b3c1a2ee] IterationControl v0.5.4
  [82899510] IteratorInterfaceExtensions v1.0.0
  [033835bb] JLD2 v0.5.10
  [1019f520] JLFzf v0.1.9
  [692b3bcd] JLLWrappers v1.7.0
  [682c06a0] JSON v0.21.4
  [0f8b85d8] JSON3 v1.14.1
  [b835a17e] JpegTurbo v0.1.5
  [98e50ef6] JuliaFormatter v1.0.62
  [aa1ae85d] JuliaInterpreter v0.9.38
  [b14d175d] JuliaVariables v0.2.4
  [ccbc3e58] JumpProcesses v9.14.0
  [ef3ab10e] KLU v0.6.0
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⌅ [6c6e2e6c] MIMEs v0.1.4
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⌅ [8913a72c] NonlinearSolve v3.15.1
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  [6ad6398a] OrdinaryDiffEqBDF v1.2.0
  [bbf590c4] OrdinaryDiffEqCore v1.14.1
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  [5960d6e9] OrdinaryDiffEqFIRK v1.6.0
  [101fe9f7] OrdinaryDiffEqFeagin v1.1.0
  [d3585ca7] OrdinaryDiffEqFunctionMap v1.1.1
  [d28bc4f8] OrdinaryDiffEqHighOrderRK v1.1.0
  [9f002381] OrdinaryDiffEqIMEXMultistep v1.2.0
  [521117fe] OrdinaryDiffEqLinear v1.1.0
  [1344f307] OrdinaryDiffEqLowOrderRK v1.2.0
  [b0944070] OrdinaryDiffEqLowStorageRK v1.2.1
  [127b3ac7] OrdinaryDiffEqNonlinearSolve v1.3.0
  [c9986a66] OrdinaryDiffEqNordsieck v1.1.0
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  [04162be5] OrdinaryDiffEqQPRK v1.1.0
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  [e3e12d00] OrdinaryDiffEqStabilizedIRK v1.2.0
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⌅ [1bd9f7bb] RemoteREPL v0.2.17
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⌅ [26aad666] SSMProblems v0.1.1
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⌅ [65257c39] ShaderAbstractions v0.4.1
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⌅ [727e6d20] SimpleNonlinearSolve v1.12.3
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⌅ [4acbeb90] Stipple v0.28.22
⌅ [ec984513] StipplePlotly v0.13.16
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⌅ [a3c5d34a] StippleUI v0.23.5
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⌅ [09ab397b] StructArrays v0.6.18
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⌅ [68821587] Arpack_jll v3.5.1+1
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⌅ [4ee394cb] CUDA_Driver_jll v0.10.4+0
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⌅ [b22a6f82] FFMPEG_jll v4.4.2+2
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⌅ [d2c73de3] GR_jll v0.73.5+0
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  [aacddb02] JpegTurbo_jll v3.1.1+0
  [9c1d0b0a] JuliaNVTXCallbacks_jll v0.2.1+0
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⌅ [88015f11] LERC_jll v3.0.0+1
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⌅ [e9f186c6] Libffi_jll v3.2.2+2
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⌅ [89763e89] Libtiff_jll v4.5.1+1
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  [856f044c] MKL_jll v2024.2.0+0
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  [e98f9f5b] NVTX_jll v3.1.0+2
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  [e7412a2a] Ogg_jll v1.3.5+1
  [18a262bb] OpenEXR_jll v3.2.4+0
⌅ [9bd350c2] OpenSSH_jll v8.9.0+1
⌅ [458c3c95] OpenSSL_jll v1.1.23+1
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⌅ [30392449] Pixman_jll v0.43.4+0
⌅ [c0090381] Qt6Base_jll v6.5.2+2
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⌅ [fb77eaff] Sundials_jll v5.2.3+0
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⌅ [02c8fc9c] XML2_jll v2.10.4+0
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  [d1454406] Xorg_libXinerama_jll v1.1.5+0
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  [12413925] Xorg_xcb_util_image_jll v0.4.0+1
  [2def613f] Xorg_xcb_util_jll v0.4.0+1
  [975044d2] Xorg_xcb_util_keysyms_jll v0.4.0+1
  [0d47668e] Xorg_xcb_util_renderutil_jll v0.3.9+1
  [c22f9ab0] Xorg_xcb_util_wm_jll v0.4.1+1
  [35661453] Xorg_xkbcomp_jll v1.4.6+1
  [33bec58e] Xorg_xkeyboard_config_jll v2.39.0+0
  [c5fb5394] Xorg_xtrans_jll v1.5.0+3
  [8f1865be] ZeroMQ_jll v4.3.5+3
  [3161d3a3] Zstd_jll v1.5.7+0
  [1e29f10c] demumble_jll v1.3.0+0
  [35ca27e7] eudev_jll v3.2.9+0
  [214eeab7] fzf_jll v0.56.3+0
  [1a1c6b14] gperf_jll v3.1.1+1
  [9a68df92] isoband_jll v0.2.3+0
  [a4ae2306] libaom_jll v3.11.0+0
  [0ac62f75] libass_jll v0.15.2+0
  [1183f4f0] libdecor_jll v0.2.2+0
  [2db6ffa8] libevdev_jll v1.11.0+0
  [f638f0a6] libfdk_aac_jll v2.0.3+0
  [36db933b] libinput_jll v1.18.0+0
  [b53b4c65] libpng_jll v1.6.45+0
  [075b6546] libsixel_jll v1.10.4+0
  [a9144af2] libsodium_jll v1.0.20+3
  [f27f6e37] libvorbis_jll v1.3.7+2
⌃ [c5f90fcd] libwebp_jll v1.4.0+0
  [009596ad] mtdev_jll v1.1.6+0
  [1317d2d5] oneTBB_jll v2021.12.0+0
⌅ [1270edf5] x264_jll v2021.5.5+0
⌅ [dfaa095f] x265_jll v3.5.0+0
  [d8fb68d0] xkbcommon_jll v1.4.1+2
  [0dad84c5] ArgTools v1.1.2
  [56f22d72] Artifacts v1.11.0
  [2a0f44e3] Base64 v1.11.0
  [8bf52ea8] CRC32c v1.11.0
  [ade2ca70] Dates v1.11.0
  [8ba89e20] Distributed v1.11.0
  [f43a241f] Downloads v1.6.0
  [7b1f6079] FileWatching v1.11.0
  [9fa8497b] Future v1.11.0
  [b77e0a4c] InteractiveUtils v1.11.0
  [4af54fe1] LazyArtifacts v1.11.0
  [b27032c2] LibCURL v0.6.4
  [76f85450] LibGit2 v1.11.0
  [8f399da3] Libdl v1.11.0
  [37e2e46d] LinearAlgebra v1.11.0
  [56ddb016] Logging v1.11.0
  [d6f4376e] Markdown v1.11.0
  [a63ad114] Mmap v1.11.0
  [ca575930] NetworkOptions v1.2.0
  [44cfe95a] Pkg v1.11.0
  [de0858da] Printf v1.11.0
  [3fa0cd96] REPL v1.11.0
  [9a3f8284] Random v1.11.0
  [ea8e919c] SHA v0.7.0
  [9e88b42a] Serialization v1.11.0
  [1a1011a3] SharedArrays v1.11.0
  [6462fe0b] Sockets v1.11.0
  [2f01184e] SparseArrays v1.11.0
  [f489334b] StyledStrings v1.11.0
  [4607b0f0] SuiteSparse
  [fa267f1f] TOML v1.0.3
  [a4e569a6] Tar v1.10.0
  [8dfed614] Test v1.11.0
  [cf7118a7] UUIDs v1.11.0
  [4ec0a83e] Unicode v1.11.0
  [e66e0078] CompilerSupportLibraries_jll v1.1.1+0
  [781609d7] GMP_jll v6.3.0+0
  [deac9b47] LibCURL_jll v8.6.0+0
  [e37daf67] LibGit2_jll v1.7.2+0
  [29816b5a] LibSSH2_jll v1.11.0+1
  [c8ffd9c3] MbedTLS_jll v2.28.6+0
  [14a3606d] MozillaCACerts_jll v2023.12.12
  [4536629a] OpenBLAS_jll v0.3.27+1
  [05823500] OpenLibm_jll v0.8.1+2
  [efcefdf7] PCRE2_jll v10.42.0+1
  [bea87d4a] SuiteSparse_jll v7.7.0+0
  [83775a58] Zlib_jll v1.2.13+1
  [8e850b90] libblastrampoline_jll v5.11.0+0
  [8e850ede] nghttp2_jll v1.59.0+0
  [3f19e933] p7zip_jll v17.4.0+2
  • Output of versioninfo()
Julia Version 1.11.2
Commit 5e9a32e7af (2024-12-01 20:02 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Windows (x86_64-w64-mingw32)
  CPU: 20 × 12th Gen Intel(R) Core(TM) i9-12900H
  WORD_SIZE: 64
  LLVM: libLLVM-16.0.6 (ORCJIT, alderlake)
Threads: 12 default, 0 interactive, 6 GC (on 20 virtual cores)
Environment:
  JULIA_NUM_THREADS = 12

Additional context

The error is due to this code: p |> ComponentArray |> gdev

@skycolt skycolt added the bug Something isn't working label Jan 3, 2025
@avik-pal
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avik-pal commented Jan 3, 2025

This seems to be happening a lot in Lux CI as well (somewhat stochastically), but I haven't been able to pin-point the source of it

@skycolt
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skycolt commented Jan 6, 2025

Could you suggest an alternative implication to run on GPU? Thanks

@avik-pal
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avik-pal commented Jan 6, 2025

cc @maleadt @ChrisRackauckas do you happen to know the source for this? I remember it came up once in the CI long back, but I don't know how we fixed it

@maleadt
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maleadt commented Jan 6, 2025

It looked like a cache corruption, but we weren't able to reduce, let alone fix it. IIRC Cody or Gabriel took the most recent look at it.

@skycolt
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skycolt commented Jan 6, 2025

what's the current recommendations if I plan to use the package? will retreat back to a previous version viable?

@ChrisRackauckas
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We're having people take a look at this. This bug is really elusive and it is not clear what is causing it so it's not clear right now what the workaround is, but @gbaraldi is on the case and hopefully we will finally be able to track it down. This example seems to recreate it easier than what we found before which happened to be very dependent on what machine it was run on. We will update you ASAP on this attempt to recreate and isolate it.

@skycolt
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skycolt commented Jan 7, 2025

Great to know! Thank you so much!

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