ERROR: LoadError: GPU compilation of kernel gpu_gpu_kernel(Cassette.Context{nametype(CUDACtx), KernelAbstractions.CompilerMetadata{KernelAbstractions.NDIteration.DynamicSize, KernelAbstractions.NDIteration.DynamicCheck, Nothing, CartesianIndices{1, Tuple{Base.OneTo{Int64}}}, KernelAbstractions.NDIteration.NDRange{1, KernelAbstractions.NDIteration.DynamicSize, KernelAbstractions.NDIteration.DynamicSize, CartesianIndices{1, Tuple{Base.OneTo{Int64}}}, CartesianIndices{1, Tuple{Base.OneTo{Int64}}}}}, Nothing, KernelAbstractions.var"##PassType#257", Nothing, Cassette.DisableHooks}, typeof(DiffEqGPU.gpu_gpu_kernel), ModelingToolkit.var"#f#148"{RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(Symbol("##arg#351"), Symbol("##arg#352"), :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", Expr}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(Symbol("##out#353"), Symbol("##arg#351"), Symbol("##arg#352"), :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", Expr}}, CUDA.CuDeviceMatrix{Float32, 1}, CUDA.CuDeviceMatrix{Float32, 1}, CUDA.CuDeviceMatrix{Float32, 1}, Float32) failed
KernelError: passing and using non-bitstype argument
Argument 4 to your kernel function is of type ModelingToolkit.var"#f#148"{RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(Symbol("##arg#351"), Symbol("##arg#352"), :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", Expr}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(Symbol("##out#353"), Symbol("##arg#351"), Symbol("##arg#352"), :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", Expr}}, which is not isbits:
.f_oop is of type RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(Symbol("##arg#351"), Symbol("##arg#352"), :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", Expr} which is not isbits.
.body is of type Expr which is not isbits.
.head is of type Symbol which is not isbits.
.args is of type Vector{Any} which is not isbits.
.f_iip is of type RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(Symbol("##out#353"), Symbol("##arg#351"), Symbol("##arg#352"), :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", Expr} which is not isbits.
.body is of type Expr which is not isbits.
.head is of type Symbol which is not isbits.
.args is of type Vector{Any} which is not isbits.
Stacktrace:
[1] check_invocation(job::GPUCompiler.CompilerJob, entry::LLVM.Function)
@ GPUCompiler ~/.julia/packages/GPUCompiler/XwWPj/src/validation.jl:68
[2] macro expansion
@ ~/.julia/packages/GPUCompiler/XwWPj/src/driver.jl:287 [inlined]
[3] macro expansion
@ ~/.julia/packages/TimerOutputs/4QAIk/src/TimerOutput.jl:206 [inlined]
[4] macro expansion
@ ~/.julia/packages/GPUCompiler/XwWPj/src/driver.jl:286 [inlined]
[5] emit_asm(job::GPUCompiler.CompilerJob, ir::LLVM.Module, kernel::LLVM.Function; strip::Bool, validate::Bool, format::LLVM.API.LLVMCodeGenFileType)
@ GPUCompiler ~/.julia/packages/GPUCompiler/XwWPj/src/utils.jl:62
[6] cufunction_compile(job::GPUCompiler.CompilerJob)
@ CUDA ~/.julia/packages/CUDA/M4jkK/src/compiler/execution.jl:306
[7] check_cache
@ ~/.julia/packages/GPUCompiler/XwWPj/src/cache.jl:44 [inlined]
[8] cached_compilation
@ ./none:0 [inlined]
[9] cufunction(f::typeof(Cassette.overdub), tt::Type{Tuple{Cassette.Context{nametype(CUDACtx), KernelAbstractions.CompilerMetadata{KernelAbstractions.NDIteration.DynamicSize, KernelAbstractions.NDIteration.DynamicCheck, Nothing, CartesianIndices{1, Tuple{Base.OneTo{Int64}}}, KernelAbstractions.NDIteration.NDRange{1, KernelAbstractions.NDIteration.DynamicSize, KernelAbstractions.NDIteration.DynamicSize, CartesianIndices{1, Tuple{Base.OneTo{Int64}}}, CartesianIndices{1, Tuple{Base.OneTo{Int64}}}}}, Nothing, KernelAbstractions.var"##PassType#257", Nothing, Cassette.DisableHooks}, typeof(DiffEqGPU.gpu_gpu_kernel), ModelingToolkit.var"#f#148"{RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(Symbol("##arg#351"), Symbol("##arg#352"), :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", Expr}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(Symbol("##out#353"), Symbol("##arg#351"), Symbol("##arg#352"), :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", Expr}}, CUDA.CuDeviceMatrix{Float32, 1}, CUDA.CuDeviceMatrix{Float32, 1}, CUDA.CuDeviceMatrix{Float32, 1}, Float32}}; name::String, kwargs::Base.Iterators.Pairs{Union{}, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
@ CUDA ~/.julia/packages/CUDA/M4jkK/src/compiler/execution.jl:294
[10] macro expansion
@ ~/.julia/packages/CUDA/M4jkK/src/compiler/execution.jl:102 [inlined]
[11] (::KernelAbstractions.Kernel{CUDAKernels.CUDADevice, KernelAbstractions.NDIteration.DynamicSize, KernelAbstractions.NDIteration.DynamicSize, typeof(DiffEqGPU.gpu_gpu_kernel)})(::Function, ::Vararg{Any, N} where N; ndrange::Int64, dependencies::CUDAKernels.CudaEvent, workgroupsize::Int64, progress::Function)
@ CUDAKernels ~/.julia/packages/CUDAKernels/94MY8/src/CUDAKernels.jl:192
[12] (::DiffEqGPU.var"#55#59"{ModelingToolkit.var"#f#148"{RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(Symbol("##arg#351"), Symbol("##arg#352"), :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0xe09e3e39, 0x901fd863, 0xaabe4072, 0xa349f5db, 0x1e2ac5dd)}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(Symbol("##out#353"), Symbol("##arg#351"), Symbol("##arg#352"), :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x255a3166, 0x06ba9a71, 0xa2d333f0, 0xa11339db, 0xc80f8c0d)}}, typeof(DiffEqGPU.gpu_kernel)})(du::CUDA.CuArray{Float32, 2}, u::CUDA.CuArray{Float32, 2}, p::CUDA.CuArray{Float32, 2}, t::Float32)
@ DiffEqGPU ~/.julia/packages/DiffEqGPU/YMmTv/src/DiffEqGPU.jl:408
[13] ODEFunction
@ ~/.julia/packages/SciMLBase/9EjAY/src/scimlfunctions.jl:334 [inlined]
[14] initialize!(integrator::OrdinaryDiffEq.ODEIntegrator{Tsit5, true, CUDA.CuArray{Float32, 2}, Nothing, Float32, CUDA.CuArray{Float32, 2}, Float32, Float32, Float32, Vector{CUDA.CuArray{Float32, 2}}, ODESolution{Float32, 3, Vector{CUDA.CuArray{Float32, 2}}, Nothing, Nothing, Vector{Float32}, Vector{Vector{CUDA.CuArray{Float32, 2}}}, ODEProblem{CUDA.CuArray{Float32, 2}, Tuple{Float32, Float32}, true, CUDA.CuArray{Float32, 2}, ODEFunction{true, DiffEqGPU.var"#55#59"{ModelingToolkit.var"#f#148"{RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(Symbol("##arg#351"), Symbol("##arg#352"), :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0xe09e3e39, 0x901fd863, 0xaabe4072, 0xa349f5db, 0x1e2ac5dd)}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(Symbol("##out#353"), Symbol("##arg#351"), Symbol("##arg#352"), :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x255a3166, 0x06ba9a71, 0xa2d333f0, 0xa11339db, 0xc80f8c0d)}}, typeof(DiffEqGPU.gpu_kernel)}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Iterators.Pairs{Union{}, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Tsit5, OrdinaryDiffEq.InterpolationData{ODEFunction{true, DiffEqGPU.var"#55#59"{ModelingToolkit.var"#f#148"{RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(Symbol("##arg#351"), Symbol("##arg#352"), :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0xe09e3e39, 0x901fd863, 0xaabe4072, 0xa349f5db, 0x1e2ac5dd)}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(Symbol("##out#353"), Symbol("##arg#351"), Symbol("##arg#352"), :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x255a3166, 0x06ba9a71, 0xa2d333f0, 0xa11339db, 0xc80f8c0d)}}, typeof(DiffEqGPU.gpu_kernel)}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Vector{CUDA.CuArray{Float32, 2}}, Vector{Float32}, Vector{Vector{CUDA.CuArray{Float32, 2}}}, OrdinaryDiffEq.Tsit5Cache{CUDA.CuArray{Float32, 2}, CUDA.CuArray{Float32, 2}, CUDA.CuArray{Float32, 2}, OrdinaryDiffEq.Tsit5ConstantCache{Float32, Float32}}}, DiffEqBase.DEStats}, ODEFunction{true, DiffEqGPU.var"#55#59"{ModelingToolkit.var"#f#148"{RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(Symbol("##arg#351"), Symbol("##arg#352"), :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0xe09e3e39, 0x901fd863, 0xaabe4072, 0xa349f5db, 0x1e2ac5dd)}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(Symbol("##out#353"), Symbol("##arg#351"), Symbol("##arg#352"), :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x255a3166, 0x06ba9a71, 0xa2d333f0, 0xa11339db, 0xc80f8c0d)}}, typeof(DiffEqGPU.gpu_kernel)}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, OrdinaryDiffEq.Tsit5Cache{CUDA.CuArray{Float32, 2}, CUDA.CuArray{Float32, 2}, CUDA.CuArray{Float32, 2}, OrdinaryDiffEq.Tsit5ConstantCache{Float32, Float32}}, OrdinaryDiffEq.DEOptions{Float32, Float32, Float32, Float32, typeof(DiffEqGPU.diffeqgpunorm), typeof(LinearAlgebra.opnorm), Nothing, CallbackSet{Tuple{}, Tuple{}}, typeof(DiffEqBase.ODE_DEFAULT_ISOUTOFDOMAIN), typeof(DiffEqBase.ODE_DEFAULT_PROG_MESSAGE), DiffEqGPU.var"#10#16", DataStructures.BinaryMinHeap{Float32}, DataStructures.BinaryMinHeap{Float32}, Nothing, Nothing, Int64, Tuple{}, Float32, Tuple{}}, CUDA.CuArray{Float32, 2}, Float32, Nothing, OrdinaryDiffEq.DefaultInit}, cache::OrdinaryDiffEq.Tsit5Cache{CUDA.CuArray{Float32, 2}, CUDA.CuArray{Float32, 2}, CUDA.CuArray{Float32, 2}, OrdinaryDiffEq.Tsit5ConstantCache{Float32, Float32}})
@ OrdinaryDiffEq ~/.julia/packages/OrdinaryDiffEq/2Z4fE/src/perform_step/low_order_rk_perform_step.jl:623
[15] __init(prob::ODEProblem{CUDA.CuArray{Float32, 2}, Tuple{Float32, Float32}, true, CUDA.CuArray{Float32, 2}, ODEFunction{true, DiffEqGPU.var"#55#59"{ModelingToolkit.var"#f#148"{RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(Symbol("##arg#351"), Symbol("##arg#352"), :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0xe09e3e39, 0x901fd863, 0xaabe4072, 0xa349f5db, 0x1e2ac5dd)}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(Symbol("##out#353"), Symbol("##arg#351"), Symbol("##arg#352"), :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x255a3166, 0x06ba9a71, 0xa2d333f0, 0xa11339db, 0xc80f8c0d)}}, typeof(DiffEqGPU.gpu_kernel)}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Iterators.Pairs{Union{}, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, alg::Tsit5, timeseries_init::Tuple{}, ts_init::Tuple{}, ks_init::Tuple{}, recompile::Type{Val{true}}; saveat::Float32, tstops::Tuple{}, d_discontinuities::Tuple{}, save_idxs::Nothing, save_everystep::Bool, save_on::Bool, save_start::Bool, save_end::Nothing, callback::Nothing, dense::Bool, calck::Bool, dt::Float32, dtmin::Nothing, 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, qoldinit::Rational{Int64}, fullnormalize::Bool, failfactor::Int64, beta1::Nothing, beta2::Nothing, maxiters::Int64, internalnorm::typeof(DiffEqGPU.diffeqgpunorm), internalopnorm::typeof(LinearAlgebra.opnorm), isoutofdomain::typeof(DiffEqBase.ODE_DEFAULT_ISOUTOFDOMAIN), unstable_check::DiffEqGPU.var"#10#16", 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), userdata::Nothing, allow_extrapolation::Bool, initialize_integrator::Bool, alias_u0::Bool, alias_du0::Bool, initializealg::OrdinaryDiffEq.DefaultInit, kwargs::Base.Iterators.Pairs{Union{}, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
@ OrdinaryDiffEq ~/.julia/packages/OrdinaryDiffEq/2Z4fE/src/solve.jl:433
[16] #__solve#403
@ ~/.julia/packages/OrdinaryDiffEq/2Z4fE/src/solve.jl:4 [inlined]
[17] #solve_call#56
@ ~/.julia/packages/DiffEqBase/jhLIm/src/solve.jl:61 [inlined]
[18] solve_up(prob::ODEProblem{CUDA.CuArray{Float32, 2}, Tuple{Float32, Float32}, true, CUDA.CuArray{Float32, 2}, ODEFunction{true, DiffEqGPU.var"#55#59"{ModelingToolkit.var"#f#148"{RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(Symbol("##arg#351"), Symbol("##arg#352"), :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0xe09e3e39, 0x901fd863, 0xaabe4072, 0xa349f5db, 0x1e2ac5dd)}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(Symbol("##out#353"), Symbol("##arg#351"), Symbol("##arg#352"), :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x255a3166, 0x06ba9a71, 0xa2d333f0, 0xa11339db, 0xc80f8c0d)}}, typeof(DiffEqGPU.gpu_kernel)}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Iterators.Pairs{Union{}, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, sensealg::Nothing, u0::CUDA.CuArray{Float32, 2}, p::CUDA.CuArray{Float32, 2}, args::Tsit5; kwargs::Base.Iterators.Pairs{Symbol, Any, NTuple{5, Symbol}, NamedTuple{(:unstable_check, :saveat, :callback, :merge_callbacks, :internalnorm), Tuple{DiffEqGPU.var"#10#16", Float32, Nothing, Bool, typeof(DiffEqGPU.diffeqgpunorm)}}})
@ DiffEqBase ~/.julia/packages/DiffEqBase/jhLIm/src/solve.jl:82
[19] #solve#57
@ ~/.julia/packages/DiffEqBase/jhLIm/src/solve.jl:70 [inlined]
[20] batch_solve_up(ensembleprob::EnsembleProblem{ODEProblem{Vector{Float32}, Tuple{Float32, Float32}, true, Vector{Float32}, ODEFunction{true, ModelingToolkit.var"#f#148"{RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(Symbol("##arg#351"), Symbol("##arg#352"), :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0xe09e3e39, 0x901fd863, 0xaabe4072, 0xa349f5db, 0x1e2ac5dd)}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(Symbol("##out#353"), Symbol("##arg#351"), Symbol("##arg#352"), :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x255a3166, 0x06ba9a71, 0xa2d333f0, 0xa11339db, 0xc80f8c0d)}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Vector{Symbol}, Symbol, ModelingToolkit.var"#121#generated_observed#155"{Bool, ODESystem, Dict{Any, Any}}, Nothing}, Base.Iterators.Pairs{Union{}, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, var"#1#2", typeof(SciMLBase.DEFAULT_OUTPUT_FUNC), typeof(SciMLBase.DEFAULT_REDUCTION), Nothing}, probs::Vector{ODEProblem{Vector{Float32}, Tuple{Float32, Float32}, true, Vector{Float32}, ODEFunction{true, ModelingToolkit.var"#f#148"{RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(Symbol("##arg#351"), Symbol("##arg#352"), :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0xe09e3e39, 0x901fd863, 0xaabe4072, 0xa349f5db, 0x1e2ac5dd)}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(Symbol("##out#353"), Symbol("##arg#351"), Symbol("##arg#352"), :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x255a3166, 0x06ba9a71, 0xa2d333f0, 0xa11339db, 0xc80f8c0d)}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Vector{Symbol}, Symbol, ModelingToolkit.var"#121#generated_observed#155"{Bool, ODESystem, Dict{Any, Any}}, Nothing}, Base.Iterators.Pairs{Union{}, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}}, alg::Tsit5, ensemblealg::EnsembleGPUArray, I::UnitRange{Int64}, u0::Matrix{Float32}, p::Matrix{Float32}; kwargs::Base.Iterators.Pairs{Symbol, Any, Tuple{Symbol, Symbol}, NamedTuple{(:unstable_check, :saveat), Tuple{DiffEqGPU.var"#10#16", Float32}}})
@ DiffEqGPU ~/.julia/packages/DiffEqGPU/YMmTv/src/DiffEqGPU.jl:313
[21] batch_solve(ensembleprob::EnsembleProblem{ODEProblem{Vector{Float32}, Tuple{Float32, Float32}, true, Vector{Float32}, ODEFunction{true, ModelingToolkit.var"#f#148"{RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(Symbol("##arg#351"), Symbol("##arg#352"), :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0xe09e3e39, 0x901fd863, 0xaabe4072, 0xa349f5db, 0x1e2ac5dd)}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(Symbol("##out#353"), Symbol("##arg#351"), Symbol("##arg#352"), :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x255a3166, 0x06ba9a71, 0xa2d333f0, 0xa11339db, 0xc80f8c0d)}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Vector{Symbol}, Symbol, ModelingToolkit.var"#121#generated_observed#155"{Bool, ODESystem, Dict{Any, Any}}, Nothing}, Base.Iterators.Pairs{Union{}, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, var"#1#2", typeof(SciMLBase.DEFAULT_OUTPUT_FUNC), typeof(SciMLBase.DEFAULT_REDUCTION), Nothing}, alg::Tsit5, ensemblealg::EnsembleGPUArray, I::UnitRange{Int64}; kwargs::Base.Iterators.Pairs{Symbol, Any, Tuple{Symbol, Symbol}, NamedTuple{(:unstable_check, :saveat), Tuple{DiffEqGPU.var"#10#16", Float32}}})
@ DiffEqGPU ~/.julia/packages/DiffEqGPU/YMmTv/src/DiffEqGPU.jl:278
[22] macro expansion
@ ./timing.jl:287 [inlined]
[23] __solve(ensembleprob::EnsembleProblem{ODEProblem{Vector{Float32}, Tuple{Float32, Float32}, true, Vector{Float32}, ODEFunction{true, ModelingToolkit.var"#f#148"{RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(Symbol("##arg#351"), Symbol("##arg#352"), :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0xe09e3e39, 0x901fd863, 0xaabe4072, 0xa349f5db, 0x1e2ac5dd)}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(Symbol("##out#353"), Symbol("##arg#351"), Symbol("##arg#352"), :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x255a3166, 0x06ba9a71, 0xa2d333f0, 0xa11339db, 0xc80f8c0d)}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Vector{Symbol}, Symbol, ModelingToolkit.var"#121#generated_observed#155"{Bool, ODESystem, Dict{Any, Any}}, Nothing}, Base.Iterators.Pairs{Union{}, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, var"#1#2", typeof(SciMLBase.DEFAULT_OUTPUT_FUNC), typeof(SciMLBase.DEFAULT_REDUCTION), Nothing}, alg::Tsit5, ensemblealg::EnsembleGPUArray; trajectories::Int64, batch_size::Int64, unstable_check::Function, kwargs::Base.Iterators.Pairs{Symbol, Float32, Tuple{Symbol}, NamedTuple{(:saveat,), Tuple{Float32}}})
@ DiffEqGPU ~/.julia/packages/DiffEqGPU/YMmTv/src/DiffEqGPU.jl:195
[24] #solve#59
@ ~/.julia/packages/DiffEqBase/jhLIm/src/solve.jl:96 [inlined]
[25] top-level scope
@ ~/test_GPU/test.jl:27
[26] include(fname::String)
@ Base.MainInclude ./client.jl:444
[27] top-level scope
@ REPL[2]:1
in expression starting at ~/test_GPU/test.jl:27