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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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MNIST Example Throws Exception at Optimization.solve (in v4.0) #954

Open jholland1 opened 1 month ago

jholland1 commented 1 month ago

Describe the bug 🐞

MNIST example throws exception at solve. https://docs.sciml.ai/DiffEqFlux/stable/examples/mnist_neural_ode/

Expected behavior

A clear and concise description of what you expected to happen.

Minimal Reproducible Example 👇

Without MRE, we would only be able to help you to a limited extent, and attention to the issue would be limited. to know more about MRE refer to wikipedia and stackoverflow.

https://docs.sciml.ai/DiffEqFlux/stable/examples/mnist_neural_ode/

Error & Stacktrace ⚠️


1-element ExceptionStack:
LoadError: Optimization algorithm not found. Either the chosen algorithm is not a valid solver
choice for the `OptimizationProblem`, or the Optimization solver library is not loaded.
Make sure that you have loaded an appropriate Optimization.jl solver library, for example,
`solve(prob,Optim.BFGS())` requires `using OptimizationOptimJL` and
`solve(prob,Adam())` requires `using OptimizationOptimisers`.

For more information, see the Optimization.jl documentation: https://docs.sciml.ai/Optimization/stable/.

Chosen Optimizer: Adam(0.05, (0.9, 0.999), 1.0e-8)
Stacktrace:
 [1] __init(prob::OptimizationProblem{true, OptimizationFunction{true, AutoZygote, var"#3#4", 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}, ComponentVector{Float32, CuArray{Float32, 1, CUDA.DeviceMemory}, Tuple{Axis{(down = ViewAxis(1:15700, Axis(layer_1 = 1:0, layer_2 = ViewAxis(1:15700, Axis(weight = ViewAxis(1:15680, ShapedAxis((20, 784))), bias = 15681:15700)))), nn_ode = ViewAxis(15701:16240, Axis(layer_1 = ViewAxis(1:210, Axis(weight = ViewAxis(1:200, ShapedAxis((10, 20))), bias = 201:210)), layer_2 = ViewAxis(211:320, Axis(weight = ViewAxis(1:100, ShapedAxis((10, 10))), bias = 101:110)), layer_3 = ViewAxis(321:540, Axis(weight = ViewAxis(1:200, ShapedAxis((20, 10))), bias = 201:220)))), convert = 16241:16240, fc = ViewAxis(16241:16450, Axis(weight = ViewAxis(1:200, ShapedAxis((10, 20))), bias = 201:210)))}}}, SciMLBase.NullParameters, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, @Kwargs{}}, alg::Adam, args::Base.Iterators.Zip{Tuple{BatchView{CuArray{Float32, 4, CUDA.DeviceMemory}, CuArray{Float32, 4, CUDA.DeviceMemory}, LearnBase.ObsDim.Last}, BatchView{CuArray{Int64, 2, CUDA.DeviceMemory}, CuArray{Int64, 2, CUDA.DeviceMemory}, LearnBase.ObsDim.Last}}}; kwargs::@Kwargs{callback::typeof(callback)})
   @ SciMLBase 
 [2] init(prob::OptimizationProblem{true, OptimizationFunction{true, AutoZygote, var"#3#4", 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}, ComponentVector{Float32, CuArray{Float32, 1, CUDA.DeviceMemory}, Tuple{Axis{(down = ViewAxis(1:15700, Axis(layer_1 = 1:0, layer_2 = ViewAxis(1:15700, Axis(weight = ViewAxis(1:15680, ShapedAxis((20, 784))), bias = 15681:15700)))), nn_ode = ViewAxis(15701:16240, Axis(layer_1 = ViewAxis(1:210, Axis(weight = ViewAxis(1:200, ShapedAxis((10, 20))), bias = 201:210)), layer_2 = ViewAxis(211:320, Axis(weight = ViewAxis(1:100, ShapedAxis((10, 10))), bias = 101:110)), layer_3 = ViewAxis(321:540, Axis(weight = ViewAxis(1:200, ShapedAxis((20, 10))), bias = 201:220)))), convert = 16241:16240, fc = ViewAxis(16241:16450, Axis(weight = ViewAxis(1:200, ShapedAxis((10, 20))), bias = 201:210)))}}}, SciMLBase.NullParameters, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, @Kwargs{}}, alg::Adam, args::Base.Iterators.Zip{Tuple{BatchView{CuArray{Float32, 4, CUDA.DeviceMemory}, CuArray{Float32, 4, CUDA.DeviceMemory}, LearnBase.ObsDim.Last}, BatchView{CuArray{Int64, 2, CUDA.DeviceMemory}, CuArray{Int64, 2, CUDA.DeviceMemory}, LearnBase.ObsDim.Last}}}; kwargs::@Kwargs{callback::typeof(callback)})
   @ SciMLBase 
 [3] solve(prob::OptimizationProblem{true, OptimizationFunction{true, AutoZygote, var"#3#4", 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}, ComponentVector{Float32, CuArray{Float32, 1, CUDA.DeviceMemory}, Tuple{Axis{(down = ViewAxis(1:15700, Axis(layer_1 = 1:0, layer_2 = ViewAxis(1:15700, Axis(weight = ViewAxis(1:15680, ShapedAxis((20, 784))), bias = 15681:15700)))), nn_ode = ViewAxis(15701:16240, Axis(layer_1 = ViewAxis(1:210, Axis(weight = ViewAxis(1:200, ShapedAxis((10, 20))), bias = 201:210)), layer_2 = ViewAxis(211:320, Axis(weight = ViewAxis(1:100, ShapedAxis((10, 10))), bias = 101:110)), layer_3 = ViewAxis(321:540, Axis(weight = ViewAxis(1:200, ShapedAxis((20, 10))), bias = 201:220)))), convert = 16241:16240, fc = ViewAxis(16241:16450, Axis(weight = ViewAxis(1:200, ShapedAxis((10, 20))), bias = 201:210)))}}}, SciMLBase.NullParameters, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, @Kwargs{}}, alg::Adam, args::Base.Iterators.Zip{Tuple{BatchView{CuArray{Float32, 4, CUDA.DeviceMemory}, CuArray{Float32, 4, CUDA.DeviceMemory}, LearnBase.ObsDim.Last}, BatchView{CuArray{Int64, 2, CUDA.DeviceMemory}, CuArray{Int64, 2, CUDA.DeviceMemory}, LearnBase.ObsDim.Last}}}; kwargs::@Kwargs{callback::typeof(callback)})
   @ SciMLBase

Environment (please complete the following information):

julia> Pkg.status()
Status `\.julia\environments\v1.11\Project.toml`
  [052768ef] CUDA v5.5.2
  [b0b7db55] ComponentArrays v0.15.17
  [aae7a2af] DiffEqFlux v4.0.0
  [b2108857] Lux v1.1.0
  [d0bbae9a] LuxCUDA v0.3.3
  [cc2ba9b6] MLDataUtils v0.5.4
  [eb30cadb] MLDatasets v0.7.18
  [872c559c] NNlib v0.9.24
  [7f7a1694] Optimization v4.0.3
  [42dfb2eb] OptimizationOptimisers v0.3.3
  [1dea7af3] OrdinaryDiffEq v6.89.0
  [10745b16] Statistics v1.11.1
  [e88e6eb3] Zygote v0.6.72
  [9a3f8284] Random v1.11.0
  [8dfed614] Test v1.11.0
Status '\.julia\environments\v1.11\Manifest.toml`
  [47edcb42] ADTypes v1.9.0
  [621f4979] AbstractFFTs v1.5.0
  [1520ce14] AbstractTrees v0.4.5
  [7d9f7c33] Accessors v0.1.38
  [79e6a3ab] Adapt v4.0.4
  [66dad0bd] AliasTables v1.1.3
  [dce04be8] ArgCheck v2.3.0
  [ec485272] ArnoldiMethod v0.4.0
  [4fba245c] ArrayInterface v7.16.0
  [4c555306] ArrayLayouts v1.10.3
  [a9b6321e] Atomix v0.1.0
⌅ [a963bdd2] AtomsBase v0.3.5
  [ab4f0b2a] BFloat16s v0.5.0
  [198e06fe] BangBang v0.4.3
  [9718e550] Baselet v0.1.1
  [d1d4a3ce] BitFlags v0.1.9
  [62783981] BitTwiddlingConvenienceFunctions v0.1.6
  [4544d5e4] Boltz v1.0.1
  [e1450e63] BufferedStreams v1.2.2
  [fa961155] CEnum v0.5.0
  [2a0fbf3d] CPUSummary v0.2.6
  [336ed68f] CSV v0.10.14
  [052768ef] CUDA v5.5.2
  [1af6417a] CUDA_Runtime_Discovery v0.3.5
  [7057c7e9] Cassette v0.3.13
  [082447d4] ChainRules v1.71.0
  [d360d2e6] ChainRulesCore v1.25.0
  [46823bd8] Chemfiles v0.10.41
  [fb6a15b2] CloseOpenIntervals v0.1.13
  [944b1d66] CodecZlib v0.7.6
  [35d6a980] ColorSchemes v3.26.0
  [3da002f7] ColorTypes v0.11.5
  [c3611d14] ColorVectorSpace v0.10.0
  [5ae59095] Colors v0.12.11
  [38540f10] CommonSolve v0.2.4
  [bbf7d656] CommonSubexpressions v0.3.1
  [f70d9fcc] CommonWorldInvalidations v1.0.0
  [34da2185] Compat v4.16.0
  [b0b7db55] ComponentArrays v0.15.17
  [a33af91c] CompositionsBase v0.1.2
  [2569d6c7] ConcreteStructs v0.2.3
  [f0e56b4a] ConcurrentUtilities v2.4.2
  [88cd18e8] ConsoleProgressMonitor v0.1.2
  [187b0558] ConstructionBase v1.5.8
  [6add18c4] ContextVariablesX v0.1.3
  [adafc99b] CpuId v0.3.1
  [a8cc5b0e] Crayons v4.1.1
  [9a962f9c] DataAPI v1.16.0
  [124859b0] DataDeps v0.7.13
  [a93c6f00] DataFrames v1.7.0
  [864edb3b] DataStructures v0.18.20
  [e2d170a0] DataValueInterfaces v1.0.0
  [244e2a9f] DefineSingletons v0.1.2
  [8bb1440f] DelimitedFiles v1.9.1
  [2b5f629d] DiffEqBase v6.158.1
  [459566f4] DiffEqCallbacks v4.0.0
  [aae7a2af] DiffEqFlux v4.0.0
  [77a26b50] DiffEqNoiseProcess v5.23.0
  [163ba53b] DiffResults v1.1.0
  [b552c78f] DiffRules v1.15.1
  [a0c0ee7d] DifferentiationInterface v0.6.16
  [8d63f2c5] DispatchDoctor v0.4.16
  [31c24e10] Distributions v0.25.112
  [ffbed154] DocStringExtensions v0.9.3
  [4e289a0a] EnumX v1.0.4
  [7da242da] Enzyme v0.13.11
  [f151be2c] EnzymeCore v0.8.4
  [460bff9d] ExceptionUnwrapping v0.1.10
  [d4d017d3] ExponentialUtilities v1.26.1
  [e2ba6199] ExprTools v0.1.10
⌅ [6b7a57c9] Expronicon v0.8.5
  [cc61a311] FLoops v0.2.2
  [b9860ae5] FLoopsBase v0.1.1
  [7034ab61] FastBroadcast v0.3.5
  [9aa1b823] FastClosures v0.3.2
  [29a986be] FastLapackInterface v2.0.4
  [5789e2e9] FileIO v1.16.4
  [48062228] FilePathsBase v0.9.22
  [1a297f60] FillArrays v1.13.0
  [6a86dc24] FiniteDiff v2.26.0
  [53c48c17] FixedPointNumbers v0.8.5
  [f6369f11] ForwardDiff v0.10.36
  [f62d2435] FunctionProperties v0.1.2
  [069b7b12] FunctionWrappers v1.1.3
  [77dc65aa] FunctionWrappersWrappers v0.1.3
  [d9f16b24] Functors v0.4.12
⌅ [0c68f7d7] GPUArrays v10.3.1
⌅ [46192b85] GPUArraysCore v0.1.6
⌅ [61eb1bfa] GPUCompiler v0.27.8
  [92fee26a] GZip v0.6.2
  [c145ed77] GenericSchur v0.5.4
  [c27321d9] Glob v1.3.1
  [86223c79] Graphs v1.12.0
  [f67ccb44] HDF5 v0.17.2
  [cd3eb016] HTTP v1.10.8
  [3e5b6fbb] HostCPUFeatures v0.1.17
  [0e44f5e4] Hwloc v3.3.0
  [34004b35] HypergeometricFunctions v0.3.24
  [7869d1d1] IRTools v0.4.14
  [615f187c] IfElse v0.1.1
  [c817782e] ImageBase v0.1.7
  [a09fc81d] ImageCore v0.10.2
  [4e3cecfd] ImageShow v0.3.8
  [d25df0c9] Inflate v0.1.5
  [22cec73e] InitialValues v0.3.1
  [842dd82b] InlineStrings v1.4.2
  [7d512f48] InternedStrings v0.7.0
  [3587e190] InverseFunctions v0.1.17
  [41ab1584] InvertedIndices v1.3.0
  [92d709cd] IrrationalConstants v0.2.2
  [82899510] IteratorInterfaceExtensions v1.0.0
  [033835bb] JLD2 v0.5.6
  [692b3bcd] JLLWrappers v1.6.1
  [0f8b85d8] JSON3 v1.14.1
  [b14d175d] JuliaVariables v0.2.4
  [ef3ab10e] KLU v0.6.0
  [63c18a36] KernelAbstractions v0.9.28
  [ba0b0d4f] Krylov v0.9.7
  [5be7bae1] LBFGSB v0.4.1
  [929cbde3] LLVM v9.1.2
  [8b046642] LLVMLoopInfo v1.0.0
  [b964fa9f] LaTeXStrings v1.4.0
  [10f19ff3] LayoutPointers v0.1.17
  [5078a376] LazyArrays v2.2.1
  [8cdb02fc] LazyModules v0.3.1
⌅ [7f8f8fb0] LearnBase v0.3.0
  [1d6d02ad] LeftChildRightSiblingTrees v0.2.0
  [87fe0de2] LineSearch v0.1.3
  [d3d80556] LineSearches v7.3.0
  [7ed4a6bd] LinearSolve v2.36.0
  [2ab3a3ac] LogExpFunctions v0.3.28
  [e6f89c97] LoggingExtras v1.0.3
  [bdcacae8] LoopVectorization v0.12.171
  [30fc2ffe] LossFunctions v0.11.2
  [b2108857] Lux v1.1.0
  [d0bbae9a] LuxCUDA v0.3.3
  [bb33d45b] LuxCore v1.0.1
  [82251201] LuxLib v1.3.4
  [23992714] MAT v0.10.7
  [7e8f7934] MLDataDevices v1.3.0
⌃ [9920b226] MLDataPattern v0.5.4
  [cc2ba9b6] MLDataUtils v0.5.4
  [eb30cadb] MLDatasets v0.7.18
  [66a33bbf] MLLabelUtils v0.5.7
  [d8e11817] MLStyle v0.4.17
  [f1d291b0] MLUtils v0.4.4
  [3da0fdf6] MPIPreferences v0.1.11
  [1914dd2f] MacroTools v0.5.13
  [d125e4d3] ManualMemory v0.1.8
  [dbb5928d] MappedArrays v0.4.2
  [bb5d69b7] MaybeInplace v0.1.4
  [739be429] MbedTLS v1.1.9
  [128add7d] MicroCollections v0.2.0
  [e1d29d7a] Missings v1.2.0
  [e94cdb99] MosaicViews v0.3.4
  [46d2c3a1] MuladdMacro v0.2.4
  [d41bc354] NLSolversBase v7.8.3
  [872c559c] NNlib v0.9.24
  [15e1cf62] NPZ v0.4.3
  [5da4648a] NVTX v0.3.4
  [77ba4419] NaNMath v1.0.2
  [71a1bf82] NameResolution v0.1.5
  [8913a72c] NonlinearSolve v3.15.1
  [d8793406] ObjectFile v0.4.2
  [6fe1bfb0] OffsetArrays v1.14.1
  [4d8831e6] OpenSSL v1.4.3
  [429524aa] Optim v1.9.4
  [3bd65402] Optimisers v0.3.3
  [7f7a1694] Optimization v4.0.3
  [bca83a33] OptimizationBase v2.3.0
  [42dfb2eb] OptimizationOptimisers v0.3.3
  [bac558e1] OrderedCollections v1.6.3
  [1dea7af3] OrdinaryDiffEq v6.89.0
  [89bda076] OrdinaryDiffEqAdamsBashforthMoulton v1.1.0
  [6ad6398a] OrdinaryDiffEqBDF v1.1.2
  [bbf590c4] OrdinaryDiffEqCore v1.7.1
  [50262376] OrdinaryDiffEqDefault v1.1.0
  [4302a76b] OrdinaryDiffEqDifferentiation v1.1.0
  [9286f039] OrdinaryDiffEqExplicitRK v1.1.0
  [e0540318] OrdinaryDiffEqExponentialRK v1.1.0
  [becaefa8] OrdinaryDiffEqExtrapolation v1.1.0
  [5960d6e9] OrdinaryDiffEqFIRK v1.1.1
  [101fe9f7] OrdinaryDiffEqFeagin v1.1.0
  [d3585ca7] OrdinaryDiffEqFunctionMap v1.1.1
  [d28bc4f8] OrdinaryDiffEqHighOrderRK v1.1.0
  [9f002381] OrdinaryDiffEqIMEXMultistep v1.1.0
  [521117fe] OrdinaryDiffEqLinear v1.1.0
  [1344f307] OrdinaryDiffEqLowOrderRK v1.2.0
  [b0944070] OrdinaryDiffEqLowStorageRK v1.2.1
  [127b3ac7] OrdinaryDiffEqNonlinearSolve v1.2.1
  [c9986a66] OrdinaryDiffEqNordsieck v1.1.0
  [5dd0a6cf] OrdinaryDiffEqPDIRK v1.1.0
  [5b33eab2] OrdinaryDiffEqPRK v1.1.0
  [04162be5] OrdinaryDiffEqQPRK v1.1.0
  [af6ede74] OrdinaryDiffEqRKN v1.1.0
  [43230ef6] OrdinaryDiffEqRosenbrock v1.2.0
  [2d112036] OrdinaryDiffEqSDIRK v1.1.0
  [669c94d9] OrdinaryDiffEqSSPRK v1.2.0
  [e3e12d00] OrdinaryDiffEqStabilizedIRK v1.1.0
  [358294b1] OrdinaryDiffEqStabilizedRK v1.1.0
  [fa646aed] OrdinaryDiffEqSymplecticRK v1.1.0
  [b1df2697] OrdinaryDiffEqTsit5 v1.1.0
  [79d7bb75] OrdinaryDiffEqVerner v1.1.1
  [90014a1f] PDMats v0.11.31
  [65ce6f38] PackageExtensionCompat v1.0.2
  [5432bcbf] PaddedViews v0.5.12
  [d96e819e] Parameters v0.12.3
  [69de0a69] Parsers v2.8.1
  [7b2266bf] PeriodicTable v1.2.1
  [fbb45041] Pickle v0.3.5
  [e409e4f3] PoissonRandom v0.4.4
  [f517fe37] Polyester v0.7.16
  [1d0040c9] PolyesterWeave v0.2.2
  [2dfb63ee] PooledArrays v1.4.3
  [85a6dd25] PositiveFactorizations v0.2.4
  [d236fae5] PreallocationTools v0.4.24
  [aea7be01] PrecompileTools v1.2.1
  [21216c6a] Preferences v1.4.3
  [8162dcfd] PrettyPrint v0.2.0
  [08abe8d2] PrettyTables v2.4.0
  [33c8b6b6] ProgressLogging v0.1.4
  [92933f4c] ProgressMeter v1.10.2
  [43287f4e] PtrArrays v1.2.1
  [1fd47b50] QuadGK v2.11.1
  [74087812] Random123 v1.7.0
  [e6cf234a] RandomNumbers v1.6.0
  [c1ae055f] RealDot v0.1.0
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  [f2c3362d] RecursiveFactorization v0.2.23
  [189a3867] Reexport v1.2.2
  [ae029012] Requires v1.3.0
  [ae5879a3] ResettableStacks v1.1.1
  [37e2e3b7] ReverseDiff v1.15.3
  [79098fc4] Rmath v0.8.0
  [7e49a35a] RuntimeGeneratedFunctions v0.5.13
  [94e857df] SIMDTypes v0.1.0
  [476501e8] SLEEFPirates v0.6.43
  [0bca4576] SciMLBase v2.56.3
  [19f34311] SciMLJacobianOperators v0.1.0
  [c0aeaf25] SciMLOperators v0.3.11
  [1ed8b502] SciMLSensitivity v7.69.0
  [53ae85a6] SciMLStructures v1.5.0
  [6c6a2e73] Scratch v1.2.1
  [91c51154] SentinelArrays v1.4.5
  [efcf1570] Setfield v1.1.1
  [605ecd9f] ShowCases v0.1.0
  [777ac1f9] SimpleBufferStream v1.2.0
  [727e6d20] SimpleNonlinearSolve v1.12.3
  [699a6c99] SimpleTraits v0.9.4
  [ce78b400] SimpleUnPack v1.1.0
  [a2af1166] SortingAlgorithms v1.2.1
  [9f842d2f] SparseConnectivityTracer v0.6.7
  [47a9eef4] SparseDiffTools v2.23.0
  [dc90abb0] SparseInverseSubset v0.1.2
  [0a514795] SparseMatrixColorings v0.4.7
  [e56a9233] Sparspak v0.3.9
  [276daf66] SpecialFunctions v2.4.0
  [171d559e] SplittablesBase v0.1.15
  [cae243ae] StackViews v0.1.1
  [aedffcd0] Static v1.1.1
  [0d7ed370] StaticArrayInterface v1.8.0
  [90137ffa] StaticArrays v1.9.7
  [1e83bf80] StaticArraysCore v1.4.3
  [10745b16] Statistics v1.11.1
  [82ae8749] StatsAPI v1.7.0
⌅ [2913bbd2] StatsBase v0.33.21
  [4c63d2b9] StatsFuns v1.3.2
  [7792a7ef] StrideArraysCore v0.5.7
⌅ [4db3bf67] StridedViews v0.2.2
  [69024149] StringEncodings v0.3.7
  [892a3eda] StringManipulation v0.4.0
  [09ab397b] StructArrays v0.6.18
  [53d494c1] StructIO v0.3.1
  [856f2bd8] StructTypes v1.11.0
  [2efcf032] SymbolicIndexingInterface v0.3.33
  [3783bdb8] TableTraits v1.0.1
  [bd369af6] Tables v1.12.0
  [62fd8b95] TensorCore v0.1.1
  [5d786b92] TerminalLoggers v0.1.7
  [8290d209] ThreadingUtilities v0.5.2
  [a759f4b9] TimerOutputs v0.5.25
  [9f7883ad] Tracker v0.2.35
  [3bb67fe8] TranscodingStreams v0.11.3
  [28d57a85] Transducers v0.4.84
  [d5829a12] TriangularSolve v0.2.1
  [781d530d] TruncatedStacktraces v1.4.0
  [5c2747f8] URIs v1.5.1
  [3a884ed6] UnPack v1.0.2
  [1986cc42] Unitful v1.21.0
  [a7773ee8] UnitfulAtomic v1.0.0
  [013be700] UnsafeAtomics v0.2.1
  [d80eeb9a] UnsafeAtomicsLLVM v0.2.1
  [3d5dd08c] VectorizationBase v0.21.70
  [19fa3120] VertexSafeGraphs v0.2.0
  [ea10d353] WeakRefStrings v1.4.2
  [d49dbf32] WeightInitializers v1.0.4
  [76eceee3] WorkerUtilities v1.6.1
  [a5390f91] ZipFile v0.10.1
  [e88e6eb3] Zygote v0.6.72
  [700de1a5] ZygoteRules v0.2.5
  [02a925ec] cuDNN v1.4.0
  [4ee394cb] CUDA_Driver_jll v0.10.3+0
  [76a88914] CUDA_Runtime_jll v0.15.3+0
  [62b44479] CUDNN_jll v9.4.0+0
  [78a364fa] Chemfiles_jll v0.10.4+0
⌅ [7cc45869] Enzyme_jll v0.0.154+0
  [0234f1f7] HDF5_jll v1.14.3+3
  [e33a78d0] Hwloc_jll v2.11.2+0
  [1d5cc7b8] IntelOpenMP_jll v2024.2.1+0
  [9c1d0b0a] JuliaNVTXCallbacks_jll v0.2.1+0
  [dad2f222] LLVMExtra_jll v0.0.34+0
  [81d17ec3] L_BFGS_B_jll v3.0.1+0
  [94ce4f54] Libiconv_jll v1.17.0+0
  [856f044c] MKL_jll v2024.2.0+0
  [7cb0a576] MPICH_jll v4.2.3+0
  [f1f71cc9] MPItrampoline_jll v5.5.1+0
  [9237b28f] MicrosoftMPI_jll v10.1.4+2
  [e98f9f5b] NVTX_jll v3.1.0+2
⌅ [fe0851c0] OpenMPI_jll v4.1.6+0
  [458c3c95] OpenSSL_jll v3.0.15+1
  [efe28fd5] OpenSpecFun_jll v0.5.5+0
  [f50d1b31] Rmath_jll v0.5.1+0
  [1e29f10c] demumble_jll v1.3.0+0
  [477f73a3] libaec_jll v1.1.2+0
  [1317d2d5] oneTBB_jll v2021.12.0+0
  [0dad84c5] ArgTools v1.1.2
  [56f22d72] Artifacts v1.11.0
  [2a0f44e3] Base64 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
  [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
  [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
  [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
  [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
Info Packages marked with ⌃ and ⌅ have new versions available. Those with ⌃ may be upgradable, but those with ⌅ are restricted by compatibility constraints from upgrading. To see why use `status --outdated -m`

julia> versioninfo()
Julia Version 1.11.1
Commit 8f5b7ca12a (2024-10-16 10:53 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Windows (x86_64-w64-mingw32)
  CPU: 16 × 12th Gen Intel(R) Core(TM) i7-12650H
  WORD_SIZE: 64
  LLVM: libLLVM-16.0.6 (ORCJIT, alderlake)
Threads: 10 default, 0 interactive, 5 GC (on 16 virtual cores)
Environment:
  JULIA_NUM_THREADS = 10

Additional context

Add any other context about the problem here.

jholland1 commented 1 month ago

Runs to completion (with some errors in the callback function) in v3.5.0. Didn't catch that docs were written for v3.5.0, v4.0 downloaded by default.

jholland1 commented 1 month ago

And no issues noticed on a similar example in the Lux documentation with v4.0.0: https://lux.csail.mit.edu/stable/tutorials/intermediate/1_NeuralODE

ChrisRackauckas commented 1 month ago

This is addressed in the docs bump https://github.com/SciML/DiffEqFlux.jl/pull/950