failed to run `@example` block in docs/src/tutorials/matrix_softmax.md:34-59 ```@example softmax_comparison using GeometricMachineLearning # hide using GeometricProblems.CoupledHarmonicOscillator: hodeensemble, default_parameters using GeometricIntegrators: ImplicitMidpoint, integrate # hide using LaTeXStrings # hide using CairoMakie # hide CairoMakie.activate!() # hide import Random # hide Random.seed!(123) # hide morange = RGBf(255 / 256, 127 / 256, 14 / 256) # hide mred = RGBf(214 / 256, 39 / 256, 40 / 256) # hide mpurple = RGBf(148 / 256, 103 / 256, 189 / 256) # hide mblue = RGBf(31 / 256, 119 / 256, 180 / 256) # hide mgreen = RGBf(44 / 256, 160 / 256, 44 / 256) # hide const timestep = .3 const n_init_con = 5 # ensemble problem ep = hodeensemble([rand(2) for _ in 1:n_init_con], [rand(2) for _ in 1:n_init_con]; timestep = timestep) dl = DataLoader(integrate(ep, ImplicitMidpoint()); suppress_info = true) # dl = DataLoader(vcat(dl_nt.input.q, dl_nt.input.p)) # hide nothing # hide ``` exception = MethodError: no method matching DataLoader(::GeometricSolutions.EnsembleSolution{Float64, Float64, Vector{GeometricSolutions.GeometricSolution{Float64, Float64, GeometricSolutions.TimeSeries{Float64, OffsetArrays.OffsetVector{Float64, StepRangeLen{Float64, Base.TwicePrecision{Float64}, Base.TwicePrecision{Float64}, Int64}}}, @NamedTuple{q::GeometricSolutions.DataSeries{Float64, GeometricBase.StateVariable{Float64, 1, Vector{Float64}, Tuple{Vector{Float64}, Vector{Float64}}, BitVector}}, p::GeometricSolutions.DataSeries{Float64, GeometricBase.StateVariable{Float64, 1, Vector{Float64}, Tuple{Vector{Float64}, Vector{Float64}}, BitVector}}}, GeometricEquations.HODEProblem{Float64, Float64, GeometricBase.StateVariable{Float64, 1, Vector{Float64}, Tuple{Vector{Float64}, Vector{Float64}}, BitVector}, GeometricEquations.HODE{RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :t, :Q, :P, :params), EulerLagrange.var"#_RGF_ModTag", EulerLagrange.var"#_RGF_ModTag", (0x817dbd6e, 0x2a2c99f6, 0x213621bd, 0xeb5e4e27, 0x4a71273d), Expr}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :t, :Q, :P, :params), EulerLagrange.var"#_RGF_ModTag", EulerLagrange.var"#_RGF_ModTag", (0x32d7601b, 0xde41fe41, 0x56d4143a, 0x8881cb11, 0xd017ff77), Expr}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :t, :Q, :P, :params), EulerLagrange.var"#_RGF_ModTag", EulerLagrange.var"#_RGF_ModTag", (0x817dbd6e, 0x2a2c99f6, 0x213621bd, 0xeb5e4e27, 0x4a71273d), Expr}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :t, :Q, :P, :params), EulerLagrange.var"#_RGF_ModTag", EulerLagrange.var"#_RGF_ModTag", (0x32d7601b, 0xde41fe41, 0x56d4143a, 0x8881cb11, 0xd017ff77), Expr}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:t, :Q, :P, :params), EulerLagrange.var"#_RGF_ModTag", EulerLagrange.var"#_RGF_ModTag", (0x3c20e916, 0xa49c2fd2, 0xe66e2ce0, 0x3130cd12, 0xb53eab21), Expr}, GeometricBase.NullInvariants, @NamedTuple{m₁::DataType, m₂::DataType, k₁::DataType, k₂::DataType, k::DataType}, GeometricBase.NullPeriodicity}, @NamedTuple{v::RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :t, :Q, :P, :params), EulerLagrange.var"#_RGF_ModTag", EulerLagrange.var"#_RGF_ModTag", (0x817dbd6e, 0x2a2c99f6, 0x213621bd, 0xeb5e4e27, 0x4a71273d), Expr}, f::RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :t, :Q, :P, :params), EulerLagrange.var"#_RGF_ModTag", EulerLagrange.var"#_RGF_ModTag", (0x32d7601b, 0xde41fe41, 0x56d4143a, 0x8881cb11, 0xd017ff77), Expr}, h::RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:t, :Q, :P, :params), EulerLagrange.var"#_RGF_ModTag", EulerLagrange.var"#_RGF_ModTag", (0x3c20e916, 0xa49c2fd2, 0xe66e2ce0, 0x3130cd12, 0xb53eab21), Expr}}, @NamedTuple{}, @NamedTuple{v::RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :t, :Q, :P, :params), EulerLagrange.var"#_RGF_ModTag", EulerLagrange.var"#_RGF_ModTag", (0x817dbd6e, 0x2a2c99f6, 0x213621bd, 0xeb5e4e27, 0x4a71273d), Expr}, f::RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :t, :Q, :P, :

failed to run `@example` block in docs/src/tutorials/linear_symplectic_transformer.md:186-188 ```@example lin_sympl_tran_tut parameterlength(nn_standard), parameterlength(nn_symplectic), parameterlength(nn_sympnet) ``` exception = UndefVarError: `nn_standard` not defined in `Main.__atexample__named__lin_sympl_tran_tut` Suggestion: check for spelling errors or missing imports. Stacktrace: [1] top-level scope @ linear_symplectic_transformer.md:187 [2] eval(m::Module, e::Any) @ Core ./boot.jl:489 [3] #61 @ ~/.julia/packages/Documenter/AXNMp/src/expander_pipeline.jl:879 [inlined] [4] cd(f::Documenter.var"#61#62"{Module, Expr}, dir::String) @ Base.Filesystem ./file.jl:112 [5] (::Documenter.var"#59#60"{Documenter.Page, Module, Expr})() @ Documenter ~/.julia/packages/Documenter/AXNMp/src/expander_pipeline.jl:878 [6] (::IOCapture.var"#12#13"{Type{InterruptException}, Documenter.var"#59#60"{Documenter.Page, Module, Expr}, IOContext{Base.PipeEndpoint}, IOContext{Base.PipeEndpoint}, IOContext{Base.PipeEndpoint}, IOContext{Base.PipeEndpoint}})() @ IOCapture ~/.julia/packages/IOCapture/MR051/src/IOCapture.jl:170 [7] with_logstate(f::IOCapture.var"#12#13"{Type{InterruptException}, Documenter.var"#59#60"{Documenter.Page, Module, Expr}, IOContext{Base.PipeEndpoint}, IOContext{Base.PipeEndpoint}, IOContext{Base.PipeEndpoint}, IOContext{Base.PipeEndpoint}}, logstate::Base.CoreLogging.LogState) @ Base.CoreLogging ./logging/logging.jl:542 [8] with_logger(f::Function, logger::Base.CoreLogging.ConsoleLogger) @ Base.CoreLogging ./logging/logging.jl:653 [9] capture(f::Documenter.var"#59#60"{Documenter.Page, Module, Expr}; rethrow::Type, color::Bool, passthrough::Bool, capture_buffer::IOBuffer, io_context::Vector{Any}) @ IOCapture ~/.julia/packages/IOCapture/MR051/src/IOCapture.jl:167 [10] runner(::Type{Documenter.Expanders.ExampleBlocks}, node::MarkdownAST.Node{Nothing}, page::Documenter.Page, doc::Documenter.Document) @ Documenter ~/.julia/packages/Documenter/AXNMp/src/expander_pipeline.jl:877

failed to run `@setup` block in docs/src/tutorials/linear_symplectic_transformer.md:133-179 ```@setup lin_sympl_tran_tut const index = 1 init_con = (q = dl.input.q[:, 1:seq_length, index], p = dl.input.p[:, 1:seq_length, index]) # when we iterate with a feedforward neural network we only need a vector as input init_con_ff = (q = dl.input.q[:, 1, index], p = dl.input.p[:, 1, index]) const n_steps = 30 function make_validation_plot(n_steps = n_steps; theme = :dark) textcolor = theme == :dark ? :white : :black fig = Figure(; backgroundcolor = :transparent) ax = Axis(fig[1, 1]; backgroundcolor = :transparent, bottomspinecolor = textcolor, topspinecolor = textcolor, leftspinecolor = textcolor, rightspinecolor = textcolor, xtickcolor = textcolor, ytickcolor = textcolor, xticklabelcolor = textcolor, yticklabelcolor = textcolor, xlabel=L"t", ylabel=L"q_1", xlabelcolor = textcolor, ylabelcolor = textcolor, ) prediction_standard = iterate(nn_standard, init_con; n_points = n_steps, prediction_window = seq_length) prediction_symplectic = iterate(nn_symplectic, init_con; n_points = n_steps, prediction_window = seq_length) prediction_sympnet = iterate(nn_sympnet, init_con_ff; n_points = n_steps) # we use linewidth = 2 lines!(ax, dl.input.q[1, 1:n_steps, index]; color = mblue, label = "Implicit midpoint", linewidth = 2) lines!(ax, prediction_standard.q[1, :]; color = mpurple, label = "ST", linewidth = 2) lines!(ax, prediction_symplectic.q[1, :]; color = mred, label = "LST", linewidth = 2) lines!(ax, prediction_sympnet.q[1, :]; color = morange, label = "SympNet", linewidth = 2) axislegend(; position = (.55, .75), backgroundcolor = :transparent, labelcolor = textcolor) fig, ax end fig_light, ax_light = make_validation_plot(n_steps; theme = :light) fig_dark, ax_dark = make_validation_plot(n_steps; theme = :dark) save("lst_validation_light.png", fig_light; px_per_unit = 1.2) save("lst_validation_dark.png", fig_dark; px_per_unit = 1.2) nothing ``` exception = LoadError: UndefVarError: `dl` not defined in `Main.__atexample__named__lin_sympl_tran_tut` Suggestion: add an appropriate import or assignment. This global was declared but not assigned. in expression starting at string:2

failed to run `@setup` block in docs/src/tutorials/linear_symplectic_transformer.md:84-125 ```@setup lin_sympl_tran_tut morange = RGBf(255 / 256, 127 / 256, 14 / 256) # hide mred = RGBf(214 / 256, 39 / 256, 40 / 256) # hide mpurple = RGBf(148 / 256, 103 / 256, 189 / 256) # hide mblue = RGBf(31 / 256, 119 / 256, 180 / 256) # hide mgreen = RGBf(44 / 256, 160 / 256, 44 / 256) # hide function plot_training_losses(loss_array_standard, loss_array_symplectic, loss_array_sympnet; theme = :dark) textcolor = theme == :dark ? :white : :black fig = Figure(; backgroundcolor = :transparent) ax = Axis(fig[1, 1]; backgroundcolor = :transparent, bottomspinecolor = textcolor, topspinecolor = textcolor, leftspinecolor = textcolor, rightspinecolor = textcolor, xtickcolor = textcolor, ytickcolor = textcolor, xticklabelcolor = textcolor, yticklabelcolor = textcolor, xlabel="Epoch", ylabel="Training loss", xlabelcolor = textcolor, ylabelcolor = textcolor, yscale = log10 ) lines!(ax, loss_array_standard, color = mpurple, label = "ST") lines!(ax, loss_array_symplectic, color = mred, label = "LST") lines!(ax, loss_array_sympnet, color = morange, label = "SympNet") axislegend(; position = (.82, .75), backgroundcolor = :transparent, labelcolor = textcolor) fig, ax end fig_dark, ax_dark = plot_training_losses(loss_array_standard, loss_array_symplectic, loss_array_sympnet; theme = :dark) fig_light, ax_light = plot_training_losses(loss_array_standard, loss_array_symplectic, loss_array_sympnet; theme = :light) save("lst_dark.png", fig_dark; px_per_unit = 1.2) save("lst_light.png", fig_light; px_per_unit = 1.2) nothing ``` exception = LoadError: UndefVarError: `loss_array_standard` not defined in `Main.__atexample__named__lin_sympl_tran_tut` Suggestion: check for spelling errors or missing imports. in expression starting at string:34

failed to run `@example` block in docs/src/tutorials/linear_symplectic_transformer.md:47-80 ```@example lin_sympl_tran_tut const seq_length = 4 const batch_size = 1024 const n_epochs = 2000 arch_standard = StandardTransformerIntegrator(dl.input_dim; n_heads = 2, L = 1, n_blocks = 2) arch_symplectic = LinearSymplecticTransformer( dl.input_dim, seq_length; n_sympnet = 2, L = 1, upscaling_dimension = 2 * dl.input_dim) arch_sympnet = GSympNet(dl.input_dim; n_layers = 4, upscaling_dimension = 2 * dl.input_dim) nn_standard = NeuralNetwork(arch_standard) nn_symplectic = NeuralNetwork(arch_symplectic) nn_sympnet = NeuralNetwork(arch_sympnet) o_method = AdamOptimizerWithDecay(n_epochs, Float64) o_standard = Optimizer(o_method, nn_standard) o_symplectic = Optimizer(o_method, nn_symplectic) o_sympnet = Optimizer(o_method, nn_sympnet) batch = Batch(batch_size, seq_length) batch2 = Batch(batch_size) loss_array_standard = o_standard(nn_standard, dl, batch, n_epochs; show_progress = false) loss_array_symplectic = o_symplectic(nn_symplectic, dl, batch, n_epochs; show_progress = false) loss_array_sympnet = o_sympnet(nn_sympnet, dl, batch2, n_epochs; show_progress = false) nothing # hide ``` exception = UndefVarError: `dl` not defined in `Main.__atexample__named__lin_sympl_tran_tut` Suggestion: add an appropriate import or assignment. This global was declared but not assigned. Stacktrace: [1] top-level scope @ linear_symplectic_transformer.md:52 [2] eval(m::Module, e::Any) @ Core ./boot.jl:489 [3] #61 @ ~/.julia/packages/Documenter/AXNMp/src/expander_pipeline.jl:879 [inlined] [4] cd(f::Documenter.var"#61#62"{Module, Expr}, dir::String) @ Base.Filesystem ./file.jl:112 [5] (::Documenter.var"#59#60"{Documenter.Page, Module, Expr})() @ Documenter ~/.julia/packages/Documenter/AXNMp/src/expander_pipeline.jl:878 [6] (::IOCapture.var"#12#13"{Type{InterruptException}, Documenter.var"#59#60"{Documenter.Page, Module, Expr}, IOContext{Base.PipeEndpoint}, IOContext{Base.PipeEndpoint}, IOContext{Base.PipeEndpoint}, IOContext{Base.PipeEndpoint}})() @ IOCapture ~/.julia/packages/IOCapture/MR051/src/IOCapture.jl:170 [7] with_logstate(f::IOCapture.var"#12#13"{Type{InterruptException}, Documenter.var"#59#60"{Documenter.Page, Module, Expr}, IOContext{Base.PipeEndpoint}, IOContext{Base.PipeEndpoint}, IOContext{Base.PipeEndpoint}, IOContext{Base.PipeEndpoint}}, logstate::Base.CoreLogging.LogState) @ Base.CoreLogging ./logging/logging.jl:542 [8] with_logger(f::Function, logger::Base.CoreLogging.ConsoleLogger) @ Base.CoreLogging ./logging/logging.jl:653 [9] capture(f::Documenter.var"#59#60"{Documenter.Page, Module, Expr}; rethrow::Type, color::Bool, passthrough::Bool, capture_buffer::IOBuffer, io_context::Vector{Any}) @ IOCapture ~/.julia/packages/IOCapture/MR051/src/IOCapture.jl:167 [10] runner(::Type{Documenter.Expanders.ExampleBlocks}, node::MarkdownAST.Node{Nothing}, page::Documenter.Page, doc::Documenter.Document) @ Documenter ~/.julia/packages/Documenter/AXNMp/src/expander_pipeline.jl:877

failed to run `@example` block in docs/src/tutorials/linear_symplectic_transformer.md:24-43 ```@example lin_sympl_tran_tut using GeometricMachineLearning # hide using GeometricProblems.CoupledHarmonicOscillator: hodeensemble, default_parameters using GeometricIntegrators: ImplicitMidpoint, integrate # hide using LaTeXStrings # hide using CairoMakie # hide CairoMakie.activate!() # hide import Random # hide Random.seed!(123) # hide const timestep = .3 const n_init_con = 5 # ensemble problem ep = hodeensemble([rand(2) for _ in 1:n_init_con], [rand(2) for _ in 1:n_init_con]; timestep = timestep) dl = DataLoader(integrate(ep, ImplicitMidpoint()); suppress_info = true) # dl = DataLoader(vcat(dl_nt.input.q, dl_nt.input.p)) # hide nothing # hide ``` exception = MethodError: no method matching DataLoader(::GeometricSolutions.EnsembleSolution{Float64, Float64, Vector{GeometricSolutions.GeometricSolution{Float64, Float64, GeometricSolutions.TimeSeries{Float64, OffsetArrays.OffsetVector{Float64, StepRangeLen{Float64, Base.TwicePrecision{Float64}, Base.TwicePrecision{Float64}, Int64}}}, @NamedTuple{q::GeometricSolutions.DataSeries{Float64, GeometricBase.StateVariable{Float64, 1, Vector{Float64}, Tuple{Vector{Float64}, Vector{Float64}}, BitVector}}, p::GeometricSolutions.DataSeries{Float64, GeometricBase.StateVariable{Float64, 1, Vector{Float64}, Tuple{Vector{Float64}, Vector{Float64}}, BitVector}}}, GeometricEquations.HODEProblem{Float64, Float64, GeometricBase.StateVariable{Float64, 1, Vector{Float64}, Tuple{Vector{Float64}, Vector{Float64}}, BitVector}, GeometricEquations.HODE{RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :t, :Q, :P, :params), EulerLagrange.var"#_RGF_ModTag", EulerLagrange.var"#_RGF_ModTag", (0x817dbd6e, 0x2a2c99f6, 0x213621bd, 0xeb5e4e27, 0x4a71273d), Expr}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :t, :Q, :P, :params), EulerLagrange.var"#_RGF_ModTag", EulerLagrange.var"#_RGF_ModTag", (0x32d7601b, 0xde41fe41, 0x56d4143a, 0x8881cb11, 0xd017ff77), Expr}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :t, :Q, :P, :params), EulerLagrange.var"#_RGF_ModTag", EulerLagrange.var"#_RGF_ModTag", (0x817dbd6e, 0x2a2c99f6, 0x213621bd, 0xeb5e4e27, 0x4a71273d), Expr}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :t, :Q, :P, :params), EulerLagrange.var"#_RGF_ModTag", EulerLagrange.var"#_RGF_ModTag", (0x32d7601b, 0xde41fe41, 0x56d4143a, 0x8881cb11, 0xd017ff77), Expr}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:t, :Q, :P, :params), EulerLagrange.var"#_RGF_ModTag", EulerLagrange.var"#_RGF_ModTag", (0x3c20e916, 0xa49c2fd2, 0xe66e2ce0, 0x3130cd12, 0xb53eab21), Expr}, GeometricBase.NullInvariants, @NamedTuple{m₁::DataType, m₂::DataType, k₁::DataType, k₂::DataType, k::DataType}, GeometricBase.NullPeriodicity}, @NamedTuple{v::RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :t, :Q, :P, :params), EulerLagrange.var"#_RGF_ModTag", EulerLagrange.var"#_RGF_ModTag", (0x817dbd6e, 0x2a2c99f6, 0x213621bd, 0xeb5e4e27, 0x4a71273d), Expr}, f::RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :t, :Q, :P, :params), EulerLagrange.var"#_RGF_ModTag", EulerLagrange.var"#_RGF_ModTag", (0x32d7601b, 0xde41fe41, 0x56d4143a, 0x8881cb11, 0xd017ff77), Expr}, h::RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:t, :Q, :P, :params), EulerLagrange.var"#_RGF_ModTag", EulerLagrange.var"#_RGF_ModTag", (0x3c20e916, 0xa49c2fd2, 0xe66e2ce0, 0x3130cd12, 0xb53eab21), Expr}}, @NamedTuple{}, @NamedTuple{v::RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :t, :Q, :P, :params), EulerLagrange.var"#_RGF_ModTag", EulerLagrange.var"#_RGF_ModTag", (0x817dbd6e, 0x2a2c99f6, 0x213621bd, 0xeb5e4e27, 0x4a71273d), Expr}, f::RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :t, :Q, :P, :params), EulerLagrange.var"#_RGF_ModTag", EulerLagrange.var"#_RGF_ModTag", (0x32d7601b, 0xde41fe41, 0x56d4143a, 0x8881cb11, 0xd017ff77), Expr}}, @NamedTuple{q::GeometricBase.StateVariable{Float64, 1, Vector{Float64}, Tuple{Vector{Float64}, Vector{Fl

failed to run `@setup` block in docs/src/tutorials/adjusting_the_loss_function.md:86-126 ```@setup change_loss using CairoMakie function make_fig(; theme = :dark) # hide textcolor = theme == :dark ? :white : :black # hide fig = Figure(; backgroundcolor = :transparent) ax = Axis(fig[1, 1]; backgroundcolor = :transparent, bottomspinecolor = textcolor, topspinecolor = textcolor, leftspinecolor = textcolor, rightspinecolor = textcolor, xtickcolor = textcolor, ytickcolor = textcolor, xticklabelcolor = textcolor, yticklabelcolor = textcolor) init_con = [0.5 0.] n_time_steps = 100 prediction1 = zeros(2, n_time_steps + 1) prediction2 = zeros(2, n_time_steps + 1) prediction1[:, 1] = init_con prediction2[:, 1] = init_con for i in 2:(n_time_steps + 1) prediction1[:, i] = nn(prediction1[:, i - 1]) prediction2[:, i] = nn_custom(prediction2[:, i - 1]) end lines!(ax, data.input.q[:], data.input.p[:], label = rich("Training Data"; color = textcolor), linewidth = 3) lines!(ax, prediction1[1, :], prediction1[2, :], label = rich("FeedForwardLoss"; color = textcolor), linewidth = 3) lines!(ax, prediction2[1, :], prediction2[2, :], label = rich("CustomLoss"; color = textcolor), linewidth = 3) axislegend(; position = (.82, .75), backgroundcolor = :transparent) # hide fig end # hide # hide save("compare_losses_light.png", make_fig(; theme = :light); px_per_unit = 1.2) # hide save("compare_losses_dark.png", make_fig(; theme = :dark); px_per_unit = 1.2) # hide nothing ``` exception = LoadError: UndefVarError: `nn` not defined in `Main.__atexample__named__change_loss` Suggestion: check for spelling errors or missing imports. in expression starting at string:36

failed to run `@example` block in docs/src/tutorials/adjusting_the_loss_function.md:71-76 ```@example change_loss loss = CustomLoss() nn_custom = NeuralNetwork(GSympNet(2)) loss_array = o(nn_custom, data, batch, n_epochs, loss; show_progress = false) print(loss_array[end]) ``` exception = UndefVarError: `o` not defined in `Main.__atexample__named__change_loss` Suggestion: check for spelling errors or missing imports. Stacktrace: [1] top-level scope @ adjusting_the_loss_function.md:74 [2] eval(m::Module, e::Any) @ Core ./boot.jl:489 [3] #61 @ ~/.julia/packages/Documenter/AXNMp/src/expander_pipeline.jl:879 [inlined] [4] cd(f::Documenter.var"#61#62"{Module, Expr}, dir::String) @ Base.Filesystem ./file.jl:112 [5] (::Documenter.var"#59#60"{Documenter.Page, Module, Expr})() @ Documenter ~/.julia/packages/Documenter/AXNMp/src/expander_pipeline.jl:878 [6] (::IOCapture.var"#12#13"{Type{InterruptException}, Documenter.var"#59#60"{Documenter.Page, Module, Expr}, IOContext{Base.PipeEndpoint}, IOContext{Base.PipeEndpoint}, IOContext{Base.PipeEndpoint}, IOContext{Base.PipeEndpoint}})() @ IOCapture ~/.julia/packages/IOCapture/MR051/src/IOCapture.jl:170 [7] with_logstate(f::IOCapture.var"#12#13"{Type{InterruptException}, Documenter.var"#59#60"{Documenter.Page, Module, Expr}, IOContext{Base.PipeEndpoint}, IOContext{Base.PipeEndpoint}, IOContext{Base.PipeEndpoint}, IOContext{Base.PipeEndpoint}}, logstate::Base.CoreLogging.LogState) @ Base.CoreLogging ./logging/logging.jl:542 [8] with_logger(f::Function, logger::Base.CoreLogging.ConsoleLogger) @ Base.CoreLogging ./logging/logging.jl:653 [9] capture(f::Documenter.var"#59#60"{Documenter.Page, Module, Expr}; rethrow::Type, color::Bool, passthrough::Bool, capture_buffer::IOBuffer, io_context::Vector{Any}) @ IOCapture ~/.julia/packages/IOCapture/MR051/src/IOCapture.jl:167 [10] runner(::Type{Documenter.Expanders.ExampleBlocks}, node::MarkdownAST.Node{Nothing}, page::Documenter.Page, doc::Documenter.Document) @ Documenter ~/.julia/packages/Documenter/AXNMp/src/expander_pipeline.jl:877

failed to run `@example` block in docs/src/tutorials/adjusting_the_loss_function.md:39-50 ```@example change_loss using LinearAlgebra: norm # hide # norm of parameters for single layer network_parameter_norm(params::NamedTuple) = sum([norm(params[i]) for i in 1:length(params)]) # norm of parameters for entire network function network_parameter_norm(params::NeuralNetworkParameters) sum([network_parameter_norm(params[key]) for key in keys(params)]) end network_parameter_norm(params(nn)) ``` exception = UndefVarError: `nn` not defined in `Main.__atexample__named__change_loss` Suggestion: check for spelling errors or missing imports. Stacktrace: [1] top-level scope @ adjusting_the_loss_function.md:49 [2] eval(m::Module, e::Any) @ Core ./boot.jl:489 [3] #61 @ ~/.julia/packages/Documenter/AXNMp/src/expander_pipeline.jl:879 [inlined] [4] cd(f::Documenter.var"#61#62"{Module, Expr}, dir::String) @ Base.Filesystem ./file.jl:112 [5] (::Documenter.var"#59#60"{Documenter.Page, Module, Expr})() @ Documenter ~/.julia/packages/Documenter/AXNMp/src/expander_pipeline.jl:878 [6] (::IOCapture.var"#12#13"{Type{InterruptException}, Documenter.var"#59#60"{Documenter.Page, Module, Expr}, IOContext{Base.PipeEndpoint}, IOContext{Base.PipeEndpoint}, IOContext{Base.PipeEndpoint}, IOContext{Base.PipeEndpoint}})() @ IOCapture ~/.julia/packages/IOCapture/MR051/src/IOCapture.jl:170 [7] with_logstate(f::IOCapture.var"#12#13"{Type{InterruptException}, Documenter.var"#59#60"{Documenter.Page, Module, Expr}, IOContext{Base.PipeEndpoint}, IOContext{Base.PipeEndpoint}, IOContext{Base.PipeEndpoint}, IOContext{Base.PipeEndpoint}}, logstate::Base.CoreLogging.LogState) @ Base.CoreLogging ./logging/logging.jl:542 [8] with_logger(f::Function, logger::Base.CoreLogging.ConsoleLogger) @ Base.CoreLogging ./logging/logging.jl:653 [9] capture(f::Documenter.var"#59#60"{Documenter.Page, Module, Expr}; rethrow::Type, color::Bool, passthrough::Bool, capture_buffer::IOBuffer, io_context::Vector{Any}) @ IOCapture ~/.julia/packages/IOCapture/MR051/src/IOCapture.jl:167 [10] runner(::Type{Documenter.Expanders.ExampleBlocks}, node::MarkdownAST.Node{Nothing}, page::Documenter.Page, doc::Documenter.Document) @ Documenter ~/.julia/packages/Documenter/AXNMp/src/expander_pipeline.jl:877

failed to run `@example` block in docs/src/tutorials/adjusting_the_loss_function.md:15-35 ```@example change_loss using GeometricMachineLearning # hide using GeometricMachineLearning: params # hide using GeometricIntegrators: integrate, ImplicitMidpoint # hide using GeometricProblems.HarmonicOscillator: hodeproblem import Random # hide Random.seed!(123) # hide sol = integrate(hodeproblem(; timespan = 100), ImplicitMidpoint()) data = DataLoader(sol; suppress_info = true) nn = NeuralNetwork(GSympNet(2)) # train the network o = Optimizer(AdamOptimizer(), nn) batch = Batch(32) n_epochs = 30 loss = FeedForwardLoss() loss_array = o(nn, data, batch, n_epochs, loss; show_progress = false) print(loss_array[end]) ``` exception = MethodError: no method matching DataLoader(::GeometricSolutions.GeometricSolution{Float64, Float64, GeometricSolutions.TimeSeries{Float64, OffsetArrays.OffsetVector{Float64, StepRangeLen{Float64, Base.TwicePrecision{Float64}, Base.TwicePrecision{Float64}, Int64}}}, @NamedTuple{q::GeometricSolutions.DataSeries{Float64, GeometricBase.StateVariable{Float64, 1, Vector{Float64}, Tuple{Vector{Float64}, Vector{Float64}}, BitVector}}, p::GeometricSolutions.DataSeries{Float64, GeometricBase.StateVariable{Float64, 1, Vector{Float64}, Tuple{Vector{Float64}, Vector{Float64}}, BitVector}}}, GeometricEquations.HODEProblem{Float64, Float64, GeometricBase.StateVariable{Float64, 1, Vector{Float64}, Tuple{Vector{Float64}, Vector{Float64}}, BitVector}, GeometricEquations.HODE{typeof(GeometricProblems.HarmonicOscillator.oscillator_pode_v), typeof(GeometricProblems.HarmonicOscillator.oscillator_pode_f), typeof(GeometricProblems.HarmonicOscillator.oscillator_pode_v), typeof(GeometricProblems.HarmonicOscillator.oscillator_pode_f), typeof(GeometricProblems.HarmonicOscillator.hamiltonian), GeometricBase.NullInvariants, @NamedTuple{m::DataType, k::DataType, ω::DataType}, GeometricBase.NullPeriodicity}, @NamedTuple{v::typeof(GeometricProblems.HarmonicOscillator.oscillator_pode_v), f::typeof(GeometricProblems.HarmonicOscillator.oscillator_pode_f), h::typeof(GeometricProblems.HarmonicOscillator.hamiltonian)}, @NamedTuple{}, @NamedTuple{v::typeof(GeometricProblems.HarmonicOscillator.oscillator_pode_v), f::typeof(GeometricProblems.HarmonicOscillator.oscillator_pode_f)}, @NamedTuple{q::GeometricBase.StateVariable{Float64, 1, Vector{Float64}, Tuple{Vector{Float64}, Vector{Float64}}, BitVector}, p::GeometricBase.StateVariable{Float64, 1, Vector{Float64}, Tuple{Vector{Float64}, Vector{Float64}}, BitVector}}, @NamedTuple{m::Float64, k::Float64, ω::Float64}}, @NamedTuple{q::GeometricBase.NullPeriodicity, p::GeometricBase.NullPeriodicity}}; suppress_info::Bool) The type `DataLoader` exists, but no method is defined for this combination of argument types when trying to construct it. Closest candidates are: DataLoader(!Matched::GeometricSolutions.GeometricSolution{T, <:Number, NT}, !Matched::Any; kwargs...) where {T<:Number, DT<:(GeometricSolutions.DataSeries{T, AT} where AT<:Union{AbstractArray{T}, T}), NT<:Union{@NamedTuple{q::DT}, @NamedTuple{q::DT, p::DT}}} @ GeometricMachineLearning ~/work/GeometricMachineLearning.jl/GeometricMachineLearning.jl/src/data_loader/data_loader.jl:315 DataLoader(!Matched::GeometricSolutions.GeometricSolution{T, <:Number, NT}; ...) where {T<:Number, DT<:(GeometricSolutions.DataSeries{T, AT} where AT<:Union{AbstractArray{T}, T}), NT<:Union{@NamedTuple{q::DT}, @NamedTuple{q::DT, p::DT}}} @ GeometricMachineLearning ~/work/GeometricMachineLearning.jl/GeometricMachineLearning.jl/src/data_loader/data_loader.jl:315 DataLoader(!Matched::GeometricSolutions.EnsembleSolution{T, T1, Vector{ST}}; autoencoder, suppress_info) where {T, T1, DT<:(GeometricSolutions.DataSeries{T, AT} where AT<:Union{AbstractArray{T}, T}), ST<:(GeometricSolutions.GeometricSolution{T, T1, @NamedTuple{q::DT, p::DT}})} @ GeometricMachineLearning ~/work/GeometricMachineLearning.jl/GeometricMachineLearning.jl/src/data_loader/data_loader.jl:368 ... Stacktrace: [1] top