Optimization.jl icon indicating copy to clipboard operation
Optimization.jl copied to clipboard

Published 20 hours ago • verified publisher icon SciML

NamedTuple parameters don't work with AutoModelingToolkit()

Open ElOceanografo opened this issue 1 year ago • 3 comments

I defined an OptimizationFunction and OptimizationProblem which expect the parameters as a named tuple (which is convenient when there are a bunch of parameters, since they can be referred to by name inside the function). The following MWE, using AutoModelingForwardDiff(), works fine:

using Optimization, OptimizationOptimJL, ModelingToolkit, ForwardDiff
ftest(u, params) = sum(abs2, params.y .- u' * params.M * u)
p = (;y = randn(5), M = randn(5, 5))
u0 = randn(5)
f = OptimizationFunction(ftest, Optimization.AutoForwardDiff())
prob = OptimizationProblem(f, u0, p)
sol = solve(prob, LBFGS())

but if I change it to use AutoModelingToolkit(), attempting to solve the problem gives the following error:

f = OptimizationFunction(ftest, Optimization.AutoModelingToolkit())
prob = OptimizationProblem(f, u0, p)
sol = solve(prob, LBFGS())

ERROR: type Array has no field y
Stacktrace:
  [1] getproperty
    @ .\Base.jl:42 [inlined]
  [2] ftest(u::Vector{Num}, params::Vector{Num})
    @ Main .\REPL[43]:1
  [3] (::OptimizationFunction{true, Optimization.AutoModelingToolkit, typeof(ftest), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing})(::Vector{Num}, ::Vararg{Vector{Num}})
    @ SciMLBase C:\Users\sam.urmy\.julia\packages\SciMLBase\2oQlD\src\scimlfunctions.jl:3261
  [4] modelingtoolkitize(prob::OptimizationProblem{true, OptimizationFunction{true, Optimization.AutoModelingToolkit, typeof(ftest), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, Vector{Float64}, NamedTuple{(:y, :M), Tuple{Vector{Float64}, Matrix{Float64}}}, Nothing, Nothing, Nothing, Nothing, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}}; kwargs::Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})  
    @ ModelingToolkit C:\Users\sam.urmy\.julia\packages\ModelingToolkit\YHIP8\src\systems\diffeqs\modelingtoolkitize.jl:235
  [5] modelingtoolkitize(prob::OptimizationProblem{true, OptimizationFunction{true, Optimization.AutoModelingToolkit, typeof(ftest), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, Vector{Float64}, NamedTuple{(:y, :M), Tuple{Vector{Float64}, Matrix{Float64}}}, Nothing, Nothing, Nothing, Nothing, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}})
    @ ModelingToolkit C:\Users\sam.urmy\.julia\packages\ModelingToolkit\YHIP8\src\systems\diffeqs\modelingtoolkitize.jl:225
  [6] instantiate_function(f::Function, x::Vector{Float64}, adtype::Optimization.AutoModelingToolkit, p::NamedTuple{(:y, :M), Tuple{Vector{Float64}, Matrix{Float64}}}, num_cons::Int64)
    @ Optimization C:\Users\sam.urmy\.julia\packages\Optimization\6nIwk\src\function\mtk.jl:10
  [7] instantiate_function(f::Function, x::Vector{Float64}, adtype::Optimization.AutoModelingToolkit, p::NamedTuple{(:y, :M), Tuple{Vector{Float64}, Matrix{Float64}}})
    @ Optimization C:\Users\sam.urmy\.julia\packages\Optimization\6nIwk\src\function\mtk.jl:9
  [8] ___solve(prob::OptimizationProblem{true, OptimizationFunction{true, Optimization.AutoModelingToolkit, typeof(ftest), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, Vector{Float64}, NamedTuple{(:y, :M), Tuple{Vector{Float64}, Matrix{Float64}}}, Nothing, Nothing, Nothing, Nothing, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}}, opt::Newton{LineSearches.InitialStatic{Float64}, LineSearches.HagerZhang{Float64, 
Base.RefValue{Bool}}}, data::Base.Iterators.Cycle{Tuple{Optimization.NullData}}; callback::Function, maxiters::Nothing, maxtime::Nothing, abstol::Nothing, reltol::Nothing, progress::Bool, kwargs::Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
    @ OptimizationOptimJL C:\Users\sam.urmy\.julia\packages\OptimizationOptimJL\fdrJg\src\OptimizationOptimJL.jl:94
  [9] ___solve(prob::OptimizationProblem{true, OptimizationFunction{true, Optimization.AutoModelingToolkit, typeof(ftest), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, Vector{Float64}, NamedTuple{(:y, :M), Tuple{Vector{Float64}, Matrix{Float64}}}, Nothing, Nothing, Nothing, Nothing, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}}, opt::Newton{LineSearches.InitialStatic{Float64}, LineSearches.HagerZhang{Float64, 
Base.RefValue{Bool}}}, data::Base.Iterators.Cycle{Tuple{Optimization.NullData}})
    @ OptimizationOptimJL C:\Users\sam.urmy\.julia\packages\OptimizationOptimJL\fdrJg\src\OptimizationOptimJL.jl:69
 [10] __solve(prob::OptimizationProblem{true, OptimizationFunction{true, Optimization.AutoModelingToolkit, typeof(ftest), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, Vector{Float64}, NamedTuple{(:y, :M), Tuple{Vector{Float64}, Matrix{Float64}}}, Nothing, Nothing, Nothing, Nothing, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}}, opt::Newton{LineSearches.InitialStatic{Float64}, LineSearches.HagerZhang{Float64, Base.RefValue{Bool}}}, data::Base.Iterators.Cycle{Tuple{Optimization.NullData}}; kwargs::Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
    @ OptimizationOptimJL C:\Users\sam.urmy\.julia\packages\OptimizationOptimJL\fdrJg\src\OptimizationOptimJL.jl:56
 [11] __solve(prob::OptimizationProblem{true, OptimizationFunction{true, Optimization.AutoModelingToolkit, typeof(ftest), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, Vector{Float64}, NamedTuple{(:y, :M), Tuple{Vector{Float64}, Matrix{Float64}}}, Nothing, Nothing, Nothing, Nothing, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}}, opt::Newton{LineSearches.InitialStatic{Float64}, LineSearches.HagerZhang{Float64, Base.RefValue{Bool}}}, data::Base.Iterators.Cycle{Tuple{Optimization.NullData}}) (repeats 2 times)
    @ OptimizationOptimJL C:\Users\sam.urmy\.julia\packages\OptimizationOptimJL\fdrJg\src\OptimizationOptimJL.jl:44
 [12] solve(::OptimizationProblem{true, OptimizationFunction{true, Optimization.AutoModelingToolkit, typeof(ftest), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, Vector{Float64}, NamedTuple{(:y, :M), Tuple{Vector{Float64}, Matrix{Float64}}}, Nothing, Nothing, Nothing, Nothing, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}}, ::Newton{LineSearches.InitialStatic{Float64}, LineSearches.HagerZhang{Float64, Base.RefValue{Bool}}}; kwargs::Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
    @ SciMLBase C:\Users\sam.urmy\.julia\packages\SciMLBase\2oQlD\src\solve.jl:71
 [13] solve(::OptimizationProblem{true, OptimizationFunction{true, Optimization.AutoModelingToolkit, typeof(ftest), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, Vector{Float64}, NamedTuple{(:y, :M), Tuple{Vector{Float64}, Matrix{Float64}}}, Nothing, Nothing, Nothing, Nothing, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}}, ::Newton{LineSearches.InitialStatic{Float64}, LineSearches.HagerZhang{Float64, Base.RefValue{Bool}}})
    @ SciMLBase C:\Users\sam.urmy\.julia\packages\SciMLBase\2oQlD\src\solve.jl:71
 [14] top-level scope
    @ REPL[50]:1

It looks like the modeling-toolkitized OptimizationFunction is calling ftest with a vector of parameters instead of a NamedTuple. is this a bug?

ElOceanografo avatar Sep 20 '22 22:09 ElOceanografo

It is indeed a bug,modelingtoolkitize called when AutoModelingToolkit is used, creates a new vector for the parameters and the names of the parameters are lost. For now you can rewrite ftest as ftest(u, params) = sum(abs2, params[1] .- u' * params[2] * u) and it should work.

Vaibhavdixit02 avatar Sep 21 '22 06:09 Vaibhavdixit02

Ok thanks, good to know. The workaround does not work either, however...defining ftest as you suggest produces this error when calling solve:

ERROR: DimensionMismatch("dimensions must match: a has dims (Base.OneTo(5), Base.OneTo(5)), must have singleton at dim 2")
Stacktrace:
  [1] promote_shape
    @ .\indices.jl:183 [inlined]
  [2] promote_shape
    @ .\indices.jl:174 [inlined]
  [3] promote_shape(a::Vector{Float64}, b::Matrix{Float64})
    @ Base .\indices.jl:169
  [4] +(A::Vector{Float64}, Bs::Matrix{Float64})
    @ Base .\arraymath.jl:45
  [5] macro expansion
    @ C:\Users\sam.urmy\.julia\packages\SymbolicUtils\vnuIf\src\code.jl:394 [inlined]
  [6] macro expansion
    @ C:\Users\sam.urmy\.julia\packages\Symbolics\9psaj\src\build_function.jl:504 [inlined]
  [7] macro expansion
    @ C:\Users\sam.urmy\.julia\packages\SymbolicUtils\vnuIf\src\code.jl:351 [inlined]
  [8] macro expansion
    @ C:\Users\sam.urmy\.julia\packages\RuntimeGeneratedFunctions\KrkGo\src\RuntimeGeneratedFunctions.jl:129 [inlined]
  [9] macro expansion
    @ .\none:0 [inlined]
 [10] generated_callfunc
    @ .\none:0 [inlined]
 [11] (::RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :ˍ₋arg1, :ˍ₋arg2), Symbolics.var"#_RGF_ModTag", Symbolics.var"#_RGF_ModTag", (0x5ebc1601, 0xf66d7688, 0x616faa43, 0xc9fdb05a, 0x91c11a17)})(::Vector{Float64}, ::Vector{Float64}, ::NamedTuple{(:y, :M), Tuple{Vector{Float64}, Matrix{Float64}}})
    @ RuntimeGeneratedFunctions C:\Users\sam.urmy\.julia\packages\RuntimeGeneratedFunctions\KrkGo\src\RuntimeGeneratedFunctions.jl:117
 [12] (::Optimization.var"#grad#106"{NamedTuple{(:y, :M), Tuple{Vector{Float64}, Matrix{Float64}}}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :ˍ₋arg1, :ˍ₋arg2), Symbolics.var"#_RGF_ModTag", Symbolics.var"#_RGF_ModTag", (0x5ebc1601, 0xf66d7688, 0x616faa43, 0xc9fdb05a, 0x91c11a17)}})(J::Vector{Float64}, u::Vector{Float64})
    @ Optimization C:\Users\sam.urmy\.julia\packages\Optimization\i9NGR\src\function\mtk.jl:16
 [13] (::OptimizationOptimJL.var"#5#13"{OptimizationProblem{true, OptimizationFunction{true, Optimization.AutoModelingToolkit, typeof(ftest), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, Vector{Float64}, NamedTuple{(:y, :M), Tuple{Vector{Float64}, Matrix{Float64}}}, Nothing, Nothing, Nothing, Nothing, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}}, OptimizationOptimJL.var"#4#12"{OptimizationProblem{true, OptimizationFunction{true, Optimization.AutoModelingToolkit, typeof(ftest), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, Vector{Float64}, NamedTuple{(:y, :M), Tuple{Vector{Float64}, Matrix{Float64}}}, Nothing, Nothing, Nothing, Nothing, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}}, OptimizationFunction{true, Optimization.AutoModelingToolkit, typeof(ftest), Optimization.var"#grad#106"{NamedTuple{(:y, :M), Tuple{Vector{Float64}, Matrix{Float64}}}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :ˍ₋arg1, :ˍ₋arg2), Symbolics.var"#_RGF_ModTag", Symbolics.var"#_RGF_ModTag", (0x5ebc1601, 0xf66d7688, 0x616faa43, 0xc9fdb05a, 0x91c11a17)}}, Optimization.var"#hess#107"{NamedTuple{(:y, :M), Tuple{Vector{Float64}, Matrix{Float64}}}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :ˍ₋arg1, :ˍ₋arg2), Symbolics.var"#_RGF_ModTag", Symbolics.var"#_RGF_ModTag", (0xc01061cf, 0xd949a7ab, 0xc58284e0, 0x80ec5617, 0x3f698c48)}}, Optimization.var"#97#108"{Optimization.AutoModelingToolkit}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Expr, Nothing}}, OptimizationFunction{true, Optimization.AutoModelingToolkit, typeof(ftest), Optimization.var"#grad#106"{NamedTuple{(:y, :M), Tuple{Vector{Float64}, Matrix{Float64}}}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :ˍ₋arg1, :ˍ₋arg2), Symbolics.var"#_RGF_ModTag", Symbolics.var"#_RGF_ModTag", (0x5ebc1601, 0xf66d7688, 0x616faa43, 0xc9fdb05a, 0x91c11a17)}}, Optimization.var"#hess#107"{NamedTuple{(:y, :M), Tuple{Vector{Float64}, Matrix{Float64}}}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :ˍ₋arg1, :ˍ₋arg2), Symbolics.var"#_RGF_ModTag", Symbolics.var"#_RGF_ModTag", (0xc01061cf, 0xd949a7ab, 0xc58284e0, 0x80ec5617, 0x3f698c48)}}, Optimization.var"#97#108"{Optimization.AutoModelingToolkit}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Expr, Nothing}})(G::Vector{Float64}, θ::Vector{Float64})
    @ OptimizationOptimJL C:\Users\sam.urmy\.julia\packages\OptimizationOptimJL\fdrJg\src\OptimizationOptimJL.jl:106
 [14] value_gradient!!(obj::TwiceDifferentiable{Float64, Vector{Float64}, Matrix{Float64}, Vector{Float64}}, x::Vector{Float64})
    @ NLSolversBase C:\Users\sam.urmy\.julia\packages\NLSolversBase\cfJrN\src\interface.jl:82
 [15] initial_state(method::LBFGS{Nothing, LineSearches.InitialStatic{Float64}, LineSearches.HagerZhang{Float64, Base.RefValue{Bool}}, Optim.var"#19#21"}, options::Optim.Options{Float64, OptimizationOptimJL.var"#_cb#11"{OptimizationOptimJL.var"#9#17", LBFGS{Nothing, LineSearches.InitialStatic{Float64}, LineSearches.HagerZhang{Float64, Base.RefValue{Bool}}, Optim.var"#19#21"}, Base.Iterators.Cycle{Tuple{Optimization.NullData}}}}, d::TwiceDifferentiable{Float64, Vector{Float64}, Matrix{Float64}, Vector{Float64}}, initial_x::Vector{Float64})
    @ Optim C:\Users\sam.urmy\.julia\packages\Optim\6Lpjy\src\multivariate\solvers\first_order\l_bfgs.jl:164
 [16] optimize(d::TwiceDifferentiable{Float64, Vector{Float64}, Matrix{Float64}, Vector{Float64}}, initial_x::Vector{Float64}, method::LBFGS{Nothing, LineSearches.InitialStatic{Float64}, LineSearches.HagerZhang{Float64, Base.RefValue{Bool}}, Optim.var"#19#21"}, options::Optim.Options{Float64, OptimizationOptimJL.var"#_cb#11"{OptimizationOptimJL.var"#9#17", LBFGS{Nothing, LineSearches.InitialStatic{Float64}, LineSearches.HagerZhang{Float64, Base.RefValue{Bool}}, Optim.var"#19#21"}, Base.Iterators.Cycle{Tuple{Optimization.NullData}}}})
    @ Optim C:\Users\sam.urmy\.julia\packages\Optim\6Lpjy\src\multivariate\optimize\optimize.jl:36
 [17] ___solve(prob::OptimizationProblem{true, OptimizationFunction{true, Optimization.AutoModelingToolkit, typeof(ftest), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, Vector{Float64}, NamedTuple{(:y, :M), Tuple{Vector{Float64}, Matrix{Float64}}}, Nothing, Nothing, Nothing, Nothing, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}}, opt::LBFGS{Nothing, LineSearches.InitialStatic{Float64}, LineSearches.HagerZhang{Float64, Base.RefValue{Bool}}, Optim.var"#19#21"}, data::Base.Iterators.Cycle{Tuple{Optimization.NullData}}; callback::Function, maxiters::Nothing, maxtime::Nothing, abstol::Nothing, reltol::Nothing, progress::Bool, kwargs::Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
    @ OptimizationOptimJL C:\Users\sam.urmy\.julia\packages\OptimizationOptimJL\fdrJg\src\OptimizationOptimJL.jl:143
 [18] ___solve
    @ C:\Users\sam.urmy\.julia\packages\OptimizationOptimJL\fdrJg\src\OptimizationOptimJL.jl:69 [inlined]
 [19] #__solve#2
    @ C:\Users\sam.urmy\.julia\packages\OptimizationOptimJL\fdrJg\src\OptimizationOptimJL.jl:56 [inlined]
 [20] __solve (repeats 2 times)
    @ C:\Users\sam.urmy\.julia\packages\OptimizationOptimJL\fdrJg\src\OptimizationOptimJL.jl:44 [inlined]
 [21] #solve#492
    @ C:\Users\sam.urmy\.julia\packages\SciMLBase\IJbT7\src\solve.jl:71 [inlined]
 [22] solve(::OptimizationProblem{true, OptimizationFunction{true, Optimization.AutoModelingToolkit, typeof(ftest), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, Vector{Float64}, NamedTuple{(:y, :M), Tuple{Vector{Float64}, Matrix{Float64}}}, Nothing, Nothing, Nothing, Nothing, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}}, ::LBFGS{Nothing, LineSearches.InitialStatic{Float64}, LineSearches.HagerZhang{Float64, Base.RefValue{Bool}}, Optim.var"#19#21"})
    @ SciMLBase C:\Users\sam.urmy\.julia\packages\SciMLBase\IJbT7\src\solve.jl:71
 [23] top-level scope
    @ REPL[14]:1

ElOceanografo avatar Sep 22 '22 14:09 ElOceanografo

Oh yeah, looks like MTK has trouble with vector/matrix parameters. So as temporary workaround you can avoid passing p to OptimizationProblem and rewrite ftest as ftest(u, params) = sum(abs2, p[1] .- u' * p[2] * u) using the global p and it should work

julia> f = OptimizationFunction(ftest, Optimization.AutoModelingToolkit())
(::OptimizationFunction{true, Optimization.AutoModelingToolkit, typeof(ftest), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}) (generic function with 1 method)

julia> prob = OptimizationProblem(f, u0, nothing)
OptimizationProblem. In-place: true
u0: 5-element Vector{Float64}:
 -0.43014445861378714
  0.43665425553480663
 -0.18704907297838141
  0.24850382091203801
 -2.277854186675249

julia> sol = solve(prob, LBFGS())
u: 5-element Vector{Float64}:
 -0.6086522984631275
  0.6079328096708877
 -0.5578515167049973
  0.2941979554692975
 -1.9204538047235244

julia> f = OptimizationFunction(ftest, Optimization.AutoForwardDiff())
(::OptimizationFunction{true, Optimization.AutoForwardDiff{nothing}, typeof(ftest), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}) (generic function with 1 method)

julia> prob = OptimizationProblem(f, u0, nothing)
OptimizationProblem. In-place: true
u0: 5-element Vector{Float64}:
 -0.43014445861378714
  0.43665425553480663
 -0.18704907297838141
  0.24850382091203801
 -2.277854186675249

julia> sol = solve(prob, LBFGS())
u: 5-element Vector{Float64}:
 -0.6086522984631274
  0.6079328096708878
 -0.5578515167049976
  0.2941979554692975
 -1.9204538047235242

Vaibhavdixit02 avatar Sep 23 '22 07:09 Vaibhavdixit02