From 5397e9f14973157dc24e9c96688c7cfff94968ba Mon Sep 17 00:00:00 2001 From: Sathvik Bhagavan Date: Sun, 26 Nov 2023 02:25:04 +0000 Subject: [PATCH 1/5] build(docs): bump the compat of QMC --- docs/Project.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/Project.toml b/docs/Project.toml index b3c1ed2088..735d81e73f 100644 --- a/docs/Project.toml +++ b/docs/Project.toml @@ -35,6 +35,6 @@ OptimizationOptimisers = "0.1" OptimizationPolyalgorithms = "0.1" OrdinaryDiffEq = "6.31" Plots = "1.36" -QuasiMonteCarlo = "0.2" +QuasiMonteCarlo = "0.3" Roots = "2.0" SpecialFunctions = "2.1" From 8675bcb69f1feb19cbde050d30b5b995d6a5fc8a Mon Sep 17 00:00:00 2001 From: Sathvik Bhagavan Date: Tue, 28 Nov 2023 06:38:01 +0000 Subject: [PATCH 2/5] docs: add debugging for Documenter --- docs/make.jl | 1 + 1 file changed, 1 insertion(+) diff --git a/docs/make.jl b/docs/make.jl index 67ee53b3d4..09bc53388c 100644 --- a/docs/make.jl +++ b/docs/make.jl @@ -4,6 +4,7 @@ cp("./docs/Manifest.toml", "./docs/src/assets/Manifest.toml", force = true) cp("./docs/Project.toml", "./docs/src/assets/Project.toml", force = true) ENV["GKSwstype"] = "100" +ENV["JULIA_DEBUG"] = "Documenter" using Plots include("pages.jl") From e72def05d98365b4c158747ca1c60ece278da65c Mon Sep 17 00:00:00 2001 From: Sathvik Bhagavan Date: Mon, 11 Dec 2023 07:33:50 +0000 Subject: [PATCH 3/5] docs: use BackTracking in BFGS for linear parabolic example --- docs/Project.toml | 1 + docs/src/examples/linear_parabolic.md | 3 ++- 2 files changed, 3 insertions(+), 1 deletion(-) diff --git a/docs/Project.toml b/docs/Project.toml index 735d81e73f..b44ae23671 100644 --- a/docs/Project.toml +++ b/docs/Project.toml @@ -6,6 +6,7 @@ DomainSets = "5b8099bc-c8ec-5219-889f-1d9e522a28bf" Flux = "587475ba-b771-5e3f-ad9e-33799f191a9c" Integrals = "de52edbc-65ea-441a-8357-d3a637375a31" IntegralsCubature = "c31f79ba-6e32-46d4-a52f-182a8ac42a54" +LineSearches = "d3d80556-e9d4-5f37-9878-2ab0fcc64255" Lux = "b2108857-7c20-44ae-9111-449ecde12c47" ModelingToolkit = "961ee093-0014-501f-94e3-6117800e7a78" NeuralPDE = "315f7962-48a3-4962-8226-d0f33b1235f0" diff --git a/docs/src/examples/linear_parabolic.md b/docs/src/examples/linear_parabolic.md index 0ae1432763..c7434ec8be 100644 --- a/docs/src/examples/linear_parabolic.md +++ b/docs/src/examples/linear_parabolic.md @@ -27,6 +27,7 @@ with a physics-informed neural network. using NeuralPDE, Lux, ModelingToolkit, Optimization, OptimizationOptimJL using Plots import ModelingToolkit: Interval, infimum, supremum +using LineSearches @parameters t, x @variables u(..), w(..) @@ -92,7 +93,7 @@ callback = function (p, l) return false end -res = Optimization.solve(prob, BFGS(); callback = callback, maxiters = 5000) +res = Optimization.solve(prob, BFGS(linesearch = BackTracking()); callback = callback, maxiters = 5000) phi = discretization.phi From 7a73616b16cd3f024d6477748f79e30a8f5bacb5 Mon Sep 17 00:00:00 2001 From: Sathvik Bhagavan Date: Tue, 16 Jan 2024 13:05:04 +0000 Subject: [PATCH 4/5] fixup! docs: use BackTracking in BFGS for linear parabolic example --- docs/src/examples/linear_parabolic.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/src/examples/linear_parabolic.md b/docs/src/examples/linear_parabolic.md index c7434ec8be..fa5bb8b6d7 100644 --- a/docs/src/examples/linear_parabolic.md +++ b/docs/src/examples/linear_parabolic.md @@ -93,7 +93,7 @@ callback = function (p, l) return false end -res = Optimization.solve(prob, BFGS(linesearch = BackTracking()); callback = callback, maxiters = 5000) +res = Optimization.solve(prob, LBFGS(linesearch = BackTracking()); callback = callback, maxiters = 5000) phi = discretization.phi From df96f3dff4b996e5bd73103c6a7c43d79cff63e3 Mon Sep 17 00:00:00 2001 From: Sathvik Bhagavan Date: Tue, 16 Jan 2024 14:23:54 +0000 Subject: [PATCH 5/5] fixup! docs: use BackTracking in BFGS for linear parabolic example --- docs/src/examples/ks.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/src/examples/ks.md b/docs/src/examples/ks.md index bb2b1064f5..ae960b5c5b 100644 --- a/docs/src/examples/ks.md +++ b/docs/src/examples/ks.md @@ -27,7 +27,7 @@ where $\theta = t - x/2$ and with initial and boundary conditions: We use physics-informed neural networks. ```@example ks -using NeuralPDE, Lux, ModelingToolkit, Optimization, OptimizationOptimJL +using NeuralPDE, Lux, ModelingToolkit, Optimization, OptimizationOptimJL, LineSearches import ModelingToolkit: Interval, infimum, supremum @parameters x, t @@ -71,7 +71,7 @@ callback = function (p, l) return false end -opt = OptimizationOptimJL.BFGS() +opt = OptimizationOptimJL.LBFGS(linesearch = BackTracking()) res = Optimization.solve(prob, opt; callback = callback, maxiters = 2000) phi = discretization.phi ```