Merge branch 'master' into pino_ode

SciML · Apr 8, 2024 · 8a98880 · 8a98880
2 parents 1e38676 + 6a555d5
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diff --git a/.buildkite/pipeline.yml b/.buildkite/pipeline.yml
@@ -16,32 +16,6 @@ steps:
     # Don't run Buildkite if the commit message includes the text [skip tests]
     if: build.message !~ /\[skip tests\]/
 
-  - label: "{{matrix.group}} v{{matrix.version}}"
-    matrix:
-      setup:
-        version:
-          - "1"
-        group:
-          - "NNODE"
-          - "NeuralAdapter"
-          - "IntegroDiff"
-          - "PINO_GPU"
-    env:
-      BUILDKITE_PLUGIN_JULIA_VERSION: "{{matrix.version}}"
-      GROUP: "{{matrix.group}}"
-    plugins:
-      - JuliaCI/julia#v1
-      - JuliaCI/julia-test#v1:
-          coverage: false
-          julia_args: "--threads=auto"
-    agents:
-      os: "linux"
-      queue: "juliaecosystem"
-      arch: "x86_64"
-    timeout_in_minutes: 680
-    # Don't run Buildkite if the commit message includes the text [skip tests]
-    if: build.message !~ /\[skip tests\]/
-
   - label: "Documentation"
     plugins:
       - JuliaCI/julia#v1:

diff --git a/.github/workflows/CI.yml b/.github/workflows/CI.yml
@@ -27,11 +27,14 @@ jobs:
           - Forward
           - DGM
           - ODEPINO
+          - NNODE
+          - NeuralAdapter
+          - IntegroDiff
         version:
           - "1"
     steps:
       - uses: actions/checkout@v4
-      - uses: julia-actions/setup-julia@v1
+      - uses: julia-actions/setup-julia@v2
         with:
           version: ${{ matrix.version }}
       - uses: actions/cache@v4

diff --git a/.github/workflows/Downgrade.yml b/.github/workflows/Downgrade.yml
@@ -26,11 +26,14 @@ jobs:
           - Logging
           - Forward
           - DGM
+          - NNODE
+          - NeuralAdapter
+          - IntegroDiff
         version:
           - "1"
     steps:
       - uses: actions/checkout@v4
-      - uses: julia-actions/setup-julia@v1
+      - uses: julia-actions/setup-julia@v2
         with:
           version: ${{ matrix.version }}
       - uses: actions/cache@v4

diff --git a/.github/workflows/Downstream.yml b/.github/workflows/Downstream.yml
@@ -20,7 +20,7 @@ jobs:
           - {user: SciML, repo: PDESystemLibrary.jl, group: NeuralPDE}
     steps:
       - uses: actions/checkout@v4
-      - uses: julia-actions/setup-julia@v1
+      - uses: julia-actions/setup-julia@v2
         with:
           version: ${{ matrix.julia-version }}
           arch: x64

diff --git a/.github/workflows/Invalidations.yml b/.github/workflows/Invalidations.yml
@@ -16,7 +16,7 @@ jobs:
     if: github.base_ref == github.event.repository.default_branch
     runs-on: ubuntu-latest
     steps:
-      - uses: julia-actions/setup-julia@v1
+      - uses: julia-actions/setup-julia@v2
         with:
           version: "1"
       - uses: actions/checkout@v4

diff --git a/Project.toml b/Project.toml
@@ -1,7 +1,7 @@
 name = "NeuralPDE"
 uuid = "315f7962-48a3-4962-8226-d0f33b1235f0"
 authors = ["Chris Rackauckas <[email protected]>"]
-version = "5.14.0"
+version = "5.16.0"
 
 [deps]
 Adapt = "79e6a3ab-5dfb-504d-930d-738a2a938a0e"
@@ -10,7 +10,6 @@ ArrayInterface = "4fba245c-0d91-5ea0-9b3e-6abc04ee57a9"
 ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
 ComponentArrays = "b0b7db55-cfe3-40fc-9ded-d10e2dbeff66"
 Cubature = "667455a9-e2ce-5579-9412-b964f529a492"
-DiffEqBase = "2b5f629d-d688-5b77-993f-72d75c75574e"
 DiffEqNoiseProcess = "77a26b50-5914-5dd7-bc55-306e6241c503"
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 DocStringExtensions = "ffbed154-4ef7-542d-bbb7-c09d3a79fcae"
@@ -42,47 +41,46 @@ Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
 Adapt = "4"
 AdvancedHMC = "0.6.1"
 Aqua = "0.8"
-ArrayInterface = "7.7"
+ArrayInterface = "7.9"
 CUDA = "5.2"
-ChainRulesCore = "1.18"
+ChainRulesCore = "1.21"
 ComponentArrays = "0.15.8"
 Cubature = "1.5"
-DiffEqBase = "6.144"
 DiffEqNoiseProcess = "5.20"
 Distributions = "0.25.107"
 DocStringExtensions = "0.9"
 DomainSets = "0.6, 0.7"
 Flux = "0.14.11"
 ForwardDiff = "0.10.36"
 Functors = "0.4.4"
-Integrals = "4"
+Integrals = "4.4"
 LineSearches = "7.2"
 LinearAlgebra = "1"
 LogDensityProblems = "2"
-Lux = "0.5.14"
+Lux = "0.5.22"
 LuxCUDA = "0.3.2"
 MCMCChains = "6"
-MethodOfLines = "0.10.7"
-ModelingToolkit = "8.75"
+MethodOfLines = "0.11"
+ModelingToolkit = "9.9"
 MonteCarloMeasurements = "1.1"
 Optim = "1.7.8"
-Optimization = "3.22"
+Optimization = "3.24"
 OptimizationOptimJL = "0.2.1"
 OptimizationOptimisers = "0.2.1"
-OrdinaryDiffEq = "6.70"
+OrdinaryDiffEq = "6.74"
 Pkg = "1"
 QuasiMonteCarlo = "0.3.2"
 Random = "1"
 Reexport = "1.2"
-RuntimeGeneratedFunctions = "0.5.11"
+RuntimeGeneratedFunctions = "0.5.12"
 SafeTestsets = "0.1"
-SciMLBase = "2.24"
+SciMLBase = "2.28"
 Statistics = "1.10"
-SymbolicUtils = "1.4"
-Symbolics = "5.17"
+SymbolicUtils = "1.5"
+Symbolics = "5.27.1"
 Test = "1"
 UnPack = "1"
-Zygote = "0.6.68"
+Zygote = "0.6.69"
 julia = "1.10"
 
 [extras]
@@ -91,12 +89,12 @@ CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
 Flux = "587475ba-b771-5e3f-ad9e-33799f191a9c"
 LineSearches = "d3d80556-e9d4-5f37-9878-2ab0fcc64255"
 LuxCUDA = "d0bbae9a-e099-4d5b-a835-1c6931763bda"
+MethodOfLines = "94925ecb-adb7-4558-8ed8-f975c56a0bf4"
 OptimizationOptimJL = "36348300-93cb-4f02-beb5-3c3902f8871e"
 OrdinaryDiffEq = "1dea7af3-3e70-54e6-95c3-0bf5283fa5ed"
 Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
 SafeTestsets = "1bc83da4-3b8d-516f-aca4-4fe02f6d838f"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
-MethodOfLines = "94925ecb-adb7-4558-8ed8-f975c56a0bf4"
 
 [targets]
 test = ["Aqua", "Test", "CUDA", "SafeTestsets", "OptimizationOptimJL", "Pkg", "OrdinaryDiffEq", "LineSearches", "LuxCUDA", "Flux", "MethodOfLines"]
diff --git a/README.md b/README.md
@@ -93,9 +93,9 @@ xs, ys = [infimum(d.domain):(dx / 10):supremum(d.domain) for d in domains]
 analytic_sol_func(x, y) = (sin(pi * x) * sin(pi * y)) / (2pi^2)
 
 u_predict = reshape([first(phi([x, y], res.minimizer)) for x in xs for y in ys],
-                    (length(xs), length(ys)))
+    (length(xs), length(ys)))
 u_real = reshape([analytic_sol_func(x, y) for x in xs for y in ys],
-                 (length(xs), length(ys)))
+    (length(xs), length(ys)))
 diff_u = abs.(u_predict .- u_real)
 
 using Plots

diff --git a/docs/Project.toml b/docs/Project.toml
@@ -28,29 +28,29 @@ Roots = "f2b01f46-fcfa-551c-844a-d8ac1e96c665"
 SpecialFunctions = "276daf66-3868-5448-9aa4-cd146d93841b"
 
 [compat]
-AdvancedHMC = "0.6"
-ComponentArrays = "0.15"
+AdvancedHMC = "0.6.1"
+ComponentArrays = "0.15.8"
 Cubature = "1.5"
-DiffEqBase = "6.106"
-Distributions = "0.25"
+DiffEqBase = "6.148"
+Distributions = "0.25.107"
 Documenter = "1"
 DomainSets = "0.6, 0.7"
-Flux = "0.14"
+Flux = "0.14.11"
 Integrals = "4"
 LineSearches = "7.2"
-Lux = "0.5"
-LuxCUDA = "0.3"
-MethodOfLines = "0.10"
-ModelingToolkit = "8.33"
+Lux = "0.5.22"
+LuxCUDA = "0.3.2"
+MethodOfLines = "0.11"
+ModelingToolkit = "9.7"
 MonteCarloMeasurements = "1"
-NeuralPDE = "5.3"
-Optimization = "3.9"
-OptimizationOptimJL = "0.2"
-OptimizationOptimisers = "0.2"
+NeuralPDE = "5.14"
+Optimization = "3.24"
+OptimizationOptimJL = "0.2.1"
+OptimizationOptimisers = "0.2.1"
 OptimizationPolyalgorithms = "0.2"
-OrdinaryDiffEq = "6.31"
+OrdinaryDiffEq = "6.74"
 Plots = "1.36"
-QuasiMonteCarlo = "0.3"
+QuasiMonteCarlo = "0.3.2"
 Random = "1"
 Roots = "2.0"
 SpecialFunctions = "2.1"
diff --git a/docs/make.jl b/docs/make.jl
@@ -10,13 +10,13 @@ using Plots
 include("pages.jl")
 
 makedocs(sitename = "NeuralPDE.jl",
-         authors = "#",
-         modules = [NeuralPDE],
-         clean = true, doctest = false, linkcheck = true,
-         warnonly = [:missing_docs, :example_block],
-         format = Documenter.HTML(assets = ["assets/favicon.ico"],
-                                  canonical = "https://docs.sciml.ai/NeuralPDE/stable/"),
-         pages = pages)
+    authors = "#",
+    modules = [NeuralPDE],
+    clean = true, doctest = false, linkcheck = true,
+    warnonly = [:missing_docs],
+    format = Documenter.HTML(assets = ["assets/favicon.ico"],
+        canonical = "https://docs.sciml.ai/NeuralPDE/stable/"),
+    pages = pages)
 
 deploydocs(repo = "github.com/SciML/NeuralPDE.jl.git";
-           push_preview = true)
+    push_preview = true)
diff --git a/docs/pages.jl b/docs/pages.jl
@@ -1,36 +1,37 @@
 pages = ["index.md",
     "ODE PINN Tutorials" => Any["Introduction to NeuralPDE for ODEs" => "tutorials/ode.md",
-                                "Bayesian PINNs for Coupled ODEs" => "tutorials/Lotka_Volterra_BPINNs.md",
-                                "PINNs DAEs" => "tutorials/dae.md",
-                                "Parameter Estimation with PINNs for ODEs" => "tutorials/ode_parameter_estimation.md",
-                                "Physics informed Neural Operator ODEs" => "tutorials/pino_ode.md",
-                                "Deep Galerkin Method" => "tutorials/dgm.md"
-                                #"examples/nnrode_example.md", # currently incorrect
-                                ],
-    "PDE PINN Tutorials" => Any["Introduction to NeuralPDE for PDEs" => "tutorials/pdesystem.md",
-                                "Bayesian PINNs for PDEs" => "tutorials/low_level_2.md",
-                                "Using GPUs" => "tutorials/gpu.md",
-                                "Defining Systems of PDEs" => "tutorials/systems.md",
-                                "Imposing Constraints" => "tutorials/constraints.md",
-                                "The symbolic_discretize Interface" => "tutorials/low_level.md",
-                                "Optimising Parameters (Solving Inverse Problems)" => "tutorials/param_estim.md",
-                                "Solving Integro Differential Equations" => "tutorials/integro_diff.md",
-                                "Transfer Learning with Neural Adapter" => "tutorials/neural_adapter.md",
-                                "The Derivative Neural Network Approximation" => "tutorials/derivative_neural_network.md"],
+        "Bayesian PINNs for Coupled ODEs" => "tutorials/Lotka_Volterra_BPINNs.md",
+        "PINNs DAEs" => "tutorials/dae.md",
+        "Parameter Estimation with PINNs for ODEs" => "tutorials/ode_parameter_estimation.md",
+        "Physics informed Neural Operator ODEs" => "tutorials/pino_ode.md",
+        "Deep Galerkin Method" => "tutorials/dgm.md"        #"examples/nnrode_example.md", # currently incorrect
+    ],
+    "PDE PINN Tutorials" => Any[
+        "Introduction to NeuralPDE for PDEs" => "tutorials/pdesystem.md",
+        "Bayesian PINNs for PDEs" => "tutorials/low_level_2.md",
+        "Using GPUs" => "tutorials/gpu.md",
+        "Defining Systems of PDEs" => "tutorials/systems.md",
+        "Imposing Constraints" => "tutorials/constraints.md",
+        "The symbolic_discretize Interface" => "tutorials/low_level.md",
+        "Optimising Parameters (Solving Inverse Problems)" => "tutorials/param_estim.md",
+        "Solving Integro Differential Equations" => "tutorials/integro_diff.md",
+        "Transfer Learning with Neural Adapter" => "tutorials/neural_adapter.md",
+        "The Derivative Neural Network Approximation" => "tutorials/derivative_neural_network.md"],
     "Extended Examples" => Any["examples/wave.md",
-                               "examples/3rd.md",
-                               "examples/ks.md",
-                               "examples/heterogeneous.md",
-                               "examples/linear_parabolic.md",
-                               "examples/nonlinear_elliptic.md",
-                               "examples/nonlinear_hyperbolic.md"],
+        "examples/3rd.md",
+        "examples/ks.md",
+        "examples/heterogeneous.md",
+        "examples/linear_parabolic.md",
+        "examples/nonlinear_elliptic.md",
+        "examples/nonlinear_hyperbolic.md",
+        "examples/complex.md"],
     "Manual" => Any["manual/ode.md",
-                    "manual/dae.md",
-                    "manual/pinns.md",
-                    "manual/bpinns.md",
-                    "manual/training_strategies.md",
-                    "manual/adaptive_losses.md",
-                    "manual/logging.md",
-                    "manual/neural_adapters.md"],
-    "Developer Documentation" => Any["developer/debugging.md"],
+        "manual/dae.md",
+        "manual/pinns.md",
+        "manual/bpinns.md",
+        "manual/training_strategies.md",
+        "manual/adaptive_losses.md",
+        "manual/logging.md",
+        "manual/neural_adapters.md"],
+    "Developer Documentation" => Any["developer/debugging.md"]
 ]
diff --git a/docs/src/developer/debugging.md b/docs/src/developer/debugging.md
@@ -58,8 +58,8 @@ strategy = NeuralPDE.GridTraining(dx)
 integral = NeuralPDE.get_numeric_integral(strategy, indvars, multioutput, chain, derivative)
 
 _pde_loss_function = NeuralPDE.build_loss_function(eq, indvars, depvars, phi, derivative,
-                                                   integral, multioutput, init_params,
-                                                   strategy)
+    integral, multioutput, init_params,
+    strategy)
 ```
 
 ```
@@ -83,9 +83,9 @@ julia> bc_indvars = NeuralPDE.get_variables(bcs,indvars,depvars)
 
 ```julia
 _bc_loss_functions = [NeuralPDE.build_loss_function(bc, indvars, depvars,
-                                                    phi, derivative, integral, multioutput,
-                                                    init_params, strategy,
-                                                    bc_indvars = bc_indvar)
+                          phi, derivative, integral, multioutput,
+                          init_params, strategy,
+                          bc_indvars = bc_indvar)
                       for (bc, bc_indvar) in zip(bcs, bc_indvars)]
 ```
 
@@ -126,7 +126,7 @@ julia> expr_bc_loss_functions = [NeuralPDE.build_symbolic_loss_function(bc,indva
 
 ```julia
 train_sets = NeuralPDE.generate_training_sets(domains, dx, [eq], bcs, eltypeθ, indvars,
-                                              depvars)
+    depvars)
 pde_train_set, bcs_train_set = train_sets
 ```
 
@@ -145,8 +145,9 @@ julia> bcs_train_set
 ```
 
 ```julia
-pde_bounds, bcs_bounds = NeuralPDE.get_bounds(domains, [eq], bcs, eltypeθ, indvars, depvars,
-                                              NeuralPDE.StochasticTraining(100))
+pde_bounds, bcs_bounds = NeuralPDE.get_bounds(
+    domains, [eq], bcs, eltypeθ, indvars, depvars,
+    NeuralPDE.StochasticTraining(100))
 ```
 
 ```