Merge pull request SciML#796 from sathvikbhagavan/sb/remove_exports

Add QA

.github/workflows/CI.yml

@@ -17,6 +17,7 @@ jobs:
       fail-fast: false
       matrix:
         group:
+          - QA
           - ODEBPINN
           - PDEBPINN
           - NNPDE1

Project.toml

@@ -43,6 +43,7 @@ Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
 Adapt = "3, 4"
 AdvancedHMC = "0.5"
 ArrayInterface = "6, 7"
+Aqua = "0.8"
 CUDA = "4"
 ChainRulesCore = "1"
 ComponentArrays = "0.13.2, 0.14, 0.15"
@@ -57,27 +58,36 @@ ForwardDiff = "0.10"
 Functors = "0.4"
 Integrals = "4"
 LineSearches = "7.2"
+LinearAlgebra = "1"
 LogDensityProblems = "2"
 Lux = "0.4, 0.5"
+LuxCUDA = "0.3"
 MCMCChains = "6"
 ModelingToolkit = "8"
 MonteCarloMeasurements = "1"
 Optim = "1.7.8"
 Optimization = "3"
+OptimizationOptimJL = "0.1"
 OptimizationOptimisers = "0.1"
+OrdinaryDiffEq = "6"
+Pkg = "1"
 QuasiMonteCarlo = "0.3.2"
+Random = "1"
 Reexport = "1.0"
 RuntimeGeneratedFunctions = "0.5"
+SafeTestsets = "0.1"
 SciMLBase = "2"
 Statistics = "1"
 StochasticDiffEq = "6.13"
 SymbolicUtils = "1"
 Symbolics = "5"
+Test = "1"
 UnPack = "1"
 Zygote = "0.6"
 julia = "1.6"
 
 [extras]
+Aqua = "4c88cf16-eb10-579e-8560-4a9242c79595"
 CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
 Flux = "587475ba-b771-5e3f-ad9e-33799f191a9c"
 LineSearches = "d3d80556-e9d4-5f37-9878-2ab0fcc64255"
@@ -87,7 +97,6 @@ OrdinaryDiffEq = "1dea7af3-3e70-54e6-95c3-0bf5283fa5ed"
 Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
 SafeTestsets = "1bc83da4-3b8d-516f-aca4-4fe02f6d838f"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
-cuDNN = "02a925ec-e4fe-4b08-9a7e-0d78e3d38ccd"
 
 [targets]
-test = ["Test", "CUDA", "SafeTestsets", "OptimizationOptimJL", "Pkg", "OrdinaryDiffEq", "LineSearches", "cuDNN", "LuxCUDA", "Flux"]
+test = ["Aqua", "Test", "CUDA", "SafeTestsets", "OptimizationOptimJL", "Pkg", "OrdinaryDiffEq", "LineSearches", "LuxCUDA", "Flux"]

src/NeuralPDE.jl

@@ -13,25 +13,24 @@ using Adapt, DiffEqNoiseProcess, StochasticDiffEq
 using Optimization
 using OptimizationOptimisers
 using Integrals, Cubature
-using QuasiMonteCarlo
+using QuasiMonteCarlo: LatinHypercubeSample
+import QuasiMonteCarlo
 using RuntimeGeneratedFunctions
 using SciMLBase
 using Statistics
 using ArrayInterface
 import Optim
-using DomainSets
-using Symbolics
 using Symbolics: wrap, unwrap, arguments, operation
 using SymbolicUtils
 using AdvancedHMC, LogDensityProblems, LinearAlgebra, Functors, MCMCChains
-using MonteCarloMeasurements
-import ModelingToolkit: value, nameof, toexpr, build_expr, expand_derivatives
-import DomainSets: Domain, ClosedInterval
-import ModelingToolkit: Interval, infimum, supremum #,Ball
-import SciMLBase: @add_kwonly, parameterless_type
-import UnPack: @unpack
+using MonteCarloMeasurements: Particles
+using ModelingToolkit: value, nameof, toexpr, build_expr, expand_derivatives, Interval, infimum, supremum
+import DomainSets
+using DomainSets: Domain, ClosedInterval, AbstractInterval, leftendpoint, rightendpoint, ProductDomain
+using SciMLBase: @add_kwonly, parameterless_type
+using UnPack: @unpack
 import ChainRulesCore, Lux, ComponentArrays
-import ChainRulesCore: @non_differentiable
+using ChainRulesCore: @non_differentiable
 
 RuntimeGeneratedFunctions.init(@__MODULE__)
 
@@ -53,16 +52,13 @@ include("advancedHMC_MCMC.jl")
 include("BPINN_ode.jl")
 include("PDE_BPINN.jl")
 
-export NNODE, TerminalPDEProblem, NNPDEHan, NNPDENS, NNRODE, NNDAE,
-    KolmogorovPDEProblem, NNKolmogorov, NNStopping, ParamKolmogorovPDEProblem,
-    KolmogorovParamDomain, NNParamKolmogorov,
+export NNODE, NNDAE,
     PhysicsInformedNN, discretize,
     GridTraining, StochasticTraining, QuadratureTraining, QuasiRandomTraining,
     WeightedIntervalTraining,
     build_loss_function, get_loss_function,
     generate_training_sets, get_variables, get_argument, get_bounds,
-    get_phi, get_numeric_derivative, get_numeric_integral,
-    build_symbolic_equation, build_symbolic_loss_function, symbolic_discretize,
+    get_numeric_integral, symbolic_discretize,
     AbstractAdaptiveLoss, NonAdaptiveLoss, GradientScaleAdaptiveLoss,
     MiniMaxAdaptiveLoss, LogOptions,
     ahmc_bayesian_pinn_ode, BNNODE, ahmc_bayesian_pinn_pde, vector_to_parameters,

test/qa.jl

@@ -0,0 +1,11 @@
+using NeuralPDE, Aqua
+@testset "Aqua" begin
+    Aqua.find_persistent_tasks_deps(NeuralPDE)
+    Aqua.test_ambiguities(NeuralPDE, recursive = false)
+    Aqua.test_deps_compat(NeuralPDE)
+    Aqua.test_piracies(NeuralPDE)
+    Aqua.test_project_extras(NeuralPDE)
+    Aqua.test_stale_deps(NeuralPDE)
+    Aqua.test_unbound_args(NeuralPDE)
+    Aqua.test_undefined_exports(NeuralPDE)
+end

test/runtests.jl

@@ -11,6 +11,9 @@ function dev_subpkg(subpkg)
 end
 
 @time begin
+    if GROUP == "All" || GROUP == "QA"
+        @time @safetestset "Quality Assurance" begin include("qa.jl") end
+    end
     if GROUP == "All" || GROUP == "ODEBPINN"
         @time @safetestset "Bpinn ODE solver" begin include("BPINN_Tests.jl") end
     end