CI overhaul

.buildkite/pipeline.yml

@@ -1,17 +1,4 @@
 steps:
-  - label: ":julia: Run tests on 1.6 LTS"
-    plugins:
-      - JuliaCI/julia#v1:
-          version: "1.6"
-      - JuliaCI/julia-test#v1:
-           coverage: false
-    agents:
-      queue: "juliagpu"
-      cuda: "*"
-    timeout_in_minutes: 60
-    # Don't run Buildkite if the commit message includes the text [skip tests]
-    if: build.message !~ /\[skip tests\]/
-
   - label: ":julia: Run tests on Julia-latest"
     plugins:
       - JuliaCI/julia#v1:

.github/dependabot.yml

@@ -5,3 +5,6 @@ updates:
     directory: "/" # Location of package manifests
     schedule:
       interval: "weekly"
+    ignore:
+      - dependency-name: "crate-ci/typos"
+        update-types: ["version-update:semver-patch"]

.github/workflows/CI.yml

@@ -1,70 +1,44 @@
 name: CI
-env:
-  DATADEPS_ALWAYS_ACCEPT: true
 on:
-  push:
-    branches: '*'
+  pull_request:
+    branches:
+      - main
     paths-ignore:
       - 'docs/**'
-    tags: '*'
-  pull_request:
+  push:
+    branches:
+      - main
     paths-ignore:
       - 'docs/**'
-concurrency:
-  # Skip intermediate builds: always.
-  # Cancel intermediate builds: only if it is a pull request build.
-  group: ${{ github.workflow }}-${{ github.ref }}
-  cancel-in-progress: ${{ startsWith(github.ref, 'refs/pull/') }}
+  schedule:
+    - cron: '17 14 * * 5'
 jobs:
   test:
-    name: Julia ${{ matrix.version }} - ${{ matrix.os }} - ${{ matrix.arch }} - ${{ github.event_name }}
     runs-on: ${{ matrix.os }}
     strategy:
       fail-fast: false
       matrix:
+        group:
+          - Core
         version:
-          - '1.6'
           - '1'
-          # - 'nightly'
         os:
           - ubuntu-latest
+          - macos-latest
           - windows-latest
-        arch:
-          - x64
     steps:
       - uses: actions/checkout@v4
       - uses: julia-actions/setup-julia@v1
         with:
           version: ${{ matrix.version }}
-          arch: ${{ matrix.arch }}
       - uses: julia-actions/cache@v1
+        with:
+          token: ${{ secrets.GITHUB_TOKEN }}
       - uses: julia-actions/julia-buildpkg@v1
       - uses: julia-actions/julia-runtest@v1
-      - uses: julia-actions/julia-processcoverage@v1
-      - uses: codecov/codecov-action@v3
-        with:
-          files: lcov.info
-  docs:
-    name: Documentation
-    runs-on: ubuntu-latest
-    permissions:
-      contents: write
-    steps:
-      - uses: actions/checkout@v4
-      - uses: julia-actions/setup-julia@v1
         with:
-          version: '1'
-      - uses: julia-actions/julia-buildpkg@v1
-      - uses: julia-actions/julia-docdeploy@v1
-        env:
-          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-      - run: |
-          julia --project=docs --code-coverage=user -e '
-            using Documenter: DocMeta, doctest
-            using NeuralOperators
-            DocMeta.setdocmeta!(NeuralOperators, :DocTestSetup, :(using NeuralOperators); recursive=true)
-            doctest(NeuralOperators)'
+          depwarn: error
       - uses: julia-actions/julia-processcoverage@v1
       - uses: codecov/codecov-action@v3
         with:
-          file: lcov.info
+          file: lcov.info

.github/workflows/Documentation.yml

@@ -0,0 +1,37 @@
+name: Documentation
+
+on:
+  push:
+    branches:
+      - main
+      - 'release-'
+    tags: '*'
+  pull_request:
+  schedule:
+    - cron: '17 14 * * 5'
+jobs:
+  build:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - uses: julia-actions/setup-julia@latest
+        with:
+          version: '1'
+      - name: Install dependencies
+        run: julia --project=docs/ -e 'using Pkg; Pkg.develop(PackageSpec(path=pwd())); Pkg.instantiate()'
+      - name: Build and deploy
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} # For authentication with GitHub Actions token
+          DOCUMENTER_KEY: ${{ secrets.DOCUMENTER_KEY }} # For authentication with SSH deploy key
+        run: julia --project=docs/ --code-coverage=user docs/make.jl
+      - name: Doctest     
+        run: |
+          julia --project=docs --code-coverage=user -e '
+            using Documenter: DocMeta, doctest
+            using NeuralOperators
+            DocMeta.setdocmeta!(NeuralOperators, :DocTestSetup, :(using NeuralOperators); recursive=true)
+            doctest(NeuralOperators)'
+      - uses: julia-actions/julia-processcoverage@v1
+      - uses: codecov/codecov-action@v3
+        with:
+          file: lcov.info

.github/workflows/Downgrade.yml

@@ -0,0 +1,41 @@
+name: Downgrade
+on:
+  pull_request:
+    branches:
+      - main
+    paths-ignore:
+      - 'docs/**'
+  push:
+    branches:
+      - main
+    paths-ignore:
+      - 'docs/**'
+  schedule:
+    - cron: '17 14 * * 5'
+jobs:
+  test:
+    runs-on: ${{ matrix.os }}
+    strategy:
+      fail-fast: false
+      matrix:
+        group:
+          - Core
+        version:
+          - '1'
+        os:
+          - ubuntu-latest
+          - macos-latest
+          - windows-latest
+    steps:
+      - uses: actions/checkout@v4
+      - uses: julia-actions/setup-julia@v1
+        with:
+          version: ${{ matrix.version }}
+      - uses: cjdoris/julia-downgrade-compat-action@v1
+        with:
+          skip: Pkg,TOML
+      - uses: julia-actions/cache@v1
+        with:
+          token: ${{ secrets.GITHUB_TOKEN }}
+      - uses: julia-actions/julia-buildpkg@v1
+      - uses: julia-actions/julia-runtest@v1

.github/workflows/SpellCheck.yml

@@ -0,0 +1,13 @@
+name: Spell Check
+
+on: [pull_request]
+
+jobs:
+  typos-check:
+    name: Spell Check with Typos
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout Actions Repository
+        uses: actions/checkout@v3
+      - name: Check spelling
+        uses: crate-ci/[email protected] 

.typos.toml

@@ -0,0 +1 @@
+[default.extend-words]

Project.toml

@@ -5,32 +5,34 @@ version = "0.4.7"
 
 [deps]
 CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
-CUDAKernels = "72cfdca4-0801-4ab0-bf6a-d52aa10adc57"
 ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
 FFTW = "7a1cc6ca-52ef-59f5-83cd-3a7055c09341"
 Flux = "587475ba-b771-5e3f-ad9e-33799f191a9c"
 GeometricFlux = "7e08b658-56d3-11e9-2997-919d5b31e4ea"
-KernelAbstractions = "63c18a36-062a-441e-b654-da1e3ab1ce7c"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 Tullio = "bc48ee85-29a4-5162-ae0b-a64e1601d4bc"
 Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
 
 [compat]
-CUDA = "3, 4, 5"
-CUDAKernels = "0.3, 0.4"
-ChainRulesCore = "1"
-FFTW = "1"
-Flux = "0.13"
-GeometricFlux = "0.13"
-KernelAbstractions = "0.7, 0.8"
-Statistics = "1"
-Tullio = "0.3"
-Zygote = "0.6"
-julia = "1.6"
+Aqua = "0.8"
+CUDA = "3.5, 4, 5"
+ChainRulesCore = "1.15"
+FFTW = "1.3.0"
+Flux = "0.13.4"
+GeometricFlux = "0.13.5"
+Graphs = "1.6"
+SafeTestsets = "0.1"
+Statistics = "1.10"
+Test = "1"
+Tullio = "0.3.1"
+Zygote = "0.6.61"
+julia = "1.10"
 
 [extras]
+Aqua = "4c88cf16-eb10-579e-8560-4a9242c79595"
 Graphs = "86223c79-3864-5bf0-83f7-82e725a168b6"
+SafeTestsets = "1bc83da4-3b8d-516f-aca4-4fe02f6d838f"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [targets]
-test = ["Graphs", "Test"]
+test = ["Aqua", "Graphs", "SafeTestsets", "Test"]

src/NeuralOperators.jl

@@ -4,8 +4,6 @@ using Flux
 using FFTW
 using Tullio
 using CUDA
-using CUDAKernels
-using KernelAbstractions
 using Zygote
 using ChainRulesCore
 using GeometricFlux

src/Transform/chebyshev_transform.jl

@@ -1,14 +1,14 @@
 export ChebyshevTransform
 
-struct ChebyshevTransform{N, S} <: AbstractTransform
-    modes::NTuple{N, S} # N == ndims(x)
+struct ChebyshevTransform{nMinus1, S} <: AbstractTransform
+    modes::Tuple{S,Vararg{S,nMinus1}} # nMinus1 == ndims(x)-1
 end
 
-Base.ndims(::ChebyshevTransform{N}) where {N} = N
+Base.ndims(::ChebyshevTransform{nMinus1}) where {nMinus1} = nMinus1 + 1
 Base.eltype(::Type{ChebyshevTransform}) = Float32
 
-function transform(t::ChebyshevTransform{N}, 𝐱::AbstractArray) where {N}
-    return FFTW.r2r(𝐱, FFTW.REDFT10, 1:N) # [size(x)..., in_chs, batch]
+function transform(t::ChebyshevTransform{nMinus1}, 𝐱::AbstractArray) where {nMinus1}
+    return FFTW.r2r(𝐱, FFTW.REDFT10, 1:(nMinus1+1)) # [size(x)..., in_chs, batch]
 end
 
 function truncate_modes(t::ChebyshevTransform, 𝐱̂::AbstractArray)
@@ -31,7 +31,7 @@ function ∇r2r(Δ::AbstractArray{T}, kind, dims) where {T}
     # derivative of r2r turns out to be r2r
     Δx = FFTW.r2r(Δ, kind, dims)
 
-    # rank 4 correction: needs @bischtob to elaborate the reason using this. 
+    # rank 4 correction: needs @bischtob to elaborate the reason using this.
     # (M,) = size(Δ)[dims]
     # a1 = fill!(similar(Δ, M), one(T))
     # CUDA.@allowscalar a1[1] = a1[end] = zero(T)

src/Transform/fourier_transform.jl

@@ -1,10 +1,10 @@
 export FourierTransform
 
-struct FourierTransform{N, S} <: AbstractTransform
-    modes::NTuple{N, S} # N == ndims(x)
+struct FourierTransform{nMinus1, S} <: AbstractTransform
+    modes::Tuple{S,Vararg{S,nMinus1}} # nMinus1 == ndims(x)-1
 end
 
-Base.ndims(::FourierTransform{N}) where {N} = N
+Base.ndims(::FourierTransform{nMinus1}) where {nMinus1} = nMinus1+1
 Base.eltype(::Type{FourierTransform}) = ComplexF32
 
 function transform(ft::FourierTransform, 𝐱::AbstractArray)

test/DeepONet/DeepONet.jl

@@ -1,3 +1,6 @@
+using NeuralOperators
+using CUDA; CUDA.allowscalar(false)
+using Flux
 @testset "DeepONet" begin
     @testset "proper construction" begin
         deeponet = DeepONet((32, 64, 72), (24, 48, 72), σ, tanh)

test/FNO/FNO.jl

@@ -1,3 +1,5 @@
+using NeuralOperators
+using Flux
 @testset "FourierNeuralOperator" begin
     m = FourierNeuralOperator()
 

test/NOMAD/NOMAD.jl

@@ -1,3 +1,5 @@
+using NeuralOperators
+using Flux
 @testset "NOMAD" begin
     @testset "proper construction" begin
         nomad = NOMAD((32, 64, 72), (24, 48, 72), σ, tanh)

test/chebyshev_transform.jl

@@ -0,0 +1,13 @@
+using NeuralOperators
+using Zygote
+ch = 6
+batch = 7
+𝐱 = rand(30, 40, 50, ch, batch)
+t = ChebyshevTransform((3, 4, 5))
+@test ndims(t) == 3
+@test size(transform(t, 𝐱)) == (30, 40, 50, ch, batch)
+@test size(truncate_modes(t, transform(t, 𝐱))) == (3, 4, 5, ch, batch)
+@test size(inverse(t, truncate_modes(t, transform(t, 𝐱)), size(𝐱))) ==
+      (3, 4, 5, ch, batch)
+g = gradient(x -> sum(inverse(t, truncate_modes(t, transform(t, x)), size(𝐱))), 𝐱)
+@test size(g[1]) == (30, 40, 50, ch, batch)