Housekeeping

.JuliaFormatter.toml

@@ -0,0 +1 @@
+style = "blue"

.github/workflows/Docs.yml

@@ -1,30 +1,37 @@
-name: Docs
+name: Documentation
 
 on:
   push:
     branches:
-      - master
+      - master # update to match your development branch (master, main, dev, trunk, ...)
     tags: '*'
   pull_request:
 
 jobs:
-  docs:
-    name: Documentation
+  build:
+    # These permissions are needed to:
+    # - Deploy the documentation: https://documenter.juliadocs.org/stable/man/hosting/#Permissions
+    # - Delete old caches: https://github.com/julia-actions/cache#usage
+    permissions:
+      actions: write
+      contents: write
+      pull-requests: read
+      statuses: write
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v2
-      - uses: julia-actions/setup-julia@v1
+      - uses: actions/checkout@v4
+      - uses: julia-actions/setup-julia@v2
         with:
           version: '1'
-      - name: Install dependencies, build and deploy
+      - uses: julia-actions/cache@v2
+      - name: Install dependencies
+        shell: julia --color=yes --project=docs {0}
         run: |
           using Pkg
           Pkg.develop(PackageSpec(path=pwd()))
           Pkg.instantiate()
-          include(joinpath(pwd(), "docs", "make.jl"))
+      - name: Build and deploy
+        run: julia --color=yes --project=docs docs/make.jl
         env:
-          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} # For authentication with GitHub Actions token
-          DOCUMENTER_KEY: ${{ secrets.DOCUMENTER_KEY }} # For authentication with SSH deploy key
-          GKSwstype: nul # turn off GR's interactive plotting for notebooks
-          JULIA_PKG_SERVER: ''
-        shell: julia --color=yes --project=docs/ {0}
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+          DOCUMENTER_KEY: ${{ secrets.DOCUMENTER_KEY }}

.github/workflows/ci.yml

@@ -20,12 +20,12 @@ jobs:
         arch:
           - x64
     steps:
-      - uses: actions/checkout@v2
-      - uses: julia-actions/setup-julia@v1
+      - uses: actions/checkout@v4
+      - uses: julia-actions/setup-julia@v2
         with:
           version: ${{ matrix.version }}
           arch: ${{ matrix.arch }}
-      - uses: actions/cache@v1
+      - uses: actions/cache@v4
         env:
           cache-name: cache-artifacts
         with:
@@ -38,6 +38,8 @@ jobs:
       - uses: julia-actions/julia-buildpkg@v1
       - uses: julia-actions/julia-runtest@v1
       - uses: julia-actions/julia-processcoverage@v1
-      - uses: codecov/codecov-action@v1
+      - uses: codecov/codecov-action@v5
         with:
-          file: lcov.info
+          files: lcov.info
+          token: ${{ secrets.CODECOV_TOKEN }}
+          fail_ci_if_error: false

NEWS.md

@@ -6,6 +6,20 @@ between versions, and discuss new features.
 If you find a breaking change this is not reported here, please either raise an issue or
 make a PR to ammend this document.
 
+## 0.9.0
+
+This version is largely a tidying up job. It simplies much of the test suite, bumps the
+required version to Julia LTS. It additionally drops the various ChainRules that were
+implemented, in favour of assuming that users make use of a more powerful AD system than was
+available when this package was originally written. For example, you may wish to make use of
+Mooncake to differentiate code in this package.
+
+### Breaking Changes
+
+Removal of dependency on ChainRulesCore.jl, and associated rules. This means that this
+package almost certainly no longer supports Zygote.jl, but achieves a great reduction in the
+amount of testing which much be performed.
+
 ## 0.8.0
 
 ### Breaking Changes

Project.toml

@@ -1,22 +1,25 @@
 name = "Stheno"
 uuid = "8188c328-b5d6-583d-959b-9690869a5511"
-version = "0.8.2"
+version = "0.9.0"
 
 [deps]
 AbstractGPs = "99985d1d-32ba-4be9-9821-2ec096f28918"
 BlockArrays = "8e7c35d0-a365-5155-bbbb-fb81a777f24e"
-ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
-KernelFunctions = "ec8451be-7e33-11e9-00cf-bbf324bd1392"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 MacroTools = "1914dd2f-81c6-5fcd-8719-6d5c9610ff09"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
-Reexport = "189a3867-3050-52da-a836-e630ba90ab69"
 
 [compat]
-AbstractGPs = "0.4, 0.5"
-BlockArrays = "0.15, 0.16"
-ChainRulesCore = "1"
-KernelFunctions = "0.9.6, 0.10"
-MacroTools = "0.4, 0.5"
-Reexport = "0.2, 1"
-julia = "1.3"
+AbstractGPs = "0.5"
+BlockArrays = "1"
+KernelFunctions = "0.10"
+MacroTools = "0.5"
+Test = "1"
+julia = "1.10"
+
+[extras]
+KernelFunctions = "ec8451be-7e33-11e9-00cf-bbf324bd1392"
+Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
+
+[targets]
+test = ["KernelFunctions", "Test"]

README.md

@@ -242,7 +242,7 @@ See the docs for more examples.
 
 ## Hyperparameter learning and inference
 
-Fortunately, there is really no need for this package to explicitly provide support for hyperparameter optimisation as the functionality is already available elsewhere -- it's sufficient that it plays nicely with other standard packages in the ecosystem such as [Zygote.jl](https://github.com/FluxML/Zygote.jl/) (reverse-mode algorithmic differentiation), [Optim.jl](https://github.com/JuliaNLSolvers/Optim.jl) (non-linear optimisation), [AdvancedHMC.jl](https://github.com/TuringLang/AdvancedHMC.jl/) (Hamiltonian Monte Carlo / NUTS), [ParameterHandling.jl](https://github.com/invenia/ParameterHandling.jl/), [Soss.jl](https://github.com/cscherrer/Soss.jl/) / [Turing.jl](https://github.com/TuringLang/Turing.jl). For concrete examples of the use of each of these packages in conjunction with Stheno, see the `Getting Started` section of the [(dev) docs](https://juliagaussianprocesses.github.io/Stheno.jl/dev).
+Fortunately, there is really no need for this package to explicitly provide support for hyperparameter optimisation as the functionality is already available elsewhere -- it's sufficient that it plays nicely with other standard packages in the ecosystem such as [Mooncake.jl](https://github.com/compintell/Mooncake.jl/) (reverse-mode algorithmic differentiation), [Optim.jl](https://github.com/JuliaNLSolvers/Optim.jl) (non-linear optimisation), [AdvancedHMC.jl](https://github.com/TuringLang/AdvancedHMC.jl/) (Hamiltonian Monte Carlo / NUTS), [ParameterHandling.jl](https://github.com/invenia/ParameterHandling.jl/), [Soss.jl](https://github.com/cscherrer/Soss.jl/) / [Turing.jl](https://github.com/TuringLang/Turing.jl). For concrete examples of the use of each of these packages in conjunction with Stheno, see the `Getting Started` section of the [(dev) docs](https://juliagaussianprocesses.github.io/Stheno.jl/dev).
 
 
 

bench/gp/abstract_gp.jl

@@ -1,13 +1,15 @@
 @benchset "abstract_gp" begin
-    for N in [10,]
+    for N in [10]
         f = GP(CustomMean(sin), SEKernel(), GPC())
         x = randn(N)
         fx = f(x)
         y = rand(fx)
         @benchset "N=$N" begin
-            create_benchmarks("logpdf SEKernel $N (x, y)", true, (x, y)->logpdf(f(x), y), x, y)
-            create_benchmarks("rand SEKernel $N", true, x->rand(f(x)), x)
-            create_benchmarks("cov(f(x)) $N", true, x->cov(f(x)), x)
+            create_benchmarks(
+                "logpdf SEKernel $N (x, y)", true, (x, y) -> logpdf(f(x), y), x, y
+            )
+            create_benchmarks("rand SEKernel $N", true, x -> rand(f(x)), x)
+            create_benchmarks("cov(f(x)) $N", true, x -> cov(f(x)), x)
         end
     end
 end

bench/mean_and_kernel/compose.jl

@@ -1,5 +1,12 @@
-using Stheno: UnaryMean, BinaryMean, BinaryKernel, BinaryCrossKernel, LhsCross, RhsCross,
-    OuterCross, OuterKernel
+using Stheno:
+    UnaryMean,
+    BinaryMean,
+    BinaryKernel,
+    BinaryCrossKernel,
+    LhsCross,
+    RhsCross,
+    OuterCross,
+    OuterKernel
 
 @benchset "compose" begin
     let

bench/mean_and_kernel/finite.jl

@@ -4,7 +4,7 @@
             μ = FiniteMean(CustomMean(sin), randn(N))
             @benchset(
                 "CustomMean(sin) $N",
-                create_benchmarks(μ; grads=false, x=1, x̄s=[1:N-1, 1:N,]),
+                create_benchmarks(μ; grads=false, x=1, x̄s=[1:(N - 1), 1:N]),
             )
         end
     end
@@ -13,7 +13,7 @@
             k = FiniteKernel(SEKernel(), randn(N))
             @benchset(
                 "SEKernel() $N",
-                create_benchmarks(k; grads=false, x=1, x′=2, x̄s=[1:N,], x̄′s=[1:N,]),
+                create_benchmarks(k; grads=false, x=1, x′=2, x̄s=[1:N], x̄′s=[1:N]),
             )
         end
     end
@@ -22,7 +22,7 @@
             k = LhsFiniteCrossKernel(SEKernel(), randn(N))
             @benchset(
                 "SEKernel() $N",
-                create_benchmarks(k; grads=false, x=1, x′=2.0, x̄s=[1:N,], x̄′s=[randn(N),]),
+                create_benchmarks(k; grads=false, x=1, x′=2.0, x̄s=[1:N], x̄′s=[randn(N)]),
             )
         end
     end
@@ -31,7 +31,7 @@
             k = RhsFiniteCrossKernel(SEKernel(), randn(N))
             @benchset(
                 "SEKernel() $N",
-                create_benchmarks(k; grads=false, x=1.0, x′=2, x̄s=[randn(N),], x̄′s=[1:N,]),
+                create_benchmarks(k; grads=false, x=1.0, x′=2, x̄s=[randn(N)], x̄′s=[1:N]),
             )
         end
     end
@@ -40,7 +40,7 @@
             k = FiniteCrossKernel(SEKernel(), randn(N), randn(N))
             @benchset(
                 "SEKernel() $N",
-                create_benchmarks(k; grads=false, x=1, x′=2, x̄s=[1:N,], x̄′s=[1:N,]),
+                create_benchmarks(k; grads=false, x=1, x′=2, x̄s=[1:N], x̄′s=[1:N]),
             )
         end
     end

bench/mean_and_kernel/kernel.jl

@@ -1,5 +1,4 @@
 @benchset "kernel" begin
-
     @benchset "ZeroKernel{Float64}()" begin
         create_benchmarks(ZeroKernel{Float64}(); grads=false)
     end
@@ -8,12 +7,12 @@
     # end
     # @benchset "SEKernel" begin
     #     @benchset "Real CPU" create_benchmarks(SEKernel())
-        # @benchset "Real GPU" create_benchmarks(
-        #     SEKernel();
-        #     x=randn(Float32), x′=randn(Float32),
-        #     x̄s=[CuArray{Float32}(randn(N)) for N in Ns()],
-        #     x̄′s=[CuArray{Float32}(randn(N)) for N in Ns()],
-        # )
+    # @benchset "Real GPU" create_benchmarks(
+    #     SEKernel();
+    #     x=randn(Float32), x′=randn(Float32),
+    #     x̄s=[CuArray{Float32}(randn(N)) for N in Ns()],
+    #     x̄′s=[CuArray{Float32}(randn(N)) for N in Ns()],
+    # )
 
     #     for D in Ds()
     #         @benchset "ColVecs (D=$D) CPU" create_benchmarks(

bench/misc/ad_perf.jl

@@ -9,8 +9,6 @@ const x2 = randn(25)
 
 @model foo(θ) = GP(ConstMean(θ.m), kernel(SEKernel(); l=θ.l));
 
-
-
 #
 # Test single-process versions of operations on foo.
 #
@@ -29,8 +27,6 @@ y = rand(foo(θ)(x, 0.1));
 @code_warntype logpdf(foo(θ)(x, 0.1), y)
 @benchmark logpdf(foo($θ)($x, 0.1), $y)
 
-
-
 #
 # Test multi-process versions of operations on foo.
 #

bench/runbenchmarks.jl

@@ -12,9 +12,9 @@ benchmarks = @benchset "Stheno" begin
 
     # @benchset "mean_and_kernel" begin
     #     include("mean_and_kernel/mean.jl")
-        include("mean_and_kernel/kernel.jl")
-        # include("mean_and_kernel/compose.jl")
-        # include("mean_and_kernel/finite.jl")
+    include("mean_and_kernel/kernel.jl")
+    # include("mean_and_kernel/compose.jl")
+    # include("mean_and_kernel/finite.jl")
     # end
 
     # @benchset "gp" begin

bench/util.jl

@@ -1,6 +1,6 @@
-Ns() = [1_000,]
+Ns() = [1_000]
 # Ns() = [10,]
-Ds() = [1,]
+Ds() = [1]
 
 generate_x̄s(x, x̄s::Nothing) = [fill(x, N) for N in Ns()]
 generate_x̄s(x, x̄s) = x̄s
@@ -27,19 +27,25 @@ function create_benchmarks(μ::MeanFunction; grads=true, x=5.0, x̄s=nothing)
 
     for x̄ in generate_x̄s(x, x̄s)
         N = length(x̄)
-        create_benchmarks("map ($(length(x̄)))", grads, x->map(μ, x), x̄)
+        create_benchmarks("map ($(length(x̄)))", grads, x -> map(μ, x), x̄)
     end
 end
 
 # Common benchmarks for CrossKernel.
-function create_benchmarks(k::CrossKernel; x=5.0, x′=4.0, x̄s=nothing, x̄′s=nothing, grads=true)
+function create_benchmarks(
+    k::CrossKernel; x=5.0, x′=4.0, x̄s=nothing, x̄′s=nothing, grads=true
+)
     create_benchmarks("k(x, x′)", grads, k, x, x′)
 
     for (x̄, x̄′) in zip(generate_x̄s(x, x̄s), generate_x̄s(x′, x̄′s))
         N = length(x̄)
         @benchset "$N" begin
-            create_benchmarks("map k(x̄, x̄′) $N", grads, (x̄, x̄′)->map(k, x̄, x̄′), x̄, x̄′)
-            create_benchmarks("pw k(x̄, x̄′) $N", grads, (x̄, x̄′)->pairwise(k, x̄, x̄′), x̄, x̄′)
+            create_benchmarks(
+                "map k(x̄, x̄′) $N", grads, (x̄, x̄′) -> map(k, x̄, x̄′), x̄, x̄′
+            )
+            create_benchmarks(
+                "pw k(x̄, x̄′) $N", grads, (x̄, x̄′) -> pairwise(k, x̄, x̄′), x̄, x̄′
+            )
         end
     end
 end
@@ -52,27 +58,31 @@ function create_benchmarks(k::Kernel; x=5.0, x′=4.0, x̄s=nothing, x̄′s=not
     for (x̄, x̄′) in zip(generate_x̄s(x, x̄s), generate_x̄s(x′, x̄′s))
         N = length(x̄)
         @benchset "$N" begin
-            create_benchmarks("map k(x̄) $N", grads, x̄->map(k, x̄), x̄)
-            create_benchmarks("map k(x̄, x̄′) $N", grads, (x̄, x̄′)->map(k, x̄, x̄′), x̄, x̄′)
-            create_benchmarks("pw k(x̄) $N", grads, x̄->pairwise(k, x̄), x̄)
-            create_benchmarks("pw k(x̄, x̄′) $N", grads, (x̄, x̄′)->pairwise(k, x̄, x̄′), x̄, x̄′)
+            create_benchmarks("map k(x̄) $N", grads, x̄ -> map(k, x̄), x̄)
+            create_benchmarks(
+                "map k(x̄, x̄′) $N", grads, (x̄, x̄′) -> map(k, x̄, x̄′), x̄, x̄′
+            )
+            create_benchmarks("pw k(x̄) $N", grads, x̄ -> pairwise(k, x̄), x̄)
+            create_benchmarks(
+                "pw k(x̄, x̄′) $N", grads, (x̄, x̄′) -> pairwise(k, x̄, x̄′), x̄, x̄′
+            )
         end
     end
 end
 
 function pretty_print(d::BenchmarkGroup, pre=1)
-    pretty_print(d.data, pre)
+    return pretty_print(d.data, pre)
 end
 
 function pretty_print(d::Dict, pre=1)
     for (k, v) in d
         if v isa BenchmarkGroup
             s = "$(repr(k))"
             println(join(fill(" ", pre)) * s)
-            pretty_print(v, pre+1+4)
+            pretty_print(v, pre + 1 + 4)
         else
             println(join(fill(" ", pre)) * "$(repr(k)) => $(repr(v))")
         end
     end
-    nothing
+    return nothing
 end

docs/Project.toml

@@ -4,6 +4,6 @@ Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
 Stheno = "8188c328-b5d6-583d-959b-9690869a5511"
 
 [compat]
-Documenter = "0.27"
-julia = "1.6"
-Stheno = "0.8"
+Documenter = "1"
+julia = "1.10"
+Pkg = "1"