Updates on .github/workflows

.github/workflows/CI.yml

@@ -21,31 +21,33 @@ jobs:
       fail-fast: false
       matrix:
         version:
-          - '1.6'
+          - '1.10'
+          - '1.12'
         os:
           - ubuntu-latest
           - macOS-latest
         arch:
           - x64
+        exclude:
+          - os: macOS-latest
+            arch: x64
+        include:
+          - os: macOS-latest
+            arch: aarch64
+            version: '1.10'
+          - os: macOS-latest
+            arch: aarch64
+            version: '1.12'
     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
-        env:
-          cache-name: cache-artifacts
-        with:
-          path: ~/.julia/artifacts
-          key: ${{ runner.os }}-test-${{ env.cache-name }}-${{ hashFiles('**/Project.toml') }}
-          restore-keys: |
-            ${{ runner.os }}-test-${{ env.cache-name }}-
-            ${{ runner.os }}-test-
-            ${{ runner.os }}-
+      - uses: julia-actions/cache@v2
       - 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@v4
         with:
           file: lcov.info

.github/workflows/docsBuild.yml

@@ -17,18 +17,20 @@ jobs:
       - uses: actions/checkout@v2
       - uses: julia-actions/setup-julia@latest
         with:
-          version: '1.7'
+          version: '1.12'
       - name: Install dependencies
         run: |
-          sudo apt install libxt6 libxrender1 libxext6 libgl1-mesa-glx libqt5widgets5
-      - run: |
+          sudo apt-get update
+          sudo apt-get install -y --no-install-recommends \
+            libxt6 libxrender1 libxext6 libgl1 libqt5widgets5
+      - name: Install Julia dependencies
+        run: |
           julia --project=docs -e '
             using Pkg
-            Pkg.instantiate()
             Pkg.develop(PackageSpec(path=pwd()))
             Pkg.instantiate()'
       - name: Build and deploy
-        run: julia --project=docs docs/make.jl
         env:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
           DOCUMENTER_KEY: ${{ secrets.DOCUMENTER_KEY }}
+        run: julia --project=docs docs/make.jl

Project.toml

@@ -1,7 +1,7 @@
 name = "FourierFilterFlux"
 uuid = "3d7dfd45-6c90-4c9b-b697-194a05757159"
-authors = ["dsweber2"]
 version = "0.3.7"
+authors = ["dsweber2"]
 
 [deps]
 AbstractFFTs = "621f4979-c628-5d54-868e-fcf4e3e8185c"
@@ -11,6 +11,7 @@ ContinuousWavelets = "96eb917e-2868-4417-9cb6-27e7ff17528f"
 FFTW = "7a1cc6ca-52ef-59f5-83cd-3a7055c09341"
 FillArrays = "1a297f60-69ca-5386-bcde-b61e274b549b"
 Flux = "587475ba-b771-5e3f-ad9e-33799f191a9c"
+Functors = "d9f16b24-f501-4c13-a1f2-28368ffc5196"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 NNlib = "872c559c-99b0-510c-b3b7-b6c96a88d5cd"
 RecipesBase = "3cdcf5f2-1ef4-517c-9805-6587b60abb01"
@@ -20,6 +21,7 @@ Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
 cuDNN = "02a925ec-e4fe-4b08-9a7e-0d78e3d38ccd"
 
 [compat]
+Functors = "0.5.2"
 julia = "1.10"
 
 [extras]

docs/Project.toml

@@ -3,8 +3,9 @@ ContinuousWavelets = "96eb917e-2868-4417-9cb6-27e7ff17528f"
 Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
 FFTW = "7a1cc6ca-52ef-59f5-83cd-3a7055c09341"
 Flux = "587475ba-b771-5e3f-ad9e-33799f191a9c"
+FourierFilterFlux = "3d7dfd45-6c90-4c9b-b697-194a05757159"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
 
 [compat]
-Documenter = "0.27"
+Documenter = "1"

docs/src/coreType.md

@@ -14,7 +14,7 @@ julia> w[55:60,2] = randn(6);
 julia> ŵ = rfft(w, 1);
 
 julia> W = ConvFFT(ŵ,nothing,(128,1,2))
-ConvFFT[input=((128,), nfilters = 2, σ=identity, bc=Periodic()]
+ConvFFT[input=((128,), nfilters = 2, σ=identity, bc=Periodic()]  # 130 parameters
 
 ```
 
@@ -72,8 +72,8 @@ address this, e.g. `Pad(6)`
 ```jldoctest 1DconvEx
 julia> W = ConvFFT(ŵ,nothing,(128,1,2),boundary= FourierFilterFlux.Pad(6))
 ┌ Warning: You didn't hand me a set of filters constructed with the boundary in mind. I'm going to adjust them to fit, this may not be what you intended
-└ @ FourierFilterFlux ~/allHail/projects/FourierFilterFlux/src/FourierFilterFlux.jl:148
-ConvFFT[input=((128,), nfilters = 2, σ=identity, bc=Pad(6,)]
+└ @ FourierFilterFlux ~/work/FourierFilterFlux.jl/FourierFilterFlux.jl/src/FourierFilterFlux.jl:180
+ConvFFT[input=((128,), nfilters = 2, σ=identity, bc=Pad(6,)]  # 142 parameters
 
 julia> r =W(x); size(r)
 (128, 2, 1, 2)
@@ -93,7 +93,7 @@ do that as well:
 julia> ex2Dsize = (127, 352, 1, 10);
 
 julia> filt = ConvFFT(ex2Dsize, 3, relu, trainable=true,bias=false)
-ConvFFT[input=((127, 352), nfilters = 3, σ=relu, bc=Periodic()]
+ConvFFT[input=((127, 352), nfilters = 3, σ=relu, bc=Periodic()]  # 67_584 parameters
 
 ```
 
@@ -118,20 +118,24 @@ julia> fitThis = zeros(64,352,3); fitThis[1:3,(176-3:176+3),1] .= 1;
 julia> fitThis[1:15,(176-15:176+15),2] .= 1; fitThis[1:32,(176-44:176+44),3] .= 1;
 
 julia> targetConv = ConvFFT(fitThis, nothing, (127,352,1,10))
-ConvFFT[input=((127, 352), nfilters = 3, σ=identity, bc=Periodic()]
+ConvFFT[input=((127, 352), nfilters = 3, σ=identity, bc=Periodic()]  # 67_584 parameters
 
 julia> sum(norm.(map(-, targetConv.weight, filt.weight)) .^ 2) / sum(norm.(targetConv.weight) .^ 2) # the relative error
-1.0038243395792357
+1.0039214694920346
 
-julia> loss(x,y) = norm(filt(x) - targetConv(x))
+julia> loss(m, x) = norm(m(x) - targetConv(x))
 loss (generic function with 1 method)
 
-julia> genEx(n) = [(cpu(randn(ex2Dsize)), true) for i=1:n];
+julia> genEx(n) = [cpu(randn(ex2Dsize)) for i=1:n];
 
-julia> Flux.train!(loss, Flux.params(filt), genEx(100), ADAM()) # train for 100 samples
+julia> opt = Flux.setup(Adam(), filt);
+
+julia> for x in genEx(100)
+           Flux.train!(loss, filt, [(x,)], opt)
+       end
 
 julia> sum(norm.(map(-, targetConv.weight, filt.weight)) .^ 2) / sum(norm.(targetConv.weight) .^ 2) # the relative error
-0.8206548516626784
+0.8207499248183181
 
 ```
 
@@ -140,10 +144,13 @@ using FourierFilterFlux, Flux, LinearAlgebra # hide
 fitThis = zeros(64,352,3); fitThis[1:3,(176-3:176+3),1] .= 1; # hide
 fitThis[1:15,(176-15:176+15),2] .= 1; fitThis[1:32,(176-44:176+44),3] .= 1; # hide
 targetConv = ConvFFT(fitThis, nothing, (127,352,1,10)) # hide
-loss(x,y) = norm(filt(x) - targetConv(x)) # hide
-genEx(n) = [(cpu(randn(ex2Dsize)), true) for i=1:n]; # hide
-Flux.train!(loss, Flux.params(filt), genEx(100), ADAM()) # hide
-loss(randn(ex2Dsize), nothing) # hide
+loss(m, x) = norm(m(x) - targetConv(x)) # hide
+genEx(n) = [cpu(randn(ex2Dsize)) for i=1:n]; # hide
+opt = Flux.setup(Adam(), filt); # hide
+for x in genEx(100) # hide
+    Flux.train!(loss, filt, [(x,)], opt) # hide
+end # hide
+loss(filt, randn(ex2Dsize)) # hide
 plot(heatmap(filt,vis=1), heatmap(filt,vis=2), heatmap(filt,vis=3),
 	heatmap(targetConv,vis=1), heatmap(targetConv,vis=2),
 	heatmap(targetConv,vis=3))

src/FourierFilterFlux.jl

@@ -5,6 +5,11 @@ using AbstractFFTs, FFTW # TODO: check the license on FFTW and such
 using ContinuousWavelets
 using RecipesBase
 using CUDA
+using Functors
+
+Functors.@leaf FFTW.rFFTWPlan
+Functors.@leaf FFTW.cFFTWPlan  
+Functors.@leaf FFTW.Plan
 
 const use_cuda = Ref(false)
 if CUDA.functional()

src/paramCollection.jl

@@ -1,8 +1,8 @@
 Flux.@layer ConvFFT
 
 function Flux.trainable(CFT::ConvFFT{A,B,C,D,E,F,G,true}) where {A,B,C,D,E,F,G}
-    (CFT.weight, CFT.bias)
+    (; weight = CFT.weight, bias = CFT.bias)
 end
 function Flux.trainable(::ConvFFT{A,B,C,D,E,F,G,false}) where {A,B,C,D,E,F,G}
-    tuple()
+    NamedTuple()
 end