Restore some support for Tracker.jl

Project.toml

@@ -1,6 +1,6 @@
 name = "Flux"
 uuid = "587475ba-b771-5e3f-ad9e-33799f191a9c"
-version = "0.14.14"
+version = "0.14.15"
 
 [deps]
 Adapt = "79e6a3ab-5dfb-504d-930d-738a2a938a0e"
@@ -54,6 +54,7 @@ ProgressLogging = "0.1"
 Reexport = "1.0"
 SpecialFunctions = "2.1.2"
 Statistics = "1"
+Tracker = "0.2.33"
 Zygote = "0.6.67"
 cuDNN = "1"
 julia = "1.9"
@@ -72,9 +73,11 @@ LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 Metal = "dde4c033-4e86-420c-a63e-0dd931031962"
 Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
+Tracker = "9f7883ad-71c0-57eb-9f7f-b5c9e6d3789c"
 cuDNN = "02a925ec-e4fe-4b08-9a7e-0d78e3d38ccd"
 
 [targets]
 test = ["Test", "Documenter", "IterTools", "LinearAlgebra", "FillArrays", 
         "ComponentArrays", "BSON", "Pkg", "CUDA", "cuDNN", "Metal", "AMDGPU", 
-        "Enzyme", "FiniteDifferences"]
+        "Enzyme", "FiniteDifferences", "Tracker"]
+

src/layers/stateless.jl

@@ -81,7 +81,8 @@ end
 _match_eltype(layer, ::Type, x::AbstractArray) = x
 
 # 2-arg method, for common layers with layer.weight
-_match_eltype(layer, x) = _match_eltype(layer, eltype(layer.weight), x)
+# NB using _eltype gets Float64 from Tracker.TrackedArray{Float64}, not TrackedReal
+_match_eltype(layer, x) = _match_eltype(layer, _eltype(layer.weight), x)
 
 # Trivial rule:
 function ChainRulesCore.rrule(::typeof(_match_eltype), layer, ::Type{T}, x::AbstractArray) where {T}

src/utils.jl

@@ -501,9 +501,12 @@ function create_bias(weights::AbstractArray, bias::Bool, dims::Integer...)
 end
 function create_bias(weights::AbstractArray, bias::AbstractArray, dims::Integer...)
   size(bias) == dims || throw(DimensionMismatch("expected bias of size $(dims), got size $(size(bias))"))
-  convert(AbstractArray{eltype(weights)}, bias)
+  convert(AbstractArray{_eltype(weights)}, bias)
 end
 
+# This avoids the issue that Tracker.TrackedArray{Float64} declares eltype() = TrackedReal
+_eltype(::AbstractArray{T}) where T = T
+
 
 # Other
 

test/runtests.jl

@@ -28,6 +28,7 @@ Random.seed!(0)
     @testset "Optimise / Train" begin
       include("optimise.jl")
       include("train.jl")
+      include("tracker.jl")
     end
 
     @testset "Data" begin

test/tracker.jl

@@ -0,0 +1,38 @@
+using Tracker: withgradient
+using Zygote: gradient
+using Functors: fmapstructure
+using Flux
+
+@testset "Tracker.jl" begin
+  @testset "some simple models" begin
+    m1 =  Dense(ones32(2,3), fill(0.1f0,2), abs2)
+    x1 = Float32[1,2,3]
+    (_, v1), g1 = withgradient(m1, x1) do m, x
+      y1 = m(x)
+      sum(abs2, y1 .- [4, 5]), y1
+    end
+    @test v1 ≈ m1(x1)
+    g1z = gradient(m1, x1) do m, x
+      sum(abs2, m(x) .- [4, 5])
+    end
+    @test g1[1].weight ≈ g1z[1].weight
+    @test g1[1].bias ≈ g1z[1].bias
+
+    m2 = Chain(Conv((2,2), 3 => 1, relu), Flux.flatten, Dense(20 => 1, tanh), only)
+    x2 = randn32(5,6,3,1)
+    v2, g2 = withgradient(m -> m(x2), m2)
+    g2z = gradient(m -> m(x2), m2)
+    @test g2[1].layers[1].weight ≈ g2z[1].layers[1].weight
+    @test g2[1].layers[1].bias ≈ g2z[1].layers[1].bias
+    @test g2[1].layers[3].weight ≈ g2z[1].layers[3].weight
+  end
+
+  @testset "Dropout" begin
+    g1z = gradient(sum∘Dropout(0.5), ones(1000))
+    v1, g1 = withgradient(sum∘Dropout(0.5), ones(1000))
+    @test 800<v1<1200
+    @test sum(g1[1]) ≈ v1
+    @test 400 < count(iszero, g1[1]) < 600
+  end
+end
+