cleaning

Project.toml

@@ -22,7 +22,6 @@ MLJBase = "a7f614a8-145f-11e9-1d2a-a57a1082229d"
 MLJModelInterface = "e80e1ace-859a-464e-9ed9-23947d8ae3ea"
 MLUtils = "f1d291b0-491e-4a28-83b9-f70985020b54"
 NNlib = "872c559c-99b0-510c-b3b7-b6c96a88d5cd"
-Octavian = "6fd5a793-0b7e-452c-907f-f8bfe9c57db4"
 Optimisers = "3bd65402-5787-11e9-1adc-39752487f4e2"
 Optimization = "7f7a1694-90dd-40f0-9382-eb1efda571ba"
 OptimizationOptimisers = "42dfb2eb-d2b4-4451-abcd-913932933ac1"
@@ -41,15 +40,15 @@ CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
 ContinuousNormalizingFlowsCUDAExt = "CUDA"
 
 [compat]
-ADTypes = "0.2, 1"
+ADTypes = "1"
 AbstractDifferentiation = "0.6"
 CUDA = "5"
 ChainRulesCore = "1"
 ComponentArrays = "0.15"
 ComputationalResources = "0.3"
 DataFrames = "1"
 Dates = "1"
-DifferentiationInterface = "0.1, 0.2, 0.3, 0.4, 0.5"
+DifferentiationInterface = "0.5"
 Distributions = "0.25"
 DistributionsAD = "0.6"
 FillArrays = "1"
@@ -60,7 +59,6 @@ MLJBase = "1"
 MLJModelInterface = "1"
 MLUtils = "0.4"
 NNlib = "0.9"
-Octavian = "0.3"
 Optimisers = "0.3"
 Optimization = "3"
 OptimizationOptimisers = "0.2"

benchmark/Project.toml

@@ -9,10 +9,10 @@ StableRNGs = "860ef19b-820b-49d6-a774-d7a799459cd3"
 Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
 
 [compat]
-ADTypes = "0.2, 1"
+ADTypes = "1"
 BenchmarkTools = "1"
 ComponentArrays = "0.15"
-DifferentiationInterface = "0.1, 0.2, 0.3, 0.4, 0.5"
+DifferentiationInterface = "0.5"
 Lux = "0.5"
 PkgBenchmark = "0.2"
 StableRNGs = "1"

src/ContinuousNormalizingFlows.jl

@@ -19,7 +19,6 @@ import AbstractDifferentiation,
     MLJModelInterface,
     MLUtils,
     NNlib,
-    Octavian,
     Optimisers,
     Optimization,
     OptimizationOptimisers,
@@ -53,8 +52,7 @@ export construct,
     ICNFModel,
     CondICNFModel,
     CondLayer,
-    PlanarLayer,
-    MulLayer
+    PlanarLayer
 
 include(joinpath("layers", "cond_layer.jl"))
 include(joinpath("layers", "planar_layer.jl"))

test/Project.toml

@@ -8,37 +8,33 @@ ComputationalResources = "ed09eef8-17a6-5b46-8889-db040fac31e3"
 DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
 DifferentiationInterface = "a0c0ee7d-e4b9-4e03-894e-1c5f64a51d63"
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
-ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
 GPUArraysCore = "46192b85-c4d5-4398-a991-12ede77f4527"
 JET = "c3a54625-cd67-489e-a8e7-0a5a0ff4e31b"
 Logging = "56ddb016-857b-54e1-b83d-db4d58db5568"
 Lux = "b2108857-7c20-44ae-9111-449ecde12c47"
 LuxCUDA = "d0bbae9a-e099-4d5b-a835-1c6931763bda"
 MLJBase = "a7f614a8-145f-11e9-1d2a-a57a1082229d"
-ReverseDiff = "37e2e3b7-166d-5795-8a7a-e32c996b4267"
 SciMLBase = "0bca4576-84f4-4d90-8ffe-ffa030f20462"
 TerminalLoggers = "5d786b92-1e48-4d6f-9151-6b4477ca9bed"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
 cuDNN = "02a925ec-e4fe-4b08-9a7e-0d78e3d38ccd"
 
 [compat]
-ADTypes = "0.2, 1"
+ADTypes = "1"
 AbstractDifferentiation = "0.6"
 Aqua = "0.8"
 CUDA = "5"
 ComponentArrays = "0.15"
 ComputationalResources = "0.3"
 DataFrames = "1"
-DifferentiationInterface = "0.1, 0.2, 0.3, 0.4, 0.5"
+DifferentiationInterface = "0.5"
 Distributions = "0.25"
-ForwardDiff = "0.10"
 GPUArraysCore = "0.1"
-JET = "0.8, 0.9"
+JET = "0.9"
 Lux = "0.5"
 LuxCUDA = "0.3"
 MLJBase = "1"
-ReverseDiff = "1"
 SciMLBase = "2"
 TerminalLoggers = "0.1"
 Zygote = "0.6"

test/call_tests.jl

@@ -29,16 +29,9 @@ Test.@testset "Call Tests" begin
     nvars_ = Int[2]
     aug_steers = Bool[false, true]
     inplaces = Bool[false, true]
-    adb_list = AbstractDifferentiation.AbstractBackend[
-        AbstractDifferentiation.ZygoteBackend(),
-        AbstractDifferentiation.ReverseDiffBackend(),
-        AbstractDifferentiation.ForwardDiffBackend(),
-    ]
-    adtypes = ADTypes.AbstractADType[
-        ADTypes.AutoZygote(),
-        ADTypes.AutoReverseDiff(),
-        ADTypes.AutoForwardDiff(),
-    ]
+    adb_list =
+        AbstractDifferentiation.AbstractBackend[AbstractDifferentiation.ZygoteBackend()]
+    adtypes = ADTypes.AbstractADType[ADTypes.AutoZygote()]
     compute_modes = ContinuousNormalizingFlows.ComputeMode[
         ContinuousNormalizingFlows.ADVecJacVectorMode(
             AbstractDifferentiation.ZygoteBackend(),
@@ -226,11 +219,7 @@ Test.@testset "Call Tests" begin
                 Test.@testset "x" begin
                     Test.@test !isnothing(
                         AbstractDifferentiation.gradient(adb, diff2_loss, r),
-                    ) broken =
-                        (GROUP != "All") &&
-                        adb isa AbstractDifferentiation.ReverseDiffBackend &&
-                        compute_mode isa ContinuousNormalizingFlows.MatrixMode &&
-                        VERSION >= v"1.10"
+                    )
                 end
             end
         end
@@ -244,11 +233,7 @@ Test.@testset "Call Tests" begin
                 Test.@testset "x" begin
                     Test.@test !isnothing(
                         DifferentiationInterface.gradient(diff2_loss, adtype, r),
-                    ) broken =
-                        (GROUP != "All") &&
-                        adtype isa ADTypes.AutoReverseDiff &&
-                        compute_mode isa ContinuousNormalizingFlows.MatrixMode &&
-                        VERSION >= v"1.10"
+                    )
                 end
             end
         end

test/fit_tests.jl

@@ -26,11 +26,7 @@ Test.@testset "Fit Tests" begin
     nvars_ = Int[2]
     aug_steers = Bool[false, true]
     inplaces = Bool[false, true]
-    adtypes = ADTypes.AbstractADType[
-        ADTypes.AutoZygote(),
-        ADTypes.AutoReverseDiff(),
-        ADTypes.AutoForwardDiff(),
-    ]
+    adtypes = ADTypes.AbstractADType[ADTypes.AutoZygote()]
     compute_modes = ContinuousNormalizingFlows.ComputeMode[
         ContinuousNormalizingFlows.ADVecJacVectorMode(
             AbstractDifferentiation.ZygoteBackend(),

test/runtests.jl

@@ -8,14 +8,12 @@ import AbstractDifferentiation,
     DataFrames,
     DifferentiationInterface,
     Distributions,
-    ForwardDiff,
     GPUArraysCore,
     JET,
     Logging,
     Lux,
     LuxCUDA,
     MLJBase,
-    ReverseDiff,
     SciMLBase,
     TerminalLoggers,
     Test,