Drop support for Julia 1.6 (#550)

* Drop support for Julia 1.6

* Fix DIT

Author: gdalle

.github/workflows/Test.yml

@@ -29,8 +29,7 @@ jobs:
       matrix:
         version:
           - "1.10"  # TODO: 1 (as of 2024.10.08, 1 means 1.11 and we're not ready yet)
-          - "lts"
-          - "pre"
+          - "1.11"
         group:
           - Misc/Internals
           - Misc/DifferentiateWith
@@ -51,50 +50,22 @@ jobs:
           - Back/Zygote
           - Down/Flux
           - Down/Lux
-        skip_lts:
-          - ${{ github.event.pull_request.draft }}
         skip_pre:
           - ${{ github.event.pull_request.draft }}
         exclude:
-          - skip_lts: true
-            version: "lts"
           - skip_pre: true
-            version: "pre"
-          # lts
-          - version: "lts"
-            group: Back/ChainRulesBackends
-          - version: "lts"
-            group: Back/Enzyme
-          - version: "lts"
-            group: Back/FiniteDiff
-          - version: "lts"
-            group: Back/Mooncake
-          - version: "lts"
-            group: Back/PolyesterForwardDiff
-          - version: "lts"
-            group: Back/SecondOrder
-          - version: "lts"
-            group: Back/SymbolicBackends
-          - version: "lts"
-            group: Misc/Internals
-          - version: "lts"
-            group: Misc/SparsityDetector
-          - version: "lts"
-            group: Down/Flux
-          - version: "lts"
-            group: Down/Lux
-          # pre-release
-          - version: "pre"
+            version: "1.11"
+          - version: "1.11"
             group: Back/ChainRulesBackends
-          - version: "pre"
+          - version: "1.11"
             group: Back/Enzyme
-          - version: "pre"
+          - version: "1.11"
             group: Back/Mooncake
-          - version: "pre"
+          - version: "1.11"
             group: Back/SecondOrder
-          - version: "pre"
+          - version: "1.11"
             group: Misc/Internals
-          - version: "pre"
+          - version: "1.11"
             group: Misc/SparsityDetector
     env:
       JULIA_DI_TEST_GROUP: ${{ matrix.group }}
@@ -135,26 +106,17 @@ jobs:
       matrix:
         version:
           - "1.10"  # TODO: 1
-          - "lts"
-          - "pre"
+          - "1.11"
         group:
           - Formalities
           - Zero
           - Standard
           - Weird
-        skip_lts:
-          - ${{ github.event.pull_request.draft }}
         skip_pre:
           - ${{ github.event.pull_request.draft }}
         exclude:
-          - skip_lts: true
-            version: "lts"
           - skip_pre: true
-            version: "pre"
-          - version: "lts"
-            group: Formalities
-          - version: "lts"
-            group: Weird
+            version: "1.11"
     env:
       JULIA_DIT_TEST_GROUP: ${{ matrix.group }}
     steps:

DifferentiationInterface/Project.toml

@@ -1,13 +1,11 @@
 name = "DifferentiationInterface"
 uuid = "a0c0ee7d-e4b9-4e03-894e-1c5f64a51d63"
 authors = ["Guillaume Dalle", "Adrian Hill"]
-version = "0.6.7"
+version = "0.6.8"
 
 [deps]
 ADTypes = "47edcb42-4c32-4615-8424-f2b9edc5f35b"
-Compat = "34da2185-b29b-5c13-b0c7-acf172513d20"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
-PackageExtensionCompat = "65ce6f38-6b18-4e1d-a461-8949797d7930"
 
 [weakdeps]
 ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
@@ -46,7 +44,6 @@ DifferentiationInterfaceZygoteExt = ["Zygote", "ForwardDiff"]
 [compat]
 ADTypes = "1.9.0"
 ChainRulesCore = "1.23.0"
-Compat = "3.46,4.2"
 Diffractor = "=0.2.6"
 Enzyme = "0.13.6"
 FastDifferentiation = "0.4.1"
@@ -55,7 +52,6 @@ FiniteDifferences = "0.12.31"
 ForwardDiff = "0.10.36"
 LinearAlgebra = "<0.0.1,1"
 Mooncake = "0.4.0"
-PackageExtensionCompat = "1.0.2"
 PolyesterForwardDiff = "0.1.2"
 ReverseDiff = "1.15.1"
 SparseArrays = "<0.0.1,1"

DifferentiationInterface/docs/src/explanation/backends.md

@@ -18,16 +18,6 @@ We support the following dense backend choices from [ADTypes.jl](https://github.
 - [`AutoTracker`](@extref ADTypes.AutoTracker)
 - [`AutoZygote`](@extref ADTypes.AutoZygote)
 
-!!! note
-    DifferentiationInterface.jl itself is compatible with Julia 1.6, the Long Term Support (LTS) version of the language.
-    However, we were only able to test the following backends on Julia 1.6:
-    - `AutoFiniteDifferences`
-    - `AutoForwardDiff`
-    - `AutoReverseDiff`
-    - `AutoTracker`
-    - `AutoZygote`
-    We strongly recommend that users upgrade to Julia 1.10 or above, where all backends are tested.
-
 ## Features
 
 Given a backend object, you can use:

DifferentiationInterface/ext/DifferentiationInterfaceChainRulesCoreExt/DifferentiationInterfaceChainRulesCoreExt.jl

@@ -9,7 +9,6 @@ using ChainRulesCore:
     RuleConfig,
     frule_via_ad,
     rrule_via_ad
-using Compat
 import DifferentiationInterface as DI
 using DifferentiationInterface:
     Constant, DifferentiateWith, NoPullbackPrep, NoPushforwardPrep, PullbackPrep, unwrap

DifferentiationInterface/ext/DifferentiationInterfaceChainRulesCoreExt/differentiate_with.jl

@@ -1,5 +1,5 @@
 function ChainRulesCore.rrule(dw::DifferentiateWith, x)
-    @compat (; f, backend) = dw
+    (; f, backend) = dw
     y = f(x)
     prep_same = DI.prepare_pullback_same_point(f, backend, x, (y,))
     function pullbackfunc(dy)

DifferentiationInterface/ext/DifferentiationInterfaceChainRulesCoreExt/reverse_onearg.jl

@@ -48,7 +48,7 @@ function DI.value_and_pullback(
     ty::NTuple,
     contexts::Vararg{Constant,C},
 ) where {C}
-    @compat (; y, pb) = prep
+    (; y, pb) = prep
     tx = map(ty) do dy
         pb(dy)[2]
     end
@@ -63,7 +63,7 @@ function DI.pullback(
     ty::NTuple,
     contexts::Vararg{Constant,C},
 ) where {C}
-    @compat (; pb) = prep
+    (; pb) = prep
     tx = map(ty) do dy
         pb(dy)[2]
     end

DifferentiationInterface/ext/DifferentiationInterfaceForwardDiffExt/DifferentiationInterfaceForwardDiffExt.jl

@@ -2,7 +2,6 @@ module DifferentiationInterfaceForwardDiffExt
 
 using ADTypes: AbstractADType, AutoForwardDiff
 using Base: Fix1, Fix2
-using Compat
 import DifferentiationInterface as DI
 using DifferentiationInterface:
     Context,

DifferentiationInterface/ext/DifferentiationInterfaceForwardDiffExt/differentiate_with.jl

@@ -1,13 +1,13 @@
 function (dw::DifferentiateWith)(x::Dual{T,V,N}) where {T,V,N}
-    @compat (; f, backend) = dw
+    (; f, backend) = dw
     xval = myvalue(T, x)
     tx = mypartials(T, Val(N), x)
     y, ty = DI.value_and_pushforward(f, backend, xval, tx)
     return make_dual(T, y, ty)
 end
 
 function (dw::DifferentiateWith)(x::AbstractArray{Dual{T,V,N}}) where {T,V,N}
-    @compat (; f, backend) = dw
+    (; f, backend) = dw
     xval = myvalue(T, x)
     tx = mypartials(T, Val(N), x)
     y, ty = DI.value_and_pushforward(f, backend, xval, tx)

DifferentiationInterface/ext/DifferentiationInterfaceForwardDiffExt/onearg.jl

@@ -31,7 +31,7 @@ function compute_ydual_onearg(
     tx::NTuple,
     contexts::Vararg{Context,C},
 ) where {F,T,C}
-    @compat (; xdual_tmp) = prep
+    (; xdual_tmp) = prep
     make_dual!(T, xdual_tmp, x, tx)
     ydual = f(xdual_tmp, map(unwrap, contexts)...)
     return ydual

DifferentiationInterface/ext/DifferentiationInterfaceForwardDiffExt/secondorder.jl

@@ -56,7 +56,7 @@ function DI.hvp(
     tx::NTuple,
     contexts::Vararg{Context,C},
 ) where {F,C}
-    @compat (; tagged_outer_backend, inner_gradient, outer_pushforward_prep) = prep
+    (; tagged_outer_backend, inner_gradient, outer_pushforward_prep) = prep
     return DI.pushforward(
         inner_gradient, outer_pushforward_prep, tagged_outer_backend, x, tx, contexts...
     )
@@ -71,7 +71,7 @@ function DI.hvp!(
     tx::NTuple,
     contexts::Vararg{Context,C},
 ) where {F,C}
-    @compat (; tagged_outer_backend, inner_gradient, outer_pushforward_prep) = prep
+    (; tagged_outer_backend, inner_gradient, outer_pushforward_prep) = prep
     DI.pushforward!(
         inner_gradient, tg, outer_pushforward_prep, tagged_outer_backend, x, tx, contexts...
     )