Merge branch 'main' into gd/coherent_map

Author: gdalle

.github/workflows/Test.yml

@@ -31,16 +31,18 @@ jobs:
           - "1.10"
           - "1"
         group:
-          - Misc/Internals
-          - Misc/DifferentiateWith
-          - Misc/FromPrimitive
-          - Misc/SparsityDetector
-          - Misc/ZeroBackends
-          - Back/ChainRulesBackends
+          - Core/Internals
+          - Back/DifferentiateWith
+          - Core/SimpleFiniteDiff
+          - Back/SparsityDetector
+          - Core/ZeroBackends
+          - Back/ChainRules
+          # - Back/Diffractor
           - Back/Enzyme
           - Back/FiniteDiff
           - Back/FiniteDifferences
           - Back/ForwardDiff
+          - Back/GTPSA
           - Back/Mooncake
           - Back/PolyesterForwardDiff
           - Back/ReverseDiff
@@ -52,12 +54,10 @@ jobs:
         skip_lts:
           - ${{ github.event.pull_request.draft }}
         exclude:
-          # - skip_lts: true
-          #   version: "1.10"
+          - skip_lts: true
+            version: "1.10"
           - version: "1"
-            group: Back/ChainRulesBackends
-          - version: "1"
-            group: Back/Enzyme
+            group: Back/ChainRules
     env:
       JULIA_DI_TEST_GROUP: ${{ matrix.group }}
     steps:
@@ -76,11 +76,10 @@ jobs:
       - uses: julia-actions/julia-processcoverage@v1
         with:
           directories: ./DifferentiationInterface/src,./DifferentiationInterface/ext,./DifferentiationInterface/test
-      - uses: codecov/codecov-action@v4
+      - uses: codecov/codecov-action@v5
         with:
           files: lcov.info
           flags: DI
-          name: ${{ matrix.version }} - DI (${{ matrix.group }})
           token: ${{ secrets.CODECOV_TOKEN }}
           fail_ci_if_error: true
 
@@ -105,9 +104,9 @@ jobs:
           - Weird
         skip_lts:
           - ${{ github.event.pull_request.draft }}
-        # exclude:
-        #   - skip_lts: true
-        #     version: "1.10"
+        exclude:
+          - skip_lts: true
+            version: "1.10"
     env:
       JULIA_DIT_TEST_GROUP: ${{ matrix.group }}
     steps:
@@ -126,10 +125,9 @@ jobs:
       - uses: julia-actions/julia-processcoverage@v1
         with:
           directories: ./DifferentiationInterfaceTest/src,./DifferentiationInterfaceTest/ext,./DifferentiationInterfaceTest/test
-      - uses: codecov/codecov-action@v4
+      - uses: codecov/codecov-action@v5
         with:
           files: lcov.info
           flags: DIT
-          name: ${{ matrix.version }} - DIT (${{ matrix.group }})
           token: ${{ secrets.CODECOV_TOKEN }}
           fail_ci_if_error: true

.gitignore

@@ -10,4 +10,5 @@
 
 *.csv
 
-playground.jl
+playground.jl
+.vscode

CITATION.bib

@@ -0,0 +1,59 @@
+# This CITATION.cff file was generated with cffinit.
+# Visit https://bit.ly/cffinit to generate yours today!
+
+cff-version: 1.2.0
+title: DifferentiationInterface.jl
+message: >-
+  If you use this software, please cite it using the
+  metadata from this file, and also cite the AbstractDifferentiation.jl software.
+type: software
+authors:
+  - given-names: Guillaume
+    family-names: Dalle
+    email: guillaume.dalle@enpc.fr
+    affiliation: >-
+      LVMT, ENPC, Institut Polytechnique de Paris, Univ
+      Gustave Eiffel, Marne-la-Vallée, France
+    orcid: 'https://orcid.org/0000-0003-4866-1687'
+  - given-names: Adrian
+    family-names: Hill
+    email: hill@tu-berlin.de
+    affiliation: 'Machine Learning Group, BIFOLD, TU Berlin'
+    orcid: 'https://orcid.org/0009-0009-5977-301X'
+identifiers:
+  - type: doi
+    value: 10.5281/zenodo.11092033
+    description: Zenodo DOI
+repository-code: 'https://github.com/JuliaDiff/DifferentiationInterface.jl'
+abstract: >-
+  An interface to various automatic differentiation backends
+  in Julia.
+keywords:
+  - automatic differentiation
+  - julia
+license: MIT
+references:
+  - title: >-
+      AbstractDifferentiation.jl: Backend-Agnostic
+      Differentiable Programming in Julia
+    type: software
+    authors:
+      - given-names: Frank
+        family-names: Schäfer
+        orcid: 'https://orcid.org/0000-0003-2684-4984'
+      - given-names: Mohamed
+        family-names: Tarek
+        orcid: 'https://orcid.org/0000-0003-3074-0678'
+      - given-names: Lyndon
+        family-names: White
+        orcid: 'https://orcid.org/0000-0003-1386-1646'
+      - given-names: Chris
+        family-names: Rackauckas
+        orcid: 'https://orcid.org/0000-0001-5850-0663'
+    identifiers:
+      - type: other
+        value: 'https://arxiv.org/abs/2109.12449'
+        description: Arxiv
+    repository-code: 'https://github.com/JuliaDiff/AbstractDifferentiation.jl'
+    abstract: An abstract interface for automatic differentiation.
+    license: MIT

CITATION.cff

@@ -1,20 +1,23 @@
 name = "DifferentiationInterface"
 uuid = "a0c0ee7d-e4b9-4e03-894e-1c5f64a51d63"
 authors = ["Guillaume Dalle", "Adrian Hill"]
-version = "0.6.22"
+version = "0.6.35"
 
 [deps]
 ADTypes = "47edcb42-4c32-4615-8424-f2b9edc5f35b"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 
 [weakdeps]
 ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
+DiffResults = "163ba53b-c6d8-5494-b064-1a9d43ac40c5"
 Diffractor = "9f5e2b26-1114-432f-b630-d3fe2085c51c"
 Enzyme = "7da242da-08ed-463a-9acd-ee780be4f1d9"
+EnzymeCore = "f151be2c-9106-41f4-ab19-57ee4f262869"
 FastDifferentiation = "eb9bf01b-bf85-4b60-bf87-ee5de06c00be"
 FiniteDiff = "6a86dc24-6348-571c-b903-95158fe2bd41"
 FiniteDifferences = "26cc04aa-876d-5657-8c51-4c34ba976000"
 ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
+GTPSA = "b27dd330-f138-47c5-815b-40db9dd9b6e8"
 Mooncake = "da2b9cff-9c12-43a0-ae48-6db2b0edb7d6"
 PolyesterForwardDiff = "98d1487c-24ca-40b6-b7ab-df2af84e126b"
 ReverseDiff = "37e2e3b7-166d-5795-8a7a-e32c996b4267"
@@ -28,14 +31,15 @@ Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
 [extensions]
 DifferentiationInterfaceChainRulesCoreExt = "ChainRulesCore"
 DifferentiationInterfaceDiffractorExt = "Diffractor"
-DifferentiationInterfaceEnzymeExt = "Enzyme"
+DifferentiationInterfaceEnzymeExt = ["EnzymeCore", "Enzyme"]
 DifferentiationInterfaceFastDifferentiationExt = "FastDifferentiation"
 DifferentiationInterfaceFiniteDiffExt = "FiniteDiff"
 DifferentiationInterfaceFiniteDifferencesExt = "FiniteDifferences"
-DifferentiationInterfaceForwardDiffExt = "ForwardDiff"
+DifferentiationInterfaceForwardDiffExt = ["ForwardDiff", "DiffResults"]
+DifferentiationInterfaceGTPSAExt = "GTPSA"
 DifferentiationInterfaceMooncakeExt = "Mooncake"
 DifferentiationInterfacePolyesterForwardDiffExt = "PolyesterForwardDiff"
-DifferentiationInterfaceReverseDiffExt = "ReverseDiff"
+DifferentiationInterfaceReverseDiffExt = ["ReverseDiff", "DiffResults"]
 DifferentiationInterfaceSparseArraysExt = "SparseArrays"
 DifferentiationInterfaceSparseMatrixColoringsExt = "SparseMatrixColorings"
 DifferentiationInterfaceStaticArraysExt = "StaticArrays"
@@ -44,27 +48,30 @@ DifferentiationInterfaceTrackerExt = "Tracker"
 DifferentiationInterfaceZygoteExt = ["Zygote", "ForwardDiff"]
 
 [compat]
-ADTypes = "1.9.0"
+ADTypes = "1.12.1"
 ChainRulesCore = "1.23.0"
+DiffResults = "1.1.0"
 Diffractor = "=0.2.6"
-Enzyme = "0.13.6"
+Enzyme = "0.13.17"
+EnzymeCore = "0.8.8"
 ExplicitImports = "1.10.1"
-FastDifferentiation = "0.4.1"
+FastDifferentiation = "0.4.3"
 FiniteDiff = "2.23.1"
 FiniteDifferences = "0.12.31"
 ForwardDiff = "0.10.36"
+GTPSA = "1.4.0"
 JuliaFormatter = "1"
 LinearAlgebra = "<0.0.1,1"
-Mooncake = "0.4.11"
+Mooncake = "0.4.52"
 PolyesterForwardDiff = "0.1.2"
 ReverseDiff = "1.15.1"
 SparseArrays = "<0.0.1,1"
 SparseConnectivityTracer = "0.5.0,0.6"
-StaticArrays = "1.9.7"
 SparseMatrixColorings = "0.4.9"
+StaticArrays = "1.9.7"
 Symbolics = "5.27.1, 6"
 Tracker = "0.2.33"
-Zygote = "0.6.69"
+Zygote = "0.6.69, 0.7"
 julia = "1.10"
 
 [extras]
@@ -80,6 +87,7 @@ FastDifferentiation = "eb9bf01b-bf85-4b60-bf87-ee5de06c00be"
 FiniteDiff = "6a86dc24-6348-571c-b903-95158fe2bd41"
 FiniteDifferences = "26cc04aa-876d-5657-8c51-4c34ba976000"
 ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
+GTPSA = "b27dd330-f138-47c5-815b-40db9dd9b6e8"
 JET = "c3a54625-cd67-489e-a8e7-0a5a0ff4e31b"
 JLArrays = "27aeb0d3-9eb9-45fb-866b-73c2ecf80fcb"
 JuliaFormatter = "98e50ef6-434e-11e9-1051-2b60c6c9e899"
@@ -99,4 +107,4 @@ Tracker = "9f7883ad-71c0-57eb-9f7f-b5c9e6d3789c"
 Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
 
 [targets]
-test = ["ADTypes", "Aqua", "ComponentArrays", "DataFrames", "ExplicitImports", "ForwardDiff", "JET", "JLArrays", "JuliaFormatter", "Pkg", "Random", "SparseArrays", "SparseConnectivityTracer", "SparseMatrixColorings", "StableRNGs", "StaticArrays", "Test", "Zygote"]
+test = ["ADTypes", "Aqua", "ComponentArrays", "DataFrames", "ExplicitImports", "JET", "JLArrays", "JuliaFormatter", "Pkg", "Random", "SparseArrays", "SparseConnectivityTracer", "SparseMatrixColorings", "StableRNGs", "StaticArrays", "Test"]

DifferentiationInterface/Project.toml

@@ -31,12 +31,13 @@ This package provides a unified syntax to differentiate functions, including:
 We support the following backends defined by [ADTypes.jl](https://github.com/SciML/ADTypes.jl):
 
 - [ChainRulesCore.jl](https://github.com/JuliaDiff/ChainRulesCore.jl)
-- [Diffractor.jl](https://github.com/JuliaDiff/Diffractor.jl)
+- [Diffractor.jl](https://github.com/JuliaDiff/Diffractor.jl) (currently broken)
 - [Enzyme.jl](https://github.com/EnzymeAD/Enzyme.jl)
 - [FastDifferentiation.jl](https://github.com/brianguenter/FastDifferentiation.jl)
 - [FiniteDiff.jl](https://github.com/JuliaDiff/FiniteDiff.jl)
 - [FiniteDifferences.jl](https://github.com/JuliaDiff/FiniteDifferences.jl)
 - [ForwardDiff.jl](https://github.com/JuliaDiff/ForwardDiff.jl)
+- [GTPSA.jl](https://github.com/bmad-sim/GTPSA.jl)
 - [Mooncake.jl](https://github.com/compintell/Mooncake.jl)
 - [PolyesterForwardDiff.jl](https://github.com/JuliaDiff/PolyesterForwardDiff.jl)
 - [ReverseDiff.jl](https://github.com/JuliaDiff/ReverseDiff.jl)
@@ -89,4 +90,4 @@ To improve your performance by up to several orders of magnitude compared to thi
 
 ## Citation
 
-Please cite both DifferentiationInterface.jl and its inspiration [AbstractDifferentiation.jl](https://github.com/JuliaDiff/AbstractDifferentiation.jl), using the provided `CITATION.bib` file.
+Please cite both DifferentiationInterface.jl and its inspiration [AbstractDifferentiation.jl](https://github.com/JuliaDiff/AbstractDifferentiation.jl), using the provided `CITATION.cff` file.

DifferentiationInterface/README.md

@@ -9,6 +9,7 @@ FiniteDiff = "6a86dc24-6348-571c-b903-95158fe2bd41"
 ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
 Markdown = "d6f4376e-aef5-505a-96c1-9c027394607a"
 PrettyTables = "08abe8d2-0d0c-5749-adfa-8a2ac140af0d"
+Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 SparseConnectivityTracer = "9f842d2f-2579-4b1d-911e-f412cf18a3f5"
 SparseMatrixColorings = "0a514795-09f3-496d-8182-132a7b665d35"
 Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"

DifferentiationInterface/docs/Project.toml

@@ -31,6 +31,7 @@ makedocs(;
             "explanation/backends.md",
             "explanation/advanced.md",
         ],
+        "FAQ" => ["faq/limitations.md", "faq/differentiability.md"],
         "api.md",
         "dev_guide.md",
     ],

DifferentiationInterface/docs/make.jl

@@ -68,7 +68,6 @@ jacobian
 jacobian!
 value_and_jacobian
 value_and_jacobian!
-MixedMode
 ```
 
 ## Second order
@@ -125,9 +124,10 @@ DifferentiationInterface.inner
 DifferentiateWith
 ```
 
-### Sparsity detection
+### Sparsity tools
 
 ```@docs
+MixedMode
 DenseSparsityDetector
 ```
 

DifferentiationInterface/docs/src/api.md

@@ -71,10 +71,26 @@ But after preparation, the more zeros are present in the matrix, the greater the
 ### Tuning the coloring algorithm
 
 The complexity of sparse Jacobians or Hessians grows with the number of distinct colors in a coloring of the sparsity pattern.
-To reduce this number of colors, [`GreedyColoringAlgorithm`](@ref) has two main settings: the order used for vertices and the decompression method.
+To reduce this number of colors, [`GreedyColoringAlgorithm`](@extref SparseMatrixColorings.GreedyColoringAlgorithm) has two main settings: the order used for vertices and the decompression method.
 Depending on your use case, you may want to modify either of these options to increase performance.
 See the documentation of [SparseMatrixColorings.jl](https://github.com/gdalle/SparseMatrixColorings.jl) for details.
 
+### Mixed mode
+
+When a Jacobian matrix has both dense rows and dense columns, it can be more efficient to use "mixed-mode" differentiation, a mixture of forward and reverse.
+The associated bidirectional coloring algorithm automatically decides how to cover the Jacobian using a set of columns (computed in forward mode) plus a set of rows (computed in reverse mode).
+This behavior is triggered as soon as you put a [`MixedMode`](@ref) object inside `AutoSparse`, like so:
+
+```julia
+AutoSparse(
+    MixedMode(forward_backend, reverse_backend);
+    sparsity_detector,
+    coloring_algorithm
+)
+```
+
+At the moment, mixed mode tends to work best when the [`GreedyColoringAlgorithm`](@extref SparseMatrixColorings.GreedyColoringAlgorithm) is provided with a [`RandomOrder`](@extref SparseMatrixColorings.RandomOrder) instead of the usual [`NaturalOrder`](@extref SparseMatrixColorings.NaturalOrder).
+
 ## Batch mode
 
 ### Multiple tangents