Merge pull request #114 from SciML/ap/nlsolve_up

Clean up the codebase and use the latest versions of NonlinearSolve and SteadyStateDiffEq

.JuliaFormatter.toml

@@ -1,6 +1,5 @@
 style = "sciml"
 whitespace_in_kwargs = false
-always_use_return = true
 format_docstrings = true
 separate_kwargs_with_semicolon = true
 format_markdown = true

.buildkite/pipeline.yml

@@ -0,0 +1,58 @@
+steps:
+  - label: ":julia: Julia {{matrix.julia}} + CUDA GPU"
+    plugins:
+      - JuliaCI/julia#v1:
+          version: "{{matrix.julia}}"
+      - JuliaCI/julia-test#v1:
+          test_args: "--quickfail"
+      - JuliaCI/julia-coverage#v1:
+          codecov: true
+          dirs:
+            - src
+            - ext
+    agents:
+      queue: "juliagpu"
+      cuda: "*"
+    env:
+      GROUP: "CUDA"
+    if: build.message !~ /\[skip tests\]/
+    timeout_in_minutes: 240
+    matrix:
+      setup:
+        julia:
+          - "1"
+
+  - label: ":open_book: Documentation"
+    plugins:
+      - JuliaCI/julia#v1:
+          version: "1"
+      - JuliaCI/julia-coverage#v1:
+          codecov: true
+          dirs:
+            - src
+            - ext
+    command: |
+      julia --project --code-coverage=user --color=yes --threads=3 -e '
+        println("--- :julia: Instantiating project")
+        using Pkg
+        Pkg.instantiate()
+        Pkg.activate("docs")
+        Pkg.develop(PackageSpec(path=pwd()))
+        Pkg.instantiate()
+        println("+++ :julia: Building documentation")
+
+        Pkg.activate("docs")
+        include("docs/make.jl")'
+    agents:
+      queue: "juliagpu"
+      cuda: "*"
+    env:
+      DATADEPS_ALWAYS_ACCEPT: true
+      JULIA_DEBUG: "Documenter"
+      GKSwstype: "100" # https://discourse.julialang.org/t/generation-of-documentation-fails-qt-qpa-xcb-could-not-connect-to-display/60988
+    if: build.message !~ /\[skip docs\]/
+    timeout_in_minutes: 240
+
+env:
+  SECRET_CODECOV_TOKEN: "fbSN+ZbScLIWr1FOpAu1Z8PYWFobqbLGFayOgZE1ebhE8LIH/PILGXUMcdm9gkXVSwgdETDD0s33k14lBkJ90O4dV9w6k79F/pEgzVHV8baMoXZG03BPMxztlcoRXrKtRtAp+MwoATc3Ldb9H5vqgAnVNn5rhn4Rp0Z6LOVRC43hbhKBBKYh/N4gqpIQlcW4dBXmELhlnMFnUILjwGRVgEt/zh8H+vmf0qiIulNIQ/rfGISROHqFML0QDL4icloiqX08J76ZP/gZCeg6rJ0gl3ok3IspNPz51rlbvijqsPNyIHWi29OrAtWX3qKHfrAOoGIrE1d5Oy4wx4XaN/YBhg==;U2FsdGVkX188gcRjkUNMEC2Z5fEFfhsYY4WJbhhINOuCUgqq9XNHVDbJhzFUFVQ+UiuPHFg7CW/gn+3IkSVyOA=="
+  SECRET_DOCUMENTER_KEY: "jzyAET5IdazYwPAEZAmYmnBALb2dC1GPizCDCdt8xpjIi4ce6QbGGJMKo00ZNzJ/A7ii4bhqysVPXniifFwIGl7x+GSCeavwcSr15pfxJSqPuQYLKxESzIo+SM+l2uJWUz8KYMJ1tSt/Z3Up3qQfLeQFtR+f43b9QrLfhgZGAAdxpwu5VHdI3Xm/gZo5d8xEJ1xs4gqVP0e2A5EFr/j/exaWJL9+AvgO+Gko8NaJGG5B89zP1W2NBlpjttbwzj2naBhDx8A43Qe4eXm+BZd9CIZImiEJnnqoGxLkAyLDksbA68getUHW5z3nGyhWTrg5yfRqq0uyZZGTIOFz6dJrRg==;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"

.github/workflows/CI.yml

@@ -21,12 +21,9 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        group:
-          - CORE
-          - LAYERS
-          - ADJOINT
         version:
           - '1'
+          - '~1.10.0-0'
     steps:
       - uses: actions/checkout@v4
       - uses: julia-actions/setup-julia@v1
@@ -45,8 +42,11 @@ jobs:
       - uses: julia-actions/julia-buildpkg@v1
       - uses: julia-actions/julia-runtest@v1
         env:
-          GROUP: ${{ matrix.group }}
+          GROUP: "CPU"
+          JULIA_NUM_THREADS: 12
       - uses: julia-actions/julia-processcoverage@v1
+        with:
+          directories: src,ext
       - uses: codecov/codecov-action@v3
         with:
           files: lcov.info

CITATION.bib

@@ -1,8 +1,6 @@
-@misc{pal2022mixing,
-      title={Mixing Implicit and Explicit Deep Learning with Skip DEQs and Infinite Time Neural ODEs (Continuous DEQs)}, 
-      author={Avik Pal and Alan Edelman and Christopher Rackauckas},
-      year={2022},
-      eprint={2201.12240},
-      archivePrefix={arXiv},
-      primaryClass={cs.LG}
+@article{pal2022continuous,
+  title={Continuous Deep Equilibrium Models: Training Neural ODEs Faster by Integrating Them to Infinity},
+  author={Pal, Avik and Edelman, Alan and Rackauckas, Christopher},
+  booktitle={2023 IEEE High Performance Extreme Computing Conference (HPEC)}, 
+  year={2023}
 }

Project.toml

@@ -1,43 +1,43 @@
 name = "DeepEquilibriumNetworks"
 uuid = "6748aba7-0e9b-415e-a410-ae3cc0ecb334"
 authors = ["Avik Pal <[email protected]>"]
-version = "1.4.0"
+version = "2.0.0"
 
 [deps]
+ADTypes = "47edcb42-4c32-4615-8424-f2b9edc5f35b"
 ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
 ConcreteStructs = "2569d6c7-a4a2-43d3-a901-331e8e4be471"
+ConstructionBase = "187b0558-2788-49d3-abe0-74a17ed4e7c9"
 DiffEqBase = "2b5f629d-d688-5b77-993f-72d75c75574e"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
-LinearSolve = "7ed4a6bd-45f5-4d41-b270-4a48e9bafcae"
 Lux = "b2108857-7c20-44ae-9111-449ecde12c47"
-NonlinearSolve = "8913a72c-1f9b-4ce2-8d82-65094dcecaec"
-OrdinaryDiffEq = "1dea7af3-3e70-54e6-95c3-0bf5283fa5ed"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
-Reexport = "189a3867-3050-52da-a836-e630ba90ab69"
 SciMLBase = "0bca4576-84f4-4d90-8ffe-ffa030f20462"
-SciMLSensitivity = "1ed8b502-d754-442c-8d5d-10ac956f44a1"
-Setfield = "efcf1570-3423-57d1-acb7-fd33fddbac46"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 SteadyStateDiffEq = "9672c7b4-1e72-59bd-8a11-6ac3964bc41f"
 TruncatedStacktraces = "781d530d-4396-4725-bb49-402e4bee1e77"
+
+[weakdeps]
+SciMLSensitivity = "1ed8b502-d754-442c-8d5d-10ac956f44a1"
 Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
 
+[extensions]
+DeepEquilibriumNetworksSciMLSensitivityExt = "SciMLSensitivity"
+DeepEquilibriumNetworksZygoteExt = "Zygote"
+
 [compat]
+ADTypes = "0.2.5"
 ChainRulesCore = "1"
 ConcreteStructs = "0.2"
+ConstructionBase = "1"
 DiffEqBase = "6.119"
 LinearAlgebra = "1"
-LinearSolve = "1, 2"
-Lux = "0.5.7"
-NonlinearSolve = "2"
-OrdinaryDiffEq = "6"
+Lux = "0.5.11"
 Random = "1"
-Reexport = "1"
 SciMLBase = "2"
 SciMLSensitivity = "7.43"
-Setfield = "1"
 Statistics = "1"
-SteadyStateDiffEq = "1.16"
+SteadyStateDiffEq = "2"
 TruncatedStacktraces = "1.1"
-Zygote = "0.6.34"
+Zygote = "0.6.67"
 julia = "1.9"

README.md

@@ -5,6 +5,7 @@
 
 [![codecov](https://codecov.io/gh/SciML/DeepEquilibriumNetworks.jl/branch/main/graph/badge.svg)](https://codecov.io/gh/SciML/DeepEquilibriumNetworks.jl)
 [![Build Status](https://github.com/SciML/DeepEquilibriumNetworks.jl/workflows/CI/badge.svg)](https://github.com/SciML/DeepEquilibriumNetworks.jl/actions?query=workflow%3ACI)
+[![Build status](https://badge.buildkite.com/d7ce1858c4f89456c2d90e80c9b04b710bd81d7641db0a087c.svg?branch=main)](https://buildkite.com/julialang/deepequilibriumnetworks)
 
 [![ColPrac: Contributor's Guide on Collaborative Practices for Community Packages](https://img.shields.io/badge/ColPrac-Contributor%27s%20Guide-blueviolet)](https://github.com/SciML/ColPrac)
 [![SciML Code Style](https://img.shields.io/static/v1?label=code%20style&message=SciML&color=9558b2&labelColor=389826)](https://github.com/SciML/SciMLStyle)
@@ -24,31 +25,27 @@ Pkg.add("DeepEquilibriumNetworks")
 ## Quickstart
 
 ```julia
-using DeepEquilibriumNetworks, Lux, Random, Zygote
-# using LuxCUDA, LuxAMDGPU ## Install and Load for GPU Support
+using DeepEquilibriumNetworks, Lux, Random, NonlinearSolve, Zygote, SciMLSensitivity
+# using LuxCUDA, LuxAMDGPU ## Install and Load for GPU Support. See https://lux.csail.mit.edu/dev/manual/gpu_management
 
 seed = 0
 rng = Random.default_rng()
 Random.seed!(rng, seed)
 
 model = Chain(Dense(2 => 2),
-    DeepEquilibriumNetwork(Parallel(+,
-            Dense(2 => 2; use_bias=false),
-            Dense(2 => 2; use_bias=false)),
-        ContinuousDEQSolver(; abstol=0.1f0, reltol=0.1f0, abstol_termination=0.1f0,
-            reltol_termination=0.1f0);
-        save_everystep=true))
+    DeepEquilibriumNetwork(Parallel(+, Dense(2 => 2; use_bias=false),
+            Dense(2 => 2; use_bias=false)), NewtonRaphson()))
 
 gdev = gpu_device()
 cdev = cpu_device()
 
 ps, st = Lux.setup(rng, model) |> gdev
-x = rand(rng, Float32, 2, 1) |> gdev
-y = rand(rng, Float32, 2, 1) |> gdev
+x = rand(rng, Float32, 2, 3) |> gdev
+y = rand(rng, Float32, 2, 3) |> gdev
 
 model(x, ps, st)
 
-gs = only(Zygote.gradient(p -> sum(abs2, first(first(model(x, p, st))) .- y), ps))
+gs = only(Zygote.gradient(p -> sum(abs2, first(model(x, p, st)) .- y), ps))
 ```
 
 ## Citation
@@ -57,14 +54,11 @@ If you are using this project for research or other academic purposes consider c
 paper:
 
 ```bibtex
-@misc{pal2022mixing,
-  title={Mixing Implicit and Explicit Deep Learning with Skip DEQs and Infinite Time Neural
-         ODEs (Continuous DEQs)}, 
-  author={Avik Pal and Alan Edelman and Christopher Rackauckas},
-  year={2022},
-  eprint={2201.12240},
-  archivePrefix={arXiv},
-  primaryClass={cs.LG}
+@article{pal2022continuous,
+  title={Continuous Deep Equilibrium Models: Training Neural ODEs Faster by Integrating Them to Infinity},
+  author={Pal, Avik and Edelman, Alan and Rackauckas, Christopher},
+  booktitle={2023 IEEE High Performance Extreme Computing Conference (HPEC)}, 
+  year={2023}
 }
 ```
 

docs/Project.toml

@@ -2,8 +2,20 @@
 DeepEquilibriumNetworks = "6748aba7-0e9b-415e-a410-ae3cc0ecb334"
 Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
 DocumenterCitations = "daee34ce-89f3-4625-b898-19384cb65244"
+LinearSolve = "7ed4a6bd-45f5-4d41-b270-4a48e9bafcae"
+Lux = "b2108857-7c20-44ae-9111-449ecde12c47"
+LuxCUDA = "d0bbae9a-e099-4d5b-a835-1c6931763bda"
+MLDataUtils = "cc2ba9b6-d476-5e6d-8eaf-a92d5412d41d"
+MLDatasets = "eb30cadb-4394-5ae3-aed4-317e484a6458"
+NonlinearSolve = "8913a72c-1f9b-4ce2-8d82-65094dcecaec"
+Optimisers = "3bd65402-5787-11e9-1adc-39752487f4e2"
+OrdinaryDiffEq = "1dea7af3-3e70-54e6-95c3-0bf5283fa5ed"
+Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
+SciMLSensitivity = "1ed8b502-d754-442c-8d5d-10ac956f44a1"
+Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
+Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
 
 [compat]
-DeepEquilibriumNetworks = "1"
+DeepEquilibriumNetworks = "2"
 Documenter = "1"
-DocumenterCitations = "0.2, 1"
+DocumenterCitations = "1"

docs/make.jl

@@ -7,17 +7,10 @@ bib = CitationBibliography(joinpath(@__DIR__, "ref.bib"); style=:authoryear)
 
 include("pages.jl")
 
-makedocs(;
-    sitename="Fast Deep Equilibrium Networks",
-    authors="Avik Pal et al.",
-    modules=[DeepEquilibriumNetworks],
-    clean=true,
-    doctest=false,
-    linkcheck=true,
-    format=Documenter.HTML(;
-        assets=["assets/favicon.ico"],
+makedocs(; sitename="Deep Equilibrium Networks", authors="Avik Pal et al.",
+    modules=[DeepEquilibriumNetworks], clean=true, doctest=true, linkcheck=true,
+    format=Documenter.HTML(; assets=["assets/favicon.ico"],
         canonical="https://docs.sciml.ai/DeepEquilibriumNetworks/stable/"),
-    plugins=[bib],
-    pages)
+    plugins=[bib], pages)
 
 deploydocs(; repo="github.com/SciML/DeepEquilibriumNetworks.jl.git", push_preview=true)

docs/pages.jl

@@ -1,9 +1,9 @@
 pages = [
     "Home" => "index.md",
-    "Manual" => [
-        "Dynamical Systems" => "manual/solvers.md",
-        "DEQ Layers" => "manual/deqs.md",
-        "Miscellaneous" => "manual/misc.md",
+    "Tutorials" => [
+        "tutorials/basic_mnist_deq.md",
+        "tutorials/reduced_dim_deq.md",
     ],
+    "API References" => "api.md",
     "References" => "references.md",
 ]

docs/src/api.md

@@ -0,0 +1,31 @@
+# Deep Equilibrium Models
+
+[baideep2019](@cite) introduced Discrete Deep Equilibrium Models which drives a Discrete
+Dynamical System to its steady-state. [pal2022mixing](@cite) extends this framework to
+Continuous Dynamical Systems which converge to the steady-stable in a more stable fashion.
+For a detailed discussion refer to [pal2022mixing](@cite).
+
+To construct a continuous DEQ, any ODE solver compatible with `DifferentialEquations.jl` API
+can be passed as the solver. To construct a discrete DEQ, any root finding algorithm
+compatible with `NonlinearSolve.jl` API can be passed as the solver.
+
+## Standard Models
+
+```@docs
+DeepEquilibriumNetwork
+SkipDeepEquilibriumNetwork
+```
+
+## MultiScale Models
+
+```@docs
+MultiScaleDeepEquilibriumNetwork
+MultiScaleSkipDeepEquilibriumNetwork
+MultiScaleNeuralODE
+```
+
+## Solution
+
+```@docs
+DeepEquilibriumSolution
+```