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Migrate to ReactiveMP 3.9.0 #119

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merged 3 commits into from
May 29, 2023
Merged

Migrate to ReactiveMP 3.9.0 #119

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45dc8be
fix Flux dependency
bvdmitri May 26, 2023
8a6d6bb
fix examples
bvdmitri May 26, 2023
811f413
return RxInfer to examples Project.toml
bvdmitri May 26, 2023
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8 changes: 4 additions & 4 deletions Project.toml
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Original file line number Diff line number Diff line change
Expand Up @@ -2,7 +2,7 @@ name = "RxInfer"
uuid = "86711068-29c9-4ff7-b620-ae75d7495b3d"
authors = ["Bagaev Dmitry <d.v.bagaev@tue.nl> and contributors"]
# Do not forget to update the version in the `codemeta.json` too
version = "2.10.4"
version = "2.11.0"

[deps]
DataStructures = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
Expand All @@ -27,7 +27,7 @@ GraphPPL = "3.1.0"
MacroTools = "0.5.6"
Optim = "1.0.0"
ProgressMeter = "1.0.0"
ReactiveMP = "~3.8.0"
ReactiveMP = "~3.9.0"
Reexport = "1.2.0"
Rocket = "1.7.0"
TupleTools = "1.2.0"
Expand All @@ -41,7 +41,7 @@ Coverage = "a2441757-f6aa-5fb2-8edb-039e3f45d037"
Dates = "ade2ca70-3891-5945-98fb-dc099432e06a"
Distributed = "8ba89e20-285c-5b6f-9357-94700520ee1b"
Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
Flux = "587475ba-b771-5e3f-ad9e-33799f191a9c"
Optimisers = "3bd65402-5787-11e9-1adc-39752487f4e2"
InteractiveUtils = "b77e0a4c-d291-57a0-90e8-8db25a27a240"
Logging = "56ddb016-857b-54e1-b83d-db4d58db5568"
Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
Expand All @@ -53,4 +53,4 @@ Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
TestSetExtensions = "98d24dd4-01ad-11ea-1b02-c9a08f80db04"

[targets]
test = ["Test", "Pkg", "Logging", "InteractiveUtils", "TestSetExtensions", "Coverage", "Dates", "Distributed", "Documenter", "Plots", "BenchmarkCI", "BenchmarkTools", "PkgBenchmark", "Aqua", "StableRNGs", "StatsFuns", "Flux"]
test = ["Test", "Pkg", "Logging", "InteractiveUtils", "TestSetExtensions", "Coverage", "Dates", "Distributed", "Documenter", "Plots", "BenchmarkCI", "BenchmarkTools", "PkgBenchmark", "Aqua", "StableRNGs", "StatsFuns", "Optimisers"]
4 changes: 2 additions & 2 deletions codemeta.json
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Expand Up @@ -9,12 +9,12 @@
"downloadUrl": "https://github.com/biaslab/RxInfer.jl/releases",
"issueTracker": "https://github.com/biaslab/RxInfer.jl/issues",
"name": "RxInfer.jl",
"version": "2.10.4",
"version": "2.11.0",
"description": "Julia package for automated, scalable and efficient Bayesian inference on factor graphs with reactive message passing. ",
"applicationCategory": "Statistics",
"developmentStatus": "active",
"readme": "https://biaslab.github.io/RxInfer.jl/stable/",
"softwareVersion": "2.10.4",
"softwareVersion": "2.11.0",
"keywords": [
"Bayesian inference",
"message passing",
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1,292 changes: 618 additions & 674 deletions examples/Conjugate-Computational Variational Message Passing.ipynb
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4,965 changes: 2,565 additions & 2,400 deletions examples/Kalman filter with LSTM network driven dynamic.ipynb
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1,325 changes: 886 additions & 439 deletions examples/Nonlinear Sensor Fusion.ipynb
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2 changes: 2 additions & 0 deletions examples/Project.toml
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Expand Up @@ -6,9 +6,11 @@ Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
Flux = "587475ba-b771-5e3f-ad9e-33799f191a9c"
GraphPPL = "b3f8163a-e979-4e85-b43e-1f63d8c8b42c"
HypergeometricFunctions = "34004b35-14d8-5ef3-9330-4cdb6864b03a"
IJulia = "7073ff75-c697-5162-941a-fcdaad2a7d2a"
JLD = "4138dd39-2aa7-5051-a626-17a0bb65d9c8"
LaTeXStrings = "b964fa9f-0449-5b57-a5c2-d3ea65f4040f"
Optim = "429524aa-4258-5aef-a3af-852621145aeb"
Optimisers = "3bd65402-5787-11e9-1adc-39752487f4e2"
Parameters = "d96e819e-fc66-5662-9728-84c9c7592b0a"
Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
ProgressMeter = "92933f4c-e287-5a05-a399-4b506db050ca"
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4 changes: 2 additions & 2 deletions test/models/nonlinear/test_cvi.jl
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Expand Up @@ -2,7 +2,7 @@ module ReactiveMPModelsNonLinearDynamicsTest

using Test, InteractiveUtils
using RxInfer, Distributions
using BenchmarkTools, Random, Plots, Dates, StableRNGs, Flux
using BenchmarkTools, Random, Plots, Dates, StableRNGs, Optimisers

# Please use StableRNGs for random number generators

Expand Down Expand Up @@ -44,7 +44,7 @@ constraints = @constraints begin
end

@meta function model_meta(rng, n_iterations, n_samples, learning_rate)
f() -> CVI(rng, n_iterations, n_samples, Descent(learning_rate))
f() -> CVI(rng, n_iterations, n_samples, Optimisers.Descent(learning_rate))
end

## -------------------------------------------- ##
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