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fixed issue with MLJFlux.train #113

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merged 4 commits into from
Aug 13, 2024
Merged

fixed issue with MLJFlux.train #113

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5cce572
fixed issue with MLJFlux.train
pasq-cat Aug 12, 2024
eb20a32
fixed doc env
pasq-cat Aug 12, 2024
4a24c99
fixed docs env .
pasq-cat Aug 12, 2024
d77e6ee
updated project.toml with new version 1.0.2
pasq-cat Aug 13, 2024
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7 changes: 7 additions & 0 deletions CHANGELOG.md
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Expand Up @@ -6,6 +6,13 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/),

*Note*: We try to adhere to these practices as of version [v0.2.1].


## Version [1.0.2] - 2024-08-12
###
- added TaijaPlotting to the docs env
### Changed
- modified the MLJFlux.train function so that it now properly return a trained chain [[#112](https://github.com/JuliaTrustworthyAI/LaplaceRedux.jl/issues/112)]

## Version [1.0.0] - 2024-07-22

### Changed
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99 changes: 20 additions & 79 deletions docs/Manifest.toml
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@@ -1,8 +1,8 @@
# This file is machine-generated - editing it directly is not advised

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@Rockdeldiablo, changing the julia version is correct?

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@MojiFarmanbar yes it shouldn't be a problem.

julia_version = "1.10.4"
julia_version = "1.10.3"
manifest_format = "2.0"
project_hash = "07bab9fa5d046478b21247a44464171c6b19ad4c"
project_hash = "e74e14fb1831d3b0a43faae4918a6a4b752d6a56"

[[deps.ANSIColoredPrinters]]
git-tree-sha1 = "574baf8110975760d391c710b6341da1afa48d8c"
Expand Down Expand Up @@ -213,18 +213,6 @@ version = "0.10.8"
SentinelArrays = "91c51154-3ec4-41a3-a24f-3f23e20d615c"
StructTypes = "856f2bd8-1eba-4b0a-8007-ebc267875bd4"

[[deps.CategoricalDistributions]]
deps = ["CategoricalArrays", "Distributions", "Missings", "OrderedCollections", "Random", "ScientificTypes"]
git-tree-sha1 = "926862f549a82d6c3a7145bc7f1adff2a91a39f0"
uuid = "af321ab8-2d2e-40a6-b165-3d674595d28e"
version = "0.1.15"

[deps.CategoricalDistributions.extensions]
UnivariateFiniteDisplayExt = "UnicodePlots"

[deps.CategoricalDistributions.weakdeps]
UnicodePlots = "b8865327-cd53-5732-bb35-84acbb429228"

[[deps.ChainRules]]
deps = ["Adapt", "ChainRulesCore", "Compat", "Distributed", "GPUArraysCore", "IrrationalConstants", "LinearAlgebra", "Random", "RealDot", "SparseArrays", "SparseInverseSubset", "Statistics", "StructArrays", "SuiteSparse"]
git-tree-sha1 = "227985d885b4dbce5e18a96f9326ea1e836e5a03"
Expand Down Expand Up @@ -372,6 +360,12 @@ version = "1.0.0"
deps = ["Printf"]
uuid = "ade2ca70-3891-5945-98fb-dc099432e06a"

[[deps.Dbus_jll]]
deps = ["Artifacts", "Expat_jll", "JLLWrappers", "Libdl"]
git-tree-sha1 = "fc173b380865f70627d7dd1190dc2fce6cc105af"
uuid = "ee1fde0b-3d02-5ea6-8484-8dfef6360eab"
version = "1.14.10+0"

[[deps.DefineSingletons]]
git-tree-sha1 = "0fba8b706d0178b4dc7fd44a96a92382c9065c2c"
uuid = "244e2a9f-e319-4986-a169-4d1fe445cd52"
Expand Down Expand Up @@ -580,7 +574,7 @@ deps = ["Random"]
uuid = "9fa8497b-333b-5362-9e8d-4d0656e87820"

[[deps.GLFW_jll]]
deps = ["Artifacts", "JLLWrappers", "Libdl", "Libglvnd_jll", "Xorg_libXcursor_jll", "Xorg_libXi_jll", "Xorg_libXinerama_jll", "Xorg_libXrandr_jll", "xkbcommon_jll"]
deps = ["Artifacts", "JLLWrappers", "Libdl", "Libglvnd_jll", "Xorg_libXcursor_jll", "Xorg_libXi_jll", "Xorg_libXinerama_jll", "Xorg_libXrandr_jll", "libdecor_jll", "xkbcommon_jll"]
git-tree-sha1 = "3f74912a156096bd8fdbef211eff66ab446e7297"
uuid = "0656b61e-2033-5cc2-a64a-77c0f6c09b89"
version = "3.4.0+0"
Expand Down Expand Up @@ -831,12 +825,6 @@ git-tree-sha1 = "50901ebc375ed41dbf8058da26f9de442febbbec"
uuid = "b964fa9f-0449-5b57-a5c2-d3ea65f4040f"
version = "1.3.1"

[[deps.LaplaceRedux]]
deps = ["ChainRulesCore", "Compat", "ComputationalResources", "Distributions", "Flux", "LinearAlgebra", "MLJBase", "MLJFlux", "MLJModelInterface", "MLUtils", "Optimisers", "ProgressMeter", "Random", "Statistics", "Tables", "Tullio", "Zygote"]
path = ".."
uuid = "c52c1a26-f7c5-402b-80be-ba1e638ad478"
version = "1.0.0"

[[deps.Latexify]]
deps = ["Format", "InteractiveUtils", "LaTeXStrings", "MacroTools", "Markdown", "OrderedCollections", "Requires"]
git-tree-sha1 = "5b0d630f3020b82c0775a51d05895852f8506f50"
Expand All @@ -860,12 +848,6 @@ version = "1.2.2"
deps = ["Artifacts", "Pkg"]
uuid = "4af54fe1-eca0-43a8-85a7-787d91b784e3"

[[deps.LearnAPI]]
deps = ["InteractiveUtils", "Statistics"]
git-tree-sha1 = "ec695822c1faaaa64cee32d0b21505e1977b4809"
uuid = "92ad9a40-7767-427a-9ee6-6e577f1266cb"
version = "0.1.0"

[[deps.LibCURL]]
deps = ["LibCURL_jll", "MozillaCACerts_jll"]
uuid = "b27032c2-a3e7-50c8-80cd-2d36dbcbfd21"
Expand Down Expand Up @@ -970,18 +952,6 @@ git-tree-sha1 = "c1dd6d7978c12545b4179fb6153b9250c96b0075"
uuid = "e6f89c97-d47a-5376-807f-9c37f3926c36"
version = "1.0.3"

[[deps.MLJBase]]
deps = ["CategoricalArrays", "CategoricalDistributions", "ComputationalResources", "Dates", "DelimitedFiles", "Distributed", "Distributions", "InteractiveUtils", "InvertedIndices", "LearnAPI", "LinearAlgebra", "MLJModelInterface", "Missings", "OrderedCollections", "Parameters", "PrettyTables", "ProgressMeter", "Random", "RecipesBase", "Reexport", "ScientificTypes", "Serialization", "StatisticalMeasuresBase", "StatisticalTraits", "Statistics", "StatsBase", "Tables"]
git-tree-sha1 = "6f45e12073bc2f2e73ed0473391db38c31e879c9"
uuid = "a7f614a8-145f-11e9-1d2a-a57a1082229d"
version = "1.7.0"

[deps.MLJBase.extensions]
DefaultMeasuresExt = "StatisticalMeasures"

[deps.MLJBase.weakdeps]
StatisticalMeasures = "a19d573c-0a75-4610-95b3-7071388c7541"

[[deps.MLJFlux]]
deps = ["CategoricalArrays", "ColorTypes", "ComputationalResources", "Flux", "MLJModelInterface", "Metalhead", "Optimisers", "ProgressMeter", "Random", "Statistics", "Tables"]
git-tree-sha1 = "50c7f24b84005a2a80875c10d4f4059df17a0f68"
Expand Down Expand Up @@ -1188,11 +1158,11 @@ git-tree-sha1 = "949347156c25054de2db3b166c52ac4728cbad65"
uuid = "90014a1f-27ba-587c-ab20-58faa44d9150"
version = "0.11.31"

[[deps.Parameters]]
deps = ["OrderedCollections", "UnPack"]
git-tree-sha1 = "34c0e9ad262e5f7fc75b10a9952ca7692cfc5fbe"
uuid = "d96e819e-fc66-5662-9728-84c9c7592b0a"
version = "0.12.3"
[[deps.Pango_jll]]
deps = ["Artifacts", "Cairo_jll", "Fontconfig_jll", "FreeType2_jll", "FriBidi_jll", "Glib_jll", "HarfBuzz_jll", "JLLWrappers", "Libdl"]
git-tree-sha1 = "cb5a2ab6763464ae0f19c86c56c63d4a2b0f5bda"
uuid = "36c8627f-9965-5494-a995-c6b170f724f3"
version = "1.52.2+0"

[[deps.Parsers]]
deps = ["Dates", "PrecompileTools", "UUIDs"]
Expand Down Expand Up @@ -1423,12 +1393,6 @@ version = "0.4.2+0"
uuid = "ea8e919c-243c-51af-8825-aaa63cd721ce"
version = "0.7.0"

[[deps.ScientificTypes]]
deps = ["CategoricalArrays", "ColorTypes", "Dates", "Distributions", "PrettyTables", "Reexport", "ScientificTypesBase", "StatisticalTraits", "Tables"]
git-tree-sha1 = "75ccd10ca65b939dab03b812994e571bf1e3e1da"
uuid = "321657f4-b219-11e9-178b-2701a2544e81"
version = "3.0.2"

[[deps.ScientificTypesBase]]
git-tree-sha1 = "a8e18eb383b5ecf1b5e6fc237eb39255044fd92b"
uuid = "30f210dd-8aff-4c5f-94ba-8e64358c1161"
Expand Down Expand Up @@ -1529,12 +1493,6 @@ git-tree-sha1 = "192954ef1208c7019899fbf8049e717f92959682"
uuid = "1e83bf80-4336-4d27-bf5d-d5a4f845583c"
version = "1.4.3"

[[deps.StatisticalMeasuresBase]]
deps = ["CategoricalArrays", "InteractiveUtils", "MLUtils", "MacroTools", "OrderedCollections", "PrecompileTools", "ScientificTypesBase", "Statistics"]
git-tree-sha1 = "17dfb22e2e4ccc9cd59b487dce52883e0151b4d3"
uuid = "c062fc1d-0d66-479b-b6ac-8b44719de4cc"
version = "0.1.1"

[[deps.StatisticalTraits]]
deps = ["ScientificTypesBase"]
git-tree-sha1 = "542d979f6e756f13f862aa00b224f04f9e445f11"
Expand Down Expand Up @@ -1685,24 +1643,6 @@ git-tree-sha1 = "79eb0ed763084a3e7de81fe1838379ac6a23b6a0"
uuid = "592b5752-818d-11e9-1e9a-2b8ca4a44cd1"
version = "2.0.3"

[[deps.Tullio]]
deps = ["DiffRules", "LinearAlgebra", "Requires"]
git-tree-sha1 = "6d476962ba4e435d7f4101a403b1d3d72afe72f3"
uuid = "bc48ee85-29a4-5162-ae0b-a64e1601d4bc"
version = "0.3.7"

[deps.Tullio.extensions]
TullioCUDAExt = "CUDA"
TullioChainRulesCoreExt = "ChainRulesCore"
TullioFillArraysExt = "FillArrays"
TullioTrackerExt = "Tracker"

[deps.Tullio.weakdeps]
CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
FillArrays = "1a297f60-69ca-5386-bcde-b61e274b549b"
Tracker = "9f7883ad-71c0-57eb-9f7f-b5c9e6d3789c"

[[deps.URIs]]
git-tree-sha1 = "67db6cc7b3821e19ebe75791a9dd19c9b1188f2b"
uuid = "5c2747f8-b7ea-4ff2-ba2e-563bfd36b1d4"
Expand All @@ -1712,11 +1652,6 @@ version = "1.5.1"
deps = ["Random", "SHA"]
uuid = "cf7118a7-6976-5b1a-9a39-7adc72f591a4"

[[deps.UnPack]]
git-tree-sha1 = "387c1f73762231e86e0c9c5443ce3b4a0a9a0c2b"
uuid = "3a884ed6-31ef-47d7-9d2a-63182c4928ed"
version = "1.0.2"

[[deps.Unicode]]
uuid = "4ec0a83e-493e-50e2-b9ac-8f72acf5a8f5"

Expand Down Expand Up @@ -2024,6 +1959,12 @@ deps = ["Artifacts", "Libdl"]
uuid = "8e850b90-86db-534c-a0d3-1478176c7d93"
version = "5.8.0+1"

[[deps.libdecor_jll]]
deps = ["Artifacts", "Dbus_jll", "JLLWrappers", "Libdl", "Libglvnd_jll", "Pango_jll", "Wayland_jll", "xkbcommon_jll"]
git-tree-sha1 = "9bf7903af251d2050b467f76bdbe57ce541f7f4f"
uuid = "1183f4f0-6f2a-5f1a-908b-139f9cdfea6f"
version = "0.2.2+0"

[[deps.libevdev_jll]]
deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"]
git-tree-sha1 = "141fe65dc3efabb0b1d5ba74e91f6ad26f84cc22"
Expand Down
1 change: 0 additions & 1 deletion docs/Project.toml
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Expand Up @@ -4,7 +4,6 @@ DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
Flux = "587475ba-b771-5e3f-ad9e-33799f191a9c"
LaplaceRedux = "c52c1a26-f7c5-402b-80be-ba1e638ad478"
MLJFlux = "094fc8d1-fd35-5302-93ea-dabda2abf845"
Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
RDatasets = "ce6b1742-4840-55fa-b093-852dadbb1d8b"
Expand Down
63 changes: 31 additions & 32 deletions src/mlj_flux.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -219,22 +219,6 @@ function MLJFlux.train(
)
X = X isa Tables.MatrixTable ? MLJBase.matrix(X) : X

if !isa(chain, AbstractLaplace)
la = LaplaceRedux.Laplace(
chain;
likelihood=:regression,
subset_of_weights=model.subset_of_weights,
subnetwork_indices=model.subnetwork_indices,
hessian_structure=model.hessian_structure,
backend=model.backend,
σ=model.σ,
μ₀=model.μ₀,
P₀=model.P₀,
)
else
la = chain
end

# Initialize history:
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@Rockdeldiablo , I would suggest to keep this if-else on top as it was because it checks if chain is abstractlaplace or not. moving this piece down before LaplaceRedux.fit doesn't add any logics. if you agree i would suggest the followings:

  • keeping that if-else as it was to check if chain is laplace object
  • line 242 and 243, changing chain to la in for-loop, it would solve the problem
    what do you think?

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@MojiFarmanbar honestly i do not think it would work because
MLJFlux.train_epoch(
model, chain, regularized_optimiser, optimiser_state, X, y
) requires an actual chain not a laplace object

the laplace object is required only by LaplaceRedux.fit which is at the end.

have you tested it?

history = []
verbose_laplace = false
Expand Down Expand Up @@ -263,6 +247,22 @@ function MLJFlux.train(
push!(history, current_loss)
end

if !isa(chain, AbstractLaplace)
la = LaplaceRedux.Laplace(
chain;
likelihood=:regression,
subset_of_weights=model.subset_of_weights,
subnetwork_indices=model.subnetwork_indices,
hessian_structure=model.hessian_structure,
backend=model.backend,
σ=model.σ,
μ₀=model.μ₀,
P₀=model.P₀,
)
else
la = chain
end

# fit the Laplace model:
LaplaceRedux.fit!(la, zip(X, y))
optimize_prior!(la; verbose=verbose_laplace, n_steps=model.fit_prior_nsteps)
Expand Down Expand Up @@ -387,22 +387,6 @@ function MLJFlux.train(
)
X = X isa Tables.MatrixTable ? MLJBase.matrix(X) : X

if !isa(chain, AbstractLaplace)
la = LaplaceRedux.Laplace(
chain;
likelihood=:classification,
subset_of_weights=model.subset_of_weights,
subnetwork_indices=model.subnetwork_indices,
hessian_structure=model.hessian_structure,
backend=model.backend,
σ=model.σ,
μ₀=model.μ₀,
P₀=model.P₀,
)
else
la = chain
end

# Initialize history:
history = []
verbose_laplace = false
Expand Down Expand Up @@ -432,6 +416,21 @@ function MLJFlux.train(
push!(history, current_loss)
end

if !isa(chain, AbstractLaplace)
la = LaplaceRedux.Laplace(
chain;
likelihood=:classification,
subset_of_weights=model.subset_of_weights,
subnetwork_indices=model.subnetwork_indices,
hessian_structure=model.hessian_structure,
backend=model.backend,
σ=model.σ,
μ₀=model.μ₀,
P₀=model.P₀,
)
else
la = chain
end
# fit the Laplace model:
LaplaceRedux.fit!(la, zip(X, y))
optimize_prior!(la; verbose=verbose_laplace, n_steps=model.fit_prior_nsteps)
Expand Down
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