bump DifferentiableFrankWolfe compat

JuliaDecisionFocusedLearning · Dec 24, 2024 · c5c1bfd · c5c1bfd
1 parent 1c0510f
commit c5c1bfd
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diff --git a/Project.toml b/Project.toml
@@ -27,7 +27,7 @@ InferOptFrankWolfeExt = "DifferentiableFrankWolfe"
 ChainRulesCore = "1"
 DensityInterface = "0.4.0"
 DifferentiableExpectations = "0.2"
-DifferentiableFrankWolfe = "0.2"
+DifferentiableFrankWolfe = "0.3"
 Distributions = "0.25"
 DocStringExtensions = "0.9.3"
 LinearAlgebra = "<0.0.1,1"

diff --git a/src/layers/perturbed/perturbation.jl b/src/layers/perturbed/perturbation.jl
@@ -82,7 +82,7 @@ $TYPEDSIGNATURES
 
 Compute the gradient of the logdensity of η = θ ⊙ exp(εZ - ε²/2) w.r.t. θ., with Z ∼ N(0, 1).
 !!! warning
-    η should be a relization of θ, i.e. should be of the same sign.
+    η should be a realization of θ, i.e. should be of the same sign.
 """
 function normal_multiplicative_grad_logdensity(ε, η, θ)
     return (inv.(ε^2 .* θ) .* (log.(abs.(η)) - log.(abs.(θ)) .+ (ε^2 / 2)),)