Formatting all files #80

yebai · 2024-08-09T14:49:12Z

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AdvancedVI.jl/test/inference/repgradelbo_locationscale_bijectors.jl

Line 11 in b2c7fa0

RepGradELBO(n_montecarlo; entropy=StickingTheLandingEntropy()),

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AdvancedVI.jl/test/inference/repgradelbo_locationscale_bijectors.jl

Lines 56 to 58 in b2c7fa0

    
           optimizer=opt, 
        
           show_progress=PROGRESS, 
        
           adtype=adtype,

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AdvancedVI.jl/test/inference/repgradelbo_locationscale_bijectors.jl

Lines 78 to 80 in b2c7fa0

    
           optimizer=opt, 
        
           show_progress=PROGRESS, 
        
           adtype=adtype,

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AdvancedVI.jl/test/inference/repgradelbo_locationscale_bijectors.jl

Lines 92 to 94 in b2c7fa0

    
           optimizer=opt, 
        
           show_progress=PROGRESS, 
        
           adtype=adtype,

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AdvancedVI.jl/test/interface/location_scale.jl

Lines 65 to 69 in b2c7fa0

    
           @test dropdims(mean(z_samples; dims=2); dims=2) ≈ μ rtol = realtype(1e-2) 
        
           @test dropdims(var(z_samples; dims=2); dims=2) ≈ diag(Σ) rtol = realtype( 
        
               1e-2 
        
           ) 
        
           @test cov(z_samples; dims=2) ≈ Σ rtol = realtype(1e-2)

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AdvancedVI.jl/test/interface/location_scale.jl

Lines 78 to 82 in b2c7fa0

    
           @test dropdims(mean(z_samples; dims=2); dims=2) ≈ μ rtol = realtype(1e-2) 
        
           @test dropdims(var(z_samples; dims=2); dims=2) ≈ diag(Σ) rtol = realtype( 
        
               1e-2 
        
           ) 
        
           @test cov(z_samples; dims=2) ≈ Σ rtol = realtype(1e-2)

[JuliaFormatter] _{reported by reviewdog 🐶}

AdvancedVI.jl/test/interface/location_scale.jl

Lines 97 to 101 in b2c7fa0

    
           @test dropdims(mean(z_samples; dims=2); dims=2) ≈ μ rtol = realtype(1e-2) 
        
           @test dropdims(var(z_samples; dims=2); dims=2) ≈ diag(Σ) rtol = realtype( 
        
               1e-2 
        
           ) 
        
           @test cov(z_samples; dims=2) ≈ Σ rtol = realtype(1e-2)

[JuliaFormatter] _{reported by reviewdog 🐶}

AdvancedVI.jl/test/interface/location_scale.jl

Lines 115 to 119 in b2c7fa0

    
           @test dropdims(mean(z_samples; dims=2); dims=2) ≈ μ rtol = realtype(1e-2) 
        
           @test dropdims(var(z_samples; dims=2); dims=2) ≈ diag(Σ) rtol = realtype( 
        
               1e-2 
        
           ) 
        
           @test cov(z_samples; dims=2) ≈ Σ rtol = realtype(1e-2)

[JuliaFormatter] _{reported by reviewdog 🐶}

AdvancedVI.jl/test/interface/location_scale.jl

Line 154 in b2c7fa0

FullRankGaussian(μ, L; scale_eps=ϵ)

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AdvancedVI.jl/test/interface/location_scale.jl

Line 157 in b2c7fa0

MeanFieldGaussian(μ, L; scale_eps=ϵ)

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AdvancedVI.jl/test/interface/optimize.jl

Lines 21 to 23 in b2c7fa0

    
           q_ref, stats_ref, _ = optimize( 
        
               rng, model, obj, q0, T; optimizer, show_progress=false, adtype 
        
           )

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AdvancedVI.jl/test/interface/optimize.jl

Line 26 in b2c7fa0

optimize(model, obj, q0, T; optimizer, show_progress=false, adtype)

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AdvancedVI.jl/test/interface/optimize.jl

Line 33 in b2c7fa0

callback(; stat, args...) = (test_value=test_values[stat.iteration],)

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AdvancedVI.jl/test/interface/optimize.jl

Lines 36 to 38 in b2c7fa0

    
           _, stats, _ = optimize( 
        
               rng, model, obj, q0, T; show_progress=false, adtype, callback 
        
           )

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AdvancedVI.jl/test/interface/optimize.jl

Lines 48 to 50 in b2c7fa0

    
           q_first, _, state = optimize( 
        
               rng, model, obj, q0, T_first; optimizer, show_progress=false, adtype 
        
           )

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AdvancedVI.jl/test/interface/optimize.jl

Lines 59 to 60 in b2c7fa0

    
           show_progress=false, 
        
           state_init=state,

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AdvancedVI.jl/test/interface/repgradelbo.jl

Line 16 in b2c7fa0

elbo_ref = estimate_objective(rng, obj, q0, model; n_samples=10^4)

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AdvancedVI.jl/test/interface/repgradelbo.jl

Line 20 in b2c7fa0

elbo = estimate_objective(rng, obj, q0, model; n_samples=10^4)

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AdvancedVI.jl/test/interface/repgradelbo.jl

Line 25 in b2c7fa0

elbo = estimate_objective(obj, q0, model; n_samples=10^4)

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AdvancedVI.jl/test/interface/repgradelbo.jl

Line 38 in b2c7fa0

ADTypes.AutoForwardDiff(), ADTypes.AutoReverseDiff(), ADTypes.AutoZygote()

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AdvancedVI.jl/test/interface/repgradelbo.jl

Line 41 in b2c7fa0

    
           Vector{eltype(μ_true)}(μ_true), Diagonal(Vector{eltype(L_true)}(diag(L_true)))

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AdvancedVI.jl/test/interface/repgradelbo.jl

Line 44 in b2c7fa0

obj = RepGradELBO(10; entropy=StickingTheLandingEntropy())

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AdvancedVI.jl/test/interface/repgradelbo.jl

Line 49 in b2c7fa0

ad, AdvancedVI.estimate_repgradelbo_ad_forward, params, aux, out

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AdvancedVI.jl/test/models/normallognormal.jl

Line 26 in b2c7fa0

[1:1, 2:(1 + length(μ_y))],

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AdvancedVI.jl/test/models/normallognormal.jl

Line 39 in b2c7fa0

    
           μ[1], L[1, 1], μ[2:end], PDMat(Σ[2:end, 2:end], Cholesky(L[2:end, 2:end], 'L', 0))

github-actions · 2024-08-09T14:50:25Z

src/families/location_scale.jl

+    location::AbstractVector{T},
+    scale::AbstractMatrix{T},
+    dist::ContinuousDistribution;
+    scale_eps::T=sqrt(eps(T)),


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Suggested change

scale_eps::T=sqrt(eps(T)),

scale_eps::T = sqrt(eps(T)),

github-actions · 2024-08-09T14:50:25Z

src/families/location_scale.jl

 end

 function Distributions.rand(
-    rng::AbstractRNG, q::MvLocationScale{S, D, L}, num_samples::Int
-)  where {S, D, L}
+    rng::AbstractRNG, q::MvLocationScale{S,D,L}, num_samples::Int


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Suggested change

rng::AbstractRNG, q::MvLocationScale{S,D,L}, num_samples::Int

rng::AbstractRNG,

q::MvLocationScale{S,D,L},

num_samples::Int,

github-actions · 2024-08-09T14:50:25Z

src/families/location_scale.jl

 end

 # This specialization improves AD performance of the sampling path
 function Distributions.rand(
-    rng::AbstractRNG, q::MvLocationScale{<:Diagonal, D, L}, num_samples::Int
-) where {L, D}
+    rng::AbstractRNG, q::MvLocationScale{<:Diagonal,D,L}, num_samples::Int


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Suggested change

rng::AbstractRNG, q::MvLocationScale{<:Diagonal,D,L}, num_samples::Int

rng::AbstractRNG,

q::MvLocationScale{<:Diagonal,D,L},

num_samples::Int,

github-actions · 2024-08-09T14:50:25Z

src/families/location_scale.jl

 end

-function Distributions._rand!(rng::AbstractRNG, q::MvLocationScale, x::AbstractVecOrMat{<:Real})
+function Distributions._rand!(
+    rng::AbstractRNG, q::MvLocationScale, x::AbstractVecOrMat{<:Real}


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Suggested change

rng::AbstractRNG, q::MvLocationScale, x::AbstractVecOrMat{<:Real}

rng::AbstractRNG,

q::MvLocationScale,

x::AbstractVecOrMat{<:Real},

github-actions · 2024-08-09T14:50:25Z

src/families/location_scale.jl

-    L::LinearAlgebra.AbstractTriangular{T};
-    scale_eps::T = sqrt(eps(T))
-) where {T <: Real}
+    μ::AbstractVector{T}, L::LinearAlgebra.AbstractTriangular{T}; scale_eps::T=sqrt(eps(T))


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Suggested change

μ::AbstractVector{T}, L::LinearAlgebra.AbstractTriangular{T}; scale_eps::T=sqrt(eps(T))

μ::AbstractVector{T},

L::LinearAlgebra.AbstractTriangular{T};

scale_eps::T = sqrt(eps(T)),

github-actions · 2024-08-09T14:50:28Z

test/inference/repgradelbo_distributionsad.jl

+                optimizer=opt,
+                show_progress=PROGRESS,
+                adtype=adtype,


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Suggested change

optimizer=opt,

show_progress=PROGRESS,

adtype=adtype,

optimizer = opt,

show_progress = PROGRESS,

adtype = adtype,

github-actions · 2024-08-09T14:50:28Z

test/inference/repgradelbo_locationscale.jl

-            :RepGradELBOStickingTheLanding => RepGradELBO(n_montecarlo, entropy = StickingTheLandingEntropy()),
+            :RepGradELBOClosedFormEntropy => RepGradELBO(n_montecarlo),
+            :RepGradELBOStickingTheLanding =>
+                RepGradELBO(n_montecarlo; entropy=StickingTheLandingEntropy()),


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Suggested change

RepGradELBO(n_montecarlo; entropy=StickingTheLandingEntropy()),

RepGradELBO(n_montecarlo; entropy = StickingTheLandingEntropy()),

github-actions · 2024-08-09T14:50:28Z

test/inference/repgradelbo_locationscale.jl

+                optimizer=opt,
+                show_progress=PROGRESS,
+                adtype=adtype,


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Suggested change

optimizer=opt,

show_progress=PROGRESS,

adtype=adtype,

optimizer = opt,

show_progress = PROGRESS,

adtype = adtype,

github-actions · 2024-08-09T14:50:28Z

test/inference/repgradelbo_locationscale.jl

+                optimizer=opt,
+                show_progress=PROGRESS,
+                adtype=adtype,


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

optimizer=opt,

show_progress=PROGRESS,

adtype=adtype,

optimizer = opt,

show_progress = PROGRESS,

adtype = adtype,

github-actions · 2024-08-09T14:50:28Z

test/inference/repgradelbo_locationscale.jl

+                optimizer=opt,
+                show_progress=PROGRESS,
+                adtype=adtype,


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

optimizer=opt,

show_progress=PROGRESS,

adtype=adtype,

optimizer = opt,

show_progress = PROGRESS,

adtype = adtype,

github-actions · 2024-08-09T14:50:31Z

src/optimize.jl

[JuliaFormatter] _{reported by reviewdog 🐶}

AdvancedVI.jl/src/optimize.jl

Lines 86 to 88 in b2c7fa0

opt_st, params = update_variational_params!(

typeof(q_init), opt_st, params, restructure, grad

)

formatting all files

b2c7fa0

yebai merged commit bce1e35 into master Aug 9, 2024
2 of 9 checks passed

yebai deleted the hg/formatting branch August 9, 2024 14:50

github-actions bot reviewed Aug 9, 2024

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yebai added a commit that referenced this pull request Aug 9, 2024

formatting all files (#80)

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yebai added a commit that referenced this pull request Aug 9, 2024

formatting all files (#80)

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Formatting all files #80

Formatting all files #80

yebai commented Aug 9, 2024

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	@test dropdims(mean(z_samples; dims=2); dims=2) ≈ μ rtol = realtype(1e-2)
	@test dropdims(var(z_samples; dims=2); dims=2) ≈ diag(Σ) rtol = realtype(
	1e-2
	)
	@test cov(z_samples; dims=2) ≈ Σ rtol = realtype(1e-2)

	q_ref, stats_ref, _ = optimize(
	rng, model, obj, q0, T; optimizer, show_progress=false, adtype
	)

	_, stats, _ = optimize(
	rng, model, obj, q0, T; show_progress=false, adtype, callback
	)

	q_first, _, state = optimize(
	rng, model, obj, q0, T_first; optimizer, show_progress=false, adtype
	)

	RepGradELBO(n_montecarlo; entropy=StickingTheLandingEntropy()),
	RepGradELBO(n_montecarlo; entropy = StickingTheLandingEntropy()),

	opt_st, params = update_variational_params!(
	typeof(q_init), opt_st, params, restructure, grad
	)

Formatting all files #80

Formatting all files #80

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