keep updating timing result

Author: zuhengxu

example/compare_traces/nextflow.config

@@ -0,0 +1,52 @@
+profiles {
+    standard {  
+        docker.enabled = true
+        process {
+            withLabel:containerized {
+                container = 'alexandrebouchardcote/default:0.1.6'
+            }
+        }
+    }
+    cluster {
+        apptainer.enabled = true
+        process {
+            scratch = true
+            executor = 'slurm'
+            cpus = 1
+            memory = 4.GB
+            time = '2h'
+            clusterOptions = "--nodes=1 --account $ALLOCATION_CODE"
+            withLabel:containerized {
+                container = 'alexandrebouchardcote/default:0.1.6'
+                module = 'apptainer'
+            }
+            withLabel:gpu {
+                clusterOptions = "--nodes=1 --account ${ALLOCATION_CODE}-gpu --gpus 1"
+            }
+        }
+    }
+}
+
+// Configs outside of profiles are applied to all profiles, but this only works correctly  
+// if they do not occur in same scope as things in profile scopes,
+// search 'Danger' in https://www.nextflow.io/docs/latest/config.html
+
+resume = true // comment out to disable resume 
+
+report {
+    enabled = true 
+    file = "report.html" 
+    overwrite = true
+}
+
+dag {
+    enabled = true 
+    file = "dag.html"
+    overwrite = true
+}
+
+timeline {
+    enabled = true 
+    file = "timeline.html"
+    overwrite = true
+}

example/compare_uhmc_hmc/nextflow.config

@@ -0,0 +1,52 @@
+profiles {
+    standard {  
+        docker.enabled = true
+        process {
+            withLabel:containerized {
+                container = 'alexandrebouchardcote/default:0.1.6'
+            }
+        }
+    }
+    cluster {
+        apptainer.enabled = true
+        process {
+            scratch = true
+            executor = 'slurm'
+            cpus = 1
+            memory = 4.GB
+            time = '2h'
+            clusterOptions = "--nodes=1 --account $ALLOCATION_CODE"
+            withLabel:containerized {
+                container = 'alexandrebouchardcote/default:0.1.6'
+                module = 'apptainer'
+            }
+            withLabel:gpu {
+                clusterOptions = "--nodes=1 --account ${ALLOCATION_CODE}-gpu --gpus 1"
+            }
+        }
+    }
+}
+
+// Configs outside of profiles are applied to all profiles, but this only works correctly  
+// if they do not occur in same scope as things in profile scopes,
+// search 'Danger' in https://www.nextflow.io/docs/latest/config.html
+
+resume = true // comment out to disable resume 
+
+report {
+    enabled = true 
+    file = "report.html" 
+    overwrite = true
+}
+
+dag {
+    enabled = true 
+    file = "dag.html"
+    overwrite = true
+}
+
+timeline {
+    enabled = true 
+    file = "timeline.html"
+    overwrite = true
+}

example/julia_env/Manifest.toml

@@ -1559,9 +1559,17 @@ version = "1.2.0"
 
 [[deps.NormalizingFlows]]
 deps = ["ADTypes", "Bijectors", "DifferentiationInterface", "Distributions", "DocStringExtensions", "LinearAlgebra", "Optimisers", "ProgressMeter", "Random", "StatsBase"]
-git-tree-sha1 = "17d89739ee13b1e62381d7ad5c6094d94cadf1bd"
+git-tree-sha1 = "fd54eff641bb9c5fbd0cd1991bae15f1a64ef0bf"
+repo-rev = "main"
+repo-url = "https://github.com/TuringLang/NormalizingFlows.jl.git"
 uuid = "50e4474d-9f12-44b7-af7a-91ab30ff6256"
-version = "0.2.0"
+version = "0.2.1"
+
+    [deps.NormalizingFlows.extensions]
+    NormalizingFlowsCUDAExt = "CUDA"
+
+    [deps.NormalizingFlows.weakdeps]
+    CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
 
 [[deps.Observables]]
 git-tree-sha1 = "7438a59546cf62428fc9d1bc94729146d37a7225"

example/julia_env/Model.jl

@@ -69,8 +69,6 @@ real_data_list = Set(["Brownian", "Sonar", "SparseRegression", "TReg", "LGCP"])
 LogDensityProblems.dimension(dist::ContinuousDistribution) = length(dist)
 LogDensityProblems.logdensity(dist::ContinuousDistribution, x) = logpdf(dist, x)
 
-
-
 # tracking logdensity prob
 mutable struct TrackedLogDensityProblem{Prob}
     n_density_evals  :: Int

example/julia_env/mfvi.jl

@@ -43,7 +43,7 @@ function mfvi(
 end
 
 # target = load_model("Banana")
-# flow, stats = mfvi(target; sample_per_iter = 10, max_iters = 10000)
+# flow, stats = mfvi(target; sample_per_iter = 10, max_iters = 1000)
 
 # function visualize(p::Bijectors.MultivariateTransformed, samples=rand(p, 1000))
 #     xrange = range(minimum(samples[1, :]) - 1, maximum(samples[1, :]) + 1; length=100)

example/julia_env/targets/brownian.jl

@@ -6,7 +6,8 @@ end
 function LogDensityProblems.capabilities(::Type{<:BrownianMotion})
     return LogDensityProblems.LogDensityOrder{2}()
 end
-function LogDensityProblems.logdensity(prob::BrownianMotion, θ)
+
+function LogDensityProblems.logdensity(prob::BrownianMotion, θ::AbstractVector)
     (; y, obs_idx) = prob
     x     = @view(θ[1:30])
     α_inn = StatsFuns.softplus(θ[31])

example/julia_env/targets/lgcp.jl

@@ -12,7 +12,7 @@ struct LogGaussianCoxProcess{
     logjac      :: LogJac
 end
 
-function LogDensityProblems.logdensity(prob::LogGaussianCoxProcess, f_white)
+function LogDensityProblems.logdensity(prob::LogGaussianCoxProcess, f_white::AbstractVector)
     (; area, counts, gp_mean, gp_cov_chol, logjac) = prob
     f    = gp_cov_chol * f_white + gp_mean
     ℓp_f = logpdf(MvNormal(Zeros(length(f)), I), f_white)

example/julia_env/targets/logreg_sonar.jl

@@ -5,7 +5,7 @@ struct LogisticRegression{XT, YT}
     y::YT
 end
 
-function LogDensityProblems.logdensity(prob::LogisticRegression, θ)
+function LogDensityProblems.logdensity(prob::LogisticRegression, θ::AbstractVector)
     (; X, y) = prob
 
     ℓp_θ   = mapreduce(normlogpdf, +, θ)

example/julia_env/targets/sparse_reg.jl

@@ -32,7 +32,7 @@ end
 
 LogDensityProblems.dimension(prob::SparseRegression) = prob.d
 
-function LogDensityProblems.logdensity(prob::SparseRegression, z)
+function LogDensityProblems.logdensity(prob::SparseRegression, z::AbstractVector)
     (; fs, rs, N, d) = prob
 
     # s := logσ²

example/julia_env/targets/t_reg.jl

@@ -37,7 +37,7 @@ end
 #######################
 # models ( t₅(Xβ, 1)-distirbution lin reg with heavy tailed prior, β ∼ Cauchy(0, 1))
 #######################
-function LogDensityProblems.logdensity(prob::StudentTRegression, β)
+function LogDensityProblems.logdensity(prob::StudentTRegression, β::AbstractVector)
     (; X, Y, N, d) = prob
 
     ℓp_β = -d*log(π) - sum(log1p, β.^2.0)