From 46f31e2b3480bd737a04c66d1715d364dec646e3 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Wed, 27 Sep 2023 09:49:15 +0200 Subject: [PATCH 001/171] trying with decay --- dev/artifacts.jl | 18 +- experiments/benchmarking/benchmarking.jl | 168 +++++++++++++----- experiments/california_housing.jl | 55 +++--- experiments/circles.jl | 43 ++--- experiments/data/data.jl | 11 +- experiments/experiment.jl | 70 +++++--- experiments/fmnist.jl | 78 ++++---- experiments/german_credit.jl | 55 +++--- experiments/gmsc.jl | 40 +++-- experiments/grid_search.jl | 142 +++++++++------ experiments/linearly_separable.jl | 42 ++--- experiments/mnist.jl | 76 ++++---- experiments/model_tuning.jl | 69 ++++--- experiments/models/additional_models.jl | 42 ++--- experiments/models/default_models.jl | 73 ++++---- experiments/models/models.jl | 68 ++++--- experiments/models/train_models.jl | 36 +++- experiments/moons.jl | 42 ++--- experiments/post_processing/artifacts.jl | 20 +-- experiments/post_processing/meta_data.jl | 49 +++-- experiments/post_processing/plotting.jl | 151 ++++++++++------ .../post_processing/post_processing.jl | 2 +- experiments/post_processing/results.jl | 77 +++++--- experiments/run_experiments.jl | 14 +- experiments/save_best.jl | 33 ++-- experiments/setup_env.jl | 60 +++---- experiments/upload_artifacts.jl | 2 +- experiments/utils.jl | 9 +- src/ECCCo.jl | 2 +- src/generator.jl | 57 ++++-- src/losses.jl | 21 ++- src/model.jl | 30 ++-- src/penalties.jl | 158 +++++++++------- src/sampling.jl | 48 ++--- src/utils.jl | 11 +- 35 files changed, 1133 insertions(+), 739 deletions(-) diff --git a/dev/artifacts.jl b/dev/artifacts.jl index 99ffb7f7..f60ac842 100644 --- a/dev/artifacts.jl +++ b/dev/artifacts.jl @@ -9,11 +9,11 @@ artifact_toml = LazyArtifacts.find_artifacts_toml(".") function generate_artifacts( datafiles; - artifact_name="artifacts-$VERSION", - root=".", - artifact_toml=joinpath(root, "Artifacts.toml"), - deploy=true, - tag=nothing, + artifact_name = "artifacts-$VERSION", + root = ".", + artifact_toml = joinpath(root, "Artifacts.toml"), + deploy = true, + tag = nothing, ) if isnothing(tag) tag = replace(lowercase(artifact_name), " " => "-") @@ -54,9 +54,9 @@ function generate_artifacts( artifact_toml, artifact_name, hash; - download_info=[(tarball_url, tarball_hash)], - lazy=true, - force=true, + download_info = [(tarball_url, tarball_hash)], + lazy = true, + force = true, ) end @@ -76,7 +76,7 @@ function generate_artifacts( end end -function get_git_remote_url(repo_path::String=".") +function get_git_remote_url(repo_path::String = ".") repo = LibGit2.GitRepo(repo_path) origin = LibGit2.get(LibGit2.GitRemote, repo, "origin") return LibGit2.url(origin) diff --git a/experiments/benchmarking/benchmarking.jl b/experiments/benchmarking/benchmarking.jl index 61164009..83f94764 100644 --- a/experiments/benchmarking/benchmarking.jl +++ b/experiments/benchmarking/benchmarking.jl @@ -1,14 +1,15 @@ function default_generators(; - Λ::AbstractArray=[0.25, 0.75, 0.75], - Λ_Δ::AbstractArray=Λ, - use_variants::Bool=true, - use_class_loss::Bool=false, - opt=Flux.Optimise.Descent(0.01), - niter_eccco::Union{Nothing,Int}=nothing, - nsamples::Union{Nothing,Int}=nothing, - nmin::Union{Nothing,Int}=nothing, - reg_strength::Real=0.5, - dim_reduction::Bool=false, + Λ::AbstractArray = [0.25, 0.75, 0.75], + Λ_Δ::AbstractArray = Λ, + use_variants::Bool = true, + use_class_loss::Bool = false, + opt = Flux.Optimise.Descent(0.01), + niter_eccco::Union{Nothing,Int} = nothing, + nsamples::Union{Nothing,Int} = nothing, + nmin::Union{Nothing,Int} = nothing, + reg_strength::Real = 0.5, + decay::Tuple = (0.1, 5), + dim_reduction::Bool = false, ) @info "Begin benchmarking counterfactual explanations." @@ -17,23 +18,91 @@ function default_generators(; if use_variants generator_dict = Dict( - "Wachter" => WachterGenerator(λ=λ₁, opt=opt), - "REVISE" => REVISEGenerator(λ=λ₁, opt=opt), - "Schut" => GreedyGenerator(η=opt.eta), - "ECCCo" => ECCCoGenerator(λ=Λ, opt=opt, use_class_loss=use_class_loss, nsamples=nsamples, nmin=nmin, niter=niter_eccco), - "ECCCo (no CP)" => ECCCoGenerator(λ=[λ₁, 0.0, λ₃], opt=opt, use_class_loss=use_class_loss, nsamples=nsamples, nmin=nmin, niter=niter_eccco), - "ECCCo (no EBM)" => ECCCoGenerator(λ=[λ₁, λ₂, 0.0], opt=opt, use_class_loss=use_class_loss, nsamples=nsamples, nmin=nmin, niter=niter_eccco), - "ECCCo-Δ" => ECCCoGenerator(λ=Λ_Δ, opt=opt, use_class_loss=use_class_loss, use_energy_delta=true, nsamples=nsamples, nmin=nmin, niter=niter_eccco, reg_strength = reg_strength), - "ECCCo-Δ (no CP)" => ECCCoGenerator(λ=[λ₁_Δ, 0.0, λ₃_Δ], opt=opt, use_class_loss=use_class_loss, use_energy_delta=true, nsamples=nsamples, nmin=nmin, niter=niter_eccco, reg_strength=reg_strength), - "ECCCo-Δ (no EBM)" => ECCCoGenerator(λ=[λ₁_Δ, λ₂_Δ, 0.0], opt=opt, use_class_loss=use_class_loss, use_energy_delta=true, nsamples=nsamples, nmin=nmin, niter=niter_eccco, reg_strength=reg_strength), + "Wachter" => WachterGenerator(λ = λ₁, opt = opt), + "REVISE" => REVISEGenerator(λ = λ₁, opt = opt), + "Schut" => GreedyGenerator(η = opt.eta), + "ECCCo" => ECCCoGenerator( + λ = Λ, + opt = opt, + use_class_loss = use_class_loss, + nsamples = nsamples, + nmin = nmin, + niter = niter_eccco, + ), + "ECCCo (no CP)" => ECCCoGenerator( + λ = [λ₁, 0.0, λ₃], + opt = opt, + use_class_loss = use_class_loss, + nsamples = nsamples, + nmin = nmin, + niter = niter_eccco, + ), + "ECCCo (no EBM)" => ECCCoGenerator( + λ = [λ₁, λ₂, 0.0], + opt = opt, + use_class_loss = use_class_loss, + nsamples = nsamples, + nmin = nmin, + niter = niter_eccco, + ), + "ECCCo-Δ" => ECCCoGenerator( + λ = Λ_Δ, + opt = opt, + use_class_loss = use_class_loss, + use_energy_delta = true, + nsamples = nsamples, + nmin = nmin, + niter = niter_eccco, + reg_strength = reg_strength, + decay = decay, + ), + "ECCCo-Δ (no CP)" => ECCCoGenerator( + λ = [λ₁_Δ, 0.0, λ₃_Δ], + opt = opt, + use_class_loss = use_class_loss, + use_energy_delta = true, + nsamples = nsamples, + nmin = nmin, + niter = niter_eccco, + reg_strength = reg_strength, + decay=decay, + ), + "ECCCo-Δ (no EBM)" => ECCCoGenerator( + λ = [λ₁_Δ, λ₂_Δ, 0.0], + opt = opt, + use_class_loss = use_class_loss, + use_energy_delta = true, + nsamples = nsamples, + nmin = nmin, + niter = niter_eccco, + reg_strength = reg_strength, + decay=decay, + ), ) else generator_dict = Dict( - "Wachter" => WachterGenerator(λ=λ₁, opt=opt), - "REVISE" => REVISEGenerator(λ=λ₁, opt=opt), + "Wachter" => WachterGenerator(λ = λ₁, opt = opt), + "REVISE" => REVISEGenerator(λ = λ₁, opt = opt), "Schut" => GreedyGenerator(), - "ECCCo" => ECCCoGenerator(λ=Λ, opt=opt, use_class_loss=use_class_loss, nsamples=nsamples, nmin=nmin, niter=niter_eccco), - "ECCCo-Δ" => ECCCoGenerator(λ=Λ_Δ, opt=opt, use_class_loss=use_class_loss, use_energy_delta=true, nsamples=nsamples, nmin=nmin, niter=niter_eccco, reg_strength=reg_strength), + "ECCCo" => ECCCoGenerator( + λ = Λ, + opt = opt, + use_class_loss = use_class_loss, + nsamples = nsamples, + nmin = nmin, + niter = niter_eccco, + ), + "ECCCo-Δ" => ECCCoGenerator( + λ = Λ_Δ, + opt = opt, + use_class_loss = use_class_loss, + use_energy_delta = true, + nsamples = nsamples, + nmin = nmin, + niter = niter_eccco, + reg_strength = reg_strength, + decay=decay, + ), ) end @@ -42,9 +111,17 @@ function default_generators(; if dim_reduction eccco_latent = Dict( "ECCCo-Δ (latent)" => ECCCoGenerator( - λ=Λ_Δ, opt=opt, use_class_loss=use_class_loss, use_energy_delta=true, nsamples=nsamples, nmin=nmin, niter=niter_eccco, reg_strength=reg_strength, - dim_reduction=dim_reduction - ) + λ = Λ_Δ, + opt = opt, + use_class_loss = use_class_loss, + use_energy_delta = true, + nsamples = nsamples, + nmin = nmin, + niter = niter_eccco, + reg_strength = reg_strength, + decay=decay, + dim_reduction = dim_reduction, + ), ) generator_dict = merge(generator_dict, eccco_latent) end @@ -72,31 +149,32 @@ function run_benchmark(exper::Experiment, model_dict::Dict) # Benchmark generators: if isnothing(generator_dict) generator_dict = default_generators(; - Λ=exper.Λ, - Λ_Δ=exper.Λ_Δ, - use_variants=exper.use_variants, - use_class_loss=exper.use_class_loss, - opt=exper.opt, - nsamples=exper.nsamples, - nmin=exper.nmin, - reg_strength=exper.reg_strength, - dim_reduction=exper.dim_reduction, + Λ = exper.Λ, + Λ_Δ = exper.Λ_Δ, + use_variants = exper.use_variants, + use_class_loss = exper.use_class_loss, + opt = exper.opt, + nsamples = exper.nsamples, + nmin = exper.nmin, + reg_strength = exper.reg_strength, + dim_reduction = exper.dim_reduction, + decay = exper.decay, ) end # Run benchmark: bmk = benchmark( counterfactual_data; - models=model_dict, - generators=generator_dict, - measure=measures, - suppress_training=true, dataname=dataname, - n_individuals=n_individuals, - initialization=:identity, - converge_when=:generator_conditions, - parallelizer=parallelizer, - store_ce=exper.store_ce, + models = model_dict, + generators = generator_dict, + measure = measures, + suppress_training = true, + dataname = dataname, + n_individuals = n_individuals, + initialization = :identity, + converge_when = :generator_conditions, + parallelizer = parallelizer, + store_ce = exper.store_ce, ) return bmk, generator_dict end - diff --git a/experiments/california_housing.jl b/experiments/california_housing.jl index 4a486a1b..bd46c0da 100644 --- a/experiments/california_housing.jl +++ b/experiments/california_housing.jl @@ -1,18 +1,23 @@ # Data: dataname = "California Housing" -counterfactual_data, test_data = train_test_split(load_california_housing(nothing); test_size=TEST_SIZE) +counterfactual_data, test_data = + train_test_split(load_california_housing(nothing); test_size = TEST_SIZE) # VAE: using CounterfactualExplanations.GenerativeModels: VAE, train! X = counterfactual_data.X y = counterfactual_data.output_encoder.y -vae = VAE(size(X, 1); nll=Flux.Losses.mse, epochs=100, λ=0.01, latent_dim=5) +vae = VAE(size(X, 1); nll = Flux.Losses.mse, epochs = 100, λ = 0.01, latent_dim = 5) train!(vae, X, y) counterfactual_data.generative_model = vae # Dimensionality reduction: maxout_dim = vae.params.latent_dim -counterfactual_data.dt = MultivariateStats.fit(MultivariateStats.PCA, counterfactual_data.X; maxoutdim=maxout_dim); +counterfactual_data.dt = MultivariateStats.fit( + MultivariateStats.PCA, + counterfactual_data.X; + maxoutdim = maxout_dim, +); # Model tuning: model_tuning_params = DEFAULT_MODEL_TUNING_LARGE @@ -22,18 +27,18 @@ tuning_params = DEFAULT_GENERATOR_TUNING_LARGE # Parameter choices: params = ( - n_hidden=32, - activation=Flux.relu, - builder=default_builder(n_hidden=32, n_layers=3, activation=Flux.relu), - α=[1.0, 1.0, 1e-1], - sampling_batch_size=10, - sampling_steps=30, - use_ensembling=true, - opt=Flux.Optimise.Descent(0.05), - Λ=[0.1, 0.1, 0.1], - reg_strength=0.0, - n_individuals=25, - dim_reduction=true, + n_hidden = 32, + activation = Flux.relu, + builder = default_builder(n_hidden = 32, n_layers = 3, activation = Flux.relu), + α = [1.0, 1.0, 1e-1], + sampling_batch_size = 10, + sampling_steps = 30, + use_ensembling = true, + opt = Flux.Optimise.Descent(0.05), + Λ = [0.1, 0.1, 0.1], + reg_strength = 0.0, + n_individuals = 25, + dim_reduction = true, ) # Best grid search params: @@ -41,10 +46,11 @@ append_best_params!(params, dataname) if GRID_SEARCH grid_search( - counterfactual_data, test_data; - dataname=dataname, - tuning_params=tuning_params, - params... + counterfactual_data, + test_data; + dataname = dataname, + tuning_params = tuning_params, + params..., ) elseif FROM_GRID_SEARCH outcomes_file_path = joinpath( @@ -56,9 +62,10 @@ elseif FROM_GRID_SEARCH bmk2csv(dataname) else run_experiment( - counterfactual_data, test_data; - dataname=dataname, - model_tuning_params=model_tuning_params, - params... + counterfactual_data, + test_data; + dataname = dataname, + model_tuning_params = model_tuning_params, + params..., ) -end \ No newline at end of file +end diff --git a/experiments/circles.jl b/experiments/circles.jl index 167ae9ae..684f72db 100644 --- a/experiments/circles.jl +++ b/experiments/circles.jl @@ -1,7 +1,8 @@ # Data: dataname = "Circles" n_obs = Int(1000 / (1.0 - TEST_SIZE)) -counterfactual_data, test_data = train_test_split(load_circles(n_obs; noise=0.05, factor=0.5); test_size=TEST_SIZE) +counterfactual_data, test_data = + train_test_split(load_circles(n_obs; noise = 0.05, factor = 0.5); test_size = TEST_SIZE) # Model tuning: model_tuning_params = DEFAULT_MODEL_TUNING_SMALL @@ -12,16 +13,16 @@ tuning_params = DEFAULT_GENERATOR_TUNING # Parameter choices: # These are the parameter choices originally used in the paper that were manually fine-tuned for the JEM. params = ( - use_tuned=false, - n_hidden=32, - n_layers=3, - activation=Flux.swish, - epochs=100, - α=[1.0, 1.0, 1e-2], - sampling_steps=30, - opt=Flux.Optimise.Descent(0.05), - Λ=[0.1, 0.1, 0.05], - reg_strength=1.0, + use_tuned = false, + n_hidden = 32, + n_layers = 3, + activation = Flux.swish, + epochs = 100, + α = [1.0, 1.0, 1e-2], + sampling_steps = 30, + opt = Flux.Optimise.Descent(0.05), + Λ = [0.1, 0.1, 0.05], + reg_strength = 1.0, ) # Best grid search params: @@ -29,10 +30,11 @@ append_best_params!(params, dataname) if GRID_SEARCH grid_search( - counterfactual_data, test_data; - dataname=dataname, - tuning_params=tuning_params, - params... + counterfactual_data, + test_data; + dataname = dataname, + tuning_params = tuning_params, + params..., ) elseif FROM_GRID_SEARCH outcomes_file_path = joinpath( @@ -44,9 +46,10 @@ elseif FROM_GRID_SEARCH bmk2csv(dataname) else run_experiment( - counterfactual_data, test_data; - dataname=dataname, - model_tuning_params=model_tuning_params, - params... + counterfactual_data, + test_data; + dataname = dataname, + model_tuning_params = model_tuning_params, + params..., ) -end \ No newline at end of file +end diff --git a/experiments/data/data.jl b/experiments/data/data.jl index 58965d3a..e81e03f7 100644 --- a/experiments/data/data.jl +++ b/experiments/data/data.jl @@ -20,9 +20,10 @@ function _prepare_data(exper::Experiment) # JEM parameters: 𝒟y = Categorical(ones(output_dim) ./ output_dim) sampler = ConditionalSampler( - 𝒟x, 𝒟y, - input_size=(input_dim,), - batch_size=sampling_batch_size, + 𝒟x, + 𝒟y, + input_size = (input_dim,), + batch_size = sampling_batch_size, ) return X, labels, n_obs, batch_size, sampler end @@ -33,11 +34,11 @@ function meta_data(exper::Experiment) end function prepare_data(exper::Experiment) - X, labels, _, _, sampler = _prepare_data(exper::Experiment) + X, labels, _, _, sampler = _prepare_data(exper::Experiment) return X, labels, sampler end function batch_size(exper::Experiment) _, _, _, batch_size, _ = _prepare_data(exper::Experiment) return batch_size -end \ No newline at end of file +end diff --git a/experiments/experiment.jl b/experiments/experiment.jl index 632ba235..333e7478 100644 --- a/experiments/experiment.jl +++ b/experiments/experiment.jl @@ -17,7 +17,8 @@ Base.@kwdef struct Experiment n_hidden::Int = 32 n_layers::Int = 3 activation::Function = Flux.relu - builder::Union{Nothing,MLJFlux.Builder} = default_builder(n_hidden=n_hidden, n_layers=n_layers, activation=activation) + builder::Union{Nothing,MLJFlux.Builder} = + default_builder(n_hidden = n_hidden, n_layers = n_layers, activation = activation) α::AbstractArray = [1.0, 1.0, 1e-1] n_ens::Int = 5 use_ensembling::Bool = true @@ -31,13 +32,14 @@ Base.@kwdef struct Experiment Λ::AbstractArray = [0.25, 0.75, 0.75] Λ_Δ::AbstractArray = Λ opt::Flux.Optimise.AbstractOptimiser = Flux.Optimise.Descent(0.01) - parallelizer::Union{Nothing, AbstractParallelizer} = PLZ + parallelizer::Union{Nothing,AbstractParallelizer} = PLZ nsamples::Union{Nothing,Int} = nothing nmin::Union{Nothing,Int} = nothing finaliser::Function = Flux.softmax loss::Function = Flux.Losses.crossentropy train_parallel::Bool = false reg_strength::Real = 0.1 + decay::Tuple = (0.1, 5) niter_eccco::Union{Nothing,Int} = nothing model_tuning_params::NamedTuple = DEFAULT_MODEL_TUNING_SMALL use_tuned::Bool = true @@ -48,9 +50,9 @@ end "A container to hold the results of an experiment." mutable struct ExperimentOutcome exper::Experiment - model_dict::Union{Nothing, Dict} - generator_dict::Union{Nothing, Dict} - bmk::Union{Nothing, Benchmark} + model_dict::Union{Nothing,Dict} + generator_dict::Union{Nothing,Dict} + bmk::Union{Nothing,Benchmark} end """ @@ -58,11 +60,16 @@ end Train the models specified by `exper` and store them in `outcome`. """ -function train_models!(outcome::ExperimentOutcome, exper::Experiment; save_models::Bool=true, save_meta::Bool=false) - model_dict = prepare_models(exper; save_models=save_models) +function train_models!( + outcome::ExperimentOutcome, + exper::Experiment; + save_models::Bool = true, + save_meta::Bool = false, +) + model_dict = prepare_models(exper; save_models = save_models) outcome.model_dict = model_dict if !(is_multi_processed(exper) && MPI.Comm_rank(exper.parallelizer.comm) != 0) - meta_model_performance(outcome; save_output=save_meta) + meta_model_performance(outcome; save_output = save_meta) end end @@ -82,10 +89,15 @@ end Run the experiment specified by `exper`. """ -function run_experiment(exper::Experiment; save_output::Bool=true, only_models::Bool=ONLY_MODELS) - +function run_experiment( + exper::Experiment; + save_output::Bool = true, + only_models::Bool = ONLY_MODELS, +) + # Setup - if save_output && !(is_multi_processed(exper) && MPI.Comm_rank(exper.parallelizer.comm) != 0) + if save_output && + !(is_multi_processed(exper) && MPI.Comm_rank(exper.parallelizer.comm) != 0) @info "All results will be saved to $(exper.output_path)." isdir(exper.output_path) || mkdir(exper.output_path) @info "All parameter choices will be saved to $(exper.params_path)." @@ -103,10 +115,10 @@ function run_experiment(exper::Experiment; save_output::Bool=true, only_models:: # Model training: if only_models - train_models!(outcome, exper; save_models=save_output, save_meta=true) + train_models!(outcome, exper; save_models = save_output, save_meta = true) return outcome else - train_models!(outcome, exper; save_models=save_output) + train_models!(outcome, exper; save_models = save_output) end # Benchmark: @@ -116,10 +128,17 @@ function run_experiment(exper::Experiment; save_output::Bool=true, only_models:: end # Save data: - if save_output && !(is_multi_processed(exper) && MPI.Comm_rank(exper.parallelizer.comm) != 0) - Serialization.serialize(joinpath(exper.output_path, "$(exper.save_name)_outcome.jls"), outcome) - Serialization.serialize(joinpath(exper.output_path, "$(exper.save_name)_bmk.jls"), outcome.bmk) - meta(outcome; save_output=true) + if save_output && + !(is_multi_processed(exper) && MPI.Comm_rank(exper.parallelizer.comm) != 0) + Serialization.serialize( + joinpath(exper.output_path, "$(exper.save_name)_outcome.jls"), + outcome, + ) + Serialization.serialize( + joinpath(exper.output_path, "$(exper.save_name)_bmk.jls"), + outcome.bmk, + ) + meta(outcome; save_output = true) end # Final barrier: @@ -136,14 +155,19 @@ end Overload the `run_experiment` function to allow for passing in `CounterfactualData` objects and other keyword arguments. """ -function run_experiment(counterfactual_data::CounterfactualData, test_data::CounterfactualData; save_output::Bool=true, kwargs...) +function run_experiment( + counterfactual_data::CounterfactualData, + test_data::CounterfactualData; + save_output::Bool = true, + kwargs..., +) # Parameters: exper = Experiment(; - counterfactual_data=counterfactual_data, - test_data=test_data, - kwargs... + counterfactual_data = counterfactual_data, + test_data = test_data, + kwargs..., ) - return run_experiment(exper; save_output=save_output) + return run_experiment(exper; save_output = save_output) end # Pre-trained models: @@ -159,4 +183,4 @@ function pretrained_path(exper::Experiment) Pkg.Artifacts.download_artifact(ARTIFACT_HASH, ARTIFACT_TOML) return joinpath(LATEST_ARTIFACT_PATH, "results") end -end \ No newline at end of file +end diff --git a/experiments/fmnist.jl b/experiments/fmnist.jl index 54a46ef8..c7d6a191 100644 --- a/experiments/fmnist.jl +++ b/experiments/fmnist.jl @@ -4,7 +4,10 @@ n_obs = 10000 counterfactual_data = load_fashion_mnist(n_obs) counterfactual_data.X = ECCCo.pre_process.(counterfactual_data.X) # Adjust domain constraints to account for noise added during pre-processing: -counterfactual_data.domain = fill((minimum(counterfactual_data.X), maximum(counterfactual_data.X)), size(counterfactual_data.X, 1)) +counterfactual_data.domain = fill( + (minimum(counterfactual_data.X), maximum(counterfactual_data.X)), + size(counterfactual_data.X, 1), +) # VAE (trained on full dataset): using CounterfactualExplanations.Models: load_fashion_mnist_vae @@ -16,52 +19,56 @@ test_data = load_fashion_mnist_test() # Dimensionality reduction: maxout_dim = vae.params.latent_dim -counterfactual_data.dt = MultivariateStats.fit(MultivariateStats.PCA, counterfactual_data.X; maxoutdim=maxout_dim); +counterfactual_data.dt = MultivariateStats.fit( + MultivariateStats.PCA, + counterfactual_data.X; + maxoutdim = maxout_dim, +); # Model tuning: model_tuning_params = DEFAULT_MODEL_TUNING_LARGE # Tuning parameters: tuning_params = DEFAULT_GENERATOR_TUNING -tuning_params = (; tuning_params..., Λ=[tuning_params.Λ[2:end]..., [0.1, 0.1, 3.0]]) +tuning_params = (; tuning_params..., Λ = [tuning_params.Λ[2:end]..., [0.1, 0.1, 3.0]]) # Additional models: -add_models = Dict( - "LeNet-5" => lenet5, -) +add_models = Dict("LeNet-5" => lenet5) # CE measures (add cosine distance): -ce_measures = [CE_MEASURES..., ECCCo.distance_from_energy_ssim, ECCCo.distance_from_targets_ssim] +ce_measures = + [CE_MEASURES..., ECCCo.distance_from_energy_ssim, ECCCo.distance_from_targets_ssim] # Parameter choices: params = ( - n_individuals=N_IND_SPECIFIED ? N_IND : 100, - builder=default_builder(n_hidden=128, n_layers=1, activation=Flux.swish), - 𝒟x=Uniform(-1.0, 1.0), - α=[1.0, 1.0, 1e-2], - sampling_batch_size=10, - sampling_steps=25, - use_ensembling=true, - use_variants=false, - additional_models=add_models, - epochs=100, - nsamples=10, - nmin=1, - niter_eccco=10, - Λ=[0.01, 0.25, 0.25], - Λ_Δ=[0.01, 0.1, 0.3], - opt=Flux.Optimise.Descent(0.1), - reg_strength=0.0, - ce_measures=ce_measures, - dim_reduction=true, + n_individuals = N_IND_SPECIFIED ? N_IND : 100, + builder = default_builder(n_hidden = 128, n_layers = 1, activation = Flux.swish), + 𝒟x = Uniform(-1.0, 1.0), + α = [1.0, 1.0, 1e-2], + sampling_batch_size = 10, + sampling_steps = 25, + use_ensembling = true, + use_variants = false, + additional_models = add_models, + epochs = 100, + nsamples = 10, + nmin = 1, + niter_eccco = 10, + Λ = [0.01, 0.25, 0.25], + Λ_Δ = [0.01, 0.1, 0.3], + opt = Flux.Optimise.Descent(0.1), + reg_strength = 0.0, + ce_measures = ce_measures, + dim_reduction = true, ) if GRID_SEARCH grid_search( - counterfactual_data, test_data; - dataname=dataname, - tuning_params=tuning_params, - params... + counterfactual_data, + test_data; + dataname = dataname, + tuning_params = tuning_params, + params..., ) elseif FROM_GRID_SEARCH outcomes_file_path = joinpath( @@ -73,9 +80,10 @@ elseif FROM_GRID_SEARCH bmk2csv(dataname) else run_experiment( - counterfactual_data, test_data; - dataname=dataname, - model_tuning_params=model_tuning_params, - params... + counterfactual_data, + test_data; + dataname = dataname, + model_tuning_params = model_tuning_params, + params..., ) -end \ No newline at end of file +end diff --git a/experiments/german_credit.jl b/experiments/german_credit.jl index e64ba13c..e87ed290 100644 --- a/experiments/german_credit.jl +++ b/experiments/german_credit.jl @@ -1,18 +1,23 @@ # Data: dataname = "German Credit" -counterfactual_data, test_data = train_test_split(load_german_credit(nothing); test_size=TEST_SIZE) +counterfactual_data, test_data = + train_test_split(load_german_credit(nothing); test_size = TEST_SIZE) # VAE: using CounterfactualExplanations.GenerativeModels: VAE, train! X = counterfactual_data.X y = counterfactual_data.output_encoder.y -vae = VAE(size(X,1); nll=Flux.Losses.mse, epochs=100, λ=0.01, latent_dim=5) +vae = VAE(size(X, 1); nll = Flux.Losses.mse, epochs = 100, λ = 0.01, latent_dim = 5) train!(vae, X, y) counterfactual_data.generative_model = vae # Dimensionality reduction: maxout_dim = vae.params.latent_dim -counterfactual_data.dt = MultivariateStats.fit(MultivariateStats.PCA, counterfactual_data.X; maxoutdim=maxout_dim); +counterfactual_data.dt = MultivariateStats.fit( + MultivariateStats.PCA, + counterfactual_data.X; + maxoutdim = maxout_dim, +); # Model tuning: model_tuning_params = DEFAULT_MODEL_TUNING_LARGE @@ -22,18 +27,18 @@ tuning_params = DEFAULT_GENERATOR_TUNING_LARGE # Parameter choices: params = ( - n_hidden=32, - activation=Flux.relu, - builder=default_builder(n_hidden=32, n_layers=3, activation=Flux.relu), - α=[1.0, 1.0, 1e-1], - sampling_batch_size=10, - sampling_steps=30, - use_ensembling=true, - opt=Flux.Optimise.Descent(0.05), - Λ=[0.2, 0.2, 0.2], - reg_strength=0.5, - n_individuals=25, - dim_reduction=true, + n_hidden = 32, + activation = Flux.relu, + builder = default_builder(n_hidden = 32, n_layers = 3, activation = Flux.relu), + α = [1.0, 1.0, 1e-1], + sampling_batch_size = 10, + sampling_steps = 30, + use_ensembling = true, + opt = Flux.Optimise.Descent(0.05), + Λ = [0.2, 0.2, 0.2], + reg_strength = 0.5, + n_individuals = 25, + dim_reduction = true, ) # Best grid search params: @@ -41,10 +46,11 @@ append_best_params!(params, dataname) if GRID_SEARCH grid_search( - counterfactual_data, test_data; - dataname=dataname, - tuning_params=tuning_params, - params... + counterfactual_data, + test_data; + dataname = dataname, + tuning_params = tuning_params, + params..., ) elseif FROM_GRID_SEARCH outcomes_file_path = joinpath( @@ -56,9 +62,10 @@ elseif FROM_GRID_SEARCH bmk2csv(dataname) else run_experiment( - counterfactual_data, test_data; - dataname=dataname, - model_tuning_params=model_tuning_params, - params... + counterfactual_data, + test_data; + dataname = dataname, + model_tuning_params = model_tuning_params, + params..., ) -end \ No newline at end of file +end diff --git a/experiments/gmsc.jl b/experiments/gmsc.jl index 9f5ab2c5..8067eaa8 100644 --- a/experiments/gmsc.jl +++ b/experiments/gmsc.jl @@ -1,19 +1,23 @@ # Data: dataname = "GMSC" -counterfactual_data, test_data = train_test_split(load_gmsc(nothing); test_size=TEST_SIZE) +counterfactual_data, test_data = train_test_split(load_gmsc(nothing); test_size = TEST_SIZE) nobs = size(counterfactual_data.X, 2) # VAE: using CounterfactualExplanations.GenerativeModels: VAE, train! X = counterfactual_data.X y = counterfactual_data.output_encoder.y -vae = VAE(size(X, 1); nll=Flux.Losses.mse, epochs=100, λ=0.01, latent_dim=5) +vae = VAE(size(X, 1); nll = Flux.Losses.mse, epochs = 100, λ = 0.01, latent_dim = 5) train!(vae, X, y) counterfactual_data.generative_model = vae # Dimensionality reduction: maxout_dim = vae.params.latent_dim -counterfactual_data.dt = MultivariateStats.fit(MultivariateStats.PCA, counterfactual_data.X; maxoutdim=maxout_dim); +counterfactual_data.dt = MultivariateStats.fit( + MultivariateStats.PCA, + counterfactual_data.X; + maxoutdim = maxout_dim, +); # Model tuning: model_tuning_params = DEFAULT_MODEL_TUNING_LARGE @@ -23,18 +27,18 @@ tuning_params = DEFAULT_GENERATOR_TUNING_LARGE # Parameter choices: params = ( - n_hidden=32, - activation=Flux.relu, - builder=default_builder(n_hidden=32, n_layers=3, activation=Flux.relu), + n_hidden = 32, + activation = Flux.relu, + builder = default_builder(n_hidden = 32, n_layers = 3, activation = Flux.relu), α = [1.0, 1.0, 1e-1], sampling_batch_size = 10, sampling_steps = 30, use_ensembling = true, - opt=Flux.Optimise.Descent(0.05), + opt = Flux.Optimise.Descent(0.05), Λ = [0.1, 0.1, 0.1], reg_strength = 0.0, - n_individuals=25, - dim_reduction=true, + n_individuals = 25, + dim_reduction = true, ) # Best grid search params: @@ -42,10 +46,11 @@ append_best_params!(params, dataname) if GRID_SEARCH grid_search( - counterfactual_data, test_data; - dataname=dataname, - tuning_params=tuning_params, - params... + counterfactual_data, + test_data; + dataname = dataname, + tuning_params = tuning_params, + params..., ) elseif FROM_GRID_SEARCH outcomes_file_path = joinpath( @@ -57,9 +62,10 @@ elseif FROM_GRID_SEARCH bmk2csv(dataname) else run_experiment( - counterfactual_data, test_data; - dataname=dataname, - model_tuning_params=model_tuning_params, - params... + counterfactual_data, + test_data; + dataname = dataname, + model_tuning_params = model_tuning_params, + params..., ) end diff --git a/experiments/grid_search.jl b/experiments/grid_search.jl index 323c47c9..fc0efebb 100644 --- a/experiments/grid_search.jl +++ b/experiments/grid_search.jl @@ -13,7 +13,7 @@ function grid_search( couterfactual_data::CounterfactualData, test_data::CounterfactualData; dataname::String, - n_individuals::Int=N_IND, + n_individuals::Int = N_IND, tuning_params::NamedTuple, kwargs..., ) @@ -25,17 +25,18 @@ function grid_search( tuning_params = [Pair.(k, vals) for (k, vals) in pairs(tuning_params)] grid = Iterators.product(tuning_params...) outcomes = Dict{Any,Any}() - + # Search: counter = 1 for tuning_params in grid @info "Running experiment $(counter)/$(length(grid)) with tuning parameters: $(tuning_params)" outcome = run_experiment( - counterfactual_data, test_data; - save_output=false, - dataname=dataname, - n_individuals=n_individuals, - output_path=grid_search_path, + counterfactual_data, + test_data; + save_output = false, + dataname = dataname, + n_individuals = n_individuals, + output_path = grid_search_path, tuning_params..., kwargs..., ) @@ -45,10 +46,31 @@ function grid_search( # Save: if !(is_multi_processed(PLZ) && MPI.Comm_rank(PLZ.comm) != 0) - Serialization.serialize(joinpath(grid_search_path, "$(replace(lowercase(dataname), " " => "_")).jls"), outcomes) - Serialization.serialize(joinpath(grid_search_path, "$(replace(lowercase(dataname), " " => "_"))_best.jls"), best_absolute_outcome(outcomes)) - Serialization.serialize(joinpath(grid_search_path, "$(replace(lowercase(dataname), " " => "_"))_best_eccco.jls"), best_absolute_outcome_eccco(outcomes)) - Serialization.serialize(joinpath(grid_search_path, "$(replace(lowercase(dataname), " " => "_"))_best_eccco_delta.jls"), best_absolute_outcome_eccco_Δ(outcomes)) + Serialization.serialize( + joinpath(grid_search_path, "$(replace(lowercase(dataname), " " => "_")).jls"), + outcomes, + ) + Serialization.serialize( + joinpath( + grid_search_path, + "$(replace(lowercase(dataname), " " => "_"))_best.jls", + ), + best_absolute_outcome(outcomes), + ) + Serialization.serialize( + joinpath( + grid_search_path, + "$(replace(lowercase(dataname), " " => "_"))_best_eccco.jls", + ), + best_absolute_outcome_eccco(outcomes), + ) + Serialization.serialize( + joinpath( + grid_search_path, + "$(replace(lowercase(dataname), " " => "_"))_best_eccco_delta.jls", + ), + best_absolute_outcome_eccco_Δ(outcomes), + ) end end @@ -61,18 +83,9 @@ const ALL_ECCCO_NAMES = [ "ECCCo-Δ (no EBM)", ] -const ECCCO_NAMES = [ - "ECCCo", - "ECCCo (no CP)", - "ECCCo (no EBM)", -] +const ECCCO_NAMES = ["ECCCo", "ECCCo (no CP)", "ECCCo (no EBM)"] -const ECCCo_Δ_NAMES = [ - "ECCCo-Δ", - "ECCCo-Δ (no CP)", - "ECCCo-Δ (no EBM)", - "ECCCo-Δ (latent)", -] +const ECCCo_Δ_NAMES = ["ECCCo-Δ", "ECCCo-Δ (no CP)", "ECCCo-Δ (no EBM)", "ECCCo-Δ (latent)"] """ best_outcome(outcomes; generator=ECCCO_NAMES, measure=["distance_from_energy", "distance_from_targets"]) @@ -80,35 +93,43 @@ const ECCCo_Δ_NAMES = [ Returns the best outcome from grid search results. The best outcome is defined as the one with the lowest average rank across all datasets and variables for the specified generator and measure. """ function best_rank_outcome( - outcomes::Dict; - generator=ALL_ECCCO_NAMES, - measure=["distance_from_energy_l2", "distance_from_targets_l2"], - model::Union{Nothing,AbstractArray}=nothing, - weights::Union{Nothing,AbstractArray}=nothing + outcomes::Dict; + generator = ALL_ECCCO_NAMES, + measure = ["distance_from_energy_l2", "distance_from_targets_l2"], + model::Union{Nothing,AbstractArray} = nothing, + weights::Union{Nothing,AbstractArray} = nothing, ) weights = isnothing(weights) ? ones(length(measure)) : weights - df_weights = DataFrame(variable=measure, weight=weights) + df_weights = DataFrame(variable = measure, weight = weights) ranks = [] for (params, outcome) in outcomes - _ranks = generator_rank(outcome; generator=generator, measure=measure, model=model) |> - x -> leftjoin(x, df_weights, on=:variable) |> - x -> x.avg_rank .* x.weight |> - x -> (sum(x) / length(x))[1] + _ranks = + generator_rank( + outcome; + generator = generator, + measure = measure, + model = model, + ) |> + x -> + leftjoin(x, df_weights, on = :variable) |> + x -> x.avg_rank .* x.weight |> x -> (sum(x)/length(x))[1] push!(ranks, _ranks) end best_index = argmin(ranks) best_outcome = ( params = collect(keys(outcomes))[best_index], - outcome = collect(values(outcomes))[best_index] + outcome = collect(values(outcomes))[best_index], ) return best_outcome end -best_rank_eccco(outcomes; kwrgs...) = best_rank_outcome(outcomes; generator=ECCCO_NAMES, kwrgs...) +best_rank_eccco(outcomes; kwrgs...) = + best_rank_outcome(outcomes; generator = ECCCO_NAMES, kwrgs...) -best_rank_eccco_Δ(outcomes; kwrgs...) = best_rank_outcome(outcomes; generator=ECCCo_Δ_NAMES, kwrgs...) +best_rank_eccco_Δ(outcomes; kwrgs...) = + best_rank_outcome(outcomes; generator = ECCCo_Δ_NAMES, kwrgs...) """ best_absolute_outcome(outcomes; generator=ECCCO_NAMES, measure="distance_from_energy") @@ -116,15 +137,15 @@ best_rank_eccco_Δ(outcomes; kwrgs...) = best_rank_outcome(outcomes; generator=E Return the best outcome from grid search results. The best outcome is defined as the one with the lowest average value across all datasets and variables for the specified generator and measure. """ function best_absolute_outcome( - outcomes::Dict; - generator=ECCCO_NAMES, - measure::AbstractArray=["distance_from_energy_l2"], - model::Union{Nothing,AbstractArray}=nothing, - weights::Union{Nothing,AbstractArray}=nothing + outcomes::Dict; + generator = ECCCO_NAMES, + measure::AbstractArray = ["distance_from_energy_l2"], + model::Union{Nothing,AbstractArray} = nothing, + weights::Union{Nothing,AbstractArray} = nothing, ) weights = isnothing(weights) ? ones(length(measure)) : weights - df_weights = DataFrame(variable=measure, weight=weights) + df_weights = DataFrame(variable = measure, weight = weights) avg_values = [] for (params, outcome) in outcomes @@ -156,13 +177,14 @@ function best_absolute_outcome( outcome = ExperimentOutcome(exper, model_dict, generator_dict, bmk) # Compute: - results = summarise_outcome(outcome, measure=measure, model=model) |> - x -> leftjoin(x, df_weights, on=:variable) - + results = + summarise_outcome(outcome, measure = measure, model = model) |> + x -> leftjoin(x, df_weights, on = :variable) + # Compute weighted averages: - _avg_values = subset(results, :generator => ByRow(x -> x ∈ generator)) |> - x -> x.mean .* x.weight |> - x -> (sum(x)/length(x))[1] + _avg_values = + subset(results, :generator => ByRow(x -> x ∈ generator)) |> + x -> x.mean .* x.weight |> x -> (sum(x)/length(x))[1] # Append: push!(avg_values, _avg_values) @@ -170,13 +192,15 @@ function best_absolute_outcome( best_index = argmin(avg_values) best_outcome = ( params = collect(keys(outcomes))[best_index], - outcome = collect(values(outcomes))[best_index] + outcome = collect(values(outcomes))[best_index], ) end -best_absolute_outcome_eccco(outcomes; kwrgs...) = best_absolute_outcome(outcomes; generator=ECCCO_NAMES, kwrgs...) +best_absolute_outcome_eccco(outcomes; kwrgs...) = + best_absolute_outcome(outcomes; generator = ECCCO_NAMES, kwrgs...) -best_absolute_outcome_eccco_Δ(outcomes; kwrgs...) = best_absolute_outcome(outcomes; generator=ECCCo_Δ_NAMES, kwrgs...) +best_absolute_outcome_eccco_Δ(outcomes; kwrgs...) = + best_absolute_outcome(outcomes; generator = ECCCo_Δ_NAMES, kwrgs...) """ append_best_params!(params::NamedTuple, dataname::String) @@ -184,12 +208,24 @@ best_absolute_outcome_eccco_Δ(outcomes; kwrgs...) = best_absolute_outcome(outco Appends the best parameters from grid search results to the specified parameters. """ function append_best_params!(params::NamedTuple, dataname::String) - if !isfile(joinpath(DEFAULT_OUTPUT_PATH, "grid_search", "$(replace(lowercase(dataname), " " => "_")).jls")) + if !isfile( + joinpath( + DEFAULT_OUTPUT_PATH, + "grid_search", + "$(replace(lowercase(dataname), " " => "_")).jls", + ), + ) @warn "No grid search results found. Using default parameters." else @info "Appending best parameters from grid search results." - grid_search_results = Serialization.deserialize(joinpath(DEFAULT_OUTPUT_PATH, "grid_search", "$(replace(lowercase(dataname), " " => "_")).jls")) + grid_search_results = Serialization.deserialize( + joinpath( + DEFAULT_OUTPUT_PATH, + "grid_search", + "$(replace(lowercase(dataname), " " => "_")).jls", + ), + ) best_params = best_absolute_outcome_eccco_Δ(grid_search_results).params params = (; params..., best_params...) end -end \ No newline at end of file +end diff --git a/experiments/linearly_separable.jl b/experiments/linearly_separable.jl index db09b5bb..b12e4b3c 100644 --- a/experiments/linearly_separable.jl +++ b/experiments/linearly_separable.jl @@ -2,8 +2,8 @@ dataname = "Linearly Separable" n_obs = Int(1000 / (1.0 - TEST_SIZE)) counterfactual_data, test_data = train_test_split( - load_blobs(n_obs; cluster_std=0.1, center_box=(-1.0 => 1.0)); - test_size=TEST_SIZE + load_blobs(n_obs; cluster_std = 0.1, center_box = (-1.0 => 1.0)); + test_size = TEST_SIZE, ) # Model tuning: @@ -15,25 +15,26 @@ tuning_params = DEFAULT_GENERATOR_TUNING # Parameter choices: # These are the parameter choices originally used in the paper that were manually fine-tuned for the JEM. params = ( - use_tuned=false, - n_hidden=16, - n_layers=3, - activation=Flux.swish, - epochs=100, - opt=Flux.Optimise.Descent(0.01), - Λ=[0.1, 0.1, 0.05], - reg_strength=0.0, + use_tuned = false, + n_hidden = 16, + n_layers = 3, + activation = Flux.swish, + epochs = 100, + opt = Flux.Optimise.Descent(0.01), + Λ = [0.1, 0.1, 0.05], + reg_strength = 0.0, ) # Best grid search params: append_best_params!(params, dataname) -if GRID_SEARCH +if GRID_SEARCH grid_search( - counterfactual_data, test_data; - dataname=dataname, - tuning_params=tuning_params, - params... + counterfactual_data, + test_data; + dataname = dataname, + tuning_params = tuning_params, + params..., ) elseif FROM_GRID_SEARCH outcomes_file_path = joinpath( @@ -45,9 +46,10 @@ elseif FROM_GRID_SEARCH bmk2csv(dataname) else run_experiment( - counterfactual_data, test_data; - dataname=dataname, - model_tuning_params=model_tuning_params, - params... + counterfactual_data, + test_data; + dataname = dataname, + model_tuning_params = model_tuning_params, + params..., ) -end \ No newline at end of file +end diff --git a/experiments/mnist.jl b/experiments/mnist.jl index 0bfc9181..e4fe2251 100644 --- a/experiments/mnist.jl +++ b/experiments/mnist.jl @@ -4,7 +4,10 @@ n_obs = 10000 counterfactual_data = load_mnist(n_obs) counterfactual_data.X = ECCCo.pre_process.(counterfactual_data.X) # Adjust domain constraints to account for noise added during pre-processing: -counterfactual_data.domain = fill((minimum(counterfactual_data.X), maximum(counterfactual_data.X)), size(counterfactual_data.X, 1)) +counterfactual_data.domain = fill( + (minimum(counterfactual_data.X), maximum(counterfactual_data.X)), + size(counterfactual_data.X, 1), +) # VAE (trained on full dataset): using CounterfactualExplanations.Models: load_mnist_vae @@ -16,52 +19,56 @@ test_data = load_mnist_test() # Dimensionality reduction: maxout_dim = vae.params.latent_dim -counterfactual_data.dt = MultivariateStats.fit(MultivariateStats.PCA, counterfactual_data.X; maxoutdim=maxout_dim); +counterfactual_data.dt = MultivariateStats.fit( + MultivariateStats.PCA, + counterfactual_data.X; + maxoutdim = maxout_dim, +); # Model tuning: model_tuning_params = DEFAULT_MODEL_TUNING_LARGE # Tuning parameters: tuning_params = DEFAULT_GENERATOR_TUNING -tuning_params = (; tuning_params..., Λ=[tuning_params.Λ[2:end]..., [0.1, 0.1, 3.0]]) +tuning_params = (; tuning_params..., Λ = [tuning_params.Λ[2:end]..., [0.1, 0.1, 3.0]]) # Additional models: -add_models = Dict( - "LeNet-5" => lenet5, -) +add_models = Dict("LeNet-5" => lenet5) # CE measures (add cosine distance): -ce_measures = [CE_MEASURES..., ECCCo.distance_from_energy_ssim, ECCCo.distance_from_targets_ssim] +ce_measures = + [CE_MEASURES..., ECCCo.distance_from_energy_ssim, ECCCo.distance_from_targets_ssim] # Parameter choices: params = ( - n_individuals=N_IND_SPECIFIED ? N_IND : 100, - builder=default_builder(n_hidden=128, n_layers=1, activation=Flux.swish), - 𝒟x=Uniform(-1.0, 1.0), - α=[1.0, 1.0, 1e-2], - sampling_batch_size=10, - sampling_steps=25, - use_ensembling=true, - use_variants=false, - additional_models=add_models, - epochs=100, - nsamples=10, - nmin=1, - niter_eccco=10, - Λ=[0.01, 0.25, 0.25], - Λ_Δ=[0.01, 0.1, 0.3], - opt=Flux.Optimise.Descent(0.1), + n_individuals = N_IND_SPECIFIED ? N_IND : 100, + builder = default_builder(n_hidden = 128, n_layers = 1, activation = Flux.swish), + 𝒟x = Uniform(-1.0, 1.0), + α = [1.0, 1.0, 1e-2], + sampling_batch_size = 10, + sampling_steps = 25, + use_ensembling = true, + use_variants = false, + additional_models = add_models, + epochs = 100, + nsamples = 10, + nmin = 1, + niter_eccco = 10, + Λ = [0.01, 0.25, 0.25], + Λ_Δ = [0.01, 0.1, 0.3], + opt = Flux.Optimise.Descent(0.1), reg_strength = 0.0, - ce_measures=ce_measures, - dim_reduction=true, + ce_measures = ce_measures, + dim_reduction = true, ) if GRID_SEARCH grid_search( - counterfactual_data, test_data; - dataname=dataname, - tuning_params=tuning_params, - params... + counterfactual_data, + test_data; + dataname = dataname, + tuning_params = tuning_params, + params..., ) elseif FROM_GRID_SEARCH outcomes_file_path = joinpath( @@ -73,9 +80,10 @@ elseif FROM_GRID_SEARCH bmk2csv(dataname) else run_experiment( - counterfactual_data, test_data; - dataname=dataname, - model_tuning_params=model_tuning_params, - params... + counterfactual_data, + test_data; + dataname = dataname, + model_tuning_params = model_tuning_params, + params..., ) -end \ No newline at end of file +end diff --git a/experiments/model_tuning.jl b/experiments/model_tuning.jl index dfabfbaa..c7a2abfe 100644 --- a/experiments/model_tuning.jl +++ b/experiments/model_tuning.jl @@ -17,23 +17,36 @@ function tune_mlp(exper::Experiment; kwargs...) model_tuning_path = mkpath(tuned_model_path(exper)) # Simple MLP: model = NeuralNetworkClassifier( - builder=default_builder(), - epochs=exper.epochs, - batch_size=batch_size(exper), - finaliser=exper.finaliser, - loss=exper.loss, - acceleration=CUDALibs(), + builder = default_builder(), + epochs = exper.epochs, + batch_size = batch_size(exper), + finaliser = exper.finaliser, + loss = exper.loss, + acceleration = CUDALibs(), ) # Unpack data: X, y, _ = prepare_data(exper::Experiment) # Tune model: measure = collect(values(exper.model_measures)) - mach = tune_mlp(model, X, y; tuning_params=exper.model_tuning_params, measure=measure, kwargs...) + mach = tune_mlp( + model, + X, + y; + tuning_params = exper.model_tuning_params, + measure = measure, + kwargs..., + ) # Machine is still on GPU, save CPU version of model: best_results = fitted_params(mach) - Serialization.serialize(joinpath(model_tuning_path, "$(exper.save_name)_best_mlp.jls"), best_results) + Serialization.serialize( + joinpath(model_tuning_path, "$(exper.save_name)_best_mlp.jls"), + best_results, + ) best_history = report(mach).best_history_entry - Serialization.serialize(joinpath(model_tuning_path, "$(exper.save_name)_best_mlp_history.jls"), best_history) + Serialization.serialize( + joinpath(model_tuning_path, "$(exper.save_name)_best_mlp_history.jls"), + best_history, + ) end return mach, best_results end @@ -44,39 +57,41 @@ end Tunes a model by performing a grid search over the parameters specified in `tuning_params`. """ function tune_mlp( - model::Supervised, X, y; + model::Supervised, + X, + y; tuning_params::NamedTuple, - measure::Vector=MODEL_MEASURE_VEC, - tuning=Grid(shuffle=false), - resampling=CV(nfolds=3, shuffle=true,), - kwargs... + measure::Vector = MODEL_MEASURE_VEC, + tuning = Grid(shuffle = false), + resampling = CV(nfolds = 3, shuffle = true), + kwargs..., ) ranges = [] for (k, v) in pairs(tuning_params) if k ∈ fieldnames(typeof(model)) - push!(ranges, range(model, k, values=v)) + push!(ranges, range(model, k, values = v)) elseif k ∈ fieldnames(typeof(model.builder)) - push!(ranges, range(model, :(builder.$(k)), values=v)) + push!(ranges, range(model, :(builder.$(k)), values = v)) elseif k ∈ fieldnames(typeof(model.optimiser)) - push!(ranges, range(model, :(optimiser.$(k)), values=v)) + push!(ranges, range(model, :(optimiser.$(k)), values = v)) else error("Parameter $k not found in model, builder or optimiser.") end end - + self_tuning_mod = TunedModel( - model=model, - range=ranges, - measure=measure, - tuning=tuning, - resampling=resampling, - kwargs... + model = model, + range = ranges, + measure = measure, + tuning = tuning, + resampling = resampling, + kwargs..., ) mach = machine(self_tuning_mod, X, y) - fit!(mach, verbosity=0) + fit!(mach, verbosity = 0) return mach @@ -87,5 +102,5 @@ end Checks if a tuned MLP exists. """ -tuned_mlp_exists(exper::Experiment) = isfile(joinpath(tuned_model_path(exper), "$(exper.save_name)_best_mlp.jls")) - +tuned_mlp_exists(exper::Experiment) = + isfile(joinpath(tuned_model_path(exper), "$(exper.save_name)_best_mlp.jls")) diff --git a/experiments/models/additional_models.jl b/experiments/models/additional_models.jl index d6e8f814..410c3c86 100644 --- a/experiments/models/additional_models.jl +++ b/experiments/models/additional_models.jl @@ -4,9 +4,9 @@ MLJFlux builder for a LeNet-like convolutional neural network. """ mutable struct LeNetBuilder - filter_size::Int - channels1::Int - channels2::Int + filter_size::Int + channels1::Int + channels2::Int end """ @@ -18,27 +18,23 @@ function MLJFlux.build(b::LeNetBuilder, rng, n_in, n_out) # Setup: _n_in = Int(sqrt(n_in)) - k, c1, c2 = b.filter_size, b.channels1, b.channels2 - mod(k, 2) == 1 || error("`filter_size` must be odd. ") + k, c1, c2 = b.filter_size, b.channels1, b.channels2 + mod(k, 2) == 1 || error("`filter_size` must be odd. ") p = div(k - 1, 2) # padding to preserve image size on convolution: # Model: - front = Flux.Chain( - Conv((k, k), 1 => c1, pad=(p, p), relu), + front = Flux.Chain( + Conv((k, k), 1 => c1, pad = (p, p), relu), MaxPool((2, 2)), - Conv((k, k), c1 => c2, pad=(p, p), relu), + Conv((k, k), c1 => c2, pad = (p, p), relu), MaxPool((2, 2)), - Flux.flatten - ) - d = Flux.outputsize(front, (_n_in, _n_in, 1, 1)) |> first - back = Flux.Chain( - Dense(d, 120, relu), - Dense(120, 84, relu), - Dense(84, n_out), + Flux.flatten, ) + d = Flux.outputsize(front, (_n_in, _n_in, 1, 1)) |> first + back = Flux.Chain(Dense(d, 120, relu), Dense(120, 84, relu), Dense(84, n_out)) chain = Flux.Chain(ECCCo.ToConv(_n_in), front, back) - return chain + return chain end """ @@ -46,7 +42,8 @@ end Builds a LeNet-like convolutional neural network. """ -lenet5(builder=LeNetBuilder(5, 6, 16); kwargs...) = NeuralNetworkClassifier(builder=builder; acceleration=CUDALibs(), kwargs...) +lenet5(builder = LeNetBuilder(5, 6, 16); kwargs...) = + NeuralNetworkClassifier(builder = builder; acceleration = CUDALibs(), kwargs...) """ ResNetBuilder @@ -62,13 +59,9 @@ Overloads the MLJFlux build function for a LeNet-like convolutional neural netwo """ function MLJFlux.build(b::ResNetBuilder, rng, n_in, n_out) _n_in = Int(sqrt(n_in)) - front = Metalhead.ResNet(18; inchannels=1) + front = Metalhead.ResNet(18; inchannels = 1) d = Flux.outputsize(front, (_n_in, _n_in, 1, 1)) |> first - back = Flux.Chain( - Dense(d, 120, relu), - Dense(120, 84, relu), - Dense(84, n_out), - ) + back = Flux.Chain(Dense(d, 120, relu), Dense(120, 84, relu), Dense(84, n_out)) chain = Flux.Chain(ECCCo.ToConv(_n_in), front, back) return chain end @@ -78,4 +71,5 @@ end Builds a LeNet-like convolutional neural network. """ -resnet18(builder=ResNetBuilder(); kwargs...) = NeuralNetworkClassifier(builder=builder; acceleration=CUDALibs(), kwargs...) +resnet18(builder = ResNetBuilder(); kwargs...) = + NeuralNetworkClassifier(builder = builder; acceleration = CUDALibs(), kwargs...) diff --git a/experiments/models/default_models.jl b/experiments/models/default_models.jl index c50ff092..597010f8 100644 --- a/experiments/models/default_models.jl +++ b/experiments/models/default_models.jl @@ -6,11 +6,12 @@ mutable struct TuningBuilder <: MLJFlux.Builder end "Outer constructor." -TuningBuilder(; n_hidden=32, n_layers=3, activation=Flux.swish) = TuningBuilder(n_hidden, n_layers, activation) +TuningBuilder(; n_hidden = 32, n_layers = 3, activation = Flux.swish) = + TuningBuilder(n_hidden, n_layers, activation) function MLJFlux.build(nn::TuningBuilder, rng, n_in, n_out) hidden = ntuple(i -> nn.n_hidden, nn.n_layers) - return MLJFlux.build(MLJFlux.MLP(hidden=hidden, σ=nn.activation), rng, n_in, n_out) + return MLJFlux.build(MLJFlux.MLP(hidden = hidden, σ = nn.activation), rng, n_in, n_out) end """ @@ -18,8 +19,13 @@ end Default builder for MLPs. """ -function default_builder(;n_hidden::Int=16, n_layers::Int=3, activation::Function=Flux.swish) - builder = TuningBuilder(n_hidden=n_hidden, n_layers=n_layers, activation=activation) +function default_builder(; + n_hidden::Int = 16, + n_layers::Int = 3, + activation::Function = Flux.swish, +) + builder = + TuningBuilder(n_hidden = n_hidden, n_layers = n_layers, activation = activation) return builder end @@ -42,55 +48,50 @@ Builds a dictionary of default models for training. """ function default_models(; sampler::AbstractSampler, - builder::MLJFlux.Builder=default_builder(), - epochs::Int=100, - batch_size::Int=128, - finaliser::Function=Flux.softmax, - loss::Function=Flux.Losses.crossentropy, - α::AbstractArray=[1.0, 1.0, 1e-1], - verbosity::Int=10, - sampling_steps::Int=30, - n_ens::Int=5, - use_ensembling::Bool=true, + builder::MLJFlux.Builder = default_builder(), + epochs::Int = 100, + batch_size::Int = 128, + finaliser::Function = Flux.softmax, + loss::Function = Flux.Losses.crossentropy, + α::AbstractArray = [1.0, 1.0, 1e-1], + verbosity::Int = 10, + sampling_steps::Int = 30, + n_ens::Int = 5, + use_ensembling::Bool = true, ) # Simple MLP: mlp = NeuralNetworkClassifier( - builder=builder, - epochs=epochs, - batch_size=batch_size, - finaliser=finaliser, - loss=loss, - acceleration=CUDALibs(), + builder = builder, + epochs = epochs, + batch_size = batch_size, + finaliser = finaliser, + loss = loss, + acceleration = CUDALibs(), ) # Deep Ensemble: - mlp_ens = EnsembleModel(model=mlp, n=n_ens) + mlp_ens = EnsembleModel(model = mlp, n = n_ens) # Joint Energy Model: jem = JointEnergyClassifier( sampler; - builder=builder, - epochs=epochs, - batch_size=batch_size, - finaliser=finaliser, - loss=loss, - jem_training_params=( - α=α, verbosity=verbosity, - ), - sampling_steps=sampling_steps, + builder = builder, + epochs = epochs, + batch_size = batch_size, + finaliser = finaliser, + loss = loss, + jem_training_params = (α = α, verbosity = verbosity), + sampling_steps = sampling_steps, # acceleration=CUDALibs(), ) # Deep Ensemble of Joint Energy Models: - jem_ens = EnsembleModel(model=jem, n=n_ens) + jem_ens = EnsembleModel(model = jem, n = n_ens) # Dictionary of models: if !use_ensembling - models = Dict( - "MLP" => mlp, - "JEM" => jem, - ) + models = Dict("MLP" => mlp, "JEM" => jem) else models = Dict( "MLP" => mlp, @@ -101,4 +102,4 @@ function default_models(; end return models -end \ No newline at end of file +end diff --git a/experiments/models/models.jl b/experiments/models/models.jl index c446b524..519a3f7e 100644 --- a/experiments/models/models.jl +++ b/experiments/models/models.jl @@ -2,7 +2,7 @@ include("additional_models.jl") include("default_models.jl") include("train_models.jl") -function prepare_models(exper::Experiment; save_models::Bool=true) +function prepare_models(exper::Experiment; save_models::Bool = true) # Unpack data: X, labels, sampler = prepare_data(exper::Experiment) @@ -13,11 +13,17 @@ function prepare_models(exper::Experiment; save_models::Bool=true) if tuned_mlp_exists(exper) && exper.use_tuned @info "Loading tuned model architecture." # Load the best MLP: - best_mlp = Serialization.deserialize(joinpath(tuned_model_path(exper), "$(exper.save_name)_best_mlp.jls")) + best_mlp = Serialization.deserialize( + joinpath(tuned_model_path(exper), "$(exper.save_name)_best_mlp.jls"), + ) builder = best_mlp.best_model.builder else # Otherwise, use default MLP: - builder = default_builder(n_hidden=exper.n_hidden, n_layers=exper.n_layers, activation=exper.activation) + builder = default_builder( + n_hidden = exper.n_hidden, + n_layers = exper.n_layers, + activation = exper.activation, + ) end else builder = exper.builder @@ -26,16 +32,16 @@ function prepare_models(exper::Experiment; save_models::Bool=true) if isnothing(exper.models) @info "Using default models." models = default_models(; - sampler=sampler, - builder=builder, - batch_size=batch_size(exper), - sampling_steps=exper.sampling_steps, - α=exper.α, - n_ens=exper.n_ens, - use_ensembling=exper.use_ensembling, - finaliser=exper.finaliser, - loss=exper.loss, - epochs=exper.epochs, + sampler = sampler, + builder = builder, + batch_size = batch_size(exper), + sampling_steps = exper.sampling_steps, + α = exper.α, + n_ens = exper.n_ens, + use_ensembling = exper.use_ensembling, + finaliser = exper.finaliser, + loss = exper.loss, + epochs = exper.epochs, ) end # Additional models: @@ -45,10 +51,10 @@ function prepare_models(exper::Experiment; save_models::Bool=true) for (k, mod) in exper.additional_models if isa(mod, Function) add_models[k] = mod(; - batch_size=batch_size(exper), - finaliser=exper.finaliser, - loss=exper.loss, - epochs=exper.epochs, + batch_size = batch_size(exper), + finaliser = exper.finaliser, + loss = exper.loss, + epochs = exper.epochs, ) else add_models[k] = mod @@ -57,30 +63,44 @@ function prepare_models(exper::Experiment; save_models::Bool=true) models = merge(models, add_models) end @info "Training models." - model_dict = train_models(models, X, labels; parallelizer=exper.parallelizer, train_parallel=exper.train_parallel, cov=exper.coverage) + model_dict = train_models( + models, + X, + labels; + parallelizer = exper.parallelizer, + train_parallel = exper.train_parallel, + cov = exper.coverage, + ) else # Pre-trained models: if !(is_multi_processed(exper) && MPI.Comm_rank(exper.parallelizer.comm) != 0) # Load models on root process: @info "Loading pre-trained models." - model_dict = Serialization.deserialize(joinpath(pretrained_path(exper), "$(exper.save_name)_models.jls")) + model_dict = Serialization.deserialize( + joinpath(pretrained_path(exper), "$(exper.save_name)_models.jls"), + ) else # Dummy model on other processes: model_dict = nothing end # Broadcast models: if is_multi_processed(exper) - model_dict = MPI.bcast(model_dict, exper.parallelizer.comm; root=0) + model_dict = MPI.bcast(model_dict, exper.parallelizer.comm; root = 0) end end # Save models: - local_models_exist = isfile(joinpath(DEFAULT_OUTPUT_PATH, "$(exper.save_name)_models.jls")) - on_root_process = !(is_multi_processed(exper) && MPI.Comm_rank(exper.parallelizer.comm) != 0) + local_models_exist = + isfile(joinpath(DEFAULT_OUTPUT_PATH, "$(exper.save_name)_models.jls")) + on_root_process = + !(is_multi_processed(exper) && MPI.Comm_rank(exper.parallelizer.comm) != 0) if save_models && on_root_process && !local_models_exist @info "Saving models to $(joinpath(exper.output_path , "$(exper.save_name)_models.jls"))." - Serialization.serialize(joinpath(exper.output_path, "$(exper.save_name)_models.jls"), model_dict) + Serialization.serialize( + joinpath(exper.output_path, "$(exper.save_name)_models.jls"), + model_dict, + ) end return model_dict -end \ No newline at end of file +end diff --git a/experiments/models/train_models.jl b/experiments/models/train_models.jl index 14d00675..14cb6b4c 100644 --- a/experiments/models/train_models.jl +++ b/experiments/models/train_models.jl @@ -5,7 +5,14 @@ using CounterfactualExplanations: AbstractParallelizer Trains all models in a dictionary and returns a dictionary of `ConformalModel` objects. """ -function train_models(models::Dict, X, y; parallelizer::Union{Nothing,AbstractParallelizer}=nothing, train_parallel::Bool=false, kwargs...) +function train_models( + models::Dict, + X, + y; + parallelizer::Union{Nothing,AbstractParallelizer} = nothing, + train_parallel::Bool = false, + kwargs..., +) verbose = is_multi_processed(parallelizer) ? false : true if is_multi_processed(parallelizer) && train_parallel # Split models into groups of approximately equal size: @@ -15,7 +22,8 @@ function train_models(models::Dict, X, y; parallelizer::Union{Nothing,AbstractPa # Train models: model_dict = Dict() for (mod_name, model) in x - model_dict[mod_name] = _train(model, X, y; mod_name=mod_name, verbose=verbose, kwargs...) + model_dict[mod_name] = + _train(model, X, y; mod_name = mod_name, verbose = verbose, kwargs...) end MPI.Barrier(parallelizer.comm) output = MPI.gather(output, parallelizer.comm) @@ -26,10 +34,14 @@ function train_models(models::Dict, X, y; parallelizer::Union{Nothing,AbstractPa output = nothing end # Broadcast output to all processes: - model_dict = MPI.bcast(output, parallelizer.comm; root=0) + model_dict = MPI.bcast(output, parallelizer.comm; root = 0) MPI.Barrier(parallelizer.comm) else - model_dict = Dict(mod_name => _train(model, X, y; mod_name=mod_name, verbose=verbose, kwargs...) for (mod_name, model) in models) + model_dict = Dict( + mod_name => + _train(model, X, y; mod_name = mod_name, verbose = verbose, kwargs...) + for (mod_name, model) in models + ) end return model_dict end @@ -46,14 +58,22 @@ end Trains a model and returns a `ConformalModel` object. """ -function _train(model, X, y; cov, method=:simple_inductive, mod_name="model", verbose::Bool=true) - conf_model = conformal_model(model; method=method, coverage=cov) +function _train( + model, + X, + y; + cov, + method = :simple_inductive, + mod_name = "model", + verbose::Bool = true, +) + conf_model = conformal_model(model; method = method, coverage = cov) mach = machine(conf_model, X, y) @info "Begin training $mod_name." if verbose fit!(mach) else - fit!(mach, verbosity=0) + fit!(mach, verbosity = 0) end @info "Finished training $mod_name." M = ECCCo.ConformalModel(mach.model, mach.fitresult) @@ -67,4 +87,4 @@ Helper function to save models. """ function save_models(model_dict::Dict; save_name::String, output_path) Serialization.serialize(joinpath(output_path, "$(save_name)_models.jls"), model_dict) -end \ No newline at end of file +end diff --git a/experiments/moons.jl b/experiments/moons.jl index c2a83e10..9677a36c 100644 --- a/experiments/moons.jl +++ b/experiments/moons.jl @@ -1,7 +1,7 @@ # Data: dataname = "Moons" n_obs = Int(2500 / (1.0 - TEST_SIZE)) -counterfactual_data, test_data = train_test_split(load_moons(n_obs); test_size=TEST_SIZE) +counterfactual_data, test_data = train_test_split(load_moons(n_obs); test_size = TEST_SIZE) # Model tuning: model_tuning_params = DEFAULT_MODEL_TUNING_SMALL @@ -12,16 +12,16 @@ tuning_params = DEFAULT_GENERATOR_TUNING # Parameter choices: # These are the parameter choices originally used in the paper that were manually fine-tuned for the JEM. params = ( - use_tuned=false, - n_hidden=32, - n_layers=3, - activation=Flux.relu, - epochs=500, - sampling_batch_size=10, - sampling_steps=30, - opt=Flux.Optimise.Descent(0.01), - Λ=[0.1, 0.1, 0.5], - reg_strength=0.0, + use_tuned = false, + n_hidden = 32, + n_layers = 3, + activation = Flux.relu, + epochs = 500, + sampling_batch_size = 10, + sampling_steps = 30, + opt = Flux.Optimise.Descent(0.01), + Λ = [0.1, 0.1, 0.5], + reg_strength = 0.0, ) # Best grid search params: @@ -29,10 +29,11 @@ append_best_params!(params, dataname) if GRID_SEARCH grid_search( - counterfactual_data, test_data; - dataname=dataname, - tuning_params=tuning_params, - params... + counterfactual_data, + test_data; + dataname = dataname, + tuning_params = tuning_params, + params..., ) elseif FROM_GRID_SEARCH outcomes_file_path = joinpath( @@ -44,9 +45,10 @@ elseif FROM_GRID_SEARCH bmk2csv(dataname) else run_experiment( - counterfactual_data, test_data; - dataname=dataname, - model_tuning_params=model_tuning_params, - params... + counterfactual_data, + test_data; + dataname = dataname, + model_tuning_params = model_tuning_params, + params..., ) -end \ No newline at end of file +end diff --git a/experiments/post_processing/artifacts.jl b/experiments/post_processing/artifacts.jl index 2912f60e..3ff26a71 100644 --- a/experiments/post_processing/artifacts.jl +++ b/experiments/post_processing/artifacts.jl @@ -17,12 +17,12 @@ using Serialization Uploads results to github releases. If `deploy=true`, then the results will be uploaded to a github release. If `deploy=false`, then the results will be saved locally. """ function generate_artifacts( - datafiles=DEFAULT_OUTPUT_PATH; - artifact_name=nothing, - root=".", - artifact_toml=LazyArtifacts.find_artifacts_toml("."), - deploy=true, - tag=nothing + datafiles = DEFAULT_OUTPUT_PATH; + artifact_name = nothing, + root = ".", + artifact_toml = LazyArtifacts.find_artifacts_toml("."), + deploy = true, + tag = nothing, ) # Artifact name: @@ -67,9 +67,9 @@ function generate_artifacts( artifact_toml, artifact_name, hash; - download_info=[(tarball_url, tarball_hash)], - lazy=true, - force=true + download_info = [(tarball_url, tarball_hash)], + lazy = true, + force = true, ) end @@ -89,7 +89,7 @@ function generate_artifacts( end end -function get_git_remote_url(repo_path::String=".") +function get_git_remote_url(repo_path::String = ".") repo = LibGit2.GitRepo(repo_path) origin = LibGit2.get(LibGit2.GitRemote, repo, "origin") return LibGit2.url(origin) diff --git a/experiments/post_processing/meta_data.jl b/experiments/post_processing/meta_data.jl index 06585632..b50ce978 100644 --- a/experiments/post_processing/meta_data.jl +++ b/experiments/post_processing/meta_data.jl @@ -3,11 +3,20 @@ Extract and save meta data about the experiment. """ -function meta(outcome::ExperimentOutcome; save_output::Bool=false, params_path::Union{Nothing,String}=nothing) - - model_params = meta_model(outcome; save_output=save_output, params_path=params_path) - model_performance = meta_model_performance(outcome; save_output=save_output, params_path=params_path) - generator_params = meta_generators(outcome; save_output=save_output, params_path=params_path) +function meta( + outcome::ExperimentOutcome; + save_output::Bool = false, + params_path::Union{Nothing,String} = nothing, +) + + model_params = meta_model(outcome; save_output = save_output, params_path = params_path) + model_performance = meta_model_performance( + outcome; + save_output = save_output, + params_path = params_path, + ) + generator_params = + meta_generators(outcome; save_output = save_output, params_path = params_path) return model_params, model_performance, generator_params @@ -18,7 +27,11 @@ end Extract and save meta data about the data and models in `outcome.model_dict`. """ -function meta_model(outcome::ExperimentOutcome; save_output::Bool=false, params_path::Union{Nothing,String}=nothing) +function meta_model( + outcome::ExperimentOutcome; + save_output::Bool = false, + params_path::Union{Nothing,String} = nothing, +) # Unpack: exper = outcome.exper @@ -38,7 +51,7 @@ function meta_model(outcome::ExperimentOutcome; save_output::Bool=false, params_ :n_ens => exper.n_ens, :lambda => string(exper.α[3]), :jem_sampling_steps => exper.sampling_steps, - ) + ), ) if save_output @@ -52,7 +65,11 @@ function meta_model(outcome::ExperimentOutcome; save_output::Bool=false, params_ end -function meta_generators(outcome::ExperimentOutcome; save_output::Bool=false, params_path::Union{Nothing,String}=nothing) +function meta_generators( + outcome::ExperimentOutcome; + save_output::Bool = false, + params_path::Union{Nothing,String} = nothing, +) # Unpack: exper = outcome.exper @@ -76,7 +93,7 @@ function meta_generators(outcome::ExperimentOutcome; save_output::Bool=false, pa :lambda_3_Δ => string(Λ_Δ[3]), :n_individuals => exper.n_individuals, :reg_strength => string(reg_strengh), - ) + ), ) if save_output @@ -94,7 +111,12 @@ end Compute and save the model performance for the models in `outcome.model_dict`. """ -function meta_model_performance(outcome::ExperimentOutcome; measures::Union{Nothing,Dict}=nothing, save_output::Bool=false, params_path::Union{Nothing,String}=nothing) +function meta_model_performance( + outcome::ExperimentOutcome; + measures::Union{Nothing,Dict} = nothing, + save_output::Bool = false, + params_path::Union{Nothing,String} = nothing, +) # Unpack: exper = outcome.exper @@ -105,7 +127,11 @@ function meta_model_performance(outcome::ExperimentOutcome; measures::Union{Noth model_performance = DataFrame() for (mod_name, model) in model_dict # Test performance: - _perf = CounterfactualExplanations.Models.model_evaluation(model, exper.test_data, measure=collect(values(measures))) + _perf = CounterfactualExplanations.Models.model_evaluation( + model, + exper.test_data, + measure = collect(values(measures)), + ) _perf = DataFrame([[p] for p in _perf], collect(keys(measures))) _perf.mod_name .= mod_name _perf.dataname .= exper.dataname @@ -127,4 +153,3 @@ function meta_model_performance(outcome::ExperimentOutcome; measures::Union{Noth return model_performance end - diff --git a/experiments/post_processing/plotting.jl b/experiments/post_processing/plotting.jl index 46d36c76..45bfdd67 100644 --- a/experiments/post_processing/plotting.jl +++ b/experiments/post_processing/plotting.jl @@ -1,6 +1,11 @@ using Plots -function choose_random_mnist(outcome::ExperimentOutcome; model::String="LeNet-5", img_height=125, seed=966) +function choose_random_mnist( + outcome::ExperimentOutcome; + model::String = "LeNet-5", + img_height = 125, + seed = 966, +) # Set seed: if !isnothing(seed) @@ -9,27 +14,33 @@ function choose_random_mnist(outcome::ExperimentOutcome; model::String="LeNet-5" # Get output: bmk = outcome.bmk() - grouped_bmk = groupby(bmk[bmk.variable.=="distance" .&& bmk.model.==model,:], [:dataname, :target, :factual]) + grouped_bmk = groupby( + bmk[bmk.variable.=="distance".&&bmk.model.==model, :], + [:dataname, :target, :factual], + ) random_choice = rand(1:length(grouped_bmk)) generators = unique(bmk.generator) n_generators = length(generators) # Get data: - df = grouped_bmk[random_choice][1:n_generators, :] |> - x -> sort(x, :generator) |> - x -> subset(x, :generator => ByRow(x -> x != "ECCCo")) + df = + grouped_bmk[random_choice][1:n_generators, :] |> + x -> sort(x, :generator) |> x -> subset(x, :generator => ByRow(x -> x != "ECCCo")) generators = df.generator replace!(generators, "ECCCo-Δ" => "ECCCo") replace!(generators, "ECCCo-Δ (latent)" => "ECCCo+") n_generators = length(generators) # Factual: - img = CounterfactualExplanations.factual(grouped_bmk[random_choice][1:n_generators,:].ce[1]) |> ECCCo.convert2mnist + img = + CounterfactualExplanations.factual( + grouped_bmk[random_choice][1:n_generators, :].ce[1], + ) |> ECCCo.convert2mnist p1 = Plots.plot( img, - axis=([], false), - size=(img_height, img_height), - title="Factual", + axis = ([], false), + size = (img_height, img_height), + title = "Factual", ) plts = [p1] ces = [] @@ -40,9 +51,9 @@ function choose_random_mnist(outcome::ExperimentOutcome; model::String="LeNet-5" img = CounterfactualExplanations.counterfactual(ce) |> ECCCo.convert2mnist p = Plots.plot( img, - axis=([], false), - size=(img_height, img_height), - title="$generator", + axis = ([], false), + size = (img_height, img_height), + title = "$generator", ) push!(plts, p) push!(ces, ce) @@ -50,9 +61,9 @@ function choose_random_mnist(outcome::ExperimentOutcome; model::String="LeNet-5" plt = Plots.plot( plts..., - layout=(1, n_generators + 1), - size=(img_height * (n_generators + 1), img_height), - dpi=300 + layout = (1, n_generators + 1), + size = (img_height * (n_generators + 1), img_height), + dpi = 300, ) display(plt) @@ -60,7 +71,13 @@ function choose_random_mnist(outcome::ExperimentOutcome; model::String="LeNet-5" end -function plot_random_eccco(outcome::ExperimentOutcome; ce=nothing, generator="ECCCo-Δ", img_height=200, seed=966) +function plot_random_eccco( + outcome::ExperimentOutcome; + ce = nothing, + generator = "ECCCo-Δ", + img_height = 200, + seed = 966, +) # Set seed: if !isnothing(seed) Random.seed!(seed) @@ -79,20 +96,28 @@ function plot_random_eccco(outcome::ExperimentOutcome; ce=nothing, generator="EC img = CounterfactualExplanations.factual(ce) |> ECCCo.convert2mnist p1 = Plots.plot( img, - axis=([], false), - size=(img_height, img_height), - title="Factual", + axis = ([], false), + size = (img_height, img_height), + title = "Factual", ) plts = [p1] for (model_name, M) in models - ce = generate_counterfactual(x, target, data, M, gen; initialization=:identity, converge_when=:generator_conditions) + ce = generate_counterfactual( + x, + target, + data, + M, + gen; + initialization = :identity, + converge_when = :generator_conditions, + ) img = CounterfactualExplanations.counterfactual(ce) |> ECCCo.convert2mnist p = Plots.plot( img, - axis=([], false), - size=(img_height, img_height), - title="$model_name", + axis = ([], false), + size = (img_height, img_height), + title = "$model_name", ) push!(plts, p) end @@ -100,16 +125,23 @@ function plot_random_eccco(outcome::ExperimentOutcome; ce=nothing, generator="EC plt = Plots.plot( plts..., - layout=(1, n_models + 1), - size=(img_height * (n_models + 1), img_height), - dpi=300 + layout = (1, n_models + 1), + size = (img_height * (n_models + 1), img_height), + dpi = 300, ) display(plt) return plt, target, seed end -function plot_all_mnist(gen, model, data=load_mnist_test(); img_height=150, seed=123, maxoutdim=64) +function plot_all_mnist( + gen, + model, + data = load_mnist_test(); + img_height = 150, + seed = 123, + maxoutdim = 64, +) # Set seed: if !isnothing(seed) @@ -117,8 +149,8 @@ function plot_all_mnist(gen, model, data=load_mnist_test(); img_height=150, seed end # Dimensionality reduction: - data.dt = MultivariateStats.fit(MultivariateStats.PCA, data.X; maxoutdim=maxoutdim) - + data.dt = MultivariateStats.fit(MultivariateStats.PCA, data.X; maxoutdim = maxoutdim) + # VAE for REVISE: data.generative_model = CounterfactualExplanations.Models.load_mnist_vae() @@ -133,21 +165,26 @@ function plot_all_mnist(gen, model, data=load_mnist_test(); img_height=150, seed if factual != target @info "Generating counterfactual for $(factual) -> $(target)" ce = generate_counterfactual( - x, target, data, model, gen; - initialization=:identity, converge_when=:generator_conditions + x, + target, + data, + model, + gen; + initialization = :identity, + converge_when = :generator_conditions, ) plt = Plots.plot( CounterfactualExplanations.counterfactual(ce) |> ECCCo.convert2mnist, - axis=([], false), - size=(img_height, img_height), - title="$factual → $target", + axis = ([], false), + size = (img_height, img_height), + title = "$factual → $target", ) else plt = Plots.plot( x |> ECCCo.convert2mnist, - axis=([], false), - size=(img_height, img_height), - title="Factual", + axis = ([], false), + size = (img_height, img_height), + title = "Factual", ) end push!(plts, plt) @@ -156,9 +193,9 @@ function plot_all_mnist(gen, model, data=load_mnist_test(); img_height=150, seed plt = Plots.plot( plts..., - layout=(length(factuals), length(targets)), - size=(img_height * length(targets), img_height * length(factuals)), - dpi=300 + layout = (length(factuals), length(targets)), + size = (img_height * length(targets), img_height * length(factuals)), + dpi = 300, ) return plt @@ -167,7 +204,7 @@ end using MLDatasets using MosaicViews -function vae_reconstructions(seed=123) +function vae_reconstructions(seed = 123) # Set seed: if !isnothing(seed) @@ -175,30 +212,32 @@ function vae_reconstructions(seed=123) end counterfactual_data = load_mnist() - counterfactual_data.generative_model = CounterfactualExplanations.Models.load_mnist_vae() + counterfactual_data.generative_model = + CounterfactualExplanations.Models.load_mnist_vae() X = counterfactual_data.X - y = counterfactual_data.output_encoder.y + y = counterfactual_data.output_encoder.y images = [] rec_images = [] - for i in 0:9 + for i = 0:9 j = 0 while j < 10 - x = X[:,rand(findall(y .== i))] - x̂ = CounterfactualExplanations.GenerativeModels.reconstruct(vae, x)[1] |> - x̂ -> clamp.((x̂ .+ 1.0) ./ 2.0, 0.0, 1.0) |> - x̂ -> reshape(x̂, 28,28) |> - x̂ -> MLDatasets.convert2image(MNIST, x̂) - x = clamp.((x .+ 1.0) ./ 2.0, 0.0, 1.0) |> - x -> reshape(x, 28,28) |> - x -> MLDatasets.convert2image(MNIST, x) + x = X[:, rand(findall(y .== i))] + x̂ = + CounterfactualExplanations.GenerativeModels.reconstruct(vae, x)[1] |> + x̂ -> + clamp.((x̂ .+ 1.0) ./ 2.0, 0.0, 1.0) |> + x̂ -> reshape(x̂, 28, 28) |> x̂ -> MLDatasets.convert2image(MNIST, x̂) + x = + clamp.((x .+ 1.0) ./ 2.0, 0.0, 1.0) |> + x -> reshape(x, 28, 28) |> x -> MLDatasets.convert2image(MNIST, x) push!(images, x) push!(rec_images, x̂) j += 1 end end - p1 = plot(mosaic(images..., ncol=10), title="Images") - p2 = plot(mosaic(rec_images..., ncol=10), title="Reconstructions") - plt = plot(p1, p2, axis=false, size=(800,375)) + p1 = plot(mosaic(images..., ncol = 10), title = "Images") + p2 = plot(mosaic(rec_images..., ncol = 10), title = "Reconstructions") + plt = plot(p1, p2, axis = false, size = (800, 375)) return plt -end \ No newline at end of file +end diff --git a/experiments/post_processing/post_processing.jl b/experiments/post_processing/post_processing.jl index a79b23b0..85c4105f 100644 --- a/experiments/post_processing/post_processing.jl +++ b/experiments/post_processing/post_processing.jl @@ -1,4 +1,4 @@ include("meta_data.jl") include("artifacts.jl") include("results.jl") -include("plotting.jl") \ No newline at end of file +include("plotting.jl") diff --git a/experiments/post_processing/results.jl b/experiments/post_processing/results.jl index 98b81fab..3f35a649 100644 --- a/experiments/post_processing/results.jl +++ b/experiments/post_processing/results.jl @@ -3,14 +3,20 @@ Helper function to quickly filter a benchmark table for the distance from targets: the smaller this distance, the higher the plausibility. """ -function summarise_outcome(outcome::ExperimentOutcome; measure::Union{Nothing,AbstractArray}=nothing, model::Union{Nothing,AbstractArray}=nothing) +function summarise_outcome( + outcome::ExperimentOutcome; + measure::Union{Nothing,AbstractArray} = nothing, + model::Union{Nothing,AbstractArray} = nothing, +) bmk = outcome.bmk measure = isnothing(measure) ? unique(bmk().variable) : measure - df = groupby(bmk(), [:dataname, :generator, :model, :variable]) |> - x -> combine(x, :value => mean => :mean, :value => std => :std) |> - x -> subset(x, :variable => ByRow(x -> x ∈ measure)) + df = + groupby(bmk(), [:dataname, :generator, :model, :variable]) |> + x -> + combine(x, :value => mean => :mean, :value => std => :std) |> + x -> subset(x, :variable => ByRow(x -> x ∈ measure)) if !isnothing(model) df = subset(df, :model => ByRow(x -> x ∈ model)) end @@ -23,56 +29,64 @@ end Helper function to quickly filter a benchmark table for the distance from targets: the smaller this distance, the higher the plausibility. """ -plausibility(outcome::ExperimentOutcome; kwrgs...) = summarise_outcome(outcome, measure=["distance_from_targets_l2"], kwrgs...) +plausibility(outcome::ExperimentOutcome; kwrgs...) = + summarise_outcome(outcome, measure = ["distance_from_targets_l2"], kwrgs...) """ plausibility_image(outcome::ExperimentOutcome) Helper function to quickly filter a benchmark table for the distance from targets: the smaller this distance, the higher the plausibility. """ -plausibility_image(outcome::ExperimentOutcome; kwrgs...) = summarise_outcome(outcome, measure=["distance_from_targets_ssim"], kwrgs...) +plausibility_image(outcome::ExperimentOutcome; kwrgs...) = + summarise_outcome(outcome, measure = ["distance_from_targets_ssim"], kwrgs...) """ faithfulness(outcome::ExperimentOutcome) Helper function to quickly filter a benchmark table for the distance from energy: the smaller this distance, the higher the faithfulness. """ -faithfulness(outcome::ExperimentOutcome; kwrgs...) = summarise_outcome(outcome, measure=["distance_from_energy_l2"], kwrgs...) +faithfulness(outcome::ExperimentOutcome; kwrgs...) = + summarise_outcome(outcome, measure = ["distance_from_energy_l2"], kwrgs...) """ faithfulness_image(outcome::ExperimentOutcome) Helper function to quickly filter a benchmark table for the distance from energy: the smaller this distance, the higher the faithfulness. """ -faithfulness_image(outcome::ExperimentOutcome; kwrgs...) = summarise_outcome(outcome, measure=["distance_from_energy_ssim"], kwrgs...) +faithfulness_image(outcome::ExperimentOutcome; kwrgs...) = + summarise_outcome(outcome, measure = ["distance_from_energy_ssim"], kwrgs...) """ closeness(outcome::ExperimentOutcome) Helper function to quickly filter a benchmark table for the distance from the factual: the smaller this distance, the higher the closeness desideratum. """ -closeness(outcome::ExperimentOutcome; kwrgs...) = summarise_outcome(outcome, measure=["distance"], kwrgs...) +closeness(outcome::ExperimentOutcome; kwrgs...) = + summarise_outcome(outcome, measure = ["distance"], kwrgs...) """ validity(outcome::ExperimentOutcome) Helper function to quickly filter a benchmark table for the validity: the higher this value, the higher the validity. """ -validity(outcome::ExperimentOutcome; kwrgs...) = summarise_outcome(outcome, measure=["validity"], kwrgs...) +validity(outcome::ExperimentOutcome; kwrgs...) = + summarise_outcome(outcome, measure = ["validity"], kwrgs...) """ redundancy(outcome::ExperimentOutcome) Helper function to quickly filter a benchmark table for the redundancy: the higher this value, the higher the redundancy. """ -redundancy(outcome::ExperimentOutcome; kwrgs...) = summarise_outcome(outcome, measure=["redundancy"], kwrgs...) +redundancy(outcome::ExperimentOutcome; kwrgs...) = + summarise_outcome(outcome, measure = ["redundancy"], kwrgs...) """ uncertainty(outcome::ExperimentOutcome) Helper function to quickly filter a benchmark table for the uncertainty: the higher this value, the higher the uncertainty. """ -uncertainty(outcome::ExperimentOutcome; kwrgs...) = summarise_outcome(outcome, measure=["set_size_penalty"], kwrgs...) +uncertainty(outcome::ExperimentOutcome; kwrgs...) = + summarise_outcome(outcome, measure = ["set_size_penalty"], kwrgs...) """ generator_rank(outcome::ExperimentOutcome; generator::Union{AbstractArray,Nothing}=nothing, measure::Union{AbstractArray,Nothing}=nothing, model::Union{Nothing,String}=nothing) @@ -80,10 +94,10 @@ uncertainty(outcome::ExperimentOutcome; kwrgs...) = summarise_outcome(outcome, m Computes the average rank of a generator across all datasets and variables. """ function generator_rank( - outcome::ExperimentOutcome; - generator::Union{AbstractArray,Nothing}=nothing, - measure::Union{AbstractArray,Nothing}=nothing, - model::Union{Nothing,AbstractArray}=nothing + outcome::ExperimentOutcome; + generator::Union{AbstractArray,Nothing} = nothing, + measure::Union{AbstractArray,Nothing} = nothing, + model::Union{Nothing,AbstractArray} = nothing, ) # Setup: @@ -92,24 +106,31 @@ function generator_rank( measure = isnothing(measure) ? unique(bmk().variable) : measure # Compute: - results = summarise_outcome(outcome, measure=measure, model=model) + results = summarise_outcome(outcome, measure = measure, model = model) # Adjust variables for which higher is better: higher_is_better = [var ∈ ["validity", "redundancy"] for var in results.variable] - results.mean[higher_is_better] .= - results.mean[higher_is_better] + results.mean[higher_is_better] .= -results.mean[higher_is_better] # Compute ranks: - ranked_results = groupby(results, [:dataname, :model, :variable]) |> - x -> combine(x, :mean => sortperm => :rank, :generator) |> - x -> subset(x, :generator => ByRow(x -> x ∈ generator)) |> - x -> groupby(x, [:dataname, :generator, :variable]) |> - x -> combine(x, :rank => mean => :avg_rank) |> - x -> subset(x, :variable => ByRow(x -> x ∈ measure)) + ranked_results = + groupby(results, [:dataname, :model, :variable]) |> + x -> + combine(x, :mean => sortperm => :rank, :generator) |> + x -> + subset(x, :generator => ByRow(x -> x ∈ generator)) |> + x -> + groupby(x, [:dataname, :generator, :variable]) |> + x -> + combine(x, :rank => mean => :avg_rank) |> + x -> subset(x, :variable => ByRow(x -> x ∈ measure)) sort!(ranked_results, [:variable, :avg_rank]) return ranked_results end -generator_rank_plausibility(outcome::ExperimentOutcome; kwrgs...) = generator_rank(outcome, measure=["distance_from_targets_l2"], kwrgs...) - -generator_rank_faithfulness(outcome::ExperimentOutcome; kwrgs...) = generator_rank(outcome, measure=["distance_from_energy_l2"], kwrgs...) +generator_rank_plausibility(outcome::ExperimentOutcome; kwrgs...) = + generator_rank(outcome, measure = ["distance_from_targets_l2"], kwrgs...) -generator_rank_closeness(outcome::ExperimentOutcome; kwrgs...) = generator_rank(outcome, measure=["distance"], kwrgs...) +generator_rank_faithfulness(outcome::ExperimentOutcome; kwrgs...) = + generator_rank(outcome, measure = ["distance_from_energy_l2"], kwrgs...) +generator_rank_closeness(outcome::ExperimentOutcome; kwrgs...) = + generator_rank(outcome, measure = ["distance"], kwrgs...) diff --git a/experiments/run_experiments.jl b/experiments/run_experiments.jl index ecf1d226..8e636fd8 100644 --- a/experiments/run_experiments.jl +++ b/experiments/run_experiments.jl @@ -1,11 +1,21 @@ include("setup_env.jl"); # User inputs: -all_data_sets = ["linearly_separable", "moons", "circles", "mnist", "fmnist", "gmsc", "german_credit", "california_housing"] +all_data_sets = [ + "linearly_separable", + "moons", + "circles", + "mnist", + "fmnist", + "gmsc", + "german_credit", + "california_housing", +] if "run-all" in ARGS datanames = all_data_sets elseif any(contains.(ARGS, "data=")) - datanames = [ARGS[findall(contains.(ARGS, "data="))][1] |> x -> replace(x, "data=" => "")] + datanames = + [ARGS[findall(contains.(ARGS, "data="))][1] |> x -> replace(x, "data=" => "")] datanames = replace.(split(datanames[1], ","), " " => "") else @warn "No dataset specified, defaulting to all." diff --git a/experiments/save_best.jl b/experiments/save_best.jl index eb09cc1a..a97c0d4e 100644 --- a/experiments/save_best.jl +++ b/experiments/save_best.jl @@ -11,26 +11,31 @@ function save_best(outcomes_file_path::String) # Save data: output_path = replace(exper.output_path, "grid_search" => "") params_path = joinpath(output_path, "params") - Serialization.serialize(joinpath(output_path, "$(exper.save_name)_outcome.jls"), outcome) - Serialization.serialize(joinpath(output_path, "$(exper.save_name)_bmk.jls"), outcome.bmk) - Serialization.serialize(joinpath(output_path, "$(exper.save_name)_models.jls"), outcome.model_dict) - meta(outcome; save_output=true, params_path=params_path) + Serialization.serialize( + joinpath(output_path, "$(exper.save_name)_outcome.jls"), + outcome, + ) + Serialization.serialize( + joinpath(output_path, "$(exper.save_name)_bmk.jls"), + outcome.bmk, + ) + Serialization.serialize( + joinpath(output_path, "$(exper.save_name)_models.jls"), + outcome.model_dict, + ) + meta(outcome; save_output = true, params_path = params_path) end function bmk2csv(dataname::String) - bmk_path = joinpath( - DEFAULT_OUTPUT_PATH, - "$(replace(lowercase(dataname), " " => "_"))_bmk.jls", - ) + bmk_path = + joinpath(DEFAULT_OUTPUT_PATH, "$(replace(lowercase(dataname), " " => "_"))_bmk.jls") bmk = Serialization.deserialize(bmk_path) - csv_path = joinpath( - DEFAULT_OUTPUT_PATH, - "$(replace(lowercase(dataname), " " => "_"))_bmk.csv", - ) + csv_path = + joinpath(DEFAULT_OUTPUT_PATH, "$(replace(lowercase(dataname), " " => "_"))_bmk.csv") bmk = bmk() if "ce" ∈ names(bmk) - CSV.write(csv_path, bmk[:,Not(:ce)]) + CSV.write(csv_path, bmk[:, Not(:ce)]) else CSV.write(csv_path, bmk) end -end \ No newline at end of file +end diff --git a/experiments/setup_env.jl b/experiments/setup_env.jl index d61ad56d..411eada0 100644 --- a/experiments/setup_env.jl +++ b/experiments/setup_env.jl @@ -6,7 +6,8 @@ using CounterfactualExplanations.Data using CounterfactualExplanations.DataPreprocessing: train_test_split using CounterfactualExplanations.Evaluation: benchmark, evaluate, Benchmark using CounterfactualExplanations.Generators: JSMADescent -using CounterfactualExplanations.Models: load_mnist_mlp, load_fashion_mnist_mlp, train, probs +using CounterfactualExplanations.Models: + load_mnist_mlp, load_fashion_mnist_mlp, train, probs using CounterfactualExplanations.Objectives using CounterfactualExplanations.Parallelization using CSV @@ -20,7 +21,8 @@ using LazyArtifacts using Logging using Metalhead using MLJ: TunedModel, Grid, CV, fitted_params, report -using MLJBase: multiclass_f1score, accuracy, multiclass_precision, table, machine, fit!, Supervised +using MLJBase: + multiclass_f1score, accuracy, multiclass_precision, table, machine, fit!, Supervised using MLJEnsembles using MLJFlux using Random @@ -58,7 +60,7 @@ end if "mpi" ∈ ARGS MPI.Init() const USE_MPI = true - plz = MPIParallelizer(MPI.COMM_WORLD; threaded=USE_THREADS) + plz = MPIParallelizer(MPI.COMM_WORLD; threaded = USE_THREADS) if MPI.Comm_rank(MPI.COMM_WORLD) != 0 global_logger(NullLogger()) else @@ -83,7 +85,9 @@ const LATEST_ARTIFACT_PATH = joinpath(artifact_path(ARTIFACT_HASH), ARTIFACT_NAM time_stamped = false if any(contains.(ARGS, "output_path")) @assert sum(contains.(ARGS, "output_path")) == 1 "Only one output path can be specified." - _path = ARGS[findall(contains.(ARGS, "output_path"))][1] |> x -> replace(x, "output_path=" => "") + _path = + ARGS[findall(contains.(ARGS, "output_path"))][1] |> + x -> replace(x, "output_path=" => "") elseif isinteractive() @info "You are running experiments interactively. By default, results will be saved in a temporary directory." _path = tempdir() @@ -98,16 +102,16 @@ const DEFAULT_OUTPUT_PATH = _path const TIME_STAMPED = time_stamped "Boolean flag to only train models." -const ONLY_MODELS = "only_models" ∈ ARGS +const ONLY_MODELS = "only_models" ∈ ARGS "Boolean flag to retrain models." -const RETRAIN = "retrain" ∈ ARGS || ONLY_MODELS +const RETRAIN = "retrain" ∈ ARGS || ONLY_MODELS "Default model performance measures." const MODEL_MEASURES = Dict( :f1score => multiclass_f1score, :acc => accuracy, - :precision => multiclass_precision + :precision => multiclass_precision, ) "Default coverage rate." @@ -122,7 +126,7 @@ const CE_MEASURES = [ ECCCo.distance_from_targets_l2, CounterfactualExplanations.Evaluation.validity, CounterfactualExplanations.Evaluation.redundancy, - ECCCo.set_size_penalty + ECCCo.set_size_penalty, ] "Test set proportion." @@ -134,7 +138,9 @@ const UPLOAD = "upload" ∈ ARGS n_ind_specified = false if any(contains.(ARGS, "n_individuals=")) n_ind_specified = true - n_individuals = ARGS[findall(contains.(ARGS, "n_individuals="))][1] |> x -> replace(x, "n_individuals=" => "") |> x -> parse(Int, x) + n_individuals = + ARGS[findall(contains.(ARGS, "n_individuals="))][1] |> + x -> replace(x, "n_individuals=" => "") |> x -> parse(Int, x) else n_individuals = 100 end @@ -150,15 +156,10 @@ const GRID_SEARCH = "grid_search" ∈ ARGS "Generator tuning parameters." DEFAULT_GENERATOR_TUNING = ( - Λ=[ - [0.1, 0.1, 0.05], - [0.1, 0.1, 0.1], - [0.1, 0.1, 0.5], - [0.1, 0.1, 1.0], - ], - reg_strength=[0.0, 0.1, 0.25, 0.5, 1.0], - opt=[ - Flux.Optimise.Descent(0.1), + Λ = [[0.1, 0.1, 0.05], [0.1, 0.1, 0.1], [0.1, 0.1, 0.5], [0.1, 0.1, 1.0]], + reg_strength = [0.0, 0.1, 0.25, 0.5, 1.0], + opt = [ + Flux.Optimise.Descent(0.1), Flux.Optimise.Descent(0.05), Flux.Optimise.Descent(0.01), ], @@ -166,32 +167,19 @@ DEFAULT_GENERATOR_TUNING = ( "Generator tuning parameters for large datasets." DEFAULT_GENERATOR_TUNING_LARGE = ( - Λ=[ - [0.1, 0.1, 0.1], - [0.1, 0.1, 0.2], - [0.2, 0.2, 0.2], - ], - reg_strength=[0.0, 0.1, 0.5], - opt=[ - Flux.Optimise.Descent(0.01), - Flux.Optimise.Descent(0.05), - ], + Λ = [[0.1, 0.1, 0.1], [0.1, 0.1, 0.2], [0.2, 0.2, 0.2]], + reg_strength = [0.0, 0.1, 0.5], + opt = [Flux.Optimise.Descent(0.01), Flux.Optimise.Descent(0.05)], ) "Boolean flag to check if model tuning was specified." const TUNE_MODEL = "tune_model" ∈ ARGS "Model tuning parameters for small datasets." -DEFAULT_MODEL_TUNING_SMALL = ( - n_hidden=[16, 32, 64], - n_layers=[1, 2, 3], -) +DEFAULT_MODEL_TUNING_SMALL = (n_hidden = [16, 32, 64], n_layers = [1, 2, 3]) "Model tuning parameters for large datasets." -DEFAULT_MODEL_TUNING_LARGE = ( - n_hidden=[32, 64, 128, 512], - n_layers=[2, 3, 5], -) +DEFAULT_MODEL_TUNING_LARGE = (n_hidden = [32, 64, 128, 512], n_layers = [2, 3, 5]) "Boolean flag to check if store counterfactual explanations was specified." STORE_CE = "store_ce" ∈ ARGS diff --git a/experiments/upload_artifacts.jl b/experiments/upload_artifacts.jl index 83db07f1..72d16295 100644 --- a/experiments/upload_artifacts.jl +++ b/experiments/upload_artifacts.jl @@ -1,2 +1,2 @@ include("setup_env.jl"); -generate_artifacts() \ No newline at end of file +generate_artifacts() diff --git a/experiments/utils.jl b/experiments/utils.jl index 9b6b8834..2f9b6845 100644 --- a/experiments/utils.jl +++ b/experiments/utils.jl @@ -5,7 +5,10 @@ function is_multi_processed(parallelizer::Union{Nothing,AbstractParallelizer}) if isnothing(parallelizer) || isa(parallelizer, ThreadsParallelizer) return false else - return isa(parallelizer, Base.get_extension(CounterfactualExplanations, :MPIExt).MPIParallelizer) + return isa( + parallelizer, + Base.get_extension(CounterfactualExplanations, :MPIExt).MPIParallelizer, + ) end end @@ -18,7 +21,7 @@ function min_max_scale(x::AbstractArray) end function standardize(x::AbstractArray) - x_norm = (x .- sum(x)/length(x)) ./ std(x) + x_norm = (x .- sum(x) / length(x)) ./ std(x) x_norm = replace(x_norm, NaN => 0.0) return x_norm -end \ No newline at end of file +end diff --git a/src/ECCCo.jl b/src/ECCCo.jl index 0cb0f598..5d72878a 100644 --- a/src/ECCCo.jl +++ b/src/ECCCo.jl @@ -15,4 +15,4 @@ export conformal_training_loss export get_lowest_energy_sample export set_size_penalty, distance_from_energy -end \ No newline at end of file +end diff --git a/src/generator.jl b/src/generator.jl index 5974f513..a1595f61 100644 --- a/src/generator.jl +++ b/src/generator.jl @@ -2,19 +2,20 @@ using CounterfactualExplanations.Objectives using CounterfactualExplanations.Generators: GradientBasedGenerator "Constructor for `ECECCCoGenerator`: Energy Constrained Conformal Counterfactual Explanation Generator." -function ECCCoGenerator(; - λ::Union{AbstractFloat,Vector{<:AbstractFloat}}=[0.2,0.4,0.4], - κ::Real=1.0, - temp::Real=0.1, - opt::Union{Nothing,Flux.Optimise.AbstractOptimiser}=nothing, - use_class_loss::Bool=false, - use_energy_delta::Bool=false, - nsamples::Union{Nothing,Int}=nothing, - nmin::Union{Nothing,Int}=nothing, - niter::Union{Nothing,Int}=nothing, - reg_strength::Real=0.1, - dim_reduction::Bool=false, - kwargs... +function ECCCoGenerator(; + λ::Union{AbstractFloat,Vector{<:AbstractFloat}} = [0.2, 0.4, 0.4], + κ::Real = 1.0, + temp::Real = 0.1, + opt::Union{Nothing,Flux.Optimise.AbstractOptimiser} = nothing, + use_class_loss::Bool = false, + use_energy_delta::Bool = false, + nsamples::Union{Nothing,Int} = nothing, + nmin::Union{Nothing,Int} = nothing, + niter::Union{Nothing,Int} = nothing, + reg_strength::Real = 0.1, + decay::Tuple = (0.1, 1), + dim_reduction::Bool = false, + kwargs..., ) # Default ECCCo parameters @@ -29,21 +30,39 @@ function ECCCoGenerator(; # Loss function if use_class_loss - loss_fun(ce::AbstractCounterfactualExplanation) = conformal_training_loss(ce; temp=temp) + loss_fun(ce::AbstractCounterfactualExplanation) = + conformal_training_loss(ce; temp = temp) else loss_fun = nothing end _energy_penalty = - use_energy_delta ? (ECCCo.energy_delta, (n=nsamples, nmin=nmin, niter=niter, reg_strength=reg_strength)) : (ECCCo.distance_from_energy, (n=nsamples, nmin=nmin, niter=niter)) + use_energy_delta ? + ( + ECCCo.energy_delta, + ( + n = nsamples, + nmin = nmin, + niter = niter, + reg_strength = reg_strength, + decay = decay, + ), + ) : (ECCCo.distance_from_energy, (n = nsamples, nmin = nmin, niter = niter)) _penalties = [ - (Objectives.distance_l1, []), - (ECCCo.set_size_penalty, (κ=κ, temp=temp)), + (Objectives.distance_l1, []), + (ECCCo.set_size_penalty, (κ = κ, temp = temp)), _energy_penalty, ] λ = λ isa AbstractFloat ? [0.0, λ, λ] : λ # Generator - return GradientBasedGenerator(; loss=loss_fun, penalty=_penalties, λ=λ, opt=opt, dim_reduction=dim_reduction, kwargs...) -end \ No newline at end of file + return GradientBasedGenerator(; + loss = loss_fun, + penalty = _penalties, + λ = λ, + opt = opt, + dim_reduction = dim_reduction, + kwargs..., + ) +end diff --git a/src/losses.jl b/src/losses.jl index 2eada63d..d235f883 100644 --- a/src/losses.jl +++ b/src/losses.jl @@ -6,7 +6,12 @@ using Statistics: mean A configurable classification loss function for Conformal Predictors. """ -function conformal_training_loss(ce::AbstractCounterfactualExplanation; temp::Real=0.1, agg=mean, kwargs...) +function conformal_training_loss( + ce::AbstractCounterfactualExplanation; + temp::Real = 0.1, + agg = mean, + kwargs..., +) conf_model = ce.M.model fitresult = ce.M.fitresult X = CounterfactualExplanations.decode_state(ce) @@ -18,13 +23,17 @@ function conformal_training_loss(ce::AbstractCounterfactualExplanation; temp::Re n_classes = length(ce.data.y_levels) loss_mat = ones(n_classes, n_classes) - loss = map(eachslice(X, dims=ndims(X))) do x - x = ndims(x) == 1 ? x[:,:]' : x + loss = map(eachslice(X, dims = ndims(X))) do x + x = ndims(x) == 1 ? x[:, :]' : x ConformalPrediction.ConformalTraining.classification_loss( - conf_model, fitresult, x, y; - temp=temp, loss_matrix = loss_mat, + conf_model, + fitresult, + x, + y; + temp = temp, + loss_matrix = loss_mat, ) end loss = agg(loss)[1] return loss -end \ No newline at end of file +end diff --git a/src/model.jl b/src/model.jl index 445bf4c7..d942e440 100644 --- a/src/model.jl +++ b/src/model.jl @@ -8,7 +8,10 @@ using MLJFlux using MLUtils using Statistics -const CompatibleAtomicModel = Union{<:MLJFlux.MLJFluxProbabilistic,MLJEnsembles.ProbabilisticEnsembleModel{<:MLJFlux.MLJFluxProbabilistic}} +const CompatibleAtomicModel = Union{ + <:MLJFlux.MLJFluxProbabilistic, + MLJEnsembles.ProbabilisticEnsembleModel{<:MLJFlux.MLJFluxProbabilistic}, +} """ ConformalModel <: Models.AbstractDifferentiableModel @@ -20,7 +23,8 @@ struct ConformalModel <: Models.AbstractDifferentiableModel fitresult::Any likelihood::Union{Nothing,Symbol} function ConformalModel(model, fitresult, likelihood) - if likelihood ∈ [:classification_binary, :classification_multi] || isnothing(likelihood) + if likelihood ∈ [:classification_binary, :classification_multi] || + isnothing(likelihood) new(model, fitresult, likelihood) else throw( @@ -38,10 +42,10 @@ end Private function that extracts the chains from a fitted model. """ function _get_chains(fitresult) - + chains = [] - ignore_derivatives() do + ignore_derivatives() do if fitresult isa MLJEnsembles.WrappedEnsemble _chains = map(res -> res[1], fitresult.ensemble) else @@ -49,7 +53,7 @@ function _get_chains(fitresult) end push!(chains, _chains...) end - + return chains end @@ -103,7 +107,11 @@ end Outer constructor for `ConformalModel`. If `fitresult` is not specified, the model is not fitted and `likelihood` is inferred from the model. If `fitresult` is specified, `likelihood` is inferred from the output dimension of the model. If `likelihood` is not specified, it defaults to `:classification_binary`. """ -function ConformalModel(model, fitresult=nothing; likelihood::Union{Nothing,Symbol}=nothing) +function ConformalModel( + model, + fitresult = nothing; + likelihood::Union{Nothing,Symbol} = nothing, +) # Check if model is fitted and infer likelihood: if isnothing(fitresult) @@ -152,13 +160,13 @@ In the binary case logits are fed through the sigmoid function instead of softma which follows from the derivation here: https://stats.stackexchange.com/questions/233658/softmax-vs-sigmoid-function-in-logistic-classifier """ function Models.logits(M::ConformalModel, X::AbstractArray) - + fitresult = M.fitresult function predict_logits(fitresult, x) - ŷ = MLUtils.stack(map(chain -> get_logits(chain,x),_get_chains(fitresult))) |> - y -> mean(y, dims=ndims(y)) |> - y -> MLUtils.unstack(y, dims=ndims(y))[1] + ŷ = + MLUtils.stack(map(chain -> get_logits(chain, x), _get_chains(fitresult))) |> + y -> mean(y, dims = ndims(y)) |> y -> MLUtils.unstack(y, dims = ndims(y))[1] if ndims(ŷ) == 2 ŷ = [ŷ] end @@ -203,4 +211,4 @@ function Models.train(M::ConformalModel, data::CounterfactualData; kwrgs...) fit!(mach; kwrgs...) likelihood, _ = CounterfactualExplanations.guess_likelihood(data.output_encoder.y) return ConformalModel(mach.model, mach.fitresult, likelihood) -end \ No newline at end of file +end diff --git a/src/penalties.jl b/src/penalties.jl index 2e611097..b2c258ca 100644 --- a/src/penalties.jl +++ b/src/penalties.jl @@ -12,8 +12,10 @@ using Statistics: mean Penalty for smooth conformal set size. """ function set_size_penalty( - ce::AbstractCounterfactualExplanation; - κ::Real=1.0, temp::Real=0.1, agg=mean + ce::AbstractCounterfactualExplanation; + κ::Real = 1.0, + temp::Real = 0.1, + agg = mean, ) _loss = 0.0 @@ -21,15 +23,17 @@ function set_size_penalty( conf_model = ce.M.model fitresult = ce.M.fitresult X = CounterfactualExplanations.decode_state(ce) - _loss = map(eachslice(X, dims=ndims(X))) do x - x = ndims(x) == 1 ? x[:,:] : x + _loss = map(eachslice(X, dims = ndims(X))) do x + x = ndims(x) == 1 ? x[:, :] : x if target_probs(ce, x)[1] >= 0.5 l = ConformalPrediction.ConformalTraining.smooth_size_loss( - conf_model, fitresult, x'; - κ=κ, - temp=temp + conf_model, + fitresult, + x'; + κ = κ, + temp = temp, )[1] - else + else l = 0.0 end return l @@ -42,19 +46,22 @@ end function energy_delta( ce::AbstractCounterfactualExplanation; - n::Int=50, niter=500, from_buffer=true, agg=mean, - choose_lowest_energy=true, - choose_random=false, - nmin::Int=25, - return_conditionals=false, - reg_strength=0.1, - decay::Real=0.1, - kwargs... + n::Int = 50, + niter = 500, + from_buffer = true, + agg = mean, + choose_lowest_energy = true, + choose_random = false, + nmin::Int = 25, + return_conditionals = false, + reg_strength = 0.1, + decay::Tuple = (0.1, 1), + kwargs..., ) xproposed = CounterfactualExplanations.decode_state(ce) # current state t = get_target_index(ce.data.y_levels, ce.target) - E(x) = -logits(ce.M, x)[t,:] # negative logits for taraget class + E(x) = -logits(ce.M, x)[t, :] # negative logits for taraget class # Generative loss: gen_loss = E(xproposed) @@ -64,7 +71,17 @@ function energy_delta( reg_loss = norm(E(xproposed))^2 reg_loss = reduce((x, y) -> x + y, reg_loss) / length(reg_loss) # aggregate over samples - return gen_loss + reg_strength * reg_loss + # Decay: + iter = total_steps(ce) + ϕ = 1.0 + if iter % decay[2] == 0 + ϕ = exp(-decay * total_steps(ce)) + end + + # Total loss: + ℒ = ϕ * (gen_loss + reg_strength * reg_loss) + + return ℒ end @@ -75,13 +92,16 @@ Computes the distance from the counterfactual to generated conditional samples. """ function distance_from_energy( ce::AbstractCounterfactualExplanation; - n::Int=50, niter=500, from_buffer=true, agg=mean, - choose_lowest_energy=true, - choose_random=false, - nmin::Int=25, - return_conditionals=false, - p::Int=1, - kwargs... + n::Int = 50, + niter = 500, + from_buffer = true, + agg = mean, + choose_lowest_energy = true, + choose_random = false, + nmin::Int = 25, + return_conditionals = false, + p::Int = 1, + kwargs..., ) _loss = 0.0 @@ -93,24 +113,25 @@ function distance_from_energy( ignore_derivatives() do _dict = ce.params if !(:energy_sampler ∈ collect(keys(_dict))) - _dict[:energy_sampler] = ECCCo.EnergySampler(ce; niter=niter, nsamples=n, kwargs...) + _dict[:energy_sampler] = + ECCCo.EnergySampler(ce; niter = niter, nsamples = n, kwargs...) end eng_sampler = _dict[:energy_sampler] if choose_lowest_energy nmin = minimum([nmin, size(eng_sampler.buffer)[end]]) - xmin = ECCCo.get_lowest_energy_sample(eng_sampler; n=nmin) + xmin = ECCCo.get_lowest_energy_sample(eng_sampler; n = nmin) push!(conditional_samples, xmin) elseif choose_random - push!(conditional_samples, rand(eng_sampler, n; from_buffer=from_buffer)) + push!(conditional_samples, rand(eng_sampler, n; from_buffer = from_buffer)) else push!(conditional_samples, eng_sampler.buffer) end end _loss = map(eachcol(conditional_samples[1])) do xsample - distance(ce; from=xsample, agg=agg, p=p) + distance(ce; from = xsample, agg = agg, p = p) end - _loss = reduce((x,y) -> x + y, _loss) / n # aggregate over samples + _loss = reduce((x, y) -> x + y, _loss) / n # aggregate over samples if return_conditionals return conditional_samples[1] @@ -119,7 +140,8 @@ function distance_from_energy( end -distance_from_energy_l2(ce::AbstractCounterfactualExplanation; kwrgs...) = distance_from_energy(ce; p=2, kwrgs...) +distance_from_energy_l2(ce::AbstractCounterfactualExplanation; kwrgs...) = + distance_from_energy(ce; p = 2, kwrgs...) """ distance_from_energy_cosine(ce::AbstractCounterfactualExplanation) @@ -128,12 +150,15 @@ Computes the cosine distance from the counterfactual to generated conditional sa """ function distance_from_energy_cosine( ce::AbstractCounterfactualExplanation; - n::Int=50, niter=500, from_buffer=true, agg=mean, - choose_lowest_energy=true, - choose_random=false, - nmin::Int=25, - return_conditionals=false, - kwargs... + n::Int = 50, + niter = 500, + from_buffer = true, + agg = mean, + choose_lowest_energy = true, + choose_random = false, + nmin::Int = 25, + return_conditionals = false, + kwargs..., ) _loss = 0.0 @@ -145,15 +170,16 @@ function distance_from_energy_cosine( ignore_derivatives() do _dict = ce.params if !(:energy_sampler ∈ collect(keys(_dict))) - _dict[:energy_sampler] = ECCCo.EnergySampler(ce; niter=niter, nsamples=n, kwargs...) + _dict[:energy_sampler] = + ECCCo.EnergySampler(ce; niter = niter, nsamples = n, kwargs...) end eng_sampler = _dict[:energy_sampler] if choose_lowest_energy nmin = minimum([nmin, size(eng_sampler.buffer)[end]]) - xmin = ECCCo.get_lowest_energy_sample(eng_sampler; n=nmin) + xmin = ECCCo.get_lowest_energy_sample(eng_sampler; n = nmin) push!(conditional_samples, xmin) elseif choose_random - push!(conditional_samples, rand(eng_sampler, n; from_buffer=from_buffer)) + push!(conditional_samples, rand(eng_sampler, n; from_buffer = from_buffer)) else push!(conditional_samples, eng_sampler.buffer) end @@ -162,7 +188,7 @@ function distance_from_energy_cosine( _loss = map(eachcol(conditional_samples[1])) do xsample cos_dist(CounterfactualExplanations.counterfactual(ce), xsample) end - _loss = reduce((x,y) -> x + y, _loss) / n # aggregate over samples + _loss = reduce((x, y) -> x + y, _loss) / n # aggregate over samples if return_conditionals return conditional_samples[1] @@ -178,12 +204,15 @@ Computes 1-SSIM from the counterfactual to generated conditional samples where S """ function distance_from_energy_ssim( ce::AbstractCounterfactualExplanation; - n::Int=50, niter=500, from_buffer=true, agg=mean, - choose_lowest_energy=true, - choose_random=false, - nmin::Int=25, - return_conditionals=false, - kwargs... + n::Int = 50, + niter = 500, + from_buffer = true, + agg = mean, + choose_lowest_energy = true, + choose_random = false, + nmin::Int = 25, + return_conditionals = false, + kwargs..., ) _loss = 0.0 @@ -195,15 +224,16 @@ function distance_from_energy_ssim( ignore_derivatives() do _dict = ce.params if !(:energy_sampler ∈ collect(keys(_dict))) - _dict[:energy_sampler] = ECCCo.EnergySampler(ce; niter=niter, nsamples=n, kwargs...) + _dict[:energy_sampler] = + ECCCo.EnergySampler(ce; niter = niter, nsamples = n, kwargs...) end eng_sampler = _dict[:energy_sampler] if choose_lowest_energy nmin = minimum([nmin, size(eng_sampler.buffer)[end]]) - xmin = ECCCo.get_lowest_energy_sample(eng_sampler; n=nmin) + xmin = ECCCo.get_lowest_energy_sample(eng_sampler; n = nmin) push!(conditional_samples, xmin) elseif choose_random - push!(conditional_samples, rand(eng_sampler, n; from_buffer=from_buffer)) + push!(conditional_samples, rand(eng_sampler, n; from_buffer = from_buffer)) else push!(conditional_samples, eng_sampler.buffer) end @@ -228,14 +258,14 @@ Computes the distance from the counterfactual to the N-nearest neighbors of the """ function distance_from_targets( ce::AbstractCounterfactualExplanation; - agg=mean, - n_nearest_neighbors::Union{Int,Nothing}=100, - p::Int=1, + agg = mean, + n_nearest_neighbors::Union{Int,Nothing} = 100, + p::Int = 1, ) target_idx = ce.data.output_encoder.labels .== ce.target - target_samples = ce.data.X[:,target_idx] + target_samples = ce.data.X[:, target_idx] x′ = CounterfactualExplanations.counterfactual(ce) - loss = map(eachslice(x′, dims=ndims(x′))) do x + loss = map(eachslice(x′, dims = ndims(x′))) do x Δ = map(eachcol(target_samples)) do xsample norm(x - xsample, p) end @@ -250,7 +280,8 @@ function distance_from_targets( end -distance_from_targets_l2(ce::AbstractCounterfactualExplanation; kwrgs...) = distance_from_targets(ce; p=2, kwrgs...) +distance_from_targets_l2(ce::AbstractCounterfactualExplanation; kwrgs...) = + distance_from_targets(ce; p = 2, kwrgs...) @@ -261,14 +292,14 @@ Computes the cosine distance from the counterfactual to the N-nearest neighbors """ function distance_from_targets_cosine( ce::AbstractCounterfactualExplanation; - agg=mean, - n_nearest_neighbors::Union{Int,Nothing}=100, + agg = mean, + n_nearest_neighbors::Union{Int,Nothing} = 100, ) target_idx = ce.data.output_encoder.labels .== ce.target - target_samples = ce.data.X[:,target_idx] + target_samples = ce.data.X[:, target_idx] x′ = CounterfactualExplanations.counterfactual(ce) - loss = map(eachslice(x′, dims=ndims(x′))) do x + loss = map(eachslice(x′, dims = ndims(x′))) do x Δ = map(eachcol(target_samples)) do xsample cos_dist(x, xsample) end @@ -290,13 +321,13 @@ Computes the distance (1-SSIM) from the counterfactual to the N-nearest neighbor """ function distance_from_targets_ssim( ce::AbstractCounterfactualExplanation; - agg=mean, - n_nearest_neighbors::Union{Int,Nothing}=100, + agg = mean, + n_nearest_neighbors::Union{Int,Nothing} = 100, ) target_idx = ce.data.output_encoder.labels .== ce.target target_samples = ce.data.X[:, target_idx] x′ = CounterfactualExplanations.counterfactual(ce) - loss = map(eachslice(x′, dims=ndims(x′))) do x + loss = map(eachslice(x′, dims = ndims(x′))) do x Δ = map(eachcol(target_samples)) do xsample ssim_dist(x, xsample) end @@ -310,4 +341,3 @@ function distance_from_targets_ssim( return loss end - diff --git a/src/sampling.jl b/src/sampling.jl index f62f26f8..aedd495b 100644 --- a/src/sampling.jl +++ b/src/sampling.jl @@ -8,7 +8,8 @@ using JointEnergyModels When called on data `x`, softmax logits are returned. In the binary case, outputs are one-hot encoded. """ -(model::AbstractFittedModel)(x) = log.(CounterfactualExplanations.predict_proba(model, nothing, x)) +(model::AbstractFittedModel)(x) = + log.(CounterfactualExplanations.predict_proba(model, nothing, x)) "Base type that stores information relevant to energy-based posterior sampling from `AbstractFittedModel`." mutable struct EnergySampler @@ -36,9 +37,9 @@ function EnergySampler( model::AbstractFittedModel, data::CounterfactualData, y::Any; - opt::JointEnergyModels.AbstractSamplingRule=ImproperSGLD(), - niter::Int=100, - nsamples::Int=100 + opt::JointEnergyModels.AbstractSamplingRule = ImproperSGLD(), + niter::Int = 100, + nsamples::Int = 100, ) @assert y ∈ data.y_levels || y ∈ 1:length(data.y_levels) @@ -47,14 +48,14 @@ function EnergySampler( input_size = size(selectdim(data.X, ndims(data.X), 1)) 𝒟x = Uniform(extrema(data.X)...) 𝒟y = Categorical(ones(K) ./ K) - sampler = ConditionalSampler(𝒟x, 𝒟y; input_size=input_size) + sampler = ConditionalSampler(𝒟x, 𝒟y; input_size = input_size) yidx = get_target_index(data.y_levels, y) # Initiate: energy_sampler = EnergySampler(model, data, sampler, opt, nothing, yidx) # Generate conditional: - generate_samples!(energy_sampler, nsamples, yidx; niter=niter) + generate_samples!(energy_sampler, nsamples, yidx; niter = niter) return energy_sampler end @@ -67,10 +68,7 @@ end Constructor for `EnergySampler` that takes a `CounterfactualExplanation` as input. The underlying model, data and `target` are used for the `EnergySampler`, where `target` is the conditioning value of `y`. """ -function EnergySampler( - ce::CounterfactualExplanation; - kwrgs... -) +function EnergySampler(ce::CounterfactualExplanation; kwrgs...) # Setup: model = ce.M @@ -85,12 +83,12 @@ end Generates `n` samples from `EnergySampler` for conditioning value `y`. """ -function generate_samples(e::EnergySampler, n::Int, y::Int; niter::Int=100) +function generate_samples(e::EnergySampler, n::Int, y::Int; niter::Int = 100) # Generate samples: f(x) = logits(e.model, x) rule = e.opt - xsamples = e.sampler(f, rule; niter=niter, n_samples=n, y=y) + xsamples = e.sampler(f, rule; niter = niter, n_samples = n, y = y) return xsamples end @@ -100,11 +98,12 @@ end Generates `n` samples from `EnergySampler` for conditioning value `y`. Assigns samples and conditioning value to `EnergySampler`. """ -function generate_samples!(e::EnergySampler, n::Int, y::Int; niter::Int=100) +function generate_samples!(e::EnergySampler, n::Int, y::Int; niter::Int = 100) if isnothing(e.buffer) - e.buffer = generate_samples(e, n, y; niter=niter) + e.buffer = generate_samples(e, n, y; niter = niter) else - e.buffer = cat(e.buffer, generate_samples(e, n, y; niter=niter), dims=ndims(e.buffer)) + e.buffer = + cat(e.buffer, generate_samples(e, n, y; niter = niter), dims = ndims(e.buffer)) end e.yidx = y end @@ -114,13 +113,18 @@ end Overloads the `rand` method to randomly draw `n` samples from `EnergySampler`. """ -function Base.rand(sampler::EnergySampler, n::Int=100; from_buffer=true, niter::Int=100) +function Base.rand( + sampler::EnergySampler, + n::Int = 100; + from_buffer = true, + niter::Int = 100, +) ntotal = size(sampler.buffer, 2) idx = rand(1:ntotal, n) if from_buffer X = sampler.buffer[:, idx] else - X = generate_samples(sampler, n, sampler.yidx; niter=niter) + X = generate_samples(sampler, n, sampler.yidx; niter = niter) end return X end @@ -130,10 +134,14 @@ end Chooses the samples with the lowest energy (i.e. highest probability) from `EnergySampler`. """ -function get_lowest_energy_sample(sampler::EnergySampler; n::Int=5) +function get_lowest_energy_sample(sampler::EnergySampler; n::Int = 5) X = sampler.buffer model = sampler.model y = sampler.yidx - x = selectdim(X, ndims(X), energy(sampler.sampler, model, X, y; agg=x -> partialsortperm(x, 1:n))) + x = selectdim( + X, + ndims(X), + energy(sampler.sampler, model, X, y; agg = x -> partialsortperm(x, 1:n)), + ) return x -end \ No newline at end of file +end diff --git a/src/utils.jl b/src/utils.jl index 53909ec8..a476fc6c 100644 --- a/src/utils.jl +++ b/src/utils.jl @@ -5,7 +5,7 @@ using Images Helper function to add tiny noise to inputs. """ -function pre_process(x; noise::Float32=0.03f0) +function pre_process(x; noise::Float32 = 0.03f0) ϵ = Float32.(randn(size(x)) * noise) x += ϵ return x @@ -31,10 +31,7 @@ end Converts a vector to a 28x28 grey image. """ function convert2mnist(x) - x = (x .+ 1) ./ 2 |> - x -> reshape(x, 28, 28) |> - permutedims |> - x -> Gray.(x) + x = (x .+ 1) ./ 2 |> x -> reshape(x, 28, 28) |> permutedims |> x -> Gray.(x) return x end @@ -58,5 +55,5 @@ Computes 1-SSIM between two images. function ssim_dist(x, y) x = convert2mnist(x) y = convert2mnist(y) - return (1 - assess_ssim(x, y))/2 -end \ No newline at end of file + return (1 - assess_ssim(x, y)) / 2 +end From d63af8aa2bdeb63acb36c7b64074f914685f8db3 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Wed, 27 Sep 2023 11:12:21 +0200 Subject: [PATCH 002/171] manifest --- experiments/Manifest.toml | 40 ++++++++++++++++++++++----------------- 1 file changed, 23 insertions(+), 17 deletions(-) diff --git a/experiments/Manifest.toml b/experiments/Manifest.toml index e39e6d98..9b8a8f96 100644 --- a/experiments/Manifest.toml +++ b/experiments/Manifest.toml @@ -363,9 +363,9 @@ version = "0.3.0" [[deps.Compat]] deps = ["UUIDs"] -git-tree-sha1 = "e460f044ca8b99be31d35fe54fc33a5c33dd8ed7" +git-tree-sha1 = "8a62af3e248a8c4bad6b32cbbe663ae02275e32c" uuid = "34da2185-b29b-5c13-b0c7-acf172513d20" -version = "4.9.0" +version = "4.10.0" weakdeps = ["Dates", "LinearAlgebra"] [deps.Compat.extensions] @@ -434,9 +434,11 @@ version = "0.6.3" [[deps.CounterfactualExplanations]] deps = ["CSV", "CUDA", "CategoricalArrays", "ChainRulesCore", "DataFrames", "DecisionTree", "Distributions", "EvoTrees", "Flux", "LaplaceRedux", "LazyArtifacts", "LinearAlgebra", "Logging", "MLDatasets", "MLJBase", "MLJDecisionTreeInterface", "MLJModels", "MLUtils", "MultivariateStats", "NearestNeighborModels", "PackageExtensionCompat", "Parameters", "PrecompileTools", "ProgressMeter", "Random", "Serialization", "Statistics", "StatsBase", "Tables", "UUIDs", "cuDNN"] -git-tree-sha1 = "14da4a8ea118b96c2477b05d5bc1c353c1d80e79" +git-tree-sha1 = "082d60e57d67cf5302ca007ccad053270d401f5f" +repo-rev = "main" +repo-url = "https://github.com/JuliaTrustworthyAI/CounterfactualExplanations.jl.git" uuid = "2f13d31b-18db-44c1-bc43-ebaf2cff0be0" -version = "0.1.28" +version = "0.1.29" [deps.CounterfactualExplanations.extensions] MPIExt = "MPI" @@ -541,9 +543,9 @@ uuid = "8ba89e20-285c-5b6f-9357-94700520ee1b" [[deps.Distributions]] deps = ["FillArrays", "LinearAlgebra", "PDMats", "Printf", "QuadGK", "Random", "SpecialFunctions", "Statistics", "StatsAPI", "StatsBase", "StatsFuns", "Test"] -git-tree-sha1 = "938fe2981db009f531b6332e31c58e9584a2f9bd" +git-tree-sha1 = "9e11104e7b41a8a5f04e8694467fc1f94a135bd7" uuid = "31c24e10-a181-5473-b8eb-7969acd0382f" -version = "0.25.100" +version = "0.25.101" [deps.Distributions.extensions] DistributionsChainRulesCoreExt = "ChainRulesCore" @@ -853,10 +855,14 @@ uuid = "42e2da0e-8278-4e71-bc24-59509adca0fe" version = "1.0.2" [[deps.HDF5]] -deps = ["Compat", "HDF5_jll", "Libdl", "Mmap", "Printf", "Random", "Requires", "UUIDs"] -git-tree-sha1 = "114e20044677badbc631ee6fdc80a67920561a29" +deps = ["Compat", "HDF5_jll", "Libdl", "MPIPreferences", "Mmap", "Preferences", "Printf", "Random", "Requires", "UUIDs"] +git-tree-sha1 = "ec7df74b7b2022e8252a8bfd4ec23411491adc3b" uuid = "f67ccb44-e63f-5c2f-98bd-6dc0ccc4ba2f" -version = "0.16.16" +version = "0.17.0" +weakdeps = ["MPI"] + + [deps.HDF5.extensions] + MPIExt = "MPI" [[deps.HDF5_jll]] deps = ["Artifacts", "JLLWrappers", "LibCURL_jll", "Libdl", "OpenSSL_jll", "Pkg", "Zlib_jll"] @@ -1148,9 +1154,9 @@ version = "0.1.3" [[deps.JpegTurbo]] deps = ["CEnum", "FileIO", "ImageCore", "JpegTurbo_jll", "TOML"] -git-tree-sha1 = "327713faef2a3e5c80f96bf38d1fa26f7a6ae29e" +git-tree-sha1 = "d65930fa2bc96b07d7691c652d701dcbe7d9cf0b" uuid = "b835a17e-a41a-41e7-81f0-2f016b05efe0" -version = "0.1.3" +version = "0.1.4" [[deps.JpegTurbo_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl"] @@ -1380,9 +1386,9 @@ weakdeps = ["CategoricalArrays"] [[deps.MAT]] deps = ["BufferedStreams", "CodecZlib", "HDF5", "SparseArrays"] -git-tree-sha1 = "79fd0b5ee384caf8ebba6c8fb3f365ca3e2c5493" +git-tree-sha1 = "ed1cf0a322d78cee07718bed5fd945e2218c35a1" uuid = "23992714-dd62-5051-b70f-ba57cb901cac" -version = "0.10.5" +version = "0.10.6" [[deps.MKL_jll]] deps = ["Artifacts", "IntelOpenMP_jll", "JLLWrappers", "LazyArtifacts", "Libdl", "Pkg"] @@ -1768,9 +1774,9 @@ version = "10.42.0+0" [[deps.PDMats]] deps = ["LinearAlgebra", "SparseArrays", "SuiteSparse"] -git-tree-sha1 = "3129380a93388e5062e946974246fe3f2e7c73e2" +git-tree-sha1 = "bf6085e8bd7735e68c210c6e5d81f9a6fe192060" uuid = "90014a1f-27ba-587c-ab20-58faa44d9150" -version = "0.11.18" +version = "0.11.19" [[deps.PNGFiles]] deps = ["Base64", "CEnum", "ImageCore", "IndirectArrays", "OffsetArrays", "libpng_jll"] @@ -2677,9 +2683,9 @@ version = "1.5.5+0" [[deps.Zygote]] deps = ["AbstractFFTs", "ChainRules", "ChainRulesCore", "DiffRules", "Distributed", "FillArrays", "ForwardDiff", "GPUArrays", "GPUArraysCore", "IRTools", "InteractiveUtils", "LinearAlgebra", "LogExpFunctions", "MacroTools", "NaNMath", "PrecompileTools", "Random", "Requires", "SparseArrays", "SpecialFunctions", "Statistics", "ZygoteRules"] -git-tree-sha1 = "b97c927497c1de55a78dc9030f6068be5d83ef80" +git-tree-sha1 = "16848c23e7961e099a4152ba0d10db887f412ee9" uuid = "e88e6eb3-aa80-5325-afca-941959d7151f" -version = "0.6.64" +version = "0.6.65" [deps.Zygote.extensions] ZygoteColorsExt = "Colors" From d478bcca6ae29a1758a539300232263e45a89c8d Mon Sep 17 00:00:00 2001 From: pat-alt Date: Wed, 27 Sep 2023 11:43:50 +0200 Subject: [PATCH 003/171] uh --- experiments/setup_env.jl | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/experiments/setup_env.jl b/experiments/setup_env.jl index 411eada0..e7eedf51 100644 --- a/experiments/setup_env.jl +++ b/experiments/setup_env.jl @@ -163,13 +163,15 @@ DEFAULT_GENERATOR_TUNING = ( Flux.Optimise.Descent(0.05), Flux.Optimise.Descent(0.01), ], + decay=[(0.0, 1), (0.1, 1), (0.5, 1),], ) "Generator tuning parameters for large datasets." DEFAULT_GENERATOR_TUNING_LARGE = ( Λ = [[0.1, 0.1, 0.1], [0.1, 0.1, 0.2], [0.2, 0.2, 0.2]], - reg_strength = [0.0, 0.1, 0.5], + reg_strength = [0.0], opt = [Flux.Optimise.Descent(0.01), Flux.Optimise.Descent(0.05)], + decay = [(0.0, 1), (0.1, 1), (0.5, 1),], ) "Boolean flag to check if model tuning was specified." From b674b4a1ea7e26205af59119e0e1c2e9a156a211 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Wed, 27 Sep 2023 13:03:14 +0200 Subject: [PATCH 004/171] rejigged grid search a little --- experiments/grid_search.jl | 27 +++++++++++++++++++-------- 1 file changed, 19 insertions(+), 8 deletions(-) diff --git a/experiments/grid_search.jl b/experiments/grid_search.jl index fc0efebb..d06214f5 100644 --- a/experiments/grid_search.jl +++ b/experiments/grid_search.jl @@ -1,3 +1,5 @@ +using DataFrames + """ grid_search( couterfactual_data::CounterfactualData, @@ -24,7 +26,8 @@ function grid_search( # Grid setup: tuning_params = [Pair.(k, vals) for (k, vals) in pairs(tuning_params)] grid = Iterators.product(tuning_params...) - outcomes = Dict{Any,Any}() + df_params = [] + df_outcomes = [] # Search: counter = 1 @@ -40,10 +43,18 @@ function grid_search( tuning_params..., kwargs..., ) - outcomes[tuning_params] = outcome + _df_params = DataFrame(Dict(:id => counter, pairs(tuning_params))) + _df_outcomes = DataFrame(Dict(:id => counter, :params => tuning_params, :outcome => outcome)) + push!(df_params, _df_params) + push!(df_outcomes, _df_outcomes) counter += 1 end + outcomes = Dict( + :df_params => vcat(df_params...), + :df_outcomes => vcat(df_outcomes...), + ) + # Save: if !(is_multi_processed(PLZ) && MPI.Comm_rank(PLZ.comm) != 0) Serialization.serialize( @@ -104,7 +115,7 @@ function best_rank_outcome( df_weights = DataFrame(variable = measure, weight = weights) ranks = [] - for (params, outcome) in outcomes + for outcome in outcomes.df_outcomes.outcome _ranks = generator_rank( outcome; @@ -119,8 +130,8 @@ function best_rank_outcome( end best_index = argmin(ranks) best_outcome = ( - params = collect(keys(outcomes))[best_index], - outcome = collect(values(outcomes))[best_index], + params=outcomes.df_outcomes.params[best_index], + outcome=outcomes.df_outcomes.outcomes[best_index], ) return best_outcome end @@ -148,7 +159,7 @@ function best_absolute_outcome( df_weights = DataFrame(variable = measure, weight = weights) avg_values = [] - for (params, outcome) in outcomes + for (params, outcome) in (outcomes.df_outcomes.params, outcomes.df_outcomes.outcome) # Setup evaluation = deepcopy(outcome.bmk.evaluation) @@ -191,8 +202,8 @@ function best_absolute_outcome( end best_index = argmin(avg_values) best_outcome = ( - params = collect(keys(outcomes))[best_index], - outcome = collect(values(outcomes))[best_index], + params = outcomes.df_outcomes.params[best_index], + outcome = outcomes.df_outcomes.outcomes[best_index], ) end From e967eaeb58cfd9717fe3bb8610b1082444c73345 Mon Sep 17 00:00:00 2001 From: Pat Alt <55311242+pat-alt@users.noreply.github.com> Date: Wed, 27 Sep 2023 13:44:22 +0200 Subject: [PATCH 005/171] bam --- src/penalties.jl | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/penalties.jl b/src/penalties.jl index b2c258ca..b295d174 100644 --- a/src/penalties.jl +++ b/src/penalties.jl @@ -75,7 +75,7 @@ function energy_delta( iter = total_steps(ce) ϕ = 1.0 if iter % decay[2] == 0 - ϕ = exp(-decay * total_steps(ce)) + ϕ = exp(-decay[1] * total_steps(ce)) end # Total loss: From 73db72846be5ea58df7f0dc895c39ac6e0880b94 Mon Sep 17 00:00:00 2001 From: Pat Alt <55311242+pat-alt@users.noreply.github.com> Date: Wed, 27 Sep 2023 14:17:54 +0200 Subject: [PATCH 006/171] fixed --- experiments/grid_search.jl | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/experiments/grid_search.jl b/experiments/grid_search.jl index d06214f5..74add7aa 100644 --- a/experiments/grid_search.jl +++ b/experiments/grid_search.jl @@ -43,7 +43,7 @@ function grid_search( tuning_params..., kwargs..., ) - _df_params = DataFrame(Dict(:id => counter, pairs(tuning_params))) + _df_params = DataFrame(merge(Dict(:id => counter), Dict(pairs(tuning_params)))) _df_outcomes = DataFrame(Dict(:id => counter, :params => tuning_params, :outcome => outcome)) push!(df_params, _df_params) push!(df_outcomes, _df_outcomes) From 1074249643bc7bab61c19dc44fa2f8b121c5c79e Mon Sep 17 00:00:00 2001 From: Pat Alt <55311242+pat-alt@users.noreply.github.com> Date: Wed, 27 Sep 2023 15:08:20 +0200 Subject: [PATCH 007/171] fix: --- experiments/benchmarking/benchmarking.jl | 8 ++++---- experiments/grid_search.jl | 24 +++++++++++++----------- experiments/setup_env.jl | 4 ++-- 3 files changed, 19 insertions(+), 17 deletions(-) diff --git a/experiments/benchmarking/benchmarking.jl b/experiments/benchmarking/benchmarking.jl index 83f94764..74ffc5a6 100644 --- a/experiments/benchmarking/benchmarking.jl +++ b/experiments/benchmarking/benchmarking.jl @@ -65,7 +65,7 @@ function default_generators(; nmin = nmin, niter = niter_eccco, reg_strength = reg_strength, - decay=decay, + decay = decay, ), "ECCCo-Δ (no EBM)" => ECCCoGenerator( λ = [λ₁_Δ, λ₂_Δ, 0.0], @@ -76,7 +76,7 @@ function default_generators(; nmin = nmin, niter = niter_eccco, reg_strength = reg_strength, - decay=decay, + decay = decay, ), ) else @@ -101,7 +101,7 @@ function default_generators(; nmin = nmin, niter = niter_eccco, reg_strength = reg_strength, - decay=decay, + decay = decay, ), ) end @@ -119,7 +119,7 @@ function default_generators(; nmin = nmin, niter = niter_eccco, reg_strength = reg_strength, - decay=decay, + decay = decay, dim_reduction = dim_reduction, ), ) diff --git a/experiments/grid_search.jl b/experiments/grid_search.jl index 74add7aa..edf46805 100644 --- a/experiments/grid_search.jl +++ b/experiments/grid_search.jl @@ -31,8 +31,8 @@ function grid_search( # Search: counter = 1 - for tuning_params in grid - @info "Running experiment $(counter)/$(length(grid)) with tuning parameters: $(tuning_params)" + for params in grid + @info "Running experiment $(counter)/$(length(grid)) with tuning parameters: $(params)" outcome = run_experiment( counterfactual_data, test_data; @@ -40,20 +40,22 @@ function grid_search( dataname = dataname, n_individuals = n_individuals, output_path = grid_search_path, - tuning_params..., + params..., kwargs..., ) - _df_params = DataFrame(merge(Dict(:id => counter), Dict(pairs(tuning_params)))) - _df_outcomes = DataFrame(Dict(:id => counter, :params => tuning_params, :outcome => outcome)) + + _df_params = + DataFrame(merge(Dict(:id => counter), Dict(params))) |> + x -> select(x, :id, Not(:id)) + _df_outcomes = + DataFrame(Dict(:id => counter, :params => params, :outcome => outcome)) |> + x -> select(x, :id, Not(:id)) push!(df_params, _df_params) push!(df_outcomes, _df_outcomes) counter += 1 end - outcomes = Dict( - :df_params => vcat(df_params...), - :df_outcomes => vcat(df_outcomes...), - ) + outcomes = Dict(:df_params => vcat(df_params...), :df_outcomes => vcat(df_outcomes...)) # Save: if !(is_multi_processed(PLZ) && MPI.Comm_rank(PLZ.comm) != 0) @@ -130,8 +132,8 @@ function best_rank_outcome( end best_index = argmin(ranks) best_outcome = ( - params=outcomes.df_outcomes.params[best_index], - outcome=outcomes.df_outcomes.outcomes[best_index], + params = outcomes.df_outcomes.params[best_index], + outcome = outcomes.df_outcomes.outcomes[best_index], ) return best_outcome end diff --git a/experiments/setup_env.jl b/experiments/setup_env.jl index e7eedf51..9c793815 100644 --- a/experiments/setup_env.jl +++ b/experiments/setup_env.jl @@ -163,7 +163,7 @@ DEFAULT_GENERATOR_TUNING = ( Flux.Optimise.Descent(0.05), Flux.Optimise.Descent(0.01), ], - decay=[(0.0, 1), (0.1, 1), (0.5, 1),], + decay = [(0.0, 1), (0.1, 1), (0.5, 1)], ) "Generator tuning parameters for large datasets." @@ -171,7 +171,7 @@ DEFAULT_GENERATOR_TUNING_LARGE = ( Λ = [[0.1, 0.1, 0.1], [0.1, 0.1, 0.2], [0.2, 0.2, 0.2]], reg_strength = [0.0], opt = [Flux.Optimise.Descent(0.01), Flux.Optimise.Descent(0.05)], - decay = [(0.0, 1), (0.1, 1), (0.5, 1),], + decay = [(0.0, 1), (0.1, 1), (0.5, 1)], ) "Boolean flag to check if model tuning was specified." From 3046e809822290fcf9389c5da23901dbfb944310 Mon Sep 17 00:00:00 2001 From: Pat Alt <55311242+pat-alt@users.noreply.github.com> Date: Wed, 27 Sep 2023 17:39:13 +0200 Subject: [PATCH 008/171] fixed --- experiments/grid_search.jl | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/experiments/grid_search.jl b/experiments/grid_search.jl index edf46805..88aa93c9 100644 --- a/experiments/grid_search.jl +++ b/experiments/grid_search.jl @@ -117,7 +117,7 @@ function best_rank_outcome( df_weights = DataFrame(variable = measure, weight = weights) ranks = [] - for outcome in outcomes.df_outcomes.outcome + for outcome in outcomes[:df_outcomes].outcome _ranks = generator_rank( outcome; @@ -161,7 +161,7 @@ function best_absolute_outcome( df_weights = DataFrame(variable = measure, weight = weights) avg_values = [] - for (params, outcome) in (outcomes.df_outcomes.params, outcomes.df_outcomes.outcome) + for (params, outcome) in (outcomes[:df_outcomes].params, outcomes[:df_outcomes].outcome) # Setup evaluation = deepcopy(outcome.bmk.evaluation) From 968c385a3b7f5c6c2ec53e50b51482726e751ec2 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Fri, 29 Sep 2023 09:39:44 +0200 Subject: [PATCH 009/171] storing ce for cali --- .../tuning/generators/innovation/california_housing.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/experiments/jobscripts/tuning/generators/innovation/california_housing.sh b/experiments/jobscripts/tuning/generators/innovation/california_housing.sh index a9bc302a..351e4602 100644 --- a/experiments/jobscripts/tuning/generators/innovation/california_housing.sh +++ b/experiments/jobscripts/tuning/generators/innovation/california_housing.sh @@ -11,4 +11,4 @@ module load 2023r1 openmpi -srun julia --project=experiments experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search n_individuals=20 > experiments/grid_search_california_housing.log +srun julia --project=experiments experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search n_individuals=20 store_ce > experiments/grid_search_california_housing.log From 6e8bda71f3568c058a8d0f45bec5209dd7644e31 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Fri, 29 Sep 2023 09:53:31 +0200 Subject: [PATCH 010/171] uh --- experiments/grid_search.jl | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/experiments/grid_search.jl b/experiments/grid_search.jl index 88aa93c9..45c24e6a 100644 --- a/experiments/grid_search.jl +++ b/experiments/grid_search.jl @@ -161,7 +161,7 @@ function best_absolute_outcome( df_weights = DataFrame(variable = measure, weight = weights) avg_values = [] - for (params, outcome) in (outcomes[:df_outcomes].params, outcomes[:df_outcomes].outcome) + for (params, outcome) in zip(outcomes[:df_outcomes].params, outcomes[:df_outcomes].outcome) # Setup evaluation = deepcopy(outcome.bmk.evaluation) From 212c8a04310131d85b1003c8e21f5155182554ca Mon Sep 17 00:00:00 2001 From: pat-alt Date: Fri, 29 Sep 2023 10:00:40 +0200 Subject: [PATCH 011/171] no yes --- experiments/grid_search.jl | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/experiments/grid_search.jl b/experiments/grid_search.jl index 45c24e6a..aa6aa1b4 100644 --- a/experiments/grid_search.jl +++ b/experiments/grid_search.jl @@ -132,8 +132,8 @@ function best_rank_outcome( end best_index = argmin(ranks) best_outcome = ( - params = outcomes.df_outcomes.params[best_index], - outcome = outcomes.df_outcomes.outcomes[best_index], + params=outcomes[:df_outcomes].params[best_index], + outcome=outcomes[:df_outcomes].outcomes[best_index], ) return best_outcome end @@ -204,8 +204,8 @@ function best_absolute_outcome( end best_index = argmin(avg_values) best_outcome = ( - params = outcomes.df_outcomes.params[best_index], - outcome = outcomes.df_outcomes.outcomes[best_index], + params=outcomes[:df_outcomes].params[best_index], + outcome=outcomes[:df_outcomes].outcomes[best_index], ) end From 3e97f5fa73d112164c4b13222d49b70768609f84 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Fri, 29 Sep 2023 10:06:40 +0200 Subject: [PATCH 012/171] uh --- experiments/grid_search.jl | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/experiments/grid_search.jl b/experiments/grid_search.jl index aa6aa1b4..e2f66709 100644 --- a/experiments/grid_search.jl +++ b/experiments/grid_search.jl @@ -133,7 +133,7 @@ function best_rank_outcome( best_index = argmin(ranks) best_outcome = ( params=outcomes[:df_outcomes].params[best_index], - outcome=outcomes[:df_outcomes].outcomes[best_index], + outcome=outcomes[:df_outcomes].outcome[best_index], ) return best_outcome end @@ -205,7 +205,7 @@ function best_absolute_outcome( best_index = argmin(avg_values) best_outcome = ( params=outcomes[:df_outcomes].params[best_index], - outcome=outcomes[:df_outcomes].outcomes[best_index], + outcome=outcomes[:df_outcomes].outcome[best_index], ) end From cdc331f71ea3b172a6130ab9a90b71be2f0bdde2 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Fri, 29 Sep 2023 15:07:33 +0200 Subject: [PATCH 013/171] moving grid search results into temporary storage --- experiments/grid_search.jl | 38 ++++++++++++++++++++++++++++++-------- 1 file changed, 30 insertions(+), 8 deletions(-) diff --git a/experiments/grid_search.jl b/experiments/grid_search.jl index e2f66709..5bdb5aaa 100644 --- a/experiments/grid_search.jl +++ b/experiments/grid_search.jl @@ -26,8 +26,11 @@ function grid_search( # Grid setup: tuning_params = [Pair.(k, vals) for (k, vals) in pairs(tuning_params)] grid = Iterators.product(tuning_params...) - df_params = [] - df_outcomes = [] + + # Temporary storage on disk: + storage_path = joinpath(grid_search_path, ".tmp_results_$(replace(lowercase(dataname), " " => "_"))") + mkpath(storage_path) + @info "Storing temporary results in $(storage_path)." # Search: counter = 1 @@ -44,21 +47,39 @@ function grid_search( kwargs..., ) - _df_params = + df_params = DataFrame(merge(Dict(:id => counter), Dict(params))) |> x -> select(x, :id, Not(:id)) - _df_outcomes = + df_outcomes = DataFrame(Dict(:id => counter, :params => params, :outcome => outcome)) |> x -> select(x, :id, Not(:id)) - push!(df_params, _df_params) - push!(df_outcomes, _df_outcomes) + + # Save: + if !(is_multi_processed(PLZ) && MPI.Comm_rank(PLZ.comm) != 0) + Serialization.serialize( + joinpath(storage_path, "$(params)_$(counter).jls"), + df_params, + ) + Serialization.serialize( + joinpath(storage_path, "$(outcomes)_$(counter).jls"), + df_outcomes, + ) + end counter += 1 end - outcomes = Dict(:df_params => vcat(df_params...), :df_outcomes => vcat(df_outcomes...)) - # Save: if !(is_multi_processed(PLZ) && MPI.Comm_rank(PLZ.comm) != 0) + + # Deserialise: + df_params = [] + df_outcomes = [] + for i in 1:length(grid) + df_params = push!(df_params, Serialization.deserialize(joinpath(storage_path_params, "$(i).jls"))) + df_outcomes = push!(df_outcomes; Serialization.deserialize(joinpath(storage_path_outcomes, "$(i).jls"))) + end + outcomes = Dict(:df_params => vcat(df_params...), :df_outcomes => vcat(df_outcomes...)) + Serialization.serialize( joinpath(grid_search_path, "$(replace(lowercase(dataname), " " => "_")).jls"), outcomes, @@ -85,6 +106,7 @@ function grid_search( best_absolute_outcome_eccco_Δ(outcomes), ) end + end const ALL_ECCCO_NAMES = [ From d3f7291e97b908eb11ec9827e38273734877de61 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Fri, 29 Sep 2023 15:34:53 +0200 Subject: [PATCH 014/171] trying to reduce memory usage by moving temporary grid search results out of memory --- experiments/grid_search.jl | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/experiments/grid_search.jl b/experiments/grid_search.jl index 5bdb5aaa..3a62e9a3 100644 --- a/experiments/grid_search.jl +++ b/experiments/grid_search.jl @@ -57,11 +57,11 @@ function grid_search( # Save: if !(is_multi_processed(PLZ) && MPI.Comm_rank(PLZ.comm) != 0) Serialization.serialize( - joinpath(storage_path, "$(params)_$(counter).jls"), + joinpath(storage_path, "params_$(counter).jls"), df_params, ) Serialization.serialize( - joinpath(storage_path, "$(outcomes)_$(counter).jls"), + joinpath(storage_path, "outcomes_$(counter).jls"), df_outcomes, ) end @@ -75,8 +75,8 @@ function grid_search( df_params = [] df_outcomes = [] for i in 1:length(grid) - df_params = push!(df_params, Serialization.deserialize(joinpath(storage_path_params, "$(i).jls"))) - df_outcomes = push!(df_outcomes; Serialization.deserialize(joinpath(storage_path_outcomes, "$(i).jls"))) + push!(df_params, Serialization.deserialize(joinpath(storage_path, "params_$(i).jls"))) + push!(df_outcomes, Serialization.deserialize(joinpath(storage_path, "outcomes_$(i).jls"))) end outcomes = Dict(:df_params => vcat(df_params...), :df_outcomes => vcat(df_outcomes...)) From b36ec996428a81eb4749a2c5cd8d18463ef42854 Mon Sep 17 00:00:00 2001 From: Pat Alt <55311242+pat-alt@users.noreply.github.com> Date: Tue, 3 Oct 2023 13:49:00 +0200 Subject: [PATCH 015/171] batching --- experiments/Manifest.toml | 72 ++++++++++++++++++++------------------- experiments/setup_env.jl | 46 ++++++++++++++++--------- 2 files changed, 66 insertions(+), 52 deletions(-) diff --git a/experiments/Manifest.toml b/experiments/Manifest.toml index 9b8a8f96..683a8b01 100644 --- a/experiments/Manifest.toml +++ b/experiments/Manifest.toml @@ -276,9 +276,9 @@ version = "0.5.0" [[deps.ChainRules]] deps = ["Adapt", "ChainRulesCore", "Compat", "Distributed", "GPUArraysCore", "IrrationalConstants", "LinearAlgebra", "Random", "RealDot", "SparseArrays", "SparseInverseSubset", "Statistics", "StructArrays", "SuiteSparse"] -git-tree-sha1 = "dbeca245b0680f5393b4e6c40dcead7230ab0b3b" +git-tree-sha1 = "01b0594d8907485ed894bc59adfc0a24a9cde7a3" uuid = "082447d4-558c-5d27-93f4-14fc19e9eca2" -version = "1.54.0" +version = "1.55.0" [[deps.ChainRulesCore]] deps = ["Compat", "LinearAlgebra", "SparseArrays"] @@ -433,12 +433,12 @@ uuid = "150eb455-5306-5404-9cee-2592286d6298" version = "0.6.3" [[deps.CounterfactualExplanations]] -deps = ["CSV", "CUDA", "CategoricalArrays", "ChainRulesCore", "DataFrames", "DecisionTree", "Distributions", "EvoTrees", "Flux", "LaplaceRedux", "LazyArtifacts", "LinearAlgebra", "Logging", "MLDatasets", "MLJBase", "MLJDecisionTreeInterface", "MLJModels", "MLUtils", "MultivariateStats", "NearestNeighborModels", "PackageExtensionCompat", "Parameters", "PrecompileTools", "ProgressMeter", "Random", "Serialization", "Statistics", "StatsBase", "Tables", "UUIDs", "cuDNN"] -git-tree-sha1 = "082d60e57d67cf5302ca007ccad053270d401f5f" +deps = ["CSV", "CUDA", "CategoricalArrays", "ChainRulesCore", "DataFrames", "DecisionTree", "Distributions", "EvoTrees", "Flux", "LaplaceRedux", "LazyArtifacts", "LinearAlgebra", "Logging", "MLDatasets", "MLJBase", "MLJDecisionTreeInterface", "MLJModels", "MLUtils", "MultivariateStats", "NearestNeighborModels", "PackageExtensionCompat", "Parameters", "PkgTemplates", "PrecompileTools", "ProgressMeter", "Random", "Serialization", "Statistics", "StatsBase", "Tables", "UUIDs", "cuDNN"] +git-tree-sha1 = "1f1861d5b947a7af85c2172e3791c03453b6a183" repo-rev = "main" repo-url = "https://github.com/JuliaTrustworthyAI/CounterfactualExplanations.jl.git" uuid = "2f13d31b-18db-44c1-bc43-ebaf2cff0be0" -version = "0.1.29" +version = "0.1.30" [deps.CounterfactualExplanations.extensions] MPIExt = "MPI" @@ -543,9 +543,9 @@ uuid = "8ba89e20-285c-5b6f-9357-94700520ee1b" [[deps.Distributions]] deps = ["FillArrays", "LinearAlgebra", "PDMats", "Printf", "QuadGK", "Random", "SpecialFunctions", "Statistics", "StatsAPI", "StatsBase", "StatsFuns", "Test"] -git-tree-sha1 = "9e11104e7b41a8a5f04e8694467fc1f94a135bd7" +git-tree-sha1 = "3d5873f811f582873bb9871fc9c451784d5dc8c7" uuid = "31c24e10-a181-5473-b8eb-7969acd0382f" -version = "0.25.101" +version = "0.25.102" [deps.Distributions.extensions] DistributionsChainRulesCoreExt = "ChainRulesCore" @@ -674,9 +674,9 @@ version = "1.16.1" [[deps.FilePathsBase]] deps = ["Compat", "Dates", "Mmap", "Printf", "Test", "UUIDs"] -git-tree-sha1 = "e27c4ebe80e8699540f2d6c805cc12203b614f12" +git-tree-sha1 = "9f00e42f8d99fdde64d40c8ea5d14269a2e2c1aa" uuid = "48062228-2e41-5def-b9a4-89aafe57970f" -version = "0.9.20" +version = "0.9.21" [[deps.FileWatching]] uuid = "7b1f6079-737a-58dc-b8bc-7a2ca5c1b5ee" @@ -804,9 +804,9 @@ version = "0.6.1" [[deps.GeoInterface]] deps = ["Extents"] -git-tree-sha1 = "bb198ff907228523f3dee1070ceee63b9359b6ab" +git-tree-sha1 = "d53480c0793b13341c40199190f92c611aa2e93c" uuid = "cf35fbd7-0cd7-5166-be24-54bfbe79505f" -version = "1.3.1" +version = "1.3.2" [[deps.GeometryBasics]] deps = ["EarCut_jll", "Extents", "GeoInterface", "IterTools", "LinearAlgebra", "StaticArrays", "StructArrays", "Tables"] @@ -845,9 +845,9 @@ version = "1.3.14+0" [[deps.Graphs]] deps = ["ArnoldiMethod", "Compat", "DataStructures", "Distributed", "Inflate", "LinearAlgebra", "Random", "SharedArrays", "SimpleTraits", "SparseArrays", "Statistics"] -git-tree-sha1 = "1cf1d7dcb4bc32d7b4a5add4232db3750c27ecb4" +git-tree-sha1 = "899050ace26649433ef1af25bc17a815b3db52b7" uuid = "86223c79-3864-5bf0-83f7-82e725a168b6" -version = "1.8.0" +version = "1.9.0" [[deps.Grisu]] git-tree-sha1 = "53bb909d1151e57e2484c3d1b53e19552b887fb2" @@ -856,9 +856,9 @@ version = "1.0.2" [[deps.HDF5]] deps = ["Compat", "HDF5_jll", "Libdl", "MPIPreferences", "Mmap", "Preferences", "Printf", "Random", "Requires", "UUIDs"] -git-tree-sha1 = "ec7df74b7b2022e8252a8bfd4ec23411491adc3b" +git-tree-sha1 = "26407bd1c60129062cec9da63dc7d08251544d53" uuid = "f67ccb44-e63f-5c2f-98bd-6dc0ccc4ba2f" -version = "0.17.0" +version = "0.17.1" weakdeps = ["MPI"] [deps.HDF5.extensions] @@ -1196,15 +1196,15 @@ version = "3.0.0+1" [[deps.LLVM]] deps = ["CEnum", "LLVMExtra_jll", "Libdl", "Printf", "Unicode"] -git-tree-sha1 = "a9d2ce1d5007b1e8f6c5b89c5a31ff8bd146db5c" +git-tree-sha1 = "4ea2928a96acfcf8589e6cd1429eff2a3a82c366" uuid = "929cbde3-209d-540e-8aea-75f648917ca0" -version = "6.2.1" +version = "6.3.0" [[deps.LLVMExtra_jll]] deps = ["Artifacts", "JLLWrappers", "LazyArtifacts", "Libdl", "TOML"] -git-tree-sha1 = "7ca6850ae880cc99b59b88517545f91a52020afa" +git-tree-sha1 = "e7c01b69bcbcb93fd4cbc3d0fea7d229541e18d2" uuid = "dad2f222-ce93-54a1-a47d-0025e8a3acab" -version = "0.0.25+0" +version = "0.0.26+0" [[deps.LLVMOpenMP_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"] @@ -1481,9 +1481,9 @@ version = "0.4.3" [[deps.MPI]] deps = ["Distributed", "DocStringExtensions", "Libdl", "MPICH_jll", "MPIPreferences", "MPItrampoline_jll", "MicrosoftMPI_jll", "OpenMPI_jll", "PkgVersion", "PrecompileTools", "Requires", "Serialization", "Sockets"] -git-tree-sha1 = "df53d0e1e0dbebf2315f4cd35e13e52ad43416c2" +git-tree-sha1 = "b4d8707e42b693720b54f0b3434abee6dd4d947a" uuid = "da04e1cc-30fd-572f-bb4f-1f8673147195" -version = "0.20.15" +version = "0.20.16" [deps.MPI.extensions] AMDGPUExt = "AMDGPU" @@ -1567,9 +1567,9 @@ version = "0.1.4" [[deps.MicrosoftMPI_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"] -git-tree-sha1 = "a8027af3d1743b3bfae34e54872359fdebb31422" +git-tree-sha1 = "a7023883872e52bc29bcaac74f19adf39347d2d5" uuid = "9237b28f-5490-5468-be7b-bb81f5f5e6cf" -version = "10.1.3+4" +version = "10.1.4+0" [[deps.Missings]] deps = ["DataAPI"] @@ -1615,18 +1615,20 @@ version = "0.3.0" [[deps.NNlib]] deps = ["Adapt", "Atomix", "ChainRulesCore", "GPUArraysCore", "KernelAbstractions", "LinearAlgebra", "Pkg", "Random", "Requires", "Statistics"] -git-tree-sha1 = "6e4e90c2e2ef091ef50b91af65fa4bb09c3d0728" +git-tree-sha1 = "3bc568de99214f72a76c7773ade218819afcc36e" uuid = "872c559c-99b0-510c-b3b7-b6c96a88d5cd" -version = "0.9.6" +version = "0.9.7" [deps.NNlib.extensions] NNlibAMDGPUExt = "AMDGPU" NNlibCUDACUDNNExt = ["CUDA", "cuDNN"] NNlibCUDAExt = "CUDA" + NNlibEnzymeCoreExt = "EnzymeCore" [deps.NNlib.weakdeps] AMDGPU = "21141c5a-9bdb-4563-92ae-f87d6854732e" CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba" + EnzymeCore = "f151be2c-9106-41f4-ab19-57ee4f262869" cuDNN = "02a925ec-e4fe-4b08-9a7e-0d78e3d38ccd" [[deps.NPZ]] @@ -1728,9 +1730,9 @@ version = "0.3.1" [[deps.OpenMPI_jll]] deps = ["Artifacts", "CompilerSupportLibraries_jll", "JLLWrappers", "LazyArtifacts", "Libdl", "MPIPreferences", "TOML"] -git-tree-sha1 = "f3080f4212a8ba2ceb10a34b938601b862094314" +git-tree-sha1 = "e25c1778a98e34219a00455d6e4384e017ea9762" uuid = "fe0851c0-eecd-5654-98d4-656369965a5c" -version = "4.1.5+0" +version = "4.1.6+0" [[deps.OpenSSL]] deps = ["BitFlags", "Dates", "MozillaCACerts_jll", "OpenSSL_jll", "Sockets"] @@ -1774,9 +1776,9 @@ version = "10.42.0+0" [[deps.PDMats]] deps = ["LinearAlgebra", "SparseArrays", "SuiteSparse"] -git-tree-sha1 = "bf6085e8bd7735e68c210c6e5d81f9a6fe192060" +git-tree-sha1 = "b7c4f29f93b548caa58f703580f4d79ab753c8ac" uuid = "90014a1f-27ba-587c-ab20-58faa44d9150" -version = "0.11.19" +version = "0.11.21" [[deps.PNGFiles]] deps = ["Base64", "CEnum", "ImageCore", "IndirectArrays", "OffsetArrays", "libpng_jll"] @@ -2238,9 +2240,9 @@ weakdeps = ["OffsetArrays", "StaticArrays"] [[deps.StaticArrays]] deps = ["LinearAlgebra", "Random", "StaticArraysCore"] -git-tree-sha1 = "d5fb407ec3179063214bc6277712928ba78459e2" +git-tree-sha1 = "0adf069a2a490c47273727e029371b31d44b72b2" uuid = "90137ffa-7385-5640-81b9-e52037218182" -version = "1.6.4" +version = "1.6.5" weakdeps = ["Statistics"] [deps.StaticArrays.extensions] @@ -2373,9 +2375,9 @@ version = "0.5.2" [[deps.TiffImages]] deps = ["ColorTypes", "DataStructures", "DocStringExtensions", "FileIO", "FixedPointNumbers", "IndirectArrays", "Inflate", "Mmap", "OffsetArrays", "PkgVersion", "ProgressMeter", "UUIDs"] -git-tree-sha1 = "b7dc44cb005a7ef743b8fe98970afef003efdce7" +git-tree-sha1 = "7fd97bd1c5b1ff53a291cbd351d1d3d6ff4da5a5" uuid = "731e570b-9d59-4bfa-96dc-6df516fadf69" -version = "0.6.6" +version = "0.6.7" [[deps.TiledIteration]] deps = ["OffsetArrays", "StaticArrayInterface"] @@ -2528,9 +2530,9 @@ version = "1.6.1" [[deps.XML2_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl", "Libiconv_jll", "Zlib_jll"] -git-tree-sha1 = "04a51d15436a572301b5abbb9d099713327e9fc4" +git-tree-sha1 = "24b81b59bd35b3c42ab84fa589086e19be919916" uuid = "02c8fc9c-b97f-50b9-bbe4-9be30ff0a78a" -version = "2.10.4+0" +version = "2.11.5+0" [[deps.XSLT_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl", "Libgcrypt_jll", "Libgpg_error_jll", "Libiconv_jll", "Pkg", "XML2_jll", "Zlib_jll"] diff --git a/experiments/setup_env.jl b/experiments/setup_env.jl index 9c793815..4a68251f 100644 --- a/experiments/setup_env.jl +++ b/experiments/setup_env.jl @@ -47,6 +47,34 @@ include("post_processing/post_processing.jl") include("utils.jl") include("save_best.jl") +# Number of counterfactuals: +n_ind_specified = false +if any(contains.(ARGS, "n_individuals=")) + n_ind_specified = true + n_individuals = + ARGS[findall(contains.(ARGS, "n_individuals="))][1] |> + x -> replace(x, "n_individuals=" => "") |> x -> parse(Int, x) +else + n_individuals = 100 +end + +"Number of individuals to use in benchmarking." +const N_IND = n_individuals + +"Boolean flag to check if number of individuals was specified." +const N_IND_SPECIFIED = n_ind_specified + +if any(contains.(ARGS, "n_each=")) + n_each = + ARGS[findall(contains.(ARGS, "n_each="))][1] |> + x -> replace(x, "n_each=" => "") |> x -> parse(Int, x) +else + n_each = 16 +end + +"Number of objects to pass to each process." +const N_EACH = n_each + # Parallelization: plz = nothing @@ -60,7 +88,7 @@ end if "mpi" ∈ ARGS MPI.Init() const USE_MPI = true - plz = MPIParallelizer(MPI.COMM_WORLD; threaded = USE_THREADS) + plz = MPIParallelizer(MPI.COMM_WORLD; threaded = USE_THREADS, n_each = N_EACH) if MPI.Comm_rank(MPI.COMM_WORLD) != 0 global_logger(NullLogger()) else @@ -135,22 +163,6 @@ const TEST_SIZE = 0.2 "Boolean flag to check if upload was specified." const UPLOAD = "upload" ∈ ARGS -n_ind_specified = false -if any(contains.(ARGS, "n_individuals=")) - n_ind_specified = true - n_individuals = - ARGS[findall(contains.(ARGS, "n_individuals="))][1] |> - x -> replace(x, "n_individuals=" => "") |> x -> parse(Int, x) -else - n_individuals = 100 -end - -"Number of individuals to use in benchmarking." -const N_IND = n_individuals - -"Boolean flag to check if number of individuals was specified." -const N_IND_SPECIFIED = n_ind_specified - "Boolean flag to check if grid search was specified." const GRID_SEARCH = "grid_search" ∈ ARGS From 8d50e7bee63c83957b22f57c0ca1bf28ebc6f026 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Tue, 3 Oct 2023 14:46:57 +0200 Subject: [PATCH 016/171] adjusted cali specs --- .../tuning/generators/innovation/california_housing.sh | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/experiments/jobscripts/tuning/generators/innovation/california_housing.sh b/experiments/jobscripts/tuning/generators/innovation/california_housing.sh index 351e4602..23560139 100644 --- a/experiments/jobscripts/tuning/generators/innovation/california_housing.sh +++ b/experiments/jobscripts/tuning/generators/innovation/california_housing.sh @@ -2,10 +2,10 @@ #SBATCH --job-name="Grid-search California Housing (ECCCo)" #SBATCH --time=04:00:00 -#SBATCH --ntasks=48 +#SBATCH --ntasks=24 #SBATCH --cpus-per-task=1 #SBATCH --partition=compute -#SBATCH --mem-per-cpu=4GB +#SBATCH --mem-per-cpu=8GB #SBATCH --account=innovation #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. From 235e790d5bf503b33f483753e4b50f7afa19b831 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Wed, 4 Oct 2023 10:04:55 +0200 Subject: [PATCH 017/171] cutting down n_each --- .../tuning/generators/innovation/california_housing.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/experiments/jobscripts/tuning/generators/innovation/california_housing.sh b/experiments/jobscripts/tuning/generators/innovation/california_housing.sh index 23560139..0430b6c5 100644 --- a/experiments/jobscripts/tuning/generators/innovation/california_housing.sh +++ b/experiments/jobscripts/tuning/generators/innovation/california_housing.sh @@ -11,4 +11,4 @@ module load 2023r1 openmpi -srun julia --project=experiments experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search n_individuals=20 store_ce > experiments/grid_search_california_housing.log +srun julia --project=experiments experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search n_individuals=20 n_each=5 store_ce > experiments/grid_search_califoenia_housing.log From 9ae247d9599d0da760b8227b8c614760ec293acc Mon Sep 17 00:00:00 2001 From: pat-alt Date: Wed, 4 Oct 2023 11:12:09 +0200 Subject: [PATCH 018/171] n_each up slightly --- .../tuning/generators/innovation/california_housing.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/experiments/jobscripts/tuning/generators/innovation/california_housing.sh b/experiments/jobscripts/tuning/generators/innovation/california_housing.sh index 0430b6c5..7360a6a9 100644 --- a/experiments/jobscripts/tuning/generators/innovation/california_housing.sh +++ b/experiments/jobscripts/tuning/generators/innovation/california_housing.sh @@ -11,4 +11,4 @@ module load 2023r1 openmpi -srun julia --project=experiments experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search n_individuals=20 n_each=5 store_ce > experiments/grid_search_califoenia_housing.log +srun julia --project=experiments experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search n_individuals=20 n_each=8 store_ce > experiments/grid_search_califoenia_housing.log From aff3fffa5bfda8d22351f6fbaa8c4df8b4423246 Mon Sep 17 00:00:00 2001 From: Pat Alt <55311242+pat-alt@users.noreply.github.com> Date: Wed, 4 Oct 2023 11:12:59 +0200 Subject: [PATCH 019/171] slight change to how grid results are stored --- experiments/grid_search.jl | 1 + experiments/setup_env.jl | 20 +++++++++++++------- 2 files changed, 14 insertions(+), 7 deletions(-) diff --git a/experiments/grid_search.jl b/experiments/grid_search.jl index 3a62e9a3..a648675c 100644 --- a/experiments/grid_search.jl +++ b/experiments/grid_search.jl @@ -47,6 +47,7 @@ function grid_search( kwargs..., ) + params = map(x -> typeof(x[2]) <: Vector ? x[1] => Tuple(x[2]) : x[1] => x[2], params) df_params = DataFrame(merge(Dict(:id => counter), Dict(params))) |> x -> select(x, :id, Not(:id)) diff --git a/experiments/setup_env.jl b/experiments/setup_env.jl index 4a68251f..29a64d54 100644 --- a/experiments/setup_env.jl +++ b/experiments/setup_env.jl @@ -16,6 +16,7 @@ using DataFrames using Distributions: Normal, Distribution, Categorical, Uniform using ECCCo using Flux +using Flux.Optimise: Optimiser, Descent, Adam, ClipValue using JointEnergyModels using LazyArtifacts using Logging @@ -171,19 +172,24 @@ DEFAULT_GENERATOR_TUNING = ( Λ = [[0.1, 0.1, 0.05], [0.1, 0.1, 0.1], [0.1, 0.1, 0.5], [0.1, 0.1, 1.0]], reg_strength = [0.0, 0.1, 0.25, 0.5, 1.0], opt = [ - Flux.Optimise.Descent(0.1), - Flux.Optimise.Descent(0.05), - Flux.Optimise.Descent(0.01), + Descent(0.01), + Descent(0.05), + Descent(0.1), ], - decay = [(0.0, 1), (0.1, 1), (0.5, 1)], + decay = [(0.0, 1), (0.01, 1), (0.1, 1)], ) "Generator tuning parameters for large datasets." DEFAULT_GENERATOR_TUNING_LARGE = ( Λ = [[0.1, 0.1, 0.1], [0.1, 0.1, 0.2], [0.2, 0.2, 0.2]], - reg_strength = [0.0], - opt = [Flux.Optimise.Descent(0.01), Flux.Optimise.Descent(0.05)], - decay = [(0.0, 1), (0.1, 1), (0.5, 1)], + reg_strength = [0.0, 0.1, 0.25,], + opt = [ + Descent(0.01), + Descent(0.05), + Optimiser(ClipValue(0.01), Descent(0.01)), + Optimiser(ClipValue(0.05), Descent(0.05)), + ], + decay = [(0.0, 1), (0.01, 1), (0.1, 1)], ) "Boolean flag to check if model tuning was specified." From 4a21070e27a9e6197c0bfda6b29e5536aea72bbf Mon Sep 17 00:00:00 2001 From: Pat Alt <55311242+pat-alt@users.noreply.github.com> Date: Wed, 4 Oct 2023 11:26:16 +0200 Subject: [PATCH 020/171] argument to specify number of benchmark runs --- experiments/benchmarking/benchmarking.jl | 1 + experiments/experiment.jl | 1 + experiments/setup_env.jl | 13 +++++++++++++ 3 files changed, 15 insertions(+) diff --git a/experiments/benchmarking/benchmarking.jl b/experiments/benchmarking/benchmarking.jl index 74ffc5a6..f07bd6db 100644 --- a/experiments/benchmarking/benchmarking.jl +++ b/experiments/benchmarking/benchmarking.jl @@ -175,6 +175,7 @@ function run_benchmark(exper::Experiment, model_dict::Dict) converge_when = :generator_conditions, parallelizer = parallelizer, store_ce = exper.store_ce, + n_runs = exper.n_runs, ) return bmk, generator_dict end diff --git a/experiments/experiment.jl b/experiments/experiment.jl index 333e7478..b1a68c73 100644 --- a/experiments/experiment.jl +++ b/experiments/experiment.jl @@ -25,6 +25,7 @@ Base.@kwdef struct Experiment coverage::Float64 = DEFAULT_COVERAGE generators::Union{Nothing,Dict} = nothing n_individuals::Int = N_IND + n_runs::Int = N_RUNS ce_measures::AbstractArray = CE_MEASURES model_measures::Dict = MODEL_MEASURES use_class_loss::Bool = false diff --git a/experiments/setup_env.jl b/experiments/setup_env.jl index 29a64d54..a7b2108a 100644 --- a/experiments/setup_env.jl +++ b/experiments/setup_env.jl @@ -65,6 +65,7 @@ const N_IND = n_individuals "Boolean flag to check if number of individuals was specified." const N_IND_SPECIFIED = n_ind_specified +# Number of tasks per process: if any(contains.(ARGS, "n_each=")) n_each = ARGS[findall(contains.(ARGS, "n_each="))][1] |> @@ -76,6 +77,18 @@ end "Number of objects to pass to each process." const N_EACH = n_each +# Number of benchmark runs: +if any(contains.(ARGS, "n_runs=")) + n_runs = + ARGS[findall(contains.(ARGS, "n_runs="))][1] |> + x -> replace(x, "n_runs=" => "") |> x -> parse(Int, x) +else + n_runs = 1 +end + +"Number of benchmark runs." +const N_RUNS = n_runs + # Parallelization: plz = nothing From 3ec4339c71dbd5a0fa4cff8e8729df07155b8936 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Wed, 4 Oct 2023 12:27:21 +0200 Subject: [PATCH 021/171] whatever --- .../tuning/generators/innovation/california_housing.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/experiments/jobscripts/tuning/generators/innovation/california_housing.sh b/experiments/jobscripts/tuning/generators/innovation/california_housing.sh index 7360a6a9..acb8e623 100644 --- a/experiments/jobscripts/tuning/generators/innovation/california_housing.sh +++ b/experiments/jobscripts/tuning/generators/innovation/california_housing.sh @@ -11,4 +11,4 @@ module load 2023r1 openmpi -srun julia --project=experiments experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search n_individuals=20 n_each=8 store_ce > experiments/grid_search_califoenia_housing.log +srun julia --project=experiments experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search n_individuals=20 n_each=32 store_ce > experiments/grid_search_califoenia_housing.log From 2d01bfd957f6ba2d1f9db3d5122933d534bd87fb Mon Sep 17 00:00:00 2001 From: Pat Alt <55311242+pat-alt@users.noreply.github.com> Date: Wed, 4 Oct 2023 12:28:32 +0200 Subject: [PATCH 022/171] trying more cores --- .../jobscripts/tuning/generators/california_housing.sh | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/experiments/jobscripts/tuning/generators/california_housing.sh b/experiments/jobscripts/tuning/generators/california_housing.sh index 373d6607..ded42416 100644 --- a/experiments/jobscripts/tuning/generators/california_housing.sh +++ b/experiments/jobscripts/tuning/generators/california_housing.sh @@ -1,7 +1,7 @@ #!/bin/bash #SBATCH --job-name="Grid-search California Housing (ECCCo)" -#SBATCH --time=04:00:00 +#SBATCH --time=02:00:00 #SBATCH --ntasks=100 #SBATCH --cpus-per-task=1 #SBATCH --partition=compute @@ -11,4 +11,4 @@ module load 2023r1 openmpi -srun julia --project=experiments experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search n_individuals=25 store_ce > experiments/grid_search_california_housing.log +srun julia --project=experiments experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search n_individuals=20 store_ce > experiments/grid_search_california_housing.log From c9ce83868c4dab26d71a6bb10813145a46dfcd04 Mon Sep 17 00:00:00 2001 From: Pat Alt <55311242+pat-alt@users.noreply.github.com> Date: Wed, 4 Oct 2023 12:36:43 +0200 Subject: [PATCH 023/171] daic testing --- experiments/daic/testing/lin_sep.sh | 14 ++++++++++++++ experiments/daic/testing/lin_sep_4each.sh | 14 ++++++++++++++ experiments/daic/testing/lin_sep_threaded.sh | 14 ++++++++++++++ .../daic/tuning/generators/linearly_separable.sh | 14 ++++++++++++++ 4 files changed, 56 insertions(+) create mode 100644 experiments/daic/testing/lin_sep.sh create mode 100644 experiments/daic/testing/lin_sep_4each.sh create mode 100644 experiments/daic/testing/lin_sep_threaded.sh create mode 100644 experiments/daic/tuning/generators/linearly_separable.sh diff --git a/experiments/daic/testing/lin_sep.sh b/experiments/daic/testing/lin_sep.sh new file mode 100644 index 00000000..ff674ad2 --- /dev/null +++ b/experiments/daic/testing/lin_sep.sh @@ -0,0 +1,14 @@ +#!/bin/bash + +#SBATCH --job-name="Grid-search Linearly Separable (ECCCo)" +#SBATCH --time=01:00:00 +#SBATCH --ntasks=100 +#SBATCH --cpus-per-task=1 +#SBATCH --partition=general +#SBATCH --mem-per-cpu=4GB +#SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. + +module use /opt/insy/modulefiles # Use DAIC INSY software collection +module load openmpi + +srun julia --project=experiments experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=10 > experiments/grid_search_linearly_separable.log diff --git a/experiments/daic/testing/lin_sep_4each.sh b/experiments/daic/testing/lin_sep_4each.sh new file mode 100644 index 00000000..b5891999 --- /dev/null +++ b/experiments/daic/testing/lin_sep_4each.sh @@ -0,0 +1,14 @@ +#!/bin/bash + +#SBATCH --job-name="Grid-search Linearly Separable (ECCCo)" +#SBATCH --time=01:00:00 +#SBATCH --ntasks=100 +#SBATCH --cpus-per-task=1 +#SBATCH --partition=general +#SBATCH --mem-per-cpu=4GB +#SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. + +module use /opt/insy/modulefiles # Use DAIC INSY software collection +module load openmpi + +srun julia --project=experiments experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=10 n_each=4 > experiments/grid_search_linearly_separable.log diff --git a/experiments/daic/testing/lin_sep_threaded.sh b/experiments/daic/testing/lin_sep_threaded.sh new file mode 100644 index 00000000..b07c5e80 --- /dev/null +++ b/experiments/daic/testing/lin_sep_threaded.sh @@ -0,0 +1,14 @@ +#!/bin/bash + +#SBATCH --job-name="Grid-search Linearly Separable (ECCCo)" +#SBATCH --time=01:00:00 +#SBATCH --ntasks=10 +#SBATCH --cpus-per-task=10 +#SBATCH --partition=general +#SBATCH --mem-per-cpu=4GB +#SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. + +module use /opt/insy/modulefiles # Use DAIC INSY software collection +module load openmpi + +srun julia --project=experiments experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=10 threaded > experiments/grid_search_linearly_separable.log diff --git a/experiments/daic/tuning/generators/linearly_separable.sh b/experiments/daic/tuning/generators/linearly_separable.sh new file mode 100644 index 00000000..20d2d855 --- /dev/null +++ b/experiments/daic/tuning/generators/linearly_separable.sh @@ -0,0 +1,14 @@ +#!/bin/bash + +#SBATCH --job-name="Grid-search Linearly Separable (ECCCo)" +#SBATCH --time=02:00:00 +#SBATCH --ntasks=1000 +#SBATCH --cpus-per-task=1 +#SBATCH --partition=general +#SBATCH --mem-per-cpu=4GB +#SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. + +module use /opt/insy/modulefiles # Use DAIC INSY software collection +module load openmpi + +srun julia --project=experiments experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search > experiments/grid_search_linearly_separable.log From 7f0b2188d03bd41bb636cb00917136d4e43e6f08 Mon Sep 17 00:00:00 2001 From: Pat Alt <55311242+pat-alt@users.noreply.github.com> Date: Wed, 4 Oct 2023 12:54:03 +0200 Subject: [PATCH 024/171] werid new complain about meta function --- experiments/experiment.jl | 2 +- experiments/post_processing/meta_data.jl | 4 ++-- experiments/save_best.jl | 2 +- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/experiments/experiment.jl b/experiments/experiment.jl index b1a68c73..a375158e 100644 --- a/experiments/experiment.jl +++ b/experiments/experiment.jl @@ -139,7 +139,7 @@ function run_experiment( joinpath(exper.output_path, "$(exper.save_name)_bmk.jls"), outcome.bmk, ) - meta(outcome; save_output = true) + all_meta(outcome; save_output = true) end # Final barrier: diff --git a/experiments/post_processing/meta_data.jl b/experiments/post_processing/meta_data.jl index b50ce978..ab4c982a 100644 --- a/experiments/post_processing/meta_data.jl +++ b/experiments/post_processing/meta_data.jl @@ -1,9 +1,9 @@ """ - meta(exper::Experiment) + all_meta(exper::Experiment) Extract and save meta data about the experiment. """ -function meta( +function all_meta( outcome::ExperimentOutcome; save_output::Bool = false, params_path::Union{Nothing,String} = nothing, diff --git a/experiments/save_best.jl b/experiments/save_best.jl index a97c0d4e..977e8720 100644 --- a/experiments/save_best.jl +++ b/experiments/save_best.jl @@ -23,7 +23,7 @@ function save_best(outcomes_file_path::String) joinpath(output_path, "$(exper.save_name)_models.jls"), outcome.model_dict, ) - meta(outcome; save_output = true, params_path = params_path) + all_meta(outcome; save_output = true, params_path = params_path) end function bmk2csv(dataname::String) From 97e5adf7cb56c53ca25a2192d452ddf372e02664 Mon Sep 17 00:00:00 2001 From: Pat Alt <55311242+pat-alt@users.noreply.github.com> Date: Wed, 4 Oct 2023 12:59:47 +0200 Subject: [PATCH 025/171] cut down grid params for small datasets --- experiments/setup_env.jl | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/experiments/setup_env.jl b/experiments/setup_env.jl index a7b2108a..1f92ef11 100644 --- a/experiments/setup_env.jl +++ b/experiments/setup_env.jl @@ -182,12 +182,13 @@ const GRID_SEARCH = "grid_search" ∈ ARGS "Generator tuning parameters." DEFAULT_GENERATOR_TUNING = ( - Λ = [[0.1, 0.1, 0.05], [0.1, 0.1, 0.1], [0.1, 0.1, 0.5], [0.1, 0.1, 1.0]], - reg_strength = [0.0, 0.1, 0.25, 0.5, 1.0], + Λ=[[0.1, 0.1, 0.1], [0.1, 0.1, 0.5],], + reg_strength = [0.0, 0.1, 1.0], opt = [ Descent(0.01), Descent(0.05), - Descent(0.1), + Optimiser(ClipValue(0.01), Descent(0.01)), + Optimiser(ClipValue(0.05), Descent(0.05)), ], decay = [(0.0, 1), (0.01, 1), (0.1, 1)], ) From 8b2a825daf162d437a83ecf338a4d802a428cc99 Mon Sep 17 00:00:00 2001 From: Pat Alt <55311242+pat-alt@users.noreply.github.com> Date: Wed, 4 Oct 2023 13:07:00 +0200 Subject: [PATCH 026/171] cali on dlue --- .../tuning/generators/innovation/california_housing.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/experiments/jobscripts/tuning/generators/innovation/california_housing.sh b/experiments/jobscripts/tuning/generators/innovation/california_housing.sh index 7360a6a9..fd825fea 100644 --- a/experiments/jobscripts/tuning/generators/innovation/california_housing.sh +++ b/experiments/jobscripts/tuning/generators/innovation/california_housing.sh @@ -11,4 +11,4 @@ module load 2023r1 openmpi -srun julia --project=experiments experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search n_individuals=20 n_each=8 store_ce > experiments/grid_search_califoenia_housing.log +srun julia --project=experiments experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search n_individuals=10 n_each=16 > experiments/grid_search_califoenia_housing.log From 3332929201d4385979077cdcd9a43ce715375785 Mon Sep 17 00:00:00 2001 From: Pat Alt <55311242+pat-alt@users.noreply.github.com> Date: Wed, 4 Oct 2023 13:12:53 +0200 Subject: [PATCH 027/171] bleh --- experiments/daic/testing/cali_16each.sh | 15 +++++++++++++++ experiments/daic/testing/cali_4each.sh | 15 +++++++++++++++ experiments/setup_env.jl | 2 +- 3 files changed, 31 insertions(+), 1 deletion(-) create mode 100644 experiments/daic/testing/cali_16each.sh create mode 100644 experiments/daic/testing/cali_4each.sh diff --git a/experiments/daic/testing/cali_16each.sh b/experiments/daic/testing/cali_16each.sh new file mode 100644 index 00000000..8db0cba7 --- /dev/null +++ b/experiments/daic/testing/cali_16each.sh @@ -0,0 +1,15 @@ +#!/bin/bash + +#SBATCH --job-name="Grid-search California Housing (ECCCo)" +#SBATCH --time=01:00:00 +#SBATCH --ntasks=100 +#SBATCH --cpus-per-task=1 +#SBATCH --partition=general +#SBATCH --mem-per-cpu=4GB +#SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. + +module use /opt/insy/modulefiles # Use DAIC INSY software collection +module load openmpi + +srun julia --project=experiments experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search n_individuals=10 n_each=16 > experiments/grid_search_california_housing.log + diff --git a/experiments/daic/testing/cali_4each.sh b/experiments/daic/testing/cali_4each.sh new file mode 100644 index 00000000..5d9c7470 --- /dev/null +++ b/experiments/daic/testing/cali_4each.sh @@ -0,0 +1,15 @@ +#!/bin/bash + +#SBATCH --job-name="Grid-search California Housing (ECCCo)" +#SBATCH --time=01:00:00 +#SBATCH --ntasks=100 +#SBATCH --cpus-per-task=1 +#SBATCH --partition=general +#SBATCH --mem-per-cpu=4GB +#SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. + +module use /opt/insy/modulefiles # Use DAIC INSY software collection +module load openmpi + +srun julia --project=experiments experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search n_individuals=10 n_each=4 > experiments/grid_search_california_housing.log + diff --git a/experiments/setup_env.jl b/experiments/setup_env.jl index 1f92ef11..608f6dc0 100644 --- a/experiments/setup_env.jl +++ b/experiments/setup_env.jl @@ -196,7 +196,7 @@ DEFAULT_GENERATOR_TUNING = ( "Generator tuning parameters for large datasets." DEFAULT_GENERATOR_TUNING_LARGE = ( Λ = [[0.1, 0.1, 0.1], [0.1, 0.1, 0.2], [0.2, 0.2, 0.2]], - reg_strength = [0.0, 0.1, 0.25,], + reg_strength = [0.0,], opt = [ Descent(0.01), Descent(0.05), From 1114a94f267ee206800b2beabd74ba89ed73a0c4 Mon Sep 17 00:00:00 2001 From: Pat Alt <55311242+pat-alt@users.noreply.github.com> Date: Wed, 4 Oct 2023 13:42:46 +0200 Subject: [PATCH 028/171] not sure what happen to cali4 --- experiments/daic/testing/cali_32each.sh | 15 +++++++++++++++ experiments/daic/testing/lin_sep_32each.sh | 14 ++++++++++++++ 2 files changed, 29 insertions(+) create mode 100644 experiments/daic/testing/cali_32each.sh create mode 100644 experiments/daic/testing/lin_sep_32each.sh diff --git a/experiments/daic/testing/cali_32each.sh b/experiments/daic/testing/cali_32each.sh new file mode 100644 index 00000000..0d3bd1f0 --- /dev/null +++ b/experiments/daic/testing/cali_32each.sh @@ -0,0 +1,15 @@ +#!/bin/bash + +#SBATCH --job-name="Grid-search California Housing (ECCCo)" +#SBATCH --time=01:00:00 +#SBATCH --ntasks=100 +#SBATCH --cpus-per-task=1 +#SBATCH --partition=general +#SBATCH --mem-per-cpu=4GB +#SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. + +module use /opt/insy/modulefiles # Use DAIC INSY software collection +module load openmpi + +srun julia --project=experiments experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search n_individuals=10 n_each=32 > experiments/grid_search_california_housing.log + diff --git a/experiments/daic/testing/lin_sep_32each.sh b/experiments/daic/testing/lin_sep_32each.sh new file mode 100644 index 00000000..ff674ad2 --- /dev/null +++ b/experiments/daic/testing/lin_sep_32each.sh @@ -0,0 +1,14 @@ +#!/bin/bash + +#SBATCH --job-name="Grid-search Linearly Separable (ECCCo)" +#SBATCH --time=01:00:00 +#SBATCH --ntasks=100 +#SBATCH --cpus-per-task=1 +#SBATCH --partition=general +#SBATCH --mem-per-cpu=4GB +#SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. + +module use /opt/insy/modulefiles # Use DAIC INSY software collection +module load openmpi + +srun julia --project=experiments experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=10 > experiments/grid_search_linearly_separable.log From 25c59fb04e6bbeec6ef2ab63358fa14320cef08a Mon Sep 17 00:00:00 2001 From: Pat Alt <55311242+pat-alt@users.noreply.github.com> Date: Wed, 4 Oct 2023 14:18:24 +0200 Subject: [PATCH 029/171] trying with 200cores --- experiments/daic/testing/lin_sep_200cpu.sh | 14 ++++++++++++++ 1 file changed, 14 insertions(+) create mode 100644 experiments/daic/testing/lin_sep_200cpu.sh diff --git a/experiments/daic/testing/lin_sep_200cpu.sh b/experiments/daic/testing/lin_sep_200cpu.sh new file mode 100644 index 00000000..173f6469 --- /dev/null +++ b/experiments/daic/testing/lin_sep_200cpu.sh @@ -0,0 +1,14 @@ +#!/bin/bash + +#SBATCH --job-name="Grid-search Linearly Separable (ECCCo)" +#SBATCH --time=00:30:00 +#SBATCH --ntasks=200 +#SBATCH --cpus-per-task=1 +#SBATCH --partition=general +#SBATCH --mem-per-cpu=4GB +#SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. + +module use /opt/insy/modulefiles # Use DAIC INSY software collection +module load openmpi + +srun julia --project=experiments experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=10 > experiments/grid_search_linearly_separable.log From b83215b63f884fe2cc2b0a88c458c81da28faeb2 Mon Sep 17 00:00:00 2001 From: Pat Alt <55311242+pat-alt@users.noreply.github.com> Date: Wed, 4 Oct 2023 14:19:59 +0200 Subject: [PATCH 030/171] uf --- .../testing/{cali_16each.sh => cali_100_8.sh} | 2 +- experiments/daic/testing/cali_4each.sh | 15 --------------- .../daic/testing/{cali_32each.sh => cali_50_8.sh} | 8 ++++---- 3 files changed, 5 insertions(+), 20 deletions(-) rename experiments/daic/testing/{cali_16each.sh => cali_100_8.sh} (95%) delete mode 100644 experiments/daic/testing/cali_4each.sh rename experiments/daic/testing/{cali_32each.sh => cali_50_8.sh} (77%) diff --git a/experiments/daic/testing/cali_16each.sh b/experiments/daic/testing/cali_100_8.sh similarity index 95% rename from experiments/daic/testing/cali_16each.sh rename to experiments/daic/testing/cali_100_8.sh index 8db0cba7..b619982c 100644 --- a/experiments/daic/testing/cali_16each.sh +++ b/experiments/daic/testing/cali_100_8.sh @@ -5,7 +5,7 @@ #SBATCH --ntasks=100 #SBATCH --cpus-per-task=1 #SBATCH --partition=general -#SBATCH --mem-per-cpu=4GB +#SBATCH --mem-per-cpu=8GB #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. module use /opt/insy/modulefiles # Use DAIC INSY software collection diff --git a/experiments/daic/testing/cali_4each.sh b/experiments/daic/testing/cali_4each.sh deleted file mode 100644 index 5d9c7470..00000000 --- a/experiments/daic/testing/cali_4each.sh +++ /dev/null @@ -1,15 +0,0 @@ -#!/bin/bash - -#SBATCH --job-name="Grid-search California Housing (ECCCo)" -#SBATCH --time=01:00:00 -#SBATCH --ntasks=100 -#SBATCH --cpus-per-task=1 -#SBATCH --partition=general -#SBATCH --mem-per-cpu=4GB -#SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. - -module use /opt/insy/modulefiles # Use DAIC INSY software collection -module load openmpi - -srun julia --project=experiments experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search n_individuals=10 n_each=4 > experiments/grid_search_california_housing.log - diff --git a/experiments/daic/testing/cali_32each.sh b/experiments/daic/testing/cali_50_8.sh similarity index 77% rename from experiments/daic/testing/cali_32each.sh rename to experiments/daic/testing/cali_50_8.sh index 0d3bd1f0..177e8215 100644 --- a/experiments/daic/testing/cali_32each.sh +++ b/experiments/daic/testing/cali_50_8.sh @@ -1,15 +1,15 @@ #!/bin/bash #SBATCH --job-name="Grid-search California Housing (ECCCo)" -#SBATCH --time=01:00:00 -#SBATCH --ntasks=100 +#SBATCH --time=02:00:00 +#SBATCH --ntasks=50 #SBATCH --cpus-per-task=1 #SBATCH --partition=general -#SBATCH --mem-per-cpu=4GB +#SBATCH --mem-per-cpu=8GB #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. module use /opt/insy/modulefiles # Use DAIC INSY software collection module load openmpi -srun julia --project=experiments experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search n_individuals=10 n_each=32 > experiments/grid_search_california_housing.log +srun julia --project=experiments experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search n_individuals=10 n_each=16 > experiments/grid_search_california_housing.log From 8f5349bbe06be9850b75cabc977e02704d27d568 Mon Sep 17 00:00:00 2001 From: Pat Alt <55311242+pat-alt@users.noreply.github.com> Date: Wed, 4 Oct 2023 15:10:43 +0200 Subject: [PATCH 031/171] testing --- experiments/daic/testing/lin_sep.sh | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/experiments/daic/testing/lin_sep.sh b/experiments/daic/testing/lin_sep.sh index ff674ad2..67df795b 100644 --- a/experiments/daic/testing/lin_sep.sh +++ b/experiments/daic/testing/lin_sep.sh @@ -2,8 +2,8 @@ #SBATCH --job-name="Grid-search Linearly Separable (ECCCo)" #SBATCH --time=01:00:00 -#SBATCH --ntasks=100 -#SBATCH --cpus-per-task=1 +#SBATCH --ntasks-per-node=5 +#SBATCH --cpus-per-task=4 #SBATCH --partition=general #SBATCH --mem-per-cpu=4GB #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. @@ -11,4 +11,6 @@ module use /opt/insy/modulefiles # Use DAIC INSY software collection module load openmpi -srun julia --project=experiments experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=10 > experiments/grid_search_linearly_separable.log +export SRUN_CPUS_PER_TASK="$SLURM_CPUS_PER_TASK" + +srun julia --project=experiments experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=10 threaded > experiments/grid_search_linearly_separable.log From c9866d83af5630854ca74094185c9c0a16b8b854 Mon Sep 17 00:00:00 2001 From: Pat Alt <55311242+pat-alt@users.noreply.github.com> Date: Wed, 4 Oct 2023 15:33:06 +0200 Subject: [PATCH 032/171] updated script --- experiments/daic/testing/lin_sep.sh | 5 +++-- experiments/daic/testing/lin_sep_no_threads.sh | 16 ++++++++++++++++ 2 files changed, 19 insertions(+), 2 deletions(-) create mode 100644 experiments/daic/testing/lin_sep_no_threads.sh diff --git a/experiments/daic/testing/lin_sep.sh b/experiments/daic/testing/lin_sep.sh index 67df795b..765609ad 100644 --- a/experiments/daic/testing/lin_sep.sh +++ b/experiments/daic/testing/lin_sep.sh @@ -1,7 +1,7 @@ #!/bin/bash #SBATCH --job-name="Grid-search Linearly Separable (ECCCo)" -#SBATCH --time=01:00:00 +#SBATCH --time=00:30:00 #SBATCH --ntasks-per-node=5 #SBATCH --cpus-per-task=4 #SBATCH --partition=general @@ -11,6 +11,7 @@ module use /opt/insy/modulefiles # Use DAIC INSY software collection module load openmpi +set -x export SRUN_CPUS_PER_TASK="$SLURM_CPUS_PER_TASK" -srun julia --project=experiments experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=10 threaded > experiments/grid_search_linearly_separable.log +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=10 threaded > experiments/grid_search_linearly_separable.log diff --git a/experiments/daic/testing/lin_sep_no_threads.sh b/experiments/daic/testing/lin_sep_no_threads.sh new file mode 100644 index 00000000..0b84c07b --- /dev/null +++ b/experiments/daic/testing/lin_sep_no_threads.sh @@ -0,0 +1,16 @@ +#!/bin/bash + +#SBATCH --job-name="Grid-search Linearly Separable (ECCCo)" +#SBATCH --time=00:30:00 +#SBATCH --ntasks-per-node=20 +#SBATCH --cpus-per-task=1 +#SBATCH --partition=general +#SBATCH --mem-per-cpu=4GB +#SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. + +module use /opt/insy/modulefiles # Use DAIC INSY software collection +module load openmpi + +export SRUN_CPUS_PER_TASK="$SLURM_CPUS_PER_TASK" + +srun julia --project=experiments experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=10 > experiments/grid_search_linearly_separable.log From 42c4bacc8b7c59145c51e64a59a0c87eaaf7bfda Mon Sep 17 00:00:00 2001 From: pat-alt Date: Wed, 11 Oct 2023 11:34:36 +0200 Subject: [PATCH 033/171] vscode setting --- .vscode/settings.json | 3 +++ 1 file changed, 3 insertions(+) create mode 100644 .vscode/settings.json diff --git a/.vscode/settings.json b/.vscode/settings.json new file mode 100644 index 00000000..f848dd07 --- /dev/null +++ b/.vscode/settings.json @@ -0,0 +1,3 @@ +{ + "julia.environmentPath": "/Users/paltmeyer/code/ECCCo.jl" +} \ No newline at end of file From ccda44234595898418f02854301c22a1c9d5b581 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Wed, 11 Oct 2023 11:37:34 +0200 Subject: [PATCH 034/171] testing script for dblue --- experiments/jobscripts/testing/lin_sep.sh | 18 ++++++++++++++++++ 1 file changed, 18 insertions(+) create mode 100644 experiments/jobscripts/testing/lin_sep.sh diff --git a/experiments/jobscripts/testing/lin_sep.sh b/experiments/jobscripts/testing/lin_sep.sh new file mode 100644 index 00000000..96345366 --- /dev/null +++ b/experiments/jobscripts/testing/lin_sep.sh @@ -0,0 +1,18 @@ +#!/bin/bash + +#SBATCH --job-name="Grid-search Linearly Separable (ECCCo)" +#SBATCH --time=00:30:00 +#SBATCH --ntasks-per-node=5 +#SBATCH --cpus-per-task=4 +#SBATCH --partition=compute +#SBATCH --mem-per-cpu=4GB +#SBATCH --account=research-eemcs-insy +#SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. + +module load 2023r1 julia +module load openmpi + +set -x +export SRUN_CPUS_PER_TASK="$SLURM_CPUS_PER_TASK" + +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=10 threaded > experiments/grid_search_linearly_separable.log From 4ff2103dd54fb8006286f2da23f72fe8737c4950 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Mon, 16 Oct 2023 10:12:14 +0200 Subject: [PATCH 035/171] open blas --- experiments/jobscripts/testing/lin_sep.sh | 4 +--- experiments/slurm_header.sh | 3 +++ 2 files changed, 4 insertions(+), 3 deletions(-) create mode 100644 experiments/slurm_header.sh diff --git a/experiments/jobscripts/testing/lin_sep.sh b/experiments/jobscripts/testing/lin_sep.sh index 96345366..9c8af82c 100644 --- a/experiments/jobscripts/testing/lin_sep.sh +++ b/experiments/jobscripts/testing/lin_sep.sh @@ -9,10 +9,8 @@ #SBATCH --account=research-eemcs-insy #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. -module load 2023r1 julia module load openmpi -set -x -export SRUN_CPUS_PER_TASK="$SLURM_CPUS_PER_TASK" +source experiments/slurm_header.sh srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=10 threaded > experiments/grid_search_linearly_separable.log diff --git a/experiments/slurm_header.sh b/experiments/slurm_header.sh new file mode 100644 index 00000000..48da377b --- /dev/null +++ b/experiments/slurm_header.sh @@ -0,0 +1,3 @@ +set -x # keep log of executed commands +export SRUN_CPUS_PER_TASK="$SLURM_CPUS_PER_TASK" # assign extra environment variable to be safe +export OPENBLAS_NUM_THREADS=1 # avoid that OpenBLAS calls too many threads \ No newline at end of file From 59deaf2852563a64a658969cbd98b9011cff40d8 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Mon, 16 Oct 2023 10:20:12 +0200 Subject: [PATCH 036/171] module loading in test file --- experiments/jobscripts/testing/lin_sep.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/experiments/jobscripts/testing/lin_sep.sh b/experiments/jobscripts/testing/lin_sep.sh index 9c8af82c..661d4dbb 100644 --- a/experiments/jobscripts/testing/lin_sep.sh +++ b/experiments/jobscripts/testing/lin_sep.sh @@ -9,7 +9,7 @@ #SBATCH --account=research-eemcs-insy #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. -module load openmpi +module load 2023r1 openmpi source experiments/slurm_header.sh From a5d07fae33b6694d576866d8fde0bd4e0c013c88 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Mon, 16 Oct 2023 10:41:24 +0200 Subject: [PATCH 037/171] manifest --- experiments/Manifest.toml | 143 +++++++++++++++++++++++--------------- 1 file changed, 87 insertions(+), 56 deletions(-) diff --git a/experiments/Manifest.toml b/experiments/Manifest.toml index 683a8b01..48d8a3c8 100644 --- a/experiments/Manifest.toml +++ b/experiments/Manifest.toml @@ -197,16 +197,20 @@ uuid = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b" version = "0.10.11" [[deps.CUDA]] -deps = ["AbstractFFTs", "Adapt", "BFloat16s", "CEnum", "CUDA_Driver_jll", "CUDA_Runtime_Discovery", "CUDA_Runtime_jll", "ExprTools", "GPUArrays", "GPUCompiler", "KernelAbstractions", "LLVM", "LazyArtifacts", "Libdl", "LinearAlgebra", "Logging", "Preferences", "Printf", "Random", "Random123", "RandomNumbers", "Reexport", "Requires", "SparseArrays", "SpecialFunctions", "UnsafeAtomicsLLVM"] -git-tree-sha1 = "968c1365e2992824c3e7a794e30907483f8469a9" +deps = ["AbstractFFTs", "Adapt", "BFloat16s", "CEnum", "CUDA_Driver_jll", "CUDA_Runtime_Discovery", "CUDA_Runtime_jll", "Crayons", "DataFrames", "ExprTools", "GPUArrays", "GPUCompiler", "KernelAbstractions", "LLVM", "LazyArtifacts", "Libdl", "LinearAlgebra", "Logging", "NVTX", "Preferences", "PrettyTables", "Printf", "Random", "Random123", "RandomNumbers", "Reexport", "Requires", "SparseArrays", "Statistics", "UnsafeAtomicsLLVM"] +git-tree-sha1 = "f062a48c26ae027f70c44f48f244862aec47bf99" uuid = "052768ef-5323-5732-b1bb-66c8b64840ba" -version = "4.4.1" +version = "5.0.0" +weakdeps = ["SpecialFunctions"] + + [deps.CUDA.extensions] + SpecialFunctionsExt = "SpecialFunctions" [[deps.CUDA_Driver_jll]] deps = ["Artifacts", "JLLWrappers", "LazyArtifacts", "Libdl", "Pkg"] -git-tree-sha1 = "498f45593f6ddc0adff64a9310bb6710e851781b" +git-tree-sha1 = "35a37bb72b35964f2895c12c687ae263b4ac170c" uuid = "4ee394cb-3365-5eb0-8335-949819d2adfc" -version = "0.5.0+1" +version = "0.6.0+3" [[deps.CUDA_Runtime_Discovery]] deps = ["Libdl"] @@ -216,9 +220,9 @@ version = "0.2.2" [[deps.CUDA_Runtime_jll]] deps = ["Artifacts", "CUDA_Driver_jll", "JLLWrappers", "LazyArtifacts", "Libdl", "TOML"] -git-tree-sha1 = "5248d9c45712e51e27ba9b30eebec65658c6ce29" +git-tree-sha1 = "178a606891f82b6d734f0eadd5336b7aad44d5df" uuid = "76a88914-d11a-5bdc-97e0-2f5a05c973a2" -version = "0.6.0+0" +version = "0.9.2+1" [[deps.CUDNN_jll]] deps = ["Artifacts", "CUDA_Runtime_jll", "JLLWrappers", "LazyArtifacts", "Libdl", "TOML"] @@ -282,9 +286,9 @@ version = "1.55.0" [[deps.ChainRulesCore]] deps = ["Compat", "LinearAlgebra", "SparseArrays"] -git-tree-sha1 = "e30f2f4e20f7f186dc36529910beaedc60cfa644" +git-tree-sha1 = "b66b8f8e3db5d7835fb8cbe2589ffd1cd456e491" uuid = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4" -version = "1.16.0" +version = "1.17.0" [[deps.Chemfiles]] deps = ["AtomsBase", "Chemfiles_jll", "DocStringExtensions", "PeriodicTable", "Unitful", "UnitfulAtomic"] @@ -306,21 +310,21 @@ version = "0.1.12" [[deps.Clustering]] deps = ["Distances", "LinearAlgebra", "NearestNeighbors", "Printf", "Random", "SparseArrays", "Statistics", "StatsBase"] -git-tree-sha1 = "b86ac2c5543660d238957dbde5ac04520ae977a7" +git-tree-sha1 = "05f9816a77231b07e634ab8715ba50e5249d6f76" uuid = "aaaa29a8-35af-508c-8bc3-b662a17a0fe5" -version = "0.15.4" +version = "0.15.5" [[deps.CodeTracking]] deps = ["InteractiveUtils", "UUIDs"] -git-tree-sha1 = "a1296f0fe01a4c3f9bf0dc2934efbf4416f5db31" +git-tree-sha1 = "c0216e792f518b39b22212127d4a84dc31e4e386" uuid = "da1fd8a2-8d9e-5ec2-8556-3022fb5608a2" -version = "1.3.4" +version = "1.3.5" [[deps.CodecZlib]] deps = ["TranscodingStreams", "Zlib_jll"] -git-tree-sha1 = "02aa26a4cf76381be7f66e020a3eddeb27b0a092" +git-tree-sha1 = "cd67fc487743b2f0fd4380d4cbd3a24660d0eec8" uuid = "944b1d66-785c-5afd-91f1-9de20f533193" -version = "0.7.2" +version = "0.7.3" [[deps.ColorSchemes]] deps = ["ColorTypes", "ColorVectorSpace", "Colors", "FixedPointNumbers", "PrecompileTools", "Random"] @@ -433,8 +437,8 @@ uuid = "150eb455-5306-5404-9cee-2592286d6298" version = "0.6.3" [[deps.CounterfactualExplanations]] -deps = ["CSV", "CUDA", "CategoricalArrays", "ChainRulesCore", "DataFrames", "DecisionTree", "Distributions", "EvoTrees", "Flux", "LaplaceRedux", "LazyArtifacts", "LinearAlgebra", "Logging", "MLDatasets", "MLJBase", "MLJDecisionTreeInterface", "MLJModels", "MLUtils", "MultivariateStats", "NearestNeighborModels", "PackageExtensionCompat", "Parameters", "PkgTemplates", "PrecompileTools", "ProgressMeter", "Random", "Serialization", "Statistics", "StatsBase", "Tables", "UUIDs", "cuDNN"] -git-tree-sha1 = "1f1861d5b947a7af85c2172e3791c03453b6a183" +deps = ["CSV", "CUDA", "CategoricalArrays", "ChainRulesCore", "DataFrames", "DecisionTree", "Distributions", "EvoTrees", "Flux", "LaplaceRedux", "LazyArtifacts", "LinearAlgebra", "Logging", "MLDatasets", "MLJBase", "MLJDecisionTreeInterface", "MLJModels", "MLUtils", "MultivariateStats", "NearestNeighborModels", "PackageExtensionCompat", "Parameters", "PrecompileTools", "ProgressMeter", "Random", "Serialization", "Statistics", "StatsBase", "Tables", "UUIDs", "cuDNN"] +git-tree-sha1 = "6ac3b59bcd9d8c75dcbe83822f050247d1143334" repo-rev = "main" repo-url = "https://github.com/JuliaTrustworthyAI/CounterfactualExplanations.jl.git" uuid = "2f13d31b-18db-44c1-bc43-ebaf2cff0be0" @@ -529,12 +533,13 @@ version = "1.15.1" [[deps.Distances]] deps = ["LinearAlgebra", "Statistics", "StatsAPI"] -git-tree-sha1 = "b6def76ffad15143924a2199f72a5cd883a2e8a9" +git-tree-sha1 = "5225c965635d8c21168e32a12954675e7bea1151" uuid = "b4f34e82-e78d-54a5-968a-f98e89d6e8f7" -version = "0.10.9" -weakdeps = ["SparseArrays"] +version = "0.10.10" +weakdeps = ["ChainRulesCore", "SparseArrays"] [deps.Distances.extensions] + DistancesChainRulesCoreExt = "ChainRulesCore" DistancesSparseArraysExt = "SparseArrays" [[deps.Distributed]] @@ -597,10 +602,14 @@ uuid = "2702e6a9-849d-5ed8-8c21-79e8b8f9ee43" version = "0.0.20230411+0" [[deps.EvoTrees]] -deps = ["BSON", "CUDA", "CategoricalArrays", "Distributions", "MLJModelInterface", "NetworkLayout", "Random", "RecipesBase", "Statistics", "StatsBase", "Tables"] -git-tree-sha1 = "a1fa1d1743478394a0a7188d054b67546e4ca143" +deps = ["BSON", "CategoricalArrays", "Distributions", "MLJModelInterface", "NetworkLayout", "Random", "RecipesBase", "Statistics", "StatsBase", "Tables"] +git-tree-sha1 = "6bae99c964218fcb9af8b0cca80f9bd278d59dcb" uuid = "f6006082-12f8-11e9-0c9c-0d5d367ab1e5" -version = "0.16.1" +version = "0.16.4" +weakdeps = ["CUDA"] + + [deps.EvoTrees.extensions] + EvoTreesCUDAExt = "CUDA" [[deps.ExceptionUnwrapping]] deps = ["Test"] @@ -620,9 +629,9 @@ uuid = "e2ba6199-217a-4e67-a87a-7c52f15ade04" version = "0.1.10" [[deps.Extents]] -git-tree-sha1 = "5e1e4c53fa39afe63a7d356e30452249365fba99" +git-tree-sha1 = "2140cd04483da90b2da7f99b2add0750504fc39c" uuid = "411431e0-e8b7-467b-b5e0-f676ba4f2910" -version = "0.1.1" +version = "0.1.2" [[deps.FFMPEG]] deps = ["FFMPEG_jll"] @@ -768,9 +777,9 @@ version = "3.3.8+0" [[deps.GPUArrays]] deps = ["Adapt", "GPUArraysCore", "LLVM", "LinearAlgebra", "Printf", "Random", "Reexport", "Serialization", "Statistics"] -git-tree-sha1 = "2e57b4a4f9cc15e85a24d603256fe08e527f48d1" +git-tree-sha1 = "8ad8f375ae365aa1eb2f42e2565a40b55a4b69a8" uuid = "0c68f7d7-f131-5f86-a1c3-88cf8149b2d7" -version = "8.8.1" +version = "9.0.0" [[deps.GPUArraysCore]] deps = ["Adapt"] @@ -780,9 +789,9 @@ version = "0.1.5" [[deps.GPUCompiler]] deps = ["ExprTools", "InteractiveUtils", "LLVM", "Libdl", "Logging", "Scratch", "TimerOutputs", "UUIDs"] -git-tree-sha1 = "72b2e3c2ba583d1a7aa35129e56cf92e07c083e3" +git-tree-sha1 = "5e4487558477f191c043166f8301dd0b4be4e2b2" uuid = "61eb1bfa-7361-4325-ad38-22787b887f55" -version = "0.21.4" +version = "0.24.5" [[deps.GR]] deps = ["Artifacts", "Base64", "DelimitedFiles", "Downloads", "GR_jll", "HTTP", "JSON", "Libdl", "LinearAlgebra", "Pkg", "Preferences", "Printf", "Random", "Serialization", "Sockets", "TOML", "Tar", "Test", "UUIDs", "p7zip_jll"] @@ -1037,9 +1046,9 @@ uuid = "9b13fd28-a010-5f03-acff-a1bbcff69959" version = "1.0.0" [[deps.Inflate]] -git-tree-sha1 = "5cd07aab533df5170988219191dfad0519391428" +git-tree-sha1 = "ea8031dea4aff6bd41f1df8f2fdfb25b33626381" uuid = "d25df0c9-e2be-5dd7-82c8-3ad0b3e990b9" -version = "0.1.3" +version = "0.1.4" [[deps.InitialValues]] git-tree-sha1 = "4da0f88e9a39111c2fa3add390ab15f3a44f3ca3" @@ -1124,9 +1133,9 @@ version = "0.4.35" [[deps.JLFzf]] deps = ["Pipe", "REPL", "Random", "fzf_jll"] -git-tree-sha1 = "f377670cda23b6b7c1c0b3893e37451c5c1a2185" +git-tree-sha1 = "9fb0b890adab1c0a4a475d4210d51f228bfc250d" uuid = "1019f520-868f-41f5-a6de-eb00f4b6a39c" -version = "0.1.5" +version = "0.1.6" [[deps.JLLWrappers]] deps = ["Artifacts", "Preferences"] @@ -1164,6 +1173,12 @@ git-tree-sha1 = "6f2675ef130a300a112286de91973805fcc5ffbc" uuid = "aacddb02-875f-59d6-b918-886e6ef4fbf8" version = "2.1.91+0" +[[deps.JuliaNVTXCallbacks_jll]] +deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"] +git-tree-sha1 = "af433a10f3942e882d3c671aacb203e006a5808f" +uuid = "9c1d0b0a-7046-5b2e-a33f-ea22f176ac7e" +version = "0.2.1+0" + [[deps.JuliaVariables]] deps = ["MLStyle", "NameResolution"] git-tree-sha1 = "49fb3cb53362ddadb4415e9b73926d6b40709e70" @@ -1172,9 +1187,9 @@ version = "0.2.4" [[deps.KernelAbstractions]] deps = ["Adapt", "Atomix", "InteractiveUtils", "LinearAlgebra", "MacroTools", "PrecompileTools", "Requires", "SparseArrays", "StaticArrays", "UUIDs", "UnsafeAtomics", "UnsafeAtomicsLLVM"] -git-tree-sha1 = "4c5875e4c228247e1c2b087669846941fb6e0118" +git-tree-sha1 = "5f1ecfddb6abde48563d08b2cc7e5116ebcd6c27" uuid = "63c18a36-062a-441e-b654-da1e3ab1ce7c" -version = "0.9.8" +version = "0.9.10" [deps.KernelAbstractions.extensions] EnzymeExt = "EnzymeCore" @@ -1359,9 +1374,9 @@ uuid = "56ddb016-857b-54e1-b83d-db4d58db5568" [[deps.LoggingExtras]] deps = ["Dates", "Logging"] -git-tree-sha1 = "0d097476b6c381ab7906460ef1ef1638fbce1d91" +git-tree-sha1 = "c1dd6d7978c12545b4179fb6153b9250c96b0075" uuid = "e6f89c97-d47a-5376-807f-9c37f3926c36" -version = "1.0.2" +version = "1.0.3" [[deps.LoopVectorization]] deps = ["ArrayInterface", "ArrayInterfaceCore", "CPUSummary", "CloseOpenIntervals", "DocStringExtensions", "HostCPUFeatures", "IfElse", "LayoutPointers", "LinearAlgebra", "OffsetArrays", "PolyesterWeave", "PrecompileTools", "SIMDTypes", "SLEEFPirates", "Static", "StaticArrayInterface", "ThreadingUtilities", "UnPack", "VectorizationBase"] @@ -1398,9 +1413,9 @@ version = "2023.2.0+0" [[deps.MLDatasets]] deps = ["CSV", "Chemfiles", "DataDeps", "DataFrames", "DelimitedFiles", "FileIO", "FixedPointNumbers", "GZip", "Glob", "HDF5", "ImageShow", "JLD2", "JSON3", "LazyModules", "MAT", "MLUtils", "NPZ", "Pickle", "Printf", "Requires", "SparseArrays", "Statistics", "Tables"] -git-tree-sha1 = "10bc70e4c875f1b2ca65cef3ef9ebe705ef936b5" +git-tree-sha1 = "aab72207b3c687086a400be710650a57494992bd" uuid = "eb30cadb-4394-5ae3-aed4-317e484a6458" -version = "0.7.13" +version = "0.7.14" [[deps.MLFlowClient]] deps = ["Dates", "FilePathsBase", "HTTP", "JSON", "ShowCases", "URIs", "UUIDs"] @@ -1458,9 +1473,9 @@ version = "1.9.2" [[deps.MLJModels]] deps = ["CategoricalArrays", "CategoricalDistributions", "Combinatorics", "Dates", "Distances", "Distributions", "InteractiveUtils", "LinearAlgebra", "MLJModelInterface", "Markdown", "OrderedCollections", "Parameters", "Pkg", "PrettyPrinting", "REPL", "Random", "RelocatableFolders", "ScientificTypes", "StatisticalTraits", "Statistics", "StatsBase", "Tables"] -git-tree-sha1 = "da9f2bfefa08d1a63167cbd9bdd862a44a1b3d9d" +git-tree-sha1 = "10d221910fc3f3eedad567178ddbca3cc0f776a3" uuid = "d491faf4-2d78-11e9-2867-c94bc002c0b7" -version = "0.16.11" +version = "0.16.12" [[deps.MLJTuning]] deps = ["ComputationalResources", "Distributed", "Distributions", "LatinHypercubeSampling", "MLJBase", "ProgressMeter", "Random", "RecipesBase"] @@ -1637,6 +1652,18 @@ git-tree-sha1 = "60a8e272fe0c5079363b28b0953831e2dd7b7e6f" uuid = "15e1cf62-19b3-5cfa-8e77-841668bca605" version = "0.4.3" +[[deps.NVTX]] +deps = ["Colors", "JuliaNVTXCallbacks_jll", "Libdl", "NVTX_jll"] +git-tree-sha1 = "8bc9ce4233be3c63f8dcd78ccaf1b63a9c0baa34" +uuid = "5da4648a-3479-48b8-97b9-01cb529c0a1f" +version = "0.3.3" + +[[deps.NVTX_jll]] +deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"] +git-tree-sha1 = "ce3269ed42816bf18d500c9f63418d4b0d9f5a3b" +uuid = "e98f9f5b-d649-5603-91fd-7774390e6439" +version = "3.1.0+2" + [[deps.NaNMath]] deps = ["OpenLibm_jll"] git-tree-sha1 = "0877504529a3e5c3343c6f8b4c0381e57e4387e4" @@ -1673,10 +1700,14 @@ uuid = "f09324ee-3d7c-5217-9330-fc30815ba969" version = "1.1.1" [[deps.NetworkLayout]] -deps = ["GeometryBasics", "LinearAlgebra", "Random", "Requires", "SparseArrays", "StaticArrays"] -git-tree-sha1 = "2bfd8cd7fba3e46ce48139ae93904ee848153660" +deps = ["GeometryBasics", "LinearAlgebra", "Random", "Requires", "StaticArrays"] +git-tree-sha1 = "91bb2fedff8e43793650e7a677ccda6e6e6e166b" uuid = "46757867-2c16-5918-afeb-47bfcb05e46a" -version = "0.4.5" +version = "0.4.6" +weakdeps = ["Graphs"] + + [deps.NetworkLayout.extensions] + NetworkLayoutGraphsExt = "Graphs" [[deps.NetworkOptions]] uuid = "ca575930-c2e3-43a9-ace4-1e988b2c1908" @@ -1776,9 +1807,9 @@ version = "10.42.0+0" [[deps.PDMats]] deps = ["LinearAlgebra", "SparseArrays", "SuiteSparse"] -git-tree-sha1 = "b7c4f29f93b548caa58f703580f4d79ab753c8ac" +git-tree-sha1 = "3d8af7d689bd228a3a6c2298a4e6d5f5944accb8" uuid = "90014a1f-27ba-587c-ab20-58faa44d9150" -version = "0.11.21" +version = "0.11.26" [[deps.PNGFiles]] deps = ["Base64", "CEnum", "ImageCore", "IndirectArrays", "OffsetArrays", "libpng_jll"] @@ -2049,9 +2080,9 @@ version = "0.3.2" [[deps.RelocatableFolders]] deps = ["SHA", "Scratch"] -git-tree-sha1 = "90bc7a7c96410424509e4263e277e43250c05691" +git-tree-sha1 = "ffdaf70d81cf6ff22c2b6e733c900c3321cab864" uuid = "05181044-ff0b-4ac5-8273-598c1e38db00" -version = "1.0.0" +version = "1.0.1" [[deps.Requires]] deps = ["UUIDs"] @@ -2375,9 +2406,9 @@ version = "0.5.2" [[deps.TiffImages]] deps = ["ColorTypes", "DataStructures", "DocStringExtensions", "FileIO", "FixedPointNumbers", "IndirectArrays", "Inflate", "Mmap", "OffsetArrays", "PkgVersion", "ProgressMeter", "UUIDs"] -git-tree-sha1 = "7fd97bd1c5b1ff53a291cbd351d1d3d6ff4da5a5" +git-tree-sha1 = "34cc045dd0aaa59b8bbe86c644679bc57f1d5bd0" uuid = "731e570b-9d59-4bfa-96dc-6df516fadf69" -version = "0.6.7" +version = "0.6.8" [[deps.TiledIteration]] deps = ["OffsetArrays", "StaticArrayInterface"] @@ -2429,9 +2460,9 @@ uuid = "9d95972d-f1c8-5527-a6e0-b4b365fa01f6" version = "1.4.3" [[deps.URIs]] -git-tree-sha1 = "b7a5e99f24892b6824a954199a45e9ffcc1c70f0" +git-tree-sha1 = "67db6cc7b3821e19ebe75791a9dd19c9b1188f2b" uuid = "5c2747f8-b7ea-4ff2-ba2e-563bfd36b1d4" -version = "1.5.0" +version = "1.5.1" [[deps.UUIDs]] deps = ["Random", "SHA"] @@ -2707,15 +2738,15 @@ version = "0.2.3" [[deps.cuDNN]] deps = ["CEnum", "CUDA", "CUDNN_jll"] -git-tree-sha1 = "5a1ba43303c62f4a09b0d6751422de03424ab0cd" +git-tree-sha1 = "0c07d5a4a40010375e3a89b7578c4e0589467f78" uuid = "02a925ec-e4fe-4b08-9a7e-0d78e3d38ccd" -version = "1.1.1" +version = "1.2.0" [[deps.fzf_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"] -git-tree-sha1 = "868e669ccb12ba16eaf50cb2957ee2ff61261c56" +git-tree-sha1 = "47cf33e62e138b920039e8ff9f9841aafe1b733e" uuid = "214eeab7-80f7-51ab-84ad-2988db7cef09" -version = "0.29.0+0" +version = "0.35.1+0" [[deps.ghr_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"] From d314e527ebeb8087bdc15c7f7ad163a35fb2bf89 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Mon, 16 Oct 2023 11:44:03 +0200 Subject: [PATCH 038/171] threaded vs non-threaded --- experiments/jobscripts/testing/lin_sep.sh | 6 +++--- .../jobscripts/testing/lin_sep_threaded.sh | 16 ++++++++++++++++ 2 files changed, 19 insertions(+), 3 deletions(-) create mode 100644 experiments/jobscripts/testing/lin_sep_threaded.sh diff --git a/experiments/jobscripts/testing/lin_sep.sh b/experiments/jobscripts/testing/lin_sep.sh index 661d4dbb..11c46c6d 100644 --- a/experiments/jobscripts/testing/lin_sep.sh +++ b/experiments/jobscripts/testing/lin_sep.sh @@ -2,8 +2,8 @@ #SBATCH --job-name="Grid-search Linearly Separable (ECCCo)" #SBATCH --time=00:30:00 -#SBATCH --ntasks-per-node=5 -#SBATCH --cpus-per-task=4 +#SBATCH --ntasks-per-node=20 +#SBATCH --cpus-per-task=1 #SBATCH --partition=compute #SBATCH --mem-per-cpu=4GB #SBATCH --account=research-eemcs-insy @@ -13,4 +13,4 @@ module load 2023r1 openmpi source experiments/slurm_header.sh -srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=10 threaded > experiments/grid_search_linearly_separable.log +srun julia --project=experiments experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=1 > experiments/grid_search_linearly_separable.log diff --git a/experiments/jobscripts/testing/lin_sep_threaded.sh b/experiments/jobscripts/testing/lin_sep_threaded.sh new file mode 100644 index 00000000..c45cbb39 --- /dev/null +++ b/experiments/jobscripts/testing/lin_sep_threaded.sh @@ -0,0 +1,16 @@ +#!/bin/bash + +#SBATCH --job-name="Grid-search Linearly Separable (ECCCo)" +#SBATCH --time=00:30:00 +#SBATCH --ntasks-per-node=5 +#SBATCH --cpus-per-task=4 +#SBATCH --partition=compute +#SBATCH --mem-per-cpu=4GB +#SBATCH --account=research-eemcs-insy +#SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. + +module load 2023r1 openmpi + +source experiments/slurm_header.sh + +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=1 threaded > experiments/grid_search_linearly_separable.log From f607f2b9cb222607ad7ac6230efef1517d9a7c9c Mon Sep 17 00:00:00 2001 From: pat-alt Date: Mon, 16 Oct 2023 12:05:51 +0200 Subject: [PATCH 039/171] increasing testing specs slightly --- experiments/jobscripts/testing/lin_sep.sh | 5 +++-- experiments/jobscripts/testing/lin_sep_threaded.sh | 6 +++--- 2 files changed, 6 insertions(+), 5 deletions(-) diff --git a/experiments/jobscripts/testing/lin_sep.sh b/experiments/jobscripts/testing/lin_sep.sh index 11c46c6d..20a95f20 100644 --- a/experiments/jobscripts/testing/lin_sep.sh +++ b/experiments/jobscripts/testing/lin_sep.sh @@ -2,7 +2,7 @@ #SBATCH --job-name="Grid-search Linearly Separable (ECCCo)" #SBATCH --time=00:30:00 -#SBATCH --ntasks-per-node=20 +#SBATCH --ntasks-per-node=100 #SBATCH --cpus-per-task=1 #SBATCH --partition=compute #SBATCH --mem-per-cpu=4GB @@ -13,4 +13,5 @@ module load 2023r1 openmpi source experiments/slurm_header.sh -srun julia --project=experiments experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=1 > experiments/grid_search_linearly_separable.log +srun julia --project=experiments experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=10 > experiments/grid_search_linearly_separable.log + \ No newline at end of file diff --git a/experiments/jobscripts/testing/lin_sep_threaded.sh b/experiments/jobscripts/testing/lin_sep_threaded.sh index c45cbb39..27a14563 100644 --- a/experiments/jobscripts/testing/lin_sep_threaded.sh +++ b/experiments/jobscripts/testing/lin_sep_threaded.sh @@ -2,8 +2,8 @@ #SBATCH --job-name="Grid-search Linearly Separable (ECCCo)" #SBATCH --time=00:30:00 -#SBATCH --ntasks-per-node=5 -#SBATCH --cpus-per-task=4 +#SBATCH --ntasks-per-node=10 +#SBATCH --cpus-per-task=10 #SBATCH --partition=compute #SBATCH --mem-per-cpu=4GB #SBATCH --account=research-eemcs-insy @@ -13,4 +13,4 @@ module load 2023r1 openmpi source experiments/slurm_header.sh -srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=1 threaded > experiments/grid_search_linearly_separable.log +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=10 threaded > experiments/grid_search_linearly_separable.log From 3e41da539103ea837f5346a957317661bae957a5 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Mon, 16 Oct 2023 12:08:12 +0200 Subject: [PATCH 040/171] small change to bash scripts --- experiments/jobscripts/testing/lin_sep.sh | 2 +- experiments/jobscripts/testing/lin_sep_threaded.sh | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/experiments/jobscripts/testing/lin_sep.sh b/experiments/jobscripts/testing/lin_sep.sh index 20a95f20..bce013b3 100644 --- a/experiments/jobscripts/testing/lin_sep.sh +++ b/experiments/jobscripts/testing/lin_sep.sh @@ -2,7 +2,7 @@ #SBATCH --job-name="Grid-search Linearly Separable (ECCCo)" #SBATCH --time=00:30:00 -#SBATCH --ntasks-per-node=100 +#SBATCH --ntasks=100 #SBATCH --cpus-per-task=1 #SBATCH --partition=compute #SBATCH --mem-per-cpu=4GB diff --git a/experiments/jobscripts/testing/lin_sep_threaded.sh b/experiments/jobscripts/testing/lin_sep_threaded.sh index 27a14563..84677789 100644 --- a/experiments/jobscripts/testing/lin_sep_threaded.sh +++ b/experiments/jobscripts/testing/lin_sep_threaded.sh @@ -2,7 +2,7 @@ #SBATCH --job-name="Grid-search Linearly Separable (ECCCo)" #SBATCH --time=00:30:00 -#SBATCH --ntasks-per-node=10 +#SBATCH --ntasks=10 #SBATCH --cpus-per-task=10 #SBATCH --partition=compute #SBATCH --mem-per-cpu=4GB From f59ba3db5f5283bc02fde1aade4aaee31888d103 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Mon, 16 Oct 2023 12:37:30 +0200 Subject: [PATCH 041/171] specs up on threaded --- experiments/jobscripts/testing/lin_sep_threaded.sh | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/experiments/jobscripts/testing/lin_sep_threaded.sh b/experiments/jobscripts/testing/lin_sep_threaded.sh index 84677789..9c7dfa85 100644 --- a/experiments/jobscripts/testing/lin_sep_threaded.sh +++ b/experiments/jobscripts/testing/lin_sep_threaded.sh @@ -1,11 +1,11 @@ #!/bin/bash #SBATCH --job-name="Grid-search Linearly Separable (ECCCo)" -#SBATCH --time=00:30:00 -#SBATCH --ntasks=10 -#SBATCH --cpus-per-task=10 +#SBATCH --time=01:00:00 +#SBATCH --ntasks=20 +#SBATCH --cpus-per-task=20 #SBATCH --partition=compute -#SBATCH --mem-per-cpu=4GB +#SBATCH --mem-per-cpu=2GB #SBATCH --account=research-eemcs-insy #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. @@ -13,4 +13,4 @@ module load 2023r1 openmpi source experiments/slurm_header.sh -srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=10 threaded > experiments/grid_search_linearly_separable.log +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=100 threaded > experiments/grid_search_linearly_separable.log From d8e5f1147c80e3786b0a6228c079b0cbd9370db8 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Mon, 16 Oct 2023 13:45:32 +0200 Subject: [PATCH 042/171] set up grid search with mutli-threading on delftblue --- .../jobscripts/testing/lin_sep_threaded.sh | 10 +++++----- .../tuning/generators/california_housing.sh | 12 +++++++----- .../jobscripts/tuning/generators/circles.sh | 12 +++++++----- .../tuning/generators/german_credit.sh | 16 ++++++++++++++++ experiments/jobscripts/tuning/generators/gmsc.sh | 16 ++++++++++++++++ .../tuning/generators/linearly_separable.sh | 16 ++++++++++++++++ .../jobscripts/tuning/generators/moons.sh | 16 ++++++++++++++++ .../jobscripts/tuning/generators/synthetic.sh | 14 -------------- .../jobscripts/tuning/generators/tabular.sh | 14 -------------- experiments/setup_env.jl | 5 ++++- 10 files changed, 87 insertions(+), 44 deletions(-) create mode 100644 experiments/jobscripts/tuning/generators/german_credit.sh create mode 100644 experiments/jobscripts/tuning/generators/gmsc.sh create mode 100644 experiments/jobscripts/tuning/generators/linearly_separable.sh create mode 100644 experiments/jobscripts/tuning/generators/moons.sh delete mode 100644 experiments/jobscripts/tuning/generators/synthetic.sh delete mode 100644 experiments/jobscripts/tuning/generators/tabular.sh diff --git a/experiments/jobscripts/testing/lin_sep_threaded.sh b/experiments/jobscripts/testing/lin_sep_threaded.sh index 9c7dfa85..be7aa826 100644 --- a/experiments/jobscripts/testing/lin_sep_threaded.sh +++ b/experiments/jobscripts/testing/lin_sep_threaded.sh @@ -1,11 +1,11 @@ #!/bin/bash #SBATCH --job-name="Grid-search Linearly Separable (ECCCo)" -#SBATCH --time=01:00:00 -#SBATCH --ntasks=20 -#SBATCH --cpus-per-task=20 +#SBATCH --time=00:30:00 +#SBATCH --ntasks=14 +#SBATCH --cpus-per-task=14 #SBATCH --partition=compute -#SBATCH --mem-per-cpu=2GB +#SBATCH --mem-per-cpu=4GB #SBATCH --account=research-eemcs-insy #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. @@ -13,4 +13,4 @@ module load 2023r1 openmpi source experiments/slurm_header.sh -srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=100 threaded > experiments/grid_search_linearly_separable.log +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=20 threaded > experiments/grid_search_linearly_separable.log diff --git a/experiments/jobscripts/tuning/generators/california_housing.sh b/experiments/jobscripts/tuning/generators/california_housing.sh index ded42416..772c8117 100644 --- a/experiments/jobscripts/tuning/generators/california_housing.sh +++ b/experiments/jobscripts/tuning/generators/california_housing.sh @@ -1,14 +1,16 @@ #!/bin/bash #SBATCH --job-name="Grid-search California Housing (ECCCo)" -#SBATCH --time=02:00:00 -#SBATCH --ntasks=100 -#SBATCH --cpus-per-task=1 +#SBATCH --time=01:00:00 +#SBATCH --ntasks=20 +#SBATCH --cpus-per-task=20 #SBATCH --partition=compute -#SBATCH --mem-per-cpu=8GB +#SBATCH --mem-per-cpu=2GB #SBATCH --account=research-eemcs-insy #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. module load 2023r1 openmpi -srun julia --project=experiments experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search n_individuals=20 store_ce > experiments/grid_search_california_housing.log +source experiments/slurm_header.sh + +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search threaded n_individuals=10 > experiments/logs/grid_search_california_housing.log diff --git a/experiments/jobscripts/tuning/generators/circles.sh b/experiments/jobscripts/tuning/generators/circles.sh index 5d926be3..f9bc0129 100644 --- a/experiments/jobscripts/tuning/generators/circles.sh +++ b/experiments/jobscripts/tuning/generators/circles.sh @@ -1,14 +1,16 @@ #!/bin/bash #SBATCH --job-name="Grid-search Circles (ECCCo)" -#SBATCH --time=02:00:00 -#SBATCH --ntasks=100 -#SBATCH --cpus-per-task=1 +#SBATCH --time=01:00:00 +#SBATCH --ntasks=30 +#SBATCH --cpus-per-task=30 #SBATCH --partition=compute -#SBATCH --mem-per-cpu=8GB +#SBATCH --mem-per-cpu=1GB #SBATCH --account=research-eemcs-insy #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. module load 2023r1 openmpi -srun julia --project=experiments experiments/run_experiments.jl -- data=circles output_path=results mpi grid_search > experiments/grid_search_circles.log +source experiments/slurm_header.sh + +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=circles output_path=results mpi grid_search threaded n_individuals=100 > experiments/logs/grid_search_circles.log diff --git a/experiments/jobscripts/tuning/generators/german_credit.sh b/experiments/jobscripts/tuning/generators/german_credit.sh new file mode 100644 index 00000000..263ac1bd --- /dev/null +++ b/experiments/jobscripts/tuning/generators/german_credit.sh @@ -0,0 +1,16 @@ +#!/bin/bash + +#SBATCH --job-name="Grid-search German Credit (ECCCo)" +#SBATCH --time=01:00:00 +#SBATCH --ntasks=30 +#SBATCH --cpus-per-task=30 +#SBATCH --partition=compute +#SBATCH --mem-per-cpu=1GB +#SBATCH --account=research-eemcs-insy +#SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. + +module load 2023r1 openmpi + +source experiments/slurm_header.sh + +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=german_credit output_path=results mpi grid_search threaded n_individuals=100 > experiments/logs/grid_search_german_credit.log diff --git a/experiments/jobscripts/tuning/generators/gmsc.sh b/experiments/jobscripts/tuning/generators/gmsc.sh new file mode 100644 index 00000000..729fa36e --- /dev/null +++ b/experiments/jobscripts/tuning/generators/gmsc.sh @@ -0,0 +1,16 @@ +#!/bin/bash + +#SBATCH --job-name="Grid-search GMSC (ECCCo)" +#SBATCH --time=01:00:00 +#SBATCH --ntasks=20 +#SBATCH --cpus-per-task=20 +#SBATCH --partition=compute +#SBATCH --mem-per-cpu=2GB +#SBATCH --account=research-eemcs-insy +#SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. + +module load 2023r1 openmpi + +source experiments/slurm_header.sh + +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=gmsc output_path=results mpi grid_search threaded n_individuals=10 > experiments/logs/grid_search_gmsc.log diff --git a/experiments/jobscripts/tuning/generators/linearly_separable.sh b/experiments/jobscripts/tuning/generators/linearly_separable.sh new file mode 100644 index 00000000..fca9ee05 --- /dev/null +++ b/experiments/jobscripts/tuning/generators/linearly_separable.sh @@ -0,0 +1,16 @@ +#!/bin/bash + +#SBATCH --job-name="Grid-search Linearly Separable (ECCCo)" +#SBATCH --time=01:00:00 +#SBATCH --ntasks=30 +#SBATCH --cpus-per-task=30 +#SBATCH --partition=compute +#SBATCH --mem-per-cpu=1GB +#SBATCH --account=research-eemcs-insy +#SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. + +module load 2023r1 openmpi + +source experiments/slurm_header.sh + +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search threaded n_individuals=100 > experiments/logs/grid_search_linearly_separable.log diff --git a/experiments/jobscripts/tuning/generators/moons.sh b/experiments/jobscripts/tuning/generators/moons.sh new file mode 100644 index 00000000..8d81d33a --- /dev/null +++ b/experiments/jobscripts/tuning/generators/moons.sh @@ -0,0 +1,16 @@ +#!/bin/bash + +#SBATCH --job-name="Grid-search Moons (ECCCo)" +#SBATCH --time=01:00:00 +#SBATCH --ntasks=30 +#SBATCH --cpus-per-task=30 +#SBATCH --partition=compute +#SBATCH --mem-per-cpu=1GB +#SBATCH --account=research-eemcs-insy +#SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. + +module load 2023r1 openmpi + +source experiments/slurm_header.sh + +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=moons output_path=results mpi grid_search threaded n_individuals=100 > experiments/logs/grid_search_moons.log diff --git a/experiments/jobscripts/tuning/generators/synthetic.sh b/experiments/jobscripts/tuning/generators/synthetic.sh deleted file mode 100644 index 66bcf412..00000000 --- a/experiments/jobscripts/tuning/generators/synthetic.sh +++ /dev/null @@ -1,14 +0,0 @@ -#!/bin/bash - -#SBATCH --job-name="Grid-search Synthetic (ECCCo)" -#SBATCH --time=05:00:00 -#SBATCH --ntasks=100 -#SBATCH --cpus-per-task=1 -#SBATCH --partition=compute -#SBATCH --mem-per-cpu=8GB -#SBATCH --account=research-eemcs-insy -#SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. - -module load 2023r1 openmpi - -srun julia --project=experiments experiments/run_experiments.jl -- data=linearly_separable,moons,circles output_path=results mpi grid_search > experiments/grid_search_synthetic.log diff --git a/experiments/jobscripts/tuning/generators/tabular.sh b/experiments/jobscripts/tuning/generators/tabular.sh deleted file mode 100644 index 3c043ea7..00000000 --- a/experiments/jobscripts/tuning/generators/tabular.sh +++ /dev/null @@ -1,14 +0,0 @@ -#!/bin/bash - -#SBATCH --job-name="Grid-search Tabular (ECCCo)" -#SBATCH --time=04:00:00 -#SBATCH --ntasks=100 -#SBATCH --cpus-per-task=1 -#SBATCH --partition=compute -#SBATCH --mem-per-cpu=8GB -#SBATCH --account=research-eemcs-insy -#SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. - -module load 2023r1 openmpi - -srun julia --project=experiments experiments/run_experiments.jl -- data=gmsc,german_credit output_path=results mpi grid_search n_individuals=25 store_ce > experiments/grid_search_tabular.log diff --git a/experiments/setup_env.jl b/experiments/setup_env.jl index 608f6dc0..931a3c1e 100644 --- a/experiments/setup_env.jl +++ b/experiments/setup_env.jl @@ -109,6 +109,9 @@ if "mpi" ∈ ARGS @info "Multi-processing using MPI. Disabling logging on non-root processes." if USE_THREADS @info "Multi-threading using $(Threads.nthreads()) threads." + if Threads.threadid() != 1 + global_logger(NullLogger()) + end end end else @@ -196,7 +199,7 @@ DEFAULT_GENERATOR_TUNING = ( "Generator tuning parameters for large datasets." DEFAULT_GENERATOR_TUNING_LARGE = ( Λ = [[0.1, 0.1, 0.1], [0.1, 0.1, 0.2], [0.2, 0.2, 0.2]], - reg_strength = [0.0,], + reg_strength=[0.0, 0.1,], opt = [ Descent(0.01), Descent(0.05), From ea483e30ef6593770c2b922f728f8d7c21004b6e Mon Sep 17 00:00:00 2001 From: pat-alt Date: Mon, 16 Oct 2023 14:11:52 +0200 Subject: [PATCH 043/171] increased default neach --- experiments/setup_env.jl | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/experiments/setup_env.jl b/experiments/setup_env.jl index 931a3c1e..1aebe6d5 100644 --- a/experiments/setup_env.jl +++ b/experiments/setup_env.jl @@ -71,7 +71,7 @@ if any(contains.(ARGS, "n_each=")) ARGS[findall(contains.(ARGS, "n_each="))][1] |> x -> replace(x, "n_each=" => "") |> x -> parse(Int, x) else - n_each = 16 + n_each = 32 end "Number of objects to pass to each process." From d51db9bcfe01000bb0f7d6040d6b02ab222b3c3f Mon Sep 17 00:00:00 2001 From: pat-alt Date: Mon, 16 Oct 2023 14:13:29 +0200 Subject: [PATCH 044/171] decreased mem on test script --- experiments/jobscripts/testing/lin_sep_threaded.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/experiments/jobscripts/testing/lin_sep_threaded.sh b/experiments/jobscripts/testing/lin_sep_threaded.sh index be7aa826..f9ae5381 100644 --- a/experiments/jobscripts/testing/lin_sep_threaded.sh +++ b/experiments/jobscripts/testing/lin_sep_threaded.sh @@ -5,7 +5,7 @@ #SBATCH --ntasks=14 #SBATCH --cpus-per-task=14 #SBATCH --partition=compute -#SBATCH --mem-per-cpu=4GB +#SBATCH --mem-per-cpu=1GB #SBATCH --account=research-eemcs-insy #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. From c5b0604bee04ab23d876fcb88b33729d7275188e Mon Sep 17 00:00:00 2001 From: pat-alt Date: Mon, 16 Oct 2023 14:55:09 +0200 Subject: [PATCH 045/171] perparing stuff for daic --- experiments/daic/testing/lin_sep_threaded.sh | 8 +++++--- .../daic/tuning/generators/california_housing.sh | 10 ++++++---- experiments/daic/tuning/generators/circles.sh | 14 ++++++++------ .../daic/tuning/generators/german_credit.sh | 14 ++++++++------ experiments/daic/tuning/generators/gmsc.sh | 12 +++++++----- .../daic/tuning/generators/linearly_separable.sh | 12 +++++++----- experiments/daic/tuning/generators/moons.sh | 16 ++++++++++++++++ experiments/daic/tuning/generators/synthetic.sh | 14 -------------- experiments/daic/tuning/generators/tabular.sh | 14 -------------- 9 files changed, 57 insertions(+), 57 deletions(-) create mode 100644 experiments/daic/tuning/generators/moons.sh delete mode 100644 experiments/daic/tuning/generators/synthetic.sh delete mode 100644 experiments/daic/tuning/generators/tabular.sh diff --git a/experiments/daic/testing/lin_sep_threaded.sh b/experiments/daic/testing/lin_sep_threaded.sh index b07c5e80..cfd2116d 100644 --- a/experiments/daic/testing/lin_sep_threaded.sh +++ b/experiments/daic/testing/lin_sep_threaded.sh @@ -1,14 +1,16 @@ #!/bin/bash #SBATCH --job-name="Grid-search Linearly Separable (ECCCo)" -#SBATCH --time=01:00:00 +#SBATCH --time=00:30:00 #SBATCH --ntasks=10 #SBATCH --cpus-per-task=10 #SBATCH --partition=general -#SBATCH --mem-per-cpu=4GB +#SBATCH --mem-per-cpu=1GB #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. module use /opt/insy/modulefiles # Use DAIC INSY software collection module load openmpi -srun julia --project=experiments experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=10 threaded > experiments/grid_search_linearly_separable.log +source experiments/slurm_header.sh + +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=10 threaded > experiments/grid_search_linearly_separable.log diff --git a/experiments/daic/tuning/generators/california_housing.sh b/experiments/daic/tuning/generators/california_housing.sh index f8648ae6..3bd54dbf 100644 --- a/experiments/daic/tuning/generators/california_housing.sh +++ b/experiments/daic/tuning/generators/california_housing.sh @@ -2,13 +2,15 @@ #SBATCH --job-name="Grid-search California Housing (ECCCo)" #SBATCH --time=01:00:00 -#SBATCH --ntasks=100 -#SBATCH --cpus-per-task=1 +#SBATCH --ntasks=20 +#SBATCH --cpus-per-task=20 #SBATCH --partition=general -#SBATCH --mem-per-cpu=4GB +#SBATCH --mem-per-cpu=2GB #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. module use /opt/insy/modulefiles # Use DAIC INSY software collection module load openmpi -srun julia --project=experiments experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search n_individuals=5 > experiments/grid_search_california_housing.log +source experiments/slurm_header.sh + +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search threaded n_individuals=10 > experiments/logs/grid_search_california_housing.log diff --git a/experiments/daic/tuning/generators/circles.sh b/experiments/daic/tuning/generators/circles.sh index beaa7e9b..2ab2cb77 100644 --- a/experiments/daic/tuning/generators/circles.sh +++ b/experiments/daic/tuning/generators/circles.sh @@ -1,14 +1,16 @@ #!/bin/bash -#SBATCH --job-name="Grid-search Synthetic (ECCCo)" -#SBATCH --time=04:00:00 -#SBATCH --ntasks=100 -#SBATCH --cpus-per-task=1 +#SBATCH --job-name="Grid-search Circles (ECCCo)" +#SBATCH --time=01:00:00 +#SBATCH --ntasks=30 +#SBATCH --cpus-per-task=30 #SBATCH --partition=general -#SBATCH --mem-per-cpu=4GB +#SBATCH --mem-per-cpu=1GB #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. module use /opt/insy/modulefiles # Use DAIC INSY software collection module load openmpi -srun julia --project=experiments experiments/run_experiments.jl -- data=linearly_separable,moons,circles output_path=results mpi grid_search > experiments/grid_search_synthetic.log \ No newline at end of file +source experiments/slurm_header.sh + +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=circles output_path=results mpi grid_search threaded n_individuals=100 > experiments/logs/grid_search_circles.log diff --git a/experiments/daic/tuning/generators/german_credit.sh b/experiments/daic/tuning/generators/german_credit.sh index 12bc660b..3b664647 100644 --- a/experiments/daic/tuning/generators/german_credit.sh +++ b/experiments/daic/tuning/generators/german_credit.sh @@ -1,14 +1,16 @@ #!/bin/bash -#SBATCH --job-name="Grid-search Germand Credit (ECCCo)" -#SBATCH --time=04:00:00 -#SBATCH --ntasks=1000 -#SBATCH --cpus-per-task=1 +#SBATCH --job-name="Grid-search German Credit (ECCCo)" +#SBATCH --time=01:00:00 +#SBATCH --ntasks=30 +#SBATCH --cpus-per-task=30 #SBATCH --partition=general -#SBATCH --mem-per-cpu=8GB +#SBATCH --mem-per-cpu=1GB #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. module use /opt/insy/modulefiles # Use DAIC INSY software collection module load openmpi -srun julia --project=experiments experiments/run_experiments.jl -- data=german_credit output_path=results mpi grid_search > experiments/grid_search_german_credit.log +source experiments/slurm_header.sh + +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=german_credit output_path=results mpi grid_search threaded n_individuals=100 > experiments/logs/grid_search_german_credit.log diff --git a/experiments/daic/tuning/generators/gmsc.sh b/experiments/daic/tuning/generators/gmsc.sh index 31962abd..35e7e637 100644 --- a/experiments/daic/tuning/generators/gmsc.sh +++ b/experiments/daic/tuning/generators/gmsc.sh @@ -1,14 +1,16 @@ #!/bin/bash #SBATCH --job-name="Grid-search GMSC (ECCCo)" -#SBATCH --time=04:00:00 -#SBATCH --ntasks=1000 -#SBATCH --cpus-per-task=1 +#SBATCH --time=01:00:00 +#SBATCH --ntasks=20 +#SBATCH --cpus-per-task=20 #SBATCH --partition=general -#SBATCH --mem-per-cpu=8GB +#SBATCH --mem-per-cpu=2GB #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. module use /opt/insy/modulefiles # Use DAIC INSY software collection module load openmpi -srun julia --project=experiments experiments/run_experiments.jl -- data=gmsc output_path=results mpi grid_search > experiments/grid_search_gmsc.log +source experiments/slurm_header.sh + +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=gmsc output_path=results mpi grid_search threaded n_individuals=10 > experiments/logs/grid_search_gmsc.log diff --git a/experiments/daic/tuning/generators/linearly_separable.sh b/experiments/daic/tuning/generators/linearly_separable.sh index 20d2d855..27f4a81a 100644 --- a/experiments/daic/tuning/generators/linearly_separable.sh +++ b/experiments/daic/tuning/generators/linearly_separable.sh @@ -1,14 +1,16 @@ #!/bin/bash #SBATCH --job-name="Grid-search Linearly Separable (ECCCo)" -#SBATCH --time=02:00:00 -#SBATCH --ntasks=1000 -#SBATCH --cpus-per-task=1 +#SBATCH --time=01:00:00 +#SBATCH --ntasks=30 +#SBATCH --cpus-per-task=30 #SBATCH --partition=general -#SBATCH --mem-per-cpu=4GB +#SBATCH --mem-per-cpu=1GB #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. module use /opt/insy/modulefiles # Use DAIC INSY software collection module load openmpi -srun julia --project=experiments experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search > experiments/grid_search_linearly_separable.log +source experiments/slurm_header.sh + +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search threaded n_individuals=100 > experiments/logs/grid_search_linearly_separable.log diff --git a/experiments/daic/tuning/generators/moons.sh b/experiments/daic/tuning/generators/moons.sh new file mode 100644 index 00000000..2c7f4aab --- /dev/null +++ b/experiments/daic/tuning/generators/moons.sh @@ -0,0 +1,16 @@ +#!/bin/bash + +#SBATCH --job-name="Grid-search Moons (ECCCo)" +#SBATCH --time=01:00:00 +#SBATCH --ntasks=30 +#SBATCH --cpus-per-task=30 +#SBATCH --partition=general +#SBATCH --mem-per-cpu=1GB +#SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. + +module use /opt/insy/modulefiles # Use DAIC INSY software collection +module load openmpi + +source experiments/slurm_header.sh + +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=moons output_path=results mpi grid_search threaded n_individuals=100 > experiments/logs/grid_search_moons.log diff --git a/experiments/daic/tuning/generators/synthetic.sh b/experiments/daic/tuning/generators/synthetic.sh deleted file mode 100644 index efe8e545..00000000 --- a/experiments/daic/tuning/generators/synthetic.sh +++ /dev/null @@ -1,14 +0,0 @@ -#!/bin/bash - -#SBATCH --job-name="Grid-search Synthetic (ECCCo)" -#SBATCH --time=02:00:00 -#SBATCH --ntasks=1000 -#SBATCH --cpus-per-task=1 -#SBATCH --partition=general -#SBATCH --mem-per-cpu=8GB -#SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. - -module use /opt/insy/modulefiles # Use DAIC INSY software collection -module load openmpi - -srun julia --project=experiments experiments/run_experiments.jl -- data=circles output_path=results mpi grid_search > experiments/grid_search_synthetic.log diff --git a/experiments/daic/tuning/generators/tabular.sh b/experiments/daic/tuning/generators/tabular.sh deleted file mode 100644 index cc139b8e..00000000 --- a/experiments/daic/tuning/generators/tabular.sh +++ /dev/null @@ -1,14 +0,0 @@ -#!/bin/bash - -#SBATCH --job-name="Grid-search Tabular (ECCCo)" -#SBATCH --time=04:00:00 -#SBATCH --ntasks=2000 -#SBATCH --cpus-per-task=1 -#SBATCH --partition=general -#SBATCH --mem-per-cpu=4GB -#SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. - -module use /opt/insy/modulefiles # Use DAIC INSY software collection -module load openmpi - -srun julia --project=experiments experiments/run_experiments.jl -- data=gmsc,german_credit output_path=results mpi grid_search > experiments/grid_search_tabular.log From 1a0384cad69509ca0caff7f65ba8b9d419b81823 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Mon, 16 Oct 2023 16:25:28 +0200 Subject: [PATCH 046/171] slowly scaling up --- experiments/daic/testing/cali_100_8.sh | 6 +++--- .../jobscripts/tuning/generators/california_housing.sh | 2 +- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/experiments/daic/testing/cali_100_8.sh b/experiments/daic/testing/cali_100_8.sh index b619982c..2435ed38 100644 --- a/experiments/daic/testing/cali_100_8.sh +++ b/experiments/daic/testing/cali_100_8.sh @@ -2,8 +2,8 @@ #SBATCH --job-name="Grid-search California Housing (ECCCo)" #SBATCH --time=01:00:00 -#SBATCH --ntasks=100 -#SBATCH --cpus-per-task=1 +#SBATCH --ntasks=10 +#SBATCH --cpus-per-task=10 #SBATCH --partition=general #SBATCH --mem-per-cpu=8GB #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. @@ -11,5 +11,5 @@ module use /opt/insy/modulefiles # Use DAIC INSY software collection module load openmpi -srun julia --project=experiments experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search n_individuals=10 n_each=16 > experiments/grid_search_california_housing.log +srun julia --project=experiments experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search n_individuals=10 > experiments/grid_search_california_housing.log diff --git a/experiments/jobscripts/tuning/generators/california_housing.sh b/experiments/jobscripts/tuning/generators/california_housing.sh index 772c8117..be1e47ff 100644 --- a/experiments/jobscripts/tuning/generators/california_housing.sh +++ b/experiments/jobscripts/tuning/generators/california_housing.sh @@ -5,7 +5,7 @@ #SBATCH --ntasks=20 #SBATCH --cpus-per-task=20 #SBATCH --partition=compute -#SBATCH --mem-per-cpu=2GB +#SBATCH --mem-per-cpu=4GB #SBATCH --account=research-eemcs-insy #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. From a5ae59878c7d686421775cd6afd2e2c0aa8bb702 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Mon, 16 Oct 2023 16:29:07 +0200 Subject: [PATCH 047/171] added slurm-header --- experiments/daic/testing/cali_100_8.sh | 2 ++ experiments/daic/testing/cali_50_8.sh | 2 ++ experiments/daic/testing/lin_sep.sh | 3 +-- experiments/daic/testing/lin_sep_200cpu.sh | 14 -------------- experiments/daic/testing/lin_sep_32each.sh | 14 -------------- experiments/daic/testing/lin_sep_4each.sh | 14 -------------- experiments/daic/testing/lin_sep_no_threads.sh | 2 +- 7 files changed, 6 insertions(+), 45 deletions(-) delete mode 100644 experiments/daic/testing/lin_sep_200cpu.sh delete mode 100644 experiments/daic/testing/lin_sep_32each.sh delete mode 100644 experiments/daic/testing/lin_sep_4each.sh diff --git a/experiments/daic/testing/cali_100_8.sh b/experiments/daic/testing/cali_100_8.sh index 2435ed38..51efed93 100644 --- a/experiments/daic/testing/cali_100_8.sh +++ b/experiments/daic/testing/cali_100_8.sh @@ -11,5 +11,7 @@ module use /opt/insy/modulefiles # Use DAIC INSY software collection module load openmpi +source experiments/slurm_header.sh + srun julia --project=experiments experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search n_individuals=10 > experiments/grid_search_california_housing.log diff --git a/experiments/daic/testing/cali_50_8.sh b/experiments/daic/testing/cali_50_8.sh index 177e8215..aa671662 100644 --- a/experiments/daic/testing/cali_50_8.sh +++ b/experiments/daic/testing/cali_50_8.sh @@ -11,5 +11,7 @@ module use /opt/insy/modulefiles # Use DAIC INSY software collection module load openmpi +source experiments/slurm_header.sh + srun julia --project=experiments experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search n_individuals=10 n_each=16 > experiments/grid_search_california_housing.log diff --git a/experiments/daic/testing/lin_sep.sh b/experiments/daic/testing/lin_sep.sh index 765609ad..80fee770 100644 --- a/experiments/daic/testing/lin_sep.sh +++ b/experiments/daic/testing/lin_sep.sh @@ -11,7 +11,6 @@ module use /opt/insy/modulefiles # Use DAIC INSY software collection module load openmpi -set -x -export SRUN_CPUS_PER_TASK="$SLURM_CPUS_PER_TASK" +source experiments/slurm_header.sh srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=10 threaded > experiments/grid_search_linearly_separable.log diff --git a/experiments/daic/testing/lin_sep_200cpu.sh b/experiments/daic/testing/lin_sep_200cpu.sh deleted file mode 100644 index 173f6469..00000000 --- a/experiments/daic/testing/lin_sep_200cpu.sh +++ /dev/null @@ -1,14 +0,0 @@ -#!/bin/bash - -#SBATCH --job-name="Grid-search Linearly Separable (ECCCo)" -#SBATCH --time=00:30:00 -#SBATCH --ntasks=200 -#SBATCH --cpus-per-task=1 -#SBATCH --partition=general -#SBATCH --mem-per-cpu=4GB -#SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. - -module use /opt/insy/modulefiles # Use DAIC INSY software collection -module load openmpi - -srun julia --project=experiments experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=10 > experiments/grid_search_linearly_separable.log diff --git a/experiments/daic/testing/lin_sep_32each.sh b/experiments/daic/testing/lin_sep_32each.sh deleted file mode 100644 index ff674ad2..00000000 --- a/experiments/daic/testing/lin_sep_32each.sh +++ /dev/null @@ -1,14 +0,0 @@ -#!/bin/bash - -#SBATCH --job-name="Grid-search Linearly Separable (ECCCo)" -#SBATCH --time=01:00:00 -#SBATCH --ntasks=100 -#SBATCH --cpus-per-task=1 -#SBATCH --partition=general -#SBATCH --mem-per-cpu=4GB -#SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. - -module use /opt/insy/modulefiles # Use DAIC INSY software collection -module load openmpi - -srun julia --project=experiments experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=10 > experiments/grid_search_linearly_separable.log diff --git a/experiments/daic/testing/lin_sep_4each.sh b/experiments/daic/testing/lin_sep_4each.sh deleted file mode 100644 index b5891999..00000000 --- a/experiments/daic/testing/lin_sep_4each.sh +++ /dev/null @@ -1,14 +0,0 @@ -#!/bin/bash - -#SBATCH --job-name="Grid-search Linearly Separable (ECCCo)" -#SBATCH --time=01:00:00 -#SBATCH --ntasks=100 -#SBATCH --cpus-per-task=1 -#SBATCH --partition=general -#SBATCH --mem-per-cpu=4GB -#SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. - -module use /opt/insy/modulefiles # Use DAIC INSY software collection -module load openmpi - -srun julia --project=experiments experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=10 n_each=4 > experiments/grid_search_linearly_separable.log diff --git a/experiments/daic/testing/lin_sep_no_threads.sh b/experiments/daic/testing/lin_sep_no_threads.sh index 0b84c07b..d69ea69a 100644 --- a/experiments/daic/testing/lin_sep_no_threads.sh +++ b/experiments/daic/testing/lin_sep_no_threads.sh @@ -11,6 +11,6 @@ module use /opt/insy/modulefiles # Use DAIC INSY software collection module load openmpi -export SRUN_CPUS_PER_TASK="$SLURM_CPUS_PER_TASK" +source experiments/slurm_header.sh srun julia --project=experiments experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=10 > experiments/grid_search_linearly_separable.log From dc72ad1de711023cc2be5f294d31b914ad9db745 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Mon, 16 Oct 2023 17:00:53 +0200 Subject: [PATCH 048/171] smaller grid --- experiments/daic/testing/cali_100_8.sh | 2 +- experiments/setup_env.jl | 6 ++---- 2 files changed, 3 insertions(+), 5 deletions(-) diff --git a/experiments/daic/testing/cali_100_8.sh b/experiments/daic/testing/cali_100_8.sh index 51efed93..ff7c6f7a 100644 --- a/experiments/daic/testing/cali_100_8.sh +++ b/experiments/daic/testing/cali_100_8.sh @@ -5,7 +5,7 @@ #SBATCH --ntasks=10 #SBATCH --cpus-per-task=10 #SBATCH --partition=general -#SBATCH --mem-per-cpu=8GB +#SBATCH --mem-per-cpu=2GB #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. module use /opt/insy/modulefiles # Use DAIC INSY software collection diff --git a/experiments/setup_env.jl b/experiments/setup_env.jl index 1aebe6d5..8c5a52d1 100644 --- a/experiments/setup_env.jl +++ b/experiments/setup_env.jl @@ -198,15 +198,13 @@ DEFAULT_GENERATOR_TUNING = ( "Generator tuning parameters for large datasets." DEFAULT_GENERATOR_TUNING_LARGE = ( - Λ = [[0.1, 0.1, 0.1], [0.1, 0.1, 0.2], [0.2, 0.2, 0.2]], + Λ = [[0.1, 0.1, 0.1], [0.1, 0.1, 0.2],], reg_strength=[0.0, 0.1,], opt = [ Descent(0.01), - Descent(0.05), Optimiser(ClipValue(0.01), Descent(0.01)), - Optimiser(ClipValue(0.05), Descent(0.05)), ], - decay = [(0.0, 1), (0.01, 1), (0.1, 1)], + decay = [(0.0, 1), (0.01, 1)], ) "Boolean flag to check if model tuning was specified." From 54e030bb8d1c6fccc87a69a0eee02d1d3b97ce7a Mon Sep 17 00:00:00 2001 From: pat-alt Date: Mon, 16 Oct 2023 17:05:14 +0200 Subject: [PATCH 049/171] now added command for threading --- experiments/daic/testing/cali_100_8.sh | 2 +- experiments/daic/testing/cali_50_8.sh | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/experiments/daic/testing/cali_100_8.sh b/experiments/daic/testing/cali_100_8.sh index ff7c6f7a..29153135 100644 --- a/experiments/daic/testing/cali_100_8.sh +++ b/experiments/daic/testing/cali_100_8.sh @@ -13,5 +13,5 @@ module load openmpi source experiments/slurm_header.sh -srun julia --project=experiments experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search n_individuals=10 > experiments/grid_search_california_housing.log +srun julia --project=experiments experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search n_individuals=10 threaded > experiments/grid_search_california_housing.log diff --git a/experiments/daic/testing/cali_50_8.sh b/experiments/daic/testing/cali_50_8.sh index aa671662..34bb1102 100644 --- a/experiments/daic/testing/cali_50_8.sh +++ b/experiments/daic/testing/cali_50_8.sh @@ -13,5 +13,5 @@ module load openmpi source experiments/slurm_header.sh -srun julia --project=experiments experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search n_individuals=10 n_each=16 > experiments/grid_search_california_housing.log +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search n_individuals=10 n_each=16 threaded > experiments/grid_search_california_housing.log From be84f6be416233a9858538fe0e1c5fe37efd2eb8 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Mon, 16 Oct 2023 17:05:29 +0200 Subject: [PATCH 050/171] threads --- experiments/daic/testing/cali_100_8.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/experiments/daic/testing/cali_100_8.sh b/experiments/daic/testing/cali_100_8.sh index 29153135..4f7ea461 100644 --- a/experiments/daic/testing/cali_100_8.sh +++ b/experiments/daic/testing/cali_100_8.sh @@ -13,5 +13,5 @@ module load openmpi source experiments/slurm_header.sh -srun julia --project=experiments experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search n_individuals=10 threaded > experiments/grid_search_california_housing.log +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search n_individuals=10 threaded > experiments/grid_search_california_housing.log From 4190226ab921ce40eabfaed3690ffd4de020b2e9 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Mon, 16 Oct 2023 17:27:31 +0200 Subject: [PATCH 051/171] grid back up --- experiments/daic/testing/cali_100_8.sh | 2 +- experiments/setup_env.jl | 4 +++- 2 files changed, 4 insertions(+), 2 deletions(-) diff --git a/experiments/daic/testing/cali_100_8.sh b/experiments/daic/testing/cali_100_8.sh index 4f7ea461..7336d0d3 100644 --- a/experiments/daic/testing/cali_100_8.sh +++ b/experiments/daic/testing/cali_100_8.sh @@ -1,7 +1,7 @@ #!/bin/bash #SBATCH --job-name="Grid-search California Housing (ECCCo)" -#SBATCH --time=01:00:00 +#SBATCH --time=01:10:00 #SBATCH --ntasks=10 #SBATCH --cpus-per-task=10 #SBATCH --partition=general diff --git a/experiments/setup_env.jl b/experiments/setup_env.jl index 8c5a52d1..8cf0de55 100644 --- a/experiments/setup_env.jl +++ b/experiments/setup_env.jl @@ -202,9 +202,11 @@ DEFAULT_GENERATOR_TUNING_LARGE = ( reg_strength=[0.0, 0.1,], opt = [ Descent(0.01), + Descent(0.05), Optimiser(ClipValue(0.01), Descent(0.01)), + Optimiser(ClipValue(0.05), Descent(0.05)), ], - decay = [(0.0, 1), (0.01, 1)], + decay = [(0.0, 1), (0.01, 1), (0.1, 1)], ) "Boolean flag to check if model tuning was specified." From 42669318392513ceec7333c572aae97b787dde4d Mon Sep 17 00:00:00 2001 From: pat-alt Date: Tue, 17 Oct 2023 08:33:24 +0200 Subject: [PATCH 052/171] let's do this --- experiments/california_housing.jl | 3 +++ experiments/circles.jl | 3 +++ experiments/daic/testing/cali_100_8.sh | 6 +++--- experiments/german_credit.jl | 3 +++ experiments/gmsc.jl | 3 +++ experiments/jobscripts/testing/cali.sh | 17 +++++++++++++++++ experiments/linearly_separable.jl | 3 +++ experiments/moons.jl | 3 +++ 8 files changed, 38 insertions(+), 3 deletions(-) create mode 100644 experiments/jobscripts/testing/cali.sh diff --git a/experiments/california_housing.jl b/experiments/california_housing.jl index bd46c0da..40f2f8a9 100644 --- a/experiments/california_housing.jl +++ b/experiments/california_housing.jl @@ -3,6 +3,9 @@ dataname = "California Housing" counterfactual_data, test_data = train_test_split(load_california_housing(nothing); test_size = TEST_SIZE) +# Domain constraints: +counterfactual_data.domain = extrema(counterfactual_data.X, dims=2) + # VAE: using CounterfactualExplanations.GenerativeModels: VAE, train! X = counterfactual_data.X diff --git a/experiments/circles.jl b/experiments/circles.jl index 684f72db..f0789906 100644 --- a/experiments/circles.jl +++ b/experiments/circles.jl @@ -4,6 +4,9 @@ n_obs = Int(1000 / (1.0 - TEST_SIZE)) counterfactual_data, test_data = train_test_split(load_circles(n_obs; noise = 0.05, factor = 0.5); test_size = TEST_SIZE) +# Domain constraints: +counterfactual_data.domain = extrema(counterfactual_data.X, dims=2) + # Model tuning: model_tuning_params = DEFAULT_MODEL_TUNING_SMALL diff --git a/experiments/daic/testing/cali_100_8.sh b/experiments/daic/testing/cali_100_8.sh index 7336d0d3..0f8d2e90 100644 --- a/experiments/daic/testing/cali_100_8.sh +++ b/experiments/daic/testing/cali_100_8.sh @@ -1,9 +1,9 @@ #!/bin/bash #SBATCH --job-name="Grid-search California Housing (ECCCo)" -#SBATCH --time=01:10:00 -#SBATCH --ntasks=10 -#SBATCH --cpus-per-task=10 +#SBATCH --time=00:35:00 +#SBATCH --ntasks=14 +#SBATCH --cpus-per-task=14 #SBATCH --partition=general #SBATCH --mem-per-cpu=2GB #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. diff --git a/experiments/german_credit.jl b/experiments/german_credit.jl index e87ed290..2095cbc9 100644 --- a/experiments/german_credit.jl +++ b/experiments/german_credit.jl @@ -3,6 +3,9 @@ dataname = "German Credit" counterfactual_data, test_data = train_test_split(load_german_credit(nothing); test_size = TEST_SIZE) +# Domain constraints: +counterfactual_data.domain = extrema(counterfactual_data.X, dims=2) + # VAE: using CounterfactualExplanations.GenerativeModels: VAE, train! X = counterfactual_data.X diff --git a/experiments/gmsc.jl b/experiments/gmsc.jl index 8067eaa8..bb2cdee8 100644 --- a/experiments/gmsc.jl +++ b/experiments/gmsc.jl @@ -3,6 +3,9 @@ dataname = "GMSC" counterfactual_data, test_data = train_test_split(load_gmsc(nothing); test_size = TEST_SIZE) nobs = size(counterfactual_data.X, 2) +# Domain constraints: +counterfactual_data.domain = extrema(counterfactual_data.X, dims=2) + # VAE: using CounterfactualExplanations.GenerativeModels: VAE, train! X = counterfactual_data.X diff --git a/experiments/jobscripts/testing/cali.sh b/experiments/jobscripts/testing/cali.sh new file mode 100644 index 00000000..95564b2a --- /dev/null +++ b/experiments/jobscripts/testing/cali.sh @@ -0,0 +1,17 @@ +#!/bin/bash + +#SBATCH --job-name="Grid-search California Housing (ECCCo)" +#SBATCH --time=00:35:00 +#SBATCH --ntasks=14 +#SBATCH --cpus-per-task=14 +#SBATCH --partition=compute +#SBATCH --mem-per-cpu=2GB +#SBATCH --account=research-eemcs-insy +#SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. + +module use /opt/insy/modulefiles # Use DAIC INSY software collection +module load openmpi + +source experiments/slurm_header.sh + +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search n_individuals=10 threaded > experiments/grid_search_california_housing.log \ No newline at end of file diff --git a/experiments/linearly_separable.jl b/experiments/linearly_separable.jl index b12e4b3c..2421bd9a 100644 --- a/experiments/linearly_separable.jl +++ b/experiments/linearly_separable.jl @@ -6,6 +6,9 @@ counterfactual_data, test_data = train_test_split( test_size = TEST_SIZE, ) +# Domain constraints: +counterfactual_data.domain = extrema(counterfactual_data.X, dims=2) + # Model tuning: model_tuning_params = DEFAULT_MODEL_TUNING_SMALL diff --git a/experiments/moons.jl b/experiments/moons.jl index 9677a36c..a1500279 100644 --- a/experiments/moons.jl +++ b/experiments/moons.jl @@ -3,6 +3,9 @@ dataname = "Moons" n_obs = Int(2500 / (1.0 - TEST_SIZE)) counterfactual_data, test_data = train_test_split(load_moons(n_obs); test_size = TEST_SIZE) +# Domain constraints: +counterfactual_data.domain = extrema(counterfactual_data.X, dims=2) + # Model tuning: model_tuning_params = DEFAULT_MODEL_TUNING_SMALL From ef514312c83337550e75a86c7483f94f055c93a5 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Tue, 17 Oct 2023 09:20:33 +0200 Subject: [PATCH 053/171] uhuhuh --- experiments/jobscripts/testing/cali.sh | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/experiments/jobscripts/testing/cali.sh b/experiments/jobscripts/testing/cali.sh index 95564b2a..1c61c0b2 100644 --- a/experiments/jobscripts/testing/cali.sh +++ b/experiments/jobscripts/testing/cali.sh @@ -5,7 +5,7 @@ #SBATCH --ntasks=14 #SBATCH --cpus-per-task=14 #SBATCH --partition=compute -#SBATCH --mem-per-cpu=2GB +#SBATCH --mem-per-cpu=1GB #SBATCH --account=research-eemcs-insy #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. @@ -14,4 +14,4 @@ module load openmpi source experiments/slurm_header.sh -srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search n_individuals=10 threaded > experiments/grid_search_california_housing.log \ No newline at end of file +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search n_individuals=10 n_each=$SLURM_CPUS_PER_TASK threaded > experiments/grid_search_california_housing.log \ No newline at end of file From c83f50ebf504b7476983d3dd463412fea02610f3 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Tue, 17 Oct 2023 09:59:11 +0200 Subject: [PATCH 054/171] try neach nothing --- experiments/jobscripts/testing/cali.sh | 2 +- experiments/setup_env.jl | 3 ++- 2 files changed, 3 insertions(+), 2 deletions(-) diff --git a/experiments/jobscripts/testing/cali.sh b/experiments/jobscripts/testing/cali.sh index 1c61c0b2..da100a68 100644 --- a/experiments/jobscripts/testing/cali.sh +++ b/experiments/jobscripts/testing/cali.sh @@ -14,4 +14,4 @@ module load openmpi source experiments/slurm_header.sh -srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search n_individuals=10 n_each=$SLURM_CPUS_PER_TASK threaded > experiments/grid_search_california_housing.log \ No newline at end of file +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search n_individuals=10 n_each=nothing threaded > experiments/grid_search_california_housing.log \ No newline at end of file diff --git a/experiments/setup_env.jl b/experiments/setup_env.jl index 8cf0de55..699dd581 100644 --- a/experiments/setup_env.jl +++ b/experiments/setup_env.jl @@ -69,7 +69,8 @@ const N_IND_SPECIFIED = n_ind_specified if any(contains.(ARGS, "n_each=")) n_each = ARGS[findall(contains.(ARGS, "n_each="))][1] |> - x -> replace(x, "n_each=" => "") |> x -> parse(Int, x) + x -> replace(x, "n_each=" => "") |> + x -> x == "nothing" ? nothing : parse(Int, x) else n_each = 32 end From 9c0eeb588edb62bc5179b91f195d7d4fd03552b2 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Tue, 17 Oct 2023 10:02:13 +0200 Subject: [PATCH 055/171] lin sep --- experiments/jobscripts/testing/cali.sh | 2 +- experiments/jobscripts/testing/lin_sep.sh | 6 +++--- experiments/jobscripts/testing/lin_sep_threaded.sh | 2 +- 3 files changed, 5 insertions(+), 5 deletions(-) diff --git a/experiments/jobscripts/testing/cali.sh b/experiments/jobscripts/testing/cali.sh index da100a68..c8ceb547 100644 --- a/experiments/jobscripts/testing/cali.sh +++ b/experiments/jobscripts/testing/cali.sh @@ -14,4 +14,4 @@ module load openmpi source experiments/slurm_header.sh -srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search n_individuals=10 n_each=nothing threaded > experiments/grid_search_california_housing.log \ No newline at end of file +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search n_individuals=10 n_each=nothing threaded > experiments/logs/grid_search_california_housing.log \ No newline at end of file diff --git a/experiments/jobscripts/testing/lin_sep.sh b/experiments/jobscripts/testing/lin_sep.sh index bce013b3..059daa4c 100644 --- a/experiments/jobscripts/testing/lin_sep.sh +++ b/experiments/jobscripts/testing/lin_sep.sh @@ -2,10 +2,10 @@ #SBATCH --job-name="Grid-search Linearly Separable (ECCCo)" #SBATCH --time=00:30:00 -#SBATCH --ntasks=100 +#SBATCH --ntasks=200 #SBATCH --cpus-per-task=1 #SBATCH --partition=compute -#SBATCH --mem-per-cpu=4GB +#SBATCH --mem-per-cpu=1GB #SBATCH --account=research-eemcs-insy #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. @@ -13,5 +13,5 @@ module load 2023r1 openmpi source experiments/slurm_header.sh -srun julia --project=experiments experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=10 > experiments/grid_search_linearly_separable.log +srun julia --project=experiments experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=20 > experiments/logs/grid_search_linearly_separable.log \ No newline at end of file diff --git a/experiments/jobscripts/testing/lin_sep_threaded.sh b/experiments/jobscripts/testing/lin_sep_threaded.sh index f9ae5381..840c55d6 100644 --- a/experiments/jobscripts/testing/lin_sep_threaded.sh +++ b/experiments/jobscripts/testing/lin_sep_threaded.sh @@ -13,4 +13,4 @@ module load 2023r1 openmpi source experiments/slurm_header.sh -srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=20 threaded > experiments/grid_search_linearly_separable.log +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=20 threaded > experiments/logs/grid_search_linearly_separable_threaded.log From 27cd7d31f31c66042faf77d9b321876649fe2b2b Mon Sep 17 00:00:00 2001 From: pat-alt Date: Tue, 17 Oct 2023 10:03:12 +0200 Subject: [PATCH 056/171] wrong slurm header in cali --- experiments/jobscripts/testing/cali.sh | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/experiments/jobscripts/testing/cali.sh b/experiments/jobscripts/testing/cali.sh index c8ceb547..bc14c1a6 100644 --- a/experiments/jobscripts/testing/cali.sh +++ b/experiments/jobscripts/testing/cali.sh @@ -9,8 +9,7 @@ #SBATCH --account=research-eemcs-insy #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. -module use /opt/insy/modulefiles # Use DAIC INSY software collection -module load openmpi +module load 2023r1 openmpi source experiments/slurm_header.sh From 406a5dbbd452f00e5874532fd7421b8760453224 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Tue, 17 Oct 2023 10:23:39 +0200 Subject: [PATCH 057/171] small changes to testing specs --- experiments/jobscripts/testing/lin_sep.sh | 2 +- experiments/jobscripts/testing/lin_sep_threaded.sh | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/experiments/jobscripts/testing/lin_sep.sh b/experiments/jobscripts/testing/lin_sep.sh index 059daa4c..db9ef9ee 100644 --- a/experiments/jobscripts/testing/lin_sep.sh +++ b/experiments/jobscripts/testing/lin_sep.sh @@ -5,7 +5,7 @@ #SBATCH --ntasks=200 #SBATCH --cpus-per-task=1 #SBATCH --partition=compute -#SBATCH --mem-per-cpu=1GB +#SBATCH --mem-per-cpu=4GB #SBATCH --account=research-eemcs-insy #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. diff --git a/experiments/jobscripts/testing/lin_sep_threaded.sh b/experiments/jobscripts/testing/lin_sep_threaded.sh index 840c55d6..b442f6fe 100644 --- a/experiments/jobscripts/testing/lin_sep_threaded.sh +++ b/experiments/jobscripts/testing/lin_sep_threaded.sh @@ -13,4 +13,4 @@ module load 2023r1 openmpi source experiments/slurm_header.sh -srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=20 threaded > experiments/logs/grid_search_linearly_separable_threaded.log +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=20 threaded n_each=nothing > experiments/logs/grid_search_linearly_separable_threaded.log From 0541c33a7969631d2538992e7ff8e10c5b2352f0 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Tue, 17 Oct 2023 10:29:10 +0200 Subject: [PATCH 058/171] hmm --- experiments/jobscripts/testing/cali.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/experiments/jobscripts/testing/cali.sh b/experiments/jobscripts/testing/cali.sh index bc14c1a6..fbf7eb31 100644 --- a/experiments/jobscripts/testing/cali.sh +++ b/experiments/jobscripts/testing/cali.sh @@ -13,4 +13,4 @@ module load 2023r1 openmpi source experiments/slurm_header.sh -srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search n_individuals=10 n_each=nothing threaded > experiments/logs/grid_search_california_housing.log \ No newline at end of file +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search n_individuals=10 n_each=70 threaded > experiments/logs/grid_search_california_housing.log \ No newline at end of file From 532680b48b104f3ff545be1ef3f9ceb7de8b53ff Mon Sep 17 00:00:00 2001 From: pat-alt Date: Tue, 17 Oct 2023 10:51:42 +0200 Subject: [PATCH 059/171] still unsure about mem --- .../jobscripts/testing/lin_sep_balance.sh | 16 ++++++++++++++++ 1 file changed, 16 insertions(+) create mode 100644 experiments/jobscripts/testing/lin_sep_balance.sh diff --git a/experiments/jobscripts/testing/lin_sep_balance.sh b/experiments/jobscripts/testing/lin_sep_balance.sh new file mode 100644 index 00000000..fce5e920 --- /dev/null +++ b/experiments/jobscripts/testing/lin_sep_balance.sh @@ -0,0 +1,16 @@ +#!/bin/bash + +#SBATCH --job-name="Grid-search Linearly Separable (ECCCo)" +#SBATCH --time=00:30:00 +#SBATCH --ntasks=40 +#SBATCH --cpus-per-task=5 +#SBATCH --partition=compute +#SBATCH --mem-per-cpu=1GB +#SBATCH --account=research-eemcs-insy +#SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. + +module load 2023r1 openmpi + +source experiments/slurm_header.sh + +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=20 threaded n_each=nothing > experiments/logs/grid_search_linearly_separable_threaded.log From b34b100f90d203f897433581f606f7745e81faac Mon Sep 17 00:00:00 2001 From: pat-alt Date: Tue, 17 Oct 2023 11:10:03 +0200 Subject: [PATCH 060/171] still unsure about mem --- experiments/jobscripts/testing/lin_sep_balance.sh | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/experiments/jobscripts/testing/lin_sep_balance.sh b/experiments/jobscripts/testing/lin_sep_balance.sh index fce5e920..e6a03dbf 100644 --- a/experiments/jobscripts/testing/lin_sep_balance.sh +++ b/experiments/jobscripts/testing/lin_sep_balance.sh @@ -1,11 +1,11 @@ #!/bin/bash #SBATCH --job-name="Grid-search Linearly Separable (ECCCo)" -#SBATCH --time=00:30:00 -#SBATCH --ntasks=40 +#SBATCH --time=00:15:00 +#SBATCH --ntasks=80 #SBATCH --cpus-per-task=5 #SBATCH --partition=compute -#SBATCH --mem-per-cpu=1GB +#SBATCH --mem-per-cpu=250MB #SBATCH --account=research-eemcs-insy #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. From b286c4e41ce8b2edcb5c0cf532048f5a072cdbd3 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Tue, 17 Oct 2023 11:15:21 +0200 Subject: [PATCH 061/171] still unsure about mem --- experiments/jobscripts/testing/lin_sep_balance.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/experiments/jobscripts/testing/lin_sep_balance.sh b/experiments/jobscripts/testing/lin_sep_balance.sh index e6a03dbf..fda1c4ed 100644 --- a/experiments/jobscripts/testing/lin_sep_balance.sh +++ b/experiments/jobscripts/testing/lin_sep_balance.sh @@ -5,7 +5,7 @@ #SBATCH --ntasks=80 #SBATCH --cpus-per-task=5 #SBATCH --partition=compute -#SBATCH --mem-per-cpu=250MB +#SBATCH --mem-per-cpu=1GB #SBATCH --account=research-eemcs-insy #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. From d6d7524916008816df029653b7c61a99e3c7f34c Mon Sep 17 00:00:00 2001 From: pat-alt Date: Tue, 17 Oct 2023 11:40:44 +0200 Subject: [PATCH 062/171] scaling up --- experiments/jobscripts/testing/lin_sep.sh | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/experiments/jobscripts/testing/lin_sep.sh b/experiments/jobscripts/testing/lin_sep.sh index db9ef9ee..177d8539 100644 --- a/experiments/jobscripts/testing/lin_sep.sh +++ b/experiments/jobscripts/testing/lin_sep.sh @@ -2,10 +2,10 @@ #SBATCH --job-name="Grid-search Linearly Separable (ECCCo)" #SBATCH --time=00:30:00 -#SBATCH --ntasks=200 -#SBATCH --cpus-per-task=1 +#SBATCH --ntasks=100 +#SBATCH --cpus-per-task=5 #SBATCH --partition=compute -#SBATCH --mem-per-cpu=4GB +#SBATCH --mem-per-cpu=1GB #SBATCH --account=research-eemcs-insy #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. @@ -13,5 +13,5 @@ module load 2023r1 openmpi source experiments/slurm_header.sh -srun julia --project=experiments experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=20 > experiments/logs/grid_search_linearly_separable.log +srun julia --project=experiments experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=50 > experiments/logs/grid_search_linearly_separable.log \ No newline at end of file From f37f5633b22497f9485ebc2a42f71bec90e128ac Mon Sep 17 00:00:00 2001 From: pat-alt Date: Tue, 17 Oct 2023 12:13:00 +0200 Subject: [PATCH 063/171] scaling up --- experiments/jobscripts/testing/lin_sep.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/experiments/jobscripts/testing/lin_sep.sh b/experiments/jobscripts/testing/lin_sep.sh index 177d8539..0d73bc4f 100644 --- a/experiments/jobscripts/testing/lin_sep.sh +++ b/experiments/jobscripts/testing/lin_sep.sh @@ -3,7 +3,7 @@ #SBATCH --job-name="Grid-search Linearly Separable (ECCCo)" #SBATCH --time=00:30:00 #SBATCH --ntasks=100 -#SBATCH --cpus-per-task=5 +#SBATCH --cpus-per-task=10 #SBATCH --partition=compute #SBATCH --mem-per-cpu=1GB #SBATCH --account=research-eemcs-insy From 9435c3f276d790bdc964db8c56bb281ffcc31d5e Mon Sep 17 00:00:00 2001 From: pat-alt Date: Tue, 17 Oct 2023 12:25:12 +0200 Subject: [PATCH 064/171] corrected header --- experiments/jobscripts/testing/lin_sep.sh | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/experiments/jobscripts/testing/lin_sep.sh b/experiments/jobscripts/testing/lin_sep.sh index 0d73bc4f..1150e0f3 100644 --- a/experiments/jobscripts/testing/lin_sep.sh +++ b/experiments/jobscripts/testing/lin_sep.sh @@ -3,7 +3,7 @@ #SBATCH --job-name="Grid-search Linearly Separable (ECCCo)" #SBATCH --time=00:30:00 #SBATCH --ntasks=100 -#SBATCH --cpus-per-task=10 +#SBATCH --cpus-per-task=5 #SBATCH --partition=compute #SBATCH --mem-per-cpu=1GB #SBATCH --account=research-eemcs-insy @@ -13,5 +13,5 @@ module load 2023r1 openmpi source experiments/slurm_header.sh -srun julia --project=experiments experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=50 > experiments/logs/grid_search_linearly_separable.log +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=50 threaded > experiments/logs/grid_search_linearly_separable.log \ No newline at end of file From 66374f4e445a94a20e5ab1428da33fc6f1f8c43d Mon Sep 17 00:00:00 2001 From: pat-alt Date: Tue, 17 Oct 2023 13:00:54 +0200 Subject: [PATCH 065/171] try with neach nothing --- experiments/jobscripts/testing/lin_sep.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/experiments/jobscripts/testing/lin_sep.sh b/experiments/jobscripts/testing/lin_sep.sh index 1150e0f3..53ed526f 100644 --- a/experiments/jobscripts/testing/lin_sep.sh +++ b/experiments/jobscripts/testing/lin_sep.sh @@ -13,5 +13,5 @@ module load 2023r1 openmpi source experiments/slurm_header.sh -srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=50 threaded > experiments/logs/grid_search_linearly_separable.log +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=50 threaded n_each=nothing > experiments/logs/grid_search_linearly_separable.log \ No newline at end of file From c5454dea3c4a39a146c5b5157b55cdf496dd0b7c Mon Sep 17 00:00:00 2001 From: pat-alt Date: Tue, 17 Oct 2023 13:42:09 +0200 Subject: [PATCH 066/171] try with neach nothing --- experiments/jobscripts/testing/lin_sep.sh | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/experiments/jobscripts/testing/lin_sep.sh b/experiments/jobscripts/testing/lin_sep.sh index 53ed526f..693d92a0 100644 --- a/experiments/jobscripts/testing/lin_sep.sh +++ b/experiments/jobscripts/testing/lin_sep.sh @@ -1,11 +1,11 @@ #!/bin/bash #SBATCH --job-name="Grid-search Linearly Separable (ECCCo)" -#SBATCH --time=00:30:00 +#SBATCH --time=00:20:00 #SBATCH --ntasks=100 -#SBATCH --cpus-per-task=5 +#SBATCH --cpus-per-task=10 #SBATCH --partition=compute -#SBATCH --mem-per-cpu=1GB +#SBATCH --mem-per-cpu=2GB #SBATCH --account=research-eemcs-insy #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. From 597cfa028515830193f88168e105eaea3894c622 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Tue, 17 Oct 2023 14:14:10 +0200 Subject: [PATCH 067/171] daic --- experiments/daic/testing/lin_sep.sh | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/experiments/daic/testing/lin_sep.sh b/experiments/daic/testing/lin_sep.sh index 80fee770..b2e8b0c8 100644 --- a/experiments/daic/testing/lin_sep.sh +++ b/experiments/daic/testing/lin_sep.sh @@ -1,11 +1,11 @@ #!/bin/bash #SBATCH --job-name="Grid-search Linearly Separable (ECCCo)" -#SBATCH --time=00:30:00 -#SBATCH --ntasks-per-node=5 -#SBATCH --cpus-per-task=4 +#SBATCH --time=00:20:00 +#SBATCH --ntasks=100 +#SBATCH --cpus-per-task=10 #SBATCH --partition=general -#SBATCH --mem-per-cpu=4GB +#SBATCH --mem-per-cpu=2GB #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. module use /opt/insy/modulefiles # Use DAIC INSY software collection From 058dc606d0f766a330973e7be9ba0e393d5e7a85 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Tue, 17 Oct 2023 14:36:41 +0200 Subject: [PATCH 068/171] trying with smaller specs --- experiments/daic/testing/lin_sep.sh | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/experiments/daic/testing/lin_sep.sh b/experiments/daic/testing/lin_sep.sh index b2e8b0c8..5ade5ba4 100644 --- a/experiments/daic/testing/lin_sep.sh +++ b/experiments/daic/testing/lin_sep.sh @@ -1,9 +1,9 @@ #!/bin/bash #SBATCH --job-name="Grid-search Linearly Separable (ECCCo)" -#SBATCH --time=00:20:00 -#SBATCH --ntasks=100 -#SBATCH --cpus-per-task=10 +#SBATCH --time=00:30:00 +#SBATCH --ntasks=10 +#SBATCH --cpus-per-task=5 #SBATCH --partition=general #SBATCH --mem-per-cpu=2GB #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. From eae89977a7abf9a051b40cd24f20777f6df00871 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Tue, 17 Oct 2023 14:42:41 +0200 Subject: [PATCH 069/171] delftblue --- experiments/jobscripts/testing/lin_sep.sh | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/experiments/jobscripts/testing/lin_sep.sh b/experiments/jobscripts/testing/lin_sep.sh index 693d92a0..b6306832 100644 --- a/experiments/jobscripts/testing/lin_sep.sh +++ b/experiments/jobscripts/testing/lin_sep.sh @@ -1,7 +1,7 @@ #!/bin/bash #SBATCH --job-name="Grid-search Linearly Separable (ECCCo)" -#SBATCH --time=00:20:00 +#SBATCH --time=00:30:00 #SBATCH --ntasks=100 #SBATCH --cpus-per-task=10 #SBATCH --partition=compute @@ -13,5 +13,5 @@ module load 2023r1 openmpi source experiments/slurm_header.sh -srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=50 threaded n_each=nothing > experiments/logs/grid_search_linearly_separable.log +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi grid_search n_individuals=100 threaded n_each=nothing > experiments/logs/grid_search_linearly_separable.log \ No newline at end of file From 92f9ae7dac1d7f7dee4835a5268a65e61798e9e8 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Tue, 17 Oct 2023 14:58:38 +0200 Subject: [PATCH 070/171] delftblue jobs --- .../jobscripts/tuning/generators/california_housing.sh | 4 ++-- experiments/jobscripts/tuning/generators/circles.sh | 8 ++++---- experiments/jobscripts/tuning/generators/german_credit.sh | 8 ++++---- experiments/jobscripts/tuning/generators/gmsc.sh | 6 +++--- .../jobscripts/tuning/generators/linearly_separable.sh | 8 ++++---- experiments/jobscripts/tuning/generators/moons.sh | 8 ++++---- 6 files changed, 21 insertions(+), 21 deletions(-) diff --git a/experiments/jobscripts/tuning/generators/california_housing.sh b/experiments/jobscripts/tuning/generators/california_housing.sh index be1e47ff..80d8f732 100644 --- a/experiments/jobscripts/tuning/generators/california_housing.sh +++ b/experiments/jobscripts/tuning/generators/california_housing.sh @@ -2,8 +2,8 @@ #SBATCH --job-name="Grid-search California Housing (ECCCo)" #SBATCH --time=01:00:00 -#SBATCH --ntasks=20 -#SBATCH --cpus-per-task=20 +#SBATCH --ntasks=50 +#SBATCH --cpus-per-task=8 #SBATCH --partition=compute #SBATCH --mem-per-cpu=4GB #SBATCH --account=research-eemcs-insy diff --git a/experiments/jobscripts/tuning/generators/circles.sh b/experiments/jobscripts/tuning/generators/circles.sh index f9bc0129..be4490b2 100644 --- a/experiments/jobscripts/tuning/generators/circles.sh +++ b/experiments/jobscripts/tuning/generators/circles.sh @@ -1,11 +1,11 @@ #!/bin/bash #SBATCH --job-name="Grid-search Circles (ECCCo)" -#SBATCH --time=01:00:00 -#SBATCH --ntasks=30 -#SBATCH --cpus-per-task=30 +#SBATCH --time=00:45:00 +#SBATCH --ntasks=100 +#SBATCH --cpus-per-task=10 #SBATCH --partition=compute -#SBATCH --mem-per-cpu=1GB +#SBATCH --mem-per-cpu=2GB #SBATCH --account=research-eemcs-insy #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. diff --git a/experiments/jobscripts/tuning/generators/german_credit.sh b/experiments/jobscripts/tuning/generators/german_credit.sh index 263ac1bd..e93a579f 100644 --- a/experiments/jobscripts/tuning/generators/german_credit.sh +++ b/experiments/jobscripts/tuning/generators/german_credit.sh @@ -1,11 +1,11 @@ #!/bin/bash #SBATCH --job-name="Grid-search German Credit (ECCCo)" -#SBATCH --time=01:00:00 -#SBATCH --ntasks=30 -#SBATCH --cpus-per-task=30 +#SBATCH --time=00:45:00 +#SBATCH --ntasks=100 +#SBATCH --cpus-per-task=10 #SBATCH --partition=compute -#SBATCH --mem-per-cpu=1GB +#SBATCH --mem-per-cpu=2GB #SBATCH --account=research-eemcs-insy #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. diff --git a/experiments/jobscripts/tuning/generators/gmsc.sh b/experiments/jobscripts/tuning/generators/gmsc.sh index 729fa36e..1e4fad5a 100644 --- a/experiments/jobscripts/tuning/generators/gmsc.sh +++ b/experiments/jobscripts/tuning/generators/gmsc.sh @@ -2,10 +2,10 @@ #SBATCH --job-name="Grid-search GMSC (ECCCo)" #SBATCH --time=01:00:00 -#SBATCH --ntasks=20 -#SBATCH --cpus-per-task=20 +#SBATCH --ntasks=50 +#SBATCH --cpus-per-task=8 #SBATCH --partition=compute -#SBATCH --mem-per-cpu=2GB +#SBATCH --mem-per-cpu=4GB #SBATCH --account=research-eemcs-insy #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. diff --git a/experiments/jobscripts/tuning/generators/linearly_separable.sh b/experiments/jobscripts/tuning/generators/linearly_separable.sh index fca9ee05..6e572851 100644 --- a/experiments/jobscripts/tuning/generators/linearly_separable.sh +++ b/experiments/jobscripts/tuning/generators/linearly_separable.sh @@ -1,11 +1,11 @@ #!/bin/bash #SBATCH --job-name="Grid-search Linearly Separable (ECCCo)" -#SBATCH --time=01:00:00 -#SBATCH --ntasks=30 -#SBATCH --cpus-per-task=30 +#SBATCH --time=00:45:00 +#SBATCH --ntasks=100 +#SBATCH --cpus-per-task=10 #SBATCH --partition=compute -#SBATCH --mem-per-cpu=1GB +#SBATCH --mem-per-cpu=2GB #SBATCH --account=research-eemcs-insy #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. diff --git a/experiments/jobscripts/tuning/generators/moons.sh b/experiments/jobscripts/tuning/generators/moons.sh index 8d81d33a..713f1c24 100644 --- a/experiments/jobscripts/tuning/generators/moons.sh +++ b/experiments/jobscripts/tuning/generators/moons.sh @@ -1,11 +1,11 @@ #!/bin/bash #SBATCH --job-name="Grid-search Moons (ECCCo)" -#SBATCH --time=01:00:00 -#SBATCH --ntasks=30 -#SBATCH --cpus-per-task=30 +#SBATCH --time=00:45:00 +#SBATCH --ntasks=100 +#SBATCH --cpus-per-task=10 #SBATCH --partition=compute -#SBATCH --mem-per-cpu=1GB +#SBATCH --mem-per-cpu=2GB #SBATCH --account=research-eemcs-insy #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. From b597c48a4f7d6910156c7520525d5d77471035f0 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Tue, 17 Oct 2023 15:00:24 +0200 Subject: [PATCH 071/171] tabular --- experiments/jobscripts/tuning/generators/california_housing.sh | 2 +- experiments/jobscripts/tuning/generators/german_credit.sh | 2 +- experiments/jobscripts/tuning/generators/gmsc.sh | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/experiments/jobscripts/tuning/generators/california_housing.sh b/experiments/jobscripts/tuning/generators/california_housing.sh index 80d8f732..9b744059 100644 --- a/experiments/jobscripts/tuning/generators/california_housing.sh +++ b/experiments/jobscripts/tuning/generators/california_housing.sh @@ -13,4 +13,4 @@ module load 2023r1 openmpi source experiments/slurm_header.sh -srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search threaded n_individuals=10 > experiments/logs/grid_search_california_housing.log +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search threaded n_individuals=25 > experiments/logs/grid_search_california_housing.log diff --git a/experiments/jobscripts/tuning/generators/german_credit.sh b/experiments/jobscripts/tuning/generators/german_credit.sh index e93a579f..03cdd9d4 100644 --- a/experiments/jobscripts/tuning/generators/german_credit.sh +++ b/experiments/jobscripts/tuning/generators/german_credit.sh @@ -13,4 +13,4 @@ module load 2023r1 openmpi source experiments/slurm_header.sh -srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=german_credit output_path=results mpi grid_search threaded n_individuals=100 > experiments/logs/grid_search_german_credit.log +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=german_credit output_path=results mpi grid_search threaded n_individuals=25 > experiments/logs/grid_search_german_credit.log diff --git a/experiments/jobscripts/tuning/generators/gmsc.sh b/experiments/jobscripts/tuning/generators/gmsc.sh index 1e4fad5a..09eca16a 100644 --- a/experiments/jobscripts/tuning/generators/gmsc.sh +++ b/experiments/jobscripts/tuning/generators/gmsc.sh @@ -13,4 +13,4 @@ module load 2023r1 openmpi source experiments/slurm_header.sh -srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=gmsc output_path=results mpi grid_search threaded n_individuals=10 > experiments/logs/grid_search_gmsc.log +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=gmsc output_path=results mpi grid_search threaded n_individuals=25 > experiments/logs/grid_search_gmsc.log From fb106c0a3f978a0d59b49a2c54edfbea92094d0e Mon Sep 17 00:00:00 2001 From: pat-alt Date: Tue, 17 Oct 2023 15:18:33 +0200 Subject: [PATCH 072/171] final changes to delftblue tuning scripts --- experiments/jobscripts/tuning/generators/circles.sh | 2 +- experiments/jobscripts/tuning/generators/linearly_separable.sh | 2 +- experiments/jobscripts/tuning/generators/moons.sh | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/experiments/jobscripts/tuning/generators/circles.sh b/experiments/jobscripts/tuning/generators/circles.sh index be4490b2..fbce9822 100644 --- a/experiments/jobscripts/tuning/generators/circles.sh +++ b/experiments/jobscripts/tuning/generators/circles.sh @@ -1,7 +1,7 @@ #!/bin/bash #SBATCH --job-name="Grid-search Circles (ECCCo)" -#SBATCH --time=00:45:00 +#SBATCH --time=00:35:00 #SBATCH --ntasks=100 #SBATCH --cpus-per-task=10 #SBATCH --partition=compute diff --git a/experiments/jobscripts/tuning/generators/linearly_separable.sh b/experiments/jobscripts/tuning/generators/linearly_separable.sh index 6e572851..473a96b4 100644 --- a/experiments/jobscripts/tuning/generators/linearly_separable.sh +++ b/experiments/jobscripts/tuning/generators/linearly_separable.sh @@ -1,7 +1,7 @@ #!/bin/bash #SBATCH --job-name="Grid-search Linearly Separable (ECCCo)" -#SBATCH --time=00:45:00 +#SBATCH --time=00:35:00 #SBATCH --ntasks=100 #SBATCH --cpus-per-task=10 #SBATCH --partition=compute diff --git a/experiments/jobscripts/tuning/generators/moons.sh b/experiments/jobscripts/tuning/generators/moons.sh index 713f1c24..aca159d6 100644 --- a/experiments/jobscripts/tuning/generators/moons.sh +++ b/experiments/jobscripts/tuning/generators/moons.sh @@ -1,7 +1,7 @@ #!/bin/bash #SBATCH --job-name="Grid-search Moons (ECCCo)" -#SBATCH --time=00:45:00 +#SBATCH --time=00:35:00 #SBATCH --ntasks=100 #SBATCH --cpus-per-task=10 #SBATCH --partition=compute From 0880ed7f98d711102bde17211a54f364872c1c02 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Wed, 18 Oct 2023 09:05:06 +0200 Subject: [PATCH 073/171] upgraded specs for tabular --- experiments/grid_search.jl | 2 +- .../jobscripts/tuning/generators/california_housing.sh | 8 ++++---- experiments/jobscripts/tuning/generators/german_credit.sh | 2 +- experiments/jobscripts/tuning/generators/gmsc.sh | 8 ++++---- 4 files changed, 10 insertions(+), 10 deletions(-) diff --git a/experiments/grid_search.jl b/experiments/grid_search.jl index a648675c..cedef8fd 100644 --- a/experiments/grid_search.jl +++ b/experiments/grid_search.jl @@ -193,7 +193,7 @@ function best_absolute_outcome( model_dict = outcome.model_dict # Discard outlier results: - if any(evaluation.value .> 1e6) + if any(abs(evaluation.value) .> 1e6) @warn "Discarding outlier results: $(params)." push!(avg_values, Inf) continue diff --git a/experiments/jobscripts/tuning/generators/california_housing.sh b/experiments/jobscripts/tuning/generators/california_housing.sh index 9b744059..607635f3 100644 --- a/experiments/jobscripts/tuning/generators/california_housing.sh +++ b/experiments/jobscripts/tuning/generators/california_housing.sh @@ -1,9 +1,9 @@ #!/bin/bash #SBATCH --job-name="Grid-search California Housing (ECCCo)" -#SBATCH --time=01:00:00 -#SBATCH --ntasks=50 -#SBATCH --cpus-per-task=8 +#SBATCH --time=01:10:00 +#SBATCH --ntasks=100 +#SBATCH --cpus-per-task=10 #SBATCH --partition=compute #SBATCH --mem-per-cpu=4GB #SBATCH --account=research-eemcs-insy @@ -13,4 +13,4 @@ module load 2023r1 openmpi source experiments/slurm_header.sh -srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search threaded n_individuals=25 > experiments/logs/grid_search_california_housing.log +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search threaded n_individuals=100 > experiments/logs/grid_search_california_housing.log diff --git a/experiments/jobscripts/tuning/generators/german_credit.sh b/experiments/jobscripts/tuning/generators/german_credit.sh index 03cdd9d4..e93a579f 100644 --- a/experiments/jobscripts/tuning/generators/german_credit.sh +++ b/experiments/jobscripts/tuning/generators/german_credit.sh @@ -13,4 +13,4 @@ module load 2023r1 openmpi source experiments/slurm_header.sh -srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=german_credit output_path=results mpi grid_search threaded n_individuals=25 > experiments/logs/grid_search_german_credit.log +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=german_credit output_path=results mpi grid_search threaded n_individuals=100 > experiments/logs/grid_search_german_credit.log diff --git a/experiments/jobscripts/tuning/generators/gmsc.sh b/experiments/jobscripts/tuning/generators/gmsc.sh index 09eca16a..e7a8a982 100644 --- a/experiments/jobscripts/tuning/generators/gmsc.sh +++ b/experiments/jobscripts/tuning/generators/gmsc.sh @@ -1,9 +1,9 @@ #!/bin/bash #SBATCH --job-name="Grid-search GMSC (ECCCo)" -#SBATCH --time=01:00:00 -#SBATCH --ntasks=50 -#SBATCH --cpus-per-task=8 +#SBATCH --time=01:10:00 +#SBATCH --ntasks=100 +#SBATCH --cpus-per-task=10 #SBATCH --partition=compute #SBATCH --mem-per-cpu=4GB #SBATCH --account=research-eemcs-insy @@ -13,4 +13,4 @@ module load 2023r1 openmpi source experiments/slurm_header.sh -srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=gmsc output_path=results mpi grid_search threaded n_individuals=25 > experiments/logs/grid_search_gmsc.log +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=gmsc output_path=results mpi grid_search threaded n_individuals=100 > experiments/logs/grid_search_gmsc.log From ca5441dc41e03a133285728747cbf17d36eb8851 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Wed, 18 Oct 2023 09:14:30 +0200 Subject: [PATCH 074/171] fixed bug --- experiments/grid_search.jl | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/experiments/grid_search.jl b/experiments/grid_search.jl index cedef8fd..7243b334 100644 --- a/experiments/grid_search.jl +++ b/experiments/grid_search.jl @@ -193,7 +193,7 @@ function best_absolute_outcome( model_dict = outcome.model_dict # Discard outlier results: - if any(abs(evaluation.value) .> 1e6) + if any(abs.(evaluation.value) .> 1e6) @warn "Discarding outlier results: $(params)." push!(avg_values, Inf) continue From 0b75be126a114c569d73b5343047b0f3afa1c7b5 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Wed, 18 Oct 2023 09:57:07 +0200 Subject: [PATCH 075/171] nindivudals arg was overwritten for tabular data --- experiments/grid_search.jl | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/experiments/grid_search.jl b/experiments/grid_search.jl index 7243b334..c11e28f0 100644 --- a/experiments/grid_search.jl +++ b/experiments/grid_search.jl @@ -39,12 +39,12 @@ function grid_search( outcome = run_experiment( counterfactual_data, test_data; - save_output = false, - dataname = dataname, - n_individuals = n_individuals, - output_path = grid_search_path, params..., kwargs..., + save_output=false, + dataname=dataname, + n_individuals=n_individuals, + output_path=grid_search_path ) params = map(x -> typeof(x[2]) <: Vector ? x[1] => Tuple(x[2]) : x[1] => x[2], params) From 0b78c79266655cfda461b25bd6f77989245428de Mon Sep 17 00:00:00 2001 From: pat-alt Date: Wed, 18 Oct 2023 10:39:57 +0200 Subject: [PATCH 076/171] let's try this again then --- experiments/california_housing.jl | 1 - experiments/german_credit.jl | 1 - experiments/gmsc.jl | 1 - experiments/grid_search.jl | 16 ++++++++++++---- 4 files changed, 12 insertions(+), 7 deletions(-) diff --git a/experiments/california_housing.jl b/experiments/california_housing.jl index 40f2f8a9..99e598a9 100644 --- a/experiments/california_housing.jl +++ b/experiments/california_housing.jl @@ -40,7 +40,6 @@ params = ( opt = Flux.Optimise.Descent(0.05), Λ = [0.1, 0.1, 0.1], reg_strength = 0.0, - n_individuals = 25, dim_reduction = true, ) diff --git a/experiments/german_credit.jl b/experiments/german_credit.jl index 2095cbc9..082567b2 100644 --- a/experiments/german_credit.jl +++ b/experiments/german_credit.jl @@ -40,7 +40,6 @@ params = ( opt = Flux.Optimise.Descent(0.05), Λ = [0.2, 0.2, 0.2], reg_strength = 0.5, - n_individuals = 25, dim_reduction = true, ) diff --git a/experiments/gmsc.jl b/experiments/gmsc.jl index bb2cdee8..3c55d0a5 100644 --- a/experiments/gmsc.jl +++ b/experiments/gmsc.jl @@ -40,7 +40,6 @@ params = ( opt = Flux.Optimise.Descent(0.05), Λ = [0.1, 0.1, 0.1], reg_strength = 0.0, - n_individuals = 25, dim_reduction = true, ) diff --git a/experiments/grid_search.jl b/experiments/grid_search.jl index c11e28f0..5af59dd6 100644 --- a/experiments/grid_search.jl +++ b/experiments/grid_search.jl @@ -36,17 +36,25 @@ function grid_search( counter = 1 for params in grid @info "Running experiment $(counter)/$(length(grid)) with tuning parameters: $(params)" + + # Filter out keyword parameters that are tuned: + not_these = keys(kwargs)[findall([k in map(k -> k[1], params) for k in keys(kwargs)])] + not_these = (not_these..., :n_individuals) + kwargs = filter(x -> !(x[1] ∈ not_these), Base.Pairs(params, keys(kwargs))) + + # Run experiment: outcome = run_experiment( counterfactual_data, test_data; + save_output = false, + dataname = dataname, + n_individuals = n_individuals, + output_path = grid_search_path, params..., kwargs..., - save_output=false, - dataname=dataname, - n_individuals=n_individuals, - output_path=grid_search_path ) + # Collect: params = map(x -> typeof(x[2]) <: Vector ? x[1] => Tuple(x[2]) : x[1] => x[2], params) df_params = DataFrame(merge(Dict(:id => counter), Dict(params))) |> From 5884a5ada260c8d5ba2fb7754e5aad116cb3b8d9 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Wed, 18 Oct 2023 10:41:24 +0200 Subject: [PATCH 077/171] moons --- experiments/jobscripts/tuning/generators/moons.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/experiments/jobscripts/tuning/generators/moons.sh b/experiments/jobscripts/tuning/generators/moons.sh index aca159d6..713f1c24 100644 --- a/experiments/jobscripts/tuning/generators/moons.sh +++ b/experiments/jobscripts/tuning/generators/moons.sh @@ -1,7 +1,7 @@ #!/bin/bash #SBATCH --job-name="Grid-search Moons (ECCCo)" -#SBATCH --time=00:35:00 +#SBATCH --time=00:45:00 #SBATCH --ntasks=100 #SBATCH --cpus-per-task=10 #SBATCH --partition=compute From 11d7a8a96a7c6537658baba598ce6fe048fe6c52 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Wed, 18 Oct 2023 10:46:25 +0200 Subject: [PATCH 078/171] final script for lin sep --- .../jobscripts/generators/linearly_separable.sh | 16 ++++++++++++++++ .../jobscripts/generators/mnist_memory.sh | 14 -------------- experiments/jobscripts/generators/tabular.sh | 14 -------------- 3 files changed, 16 insertions(+), 28 deletions(-) create mode 100644 experiments/jobscripts/generators/linearly_separable.sh delete mode 100644 experiments/jobscripts/generators/mnist_memory.sh delete mode 100644 experiments/jobscripts/generators/tabular.sh diff --git a/experiments/jobscripts/generators/linearly_separable.sh b/experiments/jobscripts/generators/linearly_separable.sh new file mode 100644 index 00000000..419fcde0 --- /dev/null +++ b/experiments/jobscripts/generators/linearly_separable.sh @@ -0,0 +1,16 @@ +#!/bin/bash + +#SBATCH --job-name="Linearly Separable (ECCCo)" +#SBATCH --time=00:35:00 +#SBATCH --ntasks=10 +#SBATCH --cpus-per-task=10 +#SBATCH --partition=compute +#SBATCH --mem-per-cpu=2GB +#SBATCH --account=research-eemcs-insy +#SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. + +module load 2023r1 openmpi + +source experiments/slurm_header.sh + +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=linearly_separable output_path=results mpi threaded n_individuals=100 n_runs=5 > experiments/logs/linearly_separable.log diff --git a/experiments/jobscripts/generators/mnist_memory.sh b/experiments/jobscripts/generators/mnist_memory.sh deleted file mode 100644 index 0f653aeb..00000000 --- a/experiments/jobscripts/generators/mnist_memory.sh +++ /dev/null @@ -1,14 +0,0 @@ -#!/bin/bash - -#SBATCH --job-name="MNIST (ECCCo)" -#SBATCH --time=10:00:00 -#SBATCH --ntasks=150 -#SBATCH --cpus-per-task=1 -#SBATCH --partition=memory -#SBATCH --mem-per-cpu=64GB -#SBATCH --account=research-eemcs-insy -#SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. - -module load 2023r1 openmpi - -srun julia --project=experiments experiments/run_experiments.jl -- data=mnist output_path=results mpi > experiments/mnist.log diff --git a/experiments/jobscripts/generators/tabular.sh b/experiments/jobscripts/generators/tabular.sh deleted file mode 100644 index 43b43b6f..00000000 --- a/experiments/jobscripts/generators/tabular.sh +++ /dev/null @@ -1,14 +0,0 @@ -#!/bin/bash - -#SBATCH --job-name="Tabular (ECCCo)" -#SBATCH --time=12:00:00 -#SBATCH --ntasks=1000 -#SBATCH --cpus-per-task=1 -#SBATCH --partition=compute -#SBATCH --mem-per-cpu=8GB -#SBATCH --account=research-eemcs-insy -#SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. - -module load 2023r1 openmpi - -srun julia --project=experiments experiments/run_experiments.jl -- data=gmsc,german_credit,california_housing output_path=results mpi > experiments/tabular.log From a93fd72470a59d4a66212285765cbe2a1e9b723c Mon Sep 17 00:00:00 2001 From: pat-alt Date: Wed, 18 Oct 2023 11:26:23 +0200 Subject: [PATCH 079/171] trying lower specs, longer time --- .../jobscripts/tuning/generators/linearly_separable.sh | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/experiments/jobscripts/tuning/generators/linearly_separable.sh b/experiments/jobscripts/tuning/generators/linearly_separable.sh index 473a96b4..ed83ba27 100644 --- a/experiments/jobscripts/tuning/generators/linearly_separable.sh +++ b/experiments/jobscripts/tuning/generators/linearly_separable.sh @@ -1,8 +1,8 @@ #!/bin/bash #SBATCH --job-name="Grid-search Linearly Separable (ECCCo)" -#SBATCH --time=00:35:00 -#SBATCH --ntasks=100 +#SBATCH --time=01:00:00 +#SBATCH --ntasks=10 #SBATCH --cpus-per-task=10 #SBATCH --partition=compute #SBATCH --mem-per-cpu=2GB From bbbdcec83573cd0e100618e613d3281d2fa5f674 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Wed, 18 Oct 2023 11:28:29 +0200 Subject: [PATCH 080/171] trying daic --- experiments/daic/tuning/generators/linearly_separable.sh | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/experiments/daic/tuning/generators/linearly_separable.sh b/experiments/daic/tuning/generators/linearly_separable.sh index 27f4a81a..e2ed9d44 100644 --- a/experiments/daic/tuning/generators/linearly_separable.sh +++ b/experiments/daic/tuning/generators/linearly_separable.sh @@ -2,10 +2,10 @@ #SBATCH --job-name="Grid-search Linearly Separable (ECCCo)" #SBATCH --time=01:00:00 -#SBATCH --ntasks=30 -#SBATCH --cpus-per-task=30 +#SBATCH --ntasks=10 +#SBATCH --cpus-per-task=10 #SBATCH --partition=general -#SBATCH --mem-per-cpu=1GB +#SBATCH --mem-per-cpu=2GB #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. module use /opt/insy/modulefiles # Use DAIC INSY software collection From be8b63d9c9dbaa38430b093b62490458f6f090dc Mon Sep 17 00:00:00 2001 From: pat-alt Date: Wed, 18 Oct 2023 11:46:50 +0200 Subject: [PATCH 081/171] fixed bug --- experiments/grid_search.jl | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/experiments/grid_search.jl b/experiments/grid_search.jl index 5af59dd6..d5d2455c 100644 --- a/experiments/grid_search.jl +++ b/experiments/grid_search.jl @@ -40,7 +40,7 @@ function grid_search( # Filter out keyword parameters that are tuned: not_these = keys(kwargs)[findall([k in map(k -> k[1], params) for k in keys(kwargs)])] not_these = (not_these..., :n_individuals) - kwargs = filter(x -> !(x[1] ∈ not_these), Base.Pairs(params, keys(kwargs))) + kwargs = filter(x -> !(x[1] ∈ not_these), kwargs) # Run experiment: outcome = run_experiment( From b92f9a26bbcecb565487540814cbcea43cecde97 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Wed, 18 Oct 2023 12:32:32 +0200 Subject: [PATCH 082/171] error accessing learning rate of composed optimisers --- experiments/benchmarking/benchmarking.jl | 2 +- experiments/grid_search.jl | 3 ++- experiments/post_processing/meta_data.jl | 2 +- experiments/utils.jl | 13 +++++++++++++ 4 files changed, 17 insertions(+), 3 deletions(-) diff --git a/experiments/benchmarking/benchmarking.jl b/experiments/benchmarking/benchmarking.jl index f07bd6db..c3bacbce 100644 --- a/experiments/benchmarking/benchmarking.jl +++ b/experiments/benchmarking/benchmarking.jl @@ -20,7 +20,7 @@ function default_generators(; generator_dict = Dict( "Wachter" => WachterGenerator(λ = λ₁, opt = opt), "REVISE" => REVISEGenerator(λ = λ₁, opt = opt), - "Schut" => GreedyGenerator(η = opt.eta), + "Schut" => GreedyGenerator(η=get_learning_rate(opt)), "ECCCo" => ECCCoGenerator( λ = Λ, opt = opt, diff --git a/experiments/grid_search.jl b/experiments/grid_search.jl index d5d2455c..36904a08 100644 --- a/experiments/grid_search.jl +++ b/experiments/grid_search.jl @@ -38,7 +38,8 @@ function grid_search( @info "Running experiment $(counter)/$(length(grid)) with tuning parameters: $(params)" # Filter out keyword parameters that are tuned: - not_these = keys(kwargs)[findall([k in map(k -> k[1], params) for k in keys(kwargs)])] + _keys = [k[1] for k in kwargs] + not_these = _keys[findall([k in map(k -> k[1], params) for k in _keys])] not_these = (not_these..., :n_individuals) kwargs = filter(x -> !(x[1] ∈ not_these), kwargs) diff --git a/experiments/post_processing/meta_data.jl b/experiments/post_processing/meta_data.jl index ab4c982a..0acd94c3 100644 --- a/experiments/post_processing/meta_data.jl +++ b/experiments/post_processing/meta_data.jl @@ -83,7 +83,7 @@ function meta_generators( generator_params = DataFrame( Dict( :opt => string(typeof(opt)), - :eta => opt.eta, + :eta => get_learning_rate(opt), :dataname => exper.dataname, :lambda_1 => string(Λ[1]), :lambda_2 => string(Λ[2]), diff --git a/experiments/utils.jl b/experiments/utils.jl index 2f9b6845..be94743d 100644 --- a/experiments/utils.jl +++ b/experiments/utils.jl @@ -1,4 +1,5 @@ using CounterfactualExplanations.Parallelization: ThreadsParallelizer +using Flux using LinearAlgebra: norm function is_multi_processed(parallelizer::Union{Nothing,AbstractParallelizer}) @@ -25,3 +26,15 @@ function standardize(x::AbstractArray) x_norm = replace(x_norm, NaN => 0.0) return x_norm end + +function get_learning_rate(opt::Flux.Optimise.AbstractOptimiser) + if hasfield(typeof(opt), :eta) + return opt.eta + elseif hasfield(typeof(opt), :os) + _os = opt.os + opt = _os[findall([:eta in fieldnames(typeof(o)) for o in _os])][1] + return opt.eta + else + throw(ArgumentError("Cannot find learning rate.")) + end +end \ No newline at end of file From 9e20c62d6297b7d2f9c248ff0e88725aaf3f07e0 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Wed, 18 Oct 2023 12:55:51 +0200 Subject: [PATCH 083/171] trying delft blue smaller specs again --- .../jobscripts/tuning/generators/california_housing.sh | 4 ++-- experiments/jobscripts/tuning/generators/circles.sh | 4 ++-- experiments/jobscripts/tuning/generators/gmsc.sh | 2 +- .../jobscripts/tuning/generators/linearly_separable.sh | 2 +- experiments/jobscripts/tuning/generators/moons.sh | 4 ++-- 5 files changed, 8 insertions(+), 8 deletions(-) diff --git a/experiments/jobscripts/tuning/generators/california_housing.sh b/experiments/jobscripts/tuning/generators/california_housing.sh index 607635f3..2677be0f 100644 --- a/experiments/jobscripts/tuning/generators/california_housing.sh +++ b/experiments/jobscripts/tuning/generators/california_housing.sh @@ -1,8 +1,8 @@ #!/bin/bash #SBATCH --job-name="Grid-search California Housing (ECCCo)" -#SBATCH --time=01:10:00 -#SBATCH --ntasks=100 +#SBATCH --time=02:00:00 +#SBATCH --ntasks=20 #SBATCH --cpus-per-task=10 #SBATCH --partition=compute #SBATCH --mem-per-cpu=4GB diff --git a/experiments/jobscripts/tuning/generators/circles.sh b/experiments/jobscripts/tuning/generators/circles.sh index fbce9822..452d4ca1 100644 --- a/experiments/jobscripts/tuning/generators/circles.sh +++ b/experiments/jobscripts/tuning/generators/circles.sh @@ -1,8 +1,8 @@ #!/bin/bash #SBATCH --job-name="Grid-search Circles (ECCCo)" -#SBATCH --time=00:35:00 -#SBATCH --ntasks=100 +#SBATCH --time=01:00:00 +#SBATCH --ntasks=15 #SBATCH --cpus-per-task=10 #SBATCH --partition=compute #SBATCH --mem-per-cpu=2GB diff --git a/experiments/jobscripts/tuning/generators/gmsc.sh b/experiments/jobscripts/tuning/generators/gmsc.sh index e7a8a982..7ce31e31 100644 --- a/experiments/jobscripts/tuning/generators/gmsc.sh +++ b/experiments/jobscripts/tuning/generators/gmsc.sh @@ -2,7 +2,7 @@ #SBATCH --job-name="Grid-search GMSC (ECCCo)" #SBATCH --time=01:10:00 -#SBATCH --ntasks=100 +#SBATCH --ntasks=15 #SBATCH --cpus-per-task=10 #SBATCH --partition=compute #SBATCH --mem-per-cpu=4GB diff --git a/experiments/jobscripts/tuning/generators/linearly_separable.sh b/experiments/jobscripts/tuning/generators/linearly_separable.sh index ed83ba27..562e1e28 100644 --- a/experiments/jobscripts/tuning/generators/linearly_separable.sh +++ b/experiments/jobscripts/tuning/generators/linearly_separable.sh @@ -2,7 +2,7 @@ #SBATCH --job-name="Grid-search Linearly Separable (ECCCo)" #SBATCH --time=01:00:00 -#SBATCH --ntasks=10 +#SBATCH --ntasks=15 #SBATCH --cpus-per-task=10 #SBATCH --partition=compute #SBATCH --mem-per-cpu=2GB diff --git a/experiments/jobscripts/tuning/generators/moons.sh b/experiments/jobscripts/tuning/generators/moons.sh index 713f1c24..f6fb460d 100644 --- a/experiments/jobscripts/tuning/generators/moons.sh +++ b/experiments/jobscripts/tuning/generators/moons.sh @@ -1,8 +1,8 @@ #!/bin/bash #SBATCH --job-name="Grid-search Moons (ECCCo)" -#SBATCH --time=00:45:00 -#SBATCH --ntasks=100 +#SBATCH --time=01:00:00 +#SBATCH --ntasks=15 #SBATCH --cpus-per-task=10 #SBATCH --partition=compute #SBATCH --mem-per-cpu=2GB From 137d3143abb61351eb7f21b9c97f63fcc9b6413a Mon Sep 17 00:00:00 2001 From: pat-alt Date: Wed, 18 Oct 2023 12:56:45 +0200 Subject: [PATCH 084/171] let's see --- experiments/jobscripts/tuning/generators/gmsc.sh | 2 +- experiments/jobscripts/tuning/generators/moons.sh | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/experiments/jobscripts/tuning/generators/gmsc.sh b/experiments/jobscripts/tuning/generators/gmsc.sh index 7ce31e31..8b407ff7 100644 --- a/experiments/jobscripts/tuning/generators/gmsc.sh +++ b/experiments/jobscripts/tuning/generators/gmsc.sh @@ -1,7 +1,7 @@ #!/bin/bash #SBATCH --job-name="Grid-search GMSC (ECCCo)" -#SBATCH --time=01:10:00 +#SBATCH --time=01:30:00 #SBATCH --ntasks=15 #SBATCH --cpus-per-task=10 #SBATCH --partition=compute diff --git a/experiments/jobscripts/tuning/generators/moons.sh b/experiments/jobscripts/tuning/generators/moons.sh index f6fb460d..eabcb86a 100644 --- a/experiments/jobscripts/tuning/generators/moons.sh +++ b/experiments/jobscripts/tuning/generators/moons.sh @@ -1,7 +1,7 @@ #!/bin/bash #SBATCH --job-name="Grid-search Moons (ECCCo)" -#SBATCH --time=01:00:00 +#SBATCH --time=01:30:00 #SBATCH --ntasks=15 #SBATCH --cpus-per-task=10 #SBATCH --partition=compute From 6f7efea5f69bb042c1b1dc6cdeaf130d9c5a513d Mon Sep 17 00:00:00 2001 From: pat-alt Date: Wed, 18 Oct 2023 13:02:09 +0200 Subject: [PATCH 085/171] daic --- .../daic/tuning/generators/california_housing.sh | 10 +++++----- experiments/daic/tuning/generators/circles.sh | 6 +++--- experiments/daic/tuning/generators/german_credit.sh | 6 +++--- experiments/daic/tuning/generators/gmsc.sh | 8 ++++---- .../daic/tuning/generators/linearly_separable.sh | 2 +- experiments/daic/tuning/generators/moons.sh | 8 ++++---- 6 files changed, 20 insertions(+), 20 deletions(-) diff --git a/experiments/daic/tuning/generators/california_housing.sh b/experiments/daic/tuning/generators/california_housing.sh index 3bd54dbf..7a6b5df0 100644 --- a/experiments/daic/tuning/generators/california_housing.sh +++ b/experiments/daic/tuning/generators/california_housing.sh @@ -1,11 +1,11 @@ #!/bin/bash #SBATCH --job-name="Grid-search California Housing (ECCCo)" -#SBATCH --time=01:00:00 -#SBATCH --ntasks=20 -#SBATCH --cpus-per-task=20 +#SBATCH --time=02:00:00 +#SBATCH --ntasks=30 +#SBATCH --cpus-per-task=10 #SBATCH --partition=general -#SBATCH --mem-per-cpu=2GB +#SBATCH --mem-per-cpu=4GB #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. module use /opt/insy/modulefiles # Use DAIC INSY software collection @@ -13,4 +13,4 @@ module load openmpi source experiments/slurm_header.sh -srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search threaded n_individuals=10 > experiments/logs/grid_search_california_housing.log +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=california_housing output_path=results mpi grid_search threaded n_individuals=100 > experiments/logs/grid_search_california_housing.log diff --git a/experiments/daic/tuning/generators/circles.sh b/experiments/daic/tuning/generators/circles.sh index 2ab2cb77..997ce415 100644 --- a/experiments/daic/tuning/generators/circles.sh +++ b/experiments/daic/tuning/generators/circles.sh @@ -2,10 +2,10 @@ #SBATCH --job-name="Grid-search Circles (ECCCo)" #SBATCH --time=01:00:00 -#SBATCH --ntasks=30 -#SBATCH --cpus-per-task=30 +#SBATCH --ntasks=20 +#SBATCH --cpus-per-task=10 #SBATCH --partition=general -#SBATCH --mem-per-cpu=1GB +#SBATCH --mem-per-cpu=2GB #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. module use /opt/insy/modulefiles # Use DAIC INSY software collection diff --git a/experiments/daic/tuning/generators/german_credit.sh b/experiments/daic/tuning/generators/german_credit.sh index 3b664647..a6518921 100644 --- a/experiments/daic/tuning/generators/german_credit.sh +++ b/experiments/daic/tuning/generators/german_credit.sh @@ -2,10 +2,10 @@ #SBATCH --job-name="Grid-search German Credit (ECCCo)" #SBATCH --time=01:00:00 -#SBATCH --ntasks=30 -#SBATCH --cpus-per-task=30 +#SBATCH --ntasks=20 +#SBATCH --cpus-per-task=10 #SBATCH --partition=general -#SBATCH --mem-per-cpu=1GB +#SBATCH --mem-per-cpu=2GB #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. module use /opt/insy/modulefiles # Use DAIC INSY software collection diff --git a/experiments/daic/tuning/generators/gmsc.sh b/experiments/daic/tuning/generators/gmsc.sh index 35e7e637..58c0464d 100644 --- a/experiments/daic/tuning/generators/gmsc.sh +++ b/experiments/daic/tuning/generators/gmsc.sh @@ -1,11 +1,11 @@ #!/bin/bash #SBATCH --job-name="Grid-search GMSC (ECCCo)" -#SBATCH --time=01:00:00 -#SBATCH --ntasks=20 -#SBATCH --cpus-per-task=20 +#SBATCH --time=02:00:00 +#SBATCH --ntasks=30 +#SBATCH --cpus-per-task=10 #SBATCH --partition=general -#SBATCH --mem-per-cpu=2GB +#SBATCH --mem-per-cpu=4GB #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. module use /opt/insy/modulefiles # Use DAIC INSY software collection diff --git a/experiments/daic/tuning/generators/linearly_separable.sh b/experiments/daic/tuning/generators/linearly_separable.sh index e2ed9d44..b7578a85 100644 --- a/experiments/daic/tuning/generators/linearly_separable.sh +++ b/experiments/daic/tuning/generators/linearly_separable.sh @@ -2,7 +2,7 @@ #SBATCH --job-name="Grid-search Linearly Separable (ECCCo)" #SBATCH --time=01:00:00 -#SBATCH --ntasks=10 +#SBATCH --ntasks=20 #SBATCH --cpus-per-task=10 #SBATCH --partition=general #SBATCH --mem-per-cpu=2GB diff --git a/experiments/daic/tuning/generators/moons.sh b/experiments/daic/tuning/generators/moons.sh index 2c7f4aab..55e16aa0 100644 --- a/experiments/daic/tuning/generators/moons.sh +++ b/experiments/daic/tuning/generators/moons.sh @@ -1,11 +1,11 @@ #!/bin/bash #SBATCH --job-name="Grid-search Moons (ECCCo)" -#SBATCH --time=01:00:00 -#SBATCH --ntasks=30 -#SBATCH --cpus-per-task=30 +#SBATCH --time=01:30:00 +#SBATCH --ntasks=20 +#SBATCH --cpus-per-task=10 #SBATCH --partition=general -#SBATCH --mem-per-cpu=1GB +#SBATCH --mem-per-cpu=2GB #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. module use /opt/insy/modulefiles # Use DAIC INSY software collection From 330828c83bfd67ecef67094ccd1773ee3bdd2ec7 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Wed, 18 Oct 2023 13:24:03 +0200 Subject: [PATCH 086/171] more things --- experiments/daic/tuning/generators/german_credit.sh | 2 +- experiments/daic/tuning/generators/gmsc.sh | 4 ++-- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/experiments/daic/tuning/generators/german_credit.sh b/experiments/daic/tuning/generators/german_credit.sh index a6518921..2358e2d9 100644 --- a/experiments/daic/tuning/generators/german_credit.sh +++ b/experiments/daic/tuning/generators/german_credit.sh @@ -5,7 +5,7 @@ #SBATCH --ntasks=20 #SBATCH --cpus-per-task=10 #SBATCH --partition=general -#SBATCH --mem-per-cpu=2GB +#SBATCH --mem-per-cpu=4GB #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. module use /opt/insy/modulefiles # Use DAIC INSY software collection diff --git a/experiments/daic/tuning/generators/gmsc.sh b/experiments/daic/tuning/generators/gmsc.sh index 58c0464d..8f08c051 100644 --- a/experiments/daic/tuning/generators/gmsc.sh +++ b/experiments/daic/tuning/generators/gmsc.sh @@ -1,7 +1,7 @@ #!/bin/bash #SBATCH --job-name="Grid-search GMSC (ECCCo)" -#SBATCH --time=02:00:00 +#SBATCH --time=01:30:00 #SBATCH --ntasks=30 #SBATCH --cpus-per-task=10 #SBATCH --partition=general @@ -13,4 +13,4 @@ module load openmpi source experiments/slurm_header.sh -srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=gmsc output_path=results mpi grid_search threaded n_individuals=10 > experiments/logs/grid_search_gmsc.log +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=gmsc output_path=results mpi grid_search threaded n_individuals=100 > experiments/logs/grid_search_gmsc.log From 14cd5d381d162234e5ea951dc115c2073ee98f7d Mon Sep 17 00:00:00 2001 From: pat-alt Date: Wed, 18 Oct 2023 13:55:39 +0200 Subject: [PATCH 087/171] circles delftbluw --- experiments/jobscripts/tuning/generators/circles.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/experiments/jobscripts/tuning/generators/circles.sh b/experiments/jobscripts/tuning/generators/circles.sh index 452d4ca1..7b3bf21e 100644 --- a/experiments/jobscripts/tuning/generators/circles.sh +++ b/experiments/jobscripts/tuning/generators/circles.sh @@ -1,7 +1,7 @@ #!/bin/bash #SBATCH --job-name="Grid-search Circles (ECCCo)" -#SBATCH --time=01:00:00 +#SBATCH --time=01:30:00 #SBATCH --ntasks=15 #SBATCH --cpus-per-task=10 #SBATCH --partition=compute From 090687bcf75eab495680e58e7dd98a9452626ce8 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Wed, 18 Oct 2023 14:01:57 +0200 Subject: [PATCH 088/171] setting up final run scripts --- experiments/jobscripts/generators/circles.sh | 16 ++++++++++++++++ experiments/jobscripts/generators/moons.sh | 16 ++++++++++++++++ 2 files changed, 32 insertions(+) create mode 100644 experiments/jobscripts/generators/circles.sh create mode 100644 experiments/jobscripts/generators/moons.sh diff --git a/experiments/jobscripts/generators/circles.sh b/experiments/jobscripts/generators/circles.sh new file mode 100644 index 00000000..dcdd277e --- /dev/null +++ b/experiments/jobscripts/generators/circles.sh @@ -0,0 +1,16 @@ +#!/bin/bash + +#SBATCH --job-name="Circles (ECCCo)" +#SBATCH --time=00:35:00 +#SBATCH --ntasks=10 +#SBATCH --cpus-per-task=10 +#SBATCH --partition=compute +#SBATCH --mem-per-cpu=2GB +#SBATCH --account=research-eemcs-insy +#SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. + +module load 2023r1 openmpi + +source experiments/slurm_header.sh + +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=circles output_path=results mpi threaded n_individuals=100 n_runs=5 > experiments/logs/circles.log diff --git a/experiments/jobscripts/generators/moons.sh b/experiments/jobscripts/generators/moons.sh new file mode 100644 index 00000000..d0feee70 --- /dev/null +++ b/experiments/jobscripts/generators/moons.sh @@ -0,0 +1,16 @@ +#!/bin/bash + +#SBATCH --job-name="Moons (ECCCo)" +#SBATCH --time=00:35:00 +#SBATCH --ntasks=10 +#SBATCH --cpus-per-task=10 +#SBATCH --partition=compute +#SBATCH --mem-per-cpu=2GB +#SBATCH --account=research-eemcs-insy +#SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. + +module load 2023r1 openmpi + +source experiments/slurm_header.sh + +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=moons output_path=results mpi threaded n_individuals=100 n_runs=5 > experiments/logs/moons.log From ea3f48a7eeeb9abb7a4c2f67e30ccce0393581d7 Mon Sep 17 00:00:00 2001 From: pat-alt Date: Wed, 18 Oct 2023 14:08:02 +0200 Subject: [PATCH 089/171] tabular delftblu --- .../jobscripts/tuning/generators/california_housing.sh | 4 ++-- experiments/jobscripts/tuning/generators/gmsc.sh | 2 +- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/experiments/jobscripts/tuning/generators/california_housing.sh b/experiments/jobscripts/tuning/generators/california_housing.sh index 2677be0f..5e8f4f40 100644 --- a/experiments/jobscripts/tuning/generators/california_housing.sh +++ b/experiments/jobscripts/tuning/generators/california_housing.sh @@ -1,8 +1,8 @@ #!/bin/bash #SBATCH --job-name="Grid-search California Housing (ECCCo)" -#SBATCH --time=02:00:00 -#SBATCH --ntasks=20 +#SBATCH --time=01:30:00 +#SBATCH --ntasks=30 #SBATCH --cpus-per-task=10 #SBATCH --partition=compute #SBATCH --mem-per-cpu=4GB diff --git a/experiments/jobscripts/tuning/generators/gmsc.sh b/experiments/jobscripts/tuning/generators/gmsc.sh index 8b407ff7..9b84593e 100644 --- a/experiments/jobscripts/tuning/generators/gmsc.sh +++ b/experiments/jobscripts/tuning/generators/gmsc.sh @@ -2,7 +2,7 @@ #SBATCH --job-name="Grid-search GMSC (ECCCo)" #SBATCH --time=01:30:00 -#SBATCH --ntasks=15 +#SBATCH --ntasks=30 #SBATCH --cpus-per-task=10 #SBATCH --partition=compute #SBATCH --mem-per-cpu=4GB From 118da1ae19dee0fcb02dd436ae6fc166a93a587b Mon Sep 17 00:00:00 2001 From: pat-alt Date: Wed, 18 Oct 2023 17:41:24 +0200 Subject: [PATCH 090/171] bloody hell --- experiments/Manifest.toml | 4 ++-- experiments/experiment.jl | 2 +- experiments/grid_search.jl | 10 ++++++---- .../jobscripts/generators/california_housing.sh | 12 +++++++----- .../tuning/generators/california_housing.sh | 2 +- experiments/jobscripts/tuning/generators/gmsc.sh | 2 +- experiments/utils.jl | 2 ++ src/sampling.jl | 4 +++- src/utils.jl | 14 ++++++++++++++ 9 files changed, 37 insertions(+), 15 deletions(-) diff --git a/experiments/Manifest.toml b/experiments/Manifest.toml index 48d8a3c8..4a9e1575 100644 --- a/experiments/Manifest.toml +++ b/experiments/Manifest.toml @@ -438,11 +438,11 @@ version = "0.6.3" [[deps.CounterfactualExplanations]] deps = ["CSV", "CUDA", "CategoricalArrays", "ChainRulesCore", "DataFrames", "DecisionTree", "Distributions", "EvoTrees", "Flux", "LaplaceRedux", "LazyArtifacts", "LinearAlgebra", "Logging", "MLDatasets", "MLJBase", "MLJDecisionTreeInterface", "MLJModels", "MLUtils", "MultivariateStats", "NearestNeighborModels", "PackageExtensionCompat", "Parameters", "PrecompileTools", "ProgressMeter", "Random", "Serialization", "Statistics", "StatsBase", "Tables", "UUIDs", "cuDNN"] -git-tree-sha1 = "6ac3b59bcd9d8c75dcbe83822f050247d1143334" +git-tree-sha1 = "7962ccc6f9e41b3f197b1050e950aca9e3630a18" repo-rev = "main" repo-url = "https://github.com/JuliaTrustworthyAI/CounterfactualExplanations.jl.git" uuid = "2f13d31b-18db-44c1-bc43-ebaf2cff0be0" -version = "0.1.30" +version = "0.1.31" [deps.CounterfactualExplanations.extensions] MPIExt = "MPI" diff --git a/experiments/experiment.jl b/experiments/experiment.jl index a375158e..1d733971 100644 --- a/experiments/experiment.jl +++ b/experiments/experiment.jl @@ -9,7 +9,7 @@ Base.@kwdef struct Experiment use_pretrained::Bool = !RETRAIN models::Union{Nothing,Dict} = nothing additional_models::Union{Nothing,Dict} = nothing - 𝒟x::Distribution = Normal() + 𝒟x::Distribution = ECCCo.prior_sampling_space(counterfactual_data) sampling_batch_size::Int = 50 sampling_steps::Int = 50 min_batch_size::Int = 128 diff --git a/experiments/grid_search.jl b/experiments/grid_search.jl index 36904a08..29ee1982 100644 --- a/experiments/grid_search.jl +++ b/experiments/grid_search.jl @@ -212,10 +212,10 @@ function best_absolute_outcome( higher_is_better = [var ∈ ["validity", "redundancy"] for var in evaluation.variable] evaluation.value[higher_is_better] .= -evaluation.value[higher_is_better] - # Normalise to allow for comparison across measures: - evaluation = - groupby(evaluation, [:dataname, :variable]) |> - x -> transform(x, :value => standardize => :value) + # # Normalise to allow for comparison across measures: + # evaluation = + # groupby(evaluation, [:dataname, :variable]) |> + # x -> transform(x, :value => standardize => :value) # Reconstruct outcome with normalised values: bmk = CounterfactualExplanations.Evaluation.Benchmark(evaluation) @@ -239,6 +239,8 @@ function best_absolute_outcome( params=outcomes[:df_outcomes].params[best_index], outcome=outcomes[:df_outcomes].outcome[best_index], ) + + return best_outcome end best_absolute_outcome_eccco(outcomes; kwrgs...) = diff --git a/experiments/jobscripts/generators/california_housing.sh b/experiments/jobscripts/generators/california_housing.sh index 07d5770e..446cb9d9 100644 --- a/experiments/jobscripts/generators/california_housing.sh +++ b/experiments/jobscripts/generators/california_housing.sh @@ -1,14 +1,16 @@ #!/bin/bash #SBATCH --job-name="California Housing (ECCCo)" -#SBATCH --time=3:00:00 -#SBATCH --ntasks=100 -#SBATCH --cpus-per-task=1 +#SBATCH --time=00:30:00 +#SBATCH --ntasks=30 +#SBATCH --cpus-per-task=10 #SBATCH --partition=compute -#SBATCH --mem-per-cpu=8GB +#SBATCH --mem-per-cpu=4GB #SBATCH --account=research-eemcs-insy #SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes. module load 2023r1 openmpi -srun julia --project=experiments experiments/run_experiments.jl -- data=california_housing output_path=results mpi > experiments/california_housing.log +source experiments/slurm_header.sh + +srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=california_housing output_path=results mpi threaded n_individuals=100 n_runs=5 > experiments/logs/california_housing.log diff --git a/experiments/jobscripts/tuning/generators/california_housing.sh b/experiments/jobscripts/tuning/generators/california_housing.sh index 5e8f4f40..e1805b58 100644 --- a/experiments/jobscripts/tuning/generators/california_housing.sh +++ b/experiments/jobscripts/tuning/generators/california_housing.sh @@ -1,7 +1,7 @@ #!/bin/bash #SBATCH --job-name="Grid-search California Housing (ECCCo)" -#SBATCH --time=01:30:00 +#SBATCH --time=01:20:00 #SBATCH --ntasks=30 #SBATCH --cpus-per-task=10 #SBATCH --partition=compute diff --git a/experiments/jobscripts/tuning/generators/gmsc.sh b/experiments/jobscripts/tuning/generators/gmsc.sh index 9b84593e..848b074f 100644 --- a/experiments/jobscripts/tuning/generators/gmsc.sh +++ b/experiments/jobscripts/tuning/generators/gmsc.sh @@ -1,7 +1,7 @@ #!/bin/bash #SBATCH --job-name="Grid-search GMSC (ECCCo)" -#SBATCH --time=01:30:00 +#SBATCH --time=01:20:00 #SBATCH --ntasks=30 #SBATCH --cpus-per-task=10 #SBATCH --partition=compute diff --git a/experiments/utils.jl b/experiments/utils.jl index be94743d..5b77538c 100644 --- a/experiments/utils.jl +++ b/experiments/utils.jl @@ -1,6 +1,8 @@ using CounterfactualExplanations.Parallelization: ThreadsParallelizer +using Distributions: Uniform using Flux using LinearAlgebra: norm +using Statistics: mean, std function is_multi_processed(parallelizer::Union{Nothing,AbstractParallelizer}) if isnothing(parallelizer) || isa(parallelizer, ThreadsParallelizer) diff --git a/src/sampling.jl b/src/sampling.jl index aedd495b..75776c2c 100644 --- a/src/sampling.jl +++ b/src/sampling.jl @@ -46,8 +46,10 @@ function EnergySampler( K = length(data.y_levels) input_size = size(selectdim(data.X, ndims(data.X), 1)) - 𝒟x = Uniform(extrema(data.X)...) + # Prior distribution: + 𝒟x = prior_sampling_space(data) 𝒟y = Categorical(ones(K) ./ K) + # Sampler: sampler = ConditionalSampler(𝒟x, 𝒟y; input_size = input_size) yidx = get_target_index(data.y_levels, y) diff --git a/src/utils.jl b/src/utils.jl index a476fc6c..a2fae145 100644 --- a/src/utils.jl +++ b/src/utils.jl @@ -57,3 +57,17 @@ function ssim_dist(x, y) y = convert2mnist(y) return (1 - assess_ssim(x, y)) / 2 end + +""" + prior_sampling_space(data::CounterfactualData; n_std=3) + +Define the prior sampling space for the data. +""" +function prior_sampling_space(data::CounterfactualData; n_std=3) + X = data.X + centers = mean(X, dims=2) + stds = std(X, dims=2) + lower_bound = minimum(centers .- n_std .* stds)[1] + upper_bound = maximum(centers .+ n_std .* stds)[1] + return Uniform(lower_bound, upper_bound) +end \ No newline at end of file From d0ada1dbc5bab4c6b69612f4d7b7582512bce86e Mon Sep 17 00:00:00 2001 From: pat-alt Date: Wed, 18 Oct 2023 18:07:18 +0200 Subject: [PATCH 091/171] updated models --- models/california_housing_models.jls | Bin 1235451 -> 1235444 bytes models/circles_models.jls | Bin 148010 -> 242041 bytes models/german_credit_models.jls | Bin 980091 -> 980084 bytes models/gmsc_models.jls | Bin 1168187 -> 1168180 bytes models/linearly_separable_models.jls | Bin 162952 -> 162945 bytes models/moons_models.jls | Bin 314139 -> 314132 bytes 6 files changed, 0 insertions(+), 0 deletions(-) diff --git a/models/california_housing_models.jls b/models/california_housing_models.jls index 24c49c4138019c7d33317e22e1a4a6b952481e60..ae975c60413909f99db0387020ad33a711858b19 100644 GIT binary patch literal 1235444 zcmZ^K2{={J*EcfHGGvO(L`sw5p1qEtqEJd{q7bD_nVJU@A|jG0(jZEu65*b`Zc39# zqS7EVDoSZmsZagi_kG^y`=0MS&$;)Ud)8iS?Y)2N?6uZj*Lt>#il~r~&=f^sQO7{P 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