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zuhengxuzuhengxu
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put julia run script in synthetic/irfflow/
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  • example

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‎example/synthetic_expt/irfflow/run.jl‎

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include(joinpath(@__DIR__, "../../julia_env/evaluation.jl"))
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n_sample_eval = 64
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# run tv evaluation
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for name in ["Banana", "Funnel", "WarpedGaussian", "Cross"]
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for flowtype in [MF.DeterministicMixFlow, MF.BackwardIRFMixFlow, MF.IRFMixFlow]
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for kernel in [MF.HMC]
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for flowlength in [300]
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for step_size in [0.01, 0.05, 0.1, 0.2]
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for nchains in [30]
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for seed in 1:32
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# run simulation
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df = run_tv_sweep(seed, name, flowtype, kernel, flowlength, step_size; nsample=n_sample_eval, nchains=nchains)
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# save simulation results
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res_dir = joinpath(@__DIR__, "csvs/")
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if !isdir(res_dir)
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mkpath(res_dir)
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end
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CSV.write(
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joinpath(res_dir, "$(name)_$(kernel)_$(flowtype)_$(flowlength)_$(step_size)_$(seed).csv"),
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df,
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)
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end
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end
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end
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end
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end
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end
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end
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for name in ["Banana", "Funnel", "WarpedGaussian", "Cross"]
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for flowtype in [MF.EnsembleIRFFlow]
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for kernel in [MF.HMC]
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for flowlength in [0, 10, 20, 50, 80, 100, 200, 300]
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for step_size in [0.01, 0.05, 0.1, 0.2]
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for nchains in [30]
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for seed in 1:32
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# run simulation
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df = run_tv_sweep(seed, name, flowtype, kernel, flowlength, step_size; nsample=n_sample_eval, nchains=nchains)
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# save simulation results
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res_dir = joinpath(@__DIR__, "csvs/")
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if !isdir(res_dir)
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mkpath(res_dir)
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end
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CSV.write(
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joinpath(res_dir, "$(name)_$(kernel)_$(flowtype)_$(flowlength)_$(step_size)_$(seed).csv"),
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df,
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)
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end
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end
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end
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end
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end
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end
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end
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for name in ["Banana", "Funnel", "WarpedGaussian", "Cross"]
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for flowtype in [MF.DeterministicMixFlow, MF.BackwardIRFMixFlow, MF.IRFMixFlow]
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for kernel in [MF.MALA]
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for flowlength in [2000]
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for step_size in [0.05, 0.2, 1.0]
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for nchains in [30]
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for seed in 1:32
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# run simulation
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df = run_tv_sweep(seed, name, flowtype, kernel, flowlength, step_size; nsample=n_sample_eval, nchains=nchains)
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# save simulation results
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res_dir = joinpath(@__DIR__, "csvs/")
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if !isdir(res_dir)
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mkpath(res_dir)
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end
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CSV.write(
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joinpath(res_dir, "$(name)_$(kernel)_$(flowtype)_$(flowlength)_$(step_size)_$(seed).csv"),
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df,
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)
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end
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end
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end
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end
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end
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end
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end
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for name in ["Banana", "Funnel", "WarpedGaussian", "Cross"]
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for flowtype in [MF.EnsembleIRFFlow]
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for kernel in [MF.MALA]
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for flowlength in [0, 10, 20, 50, 80, 100, 200, 300]
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for step_size in [0.05, 0.2, 1.0]
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for nchains in [30]
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for seed in 1:32
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# run simulation
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df = run_tv_sweep(seed, name, flowtype, kernel, flowlength, step_size; nsample=n_sample_eval, nchains=nchains)
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# save simulation results
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res_dir = joinpath(@__DIR__, "csvs/")
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if !isdir(res_dir)
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mkpath(res_dir)
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end
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CSV.write(
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joinpath(res_dir, "$(name)_$(kernel)_$(flowtype)_$(flowlength)_$(step_size)_$(seed).csv"),
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df,
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)
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end
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end
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end
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end
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end
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end
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end
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for name in ["Banana", "Funnel", "WarpedGaussian", "Cross"]
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for flowtype in [MF.DeterministicMixFlow, MF.BackwardIRFMixFlow, MF.IRFMixFlow]
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for kernel in [MF.RWMH]
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for flowlength in [4000]
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for step_size in [0.05, 0.2, 1.0]
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for nchains in [30]
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for seed in 1:32
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# run simulation
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df = run_tv_sweep(seed, name, flowtype, kernel, flowlength, step_size; nsample=n_sample_eval, nchains=nchains)
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# save simulation results
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res_dir = joinpath(@__DIR__, "csvs/")
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if !isdir(res_dir)
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mkpath(res_dir)
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end
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CSV.write(
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joinpath(res_dir, "$(name)_$(kernel)_$(flowtype)_$(flowlength)_$(step_size)_$(seed).csv"),
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df,
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)
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end
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end
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end
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end
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end
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end
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end
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for name in ["Banana", "Funnel", "WarpedGaussian", "Cross"]
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for flowtype in [MF.EnsembleIRFFlow]
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for kernel in [MF.RWMH]
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for flowlength in [0, 10, 20, 50, 80, 100, 200, 300]
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for step_size in [0.05, 0.2, 1.0]
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for nchains in [30]
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for seed in 1:32
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# run simulation
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df = run_tv_sweep(seed, name, flowtype, kernel, flowlength, step_size; nsample=n_sample_eval, nchains=nchains)
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# save simulation results
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res_dir = joinpath(@__DIR__, "csvs/")
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if !isdir(res_dir)
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mkpath(res_dir)
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end
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CSV.write(
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joinpath(res_dir, "$(name)_$(kernel)_$(flowtype)_$(flowlength)_$(step_size)_$(seed).csv"),
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df,
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)
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end
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end
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end
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end
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end
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end
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end
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# get elbo, ess, logz results
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for name in ["Banana", "Funnel", "WarpedGaussian", "Cross"]
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for flowtype in [MF.DeterministicMixFlow, MF.BackwardIRFMixFlow, MF.EnsembleIRFFlow, MF.IRFMixFlow]
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for kernel in [MF.RWMH]
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for flow_length in [4000]
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for step_size in [1.0]
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for nchains in [30]
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for seed in 1:32
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if flowtype == MF.EnsembleIRFFlow
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flowlength = 3000
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end
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# run simulation
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df, _ = flow_evaluation(
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seed, name, flowtype, kernel, flow_length, step_size;
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nsample=n_sample_eval, nchains=nchains,
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track_cost=false,
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)
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# save simulation results
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res_dir = joinpath(@__DIR__, "elbos/")
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if !isdir(res_dir)
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mkpath(res_dir)
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end
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CSV.write(
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joinpath(res_dir, "$(name)_$(kernel)_$(flowtype)_$(flowlength)_$(step_size)_$(seed).csv"),
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df,
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)
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end
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end
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end
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end
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end
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for kernel in [MF.HMC]
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for flow_length in [200]
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for step_size in [0.1, 0.2]
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for nchains in [30]
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for seed in 1:32
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# run simulation
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df, _ = flow_evaluation(
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seed, name, flowtype, kernel, flow_length, step_size;
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nsample=n_sample_eval, nchains=nchains,
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track_cost=false,
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)
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# save simulation results
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res_dir = joinpath(@__DIR__, "elbos/")
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if !isdir(res_dir)
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mkpath(res_dir)
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end
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CSV.write(
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joinpath(res_dir, "$(name)_$(kernel)_$(flowtype)_$(flowlength)_$(step_size)_$(seed).csv"),
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df,
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)
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end
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end
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end
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end
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end
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end
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end
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‎example/synthetic_tuning/tv.nf‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -13,7 +13,7 @@ def plot_script = file(moduleDir/'plotting.jl')
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def variables = [
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seed: 1..32,
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target: ["Banana", "Cross", "Funnel", "WarpedGaussian"],
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flowtype: ["MF.IRFMixFlow"],
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flowtype: ["MF.DeterministicMixFlow", "MF.BackwardIRFMixFlow", "MF.IRFMixFlow"],
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kernel: ["MF.RWMH"],
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step_size: [0.05, 0.2, 1.0],
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flow_length: [4000],

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