├── .gitignore ├── LICENSE ├── README.md ├── examples ├── PPO_on_cartpole │ ├── NEMO_OUTPUT │ │ ├── BC_1 │ │ │ ├── 1 │ │ │ │ ├── 2018-12-21--9-52-29-733387.err │ │ │ │ ├── 2018-12-21--9-52-29-733387.out │ │ │ │ └── job_1.cmd_2018-12-21--9-52-29-733387.pbs │ │ │ ├── configs.json │ │ │ ├── configspace.json │ │ │ ├── results.json │ │ │ └── results.pkl │ │ ├── BC_10 │ │ │ ├── 10 │ │ │ │ ├── 2018-12-21--13-22-51-780339.err │ │ │ │ ├── 2018-12-21--13-22-51-780339.out │ │ │ │ └── job_10.cmd_2018-12-21--13-22-51-780339.pbs │ │ │ ├── configs.json │ │ │ ├── configspace.json │ │ │ ├── results.json │ │ │ └── results.pkl │ │ ├── BC_2 │ │ │ ├── 2 │ │ │ │ ├── 2018-12-21--9-52-30-296000.err │ │ │ │ ├── 2018-12-21--9-52-30-296000.out │ │ │ │ └── job_2.cmd_2018-12-21--9-52-30-296000.pbs │ │ │ ├── configs.json │ │ │ ├── configspace.json │ │ │ ├── results.json │ │ │ └── results.pkl │ │ ├── BC_3 │ │ │ ├── 3 │ │ │ │ ├── 2018-12-21--9-52-30-868730.err │ │ │ │ ├── 2018-12-21--9-52-30-868730.out │ │ │ │ └── job_3.cmd_2018-12-21--9-52-30-868730.pbs │ │ │ ├── configs.json │ │ │ ├── configspace.json │ │ │ ├── results.json │ │ │ └── results.pkl │ │ ├── BC_4 │ │ │ ├── 4 │ │ │ │ ├── 2018-12-21--9-52-31-446298.err │ │ │ │ ├── 2018-12-21--9-52-31-446298.out │ │ │ │ └── job_4.cmd_2018-12-21--9-52-31-446298.pbs │ │ │ ├── configs.json │ │ │ ├── configspace.json │ │ │ ├── results.json │ │ │ └── results.pkl │ │ ├── BC_5 │ │ │ ├── 5 │ │ │ │ ├── 2018-12-21--13-22-26-631079.err │ │ │ │ ├── 2018-12-21--13-22-26-631079.out │ │ │ │ └── job_5.cmd_2018-12-21--13-22-26-631079.pbs │ │ │ ├── configs.json │ │ │ ├── configspace.json │ │ │ ├── results.json │ │ │ └── results.pkl │ │ ├── BC_6 │ │ │ ├── 6 │ │ │ │ ├── 2018-12-21--13-22-32-687552.err │ │ │ │ ├── 2018-12-21--13-22-32-687552.out │ │ │ │ └── job_6.cmd_2018-12-21--13-22-32-687552.pbs │ │ │ ├── configs.json │ │ │ ├── configspace.json │ │ │ ├── results.json │ │ │ └── results.pkl │ │ ├── BC_7 │ │ │ ├── 7 │ │ │ │ ├── 2018-12-21--13-22-41-11044.err │ │ │ │ ├── 2018-12-21--13-22-41-11044.out │ │ │ │ └── job_7.cmd_2018-12-21--13-22-41-11044.pbs │ │ │ ├── configs.json │ │ │ ├── configspace.json │ │ │ ├── results.json │ │ │ └── results.pkl │ │ ├── BC_8 │ │ │ ├── 8 │ │ │ │ ├── 2018-12-21--9-52-33-855478.err │ │ │ │ ├── 2018-12-21--9-52-33-855478.out │ │ │ │ └── job_8.cmd_2018-12-21--9-52-33-855478.pbs │ │ │ ├── configs.json │ │ │ ├── configspace.json │ │ │ ├── results.json │ │ │ └── results.pkl │ │ └── BC_9 │ │ │ ├── 9 │ │ │ ├── 2018-12-21--13-22-46-352613.err │ │ │ ├── 2018-12-21--13-22-46-352613.out │ │ │ └── job_9.cmd_2018-12-21--13-22-46-352613.pbs │ │ │ ├── configs.json │ │ │ ├── configspace.json │ │ │ ├── results.json │ │ │ └── results.pkl │ ├── notebook.ipynb │ └── run_BOHB.py ├── __init__.py ├── icml_2018_experiments │ ├── bnn.ipynb │ ├── cartpole.ipynb │ ├── icml2018requirements.txt │ ├── opt_results │ │ ├── bnn │ │ │ ├── bostonhousing │ │ │ │ ├── bohb │ │ │ │ │ ├── configs.json │ │ │ │ │ ├── configspace.pcs │ │ │ │ │ └── results.json │ │ │ │ ├── hyperband │ │ │ │ │ ├── configs.json │ │ │ │ │ ├── configspace.pcs │ │ │ │ │ └── results.json │ │ │ │ ├── randomsearch │ │ │ │ │ ├── configs.json │ │ │ │ │ ├── configspace.pcs │ │ │ │ │ └── results.json │ │ │ │ └── smac │ │ │ │ │ └── run_1739378298 │ │ │ │ │ ├── configspace.json │ │ │ │ │ ├── configspace.pcs │ │ │ │ │ ├── runhistory.json │ │ │ │ │ ├── scenario.txt │ │ │ │ │ ├── stats.json │ │ │ │ │ ├── traj_aclib2.json │ │ │ │ │ └── traj_old.csv │ │ │ ├── proteinstructure │ │ │ │ ├── bohb │ │ │ │ │ ├── configs.json │ │ │ │ │ ├── configspace.pcs │ │ │ │ │ └── results.json │ │ │ │ ├── hyperband │ │ │ │ │ ├── HPB_run_0_pyro.pkl │ │ │ │ │ ├── configs.json │ │ │ │ │ ├── configspace.pcs │ │ │ │ │ └── results.json │ │ │ │ ├── randomsearch │ │ │ │ │ ├── configs.json │ │ │ │ │ ├── configspace.pcs │ │ │ │ │ └── results.json │ │ │ │ └── smac │ │ │ │ │ └── run_314009415 │ │ │ │ │ ├── configspace.json │ │ │ │ │ ├── configspace.pcs │ │ │ │ │ ├── runhistory.json │ │ │ │ │ ├── scenario.txt │ │ │ │ │ ├── stats.json │ │ │ │ │ ├── traj_aclib2.json │ │ │ │ │ └── traj_old.csv │ │ │ └── toyfunction │ │ │ │ ├── bohb │ │ │ │ ├── configs.json │ │ │ │ ├── configspace.pcs │ │ │ │ └── results.json │ │ │ │ ├── hyperband │ │ │ │ ├── configs.json │ │ │ │ ├── configspace.pcs │ │ │ │ └── results.json │ │ │ │ ├── randomsearch │ │ │ │ ├── configs.json │ │ │ │ ├── configspace.pcs │ │ │ │ └── results.json │ │ │ │ └── smac │ │ │ │ └── run_1119649367 │ │ │ │ ├── configspace.json │ │ │ │ ├── configspace.pcs │ │ │ │ ├── runhistory.json │ │ │ │ ├── scenario.txt │ │ │ │ ├── stats.json │ │ │ │ ├── traj_aclib2.json │ │ │ │ └── traj_old.csv │ │ ├── cartpole │ │ │ └── bohb │ │ │ │ ├── configs.json │ │ │ │ ├── configspace.pcs │ │ │ │ └── results.json │ │ ├── paramnet_surrogates │ │ │ ├── adult │ │ │ │ ├── bohb │ │ │ │ │ ├── configs.json │ │ │ │ │ ├── configspace.pcs │ │ │ │ │ └── results.json │ │ │ │ ├── hyperband │ │ │ │ │ ├── configs.json │ │ │ │ │ ├── configspace.pcs │ │ │ │ │ └── results.json │ │ │ │ ├── randomsearch │ │ │ │ │ ├── configs.json │ │ │ │ │ ├── configspace.pcs │ │ │ │ │ └── results.json │ │ │ │ └── smac │ │ │ │ │ └── run_1569982670 │ │ │ │ │ ├── configspace.json │ │ │ │ │ ├── configspace.pcs │ │ │ │ │ ├── runhistory.json │ │ │ │ │ ├── scenario.txt │ │ │ │ │ ├── stats.json │ │ │ │ │ ├── traj_aclib2.json │ │ │ │ │ └── traj_old.csv │ │ │ ├── higgs │ │ │ │ ├── bohb │ │ │ │ │ ├── configs.json │ │ │ │ │ ├── configspace.pcs │ │ │ │ │ └── results.json │ │ │ │ ├── hyperband │ │ │ │ │ ├── configs.json │ │ │ │ │ ├── configspace.pcs │ │ │ │ │ └── results.json │ │ │ │ ├── randomsearch │ │ │ │ │ ├── configs.json │ │ │ │ │ ├── configspace.pcs │ │ │ │ │ └── results.json │ │ │ │ └── smac │ │ │ │ │ └── run_2040386885 │ │ │ │ │ ├── configspace.json │ │ │ │ │ ├── configspace.pcs │ │ │ │ │ ├── runhistory.json │ │ │ │ │ ├── scenario.txt │ │ │ │ │ ├── stats.json │ │ │ │ │ ├── traj_aclib2.json │ │ │ │ │ └── traj_old.csv │ │ │ ├── letter │ │ │ │ ├── bohb │ │ │ │ │ ├── configs.json │ │ │ │ │ ├── configspace.pcs │ │ │ │ │ └── results.json │ │ │ │ ├── hyperband │ │ │ │ │ ├── configs.json │ │ │ │ │ ├── configspace.pcs │ │ │ │ │ └── results.json │ │ │ │ ├── randomsearch │ │ │ │ │ ├── configs.json │ │ │ │ │ ├── configspace.pcs │ │ │ │ │ └── results.json │ │ │ │ └── smac │ │ │ │ │ └── run_727669348 │ │ │ │ │ ├── configspace.json │ │ │ │ │ ├── configspace.pcs │ │ │ │ │ ├── runhistory.json │ │ │ │ │ ├── scenario.txt │ │ │ │ │ ├── stats.json │ │ │ │ │ ├── traj_aclib2.json │ │ │ │ │ └── traj_old.csv │ │ │ ├── mnist │ │ │ │ ├── bohb │ │ │ │ │ ├── configs.json │ │ │ │ │ ├── configspace.pcs │ │ │ │ │ └── results.json │ │ │ │ ├── hyperband │ │ │ │ │ ├── configs.json │ │ │ │ │ ├── configspace.pcs │ │ │ │ │ └── results.json │ │ │ │ ├── randomsearch │ │ │ │ │ ├── configs.json │ │ │ │ │ ├── configspace.pcs │ │ │ │ │ └── results.json │ │ │ │ └── smac │ │ │ │ │ └── run_1765023969 │ │ │ │ │ ├── configspace.json │ │ │ │ │ ├── configspace.pcs │ │ │ │ │ ├── runhistory.json │ │ │ │ │ ├── scenario.txt │ │ │ │ │ ├── stats.json │ │ │ │ │ ├── traj_aclib2.json │ │ │ │ │ └── traj_old.csv │ │ │ ├── optdigits │ │ │ │ ├── bohb │ │ │ │ │ ├── configs.json │ │ │ │ │ ├── configspace.pcs │ │ │ │ │ └── results.json │ │ │ │ ├── hyperband │ │ │ │ │ ├── configs.json │ │ │ │ │ ├── configspace.pcs │ │ │ │ │ └── results.json │ │ │ │ ├── randomsearch │ │ │ │ │ ├── configs.json │ │ │ │ │ ├── configspace.pcs │ │ │ │ │ └── results.json │ │ │ │ └── smac │ │ │ │ │ └── run_1254519304 │ │ │ │ │ ├── configspace.json │ │ │ │ │ ├── configspace.pcs │ │ │ │ │ ├── runhistory.json │ │ │ │ │ ├── scenario.txt │ │ │ │ │ ├── stats.json │ │ │ │ │ ├── traj_aclib2.json │ │ │ │ │ └── traj_old.csv │ │ │ └── poker │ │ │ │ ├── bohb │ │ │ │ ├── configs.json │ │ │ │ ├── configspace.pcs │ │ │ │ └── results.json │ │ │ │ ├── hyperband │ │ │ │ ├── HPB_run_0_pyro.pkl │ │ │ │ ├── configs.json │ │ │ │ ├── configspace.pcs │ │ │ │ └── results.json │ │ │ │ ├── randomsearch │ │ │ │ ├── configs.json │ │ │ │ ├── configspace.pcs │ │ │ │ └── results.json │ │ │ │ └── smac │ │ │ │ └── run_965337418 │ │ │ │ ├── configspace.json │ │ │ │ ├── configspace.pcs │ │ │ │ ├── runhistory.json │ │ │ │ ├── scenario.txt │ │ │ │ ├── stats.json │ │ │ │ ├── traj_aclib2.json │ │ │ │ └── traj_old.csv │ │ └── svm_surrogate │ │ │ ├── bohb │ │ │ ├── configs.json │ │ │ ├── configspace.pcs │ │ │ └── results.json │ │ │ ├── hyperband │ │ │ ├── HPB_run_0_pyro.pkl │ │ │ ├── configs.json │ │ │ ├── configspace.pcs │ │ │ └── results.json │ │ │ ├── randomsearch │ │ │ ├── configs.json │ │ │ ├── configspace.pcs │ │ │ └── results.json │ │ │ └── smac │ │ │ ├── run_1290122126 │ │ │ ├── configspace.json │ │ │ ├── configspace.pcs │ │ │ ├── runhistory.json │ │ │ ├── scenario.txt │ │ │ ├── stats.json │ │ │ ├── traj_aclib2.json │ │ │ └── traj_old.csv │ │ │ └── run_178863434 │ │ │ ├── configspace.json │ │ │ ├── configspace.pcs │ │ │ ├── runhistory.json │ │ │ ├── scenario.txt │ │ │ ├── stats.json │ │ │ ├── traj_aclib2.json │ │ │ └── traj_old.csv │ ├── paramnet_surrogates.ipynb │ ├── scripts │ │ ├── cluster │ │ │ ├── job_bnn.sh │ │ │ └── job_cartpole.sh │ │ ├── generate_all_cave_reports.py │ │ ├── run_all_exps.py │ │ ├── run_experiment.py │ │ └── workers │ │ │ ├── base_worker.py │ │ │ ├── bnn_worker.py │ │ │ ├── cartpole_worker.py │ │ │ ├── paramnet_surrogates.py │ │ │ └── svm_surrogate.py │ └── svm_surrogate.ipynb └── mlp_on_digits │ ├── __init__.py │ ├── helper_functions.py │ ├── notebook.ipynb │ └── test_fmin.py ├── requirements.txt ├── scripts ├── FMin.py └── __init__.py └── setup.sh /.gitignore: -------------------------------------------------------------------------------- 1 | # Folders for cluster / local results 2 | examples/icml_2018_experiments/CAVE_reports 3 | examples/icml_2018_experiments/log 4 | 5 | # Byte-compiled / optimized / DLL files 6 | __pycache__/ 7 | *.py[cod] 8 | *$py.class 9 | 10 | # C extensions 11 | *.so 12 | 13 | # Distribution / packaging 14 | .Python 15 | build/ 16 | develop-eggs/ 17 | dist/ 18 | downloads/ 19 | eggs/ 20 | .eggs/ 21 | lib/ 22 | lib64/ 23 | parts/ 24 | sdist/ 25 | var/ 26 | wheels/ 27 | *.egg-info/ 28 | .installed.cfg 29 | *.egg 30 | MANIFEST 31 | 32 | # PyInstaller 33 | # Usually these files are written by a python script from a template 34 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 35 | *.manifest 36 | *.spec 37 | 38 | # Installer logs 39 | pip-log.txt 40 | pip-delete-this-directory.txt 41 | 42 | # Unit test / coverage reports 43 | htmlcov/ 44 | .tox/ 45 | .coverage 46 | .coverage.* 47 | .cache 48 | nosetests.xml 49 | coverage.xml 50 | *.cover 51 | .hypothesis/ 52 | .pytest_cache/ 53 | 54 | # Translations 55 | *.mo 56 | *.pot 57 | 58 | # Django stuff: 59 | *.log 60 | local_settings.py 61 | db.sqlite3 62 | 63 | # Flask stuff: 64 | instance/ 65 | .webassets-cache 66 | 67 | # Scrapy stuff: 68 | .scrapy 69 | 70 | # Sphinx documentation 71 | docs/_build/ 72 | 73 | # PyBuilder 74 | target/ 75 | 76 | # Jupyter Notebook 77 | .ipynb_checkpoints 78 | 79 | # pyenv 80 | .python-version 81 | 82 | # celery beat schedule file 83 | celerybeat-schedule 84 | 85 | # SageMath parsed files 86 | *.sage.py 87 | 88 | # Environments 89 | .env 90 | .venv 91 | env/ 92 | venv/ 93 | ENV/ 94 | env.bak/ 95 | venv.bak/ 96 | 97 | # Spyder project settings 98 | .spyderproject 99 | .spyproject 100 | 101 | # Rope project settings 102 | .ropeproject 103 | 104 | # mkdocs documentation 105 | /site 106 | 107 | # mypy 108 | .mypy_cache/ 109 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # BOAH Tool Suite 2 | 3 | (see also [automl.org](https://www.automl.org/boah/)) 4 | 5 | ## Bayesian Optimization & Analysis of Hyperparameters 6 | 7 | Hyperparameter optimization and architecture search can easily become prohibitively expensive for regular black-box 8 | Bayesian optimization as training and validation of a single model can already take several hours. To overcome 9 | this, we introduce a tool suite for multi-fidelity Bayesian optimization that allows the specification of design spaces 10 | (via [ConfigSpace](https://github.com/automl/ConfigSpace)) 11 | in Python, the efficient optimization of black-box functions using cheap approximations 12 | (via [BOHB](https://github.com/automl/HpBandSter)) 13 | and an automatic analysis of the optimization process and results (via [CAVE](https://github.com/automl/CAVE)) to gain better understanding. 14 | 15 | ## Content 16 | 17 | This repository provides simple examples of how to construct a configuration space using the ConfigSpace package, 18 | how to use BOHB with minimal efforts and how to run CAVE to generate a comprehensive 19 | analysis of BOHB's optimization. 20 | 21 | ### Example 1: fmin interface 22 | 23 | To improve the first-time usage experience, with BOAH we provide an easy-to-use interface for using BOHB with subsequent analyzing, called [fmin](https://github.com/automl/BOAH/blob/master/examples/mlp_on_digits/FMin.py), inspired by the well-known _fmin_ interface of scipy. Check out this [notebook](https://github.com/automl/BOAH/tree/master/examples/mlp_on_digits/notebook.ipynb) to see how it all comes together. 24 | 25 | ### Example 2: Proximal Policy Optimization on Cartpole 26 | 27 | [PPO on Cartpole](https://github.com/automl/BOAH/tree/master/examples/PPO_on_cartpole) optimizes the Proximal Policy Optimization on the well-known reinforcement problem Cartpole. We provide results from a HPC cluster for the optimization data and a notebook to easily reproduce analysis. 28 | 29 | ### ICML 2018 Experiments 30 | 31 | In this [series of notebooks](https://github.com/automl/BOAH/tree/master/examples/icml_2018_experiments) you can reproduce the 32 | experiments described in [BOHB's introduction in 2018 (Falkner et al.)](http://proceedings.mlr.press/v80/falkner18a.html). 33 | The results are available precomputed and ready for analysis, however you can re-run the experiments - just keep in mind, 34 | that the notebooks might run for a long time (several days) for some of the experiments. 35 | 36 | ## Requirements 37 | 38 | This is a Python3 package (developed under Python 3.6). For convenience, we recommend to install Anaconda with a recent 39 | Python 3 (see also `setup.sh`). If you want to set up the package manually, you find requirements in the `requirements.txt` (or, for the ICML 2018 Experiments, in `examples/icml_2018_experiments/icml2018requirements.txt`). 40 | 41 | ## About the tools 42 | 43 | ### ConfigSpace 44 | 45 | ConfigSpace is a python module to manage configuration spaces for algorithm configuration and hyperparameter optimization tasks. Supports all common types, like numericals, ordinals, categoricals and also log-scale sampling or conditions. Includes various scripts to translate between different text formats for configuration space description. 46 | 47 | ### HpBandSter 48 | 49 | HpBandSter (HyperBand on Steroids) implements recently published methods for optimizing hyperparameters of machine learning algorithms. One of the implemented algorithms is BOHB, combining Bayesian Optimization and HyperBand to efficiently search for well-performing configurations. Learn more about this method by reading our paper, published at ICML 2018. 50 | 51 | ### CAVE 52 | 53 | CAVE (Configuration Assessment, Visualization, and Evaluation) is designed to create comprehensive reports about an optimization process. The resulting figures and interactive plots can be used to gain insights into the parameter importance, feature importance, search behavior, and quality. Learn more about CAVE from our paper. 54 | 55 | ## License 56 | 57 | This package is free software: you can redistribute it and/or modify it under the terms of the Apache license 2.0 58 | (please see the LICENSE file). 59 | 60 | ## Contact 61 | 62 | This repository is developed by the [AutoML Group Freiburg](https://www.automl.org) 63 | 64 | ## Citing BOAH 65 | 66 | ```bibtex 67 | @journal{ 68 | title = {BOAH: A Tool Suite for Multi-Fidelity Bayesian Optimization & Analysis of Hyperparameters}, 69 | author = {M. Lindauer and K. Eggensperger and M. Feurer and A. Biedenkapp and J. Marben and P. Müller and F. Hutter}, 70 | journal = {arXiv:1908.06756 {[cs.LG]}}, 71 | date = {2019}, 72 | } 73 | ``` 74 | -------------------------------------------------------------------------------- /examples/PPO_on_cartpole/NEMO_OUTPUT/BC_1/1/2018-12-21--9-52-29-733387.out: -------------------------------------------------------------------------------- 1 | Here's what we know from the MOAB environment 2 | MOAB_MACHINE=torque 3 | SHELL=/bin/bash 4 | HOME=/home/fr/fr_fr/fr_ke1011 5 | USER=fr_ke1011 6 | MOAB_JOBID=4603311[1] 7 | HOSTNAME=n3470.nemo.privat 8 | MOAB_JOBARRAYINDEX=1 9 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_1.cmd 10 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 11 | Calling: bash -c python run_BOHB.py --n 128 --run_id 1 --shared_directory ./BC_1/ --interface boot0 12 | Here's what we know from the MOAB environment 13 | MOAB_MACHINE=torque 14 | SHELL=/bin/bash 15 | HOME=/home/fr/fr_fr/fr_ke1011 16 | USER=fr_ke1011 17 | MOAB_JOBID=4603311[2] 18 | HOSTNAME=n3470.nemo.privat 19 | MOAB_JOBARRAYINDEX=2 20 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_1.cmd 21 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 22 | Calling: bash -c python run_BOHB.py --n 128 --run_id 1 --shared_directory ./BC_1/ --interface boot0 --worker 23 | Here's what we know from the MOAB environment 24 | MOAB_MACHINE=torque 25 | SHELL=/bin/bash 26 | HOME=/home/fr/fr_fr/fr_ke1011 27 | USER=fr_ke1011 28 | MOAB_JOBID=4603311[3] 29 | HOSTNAME=n3470.nemo.privat 30 | MOAB_JOBARRAYINDEX=3 31 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_1.cmd 32 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 33 | Calling: bash -c python run_BOHB.py --n 128 --run_id 1 --shared_directory ./BC_1/ --interface boot0 --worker 34 | Here's what we know from the MOAB environment 35 | MOAB_MACHINE=torque 36 | SHELL=/bin/bash 37 | HOME=/home/fr/fr_fr/fr_ke1011 38 | USER=fr_ke1011 39 | MOAB_JOBID=4603311[5] 40 | HOSTNAME=n3470.nemo.privat 41 | MOAB_JOBARRAYINDEX=5 42 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_1.cmd 43 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 44 | Calling: bash -c python run_BOHB.py --n 128 --run_id 1 --shared_directory ./BC_1/ --interface boot0 --worker 45 | Here's what we know from the MOAB environment 46 | MOAB_MACHINE=torque 47 | SHELL=/bin/bash 48 | HOME=/home/fr/fr_fr/fr_ke1011 49 | USER=fr_ke1011 50 | MOAB_JOBID=4603311[4] 51 | HOSTNAME=n3470.nemo.privat 52 | MOAB_JOBARRAYINDEX=4 53 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_1.cmd 54 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 55 | Calling: bash -c python run_BOHB.py --n 128 --run_id 1 --shared_directory ./BC_1/ --interface boot0 --worker 56 | Here's what we know from the MOAB environment 57 | MOAB_MACHINE=torque 58 | SHELL=/bin/bash 59 | HOME=/home/fr/fr_fr/fr_ke1011 60 | USER=fr_ke1011 61 | MOAB_JOBID=4603311[6] 62 | HOSTNAME=n3470.nemo.privat 63 | MOAB_JOBARRAYINDEX=6 64 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_1.cmd 65 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 66 | Calling: bash -c python run_BOHB.py --n 128 --run_id 1 --shared_directory ./BC_1/ --interface boot0 --worker 67 | Here's what we know from the MOAB environment 68 | MOAB_MACHINE=torque 69 | SHELL=/bin/bash 70 | HOME=/home/fr/fr_fr/fr_ke1011 71 | USER=fr_ke1011 72 | MOAB_JOBID=4603311[7] 73 | HOSTNAME=n3470.nemo.privat 74 | MOAB_JOBARRAYINDEX=7 75 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_1.cmd 76 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 77 | Calling: bash -c python run_BOHB.py --n 128 --run_id 1 --shared_directory ./BC_1/ --interface boot0 --worker 78 | Here's what we know from the MOAB environment 79 | MOAB_MACHINE=torque 80 | SHELL=/bin/bash 81 | HOME=/home/fr/fr_fr/fr_ke1011 82 | USER=fr_ke1011 83 | MOAB_JOBID=4603311[8] 84 | HOSTNAME=n3470.nemo.privat 85 | MOAB_JOBARRAYINDEX=8 86 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_1.cmd 87 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 88 | Calling: bash -c python run_BOHB.py --n 128 --run_id 1 --shared_directory ./BC_1/ --interface boot0 --worker 89 | Here's what we know from the MOAB environment 90 | MOAB_MACHINE=torque 91 | SHELL=/bin/bash 92 | HOME=/home/fr/fr_fr/fr_ke1011 93 | USER=fr_ke1011 94 | MOAB_JOBID=4603311[9] 95 | HOSTNAME=n3470.nemo.privat 96 | MOAB_JOBARRAYINDEX=9 97 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_1.cmd 98 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 99 | Calling: bash -c python run_BOHB.py --n 128 --run_id 1 --shared_directory ./BC_1/ --interface boot0 --worker 100 | Here's what we know from the MOAB environment 101 | MOAB_MACHINE=torque 102 | SHELL=/bin/bash 103 | HOME=/home/fr/fr_fr/fr_ke1011 104 | USER=fr_ke1011 105 | MOAB_JOBID=4603311[10] 106 | HOSTNAME=n3470.nemo.privat 107 | MOAB_JOBARRAYINDEX=10 108 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_1.cmd 109 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 110 | Calling: bash -c python run_BOHB.py --n 128 --run_id 1 --shared_directory ./BC_1/ --interface boot0 --worker 111 | Job started at: Fri Dec 21 10:20:40 CET 2018 112 | 113 | Job started at: Fri Dec 21 10:20:50 CET 2018 114 | 115 | Job started at: Fri Dec 21 10:20:52 CET 2018 116 | 117 | Job started at: Fri Dec 21 10:21:06 CET 2018 118 | 119 | Job started at: Fri Dec 21 10:21:28 CET 2018 120 | 121 | Job started at: Fri Dec 21 10:22:18 CET 2018 122 | 123 | Job started at: Fri Dec 21 10:22:44 CET 2018 124 | 125 | Job started at: Fri Dec 21 10:26:11 CET 2018 126 | 127 | Job started at: Fri Dec 21 10:26:16 CET 2018 128 | 129 | Job started at: Fri Dec 21 10:26:58 CET 2018 130 | 131 | 132 | 133 | 134 | Job finished with exit code 0 at: Fri Dec 21 15:55:28 CET 2018 135 | Job finished with exit code 0 at: Fri Dec 21 15:55:28 CET 2018 136 | Job finished with exit code 0 at: Fri Dec 21 15:55:28 CET 2018 137 | DONE 138 | DONE 139 | DONE 140 | 141 | Job finished with exit code 0 at: Fri Dec 21 15:55:28 CET 2018 142 | DONE 143 | 144 | 145 | Job finished with exit code 0 at: Fri Dec 21 15:55:28 CET 2018 146 | DONE 147 | Job finished with exit code 0 at: Fri Dec 21 15:55:28 CET 2018 148 | DONE 149 | 150 | Job finished with exit code 0 at: Fri Dec 21 15:55:28 CET 2018 151 | DONE 152 | 153 | Job finished with exit code 0 at: Fri Dec 21 15:55:28 CET 2018 154 | DONE 155 | 156 | Job finished with exit code 0 at: Fri Dec 21 15:55:28 CET 2018 157 | DONE 158 | 159 | Job finished with exit code 0 at: Fri Dec 21 15:55:28 CET 2018 160 | DONE 161 | -------------------------------------------------------------------------------- /examples/PPO_on_cartpole/NEMO_OUTPUT/BC_1/1/job_1.cmd_2018-12-21--9-52-29-733387.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #$ -S /bin/bash 3 | 4 | cd "/work/ws/nemo/fr_ke1011-BOHB_CAVE-0" 5 | jobs_file="/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_1.cmd" 6 | 7 | echo "Here's what we know from the MOAB environment" 8 | echo MOAB_MACHINE=$MOAB_MACHINE 9 | echo SHELL=$SHELL 10 | echo HOME=$HOME 11 | echo USER=$USER 12 | echo MOAB_JOBID=$MOAB_JOBID 13 | echo HOSTNAME=$HOSTNAME 14 | echo MOAB_JOBARRAYINDEX=$MOAB_JOBARRAYINDEX 15 | echo jobs_file=${jobs_file} 16 | echo PWD=`pwd` 17 | line=`head -n $MOAB_JOBARRAYINDEX "${jobs_file}" | tail -1` # Get line of todoFilename. 18 | echo Calling: bash -c "$line" #output 19 | 20 | export PATH=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/miniconda3/bin:$PATH 21 | 22 | mkdir -p ~/.lockdir/ 23 | LOCKDIR=~/.lockdir/lock/ 24 | VENVDIR="$1" 25 | 26 | for i in {1..10000}; do 27 | if mkdir "$LOCKDIR"; then 28 | echo "Locking succeeded - Going to activate Conda" >&2 29 | source activate BC_36 30 | break 31 | 32 | else 33 | echo "Lock failed - sleep and try again" >&2 34 | pid=$$ 35 | sleeptime=$((pid%30)) 36 | 37 | sleep $((sleeptime+5))s 38 | fi 39 | done 40 | 41 | rmdir "$LOCKDIR" 42 | 43 | 44 | echo "Job started at: `date`" 45 | 46 | echo 47 | bash -c "$line" 48 | echo 49 | 50 | echo "Job finished with exit code $? at: `date`" 51 | 52 | echo DONE 53 | 54 | 55 | -------------------------------------------------------------------------------- /examples/PPO_on_cartpole/NEMO_OUTPUT/BC_1/configspace.json: -------------------------------------------------------------------------------- 1 | { 2 | "hyperparameters": [ 3 | { 4 | "name": "batch_size", 5 | "type": "uniform_int", 6 | "log": true, 7 | "lower": 8, 8 | "upper": 256, 9 | "default": 64 10 | }, 11 | { 12 | "name": "discount", 13 | "type": "uniform_float", 14 | "log": false, 15 | "lower": 0.0, 16 | "upper": 1.0, 17 | "default": 0.99 18 | }, 19 | { 20 | "name": "entropy_regularization", 21 | "type": "uniform_float", 22 | "log": false, 23 | "lower": 0.0, 24 | "upper": 1.0, 25 | "default": 0.01 26 | }, 27 | { 28 | "name": "learning_rate", 29 | "type": "uniform_float", 30 | "log": true, 31 | "lower": 1e-07, 32 | "upper": 0.1, 33 | "default": 0.001 34 | }, 35 | { 36 | "name": "likelihood_ratio_clipping", 37 | "type": "uniform_float", 38 | "log": false, 39 | "lower": 0.0, 40 | "upper": 1.0, 41 | "default": 0.2 42 | }, 43 | { 44 | "name": "n_units_1", 45 | "type": "uniform_int", 46 | "log": true, 47 | "lower": 8, 48 | "upper": 128, 49 | "default": 64 50 | }, 51 | { 52 | "name": "n_units_2", 53 | "type": "uniform_int", 54 | "log": true, 55 | "lower": 8, 56 | "upper": 128, 57 | "default": 64 58 | } 59 | ], 60 | "conditions": [], 61 | "forbiddens": [], 62 | "python_module_version": "0.4.7", 63 | "json_format_version": 0.1 64 | } -------------------------------------------------------------------------------- /examples/PPO_on_cartpole/NEMO_OUTPUT/BC_1/results.pkl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/automl/BOAH/7bbc5b97ccbb742c32dc8e6318ed628414cb86dc/examples/PPO_on_cartpole/NEMO_OUTPUT/BC_1/results.pkl -------------------------------------------------------------------------------- /examples/PPO_on_cartpole/NEMO_OUTPUT/BC_10/10/2018-12-21--13-22-51-780339.out: -------------------------------------------------------------------------------- 1 | Here's what we know from the MOAB environment 2 | MOAB_MACHINE=torque 3 | SHELL=/bin/bash 4 | HOME=/home/fr/fr_fr/fr_ke1011 5 | USER=fr_ke1011 6 | MOAB_JOBID=4606562[1] 7 | HOSTNAME=n4529.nemo.privat 8 | MOAB_JOBARRAYINDEX=1 9 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_10.cmd 10 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 11 | Calling: bash -c python run_BOHB.py --n 128 --run_id 10 --shared_directory ./BC_10/ --interface boot0 12 | Here's what we know from the MOAB environment 13 | MOAB_MACHINE=torque 14 | SHELL=/bin/bash 15 | HOME=/home/fr/fr_fr/fr_ke1011 16 | USER=fr_ke1011 17 | MOAB_JOBID=4606562[2] 18 | HOSTNAME=n4529.nemo.privat 19 | MOAB_JOBARRAYINDEX=2 20 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_10.cmd 21 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 22 | Calling: bash -c python run_BOHB.py --n 128 --run_id 10 --shared_directory ./BC_10/ --interface boot0 --worker 23 | Here's what we know from the MOAB environment 24 | MOAB_MACHINE=torque 25 | SHELL=/bin/bash 26 | HOME=/home/fr/fr_fr/fr_ke1011 27 | USER=fr_ke1011 28 | MOAB_JOBID=4606562[3] 29 | HOSTNAME=n4529.nemo.privat 30 | MOAB_JOBARRAYINDEX=3 31 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_10.cmd 32 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 33 | Calling: bash -c python run_BOHB.py --n 128 --run_id 10 --shared_directory ./BC_10/ --interface boot0 --worker 34 | Here's what we know from the MOAB environment 35 | MOAB_MACHINE=torque 36 | SHELL=/bin/bash 37 | HOME=/home/fr/fr_fr/fr_ke1011 38 | USER=fr_ke1011 39 | MOAB_JOBID=4606562[4] 40 | HOSTNAME=n4529.nemo.privat 41 | MOAB_JOBARRAYINDEX=4 42 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_10.cmd 43 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 44 | Calling: bash -c python run_BOHB.py --n 128 --run_id 10 --shared_directory ./BC_10/ --interface boot0 --worker 45 | Here's what we know from the MOAB environment 46 | MOAB_MACHINE=torque 47 | SHELL=/bin/bash 48 | HOME=/home/fr/fr_fr/fr_ke1011 49 | USER=fr_ke1011 50 | MOAB_JOBID=4606562[5] 51 | HOSTNAME=n4529.nemo.privat 52 | MOAB_JOBARRAYINDEX=5 53 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_10.cmd 54 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 55 | Calling: bash -c python run_BOHB.py --n 128 --run_id 10 --shared_directory ./BC_10/ --interface boot0 --worker 56 | Here's what we know from the MOAB environment 57 | MOAB_MACHINE=torque 58 | SHELL=/bin/bash 59 | HOME=/home/fr/fr_fr/fr_ke1011 60 | USER=fr_ke1011 61 | MOAB_JOBID=4606562[6] 62 | HOSTNAME=n4529.nemo.privat 63 | MOAB_JOBARRAYINDEX=6 64 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_10.cmd 65 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 66 | Calling: bash -c python run_BOHB.py --n 128 --run_id 10 --shared_directory ./BC_10/ --interface boot0 --worker 67 | Here's what we know from the MOAB environment 68 | MOAB_MACHINE=torque 69 | SHELL=/bin/bash 70 | HOME=/home/fr/fr_fr/fr_ke1011 71 | USER=fr_ke1011 72 | MOAB_JOBID=4606562[7] 73 | HOSTNAME=n4529.nemo.privat 74 | MOAB_JOBARRAYINDEX=7 75 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_10.cmd 76 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 77 | Calling: bash -c python run_BOHB.py --n 128 --run_id 10 --shared_directory ./BC_10/ --interface boot0 --worker 78 | Here's what we know from the MOAB environment 79 | MOAB_MACHINE=torque 80 | SHELL=/bin/bash 81 | HOME=/home/fr/fr_fr/fr_ke1011 82 | USER=fr_ke1011 83 | MOAB_JOBID=4606562[8] 84 | HOSTNAME=n4529.nemo.privat 85 | MOAB_JOBARRAYINDEX=8 86 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_10.cmd 87 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 88 | Calling: bash -c python run_BOHB.py --n 128 --run_id 10 --shared_directory ./BC_10/ --interface boot0 --worker 89 | Here's what we know from the MOAB environment 90 | MOAB_MACHINE=torque 91 | SHELL=/bin/bash 92 | HOME=/home/fr/fr_fr/fr_ke1011 93 | USER=fr_ke1011 94 | MOAB_JOBID=4606562[9] 95 | HOSTNAME=n4529.nemo.privat 96 | MOAB_JOBARRAYINDEX=9 97 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_10.cmd 98 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 99 | Calling: bash -c python run_BOHB.py --n 128 --run_id 10 --shared_directory ./BC_10/ --interface boot0 --worker 100 | Here's what we know from the MOAB environment 101 | MOAB_MACHINE=torque 102 | SHELL=/bin/bash 103 | HOME=/home/fr/fr_fr/fr_ke1011 104 | USER=fr_ke1011 105 | MOAB_JOBID=4606562[10] 106 | HOSTNAME=n4529.nemo.privat 107 | MOAB_JOBARRAYINDEX=10 108 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_10.cmd 109 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 110 | Calling: bash -c python run_BOHB.py --n 128 --run_id 10 --shared_directory ./BC_10/ --interface boot0 --worker 111 | Job started at: Fri Dec 21 15:25:19 CET 2018 112 | 113 | Job started at: Fri Dec 21 15:25:33 CET 2018 114 | 115 | Job started at: Fri Dec 21 15:25:56 CET 2018 116 | 117 | Job started at: Fri Dec 21 15:26:02 CET 2018 118 | 119 | Job started at: Fri Dec 21 15:26:07 CET 2018 120 | 121 | Job started at: Fri Dec 21 15:26:14 CET 2018 122 | 123 | Job started at: Fri Dec 21 15:26:21 CET 2018 124 | 125 | Job started at: Fri Dec 21 15:26:26 CET 2018 126 | 127 | Job started at: Fri Dec 21 15:26:44 CET 2018 128 | 129 | Job started at: Fri Dec 21 15:27:04 CET 2018 130 | 131 | 132 | 133 | 134 | Job finished with exit code 0 at: Fri Dec 21 20:51:15 CET 2018 135 | Job finished with exit code 0 at: Fri Dec 21 20:51:15 CET 2018 136 | Job finished with exit code 0 at: Fri Dec 21 20:51:15 CET 2018 137 | DONE 138 | DONE 139 | DONE 140 | 141 | Job finished with exit code 0 at: Fri Dec 21 20:51:15 CET 2018 142 | DONE 143 | 144 | 145 | 146 | Job finished with exit code 0 at: Fri Dec 21 20:51:15 CET 2018 147 | DONE 148 | 149 | Job finished with exit code 0 at: Fri Dec 21 20:51:15 CET 2018 150 | DONE 151 | Job finished with exit code 0 at: Fri Dec 21 20:51:15 CET 2018 152 | DONE 153 | Job finished with exit code 0 at: Fri Dec 21 20:51:15 CET 2018 154 | DONE 155 | 156 | Job finished with exit code 0 at: Fri Dec 21 20:51:15 CET 2018 157 | DONE 158 | 159 | Job finished with exit code 0 at: Fri Dec 21 20:51:15 CET 2018 160 | DONE 161 | -------------------------------------------------------------------------------- /examples/PPO_on_cartpole/NEMO_OUTPUT/BC_10/10/job_10.cmd_2018-12-21--13-22-51-780339.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #$ -S /bin/bash 3 | 4 | cd "/work/ws/nemo/fr_ke1011-BOHB_CAVE-0" 5 | jobs_file="/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_10.cmd" 6 | 7 | echo "Here's what we know from the MOAB environment" 8 | echo MOAB_MACHINE=$MOAB_MACHINE 9 | echo SHELL=$SHELL 10 | echo HOME=$HOME 11 | echo USER=$USER 12 | echo MOAB_JOBID=$MOAB_JOBID 13 | echo HOSTNAME=$HOSTNAME 14 | echo MOAB_JOBARRAYINDEX=$MOAB_JOBARRAYINDEX 15 | echo jobs_file=${jobs_file} 16 | echo PWD=`pwd` 17 | line=`head -n $MOAB_JOBARRAYINDEX "${jobs_file}" | tail -1` # Get line of todoFilename. 18 | echo Calling: bash -c "$line" #output 19 | 20 | export PATH=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/miniconda3/bin:$PATH 21 | 22 | mkdir -p ~/.lockdir/ 23 | LOCKDIR=~/.lockdir/lock/ 24 | VENVDIR="$1" 25 | 26 | for i in {1..10000}; do 27 | if mkdir "$LOCKDIR"; then 28 | echo "Locking succeeded - Going to activate Conda" >&2 29 | source activate BC_36 30 | break 31 | 32 | else 33 | echo "Lock failed - sleep and try again" >&2 34 | pid=$$ 35 | sleeptime=$((pid%30)) 36 | 37 | sleep $((sleeptime+5))s 38 | fi 39 | done 40 | 41 | rmdir "$LOCKDIR" 42 | 43 | 44 | echo "Job started at: `date`" 45 | 46 | echo 47 | bash -c "$line" 48 | echo 49 | 50 | echo "Job finished with exit code $? at: `date`" 51 | 52 | echo DONE 53 | 54 | 55 | -------------------------------------------------------------------------------- /examples/PPO_on_cartpole/NEMO_OUTPUT/BC_10/configspace.json: -------------------------------------------------------------------------------- 1 | { 2 | "hyperparameters": [ 3 | { 4 | "name": "batch_size", 5 | "type": "uniform_int", 6 | "log": true, 7 | "lower": 8, 8 | "upper": 256, 9 | "default": 64 10 | }, 11 | { 12 | "name": "discount", 13 | "type": "uniform_float", 14 | "log": false, 15 | "lower": 0.0, 16 | "upper": 1.0, 17 | "default": 0.99 18 | }, 19 | { 20 | "name": "entropy_regularization", 21 | "type": "uniform_float", 22 | "log": false, 23 | "lower": 0.0, 24 | "upper": 1.0, 25 | "default": 0.01 26 | }, 27 | { 28 | "name": "learning_rate", 29 | "type": "uniform_float", 30 | "log": true, 31 | "lower": 1e-07, 32 | "upper": 0.1, 33 | "default": 0.001 34 | }, 35 | { 36 | "name": "likelihood_ratio_clipping", 37 | "type": "uniform_float", 38 | "log": false, 39 | "lower": 0.0, 40 | "upper": 1.0, 41 | "default": 0.2 42 | }, 43 | { 44 | "name": "n_units_1", 45 | "type": "uniform_int", 46 | "log": true, 47 | "lower": 8, 48 | "upper": 128, 49 | "default": 64 50 | }, 51 | { 52 | "name": "n_units_2", 53 | "type": "uniform_int", 54 | "log": true, 55 | "lower": 8, 56 | "upper": 128, 57 | "default": 64 58 | } 59 | ], 60 | "conditions": [], 61 | "forbiddens": [], 62 | "python_module_version": "0.4.7", 63 | "json_format_version": 0.1 64 | } -------------------------------------------------------------------------------- /examples/PPO_on_cartpole/NEMO_OUTPUT/BC_10/results.pkl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/automl/BOAH/7bbc5b97ccbb742c32dc8e6318ed628414cb86dc/examples/PPO_on_cartpole/NEMO_OUTPUT/BC_10/results.pkl -------------------------------------------------------------------------------- /examples/PPO_on_cartpole/NEMO_OUTPUT/BC_2/2/2018-12-21--9-52-30-296000.out: -------------------------------------------------------------------------------- 1 | Here's what we know from the MOAB environment 2 | MOAB_MACHINE=torque 3 | SHELL=/bin/bash 4 | HOME=/home/fr/fr_fr/fr_ke1011 5 | USER=fr_ke1011 6 | MOAB_JOBID=4603312[1] 7 | HOSTNAME=n3470.nemo.privat 8 | MOAB_JOBARRAYINDEX=1 9 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_2.cmd 10 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 11 | Calling: bash -c python run_BOHB.py --n 128 --run_id 2 --shared_directory ./BC_2/ --interface boot0 12 | Here's what we know from the MOAB environment 13 | MOAB_MACHINE=torque 14 | SHELL=/bin/bash 15 | HOME=/home/fr/fr_fr/fr_ke1011 16 | USER=fr_ke1011 17 | MOAB_JOBID=4603312[2] 18 | HOSTNAME=n3470.nemo.privat 19 | MOAB_JOBARRAYINDEX=2 20 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_2.cmd 21 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 22 | Calling: bash -c python run_BOHB.py --n 128 --run_id 2 --shared_directory ./BC_2/ --interface boot0 --worker 23 | Here's what we know from the MOAB environment 24 | MOAB_MACHINE=torque 25 | SHELL=/bin/bash 26 | HOME=/home/fr/fr_fr/fr_ke1011 27 | USER=fr_ke1011 28 | MOAB_JOBID=4603312[3] 29 | HOSTNAME=n3470.nemo.privat 30 | MOAB_JOBARRAYINDEX=3 31 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_2.cmd 32 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 33 | Calling: bash -c python run_BOHB.py --n 128 --run_id 2 --shared_directory ./BC_2/ --interface boot0 --worker 34 | Here's what we know from the MOAB environment 35 | MOAB_MACHINE=torque 36 | SHELL=/bin/bash 37 | HOME=/home/fr/fr_fr/fr_ke1011 38 | USER=fr_ke1011 39 | MOAB_JOBID=4603312[4] 40 | HOSTNAME=n3470.nemo.privat 41 | MOAB_JOBARRAYINDEX=4 42 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_2.cmd 43 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 44 | Calling: bash -c python run_BOHB.py --n 128 --run_id 2 --shared_directory ./BC_2/ --interface boot0 --worker 45 | Here's what we know from the MOAB environment 46 | MOAB_MACHINE=torque 47 | SHELL=/bin/bash 48 | HOME=/home/fr/fr_fr/fr_ke1011 49 | USER=fr_ke1011 50 | MOAB_JOBID=4603312[5] 51 | HOSTNAME=n3470.nemo.privat 52 | MOAB_JOBARRAYINDEX=5 53 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_2.cmd 54 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 55 | Calling: bash -c python run_BOHB.py --n 128 --run_id 2 --shared_directory ./BC_2/ --interface boot0 --worker 56 | Here's what we know from the MOAB environment 57 | MOAB_MACHINE=torque 58 | SHELL=/bin/bash 59 | HOME=/home/fr/fr_fr/fr_ke1011 60 | USER=fr_ke1011 61 | MOAB_JOBID=4603312[6] 62 | HOSTNAME=n3470.nemo.privat 63 | MOAB_JOBARRAYINDEX=6 64 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_2.cmd 65 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 66 | Calling: bash -c python run_BOHB.py --n 128 --run_id 2 --shared_directory ./BC_2/ --interface boot0 --worker 67 | Here's what we know from the MOAB environment 68 | MOAB_MACHINE=torque 69 | SHELL=/bin/bash 70 | HOME=/home/fr/fr_fr/fr_ke1011 71 | USER=fr_ke1011 72 | MOAB_JOBID=4603312[7] 73 | HOSTNAME=n3470.nemo.privat 74 | MOAB_JOBARRAYINDEX=7 75 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_2.cmd 76 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 77 | Calling: bash -c python run_BOHB.py --n 128 --run_id 2 --shared_directory ./BC_2/ --interface boot0 --worker 78 | Here's what we know from the MOAB environment 79 | MOAB_MACHINE=torque 80 | SHELL=/bin/bash 81 | HOME=/home/fr/fr_fr/fr_ke1011 82 | USER=fr_ke1011 83 | MOAB_JOBID=4603312[8] 84 | HOSTNAME=n3470.nemo.privat 85 | MOAB_JOBARRAYINDEX=8 86 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_2.cmd 87 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 88 | Calling: bash -c python run_BOHB.py --n 128 --run_id 2 --shared_directory ./BC_2/ --interface boot0 --worker 89 | Here's what we know from the MOAB environment 90 | MOAB_MACHINE=torque 91 | SHELL=/bin/bash 92 | HOME=/home/fr/fr_fr/fr_ke1011 93 | USER=fr_ke1011 94 | MOAB_JOBID=4603312[9] 95 | HOSTNAME=n3470.nemo.privat 96 | MOAB_JOBARRAYINDEX=9 97 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_2.cmd 98 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 99 | Calling: bash -c python run_BOHB.py --n 128 --run_id 2 --shared_directory ./BC_2/ --interface boot0 --worker 100 | Here's what we know from the MOAB environment 101 | MOAB_MACHINE=torque 102 | SHELL=/bin/bash 103 | HOME=/home/fr/fr_fr/fr_ke1011 104 | USER=fr_ke1011 105 | MOAB_JOBID=4603312[10] 106 | HOSTNAME=n3470.nemo.privat 107 | MOAB_JOBARRAYINDEX=10 108 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_2.cmd 109 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 110 | Calling: bash -c python run_BOHB.py --n 128 --run_id 2 --shared_directory ./BC_2/ --interface boot0 --worker 111 | Job started at: Fri Dec 21 10:20:38 CET 2018 112 | 113 | Job started at: Fri Dec 21 10:21:39 CET 2018 114 | 115 | Job started at: Fri Dec 21 10:22:59 CET 2018 116 | 117 | Job started at: Fri Dec 21 10:23:01 CET 2018 118 | 119 | Job started at: Fri Dec 21 10:23:10 CET 2018 120 | 121 | Job started at: Fri Dec 21 10:23:13 CET 2018 122 | 123 | Job started at: Fri Dec 21 10:25:31 CET 2018 124 | 125 | Job started at: Fri Dec 21 10:25:52 CET 2018 126 | 127 | Job started at: Fri Dec 21 10:26:08 CET 2018 128 | 129 | Job started at: Fri Dec 21 10:27:10 CET 2018 130 | 131 | 132 | 133 | Job finished with exit code 0 at: Fri Dec 21 15:18:00 CET 2018 134 | Job finished with exit code 0 at: Fri Dec 21 15:18:00 CET 2018 135 | DONE 136 | DONE 137 | 138 | Job finished with exit code 0 at: Fri Dec 21 15:18:00 CET 2018 139 | DONE 140 | 141 | Job finished with exit code 0 at: Fri Dec 21 15:18:00 CET 2018 142 | DONE 143 | 144 | Job finished with exit code 0 at: Fri Dec 21 15:18:00 CET 2018 145 | DONE 146 | 147 | 148 | Job finished with exit code 0 at: Fri Dec 21 15:18:00 CET 2018 149 | Job finished with exit code 0 at: Fri Dec 21 15:18:00 CET 2018 150 | DONE 151 | DONE 152 | 153 | Job finished with exit code 0 at: Fri Dec 21 15:18:00 CET 2018 154 | DONE 155 | 156 | Job finished with exit code 0 at: Fri Dec 21 15:18:00 CET 2018 157 | DONE 158 | 159 | Job finished with exit code 0 at: Fri Dec 21 15:18:01 CET 2018 160 | DONE 161 | -------------------------------------------------------------------------------- /examples/PPO_on_cartpole/NEMO_OUTPUT/BC_2/2/job_2.cmd_2018-12-21--9-52-30-296000.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #$ -S /bin/bash 3 | 4 | cd "/work/ws/nemo/fr_ke1011-BOHB_CAVE-0" 5 | jobs_file="/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_2.cmd" 6 | 7 | echo "Here's what we know from the MOAB environment" 8 | echo MOAB_MACHINE=$MOAB_MACHINE 9 | echo SHELL=$SHELL 10 | echo HOME=$HOME 11 | echo USER=$USER 12 | echo MOAB_JOBID=$MOAB_JOBID 13 | echo HOSTNAME=$HOSTNAME 14 | echo MOAB_JOBARRAYINDEX=$MOAB_JOBARRAYINDEX 15 | echo jobs_file=${jobs_file} 16 | echo PWD=`pwd` 17 | line=`head -n $MOAB_JOBARRAYINDEX "${jobs_file}" | tail -1` # Get line of todoFilename. 18 | echo Calling: bash -c "$line" #output 19 | 20 | export PATH=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/miniconda3/bin:$PATH 21 | 22 | mkdir -p ~/.lockdir/ 23 | LOCKDIR=~/.lockdir/lock/ 24 | VENVDIR="$1" 25 | 26 | for i in {1..10000}; do 27 | if mkdir "$LOCKDIR"; then 28 | echo "Locking succeeded - Going to activate Conda" >&2 29 | source activate BC_36 30 | break 31 | 32 | else 33 | echo "Lock failed - sleep and try again" >&2 34 | pid=$$ 35 | sleeptime=$((pid%30)) 36 | 37 | sleep $((sleeptime+5))s 38 | fi 39 | done 40 | 41 | rmdir "$LOCKDIR" 42 | 43 | 44 | echo "Job started at: `date`" 45 | 46 | echo 47 | bash -c "$line" 48 | echo 49 | 50 | echo "Job finished with exit code $? at: `date`" 51 | 52 | echo DONE 53 | 54 | 55 | -------------------------------------------------------------------------------- /examples/PPO_on_cartpole/NEMO_OUTPUT/BC_2/configspace.json: -------------------------------------------------------------------------------- 1 | { 2 | "hyperparameters": [ 3 | { 4 | "name": "batch_size", 5 | "type": "uniform_int", 6 | "log": true, 7 | "lower": 8, 8 | "upper": 256, 9 | "default": 64 10 | }, 11 | { 12 | "name": "discount", 13 | "type": "uniform_float", 14 | "log": false, 15 | "lower": 0.0, 16 | "upper": 1.0, 17 | "default": 0.99 18 | }, 19 | { 20 | "name": "entropy_regularization", 21 | "type": "uniform_float", 22 | "log": false, 23 | "lower": 0.0, 24 | "upper": 1.0, 25 | "default": 0.01 26 | }, 27 | { 28 | "name": "learning_rate", 29 | "type": "uniform_float", 30 | "log": true, 31 | "lower": 1e-07, 32 | "upper": 0.1, 33 | "default": 0.001 34 | }, 35 | { 36 | "name": "likelihood_ratio_clipping", 37 | "type": "uniform_float", 38 | "log": false, 39 | "lower": 0.0, 40 | "upper": 1.0, 41 | "default": 0.2 42 | }, 43 | { 44 | "name": "n_units_1", 45 | "type": "uniform_int", 46 | "log": true, 47 | "lower": 8, 48 | "upper": 128, 49 | "default": 64 50 | }, 51 | { 52 | "name": "n_units_2", 53 | "type": "uniform_int", 54 | "log": true, 55 | "lower": 8, 56 | "upper": 128, 57 | "default": 64 58 | } 59 | ], 60 | "conditions": [], 61 | "forbiddens": [], 62 | "python_module_version": "0.4.7", 63 | "json_format_version": 0.1 64 | } -------------------------------------------------------------------------------- /examples/PPO_on_cartpole/NEMO_OUTPUT/BC_2/results.pkl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/automl/BOAH/7bbc5b97ccbb742c32dc8e6318ed628414cb86dc/examples/PPO_on_cartpole/NEMO_OUTPUT/BC_2/results.pkl -------------------------------------------------------------------------------- /examples/PPO_on_cartpole/NEMO_OUTPUT/BC_3/3/2018-12-21--9-52-30-868730.out: -------------------------------------------------------------------------------- 1 | Here's what we know from the MOAB environment 2 | MOAB_MACHINE=torque 3 | SHELL=/bin/bash 4 | HOME=/home/fr/fr_fr/fr_ke1011 5 | USER=fr_ke1011 6 | MOAB_JOBID=4603313[1] 7 | HOSTNAME=n3732.nemo.privat 8 | MOAB_JOBARRAYINDEX=1 9 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_3.cmd 10 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 11 | Calling: bash -c python run_BOHB.py --n 128 --run_id 3 --shared_directory ./BC_3/ --interface boot0 12 | Here's what we know from the MOAB environment 13 | MOAB_MACHINE=torque 14 | SHELL=/bin/bash 15 | HOME=/home/fr/fr_fr/fr_ke1011 16 | USER=fr_ke1011 17 | MOAB_JOBID=4603313[2] 18 | HOSTNAME=n3732.nemo.privat 19 | MOAB_JOBARRAYINDEX=2 20 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_3.cmd 21 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 22 | Calling: bash -c python run_BOHB.py --n 128 --run_id 3 --shared_directory ./BC_3/ --interface boot0 --worker 23 | Here's what we know from the MOAB environment 24 | MOAB_MACHINE=torque 25 | SHELL=/bin/bash 26 | HOME=/home/fr/fr_fr/fr_ke1011 27 | USER=fr_ke1011 28 | MOAB_JOBID=4603313[3] 29 | HOSTNAME=n3732.nemo.privat 30 | MOAB_JOBARRAYINDEX=3 31 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_3.cmd 32 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 33 | Calling: bash -c python run_BOHB.py --n 128 --run_id 3 --shared_directory ./BC_3/ --interface boot0 --worker 34 | Here's what we know from the MOAB environment 35 | MOAB_MACHINE=torque 36 | SHELL=/bin/bash 37 | HOME=/home/fr/fr_fr/fr_ke1011 38 | USER=fr_ke1011 39 | MOAB_JOBID=4603313[4] 40 | HOSTNAME=n3732.nemo.privat 41 | MOAB_JOBARRAYINDEX=4 42 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_3.cmd 43 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 44 | Calling: bash -c python run_BOHB.py --n 128 --run_id 3 --shared_directory ./BC_3/ --interface boot0 --worker 45 | Here's what we know from the MOAB environment 46 | MOAB_MACHINE=torque 47 | SHELL=/bin/bash 48 | HOME=/home/fr/fr_fr/fr_ke1011 49 | USER=fr_ke1011 50 | MOAB_JOBID=4603313[5] 51 | HOSTNAME=n3732.nemo.privat 52 | MOAB_JOBARRAYINDEX=5 53 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_3.cmd 54 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 55 | Calling: bash -c python run_BOHB.py --n 128 --run_id 3 --shared_directory ./BC_3/ --interface boot0 --worker 56 | Here's what we know from the MOAB environment 57 | MOAB_MACHINE=torque 58 | SHELL=/bin/bash 59 | HOME=/home/fr/fr_fr/fr_ke1011 60 | USER=fr_ke1011 61 | MOAB_JOBID=4603313[6] 62 | HOSTNAME=n3732.nemo.privat 63 | MOAB_JOBARRAYINDEX=6 64 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_3.cmd 65 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 66 | Calling: bash -c python run_BOHB.py --n 128 --run_id 3 --shared_directory ./BC_3/ --interface boot0 --worker 67 | Here's what we know from the MOAB environment 68 | MOAB_MACHINE=torque 69 | SHELL=/bin/bash 70 | HOME=/home/fr/fr_fr/fr_ke1011 71 | USER=fr_ke1011 72 | MOAB_JOBID=4603313[7] 73 | HOSTNAME=n3732.nemo.privat 74 | MOAB_JOBARRAYINDEX=7 75 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_3.cmd 76 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 77 | Calling: bash -c python run_BOHB.py --n 128 --run_id 3 --shared_directory ./BC_3/ --interface boot0 --worker 78 | Here's what we know from the MOAB environment 79 | MOAB_MACHINE=torque 80 | SHELL=/bin/bash 81 | HOME=/home/fr/fr_fr/fr_ke1011 82 | USER=fr_ke1011 83 | MOAB_JOBID=4603313[8] 84 | HOSTNAME=n3732.nemo.privat 85 | MOAB_JOBARRAYINDEX=8 86 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_3.cmd 87 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 88 | Calling: bash -c python run_BOHB.py --n 128 --run_id 3 --shared_directory ./BC_3/ --interface boot0 --worker 89 | Here's what we know from the MOAB environment 90 | MOAB_MACHINE=torque 91 | SHELL=/bin/bash 92 | HOME=/home/fr/fr_fr/fr_ke1011 93 | USER=fr_ke1011 94 | MOAB_JOBID=4603313[9] 95 | HOSTNAME=n3732.nemo.privat 96 | MOAB_JOBARRAYINDEX=9 97 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_3.cmd 98 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 99 | Calling: bash -c python run_BOHB.py --n 128 --run_id 3 --shared_directory ./BC_3/ --interface boot0 --worker 100 | Here's what we know from the MOAB environment 101 | MOAB_MACHINE=torque 102 | SHELL=/bin/bash 103 | HOME=/home/fr/fr_fr/fr_ke1011 104 | USER=fr_ke1011 105 | MOAB_JOBID=4603313[10] 106 | HOSTNAME=n3732.nemo.privat 107 | MOAB_JOBARRAYINDEX=10 108 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_3.cmd 109 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 110 | Calling: bash -c python run_BOHB.py --n 128 --run_id 3 --shared_directory ./BC_3/ --interface boot0 --worker 111 | Job started at: Fri Dec 21 10:20:59 CET 2018 112 | 113 | Job started at: Fri Dec 21 10:21:14 CET 2018 114 | 115 | Job started at: Fri Dec 21 10:21:19 CET 2018 116 | 117 | Job started at: Fri Dec 21 10:21:34 CET 2018 118 | 119 | Job started at: Fri Dec 21 10:21:46 CET 2018 120 | 121 | Job started at: Fri Dec 21 10:21:54 CET 2018 122 | 123 | Job started at: Fri Dec 21 10:23:59 CET 2018 124 | 125 | Job started at: Fri Dec 21 10:25:26 CET 2018 126 | 127 | Job started at: Fri Dec 21 10:25:55 CET 2018 128 | 129 | Job started at: Fri Dec 21 10:26:41 CET 2018 130 | 131 | 132 | Job finished with exit code 0 at: Fri Dec 21 16:08:27 CET 2018 133 | DONE 134 | 135 | Job finished with exit code 0 at: Fri Dec 21 16:08:27 CET 2018 136 | DONE 137 | 138 | 139 | Job finished with exit code 0 at: Fri Dec 21 16:08:27 CET 2018 140 | DONE 141 | Job finished with exit code 0 at: Fri Dec 21 16:08:27 CET 2018 142 | DONE 143 | 144 | 145 | Job finished with exit code 0 at: Fri Dec 21 16:08:27 CET 2018 146 | DONE 147 | Job finished with exit code 0 at: Fri Dec 21 16:08:27 CET 2018 148 | DONE 149 | 150 | Job finished with exit code 0 at: Fri Dec 21 16:08:27 CET 2018 151 | DONE 152 | 153 | Job finished with exit code 0 at: Fri Dec 21 16:08:28 CET 2018 154 | DONE 155 | 156 | Job finished with exit code 0 at: Fri Dec 21 16:08:28 CET 2018 157 | DONE 158 | 159 | Job finished with exit code 0 at: Fri Dec 21 16:08:28 CET 2018 160 | DONE 161 | -------------------------------------------------------------------------------- /examples/PPO_on_cartpole/NEMO_OUTPUT/BC_3/3/job_3.cmd_2018-12-21--9-52-30-868730.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #$ -S /bin/bash 3 | 4 | cd "/work/ws/nemo/fr_ke1011-BOHB_CAVE-0" 5 | jobs_file="/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_3.cmd" 6 | 7 | echo "Here's what we know from the MOAB environment" 8 | echo MOAB_MACHINE=$MOAB_MACHINE 9 | echo SHELL=$SHELL 10 | echo HOME=$HOME 11 | echo USER=$USER 12 | echo MOAB_JOBID=$MOAB_JOBID 13 | echo HOSTNAME=$HOSTNAME 14 | echo MOAB_JOBARRAYINDEX=$MOAB_JOBARRAYINDEX 15 | echo jobs_file=${jobs_file} 16 | echo PWD=`pwd` 17 | line=`head -n $MOAB_JOBARRAYINDEX "${jobs_file}" | tail -1` # Get line of todoFilename. 18 | echo Calling: bash -c "$line" #output 19 | 20 | export PATH=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/miniconda3/bin:$PATH 21 | 22 | mkdir -p ~/.lockdir/ 23 | LOCKDIR=~/.lockdir/lock/ 24 | VENVDIR="$1" 25 | 26 | for i in {1..10000}; do 27 | if mkdir "$LOCKDIR"; then 28 | echo "Locking succeeded - Going to activate Conda" >&2 29 | source activate BC_36 30 | break 31 | 32 | else 33 | echo "Lock failed - sleep and try again" >&2 34 | pid=$$ 35 | sleeptime=$((pid%30)) 36 | 37 | sleep $((sleeptime+5))s 38 | fi 39 | done 40 | 41 | rmdir "$LOCKDIR" 42 | 43 | 44 | echo "Job started at: `date`" 45 | 46 | echo 47 | bash -c "$line" 48 | echo 49 | 50 | echo "Job finished with exit code $? at: `date`" 51 | 52 | echo DONE 53 | 54 | 55 | -------------------------------------------------------------------------------- /examples/PPO_on_cartpole/NEMO_OUTPUT/BC_3/configspace.json: -------------------------------------------------------------------------------- 1 | { 2 | "hyperparameters": [ 3 | { 4 | "name": "batch_size", 5 | "type": "uniform_int", 6 | "log": true, 7 | "lower": 8, 8 | "upper": 256, 9 | "default": 64 10 | }, 11 | { 12 | "name": "discount", 13 | "type": "uniform_float", 14 | "log": false, 15 | "lower": 0.0, 16 | "upper": 1.0, 17 | "default": 0.99 18 | }, 19 | { 20 | "name": "entropy_regularization", 21 | "type": "uniform_float", 22 | "log": false, 23 | "lower": 0.0, 24 | "upper": 1.0, 25 | "default": 0.01 26 | }, 27 | { 28 | "name": "learning_rate", 29 | "type": "uniform_float", 30 | "log": true, 31 | "lower": 1e-07, 32 | "upper": 0.1, 33 | "default": 0.001 34 | }, 35 | { 36 | "name": "likelihood_ratio_clipping", 37 | "type": "uniform_float", 38 | "log": false, 39 | "lower": 0.0, 40 | "upper": 1.0, 41 | "default": 0.2 42 | }, 43 | { 44 | "name": "n_units_1", 45 | "type": "uniform_int", 46 | "log": true, 47 | "lower": 8, 48 | "upper": 128, 49 | "default": 64 50 | }, 51 | { 52 | "name": "n_units_2", 53 | "type": "uniform_int", 54 | "log": true, 55 | "lower": 8, 56 | "upper": 128, 57 | "default": 64 58 | } 59 | ], 60 | "conditions": [], 61 | "forbiddens": [], 62 | "python_module_version": "0.4.7", 63 | "json_format_version": 0.1 64 | } -------------------------------------------------------------------------------- /examples/PPO_on_cartpole/NEMO_OUTPUT/BC_3/results.pkl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/automl/BOAH/7bbc5b97ccbb742c32dc8e6318ed628414cb86dc/examples/PPO_on_cartpole/NEMO_OUTPUT/BC_3/results.pkl -------------------------------------------------------------------------------- /examples/PPO_on_cartpole/NEMO_OUTPUT/BC_4/4/2018-12-21--9-52-31-446298.out: -------------------------------------------------------------------------------- 1 | Here's what we know from the MOAB environment 2 | MOAB_MACHINE=torque 3 | SHELL=/bin/bash 4 | HOME=/home/fr/fr_fr/fr_ke1011 5 | USER=fr_ke1011 6 | MOAB_JOBID=4603314[1] 7 | HOSTNAME=n3732.nemo.privat 8 | MOAB_JOBARRAYINDEX=1 9 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_4.cmd 10 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 11 | Calling: bash -c python run_BOHB.py --n 128 --run_id 4 --shared_directory ./BC_4/ --interface boot0 12 | Here's what we know from the MOAB environment 13 | MOAB_MACHINE=torque 14 | SHELL=/bin/bash 15 | HOME=/home/fr/fr_fr/fr_ke1011 16 | USER=fr_ke1011 17 | MOAB_JOBID=4603314[2] 18 | HOSTNAME=n3732.nemo.privat 19 | MOAB_JOBARRAYINDEX=2 20 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_4.cmd 21 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 22 | Calling: bash -c python run_BOHB.py --n 128 --run_id 4 --shared_directory ./BC_4/ --interface boot0 --worker 23 | Here's what we know from the MOAB environment 24 | MOAB_MACHINE=torque 25 | SHELL=/bin/bash 26 | HOME=/home/fr/fr_fr/fr_ke1011 27 | USER=fr_ke1011 28 | MOAB_JOBID=4603314[3] 29 | HOSTNAME=n3732.nemo.privat 30 | MOAB_JOBARRAYINDEX=3 31 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_4.cmd 32 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 33 | Calling: bash -c python run_BOHB.py --n 128 --run_id 4 --shared_directory ./BC_4/ --interface boot0 --worker 34 | Here's what we know from the MOAB environment 35 | MOAB_MACHINE=torque 36 | SHELL=/bin/bash 37 | HOME=/home/fr/fr_fr/fr_ke1011 38 | USER=fr_ke1011 39 | MOAB_JOBID=4603314[4] 40 | HOSTNAME=n3732.nemo.privat 41 | MOAB_JOBARRAYINDEX=4 42 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_4.cmd 43 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 44 | Calling: bash -c python run_BOHB.py --n 128 --run_id 4 --shared_directory ./BC_4/ --interface boot0 --worker 45 | Here's what we know from the MOAB environment 46 | MOAB_MACHINE=torque 47 | SHELL=/bin/bash 48 | HOME=/home/fr/fr_fr/fr_ke1011 49 | USER=fr_ke1011 50 | MOAB_JOBID=4603314[5] 51 | HOSTNAME=n3732.nemo.privat 52 | MOAB_JOBARRAYINDEX=5 53 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_4.cmd 54 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 55 | Calling: bash -c python run_BOHB.py --n 128 --run_id 4 --shared_directory ./BC_4/ --interface boot0 --worker 56 | Here's what we know from the MOAB environment 57 | MOAB_MACHINE=torque 58 | SHELL=/bin/bash 59 | HOME=/home/fr/fr_fr/fr_ke1011 60 | USER=fr_ke1011 61 | MOAB_JOBID=4603314[6] 62 | HOSTNAME=n3732.nemo.privat 63 | MOAB_JOBARRAYINDEX=6 64 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_4.cmd 65 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 66 | Calling: bash -c python run_BOHB.py --n 128 --run_id 4 --shared_directory ./BC_4/ --interface boot0 --worker 67 | Here's what we know from the MOAB environment 68 | MOAB_MACHINE=torque 69 | SHELL=/bin/bash 70 | HOME=/home/fr/fr_fr/fr_ke1011 71 | USER=fr_ke1011 72 | MOAB_JOBID=4603314[7] 73 | HOSTNAME=n3732.nemo.privat 74 | MOAB_JOBARRAYINDEX=7 75 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_4.cmd 76 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 77 | Calling: bash -c python run_BOHB.py --n 128 --run_id 4 --shared_directory ./BC_4/ --interface boot0 --worker 78 | Here's what we know from the MOAB environment 79 | MOAB_MACHINE=torque 80 | SHELL=/bin/bash 81 | HOME=/home/fr/fr_fr/fr_ke1011 82 | USER=fr_ke1011 83 | MOAB_JOBID=4603314[8] 84 | HOSTNAME=n3732.nemo.privat 85 | MOAB_JOBARRAYINDEX=8 86 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_4.cmd 87 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 88 | Calling: bash -c python run_BOHB.py --n 128 --run_id 4 --shared_directory ./BC_4/ --interface boot0 --worker 89 | Here's what we know from the MOAB environment 90 | MOAB_MACHINE=torque 91 | SHELL=/bin/bash 92 | HOME=/home/fr/fr_fr/fr_ke1011 93 | USER=fr_ke1011 94 | MOAB_JOBID=4603314[9] 95 | HOSTNAME=n3732.nemo.privat 96 | MOAB_JOBARRAYINDEX=9 97 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_4.cmd 98 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 99 | Calling: bash -c python run_BOHB.py --n 128 --run_id 4 --shared_directory ./BC_4/ --interface boot0 --worker 100 | Here's what we know from the MOAB environment 101 | MOAB_MACHINE=torque 102 | SHELL=/bin/bash 103 | HOME=/home/fr/fr_fr/fr_ke1011 104 | USER=fr_ke1011 105 | MOAB_JOBID=4603314[10] 106 | HOSTNAME=n3732.nemo.privat 107 | MOAB_JOBARRAYINDEX=10 108 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_4.cmd 109 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 110 | Calling: bash -c python run_BOHB.py --n 128 --run_id 4 --shared_directory ./BC_4/ --interface boot0 --worker 111 | Job started at: Fri Dec 21 10:20:27 CET 2018 112 | 113 | Job started at: Fri Dec 21 10:21:08 CET 2018 114 | 115 | Job started at: Fri Dec 21 10:21:23 CET 2018 116 | 117 | Job started at: Fri Dec 21 10:21:30 CET 2018 118 | 119 | Job started at: Fri Dec 21 10:22:49 CET 2018 120 | 121 | Job started at: Fri Dec 21 10:22:51 CET 2018 122 | 123 | Job started at: Fri Dec 21 10:23:05 CET 2018 124 | 125 | Job started at: Fri Dec 21 10:25:15 CET 2018 126 | 127 | Job started at: Fri Dec 21 10:25:46 CET 2018 128 | 129 | Job started at: Fri Dec 21 10:26:19 CET 2018 130 | 131 | 132 | Job finished with exit code 0 at: Fri Dec 21 15:51:45 CET 2018 133 | DONE 134 | 135 | Job finished with exit code 0 at: Fri Dec 21 15:51:45 CET 2018 136 | DONE 137 | 138 | Job finished with exit code 0 at: Fri Dec 21 15:51:45 CET 2018 139 | DONE 140 | 141 | Job finished with exit code 0 at: Fri Dec 21 15:51:45 CET 2018 142 | DONE 143 | 144 | 145 | Job finished with exit code 0 at: Fri Dec 21 15:51:45 CET 2018 146 | DONE 147 | 148 | Job finished with exit code 0 at: Fri Dec 21 15:51:45 CET 2018 149 | DONE 150 | Job finished with exit code 0 at: Fri Dec 21 15:51:45 CET 2018 151 | DONE 152 | 153 | Job finished with exit code 0 at: Fri Dec 21 15:51:45 CET 2018 154 | DONE 155 | 156 | Job finished with exit code 0 at: Fri Dec 21 15:51:45 CET 2018 157 | DONE 158 | 159 | Job finished with exit code 0 at: Fri Dec 21 15:51:45 CET 2018 160 | DONE 161 | -------------------------------------------------------------------------------- /examples/PPO_on_cartpole/NEMO_OUTPUT/BC_4/4/job_4.cmd_2018-12-21--9-52-31-446298.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #$ -S /bin/bash 3 | 4 | cd "/work/ws/nemo/fr_ke1011-BOHB_CAVE-0" 5 | jobs_file="/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_4.cmd" 6 | 7 | echo "Here's what we know from the MOAB environment" 8 | echo MOAB_MACHINE=$MOAB_MACHINE 9 | echo SHELL=$SHELL 10 | echo HOME=$HOME 11 | echo USER=$USER 12 | echo MOAB_JOBID=$MOAB_JOBID 13 | echo HOSTNAME=$HOSTNAME 14 | echo MOAB_JOBARRAYINDEX=$MOAB_JOBARRAYINDEX 15 | echo jobs_file=${jobs_file} 16 | echo PWD=`pwd` 17 | line=`head -n $MOAB_JOBARRAYINDEX "${jobs_file}" | tail -1` # Get line of todoFilename. 18 | echo Calling: bash -c "$line" #output 19 | 20 | export PATH=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/miniconda3/bin:$PATH 21 | 22 | mkdir -p ~/.lockdir/ 23 | LOCKDIR=~/.lockdir/lock/ 24 | VENVDIR="$1" 25 | 26 | for i in {1..10000}; do 27 | if mkdir "$LOCKDIR"; then 28 | echo "Locking succeeded - Going to activate Conda" >&2 29 | source activate BC_36 30 | break 31 | 32 | else 33 | echo "Lock failed - sleep and try again" >&2 34 | pid=$$ 35 | sleeptime=$((pid%30)) 36 | 37 | sleep $((sleeptime+5))s 38 | fi 39 | done 40 | 41 | rmdir "$LOCKDIR" 42 | 43 | 44 | echo "Job started at: `date`" 45 | 46 | echo 47 | bash -c "$line" 48 | echo 49 | 50 | echo "Job finished with exit code $? at: `date`" 51 | 52 | echo DONE 53 | 54 | 55 | -------------------------------------------------------------------------------- /examples/PPO_on_cartpole/NEMO_OUTPUT/BC_4/configspace.json: -------------------------------------------------------------------------------- 1 | { 2 | "hyperparameters": [ 3 | { 4 | "name": "batch_size", 5 | "type": "uniform_int", 6 | "log": true, 7 | "lower": 8, 8 | "upper": 256, 9 | "default": 64 10 | }, 11 | { 12 | "name": "discount", 13 | "type": "uniform_float", 14 | "log": false, 15 | "lower": 0.0, 16 | "upper": 1.0, 17 | "default": 0.99 18 | }, 19 | { 20 | "name": "entropy_regularization", 21 | "type": "uniform_float", 22 | "log": false, 23 | "lower": 0.0, 24 | "upper": 1.0, 25 | "default": 0.01 26 | }, 27 | { 28 | "name": "learning_rate", 29 | "type": "uniform_float", 30 | "log": true, 31 | "lower": 1e-07, 32 | "upper": 0.1, 33 | "default": 0.001 34 | }, 35 | { 36 | "name": "likelihood_ratio_clipping", 37 | "type": "uniform_float", 38 | "log": false, 39 | "lower": 0.0, 40 | "upper": 1.0, 41 | "default": 0.2 42 | }, 43 | { 44 | "name": "n_units_1", 45 | "type": "uniform_int", 46 | "log": true, 47 | "lower": 8, 48 | "upper": 128, 49 | "default": 64 50 | }, 51 | { 52 | "name": "n_units_2", 53 | "type": "uniform_int", 54 | "log": true, 55 | "lower": 8, 56 | "upper": 128, 57 | "default": 64 58 | } 59 | ], 60 | "conditions": [], 61 | "forbiddens": [], 62 | "python_module_version": "0.4.7", 63 | "json_format_version": 0.1 64 | } -------------------------------------------------------------------------------- /examples/PPO_on_cartpole/NEMO_OUTPUT/BC_4/results.pkl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/automl/BOAH/7bbc5b97ccbb742c32dc8e6318ed628414cb86dc/examples/PPO_on_cartpole/NEMO_OUTPUT/BC_4/results.pkl -------------------------------------------------------------------------------- /examples/PPO_on_cartpole/NEMO_OUTPUT/BC_5/5/2018-12-21--13-22-26-631079.out: -------------------------------------------------------------------------------- 1 | Here's what we know from the MOAB environment 2 | MOAB_MACHINE=torque 3 | SHELL=/bin/bash 4 | HOME=/home/fr/fr_fr/fr_ke1011 5 | USER=fr_ke1011 6 | MOAB_JOBID=4606558[1] 7 | HOSTNAME=n3753.nemo.privat 8 | MOAB_JOBARRAYINDEX=1 9 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_5.cmd 10 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 11 | Calling: bash -c python run_BOHB.py --n 128 --run_id 5 --shared_directory ./BC_5/ --interface boot0 12 | Here's what we know from the MOAB environment 13 | MOAB_MACHINE=torque 14 | SHELL=/bin/bash 15 | HOME=/home/fr/fr_fr/fr_ke1011 16 | USER=fr_ke1011 17 | MOAB_JOBID=4606558[2] 18 | HOSTNAME=n3753.nemo.privat 19 | MOAB_JOBARRAYINDEX=2 20 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_5.cmd 21 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 22 | Calling: bash -c python run_BOHB.py --n 128 --run_id 5 --shared_directory ./BC_5/ --interface boot0 --worker 23 | Here's what we know from the MOAB environment 24 | MOAB_MACHINE=torque 25 | SHELL=/bin/bash 26 | HOME=/home/fr/fr_fr/fr_ke1011 27 | USER=fr_ke1011 28 | MOAB_JOBID=4606558[3] 29 | HOSTNAME=n3753.nemo.privat 30 | MOAB_JOBARRAYINDEX=3 31 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_5.cmd 32 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 33 | Calling: bash -c python run_BOHB.py --n 128 --run_id 5 --shared_directory ./BC_5/ --interface boot0 --worker 34 | Here's what we know from the MOAB environment 35 | MOAB_MACHINE=torque 36 | SHELL=/bin/bash 37 | HOME=/home/fr/fr_fr/fr_ke1011 38 | USER=fr_ke1011 39 | MOAB_JOBID=4606558[4] 40 | HOSTNAME=n3753.nemo.privat 41 | MOAB_JOBARRAYINDEX=4 42 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_5.cmd 43 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 44 | Calling: bash -c python run_BOHB.py --n 128 --run_id 5 --shared_directory ./BC_5/ --interface boot0 --worker 45 | Here's what we know from the MOAB environment 46 | MOAB_MACHINE=torque 47 | SHELL=/bin/bash 48 | HOME=/home/fr/fr_fr/fr_ke1011 49 | USER=fr_ke1011 50 | MOAB_JOBID=4606558[5] 51 | HOSTNAME=n3753.nemo.privat 52 | MOAB_JOBARRAYINDEX=5 53 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_5.cmd 54 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 55 | Calling: bash -c python run_BOHB.py --n 128 --run_id 5 --shared_directory ./BC_5/ --interface boot0 --worker 56 | Here's what we know from the MOAB environment 57 | MOAB_MACHINE=torque 58 | SHELL=/bin/bash 59 | HOME=/home/fr/fr_fr/fr_ke1011 60 | USER=fr_ke1011 61 | MOAB_JOBID=4606558[6] 62 | HOSTNAME=n3753.nemo.privat 63 | MOAB_JOBARRAYINDEX=6 64 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_5.cmd 65 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 66 | Calling: bash -c python run_BOHB.py --n 128 --run_id 5 --shared_directory ./BC_5/ --interface boot0 --worker 67 | Here's what we know from the MOAB environment 68 | MOAB_MACHINE=torque 69 | SHELL=/bin/bash 70 | HOME=/home/fr/fr_fr/fr_ke1011 71 | USER=fr_ke1011 72 | MOAB_JOBID=4606558[7] 73 | HOSTNAME=n3753.nemo.privat 74 | MOAB_JOBARRAYINDEX=7 75 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_5.cmd 76 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 77 | Calling: bash -c python run_BOHB.py --n 128 --run_id 5 --shared_directory ./BC_5/ --interface boot0 --worker 78 | Here's what we know from the MOAB environment 79 | MOAB_MACHINE=torque 80 | SHELL=/bin/bash 81 | HOME=/home/fr/fr_fr/fr_ke1011 82 | USER=fr_ke1011 83 | MOAB_JOBID=4606558[8] 84 | HOSTNAME=n3753.nemo.privat 85 | MOAB_JOBARRAYINDEX=8 86 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_5.cmd 87 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 88 | Calling: bash -c python run_BOHB.py --n 128 --run_id 5 --shared_directory ./BC_5/ --interface boot0 --worker 89 | Here's what we know from the MOAB environment 90 | MOAB_MACHINE=torque 91 | SHELL=/bin/bash 92 | HOME=/home/fr/fr_fr/fr_ke1011 93 | USER=fr_ke1011 94 | MOAB_JOBID=4606558[9] 95 | HOSTNAME=n3753.nemo.privat 96 | MOAB_JOBARRAYINDEX=9 97 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_5.cmd 98 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 99 | Calling: bash -c python run_BOHB.py --n 128 --run_id 5 --shared_directory ./BC_5/ --interface boot0 --worker 100 | Here's what we know from the MOAB environment 101 | MOAB_MACHINE=torque 102 | SHELL=/bin/bash 103 | HOME=/home/fr/fr_fr/fr_ke1011 104 | USER=fr_ke1011 105 | MOAB_JOBID=4606558[10] 106 | HOSTNAME=n3753.nemo.privat 107 | MOAB_JOBARRAYINDEX=10 108 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_5.cmd 109 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 110 | Calling: bash -c python run_BOHB.py --n 128 --run_id 5 --shared_directory ./BC_5/ --interface boot0 --worker 111 | Job started at: Fri Dec 21 13:23:03 CET 2018 112 | 113 | Job started at: Fri Dec 21 13:23:08 CET 2018 114 | 115 | Job started at: Fri Dec 21 13:23:15 CET 2018 116 | 117 | Job started at: Fri Dec 21 13:23:25 CET 2018 118 | 119 | Job started at: Fri Dec 21 13:23:28 CET 2018 120 | 121 | Job started at: Fri Dec 21 13:23:32 CET 2018 122 | 123 | Job started at: Fri Dec 21 13:23:36 CET 2018 124 | 125 | Job started at: Fri Dec 21 13:23:44 CET 2018 126 | 127 | Job started at: Fri Dec 21 13:23:57 CET 2018 128 | 129 | Job started at: Fri Dec 21 13:24:04 CET 2018 130 | 131 | 132 | Job finished with exit code 0 at: Fri Dec 21 19:00:46 CET 2018 133 | DONE 134 | 135 | 136 | Job finished with exit code 0 at: Fri Dec 21 19:00:46 CET 2018 137 | Job finished with exit code 0 at: Fri Dec 21 19:00:46 CET 2018 138 | DONE 139 | DONE 140 | 141 | 142 | Job finished with exit code 0 at: Fri Dec 21 19:00:46 CET 2018 143 | DONE 144 | Job finished with exit code 0 at: Fri Dec 21 19:00:46 CET 2018 145 | DONE 146 | 147 | Job finished with exit code 0 at: Fri Dec 21 19:00:46 CET 2018 148 | DONE 149 | 150 | Job finished with exit code 0 at: Fri Dec 21 19:00:46 CET 2018 151 | DONE 152 | 153 | Job finished with exit code 0 at: Fri Dec 21 19:00:46 CET 2018 154 | DONE 155 | 156 | Job finished with exit code 0 at: Fri Dec 21 19:00:46 CET 2018 157 | DONE 158 | 159 | Job finished with exit code 0 at: Fri Dec 21 19:00:47 CET 2018 160 | DONE 161 | -------------------------------------------------------------------------------- /examples/PPO_on_cartpole/NEMO_OUTPUT/BC_5/5/job_5.cmd_2018-12-21--13-22-26-631079.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #$ -S /bin/bash 3 | 4 | cd "/work/ws/nemo/fr_ke1011-BOHB_CAVE-0" 5 | jobs_file="/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_5.cmd" 6 | 7 | echo "Here's what we know from the MOAB environment" 8 | echo MOAB_MACHINE=$MOAB_MACHINE 9 | echo SHELL=$SHELL 10 | echo HOME=$HOME 11 | echo USER=$USER 12 | echo MOAB_JOBID=$MOAB_JOBID 13 | echo HOSTNAME=$HOSTNAME 14 | echo MOAB_JOBARRAYINDEX=$MOAB_JOBARRAYINDEX 15 | echo jobs_file=${jobs_file} 16 | echo PWD=`pwd` 17 | line=`head -n $MOAB_JOBARRAYINDEX "${jobs_file}" | tail -1` # Get line of todoFilename. 18 | echo Calling: bash -c "$line" #output 19 | 20 | export PATH=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/miniconda3/bin:$PATH 21 | 22 | mkdir -p ~/.lockdir/ 23 | LOCKDIR=~/.lockdir/lock/ 24 | VENVDIR="$1" 25 | 26 | for i in {1..10000}; do 27 | if mkdir "$LOCKDIR"; then 28 | echo "Locking succeeded - Going to activate Conda" >&2 29 | source activate BC_36 30 | break 31 | 32 | else 33 | echo "Lock failed - sleep and try again" >&2 34 | pid=$$ 35 | sleeptime=$((pid%30)) 36 | 37 | sleep $((sleeptime+5))s 38 | fi 39 | done 40 | 41 | rmdir "$LOCKDIR" 42 | 43 | 44 | echo "Job started at: `date`" 45 | 46 | echo 47 | bash -c "$line" 48 | echo 49 | 50 | echo "Job finished with exit code $? at: `date`" 51 | 52 | echo DONE 53 | 54 | 55 | -------------------------------------------------------------------------------- /examples/PPO_on_cartpole/NEMO_OUTPUT/BC_5/configspace.json: -------------------------------------------------------------------------------- 1 | { 2 | "hyperparameters": [ 3 | { 4 | "name": "batch_size", 5 | "type": "uniform_int", 6 | "log": true, 7 | "lower": 8, 8 | "upper": 256, 9 | "default": 64 10 | }, 11 | { 12 | "name": "discount", 13 | "type": "uniform_float", 14 | "log": false, 15 | "lower": 0.0, 16 | "upper": 1.0, 17 | "default": 0.99 18 | }, 19 | { 20 | "name": "entropy_regularization", 21 | "type": "uniform_float", 22 | "log": false, 23 | "lower": 0.0, 24 | "upper": 1.0, 25 | "default": 0.01 26 | }, 27 | { 28 | "name": "learning_rate", 29 | "type": "uniform_float", 30 | "log": true, 31 | "lower": 1e-07, 32 | "upper": 0.1, 33 | "default": 0.001 34 | }, 35 | { 36 | "name": "likelihood_ratio_clipping", 37 | "type": "uniform_float", 38 | "log": false, 39 | "lower": 0.0, 40 | "upper": 1.0, 41 | "default": 0.2 42 | }, 43 | { 44 | "name": "n_units_1", 45 | "type": "uniform_int", 46 | "log": true, 47 | "lower": 8, 48 | "upper": 128, 49 | "default": 64 50 | }, 51 | { 52 | "name": "n_units_2", 53 | "type": "uniform_int", 54 | "log": true, 55 | "lower": 8, 56 | "upper": 128, 57 | "default": 64 58 | } 59 | ], 60 | "conditions": [], 61 | "forbiddens": [], 62 | "python_module_version": "0.4.7", 63 | "json_format_version": 0.1 64 | } -------------------------------------------------------------------------------- /examples/PPO_on_cartpole/NEMO_OUTPUT/BC_5/results.pkl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/automl/BOAH/7bbc5b97ccbb742c32dc8e6318ed628414cb86dc/examples/PPO_on_cartpole/NEMO_OUTPUT/BC_5/results.pkl -------------------------------------------------------------------------------- /examples/PPO_on_cartpole/NEMO_OUTPUT/BC_6/6/2018-12-21--13-22-32-687552.out: -------------------------------------------------------------------------------- 1 | Here's what we know from the MOAB environment 2 | MOAB_MACHINE=torque 3 | SHELL=/bin/bash 4 | HOME=/home/fr/fr_fr/fr_ke1011 5 | USER=fr_ke1011 6 | MOAB_JOBID=4606559[1] 7 | HOSTNAME=n3470.nemo.privat 8 | MOAB_JOBARRAYINDEX=1 9 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_6.cmd 10 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 11 | Calling: bash -c python run_BOHB.py --n 128 --run_id 6 --shared_directory ./BC_6/ --interface boot0 12 | Here's what we know from the MOAB environment 13 | MOAB_MACHINE=torque 14 | SHELL=/bin/bash 15 | HOME=/home/fr/fr_fr/fr_ke1011 16 | USER=fr_ke1011 17 | MOAB_JOBID=4606559[2] 18 | HOSTNAME=n3470.nemo.privat 19 | MOAB_JOBARRAYINDEX=2 20 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_6.cmd 21 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 22 | Calling: bash -c python run_BOHB.py --n 128 --run_id 6 --shared_directory ./BC_6/ --interface boot0 --worker 23 | Here's what we know from the MOAB environment 24 | MOAB_MACHINE=torque 25 | SHELL=/bin/bash 26 | HOME=/home/fr/fr_fr/fr_ke1011 27 | USER=fr_ke1011 28 | MOAB_JOBID=4606559[3] 29 | HOSTNAME=n3470.nemo.privat 30 | MOAB_JOBARRAYINDEX=3 31 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_6.cmd 32 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 33 | Calling: bash -c python run_BOHB.py --n 128 --run_id 6 --shared_directory ./BC_6/ --interface boot0 --worker 34 | Here's what we know from the MOAB environment 35 | MOAB_MACHINE=torque 36 | SHELL=/bin/bash 37 | HOME=/home/fr/fr_fr/fr_ke1011 38 | USER=fr_ke1011 39 | MOAB_JOBID=4606559[4] 40 | HOSTNAME=n3470.nemo.privat 41 | MOAB_JOBARRAYINDEX=4 42 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_6.cmd 43 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 44 | Calling: bash -c python run_BOHB.py --n 128 --run_id 6 --shared_directory ./BC_6/ --interface boot0 --worker 45 | Here's what we know from the MOAB environment 46 | MOAB_MACHINE=torque 47 | SHELL=/bin/bash 48 | HOME=/home/fr/fr_fr/fr_ke1011 49 | USER=fr_ke1011 50 | MOAB_JOBID=4606559[5] 51 | HOSTNAME=n3470.nemo.privat 52 | MOAB_JOBARRAYINDEX=5 53 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_6.cmd 54 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 55 | Calling: bash -c python run_BOHB.py --n 128 --run_id 6 --shared_directory ./BC_6/ --interface boot0 --worker 56 | Here's what we know from the MOAB environment 57 | MOAB_MACHINE=torque 58 | SHELL=/bin/bash 59 | HOME=/home/fr/fr_fr/fr_ke1011 60 | USER=fr_ke1011 61 | MOAB_JOBID=4606559[6] 62 | HOSTNAME=n3470.nemo.privat 63 | MOAB_JOBARRAYINDEX=6 64 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_6.cmd 65 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 66 | Calling: bash -c python run_BOHB.py --n 128 --run_id 6 --shared_directory ./BC_6/ --interface boot0 --worker 67 | Here's what we know from the MOAB environment 68 | MOAB_MACHINE=torque 69 | SHELL=/bin/bash 70 | HOME=/home/fr/fr_fr/fr_ke1011 71 | USER=fr_ke1011 72 | MOAB_JOBID=4606559[7] 73 | HOSTNAME=n3470.nemo.privat 74 | MOAB_JOBARRAYINDEX=7 75 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_6.cmd 76 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 77 | Calling: bash -c python run_BOHB.py --n 128 --run_id 6 --shared_directory ./BC_6/ --interface boot0 --worker 78 | Here's what we know from the MOAB environment 79 | MOAB_MACHINE=torque 80 | SHELL=/bin/bash 81 | HOME=/home/fr/fr_fr/fr_ke1011 82 | USER=fr_ke1011 83 | MOAB_JOBID=4606559[8] 84 | HOSTNAME=n3470.nemo.privat 85 | MOAB_JOBARRAYINDEX=8 86 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_6.cmd 87 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 88 | Calling: bash -c python run_BOHB.py --n 128 --run_id 6 --shared_directory ./BC_6/ --interface boot0 --worker 89 | Here's what we know from the MOAB environment 90 | MOAB_MACHINE=torque 91 | SHELL=/bin/bash 92 | HOME=/home/fr/fr_fr/fr_ke1011 93 | USER=fr_ke1011 94 | MOAB_JOBID=4606559[9] 95 | HOSTNAME=n3470.nemo.privat 96 | MOAB_JOBARRAYINDEX=9 97 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_6.cmd 98 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 99 | Calling: bash -c python run_BOHB.py --n 128 --run_id 6 --shared_directory ./BC_6/ --interface boot0 --worker 100 | Here's what we know from the MOAB environment 101 | MOAB_MACHINE=torque 102 | SHELL=/bin/bash 103 | HOME=/home/fr/fr_fr/fr_ke1011 104 | USER=fr_ke1011 105 | MOAB_JOBID=4606559[10] 106 | HOSTNAME=n3470.nemo.privat 107 | MOAB_JOBARRAYINDEX=10 108 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_6.cmd 109 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 110 | Calling: bash -c python run_BOHB.py --n 128 --run_id 6 --shared_directory ./BC_6/ --interface boot0 --worker 111 | Job started at: Fri Dec 21 15:18:45 CET 2018 112 | 113 | Job started at: Fri Dec 21 15:18:54 CET 2018 114 | 115 | Job started at: Fri Dec 21 15:19:01 CET 2018 116 | 117 | Job started at: Fri Dec 21 15:19:04 CET 2018 118 | 119 | Job started at: Fri Dec 21 15:19:06 CET 2018 120 | 121 | Job started at: Fri Dec 21 15:19:12 CET 2018 122 | 123 | Job started at: Fri Dec 21 15:19:22 CET 2018 124 | 125 | Job started at: Fri Dec 21 15:19:30 CET 2018 126 | 127 | Job started at: Fri Dec 21 15:19:40 CET 2018 128 | 129 | Job started at: Fri Dec 21 15:19:42 CET 2018 130 | 131 | 132 | Job finished with exit code 0 at: Fri Dec 21 20:09:27 CET 2018 133 | 134 | DONE 135 | Job finished with exit code 0 at: Fri Dec 21 20:09:27 CET 2018 136 | DONE 137 | 138 | Job finished with exit code 0 at: Fri Dec 21 20:09:27 CET 2018 139 | DONE 140 | 141 | Job finished with exit code 0 at: Fri Dec 21 20:09:27 CET 2018 142 | DONE 143 | 144 | Job finished with exit code 0 at: Fri Dec 21 20:09:27 CET 2018 145 | DONE 146 | 147 | Job finished with exit code 0 at: Fri Dec 21 20:09:27 CET 2018 148 | DONE 149 | 150 | Job finished with exit code 0 at: Fri Dec 21 20:09:27 CET 2018 151 | DONE 152 | 153 | Job finished with exit code 0 at: Fri Dec 21 20:09:27 CET 2018 154 | DONE 155 | 156 | Job finished with exit code 0 at: Fri Dec 21 20:09:27 CET 2018 157 | DONE 158 | 159 | Job finished with exit code 0 at: Fri Dec 21 20:09:27 CET 2018 160 | DONE 161 | -------------------------------------------------------------------------------- /examples/PPO_on_cartpole/NEMO_OUTPUT/BC_6/6/job_6.cmd_2018-12-21--13-22-32-687552.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #$ -S /bin/bash 3 | 4 | cd "/work/ws/nemo/fr_ke1011-BOHB_CAVE-0" 5 | jobs_file="/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_6.cmd" 6 | 7 | echo "Here's what we know from the MOAB environment" 8 | echo MOAB_MACHINE=$MOAB_MACHINE 9 | echo SHELL=$SHELL 10 | echo HOME=$HOME 11 | echo USER=$USER 12 | echo MOAB_JOBID=$MOAB_JOBID 13 | echo HOSTNAME=$HOSTNAME 14 | echo MOAB_JOBARRAYINDEX=$MOAB_JOBARRAYINDEX 15 | echo jobs_file=${jobs_file} 16 | echo PWD=`pwd` 17 | line=`head -n $MOAB_JOBARRAYINDEX "${jobs_file}" | tail -1` # Get line of todoFilename. 18 | echo Calling: bash -c "$line" #output 19 | 20 | export PATH=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/miniconda3/bin:$PATH 21 | 22 | mkdir -p ~/.lockdir/ 23 | LOCKDIR=~/.lockdir/lock/ 24 | VENVDIR="$1" 25 | 26 | for i in {1..10000}; do 27 | if mkdir "$LOCKDIR"; then 28 | echo "Locking succeeded - Going to activate Conda" >&2 29 | source activate BC_36 30 | break 31 | 32 | else 33 | echo "Lock failed - sleep and try again" >&2 34 | pid=$$ 35 | sleeptime=$((pid%30)) 36 | 37 | sleep $((sleeptime+5))s 38 | fi 39 | done 40 | 41 | rmdir "$LOCKDIR" 42 | 43 | 44 | echo "Job started at: `date`" 45 | 46 | echo 47 | bash -c "$line" 48 | echo 49 | 50 | echo "Job finished with exit code $? at: `date`" 51 | 52 | echo DONE 53 | 54 | 55 | -------------------------------------------------------------------------------- /examples/PPO_on_cartpole/NEMO_OUTPUT/BC_6/configspace.json: -------------------------------------------------------------------------------- 1 | { 2 | "hyperparameters": [ 3 | { 4 | "name": "batch_size", 5 | "type": "uniform_int", 6 | "log": true, 7 | "lower": 8, 8 | "upper": 256, 9 | "default": 64 10 | }, 11 | { 12 | "name": "discount", 13 | "type": "uniform_float", 14 | "log": false, 15 | "lower": 0.0, 16 | "upper": 1.0, 17 | "default": 0.99 18 | }, 19 | { 20 | "name": "entropy_regularization", 21 | "type": "uniform_float", 22 | "log": false, 23 | "lower": 0.0, 24 | "upper": 1.0, 25 | "default": 0.01 26 | }, 27 | { 28 | "name": "learning_rate", 29 | "type": "uniform_float", 30 | "log": true, 31 | "lower": 1e-07, 32 | "upper": 0.1, 33 | "default": 0.001 34 | }, 35 | { 36 | "name": "likelihood_ratio_clipping", 37 | "type": "uniform_float", 38 | "log": false, 39 | "lower": 0.0, 40 | "upper": 1.0, 41 | "default": 0.2 42 | }, 43 | { 44 | "name": "n_units_1", 45 | "type": "uniform_int", 46 | "log": true, 47 | "lower": 8, 48 | "upper": 128, 49 | "default": 64 50 | }, 51 | { 52 | "name": "n_units_2", 53 | "type": "uniform_int", 54 | "log": true, 55 | "lower": 8, 56 | "upper": 128, 57 | "default": 64 58 | } 59 | ], 60 | "conditions": [], 61 | "forbiddens": [], 62 | "python_module_version": "0.4.7", 63 | "json_format_version": 0.1 64 | } -------------------------------------------------------------------------------- /examples/PPO_on_cartpole/NEMO_OUTPUT/BC_6/results.pkl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/automl/BOAH/7bbc5b97ccbb742c32dc8e6318ed628414cb86dc/examples/PPO_on_cartpole/NEMO_OUTPUT/BC_6/results.pkl -------------------------------------------------------------------------------- /examples/PPO_on_cartpole/NEMO_OUTPUT/BC_7/7/2018-12-21--13-22-41-11044.out: -------------------------------------------------------------------------------- 1 | Here's what we know from the MOAB environment 2 | MOAB_MACHINE=torque 3 | SHELL=/bin/bash 4 | HOME=/home/fr/fr_fr/fr_ke1011 5 | USER=fr_ke1011 6 | MOAB_JOBID=4606560[1] 7 | HOSTNAME=n4254.nemo.privat 8 | MOAB_JOBARRAYINDEX=1 9 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_7.cmd 10 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 11 | Calling: bash -c python run_BOHB.py --n 128 --run_id 7 --shared_directory ./BC_7/ --interface boot0 12 | Here's what we know from the MOAB environment 13 | MOAB_MACHINE=torque 14 | SHELL=/bin/bash 15 | HOME=/home/fr/fr_fr/fr_ke1011 16 | USER=fr_ke1011 17 | MOAB_JOBID=4606560[2] 18 | HOSTNAME=n4254.nemo.privat 19 | MOAB_JOBARRAYINDEX=2 20 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_7.cmd 21 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 22 | Calling: bash -c python run_BOHB.py --n 128 --run_id 7 --shared_directory ./BC_7/ --interface boot0 --worker 23 | Here's what we know from the MOAB environment 24 | MOAB_MACHINE=torque 25 | SHELL=/bin/bash 26 | HOME=/home/fr/fr_fr/fr_ke1011 27 | USER=fr_ke1011 28 | MOAB_JOBID=4606560[3] 29 | HOSTNAME=n4254.nemo.privat 30 | MOAB_JOBARRAYINDEX=3 31 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_7.cmd 32 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 33 | Calling: bash -c python run_BOHB.py --n 128 --run_id 7 --shared_directory ./BC_7/ --interface boot0 --worker 34 | Here's what we know from the MOAB environment 35 | MOAB_MACHINE=torque 36 | SHELL=/bin/bash 37 | HOME=/home/fr/fr_fr/fr_ke1011 38 | USER=fr_ke1011 39 | MOAB_JOBID=4606560[4] 40 | HOSTNAME=n4254.nemo.privat 41 | MOAB_JOBARRAYINDEX=4 42 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_7.cmd 43 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 44 | Calling: bash -c python run_BOHB.py --n 128 --run_id 7 --shared_directory ./BC_7/ --interface boot0 --worker 45 | Here's what we know from the MOAB environment 46 | MOAB_MACHINE=torque 47 | SHELL=/bin/bash 48 | HOME=/home/fr/fr_fr/fr_ke1011 49 | USER=fr_ke1011 50 | MOAB_JOBID=4606560[5] 51 | HOSTNAME=n4254.nemo.privat 52 | MOAB_JOBARRAYINDEX=5 53 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_7.cmd 54 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 55 | Calling: bash -c python run_BOHB.py --n 128 --run_id 7 --shared_directory ./BC_7/ --interface boot0 --worker 56 | Here's what we know from the MOAB environment 57 | MOAB_MACHINE=torque 58 | SHELL=/bin/bash 59 | HOME=/home/fr/fr_fr/fr_ke1011 60 | USER=fr_ke1011 61 | MOAB_JOBID=4606560[6] 62 | HOSTNAME=n4254.nemo.privat 63 | MOAB_JOBARRAYINDEX=6 64 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_7.cmd 65 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 66 | Calling: bash -c python run_BOHB.py --n 128 --run_id 7 --shared_directory ./BC_7/ --interface boot0 --worker 67 | Here's what we know from the MOAB environment 68 | MOAB_MACHINE=torque 69 | SHELL=/bin/bash 70 | HOME=/home/fr/fr_fr/fr_ke1011 71 | USER=fr_ke1011 72 | MOAB_JOBID=4606560[7] 73 | HOSTNAME=n4254.nemo.privat 74 | MOAB_JOBARRAYINDEX=7 75 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_7.cmd 76 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 77 | Calling: bash -c python run_BOHB.py --n 128 --run_id 7 --shared_directory ./BC_7/ --interface boot0 --worker 78 | Here's what we know from the MOAB environment 79 | MOAB_MACHINE=torque 80 | SHELL=/bin/bash 81 | HOME=/home/fr/fr_fr/fr_ke1011 82 | USER=fr_ke1011 83 | MOAB_JOBID=4606560[8] 84 | HOSTNAME=n4254.nemo.privat 85 | MOAB_JOBARRAYINDEX=8 86 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_7.cmd 87 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 88 | Calling: bash -c python run_BOHB.py --n 128 --run_id 7 --shared_directory ./BC_7/ --interface boot0 --worker 89 | Here's what we know from the MOAB environment 90 | MOAB_MACHINE=torque 91 | SHELL=/bin/bash 92 | HOME=/home/fr/fr_fr/fr_ke1011 93 | USER=fr_ke1011 94 | MOAB_JOBID=4606560[9] 95 | HOSTNAME=n4254.nemo.privat 96 | MOAB_JOBARRAYINDEX=9 97 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_7.cmd 98 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 99 | Calling: bash -c python run_BOHB.py --n 128 --run_id 7 --shared_directory ./BC_7/ --interface boot0 --worker 100 | Here's what we know from the MOAB environment 101 | MOAB_MACHINE=torque 102 | SHELL=/bin/bash 103 | HOME=/home/fr/fr_fr/fr_ke1011 104 | USER=fr_ke1011 105 | MOAB_JOBID=4606560[10] 106 | HOSTNAME=n4254.nemo.privat 107 | MOAB_JOBARRAYINDEX=10 108 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_7.cmd 109 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 110 | Calling: bash -c python run_BOHB.py --n 128 --run_id 7 --shared_directory ./BC_7/ --interface boot0 --worker 111 | Job started at: Fri Dec 21 15:25:10 CET 2018 112 | 113 | Job started at: Fri Dec 21 15:25:16 CET 2018 114 | 115 | Job started at: Fri Dec 21 15:25:22 CET 2018 116 | 117 | Job started at: Fri Dec 21 15:25:27 CET 2018 118 | 119 | Job started at: Fri Dec 21 15:25:44 CET 2018 120 | 121 | Job started at: Fri Dec 21 15:25:47 CET 2018 122 | 123 | Job started at: Fri Dec 21 15:25:53 CET 2018 124 | 125 | Job started at: Fri Dec 21 15:26:04 CET 2018 126 | 127 | Job started at: Fri Dec 21 15:26:34 CET 2018 128 | 129 | Job started at: Fri Dec 21 15:27:06 CET 2018 130 | 131 | 132 | Job finished with exit code 0 at: Fri Dec 21 20:32:05 CET 2018 133 | 134 | 135 | 136 | 137 | 138 | DONE 139 | 140 | 141 | 142 | Job finished with exit code 0 at: Fri Dec 21 20:32:05 CET 2018 143 | Job finished with exit code 0 at: Fri Dec 21 20:32:05 CET 2018 144 | DONE 145 | DONE 146 | Job finished with exit code 0 at: Fri Dec 21 20:32:05 CET 2018 147 | DONE 148 | 149 | Job finished with exit code 0 at: Fri Dec 21 20:32:05 CET 2018 150 | Job finished with exit code 0 at: Fri Dec 21 20:32:05 CET 2018 151 | Job finished with exit code 0 at: Fri Dec 21 20:32:05 CET 2018 152 | Job finished with exit code 0 at: Fri Dec 21 20:32:05 CET 2018 153 | Job finished with exit code 0 at: Fri Dec 21 20:32:05 CET 2018 154 | Job finished with exit code 0 at: Fri Dec 21 20:32:05 CET 2018 155 | DONE 156 | DONE 157 | DONE 158 | DONE 159 | DONE 160 | DONE 161 | -------------------------------------------------------------------------------- /examples/PPO_on_cartpole/NEMO_OUTPUT/BC_7/7/job_7.cmd_2018-12-21--13-22-41-11044.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #$ -S /bin/bash 3 | 4 | cd "/work/ws/nemo/fr_ke1011-BOHB_CAVE-0" 5 | jobs_file="/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_7.cmd" 6 | 7 | echo "Here's what we know from the MOAB environment" 8 | echo MOAB_MACHINE=$MOAB_MACHINE 9 | echo SHELL=$SHELL 10 | echo HOME=$HOME 11 | echo USER=$USER 12 | echo MOAB_JOBID=$MOAB_JOBID 13 | echo HOSTNAME=$HOSTNAME 14 | echo MOAB_JOBARRAYINDEX=$MOAB_JOBARRAYINDEX 15 | echo jobs_file=${jobs_file} 16 | echo PWD=`pwd` 17 | line=`head -n $MOAB_JOBARRAYINDEX "${jobs_file}" | tail -1` # Get line of todoFilename. 18 | echo Calling: bash -c "$line" #output 19 | 20 | export PATH=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/miniconda3/bin:$PATH 21 | 22 | mkdir -p ~/.lockdir/ 23 | LOCKDIR=~/.lockdir/lock/ 24 | VENVDIR="$1" 25 | 26 | for i in {1..10000}; do 27 | if mkdir "$LOCKDIR"; then 28 | echo "Locking succeeded - Going to activate Conda" >&2 29 | source activate BC_36 30 | break 31 | 32 | else 33 | echo "Lock failed - sleep and try again" >&2 34 | pid=$$ 35 | sleeptime=$((pid%30)) 36 | 37 | sleep $((sleeptime+5))s 38 | fi 39 | done 40 | 41 | rmdir "$LOCKDIR" 42 | 43 | 44 | echo "Job started at: `date`" 45 | 46 | echo 47 | bash -c "$line" 48 | echo 49 | 50 | echo "Job finished with exit code $? at: `date`" 51 | 52 | echo DONE 53 | 54 | 55 | -------------------------------------------------------------------------------- /examples/PPO_on_cartpole/NEMO_OUTPUT/BC_7/configspace.json: -------------------------------------------------------------------------------- 1 | { 2 | "hyperparameters": [ 3 | { 4 | "name": "batch_size", 5 | "type": "uniform_int", 6 | "log": true, 7 | "lower": 8, 8 | "upper": 256, 9 | "default": 64 10 | }, 11 | { 12 | "name": "discount", 13 | "type": "uniform_float", 14 | "log": false, 15 | "lower": 0.0, 16 | "upper": 1.0, 17 | "default": 0.99 18 | }, 19 | { 20 | "name": "entropy_regularization", 21 | "type": "uniform_float", 22 | "log": false, 23 | "lower": 0.0, 24 | "upper": 1.0, 25 | "default": 0.01 26 | }, 27 | { 28 | "name": "learning_rate", 29 | "type": "uniform_float", 30 | "log": true, 31 | "lower": 1e-07, 32 | "upper": 0.1, 33 | "default": 0.001 34 | }, 35 | { 36 | "name": "likelihood_ratio_clipping", 37 | "type": "uniform_float", 38 | "log": false, 39 | "lower": 0.0, 40 | "upper": 1.0, 41 | "default": 0.2 42 | }, 43 | { 44 | "name": "n_units_1", 45 | "type": "uniform_int", 46 | "log": true, 47 | "lower": 8, 48 | "upper": 128, 49 | "default": 64 50 | }, 51 | { 52 | "name": "n_units_2", 53 | "type": "uniform_int", 54 | "log": true, 55 | "lower": 8, 56 | "upper": 128, 57 | "default": 64 58 | } 59 | ], 60 | "conditions": [], 61 | "forbiddens": [], 62 | "python_module_version": "0.4.7", 63 | "json_format_version": 0.1 64 | } -------------------------------------------------------------------------------- /examples/PPO_on_cartpole/NEMO_OUTPUT/BC_7/results.pkl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/automl/BOAH/7bbc5b97ccbb742c32dc8e6318ed628414cb86dc/examples/PPO_on_cartpole/NEMO_OUTPUT/BC_7/results.pkl -------------------------------------------------------------------------------- /examples/PPO_on_cartpole/NEMO_OUTPUT/BC_8/8/2018-12-21--9-52-33-855478.out: -------------------------------------------------------------------------------- 1 | Here's what we know from the MOAB environment 2 | MOAB_MACHINE=torque 3 | SHELL=/bin/bash 4 | HOME=/home/fr/fr_fr/fr_ke1011 5 | USER=fr_ke1011 6 | MOAB_JOBID=4603318[1] 7 | HOSTNAME=n3753.nemo.privat 8 | MOAB_JOBARRAYINDEX=1 9 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_8.cmd 10 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 11 | Calling: bash -c python run_BOHB.py --n 128 --run_id 8 --shared_directory ./BC_8/ --interface boot0 12 | Here's what we know from the MOAB environment 13 | MOAB_MACHINE=torque 14 | SHELL=/bin/bash 15 | HOME=/home/fr/fr_fr/fr_ke1011 16 | USER=fr_ke1011 17 | MOAB_JOBID=4603318[2] 18 | HOSTNAME=n3753.nemo.privat 19 | MOAB_JOBARRAYINDEX=2 20 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_8.cmd 21 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 22 | Calling: bash -c python run_BOHB.py --n 128 --run_id 8 --shared_directory ./BC_8/ --interface boot0 --worker 23 | Here's what we know from the MOAB environment 24 | MOAB_MACHINE=torque 25 | SHELL=/bin/bash 26 | HOME=/home/fr/fr_fr/fr_ke1011 27 | USER=fr_ke1011 28 | MOAB_JOBID=4603318[3] 29 | HOSTNAME=n3753.nemo.privat 30 | MOAB_JOBARRAYINDEX=3 31 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_8.cmd 32 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 33 | Calling: bash -c python run_BOHB.py --n 128 --run_id 8 --shared_directory ./BC_8/ --interface boot0 --worker 34 | Here's what we know from the MOAB environment 35 | MOAB_MACHINE=torque 36 | SHELL=/bin/bash 37 | HOME=/home/fr/fr_fr/fr_ke1011 38 | USER=fr_ke1011 39 | MOAB_JOBID=4603318[4] 40 | HOSTNAME=n3753.nemo.privat 41 | MOAB_JOBARRAYINDEX=4 42 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_8.cmd 43 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 44 | Calling: bash -c python run_BOHB.py --n 128 --run_id 8 --shared_directory ./BC_8/ --interface boot0 --worker 45 | Here's what we know from the MOAB environment 46 | MOAB_MACHINE=torque 47 | SHELL=/bin/bash 48 | HOME=/home/fr/fr_fr/fr_ke1011 49 | USER=fr_ke1011 50 | MOAB_JOBID=4603318[5] 51 | HOSTNAME=n3753.nemo.privat 52 | MOAB_JOBARRAYINDEX=5 53 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_8.cmd 54 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 55 | Calling: bash -c python run_BOHB.py --n 128 --run_id 8 --shared_directory ./BC_8/ --interface boot0 --worker 56 | Here's what we know from the MOAB environment 57 | MOAB_MACHINE=torque 58 | SHELL=/bin/bash 59 | HOME=/home/fr/fr_fr/fr_ke1011 60 | USER=fr_ke1011 61 | MOAB_JOBID=4603318[6] 62 | HOSTNAME=n3753.nemo.privat 63 | MOAB_JOBARRAYINDEX=6 64 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_8.cmd 65 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 66 | Calling: bash -c python run_BOHB.py --n 128 --run_id 8 --shared_directory ./BC_8/ --interface boot0 --worker 67 | Here's what we know from the MOAB environment 68 | MOAB_MACHINE=torque 69 | SHELL=/bin/bash 70 | HOME=/home/fr/fr_fr/fr_ke1011 71 | USER=fr_ke1011 72 | MOAB_JOBID=4603318[7] 73 | HOSTNAME=n3753.nemo.privat 74 | MOAB_JOBARRAYINDEX=7 75 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_8.cmd 76 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 77 | Calling: bash -c python run_BOHB.py --n 128 --run_id 8 --shared_directory ./BC_8/ --interface boot0 --worker 78 | Here's what we know from the MOAB environment 79 | MOAB_MACHINE=torque 80 | SHELL=/bin/bash 81 | HOME=/home/fr/fr_fr/fr_ke1011 82 | USER=fr_ke1011 83 | MOAB_JOBID=4603318[8] 84 | HOSTNAME=n3753.nemo.privat 85 | MOAB_JOBARRAYINDEX=8 86 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_8.cmd 87 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 88 | Calling: bash -c python run_BOHB.py --n 128 --run_id 8 --shared_directory ./BC_8/ --interface boot0 --worker 89 | Here's what we know from the MOAB environment 90 | MOAB_MACHINE=torque 91 | SHELL=/bin/bash 92 | HOME=/home/fr/fr_fr/fr_ke1011 93 | USER=fr_ke1011 94 | MOAB_JOBID=4603318[9] 95 | HOSTNAME=n3753.nemo.privat 96 | MOAB_JOBARRAYINDEX=9 97 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_8.cmd 98 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 99 | Calling: bash -c python run_BOHB.py --n 128 --run_id 8 --shared_directory ./BC_8/ --interface boot0 --worker 100 | Here's what we know from the MOAB environment 101 | MOAB_MACHINE=torque 102 | SHELL=/bin/bash 103 | HOME=/home/fr/fr_fr/fr_ke1011 104 | USER=fr_ke1011 105 | MOAB_JOBID=4603318[10] 106 | HOSTNAME=n3753.nemo.privat 107 | MOAB_JOBARRAYINDEX=10 108 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_8.cmd 109 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 110 | Calling: bash -c python run_BOHB.py --n 128 --run_id 8 --shared_directory ./BC_8/ --interface boot0 --worker 111 | Job started at: Fri Dec 21 10:20:30 CET 2018 112 | 113 | Job started at: Fri Dec 21 10:21:42 CET 2018 114 | 115 | Job started at: Fri Dec 21 10:21:49 CET 2018 116 | 117 | Job started at: Fri Dec 21 10:22:10 CET 2018 118 | 119 | Job started at: Fri Dec 21 10:23:08 CET 2018 120 | 121 | Job started at: Fri Dec 21 10:23:32 CET 2018 122 | 123 | Job started at: Fri Dec 21 10:25:38 CET 2018 124 | 125 | Job started at: Fri Dec 21 10:26:01 CET 2018 126 | 127 | Job started at: Fri Dec 21 10:26:24 CET 2018 128 | 129 | Job started at: Fri Dec 21 10:26:31 CET 2018 130 | 131 | 132 | Job finished with exit code 0 at: Fri Dec 21 15:59:09 CET 2018 133 | DONE 134 | 135 | Job finished with exit code 0 at: Fri Dec 21 15:59:09 CET 2018 136 | DONE 137 | 138 | Job finished with exit code 0 at: Fri Dec 21 15:59:09 CET 2018 139 | DONE 140 | 141 | Job finished with exit code 0 at: Fri Dec 21 15:59:09 CET 2018 142 | DONE 143 | 144 | Job finished with exit code 0 at: Fri Dec 21 15:59:09 CET 2018 145 | DONE 146 | 147 | Job finished with exit code 0 at: Fri Dec 21 15:59:09 CET 2018 148 | DONE 149 | 150 | 151 | Job finished with exit code 0 at: Fri Dec 21 15:59:09 CET 2018 152 | DONE 153 | Job finished with exit code 0 at: Fri Dec 21 15:59:09 CET 2018 154 | DONE 155 | 156 | Job finished with exit code 0 at: Fri Dec 21 15:59:09 CET 2018 157 | DONE 158 | 159 | Job finished with exit code 0 at: Fri Dec 21 15:59:09 CET 2018 160 | DONE 161 | -------------------------------------------------------------------------------- /examples/PPO_on_cartpole/NEMO_OUTPUT/BC_8/8/job_8.cmd_2018-12-21--9-52-33-855478.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #$ -S /bin/bash 3 | 4 | cd "/work/ws/nemo/fr_ke1011-BOHB_CAVE-0" 5 | jobs_file="/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_8.cmd" 6 | 7 | echo "Here's what we know from the MOAB environment" 8 | echo MOAB_MACHINE=$MOAB_MACHINE 9 | echo SHELL=$SHELL 10 | echo HOME=$HOME 11 | echo USER=$USER 12 | echo MOAB_JOBID=$MOAB_JOBID 13 | echo HOSTNAME=$HOSTNAME 14 | echo MOAB_JOBARRAYINDEX=$MOAB_JOBARRAYINDEX 15 | echo jobs_file=${jobs_file} 16 | echo PWD=`pwd` 17 | line=`head -n $MOAB_JOBARRAYINDEX "${jobs_file}" | tail -1` # Get line of todoFilename. 18 | echo Calling: bash -c "$line" #output 19 | 20 | export PATH=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/miniconda3/bin:$PATH 21 | 22 | mkdir -p ~/.lockdir/ 23 | LOCKDIR=~/.lockdir/lock/ 24 | VENVDIR="$1" 25 | 26 | for i in {1..10000}; do 27 | if mkdir "$LOCKDIR"; then 28 | echo "Locking succeeded - Going to activate Conda" >&2 29 | source activate BC_36 30 | break 31 | 32 | else 33 | echo "Lock failed - sleep and try again" >&2 34 | pid=$$ 35 | sleeptime=$((pid%30)) 36 | 37 | sleep $((sleeptime+5))s 38 | fi 39 | done 40 | 41 | rmdir "$LOCKDIR" 42 | 43 | 44 | echo "Job started at: `date`" 45 | 46 | echo 47 | bash -c "$line" 48 | echo 49 | 50 | echo "Job finished with exit code $? at: `date`" 51 | 52 | echo DONE 53 | 54 | 55 | -------------------------------------------------------------------------------- /examples/PPO_on_cartpole/NEMO_OUTPUT/BC_8/configspace.json: -------------------------------------------------------------------------------- 1 | { 2 | "hyperparameters": [ 3 | { 4 | "name": "batch_size", 5 | "type": "uniform_int", 6 | "log": true, 7 | "lower": 8, 8 | "upper": 256, 9 | "default": 64 10 | }, 11 | { 12 | "name": "discount", 13 | "type": "uniform_float", 14 | "log": false, 15 | "lower": 0.0, 16 | "upper": 1.0, 17 | "default": 0.99 18 | }, 19 | { 20 | "name": "entropy_regularization", 21 | "type": "uniform_float", 22 | "log": false, 23 | "lower": 0.0, 24 | "upper": 1.0, 25 | "default": 0.01 26 | }, 27 | { 28 | "name": "learning_rate", 29 | "type": "uniform_float", 30 | "log": true, 31 | "lower": 1e-07, 32 | "upper": 0.1, 33 | "default": 0.001 34 | }, 35 | { 36 | "name": "likelihood_ratio_clipping", 37 | "type": "uniform_float", 38 | "log": false, 39 | "lower": 0.0, 40 | "upper": 1.0, 41 | "default": 0.2 42 | }, 43 | { 44 | "name": "n_units_1", 45 | "type": "uniform_int", 46 | "log": true, 47 | "lower": 8, 48 | "upper": 128, 49 | "default": 64 50 | }, 51 | { 52 | "name": "n_units_2", 53 | "type": "uniform_int", 54 | "log": true, 55 | "lower": 8, 56 | "upper": 128, 57 | "default": 64 58 | } 59 | ], 60 | "conditions": [], 61 | "forbiddens": [], 62 | "python_module_version": "0.4.7", 63 | "json_format_version": 0.1 64 | } -------------------------------------------------------------------------------- /examples/PPO_on_cartpole/NEMO_OUTPUT/BC_8/results.pkl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/automl/BOAH/7bbc5b97ccbb742c32dc8e6318ed628414cb86dc/examples/PPO_on_cartpole/NEMO_OUTPUT/BC_8/results.pkl -------------------------------------------------------------------------------- /examples/PPO_on_cartpole/NEMO_OUTPUT/BC_9/9/2018-12-21--13-22-46-352613.out: -------------------------------------------------------------------------------- 1 | Here's what we know from the MOAB environment 2 | MOAB_MACHINE=torque 3 | SHELL=/bin/bash 4 | HOME=/home/fr/fr_fr/fr_ke1011 5 | USER=fr_ke1011 6 | MOAB_JOBID=4606561[1] 7 | HOSTNAME=n4254.nemo.privat 8 | MOAB_JOBARRAYINDEX=1 9 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_9.cmd 10 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 11 | Calling: bash -c python run_BOHB.py --n 128 --run_id 9 --shared_directory ./BC_9/ --interface boot0 12 | Here's what we know from the MOAB environment 13 | MOAB_MACHINE=torque 14 | SHELL=/bin/bash 15 | HOME=/home/fr/fr_fr/fr_ke1011 16 | USER=fr_ke1011 17 | MOAB_JOBID=4606561[2] 18 | HOSTNAME=n4254.nemo.privat 19 | MOAB_JOBARRAYINDEX=2 20 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_9.cmd 21 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 22 | Calling: bash -c python run_BOHB.py --n 128 --run_id 9 --shared_directory ./BC_9/ --interface boot0 --worker 23 | Here's what we know from the MOAB environment 24 | MOAB_MACHINE=torque 25 | SHELL=/bin/bash 26 | HOME=/home/fr/fr_fr/fr_ke1011 27 | USER=fr_ke1011 28 | MOAB_JOBID=4606561[3] 29 | HOSTNAME=n4254.nemo.privat 30 | MOAB_JOBARRAYINDEX=3 31 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_9.cmd 32 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 33 | Calling: bash -c python run_BOHB.py --n 128 --run_id 9 --shared_directory ./BC_9/ --interface boot0 --worker 34 | Here's what we know from the MOAB environment 35 | MOAB_MACHINE=torque 36 | SHELL=/bin/bash 37 | HOME=/home/fr/fr_fr/fr_ke1011 38 | USER=fr_ke1011 39 | MOAB_JOBID=4606561[4] 40 | HOSTNAME=n4254.nemo.privat 41 | MOAB_JOBARRAYINDEX=4 42 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_9.cmd 43 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 44 | Calling: bash -c python run_BOHB.py --n 128 --run_id 9 --shared_directory ./BC_9/ --interface boot0 --worker 45 | Here's what we know from the MOAB environment 46 | MOAB_MACHINE=torque 47 | SHELL=/bin/bash 48 | HOME=/home/fr/fr_fr/fr_ke1011 49 | USER=fr_ke1011 50 | MOAB_JOBID=4606561[5] 51 | HOSTNAME=n4254.nemo.privat 52 | MOAB_JOBARRAYINDEX=5 53 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_9.cmd 54 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 55 | Calling: bash -c python run_BOHB.py --n 128 --run_id 9 --shared_directory ./BC_9/ --interface boot0 --worker 56 | Here's what we know from the MOAB environment 57 | MOAB_MACHINE=torque 58 | SHELL=/bin/bash 59 | HOME=/home/fr/fr_fr/fr_ke1011 60 | USER=fr_ke1011 61 | MOAB_JOBID=4606561[6] 62 | HOSTNAME=n4254.nemo.privat 63 | MOAB_JOBARRAYINDEX=6 64 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_9.cmd 65 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 66 | Calling: bash -c python run_BOHB.py --n 128 --run_id 9 --shared_directory ./BC_9/ --interface boot0 --worker 67 | Here's what we know from the MOAB environment 68 | MOAB_MACHINE=torque 69 | SHELL=/bin/bash 70 | HOME=/home/fr/fr_fr/fr_ke1011 71 | USER=fr_ke1011 72 | MOAB_JOBID=4606561[7] 73 | HOSTNAME=n4254.nemo.privat 74 | MOAB_JOBARRAYINDEX=7 75 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_9.cmd 76 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 77 | Calling: bash -c python run_BOHB.py --n 128 --run_id 9 --shared_directory ./BC_9/ --interface boot0 --worker 78 | Here's what we know from the MOAB environment 79 | MOAB_MACHINE=torque 80 | SHELL=/bin/bash 81 | HOME=/home/fr/fr_fr/fr_ke1011 82 | USER=fr_ke1011 83 | MOAB_JOBID=4606561[8] 84 | HOSTNAME=n4254.nemo.privat 85 | MOAB_JOBARRAYINDEX=8 86 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_9.cmd 87 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 88 | Calling: bash -c python run_BOHB.py --n 128 --run_id 9 --shared_directory ./BC_9/ --interface boot0 --worker 89 | Here's what we know from the MOAB environment 90 | MOAB_MACHINE=torque 91 | SHELL=/bin/bash 92 | HOME=/home/fr/fr_fr/fr_ke1011 93 | USER=fr_ke1011 94 | MOAB_JOBID=4606561[9] 95 | HOSTNAME=n4254.nemo.privat 96 | MOAB_JOBARRAYINDEX=9 97 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_9.cmd 98 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 99 | Calling: bash -c python run_BOHB.py --n 128 --run_id 9 --shared_directory ./BC_9/ --interface boot0 --worker 100 | Here's what we know from the MOAB environment 101 | MOAB_MACHINE=torque 102 | SHELL=/bin/bash 103 | HOME=/home/fr/fr_fr/fr_ke1011 104 | USER=fr_ke1011 105 | MOAB_JOBID=4606561[10] 106 | HOSTNAME=n4254.nemo.privat 107 | MOAB_JOBARRAYINDEX=10 108 | jobs_file=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_9.cmd 109 | PWD=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0 110 | Calling: bash -c python run_BOHB.py --n 128 --run_id 9 --shared_directory ./BC_9/ --interface boot0 --worker 111 | Job started at: Fri Dec 21 15:25:24 CET 2018 112 | 113 | Job started at: Fri Dec 21 15:25:30 CET 2018 114 | 115 | Job started at: Fri Dec 21 15:25:35 CET 2018 116 | 117 | Job started at: Fri Dec 21 15:25:38 CET 2018 118 | 119 | Job started at: Fri Dec 21 15:25:41 CET 2018 120 | 121 | Job started at: Fri Dec 21 15:25:59 CET 2018 122 | 123 | Job started at: Fri Dec 21 15:26:11 CET 2018 124 | 125 | Job started at: Fri Dec 21 15:26:19 CET 2018 126 | 127 | Job started at: Fri Dec 21 15:26:41 CET 2018 128 | 129 | Job started at: Fri Dec 21 15:26:49 CET 2018 130 | 131 | 132 | Job finished with exit code 0 at: Fri Dec 21 20:37:48 CET 2018 133 | DONE 134 | 135 | Job finished with exit code 0 at: Fri Dec 21 20:37:48 CET 2018 136 | DONE 137 | 138 | Job finished with exit code 0 at: Fri Dec 21 20:37:48 CET 2018 139 | DONE 140 | 141 | Job finished with exit code 0 at: Fri Dec 21 20:37:48 CET 2018 142 | DONE 143 | 144 | Job finished with exit code 0 at: Fri Dec 21 20:37:48 CET 2018 145 | DONE 146 | 147 | Job finished with exit code 0 at: Fri Dec 21 20:37:48 CET 2018 148 | DONE 149 | 150 | 151 | Job finished with exit code 0 at: Fri Dec 21 20:37:48 CET 2018 152 | DONE 153 | Job finished with exit code 0 at: Fri Dec 21 20:37:48 CET 2018 154 | DONE 155 | 156 | Job finished with exit code 0 at: Fri Dec 21 20:37:48 CET 2018 157 | DONE 158 | 159 | Job finished with exit code 0 at: Fri Dec 21 20:37:48 CET 2018 160 | DONE 161 | -------------------------------------------------------------------------------- /examples/PPO_on_cartpole/NEMO_OUTPUT/BC_9/9/job_9.cmd_2018-12-21--13-22-46-352613.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #$ -S /bin/bash 3 | 4 | cd "/work/ws/nemo/fr_ke1011-BOHB_CAVE-0" 5 | jobs_file="/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/job_9.cmd" 6 | 7 | echo "Here's what we know from the MOAB environment" 8 | echo MOAB_MACHINE=$MOAB_MACHINE 9 | echo SHELL=$SHELL 10 | echo HOME=$HOME 11 | echo USER=$USER 12 | echo MOAB_JOBID=$MOAB_JOBID 13 | echo HOSTNAME=$HOSTNAME 14 | echo MOAB_JOBARRAYINDEX=$MOAB_JOBARRAYINDEX 15 | echo jobs_file=${jobs_file} 16 | echo PWD=`pwd` 17 | line=`head -n $MOAB_JOBARRAYINDEX "${jobs_file}" | tail -1` # Get line of todoFilename. 18 | echo Calling: bash -c "$line" #output 19 | 20 | export PATH=/work/ws/nemo/fr_ke1011-BOHB_CAVE-0/miniconda3/bin:$PATH 21 | 22 | mkdir -p ~/.lockdir/ 23 | LOCKDIR=~/.lockdir/lock/ 24 | VENVDIR="$1" 25 | 26 | for i in {1..10000}; do 27 | if mkdir "$LOCKDIR"; then 28 | echo "Locking succeeded - Going to activate Conda" >&2 29 | source activate BC_36 30 | break 31 | 32 | else 33 | echo "Lock failed - sleep and try again" >&2 34 | pid=$$ 35 | sleeptime=$((pid%30)) 36 | 37 | sleep $((sleeptime+5))s 38 | fi 39 | done 40 | 41 | rmdir "$LOCKDIR" 42 | 43 | 44 | echo "Job started at: `date`" 45 | 46 | echo 47 | bash -c "$line" 48 | echo 49 | 50 | echo "Job finished with exit code $? at: `date`" 51 | 52 | echo DONE 53 | 54 | 55 | -------------------------------------------------------------------------------- /examples/PPO_on_cartpole/NEMO_OUTPUT/BC_9/configspace.json: -------------------------------------------------------------------------------- 1 | { 2 | "hyperparameters": [ 3 | { 4 | "name": "batch_size", 5 | "type": "uniform_int", 6 | "log": true, 7 | "lower": 8, 8 | "upper": 256, 9 | "default": 64 10 | }, 11 | { 12 | "name": "discount", 13 | "type": "uniform_float", 14 | "log": false, 15 | "lower": 0.0, 16 | "upper": 1.0, 17 | "default": 0.99 18 | }, 19 | { 20 | "name": "entropy_regularization", 21 | "type": "uniform_float", 22 | "log": false, 23 | "lower": 0.0, 24 | "upper": 1.0, 25 | "default": 0.01 26 | }, 27 | { 28 | "name": "learning_rate", 29 | "type": "uniform_float", 30 | "log": true, 31 | "lower": 1e-07, 32 | "upper": 0.1, 33 | "default": 0.001 34 | }, 35 | { 36 | "name": "likelihood_ratio_clipping", 37 | "type": "uniform_float", 38 | "log": false, 39 | "lower": 0.0, 40 | "upper": 1.0, 41 | "default": 0.2 42 | }, 43 | { 44 | "name": "n_units_1", 45 | "type": "uniform_int", 46 | "log": true, 47 | "lower": 8, 48 | "upper": 128, 49 | "default": 64 50 | }, 51 | { 52 | "name": "n_units_2", 53 | "type": "uniform_int", 54 | "log": true, 55 | "lower": 8, 56 | "upper": 128, 57 | "default": 64 58 | } 59 | ], 60 | "conditions": [], 61 | "forbiddens": [], 62 | "python_module_version": "0.4.7", 63 | "json_format_version": 0.1 64 | } -------------------------------------------------------------------------------- /examples/PPO_on_cartpole/NEMO_OUTPUT/BC_9/results.pkl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/automl/BOAH/7bbc5b97ccbb742c32dc8e6318ed628414cb86dc/examples/PPO_on_cartpole/NEMO_OUTPUT/BC_9/results.pkl -------------------------------------------------------------------------------- /examples/PPO_on_cartpole/run_BOHB.py: -------------------------------------------------------------------------------- 1 | import logging 2 | logging.basicConfig(level=logging.INFO) 3 | 4 | import argparse 5 | import pickle 6 | import os 7 | import shutil 8 | import time 9 | 10 | import hpbandster.core.nameserver as hpns 11 | import hpbandster.core.result as hpres 12 | from hpbandster.optimizers import BOHB as BOHB 13 | from hpbandster.core.worker import Worker 14 | 15 | import hpolib.benchmarks.rl.cartpole as cartpole 16 | 17 | import tensorflow as tf 18 | import ConfigSpace.configuration_space as cs 19 | import ConfigSpace.read_and_write.json as pcs_out 20 | 21 | session_conf = tf.ConfigProto( 22 | intra_op_parallelism_threads=1, 23 | inter_op_parallelism_threads=1) 24 | sess = tf.Session(config=session_conf) 25 | MOAB_JOBID=4598620 26 | 27 | 28 | class MyWorker(Worker): 29 | 30 | def compute(self, config, budget, **kwargs): 31 | b = cartpole.CartpoleReduced(rng=1) 32 | config = cs.Configuration(b.get_configuration_space(), config) 33 | res_val = b.objective_function(configuration=config, budget=int(budget)) 34 | 35 | return({ 36 | 'loss': res_val['function_value'], 37 | 'info': res_val 38 | }) 39 | 40 | @staticmethod 41 | def get_configspace(): 42 | return cartpole.CartpoleReduced.get_configuration_space() 43 | 44 | 45 | def main(): 46 | parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter) 47 | parser.add_argument('--n_iterations', type=int, help='Number of iterations performed by the optimizer', default=4) 48 | parser.add_argument('--worker', help='Flag to turn this into a worker process', action='store_true') 49 | parser.add_argument('--run_id', type=str, help='A unique run id for this optimization run. An easy option is to use' 50 | ' the job id of the clusters scheduler.') 51 | parser.add_argument('--shared_directory', type=str, help='A directory that is accessible for all processes, e.g. a NFS share.') 52 | parser.add_argument('--interface', type=str, help='Which network interface to use', default="eth1") 53 | 54 | args = parser.parse_args() 55 | 56 | try: 57 | os.mkdir(args.shared_directory) 58 | except FileExistsError: 59 | pass 60 | 61 | # Every process has to lookup the hostname 62 | host = hpns.nic_name_to_host(args.interface) 63 | 64 | if args.worker: 65 | time.sleep(60) # short artificial delay to make sure the nameserver is already running 66 | w = MyWorker(run_id=args.run_id, host=host) 67 | w.load_nameserver_credentials(working_directory=args.shared_directory) 68 | w.run(background=False) 69 | exit(0) 70 | 71 | # Write the configspace 72 | cs = MyWorker.get_configspace() 73 | with open(os.path.join(args.shared_directory, 'configspace.json'), "w") as fh: 74 | fh.write( 75 | pcs_out.write(cs) 76 | ) 77 | 78 | result_logger = hpres.json_result_logger(directory=args.shared_directory, overwrite=True) 79 | NS = hpns.NameServer(run_id=args.run_id, host=host, port=0, working_directory=args.shared_directory) 80 | ns_host, ns_port = NS.start() 81 | 82 | w = MyWorker(run_id=args.run_id, host=host, nameserver=ns_host, nameserver_port=ns_port) 83 | w.run(background=True) 84 | 85 | # Run an optimizer 86 | # We now have to specify the host, and the nameserver information 87 | bohb = BOHB(configspace=cs, 88 | run_id=args.run_id, 89 | host=host, 90 | nameserver=ns_host, 91 | nameserver_port=ns_port, 92 | eta=3, 93 | result_logger=result_logger, 94 | min_budget=1, max_budget=9 95 | ) 96 | res = bohb.run(n_iterations=args.n_iterations, min_n_workers=1) 97 | 98 | # In a cluster environment, you usually want to store the results for later analysis. 99 | # One option is to simply pickle the Result object 100 | with open(os.path.join(args.shared_directory, 'results.pkl'), 'wb') as fh: 101 | pickle.dump(res, fh) 102 | 103 | # Step 4: Shutdown 104 | # After the optimizer run, we must shutdown the master and the nameserver. 105 | bohb.shutdown(shutdown_workers=True) 106 | NS.shutdown() 107 | 108 | 109 | if __name__ == "__main__": 110 | main() 111 | 112 | -------------------------------------------------------------------------------- /examples/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/automl/BOAH/7bbc5b97ccbb742c32dc8e6318ed628414cb86dc/examples/__init__.py -------------------------------------------------------------------------------- /examples/icml_2018_experiments/icml2018requirements.txt: -------------------------------------------------------------------------------- 1 | cython 2 | numpy 3 | jupyter 4 | cave 5 | hpbandster 6 | gym 7 | matplotlib 8 | git+https://github.com/hyperopt/hyperopt.git 9 | git+https://github.com/automl/sgmcmc.git 10 | git+https://github.com/Lasagne/Lasagne.git 11 | git+https://github.com/automl/HPOlib2.git@new_benchmarks 12 | theano 13 | tensorforce 14 | tensorflow 15 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/bnn/bostonhousing/bohb/configspace.pcs: -------------------------------------------------------------------------------- 1 | burn_in real [0.0, 0.8] [0.3] 2 | l_rate real [1e-06, 0.1] [0.01]log 3 | mdecay real [0.0, 1.0] [0.05] 4 | n_units_1 integer [16, 512] [64]log 5 | n_units_2 integer [16, 512] [64]log -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/bnn/bostonhousing/hyperband/configspace.pcs: -------------------------------------------------------------------------------- 1 | burn_in real [0.0, 0.8] [0.3] 2 | l_rate real [1e-06, 0.1] [0.01]log 3 | mdecay real [0.0, 1.0] [0.05] 4 | n_units_1 integer [16, 512] [64]log 5 | n_units_2 integer [16, 512] [64]log -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/bnn/bostonhousing/randomsearch/configs.json: -------------------------------------------------------------------------------- 1 | [[0, 0, 0], {"burn_in": 0.44963794527553835, "l_rate": 0.010183803712916684, "mdecay": 0.6085956146982001, "n_units_1": 188, "n_units_2": 38}, {}] 2 | [[0, 0, 1], {"burn_in": 0.02372424180240662, "l_rate": 0.000507609166686678, "mdecay": 0.3868284000371073, "n_units_1": 39, "n_units_2": 35}, {}] 3 | [[0, 0, 2], {"burn_in": 0.38255713092599203, "l_rate": 7.374645650848418e-05, "mdecay": 0.18274441252610585, "n_units_1": 31, "n_units_2": 503}, {}] 4 | [[0, 0, 3], {"burn_in": 0.23815525336749443, "l_rate": 8.379524952601937e-06, "mdecay": 0.7729473094375484, "n_units_1": 36, "n_units_2": 20}, {}] 5 | [[1, 0, 0], {"burn_in": 0.15977747601901904, "l_rate": 0.00016770372033964506, "mdecay": 0.8302302480155892, "n_units_1": 278, "n_units_2": 228}, {}] 6 | [[1, 0, 1], {"burn_in": 0.3889287787867409, "l_rate": 1.8019758530619887e-06, "mdecay": 0.6824848424114307, "n_units_1": 297, "n_units_2": 260}, {}] 7 | [[1, 0, 2], {"burn_in": 0.7596773822499889, "l_rate": 0.01580224495392485, "mdecay": 0.1513906835292036, "n_units_1": 21, "n_units_2": 48}, {}] 8 | [[1, 0, 3], {"burn_in": 0.1347141533969288, "l_rate": 6.049850488837676e-05, "mdecay": 0.8241321548820925, "n_units_1": 263, "n_units_2": 49}, {}] 9 | [[2, 0, 0], {"burn_in": 0.6906690603138327, "l_rate": 0.0005346688231212849, "mdecay": 0.1686694108376411, "n_units_1": 196, "n_units_2": 42}, {}] 10 | [[2, 0, 1], {"burn_in": 0.7109545549767687, "l_rate": 0.0007043313118039121, "mdecay": 0.6826227212688709, "n_units_1": 17, "n_units_2": 432}, {}] 11 | [[2, 0, 2], {"burn_in": 0.06572088536401192, "l_rate": 0.0139544722260954, "mdecay": 0.6008177291145333, "n_units_1": 26, "n_units_2": 84}, {}] 12 | [[2, 0, 3], {"burn_in": 0.47856694021611856, "l_rate": 0.0004855110216577847, "mdecay": 0.7449887777488832, "n_units_1": 214, "n_units_2": 33}, {}] 13 | [[3, 0, 0], {"burn_in": 0.2559562104180197, "l_rate": 0.00027459876017085105, "mdecay": 0.017200231880746264, "n_units_1": 108, "n_units_2": 130}, {}] 14 | [[3, 0, 1], {"burn_in": 0.0013835441180534147, "l_rate": 0.011169329608669808, "mdecay": 0.9333125199232594, "n_units_1": 118, "n_units_2": 50}, {}] 15 | [[3, 0, 2], {"burn_in": 0.34752463319246063, "l_rate": 0.0008687852464753803, "mdecay": 0.8383717186097498, "n_units_1": 22, "n_units_2": 60}, {}] 16 | [[3, 0, 3], {"burn_in": 0.06468823912939854, "l_rate": 2.589631737280751e-05, "mdecay": 0.39131011967842066, "n_units_1": 413, "n_units_2": 44}, {}] 17 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/bnn/bostonhousing/randomsearch/configspace.pcs: -------------------------------------------------------------------------------- 1 | burn_in real [0.0, 0.8] [0.3] 2 | l_rate real [1e-06, 0.1] [0.01]log 3 | mdecay real [0.0, 1.0] [0.05] 4 | n_units_1 integer [16, 512] [64]log 5 | n_units_2 integer [16, 512] [64]log -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/bnn/bostonhousing/randomsearch/results.json: -------------------------------------------------------------------------------- 1 | [[0, 0, 0], 10000, {"submitted": 1556233428.1287634, "started": 1556233428.1293104, "finished": 1556233457.4017665}, {"loss": 36.00227167318795, "info": {"function_value": 36.00227167318795, "cost": 29.26032328605652}}, null] 2 | [[0, 0, 1], 10000, {"submitted": 1556233457.404781, "started": 1556233457.405254, "finished": 1556233473.6992638}, {"loss": 2394.778951563532, "info": {"function_value": 2394.778951563532, "cost": 16.285648345947266}}, null] 3 | [[0, 0, 2], 10000, {"submitted": 1556233473.701371, "started": 1556233473.7018306, "finished": 1556233522.5702417}, {"loss": 923371.2592966629, "info": {"function_value": 923371.2592966629, "cost": 48.85769557952881}}, null] 4 | [[0, 0, 3], 10000, {"submitted": 1556233522.5727465, "started": 1556233522.573214, "finished": 1556233535.982756}, {"loss": 948209501.3180763, "info": {"function_value": 948209501.3180763, "cost": 13.401951789855957}}, null] 5 | [[1, 0, 0], 10000, {"submitted": 1556233535.9859276, "started": 1556233535.9863577, "finished": 1556233660.694222}, {"loss": 2410.260176877477, "info": {"function_value": 2410.260176877477, "cost": 124.69631171226501}}, null] 6 | [[1, 0, 1], 10000, {"submitted": 1556233660.6967733, "started": 1556233660.6972642, "finished": 1556233818.8101218}, {"loss": 3958767219.431383, "info": {"function_value": 3958767219.431383, "cost": 158.1065981388092}}, null] 7 | [[1, 0, 2], 10000, {"submitted": 1556233818.8126626, "started": 1556233818.81315, "finished": 1556233834.449396}, {"loss": 29.03885408922502, "info": {"function_value": 29.03885408922502, "cost": 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1556233956.8894892, "started": 1556233956.890096, "finished": 1556233986.7900736}, {"loss": 12327.111175682216, "info": {"function_value": 12327.111175682216, "cost": 29.891435861587524}}, null] 13 | [[3, 0, 0], 10000, {"submitted": 1556233986.792641, "started": 1556233986.7931159, "finished": 1556234028.282208}, {"loss": 130.9928884371912, "info": {"function_value": 130.9928884371912, "cost": 41.47801899909973}}, null] 14 | [[3, 0, 1], 10000, {"submitted": 1556234028.2846582, "started": 1556234028.285121, "finished": 1556234052.3907852}, {"loss": 101.13238910908652, "info": {"function_value": 101.13238910908652, "cost": 24.09392213821411}}, null] 15 | [[3, 0, 2], 10000, {"submitted": 1556234052.3932624, "started": 1556234052.3937256, "finished": 1556234068.5042982}, {"loss": 5796.1314218607995, "info": {"function_value": 5796.1314218607995, "cost": 16.102370977401733}}, null] 16 | [[3, 0, 3], 10000, {"submitted": 1556234068.5065312, "started": 1556234068.5070784, "finished": 1556234123.4422617}, {"loss": 2520871.3598693423, "info": {"function_value": 2520871.3598693423, "cost": 54.923059701919556}}, null] 17 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/bnn/bostonhousing/smac/run_1739378298/configspace.json: -------------------------------------------------------------------------------- 1 | { 2 | "hyperparameters": [ 3 | { 4 | "name": "burn_in", 5 | "type": "uniform_float", 6 | "log": false, 7 | "lower": 0.0, 8 | "upper": 0.8, 9 | "default": 0.3 10 | }, 11 | { 12 | "name": "l_rate", 13 | "type": "uniform_float", 14 | "log": true, 15 | "lower": 1e-06, 16 | "upper": 0.1, 17 | "default": 0.01 18 | }, 19 | { 20 | "name": "mdecay", 21 | "type": "uniform_float", 22 | "log": false, 23 | "lower": 0.0, 24 | "upper": 1.0, 25 | "default": 0.05 26 | }, 27 | { 28 | "name": "n_units_1", 29 | "type": "uniform_int", 30 | "log": true, 31 | "lower": 16, 32 | "upper": 512, 33 | "default": 64 34 | }, 35 | { 36 | "name": "n_units_2", 37 | "type": "uniform_int", 38 | "log": true, 39 | "lower": 16, 40 | "upper": 512, 41 | "default": 64 42 | } 43 | ], 44 | "conditions": [], 45 | "forbiddens": [], 46 | "python_module_version": "0.4.10", 47 | "json_format_version": 0.1 48 | } -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/bnn/bostonhousing/smac/run_1739378298/configspace.pcs: -------------------------------------------------------------------------------- 1 | burn_in real [0.0, 0.8] [0.3] 2 | l_rate real [1e-06, 0.1] [0.01]log 3 | mdecay real [0.0, 1.0] [0.05] 4 | n_units_1 integer [16, 512] [64]log 5 | n_units_2 integer [16, 512] [64]log -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/bnn/bostonhousing/smac/run_1739378298/scenario.txt: -------------------------------------------------------------------------------- 1 | execdir = . 2 | deterministic = True 3 | run_obj = quality 4 | overall_obj = par10 5 | par_factor = 10 6 | cost_for_crash = 2147483647.0 7 | algo_runs_timelimit = inf 8 | wallclock_limit = inf 9 | always_race_default = False 10 | ta_run_limit = 16.0 11 | initial_incumbent = RANDOM 12 | pcs_fn = opt_results/bnn/bostonhousing/smac/run_1739378298/configspace.json 13 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/bnn/bostonhousing/smac/run_1739378298/stats.json: -------------------------------------------------------------------------------- 1 | {"ta_runs": 16, "n_configs": 16, "wallclock_time_used": 2747.6394968032837, "ta_time_used": 2726.6860847473145, "inc_changed": 4, "_n_configs_per_intensify": 14, "_n_calls_of_intensify": 7, "_ema_n_configs_per_intensifiy": 2.0, "_EMA_ALPHA": 0.2} -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/bnn/bostonhousing/smac/run_1739378298/traj_aclib2.json: -------------------------------------------------------------------------------- 1 | {"cpu_time": 0, "total_cpu_time": null, "wallclock_time": 0.0023317337036132812, "evaluations": 0, "cost": 2147483648, "incumbent": ["burn_in='0.7449168972841247'", "l_rate='0.023274625892008422'", "mdecay='0.34691504838649156'", "n_units_1='299'", "n_units_2='378'"], "origin": "Random initial design."} 2 | {"cpu_time": 338.2403540611267, "total_cpu_time": null, "wallclock_time": 338.28612875938416, "evaluations": 1, "cost": 44.73394077098371, "incumbent": ["burn_in='0.7449168972841247'", "l_rate='0.023274625892008422'", "mdecay='0.34691504838649156'", "n_units_1='299'", "n_units_2='378'"], "origin": "Random initial design."} 3 | {"cpu_time": 888.9682219028473, "total_cpu_time": null, "wallclock_time": 895.5453667640686, "evaluations": 8, "cost": 8.850105446315997, "incumbent": ["burn_in='0.7821861723196819'", "l_rate='0.09864203596860698'", "mdecay='0.15556741022530218'", "n_units_1='20'", "n_units_2='425'"], "origin": "Random Search (sorted)"} 4 | {"cpu_time": 1538.6030957698822, "total_cpu_time": null, "wallclock_time": 1548.278410434723, "evaluations": 11, "cost": 7.389351352343085, "incumbent": ["burn_in='0.4401689253145046'", "l_rate='0.016992876300442057'", "mdecay='0.004043439598518939'", "n_units_1='173'", "n_units_2='152'"], "origin": "Random Search (sorted)"} 5 | {"cpu_time": 2539.6154973506927, "total_cpu_time": null, "wallclock_time": 2556.4256768226624, "evaluations": 15, "cost": 3.8516996888768507, "incumbent": ["burn_in='0.7753793259809143'", "l_rate='0.07658283284744892'", "mdecay='0.26226539027151374'", "n_units_1='69'", "n_units_2='21'"], "origin": "Random Search (sorted)"} 6 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/bnn/bostonhousing/smac/run_1739378298/traj_old.csv: -------------------------------------------------------------------------------- 1 | "CPU Time Used","Estimated Training Performance","Wallclock Time","Incumbent ID","Automatic Configurator (CPU) Time","Configuration..." 2 | 0.000000, 2147483648.000000, 0.002332, 1, 0.002332, burn_in='0.7449168972841247', l_rate='0.023274625892008422', mdecay='0.34691504838649156', n_units_1='299', n_units_2='378' 3 | 338.240354, 44.733941, 338.286129, 1, 0.045775, burn_in='0.7449168972841247', l_rate='0.023274625892008422', mdecay='0.34691504838649156', n_units_1='299', n_units_2='378' 4 | 888.968222, 8.850105, 895.545367, 2, 6.577145, burn_in='0.7821861723196819', l_rate='0.09864203596860698', mdecay='0.15556741022530218', n_units_1='20', n_units_2='425' 5 | 1538.603096, 7.389351, 1548.278410, 3, 9.675315, burn_in='0.4401689253145046', l_rate='0.016992876300442057', mdecay='0.004043439598518939', n_units_1='173', n_units_2='152' 6 | 2539.615497, 3.851700, 2556.425677, 4, 16.810179, burn_in='0.7753793259809143', l_rate='0.07658283284744892', mdecay='0.26226539027151374', n_units_1='69', n_units_2='21' 7 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/bnn/proteinstructure/bohb/configspace.pcs: -------------------------------------------------------------------------------- 1 | burn_in real [0.0, 0.8] [0.3] 2 | l_rate real [1e-06, 0.1] [0.01]log 3 | mdecay real [0.0, 1.0] [0.05] 4 | n_units_1 integer [16, 512] [64]log 5 | n_units_2 integer [16, 512] [64]log -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/bnn/proteinstructure/hyperband/HPB_run_0_pyro.pkl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/automl/BOAH/7bbc5b97ccbb742c32dc8e6318ed628414cb86dc/examples/icml_2018_experiments/opt_results/bnn/proteinstructure/hyperband/HPB_run_0_pyro.pkl -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/bnn/proteinstructure/hyperband/configspace.pcs: -------------------------------------------------------------------------------- 1 | burn_in real [0.0, 0.8] [0.3] 2 | l_rate real [1e-06, 0.1] [0.01]log 3 | mdecay real [0.0, 1.0] [0.05] 4 | n_units_1 integer [16, 512] [64]log 5 | n_units_2 integer [16, 512] [64]log -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/bnn/proteinstructure/randomsearch/configs.json: -------------------------------------------------------------------------------- 1 | [[0, 0, 0], {"burn_in": 0.3462627777223519, "l_rate": 0.001296700235723483, "mdecay": 0.7072693800970119, "n_units_1": 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-------------------------------------------------------------------------------- 1 | { 2 | "hyperparameters": [ 3 | { 4 | "name": "burn_in", 5 | "type": "uniform_float", 6 | "log": false, 7 | "lower": 0.0, 8 | "upper": 0.8, 9 | "default": 0.3 10 | }, 11 | { 12 | "name": "l_rate", 13 | "type": "uniform_float", 14 | "log": true, 15 | "lower": 1e-06, 16 | "upper": 0.1, 17 | "default": 0.01 18 | }, 19 | { 20 | "name": "mdecay", 21 | "type": "uniform_float", 22 | "log": false, 23 | "lower": 0.0, 24 | "upper": 1.0, 25 | "default": 0.05 26 | }, 27 | { 28 | "name": "n_units_1", 29 | "type": "uniform_int", 30 | "log": true, 31 | "lower": 16, 32 | "upper": 512, 33 | "default": 64 34 | }, 35 | { 36 | "name": "n_units_2", 37 | "type": "uniform_int", 38 | "log": true, 39 | "lower": 16, 40 | "upper": 512, 41 | "default": 64 42 | } 43 | ], 44 | "conditions": [], 45 | "forbiddens": [], 46 | "python_module_version": "0.4.10", 47 | "json_format_version": 0.1 48 | } -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/bnn/proteinstructure/smac/run_314009415/configspace.pcs: -------------------------------------------------------------------------------- 1 | burn_in real [0.0, 0.8] [0.3] 2 | l_rate real [1e-06, 0.1] [0.01]log 3 | mdecay real [0.0, 1.0] [0.05] 4 | n_units_1 integer [16, 512] [64]log 5 | n_units_2 integer [16, 512] [64]log -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/bnn/proteinstructure/smac/run_314009415/scenario.txt: -------------------------------------------------------------------------------- 1 | execdir = . 2 | deterministic = True 3 | run_obj = quality 4 | overall_obj = par10 5 | par_factor = 10 6 | cost_for_crash = 2147483647.0 7 | algo_runs_timelimit = inf 8 | wallclock_limit = inf 9 | always_race_default = False 10 | ta_run_limit = 16.0 11 | initial_incumbent = RANDOM 12 | pcs_fn = opt_results/bnn/proteinstructure/smac/run_314009415/configspace.json 13 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/bnn/proteinstructure/smac/run_314009415/stats.json: -------------------------------------------------------------------------------- 1 | {"ta_runs": 16, "n_configs": 16, "wallclock_time_used": 1788.763863325119, "ta_time_used": 1766.1547029018402, "inc_changed": 2, "_n_configs_per_intensify": 14, "_n_calls_of_intensify": 7, "_ema_n_configs_per_intensifiy": 2.0, "_EMA_ALPHA": 0.2} -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/bnn/proteinstructure/smac/run_314009415/traj_aclib2.json: -------------------------------------------------------------------------------- 1 | {"cpu_time": 0, "total_cpu_time": null, "wallclock_time": 0.00035691261291503906, "evaluations": 0, "cost": 2147483648, "incumbent": ["burn_in='0.6366132108139522'", "l_rate='0.007812133521750205'", "mdecay='0.7822969392825124'", "n_units_1='72'", "n_units_2='59'"], "origin": "Random initial design."} 2 | {"cpu_time": 46.228333950042725, "total_cpu_time": null, "wallclock_time": 46.283263206481934, "evaluations": 1, "cost": 375.02425943744, "incumbent": ["burn_in='0.6366132108139522'", "l_rate='0.007812133521750205'", "mdecay='0.7822969392825124'", "n_units_1='72'", "n_units_2='59'"], "origin": "Random initial design."} 3 | {"cpu_time": 191.24676823616028, "total_cpu_time": null, "wallclock_time": 191.97472262382507, "evaluations": 2, "cost": 14.037101885341464, "incumbent": ["burn_in='0.45364269906708066'", "l_rate='0.07767477745522469'", "mdecay='0.9413248911823285'", "n_units_1='78'", "n_units_2='328'"], "origin": "Random Search (sorted)"} 4 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/bnn/proteinstructure/smac/run_314009415/traj_old.csv: -------------------------------------------------------------------------------- 1 | "CPU Time Used","Estimated Training Performance","Wallclock Time","Incumbent ID","Automatic Configurator (CPU) Time","Configuration..." 2 | 0.000000, 2147483648.000000, 0.000357, 1, 0.000357, burn_in='0.6366132108139522', l_rate='0.007812133521750205', mdecay='0.7822969392825124', n_units_1='72', n_units_2='59' 3 | 46.228334, 375.024259, 46.283263, 1, 0.054929, burn_in='0.6366132108139522', l_rate='0.007812133521750205', mdecay='0.7822969392825124', n_units_1='72', n_units_2='59' 4 | 191.246768, 14.037102, 191.974723, 2, 0.727954, burn_in='0.45364269906708066', l_rate='0.07767477745522469', mdecay='0.9413248911823285', n_units_1='78', n_units_2='328' 5 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/bnn/toyfunction/bohb/configspace.pcs: -------------------------------------------------------------------------------- 1 | burn_in real [0.0, 0.8] [0.3] 2 | l_rate real [1e-06, 0.1] [0.01]log 3 | mdecay real [0.0, 1.0] [0.05] 4 | n_units_1 integer [16, 512] [64]log 5 | n_units_2 integer [16, 512] [64]log -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/bnn/toyfunction/hyperband/configspace.pcs: -------------------------------------------------------------------------------- 1 | burn_in real [0.0, 0.8] [0.3] 2 | l_rate real [1e-06, 0.1] [0.01]log 3 | mdecay real [0.0, 1.0] [0.05] 4 | n_units_1 integer [16, 512] [64]log 5 | n_units_2 integer [16, 512] [64]log -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/bnn/toyfunction/randomsearch/configs.json: 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-------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/bnn/toyfunction/smac/run_1119649367/configspace.json: -------------------------------------------------------------------------------- 1 | { 2 | "hyperparameters": [ 3 | { 4 | "name": "burn_in", 5 | "type": "uniform_float", 6 | "log": false, 7 | "lower": 0.0, 8 | "upper": 0.8, 9 | "default": 0.3 10 | }, 11 | { 12 | "name": "l_rate", 13 | "type": "uniform_float", 14 | "log": true, 15 | "lower": 1e-06, 16 | "upper": 0.1, 17 | "default": 0.01 18 | }, 19 | { 20 | "name": "mdecay", 21 | "type": "uniform_float", 22 | "log": false, 23 | "lower": 0.0, 24 | "upper": 1.0, 25 | "default": 0.05 26 | }, 27 | { 28 | "name": "n_units_1", 29 | "type": "uniform_int", 30 | "log": true, 31 | "lower": 16, 32 | "upper": 512, 33 | "default": 64 34 | }, 35 | { 36 | "name": "n_units_2", 37 | "type": "uniform_int", 38 | "log": true, 39 | "lower": 16, 40 | "upper": 512, 41 | "default": 64 42 | } 43 | ], 44 | "conditions": [], 45 | "forbiddens": [], 46 | "python_module_version": "0.4.10", 47 | "json_format_version": 0.1 48 | } -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/bnn/toyfunction/smac/run_1119649367/configspace.pcs: -------------------------------------------------------------------------------- 1 | burn_in real [0.0, 0.8] [0.3] 2 | l_rate real [1e-06, 0.1] [0.01]log 3 | mdecay real [0.0, 1.0] [0.05] 4 | n_units_1 integer [16, 512] [64]log 5 | n_units_2 integer [16, 512] [64]log -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/bnn/toyfunction/smac/run_1119649367/scenario.txt: -------------------------------------------------------------------------------- 1 | execdir = . 2 | deterministic = True 3 | run_obj = quality 4 | overall_obj = par10 5 | par_factor = 10 6 | cost_for_crash = 2147483647.0 7 | algo_runs_timelimit = inf 8 | wallclock_limit = inf 9 | always_race_default = False 10 | ta_run_limit = 16.0 11 | initial_incumbent = RANDOM 12 | pcs_fn = opt_results/bnn/toyfunction/smac/run_1119649367/configspace.json 13 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/bnn/toyfunction/smac/run_1119649367/stats.json: -------------------------------------------------------------------------------- 1 | {"ta_runs": 16, "n_configs": 16, "wallclock_time_used": 1795.8314158916473, "ta_time_used": 1773.5128891468048, "inc_changed": 4, "_n_configs_per_intensify": 14, "_n_calls_of_intensify": 7, "_ema_n_configs_per_intensifiy": 2.0, "_EMA_ALPHA": 0.2} -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/bnn/toyfunction/smac/run_1119649367/traj_aclib2.json: -------------------------------------------------------------------------------- 1 | {"cpu_time": 0, "total_cpu_time": null, "wallclock_time": 0.0003876686096191406, "evaluations": 0, "cost": 2147483648, "incumbent": ["burn_in='0.3524645578711918'", "l_rate='0.003429552862346398'", "mdecay='0.13764096034997053'", "n_units_1='172'", "n_units_2='413'"], "origin": "Random initial design."} 2 | {"cpu_time": 223.37937831878662, "total_cpu_time": null, "wallclock_time": 223.43469548225403, "evaluations": 1, "cost": 4.987080365583064, "incumbent": ["burn_in='0.3524645578711918'", "l_rate='0.003429552862346398'", "mdecay='0.13764096034997053'", "n_units_1='172'", "n_units_2='413'"], "origin": "Random initial design."} 3 | {"cpu_time": 558.970231294632, "total_cpu_time": null, "wallclock_time": 560.8218863010406, "evaluations": 5, "cost": 1.756934165349096, "incumbent": ["burn_in='0.6394829809745686'", "l_rate='0.021555510547828824'", "mdecay='0.3906329904195024'", "n_units_1='279'", "n_units_2='76'"], "origin": "Random Search (sorted)"} 4 | {"cpu_time": 608.7749814987183, "total_cpu_time": null, "wallclock_time": 612.946967124939, "evaluations": 6, "cost": -0.03290410378263687, "incumbent": ["burn_in='0.12292719841052585'", "l_rate='0.007679056661525063'", "mdecay='0.34886332949974186'", "n_units_1='412'", "n_units_2='31'"], "origin": "Random Search"} 5 | {"cpu_time": 911.3870751857758, "total_cpu_time": null, "wallclock_time": 918.3930883407593, "evaluations": 9, "cost": -0.6580043649771659, "incumbent": ["burn_in='0.2523571093289596'", "l_rate='0.04458325253349339'", "mdecay='0.3407451637834581'", "n_units_1='273'", "n_units_2='184'"], "origin": "Random Search (sorted)"} 6 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/bnn/toyfunction/smac/run_1119649367/traj_old.csv: -------------------------------------------------------------------------------- 1 | "CPU Time Used","Estimated Training Performance","Wallclock Time","Incumbent ID","Automatic Configurator (CPU) Time","Configuration..." 2 | 0.000000, 2147483648.000000, 0.000388, 1, 0.000388, burn_in='0.3524645578711918', l_rate='0.003429552862346398', mdecay='0.13764096034997053', n_units_1='172', n_units_2='413' 3 | 223.379378, 4.987080, 223.434695, 1, 0.055317, burn_in='0.3524645578711918', l_rate='0.003429552862346398', mdecay='0.13764096034997053', n_units_1='172', n_units_2='413' 4 | 558.970231, 1.756934, 560.821886, 2, 1.851655, burn_in='0.6394829809745686', l_rate='0.021555510547828824', mdecay='0.3906329904195024', n_units_1='279', n_units_2='76' 5 | 608.774981, -0.032904, 612.946967, 3, 4.171986, burn_in='0.12292719841052585', l_rate='0.007679056661525063', mdecay='0.34886332949974186', n_units_1='412', n_units_2='31' 6 | 911.387075, -0.658004, 918.393088, 4, 7.006013, burn_in='0.2523571093289596', l_rate='0.04458325253349339', mdecay='0.3407451637834581', n_units_1='273', n_units_2='184' 7 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/cartpole/bohb/configspace.pcs: -------------------------------------------------------------------------------- 1 | batch_size integer [8, 256] [64]log 2 | discount real [0.0, 1.0] [0.99] 3 | entropy_regularization real [0.0, 1.0] [0.01] 4 | learning_rate real [1e-07, 0.1] [0.001]log 5 | likelihood_ratio_clipping real [0.0, 1.0] [0.2] 6 | n_units_1 integer [8, 128] [64]log 7 | n_units_2 integer [8, 128] [64]log -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/adult/bohb/configspace.pcs: -------------------------------------------------------------------------------- 1 | x0 real [-6.0, -2.0] [-4.0] 2 | x1 real [3.0, 8.0] [5.5] 3 | x2 real [4.0, 8.0] [6.0] 4 | x3 real [-4.0, 0.0] [-2.0] 5 | x4 real [1.0, 5.0] [3.0] 6 | x5 real [0.0, 0.5] [0.25] -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/adult/hyperband/configspace.pcs: -------------------------------------------------------------------------------- 1 | x0 real [-6.0, -2.0] [-4.0] 2 | x1 real [3.0, 8.0] [5.5] 3 | x2 real [4.0, 8.0] [6.0] 4 | x3 real [-4.0, 0.0] [-2.0] 5 | x4 real [1.0, 5.0] [3.0] 6 | x5 real [0.0, 0.5] [0.25] -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/adult/randomsearch/configspace.pcs: -------------------------------------------------------------------------------- 1 | x0 real [-6.0, -2.0] [-4.0] 2 | x1 real [3.0, 8.0] [5.5] 3 | x2 real [4.0, 8.0] [6.0] 4 | x3 real [-4.0, 0.0] [-2.0] 5 | x4 real [1.0, 5.0] [3.0] 6 | x5 real [0.0, 0.5] [0.25] -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/adult/smac/run_1569982670/configspace.json: -------------------------------------------------------------------------------- 1 | { 2 | "hyperparameters": [ 3 | { 4 | "name": "x0", 5 | "type": "uniform_float", 6 | "log": false, 7 | "lower": -6.0, 8 | "upper": -2.0, 9 | "default": -4.0 10 | }, 11 | { 12 | "name": "x1", 13 | "type": "uniform_float", 14 | "log": false, 15 | "lower": 3.0, 16 | "upper": 8.0, 17 | "default": 5.5 18 | }, 19 | { 20 | "name": "x2", 21 | "type": "uniform_float", 22 | "log": false, 23 | "lower": 4.0, 24 | "upper": 8.0, 25 | "default": 6.0 26 | }, 27 | { 28 | "name": "x3", 29 | "type": "uniform_float", 30 | "log": false, 31 | "lower": -4.0, 32 | "upper": 0.0, 33 | "default": -2.0 34 | }, 35 | { 36 | "name": "x4", 37 | "type": "uniform_float", 38 | "log": false, 39 | "lower": 1.0, 40 | "upper": 5.0, 41 | "default": 3.0 42 | }, 43 | { 44 | "name": "x5", 45 | "type": "uniform_float", 46 | "log": false, 47 | "lower": 0.0, 48 | "upper": 0.5, 49 | "default": 0.25 50 | } 51 | ], 52 | "conditions": [], 53 | "forbiddens": [], 54 | "python_module_version": "0.4.10", 55 | "json_format_version": 0.1 56 | } -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/adult/smac/run_1569982670/configspace.pcs: -------------------------------------------------------------------------------- 1 | x0 real [-6.0, -2.0] [-4.0] 2 | x1 real [3.0, 8.0] [5.5] 3 | x2 real [4.0, 8.0] [6.0] 4 | x3 real [-4.0, 0.0] [-2.0] 5 | x4 real [1.0, 5.0] [3.0] 6 | x5 real [0.0, 0.5] [0.25] -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/adult/smac/run_1569982670/scenario.txt: -------------------------------------------------------------------------------- 1 | execdir = . 2 | deterministic = True 3 | run_obj = quality 4 | overall_obj = par10 5 | par_factor = 10 6 | cost_for_crash = 2147483647.0 7 | algo_runs_timelimit = inf 8 | wallclock_limit = inf 9 | always_race_default = False 10 | ta_run_limit = 39.0 11 | initial_incumbent = RANDOM 12 | pcs_fn = ../opt_results/paramnet_surrogates/adult/smac/run_1569982670/configspace.json 13 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/adult/smac/run_1569982670/stats.json: -------------------------------------------------------------------------------- 1 | {"ta_runs": 39, "n_configs": 39, "wallclock_time_used": 38.68742895126343, "ta_time_used": 0.9097795486450195, "inc_changed": 2, "_n_configs_per_intensify": 38, "_n_calls_of_intensify": 19, "_ema_n_configs_per_intensifiy": 2.0, "_EMA_ALPHA": 0.2} -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/adult/smac/run_1569982670/traj_aclib2.json: -------------------------------------------------------------------------------- 1 | {"cpu_time": 0, "total_cpu_time": null, "wallclock_time": 8.988380432128906e-05, "evaluations": 0, "cost": 2147483648, "incumbent": ["x0='-4.427184146847615'", "x1='5.468409116159567'", "x2='5.166697446737537'", "x3='-2.4737392169558943'", "x4='4.557793026011394'", "x5='0.26048328742862104'"], "origin": "Random initial design."} 2 | {"cpu_time": 0.014215469360351562, "total_cpu_time": null, "wallclock_time": 0.03326892852783203, "evaluations": 1, "cost": 0.16898147900181787, "incumbent": ["x0='-4.427184146847615'", "x1='5.468409116159567'", "x2='5.166697446737537'", "x3='-2.4737392169558943'", "x4='4.557793026011394'", "x5='0.26048328742862104'"], "origin": "Random initial design."} 3 | {"cpu_time": 0.02863907814025879, "total_cpu_time": null, "wallclock_time": 0.3213036060333252, "evaluations": 2, "cost": 0.14852777666984882, "incumbent": ["x0='-3.0208079181949494'", "x1='4.302339512022793'", "x2='6.682814513749159'", "x3='-1.5860107594761308'", "x4='1.7579816943137954'", "x5='0.29784322077691755'"], "origin": "Random Search"} 4 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/adult/smac/run_1569982670/traj_old.csv: -------------------------------------------------------------------------------- 1 | "CPU Time Used","Estimated Training Performance","Wallclock Time","Incumbent ID","Automatic Configurator (CPU) Time","Configuration..." 2 | 0.000000, 2147483648.000000, 0.000090, 1, 0.000090, x0='-4.427184146847615', x1='5.468409116159567', x2='5.166697446737537', x3='-2.4737392169558943', x4='4.557793026011394', x5='0.26048328742862104' 3 | 0.014215, 0.168981, 0.033269, 1, 0.019053, x0='-4.427184146847615', x1='5.468409116159567', x2='5.166697446737537', x3='-2.4737392169558943', x4='4.557793026011394', x5='0.26048328742862104' 4 | 0.028639, 0.148528, 0.321304, 2, 0.292665, x0='-3.0208079181949494', x1='4.302339512022793', x2='6.682814513749159', x3='-1.5860107594761308', x4='1.7579816943137954', x5='0.29784322077691755' 5 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/higgs/bohb/configspace.pcs: -------------------------------------------------------------------------------- 1 | x0 real [-6.0, -2.0] [-4.0] 2 | x1 real [3.0, 8.0] [5.5] 3 | x2 real [4.0, 8.0] [6.0] 4 | x3 real [-4.0, 0.0] [-2.0] 5 | x4 real [1.0, 5.0] [3.0] 6 | x5 real [0.0, 0.5] [0.25] -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/higgs/hyperband/configspace.pcs: -------------------------------------------------------------------------------- 1 | x0 real [-6.0, -2.0] [-4.0] 2 | x1 real [3.0, 8.0] [5.5] 3 | x2 real [4.0, 8.0] [6.0] 4 | x3 real [-4.0, 0.0] [-2.0] 5 | x4 real [1.0, 5.0] [3.0] 6 | x5 real [0.0, 0.5] [0.25] -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/higgs/randomsearch/configspace.pcs: -------------------------------------------------------------------------------- 1 | x0 real [-6.0, -2.0] [-4.0] 2 | x1 real [3.0, 8.0] [5.5] 3 | x2 real [4.0, 8.0] [6.0] 4 | x3 real [-4.0, 0.0] [-2.0] 5 | x4 real [1.0, 5.0] [3.0] 6 | x5 real [0.0, 0.5] [0.25] -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/higgs/smac/run_2040386885/configspace.json: -------------------------------------------------------------------------------- 1 | { 2 | "hyperparameters": [ 3 | { 4 | "name": "x0", 5 | "type": "uniform_float", 6 | "log": false, 7 | "lower": -6.0, 8 | "upper": -2.0, 9 | "default": -4.0 10 | }, 11 | { 12 | "name": "x1", 13 | "type": "uniform_float", 14 | "log": false, 15 | "lower": 3.0, 16 | "upper": 8.0, 17 | "default": 5.5 18 | }, 19 | { 20 | "name": "x2", 21 | "type": "uniform_float", 22 | "log": false, 23 | "lower": 4.0, 24 | "upper": 8.0, 25 | "default": 6.0 26 | }, 27 | { 28 | "name": "x3", 29 | "type": "uniform_float", 30 | "log": false, 31 | "lower": -4.0, 32 | "upper": 0.0, 33 | "default": -2.0 34 | }, 35 | { 36 | "name": "x4", 37 | "type": "uniform_float", 38 | "log": false, 39 | "lower": 1.0, 40 | "upper": 5.0, 41 | "default": 3.0 42 | }, 43 | { 44 | "name": "x5", 45 | "type": "uniform_float", 46 | "log": false, 47 | "lower": 0.0, 48 | "upper": 0.5, 49 | "default": 0.25 50 | } 51 | ], 52 | "conditions": [], 53 | "forbiddens": [], 54 | "python_module_version": "0.4.10", 55 | "json_format_version": 0.1 56 | } -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/higgs/smac/run_2040386885/configspace.pcs: -------------------------------------------------------------------------------- 1 | x0 real [-6.0, -2.0] [-4.0] 2 | x1 real [3.0, 8.0] [5.5] 3 | x2 real [4.0, 8.0] [6.0] 4 | x3 real [-4.0, 0.0] [-2.0] 5 | x4 real [1.0, 5.0] [3.0] 6 | x5 real [0.0, 0.5] [0.25] -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/higgs/smac/run_2040386885/scenario.txt: -------------------------------------------------------------------------------- 1 | execdir = . 2 | deterministic = True 3 | run_obj = quality 4 | overall_obj = par10 5 | par_factor = 10 6 | cost_for_crash = 2147483647.0 7 | algo_runs_timelimit = inf 8 | wallclock_limit = inf 9 | always_race_default = False 10 | ta_run_limit = 39.0 11 | initial_incumbent = RANDOM 12 | pcs_fn = ../opt_results/paramnet_surrogates/higgs/smac/run_2040386885/configspace.json 13 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/higgs/smac/run_2040386885/stats.json: -------------------------------------------------------------------------------- 1 | {"ta_runs": 39, "n_configs": 39, "wallclock_time_used": 39.5362651348114, "ta_time_used": 0.8841092586517334, "inc_changed": 3, "_n_configs_per_intensify": 38, "_n_calls_of_intensify": 19, "_ema_n_configs_per_intensifiy": 2.0, "_EMA_ALPHA": 0.2} -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/higgs/smac/run_2040386885/traj_aclib2.json: -------------------------------------------------------------------------------- 1 | {"cpu_time": 0, "total_cpu_time": null, "wallclock_time": 9.298324584960938e-05, "evaluations": 0, "cost": 2147483648, "incumbent": ["x0='-2.0657575240907544'", "x1='4.407157054680956'", "x2='4.151022090088189'", "x3='-2.5879077570296203'", "x4='4.435772852524021'", "x5='0.14278005896896523'"], "origin": "Random initial design."} 2 | {"cpu_time": 0.014195919036865234, "total_cpu_time": null, "wallclock_time": 0.033194541931152344, "evaluations": 1, "cost": 0.31500461093510923, "incumbent": ["x0='-2.0657575240907544'", "x1='4.407157054680956'", "x2='4.151022090088189'", "x3='-2.5879077570296203'", "x4='4.435772852524021'", "x5='0.14278005896896523'"], "origin": "Random initial design."} 3 | {"cpu_time": 0.02872180938720703, "total_cpu_time": null, "wallclock_time": 0.31720399856567383, "evaluations": 2, "cost": 0.29713560265822275, "incumbent": ["x0='-2.5823484951818534'", "x1='5.983734051213035'", "x2='5.470197296257254'", "x3='-1.6326409112077305'", "x4='3.4835446228531746'", "x5='0.4066325828279558'"], "origin": "Random Search (sorted)"} 4 | {"cpu_time": 0.08895373344421387, "total_cpu_time": null, "wallclock_time": 2.2272708415985107, "evaluations": 6, "cost": 0.28339482690108, "incumbent": ["x0='-2.6499931824483633'", "x1='5.576224879379426'", "x2='7.0041297512080956'", "x3='-0.22078033585292012'", "x4='3.507694880874969'", "x5='0.2633239134302519'"], "origin": "Random Search"} 5 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/higgs/smac/run_2040386885/traj_old.csv: -------------------------------------------------------------------------------- 1 | "CPU Time Used","Estimated Training Performance","Wallclock Time","Incumbent ID","Automatic Configurator (CPU) Time","Configuration..." 2 | 0.000000, 2147483648.000000, 0.000093, 1, 0.000093, x0='-2.0657575240907544', x1='4.407157054680956', x2='4.151022090088189', x3='-2.5879077570296203', x4='4.435772852524021', x5='0.14278005896896523' 3 | 0.014196, 0.315005, 0.033195, 1, 0.018999, x0='-2.0657575240907544', x1='4.407157054680956', x2='4.151022090088189', x3='-2.5879077570296203', x4='4.435772852524021', x5='0.14278005896896523' 4 | 0.028722, 0.297136, 0.317204, 2, 0.288482, x0='-2.5823484951818534', x1='5.983734051213035', x2='5.470197296257254', x3='-1.6326409112077305', x4='3.4835446228531746', x5='0.4066325828279558' 5 | 0.088954, 0.283395, 2.227271, 3, 2.138317, x0='-2.6499931824483633', x1='5.576224879379426', x2='7.0041297512080956', x3='-0.22078033585292012', x4='3.507694880874969', x5='0.2633239134302519' 6 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/letter/bohb/configspace.pcs: -------------------------------------------------------------------------------- 1 | x0 real [-6.0, -2.0] [-4.0] 2 | x1 real [3.0, 8.0] [5.5] 3 | x2 real [4.0, 8.0] [6.0] 4 | x3 real [-4.0, 0.0] [-2.0] 5 | x4 real [1.0, 5.0] [3.0] 6 | x5 real [0.0, 0.5] [0.25] -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/letter/hyperband/configspace.pcs: -------------------------------------------------------------------------------- 1 | x0 real [-6.0, -2.0] [-4.0] 2 | x1 real [3.0, 8.0] [5.5] 3 | x2 real [4.0, 8.0] [6.0] 4 | x3 real [-4.0, 0.0] [-2.0] 5 | x4 real [1.0, 5.0] [3.0] 6 | x5 real [0.0, 0.5] [0.25] -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/letter/randomsearch/configspace.pcs: -------------------------------------------------------------------------------- 1 | x0 real [-6.0, -2.0] [-4.0] 2 | x1 real [3.0, 8.0] [5.5] 3 | x2 real [4.0, 8.0] [6.0] 4 | x3 real [-4.0, 0.0] [-2.0] 5 | x4 real [1.0, 5.0] [3.0] 6 | x5 real [0.0, 0.5] [0.25] -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/letter/smac/run_727669348/configspace.json: -------------------------------------------------------------------------------- 1 | { 2 | "hyperparameters": [ 3 | { 4 | "name": "x0", 5 | "type": "uniform_float", 6 | "log": false, 7 | "lower": -6.0, 8 | "upper": -2.0, 9 | "default": -4.0 10 | }, 11 | { 12 | "name": "x1", 13 | "type": "uniform_float", 14 | "log": false, 15 | "lower": 3.0, 16 | "upper": 8.0, 17 | "default": 5.5 18 | }, 19 | { 20 | "name": "x2", 21 | "type": "uniform_float", 22 | "log": false, 23 | "lower": 4.0, 24 | "upper": 8.0, 25 | "default": 6.0 26 | }, 27 | { 28 | "name": "x3", 29 | "type": "uniform_float", 30 | "log": false, 31 | "lower": -4.0, 32 | "upper": 0.0, 33 | "default": -2.0 34 | }, 35 | { 36 | "name": "x4", 37 | "type": "uniform_float", 38 | "log": false, 39 | "lower": 1.0, 40 | "upper": 5.0, 41 | "default": 3.0 42 | }, 43 | { 44 | "name": "x5", 45 | "type": "uniform_float", 46 | "log": false, 47 | "lower": 0.0, 48 | "upper": 0.5, 49 | "default": 0.25 50 | } 51 | ], 52 | "conditions": [], 53 | "forbiddens": [], 54 | "python_module_version": "0.4.10", 55 | "json_format_version": 0.1 56 | } -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/letter/smac/run_727669348/configspace.pcs: -------------------------------------------------------------------------------- 1 | x0 real [-6.0, -2.0] [-4.0] 2 | x1 real [3.0, 8.0] [5.5] 3 | x2 real [4.0, 8.0] [6.0] 4 | x3 real [-4.0, 0.0] [-2.0] 5 | x4 real [1.0, 5.0] [3.0] 6 | x5 real [0.0, 0.5] [0.25] -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/letter/smac/run_727669348/scenario.txt: -------------------------------------------------------------------------------- 1 | execdir = . 2 | deterministic = True 3 | run_obj = quality 4 | overall_obj = par10 5 | par_factor = 10 6 | cost_for_crash = 2147483647.0 7 | algo_runs_timelimit = inf 8 | wallclock_limit = inf 9 | always_race_default = False 10 | ta_run_limit = 40.0 11 | initial_incumbent = RANDOM 12 | pcs_fn = ../opt_results/paramnet_surrogates/letter/smac/run_727669348/configspace.json 13 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/letter/smac/run_727669348/stats.json: -------------------------------------------------------------------------------- 1 | {"ta_runs": 40, "n_configs": 40, "wallclock_time_used": 47.32938528060913, "ta_time_used": 1.0863277912139893, "inc_changed": 6, "_n_configs_per_intensify": 38, "_n_calls_of_intensify": 19, "_ema_n_configs_per_intensifiy": 2.0, "_EMA_ALPHA": 0.2} -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/letter/smac/run_727669348/traj_aclib2.json: -------------------------------------------------------------------------------- 1 | {"cpu_time": 0, "total_cpu_time": null, "wallclock_time": 9.703636169433594e-05, "evaluations": 0, "cost": 2147483648, "incumbent": ["x0='-2.6825397313802792'", "x1='7.619548198595208'", "x2='4.145019634442923'", "x3='-1.1709274274827868'", "x4='3.083628549201582'", "x5='0.4016129149717395'"], "origin": "Random initial design."} 2 | {"cpu_time": 0.014354705810546875, "total_cpu_time": null, "wallclock_time": 0.03343462944030762, "evaluations": 1, "cost": 0.4528719992715948, "incumbent": ["x0='-2.6825397313802792'", "x1='7.619548198595208'", "x2='4.145019634442923'", "x3='-1.1709274274827868'", "x4='3.083628549201582'", "x5='0.4016129149717395'"], "origin": "Random initial design."} 3 | {"cpu_time": 0.029262065887451172, "total_cpu_time": null, "wallclock_time": 0.3221702575683594, "evaluations": 2, "cost": 0.07017186877415874, "incumbent": ["x0='-3.0497673710891613'", "x1='5.330919757007382'", "x2='6.940968125883387'", "x3='-1.539624143253262'", "x4='3.0835006236294973'", "x5='0.13989358695433468'"], "origin": "Random Search"} 4 | {"cpu_time": 0.35594820976257324, "total_cpu_time": null, "wallclock_time": 7.989388465881348, "evaluations": 13, "cost": 0.06978742599298596, "incumbent": ["x0='-2.080773012338321'", "x1='7.506384712120714'", "x2='6.896214129221207'", "x3='-2.72928328234397'", "x4='2.272471024389858'", "x5='0.2980244053518462'"], "origin": "Random Search (sorted)"} 5 | {"cpu_time": 0.5214650630950928, "total_cpu_time": null, "wallclock_time": 16.556226015090942, "evaluations": 19, "cost": 0.06571687099379363, "incumbent": ["x0='-2.3405863434213656'", "x1='5.792361305300507'", "x2='7.327439884780533'", "x3='-2.3234915721205947'", "x4='1.4778937397419685'", "x5='0.028695689863961982'"], "origin": "Random Search (sorted)"} 6 | {"cpu_time": 0.5641236305236816, "total_cpu_time": null, "wallclock_time": 19.506958723068237, "evaluations": 21, "cost": 0.057892353191789814, "incumbent": ["x0='-2.5491670410058593'", "x1='6.425536998040009'", "x2='6.936642202921141'", "x3='-1.3976295959426155'", "x4='4.26709788987649'", "x5='0.10374118577443192'"], "origin": "Random Search (sorted)"} 7 | {"cpu_time": 0.9305191040039062, "total_cpu_time": null, "wallclock_time": 39.099194049835205, "evaluations": 34, "cost": 0.04242423898302448, "incumbent": ["x0='-2.459187504000582'", "x1='5.380176653573916'", "x2='7.223467832882394'", "x3='-2.232403616774815'", "x4='2.916420099006719'", "x5='0.07248265530684728'"], "origin": "Random Search (sorted)"} 8 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/letter/smac/run_727669348/traj_old.csv: -------------------------------------------------------------------------------- 1 | "CPU Time Used","Estimated Training Performance","Wallclock Time","Incumbent ID","Automatic Configurator (CPU) Time","Configuration..." 2 | 0.000000, 2147483648.000000, 0.000097, 1, 0.000097, x0='-2.6825397313802792', x1='7.619548198595208', x2='4.145019634442923', x3='-1.1709274274827868', x4='3.083628549201582', x5='0.4016129149717395' 3 | 0.014355, 0.452872, 0.033435, 1, 0.019080, x0='-2.6825397313802792', x1='7.619548198595208', x2='4.145019634442923', x3='-1.1709274274827868', x4='3.083628549201582', x5='0.4016129149717395' 4 | 0.029262, 0.070172, 0.322170, 2, 0.292908, x0='-3.0497673710891613', x1='5.330919757007382', x2='6.940968125883387', x3='-1.539624143253262', x4='3.0835006236294973', x5='0.13989358695433468' 5 | 0.355948, 0.069787, 7.989388, 3, 7.633440, x0='-2.080773012338321', x1='7.506384712120714', x2='6.896214129221207', x3='-2.72928328234397', x4='2.272471024389858', x5='0.2980244053518462' 6 | 0.521465, 0.065717, 16.556226, 4, 16.034761, x0='-2.3405863434213656', x1='5.792361305300507', x2='7.327439884780533', x3='-2.3234915721205947', x4='1.4778937397419685', x5='0.028695689863961982' 7 | 0.564124, 0.057892, 19.506959, 5, 18.942835, x0='-2.5491670410058593', x1='6.425536998040009', x2='6.936642202921141', x3='-1.3976295959426155', x4='4.26709788987649', x5='0.10374118577443192' 8 | 0.930519, 0.042424, 39.099194, 6, 38.168675, x0='-2.459187504000582', x1='5.380176653573916', x2='7.223467832882394', x3='-2.232403616774815', x4='2.916420099006719', x5='0.07248265530684728' 9 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/mnist/bohb/configspace.pcs: -------------------------------------------------------------------------------- 1 | x0 real [-6.0, -2.0] [-4.0] 2 | x1 real [3.0, 8.0] [5.5] 3 | x2 real [4.0, 8.0] [6.0] 4 | x3 real [-4.0, 0.0] [-2.0] 5 | x4 real [1.0, 5.0] [3.0] 6 | x5 real [0.0, 0.5] [0.25] -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/mnist/hyperband/configspace.pcs: -------------------------------------------------------------------------------- 1 | x0 real [-6.0, -2.0] [-4.0] 2 | x1 real [3.0, 8.0] [5.5] 3 | x2 real [4.0, 8.0] [6.0] 4 | x3 real [-4.0, 0.0] [-2.0] 5 | x4 real [1.0, 5.0] [3.0] 6 | x5 real [0.0, 0.5] [0.25] -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/mnist/randomsearch/configspace.pcs: -------------------------------------------------------------------------------- 1 | x0 real [-6.0, -2.0] [-4.0] 2 | x1 real [3.0, 8.0] [5.5] 3 | x2 real [4.0, 8.0] [6.0] 4 | x3 real [-4.0, 0.0] [-2.0] 5 | x4 real [1.0, 5.0] [3.0] 6 | x5 real [0.0, 0.5] [0.25] -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/mnist/smac/run_1765023969/configspace.json: -------------------------------------------------------------------------------- 1 | { 2 | "hyperparameters": [ 3 | { 4 | "name": "x0", 5 | "type": "uniform_float", 6 | "log": false, 7 | "lower": -6.0, 8 | "upper": -2.0, 9 | "default": -4.0 10 | }, 11 | { 12 | "name": "x1", 13 | "type": "uniform_float", 14 | "log": false, 15 | "lower": 3.0, 16 | "upper": 8.0, 17 | "default": 5.5 18 | }, 19 | { 20 | "name": "x2", 21 | "type": "uniform_float", 22 | "log": false, 23 | "lower": 4.0, 24 | "upper": 8.0, 25 | "default": 6.0 26 | }, 27 | { 28 | "name": "x3", 29 | "type": "uniform_float", 30 | "log": false, 31 | "lower": -4.0, 32 | "upper": 0.0, 33 | "default": -2.0 34 | }, 35 | { 36 | "name": "x4", 37 | "type": "uniform_float", 38 | "log": false, 39 | "lower": 1.0, 40 | "upper": 5.0, 41 | "default": 3.0 42 | }, 43 | { 44 | "name": "x5", 45 | "type": "uniform_float", 46 | "log": false, 47 | "lower": 0.0, 48 | "upper": 0.5, 49 | "default": 0.25 50 | } 51 | ], 52 | "conditions": [], 53 | "forbiddens": [], 54 | "python_module_version": "0.4.10", 55 | "json_format_version": 0.1 56 | } -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/mnist/smac/run_1765023969/configspace.pcs: -------------------------------------------------------------------------------- 1 | x0 real [-6.0, -2.0] [-4.0] 2 | x1 real [3.0, 8.0] [5.5] 3 | x2 real [4.0, 8.0] [6.0] 4 | x3 real [-4.0, 0.0] [-2.0] 5 | x4 real [1.0, 5.0] [3.0] 6 | x5 real [0.0, 0.5] [0.25] -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/mnist/smac/run_1765023969/scenario.txt: -------------------------------------------------------------------------------- 1 | execdir = . 2 | deterministic = True 3 | run_obj = quality 4 | overall_obj = par10 5 | par_factor = 10 6 | cost_for_crash = 2147483647.0 7 | algo_runs_timelimit = inf 8 | wallclock_limit = inf 9 | always_race_default = False 10 | ta_run_limit = 39.0 11 | initial_incumbent = RANDOM 12 | pcs_fn = ../opt_results/paramnet_surrogates/mnist/smac/run_1765023969/configspace.json 13 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/mnist/smac/run_1765023969/stats.json: -------------------------------------------------------------------------------- 1 | {"ta_runs": 39, "n_configs": 39, "wallclock_time_used": 43.50497221946716, "ta_time_used": 0.9439225196838379, "inc_changed": 5, "_n_configs_per_intensify": 38, "_n_calls_of_intensify": 19, "_ema_n_configs_per_intensifiy": 2.0, "_EMA_ALPHA": 0.2} -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/mnist/smac/run_1765023969/traj_aclib2.json: -------------------------------------------------------------------------------- 1 | {"cpu_time": 0, "total_cpu_time": null, "wallclock_time": 0.00010132789611816406, "evaluations": 0, "cost": 2147483648, "incumbent": ["x0='-2.680037398569014'", "x1='7.104944615374214'", "x2='5.291855763284372'", "x3='-3.6164697336704057'", "x4='3.9699774206883713'", "x5='0.15765586728812586'"], "origin": "Random initial design."} 2 | {"cpu_time": 0.015165567398071289, "total_cpu_time": null, "wallclock_time": 0.03575706481933594, "evaluations": 1, "cost": 0.03080000223398207, "incumbent": ["x0='-2.680037398569014'", "x1='7.104944615374214'", "x2='5.291855763284372'", "x3='-3.6164697336704057'", "x4='3.9699774206883713'", "x5='0.15765586728812586'"], "origin": "Random initial design."} 3 | {"cpu_time": 0.03326272964477539, "total_cpu_time": null, "wallclock_time": 0.3760969638824463, "evaluations": 2, "cost": 0.02095000512361528, "incumbent": ["x0='-3.350619453760151'", "x1='6.28234639957985'", "x2='7.523416363908132'", "x3='-1.2234671481602377'", "x4='1.2427417727578125'", "x5='0.35054808115153135'"], "origin": "Random Search (sorted)"} 4 | {"cpu_time": 0.5583105087280273, "total_cpu_time": null, "wallclock_time": 22.344090461730957, "evaluations": 22, "cost": 0.019880000931024544, "incumbent": ["x0='-3.363406167420284'", "x1='3.1847719969803885'", "x2='7.1538943396554515'", "x3='-3.822179828964913'", "x4='1.0900530657752872'", "x5='0.12801727321259682'"], "origin": "Random Search (sorted)"} 5 | {"cpu_time": 0.5791840553283691, "total_cpu_time": null, "wallclock_time": 22.385263681411743, "evaluations": 23, "cost": 0.019679999596476573, "incumbent": ["x0='-3.0625193163807376'", "x1='4.188859373392755'", "x2='6.651683755882928'", "x3='-3.2232680901657504'", "x4='2.9504999828406016'", "x5='0.1408310033391113'"], "origin": "Random Search (sorted)"} 6 | {"cpu_time": 0.7371954917907715, "total_cpu_time": null, "wallclock_time": 33.71429228782654, "evaluations": 30, "cost": 0.019659999843835808, "incumbent": ["x0='-3.164055905466697'", "x1='7.096104975348439'", "x2='7.775828954617282'", "x3='-3.9285833348833252'", "x4='1.3143931240853832'", "x5='0.17958073153625176'"], "origin": "Random Search"} 7 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/mnist/smac/run_1765023969/traj_old.csv: -------------------------------------------------------------------------------- 1 | "CPU Time Used","Estimated Training Performance","Wallclock Time","Incumbent ID","Automatic Configurator (CPU) Time","Configuration..." 2 | 0.000000, 2147483648.000000, 0.000101, 1, 0.000101, x0='-2.680037398569014', x1='7.104944615374214', x2='5.291855763284372', x3='-3.6164697336704057', x4='3.9699774206883713', x5='0.15765586728812586' 3 | 0.015166, 0.030800, 0.035757, 1, 0.020591, x0='-2.680037398569014', x1='7.104944615374214', x2='5.291855763284372', x3='-3.6164697336704057', x4='3.9699774206883713', x5='0.15765586728812586' 4 | 0.033263, 0.020950, 0.376097, 2, 0.342834, x0='-3.350619453760151', x1='6.28234639957985', x2='7.523416363908132', x3='-1.2234671481602377', x4='1.2427417727578125', x5='0.35054808115153135' 5 | 0.558311, 0.019880, 22.344090, 3, 21.785780, x0='-3.363406167420284', x1='3.1847719969803885', x2='7.1538943396554515', x3='-3.822179828964913', x4='1.0900530657752872', x5='0.12801727321259682' 6 | 0.579184, 0.019680, 22.385264, 4, 21.806080, x0='-3.0625193163807376', x1='4.188859373392755', x2='6.651683755882928', x3='-3.2232680901657504', x4='2.9504999828406016', x5='0.1408310033391113' 7 | 0.737195, 0.019660, 33.714292, 5, 32.977097, x0='-3.164055905466697', x1='7.096104975348439', x2='7.775828954617282', x3='-3.9285833348833252', x4='1.3143931240853832', x5='0.17958073153625176' 8 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/optdigits/bohb/configspace.pcs: -------------------------------------------------------------------------------- 1 | x0 real [-6.0, -2.0] [-4.0] 2 | x1 real [3.0, 8.0] [5.5] 3 | x2 real [4.0, 8.0] [6.0] 4 | x3 real [-4.0, 0.0] [-2.0] 5 | x4 real [1.0, 5.0] [3.0] 6 | x5 real [0.0, 0.5] [0.25] -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/optdigits/hyperband/configspace.pcs: -------------------------------------------------------------------------------- 1 | x0 real [-6.0, -2.0] [-4.0] 2 | x1 real [3.0, 8.0] [5.5] 3 | x2 real [4.0, 8.0] [6.0] 4 | x3 real [-4.0, 0.0] [-2.0] 5 | x4 real [1.0, 5.0] [3.0] 6 | x5 real [0.0, 0.5] [0.25] -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/optdigits/randomsearch/configspace.pcs: -------------------------------------------------------------------------------- 1 | x0 real [-6.0, -2.0] [-4.0] 2 | x1 real [3.0, 8.0] [5.5] 3 | x2 real [4.0, 8.0] [6.0] 4 | x3 real [-4.0, 0.0] [-2.0] 5 | x4 real [1.0, 5.0] [3.0] 6 | x5 real [0.0, 0.5] [0.25] -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/optdigits/smac/run_1254519304/configspace.json: -------------------------------------------------------------------------------- 1 | { 2 | "hyperparameters": [ 3 | { 4 | "name": "x0", 5 | "type": "uniform_float", 6 | "log": false, 7 | "lower": -6.0, 8 | "upper": -2.0, 9 | "default": -4.0 10 | }, 11 | { 12 | "name": "x1", 13 | "type": "uniform_float", 14 | "log": false, 15 | "lower": 3.0, 16 | "upper": 8.0, 17 | "default": 5.5 18 | }, 19 | { 20 | "name": "x2", 21 | "type": "uniform_float", 22 | "log": false, 23 | "lower": 4.0, 24 | "upper": 8.0, 25 | "default": 6.0 26 | }, 27 | { 28 | "name": "x3", 29 | "type": "uniform_float", 30 | "log": false, 31 | "lower": -4.0, 32 | "upper": 0.0, 33 | "default": -2.0 34 | }, 35 | { 36 | "name": "x4", 37 | "type": "uniform_float", 38 | "log": false, 39 | "lower": 1.0, 40 | "upper": 5.0, 41 | "default": 3.0 42 | }, 43 | { 44 | "name": "x5", 45 | "type": "uniform_float", 46 | "log": false, 47 | "lower": 0.0, 48 | "upper": 0.5, 49 | "default": 0.25 50 | } 51 | ], 52 | "conditions": [], 53 | "forbiddens": [], 54 | "python_module_version": "0.4.10", 55 | "json_format_version": 0.1 56 | } -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/optdigits/smac/run_1254519304/configspace.pcs: -------------------------------------------------------------------------------- 1 | x0 real [-6.0, -2.0] [-4.0] 2 | x1 real [3.0, 8.0] [5.5] 3 | x2 real [4.0, 8.0] [6.0] 4 | x3 real [-4.0, 0.0] [-2.0] 5 | x4 real [1.0, 5.0] [3.0] 6 | x5 real [0.0, 0.5] [0.25] -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/optdigits/smac/run_1254519304/scenario.txt: -------------------------------------------------------------------------------- 1 | execdir = . 2 | deterministic = True 3 | run_obj = quality 4 | overall_obj = par10 5 | par_factor = 10 6 | cost_for_crash = 2147483647.0 7 | algo_runs_timelimit = inf 8 | wallclock_limit = inf 9 | always_race_default = False 10 | ta_run_limit = 40.0 11 | initial_incumbent = RANDOM 12 | pcs_fn = ../opt_results/paramnet_surrogates/optdigits/smac/run_1254519304/configspace.json 13 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/optdigits/smac/run_1254519304/stats.json: -------------------------------------------------------------------------------- 1 | {"ta_runs": 40, "n_configs": 40, "wallclock_time_used": 48.67980408668518, "ta_time_used": 1.134052038192749, "inc_changed": 7, "_n_configs_per_intensify": 38, "_n_calls_of_intensify": 19, "_ema_n_configs_per_intensifiy": 2.0, "_EMA_ALPHA": 0.2} -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/optdigits/smac/run_1254519304/traj_aclib2.json: -------------------------------------------------------------------------------- 1 | {"cpu_time": 0, "total_cpu_time": null, "wallclock_time": 9.393692016601562e-05, "evaluations": 0, "cost": 2147483648, "incumbent": ["x0='-5.901036752912455'", "x1='3.221638046453227'", "x2='7.617107551611429'", "x3='-0.1689250213983846'", "x4='4.396231385345797'", "x5='0.46455645166091974'"], "origin": "Random initial design."} 2 | {"cpu_time": 0.014675378799438477, "total_cpu_time": null, "wallclock_time": 0.03440260887145996, "evaluations": 1, "cost": 0.45398229632110054, "incumbent": ["x0='-5.901036752912455'", "x1='3.221638046453227'", "x2='7.617107551611429'", "x3='-0.1689250213983846'", "x4='4.396231385345797'", "x5='0.46455645166091974'"], "origin": "Random initial design."} 3 | {"cpu_time": 0.029813766479492188, "total_cpu_time": null, "wallclock_time": 0.36567044258117676, 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"origin": "Random Search"} 9 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/optdigits/smac/run_1254519304/traj_old.csv: -------------------------------------------------------------------------------- 1 | "CPU Time Used","Estimated Training Performance","Wallclock Time","Incumbent ID","Automatic Configurator (CPU) Time","Configuration..." 2 | 0.000000, 2147483648.000000, 0.000094, 1, 0.000094, x0='-5.901036752912455', x1='3.221638046453227', x2='7.617107551611429', x3='-0.1689250213983846', x4='4.396231385345797', x5='0.46455645166091974' 3 | 0.014675, 0.453982, 0.034403, 1, 0.019727, x0='-5.901036752912455', x1='3.221638046453227', x2='7.617107551611429', x3='-0.1689250213983846', x4='4.396231385345797', x5='0.46455645166091974' 4 | 0.029814, 0.055511, 0.365670, 2, 0.335857, x0='-2.988385430258473', x1='5.569945694158359', x2='5.897997928985314', x3='-2.2942176503281444', x4='2.3002429780299942', x5='0.47119457519131447' 5 | 0.080271, 0.038697, 1.307113, 3, 1.226842, x0='-3.1914125169356584', x1='7.214990125768712', x2='7.696512969510755', x3='-3.948947265939128', x4='2.2614500740521755', x5='0.24197149060224105' 6 | 0.164467, 0.030732, 6.249393, 4, 6.084926, x0='-3.1876370811293464', x1='4.584445182076711', x2='6.497718836440081', x3='-3.331887468467503', x4='4.418498287838387', x5='0.4024185653628192' 7 | 0.201525, 0.027112, 8.716111, 5, 8.514585, x0='-3.4402391368932332', x1='7.351839158062646', x2='7.571081862435461', x3='-0.8953586415165598', x4='4.222120977175425', x5='0.04183994613865588' 8 | 0.781240, 0.025020, 32.870060, 6, 32.088820, x0='-2.7120469419112', x1='3.3802476513269344', x2='6.2838212996159974', x3='-2.385583625898922', x4='4.681645973967414', x5='0.24418913554775123' 9 | 0.939408, 0.024859, 39.953045, 7, 39.013637, x0='-2.5877099479354286', x1='5.590285720666181', x2='6.45514174698543', x3='-1.322227612099546', x4='2.212377975001813', x5='0.39278208828980926' 10 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/poker/bohb/configspace.pcs: -------------------------------------------------------------------------------- 1 | x0 real [-6.0, -2.0] [-4.0] 2 | x1 real [3.0, 8.0] [5.5] 3 | x2 real [4.0, 8.0] [6.0] 4 | x3 real [-4.0, 0.0] [-2.0] 5 | x4 real [1.0, 5.0] [3.0] 6 | x5 real [0.0, 0.5] [0.25] -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/poker/hyperband/HPB_run_0_pyro.pkl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/automl/BOAH/7bbc5b97ccbb742c32dc8e6318ed628414cb86dc/examples/icml_2018_experiments/opt_results/paramnet_surrogates/poker/hyperband/HPB_run_0_pyro.pkl -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/poker/hyperband/configspace.pcs: -------------------------------------------------------------------------------- 1 | x0 real [-6.0, -2.0] [-4.0] 2 | x1 real [3.0, 8.0] [5.5] 3 | x2 real [4.0, 8.0] [6.0] 4 | x3 real [-4.0, 0.0] [-2.0] 5 | x4 real [1.0, 5.0] [3.0] 6 | x5 real [0.0, 0.5] [0.25] -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/poker/randomsearch/configspace.pcs: -------------------------------------------------------------------------------- 1 | x0 real [-6.0, -2.0] [-4.0] 2 | x1 real [3.0, 8.0] [5.5] 3 | x2 real [4.0, 8.0] [6.0] 4 | x3 real [-4.0, 0.0] [-2.0] 5 | x4 real [1.0, 5.0] [3.0] 6 | x5 real [0.0, 0.5] [0.25] -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/poker/smac/run_965337418/configspace.json: -------------------------------------------------------------------------------- 1 | { 2 | "hyperparameters": [ 3 | { 4 | "name": "x0", 5 | "type": "uniform_float", 6 | "log": false, 7 | "lower": -6.0, 8 | "upper": -2.0, 9 | "default": -4.0 10 | }, 11 | { 12 | "name": "x1", 13 | "type": "uniform_float", 14 | "log": false, 15 | "lower": 3.0, 16 | "upper": 8.0, 17 | "default": 5.5 18 | }, 19 | { 20 | "name": "x2", 21 | "type": "uniform_float", 22 | "log": false, 23 | "lower": 4.0, 24 | "upper": 8.0, 25 | "default": 6.0 26 | }, 27 | { 28 | "name": "x3", 29 | "type": "uniform_float", 30 | "log": false, 31 | "lower": -4.0, 32 | "upper": 0.0, 33 | "default": -2.0 34 | }, 35 | { 36 | "name": "x4", 37 | "type": "uniform_float", 38 | "log": false, 39 | "lower": 1.0, 40 | "upper": 5.0, 41 | "default": 3.0 42 | }, 43 | { 44 | "name": "x5", 45 | "type": "uniform_float", 46 | "log": false, 47 | "lower": 0.0, 48 | "upper": 0.5, 49 | "default": 0.25 50 | } 51 | ], 52 | "conditions": [], 53 | "forbiddens": [], 54 | "python_module_version": "0.4.10", 55 | "json_format_version": 0.1 56 | } -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/poker/smac/run_965337418/configspace.pcs: -------------------------------------------------------------------------------- 1 | x0 real [-6.0, -2.0] [-4.0] 2 | x1 real [3.0, 8.0] [5.5] 3 | x2 real [4.0, 8.0] [6.0] 4 | x3 real [-4.0, 0.0] [-2.0] 5 | x4 real [1.0, 5.0] [3.0] 6 | x5 real [0.0, 0.5] [0.25] -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/poker/smac/run_965337418/scenario.txt: -------------------------------------------------------------------------------- 1 | execdir = . 2 | deterministic = True 3 | run_obj = quality 4 | overall_obj = par10 5 | par_factor = 10 6 | cost_for_crash = 2147483647.0 7 | algo_runs_timelimit = inf 8 | wallclock_limit = inf 9 | always_race_default = False 10 | ta_run_limit = 40.0 11 | initial_incumbent = RANDOM 12 | pcs_fn = ../opt_results/paramnet_surrogates/poker/smac/run_965337418/configspace.json 13 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/poker/smac/run_965337418/stats.json: -------------------------------------------------------------------------------- 1 | {"ta_runs": 40, "n_configs": 40, "wallclock_time_used": 55.47499489784241, "ta_time_used": 1.5194895267486572, "inc_changed": 4, "_n_configs_per_intensify": 38, "_n_calls_of_intensify": 19, "_ema_n_configs_per_intensifiy": 2.0, "_EMA_ALPHA": 0.2} -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/poker/smac/run_965337418/traj_aclib2.json: -------------------------------------------------------------------------------- 1 | {"cpu_time": 0, "total_cpu_time": null, "wallclock_time": 0.0001914501190185547, "evaluations": 0, "cost": 2147483648, "incumbent": ["x0='-2.763456783161529'", "x1='6.681601775093551'", "x2='7.777465262058573'", "x3='-1.614322334367868'", "x4='1.0714981172735687'", "x5='0.012826150125409497'"], "origin": "Random initial design."} 2 | {"cpu_time": 0.030979394912719727, "total_cpu_time": null, "wallclock_time": 0.07370328903198242, "evaluations": 1, "cost": 0.26680712789807987, "incumbent": ["x0='-2.763456783161529'", "x1='6.681601775093551'", "x2='7.777465262058573'", "x3='-1.614322334367868'", "x4='1.0714981172735687'", "x5='0.012826150125409497'"], "origin": "Random initial design."} 3 | {"cpu_time": 0.08523941040039062, "total_cpu_time": null, "wallclock_time": 0.7302227020263672, "evaluations": 3, "cost": 0.08035564384324528, "incumbent": ["x0='-2.975028821874204'", "x1='3.37687820329722'", "x2='5.20362478305125'", "x3='-2.4549191822839265'", "x4='3.6406619843765307'", "x5='0.09726420263601987'"], "origin": "Random Search"} 4 | {"cpu_time": 0.16112351417541504, "total_cpu_time": null, "wallclock_time": 4.5691819190979, "evaluations": 6, "cost": 0.002223006958301432, "incumbent": ["x0='-3.3296390336760147'", "x1='5.593861737903584'", "x2='7.723454971546828'", "x3='-2.4347001816089113'", "x4='2.8808660453391677'", "x5='0.14284223976501176'"], "origin": "Random Search (sorted)"} 5 | {"cpu_time": 1.4907829761505127, "total_cpu_time": null, "wallclock_time": 52.70077872276306, "evaluations": 39, "cost": 0.001607906271525239, "incumbent": ["x0='-3.6253867093927665'", "x1='5.500766337200364'", "x2='7.597126214974917'", "x3='-2.21662246745676'", "x4='2.8558631974361828'", "x5='0.08394208264413566'"], "origin": "Local Search"} 6 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/paramnet_surrogates/poker/smac/run_965337418/traj_old.csv: -------------------------------------------------------------------------------- 1 | "CPU Time Used","Estimated Training Performance","Wallclock Time","Incumbent ID","Automatic Configurator (CPU) Time","Configuration..." 2 | 0.000000, 2147483648.000000, 0.000191, 1, 0.000191, x0='-2.763456783161529', x1='6.681601775093551', x2='7.777465262058573', x3='-1.614322334367868', x4='1.0714981172735687', x5='0.012826150125409497' 3 | 0.030979, 0.266807, 0.073703, 1, 0.042724, x0='-2.763456783161529', x1='6.681601775093551', x2='7.777465262058573', x3='-1.614322334367868', x4='1.0714981172735687', x5='0.012826150125409497' 4 | 0.085239, 0.080356, 0.730223, 2, 0.644983, x0='-2.975028821874204', x1='3.37687820329722', x2='5.20362478305125', x3='-2.4549191822839265', x4='3.6406619843765307', x5='0.09726420263601987' 5 | 0.161124, 0.002223, 4.569182, 3, 4.408058, x0='-3.3296390336760147', x1='5.593861737903584', x2='7.723454971546828', x3='-2.4347001816089113', x4='2.8808660453391677', x5='0.14284223976501176' 6 | 1.490783, 0.001608, 52.700779, 4, 51.209996, x0='-3.6253867093927665', x1='5.500766337200364', x2='7.597126214974917', x3='-2.21662246745676', x4='2.8558631974361828', x5='0.08394208264413566' 7 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/svm_surrogate/bohb/configspace.pcs: -------------------------------------------------------------------------------- 1 | x0 real [-10.0, 10.0] [0.0] 2 | x1 real [-10.0, 10.0] [0.0] -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/svm_surrogate/hyperband/HPB_run_0_pyro.pkl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/automl/BOAH/7bbc5b97ccbb742c32dc8e6318ed628414cb86dc/examples/icml_2018_experiments/opt_results/svm_surrogate/hyperband/HPB_run_0_pyro.pkl -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/svm_surrogate/hyperband/configspace.pcs: -------------------------------------------------------------------------------- 1 | x0 real [-10.0, 10.0] [0.0] 2 | x1 real [-10.0, 10.0] [0.0] -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/svm_surrogate/randomsearch/configspace.pcs: -------------------------------------------------------------------------------- 1 | x0 real [-10.0, 10.0] [0.0] 2 | x1 real [-10.0, 10.0] [0.0] -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/svm_surrogate/smac/run_1290122126/configspace.json: -------------------------------------------------------------------------------- 1 | { 2 | "hyperparameters": [ 3 | { 4 | "name": "x0", 5 | "type": "uniform_float", 6 | "log": false, 7 | "lower": -10.0, 8 | "upper": 10.0, 9 | "default": 0.0 10 | }, 11 | { 12 | "name": "x1", 13 | "type": "uniform_float", 14 | "log": false, 15 | "lower": -10.0, 16 | "upper": 10.0, 17 | "default": 0.0 18 | } 19 | ], 20 | "conditions": [], 21 | "forbiddens": [], 22 | "python_module_version": "0.4.10", 23 | "json_format_version": 0.1 24 | } -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/svm_surrogate/smac/run_1290122126/configspace.pcs: -------------------------------------------------------------------------------- 1 | x0 real [-10.0, 10.0] [0.0] 2 | x1 real [-10.0, 10.0] [0.0] -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/svm_surrogate/smac/run_1290122126/scenario.txt: -------------------------------------------------------------------------------- 1 | execdir = . 2 | deterministic = True 3 | run_obj = quality 4 | overall_obj = par10 5 | par_factor = 10 6 | cost_for_crash = 2147483647.0 7 | algo_runs_timelimit = inf 8 | wallclock_limit = inf 9 | always_race_default = False 10 | ta_run_limit = 213.0 11 | initial_incumbent = RANDOM 12 | pcs_fn = opt_results/svm_surrogate/smac/run_1290122126/configspace.json 13 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/svm_surrogate/smac/run_1290122126/stats.json: -------------------------------------------------------------------------------- 1 | {"ta_runs": 213, "n_configs": 213, "wallclock_time_used": 97.41573762893677, "ta_time_used": 9.728442907333374, "inc_changed": 6, "_n_configs_per_intensify": 212, "_n_calls_of_intensify": 106, "_ema_n_configs_per_intensifiy": 2.0, "_EMA_ALPHA": 0.2} -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/svm_surrogate/smac/run_1290122126/traj_aclib2.json: -------------------------------------------------------------------------------- 1 | {"cpu_time": 0, "total_cpu_time": null, "wallclock_time": 0.00016307830810546875, "evaluations": 0, "cost": 2147483648, "incumbent": ["x0='1.342681752644344'", "x1='0.033096295208123294'"], "origin": "Random initial design."} 2 | {"cpu_time": 0.028259754180908203, "total_cpu_time": null, "wallclock_time": 0.051781654357910156, "evaluations": 1, "cost": 0.8935996166550483, "incumbent": ["x0='1.342681752644344'", "x1='0.033096295208123294'"], "origin": "Random initial design."} 3 | {"cpu_time": 0.05344820022583008, "total_cpu_time": null, "wallclock_time": 0.24739456176757812, "evaluations": 2, "cost": 0.8935989075630235, "incumbent": ["x0='-0.97784162455876'", "x1='4.914683922564322'"], "origin": "Random Search (sorted)"} 4 | {"cpu_time": 0.13778352737426758, "total_cpu_time": null, "wallclock_time": 0.7643780708312988, "evaluations": 5, "cost": 0.06601466666666664, "incumbent": ["x0='2.5443176037247923'", "x1='-9.83681797180838'"], "origin": "Random Search (sorted)"} 5 | {"cpu_time": 0.1992955207824707, "total_cpu_time": null, "wallclock_time": 1.4355568885803223, "evaluations": 7, "cost": 0.02901773809523811, "incumbent": ["x0='9.531974224362365'", "x1='-6.744386282758659'"], "origin": "Random Search"} 6 | {"cpu_time": 0.7206223011016846, "total_cpu_time": null, "wallclock_time": 11.181859016418457, "evaluations": 24, "cost": 0.01513580194805196, "incumbent": ["x0='2.517420112509072'", "x1='-3.620156907778103'"], "origin": "Random Search (sorted)"} 7 | {"cpu_time": 2.4739201068878174, "total_cpu_time": null, "wallclock_time": 33.36119794845581, "evaluations": 62, "cost": 0.015045801948051959, "incumbent": ["x0='7.2066571581867365'", "x1='-3.8520441556979668'"], "origin": "Random Search (sorted)"} 8 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/svm_surrogate/smac/run_1290122126/traj_old.csv: -------------------------------------------------------------------------------- 1 | "CPU Time Used","Estimated Training Performance","Wallclock Time","Incumbent ID","Automatic Configurator (CPU) Time","Configuration..." 2 | 0.000000, 2147483648.000000, 0.000163, 1, 0.000163, x0='1.342681752644344', x1='0.033096295208123294' 3 | 0.028260, 0.893600, 0.051782, 1, 0.023522, x0='1.342681752644344', x1='0.033096295208123294' 4 | 0.053448, 0.893599, 0.247395, 2, 0.193946, x0='-0.97784162455876', x1='4.914683922564322' 5 | 0.137784, 0.066015, 0.764378, 3, 0.626595, x0='2.5443176037247923', x1='-9.83681797180838' 6 | 0.199296, 0.029018, 1.435557, 4, 1.236261, x0='9.531974224362365', x1='-6.744386282758659' 7 | 0.720622, 0.015136, 11.181859, 5, 10.461237, x0='2.517420112509072', x1='-3.620156907778103' 8 | 2.473920, 0.015046, 33.361198, 6, 30.887278, x0='7.2066571581867365', x1='-3.8520441556979668' 9 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/svm_surrogate/smac/run_178863434/configspace.json: -------------------------------------------------------------------------------- 1 | { 2 | "hyperparameters": [ 3 | { 4 | "name": "x0", 5 | "type": "uniform_float", 6 | "log": false, 7 | "lower": -10.0, 8 | "upper": 10.0, 9 | "default": 0.0 10 | }, 11 | { 12 | "name": "x1", 13 | "type": "uniform_float", 14 | "log": false, 15 | "lower": -10.0, 16 | "upper": 10.0, 17 | "default": 0.0 18 | } 19 | ], 20 | "conditions": [], 21 | "forbiddens": [], 22 | "python_module_version": "0.4.10", 23 | "json_format_version": 0.1 24 | } -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/svm_surrogate/smac/run_178863434/configspace.pcs: -------------------------------------------------------------------------------- 1 | x0 real [-10.0, 10.0] [0.0] 2 | x1 real [-10.0, 10.0] [0.0] -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/svm_surrogate/smac/run_178863434/scenario.txt: -------------------------------------------------------------------------------- 1 | execdir = . 2 | deterministic = True 3 | run_obj = quality 4 | overall_obj = par10 5 | par_factor = 10 6 | cost_for_crash = 2147483647.0 7 | algo_runs_timelimit = inf 8 | wallclock_limit = inf 9 | always_race_default = False 10 | ta_run_limit = 213.0 11 | initial_incumbent = RANDOM 12 | pcs_fn = opt_results/svm_surrogate/smac/run_178863434/configspace.json 13 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/svm_surrogate/smac/run_178863434/stats.json: -------------------------------------------------------------------------------- 1 | {"ta_runs": 213, "n_configs": 213, "wallclock_time_used": 110.00463128089905, "ta_time_used": 13.521803379058838, "inc_changed": 5, "_n_configs_per_intensify": 212, "_n_calls_of_intensify": 106, "_ema_n_configs_per_intensifiy": 2.0, "_EMA_ALPHA": 0.2} -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/svm_surrogate/smac/run_178863434/traj_aclib2.json: -------------------------------------------------------------------------------- 1 | {"cpu_time": 0, "total_cpu_time": null, "wallclock_time": 0.00012350082397460938, "evaluations": 0, "cost": 2147483648, "incumbent": ["x0='7.9466769715940195'", "x1='-8.686702776049785'"], "origin": "Random initial design."} 2 | {"cpu_time": 0.03505849838256836, "total_cpu_time": null, "wallclock_time": 0.05985736846923828, "evaluations": 1, "cost": 0.04299333333333334, "incumbent": ["x0='7.9466769715940195'", "x1='-8.686702776049785'"], "origin": "Random initial design."} 3 | {"cpu_time": 0.10093188285827637, "total_cpu_time": null, "wallclock_time": 0.3517172336578369, "evaluations": 3, "cost": 0.02090835858585861, "incumbent": ["x0='3.820724300119389'", "x1='-2.848474530069394'"], "origin": "Random Search (sorted)"} 4 | {"cpu_time": 0.27942967414855957, "total_cpu_time": null, "wallclock_time": 2.1791176795959473, "evaluations": 9, "cost": 0.01749450013875011, "incumbent": ["x0='7.46199469029164'", "x1='-4.804613281193277'"], "origin": "Random Search (sorted)"} 5 | {"cpu_time": 0.40927696228027344, "total_cpu_time": null, "wallclock_time": 4.407450437545776, "evaluations": 13, "cost": 0.01513580194805196, "incumbent": ["x0='1.1537695568941224'", "x1='-3.174098477835545'"], "origin": "Random Search"} 6 | {"cpu_time": 0.6449446678161621, "total_cpu_time": null, "wallclock_time": 8.857359647750854, "evaluations": 20, "cost": 0.015045801948051959, "incumbent": ["x0='3.6333336287953664'", "x1='-4.0831235766574085'"], "origin": "Random Search"} 7 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/opt_results/svm_surrogate/smac/run_178863434/traj_old.csv: -------------------------------------------------------------------------------- 1 | "CPU Time Used","Estimated Training Performance","Wallclock Time","Incumbent ID","Automatic Configurator (CPU) Time","Configuration..." 2 | 0.000000, 2147483648.000000, 0.000124, 1, 0.000124, x0='7.9466769715940195', x1='-8.686702776049785' 3 | 0.035058, 0.042993, 0.059857, 1, 0.024799, x0='7.9466769715940195', x1='-8.686702776049785' 4 | 0.100932, 0.020908, 0.351717, 2, 0.250785, x0='3.820724300119389', x1='-2.848474530069394' 5 | 0.279430, 0.017495, 2.179118, 3, 1.899688, x0='7.46199469029164', x1='-4.804613281193277' 6 | 0.409277, 0.015136, 4.407450, 4, 3.998173, x0='1.1537695568941224', x1='-3.174098477835545' 7 | 0.644945, 0.015046, 8.857360, 5, 8.212415, x0='3.6333336287953664', x1='-4.0831235766574085' 8 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/scripts/cluster/job_bnn.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #SBATCH -p queue-name # partition (queue) 3 | #SBATCH --mem 4000 # memory pool for all cores (4GB) 4 | #SBATCH -t 0-10:00 # time (D-HH:MM) 5 | #SBATCH -c 4 # number of cores 6 | #SBATCH -o log/%x.%N.%j.out # STDOUT (the folder log has to be created prior to running or this won't work) 7 | #SBATCH -e log/%x.%N.%j.err # STDERR (the folder log has to be created prior to running or this won't work) 8 | #SBATCH -J bnn # sets the job name. If not specified, the file name will be used as job name 9 | #SBATCH --mail-type=END,FAIL # (recive mails about end and timeouts/crashes of your job) 10 | #SBATCH --array 0-3 11 | # Print some information about the job to STDOUT 12 | echo "Workingdir: $PWD"; 13 | echo "NOTE: Always submit from dir with run_experiment.py"; 14 | echo "Started at $(date)"; 15 | echo "Running job $SLURM_JOB_NAME using $SLURM_JOB_CPUS_PER_NODE cpus per node with given JID $SLURM_JOB_ID on queue $SLURM_JOB_PARTITION"; 16 | echo "SLURM_ARRAY_TASK_ID: $SLURM_ARRAY_TASK_ID"; 17 | 18 | source ~/BOHBsCAVE/.ve_BOHBsCAVE/bin/activate; 19 | 20 | # Job to perform 21 | if [ $SLURM_ARRAY_TASK_ID -eq 1 ] 22 | then python run_experiment.py --exp_name bnn --run_id 42 --nic_name eth0 --dataset_bnn bostonhousing --opt_method bohb --max_budget 10000 --min_budget 300 --n_workers 3 23 | else 24 | python run_experiment.py --exp_name bnn --run_id 42 --nic_name eth0 --worker --dataset_bnn bostonhousing --opt_method bohb --max_budget 10000 --min_budget 300 --n_workers 3 25 | fi 26 | 27 | # Print some Information about the end-time to STDOUT 28 | echo "DONE"; 29 | echo "Finished at $(date)"; 30 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/scripts/cluster/job_cartpole.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #SBATCH -p queue-name # partition (queue) 3 | #SBATCH --mem 4000 # memory pool for all cores (4GB) 4 | #SBATCH -t 1-10:00 # time (D-HH:MM) 5 | #SBATCH -c 4 # number of cores 6 | #SBATCH -o log/%x.%N.%j.out # STDOUT (the folder log has to be created prior to running or this won't work) 7 | #SBATCH -e log/%x.%N.%j.err # STDERR (the folder log has to be created prior to running or this won't work) 8 | #SBATCH -J cartpole # sets the job name. If not specified, the file name will be used as job name 9 | #SBATCH --mail-type=END,FAIL # (recive mails about end and timeouts/crashes of your job) 10 | #SBATCH --array 0-3 11 | # Print some information about the job to STDOUT 12 | echo "Workingdir: $PWD"; 13 | echo "NOTE: Always submit from dir with run_experiment.py"; 14 | echo "Started at $(date)"; 15 | echo "Running job $SLURM_JOB_NAME using $SLURM_JOB_CPUS_PER_NODE cpus per node with given JID $SLURM_JOB_ID on queue $SLURM_JOB_PARTITION"; 16 | echo "SLURM_ARRAY_TASK_ID: $SLURM_ARRAY_TASK_ID"; 17 | 18 | source ~/BOHBsCAVE/.ve_BOHBsCAVE/bin/activate; 19 | 20 | # Job to perform 21 | if [ $SLURM_ARRAY_TASK_ID -eq 0 ] 22 | then 23 | python run_experiment.py --exp_name cartpole --run_id 43 --nic_name eth0 --no_worker --opt_method bohb --dest_dir opt_results/cartpole/bohb --max_budget 9 --min_budget 1 --n_workers 4 24 | else 25 | python run_experiment.py --exp_name cartpole --run_id 43 --nic_name eth0 --worker --opt_method bohb --dest_dir opt_results/cartpole/bohb --max_budget 9 --min_budget 1 --n_workers 4 26 | fi 27 | 28 | # Print some Information about the end-time to STDOUT 29 | echo "DONE"; 30 | echo "Finished at $(date)"; 31 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/scripts/generate_all_cave_reports.py: -------------------------------------------------------------------------------- 1 | import os 2 | 3 | from cave.cavefacade import CAVE 4 | 5 | def analyze_all(): 6 | for dirpath, dirnames, filenames in os.walk('../opt_results/'): 7 | if not dirnames: 8 | print(dirpath) 9 | cave = CAVE(folders=[dirpath], 10 | output_dir=os.path.join("../CAVE_reports", dirpath[15:]), # output for debug/images/etc 11 | ta_exec_dir=["."], # Only important for SMAC-results 12 | file_format='BOHB' if os.path.exists(os.path.join(dirpath, 'configs.json')) else 'SMAC3', 13 | #verbose_level='DEV_DEBUG', 14 | verbose_level='OFF', 15 | show_jupyter=False, 16 | ) 17 | cave.analyze() 18 | 19 | if __name__ == '__main__': 20 | analyze_all() 21 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/scripts/workers/base_worker.py: -------------------------------------------------------------------------------- 1 | import os 2 | import pickle, json 3 | import time 4 | 5 | from hpbandster.workers.hpolibbenchmark import HPOlib2Worker 6 | from hpbandster.core.base_iteration import Datum 7 | from hpbandster.core.result import Result 8 | 9 | 10 | class BaseWorker(HPOlib2Worker): 11 | 12 | def __init__(self, max_budget, **kwargs): 13 | super().__init__(**kwargs) 14 | 15 | self.time_ref = time.time() 16 | self.max_budget=max_budget 17 | self.run_data = {} 18 | 19 | 20 | def tpe_configspace(self): 21 | """ 22 | specifies the configuration space for TPE 23 | """ 24 | raise NotImplementedError("Overwrite for actual experiment") 25 | 26 | 27 | def subdir(self): 28 | """ 29 | specifies the subdirectory to store the data 30 | """ 31 | 32 | def evaluate_and_log (self, config, budget): 33 | """ 34 | Helper functions to log results and store them in the same format as Hyperband and BOHB runs 35 | """ 36 | 37 | start = time.time() 38 | res = self.compute(config, budget=budget) 39 | end = time.time() 40 | 41 | 42 | id = (len(self.run_data), 0,0) 43 | 44 | # construct a Datum object to mimic the internals of a HpBandSter iteration 45 | res_dict = {budget: {'loss': res['loss'], 'info': res['info']}} 46 | ts_dict = {budget: {'submitted': start, 'started': start, 'finished': end}} 47 | self.run_data[id] = Datum(config, {}, results=res_dict, budget=budget, time_stamps = ts_dict, status='FINISHED') 48 | 49 | return(res["loss"]) 50 | 51 | 52 | def get_result(self): 53 | 54 | # mock minial HB_config to have meaningful output 55 | mock_HB_config = {'min_budget': self.max_budget, 'max_budget': self.max_budget, 'time_ref': self.time_ref} 56 | 57 | # get Result by pretending to be a HB-run with one iteration 58 | res = Result([self.run_data, ], mock_HB_config) 59 | 60 | return(res) 61 | 62 | def run_tpe(self, num_iterations): 63 | """ 64 | Wrapper around TPE to return a HpBandSter Result object to integrate better with the other methods 65 | """ 66 | try: 67 | from hyperopt import fmin, tpe, hp, STATUS_OK, Trials 68 | except ImportError: 69 | raise ImportError('To run TPE, please install the hyperopt package!') 70 | except: 71 | raise 72 | 73 | def tpe_objective(config): 74 | loss = self.evaluate_and_log(config, budget=self.max_budget) 75 | return({ 'config': config, 76 | 'loss': loss, 77 | 'status': STATUS_OK}) 78 | 79 | 80 | 81 | 82 | space = self.tpe_configspace() 83 | trials = Trials() 84 | best = fmin(tpe_objective, 85 | space=space, 86 | algo=tpe.suggest, 87 | max_evals=num_iterations, 88 | trials=trials) 89 | return(self.get_result()) 90 | 91 | 92 | 93 | def run_smac(self, num_iterations, deterministic=True, working_directory='/tmp'): 94 | """ 95 | Wrapper around SMAC to return a HpBandSter Result object to integrate better with the other methods 96 | """ 97 | 98 | try: 99 | from smac.facade.smac_facade import SMAC 100 | from smac.scenario.scenario import Scenario 101 | except ImportError: 102 | raise ImportError('To run SMAC, please install the latest python implementation of SMAC (pip install smac)!') 103 | except: 104 | raise 105 | 106 | os.makedirs(working_directory, exist_ok=True) 107 | tmp_fn = os.path.join(working_directory, 'smac_%s.json'%self.run_id) 108 | 109 | # SMAC puts every call into a subprocess, so the data has to be stored on disk to 110 | # be persistent. Here, we simply pickle the run data to disk after every call and 111 | # load it before the actual call. 112 | with open(tmp_fn, 'wb') as fh: 113 | pickle.dump(self.run_data, fh) 114 | 115 | 116 | def smac_objective(config, **kwargs): 117 | 118 | with open(tmp_fn, 'rb') as fh: 119 | self.run_data = pickle.load(fh) 120 | 121 | loss = self.evaluate_and_log(config, budget=self.max_budget) 122 | 123 | with open(tmp_fn, 'wb') as fh: 124 | pickle.dump(self.run_data, fh) 125 | 126 | return loss, [] 127 | 128 | scenario = Scenario({ "run_obj": "quality", 129 | "runcount-limit": num_iterations, 130 | "cs": self.configspace, 131 | "deterministic": deterministic, 132 | "initial_incumbent": "RANDOM", 133 | "output_dir": working_directory}) 134 | 135 | 136 | smac = SMAC(scenario=scenario, tae_runner=smac_objective) 137 | smac.optimize() 138 | 139 | 140 | with open(tmp_fn, 'rb') as fh: 141 | self.run_data = pickle.load(fh) 142 | 143 | os.remove(tmp_fn) 144 | 145 | return(self.get_result()) 146 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/scripts/workers/bnn_worker.py: -------------------------------------------------------------------------------- 1 | from hpolib.benchmarks.ml.bnn_benchmark import BNNOnToyFunction, BNNOnBostonHousing, BNNOnProteinStructure, BNNOnYearPrediction 2 | 3 | from .base_worker import BaseWorker 4 | 5 | from hyperopt import fmin, tpe, hp, STATUS_OK, Trials 6 | 7 | 8 | class BNNWorker(BaseWorker): 9 | def __init__(self, dataset, path=None, **kwargs): 10 | 11 | if dataset == 'toyfunction': 12 | b = BNNOnToyFunction() 13 | elif dataset == 'bostonhousing': 14 | b = BNNOnBostonHousing() 15 | elif dataset == 'proteinstructure': 16 | b = BNNOnProteinStructure() 17 | elif dataset == 'yearprediction': 18 | b = BNNOnYearPrediction() 19 | else: 20 | raise ValueError('Unknown dataset %s!'%dataset) 21 | #cs = b.get_configuration_space() 22 | #super().__init__(benchmark=b, configspace=cs, **kwargs) 23 | 24 | super().__init__(benchmark=b, **kwargs) 25 | 26 | def compute(self, config, **kwargs): 27 | config["n_units_1"] = int(config["n_units_1"]) 28 | config["n_units_2"] = int(config["n_units_2"]) 29 | return(super().compute(config, **kwargs)) 30 | 31 | def tpe_configspace(self): 32 | from hyperopt import hp 33 | import numpy as np 34 | space = { 35 | 'l_rate': hp.loguniform('l_rate', np.log(1e-6), np.log(1e-1)), 36 | 'burn_in': hp.uniform('burn_in', 0, .8), 37 | 'n_units_1': hp.qloguniform('n_units_1', np.log(16), np.log(512), 1), 38 | 'n_units_2': hp.qloguniform('n_units_2', np.log(16), np.log(512), 1), 39 | 'mdecay': hp.uniform('mdecay', 0, 1) 40 | } 41 | return(space) 42 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/scripts/workers/cartpole_worker.py: -------------------------------------------------------------------------------- 1 | import time 2 | import numpy 3 | 4 | from hpbandster.core.worker import Worker 5 | 6 | from hpolib.benchmarks.rl.cartpole import CartpoleReduced as surrogate 7 | from .base_worker import BaseWorker 8 | 9 | 10 | class CartpoleReducedWorker(BaseWorker): 11 | def __init__(self, max_budget=None, **kwargs): 12 | 13 | b = surrogate() 14 | 15 | if max_budget is None: 16 | max_budget = b.max_budget 17 | 18 | super().__init__(benchmark=b, max_budget=max_budget, budget_preprocessor=int, **kwargs) 19 | 20 | def compute(self, config, **kwargs): 21 | config["batch_size"] = int(config["batch_size"]) 22 | config["n_units_1"] = int(config["n_units_1"]) 23 | config["n_units_2"] = int(config["n_units_2"]) 24 | 25 | return(super().compute(config=config, **kwargs)) 26 | 27 | def tpe_configspace(self): 28 | 29 | import numpy as np 30 | from hyperopt import hp 31 | 32 | space = { 33 | 'learning_rate': hp.loguniform('learning_rate', np.log(1e-7), np.log(1e-1)), 34 | 'batch_size': hp.qloguniform('batch_size', np.log(8), np.log(256), 1), 35 | 'n_units_1': hp.qloguniform('n_units_1', np.log(8), np.log(128), 1), 36 | 'n_units_2': hp.qloguniform('n_units_2', np.log(8), np.log(128), 1), 37 | 'discount': hp.uniform('discount', 0, 1), 38 | 'likelihood_ratio_clipping': hp.uniform('likelihood_ratio_clipping', 0, 1), 39 | 'entropy_regularization': hp.uniform('entropy_regularization', 0, 1) 40 | } 41 | return(space) 42 | 43 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/scripts/workers/paramnet_surrogates.py: -------------------------------------------------------------------------------- 1 | import time 2 | import numpy 3 | 4 | 5 | from hpolib.benchmarks.surrogates.paramnet import SurrogateReducedParamNetTime as surrogate 6 | from .base_worker import BaseWorker 7 | 8 | class ParamNetSurrogateWorker(BaseWorker): 9 | budgets = { # (min, max)-budget for the different data sets 10 | 'adult' : (9, 243), 11 | 'higgs' : (9, 243), 12 | 'letter' : (3, 81), 13 | 'mnist' : (9, 243), 14 | 'optdigits' : (1, 27), 15 | 'poker' : (81, 2187), 16 | } 17 | 18 | def __init__(self, dataset, surrogate_path,*args, sleep=False, **kwargs): 19 | 20 | b = surrogate(dataset=dataset,path=surrogate_path) 21 | cs = surrogate.get_configuration_space() 22 | super().__init__(benchmark=b, configspace=cs, max_budget=self.budgets[dataset][1], **kwargs) 23 | self.sleep = sleep 24 | 25 | 26 | def compute(self, config, budget, **kwargs): 27 | 28 | x = numpy.array([ config["x0"], config["x1"], config["x2"], 29 | config["x3"], config["x4"], config["x5"]]) 30 | if self.sleep: time.sleep(budget) 31 | 32 | return({ 33 | 'loss': self.benchmark(x, budget=budget), 34 | 'info': config 35 | }) 36 | 37 | 38 | def tpe_configspace(self): 39 | 40 | from hyperopt import hp 41 | 42 | space = { 43 | 'x0': hp.uniform("x0", -6., -2.), 44 | 'x1': hp.uniform("x1", 3., 8.), 45 | 'x2': hp.uniform("x2", 4., 8.), 46 | 'x3': hp.uniform("x3", -4., 0.), 47 | 'x4': hp.uniform("x4", 1., 5.), 48 | 'x5': hp.uniform("x5", 0., .5), 49 | } 50 | return(space) 51 | 52 | -------------------------------------------------------------------------------- /examples/icml_2018_experiments/scripts/workers/svm_surrogate.py: -------------------------------------------------------------------------------- 1 | 2 | import argparse 3 | import numpy 4 | 5 | from hpbandster.core.worker import Worker 6 | 7 | from hpolib.benchmarks.surrogates.svm import SurrogateSVM as surrogate 8 | from .base_worker import BaseWorker 9 | 10 | class SVMSurrogateWorker(BaseWorker): 11 | def __init__(self, surrogate_path=None, sleep=False, **kwargs): 12 | 13 | b = surrogate(path=surrogate_path) 14 | cs = surrogate.get_configuration_space() 15 | kwargs.update({'max_budget': 1.}) 16 | kwargs.update({'budget_name': 'dataset_fraction'}) 17 | super().__init__(benchmark=b, configspace=cs, **kwargs) 18 | self.sleep = sleep 19 | 20 | 21 | def tpe_configspace(self): 22 | 23 | from hyperopt import hp 24 | 25 | space = { 26 | 'x0': hp.uniform("x0", -10., 10.), 27 | 'x1': hp.uniform("x1", -10., 10.), 28 | } 29 | return(space) 30 | -------------------------------------------------------------------------------- /examples/mlp_on_digits/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/automl/BOAH/7bbc5b97ccbb742c32dc8e6318ed628414cb86dc/examples/mlp_on_digits/__init__.py -------------------------------------------------------------------------------- /examples/mlp_on_digits/helper_functions.py: -------------------------------------------------------------------------------- 1 | from sklearn import datasets, neural_network, metrics 2 | from hpbandster.core.worker import Worker 3 | 4 | # inherit from the hpbandster.core.worker class 5 | class MyWorker(Worker): 6 | """ This is a worker for the jupyter-notebook that shows how to connect BOHB to CAVE. """ 7 | def __init__(self, *args, **kwargs): 8 | super(MyWorker, self).__init__(*args, **kwargs) 9 | digits = datasets.load_digits() # load the digits dataset 10 | n_samples = len(digits.images) 11 | data = digits.images.reshape((n_samples, -1)) 12 | 13 | # split it into training and validation set. 14 | split = n_samples // 2 15 | self.train_x, self.valid_x = data[:split], data[split:] 16 | self.train_y, self.valid_y = digits.target[:split], digits.target[split:] 17 | 18 | def compute(self, config, budget, *args, **kwargs): 19 | """ overwrite the *compute* methode: the training of the model happens here """ 20 | beta_1 = 0 if 'beta_1' not in config else config['beta_1'] 21 | beta_2 = 0 if 'beta_2' not in config else config['beta_2'] 22 | 23 | clf = neural_network.MLPClassifier(max_iter=int(budget), 24 | learning_rate='constant', 25 | learning_rate_init=config['learning_rate_init'], 26 | activation=config['activation'], 27 | solver=config['solver'], 28 | beta_1=beta_1, 29 | beta_2=beta_2 30 | ) 31 | clf.fit(self.train_x, self.train_y) 32 | 33 | predicted = clf.predict(self.valid_x) 34 | loss_train = metrics.log_loss(self.train_y, clf.predict_proba(self.train_x)) 35 | loss_valid = metrics.log_loss(self.valid_y, clf.predict_proba(self.valid_x)) 36 | 37 | accuracy_train = clf.score(self.train_x, self.train_y) 38 | accuracy_valid = clf.score(self.valid_x, self.valid_y) 39 | 40 | # make sure that the returned dictionary contains the fields *loss* and *info* 41 | return ({ 42 | 'loss': loss_valid, # this is the a mandatory field to run hyperband 43 | 'info': {'loss_train': loss_train, 44 | 'loss_test': loss_valid, 45 | 'accuracy_train': accuracy_train, 46 | 'accuracy_test': accuracy_valid, 47 | } # can be used for any user-defined information - also mandatory 48 | }) 49 | 50 | 51 | import ConfigSpace as CS 52 | import ConfigSpace.hyperparameters as CSH 53 | 54 | def get_configspace(): 55 | """ Returns the configuration space for the network to be configured in the example. """ 56 | config_space = CS.ConfigurationSpace() 57 | config_space.add_hyperparameters([ 58 | CSH.CategoricalHyperparameter('activation', ['tanh', 'relu']), 59 | CS.UniformFloatHyperparameter( 60 | 'learning_rate_init', lower=1e-6, upper=1e-2, log=True)]) 61 | 62 | solver = CSH.CategoricalHyperparameter('solver', ['sgd', 'adam']) 63 | config_space.add_hyperparameter(solver) 64 | 65 | beta_1 = CS.UniformFloatHyperparameter('beta_1', lower=0, upper=1) 66 | config_space.add_hyperparameter(beta_1) 67 | 68 | condition = CS.EqualsCondition(beta_1, solver, 'adam') 69 | config_space.add_condition(condition) 70 | 71 | beta_2 = CS.UniformFloatHyperparameter('beta_2', lower=0, upper=1) 72 | config_space.add_hyperparameter(beta_2) 73 | 74 | condition = CS.EqualsCondition(beta_2, solver, 'adam') 75 | config_space.add_condition(condition) 76 | 77 | return config_space 78 | 79 | 80 | def optimize_mlp_on_digits(train, valid, budget, **config): 81 | """ 82 | Overwrite BOHB'S *compute* method: the training of the model happens here 83 | 84 | Args: 85 | train : (tuple(np.ndarray, npndarray) 86 | data and labels for training 87 | valid (tuple(np.ndarray, npndarray) 88 | data and labels for training 89 | config : (ConfigSpace.configuration) 90 | a sampled configuration from the 91 | configuration space 92 | budget : (float) 93 | budget, which is passed by the BOHB optimizer 94 | 95 | Returns: 96 | float: validation loss 97 | """ 98 | train_x, train_y = train 99 | valid_x, valid_y = valid 100 | 101 | beta_1 = 0 if 'beta_1' not in config else config['beta_1'] 102 | beta_2 = 0 if 'beta_2' not in config else config['beta_2'] 103 | 104 | clf = neural_network.MLPClassifier(max_iter=int(budget), 105 | learning_rate='constant', 106 | learning_rate_init=config[ 107 | 'learning_rate_init'], 108 | activation=config['activation'], 109 | solver=config['solver'], 110 | beta_1=beta_1, 111 | beta_2=beta_2 112 | ) 113 | clf.fit(train_x, train_y, ) 114 | 115 | loss_valid = metrics.log_loss(valid_y, clf.predict_proba(valid_x)) 116 | return loss_valid 117 | 118 | 119 | def load_digits(): 120 | digits = datasets.load_digits() # load the digits dataset 121 | n_samples = len(digits.images) 122 | data = digits.images.reshape((n_samples, -1)) 123 | 124 | # split it into training and validation set. 125 | split = n_samples // 2 126 | train_x, valid_x = data[:split], data[split:] 127 | train_y, valid_y = digits.target[:split], digits.target[split:] 128 | 129 | return (train_x, train_y), (valid_x, valid_y) 130 | -------------------------------------------------------------------------------- /examples/mlp_on_digits/test_fmin.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | import unittest 3 | import logging 4 | from FMin import fmin, load_func, load_configspace 5 | import ConfigSpace as CS 6 | 7 | 8 | class TestFMin(unittest.TestCase): 9 | def setUp(self): 10 | logging.basicConfig(level=logging.ERROR) 11 | np.random.seed(123) 12 | 13 | self.X = np.random.uniform(-5, 5, 100) 14 | self.y = np.random.normal(self.X, 1) 15 | 16 | self.opt_func = lambda x, y, w, budget: np.mean( 17 | (y[:int(budget)] - w * x[:int(budget)]) ** 2) 18 | 19 | self.cs = CS.ConfigurationSpace() 20 | self.cs.add_hyperparameter( 21 | CS.CategoricalHyperparameter('w', [0, 1]) 22 | ) 23 | 24 | def test_predict(self): 25 | 26 | min_budget = 3 27 | max_budget = 100 28 | inc_best, inc_best_cfg, result = fmin(self.opt_func, self.cs, 29 | func_args=(self.X, self.y), 30 | min_budget=min_budget, 31 | max_budget=max_budget, 32 | num_iterations=1) 33 | id2config = result.get_id2config_mapping() 34 | incumbent = result.get_incumbent_id() 35 | 36 | self.assertTrue(inc_best, result.get_runs_by_id(incumbent)[-1]['loss']) 37 | self.assertTrue(inc_best_cfg, id2config[incumbent]['config']) 38 | 39 | # The best solution shoud be w = 1, since the data is generated from 40 | # f(x) = x 41 | self.assertTrue(inc_best_cfg, 1) 42 | 43 | traj = result.get_incumbent_trajectory() 44 | budgets = [b for b in traj['budgets']] 45 | for i in range(len(budgets)): 46 | self.assertTrue(min_budget <= budgets[i] <= max_budget) 47 | 48 | def test_parse_cmd_args(self): 49 | import argparse 50 | from pathlib import Path 51 | 52 | args = argparse.ArgumentParser() 53 | args.config_space = str(Path.cwd() / 'configSpace.pcs') 54 | args.func = str(Path.cwd() / 'OptFunc.py') 55 | 56 | func = load_func(args.func) 57 | config = load_configspace(args.config_space) 58 | result_loaded = func(w=1, budget=100) 59 | 60 | func_to_load = lambda X, y, w, budget: \ 61 | np.mean((y[:int(budget)] - w*X[:int(budget)])**2) 62 | result_to_load = func_to_load(self.X, self.y, w=1, budget=100) 63 | 64 | self.assertTrue(result_loaded, result_to_load) 65 | self.assertTrue(self.cs.__repr__() == config.__repr__()) 66 | 67 | 68 | if __name__ == '__main__': 69 | unittest.main() 70 | 71 | # TODO: REMOVE THIS AFTER MONDAY -> Just for demonstration purpose 72 | cs = CS.ConfigurationSpace() 73 | cs.add_hyperparameter( 74 | CS.UniformFloatHyperparameter('w', lower=-5, upper=5) 75 | ) 76 | 77 | X = np.random.uniform(-5, 5, 100) 78 | y = np.random.normal(X, 1) 79 | 80 | opt_func = lambda x, y, w, budget: np.mean((y[:int(budget)] - w*x[:int(budget)])**2) 81 | 82 | for w in cs.sample_configuration(size=3): 83 | print("W: {} --> {}".format(w['w'], opt_func(X, y, **w, budget=3))) 84 | 85 | inc_value, inc_cfg, result = fmin(opt_func, cs, func_args=(X, y), 86 | min_budget=3, max_budget=len(X), 87 | num_iterations=3, num_workers=1) 88 | # Plot the results 89 | id2config = result.get_id2config_mapping() 90 | incumbent = result.get_incumbent_id() 91 | 92 | traj = result.get_incumbent_trajectory() 93 | budgets = [b for b in traj['budgets']] 94 | values = [id2config[id]['config'] for id in traj['config_ids']] 95 | 96 | import matplotlib.pyplot as plt 97 | 98 | plt.scatter(X, y) 99 | plt.xlim(-5, 5) 100 | plt.ylim(-5, 5) 101 | for i in range(len(values)): 102 | plt.plot(X, values[i]['w']*X, label="{}. W: {:.2f}".format(i+1, values[i]['w'])) 103 | plt.legend(loc=1) 104 | plt.show() 105 | -------------------------------------------------------------------------------- /requirements.txt: -------------------------------------------------------------------------------- 1 | cython 2 | numpy 3 | jupyter 4 | cave 5 | hpbandster 6 | gym 7 | -------------------------------------------------------------------------------- /scripts/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/automl/BOAH/7bbc5b97ccbb742c32dc8e6318ed628414cb86dc/scripts/__init__.py -------------------------------------------------------------------------------- /setup.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | conda create -n bohb_cave pip 4 | conda activate bohb_cave 5 | cat requirements.txt | xargs -n 1 -L 1 pip install 6 | --------------------------------------------------------------------------------