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# Author: Simon Blanke |
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# Email: [email protected] |
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# License: MIT License |
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from .opt_args import Arguments |
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from .distribution import Distribution |
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from .optimizers import ( |
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HillClimbingOptimizer, |
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StochasticHillClimbingOptimizer, |
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TabuOptimizer, |
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RandomSearchOptimizer, |
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RandomRestartHillClimbingOptimizer, |
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RandomAnnealingOptimizer, |
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SimulatedAnnealingOptimizer, |
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StochasticTunnelingOptimizer, |
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ParallelTemperingOptimizer, |
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ParticleSwarmOptimizer, |
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EvolutionStrategyOptimizer, |
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BayesianOptimizer, |
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) |
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optimizer_dict = { |
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"HillClimbing": HillClimbingOptimizer, |
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"StochasticHillClimbing": StochasticHillClimbingOptimizer, |
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"TabuSearch": TabuOptimizer, |
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"RandomSearch": RandomSearchOptimizer, |
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"RandomRestartHillClimbing": RandomRestartHillClimbingOptimizer, |
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"RandomAnnealing": RandomAnnealingOptimizer, |
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"SimulatedAnnealing": SimulatedAnnealingOptimizer, |
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"StochasticTunneling": StochasticTunnelingOptimizer, |
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"ParallelTempering": ParallelTemperingOptimizer, |
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"ParticleSwarm": ParticleSwarmOptimizer, |
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"EvolutionStrategy": EvolutionStrategyOptimizer, |
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"Bayesian": BayesianOptimizer, |
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} |
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class HyperactiveCore: |
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def __init__(self, _main_args_): |
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self._main_args_ = _main_args_ |
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self._opt_args_ = Arguments(**self._main_args_.opt_para) |
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def run(self): |
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optimizer_class = optimizer_dict[self._main_args_.optimizer] |
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dist = Distribution() |
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dist.dist(optimizer_class, self._main_args_, self._opt_args_) |
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self.results = dist.results |
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self.pos_list = dist.pos |
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# self.para_list = None |
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self.score_list = dist.scores |
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self.eval_times = dist.eval_times |
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self.iter_times = dist.iter_times |
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self.best_scores = dist.best_scores |
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SimonBlanke /
Hyperactive
