Kurobako blog: random.py

random.py

# A solver implementation based on Random Search algorithm.
from kurobako import problem
from kurobako import solver
import numpy as np
 
class RandomSolverFactory(solver.SolverFactory):
    def specification(self):
        return solver.SolverSpec(name='Random Search')
 
    def create_solver(self, seed, problem):
        return RandomSolver(seed, problem)
 
class RandomSolver(solver.Solver):
    def __init__(self, seed, problem):
        self._rng = np.random.RandomState(seed)
        self._problem = problem
 
    def ask(self, idg):
        trial_id = idg.generate()
        next_step = self._problem.steps.last_step
        params = []
        for p in self._problem.params:
            if p.distribution == problem.Distribution.LOG_UNIFORM:
                low = np.log(p.range.low)
                high = np.log(p.range.high)
                params.append(float(np.exp(self._rng.uniform(log, high))))
            else:
                params.append(self._rng.uniform(p.range.low, p.range.high))
 
        return solver.NextTrial(trial_id, params, next_step)
 
    def tell(self, trial):
        pass
 
if __name__ == '__main__':
    runner = solver.SolverRunner(RandomSolverFactory())
    runner.run()