def smac_gm(self):
clu_cs = ConfigurationSpace()
cov_t = CategoricalHyperparameter(
"covariance_type", ["full", "tied", "diag", "spherical"])
tol = UniformFloatHyperparameter("tol", 1e-6, 0.1)
reg_c = UniformFloatHyperparameter("reg_covar", 1e-10, 0.1)
n_com = UniformIntegerHyperparameter("n_components", 2, 10)
max_iter = UniformIntegerHyperparameter("max_iter", 10, 1000)
clu_cs.add_hyperparameters([cov_t, tol, reg_c, n_com, max_iter])
clu_scenario = Scenario({
"run_obj":
"quality", # we optimize quality (alternatively runtime)
# "runcount-limit": Constants.num_eval, # maximum function evaluations
"cs": clu_cs, # configuration space
"deterministic": "true",
"tuner-timeout": constants.timeout,
"wallclock_limit": constants.timeout,
"cutoff_time": constants.timeout
})
print('Run GM SMAC ' + self.name)
smac = SMAC(scenario=clu_scenario, tae_runner=self.run_gm)
parameters = smac.optimize()
value = smac.get_runhistory().get_cost(parameters)
return value, parameters
def smac_em(self):
clu_cs = ConfigurationSpace()
n_init = UniformIntegerHyperparameter("n_init", 1, 15)
n_com = UniformIntegerHyperparameter("n_components", 2, 10)
reg_c = UniformFloatHyperparameter("min_covar", 1e-6, 0.1)
max_iter = UniformIntegerHyperparameter("n_iters", 10, 1000)
tr = UniformFloatHyperparameter("threshold", 1e-6, 0.1)
clu_cs.add_hyperparameters([n_init, tr, reg_c, n_com, max_iter])
clu_scenario = Scenario({
"run_obj":
"quality", # we optimize quality (alternatively runtime)
# "runcount-limit": Constants.num_eval, # maximum function evaluations
"cs": clu_cs, # configuration space
"deterministic": "true",
"tuner-timeout": constants.em_timeout,
"wallclock_limit": constants.em_timeout,
"cutoff_time": constants.em_timeout,
"runcount-limit": 1
})
print('Run EM SMAC ' + self.name)
smac = SMAC(scenario=clu_scenario, tae_runner=self.run_em)
parameters = smac.optimize()
value = smac.get_runhistory().get_cost(parameters)
return value, parameters
def test_get_runhistory_and_trajectory(self):
ta = ExecuteTAFuncDict(lambda x: x ** 2)
smac = SMAC(tae_runner=ta, scenario=self.scenario)
self.assertRaises(ValueError, smac.get_runhistory)
self.assertRaises(ValueError, smac.get_trajectory)
smac.trajectory = 'dummy'
self.assertEqual(smac.get_trajectory(), 'dummy')
smac.runhistory = 'dummy'
self.assertEqual(smac.get_runhistory(), 'dummy')
