<filename>nasbench301/surrogate_models/configs/model_configs/svr_nu/create_svr_nu_configspace.py
import ConfigSpace as CS
import ConfigSpace.hyperparameters as CSH
from ConfigSpace.read_and_write import json as cs_json

cs = CS.ConfigurationSpace()

kernel = CSH.CategoricalHyperparameter('kernel', choices=['linear', 'rbf',
                                                          'poly', 'sigmoid'],
                                       default_value='rbf')
degree = CSH.UniformIntegerHyperparameter('degree', lower=1, upper=128,
                                          log=True, default_value=18)
coef0 = CSH.UniformFloatHyperparameter('coef0', lower=-.5, upper=.5,
                                     log=False, default_value=0.27073849350462764)
tol = CSH.UniformFloatHyperparameter('tol', lower=1e-4, upper=1e-2,
                                     log=True, default_value=0.00022086199204762887)
gamma = CSH.CategoricalHyperparameter('gamma', choices=['scale', 'auto'],
                                      default_value='scale')
C = CSH.UniformFloatHyperparameter('C', lower=1.0, upper=20, log=True,
                                   default_value=3.0079917803781395)
nu = CSH.UniformFloatHyperparameter('nu', lower=0.01, upper=1, log=False,
                                    default_value=0.40518108684088283)
shrinking = CSH.CategoricalHyperparameter('shrinking', choices=['True',
                                                                'False'],
                                          default_value='False')

cs.add_hyperparameters([kernel, tol, gamma, C, nu, shrinking, degree, coef0])

with open('svr_nu_configspace.json', 'w') as f:
    f.write(cs_json.write(cs))


<filename>nasbench301/surrogate_models/configs/model_configs/svr_nu/create_svr_nu_configspace.py
import ConfigSpace as CS
import ConfigSpace.hyperparameters as CSH
from ConfigSpace.read_and_write import json as cs_json

cs = CS.ConfigurationSpace()

kernel = CSH.CategoricalHyperparameter('kernel', choices=['linear', 'rbf',
                                                          'poly', 'sigmoid'],
                                       default_value='rbf')
degree = CSH.UniformIntegerHyperparameter('degree', lower=1, upper=128,
                                          log=True, default_value=18)
coef0 = CSH.UniformFloatHyperparameter('coef0', lower=-.5, upper=.5,
                                     log=False, default_value=0.27073849350462764)
tol = CSH.UniformFloatHyperparameter('tol', lower=1e-4, upper=1e-2,
                                     log=True, default_value=0.00022086199204762887)
gamma = CSH.CategoricalHyperparameter('gamma', choices=['scale', 'auto'],
                                      default_value='scale')
C = CSH.UniformFloatHyperparameter('C', lower=1.0, upper=20, log=True,
                                   default_value=3.0079917803781395)
nu = CSH.UniformFloatHyperparameter('nu', lower=0.01, upper=1, log=False,
                                    default_value=0.40518108684088283)
shrinking = CSH.CategoricalHyperparameter('shrinking', choices=['True',
                                                                'False'],
                                          default_value='False')

cs.add_hyperparameters([kernel, tol, gamma, C, nu, shrinking, degree, coef0])

with open('svr_nu_configspace.json', 'w') as f:
    f.write(cs_json.write(cs))

