from __future__ import absolute_import
import numpy as np
import os
from scipy.stats import norm
from scipy.stats import foldnorm
from stratified_bayesian_optimization.initializers.log import SBOLog
from stratified_bayesian_optimization.util.json_file import JSONFile
logger = SBOLog(__name__)
class RandomPolicy(object):
def __init__(self, dict_stat_models, name_model, problem_name, type_model='grad_epoch', n_epochs=1,
stop_iteration_per_point=100, random_seed=None, n_restarts=None):
self.dict_stat_models = dict_stat_models
self.points_index = range(len(self.dict_stat_models))
self.current_index = 0
self.type_model = type_model
self.problem_name = problem_name
self.name_model = name_model
self.n_epochs = n_epochs
self.chosen_points = {}
self.evaluations_obj = {}
self.stop_iteration_per_point = stop_iteration_per_point
def test_info(self):
logger = SBOLog(__name__)
logger.info('testing')