class_docstr: The class for driving the Bayesian optimization according to the configuration.
class_docstr_tok: ["The","class","for","driving","the","Bayesian","optimization","according","to","the","configuration","."]
code: def __init__(self, config=None, obj_func=None, outputEng=None):
      if config is None:
          from .config_parser import default_config
          import copy
  
          self.config = copy.deepcopy(default_config)
      else:
          self.config = config
      self.obj_func = obj_func
      self.outputEng = outputEng
  
file_path: GPyOpt/GPyOpt/interface/driver.py
imports: import numpy
  import time
  from ..methods import BayesianOptimization
label_desc: Use image node_id 1 to create a new BODriver object from inherited base classes: object with example: obj = BODriver(config, obj_func, outputEng)