docstr: Parameters:
  -----------
  
  directory: string
      where the results are logged
  logger: hpbandster.utils.result_logger_v??
      the logger to store the data, defaults to v1
  overwrite: bool
      whether or not existing data will be overwritten
docstr_tok: ["Parameters",":","--","--","--","--","--","-","directory",":","string","where","the","results","are","logged","logger",":","hpbandster.utils.result_logger_v","?","?","the","logger","to","store","the","data",",","defaults","to","v1","overwrite",":","bool","whether","or","not","existing","data","will","be","overwritten"]
code: def __init__(
      self,
      configspace,
      max_budget,
      n_points=2000,
      delta=1.0,
      n_candidates=1024,
      **kwargs,
  ):
      """
      Parameters:
      -----------
  
      directory: string
          where the results are logged
      logger: hpbandster.utils.result_logger_v??
          the logger to store the data, defaults to v1
      overwrite: bool
          whether or not existing data will be overwritten
  
      """
  
      super(LCNetWrapper, self).__init__(**kwargs)
  
      self.n_candidates = n_candidates
      self.model = LCNet(
          sampling_method="sghmc",
          l_rate=np.sqrt(1e-4),
          mdecay=0.05,
          n_nets=100,
          burn_in=500,
          n_iters=3000,
          get_net=get_lc_net,
          precondition=True,
      )
  
      self.config_space = configspace
      self.max_budget = max_budget
      self.train = None
      self.train_targets = None
      self.n_points = n_points
      self.is_trained = False
      self.counter = 0
      self.delta = delta
      self.lock = threading.Lock()
  
file_path: HpBandSter/hpbandster/optimizers/config_generators/lcnet.py
imports: import ConfigSpace
  import numpy
  import threading
  from robo.models.lcnet import LCNet, get_lc_net
  from hpbandster.core.base_config_generator import base_config_generator
label_desc: Use image node_id 1 to create a new LCNetWrapper object from inherited base classes: base_config_generator with example: obj = LCNetWrapper(configspace, max_budget, n_points, delta, n_candidates)