docstr: :param method: 'grid_search', 'random_search'
  :param enabled:
docstr_tok: [":","param","method",":","'grid_search","'",",","'random_search'",":","param","enabled",":"]
code: def __init__(
      self, method="grid_search", enabled=True, experiment=None
  ):
      """
      :param method: 'grid_search', 'random_search'
      :param enabled:
      """
      self.method = method
      self.enabled = enabled
      self.experiment = experiment
      self.seen_params = {}
      self.current_iteration = 0
  
      # the params to use at each trial
      self.trials = None
  
      # total iterations we're doing
      self.nb_iterations = None
  
      # details about each param
      self.params = []
  
file_path: test-tube/test_tube/hyperopt.py
imports: import itertools
  import json
  import random
label_desc: Use image node_id 1 to create a new HyperParamOptimizer object from inherited base classes: object with example: obj = HyperParamOptimizer(method, enabled, experiment)