class_docstr: Configuration class
      
class_docstr_tok: ["Configuration","class"]
code: def __init__(self, search_space):
      self.params = {}
      self.key_order = []
      for key in search_space.keys():
          if search_space[key]["_type"] == "factor":
              self.key_order.append(key)
              self.params[key] = Factor(search_space[key]["_value"])
          else:
              raise RuntimeError(
                  "N_A2C Tuner doesn't support this kind of parameter: "
                  + str(search_space[key]["_type"])
              )
  
imports: import math
  import random
  import logging
  import copy
  import torch
  from torch import optim
  from torch import nn
  import torch.nn.functional
  import numpy
  import nni
  from nni.tuner import Tuner
label_desc: Use image node_id 1 to create a new Configuration object from inherited base classes: object with example: obj = Configuration(search_space)