code: def validate_class_args(self, **kwargs):
      Schema(
          {
              Optional("optimize_mode"): self.choices(
                  "optimize_mode", "maximize", "minimize"
              ),
              Optional("parallel_optimize"): bool,
              Optional("constant_liar_type"): self.choices(
                  "constant_liar_type", "min", "max", "mean"
              ),
          }
      ).validate(kwargs)
  
imports: import copy
  import logging
  import hyperopt
  import numpy
  from schema import Optional, Schema
  from nni import ClassArgsValidator
  from nni.common.hpo_utils import validate_search_space
  from nni.tuner import Tuner
  from nni.utils import NodeType, OptimizeMode, extract_scalar_reward, split_index
label_desc: Use image node_id 1 for calling the HyperoptClassArgsValidator obj's underlying member method code with example usage: obj.validate_class_args() without return types