code: def tune_evens(self, low, high, default, name):
      start = low if low % 2 == 0 else low + 1
  
      def gen_samples():
          return range(start, high + 1, 2)
  
      return self.__resolve_param(gen_samples, default, name)
  
file_path: test-tube/test_tube/hyperopt.py
imports: import itertools
  import json
  import random
label_desc: Use image node_id 4 for calling the HyperParamOptimizer obj's underlying member method code with example usage: obj.tune_evens(low, high, default, name) and returns: self, range