code: def generate_parameters(self, parameter_id, **kwargs):
      params = {}
      for k in self._space:
          t, v = self._space[k]["_type"], self._space[k]["_value"]
          if t == "choice":
              params[k] = random.choice(v)
          elif t == "randint":
              params[k] = random.choice(range(v[0], v[1]))
          elif t == "uniform":
              params[k] = np.random.uniform(v[0], v[1])
          else:
              raise RuntimeError(
                  "parameter type {} is supported by DemoTuner!".format(
                      t
                  )
              )
      return params
  
file_path: nni/examples/tuners/customized_tuner/demo_tuner/demo_tuner.py
imports: import random
  import numpy
  from nni.tuner import Tuner
  from nni.utils import ClassArgsValidator
label_desc: Use image node_id 3 for calling the DemoTuner obj's underlying member method code with example usage: obj.generate_parameters(parameter_id) and returns: params