code: def test_random_sample_with_raw_choices_1(self):
      batch_size = 1
      input_param = ng.p.Dict(
          choice1=ng.p.Choice([32, 64, 128]),
          choice2=ng.p.Choice([True, False]),
          choice3=ng.p.Choice(
              ["Red", "Blue", "Green", "Yellow", "Purple"]
          ),
      )
      obj_func = None
      optimizer = RandomSearchOptimizer(
          input_param,
          obj_func,
          batch_size=batch_size,
          sampling_weights=None,
      )
      sampled_sol = optimizer.sample(batch_size)
      sampled_sol = optimizer.indices_to_raw_choices(sampled_sol)
      self.assertEqual(len(sampled_sol), batch_size)
      self.assertIsInstance(sampled_sol, list)
      for sample in sampled_sol:
          self.assertSetEqual(
              set(sample.keys()), set(input_param.keys())
          )
          for key in sample:
              self.assertIn(sample[key], input_param[key].choices.value)
  
imports: import random
  import unittest
  from collections import defaultdict
  from typing import Dict
  import nevergrad
  import numpy
  import torch
  import torch.nn
  from reagent.lite.optimizer import BayesianByBackpropOptimizer, BayesianMLPEnsemblerOptimizer, BayesianOptimizerBase, GREEDY_TEMP, GumbelSoftmaxOptimizer, NeverGradOptimizer, PolicyGradientOptimizer, QLearningOptimizer, RandomSearchOptimizer, sol_to_tensors
label_desc: Use image node_id 3 for calling the TestComboOptimizer obj's underlying member method code with example usage: obj.test_random_sample_with_raw_choices_1() without return types