code: def test_complete_and_get_new_suggestions(self):
      tpeAlgorithm = TpeAlgorithm()
  
      new_trials = tpeAlgorithm.get_new_suggestions(
          self.study.id, [], 1
      )
      new_trials[0].status = "Completed"
      new_trials[0].objective_value = 0.6
      new_trials[0].save()
  
      new_trials = tpeAlgorithm.get_new_suggestions(
          self.study.id, [], 1
      )
      new_trials[0].status = "Completed"
      new_trials[0].objective_value = 0.7
      new_trials[0].save()
  
      new_trials = tpeAlgorithm.get_new_suggestions(
          self.study.id, [], 3
      )
  
      # Assert getting two trials
      self.assertEqual(len(new_trials), 3)
  
      # Assert getting the trials
      new_trial = new_trials[0]
      new_parameter_values = new_trial.parameter_values
      new_parameter_values_json = json.loads(new_parameter_values)
      self.assertTrue(
          0.99 >= new_parameter_values_json["l1_normalization"] >= 0.01
      )
      self.assertTrue(
          0.5 >= new_parameter_values_json["learning_rate"] >= 0.01
      )
      self.assertTrue(
          new_parameter_values_json["hidden2"] in [8, 16, 32, 64]
      )
      self.assertTrue(
          new_parameter_values_json["optimizer"]
          in ["sgd", "adagrad", "adam", "ftrl"]
      )
  
file_path: advisor/advisor_server/suggestion/algorithm/tpe_test.py
imports: import json
  from django.test import TestCase
  from suggestion.models import Study
  from suggestion.algorithm.abstract_algorithm import AbstractSuggestionAlgorithm
  from suggestion.algorithm.tpe import TpeAlgorithm
label_desc: Use image node_id 6 for calling the TpeAlgorithmTest obj's underlying member method code with example usage: obj.test_complete_and_get_new_suggestions() without return types