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"])
def test_get_multiple_new_suggestions(self): tpeAlgorithm = TpeAlgorithm() # Assert getting one trial new_trials = tpeAlgorithm.get_new_suggestions(self.study.id, number=1) self.assertEqual(len(new_trials), 1) # Assert getting multiple trials new_trials = tpeAlgorithm.get_new_suggestions(self.study.id, number=10) self.assertEqual(len(new_trials), 10)
def test_get_new_suggestions(self): tpeAlgorithm = TpeAlgorithm() new_trials = tpeAlgorithm.get_new_suggestions( self.study.id, number=1) new_trial = new_trials[0] new_parameter_values_json = json.loads(new_trial.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["l1_normalization"] >= 0.01) self.assertTrue(new_parameter_values_json["learning_rate"] >= 0.01)
def test_get_new_suggestions(self): tpeAlgorithm = TpeAlgorithm() new_trials = tpeAlgorithm.get_new_suggestions(self.study.id, number=1) new_trial = new_trials[0] new_parameter_values_json = json.loads(new_trial.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"])