def test_greedy_searcher_mlp(_, _1, _2): train_data, test_data = get_classification_data_loaders_mlp() clean_dir(TEST_TEMP_DIR) generator = GreedySearcher(3, (28,), verbose=False, path=TEST_TEMP_DIR, metric=Accuracy, loss=classification_loss, generators=[MlpGenerator, MlpGenerator]) for _ in range(2): generator.search(train_data, test_data) clean_dir(TEST_TEMP_DIR) assert len(generator.history) == 2
def test_greedy_searcher_sp(_, _1, _2, _3): train_data, test_data = get_classification_data_loaders() clean_dir(TEST_TEMP_DIR) searcher = GreedySearcher(3, (28, 28, 3), verbose=False, path=TEST_TEMP_DIR, metric=Accuracy, loss=classification_loss, generators=[CnnGenerator, CnnGenerator]) for _ in range(2): searcher.search(train_data, test_data) clean_dir(TEST_TEMP_DIR) assert len(searcher.history) == 2
loss=classification_loss, generators=[MlpGenerator, MlpGenerator]) Constant.N_NEIGHBOURS = 1 Constant.T_MIN = 0.8 for _ in range(2): generator.search(train_data, test_data) clean_dir(TEST_TEMP_DIR) assert len(generator.history) == 2 @patch('torch.multiprocessing.get_context', side_effect=MockProcess) @patch('autokeras.bayesian.transform', side_effect=simple_transform) @patch('autokeras.search.ModelTrainer.train_model', side_effect=mock_train) def test_greedy_searcher(_, _1, _2): train_data, test_data = get_classification_data_loaders() clean_dir(TEST_TEMP_DIR) searcher = GreedySearcher(3, (28, 28, 3), verbose=False, path=TEST_TEMP_DIR, metric=Accuracy, loss=classification_loss, generators=[CnnGenerator, CnnGenerator]) for _ in range(2): searcher.search(train_data, test_data) clean_dir(TEST_TEMP_DIR) assert len(searcher.history) == 2 @patch('torch.multiprocessing.get_context', side_effect=MockProcess) @patch('autokeras.bayesian.transform', side_effect=simple_transform) @patch('autokeras.search.ModelTrainer.train_model', side_effect=mock_train) @patch('autokeras.search.get_system', return_value=Constant.SYS_GOOGLE_COLAB) def test_greedy_searcher_sp(_, _1, _2, _3): train_data, test_data = get_classification_data_loaders() clean_dir(TEST_TEMP_DIR) searcher = GreedySearcher(3, (28, 28, 3), verbose=False, path=TEST_TEMP_DIR, metric=Accuracy, loss=classification_loss, generators=[CnnGenerator, CnnGenerator])