Python GreedySearcherの例

コード例 #1

ファイル: test_search.py プロジェクト: Saiuz/autokeras

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

コード例 #2

ファイル: test_search.py プロジェクト: Saiuz/autokeras

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

コード例 #3

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

コード例 #4

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

コード例 #5

                         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])