Python get_classification_data_loaders_mlp Beispiele

Beispiel #1

Datei: test_search.py Projekt: 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

Beispiel #2

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

Beispiel #3

Datei: test_search.py Projekt: Saiuz/autokeras

def test_bayesian_searcher_mlp(_, _1, _2):
    train_data, test_data = get_classification_data_loaders_mlp()
    clean_dir(TEST_TEMP_DIR)
    generator = BayesianSearcher(3, (28,), verbose=False, path=TEST_TEMP_DIR, metric=Accuracy,
                         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

Beispiel #4

Datei: test_search.py Projekt: tl-yang/autokeras

def test_bayesian_searcher_mlp(_, _1, _2):
    train_data, test_data = get_classification_data_loaders_mlp()
    clean_dir(TEST_TEMP_DIR)
    generator = Searcher(3, (28,), verbose=False, path=TEST_TEMP_DIR, metric=Accuracy,
                         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

Beispiel #5

def test_bayesian_searcher_mlp(_, _1, _2):
    train_data, test_data = get_classification_data_loaders_mlp()