Function test_cross_entropy

numpy_ml/tests/test_nn.py:117–144

(N=15)

def test_cross_entropy(N=15):
    from numpy_ml.neural_nets.losses import CrossEntropy

    np.random.seed(12345)

    N = np.inf if N is None else N

    mine = CrossEntropy()
    gold = log_loss

    # ensure we get 0 when the two arrays are equal
    n_classes = np.random.randint(2, 100)
    n_examples = np.random.randint(1, 1000)
    y = y_pred = random_one_hot_matrix(n_examples, n_classes)
    assert_almost_equal(mine.loss(y, y_pred), gold(y, y_pred))
    print("PASSED")

    # test on random inputs
    i = 1
    while i < N:
        n_classes = np.random.randint(2, 100)
        n_examples = np.random.randint(1, 1000)
        y = random_one_hot_matrix(n_examples, n_classes)
        y_pred = random_stochastic_matrix(n_examples, n_classes)

        assert_almost_equal(mine.loss(y, y_pred), gold(y, y_pred, normalize=False))
        print("PASSED")
        i += 1


def test_VAE_loss(N=15):