Function test_cross_entropy_grad

numpy_ml/tests/test_nn.py:368–393

(N=15)

def test_cross_entropy_grad(N=15):
    from numpy_ml.neural_nets.losses import CrossEntropy
    from numpy_ml.neural_nets.layers import Softmax

    np.random.seed(12345)

    N = np.inf if N is None else N

    mine = CrossEntropy()
    gold = torch_xe_grad
    sm = Softmax()

    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)

        # the cross_entropy_gradient returns the gradient wrt. z (NOT softmax(z))
        z = random_tensor((n_examples, n_classes))
        y_pred = sm.forward(z)

        assert_almost_equal(mine.grad(y, y_pred), gold(y, z), decimal=5)
        print("PASSED")
        i += 1


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