Function test_squared_error_grad

numpy_ml/tests/test_nn.py:339–365

(N=15)

def test_squared_error_grad(N=15):
    from numpy_ml.neural_nets.losses import SquaredError
    from numpy_ml.neural_nets.activations import Tanh

    np.random.seed(12345)

    N = np.inf if N is None else N

    mine = SquaredError()
    gold = torch_mse_grad
    act = Tanh()

    i = 1
    while i < N:
        n_dims = np.random.randint(2, 100)
        n_examples = np.random.randint(1, 1000)
        y = random_tensor((n_examples, n_dims))

        # raw inputs
        z = random_tensor((n_examples, n_dims))
        y_pred = act.fn(z)

        assert_almost_equal(
            mine.grad(y, y_pred, z, act), 0.5 * gold(y, z, torch.tanh), decimal=4
        )
        print("PASSED")
        i += 1


def test_cross_entropy_grad(N=15):