def test_smoothL1_random_derivative(backend_default, fargs):
    s1, s2, m = fargs
    shape = (s1, s2)
    magnitude = m
    outputs = (np.random.random(shape) - 0.5) * magnitude
    targets = np.random.random(shape)
    x = outputs - targets
    expected_result = np.zeros(shape)
    I1, J1 = np.where(1 < abs(x))
    I2, J2 = np.where(abs(x) >= 1)
    expected_result[I1, J1] = x[I1, J1]
    expected_result[I2, J2] = np.sign(x[I2, J2])
    compare_tensors(SmoothL1Loss(), outputs,
                    targets, expected_result,
                    deriv=True, tol=1e-5)
dataset/ETHPy150Open NervanaSystems/neon/tests/test_costs.py/test_smoothL1_random_derivative/swapped operands of `<`