def _gradients(self, params):
if settings.options['numerical_grad']:
gradients = numerical_gradient(self.value, params=params)
else:
gradients = autodiff_gradient(self.value, params=params)
return gradients
def test_numerical_gradient():
param1 = zfit.Parameter('param1', 4.)
param2 = zfit.Parameter('param2', 5.)
param3 = zfit.Parameter('param3', 2.)
def func1():
return param1 * param2**2 + param3**param1
num_gradients = numerical_gradient(func1, params=[param1, param2, param3])
tf_gradients = autodiff_gradient(func1, params=[param1, param2, param3])
np.testing.assert_allclose(num_gradients, tf_gradients)