test_pfunc.py 文件源码

def test_param_allow_downcast_vector_floatX(self):
        a = tensor.fvector('a')
        b = tensor.fvector('b')
        c = tensor.fvector('c')

        f = pfunc([In(a, allow_downcast=True),
                   In(b, allow_downcast=False),
                   In(c, allow_downcast=None)],
                  (a + b + c))

        # If the values can be accurately represented, everything is OK
        z = [0]
        assert numpy.all(f(z, z, z) == 0)

        # If allow_downcast is True, idem
        assert numpy.allclose(f([0.1], z, z), 0.1)

        # If allow_downcast is False, nope
        self.assertRaises(TypeError, f, z, [0.1], z)

        # If allow_downcast is None, like False
        self.assertRaises(TypeError, f, z, z, [0.1])