test_pfunc.py 文件源码

def test_param_allow_downcast_int(self):
        a = tensor.wvector('a')  # int16
        b = tensor.bvector('b')  # int8
        c = tensor.bscalar('c')  # int8
        f = pfunc([In(a, allow_downcast=True),
                   In(b, allow_downcast=False),
                   In(c, allow_downcast=None)],
                  (a + b + c))

        # Both values are in range. Since they're not ndarrays (but lists),
        # they will be converted, and their value checked.
        assert numpy.all(f([3], [6], 1) == 10)

        # Values are in range, but a dtype too large has explicitly been given
        # For performance reasons, no check of the data is explicitly performed
        # (It might be OK to change this in the future.)
        self.assertRaises(TypeError, f,
                          [3], numpy.array([6], dtype='int16'), 1)

        # Value too big for a, silently ignored
        assert numpy.all(f([2 ** 20], numpy.ones(1, dtype='int8'), 1) == 2)

        # Value too big for b, raises TypeError
        self.assertRaises(TypeError, f, [3], [312], 1)

        # Value too big for c, raises TypeError
        self.assertRaises(TypeError, f, [3], [6], 806)