def test_as_type():
x = Tensor([1, 2, 3], dtype=np.float32)
y = x.astype(qint8(0.1))
np.testing.assert_almost_equal(get_scale(y.dtype), 0.1)
z = y.astype(qint8(0.2))
np.testing.assert_almost_equal(get_scale(z.dtype), 0.2)
a = z.astype(quint8(0.3, 127))
np.testing.assert_almost_equal(get_scale(a.dtype), 0.3)
np.testing.assert_equal(get_zero_point(a.dtype), 127)
b = a.astype(quint8(0.3, 128))
np.testing.assert_almost_equal(get_scale(b.dtype), 0.3)
np.testing.assert_equal(get_zero_point(b.dtype), 128)
def test_qint_new_tensor(dtype, dtype_name):
convert_to_dtype = eval("convert_to_%s" % dtype_name)
convert_from_dtype = eval("convert_from_%s" % dtype_name)
shape = (3, 3, 3)
data = np.random.random(shape).astype(np.float32) * 5 - 1
# create a new Tensor with quint8 dtype
inp = Tensor(convert_to_dtype(data, dtype), dtype=dtype)
_check_result_attr(inp, dtype, dtype_name, dtype_name.startswith("qu"))
np.testing.assert_equal(inp.numpy(), convert_to_dtype(data, dtype))
# convert from quint8 to float32
inp_float = inp.astype("float32")
assert inp_float.dtype == np.float32
np.testing.assert_equal(inp_float.numpy(),
convert_from_dtype(convert_to_dtype(data, dtype)))
def test_qint_astype(dtype, dtype_name):
convert_to_dtype = eval("convert_to_%s" % dtype_name)
convert_from_dtype = eval("convert_from_%s" % dtype_name)
shape = (3, 3, 3)
data = np.random.random(shape).astype(np.float32) * 5 - 1
inp = Tensor(data, dtype="float32")
# convert to quint4
oup = inp.astype(dtype)
_check_result_attr(oup, dtype, dtype_name, dtype_name.startswith("qu"))
np.testing.assert_equal(oup.numpy(), convert_to_dtype(data, dtype))
# convert from quint4 to float32
oup_float = oup.astype("float32")
assert oup_float.dtype == np.float32
np.testing.assert_equal(oup_float.numpy(),
convert_from_dtype(convert_to_dtype(data, dtype)))
