def test_quint8_typecvt():
device = "xpux"
shape = (3, 3, 3)
data = np.random.random(shape).astype(np.float32) * 5 - 1
def typecvt(x, dt=None):
(y, ) = G.apply_normal_varnode(ops.TypeCvt(dtype=dt), x)
return y
# convert to quint8
dtype = quint8(0.01, 135)
oup = _get_compiled_result(data,
np.float32,
shape,
device,
calc_func=partial(typecvt, dt=dtype))
_check_result_attr(oup, dtype, "quint8")
np.testing.assert_equal(oup, convert_to_quint8(data, dtype))
# convert from quint8 to float32
oup_float = _get_compiled_result(oup,
dtype,
shape,
device,
calc_func=partial(typecvt, dt=np.float32))
assert oup_float.dtype == np.float32
np.testing.assert_equal(
oup_float, convert_from_quint8(convert_to_quint8(data, dtype)))
def test_dtype_int8_ffi_handle():
device = "xpux"
shape = (3, 3, 3)
data = np.random.random(shape).astype(np.float32) * 5 - 1
def identity(x):
return x
dtype = quint8(0.01, 127)
inp = convert_to_quint8(data, dtype)
oup = _get_compiled_result(inp, dtype, shape, device, calc_func=identity)
_check_result_attr(oup, dtype, "quint8")
np.testing.assert_allclose(convert_from_quint8(oup), convert_from_quint8(inp))
dtype = qint8(0.01)
inp = convert_to_qint8(data, dtype)
oup = _get_compiled_result(inp, dtype, shape, device, calc_func=identity)
_check_result_attr(oup, dtype, "qint8", is_unsigned=False)
np.testing.assert_allclose(convert_from_qint8(oup), convert_from_qint8(inp))
def get_qat_inputs_quint8(inp_dtype, num_inp=1, shape=(1, 16, 384, 512)):
inps = []
for _ in range(num_inp):
data1 = mge.tensor(np.random.random(shape)) * 16
data1 = data1.astype(inp_dtype)
inp1 = mge.tensor(dtype.convert_from_quint8(data1.numpy()))
inp1.qparams.scale = mge.tensor(dtype.get_scale(inp_dtype))
inp1.qparams.zero_point = mge.tensor(dtype.get_zero_point(inp_dtype))
inp1.qparams.dtype_meta = dtype._builtin_quant_dtypes["quint8"]
inps.append(inp1)
return inps