def test_unary_ops(filter_str, unary_op, input_arrays, get_shape, capfd):
a = input_arrays[0]
op, name = unary_op
if name != "argsort" and name != "copy":
a = np.reshape(a, get_shape)
if name == "cumprod" and (filter_str == "opencl:cpu:0"
or a.dtype == np.int32 or is_gen12(filter_str)):
pytest.skip()
if name == "cumsum" and (filter_str == "opencl:cpu:0"
or a.dtype == np.int32 or is_gen12(filter_str)):
pytest.skip()
if name == "mean" and is_gen12(filter_str):
pytest.skip()
if name == "argmax" and is_gen12(filter_str):
pytest.skip()
actual = np.empty(shape=a.shape, dtype=a.dtype)
expected = np.empty(shape=a.shape, dtype=a.dtype)
f = njit(op)
device = dpctl.SyclDevice(filter_str)
with dpctl.device_context(device), dpnp_debug():
actual = f(a)
captured = capfd.readouterr()
assert "dpnp implementation" in captured.out
expected = op(a)
np.testing.assert_allclose(actual, expected, rtol=1e-3, atol=0)
def test_trigonometric_fn(filter_str, trig_op, input_arrays):
# FIXME: Why does archcosh fail on Gen12 discrete graphics card?
if trig_op == "arccosh" and is_gen12(filter_str):
pytest.skip()
a, b = input_arrays
trig_fn = getattr(np, trig_op)
actual = np.empty(shape=a.shape, dtype=a.dtype)
expected = np.empty(shape=a.shape, dtype=a.dtype)
if trig_op == "arctan2":
@njit
def f(a, b):
return trig_fn(a, b)
device = dpctl.SyclDevice(filter_str)
with dpctl.device_context(device), assert_auto_offloading():
actual = f(a, b)
expected = trig_fn(a, b)
else:
@njit
def f(a):
return trig_fn(a)
device = dpctl.SyclDevice(filter_str)
with dpctl.device_context(device), assert_auto_offloading():
actual = f(a)
expected = trig_fn(a)
np.testing.assert_allclose(actual, expected, rtol=1e-5, atol=0)
def test_unary_ops(filter_str, unary_op, input_arrays):
# FIXME: Why does sign fail on Gen12 discrete graphics card?
skip_ops = ["sign", "log", "log2", "log10", "expm1"]
if unary_op in skip_ops and is_gen12(filter_str):
pytest.skip()
a = input_arrays[0]
uop = getattr(np, unary_op)
actual = np.empty(shape=a.shape, dtype=a.dtype)
expected = np.empty(shape=a.shape, dtype=a.dtype)
@njit
def f(a):
return uop(a)
device = dpctl.SyclDevice(filter_str)
with dpctl.device_context(device), assert_auto_offloading():
actual = f(a)
expected = uop(a)
np.testing.assert_allclose(actual, expected, rtol=1e-5, atol=0)
def test_unary_ops(filter_str, unary_op, input_array, get_shape, capfd):
a = input_array
a = np.reshape(a, get_shape)
op, name = unary_op
if (name == "cumprod" or name == "cumsum") and (
filter_str == "opencl:cpu:0" or is_gen12(filter_str)
):
pytest.skip()
actual = np.empty(shape=a.shape, dtype=a.dtype)
expected = np.empty(shape=a.shape, dtype=a.dtype)
f = njit(op)
device = dpctl.SyclDevice(filter_str)
with dpctl.device_context(device), dpnp_debug():
actual = f(a)
captured = capfd.readouterr()
assert "dpnp implementation" in captured.out
expected = op(a)
max_abs_err = np.sum(actual - expected)
assert max_abs_err < 1e-4
