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Merged
merged 2 commits into from
Jul 23, 2022
Merged

Test iris xe part2 #862

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c056398
Changed test from copying doubles to copying int64 to run on Iris Xe
oleksandr-pavlyk Jul 22, 2022
75eac28
Added testing logic to skip test cases resulting in JIT-ting kernel f…
oleksandr-pavlyk Jul 22, 2022
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4 changes: 3 additions & 1 deletion dpctl/tests/test_tensor_asarray.py
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Original file line number Diff line number Diff line change
Expand Up @@ -191,7 +191,9 @@ def test_asarray_copy_false():
q = dpctl.SyclQueue()
except dpctl.SyclQueueCreationError:
pytest.skip("Could not create a queue")
X = dpt.from_numpy(np.random.randn(10, 4), usm_type="device", sycl_queue=q)
rng = np.random.default_rng()
Xnp = rng.integers(low=-255, high=255, size=(10, 4), dtype=np.int64)
X = dpt.from_numpy(Xnp, usm_type="device", sycl_queue=q)
Y1 = dpt.asarray(X, copy=False, order="K")
assert Y1 is X
Y1c = dpt.asarray(X, copy=True, order="K")
Expand Down
70 changes: 61 additions & 9 deletions dpctl/tests/test_usm_ndarray_ctor.py
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Original file line number Diff line number Diff line change
Expand Up @@ -601,6 +601,14 @@ def test_tofrom_numpy(shape, dtype, usm_type):
@pytest.mark.parametrize("src_usm_type", ["device", "shared", "host"])
@pytest.mark.parametrize("dst_usm_type", ["device", "shared", "host"])
def test_setitem_same_dtype(dtype, src_usm_type, dst_usm_type):
try:
q = dpctl.SyclQueue()
except dpctl.SyclQueueCreationError:
pytest.skip("Could not create default SyclQueue.")
if q.sycl_device.has_aspect_fp64 is False and dtype in ["f8", "c16"]:
pytest.skip(
"Device does not support double precision floating point types."
)
Xnp = (
np.random.randint(-10, 10, size=2 * 3 * 4)
.astype(dtype)
Expand Down Expand Up @@ -649,6 +657,12 @@ def test_setitem_same_dtype(dtype, src_usm_type, dst_usm_type):
)
@pytest.mark.parametrize("usm_type", ["device", "shared", "host"])
def test_setitem_scalar(dtype, usm_type):
try:
q = dpctl.SyclQueue()
except dpctl.SyclQueueCreationError:
pytest.skip("Could not create default SyclQueue")
if q.sycl_device.has_aspect_fp64 is False and dtype in ["f8", "c16"]:
pytest.skip("Device does not support double precision floating type")
X = dpt.usm_ndarray((6, 6), dtype=dtype, buffer=usm_type)
for i in range(X.size):
X[np.unravel_index(i, X.shape)] = np.asarray(i, dtype=dtype)
Expand All @@ -673,13 +687,22 @@ def test_setitem_errors():
X[:] = Y[None, :, 0]


def test_setitem_different_dtypes():
X = dpt.from_numpy(np.ones(10, "f4"))
Y = dpt.from_numpy(np.zeros(10, "f4"))
Z = dpt.usm_ndarray((20,), "d")
@pytest.mark.parametrize("src_dt,dst_dt", [("i4", "i8"), ("f4", "f8")])
def test_setitem_different_dtypes(src_dt, dst_dt):
try:
q = dpctl.SyclQueue()
except dpctl.SyclQueueCreationError:
pytest.skip("Default queue could not be created")
if dst_dt == "f8" and q.sycl_device.has_aspect_fp64 is False:
pytest.skip(
"Device does not support double precision floating point type"
)
X = dpt.from_numpy(np.ones(10, src_dt), sycl_queue=q)
Y = dpt.from_numpy(np.zeros(10, src_dt), sycl_queue=q)
Z = dpt.empty((20,), dtype=dst_dt, sycl_queue=q)
Z[::2] = X
Z[1::2] = Y
assert np.allclose(dpt.asnumpy(Z), np.tile(np.array([1, 0], "d"), 10))
assert np.allclose(dpt.asnumpy(Z), np.tile(np.array([1, 0], Z.dtype), 10))


def test_shape_setter():
Expand Down Expand Up @@ -804,8 +827,8 @@ def test_to_device_migration():
def test_astype():
X = dpt.empty((5, 5), dtype="i4")
X[:] = np.full((5, 5), 7, dtype="i4")
Y = dpt.astype(X, "c16", order="C")
assert np.allclose(dpt.to_numpy(Y), np.full((5, 5), 7, dtype="c16"))
Y = dpt.astype(X, "c8", order="C")
assert np.allclose(dpt.to_numpy(Y), np.full((5, 5), 7, dtype="c8"))
Y = dpt.astype(X[::2, ::-1], "f2", order="K")
assert np.allclose(dpt.to_numpy(Y), np.full(Y.shape, 7, dtype="f2"))
Y = dpt.astype(X[::2, ::-1], "i4", order="K", copy=False)
Expand Down Expand Up @@ -946,7 +969,15 @@ def test_zeros(dtype):
_all_dtypes,
)
def test_ones(dtype):
X = dpt.ones(10, dtype=dtype)
try:
q = dpctl.SyclQueue()
except dpctl.SyclQueueCreationError:
pytest.skip("Could not created default queue")
if dtype in ["f8", "c16"] and q.sycl_device.has_aspect_fp64 is False:
pytest.skip(
"Device does not support double precision floating point type"
)
X = dpt.ones(10, dtype=dtype, sycl_queue=q)
assert np.array_equal(dpt.asnumpy(X), np.ones(10, dtype=dtype))


Expand All @@ -955,7 +986,15 @@ def test_ones(dtype):
_all_dtypes,
)
def test_full(dtype):
X = dpt.full(10, 4, dtype=dtype)
try:
q = dpctl.SyclQueue()
except dpctl.SyclQueueCreationError:
pytest.skip("Could not created default queue")
if dtype in ["f8", "c16"] and q.sycl_device.has_aspect_fp64 is False:
pytest.skip(
"Device does not support double precision floating point type"
)
X = dpt.full(10, 4, dtype=dtype, sycl_queue=q)
assert np.array_equal(dpt.asnumpy(X), np.full(10, 4, dtype=dtype))


Expand All @@ -976,6 +1015,10 @@ def test_arange(dt):
except dpctl.SyclQueueCreationError:
pytest.skip("Queue could not be created")

if dt in ["f8", "c16"] and q.sycl_device.has_aspect_fp64 is False:
pytest.skip(
"Device does not support double precision floating point type"
)
X = dpt.arange(0, 123, dtype=dt, sycl_queue=q)
dt = np.dtype(dt)
if np.issubdtype(dt, np.integer):
Expand Down Expand Up @@ -1093,6 +1136,10 @@ def test_ones_like(dt, usm_kind):
q = dpctl.SyclQueue()
except dpctl.SyclQueueCreationError:
pytest.skip("Queue could not be created")
if dt in ["f8", "c16"] and q.sycl_device.has_aspect_fp64 is False:
pytest.skip(
"Device does not support double precision floating point type"
)

X = dpt.empty((4, 5), dtype=dt, usm_type=usm_kind, sycl_queue=q)
Y = dpt.ones_like(X)
Expand Down Expand Up @@ -1129,6 +1176,11 @@ def test_full_like(dt, usm_kind):
except dpctl.SyclQueueCreationError:
pytest.skip("Queue could not be created")

if dt in ["f8", "c16"] and q.sycl_device.has_aspect_fp64 is False:
pytest.skip(
"Device does not support double precision floating point type"
)

fill_v = np.dtype(dt).type(1)
X = dpt.empty((4, 5), dtype=dt, usm_type=usm_kind, sycl_queue=q)
Y = dpt.full_like(X, fill_v)
Expand Down