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Fix technical debt in trig element-wise function tests #2126

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Merged
merged 8 commits into from
Jul 23, 2025
Merged

Fix technical debt in trig element-wise function tests #2126

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bd7e9a6
refactor test_trig_out_type
ndgrigorian Jul 21, 2025
76aaf9f
refactor test_hyper_out_type
ndgrigorian Jul 21, 2025
a6a1c48
remove redundant usm_type tests
ndgrigorian Jul 21, 2025
878640b
remove redundant tests using out keyword
ndgrigorian Jul 21, 2025
0a7c95a
remove redundant memory order tests
ndgrigorian Jul 21, 2025
de8c3ee
remove complex special case tests for trig elementwise funcs
ndgrigorian Jul 22, 2025
f6d9043
unpin NumPy in coverage and OS compiler CI
ndgrigorian Jul 22, 2025
636147d
remove unused `_dpc_funcs` from both trig test files
ndgrigorian Jul 22, 2025
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3 changes: 1 addition & 2 deletions .github/workflows/generate-coverage.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -91,8 +91,7 @@ jobs:
- name: Install dpctl dependencies
shell: bash -l {0}
run: |
# TODO: unpin numpy when numpy#29167 resolved
pip install numpy"<2.3.0" cython setuptools"<80" pytest pytest-cov scikit-build cmake coverage[toml] versioneer[toml]==0.29
pip install numpy cython setuptools"<80" pytest pytest-cov scikit-build cmake coverage[toml] versioneer[toml]==0.29

- name: Build dpctl with coverage
shell: bash -l {0}
Expand Down
3 changes: 1 addition & 2 deletions .github/workflows/os-llvm-sycl-build.yml
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Original file line number Diff line number Diff line change
Expand Up @@ -107,8 +107,7 @@ jobs:
- name: Install dpctl dependencies
shell: bash -l {0}
run: |
# TODO: unpin numpy when numpy#29167 resolved
pip install numpy"<2.3.0" cython setuptools"<80" pytest scikit-build cmake ninja versioneer[toml]==0.29
pip install numpy cython setuptools"<80" pytest scikit-build cmake ninja versioneer[toml]==0.29

- name: Checkout repo
uses: actions/checkout@v4.2.2
Expand Down
132 changes: 2 additions & 130 deletions dpctl/tests/elementwise/test_hyperbolic.py
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Original file line number Diff line number Diff line change
Expand Up @@ -14,10 +14,6 @@
# See the License for the specific language governing permissions and
# limitations under the License.

import itertools
import os
import re

import numpy as np
import pytest
from numpy.testing import assert_allclose
Expand All @@ -34,7 +30,6 @@
(np.arctanh, dpt.atanh),
]
_all_funcs = _hyper_funcs + _inv_hyper_funcs
_dpt_funcs = [t[1] for t in _all_funcs]


@pytest.mark.parametrize("np_call, dpt_call", _all_funcs)
Expand All @@ -45,17 +40,10 @@ def test_hyper_out_type(np_call, dpt_call, dtype):

a = 1 if np_call == np.arccosh else 0

X = dpt.asarray(a, dtype=dtype, sycl_queue=q)
expected_dtype = np_call(np.array(a, dtype=dtype)).dtype
expected_dtype = _map_to_device_dtype(expected_dtype, q.sycl_device)
assert dpt_call(X).dtype == expected_dtype

X = dpt.asarray(a, dtype=dtype, sycl_queue=q)
x = dpt.asarray(a, dtype=dtype, sycl_queue=q)
expected_dtype = np_call(np.array(a, dtype=dtype)).dtype
expected_dtype = _map_to_device_dtype(expected_dtype, q.sycl_device)
Y = dpt.empty_like(X, dtype=expected_dtype)
dpt_call(X, out=Y)
assert_allclose(dpt.asnumpy(dpt_call(X)), dpt.asnumpy(Y))
assert dpt_call(x).dtype == expected_dtype


@pytest.mark.parametrize("np_call, dpt_call", _all_funcs)
Expand Down Expand Up @@ -119,79 +107,6 @@ def test_hyper_complex_contig(np_call, dpt_call, dtype):
)


@pytest.mark.parametrize("np_call, dpt_call", _all_funcs)
@pytest.mark.parametrize("usm_type", ["device", "shared", "host"])
def test_hyper_usm_type(np_call, dpt_call, usm_type):
q = get_queue_or_skip()

arg_dt = np.dtype("f4")
input_shape = (10, 10, 10, 10)
X = dpt.empty(input_shape, dtype=arg_dt, usm_type=usm_type, sycl_queue=q)
if np_call == np.arctanh:
X[..., 0::2] = -0.4
X[..., 1::2] = 0.3
elif np_call == np.arccosh:
X[..., 0::2] = 2.2
X[..., 1::2] = 5.5
else:
X[..., 0::2] = -4.4
X[..., 1::2] = 5.5

Y = dpt_call(X)
assert Y.usm_type == X.usm_type
assert Y.sycl_queue == X.sycl_queue
assert Y.flags.c_contiguous

expected_Y = np_call(dpt.asnumpy(X))
tol = 8 * dpt.finfo(Y.dtype).resolution
assert_allclose(dpt.asnumpy(Y), expected_Y, atol=tol, rtol=tol)


@pytest.mark.parametrize("np_call, dpt_call", _all_funcs)
@pytest.mark.parametrize("dtype", _all_dtypes)
def test_hyper_order(np_call, dpt_call, dtype):
q = get_queue_or_skip()
skip_if_dtype_not_supported(dtype, q)

arg_dt = np.dtype(dtype)
input_shape = (4, 4, 4, 4)
X = dpt.empty(input_shape, dtype=arg_dt, sycl_queue=q)
if np_call == np.arctanh:
X[..., 0::2] = -0.4
X[..., 1::2] = 0.3
elif np_call == np.arccosh:
X[..., 0::2] = 2.2
X[..., 1::2] = 5.5
else:
X[..., 0::2] = -4.4
X[..., 1::2] = 5.5

for perms in itertools.permutations(range(4)):
U = dpt.permute_dims(X[:, ::-1, ::-1, :], perms)
with np.errstate(all="ignore"):
expected_Y = np_call(dpt.asnumpy(U))
for ord in ["C", "F", "A", "K"]:
Y = dpt_call(U, order=ord)
tol = 8 * max(
dpt.finfo(Y.dtype).resolution,
np.finfo(expected_Y.dtype).resolution,
)
assert_allclose(dpt.asnumpy(Y), expected_Y, atol=tol, rtol=tol)


@pytest.mark.parametrize("callable", _dpt_funcs)
@pytest.mark.parametrize("dtype", _all_dtypes)
def test_hyper_error_dtype(callable, dtype):
q = get_queue_or_skip()
skip_if_dtype_not_supported(dtype, q)

x = dpt.ones(5, dtype=dtype)
y = dpt.empty_like(x, dtype="int16")
with pytest.raises(ValueError) as excinfo:
callable(x, out=y)
assert re.match("Output array of type.*is needed", str(excinfo.value))


@pytest.mark.parametrize("np_call, dpt_call", _all_funcs)
@pytest.mark.parametrize("dtype", ["f2", "f4", "f8"])
def test_hyper_real_strided(np_call, dpt_call, dtype):
Expand Down Expand Up @@ -270,46 +185,3 @@ def test_hyper_real_special_cases(np_call, dpt_call, dtype):

tol = 8 * dpt.finfo(dtype).resolution
assert_allclose(dpt.asnumpy(dpt_call(yf)), Y_np, atol=tol, rtol=tol)


@pytest.mark.parametrize("np_call, dpt_call", _all_funcs)
@pytest.mark.parametrize("dtype", ["c8", "c16"])
def test_hyper_complex_special_cases_conj_property(np_call, dpt_call, dtype):
q = get_queue_or_skip()
skip_if_dtype_not_supported(dtype, q)

x = [np.nan, np.inf, -np.inf, +0.0, -0.0, +1.0, -1.0]
xc = [complex(*val) for val in itertools.product(x, repeat=2)]

Xc_np = np.array(xc, dtype=dtype)
Xc = dpt.asarray(Xc_np, dtype=dtype, sycl_queue=q)

tol = 50 * dpt.finfo(dtype).resolution
Y = dpt_call(Xc)
Yc = dpt_call(dpt.conj(Xc))

dpt.allclose(Y, dpt.conj(Yc), atol=tol, rtol=tol)


@pytest.mark.skipif(
os.name != "posix", reason="Known to fail on Windows due to bug in NumPy"
)
@pytest.mark.parametrize("np_call, dpt_call", _all_funcs)
@pytest.mark.parametrize("dtype", ["c8", "c16"])
def test_hyper_complex_special_cases(np_call, dpt_call, dtype):
q = get_queue_or_skip()
skip_if_dtype_not_supported(dtype, q)

x = [np.nan, np.inf, -np.inf, +0.0, -0.0, +1.0, -1.0]
xc = [complex(*val) for val in itertools.product(x, repeat=2)]

Xc_np = np.array(xc, dtype=dtype)
Xc = dpt.asarray(Xc_np, dtype=dtype, sycl_queue=q)

with np.errstate(all="ignore"):
Ynp = np_call(Xc_np)

tol = 50 * dpt.finfo(dtype).resolution
Y = dpt_call(Xc)
assert_allclose(dpt.asnumpy(dpt.real(Y)), np.real(Ynp), atol=tol, rtol=tol)
assert_allclose(dpt.asnumpy(dpt.imag(Y)), np.imag(Ynp), atol=tol, rtol=tol)
132 changes: 2 additions & 130 deletions dpctl/tests/elementwise/test_trigonometric.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -14,10 +14,6 @@
# See the License for the specific language governing permissions and
# limitations under the License.

import itertools
import os
import re

import numpy as np
import pytest
from numpy.testing import assert_allclose
Expand All @@ -34,7 +30,6 @@
(np.arctan, dpt.atan),
]
_all_funcs = _trig_funcs + _inv_trig_funcs
_dpt_funcs = [t[1] for t in _all_funcs]


@pytest.mark.parametrize("np_call, dpt_call", _all_funcs)
Expand All @@ -43,17 +38,10 @@ def test_trig_out_type(np_call, dpt_call, dtype):
q = get_queue_or_skip()
skip_if_dtype_not_supported(dtype, q)

X = dpt.asarray(0, dtype=dtype, sycl_queue=q)
expected_dtype = np_call(np.array(0, dtype=dtype)).dtype
expected_dtype = _map_to_device_dtype(expected_dtype, q.sycl_device)
assert dpt_call(X).dtype == expected_dtype

X = dpt.asarray(0, dtype=dtype, sycl_queue=q)
x = dpt.asarray(0, dtype=dtype, sycl_queue=q)
expected_dtype = np_call(np.array(0, dtype=dtype)).dtype
expected_dtype = _map_to_device_dtype(expected_dtype, q.sycl_device)
Y = dpt.empty_like(X, dtype=expected_dtype)
dpt_call(X, out=Y)
assert_allclose(dpt.asnumpy(dpt_call(X)), dpt.asnumpy(Y))
assert dpt_call(x).dtype == expected_dtype


@pytest.mark.parametrize("np_call, dpt_call", _all_funcs)
Expand Down Expand Up @@ -127,78 +115,6 @@ def test_trig_complex_contig(np_call, dpt_call, dtype):
assert_allclose(dpt.asnumpy(Z), expected, atol=tol, rtol=tol)


@pytest.mark.parametrize("np_call, dpt_call", _all_funcs)
@pytest.mark.parametrize("usm_type", ["device", "shared", "host"])
def test_trig_usm_type(np_call, dpt_call, usm_type):
q = get_queue_or_skip()

arg_dt = np.dtype("f4")
input_shape = (10, 10, 10, 10)
X = dpt.empty(input_shape, dtype=arg_dt, usm_type=usm_type, sycl_queue=q)
if np_call in _trig_funcs:
X[..., 0::2] = np.pi / 6
X[..., 1::2] = np.pi / 3
if np_call == np.arctan:
X[..., 0::2] = -2.2
X[..., 1::2] = 3.3
else:
X[..., 0::2] = -0.3
X[..., 1::2] = 0.7

Y = dpt_call(X)
assert Y.usm_type == X.usm_type
assert Y.sycl_queue == X.sycl_queue
assert Y.flags.c_contiguous

expected_Y = np_call(dpt.asnumpy(X))
tol = 8 * dpt.finfo(Y.dtype).resolution
assert_allclose(dpt.asnumpy(Y), expected_Y, atol=tol, rtol=tol)


@pytest.mark.parametrize("np_call, dpt_call", _all_funcs)
@pytest.mark.parametrize("dtype", _all_dtypes)
def test_trig_order(np_call, dpt_call, dtype):
q = get_queue_or_skip()
skip_if_dtype_not_supported(dtype, q)

arg_dt = np.dtype(dtype)
input_shape = (4, 4, 4, 4)
X = dpt.empty(input_shape, dtype=arg_dt, sycl_queue=q)
if np_call in _trig_funcs:
X[..., 0::2] = np.pi / 6
X[..., 1::2] = np.pi / 3
if np_call == np.arctan:
X[..., 0::2] = -2.2
X[..., 1::2] = 3.3
else:
X[..., 0::2] = -0.3
X[..., 1::2] = 0.7

for perms in itertools.permutations(range(4)):
U = dpt.permute_dims(X[:, ::-1, ::-1, :], perms)
expected_Y = np_call(dpt.asnumpy(U))
for ord in ["C", "F", "A", "K"]:
Y = dpt_call(U, order=ord)
tol = 8 * max(
dpt.finfo(Y.dtype).resolution,
np.finfo(expected_Y.dtype).resolution,
)
assert_allclose(dpt.asnumpy(Y), expected_Y, atol=tol, rtol=tol)


@pytest.mark.parametrize("callable", _dpt_funcs)
@pytest.mark.parametrize("dtype", _all_dtypes)
def test_trig_error_dtype(callable, dtype):
q = get_queue_or_skip()
skip_if_dtype_not_supported(dtype, q)

x = dpt.zeros(5, dtype=dtype)
y = dpt.empty_like(x, dtype="int16")
with pytest.raises(ValueError) as excinfo:
callable(x, out=y)
assert re.match("Output array of type.*is needed", str(excinfo.value))


@pytest.mark.parametrize("np_call, dpt_call", _all_funcs)
@pytest.mark.parametrize("dtype", ["f2", "f4", "f8"])
def test_trig_real_strided(np_call, dpt_call, dtype):
Expand Down Expand Up @@ -298,47 +214,3 @@ def test_trig_real_special_cases(np_call, dpt_call, dtype):
tol = 8 * dpt.finfo(dtype).resolution
Y = dpt_call(yf)
assert_allclose(dpt.asnumpy(Y), Y_np, atol=tol, rtol=tol)


@pytest.mark.parametrize("np_call, dpt_call", _all_funcs)
@pytest.mark.parametrize("dtype", ["c8", "c16"])
def test_trig_complex_special_cases_conj_property(np_call, dpt_call, dtype):
q = get_queue_or_skip()
skip_if_dtype_not_supported(dtype, q)

x = [np.nan, np.inf, -np.inf, +0.0, -0.0, +1.0, -1.0]
xc = [complex(*val) for val in itertools.product(x, repeat=2)]

Xc_np = np.array(xc, dtype=dtype)
Xc = dpt.asarray(Xc_np, dtype=dtype, sycl_queue=q)

tol = 50 * dpt.finfo(dtype).resolution
Y = dpt_call(Xc)
Yc = dpt_call(dpt.conj(Xc))

dpt.allclose(Y, dpt.conj(Yc), atol=tol, rtol=tol)


@pytest.mark.skipif(
os.name != "posix", reason="Known to fail on Windows due to bug in NumPy"
)
@pytest.mark.parametrize("np_call, dpt_call", _all_funcs)
@pytest.mark.parametrize("dtype", ["c8", "c16"])
def test_trig_complex_special_cases(np_call, dpt_call, dtype):

q = get_queue_or_skip()
skip_if_dtype_not_supported(dtype, q)

x = [np.nan, np.inf, -np.inf, +0.0, -0.0, +1.0, -1.0]
xc = [complex(*val) for val in itertools.product(x, repeat=2)]

Xc_np = np.array(xc, dtype=dtype)
Xc = dpt.asarray(Xc_np, dtype=dtype, sycl_queue=q)

with np.errstate(all="ignore"):
Ynp = np_call(Xc_np)

tol = 50 * dpt.finfo(dtype).resolution
Y = dpt_call(Xc)
assert_allclose(dpt.asnumpy(dpt.real(Y)), np.real(Ynp), atol=tol, rtol=tol)
assert_allclose(dpt.asnumpy(dpt.imag(Y)), np.imag(Ynp), atol=tol, rtol=tol)
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