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Unmuted tests from test_mathematical.py scope #1668

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merged 6 commits into from
Feb 2, 2024
Merged

Unmuted tests from test_mathematical.py scope #1668

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db318d7
Unmuted tests from test_mathematical.py scope
antonwolfy Jan 25, 2024
d8f2989
Merge branch 'master' into unmute_mathematical_tests
antonwolfy Jan 25, 2024
9821733
Merge branch 'master' into unmute_mathematical_tests
antonwolfy Feb 1, 2024
5380736
Removed fallback fixture for dpnp.copysign
antonwolfy Feb 1, 2024
476bcc0
Tests for dpnp.clip with NaN edges require numpy>=1.25.0
antonwolfy Feb 1, 2024
7ce622e
Muted again power tests with complex types (until 2024.1 release)
antonwolfy Feb 1, 2024
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24 changes: 5 additions & 19 deletions tests/test_mathematical.py
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Original file line number Diff line number Diff line change
Expand Up @@ -15,6 +15,7 @@

import dpnp
from dpnp.dpnp_array import dpnp_array
from tests.third_party.cupy import testing

from .helper import (
assert_dtype_allclose,
Expand All @@ -25,7 +26,6 @@
get_integer_dtypes,
has_support_aspect64,
is_cpu_device,
is_win_platform,
)


Expand Down Expand Up @@ -125,8 +125,7 @@ def test_input_nan(self):
expected = numpy.clip(np_a, -1, 1)
assert_array_equal(result, expected)

# TODO: unmute the test once dpctl resolves the issue
@pytest.mark.skip(reason="dpctl-1489 issue")
@testing.with_requires("numpy>=1.25.0")
@pytest.mark.parametrize(
"kwargs",
[
Expand All @@ -138,7 +137,7 @@ def test_input_nan(self):
],
)
def test_nan_edges(self, kwargs):
np_a = numpy.arange(7)
np_a = numpy.arange(7.0)
dp_a = dpnp.asarray(np_a)

result = dp_a.clip(**kwargs)
Expand Down Expand Up @@ -424,7 +423,6 @@ def test_add(self, dtype, lhs, rhs):
def test_arctan2(self, dtype, lhs, rhs):
self._test_mathematical("arctan2", dtype, lhs, rhs)

@pytest.mark.usefixtures("allow_fall_back_on_numpy")
@pytest.mark.parametrize(
"dtype", get_all_dtypes(no_bool=True, no_complex=True)
)
Expand Down Expand Up @@ -564,7 +562,7 @@ def test_op_with_scalar(array, val, func, data_type, val_type):
pytest.skip(
"(0j ** 0) is different: (NaN + NaNj) in dpnp and (1 + 0j) in numpy"
)
# TODO: Remove when #1378 (dpctl) is solved
# TODO: Remove when #1378 (dpctl) is solved and 2024.1 is released (coverage is failing otherwise)
elif (
is_cpu_device()
and dpnp_a.dtype == dpnp.complex128
Expand Down Expand Up @@ -1002,7 +1000,7 @@ def test_power(array, val, data_type, val_type):
dpnp_a = dpnp.array(array, dtype=data_type)
val_ = val_type(val)

# TODO: Remove when #1378 (dpctl) is solved
# TODO: Remove when #1378 (dpctl) is solved and 2024.1 is released (coverage is failing otherwise)
if (
is_cpu_device()
and (
Expand Down Expand Up @@ -2306,12 +2304,6 @@ def test_complex_values(self):
dp_arr = dpnp.array(np_arr)
func = lambda x: x**2

# TODO: unmute the test once it's available
if is_win_platform():
pytest.skip(
"Until the latest dpctl is available on internal channel"
)

assert_dtype_allclose(func(dp_arr), func(np_arr))

@pytest.mark.parametrize("val", [0, 1], ids=["0", "1"])
Expand Down Expand Up @@ -2696,9 +2688,6 @@ def test_matmul_dtype_matrix_inputs(self, dtype1, dtype2, shape_pair):
with pytest.raises(TypeError):
dpnp.matmul(b1, b2, dtype=dtype2)

# TODO: Temporary skipping the test, until Internal CI is updated with
# recent changed in dpctl regarding dpt.result_type function
@pytest.mark.skip("Temporary skipping the test")
@pytest.mark.parametrize("dtype1", get_all_dtypes(no_bool=True))
@pytest.mark.parametrize("dtype2", get_all_dtypes(no_bool=True))
@pytest.mark.parametrize(
Expand Down Expand Up @@ -2846,9 +2835,6 @@ def test_exe_q(self):
with pytest.raises(ValueError):
dpnp.matmul(x1, x2)

# TODO: Temporary skipping the test, until Internal CI is updated with
# recent changed in dpctl regarding dpt.result_type function
@pytest.mark.skip("Temporary skipping the test")
def test_matmul_casting(self):
a1 = dpnp.arange(2 * 4, dtype=dpnp.float32).reshape(2, 4)
a2 = dpnp.arange(4 * 3).reshape(4, 3)
Expand Down
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