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update fft tests #2502

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Merged
merged 3 commits into from
Jun 27, 2025
Merged

update fft tests #2502

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684c457
update fft tests
vtavana Jun 25, 2025
9760b05
Merge branch 'master' into fix-fft
antonwolfy Jun 26, 2025
e3418f4
change tolerance for irfft test
vtavana Jun 26, 2025
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34 changes: 23 additions & 11 deletions dpnp/tests/test_fft.py
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Original file line number Diff line number Diff line change
Expand Up @@ -563,9 +563,13 @@ def test_basic(self, dtype, n, norm):

result = dpnp.fft.hfft(ia, n=n, norm=norm)
expected = numpy.fft.hfft(a, n=n, norm=norm)
# check_only_type_kind=True since NumPy always returns float64
# but dpnp return float32 if input is float32
assert_dtype_allclose(result, expected, check_only_type_kind=True)
# TODO: change to the commented line when mkl_fft-2.0.0 is released
# and being used with Intel NumPy >= 2.0.0
flag = True
# flag = True if numpy_version() < "2.0.0" else False
assert_dtype_allclose(
result, expected, factor=24, check_only_type_kind=flag
)

@pytest.mark.parametrize(
"dtype", get_all_dtypes(no_none=True, no_complex=True)
Expand All @@ -579,7 +583,7 @@ def test_inverse(self, dtype, n, norm):
result = dpnp.fft.ihfft(ia, n=n, norm=norm)
expected = numpy.fft.ihfft(a, n=n, norm=norm)
flag = True if numpy_version() < "2.0.0" else False
assert_dtype_allclose(result, expected, check_only_type_kind=True)
assert_dtype_allclose(result, expected, check_only_type_kind=flag)

def test_error(self):
a = dpnp.ones(11)
Expand All @@ -600,14 +604,18 @@ class TestIrfft:
@pytest.mark.parametrize("n", [None, 5, 18])
@pytest.mark.parametrize("norm", [None, "backward", "forward", "ortho"])
def test_basic(self, dtype, n, norm):
a = generate_random_numpy_array(11)
a = generate_random_numpy_array(11, dtype=dtype)
ia = dpnp.array(a)

result = dpnp.fft.irfft(ia, n=n, norm=norm)
expected = numpy.fft.irfft(a, n=n, norm=norm)
# check_only_type_kind=True since NumPy always returns float64
# but dpnp return float32 if input is float32
assert_dtype_allclose(result, expected, check_only_type_kind=True)
# TODO: change to the commented line when mkl_fft-2.0.0 is released
# and being used with Intel NumPy >= 2.0.0
flag = True
# flag = True if numpy_version() < "2.0.0" else False
assert_dtype_allclose(
result, expected, factor=24, check_only_type_kind=flag
)

@pytest.mark.parametrize("dtype", get_complex_dtypes())
@pytest.mark.parametrize("n", [None, 5, 8])
Expand Down Expand Up @@ -771,8 +779,11 @@ def test_float16(self):

expected = numpy.fft.rfft(a)
result = dpnp.fft.rfft(ia)
# check_only_type_kind=True since Intel NumPy returns complex128
assert_dtype_allclose(result, expected, check_only_type_kind=True)
# TODO: change to the commented line when mkl_fft-2.0.0 is released
# and being used with Intel NumPy >= 2.0.0
flag = True
# flag = True if numpy_version() < "2.0.0" else False
assert_dtype_allclose(result, expected, check_only_type_kind=flag)

@testing.with_requires("numpy>=2.0.0")
@pytest.mark.parametrize("xp", [numpy, dpnp])
Expand Down Expand Up @@ -954,7 +965,8 @@ def test_1d_array(self):

result = dpnp.fft.irfftn(ia)
expected = numpy.fft.irfftn(a)
# TODO: change to the commented line when mkl_fft-gh-180 is merged
# TODO: change to the commented line when mkl_fft-2.0.0 is released
# and being used with Intel NumPy >= 2.0.0
flag = True
# flag = True if numpy_version() < "2.0.0" else False
assert_dtype_allclose(result, expected, check_only_type_kind=flag)
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