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Hello community,
here is the log from the commit of package python-numba for openSUSE:Factory
checked in at 2023-01-04 17:51:09
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Comparing /work/SRC/openSUSE:Factory/python-numba (Old)
and /work/SRC/openSUSE:Factory/.python-numba.new.1563 (New)
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Package is "python-numba"
Wed Jan 4 17:51:09 2023 rev:36 rq:1046630 version:0.56.4
Changes:
--------
--- /work/SRC/openSUSE:Factory/python-numba/python-numba.changes
2022-10-11 18:05:22.438067751 +0200
+++ /work/SRC/openSUSE:Factory/.python-numba.new.1563/python-numba.changes
2023-01-04 17:51:31.829802424 +0100
@@ -1,0 +2,32 @@
+Tue Jan 3 12:13:00 UTC 2023 - Ben Greiner <c...@bnavigator.de>
+
+- Split out python flavors into testing multibuilds. Depending on
+ the obs worker, the test suite can take almost an hour per
+ flavor.
+- Replace allow-numpy-1.24.patch with an updated
+ numba-pr8620-np1.24.patch to also work with still present numpy
+ 1.23 in Factory (discussed upstream in gh#numba/numba#8620)
+- Merge fix-cli-test.patch into skip-failing-tests.patch
+
+-------------------------------------------------------------------
+Mon Jan 2 21:27:24 UTC 2023 - Ben Greiner <c...@bnavigator.de>
+
+- Clean up the specfile
+ * restore the multibuild
+ * Patch allow-numpy-1.24.patch is the WIP gh#numba/numba#8620
+
+-------------------------------------------------------------------
+Sun Jan 1 11:41:11 UTC 2023 - Matej Cepl <mc...@suse.com>
+
+- Update to 0.56.4:
+ - This is a bugfix release to fix a regression in the CUDA
+ target in relation to the .view() method on CUDA device
+ arrays that is present when using NumPy version 1.23.0 or
+ later.
+ - This is a bugfix release to remove the version restriction
+ applied to the setuptools package and to fix a bug in the
+ CUDA target in relation to copying zero length device arrays
+ to zero length host arrays.
+- Add allow-numpy-1.24.patch to allow work with numpy 1.24
+
+-------------------------------------------------------------------
Old:
----
fix-cli-test.patch
numba-0.56.2.tar.gz
New:
----
numba-0.56.4.tar.gz
numba-pr8620-np1.24.patch
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Other differences:
------------------
++++++ python-numba.spec ++++++
--- /var/tmp/diff_new_pack.XWJ64l/_old 2023-01-04 17:51:32.765807941 +0100
+++ /var/tmp/diff_new_pack.XWJ64l/_new 2023-01-04 17:51:32.797808129 +0100
@@ -1,7 +1,7 @@
#
# spec file
#
-# Copyright (c) 2022 SUSE LLC
+# Copyright (c) 2023 SUSE LLC
#
# All modifications and additions to the file contributed by third parties
# remain the property of their copyright owners, unless otherwise agreed
@@ -16,35 +16,59 @@
#
-%{?!python_module:%define python_module() python3-%{**}}
%define skip_python2 1
+# Not compatible with Python 3.11 yet. If this changes, and the python311
+# flavor is active, make sure to expand the multibuild test flavors
+# https://github.com/numba/numba/issues/8304
+%define skip_python311 1
%define plainpython python
# upper bound is exclusive: min-numpy_ver <= numpy < max_numpy_ver
%define min_numpy_ver 1.18
-%define max_numpy_ver 1.24
+%define max_numpy_ver 1.25
+
%global flavor @BUILD_FLAVOR@%{nil}
-%if "%{flavor}" == "test"
-%define psuffix -test
-%bcond_without test
-%else
+%if "%{flavor}" == ""
%define psuffix %{nil}
%bcond_with test
%endif
-Name: python-numba%{psuffix}
-Version: 0.56.2
+%if "%{flavor}" == "test-py38"
+%define psuffix -test-py38
+%define skip_python39 1
+%define skip_python310 1
+%bcond_without test
+%endif
+%if "%{flavor}" == "test-py39"
+%define psuffix -test-py39
+%define skip_python38 1
+%define skip_python310 1
+%bcond_without test
+%endif
+%if "%{flavor}" == "test-py310"
+%define psuffix -test-py310
+%define skip_python38 1
+%define skip_python39 1
+%bcond_without test
+%endif
+
+Name: python-numba%{?psuffix}
+Version: 0.56.4
Release: 0
Summary: NumPy-aware optimizing compiler for Python using LLVM
License: BSD-2-Clause
URL: https://numba.pydata.org/
+# SourceRepository: https://github.com/numba/numba
Source:
https://files.pythonhosted.org/packages/source/n/numba/numba-%{version}.tar.gz
+# PATCH-FIX-UPSTREAM numba-pr8620-np1.24.patch gh#numba/numba#8620 + raising
upper bound in setup.py and numba/__init__.py
+Patch1: numba-pr8620-np1.24.patch
# PATCH-FIX-OPENSUSE skip tests failing due to OBS specifics
-Patch2: fix-cli-test.patch
Patch3: skip-failing-tests.patch
# PATCH-FIX-OPENSUSE update-tbb-backend-calls-2021.6.patch, based on
gh#numba/numba#7608
Patch4: update-tbb-backend-calls-2021.6.patch
BuildRequires: %{python_module devel >= 3.7}
BuildRequires: %{python_module numpy-devel >= %{min_numpy_ver} with
%python-numpy-devel < %{max_numpy_ver}}
+BuildRequires: %{python_module pip}
BuildRequires: %{python_module setuptools}
+BuildRequires: %{python_module wheel}
BuildRequires: fdupes
BuildRequires: gcc-c++
BuildRequires: python-rpm-macros
@@ -116,19 +140,18 @@
%build
%if !%{with test}
export CFLAGS="%{optflags} -fPIC"
-%python_build
+%pyproject_wheel
%endif
%install
%if !%{with test}
-%python_install
+%pyproject_install
%{python_expand #
%fdupes %{buildroot}%{$python_sitearch}
find %{buildroot}%{$python_sitearch} -name '*.[ch]' >
devel-files0-%{$python_bin_suffix}.files
sed 's|^%{buildroot}||' devel-files0-%{$python_bin_suffix}.files >
devel-files-%{$python_bin_suffix}.files
sed 's|^%{buildroot}|%%exclude |' devel-files0-%{$python_bin_suffix}.files >
devel-files-exclude-%{$python_bin_suffix}.files
}
-
%python_clone -a %{buildroot}%{_bindir}/numba
%python_clone -a %{buildroot}%{_bindir}/pycc
%endif
@@ -139,7 +162,7 @@
mkdir emptytestdir
pushd emptytestdir
%{python_expand # numbatests: check specific tests with `osc build -M test
--define="numbatests <testnames>"`
-%{_bindir}/numba-%{$python_bin_suffix} -s
+%{_bindir}/numba-%%{$python_bin_suffix} -s
$python -m numba.runtests -v -b --exclude-tags='long_running' -m
%{_smp_build_ncpus} -- %{?!numbatests:numba.tests}%{?numbatests}
}
popd
@@ -158,7 +181,7 @@
%python_alternative %{_bindir}/numba
%python_alternative %{_bindir}/pycc
%{python_sitearch}/numba/
-%{python_sitearch}/numba-%{version}-py*.egg-info
+%{python_sitearch}/numba-%{version}.dist-info
%files %{python_files devel} -f devel-files-%{python_bin_suffix}.files
%license LICENSE
++++++ _multibuild ++++++
--- /var/tmp/diff_new_pack.XWJ64l/_old 2023-01-04 17:51:33.097809898 +0100
+++ /var/tmp/diff_new_pack.XWJ64l/_new 2023-01-04 17:51:33.125810063 +0100
@@ -1,4 +1,6 @@
<multibuild>
- <package>test</package>
+ <package>test-py38</package>
+ <package>test-py39</package>
+ <package>test-py310</package>
</multibuild>
++++++ numba-0.56.2.tar.gz -> numba-0.56.4.tar.gz ++++++
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/numba-0.56.2/CHANGE_LOG new/numba-0.56.4/CHANGE_LOG
--- old/numba-0.56.2/CHANGE_LOG 2022-09-02 05:48:15.974872600 +0200
+++ new/numba-0.56.4/CHANGE_LOG 2022-11-03 16:41:43.800891400 +0100
@@ -1,3 +1,43 @@
+Version 0.56.4 (3 November, 2022)
+---------------------------------
+
+This is a bugfix release to fix a regression in the CUDA target in relation to
+the ``.view()`` method on CUDA device arrays that is present when using NumPy
+version 1.23.0 or later.
+
+Pull-Requests:
+
+* PR `#8537 <https://github.com/numba/numba/pull/8537>`_: Make
ol_compatible_view accessible on all targets (`gmarkall
<https://github.com/gmarkall>`_)
+* PR `#8552 <https://github.com/numba/numba/pull/8552>`_: Update version
support table for 0.56.4. (`stuartarchibald
<https://github.com/stuartarchibald>`_)
+* PR `#8553 <https://github.com/numba/numba/pull/8553>`_: Update CHANGE_LOG
for 0.56.4 (`stuartarchibald <https://github.com/stuartarchibald>`_)
+* PR `#8570 <https://github.com/numba/numba/pull/8570>`_: Release 0.56 branch:
Fix overloads with ``target="generic"`` for CUDA (`gmarkall
<https://github.com/gmarkall>`_)
+* PR `#8571 <https://github.com/numba/numba/pull/8571>`_: Additional update to
CHANGE_LOG for 0.56.4 (`stuartarchibald <https://github.com/stuartarchibald>`_)
+
+Authors:
+
+* `gmarkall <https://github.com/gmarkall>`_
+* `stuartarchibald <https://github.com/stuartarchibald>`_
+
+Version 0.56.3 (13 October, 2022)
+---------------------------------
+
+This is a bugfix release to remove the version restriction applied to the
+``setuptools`` package and to fix a bug in the CUDA target in relation to
+copying zero length device arrays to zero length host arrays.
+
+Pull-Requests:
+
+* PR `#8475 <https://github.com/numba/numba/pull/8475>`_: Remove setuptools
version pin (`gmarkall <https://github.com/gmarkall>`_)
+* PR `#8482 <https://github.com/numba/numba/pull/8482>`_: Fix #8477: Allow
copies with different strides for 0-length data (`gmarkall
<https://github.com/gmarkall>`_)
+* PR `#8486 <https://github.com/numba/numba/pull/8486>`_: Restrict the TBB
development package to supported version in Azure. (`stuartarchibald
<https://github.com/stuartarchibald>`_)
+* PR `#8503 <https://github.com/numba/numba/pull/8503>`_: Update version
support table for 0.56.3 (`stuartarchibald
<https://github.com/stuartarchibald>`_)
+* PR `#8504 <https://github.com/numba/numba/pull/8504>`_: Update CHANGE_LOG
for 0.56.3 (`stuartarchibald <https://github.com/stuartarchibald>`_)
+
+Authors:
+
+* `gmarkall <https://github.com/gmarkall>`_
+* `stuartarchibald <https://github.com/stuartarchibald>`_
+
Version 0.56.2 (1 September, 2022)
----------------------------------
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/numba-0.56.2/PKG-INFO new/numba-0.56.4/PKG-INFO
--- old/numba-0.56.2/PKG-INFO 2022-09-02 05:48:23.630758300 +0200
+++ new/numba-0.56.4/PKG-INFO 2022-11-03 16:41:52.920761300 +0100
@@ -1,6 +1,6 @@
Metadata-Version: 2.1
Name: numba
-Version: 0.56.2
+Version: 0.56.4
Summary: compiling Python code using LLVM
Home-page: https://numba.pydata.org
License: BSD
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/numba-0.56.2/docs/source/user/installing.rst
new/numba-0.56.4/docs/source/user/installing.rst
--- old/numba-0.56.2/docs/source/user/installing.rst 2022-09-02
05:48:15.978872500 +0200
+++ new/numba-0.56.4/docs/source/user/installing.rst 2022-11-03
16:41:43.808891300 +0100
@@ -194,14 +194,14 @@
* Required build time:
- * ``setuptools<60``
+ * ``setuptools``
* ``numpy``
* ``llvmlite``
* Compiler toolchain mentioned above
* Required run time:
- * ``setuptools<60``
+ * ``setuptools``
* ``numpy``
* ``llvmlite``
@@ -278,6 +278,10 @@
+===========+==============+===========================+============================+==============================+===================+=============================+
| 0.57.x | TBC | 3.8.x <= version < 3.12 | 1.19 <= version <
1.24 | 0.40.x | 11.x | 2021.x
|
+-----------+--------------+---------------------------+----------------------------+------------------------------+-------------------+-----------------------------+
+| 0.56.4 | 2022-11-03 | 3.7.x <= version < 3.11 | 1.18 <= version <
1.24 | 0.39.x | 11.x | 2021.x
|
++-----------+--------------+---------------------------+----------------------------+------------------------------+-------------------+-----------------------------+
+| 0.56.3 | 2022-10-13 | 3.7.x <= version < 3.11 | 1.18 <= version <
1.24 | 0.39.x | 11.x | 2021.x
|
++-----------+--------------+---------------------------+----------------------------+------------------------------+-------------------+-----------------------------+
| 0.56.2 | 2022-09-01 | 3.7.x <= version < 3.11 | 1.18 <= version <
1.24 | 0.39.x | 11.x | 2021.x
|
+-----------+--------------+---------------------------+----------------------------+------------------------------+-------------------+-----------------------------+
| 0.56.0 | 2022-07-25 | 3.7.x <= version < 3.11 | 1.18 <= version <
1.23 | 0.39.x | 11.x | 2021.x
|
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/numba-0.56.2/numba/_version.py
new/numba-0.56.4/numba/_version.py
--- old/numba-0.56.2/numba/_version.py 2022-09-02 05:48:23.630758300 +0200
+++ new/numba-0.56.4/numba/_version.py 2022-11-03 16:41:52.920761300 +0100
@@ -4,8 +4,8 @@
# unpacked source archive. Distribution tarballs contain a pre-generated copy
# of this file.
-version_version = '0.56.2'
-version_full = 'd6731f6d22f6695ee7abc305f81f81115639e2a4'
+version_version = '0.56.4'
+version_full = '288a38bbd5a15418a211bf067878dfdf3c139509'
def get_versions(default={}, verbose=False):
return {'version': version_version, 'full': version_full}
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/numba-0.56.2/numba/cuda/compiler.py
new/numba-0.56.4/numba/cuda/compiler.py
--- old/numba-0.56.2/numba/cuda/compiler.py 2022-09-02 05:48:15.978872500
+0200
+++ new/numba-0.56.4/numba/cuda/compiler.py 2022-11-03 16:41:43.816891200
+0100
@@ -207,14 +207,16 @@
flags.nvvm_options = nvvm_options
# Run compilation pipeline
- cres = compiler.compile_extra(typingctx=typingctx,
- targetctx=targetctx,
- func=pyfunc,
- args=args,
- return_type=return_type,
- flags=flags,
- locals={},
- pipeline_class=CUDACompiler)
+ from numba.core.target_extension import target_override
+ with target_override('cuda'):
+ cres = compiler.compile_extra(typingctx=typingctx,
+ targetctx=targetctx,
+ func=pyfunc,
+ args=args,
+ return_type=return_type,
+ flags=flags,
+ locals={},
+ pipeline_class=CUDACompiler)
library = cres.library
library.finalize()
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/numba-0.56.2/numba/cuda/cudadrv/devicearray.py
new/numba-0.56.4/numba/cuda/cudadrv/devicearray.py
--- old/numba-0.56.2/numba/cuda/cudadrv/devicearray.py 2022-09-02
05:48:15.882874000 +0200
+++ new/numba-0.56.4/numba/cuda/cudadrv/devicearray.py 2022-11-03
16:41:43.660893400 +0100
@@ -895,6 +895,8 @@
if ary1sq.shape != ary2sq.shape:
raise ValueError('incompatible shape: %s vs. %s' %
(ary1.shape, ary2.shape))
- if ary1sq.strides != ary2sq.strides:
+ # We check strides only if the size is nonzero, because strides are
+ # irrelevant (and can differ) for zero-length copies.
+ if ary1.size and ary1sq.strides != ary2sq.strides:
raise ValueError('incompatible strides: %s vs. %s' %
(ary1.strides, ary2.strides))
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore'
old/numba-0.56.2/numba/cuda/tests/cudadrv/test_cuda_ndarray.py
new/numba-0.56.4/numba/cuda/tests/cudadrv/test_cuda_ndarray.py
--- old/numba-0.56.2/numba/cuda/tests/cudadrv/test_cuda_ndarray.py
2022-09-02 05:48:15.886874000 +0200
+++ new/numba-0.56.4/numba/cuda/tests/cudadrv/test_cuda_ndarray.py
2022-11-03 16:41:43.664893400 +0100
@@ -420,6 +420,41 @@
got = np.asarray(dary)
self.assertEqual(got.dtype, dary.dtype)
+ @skip_on_cudasim('DeviceNDArray class not present in simulator')
+ def test_issue_8477(self):
+ # Ensure that we can copy a zero-length device array to a zero-length
+ # host array when the strides of the device and host arrays differ -
+ # this should be possible because the strides are irrelevant when the
+ # length is zero. For more info see
+ # https://github.com/numba/numba/issues/8477.
+
+ # Create a device array with shape (0,) and strides (8,)
+ dev_array = devicearray.DeviceNDArray(shape=(0,), strides=(8,),
+ dtype=np.int8)
+
+ # Create a host array with shape (0,) and strides (0,)
+ host_array = np.ndarray(shape=(0,), strides=(0,), dtype=np.int8)
+
+ # Sanity check for this test - ensure our destination has the strides
+ # we expect, because strides can be ignored in some cases by the
+ # ndarray constructor - checking here ensures that we haven't failed to
+ # account for unexpected behaviour across different versions of NumPy
+ self.assertEqual(host_array.strides, (0,))
+
+ # Ensure that the copy succeeds in both directions
+ dev_array.copy_to_host(host_array)
+ dev_array.copy_to_device(host_array)
+
+ # Ensure that a device-to-device copy also succeeds when the strides
+ # differ - one way of doing this is to copy the host array across and
+ # use that for copies in both directions.
+ dev_array_from_host = cuda.to_device(host_array)
+ self.assertEqual(dev_array_from_host.shape, (0,))
+ self.assertEqual(dev_array_from_host.strides, (0,))
+
+ dev_array.copy_to_device(dev_array_from_host)
+ dev_array_from_host.copy_to_device(dev_array)
+
class TestRecarray(CUDATestCase):
def test_recarray(self):
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/numba-0.56.2/numba/np/arrayobj.py
new/numba-0.56.4/numba/np/arrayobj.py
--- old/numba-0.56.2/numba/np/arrayobj.py 2022-09-02 05:48:15.982872500
+0200
+++ new/numba-0.56.4/numba/np/arrayobj.py 2022-11-03 16:41:43.820891100
+0100
@@ -2420,7 +2420,7 @@
pass
-@overload(_compatible_view)
+@overload(_compatible_view, target='generic')
def ol_compatible_view(a, dtype):
"""Determines if the array and dtype are compatible for forming a view."""
# NOTE: NumPy 1.23+ uses this check.
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/numba-0.56.2/numba/testing/main.py
new/numba-0.56.4/numba/testing/main.py
--- old/numba-0.56.2/numba/testing/main.py 2022-09-02 05:48:15.906873700
+0200
+++ new/numba-0.56.4/numba/testing/main.py 2022-11-03 16:41:43.824891000
+0100
@@ -207,7 +207,8 @@
parser.add_argument('-g', '--gitdiff', dest='gitdiff',
type=git_diff_str,
default=False, nargs='?',
help=('Run tests from changes made against '
- 'origin/main as identified by `git diff`. '
+ 'origin/release0.56 as identified by'
+ '`git diff`. '
'If set to "ancestor", the diff compares '
'against the common ancestor.'))
return parser
@@ -399,9 +400,9 @@
path = os.path.join('numba', 'tests')
if use_common_ancestor:
print(f"Git diff by common ancestor")
- target = 'origin/main...HEAD'
+ target = 'origin/release0.56...HEAD'
else:
- target = 'origin/main..HEAD'
+ target = 'origin/release0.56..HEAD'
gdiff_paths = repo.git.diff(target, path, name_only=True).split()
# normalise the paths as they are unix style from repo.git.diff
gdiff_paths = [os.path.normpath(x) for x in gdiff_paths]
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/numba-0.56.2/setup.py new/numba-0.56.4/setup.py
--- old/numba-0.56.2/setup.py 2022-09-02 05:48:15.990872400 +0200
+++ new/numba-0.56.4/setup.py 2022-11-03 16:41:43.832891000 +0100
@@ -375,7 +375,7 @@
install_requires = [
'llvmlite >={},<{}'.format(min_llvmlite_version, max_llvmlite_version),
'numpy >={},<{}'.format(min_numpy_run_version, max_numpy_run_version),
- 'setuptools<60',
+ 'setuptools',
'importlib_metadata; python_version < "3.9"',
]
++++++ numba-pr8620-np1.24.patch ++++++
Index: numba-0.56.4/numba/cuda/tests/cudapy/test_intrinsics.py
===================================================================
--- numba-0.56.4.orig/numba/cuda/tests/cudapy/test_intrinsics.py
+++ numba-0.56.4/numba/cuda/tests/cudapy/test_intrinsics.py
@@ -619,7 +619,7 @@ class TestCudaIntrinsic(CUDATestCase):
arg2 = np.float16(4.)
compiled[1, 1](ary, arg1, arg2)
np.testing.assert_allclose(ary[0], arg2)
- arg1 = np.float(5.)
+ arg1 = np.float16(5.)
compiled[1, 1](ary, arg1, arg2)
np.testing.assert_allclose(ary[0], arg1)
@@ -631,7 +631,7 @@ class TestCudaIntrinsic(CUDATestCase):
arg2 = np.float16(4.)
compiled[1, 1](ary, arg1, arg2)
np.testing.assert_allclose(ary[0], arg1)
- arg1 = np.float(5.)
+ arg1 = np.float16(5.)
compiled[1, 1](ary, arg1, arg2)
np.testing.assert_allclose(ary[0], arg2)
Index: numba-0.56.4/numba/np/arraymath.py
===================================================================
--- numba-0.56.4.orig/numba/np/arraymath.py
+++ numba-0.56.4/numba/np/arraymath.py
@@ -4177,6 +4177,10 @@ iinfo = namedtuple('iinfo', _iinfo_suppo
# This module is imported under the compiler lock which should deal with the
# lack of thread safety in the warning filter.
def _gen_np_machar():
+ # NumPy 1.24 removed np.MachAr
+ if numpy_version >= (1, 24):
+ return
+
np122plus = numpy_version >= (1, 22)
w = None
with warnings.catch_warnings(record=True) as w:
Index: numba-0.56.4/numba/np/ufunc/_internal.c
===================================================================
--- numba-0.56.4.orig/numba/np/ufunc/_internal.c
+++ numba-0.56.4/numba/np/ufunc/_internal.c
@@ -285,9 +285,7 @@ static struct _ufunc_dispatch {
PyCFunctionWithKeywords ufunc_accumulate;
PyCFunctionWithKeywords ufunc_reduceat;
PyCFunctionWithKeywords ufunc_outer;
-#if NPY_API_VERSION >= 0x00000008
PyCFunction ufunc_at;
-#endif
} ufunc_dispatch;
static int
@@ -303,10 +301,8 @@ init_ufunc_dispatch(int *numpy_uses_fast
if (strncmp(crnt_name, "accumulate", 11) == 0) {
ufunc_dispatch.ufunc_accumulate =
(PyCFunctionWithKeywords)crnt->ml_meth;
-#if NPY_API_VERSION >= 0x00000008
} else if (strncmp(crnt_name, "at", 3) == 0) {
ufunc_dispatch.ufunc_at = crnt->ml_meth;
-#endif
} else {
result = -1;
}
@@ -326,10 +322,15 @@ init_ufunc_dispatch(int *numpy_uses_fast
} else if (strncmp(crnt_name, "reduceat", 9) == 0) {
ufunc_dispatch.ufunc_reduceat =
(PyCFunctionWithKeywords)crnt->ml_meth;
+ } else if (strncmp(crnt_name, "resolve_dtypes", 15) == 0) {
+ /* Ignored */
} else {
result = -1;
}
break;
+ case '_':
+ // We ignore private methods
+ break;
default:
result = -1; /* Unknown method */
}
@@ -341,6 +342,8 @@ init_ufunc_dispatch(int *numpy_uses_fast
*numpy_uses_fastcall = crnt->ml_flags & METH_FASTCALL;
}
else if (*numpy_uses_fastcall != (crnt->ml_flags & METH_FASTCALL))
{
+ PyErr_SetString(PyExc_RuntimeError,
+ "ufunc.at() flags do not match numpy_uses_fastcall");
return -1;
}
}
@@ -351,11 +354,13 @@ init_ufunc_dispatch(int *numpy_uses_fast
&& (ufunc_dispatch.ufunc_accumulate != NULL)
&& (ufunc_dispatch.ufunc_reduceat != NULL)
&& (ufunc_dispatch.ufunc_outer != NULL)
-#if NPY_API_VERSION >= 0x00000008
&& (ufunc_dispatch.ufunc_at != NULL)
-#endif
);
+ } else {
+ char const * const fmt = "Unexpected ufunc method %s()";
+ PyErr_Format(PyExc_RuntimeError, fmt, crnt_name);
}
+
return result;
}
@@ -425,13 +430,11 @@ dufunc_outer_fast(PyDUFuncObject * self,
}
-#if NPY_API_VERSION >= 0x00000008
static PyObject *
dufunc_at(PyDUFuncObject * self, PyObject * args)
{
return ufunc_dispatch.ufunc_at((PyObject*)self->ufunc, args);
}
-#endif
static PyObject *
dufunc__compile_for_args(PyDUFuncObject * self, PyObject * args,
@@ -609,11 +612,9 @@ static struct PyMethodDef dufunc_methods
{"outer",
(PyCFunction)dufunc_outer,
METH_VARARGS | METH_KEYWORDS, NULL},
-#if NPY_API_VERSION >= 0x00000008
{"at",
(PyCFunction)dufunc_at,
METH_VARARGS, NULL},
-#endif
{"_compile_for_args",
(PyCFunction)dufunc__compile_for_args,
METH_VARARGS | METH_KEYWORDS,
@@ -643,11 +644,9 @@ static struct PyMethodDef dufunc_methods
{"outer",
(PyCFunction)dufunc_outer_fast,
METH_FASTCALL | METH_KEYWORDS, NULL},
-#if NPY_API_VERSION >= 0x00000008
{"at",
(PyCFunction)dufunc_at,
METH_VARARGS, NULL},
-#endif
{"_compile_for_args",
(PyCFunction)dufunc__compile_for_args,
METH_VARARGS | METH_KEYWORDS,
@@ -791,9 +790,7 @@ MOD_INIT(_internal)
if (PyModule_AddIntMacro(m, PyUFunc_One)
|| PyModule_AddIntMacro(m, PyUFunc_Zero)
|| PyModule_AddIntMacro(m, PyUFunc_None)
-#if NPY_API_VERSION >= 0x00000007
|| PyModule_AddIntMacro(m, PyUFunc_ReorderableNone)
-#endif
)
return MOD_ERROR_VAL;
Index: numba-0.56.4/numba/stencils/stencilparfor.py
===================================================================
--- numba-0.56.4.orig/numba/stencils/stencilparfor.py
+++ numba-0.56.4/numba/stencils/stencilparfor.py
@@ -21,6 +21,7 @@ from numba.core.ir_utils import (get_cal
find_callname, require, find_const, GuardException)
from numba.core.errors import NumbaValueError
from numba.core.utils import OPERATORS_TO_BUILTINS
+from numba.np import numpy_support
def _compute_last_ind(dim_size, index_const):
@@ -264,7 +265,11 @@ class StencilPass(object):
dtype_g_np_assign = ir.Assign(dtype_g_np, dtype_g_np_var, loc)
init_block.body.append(dtype_g_np_assign)
- dtype_np_attr_call = ir.Expr.getattr(dtype_g_np_var,
return_type.dtype.name, loc)
+ return_type_name = numpy_support.as_dtype(
+ return_type.dtype).type.__name__
+ if return_type_name == 'bool':
+ return_type_name = 'bool_'
+ dtype_np_attr_call = ir.Expr.getattr(dtype_g_np_var,
return_type_name, loc)
dtype_attr_var = ir.Var(scope, mk_unique_var("$np_attr_attr"), loc)
self.typemap[dtype_attr_var.name] =
types.functions.NumberClass(return_type.dtype)
dtype_attr_assign = ir.Assign(dtype_np_attr_call, dtype_attr_var,
loc)
Index: numba-0.56.4/numba/tests/test_array_methods.py
===================================================================
--- numba-0.56.4.orig/numba/tests/test_array_methods.py
+++ numba-0.56.4/numba/tests/test_array_methods.py
@@ -1193,7 +1193,7 @@ class TestArrayMethods(MemoryLeakMixin,
pyfunc = array_sum_dtype_kws
cfunc = jit(nopython=True)(pyfunc)
all_dtypes = [np.float64, np.float32, np.int64, np.int32, np.uint32,
- np.uint64, np.complex64, np.complex128, TIMEDELTA_M]
+ np.uint64, np.complex64, np.complex128]
all_test_arrays = [
[np.ones((7, 6, 5, 4, 3), arr_dtype),
np.ones(1, arr_dtype),
@@ -1207,8 +1207,7 @@ class TestArrayMethods(MemoryLeakMixin,
np.dtype('uint32'): [np.float64, np.int64, np.float32],
np.dtype('uint64'): [np.float64, np.int64],
np.dtype('complex64'): [np.complex64, np.complex128],
- np.dtype('complex128'): [np.complex128],
- np.dtype(TIMEDELTA_M): [np.dtype(TIMEDELTA_M)]}
+ np.dtype('complex128'): [np.complex128]}
for arr_list in all_test_arrays:
for arr in arr_list:
@@ -1216,15 +1215,15 @@ class TestArrayMethods(MemoryLeakMixin,
subtest_str = ("Testing np.sum with {} input and {} output"
.format(arr.dtype, out_dtype))
with self.subTest(subtest_str):
- self.assertPreciseEqual(pyfunc(arr, dtype=out_dtype),
- cfunc(arr, dtype=out_dtype))
+ self.assertPreciseEqual(pyfunc(arr,
dtype=out_dtype),
+ cfunc(arr,
dtype=out_dtype))
def test_sum_axis_dtype_kws(self):
""" test sum with axis and dtype parameters over a whole range of
dtypes """
pyfunc = array_sum_axis_dtype_kws
cfunc = jit(nopython=True)(pyfunc)
all_dtypes = [np.float64, np.float32, np.int64, np.int32, np.uint32,
- np.uint64, np.complex64, np.complex128, TIMEDELTA_M]
+ np.uint64, np.complex64, np.complex128]
all_test_arrays = [
[np.ones((7, 6, 5, 4, 3), arr_dtype),
np.ones(1, arr_dtype),
@@ -1238,9 +1237,7 @@ class TestArrayMethods(MemoryLeakMixin,
np.dtype('uint32'): [np.float64, np.int64, np.float32],
np.dtype('uint64'): [np.float64, np.uint64],
np.dtype('complex64'): [np.complex64, np.complex128],
- np.dtype('complex128'): [np.complex128],
- np.dtype(TIMEDELTA_M): [np.dtype(TIMEDELTA_M)],
- np.dtype(TIMEDELTA_Y): [np.dtype(TIMEDELTA_Y)]}
+ np.dtype('complex128'): [np.complex128]}
for arr_list in all_test_arrays:
for arr in arr_list:
Index: numba-0.56.4/numba/tests/test_comprehension.py
===================================================================
--- numba-0.56.4.orig/numba/tests/test_comprehension.py
+++ numba-0.56.4/numba/tests/test_comprehension.py
@@ -11,6 +11,7 @@ from numba import jit, typed
from numba.core import types, utils
from numba.core.errors import TypingError, LoweringError
from numba.core.types.functions import _header_lead
+from numba.np.numpy_support import numpy_version
from numba.tests.support import tag, _32bit, captured_stdout
@@ -360,6 +361,7 @@ class TestArrayComprehension(unittest.Te
self.check(comp_nest_with_array_conditional, 5,
assert_allocate_list=True)
+ @unittest.skipUnless(numpy_version < (1, 24), 'Removed in NumPy 1.24')
def test_comp_nest_with_dependency(self):
def comp_nest_with_dependency(n):
l = np.array([[i * j for j in range(i+1)] for i in range(n)])
Index: numba-0.56.4/numba/tests/test_linalg.py
===================================================================
--- numba-0.56.4.orig/numba/tests/test_linalg.py
+++ numba-0.56.4/numba/tests/test_linalg.py
@@ -1122,6 +1122,32 @@ class TestLinalgSvd(TestLinalgBase):
Tests for np.linalg.svd.
"""
+ # This checks that A ~= U*S*V**H, i.e. SV decomposition ties out. This is
+ # required as NumPy uses only double precision LAPACK routines and
+ # computation of SVD is numerically sensitive. Numba uses type-specific
+ # routines and therefore sometimes comes out with a different answer to
+ # NumPy (orthonormal bases are not unique, etc.).
+
+ def check_reconstruction(self, a, got, expected):
+ u, sv, vt = got
+
+ # Check they are dimensionally correct
+ for k in range(len(expected)):
+ self.assertEqual(got[k].shape, expected[k].shape)
+
+ # Columns in u and rows in vt dictates the working size of s
+ s = np.zeros((u.shape[1], vt.shape[0]))
+ np.fill_diagonal(s, sv)
+
+ rec = np.dot(np.dot(u, s), vt)
+ resolution = np.finfo(a.dtype).resolution
+ np.testing.assert_allclose(
+ a,
+ rec,
+ rtol=10 * resolution,
+ atol=100 * resolution # zeros tend to be fuzzy
+ )
+
@needs_lapack
def test_linalg_svd(self):
"""
@@ -1150,34 +1176,8 @@ class TestLinalgSvd(TestLinalgBase):
# plain match failed, test by reconstruction
use_reconstruction = True
- # if plain match fails then reconstruction is used.
- # this checks that A ~= U*S*V**H
- # i.e. SV decomposition ties out
- # this is required as numpy uses only double precision lapack
- # routines and computation of svd is numerically
- # sensitive, numba using the type specific routines therefore
- # sometimes comes out with a different answer (orthonormal bases
- # are not unique etc.).
if use_reconstruction:
- u, sv, vt = got
-
- # check they are dimensionally correct
- for k in range(len(expected)):
- self.assertEqual(got[k].shape, expected[k].shape)
-
- # regardless of full_matrices cols in u and rows in vt
- # dictates the working size of s
- s = np.zeros((u.shape[1], vt.shape[0]))
- np.fill_diagonal(s, sv)
-
- rec = np.dot(np.dot(u, s), vt)
- resolution = np.finfo(a.dtype).resolution
- np.testing.assert_allclose(
- a,
- rec,
- rtol=10 * resolution,
- atol=100 * resolution # zeros tend to be fuzzy
- )
+ self.check_reconstruction(a, got, expected)
# Ensure proper resource management
with self.assertNoNRTLeak():
@@ -1238,8 +1238,11 @@ class TestLinalgSvd(TestLinalgBase):
got = func(X, False)
np.testing.assert_allclose(X, X_orig)
- for e_a, g_a in zip(expected, got):
- np.testing.assert_allclose(e_a, g_a)
+ try:
+ for e_a, g_a in zip(expected, got):
+ np.testing.assert_allclose(e_a, g_a)
+ except AssertionError:
+ self.check_reconstruction(X, got, expected)
class TestLinalgQr(TestLinalgBase):
Index: numba-0.56.4/numba/tests/test_mathlib.py
===================================================================
--- numba-0.56.4.orig/numba/tests/test_mathlib.py
+++ numba-0.56.4/numba/tests/test_mathlib.py
@@ -516,7 +516,7 @@ class TestMathLib(TestCase):
with warnings.catch_warnings():
warnings.simplefilter("error", RuntimeWarning)
self.assertRaisesRegexp(RuntimeWarning,
- 'overflow encountered in .*_scalars',
+ 'overflow encountered in .*scalar',
naive_hypot, val, val)
def test_hypot_npm(self):
Index: numba-0.56.4/numba/tests/test_np_functions.py
===================================================================
--- numba-0.56.4.orig/numba/tests/test_np_functions.py
+++ numba-0.56.4/numba/tests/test_np_functions.py
@@ -932,11 +932,11 @@ class TestNPFunctions(MemoryLeakMixin, T
yield np.inf, None
yield np.PINF, None
yield np.asarray([-np.inf, 0., np.inf]), None
- yield np.NINF, np.zeros(1, dtype=np.bool)
- yield np.inf, np.zeros(1, dtype=np.bool)
- yield np.PINF, np.zeros(1, dtype=np.bool)
+ yield np.NINF, np.zeros(1, dtype=np.bool_)
+ yield np.inf, np.zeros(1, dtype=np.bool_)
+ yield np.PINF, np.zeros(1, dtype=np.bool_)
yield np.NINF, np.empty(12)
- yield np.asarray([-np.inf, 0., np.inf]), np.zeros(3, dtype=np.bool)
+ yield np.asarray([-np.inf, 0., np.inf]), np.zeros(3,
dtype=np.bool_)
pyfuncs = [isneginf, isposinf]
for pyfunc in pyfuncs:
@@ -4775,6 +4775,7 @@ def foo():
eval(compile(funcstr, '<string>', 'exec'))
return locals()['foo']
+ @unittest.skipIf(numpy_version >= (1, 24), "NumPy < 1.24 required")
def test_MachAr(self):
attrs = ('ibeta', 'it', 'machep', 'eps', 'negep', 'epsneg', 'iexp',
'minexp', 'xmin', 'maxexp', 'xmax', 'irnd', 'ngrd',
@@ -4817,7 +4818,8 @@ def foo():
cfunc = jit(nopython=True)(iinfo)
cfunc(np.float64(7))
- @unittest.skipUnless(numpy_version >= (1, 22), "Needs NumPy >= 1.22")
+ @unittest.skipUnless((1, 22) <= numpy_version < (1, 24),
+ "Needs NumPy >= 1.22, < 1.24")
@TestCase.run_test_in_subprocess
def test_np_MachAr_deprecation_np122(self):
# Tests that Numba is replaying the NumPy 1.22 deprecation warning
Index: numba-0.56.4/setup.py
===================================================================
--- numba-0.56.4.orig/setup.py
+++ numba-0.56.4/setup.py
@@ -23,7 +23,7 @@ min_python_version = "3.7"
max_python_version = "3.11" # exclusive
min_numpy_build_version = "1.11"
min_numpy_run_version = "1.18"
-max_numpy_run_version = "1.24"
+max_numpy_run_version = "1.25" # exclusive
min_llvmlite_version = "0.39.0dev0"
max_llvmlite_version = "0.40"
Index: numba-0.56.4/numba/__init__.py
===================================================================
--- numba-0.56.4.orig/numba/__init__.py
+++ numba-0.56.4/numba/__init__.py
@@ -142,8 +142,8 @@ def _ensure_critical_deps():
if numpy_version < (1, 18):
raise ImportError("Numba needs NumPy 1.18 or greater")
- elif numpy_version > (1, 23):
- raise ImportError("Numba needs NumPy 1.23 or less")
+ elif numpy_version > (1, 24):
+ raise ImportError("Numba needs NumPy 1.24 or less")
try:
import scipy
++++++ skip-failing-tests.patch ++++++
--- /var/tmp/diff_new_pack.XWJ64l/_old 2023-01-04 17:51:34.229816570 +0100
+++ /var/tmp/diff_new_pack.XWJ64l/_new 2023-01-04 17:51:34.265816782 +0100
@@ -1,8 +1,11 @@
-Index: numba-0.54.0/numba/tests/test_parfors.py
-===================================================================
---- numba-0.54.0.orig/numba/tests/test_parfors.py
-+++ numba-0.54.0/numba/tests/test_parfors.py
-@@ -1146,6 +1146,7 @@ class TestParforNumPy(TestParforsBase):
+---
+ numba/tests/test_parfors.py | 5 +++--
+ numba/tests/test_parfors_passes.py | 1 +
+ 2 files changed, 4 insertions(+), 2 deletions(-)
+
+--- a/numba/tests/test_parfors.py
++++ b/numba/tests/test_parfors.py
+@@ -1174,6 +1174,7 @@ class TestParforNumPy(TestParforsBase):
self.check_variants(test_impl2, data_gen)
self.count_parfors_variants(test_impl2, data_gen)
@@ -10,7 +13,7 @@
def test_ndarray_fill(self):
def test_impl(x):
x.fill(7.0)
-@@ -3890,7 +3891,7 @@ class TestParforsVectorizer(TestPrangeBa
+@@ -4396,7 +4397,7 @@ class TestParforsVectorizer(TestPrangeBa
# to check vsqrtpd operates on zmm
match_vsqrtpd_on_zmm = re.compile('\n\s+vsqrtpd\s+.*zmm.*\n')
@@ -19,7 +22,7 @@
def test_vectorizer_fastmath_asm(self):
""" This checks that if fastmath is set and the underlying hardware
is suitable, and the function supplied is amenable to fastmath based
-@@ -3933,7 +3934,7 @@ class TestParforsVectorizer(TestPrangeBa
+@@ -4439,7 +4440,7 @@ class TestParforsVectorizer(TestPrangeBa
# check no zmm addressing is present
self.assertTrue('zmm' not in v)
@@ -28,10 +31,8 @@
def test_unsigned_refusal_to_vectorize(self):
""" This checks that if fastmath is set and the underlying hardware
is suitable, and the function supplied is amenable to fastmath based
-Index: numba-0.54.0/numba/tests/test_parfors_passes.py
-===================================================================
---- numba-0.54.0.orig/numba/tests/test_parfors_passes.py
-+++ numba-0.54.0/numba/tests/test_parfors_passes.py
+--- a/numba/tests/test_parfors_passes.py
++++ b/numba/tests/test_parfors_passes.py
@@ -516,6 +516,7 @@ class TestConvertLoopPass(BaseTest):
str(raises.exception),
)
@@ -40,4 +41,16 @@
def test_init_prange(self):
def test_impl():
n = 20
+Index: numba-0.56.2/numba/tests/test_cli.py
+===================================================================
+--- numba-0.56.2.orig/numba/tests/test_cli.py
++++ numba-0.56.2/numba/tests/test_cli.py
+@@ -264,6 +264,7 @@ class TestGDBCLIInfoBrokenGdbs(TestCase)
+ self.assertIn("No such file or directory", stdout)
+ self.assertIn(path, stdout)
+
++ @unittest.skip("Fails on type check in OBS")
+ def test_nonsense_gdb_binary(self):
+ # Tests that a nonsense binary specified as gdb it picked up ok
+ env = os.environ.copy()
++++++ update-tbb-backend-calls-2021.6.patch ++++++
--- /var/tmp/diff_new_pack.XWJ64l/_old 2023-01-04 17:51:34.405817608 +0100
+++ /var/tmp/diff_new_pack.XWJ64l/_new 2023-01-04 17:51:34.441817820 +0100
@@ -1,7 +1,9 @@
-Index: numba-0.56.2/numba/np/ufunc/tbbpool.cpp
-===================================================================
---- numba-0.56.2.orig/numba/np/ufunc/tbbpool.cpp
-+++ numba-0.56.2/numba/np/ufunc/tbbpool.cpp
+---
+ numba/np/ufunc/tbbpool.cpp | 29 ++++++++++++++++++++++++-----
+ 1 file changed, 24 insertions(+), 5 deletions(-)
+
+--- a/numba/np/ufunc/tbbpool.cpp
++++ b/numba/np/ufunc/tbbpool.cpp
@@ -12,6 +12,7 @@ Implement parallel vectorize workqueue o
#undef _XOPEN_SOURCE
#endif
