python-numba/skip-failing-tests.patch

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---
numba/tests/test_parfors.py | 5 +++--
numba/tests/test_parfors_passes.py | 1 +
2 files changed, 4 insertions(+), 2 deletions(-)
Index: numba-0.59.1/numba/tests/test_parfors.py
===================================================================
--- numba-0.59.1.orig/numba/tests/test_parfors.py
+++ numba-0.59.1/numba/tests/test_parfors.py
@@ -1199,6 +1199,7 @@ class TestParforNumPy(TestParforsBase):
self.check_variants(test_impl2, data_gen)
self.count_parfors_variants(test_impl2, data_gen)
+ @unittest.skip("Fails on type check in OBS")
def test_ndarray_fill(self):
def test_impl(x):
x.fill(7.0)
@@ -4659,7 +4660,7 @@ class TestParforsVectorizer(TestPrangeBa
return asm
Accepting request 798175 from home:mcalabkova:branches:devel:languages:python:numeric - Update to 0.49.0 * Removal of all Python 2 related code and also updating the minimum supported Python version to 3.6, the minimum supported NumPy version to 1.15 and the minimum supported SciPy version to 1.0. (Stuart Archibald). * Refactoring of the Numba code base. The code is now organised into submodules by functionality. This cleans up Numba's top level namespace. (Stuart Archibald). * Introduction of an ``ir.Del`` free static single assignment form for Numba's intermediate representation (Siu Kwan Lam and Stuart Archibald). * An OpenMP-like thread masking API has been added for use with code using the parallel CPU backends (Aaron Meurer and Stuart Archibald). * For the CUDA target, all kernel launches now require a configuration, this preventing accidental launches of kernels with the old default of a single thread in a single block. The hard-coded autotuner is also now removed, such tuning is deferred to CUDA API calls that provide the same functionality (Graham Markall). * The CUDA target also gained an External Memory Management plugin interface to allow Numba to use another CUDA-aware library for all memory allocations and deallocations (Graham Markall). * The Numba Typed List container gained support for construction from iterables (Valentin Haenel). * Experimental support was added for first-class function types (Pearu Peterson). - Refreshed patch skip-failing-tests.patch * the troublesome tests are skipped upstream on 32-bit - Unpin llvmlite OBS-URL: https://build.opensuse.org/request/show/798175 OBS-URL: https://build.opensuse.org/package/show/devel:languages:python:numeric/python-numba?expand=0&rev=41
2020-04-27 21:40:16 +02:00
- @linux_only
+ @unittest.skip("Our x86_64 asm is most probably different from the upstream one.")
- update to 0.59.0 * Python 3.12 support * minimum supported version to 3.9 * Add support for ufunc attributes and reduce * Add a config variable to enable / disable the llvmlite memory manager * see https://numba.readthedocs.io/en/stable/release/0.59.0-notes.html#highlights * fix regressions with 0.57.0 + Support is added for the dict(iterable) constructor. - Clean up leftover Python 3.8 gubbins, look forward to Python 3.11 support. This release focuses on performance improvements, but also adds some new features and contains numerous bug fixes and stability * Intel kindly sponsored research and development into producing a new reference count pruning pass. This pass operates at the LLVM level and can prune a number of common reference counting patterns. This will improve performance for two primary - There will be less pressure on the atomic locks used to do - Removal of reference counting operations permits more inlining and the optimisation passes can in general do more * Intel also sponsored work to improve the performance of the numba.typed.List container, particularly in the case of * Superword-level parallelism vectorization is now switched on and the optimisation pipeline has been lightly analysed and tuned so as to be able to vectorize more and more often * The inspect_cfg method on the JIT dispatcher object has been significantly enhanced and now includes highlighted output and * The BSD operating system is now unofficially supported (Stuart * Numerous features/functionality improvements to NumPy support, - the ndarray allocators, empty, ones and zeros, accepting a * Cudasim support for mapped array, memcopies and memset has OBS-URL: https://build.opensuse.org/package/show/devel:languages:python:numeric/python-numba?expand=0&rev=77
2024-02-03 08:06:15 +01:00
@TestCase.run_test_in_subprocess
Accepting request 798175 from home:mcalabkova:branches:devel:languages:python:numeric - Update to 0.49.0 * Removal of all Python 2 related code and also updating the minimum supported Python version to 3.6, the minimum supported NumPy version to 1.15 and the minimum supported SciPy version to 1.0. (Stuart Archibald). * Refactoring of the Numba code base. The code is now organised into submodules by functionality. This cleans up Numba's top level namespace. (Stuart Archibald). * Introduction of an ``ir.Del`` free static single assignment form for Numba's intermediate representation (Siu Kwan Lam and Stuart Archibald). * An OpenMP-like thread masking API has been added for use with code using the parallel CPU backends (Aaron Meurer and Stuart Archibald). * For the CUDA target, all kernel launches now require a configuration, this preventing accidental launches of kernels with the old default of a single thread in a single block. The hard-coded autotuner is also now removed, such tuning is deferred to CUDA API calls that provide the same functionality (Graham Markall). * The CUDA target also gained an External Memory Management plugin interface to allow Numba to use another CUDA-aware library for all memory allocations and deallocations (Graham Markall). * The Numba Typed List container gained support for construction from iterables (Valentin Haenel). * Experimental support was added for first-class function types (Pearu Peterson). - Refreshed patch skip-failing-tests.patch * the troublesome tests are skipped upstream on 32-bit - Unpin llvmlite OBS-URL: https://build.opensuse.org/request/show/798175 OBS-URL: https://build.opensuse.org/package/show/devel:languages:python:numeric/python-numba?expand=0&rev=41
2020-04-27 21:40:16 +02:00
def test_vectorizer_fastmath_asm(self):
""" This checks that if fastmath is set and the underlying hardware
@@ -4700,7 +4701,7 @@ class TestParforsVectorizer(TestPrangeBa
Accepting request 798175 from home:mcalabkova:branches:devel:languages:python:numeric - Update to 0.49.0 * Removal of all Python 2 related code and also updating the minimum supported Python version to 3.6, the minimum supported NumPy version to 1.15 and the minimum supported SciPy version to 1.0. (Stuart Archibald). * Refactoring of the Numba code base. The code is now organised into submodules by functionality. This cleans up Numba's top level namespace. (Stuart Archibald). * Introduction of an ``ir.Del`` free static single assignment form for Numba's intermediate representation (Siu Kwan Lam and Stuart Archibald). * An OpenMP-like thread masking API has been added for use with code using the parallel CPU backends (Aaron Meurer and Stuart Archibald). * For the CUDA target, all kernel launches now require a configuration, this preventing accidental launches of kernels with the old default of a single thread in a single block. The hard-coded autotuner is also now removed, such tuning is deferred to CUDA API calls that provide the same functionality (Graham Markall). * The CUDA target also gained an External Memory Management plugin interface to allow Numba to use another CUDA-aware library for all memory allocations and deallocations (Graham Markall). * The Numba Typed List container gained support for construction from iterables (Valentin Haenel). * Experimental support was added for first-class function types (Pearu Peterson). - Refreshed patch skip-failing-tests.patch * the troublesome tests are skipped upstream on 32-bit - Unpin llvmlite OBS-URL: https://build.opensuse.org/request/show/798175 OBS-URL: https://build.opensuse.org/package/show/devel:languages:python:numeric/python-numba?expand=0&rev=41
2020-04-27 21:40:16 +02:00
# check no zmm addressing is present
self.assertTrue('zmm' not in v)
- @linux_only
+ @unittest.skip("Our x86_64 asm is most probably different from the upstream one.")
- update to 0.59.0 * Python 3.12 support * minimum supported version to 3.9 * Add support for ufunc attributes and reduce * Add a config variable to enable / disable the llvmlite memory manager * see https://numba.readthedocs.io/en/stable/release/0.59.0-notes.html#highlights * fix regressions with 0.57.0 + Support is added for the dict(iterable) constructor. - Clean up leftover Python 3.8 gubbins, look forward to Python 3.11 support. This release focuses on performance improvements, but also adds some new features and contains numerous bug fixes and stability * Intel kindly sponsored research and development into producing a new reference count pruning pass. This pass operates at the LLVM level and can prune a number of common reference counting patterns. This will improve performance for two primary - There will be less pressure on the atomic locks used to do - Removal of reference counting operations permits more inlining and the optimisation passes can in general do more * Intel also sponsored work to improve the performance of the numba.typed.List container, particularly in the case of * Superword-level parallelism vectorization is now switched on and the optimisation pipeline has been lightly analysed and tuned so as to be able to vectorize more and more often * The inspect_cfg method on the JIT dispatcher object has been significantly enhanced and now includes highlighted output and * The BSD operating system is now unofficially supported (Stuart * Numerous features/functionality improvements to NumPy support, - the ndarray allocators, empty, ones and zeros, accepting a * Cudasim support for mapped array, memcopies and memset has OBS-URL: https://build.opensuse.org/package/show/devel:languages:python:numeric/python-numba?expand=0&rev=77
2024-02-03 08:06:15 +01:00
@TestCase.run_test_in_subprocess(envvars={'NUMBA_BOUNDSCHECK': '0'})
Accepting request 798175 from home:mcalabkova:branches:devel:languages:python:numeric - Update to 0.49.0 * Removal of all Python 2 related code and also updating the minimum supported Python version to 3.6, the minimum supported NumPy version to 1.15 and the minimum supported SciPy version to 1.0. (Stuart Archibald). * Refactoring of the Numba code base. The code is now organised into submodules by functionality. This cleans up Numba's top level namespace. (Stuart Archibald). * Introduction of an ``ir.Del`` free static single assignment form for Numba's intermediate representation (Siu Kwan Lam and Stuart Archibald). * An OpenMP-like thread masking API has been added for use with code using the parallel CPU backends (Aaron Meurer and Stuart Archibald). * For the CUDA target, all kernel launches now require a configuration, this preventing accidental launches of kernels with the old default of a single thread in a single block. The hard-coded autotuner is also now removed, such tuning is deferred to CUDA API calls that provide the same functionality (Graham Markall). * The CUDA target also gained an External Memory Management plugin interface to allow Numba to use another CUDA-aware library for all memory allocations and deallocations (Graham Markall). * The Numba Typed List container gained support for construction from iterables (Valentin Haenel). * Experimental support was added for first-class function types (Pearu Peterson). - Refreshed patch skip-failing-tests.patch * the troublesome tests are skipped upstream on 32-bit - Unpin llvmlite OBS-URL: https://build.opensuse.org/request/show/798175 OBS-URL: https://build.opensuse.org/package/show/devel:languages:python:numeric/python-numba?expand=0&rev=41
2020-04-27 21:40:16 +02:00
def test_unsigned_refusal_to_vectorize(self):
""" This checks that if fastmath is set and the underlying hardware
Index: numba-0.59.1/numba/tests/test_parfors_passes.py
===================================================================
--- numba-0.59.1.orig/numba/tests/test_parfors_passes.py
+++ numba-0.59.1/numba/tests/test_parfors_passes.py
- update to 0.59.0 * Python 3.12 support * minimum supported version to 3.9 * Add support for ufunc attributes and reduce * Add a config variable to enable / disable the llvmlite memory manager * see https://numba.readthedocs.io/en/stable/release/0.59.0-notes.html#highlights * fix regressions with 0.57.0 + Support is added for the dict(iterable) constructor. - Clean up leftover Python 3.8 gubbins, look forward to Python 3.11 support. This release focuses on performance improvements, but also adds some new features and contains numerous bug fixes and stability * Intel kindly sponsored research and development into producing a new reference count pruning pass. This pass operates at the LLVM level and can prune a number of common reference counting patterns. This will improve performance for two primary - There will be less pressure on the atomic locks used to do - Removal of reference counting operations permits more inlining and the optimisation passes can in general do more * Intel also sponsored work to improve the performance of the numba.typed.List container, particularly in the case of * Superword-level parallelism vectorization is now switched on and the optimisation pipeline has been lightly analysed and tuned so as to be able to vectorize more and more often * The inspect_cfg method on the JIT dispatcher object has been significantly enhanced and now includes highlighted output and * The BSD operating system is now unofficially supported (Stuart * Numerous features/functionality improvements to NumPy support, - the ndarray allocators, empty, ones and zeros, accepting a * Cudasim support for mapped array, memcopies and memset has OBS-URL: https://build.opensuse.org/package/show/devel:languages:python:numeric/python-numba?expand=0&rev=77
2024-02-03 08:06:15 +01:00
@@ -514,6 +514,7 @@ class TestConvertLoopPass(BaseTest):
Accepting request 798175 from home:mcalabkova:branches:devel:languages:python:numeric - Update to 0.49.0 * Removal of all Python 2 related code and also updating the minimum supported Python version to 3.6, the minimum supported NumPy version to 1.15 and the minimum supported SciPy version to 1.0. (Stuart Archibald). * Refactoring of the Numba code base. The code is now organised into submodules by functionality. This cleans up Numba's top level namespace. (Stuart Archibald). * Introduction of an ``ir.Del`` free static single assignment form for Numba's intermediate representation (Siu Kwan Lam and Stuart Archibald). * An OpenMP-like thread masking API has been added for use with code using the parallel CPU backends (Aaron Meurer and Stuart Archibald). * For the CUDA target, all kernel launches now require a configuration, this preventing accidental launches of kernels with the old default of a single thread in a single block. The hard-coded autotuner is also now removed, such tuning is deferred to CUDA API calls that provide the same functionality (Graham Markall). * The CUDA target also gained an External Memory Management plugin interface to allow Numba to use another CUDA-aware library for all memory allocations and deallocations (Graham Markall). * The Numba Typed List container gained support for construction from iterables (Valentin Haenel). * Experimental support was added for first-class function types (Pearu Peterson). - Refreshed patch skip-failing-tests.patch * the troublesome tests are skipped upstream on 32-bit - Unpin llvmlite OBS-URL: https://build.opensuse.org/request/show/798175 OBS-URL: https://build.opensuse.org/package/show/devel:languages:python:numeric/python-numba?expand=0&rev=41
2020-04-27 21:40:16 +02:00
str(raises.exception),
)
+ @unittest.skip("Fails on type check in OBS")
def test_init_prange(self):
def test_impl():
n = 20
Index: numba-0.59.1/numba/tests/test_cli.py
===================================================================
--- numba-0.59.1.orig/numba/tests/test_cli.py
+++ numba-0.59.1/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()
Index: numba-0.59.1/numba/tests/test_mathlib.py
===================================================================
--- numba-0.59.1.orig/numba/tests/test_mathlib.py
+++ numba-0.59.1/numba/tests/test_mathlib.py
@@ -508,6 +508,7 @@ class TestMathLib(TestCase):
float('-inf'), float('inf'), float('nan')]
self.run_unary(pyfunc, x_types, x_values, prec='exact')
+ @unittest.skip("Fails on ppc64le https://github.com/numba/numba/issues/8489")
def test_ldexp(self):
pyfunc = ldexp
cfunc = njit(pyfunc)