From 7b8dbe2d733b8505e64dd6c2695ff950b993d45a Mon Sep 17 00:00:00 2001 From: Martin Weinelt Date: Wed, 1 Mar 2023 04:43:51 +0100 Subject: [PATCH] python310Packages.numba: Backport support for numpy 1.24.x This is a last ditch effort to keep numba working. --- .../python-modules/numba/default.nix | 10 +- .../python-modules/numba/numpy-1.24.patch | 644 ++++++++++++++++++ 2 files changed, 652 insertions(+), 2 deletions(-) create mode 100644 pkgs/development/python-modules/numba/numpy-1.24.patch diff --git a/pkgs/development/python-modules/numba/default.nix b/pkgs/development/python-modules/numba/default.nix index 9c60eac4116a..fae84969a661 100644 --- a/pkgs/development/python-modules/numba/default.nix +++ b/pkgs/development/python-modules/numba/default.nix @@ -37,12 +37,16 @@ in buildPythonPackage rec { postPatch = '' substituteInPlace setup.py \ - --replace "setuptools<60" "setuptools" + --replace 'max_numpy_run_version = "1.24"' 'max_numpy_run_version = "1.25"' + substituteInPlace numba/__init__.py \ + --replace "elif numpy_version > (1, 23):" "elif numpy_version > (1, 24):" ''; env.NIX_CFLAGS_COMPILE = lib.optionalString stdenv.isDarwin "-I${lib.getDev libcxx}/include/c++/v1"; - nativeBuildInputs = lib.optionals cudaSupport [ + nativeBuildInputs = [ + numpy + ] ++ lib.optionals cudaSupport [ addOpenGLRunpath ]; @@ -65,6 +69,8 @@ in buildPythonPackage rec { url = "https://github.com/numba/numba/commit/993e8c424055a7677b2755b184fc9e07549713b9.patch"; hash = "sha256-IhIqRLmP8gazx+KWIyCxZrNLMT4jZT8CWD3KcH4KjOo="; }) + # Backport numpy 1.24 support from https://github.com/numba/numba/pull/8691 + ./numpy-1.24.patch ] ++ lib.optionals cudaSupport [ (substituteAll { src = ./cuda_path.patch; diff --git a/pkgs/development/python-modules/numba/numpy-1.24.patch b/pkgs/development/python-modules/numba/numpy-1.24.patch new file mode 100644 index 000000000000..8a0214b79f7f --- /dev/null +++ b/pkgs/development/python-modules/numba/numpy-1.24.patch @@ -0,0 +1,644 @@ +From c3e6994e07fb6ac57be5d9d33d9046c5453b2256 Mon Sep 17 00:00:00 2001 +From: Graham Markall +Date: Thu, 24 Nov 2022 15:41:24 +0000 +Subject: [PATCH 01/13] CUDA intrinsics tests: correct np.float -> np.float16 + +I believe this was written in error and should always have been float16. +--- + numba/cuda/tests/cudapy/test_intrinsics.py | 4 ++-- + 1 file changed, 2 insertions(+), 2 deletions(-) + +diff --git a/numba/cuda/tests/cudapy/test_intrinsics.py b/numba/cuda/tests/cudapy/test_intrinsics.py +index 6e5fc0a0e..46fe8c607 100644 +--- a/numba/cuda/tests/cudapy/test_intrinsics.py ++++ b/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) + +-- +2.39.1 + +From 550fc6a25a82f76bc1f06bdea39177df635038c2 Mon Sep 17 00:00:00 2001 +From: Graham Markall +Date: Thu, 22 Dec 2022 13:02:22 +0000 +Subject: [PATCH 02/13] TestLinalgSvd.test_no_input_mutation: use + reconstruction if necessary + +This test only checked for a plain match when comparing outputs. +However, in some cases a reconstruction check can be necessary, as in +`test_linalg_svd`. +--- + numba/tests/test_linalg.py | 61 ++++++++++++++++++++------------------ + 1 file changed, 32 insertions(+), 29 deletions(-) + +diff --git a/numba/tests/test_linalg.py b/numba/tests/test_linalg.py +index db183059d..b1d4f0a83 100644 +--- a/numba/tests/test_linalg.py ++++ b/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): +-- +2.39.1 + +From c9ca2d1ae5e09ace729cddf6fba08effcd69a0b7 Mon Sep 17 00:00:00 2001 +From: Graham Markall +Date: Thu, 24 Nov 2022 21:39:27 +0000 +Subject: [PATCH 03/13] test_comp_nest_with_dependency: skip on NumPy 1.24 + +Setting an array element with a sequence is removed in NumPy 1.24. +--- + numba/tests/test_comprehension.py | 2 ++ + 1 file changed, 2 insertions(+) + +diff --git a/numba/tests/test_comprehension.py b/numba/tests/test_comprehension.py +index 2cdd3dc25..092ed51da 100644 +--- a/numba/tests/test_comprehension.py ++++ b/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.TestCase): + 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)]) +-- +2.39.1 + +From e69ad519352ac5a1f7714083968fcbac3ba92f95 Mon Sep 17 00:00:00 2001 +From: Graham Markall +Date: Thu, 24 Nov 2022 16:48:37 +0000 +Subject: [PATCH 04/13] Avoid use of np.bool in stencilparfor.py + +--- + numba/stencils/stencilparfor.py | 7 ++++++- + 1 file changed, 6 insertions(+), 1 deletion(-) + +diff --git a/numba/stencils/stencilparfor.py b/numba/stencils/stencilparfor.py +index 5f30893b3..4f23ed903 100644 +--- a/numba/stencils/stencilparfor.py ++++ b/numba/stencils/stencilparfor.py +@@ -21,6 +21,7 @@ from numba.core.ir_utils import (get_call_table, mk_unique_var, + 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) +-- +2.39.1 + +From dd96d5996abd8646443501f2bbd7d4e1a9c0eec4 Mon Sep 17 00:00:00 2001 +From: Graham Markall +Date: Thu, 24 Nov 2022 15:46:52 +0000 +Subject: [PATCH 05/13] test_hypot: Tweak regex so it matches NumPy 1.24 + +The modified regex matches the existing message produced by NumPy < +1.24, and the new improved message in 1.24. +--- + numba/tests/test_mathlib.py | 2 +- + 1 file changed, 1 insertion(+), 1 deletion(-) + +diff --git a/numba/tests/test_mathlib.py b/numba/tests/test_mathlib.py +index a3f535316..05e3d68f5 100644 +--- a/numba/tests/test_mathlib.py ++++ b/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): +-- +2.39.1 + +From b755c22caeec9e6b0e0606f0cee245648914d592 Mon Sep 17 00:00:00 2001 +From: Graham Markall +Date: Thu, 24 Nov 2022 11:29:53 +0000 +Subject: [PATCH 06/13] Don't test summing with timedelta dtype + +This always produced invalid results (though they were consistent +between Numba and NumPy) but now this fails in NumPy 1.24 with an +exception: + +``` +TypeError: The `dtype` and `signature` arguments to ufuncs only select +the general DType and not details such as the byte order or time unit. +You can avoid this error by using the scalar types `np.float64` or the +dtype string notation. +``` + +Note that the exception message is misleading, and using the dtype +string notation does not provide a workaround. +--- + numba/tests/test_array_methods.py | 15 ++++++--------- + 1 file changed, 6 insertions(+), 9 deletions(-) + +diff --git a/numba/tests/test_array_methods.py b/numba/tests/test_array_methods.py +index eee5cfeff..a2312adba 100644 +--- a/numba/tests/test_array_methods.py ++++ b/numba/tests/test_array_methods.py +@@ -1193,7 +1193,7 @@ class TestArrayMethods(MemoryLeakMixin, TestCase): + 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, TestCase): + 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, TestCase): + 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, TestCase): + 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: +-- +2.39.1 + +From 65df00379df1276b7045b44818347a119bb32361 Mon Sep 17 00:00:00 2001 +From: Graham Markall +Date: Thu, 24 Nov 2022 10:03:54 +0000 +Subject: [PATCH 07/13] Replace use of deprecated np.bool with np.bool_ + +np.bool was removed in NumPy 1.24. +--- + numba/tests/test_np_functions.py | 8 ++++---- + 1 file changed, 4 insertions(+), 4 deletions(-) + +diff --git a/numba/tests/test_np_functions.py b/numba/tests/test_np_functions.py +index 4cdaf548b..e195ac781 100644 +--- a/numba/tests/test_np_functions.py ++++ b/numba/tests/test_np_functions.py +@@ -932,11 +932,11 @@ class TestNPFunctions(MemoryLeakMixin, TestCase): + 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: +-- +2.39.1 + +From 065475bd8d5f39ad0a2b0d154ca283dec10bf5d0 Mon Sep 17 00:00:00 2001 +From: Graham Markall +Date: Thu, 24 Nov 2022 09:56:06 +0000 +Subject: [PATCH 08/13] Overload np.MachAr only for NumPy < 1.24 + +--- + numba/np/arraymath.py | 4 ++++ + numba/tests/test_np_functions.py | 4 +++- + 2 files changed, 7 insertions(+), 1 deletion(-) + +diff --git a/numba/np/arraymath.py b/numba/np/arraymath.py +index 9885526ee..f6e5f5560 100644 +--- a/numba/np/arraymath.py ++++ b/numba/np/arraymath.py +@@ -4177,6 +4177,10 @@ iinfo = namedtuple('iinfo', _iinfo_supported) + # 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: +diff --git a/numba/tests/test_np_functions.py b/numba/tests/test_np_functions.py +index e195ac781..e8a9bccd0 100644 +--- a/numba/tests/test_np_functions.py ++++ b/numba/tests/test_np_functions.py +@@ -4775,6 +4775,7 @@ def foo(): + eval(compile(funcstr, '', '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 +-- +2.39.1 + +From 4925287144b9dca5624886ac44a27831178a7198 Mon Sep 17 00:00:00 2001 +From: Graham Markall +Date: Fri, 25 Nov 2022 10:55:04 +0000 +Subject: [PATCH 09/13] _internal.c: Remove NPY_API_VERSION checks + +The API version has long since been greater than 0x7 / 0x8 for any +supported NumPy. +--- + numba/np/ufunc/_internal.c | 14 -------------- + 1 file changed, 14 deletions(-) + +diff --git a/numba/np/ufunc/_internal.c b/numba/np/ufunc/_internal.c +index 98a643788..3ab725f8f 100644 +--- a/numba/np/ufunc/_internal.c ++++ b/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_fastcall) + 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; + } +@@ -351,9 +347,7 @@ init_ufunc_dispatch(int *numpy_uses_fastcall) + && (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 + ); + } + return result; +@@ -425,13 +419,11 @@ 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 +601,9 @@ 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 +633,9 @@ static struct PyMethodDef dufunc_methods_fast[] = { + {"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 +779,7 @@ 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; + +-- +2.39.1 + +From 783ef5a297f15d16eec61fe38d13648b876e3750 Mon Sep 17 00:00:00 2001 +From: Graham Markall +Date: Tue, 3 Jan 2023 17:08:44 +0000 +Subject: [PATCH 10/13] init_ufunc_dispatch: Handle unexpected ufunc methods + gracefully + +If an unexpected ufunc method was encountered, `init_ufunc_dispatch()` +would return an error code indicating failure without setting an +exception, leading to errors like + +``` +SystemError: initialization of _internal failed without raising an +exception +``` + +as reported in Issue #8615. + +This commit fixes the issue by setting an appropriate exception in this +case. +--- + numba/np/ufunc/_internal.c | 6 ++++++ + 1 file changed, 6 insertions(+) + +diff --git a/numba/np/ufunc/_internal.c b/numba/np/ufunc/_internal.c +index 3ab725f8f..6ce8989cd 100644 +--- a/numba/np/ufunc/_internal.c ++++ b/numba/np/ufunc/_internal.c +@@ -337,6 +337,8 @@ init_ufunc_dispatch(int *numpy_uses_fastcall) + *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; + } + } +@@ -349,7 +351,11 @@ init_ufunc_dispatch(int *numpy_uses_fastcall) + && (ufunc_dispatch.ufunc_outer != NULL) + && (ufunc_dispatch.ufunc_at != NULL) + ); ++ } else { ++ char const * const fmt = "Unexpected ufunc method %s()"; ++ PyErr_Format(PyExc_RuntimeError, fmt, crnt_name); + } ++ + return result; + } + +-- +2.39.1 + +From 5c259e46a8e510c2b82c7ff449b167d3b430294b Mon Sep 17 00:00:00 2001 +From: Graham Markall +Date: Tue, 3 Jan 2023 17:11:10 +0000 +Subject: [PATCH 11/13] init_ufunc_dispatch: Update for NumPy 1.24 + +NumPy 1.24 adds a new method, `resolve_dtypes()`, and a private method +`_resolve_dtypes_and_context()`. We handle these by just ignoring them +(ignoring all private methods in general) in order to provide the same +level of functionality in Numba as for NumPy 1.23. + +There is further room to build new functionality on top of this: + +- Providing an implementation of `resolve_dtypes()` for `DUFunc` + objects. +- Using the `resolve_dtypes()` method in place of logic in Numba that + implements a similar dtype resolution process. +--- + numba/np/ufunc/_internal.c | 5 +++++ + 1 file changed, 5 insertions(+) + +diff --git a/numba/np/ufunc/_internal.c b/numba/np/ufunc/_internal.c +index 6ce8989cd..e860081fb 100644 +--- a/numba/np/ufunc/_internal.c ++++ b/numba/np/ufunc/_internal.c +@@ -322,10 +322,15 @@ init_ufunc_dispatch(int *numpy_uses_fastcall) + } 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 */ + } +-- +2.39.1 + +From 3736714982be943eb94f4a259368b1dce525ea64 Mon Sep 17 00:00:00 2001 +From: Graham Markall +Date: Wed, 11 Jan 2023 16:25:19 +0000 +Subject: [PATCH 12/13] Update comment on skipped test + +PR #8691 feedback. +--- + numba/tests/test_comprehension.py | 4 +++- + 1 file changed, 3 insertions(+), 1 deletion(-) + +diff --git a/numba/tests/test_comprehension.py b/numba/tests/test_comprehension.py +index 092ed51da..9327b4ed3 100644 +--- a/numba/tests/test_comprehension.py ++++ b/numba/tests/test_comprehension.py +@@ -361,7 +361,9 @@ class TestArrayComprehension(unittest.TestCase): + self.check(comp_nest_with_array_conditional, 5, + assert_allocate_list=True) + +- @unittest.skipUnless(numpy_version < (1, 24), 'Removed in NumPy 1.24') ++ @unittest.skipUnless(numpy_version < (1, 24), ++ 'Setting an array element with a sequence is 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)]) +-- +2.39.1 + +From 3cbab7ee436e3452e7d078f8283136671a36d944 Mon Sep 17 00:00:00 2001 +From: Graham Markall +Date: Fri, 27 Jan 2023 12:06:57 +0000 +Subject: [PATCH 13/13] Correct name of ufunc method in fastcall flags error + +The name of the method should be given, which was never `at()`. +--- + numba/np/ufunc/_internal.c | 5 +++-- + 1 file changed, 3 insertions(+), 2 deletions(-) + +diff --git a/numba/np/ufunc/_internal.c b/numba/np/ufunc/_internal.c +index e860081fb..0a33de170 100644 +--- a/numba/np/ufunc/_internal.c ++++ b/numba/np/ufunc/_internal.c +@@ -342,8 +342,9 @@ init_ufunc_dispatch(int *numpy_uses_fastcall) + *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"); ++ PyErr_Format(PyExc_RuntimeError, ++ "ufunc.%s() flags do not match numpy_uses_fastcall", ++ crnt_name); + return -1; + } + } +-- +2.39.1 +