diff options
Diffstat (limited to 'pkgs/development/python-modules/numba/numpy-1.24.patch')
| -rw-r--r-- | pkgs/development/python-modules/numba/numpy-1.24.patch | 644 |
1 files changed, 0 insertions, 644 deletions
diff --git a/pkgs/development/python-modules/numba/numpy-1.24.patch b/pkgs/development/python-modules/numba/numpy-1.24.patch deleted file mode 100644 index 8a0214b79f7..00000000000 --- a/pkgs/development/python-modules/numba/numpy-1.24.patch +++ /dev/null @@ -1,644 +0,0 @@ -From c3e6994e07fb6ac57be5d9d33d9046c5453b2256 Mon Sep 17 00:00:00 2001 -From: Graham Markall <gmarkall@nvidia.com> -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 <gmarkall@nvidia.com> -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 <gmarkall@nvidia.com> -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 <gmarkall@nvidia.com> -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 <gmarkall@nvidia.com> -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 <gmarkall@nvidia.com> -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 <gmarkall@nvidia.com> -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 <gmarkall@nvidia.com> -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, '<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 --- -2.39.1 - -From 4925287144b9dca5624886ac44a27831178a7198 Mon Sep 17 00:00:00 2001 -From: Graham Markall <gmarkall@nvidia.com> -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 <gmarkall@nvidia.com> -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 <gmarkall@nvidia.com> -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 <gmarkall@nvidia.com> -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 <gmarkall@nvidia.com> -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 - |