8000 Merge pull request #25072 from rgommers/fix-build-warnings · numpy/numpy@a7b7e55 · GitHub
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sebergseberg
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Merge pull request #25072 from rgommers/fix-build-warnings
MAINT: default to C11 rather than C99, fix most build warnings with Clang 14
2 parents 3ffad97 + 0ee0b6f commit a7b7e55

11 files changed

+18
-93
lines changed

‎build_requirements.txt

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -1,5 +1,5 @@
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meson-python>=0.13.1
2-
Cython>=3.0
2+
Cython>=3.0.6
33
ninja
44
spin==0.8
55
build

‎doc/source/dev/development_environment.rst

Lines changed: 1 addition & 1 deletion
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@@ -11,7 +11,7 @@ Recommended development setup
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Since NumPy contains parts written in C and Cython that need to be
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compiled before use, make sure you have the necessary compilers and Python
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development headers installed - see :ref:`building-from-source`. Building
14-
NumPy as of version ``1.17`` requires a C99 compliant compiler.
14+
NumPy as of version ``2.0`` requires C11 and C++17 compliant compilers.
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Having compiled code also means that importing NumPy from the development
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sources needs some additional steps, which are explained below. For the rest

‎meson.build

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@@ -10,7 +10,7 @@ project(
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default_options: [
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'buildtype=debugoptimized',
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'b_ndebug=if-release',
13-
'c_std=c99',
13+
'c_std=c11',
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'cpp_std=c++17',
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'pkgconfig.relocatable=true',
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],
@@ -33,8 +33,8 @@ elif cc.get_id() == 'msvc'
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'when building with MSVC')
3434
endif
3535
endif
36-
if not cy.version().version_compare('>=0.29.34')
37-
error('NumPy requires Cython >= 0.29.34')
36+
if not cy.version().version_compare('>=3.0.6')
37+
error('NumPy requires Cython >= 3.0.6')
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endif
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py = import('python').find_installation(pure: false)

‎numpy/_core/src/multiarray/einsum.c.src

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Original file line numberDiff line numberDiff line change
@@ -402,11 +402,6 @@ get_combined_dims_view(PyArrayObject *op, int iop, char *labels)
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}
403403
/* A repeated label, find the original one and merge them. */
404404
else {
405-
#ifdef __GNUC__
406-
#pragma GCC diagnostic push
407-
#pragma GCC diagnostic ignored "-Wuninitialized"
408-
#pragma GCC diagnostic ignored "-Wmaybe-uninitialized"
409-
#endif
410405
int i = icombinemap[idim + label];
411406

412407
icombinemap[idim] = -1;
@@ -419,9 +414,6 @@ get_combined_dims_view(PyArrayObject *op, int iop, char *labels)
419414
return NULL;
420415
}
421416
new_strides[i] += stride;
422-
#ifdef __GNUC__
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#pragma GCC diagnostic pop
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#endif
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}
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}
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‎numpy/_core/src/multiarray/item_selection.c

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@@ -2367,6 +2367,7 @@ PyArray_Compress(PyArrayObject *self, PyObject *condition, int axis,
23672367
* even though it uses 64 bit types its faster than the bytewise sum on 32 bit
23682368
* but a 32 bit type version would make it even faster on these platforms
23692369
*/
2370+
#if !NPY_SIMD
23702371
static inline npy_intp
23712372
count_nonzero_bytes_384(const npy_uint64 * w)
23722373
{
@@ -2407,6 +2408,7 @@ count_nonzero_bytes_384(const npy_uint64 * w)
24072408

24082409
return r;
24092410
}
2411+
#endif
24102412

24112413
#if NPY_SIMD
24122414
/* Count the zero bytes between `*d` and `end`, updating `*d` to point to where to keep counting from. */

‎numpy/_core/src/npysort/selection.cpp

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@@ -518,7 +518,7 @@ _get_partition_func(int type, NPY_SELECTKIND which)
518518
npy_intp i;
519519
npy_intp ntypes = partition_t::map.size();
520520

521-
if (which >= NPY_NSELECTS) {
521+
if ((int)which < 0 || (int)which >= NPY_NSELECTS) {
522522
return NULL;
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}
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for (i = 0; i < ntypes; i++) {

‎numpy/_core/src/umath/loops_arithm_fp.dispatch.c.src

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@@ -215,7 +215,7 @@ NPY_NO_EXPORT int NPY_CPU_DISPATCH_CURFX(@TYPE@_@kind@_indexed)
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//###############################################################################
216216

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/********************************************************************************
218-
** op intrinics
218+
** op intrinsics
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********************************************************************************/
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#if NPY_SIMD_F32
@@ -296,61 +296,6 @@ simd_csquare_f64(npyv_f64 x)
296296
{ return simd_cmul_f64(x, x); }
297297
#endif
298298

299-
/**begin repeat
300-
* #type = npy_float, npy_double#
301-
* #sfx = f32, f64#
302-
* #bsfx = b32, b64#
303-
* #usfx = b32, u64#
304-
* #VECTOR = NPY_SIMD_F32, NPY_SIMD_F64#
305-
* #is_double = 0, 1#
306-
* #c = f, #
307-
* #INF = NPY_INFINITYF, NPY_INFINITY#
308-
* #NAN = NPY_NANF, NPY_NAN#
309-
*/
310-
#if @VECTOR@
311-
NPY_FINLINE npyv_@sfx@
312-
simd_cabsolute_@sfx@(npyv_@sfx@ re, npyv_@sfx@ im)
313-
{
314-
const npyv_@sfx@ inf = npyv_setall_@sfx@(@INF@);
315-
const npyv_@sfx@ nan = npyv_setall_@sfx@(@NAN@);
316-
317-
re = npyv_abs_@sfx@(re);
318-
im = npyv_abs_@sfx@(im);
319-
/*
320-
* If real or imag = INF, then convert it to inf + j*inf
321-
* Handles: inf + j*nan, nan + j*inf
322-
*/
323-
npyv_@bsfx@ re_infmask = npyv_cmpeq_@sfx@(re, inf);
324-
npyv_@bsfx@ im_infmask = npyv_cmpeq_@sfx@(im, inf);
325-
im = npyv_select_@sfx@(re_infmask, inf, im);
326-
re = npyv_select_@sfx@(im_infmask, inf, re);
327-
/*
328-
* If real or imag = NAN, then convert it to nan + j*nan
329-
* Handles: x + j*nan, nan + j*x
330-
*/
331-
npyv_@bsfx@ re_nnanmask = npyv_notnan_@sfx@(re);
332-
npyv_@bsfx@ im_nnanmask = npyv_notnan_@sfx@(im);
333-
im = npyv_select_@sfx@(re_nnanmask, im, nan);
334-
re = npyv_select_@sfx@(im_nnanmask, re, nan);
335-
336-
npyv_@sfx@ larger = npyv_max_@sfx@(re, im);
337-
npyv_@sfx@ smaller = npyv_min_@sfx@(im, re);
338-
/*
339-
* Calculate div_mask to prevent 0./0. and inf/inf operations in div
340-
*/
341-
npyv_@bsfx@ zeromask = npyv_cmpeq_@sfx@(larger, npyv_zero_@sfx@());
342-
npyv_@bsfx@ infmask = npyv_cmpeq_@sfx@(smaller, inf);
343-
npyv_@bsfx@ div_mask = npyv_not_@bsfx@(npyv_or_@bsfx@(zeromask, infmask));
344-
345-
npyv_@sfx@ ratio = npyv_ifdivz_@sfx@(div_mask, smaller, larger);
346-
npyv_@sfx@ hypot = npyv_sqrt_@sfx@(
347-
npyv_muladd_@sfx@(ratio, ratio, npyv_setall_@sfx@(1.0@c@)
348-
));
349-
return npyv_mul_@sfx@(hypot, larger);
350-
}
351-
#endif // VECTOR
352-
/**end repeat**/
353-
354299
/********************************************************************************
355300
** Defining ufunc inner functions
356301
********************************************************************************/

‎numpy/_core/src/umath/scalarmath.c.src

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@@ -1804,12 +1804,6 @@ static PyObject *
18041804
}
18051805
/**end repeat**/
18061806

1807-
#if __GNUC__ < 10
1808-
/* At least GCC 9.2 issues spurious warnings for arg2 below. */
1809-
#pragma GCC diagnostic push /* matching pop after function and repeat */
1810-
#pragma GCC diagnostic ignored "-Wmaybe-uninitialized"
1811-
#endif
1812-
18131807
/**begin repeat
18141808
* #oper = le, ge, lt, gt, eq, ne#
18151809
* #op = <=, >=, <, >, ==, !=#
@@ -1941,10 +1935,6 @@ static PyObject*
19411935
#undef IS_@name@
19421936
/**end repeat**/
19431937

1944-
#if __GNUC__ < 10
1945-
#pragma GCC diagnostic pop
1946-
#endif
1947-
19481938

19491939
/**begin repeat
19501940
* #name = byte, ubyte, short, ushort, int, uint,

‎numpy/_core/src/umath/special_integer_comparisons.cpp

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@@ -99,6 +99,7 @@ get_min_max(int typenum, long long *min, unsigned long long *max)
9999
*max = NPY_MAX_ULONGLONG;
100100
break;
101101
default:
102+
*max = 0;
102103
assert(0);
103104
}
104105
}

‎numpy/linalg/umath_linalg.cpp

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@@ -34,6 +34,8 @@ static const char* umath_linalg_version_string = "0.1.5";
3434
* Debugging support *
3535
****************************************************************************
3636
*/
37+
#define _UMATH_LINALG_DEBUG 0
38+
3739
#define TRACE_TXT(...) do { fprintf (stderr, __VA_ARGS__); } while (0)
3840
#define STACK_TRACE do {} while (0)
3941
#define TRACE\
@@ -46,7 +48,7 @@ static const char* umath_linalg_version_string = "0.1.5";
4648
STACK_TRACE; \
4749
} while (0)
4850

49-
#if 0
51+
#if _UMATH_LINALG_DEBUG
5052
#if defined HAVE_EXECINFO_H
5153
#include <execinfo.h>
5254
#elif defined HAVE_LIBUNWIND_H
@@ -574,6 +576,7 @@ init_linearize_data(LINEARIZE_DATA_t *lin_data,
574576
lin_data, rows, columns, row_strides, column_strides, columns);
575577
}
576578

579+
#if _UMATH_LINALG_DEBUG
577580
static inline void
578581
dump_ufunc_object(PyUFuncObject* ufunc)
579582
{
@@ -651,7 +654,7 @@ dump_matrix(const char* name,
651654
TRACE_TXT(" |\n");
652655
}
653656
}
654-
657+
#endif
655658

656659
/*
657660
*****************************************************************************
@@ -761,12 +764,6 @@ update_pointers(npy_uint8** bases, ptrdiff_t* offsets, size_t count)
761764
}
762765

763766

764-
/* disable -Wmaybe-uninitialized as there is some code that generate false
765-
positives with this warning
766-
*/
767-
#pragma GCC diagnostic push
768-
#pragma GCC diagnostic ignored "-Wmaybe-uninitialized"
769-
770767
/*
771768
*****************************************************************************
772769
** DISPATCHER FUNCS **
@@ -2926,7 +2923,7 @@ using basetyp = basetype_t<typ>;
29262923
(fortran_int)dimensions[0],
29272924
(fortran_int)dimensions[1],
29282925
dispatch_scalar<typ>())) {
2929-
LINEARIZE_DATA_t a_in, u_out, s_out, v_out;
2926+
LINEARIZE_DATA_t a_in, u_out = {}, s_out = {}, v_out = {};
29302927
fortran_int min_m_n = params.M < params.N ? params.M : params.N;
29312928

29322929
init_linearize_data(&a_in, params.N, params.M, steps[1], steps[0]);
@@ -4081,8 +4078,6 @@ dispatch_scalar<typ>{});
40814078
set_fp_invalid_or_clear(error_occurred);
40824079
}
40834080

4084-
#pragma GCC diagnostic pop
4085-
40864081
/* -------------------------------------------------------------------------- */
40874082
/* gufunc registration */
40884083

@@ -4548,7 +4543,7 @@ addUfuncs(PyObject *dictionary) {
45484543
if (f == NULL) {
45494544
return -1;
45504545
}
4551-
#if 0
4546+
#if _UMATH_LINALG_DEBUG
45524547
dump_ufunc_object((PyUFuncObject*) f);
45534548
#endif
45544549
int ret = PyDict_SetItemString(dictionary, d->name, f);

‎pyproject.toml

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@@ -2,7 +2,7 @@
22
build-backend = "mesonpy"
33
requires = [
44
"meson-python>=0.15.0",
5-
"Cython>=3.0",
5+
"Cython>=3.0.6", # keep in sync with version check in meson.build
66
]
77

88
[project]

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