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loops.c.src
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loops.c.src
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/* -*- c -*- */
#define _UMATHMODULE
#define _MULTIARRAYMODULE
#define NPY_NO_DEPRECATED_API NPY_API_VERSION
#include "Python.h"
#include "npy_config.h"
#include "numpy/npy_common.h"
#include "numpy/arrayobject.h"
#include "numpy/ufuncobject.h"
#include "numpy/npy_math.h"
#include "numpy/halffloat.h"
#include "lowlevel_strided_loops.h"
#include "npy_pycompat.h"
#include "ufunc_object.h"
#include <string.h> /* for memchr */
/* Use Libdivide for faster division */
#include "numpy/libdivide/libdivide.h"
/*
* cutoff blocksize for pairwise summation
* decreasing it decreases errors slightly as more pairs are summed but
* also lowers performance, as the inner loop is unrolled eight times it is
* effectively 16
*/
#define PW_BLOCKSIZE 128
/*
* largest simd vector size in bytes numpy supports
* it is currently a extremely large value as it is only used for memory
* overlap checks
*/
#ifndef NPY_MAX_SIMD_SIZE
#define NPY_MAX_SIMD_SIZE 1024
#endif
/** Provides the various *_LOOP macros */
#include "fast_loop_macros.h"
/*
* include vectorized functions and dispatchers
* this file is safe to include also for generic builds
* platform specific instructions are either masked via the proprocessor or
* runtime detected
*/
#include "simd.inc"
/******************************************************************************
** GENERIC FLOAT LOOPS **
*****************************************************************************/
/* direct loops using a suitable callback */
/**begin repeat
* #c = e, f, d, g#
* #type = npy_half, npy_float, npy_double, npy_longdouble#
**/
/*UFUNC_API*/
NPY_NO_EXPORT void
PyUFunc_@c@_@c@(char **args, npy_intp const *dimensions, npy_intp const *steps, void *func)
{
typedef @type@ func_type(@type@);
func_type *f = (func_type *)func;
UNARY_LOOP {
const @type@ in1 = *(@type@ *)ip1;
*(@type@ *)op1 = f(in1);
}
}
/*UFUNC_API*/
NPY_NO_EXPORT void
PyUFunc_@c@@c@_@c@(char **args, npy_intp const *dimensions, npy_intp const *steps, void *func)
{
typedef @type@ func_type(@type@, @type@);
func_type *f = (func_type *)func;
BINARY_LOOP {
@type@ in1 = *(@type@ *)ip1;
@type@ in2 = *(@type@ *)ip2;
*(@type@ *)op1 = f(in1, in2);
}
}
/**end repeat**/
/* indirect loops with casting */
/**begin repeat
* #c1 = e, e, f#
* #type1 = npy_half, npy_half, npy_float#
* #c2 = f, d, d#
* #type2 = npy_float, npy_double, npy_double#
*
* #conv12 = npy_half_to_float, npy_half_to_double, (double)#
* #conv21 = npy_float_to_half, npy_double_to_half, (float)#
**/
/*UFUNC_API*/
NPY_NO_EXPORT void
PyUFunc_@c1@_@c1@_As_@c2@_@c2@(char **args, npy_intp const *dimensions, npy_intp const *steps, void *func)
{
typedef @type2@ func_type(@type2@);
func_type *f = (func_type *)func;
UNARY_LOOP {
const @type2@ in1 = @conv12@(*(@type1@ *)ip1);
*(@type1@ *)op1 = @conv21@(f(in1));
}
}
/*UFUNC_API*/
NPY_NO_EXPORT void
PyUFunc_@c1@@c1@_@c1@_As_@c2@@c2@_@c2@(char **args, npy_intp const *dimensions, npy_intp const *steps, void *func)
{
typedef @type2@ func_type(@type2@, @type2@);
func_type *f = (func_type *)func;
BINARY_LOOP {
const @type2@ in1 = @conv12@(*(@type1@ *)ip1);
const @type2@ in2 = @conv12@(*(@type1@ *)ip2);
*(@type1@ *)op1 = @conv21@(f(in1, in2));
}
}
/**end repeat**/
/******************************************************************************
** GENERIC COMPLEX LOOPS **
*****************************************************************************/
/* direct loops using a suitable callback */
/**begin repeat
* #c = F, D, G#
* #type = npy_cfloat, npy_cdouble, npy_clongdouble#
**/
/*UFUNC_API*/
NPY_NO_EXPORT void
PyUFunc_@c@_@c@(char **args, npy_intp const *dimensions, npy_intp const *steps, void *func)
{
typedef void func_type(@type@ *, @type@ *);
func_type *f = (func_type *)func;
UNARY_LOOP {
@type@ in1 = *(@type@ *)ip1;
@type@ *out = (@type@ *)op1;
f(&in1, out);
}
}
/*UFUNC_API*/
NPY_NO_EXPORT void
PyUFunc_@c@@c@_@c@(char **args, npy_intp const *dimensions, npy_intp const *steps, void *func)
{
typedef void func_type(@type@ *, @type@ *, @type@ *);
func_type *f = (func_type *)func;
BINARY_LOOP {
@type@ in1 = *(@type@ *)ip1;
@type@ in2 = *(@type@ *)ip2;
@type@ *out = (@type@ *)op1;
f(&in1, &in2, out);
}
}
/**end repeat**/
/* indirect loops with casting */
/*UFUNC_API*/
NPY_NO_EXPORT void
PyUFunc_F_F_As_D_D(char **args, npy_intp const *dimensions, npy_intp const *steps, void *func)
{
typedef void func_type(npy_cdouble *, npy_cdouble *);
func_type *f = (func_type *)func;
UNARY_LOOP {
npy_cdouble tmp, out;
tmp.real = (double)((float *)ip1)[0];
tmp.imag = (double)((float *)ip1)[1];
f(&tmp, &out);
((float *)op1)[0] = (float)out.real;
((float *)op1)[1] = (float)out.imag;
}
}
/*UFUNC_API*/
NPY_NO_EXPORT void
PyUFunc_FF_F_As_DD_D(char **args, npy_intp const *dimensions, npy_intp const *steps, void *func)
{
typedef void func_type(npy_cdouble *, npy_cdouble *, npy_cdouble *);
func_type *f = (func_type *)func;
BINARY_LOOP {
npy_cdouble tmp1, tmp2, out;
tmp1.real = (double)((float *)ip1)[0];
tmp1.imag = (double)((float *)ip1)[1];
tmp2.real = (double)((float *)ip2)[0];
tmp2.imag = (double)((float *)ip2)[1];
f(&tmp1, &tmp2, &out);
((float *)op1)[0] = (float)out.real;
((float *)op1)[1] = (float)out.imag;
}
}
/******************************************************************************
** GENERIC OBJECT lOOPS **
*****************************************************************************/
/*UFUNC_API*/
NPY_NO_EXPORT void
PyUFunc_O_O(char **args, npy_intp const *dimensions, npy_intp const *steps, void *func)
{
unaryfunc f = (unaryfunc)func;
UNARY_LOOP {
PyObject *in1 = *(PyObject **)ip1;
PyObject **out = (PyObject **)op1;
PyObject *ret = f(in1 ? in1 : Py_None);
if (ret == NULL) {
return;
}
Py_XDECREF(*out);
*out = ret;
}
}
/*UFUNC_API*/
NPY_NO_EXPORT void
PyUFunc_O_O_method(char **args, npy_intp const *dimensions, npy_intp const *steps, void *func)
{
char *meth = (char *)func;
UNARY_LOOP {
PyObject *in1 = *(PyObject **)ip1;
PyObject **out = (PyObject **)op1;
PyObject *ret, *func;
func = PyObject_GetAttrString(in1 ? in1 : Py_None, meth);
if (func != NULL && !PyCallable_Check(func)) {
Py_DECREF(func);
func = NULL;
}
if (func == NULL) {
PyObject *exc, *val, *tb;
PyTypeObject *type = in1 ? Py_TYPE(in1) : Py_TYPE(Py_None);
PyErr_Fetch(&exc, &val, &tb);
PyErr_Format(PyExc_TypeError,
"loop of ufunc does not support argument %d of "
"type %s which has no callable %s method",
i, type->tp_name, meth);
npy_PyErr_ChainExceptionsCause(exc, val, tb);
Py_XDECREF(func);
return;
}
ret = PyObject_CallObject(func, NULL);
Py_DECREF(func);
if (ret == NULL) {
return;
}
Py_XDECREF(*out);
*out = ret;
}
}
/*UFUNC_API*/
NPY_NO_EXPORT void
PyUFunc_OO_O(char **args, npy_intp const *dimensions, npy_intp const *steps, void *func)
{
binaryfunc f = (binaryfunc)func;
BINARY_LOOP {
PyObject *in1 = *(PyObject **)ip1;
PyObject *in2 = *(PyObject **)ip2;
PyObject **out = (PyObject **)op1;
PyObject *ret = f(in1 ? in1 : Py_None, in2 ? in2 : Py_None);
if (ret == NULL) {
return;
}
Py_XDECREF(*out);
*out = ret;
}
}
NPY_NO_EXPORT void
PyUFunc_OOO_O(char **args, npy_intp const *dimensions, npy_intp const *steps, void *func)
{
ternaryfunc f = (ternaryfunc)func;
TERNARY_LOOP {
PyObject *in1 = *(PyObject **)ip1;
PyObject *in2 = *(PyObject **)ip2;
PyObject *in3 = *(PyObject **)ip3;
PyObject **out = (PyObject **)op1;
PyObject *ret = f(
in1 ? in1 : Py_None,
in2 ? in2 : Py_None,
in3 ? in3 : Py_None
);
if (ret == NULL) {
return;
}
Py_XDECREF(*out);
*out = ret;
}
}
/*UFUNC_API*/
NPY_NO_EXPORT void
PyUFunc_OO_O_method(char **args, npy_intp const *dimensions, npy_intp const *steps, void *func)
{
char *meth = (char *)func;
BINARY_LOOP {
PyObject *in1 = *(PyObject **)ip1;
PyObject *in2 = *(PyObject **)ip2;
PyObject **out = (PyObject **)op1;
PyObject *ret = PyObject_CallMethod(in1 ? in1 : Py_None,
meth, "(O)", in2);
if (ret == NULL) {
return;
}
Py_XDECREF(*out);
*out = ret;
}
}
/*
* A general-purpose ufunc that deals with general-purpose Python callable.
* func is a structure with nin, nout, and a Python callable function
*/
/*UFUNC_API*/
NPY_NO_EXPORT void
PyUFunc_On_Om(char **args, npy_intp const *dimensions, npy_intp const *steps, void *func)
{
npy_intp n = dimensions[0];
PyUFunc_PyFuncData *data = (PyUFunc_PyFuncData *)func;
int nin = data->nin;
int nout = data->nout;
PyObject *tocall = data->callable;
char *ptrs[NPY_MAXARGS];
PyObject *arglist, *result;
PyObject *in, **op;
npy_intp i, j, ntot;
ntot = nin+nout;
for(j = 0; j < ntot; j++) {
ptrs[j] = args[j];
}
for(i = 0; i < n; i++) {
arglist = PyTuple_New(nin);
if (arglist == NULL) {
return;
}
for(j = 0; j < nin; j++) {
in = *((PyObject **)ptrs[j]);
if (in == NULL) {
in = Py_None;
}
PyTuple_SET_ITEM(arglist, j, in);
Py_INCREF(in);
}
result = PyObject_CallObject(tocall, arglist);
Py_DECREF(arglist);
if (result == NULL) {
return;
}
if (nout == 0 && result == Py_None) {
/* No output expected, no output received, continue */
Py_DECREF(result);
}
else if (nout == 1) {
/* Single output expected, assign and continue */
op = (PyObject **)ptrs[nin];
Py_XDECREF(*op);
*op = result;
}
else if (PyTuple_Check(result) && nout == PyTuple_Size(result)) {
/*
* Multiple returns match expected number of outputs, assign
* and continue. Will also gobble empty tuples if nout == 0.
*/
for(j = 0; j < nout; j++) {
op = (PyObject **)ptrs[j+nin];
Py_XDECREF(*op);
*op = PyTuple_GET_ITEM(result, j);
Py_INCREF(*op);
}
Py_DECREF(result);
}
else {
/* Mismatch between returns and expected outputs, exit */
Py_DECREF(result);
return;
}
for(j = 0; j < ntot; j++) {
ptrs[j] += steps[j];
}
}
}
/*
*****************************************************************************
** BOOLEAN LOOPS **
*****************************************************************************
*/
/**begin repeat
* #kind = equal, not_equal, greater, greater_equal, less, less_equal#
* #OP = ==, !=, >, >=, <, <=#
**/
NPY_NO_EXPORT void
BOOL_@kind@(char **args, npy_intp const *dimensions, npy_intp const *steps, void *NPY_UNUSED(func))
{
BINARY_LOOP {
npy_bool in1 = *((npy_bool *)ip1) != 0;
npy_bool in2 = *((npy_bool *)ip2) != 0;
*((npy_bool *)op1)= in1 @OP@ in2;
}
}
/**end repeat**/
/**begin repeat
* #kind = logical_and, logical_or#
* #OP = &&, ||#
* #SC = ==, !=#
* #and = 1, 0#
**/
NPY_NO_EXPORT void
BOOL_@kind@(char **args, npy_intp const *dimensions, npy_intp const *steps, void *NPY_UNUSED(func))
{
if(IS_BINARY_REDUCE) {
#ifdef NPY_HAVE_SSE2_INTRINSICS
/*
* stick with our variant for more reliable performance, only known
* platform which outperforms it by ~20% is an i7 with glibc 2.17
*/
if (run_reduce_simd_@kind@_BOOL(args, dimensions, steps)) {
return;
}
#else
/* for now only use libc on 32-bit/non-x86 */
if (steps[1] == 1) {
npy_bool * op = (npy_bool *)args[0];
#if @and@
/* np.all(), search for a zero (false) */
if (*op) {
*op = memchr(args[1], 0, dimensions[0]) == NULL;
}
#else
/*
* np.any(), search for a non-zero (true) via comparing against
* zero blocks, memcmp is faster than memchr on SSE4 machines
* with glibc >= 2.12 and memchr can only check for equal 1
*/
static const npy_bool zero[4096]; /* zero by C standard */
npy_uintp i, n = dimensions[0];
for (i = 0; !*op && i < n - (n % sizeof(zero)); i += sizeof(zero)) {
*op = memcmp(&args[1][i], zero, sizeof(zero)) != 0;
}
if (!*op && n - i > 0) {
*op = memcmp(&args[1][i], zero, n - i) != 0;
}
#endif
return;
}
#endif
else {
BINARY_REDUCE_LOOP(npy_bool) {
const npy_bool in2 = *(npy_bool *)ip2;
io1 = io1 @OP@ in2;
if (io1 @SC@ 0) {
break;
}
}
*((npy_bool *)iop1) = io1;
}
}
else {
if (run_binary_simd_@kind@_BOOL(args, dimensions, steps)) {
return;
}
else {
BINARY_LOOP {
const npy_bool in1 = *(npy_bool *)ip1;
const npy_bool in2 = *(npy_bool *)ip2;
*((npy_bool *)op1) = in1 @OP@ in2;
}
}
}
}
/**end repeat**/
/**begin repeat
* #kind = absolute, logical_not#
* #OP = !=, ==#
**/
NPY_NO_EXPORT void
BOOL_@kind@(char **args, npy_intp const *dimensions, npy_intp const *steps, void *NPY_UNUSED(func))
{
if (run_unary_simd_@kind@_BOOL(args, dimensions, steps)) {
return;
}
else {
UNARY_LOOP {
npy_bool in1 = *(npy_bool *)ip1;
*((npy_bool *)op1) = in1 @OP@ 0;
}
}
}
/**end repeat**/
NPY_NO_EXPORT void
BOOL__ones_like(char **args, npy_intp const *dimensions, npy_intp const *steps, void *NPY_UNUSED(data))
{
OUTPUT_LOOP {
*((npy_bool *)op1) = 1;
}
}
/**begin repeat
* #kind = isnan, isinf, isfinite#
* #func = npy_isnan, npy_isinf, npy_isfinite#
* #val = NPY_FALSE, NPY_FALSE, NPY_TRUE#
**/
NPY_NO_EXPORT void
BOOL_@kind@(char **args, npy_intp const *dimensions, npy_intp const *steps, void *NPY_UNUSED(func))
{
/*
* The (void)in; suppresses an unused variable warning raised by gcc and allows
* us to re-use this macro even though we do not depend on in
*/
UNARY_LOOP_FAST(npy_bool, npy_bool, (void)in; *out = @val@);
}
/**end repeat**/
/*
*****************************************************************************
** INTEGER LOOPS
*****************************************************************************
*/
/**begin repeat
* #TYPE = BYTE, UBYTE, SHORT, USHORT, INT, UINT,
* LONG, ULONG, LONGLONG, ULONGLONG#
* #type = npy_byte, npy_ubyte, npy_short, npy_ushort, npy_int, npy_uint,
* npy_long, npy_ulong, npy_longlong, npy_ulonglong#
* #ftype = npy_float, npy_float, npy_float, npy_float, npy_double, npy_double,
* npy_double, npy_double, npy_double, npy_double#
* #SIGNED = 1, 0, 1, 0, 1, 0, 1, 0, 1, 0#
* #c = hh,uhh,h,uh,,u,l,ul,ll,ull#
*/
#define @TYPE@_floor_divide @TYPE@_divide
#define @TYPE@_fmax @TYPE@_maximum
#define @TYPE@_fmin @TYPE@_minimum
NPY_NO_EXPORT void
@TYPE@__ones_like(char **args, npy_intp const *dimensions, npy_intp const *steps, void *NPY_UNUSED(data))
{
OUTPUT_LOOP {
*((@type@ *)op1) = 1;
}
}
NPY_NO_EXPORT void
@TYPE@_positive(char **args, npy_intp const *dimensions, npy_intp const *steps, void *NPY_UNUSED(func))
{
UNARY_LOOP_FAST(@type@, @type@, *out = +in);
}
/**begin repeat1
* #isa = , _avx2#
* #ISA = , AVX2#
* #CHK = 1, defined(HAVE_ATTRIBUTE_TARGET_AVX2)#
* #ATTR = , NPY_GCC_TARGET_AVX2#
*/
#if @CHK@
NPY_NO_EXPORT NPY_GCC_OPT_3 @ATTR@ void
@TYPE@_square@isa@(char **args, npy_intp const *dimensions, npy_intp const *steps, void *NPY_UNUSED(data))
{
UNARY_LOOP_FAST(@type@, @type@, *out = in * in);
}
#endif
#if @CHK@
NPY_NO_EXPORT NPY_GCC_OPT_3 @ATTR@ void
@TYPE@_reciprocal@isa@(char **args, npy_intp const *dimensions, npy_intp const *steps, void *NPY_UNUSED(data))
{
UNARY_LOOP_FAST(@type@, @type@, *out = 1.0 / in);
}
#endif
#if @CHK@
NPY_NO_EXPORT NPY_GCC_OPT_3 @ATTR@ void
@TYPE@_conjugate@isa@(char **args, npy_intp const *dimensions, npy_intp const *steps, void *NPY_UNUSED(func))
{
UNARY_LOOP_FAST(@type@, @type@, *out = in);
}
#endif
#if @CHK@
NPY_NO_EXPORT NPY_GCC_OPT_3 @ATTR@ void
@TYPE@_negative@isa@(char **args, npy_intp const *dimensions, npy_intp const *steps, void *NPY_UNUSED(func))
{
UNARY_LOOP_FAST(@type@, @type@, *out = -in);
}
#endif
#if @CHK@
NPY_NO_EXPORT NPY_GCC_OPT_3 @ATTR@ void
@TYPE@_logical_not@isa@(char **args, npy_intp const *dimensions, npy_intp const *steps, void *NPY_UNUSED(func))
{
UNARY_LOOP_FAST(@type@, npy_bool, *out = !in);
}
#endif
#if @CHK@
NPY_NO_EXPORT NPY_GCC_OPT_3 @ATTR@ void
@TYPE@_invert@isa@(char **args, npy_intp const *dimensions, npy_intp const *steps, void *NPY_UNUSED(func))
{
UNARY_LOOP_FAST(@type@, @type@, *out = ~in);
}
#endif
/**begin repeat2
* Arithmetic
* #kind = add, subtract, multiply, bitwise_and, bitwise_or, bitwise_xor#
* #OP = +, -, *, &, |, ^#
*/
#if @CHK@
NPY_NO_EXPORT NPY_GCC_OPT_3 @ATTR@ void
@TYPE@_@kind@@isa@(char **args, npy_intp const *dimensions, npy_intp const *steps, void *NPY_UNUSED(func))
{
if (IS_BINARY_REDUCE) {
BINARY_REDUCE_LOOP(@type@) {
io1 @OP@= *(@type@ *)ip2;
}
*((@type@ *)iop1) = io1;
}
else {
BINARY_LOOP_FAST(@type@, @type@, *out = in1 @OP@ in2);
}
}
#endif
/**end repeat2**/
/*
* Arithmetic bit shift operations.
*
* Intel hardware masks bit shift values, so large shifts wrap around
* and can produce surprising results. The special handling ensures that
* behavior is independent of compiler or hardware.
* TODO: We could implement consistent behavior for negative shifts,
* which is undefined in C.
*/
#define INT_left_shift_needs_clear_floatstatus
#define UINT_left_shift_needs_clear_floatstatus
NPY_NO_EXPORT NPY_GCC_OPT_3 void
@TYPE@_left_shift@isa@(char **args, npy_intp const *dimensions, npy_intp const *steps,
void *NPY_UNUSED(func))
{
BINARY_LOOP_FAST(@type@, @type@, *out = npy_lshift@c@(in1, in2));
#ifdef @TYPE@_left_shift_needs_clear_floatstatus
// For some reason, our macOS CI sets an "invalid" flag here, but only
// for some types.
npy_clear_floatstatus_barrier((char*)dimensions);
#endif
}
#undef INT_left_shift_needs_clear_floatstatus
#undef UINT_left_shift_needs_clear_floatstatus
NPY_NO_EXPORT
#ifndef NPY_DO_NOT_OPTIMIZE_@TYPE@_right_shift
NPY_GCC_OPT_3
#endif
void
@TYPE@_right_shift@isa@(char **args, npy_intp const *dimensions, npy_intp const *steps,
void *NPY_UNUSED(func))
{
BINARY_LOOP_FAST(@type@, @type@, *out = npy_rshift@c@(in1, in2));
}
/**begin repeat2
* #kind = equal, not_equal, greater, greater_equal, less, less_equal,
* logical_and, logical_or#
* #OP = ==, !=, >, >=, <, <=, &&, ||#
*/
#if @CHK@
NPY_NO_EXPORT NPY_GCC_OPT_3 @ATTR@ void
@TYPE@_@kind@@isa@(char **args, npy_intp const *dimensions, npy_intp const *steps, void *NPY_UNUSED(func))
{
/*
* gcc vectorization of this is not good (PR60575) but manual integer
* vectorization is too tedious to be worthwhile
*/
BINARY_LOOP_FAST(@type@, npy_bool, *out = in1 @OP@ in2);
}
#endif
/**end repeat2**/
#if @CHK@
NPY_NO_EXPORT NPY_GCC_OPT_3 @ATTR@ void
@TYPE@_logical_xor@isa@(char **args, npy_intp const *dimensions, npy_intp const *steps, void *NPY_UNUSED(func))
{
BINARY_LOOP {
const int t1 = !!*(@type@ *)ip1;
const int t2 = !!*(@type@ *)ip2;
*((npy_bool *)op1) = (t1 != t2);
}
}
#endif
/**end repeat1**/
/**begin repeat1
* #kind = maximum, minimum#
* #OP = >, <#
**/
NPY_NO_EXPORT void
@TYPE@_@kind@(char **args, npy_intp const *dimensions, npy_intp const *steps, void *NPY_UNUSED(func))
{
if (IS_BINARY_REDUCE) {
BINARY_REDUCE_LOOP(@type@) {
const @type@ in2 = *(@type@ *)ip2;
io1 = (io1 @OP@ in2) ? io1 : in2;
}
*((@type@ *)iop1) = io1;
}
else {
BINARY_LOOP {
const @type@ in1 = *(@type@ *)ip1;
const @type@ in2 = *(@type@ *)ip2;
*((@type@ *)op1) = (in1 @OP@ in2) ? in1 : in2;
}
}
}
/**end repeat1**/
NPY_NO_EXPORT void
@TYPE@_power(char **args, npy_intp const *dimensions, npy_intp const *steps, void *NPY_UNUSED(func))
{
BINARY_LOOP {
@type@ in1 = *(@type@ *)ip1;
@type@ in2 = *(@type@ *)ip2;
@type@ out;
#if @SIGNED@
if (in2 < 0) {
NPY_ALLOW_C_API_DEF
NPY_ALLOW_C_API;
PyErr_SetString(PyExc_ValueError,
"Integers to negative integer powers are not allowed.");
NPY_DISABLE_C_API;
return;
}
#endif
if (in2 == 0) {
*((@type@ *)op1) = 1;
continue;
}
if (in1 == 1) {
*((@type@ *)op1) = 1;
continue;
}
out = in2 & 1 ? in1 : 1;
in2 >>= 1;
while (in2 > 0) {
in1 *= in1;
if (in2 & 1) {
out *= in1;
}
in2 >>= 1;
}
*((@type@ *) op1) = out;
}
}
NPY_NO_EXPORT void
@TYPE@_fmod(char **args, npy_intp const *dimensions, npy_intp const *steps, void *NPY_UNUSED(func))
{
BINARY_LOOP {
const @type@ in1 = *(@type@ *)ip1;
const @type@ in2 = *(@type@ *)ip2;
if (in2 == 0) {
npy_set_floatstatus_divbyzero();
*((@type@ *)op1) = 0;
}
else {
*((@type@ *)op1)= in1 % in2;
}
}
}
/**begin repeat1
* #kind = isnan, isinf, isfinite#
* #func = npy_isnan, npy_isinf, npy_isfinite#
* #val = NPY_FALSE, NPY_FALSE, NPY_TRUE#
**/
NPY_NO_EXPORT void
@TYPE@_@kind@(char **args, npy_intp const *dimensions, npy_intp const *steps, void *NPY_UNUSED(func))
{
/*
* The (void)in; suppresses an unused variable warning raised by gcc and allows
* us to re-use this macro even though we do not depend on in
*/
UNARY_LOOP_FAST(@type@, npy_bool, (void)in; *out = @val@);
}
/**end repeat1**/
/**end repeat**/
/**begin repeat
* #TYPE = BYTE, SHORT, INT, LONG, LONGLONG#
* #type = npy_byte, npy_short, npy_int, npy_long, npy_longlong#
* #c = ,,,l,ll#
*/
NPY_NO_EXPORT NPY_GCC_OPT_3 void
@TYPE@_absolute(char **args, npy_intp const *dimensions, npy_intp const *steps, void *NPY_UNUSED(func))
{
UNARY_LOOP_FAST(@type@, @type@, *out = (in >= 0) ? in : -in);
}
NPY_NO_EXPORT NPY_GCC_OPT_3 void
@TYPE@_sign(char **args, npy_intp const *dimensions, npy_intp const *steps, void *NPY_UNUSED(func))
{
UNARY_LOOP_FAST(@type@, @type@, *out = in > 0 ? 1 : (in < 0 ? -1 : 0));
}
/* Libdivide only supports 32 and 64 bit types
* We try to pick the best possible one */
#if NPY_BITSOF_@TYPE@ <= 32
#define libdivide_@type@_t libdivide_s32_t
#define libdivide_@type@_gen libdivide_s32_gen
#define libdivide_@type@_do libdivide_s32_do
#else
#define libdivide_@type@_t libdivide_s64_t
#define libdivide_@type@_gen libdivide_s64_gen
#define libdivide_@type@_do libdivide_s64_do
#endif
NPY_NO_EXPORT void
@TYPE@_divide(char **args, npy_intp const *dimensions, npy_intp const *steps, void *NPY_UNUSED(func))
{
BINARY_DEFS
/* When the divisor is a constant, use libdivide for faster division */
if (steps[1] == 0) {
/* In case of empty array, just return */
if (n == 0) {
return;
}
const @type@ in2 = *(@type@ *)ip2;
/* If divisor is 0, we need not compute anything */
if (in2 == 0) {
npy_set_floatstatus_divbyzero();
BINARY_LOOP_SLIDING {
*((@type@ *)op1) = 0;
}
}
else {
struct libdivide_@type@_t fast_d = libdivide_@type@_gen(in2);
BINARY_LOOP_SLIDING {
const @type@ in1 = *(@type@ *)ip1;
/*
* FIXME: On x86 at least, dividing the smallest representable integer
* by -1 causes a SIFGPE (division overflow). We treat this case here
* (to avoid a SIGFPE crash at python level), but a good solution would
* be to treat integer division problems separately from FPU exceptions
* (i.e. a different approach than npy_set_floatstatus_divbyzero()).
*/
if (in1 == NPY_MIN_@TYPE@ && in2 == -1) {
npy_set_floatstatus_divbyzero();
*((@type@ *)op1) = 0;
}
else {
*((@type@ *)op1) = libdivide_@type@_do(in1, &fast_d);
/* Negative quotients needs to be rounded down */
if (((in1 > 0) != (in2 > 0)) && (*((@type@ *)op1) * in2 != in1)) {
*((@type@ *)op1) = *((@type@ *)op1) - 1;
}
}
}
}
}
else {
BINARY_LOOP_SLIDING {
const @type@ in1 = *(@type@ *)ip1;
const @type@ in2 = *(@type@ *)ip2;
/*
* FIXME: On x86 at least, dividing the smallest representable integer
* by -1 causes a SIFGPE (division overflow). We treat this case here
* (to avoid a SIGFPE crash at python level), but a good solution would
* be to treat integer division problems separately from FPU exceptions
* (i.e. a different approach than npy_set_floatstatus_divbyzero()).
*/
if (in2 == 0 || (in1 == NPY_MIN_@TYPE@ && in2 == -1)) {
npy_set_floatstatus_divbyzero();
*((@type@ *)op1) = 0;
}
else {
*((@type@ *)op1) = in1/in2;
/* Negative quotients needs to be rounded down */
if (((in1 > 0) != (in2 > 0)) && (*((@type@ *)op1) * in2 != in1)) {
*((@type@ *)op1) = *((@type@ *)op1) - 1;
}
}
}
}
}
NPY_NO_EXPORT void
@TYPE@_remainder(char **args, npy_intp const *dimensions, npy_intp const *steps, void *NPY_UNUSED(func))
{
BINARY_LOOP {
const @type@ in1 = *(@type@ *)ip1;
const @type@ in2 = *(@type@ *)ip2;
if (in2 == 0) {
npy_set_floatstatus_divbyzero();
*((@type@ *)op1) = 0;
}
else {
/* handle mixed case the way Python does */
const @type@ rem = in1 % in2;
if ((in1 > 0) == (in2 > 0) || rem == 0) {
*((@type@ *)op1) = rem;
}
else {
*((@type@ *)op1) = rem + in2;
}
}
}
}
NPY_NO_EXPORT void
@TYPE@_divmod(char **args, npy_intp const *dimensions, npy_intp const *steps, void *NPY_UNUSED(func))
{
BINARY_LOOP_TWO_OUT {
const @type@ in1 = *(@type@ *)ip1;
const @type@ in2 = *(@type@ *)ip2;
/* see FIXME note for divide above */
if (in2 == 0 || (in1 == NPY_MIN_@TYPE@ && in2 == -1)) {
npy_set_floatstatus_divbyzero();
*((@type@ *)op1) = 0;
*((@type@ *)op2) = 0;
}
else {
/* handle mixed case the way Python does */
const @type@ quo = in1 / in2;
const @type@ rem = in1 % in2;
if ((in1 > 0) == (in2 > 0) || rem == 0) {
*((@type@ *)op1) = quo;
*((@type@ *)op2) = rem;
}
else {
*((@type@ *)op1) = quo - 1;
*((@type@ *)op2) = rem + in2;
}
}
}
}
/**begin repeat1
* #kind = gcd, lcm#
**/
NPY_NO_EXPORT void
@TYPE@_@kind@(char **args, npy_intp const *dimensions, npy_intp const *steps, void *NPY_UNUSED(func))
{
BINARY_LOOP {
const @type@ in1 = *(@type@ *)ip1;
const @type@ in2 = *(@type@ *)ip2;
*((@type@ *)op1) = npy_@kind@@c@(in1, in2);
}
}
/**end repeat1**/
/**end repeat**/
/**begin repeat
* #TYPE = UBYTE, USHORT, UINT, ULONG, ULONGLONG#