ccv_nnc_8i_rowwise.c

Bug Summary

File:	nnc/ccv_nnc_8i_rowwise.c
Warning:	line 2077, column 38 The left operand of '/' is a garbage value
Annotated Source Code

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clang -cc1 -cc1 -triple x86_64-unknown-linux-gnu -analyze -disable-free -clear-ast-before-backend -disable-llvm-verifier -discard-value-names -main-file-name ccv_nnc_8i_rowwise.c -analyzer-checker=core -analyzer-checker=apiModeling -analyzer-checker=unix -analyzer-checker=deadcode -analyzer-checker=security.insecureAPI.UncheckedReturn -analyzer-checker=security.insecureAPI.getpw -analyzer-checker=security.insecureAPI.gets -analyzer-checker=security.insecureAPI.mktemp -analyzer-checker=security.insecureAPI.mkstemp -analyzer-checker=security.insecureAPI.vfork -analyzer-checker=nullability.NullPassedToNonnull -analyzer-checker=nullability.NullReturnedFromNonnull -analyzer-output plist -w -setup-static-analyzer -mrelocation-model pic -pic-level 2 -pic-is-pie -mframe-pointer=none -fmath-errno -ffp-contract=on -fno-rounding-math -mconstructor-aliases -funwind-tables=2 -target-cpu x86-64 -target-feature +sse2 -tune-cpu generic -debugger-tuning=gdb -fdebug-compilation-dir=/home/liu/actions-runner/_work/ccv/ccv/lib/nnc -fcoverage-compilation-dir=/home/liu/actions-runner/_work/ccv/ccv/lib/nnc -resource-dir /usr/local/lib/clang/19 -I ../ -I /usr/local/cuda/include -D HAVE_CBLAS -D HAVE_LIBPNG -D HAVE_LIBJPEG -D HAVE_FFTW3 -D HAVE_PTHREAD -D HAVE_LIBLINEAR -D HAVE_TESSERACT -D HAVE_AVCODEC -D HAVE_AVFORMAT -D HAVE_AVUTIL -D HAVE_SWSCALE -D HAVE_SSE2 -D HAVE_GSL -D HAVE_CUDA -D HAVE_CUDNN -D HAVE_NCCL -D USE_SYSTEM_CUB -I /usr/local/include -internal-isystem /usr/local/lib/clang/19/include -internal-isystem /usr/local/include -internal-isystem /usr/lib/gcc/x86_64-linux-gnu/12/../../../../x86_64-linux-gnu/include -internal-externc-isystem /usr/include/x86_64-linux-gnu -internal-externc-isystem /include -internal-externc-isystem /usr/include -O3 -ferror-limit 19 -fgnuc-version=4.2.1 -fskip-odr-check-in-gmf -vectorize-loops -vectorize-slp -analyzer-output=html -faddrsig -D__GCC_HAVE_DWARF2_CFI_ASM=1 -o /home/liu/actions-runner/_work/ccv/ccv/_analyze/2026-10-29-182601-401862-1 -x c ccv_nnc_8i_rowwise.c
1#include "ccv_nnc.h"
2#include "ccv_nnc_internal.h"
3#include "ccv_nnc_easy.h"
4#include <float.h>
5#include <limits.h>
6#if HAVE_ACCELERATE_FRAMEWORK
7#include <Accelerate/Accelerate.h>
8#elif HAVE_CBLAS1
9#include <cblas.h>
10#endif
11#include "ccv_nnc_8i_rowwise_packed_grids.inc"
12#ifdef USE_DISPATCH
13#include <dispatch/dispatch.h>
14#endif
15#ifdef HAVE_CUDA1
16#include "gpu/ccv_nnc_compat.h"
17#elif defined(HAVE_MPS)
18#include "mps/ccv_nnc_mps.h"
19#endif

21enum {
CCV_NNC_8I_ROWWISE_X_REFINEMENT_STEPS = 8,
CCV_NNC_8I_ROWWISE_IQ2_CANDIDATES = 16,
CCV_NNC_8I_ROWWISE_IQ3_CANDIDATES = 24,
CCV_NNC_8I_ROWWISE_X_FEEDBACK_ROWS = 32,
CCV_NNC_8I_ROWWISE_X_CHOLESKY_PANEL = 64,
27};

29static size_t _ccv_nnc_8i_rowwise_packed_scale_offset(const int format, const size_t input_length, const size_t row_length)
30{
assert(row_length > 0)((void) sizeof ((row_length > 0) ? 1 : 0), __extension__ (
{ if (row_length > 0) ; else __assert_fail ("row_length > 0"
, "ccv_nnc_8i_rowwise.c", 31, __extension__ __PRETTY_FUNCTION__
); }));
assert(input_length % row_length == 0)((void) sizeof ((input_length % row_length == 0) ? 1 : 0), __extension__
 ({ if (input_length % row_length == 0) ; else __assert_fail (
"input_length % row_length == 0", "ccv_nnc_8i_rowwise.c", 32,
 __extension__ __PRETTY_FUNCTION__); }));
const size_t row_count = input_length / row_length;
const size_t group_size = ccv_nnc_8i_rowwise_x_group_size(format);
const size_t groups_per_row = (row_length + group_size - 1) / group_size;
const size_t group_bits = ccv_nnc_8i_rowwise_x_group_bits(format);
const size_t payload_size = (row_count * groups_per_row * group_bits + 7) / 8;
return (payload_size + 127) & -128;
39}

41CCV_WARN_UNUSED(size_t)size_t __attribute__((warn_unused_result)) ccv_nnc_8i_rowwise_x_data_size(const int format, const int datatype, const size_t input_length, const size_t row_length)
42{
if (row_length == 0 || input_length % row_length != 0 ||
((format & CCV_NNC_QX_8I_ROWWISE_HADAMARD_256) && row_length % 256 != 0))
return 0;
assert(datatype == CCV_16F || datatype == CCV_16BF || datatype == CCV_32F || datatype == CCV_64F)((void) sizeof ((datatype == CCV_16F || datatype == CCV_16BF ||
 datatype == CCV_32F || datatype == CCV_64F) ? 1 : 0), __extension__
 ({ if (datatype == CCV_16F || datatype == CCV_16BF || datatype
 == CCV_32F || datatype == CCV_64F) ; else __assert_fail ("datatype == CCV_16F || datatype == CCV_16BF || datatype == CCV_32F || datatype == CCV_64F"
, "ccv_nnc_8i_rowwise.c", 46, __extension__ __PRETTY_FUNCTION__
); }));
assert(row_length > 0)((void) sizeof ((row_length > 0) ? 1 : 0), __extension__ (
{ if (row_length > 0) ; else __assert_fail ("row_length > 0"
, "ccv_nnc_8i_rowwise.c", 47, __extension__ __PRETTY_FUNCTION__
); }));
assert(input_length % row_length == 0)((void) sizeof ((input_length % row_length == 0) ? 1 : 0), __extension__
 ({ if (input_length % row_length == 0) ; else __assert_fail (
"input_length % row_length == 0", "ccv_nnc_8i_rowwise.c", 48,
 __extension__ __PRETTY_FUNCTION__); }));
const size_t row_count = input_length / row_length;
const size_t scale_offset = _ccv_nnc_8i_rowwise_packed_scale_offset(format, input_length, row_length);
return scale_offset + row_count * CCV_GET_DATA_TYPE_SIZE(datatype)_ccv_get_data_type_size[((datatype) & 0xFF000) >> 12
];
52}

54static void _ccv_nnc_8i_rowwise_packed_write_bits(uint8_t* const data, const size_t bit_offset, const uint32_t value, const int bits)
55{
int i;
for (i = 0; i < bits; i++)
if (value & (1u << i))
	data[(bit_offset + i) >> 3] |= (uint8_t)(1u << ((bit_offset + i) & 7));
60}

62static uint32_t _ccv_nnc_8i_rowwise_packed_read_bits(const uint8_t* const data, const size_t bit_offset, const int bits)
63{
uint32_t value = 0;
int i;
for (i = 0; i < bits; i++)
if (data[(bit_offset + i) >> 3] & (uint8_t)(1u << ((bit_offset + i) & 7)))
	value |= (1u << i);
return value;
70}

72static inline int _ccv_nnc_8i_rowwise_packed_sign_extend(const uint32_t value, const int bits)
73{
const uint32_t sign = 1u << (bits - 1);
return (value & sign) ? (int)value - (int)(1u << bits) : (int)value;
76}

78static inline int _ccv_nnc_8i_rowwise_packed_floor_div(const int numerator, const int denominator)
79{
assert(denominator > 0)((void) sizeof ((denominator > 0) ? 1 : 0), __extension__ (
{ if (denominator > 0) ; else __assert_fail ("denominator > 0"
, "ccv_nnc_8i_rowwise.c", 80, __extension__ __PRETTY_FUNCTION__
); }));
return numerator >= 0 ? numerator / denominator : -((-numerator + denominator - 1) / denominator);
82}

84static inline int _ccv_nnc_8i_rowwise_packed_ceil_div(const int numerator, const int denominator)
85{
assert(denominator > 0)((void) sizeof ((denominator > 0) ? 1 : 0), __extension__ (
{ if (denominator > 0) ; else __assert_fail ("denominator > 0"
, "ccv_nnc_8i_rowwise.c", 86, __extension__ __PRETTY_FUNCTION__
); }));
return numerator >= 0 ? (numerator + denominator - 1) / denominator : -((-numerator) / denominator);
88}

90static double _ccv_nnc_8i_rowwise_packed_stored_scale(const double scale, const int datatype)
91{
if (datatype == CCV_16F)
{
const float scale_f = (float)scale;
uint16_t scale_h;
float stored_scale;
ccv_float_to_half_precision(&scale_f, &scale_h, 1);
ccv_half_precision_to_float(&scale_h, &stored_scale, 1);
return stored_scale;
} else if (datatype == CCV_16BF) {
const float scale_f = (float)scale;
uint16_t scale_bf;
float stored_scale;
ccv_float_to_bfloat(&scale_f, &scale_bf, 1);
ccv_bfloat_to_float(&scale_bf, &stored_scale, 1);
return stored_scale;
} else if (datatype == CCV_32F)
return (float)scale;
return scale;
110}

112static void _ccv_nnc_8i_rowwise_packed_store_scale(uint8_t* const scales, const int datatype, const size_t i, const double scale)
113{
if (datatype == CCV_16F)
{
const float scale_f = (float)scale;
ccv_float_to_half_precision(&scale_f, (uint16_t*)scales + i, 1);
} else if (datatype == CCV_16BF) {
const float scale_f = (float)scale;
ccv_float_to_bfloat(&scale_f, (uint16_t*)scales + i, 1);
} else if (datatype == CCV_32F)
((float*)scales)[i] = (float)scale;
else
((double*)scales)[i] = scale;
125}

127static double _ccv_nnc_8i_rowwise_packed_load_scale(const uint8_t* const scales, const int datatype, const size_t i)
128{
if (datatype == CCV_16F)
{
float scale_f;
ccv_half_precision_to_float((const uint16_t*)scales + i, &scale_f, 1);
return scale_f;
} else if (datatype == CCV_16BF) {
float scale_f;
ccv_bfloat_to_float((const uint16_t*)scales + i, &scale_f, 1);
return scale_f;
} else if (datatype == CCV_32F)
return ((const float*)scales)[i];
return ((const double*)scales)[i];
141}

143static void _ccv_nnc_8i_rowwise_packed_read_row(const void* const input, const int datatype, const size_t row_start, const size_t row_length, const size_t padded_row_length, double* const row)
144{
size_t j;
if (datatype42.1
'datatype' is not equal to CCV_16F
 == CCV_16F)
43
←
Taking false branch→
{
const uint16_t* const f16 = (const uint16_t*)input + row_start;
for (j = 0; j < row_length; j++)
{
	float v;
	ccv_half_precision_to_float(f16 + j, &v, 1);
	row[j] = v;
}
} else if (datatype43.1
'datatype' is not equal to CCV_16BF
 == CCV_16BF) {
44
←
Taking false branch→
const uint16_t* const bf16 = (const uint16_t*)input + row_start;
for (j = 0; j < row_length; j++)
{
	float v;
	ccv_bfloat_to_float(bf16 + j, &v, 1);
	row[j] = v;
}
} else if (datatype44.1
'datatype' is not equal to CCV_32F
 == CCV_32F) {
45
←
Taking false branch→
const float* const f32 = (const float*)input + row_start;
for (j = 0; j < row_length; j++)
	row[j] = f32[j];
} else {
const double* const f64 = (const double*)input + row_start;
for (j = 0; j45.1
'j' is < 'row_length'
 < row_length; j++)
46
←
Loop condition is true.  Entering loop body→
47
←
Assuming 'j' is >= 'row_length'→
48
←
Loop condition is false. Execution continues on line 172→
	row[j] = f64[j];
}
for (; j < padded_row_length; j++)
49
←
Assuming 'j' is >= 'padded_row_length'→
50
←
Loop condition is false. Execution continues on line 172→
row[j] = 0;
174}

176static void _ccv_nnc_8i_rowwise_packed_write_value(void* const output, const int datatype, const size_t j, const double v)
177{
if (datatype == CCV_16F)
{
const float v_f = (float)v;
ccv_float_to_half_precision(&v_f, (uint16_t*)output + j, 1);
} else if (datatype == CCV_16BF) {
const float v_f = (float)v;
ccv_float_to_bfloat(&v_f, (uint16_t*)output + j, 1);
} else if (datatype == CCV_32F)
((float*)output)[j] = (float)v;
else
((double*)output)[j] = v;
189}

191static inline double _ccv_nnc_8i_rowwise_weight(const float* const imatrix, const size_t j)
192{
return imatrix ? ccv_max((double)imatrix[j], 0.)({ typeof ((double)imatrix[j]) _a = ((double)imatrix[j]); typeof
 (0.) _b = (0.); (_a > _b) ? _a : _b; }) : 1.;
194}

196static inline int _ccv_nnc_8i_rowwise_imatrix_is_valid(const float* const imatrix, const size_t imatrix_length, const size_t row_length, const size_t row_count)
197{
if (!imatrix)
return 1;
if (imatrix_length < row_length || imatrix_length % row_length != 0)
return 0;
const size_t imatrix_slices = imatrix_length / row_length;
return imatrix_slices > 0 && row_count % imatrix_slices == 0;
204}

206static inline const float* _ccv_nnc_8i_rowwise_imatrix_for_row(const float* const imatrix, const size_t imatrix_length, const size_t row_length, const size_t row_count, const size_t row_idx)
207{
if (!imatrix)
return 0;
const size_t imatrix_slices = imatrix_length / row_length;
if (imatrix_slices == 1)
return imatrix;
const size_t rows_per_slice = row_count / imatrix_slices;
return imatrix + (row_idx / rows_per_slice) * row_length;
215}

217typedef struct {
int q[32];
int q8[32];
int m;
int b;
int z;
int scale;
int grid[4];
uint32_t signs;
226} ccv_nnc_8i_rowwise_packed_group_t;

228static const int ccv_nnc_8i_rowwise_packed_iq1s_scales[8] = {1, 2, 3, 5, 7, 9, 12, 16};
229static const int ccv_nnc_8i_rowwise_packed_iq1_powers[8] = {1, 3, 9, 27, 81, 243, 729, 2187};

231typedef struct {
int lane;
int trit[3];
double cost[3];
235} ccv_nnc_8i_rowwise_iq1_lane_t;

237typedef struct {
ccv_nnc_8i_rowwise_iq1_lane_t lanes[8];
const int16_t* map;
double best;
int index;
242} ccv_nnc_8i_rowwise_iq1_search_t;

244static void _ccv_nnc_8i_rowwise_packed_iq1_search(ccv_nnc_8i_rowwise_iq1_search_t* const search, const int depth, const int code, const double cost)
245{
if (cost >= search->best)
return;
if (depth == 8)
{
if (search->map[code] >= 0)
{
	search->best = cost;
	search->index = search->map[code];
}
return;
}
const ccv_nnc_8i_rowwise_iq1_lane_t* const lane = search->lanes + depth;
int k;
for (k = 0; k < 3; k++)
{
const double next = cost + lane->cost[k];
if (next >= search->best)
	break;
_ccv_nnc_8i_rowwise_packed_iq1_search(search, depth + 1, code + lane->trit[k] * ccv_nnc_8i_rowwise_packed_iq1_powers[lane->lane], next);
}
266}

268static double _ccv_nnc_8i_rowwise_packed_iq1_nearest(const double* const y, const double* const w, const int m, const int shift, const int16_t* const map, int* const index)
269{
const int levels[3] = {ccv_max((-8 + shift) * m, -127)({ typeof ((-8 + shift) * m) _a = ((-8 + shift) * m); typeof (
-127) _b = (-127); (_a > _b) ? _a : _b; }), shift * m, ccv_min((8 + shift) * m, 127)({ typeof ((8 + shift) * m) _a = ((8 + shift) * m); typeof (127
) _b = (127); (_a < _b) ? _a : _b; })};
ccv_nnc_8i_rowwise_iq1_search_t search;
search.map = map;
double baseline = 0;
int natural_code = 0;
int j, k;
for (j = 0; j < 8; j++)
{
ccv_nnc_8i_rowwise_iq1_lane_t* const lane = search.lanes + j;
lane->lane = j;
for (k = 0; k < 3; k++)
{
	const double d = levels[k] - y[j];
	lane->trit[k] = k;
	lane->cost[k] = w[j] * d * d;
}
for (k = 1; k < 3; k++)
{
	int t;
	for (t = k; t > 0 && lane->cost[t] < lane->cost[t - 1]; t--)
	{
		const double cost = lane->cost[t];
		lane->cost[t] = lane->cost[t - 1];
		lane->cost[t - 1] = cost;
		const int trit = lane->trit[t];
		lane->trit[t] = lane->trit[t - 1];
		lane->trit[t - 1] = trit;
	}
}
natural_code += lane->trit[0] * ccv_nnc_8i_rowwise_packed_iq1_powers[j];
const double minimum = lane->cost[0];
baseline += minimum;
for (k = 0; k < 3; k++)
	lane->cost[k] -= minimum;
}
if (map[natural_code] >= 0)
{
*index = map[natural_code];
return baseline;
}
search.best = DBL_MAX1.7976931348623157e+308;
search.index = -1;
for (j = 0; j < 8; j++)
for (k = 1; k < 3; k++)
{
	const ccv_nnc_8i_rowwise_iq1_lane_t* const lane = search.lanes + j;
	const int code = natural_code + (lane->trit[k] - lane->trit[0]) * ccv_nnc_8i_rowwise_packed_iq1_powers[j];
	if (map[code] >= 0 && lane->cost[k] < search.best)
	{
		search.best = lane->cost[k];
		search.index = map[code];
	}
}
// Independent lane costs bound the exact search; put cheap changes last.
for (j = 1; j < 8; j++)
for (k = j; k > 0 && search.lanes[k].cost[1] > search.lanes[k - 1].cost[1]; k--)
{
	const ccv_nnc_8i_rowwise_iq1_lane_t lane = search.lanes[k];
	search.lanes[k] = search.lanes[k - 1];
	search.lanes[k - 1] = lane;
}
_ccv_nnc_8i_rowwise_packed_iq1_search(&search, 0, 0, 0);
assert(search.index >= 0)((void) sizeof ((search.index >= 0) ? 1 : 0), __extension__
 ({ if (search.index >= 0) ; else __assert_fail ("search.index >= 0"
, "ccv_nnc_8i_rowwise.c", 332, __extension__ __PRETTY_FUNCTION__
); }));
*index = search.index;
return baseline + search.best;
335}

337static void _ccv_nnc_8i_rowwise_packed_quant_iq1_m(const double* const y, const double* const w, const int16_t* const map, ccv_nnc_8i_rowwise_packed_group_t* const group)
338{
double best_sse = DBL_MAX1.7976931348623157e+308;
int m, sg, j;
for (m = 1; m <= 16; m++)
{
double sse = 0;
int grid[2];
uint32_t shifts = 0;
for (sg = 0; sg < 2; sg++)
{
	int index[2];
	const double plus = _ccv_nnc_8i_rowwise_packed_iq1_nearest(y + sg * 8, w + sg * 8, m, 1, map, index);
	const double minus = _ccv_nnc_8i_rowwise_packed_iq1_nearest(y + sg * 8, w + sg * 8, m, -1, map, index + 1);
	const int shift = minus < plus;
	sse += shift ? minus : plus;
	grid[sg] = index[shift];
	shifts |= (uint32_t)shift << sg;
}
if (sse < best_sse)
{
	best_sse = sse;
	group->scale = m;
	group->signs = shifts;
	memcpy(group->grid, grid, sizeof(grid));
}
}
for (sg = 0; sg < 2; sg++)
for (j = 0; j < 8; j++)
{
	const int g = (int)((ccv_nnc_8i_rowwise_packed_iq1_grid[group->grid[sg]] >> (2 * j)) & 3) - 1;
	const int shift = (group->signs & (1u << sg)) ? -1 : 1;
	group->q8[sg * 8 + j] = ccv_clamp(group->scale * (8 * g + shift), -127, 127)({ typeof (-127) _a = (-127); typeof (127) _b = (127); typeof
 (group->scale * (8 * g + shift)) _x = (group->scale * (
* g + shift)); (_x < _a) ? _a : ((_x > _b) ? _b : _x)
; });
}
371}

373static void _ccv_nnc_8i_rowwise_packed_quant_iq1_s(const double* const y, const double* const w, const int16_t* const map, ccv_nnc_8i_rowwise_packed_group_t* const group)
374{
double best_sse = DBL_MAX1.7976931348623157e+308;
int sc, sg, j;
for (sc = 0; sc < 8; sc++)
{
const int m = ccv_nnc_8i_rowwise_packed_iq1s_scales[sc];
double costs[4][2];
int indices[4][2];
for (sg = 0; sg < 4; sg++)
	for (j = 0; j < 2; j++)
		costs[sg][j] = _ccv_nnc_8i_rowwise_packed_iq1_nearest(y + sg * 8, w + sg * 8, m, j ? -1 : 1, map, &indices[sg][j]);
int mask;
for (mask = 0; mask < 16; mask++)
{
	if ((mask ^ (mask >> 1) ^ (mask >> 2) ^ (mask >> 3)) & 1)
		continue;
	double sse = 0;
	for (sg = 0; sg < 4; sg++)
		sse += costs[sg][(mask >> sg) & 1];
	if (sse < best_sse)
	{
		best_sse = sse;
		group->scale = sc;
		group->signs = (uint32_t)mask;
		for (sg = 0; sg < 4; sg++)
			group->grid[sg] = indices[sg][(mask >> sg) & 1];
	}
}
}
const int m = ccv_nnc_8i_rowwise_packed_iq1s_scales[group->scale];
for (sg = 0; sg < 4; sg++)
for (j = 0; j < 8; j++)
{
	const int g = (int)((ccv_nnc_8i_rowwise_packed_iq1_grid[group->grid[sg]] >> (2 * j)) & 3) - 1;
	const int shift = (group->signs & (1u << sg)) ? -1 : 1;
	group->q8[sg * 8 + j] = ccv_clamp(m * (8 * g + shift), -127, 127)({ typeof (-127) _a = (-127); typeof (127) _b = (127); typeof
 (m * (8 * g + shift)) _x = (m * (8 * g + shift)); (_x < _a
) ? _a : ((_x > _b) ? _b : _x); });
}
411}

413static void _ccv_nnc_8i_rowwise_packed_nearest_candidates(const uint8_t* const grid, const int grid_size, const int lanes, const int levels, const int code_count, const int candidate_count, uint16_t* const candidates)
414{
assert(candidate_count <= CCV_NNC_8I_ROWWISE_IQ3_CANDIDATES)((void) sizeof ((candidate_count <= CCV_NNC_8I_ROWWISE_IQ3_CANDIDATES
) ? 1 : 0), __extension__ ({ if (candidate_count <= CCV_NNC_8I_ROWWISE_IQ3_CANDIDATES
) ; else __assert_fail ("candidate_count <= CCV_NNC_8I_ROWWISE_IQ3_CANDIDATES"
, "ccv_nnc_8i_rowwise.c", 415, __extension__ __PRETTY_FUNCTION__
); }));
assert(candidate_count <= grid_size)((void) sizeof ((candidate_count <= grid_size) ? 1 : 0), __extension__
 ({ if (candidate_count <= grid_size) ; else __assert_fail
 ("candidate_count <= grid_size", "ccv_nnc_8i_rowwise.c", 416
, __extension__ __PRETTY_FUNCTION__); }));
int code;
for (code = 0; code < code_count; code++)
{
uint8_t target[8];
int value = code;
int j;
for (j = 0; j < lanes; j++)
{
	target[j] = (uint8_t)(value % levels);
	value /= levels;
}
int best_distance[CCV_NNC_8I_ROWWISE_IQ3_CANDIDATES];
int k;
for (k = 0; k < candidate_count; k++)
{
	best_distance[k] = INT_MAX2147483647;
	candidates[(size_t)code * candidate_count + k] = 0;
}
int index;
for (index = 0; index < grid_size; index++)
{
	int distance = 0;
	for (j = 0; j < lanes; j++)
	{
		const int d = (int)grid[(size_t)index * lanes + j] - target[j];
		distance += d * d;
	}
	if (distance >= best_distance[candidate_count - 1])
		continue;
	k = candidate_count - 1;
	while (k > 0 && distance < best_distance[k - 1])
	{
		best_distance[k] = best_distance[k - 1];
		candidates[(size_t)code * candidate_count + k] = candidates[(size_t)code * candidate_count + k - 1];
		--k;
	}
	best_distance[k] = distance;
	candidates[(size_t)code * candidate_count + k] = (uint16_t)index;
}
}
457}

459static void _ccv_nnc_8i_rowwise_packed_quant_q5(const double* const y, const double* const w, ccv_nnc_8i_rowwise_packed_group_t* const group)
460{
double best_sse = DBL_MAX1.7976931348623157e+308;
int best_q[16] = {0};
int best_q8[16] = {0};
int best_m = 1, best_b = 0;
int m, b, j;
for (m = 1; m <= 8; m++)
for (b = -16; b <= 15; b++)
{
	if (-16 * m + b < -127 || 15 * m + b > 127)
		continue;
	double sse = 0;
	int q[16];
	int q8[16];
	for (j = 0; j < 16; j++)
	{
		q[j] = ccv_clamp((int)lrint((y[j] - b) / m), -16, 15)({ typeof (-16) _a = (-16); typeof (15) _b = (15); typeof ((int
)lrint((y[j] - b) / m)) _x = ((int)lrint((y[j] - b) / m)); (_x
 < _a) ? _a : ((_x > _b) ? _b : _x); });
		q8[j] = q[j] * m + b;
		const double d = q8[j] - y[j];
		sse += w[j] * d * d;
	}
	if (sse < best_sse)
	{
		best_sse = sse;
		best_m = m;
		best_b = b;
		memcpy(best_q, q, sizeof(best_q));
		memcpy(best_q8, q8, sizeof(best_q8));
	}
}
group->m = best_m;
group->b = best_b;
memcpy(group->q, best_q, sizeof(best_q));
memcpy(group->q8, best_q8, sizeof(best_q8));
494}

496static void _ccv_nnc_8i_rowwise_packed_quant_q6(const double* const y, const double* const w, ccv_nnc_8i_rowwise_packed_group_t* const group)
497{
double best_sse = DBL_MAX1.7976931348623157e+308;
int best_q[8] = {0};
int best_q8[8] = {0};
int best_m = 1, best_b = 0;
int m, b, j;
for (m = 1; m <= 4; m++)
for (b = -2; b <= 1; b++)
{
		const int qmin = ccv_max(-32, _ccv_nnc_8i_rowwise_packed_ceil_div(-127 - b, m))({ typeof (-32) _a = (-32); typeof (_ccv_nnc_8i_rowwise_packed_ceil_div
(-127 - b, m)) _b = (_ccv_nnc_8i_rowwise_packed_ceil_div(-127
 - b, m)); (_a > _b) ? _a : _b; });
		const int qmax = ccv_min(31, _ccv_nnc_8i_rowwise_packed_floor_div(127 - b, m))({ typeof (31) _a = (31); typeof (_ccv_nnc_8i_rowwise_packed_floor_div
(127 - b, m)) _b = (_ccv_nnc_8i_rowwise_packed_floor_div(127 -
 b, m)); (_a < _b) ? _a : _b; });
	if (qmin > qmax)
		continue;
	double sse = 0;
	int q[8];
	int q8[8];
	for (j = 0; j < 8; j++)
	{
		q[j] = ccv_clamp((int)lrint((y[j] - b) / m), qmin, qmax)({ typeof (qmin) _a = (qmin); typeof (qmax) _b = (qmax); typeof
 ((int)lrint((y[j] - b) / m)) _x = ((int)lrint((y[j] - b) / m
)); (_x < _a) ? _a : ((_x > _b) ? _b : _x); });
		q8[j] = q[j] * m + b;
		const double d = q8[j] - y[j];
		sse += w[j] * d * d;
	}
	if (sse < best_sse)
	{
		best_sse = sse;
		best_m = m;
		best_b = b;
		memcpy(best_q, q, sizeof(best_q));
		memcpy(best_q8, q8, sizeof(best_q8));
	}
}
group->m = best_m;
group->b = best_b;
memcpy(group->q, best_q, sizeof(best_q));
memcpy(group->q8, best_q8, sizeof(best_q8));
533}

535static void _ccv_nnc_8i_rowwise_packed_quant_q4(const double* const y, const double* const w, ccv_nnc_8i_rowwise_packed_group_t* const group)
536{
double best_sse = DBL_MAX1.7976931348623157e+308;
int best_q[16] = {0};
int best_q8[16] = {0};
int best_m = 1, best_b = 0;
int m, b, j;
for (m = 1; m <= 16; m++)
for (b = -8; b <= 7; b++)
{
	if (-8 * m + b < -127 || 7 * m + b > 127)
		continue;
	double sse = 0;
	int q[16];
	int q8[16];
	for (j = 0; j < 16; j++)
	{
		q[j] = ccv_clamp((int)lrint((y[j] - b) / m), -8, 7)({ typeof (-8) _a = (-8); typeof (7) _b = (7); typeof ((int)lrint
((y[j] - b) / m)) _x = ((int)lrint((y[j] - b) / m)); (_x <
 _a) ? _a : ((_x > _b) ? _b : _x); });
		q8[j] = q[j] * m + b;
		const double d = q8[j] - y[j];
		sse += w[j] * d * d;
	}
	if (sse < best_sse)
	{
		best_sse = sse;
		best_m = m;
		best_b = b;
		memcpy(best_q, q, sizeof(best_q));
		memcpy(best_q8, q8, sizeof(best_q8));
	}
}
group->m = best_m;
group->b = best_b;
memcpy(group->q, best_q, sizeof(best_q));
memcpy(group->q8, best_q8, sizeof(best_q8));
570}

572static void _ccv_nnc_8i_rowwise_packed_quant_q3(const double* const y, const double* const w, ccv_nnc_8i_rowwise_packed_group_t* const group)
573{
double best_sse = DBL_MAX1.7976931348623157e+308;
int best_q[16] = {0};
int best_q8[16] = {0};
int best_m = 1, best_b = 0;
int m, b, j;
for (m = 1; m <= 32; m++)
for (b = -8; b <= 6; b += 2)
{
	if (-4 * m + b < -127 || 3 * m + b > 127)
		continue;
	double sse = 0;
	int q[16];
	int q8[16];
	for (j = 0; j < 16; j++)
	{
		q[j] = ccv_clamp((int)lrint((y[j] - b) / m), -4, 3)({ typeof (-4) _a = (-4); typeof (3) _b = (3); typeof ((int)lrint
((y[j] - b) / m)) _x = ((int)lrint((y[j] - b) / m)); (_x <
 _a) ? _a : ((_x > _b) ? _b : _x); });
		q8[j] = q[j] * m + b;
		const double d = q8[j] - y[j];
		sse += w[j] * d * d;
	}
	if (sse < best_sse)
	{
		best_sse = sse;
		best_m = m;
		best_b = b;
		memcpy(best_q, q, sizeof(best_q));
		memcpy(best_q8, q8, sizeof(best_q8));
	}
}
group->m = best_m;
group->b = best_b;
memcpy(group->q, best_q, sizeof(best_q));
memcpy(group->q8, best_q8, sizeof(best_q8));
607}

609static void _ccv_nnc_8i_rowwise_packed_quant_q2(const double* const y, const double* const w, ccv_nnc_8i_rowwise_packed_group_t* const group)
610{
double best_sse = DBL_MAX1.7976931348623157e+308;
int best_q[16] = {0};
int best_q8[16] = {0};
int best_m = 1, best_z = 0;
int m, z, j;
for (m = 1; m <= 64; m++)
for (z = 0; z <= 120; z += 8)
{
	if (3 * m - z > 127)
		continue;
	double sse = 0;
	int q[16];
	int q8[16];
	for (j = 0; j < 16; j++)
	{
		q[j] = ccv_clamp((int)lrint((y[j] + z) / m), 0, 3)({ typeof (0) _a = (0); typeof (3) _b = (3); typeof ((int)lrint
((y[j] + z) / m)) _x = ((int)lrint((y[j] + z) / m)); (_x <
 _a) ? _a : ((_x > _b) ? _b : _x); });
		q8[j] = q[j] * m - z;
		const double d = q8[j] - y[j];
		sse += w[j] * d * d;
	}
	if (sse < best_sse)
	{
		best_sse = sse;
		best_m = m;
		best_z = z;
		memcpy(best_q, q, sizeof(best_q));
		memcpy(best_q8, q8, sizeof(best_q8));
	}
}
group->m = best_m;
group->z = best_z;
memcpy(group->q, best_q, sizeof(best_q));
memcpy(group->q8, best_q8, sizeof(best_q8));
644}

646static int _ccv_nnc_8i_rowwise_packed_iq2_value(const uint64_t* const grid, const int index, const int lane)
647{
const int v = (int)((grid[index] >> (lane * 8)) & 0xff);
if (v == 8)
return 1;
if (v == 25)
return 3;
assert(v == 43)((void) sizeof ((v == 43) ? 1 : 0), __extension__ ({ if (v ==
 43) ; else __assert_fail ("v == 43", "ccv_nnc_8i_rowwise.c",
 653, __extension__ __PRETTY_FUNCTION__); }));
return 5;
655}

657static int _ccv_nnc_8i_rowwise_packed_iq2xxs_value(const int index, const int lane)
658{
const int v = (int)((ccv_nnc_8i_rowwise_packed_iq2xxs_grid[index] >> (lane * 2)) & 3);
assert(v < 3)((void) sizeof ((v < 3) ? 1 : 0), __extension__ ({ if (v <
 3) ; else __assert_fail ("v < 3", "ccv_nnc_8i_rowwise.c",
 660, __extension__ __PRETTY_FUNCTION__); }));
return 1 + v * 2;
662}

664enum {
CCV_NNC_8I_ROWWISE_PACKED_IQ2XXS_GRID_SIZE = 256,
CCV_NNC_8I_ROWWISE_PACKED_IQ2S_GRID_SIZE = 1024,
CCV_NNC_8I_ROWWISE_PACKED_IQ2_CODE_COUNT = 6561,
668};

670static const int ccv_nnc_8i_rowwise_packed_iq2xxs_scales[16] = {1, 2, 3, 4, 5, 6, 7, 8, 10, 12, 14, 16, 20, 24, 28, 32};
671static int ccv_nnc_8i_rowwise_packed_iq2_scale_initialized = 0;
672static uint8_t ccv_nnc_8i_rowwise_packed_iq2xxs_scale_level[33][3];
673static int ccv_nnc_8i_rowwise_packed_iq2xxs_initialized = 0;
674static int ccv_nnc_8i_rowwise_packed_iq2xxs_candidates_initialized = 0;
675static uint8_t ccv_nnc_8i_rowwise_packed_iq2xxs_level[CCV_NNC_8I_ROWWISE_PACKED_IQ2XXS_GRID_SIZE][8];
676static uint8_t ccv_nnc_8i_rowwise_packed_iq2xxs_scaled_value[33][CCV_NNC_8I_ROWWISE_PACKED_IQ2XXS_GRID_SIZE][8];
677static uint16_t ccv_nnc_8i_rowwise_packed_iq2xxs_candidates[CCV_NNC_8I_ROWWISE_PACKED_IQ2_CODE_COUNT][CCV_NNC_8I_ROWWISE_IQ2_CANDIDATES];

679static void _ccv_nnc_8i_rowwise_packed_iq2_scale_init(void)
680{
if (ccv_nnc_8i_rowwise_packed_iq2_scale_initialized)
return;
int scale, level;
for (scale = 1; scale <= 32; scale++)
for (level = 0; level < 3; level++)
	ccv_nnc_8i_rowwise_packed_iq2xxs_scale_level[scale][level] = (uint8_t)ccv_min((1 + level * 2) * scale, 127)({ typeof ((1 + level * 2) * scale) _a = ((1 + level * 2) * scale
); typeof (127) _b = (127); (_a < _b) ? _a : _b; });
ccv_nnc_8i_rowwise_packed_iq2_scale_initialized = 1;
688}

690static void _ccv_nnc_8i_rowwise_packed_iq2xxs_init(void)
691{
if (ccv_nnc_8i_rowwise_packed_iq2xxs_initialized)
return;
_ccv_nnc_8i_rowwise_packed_iq2_scale_init();
int index, j, scale;
for (index = 0; index < CCV_NNC_8I_ROWWISE_PACKED_IQ2XXS_GRID_SIZE; index++)
for (j = 0; j < 8; j++)
	ccv_nnc_8i_rowwise_packed_iq2xxs_level[index][j] = (uint8_t)((_ccv_nnc_8i_rowwise_packed_iq2xxs_value(index, j) - 1) / 2);
for (scale = 1; scale <= 32; scale++)
{
for (index = 0; index < CCV_NNC_8I_ROWWISE_PACKED_IQ2XXS_GRID_SIZE; index++)
	for (j = 0; j < 8; j++)
		ccv_nnc_8i_rowwise_packed_iq2xxs_scaled_value[scale][index][j] = ccv_nnc_8i_rowwise_packed_iq2xxs_scale_level[scale][ccv_nnc_8i_rowwise_packed_iq2xxs_level[index][j]];
}
ccv_nnc_8i_rowwise_packed_iq2xxs_initialized = 1;
706}

708static void _ccv_nnc_8i_rowwise_packed_iq2xxs_candidates_init(void)
709{
if (ccv_nnc_8i_rowwise_packed_iq2xxs_candidates_initialized)
return;
_ccv_nnc_8i_rowwise_packed_iq2xxs_init();
_ccv_nnc_8i_rowwise_packed_nearest_candidates(&ccv_nnc_8i_rowwise_packed_iq2xxs_level[0][0], CCV_NNC_8I_ROWWISE_PACKED_IQ2XXS_GRID_SIZE, 8, 3, CCV_NNC_8I_ROWWISE_PACKED_IQ2_CODE_COUNT, CCV_NNC_8I_ROWWISE_IQ2_CANDIDATES, &ccv_nnc_8i_rowwise_packed_iq2xxs_candidates[0][0]);
ccv_nnc_8i_rowwise_packed_iq2xxs_candidates_initialized = 1;
715}

717enum {
CCV_NNC_8I_ROWWISE_PACKED_IQ2XS_GRID_SIZE = 512,
719};

721static int ccv_nnc_8i_rowwise_packed_iq2xs_initialized = 0;
722static int ccv_nnc_8i_rowwise_packed_iq2xs_candidates_initialized = 0;
723static uint8_t ccv_nnc_8i_rowwise_packed_iq2xs_level[CCV_NNC_8I_ROWWISE_PACKED_IQ2XS_GRID_SIZE][8];
724static uint8_t ccv_nnc_8i_rowwise_packed_iq2xs_scaled_value[16][CCV_NNC_8I_ROWWISE_PACKED_IQ2XS_GRID_SIZE][8];
725static uint16_t ccv_nnc_8i_rowwise_packed_iq2xs_candidates[CCV_NNC_8I_ROWWISE_PACKED_IQ2_CODE_COUNT][CCV_NNC_8I_ROWWISE_IQ2_CANDIDATES];

727static void _ccv_nnc_8i_rowwise_packed_iq2xs_init(void)
728{
if (ccv_nnc_8i_rowwise_packed_iq2xs_initialized)
return;
_ccv_nnc_8i_rowwise_packed_iq2_scale_init();
int index, j, scale_code;
for (index = 0; index < CCV_NNC_8I_ROWWISE_PACKED_IQ2XS_GRID_SIZE; index++)
for (j = 0; j < 8; j++)
	ccv_nnc_8i_rowwise_packed_iq2xs_level[index][j] = (uint8_t)((_ccv_nnc_8i_rowwise_packed_iq2_value(ccv_nnc_8i_rowwise_packed_iq2xs_grid, index, j) - 1) / 2);
for (scale_code = 0; scale_code < 16; scale_code++)
{
const int scale = ccv_nnc_8i_rowwise_packed_iq2xxs_scales[scale_code];
for (index = 0; index < CCV_NNC_8I_ROWWISE_PACKED_IQ2XS_GRID_SIZE; index++)
	for (j = 0; j < 8; j++)
		ccv_nnc_8i_rowwise_packed_iq2xs_scaled_value[scale_code][index][j] = ccv_nnc_8i_rowwise_packed_iq2xxs_scale_level[scale][ccv_nnc_8i_rowwise_packed_iq2xs_level[index][j]];
}
ccv_nnc_8i_rowwise_packed_iq2xs_initialized = 1;
744}

746static void _ccv_nnc_8i_rowwise_packed_iq2xs_candidates_init(void)
747{
if (ccv_nnc_8i_rowwise_packed_iq2xs_candidates_initialized)
return;
_ccv_nnc_8i_rowwise_packed_iq2xs_init();
_ccv_nnc_8i_rowwise_packed_nearest_candidates(&ccv_nnc_8i_rowwise_packed_iq2xs_level[0][0], CCV_NNC_8I_ROWWISE_PACKED_IQ2XS_GRID_SIZE, 8, 3, CCV_NNC_8I_ROWWISE_PACKED_IQ2_CODE_COUNT, CCV_NNC_8I_ROWWISE_IQ2_CANDIDATES, &ccv_nnc_8i_rowwise_packed_iq2xs_candidates[0][0]);
ccv_nnc_8i_rowwise_packed_iq2xs_candidates_initialized = 1;
753}

755static int ccv_nnc_8i_rowwise_packed_iq2s_initialized = 0;
756static uint8_t ccv_nnc_8i_rowwise_packed_iq2s_level[CCV_NNC_8I_ROWWISE_PACKED_IQ2S_GRID_SIZE][8];
757static uint8_t ccv_nnc_8i_rowwise_packed_iq2s_scale_level[65][3];
758static uint16_t ccv_nnc_8i_rowwise_packed_iq2s_scale_level2[65][3];
759static uint8_t ccv_nnc_8i_rowwise_packed_iq2s_scaled_value[65][CCV_NNC_8I_ROWWISE_PACKED_IQ2S_GRID_SIZE][8];

761static void _ccv_nnc_8i_rowwise_packed_iq2s_init(void)
762{
if (ccv_nnc_8i_rowwise_packed_iq2s_initialized)
return;
int index, j, scale;
for (index = 0; index < CCV_NNC_8I_ROWWISE_PACKED_IQ2S_GRID_SIZE; index++)
for (j = 0; j < 8; j++)
{
	const int v = _ccv_nnc_8i_rowwise_packed_iq2_value(ccv_nnc_8i_rowwise_packed_iq2s_grid, index, j);
	ccv_nnc_8i_rowwise_packed_iq2s_level[index][j] = (uint8_t)((v - 1) / 2);
}
for (scale = 1; scale <= 64; scale++)
{
for (j = 0; j < 3; j++)
{
	const int v = ccv_min((1 + j * 2) * scale, 127)({ typeof ((1 + j * 2) * scale) _a = ((1 + j * 2) * scale); typeof
 (127) _b = (127); (_a < _b) ? _a : _b; });
	ccv_nnc_8i_rowwise_packed_iq2s_scale_level[scale][j] = (uint8_t)v;
	ccv_nnc_8i_rowwise_packed_iq2s_scale_level2[scale][j] = (uint16_t)(v * v);
}
for (index = 0; index < CCV_NNC_8I_ROWWISE_PACKED_IQ2S_GRID_SIZE; index++)
	for (j = 0; j < 8; j++)
		ccv_nnc_8i_rowwise_packed_iq2s_scaled_value[scale][index][j] = ccv_nnc_8i_rowwise_packed_iq2s_scale_level[scale][ccv_nnc_8i_rowwise_packed_iq2s_level[index][j]];
}
ccv_nnc_8i_rowwise_packed_iq2s_initialized = 1;
785}

787static double _ccv_nnc_8i_rowwise_packed_iq2s_sse(const double* const ay, const double* const w, const int lane, const int scale, const int index)
788{
const uint8_t* const mag = ccv_nnc_8i_rowwise_packed_iq2s_scaled_value[scale][index];
double d = (double)mag[0] - ay[lane];
double sse = w[lane] * d * d;
d = (double)mag[1] - ay[lane + 1];
sse += w[lane + 1] * d * d;
d = (double)mag[2] - ay[lane + 2];
sse += w[lane + 2] * d * d;
d = (double)mag[3] - ay[lane + 3];
sse += w[lane + 3] * d * d;
d = (double)mag[4] - ay[lane + 4];
sse += w[lane + 4] * d * d;
d = (double)mag[5] - ay[lane + 5];
sse += w[lane + 5] * d * d;
d = (double)mag[6] - ay[lane + 6];
sse += w[lane + 6] * d * d;
d = (double)mag[7] - ay[lane + 7];
sse += w[lane + 7] * d * d;
return sse;
807}

809static int _ccv_nnc_8i_rowwise_packed_iq3xxs_value(const int index, const int lane)
810{
const int v = (int)((ccv_nnc_8i_rowwise_packed_iq3xxs_grid[index] >> (lane * 8)) & 0xff);
switch (v)
{
case 4: return 1;
case 12: return 3;
case 20: return 5;
case 28: return 7;
case 36: return 9;
case 44: return 11;
case 52: return 13;
default:
	assert(v == 62)((void) sizeof ((v == 62) ? 1 : 0), __extension__ ({ if (v ==
 62) ; else __assert_fail ("v == 62", "ccv_nnc_8i_rowwise.c",
 822, __extension__ __PRETTY_FUNCTION__); }));
	return 15;
}
825}

827static int _ccv_nnc_8i_rowwise_packed_iq3s_value(const int index, const int lane)
828{
return (int)((ccv_nnc_8i_rowwise_packed_iq3s_grid[index] >> (lane * 8)) & 0xff);
830}

832#define CCV_NNC_8I_ROWWISE_PACKED_IQ3S_GRID_SIZE(512) (512)
833#define CCV_NNC_8I_ROWWISE_PACKED_IQ3XXS_GRID_SIZE(256) (256)
834#define CCV_NNC_8I_ROWWISE_PACKED_IQ3_CODE_COUNT(4096) (4096)

836static int ccv_nnc_8i_rowwise_packed_iq3s_initialized = 0;
837static uint8_t ccv_nnc_8i_rowwise_packed_iq3s_scaled_value[17][CCV_NNC_8I_ROWWISE_PACKED_IQ3S_GRID_SIZE(512)][4];

839static int ccv_nnc_8i_rowwise_packed_iq3xxs_initialized = 0;
840static int ccv_nnc_8i_rowwise_packed_iq3xxs_candidates_initialized = 0;
841static uint8_t ccv_nnc_8i_rowwise_packed_iq3xxs_level[CCV_NNC_8I_ROWWISE_PACKED_IQ3XXS_GRID_SIZE(256)][4];
842static uint8_t ccv_nnc_8i_rowwise_packed_iq3xxs_scaled_value[17][CCV_NNC_8I_ROWWISE_PACKED_IQ3XXS_GRID_SIZE(256)][4];
843static uint16_t ccv_nnc_8i_rowwise_packed_iq3xxs_candidates[CCV_NNC_8I_ROWWISE_PACKED_IQ3_CODE_COUNT(4096)][CCV_NNC_8I_ROWWISE_IQ3_CANDIDATES];

845static void _ccv_nnc_8i_rowwise_packed_iq3s_init(void)
846{
if (ccv_nnc_8i_rowwise_packed_iq3s_initialized)
return;
int index, j, scale;
for (scale = 1; scale <= 16; scale++)
for (index = 0; index < CCV_NNC_8I_ROWWISE_PACKED_IQ3S_GRID_SIZE(512); index++)
	for (j = 0; j < 4; j++)
		ccv_nnc_8i_rowwise_packed_iq3s_scaled_value[scale][index][j] = (uint8_t)ccv_min(_ccv_nnc_8i_rowwise_packed_iq3s_value(index, j) * scale, 127)({ typeof (_ccv_nnc_8i_rowwise_packed_iq3s_value(index, j) * scale
) _a = (_ccv_nnc_8i_rowwise_packed_iq3s_value(index, j) * scale
); typeof (127) _b = (127); (_a < _b) ? _a : _b; });
ccv_nnc_8i_rowwise_packed_iq3s_initialized = 1;
855}

857static void _ccv_nnc_8i_rowwise_packed_iq3xxs_init(void)
858{
if (ccv_nnc_8i_rowwise_packed_iq3xxs_initialized)
return;
int index, j, scale;
for (index = 0; index < CCV_NNC_8I_ROWWISE_PACKED_IQ3XXS_GRID_SIZE(256); index++)
for (j = 0; j < 4; j++)
	ccv_nnc_8i_rowwise_packed_iq3xxs_level[index][j] = (uint8_t)((_ccv_nnc_8i_rowwise_packed_iq3xxs_value(index, j) - 1) / 2);
for (scale = 1; scale <= 16; scale++)
for (index = 0; index < CCV_NNC_8I_ROWWISE_PACKED_IQ3XXS_GRID_SIZE(256); index++)
	for (j = 0; j < 4; j++)
		ccv_nnc_8i_rowwise_packed_iq3xxs_scaled_value[scale][index][j] = (uint8_t)ccv_min((1 + ccv_nnc_8i_rowwise_packed_iq3xxs_level[index][j] * 2) * scale, 127)({ typeof ((1 + ccv_nnc_8i_rowwise_packed_iq3xxs_level[index]
[j] * 2) * scale) _a = ((1 + ccv_nnc_8i_rowwise_packed_iq3xxs_level
[index][j] * 2) * scale); typeof (127) _b = (127); (_a < _b
) ? _a : _b; });
ccv_nnc_8i_rowwise_packed_iq3xxs_initialized = 1;
870}

872static void _ccv_nnc_8i_rowwise_packed_iq3xxs_candidates_init(void)
873{
if (ccv_nnc_8i_rowwise_packed_iq3xxs_candidates_initialized)
return;
_ccv_nnc_8i_rowwise_packed_iq3xxs_init();
_ccv_nnc_8i_rowwise_packed_nearest_candidates(&ccv_nnc_8i_rowwise_packed_iq3xxs_level[0][0], CCV_NNC_8I_ROWWISE_PACKED_IQ3XXS_GRID_SIZE(256), 4, 8, CCV_NNC_8I_ROWWISE_PACKED_IQ3_CODE_COUNT(4096), CCV_NNC_8I_ROWWISE_IQ3_CANDIDATES, &ccv_nnc_8i_rowwise_packed_iq3xxs_candidates[0][0]);
ccv_nnc_8i_rowwise_packed_iq3xxs_candidates_initialized = 1;
879}

881static double _ccv_nnc_8i_rowwise_packed_iq3s_sse(const double* const ay, const double* const w, const int lane, const int scale, const int index)
882{
const uint8_t* const mag = ccv_nnc_8i_rowwise_packed_iq3s_scaled_value[scale][index];
double d = (double)mag[0] - ay[lane];
double sse = w[lane] * d * d;
d = (double)mag[1] - ay[lane + 1];
sse += w[lane + 1] * d * d;
d = (double)mag[2] - ay[lane + 2];
sse += w[lane + 2] * d * d;
d = (double)mag[3] - ay[lane + 3];
sse += w[lane + 3] * d * d;
return sse;
893}

895static inline double _ccv_nnc_8i_rowwise_packed_iq2_cost(const double cost[8][3], const uint8_t* const levels)
896{
double sse = 0;
int j;
for (j = 0; j < 8; j++)
sse += cost[j][levels[j]];
return sse;
902}

904static inline double _ccv_nnc_8i_rowwise_packed_safe_lower_bound(const double value)
905{
return nextafter(value - (fabs(value) + 1) * (64 * DBL_EPSILON2.2204460492503131e-16), -INFINITY(__builtin_inff ()));
907}

909static inline double _ccv_nnc_8i_rowwise_packed_iq2xxs_cost(const double cost[8][3], const double flipped_cost[8][3], const double flip_metric[8][3], const uint8_t* const levels, const uint8_t signs, const int flip_sign, int* const sign_index)
910{
int best_flip = -1;
int j;
if (flip_sign)
{
double best_flip_metric = DBL_MAX1.7976931348623157e+308;
for (j = 0; j < 8; j++)
{
	const double metric = flip_metric[j][levels[j]];
	if (metric < best_flip_metric)
	{
		best_flip_metric = metric;
		best_flip = j;
	}
}
}
double sse = 0;
for (j = 0; j < 8; j++)
sse += j == best_flip ? flipped_cost[j][levels[j]] : cost[j][levels[j]];
*sign_index = (signs ^ (best_flip >= 0 ? (uint8_t)(1u << best_flip) : 0)) & 0x7f;
return sse;
931}

933static void _ccv_nnc_8i_rowwise_packed_quant_iq2_xxs(const double* const y, const double* const w, ccv_nnc_8i_rowwise_packed_group_t* const group)
934{
assert(ccv_nnc_8i_rowwise_packed_iq2xxs_initialized)((void) sizeof ((ccv_nnc_8i_rowwise_packed_iq2xxs_initialized
) ? 1 : 0), __extension__ ({ if (ccv_nnc_8i_rowwise_packed_iq2xxs_initialized
) ; else __assert_fail ("ccv_nnc_8i_rowwise_packed_iq2xxs_initialized"
, "ccv_nnc_8i_rowwise.c", 935, __extension__ __PRETTY_FUNCTION__
); }));
double best_sse = DBL_MAX1.7976931348623157e+308;
int best_scale_code = 0;
int best_grid[4] = {0};
int best_sign[4] = {0};
int scale_code;
for (scale_code = 0; scale_code < 16; scale_code++)
{
const int scale = ccv_nnc_8i_rowwise_packed_iq2xxs_scales[scale_code];
double group_sse = 0;
int group_grid[4] = {0};
int group_sign[4] = {0};
int sg;
for (sg = 0; sg < 4; sg++)
{
	double best_sub_sse = DBL_MAX1.7976931348623157e+308;
	int best_sub_grid = 0;
	int best_sub_sign = 0;
	const int lane = sg * 8;
	uint8_t signs = 0;
	int negative_count = 0;
	double cost[8][3];
	double flipped_cost[8][3];
	double flip_metric[8][3];
	int j;
	for (j = 0; j < 8; j++)
	{
		if (y[lane + j] < 0)
		{
			signs |= (uint8_t)(1u << j);
			negative_count++;
		}
		int level;
		for (level = 0; level < 3; level++)
		{
			const int mag = ccv_nnc_8i_rowwise_packed_iq2xxs_scale_level[scale][level];
			const int q8 = (signs & (1u << j)) ? -mag : mag;
			double d = (double)q8 - y[lane + j];
			cost[j][level] = w[lane + j] * d * d;
			d = (double)-q8 - y[lane + j];
			flipped_cost[j][level] = w[lane + j] * d * d;
			flip_metric[j][level] = w[lane + j] * (double)mag * fabs(y[lane + j]);
		}
	}
	int target_code = 0;
	int code_multiplier = 1;
	uint8_t target_levels[8];
	double lower_bound_base = 0;
	double lower_bound_ratio = DBL_MAX1.7976931348623157e+308;
	double lower_bound_flip = DBL_MAX1.7976931348623157e+308;
	for (j = 0; j < 8; j++)
	{
		int target_level = 0;
		if (cost[j][1] < cost[j][target_level])
			target_level = 1;
		if (cost[j][2] < cost[j][target_level])
			target_level = 2;
		target_levels[j] = (uint8_t)target_level;
		target_code += target_level * code_multiplier;
		code_multiplier *= 3;
		lower_bound_base += cost[j][target_level];
		int level;
		for (level = 0; level < 3; level++)
		{
			if (level != target_level)
			{
				const int d = level - target_level;
				lower_bound_ratio = ccv_min(lower_bound_ratio, (cost[j][level] - cost[j][target_level]) / (double)(d * d))({ typeof (lower_bound_ratio) _a = (lower_bound_ratio); typeof
 ((cost[j][level] - cost[j][target_level]) / (double)(d * d))
 _b = ((cost[j][level] - cost[j][target_level]) / (double)(d *
 d)); (_a < _b) ? _a : _b; });
			}
			lower_bound_flip = ccv_min(lower_bound_flip, flipped_cost[j][level] - cost[j][level])({ typeof (lower_bound_flip) _a = (lower_bound_flip); typeof (
flipped_cost[j][level] - cost[j][level]) _b = (flipped_cost[j
][level] - cost[j][level]); (_a < _b) ? _a : _b; });
		}
	}
	int candidate;
	for (candidate = 0; candidate < CCV_NNC_8I_ROWWISE_IQ2_CANDIDATES; candidate++)
	{
		const int index = ccv_nnc_8i_rowwise_packed_iq2xxs_candidates[target_code][candidate];
		const uint8_t* const levels = ccv_nnc_8i_rowwise_packed_iq2xxs_level[index];
		int sign_index;
		const double sse = _ccv_nnc_8i_rowwise_packed_iq2xxs_cost(cost, flipped_cost, flip_metric, levels, signs, negative_count & 1, &sign_index);
		if (sse < best_sub_sse || (sse == best_sub_sse && index < best_sub_grid))
		{
			best_sub_sse = sse;
			best_sub_grid = index;
			best_sub_sign = sign_index;
		}
	}
	const uint8_t* const cutoff_levels = ccv_nnc_8i_rowwise_packed_iq2xxs_level[ccv_nnc_8i_rowwise_packed_iq2xxs_candidates[target_code][CCV_NNC_8I_ROWWISE_IQ2_CANDIDATES - 1]];
	int cutoff_distance = 0;
	for (j = 0; j < 8; j++)
	{
		const int d = (int)cutoff_levels[j] - target_levels[j];
		cutoff_distance += d * d;
	}
	const double safe_ratio = nextafter(lower_bound_ratio, 0);
	const double lower_bound = _ccv_nnc_8i_rowwise_packed_safe_lower_bound(lower_bound_base + safe_ratio * cutoff_distance + ((negative_count & 1) ? nextafter(lower_bound_flip, -INFINITY(__builtin_inff ())) : 0));
	if (!(best_sub_sse < lower_bound))
	{
		int index;
		for (index = 0; index < CCV_NNC_8I_ROWWISE_PACKED_IQ2XXS_GRID_SIZE; index++)
		{
			int sign_index;
			const double sse = _ccv_nnc_8i_rowwise_packed_iq2xxs_cost(cost, flipped_cost, flip_metric, ccv_nnc_8i_rowwise_packed_iq2xxs_level[index], signs, negative_count & 1, &sign_index);
			if (sse < best_sub_sse || (sse == best_sub_sse && index < best_sub_grid))
			{
				best_sub_sse = sse;
				best_sub_grid = index;
				best_sub_sign = sign_index;
			}
		}
	}
	group_sse += best_sub_sse;
	group_grid[sg] = best_sub_grid;
	group_sign[sg] = best_sub_sign;
}
if (group_sse < best_sse)
{
	best_sse = group_sse;
	best_scale_code = scale_code;
	memcpy(best_grid, group_grid, sizeof(best_grid));
	memcpy(best_sign, group_sign, sizeof(best_sign));
}
}
group->scale = best_scale_code;
group->signs = 0;
memcpy(group->grid, best_grid, sizeof(best_grid));
int j;
for (j = 0; j < 4; j++)
group->signs |= (uint32_t)best_sign[j] << (j * 7);
for (j = 0; j < 32; j++)
{
const int sg = j >> 3;
const int lane = j & 7;
const uint8_t signs = ccv_nnc_8i_rowwise_packed_iq2xxs_ksigns[best_sign[sg]];
const int mag = ccv_nnc_8i_rowwise_packed_iq2xxs_scaled_value[ccv_nnc_8i_rowwise_packed_iq2xxs_scales[best_scale_code]][best_grid[sg]][lane];
group->q8[j] = (signs & (1u << lane)) ? -mag : mag;
}
1071}

1073static void _ccv_nnc_8i_rowwise_packed_quant_iq2_s(const double* const y, const double* const w, ccv_nnc_8i_rowwise_packed_group_t* const group)
1074{
assert(ccv_nnc_8i_rowwise_packed_iq2s_initialized)((void) sizeof ((ccv_nnc_8i_rowwise_packed_iq2s_initialized) ?
: 0), __extension__ ({ if (ccv_nnc_8i_rowwise_packed_iq2s_initialized
) ; else __assert_fail ("ccv_nnc_8i_rowwise_packed_iq2s_initialized"
, "ccv_nnc_8i_rowwise.c", 1075, __extension__ __PRETTY_FUNCTION__
); }));
double best_sse = DBL_MAX1.7976931348623157e+308;
int best_scale = 1;
int best_grid[2] = {0};
double ay[16];
double wy[16];
uint32_t signs = 0;
int j;
for (j = 0; j < 16; j++)
{
ay[j] = fabs(y[j]);
wy[j] = w[j] * ay[j];
if (y[j] < 0)
	signs |= (1u << j);
}
double sub_sse[2][65];
int sub_grid[2][65];
int sg, scale;
for (sg = 0; sg < 2; sg++)
for (scale = 1; scale <= 64; scale++)
{
	sub_sse[sg][scale] = DBL_MAX1.7976931348623157e+308;
	sub_grid[sg][scale] = 0;
}
for (sg = 0; sg < 2; sg++)
{
const int lane = sg * 8;
double sum_y2 = 0;
for (j = 0; j < 8; j++)
	sum_y2 += w[lane + j] * ay[lane + j] * ay[lane + j];
int index;
for (index = 0; index < CCV_NNC_8I_ROWWISE_PACKED_IQ2S_GRID_SIZE; index++)
{
	double sw[3] = {0};
	double swy[3] = {0};
	for (j = 0; j < 8; j++)
	{
		const int level = ccv_nnc_8i_rowwise_packed_iq2s_level[index][j];
		sw[level] += w[lane + j];
		swy[level] += wy[lane + j];
	}
	for (scale = 1; scale <= 64; scale++)
	{
		const double sse = sum_y2 +
			sw[0] * (double)ccv_nnc_8i_rowwise_packed_iq2s_scale_level2[scale][0] - 2 * swy[0] * (double)ccv_nnc_8i_rowwise_packed_iq2s_scale_level[scale][0] +
			sw[1] * (double)ccv_nnc_8i_rowwise_packed_iq2s_scale_level2[scale][1] - 2 * swy[1] * (double)ccv_nnc_8i_rowwise_packed_iq2s_scale_level[scale][1] +
			sw[2] * (double)ccv_nnc_8i_rowwise_packed_iq2s_scale_level2[scale][2] - 2 * swy[2] * (double)ccv_nnc_8i_rowwise_packed_iq2s_scale_level[scale][2];
		if (sub_sse[sg][scale] == DBL_MAX1.7976931348623157e+308 || sse <= sub_sse[sg][scale] + ccv_max(1., fabs(sub_sse[sg][scale]))({ typeof (1.) _a = (1.); typeof (fabs(sub_sse[sg][scale])) _b
 = (fabs(sub_sse[sg][scale])); (_a > _b) ? _a : _b; }) * 1e-9)
		{
			const double exact_sse = _ccv_nnc_8i_rowwise_packed_iq2s_sse(ay, w, lane, scale, index);
			if (exact_sse < sub_sse[sg][scale])
			{
				sub_sse[sg][scale] = exact_sse;
				sub_grid[sg][scale] = index;
			}
		}
	}
}
}
for (scale = 1; scale <= 64; scale++)
{
const double group_sse = sub_sse[0][scale] + sub_sse[1][scale];
if (group_sse < best_sse)
{
	best_sse = group_sse;
	best_scale = scale;
	best_grid[0] = sub_grid[0][scale];
	best_grid[1] = sub_grid[1][scale];
}
}
group->scale = best_scale;
group->signs = signs;
memcpy(group->grid, best_grid, sizeof(best_grid));
for (j = 0; j < 16; j++)
{
const int sg = j >> 3;
const int lane = j & 7;
const int mag = ccv_nnc_8i_rowwise_packed_iq2s_scaled_value[best_scale][best_grid[sg]][lane];
group->q8[j] = (signs & (1u << j)) ? -mag : mag;
}
1155}

1157static void _ccv_nnc_8i_rowwise_packed_quant_iq2_xs(const double* const y, const double* const w, ccv_nnc_8i_rowwise_packed_group_t* const group)
1158{
assert(ccv_nnc_8i_rowwise_packed_iq2xs_initialized)((void) sizeof ((ccv_nnc_8i_rowwise_packed_iq2xs_initialized)
 ? 1 : 0), __extension__ ({ if (ccv_nnc_8i_rowwise_packed_iq2xs_initialized
) ; else __assert_fail ("ccv_nnc_8i_rowwise_packed_iq2xs_initialized"
, "ccv_nnc_8i_rowwise.c", 1159, __extension__ __PRETTY_FUNCTION__
); }));
double best_sse = DBL_MAX1.7976931348623157e+308;
int best_scale_code = 0;
int best_grid = 0;
uint32_t signs = 0;
int j;
for (j = 0; j < 8; j++)
if (y[j] < 0)
	signs |= (1u << j);
int scale_code;
for (scale_code = 0; scale_code < 16; scale_code++)
{
double cost[8][3];
for (j = 0; j < 8; j++)
{
	int level;
	for (level = 0; level < 3; level++)
	{
		const int mag = ccv_nnc_8i_rowwise_packed_iq2xxs_scale_level[ccv_nnc_8i_rowwise_packed_iq2xxs_scales[scale_code]][level];
		const int q8 = (signs & (1u << j)) ? -mag : mag;
		const double d = (double)q8 - y[j];
		cost[j][level] = w[j] * d * d;
	}
}
int target_code = 0;
int code_multiplier = 1;
uint8_t target_levels[8];
double lower_bound_base = 0;
double lower_bound_ratio = DBL_MAX1.7976931348623157e+308;
for (j = 0; j < 8; j++)
{
	int target_level = 0;
	if (cost[j][1] < cost[j][target_level])
		target_level = 1;
	if (cost[j][2] < cost[j][target_level])
		target_level = 2;
	target_levels[j] = (uint8_t)target_level;
	target_code += target_level * code_multiplier;
	code_multiplier *= 3;
	lower_bound_base += cost[j][target_level];
	int level;
	for (level = 0; level < 3; level++)
		if (level != target_level)
		{
			const int d = level - target_level;
			lower_bound_ratio = ccv_min(lower_bound_ratio, (cost[j][level] - cost[j][target_level]) / (double)(d * d))({ typeof (lower_bound_ratio) _a = (lower_bound_ratio); typeof
 ((cost[j][level] - cost[j][target_level]) / (double)(d * d))
 _b = ((cost[j][level] - cost[j][target_level]) / (double)(d *
 d)); (_a < _b) ? _a : _b; });
		}
}
int candidate;
for (candidate = 0; candidate < CCV_NNC_8I_ROWWISE_IQ2_CANDIDATES; candidate++)
{
	const int index = ccv_nnc_8i_rowwise_packed_iq2xs_candidates[target_code][candidate];
	const uint8_t* const levels = ccv_nnc_8i_rowwise_packed_iq2xs_level[index];
	const double sse = _ccv_nnc_8i_rowwise_packed_iq2_cost(cost, levels);
	if (sse < best_sse || (sse == best_sse && scale_code == best_scale_code && index < best_grid))
	{
		best_sse = sse;
		best_scale_code = scale_code;
		best_grid = index;
	}
}
const uint8_t* const cutoff_levels = ccv_nnc_8i_rowwise_packed_iq2xs_level[ccv_nnc_8i_rowwise_packed_iq2xs_candidates[target_code][CCV_NNC_8I_ROWWISE_IQ2_CANDIDATES - 1]];
int cutoff_distance = 0;
for (j = 0; j < 8; j++)
{
	const int d = (int)cutoff_levels[j] - target_levels[j];
	cutoff_distance += d * d;
}
const double lower_bound = _ccv_nnc_8i_rowwise_packed_safe_lower_bound(lower_bound_base + nextafter(lower_bound_ratio, 0) * cutoff_distance);
if (!(best_sse < lower_bound))
{
	int index;
	for (index = 0; index < CCV_NNC_8I_ROWWISE_PACKED_IQ2XS_GRID_SIZE; index++)
	{
		const double sse = _ccv_nnc_8i_rowwise_packed_iq2_cost(cost, ccv_nnc_8i_rowwise_packed_iq2xs_level[index]);
		if (sse < best_sse || (sse == best_sse && scale_code == best_scale_code && index < best_grid))
		{
			best_sse = sse;
			best_scale_code = scale_code;
			best_grid = index;
		}
	}
}
}
group->scale = best_scale_code;
group->grid[0] = best_grid;
group->signs = signs;
memset(group->q8, 0, sizeof(group->q8));
for (j = 0; j < 8; j++)
{
const int mag = ccv_nnc_8i_rowwise_packed_iq2xs_scaled_value[best_scale_code][best_grid][j];
group->q8[j] = (signs & (1u << j)) ? -mag : mag;
}
1252}

1254static void _ccv_nnc_8i_rowwise_packed_quant_iq3_s(const double* const y, const double* const w, ccv_nnc_8i_rowwise_packed_group_t* const group)
1255{
assert(ccv_nnc_8i_rowwise_packed_iq3s_initialized)((void) sizeof ((ccv_nnc_8i_rowwise_packed_iq3s_initialized) ?
: 0), __extension__ ({ if (ccv_nnc_8i_rowwise_packed_iq3s_initialized
) ; else __assert_fail ("ccv_nnc_8i_rowwise_packed_iq3s_initialized"
, "ccv_nnc_8i_rowwise.c", 1256, __extension__ __PRETTY_FUNCTION__
); }));
double best_sse = DBL_MAX1.7976931348623157e+308;
int best_scale = 1;
int best_grid[4] = {0};
double ay[16];
uint32_t signs = 0;
int j;
for (j = 0; j < 16; j++)
{
ay[j] = fabs(y[j]);
if (y[j] < 0)
	signs |= (1u << j);
}
int scale;
for (scale = 1; scale <= 16; scale++)
{
double group_sse = 0;
int group_grid[4] = {0};
int sg;
for (sg = 0; sg < 4; sg++)
{
	double best_sub_sse = DBL_MAX1.7976931348623157e+308;
	int best_sub_grid = 0;
	const int lane = sg * 4;
	int index;
	for (index = 0; index < CCV_NNC_8I_ROWWISE_PACKED_IQ3S_GRID_SIZE(512); index++)
	{
		const double sse = _ccv_nnc_8i_rowwise_packed_iq3s_sse(ay, w, lane, scale, index);
		if (sse < best_sub_sse)
		{
			best_sub_sse = sse;
			best_sub_grid = index;
		}
	}
	group_sse += best_sub_sse;
	group_grid[sg] = best_sub_grid;
}
if (group_sse < best_sse)
{
	best_sse = group_sse;
	best_scale = scale;
	memcpy(best_grid, group_grid, sizeof(best_grid));
}
}
group->scale = best_scale;
group->signs = signs;
memcpy(group->grid, best_grid, sizeof(best_grid));
for (j = 0; j < 16; j++)
{
const int sg = j >> 2;
const int lane = j & 3;
const int mag = ccv_nnc_8i_rowwise_packed_iq3s_scaled_value[best_scale][best_grid[sg]][lane];
group->q8[j] = (signs & (1u << j)) ? -mag : mag;
}
1310}

1312static void _ccv_nnc_8i_rowwise_packed_quant_iq3_xxs(const double* const y, const double* const w, ccv_nnc_8i_rowwise_packed_group_t* const group)
1313{
assert(ccv_nnc_8i_rowwise_packed_iq3xxs_initialized)((void) sizeof ((ccv_nnc_8i_rowwise_packed_iq3xxs_initialized
) ? 1 : 0), __extension__ ({ if (ccv_nnc_8i_rowwise_packed_iq3xxs_initialized
) ; else __assert_fail ("ccv_nnc_8i_rowwise_packed_iq3xxs_initialized"
, "ccv_nnc_8i_rowwise.c", 1314, __extension__ __PRETTY_FUNCTION__
); }));
double best_sse = DBL_MAX1.7976931348623157e+308;
int best_scale = 1;
int best_grid[2] = {0};
double ay[8];
uint32_t signs = 0;
int j;
for (j = 0; j < 8; j++)
{
ay[j] = fabs(y[j]);
if (y[j] < 0)
	signs |= (1u << j);
}
int scale;
for (scale = 1; scale <= 16; scale++)
{
double group_sse = 0;
int group_grid[2] = {0};
int sg;
for (sg = 0; sg < 2; sg++)
{
	double best_sub_sse = DBL_MAX1.7976931348623157e+308;
	int best_sub_grid = 0;
	const int lane = sg * 4;
	double cost[4][8];
	for (j = 0; j < 4; j++)
	{
		int level;
		for (level = 0; level < 8; level++)
		{
			const int mag = ccv_min((1 + level * 2) * scale, 127)({ typeof ((1 + level * 2) * scale) _a = ((1 + level * 2) * scale
); typeof (127) _b = (127); (_a < _b) ? _a : _b; });
			const double d = (double)mag - ay[lane + j];
			cost[j][level] = w[lane + j] * d * d;
		}
	}
	int target_code = 0;
	uint8_t target_levels[4];
	double lower_bound_base = 0;
	double lower_bound_ratio = DBL_MAX1.7976931348623157e+308;
	for (j = 0; j < 4; j++)
	{
		int target_level = 0;
		int level;
		for (level = 1; level < 8; level++)
			if (cost[j][level] < cost[j][target_level])
				target_level = level;
		target_levels[j] = (uint8_t)target_level;
		target_code |= target_level << (j * 3);
		lower_bound_base += cost[j][target_level];
		for (level = 0; level < 8; level++)
			if (level != target_level)
			{
				const int d = level - target_level;
				lower_bound_ratio = ccv_min(lower_bound_ratio, (cost[j][level] - cost[j][target_level]) / (double)(d * d))({ typeof (lower_bound_ratio) _a = (lower_bound_ratio); typeof
 ((cost[j][level] - cost[j][target_level]) / (double)(d * d))
 _b = ((cost[j][level] - cost[j][target_level]) / (double)(d *
 d)); (_a < _b) ? _a : _b; });
			}
	}
	int candidate;
	for (candidate = 0; candidate < CCV_NNC_8I_ROWWISE_IQ3_CANDIDATES; candidate++)
	{
		const int index = ccv_nnc_8i_rowwise_packed_iq3xxs_candidates[target_code][candidate];
		const uint8_t* const levels = ccv_nnc_8i_rowwise_packed_iq3xxs_level[index];
		const double sse = cost[0][levels[0]] + cost[1][levels[1]] + cost[2][levels[2]] + cost[3][levels[3]];
		if (sse < best_sub_sse || (sse == best_sub_sse && index < best_sub_grid))
		{
			best_sub_sse = sse;
			best_sub_grid = index;
		}
	}
	const uint8_t* const cutoff_levels = ccv_nnc_8i_rowwise_packed_iq3xxs_level[ccv_nnc_8i_rowwise_packed_iq3xxs_candidates[target_code][CCV_NNC_8I_ROWWISE_IQ3_CANDIDATES - 1]];
	int cutoff_distance = 0;
	for (j = 0; j < 4; j++)
	{
		const int d = (int)cutoff_levels[j] - target_levels[j];
		cutoff_distance += d * d;
	}
	const double lower_bound = _ccv_nnc_8i_rowwise_packed_safe_lower_bound(lower_bound_base + nextafter(lower_bound_ratio, 0) * cutoff_distance);
	if (!(best_sub_sse < lower_bound))
	{
		int index;
		for (index = 0; index < CCV_NNC_8I_ROWWISE_PACKED_IQ3XXS_GRID_SIZE(256); index++)
		{
			const uint8_t* const levels = ccv_nnc_8i_rowwise_packed_iq3xxs_level[index];
			const double sse = cost[0][levels[0]] + cost[1][levels[1]] + cost[2][levels[2]] + cost[3][levels[3]];
			if (sse < best_sub_sse || (sse == best_sub_sse && index < best_sub_grid))
			{
				best_sub_sse = sse;
				best_sub_grid = index;
			}
		}
	}
	group_sse += best_sub_sse;
	group_grid[sg] = best_sub_grid;
}
if (group_sse < best_sse)
{
	best_sse = group_sse;
	best_scale = scale;
	memcpy(best_grid, group_grid, sizeof(best_grid));
}
}
group->scale = best_scale;
group->signs = signs;
memcpy(group->grid, best_grid, sizeof(best_grid));
memset(group->q8, 0, sizeof(group->q8));
for (j = 0; j < 8; j++)
{
const int sg = j >> 2;
const int lane = j & 3;
const int mag = ccv_nnc_8i_rowwise_packed_iq3xxs_scaled_value[best_scale][best_grid[sg]][lane];
group->q8[j] = (signs & (1u << j)) ? -mag : mag;
}
1425}

1427static void _ccv_nnc_8i_rowwise_packed_quant_group(const int format, const double* const y, const double* const w, const int16_t* const iq1_map, ccv_nnc_8i_rowwise_packed_group_t* const group)
1428{
switch (format)
{
case CCV_NNC_QX_8I_ROWWISE_IQ1_S:
	_ccv_nnc_8i_rowwise_packed_quant_iq1_s(y, w, iq1_map, group);
	break;
case CCV_NNC_QX_8I_ROWWISE_IQ1_M:
	_ccv_nnc_8i_rowwise_packed_quant_iq1_m(y, w, iq1_map, group);
	break;
case CCV_NNC_QX_8I_ROWWISE_Q5_K:
	_ccv_nnc_8i_rowwise_packed_quant_q5(y, w, group);
	break;
case CCV_NNC_QX_8I_ROWWISE_Q6_K:
	_ccv_nnc_8i_rowwise_packed_quant_q6(y, w, group);
	break;
case CCV_NNC_QX_8I_ROWWISE_Q4_K:
	_ccv_nnc_8i_rowwise_packed_quant_q4(y, w, group);
	break;
case CCV_NNC_QX_8I_ROWWISE_Q3_K:
	_ccv_nnc_8i_rowwise_packed_quant_q3(y, w, group);
	break;
case CCV_NNC_QX_8I_ROWWISE_Q2_K:
	_ccv_nnc_8i_rowwise_packed_quant_q2(y, w, group);
	break;
case CCV_NNC_QX_8I_ROWWISE_IQ2_XXS:
	_ccv_nnc_8i_rowwise_packed_quant_iq2_xxs(y, w, group);
	break;
case CCV_NNC_QX_8I_ROWWISE_IQ2_S:
	_ccv_nnc_8i_rowwise_packed_quant_iq2_s(y, w, group);
	break;
case CCV_NNC_QX_8I_ROWWISE_IQ2_XS:
	_ccv_nnc_8i_rowwise_packed_quant_iq2_xs(y, w, group);
	break;
case CCV_NNC_QX_8I_ROWWISE_IQ3_S:
	_ccv_nnc_8i_rowwise_packed_quant_iq3_s(y, w, group);
	break;
case CCV_NNC_QX_8I_ROWWISE_IQ3_XXS:
	_ccv_nnc_8i_rowwise_packed_quant_iq3_xxs(y, w, group);
	break;
default:
	assert(0)((void) sizeof ((0) ? 1 : 0), __extension__ ({ if (0) ; else __assert_fail
 ("0", "ccv_nnc_8i_rowwise.c", 1468, __extension__ __PRETTY_FUNCTION__
); }));
}
1470}

1472static void _ccv_nnc_8i_rowwise_packed_pack_group(uint8_t* const output, const size_t group_index, const int format, const ccv_nnc_8i_rowwise_packed_group_t* const group)
1473{
const size_t bit_offset = group_index * ccv_nnc_8i_rowwise_x_group_bits(format);
size_t bit = bit_offset;
int j;
switch (format)
{
case CCV_NNC_QX_8I_ROWWISE_IQ1_S:
	for (j = 0; j < 4; j++)
		_ccv_nnc_8i_rowwise_packed_write_bits(output, bit + j * 11, (uint32_t)group->grid[j], 11);
	_ccv_nnc_8i_rowwise_packed_write_bits(output, bit + 44, group->signs & 7, 3);
	_ccv_nnc_8i_rowwise_packed_write_bits(output, bit + 47, (uint32_t)group->scale, 3);
	break;
case CCV_NNC_QX_8I_ROWWISE_IQ1_M:
	for (j = 0; j < 2; j++)
		_ccv_nnc_8i_rowwise_packed_write_bits(output, bit + j * 12, (uint32_t)group->grid[j] | (((group->signs >> j) & 1) << 11), 12);
	_ccv_nnc_8i_rowwise_packed_write_bits(output, bit + 24, (uint32_t)(group->scale - 1), 4);
	break;
case CCV_NNC_QX_8I_ROWWISE_Q5_K:
	for (j = 0; j < 16; j++, bit += 5)
		_ccv_nnc_8i_rowwise_packed_write_bits(output, bit, (uint32_t)(group->q[j] + 16), 5);
	_ccv_nnc_8i_rowwise_packed_write_bits(output, bit, (uint32_t)(group->m - 1), 3);
	_ccv_nnc_8i_rowwise_packed_write_bits(output, bit + 3, (uint32_t)(group->b + 16), 5);
	break;
case CCV_NNC_QX_8I_ROWWISE_Q6_K:
	for (j = 0; j < 8; j++, bit += 6)
		_ccv_nnc_8i_rowwise_packed_write_bits(output, bit, (uint32_t)(group->q[j] & 0x3f), 6);
	_ccv_nnc_8i_rowwise_packed_write_bits(output, bit, (uint32_t)(group->m - 1), 2);
	_ccv_nnc_8i_rowwise_packed_write_bits(output, bit + 2, (uint32_t)(group->b & 3), 2);
	break;
case CCV_NNC_QX_8I_ROWWISE_Q4_K:
	for (j = 0; j < 16; j++, bit += 4)
		_ccv_nnc_8i_rowwise_packed_write_bits(output, bit, (uint32_t)(group->q[j] + 8), 4);
	_ccv_nnc_8i_rowwise_packed_write_bits(output, bit, (uint32_t)(group->m - 1), 4);
	_ccv_nnc_8i_rowwise_packed_write_bits(output, bit + 4, (uint32_t)(group->b + 8), 4);
	break;
case CCV_NNC_QX_8I_ROWWISE_Q3_K:
	for (j = 0; j < 16; j++, bit += 3)
		_ccv_nnc_8i_rowwise_packed_write_bits(output, bit, (uint32_t)(group->q[j] + 4), 3);
	_ccv_nnc_8i_rowwise_packed_write_bits(output, bit, (uint32_t)(group->m - 1), 5);
	_ccv_nnc_8i_rowwise_packed_write_bits(output, bit + 5, (uint32_t)(group->b / 2 + 4), 3);
	break;
case CCV_NNC_QX_8I_ROWWISE_Q2_K:
	for (j = 0; j < 16; j++, bit += 2)
		_ccv_nnc_8i_rowwise_packed_write_bits(output, bit, (uint32_t)group->q[j], 2);
	_ccv_nnc_8i_rowwise_packed_write_bits(output, bit, (uint32_t)(group->m - 1), 6);
	_ccv_nnc_8i_rowwise_packed_write_bits(output, bit + 6, (uint32_t)(group->z >> 3), 4);
	break;
case CCV_NNC_QX_8I_ROWWISE_IQ2_S:
	_ccv_nnc_8i_rowwise_packed_write_bits(output, bit, (uint32_t)group->grid[0], 10);
	_ccv_nnc_8i_rowwise_packed_write_bits(output, bit + 10, (uint32_t)group->grid[1], 10);
	_ccv_nnc_8i_rowwise_packed_write_bits(output, bit + 20, group->signs, 16);
	_ccv_nnc_8i_rowwise_packed_write_bits(output, bit + 36, (uint32_t)(group->scale - 1), 6);
	break;
case CCV_NNC_QX_8I_ROWWISE_IQ2_XS:
	_ccv_nnc_8i_rowwise_packed_write_bits(output, bit, (uint32_t)group->grid[0], 9);
	_ccv_nnc_8i_rowwise_packed_write_bits(output, bit + 9, group->signs, 8);
	_ccv_nnc_8i_rowwise_packed_write_bits(output, bit + 17, (uint32_t)group->scale, 4);
	break;
case CCV_NNC_QX_8I_ROWWISE_IQ2_XXS:
	for (j = 0; j < 4; j++)
		_ccv_nnc_8i_rowwise_packed_write_bits(output, bit + j * 8, (uint32_t)group->grid[j], 8);
	_ccv_nnc_8i_rowwise_packed_write_bits(output, bit + 32, group->signs, 28);
	_ccv_nnc_8i_rowwise_packed_write_bits(output, bit + 60, (uint32_t)group->scale, 4);
	break;
case CCV_NNC_QX_8I_ROWWISE_IQ3_S:
	for (j = 0; j < 4; j++)
		_ccv_nnc_8i_rowwise_packed_write_bits(output, bit + j * 9, (uint32_t)group->grid[j], 9);
	_ccv_nnc_8i_rowwise_packed_write_bits(output, bit + 36, group->signs, 16);
	_ccv_nnc_8i_rowwise_packed_write_bits(output, bit + 52, (uint32_t)(group->scale - 1), 4);
	break;
case CCV_NNC_QX_8I_ROWWISE_IQ3_XXS:
	_ccv_nnc_8i_rowwise_packed_write_bits(output, bit, (uint32_t)group->grid[0], 8);
	_ccv_nnc_8i_rowwise_packed_write_bits(output, bit + 8, (uint32_t)group->grid[1], 8);
	_ccv_nnc_8i_rowwise_packed_write_bits(output, bit + 16, group->signs, 8);
	_ccv_nnc_8i_rowwise_packed_write_bits(output, bit + 24, (uint32_t)(group->scale - 1), 4);
	break;
default:
	assert(0)((void) sizeof ((0) ? 1 : 0), __extension__ ({ if (0) ; else __assert_fail
 ("0", "ccv_nnc_8i_rowwise.c", 1550, __extension__ __PRETTY_FUNCTION__
); }));
}
1552}

1554static void _ccv_nnc_8i_rowwise_packed_decode_group(const uint8_t* const input, const size_t group_index, const int format, int* const q8)
1555{
static const int q2_xs_scales[16] = {1, 2, 3, 4, 5, 6, 7, 8, 10, 12, 14, 16, 20, 24, 28, 32};
const size_t bit_offset = group_index * ccv_nnc_8i_rowwise_x_group_bits(format);
size_t bit = bit_offset;
int j;
switch (format)
{
case CCV_NNC_QX_8I_ROWWISE_IQ1_S: {
	uint32_t shifts = _ccv_nnc_8i_rowwise_packed_read_bits(input, bit + 44, 3);
	shifts |= ((shifts ^ (shifts >> 1) ^ (shifts >> 2)) & 1) << 3;
	const int m = ccv_nnc_8i_rowwise_packed_iq1s_scales[_ccv_nnc_8i_rowwise_packed_read_bits(input, bit + 47, 3)];
	int sg;
	for (sg = 0; sg < 4; sg++)
	{
		const int index = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit + sg * 11, 11);
		const int shift = (shifts & (1u << sg)) ? -1 : 1;
		for (j = 0; j < 8; j++)
		{
			const int g = (int)((ccv_nnc_8i_rowwise_packed_iq1_grid[index] >> (2 * j)) & 3) - 1;
			q8[sg * 8 + j] = ccv_clamp(m * (8 * g + shift), -127, 127)({ typeof (-127) _a = (-127); typeof (127) _b = (127); typeof
 (m * (8 * g + shift)) _x = (m * (8 * g + shift)); (_x < _a
) ? _a : ((_x > _b) ? _b : _x); });
		}
	}
	break;
}
case CCV_NNC_QX_8I_ROWWISE_IQ1_M: {
	const int m = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit + 24, 4) + 1;
	int sg;
	for (sg = 0; sg < 2; sg++)
	{
		const uint32_t code = _ccv_nnc_8i_rowwise_packed_read_bits(input, bit + sg * 12, 12);
		const int shift = (code & 2048) ? -1 : 1;
		for (j = 0; j < 8; j++)
		{
			const int g = (int)((ccv_nnc_8i_rowwise_packed_iq1_grid[code & 2047] >> (2 * j)) & 3) - 1;
			q8[sg * 8 + j] = ccv_clamp(m * (8 * g + shift), -127, 127)({ typeof (-127) _a = (-127); typeof (127) _b = (127); typeof
 (m * (8 * g + shift)) _x = (m * (8 * g + shift)); (_x < _a
) ? _a : ((_x > _b) ? _b : _x); });
		}
	}
	break;
}
case CCV_NNC_QX_8I_ROWWISE_Q5_K: {
	int q[16];
	for (j = 0; j < 16; j++, bit += 5)
		q[j] = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit, 5) - 16;
	const int m = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit, 3) + 1;
	const int b = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit + 3, 5) - 16;
	for (j = 0; j < 16; j++)
		q8[j] = q[j] * m + b;
	break;
}
case CCV_NNC_QX_8I_ROWWISE_Q6_K: {
	int q[8];
	for (j = 0; j < 8; j++, bit += 6)
		q[j] = _ccv_nnc_8i_rowwise_packed_sign_extend(_ccv_nnc_8i_rowwise_packed_read_bits(input, bit, 6), 6);
	const int m = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit, 2) + 1;
	const int b = _ccv_nnc_8i_rowwise_packed_sign_extend(_ccv_nnc_8i_rowwise_packed_read_bits(input, bit + 2, 2), 2);
	for (j = 0; j < 8; j++)
		q8[j] = q[j] * m + b;
	break;
}
case CCV_NNC_QX_8I_ROWWISE_Q4_K: {
	int q[16];
	for (j = 0; j < 16; j++, bit += 4)
		q[j] = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit, 4) - 8;
	const int m = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit, 4) + 1;
	const int b = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit + 4, 4) - 8;
	for (j = 0; j < 16; j++)
		q8[j] = q[j] * m + b;
	break;
}
case CCV_NNC_QX_8I_ROWWISE_Q3_K: {
	int q[16];
	for (j = 0; j < 16; j++, bit += 3)
		q[j] = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit, 3) - 4;
	const int m = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit, 5) + 1;
	const int b = ((int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit + 5, 3) - 4) << 1;
	for (j = 0; j < 16; j++)
		q8[j] = q[j] * m + b;
	break;
}
case CCV_NNC_QX_8I_ROWWISE_Q2_K: {
	int q[16];
	for (j = 0; j < 16; j++, bit += 2)
		q[j] = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit, 2);
	const int m = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit, 6) + 1;
	const int z = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit + 6, 4) << 3;
	for (j = 0; j < 16; j++)
		q8[j] = q[j] * m - z;
	break;
}
case CCV_NNC_QX_8I_ROWWISE_IQ2_S: {
	const int grid0 = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit, 10);
	const int grid1 = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit + 10, 10);
	const uint32_t signs = _ccv_nnc_8i_rowwise_packed_read_bits(input, bit + 20, 16);
	const int scale = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit + 36, 6) + 1;
	for (j = 0; j < 8; j++)
	{
		const int mag0 = ccv_min(_ccv_nnc_8i_rowwise_packed_iq2_value(ccv_nnc_8i_rowwise_packed_iq2s_grid, grid0, j) * scale, 127)({ typeof (_ccv_nnc_8i_rowwise_packed_iq2_value(ccv_nnc_8i_rowwise_packed_iq2s_grid
, grid0, j) * scale) _a = (_ccv_nnc_8i_rowwise_packed_iq2_value
(ccv_nnc_8i_rowwise_packed_iq2s_grid, grid0, j) * scale); typeof
 (127) _b = (127); (_a < _b) ? _a : _b; });
		const int mag1 = ccv_min(_ccv_nnc_8i_rowwise_packed_iq2_value(ccv_nnc_8i_rowwise_packed_iq2s_grid, grid1, j) * scale, 127)({ typeof (_ccv_nnc_8i_rowwise_packed_iq2_value(ccv_nnc_8i_rowwise_packed_iq2s_grid
, grid1, j) * scale) _a = (_ccv_nnc_8i_rowwise_packed_iq2_value
(ccv_nnc_8i_rowwise_packed_iq2s_grid, grid1, j) * scale); typeof
 (127) _b = (127); (_a < _b) ? _a : _b; });
		q8[j] = (signs & (1u << j)) ? -mag0 : mag0;
		q8[8 + j] = (signs & (1u << (8 + j))) ? -mag1 : mag1;
	}
	break;
}
case CCV_NNC_QX_8I_ROWWISE_IQ2_XS: {
	const int grid0 = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit, 9);
	const uint32_t signs = _ccv_nnc_8i_rowwise_packed_read_bits(input, bit + 9, 8);
	const int scale = q2_xs_scales[_ccv_nnc_8i_rowwise_packed_read_bits(input, bit + 17, 4)];
	for (j = 0; j < 8; j++)
	{
		const int mag = ccv_min(_ccv_nnc_8i_rowwise_packed_iq2_value(ccv_nnc_8i_rowwise_packed_iq2xs_grid, grid0, j) * scale, 127)({ typeof (_ccv_nnc_8i_rowwise_packed_iq2_value(ccv_nnc_8i_rowwise_packed_iq2xs_grid
, grid0, j) * scale) _a = (_ccv_nnc_8i_rowwise_packed_iq2_value
(ccv_nnc_8i_rowwise_packed_iq2xs_grid, grid0, j) * scale); typeof
 (127) _b = (127); (_a < _b) ? _a : _b; });
		q8[j] = (signs & (1u << j)) ? -mag : mag;
	}
	break;
}
case CCV_NNC_QX_8I_ROWWISE_IQ2_XXS: {
	int grid[4];
	for (j = 0; j < 4; j++)
		grid[j] = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit + j * 8, 8);
	const uint32_t sign_codes = _ccv_nnc_8i_rowwise_packed_read_bits(input, bit + 32, 28);
	const int scale = ccv_nnc_8i_rowwise_packed_iq2xxs_scales[_ccv_nnc_8i_rowwise_packed_read_bits(input, bit + 60, 4)];
	int sg;
	for (sg = 0; sg < 4; sg++)
	{
		const uint8_t signs = ccv_nnc_8i_rowwise_packed_iq2xxs_ksigns[(sign_codes >> (sg * 7)) & 0x7f];
		for (j = 0; j < 8; j++)
		{
			const int lane = sg * 8 + j;
			const int mag = ccv_min(_ccv_nnc_8i_rowwise_packed_iq2xxs_value(grid[sg], j) * scale, 127)({ typeof (_ccv_nnc_8i_rowwise_packed_iq2xxs_value(grid[sg], j
) * scale) _a = (_ccv_nnc_8i_rowwise_packed_iq2xxs_value(grid
[sg], j) * scale); typeof (127) _b = (127); (_a < _b) ? _a
 : _b; });
			q8[lane] = (signs & (1u << j)) ? -mag : mag;
		}
	}
	break;
}
case CCV_NNC_QX_8I_ROWWISE_IQ3_S: {
	int grid[4];
	for (j = 0; j < 4; j++)
		grid[j] = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit + j * 9, 9);
	const uint32_t signs = _ccv_nnc_8i_rowwise_packed_read_bits(input, bit + 36, 16);
	const int scale = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit + 52, 4) + 1;
	int sg;
	for (sg = 0; sg < 4; sg++)
		for (j = 0; j < 4; j++)
		{
			const int lane = sg * 4 + j;
			const int mag = ccv_min(_ccv_nnc_8i_rowwise_packed_iq3s_value(grid[sg], j) * scale, 127)({ typeof (_ccv_nnc_8i_rowwise_packed_iq3s_value(grid[sg], j)
 * scale) _a = (_ccv_nnc_8i_rowwise_packed_iq3s_value(grid[sg
], j) * scale); typeof (127) _b = (127); (_a < _b) ? _a : _b
; });
			q8[lane] = (signs & (1u << lane)) ? -mag : mag;
		}
	break;
}
case CCV_NNC_QX_8I_ROWWISE_IQ3_XXS: {
	const int grid0 = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit, 8);
	const int grid1 = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit + 8, 8);
	const uint32_t signs = _ccv_nnc_8i_rowwise_packed_read_bits(input, bit + 16, 8);
	const int scale = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit + 24, 4) + 1;
	for (j = 0; j < 4; j++)
	{
		const int mag0 = ccv_min(_ccv_nnc_8i_rowwise_packed_iq3xxs_value(grid0, j) * scale, 127)({ typeof (_ccv_nnc_8i_rowwise_packed_iq3xxs_value(grid0, j) *
 scale) _a = (_ccv_nnc_8i_rowwise_packed_iq3xxs_value(grid0, j
) * scale); typeof (127) _b = (127); (_a < _b) ? _a : _b; }
);
		const int mag1 = ccv_min(_ccv_nnc_8i_rowwise_packed_iq3xxs_value(grid1, j) * scale, 127)({ typeof (_ccv_nnc_8i_rowwise_packed_iq3xxs_value(grid1, j) *
 scale) _a = (_ccv_nnc_8i_rowwise_packed_iq3xxs_value(grid1, j
) * scale); typeof (127) _b = (127); (_a < _b) ? _a : _b; }
);
		q8[j] = (signs & (1u << j)) ? -mag0 : mag0;
		q8[4 + j] = (signs & (1u << (4 + j))) ? -mag1 : mag1;
	}
	break;
}
default:
	assert(0)((void) sizeof ((0) ? 1 : 0), __extension__ ({ if (0) ; else __assert_fail
 ("0", "ccv_nnc_8i_rowwise.c", 1719, __extension__ __PRETTY_FUNCTION__
); }));
}
1721}

1723// Regular normalized H256, matching NAInt8MatMul activation staging. This is
1724// not the Sylvester WHT. Transform the existing floating row before fitting scales.
1725static void _ccv_nnc_8i_rowwise_hadamard_256(double* const row, const size_t row_length)
1726{
size_t base;
for (base = 0; base < row_length; base += 256)
{
int stride;
for (stride = 1; stride < 256; stride *= 4)
{
	int i, j;
	for (i = 0; i < 256; i += stride * 4)
		for (j = 0; j < stride; j++)
		{
			double* const v = row + base + i + j;
			const double a = v[0], b = v[stride], c = v[stride * 2], d = v[stride * 3];
			v[0] = a + b + c - d;
			v[stride] = a + b - c + d;
			v[stride * 2] = a - b + c + d;
			v[stride * 3] = -a + b + c + d;
		}
}
int i;
for (i = 0; i < 256; i++)
	row[base + i] *= 1. / 16.;
}
1749}

1751typedef struct {
const float* hessian; // row_length x row_length Hessian of the current slice, e.g. input second moments.
double* hessian64; // Double copy of hessian for BLAS products; 0 without BLAS.
double ridge; // Added to the Hessian diagonal to keep it positive definite.
double* u; // Feedback coefficients U[j][k] for lane j and lanes k in later groups.
double* rbb; // Upper-triangular diagonal blocks R_bb of H = R R^T, one group_size^2 block per group.
double* weights; // Conditional variances diag(D_b) = diag(R_bb R_bb^T), 0 for padded lanes.
1758} ccv_nnc_8i_rowwise_x_feedback_t;

1760// a[i][j] -= sum_{m in [k0, k1)} a[i][m] a[j][m] for i <= j < k0.
1761static void _ccv_nnc_8i_rowwise_x_rank_update(double* const a, const size_t n, const size_t k0, const size_t k1)
1762{
1763#if (defined HAVE_CBLAS1 || defined HAVE_ACCELERATE_FRAMEWORK)
cblas_dsyrk(CblasRowMajor, CblasUpper, CblasNoTrans, (int)k0, (int)(k1 - k0), -1, a + k0, (int)n, 1, a, (int)n);
1765#else
const size_t w = k1 - k0;
double* const panel = (double*)ccmallocmalloc(sizeof(double) * k0 * w);
size_t i;
for (i = 0; i < k0; i++)
memcpy(panel + i * w, a + i * n + k0, sizeof(double) * w);
const size_t blocks = (k0 + 15) / 16;
1772#ifdef USE_DISPATCH
dispatch_apply(blocks, dispatch_get_global_queue(DISPATCH_QUEUE_PRIORITY_DEFAULT, 0), ^(size_t block_idx) {
1774#else
parallel_for(block_idx, (int)blocks){ int block_idx; for ((block_idx) = 0; (block_idx) < ((int
)blocks); (block_idx)++) { {
1776#endif
const size_t row_end = ccv_min(((size_t)block_idx + 1) * 16, k0)({ typeof (((size_t)block_idx + 1) * 16) _a = (((size_t)block_idx
 + 1) * 16); typeof (k0) _b = (k0); (_a < _b) ? _a : _b; }
);
size_t r, j, m;
for (r = (size_t)block_idx * 16; r < row_end; r++)
{
	const double* const pr = panel + r * w;
	for (j = r; j < k0; j++)
	{
		const double* const pj = panel + j * w;
		double v = 0;
		for (m = 0; m < w; m++)
			v += pr[m] * pj[m];
		a[r * n + j] -= v;
	}
}
1791#ifdef USE_DISPATCH
});
1793#else
} parallel_endfor} }
1795#endif
ccfreefree(panel);
1797#endif
1798}

1800// Factor H = R R^T with R upper triangular, in place on the upper triangle of a, starting from the
1801// last column so that column k only depends on lanes at or after k. Columns go in panels: factor the
1802// panel's diagonal block, solve each row above it on its contiguous panel segment, then one rank-k
1803// update of the leading block.
1804static int _ccv_nnc_8i_rowwise_x_reverse_cholesky(double* const a, const size_t n)
1805{
size_t k1 = n;
while (k1 > 0)
{
const size_t k0 = k1 > CCV_NNC_8I_ROWWISE_X_CHOLESKY_PANEL ? k1 - CCV_NNC_8I_ROWWISE_X_CHOLESKY_PANEL : 0;
size_t k = k1;
while (k-- > k0)
{
	const double d = a[k * n + k];
	if (!(d > 0))
		return 0;
	const double rkk = sqrt(d);
	a[k * n + k] = rkk;
	size_t i, j;
	for (i = k0; i < k; i++)
		a[i * n + k] /= rkk;
	for (i = k0; i < k; i++)
	{
		const double ci = a[i * n + k];
		for (j = i; j < k; j++)
			a[i * n + j] -= ci * a[j * n + k];
	}
}
// R[i][m] = (H[i][m] - sum_{p in (m, k1)} R[i][p] R[m][p]) / R[m][m] for rows i above the panel.
const size_t blocks = (k0 + 63) / 64;
1830#ifdef USE_DISPATCH
dispatch_apply(blocks, dispatch_get_global_queue(DISPATCH_QUEUE_PRIORITY_DEFAULT, 0), ^(size_t block_idx) {
1832#else
parallel_for(block_idx, (int)blocks){ int block_idx; for ((block_idx) = 0; (block_idx) < ((int
)blocks); (block_idx)++) { {
1834#endif
	const size_t row_end = ccv_min(((size_t)block_idx + 1) * 64, k0)({ typeof (((size_t)block_idx + 1) * 64) _a = (((size_t)block_idx
 + 1) * 64); typeof (k0) _b = (k0); (_a < _b) ? _a : _b; }
);
	size_t r;
	for (r = (size_t)block_idx * 64; r < row_end; r++)
	{
		double* const ar = a + r * n;
		size_t m = k1;
		while (m-- > k0)
		{
			const double* const am = a + m * n;
			double v = ar[m];
			size_t p;
			for (p = m + 1; p < k1; p++)
				v -= ar[p] * am[p];
			ar[m] = v / am[m];
		}
	}
1851#ifdef USE_DISPATCH
});
1853#else
} parallel_endfor} }
1855#endif
if (k0 > 0)
	_ccv_nnc_8i_rowwise_x_rank_update(a, n, k0, k1);
k1 = k0;
}
return 1;
1861}

1863// Block UDU^T of H = hessian + ridge I over quantization groups, U unit upper block-triangular. Walking
1864// the groups in order with targets t_k = x_k + sum_{j in earlier groups} e_j U[j][k], where e = x - x_hat,
1865// makes e H e^T = sum_b r_b D_b r_b^T for the rounding residuals r = t - x_hat. Each group then only rounds
1866// against D_b (the input variance conditioned on later groups) instead of the imatrix diagonal.
1867static void _ccv_nnc_8i_rowwise_x_feedback_init(ccv_nnc_8i_rowwise_x_feedback_t* const feedback, const float* const hessian, const size_t row_length, const size_t padded_row_length, const size_t group_size)
1868{
double* const u = feedback->u;
const size_t n = padded_row_length;
size_t i, j;
double mean_diag = 0;
for (i = 0; i < row_length; i++)
mean_diag += hessian[i * row_length + i];
mean_diag /= (double)row_length;
if (!(mean_diag > 0))
mean_diag = 1;
double ridge = mean_diag * 1e-6;
int factored = 0;
int attempt;
for (attempt = 0; !factored && attempt < 8; attempt++)
{
if (attempt > 0)
	ridge *= 10;
for (i = 0; i < n; i++)
{
	for (j = i; j < n; j++)
		u[i * n + j] = (j < row_length) ? hessian[i * row_length + j] : 0;
	u[i * n + i] += i < row_length ? ridge : mean_diag;
}
factored = _ccv_nnc_8i_rowwise_x_reverse_cholesky(u, n);
}
if (!factored)
{
// Not positive definite even with a large ridge (non-finite input): drop the feedback.
memset(u, 0, sizeof(double) * n * n);
for (i = 0; i < n; i++)
	u[i * n + i] = sqrt(i < row_length ? ccv_max((double)hessian[i * row_length + i], 0.)({ typeof ((double)hessian[i * row_length + i]) _a = ((double
)hessian[i * row_length + i]); typeof (0.) _b = (0.); (_a >
 _b) ? _a : _b; }) + ridge : mean_diag);
}
feedback->hessian = hessian;
feedback->ridge = ridge;
if (feedback->hessian64)
for (i = 0; i < row_length * row_length; i++)
	feedback->hessian64[i] = hessian[i];
const size_t groups = n / group_size;
size_t g;
for (g = 0; g < groups; g++)
{
const size_t s = g * group_size;
double* const rbb = feedback->rbb + g * group_size * group_size;
size_t m, l;
for (m = 0; m < group_size; m++)
{
	double d = 0;
	for (l = 0; l < group_size; l++)
	{
		const double v = l >= m ? u[(s + m) * n + s + l] : 0;
		rbb[m * group_size + l] = v;
		d += v * v;
	}
	feedback->weights[s + m] = s + m < row_length ? d : 0;
}
if (s == 0)
	continue;
double inv_data[32 * 32] = {0};
double* const inv = inv_data;
for (l = 0; l < group_size; l++)
{
	inv[l * group_size + l] = 1. / rbb[l * group_size + l];
	m = l;
	while (m-- > 0)
	{
		double v = 0;
		size_t t;
		for (t = m + 1; t <= l; t++)
			v += rbb[m * group_size + t] * inv[t * group_size + l];
		inv[m * group_size + l] = -v / rbb[m * group_size + m];
	}
}
// U[j][group g] = R[j][group g] R_gg^-1 for every lane j in earlier groups.
const size_t blocks = (s + 63) / 64;
1942#ifdef USE_DISPATCH
dispatch_apply(blocks, dispatch_get_global_queue(DISPATCH_QUEUE_PRIORITY_DEFAULT, 0), ^(size_t block_idx) {
1944#else
parallel_for(block_idx, (int)blocks){ int block_idx; for ((block_idx) = 0; (block_idx) < ((int
)blocks); (block_idx)++) { {
1946#endif
	const size_t row_end = ccv_min(((size_t)block_idx + 1) * 64, s)({ typeof (((size_t)block_idx + 1) * 64) _a = (((size_t)block_idx
 + 1) * 64); typeof (s) _b = (s); (_a < _b) ? _a : _b; });
	size_t r, a, b;
	for (r = (size_t)block_idx * 64; r < row_end; r++)
	{
		double* const ur = u + r * n + s;
		double t[32];
		for (b = 0; b < group_size; b++)
		{
			double v = 0;
			for (a = 0; a <= b; a++)
				v += ur[a] * inv[a * group_size + b];
			t[b] = v;
		}
		memcpy(ur, t, sizeof(double) * group_size);
	}
1962#ifdef USE_DISPATCH
});
1964#else
} parallel_endfor} }
1966#endif
}
1968}

1970typedef struct {
const void* input;
int datatype;
int format;
int codec;
int starts;
size_t row_length;
size_t row_count;
const float* imatrix;
size_t imatrix_length;
size_t group_size;
size_t groups_per_row;
size_t padded_row_length;
const int16_t* iq1_map;
uint8_t* u8;
uint8_t* scales;
1986} ccv_nnc_8i_rowwise_x_rows_t;

1988static double _ccv_nnc_8i_rowwise_x_start_scale(const double max_abs, const int start, const int starts, const int datatype)
1989{
double scale = max_abs / 127.;
if (starts == 3)
{
scale *= start == 0 ? 0.75 : start == 1 ? 1. : 1.25;
if (datatype == CCV_16F && max_abs > 0 && _ccv_nnc_8i_rowwise_packed_stored_scale(scale, datatype) == 0)
	scale = 0x1p-24;
}
return scale;
1998}

2000static void _ccv_nnc_8i_rowwise_x_pack_row(const ccv_nnc_8i_rowwise_x_rows_t* const ctx, const size_t i, const double* const row, const double* const weights, const int has_best, const double best_scale, const ccv_nnc_8i_rowwise_packed_group_t* const best_groups)
2001{
const size_t group_size = ctx->group_size;
_ccv_nnc_8i_rowwise_packed_store_scale(ctx->scales, ctx->datatype, i, best_scale);
size_t g, j;
if (has_best)
{
for (g = 0; g < ctx->groups_per_row; g++)
	_ccv_nnc_8i_rowwise_packed_pack_group(ctx->u8, i * ctx->groups_per_row + g, ctx->codec, best_groups + g);
} else {
for (g = 0; g < ctx->groups_per_row; g++)
{
	double y[32] = {0};
	double w[32] = {0};
	for (j = 0; j < group_size; j++)
	{
		y[j] = row[g * group_size + j];
		w[j] = weights[g * group_size + j];
	}
	ccv_nnc_8i_rowwise_packed_group_t group;
	_ccv_nnc_8i_rowwise_packed_quant_group(ctx->codec, y, w, ctx->iq1_map, &group);
	_ccv_nnc_8i_rowwise_packed_pack_group(ctx->u8, i * ctx->groups_per_row + g, ctx->codec, &group);
}
}
2024}

2026static void _ccv_nnc_8i_rowwise_x_quantize_rows(const ccv_nnc_8i_rowwise_x_rows_t* const ctx, const size_t row_begin, const size_t row_end)
2027{
const size_t row_length = ctx->row_length;
const size_t padded_row_length = ctx->padded_row_length;
const size_t group_size = ctx->group_size;
const size_t groups_per_row = ctx->groups_per_row;
const int datatype = ctx->datatype;
double* const row = (double*)ccmallocmalloc(sizeof(double) * padded_row_length);
39
←
Storing uninitialized value→
double* const weights = (double*)ccmallocmalloc(sizeof(double) * padded_row_length);
ccv_nnc_8i_rowwise_packed_group_t* const groups = (ccv_nnc_8i_rowwise_packed_group_t*)ccmallocmalloc(sizeof(ccv_nnc_8i_rowwise_packed_group_t) * groups_per_row);
ccv_nnc_8i_rowwise_packed_group_t* const best_groups = (ccv_nnc_8i_rowwise_packed_group_t*)ccmallocmalloc(sizeof(ccv_nnc_8i_rowwise_packed_group_t) * groups_per_row);
size_t i;
for (i = row_begin; i < row_end; i++)
40
←
Assuming 'i' is < 'row_end'→
41
←
Loop condition is true.  Entering loop body→
{
const size_t row_start = i * row_length;
const float* const row_imatrix = _ccv_nnc_8i_rowwise_imatrix_for_row(ctx->imatrix, ctx->imatrix_length, row_length, ctx->row_count, i);
_ccv_nnc_8i_rowwise_packed_read_row(ctx->input, datatype, row_start, row_length, padded_row_length, row);
42
←
Calling '_ccv_nnc_8i_rowwise_packed_read_row'→
51
←
Returning from '_ccv_nnc_8i_rowwise_packed_read_row'→
if (ctx->format & CCV_NNC_QX_8I_ROWWISE_HADAMARD_256)
52
←
Taking false branch→
	_ccv_nnc_8i_rowwise_hadamard_256(row, row_length);
double max_abs = 0;
size_t j;
for (j = 0; j < row_length; j++)
53
←
Loop condition is true.  Entering loop body→
56
←
Loop condition is false. Execution continues on line 2052→
{
	max_abs = ccv_max(max_abs, fabs(row[j]))({ typeof (max_abs) _a = (max_abs); typeof (fabs(row[j])) _b =
 (fabs(row[j])); (_a > _b) ? _a : _b; });
54
←
Assuming '_a' is <= '_b'→
55
←
'?' condition is false→
	weights[j] = _ccv_nnc_8i_rowwise_weight(row_imatrix, j);
}
for (; j56.1
'j' is >= 'padded_row_length'
 < padded_row_length; j++)
57
←
Loop condition is false. Execution continues on line 2054→
	weights[j] = 0;
double best_scale = 0;
double best_sse = DBL_MAX1.7976931348623157e+308;
int has_best = 0;
int start;
for (start = 0; start < ctx->starts; start++)
58
←
Loop condition is true.  Entering loop body→
{
	double scale = _ccv_nnc_8i_rowwise_x_start_scale(max_abs, start, ctx->starts, datatype);
	int k;
	for (k = 0; k < CCV_NNC_8I_ROWWISE_X_REFINEMENT_STEPS; k++)
59
←
Loop condition is true.  Entering loop body→
	{
		const double stored_scale = _ccv_nnc_8i_rowwise_packed_stored_scale(scale, datatype);
		if (!(stored_scale > 0))
60
←
Assuming 'stored_scale' is > 0→
61
←
Taking false branch→
			break;
		double sse = 0;
		double sum_qx = 0;
		double sum_qq = 0;
		size_t g;
		for (g = 0; g < groups_per_row; g++)
62
←
Assuming 'g' is < 'groups_per_row'→
63
←
Loop condition is true.  Entering loop body→
		{
			double y[32] = {0};
			double w[32] = {0};
			for (j = 0; j < group_size; j++)
64
←
Assuming 'j' is < 'group_size'→
65
←
Loop condition is true.  Entering loop body→
66
←
Assuming 'j' is < 'group_size'→
67
←
Loop condition is true.  Entering loop body→
			{
				y[j] = row[g * group_size + j] / stored_scale;
68
←
The left operand of '/' is a garbage value
				w[j] = weights[g * group_size + j];
			}
			ccv_nnc_8i_rowwise_packed_group_t group;
			_ccv_nnc_8i_rowwise_packed_quant_group(ctx->codec, y, w, ctx->iq1_map, &group);
			groups[g] = group;
			const size_t group_start = g * group_size;
			const size_t group_end = ccv_min(group_start + group_size, row_length)({ typeof (group_start + group_size) _a = (group_start + group_size
); typeof (row_length) _b = (row_length); (_a < _b) ? _a :
 _b; });
			for (j = group_start; j < group_end; j++)
			{
				const int q8 = group.q8[j - group_start];
				const double d = row[j] - stored_scale * q8;
				sse += weights[j] * d * d;
				sum_qx += weights[j] * q8 * row[j];
				sum_qq += weights[j] * q8 * q8;
			}
		}
		if (sse < best_sse)
		{
			best_sse = sse;
			best_scale = stored_scale;
			has_best = 1;
			memcpy(best_groups, groups, sizeof(ccv_nnc_8i_rowwise_packed_group_t) * groups_per_row);
		}
		if (!(sum_qq > 0) || !(sum_qx > 0))
			break;
		const double next_scale = sum_qx / sum_qq;
		if (_ccv_nnc_8i_rowwise_packed_stored_scale(next_scale, datatype) == stored_scale)
			break;
		scale = next_scale;
	}
}
_ccv_nnc_8i_rowwise_x_pack_row(ctx, i, row, weights, has_best, best_scale, best_groups);
}
ccfreefree(best_groups);
ccfreefree(groups);
ccfreefree(weights);
ccfreefree(row);
2115}

2117// The same refinement as the imatrix path, with each pass adding group errors into later targets. Rows of a
2118// chunk run their passes in lockstep so every pass reads the feedback matrix once per chunk, not per row.
2119static void _ccv_nnc_8i_rowwise_x_quantize_rows_feedback(const ccv_nnc_8i_rowwise_x_rows_t* const ctx, const ccv_nnc_8i_rowwise_x_feedback_t* const fb, const size_t row_begin, const size_t row_end)
2120{
enum { R = CCV_NNC_8I_ROWWISE_X_FEEDBACK_ROWS };
const size_t rows = row_end - row_begin;
assert(rows <= R)((void) sizeof ((rows <= R) ? 1 : 0), __extension__ ({ if (
rows <= R) ; else __assert_fail ("rows <= R", "ccv_nnc_8i_rowwise.c"
, 2123, __extension__ __PRETTY_FUNCTION__); }));
const size_t row_length = ctx->row_length;
const size_t n = ctx->padded_row_length;
const size_t group_size = ctx->group_size;
const size_t groups_per_row = ctx->groups_per_row;
double* const x = (double*)ccmallocmalloc(sizeof(double) * rows * n);
double* const target = (double*)ccmallocmalloc(sizeof(double) * n * R); // Lane-major: target[l * R + r].
double* const hx = (double*)ccmallocmalloc(sizeof(double) * rows * row_length);
ccv_nnc_8i_rowwise_packed_group_t* const groups = (ccv_nnc_8i_rowwise_packed_group_t*)ccmallocmalloc(sizeof(ccv_nnc_8i_rowwise_packed_group_t) * rows * groups_per_row);
ccv_nnc_8i_rowwise_packed_group_t* const best_groups = (ccv_nnc_8i_rowwise_packed_group_t*)ccmallocmalloc(sizeof(ccv_nnc_8i_rowwise_packed_group_t) * rows * groups_per_row);
double max_abs[R], xhx[R], scale[R], stored_scale[R], sse[R], sum_qx[R], best_sse[R], best_scale[R];
int has_best[R], start[R], step[R], ready[R], done[R];
double e[32][R];
size_t r, j, l;
for (r = 0; r < rows; r++)
{
double* const xr = x + r * n;
_ccv_nnc_8i_rowwise_packed_read_row(ctx->input, ctx->datatype, (row_begin + r) * row_length, row_length, n, xr);
max_abs[r] = 0;
for (j = 0; j < row_length; j++)
	max_abs[r] = ccv_max(max_abs[r], fabs(xr[j]))({ typeof (max_abs[r]) _a = (max_abs[r]); typeof (fabs(xr[j])
) _b = (fabs(xr[j])); (_a > _b) ? _a : _b; });
xhx[r] = 0;
best_sse[r] = DBL_MAX1.7976931348623157e+308;
best_scale[r] = 0;
has_best[r] = 0;
start[r] = 0;
step[r] = 0;
done[r] = 0;
scale[r] = _ccv_nnc_8i_rowwise_x_start_scale(max_abs[r], 0, ctx->starts, ctx->datatype);
}
// hx = (hessian + ridge I) x, reading each Hessian row once for the chunk.
2154#if (defined HAVE_CBLAS1 || defined HAVE_ACCELERATE_FRAMEWORK)
// hx[r][j] = sum_l hessian[j][l] x[r][l] for the whole chunk in one product.
cblas_dgemm(CblasRowMajor, CblasNoTrans, CblasTrans, (int)rows, (int)row_length, (int)row_length, 1, x, (int)n, fb->hessian64, (int)row_length, 0, hx, (int)row_length);
for (r = 0; r < rows; r++)
{
const double* const xr = x + r * n;
for (j = 0; j < row_length; j++)
{
	const double v = hx[r * row_length + j] + fb->ridge * xr[j];
	hx[r * row_length + j] = v;
	xhx[r] += xr[j] * v;
}
}
2167#else
for (j = 0; j < row_length; j++)
{
const float* const cj = fb->hessian + j * row_length;
for (r = 0; r < rows; r++)
{
	const double* const xr = x + r * n;
	double v = fb->ridge * xr[j];
	for (l = 0; l < row_length; l++)
		v += cj[l] * xr[l];
	hx[r * row_length + j] = v;
	xhx[r] += xr[j] * v;
}
}
2181#endif
for (;;)
{
int any = 0;
for (r = 0; r < rows; r++)
{
	ready[r] = 0;
	while (!done[r])
	{
		stored_scale[r] = _ccv_nnc_8i_rowwise_packed_stored_scale(scale[r], ctx->datatype);
		if (stored_scale[r] > 0)
		{
			ready[r] = 1;
			any = 1;
			break;
		}
		if (++start[r] >= ctx->starts)
			done[r] = 1;
		else {
			step[r] = 0;
			scale[r] = _ccv_nnc_8i_rowwise_x_start_scale(max_abs[r], start[r], ctx->starts, ctx->datatype);
		}
	}
	sse[r] = 0;
	sum_qx[r] = 0;
}
if (!any)
	break;
for (l = 0; l < n; l++)
	for (r = 0; r < R; r++)
		target[l * R + r] = (r < rows && ready[r]) ? x[r * n + l] : 0;
size_t g;
for (g = 0; g < groups_per_row; g++)
{
	const size_t group_start = g * group_size;
	const size_t group_end = ccv_min(group_start + group_size, row_length)({ typeof (group_start + group_size) _a = (group_start + group_size
); typeof (row_length) _b = (row_length); (_a < _b) ? _a :
 _b; });
	const size_t next_group = group_start + group_size;
	memset(e, 0, sizeof(e));
	for (r = 0; r < rows; r++)
	{
		if (!ready[r])
			continue;
		double y[32] = {0};
		double w[32] = {0};
		for (j = 0; j < group_size; j++)
		{
			y[j] = target[(group_start + j) * R + r] / stored_scale[r];
			w[j] = fb->weights[group_start + j];
		}
		ccv_nnc_8i_rowwise_packed_group_t* const group = groups + r * groups_per_row + g;
		_ccv_nnc_8i_rowwise_packed_quant_group(ctx->codec, y, w, ctx->iq1_map, group);
		double res[32] = {0};
		for (j = group_start; j < group_end; j++)
		{
			const int q8 = group->q8[j - group_start];
			res[j - group_start] = target[j * R + r] - stored_scale[r] * q8;
			e[j - group_start][r] = x[r * n + j] - stored_scale[r] * q8;
			sum_qx[r] += q8 * hx[r * row_length + j];
		}
		// r_b D_b r_b^T = |r_b R_bb|^2.
		const double* const rbb = fb->rbb + g * group_size * group_size;
		size_t m;
		for (l = 0; l < group_size; l++)
		{
			double v = 0;
			for (m = 0; m <= l; m++)
				v += res[m] * rbb[m * group_size + l];
			sse[r] += v * v;
		}
	}
2251#if (defined HAVE_CBLAS1 || defined HAVE_ACCELERATE_FRAMEWORK)
	// target[l][r] += sum_j U[group_start + j][l] e[j][r] for every later lane l, as one product.
	if (next_group < n)
		cblas_dgemm(CblasRowMajor, CblasTrans, CblasNoTrans, (int)(n - next_group), R, (int)(group_end - group_start), 1, fb->u + group_start * n + next_group, (int)n, &e[0][0], R, 1, target + next_group * R, R);
2255#else
	// Later lanes in tiles that stay in cache across this group's feedback rows.
	size_t l0;
	for (l0 = next_group; l0 < n; l0 += 64)
	{
		const size_t l1 = ccv_min(l0 + 64, n)({ typeof (l0 + 64) _a = (l0 + 64); typeof (n) _b = (n); (_a <
 _b) ? _a : _b; });
		for (j = 0; j < group_end - group_start; j++)
		{
			const double* const uj = fb->u + (group_start + j) * n;
			const double* const ej = e[j];
			for (l = l0; l < l1; l++)
			{
				const double u = uj[l];
				double* const t = target + l * R;
				for (r = 0; r < R; r++)
					t[r] += ej[r] * u;
			}
		}
	}
2274#endif
}
for (r = 0; r < rows; r++)
{
	if (!ready[r])
		continue;
	// sse = e H e^T = x H x - 2 s q H x + s^2 q H q.
	const double s = stored_scale[r];
	const double sum_qq = (sse[r] - xhx[r] + 2 * s * sum_qx[r]) / (s * s);
	if (sse[r] < best_sse[r])
	{
		best_sse[r] = sse[r];
		best_scale[r] = s;
		has_best[r] = 1;
		memcpy(best_groups + r * groups_per_row, groups + r * groups_per_row, sizeof(ccv_nnc_8i_rowwise_packed_group_t) * groups_per_row);
	}
	int next_start = 1;
	if (sum_qq > 0 && sum_qx[r] > 0)
	{
		const double next_scale = sum_qx[r] / sum_qq;
		if (_ccv_nnc_8i_rowwise_packed_stored_scale(next_scale, ctx->datatype) != s && ++step[r] < CCV_NNC_8I_ROWWISE_X_REFINEMENT_STEPS)
		{
			scale[r] = next_scale;
			next_start = 0;
		}
	}
	if (next_start)
	{
		step[r] = 0;
		if (++start[r] >= ctx->starts)
			done[r] = 1;
		else
			scale[r] = _ccv_nnc_8i_rowwise_x_start_scale(max_abs[r], start[r], ctx->starts, ctx->datatype);
	}
}
}
for (r = 0; r < rows; r++)
_ccv_nnc_8i_rowwise_x_pack_row(ctx, row_begin + r, x + r * n, fb->weights, has_best[r], best_scale[r], best_groups + r * groups_per_row);
ccfreefree(best_groups);
ccfreefree(groups);
ccfreefree(hx);
ccfreefree(target);
ccfreefree(x);
2317}

2319static size_t _ccv_nnc_quantize_8i_rowwise_x(const void* input, const int datatype, const size_t input_length, const size_t row_length, const int format, const float* const imatrix, const size_t imatrix_length, const float* const hessian, const size_t hessian_length, void* output, const size_t output_length)
2320{
const int codec = format & CCV_NNC_QX_8I_ROWWISE_FORMAT_MASK;
const size_t row_count = input_length / row_length;
const size_t group_size = ccv_nnc_8i_rowwise_x_group_size(format);
const int group_bits = ccv_nnc_8i_rowwise_x_group_bits(format);
const size_t groups_per_row = (row_length + group_size - 1) / group_size;
const size_t padded_row_length = groups_per_row * group_size;
const size_t scale_offset = _ccv_nnc_8i_rowwise_packed_scale_offset(format, input_length, row_length);
const size_t output_size = scale_offset + row_count * CCV_GET_DATA_TYPE_SIZE(datatype)_ccv_get_data_type_size[((datatype) & 0xFF000) >> 12
];
if (output_length < output_size)
16
←
Assuming 'output_length' is >= 'output_size'→
17
←
Taking false branch→
return 0;
int16_t* iq1_map = 0;
const int starts = (codec == CCV_NNC_QX_8I_ROWWISE_IQ1_S || codec == CCV_NNC_QX_8I_ROWWISE_IQ1_M) ? 3 : 1;
18
←
Assuming 'codec' is not equal to CCV_NNC_QX_8I_ROWWISE_IQ1_S→
19
←
Assuming 'codec' is not equal to CCV_NNC_QX_8I_ROWWISE_IQ1_M→
20
←
'?' condition is false→
if (starts20.1
'starts' is not equal to 3
 == 3)
21
←
Taking false branch→
{
iq1_map = (int16_t*)ccmallocmalloc(sizeof(int16_t) * 6561);
int i, j;
for (i = 0; i < 6561; i++)
	iq1_map[i] = -1;
for (i = 0; i < 2048; i++)
{
	int code = 0;
	for (j = 0; j < 8; j++)
		code += ((ccv_nnc_8i_rowwise_packed_iq1_grid[i] >> (2 * j)) & 3) * ccv_nnc_8i_rowwise_packed_iq1_powers[j];
	iq1_map[code] = (int16_t)i;
}
}
switch (codec)
22
←
'Default' branch taken. Execution continues on line 2365→
{
case CCV_NNC_QX_8I_ROWWISE_IQ2_XXS:
	_ccv_nnc_8i_rowwise_packed_iq2xxs_candidates_init();
	break;
case CCV_NNC_QX_8I_ROWWISE_IQ2_XS:
	_ccv_nnc_8i_rowwise_packed_iq2xs_candidates_init();
	break;
case CCV_NNC_QX_8I_ROWWISE_IQ2_S:
	_ccv_nnc_8i_rowwise_packed_iq2s_init();
	break;
case CCV_NNC_QX_8I_ROWWISE_IQ3_S:
	_ccv_nnc_8i_rowwise_packed_iq3s_init();
	break;
case CCV_NNC_QX_8I_ROWWISE_IQ3_XXS:
	_ccv_nnc_8i_rowwise_packed_iq3xxs_candidates_init();
	break;
}
uint8_t* const u8 = (uint8_t*)output;
uint8_t* const scales = u8 + scale_offset;
memset(u8, 0, scale_offset);
const size_t row_bits = groups_per_row * group_bits;
size_t rows_per_chunk;
switch (row_bits & 7)
23
←
Control jumps to the 'default' case at line 2382→
{
case 0:
	rows_per_chunk = 1;
	break;
case 4:
	rows_per_chunk = 2;
	break;
case 2:
case 6:
	rows_per_chunk = 4;
	break;
default:
	rows_per_chunk = 8;
	break;
24
←
 Execution continues on line 2386→
}
rows_per_chunk = ccv_max(rows_per_chunk, (size_t)8)({ typeof (rows_per_chunk) _a = (rows_per_chunk); typeof ((size_t
)8) _b = ((size_t)8); (_a > _b) ? _a : _b; });
25
←
'?' condition is false→
// Feedback chunks are a multiple of the packing chunk, so they stay byte aligned.
if (hessian25.1
'hessian' is null
)
26
←
Taking false branch→
rows_per_chunk = CCV_NNC_8I_ROWWISE_X_FEEDBACK_ROWS;
const ccv_nnc_8i_rowwise_x_rows_t rows_data = {
.input = input,
.datatype = datatype,
.format = format,
.codec = codec,
.starts = starts,
.row_length = row_length,
.row_count = row_count,
.imatrix = imatrix,
.imatrix_length = imatrix_length,
.group_size = group_size,
.groups_per_row = groups_per_row,
.padded_row_length = padded_row_length,
.iq1_map = iq1_map,
.u8 = u8,
.scales = scales,
};
const ccv_nnc_8i_rowwise_x_rows_t* const ctx = &rows_data;
// Each Hessian slice is factored once and shared by its rows. Slices run one after another, so a
// chunk that straddles two slices never writes its packed bytes concurrently.
const size_t slices = hessian26.1
'hessian' is null
 ? hessian_length / (row_length * row_length) : 1;
27
←
'?' condition is false→
const size_t rows_per_slice = row_count / slices;
ccv_nnc_8i_rowwise_x_feedback_t feedback = {0};
if (hessian27.1
'hessian' is null
)
28
←
Taking false branch→
{
feedback.u = (double*)ccmallocmalloc(sizeof(double) * padded_row_length * padded_row_length);
feedback.rbb = (double*)ccmallocmalloc(sizeof(double) * padded_row_length * group_size);
feedback.weights = (double*)ccmallocmalloc(sizeof(double) * padded_row_length);
2418#if (defined HAVE_CBLAS1 || defined HAVE_ACCELERATE_FRAMEWORK)
feedback.hessian64 = (double*)ccmallocmalloc(sizeof(double) * row_length * row_length);
2420#endif
}
size_t slice;
for (slice = 0; slice < slices; slice++)
29
←
Loop condition is true.  Entering loop body→
{
const size_t row_begin = slice * rows_per_slice;
const size_t row_end = row_begin + rows_per_slice;
if (hessian29.1
'hessian' is null
)
	_ccv_nnc_8i_rowwise_x_feedback_init(&feedback, hessian + slice * row_length * row_length, row_length, padded_row_length, group_size);
const ccv_nnc_8i_rowwise_x_feedback_t* const fb = hessian30.1
'hessian' is null
 ? &feedback : 0;
30
←
Taking false branch→
31
←
'?' condition is false→
const size_t first_chunk = row_begin / rows_per_chunk;
const size_t row_chunks = (row_end + rows_per_chunk - 1) / rows_per_chunk - first_chunk;
2432#ifdef USE_DISPATCH
dispatch_apply(row_chunks, dispatch_get_global_queue(DISPATCH_QUEUE_PRIORITY_DEFAULT, 0), ^(size_t chunk_idx) {
2434#else
parallel_for(chunk_idx, (int)row_chunks){ int chunk_idx; for ((chunk_idx) = 0; (chunk_idx) < ((int
)row_chunks); (chunk_idx)++) { {
32
←
Assuming 'chunk_idx' is < 'row_chunks'→
33
←
Loop condition is true.  Entering loop body→
2436#endif
	const size_t chunk_begin = ccv_max((first_chunk + (size_t)chunk_idx) * rows_per_chunk, row_begin)({ typeof ((first_chunk + (size_t)chunk_idx) * rows_per_chunk
) _a = ((first_chunk + (size_t)chunk_idx) * rows_per_chunk); typeof
 (row_begin) _b = (row_begin); (_a > _b) ? _a : _b; });
34
←
'?' condition is false→
	const size_t chunk_end = ccv_min((first_chunk + (size_t)chunk_idx + 1) * rows_per_chunk, row_end)({ typeof ((first_chunk + (size_t)chunk_idx + 1) * rows_per_chunk
) _a = ((first_chunk + (size_t)chunk_idx + 1) * rows_per_chunk
); typeof (row_end) _b = (row_end); (_a < _b) ? _a : _b; }
);
35
←
Assuming '_a' is >= '_b'→
36
←
'?' condition is false→
	if (fb36.1
'fb' is null
)
37
←
Taking false branch→
		_ccv_nnc_8i_rowwise_x_quantize_rows_feedback(ctx, fb, chunk_begin, chunk_end);
	else
		_ccv_nnc_8i_rowwise_x_quantize_rows(ctx, chunk_begin, chunk_end);
38
←
Calling '_ccv_nnc_8i_rowwise_x_quantize_rows'→
2443#ifdef USE_DISPATCH
});
2445#else
} parallel_endfor} }
2447#endif
}
if (hessian)
{
ccfreefree(feedback.weights);
ccfreefree(feedback.rbb);
ccfreefree(feedback.u);
if (feedback.hessian64)
	ccfreefree(feedback.hessian64);
}
ccfreefree(iq1_map);
return output_size;
2459}

2461CCV_WARN_UNUSED(size_t)size_t __attribute__((warn_unused_result)) ccv_nnc_quantize_8i_rowwise_x(const void* input, const int datatype, const int memory_type, const size_t input_length, const size_t row_length, const int format, const float* const imatrix, const size_t imatrix_length, const float* const hessian, const size_t hessian_length, void* output, const size_t output_length)
2462{
if (row_length == 0 || input_length % row_length != 0 || (imatrix && hessian) ||
1
Assuming 'row_length' is not equal to 0→
2
←
Assuming the condition is false→
3
←
Assuming 'imatrix' is null→
((format & CCV_NNC_QX_8I_ROWWISE_HADAMARD_256) && (row_length % 256 != 0 || hessian)))
4
←
Assuming the condition is false→
return 0;
assert(datatype == CCV_16F || datatype == CCV_16BF || datatype == CCV_32F || datatype == CCV_64F)((void) sizeof ((datatype == CCV_16F || datatype == CCV_16BF ||
 datatype == CCV_32F || datatype == CCV_64F) ? 1 : 0), __extension__
 ({ if (datatype == CCV_16F || datatype == CCV_16BF || datatype
 == CCV_32F || datatype == CCV_64F) ; else __assert_fail ("datatype == CCV_16F || datatype == CCV_16BF || datatype == CCV_32F || datatype == CCV_64F"
, "ccv_nnc_8i_rowwise.c", 2466, __extension__ __PRETTY_FUNCTION__
); }));
5
←
Assuming 'datatype' is not equal to CCV_16F→
6
←
Assuming 'datatype' is not equal to CCV_16BF→
7
←
Assuming 'datatype' is not equal to CCV_32F→
8
←
Assuming 'datatype' is equal to CCV_64F→
9
←
Taking true branch→
assert(memory_type == CCV_TENSOR_CPU_MEMORY)((void) sizeof ((memory_type == CCV_TENSOR_CPU_MEMORY) ? 1 : 0
), __extension__ ({ if (memory_type == CCV_TENSOR_CPU_MEMORY)
 ; else __assert_fail ("memory_type == CCV_TENSOR_CPU_MEMORY"
, "ccv_nnc_8i_rowwise.c", 2467, __extension__ __PRETTY_FUNCTION__
); }));
10
←
Assuming 'memory_type' is equal to CCV_TENSOR_CPU_MEMORY→
11
←
Taking true branch→
const size_t row_count = input_length / row_length;
if (!_ccv_nnc_8i_rowwise_imatrix_is_valid(imatrix, imatrix_length, row_length, row_count))
12
←
Taking false branch→
return 0;
if (hessian)
13
←
Assuming 'hessian' is null→
14
←
Taking false branch→
{
const size_t matrix_length = row_length * row_length;
if (hessian_length < matrix_length || hessian_length % matrix_length != 0 || row_count % (hessian_length / matrix_length) != 0)
	return 0;
}
return _ccv_nnc_quantize_8i_rowwise_x(input, datatype, input_length, row_length, format, imatrix, imatrix_length, hessian, hessian_length, output, output_length);
15
←
Calling '_ccv_nnc_quantize_8i_rowwise_x'→
2478}

2480void ccv_nnc_dequantize_8i_rowwise_x(const void* input, const int datatype, const int memory_type, const size_t input_length, const size_t row_length, const int format, void* output, const size_t output_length)
2481{
assert(datatype == CCV_16F || datatype == CCV_16BF || datatype == CCV_32F || datatype == CCV_64F)((void) sizeof ((datatype == CCV_16F || datatype == CCV_16BF ||
 datatype == CCV_32F || datatype == CCV_64F) ? 1 : 0), __extension__
 ({ if (datatype == CCV_16F || datatype == CCV_16BF || datatype
 == CCV_32F || datatype == CCV_64F) ; else __assert_fail ("datatype == CCV_16F || datatype == CCV_16BF || datatype == CCV_32F || datatype == CCV_64F"
, "ccv_nnc_8i_rowwise.c", 2482, __extension__ __PRETTY_FUNCTION__
); }));
assert(memory_type == CCV_TENSOR_CPU_MEMORY || memory_type == CCV_TENSOR_GPU_MEMORY)((void) sizeof ((memory_type == CCV_TENSOR_CPU_MEMORY || memory_type
 == CCV_TENSOR_GPU_MEMORY) ? 1 : 0), __extension__ ({ if (memory_type
 == CCV_TENSOR_CPU_MEMORY || memory_type == CCV_TENSOR_GPU_MEMORY
) ; else __assert_fail ("memory_type == CCV_TENSOR_CPU_MEMORY || memory_type == CCV_TENSOR_GPU_MEMORY"
, "ccv_nnc_8i_rowwise.c", 2483, __extension__ __PRETTY_FUNCTION__
); }));
assert(row_length > 0)((void) sizeof ((row_length > 0) ? 1 : 0), __extension__ (
{ if (row_length > 0) ; else __assert_fail ("row_length > 0"
, "ccv_nnc_8i_rowwise.c", 2484, __extension__ __PRETTY_FUNCTION__
); }));
assert(output_length % row_length == 0)((void) sizeof ((output_length % row_length == 0) ? 1 : 0), __extension__
 ({ if (output_length % row_length == 0) ; else __assert_fail
 ("output_length % row_length == 0", "ccv_nnc_8i_rowwise.c", 2485
, __extension__ __PRETTY_FUNCTION__); }));
assert(!(format & CCV_NNC_QX_8I_ROWWISE_HADAMARD_256) || row_length % 256 == 0)((void) sizeof ((!(format & CCV_NNC_QX_8I_ROWWISE_HADAMARD_256
) || row_length % 256 == 0) ? 1 : 0), __extension__ ({ if (!(
format & CCV_NNC_QX_8I_ROWWISE_HADAMARD_256) || row_length
 % 256 == 0) ; else __assert_fail ("!(format & CCV_NNC_QX_8I_ROWWISE_HADAMARD_256) || row_length % 256 == 0"
, "ccv_nnc_8i_rowwise.c", 2486, __extension__ __PRETTY_FUNCTION__
); }));
if (memory_type != CCV_TENSOR_CPU_MEMORY)
{
2489#ifdef HAVE_CUDA1
ccv_nnc_compat_dequantize_8i_rowwise_x_fp(input, datatype, input_length, row_length, format, output, output_length, 0);
2491#elif defined(HAVE_MPS)
assert(datatype != CCV_64F)((void) sizeof ((datatype != CCV_64F) ? 1 : 0), __extension__
 ({ if (datatype != CCV_64F) ; else __assert_fail ("datatype != CCV_64F"
, "ccv_nnc_8i_rowwise.c", 2492, __extension__ __PRETTY_FUNCTION__
); }));
ccv_nnc_mps_dequantize_8i_rowwise_x(input, datatype, input_length, row_length, format, output, output_length, 0);
2494#else
assert(memory_type == CCV_TENSOR_CPU_MEMORY)((void) sizeof ((memory_type == CCV_TENSOR_CPU_MEMORY) ? 1 : 0
), __extension__ ({ if (memory_type == CCV_TENSOR_CPU_MEMORY)
 ; else __assert_fail ("memory_type == CCV_TENSOR_CPU_MEMORY"
, "ccv_nnc_8i_rowwise.c", 2495, __extension__ __PRETTY_FUNCTION__
); }));
2496#endif
return;
}
const size_t row_count = output_length / row_length;
const size_t group_size = ccv_nnc_8i_rowwise_x_group_size(format);
const size_t groups_per_row = (row_length + group_size - 1) / group_size;
const size_t scale_offset = _ccv_nnc_8i_rowwise_packed_scale_offset(format, output_length, row_length);
assert(input_length >= scale_offset + row_count * CCV_GET_DATA_TYPE_SIZE(datatype))((void) sizeof ((input_length >= scale_offset + row_count *
 _ccv_get_data_type_size[((datatype) & 0xFF000) >> 12
]) ? 1 : 0), __extension__ ({ if (input_length >= scale_offset
 + row_count * _ccv_get_data_type_size[((datatype) & 0xFF000
) >> 12]) ; else __assert_fail ("input_length >= scale_offset + row_count * CCV_GET_DATA_TYPE_SIZE(datatype)"
, "ccv_nnc_8i_rowwise.c", 2503, __extension__ __PRETTY_FUNCTION__
); }));
const uint8_t* const u8 = (const uint8_t*)input;
const uint8_t* const scales = u8 + scale_offset;
parallel_for(i, (int)row_count){ int i; for ((i) = 0; (i) < ((int)row_count); (i)++) { {
const double scale = _ccv_nnc_8i_rowwise_packed_load_scale(scales, datatype, i);
if (format & CCV_NNC_QX_8I_ROWWISE_HADAMARD_256)
{
	// Transform decoded integers before scaling / rounding to the destination
	// precision. H256 is its own inverse and acts on independent blocks.
	double block[256];
	size_t base;
	for (base = 0; base < row_length; base += 256)
	{
		size_t g;
		for (g = 0; g < 256 / group_size; g++)
		{
			int q8[32] = {0};
			_ccv_nnc_8i_rowwise_packed_decode_group(u8, (size_t)i * groups_per_row + base / group_size + g, format & CCV_NNC_QX_8I_ROWWISE_FORMAT_MASK, q8);
			size_t j;
			for (j = 0; j < group_size; j++)
				block[g * group_size + j] = q8[j];
		}
		_ccv_nnc_8i_rowwise_hadamard_256(block, 256);
		size_t j;
		for (j = 0; j < 256; j++)
			_ccv_nnc_8i_rowwise_packed_write_value(output, datatype, (size_t)i * row_length + base + j, scale * block[j]);
	}
} else {
	size_t g;
	for (g = 0; g < groups_per_row; g++)
	{
		int q8[32] = {0};
		_ccv_nnc_8i_rowwise_packed_decode_group(u8, (size_t)i * groups_per_row + g, format, q8);
		size_t j;
		for (j = 0; j < group_size; j++)
		{
			const size_t col = g * group_size + j;
			if (col < row_length)
				_ccv_nnc_8i_rowwise_packed_write_value(output, datatype, (size_t)i * row_length + col, scale * q8[j]);
		}
	}
}
} parallel_endfor} }
2546}

2548static inline int _ccv_nnc_8i_rowwise_quantize(const double v, const double inv_scale)
2549{
const int q = (int)lrint(v * inv_scale);
return ccv_clamp(q, -127, 127)({ typeof (-127) _a = (-127); typeof (127) _b = (127); typeof
 (q) _x = (q); (_x < _a) ? _a : ((_x > _b) ? _b : _x); }
);
2552}

2554static float _ccv_nnc_quantize_8i_rowwise_16f(const uint16_t* const row, const size_t row_length, const float* const imatrix, int8_t* const q)
2555{
size_t j;
double max_abs = 0;
for (j = 0; j < row_length; j++)
{
float v;
ccv_half_precision_to_float(row + j, &v, 1);
max_abs = ccv_max(max_abs, fabs(v))({ typeof (max_abs) _a = (max_abs); typeof (fabs(v)) _b = (fabs
(v)); (_a > _b) ? _a : _b; });
}
if (max_abs == 0)
{
memset(q, 0, row_length);
return 0;
}
double scale = max_abs / 127.;
float best_scale = 0;
double best_sse = DBL_MAX1.7976931348623157e+308;
int k;
for (k = 0; k < 8; k++)
{
// Round with the scale that will actually be stored, then refit scale by least squares.
const float scale_f = (float)scale;
uint16_t scale_h;
float stored_scale;
ccv_float_to_half_precision(&scale_f, &scale_h, 1);
ccv_half_precision_to_float(&scale_h, &stored_scale, 1);
if (!(stored_scale > 0))
	break;
const double inv_scale = 1. / stored_scale;
double sum_qx = 0;
double sum_qq = 0;
double sse = 0;
for (j = 0; j < row_length; j++)
{
	const double w = _ccv_nnc_8i_rowwise_weight(imatrix, j);
	float v_f;
	ccv_half_precision_to_float(row + j, &v_f, 1);
	const double v = v_f;
	const int qj = _ccv_nnc_8i_rowwise_quantize(v, inv_scale);
	const double d = v - stored_scale * qj;
	sse += w * d * d;
	sum_qx += w * qj * v;
	sum_qq += w * qj * qj;
}
if (sse < best_sse)
{
	best_sse = sse;
	best_scale = stored_scale;
}
if (!(sum_qq > 0) || !(sum_qx > 0))
	break;
const double next_scale = sum_qx / sum_qq;
const float next_scale_f = (float)next_scale;
uint16_t next_scale_h;
float next_stored_scale;
ccv_float_to_half_precision(&next_scale_f, &next_scale_h, 1);
ccv_half_precision_to_float(&next_scale_h, &next_stored_scale, 1);
if (next_stored_scale == stored_scale)
	break;
scale = next_scale;
}
if (!(best_scale > 0))
{
memset(q, 0, row_length);
return 0;
}
const double inv_scale = 1. / best_scale;
for (j = 0; j < row_length; j++)
{
float v;
ccv_half_precision_to_float(row + j, &v, 1);
q[j] = (int8_t)_ccv_nnc_8i_rowwise_quantize(v, inv_scale);
}
return best_scale;
2629}

2631static float _ccv_nnc_quantize_8i_rowwise_16bf(const uint16_t* const row, const size_t row_length, const float* const imatrix, int8_t* const q)
2632{
size_t j;
double max_abs = 0;
for (j = 0; j < row_length; j++)
{
float v;
ccv_bfloat_to_float(row + j, &v, 1);
max_abs = ccv_max(max_abs, fabs(v))({ typeof (max_abs) _a = (max_abs); typeof (fabs(v)) _b = (fabs
(v)); (_a > _b) ? _a : _b; });
}
if (max_abs == 0)
{
memset(q, 0, row_length);
return 0;
}
double scale = max_abs / 127.;
float best_scale = 0;
double best_sse = DBL_MAX1.7976931348623157e+308;
int k;
for (k = 0; k < 8; k++)
{
const float scale_f = (float)scale;
uint16_t scale_bf;
float stored_scale;
ccv_float_to_bfloat(&scale_f, &scale_bf, 1);
ccv_bfloat_to_float(&scale_bf, &stored_scale, 1);
if (!(stored_scale > 0))
	break;
const double inv_scale = 1. / stored_scale;
double sum_qx = 0;
double sum_qq = 0;
double sse = 0;
for (j = 0; j < row_length; j++)
{
	const double w = _ccv_nnc_8i_rowwise_weight(imatrix, j);
	float v_f;
	ccv_bfloat_to_float(row + j, &v_f, 1);
	const double v = v_f;
	const int qj = _ccv_nnc_8i_rowwise_quantize(v, inv_scale);
	const double d = v - stored_scale * qj;
	sse += w * d * d;
	sum_qx += w * qj * v;
	sum_qq += w * qj * qj;
}
if (sse < best_sse)
{
	best_sse = sse;
	best_scale = stored_scale;
}
if (!(sum_qq > 0) || !(sum_qx > 0))
	break;
const double next_scale = sum_qx / sum_qq;
const float next_scale_f = (float)next_scale;
uint16_t next_scale_bf;
float next_stored_scale;
ccv_float_to_bfloat(&next_scale_f, &next_scale_bf, 1);
ccv_bfloat_to_float(&next_scale_bf, &next_stored_scale, 1);
if (next_stored_scale == stored_scale)
	break;
scale = next_scale;
}
if (!(best_scale > 0))
{
memset(q, 0, row_length);
return 0;
}
const double inv_scale = 1. / best_scale;
for (j = 0; j < row_length; j++)
{
float v;
ccv_bfloat_to_float(row + j, &v, 1);
q[j] = (int8_t)_ccv_nnc_8i_rowwise_quantize(v, inv_scale);
}
return best_scale;
2705}

2707static float _ccv_nnc_quantize_8i_rowwise_32f(const float* const row, const size_t row_length, const float* const imatrix, int8_t* const q)
2708{
size_t j;
double max_abs = 0;
for (j = 0; j < row_length; j++)
max_abs = ccv_max(max_abs, fabs(row[j]))({ typeof (max_abs) _a = (max_abs); typeof (fabs(row[j])) _b =
 (fabs(row[j])); (_a > _b) ? _a : _b; });
if (max_abs == 0)
{
memset(q, 0, row_length);
return 0;
}
double scale = max_abs / 127.;
float best_scale = 0;
double best_sse = DBL_MAX1.7976931348623157e+308;
int k;
for (k = 0; k < 8; k++)
{
const float stored_scale = (float)scale;
if (!(stored_scale > 0))
	break;
const double inv_scale = 1. / stored_scale;
double sum_qx = 0;
double sum_qq = 0;
double sse = 0;
for (j = 0; j < row_length; j++)
{
	const double w = _ccv_nnc_8i_rowwise_weight(imatrix, j);
	const double v = row[j];
	const int qj = _ccv_nnc_8i_rowwise_quantize(v, inv_scale);
	const double d = v - stored_scale * qj;
	sse += w * d * d;
	sum_qx += w * qj * v;
	sum_qq += w * qj * qj;
}
if (sse < best_sse)
{
	best_sse = sse;
	best_scale = stored_scale;
}
if (!(sum_qq > 0) || !(sum_qx > 0))
	break;
const double next_scale = sum_qx / sum_qq;
if ((float)next_scale == stored_scale)
	break;
scale = next_scale;
}
if (!(best_scale > 0))
{
memset(q, 0, row_length);
return 0;
}
const double inv_scale = 1. / best_scale;
for (j = 0; j < row_length; j++)
q[j] = (int8_t)_ccv_nnc_8i_rowwise_quantize(row[j], inv_scale);
return best_scale;
2762}

2764static double _ccv_nnc_quantize_8i_rowwise_64f(const double* const row, const size_t row_length, const float* const imatrix, int8_t* const q)
2765{
size_t j;
double max_abs = 0;
for (j = 0; j < row_length; j++)
max_abs = ccv_max(max_abs, fabs(row[j]))({ typeof (max_abs) _a = (max_abs); typeof (fabs(row[j])) _b =
 (fabs(row[j])); (_a > _b) ? _a : _b; });
if (max_abs == 0)
{
memset(q, 0, row_length);
return 0;
}
double scale = max_abs / 127.;
double best_scale = 0;
double best_sse = DBL_MAX1.7976931348623157e+308;
int k;
for (k = 0; k < 8; k++)
{
const double stored_scale = scale;
if (!(stored_scale > 0))
	break;
const double inv_scale = 1. / stored_scale;
double sum_qx = 0;
double sum_qq = 0;
double sse = 0;
for (j = 0; j < row_length; j++)
{
	const double w = _ccv_nnc_8i_rowwise_weight(imatrix, j);
	const double v = row[j];
	const int qj = _ccv_nnc_8i_rowwise_quantize(v, inv_scale);
	const double d = v - stored_scale * qj;
	sse += w * d * d;
	sum_qx += w * qj * v;
	sum_qq += w * qj * qj;
}
if (sse < best_sse)
{
	best_sse = sse;
	best_scale = stored_scale;
}
if (!(sum_qq > 0) || !(sum_qx > 0))
	break;
const double next_scale = sum_qx / sum_qq;
if (next_scale == stored_scale)
	break;
scale = next_scale;
}
if (!(best_scale > 0))
{
memset(q, 0, row_length);
return 0;
}
const double inv_scale = 1. / best_scale;
for (j = 0; j < row_length; j++)
q[j] = (int8_t)_ccv_nnc_8i_rowwise_quantize(row[j], inv_scale);
return best_scale;
2819}

2821CCV_WARN_UNUSED(size_t)size_t __attribute__((warn_unused_result)) ccv_nnc_quantize_8i_rowwise(const void* input, const int datatype, const int memory_type, const size_t input_length, const size_t row_length, const float* const imatrix, const size_t imatrix_length, void* output, const size_t output_length)
2822{
assert(datatype == CCV_16F || datatype == CCV_16BF || datatype == CCV_32F || datatype == CCV_64F)((void) sizeof ((datatype == CCV_16F || datatype == CCV_16BF ||
 datatype == CCV_32F || datatype == CCV_64F) ? 1 : 0), __extension__
 ({ if (datatype == CCV_16F || datatype == CCV_16BF || datatype
 == CCV_32F || datatype == CCV_64F) ; else __assert_fail ("datatype == CCV_16F || datatype == CCV_16BF || datatype == CCV_32F || datatype == CCV_64F"
, "ccv_nnc_8i_rowwise.c", 2823, __extension__ __PRETTY_FUNCTION__
); }));
assert(memory_type == CCV_TENSOR_CPU_MEMORY)((void) sizeof ((memory_type == CCV_TENSOR_CPU_MEMORY) ? 1 : 0
), __extension__ ({ if (memory_type == CCV_TENSOR_CPU_MEMORY)
 ; else __assert_fail ("memory_type == CCV_TENSOR_CPU_MEMORY"
, "ccv_nnc_8i_rowwise.c", 2824, __extension__ __PRETTY_FUNCTION__
); }));
assert(row_length > 0)((void) sizeof ((row_length > 0) ? 1 : 0), __extension__ (
{ if (row_length > 0) ; else __assert_fail ("row_length > 0"
, "ccv_nnc_8i_rowwise.c", 2825, __extension__ __PRETTY_FUNCTION__
); }));
assert(input_length % row_length == 0)((void) sizeof ((input_length % row_length == 0) ? 1 : 0), __extension__
 ({ if (input_length % row_length == 0) ; else __assert_fail (
"input_length % row_length == 0", "ccv_nnc_8i_rowwise.c", 2826
, __extension__ __PRETTY_FUNCTION__); }));
const size_t row_count = input_length / row_length;
if (!_ccv_nnc_8i_rowwise_imatrix_is_valid(imatrix, imatrix_length, row_length, row_count))
return 0;
const size_t scale_offset = (input_length + 127) & -128;
const size_t scale_size = row_count * CCV_GET_DATA_TYPE_SIZE(datatype)_ccv_get_data_type_size[((datatype) & 0xFF000) >> 12
];
assert(output_length >= scale_offset + scale_size)((void) sizeof ((output_length >= scale_offset + scale_size
) ? 1 : 0), __extension__ ({ if (output_length >= scale_offset
 + scale_size) ; else __assert_fail ("output_length >= scale_offset + scale_size"
, "ccv_nnc_8i_rowwise.c", 2832, __extension__ __PRETTY_FUNCTION__
); }));
int8_t* const q = (int8_t*)output;
uint8_t* const u8 = (uint8_t*)output;
if (datatype == CCV_16F)
{
const uint16_t* const f16 = (const uint16_t*)input;
uint16_t* const scales = (uint16_t*)(u8 + scale_offset);
parallel_for(i, (int)row_count){ int i; for ((i) = 0; (i) < ((int)row_count); (i)++) { {
	const size_t row_start = (size_t)i * row_length;
	const float* const row_imatrix = _ccv_nnc_8i_rowwise_imatrix_for_row(imatrix, imatrix_length, row_length, row_count, (size_t)i);
	const float scale_f = _ccv_nnc_quantize_8i_rowwise_16f(f16 + row_start, row_length, row_imatrix, q + row_start);
	ccv_float_to_half_precision(&scale_f, scales + i, 1);
} parallel_endfor} }
} else if (datatype == CCV_16BF) {
const uint16_t* const bf16 = (const uint16_t*)input;
uint16_t* const scales = (uint16_t*)(u8 + scale_offset);
parallel_for(i, (int)row_count){ int i; for ((i) = 0; (i) < ((int)row_count); (i)++) { {
	const size_t row_start = (size_t)i * row_length;
	const float* const row_imatrix = _ccv_nnc_8i_rowwise_imatrix_for_row(imatrix, imatrix_length, row_length, row_count, (size_t)i);
	const float scale_f = _ccv_nnc_quantize_8i_rowwise_16bf(bf16 + row_start, row_length, row_imatrix, q + row_start);
	ccv_float_to_bfloat(&scale_f, scales + i, 1);
} parallel_endfor} }
} else if (datatype == CCV_32F) {
const float* const f32 = (const float*)input;
float* const scales = (float*)(u8 + scale_offset);
parallel_for(i, (int)row_count){ int i; for ((i) = 0; (i) < ((int)row_count); (i)++) { {
	const size_t row_start = (size_t)i * row_length;
	const float* const row_imatrix = _ccv_nnc_8i_rowwise_imatrix_for_row(imatrix, imatrix_length, row_length, row_count, (size_t)i);
	scales[i] = _ccv_nnc_quantize_8i_rowwise_32f(f32 + row_start, row_length, row_imatrix, q + row_start);
} parallel_endfor} }
} else {
assert(datatype == CCV_64F)((void) sizeof ((datatype == CCV_64F) ? 1 : 0), __extension__
 ({ if (datatype == CCV_64F) ; else __assert_fail ("datatype == CCV_64F"
, "ccv_nnc_8i_rowwise.c", 2863, __extension__ __PRETTY_FUNCTION__
); }));
const double* const f64 = (const double*)input;
double* const scales = (double*)(u8 + scale_offset);
parallel_for(i, (int)row_count){ int i; for ((i) = 0; (i) < ((int)row_count); (i)++) { {
	const size_t row_start = (size_t)i * row_length;
	const float* const row_imatrix = _ccv_nnc_8i_rowwise_imatrix_for_row(imatrix, imatrix_length, row_length, row_count, (size_t)i);
	scales[i] = _ccv_nnc_quantize_8i_rowwise_64f(f64 + row_start, row_length, row_imatrix, q + row_start);
} parallel_endfor} }
}
return scale_offset + scale_size;
2873}

2875void ccv_nnc_dequantize_8i_rowwise(const void* input, const int datatype, const int memory_type, const size_t input_length, const size_t row_length, void* output, const size_t output_length)
2876{
assert(datatype == CCV_16F || datatype == CCV_16BF || datatype == CCV_32F || datatype == CCV_64F)((void) sizeof ((datatype == CCV_16F || datatype == CCV_16BF ||
 datatype == CCV_32F || datatype == CCV_64F) ? 1 : 0), __extension__
 ({ if (datatype == CCV_16F || datatype == CCV_16BF || datatype
 == CCV_32F || datatype == CCV_64F) ; else __assert_fail ("datatype == CCV_16F || datatype == CCV_16BF || datatype == CCV_32F || datatype == CCV_64F"
, "ccv_nnc_8i_rowwise.c", 2877, __extension__ __PRETTY_FUNCTION__
); }));
assert(memory_type == CCV_TENSOR_CPU_MEMORY || memory_type == CCV_TENSOR_GPU_MEMORY)((void) sizeof ((memory_type == CCV_TENSOR_CPU_MEMORY || memory_type
 == CCV_TENSOR_GPU_MEMORY) ? 1 : 0), __extension__ ({ if (memory_type
 == CCV_TENSOR_CPU_MEMORY || memory_type == CCV_TENSOR_GPU_MEMORY
) ; else __assert_fail ("memory_type == CCV_TENSOR_CPU_MEMORY || memory_type == CCV_TENSOR_GPU_MEMORY"
, "ccv_nnc_8i_rowwise.c", 2878, __extension__ __PRETTY_FUNCTION__
); }));
assert(row_length > 0)((void) sizeof ((row_length > 0) ? 1 : 0), __extension__ (
{ if (row_length > 0) ; else __assert_fail ("row_length > 0"
, "ccv_nnc_8i_rowwise.c", 2879, __extension__ __PRETTY_FUNCTION__
); }));
assert(output_length % row_length == 0)((void) sizeof ((output_length % row_length == 0) ? 1 : 0), __extension__
 ({ if (output_length % row_length == 0) ; else __assert_fail
 ("output_length % row_length == 0", "ccv_nnc_8i_rowwise.c", 2880
, __extension__ __PRETTY_FUNCTION__); }));
if (memory_type != CCV_TENSOR_CPU_MEMORY)
{
2883#ifdef HAVE_CUDA1
ccv_nnc_compat_dequantize_8i_rowwise(input, datatype, input_length, row_length, output, output_length, 0);
2885#elif defined(HAVE_MPS)
assert(datatype != CCV_64F)((void) sizeof ((datatype != CCV_64F) ? 1 : 0), __extension__
 ({ if (datatype != CCV_64F) ; else __assert_fail ("datatype != CCV_64F"
, "ccv_nnc_8i_rowwise.c", 2886, __extension__ __PRETTY_FUNCTION__
); }));
ccv_nnc_mps_dequantize_8i_rowwise(input, datatype, input_length, row_length, output, output_length, 0);
2888#else
assert(memory_type == CCV_TENSOR_CPU_MEMORY)((void) sizeof ((memory_type == CCV_TENSOR_CPU_MEMORY) ? 1 : 0
), __extension__ ({ if (memory_type == CCV_TENSOR_CPU_MEMORY)
 ; else __assert_fail ("memory_type == CCV_TENSOR_CPU_MEMORY"
, "ccv_nnc_8i_rowwise.c", 2889, __extension__ __PRETTY_FUNCTION__
); }));
2890#endif
return;
}
const size_t row_count = output_length / row_length;
const size_t scale_offset = (output_length + 127) & -128;
assert(input_length >= scale_offset + row_count * CCV_GET_DATA_TYPE_SIZE(datatype))((void) sizeof ((input_length >= scale_offset + row_count *
 _ccv_get_data_type_size[((datatype) & 0xFF000) >> 12
]) ? 1 : 0), __extension__ ({ if (input_length >= scale_offset
 + row_count * _ccv_get_data_type_size[((datatype) & 0xFF000
) >> 12]) ; else __assert_fail ("input_length >= scale_offset + row_count * CCV_GET_DATA_TYPE_SIZE(datatype)"
, "ccv_nnc_8i_rowwise.c", 2895, __extension__ __PRETTY_FUNCTION__
); }));
const int8_t* const q = (const int8_t*)input;
const uint8_t* const u8 = (const uint8_t*)input;
if (datatype == CCV_16F)
{
uint16_t* const f16 = (uint16_t*)output;
const uint16_t* const scales = (const uint16_t*)(u8 + scale_offset);
parallel_for(i, (int)row_count){ int i; for ((i) = 0; (i) < ((int)row_count); (i)++) { {
	const size_t row_start = (size_t)i * row_length;
	float scale_f;
	ccv_half_precision_to_float(scales + i, &scale_f, 1);
	size_t j;
	for (j = 0; j < row_length; j++)
	{
		const float v = q[row_start + j] * scale_f;
		ccv_float_to_half_precision(&v, f16 + row_start + j, 1);
	}
} parallel_endfor} }
} else if (datatype == CCV_16BF) {
uint16_t* const bf16 = (uint16_t*)output;
const uint16_t* const scales = (const uint16_t*)(u8 + scale_offset);
parallel_for(i, (int)row_count){ int i; for ((i) = 0; (i) < ((int)row_count); (i)++) { {
	const size_t row_start = (size_t)i * row_length;
	float scale_f;
	ccv_bfloat_to_float(scales + i, &scale_f, 1);
	size_t j;
	for (j = 0; j < row_length; j++)
	{
		const float v = q[row_start + j] * scale_f;
		ccv_float_to_bfloat(&v, bf16 + row_start + j, 1);
	}
} parallel_endfor} }
} else if (datatype == CCV_32F) {
float* const f32 = (float*)output;
const float* const scales = (const float*)(u8 + scale_offset);
parallel_for(i, (int)row_count){ int i; for ((i) = 0; (i) < ((int)row_count); (i)++) { {
	const size_t row_start = (size_t)i * row_length;
	const float scale = scales[i];
	size_t j;
	for (j = 0; j < row_length; j++)
		f32[row_start + j] = q[row_start + j] * scale;
} parallel_endfor} }
} else {
assert(datatype == CCV_64F)((void) sizeof ((datatype == CCV_64F) ? 1 : 0), __extension__
 ({ if (datatype == CCV_64F) ; else __assert_fail ("datatype == CCV_64F"
, "ccv_nnc_8i_rowwise.c", 2938, __extension__ __PRETTY_FUNCTION__
); }));
double* const f64 = (double*)output;
const double* const scales = (const double*)(u8 + scale_offset);
parallel_for(i, (int)row_count){ int i; for ((i) = 0; (i) < ((int)row_count); (i)++) { {
	const size_t row_start = (size_t)i * row_length;
	const double scale = scales[i];
	size_t j;
	for (j = 0; j < row_length; j++)
		f64[row_start + j] = q[row_start + j] * scale;
} parallel_endfor} }
}
2949}