Bug Summary

File:nnc/ccv_nnc_8i_rowwise.c
Warning:line 1664, column 12
Assigned value is garbage or undefined

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/2026-09-23-070922-177476-1 -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#include "ccv_nnc_8i_rowwise_packed_grids.inc"
7#ifdef USE_DISPATCH
8#include <dispatch/dispatch.h>
9#endif
10#ifdef HAVE_CUDA1
11#include "gpu/ccv_nnc_compat.h"
12#elif defined(HAVE_MPS)
13#include "mps/ccv_nnc_mps.h"
14#endif
15
16enum {
17 CCV_NNC_8I_ROWWISE_X_REFINEMENT_STEPS = 8,
18 CCV_NNC_8I_ROWWISE_IQ2_CANDIDATES = 16,
19 CCV_NNC_8I_ROWWISE_IQ3_CANDIDATES = 24,
20};
21
22static size_t _ccv_nnc_8i_rowwise_packed_scale_offset(const int format, const size_t input_length, const size_t row_length)
23{
24 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", 24, __extension__ __PRETTY_FUNCTION__
); }))
;
25 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", 25,
__extension__ __PRETTY_FUNCTION__); }))
;
26 const size_t row_count = input_length / row_length;
27 const size_t group_size = ccv_nnc_8i_rowwise_x_group_size(format);
28 const size_t groups_per_row = (row_length + group_size - 1) / group_size;
29 const size_t group_bits = ccv_nnc_8i_rowwise_x_group_bits(format);
30 const size_t payload_size = (row_count * groups_per_row * group_bits + 7) / 8;
31 return (payload_size + 127) & -128;
32}
33
34CCV_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)
35{
36 if (row_length == 0 || input_length % row_length != 0 ||
37 ((format & CCV_NNC_QX_8I_ROWWISE_HADAMARD_256) && row_length % 256 != 0))
38 return 0;
39 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", 39, __extension__ __PRETTY_FUNCTION__
); }))
;
40 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", 40, __extension__ __PRETTY_FUNCTION__
); }))
;
41 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", 41,
__extension__ __PRETTY_FUNCTION__); }))
;
42 const size_t row_count = input_length / row_length;
43 const size_t scale_offset = _ccv_nnc_8i_rowwise_packed_scale_offset(format, input_length, row_length);
44 return scale_offset + row_count * CCV_GET_DATA_TYPE_SIZE(datatype)_ccv_get_data_type_size[((datatype) & 0xFF000) >> 12
]
;
45}
46
47static void _ccv_nnc_8i_rowwise_packed_write_bits(uint8_t* const data, const size_t bit_offset, const uint32_t value, const int bits)
48{
49 int i;
50 for (i = 0; i < bits; i++)
51 if (value & (1u << i))
52 data[(bit_offset + i) >> 3] |= (uint8_t)(1u << ((bit_offset + i) & 7));
53}
54
55static uint32_t _ccv_nnc_8i_rowwise_packed_read_bits(const uint8_t* const data, const size_t bit_offset, const int bits)
56{
57 uint32_t value = 0;
58 int i;
59 for (i = 0; i < bits; i++)
60 if (data[(bit_offset + i) >> 3] & (uint8_t)(1u << ((bit_offset + i) & 7)))
61 value |= (1u << i);
62 return value;
63}
64
65static inline int _ccv_nnc_8i_rowwise_packed_sign_extend(const uint32_t value, const int bits)
66{
67 const uint32_t sign = 1u << (bits - 1);
68 return (value & sign) ? (int)value - (int)(1u << bits) : (int)value;
69}
70
71static inline int _ccv_nnc_8i_rowwise_packed_floor_div(const int numerator, const int denominator)
72{
73 assert(denominator > 0)((void) sizeof ((denominator > 0) ? 1 : 0), __extension__ (
{ if (denominator > 0) ; else __assert_fail ("denominator > 0"
, "ccv_nnc_8i_rowwise.c", 73, __extension__ __PRETTY_FUNCTION__
); }))
;
74 return numerator >= 0 ? numerator / denominator : -((-numerator + denominator - 1) / denominator);
75}
76
77static inline int _ccv_nnc_8i_rowwise_packed_ceil_div(const int numerator, const int denominator)
78{
79 assert(denominator > 0)((void) sizeof ((denominator > 0) ? 1 : 0), __extension__ (
{ if (denominator > 0) ; else __assert_fail ("denominator > 0"
, "ccv_nnc_8i_rowwise.c", 79, __extension__ __PRETTY_FUNCTION__
); }))
;
80 return numerator >= 0 ? (numerator + denominator - 1) / denominator : -((-numerator) / denominator);
81}
82
83static double _ccv_nnc_8i_rowwise_packed_stored_scale(const double scale, const int datatype)
84{
85 if (datatype == CCV_16F)
86 {
87 const float scale_f = (float)scale;
88 uint16_t scale_h;
89 float stored_scale;
90 ccv_float_to_half_precision(&scale_f, &scale_h, 1);
91 ccv_half_precision_to_float(&scale_h, &stored_scale, 1);
92 return stored_scale;
93 } else if (datatype == CCV_16BF) {
94 const float scale_f = (float)scale;
95 uint16_t scale_bf;
96 float stored_scale;
97 ccv_float_to_bfloat(&scale_f, &scale_bf, 1);
98 ccv_bfloat_to_float(&scale_bf, &stored_scale, 1);
99 return stored_scale;
100 } else if (datatype == CCV_32F)
101 return (float)scale;
102 return scale;
103}
104
105static void _ccv_nnc_8i_rowwise_packed_store_scale(uint8_t* const scales, const int datatype, const size_t i, const double scale)
106{
107 if (datatype == CCV_16F)
108 {
109 const float scale_f = (float)scale;
110 ccv_float_to_half_precision(&scale_f, (uint16_t*)scales + i, 1);
111 } else if (datatype == CCV_16BF) {
112 const float scale_f = (float)scale;
113 ccv_float_to_bfloat(&scale_f, (uint16_t*)scales + i, 1);
114 } else if (datatype == CCV_32F)
115 ((float*)scales)[i] = (float)scale;
116 else
117 ((double*)scales)[i] = scale;
118}
119
120static double _ccv_nnc_8i_rowwise_packed_load_scale(const uint8_t* const scales, const int datatype, const size_t i)
121{
122 if (datatype == CCV_16F)
123 {
124 float scale_f;
125 ccv_half_precision_to_float((const uint16_t*)scales + i, &scale_f, 1);
126 return scale_f;
127 } else if (datatype == CCV_16BF) {
128 float scale_f;
129 ccv_bfloat_to_float((const uint16_t*)scales + i, &scale_f, 1);
130 return scale_f;
131 } else if (datatype == CCV_32F)
132 return ((const float*)scales)[i];
133 return ((const double*)scales)[i];
134}
135
136static 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)
137{
138 size_t j;
139 if (datatype
27.1
'datatype' is not equal to CCV_16F
== CCV_16F)
28
Taking false branch
140 {
141 const uint16_t* const f16 = (const uint16_t*)input + row_start;
142 for (j = 0; j < row_length; j++)
143 {
144 float v;
145 ccv_half_precision_to_float(f16 + j, &v, 1);
146 row[j] = v;
147 }
148 } else if (datatype
28.1
'datatype' is not equal to CCV_16BF
== CCV_16BF) {
29
Taking false branch
149 const uint16_t* const bf16 = (const uint16_t*)input + row_start;
150 for (j = 0; j < row_length; j++)
151 {
152 float v;
153 ccv_bfloat_to_float(bf16 + j, &v, 1);
154 row[j] = v;
155 }
156 } else if (datatype
29.1
'datatype' is not equal to CCV_32F
== CCV_32F) {
30
Taking false branch
157 const float* const f32 = (const float*)input + row_start;
158 for (j = 0; j < row_length; j++)
159 row[j] = f32[j];
160 } else {
161 const double* const f64 = (const double*)input + row_start;
162 for (j = 0; j
30.1
'j' is < 'row_length'
< row_length
; j++)
31
Loop condition is true. Entering loop body
32
Assuming 'j' is >= 'row_length'
33
Loop condition is false. Execution continues on line 165
163 row[j] = f64[j];
164 }
165 for (; j < padded_row_length; j++)
34
Assuming 'j' is >= 'padded_row_length'
35
Loop condition is false. Execution continues on line 165
166 row[j] = 0;
167}
168
169static void _ccv_nnc_8i_rowwise_packed_write_value(void* const output, const int datatype, const size_t j, const double v)
170{
171 if (datatype == CCV_16F)
172 {
173 const float v_f = (float)v;
174 ccv_float_to_half_precision(&v_f, (uint16_t*)output + j, 1);
175 } else if (datatype == CCV_16BF) {
176 const float v_f = (float)v;
177 ccv_float_to_bfloat(&v_f, (uint16_t*)output + j, 1);
178 } else if (datatype == CCV_32F)
179 ((float*)output)[j] = (float)v;
180 else
181 ((double*)output)[j] = v;
182}
183
184static inline double _ccv_nnc_8i_rowwise_weight(const float* const imatrix, const size_t j)
185{
186 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.;
187}
188
189static 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)
190{
191 if (!imatrix)
192 return 1;
193 if (imatrix_length < row_length || imatrix_length % row_length != 0)
194 return 0;
195 const size_t imatrix_slices = imatrix_length / row_length;
196 return imatrix_slices > 0 && row_count % imatrix_slices == 0;
197}
198
199static 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)
200{
201 if (!imatrix)
202 return 0;
203 const size_t imatrix_slices = imatrix_length / row_length;
204 if (imatrix_slices == 1)
205 return imatrix;
206 const size_t rows_per_slice = row_count / imatrix_slices;
207 return imatrix + (row_idx / rows_per_slice) * row_length;
208}
209
210typedef struct {
211 int q[32];
212 int q8[32];
213 int m;
214 int b;
215 int z;
216 int scale;
217 int grid[4];
218 uint32_t signs;
219} ccv_nnc_8i_rowwise_packed_group_t;
220
221static 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)
222{
223 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", 223, __extension__ __PRETTY_FUNCTION__
); }))
;
224 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", 224
, __extension__ __PRETTY_FUNCTION__); }))
;
225 int code;
226 for (code = 0; code < code_count; code++)
227 {
228 uint8_t target[8];
229 int value = code;
230 int j;
231 for (j = 0; j < lanes; j++)
232 {
233 target[j] = (uint8_t)(value % levels);
234 value /= levels;
235 }
236 int best_distance[CCV_NNC_8I_ROWWISE_IQ3_CANDIDATES];
237 int k;
238 for (k = 0; k < candidate_count; k++)
239 {
240 best_distance[k] = INT_MAX2147483647;
241 candidates[(size_t)code * candidate_count + k] = 0;
242 }
243 int index;
244 for (index = 0; index < grid_size; index++)
245 {
246 int distance = 0;
247 for (j = 0; j < lanes; j++)
248 {
249 const int d = (int)grid[(size_t)index * lanes + j] - target[j];
250 distance += d * d;
251 }
252 if (distance >= best_distance[candidate_count - 1])
253 continue;
254 k = candidate_count - 1;
255 while (k > 0 && distance < best_distance[k - 1])
256 {
257 best_distance[k] = best_distance[k - 1];
258 candidates[(size_t)code * candidate_count + k] = candidates[(size_t)code * candidate_count + k - 1];
259 --k;
260 }
261 best_distance[k] = distance;
262 candidates[(size_t)code * candidate_count + k] = (uint16_t)index;
263 }
264 }
265}
266
267static 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)
268{
269 double best_sse = DBL_MAX1.7976931348623157e+308;
270 int best_q[16] = {0};
271 int best_q8[16] = {0};
272 int best_m = 1, best_b = 0;
273 int m, b, j;
274 for (m = 1; m <= 8; m++)
275 for (b = -16; b <= 15; b++)
276 {
277 if (-16 * m + b < -127 || 15 * m + b > 127)
278 continue;
279 double sse = 0;
280 int q[16];
281 int q8[16];
282 for (j = 0; j < 16; j++)
283 {
284 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); })
;
285 q8[j] = q[j] * m + b;
286 const double d = q8[j] - y[j];
287 sse += w[j] * d * d;
288 }
289 if (sse < best_sse)
290 {
291 best_sse = sse;
292 best_m = m;
293 best_b = b;
294 memcpy(best_q, q, sizeof(best_q));
295 memcpy(best_q8, q8, sizeof(best_q8));
296 }
297 }
298 group->m = best_m;
299 group->b = best_b;
300 memcpy(group->q, best_q, sizeof(best_q));
301 memcpy(group->q8, best_q8, sizeof(best_q8));
302}
303
304static 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)
305{
306 double best_sse = DBL_MAX1.7976931348623157e+308;
307 int best_q[8] = {0};
308 int best_q8[8] = {0};
309 int best_m = 1, best_b = 0;
310 int m, b, j;
311 for (m = 1; m <= 4; m++)
312 for (b = -2; b <= 1; b++)
313 {
314 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; })
;
315 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; })
;
316 if (qmin > qmax)
317 continue;
318 double sse = 0;
319 int q[8];
320 int q8[8];
321 for (j = 0; j < 8; j++)
322 {
323 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); })
;
324 q8[j] = q[j] * m + b;
325 const double d = q8[j] - y[j];
326 sse += w[j] * d * d;
327 }
328 if (sse < best_sse)
329 {
330 best_sse = sse;
331 best_m = m;
332 best_b = b;
333 memcpy(best_q, q, sizeof(best_q));
334 memcpy(best_q8, q8, sizeof(best_q8));
335 }
336 }
337 group->m = best_m;
338 group->b = best_b;
339 memcpy(group->q, best_q, sizeof(best_q));
340 memcpy(group->q8, best_q8, sizeof(best_q8));
341}
342
343static 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)
344{
345 double best_sse = DBL_MAX1.7976931348623157e+308;
346 int best_q[16] = {0};
347 int best_q8[16] = {0};
348 int best_m = 1, best_b = 0;
349 int m, b, j;
350 for (m = 1; m <= 16; m++)
351 for (b = -8; b <= 7; b++)
352 {
353 if (-8 * m + b < -127 || 7 * m + b > 127)
354 continue;
355 double sse = 0;
356 int q[16];
357 int q8[16];
358 for (j = 0; j < 16; j++)
359 {
360 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); })
;
361 q8[j] = q[j] * m + b;
362 const double d = q8[j] - y[j];
363 sse += w[j] * d * d;
364 }
365 if (sse < best_sse)
366 {
367 best_sse = sse;
368 best_m = m;
369 best_b = b;
370 memcpy(best_q, q, sizeof(best_q));
371 memcpy(best_q8, q8, sizeof(best_q8));
372 }
373 }
374 group->m = best_m;
375 group->b = best_b;
376 memcpy(group->q, best_q, sizeof(best_q));
377 memcpy(group->q8, best_q8, sizeof(best_q8));
378}
379
380static 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)
381{
382 double best_sse = DBL_MAX1.7976931348623157e+308;
383 int best_q[16] = {0};
384 int best_q8[16] = {0};
385 int best_m = 1, best_b = 0;
386 int m, b, j;
387 for (m = 1; m <= 32; m++)
388 for (b = -8; b <= 6; b += 2)
389 {
390 if (-4 * m + b < -127 || 3 * m + b > 127)
391 continue;
392 double sse = 0;
393 int q[16];
394 int q8[16];
395 for (j = 0; j < 16; j++)
396 {
397 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); })
;
398 q8[j] = q[j] * m + b;
399 const double d = q8[j] - y[j];
400 sse += w[j] * d * d;
401 }
402 if (sse < best_sse)
403 {
404 best_sse = sse;
405 best_m = m;
406 best_b = b;
407 memcpy(best_q, q, sizeof(best_q));
408 memcpy(best_q8, q8, sizeof(best_q8));
409 }
410 }
411 group->m = best_m;
412 group->b = best_b;
413 memcpy(group->q, best_q, sizeof(best_q));
414 memcpy(group->q8, best_q8, sizeof(best_q8));
415}
416
417static 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)
418{
419 double best_sse = DBL_MAX1.7976931348623157e+308;
420 int best_q[16] = {0};
421 int best_q8[16] = {0};
422 int best_m = 1, best_z = 0;
423 int m, z, j;
424 for (m = 1; m <= 64; m++)
425 for (z = 0; z <= 120; z += 8)
426 {
427 if (3 * m - z > 127)
428 continue;
429 double sse = 0;
430 int q[16];
431 int q8[16];
432 for (j = 0; j < 16; j++)
433 {
434 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); })
;
435 q8[j] = q[j] * m - z;
436 const double d = q8[j] - y[j];
437 sse += w[j] * d * d;
438 }
439 if (sse < best_sse)
440 {
441 best_sse = sse;
442 best_m = m;
443 best_z = z;
444 memcpy(best_q, q, sizeof(best_q));
445 memcpy(best_q8, q8, sizeof(best_q8));
446 }
447 }
448 group->m = best_m;
449 group->z = best_z;
450 memcpy(group->q, best_q, sizeof(best_q));
451 memcpy(group->q8, best_q8, sizeof(best_q8));
452}
453
454static int _ccv_nnc_8i_rowwise_packed_iq2_value(const uint64_t* const grid, const int index, const int lane)
455{
456 const int v = (int)((grid[index] >> (lane * 8)) & 0xff);
457 if (v == 8)
458 return 1;
459 if (v == 25)
460 return 3;
461 assert(v == 43)((void) sizeof ((v == 43) ? 1 : 0), __extension__ ({ if (v ==
43) ; else __assert_fail ("v == 43", "ccv_nnc_8i_rowwise.c",
461, __extension__ __PRETTY_FUNCTION__); }))
;
462 return 5;
463}
464
465static int _ccv_nnc_8i_rowwise_packed_iq2xxs_value(const int index, const int lane)
466{
467 const int v = (int)((ccv_nnc_8i_rowwise_packed_iq2xxs_grid[index] >> (lane * 2)) & 3);
468 assert(v < 3)((void) sizeof ((v < 3) ? 1 : 0), __extension__ ({ if (v <
3) ; else __assert_fail ("v < 3", "ccv_nnc_8i_rowwise.c",
468, __extension__ __PRETTY_FUNCTION__); }))
;
469 return 1 + v * 2;
470}
471
472enum {
473 CCV_NNC_8I_ROWWISE_PACKED_IQ2XXS_GRID_SIZE = 256,
474 CCV_NNC_8I_ROWWISE_PACKED_IQ2S_GRID_SIZE = 1024,
475 CCV_NNC_8I_ROWWISE_PACKED_IQ2_CODE_COUNT = 6561,
476};
477
478static 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};
479static int ccv_nnc_8i_rowwise_packed_iq2_scale_initialized = 0;
480static uint8_t ccv_nnc_8i_rowwise_packed_iq2xxs_scale_level[33][3];
481static int ccv_nnc_8i_rowwise_packed_iq2xxs_initialized = 0;
482static int ccv_nnc_8i_rowwise_packed_iq2xxs_candidates_initialized = 0;
483static uint8_t ccv_nnc_8i_rowwise_packed_iq2xxs_level[CCV_NNC_8I_ROWWISE_PACKED_IQ2XXS_GRID_SIZE][8];
484static uint8_t ccv_nnc_8i_rowwise_packed_iq2xxs_scaled_value[33][CCV_NNC_8I_ROWWISE_PACKED_IQ2XXS_GRID_SIZE][8];
485static uint16_t ccv_nnc_8i_rowwise_packed_iq2xxs_candidates[CCV_NNC_8I_ROWWISE_PACKED_IQ2_CODE_COUNT][CCV_NNC_8I_ROWWISE_IQ2_CANDIDATES];
486
487static void _ccv_nnc_8i_rowwise_packed_iq2_scale_init(void)
488{
489 if (ccv_nnc_8i_rowwise_packed_iq2_scale_initialized)
490 return;
491 int scale, level;
492 for (scale = 1; scale <= 32; scale++)
493 for (level = 0; level < 3; level++)
494 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; })
;
495 ccv_nnc_8i_rowwise_packed_iq2_scale_initialized = 1;
496}
497
498static void _ccv_nnc_8i_rowwise_packed_iq2xxs_init(void)
499{
500 if (ccv_nnc_8i_rowwise_packed_iq2xxs_initialized)
501 return;
502 _ccv_nnc_8i_rowwise_packed_iq2_scale_init();
503 int index, j, scale;
504 for (index = 0; index < CCV_NNC_8I_ROWWISE_PACKED_IQ2XXS_GRID_SIZE; index++)
505 for (j = 0; j < 8; j++)
506 ccv_nnc_8i_rowwise_packed_iq2xxs_level[index][j] = (uint8_t)((_ccv_nnc_8i_rowwise_packed_iq2xxs_value(index, j) - 1) / 2);
507 for (scale = 1; scale <= 32; scale++)
508 {
509 for (index = 0; index < CCV_NNC_8I_ROWWISE_PACKED_IQ2XXS_GRID_SIZE; index++)
510 for (j = 0; j < 8; j++)
511 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]];
512 }
513 ccv_nnc_8i_rowwise_packed_iq2xxs_initialized = 1;
514}
515
516static void _ccv_nnc_8i_rowwise_packed_iq2xxs_candidates_init(void)
517{
518 if (ccv_nnc_8i_rowwise_packed_iq2xxs_candidates_initialized)
519 return;
520 _ccv_nnc_8i_rowwise_packed_iq2xxs_init();
521 _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]);
522 ccv_nnc_8i_rowwise_packed_iq2xxs_candidates_initialized = 1;
523}
524
525enum {
526 CCV_NNC_8I_ROWWISE_PACKED_IQ2XS_GRID_SIZE = 512,
527};
528
529static int ccv_nnc_8i_rowwise_packed_iq2xs_initialized = 0;
530static int ccv_nnc_8i_rowwise_packed_iq2xs_candidates_initialized = 0;
531static uint8_t ccv_nnc_8i_rowwise_packed_iq2xs_level[CCV_NNC_8I_ROWWISE_PACKED_IQ2XS_GRID_SIZE][8];
532static uint8_t ccv_nnc_8i_rowwise_packed_iq2xs_scaled_value[16][CCV_NNC_8I_ROWWISE_PACKED_IQ2XS_GRID_SIZE][8];
533static uint16_t ccv_nnc_8i_rowwise_packed_iq2xs_candidates[CCV_NNC_8I_ROWWISE_PACKED_IQ2_CODE_COUNT][CCV_NNC_8I_ROWWISE_IQ2_CANDIDATES];
534
535static void _ccv_nnc_8i_rowwise_packed_iq2xs_init(void)
536{
537 if (ccv_nnc_8i_rowwise_packed_iq2xs_initialized)
538 return;
539 _ccv_nnc_8i_rowwise_packed_iq2_scale_init();
540 int index, j, scale_code;
541 for (index = 0; index < CCV_NNC_8I_ROWWISE_PACKED_IQ2XS_GRID_SIZE; index++)
542 for (j = 0; j < 8; j++)
543 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);
544 for (scale_code = 0; scale_code < 16; scale_code++)
545 {
546 const int scale = ccv_nnc_8i_rowwise_packed_iq2xxs_scales[scale_code];
547 for (index = 0; index < CCV_NNC_8I_ROWWISE_PACKED_IQ2XS_GRID_SIZE; index++)
548 for (j = 0; j < 8; j++)
549 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]];
550 }
551 ccv_nnc_8i_rowwise_packed_iq2xs_initialized = 1;
552}
553
554static void _ccv_nnc_8i_rowwise_packed_iq2xs_candidates_init(void)
555{
556 if (ccv_nnc_8i_rowwise_packed_iq2xs_candidates_initialized)
557 return;
558 _ccv_nnc_8i_rowwise_packed_iq2xs_init();
559 _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]);
560 ccv_nnc_8i_rowwise_packed_iq2xs_candidates_initialized = 1;
561}
562
563static int ccv_nnc_8i_rowwise_packed_iq2s_initialized = 0;
564static uint8_t ccv_nnc_8i_rowwise_packed_iq2s_level[CCV_NNC_8I_ROWWISE_PACKED_IQ2S_GRID_SIZE][8];
565static uint8_t ccv_nnc_8i_rowwise_packed_iq2s_scale_level[65][3];
566static uint16_t ccv_nnc_8i_rowwise_packed_iq2s_scale_level2[65][3];
567static uint8_t ccv_nnc_8i_rowwise_packed_iq2s_scaled_value[65][CCV_NNC_8I_ROWWISE_PACKED_IQ2S_GRID_SIZE][8];
568
569static void _ccv_nnc_8i_rowwise_packed_iq2s_init(void)
570{
571 if (ccv_nnc_8i_rowwise_packed_iq2s_initialized)
572 return;
573 int index, j, scale;
574 for (index = 0; index < CCV_NNC_8I_ROWWISE_PACKED_IQ2S_GRID_SIZE; index++)
575 for (j = 0; j < 8; j++)
576 {
577 const int v = _ccv_nnc_8i_rowwise_packed_iq2_value(ccv_nnc_8i_rowwise_packed_iq2s_grid, index, j);
578 ccv_nnc_8i_rowwise_packed_iq2s_level[index][j] = (uint8_t)((v - 1) / 2);
579 }
580 for (scale = 1; scale <= 64; scale++)
581 {
582 for (j = 0; j < 3; j++)
583 {
584 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; })
;
585 ccv_nnc_8i_rowwise_packed_iq2s_scale_level[scale][j] = (uint8_t)v;
586 ccv_nnc_8i_rowwise_packed_iq2s_scale_level2[scale][j] = (uint16_t)(v * v);
587 }
588 for (index = 0; index < CCV_NNC_8I_ROWWISE_PACKED_IQ2S_GRID_SIZE; index++)
589 for (j = 0; j < 8; j++)
590 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]];
591 }
592 ccv_nnc_8i_rowwise_packed_iq2s_initialized = 1;
593}
594
595static 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)
596{
597 const uint8_t* const mag = ccv_nnc_8i_rowwise_packed_iq2s_scaled_value[scale][index];
598 double d = (double)mag[0] - ay[lane];
599 double sse = w[lane] * d * d;
600 d = (double)mag[1] - ay[lane + 1];
601 sse += w[lane + 1] * d * d;
602 d = (double)mag[2] - ay[lane + 2];
603 sse += w[lane + 2] * d * d;
604 d = (double)mag[3] - ay[lane + 3];
605 sse += w[lane + 3] * d * d;
606 d = (double)mag[4] - ay[lane + 4];
607 sse += w[lane + 4] * d * d;
608 d = (double)mag[5] - ay[lane + 5];
609 sse += w[lane + 5] * d * d;
610 d = (double)mag[6] - ay[lane + 6];
611 sse += w[lane + 6] * d * d;
612 d = (double)mag[7] - ay[lane + 7];
613 sse += w[lane + 7] * d * d;
614 return sse;
615}
616
617static int _ccv_nnc_8i_rowwise_packed_iq3xxs_value(const int index, const int lane)
618{
619 const int v = (int)((ccv_nnc_8i_rowwise_packed_iq3xxs_grid[index] >> (lane * 8)) & 0xff);
620 switch (v)
621 {
622 case 4: return 1;
623 case 12: return 3;
624 case 20: return 5;
625 case 28: return 7;
626 case 36: return 9;
627 case 44: return 11;
628 case 52: return 13;
629 default:
630 assert(v == 62)((void) sizeof ((v == 62) ? 1 : 0), __extension__ ({ if (v ==
62) ; else __assert_fail ("v == 62", "ccv_nnc_8i_rowwise.c",
630, __extension__ __PRETTY_FUNCTION__); }))
;
631 return 15;
632 }
633}
634
635static int _ccv_nnc_8i_rowwise_packed_iq3s_value(const int index, const int lane)
636{
637 return (int)((ccv_nnc_8i_rowwise_packed_iq3s_grid[index] >> (lane * 8)) & 0xff);
638}
639
640#define CCV_NNC_8I_ROWWISE_PACKED_IQ3S_GRID_SIZE(512) (512)
641#define CCV_NNC_8I_ROWWISE_PACKED_IQ3XXS_GRID_SIZE(256) (256)
642#define CCV_NNC_8I_ROWWISE_PACKED_IQ3_CODE_COUNT(4096) (4096)
643
644static int ccv_nnc_8i_rowwise_packed_iq3s_initialized = 0;
645static uint8_t ccv_nnc_8i_rowwise_packed_iq3s_scaled_value[17][CCV_NNC_8I_ROWWISE_PACKED_IQ3S_GRID_SIZE(512)][4];
646
647static int ccv_nnc_8i_rowwise_packed_iq3xxs_initialized = 0;
648static int ccv_nnc_8i_rowwise_packed_iq3xxs_candidates_initialized = 0;
649static uint8_t ccv_nnc_8i_rowwise_packed_iq3xxs_level[CCV_NNC_8I_ROWWISE_PACKED_IQ3XXS_GRID_SIZE(256)][4];
650static uint8_t ccv_nnc_8i_rowwise_packed_iq3xxs_scaled_value[17][CCV_NNC_8I_ROWWISE_PACKED_IQ3XXS_GRID_SIZE(256)][4];
651static uint16_t ccv_nnc_8i_rowwise_packed_iq3xxs_candidates[CCV_NNC_8I_ROWWISE_PACKED_IQ3_CODE_COUNT(4096)][CCV_NNC_8I_ROWWISE_IQ3_CANDIDATES];
652
653static void _ccv_nnc_8i_rowwise_packed_iq3s_init(void)
654{
655 if (ccv_nnc_8i_rowwise_packed_iq3s_initialized)
656 return;
657 int index, j, scale;
658 for (scale = 1; scale <= 16; scale++)
659 for (index = 0; index < CCV_NNC_8I_ROWWISE_PACKED_IQ3S_GRID_SIZE(512); index++)
660 for (j = 0; j < 4; j++)
661 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; })
;
662 ccv_nnc_8i_rowwise_packed_iq3s_initialized = 1;
663}
664
665static void _ccv_nnc_8i_rowwise_packed_iq3xxs_init(void)
666{
667 if (ccv_nnc_8i_rowwise_packed_iq3xxs_initialized)
668 return;
669 int index, j, scale;
670 for (index = 0; index < CCV_NNC_8I_ROWWISE_PACKED_IQ3XXS_GRID_SIZE(256); index++)
671 for (j = 0; j < 4; j++)
672 ccv_nnc_8i_rowwise_packed_iq3xxs_level[index][j] = (uint8_t)((_ccv_nnc_8i_rowwise_packed_iq3xxs_value(index, j) - 1) / 2);
673 for (scale = 1; scale <= 16; scale++)
674 for (index = 0; index < CCV_NNC_8I_ROWWISE_PACKED_IQ3XXS_GRID_SIZE(256); index++)
675 for (j = 0; j < 4; j++)
676 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; })
;
677 ccv_nnc_8i_rowwise_packed_iq3xxs_initialized = 1;
678}
679
680static void _ccv_nnc_8i_rowwise_packed_iq3xxs_candidates_init(void)
681{
682 if (ccv_nnc_8i_rowwise_packed_iq3xxs_candidates_initialized)
683 return;
684 _ccv_nnc_8i_rowwise_packed_iq3xxs_init();
685 _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]);
686 ccv_nnc_8i_rowwise_packed_iq3xxs_candidates_initialized = 1;
687}
688
689static 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)
690{
691 const uint8_t* const mag = ccv_nnc_8i_rowwise_packed_iq3s_scaled_value[scale][index];
692 double d = (double)mag[0] - ay[lane];
693 double sse = w[lane] * d * d;
694 d = (double)mag[1] - ay[lane + 1];
695 sse += w[lane + 1] * d * d;
696 d = (double)mag[2] - ay[lane + 2];
697 sse += w[lane + 2] * d * d;
698 d = (double)mag[3] - ay[lane + 3];
699 sse += w[lane + 3] * d * d;
700 return sse;
701}
702
703static inline double _ccv_nnc_8i_rowwise_packed_iq2_cost(const double cost[8][3], const uint8_t* const levels)
704{
705 double sse = 0;
706 int j;
707 for (j = 0; j < 8; j++)
708 sse += cost[j][levels[j]];
709 return sse;
710}
711
712static inline double _ccv_nnc_8i_rowwise_packed_safe_lower_bound(const double value)
713{
714 return nextafter(value - (fabs(value) + 1) * (64 * DBL_EPSILON2.2204460492503131e-16), -INFINITY(__builtin_inff ()));
715}
716
717static 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)
718{
719 int best_flip = -1;
720 int j;
721 if (flip_sign)
722 {
723 double best_flip_metric = DBL_MAX1.7976931348623157e+308;
724 for (j = 0; j < 8; j++)
725 {
726 const double metric = flip_metric[j][levels[j]];
727 if (metric < best_flip_metric)
728 {
729 best_flip_metric = metric;
730 best_flip = j;
731 }
732 }
733 }
734 double sse = 0;
735 for (j = 0; j < 8; j++)
736 sse += j == best_flip ? flipped_cost[j][levels[j]] : cost[j][levels[j]];
737 *sign_index = (signs ^ (best_flip >= 0 ? (uint8_t)(1u << best_flip) : 0)) & 0x7f;
738 return sse;
739}
740
741static 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)
742{
743 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", 743, __extension__ __PRETTY_FUNCTION__
); }))
;
744 double best_sse = DBL_MAX1.7976931348623157e+308;
745 int best_scale_code = 0;
746 int best_grid[4] = {0};
747 int best_sign[4] = {0};
748 int scale_code;
749 for (scale_code = 0; scale_code < 16; scale_code++)
750 {
751 const int scale = ccv_nnc_8i_rowwise_packed_iq2xxs_scales[scale_code];
752 double group_sse = 0;
753 int group_grid[4] = {0};
754 int group_sign[4] = {0};
755 int sg;
756 for (sg = 0; sg < 4; sg++)
757 {
758 double best_sub_sse = DBL_MAX1.7976931348623157e+308;
759 int best_sub_grid = 0;
760 int best_sub_sign = 0;
761 const int lane = sg * 8;
762 uint8_t signs = 0;
763 int negative_count = 0;
764 double cost[8][3];
765 double flipped_cost[8][3];
766 double flip_metric[8][3];
767 int j;
768 for (j = 0; j < 8; j++)
769 {
770 if (y[lane + j] < 0)
771 {
772 signs |= (uint8_t)(1u << j);
773 negative_count++;
774 }
775 int level;
776 for (level = 0; level < 3; level++)
777 {
778 const int mag = ccv_nnc_8i_rowwise_packed_iq2xxs_scale_level[scale][level];
779 const int q8 = (signs & (1u << j)) ? -mag : mag;
780 double d = (double)q8 - y[lane + j];
781 cost[j][level] = w[lane + j] * d * d;
782 d = (double)-q8 - y[lane + j];
783 flipped_cost[j][level] = w[lane + j] * d * d;
784 flip_metric[j][level] = w[lane + j] * (double)mag * fabs(y[lane + j]);
785 }
786 }
787 int target_code = 0;
788 int code_multiplier = 1;
789 uint8_t target_levels[8];
790 double lower_bound_base = 0;
791 double lower_bound_ratio = DBL_MAX1.7976931348623157e+308;
792 double lower_bound_flip = DBL_MAX1.7976931348623157e+308;
793 for (j = 0; j < 8; j++)
794 {
795 int target_level = 0;
796 if (cost[j][1] < cost[j][target_level])
797 target_level = 1;
798 if (cost[j][2] < cost[j][target_level])
799 target_level = 2;
800 target_levels[j] = (uint8_t)target_level;
801 target_code += target_level * code_multiplier;
802 code_multiplier *= 3;
803 lower_bound_base += cost[j][target_level];
804 int level;
805 for (level = 0; level < 3; level++)
806 {
807 if (level != target_level)
808 {
809 const int d = level - target_level;
810 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; })
;
811 }
812 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; })
;
813 }
814 }
815 int candidate;
816 for (candidate = 0; candidate < CCV_NNC_8I_ROWWISE_IQ2_CANDIDATES; candidate++)
817 {
818 const int index = ccv_nnc_8i_rowwise_packed_iq2xxs_candidates[target_code][candidate];
819 const uint8_t* const levels = ccv_nnc_8i_rowwise_packed_iq2xxs_level[index];
820 int sign_index;
821 const double sse = _ccv_nnc_8i_rowwise_packed_iq2xxs_cost(cost, flipped_cost, flip_metric, levels, signs, negative_count & 1, &sign_index);
822 if (sse < best_sub_sse || (sse == best_sub_sse && index < best_sub_grid))
823 {
824 best_sub_sse = sse;
825 best_sub_grid = index;
826 best_sub_sign = sign_index;
827 }
828 }
829 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]];
830 int cutoff_distance = 0;
831 for (j = 0; j < 8; j++)
832 {
833 const int d = (int)cutoff_levels[j] - target_levels[j];
834 cutoff_distance += d * d;
835 }
836 const double safe_ratio = nextafter(lower_bound_ratio, 0);
837 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));
838 if (!(best_sub_sse < lower_bound))
839 {
840 int index;
841 for (index = 0; index < CCV_NNC_8I_ROWWISE_PACKED_IQ2XXS_GRID_SIZE; index++)
842 {
843 int sign_index;
844 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);
845 if (sse < best_sub_sse || (sse == best_sub_sse && index < best_sub_grid))
846 {
847 best_sub_sse = sse;
848 best_sub_grid = index;
849 best_sub_sign = sign_index;
850 }
851 }
852 }
853 group_sse += best_sub_sse;
854 group_grid[sg] = best_sub_grid;
855 group_sign[sg] = best_sub_sign;
856 }
857 if (group_sse < best_sse)
858 {
859 best_sse = group_sse;
860 best_scale_code = scale_code;
861 memcpy(best_grid, group_grid, sizeof(best_grid));
862 memcpy(best_sign, group_sign, sizeof(best_sign));
863 }
864 }
865 group->scale = best_scale_code;
866 group->signs = 0;
867 memcpy(group->grid, best_grid, sizeof(best_grid));
868 int j;
869 for (j = 0; j < 4; j++)
870 group->signs |= (uint32_t)best_sign[j] << (j * 7);
871 for (j = 0; j < 32; j++)
872 {
873 const int sg = j >> 3;
874 const int lane = j & 7;
875 const uint8_t signs = ccv_nnc_8i_rowwise_packed_iq2xxs_ksigns[best_sign[sg]];
876 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];
877 group->q8[j] = (signs & (1u << lane)) ? -mag : mag;
878 }
879}
880
881static 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)
882{
883 assert(ccv_nnc_8i_rowwise_packed_iq2s_initialized)((void) sizeof ((ccv_nnc_8i_rowwise_packed_iq2s_initialized) ?
1 : 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", 883, __extension__ __PRETTY_FUNCTION__
); }))
;
884 double best_sse = DBL_MAX1.7976931348623157e+308;
885 int best_scale = 1;
886 int best_grid[2] = {0};
887 double ay[16];
888 double wy[16];
889 uint32_t signs = 0;
890 int j;
891 for (j = 0; j < 16; j++)
892 {
893 ay[j] = fabs(y[j]);
894 wy[j] = w[j] * ay[j];
895 if (y[j] < 0)
896 signs |= (1u << j);
897 }
898 double sub_sse[2][65];
899 int sub_grid[2][65];
900 int sg, scale;
901 for (sg = 0; sg < 2; sg++)
902 for (scale = 1; scale <= 64; scale++)
903 {
904 sub_sse[sg][scale] = DBL_MAX1.7976931348623157e+308;
905 sub_grid[sg][scale] = 0;
906 }
907 for (sg = 0; sg < 2; sg++)
908 {
909 const int lane = sg * 8;
910 double sum_y2 = 0;
911 for (j = 0; j < 8; j++)
912 sum_y2 += w[lane + j] * ay[lane + j] * ay[lane + j];
913 int index;
914 for (index = 0; index < CCV_NNC_8I_ROWWISE_PACKED_IQ2S_GRID_SIZE; index++)
915 {
916 double sw[3] = {0};
917 double swy[3] = {0};
918 for (j = 0; j < 8; j++)
919 {
920 const int level = ccv_nnc_8i_rowwise_packed_iq2s_level[index][j];
921 sw[level] += w[lane + j];
922 swy[level] += wy[lane + j];
923 }
924 for (scale = 1; scale <= 64; scale++)
925 {
926 const double sse = sum_y2 +
927 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] +
928 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] +
929 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];
930 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)
931 {
932 const double exact_sse = _ccv_nnc_8i_rowwise_packed_iq2s_sse(ay, w, lane, scale, index);
933 if (exact_sse < sub_sse[sg][scale])
934 {
935 sub_sse[sg][scale] = exact_sse;
936 sub_grid[sg][scale] = index;
937 }
938 }
939 }
940 }
941 }
942 for (scale = 1; scale <= 64; scale++)
943 {
944 const double group_sse = sub_sse[0][scale] + sub_sse[1][scale];
945 if (group_sse < best_sse)
946 {
947 best_sse = group_sse;
948 best_scale = scale;
949 best_grid[0] = sub_grid[0][scale];
950 best_grid[1] = sub_grid[1][scale];
951 }
952 }
953 group->scale = best_scale;
954 group->signs = signs;
955 memcpy(group->grid, best_grid, sizeof(best_grid));
956 for (j = 0; j < 16; j++)
957 {
958 const int sg = j >> 3;
959 const int lane = j & 7;
960 const int mag = ccv_nnc_8i_rowwise_packed_iq2s_scaled_value[best_scale][best_grid[sg]][lane];
961 group->q8[j] = (signs & (1u << j)) ? -mag : mag;
962 }
963}
964
965static 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)
966{
967 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", 967, __extension__ __PRETTY_FUNCTION__
); }))
;
968 double best_sse = DBL_MAX1.7976931348623157e+308;
969 int best_scale_code = 0;
970 int best_grid = 0;
971 uint32_t signs = 0;
972 int j;
973 for (j = 0; j < 8; j++)
974 if (y[j] < 0)
975 signs |= (1u << j);
976 int scale_code;
977 for (scale_code = 0; scale_code < 16; scale_code++)
978 {
979 double cost[8][3];
980 for (j = 0; j < 8; j++)
981 {
982 int level;
983 for (level = 0; level < 3; level++)
984 {
985 const int mag = ccv_nnc_8i_rowwise_packed_iq2xxs_scale_level[ccv_nnc_8i_rowwise_packed_iq2xxs_scales[scale_code]][level];
986 const int q8 = (signs & (1u << j)) ? -mag : mag;
987 const double d = (double)q8 - y[j];
988 cost[j][level] = w[j] * d * d;
989 }
990 }
991 int target_code = 0;
992 int code_multiplier = 1;
993 uint8_t target_levels[8];
994 double lower_bound_base = 0;
995 double lower_bound_ratio = DBL_MAX1.7976931348623157e+308;
996 for (j = 0; j < 8; j++)
997 {
998 int target_level = 0;
999 if (cost[j][1] < cost[j][target_level])
1000 target_level = 1;
1001 if (cost[j][2] < cost[j][target_level])
1002 target_level = 2;
1003 target_levels[j] = (uint8_t)target_level;
1004 target_code += target_level * code_multiplier;
1005 code_multiplier *= 3;
1006 lower_bound_base += cost[j][target_level];
1007 int level;
1008 for (level = 0; level < 3; level++)
1009 if (level != target_level)
1010 {
1011 const int d = level - target_level;
1012 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; })
;
1013 }
1014 }
1015 int candidate;
1016 for (candidate = 0; candidate < CCV_NNC_8I_ROWWISE_IQ2_CANDIDATES; candidate++)
1017 {
1018 const int index = ccv_nnc_8i_rowwise_packed_iq2xs_candidates[target_code][candidate];
1019 const uint8_t* const levels = ccv_nnc_8i_rowwise_packed_iq2xs_level[index];
1020 const double sse = _ccv_nnc_8i_rowwise_packed_iq2_cost(cost, levels);
1021 if (sse < best_sse || (sse == best_sse && scale_code == best_scale_code && index < best_grid))
1022 {
1023 best_sse = sse;
1024 best_scale_code = scale_code;
1025 best_grid = index;
1026 }
1027 }
1028 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]];
1029 int cutoff_distance = 0;
1030 for (j = 0; j < 8; j++)
1031 {
1032 const int d = (int)cutoff_levels[j] - target_levels[j];
1033 cutoff_distance += d * d;
1034 }
1035 const double lower_bound = _ccv_nnc_8i_rowwise_packed_safe_lower_bound(lower_bound_base + nextafter(lower_bound_ratio, 0) * cutoff_distance);
1036 if (!(best_sse < lower_bound))
1037 {
1038 int index;
1039 for (index = 0; index < CCV_NNC_8I_ROWWISE_PACKED_IQ2XS_GRID_SIZE; index++)
1040 {
1041 const double sse = _ccv_nnc_8i_rowwise_packed_iq2_cost(cost, ccv_nnc_8i_rowwise_packed_iq2xs_level[index]);
1042 if (sse < best_sse || (sse == best_sse && scale_code == best_scale_code && index < best_grid))
1043 {
1044 best_sse = sse;
1045 best_scale_code = scale_code;
1046 best_grid = index;
1047 }
1048 }
1049 }
1050 }
1051 group->scale = best_scale_code;
1052 group->grid[0] = best_grid;
1053 group->signs = signs;
1054 memset(group->q8, 0, sizeof(group->q8));
1055 for (j = 0; j < 8; j++)
1056 {
1057 const int mag = ccv_nnc_8i_rowwise_packed_iq2xs_scaled_value[best_scale_code][best_grid][j];
1058 group->q8[j] = (signs & (1u << j)) ? -mag : mag;
1059 }
1060}
1061
1062static 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)
1063{
1064 assert(ccv_nnc_8i_rowwise_packed_iq3s_initialized)((void) sizeof ((ccv_nnc_8i_rowwise_packed_iq3s_initialized) ?
1 : 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", 1064, __extension__ __PRETTY_FUNCTION__
); }))
;
1065 double best_sse = DBL_MAX1.7976931348623157e+308;
1066 int best_scale = 1;
1067 int best_grid[4] = {0};
1068 double ay[16];
1069 uint32_t signs = 0;
1070 int j;
1071 for (j = 0; j < 16; j++)
1072 {
1073 ay[j] = fabs(y[j]);
1074 if (y[j] < 0)
1075 signs |= (1u << j);
1076 }
1077 int scale;
1078 for (scale = 1; scale <= 16; scale++)
1079 {
1080 double group_sse = 0;
1081 int group_grid[4] = {0};
1082 int sg;
1083 for (sg = 0; sg < 4; sg++)
1084 {
1085 double best_sub_sse = DBL_MAX1.7976931348623157e+308;
1086 int best_sub_grid = 0;
1087 const int lane = sg * 4;
1088 int index;
1089 for (index = 0; index < CCV_NNC_8I_ROWWISE_PACKED_IQ3S_GRID_SIZE(512); index++)
1090 {
1091 const double sse = _ccv_nnc_8i_rowwise_packed_iq3s_sse(ay, w, lane, scale, index);
1092 if (sse < best_sub_sse)
1093 {
1094 best_sub_sse = sse;
1095 best_sub_grid = index;
1096 }
1097 }
1098 group_sse += best_sub_sse;
1099 group_grid[sg] = best_sub_grid;
1100 }
1101 if (group_sse < best_sse)
1102 {
1103 best_sse = group_sse;
1104 best_scale = scale;
1105 memcpy(best_grid, group_grid, sizeof(best_grid));
1106 }
1107 }
1108 group->scale = best_scale;
1109 group->signs = signs;
1110 memcpy(group->grid, best_grid, sizeof(best_grid));
1111 for (j = 0; j < 16; j++)
1112 {
1113 const int sg = j >> 2;
1114 const int lane = j & 3;
1115 const int mag = ccv_nnc_8i_rowwise_packed_iq3s_scaled_value[best_scale][best_grid[sg]][lane];
1116 group->q8[j] = (signs & (1u << j)) ? -mag : mag;
1117 }
1118}
1119
1120static 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)
1121{
1122 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", 1122, __extension__ __PRETTY_FUNCTION__
); }))
;
1123 double best_sse = DBL_MAX1.7976931348623157e+308;
1124 int best_scale = 1;
1125 int best_grid[2] = {0};
1126 double ay[8];
1127 uint32_t signs = 0;
1128 int j;
1129 for (j = 0; j < 8; j++)
1130 {
1131 ay[j] = fabs(y[j]);
1132 if (y[j] < 0)
1133 signs |= (1u << j);
1134 }
1135 int scale;
1136 for (scale = 1; scale <= 16; scale++)
1137 {
1138 double group_sse = 0;
1139 int group_grid[2] = {0};
1140 int sg;
1141 for (sg = 0; sg < 2; sg++)
1142 {
1143 double best_sub_sse = DBL_MAX1.7976931348623157e+308;
1144 int best_sub_grid = 0;
1145 const int lane = sg * 4;
1146 double cost[4][8];
1147 for (j = 0; j < 4; j++)
1148 {
1149 int level;
1150 for (level = 0; level < 8; level++)
1151 {
1152 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; })
;
1153 const double d = (double)mag - ay[lane + j];
1154 cost[j][level] = w[lane + j] * d * d;
1155 }
1156 }
1157 int target_code = 0;
1158 uint8_t target_levels[4];
1159 double lower_bound_base = 0;
1160 double lower_bound_ratio = DBL_MAX1.7976931348623157e+308;
1161 for (j = 0; j < 4; j++)
1162 {
1163 int target_level = 0;
1164 int level;
1165 for (level = 1; level < 8; level++)
1166 if (cost[j][level] < cost[j][target_level])
1167 target_level = level;
1168 target_levels[j] = (uint8_t)target_level;
1169 target_code |= target_level << (j * 3);
1170 lower_bound_base += cost[j][target_level];
1171 for (level = 0; level < 8; level++)
1172 if (level != target_level)
1173 {
1174 const int d = level - target_level;
1175 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; })
;
1176 }
1177 }
1178 int candidate;
1179 for (candidate = 0; candidate < CCV_NNC_8I_ROWWISE_IQ3_CANDIDATES; candidate++)
1180 {
1181 const int index = ccv_nnc_8i_rowwise_packed_iq3xxs_candidates[target_code][candidate];
1182 const uint8_t* const levels = ccv_nnc_8i_rowwise_packed_iq3xxs_level[index];
1183 const double sse = cost[0][levels[0]] + cost[1][levels[1]] + cost[2][levels[2]] + cost[3][levels[3]];
1184 if (sse < best_sub_sse || (sse == best_sub_sse && index < best_sub_grid))
1185 {
1186 best_sub_sse = sse;
1187 best_sub_grid = index;
1188 }
1189 }
1190 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]];
1191 int cutoff_distance = 0;
1192 for (j = 0; j < 4; j++)
1193 {
1194 const int d = (int)cutoff_levels[j] - target_levels[j];
1195 cutoff_distance += d * d;
1196 }
1197 const double lower_bound = _ccv_nnc_8i_rowwise_packed_safe_lower_bound(lower_bound_base + nextafter(lower_bound_ratio, 0) * cutoff_distance);
1198 if (!(best_sub_sse < lower_bound))
1199 {
1200 int index;
1201 for (index = 0; index < CCV_NNC_8I_ROWWISE_PACKED_IQ3XXS_GRID_SIZE(256); index++)
1202 {
1203 const uint8_t* const levels = ccv_nnc_8i_rowwise_packed_iq3xxs_level[index];
1204 const double sse = cost[0][levels[0]] + cost[1][levels[1]] + cost[2][levels[2]] + cost[3][levels[3]];
1205 if (sse < best_sub_sse || (sse == best_sub_sse && index < best_sub_grid))
1206 {
1207 best_sub_sse = sse;
1208 best_sub_grid = index;
1209 }
1210 }
1211 }
1212 group_sse += best_sub_sse;
1213 group_grid[sg] = best_sub_grid;
1214 }
1215 if (group_sse < best_sse)
1216 {
1217 best_sse = group_sse;
1218 best_scale = scale;
1219 memcpy(best_grid, group_grid, sizeof(best_grid));
1220 }
1221 }
1222 group->scale = best_scale;
1223 group->signs = signs;
1224 memcpy(group->grid, best_grid, sizeof(best_grid));
1225 memset(group->q8, 0, sizeof(group->q8));
1226 for (j = 0; j < 8; j++)
1227 {
1228 const int sg = j >> 2;
1229 const int lane = j & 3;
1230 const int mag = ccv_nnc_8i_rowwise_packed_iq3xxs_scaled_value[best_scale][best_grid[sg]][lane];
1231 group->q8[j] = (signs & (1u << j)) ? -mag : mag;
1232 }
1233}
1234
1235static void _ccv_nnc_8i_rowwise_packed_quant_group(const int format, const double* const y, const double* const w, ccv_nnc_8i_rowwise_packed_group_t* const group)
1236{
1237 switch (format)
1238 {
1239 case CCV_NNC_QX_8I_ROWWISE_Q5_K:
1240 _ccv_nnc_8i_rowwise_packed_quant_q5(y, w, group);
1241 break;
1242 case CCV_NNC_QX_8I_ROWWISE_Q6_K:
1243 _ccv_nnc_8i_rowwise_packed_quant_q6(y, w, group);
1244 break;
1245 case CCV_NNC_QX_8I_ROWWISE_Q4_K:
1246 _ccv_nnc_8i_rowwise_packed_quant_q4(y, w, group);
1247 break;
1248 case CCV_NNC_QX_8I_ROWWISE_Q3_K:
1249 _ccv_nnc_8i_rowwise_packed_quant_q3(y, w, group);
1250 break;
1251 case CCV_NNC_QX_8I_ROWWISE_Q2_K:
1252 _ccv_nnc_8i_rowwise_packed_quant_q2(y, w, group);
1253 break;
1254 case CCV_NNC_QX_8I_ROWWISE_IQ2_XXS:
1255 _ccv_nnc_8i_rowwise_packed_quant_iq2_xxs(y, w, group);
1256 break;
1257 case CCV_NNC_QX_8I_ROWWISE_IQ2_S:
1258 _ccv_nnc_8i_rowwise_packed_quant_iq2_s(y, w, group);
1259 break;
1260 case CCV_NNC_QX_8I_ROWWISE_IQ2_XS:
1261 _ccv_nnc_8i_rowwise_packed_quant_iq2_xs(y, w, group);
1262 break;
1263 case CCV_NNC_QX_8I_ROWWISE_IQ3_S:
1264 _ccv_nnc_8i_rowwise_packed_quant_iq3_s(y, w, group);
1265 break;
1266 case CCV_NNC_QX_8I_ROWWISE_IQ3_XXS:
1267 _ccv_nnc_8i_rowwise_packed_quant_iq3_xxs(y, w, group);
1268 break;
1269 default:
1270 assert(0)((void) sizeof ((0) ? 1 : 0), __extension__ ({ if (0) ; else __assert_fail
("0", "ccv_nnc_8i_rowwise.c", 1270, __extension__ __PRETTY_FUNCTION__
); }))
;
1271 }
1272}
1273
1274static 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)
1275{
1276 const size_t bit_offset = group_index * ccv_nnc_8i_rowwise_x_group_bits(format);
1277 size_t bit = bit_offset;
1278 int j;
1279 switch (format)
1280 {
1281 case CCV_NNC_QX_8I_ROWWISE_Q5_K:
1282 for (j = 0; j < 16; j++, bit += 5)
1283 _ccv_nnc_8i_rowwise_packed_write_bits(output, bit, (uint32_t)(group->q[j] + 16), 5);
1284 _ccv_nnc_8i_rowwise_packed_write_bits(output, bit, (uint32_t)(group->m - 1), 3);
1285 _ccv_nnc_8i_rowwise_packed_write_bits(output, bit + 3, (uint32_t)(group->b + 16), 5);
1286 break;
1287 case CCV_NNC_QX_8I_ROWWISE_Q6_K:
1288 for (j = 0; j < 8; j++, bit += 6)
1289 _ccv_nnc_8i_rowwise_packed_write_bits(output, bit, (uint32_t)(group->q[j] & 0x3f), 6);
1290 _ccv_nnc_8i_rowwise_packed_write_bits(output, bit, (uint32_t)(group->m - 1), 2);
1291 _ccv_nnc_8i_rowwise_packed_write_bits(output, bit + 2, (uint32_t)(group->b & 3), 2);
1292 break;
1293 case CCV_NNC_QX_8I_ROWWISE_Q4_K:
1294 for (j = 0; j < 16; j++, bit += 4)
1295 _ccv_nnc_8i_rowwise_packed_write_bits(output, bit, (uint32_t)(group->q[j] + 8), 4);
1296 _ccv_nnc_8i_rowwise_packed_write_bits(output, bit, (uint32_t)(group->m - 1), 4);
1297 _ccv_nnc_8i_rowwise_packed_write_bits(output, bit + 4, (uint32_t)(group->b + 8), 4);
1298 break;
1299 case CCV_NNC_QX_8I_ROWWISE_Q3_K:
1300 for (j = 0; j < 16; j++, bit += 3)
1301 _ccv_nnc_8i_rowwise_packed_write_bits(output, bit, (uint32_t)(group->q[j] + 4), 3);
1302 _ccv_nnc_8i_rowwise_packed_write_bits(output, bit, (uint32_t)(group->m - 1), 5);
1303 _ccv_nnc_8i_rowwise_packed_write_bits(output, bit + 5, (uint32_t)(group->b / 2 + 4), 3);
1304 break;
1305 case CCV_NNC_QX_8I_ROWWISE_Q2_K:
1306 for (j = 0; j < 16; j++, bit += 2)
1307 _ccv_nnc_8i_rowwise_packed_write_bits(output, bit, (uint32_t)group->q[j], 2);
1308 _ccv_nnc_8i_rowwise_packed_write_bits(output, bit, (uint32_t)(group->m - 1), 6);
1309 _ccv_nnc_8i_rowwise_packed_write_bits(output, bit + 6, (uint32_t)(group->z >> 3), 4);
1310 break;
1311 case CCV_NNC_QX_8I_ROWWISE_IQ2_S:
1312 _ccv_nnc_8i_rowwise_packed_write_bits(output, bit, (uint32_t)group->grid[0], 10);
1313 _ccv_nnc_8i_rowwise_packed_write_bits(output, bit + 10, (uint32_t)group->grid[1], 10);
1314 _ccv_nnc_8i_rowwise_packed_write_bits(output, bit + 20, group->signs, 16);
1315 _ccv_nnc_8i_rowwise_packed_write_bits(output, bit + 36, (uint32_t)(group->scale - 1), 6);
1316 break;
1317 case CCV_NNC_QX_8I_ROWWISE_IQ2_XS:
1318 _ccv_nnc_8i_rowwise_packed_write_bits(output, bit, (uint32_t)group->grid[0], 9);
1319 _ccv_nnc_8i_rowwise_packed_write_bits(output, bit + 9, group->signs, 8);
1320 _ccv_nnc_8i_rowwise_packed_write_bits(output, bit + 17, (uint32_t)group->scale, 4);
1321 break;
1322 case CCV_NNC_QX_8I_ROWWISE_IQ2_XXS:
1323 for (j = 0; j < 4; j++)
1324 _ccv_nnc_8i_rowwise_packed_write_bits(output, bit + j * 8, (uint32_t)group->grid[j], 8);
1325 _ccv_nnc_8i_rowwise_packed_write_bits(output, bit + 32, group->signs, 28);
1326 _ccv_nnc_8i_rowwise_packed_write_bits(output, bit + 60, (uint32_t)group->scale, 4);
1327 break;
1328 case CCV_NNC_QX_8I_ROWWISE_IQ3_S:
1329 for (j = 0; j < 4; j++)
1330 _ccv_nnc_8i_rowwise_packed_write_bits(output, bit + j * 9, (uint32_t)group->grid[j], 9);
1331 _ccv_nnc_8i_rowwise_packed_write_bits(output, bit + 36, group->signs, 16);
1332 _ccv_nnc_8i_rowwise_packed_write_bits(output, bit + 52, (uint32_t)(group->scale - 1), 4);
1333 break;
1334 case CCV_NNC_QX_8I_ROWWISE_IQ3_XXS:
1335 _ccv_nnc_8i_rowwise_packed_write_bits(output, bit, (uint32_t)group->grid[0], 8);
1336 _ccv_nnc_8i_rowwise_packed_write_bits(output, bit + 8, (uint32_t)group->grid[1], 8);
1337 _ccv_nnc_8i_rowwise_packed_write_bits(output, bit + 16, group->signs, 8);
1338 _ccv_nnc_8i_rowwise_packed_write_bits(output, bit + 24, (uint32_t)(group->scale - 1), 4);
1339 break;
1340 default:
1341 assert(0)((void) sizeof ((0) ? 1 : 0), __extension__ ({ if (0) ; else __assert_fail
("0", "ccv_nnc_8i_rowwise.c", 1341, __extension__ __PRETTY_FUNCTION__
); }))
;
1342 }
1343}
1344
1345static void _ccv_nnc_8i_rowwise_packed_decode_group(const uint8_t* const input, const size_t group_index, const int format, int* const q8)
1346{
1347 static const int q2_xs_scales[16] = {1, 2, 3, 4, 5, 6, 7, 8, 10, 12, 14, 16, 20, 24, 28, 32};
1348 const size_t bit_offset = group_index * ccv_nnc_8i_rowwise_x_group_bits(format);
1349 size_t bit = bit_offset;
1350 int j;
1351 switch (format)
1352 {
1353 case CCV_NNC_QX_8I_ROWWISE_Q5_K: {
1354 int q[16];
1355 for (j = 0; j < 16; j++, bit += 5)
1356 q[j] = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit, 5) - 16;
1357 const int m = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit, 3) + 1;
1358 const int b = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit + 3, 5) - 16;
1359 for (j = 0; j < 16; j++)
1360 q8[j] = q[j] * m + b;
1361 break;
1362 }
1363 case CCV_NNC_QX_8I_ROWWISE_Q6_K: {
1364 int q[8];
1365 for (j = 0; j < 8; j++, bit += 6)
1366 q[j] = _ccv_nnc_8i_rowwise_packed_sign_extend(_ccv_nnc_8i_rowwise_packed_read_bits(input, bit, 6), 6);
1367 const int m = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit, 2) + 1;
1368 const int b = _ccv_nnc_8i_rowwise_packed_sign_extend(_ccv_nnc_8i_rowwise_packed_read_bits(input, bit + 2, 2), 2);
1369 for (j = 0; j < 8; j++)
1370 q8[j] = q[j] * m + b;
1371 break;
1372 }
1373 case CCV_NNC_QX_8I_ROWWISE_Q4_K: {
1374 int q[16];
1375 for (j = 0; j < 16; j++, bit += 4)
1376 q[j] = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit, 4) - 8;
1377 const int m = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit, 4) + 1;
1378 const int b = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit + 4, 4) - 8;
1379 for (j = 0; j < 16; j++)
1380 q8[j] = q[j] * m + b;
1381 break;
1382 }
1383 case CCV_NNC_QX_8I_ROWWISE_Q3_K: {
1384 int q[16];
1385 for (j = 0; j < 16; j++, bit += 3)
1386 q[j] = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit, 3) - 4;
1387 const int m = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit, 5) + 1;
1388 const int b = ((int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit + 5, 3) - 4) << 1;
1389 for (j = 0; j < 16; j++)
1390 q8[j] = q[j] * m + b;
1391 break;
1392 }
1393 case CCV_NNC_QX_8I_ROWWISE_Q2_K: {
1394 int q[16];
1395 for (j = 0; j < 16; j++, bit += 2)
1396 q[j] = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit, 2);
1397 const int m = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit, 6) + 1;
1398 const int z = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit + 6, 4) << 3;
1399 for (j = 0; j < 16; j++)
1400 q8[j] = q[j] * m - z;
1401 break;
1402 }
1403 case CCV_NNC_QX_8I_ROWWISE_IQ2_S: {
1404 const int grid0 = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit, 10);
1405 const int grid1 = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit + 10, 10);
1406 const uint32_t signs = _ccv_nnc_8i_rowwise_packed_read_bits(input, bit + 20, 16);
1407 const int scale = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit + 36, 6) + 1;
1408 for (j = 0; j < 8; j++)
1409 {
1410 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; })
;
1411 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; })
;
1412 q8[j] = (signs & (1u << j)) ? -mag0 : mag0;
1413 q8[8 + j] = (signs & (1u << (8 + j))) ? -mag1 : mag1;
1414 }
1415 break;
1416 }
1417 case CCV_NNC_QX_8I_ROWWISE_IQ2_XS: {
1418 const int grid0 = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit, 9);
1419 const uint32_t signs = _ccv_nnc_8i_rowwise_packed_read_bits(input, bit + 9, 8);
1420 const int scale = q2_xs_scales[_ccv_nnc_8i_rowwise_packed_read_bits(input, bit + 17, 4)];
1421 for (j = 0; j < 8; j++)
1422 {
1423 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; })
;
1424 q8[j] = (signs & (1u << j)) ? -mag : mag;
1425 }
1426 break;
1427 }
1428 case CCV_NNC_QX_8I_ROWWISE_IQ2_XXS: {
1429 int grid[4];
1430 for (j = 0; j < 4; j++)
1431 grid[j] = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit + j * 8, 8);
1432 const uint32_t sign_codes = _ccv_nnc_8i_rowwise_packed_read_bits(input, bit + 32, 28);
1433 const int scale = ccv_nnc_8i_rowwise_packed_iq2xxs_scales[_ccv_nnc_8i_rowwise_packed_read_bits(input, bit + 60, 4)];
1434 int sg;
1435 for (sg = 0; sg < 4; sg++)
1436 {
1437 const uint8_t signs = ccv_nnc_8i_rowwise_packed_iq2xxs_ksigns[(sign_codes >> (sg * 7)) & 0x7f];
1438 for (j = 0; j < 8; j++)
1439 {
1440 const int lane = sg * 8 + j;
1441 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; })
;
1442 q8[lane] = (signs & (1u << j)) ? -mag : mag;
1443 }
1444 }
1445 break;
1446 }
1447 case CCV_NNC_QX_8I_ROWWISE_IQ3_S: {
1448 int grid[4];
1449 for (j = 0; j < 4; j++)
1450 grid[j] = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit + j * 9, 9);
1451 const uint32_t signs = _ccv_nnc_8i_rowwise_packed_read_bits(input, bit + 36, 16);
1452 const int scale = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit + 52, 4) + 1;
1453 int sg;
1454 for (sg = 0; sg < 4; sg++)
1455 for (j = 0; j < 4; j++)
1456 {
1457 const int lane = sg * 4 + j;
1458 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
; })
;
1459 q8[lane] = (signs & (1u << lane)) ? -mag : mag;
1460 }
1461 break;
1462 }
1463 case CCV_NNC_QX_8I_ROWWISE_IQ3_XXS: {
1464 const int grid0 = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit, 8);
1465 const int grid1 = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit + 8, 8);
1466 const uint32_t signs = _ccv_nnc_8i_rowwise_packed_read_bits(input, bit + 16, 8);
1467 const int scale = (int)_ccv_nnc_8i_rowwise_packed_read_bits(input, bit + 24, 4) + 1;
1468 for (j = 0; j < 4; j++)
1469 {
1470 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; }
)
;
1471 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; }
)
;
1472 q8[j] = (signs & (1u << j)) ? -mag0 : mag0;
1473 q8[4 + j] = (signs & (1u << (4 + j))) ? -mag1 : mag1;
1474 }
1475 break;
1476 }
1477 default:
1478 assert(0)((void) sizeof ((0) ? 1 : 0), __extension__ ({ if (0) ; else __assert_fail
("0", "ccv_nnc_8i_rowwise.c", 1478, __extension__ __PRETTY_FUNCTION__
); }))
;
1479 }
1480}
1481
1482// Regular normalized H256, matching NAInt8MatMul activation staging. This is
1483// not the Sylvester WHT. Transform the existing floating row before fitting scales.
1484static void _ccv_nnc_8i_rowwise_hadamard_256(double* const row, const size_t row_length)
1485{
1486 size_t base;
1487 for (base = 0; base < row_length; base += 256)
1488 {
1489 int stride;
1490 for (stride = 1; stride < 256; stride *= 4)
1491 {
1492 int i, j;
1493 for (i = 0; i < 256; i += stride * 4)
1494 for (j = 0; j < stride; j++)
1495 {
1496 double* const v = row + base + i + j;
1497 const double a = v[0], b = v[stride], c = v[stride * 2], d = v[stride * 3];
1498 v[0] = a + b + c - d;
1499 v[stride] = a + b - c + d;
1500 v[stride * 2] = a - b + c + d;
1501 v[stride * 3] = -a + b + c + d;
1502 }
1503 }
1504 int i;
1505 for (i = 0; i < 256; i++)
1506 row[base + i] *= 1. / 16.;
1507 }
1508}
1509
1510CCV_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, void* output, const size_t output_length)
1511{
1512 if (row_length == 0 || input_length % row_length != 0 ||
1
Assuming 'row_length' is not equal to 0
2
Assuming the condition is false
1513 ((format & CCV_NNC_QX_8I_ROWWISE_HADAMARD_256) && row_length % 256 != 0))
3
Assuming the condition is false
1514 return 0;
1515 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", 1515, __extension__ __PRETTY_FUNCTION__
); }))
;
4
Assuming 'datatype' is not equal to CCV_16F
5
Assuming 'datatype' is not equal to CCV_16BF
6
Assuming 'datatype' is not equal to CCV_32F
7
Assuming 'datatype' is equal to CCV_64F
8
Taking true branch
1516 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", 1516, __extension__ __PRETTY_FUNCTION__
); }))
;
9
Assuming 'memory_type' is equal to CCV_TENSOR_CPU_MEMORY
10
Taking true branch
1517 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", 1517, __extension__ __PRETTY_FUNCTION__
); }))
;
11
Taking true branch
1518 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", 1518
, __extension__ __PRETTY_FUNCTION__); }))
;
12
Taking true branch
1519 const int codec = format & CCV_NNC_QX_8I_ROWWISE_FORMAT_MASK;
1520 const size_t row_count = input_length / row_length;
1521 if (!_ccv_nnc_8i_rowwise_imatrix_is_valid(imatrix, imatrix_length, row_length, row_count))
13
Taking false branch
1522 return 0;
1523 const size_t group_size = ccv_nnc_8i_rowwise_x_group_size(format);
1524 const int group_bits = ccv_nnc_8i_rowwise_x_group_bits(format);
1525 const size_t groups_per_row = (row_length + group_size - 1) / group_size;
1526 const size_t padded_row_length = groups_per_row * group_size;
1527 const size_t scale_offset = _ccv_nnc_8i_rowwise_packed_scale_offset(format, input_length, row_length);
1528 const size_t output_size = scale_offset + row_count * CCV_GET_DATA_TYPE_SIZE(datatype)_ccv_get_data_type_size[((datatype) & 0xFF000) >> 12
]
;
1529 if (output_length < output_size)
14
Assuming 'output_length' is >= 'output_size'
15
Taking false branch
1530 return 0;
1531 switch (codec)
16
'Default' branch taken. Execution continues on line 1549
1532 {
1533 case CCV_NNC_QX_8I_ROWWISE_IQ2_XXS:
1534 _ccv_nnc_8i_rowwise_packed_iq2xxs_candidates_init();
1535 break;
1536 case CCV_NNC_QX_8I_ROWWISE_IQ2_XS:
1537 _ccv_nnc_8i_rowwise_packed_iq2xs_candidates_init();
1538 break;
1539 case CCV_NNC_QX_8I_ROWWISE_IQ2_S:
1540 _ccv_nnc_8i_rowwise_packed_iq2s_init();
1541 break;
1542 case CCV_NNC_QX_8I_ROWWISE_IQ3_S:
1543 _ccv_nnc_8i_rowwise_packed_iq3s_init();
1544 break;
1545 case CCV_NNC_QX_8I_ROWWISE_IQ3_XXS:
1546 _ccv_nnc_8i_rowwise_packed_iq3xxs_candidates_init();
1547 break;
1548 }
1549 uint8_t* const u8 = (uint8_t*)output;
1550 uint8_t* const scales = u8 + scale_offset;
1551 memset(u8, 0, scale_offset);
1552 const size_t row_bits = groups_per_row * group_bits;
1553 size_t rows_per_chunk;
1554 switch (row_bits & 7)
17
Control jumps to the 'default' case at line 1566
1555 {
1556 case 0:
1557 rows_per_chunk = 1;
1558 break;
1559 case 4:
1560 rows_per_chunk = 2;
1561 break;
1562 case 2:
1563 case 6:
1564 rows_per_chunk = 4;
1565 break;
1566 default:
1567 rows_per_chunk = 8;
1568 break;
18
Execution continues on line 1570
1569 }
1570 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; })
;
19
'?' condition is false
1571 const size_t row_chunks = (row_count + rows_per_chunk - 1) / rows_per_chunk;
1572#ifdef USE_DISPATCH
1573 dispatch_apply(row_chunks, dispatch_get_global_queue(DISPATCH_QUEUE_PRIORITY_DEFAULT, 0), ^(size_t chunk_idx) {
1574#else
1575 parallel_for(chunk_idx, (int)row_chunks){ int chunk_idx; for ((chunk_idx) = 0; (chunk_idx) < ((int
)row_chunks); (chunk_idx)++) {
{
20
Assuming 'chunk_idx' is < 'row_chunks'
21
Loop condition is true. Entering loop body
1576#endif
1577 const size_t chunk_begin = (size_t)chunk_idx * rows_per_chunk;
1578 const size_t chunk_end = ccv_min(chunk_begin + rows_per_chunk, row_count)({ typeof (chunk_begin + rows_per_chunk) _a = (chunk_begin + rows_per_chunk
); typeof (row_count) _b = (row_count); (_a < _b) ? _a : _b
; })
;
22
Assuming '_a' is >= '_b'
23
'?' condition is false
1579 double* const row = (double*)ccmallocmalloc(sizeof(double) * padded_row_length);
24
Storing uninitialized value
1580 double* const weights = (double*)ccmallocmalloc(sizeof(double) * padded_row_length);
1581 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);
1582 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);
1583 size_t i;
1584 for (i = chunk_begin; i < chunk_end; i++)
25
Assuming 'i' is < 'chunk_end'
26
Loop condition is true. Entering loop body
1585 {
1586 const size_t row_start = i * row_length;
1587 const float* const row_imatrix = _ccv_nnc_8i_rowwise_imatrix_for_row(imatrix, imatrix_length, row_length, row_count, i);
1588 _ccv_nnc_8i_rowwise_packed_read_row(input, datatype, row_start, row_length, padded_row_length, row);
27
Calling '_ccv_nnc_8i_rowwise_packed_read_row'
36
Returning from '_ccv_nnc_8i_rowwise_packed_read_row'
1589 if (format & CCV_NNC_QX_8I_ROWWISE_HADAMARD_256)
37
Taking false branch
1590 _ccv_nnc_8i_rowwise_hadamard_256(row, row_length);
1591 double max_abs = 0;
1592 size_t j;
1593 for (j = 0; j < row_length; j++)
38
Loop condition is true. Entering loop body
41
Loop condition is false. Execution continues on line 1598
1594 {
1595 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; })
;
39
Assuming '_a' is <= '_b'
40
'?' condition is false
1596 weights[j] = _ccv_nnc_8i_rowwise_weight(row_imatrix, j);
1597 }
1598 for (; j
41.1
'j' is >= 'padded_row_length'
< padded_row_length; j++)
42
Loop condition is false. Execution continues on line 1600
1599 weights[j] = 0;
1600 double scale = max_abs / 127.;
1601 double best_scale = 0;
1602 double best_sse = DBL_MAX1.7976931348623157e+308;
1603 int has_best = 0;
1604 int k;
1605 for (k = 0; k < CCV_NNC_8I_ROWWISE_X_REFINEMENT_STEPS; k++)
43
Loop condition is true. Entering loop body
1606 {
1607 const double stored_scale = _ccv_nnc_8i_rowwise_packed_stored_scale(scale, datatype);
1608 if (!(stored_scale > 0))
44
Assuming 'stored_scale' is <= 0
45
Taking true branch
1609 break;
1610 double sse = 0;
1611 double sum_qx = 0;
1612 double sum_qq = 0;
1613 size_t g;
1614 for (g = 0; g < groups_per_row; g++)
1615 {
1616 double y[32] = {0};
1617 double w[32] = {0};
1618 for (j = 0; j < group_size; j++)
1619 {
1620 y[j] = row[g * group_size + j] / stored_scale;
1621 w[j] = weights[g * group_size + j];
1622 }
1623 ccv_nnc_8i_rowwise_packed_group_t group;
1624 _ccv_nnc_8i_rowwise_packed_quant_group(codec, y, w, &group);
1625 groups[g] = group;
1626 const size_t group_start = g * group_size;
1627 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; })
;
1628 for (j = group_start; j < group_end; j++)
1629 {
1630 const int q8 = group.q8[j - group_start];
1631 const double d = row[j] - stored_scale * q8;
1632 sse += weights[j] * d * d;
1633 sum_qx += weights[j] * q8 * row[j];
1634 sum_qq += weights[j] * q8 * q8;
1635 }
1636 }
1637 if (sse < best_sse)
1638 {
1639 best_sse = sse;
1640 best_scale = stored_scale;
1641 has_best = 1;
1642 memcpy(best_groups, groups, sizeof(ccv_nnc_8i_rowwise_packed_group_t) * groups_per_row);
1643 }
1644 if (!(sum_qq > 0) || !(sum_qx > 0))
1645 break;
1646 const double next_scale = sum_qx / sum_qq;
1647 if (_ccv_nnc_8i_rowwise_packed_stored_scale(next_scale, datatype) == stored_scale)
1648 break;
1649 scale = next_scale;
1650 }
1651 _ccv_nnc_8i_rowwise_packed_store_scale(scales, datatype, i, best_scale);
1652 size_t g;
1653 if (has_best
45.1
'has_best' is 0
)
46
Taking false branch
1654 {
1655 for (g = 0; g < groups_per_row; g++)
1656 _ccv_nnc_8i_rowwise_packed_pack_group(u8, i * groups_per_row + g, codec, best_groups + g);
1657 } else {
1658 for (g = 0; g < groups_per_row; g++)
47
Assuming 'g' is < 'groups_per_row'
48
Loop condition is true. Entering loop body
1659 {
1660 double y[32] = {0};
1661 double w[32] = {0};
1662 for (j = 0; j < group_size; j++)
49
Assuming 'j' is < 'group_size'
50
Loop condition is true. Entering loop body
51
Assuming 'j' is < 'group_size'
52
Loop condition is true. Entering loop body
1663 {
1664 y[j] = row[g * group_size + j];
53
Assigned value is garbage or undefined
1665 w[j] = weights[g * group_size + j];
1666 }
1667 ccv_nnc_8i_rowwise_packed_group_t group;
1668 _ccv_nnc_8i_rowwise_packed_quant_group(codec, y, w, &group);
1669 _ccv_nnc_8i_rowwise_packed_pack_group(u8, i * groups_per_row + g, codec, &group);
1670 }
1671 }
1672 }
1673 ccfreefree(best_groups);
1674 ccfreefree(groups);
1675 ccfreefree(weights);
1676 ccfreefree(row);
1677#ifdef USE_DISPATCH
1678 });
1679#else
1680 } parallel_endfor} }
1681#endif
1682 return output_size;
1683}
1684
1685void 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)
1686{
1687 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", 1687, __extension__ __PRETTY_FUNCTION__
); }))
;
1688 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", 1688, __extension__ __PRETTY_FUNCTION__
); }))
;
1689 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", 1689, __extension__ __PRETTY_FUNCTION__
); }))
;
1690 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", 1690
, __extension__ __PRETTY_FUNCTION__); }))
;
1691 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", 1691, __extension__ __PRETTY_FUNCTION__
); }))
;
1692 if (memory_type != CCV_TENSOR_CPU_MEMORY)
1693 {
1694#ifdef HAVE_CUDA1
1695 ccv_nnc_compat_dequantize_8i_rowwise_x_fp(input, datatype, input_length, row_length, format, output, output_length, 0);
1696#elif defined(HAVE_MPS)
1697 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", 1697, __extension__ __PRETTY_FUNCTION__
); }))
;
1698 ccv_nnc_mps_dequantize_8i_rowwise_x(input, datatype, input_length, row_length, format, output, output_length, 0);
1699#else
1700 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", 1700, __extension__ __PRETTY_FUNCTION__
); }))
;
1701#endif
1702 return;
1703 }
1704 const size_t row_count = output_length / row_length;
1705 const size_t group_size = ccv_nnc_8i_rowwise_x_group_size(format);
1706 const size_t groups_per_row = (row_length + group_size - 1) / group_size;
1707 const size_t scale_offset = _ccv_nnc_8i_rowwise_packed_scale_offset(format, output_length, row_length);
1708 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", 1708, __extension__ __PRETTY_FUNCTION__
); }))
;
1709 const uint8_t* const u8 = (const uint8_t*)input;
1710 const uint8_t* const scales = u8 + scale_offset;
1711 parallel_for(i, (int)row_count){ int i; for ((i) = 0; (i) < ((int)row_count); (i)++) { {
1712 const double scale = _ccv_nnc_8i_rowwise_packed_load_scale(scales, datatype, i);
1713 if (format & CCV_NNC_QX_8I_ROWWISE_HADAMARD_256)
1714 {
1715 // Transform decoded integers before scaling / rounding to the destination
1716 // precision. H256 is its own inverse and acts on independent blocks.
1717 double block[256];
1718 size_t base;
1719 for (base = 0; base < row_length; base += 256)
1720 {
1721 size_t g;
1722 for (g = 0; g < 256 / group_size; g++)
1723 {
1724 int q8[32] = {0};
1725 _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);
1726 size_t j;
1727 for (j = 0; j < group_size; j++)
1728 block[g * group_size + j] = q8[j];
1729 }
1730 _ccv_nnc_8i_rowwise_hadamard_256(block, 256);
1731 size_t j;
1732 for (j = 0; j < 256; j++)
1733 _ccv_nnc_8i_rowwise_packed_write_value(output, datatype, (size_t)i * row_length + base + j, scale * block[j]);
1734 }
1735 } else {
1736 size_t g;
1737 for (g = 0; g < groups_per_row; g++)
1738 {
1739 int q8[32] = {0};
1740 _ccv_nnc_8i_rowwise_packed_decode_group(u8, (size_t)i * groups_per_row + g, format, q8);
1741 size_t j;
1742 for (j = 0; j < group_size; j++)
1743 {
1744 const size_t col = g * group_size + j;
1745 if (col < row_length)
1746 _ccv_nnc_8i_rowwise_packed_write_value(output, datatype, (size_t)i * row_length + col, scale * q8[j]);
1747 }
1748 }
1749 }
1750 } parallel_endfor} }
1751}
1752
1753static inline int _ccv_nnc_8i_rowwise_quantize(const double v, const double inv_scale)
1754{
1755 const int q = (int)lrint(v * inv_scale);
1756 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); }
)
;
1757}
1758
1759static 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)
1760{
1761 size_t j;
1762 double max_abs = 0;
1763 for (j = 0; j < row_length; j++)
1764 {
1765 float v;
1766 ccv_half_precision_to_float(row + j, &v, 1);
1767 max_abs = ccv_max(max_abs, fabs(v))({ typeof (max_abs) _a = (max_abs); typeof (fabs(v)) _b = (fabs
(v)); (_a > _b) ? _a : _b; })
;
1768 }
1769 if (max_abs == 0)
1770 {
1771 memset(q, 0, row_length);
1772 return 0;
1773 }
1774 double scale = max_abs / 127.;
1775 float best_scale = 0;
1776 double best_sse = DBL_MAX1.7976931348623157e+308;
1777 int k;
1778 for (k = 0; k < 8; k++)
1779 {
1780 // Round with the scale that will actually be stored, then refit scale by least squares.
1781 const float scale_f = (float)scale;
1782 uint16_t scale_h;
1783 float stored_scale;
1784 ccv_float_to_half_precision(&scale_f, &scale_h, 1);
1785 ccv_half_precision_to_float(&scale_h, &stored_scale, 1);
1786 if (!(stored_scale > 0))
1787 break;
1788 const double inv_scale = 1. / stored_scale;
1789 double sum_qx = 0;
1790 double sum_qq = 0;
1791 double sse = 0;
1792 for (j = 0; j < row_length; j++)
1793 {
1794 const double w = _ccv_nnc_8i_rowwise_weight(imatrix, j);
1795 float v_f;
1796 ccv_half_precision_to_float(row + j, &v_f, 1);
1797 const double v = v_f;
1798 const int qj = _ccv_nnc_8i_rowwise_quantize(v, inv_scale);
1799 const double d = v - stored_scale * qj;
1800 sse += w * d * d;
1801 sum_qx += w * qj * v;
1802 sum_qq += w * qj * qj;
1803 }
1804 if (sse < best_sse)
1805 {
1806 best_sse = sse;
1807 best_scale = stored_scale;
1808 }
1809 if (!(sum_qq > 0) || !(sum_qx > 0))
1810 break;
1811 const double next_scale = sum_qx / sum_qq;
1812 const float next_scale_f = (float)next_scale;
1813 uint16_t next_scale_h;
1814 float next_stored_scale;
1815 ccv_float_to_half_precision(&next_scale_f, &next_scale_h, 1);
1816 ccv_half_precision_to_float(&next_scale_h, &next_stored_scale, 1);
1817 if (next_stored_scale == stored_scale)
1818 break;
1819 scale = next_scale;
1820 }
1821 if (!(best_scale > 0))
1822 {
1823 memset(q, 0, row_length);
1824 return 0;
1825 }
1826 const double inv_scale = 1. / best_scale;
1827 for (j = 0; j < row_length; j++)
1828 {
1829 float v;
1830 ccv_half_precision_to_float(row + j, &v, 1);
1831 q[j] = (int8_t)_ccv_nnc_8i_rowwise_quantize(v, inv_scale);
1832 }
1833 return best_scale;
1834}
1835
1836static 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)
1837{
1838 size_t j;
1839 double max_abs = 0;
1840 for (j = 0; j < row_length; j++)
1841 {
1842 float v;
1843 ccv_bfloat_to_float(row + j, &v, 1);
1844 max_abs = ccv_max(max_abs, fabs(v))({ typeof (max_abs) _a = (max_abs); typeof (fabs(v)) _b = (fabs
(v)); (_a > _b) ? _a : _b; })
;
1845 }
1846 if (max_abs == 0)
1847 {
1848 memset(q, 0, row_length);
1849 return 0;
1850 }
1851 double scale = max_abs / 127.;
1852 float best_scale = 0;
1853 double best_sse = DBL_MAX1.7976931348623157e+308;
1854 int k;
1855 for (k = 0; k < 8; k++)
1856 {
1857 const float scale_f = (float)scale;
1858 uint16_t scale_bf;
1859 float stored_scale;
1860 ccv_float_to_bfloat(&scale_f, &scale_bf, 1);
1861 ccv_bfloat_to_float(&scale_bf, &stored_scale, 1);
1862 if (!(stored_scale > 0))
1863 break;
1864 const double inv_scale = 1. / stored_scale;
1865 double sum_qx = 0;
1866 double sum_qq = 0;
1867 double sse = 0;
1868 for (j = 0; j < row_length; j++)
1869 {
1870 const double w = _ccv_nnc_8i_rowwise_weight(imatrix, j);
1871 float v_f;
1872 ccv_bfloat_to_float(row + j, &v_f, 1);
1873 const double v = v_f;
1874 const int qj = _ccv_nnc_8i_rowwise_quantize(v, inv_scale);
1875 const double d = v - stored_scale * qj;
1876 sse += w * d * d;
1877 sum_qx += w * qj * v;
1878 sum_qq += w * qj * qj;
1879 }
1880 if (sse < best_sse)
1881 {
1882 best_sse = sse;
1883 best_scale = stored_scale;
1884 }
1885 if (!(sum_qq > 0) || !(sum_qx > 0))
1886 break;
1887 const double next_scale = sum_qx / sum_qq;
1888 const float next_scale_f = (float)next_scale;
1889 uint16_t next_scale_bf;
1890 float next_stored_scale;
1891 ccv_float_to_bfloat(&next_scale_f, &next_scale_bf, 1);
1892 ccv_bfloat_to_float(&next_scale_bf, &next_stored_scale, 1);
1893 if (next_stored_scale == stored_scale)
1894 break;
1895 scale = next_scale;
1896 }
1897 if (!(best_scale > 0))
1898 {
1899 memset(q, 0, row_length);
1900 return 0;
1901 }
1902 const double inv_scale = 1. / best_scale;
1903 for (j = 0; j < row_length; j++)
1904 {
1905 float v;
1906 ccv_bfloat_to_float(row + j, &v, 1);
1907 q[j] = (int8_t)_ccv_nnc_8i_rowwise_quantize(v, inv_scale);
1908 }
1909 return best_scale;
1910}
1911
1912static float _ccv_nnc_quantize_8i_rowwise_32f(const float* const row, const size_t row_length, const float* const imatrix, int8_t* const q)
1913{
1914 size_t j;
1915 double max_abs = 0;
1916 for (j = 0; j < row_length; j++)
1917 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; })
;
1918 if (max_abs == 0)
1919 {
1920 memset(q, 0, row_length);
1921 return 0;
1922 }
1923 double scale = max_abs / 127.;
1924 float best_scale = 0;
1925 double best_sse = DBL_MAX1.7976931348623157e+308;
1926 int k;
1927 for (k = 0; k < 8; k++)
1928 {
1929 const float stored_scale = (float)scale;
1930 if (!(stored_scale > 0))
1931 break;
1932 const double inv_scale = 1. / stored_scale;
1933 double sum_qx = 0;
1934 double sum_qq = 0;
1935 double sse = 0;
1936 for (j = 0; j < row_length; j++)
1937 {
1938 const double w = _ccv_nnc_8i_rowwise_weight(imatrix, j);
1939 const double v = row[j];
1940 const int qj = _ccv_nnc_8i_rowwise_quantize(v, inv_scale);
1941 const double d = v - stored_scale * qj;
1942 sse += w * d * d;
1943 sum_qx += w * qj * v;
1944 sum_qq += w * qj * qj;
1945 }
1946 if (sse < best_sse)
1947 {
1948 best_sse = sse;
1949 best_scale = stored_scale;
1950 }
1951 if (!(sum_qq > 0) || !(sum_qx > 0))
1952 break;
1953 const double next_scale = sum_qx / sum_qq;
1954 if ((float)next_scale == stored_scale)
1955 break;
1956 scale = next_scale;
1957 }
1958 if (!(best_scale > 0))
1959 {
1960 memset(q, 0, row_length);
1961 return 0;
1962 }
1963 const double inv_scale = 1. / best_scale;
1964 for (j = 0; j < row_length; j++)
1965 q[j] = (int8_t)_ccv_nnc_8i_rowwise_quantize(row[j], inv_scale);
1966 return best_scale;
1967}
1968
1969static double _ccv_nnc_quantize_8i_rowwise_64f(const double* const row, const size_t row_length, const float* const imatrix, int8_t* const q)
1970{
1971 size_t j;
1972 double max_abs = 0;
1973 for (j = 0; j < row_length; j++)
1974 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; })
;
1975 if (max_abs == 0)
1976 {
1977 memset(q, 0, row_length);
1978 return 0;
1979 }
1980 double scale = max_abs / 127.;
1981 double best_scale = 0;
1982 double best_sse = DBL_MAX1.7976931348623157e+308;
1983 int k;
1984 for (k = 0; k < 8; k++)
1985 {
1986 const double stored_scale = scale;
1987 if (!(stored_scale > 0))
1988 break;
1989 const double inv_scale = 1. / stored_scale;
1990 double sum_qx = 0;
1991 double sum_qq = 0;
1992 double sse = 0;
1993 for (j = 0; j < row_length; j++)
1994 {
1995 const double w = _ccv_nnc_8i_rowwise_weight(imatrix, j);
1996 const double v = row[j];
1997 const int qj = _ccv_nnc_8i_rowwise_quantize(v, inv_scale);
1998 const double d = v - stored_scale * qj;
1999 sse += w * d * d;
2000 sum_qx += w * qj * v;
2001 sum_qq += w * qj * qj;
2002 }
2003 if (sse < best_sse)
2004 {
2005 best_sse = sse;
2006 best_scale = stored_scale;
2007 }
2008 if (!(sum_qq > 0) || !(sum_qx > 0))
2009 break;
2010 const double next_scale = sum_qx / sum_qq;
2011 if (next_scale == stored_scale)
2012 break;
2013 scale = next_scale;
2014 }
2015 if (!(best_scale > 0))
2016 {
2017 memset(q, 0, row_length);
2018 return 0;
2019 }
2020 const double inv_scale = 1. / best_scale;
2021 for (j = 0; j < row_length; j++)
2022 q[j] = (int8_t)_ccv_nnc_8i_rowwise_quantize(row[j], inv_scale);
2023 return best_scale;
2024}
2025
2026CCV_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)
2027{
2028 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", 2028, __extension__ __PRETTY_FUNCTION__
); }))
;
2029 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", 2029, __extension__ __PRETTY_FUNCTION__
); }))
;
2030 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", 2030, __extension__ __PRETTY_FUNCTION__
); }))
;
2031 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", 2031
, __extension__ __PRETTY_FUNCTION__); }))
;
2032 const size_t row_count = input_length / row_length;
2033 if (!_ccv_nnc_8i_rowwise_imatrix_is_valid(imatrix, imatrix_length, row_length, row_count))
2034 return 0;
2035 const size_t scale_offset = (input_length + 127) & -128;
2036 const size_t scale_size = row_count * CCV_GET_DATA_TYPE_SIZE(datatype)_ccv_get_data_type_size[((datatype) & 0xFF000) >> 12
]
;
2037 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", 2037, __extension__ __PRETTY_FUNCTION__
); }))
;
2038 int8_t* const q = (int8_t*)output;
2039 uint8_t* const u8 = (uint8_t*)output;
2040 if (datatype == CCV_16F)
2041 {
2042 const uint16_t* const f16 = (const uint16_t*)input;
2043 uint16_t* const scales = (uint16_t*)(u8 + scale_offset);
2044 parallel_for(i, (int)row_count){ int i; for ((i) = 0; (i) < ((int)row_count); (i)++) { {
2045 const size_t row_start = (size_t)i * row_length;
2046 const float* const row_imatrix = _ccv_nnc_8i_rowwise_imatrix_for_row(imatrix, imatrix_length, row_length, row_count, (size_t)i);
2047 const float scale_f = _ccv_nnc_quantize_8i_rowwise_16f(f16 + row_start, row_length, row_imatrix, q + row_start);
2048 ccv_float_to_half_precision(&scale_f, scales + i, 1);
2049 } parallel_endfor} }
2050 } else if (datatype == CCV_16BF) {
2051 const uint16_t* const bf16 = (const uint16_t*)input;
2052 uint16_t* const scales = (uint16_t*)(u8 + scale_offset);
2053 parallel_for(i, (int)row_count){ int i; for ((i) = 0; (i) < ((int)row_count); (i)++) { {
2054 const size_t row_start = (size_t)i * row_length;
2055 const float* const row_imatrix = _ccv_nnc_8i_rowwise_imatrix_for_row(imatrix, imatrix_length, row_length, row_count, (size_t)i);
2056 const float scale_f = _ccv_nnc_quantize_8i_rowwise_16bf(bf16 + row_start, row_length, row_imatrix, q + row_start);
2057 ccv_float_to_bfloat(&scale_f, scales + i, 1);
2058 } parallel_endfor} }
2059 } else if (datatype == CCV_32F) {
2060 const float* const f32 = (const float*)input;
2061 float* const scales = (float*)(u8 + scale_offset);
2062 parallel_for(i, (int)row_count){ int i; for ((i) = 0; (i) < ((int)row_count); (i)++) { {
2063 const size_t row_start = (size_t)i * row_length;
2064 const float* const row_imatrix = _ccv_nnc_8i_rowwise_imatrix_for_row(imatrix, imatrix_length, row_length, row_count, (size_t)i);
2065 scales[i] = _ccv_nnc_quantize_8i_rowwise_32f(f32 + row_start, row_length, row_imatrix, q + row_start);
2066 } parallel_endfor} }
2067 } else {
2068 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", 2068, __extension__ __PRETTY_FUNCTION__
); }))
;
2069 const double* const f64 = (const double*)input;
2070 double* const scales = (double*)(u8 + scale_offset);
2071 parallel_for(i, (int)row_count){ int i; for ((i) = 0; (i) < ((int)row_count); (i)++) { {
2072 const size_t row_start = (size_t)i * row_length;
2073 const float* const row_imatrix = _ccv_nnc_8i_rowwise_imatrix_for_row(imatrix, imatrix_length, row_length, row_count, (size_t)i);
2074 scales[i] = _ccv_nnc_quantize_8i_rowwise_64f(f64 + row_start, row_length, row_imatrix, q + row_start);
2075 } parallel_endfor} }
2076 }
2077 return scale_offset + scale_size;
2078}
2079
2080void 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)
2081{
2082 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", 2082, __extension__ __PRETTY_FUNCTION__
); }))
;
2083 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", 2083, __extension__ __PRETTY_FUNCTION__
); }))
;
2084 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", 2084, __extension__ __PRETTY_FUNCTION__
); }))
;
2085 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", 2085
, __extension__ __PRETTY_FUNCTION__); }))
;
2086 if (memory_type != CCV_TENSOR_CPU_MEMORY)
2087 {
2088#ifdef HAVE_CUDA1
2089 ccv_nnc_compat_dequantize_8i_rowwise(input, datatype, input_length, row_length, output, output_length, 0);
2090#elif defined(HAVE_MPS)
2091 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", 2091, __extension__ __PRETTY_FUNCTION__
); }))
;
2092 ccv_nnc_mps_dequantize_8i_rowwise(input, datatype, input_length, row_length, output, output_length, 0);
2093#else
2094 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", 2094, __extension__ __PRETTY_FUNCTION__
); }))
;
2095#endif
2096 return;
2097 }
2098 const size_t row_count = output_length / row_length;
2099 const size_t scale_offset = (output_length + 127) & -128;
2100 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", 2100, __extension__ __PRETTY_FUNCTION__
); }))
;
2101 const int8_t* const q = (const int8_t*)input;
2102 const uint8_t* const u8 = (const uint8_t*)input;
2103 if (datatype == CCV_16F)
2104 {
2105 uint16_t* const f16 = (uint16_t*)output;
2106 const uint16_t* const scales = (const uint16_t*)(u8 + scale_offset);
2107 parallel_for(i, (int)row_count){ int i; for ((i) = 0; (i) < ((int)row_count); (i)++) { {
2108 const size_t row_start = (size_t)i * row_length;
2109 float scale_f;
2110 ccv_half_precision_to_float(scales + i, &scale_f, 1);
2111 size_t j;
2112 for (j = 0; j < row_length; j++)
2113 {
2114 const float v = q[row_start + j] * scale_f;
2115 ccv_float_to_half_precision(&v, f16 + row_start + j, 1);
2116 }
2117 } parallel_endfor} }
2118 } else if (datatype == CCV_16BF) {
2119 uint16_t* const bf16 = (uint16_t*)output;
2120 const uint16_t* const scales = (const uint16_t*)(u8 + scale_offset);
2121 parallel_for(i, (int)row_count){ int i; for ((i) = 0; (i) < ((int)row_count); (i)++) { {
2122 const size_t row_start = (size_t)i * row_length;
2123 float scale_f;
2124 ccv_bfloat_to_float(scales + i, &scale_f, 1);
2125 size_t j;
2126 for (j = 0; j < row_length; j++)
2127 {
2128 const float v = q[row_start + j] * scale_f;
2129 ccv_float_to_bfloat(&v, bf16 + row_start + j, 1);
2130 }
2131 } parallel_endfor} }
2132 } else if (datatype == CCV_32F) {
2133 float* const f32 = (float*)output;
2134 const float* const scales = (const float*)(u8 + scale_offset);
2135 parallel_for(i, (int)row_count){ int i; for ((i) = 0; (i) < ((int)row_count); (i)++) { {
2136 const size_t row_start = (size_t)i * row_length;
2137 const float scale = scales[i];
2138 size_t j;
2139 for (j = 0; j < row_length; j++)
2140 f32[row_start + j] = q[row_start + j] * scale;
2141 } parallel_endfor} }
2142 } else {
2143 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", 2143, __extension__ __PRETTY_FUNCTION__
); }))
;
2144 double* const f64 = (double*)output;
2145 const double* const scales = (const double*)(u8 + scale_offset);
2146 parallel_for(i, (int)row_count){ int i; for ((i) = 0; (i) < ((int)row_count); (i)++) { {
2147 const size_t row_start = (size_t)i * row_length;
2148 const double scale = scales[i];
2149 size_t j;
2150 for (j = 0; j < row_length; j++)
2151 f64[row_start + j] = q[row_start + j] * scale;
2152 } parallel_endfor} }
2153 }
2154}