mirror of
https://github.com/ggerganov/llama.cpp.git
synced 2024-12-27 22:59:24 +01:00
ae8de6d50a
* ggml : build backends as libraries --------- Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com> Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> Co-authored-by: R0CKSTAR <xiaodong.ye@mthreads.com>
5248 lines
209 KiB
C
5248 lines
209 KiB
C
#define GGML_COMMON_IMPL_C
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#include "ggml-common.h"
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#include "ggml-quants.h"
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#include "ggml-impl.h"
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#include "ggml-cpu/ggml-cpu-impl.h"
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#include "ggml-cpu.h"
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#include <math.h>
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#include <string.h>
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#include <assert.h>
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#include <float.h>
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#include <stdlib.h> // for qsort
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#include <stdio.h> // for GGML_ASSERT
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#define GROUP_MAX_EPS 1e-15f
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#define GROUP_MAX_EPS_IQ3_XXS 1e-8f
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#define GROUP_MAX_EPS_IQ2_S 1e-8f
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#define GROUP_MAX_EPS_IQ1_M 1e-7f
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#define GROUP_MAX_EPS_IQ1_S 1e-12f
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#if defined(_MSC_VER)
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// disable "possible loss of data" to avoid warnings for hundreds of casts
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// we should just be careful :)
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#pragma warning(disable: 4244 4267)
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#endif
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#define UNUSED GGML_UNUSED
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// reference implementation for deterministic creation of model files
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void quantize_row_q4_0_ref(const float * restrict x, block_q4_0 * restrict y, int64_t k) {
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static const int qk = QK4_0;
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assert(k % qk == 0);
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const int nb = k / qk;
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for (int i = 0; i < nb; i++) {
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float amax = 0.0f; // absolute max
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float max = 0.0f;
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for (int j = 0; j < qk; j++) {
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const float v = x[i*qk + j];
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if (amax < fabsf(v)) {
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amax = fabsf(v);
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max = v;
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}
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}
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const float d = max / -8;
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const float id = d ? 1.0f/d : 0.0f;
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y[i].d = GGML_FP32_TO_FP16(d);
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for (int j = 0; j < qk/2; ++j) {
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const float x0 = x[i*qk + 0 + j]*id;
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const float x1 = x[i*qk + qk/2 + j]*id;
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const uint8_t xi0 = MIN(15, (int8_t)(x0 + 8.5f));
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const uint8_t xi1 = MIN(15, (int8_t)(x1 + 8.5f));
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y[i].qs[j] = xi0;
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y[i].qs[j] |= xi1 << 4;
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}
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}
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}
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void quantize_row_q4_1_ref(const float * restrict x, block_q4_1 * restrict y, int64_t k) {
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const int qk = QK4_1;
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assert(k % qk == 0);
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const int nb = k / qk;
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for (int i = 0; i < nb; i++) {
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float min = FLT_MAX;
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float max = -FLT_MAX;
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for (int j = 0; j < qk; j++) {
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const float v = x[i*qk + j];
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if (v < min) min = v;
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if (v > max) max = v;
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}
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const float d = (max - min) / ((1 << 4) - 1);
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const float id = d ? 1.0f/d : 0.0f;
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y[i].d = GGML_FP32_TO_FP16(d);
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y[i].m = GGML_FP32_TO_FP16(min);
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for (int j = 0; j < qk/2; ++j) {
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const float x0 = (x[i*qk + 0 + j] - min)*id;
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const float x1 = (x[i*qk + qk/2 + j] - min)*id;
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const uint8_t xi0 = MIN(15, (int8_t)(x0 + 0.5f));
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const uint8_t xi1 = MIN(15, (int8_t)(x1 + 0.5f));
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y[i].qs[j] = xi0;
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y[i].qs[j] |= xi1 << 4;
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}
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}
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}
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void quantize_row_q5_0_ref(const float * restrict x, block_q5_0 * restrict y, int64_t k) {
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static const int qk = QK5_0;
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assert(k % qk == 0);
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const int nb = k / qk;
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for (int i = 0; i < nb; i++) {
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float amax = 0.0f; // absolute max
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float max = 0.0f;
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for (int j = 0; j < qk; j++) {
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const float v = x[i*qk + j];
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if (amax < fabsf(v)) {
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amax = fabsf(v);
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max = v;
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}
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}
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const float d = max / -16;
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const float id = d ? 1.0f/d : 0.0f;
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y[i].d = GGML_FP32_TO_FP16(d);
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uint32_t qh = 0;
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for (int j = 0; j < qk/2; ++j) {
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const float x0 = x[i*qk + 0 + j]*id;
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const float x1 = x[i*qk + qk/2 + j]*id;
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const uint8_t xi0 = MIN(31, (int8_t)(x0 + 16.5f));
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const uint8_t xi1 = MIN(31, (int8_t)(x1 + 16.5f));
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y[i].qs[j] = (xi0 & 0x0F) | ((xi1 & 0x0F) << 4);
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// get the 5-th bit and store it in qh at the right position
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qh |= ((xi0 & 0x10u) >> 4) << (j + 0);
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qh |= ((xi1 & 0x10u) >> 4) << (j + qk/2);
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}
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memcpy(&y[i].qh, &qh, sizeof(qh));
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}
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}
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void quantize_row_q5_1_ref(const float * restrict x, block_q5_1 * restrict y, int64_t k) {
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const int qk = QK5_1;
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assert(k % qk == 0);
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const int nb = k / qk;
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for (int i = 0; i < nb; i++) {
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float min = FLT_MAX;
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float max = -FLT_MAX;
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for (int j = 0; j < qk; j++) {
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const float v = x[i*qk + j];
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if (v < min) min = v;
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if (v > max) max = v;
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}
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const float d = (max - min) / ((1 << 5) - 1);
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const float id = d ? 1.0f/d : 0.0f;
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y[i].d = GGML_FP32_TO_FP16(d);
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y[i].m = GGML_FP32_TO_FP16(min);
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uint32_t qh = 0;
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for (int j = 0; j < qk/2; ++j) {
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const float x0 = (x[i*qk + 0 + j] - min)*id;
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const float x1 = (x[i*qk + qk/2 + j] - min)*id;
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const uint8_t xi0 = (uint8_t)(x0 + 0.5f);
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const uint8_t xi1 = (uint8_t)(x1 + 0.5f);
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y[i].qs[j] = (xi0 & 0x0F) | ((xi1 & 0x0F) << 4);
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// get the 5-th bit and store it in qh at the right position
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qh |= ((xi0 & 0x10u) >> 4) << (j + 0);
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qh |= ((xi1 & 0x10u) >> 4) << (j + qk/2);
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}
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memcpy(&y[i].qh, &qh, sizeof(y[i].qh));
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}
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}
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// reference implementation for deterministic creation of model files
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void quantize_row_q8_0_ref(const float * restrict x, block_q8_0 * restrict y, int64_t k) {
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assert(k % QK8_0 == 0);
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const int nb = k / QK8_0;
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for (int i = 0; i < nb; i++) {
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float amax = 0.0f; // absolute max
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for (int j = 0; j < QK8_0; j++) {
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const float v = x[i*QK8_0 + j];
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amax = MAX(amax, fabsf(v));
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}
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const float d = amax / ((1 << 7) - 1);
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const float id = d ? 1.0f/d : 0.0f;
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y[i].d = GGML_FP32_TO_FP16(d);
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for (int j = 0; j < QK8_0; ++j) {
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const float x0 = x[i*QK8_0 + j]*id;
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y[i].qs[j] = roundf(x0);
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}
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}
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}
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// reference implementation for deterministic creation of model files
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void quantize_row_q8_1_ref(const float * restrict x, block_q8_1 * restrict y, int64_t k) {
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assert(QK8_1 == 32);
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assert(k % QK8_1 == 0);
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const int nb = k / QK8_1;
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for (int i = 0; i < nb; i++) {
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float amax = 0.0f; // absolute max
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for (int j = 0; j < QK8_1; j++) {
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const float v = x[i*QK8_1 + j];
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amax = MAX(amax, fabsf(v));
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}
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const float d = amax / ((1 << 7) - 1);
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const float id = d ? 1.0f/d : 0.0f;
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y[i].d = GGML_FP32_TO_FP16(d);
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int sum = 0;
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for (int j = 0; j < QK8_1/2; ++j) {
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const float v0 = x[i*QK8_1 + j]*id;
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const float v1 = x[i*QK8_1 + QK8_1/2 + j]*id;
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y[i].qs[ j] = roundf(v0);
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y[i].qs[QK8_1/2 + j] = roundf(v1);
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sum += y[i].qs[ j];
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sum += y[i].qs[QK8_1/2 + j];
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}
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y[i].s = GGML_FP32_TO_FP16(sum*d);
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}
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}
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void dequantize_row_q4_0(const block_q4_0 * restrict x, float * restrict y, int64_t k) {
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static const int qk = QK4_0;
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assert(k % qk == 0);
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const int nb = k / qk;
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for (int i = 0; i < nb; i++) {
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const float d = GGML_FP16_TO_FP32(x[i].d);
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for (int j = 0; j < qk/2; ++j) {
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const int x0 = (x[i].qs[j] & 0x0F) - 8;
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const int x1 = (x[i].qs[j] >> 4) - 8;
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y[i*qk + j + 0 ] = x0*d;
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y[i*qk + j + qk/2] = x1*d;
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}
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}
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}
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void dequantize_row_q4_1(const block_q4_1 * restrict x, float * restrict y, int64_t k) {
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static const int qk = QK4_1;
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assert(k % qk == 0);
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const int nb = k / qk;
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for (int i = 0; i < nb; i++) {
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const float d = GGML_FP16_TO_FP32(x[i].d);
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const float m = GGML_FP16_TO_FP32(x[i].m);
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for (int j = 0; j < qk/2; ++j) {
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const int x0 = (x[i].qs[j] & 0x0F);
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const int x1 = (x[i].qs[j] >> 4);
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y[i*qk + j + 0 ] = x0*d + m;
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y[i*qk + j + qk/2] = x1*d + m;
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}
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}
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}
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void dequantize_row_q5_0(const block_q5_0 * restrict x, float * restrict y, int64_t k) {
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static const int qk = QK5_0;
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assert(k % qk == 0);
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const int nb = k / qk;
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for (int i = 0; i < nb; i++) {
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const float d = GGML_FP16_TO_FP32(x[i].d);
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uint32_t qh;
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memcpy(&qh, x[i].qh, sizeof(qh));
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for (int j = 0; j < qk/2; ++j) {
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const uint8_t xh_0 = ((qh >> (j + 0)) << 4) & 0x10;
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const uint8_t xh_1 = ((qh >> (j + 12)) ) & 0x10;
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const int32_t x0 = ((x[i].qs[j] & 0x0F) | xh_0) - 16;
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const int32_t x1 = ((x[i].qs[j] >> 4) | xh_1) - 16;
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y[i*qk + j + 0 ] = x0*d;
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y[i*qk + j + qk/2] = x1*d;
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}
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}
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}
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void dequantize_row_q5_1(const block_q5_1 * restrict x, float * restrict y, int64_t k) {
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static const int qk = QK5_1;
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assert(k % qk == 0);
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const int nb = k / qk;
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for (int i = 0; i < nb; i++) {
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const float d = GGML_FP16_TO_FP32(x[i].d);
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const float m = GGML_FP16_TO_FP32(x[i].m);
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uint32_t qh;
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memcpy(&qh, x[i].qh, sizeof(qh));
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for (int j = 0; j < qk/2; ++j) {
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const uint8_t xh_0 = ((qh >> (j + 0)) << 4) & 0x10;
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const uint8_t xh_1 = ((qh >> (j + 12)) ) & 0x10;
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const int x0 = (x[i].qs[j] & 0x0F) | xh_0;
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const int x1 = (x[i].qs[j] >> 4) | xh_1;
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y[i*qk + j + 0 ] = x0*d + m;
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y[i*qk + j + qk/2] = x1*d + m;
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}
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}
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}
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void dequantize_row_q8_0(const block_q8_0 * restrict x, float * restrict y, int64_t k) {
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static const int qk = QK8_0;
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assert(k % qk == 0);
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const int nb = k / qk;
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for (int i = 0; i < nb; i++) {
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const float d = GGML_FP16_TO_FP32(x[i].d);
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for (int j = 0; j < qk; ++j) {
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y[i*qk + j] = x[i].qs[j]*d;
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}
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}
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}
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//
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// 2-6 bit quantization in super-blocks
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//
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//
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// ===================== Helper functions
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//
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static inline int nearest_int(float fval) {
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assert(fabsf(fval) <= 4194303.f);
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float val = fval + 12582912.f;
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int i; memcpy(&i, &val, sizeof(int));
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return (i & 0x007fffff) - 0x00400000;
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}
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static float make_qx_quants(int n, int nmax, const float * restrict x, int8_t * restrict L, int rmse_type,
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const float * restrict qw) {
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float max = 0;
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float amax = 0;
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for (int i = 0; i < n; ++i) {
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float ax = fabsf(x[i]);
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if (ax > amax) { amax = ax; max = x[i]; }
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}
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if (amax < GROUP_MAX_EPS) { // all zero
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for (int i = 0; i < n; ++i) {
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L[i] = 0;
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}
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return 0.f;
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}
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float iscale = -nmax / max;
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if (rmse_type == 0) {
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for (int i = 0; i < n; ++i) {
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int l = nearest_int(iscale * x[i]);
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L[i] = nmax + MAX(-nmax, MIN(nmax-1, l));
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}
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return 1/iscale;
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}
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bool return_early = false;
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if (rmse_type < 0) {
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rmse_type = -rmse_type;
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return_early = true;
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}
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float sumlx = 0;
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float suml2 = 0;
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#ifdef HAVE_BUGGY_APPLE_LINKER
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// use 'volatile' to prevent unroll and work around a bug in Apple ld64 1015.7
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for (volatile int i = 0; i < n; ++i) {
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#else
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for (int i = 0; i < n; ++i) {
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#endif
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int l = nearest_int(iscale * x[i]);
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l = MAX(-nmax, MIN(nmax-1, l));
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L[i] = l + nmax;
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float w = qw ? qw[i] : rmse_type == 1 ? x[i] * x[i] : rmse_type == 2 ? 1 : rmse_type == 3 ? fabsf(x[i]) : sqrtf(fabsf(x[i]));
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sumlx += w*x[i]*l;
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suml2 += w*l*l;
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}
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float scale = suml2 ? sumlx/suml2 : 0.0f;
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if (return_early) return suml2 > 0 ? 0.5f*(scale + 1/iscale) : 1/iscale;
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float best = scale * sumlx;
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for (int is = -9; is <= 9; ++is) {
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if (is == 0) {
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continue;
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}
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iscale = -(nmax + 0.1f*is) / max;
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sumlx = suml2 = 0;
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for (int i = 0; i < n; ++i) {
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int l = nearest_int(iscale * x[i]);
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l = MAX(-nmax, MIN(nmax-1, l));
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float w = qw ? qw[i] : rmse_type == 1 ? x[i] * x[i] : rmse_type == 2 ? 1 : rmse_type == 3 ? fabsf(x[i]) : sqrtf(fabsf(x[i]));
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sumlx += w*x[i]*l;
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suml2 += w*l*l;
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}
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if (suml2 > 0 && sumlx*sumlx > best*suml2) {
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for (int i = 0; i < n; ++i) {
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int l = nearest_int(iscale * x[i]);
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L[i] = nmax + MAX(-nmax, MIN(nmax-1, l));
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}
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scale = sumlx/suml2; best = scale*sumlx;
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}
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}
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return scale;
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}
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static float make_q3_quants(int n, int nmax, const float * restrict x, int8_t * restrict L, bool do_rmse) {
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float max = 0;
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float amax = 0;
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for (int i = 0; i < n; ++i) {
|
|
float ax = fabsf(x[i]);
|
|
if (ax > amax) { amax = ax; max = x[i]; }
|
|
}
|
|
if (amax < GROUP_MAX_EPS) { // all zero
|
|
for (int i = 0; i < n; ++i) { L[i] = 0; }
|
|
return 0.f;
|
|
}
|
|
float iscale = -nmax / max;
|
|
if (do_rmse) {
|
|
float sumlx = 0;
|
|
float suml2 = 0;
|
|
for (int i = 0; i < n; ++i) {
|
|
int l = nearest_int(iscale * x[i]);
|
|
l = MAX(-nmax, MIN(nmax-1, l));
|
|
L[i] = l;
|
|
float w = x[i]*x[i];
|
|
sumlx += w*x[i]*l;
|
|
suml2 += w*l*l;
|
|
}
|
|
for (int itry = 0; itry < 5; ++itry) {
|
|
int n_changed = 0;
|
|
for (int i = 0; i < n; ++i) {
|
|
float w = x[i]*x[i];
|
|
float slx = sumlx - w*x[i]*L[i];
|
|
if (slx > 0) {
|
|
float sl2 = suml2 - w*L[i]*L[i];
|
|
int new_l = nearest_int(x[i] * sl2 / slx);
|
|
new_l = MAX(-nmax, MIN(nmax-1, new_l));
|
|
if (new_l != L[i]) {
|
|
slx += w*x[i]*new_l;
|
|
sl2 += w*new_l*new_l;
|
|
if (sl2 > 0 && slx*slx*suml2 > sumlx*sumlx*sl2) {
|
|
L[i] = new_l; sumlx = slx; suml2 = sl2;
|
|
++n_changed;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
if (!n_changed) {
|
|
break;
|
|
}
|
|
}
|
|
for (int i = 0; i < n; ++i) {
|
|
L[i] += nmax;
|
|
}
|
|
return sumlx / suml2;
|
|
}
|
|
for (int i = 0; i < n; ++i) {
|
|
int l = nearest_int(iscale * x[i]);
|
|
l = MAX(-nmax, MIN(nmax-1, l));
|
|
L[i] = l + nmax;
|
|
}
|
|
return 1/iscale;
|
|
}
|
|
|
|
static float make_qkx1_quants(int n, int nmax, const float * restrict x, uint8_t * restrict L, float * restrict the_min,
|
|
int ntry, float alpha) {
|
|
float min = x[0];
|
|
float max = x[0];
|
|
for (int i = 1; i < n; ++i) {
|
|
if (x[i] < min) min = x[i];
|
|
if (x[i] > max) max = x[i];
|
|
}
|
|
if (max == min) {
|
|
for (int i = 0; i < n; ++i) L[i] = 0;
|
|
*the_min = 0;
|
|
return 0.f;
|
|
}
|
|
if (min > 0) min = 0;
|
|
float iscale = nmax/(max - min);
|
|
float scale = 1/iscale;
|
|
for (int itry = 0; itry < ntry; ++itry) {
|
|
float sumlx = 0; int suml2 = 0;
|
|
bool did_change = false;
|
|
for (int i = 0; i < n; ++i) {
|
|
int l = nearest_int(iscale*(x[i] - min));
|
|
l = MAX(0, MIN(nmax, l));
|
|
if (l != L[i]) {
|
|
L[i] = l;
|
|
did_change = true;
|
|
}
|
|
sumlx += (x[i] - min)*l;
|
|
suml2 += l*l;
|
|
}
|
|
scale = sumlx/suml2;
|
|
float sum = 0;
|
|
for (int i = 0; i < n; ++i) {
|
|
sum += x[i] - scale*L[i];
|
|
}
|
|
min = alpha*min + (1 - alpha)*sum/n;
|
|
if (min > 0) min = 0;
|
|
iscale = 1/scale;
|
|
if (!did_change) break;
|
|
}
|
|
*the_min = -min;
|
|
return scale;
|
|
}
|
|
|
|
static float make_qkx2_quants(int n, int nmax, const float * restrict x, const float * restrict weights,
|
|
uint8_t * restrict L, float * restrict the_min, uint8_t * restrict Laux,
|
|
float rmin, float rdelta, int nstep, bool use_mad) {
|
|
float min = x[0];
|
|
float max = x[0];
|
|
float sum_w = weights[0];
|
|
float sum_x = sum_w * x[0];
|
|
#ifdef HAVE_BUGGY_APPLE_LINKER
|
|
// use 'volatile' to prevent unroll and work around a bug in Apple ld64 1015.7
|
|
for (volatile int i = 1; i < n; ++i) {
|
|
#else
|
|
for (int i = 1; i < n; ++i) {
|
|
#endif
|
|
if (x[i] < min) min = x[i];
|
|
if (x[i] > max) max = x[i];
|
|
float w = weights[i];
|
|
sum_w += w;
|
|
sum_x += w * x[i];
|
|
}
|
|
if (min > 0) min = 0;
|
|
if (max == min) {
|
|
for (int i = 0; i < n; ++i) L[i] = 0;
|
|
*the_min = -min;
|
|
return 0.f;
|
|
}
|
|
float iscale = nmax/(max - min);
|
|
float scale = 1/iscale;
|
|
float best_mad = 0;
|
|
for (int i = 0; i < n; ++i) {
|
|
int l = nearest_int(iscale*(x[i] - min));
|
|
L[i] = MAX(0, MIN(nmax, l));
|
|
float diff = scale * L[i] + min - x[i];
|
|
diff = use_mad ? fabsf(diff) : diff * diff;
|
|
float w = weights[i];
|
|
best_mad += w * diff;
|
|
}
|
|
if (nstep < 1) {
|
|
*the_min = -min;
|
|
return scale;
|
|
}
|
|
for (int is = 0; is <= nstep; ++is) {
|
|
iscale = (rmin + rdelta*is + nmax)/(max - min);
|
|
float sum_l = 0, sum_l2 = 0, sum_xl = 0;
|
|
for (int i = 0; i < n; ++i) {
|
|
int l = nearest_int(iscale*(x[i] - min));
|
|
l = MAX(0, MIN(nmax, l));
|
|
Laux[i] = l;
|
|
float w = weights[i];
|
|
sum_l += w*l;
|
|
sum_l2 += w*l*l;
|
|
sum_xl += w*l*x[i];
|
|
}
|
|
float D = sum_w * sum_l2 - sum_l * sum_l;
|
|
if (D > 0) {
|
|
float this_scale = (sum_w * sum_xl - sum_x * sum_l)/D;
|
|
float this_min = (sum_l2 * sum_x - sum_l * sum_xl)/D;
|
|
if (this_min > 0) {
|
|
this_min = 0;
|
|
this_scale = sum_xl / sum_l2;
|
|
}
|
|
float mad = 0;
|
|
for (int i = 0; i < n; ++i) {
|
|
float diff = this_scale * Laux[i] + this_min - x[i];
|
|
diff = use_mad ? fabsf(diff) : diff * diff;
|
|
float w = weights[i];
|
|
mad += w * diff;
|
|
}
|
|
if (mad < best_mad) {
|
|
for (int i = 0; i < n; ++i) {
|
|
L[i] = Laux[i];
|
|
}
|
|
best_mad = mad;
|
|
scale = this_scale;
|
|
min = this_min;
|
|
}
|
|
}
|
|
}
|
|
*the_min = -min;
|
|
return scale;
|
|
}
|
|
|
|
static inline void get_scale_min_k4(int j, const uint8_t * restrict q, uint8_t * restrict d, uint8_t * restrict m) {
|
|
if (j < 4) {
|
|
*d = q[j] & 63; *m = q[j + 4] & 63;
|
|
} else {
|
|
*d = (q[j+4] & 0xF) | ((q[j-4] >> 6) << 4);
|
|
*m = (q[j+4] >> 4) | ((q[j-0] >> 6) << 4);
|
|
}
|
|
}
|
|
|
|
//========================- 2-bit (de)-quantization
|
|
|
|
void quantize_row_q2_K_ref(const float * restrict x, block_q2_K * restrict y, int64_t k) {
|
|
assert(k % QK_K == 0);
|
|
const int nb = k / QK_K;
|
|
|
|
uint8_t L[QK_K];
|
|
uint8_t Laux[16];
|
|
float weights[16];
|
|
float mins[QK_K/16];
|
|
float scales[QK_K/16];
|
|
|
|
const float q4scale = 15.f;
|
|
|
|
for (int i = 0; i < nb; i++) {
|
|
float max_scale = 0; // as we are deducting the min, scales are always positive
|
|
float max_min = 0;
|
|
for (int j = 0; j < QK_K/16; ++j) {
|
|
for (int l = 0; l < 16; ++l) weights[l] = fabsf(x[16*j + l]);
|
|
scales[j] = make_qkx2_quants(16, 3, x + 16*j, weights, L + 16*j, &mins[j], Laux, -0.5f, 0.1f, 15, true);
|
|
float scale = scales[j];
|
|
if (scale > max_scale) {
|
|
max_scale = scale;
|
|
}
|
|
float min = mins[j];
|
|
if (min > max_min) {
|
|
max_min = min;
|
|
}
|
|
}
|
|
|
|
if (max_scale > 0) {
|
|
float iscale = q4scale/max_scale;
|
|
for (int j = 0; j < QK_K/16; ++j) {
|
|
int l = nearest_int(iscale*scales[j]);
|
|
y[i].scales[j] = l;
|
|
}
|
|
y[i].d = GGML_FP32_TO_FP16(max_scale/q4scale);
|
|
} else {
|
|
for (int j = 0; j < QK_K/16; ++j) y[i].scales[j] = 0;
|
|
y[i].d = GGML_FP32_TO_FP16(0.f);
|
|
}
|
|
if (max_min > 0) {
|
|
float iscale = q4scale/max_min;
|
|
for (int j = 0; j < QK_K/16; ++j) {
|
|
int l = nearest_int(iscale*mins[j]);
|
|
y[i].scales[j] |= (l << 4);
|
|
}
|
|
y[i].dmin = GGML_FP32_TO_FP16(max_min/q4scale);
|
|
} else {
|
|
y[i].dmin = GGML_FP32_TO_FP16(0.f);
|
|
}
|
|
for (int j = 0; j < QK_K/16; ++j) {
|
|
const float d = GGML_FP16_TO_FP32(y[i].d) * (y[i].scales[j] & 0xF);
|
|
if (!d) continue;
|
|
const float dm = GGML_FP16_TO_FP32(y[i].dmin) * (y[i].scales[j] >> 4);
|
|
for (int ii = 0; ii < 16; ++ii) {
|
|
int l = nearest_int((x[16*j + ii] + dm)/d);
|
|
l = MAX(0, MIN(3, l));
|
|
L[16*j + ii] = l;
|
|
}
|
|
}
|
|
|
|
for (int j = 0; j < QK_K; j += 128) {
|
|
for (int l = 0; l < 32; ++l) {
|
|
y[i].qs[j/4 + l] = L[j + l] | (L[j + l + 32] << 2) | (L[j + l + 64] << 4) | (L[j + l + 96] << 6);
|
|
}
|
|
}
|
|
|
|
x += QK_K;
|
|
}
|
|
}
|
|
|
|
void dequantize_row_q2_K(const block_q2_K * restrict x, float * restrict y, int64_t k) {
|
|
assert(k % QK_K == 0);
|
|
const int nb = k / QK_K;
|
|
|
|
for (int i = 0; i < nb; i++) {
|
|
|
|
const float d = GGML_FP16_TO_FP32(x[i].d);
|
|
const float min = GGML_FP16_TO_FP32(x[i].dmin);
|
|
|
|
const uint8_t * q = x[i].qs;
|
|
|
|
int is = 0;
|
|
float dl, ml;
|
|
for (int n = 0; n < QK_K; n += 128) {
|
|
int shift = 0;
|
|
for (int j = 0; j < 4; ++j) {
|
|
|
|
uint8_t sc = x[i].scales[is++];
|
|
dl = d * (sc & 0xF); ml = min * (sc >> 4);
|
|
for (int l = 0; l < 16; ++l) *y++ = dl * ((int8_t)((q[l] >> shift) & 3)) - ml;
|
|
|
|
sc = x[i].scales[is++];
|
|
dl = d * (sc & 0xF); ml = min * (sc >> 4);
|
|
for (int l = 0; l < 16; ++l) *y++ = dl * ((int8_t)((q[l+16] >> shift) & 3)) - ml;
|
|
|
|
shift += 2;
|
|
}
|
|
q += 32;
|
|
}
|
|
}
|
|
}
|
|
|
|
static float make_qkx3_quants(int n, int nmax, const float * restrict x, const float * restrict weights,
|
|
uint8_t * restrict L, float * restrict the_min, uint8_t * restrict Laux,
|
|
float rmin, float rdelta, int nstep, bool use_mad) {
|
|
float min = x[0];
|
|
float max = x[0];
|
|
float sum_w = weights ? weights[0] : x[0]*x[0];
|
|
float sum_x = sum_w * x[0];
|
|
#ifdef HAVE_BUGGY_APPLE_LINKER
|
|
// use 'volatile' to prevent unroll and work around a bug in Apple ld64 1015.7
|
|
for (volatile int i = 1; i < n; ++i) {
|
|
#else
|
|
for (int i = 1; i < n; ++i) {
|
|
#endif
|
|
if (x[i] < min) min = x[i];
|
|
if (x[i] > max) max = x[i];
|
|
float w = weights ? weights[i] : x[i]*x[i];
|
|
sum_w += w;
|
|
sum_x += w * x[i];
|
|
}
|
|
if (min > 0) {
|
|
min = 0;
|
|
}
|
|
if (max <= min) {
|
|
memset(L, 0, n);
|
|
*the_min = -min;
|
|
return 0.f;
|
|
}
|
|
float iscale = nmax/(max - min);
|
|
float scale = 1/iscale;
|
|
float best_mad = 0;
|
|
for (int i = 0; i < n; ++i) {
|
|
int l = nearest_int(iscale*(x[i] - min));
|
|
L[i] = MAX(0, MIN(nmax, l));
|
|
float diff = scale * L[i] + min - x[i];
|
|
diff = use_mad ? fabsf(diff) : diff*diff;
|
|
float w = weights ? weights[i] : x[i]*x[i];
|
|
best_mad += w * diff;
|
|
}
|
|
if (nstep < 1) {
|
|
*the_min = -min;
|
|
return scale;
|
|
}
|
|
for (int is = 0; is <= nstep; ++is) {
|
|
iscale = (rmin + rdelta*is + nmax)/(max - min);
|
|
float sum_l = 0, sum_l2 = 0, sum_xl = 0;
|
|
for (int i = 0; i < n; ++i) {
|
|
int l = nearest_int(iscale*(x[i] - min));
|
|
l = MAX(0, MIN(nmax, l));
|
|
Laux[i] = l;
|
|
float w = weights ? weights[i] : x[i]*x[i];
|
|
sum_l += w*l;
|
|
sum_l2 += w*l*l;
|
|
sum_xl += w*l*x[i];
|
|
}
|
|
float D = sum_w * sum_l2 - sum_l * sum_l;
|
|
if (D > 0) {
|
|
float this_scale = (sum_w * sum_xl - sum_x * sum_l)/D;
|
|
float this_min = (sum_l2 * sum_x - sum_l * sum_xl)/D;
|
|
if (this_min > 0) {
|
|
this_min = 0;
|
|
this_scale = sum_xl / sum_l2;
|
|
}
|
|
float mad = 0;
|
|
for (int i = 0; i < n; ++i) {
|
|
float diff = this_scale * Laux[i] + this_min - x[i];
|
|
diff = use_mad ? fabsf(diff) : diff*diff;
|
|
float w = weights ? weights[i] : x[i]*x[i];
|
|
mad += w * diff;
|
|
}
|
|
if (mad < best_mad) {
|
|
for (int i = 0; i < n; ++i) {
|
|
L[i] = Laux[i];
|
|
}
|
|
best_mad = mad;
|
|
scale = this_scale;
|
|
min = this_min;
|
|
}
|
|
}
|
|
}
|
|
*the_min = -min;
|
|
return scale;
|
|
}
|
|
|
|
static float make_qp_quants(int n, int nmax, const float * restrict x, uint8_t * restrict L, const float * quant_weights) {
|
|
float max = 0;
|
|
for (int i = 0; i < n; ++i) {
|
|
max = MAX(max, x[i]);
|
|
}
|
|
if (!max) { // all zero
|
|
for (int i = 0; i < n; ++i) { L[i] = 0; }
|
|
return 0.f;
|
|
}
|
|
float iscale = nmax / max;
|
|
for (int i = 0; i < n; ++i) {
|
|
L[i] = nearest_int(iscale * x[i]);
|
|
}
|
|
float scale = 1/iscale;
|
|
float best_mse = 0;
|
|
for (int i = 0; i < n; ++i) {
|
|
float diff = x[i] - scale*L[i];
|
|
float w = quant_weights[i];
|
|
best_mse += w*diff*diff;
|
|
}
|
|
for (int is = -4; is <= 4; ++is) {
|
|
if (is == 0) continue;
|
|
float iscale_is = (0.1f*is + nmax)/max;
|
|
float scale_is = 1/iscale_is;
|
|
float mse = 0;
|
|
for (int i = 0; i < n; ++i) {
|
|
int l = nearest_int(iscale_is*x[i]);
|
|
l = MIN(nmax, l);
|
|
float diff = x[i] - scale_is*l;
|
|
float w = quant_weights[i];
|
|
mse += w*diff*diff;
|
|
}
|
|
if (mse < best_mse) {
|
|
best_mse = mse;
|
|
iscale = iscale_is;
|
|
}
|
|
}
|
|
float sumlx = 0;
|
|
float suml2 = 0;
|
|
for (int i = 0; i < n; ++i) {
|
|
int l = nearest_int(iscale * x[i]);
|
|
l = MIN(nmax, l);
|
|
L[i] = l;
|
|
float w = quant_weights[i];
|
|
sumlx += w*x[i]*l;
|
|
suml2 += w*l*l;
|
|
}
|
|
for (int itry = 0; itry < 5; ++itry) {
|
|
int n_changed = 0;
|
|
for (int i = 0; i < n; ++i) {
|
|
float w = quant_weights[i];
|
|
float slx = sumlx - w*x[i]*L[i];
|
|
float sl2 = suml2 - w*L[i]*L[i];
|
|
if (slx > 0 && sl2 > 0) {
|
|
int new_l = nearest_int(x[i] * sl2 / slx);
|
|
new_l = MIN(nmax, new_l);
|
|
if (new_l != L[i]) {
|
|
slx += w*x[i]*new_l;
|
|
sl2 += w*new_l*new_l;
|
|
if (slx*slx*suml2 > sumlx*sumlx*sl2) {
|
|
L[i] = new_l; sumlx = slx; suml2 = sl2;
|
|
++n_changed;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
if (!n_changed) {
|
|
break;
|
|
}
|
|
}
|
|
return sumlx/suml2;
|
|
}
|
|
|
|
static void quantize_row_q2_K_impl(const float * restrict x, block_q2_K * restrict y, int k, const float * restrict quant_weights) {
|
|
GGML_ASSERT(quant_weights);
|
|
assert(k % QK_K == 0);
|
|
const int nb = k / QK_K;
|
|
const bool requantize = true;
|
|
|
|
uint8_t L[QK_K];
|
|
uint8_t Laux[16];
|
|
float mins[QK_K/16];
|
|
float scales[QK_K/16];
|
|
float sw[QK_K/16];
|
|
float weight[16];
|
|
uint8_t Ls[QK_K/16], Lm[QK_K/16];
|
|
|
|
for (int i = 0; i < nb; i++) {
|
|
memset(sw, 0, QK_K/16*sizeof(float));
|
|
float sumx2 = 0;
|
|
for (int j = 0; j < QK_K; ++j) sumx2 += x[j]*x[j];
|
|
float sigma2 = sumx2/QK_K;
|
|
for (int j = 0; j < QK_K/16; ++j) {
|
|
const float * restrict qw = quant_weights + QK_K * i + 16*j;
|
|
for (int l = 0; l < 16; ++l) weight[l] = qw[l] * sqrtf(sigma2 + x[16*j + l]*x[16*j + l]);
|
|
for (int l = 0; l < QK_K/16; ++l) sw[j] += weight[l];
|
|
scales[j] = make_qkx3_quants(16, 3, x + 16*j, weight, L + 16*j, &mins[j], Laux, -0.9f, 0.05f, 36, false);
|
|
}
|
|
|
|
float dm, mm;
|
|
dm = make_qp_quants(QK_K/16, 15, scales, Ls, sw);
|
|
mm = make_qp_quants(QK_K/16, 15, mins, Lm, sw);
|
|
|
|
y[i].d = GGML_FP32_TO_FP16(dm);
|
|
y[i].dmin = GGML_FP32_TO_FP16(mm);
|
|
dm = GGML_FP16_TO_FP32(y[i].d);
|
|
mm = GGML_FP16_TO_FP32(y[i].dmin);
|
|
|
|
for (int j = 0; j < QK_K/16; ++j) {
|
|
y[i].scales[j] = Ls[j] | (Lm[j] << 4);
|
|
}
|
|
|
|
if (requantize) {
|
|
for (int j = 0; j < QK_K/16; ++j) {
|
|
const float d = dm * (y[i].scales[j] & 0xF);
|
|
if (!d) continue;
|
|
const float m = mm * (y[i].scales[j] >> 4);
|
|
for (int ii = 0; ii < 16; ++ii) {
|
|
int l = nearest_int((x[16*j + ii] + m)/d);
|
|
l = MAX(0, MIN(3, l));
|
|
L[16*j + ii] = l;
|
|
}
|
|
}
|
|
}
|
|
|
|
for (int j = 0; j < QK_K; j += 128) {
|
|
for (int l = 0; l < 32; ++l) {
|
|
y[i].qs[j/4 + l] = L[j + l] | (L[j + l + 32] << 2) | (L[j + l + 64] << 4) | (L[j + l + 96] << 6);
|
|
}
|
|
}
|
|
|
|
x += QK_K;
|
|
}
|
|
}
|
|
|
|
size_t quantize_q2_K(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
|
|
size_t row_size = ggml_row_size(GGML_TYPE_Q2_K, n_per_row);
|
|
if (!quant_weights) {
|
|
quantize_row_q2_K_ref(src, dst, (int64_t)nrow*n_per_row);
|
|
}
|
|
else {
|
|
char * qrow = (char *)dst;
|
|
for (int64_t row = 0; row < nrow; ++row) {
|
|
quantize_row_q2_K_impl(src, (block_q2_K*)qrow, n_per_row, quant_weights);
|
|
src += n_per_row;
|
|
qrow += row_size;
|
|
}
|
|
}
|
|
return nrow * row_size;
|
|
}
|
|
|
|
//========================= 3-bit (de)-quantization
|
|
|
|
void quantize_row_q3_K_ref(const float * restrict x, block_q3_K * restrict y, int64_t k) {
|
|
assert(k % QK_K == 0);
|
|
const int nb = k / QK_K;
|
|
|
|
int8_t L[QK_K];
|
|
float scales[QK_K / 16];
|
|
|
|
for (int i = 0; i < nb; i++) {
|
|
|
|
float max_scale = 0;
|
|
float amax = 0;
|
|
for (int j = 0; j < QK_K/16; ++j) {
|
|
scales[j] = make_q3_quants(16, 4, x + 16*j, L + 16*j, true);
|
|
float scale = fabsf(scales[j]);
|
|
if (scale > amax) {
|
|
amax = scale; max_scale = scales[j];
|
|
}
|
|
}
|
|
|
|
memset(y[i].scales, 0, 12);
|
|
if (max_scale) {
|
|
float iscale = -32.f/max_scale;
|
|
for (int j = 0; j < QK_K/16; ++j) {
|
|
int8_t l = nearest_int(iscale*scales[j]);
|
|
l = MAX(-32, MIN(31, l)) + 32;
|
|
if (j < 8) {
|
|
y[i].scales[j] = l & 0xF;
|
|
} else {
|
|
y[i].scales[j-8] |= ((l & 0xF) << 4);
|
|
}
|
|
l >>= 4;
|
|
y[i].scales[j%4 + 8] |= (l << (2*(j/4)));
|
|
}
|
|
y[i].d = GGML_FP32_TO_FP16(1/iscale);
|
|
} else {
|
|
y[i].d = GGML_FP32_TO_FP16(0.f);
|
|
}
|
|
|
|
int8_t sc;
|
|
for (int j = 0; j < QK_K/16; ++j) {
|
|
sc = j < 8 ? y[i].scales[j] & 0xF : y[i].scales[j-8] >> 4;
|
|
sc = (sc | (((y[i].scales[8 + j%4] >> (2*(j/4))) & 3) << 4)) - 32;
|
|
float d = GGML_FP16_TO_FP32(y[i].d) * sc;
|
|
if (!d) {
|
|
continue;
|
|
}
|
|
for (int ii = 0; ii < 16; ++ii) {
|
|
int l = nearest_int(x[16*j + ii]/d);
|
|
l = MAX(-4, MIN(3, l));
|
|
L[16*j + ii] = l + 4;
|
|
}
|
|
}
|
|
|
|
memset(y[i].hmask, 0, QK_K/8);
|
|
// We put the high-bit for the 1st 8 quants into bit 0, the next 8 into bit 1, etc.
|
|
int m = 0;
|
|
uint8_t hm = 1;
|
|
for (int j = 0; j < QK_K; ++j) {
|
|
if (L[j] > 3) {
|
|
y[i].hmask[m] |= hm;
|
|
L[j] -= 4;
|
|
}
|
|
if (++m == QK_K/8) {
|
|
m = 0; hm <<= 1;
|
|
}
|
|
}
|
|
for (int j = 0; j < QK_K; j += 128) {
|
|
for (int l = 0; l < 32; ++l) {
|
|
y[i].qs[j/4 + l] = L[j + l] | (L[j + l + 32] << 2) | (L[j + l + 64] << 4) | (L[j + l + 96] << 6);
|
|
}
|
|
}
|
|
|
|
x += QK_K;
|
|
}
|
|
}
|
|
|
|
void dequantize_row_q3_K(const block_q3_K * restrict x, float * restrict y, int64_t k) {
|
|
assert(k % QK_K == 0);
|
|
const int nb = k / QK_K;
|
|
|
|
const uint32_t kmask1 = 0x03030303;
|
|
const uint32_t kmask2 = 0x0f0f0f0f;
|
|
|
|
uint32_t aux[4];
|
|
const int8_t * scales = (const int8_t*)aux;
|
|
|
|
for (int i = 0; i < nb; i++) {
|
|
|
|
const float d_all = GGML_FP16_TO_FP32(x[i].d);
|
|
|
|
const uint8_t * restrict q = x[i].qs;
|
|
const uint8_t * restrict hm = x[i].hmask;
|
|
uint8_t m = 1;
|
|
|
|
memcpy(aux, x[i].scales, 12);
|
|
uint32_t tmp = aux[2];
|
|
aux[2] = ((aux[0] >> 4) & kmask2) | (((tmp >> 4) & kmask1) << 4);
|
|
aux[3] = ((aux[1] >> 4) & kmask2) | (((tmp >> 6) & kmask1) << 4);
|
|
aux[0] = (aux[0] & kmask2) | (((tmp >> 0) & kmask1) << 4);
|
|
aux[1] = (aux[1] & kmask2) | (((tmp >> 2) & kmask1) << 4);
|
|
|
|
int is = 0;
|
|
float dl;
|
|
for (int n = 0; n < QK_K; n += 128) {
|
|
int shift = 0;
|
|
for (int j = 0; j < 4; ++j) {
|
|
|
|
dl = d_all * (scales[is++] - 32);
|
|
for (int l = 0; l < 16; ++l) {
|
|
*y++ = dl * ((int8_t)((q[l+ 0] >> shift) & 3) - ((hm[l+ 0] & m) ? 0 : 4));
|
|
}
|
|
|
|
dl = d_all * (scales[is++] - 32);
|
|
for (int l = 0; l < 16; ++l) {
|
|
*y++ = dl * ((int8_t)((q[l+16] >> shift) & 3) - ((hm[l+16] & m) ? 0 : 4));
|
|
}
|
|
|
|
shift += 2;
|
|
m <<= 1;
|
|
}
|
|
q += 32;
|
|
}
|
|
|
|
}
|
|
}
|
|
|
|
static void quantize_row_q3_K_impl(const float * restrict x, block_q3_K * restrict y, int64_t n_per_row, const float * restrict quant_weights) {
|
|
assert(n_per_row % QK_K == 0);
|
|
const int nb = n_per_row / QK_K;
|
|
|
|
int8_t L[QK_K];
|
|
float scales[QK_K / 16];
|
|
float weight[16];
|
|
float sw[QK_K / 16];
|
|
int8_t Ls[QK_K / 16];
|
|
|
|
for (int i = 0; i < nb; i++) {
|
|
|
|
float sumx2 = 0;
|
|
for (int j = 0; j < QK_K; ++j) sumx2 += x[j]*x[j];
|
|
float sigma2 = 2*sumx2/QK_K;
|
|
|
|
for (int j = 0; j < QK_K/16; ++j) {
|
|
if (quant_weights) {
|
|
const float * qw = quant_weights + QK_K * i + 16*j;
|
|
for (int l = 0; l < 16; ++l) weight[l] = qw[l] * sqrtf(sigma2 + x[16*j+l]*x[16*j+l]);
|
|
} else {
|
|
for (int l = 0; l < 16; ++l) weight[l] = x[16*j+l]*x[16*j+l];
|
|
}
|
|
float sumw = 0;
|
|
for (int l = 0; l < 16; ++l) sumw += weight[l];
|
|
sw[j] = sumw;
|
|
|
|
scales[j] = make_qx_quants(16, 4, x + 16*j, L + 16*j, 1, weight);
|
|
|
|
}
|
|
|
|
memset(y[i].scales, 0, 12);
|
|
|
|
float d_block = make_qx_quants(QK_K/16, 32, scales, Ls, 1, sw);
|
|
for (int j = 0; j < QK_K/16; ++j) {
|
|
int l = Ls[j];
|
|
if (j < 8) {
|
|
y[i].scales[j] = l & 0xF;
|
|
} else {
|
|
y[i].scales[j-8] |= ((l & 0xF) << 4);
|
|
}
|
|
l >>= 4;
|
|
y[i].scales[j%4 + 8] |= (l << (2*(j/4)));
|
|
}
|
|
y[i].d = GGML_FP32_TO_FP16(d_block);
|
|
|
|
int8_t sc;
|
|
for (int j = 0; j < QK_K/16; ++j) {
|
|
sc = j < 8 ? y[i].scales[j] & 0xF : y[i].scales[j-8] >> 4;
|
|
sc = (sc | (((y[i].scales[8 + j%4] >> (2*(j/4))) & 3) << 4)) - 32;
|
|
float d = GGML_FP16_TO_FP32(y[i].d) * sc;
|
|
if (!d) {
|
|
continue;
|
|
}
|
|
for (int ii = 0; ii < 16; ++ii) {
|
|
int l = nearest_int(x[16*j + ii]/d);
|
|
l = MAX(-4, MIN(3, l));
|
|
L[16*j + ii] = l + 4;
|
|
}
|
|
}
|
|
|
|
memset(y[i].hmask, 0, QK_K/8);
|
|
// We put the high-bit for the 1st 8 quants into bit 0, the next 8 into bit 1, etc.
|
|
int m = 0;
|
|
uint8_t hm = 1;
|
|
for (int j = 0; j < QK_K; ++j) {
|
|
if (L[j] > 3) {
|
|
y[i].hmask[m] |= hm;
|
|
L[j] -= 4;
|
|
}
|
|
if (++m == QK_K/8) {
|
|
m = 0; hm <<= 1;
|
|
}
|
|
}
|
|
for (int j = 0; j < QK_K; j += 128) {
|
|
for (int l = 0; l < 32; ++l) {
|
|
y[i].qs[j/4 + l] = L[j + l] | (L[j + l + 32] << 2) | (L[j + l + 64] << 4) | (L[j + l + 96] << 6);
|
|
}
|
|
}
|
|
|
|
x += QK_K;
|
|
}
|
|
}
|
|
|
|
size_t quantize_q3_K(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
|
|
size_t row_size = ggml_row_size(GGML_TYPE_Q3_K, n_per_row);
|
|
if (!quant_weights) {
|
|
quantize_row_q3_K_ref(src, dst, (int64_t)nrow*n_per_row);
|
|
}
|
|
else {
|
|
char * qrow = (char *)dst;
|
|
for (int64_t row = 0; row < nrow; ++row) {
|
|
quantize_row_q3_K_impl(src, (block_q3_K*)qrow, n_per_row, quant_weights);
|
|
src += n_per_row;
|
|
qrow += row_size;
|
|
}
|
|
}
|
|
return nrow * row_size;
|
|
}
|
|
|
|
// ====================== 4-bit (de)-quantization
|
|
|
|
void quantize_row_q4_K_ref(const float * restrict x, block_q4_K * restrict y, int64_t k) {
|
|
assert(k % QK_K == 0);
|
|
const int nb = k / QK_K;
|
|
|
|
uint8_t L[QK_K];
|
|
uint8_t Laux[32];
|
|
float weights[32];
|
|
float mins[QK_K/32];
|
|
float scales[QK_K/32];
|
|
|
|
for (int i = 0; i < nb; i++) {
|
|
float max_scale = 0; // as we are deducting the min, scales are always positive
|
|
float max_min = 0;
|
|
for (int j = 0; j < QK_K/32; ++j) {
|
|
//scales[j] = make_qkx1_quants(32, 15, x + 32*j, L + 32*j, &mins[j], 9, 0.5f);
|
|
float sum_x2 = 0;
|
|
for (int l = 0; l < 32; ++l) sum_x2 += x[32*j + l] * x[32*j + l];
|
|
float av_x = sqrtf(sum_x2/32);
|
|
for (int l = 0; l < 32; ++l) weights[l] = av_x + fabsf(x[32*j + l]);
|
|
scales[j] = make_qkx2_quants(32, 15, x + 32*j, weights, L + 32*j, &mins[j], Laux, -1.f, 0.1f, 20, false);
|
|
float scale = scales[j];
|
|
if (scale > max_scale) {
|
|
max_scale = scale;
|
|
}
|
|
float min = mins[j];
|
|
if (min > max_min) {
|
|
max_min = min;
|
|
}
|
|
}
|
|
|
|
float inv_scale = max_scale > 0 ? 63.f/max_scale : 0.f;
|
|
float inv_min = max_min > 0 ? 63.f/max_min : 0.f;
|
|
for (int j = 0; j < QK_K/32; ++j) {
|
|
uint8_t ls = nearest_int(inv_scale*scales[j]);
|
|
uint8_t lm = nearest_int(inv_min*mins[j]);
|
|
ls = MIN(63, ls);
|
|
lm = MIN(63, lm);
|
|
if (j < 4) {
|
|
y[i].scales[j] = ls;
|
|
y[i].scales[j+4] = lm;
|
|
} else {
|
|
y[i].scales[j+4] = (ls & 0xF) | ((lm & 0xF) << 4);
|
|
y[i].scales[j-4] |= ((ls >> 4) << 6);
|
|
y[i].scales[j-0] |= ((lm >> 4) << 6);
|
|
}
|
|
}
|
|
y[i].d = GGML_FP32_TO_FP16(max_scale/63.f);
|
|
y[i].dmin = GGML_FP32_TO_FP16(max_min/63.f);
|
|
|
|
uint8_t sc, m;
|
|
for (int j = 0; j < QK_K/32; ++j) {
|
|
get_scale_min_k4(j, y[i].scales, &sc, &m);
|
|
const float d = GGML_FP16_TO_FP32(y[i].d) * sc;
|
|
if (!d) continue;
|
|
const float dm = GGML_FP16_TO_FP32(y[i].dmin) * m;
|
|
for (int ii = 0; ii < 32; ++ii) {
|
|
int l = nearest_int((x[32*j + ii] + dm)/d);
|
|
l = MAX(0, MIN(15, l));
|
|
L[32*j + ii] = l;
|
|
}
|
|
}
|
|
|
|
uint8_t * q = y[i].qs;
|
|
for (int j = 0; j < QK_K; j += 64) {
|
|
for (int l = 0; l < 32; ++l) q[l] = L[j + l] | (L[j + l + 32] << 4);
|
|
q += 32;
|
|
}
|
|
|
|
x += QK_K;
|
|
}
|
|
}
|
|
|
|
void dequantize_row_q4_K(const block_q4_K * restrict x, float * restrict y, int64_t k) {
|
|
assert(k % QK_K == 0);
|
|
const int nb = k / QK_K;
|
|
|
|
for (int i = 0; i < nb; i++) {
|
|
const uint8_t * q = x[i].qs;
|
|
|
|
const float d = GGML_FP16_TO_FP32(x[i].d);
|
|
const float min = GGML_FP16_TO_FP32(x[i].dmin);
|
|
|
|
int is = 0;
|
|
uint8_t sc, m;
|
|
for (int j = 0; j < QK_K; j += 64) {
|
|
get_scale_min_k4(is + 0, x[i].scales, &sc, &m);
|
|
const float d1 = d * sc; const float m1 = min * m;
|
|
get_scale_min_k4(is + 1, x[i].scales, &sc, &m);
|
|
const float d2 = d * sc; const float m2 = min * m;
|
|
for (int l = 0; l < 32; ++l) *y++ = d1 * (q[l] & 0xF) - m1;
|
|
for (int l = 0; l < 32; ++l) *y++ = d2 * (q[l] >> 4) - m2;
|
|
q += 32; is += 2;
|
|
}
|
|
}
|
|
}
|
|
|
|
static void quantize_row_q4_K_impl(const float * restrict x, block_q4_K * restrict y, int64_t n_per_row, const float * quant_weights) {
|
|
assert(n_per_row % QK_K == 0);
|
|
const int64_t nb = n_per_row / QK_K;
|
|
|
|
uint8_t L[QK_K];
|
|
uint8_t Laux[32];
|
|
uint8_t Ls[QK_K/32];
|
|
uint8_t Lm[QK_K/32];
|
|
float weights[32];
|
|
float sw[QK_K/32];
|
|
float mins[QK_K/32];
|
|
float scales[QK_K/32];
|
|
|
|
for (int i = 0; i < nb; i++) {
|
|
|
|
float sum_x2 = 0;
|
|
for (int l = 0; l < QK_K; ++l) sum_x2 += x[l] * x[l];
|
|
float sigma2 = 2*sum_x2/QK_K;
|
|
float av_x = sqrtf(sigma2);
|
|
|
|
for (int j = 0; j < QK_K/32; ++j) {
|
|
if (quant_weights) {
|
|
const float * qw = quant_weights + QK_K*i + 32*j;
|
|
for (int l = 0; l < 32; ++l) weights[l] = qw[l] * sqrtf(sigma2 + x[32*j + l]*x[32*j + l]);
|
|
} else {
|
|
for (int l = 0; l < 32; ++l) weights[l] = av_x + fabsf(x[32*j + l]);
|
|
}
|
|
float sumw = 0;
|
|
for (int l = 0; l < 32; ++l) sumw += weights[l];
|
|
sw[j] = sumw;
|
|
scales[j] = make_qkx3_quants(32, 15, x + 32*j, weights, L + 32*j, &mins[j], Laux, -0.9f, 0.05f, 36, false);
|
|
}
|
|
|
|
float d_block = make_qp_quants(QK_K/32, 63, scales, Ls, sw);
|
|
float m_block = make_qp_quants(QK_K/32, 63, mins, Lm, sw);
|
|
for (int j = 0; j < QK_K/32; ++j) {
|
|
uint8_t ls = Ls[j];
|
|
uint8_t lm = Lm[j];
|
|
if (j < 4) {
|
|
y[i].scales[j] = ls;
|
|
y[i].scales[j+4] = lm;
|
|
} else {
|
|
y[i].scales[j+4] = (ls & 0xF) | ((lm & 0xF) << 4);
|
|
y[i].scales[j-4] |= ((ls >> 4) << 6);
|
|
y[i].scales[j-0] |= ((lm >> 4) << 6);
|
|
}
|
|
}
|
|
y[i].d = GGML_FP32_TO_FP16(d_block);
|
|
y[i].dmin = GGML_FP32_TO_FP16(m_block);
|
|
|
|
uint8_t sc, m;
|
|
for (int j = 0; j < QK_K/32; ++j) {
|
|
get_scale_min_k4(j, y[i].scales, &sc, &m);
|
|
const float d = GGML_FP16_TO_FP32(y[i].d) * sc;
|
|
if (!d) continue;
|
|
const float dm = GGML_FP16_TO_FP32(y[i].dmin) * m;
|
|
for (int ii = 0; ii < 32; ++ii) {
|
|
int l = nearest_int((x[32*j + ii] + dm)/d);
|
|
l = MAX(0, MIN(15, l));
|
|
L[32*j + ii] = l;
|
|
}
|
|
}
|
|
uint8_t * q = y[i].qs;
|
|
for (int j = 0; j < QK_K; j += 64) {
|
|
for (int l = 0; l < 32; ++l) q[l] = L[j + l] | (L[j + l + 32] << 4);
|
|
q += 32;
|
|
}
|
|
|
|
x += QK_K;
|
|
|
|
}
|
|
}
|
|
|
|
size_t quantize_q4_K(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
|
|
size_t row_size = ggml_row_size(GGML_TYPE_Q4_K, n_per_row);
|
|
if (!quant_weights) {
|
|
quantize_row_q4_K_ref(src, dst, (int64_t)nrow*n_per_row);
|
|
}
|
|
else {
|
|
char * qrow = (char *)dst;
|
|
for (int64_t row = 0; row < nrow; ++row) {
|
|
quantize_row_q4_K_impl(src, (block_q4_K*)qrow, n_per_row, quant_weights);
|
|
src += n_per_row;
|
|
qrow += row_size;
|
|
}
|
|
}
|
|
return nrow * row_size;
|
|
}
|
|
|
|
// ====================== 5-bit (de)-quantization
|
|
|
|
void quantize_row_q5_K_ref(const float * restrict x, block_q5_K * restrict y, int64_t k) {
|
|
assert(k % QK_K == 0);
|
|
const int64_t nb = k / QK_K;
|
|
|
|
uint8_t L[QK_K];
|
|
float mins[QK_K/32];
|
|
float scales[QK_K/32];
|
|
float weights[32];
|
|
uint8_t Laux[32];
|
|
|
|
for (int i = 0; i < nb; i++) {
|
|
float max_scale = 0; // as we are deducting the min, scales are always positive
|
|
float max_min = 0;
|
|
for (int j = 0; j < QK_K/32; ++j) {
|
|
//scales[j] = make_qkx1_quants(32, 31, x + 32*j, L + 32*j, &mins[j], 9, 0.5f);
|
|
float sum_x2 = 0;
|
|
for (int l = 0; l < 32; ++l) sum_x2 += x[32*j + l] * x[32*j + l];
|
|
float av_x = sqrtf(sum_x2/32);
|
|
for (int l = 0; l < 32; ++l) weights[l] = av_x + fabsf(x[32*j + l]);
|
|
scales[j] = make_qkx2_quants(32, 31, x + 32*j, weights, L + 32*j, &mins[j], Laux, -0.5f, 0.1f, 15, false);
|
|
float scale = scales[j];
|
|
if (scale > max_scale) {
|
|
max_scale = scale;
|
|
}
|
|
float min = mins[j];
|
|
if (min > max_min) {
|
|
max_min = min;
|
|
}
|
|
}
|
|
|
|
float inv_scale = max_scale > 0 ? 63.f/max_scale : 0.f;
|
|
float inv_min = max_min > 0 ? 63.f/max_min : 0.f;
|
|
for (int j = 0; j < QK_K/32; ++j) {
|
|
uint8_t ls = nearest_int(inv_scale*scales[j]);
|
|
uint8_t lm = nearest_int(inv_min*mins[j]);
|
|
ls = MIN(63, ls);
|
|
lm = MIN(63, lm);
|
|
if (j < 4) {
|
|
y[i].scales[j] = ls;
|
|
y[i].scales[j+4] = lm;
|
|
} else {
|
|
y[i].scales[j+4] = (ls & 0xF) | ((lm & 0xF) << 4);
|
|
y[i].scales[j-4] |= ((ls >> 4) << 6);
|
|
y[i].scales[j-0] |= ((lm >> 4) << 6);
|
|
}
|
|
}
|
|
y[i].d = GGML_FP32_TO_FP16(max_scale/63.f);
|
|
y[i].dmin = GGML_FP32_TO_FP16(max_min/63.f);
|
|
|
|
uint8_t sc, m;
|
|
for (int j = 0; j < QK_K/32; ++j) {
|
|
get_scale_min_k4(j, y[i].scales, &sc, &m);
|
|
const float d = GGML_FP16_TO_FP32(y[i].d) * sc;
|
|
if (!d) continue;
|
|
const float dm = GGML_FP16_TO_FP32(y[i].dmin) * m;
|
|
for (int ii = 0; ii < 32; ++ii) {
|
|
int l = nearest_int((x[32*j + ii] + dm)/d);
|
|
l = MAX(0, MIN(31, l));
|
|
L[32*j + ii] = l;
|
|
}
|
|
}
|
|
|
|
uint8_t * restrict qh = y[i].qh;
|
|
uint8_t * restrict ql = y[i].qs;
|
|
memset(qh, 0, QK_K/8);
|
|
|
|
uint8_t m1 = 1, m2 = 2;
|
|
for (int n = 0; n < QK_K; n += 64) {
|
|
for (int j = 0; j < 32; ++j) {
|
|
int l1 = L[n + j];
|
|
if (l1 > 15) {
|
|
l1 -= 16; qh[j] |= m1;
|
|
}
|
|
int l2 = L[n + j + 32];
|
|
if (l2 > 15) {
|
|
l2 -= 16; qh[j] |= m2;
|
|
}
|
|
ql[j] = l1 | (l2 << 4);
|
|
}
|
|
m1 <<= 2; m2 <<= 2;
|
|
ql += 32;
|
|
}
|
|
|
|
x += QK_K;
|
|
}
|
|
}
|
|
|
|
void dequantize_row_q5_K(const block_q5_K * restrict x, float * restrict y, int64_t k) {
|
|
assert(k % QK_K == 0);
|
|
const int64_t nb = k / QK_K;
|
|
|
|
for (int i = 0; i < nb; i++) {
|
|
const uint8_t * ql = x[i].qs;
|
|
const uint8_t * qh = x[i].qh;
|
|
|
|
const float d = GGML_FP16_TO_FP32(x[i].d);
|
|
const float min = GGML_FP16_TO_FP32(x[i].dmin);
|
|
|
|
int is = 0;
|
|
uint8_t sc, m;
|
|
uint8_t u1 = 1, u2 = 2;
|
|
for (int j = 0; j < QK_K; j += 64) {
|
|
get_scale_min_k4(is + 0, x[i].scales, &sc, &m);
|
|
const float d1 = d * sc; const float m1 = min * m;
|
|
get_scale_min_k4(is + 1, x[i].scales, &sc, &m);
|
|
const float d2 = d * sc; const float m2 = min * m;
|
|
for (int l = 0; l < 32; ++l) *y++ = d1 * ((ql[l] & 0xF) + (qh[l] & u1 ? 16 : 0)) - m1;
|
|
for (int l = 0; l < 32; ++l) *y++ = d2 * ((ql[l] >> 4) + (qh[l] & u2 ? 16 : 0)) - m2;
|
|
ql += 32; is += 2;
|
|
u1 <<= 2; u2 <<= 2;
|
|
}
|
|
}
|
|
}
|
|
|
|
static void quantize_row_q5_K_impl(const float * restrict x, block_q5_K * restrict y, int64_t n_per_row, const float * quant_weights) {
|
|
assert(n_per_row % QK_K == 0);
|
|
const int64_t nb = n_per_row / QK_K;
|
|
|
|
uint8_t L[QK_K];
|
|
uint8_t Laux[32];
|
|
uint8_t Ls[QK_K/32];
|
|
uint8_t Lm[QK_K/32];
|
|
float mins[QK_K/32];
|
|
float scales[QK_K/32];
|
|
float sw[QK_K/32];
|
|
float weights[32];
|
|
|
|
for (int i = 0; i < nb; i++) {
|
|
|
|
float sum_x2 = 0;
|
|
for (int l = 0; l < QK_K; ++l) sum_x2 += x[l] * x[l];
|
|
float sigma2 = 2*sum_x2/QK_K;
|
|
float av_x = sqrtf(sigma2);
|
|
|
|
for (int j = 0; j < QK_K/32; ++j) {
|
|
if (quant_weights) {
|
|
const float * qw = quant_weights + QK_K*i + 32*j;
|
|
for (int l = 0; l < 32; ++l) weights[l] = qw[l] * sqrtf(sigma2 + x[32*j + l]*x[32*j + l]);
|
|
} else {
|
|
for (int l = 0; l < 32; ++l) weights[l] = av_x + fabsf(x[32*j + l]);
|
|
}
|
|
float sumw = 0;
|
|
for (int l = 0; l < 32; ++l) sumw += weights[l];
|
|
sw[j] = sumw;
|
|
|
|
scales[j] = make_qkx3_quants(32, 31, x + 32*j, weights, L + 32*j, &mins[j], Laux, -0.9f, 0.05f, 36, false);
|
|
}
|
|
|
|
float d_block = make_qp_quants(QK_K/32, 63, scales, Ls, sw);
|
|
float m_block = make_qp_quants(QK_K/32, 63, mins, Lm, sw);
|
|
|
|
for (int j = 0; j < QK_K/32; ++j) {
|
|
uint8_t ls = Ls[j];
|
|
uint8_t lm = Lm[j];
|
|
ls = MIN(63, ls);
|
|
lm = MIN(63, lm);
|
|
if (j < 4) {
|
|
y[i].scales[j] = ls;
|
|
y[i].scales[j+4] = lm;
|
|
} else {
|
|
y[i].scales[j+4] = (ls & 0xF) | ((lm & 0xF) << 4);
|
|
y[i].scales[j-4] |= ((ls >> 4) << 6);
|
|
y[i].scales[j-0] |= ((lm >> 4) << 6);
|
|
}
|
|
}
|
|
y[i].d = GGML_FP32_TO_FP16(d_block);
|
|
y[i].dmin = GGML_FP32_TO_FP16(m_block);
|
|
|
|
uint8_t sc, m;
|
|
for (int j = 0; j < QK_K/32; ++j) {
|
|
get_scale_min_k4(j, y[i].scales, &sc, &m);
|
|
const float d = GGML_FP16_TO_FP32(y[i].d) * sc;
|
|
if (!d) continue;
|
|
const float dm = GGML_FP16_TO_FP32(y[i].dmin) * m;
|
|
for (int ii = 0; ii < 32; ++ii) {
|
|
int l = nearest_int((x[32*j + ii] + dm)/d);
|
|
l = MAX(0, MIN(31, l));
|
|
L[32*j + ii] = l;
|
|
}
|
|
}
|
|
|
|
uint8_t * restrict qh = y[i].qh;
|
|
uint8_t * restrict ql = y[i].qs;
|
|
memset(qh, 0, QK_K/8);
|
|
|
|
uint8_t m1 = 1, m2 = 2;
|
|
for (int n = 0; n < QK_K; n += 64) {
|
|
for (int j = 0; j < 32; ++j) {
|
|
int l1 = L[n + j];
|
|
if (l1 > 15) {
|
|
l1 -= 16; qh[j] |= m1;
|
|
}
|
|
int l2 = L[n + j + 32];
|
|
if (l2 > 15) {
|
|
l2 -= 16; qh[j] |= m2;
|
|
}
|
|
ql[j] = l1 | (l2 << 4);
|
|
}
|
|
m1 <<= 2; m2 <<= 2;
|
|
ql += 32;
|
|
}
|
|
|
|
x += QK_K;
|
|
|
|
}
|
|
}
|
|
|
|
size_t quantize_q5_K(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
|
|
size_t row_size = ggml_row_size(GGML_TYPE_Q5_K, n_per_row);
|
|
if (!quant_weights) {
|
|
quantize_row_q5_K_ref(src, dst, (int64_t)nrow*n_per_row);
|
|
}
|
|
else {
|
|
char * qrow = (char *)dst;
|
|
for (int64_t row = 0; row < nrow; ++row) {
|
|
quantize_row_q5_K_impl(src, (block_q5_K*)qrow, n_per_row, quant_weights);
|
|
src += n_per_row;
|
|
qrow += row_size;
|
|
}
|
|
}
|
|
return nrow * row_size;
|
|
}
|
|
|
|
// ====================== 6-bit (de)-quantization
|
|
|
|
void quantize_row_q6_K_ref(const float * restrict x, block_q6_K * restrict y, int64_t k) {
|
|
assert(k % QK_K == 0);
|
|
const int64_t nb = k / QK_K;
|
|
|
|
int8_t L[QK_K];
|
|
float scales[QK_K/16];
|
|
|
|
for (int i = 0; i < nb; i++) {
|
|
|
|
float max_scale = 0;
|
|
float max_abs_scale = 0;
|
|
|
|
for (int ib = 0; ib < QK_K/16; ++ib) {
|
|
|
|
const float scale = make_qx_quants(16, 32, x + 16*ib, L + 16*ib, 1, NULL);
|
|
scales[ib] = scale;
|
|
|
|
const float abs_scale = fabsf(scale);
|
|
if (abs_scale > max_abs_scale) {
|
|
max_abs_scale = abs_scale;
|
|
max_scale = scale;
|
|
}
|
|
|
|
}
|
|
|
|
if (max_abs_scale < GROUP_MAX_EPS) {
|
|
memset(&y[i], 0, sizeof(block_q6_K));
|
|
y[i].d = GGML_FP32_TO_FP16(0.f);
|
|
x += QK_K;
|
|
continue;
|
|
}
|
|
|
|
float iscale = -128.f/max_scale;
|
|
y[i].d = GGML_FP32_TO_FP16(1/iscale);
|
|
for (int ib = 0; ib < QK_K/16; ++ib) {
|
|
y[i].scales[ib] = MIN(127, nearest_int(iscale*scales[ib]));
|
|
}
|
|
|
|
for (int j = 0; j < QK_K/16; ++j) {
|
|
float d = GGML_FP16_TO_FP32(y[i].d) * y[i].scales[j];
|
|
if (!d) {
|
|
continue;
|
|
}
|
|
for (int ii = 0; ii < 16; ++ii) {
|
|
int l = nearest_int(x[16*j + ii]/d);
|
|
l = MAX(-32, MIN(31, l));
|
|
L[16*j + ii] = l + 32;
|
|
}
|
|
}
|
|
|
|
uint8_t * restrict ql = y[i].ql;
|
|
uint8_t * restrict qh = y[i].qh;
|
|
for (int j = 0; j < QK_K; j += 128) {
|
|
for (int l = 0; l < 32; ++l) {
|
|
const uint8_t q1 = L[j + l + 0] & 0xF;
|
|
const uint8_t q2 = L[j + l + 32] & 0xF;
|
|
const uint8_t q3 = L[j + l + 64] & 0xF;
|
|
const uint8_t q4 = L[j + l + 96] & 0xF;
|
|
ql[l+ 0] = q1 | (q3 << 4);
|
|
ql[l+32] = q2 | (q4 << 4);
|
|
qh[l] = (L[j + l] >> 4) | ((L[j + l + 32] >> 4) << 2) | ((L[j + l + 64] >> 4) << 4) | ((L[j + l + 96] >> 4) << 6);
|
|
}
|
|
ql += 64;
|
|
qh += 32;
|
|
}
|
|
|
|
x += QK_K;
|
|
}
|
|
}
|
|
|
|
void dequantize_row_q6_K(const block_q6_K * restrict x, float * restrict y, int64_t k) {
|
|
assert(k % QK_K == 0);
|
|
const int64_t nb = k / QK_K;
|
|
|
|
for (int i = 0; i < nb; i++) {
|
|
const float d = GGML_FP16_TO_FP32(x[i].d);
|
|
|
|
const uint8_t * restrict ql = x[i].ql;
|
|
const uint8_t * restrict qh = x[i].qh;
|
|
const int8_t * restrict sc = x[i].scales;
|
|
|
|
for (int n = 0; n < QK_K; n += 128) {
|
|
for (int l = 0; l < 32; ++l) {
|
|
int is = l/16;
|
|
const int8_t q1 = (int8_t)((ql[l + 0] & 0xF) | (((qh[l] >> 0) & 3) << 4)) - 32;
|
|
const int8_t q2 = (int8_t)((ql[l + 32] & 0xF) | (((qh[l] >> 2) & 3) << 4)) - 32;
|
|
const int8_t q3 = (int8_t)((ql[l + 0] >> 4) | (((qh[l] >> 4) & 3) << 4)) - 32;
|
|
const int8_t q4 = (int8_t)((ql[l + 32] >> 4) | (((qh[l] >> 6) & 3) << 4)) - 32;
|
|
y[l + 0] = d * sc[is + 0] * q1;
|
|
y[l + 32] = d * sc[is + 2] * q2;
|
|
y[l + 64] = d * sc[is + 4] * q3;
|
|
y[l + 96] = d * sc[is + 6] * q4;
|
|
}
|
|
y += 128;
|
|
ql += 64;
|
|
qh += 32;
|
|
sc += 8;
|
|
}
|
|
}
|
|
}
|
|
|
|
static void quantize_row_q6_K_impl(const float * restrict x, block_q6_K * restrict y, int64_t n_per_row, const float * quant_weights) {
|
|
assert(n_per_row % QK_K == 0);
|
|
const int64_t nb = n_per_row / QK_K;
|
|
|
|
int8_t L[QK_K];
|
|
float scales[QK_K/16];
|
|
//float weights[16];
|
|
|
|
for (int i = 0; i < nb; i++) {
|
|
|
|
//float sum_x2 = 0;
|
|
//for (int j = 0; j < QK_K; ++j) sum_x2 += x[j]*x[j];
|
|
//float sigma2 = sum_x2/QK_K;
|
|
|
|
float max_scale = 0;
|
|
float max_abs_scale = 0;
|
|
|
|
for (int ib = 0; ib < QK_K/16; ++ib) {
|
|
|
|
float scale;
|
|
if (quant_weights) {
|
|
const float * qw = quant_weights + QK_K*i + 16*ib;
|
|
//for (int j = 0; j < 16; ++j) weights[j] = qw[j] * sqrtf(sigma2 + x[16*ib + j]*x[16*ib + j]);
|
|
//scale = make_qx_quants(16, 32, x + 16*ib, L + 16*ib, 1, weights);
|
|
scale = make_qx_quants(16, 32, x + 16*ib, L + 16*ib, 1, qw);
|
|
} else {
|
|
scale = make_qx_quants(16, 32, x + 16*ib, L + 16*ib, 1, NULL);
|
|
}
|
|
scales[ib] = scale;
|
|
|
|
const float abs_scale = fabsf(scale);
|
|
if (abs_scale > max_abs_scale) {
|
|
max_abs_scale = abs_scale;
|
|
max_scale = scale;
|
|
}
|
|
|
|
}
|
|
|
|
if (max_abs_scale < GROUP_MAX_EPS) {
|
|
memset(&y[i], 0, sizeof(block_q6_K));
|
|
y[i].d = GGML_FP32_TO_FP16(0.f);
|
|
x += QK_K;
|
|
continue;
|
|
}
|
|
|
|
float iscale = -128.f/max_scale;
|
|
y[i].d = GGML_FP32_TO_FP16(1/iscale);
|
|
for (int ib = 0; ib < QK_K/16; ++ib) {
|
|
y[i].scales[ib] = MIN(127, nearest_int(iscale*scales[ib]));
|
|
}
|
|
|
|
for (int j = 0; j < QK_K/16; ++j) {
|
|
float d = GGML_FP16_TO_FP32(y[i].d) * y[i].scales[j];
|
|
if (!d) {
|
|
continue;
|
|
}
|
|
for (int ii = 0; ii < 16; ++ii) {
|
|
int l = nearest_int(x[16*j + ii]/d);
|
|
l = MAX(-32, MIN(31, l));
|
|
L[16*j + ii] = l + 32;
|
|
}
|
|
}
|
|
|
|
uint8_t * restrict ql = y[i].ql;
|
|
uint8_t * restrict qh = y[i].qh;
|
|
for (int j = 0; j < QK_K; j += 128) {
|
|
for (int l = 0; l < 32; ++l) {
|
|
const uint8_t q1 = L[j + l + 0] & 0xF;
|
|
const uint8_t q2 = L[j + l + 32] & 0xF;
|
|
const uint8_t q3 = L[j + l + 64] & 0xF;
|
|
const uint8_t q4 = L[j + l + 96] & 0xF;
|
|
ql[l+ 0] = q1 | (q3 << 4);
|
|
ql[l+32] = q2 | (q4 << 4);
|
|
qh[l] = (L[j + l] >> 4) | ((L[j + l + 32] >> 4) << 2) | ((L[j + l + 64] >> 4) << 4) | ((L[j + l + 96] >> 4) << 6);
|
|
}
|
|
ql += 64;
|
|
qh += 32;
|
|
}
|
|
|
|
x += QK_K;
|
|
|
|
}
|
|
}
|
|
|
|
size_t quantize_q6_K(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
|
|
size_t row_size = ggml_row_size(GGML_TYPE_Q6_K, n_per_row);
|
|
if (!quant_weights) {
|
|
quantize_row_q6_K_ref(src, dst, (int64_t)nrow*n_per_row);
|
|
}
|
|
else {
|
|
char * qrow = (char *)dst;
|
|
for (int64_t row = 0; row < nrow; ++row) {
|
|
quantize_row_q6_K_impl(src, (block_q6_K*)qrow, n_per_row, quant_weights);
|
|
src += n_per_row;
|
|
qrow += row_size;
|
|
}
|
|
}
|
|
return nrow * row_size;
|
|
}
|
|
|
|
static void quantize_row_q4_0_impl(const float * restrict x, block_q4_0 * restrict y, int64_t n_per_row, const float * quant_weights) {
|
|
static_assert(QK4_0 == 32, "QK4_0 must be 32");
|
|
|
|
if (!quant_weights) {
|
|
quantize_row_q4_0_ref(x, y, n_per_row);
|
|
return;
|
|
}
|
|
|
|
float weight[QK4_0];
|
|
int8_t L[QK4_0];
|
|
|
|
float sum_x2 = 0;
|
|
for (int j = 0; j < n_per_row; ++j) sum_x2 += x[j]*x[j];
|
|
float sigma2 = sum_x2/n_per_row;
|
|
|
|
const int64_t nb = n_per_row/QK4_0;
|
|
for (int ib = 0; ib < nb; ++ib) {
|
|
const float * xb = x + QK4_0 * ib;
|
|
const float * qw = quant_weights + QK4_0 * ib;
|
|
for (int j = 0; j < QK4_0; ++j) weight[j] = qw[j] * sqrtf(sigma2 + xb[j]*xb[j]);
|
|
float d = make_qx_quants(QK4_0, 8, xb, L, 1, weight);
|
|
y[ib].d = GGML_FP32_TO_FP16(d);
|
|
for (int j = 0; j < 16; ++j) {
|
|
y[ib].qs[j] = L[j] | (L[j+16] << 4);
|
|
}
|
|
}
|
|
}
|
|
|
|
size_t quantize_q4_0(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
|
|
if (!quant_weights) {
|
|
quantize_row_q4_0_ref(src, dst, (int64_t)nrow*n_per_row);
|
|
return nrow * ggml_row_size(GGML_TYPE_Q4_0, n_per_row);
|
|
}
|
|
size_t row_size = ggml_row_size(GGML_TYPE_Q4_0, n_per_row);
|
|
char * qrow = (char *)dst;
|
|
for (int64_t row = 0; row < nrow; ++row) {
|
|
quantize_row_q4_0_impl(src, (block_q4_0*)qrow, n_per_row, quant_weights);
|
|
src += n_per_row;
|
|
qrow += row_size;
|
|
}
|
|
return nrow * row_size;
|
|
}
|
|
|
|
static void quantize_row_q4_1_impl(const float * restrict x, block_q4_1 * restrict y, int64_t n_per_row, const float * quant_weights) {
|
|
static_assert(QK4_1 == 32, "QK4_1 must be 32");
|
|
|
|
if (!quant_weights) {
|
|
quantize_row_q4_1_ref(x, y, n_per_row);
|
|
return;
|
|
}
|
|
|
|
float weight[QK4_1];
|
|
uint8_t L[QK4_1], Laux[QK4_1];
|
|
|
|
float sum_x2 = 0;
|
|
for (int j = 0; j < n_per_row; ++j) sum_x2 += x[j]*x[j];
|
|
float sigma2 = sum_x2/n_per_row;
|
|
|
|
const int64_t nb = n_per_row/QK4_1;
|
|
for (int ib = 0; ib < nb; ++ib) {
|
|
const float * xb = x + QK4_1 * ib;
|
|
const float * qw = quant_weights + QK4_1 * ib;
|
|
for (int j = 0; j < QK4_1; ++j) weight[j] = qw[j] * sqrtf(sigma2 + xb[j]*xb[j]);
|
|
float min;
|
|
float d = make_qkx3_quants(QK4_1, 15, xb, weight, L, &min, Laux, -0.9f, 0.05f, 36, false);
|
|
y[ib].d = GGML_FP32_TO_FP16(d);
|
|
y[ib].m = GGML_FP32_TO_FP16(-min);
|
|
for (int j = 0; j < 16; ++j) {
|
|
y[ib].qs[j] = L[j] | (L[j+16] << 4);
|
|
}
|
|
}
|
|
}
|
|
|
|
size_t quantize_q4_1(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
|
|
if (!quant_weights) {
|
|
quantize_row_q4_1_ref(src, dst, (int64_t)nrow*n_per_row);
|
|
return nrow * ggml_row_size(GGML_TYPE_Q4_1, n_per_row);
|
|
}
|
|
size_t row_size = ggml_row_size(GGML_TYPE_Q4_1, n_per_row);
|
|
char * qrow = (char *)dst;
|
|
for (int64_t row = 0; row < nrow; ++row) {
|
|
quantize_row_q4_1_impl(src, (block_q4_1*)qrow, n_per_row, quant_weights);
|
|
src += n_per_row;
|
|
qrow += row_size;
|
|
}
|
|
return nrow * row_size;
|
|
}
|
|
|
|
static void quantize_row_q5_0_impl(const float * restrict x, block_q5_0 * restrict y, int64_t n_per_row, const float * quant_weights) {
|
|
static_assert(QK5_0 == 32, "QK5_0 must be 32");
|
|
|
|
if (!quant_weights) {
|
|
quantize_row_q5_0_ref(x, y, n_per_row);
|
|
return;
|
|
}
|
|
|
|
float weight[QK5_0];
|
|
int8_t L[QK5_0];
|
|
|
|
float sum_x2 = 0;
|
|
for (int j = 0; j < n_per_row; ++j) sum_x2 += x[j]*x[j];
|
|
float sigma2 = sum_x2/n_per_row;
|
|
|
|
const int64_t nb = n_per_row/QK5_0;
|
|
for (int ib = 0; ib < nb; ++ib) {
|
|
const float * xb = x + QK5_0 * ib;
|
|
const float * qw = quant_weights + QK5_0 * ib;
|
|
for (int j = 0; j < QK5_0; ++j) weight[j] = qw[j] * sqrtf(sigma2 + xb[j]*xb[j]);
|
|
float d = make_qx_quants(QK5_0, 16, xb, L, 1, weight);
|
|
y[ib].d = GGML_FP32_TO_FP16(d);
|
|
|
|
uint32_t qh = 0;
|
|
|
|
for (int j = 0; j < 16; ++j) {
|
|
const uint8_t xi0 = L[j];
|
|
const uint8_t xi1 = L[j+16];
|
|
y[ib].qs[j] = (xi0 & 0x0F) | ((xi1 & 0x0F) << 4);
|
|
|
|
// get the 5-th bit and store it in qh at the right position
|
|
qh |= ((xi0 & 0x10u) >> 4) << (j + 0);
|
|
qh |= ((xi1 & 0x10u) >> 4) << (j + QK5_0/2);
|
|
}
|
|
|
|
memcpy(&y[ib].qh, &qh, sizeof(qh));
|
|
}
|
|
}
|
|
|
|
size_t quantize_q5_0(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
|
|
if (!quant_weights) {
|
|
quantize_row_q5_0_ref(src, dst, (int64_t)nrow*n_per_row);
|
|
return nrow * ggml_row_size(GGML_TYPE_Q5_0, n_per_row);
|
|
}
|
|
size_t row_size = ggml_row_size(GGML_TYPE_Q5_0, n_per_row);
|
|
char * qrow = (char *)dst;
|
|
for (int64_t row = 0; row < nrow; ++row) {
|
|
quantize_row_q5_0_impl(src, (block_q5_0*)qrow, n_per_row, quant_weights);
|
|
src += n_per_row;
|
|
qrow += row_size;
|
|
}
|
|
return nrow * row_size;
|
|
}
|
|
|
|
static void quantize_row_q5_1_impl(const float * restrict x, block_q5_1 * restrict y, int64_t n_per_row, const float * quant_weights) {
|
|
static_assert(QK5_1 == 32, "QK5_1 must be 32");
|
|
|
|
if (!quant_weights) {
|
|
quantize_row_q5_1_ref(x, y, n_per_row);
|
|
return;
|
|
}
|
|
|
|
float weight[QK5_1];
|
|
uint8_t L[QK5_1], Laux[QK5_1];
|
|
|
|
float sum_x2 = 0;
|
|
for (int j = 0; j < n_per_row; ++j) sum_x2 += x[j]*x[j];
|
|
float sigma2 = sum_x2/n_per_row;
|
|
|
|
const int64_t nb = n_per_row/QK5_1;
|
|
for (int ib = 0; ib < nb; ++ib) {
|
|
const float * xb = x + QK5_1 * ib;
|
|
const float * qw = quant_weights + QK5_1 * ib;
|
|
for (int j = 0; j < QK5_1; ++j) weight[j] = qw[j] * sqrtf(sigma2 + xb[j]*xb[j]);
|
|
float min;
|
|
float d = make_qkx3_quants(QK5_1, 31, xb, weight, L, &min, Laux, -0.9f, 0.05f, 36, false);
|
|
y[ib].d = GGML_FP32_TO_FP16(d);
|
|
y[ib].m = GGML_FP32_TO_FP16(-min);
|
|
|
|
uint32_t qh = 0;
|
|
for (int j = 0; j < 16; ++j) {
|
|
const uint8_t xi0 = L[j];
|
|
const uint8_t xi1 = L[j+16];
|
|
y[ib].qs[j] = (xi0 & 0x0F) | ((xi1 & 0x0F) << 4);
|
|
// get the 5-th bit and store it in qh at the right position
|
|
qh |= ((xi0 & 0x10u) >> 4) << (j + 0);
|
|
qh |= ((xi1 & 0x10u) >> 4) << (j + QK5_0/2);
|
|
}
|
|
memcpy(&y[ib].qh, &qh, sizeof(qh));
|
|
}
|
|
}
|
|
|
|
size_t quantize_q5_1(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
|
|
if (!quant_weights) {
|
|
quantize_row_q5_1_ref(src, dst, (int64_t)nrow*n_per_row);
|
|
return nrow * ggml_row_size(GGML_TYPE_Q5_1, n_per_row);
|
|
}
|
|
size_t row_size = ggml_row_size(GGML_TYPE_Q5_1, n_per_row);
|
|
char * qrow = (char *)dst;
|
|
for (int64_t row = 0; row < nrow; ++row) {
|
|
quantize_row_q5_1_impl(src, (block_q5_1*)qrow, n_per_row, quant_weights);
|
|
src += n_per_row;
|
|
qrow += row_size;
|
|
}
|
|
return nrow * row_size;
|
|
}
|
|
|
|
size_t quantize_q8_0(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
|
|
(void)quant_weights; // not used
|
|
const size_t row_size = ggml_row_size(GGML_TYPE_Q8_0, n_per_row);
|
|
quantize_row_q8_0_ref(src, dst, (int64_t)nrow*n_per_row);
|
|
return nrow * row_size;
|
|
}
|
|
|
|
// ====================== Ternary (de)-quantization (BitNet b1.58 and TriLMs)
|
|
|
|
void quantize_row_tq1_0_ref(const float * restrict x, block_tq1_0 * restrict y, int64_t k) {
|
|
assert(k % QK_K == 0);
|
|
const int64_t nb = k / QK_K;
|
|
|
|
for (int64_t i = 0; i < nb; i++) {
|
|
float amax = 0.0f; // absolute max
|
|
|
|
for (int j = 0; j < QK_K; j++) {
|
|
const float v = x[j];
|
|
amax = MAX(amax, fabsf(v));
|
|
}
|
|
|
|
const float d = amax;
|
|
const float id = d ? 1.0f/d : 0.0f;
|
|
|
|
y[i].d = GGML_FP32_TO_FP16(d);
|
|
|
|
// 5 elements per byte, along 32 bytes
|
|
for (size_t j = 0; j < sizeof(y->qs) - sizeof(y->qs) % 32; j += 32) {
|
|
for (size_t m = 0; m < 32; ++m) {
|
|
uint8_t q = 0;
|
|
for (size_t n = 0; n < 5; ++n) {
|
|
int xi = lroundf(x[m + n*32] * id) + 1; // -1, 0, 1 -> 0, 1, 2
|
|
q *= 3;
|
|
q += xi;
|
|
}
|
|
// ceiling division (243 == pow(3, 5))
|
|
q = ((uint16_t)q * 256 + (243 - 1)) / 243;
|
|
y[i].qs[j + m] = q;
|
|
}
|
|
x += 5*32;
|
|
}
|
|
// along 16 bytes
|
|
for (size_t j = sizeof(y->qs) - sizeof(y->qs) % 32; j < sizeof(y->qs); j += 16) {
|
|
for (size_t m = 0; m < 16; ++m) {
|
|
uint8_t q = 0;
|
|
for (size_t n = 0; n < 5; ++n) {
|
|
int xi = lroundf(x[m + n*16] * id) + 1; // -1, 0, 1 -> 0, 1, 2
|
|
q *= 3;
|
|
q += xi;
|
|
}
|
|
// ceiling division (243 == pow(3, 5))
|
|
q = ((uint16_t)q * 256 + (243 - 1)) / 243;
|
|
y[i].qs[j + m] = q;
|
|
}
|
|
x += 5*16;
|
|
}
|
|
// 4 elements per byte
|
|
for (size_t j = 0; j < sizeof(y->qh); ++j) {
|
|
uint8_t q = 0;
|
|
for (size_t m = 0; m < 4; ++m) {
|
|
// -1, 0, 1 -> 0, 1, 2
|
|
int xi = lroundf(x[j + m*sizeof(y->qh)] * id) + 1;
|
|
q *= 3;
|
|
q += xi;
|
|
}
|
|
// shift the first value to the most significant trit
|
|
q *= 3;
|
|
// ceiling division (243 == pow(3, 5))
|
|
q = ((uint16_t)q * 256 + (243 - 1)) / 243;
|
|
y[i].qh[j] = q;
|
|
}
|
|
x += 4*sizeof(y->qh);
|
|
}
|
|
}
|
|
|
|
void quantize_row_tq2_0_ref(const float * restrict x, block_tq2_0 * restrict y, int64_t k) {
|
|
assert(k % QK_K == 0);
|
|
const int64_t nb = k / QK_K;
|
|
|
|
for (int64_t i = 0; i < nb; i++) {
|
|
float amax = 0.0f; // absolute max
|
|
|
|
for (int j = 0; j < QK_K; j++) {
|
|
const float v = x[j];
|
|
amax = MAX(amax, fabsf(v));
|
|
}
|
|
|
|
const float d = amax;
|
|
const float id = d ? 1.0f/d : 0.0f;
|
|
|
|
y[i].d = GGML_FP32_TO_FP16(d);
|
|
|
|
for (size_t j = 0; j < sizeof(y->qs); j += 32) {
|
|
for (size_t m = 0; m < 32; ++m) {
|
|
uint8_t q = 0;
|
|
for (size_t n = 0; n < 4; ++n) {
|
|
// -1, 0, 1 -> 0, 1, 2
|
|
int xi = lroundf(x[m + n*32] * id) + 1;
|
|
q += (xi & 3) << (2*n);
|
|
}
|
|
y[i].qs[j + m] = q;
|
|
}
|
|
x += 4*32;
|
|
}
|
|
}
|
|
}
|
|
|
|
size_t quantize_tq1_0(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
|
|
(void)quant_weights; // not used
|
|
const size_t row_size = ggml_row_size(GGML_TYPE_TQ1_0, n_per_row);
|
|
quantize_row_tq1_0_ref(src, dst, (int64_t)nrow*n_per_row);
|
|
return nrow * row_size;
|
|
}
|
|
|
|
size_t quantize_tq2_0(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
|
|
(void)quant_weights; // not used
|
|
const size_t row_size = ggml_row_size(GGML_TYPE_TQ2_0, n_per_row);
|
|
quantize_row_tq2_0_ref(src, dst, (int64_t)nrow*n_per_row);
|
|
return nrow * row_size;
|
|
}
|
|
|
|
void dequantize_row_tq1_0(const block_tq1_0 * restrict x, float * restrict y, int64_t k) {
|
|
assert(k % QK_K == 0);
|
|
const int64_t nb = k / QK_K;
|
|
|
|
const uint8_t pow3[6] = {1, 3, 9, 27, 81, 243};
|
|
|
|
for (int64_t i = 0; i < nb; ++i) {
|
|
|
|
const float d = GGML_FP16_TO_FP32(x[i].d);
|
|
|
|
for (size_t j = 0; j < sizeof(x->qs) - sizeof(x->qs) % 32; j += 32) {
|
|
for (size_t n = 0; n < 5; ++n) {
|
|
for (size_t m = 0; m < 32; ++m) {
|
|
uint8_t q = x[i].qs[j + m] * pow3[n];
|
|
int16_t xi = ((uint16_t) q * 3) >> 8;
|
|
*y++ = (float) (xi - 1) * d;
|
|
}
|
|
}
|
|
}
|
|
for (size_t j = sizeof(x->qs) - sizeof(x->qs) % 32; j < sizeof(x->qs); j += 16) {
|
|
for (size_t n = 0; n < 5; ++n) {
|
|
for (size_t m = 0; m < 16; ++m) {
|
|
uint8_t q = x[i].qs[j + m] * pow3[n];
|
|
int16_t xi = ((uint16_t) q * 3) >> 8;
|
|
*y++ = (float) (xi - 1) * d;
|
|
}
|
|
}
|
|
}
|
|
|
|
for (size_t n = 0; n < 4; ++n) {
|
|
for (size_t j = 0; j < sizeof(x->qh); ++j) {
|
|
uint8_t q = x[i].qh[j] * pow3[n];
|
|
int16_t xi = ((uint16_t) q * 3) >> 8;
|
|
*y++ = (float) (xi - 1) * d;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
void dequantize_row_tq2_0(const block_tq2_0 * restrict x, float * restrict y, int64_t k) {
|
|
assert(k % QK_K == 0);
|
|
const int64_t nb = k / QK_K;
|
|
|
|
for (int64_t i = 0; i < nb; ++i) {
|
|
|
|
const float d = GGML_FP16_TO_FP32(x[i].d);
|
|
|
|
for (size_t j = 0; j < sizeof(x->qs); j += 32) {
|
|
for (size_t l = 0; l < 4; ++l) {
|
|
for (size_t m = 0; m < 32; ++m) {
|
|
int8_t q = (x[i].qs[j + m] >> (l*2)) & 3;
|
|
*y++ = (float) (q - 1) * d;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
// ====================== "True" 2-bit (de)-quantization
|
|
|
|
void dequantize_row_iq2_xxs(const block_iq2_xxs * restrict x, float * restrict y, int64_t k) {
|
|
assert(k % QK_K == 0);
|
|
const int64_t nb = k / QK_K;
|
|
|
|
uint32_t aux32[2];
|
|
const uint8_t * aux8 = (const uint8_t *)aux32;
|
|
|
|
for (int i = 0; i < nb; i++) {
|
|
|
|
const float d = GGML_FP16_TO_FP32(x[i].d);
|
|
|
|
for (int ib32 = 0; ib32 < QK_K/32; ++ib32) {
|
|
memcpy(aux32, x[i].qs + 4*ib32, 2*sizeof(uint32_t));
|
|
const float db = d * (0.5f + (aux32[1] >> 28)) * 0.25f;
|
|
for (int l = 0; l < 4; ++l) {
|
|
const uint8_t * grid = (const uint8_t *)(iq2xxs_grid + aux8[l]);
|
|
const uint8_t signs = ksigns_iq2xs[(aux32[1] >> 7*l) & 127];
|
|
for (int j = 0; j < 8; ++j) {
|
|
y[j] = db * grid[j] * (signs & kmask_iq2xs[j] ? -1.f : 1.f);
|
|
}
|
|
y += 8;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
// ====================== 2.3125 bpw (de)-quantization
|
|
|
|
void dequantize_row_iq2_xs(const block_iq2_xs * restrict x, float * restrict y, int64_t k) {
|
|
assert(k % QK_K == 0);
|
|
const int64_t nb = k / QK_K;
|
|
|
|
float db[2];
|
|
|
|
for (int i = 0; i < nb; i++) {
|
|
|
|
const float d = GGML_FP16_TO_FP32(x[i].d);
|
|
|
|
for (int ib32 = 0; ib32 < QK_K/32; ++ib32) {
|
|
db[0] = d * (0.5f + (x[i].scales[ib32] & 0xf)) * 0.25f;
|
|
db[1] = d * (0.5f + (x[i].scales[ib32] >> 4)) * 0.25f;
|
|
for (int l = 0; l < 4; ++l) {
|
|
const uint8_t * grid = (const uint8_t *)(iq2xs_grid + (x[i].qs[4*ib32 + l] & 511));
|
|
const uint8_t signs = ksigns_iq2xs[x[i].qs[4*ib32 + l] >> 9];
|
|
for (int j = 0; j < 8; ++j) {
|
|
y[j] = db[l/2] * grid[j] * (signs & kmask_iq2xs[j] ? -1.f : 1.f);
|
|
}
|
|
y += 8;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
// ====================== 2.5625 bpw (de)-quantization
|
|
|
|
void dequantize_row_iq2_s(const block_iq2_s * restrict x, float * restrict y, int64_t k) {
|
|
assert(k % QK_K == 0);
|
|
const int64_t nb = k / QK_K;
|
|
|
|
float db[2];
|
|
|
|
for (int i = 0; i < nb; i++) {
|
|
|
|
const float d = GGML_FP16_TO_FP32(x[i].d);
|
|
const uint8_t * qs = x[i].qs;
|
|
const uint8_t * qh = x[i].qh;
|
|
const uint8_t * signs = qs + QK_K/8;
|
|
|
|
for (int ib32 = 0; ib32 < QK_K/32; ++ib32) {
|
|
db[0] = d * (0.5f + (x[i].scales[ib32] & 0xf)) * 0.25f;
|
|
db[1] = d * (0.5f + (x[i].scales[ib32] >> 4)) * 0.25f;
|
|
for (int l = 0; l < 4; ++l) {
|
|
const float dl = db[l/2];
|
|
const uint8_t * grid = (const uint8_t *)(iq2s_grid + (qs[l] | (qh[ib32] << (8-2*l) & 0x300)));
|
|
for (int j = 0; j < 8; ++j) {
|
|
y[j] = dl * grid[j] * (signs[l] & kmask_iq2xs[j] ? -1.f : 1.f);
|
|
}
|
|
y += 8;
|
|
}
|
|
qs += 4;
|
|
signs += 4;
|
|
}
|
|
}
|
|
}
|
|
|
|
// ====================== 3.0625 bpw (de)-quantization
|
|
|
|
void dequantize_row_iq3_xxs(const block_iq3_xxs * restrict x, float * restrict y, int64_t k) {
|
|
assert(k % QK_K == 0);
|
|
const int64_t nb = k / QK_K;
|
|
|
|
uint32_t aux32;
|
|
|
|
for (int i = 0; i < nb; i++) {
|
|
|
|
const float d = GGML_FP16_TO_FP32(x[i].d);
|
|
const uint8_t * qs = x[i].qs;
|
|
const uint8_t * scales_and_signs = qs + QK_K/4;
|
|
|
|
for (int ib32 = 0; ib32 < QK_K/32; ++ib32) {
|
|
memcpy(&aux32, scales_and_signs + 4*ib32, sizeof(uint32_t));
|
|
const float db = d * (0.5f + (aux32 >> 28)) * 0.5f;
|
|
for (int l = 0; l < 4; ++l) {
|
|
const uint8_t signs = ksigns_iq2xs[(aux32 >> 7*l) & 127];
|
|
const uint8_t * grid1 = (const uint8_t *)(iq3xxs_grid + qs[2*l+0]);
|
|
const uint8_t * grid2 = (const uint8_t *)(iq3xxs_grid + qs[2*l+1]);
|
|
for (int j = 0; j < 4; ++j) {
|
|
y[j+0] = db * grid1[j] * (signs & kmask_iq2xs[j+0] ? -1.f : 1.f);
|
|
y[j+4] = db * grid2[j] * (signs & kmask_iq2xs[j+4] ? -1.f : 1.f);
|
|
}
|
|
y += 8;
|
|
}
|
|
qs += 8;
|
|
}
|
|
}
|
|
}
|
|
|
|
// ====================== 3.3125 bpw (de)-quantization
|
|
|
|
void dequantize_row_iq3_s(const block_iq3_s * restrict x, float * restrict y, int64_t k) {
|
|
assert(k % QK_K == 0);
|
|
const int64_t nb = k / QK_K;
|
|
|
|
for (int i = 0; i < nb; i++) {
|
|
|
|
const float d = GGML_FP16_TO_FP32(x[i].d);
|
|
const uint8_t * qs = x[i].qs;
|
|
const uint8_t * qh = x[i].qh;
|
|
const uint8_t * signs = x[i].signs;
|
|
|
|
for (int ib32 = 0; ib32 < QK_K/32; ib32 += 2) {
|
|
const float db1 = d * (1 + 2*(x[i].scales[ib32/2] & 0xf));
|
|
const float db2 = d * (1 + 2*(x[i].scales[ib32/2] >> 4));
|
|
for (int l = 0; l < 4; ++l) {
|
|
const uint8_t * grid1 = (const uint8_t *)(iq3s_grid + (qs[2*l+0] | ((qh[0] << (8-2*l)) & 256)));
|
|
const uint8_t * grid2 = (const uint8_t *)(iq3s_grid + (qs[2*l+1] | ((qh[0] << (7-2*l)) & 256)));
|
|
for (int j = 0; j < 4; ++j) {
|
|
y[j+0] = db1 * grid1[j] * (signs[l] & kmask_iq2xs[j+0] ? -1.f : 1.f);
|
|
y[j+4] = db1 * grid2[j] * (signs[l] & kmask_iq2xs[j+4] ? -1.f : 1.f);
|
|
}
|
|
y += 8;
|
|
}
|
|
qs += 8;
|
|
signs += 4;
|
|
for (int l = 0; l < 4; ++l) {
|
|
const uint8_t * grid1 = (const uint8_t *)(iq3s_grid + (qs[2*l+0] | ((qh[1] << (8-2*l)) & 256)));
|
|
const uint8_t * grid2 = (const uint8_t *)(iq3s_grid + (qs[2*l+1] | ((qh[1] << (7-2*l)) & 256)));
|
|
for (int j = 0; j < 4; ++j) {
|
|
y[j+0] = db2 * grid1[j] * (signs[l] & kmask_iq2xs[j+0] ? -1.f : 1.f);
|
|
y[j+4] = db2 * grid2[j] * (signs[l] & kmask_iq2xs[j+4] ? -1.f : 1.f);
|
|
}
|
|
y += 8;
|
|
}
|
|
qh += 2;
|
|
qs += 8;
|
|
signs += 4;
|
|
}
|
|
}
|
|
}
|
|
|
|
// ====================== 1.5625 bpw (de)-quantization
|
|
|
|
void dequantize_row_iq1_s(const block_iq1_s * restrict x, float * restrict y, int64_t k) {
|
|
assert(k % QK_K == 0);
|
|
const int64_t nb = k / QK_K;
|
|
|
|
for (int i = 0; i < nb; i++) {
|
|
|
|
const float d = GGML_FP16_TO_FP32(x[i].d);
|
|
const uint8_t * qs = x[i].qs;
|
|
const uint16_t * qh = x[i].qh;
|
|
|
|
for (int ib = 0; ib < QK_K/32; ++ib) {
|
|
const float dl = d * (2*((qh[ib] >> 12) & 7) + 1);
|
|
const float delta = qh[ib] & 0x8000 ? -IQ1S_DELTA : IQ1S_DELTA;
|
|
for (int l = 0; l < 4; ++l) {
|
|
const int8_t * grid = (const int8_t *)(iq1s_grid + (qs[l] | (((qh[ib] >> 3*l) & 7) << 8)));
|
|
for (int j = 0; j < 8; ++j) {
|
|
y[j] = dl * (grid[j] + delta);
|
|
}
|
|
y += 8;
|
|
}
|
|
qs += 4;
|
|
}
|
|
}
|
|
}
|
|
|
|
void dequantize_row_iq1_m(const block_iq1_m * restrict x, float * restrict y, int64_t k) {
|
|
assert(k % QK_K == 0);
|
|
const int64_t nb = k / QK_K;
|
|
|
|
float delta[4];
|
|
uint16_t idx[4];
|
|
|
|
iq1m_scale_t scale;
|
|
|
|
for (int i = 0; i < nb; i++) {
|
|
|
|
const uint16_t * sc = (const uint16_t *)x[i].scales;
|
|
scale.u16 = (sc[0] >> 12) | ((sc[1] >> 8) & 0x00f0) | ((sc[2] >> 4) & 0x0f00) | (sc[3] & 0xf000);
|
|
const float d = GGML_FP16_TO_FP32(scale.f16);
|
|
|
|
const uint8_t * qs = x[i].qs;
|
|
const uint8_t * qh = x[i].qh;
|
|
|
|
for (int ib = 0; ib < QK_K/32; ++ib) {
|
|
const float dl1 = d * (2*((sc[ib/2] >> (6*(ib%2)+0)) & 0x7) + 1);
|
|
const float dl2 = d * (2*((sc[ib/2] >> (6*(ib%2)+3)) & 0x7) + 1);
|
|
|
|
idx[0] = qs[0] | ((qh[0] << 8) & 0x700);
|
|
idx[1] = qs[1] | ((qh[0] << 4) & 0x700);
|
|
idx[2] = qs[2] | ((qh[1] << 8) & 0x700);
|
|
idx[3] = qs[3] | ((qh[1] << 4) & 0x700);
|
|
delta[0] = qh[0] & 0x08 ? -IQ1S_DELTA : IQ1S_DELTA;
|
|
delta[1] = qh[0] & 0x80 ? -IQ1S_DELTA : IQ1S_DELTA;
|
|
delta[2] = qh[1] & 0x08 ? -IQ1S_DELTA : IQ1S_DELTA;
|
|
delta[3] = qh[1] & 0x80 ? -IQ1S_DELTA : IQ1S_DELTA;
|
|
for (int l = 0; l < 2; ++l) {
|
|
const int8_t * grid = (const int8_t *)(iq1s_grid + idx[l]);
|
|
for (int j = 0; j < 8; ++j) {
|
|
y[j] = dl1 * (grid[j] + delta[l]);
|
|
}
|
|
y += 8;
|
|
}
|
|
for (int l = 2; l < 4; ++l) {
|
|
const int8_t * grid = (const int8_t *)(iq1s_grid + idx[l]);
|
|
for (int j = 0; j < 8; ++j) {
|
|
y[j] = dl2 * (grid[j] + delta[l]);
|
|
}
|
|
y += 8;
|
|
}
|
|
qs += 4;
|
|
qh += 2;
|
|
}
|
|
}
|
|
}
|
|
|
|
static const int8_t kvalues_iq4nl[16] = {-127, -104, -83, -65, -49, -35, -22, -10, 1, 13, 25, 38, 53, 69, 89, 113};
|
|
|
|
void dequantize_row_iq4_nl(const block_iq4_nl * restrict x, float * restrict y, int64_t k) {
|
|
assert(k % QK4_NL == 0);
|
|
const int64_t nb = k / QK4_NL;
|
|
|
|
for (int i = 0; i < nb; i++) {
|
|
|
|
const uint8_t * qs = x[i].qs;
|
|
|
|
const float d = GGML_FP16_TO_FP32(x[i].d);
|
|
for (int j = 0; j < QK4_NL/2; ++j) {
|
|
y[j+ 0] = d * kvalues_iq4nl[qs[j] & 0xf];
|
|
y[j+QK4_NL/2] = d * kvalues_iq4nl[qs[j] >> 4];
|
|
}
|
|
y += QK4_NL;
|
|
qs += QK4_NL/2;
|
|
}
|
|
}
|
|
|
|
void dequantize_row_iq4_xs(const block_iq4_xs * restrict x, float * restrict y, int64_t k) {
|
|
assert(k % QK_K == 0);
|
|
const int64_t nb = k / QK_K;
|
|
|
|
for (int i = 0; i < nb; i++) {
|
|
|
|
const uint8_t * qs = x[i].qs;
|
|
|
|
const float d = GGML_FP16_TO_FP32(x[i].d);
|
|
|
|
for (int ib = 0; ib < QK_K/32; ++ib) {
|
|
const int ls = ((x[i].scales_l[ib/2] >> 4*(ib%2)) & 0xf) | (((x[i].scales_h >> 2*ib) & 3) << 4);
|
|
const float dl = d * (ls - 32);
|
|
for (int j = 0; j < 16; ++j) {
|
|
y[j+ 0] = dl * kvalues_iq4nl[qs[j] & 0xf];
|
|
y[j+16] = dl * kvalues_iq4nl[qs[j] >> 4];
|
|
}
|
|
y += 32;
|
|
qs += 16;
|
|
}
|
|
}
|
|
}
|
|
|
|
//===================================== Q8_K ==============================================
|
|
|
|
void quantize_row_q8_K_ref(const float * restrict x, block_q8_K * restrict y, int64_t k) {
|
|
assert(k % QK_K == 0);
|
|
const int64_t nb = k / QK_K;
|
|
|
|
for (int i = 0; i < nb; i++) {
|
|
|
|
float max = 0;
|
|
float amax = 0;
|
|
for (int j = 0; j < QK_K; ++j) {
|
|
float ax = fabsf(x[j]);
|
|
if (ax > amax) {
|
|
amax = ax; max = x[j];
|
|
}
|
|
}
|
|
if (!amax) {
|
|
y[i].d = 0;
|
|
memset(y[i].qs, 0, QK_K);
|
|
x += QK_K;
|
|
continue;
|
|
}
|
|
//const float iscale = -128.f/max;
|
|
// We need this change for IQ2_XXS, else the AVX implementation becomes very awkward
|
|
const float iscale = -127.f/max;
|
|
for (int j = 0; j < QK_K; ++j) {
|
|
int v = nearest_int(iscale*x[j]);
|
|
y[i].qs[j] = MIN(127, v);
|
|
}
|
|
for (int j = 0; j < QK_K/16; ++j) {
|
|
int sum = 0;
|
|
for (int ii = 0; ii < 16; ++ii) {
|
|
sum += y[i].qs[j*16 + ii];
|
|
}
|
|
y[i].bsums[j] = sum;
|
|
}
|
|
y[i].d = 1/iscale;
|
|
x += QK_K;
|
|
}
|
|
}
|
|
|
|
void dequantize_row_q8_K(const block_q8_K * restrict x, float * restrict y, int64_t k) {
|
|
assert(k % QK_K == 0);
|
|
const int64_t nb = k / QK_K;
|
|
|
|
for (int i = 0; i < nb; i++) {
|
|
for (int j = 0; j < QK_K; ++j) {
|
|
*y++ = x[i].d * x[i].qs[j];
|
|
}
|
|
}
|
|
}
|
|
|
|
// ================================ IQ2 quantization =============================================
|
|
|
|
typedef struct {
|
|
uint64_t * grid;
|
|
int * map;
|
|
uint16_t * neighbours;
|
|
} iq2_entry_t;
|
|
|
|
static iq2_entry_t iq2_data[4] = {
|
|
{NULL, NULL, NULL},
|
|
{NULL, NULL, NULL},
|
|
{NULL, NULL, NULL},
|
|
{NULL, NULL, NULL},
|
|
};
|
|
|
|
static inline int iq2_data_index(enum ggml_type type) {
|
|
GGML_ASSERT(type == GGML_TYPE_IQ2_XXS || type == GGML_TYPE_IQ2_XS || type == GGML_TYPE_IQ1_S || type == GGML_TYPE_IQ1_M || type == GGML_TYPE_IQ2_S);
|
|
return type == GGML_TYPE_IQ2_XXS ? 0 :
|
|
type == GGML_TYPE_IQ2_XS ? 1 :
|
|
type == GGML_TYPE_IQ1_S || type == GGML_TYPE_IQ1_M ? 2 : 3;
|
|
}
|
|
|
|
static inline int iq2_grid_size(enum ggml_type type) {
|
|
GGML_ASSERT(type == GGML_TYPE_IQ2_XXS || type == GGML_TYPE_IQ2_XS || type == GGML_TYPE_IQ1_S || type == GGML_TYPE_IQ1_M || type == GGML_TYPE_IQ2_S);
|
|
return type == GGML_TYPE_IQ2_XXS ? 256 :
|
|
type == GGML_TYPE_IQ2_XS ? 512 :
|
|
type == GGML_TYPE_IQ1_S || type == GGML_TYPE_IQ1_M ? NGRID_IQ1S : 1024;
|
|
}
|
|
|
|
static int iq2_compare_func(const void * left, const void * right) {
|
|
const int * l = (const int *)left;
|
|
const int * r = (const int *)right;
|
|
return l[0] < r[0] ? -1 : l[0] > r[0] ? 1 : l[1] < r[1] ? -1 : l[1] > r[1] ? 1 : 0;
|
|
}
|
|
|
|
void iq2xs_init_impl(enum ggml_type type) {
|
|
const int gindex = iq2_data_index(type);
|
|
const int grid_size = iq2_grid_size(type);
|
|
if (iq2_data[gindex].grid) {
|
|
return;
|
|
}
|
|
static const uint16_t kgrid_2bit_256[256] = {
|
|
0, 2, 5, 8, 10, 17, 20, 32, 34, 40, 42, 65, 68, 80, 88, 97,
|
|
100, 128, 130, 138, 162, 257, 260, 272, 277, 320, 388, 408, 512, 514, 546, 642,
|
|
1025, 1028, 1040, 1057, 1060, 1088, 1090, 1096, 1120, 1153, 1156, 1168, 1188, 1280, 1282, 1288,
|
|
1312, 1350, 1385, 1408, 1425, 1545, 1552, 1600, 1668, 1700, 2048, 2053, 2056, 2068, 2088, 2113,
|
|
2116, 2128, 2130, 2184, 2308, 2368, 2562, 2580, 4097, 4100, 4112, 4129, 4160, 4192, 4228, 4240,
|
|
4245, 4352, 4360, 4384, 4432, 4442, 4480, 4644, 4677, 5120, 5128, 5152, 5157, 5193, 5248, 5400,
|
|
5474, 5632, 5654, 6145, 6148, 6160, 6208, 6273, 6400, 6405, 6560, 6737, 8192, 8194, 8202, 8260,
|
|
8289, 8320, 8322, 8489, 8520, 8704, 8706, 9217, 9220, 9232, 9280, 9302, 9472, 9537, 9572, 9872,
|
|
10248, 10272, 10388, 10820, 16385, 16388, 16400, 16408, 16417, 16420, 16448, 16456, 16470, 16480, 16513, 16516,
|
|
16528, 16640, 16672, 16737, 16768, 16773, 16897, 16912, 16968, 16982, 17000, 17408, 17416, 17440, 17536, 17561,
|
|
17682, 17700, 17920, 18433, 18436, 18448, 18496, 18501, 18688, 18776, 18785, 18818, 19013, 19088, 20480, 20488,
|
|
20497, 20505, 20512, 20608, 20616, 20740, 20802, 20900, 21137, 21648, 21650, 21770, 22017, 22100, 22528, 22545,
|
|
22553, 22628, 22848, 23048, 24580, 24592, 24640, 24680, 24832, 24917, 25112, 25184, 25600, 25605, 25872, 25874,
|
|
25988, 26690, 32768, 32770, 32778, 32833, 32898, 33028, 33048, 33088, 33297, 33793, 33796, 33808, 33813, 33856,
|
|
33888, 34048, 34118, 34196, 34313, 34368, 34400, 34818, 35076, 35345, 36868, 36880, 36900, 36928, 37025, 37142,
|
|
37248, 37445, 37888, 37922, 37956, 38225, 39041, 39200, 40962, 41040, 41093, 41225, 41472, 42008, 43088, 43268,
|
|
};
|
|
static const uint16_t kgrid_2bit_512[512] = {
|
|
0, 2, 5, 8, 10, 17, 20, 22, 25, 32, 34, 37, 40, 65, 68, 70,
|
|
73, 80, 82, 85, 88, 97, 100, 128, 130, 133, 136, 145, 148, 153, 160, 257,
|
|
260, 262, 265, 272, 274, 277, 280, 282, 289, 292, 320, 322, 325, 328, 337, 340,
|
|
352, 360, 385, 388, 400, 512, 514, 517, 520, 529, 532, 544, 577, 580, 592, 597,
|
|
640, 650, 1025, 1028, 1030, 1033, 1040, 1042, 1045, 1048, 1057, 1060, 1088, 1090, 1093, 1096,
|
|
1105, 1108, 1110, 1120, 1153, 1156, 1168, 1280, 1282, 1285, 1288, 1297, 1300, 1312, 1345, 1348,
|
|
1360, 1377, 1408, 1537, 1540, 1552, 1574, 1600, 1602, 1668, 2048, 2050, 2053, 2056, 2058, 2065,
|
|
2068, 2080, 2085, 2113, 2116, 2128, 2136, 2176, 2208, 2218, 2305, 2308, 2320, 2368, 2433, 2441,
|
|
2560, 2592, 2600, 2710, 2720, 4097, 4100, 4102, 4105, 4112, 4114, 4117, 4120, 4129, 4132, 4160,
|
|
4162, 4165, 4168, 4177, 4180, 4192, 4202, 4225, 4228, 4240, 4352, 4354, 4357, 4360, 4369, 4372,
|
|
4384, 4417, 4420, 4432, 4480, 4500, 4502, 4609, 4612, 4614, 4624, 4672, 4704, 5120, 5122, 5125,
|
|
5128, 5137, 5140, 5152, 5185, 5188, 5193, 5200, 5220, 5248, 5377, 5380, 5392, 5440, 5632, 5652,
|
|
5705, 6145, 6148, 6160, 6162, 6208, 6228, 6278, 6400, 6405, 6502, 6737, 6825, 8192, 8194, 8197,
|
|
8200, 8202, 8209, 8212, 8224, 8257, 8260, 8272, 8320, 8352, 8449, 8452, 8464, 8512, 8520, 8549,
|
|
8704, 8738, 8832, 8872, 9217, 9220, 9232, 9257, 9280, 9472, 9537, 9554, 9625, 9729, 9754, 9894,
|
|
10240, 10248, 10250, 10272, 10325, 10376, 10402, 10600, 10640, 10760, 10784, 10882, 10888, 10890, 16385, 16388,
|
|
16390, 16393, 16400, 16402, 16405, 16408, 16417, 16420, 16448, 16450, 16453, 16456, 16458, 16465, 16468, 16480,
|
|
16485, 16513, 16516, 16528, 16640, 16642, 16645, 16648, 16657, 16660, 16672, 16705, 16708, 16720, 16768, 16773,
|
|
16802, 16897, 16900, 16912, 16914, 16937, 16960, 17408, 17410, 17413, 17416, 17425, 17428, 17433, 17440, 17473,
|
|
17476, 17488, 17536, 17556, 17665, 17668, 17680, 17700, 17728, 17818, 17920, 17930, 17988, 18000, 18433, 18436,
|
|
18448, 18496, 18501, 18516, 18530, 18688, 18705, 18756, 18768, 18793, 18948, 20480, 20482, 20485, 20488, 20497,
|
|
20500, 20512, 20520, 20545, 20548, 20560, 20608, 20737, 20740, 20752, 20757, 20800, 20802, 20992, 21060, 21162,
|
|
21505, 21508, 21520, 21537, 21568, 21600, 21633, 21665, 21760, 21768, 21888, 21896, 22049, 22120, 22177, 22528,
|
|
22548, 22593, 22608, 22681, 22810, 22848, 22850, 23173, 24577, 24580, 24592, 24640, 24660, 24674, 24710, 24745,
|
|
24832, 25124, 25162, 25234, 25600, 25622, 25872, 25920, 25925, 26020, 26625, 26730, 26917, 27142, 27220, 27234,
|
|
32768, 32770, 32773, 32776, 32785, 32788, 32800, 32810, 32833, 32836, 32848, 32896, 32898, 32936, 32938, 33025,
|
|
33028, 33030, 33040, 33088, 33105, 33113, 33280, 33312, 33408, 33410, 33440, 33448, 33793, 33796, 33808, 33810,
|
|
33813, 33856, 33888, 33929, 34048, 34116, 34213, 34328, 34410, 34816, 34824, 34853, 34906, 34944, 34946, 34984,
|
|
35078, 35362, 35456, 35464, 35478, 35496, 36865, 36868, 36880, 36928, 36950, 36996, 37120, 37154, 37220, 37462,
|
|
37513, 37888, 37893, 37956, 37968, 37976, 38185, 38288, 38290, 38465, 38993, 39078, 39241, 39445, 39520, 40960,
|
|
40962, 40968, 40970, 40992, 41002, 41120, 41297, 41305, 41382, 41472, 41474, 41480, 41514, 41600, 41632, 42048,
|
|
42133, 42597, 42648, 43018, 43040, 43042, 43048, 43168, 43176, 43268, 43396, 43398, 43560, 43562, 43665, 43690,
|
|
};
|
|
static const uint16_t kgrid_1bit_2048[NGRID_IQ1S] = {
|
|
0, 2, 5, 8, 10, 17, 21, 32, 34, 40, 42, 69, 81, 84, 86, 101,
|
|
128, 130, 136, 138, 149, 160, 162, 168, 170, 260, 261, 273, 276, 278, 281, 282,
|
|
293, 321, 326, 329, 338, 341, 346, 353, 356, 358, 360, 389, 401, 404, 406, 421,
|
|
512, 514, 520, 522, 533, 544, 546, 552, 554, 581, 593, 601, 612, 617, 640, 642,
|
|
648, 650, 657, 661, 665, 672, 674, 680, 682, 1041, 1044, 1046, 1061, 1089, 1097, 1109,
|
|
1114, 1124, 1125, 1169, 1177, 1189, 1281, 1284, 1285, 1286, 1301, 1304, 1306, 1321, 1344, 1349,
|
|
1354, 1360, 1361, 1364, 1365, 1366, 1369, 1376, 1378, 1381, 1384, 1386, 1409, 1425, 1429, 1432,
|
|
1434, 1441, 1444, 1445, 1446, 1449, 1556, 1561, 1601, 1604, 1616, 1618, 1621, 1624, 1632, 1633,
|
|
1638, 1641, 1669, 1681, 1684, 1689, 2048, 2050, 2056, 2058, 2069, 2080, 2082, 2088, 2090, 2117,
|
|
2129, 2134, 2149, 2176, 2178, 2184, 2186, 2197, 2208, 2210, 2216, 2218, 2309, 2321, 2324, 2329,
|
|
2340, 2341, 2369, 2384, 2385, 2389, 2401, 2404, 2409, 2449, 2452, 2454, 2457, 2469, 2560, 2562,
|
|
2568, 2570, 2581, 2592, 2594, 2600, 2602, 2629, 2641, 2649, 2657, 2661, 2688, 2690, 2693, 2696,
|
|
2698, 2709, 2720, 2722, 2728, 2730, 4112, 4113, 4116, 4121, 4132, 4133, 4161, 4164, 4176, 4181,
|
|
4184, 4193, 4196, 4197, 4201, 4241, 4244, 4246, 4257, 4261, 4353, 4356, 4358, 4361, 4368, 4370,
|
|
4373, 4376, 4385, 4388, 4393, 4421, 4426, 4432, 4433, 4434, 4436, 4437, 4438, 4441, 4448, 4453,
|
|
4484, 4498, 4501, 4513, 4516, 4625, 4628, 4630, 4645, 4672, 4678, 4681, 4690, 4693, 4696, 4698,
|
|
4708, 4710, 4741, 4753, 4756, 4758, 4773, 5121, 5126, 5129, 5140, 5141, 5144, 5145, 5153, 5158,
|
|
5185, 5189, 5190, 5192, 5194, 5201, 5204, 5205, 5206, 5209, 5218, 5221, 5224, 5252, 5257, 5264,
|
|
5268, 5269, 5272, 5273, 5274, 5281, 5284, 5285, 5289, 5378, 5381, 5386, 5393, 5396, 5397, 5398,
|
|
5401, 5408, 5410, 5413, 5416, 5418, 5441, 5444, 5445, 5446, 5457, 5458, 5460, 5461, 5462, 5465,
|
|
5466, 5473, 5476, 5477, 5478, 5481, 5504, 5506, 5508, 5509, 5512, 5514, 5520, 5521, 5524, 5525,
|
|
5526, 5529, 5530, 5536, 5538, 5541, 5633, 5636, 5637, 5638, 5653, 5654, 5656, 5658, 5665, 5670,
|
|
5696, 5698, 5700, 5701, 5704, 5706, 5713, 5717, 5718, 5720, 5721, 5729, 5732, 5733, 5736, 5737,
|
|
5738, 5766, 5770, 5778, 5781, 5796, 5801, 6161, 6166, 6181, 6209, 6212, 6214, 6217, 6224, 6229,
|
|
6232, 6234, 6240, 6241, 6244, 6246, 6249, 6277, 6289, 6292, 6309, 6416, 6418, 6421, 6426, 6433,
|
|
6437, 6466, 6468, 6469, 6472, 6481, 6484, 6485, 6486, 6489, 6490, 6496, 6501, 6506, 6537, 6545,
|
|
6546, 6549, 6552, 6561, 6566, 6569, 6665, 6678, 6692, 6694, 6724, 6726, 6729, 6736, 6738, 6741,
|
|
6744, 6753, 6758, 6761, 6789, 6801, 6806, 6810, 8192, 8194, 8200, 8202, 8213, 8224, 8226, 8229,
|
|
8232, 8234, 8261, 8273, 8281, 8289, 8293, 8320, 8322, 8328, 8330, 8341, 8352, 8354, 8357, 8360,
|
|
8362, 8453, 8465, 8468, 8473, 8485, 8514, 8516, 8521, 8533, 8536, 8538, 8545, 8548, 8549, 8550,
|
|
8581, 8592, 8598, 8601, 8613, 8705, 8712, 8714, 8721, 8725, 8736, 8738, 8744, 8746, 8773, 8785,
|
|
8790, 8793, 8805, 8833, 8840, 8842, 8849, 8853, 8864, 8866, 8872, 8874, 9221, 9236, 9238, 9241,
|
|
9253, 9284, 9285, 9286, 9289, 9298, 9301, 9304, 9306, 9318, 9349, 9361, 9364, 9369, 9377, 9381,
|
|
9481, 9493, 9505, 9513, 9536, 9541, 9544, 9553, 9556, 9557, 9561, 9570, 9573, 9576, 9609, 9616,
|
|
9620, 9621, 9624, 9626, 9633, 9636, 9638, 9641, 9733, 9744, 9746, 9753, 9765, 9793, 9801, 9813,
|
|
9824, 9825, 9833, 9860, 9862, 9872, 9882, 10240, 10242, 10248, 10250, 10261, 10272, 10274, 10280, 10282,
|
|
10309, 10321, 10324, 10341, 10368, 10370, 10376, 10378, 10400, 10402, 10408, 10410, 10505, 10513, 10516, 10521,
|
|
10533, 10566, 10569, 10578, 10581, 10593, 10596, 10598, 10601, 10629, 10640, 10646, 10649, 10660, 10661, 10752,
|
|
10754, 10760, 10762, 10784, 10786, 10792, 10794, 10821, 10833, 10838, 10841, 10853, 10880, 10882, 10888, 10890,
|
|
10901, 10912, 10914, 10920, 10922, 16389, 16401, 16406, 16421, 16457, 16466, 16469, 16472, 16474, 16481, 16484,
|
|
16486, 16532, 16537, 16545, 16550, 16640, 16641, 16644, 16646, 16649, 16658, 16661, 16662, 16664, 16666, 16673,
|
|
16678, 16681, 16709, 16712, 16714, 16721, 16724, 16725, 16726, 16729, 16730, 16741, 16744, 16746, 16769, 16772,
|
|
16774, 16784, 16786, 16789, 16800, 16801, 16802, 16901, 16913, 16916, 16918, 16933, 16961, 16978, 16981, 16986,
|
|
16996, 17001, 17033, 17044, 17061, 17409, 17429, 17433, 17449, 17477, 17480, 17482, 17489, 17492, 17493, 17494,
|
|
17505, 17506, 17509, 17512, 17514, 17537, 17542, 17545, 17552, 17554, 17557, 17568, 17569, 17577, 17665, 17666,
|
|
17669, 17674, 17681, 17684, 17685, 17686, 17689, 17696, 17701, 17706, 17729, 17732, 17733, 17734, 17737, 17744,
|
|
17745, 17748, 17749, 17750, 17752, 17753, 17761, 17764, 17765, 17766, 17769, 17794, 17796, 17797, 17800, 17809,
|
|
17812, 17813, 17814, 17817, 17818, 17829, 17832, 17834, 17921, 17925, 17929, 17940, 17941, 17944, 17946, 17953,
|
|
17956, 17961, 17984, 17986, 17989, 17992, 18000, 18001, 18002, 18005, 18006, 18009, 18018, 18021, 18024, 18049,
|
|
18053, 18058, 18068, 18069, 18081, 18084, 18086, 18437, 18449, 18453, 18458, 18469, 18498, 18505, 18512, 18517,
|
|
18520, 18529, 18532, 18534, 18537, 18565, 18577, 18580, 18582, 18585, 18597, 18689, 18693, 18694, 18698, 18704,
|
|
18708, 18709, 18712, 18721, 18724, 18726, 18752, 18757, 18762, 18769, 18770, 18772, 18773, 18774, 18777, 18784,
|
|
18786, 18789, 18790, 18794, 18822, 18825, 18834, 18837, 18838, 18840, 18849, 18852, 18854, 18857, 18966, 19012,
|
|
19014, 19017, 19029, 19032, 19034, 19044, 19049, 19092, 19109, 20481, 20484, 20485, 20486, 20489, 20498, 20501,
|
|
20506, 20513, 20516, 20521, 20544, 20549, 20552, 20561, 20564, 20565, 20566, 20569, 20581, 20584, 20614, 20617,
|
|
20629, 20632, 20640, 20641, 20646, 20649, 20741, 20744, 20745, 20746, 20753, 20756, 20757, 20758, 20760, 20761,
|
|
20768, 20773, 20774, 20776, 20778, 20801, 20804, 20805, 20806, 20809, 20816, 20817, 20818, 20820, 20821, 20822,
|
|
20824, 20825, 20826, 20833, 20836, 20837, 20838, 20841, 20866, 20869, 20881, 20884, 20885, 20886, 20889, 20896,
|
|
20901, 20906, 20993, 20998, 21010, 21013, 21018, 21025, 21028, 21058, 21061, 21066, 21073, 21076, 21077, 21078,
|
|
21081, 21090, 21093, 21125, 21136, 21138, 21141, 21145, 21146, 21156, 21508, 21509, 21521, 21524, 21525, 21526,
|
|
21528, 21529, 21537, 21541, 21544, 21546, 21569, 21572, 21573, 21574, 21577, 21578, 21584, 21585, 21588, 21589,
|
|
21590, 21592, 21593, 21594, 21601, 21602, 21604, 21605, 21606, 21609, 21632, 21640, 21642, 21649, 21652, 21653,
|
|
21654, 21657, 21665, 21668, 21669, 21674, 21761, 21762, 21764, 21765, 21766, 21769, 21776, 21777, 21778, 21780,
|
|
21781, 21782, 21785, 21786, 21793, 21796, 21797, 21798, 21801, 21824, 21825, 21826, 21828, 21829, 21830, 21832,
|
|
21833, 21840, 21841, 21842, 21844, 21845, 21846, 21848, 21849, 21850, 21856, 21857, 21860, 21861, 21862, 21864,
|
|
21865, 21866, 21889, 21892, 21893, 21897, 21898, 21904, 21905, 21908, 21909, 21910, 21912, 21913, 21921, 21924,
|
|
21925, 21926, 21929, 22016, 22017, 22018, 22020, 22022, 22024, 22025, 22033, 22036, 22037, 22040, 22041, 22048,
|
|
22049, 22050, 22052, 22053, 22054, 22056, 22057, 22081, 22085, 22086, 22088, 22089, 22090, 22096, 22097, 22098,
|
|
22100, 22101, 22102, 22104, 22105, 22106, 22113, 22116, 22117, 22121, 22146, 22149, 22150, 22152, 22153, 22154,
|
|
22161, 22165, 22170, 22178, 22181, 22182, 22184, 22185, 22532, 22533, 22534, 22537, 22544, 22549, 22552, 22561,
|
|
22570, 22597, 22600, 22602, 22609, 22612, 22613, 22614, 22616, 22617, 22624, 22626, 22628, 22629, 22658, 22665,
|
|
22672, 22674, 22677, 22680, 22689, 22697, 22785, 22786, 22789, 22794, 22801, 22804, 22805, 22806, 22809, 22821,
|
|
22849, 22852, 22853, 22854, 22857, 22864, 22865, 22866, 22868, 22869, 22870, 22872, 22873, 22874, 22881, 22884,
|
|
22885, 22886, 22889, 22913, 22917, 22921, 22929, 22932, 22933, 22934, 22936, 22937, 22949, 23044, 23048, 23061,
|
|
23066, 23072, 23077, 23078, 23081, 23109, 23112, 23113, 23121, 23125, 23126, 23128, 23129, 23138, 23141, 23144,
|
|
23146, 23169, 23178, 23186, 23189, 23190, 23192, 23194, 23201, 24581, 24596, 24598, 24601, 24613, 24644, 24656,
|
|
24661, 24662, 24664, 24666, 24673, 24676, 24678, 24681, 24705, 24726, 24741, 24833, 24836, 24838, 24841, 24850,
|
|
24853, 24865, 24866, 24870, 24873, 24901, 24905, 24913, 24917, 24918, 24921, 24933, 24934, 24938, 24964, 24970,
|
|
24978, 24981, 24993, 24998, 25001, 25105, 25110, 25113, 25152, 25153, 25158, 25173, 25174, 25176, 25184, 25221,
|
|
25233, 25238, 25253, 25617, 25618, 25621, 25622, 25626, 25633, 25638, 25641, 25664, 25666, 25669, 25672, 25674,
|
|
25681, 25684, 25685, 25686, 25689, 25690, 25696, 25698, 25701, 25732, 25733, 25737, 25744, 25746, 25748, 25749,
|
|
25750, 25752, 25754, 25761, 25764, 25769, 25861, 25864, 25866, 25873, 25877, 25878, 25881, 25924, 25925, 25926,
|
|
25929, 25936, 25937, 25940, 25941, 25942, 25945, 25953, 25956, 25957, 25958, 25961, 25990, 25993, 25994, 26001,
|
|
26005, 26006, 26009, 26010, 26018, 26021, 26022, 26024, 26114, 26121, 26133, 26144, 26150, 26152, 26153, 26176,
|
|
26181, 26184, 26186, 26193, 26196, 26197, 26198, 26200, 26202, 26208, 26213, 26216, 26240, 26242, 26245, 26250,
|
|
26260, 26262, 26264, 26265, 26272, 26276, 26278, 26282, 26646, 26649, 26661, 26689, 26706, 26709, 26714, 26721,
|
|
26729, 26757, 26769, 26776, 26790, 26881, 26884, 26896, 26901, 26913, 26916, 26918, 26921, 26944, 26945, 26949,
|
|
26950, 26952, 26961, 26964, 26965, 26966, 26969, 26976, 26981, 26986, 27010, 27012, 27018, 27029, 27041, 27044,
|
|
27045, 27049, 27153, 27158, 27160, 27201, 27204, 27209, 27216, 27221, 27224, 27226, 27236, 27237, 27241, 27270,
|
|
27284, 27288, 27290, 27302, 32768, 32770, 32776, 32778, 32800, 32802, 32808, 32810, 32837, 32848, 32849, 32852,
|
|
32854, 32857, 32869, 32896, 32898, 32904, 32906, 32917, 32928, 32930, 32936, 32938, 33029, 33041, 33044, 33046,
|
|
33049, 33061, 33089, 33092, 33097, 33104, 33106, 33109, 33110, 33112, 33113, 33124, 33126, 33129, 33157, 33161,
|
|
33172, 33174, 33177, 33189, 33280, 33282, 33288, 33290, 33301, 33312, 33314, 33320, 33322, 33361, 33364, 33369,
|
|
33381, 33408, 33410, 33416, 33418, 33429, 33440, 33442, 33448, 33450, 33812, 33817, 33857, 33860, 33873, 33877,
|
|
33882, 33889, 33892, 33897, 33940, 33945, 34049, 34057, 34066, 34069, 34074, 34086, 34089, 34112, 34113, 34117,
|
|
34120, 34129, 34132, 34133, 34134, 34137, 34138, 34149, 34150, 34152, 34154, 34177, 34180, 34182, 34185, 34192,
|
|
34194, 34197, 34200, 34214, 34321, 34326, 34329, 34341, 34369, 34372, 34377, 34378, 34384, 34389, 34393, 34394,
|
|
34401, 34406, 34410, 34437, 34449, 34458, 34468, 34816, 34818, 34824, 34826, 34837, 34848, 34850, 34856, 34858,
|
|
34881, 34885, 34897, 34900, 34905, 34917, 34921, 34944, 34946, 34952, 34954, 34965, 34976, 34978, 34984, 34986,
|
|
35077, 35078, 35089, 35092, 35094, 35109, 35137, 35140, 35142, 35145, 35152, 35154, 35157, 35162, 35169, 35172,
|
|
35205, 35222, 35225, 35237, 35328, 35330, 35336, 35338, 35349, 35360, 35362, 35368, 35370, 35397, 35409, 35412,
|
|
35414, 35456, 35458, 35464, 35466, 35477, 35488, 35490, 35496, 35498, 36869, 36881, 36886, 36888, 36889, 36901,
|
|
36929, 36934, 36937, 36949, 36952, 36954, 36969, 36970, 36997, 37009, 37012, 37014, 37017, 37029, 37121, 37124,
|
|
37126, 37129, 37136, 37141, 37144, 37146, 37153, 37156, 37158, 37161, 37184, 37189, 37200, 37201, 37204, 37205,
|
|
37206, 37209, 37218, 37221, 37252, 37254, 37266, 37269, 37272, 37281, 37284, 37286, 37289, 37381, 37393, 37396,
|
|
37401, 37413, 37444, 37446, 37449, 37456, 37458, 37461, 37464, 37478, 37481, 37509, 37524, 37526, 37545, 37889,
|
|
37892, 37894, 37904, 37909, 37912, 37926, 37952, 37962, 37969, 37972, 37973, 37974, 37976, 37977, 37984, 37985,
|
|
37986, 37989, 38020, 38022, 38034, 38036, 38037, 38040, 38049, 38057, 38144, 38149, 38152, 38154, 38160, 38161,
|
|
38164, 38165, 38166, 38169, 38177, 38181, 38185, 38186, 38209, 38212, 38213, 38214, 38217, 38224, 38225, 38226,
|
|
38228, 38229, 38230, 38232, 38233, 38234, 38241, 38244, 38245, 38246, 38249, 38273, 38277, 38280, 38289, 38290,
|
|
38292, 38293, 38294, 38297, 38298, 38304, 38306, 38309, 38312, 38314, 38401, 38404, 38416, 38421, 38425, 38432,
|
|
38438, 38441, 38469, 38472, 38473, 38481, 38482, 38485, 38486, 38489, 38501, 38504, 38530, 38532, 38537, 38538,
|
|
38546, 38548, 38549, 38564, 38566, 38569, 38917, 38934, 38937, 38949, 38977, 38982, 38992, 38994, 38997, 38998,
|
|
39002, 39012, 39013, 39045, 39057, 39062, 39065, 39077, 39172, 39174, 39177, 39184, 39186, 39189, 39192, 39194,
|
|
39200, 39201, 39204, 39206, 39232, 39234, 39237, 39240, 39242, 39249, 39252, 39253, 39254, 39257, 39266, 39269,
|
|
39270, 39274, 39297, 39300, 39312, 39314, 39317, 39322, 39329, 39334, 39429, 39445, 39461, 39492, 39494, 39497,
|
|
39504, 39509, 39512, 39521, 39557, 39569, 39572, 39573, 39574, 40960, 40962, 40968, 40970, 40981, 40992, 40994,
|
|
41000, 41002, 41029, 41041, 41044, 41046, 41049, 41088, 41090, 41096, 41098, 41109, 41120, 41122, 41128, 41130,
|
|
41221, 41225, 41233, 41236, 41238, 41241, 41242, 41286, 41289, 41297, 41301, 41304, 41306, 41313, 41316, 41349,
|
|
41360, 41362, 41366, 41369, 41474, 41480, 41482, 41488, 41497, 41506, 41512, 41514, 41541, 41553, 41558, 41561,
|
|
41573, 41600, 41602, 41608, 41610, 41621, 41632, 41634, 41640, 41642, 42009, 42021, 42049, 42052, 42064, 42068,
|
|
42069, 42072, 42074, 42081, 42085, 42086, 42088, 42089, 42117, 42246, 42249, 42256, 42258, 42261, 42264, 42278,
|
|
42281, 42306, 42309, 42321, 42324, 42325, 42326, 42329, 42341, 42346, 42369, 42372, 42373, 42374, 42377, 42386,
|
|
42389, 42392, 42501, 42513, 42518, 42522, 42529, 42533, 42564, 42566, 42570, 42578, 42581, 42582, 42584, 42592,
|
|
42594, 42630, 42640, 42645, 42646, 42649, 42657, 42660, 42662, 43008, 43010, 43016, 43018, 43040, 43042, 43048,
|
|
43050, 43089, 43092, 43094, 43097, 43136, 43138, 43144, 43146, 43157, 43168, 43170, 43176, 43178, 43269, 43284,
|
|
43289, 43297, 43301, 43329, 43344, 43349, 43354, 43361, 43366, 43369, 43408, 43414, 43520, 43522, 43528, 43530,
|
|
43552, 43554, 43560, 43562, 43601, 43604, 43606, 43648, 43650, 43656, 43658, 43669, 43680, 43682, 43688, 43690,
|
|
};
|
|
static const uint16_t kgrid_2bit_1024[1024] = {
|
|
0, 2, 5, 8, 10, 17, 20, 22, 25, 32, 34, 37, 40, 65, 68, 70,
|
|
73, 80, 82, 85, 88, 97, 100, 102, 105, 128, 130, 133, 136, 145, 148, 160,
|
|
165, 170, 257, 260, 262, 265, 272, 274, 277, 280, 289, 292, 320, 322, 325, 328,
|
|
337, 340, 342, 345, 352, 357, 360, 385, 388, 400, 402, 405, 417, 420, 512, 514,
|
|
517, 520, 529, 532, 544, 554, 577, 580, 582, 585, 592, 597, 640, 645, 650, 660,
|
|
674, 1025, 1028, 1030, 1033, 1040, 1042, 1045, 1048, 1057, 1060, 1062, 1065, 1088, 1090, 1093,
|
|
1096, 1098, 1105, 1108, 1110, 1113, 1120, 1122, 1125, 1153, 1156, 1158, 1161, 1168, 1173, 1176,
|
|
1185, 1188, 1280, 1282, 1285, 1288, 1290, 1297, 1300, 1302, 1305, 1312, 1317, 1320, 1345, 1348,
|
|
1350, 1353, 1360, 1362, 1365, 1368, 1377, 1380, 1408, 1410, 1413, 1416, 1425, 1428, 1440, 1537,
|
|
1540, 1542, 1545, 1552, 1557, 1600, 1605, 1608, 1617, 1620, 1632, 1665, 1668, 1680, 2048, 2050,
|
|
2053, 2056, 2065, 2068, 2070, 2073, 2080, 2085, 2090, 2113, 2116, 2118, 2121, 2128, 2130, 2133,
|
|
2136, 2145, 2148, 2176, 2181, 2196, 2218, 2305, 2308, 2320, 2322, 2325, 2328, 2337, 2368, 2373,
|
|
2376, 2385, 2388, 2400, 2433, 2448, 2560, 2577, 2580, 2594, 2600, 2602, 2640, 2713, 4097, 4100,
|
|
4102, 4105, 4112, 4114, 4117, 4120, 4129, 4132, 4134, 4160, 4162, 4165, 4168, 4177, 4180, 4182,
|
|
4185, 4192, 4194, 4197, 4200, 4225, 4228, 4230, 4240, 4245, 4248, 4257, 4260, 4352, 4354, 4357,
|
|
4360, 4362, 4369, 4372, 4374, 4377, 4384, 4386, 4389, 4392, 4417, 4420, 4422, 4425, 4432, 4434,
|
|
4437, 4440, 4449, 4452, 4480, 4482, 4485, 4488, 4497, 4500, 4609, 4612, 4617, 4624, 4629, 4641,
|
|
4644, 4672, 4677, 4689, 4692, 4737, 4740, 4752, 5120, 5122, 5125, 5128, 5137, 5140, 5142, 5145,
|
|
5152, 5157, 5160, 5185, 5188, 5190, 5193, 5200, 5202, 5205, 5208, 5217, 5220, 5248, 5250, 5253,
|
|
5256, 5265, 5268, 5280, 5377, 5380, 5382, 5385, 5392, 5394, 5397, 5400, 5409, 5412, 5440, 5442,
|
|
5445, 5448, 5457, 5460, 5472, 5505, 5508, 5520, 5632, 5637, 5640, 5649, 5652, 5664, 5697, 5700,
|
|
5712, 5760, 5802, 6145, 6148, 6150, 6153, 6160, 6165, 6168, 6177, 6208, 6210, 6213, 6216, 6225,
|
|
6228, 6240, 6273, 6276, 6400, 6402, 6405, 6408, 6417, 6420, 6432, 6465, 6468, 6480, 6505, 6562,
|
|
6660, 6672, 6720, 6742, 8192, 8194, 8197, 8200, 8209, 8212, 8214, 8217, 8224, 8229, 8234, 8257,
|
|
8260, 8272, 8274, 8277, 8292, 8320, 8330, 8340, 8362, 8449, 8452, 8464, 8466, 8469, 8481, 8512,
|
|
8514, 8517, 8529, 8532, 8544, 8577, 8580, 8592, 8704, 8714, 8738, 8744, 8746, 8772, 8784, 8840,
|
|
8842, 8872, 9217, 9220, 9222, 9225, 9232, 9237, 9240, 9249, 9252, 9280, 9282, 9285, 9288, 9297,
|
|
9300, 9312, 9345, 9348, 9360, 9472, 9477, 9480, 9489, 9492, 9504, 9537, 9540, 9552, 9574, 9600,
|
|
9729, 9732, 9744, 9792, 9817, 10240, 10245, 10257, 10260, 10305, 10308, 10320, 10378, 10410, 10497, 10500,
|
|
10512, 10645, 10762, 10786, 10852, 10888, 10890, 16385, 16388, 16390, 16393, 16400, 16402, 16405, 16408, 16410,
|
|
16417, 16420, 16422, 16448, 16450, 16453, 16456, 16458, 16465, 16468, 16470, 16473, 16480, 16482, 16485, 16513,
|
|
16516, 16528, 16533, 16536, 16545, 16548, 16640, 16642, 16645, 16648, 16657, 16660, 16662, 16665, 16672, 16674,
|
|
16677, 16705, 16708, 16710, 16713, 16720, 16722, 16725, 16728, 16737, 16740, 16768, 16770, 16773, 16776, 16785,
|
|
16788, 16800, 16897, 16900, 16912, 16914, 16917, 16920, 16932, 16960, 16965, 16968, 16977, 16980, 16992, 17025,
|
|
17028, 17408, 17410, 17413, 17416, 17418, 17425, 17428, 17430, 17433, 17440, 17442, 17445, 17448, 17473, 17476,
|
|
17478, 17481, 17488, 17490, 17493, 17496, 17505, 17508, 17536, 17538, 17541, 17544, 17553, 17556, 17568, 17665,
|
|
17668, 17670, 17673, 17680, 17682, 17685, 17688, 17697, 17700, 17728, 17730, 17733, 17736, 17745, 17748, 17760,
|
|
17770, 17793, 17796, 17808, 17920, 17922, 17925, 17928, 17937, 17940, 17952, 17985, 17988, 18000, 18048, 18085,
|
|
18433, 18436, 18441, 18448, 18450, 18453, 18456, 18465, 18468, 18496, 18498, 18501, 18504, 18513, 18516, 18528,
|
|
18564, 18576, 18688, 18690, 18693, 18696, 18705, 18708, 18720, 18753, 18756, 18768, 18816, 18838, 18945, 18948,
|
|
18960, 19008, 20480, 20482, 20485, 20488, 20497, 20500, 20502, 20505, 20512, 20514, 20517, 20520, 20545, 20548,
|
|
20550, 20553, 20560, 20562, 20565, 20568, 20577, 20580, 20608, 20610, 20613, 20616, 20625, 20628, 20737, 20740,
|
|
20742, 20745, 20752, 20754, 20757, 20760, 20769, 20772, 20800, 20802, 20805, 20808, 20817, 20820, 20832, 20865,
|
|
20868, 20880, 20992, 20997, 21000, 21009, 21012, 21024, 21057, 21060, 21072, 21097, 21120, 21505, 21508, 21510,
|
|
21513, 21520, 21522, 21525, 21528, 21537, 21540, 21568, 21570, 21573, 21576, 21585, 21588, 21600, 21633, 21636,
|
|
21648, 21760, 21762, 21765, 21768, 21777, 21780, 21792, 21825, 21828, 21840, 21888, 22017, 22020, 22032, 22054,
|
|
22080, 22528, 22530, 22533, 22536, 22545, 22548, 22560, 22593, 22596, 22608, 22618, 22656, 22785, 22788, 22800,
|
|
22848, 23040, 23065, 23173, 23208, 24577, 24580, 24582, 24592, 24594, 24597, 24600, 24609, 24612, 24640, 24645,
|
|
24648, 24657, 24660, 24672, 24708, 24720, 24832, 24834, 24837, 24840, 24849, 24852, 24864, 24897, 24900, 24912,
|
|
24960, 24985, 25092, 25104, 25152, 25174, 25249, 25600, 25605, 25608, 25617, 25620, 25632, 25665, 25668, 25680,
|
|
25728, 25857, 25860, 25872, 25920, 25930, 25960, 26002, 26112, 26260, 26625, 26628, 26640, 26725, 26776, 26880,
|
|
26922, 27202, 27297, 32768, 32770, 32773, 32776, 32785, 32788, 32793, 32800, 32805, 32833, 32836, 32848, 32850,
|
|
32853, 32856, 32865, 32896, 32901, 32913, 32916, 33025, 33028, 33033, 33040, 33042, 33045, 33048, 33057, 33060,
|
|
33088, 33090, 33093, 33096, 33105, 33108, 33153, 33156, 33168, 33193, 33280, 33285, 33290, 33297, 33300, 33345,
|
|
33348, 33360, 33793, 33796, 33798, 33801, 33808, 33810, 33813, 33816, 33825, 33856, 33858, 33861, 33864, 33873,
|
|
33876, 33888, 33921, 33924, 33936, 34048, 34050, 34053, 34056, 34065, 34068, 34080, 34113, 34116, 34128, 34176,
|
|
34186, 34305, 34308, 34320, 34345, 34368, 34816, 34821, 34833, 34836, 34881, 34884, 34896, 34978, 35073, 35076,
|
|
35136, 35173, 35362, 35416, 35418, 35458, 35490, 36865, 36868, 36873, 36880, 36882, 36885, 36888, 36900, 36928,
|
|
36930, 36933, 36936, 36945, 36948, 36960, 36993, 36996, 37008, 37120, 37125, 37137, 37140, 37185, 37188, 37200,
|
|
37210, 37377, 37380, 37392, 37440, 37542, 37888, 37890, 37893, 37896, 37905, 37908, 37920, 37953, 37956, 37968,
|
|
38016, 38038, 38145, 38148, 38160, 38208, 38296, 38305, 38400, 38470, 38500, 38913, 38916, 38928, 38950, 38976,
|
|
39081, 39168, 39241, 39250, 39568, 40960, 40965, 40970, 40980, 40994, 41002, 41025, 41028, 41040, 41122, 41130,
|
|
41280, 41317, 41474, 41482, 41506, 41512, 41514, 41602, 41608, 41610, 41640, 41985, 41988, 42000, 42048, 42121,
|
|
42148, 42240, 42265, 42577, 43018, 43048, 43170, 43348, 43398, 43528, 43530, 43552, 43554, 43560, 43656, 43690,
|
|
};
|
|
|
|
const int kmap_size = 43692;
|
|
//const int nwant = type == GGML_TYPE_IQ1_S ? 3 : 2;
|
|
const int nwant = type == GGML_TYPE_IQ1_S || type == GGML_TYPE_IQ1_M ? 3 : type == GGML_TYPE_IQ2_S ? 1 : 2;
|
|
const uint16_t * kgrid = type == GGML_TYPE_IQ2_XXS ? kgrid_2bit_256 :
|
|
type == GGML_TYPE_IQ2_XS ? kgrid_2bit_512 :
|
|
type == GGML_TYPE_IQ1_S || type == GGML_TYPE_IQ1_M ? kgrid_1bit_2048 : kgrid_2bit_1024;
|
|
uint64_t * kgrid_q2xs;
|
|
int * kmap_q2xs;
|
|
uint16_t * kneighbors_q2xs;
|
|
|
|
//printf("================================================================= %s(grid_size = %d)\n", __func__, grid_size);
|
|
uint64_t * the_grid = (uint64_t *)malloc(grid_size*sizeof(uint64_t));
|
|
for (int k = 0; k < grid_size; ++k) {
|
|
int8_t * pos = (int8_t *)(the_grid + k);
|
|
for (int i = 0; i < 8; ++i) {
|
|
int l = (kgrid[k] >> 2*i) & 0x3;
|
|
pos[i] = 2*l + 1;
|
|
}
|
|
}
|
|
kgrid_q2xs = the_grid;
|
|
iq2_data[gindex].grid = the_grid;
|
|
kmap_q2xs = (int *)malloc(kmap_size*sizeof(int));
|
|
iq2_data[gindex].map = kmap_q2xs;
|
|
for (int i = 0; i < kmap_size; ++i) kmap_q2xs[i] = -1;
|
|
uint64_t aux64;
|
|
uint8_t * aux8 = (uint8_t *)&aux64;
|
|
for (int i = 0; i < grid_size; ++i) {
|
|
aux64 = kgrid_q2xs[i];
|
|
uint16_t index = 0;
|
|
for (int k=0; k<8; ++k) {
|
|
uint16_t q = (aux8[k] - 1)/2;
|
|
index |= (q << 2*k);
|
|
}
|
|
kmap_q2xs[index] = i;
|
|
}
|
|
int8_t pos[8];
|
|
int * dist2 = (int *)malloc(2*grid_size*sizeof(int));
|
|
int num_neighbors = 0, num_not_in_map = 0;
|
|
for (int i = 0; i < kmap_size; ++i) {
|
|
if (kmap_q2xs[i] >= 0) continue;
|
|
++num_not_in_map;
|
|
for (int k = 0; k < 8; ++k) {
|
|
int l = (i >> 2*k) & 0x3;
|
|
pos[k] = 2*l + 1;
|
|
}
|
|
for (int j = 0; j < grid_size; ++j) {
|
|
const int8_t * pg = (const int8_t *)(kgrid_q2xs + j);
|
|
int d2 = 0;
|
|
for (int k = 0; k < 8; ++k) d2 += (pg[k] - pos[k])*(pg[k] - pos[k]);
|
|
dist2[2*j+0] = d2;
|
|
dist2[2*j+1] = j;
|
|
}
|
|
qsort(dist2, grid_size, 2*sizeof(int), iq2_compare_func);
|
|
int n = 0; int d2 = dist2[0];
|
|
int nhave = 1;
|
|
for (int j = 0; j < grid_size; ++j) {
|
|
if (dist2[2*j] > d2) {
|
|
if (nhave == nwant) break;
|
|
d2 = dist2[2*j];
|
|
++nhave;
|
|
}
|
|
++n;
|
|
}
|
|
num_neighbors += n;
|
|
}
|
|
//printf("%s: %d neighbours in total\n", __func__, num_neighbors);
|
|
kneighbors_q2xs = (uint16_t *)malloc((num_neighbors + num_not_in_map)*sizeof(uint16_t));
|
|
iq2_data[gindex].neighbours = kneighbors_q2xs;
|
|
int counter = 0;
|
|
for (int i = 0; i < kmap_size; ++i) {
|
|
if (kmap_q2xs[i] >= 0) continue;
|
|
for (int k = 0; k < 8; ++k) {
|
|
int l = (i >> 2*k) & 0x3;
|
|
pos[k] = 2*l + 1;
|
|
}
|
|
for (int j = 0; j < grid_size; ++j) {
|
|
const int8_t * pg = (const int8_t *)(kgrid_q2xs + j);
|
|
int d2 = 0;
|
|
for (int k = 0; k < 8; ++k) d2 += (pg[k] - pos[k])*(pg[k] - pos[k]);
|
|
dist2[2*j+0] = d2;
|
|
dist2[2*j+1] = j;
|
|
}
|
|
qsort(dist2, grid_size, 2*sizeof(int), iq2_compare_func);
|
|
kmap_q2xs[i] = -(counter + 1);
|
|
int d2 = dist2[0];
|
|
uint16_t * start = &kneighbors_q2xs[counter++];
|
|
int n = 0, nhave = 1;
|
|
for (int j = 0; j < grid_size; ++j) {
|
|
if (dist2[2*j] > d2) {
|
|
if (nhave == nwant) break;
|
|
d2 = dist2[2*j];
|
|
++nhave;
|
|
}
|
|
kneighbors_q2xs[counter++] = dist2[2*j+1];
|
|
++n;
|
|
}
|
|
*start = n;
|
|
}
|
|
free(dist2);
|
|
}
|
|
|
|
void iq2xs_free_impl(enum ggml_type type) {
|
|
GGML_ASSERT(type == GGML_TYPE_IQ2_XXS || type == GGML_TYPE_IQ2_XS || type == GGML_TYPE_IQ1_S || type == GGML_TYPE_IQ1_M || type == GGML_TYPE_IQ2_S);
|
|
const int gindex = iq2_data_index(type);
|
|
if (iq2_data[gindex].grid) {
|
|
free(iq2_data[gindex].grid); iq2_data[gindex].grid = NULL;
|
|
free(iq2_data[gindex].map); iq2_data[gindex].map = NULL;
|
|
free(iq2_data[gindex].neighbours); iq2_data[gindex].neighbours = NULL;
|
|
}
|
|
}
|
|
|
|
static int iq2_find_best_neighbour(const uint16_t * restrict neighbours, const uint64_t * restrict grid,
|
|
const float * restrict xval, const float * restrict weight, float scale, int8_t * restrict L) {
|
|
int num_neighbors = neighbours[0];
|
|
GGML_ASSERT(num_neighbors > 0);
|
|
float best_d2 = FLT_MAX;
|
|
int grid_index = -1;
|
|
for (int j = 1; j <= num_neighbors; ++j) {
|
|
const int8_t * pg = (const int8_t *)(grid + neighbours[j]);
|
|
float d2 = 0;
|
|
for (int i = 0; i < 8; ++i) {
|
|
float q = pg[i];
|
|
float diff = scale*q - xval[i];
|
|
d2 += weight[i]*diff*diff;
|
|
}
|
|
if (d2 < best_d2) {
|
|
best_d2 = d2; grid_index = neighbours[j];
|
|
}
|
|
}
|
|
GGML_ASSERT(grid_index >= 0);
|
|
const int8_t * pg = (const int8_t *)(grid + grid_index);
|
|
for (int i = 0; i < 8; ++i) L[i] = (pg[i] - 1)/2;
|
|
return grid_index;
|
|
}
|
|
|
|
static void quantize_row_iq2_xxs_impl(const float * restrict x, void * restrict vy, int64_t n, const float * restrict quant_weights) {
|
|
|
|
const int gindex = iq2_data_index(GGML_TYPE_IQ2_XXS);
|
|
|
|
const uint64_t * kgrid_q2xs = iq2_data[gindex].grid;
|
|
const int * kmap_q2xs = iq2_data[gindex].map;
|
|
const uint16_t * kneighbors_q2xs = iq2_data[gindex].neighbours;
|
|
|
|
GGML_ASSERT(quant_weights && "missing quantization weights");
|
|
GGML_ASSERT(kgrid_q2xs && "forgot to call ggml_quantize_init()?");
|
|
GGML_ASSERT(kmap_q2xs && "forgot to call ggml_quantize_init()?");
|
|
GGML_ASSERT(kneighbors_q2xs && "forgot to call ggml_quantize_init()?");
|
|
GGML_ASSERT(n%QK_K == 0);
|
|
|
|
const int kMaxQ = 3;
|
|
|
|
const int64_t nbl = n/QK_K;
|
|
|
|
block_iq2_xxs * y = vy;
|
|
|
|
float scales[QK_K/32];
|
|
float weight[32];
|
|
float xval[32];
|
|
int8_t L[32];
|
|
int8_t Laux[32];
|
|
float waux[32];
|
|
uint8_t block_signs[4];
|
|
uint32_t q2[2*(QK_K/32)];
|
|
|
|
for (int ibl = 0; ibl < nbl; ++ibl) {
|
|
|
|
y[ibl].d = GGML_FP32_TO_FP16(0.f);
|
|
memset(q2, 0, QK_K/4);
|
|
|
|
float max_scale = 0;
|
|
|
|
const float * xbl = x + QK_K*ibl;
|
|
float sumx2 = 0;
|
|
for (int i = 0; i < QK_K; ++i) sumx2 += xbl[i]*xbl[i];
|
|
float sigma2 = sumx2/QK_K;
|
|
|
|
for (int ib = 0; ib < QK_K/32; ++ib) {
|
|
const float * xb = xbl + 32*ib;
|
|
const float * qw = quant_weights + QK_K*ibl + 32*ib;
|
|
for (int i = 0; i < 32; ++i) weight[i] = qw[i] * sqrtf(sigma2 + xb[i]*xb[i]);
|
|
for (int i = 0; i < 32; ++i) waux[i] = sqrtf(weight[i]);
|
|
for (int k = 0; k < 4; ++k) {
|
|
int nflip = 0;
|
|
uint8_t s = 0;
|
|
for (int i = 0; i < 8; ++i) {
|
|
if (xb[8*k + i] >= 0) xval[8*k + i] = xb[8*k + i];
|
|
else {
|
|
xval[8*k + i] = -xb[8*k + i]; ++nflip; s |= (1 << i);
|
|
}
|
|
}
|
|
if (nflip%2) {
|
|
int imin = 0; float min = weight[8*k+imin]*xb[8*k+imin]*xb[8*k+imin];
|
|
for (int i = 1; i < 8; ++i) {
|
|
float ax = weight[8*k+i]*xb[8*k+i]*xb[8*k+i];
|
|
if (ax < min) {
|
|
min = ax; imin = i;
|
|
}
|
|
}
|
|
xval[8*k+imin] = -xval[8*k+imin];
|
|
s ^= (1 << imin);
|
|
}
|
|
block_signs[k] = s & 127;
|
|
}
|
|
float max = xval[0];
|
|
for (int i = 1; i < 32; ++i) max = MAX(max, xval[i]);
|
|
if (max < GROUP_MAX_EPS) {
|
|
scales[ib] = 0;
|
|
memset(L, 0, 32);
|
|
continue;
|
|
}
|
|
float scale = make_qp_quants(32, kMaxQ+1, xval, (uint8_t*)L, weight);
|
|
float eff_max = scale*kMaxQ;
|
|
float best = 0;
|
|
for (int is = -6; is <= 6; ++is) {
|
|
float id = (2*kMaxQ-1+is*0.1f)/eff_max;
|
|
float this_scale = 1/id;
|
|
for (int k = 0; k < 4; ++k) {
|
|
for (int i = 0; i < 8; ++i) {
|
|
int l = nearest_int(0.5f*(id*xval[8*k+i]-1));
|
|
Laux[8*k+i] = MAX(0, MIN(kMaxQ-1, l));
|
|
}
|
|
uint16_t u = 0;
|
|
for (int i = 0; i < 8; ++i) u |= (Laux[8*k+i] << 2*i);
|
|
int grid_index = kmap_q2xs[u];
|
|
if (grid_index < 0) {
|
|
const uint16_t * neighbours = kneighbors_q2xs - kmap_q2xs[u] - 1;
|
|
grid_index = iq2_find_best_neighbour(neighbours, kgrid_q2xs, xval + 8*k, waux + 8*k, this_scale, Laux + 8*k);
|
|
}
|
|
}
|
|
float sumqx = 0, sumq2 = 0;
|
|
for (int i = 0; i < 32; ++i) {
|
|
float w = weight[i];
|
|
float q = 2*Laux[i] + 1;
|
|
sumqx += w*xval[i]*q;
|
|
sumq2 += w*q*q;
|
|
}
|
|
if (sumq2 > 0 && sumqx*sumqx > best*sumq2) {
|
|
scale = sumqx/sumq2; best = scale*sumqx;
|
|
memcpy(L, Laux, 32);
|
|
}
|
|
}
|
|
if (scale > 0) {
|
|
float id = 1/scale;
|
|
for (int k = 0; k < 4; ++k) {
|
|
uint16_t u = 0;
|
|
for (int i = 0; i < 8; ++i) {
|
|
int l = nearest_int(0.5f*(id*xval[8*k+i]-1));
|
|
l = MAX(0, MIN(kMaxQ-1, l));
|
|
u |= (l << 2*i);
|
|
}
|
|
int grid_index = kmap_q2xs[u];
|
|
if (grid_index < 0) {
|
|
const uint16_t * neighbours = kneighbors_q2xs - kmap_q2xs[u] - 1;
|
|
grid_index = iq2_find_best_neighbour(neighbours, kgrid_q2xs, xval + 8*k, waux + 8*k, scale, L + 8*k);
|
|
}
|
|
const int8_t * pg = (const int8_t *)(kgrid_q2xs + grid_index);
|
|
for (int i = 0; i < 8; ++i) L[8*k+i] = (pg[i] - 1)/2;
|
|
}
|
|
float sumqx = 0, sumq2 = 0;
|
|
for (int i = 0; i < 32; ++i) {
|
|
float w = weight[i];
|
|
float q = 2*L[i] + 1;
|
|
sumqx += w*xval[i]*q;
|
|
sumq2 += w*q*q;
|
|
}
|
|
if (sumq2 > 0) scale = sumqx/sumq2;
|
|
}
|
|
if (scale < 0) {
|
|
// This should never happen, but just in case, flip scale so that it is positive (we use uint's to encode the scale)
|
|
// and correspondingly flip quant signs.
|
|
scale = -scale;
|
|
for (int k = 0; k < 4; ++k) block_signs[k] = (~block_signs[k]) & 127;
|
|
}
|
|
for (int k = 0; k < 4; ++k) {
|
|
uint16_t u = 0;
|
|
for (int i = 0; i < 8; ++i) u |= (L[8*k+i] << 2*i);
|
|
int grid_index = kmap_q2xs[u];
|
|
if (grid_index < 0) {
|
|
printf("Oops: found point %u not on grid:", u);
|
|
for (int i = 0; i < 8; ++i) printf(" %d", L[8*k+i]);
|
|
printf("\n");
|
|
GGML_ABORT("fatal error");
|
|
}
|
|
q2[2*ib+0] |= ((uint32_t) grid_index << 8*k);
|
|
q2[2*ib+1] |= (block_signs[k] << 7*k);
|
|
}
|
|
GGML_ASSERT(scale >= 0);
|
|
scales[ib] = scale;
|
|
max_scale = MAX(max_scale, scale);
|
|
}
|
|
|
|
if (!max_scale) {
|
|
memset(y[ibl].qs, 0, QK_K/4);
|
|
continue;
|
|
}
|
|
|
|
float d = max_scale/31;
|
|
y[ibl].d = GGML_FP32_TO_FP16(d);
|
|
float id = 1/d;
|
|
for (int ib = 0; ib < QK_K/32; ++ib) {
|
|
int l = nearest_int(0.5f*(id*scales[ib]-1));
|
|
l = MAX(0, MIN(15, l));
|
|
q2[2*ib+1] |= ((uint32_t)l << 28);
|
|
}
|
|
memcpy(y[ibl].qs, q2, QK_K/4);
|
|
}
|
|
}
|
|
|
|
static void quantize_row_iq2_xs_impl(const float * restrict x, void * restrict vy, int64_t n, const float * restrict quant_weights) {
|
|
|
|
const int gindex = iq2_data_index(GGML_TYPE_IQ2_XS);
|
|
|
|
const uint64_t * kgrid_q2xs = iq2_data[gindex].grid;
|
|
const int * kmap_q2xs = iq2_data[gindex].map;
|
|
const uint16_t * kneighbors_q2xs = iq2_data[gindex].neighbours;
|
|
|
|
GGML_ASSERT(quant_weights && "missing quantization weights");
|
|
GGML_ASSERT(kmap_q2xs && "forgot to call ggml_quantize_init()?");
|
|
GGML_ASSERT(kgrid_q2xs && "forgot to call ggml_quantize_init()?");
|
|
GGML_ASSERT(kneighbors_q2xs && "forgot to call ggml_quantize_init()?");
|
|
GGML_ASSERT(n%QK_K == 0);
|
|
|
|
const int kMaxQ = 3;
|
|
|
|
const int64_t nbl = n/QK_K;
|
|
|
|
block_iq2_xs * y = vy;
|
|
|
|
float scales[QK_K/16];
|
|
float weight[16];
|
|
float xval[16];
|
|
int8_t L[16];
|
|
int8_t Laux[16];
|
|
float waux[16];
|
|
bool is_on_grid[2];
|
|
bool is_on_grid_aux[2];
|
|
uint8_t block_signs[2];
|
|
uint16_t q2[2*(QK_K/16)];
|
|
|
|
for (int ibl = 0; ibl < nbl; ++ibl) {
|
|
|
|
y[ibl].d = GGML_FP32_TO_FP16(0.f);
|
|
memset(q2, 0, QK_K/4);
|
|
memset(y[ibl].scales, 0, QK_K/32);
|
|
|
|
float max_scale = 0;
|
|
|
|
const float * xbl = x + QK_K*ibl;
|
|
float sumx2 = 0;
|
|
for (int i = 0; i < QK_K; ++i) sumx2 += xbl[i]*xbl[i];
|
|
float sigma2 = sumx2/QK_K;
|
|
|
|
for (int ib = 0; ib < QK_K/16; ++ib) {
|
|
const float * xb = xbl + 16*ib;
|
|
const float * qw = quant_weights + QK_K*ibl + 16*ib;
|
|
for (int i = 0; i < 16; ++i) weight[i] = qw[i] * sqrtf(sigma2 + xb[i]*xb[i]);
|
|
for (int i = 0; i < 16; ++i) waux[i] = sqrtf(weight[i]);
|
|
for (int k = 0; k < 2; ++k) {
|
|
int nflip = 0;
|
|
uint8_t s = 0;
|
|
for (int i = 0; i < 8; ++i) {
|
|
if (xb[8*k + i] >= 0) xval[8*k + i] = xb[8*k + i];
|
|
else {
|
|
xval[8*k + i] = -xb[8*k + i]; ++nflip; s |= (1 << i);
|
|
}
|
|
}
|
|
if (nflip%2) {
|
|
int imin = 0; float min = weight[8*k+imin]*xb[8*k+imin]*xb[8*k+imin];
|
|
for (int i = 1; i < 8; ++i) {
|
|
float ax = weight[8*k+i]*xb[8*k+i]*xb[8*k+i];
|
|
if (ax < min) {
|
|
min = ax; imin = i;
|
|
}
|
|
}
|
|
xval[8*k+imin] = -xval[8*k+imin];
|
|
s ^= (1 << imin);
|
|
}
|
|
block_signs[k] = s & 127;
|
|
}
|
|
float max = xval[0];
|
|
for (int i = 1; i < 16; ++i) max = MAX(max, xval[i]);
|
|
if (max < GROUP_MAX_EPS) {
|
|
scales[ib] = 0;
|
|
memset(L, 0, 16);
|
|
continue;
|
|
}
|
|
float best = 0;
|
|
float scale = max/(2*kMaxQ-1);
|
|
is_on_grid[0] = is_on_grid[1] = true;
|
|
for (int is = -9; is <= 9; ++is) {
|
|
float id = (2*kMaxQ-1+is*0.1f)/max;
|
|
float this_scale = 1/id;
|
|
for (int k = 0; k < 2; ++k) {
|
|
for (int i = 0; i < 8; ++i) {
|
|
int l = nearest_int(0.5f*(id*xval[8*k+i]-1));
|
|
Laux[8*k+i] = MAX(0, MIN(kMaxQ-1, l));
|
|
}
|
|
uint16_t u = 0;
|
|
for (int i = 0; i < 8; ++i) u |= (Laux[8*k+i] << 2*i);
|
|
int grid_index = kmap_q2xs[u];
|
|
is_on_grid_aux[k] = true;
|
|
if (grid_index < 0) {
|
|
is_on_grid_aux[k] = false;
|
|
const uint16_t * neighbours = kneighbors_q2xs - kmap_q2xs[u] - 1;
|
|
grid_index = iq2_find_best_neighbour(neighbours, kgrid_q2xs, xval + 8*k, waux + 8*k, this_scale, Laux + 8*k);
|
|
}
|
|
}
|
|
float sumqx = 0, sumq2 = 0;
|
|
for (int i = 0; i < 16; ++i) {
|
|
float w = weight[i];
|
|
float q = 2*Laux[i] + 1;
|
|
sumqx += w*xval[i]*q;
|
|
sumq2 += w*q*q;
|
|
}
|
|
if (sumq2 > 0 && sumqx*sumqx > best*sumq2) {
|
|
scale = sumqx/sumq2; best = scale*sumqx;
|
|
for (int i = 0; i < 16; ++i) L[i] = Laux[i];
|
|
for (int k = 0; k < 2; ++k) is_on_grid[k] = is_on_grid_aux[k];
|
|
}
|
|
}
|
|
int n_not_ongrid = 0;
|
|
for (int k = 0; k < 2; ++k) if (!is_on_grid[k]) ++n_not_ongrid;
|
|
if (n_not_ongrid > 0 && scale > 0) {
|
|
float id = 1/scale;
|
|
for (int k = 0; k < 2; ++k) {
|
|
if (is_on_grid[k]) continue;
|
|
uint16_t u = 0;
|
|
for (int i = 0; i < 8; ++i) {
|
|
int l = nearest_int(0.5f*(id*xval[8*k+i]-1));
|
|
l = MAX(0, MIN(kMaxQ-1, l));
|
|
u |= (l << 2*i);
|
|
L[8*k + i] = l;
|
|
}
|
|
int grid_index = kmap_q2xs[u];
|
|
if (grid_index < 0) {
|
|
const uint16_t * neighbours = kneighbors_q2xs - kmap_q2xs[u] - 1;
|
|
grid_index = iq2_find_best_neighbour(neighbours, kgrid_q2xs, xval + 8*k, waux + 8*k, scale, L + 8*k);
|
|
}
|
|
}
|
|
float sumqx = 0, sumq2 = 0;
|
|
for (int i = 0; i < 16; ++i) {
|
|
float w = weight[i];
|
|
float q = 2*L[i] + 1;
|
|
sumqx += w*xval[i]*q;
|
|
sumq2 += w*q*q;
|
|
}
|
|
if (sumq2 > 0) scale = sumqx/sumq2;
|
|
}
|
|
if (scale < 0) {
|
|
scale = -scale;
|
|
for (int k = 0; k < 2; ++k) block_signs[k] = (~block_signs[k]) & 127;
|
|
}
|
|
for (int k = 0; k < 2; ++k) {
|
|
uint16_t u = 0;
|
|
for (int i = 0; i < 8; ++i) u |= (L[8*k+i] << 2*i);
|
|
int grid_index = kmap_q2xs[u];
|
|
if (grid_index < 0) {
|
|
printf("Oops: found point %u not on grid:", u);
|
|
for (int i = 0; i < 8; ++i) printf(" %d", L[8*k+i]);
|
|
printf("\n");
|
|
GGML_ABORT("fatal error");
|
|
}
|
|
q2[2*ib+k] = grid_index | (block_signs[k] << 9);
|
|
}
|
|
GGML_ASSERT(scale >= 0);
|
|
scales[ib] = scale;
|
|
max_scale = MAX(max_scale, scale);
|
|
}
|
|
|
|
if (!max_scale) {
|
|
memset(y[ibl].qs, 0, QK_K/4);
|
|
continue;
|
|
}
|
|
|
|
float d = max_scale/31;
|
|
y[ibl].d = GGML_FP32_TO_FP16(d);
|
|
float id = 1/d;
|
|
for (int ib = 0; ib < QK_K/16; ++ib) {
|
|
int l = nearest_int(0.5f*(id*scales[ib]-1));
|
|
l = MAX(0, MIN(15, l));
|
|
if (ib%2 == 0) y[ibl].scales[ib/2] = l;
|
|
else y[ibl].scales[ib/2] |= (l << 4);
|
|
}
|
|
memcpy(y[ibl].qs, q2, QK_K/4);
|
|
|
|
}
|
|
}
|
|
|
|
size_t quantize_iq2_xxs(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
|
|
GGML_ASSERT(n_per_row%QK_K == 0);
|
|
int64_t nblock = n_per_row/QK_K;
|
|
char * qrow = (char *)dst;
|
|
for (int64_t row = 0; row < nrow; ++row) {
|
|
quantize_row_iq2_xxs_impl(src, qrow, n_per_row, quant_weights);
|
|
src += n_per_row;
|
|
qrow += nblock*sizeof(block_iq2_xxs);
|
|
}
|
|
return nrow * nblock * sizeof(block_iq2_xxs);
|
|
}
|
|
|
|
size_t quantize_iq2_xs(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
|
|
GGML_ASSERT(n_per_row%QK_K == 0);
|
|
int64_t nblock = n_per_row/QK_K;
|
|
char * qrow = (char *)dst;
|
|
for (int64_t row = 0; row < nrow; ++row) {
|
|
quantize_row_iq2_xs_impl(src, qrow, n_per_row, quant_weights);
|
|
src += n_per_row;
|
|
qrow += nblock*sizeof(block_iq2_xs);
|
|
}
|
|
return nrow * nblock * sizeof(block_iq2_xs);
|
|
}
|
|
|
|
//
|
|
// ============================================= 3-bit using D4 lattice
|
|
//
|
|
|
|
typedef struct {
|
|
uint32_t * grid;
|
|
int * map;
|
|
uint16_t * neighbours;
|
|
} iq3_entry_t;
|
|
|
|
static iq3_entry_t iq3_data[2] = {
|
|
{NULL, NULL, NULL},
|
|
{NULL, NULL, NULL},
|
|
};
|
|
|
|
static inline int iq3_data_index(int grid_size) {
|
|
(void)grid_size;
|
|
GGML_ASSERT(grid_size == 256 || grid_size == 512);
|
|
return grid_size == 256 ? 0 : 1;
|
|
}
|
|
|
|
static int iq3_compare_func(const void * left, const void * right) {
|
|
const int * l = (const int *)left;
|
|
const int * r = (const int *)right;
|
|
return l[0] < r[0] ? -1 : l[0] > r[0] ? 1 : l[1] < r[1] ? -1 : l[1] > r[1] ? 1 : 0;
|
|
}
|
|
|
|
void iq3xs_init_impl(int grid_size) {
|
|
const int gindex = iq3_data_index(grid_size);
|
|
if (iq3_data[gindex].grid) {
|
|
return;
|
|
}
|
|
static const uint16_t kgrid_256[256] = {
|
|
0, 2, 4, 9, 11, 15, 16, 18, 25, 34, 59, 61, 65, 67, 72, 74,
|
|
81, 85, 88, 90, 97, 108, 120, 128, 130, 132, 137, 144, 146, 153, 155, 159,
|
|
169, 175, 189, 193, 199, 200, 202, 213, 248, 267, 287, 292, 303, 315, 317, 321,
|
|
327, 346, 362, 413, 436, 456, 460, 462, 483, 497, 513, 515, 520, 522, 529, 531,
|
|
536, 538, 540, 551, 552, 576, 578, 585, 592, 594, 641, 643, 648, 650, 657, 664,
|
|
698, 704, 706, 720, 729, 742, 758, 769, 773, 808, 848, 852, 870, 889, 901, 978,
|
|
992, 1024, 1026, 1033, 1035, 1040, 1042, 1046, 1049, 1058, 1089, 1091, 1093, 1096, 1098, 1105,
|
|
1112, 1139, 1143, 1144, 1152, 1154, 1161, 1167, 1168, 1170, 1183, 1184, 1197, 1217, 1224, 1228,
|
|
1272, 1276, 1309, 1323, 1347, 1367, 1377, 1404, 1473, 1475, 1486, 1509, 1537, 1544, 1546, 1553,
|
|
1555, 1576, 1589, 1594, 1600, 1602, 1616, 1625, 1636, 1638, 1665, 1667, 1672, 1685, 1706, 1722,
|
|
1737, 1755, 1816, 1831, 1850, 1856, 1862, 1874, 1901, 1932, 1950, 1971, 2011, 2032, 2052, 2063,
|
|
2077, 2079, 2091, 2095, 2172, 2192, 2207, 2208, 2224, 2230, 2247, 2277, 2308, 2345, 2356, 2389,
|
|
2403, 2424, 2501, 2504, 2506, 2520, 2570, 2593, 2616, 2624, 2630, 2646, 2669, 2700, 2714, 2746,
|
|
2754, 2795, 2824, 2835, 2839, 2874, 2882, 2905, 2984, 3028, 3042, 3092, 3108, 3110, 3124, 3153,
|
|
3185, 3215, 3252, 3288, 3294, 3364, 3397, 3434, 3483, 3523, 3537, 3587, 3589, 3591, 3592, 3610,
|
|
3626, 3670, 3680, 3722, 3749, 3754, 3776, 3789, 3803, 3824, 3857, 3873, 3904, 3906, 3924, 3992,
|
|
};
|
|
static const uint16_t kgrid_512[512] = {
|
|
0, 1, 2, 5, 7, 8, 9, 10, 12, 14, 16, 17, 21, 27, 32, 34,
|
|
37, 39, 41, 43, 48, 50, 57, 60, 63, 64, 65, 66, 68, 72, 73, 77,
|
|
80, 83, 87, 89, 93, 100, 113, 117, 122, 128, 129, 133, 135, 136, 139, 142,
|
|
145, 149, 152, 156, 162, 165, 167, 169, 171, 184, 187, 195, 201, 205, 208, 210,
|
|
217, 219, 222, 228, 232, 234, 247, 249, 253, 256, 267, 271, 273, 276, 282, 288,
|
|
291, 297, 312, 322, 324, 336, 338, 342, 347, 353, 357, 359, 374, 379, 390, 393,
|
|
395, 409, 426, 441, 448, 450, 452, 464, 466, 470, 475, 488, 492, 512, 513, 514,
|
|
516, 520, 521, 523, 525, 527, 528, 530, 537, 540, 542, 556, 558, 561, 570, 576,
|
|
577, 579, 582, 584, 588, 593, 600, 603, 609, 616, 618, 632, 638, 640, 650, 653,
|
|
655, 656, 660, 666, 672, 675, 685, 688, 698, 705, 708, 711, 712, 715, 721, 727,
|
|
728, 732, 737, 754, 760, 771, 773, 778, 780, 793, 795, 802, 806, 808, 812, 833,
|
|
840, 843, 849, 856, 858, 873, 912, 916, 919, 932, 934, 961, 963, 968, 970, 977,
|
|
989, 993, 1010, 1016, 1024, 1025, 1027, 1029, 1031, 1032, 1034, 1036, 1038, 1041, 1043, 1047,
|
|
1048, 1050, 1057, 1059, 1061, 1064, 1066, 1079, 1080, 1083, 1085, 1088, 1090, 1096, 1099, 1103,
|
|
1106, 1109, 1113, 1116, 1122, 1129, 1153, 1156, 1159, 1169, 1171, 1176, 1183, 1185, 1195, 1199,
|
|
1209, 1212, 1216, 1218, 1221, 1225, 1234, 1236, 1241, 1243, 1250, 1256, 1270, 1281, 1287, 1296,
|
|
1299, 1306, 1309, 1313, 1338, 1341, 1348, 1353, 1362, 1375, 1376, 1387, 1400, 1408, 1410, 1415,
|
|
1425, 1453, 1457, 1477, 1481, 1494, 1496, 1507, 1512, 1538, 1545, 1547, 1549, 1551, 1554, 1561,
|
|
1563, 1565, 1570, 1572, 1575, 1577, 1587, 1593, 1601, 1603, 1605, 1612, 1617, 1619, 1632, 1648,
|
|
1658, 1662, 1664, 1674, 1680, 1690, 1692, 1704, 1729, 1736, 1740, 1745, 1747, 1751, 1752, 1761,
|
|
1763, 1767, 1773, 1787, 1795, 1801, 1806, 1810, 1817, 1834, 1840, 1844, 1857, 1864, 1866, 1877,
|
|
1882, 1892, 1902, 1915, 1934, 1953, 1985, 1987, 2000, 2002, 2013, 2048, 2052, 2058, 2064, 2068,
|
|
2071, 2074, 2081, 2088, 2104, 2114, 2119, 2121, 2123, 2130, 2136, 2141, 2147, 2153, 2157, 2177,
|
|
2179, 2184, 2189, 2193, 2203, 2208, 2223, 2226, 2232, 2244, 2249, 2251, 2256, 2258, 2265, 2269,
|
|
2304, 2306, 2324, 2335, 2336, 2361, 2373, 2375, 2385, 2418, 2443, 2460, 2480, 2504, 2509, 2520,
|
|
2531, 2537, 2562, 2568, 2572, 2578, 2592, 2596, 2599, 2602, 2614, 2620, 2625, 2627, 2629, 2634,
|
|
2641, 2650, 2682, 2688, 2697, 2707, 2712, 2718, 2731, 2754, 2759, 2760, 2775, 2788, 2793, 2805,
|
|
2811, 2817, 2820, 2832, 2842, 2854, 2890, 2902, 2921, 2923, 2978, 3010, 3012, 3026, 3081, 3083,
|
|
3085, 3097, 3099, 3120, 3136, 3152, 3159, 3188, 3210, 3228, 3234, 3245, 3250, 3256, 3264, 3276,
|
|
3281, 3296, 3349, 3363, 3378, 3392, 3395, 3420, 3440, 3461, 3488, 3529, 3531, 3584, 3588, 3591,
|
|
3600, 3602, 3614, 3616, 3628, 3634, 3650, 3657, 3668, 3683, 3685, 3713, 3716, 3720, 3726, 3729,
|
|
3736, 3753, 3778, 3802, 3805, 3819, 3841, 3845, 3851, 3856, 3880, 3922, 3938, 3970, 3993, 4032,
|
|
};
|
|
|
|
const int kmap_size = 4096;
|
|
const int nwant = grid_size == 256 ? 2 : 3;
|
|
const uint16_t * kgrid = grid_size == 256 ? kgrid_256 : kgrid_512;
|
|
uint32_t * kgrid_q3xs;
|
|
int * kmap_q3xs;
|
|
uint16_t * kneighbors_q3xs;
|
|
|
|
//printf("================================================================= %s(grid_size = %d)\n", __func__, grid_size);
|
|
uint32_t * the_grid = (uint32_t *)malloc(grid_size*sizeof(uint32_t));
|
|
for (int k = 0; k < grid_size; ++k) {
|
|
int8_t * pos = (int8_t *)(the_grid + k);
|
|
for (int i = 0; i < 4; ++i) {
|
|
int l = (kgrid[k] >> 3*i) & 0x7;
|
|
pos[i] = 2*l + 1;
|
|
}
|
|
}
|
|
kgrid_q3xs = the_grid;
|
|
iq3_data[gindex].grid = the_grid;
|
|
kmap_q3xs = (int *)malloc(kmap_size*sizeof(int));
|
|
iq3_data[gindex].map = kmap_q3xs;
|
|
for (int i = 0; i < kmap_size; ++i) kmap_q3xs[i] = -1;
|
|
uint32_t aux32;
|
|
uint8_t * aux8 = (uint8_t *)&aux32;
|
|
for (int i = 0; i < grid_size; ++i) {
|
|
aux32 = kgrid_q3xs[i];
|
|
uint16_t index = 0;
|
|
for (int k=0; k<4; ++k) {
|
|
uint16_t q = (aux8[k] - 1)/2;
|
|
index |= (q << 3*k);
|
|
}
|
|
kmap_q3xs[index] = i;
|
|
}
|
|
int8_t pos[4];
|
|
int * dist2 = (int *)malloc(2*grid_size*sizeof(int));
|
|
int num_neighbors = 0, num_not_in_map = 0;
|
|
for (int i = 0; i < kmap_size; ++i) {
|
|
if (kmap_q3xs[i] >= 0) continue;
|
|
++num_not_in_map;
|
|
for (int k = 0; k < 4; ++k) {
|
|
int l = (i >> 3*k) & 0x7;
|
|
pos[k] = 2*l + 1;
|
|
}
|
|
for (int j = 0; j < grid_size; ++j) {
|
|
const int8_t * pg = (const int8_t *)(kgrid_q3xs + j);
|
|
int d2 = 0;
|
|
for (int k = 0; k < 4; ++k) d2 += (pg[k] - pos[k])*(pg[k] - pos[k]);
|
|
dist2[2*j+0] = d2;
|
|
dist2[2*j+1] = j;
|
|
}
|
|
qsort(dist2, grid_size, 2*sizeof(int), iq3_compare_func);
|
|
int n = 0; int d2 = dist2[0];
|
|
int nhave = 1;
|
|
for (int j = 0; j < grid_size; ++j) {
|
|
if (dist2[2*j] > d2) {
|
|
if (nhave == nwant) break;
|
|
d2 = dist2[2*j];
|
|
++nhave;
|
|
}
|
|
++n;
|
|
}
|
|
num_neighbors += n;
|
|
}
|
|
//printf("%s: %d neighbours in total\n", __func__, num_neighbors);
|
|
kneighbors_q3xs = (uint16_t *)malloc((num_neighbors + num_not_in_map)*sizeof(uint16_t));
|
|
iq3_data[gindex].neighbours = kneighbors_q3xs;
|
|
int counter = 0;
|
|
for (int i = 0; i < kmap_size; ++i) {
|
|
if (kmap_q3xs[i] >= 0) continue;
|
|
for (int k = 0; k < 4; ++k) {
|
|
int l = (i >> 3*k) & 0x7;
|
|
pos[k] = 2*l + 1;
|
|
}
|
|
for (int j = 0; j < grid_size; ++j) {
|
|
const int8_t * pg = (const int8_t *)(kgrid_q3xs + j);
|
|
int d2 = 0;
|
|
for (int k = 0; k < 4; ++k) d2 += (pg[k] - pos[k])*(pg[k] - pos[k]);
|
|
dist2[2*j+0] = d2;
|
|
dist2[2*j+1] = j;
|
|
}
|
|
qsort(dist2, grid_size, 2*sizeof(int), iq3_compare_func);
|
|
kmap_q3xs[i] = -(counter + 1);
|
|
int d2 = dist2[0];
|
|
uint16_t * start = &kneighbors_q3xs[counter++];
|
|
int n = 0, nhave = 1;
|
|
for (int j = 0; j < grid_size; ++j) {
|
|
if (dist2[2*j] > d2) {
|
|
if (nhave == nwant) break;
|
|
d2 = dist2[2*j];
|
|
++nhave;
|
|
}
|
|
kneighbors_q3xs[counter++] = dist2[2*j+1];
|
|
++n;
|
|
}
|
|
*start = n;
|
|
}
|
|
free(dist2);
|
|
}
|
|
|
|
void iq3xs_free_impl(int grid_size) {
|
|
GGML_ASSERT(grid_size == 256 || grid_size == 512);
|
|
const int gindex = iq3_data_index(grid_size);
|
|
if (iq3_data[gindex].grid) {
|
|
free(iq3_data[gindex].grid); iq3_data[gindex].grid = NULL;
|
|
free(iq3_data[gindex].map); iq3_data[gindex].map = NULL;
|
|
free(iq3_data[gindex].neighbours); iq3_data[gindex].neighbours = NULL;
|
|
}
|
|
}
|
|
|
|
static int iq3_find_best_neighbour(const uint16_t * restrict neighbours, const uint32_t * restrict grid,
|
|
const float * restrict xval, const float * restrict weight, float scale, int8_t * restrict L) {
|
|
int num_neighbors = neighbours[0];
|
|
GGML_ASSERT(num_neighbors > 0);
|
|
float best_d2 = FLT_MAX;
|
|
int grid_index = -1;
|
|
for (int j = 1; j <= num_neighbors; ++j) {
|
|
const int8_t * pg = (const int8_t *)(grid + neighbours[j]);
|
|
float d2 = 0;
|
|
for (int i = 0; i < 4; ++i) {
|
|
float q = pg[i];
|
|
float diff = scale*q - xval[i];
|
|
d2 += weight[i]*diff*diff;
|
|
}
|
|
if (d2 < best_d2) {
|
|
best_d2 = d2; grid_index = neighbours[j];
|
|
}
|
|
}
|
|
GGML_ASSERT(grid_index >= 0);
|
|
const int8_t * pg = (const int8_t *)(grid + grid_index);
|
|
for (int i = 0; i < 4; ++i) L[i] = (pg[i] - 1)/2;
|
|
return grid_index;
|
|
}
|
|
|
|
static void quantize_row_iq3_xxs_impl(int grid_size, const float * restrict x, void * restrict vy, int64_t n,
|
|
const float * restrict quant_weights) {
|
|
|
|
const int gindex = iq3_data_index(grid_size);
|
|
|
|
const uint32_t * kgrid_q3xs = iq3_data[gindex].grid;
|
|
const int * kmap_q3xs = iq3_data[gindex].map;
|
|
const uint16_t * kneighbors_q3xs = iq3_data[gindex].neighbours;
|
|
|
|
//GGML_ASSERT(quant_weights && "missing quantization weights");
|
|
GGML_ASSERT(kgrid_q3xs && "forgot to call ggml_quantize_init()?");
|
|
GGML_ASSERT(kmap_q3xs && "forgot to call ggml_quantize_init()?");
|
|
GGML_ASSERT(kneighbors_q3xs && "forgot to call ggml_quantize_init()?");
|
|
GGML_ASSERT(n%QK_K == 0);
|
|
|
|
const int kMaxQ = 8;
|
|
|
|
const int64_t nbl = n/QK_K;
|
|
|
|
ggml_fp16_t * dh;
|
|
uint8_t * qs;
|
|
int block_size;
|
|
if (grid_size == 256) {
|
|
block_iq3_xxs * y = vy;
|
|
dh = &y->d;
|
|
qs = y->qs;
|
|
block_size = sizeof(block_iq3_xxs);
|
|
} else {
|
|
block_iq3_s * y = vy;
|
|
dh = &y->d;
|
|
qs = y->qs;
|
|
block_size = sizeof(block_iq3_s);
|
|
}
|
|
int quant_size = block_size - sizeof(ggml_fp16_t);
|
|
|
|
float scales[QK_K/32];
|
|
float weight[32];
|
|
float xval[32];
|
|
int8_t L[32];
|
|
int8_t Laux[32];
|
|
float waux[32];
|
|
bool is_on_grid[8];
|
|
bool is_on_grid_aux[8];
|
|
uint8_t block_signs[8];
|
|
uint8_t q3[3*(QK_K/8)+QK_K/32];
|
|
uint32_t * scales_and_signs = (uint32_t *)(q3 + QK_K/4);
|
|
uint8_t * qh = q3 + 3*(QK_K/8);
|
|
|
|
for (int ibl = 0; ibl < nbl; ++ibl) {
|
|
|
|
dh[0] = GGML_FP32_TO_FP16(0.f);
|
|
memset(q3, 0, 3*QK_K/8+QK_K/32);
|
|
|
|
float max_scale = 0;
|
|
|
|
const float * xbl = x + QK_K*ibl;
|
|
float sumx2 = 0;
|
|
for (int i = 0; i < QK_K; ++i) sumx2 += xbl[i]*xbl[i];
|
|
float sigma2 = 2*sumx2/QK_K;
|
|
|
|
for (int ib = 0; ib < QK_K/32; ++ib) {
|
|
const float * xb = xbl + 32*ib;
|
|
if (quant_weights) {
|
|
const float * qw = quant_weights + QK_K*ibl + 32*ib;
|
|
for (int i = 0; i < 32; ++i) weight[i] = qw[i] * sqrtf(sigma2 + xb[i]*xb[i]);
|
|
} else {
|
|
for (int i = 0; i < 32; ++i) weight[i] = xb[i]*xb[i];
|
|
}
|
|
for (int i = 0; i < 32; ++i) waux[i] = sqrtf(weight[i]);
|
|
for (int k = 0; k < 4; ++k) {
|
|
int nflip = 0;
|
|
uint8_t s = 0;
|
|
for (int i = 0; i < 8; ++i) {
|
|
if (xb[8*k + i] >= 0) xval[8*k + i] = xb[8*k + i];
|
|
else {
|
|
xval[8*k + i] = -xb[8*k + i]; ++nflip; s |= (1 << i);
|
|
}
|
|
}
|
|
if (nflip%2) {
|
|
int imin = 0; float min = weight[8*k+imin]*xb[8*k+imin]*xb[8*k+imin];
|
|
for (int i = 1; i < 8; ++i) {
|
|
float ax = weight[8*k+i]*xb[8*k+i]*xb[8*k+i];
|
|
if (ax < min) {
|
|
min = ax; imin = i;
|
|
}
|
|
}
|
|
xval[8*k+imin] = -xval[8*k+imin];
|
|
s ^= (1 << imin);
|
|
}
|
|
block_signs[k] = s & 127;
|
|
}
|
|
float max = xval[0];
|
|
for (int i = 1; i < 32; ++i) max = MAX(max, xval[i]);
|
|
if (max < GROUP_MAX_EPS_IQ3_XXS) {
|
|
scales[ib] = 0;
|
|
memset(L, 0, 32);
|
|
continue;
|
|
}
|
|
float best = 0;
|
|
float scale = max/(2*kMaxQ-1);
|
|
for (int is = -15; is <= 15; ++is) {
|
|
float id = (2*kMaxQ-1+is*0.2f)/max;
|
|
float this_scale = 1/id;
|
|
for (int k = 0; k < 8; ++k) {
|
|
for (int i = 0; i < 4; ++i) {
|
|
int l = nearest_int(0.5f*(id*xval[4*k+i]-1));
|
|
Laux[4*k+i] = MAX(0, MIN(kMaxQ-1, l));
|
|
}
|
|
uint16_t u = 0;
|
|
for (int i = 0; i < 4; ++i) u |= (Laux[4*k+i] << 3*i);
|
|
int grid_index = kmap_q3xs[u];
|
|
is_on_grid_aux[k] = true;
|
|
if (grid_index < 0) {
|
|
is_on_grid_aux[k] = false;
|
|
const uint16_t * neighbours = kneighbors_q3xs - kmap_q3xs[u] - 1;
|
|
grid_index = iq3_find_best_neighbour(neighbours, kgrid_q3xs, xval + 4*k, waux + 4*k, this_scale, Laux + 4*k);
|
|
}
|
|
}
|
|
float sumqx = 0, sumq2 = 0;
|
|
for (int i = 0; i < 32; ++i) {
|
|
float w = weight[i];
|
|
float q = 2*Laux[i] + 1;
|
|
sumqx += w*xval[i]*q;
|
|
sumq2 += w*q*q;
|
|
}
|
|
if (sumq2 > 0 && sumqx*sumqx > best*sumq2) {
|
|
scale = sumqx/sumq2; best = scale*sumqx;
|
|
for (int i = 0; i < 32; ++i) L[i] = Laux[i];
|
|
for (int k = 0; k < 8; ++k) is_on_grid[k] = is_on_grid_aux[k];
|
|
}
|
|
}
|
|
int n_not_ongrid = 0;
|
|
for (int k = 0; k < 8; ++k) if (!is_on_grid[k]) ++n_not_ongrid;
|
|
if (n_not_ongrid > 0 && scale > 0) {
|
|
float id = 1/scale;
|
|
for (int k = 0; k < 8; ++k) {
|
|
if (is_on_grid[k]) continue;
|
|
uint16_t u = 0;
|
|
for (int i = 0; i < 4; ++i) {
|
|
int l = nearest_int(0.5f*(id*xval[4*k+i]-1));
|
|
l = MAX(0, MIN(kMaxQ-1, l));
|
|
u |= (l << 3*i);
|
|
}
|
|
int grid_index = kmap_q3xs[u];
|
|
if (grid_index < 0) {
|
|
const uint16_t * neighbours = kneighbors_q3xs - kmap_q3xs[u] - 1;
|
|
grid_index = iq3_find_best_neighbour(neighbours, kgrid_q3xs, xval + 4*k, waux + 4*k, scale, L + 4*k);
|
|
}
|
|
const int8_t * pg = (const int8_t *)(kgrid_q3xs + grid_index);
|
|
for (int i = 0; i < 4; ++i) L[4*k+i] = (pg[i] - 1)/2;
|
|
}
|
|
float sumqx = 0, sumq2 = 0;
|
|
for (int i = 0; i < 32; ++i) {
|
|
float w = weight[i];
|
|
float q = 2*L[i] + 1;
|
|
sumqx += w*xval[i]*q;
|
|
sumq2 += w*q*q;
|
|
}
|
|
if (sumq2 > 0) scale = sumqx/sumq2;
|
|
}
|
|
if (scale < 0) {
|
|
// This should never happen, but just in case, flip scale so that it is positive (we use uint's to encode the scale)
|
|
// and correspondingly flip quant signs.
|
|
scale = -scale;
|
|
for (int k = 0; k < 4; ++k) block_signs[k] = (~block_signs[k]) & 127;
|
|
}
|
|
for (int k = 0; k < 8; ++k) {
|
|
uint16_t u = 0;
|
|
for (int i = 0; i < 4; ++i) u |= (L[4*k+i] << 3*i);
|
|
int grid_index = kmap_q3xs[u];
|
|
if (grid_index < 0) {
|
|
printf("Oops: found point %u not on grid:", u);
|
|
for (int i = 0; i < 4; ++i) printf(" %d", L[4*k+i]);
|
|
printf("\n");
|
|
GGML_ABORT("fatal error");
|
|
}
|
|
if (grid_size == 256) {
|
|
q3[8*ib+k] = grid_index;
|
|
} else {
|
|
q3[8*ib+k] = grid_index & 255;
|
|
qh[ib] |= ((grid_index >> 8) << k);
|
|
}
|
|
|
|
}
|
|
scales_and_signs[ib] = block_signs[0] | (block_signs[1] << 7) | (block_signs[2] << 14) | (block_signs[3] << 21);
|
|
GGML_ASSERT(scale >= 0);
|
|
scales[ib] = scale;
|
|
max_scale = MAX(max_scale, scale);
|
|
}
|
|
|
|
if (!max_scale) {
|
|
memset(qs, 0, quant_size);
|
|
dh += block_size/sizeof(ggml_fp16_t);
|
|
qs += block_size;
|
|
continue;
|
|
}
|
|
|
|
float d = max_scale/31;
|
|
dh[0] = GGML_FP32_TO_FP16(d * 1.0125f); // small improvement via this fudge factor
|
|
float id = 1/d;
|
|
for (int ib = 0; ib < QK_K/32; ++ib) {
|
|
int l = nearest_int(0.5f*(id*scales[ib]-1));
|
|
l = MAX(0, MIN(15, l));
|
|
scales_and_signs[ib] |= ((uint32_t)l << 28);
|
|
}
|
|
memcpy(qs, q3, quant_size);
|
|
|
|
dh += block_size/sizeof(ggml_fp16_t);
|
|
qs += block_size;
|
|
|
|
}
|
|
}
|
|
|
|
size_t quantize_iq3_xxs(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
|
|
GGML_ASSERT(n_per_row%QK_K == 0);
|
|
int64_t nblock = n_per_row/QK_K;
|
|
char * qrow = (char *)dst;
|
|
for (int64_t row = 0; row < nrow; ++row) {
|
|
quantize_row_iq3_xxs_impl(256, src, qrow, n_per_row, quant_weights);
|
|
src += n_per_row;
|
|
qrow += nblock*sizeof(block_iq3_xxs);
|
|
}
|
|
return nrow * nblock * sizeof(block_iq3_xxs);
|
|
}
|
|
|
|
void quantize_row_iq3_xxs_ref(const float * restrict x, block_iq3_xxs * restrict y, int64_t k) {
|
|
assert(k % QK_K == 0);
|
|
quantize_row_iq3_xxs_impl(256, x, y, k, NULL);
|
|
}
|
|
|
|
static void quantize_row_iq3_s_impl(int block_size, const float * restrict x, void * restrict vy, int n,
|
|
const float * restrict quant_weights,
|
|
float * scales,
|
|
float * weight,
|
|
float * xval,
|
|
int8_t * L,
|
|
int8_t * Laux,
|
|
float * waux,
|
|
bool * is_on_grid,
|
|
bool * is_on_grid_aux,
|
|
uint8_t * block_signs) {
|
|
|
|
const int gindex = iq3_data_index(512);
|
|
|
|
const uint32_t * kgrid_q3xs = iq3_data[gindex].grid;
|
|
const int * kmap_q3xs = iq3_data[gindex].map;
|
|
const uint16_t * kneighbors_q3xs = iq3_data[gindex].neighbours;
|
|
|
|
//GGML_ASSERT(quant_weights && "missing quantization weights");
|
|
GGML_ASSERT(kgrid_q3xs && "forgot to call ggml_quantize_init()?");
|
|
GGML_ASSERT(kmap_q3xs && "forgot to call ggml_quantize_init()?");
|
|
GGML_ASSERT(kneighbors_q3xs && "forgot to call ggml_quantize_init()?");
|
|
GGML_ASSERT(n%QK_K == 0);
|
|
|
|
const int kMaxQ = 8;
|
|
|
|
const int64_t nbl = n/QK_K;
|
|
|
|
block_iq3_s * y = vy;
|
|
|
|
const int bs4 = block_size/4;
|
|
const int bs8 = block_size/8;
|
|
|
|
for (int ibl = 0; ibl < nbl; ++ibl) {
|
|
|
|
memset(&y[ibl], 0, sizeof(block_iq3_s));
|
|
y[ibl].d = GGML_FP32_TO_FP16(0.f);
|
|
|
|
uint8_t * qs = y[ibl].qs;
|
|
uint8_t * qh = y[ibl].qh;
|
|
uint8_t * signs = y[ibl].signs;
|
|
|
|
float max_scale = 0;
|
|
|
|
const float * xbl = x + QK_K*ibl;
|
|
float sumx2 = 0;
|
|
for (int i = 0; i < QK_K; ++i) sumx2 += xbl[i]*xbl[i];
|
|
float sigma2 = 2*sumx2/QK_K;
|
|
|
|
for (int ib = 0; ib < QK_K/block_size; ++ib) {
|
|
const float * xb = xbl + block_size*ib;
|
|
if (quant_weights) {
|
|
const float * qw = quant_weights + QK_K*ibl + block_size*ib;
|
|
for (int i = 0; i < block_size; ++i) weight[i] = qw[i] * sqrtf(sigma2 + xb[i]*xb[i]);
|
|
} else {
|
|
for (int i = 0; i < block_size; ++i) weight[i] = xb[i]*xb[i];
|
|
}
|
|
for (int i = 0; i < block_size; ++i) waux[i] = sqrtf(weight[i]);
|
|
for (int k = 0; k < bs8; ++k) {
|
|
uint8_t s = 0;
|
|
for (int i = 0; i < 8; ++i) {
|
|
if (xb[8*k + i] >= 0) xval[8*k + i] = xb[8*k + i];
|
|
else {
|
|
xval[8*k + i] = -xb[8*k + i]; s |= (1 << i);
|
|
}
|
|
}
|
|
block_signs[k] = s;
|
|
}
|
|
float max = xval[0];
|
|
for (int i = 1; i < block_size; ++i) max = MAX(max, xval[i]);
|
|
if (!max) {
|
|
scales[ib] = 0;
|
|
continue;
|
|
}
|
|
float best = 0;
|
|
float scale = max/(2*kMaxQ-1);
|
|
for (int k = 0; k < bs4; ++k) is_on_grid[k] = false;
|
|
for (int is = -9; is <= 9; ++is) {
|
|
float id = (2*kMaxQ-1+is*0.2f)/max;
|
|
float this_scale = 1/id;
|
|
for (int k = 0; k < bs4; ++k) {
|
|
for (int i = 0; i < 4; ++i) {
|
|
int l = nearest_int(0.5f*(id*xval[4*k+i]-1));
|
|
Laux[4*k+i] = MAX(0, MIN(kMaxQ-1, l));
|
|
}
|
|
uint16_t u = 0;
|
|
for (int i = 0; i < 4; ++i) u |= (Laux[4*k+i] << 3*i);
|
|
int grid_index = kmap_q3xs[u];
|
|
is_on_grid_aux[k] = true;
|
|
if (grid_index < 0) {
|
|
is_on_grid_aux[k] = false;
|
|
const uint16_t * neighbours = kneighbors_q3xs - kmap_q3xs[u] - 1;
|
|
grid_index = iq3_find_best_neighbour(neighbours, kgrid_q3xs, xval + 4*k, waux + 4*k, this_scale, Laux + 4*k);
|
|
}
|
|
}
|
|
float sumqx = 0, sumq2 = 0;
|
|
for (int i = 0; i < block_size; ++i) {
|
|
float w = weight[i];
|
|
float q = 2*Laux[i] + 1;
|
|
sumqx += w*xval[i]*q;
|
|
sumq2 += w*q*q;
|
|
}
|
|
if (sumq2 > 0 && sumqx*sumqx > best*sumq2) {
|
|
scale = sumqx/sumq2; best = scale*sumqx;
|
|
for (int i = 0; i < block_size; ++i) L[i] = Laux[i];
|
|
for (int k = 0; k < bs4; ++k) is_on_grid[k] = is_on_grid_aux[k];
|
|
}
|
|
}
|
|
int n_not_ongrid = 0;
|
|
for (int k = 0; k < bs4; ++k) if (!is_on_grid[k]) ++n_not_ongrid;
|
|
if (n_not_ongrid > 0 && scale > 0) {
|
|
float id = 1/scale;
|
|
for (int k = 0; k < bs4; ++k) {
|
|
//if (is_on_grid[k]) continue;
|
|
uint16_t u = 0;
|
|
for (int i = 0; i < 4; ++i) {
|
|
int l = nearest_int(0.5f*(id*xval[4*k+i]-1));
|
|
l = MAX(0, MIN(kMaxQ-1, l));
|
|
u |= (l << 3*i);
|
|
}
|
|
int grid_index = kmap_q3xs[u];
|
|
if (grid_index < 0) {
|
|
const uint16_t * neighbours = kneighbors_q3xs - kmap_q3xs[u] - 1;
|
|
grid_index = iq3_find_best_neighbour(neighbours, kgrid_q3xs, xval + 4*k, waux + 4*k, scale, L + 4*k);
|
|
}
|
|
const int8_t * pg = (const int8_t *)(kgrid_q3xs + grid_index);
|
|
for (int i = 0; i < 4; ++i) L[4*k+i] = (pg[i] - 1)/2;
|
|
}
|
|
float sumqx = 0, sumq2 = 0;
|
|
for (int i = 0; i < block_size; ++i) {
|
|
float w = weight[i];
|
|
float q = 2*L[i] + 1;
|
|
sumqx += w*xval[i]*q;
|
|
sumq2 += w*q*q;
|
|
}
|
|
if (sumq2 > 0) scale = sumqx/sumq2;
|
|
}
|
|
if (scale < 0) {
|
|
// This should never happen, but just in case, flip scale so that it is positive (we use uint's to encode the scale)
|
|
// and correspondingly flip quant signs.
|
|
scale = -scale;
|
|
for (int k = 0; k < bs8; ++k) block_signs[k] = ~block_signs[k];
|
|
}
|
|
for (int k = 0; k < bs4; ++k) {
|
|
uint16_t u = 0;
|
|
for (int i = 0; i < 4; ++i) u |= (L[4*k+i] << 3*i);
|
|
int grid_index = kmap_q3xs[u];
|
|
if (grid_index < 0) {
|
|
printf("Oops: found point %u not on grid:", u);
|
|
for (int i = 0; i < 4; ++i) printf(" %d", L[4*k+i]);
|
|
printf("\n");
|
|
GGML_ABORT("fatal error");
|
|
}
|
|
qs[k] = grid_index & 255;
|
|
qh[(ib*bs4+k)/8] |= ((grid_index >> 8) << ((ib*bs4+k)%8));
|
|
}
|
|
qs += bs4;
|
|
for (int k = 0; k < bs8; ++k) signs[k] = block_signs[k];
|
|
signs += bs8;
|
|
GGML_ASSERT(scale >= 0);
|
|
scales[ib] = scale;
|
|
max_scale = MAX(max_scale, scale);
|
|
}
|
|
|
|
if (!max_scale) {
|
|
continue;
|
|
}
|
|
|
|
float d = max_scale/31;
|
|
y[ibl].d = GGML_FP32_TO_FP16(d * 1.033f);
|
|
float id = 1/d;
|
|
for (int ib = 0; ib < QK_K/block_size; ib += 2) {
|
|
int l1 = nearest_int(0.5f*(id*scales[ib+0]-1));
|
|
l1 = MAX(0, MIN(15, l1));
|
|
int l2 = nearest_int(0.5f*(id*scales[ib+1]-1));
|
|
l2 = MAX(0, MIN(15, l2));
|
|
y[ibl].scales[ib/2] = l1 | (l2 << 4);
|
|
}
|
|
|
|
}
|
|
}
|
|
|
|
#define IQ3S_BLOCK_SIZE 32
|
|
size_t quantize_iq3_s(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
|
|
GGML_ASSERT(n_per_row%QK_K == 0);
|
|
int64_t nblock = n_per_row/QK_K;
|
|
float scales[QK_K/IQ3S_BLOCK_SIZE];
|
|
float weight[IQ3S_BLOCK_SIZE];
|
|
float xval[IQ3S_BLOCK_SIZE];
|
|
int8_t L[IQ3S_BLOCK_SIZE];
|
|
int8_t Laux[IQ3S_BLOCK_SIZE];
|
|
float waux[IQ3S_BLOCK_SIZE];
|
|
bool is_on_grid[IQ3S_BLOCK_SIZE/4];
|
|
bool is_on_grid_aux[IQ3S_BLOCK_SIZE/4];
|
|
uint8_t block_signs[IQ3S_BLOCK_SIZE/8];
|
|
char * qrow = (char *)dst;
|
|
for (int64_t row = 0; row < nrow; ++row) {
|
|
quantize_row_iq3_s_impl(IQ3S_BLOCK_SIZE, src, qrow, n_per_row, quant_weights,
|
|
scales, weight, xval, L, Laux, waux, is_on_grid, is_on_grid_aux, block_signs);
|
|
src += n_per_row;
|
|
qrow += nblock*sizeof(block_iq3_s);
|
|
}
|
|
return nrow * nblock * sizeof(block_iq3_s);
|
|
}
|
|
|
|
void quantize_row_iq3_s_ref(const float * restrict x, block_iq3_s * restrict y, int64_t k) {
|
|
assert(k % QK_K == 0);
|
|
quantize_iq3_s(x, y, 1, k, NULL);
|
|
}
|
|
|
|
|
|
// =================================== 1.5 bpw ===================================================
|
|
|
|
static int iq1_find_best_neighbour(const uint16_t * restrict neighbours, const uint64_t * restrict grid,
|
|
const float * restrict xval, const float * restrict weight, float * scale, int8_t * restrict L, int ngrid) {
|
|
int num_neighbors = neighbours[0];
|
|
GGML_ASSERT(num_neighbors > 0);
|
|
float best_score = -FLT_MAX;
|
|
int grid_index = -1;
|
|
for (int j = 1; j <= num_neighbors; ++j) {
|
|
const int8_t * pg = (const int8_t *)(grid + neighbours[j]);
|
|
float sumqx = 0, sumq2 = 0;
|
|
for (int i = 0; i < 8; ++i) {
|
|
float q = (pg[i] - 3)/2;
|
|
float w = weight[i];
|
|
sumqx += w*q*xval[i];
|
|
sumq2 += w*q*q;
|
|
}
|
|
if (sumqx > 0 && sumq2 > 0 && sumqx*sumqx > best_score*sumq2) {
|
|
*scale = sumqx/sumq2; best_score = *scale * sumqx;
|
|
grid_index = neighbours[j];
|
|
}
|
|
}
|
|
if (grid_index < 0) {
|
|
for (int i = 0; i < ngrid; ++i) {
|
|
const int8_t * grid_i = (const int8_t *)(grid + i);
|
|
float sumqx = 0, sumq2 = 0;
|
|
for (int j = 0; j < 8; ++j) {
|
|
float w = weight[j];
|
|
float q = (grid_i[j] - 3)/2;
|
|
sumqx += w*q*xval[j];
|
|
sumq2 += w*q*q;
|
|
}
|
|
if (sumqx > 0 && sumq2 > 0 && sumqx*sumqx > best_score*sumq2) {
|
|
*scale = sumqx/sumq2; best_score = *scale*sumqx;
|
|
grid_index = i;
|
|
}
|
|
}
|
|
}
|
|
if (grid_index < 0) {
|
|
printf("Oops, did not find grid point\n");
|
|
printf("Have %d neighbours\n", num_neighbors);
|
|
for (int j = 1; j <= num_neighbors; ++j) {
|
|
const int8_t * pg = (const int8_t *)(grid + neighbours[j]);
|
|
float sumqx = 0, sumq2 = 0;
|
|
for (int i = 0; i < 8; ++i) {
|
|
float q = (pg[i] - 3)/2;
|
|
float w = weight[i];
|
|
sumqx += w*q*xval[i];
|
|
sumq2 += w*q*q;
|
|
}
|
|
printf(" neighbour %d: sumqx = %g sumq2 = %g\n", j, (double)sumqx, (double)sumq2);
|
|
}
|
|
}
|
|
GGML_ASSERT(grid_index >= 0);
|
|
//!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
|
|
*scale *= 1.05f; // This is a fudge factor. Don't ask me why it improves the result.
|
|
//!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
|
|
const int8_t * pg = (const int8_t *)(grid + grid_index);
|
|
for (int i = 0; i < 8; ++i) L[i] = (pg[i] - 1)/2;
|
|
return grid_index;
|
|
}
|
|
|
|
static int iq1_find_best_neighbour2(const uint16_t * restrict neighbours, const uint64_t * restrict grid,
|
|
const float * restrict xval, const float * restrict weight, float scale, const float * restrict xg, int8_t * restrict L, int ngrid) {
|
|
int num_neighbors = neighbours[0];
|
|
GGML_ASSERT(num_neighbors > 0);
|
|
float best_score = FLT_MAX;
|
|
int grid_index = -1;
|
|
for (int j = 1; j <= num_neighbors; ++j) {
|
|
const int8_t * pg = (const int8_t *)(grid + neighbours[j]);
|
|
float d2 = 0;
|
|
for (int i = 0; i < 8; ++i) {
|
|
float q = xg[(pg[i] - 1)/2];
|
|
float w = weight[i];
|
|
float diff = scale*q - xval[i];
|
|
d2 += w*diff*diff;
|
|
}
|
|
if (d2 < best_score) {
|
|
best_score = d2;
|
|
grid_index = neighbours[j];
|
|
}
|
|
}
|
|
if (grid_index < 0) {
|
|
for (int i = 0; i < ngrid; ++i) {
|
|
const int8_t * grid_i = (const int8_t *)(grid + i);
|
|
float d2 = 0;
|
|
for (int j = 0; j < 8; ++j) {
|
|
float w = weight[j];
|
|
float q = xg[(grid_i[j] - 1)/2];
|
|
float diff = scale*q - xval[i];
|
|
d2 += w*diff*diff;
|
|
}
|
|
if (d2 < best_score) {
|
|
best_score = d2;
|
|
grid_index = i;
|
|
}
|
|
}
|
|
}
|
|
if (grid_index < 0) {
|
|
printf("Oops, did not find grid point\n");
|
|
printf("Have %d neighbours\n", num_neighbors);
|
|
for (int j = 1; j <= num_neighbors; ++j) {
|
|
const int8_t * pg = (const int8_t *)(grid + neighbours[j]);
|
|
float sumqx = 0, sumq2 = 0;
|
|
for (int i = 0; i < 8; ++i) {
|
|
float q = xg[(pg[i] - 1)/2];
|
|
float w = weight[i];
|
|
sumqx += w*q*xval[i];
|
|
sumq2 += w*q*q;
|
|
}
|
|
printf(" neighbour %d: sumqx = %g sumq2 = %g\n", j, (double)sumqx, (double)sumq2);
|
|
}
|
|
}
|
|
GGML_ASSERT(grid_index >= 0);
|
|
const int8_t * pg = (const int8_t *)(grid + grid_index);
|
|
for (int i = 0; i < 8; ++i) L[i] = (pg[i] - 1)/2;
|
|
return grid_index;
|
|
}
|
|
|
|
static int iq1_sort_helper(const void * left, const void * right) {
|
|
const float * l = left;
|
|
const float * r = right;
|
|
return *l < *r ? -1 : *l > *r ? 1 : 0;
|
|
}
|
|
|
|
#define IQ1S_BLOCK_SIZE 32
|
|
#define IQ1M_BLOCK_SIZE 16
|
|
static void quantize_row_iq1_s_impl(const float * restrict x, void * restrict vy, int64_t n, const float * restrict quant_weights,
|
|
float * scales,
|
|
float * weight,
|
|
float * sumx,
|
|
float * sumw,
|
|
float * pairs,
|
|
int8_t * L,
|
|
uint16_t * index,
|
|
int8_t * shifts) {
|
|
|
|
const int gindex = iq2_data_index(GGML_TYPE_IQ1_S);
|
|
|
|
const uint64_t * kgrid_q2xs = iq2_data[gindex].grid;
|
|
const int * kmap_q2xs = iq2_data[gindex].map;
|
|
const uint16_t * kneighbors_q2xs = iq2_data[gindex].neighbours;
|
|
|
|
GGML_ASSERT(quant_weights && "missing quantization weights");
|
|
GGML_ASSERT(kgrid_q2xs && "forgot to call ggml_quantize_init()?");
|
|
GGML_ASSERT(kmap_q2xs && "forgot to call ggml_quantize_init()?");
|
|
GGML_ASSERT(kneighbors_q2xs && "forgot to call ggml_quantize_init()?");
|
|
GGML_ASSERT(n%QK_K == 0);
|
|
|
|
block_iq1_s * y = vy;
|
|
|
|
const int64_t nbl = n/QK_K;
|
|
|
|
const int block_size = IQ1S_BLOCK_SIZE;
|
|
|
|
const float x_p[3] = {-1 + IQ1S_DELTA, IQ1S_DELTA, 1 + IQ1S_DELTA};
|
|
const float x_m[3] = {-1 - IQ1S_DELTA, -IQ1S_DELTA, 1 - IQ1S_DELTA};
|
|
|
|
|
|
int * idx = (int *)(pairs + 1);
|
|
|
|
for (int ibl = 0; ibl < nbl; ++ibl) {
|
|
|
|
y[ibl].d = GGML_FP32_TO_FP16(0.f);
|
|
memset(y[ibl].qs, 0, QK_K/8);
|
|
memset(y[ibl].qh, 0, QK_K/16);
|
|
|
|
float max_scale = 0;
|
|
|
|
const float * xbl = x + QK_K*ibl;
|
|
float sumx2 = 0;
|
|
for (int i = 0; i < QK_K; ++i) sumx2 += xbl[i]*xbl[i];
|
|
float sigma2 = 2*sumx2/QK_K;
|
|
|
|
for (int ib = 0; ib < QK_K/block_size; ++ib) {
|
|
const float * xb = xbl + block_size*ib;
|
|
const float * qw = quant_weights + QK_K*ibl + block_size*ib;
|
|
for (int i = 0; i < block_size; ++i) weight[i] = qw[i] * sqrtf(sigma2 + xb[i]*xb[i]);
|
|
float max = fabsf(xb[0]);
|
|
for (int i = 1; i < block_size; ++i) max = MAX(max, fabsf(xb[i]));
|
|
if (max < GROUP_MAX_EPS_IQ1_S) {
|
|
scales[ib] = 0;
|
|
memset(L, 1, block_size);
|
|
continue;
|
|
}
|
|
// Here we solve exactly the sum of squared difference (SSD) weighted minimization problem.
|
|
// With just 3 allowed quant values (-1, 0, 1), we can search exhaustively for the two
|
|
// boundaries that split the weights xb[i] into 3 groups. To do so, we sort the weights
|
|
// in ascending order, compute Si = sum[weight[j] xb[j], j = 0...i] and
|
|
// Wi = sum[weight[j], j = 0...i], and use these to quckly get get the optimum scale
|
|
// for each possible and score for each split.
|
|
for (int j = 0; j < block_size; ++j) {
|
|
pairs[2*j] = xb[j];
|
|
idx[2*j] = j;
|
|
}
|
|
qsort(pairs, block_size, 2*sizeof(float), iq1_sort_helper);
|
|
{
|
|
sumx[0] = sumw[0] = 0;
|
|
for (int j = 0; j < block_size; ++j) {
|
|
int i = idx[2*j];
|
|
sumx[j+1] = sumx[j] + weight[i]*xb[i];
|
|
sumw[j+1] = sumw[j] + weight[i];
|
|
}
|
|
}
|
|
float best_score = -FLT_MIN, scale = max;
|
|
int besti1 = -1, besti2 = -1, best_shift = 0;
|
|
for (int i1 = 0; i1 <= block_size; ++i1) {
|
|
for (int i2 = i1; i2 <= block_size; ++i2) {
|
|
float sumqx = (sumx[i1] - sumx[0])*x_p[0] + (sumx[i2] - sumx[i1])*x_p[1] + (sumx[block_size] - sumx[i2])*x_p[2];
|
|
float sumq2 = (sumw[i1] - sumw[0])*x_p[0]*x_p[0] + (sumw[i2] - sumw[i1])*x_p[1]*x_p[1] + (sumw[block_size] - sumw[i2])*x_p[2]*x_p[2];
|
|
if (sumq2 > 0 && sumqx*sumqx > best_score*sumq2) {
|
|
scale = sumqx/sumq2; best_score = scale*sumqx;
|
|
besti1 = i1; besti2 = i2; best_shift = 1;
|
|
}
|
|
sumqx = (sumx[i1] - sumx[0])*x_m[0] + (sumx[i2] - sumx[i1])*x_m[1] + (sumx[block_size] - sumx[i2])*x_m[2];
|
|
sumq2 = (sumw[i1] - sumw[0])*x_m[0]*x_m[0] + (sumw[i2] - sumw[i1])*x_m[1]*x_m[1] + (sumw[block_size] - sumw[i2])*x_m[2]*x_m[2];
|
|
if (sumq2 > 0 && sumqx*sumqx > best_score*sumq2) {
|
|
scale = sumqx/sumq2; best_score = scale*sumqx;
|
|
besti1 = i1; besti2 = i2; best_shift = -1;
|
|
}
|
|
}
|
|
}
|
|
GGML_ASSERT(besti1 >= 0 && besti2 >= 0 && best_shift != 0);
|
|
for (int j = 0; j < besti1; ++j) L[idx[2*j]] = 0;
|
|
for (int j = besti1; j < besti2; ++j) L[idx[2*j]] = 1;
|
|
for (int j = besti2; j < block_size; ++j) L[idx[2*j]] = 2;
|
|
if (scale < 0) {
|
|
for (int j = 0; j < block_size; ++j) L[j] = 2 - L[j];
|
|
scale = -scale; best_shift = -best_shift;
|
|
}
|
|
bool all_on_grid = true;
|
|
const float * xx = best_shift == 1 ? x_p : x_m;
|
|
for (int k = 0; k < block_size/8; ++k) {
|
|
uint16_t u = 0;
|
|
for (int j = 0; j < 8; ++j) u |= (L[8*k+j] << 2*j);
|
|
int grid_index = kmap_q2xs[u];
|
|
if (grid_index < 0) {
|
|
all_on_grid = false;
|
|
const uint16_t * neighbours = kneighbors_q2xs - kmap_q2xs[u] - 1;
|
|
grid_index = iq1_find_best_neighbour2(neighbours, kgrid_q2xs, xb + 8*k, weight + 8*k, scale, xx, L + 8*k, NGRID_IQ1S);
|
|
GGML_ASSERT(grid_index >= 0);
|
|
}
|
|
index[k] = grid_index;
|
|
}
|
|
if (!all_on_grid) {
|
|
float sumqx = 0, sumq2 = 0;
|
|
for (int k = 0; k < block_size/8; ++k) {
|
|
const int8_t * pg = (const int8_t *)(kgrid_q2xs + index[k]);
|
|
for (int j = 0; j < 8; ++j) {
|
|
float w = weight[8*k + j];
|
|
float q = xx[(pg[j] - 1)/2];
|
|
sumqx += w*q*xb[8*k+j];
|
|
sumq2 += w*q*q;
|
|
}
|
|
}
|
|
if (sumqx > 0 && sumq2 > 0) scale = sumqx/sumq2;
|
|
}
|
|
uint16_t h = 0;
|
|
for (int k = 0; k < block_size/8; ++k) {
|
|
y[ibl].qs[(block_size/8)*ib + k] = index[k] & 255;
|
|
h |= (index[k] >> 8) << 3*k;
|
|
}
|
|
y[ibl].qh[ib] = h;
|
|
GGML_ASSERT(scale >= 0);
|
|
scales[ib] = scale;
|
|
shifts[ib] = best_shift;
|
|
max_scale = MAX(max_scale, scale);
|
|
}
|
|
|
|
if (!max_scale) {
|
|
continue;
|
|
}
|
|
|
|
float d = max_scale/15;
|
|
y[ibl].d = GGML_FP32_TO_FP16(d*1.125f); // 1.125f is another fudge factor. Don't ask me why it is needed.
|
|
float id = 1/d;
|
|
for (int ib = 0; ib < QK_K/block_size; ++ib) {
|
|
int l = nearest_int(0.5f*(id*scales[ib]-1));
|
|
l = MAX(0, MIN(7, l));
|
|
if (shifts[ib] == -1) l |= 8;
|
|
y[ibl].qh[ib] |= (l << 12);
|
|
}
|
|
}
|
|
}
|
|
|
|
size_t quantize_iq1_s(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
|
|
GGML_ASSERT(n_per_row%QK_K == 0);
|
|
float scales[QK_K/IQ1S_BLOCK_SIZE];
|
|
float weight[IQ1S_BLOCK_SIZE];
|
|
int8_t L[IQ1S_BLOCK_SIZE];
|
|
float sumx[IQ1S_BLOCK_SIZE+1];
|
|
float sumw[IQ1S_BLOCK_SIZE+1];
|
|
float pairs[2*IQ1S_BLOCK_SIZE];
|
|
uint16_t index[IQ1S_BLOCK_SIZE/8];
|
|
int8_t shifts[QK_K/IQ1S_BLOCK_SIZE];
|
|
int64_t nblock = n_per_row/QK_K;
|
|
char * qrow = (char *)dst;
|
|
for (int64_t row = 0; row < nrow; ++row) {
|
|
quantize_row_iq1_s_impl(src, qrow, n_per_row, quant_weights, scales, weight, sumx, sumw, pairs, L, index, shifts);
|
|
src += n_per_row;
|
|
qrow += nblock*sizeof(block_iq1_s);
|
|
}
|
|
return nrow * nblock * sizeof(block_iq1_s);
|
|
}
|
|
|
|
static void quantize_row_iq1_m_impl(const float * restrict x, void * restrict vy, int64_t n, const float * restrict quant_weights,
|
|
float * scales,
|
|
float * weight,
|
|
float * pairs,
|
|
int8_t * L,
|
|
uint16_t * index,
|
|
int8_t * shifts) {
|
|
|
|
const int gindex = iq2_data_index(GGML_TYPE_IQ1_M);
|
|
|
|
const uint64_t * kgrid_q2xs = iq2_data[gindex].grid;
|
|
const int * kmap_q2xs = iq2_data[gindex].map;
|
|
const uint16_t * kneighbors_q2xs = iq2_data[gindex].neighbours;
|
|
|
|
//GGML_ASSERT(quant_weights && "missing quantization weights");
|
|
GGML_ASSERT(kgrid_q2xs && "forgot to call ggml_quantize_init()?");
|
|
GGML_ASSERT(kmap_q2xs && "forgot to call ggml_quantize_init()?");
|
|
GGML_ASSERT(kneighbors_q2xs && "forgot to call ggml_quantize_init()?");
|
|
GGML_ASSERT(n%QK_K == 0);
|
|
|
|
block_iq1_m * y = vy;
|
|
|
|
const int64_t nbl = n/QK_K;
|
|
|
|
const int block_size = IQ1M_BLOCK_SIZE;
|
|
|
|
const float x_p[3] = {-1 + IQ1M_DELTA, IQ1M_DELTA, 1 + IQ1M_DELTA};
|
|
const float x_m[3] = {-1 - IQ1M_DELTA, -IQ1M_DELTA, 1 - IQ1M_DELTA};
|
|
const uint8_t masks[4] = {0x00, 0x80, 0x08, 0x88};
|
|
|
|
int * idx = (int *)(pairs + 1);
|
|
|
|
float sumqx[4], sumq2[4];
|
|
|
|
iq1m_scale_t s;
|
|
const float * xx;
|
|
|
|
for (int ibl = 0; ibl < nbl; ++ibl) {
|
|
memset(y[ibl].qs, 0, QK_K/8);
|
|
memset(y[ibl].qh, 0, QK_K/16);
|
|
memset(y[ibl].scales, 0, QK_K/32);
|
|
|
|
float max_scale = 0;
|
|
|
|
const float * xbl = x + QK_K*ibl;
|
|
float sumx2 = 0;
|
|
for (int i = 0; i < QK_K; ++i) sumx2 += xbl[i]*xbl[i];
|
|
float sigma2 = 2*sumx2/QK_K;
|
|
|
|
for (int ib = 0; ib < QK_K/block_size; ++ib) {
|
|
const float * xb = xbl + block_size*ib;
|
|
if (quant_weights) {
|
|
const float * qw = quant_weights + QK_K*ibl + block_size*ib;
|
|
for (int i = 0; i < block_size; ++i) weight[i] = qw[i] * sqrtf(sigma2 + xb[i]*xb[i]);
|
|
} else {
|
|
for (int i = 0; i < block_size; ++i) weight[i] = xb[i]*xb[i];
|
|
}
|
|
float max = fabsf(xb[0]);
|
|
for (int i = 1; i < block_size; ++i) max = MAX(max, fabsf(xb[i]));
|
|
if (max < GROUP_MAX_EPS_IQ1_M) {
|
|
scales[ib] = 0;
|
|
memset(L, 1, block_size);
|
|
continue;
|
|
}
|
|
// Here we solve exactly the sum of squared difference (SSD) weighted minimization problem.
|
|
// With just 3 allowed quant values (-1, 0, 1), we can search exhaustively for the two
|
|
// boundaries that split the weights xb[i] into 3 groups. To do so, we sort the weights
|
|
// in ascending order, compute Si = sum[weight[j] xb[j], j = 0...i] and
|
|
// Wi = sum[weight[j], j = 0...i], and use these to quckly get get the optimum scale
|
|
// for each possible and score for each split.
|
|
for (int j = 0; j < block_size; ++j) {
|
|
pairs[2*j] = xb[j];
|
|
idx[2*j] = j;
|
|
}
|
|
qsort(pairs, block_size, 2*sizeof(float), iq1_sort_helper);
|
|
float best_score = -FLT_MIN, scale = max;
|
|
int besti1 = -1, besti2 = -1, best_k = -1;
|
|
// 0: +, +
|
|
// 1: +, -
|
|
// 2: -, +
|
|
// 3: -, -
|
|
for (int i1 = 0; i1 <= block_size; ++i1) {
|
|
for (int i2 = i1; i2 <= block_size; ++i2) {
|
|
memset(sumqx, 0, 4*sizeof(float));
|
|
memset(sumq2, 0, 4*sizeof(float));
|
|
for (int j = 0; j < i1; ++j) {
|
|
int i = idx[2*j];
|
|
if (i < block_size/2) {
|
|
sumqx[0] += weight[i]*x_p[0]*xb[i];
|
|
sumqx[1] += weight[i]*x_p[0]*xb[i];
|
|
sumqx[2] += weight[i]*x_m[0]*xb[i];
|
|
sumqx[3] += weight[i]*x_m[0]*xb[i];
|
|
sumq2[0] += weight[i]*x_p[0]*x_p[0];
|
|
sumq2[1] += weight[i]*x_p[0]*x_p[0];
|
|
sumq2[2] += weight[i]*x_m[0]*x_m[0];
|
|
sumq2[3] += weight[i]*x_m[0]*x_m[0];
|
|
} else {
|
|
sumqx[0] += weight[i]*x_p[0]*xb[i];
|
|
sumqx[2] += weight[i]*x_p[0]*xb[i];
|
|
sumqx[1] += weight[i]*x_m[0]*xb[i];
|
|
sumqx[3] += weight[i]*x_m[0]*xb[i];
|
|
sumq2[0] += weight[i]*x_p[0]*x_p[0];
|
|
sumq2[2] += weight[i]*x_p[0]*x_p[0];
|
|
sumq2[1] += weight[i]*x_m[0]*x_m[0];
|
|
sumq2[3] += weight[i]*x_m[0]*x_m[0];
|
|
}
|
|
}
|
|
for (int j = i1; j < i2; ++j) {
|
|
int i = idx[2*j];
|
|
if (i < block_size/2) {
|
|
sumqx[0] += weight[i]*x_p[1]*xb[i];
|
|
sumqx[1] += weight[i]*x_p[1]*xb[i];
|
|
sumqx[2] += weight[i]*x_m[1]*xb[i];
|
|
sumqx[3] += weight[i]*x_m[1]*xb[i];
|
|
sumq2[0] += weight[i]*x_p[1]*x_p[1];
|
|
sumq2[1] += weight[i]*x_p[1]*x_p[1];
|
|
sumq2[2] += weight[i]*x_m[1]*x_m[1];
|
|
sumq2[3] += weight[i]*x_m[1]*x_m[1];
|
|
} else {
|
|
sumqx[0] += weight[i]*x_p[1]*xb[i];
|
|
sumqx[2] += weight[i]*x_p[1]*xb[i];
|
|
sumqx[1] += weight[i]*x_m[1]*xb[i];
|
|
sumqx[3] += weight[i]*x_m[1]*xb[i];
|
|
sumq2[0] += weight[i]*x_p[1]*x_p[1];
|
|
sumq2[2] += weight[i]*x_p[1]*x_p[1];
|
|
sumq2[1] += weight[i]*x_m[1]*x_m[1];
|
|
sumq2[3] += weight[i]*x_m[1]*x_m[1];
|
|
}
|
|
}
|
|
for (int j = i2; j < block_size; ++j) {
|
|
int i = idx[2*j];
|
|
if (i < block_size/2) {
|
|
sumqx[0] += weight[i]*x_p[2]*xb[i];
|
|
sumqx[1] += weight[i]*x_p[2]*xb[i];
|
|
sumqx[2] += weight[i]*x_m[2]*xb[i];
|
|
sumqx[3] += weight[i]*x_m[2]*xb[i];
|
|
sumq2[0] += weight[i]*x_p[2]*x_p[2];
|
|
sumq2[1] += weight[i]*x_p[2]*x_p[2];
|
|
sumq2[2] += weight[i]*x_m[2]*x_m[2];
|
|
sumq2[3] += weight[i]*x_m[2]*x_m[2];
|
|
} else {
|
|
sumqx[0] += weight[i]*x_p[2]*xb[i];
|
|
sumqx[2] += weight[i]*x_p[2]*xb[i];
|
|
sumqx[1] += weight[i]*x_m[2]*xb[i];
|
|
sumqx[3] += weight[i]*x_m[2]*xb[i];
|
|
sumq2[0] += weight[i]*x_p[2]*x_p[2];
|
|
sumq2[2] += weight[i]*x_p[2]*x_p[2];
|
|
sumq2[1] += weight[i]*x_m[2]*x_m[2];
|
|
sumq2[3] += weight[i]*x_m[2]*x_m[2];
|
|
}
|
|
}
|
|
for (int k = 0; k < 4; ++k) {
|
|
if (sumq2[k] > 0 && sumqx[k]*sumqx[k] > best_score*sumq2[k]) {
|
|
scale = sumqx[k]/sumq2[k]; best_score = scale*sumqx[k];
|
|
besti1 = i1; besti2 = i2; best_k = k;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
GGML_ASSERT(besti1 >= 0 && besti2 >= 0 && best_k >= 0);
|
|
for (int j = 0; j < besti1; ++j) L[idx[2*j]] = 0;
|
|
for (int j = besti1; j < besti2; ++j) L[idx[2*j]] = 1;
|
|
for (int j = besti2; j < block_size; ++j) L[idx[2*j]] = 2;
|
|
if (scale < 0) {
|
|
for (int j = 0; j < block_size; ++j) L[j] = 2 - L[j];
|
|
scale = -scale;
|
|
best_k = best_k == 0 ? 3 : best_k == 1 ? 2 : best_k == 2 ? 1 : 0;
|
|
}
|
|
bool all_on_grid = true;
|
|
for (int k = 0; k < block_size/8; ++k) {
|
|
if (k == 0) xx = best_k < 2 ? x_p : x_m;
|
|
else xx = best_k%2 == 0 ? x_p : x_m;
|
|
uint16_t u = 0;
|
|
for (int j = 0; j < 8; ++j) u |= (L[8*k+j] << 2*j);
|
|
int grid_index = kmap_q2xs[u];
|
|
if (grid_index < 0) {
|
|
all_on_grid = false;
|
|
const uint16_t * neighbours = kneighbors_q2xs - kmap_q2xs[u] - 1;
|
|
grid_index = iq1_find_best_neighbour2(neighbours, kgrid_q2xs, xb + 8*k, weight + 8*k, scale, xx, L + 8*k, NGRID_IQ1S);
|
|
GGML_ASSERT(grid_index >= 0);
|
|
}
|
|
index[k] = grid_index;
|
|
}
|
|
if (!all_on_grid) {
|
|
float sumqx_f = 0, sumq2_f = 0;
|
|
for (int k = 0; k < block_size/8; ++k) {
|
|
if (k == 0) xx = best_k < 2 ? x_p : x_m;
|
|
else xx = best_k%2 == 0 ? x_p : x_m;
|
|
const int8_t * pg = (const int8_t *)(kgrid_q2xs + index[k]);
|
|
for (int j = 0; j < 8; ++j) {
|
|
float w = weight[8*k + j];
|
|
float q = xx[(pg[j] - 1)/2];
|
|
sumqx_f += w*q*xb[8*k+j];
|
|
sumq2_f += w*q*q;
|
|
}
|
|
}
|
|
if (sumqx_f > 0 && sumq2_f > 0) scale = sumqx_f/sumq2_f;
|
|
}
|
|
y[ibl].qs[2*ib + 0] = index[0] & 255;
|
|
y[ibl].qs[2*ib + 1] = index[1] & 255;
|
|
y[ibl].qh[ib] = (index[0] >> 8) | ((index[1] >> 8) << 4);
|
|
GGML_ASSERT(scale >= 0);
|
|
scales[ib] = scale;
|
|
shifts[ib] = best_k;
|
|
max_scale = MAX(max_scale, scale);
|
|
}
|
|
|
|
if (!max_scale) {
|
|
continue;
|
|
}
|
|
|
|
uint16_t * sc = (uint16_t *)y[ibl].scales;
|
|
float d = max_scale/15;
|
|
float id = 1/d;
|
|
float sumqx_f = 0, sumq2_f = 0;
|
|
for (int ib = 0; ib < QK_K/block_size; ++ib) {
|
|
int l = nearest_int(0.5f*(id*scales[ib+0]-1));
|
|
l = MAX(0, MIN(7, l));
|
|
sc[ib/4] |= (l << 3*(ib%4));
|
|
y[ibl].qh[ib] |= masks[shifts[ib]];
|
|
const float * xb = xbl + block_size*ib;
|
|
if (quant_weights) {
|
|
const float * qw = quant_weights + QK_K*ibl + block_size*ib;
|
|
for (int i = 0; i < block_size; ++i) weight[i] = qw[i] * sqrtf(sigma2 + xb[i]*xb[i]);
|
|
} else {
|
|
for (int i = 0; i < block_size; ++i) weight[i] = xb[i]*xb[i];
|
|
}
|
|
for (int k = 0; k < block_size/8; ++k) {
|
|
if (k == 0) xx = shifts[ib] < 2 ? x_p : x_m;
|
|
else xx = shifts[ib]%2 == 0 ? x_p : x_m;
|
|
const int8_t * pg = (const int8_t *)(kgrid_q2xs + y[ibl].qs[2*ib+k] + ((y[ibl].qh[ib] << (8 - 4*k)) & 0x700));
|
|
for (int j = 0; j < 8; ++j) {
|
|
float w = weight[8*k + j];
|
|
float q = xx[(pg[j] - 1)/2]*(2*l+1);
|
|
sumqx_f += w*q*xb[8*k+j];
|
|
sumq2_f += w*q*q;
|
|
}
|
|
}
|
|
}
|
|
if (sumq2_f > 0) d = sumqx_f/sumq2_f;
|
|
s.f16 = GGML_FP32_TO_FP16(d*1.1125f); // 1.1125f is another fudge factor. Don't ask me why it is needed.
|
|
sc[0] |= ((s.u16 & 0x000f) << 12);
|
|
sc[1] |= ((s.u16 & 0x00f0) << 8);
|
|
sc[2] |= ((s.u16 & 0x0f00) << 4);
|
|
sc[3] |= ((s.u16 & 0xf000) << 0);
|
|
}
|
|
}
|
|
|
|
size_t quantize_iq1_m(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
|
|
GGML_ASSERT(n_per_row%QK_K == 0);
|
|
float scales[QK_K/IQ1M_BLOCK_SIZE];
|
|
float weight[IQ1M_BLOCK_SIZE];
|
|
int8_t L[IQ1M_BLOCK_SIZE];
|
|
float pairs[2*IQ1M_BLOCK_SIZE];
|
|
uint16_t index[IQ1M_BLOCK_SIZE/8];
|
|
int8_t shifts[QK_K/IQ1M_BLOCK_SIZE];
|
|
int64_t nblock = n_per_row/QK_K;
|
|
char * qrow = (char *)dst;
|
|
for (int64_t row = 0; row < nrow; ++row) {
|
|
quantize_row_iq1_m_impl(src, qrow, n_per_row, quant_weights, scales, weight, pairs, L, index, shifts);
|
|
src += n_per_row;
|
|
qrow += nblock*sizeof(block_iq1_m);
|
|
}
|
|
return nrow * nblock * sizeof(block_iq1_m);
|
|
}
|
|
|
|
// ============================ 4-bit non-linear quants
|
|
|
|
static inline int best_index_int8(int n, const int8_t * val, float x) {
|
|
if (x <= val[0]) return 0;
|
|
if (x >= val[n-1]) return n-1;
|
|
int ml = 0, mu = n-1;
|
|
while (mu-ml > 1) {
|
|
int mav = (ml+mu)/2;
|
|
if (x < val[mav]) mu = mav; else ml = mav;
|
|
}
|
|
return x - val[mu-1] < val[mu] - x ? mu-1 : mu;
|
|
}
|
|
|
|
static void quantize_row_iq4_nl_impl(const int super_block_size, const int block_size, const float * restrict x,
|
|
ggml_fp16_t * dh, uint8_t * q4, uint16_t * scales_h, uint8_t * scales_l,
|
|
float * scales, float * weight, uint8_t * L,
|
|
const int8_t * values,
|
|
const float * quant_weights,
|
|
const int ntry) {
|
|
|
|
float sigma2 = 0;
|
|
for (int j = 0; j < super_block_size; ++j) sigma2 += x[j]*x[j];
|
|
sigma2 *= 2.f/super_block_size;
|
|
|
|
memset(q4, 0, super_block_size/2);
|
|
dh[0] = GGML_FP32_TO_FP16(0.f);
|
|
|
|
float max_scale = 0, amax_scale = 0;
|
|
for (int ib = 0; ib < super_block_size/block_size; ++ib) {
|
|
const float * xb = x + ib*block_size;
|
|
uint8_t * Lb = L + ib*block_size;
|
|
if (quant_weights) {
|
|
const float * qw = quant_weights + ib*block_size;
|
|
for (int j = 0; j < block_size; ++j) weight[j] = qw[j] * sqrtf(sigma2 + xb[j]*xb[j]);
|
|
} else {
|
|
for (int j = 0; j < block_size; ++j) weight[j] = xb[j]*xb[j];
|
|
}
|
|
float amax = 0, max = 0;
|
|
for (int j = 0; j < block_size; ++j) {
|
|
float ax = fabsf(xb[j]);
|
|
if (ax > amax) {
|
|
amax = ax; max = xb[j];
|
|
}
|
|
}
|
|
if (amax < GROUP_MAX_EPS) {
|
|
scales[ib] = 0;
|
|
continue;
|
|
}
|
|
float d = ntry > 0 ? -max/values[0] : max/values[0];
|
|
float id = 1/d;
|
|
float sumqx = 0, sumq2 = 0;
|
|
for (int j = 0; j < block_size; ++j) {
|
|
float al = id*xb[j];
|
|
int l = best_index_int8(16, values, al);
|
|
Lb[j] = l;
|
|
float q = values[l];
|
|
float w = weight[j];
|
|
sumqx += w*q*xb[j];
|
|
sumq2 += w*q*q;
|
|
}
|
|
d = sumqx/sumq2;
|
|
float best = d*sumqx;
|
|
for (int itry = -ntry; itry <= ntry; ++itry) {
|
|
id = (itry + values[0])/max;
|
|
sumqx = sumq2 = 0;
|
|
for (int j = 0; j < block_size; ++j) {
|
|
float al = id*xb[j];
|
|
int l = best_index_int8(16, values, al);
|
|
float q = values[l];
|
|
float w = weight[j];
|
|
sumqx += w*q*xb[j];
|
|
sumq2 += w*q*q;
|
|
}
|
|
if (sumq2 > 0 && sumqx*sumqx > best*sumq2) {
|
|
d = sumqx/sumq2; best = d * sumqx;
|
|
}
|
|
}
|
|
scales[ib] = d;
|
|
float abs_d = fabsf(d);
|
|
if (abs_d > amax_scale) {
|
|
amax_scale = abs_d; max_scale = d;
|
|
}
|
|
}
|
|
|
|
if (super_block_size/block_size > 1) {
|
|
int nb = super_block_size/block_size;
|
|
memset(scales_h, 0, ((nb+7)/8)*sizeof(uint16_t));
|
|
float d = -max_scale/32;
|
|
dh[0] = GGML_FP32_TO_FP16(d);
|
|
float id = d ? 1/d : 0.f;
|
|
for (int ib = 0; ib < super_block_size/block_size; ++ib) {
|
|
int l = nearest_int(id*scales[ib]);
|
|
l = MAX(-32, MIN(31, l));
|
|
float dl = d * l;
|
|
float idl = dl ? 1/dl : 0.f;
|
|
uint8_t * Lb = L + ib*block_size;
|
|
const float * xb = x + ib*block_size;
|
|
for (int j = 0; j < block_size; ++j) {
|
|
Lb[j] = best_index_int8(16, values, idl*xb[j]);
|
|
}
|
|
l += 32;
|
|
uint8_t l_l = l & 0xf;
|
|
uint8_t l_h = l >> 4;
|
|
if (ib%2 == 0) scales_l[ib/2] = l_l;
|
|
else scales_l[ib/2] |= (l_l << 4);
|
|
scales_h[ib/8] |= (l_h << 2*(ib%8));
|
|
}
|
|
} else {
|
|
dh[0] = GGML_FP32_TO_FP16(scales[0]);
|
|
if (ntry > 0) {
|
|
float id = scales[0] ? 1/scales[0] : 0;
|
|
for (int j = 0; j < super_block_size; ++j) {
|
|
L[j] = best_index_int8(16, values, id*x[j]);
|
|
}
|
|
}
|
|
}
|
|
|
|
for (int i = 0; i < super_block_size/32; ++i) {
|
|
for (int j = 0; j < 16; ++j) {
|
|
q4[16*i + j] = L[32*i + j] | (L[32*i + 16 + j] << 4);
|
|
}
|
|
}
|
|
}
|
|
|
|
size_t quantize_iq4_nl(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
|
|
GGML_ASSERT(n_per_row%QK4_NL == 0);
|
|
int64_t nblock = n_per_row/QK4_NL;
|
|
char * qrow = (char *)dst;
|
|
uint8_t L[QK4_NL];
|
|
float weight[QK4_NL];
|
|
uint16_t unused_h;
|
|
uint8_t * unused_l = NULL;
|
|
float scale;
|
|
for (int64_t row = 0; row < nrow; ++row) {
|
|
block_iq4_nl * iq4 = (block_iq4_nl *)qrow;
|
|
for (int ibl = 0; ibl < nblock; ++ibl) {
|
|
const float * qw = quant_weights ? quant_weights + QK4_NL*ibl : NULL;
|
|
quantize_row_iq4_nl_impl(QK4_NL, 32, src + QK4_NL*ibl, &iq4[ibl].d, iq4[ibl].qs, &unused_h, unused_l,
|
|
&scale, weight, L, kvalues_iq4nl, qw, 7);
|
|
}
|
|
src += n_per_row;
|
|
qrow += nblock*sizeof(block_iq4_nl);
|
|
}
|
|
return nrow * nblock * sizeof(block_iq4_nl);
|
|
}
|
|
|
|
//void quantize_row_iq4_nl_ref(const float * restrict x, void * restrict vy, int64_t k) {
|
|
void quantize_row_iq4_nl_ref(const float * restrict x, block_iq4_nl * restrict y, int64_t k) {
|
|
GGML_ASSERT(k%QK4_NL == 0);
|
|
int64_t nblock = k/QK4_NL;
|
|
uint8_t L[QK4_NL];
|
|
float weight[QK4_NL];
|
|
uint16_t unused_h;
|
|
uint8_t * unused_l = NULL;
|
|
float scale;
|
|
block_iq4_nl * iq4 = y;
|
|
for (int ibl = 0; ibl < nblock; ++ibl) {
|
|
quantize_row_iq4_nl_impl(QK4_NL, 32, x + QK4_NL*ibl, &iq4[ibl].d, iq4[ibl].qs, &unused_h, unused_l,
|
|
&scale, weight, L, kvalues_iq4nl, NULL, -1);
|
|
}
|
|
}
|
|
|
|
size_t quantize_iq4_xs(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
|
|
GGML_ASSERT(n_per_row%QK_K == 0);
|
|
int64_t nblock = n_per_row/QK_K;
|
|
char * qrow = (char *)dst;
|
|
uint8_t L[QK_K];
|
|
float weight[32];
|
|
float scales[QK_K/32];
|
|
for (int64_t row = 0; row < nrow; ++row) {
|
|
block_iq4_xs * iq4 = (block_iq4_xs *)qrow;
|
|
for (int ibl = 0; ibl < nblock; ++ibl) {
|
|
const float * qw = quant_weights ? quant_weights + QK_K*ibl : NULL;
|
|
quantize_row_iq4_nl_impl(QK_K, 32, src + QK_K*ibl, &iq4[ibl].d, iq4[ibl].qs, &iq4[ibl].scales_h, iq4[ibl].scales_l,
|
|
scales, weight, L, kvalues_iq4nl, qw, 7);
|
|
}
|
|
src += n_per_row;
|
|
qrow += nblock*sizeof(block_iq4_xs);
|
|
}
|
|
return nrow * nblock * sizeof(block_iq4_xs);
|
|
}
|
|
|
|
void quantize_row_iq4_xs_ref(const float * restrict x, block_iq4_xs * restrict y, int64_t k) {
|
|
assert(k % QK_K == 0);
|
|
quantize_iq4_xs(x, y, 1, k, NULL);
|
|
}
|
|
|
|
// =============================== 2.5625 bpw
|
|
|
|
static void quantize_row_iq2_s_impl(const float * restrict x, void * restrict vy, int64_t n, const float * restrict quant_weights) {
|
|
|
|
const int gindex = iq2_data_index(GGML_TYPE_IQ2_S);
|
|
|
|
const uint64_t * kgrid_q2xs = iq2_data[gindex].grid;
|
|
const int * kmap_q2xs = iq2_data[gindex].map;
|
|
const uint16_t * kneighbors_q2xs = iq2_data[gindex].neighbours;
|
|
|
|
GGML_ASSERT(kmap_q2xs && "forgot to call ggml_quantize_init()?");
|
|
GGML_ASSERT(kgrid_q2xs && "forgot to call ggml_quantize_init()?");
|
|
GGML_ASSERT(kneighbors_q2xs && "forgot to call ggml_quantize_init()?");
|
|
GGML_ASSERT(n%QK_K == 0);
|
|
|
|
const int kMaxQ = 3;
|
|
|
|
const int64_t nbl = n/QK_K;
|
|
|
|
block_iq2_s * y = vy;
|
|
|
|
float scales[QK_K/16];
|
|
float weight[16];
|
|
float xval[16];
|
|
int8_t L[16];
|
|
int8_t Laux[16];
|
|
float waux[16];
|
|
bool is_on_grid[2];
|
|
bool is_on_grid_aux[2];
|
|
uint8_t block_signs[2];
|
|
|
|
for (int ibl = 0; ibl < nbl; ++ibl) {
|
|
|
|
memset(&y[ibl], 0, sizeof(block_iq2_s));
|
|
y[ibl].d = GGML_FP32_TO_FP16(0.f);
|
|
|
|
float max_scale = 0;
|
|
|
|
const float * xbl = x + QK_K*ibl;
|
|
float sumx2 = 0;
|
|
for (int i = 0; i < QK_K; ++i) sumx2 += xbl[i]*xbl[i];
|
|
float sigma2 = 2*sumx2/QK_K;
|
|
|
|
for (int ib = 0; ib < QK_K/16; ++ib) {
|
|
const float * xb = xbl + 16*ib;
|
|
if (quant_weights) {
|
|
const float * qw = quant_weights + QK_K*ibl + 16*ib;
|
|
for (int i = 0; i < 16; ++i) weight[i] = qw[i] * sqrtf(sigma2 + xb[i]*xb[i]);
|
|
} else {
|
|
for (int i = 0; i < 16; ++i) weight[i] = 0.25f*sigma2 + xb[i]*xb[i];
|
|
}
|
|
for (int i = 0; i < 16; ++i) waux[i] = sqrtf(weight[i]);
|
|
for (int k = 0; k < 2; ++k) {
|
|
uint8_t s = 0;
|
|
for (int i = 0; i < 8; ++i) {
|
|
if (xb[8*k + i] >= 0) xval[8*k + i] = xb[8*k + i];
|
|
else {
|
|
xval[8*k + i] = -xb[8*k + i]; s |= (1 << i);
|
|
}
|
|
}
|
|
block_signs[k] = s;
|
|
}
|
|
float max = xval[0];
|
|
for (int i = 1; i < 16; ++i) max = MAX(max, xval[i]);
|
|
if (max < GROUP_MAX_EPS_IQ2_S) {
|
|
scales[ib] = 0;
|
|
continue;
|
|
}
|
|
float best = 0;
|
|
float scale = max/(2*kMaxQ-1);
|
|
is_on_grid[0] = is_on_grid[1] = true;
|
|
for (int is = -9; is <= 9; ++is) {
|
|
float id = (2*kMaxQ-1+is*0.1f)/max;
|
|
float this_scale = 1/id;
|
|
for (int k = 0; k < 2; ++k) {
|
|
for (int i = 0; i < 8; ++i) {
|
|
int l = nearest_int(0.5f*(id*xval[8*k+i]-1));
|
|
Laux[8*k+i] = MAX(0, MIN(kMaxQ-1, l));
|
|
}
|
|
uint16_t u = 0;
|
|
for (int i = 0; i < 8; ++i) u |= (Laux[8*k+i] << 2*i);
|
|
int grid_index = kmap_q2xs[u];
|
|
is_on_grid_aux[k] = true;
|
|
if (grid_index < 0) {
|
|
is_on_grid_aux[k] = false;
|
|
const uint16_t * neighbours = kneighbors_q2xs - kmap_q2xs[u] - 1;
|
|
grid_index = iq2_find_best_neighbour(neighbours, kgrid_q2xs, xval + 8*k, waux + 8*k, this_scale, Laux + 8*k);
|
|
}
|
|
}
|
|
float sumqx = 0, sumq2 = 0;
|
|
for (int i = 0; i < 16; ++i) {
|
|
float w = weight[i];
|
|
float q = 2*Laux[i] + 1;
|
|
sumqx += w*xval[i]*q;
|
|
sumq2 += w*q*q;
|
|
}
|
|
if (sumq2 > 0 && sumqx*sumqx > best*sumq2) {
|
|
scale = sumqx/sumq2; best = scale*sumqx;
|
|
for (int i = 0; i < 16; ++i) L[i] = Laux[i];
|
|
for (int k = 0; k < 2; ++k) is_on_grid[k] = is_on_grid_aux[k];
|
|
}
|
|
}
|
|
int n_not_ongrid = 0;
|
|
for (int k = 0; k < 2; ++k) if (!is_on_grid[k]) ++n_not_ongrid;
|
|
if (n_not_ongrid > 0 && scale > 0) {
|
|
float id = 1/scale;
|
|
for (int k = 0; k < 2; ++k) {
|
|
if (is_on_grid[k]) continue;
|
|
uint16_t u = 0;
|
|
for (int i = 0; i < 8; ++i) {
|
|
int l = nearest_int(0.5f*(id*xval[8*k+i]-1));
|
|
l = MAX(0, MIN(kMaxQ-1, l));
|
|
u |= (l << 2*i);
|
|
L[8*k + i] = l;
|
|
}
|
|
int grid_index = kmap_q2xs[u];
|
|
if (grid_index < 0) {
|
|
const uint16_t * neighbours = kneighbors_q2xs - kmap_q2xs[u] - 1;
|
|
grid_index = iq2_find_best_neighbour(neighbours, kgrid_q2xs, xval + 8*k, waux + 8*k, scale, L + 8*k);
|
|
}
|
|
}
|
|
float sumqx = 0, sumq2 = 0;
|
|
for (int i = 0; i < 16; ++i) {
|
|
float w = weight[i];
|
|
float q = 2*L[i] + 1;
|
|
sumqx += w*xval[i]*q;
|
|
sumq2 += w*q*q;
|
|
}
|
|
if (sumq2 > 0) scale = sumqx/sumq2;
|
|
}
|
|
if (scale < 0) {
|
|
scale = -scale;
|
|
for (int k = 0; k < 2; ++k) block_signs[k] = ~block_signs[k];
|
|
}
|
|
for (int k = 0; k < 2; ++k) {
|
|
uint16_t u = 0;
|
|
for (int i = 0; i < 8; ++i) u |= (L[8*k+i] << 2*i);
|
|
int grid_index = kmap_q2xs[u];
|
|
if (grid_index < 0) {
|
|
printf("Oops: found point %u not on grid:", u);
|
|
for (int i = 0; i < 8; ++i) printf(" %d", L[8*k+i]);
|
|
printf("\n");
|
|
GGML_ABORT("fatal error");
|
|
}
|
|
const int i8 = 2*ib + k;
|
|
y[ibl].qs[i8] = grid_index & 255;
|
|
y[ibl].qh[i8/4] |= ((grid_index >> 8) << 2*(i8%4));
|
|
y[ibl].qs[QK_K/8 + i8] = block_signs[k];
|
|
}
|
|
GGML_ASSERT(scale >= 0);
|
|
scales[ib] = scale;
|
|
max_scale = MAX(max_scale, scale);
|
|
}
|
|
|
|
if (!max_scale) {
|
|
continue;
|
|
}
|
|
|
|
float d = max_scale/31;
|
|
y[ibl].d = GGML_FP32_TO_FP16(d * 0.9875f);
|
|
float id = 1/d;
|
|
for (int ib = 0; ib < QK_K/16; ++ib) {
|
|
int l = nearest_int(0.5f*(id*scales[ib]-1));
|
|
l = MAX(0, MIN(15, l));
|
|
if (ib%2 == 0) y[ibl].scales[ib/2] = l;
|
|
else y[ibl].scales[ib/2] |= (l << 4);
|
|
}
|
|
}
|
|
}
|
|
|
|
size_t quantize_iq2_s(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
|
|
GGML_ASSERT(n_per_row%QK_K == 0);
|
|
int64_t nblock = n_per_row/QK_K;
|
|
char * qrow = (char *)dst;
|
|
for (int64_t row = 0; row < nrow; ++row) {
|
|
quantize_row_iq2_s_impl(src, qrow, n_per_row, quant_weights);
|
|
src += n_per_row;
|
|
qrow += nblock*sizeof(block_iq2_s);
|
|
}
|
|
return nrow * nblock * sizeof(block_iq2_s);
|
|
}
|
|
|
|
void quantize_row_iq2_s_ref(const float * restrict x, block_iq2_s * restrict y, int64_t k) {
|
|
assert(k % QK_K == 0);
|
|
quantize_iq2_s(x, y, 1, k, NULL);
|
|
}
|
|
|
|
// =============================== data validation
|
|
|
|
static bool validate_float(float f, size_t i) {
|
|
if (isinf(f)) {
|
|
fprintf(stderr, "ggml_validate_row_data: found inf value at block %zu\n", i);
|
|
return false;
|
|
}
|
|
|
|
if (isnan(f)) {
|
|
fprintf(stderr, "ggml_validate_row_data: found nan value at block %zu\n", i);
|
|
return false;
|
|
}
|
|
|
|
return true;
|
|
}
|
|
|
|
static bool isinf_fp16(ggml_fp16_t f) {
|
|
return (f & 0x7c00) == 0x7c00 && (f & 0x03ff) == 0;
|
|
}
|
|
|
|
static bool isnan_fp16(ggml_fp16_t f) {
|
|
return (f & 0x7c00) == 0x7c00 && (f & 0x03ff) != 0;
|
|
}
|
|
|
|
static bool validate_fp16(ggml_fp16_t f, size_t i) {
|
|
if (isinf_fp16(f)) {
|
|
fprintf(stderr, "ggml_validate_row_data: found inf value at block %zu\n", i);
|
|
return false;
|
|
}
|
|
|
|
if (isnan_fp16(f)) {
|
|
fprintf(stderr, "ggml_validate_row_data: found nan value at block %zu\n", i);
|
|
return false;
|
|
}
|
|
|
|
return true;
|
|
}
|
|
|
|
#define VALIDATE_ROW_DATA_D_F16_IMPL(type, data, nb) \
|
|
const type * q = (const type *) (data); \
|
|
for (size_t i = 0; i < (nb); ++i) { \
|
|
if (!validate_fp16(q[i].d, i)) { \
|
|
return false; \
|
|
} \
|
|
}
|
|
|
|
#define VALIDATE_ROW_DATA_DM_F16_IMPL(type, data, nb, d, m) \
|
|
const type * q = (const type *) (data); \
|
|
for (size_t i = 0; i < (nb); ++i) { \
|
|
if (!validate_fp16(q[i].d, i) || !validate_fp16(q[i].m, i)) { \
|
|
return false; \
|
|
} \
|
|
}
|
|
|
|
#define VALIDATE_ROW_DATA_DVEC_F16_IMPL(type, data, nb, nr) \
|
|
const type * q = (const type *) (data); \
|
|
for (size_t i = 0; i < (nb); ++i) { \
|
|
for (size_t j = 0; j < (nr); ++j) { \
|
|
if (!validate_fp16(q[i].d[j], i)) { \
|
|
return false; \
|
|
} \
|
|
} \
|
|
}
|
|
|
|
bool ggml_validate_row_data(enum ggml_type type, const void * data, size_t nbytes) {
|
|
if (type < 0 || type >= GGML_TYPE_COUNT) {
|
|
fprintf(stderr, "%s: invalid type %d\n", __func__, type);
|
|
return false;
|
|
}
|
|
|
|
if (nbytes % ggml_type_size(type) != 0) {
|
|
fprintf(stderr, "%s: invalid size %zu for type %s (type size = %zu)\n", __func__, nbytes, ggml_type_name(type), ggml_type_size(type));
|
|
return false;
|
|
}
|
|
|
|
const size_t nb = nbytes/ggml_type_size(type);
|
|
|
|
switch (type) {
|
|
case GGML_TYPE_BF16:
|
|
{
|
|
int nans = 0;
|
|
int infs = 0;
|
|
const unsigned short * f = (const unsigned short *) data;
|
|
for (size_t i = 0; i < nb; ++i) {
|
|
nans += (f[i] & 0x7fff) > 0x7f80;
|
|
infs += (f[i] & 0x7fff) == 0x7f80;
|
|
}
|
|
if (nans) {
|
|
fprintf(stderr, "%s: found %d NaNs in row of %zu BF16 values\n", __func__, nans, nb);
|
|
return false;
|
|
}
|
|
if (infs) {
|
|
fprintf(stderr, "%s: found %d infinities in row of %zu BF16 values\n", __func__, infs, nb);
|
|
return false;
|
|
}
|
|
} break;
|
|
case GGML_TYPE_F16:
|
|
{
|
|
const ggml_fp16_t * f = (const ggml_fp16_t *) data;
|
|
size_t i = 0;
|
|
#if defined(__AVX2__)
|
|
for (; i + 15 < nb; i += 16) {
|
|
__m256i v = _mm256_loadu_si256((const __m256i *)(f + i));
|
|
__m256i vexp = _mm256_and_si256(v, _mm256_set1_epi16(0x7c00));
|
|
__m256i cmp = _mm256_cmpeq_epi16(vexp, _mm256_set1_epi16(0x7c00));
|
|
int mask = _mm256_movemask_epi8(cmp);
|
|
if (mask) {
|
|
for (size_t j = 0; j < 16; ++j) {
|
|
if (!validate_fp16(f[i + j], i + j)) {
|
|
return false;
|
|
}
|
|
}
|
|
GGML_UNREACHABLE();
|
|
}
|
|
}
|
|
#elif defined(__ARM_NEON)
|
|
for (; i + 7 < nb; i += 8) {
|
|
uint16x8_t v = vld1q_u16(f + i);
|
|
uint16x8_t vexp = vandq_u16(v, vdupq_n_u16(0x7c00));
|
|
uint16x8_t cmp = vceqq_u16(vexp, vdupq_n_u16(0x7c00));
|
|
uint64_t mask = vget_lane_u64(vreinterpret_u64_u8(vshrn_n_u16(cmp, 4)), 0);
|
|
if (mask) {
|
|
for (size_t j = 0; j < 8; ++j) {
|
|
if (!validate_fp16(f[i + j], i + j)) {
|
|
return false;
|
|
}
|
|
}
|
|
GGML_UNREACHABLE();
|
|
}
|
|
}
|
|
#endif
|
|
for (; i < nb; ++i) {
|
|
if (!validate_fp16(f[i], i)) {
|
|
return false;
|
|
}
|
|
}
|
|
} break;
|
|
case GGML_TYPE_F32:
|
|
{
|
|
const float * f = (const float *) data;
|
|
size_t i = 0;
|
|
#if defined(__AVX2__)
|
|
for (; i + 7 < nb; i += 8) {
|
|
__m256i v = _mm256_loadu_si256((const __m256i *)(f + i));
|
|
__m256i vexp = _mm256_and_si256(v, _mm256_set1_epi32(0x7f800000));
|
|
__m256i cmp = _mm256_cmpeq_epi32(vexp, _mm256_set1_epi32(0x7f800000));
|
|
int mask = _mm256_movemask_epi8(cmp);
|
|
if (mask) {
|
|
for (size_t j = 0; j < 8; ++j) {
|
|
if (!validate_float(f[i + j], i + j)) {
|
|
return false;
|
|
}
|
|
}
|
|
GGML_UNREACHABLE();
|
|
}
|
|
}
|
|
#elif defined(__ARM_NEON)
|
|
for (; i + 3 < nb; i += 4) {
|
|
uint32x4_t v = vld1q_u32((const uint32_t *)f + i);
|
|
uint32x4_t vexp = vandq_u32(v, vdupq_n_u32(0x7f800000));
|
|
uint32x4_t cmp = vceqq_u32(vexp, vdupq_n_u32(0x7f800000));
|
|
uint64_t mask = vget_lane_u64(vreinterpret_u64_u16(vshrn_n_u32(cmp, 8)), 0);
|
|
if (mask) {
|
|
for (size_t j = 0; j < 4; ++j) {
|
|
if (!validate_float(f[i + j], i + j)) {
|
|
return false;
|
|
}
|
|
}
|
|
GGML_UNREACHABLE();
|
|
}
|
|
}
|
|
#endif
|
|
for (; i < nb; ++i) {
|
|
if (!validate_float(f[i], i)) {
|
|
return false;
|
|
}
|
|
}
|
|
} break;
|
|
case GGML_TYPE_F64:
|
|
{
|
|
const double * f = (const double *) data;
|
|
for (size_t i = 0; i < nb; ++i) {
|
|
if (!validate_float(f[i], i)) {
|
|
return false;
|
|
}
|
|
}
|
|
} break;
|
|
case GGML_TYPE_Q4_0:
|
|
{
|
|
VALIDATE_ROW_DATA_D_F16_IMPL(block_q4_0, data, nb);
|
|
} break;
|
|
case GGML_TYPE_Q4_1:
|
|
{
|
|
VALIDATE_ROW_DATA_DM_F16_IMPL(block_q4_1, data, nb, d, m);
|
|
} break;
|
|
case GGML_TYPE_Q5_0:
|
|
{
|
|
VALIDATE_ROW_DATA_D_F16_IMPL(block_q5_0, data, nb);
|
|
} break;
|
|
case GGML_TYPE_Q5_1:
|
|
{
|
|
VALIDATE_ROW_DATA_DM_F16_IMPL(block_q5_1, data, nb, d, m);
|
|
} break;
|
|
case GGML_TYPE_Q8_0:
|
|
{
|
|
VALIDATE_ROW_DATA_D_F16_IMPL(block_q8_0, data, nb);
|
|
} break;
|
|
case GGML_TYPE_Q2_K:
|
|
{
|
|
VALIDATE_ROW_DATA_DM_F16_IMPL(block_q2_K, data, nb, d, dmin);
|
|
} break;
|
|
case GGML_TYPE_Q3_K:
|
|
{
|
|
VALIDATE_ROW_DATA_D_F16_IMPL(block_q3_K, data, nb);
|
|
} break;
|
|
case GGML_TYPE_Q4_K:
|
|
{
|
|
VALIDATE_ROW_DATA_DM_F16_IMPL(block_q4_K, data, nb, d, dmin);
|
|
} break;
|
|
case GGML_TYPE_Q5_K:
|
|
{
|
|
VALIDATE_ROW_DATA_DM_F16_IMPL(block_q5_K, data, nb, d, dmin);
|
|
} break;
|
|
case GGML_TYPE_Q6_K:
|
|
{
|
|
VALIDATE_ROW_DATA_D_F16_IMPL(block_q6_K, data, nb);
|
|
} break;
|
|
case GGML_TYPE_Q8_K:
|
|
{
|
|
const block_q8_K * q = (const block_q8_K *) data;
|
|
for (size_t i = 0; i < nb; ++i) {
|
|
if (!validate_float(q[i].d, i)) {
|
|
return false;
|
|
}
|
|
}
|
|
} break;
|
|
case GGML_TYPE_TQ1_0:
|
|
{
|
|
VALIDATE_ROW_DATA_D_F16_IMPL(block_tq1_0, data, nb);
|
|
} break;
|
|
case GGML_TYPE_TQ2_0:
|
|
{
|
|
VALIDATE_ROW_DATA_D_F16_IMPL(block_tq2_0, data, nb);
|
|
} break;
|
|
case GGML_TYPE_IQ1_S:
|
|
{
|
|
VALIDATE_ROW_DATA_D_F16_IMPL(block_iq1_s, data, nb);
|
|
} break;
|
|
case GGML_TYPE_IQ1_M:
|
|
{
|
|
const block_iq1_m * q = (const block_iq1_m *) data;
|
|
for (size_t i = 0; i < nb; ++i) {
|
|
iq1m_scale_t scale;
|
|
const uint16_t * sc = (const uint16_t *)q[i].scales;
|
|
scale.u16 = (sc[0] >> 12) | ((sc[1] >> 8) & 0x00f0) | ((sc[2] >> 4) & 0x0f00) | (sc[3] & 0xf000);
|
|
if (!validate_fp16(scale.f16, i)) {
|
|
return false;
|
|
}
|
|
}
|
|
} break;
|
|
case GGML_TYPE_IQ2_XXS:
|
|
{
|
|
VALIDATE_ROW_DATA_D_F16_IMPL(block_iq2_xxs, data, nb);
|
|
} break;
|
|
case GGML_TYPE_IQ2_XS:
|
|
{
|
|
VALIDATE_ROW_DATA_D_F16_IMPL(block_iq2_xs, data, nb);
|
|
} break;
|
|
case GGML_TYPE_IQ2_S:
|
|
{
|
|
VALIDATE_ROW_DATA_D_F16_IMPL(block_iq2_s, data, nb);
|
|
} break;
|
|
case GGML_TYPE_IQ3_XXS:
|
|
{
|
|
VALIDATE_ROW_DATA_D_F16_IMPL(block_iq3_xxs, data, nb);
|
|
} break;
|
|
|
|
case GGML_TYPE_IQ3_S:
|
|
{
|
|
VALIDATE_ROW_DATA_D_F16_IMPL(block_iq3_s, data, nb);
|
|
} break;
|
|
case GGML_TYPE_IQ4_XS:
|
|
{
|
|
VALIDATE_ROW_DATA_D_F16_IMPL(block_iq4_xs, data, nb);
|
|
} break;
|
|
case GGML_TYPE_IQ4_NL:
|
|
{
|
|
VALIDATE_ROW_DATA_D_F16_IMPL(block_iq4_nl, data, nb);
|
|
} break;
|
|
case GGML_TYPE_Q4_0_4_4:
|
|
case GGML_TYPE_Q4_0_4_8:
|
|
{
|
|
VALIDATE_ROW_DATA_DVEC_F16_IMPL(block_q4_0x4, data, nbytes / sizeof(block_q4_0x4), 4);
|
|
} break;
|
|
case GGML_TYPE_Q4_0_8_8:
|
|
{
|
|
VALIDATE_ROW_DATA_DVEC_F16_IMPL(block_q4_0x8, data, nbytes / sizeof(block_q4_0x8), 8);
|
|
} break;
|
|
|
|
case GGML_TYPE_I8:
|
|
case GGML_TYPE_I16:
|
|
case GGML_TYPE_I32:
|
|
case GGML_TYPE_I64:
|
|
// nothing to validate
|
|
break;
|
|
default:
|
|
{
|
|
fprintf(stderr, "%s: invalid type %d\n", __func__, type);
|
|
return false;
|
|
}
|
|
}
|
|
|
|
return true;
|
|
}
|