ikawrakow/ik_llama.cpp
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ik_llama.cpp/ggml/src/iqk/iqk_quantize.cpp
Kawrakow afcfa85756 Trying to fix iq1_s_r4/iq1_m_r4 quantization failure (#368) 
Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
2025-05-03 14:43:55 +03:00

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//
// Copyright (C) 2024 Iwan Kawrakow
// MIT license
// SPDX-License-Identifier: MIT
//
#if GGML_USE_IQK_MULMAT
#include "iqk_mul_mat.h"
#endif
#include "ggml-quants.h"
#include "ggml-impl.h"
#define GGML_COMMON_IMPL_C
#include "ggml-common.h"
#include "iqk_quantize.h"
#include "iqk_config.h"
#include <vector>
#include <utility>
#include <cstdint>
#include <cmath>
#include <array>
#include <algorithm>
#include <cstring>
#include <mutex>
#include <thread>
#include <atomic>
#include <unordered_map>
#include <string>
#if defined(_MSC_VER)
#pragma warning(disable: 4244 4267) // possible loss of data
#include <intrin.h>
#include <ammintrin.h>
#include <nmmintrin.h>
#include <immintrin.h>
#include <stdlib.h>
inline int popcount(uint8_t x) { return __popcnt(x); }
inline int popcount(uint16_t x) { return __popcnt(x); }
inline int popcount(uint32_t x) { return __popcnt(x); }
inline int popcount(uint64_t x) { return _mm_popcnt_u64(x); }
#else
constexpr int popcount(uint8_t x) { return __builtin_popcount(x); }
constexpr int popcount(uint16_t x) { return __builtin_popcount(x); }
constexpr int popcount(uint32_t x) { return __builtin_popcount(x); }
constexpr int popcount(uint64_t x) { return __builtin_popcountll(x); }
#endif
namespace {
inline int nearest_int(float fval) {
assert(fval <= 4194303.f);
float val = fval + 12582912.f;
int i; memcpy(&i, &val, sizeof(int));
return (i & 0x007fffff) - 0x00400000;
}
float make_qx_quants(int n, int nmax, const float * x, int8_t * L, const float * qw) {
float max = 0;
float amax = 0;
for (int i = 0; i < n; ++i) {
float ax = fabsf(x[i]);
if (ax > amax) { amax = ax; max = x[i]; }
}
if (!amax) { // all zero
for (int i = 0; i < n; ++i) L[i] = 0;
return 0.f;
}
float iscale = -nmax / max;
float sumlx = 0;
float suml2 = 0;
for (int i = 0; i < n; ++i) {
int l = nearest_int(iscale * x[i]);
l = std::max(-nmax, std::min(nmax-1, l));
L[i] = l + nmax;
sumlx += qw[i]*x[i]*l;
suml2 += qw[i]*l*l;
}
float scale = suml2 ? sumlx/suml2 : 0.0f;
float best = scale * sumlx;
for (int is = -9; is <= 9; ++is) {
if (is == 0) continue;
iscale = -(nmax + 0.1f*is) / max;
sumlx = suml2 = 0;
for (int i = 0; i < n; ++i) {
int l = nearest_int(iscale * x[i]);
l = std::max(-nmax, std::min(nmax-1, l));
sumlx += qw[i]*x[i]*l;
suml2 += qw[i]*l*l;
}
if (suml2 > 0 && sumlx*sumlx > best*suml2) {
for (int i = 0; i < n; ++i) {
int l = nearest_int(iscale * x[i]);
L[i] = nmax + std::max(-nmax, std::min(nmax-1, l));
}
scale = sumlx/suml2; best = scale*sumlx;
}
}
return scale;
}
struct IQ1BNQuantizer {
int8_t L[QK_IQ1BN];
void quantize_one_row_1bn(const float * src, block_iq1_bn * y, int n_per_row, const float * imatrix);
void quantize_one_row_2bn(const float * src, block_iq2_bn * y, int n_per_row, const float * imatrix);
static inline float row_max(int n_per_row, const float * src) {
float max_in_row = 0;
for (int j = 0; j < n_per_row; ++j) {
float ax = fabsf(src[j]);
max_in_row = std::max(max_in_row, ax);
}
return max_in_row;
}
// The Makefile has issues dwaling with this?
//static constexpr uint8_t k_mult[5] = {81, 27, 9, 3, 1};
static const uint8_t k_mult[5];
};
const uint8_t IQ1BNQuantizer::k_mult[5] = {81, 27, 9, 3, 1};
void IQ1BNQuantizer::quantize_one_row_1bn(const float * src, block_iq1_bn * y, int n_per_row, const float * imatrix) {
static const int k_nb[6] = {1, 3, 9, 27, 81, 243};
(void)imatrix;
const int nblock = n_per_row/QK_IQ1BN;
ggml_half * dptr = (ggml_half *)y;
y = (block_iq1_bn *)(dptr + 1);
float max = 0;
for (int j = 0; j < n_per_row; ++j) max = std::max(max, fabsf(src[j]));
ggml_half d = GGML_FP32_TO_FP16(max);
std::memcpy(dptr, &d, sizeof(d));
float thresh = 0.5f*max;
for (int ib = 0; ib < nblock; ++ib) {
std::memset(&y[ib], 0, sizeof(block_iq1_bn));
auto xb = src + ib*QK_IQ1BN;
int v13 = 0;
for (int i16 = 0; i16 < QK_IQ1BN/16; ++i16) {
for (int k = 0; k < 3; ++k) {
int idx = 0;
for (int j = 0; j < 5; ++j) {
float v = xb[16*i16 + 5*k + j];
int q = fabsf(v) < thresh ? 1 : v < 0 ? 0 : 2;
idx += k_nb[j]*q;
}
idx = (256*idx + k_nb[5] - 1)/k_nb[5];
y[ib].ql[3*i16 + k] = idx;
}
float v = xb[16*i16 + 15];
int q = fabsf(v) < thresh ? 1 : v < 0 ? 0 : 2;
v13 += k_nb[i16]*q;
}
y[ib].extra = (256*v13 + k_nb[5] - 1)/k_nb[5];
}
}
void IQ1BNQuantizer::quantize_one_row_2bn(const float * src, block_iq2_bn * y, int n_per_row, const float * imatrix) {
(void)imatrix;
const int nblock = n_per_row/QK_IQ1BN;
constexpr int Nj = QK_IQ1BN/4;
float max = 0;
for (int j = 0; j < n_per_row; ++j) max = std::max(max, fabsf(src[j]));
float * dptr = (float *)y;
*dptr = max;
y = (block_iq2_bn *)(dptr + 1);
float thresh = 0.5f*max;
for (int ib = 0; ib < nblock; ++ib) {
auto xb = src + QK_IQ1BN*ib;
for (int j = 0; j < QK_IQ1BN; ++j) {
L[j] = fabsf(xb[j]) < thresh ? 1 : xb[j] < 0 ? 0 : 2;
}
for (int j = 0; j < Nj; ++j) {
y[ib].qs[j] = L[j] | (L[j + Nj] << 2) | (L[j + 2*Nj] << 4) | (L[j + 3*Nj] << 6);
}
}
}
}
void iqk_quantize_any(int from_type, int to_type,
int64_t ne0, int64_t ne1, int64_t ne2, int64_t ne3,
uint64_t nb0, uint64_t nb1, uint64_t nb2, uint64_t nb3,
const void * x, void * y, void * work_buffer,
to_float_t to_float, from_float_t from_float, int ith, int nth) {
auto type_x = ggml_type(from_type);
GGML_ASSERT(ggml_type_size(type_x) == nb0);
auto type_y = ggml_type(to_type);
auto row_size_y = ggml_row_size(type_y, ne0);
int64_t nrows = ne1*ne2*ne3;
int64_t nrows_per_thread = (nrows + nth - 1)/nth;
int64_t first_row = nrows_per_thread*ith;
if (first_row >= nrows) return;
int64_t last_row = std::min(first_row + nrows_per_thread, nrows);
for (int64_t row = first_row; row < last_row; ++row) {
int64_t i3 = row/(ne1*ne2);
int64_t i2 = (row - i3*ne1*ne2)/ne1;
int64_t i1 = row - i3*ne1*ne2 - i2*ne1;
const char * cx = (const char *)x + i1*nb1 + i2*nb2 + i3*nb3;
// TODO: special case common types such as f16, q8_0
// (although the performance gains may be too small to justify the added complexity)
to_float((const void *)cx, (float *)work_buffer, ne0);
auto cy = (char *)y + (i3*ne1*ne2 + i2*ne1 + i1)*row_size_y;
from_float((const float *)work_buffer, (void *)cy, ne0);
}
}
size_t quantize_iq1_bn(const float * src, void * dst, int64_t nrows, int64_t n_per_row, const float * imatrix) {
IQ1BNQuantizer iq1bn;
auto row_size = ggml_row_size(GGML_TYPE_IQ1_BN, n_per_row);
auto qrow = (char *)dst;
for (int row = 0; row < nrows; ++row) {
iq1bn.quantize_one_row_1bn(src + row*n_per_row, (block_iq1_bn *)qrow, n_per_row, imatrix);
qrow += row_size;
}
return nrows*row_size;
}
void quantize_row_iq1_bn_ref(const float * x, block_iq1_bn * y, int64_t k) {
quantize_iq1_bn(x, y, 1, k, nullptr);
}
void quantize_row_iq1_bn(const float * x, void * y, int64_t k) {
quantize_iq1_bn(x, y, 1, k, nullptr);
}
void dequantize_row_iq1_bn(const block_iq1_bn * x, float * y, int64_t k) {
assert(k%QK_IQ1BN == 0);
int nblock = k / QK_IQ1BN;
for (int i = 0; i < nblock; ++i) {
uint8_t extra = x[i].extra;
auto ql = x[i].ql;
for (int i16 = 0; i16 < QK_IQ1BN/16; ++i16) {
for (int k = 0; k < 3; ++k) {
for (int j = 0; j < 5; ++j) {
uint8_t v = ql[k]*IQ1BNQuantizer::k_mult[j];
int8_t vs = ((v + (v >> 1)) >> 7);
*y++ = vs - 1;
}
}
ql += 3;
uint8_t v = extra*IQ1BNQuantizer::k_mult[i16];
int8_t vs = ((v + (v >> 1)) >> 7);
*y++ = vs - 1;
}
}
}
size_t quantize_iq2_bn(const float * src, void * dst, int64_t nrows, int64_t n_per_row, const float * imatrix) {
IQ1BNQuantizer iq1bn;
auto row_size = ggml_row_size(GGML_TYPE_IQ2_BN, n_per_row);
auto qrow = (char *)dst;
for (int row = 0; row < nrows; ++row) {
iq1bn.quantize_one_row_2bn(src + row*n_per_row, (block_iq2_bn *)qrow, n_per_row, imatrix);
qrow += row_size;
}
return nrows*row_size;
}
void quantize_row_iq2_bn_ref(const float * x, block_iq2_bn * y, int64_t k) {
quantize_iq2_bn(x, y, 1, k, nullptr);
}
void quantize_row_iq2_bn(const float * x, void * y, int64_t k) {
quantize_iq2_bn(x, y, 1, k, nullptr);
}
void dequantize_row_iq2_bn(const block_iq2_bn * x, float * y, int64_t k) {
assert(k%QK_IQ1BN == 0);
int nblock = k / QK_IQ1BN;
auto d1 = 1.f, d2 = 0.25f, d3 = d2*0.25f, d4 = d3*0.25f;
auto m = -1.f;
constexpr int Nj = QK_IQ1BN/4;
for (int i = 0; i < nblock; ++i) {
for (int j = 0; j < Nj; ++j) {
y[j+ 0] = d1*(x[i].qs[j] & 0x03) + m;
y[j+1*Nj] = d2*(x[i].qs[j] & 0x0c) + m;
y[j+2*Nj] = d3*(x[i].qs[j] & 0x30) + m;
y[j+3*Nj] = d4*(x[i].qs[j] & 0xc0) + m;
}
y += QK_IQ1BN;
}
}
namespace {
inline int8_t iq1bn_dequant(uint8_t q, int i) {
uint8_t v = IQ1BNQuantizer::k_mult[i]*q;
//int8_t vs = (v + (v << 1)) >> 8;
int8_t vs = 3*v >> 8;
return vs - 1;
}
}
static const int8_t iq1bn_values[1280] = {
-1, -1, -1, -1, -1, 0, 0, 0, 0, 0, 0, -1, -1, -1, -1, 1, -1, -1, -1, -1, -1, 0, -1, -1, -1, 0, 0, -1, -1, -1, 1, 0,
-1, -1, -1, -1, 1, -1, -1, -1, 0, 1, -1, -1, -1, 1, 1, -1, -1, -1, -1, -1, 0, -1, -1, 0, -1, 0, -1, -1, 1, -1, 0, -1,
-1, -1, 0, 0, -1, -1, 0, 0, 0, -1, -1, 1, 0, 0, -1, -1, -1, 1, 0, -1, -1, 0, 1, 0, -1, -1, 1, 1, 0, -1, -1, -1,
-1, 1, -1, -1, 0, 0, 0, 0, 0, 0, -1, 1, -1, -1, 1, -1, 1, -1, -1, -1, 0, 1, -1, -1, 0, 0, 1, -1, -1, 1, 0, 1,
-1, -1, -1, 1, 1, -1, -1, 0, 1, 1, -1, -1, 1, 1, 1, -1, -1, -1, -1, -1, 0, -1, 0, -1, -1, 0, -1, 1, -1, -1, 0, -1,
-1, 0, -1, 0, -1, 0, 0, -1, 0, -1, 1, 0, -1, 0, -1, -1, 1, -1, 0, -1, 0, 1, -1, 0, -1, 1, 1, -1, 0, -1, -1, -1,
0, 0, -1, 0, -1, 0, 0, -1, 0, 0, 0, 0, 0, 1, -1, 0, 0, -1, -1, 0, 0, 0, -1, 0, 0, 0, 0, -1, 1, 0, 0, 0,
-1, -1, 1, 0, 0, -1, 0, 1, 0, 0, -1, 1, 1, 0, 0, -1, -1, -1, 1, 0, -1, 0, -1, 1, 0, -1, 1, -1, 1, 0, -1, -1,
0, 1, 0, -1, 0, 0, 1, 0, -1, 1, 0, 1, 0, -1, -1, 1, 1, 0, -1, 0, 1, 1, 0, -1, 1, 1, 1, 0, -1, -1, -1, -1,
1, -1, 0, -1, -1, 1, -1, 1, -1, -1, 1, -1, 0, 0, 0, 0, 0, -1, 0, -1, 1, -1, 0, 0, -1, 1, -1, 1, 0, -1, 1, -1,
-1, 1, -1, 1, -1, 0, 1, -1, 1, -1, 1, 1, -1, 1, -1, -1, -1, 0, 1, -1, 0, -1, 0, 1, -1, 1, -1, 0, 1, -1, -1, 0,
0, 1, -1, 0, 0, 0, 1, -1, 1, 0, 0, 1, -1, -1, 1, 0, 1, -1, 0, 1, 0, 1, -1, 1, 1, 0, 1, -1, -1, -1, 1, 1,
-1, 0, -1, 1, 1, -1, 1, -1, 1, 1, -1, 0, 0, 0, 0, 0, -1, 0, 1, 1, -1, 0, 0, 1, 1, -1, 1, 0, 1, 1, -1, -1,
1, 1, 1, -1, 0, 1, 1, 1, -1, 1, 1, 1, 1, -1, -1, -1, -1, -1, 0, 0, -1, -1, -1, 0, 1, -1, -1, -1, 0, -1, 0, -1,
-1, 0, 0, 0, -1, -1, 0, 1, 0, -1, -1, 0, -1, 1, -1, -1, 0, 0, 1, -1, -1, 0, 1, 1, -1, -1, 0, -1, -1, 0, -1, 0,
0, -1, 0, -1, 0, 1, -1, 0, -1, 0, -1, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1, 0, 1, 0, 0, -1, 0, -1, 1,
0, -1, 0, 0, 1, 0, -1, 0, 1, 1, 0, -1, 0, -1, -1, 1, -1, 0, 0, -1, 1, -1, 0, 1, -1, 1, -1, 0, -1, 0, 1, -1,
0, 0, 0, 1, -1, 0, 1, 0, 1, -1, 0, -1, 1, 1, -1, 0, 0, 1, 1, -1, 0, 1, 1, 1, -1, 0, -1, -1, -1, 0, 0, 0,
-1, -1, 0, 0, 1, -1, -1, 0, 0, -1, 0, -1, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 1, 0, -1, 0, 0, -1, 1, -1,
0, 0, 0, 1, -1, 0, 0, 1, 1, -1, 0, 0, -1, -1, 0, 0, 0, 0, -1, 0, 0, 0, 1, -1, 0, 0, 0, -1, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, -1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, -1, -1, 1, 0, 0, 0, -1,
1, 0, 0, 1, -1, 1, 0, 0, -1, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, -1, 1, 1, 0,
0, 0, 1, 1, 0, 0, 1, 1, 1, 0, 0, -1, -1, -1, 1, 0, 0, -1, -1, 1, 0, 1, -1, -1, 1, 0, -1, 0, -1, 1, 0, 0,
0, -1, 1, 0, 1, 0, -1, 1, 0, -1, 1, -1, 1, 0, 0, 1, -1, 1, 0, 1, 1, -1, 1, 0, -1, -1, 0, 1, 0, 0, -1, 0,
1, 0, 1, -1, 0, 1, 0, -1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, -1, 1, 0, 1, 0,
0, 1, 0, 1, 0, 1, 1, 0, 1, 0, -1, -1, 1, 1, 0, 0, -1, 1, 1, 0, 1, -1, 1, 1, 0, -1, 0, 1, 1, 0, 0, 0,
1, 1, 0, 1, 0, 1, 1, 0, -1, 1, 1, 1, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, -1, -1, -1, -1, 1, 0, -1, -1, -1,
1, 1, -1, -1, -1, 1, -1, 0, -1, -1, 1, 0, 0, -1, -1, 1, 1, 0, -1, -1, 1, -1, 1, -1, -1, 1, 0, 0, 0, 0, 0, 0,
1, -1, -1, 1, 1, 1, -1, -1, 1, -1, -1, 0, -1, 1, 0, -1, 0, -1, 1, 1, -1, 0, -1, 1, -1, 0, 0, -1, 1, 0, 0, 0,
-1, 1, 1, 0, 0, -1, 1, -1, 1, 0, -1, 1, 0, 1, 0, -1, 1, 1, 1, 0, -1, 1, -1, -1, 1, -1, 1, 0, -1, 1, -1, 1,
1, -1, 1, -1, 1, -1, 0, 1, -1, 1, 0, 0, 1, -1, 1, 1, 0, 1, -1, 1, -1, 1, 1, -1, 1, 0, 0, 0, 0, 0, 0, 1,
1, -1, 1, 1, 1, 1, -1, 1, -1, -1, -1, 0, 1, 0, -1, -1, 0, 1, 1, -1, -1, 0, 1, -1, 0, -1, 0, 1, 0, 0, -1, 0,
1, 1, 0, -1, 0, 1, -1, 1, -1, 0, 1, 0, 1, -1, 0, 1, 1, 1, -1, 0, 1, -1, -1, 0, 0, 1, 0, -1, 0, 0, 1, 1,
-1, 0, 0, 1, -1, 0, 0, 0, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 1, -1, 1, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0,
0, 0, 1, 1, 0, 0, 1, -1, -1, 1, 0, 1, 0, -1, 1, 0, 1, 1, -1, 1, 0, 1, -1, 0, 1, 0, 1, 0, 0, 1, 0, 1,
1, 0, 1, 0, 1, -1, 1, 1, 0, 1, 0, 1, 1, 0, 1, 1, 1, 1, 0, 1, -1, -1, -1, 1, 1, 0, -1, -1, 1, 1, 1, -1,
-1, 1, 1, -1, 0, -1, 1, 1, 0, 0, -1, 1, 1, 1, 0, -1, 1, 1, -1, 1, -1, 1, 1, 0, 1, -1, 1, 1, 1, 1, -1, 1,
1, 0, 0, 0, 0, 0, -1, -1, 0, 1, 1, 0, -1, 0, 1, 1, 1, -1, 0, 1, 1, -1, 0, 0, 1, 1, 0, 0, 0, 1, 1, 1,
0, 0, 1, 1, -1, 1, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 1, 1, -1, -1, 1, 1, 1, 0, -1, 1, 1, 1, 1, -1, 1,
1, 1, -1, 0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 1, 1, 1, -1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1,
};
void ggml_vec_dot_iq1_bn_q8_K64(int n, float * s, size_t bs, const void * vx, size_t bx, const void * vy, size_t by, int nrc) {
GGML_UNUSED(bs);
GGML_UNUSED(bx);
GGML_UNUSED(by);
GGML_UNUSED(nrc);
static_assert(QK_IQ1BN == 64, "This dot product implementation for iq1_bn requires a block size of 64");
#if GGML_USE_IQK_MULMAT
if (iqk_mul_mat(1, 1, n, GGML_TYPE_IQ1_BN, vx, 0, GGML_TYPE_Q8_K64, vy, 0, s, 0, 0, 1)) {
return;
}
#endif
const block_iq1_bn * x = (const block_iq1_bn *)vx;
const float * d8 = (const float *)vy;
const int8_t * q8 = (const int8_t *)(d8 + 4);
int nblock = n / QK_IQ1BN;
int sumi[8] = {};
int8_t q1[16];
for (int ii = 0; ii < nblock; ii += 32) {
int16_t sum16[8] = {};
int nb = std::min(ii + 32, nblock);
for (int i = ii; i < nb; ++i) {
auto ql = x[i].ql;
const int8_t * extra = iq1bn_values + 5*x[i].extra;
for (int i16 = 0; i16 < QK_IQ1BN/16; ++i16) {
for (int k = 0; k < 3; ++k) {
uint8_t q = *ql++;
const int8_t * vs = iq1bn_values + 5*q;
for (int j = 0; j < 5; ++j) q1[5*k+j] = vs[j];
}
q1[15] = extra[i16];
// We collect 8 q8 values per block into each element of sum16
// => 32 x 8 = 256 values in each loop over i, so this cannot overflow the int16_t range
// (q8 is in -127...127, and hence the sum is in -32512...32512
for (int j = 0; j < 8; ++j) sum16[j] += q8[2*j+0]*q1[2*j+0] + q8[2*j+1]*q1[2*j+1];
q8 += 16;
}
}
for (int j = 0; j < 8; ++j) sumi[j] += sum16[j];
}
*s = d8[0] * (sumi[0] + sumi[1]) + d8[1] * (sumi[2] + sumi[3]) + d8[2] * (sumi[4] + sumi[5]) + d8[3] * (sumi[6] + sumi[7]);
}
void vec_dot_iq2_bn_q8_K64(int n, float * s, size_t bs, const void * vx, size_t bx, const void * vy, size_t by, int nrc) {
GGML_ASSERT(nrc == 1);
GGML_UNUSED(bs);
GGML_UNUSED(bx);
GGML_UNUSED(by);
GGML_UNUSED(nrc);
static_assert(QK_IQ1BN == 64, "This dot product implementation for iq2_bn requires a block size of 64");
#if GGML_USE_IQK_MULMAT
if (iqk_mul_mat(1, 1, n, GGML_TYPE_IQ2_BN, vx, 0, GGML_TYPE_Q8_K64, vy, 0, s, 0, 0, 1)) {
return;
}
#endif
constexpr int Nj = QK_IQ1BN/4;
const block_iq2_bn * x = (const block_iq2_bn *)vx;
int nblock = n / QK_IQ1BN;
const float * d = (const float *)vy;
const int8_t * q8 = (const int8_t *)(d + 4);
int sum[16] = { };
int sum0[4] = { };
for (int i = 0; i < nblock; ++i) {
for (int j = 0; j < Nj/4; ++j) {
for (int l = 0; l < 4; ++l) {
sum[4*j + 0] += q8[4*j + l + 0] * (x[i].qs[4*j+l] & 0x03);
sum[4*j + 1] += q8[4*j + l + 1*Nj] * (x[i].qs[4*j+l] & 0x0c);
sum[4*j + 2] += q8[4*j + l + 2*Nj] * (x[i].qs[4*j+l] & 0x30);
sum[4*j + 3] += q8[4*j + l + 3*Nj] * (x[i].qs[4*j+l] & 0xc0);
sum0[j] += q8[4*j + l] + q8[4*j + l + 1*Nj] + q8[4*j + l + 2*Nj] + q8[4*j + l + 3*Nj];
}
}
q8 += QK_IQ1BN;
}
float sumf = 0;
for (int j = 0; j < 4; ++j) {
sumf += d[j] * (sum[4*j + 0] + 0.25f*sum[4*j + 1] + 0.0625*sum[4*j + 2] + 0.015625*sum[4*j + 3] - sum0[j]);
}
*s = sumf;
}
void quantize_row_q8_K64_ref(const float * x, block_q8_K64 * y, int64_t k) {
GGML_ASSERT(k >= 8*QK_IQ1BN);
float * dptr = (float *)y;
auto qs = (int8_t *)(dptr + 8);
#ifdef __ARM_NEON
static const uint8_t k_shuffle[16] = {0, 4, 8, 12, 16, 20, 24, 28, 32, 36, 40, 44, 48, 52, 56, 60};
auto shuffle = vld1q_u8(k_shuffle);
float32x4_t max[4] = { };
for (int j = 0; j < k; j += 16) {
for (int i = 0; i < 4; ++i) {
auto val = vld1q_f32(x + j + 4*i);
val = vabsq_f32(val);
max[i] = vmaxq_f32(max[i], val);
}
}
float32x4_t vid[4];
for (int i = 0; i < 4; ++i) {
dptr[i] = vmaxvq_f32(max[i])/127;
float id = dptr[i] > 0 ? 1/dptr[i] : 0.f;
vid[i] = vdupq_n_f32(id);
}
int8x16x4_t q;
int32x4_t qsum = {};
const int8x16_t m1 = vdupq_n_s8(1);
for (int j = 0; j < k; j += 16) {
for (int i = 0; i < 4; ++i) {
auto val = vld1q_f32(x + j + 4*i);
val = vmulq_f32(vid[i], val);
auto ival = vcvtnq_s32_f32(val);
q.val[i] = vreinterpretq_s8_s32(ival);
}
auto qi = vqtbl4q_s8(q, shuffle);
qsum = ggml_vdotq_s32(qsum, qi, m1);
vst1q_s8(qs, qi);
qs += 16;
}
auto sumf = vmulq_f32(vld1q_f32(dptr), vcvtq_f32_s32(qsum));
vst1q_f32(dptr + 4, sumf);
#elif defined __AVX__
__m128 max[4] = {};
__m128 sign_bit = _mm_set1_ps(-0.f);
for (int j = 0; j < k; j += 16) {
for (int i = 0; i < 4; ++i) {
auto val = _mm_loadu_ps(x + j + 4*i);
val = _mm_andnot_ps(sign_bit, val);
max[i] = _mm_max_ps(max[i], val);
}
}
__m128 vid[4];
for (int i = 0; i < 4; ++i) {
max[i] = _mm_max_ps(max[i], _mm_movehl_ps(max[i], max[i]));
max[i] = _mm_max_ss(max[i], _mm_movehdup_ps(max[i]));
float maxi = _mm_cvtss_f32(max[i]);
dptr[i] = maxi/127;
float id = dptr[i] > 0 ? 1/dptr[i] : 0.f;
vid[i] = _mm_set1_ps(id);
}
__m128i q[4];
__m128i sums = _mm_setzero_si128();
__m128i m1_8 = _mm_set1_epi8(1);
__m128i m1_16 = _mm_set1_epi16(1);
for (int j = 0; j < k; j += 16) {
for (int i = 0; i < 4; ++i) {
auto val = _mm_loadu_ps(x + j + 4*i);
val = _mm_round_ps(_mm_mul_ps(vid[i], val), _MM_ROUND_NEAREST);
q[i] = _mm_cvtps_epi32(val);
}
auto q1 = _mm_packs_epi32(q[0], q[1]);
auto q2 = _mm_packs_epi32(q[2], q[3]);
auto qi = _mm_packs_epi16(q1, q2);
auto aux = _mm_maddubs_epi16(m1_8, qi);
sums = _mm_add_epi32(sums, _mm_madd_epi16(m1_16, aux));
_mm_storeu_si128((__m128i *)qs, qi);
qs += 16;
}
auto minus = _mm_mul_ps(_mm_loadu_ps(dptr), _mm_cvtepi32_ps(sums));
_mm_storeu_ps(dptr + 4, minus);
#else
float aux[4] = {0.f, 0.f, 0.f, 0.f};
for (int j = 0; j < k; j += 16) {
for (int i = 0; i < 4; ++i) {
for (int l = 0; l < 4; ++l) {
float ax = fabsf(x[j+4*i+l]);
aux[i] = std::max(aux[i], ax);
}
}
}
for (int i = 0; i < 4; ++i) {
dptr[i] = aux[i]/127;
aux[i] = dptr[i] > 0 ? 1/dptr[i] : 0.f;
}
int32_t sum[4] = {};
for (int j = 0; j < k; j += 16) {
for (int i = 0; i < 4; ++i) {
for (int l = 0; l < 4; ++l) {
qs[j+4*i+l] = nearest_int(aux[i]*x[j+4*i+l]);
sum[i] += qs[j+4*i+l];
}
}
}
for (int i = 0; i < 4; ++i) dptr[4+i] = dptr[i]*sum[i];
#endif
}
void quantize_row_q8_K64(const float * x, void * y, int64_t k) {
quantize_row_q8_K64_ref(x, (block_q8_K64 *)y, k);
}
#ifdef __AVX2__
namespace {
inline float hsum_float_4(__m128 x) {
x = _mm_add_ps(x, _mm_movehl_ps(x, x));
x = _mm_add_ss(x, _mm_movehdup_ps(x));
return _mm_cvtss_f32(x);
}
inline float hsum_float_8(__m256 x) {
return hsum_float_4(_mm_add_ps(_mm256_castps256_ps128(x), _mm256_extractf128_ps(x, 1)));
}
inline int hsum_i32_8(const __m256i a) {
const __m128i sum128 = _mm_add_epi32(_mm256_castsi256_si128(a), _mm256_extractf128_si256(a, 1));
const __m128i hi64 = _mm_unpackhi_epi64(sum128, sum128);
const __m128i sum64 = _mm_add_epi32(hi64, sum128);
const __m128i hi32 = _mm_shuffle_epi32(sum64, _MM_SHUFFLE(2, 3, 0, 1));
return _mm_cvtsi128_si32(_mm_add_epi32(sum64, hi32));
}
inline float hmax_f32_8(__m256 x) {
__m128 max4 = _mm_max_ps(_mm256_extractf128_ps(x, 1), _mm256_castps256_ps128(x));
max4 = _mm_max_ps( max4, _mm_movehl_ps(max4, max4));
max4 = _mm_max_ss( max4, _mm_movehdup_ps( max4));
return _mm_cvtss_f32(max4);
}
}
#endif
void quantize_row_q8_K16(const float * x, void * vy, int64_t nk) {
float * dptr = (float *)vy;
int8_t * qy = (int8_t *)(dptr + 5);
int n64 = nk / 64;
#ifdef z__AVX2__
__m256 sign_bit = _mm256_set1_ps(-0.f);
__m256 vmax[4] = {};
__m256 vsum[4] = {};
for (int i64 = 0; i64 < n64; ++i64) {
for (int k = 0; k < 4; ++k) {
auto v1 = _mm256_loadu_ps(x + 64*i64 + 16*k + 0);
auto v2 = _mm256_loadu_ps(x + 64*i64 + 16*k + 8);
vsum[k] = _mm256_add_ps(vsum[k], _mm256_add_ps(v1, v2));
v1 = _mm256_andnot_ps(sign_bit, v1);
v2 = _mm256_andnot_ps(sign_bit, v2);
vmax[k] = _mm256_max_ps(vmax[k], _mm256_max_ps(v1, v2));
}
}
__m256 sum = _mm256_add_ps(_mm256_add_ps(vsum[0], vsum[1]), _mm256_add_ps(vsum[2], vsum[3]));
dptr[4] = hsum_float_8(sum);
for (int k = 0; k < 4; ++k) {
float max = hmax_f32_8(vmax[k]);
dptr[k] = max/127;
vmax[k] = _mm256_set1_ps(dptr[k] > 0 ? 1/dptr[k] : 0.f);
}
__m256i ival[8];
const __m256i perm = _mm256_setr_epi32(0, 4, 1, 5, 2, 6, 3, 7);
for (int i64 = 0; i64 < n64; ++i64) {
for (int k = 0; k < 4; ++k) {
__m256 v0 = _mm256_mul_ps(vmax[k], _mm256_loadu_ps(x + 64*i64 + 16*k + 0));
__m256 v1 = _mm256_mul_ps(vmax[k], _mm256_loadu_ps(x + 64*i64 + 16*k + 8));
v0 = _mm256_round_ps(v0, _MM_ROUND_NEAREST);
v1 = _mm256_round_ps(v1, _MM_ROUND_NEAREST);
ival[2*k+0] = _mm256_cvtps_epi32(v0);
ival[2*k+1] = _mm256_cvtps_epi32(v1);
}
for (int k = 0; k < 2; ++k) {
auto i0 = _mm256_packs_epi32(ival[4*k+0], ival[4*k+1]);
auto i1 = _mm256_packs_epi32(ival[4*k+2], ival[4*k+3]);
i0 = _mm256_packs_epi16(i0, i1);
i0 = _mm256_permutevar8x32_epi32(i0, perm);
_mm256_storeu_si256((__m256i *)qy, i0);
qy += 32;
}
}
#elif defined z__ARM_NEON
static const uint8_t k_shuffle[16] = {0, 4, 8, 12, 16, 20, 24, 28, 32, 36, 40, 44, 48, 52, 56, 60};
auto shuffle = vld1q_u8(k_shuffle);
float32x4_t vmax[4] = {};
float32x4_t vsum[4] = {};
for (int i64 = 0; i64 < n64; ++i64) {
for (int k = 0; k < 4; ++k) {
auto v = vld1q_f32_x4(x + 64*i64 + 16*k);
vsum[k] = vaddq_f32(vsum[k], vaddq_f32(v.val[0], v.val[1]));
vsum[k] = vaddq_f32(vsum[k], vaddq_f32(v.val[2], v.val[3]));
vmax[k] = vmaxq_f32(vmax[k], vmaxq_f32(vabsq_f32(v.val[0]), vabsq_f32(v.val[1])));
vmax[k] = vmaxq_f32(vmax[k], vmaxq_f32(vabsq_f32(v.val[2]), vabsq_f32(v.val[3])));
}
}
dptr[4] = vaddvq_f32(vaddq_f32(vaddq_f32(vsum[0], vsum[1]), vaddq_f32(vsum[2], vsum[3])));
for (int k = 0; k < 4; ++k) {
float max = vmaxvq_f32(vmax[k]);
dptr[k] = max/127;
vmax[k] = vdupq_n_f32(dptr[k] > 0 ? 1/dptr[k] : 0.f);
}
int8x16x4_t q;
for (int i64 = 0; i64 < n64; ++i64) {
for (int k = 0; k < 4; ++k) {
auto v = vld1q_f32_x4(x + 64*i64 + 16*k);
for (int j = 0; j < 4; ++j) {
q.val[j] = vreinterpretq_s8_s32(vcvtnq_s32_f32(vmulq_f32(vmax[k], v.val[j])));
}
auto qi = vqtbl4q_s8(q, shuffle);
vst1q_s8(qy, qi);
qy += 16;
}
}
#else
float amax[4] = {0.f, 0.f, 0.f, 0.f};
for (int i64 = 0; i64 < n64; ++i64) {
for (int k = 0; k < 4; ++k) {
for (int j = 0; j < 16; ++j) {
float ax = std::abs(x[64*i64 + 16*k + j]);
amax[k] = std::max(amax[k], ax);
}
}
}
for (int k = 0; k < 4; ++k) {
dptr[k] = amax[k]/127;
amax[k] = dptr[k] > 0 ? 1/dptr[k] : 0.f;
}
int sumi[4] = {};
for (int i64 = 0; i64 < n64; ++i64) {
for (int k = 0; k < 4; ++k) {
for (int j = 0; j < 16; ++j) {
int ix = nearest_int(amax[k]*x[64*i64 + 16*k + j]);
sumi[k] += ix;
qy[64*i64 + 16*k + j] = ix;
}
}
}
dptr[4] = dptr[0]*sumi[0] + dptr[1]*sumi[1] + dptr[2]*sumi[2] + dptr[3]*sumi[3];
#endif
}
void quantize_row_q8_0_x4(const float * x, void * vy, int64_t k) {
const int nb = k / QK8_0;
const int nb4 = 4*(nb/4);
block_q8_0 * y = (block_q8_0 *)vy;
block_q8_0_x4 * y4 = (block_q8_0_x4 *)vy;
#if defined(__aarch64__)
for (int i = 0; i < nb; i++) {
int i4 = i/4, ir = i%4;
float32x4_t srcv [8];
float32x4_t asrcv[8];
float32x4_t amaxv[8];
for (int j = 0; j < 8; j++) srcv[j] = vld1q_f32(x + i*32 + 4*j);
for (int j = 0; j < 8; j++) asrcv[j] = vabsq_f32(srcv[j]);
for (int j = 0; j < 4; j++) amaxv[2*j] = vmaxq_f32(asrcv[2*j], asrcv[2*j+1]);
for (int j = 0; j < 2; j++) amaxv[4*j] = vmaxq_f32(amaxv[4*j], amaxv[4*j+2]);
for (int j = 0; j < 1; j++) amaxv[8*j] = vmaxq_f32(amaxv[8*j], amaxv[8*j+4]);
const float amax = vmaxvq_f32(amaxv[0]);
const float d = amax / ((1 << 7) - 1);
const float id = d ? 1.0f/d : 0.0f;
if (i < nb4) {
y4[i4].d[ir] = GGML_FP32_TO_FP16(d);
} else {
y[i].d = GGML_FP32_TO_FP16(d);
}
for (int j = 0; j < 8; j++) {
const float32x4_t v = vmulq_n_f32(srcv[j], id);
const int32x4_t vi = vcvtnq_s32_f32(v);
if (i < nb4) {
y4[i4].qs[32*ir + 4*j + 0] = vgetq_lane_s32(vi, 0);
y4[i4].qs[32*ir + 4*j + 1] = vgetq_lane_s32(vi, 1);
y4[i4].qs[32*ir + 4*j + 2] = vgetq_lane_s32(vi, 2);
y4[i4].qs[32*ir + 4*j + 3] = vgetq_lane_s32(vi, 3);
} else {
y[i].qs[4*j + 0] = vgetq_lane_s32(vi, 0);
y[i].qs[4*j + 1] = vgetq_lane_s32(vi, 1);
y[i].qs[4*j + 2] = vgetq_lane_s32(vi, 2);
y[i].qs[4*j + 3] = vgetq_lane_s32(vi, 3);
}
}
}
#else
for (int i = 0; i < nb; i++) {
int i4 = i/4, ir = i%4;
// Load elements into 4 AVX vectors
__m256 v0 = _mm256_loadu_ps( x );
__m256 v1 = _mm256_loadu_ps( x + 8 );
__m256 v2 = _mm256_loadu_ps( x + 16 );
__m256 v3 = _mm256_loadu_ps( x + 24 );
x += 32;
const __m256 signBit = _mm256_set1_ps( -0.0f );
__m256 maxAbs = _mm256_andnot_ps( signBit, v0 );
maxAbs = _mm256_max_ps( maxAbs, _mm256_andnot_ps( signBit, v1 ) );
maxAbs = _mm256_max_ps( maxAbs, _mm256_andnot_ps( signBit, v2 ) );
maxAbs = _mm256_max_ps( maxAbs, _mm256_andnot_ps( signBit, v3 ) );
__m128 max4 = _mm_max_ps( _mm256_extractf128_ps( maxAbs, 1 ), _mm256_castps256_ps128( maxAbs ) );
max4 = _mm_max_ps( max4, _mm_movehl_ps( max4, max4 ) );
max4 = _mm_max_ss( max4, _mm_movehdup_ps( max4 ) );
const float maxScalar = _mm_cvtss_f32( max4 );
const float d = maxScalar / 127.f;
if (i < nb4) {
y4[i4].d[ir] = GGML_FP32_TO_FP16(d);
} else {
y[i].d = GGML_FP32_TO_FP16(d);
}
const float id = ( maxScalar != 0.0f ) ? 127.f / maxScalar : 0.0f;
const __m256 mul = _mm256_set1_ps( id );
v0 = _mm256_mul_ps( v0, mul );
v1 = _mm256_mul_ps( v1, mul );
v2 = _mm256_mul_ps( v2, mul );
v3 = _mm256_mul_ps( v3, mul );
v0 = _mm256_round_ps( v0, _MM_ROUND_NEAREST );
v1 = _mm256_round_ps( v1, _MM_ROUND_NEAREST );
v2 = _mm256_round_ps( v2, _MM_ROUND_NEAREST );
v3 = _mm256_round_ps( v3, _MM_ROUND_NEAREST );
__m256i i0 = _mm256_cvtps_epi32( v0 );
__m256i i1 = _mm256_cvtps_epi32( v1 );
__m256i i2 = _mm256_cvtps_epi32( v2 );
__m256i i3 = _mm256_cvtps_epi32( v3 );
// Convert int32 to int16
i0 = _mm256_packs_epi32( i0, i1 ); // 0, 1, 2, 3, 8, 9, 10, 11, 4, 5, 6, 7, 12, 13, 14, 15
i2 = _mm256_packs_epi32( i2, i3 ); // 16, 17, 18, 19, 24, 25, 26, 27, 20, 21, 22, 23, 28, 29, 30, 31
// Convert int16 to int8
i0 = _mm256_packs_epi16( i0, i2 ); // 0, 1, 2, 3, 8, 9, 10, 11, 16, 17, 18, 19, 24, 25, 26, 27, 4, 5, 6, 7, 12, 13, 14, 15, 20, 21, 22, 23, 28, 29, 30, 31
// We got our precious signed bytes, but the order is now wrong
// These AVX2 pack instructions process 16-byte pieces independently
// The following instruction is fixing the order
const __m256i perm = _mm256_setr_epi32( 0, 4, 1, 5, 2, 6, 3, 7 );
i0 = _mm256_permutevar8x32_epi32( i0, perm );
if (i < nb4) {
_mm256_storeu_si256((__m256i *)y4[i4].qs + ir, i0);
} else {
_mm256_storeu_si256((__m256i *)y[i].qs, i0);
}
}
#endif
}
namespace {
template <typename Block, typename Block_x4>
void quantize_row_q8_1_x4_T(const float * x, Block * y, int64_t k) {
assert(k % QK8_1 == 0);
const int nb = k / QK8_1;
const int nb4 = 4*(nb/4);
Block_x4 * y4 = (Block_x4 *)y;
#if defined(__aarch64__)
for (int i = 0; i < nb; i++) {
int i4 = i/4, ir = i%4;
float32x4_t srcv [8];
float32x4_t asrcv[8];
float32x4_t amaxv[8];
for (int j = 0; j < 8; j++) srcv[j] = vld1q_f32(x + i*32 + 4*j);
for (int j = 0; j < 8; j++) asrcv[j] = vabsq_f32(srcv[j]);
for (int j = 0; j < 4; j++) amaxv[2*j] = vmaxq_f32(asrcv[2*j], asrcv[2*j+1]);
for (int j = 0; j < 2; j++) amaxv[4*j] = vmaxq_f32(amaxv[4*j], amaxv[4*j+2]);
for (int j = 0; j < 1; j++) amaxv[8*j] = vmaxq_f32(amaxv[8*j], amaxv[8*j+4]);
const float amax = vmaxvq_f32(amaxv[0]);
const float d = amax / ((1 << 7) - 1);
const float id = d ? 1.0f/d : 0.0f;
if (i < nb4) {
y4[i4].d[ir] = GGML_FP32_TO_FP16(d);
} else {
y[i].d = GGML_FP32_TO_FP16(d);
}
int32x4_t accv = vdupq_n_s32(0);
for (int j = 0; j < 8; j++) {
const float32x4_t v = vmulq_n_f32(srcv[j], id);
const int32x4_t vi = vcvtnq_s32_f32(v);
if (i < nb4) {
y4[i4].qs[QK8_1*ir + 4*j + 0] = vgetq_lane_s32(vi, 0);
y4[i4].qs[QK8_1*ir + 4*j + 1] = vgetq_lane_s32(vi, 1);
y4[i4].qs[QK8_1*ir + 4*j + 2] = vgetq_lane_s32(vi, 2);
y4[i4].qs[QK8_1*ir + 4*j + 3] = vgetq_lane_s32(vi, 3);
} else {
y[i].qs[4*j + 0] = vgetq_lane_s32(vi, 0);
y[i].qs[4*j + 1] = vgetq_lane_s32(vi, 1);
y[i].qs[4*j + 2] = vgetq_lane_s32(vi, 2);
y[i].qs[4*j + 3] = vgetq_lane_s32(vi, 3);
}
accv = vaddq_s32(accv, vi);
}
if constexpr (std::is_same_v<Block, block_q8_1>) {
if (i < nb4) {
y4[i4].d[ir+4] = GGML_FP32_TO_FP16(d * vaddvq_s32(accv));
} else {
y[i].s = GGML_FP32_TO_FP16(d * vaddvq_s32(accv));
}
} else {
if (i < nb4) {
y4[i4].d[ir+4] = GGML_FP32_TO_BF16(d * vaddvq_s32(accv)).bits;
} else {
y[i].s = GGML_FP32_TO_BF16(d * vaddvq_s32(accv)).bits;
}
}
}
#else
for (int i = 0; i < nb; i++) {
int i4 = i/4, ir = i%4;
// Load elements into 4 AVX vectors
__m256 v0 = _mm256_loadu_ps( x );
__m256 v1 = _mm256_loadu_ps( x + 8 );
__m256 v2 = _mm256_loadu_ps( x + 16 );
__m256 v3 = _mm256_loadu_ps( x + 24 );
x += 32;
// Compute max(abs(e)) for the block
const __m256 signBit = _mm256_set1_ps( -0.0f );
__m256 maxAbs = _mm256_andnot_ps( signBit, v0 );
maxAbs = _mm256_max_ps( maxAbs, _mm256_andnot_ps( signBit, v1 ) );
maxAbs = _mm256_max_ps( maxAbs, _mm256_andnot_ps( signBit, v2 ) );
maxAbs = _mm256_max_ps( maxAbs, _mm256_andnot_ps( signBit, v3 ) );
__m128 max4 = _mm_max_ps( _mm256_extractf128_ps( maxAbs, 1 ), _mm256_castps256_ps128( maxAbs ) );
max4 = _mm_max_ps( max4, _mm_movehl_ps( max4, max4 ) );
max4 = _mm_max_ss( max4, _mm_movehdup_ps( max4 ) );
const float max_scalar = _mm_cvtss_f32( max4 );
// Quantize these floats
float d = max_scalar / 127.f;
if constexpr (std::is_same_v<Block, block_q8_1>) {
if (i < nb4) {
y4[i4].d[ir] = GGML_FP32_TO_FP16(d);
} else {
y[i].d = GGML_FP32_TO_FP16(d);
}
} else {
if (i < nb4) {
auto t = GGML_FP32_TO_BF16(d);
y4[i4].d[ir] = t.bits;
d = ggml_bf16_to_fp32(t);
} else {
auto t = GGML_FP32_TO_BF16(d);
y[i].d = t.bits;
d = ggml_bf16_to_fp32(t);
}
}
const float id = d > 0 ? 1/d : 0.f;
const __m256 mul = _mm256_set1_ps( id );
// Apply the multiplier
v0 = _mm256_mul_ps( v0, mul );
v1 = _mm256_mul_ps( v1, mul );
v2 = _mm256_mul_ps( v2, mul );
v3 = _mm256_mul_ps( v3, mul );
// Round to nearest integer
v0 = _mm256_round_ps( v0, _MM_ROUND_NEAREST );
v1 = _mm256_round_ps( v1, _MM_ROUND_NEAREST );
v2 = _mm256_round_ps( v2, _MM_ROUND_NEAREST );
v3 = _mm256_round_ps( v3, _MM_ROUND_NEAREST );
// Convert floats to integers
__m256i i0 = _mm256_cvtps_epi32( v0 );
__m256i i1 = _mm256_cvtps_epi32( v1 );
__m256i i2 = _mm256_cvtps_epi32( v2 );
__m256i i3 = _mm256_cvtps_epi32( v3 );
// Compute the sum of the quants and set y[i].s
int isum = hsum_i32_8(_mm256_add_epi32(_mm256_add_epi32(i0, i1), _mm256_add_epi32(i2, i3)));
if constexpr (std::is_same_v<Block, block_q8_1>) {
if (i < nb4) {
y4[i4].d[ir+4] = GGML_FP32_TO_FP16(d * isum);
} else {
y[i].s = GGML_FP32_TO_FP16(d * isum);
}
} else {
if (i < nb4) {
y4[i4].d[ir+4] = GGML_FP32_TO_BF16(d * isum).bits;
} else {
y[i].s = GGML_FP32_TO_BF16(d * isum).bits;
}
}
// Convert int32 to int16
i0 = _mm256_packs_epi32( i0, i1 ); // 0, 1, 2, 3, 8, 9, 10, 11, 4, 5, 6, 7, 12, 13, 14, 15
i2 = _mm256_packs_epi32( i2, i3 ); // 16, 17, 18, 19, 24, 25, 26, 27, 20, 21, 22, 23, 28, 29, 30, 31
// Convert int16 to int8
i0 = _mm256_packs_epi16( i0, i2 ); // 0, 1, 2, 3, 8, 9, 10, 11, 16, 17, 18, 19, 24, 25, 26, 27, 4, 5, 6, 7, 12, 13, 14, 15, 20, 21, 22, 23, 28, 29, 30, 31
// We got our precious signed bytes, but the order is now wrong
// These AVX2 pack instructions process 16-byte pieces independently
// The following instruction is fixing the order
const __m256i perm = _mm256_setr_epi32( 0, 4, 1, 5, 2, 6, 3, 7 );
i0 = _mm256_permutevar8x32_epi32( i0, perm );
if (i < nb4) {
_mm256_storeu_si256((__m256i *)y4[i4].qs + ir, i0);
} else {
_mm256_storeu_si256((__m256i *)y[i].qs, i0);
}
}
#endif
}
}
void quantize_row_q8_1_x4(const float * x, void * vy, int64_t k) {
quantize_row_q8_1_x4_T<block_q8_1, block_q8_1_x4>(x, (block_q8_1 *)vy, k);
}
void quantize_row_q8_2_x4(const float * x, void * vy, int64_t k) {
quantize_row_q8_1_x4_T<block_q8_2, block_q8_2_x4>(x, (block_q8_2 *)vy, k);
}
//
// ============================================== iq2_K
//
namespace {
inline int best_index_iq2nl(const int8_t * values, float x) {
int idx = x < values[1] ? 0 : x > values[2] ? 2 : 1;
return x - values[idx] < values[idx+1] - x ? idx : idx + 1;
}
void quantize_row_iq2_k_impl(const float * x, void * vy, int n_per_row, const float * quant_weights) {
constexpr int kBlockSize = 16;
block_iq2_k * y = (block_iq2_k *)vy;
float scales[QK_K/kBlockSize];
float weight[kBlockSize];
float sumx[kBlockSize+1], sumw[kBlockSize+1];
float sw[QK_K/kBlockSize];
int8_t Ls[QK_K/kBlockSize];
std::array<std::pair<float,int>, kBlockSize> pairs;
const int8_t * shifted_values = iq2nl_values + 4;
for (int ibl = 0; ibl < n_per_row/QK_K; ++ibl) {
memset(&y[ibl], 0, sizeof(block_iq2_k));
y[ibl].d = GGML_FP32_TO_FP16(0.f);
const float * xbl = x + ibl*QK_K;
float sumx2 = 0;
for (int j = 0; j < QK_K; ++j) sumx2 += xbl[j]*xbl[j];
const float sigma2 = 1.5f*sumx2/QK_K;
uint16_t extra = 0;
float max_abs_scale = 0;
for (int ib = 0; ib < QK_K/kBlockSize; ++ib) {
const float * xb = xbl + kBlockSize*ib;
if (quant_weights) {
const float * qw = quant_weights + ibl*QK_K + ib*kBlockSize;
for (int j = 0; j < kBlockSize; ++j) weight[j] = qw[j] * sqrtf(sigma2 + xb[j]*xb[j]);
} else {
for (int j = 0; j < kBlockSize; ++j) weight[j] = 0.25f*sigma2 + xb[j]*xb[j];
}
sw[ib] = 0;
for (int j = 0; j < kBlockSize; ++j) {
sw[ib] += weight[j];
pairs[j] = {xb[j], j};
}
std::sort(pairs.begin(), pairs.end());
sumx[0] = sumw[0] = 0;
for (int j = 0; j < kBlockSize; ++j) {
int jj = pairs[j].second;
sumw[j+1] = sumw[j] + weight[jj];
sumx[j+1] = sumx[j] + weight[jj]*xb[jj];
}
float best = 0, d = 0;
bool is_shifted = false;
float sumqx, sumq2;
for (int i1 = 0; i1 < kBlockSize; ++i1) {
for (int i2 = i1; i2 < kBlockSize; ++i2) {
for (int i3 = i2; i3 < kBlockSize; ++i3) {
sumqx = (sumx[i1] - sumx[ 0])*iq2nl_values[0] + (sumx[i2] - sumx[i1])*iq2nl_values[1]
+ (sumx[i3] - sumx[i2])*iq2nl_values[2] + (sumx[kBlockSize] - sumx[i3])*iq2nl_values[3];
sumq2 = (sumw[i1] - sumw[ 0])*iq2nl_values[0]*iq2nl_values[0] + (sumw[i2] - sumw[i1])*iq2nl_values[1]*iq2nl_values[1]
+ (sumw[i3] - sumw[i2])*iq2nl_values[2]*iq2nl_values[2] + (sumw[kBlockSize] - sumw[i3])*iq2nl_values[3]*iq2nl_values[3];
if (sumq2 > 0 && sumqx*sumqx > best*sumq2) {
d = sumqx/sumq2; best = d*sumqx; is_shifted = false;
}
sumqx = (sumx[i1] - sumx[ 0])*shifted_values[0] + (sumx[i2] - sumx[i1])*shifted_values[1]
+ (sumx[i3] - sumx[i2])*shifted_values[2] + (sumx[kBlockSize] - sumx[i3])*shifted_values[3];
sumq2 = (sumw[i1] - sumw[ 0])*shifted_values[0]*shifted_values[0] + (sumw[i2] - sumw[i1])*shifted_values[1]*shifted_values[1]
+ (sumw[i3] - sumw[i2])*shifted_values[2]*shifted_values[2] + (sumw[kBlockSize] - sumw[i3])*shifted_values[3]*shifted_values[3];
if (sumq2 > 0 && sumqx*sumqx > best*sumq2) {
d = sumqx/sumq2; best = d*sumqx; is_shifted = true;
}
sumqx = (sumx[i1] - sumx[ 0])*iq2nl_values[3] + (sumx[i2] - sumx[i1])*iq2nl_values[2]
+ (sumx[i3] - sumx[i2])*iq2nl_values[1] + (sumx[kBlockSize] - sumx[i3])*iq2nl_values[0];
sumq2 = (sumw[i1] - sumw[ 0])*iq2nl_values[3]*iq2nl_values[3] + (sumw[i2] - sumw[i1])*iq2nl_values[2]*iq2nl_values[2]
+ (sumw[i3] - sumw[i2])*iq2nl_values[1]*iq2nl_values[1] + (sumw[kBlockSize] - sumw[i3])*iq2nl_values[0]*iq2nl_values[0];
if (sumq2 > 0 && sumqx*sumqx > best*sumq2) {
d = sumqx/sumq2; best = d*sumqx; is_shifted = false;
}
sumqx = (sumx[i1] - sumx[ 0])*shifted_values[3] + (sumx[i2] - sumx[i1])*shifted_values[2]
+ (sumx[i3] - sumx[i2])*shifted_values[1] + (sumx[kBlockSize] - sumx[i3])*shifted_values[0];
sumq2 = (sumw[i1] - sumw[ 0])*shifted_values[3]*shifted_values[3] + (sumw[i2] - sumw[i1])*shifted_values[2]*shifted_values[2]
+ (sumw[i3] - sumw[i2])*shifted_values[1]*shifted_values[1] + (sumw[kBlockSize] - sumw[i3])*shifted_values[0]*shifted_values[0];
if (sumq2 > 0 && sumqx*sumqx > best*sumq2) {
d = sumqx/sumq2; best = d*sumqx; is_shifted = true;
}
}
}
}
scales[ib] = d;
if (is_shifted) extra |= (1 << ib);
float abs_scale = fabsf(scales[ib]);
max_abs_scale = std::max(max_abs_scale, abs_scale);
}
if (!max_abs_scale) continue;
float d = make_qx_quants(QK_K/kBlockSize, 8, scales, Ls, sw);
if (!d) continue;
//float d = -max_scale/8;
y[ibl].extra = extra;
float id = 1/d;
float sumqx = 0, sumq2 = 0;
for (int ib = 0; ib < QK_K/kBlockSize; ++ib) {
int ls = nearest_int(id*scales[ib]);
ls = std::max(-8, std::min(7, ls));
y[ibl].scales[ib/2] |= ((ls + 8) << 4*(ib%2));
float dl = d * ls;
if (dl) {
const int8_t * block_values = y[ibl].extra & (1 << ib) ? shifted_values : iq2nl_values;
const float * xb = xbl + kBlockSize*ib;
if (quant_weights) {
const float * qw = quant_weights + ibl*QK_K + ib*kBlockSize;
for (int j = 0; j < kBlockSize; ++j) weight[j] = qw[j] * sqrtf(sigma2 + xb[j]*xb[j]);
} else {
for (int j = 0; j < kBlockSize; ++j) weight[j] = 0.25f*sigma2 + xb[j]*xb[j];
}
float idl = 1/dl;
int ib32 = ib/2;
int offset = 16*(ib%2);
uint8_t * qs = y[ibl].qs + 32*(ib32/4) + offset;
for (int j = 0; j < 16; ++j) {
const float al = idl*xb[j];
int ibest = best_index_iq2nl(block_values, al);
qs[j] |= (ibest << 2*(ib32%4));
float w = weight[j];
float q = block_values[ibest]*ls;
sumqx += w*q*xb[j];
sumq2 += w*q*q;
}
}
}
y[ibl].d = GGML_FP32_TO_FP16(1.030f*(sumq2 > 0 ? sumqx/sumq2 : d));
}
}
}
void quantize_row_iq2_k_ref(const float * x, block_iq2_k * y, int64_t k) {
assert(k % QK_K == 0);
quantize_iq2_k(x, (void *)y, 1, k, nullptr);
}
void quantize_row_iq2_k(const float * x, void * vy, int64_t k) {
assert(k % QK_K == 0);
block_iq2_k * y = (block_iq2_k *)vy;
quantize_row_iq2_k_ref(x, y, k);
}
size_t quantize_iq2_k(const float * src, void * dst, int64_t nrows, int64_t n_per_row, const float * imatrix) {
GGML_ASSERT(n_per_row%QK_K == 0);
int nblock = n_per_row/QK_K;
char * qrow = (char *)dst;
for (int64_t row = 0; row < nrows; ++row) {
quantize_row_iq2_k_impl(src, (void *)qrow, n_per_row, imatrix);
src += n_per_row;
qrow += nblock*sizeof(block_iq2_k);
}
return nrows * nblock * sizeof(block_iq2_k);
}
void dequantize_row_iq2_k(const block_iq2_k * x, float * 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 uint8_t * qs = x[i].qs;
uint16_t extra = x[i].extra;
int shift = 0;
for (int ib32 = 0; ib32 < QK_K/32; ++ib32) {
float dl1 = d * ((x[i].scales[ib32] & 0xf) - 8);
float dl2 = d * ((x[i].scales[ib32] >> 4) - 8);
const int8_t * values1 = extra & 1 ? iq2nl_values + 4 : iq2nl_values;
const int8_t * values2 = extra & 2 ? iq2nl_values + 4 : iq2nl_values;
extra >>= 2;
for (int j = 0; j < 16; ++j) {
y[j+ 0] = dl1 * values1[(qs[j+ 0] >> shift) & 3];
y[j+16] = dl2 * values2[(qs[j+16] >> shift) & 3];
}
y += 32;
shift += 2;
if (shift == 8) { qs += 32; shift = 0; }
}
}
}
void vec_dot_iq2_k_q8_k(int n, float * s, size_t bs, const void * vx, size_t bx, const void * vy, size_t by, int nrc) {
assert(n % QK_K == 0);
assert(nrc == 1);
GGML_UNUSED(nrc);
GGML_UNUSED(bx);
GGML_UNUSED(by);
GGML_UNUSED(bs);
#if GGML_USE_IQK_MULMAT
if (iqk_mul_mat(1, 1, n, GGML_TYPE_IQ2_K, vx, 0, GGML_TYPE_Q8_K, vy, 0, s, 0, 0, 1)) {
return;
}
#endif
GGML_ABORT("not implemented");
}
namespace {
void quantize_row_iq2_ks_impl(const float * x, void * vy, int n_per_row, const float * quant_weights, float * all_scales, float * all_sw, int8_t * all_Ls) {
constexpr int kBlockSize = 32;
constexpr int kMax_i1 = 3*kBlockSize/4;
constexpr int kMin_i3 = kBlockSize/4;
//constexpr int kNtry = 5;
//constexpr float kStep = 1.f;
ggml_half * dptr = (ggml_half *)vy;
*dptr = GGML_FP32_TO_FP16(0.f);
block_iq2_ks * y = (block_iq2_ks *)(dptr + 1);
float weight[kBlockSize];
float sumx[kBlockSize+1], sumw[kBlockSize+1];
std::array<std::pair<float,int>, kBlockSize> pairs;
float val [4] = {float(iq2nl_values[0]), float(iq2nl_values[1]), float(iq2nl_values[2]), float(iq2nl_values[3])};
float sval[4] = {float(iq2nl_values[4]), float(iq2nl_values[5]), float(iq2nl_values[6]), float(iq2nl_values[7])};
const int8_t * shifted_values = iq2nl_values + 4;
const int nblock = n_per_row/QK_K;
for (int ibl = 0; ibl < nblock; ++ibl) {
memset(&y[ibl], 0, sizeof(block_iq2_ks));
auto scales = all_scales + ibl*(QK_K/kBlockSize);
auto sw = all_sw + ibl*(QK_K/kBlockSize);
const float * xbl = x + ibl*QK_K;
float sumx2 = 0;
for (int j = 0; j < QK_K; ++j) sumx2 += xbl[j]*xbl[j];
const float sigma2 = 1.5f*sumx2/QK_K;
uint16_t extra = 0;
for (int ib = 0; ib < QK_K/kBlockSize; ++ib) {
const float * xb = xbl + kBlockSize*ib;
if (quant_weights) {
const float * qw = quant_weights + ibl*QK_K + ib*kBlockSize;
for (int j = 0; j < kBlockSize; ++j) weight[j] = qw[j] * sqrtf(sigma2 + xb[j]*xb[j]);
} else {
for (int j = 0; j < kBlockSize; ++j) weight[j] = 0.25f*sigma2 + xb[j]*xb[j];
}
sw[ib] = 0;
for (int j = 0; j < kBlockSize; ++j) {
sw[ib] += weight[j];
pairs[j] = {xb[j], j};
}
//float amax = 0, max = 0;
//for (int j = 0; j < kBlockSize; ++j) {
// float ax = fabsf(xb[j]);
// if (ax > amax) {
// amax = ax; max = xb[j];
// }
//}
//if (!amax) {
// scales[ib] = 0;
// continue;
//}
//float d = kNtry > 0 ? -max/iq2nl_values[0] : max/iq2nl_values[0];
//float id = 1/d;
//float sumqx_p = 0, sumq2_p = 0;
//float sumqx_m = 0, sumq2_m = 0;
//for (int j = 0; j < kBlockSize; ++j) {
// float w = weight[j];
// float al = id*xb[j];
// int l = best_index_iq2nl(iq2nl_values, al);
// float q = iq2nl_values[l];
// sumqx_p += w*q*xb[j];
// sumq2_p += w*q*q;
// l = best_index_iq2nl(iq2nl_values, -al);
// q = iq2nl_values[l];
// sumqx_m += w*q*xb[j];
// sumq2_m += w*q*q;
//}
//d = sumqx_p/sumq2_p;
//float best = d*sumqx_p;
//if (sumq2_m > 0 && sumqx_m*sumqx_m > best*sumq2_m) {
// d = sumqx_m/sumq2_m; best = d*sumqx_m;
//}
//bool is_shifted = false;
//for (int itry = -kNtry; itry <= kNtry; ++itry) {
// id = (kStep*itry + iq2nl_values[0])/max;
// sumqx_p = sumq2_p = 0;
// sumqx_m = sumq2_m = 0;
// for (int j = 0; j < kBlockSize; ++j) {
// float w = weight[j];
// float al = id*xb[j];
// int l = best_index_iq2nl(iq2nl_values, al);
// float q = iq2nl_values[l];
// sumqx_p += w*q*xb[j];
// sumq2_p += w*q*q;
// l = best_index_iq2nl(iq2nl_values, -al);
// q = iq2nl_values[l];
// sumqx_m += w*q*xb[j];
// sumq2_m += w*q*q;
// }
// if (sumq2_p > 0 && sumqx_p*sumqx_p > best*sumq2_p) {
// d = sumqx_p/sumq2_p; best = d * sumqx_p; is_shifted = false;
// }
// if (sumq2_m > 0 && sumqx_m*sumqx_m > best*sumq2_m) {
// d = sumqx_m/sumq2_m; best = d * sumqx_m; is_shifted = false;
// }
// id = (kStep*itry + shifted_values[0])/max;
// sumqx_p = sumq2_p = 0;
// sumqx_m = sumq2_m = 0;
// for (int j = 0; j < kBlockSize; ++j) {
// float w = weight[j];
// float al = id*xb[j];
// int l = best_index_iq2nl(shifted_values, al);
// float q = shifted_values[l];
// sumqx_p += w*q*xb[j];
// sumq2_p += w*q*q;
// l = best_index_iq2nl(shifted_values, -al);
// q = shifted_values[l];
// sumqx_m += w*q*xb[j];
// sumq2_m += w*q*q;
// }
// if (sumq2_p > 0 && sumqx_p*sumqx_p > best*sumq2_p) {
// d = sumqx_p/sumq2_p; best = d * sumqx_p; is_shifted = true;
// }
// if (sumq2_m > 0 && sumqx_m*sumqx_m > best*sumq2_m) {
// d = sumqx_m/sumq2_m; best = d * sumqx_m; is_shifted = true;
// }
//}
std::sort(pairs.begin(), pairs.end());
sumx[0] = sumw[0] = 0;
for (int j = 0; j < kBlockSize; ++j) {
int jj = pairs[j].second;
sumw[j+1] = sumw[j] + weight[jj];
sumx[j+1] = sumx[j] + weight[jj]*xb[jj];
}
float best = 0, d = 0;
bool is_shifted = false;
float sumqx, sumq2;
for (int i1 = 0; i1 < kMax_i1; ++i1) {
for (int i2 = i1; i2 < kBlockSize; ++i2) {
for (int i3 = std::max(i2, kMin_i3); i3 < kBlockSize; ++i3) {
sumqx = (sumx[i1] - sumx[ 0])*val[0] + (sumx[i2] - sumx[i1])*val[1]
+ (sumx[i3] - sumx[i2])*val[2] + (sumx[kBlockSize] - sumx[i3])*val[3];
sumq2 = (sumw[i1] - sumw[ 0])*val[0]*val[0] + (sumw[i2] - sumw[i1])*val[1]*val[1]
+ (sumw[i3] - sumw[i2])*val[2]*val[2] + (sumw[kBlockSize] - sumw[i3])*val[3]*val[3];
if (sumq2 > 0 && sumqx*sumqx > best*sumq2) {
d = sumqx/sumq2; best = d*sumqx; is_shifted = false;
}
sumqx = (sumx[i1] - sumx[ 0])*sval[0] + (sumx[i2] - sumx[i1])*sval[1]
+ (sumx[i3] - sumx[i2])*sval[2] + (sumx[kBlockSize] - sumx[i3])*sval[3];
sumq2 = (sumw[i1] - sumw[ 0])*sval[0]*sval[0] + (sumw[i2] - sumw[i1])*sval[1]*sval[1]
+ (sumw[i3] - sumw[i2])*sval[2]*sval[2] + (sumw[kBlockSize] - sumw[i3])*sval[3]*sval[3];
if (sumq2 > 0 && sumqx*sumqx > best*sumq2) {
d = sumqx/sumq2; best = d*sumqx; is_shifted = true;
}
sumqx = (sumx[i1] - sumx[ 0])*val[3] + (sumx[i2 ] - sumx[i1])*val[2]
+ (sumx[i3] - sumx[i2])*val[1] + (sumx[kBlockSize] - sumx[i3])*val[0];
sumq2 = (sumw[i1] - sumw[ 0])*val[3]*val[3] + (sumw[i2 ] - sumw[i1])*val[2]*val[2]
+ (sumw[i3] - sumw[i2])*val[1]*val[1] + (sumw[kBlockSize] - sumw[i3])*val[0]*val[0];
if (sumq2 > 0 && sumqx*sumqx > best*sumq2) {
d = sumqx/sumq2; best = d*sumqx; is_shifted = false;
}
sumqx = (sumx[i1] - sumx[ 0])*sval[3] + (sumx[i2 ] - sumx[i1])*sval[2]
+ (sumx[i3] - sumx[i2])*sval[1] + (sumx[kBlockSize] - sumx[i3])*sval[0];
sumq2 = (sumw[i1] - sumw[ 0])*sval[3]*sval[3] + (sumw[i2 ] - sumw[i1])*sval[2]*sval[2]
+ (sumw[i3] - sumw[i2])*sval[1]*sval[1] + (sumw[kBlockSize] - sumw[i3])*sval[0]*sval[0];
if (sumq2 > 0 && sumqx*sumqx > best*sumq2) {
d = sumqx/sumq2; best = d*sumqx; is_shifted = true;
}
}
}
}
scales[ib] = d;
if (is_shifted) extra |= (1 << ib);
}
y[ibl].extra = extra;
}
float d = make_qx_quants(nblock*(QK_K/kBlockSize), 16, all_scales, all_Ls, all_sw);
if (!d) return;
float sumqx = 0, sumq2 = 0;
for (int ibl = 0; ibl < nblock; ++ibl) {
auto xbl = x + ibl*QK_K;
float sumx2 = 0;
for (int j = 0; j < QK_K; ++j) sumx2 += xbl[j]*xbl[j];
const float sigma2 = 1.5f*sumx2/QK_K;
auto Ls = all_Ls + ibl*(QK_K/kBlockSize);
for (int ib = 0; ib < QK_K/kBlockSize; ++ib) {
int ls = Ls[ib];
y[ibl].scales[ib/2] |= ((ls & 0xf) << 4*(ib%2));
y[ibl].extra |= ((ls >> 4) << (8 + ib));
ls -= 16;
float dl = d * ls;
if (dl) {
const int8_t * block_values = y[ibl].extra & (1 << ib) ? shifted_values : iq2nl_values;
const float * xb = xbl + kBlockSize*ib;
if (quant_weights) {
const float * qw = quant_weights + ibl*QK_K + ib*kBlockSize;
for (int j = 0; j < kBlockSize; ++j) weight[j] = qw[j] * sqrtf(sigma2 + xb[j]*xb[j]);
} else {
for (int j = 0; j < kBlockSize; ++j) weight[j] = 0.25f*sigma2 + xb[j]*xb[j];
}
float idl = 1/dl;
uint8_t * qs = y[ibl].qs + 32*(ib/4);
for (int j = 0; j < 32; ++j) {
const float al = idl*xb[j];
int ibest = best_index_iq2nl(block_values, al);
qs[j] |= (ibest << 2*(ib%4));
float w = weight[j];
float q = block_values[ibest]*ls;
sumqx += w*q*xb[j];
sumq2 += w*q*q;
}
}
}
}
*dptr = GGML_FP32_TO_FP16(1.030f*(sumq2 > 0 ? sumqx/sumq2 : d));
}
}
void quantize_row_iq2_ks_ref(const float * x, block_iq2_ks * y, int64_t k) {
assert(k % QK_K == 0);
quantize_iq2_ks(x, (void *)y, 1, k, nullptr);
}
void quantize_row_iq2_ks(const float * x, void * vy, int64_t k) {
assert(k % QK_K == 0);
block_iq2_ks * y = (block_iq2_ks *)vy;
quantize_row_iq2_ks_ref(x, y, k);
}
size_t quantize_iq2_ks(const float * src, void * dst, int64_t nrows, int64_t n_per_row, const float * imatrix) {
constexpr int kBlockSize = 32;
GGML_ASSERT(n_per_row%QK_K == 0);
auto row_size = ggml_row_size(GGML_TYPE_IQ2_KS, n_per_row);
int nblock = n_per_row/QK_K;
std::vector<float> all_scales(nblock*(QK_K/kBlockSize)), all_sw(nblock*(QK_K/kBlockSize));
std::vector<int8_t> all_Ls(nblock*(QK_K/kBlockSize));
char * qrow = (char *)dst;
for (int64_t row = 0; row < nrows; ++row) {
quantize_row_iq2_ks_impl(src, (void *)qrow, n_per_row, imatrix, all_scales.data(), all_sw.data(), all_Ls.data());
src += n_per_row;
qrow += row_size;
}
return nrows * row_size;
}
void dequantize_row_iq2_ks(const block_iq2_ks * x, float * y, int64_t k) {
assert(k % QK_K == 0);
const int nb = k / QK_K;
const ggml_half * dptr = (const ggml_half *)x;
const float d = GGML_FP16_TO_FP32(*dptr);
x = (const block_iq2_ks *)(dptr + 1);
for (int i = 0; i < nb; i++) {
const uint8_t * qs = x[i].qs;
uint16_t extra = x[i].extra;
int shift = 0;
for (int ib64 = 0; ib64 < QK_K/64; ++ib64) {
float dl1 = d * (((x[i].scales[ib64] & 0xf) | ((extra >> 4) & 0x10)) - 16);
float dl2 = d * (((x[i].scales[ib64] >> 4) | ((extra >> 5) & 0x10)) - 16);
const int8_t * values1 = extra & 1 ? iq2nl_values + 4 : iq2nl_values;
const int8_t * values2 = extra & 2 ? iq2nl_values + 4 : iq2nl_values;
extra >>= 2;
for (int j = 0; j < 32; ++j) {
y[j+ 0] = dl1 * values1[(qs[j] >> (shift+0)) & 3];
y[j+32] = dl2 * values2[(qs[j] >> (shift+2)) & 3];
}
y += 64;
shift += 4;
if (shift == 8) { qs += 32; shift = 0; }
}
}
}
void vec_dot_iq2_ks_q8_k(int n, float * s, size_t bs, const void * vx, size_t bx, const void * vy, size_t by, int nrc) {
assert(n % QK_K == 0);
assert(nrc == 1);
GGML_UNUSED(nrc);
GGML_UNUSED(bx);
GGML_UNUSED(by);
GGML_UNUSED(bs);
#if GGML_USE_IQK_MULMAT
if (iqk_mul_mat(1, 1, n, GGML_TYPE_IQ2_KS, vx, 0, GGML_TYPE_Q8_K, vy, 0, s, 0, 0, 1)) {
return;
}
#endif
const ggml_half * dptr = (const ggml_half *)vx;
const float d = GGML_FP16_TO_FP32(*dptr);
const block_iq2_ks * x = (const block_iq2_ks *)(dptr + 1);
const block_q8_K * y = (const block_q8_K *)vy;
const int nb = n / QK_K;
float sumf = 0;
for (int i = 0; i < nb; i++) {
const uint8_t * qs = x[i].qs;
const int8_t * q8 = y[i].qs;
uint16_t extra = x[i].extra;
int sumi = 0;
for (int ib128 = 0; ib128 < QK_K/128; ++ib128) {
int d1 = (((x[i].scales[2*ib128+0] & 0xf) | ((extra >> 4) & 0x10)) - 16);
int d2 = (((x[i].scales[2*ib128+0] >> 4) | ((extra >> 5) & 0x10)) - 16);
int d3 = (((x[i].scales[2*ib128+1] & 0xf) | ((extra >> 6) & 0x10)) - 16);
int d4 = (((x[i].scales[2*ib128+1] >> 4) | ((extra >> 7) & 0x10)) - 16);
const int8_t * values1 = extra & 1 ? iq2nl_values + 4 : iq2nl_values;
const int8_t * values2 = extra & 2 ? iq2nl_values + 4 : iq2nl_values;
const int8_t * values3 = extra & 4 ? iq2nl_values + 4 : iq2nl_values;
const int8_t * values4 = extra & 8 ? iq2nl_values + 4 : iq2nl_values;
extra >>= 4;
int sumi1 = 0, sumi2 = 0, sumi3 = 0, sumi4 = 0;
for (int j = 0; j < 32; ++j) {
sumi1 += q8[j+ 0] * values1[(qs[j] >> 0) & 3];
sumi2 += q8[j+32] * values2[(qs[j] >> 2) & 3];
sumi3 += q8[j+64] * values3[(qs[j] >> 4) & 3];
sumi4 += q8[j+96] * values4[(qs[j] >> 6) & 3];
}
sumi += d1*sumi1 + d2*sumi2 + d3*sumi3 + d4*sumi4;
q8 += 128;
qs += 32;
}
sumf += y[i].d * sumi;
}
*s = d * sumf;
}
//
// ============================================== iq3_k
//
namespace {
const int8_t iq3nl_index[111] = {
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 8, 8, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 9,
9, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 10, 10, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 11, 11, 4, 4, 4, 4,
4, 4, 4, 4, 4, 4, 12, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 13, 13, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6,
6, 6, 6, 6, 14, 14, 7, 7, 7, 7, 7, 7, 7, 7, 7
};
inline int best_index_iq3nl(const int8_t * values, float x) {
int ix = (int)x - values[0];
if (ix < 0 || ix >= 111) return ix < 0 ? 0 : 7;
ix = iq3nl_index[ix];
return ix < 8 ? ix : x - values[ix-8] < values[ix-7] - x ? ix-8 : ix-7;
}
static void quantize_row_iq3_k_impl(const float * x, void * vy, int n_per_row, const float * quant_weights) {
constexpr int ntry = 3;
block_iq3_k * y = (block_iq3_k *)vy;
float scales[QK_K/16];
float weight[16];
uint8_t L[16];
const int8_t * shifted_values = iq3nl_values + 8;
for (int ibl = 0; ibl < n_per_row/QK_K; ++ibl) {
memset(&y[ibl], 0, sizeof(block_iq3_k));
y[ibl].d = GGML_FP32_TO_FP16(0.f);
const float * xbl = x + ibl*QK_K;
float sumx2 = 0;
for (int j = 0; j < QK_K; ++j) sumx2 += xbl[j]*xbl[j];
const float sigma2 = 1.5f*sumx2/QK_K;
uint16_t extra = 0;
float max_abs_scale = 0;
for (int ib = 0; ib < QK_K/16; ++ib) {
const float * xb = xbl + 16*ib;
if (quant_weights) {
const float * qw = quant_weights + ibl*QK_K + ib*16;
for (int j = 0; j < 16; ++j) weight[j] = qw[j] * sqrtf(sigma2 + xb[j]*xb[j]);
} else {
for (int j = 0; j < 16; ++j) weight[j] = 0.25f*sigma2 + xb[j]*xb[j];
}
float amax = 0, max = 0;
for (int j = 0; j < 16; ++j) {
float ax = fabsf(xb[j]);
if (ax > amax) {
amax = ax; max = xb[j];
}
}
if (!amax) {
scales[ib] = 0;
continue;
}
float d = ntry > 0 ? -max/iq3nl_values[0] : max/iq3nl_values[0];
float id = 1/d;
float sumqx_p = 0, sumq2_p = 0;
float sumqx_m = 0, sumq2_m = 0;
for (int j = 0; j < 16; ++j) {
float w = weight[j];
float al = id*xb[j];
int l = best_index_iq3nl(iq3nl_values, al);
float q = iq3nl_values[l];
sumqx_p += w*q*xb[j];
sumq2_p += w*q*q;
l = best_index_iq3nl(iq3nl_values, -al);
q = iq3nl_values[l];
sumqx_m += w*q*xb[j];
sumq2_m += w*q*q;
}
d = sumqx_p/sumq2_p;
float best = d*sumqx_p;
if (sumq2_m > 0 && sumqx_m*sumqx_m > best*sumq2_m) {
d = sumqx_m/sumq2_m; best = d*sumqx_m;
}
bool is_shifted = false;
for (int itry = -ntry; itry <= ntry; ++itry) {
id = (2*itry + iq3nl_values[0])/max;
sumqx_p = sumq2_p = 0;
sumqx_m = sumq2_m = 0;
for (int j = 0; j < 16; ++j) {
float w = weight[j];
float al = id*xb[j];
int l = best_index_iq3nl(iq3nl_values, al);
float q = iq3nl_values[l];
sumqx_p += w*q*xb[j];
sumq2_p += w*q*q;
l = best_index_iq3nl(iq3nl_values, -al);
q = iq3nl_values[l];
sumqx_m += w*q*xb[j];
sumq2_m += w*q*q;
}
if (sumq2_p > 0 && sumqx_p*sumqx_p > best*sumq2_p) {
d = sumqx_p/sumq2_p; best = d * sumqx_p; is_shifted = false;
}
if (sumq2_m > 0 && sumqx_m*sumqx_m > best*sumq2_m) {
d = sumqx_m/sumq2_m; best = d * sumqx_m; is_shifted = false;
}
id = (2*itry + shifted_values[0])/max;
sumqx_p = sumq2_p = 0;
sumqx_m = sumq2_m = 0;
for (int j = 0; j < 16; ++j) {
float w = weight[j];
float al = id*xb[j];
int l = best_index_iq3nl(shifted_values, al);
float q = shifted_values[l];
sumqx_p += w*q*xb[j];
sumq2_p += w*q*q;
l = best_index_iq3nl(shifted_values, -al);
q = shifted_values[l];
sumqx_m += w*q*xb[j];
sumq2_m += w*q*q;
}
if (sumq2_p > 0 && sumqx_p*sumqx_p > best*sumq2_p) {
d = sumqx_p/sumq2_p; best = d * sumqx_p; is_shifted = true;
}
if (sumq2_m > 0 && sumqx_m*sumqx_m > best*sumq2_m) {
d = sumqx_m/sumq2_m; best = d * sumqx_m; is_shifted = true;
}
}
if (!d) {
scales[ib] = 0; continue;
}
const int8_t * block_values = is_shifted ? shifted_values : iq3nl_values;
float sumqx = 0, sumq2 = 0;
id = 1/d;
for (int j = 0; j < 16; ++j) {
float w = weight[j];
float al = id*xb[j];
int l = best_index_iq3nl(block_values, al);
L[j] = l;
float q = block_values[l];
sumqx += w*q*xb[j];
sumq2 += w*q*q;
}
if (sumq2 > 0) d = sumqx/sumq2;
float best_d = d;
for (int iter = 0; iter < 128; ++iter) {
float gmax = 0;
int best_j = -1, dir = 0;
for (int j = 0; j < 16; ++j) {
float w = weight[j];
float g = d * w * (xb[j] - d*block_values[L[j]]);
if (g > 0 && L[j] < 7) {
if (g > gmax) {
gmax = g; best_j = j; dir = 1;
}
}
else if (g < 0 && L[j] > 0) {
if (-g > gmax) {
gmax = -g; best_j = j; dir = -1;
}
}
}
if (best_j < 0) break;
float w = weight[best_j];
sumqx += w*xb[best_j]*(block_values[L[best_j]+dir] - block_values[L[best_j]]);
sumq2 += w*(block_values[L[best_j]+dir]*block_values[L[best_j]+dir] - block_values[L[best_j]]*block_values[L[best_j]]);
L[best_j] += dir;
if (sumq2 > 0 && sumqx*sumqx > best*sumq2) {
best_d = sumqx/sumq2; best = best_d*sumqx;
}
else if (iter > 8) break;
}
scales[ib] = d;
if (is_shifted) extra |= (1 << ib);
float abs_scale = fabsf(scales[ib]);
max_abs_scale = MAX(max_abs_scale, abs_scale);
}
if (!max_abs_scale) continue;
float d = max_abs_scale/31;
y[ibl].extra = extra;
float id = 1/d;
float sumqx = 0, sumq2 = 0;
for (int ib = 0; ib < QK_K/16; ++ib) {
int ls = nearest_int(0.5f*(id*fabsf(scales[ib])-1));
ls = MAX(0, MIN(15, ls));
y[ibl].scales_l[ib/2] |= (ls << 4*(ib%2));
if (scales[ib] < 0) y[ibl].scales_h |= (1 << ib);
ls = (2*ls + 1) * (scales[ib] < 0 ? -1 : 1);
float dl = d * ls;
if (dl) {
const int8_t * block_values = y[ibl].extra & (1 << ib) ? shifted_values : iq3nl_values;
const float * xb = xbl + 16*ib;
if (quant_weights) {
const float * qw = quant_weights + ibl*QK_K + ib*16;
for (int j = 0; j < 16; ++j) weight[j] = qw[j] * sqrtf(sigma2 + xb[j]*xb[j]);
} else {
for (int j = 0; j < 16; ++j) weight[j] = 0.25f*sigma2 + xb[j]*xb[j];
}
float idl = 1/dl;
int ib32 = ib/2;
int offset = 16*(ib%2);
uint8_t * qs = y[ibl].qs + 32*(ib32/4) + offset;
uint8_t * qh = y[ibl].qh + 32*(ib32/8) + offset;
for (int j = 0; j < 16; ++j) {
const float al = idl*xb[j];
int ibest = best_index_iq3nl(block_values, al);
qs[j] |= ((ibest & 3) << 2*(ib32%4));
qh[j] |= ((ibest >> 2) << (ib32%8));
float w = weight[j];
float q = block_values[ibest]*ls;
sumqx += w*q*xb[j];
sumq2 += w*q*q;
}
}
}
y[ibl].d = GGML_FP32_TO_FP16(1.01f*(sumq2 > 0 ? sumqx/sumq2 : d));
}
}
}
void quantize_row_iq3_k_ref(const float * x, block_iq3_k * y, int64_t k) {
assert(k % QK_K == 0);
quantize_iq3_k(x, (void *)y, 1, k, nullptr);
}
void quantize_row_iq3_k(const float * x, void * vy, int64_t k) {
assert(k % QK_K == 0);
block_iq3_k * y = (block_iq3_k *)vy;
quantize_row_iq3_k_ref(x, y, k);
}
size_t quantize_iq3_k(const float * src, void * dst, int64_t nrows, int64_t n_per_row, const float * imatrix) {
GGML_ASSERT(n_per_row%QK_K == 0);
int nblock = n_per_row/QK_K;
char * qrow = (char *)dst;
for (int64_t row = 0; row < nrows; ++row) {
quantize_row_iq3_k_impl(src, (void *)qrow, n_per_row, imatrix);
src += n_per_row;
qrow += nblock*sizeof(block_iq3_k);
}
return nrows * nblock * sizeof(block_iq3_k);
}
void dequantize_row_iq3_k(const block_iq3_k * x, float * 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 uint8_t * qs = x[i].qs;
const uint8_t * qh = x[i].qh;
uint16_t sh = x[i].scales_h;
uint16_t extra = x[i].extra;
for (int ib32 = 0; ib32 < QK_K/32; ++ib32) {
float dl1 = d * ((2*(x[i].scales_l[ib32] & 0xf) + 1) * ((sh & 1) ? -1 : 1));
float dl2 = d * ((2*(x[i].scales_l[ib32] >> 4) + 1) * ((sh & 2) ? -1 : 1));
sh >>= 2;
const int8_t * values1 = extra & 1 ? iq3nl_values + 8 : iq3nl_values;
const int8_t * values2 = extra & 2 ? iq3nl_values + 8 : iq3nl_values;
extra >>= 2;
int shift_l = 2*(ib32%4);
int shift_h = ib32%8;
for (int j = 0; j < 16; ++j) {
y[j+ 0] = dl1 * values1[((qs[j+ 0] >> shift_l) & 3) | (((qh[j+ 0] >> shift_h) & 1) << 2)];
y[j+16] = dl2 * values2[((qs[j+16] >> shift_l) & 3) | (((qh[j+16] >> shift_h) & 1) << 2)];
}
y += 32;
if (shift_l == 6) qs += 32;
}
}
}
void vec_dot_iq3_k_q8_k(int n, float * s, size_t bs, const void * vx, size_t bx, const void * vy, size_t by, int nrc) {
assert(n % QK_K == 0);
assert(nrc == 1);
GGML_UNUSED(nrc);
GGML_UNUSED(bx);
GGML_UNUSED(by);
GGML_UNUSED(bs);
#if GGML_USE_IQK_MULMAT
if (iqk_mul_mat(1, 1, n, GGML_TYPE_IQ3_K, vx, 0, GGML_TYPE_Q8_K, vy, 0, s, 0, 0, 1)) {
return;
}
#endif
GGML_ABORT("not implemented");
}
//
// ============================================== iq4_K
//
void dequantize_row_iq4_k(const block_iq4_k * x, float * 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 * qs = x[i].qs;
const float d = GGML_FP16_TO_FP32(x[i].d);
uint16_t extra = x[i].extra;
for (int ib = 0; ib < QK_K/32; ++ib) {
const uint8_t sh = x[i].scales_h[ib/2] >> 4*(ib%2);
const float dl1 = d * (((x[i].scales_l[ib] & 0xf) | ((sh << 4) & 0x30)) - 32);
const float dl2 = d * (((x[i].scales_l[ib] >> 4) | ((sh << 2) & 0x30)) - 32);
const int8_t * values1 = extra & 1 ? iq4k_values + 16 : iq4k_values;
const int8_t * values2 = extra & 2 ? iq4k_values + 16 : iq4k_values;
extra >>= 2;
for (int j = 0; j < 16; ++j) {
y[j+ 0] = dl1 * values1[qs[j] & 0xf];
y[j+16] = dl2 * values2[qs[j] >> 4];
}
y += 32;
qs += 16;
}
}
}
void vec_dot_iq4_k_q8_k(int n, float * s, size_t bs, const void * vx, size_t bx, const void * vy, size_t by, int nrc) {
assert(n % QK_K == 0);
assert(nrc == 1);
GGML_UNUSED(nrc);
GGML_UNUSED(bx);
GGML_UNUSED(by);
GGML_UNUSED(bs);
#if GGML_USE_IQK_MULMAT
if (iqk_mul_mat(1, 1, n, GGML_TYPE_IQ4_K, vx, 0, GGML_TYPE_Q8_K, vy, 0, s, 0, 0, 1)) {
return;
}
#endif
const int nb = n / QK_K;
const block_iq4_k * x = (const block_iq4_k *)vx;
const block_q8_K * y = (const block_q8_K *)vy;
float sumf = 0;
for (int ibl = 0; ibl < nb; ++ibl) {
const float d4d8 = GGML_FP16_TO_FP32(x[ibl].d) * y[ibl].d;
uint16_t extra = x[ibl].extra;
uint32_t h = *((const uint32_t *)x[ibl].scales_h);
const uint8_t * qs = x[ibl].qs;
const int8_t * q8 = y[ibl].qs;
int32_t sum = 0;
for (int ib = 0; ib < QK_K/32; ++ib) {
const int ls1 = ((x[ibl].scales_l[ib] & 0xf) | ((h << 4) & 0x30)) - 32;
const int ls2 = ((x[ibl].scales_l[ib] >> 4) | ((h << 2) & 0x30)) - 32;
h >>= 4;
const int8_t * values1 = iq4k_values + 16*(extra & 1);
const int8_t * values2 = iq4k_values + 8*(extra & 2);
extra >>= 2;
int sumi1 = 0, sumi2 = 0;
for (int j = 0; j < 16; ++j) {
sumi1 += q8[j+ 0] * values1[qs[j] & 0xf];
sumi2 += q8[j+16] * values2[qs[j] >> 4];
}
sum += ls1*sumi1 + ls2*sumi2;
qs += 16;
q8 += 32;
}
sumf += d4d8 * sum;
}
*s = sumf;
}
namespace {
const int8_t iq4nl_index[241] = {
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 16, 16, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 17, 17, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 18, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
3, 3, 3, 3, 3, 3, 19, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 20, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5,
5, 5, 21, 21, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 22, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 23, 23, 8, 8, 8, 8,
8, 8, 8, 8, 8, 8, 24, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 25, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 26, 26,
11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 27, 27, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 28, 13, 13, 13,
13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 29, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14,
14, 14, 14, 14, 30, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15
};
inline int best_index_iq4nl(const int8_t * values, float x) {
int ix = (int)x - values[0];
if (ix < 0 || ix >= 241) return ix < 0 ? 0 : 15;
ix = iq4nl_index[ix];
return ix < 16 ? ix : x - values[ix-16] < values[ix-15] - x ? ix-16 : ix-15;
}
static void quantize_row_iq4_k_impl_bs16(const int super_block_size, const int block_size, const float * x,
block_iq4_k * y,
float * scales, float * weight, uint8_t * L,
const int8_t * values,
const float * quant_weights,
const int ntry) {
GGML_ASSERT(super_block_size == 256 && block_size == 16);
float sigma2 = 0;
for (int j = 0; j < super_block_size; ++j) sigma2 += x[j]*x[j];
sigma2 *= 2.f/super_block_size;
memset(y, 0, sizeof(block_iq4_k));
y->d = GGML_FP32_TO_FP16(0.f);
uint16_t * scales_h = (uint16_t *)y->scales_h;
const int8_t * shifted_values = values + 16;
float max_scale = 0, amax_scale = 0;
uint16_t extra = 0;
for (int ib = 0; ib < super_block_size/block_size; ++ib) {
const float * xb = x + 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) {
scales[ib] = 0;
continue;
}
float d = ntry > 0 ? -max/values[0] : max/values[0];
float id = 1/d;
float sumqx_p = 0, sumq2_p = 0;
float sumqx_m = 0, sumq2_m = 0;
for (int j = 0; j < block_size; ++j) {
float w = weight[j];
float al = id*xb[j];
int l = best_index_iq4nl(values, al);
float q = values[l];
sumqx_p += w*q*xb[j];
sumq2_p += w*q*q;
l = best_index_iq4nl(values, -al);
q = values[l];
sumqx_m += w*q*xb[j];
sumq2_m += w*q*q;
}
d = sumqx_p/sumq2_p;
bool is_shifted = false;
float best = d*sumqx_p;
if (sumq2_m > 0 && sumqx_m*sumqx_m > best*sumq2_m) {
d = sumqx_m/sumq2_m; best = d*sumqx_m;
}
for (int itry = -ntry; itry <= ntry; ++itry) {
id = (itry + values[0])/max;
sumqx_p = sumq2_p = 0;
sumqx_m = sumq2_m = 0;
for (int j = 0; j < block_size; ++j) {
float w = weight[j];
float al = id*xb[j];
int l = best_index_iq4nl(values, al);
float q = values[l];
sumqx_p += w*q*xb[j];
sumq2_p += w*q*q;
l = best_index_iq4nl(values, -al);
q = values[l];
sumqx_m += w*q*xb[j];
sumq2_m += w*q*q;
}
if (sumq2_p > 0 && sumqx_p*sumqx_p > best*sumq2_p) {
d = sumqx_p/sumq2_p; best = d * sumqx_p; is_shifted = false;
}
if (sumq2_m > 0 && sumqx_m*sumqx_m > best*sumq2_m) {
d = sumqx_m/sumq2_m; best = d * sumqx_m; is_shifted = false;
}
id = (itry + shifted_values[0])/max;
sumqx_p = sumq2_p = 0;
sumqx_m = sumq2_m = 0;
for (int j = 0; j < block_size; ++j) {
float w = weight[j];
float al = id*xb[j];
int l = best_index_iq4nl(shifted_values, al);
float q = shifted_values[l];
sumqx_p += w*q*xb[j];
sumq2_p += w*q*q;
l = best_index_iq4nl(shifted_values, -al);
q = shifted_values[l];
sumqx_m += w*q*xb[j];
sumq2_m += w*q*q;
}
if (sumq2_p > 0 && sumqx_p*sumqx_p > best*sumq2_p) {
d = sumqx_p/sumq2_p; best = d * sumqx_p; is_shifted = true;
}
if (sumq2_m > 0 && sumqx_m*sumqx_m > best*sumq2_m) {
d = sumqx_m/sumq2_m; best = d * sumqx_m; is_shifted = true;
}
}
if (is_shifted) extra |= (1 << ib);
scales[ib] = d;
float abs_d = fabsf(d);
if (abs_d > amax_scale) {
amax_scale = abs_d; max_scale = d;
}
}
float d = -max_scale/32;
y->d = GGML_FP32_TO_FP16(d);
y->extra = extra;
float id = d ? 1/d : 0.f;
float sumqx = 0, sumq2 = 0;
for (int ib = 0; ib < super_block_size/block_size; ++ib) {
const int8_t * block_values = extra & (1 << ib) ? shifted_values : values;
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;
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];
}
for (int j = 0; j < block_size; ++j) {
Lb[j] = best_index_iq4nl(block_values, idl*xb[j]);
float w = weight[j];
float q = block_values[Lb[j]]*l;
sumqx += w*q*xb[j];
sumq2 += w*q*q;
}
l += 32;
uint8_t l_l = l & 0xf;
uint8_t l_h = l >> 4;
if (ib%2 == 0) y->scales_l[ib/2] = l_l;
else y->scales_l[ib/2] |= (l_l << 4);
scales_h[ib/8] |= (l_h << 2*(ib%8));
}
if (sumq2 > 0) y->d = GGML_FP32_TO_FP16(sumqx/sumq2);
for (int i = 0; i < super_block_size/32; ++i) {
for (int j = 0; j < 16; ++j) {
y->qs[16*i + j] = L[32*i + j] | (L[32*i + 16 + j] << 4);
}
}
}
}
void quantize_row_iq4_k_ref(const float * x, block_iq4_k * y, int64_t k) {
assert(k % QK_K == 0);
quantize_iq4_k(x, (void *)y, 1, k, nullptr);
}
void quantize_row_iq4_k(const float * x, void * vy, int64_t k) {
assert(k % QK_K == 0);
block_iq4_k * y = (block_iq4_k *)vy;
quantize_row_iq4_k_ref(x, y, k);
}
size_t quantize_iq4_k(const float * src, void * dst, int64_t nrows, int64_t n_per_row, const float * imatrix) {
GGML_ASSERT(n_per_row%QK_K == 0);
int nblock = n_per_row/QK_K;
char * qrow = (char *)dst;
uint8_t L[QK_K];
float weight[16];
float scales[QK_K/16];
for (int64_t row = 0; row < nrows; ++row) {
block_iq4_k * iq4 = (block_iq4_k *)qrow;
for (int ibl = 0; ibl < nblock; ++ibl) {
const float * qw = imatrix ? imatrix + QK_K*ibl : NULL;
quantize_row_iq4_k_impl_bs16(QK_K, 16, src + QK_K*ibl, iq4 + ibl,
scales, weight, L, iq4k_values, qw, 7);
}
src += n_per_row;
qrow += nblock*sizeof(block_iq4_k);
}
return nrows * nblock * sizeof(block_iq4_k);
}
//
// ============================================== iq5_K
//
void dequantize_row_iq5_k(const block_iq5_k * x, float * 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 uint8_t * qs = x[i].qs;
const uint8_t * qh = x[i].qh;
const uint8_t * sl = x[i].scales_l;
const uint8_t * sh = x[i].scales_h;
uint16_t extra = x[i].extra;
int shift = 0;
for (int ib64 = 0; ib64 < QK_K/64; ++ib64) {
float dl1 = d * (((sl[2*ib64+0] & 0xf) | ((sh[ib64] << 4) & 0x30)) - 32);
float dl2 = d * (((sl[2*ib64+0] >> 4) | ((sh[ib64] << 2) & 0x30)) - 32);
float dl3 = d * (((sl[2*ib64+1] & 0xf) | ((sh[ib64] >> 0) & 0x30)) - 32);
float dl4 = d * (((sl[2*ib64+1] >> 4) | ((sh[ib64] >> 2) & 0x30)) - 32);
const int8_t * values1 = iq5nl_values + ((extra & 1) << 5);
const int8_t * values2 = iq5nl_values + ((extra & 2) << 4);
const int8_t * values3 = iq5nl_values + ((extra & 4) << 3);
const int8_t * values4 = iq5nl_values + ((extra & 8) << 2);
for (int j = 0; j < 16; ++j) {
y[j+ 0] = dl1 * values1[(qs[j+ 0] & 0xf) | (((qh[j+ 0] >> shift) & 1) << 4)];
y[j+16] = dl2 * values2[(qs[j+16] & 0xf) | (((qh[j+16] >> shift) & 1) << 4)];
y[j+32] = dl3 * values3[(qs[j+ 0] >> 4) | (((qh[j+ 0] >> shift) & 2) << 3)];
y[j+48] = dl4 * values4[(qs[j+16] >> 4) | (((qh[j+16] >> shift) & 2) << 3)];
}
y += 64;
qs += 32;
extra >>= 4;
shift += 2;
if (shift == 8) { qh += 32; shift = 0; }
}
}
}
void vec_dot_iq5_k_q8_k(int n, float * s, size_t bs, const void * vx, size_t bx, const void * vy, size_t by, int nrc) {
assert(n % QK_K == 0);
assert(nrc == 1);
GGML_UNUSED(nrc);
GGML_UNUSED(bx);
GGML_UNUSED(by);
GGML_UNUSED(bs);
#if GGML_USE_IQK_MULMAT
if (iqk_mul_mat(1, 1, n, GGML_TYPE_IQ5_K, vx, 0, GGML_TYPE_Q8_K, vy, 0, s, 0, 0, 1)) {
return;
}
#endif
const int nb = n / QK_K;
const block_iq5_k * x = (const block_iq5_k *)vx;
const block_q8_K * y = (const block_q8_K *)vy;
float sumf = 0;
for (int i = 0; i < nb; i++) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const uint8_t * qs = x[i].qs;
const uint8_t * qh = x[i].qh;
const uint8_t * sl = x[i].scales_l;
const uint8_t * sh = x[i].scales_h;
const int8_t * q8 = y[i].qs;
uint16_t extra = x[i].extra;
int shift = 0;
int sumb = 0;
for (int ib64 = 0; ib64 < QK_K/64; ++ib64) {
int dl1 = (((sl[2*ib64+0] & 0xf) | ((sh[ib64] << 4) & 0x30)) - 32);
int dl2 = (((sl[2*ib64+0] >> 4) | ((sh[ib64] << 2) & 0x30)) - 32);
int dl3 = (((sl[2*ib64+1] & 0xf) | ((sh[ib64] >> 0) & 0x30)) - 32);
int dl4 = (((sl[2*ib64+1] >> 4) | ((sh[ib64] >> 2) & 0x30)) - 32);
const int8_t * values1 = iq5nl_values + ((extra & 1) << 5);
const int8_t * values2 = iq5nl_values + ((extra & 2) << 4);
const int8_t * values3 = iq5nl_values + ((extra & 4) << 3);
const int8_t * values4 = iq5nl_values + ((extra & 8) << 2);
int sumi1 = 0, sumi2 = 0, sumi3 = 0, sumi4 = 0;
for (int j = 0; j < 16; ++j) {
sumi1 += q8[j+ 0] * values1[(qs[j+ 0] & 0xf) | (((qh[j+ 0] >> shift) & 1) << 4)];
sumi2 += q8[j+16] * values2[(qs[j+16] & 0xf) | (((qh[j+16] >> shift) & 1) << 4)];
sumi3 += q8[j+32] * values3[(qs[j+ 0] >> 4) | (((qh[j+ 0] >> shift) & 2) << 3)];
sumi4 += q8[j+48] * values4[(qs[j+16] >> 4) | (((qh[j+16] >> shift) & 2) << 3)];
}
sumb += dl1 * sumi1 + dl2 * sumi2 + dl3 * sumi3 + dl4 * sumi4;
q8 += 64;
qs += 32;
extra >>= 4;
shift += 2;
}
sumf += d * sumb;
}
*s = sumf;
}
namespace {
const int8_t iq5nl_index[248] = {
0, 0, 0, 0, 0, 0, 32, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 33, 33, 2, 2, 2, 2, 2, 2, 2, 2, 2, 34, 34, 3, 3,
3, 3, 3, 3, 3, 3, 35, 35, 4, 4, 4, 4, 4, 4, 4, 36, 36, 5, 5, 5, 5, 5, 5, 5, 37, 37, 6, 6, 6, 6, 6, 6,
6, 38, 7, 7, 7, 7, 7, 7, 39, 39, 8, 8, 8, 8, 8, 40, 40, 9, 9, 9, 9, 9, 41, 41, 10, 10, 10, 10, 10, 42, 11, 11,
11, 11, 11, 43, 12, 12, 12, 12, 12, 44, 13, 13, 13, 13, 13, 45, 14, 14, 14, 14, 14, 46, 15, 15, 15, 15, 47, 47, 16, 16, 16, 16,
48, 17, 17, 17, 17, 17, 49, 18, 18, 18, 18, 18, 50, 19, 19, 19, 19, 19, 51, 20, 20, 20, 20, 20, 52, 21, 21, 21, 21, 21, 53, 53,
22, 22, 22, 22, 22, 54, 54, 23, 23, 23, 23, 23, 23, 55, 24, 24, 24, 24, 24, 24, 24, 56, 25, 25, 25, 25, 25, 25, 25, 57, 57, 26,
26, 26, 26, 26, 26, 26, 58, 58, 27, 27, 27, 27, 27, 27, 27, 27, 59, 28, 28, 28, 28, 28, 28, 28, 28, 28, 60, 29, 29, 29, 29, 29,
29, 29, 29, 29, 29, 61, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 62, 31, 31, 31, 31, 31, 31
};
inline int best_index_iq5nl(const int8_t * values, float x) {
int ix = (int)x - values[0];
if (ix < 0 || ix >= 247) return ix < 0 ? 0 : 31;
ix = iq5nl_index[ix];
return ix < 32 ? ix : x - values[ix-32] < values[ix-31] - x ? ix-32 : ix-31;
}
void quantize_row_iq5_k_impl(const float * x, void * vy, int n_per_row, const float * quant_weights) {
const int ntry = 5;
const float step = 1.f;
block_iq5_k * y = (block_iq5_k *)vy;
float scales[QK_K/16];
float weight[16];
const int8_t * shifted_values = iq5nl_values + 32;
for (int ibl = 0; ibl < n_per_row/QK_K; ++ibl) {
memset(&y[ibl], 0, sizeof(block_iq5_k));
y[ibl].d = GGML_FP32_TO_FP16(0.f);
const float * xbl = x + ibl*QK_K;
float sumx2 = 0;
for (int j = 0; j < QK_K; ++j) sumx2 += xbl[j]*xbl[j];
const float sigma2 = 2*sumx2/QK_K;
float max_scale = 0, max_abs_scale = 0;
uint16_t extra = 0;
for (int ib = 0; ib < QK_K/16; ++ib) {
const float * xb = xbl + 16*ib;
if (quant_weights) {
const float * qw = quant_weights + ibl*QK_K + ib*16;
for (int j = 0; j < 16; ++j) weight[j] = qw[j] * sqrtf(sigma2 + xb[j]*xb[j]);
} else {
for (int j = 0; j < 16; ++j) weight[j] = 0.25f*sigma2 + xb[j]*xb[j];
}
float amax = 0, max = 0;
for (int j = 0; j < 16; ++j) {
float ax = fabsf(xb[j]);
if (ax > amax) {
amax = ax; max = xb[j];
}
}
if (!amax) {
scales[ib] = 0;
continue;
}
float d = ntry > 0 ? -max/iq5nl_values[0] : max/iq5nl_values[0];
float id = 1/d;
float sumqx_p = 0, sumq2_p = 0;
float sumqx_m = 0, sumq2_m = 0;
for (int j = 0; j < 16; ++j) {
float w = weight[j];
float al = id*xb[j];
int l = best_index_iq5nl(iq5nl_values, al);
float q = iq5nl_values[l];
sumqx_p += w*q*xb[j];
sumq2_p += w*q*q;
l = best_index_iq5nl(iq5nl_values, -al);
q = iq5nl_values[l];
sumqx_m += w*q*xb[j];
sumq2_m += w*q*q;
}
d = sumqx_p/sumq2_p;
float best = d*sumqx_p;
if (sumq2_m > 0 && sumqx_m*sumqx_m > best*sumq2_m) {
d = sumqx_m/sumq2_m; best = d*sumqx_m;
}
bool is_shifted = false;
for (int itry = -ntry; itry <= ntry; ++itry) {
id = (itry*step + iq5nl_values[0])/max;
sumqx_p = sumq2_p = 0;
sumqx_m = sumq2_m = 0;
for (int j = 0; j < 16; ++j) {
float w = weight[j];
float al = id*xb[j];
int l = best_index_iq5nl(iq5nl_values, al);
float q = iq5nl_values[l];
sumqx_p += w*q*xb[j];
sumq2_p += w*q*q;
l = best_index_iq5nl(iq5nl_values, -al);
q = iq5nl_values[l];
sumqx_m += w*q*xb[j];
sumq2_m += w*q*q;
}
if (sumq2_p > 0 && sumqx_p*sumqx_p > best*sumq2_p) {
d = sumqx_p/sumq2_p; best = d * sumqx_p; is_shifted = false;
}
if (sumq2_m > 0 && sumqx_m*sumqx_m > best*sumq2_m) {
d = sumqx_m/sumq2_m; best = d * sumqx_m; is_shifted = false;
}
id = (itry*step + shifted_values[0])/max;
sumqx_p = sumq2_p = 0;
sumqx_m = sumq2_m = 0;
for (int j = 0; j < 16; ++j) {
float w = weight[j];
float al = id*xb[j];
int l = best_index_iq5nl(shifted_values, al);
float q = shifted_values[l];
sumqx_p += w*q*xb[j];
sumq2_p += w*q*q;
l = best_index_iq5nl(shifted_values, -al);
q = shifted_values[l];
sumqx_m += w*q*xb[j];
sumq2_m += w*q*q;
}
if (sumq2_p > 0 && sumqx_p*sumqx_p > best*sumq2_p) {
d = sumqx_p/sumq2_p; best = d * sumqx_p; is_shifted = true;
}
if (sumq2_m > 0 && sumqx_m*sumqx_m > best*sumq2_m) {
d = sumqx_m/sumq2_m; best = d * sumqx_m; is_shifted = true;
}
}
if (d) {
const int8_t * block_values = is_shifted ? shifted_values : iq5nl_values;
float sumqx = 0, sumq2 = 0;
id = 1/d;
for (int j = 0; j < 16; ++j) {
float w = weight[j];
float al = id*xb[j];
int l = best_index_iq5nl(block_values, al);
float q = block_values[l];
sumqx += w*q*xb[j];
sumq2 += w*q*q;
}
if (sumq2 > 0) d = sumqx/sumq2;
}
scales[ib] = d;
if (is_shifted) extra |= (1 << ib);
float abs_scale = fabsf(scales[ib]);
if (abs_scale > max_abs_scale) {
max_abs_scale = abs_scale; max_scale = scales[ib];
}
}
if (!max_abs_scale) continue;
float d = -max_scale/32;
y[ibl].d = GGML_FP32_TO_FP16(d);
y[ibl].extra = extra;
float id = 1/d;
float sumqx = 0, sumq2 = 0;
for (int ib = 0; ib < QK_K/16; ++ib) {
int ls = nearest_int(id*scales[ib]);
ls = MAX(-32, MIN(31, ls));
int uls = ls + 32;
y[ibl].scales_l[ib/2] |= ((uls & 0xf) << 4*(ib%2));
y[ibl].scales_h[ib/4] |= ((uls >> 4) << 2*(ib%4));
float dl = d * ls;
if (dl) {
const int8_t * block_values = y[ibl].extra & (1 << ib) ? shifted_values : iq5nl_values;
const float * xb = xbl + 16*ib;
if (quant_weights) {
const float * qw = quant_weights + ibl*QK_K + ib*16;
for (int j = 0; j < 16; ++j) weight[j] = qw[j] * sqrtf(sigma2 + xb[j]*xb[j]);
} else {
for (int j = 0; j < 16; ++j) weight[j] = 0.25f*sigma2 + xb[j]*xb[j];
}
float idl = 1/dl;
int ib32 = ib/2;
int offset = 16*(ib%2);
uint8_t * qs = y[ibl].qs + 32*(ib32/2) + offset;
uint8_t * qh = y[ibl].qh + 32*(ib32/8) + offset;
for (int j = 0; j < 16; ++j) {
const float al = idl*xb[j];
int ibest = best_index_iq5nl(block_values, al);
qs[j] |= ((ibest & 0xf) << 4*(ib32%2));
qh[j] |= ((ibest >> 4) << (ib32%8));
float w = weight[j];
float q = block_values[ibest]*ls;
sumqx += w*q*xb[j];
sumq2 += w*q*q;
}
}
}
if (sumq2 > 0) y[ibl].d = GGML_FP32_TO_FP16(sumqx/sumq2);
}
}
}
void quantize_row_iq5_k_ref(const float * x, block_iq5_k * y, int64_t k) {
assert(k % QK_K == 0);
quantize_iq5_k(x, (void *)y, 1, k, nullptr);
}
void quantize_row_iq5_k(const float * x, void * vy, int64_t k) {
assert(k % QK_K == 0);
block_iq5_k * y = (block_iq5_k *)vy;
quantize_row_iq5_k_ref(x, y, k);
}
size_t quantize_iq5_k(const float * src, void * dst, int64_t nrows, int64_t n_per_row, const float * imatrix) {
GGML_ASSERT(n_per_row%QK_K == 0);
int nblock = n_per_row/QK_K;
char * qrow = (char *)dst;
for (int64_t row = 0; row < nrows; ++row) {
quantize_row_iq5_k_impl(src, (void *)qrow, n_per_row, imatrix);
src += n_per_row;
qrow += nblock*sizeof(block_iq5_k);
}
return nrows * nblock * sizeof(block_iq5_k);
}
//
// ============================================== iq6_K
//
#define A_IQ6K -127.f
#define B_IQ6K 6.2568f
#define C_IQ6K 0.11218f
#define D_IQ6K 0.0011972f
#define S_IQ6K 1.f
void dequantize_row_iq6_k(const block_iq6_k * x, float * 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 uint8_t * qs = x[i].qs;
const uint8_t * qh = x[i].qh;
const int8_t * sl = x[i].scales;
uint16_t extra = x[i].extra;
int shift = 0;
for (int ib64 = 0; ib64 < QK_K/64; ++ib64) {
float dl1 = d * sl[4*ib64 + 0];
float dl2 = d * sl[4*ib64 + 1];
float dl3 = d * sl[4*ib64 + 2];
float dl4 = d * sl[4*ib64 + 3];
float m1 = extra & 1 ? S_IQ6K : 0;
float m2 = extra & 2 ? S_IQ6K : 0;
float m3 = extra & 4 ? S_IQ6K : 0;
float m4 = extra & 8 ? S_IQ6K : 0;
for (int j = 0; j < 16; ++j) {
float q1 = ((qs[j+ 0] & 0xf) | (((qh[j+ 0] >> shift) & 0x03) << 4));
float q2 = ((qs[j+16] & 0xf) | (((qh[j+16] >> shift) & 0x03) << 4));
float q3 = ((qs[j+ 0] >> 4) | (((qh[j+ 0] >> shift) & 0x0c) << 2));
float q4 = ((qs[j+16] >> 4) | (((qh[j+16] >> shift) & 0x0c) << 2));
y[j+ 0] = dl1 * (A_IQ6K + q1*(B_IQ6K + q1*(-C_IQ6K + q1*D_IQ6K)) + m1);
y[j+16] = dl2 * (A_IQ6K + q2*(B_IQ6K + q2*(-C_IQ6K + q2*D_IQ6K)) + m2);
y[j+32] = dl3 * (A_IQ6K + q3*(B_IQ6K + q3*(-C_IQ6K + q3*D_IQ6K)) + m3);
y[j+48] = dl4 * (A_IQ6K + q4*(B_IQ6K + q4*(-C_IQ6K + q4*D_IQ6K)) + m4);
}
y += 64;
qs += 32;
extra >>= 4;
shift += 4;
if (shift == 8) { qh += 32; shift = 0; }
}
}
}
void vec_dot_iq6_k_q8_k(int n, float * s, size_t bs, const void * vx, size_t bx, const void * vy, size_t by, int nrc) {
assert(n % QK_K == 0);
assert(nrc == 1);
GGML_UNUSED(nrc);
GGML_UNUSED(bx);
GGML_UNUSED(by);
GGML_UNUSED(bs);
#if GGML_USE_IQK_MULMAT
if (iqk_mul_mat(1, 1, n, GGML_TYPE_IQ6_K, vx, 0, GGML_TYPE_Q8_K, vy, 0, s, 0, 0, 1)) {
return;
}
#endif
GGML_ABORT("not implemented");
// TODO
//const int nb = n / QK_K;
//const block_iq5_k * x = (const block_iq5_k *)vx;
//const block_q8_K * y = (const block_q8_K *)vy;
//float sumf = 0;
//for (int i = 0; i < nb; i++) {
// const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
// const uint8_t * qs = x[i].qs;
// const uint8_t * qh = x[i].qh;
// const uint8_t * sl = x[i].scales_l;
// const uint8_t * sh = x[i].scales_h;
// const int8_t * q8 = y[i].qs;
// uint16_t extra = x[i].extra;
// int shift = 0;
// int sumb = 0;
// for (int ib64 = 0; ib64 < QK_K/64; ++ib64) {
// int dl1 = (((sl[2*ib64+0] & 0xf) | ((sh[ib64] << 4) & 0x30)) - 32);
// int dl2 = (((sl[2*ib64+0] >> 4) | ((sh[ib64] << 2) & 0x30)) - 32);
// int dl3 = (((sl[2*ib64+1] & 0xf) | ((sh[ib64] >> 0) & 0x30)) - 32);
// int dl4 = (((sl[2*ib64+1] >> 4) | ((sh[ib64] >> 2) & 0x30)) - 32);
// const int8_t * values1 = iq5nl_values + ((extra & 1) << 5);
// const int8_t * values2 = iq5nl_values + ((extra & 2) << 4);
// const int8_t * values3 = iq5nl_values + ((extra & 4) << 3);
// const int8_t * values4 = iq5nl_values + ((extra & 8) << 2);
// int sumi1 = 0, sumi2 = 0, sumi3 = 0, sumi4 = 0;
// for (int j = 0; j < 16; ++j) {
// sumi1 += q8[j+ 0] * values1[(qs[j+ 0] & 0xf) | (((qh[j+ 0] >> shift) & 1) << 4)];
// sumi2 += q8[j+16] * values2[(qs[j+16] & 0xf) | (((qh[j+16] >> shift) & 1) << 4)];
// sumi3 += q8[j+32] * values3[(qs[j+ 0] >> 4) | (((qh[j+ 0] >> shift) & 2) << 3)];
// sumi4 += q8[j+48] * values4[(qs[j+16] >> 4) | (((qh[j+16] >> shift) & 2) << 3)];
// }
// sumb += dl1 * sumi1 + dl2 * sumi2 + dl3 * sumi3 + dl4 * sumi4;
// q8 += 64;
// qs += 32;
// extra >>= 4;
// shift += 2;
// }
// sumf += d * sumb;
//}
//*s = sumf;
}
namespace {
inline int best_index(int n, const float * 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;
}
uint8_t iq6nl_index[249] = {
0, 0, 0, 64, 1, 1, 1, 1, 1, 65, 2, 2, 2, 2, 2, 66, 3, 3, 3, 3, 67, 67, 4, 4, 4, 4, 68, 5, 5, 5, 5, 69,
69, 6, 6, 6, 70, 70, 7, 7, 7, 71, 8, 8, 8, 72, 72, 9, 9, 9, 73, 73, 10, 10, 10, 74, 11, 11, 11, 75, 12, 12, 12, 76,
13, 13, 13, 77, 14, 14, 14, 78, 15, 15, 79, 79, 16, 16, 80, 17, 17, 81, 81, 18, 18, 82, 19, 19, 83, 83, 20, 84, 84, 21, 85, 85,
22, 86, 86, 23, 87, 87, 24, 88, 88, 25, 89, 89, 26, 90, 90, 27, 91, 91, 28, 92, 29, 93, 93, 30, 94, 94, 31, 95, 95, 32, 96, 33,
97, 97, 34, 98, 98, 35, 99, 99, 36, 100, 100, 37, 101, 38, 102, 102, 39, 103, 103, 40, 104, 104, 41, 41, 105, 42, 42, 106, 106, 43, 107, 107,
44, 108, 108, 45, 45, 109, 46, 46, 46, 110, 47, 47, 111, 111, 48, 48, 112, 49, 49, 49, 113, 50, 50, 50, 114, 51, 51, 51, 115, 52, 52, 52,
116, 116, 53, 53, 53, 117, 54, 54, 54, 118, 118, 55, 55, 55, 119, 119, 56, 56, 56, 120, 120, 57, 57, 57, 121, 121, 58, 58, 58, 58, 122, 59,
59, 59, 59, 123, 123, 60, 60, 60, 60, 124, 61, 61, 61, 61, 61, 125, 62, 62, 62, 62, 62, 126, 63, 63, 63,
};
inline int best_index_iq6nl(const float * values, float x) {
int ix = (int)(x - values[0]);
if (ix < 0 || ix >= 249) return ix < 0 ? 0 : 63;
ix = iq6nl_index[ix];
return ix < 64 ? ix : x - values[ix-64] < values[ix-63] - x ? ix-64 : ix-63;
//if (x <= val[0]) return 0;
//if (x >= val[63]) return 63;
//int index = iq6nl_index[int(x - val[0])];
//return index < 64 ? index : x - val[index-64] < val[index-63] - x ? index - 64 : index - 63;
}
void quantize_row_iq6_k_impl(const float * x, void * vy, int n_per_row, const float * quant_weights, const float * values, const float * shifted_values) {
const int ntry = 5;
const float step = 1.f;
block_iq6_k * y = (block_iq6_k *)vy;
float scales[QK_K/16];
float weight[16];
for (int ibl = 0; ibl < n_per_row/QK_K; ++ibl) {
memset(&y[ibl], 0, sizeof(block_iq6_k));
y[ibl].d = GGML_FP32_TO_FP16(0.f);
const float * xbl = x + ibl*QK_K;
float sumx2 = 0;
for (int j = 0; j < QK_K; ++j) sumx2 += xbl[j]*xbl[j];
const float sigma2 = 2*sumx2/QK_K;
float max_scale = 0, max_abs_scale = 0;
uint16_t extra = 0;
for (int ib = 0; ib < QK_K/16; ++ib) {
const float * xb = xbl + 16*ib;
if (quant_weights) {
const float * qw = quant_weights + ibl*QK_K + ib*16;
for (int j = 0; j < 16; ++j) weight[j] = qw[j] * sqrtf(sigma2 + xb[j]*xb[j]);
} else {
for (int j = 0; j < 16; ++j) weight[j] = 0.25f*sigma2 + xb[j]*xb[j];
}
float amax = 0, max = 0;
for (int j = 0; j < 16; ++j) {
float ax = fabsf(xb[j]);
if (ax > amax) {
amax = ax; max = xb[j];
}
}
if (!amax) {
scales[ib] = 0;
continue;
}
float d = ntry > 0 ? -max/values[0] : max/values[0];
float id = 1/d;
float sumqx_p = 0, sumq2_p = 0;
float sumqx_m = 0, sumq2_m = 0;
for (int j = 0; j < 16; ++j) {
float w = weight[j];
float al = id*xb[j];
//int l = best_index(64, values, al);
int l = best_index_iq6nl(values, al);
float q = values[l];
sumqx_p += w*q*xb[j];
sumq2_p += w*q*q;
//l = best_index(64, values, -al);
l = best_index_iq6nl(values, -al);
q = values[l];
sumqx_m += w*q*xb[j];
sumq2_m += w*q*q;
}
d = sumqx_p/sumq2_p;
float best = d*sumqx_p;
if (sumq2_m > 0 && sumqx_m*sumqx_m > best*sumq2_m) {
d = sumqx_m/sumq2_m; best = d*sumqx_m;
}
bool is_shifted = false;
for (int itry = -ntry; itry <= ntry; ++itry) {
id = (itry*step + values[0])/max;
sumqx_p = sumq2_p = 0;
sumqx_m = sumq2_m = 0;
for (int j = 0; j < 16; ++j) {
float w = weight[j];
float al = id*xb[j];
//int l = best_index(64, values, al);
int l = best_index_iq6nl(values, al);
float q = values[l];
sumqx_p += w*q*xb[j];
sumq2_p += w*q*q;
//l = best_index(64, values, -al);
l = best_index_iq6nl(values, -al);
q = values[l];
sumqx_m += w*q*xb[j];
sumq2_m += w*q*q;
}
if (sumq2_p > 0 && sumqx_p*sumqx_p > best*sumq2_p) {
d = sumqx_p/sumq2_p; best = d * sumqx_p; is_shifted = false;
}
if (sumq2_m > 0 && sumqx_m*sumqx_m > best*sumq2_m) {
d = sumqx_m/sumq2_m; best = d * sumqx_m; is_shifted = false;
}
id = (itry*step + shifted_values[0])/max;
sumqx_p = sumq2_p = 0;
sumqx_m = sumq2_m = 0;
for (int j = 0; j < 16; ++j) {
float w = weight[j];
float al = id*xb[j];
//int l = best_index(64, shifted_values, al);
int l = best_index_iq6nl(shifted_values, al);
float q = shifted_values[l];
sumqx_p += w*q*xb[j];
sumq2_p += w*q*q;
//l = best_index(64, shifted_values, -al);
l = best_index_iq6nl(shifted_values, -al);
q = shifted_values[l];
sumqx_m += w*q*xb[j];
sumq2_m += w*q*q;
}
if (sumq2_p > 0 && sumqx_p*sumqx_p > best*sumq2_p) {
d = sumqx_p/sumq2_p; best = d * sumqx_p; is_shifted = true;
}
if (sumq2_m > 0 && sumqx_m*sumqx_m > best*sumq2_m) {
d = sumqx_m/sumq2_m; best = d * sumqx_m; is_shifted = true;
}
}
if (d) {
const float * block_values = is_shifted ? shifted_values : values;
float sumqx = 0, sumq2 = 0;
id = 1/d;
for (int j = 0; j < 16; ++j) {
float w = weight[j];
float al = id*xb[j];
//int l = best_index(64, block_values, al);
int l = best_index_iq6nl(block_values, al);
float q = block_values[l];
sumqx += w*q*xb[j];
sumq2 += w*q*q;
}
if (sumq2 > 0) d = sumqx/sumq2;
}
scales[ib] = d;
if (is_shifted) extra |= (1 << ib);
float abs_scale = fabsf(scales[ib]);
if (abs_scale > max_abs_scale) {
max_abs_scale = abs_scale; max_scale = scales[ib];
}
}
if (!max_abs_scale) continue;
float d = -max_scale/127;
y[ibl].d = GGML_FP32_TO_FP16(d);
y[ibl].extra = extra;
float id = 1/d;
float sumqx = 0, sumq2 = 0;
for (int ib = 0; ib < QK_K/16; ++ib) {
int ls = nearest_int(id*scales[ib]);
ls = MAX(-127, MIN(127, ls));
y[ibl].scales[ib] |= ls;
float dl = d * ls;
if (dl) {
const float * block_values = y[ibl].extra & (1 << ib) ? shifted_values : values;
const float * xb = xbl + 16*ib;
if (quant_weights) {
const float * qw = quant_weights + ibl*QK_K + ib*16;
for (int j = 0; j < 16; ++j) weight[j] = qw[j] * sqrtf(sigma2 + xb[j]*xb[j]);
} else {
for (int j = 0; j < 16; ++j) weight[j] = 0.25f*sigma2 + xb[j]*xb[j];
}
float idl = 1/dl;
int ib32 = ib/2;
int offset = 16*(ib%2);
uint8_t * qs = y[ibl].qs + 32*(ib32/2) + offset;
uint8_t * qh = y[ibl].qh + 32*(ib32/4) + offset;
for (int j = 0; j < 16; ++j) {
const float al = idl*xb[j];
//int ibest = best_index(64, block_values, al);
int ibest = best_index_iq6nl(block_values, al);
qs[j] |= ((ibest & 0xf) << 4*(ib32%2));
qh[j] |= ((ibest >> 4) << 2*(ib32%4));
float w = weight[j];
float q = block_values[ibest]*ls;
sumqx += w*q*xb[j];
sumq2 += w*q*q;
}
}
}
if (sumq2 > 0) y[ibl].d = GGML_FP32_TO_FP16(sumqx/sumq2);
}
}
}
void quantize_row_iq6_k_ref(const float * x, block_iq6_k * y, int64_t k) {
assert(k % QK_K == 0);
quantize_iq6_k(x, (void *)y, 1, k, nullptr);
}
void quantize_row_iq6_k(const float * x, void * vy, int64_t k) {
assert(k % QK_K == 0);
block_iq6_k * y = (block_iq6_k *)vy;
quantize_row_iq6_k_ref(x, y, k);
}
size_t quantize_iq6_k(const float * src, void * dst, int64_t nrows, int64_t n_per_row, const float * imatrix) {
GGML_ASSERT(n_per_row%QK_K == 0);
int nblock = n_per_row/QK_K;
char * qrow = (char *)dst;
float values[128];
for (int i = 0; i < 64; ++i) {
values[i] = iq6nl_values[i];
values[i+64] = values[i] + S_IQ6K;
}
for (int64_t row = 0; row < nrows; ++row) {
quantize_row_iq6_k_impl(src, (void *)qrow, n_per_row, imatrix, values, values + 64);
src += n_per_row;
qrow += nblock*sizeof(block_iq6_k);
}
return nrows * nblock * sizeof(block_iq6_k);
}
namespace {
template <int q8_type>
void iqk_quantize_row_q8_K_T(const float * x, void * vy, int64_t k) {
assert(k % QK_K == 0);
const int nb = k / QK_K;
block_q8_K * y = (block_q8_K *)vy;
#ifdef __AVX2__
const __m256 signBit = _mm256_set1_ps(-0.0f);
const __m256i perm = _mm256_setr_epi32(0, 4, 1, 5, 2, 6, 3, 7);
for (int i = 0; i < nb; i++) {
const float * xb = x + i*QK_K;
__m256 maxAbs = _mm256_setzero_ps();
const float * xx = xb;
for (int ib = 0; ib < QK_K/8; ++ib) {
const __m256 v = _mm256_loadu_ps(xx); xx += 8;
maxAbs = _mm256_max_ps( maxAbs, _mm256_andnot_ps(signBit, v));
}
const float maxScalar = hmax_f32_8(maxAbs);
const float d = maxScalar / 127.f;
y[i].d = d;
const float id = ( maxScalar != 0.0f ) ? 127.f / maxScalar : 0.0f;
const __m256 mul = _mm256_set1_ps( id );
xx = xb;
int8_t * q8 = y[i].qs;
for (int ib = 0; ib < QK_K/32; ++ib) {
__m256 v0 = _mm256_mul_ps(mul, _mm256_loadu_ps(xx)); xx += 8;
__m256 v1 = _mm256_mul_ps(mul, _mm256_loadu_ps(xx)); xx += 8;
__m256 v2 = _mm256_mul_ps(mul, _mm256_loadu_ps(xx)); xx += 8;
__m256 v3 = _mm256_mul_ps(mul, _mm256_loadu_ps(xx)); xx += 8;
v0 = _mm256_round_ps(v0, _MM_ROUND_NEAREST);
v1 = _mm256_round_ps(v1, _MM_ROUND_NEAREST);
v2 = _mm256_round_ps(v2, _MM_ROUND_NEAREST);
v3 = _mm256_round_ps(v3, _MM_ROUND_NEAREST);
__m256i i0 = _mm256_cvtps_epi32(v0);
__m256i i1 = _mm256_cvtps_epi32(v1);
__m256i i2 = _mm256_cvtps_epi32(v2);
__m256i i3 = _mm256_cvtps_epi32(v3);
if constexpr (q8_type > 0) {
int bsum = hsum_i32_8(_mm256_add_epi32(_mm256_add_epi32(i0, i1), _mm256_add_epi32(i2, i3)));
auto bs = (float *)y[i].bsums;
bs[ib] = d*bsum;
} else {
y[i].bsums[2*ib+0] = hsum_i32_8(_mm256_add_epi32(i0, i1));
y[i].bsums[2*ib+1] = hsum_i32_8(_mm256_add_epi32(i2, i3));
}
i0 = _mm256_packs_epi32( i0, i1 );
i2 = _mm256_packs_epi32( i2, i3 );
i0 = _mm256_packs_epi16( i0, i2 );
i0 = _mm256_permutevar8x32_epi32( i0, perm );
_mm256_storeu_si256((__m256i *)q8, i0);
q8 += 32;
}
if constexpr (q8_type == 2) {
auto bs = (float *)y[i].bsums;
float sum = 0;
for (int ib = 0; ib < QK_K/32; ++ib) sum += bs[ib];
bs[0] = sum;
}
}
#else
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);
}
if constexpr (q8_type > 0) {
auto bs = (float *)y[i].bsums;
float d = 1/iscale;
float sum = 0;
for (int j = 0; j < QK_K/32; ++j) {
int sum = 0;
for (int ii = 0; ii < 32; ++ii) {
sum += y[i].qs[j*32 + ii];
}
bs[j] = d*sum;
sum += bs[j];
}
if constexpr (q8_type == 2) {
bs[0] = sum;
}
} else {
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;
}
#endif
}
}
void iqk_quantize_row_q8_K(const float * x, void * vy, int64_t k) {
iqk_quantize_row_q8_K_T<0>(x, vy, k);
}
void quantize_row_q8_K32(const float * x, void * vy, int64_t k) {
iqk_quantize_row_q8_K_T<1>(x, vy, k);
}
void quantize_row_q8_KR8(const float * x, void * vy, int64_t k) {
iqk_quantize_row_q8_K_T<2>(x, vy, k);
}
namespace {
// TODO: merge this with the above template
void iqk_quantize_row_q8_K128(const float * x, void * vy, int64_t k) {
constexpr int kBlockSize = 128;
assert(k % kBlockSize == 0);
const int nb = k / kBlockSize;
auto y = (block_q8_K128 *)vy;
#ifdef __AVX2__
const __m256 signBit = _mm256_set1_ps(-0.0f);
const __m256i perm = _mm256_setr_epi32(0, 4, 1, 5, 2, 6, 3, 7);
for (int i = 0; i < nb; i++) {
const float * xb = x + i*kBlockSize;
__m256 maxAbs = _mm256_setzero_ps();
const float * xx = xb;
for (int ib = 0; ib < kBlockSize/8; ++ib) {
const __m256 v = _mm256_loadu_ps(xx); xx += 8;
maxAbs = _mm256_max_ps( maxAbs, _mm256_andnot_ps(signBit, v));
}
const float maxScalar = hmax_f32_8(maxAbs);
const float d = maxScalar / 127.f;
y[i].d = d;
const float id = ( maxScalar != 0.0f ) ? 127.f / maxScalar : 0.0f;
const __m256 mul = _mm256_set1_ps( id );
xx = xb;
int8_t * q8 = y[i].qs;
for (int ib = 0; ib < kBlockSize/32; ++ib) {
__m256 v0 = _mm256_mul_ps(mul, _mm256_loadu_ps(xx)); xx += 8;
__m256 v1 = _mm256_mul_ps(mul, _mm256_loadu_ps(xx)); xx += 8;
__m256 v2 = _mm256_mul_ps(mul, _mm256_loadu_ps(xx)); xx += 8;
__m256 v3 = _mm256_mul_ps(mul, _mm256_loadu_ps(xx)); xx += 8;
v0 = _mm256_round_ps(v0, _MM_ROUND_NEAREST);
v1 = _mm256_round_ps(v1, _MM_ROUND_NEAREST);
v2 = _mm256_round_ps(v2, _MM_ROUND_NEAREST);
v3 = _mm256_round_ps(v3, _MM_ROUND_NEAREST);
__m256i i0 = _mm256_cvtps_epi32(v0);
__m256i i1 = _mm256_cvtps_epi32(v1);
__m256i i2 = _mm256_cvtps_epi32(v2);
__m256i i3 = _mm256_cvtps_epi32(v3);
y[i].bsums[ib] = hsum_i32_8(_mm256_add_epi32(_mm256_add_epi32(i0, i1), _mm256_add_epi32(i2, i3)));
i0 = _mm256_packs_epi32( i0, i1 );
i2 = _mm256_packs_epi32( i2, i3 );
i0 = _mm256_packs_epi16( i0, i2 );
i0 = _mm256_permutevar8x32_epi32( i0, perm );
_mm256_storeu_si256((__m256i *)q8, i0);
q8 += 32;
}
}
#elif defined __ARM_NEON
int32x4_t ival[8];
for (int i = 0; i < nb; i++) {
const float * xb = x + i*kBlockSize;
auto vmax = vdupq_n_f32(0.f);
for (int j = 0; j < kBlockSize; j += 4) {
vmax = vmaxq_f32(vmax, vabsq_f32(vld1q_f32(xb + j)));
}
auto smax = vmaxvq_f32(vmax);
if (!smax) {
std::memset(&y[i], 0, sizeof(y[i]));
continue;
}
y[i].d = smax/127;
auto vid = vdupq_n_f32(127/smax);
for (int ib = 0; ib < kBlockSize/32; ++ib) {
auto isum = vdupq_n_s32(0);
for (int k = 0; k < 8; ++k) {
auto val = vld1q_f32(xb + 32*ib + 4*k);
ival[k] = vcvtnq_s32_f32(vmulq_f32(val, vid));
isum = vaddq_s32(isum, ival[k]);
}
y[i].bsums[ib] = vaddvq_s32(isum);
for (int k = 0; k < 4; ++k) {
auto i16 = vcombine_s16(vmovn_s32(ival[2*k+0]), vmovn_s32(ival[2*k+1]));
vst1_s8(y[i].qs + 32*ib + 8*k, vmovn_s16(i16));
}
}
}
#else
for (int i = 0; i < nb; i++) {
float amax = 0;
for (int j = 0; j < kBlockSize; ++j) {
float ax = std::abs(x[j]);
amax = std::max(amax, ax);
}
if (!amax) {
y[i].d = 0;
memset(y[i].qs, 0, kBlockSize);
memset(y[i].bsums, 0, kBlockSize/32*(sizeof(int16_t)));
x += kBlockSize;
continue;
}
const float iscale = 127.f/amax;
for (int j = 0; j < kBlockSize; ++j) {
int v = nearest_int(iscale*x[j]);
y[i].qs[j] = v;
}
for (int j = 0; j < kBlockSize/32; ++j) {
int sum = 0;
for (int ii = 0; ii < 32; ++ii) {
sum += y[i].qs[j*32 + ii];
}
y[i].bsums[j] = sum;
}
y[i].d = 1/iscale;
x += kBlockSize;
}
#endif
}
// TODO: merge this with the above template
void iqk_quantize_row_q8_KV(const float * x, void * vy, int64_t k) {
assert(k % 32 == 0);
auto dptr = (float *)vy;
auto q8 = (int8_t *)(dptr + 2);
#ifdef __AVX2__
const __m256 signBit = _mm256_set1_ps(-0.0f);
const __m256i perm = _mm256_setr_epi32(0, 4, 1, 5, 2, 6, 3, 7);
__m256 maxAbs = _mm256_setzero_ps();
for (int ib = 0; ib < k/8; ++ib) {
const __m256 v = _mm256_loadu_ps(x + 8*ib);
maxAbs = _mm256_max_ps( maxAbs, _mm256_andnot_ps(signBit, v));
}
const float maxScalar = hmax_f32_8(maxAbs);
if (!maxScalar) {
dptr[0] = dptr[1] = 0;
std::memset(q8, 0, k*sizeof(int8_t));
return;
}
dptr[0] = maxScalar / 127.f;
auto mul = _mm256_set1_ps(1/dptr[0]);
auto isum = _mm256_setzero_si256();
for (int i = 0; i < k/32; i++) {
__m256 v0 = _mm256_mul_ps(mul, _mm256_loadu_ps(x + 32*i + 0));
__m256 v1 = _mm256_mul_ps(mul, _mm256_loadu_ps(x + 32*i + 8));
__m256 v2 = _mm256_mul_ps(mul, _mm256_loadu_ps(x + 32*i + 16));
__m256 v3 = _mm256_mul_ps(mul, _mm256_loadu_ps(x + 32*i + 24));
v0 = _mm256_round_ps(v0, _MM_ROUND_NEAREST);
v1 = _mm256_round_ps(v1, _MM_ROUND_NEAREST);
v2 = _mm256_round_ps(v2, _MM_ROUND_NEAREST);
v3 = _mm256_round_ps(v3, _MM_ROUND_NEAREST);
__m256i i0 = _mm256_cvtps_epi32(v0);
__m256i i1 = _mm256_cvtps_epi32(v1);
__m256i i2 = _mm256_cvtps_epi32(v2);
__m256i i3 = _mm256_cvtps_epi32(v3);
isum = _mm256_add_epi32(isum, _mm256_add_epi32(_mm256_add_epi32(i0, i1), _mm256_add_epi32(i2, i3)));
i0 = _mm256_packs_epi32( i0, i1 );
i2 = _mm256_packs_epi32( i2, i3 );
i0 = _mm256_packs_epi16( i0, i2 );
i0 = _mm256_permutevar8x32_epi32( i0, perm );
_mm256_storeu_si256((__m256i *)q8, i0);
q8 += 32;
}
auto iptr = (int32_t *)(dptr + 1);
iptr[0] = hsum_i32_8(isum);
#elif defined __ARM_NEON
int32x4_t ival[8];
auto vmax = vdupq_n_f32(0.f);
for (int j = 0; j < k; j += 4) {
vmax = vmaxq_f32(vmax, vabsq_f32(vld1q_f32(x + j)));
}
auto smax = vmaxvq_f32(vmax);
if (!smax) {
dptr[0] = dptr[1] = 0;
std::memset(q8, 0, k*sizeof(int8_t));
return;
}
dptr[0] = smax/127;
auto vid = vdupq_n_f32(1/dptr[0]);
auto isum = vdupq_n_s32(0);
for (int ib = 0; ib < k/32; ++ib) {
auto xb = x + 32*ib;
for (int k = 0; k < 8; ++k) {
auto val = vld1q_f32(xb + 4*k);
ival[k] = vcvtnq_s32_f32(vmulq_f32(val, vid));
isum = vaddq_s32(isum, ival[k]);
}
for (int k = 0; k < 4; ++k) {
auto i16 = vcombine_s16(vmovn_s32(ival[2*k+0]), vmovn_s32(ival[2*k+1]));
vst1_s8(q8, vmovn_s16(i16));
q8 += 8;
}
}
auto iptr = (int32_t *)(dptr + 1);
iptr[0] = vaddvq_s32(isum);
#else
float amax = 0;
for (int j = 0; j < k; ++j) {
float ax = std::abs(x[j]);
amax = std::max(amax, ax);
}
if (!amax) {
dptr[0] = dptr[1] = 0;
std::memset(q8, 0, k*sizeof(int8_t));
return;
}
dptr[0] = amax/127;
float id = 1/dptr[0];
int isum = 0;
for (int i = 0; i < k; i++) {
q8[i] = nearest_int(id*x[i]);
isum += q8[i];
}
auto iptr = (int32_t *)(dptr + 1);
iptr[0] = isum;
#endif
}
}
void quantize_row_q8_K128(const float * x, void * vy, int64_t k) {
iqk_quantize_row_q8_K128(x, vy, k);
}
namespace {
static void quantize_row_iq4_k_impl_bs128(const int super_block_size, const int block_size,
int n_per_row, const float * x, char * cy,
float * all_scales, float * weight,
const int8_t * values,
const float * quant_weights,
const int ntry) {
//GGML_ASSERT(super_block_size == 256 && block_size == 128);
float * dptr = (float *)cy;
block_iq4_ks * y = (block_iq4_ks *)(dptr + 1);
const int8_t * shifted_values = values + 16;
float amax_scale = 0;
for (int ibl = 0; ibl < n_per_row/super_block_size; ++ibl) {
memset(&y[ibl], 0, sizeof(block_iq4_ks));
const float * xbl = x + ibl*super_block_size;
auto scales = all_scales + ibl*(super_block_size/block_size);
float sigma2 = 0;
for (int j = 0; j < super_block_size; ++j) sigma2 += xbl[j]*xbl[j];
sigma2 *= 2.f/super_block_size;
for (int ib = 0; ib < super_block_size/block_size; ++ib) {
const float * xb = xbl + ib*block_size;
if (quant_weights) {
const float * qw = quant_weights + ibl*super_block_size + 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) {
scales[ib] = 0;
continue;
}
float d = ntry > 0 ? -max/values[0] : max/values[0];
float id = 1/d;
float sumqx_p = 0, sumq2_p = 0;
float sumqx_m = 0, sumq2_m = 0;
for (int j = 0; j < block_size; ++j) {
float w = weight[j];
float al = id*xb[j];
int l = best_index_iq4nl(values, al);
float q = values[l];
sumqx_p += w*q*xb[j];
sumq2_p += w*q*q;
l = best_index_iq4nl(values, -al);
q = values[l];
sumqx_m += w*q*xb[j];
sumq2_m += w*q*q;
}
d = sumqx_p/sumq2_p;
bool is_shifted = false;
float best = d*sumqx_p;
if (sumq2_m > 0 && sumqx_m*sumqx_m > best*sumq2_m) {
d = sumqx_m/sumq2_m; best = d*sumqx_m;
}
for (int itry = -ntry; itry <= ntry; ++itry) {
id = (itry + values[0])/max;
sumqx_p = sumq2_p = 0;
sumqx_m = sumq2_m = 0;
for (int j = 0; j < block_size; ++j) {
float w = weight[j];
float al = id*xb[j];
int l = best_index_iq4nl(values, al);
float q = values[l];
sumqx_p += w*q*xb[j];
sumq2_p += w*q*q;
l = best_index_iq4nl(values, -al);
q = values[l];
sumqx_m += w*q*xb[j];
sumq2_m += w*q*q;
}
if (sumq2_p > 0 && sumqx_p*sumqx_p > best*sumq2_p) {
d = sumqx_p/sumq2_p; best = d * sumqx_p; is_shifted = false;
}
if (sumq2_m > 0 && sumqx_m*sumqx_m > best*sumq2_m) {
d = sumqx_m/sumq2_m; best = d * sumqx_m; is_shifted = false;
}
id = (itry + shifted_values[0])/max;
sumqx_p = sumq2_p = 0;
sumqx_m = sumq2_m = 0;
for (int j = 0; j < block_size; ++j) {
float w = weight[j];
float al = id*xb[j];
int l = best_index_iq4nl(shifted_values, al);
float q = shifted_values[l];
sumqx_p += w*q*xb[j];
sumq2_p += w*q*q;
l = best_index_iq4nl(shifted_values, -al);
q = shifted_values[l];
sumqx_m += w*q*xb[j];
sumq2_m += w*q*q;
}
if (sumq2_p > 0 && sumqx_p*sumqx_p > best*sumq2_p) {
d = sumqx_p/sumq2_p; best = d * sumqx_p; is_shifted = true;
}
if (sumq2_m > 0 && sumqx_m*sumqx_m > best*sumq2_m) {
d = sumqx_m/sumq2_m; best = d * sumqx_m; is_shifted = true;
}
}
if (is_shifted) y[ibl].scales[ib] = 0x01;
scales[ib] = d;
amax_scale = std::max(amax_scale, std::abs(d));
}
}
float d = amax_scale/127;
*dptr = d;
if (!d) return;
float id = d ? 1/d : 0.f;
float sumqx = 0, sumq2 = 0;
//float mse = 0;
for (int ibl = 0; ibl < n_per_row/super_block_size; ++ibl) {
const float * xbl = x + ibl*super_block_size;
float sigma2 = 0;
for (int j = 0; j < super_block_size; ++j) sigma2 += xbl[j]*xbl[j];
sigma2 *= 2.f/super_block_size;
auto scales = all_scales + (super_block_size/block_size)*ibl;
for (int ib = 0; ib < super_block_size/block_size; ++ib) {
const int8_t * block_values = y[ibl].scales[ib] & 0x01 ? shifted_values : values;
int l = nearest_int(0.5f*(id*scales[ib]+127.f));
l = std::max(0, std::min(127, l)) << 1;
//printf("d = %g, id = %g, scales = %g, l = %d, dl = %g\n", d, id, scales[ib], l, d*(l - 127));
y[ibl].scales[ib] |= l;
l -= 127;
float dl = d * l;
float idl = dl ? 1/dl : 0.f;
const float * xb = xbl + ib*block_size;
if (quant_weights) {
const float * qw = quant_weights + ibl*super_block_size + 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];
}
auto qs = y[ibl].qs + ib*(block_size/2);
for (int j = 0; j < block_size/2; ++j) {
uint8_t i1 = best_index_iq4nl(block_values, idl*xb[j]);
uint8_t i2 = best_index_iq4nl(block_values, idl*xb[j+block_size/2]);
qs[j] = i1 | (i2 << 4);
float w1 = weight[j];
float w2 = weight[j+block_size/2];
float q1 = block_values[i1]*l;
float q2 = block_values[i2]*l;
sumqx += w1*q1*xb[j] + w2*q2*xb[j+block_size/2];
sumq2 += w1*q1*q1 + w2*q2*q2;
//float diff = xb[j] - d*q1; mse += diff*diff;
//diff = xb[j+block_size/2] - d*q2; mse += diff*diff;
}
}
}
//printf("rmse = %g\n", sqrt(mse/n_per_row));
if (sumq2 > 0) *dptr = sumqx/sumq2;
}
}
void quantize_row_iq4_ks_ref(const float * x, block_iq4_ks * y, int64_t k) {
quantize_iq4_ks(x, (void *)y, 1, k, nullptr);
}
void quantize_row_iq4_ks(const float * x, void * y, int64_t k) {
quantize_iq4_ks(x, (void *)y, 1, k, nullptr);
}
size_t quantize_iq4_ks(const float * src, void * dst, int64_t nrows, int64_t n_per_row, const float * imatrix) {
//printf("============ %s(%d, %d)\n", __func__, int(nrows), int(n_per_row));
constexpr int kBlockSize = 32; //128;
GGML_ASSERT(n_per_row%QK_K == 0);
auto row_size = ggml_row_size(GGML_TYPE_IQ4_KS, n_per_row);
char * qrow = (char *)dst;
float weight[kBlockSize];
std::vector<float> all_scales(n_per_row/kBlockSize);
for (int64_t row = 0; row < nrows; ++row) {
quantize_row_iq4_k_impl_bs128(QK_K, kBlockSize, n_per_row, src, qrow, all_scales.data(), weight, iq4k_values, imatrix, 7);
src += n_per_row;
qrow += row_size;
}
return nrows * row_size;
}
void dequantize_row_iq4_ks(const block_iq4_ks * x, float * y, int64_t k) {
constexpr int kBlockSize = 32; //128;
GGML_ASSERT(k%QK_K == 0);
const float * dptr = (const float *)x;
float d = *dptr;
x = (const block_iq4_ks *)(dptr + 1);
int nblock = k/QK_K;
for (int ibl = 0; ibl < nblock; ++ibl) {
auto qs = x[ibl].qs;
for (int ib = 0; ib < QK_K/kBlockSize; ++ib) {
float dl = d * ((int)(x[ibl].scales[ib] & 254) - 127);
const int8_t * values = iq4k_values + ((x[ibl].scales[ib] & 1) << 4);
for (int j = 0; j < kBlockSize/2; ++j) {
y[j ] = dl * values[qs[j] & 0xf];
y[j+kBlockSize/2] = dl * values[qs[j] >> 4];
}
y += kBlockSize;
qs += kBlockSize/2;
}
}
}
void vec_dot_iq4_ks_q8_k(int n, float * s, size_t bs, const void * vx, size_t bx, const void * vy, size_t by, int nrc) {
constexpr int kBlockSize = 32;
#if GGML_USE_IQK_MULMAT
if (iqk_mul_mat(1, 1, n, GGML_TYPE_IQ4_KS, vx, 0, GGML_TYPE_Q8_K, vy, 0, s, 0, 0, 1)) {
return;
}
#endif
GGML_ASSERT(n%QK_K == 0);
GGML_ASSERT(nrc == 1);
GGML_UNUSED(bs);
GGML_UNUSED(bx);
GGML_UNUSED(by);
const float * dptr = (const float *)vx;
const float d = *dptr;
//printf("%s: n = %d, d = %g\n", __func__, n, d);
const block_iq4_ks * x = (const block_iq4_ks *)(dptr + 1);
const block_q8_K * y = (const block_q8_K *)vy;
int nblock = n/QK_K;
float sumf = 0;
for (int ibl = 0; ibl < nblock; ++ibl) {
//int sumi = 0;
auto qy = y[ibl].qs;
auto qx = x[ibl].qs;
float db = d * y[ibl].d;
for (int ib = 0; ib < QK_K/kBlockSize; ++ib) {
float dl = db * ((x[ibl].scales[ib] & 254) - 127);
//int ls = (x[ibl].scales[ib] & 254) - 127;
const int8_t * values = iq4k_values + ((x[ibl].scales[ib] & 1) << 4);
int suml = 0;
for (int j = 0; j < kBlockSize/2; ++j) {
suml += qy[j ] * values[qx[j] & 0xf]
+ qy[j + kBlockSize/2] * values[qx[j] >> 4];
}
sumf += dl * suml;
//sumi += ls * suml;
qy += kBlockSize;
qx += kBlockSize/2;
}
//sumf += d * y[ibl].d * sumi;
}
*s = sumf;
}
namespace {
const uint16_t * scramble_table() {
static std::mutex mutex;
static std::vector<uint16_t> table;
std::lock_guard<std::mutex> lock(mutex);
if (table.empty()) {
table.resize(1 << 15);
for (int i = 0; i < int(table.size()); ++i) {
uint16_t val = i;
int non = popcount(val);
if (non%2) val |= (1 << 15);
bool found = false;
for (int j = 0; j < int(table.size()); ++j) {
if ((j ^ (j << 1)) == val) {
table[i] = j; found = true; break;
}
}
if (!found) {
printf("Oops: did not find for %d %u\n", i, val);
exit(1);
}
}
}
return table.data();
}
uint16_t prune_iq4ks(uint16_t v, const int8_t * values, const float * x, const float * w, float dl) {
if (popcount(v)%2 == 0) return v;
float best_score = std::numeric_limits<float>::max();
uint8_t q4[4];
int jbest = -1;
uint8_t bestq = 0;
for (int j = 0; j < 4; ++j) {
uint8_t q = (v >> 4*j) & 0xf;
q4[j] = q;
auto pc = popcount(q);
float diff0 = dl*iq4k_values[q] - x[j];
if (q > 0) {
uint8_t qm = q - 1u;
int pcm = popcount(qm);
if (pcm == pc-1 || pcm == pc+1) {
float diff1 = dl*values[qm] - x[j];
float score = w[j]*(diff1*diff1 - diff0*diff0);
if (score < best_score) {
best_score = score; jbest = j; bestq = qm;
}
}
}
if (q < 15) {
uint8_t qp = q + 1u;
int pcp = popcount(qp);
if (pcp == pc-1 || pcp == pc+1) {
float diff1 = dl*values[qp] - x[j];
float score = w[j]*(diff1*diff1 - diff0*diff0);
if (score < best_score) {
best_score = score; jbest = j; bestq = qp;
}
}
}
}
GGML_ASSERT(jbest >= 0);
q4[jbest] = bestq;
return (q4[0] | (q4[1] << 4) | (q4[2] << 8) | (q4[3] << 12));
}
static void quantize_row_iq4_kss_impl(int n_per_row, const float * x, char * cy,
float * all_scales, float * weight,
const int8_t * values,
const float * quant_weights,
const uint16_t * table,
const int ntry) {
constexpr int super_block_size = 256;
constexpr int block_size = 32;
float * dptr = (float *)cy;
*dptr = 0;
block_iq4_kss * y = (block_iq4_kss *)(dptr + 1);
const int8_t * shifted_values = values + 16;
uint16_t vps[block_size/2], vms[block_size/2], vs[block_size/2];
float xv[4], wv[4];
float amax_scale = 0;
for (int ibl = 0; ibl < n_per_row/super_block_size; ++ibl) {
memset(&y[ibl], 0, sizeof(block_iq4_kss));
const float * xbl = x + ibl*super_block_size;
auto scales = all_scales + ibl*(super_block_size/block_size);
float sigma2 = 0;
for (int j = 0; j < super_block_size; ++j) sigma2 += xbl[j]*xbl[j];
sigma2 *= 2.f/super_block_size;
for (int ib = 0; ib < super_block_size/block_size; ++ib) {
const float * xb = xbl + ib*block_size;
if (quant_weights) {
const float * qw = quant_weights + ibl*super_block_size + 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) {
scales[ib] = 0;
continue;
}
float best = 0;
float d = -max/iq4k_values[0];
std::memset(vs, 0, block_size);
for (int itry = -ntry; itry <= ntry; ++itry) {
float id = (itry + values[0])/max;
float sumqx_p = 0, sumq2_p = 0;
float sumqx_m = 0, sumq2_m = 0;
float this_d = 1/id;
for (int k = 0; k < block_size/4; ++k) {
xv[0] = xb[2*k+0]; xv[1] = xb[2*k+0+block_size/2]; xv[2] = xb[2*k+1]; xv[3] = xb[2*k+1+block_size/2];
wv[0] = weight[2*k+0]; wv[1] = weight[2*k+0+block_size/2]; wv[2] = weight[2*k+1]; wv[3] = weight[2*k+1+block_size/2];
uint16_t vp = 0, vm = 0;
for (int j = 0; j < 4; ++j) {
float al = id*xv[j];
vp |= (best_index_iq4nl(values, al) << 4*j);
vm |= (best_index_iq4nl(values, -al) << 4*j);
}
vp = prune_iq4ks(vp, values, xv, wv, this_d);
vm = prune_iq4ks(vm, values, xv, wv, this_d);
for (int j = 0; j < 4; ++j) {
float w = wv[j];
float q = values[(vp >> 4*j) & 0xf];
sumqx_p += w*q*xv[j];
sumq2_p += w*q*q;
q = values[(vm >> 4*j) & 0xf];
sumqx_m += w*q*xv[j];
sumq2_m += w*q*q;
}
vps[k] = vp;
vms[k] = vm;
}
bool copy_p = false, copy_m = false;
if (sumq2_p > 0 && sumqx_p*sumqx_p > best*sumq2_p) {
d = sumqx_p/sumq2_p; best = d * sumqx_p; copy_p = true;
}
if (sumq2_m > 0 && sumqx_m*sumqx_m > best*sumq2_m) {
d = sumqx_m/sumq2_m; best = d * sumqx_m; copy_m = true;
}
if (copy_m) {
std::memcpy(vs, vms, block_size);
} else if (copy_p) {
std::memcpy(vs, vps, block_size);
}
id = (itry + shifted_values[0])/max;
this_d = 1/id;
sumqx_p = sumq2_p = 0;
sumqx_m = sumq2_m = 0;
for (int k = 0; k < block_size/4; ++k) {
xv[0] = xb[2*k+0]; xv[1] = xb[2*k+0+block_size/2]; xv[2] = xb[2*k+1]; xv[3] = xb[2*k+1+block_size/2];
wv[0] = weight[2*k+0]; wv[1] = weight[2*k+0+block_size/2]; wv[2] = weight[2*k+1]; wv[3] = weight[2*k+1+block_size/2];
uint16_t vp = 0, vm = 0;
for (int j = 0; j < 4; ++j) {
float al = id*xv[j];
vp |= (best_index_iq4nl(shifted_values, al) << 4*j);
vm |= (best_index_iq4nl(shifted_values, -al) << 4*j);
}
vp = prune_iq4ks(vp, shifted_values, xv, wv, this_d);
vm = prune_iq4ks(vm, shifted_values, xv, wv, this_d);
for (int j = 0; j < 4; ++j) {
float w = wv[j];
float q = shifted_values[(vp >> 4*j) & 0xf];
sumqx_p += w*q*xv[j];
sumq2_p += w*q*q;
q = shifted_values[(vm >> 4*j) & 0xf];
sumqx_m += w*q*xv[j];
sumq2_m += w*q*q;
}
vps[k] = vp;
vms[k] = vm;
}
copy_p = copy_m = false;
if (sumq2_p > 0 && sumqx_p*sumqx_p > best*sumq2_p) {
d = sumqx_p/sumq2_p; best = d * sumqx_p; copy_p = true;
}
if (sumq2_m > 0 && sumqx_m*sumqx_m > best*sumq2_m) {
d = sumqx_m/sumq2_m; best = d * sumqx_m; copy_m = true;
}
if (copy_m) {
std::memcpy(vs, vms, block_size);
} else if (copy_p) {
std::memcpy(vs, vps, block_size);
}
}
scales[ib] = d;
amax_scale = std::max(amax_scale, std::abs(d));
}
}
float d = amax_scale/127;
*dptr = d;
if (!d) return;
float id = 1/d;
float sumqx = 0, sumq2 = 0;
for (int ibl = 0; ibl < n_per_row/super_block_size; ++ibl) {
auto scales = all_scales + (super_block_size/block_size)*ibl;
const float * xbl = x + ibl*super_block_size;
float sigma2 = 0;
for (int j = 0; j < super_block_size; ++j) sigma2 += xbl[j]*xbl[j];
sigma2 *= 2.f/super_block_size;
for (int ib = 0; ib < super_block_size/block_size; ++ib) {
const float * xb = xbl + ib*block_size;
if (quant_weights) {
const float * qw = quant_weights + ibl*super_block_size + 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];
}
int l = nearest_int(0.5f*(id*scales[ib]+127.f));
l = (std::max(0, std::min(127, l)) << 1) - 127;
if (l) {
float dl = d*l;
float idl = 1/dl;
float mse_p = 0, mse_m = 0;
for (int k = 0; k < block_size/4; ++k) {
xv[0] = xb[2*k+0]; xv[1] = xb[2*k+0+block_size/2]; xv[2] = xb[2*k+1]; xv[3] = xb[2*k+1+block_size/2];
wv[0] = weight[2*k+0]; wv[1] = weight[2*k+0+block_size/2]; wv[2] = weight[2*k+1]; wv[3] = weight[2*k+1+block_size/2];
uint16_t vp = 0, vm = 0;
for (int j = 0; j < 4; ++j) {
float al = idl*xv[j];
vp |= (best_index_iq4nl( values, al) << 4*j);
vm |= (best_index_iq4nl(shifted_values, al) << 4*j);
}
vp = prune_iq4ks(vp, values, xv, wv, dl);
vm = prune_iq4ks(vm, shifted_values, xv, wv, dl);
for (int j = 0; j < 4; ++j) {
float w = wv[j];
float q = values[(vp >> 4*j) & 0xf];
mse_p += w*(xv[j] - dl*q)*(xv[j] - dl*q);
q = shifted_values[(vm >> 4*j) & 0xf];
mse_m += w*(xv[j] - dl*q)*(xv[j] - dl*q);
}
vps[k] = vp;
vms[k] = vm;
}
const uint16_t * v = vps;
const int8_t * block_values = values;
if (mse_m < mse_p) {
v = vms;
block_values = values + 16;
}
for (int k = 0; k < block_size/4; ++k) {
xv[0] = xb[2*k+0]; xv[1] = xb[2*k+0+block_size/2]; xv[2] = xb[2*k+1]; xv[3] = xb[2*k+1+block_size/2];
wv[0] = weight[2*k+0]; wv[1] = weight[2*k+0+block_size/2]; wv[2] = weight[2*k+1]; wv[3] = weight[2*k+1+block_size/2];
for (int j = 0; j < 4; ++j) {
float q = block_values[(v[k] >> 4*j) & 0xf] * l;
sumqx += wv[j]*q*xv[j];
sumq2 += wv[j]*q*q;
}
}
l += 127;
if (mse_m < mse_p) l |= 1;
uint16_t * q16 = (uint16_t *)y[ibl].qs + (block_size/4)*ib;
for (int k = 0; k < block_size/4; ++k) {
auto val = table[v[k] & 0x7fff];
q16[k] = (val << 1) | ((l >> k) & 1);
}
} else {
l += 127;
uint16_t * q16 = (uint16_t *)y[ibl].qs + (block_size/4)*ib;
for (int k = 0; k < block_size/4; ++k) {
q16[k] = ((l >> k) & 1);
}
}
}
}
if (sumq2 > 0) *dptr = sumqx/sumq2;
}
void prune_iq4ks_to_iq4kss(int n_per_row, const uint16_t * table, const char * cx, const float * x, char *cy,
const float * quant_weights, float * weight, float * all_scales) {
constexpr int kBlockSize = 32;
float xv[4], wv[4];
uint16_t vps[kBlockSize/4];
const float * dptr_ks = (const float *)cx;
const float d_ks = *dptr_ks;
const block_iq4_ks * iq4ks = (const block_iq4_ks *)(dptr_ks + 1);
float * dptr = (float *)cy;
*dptr = d_ks;
block_iq4_kss * y = (block_iq4_kss *)(dptr + 1);
int nblock = n_per_row/QK_K;
float max_abs_scale = 0;
for (int ibl = 0; ibl < nblock; ++ibl) {
auto scales = all_scales + ibl*(QK_K/kBlockSize);
const float * xbl = x + ibl*QK_K;
float sigma2 = 0;
for (int j = 0; j < QK_K; ++j) sigma2 += xbl[j]*xbl[j];
sigma2 *= 2.f/QK_K;
const uint16_t * q4 = (const uint16_t *)iq4ks[ibl].qs;
for (int ib = 0; ib < QK_K/kBlockSize; ++ib) {
const float * xb = xbl + ib*kBlockSize;
if (quant_weights) {
const float * qw = quant_weights + ibl*QK_K + ib*kBlockSize;
for (int j = 0; j < kBlockSize; ++j) weight[j] = qw[j] * sqrtf(sigma2 + xb[j]*xb[j]);
} else {
for (int j = 0; j < kBlockSize; ++j) weight[j] = xb[j]*xb[j];
}
const int8_t * values = iq4k_values + ((iq4ks[ibl].scales[ib] & 1) << 4);
float dl = d_ks * ((iq4ks[ibl].scales[ib] & 254) - 127);
float sumqx = 0, sumq2 = 0;
for (int k = 0; k < kBlockSize/4; ++k) {
xv[0] = xb[2*k+0]; xv[1] = xb[2*k+kBlockSize/2]; xv[2] = xb[2*k+1]; xv[3] = xb[2*k+1+kBlockSize/2];
wv[0] = weight[2*k+0]; wv[1] = weight[2*k+kBlockSize/2]; wv[2] = weight[2*k+1]; wv[3] = weight[2*k+1+kBlockSize/2];
auto vp = prune_iq4ks(q4[k], values, xv, wv, dl);
vps[k] = table[vp & 0x7fff];
for (int j = 0; j < 4; ++j) {
float q = values[(vp >> 4*j) & 0xf];
sumqx += wv[j]*q*xv[j];
sumq2 += wv[j]*q*q;
}
}
for (int k = 0; k < kBlockSize/8; ++k) {
y[ibl].qs[(kBlockSize/8)*ib + k] = vps[2*k+0] | (vps[2*k+1] << 15) | (((iq4ks[ibl].scales[ib] >> 2*k) & 3) << 30);
//y[ibl].qs[(kBlockSize/8)*ib + k] = vps[2*k+0] | (vps[2*k+1] << 15);
}
scales[ib] = sumq2 > 0 ? sumqx/sumq2 : dl;
max_abs_scale = std::max(max_abs_scale, scales[ib]);
q4 += kBlockSize/4;
}
}
//if (!max_abs_scale) return;
//float d = max_abs_scale/127;
//*dptr = d;
//float id = 1/d;
//for (int ibl = 0; ibl < nblock; ++ibl) {
// auto scales = all_scales + ibl*(QK_K/kBlockSize);
// for (int ib = 0; ib < QK_K/kBlockSize; ++ib) {
// int l = nearest_int(0.5f*(id*scales[ib]+127.f));
// l = std::max(0, std::min(127, l)) << 1;
// l |= (iq4ks[ibl].scales[ib] & 1);
// for (int k = 0; k < 4; ++k) {
// //y[ibl].qs[4*ib+k] &= 0x3fffffff;
// y[ibl].qs[4*ib+k] |= (((l >> 2*k) & 3) << 30);
// }
// }
//}
}
}
size_t quantize_iq4_kss(const float * src, void * dst, int64_t nrows, int64_t n_per_row, const float * imatrix) {
constexpr int kBlockSize = 32; //128;
GGML_ASSERT(n_per_row%QK_K == 0);
auto row_size = ggml_row_size(GGML_TYPE_IQ4_KSS, n_per_row);
auto row_size_ks = ggml_row_size(GGML_TYPE_IQ4_KS, n_per_row);
std::vector<char> work(row_size_ks);
std::vector<float> all_scales(n_per_row/kBlockSize);
float weight[kBlockSize];
auto qrow = (char *)dst;
auto table = scramble_table();
for (int row = 0; row < nrows; ++row) {
quantize_row_iq4_kss_impl(n_per_row, src, qrow, all_scales.data(), weight, iq4k_values, imatrix, table, 7);
src += n_per_row;
qrow += row_size;
}
return nrows * row_size;
}
void quantize_row_iq4_kss_ref(const float * x, block_iq4_kss * y, int64_t k) {
quantize_iq4_kss(x, y, 1, k, nullptr);
}
void quantize_row_iq4_kss(const float * x, void * y, int64_t k) {
quantize_iq4_kss(x, (block_iq4_kss *)y, 1, k, nullptr);
}
void dequantize_row_iq4_kss(const block_iq4_kss * x, float * y, int64_t k) {
const float * dptr = (const float *)x;
const float d = *dptr;
x = (const block_iq4_kss *)(dptr + 1);
uint16_t aux16[8];
const uint8_t * aux8 = (const uint8_t *)aux16;
for (int ibl = 0; ibl < k/QK_K; ++ibl) {
auto qs = (const uint16_t *)x[ibl].qs;
for (int ib = 0; ib < QK_K/32; ++ib) {
//uint8_t ls = ((qs[0] >> 30) | ((qs[1] >> 28) & 0x0c) | ((qs[2] >> 26) & 0x30) | ((qs[3] >> 24) & 0xc0));
//const int8_t * values = iq4k_values + ((ls & 1) << 4);
//const float dl = d * ((ls & 254) - 127);
//for (int k = 0; k < 4; ++k) {
// uint16_t vl = qs[k] & 0x7fff;
// vl ^= (vl << 1);
// uint16_t vh = (qs[k] >> 15) & 0x7fff;
// vh ^= (vh << 1);
// for (int j = 0; j < 4; ++j) {
// y[4*k + j + 0] = dl*values[(vl >> 4*j) & 0xf];
// y[4*k + j + 16] = dl*values[(vh >> 4*j) & 0xf];
// }
//}
int16_t ls = 0;
for (int k = 0; k < 8; ++k) {
aux16[k] = qs[k] & 0xfffe;
aux16[k] ^= (aux16[k] >> 1);
ls |= (qs[k] & 1) << k;
}
const int8_t * values = iq4k_values + ((ls & 1) << 4);
float dl = d * ((ls & 254) - 127);
for (int j = 0; j < 16; ++j) {
y[j+ 0] = dl * values[aux8[j] & 0xf];
y[j+16] = dl * values[aux8[j] >> 4];
}
y += 32;
qs += 8;
}
}
}
void vec_dot_iq4_kss_q8_k(int n, float * s, size_t bs, const void * vx, size_t bx, const void * vy, size_t by, int nrc) {
#if GGML_USE_IQK_MULMAT
if (iqk_mul_mat(1, 1, n, GGML_TYPE_IQ4_KSS, vx, 0, GGML_TYPE_Q8_K, vy, 0, s, 0, 0, 1)) {
return;
}
#endif
GGML_ASSERT(n%QK_K == 0);
GGML_ASSERT(nrc == 1);
GGML_UNUSED(bs);
GGML_UNUSED(bx);
GGML_UNUSED(by);
}
//
// ========================================= iq4_nl_r4
//
void quantize_row_iq4_nl_r4_ref(const float * x, block_iq4_nl_r4 * y, int64_t k) {
// we assume we are called with 4 rows
quantize_iq4_nl_r4(x, (void *)y, 4, k/4, nullptr);
}
void quantize_row_iq4_nl_r4(const float * x, void * y, int64_t k) {
// we assume we are called with 4 rows
quantize_iq4_nl_r4(x, y, 4, k/4, nullptr);
}
static void repack_iq4_nl(int nrows, int n_per_row, const block_iq4_nl * x, block_iq4_nl_r4 * y, [[maybe_unused]] bool online) {
GGML_ASSERT(nrows%4 == 0);
GGML_ASSERT(n_per_row%QK4_NL == 0);
int nblock = n_per_row/QK4_NL;
const block_iq4_nl * x4[4];
for (int row = 0; row < nrows; row += 4) {
for (int k = 0; k < 4; ++k) x4[k] = x + nblock*k;
for (int ib = 0; ib < nblock; ++ib) {
for (int k = 0; k < 4; ++k) y[ib].d[k] = x4[k][ib].d;
for (int k = 0; k < 4; ++k) for (int i = 0; i < 4; ++i) {
y[ib].qs[4*k+i+ 0] = (x4[k][ib].qs[i+0] & 0xf) | ((x4[k][ib].qs[i+ 8] & 0x0f) << 4); // 0....3 + 8...11 from each row
y[ib].qs[4*k+i+16] = (x4[k][ib].qs[i+0] >> 4) | ((x4[k][ib].qs[i+ 8] & 0xf0)); // 16...19 + 24...27 from each row
y[ib].qs[4*k+i+32] = (x4[k][ib].qs[i+4] & 0xf) | ((x4[k][ib].qs[i+12] & 0x0f) << 4); // 4....7 + 12...15 from each row
y[ib].qs[4*k+i+48] = (x4[k][ib].qs[i+4] >> 4) | ((x4[k][ib].qs[i+12] & 0xf0)); // 20...23 + 28...31 from each row
}
}
x += 4*nblock;
y += nblock;
}
}
size_t quantize_iq4_nl_r4(const float * src, void * dst, int64_t nrows, int64_t n_per_row, const float * imatrix) {
GGML_ASSERT(nrows%4 == 0);
auto row_size_nl = ggml_row_size(GGML_TYPE_IQ4_NL, n_per_row);
std::vector<char> qtmp(4*row_size_nl);
char * qrow = (char *)dst;
for (int row = 0; row < nrows; row += 4) {
quantize_iq4_nl(src, qtmp.data(), 4, n_per_row, imatrix);
repack_iq4_nl(4, n_per_row, (const block_iq4_nl *)qtmp.data(), (block_iq4_nl_r4 *)qrow, false);
src += 4*n_per_row;
qrow += 4*row_size_nl;
}
return nrows*row_size_nl;
}
void dequantize_row_iq4_nl_r4(const block_iq4_nl_r4 * x, float * y, int64_t k) {
// we assume we are called with 4 rows
int n_per_row = k/4;
int nb = n_per_row/QK4_NL;
float * yk[4];
for (int k = 0; k < 4; ++k) yk[k] = y + k*n_per_row;
for (int ib = 0; ib < nb; ++ib) {
for (int k = 0; k < 4; ++k) {
float scale = GGML_FP16_TO_FP32(x[ib].d[k]);
for (int i = 0; i < 4; ++i) {
yk[k][QK4_NL*ib+i+ 0] = scale * iq4k_values[x[ib].qs[4*k+i+ 0] & 0xf];
yk[k][QK4_NL*ib+i+ 8] = scale * iq4k_values[x[ib].qs[4*k+i+ 0] >> 4];
yk[k][QK4_NL*ib+i+16] = scale * iq4k_values[x[ib].qs[4*k+i+16] & 0xf];
yk[k][QK4_NL*ib+i+24] = scale * iq4k_values[x[ib].qs[4*k+i+16] >> 4];
yk[k][QK4_NL*ib+i+ 4] = scale * iq4k_values[x[ib].qs[4*k+i+32] & 0xf];
yk[k][QK4_NL*ib+i+12] = scale * iq4k_values[x[ib].qs[4*k+i+32] >> 4];
yk[k][QK4_NL*ib+i+20] = scale * iq4k_values[x[ib].qs[4*k+i+48] & 0xf];
yk[k][QK4_NL*ib+i+28] = scale * iq4k_values[x[ib].qs[4*k+i+48] >> 4];
}
}
}
}
void vec_dot_iq4_nl_r4_q8_0(int n, float * s, size_t bs, const void * vx, size_t bx, const void * vy, size_t by, int nrc) {
#if GGML_USE_IQK_MULMAT
if (iqk_mul_mat(1, 1, n, GGML_TYPE_IQ4_NL_R4, vx, 0, GGML_TYPE_Q8_0, vy, 0, s, 0, 0, 1)) {
return;
}
#endif
GGML_ASSERT(n%QK4_NL == 0);
GGML_ASSERT(nrc == 1);
GGML_UNUSED(bs);
GGML_UNUSED(bx);
GGML_UNUSED(by);
}
//
// ========================================= q4_0_r8
//
void quantize_row_q4_0_r8_ref(const float * x, block_iq4_nl_r8 * y, int64_t k) {
// we assume we are called with 8 rows
quantize_q4_0_r8(x, (void *)y, 8, k/8, nullptr);
}
void quantize_row_q4_0_r8(const float * x, void * y, int64_t k) {
// we assume we are called with 8 rows
quantize_q4_0_r8(x, y, 8, k/8, nullptr);
}
static void repack_q4_0(int nrows, int n_per_row, const block_q4_0 * x, block_iq4_nl_r8 * y, [[maybe_unused]] bool online) {
GGML_ASSERT(nrows%8 == 0);
GGML_ASSERT(n_per_row%QK4_0 == 0);
int nblock = n_per_row/QK4_0;
const block_q4_0 * x8[8];
for (int row = 0; row < nrows; row += 8) {
for (int k = 0; k < 8; ++k) x8[k] = x + nblock*k;
for (int ib = 0; ib < nblock; ++ib) {
for (int k = 0; k < 8; ++k) {
y[ib].d[k] = x8[k][ib].d;
for (int l = 0; l < 4; ++l) {
for (int i = 0; i < 4; ++i) {
y[ib].qs[32*l+4*k+i] = x8[k][ib].qs[4*l + i];
}
}
}
#ifdef __ARM_NEON
if (online) {
for (int l = 0; l < 8; ++l) {
auto v = vld1q_u8(y[ib].qs + 16*l);
vst1q_u8(y[ib].qs + 16*l, veorq_u8(v, vdupq_n_u8(0x88)));
}
}
#endif
}
x += 8*nblock;
y += nblock;
}
}
#ifdef __ARM_NEON
static void modify_q4_0_r8(int64_t k, char * cy) {
auto y = (block_iq4_nl_r8 *)cy;
int nb = k/(32*8);
for (int ib = 0; ib < nb; ++ib) {
auto v1 = vld1q_u8_x4(y[ib].qs);
auto v2 = vld1q_u8_x4(y[ib].qs+64);
for (int j = 0; j < 4; ++j) {
v1.val[j] = veorq_u8(v1.val[j], vdupq_n_u8(0x88));
v2.val[j] = veorq_u8(v2.val[j], vdupq_n_u8(0x88));
}
vst1q_u8_x4(y[ib].qs+ 0, v1);
vst1q_u8_x4(y[ib].qs+64, v2);
}
}
#endif
size_t quantize_q4_0_r8(const float * src, void * dst, int64_t nrows, int64_t n_per_row, const float * imatrix) {
GGML_ASSERT(nrows%8 == 0);
auto row_size_nl = ggml_row_size(GGML_TYPE_IQ4_NL, n_per_row);
std::vector<char> qtmp(8*row_size_nl);
char * qrow = (char *)dst;
for (int row = 0; row < nrows; row += 8) {
quantize_q4_0(src, qtmp.data(), 8, n_per_row, imatrix);
repack_q4_0(8, n_per_row, (const block_q4_0 *)qtmp.data(), (block_iq4_nl_r8 *)qrow, false);
src += 8*n_per_row;
qrow += 8*row_size_nl;
}
return nrows*row_size_nl;
}
void dequantize_row_q4_0_r8(const block_iq4_nl_r8 * x, float * y, int64_t k) {
// we assume we are called with 8 rows
int n_per_row = k/8;
int nb = n_per_row/QK4_0;
float * yk[8];
for (int k = 0; k < 8; ++k) yk[k] = y + k*n_per_row;
for (int ib = 0; ib < nb; ++ib) {
for (int k = 0; k < 8; ++k) {
float scale = GGML_FP16_TO_FP32(x[ib].d[k]);
for (int l = 0; l < 4; ++l) {
for (int i = 0; i < 4; ++i) {
yk[k][QK4_0*ib+4*l+i+ 0] = scale * ((x[ib].qs[32*l+4*k+i] & 0xf) - 8);
yk[k][QK4_0*ib+4*l+i+16] = scale * ((x[ib].qs[32*l+4*k+i] >> 4) - 8);
}
}
}
}
}
void vec_dot_q4_0_r8_q8_0(int n, float * s, size_t bs, const void * vx, size_t bx, const void * vy, size_t by, int nrc) {
#if GGML_USE_IQK_MULMAT
if (iqk_mul_mat(1, 1, n, GGML_TYPE_Q4_0_R8, vx, 0, GGML_TYPE_Q8_0, vy, 0, s, 0, 0, 1)) {
return;
}
#endif
GGML_ASSERT(n%QK4_NL == 0);
GGML_ASSERT(nrc == 1);
GGML_UNUSED(bs);
GGML_UNUSED(bx);
GGML_UNUSED(by);
}
//
// ========================================= q8_0_r8
//
void quantize_row_q8_0_r8_ref(const float * x, block_q8_0_r8 * y, int64_t k) {
// we assume we are called with 4 rows
quantize_q8_0_r8(x, (void *)y, 8, k/8, nullptr);
}
void quantize_row_q8_0_r8(const float * x, void * y, int64_t k) {
// we assume we are called with 4 rows
quantize_q8_0_r8(x, y, 8, k/8, nullptr);
}
static void repack_q8_0(int nrows, int n_per_row, const block_q8_0 * x, block_q8_0_r8 * y, [[maybe_unused]] bool online) {
GGML_ASSERT(nrows%8 == 0);
GGML_ASSERT(n_per_row%QK8_0 == 0);
int nblock = n_per_row/QK8_0;
const block_q8_0 * x8[8];
for (int row = 0; row < nrows; row += 8) {
for (int k = 0; k < 8; ++k) x8[k] = x + nblock*k;
for (int ib = 0; ib < nblock; ++ib) {
for (int k = 0; k < 8; ++k) y[ib].d[k] = x8[k][ib].d;
for (int l = 0; l < 4; ++l) {
for (int k = 0; k < 8; ++k) for (int i = 0; i < 4; ++i) {
y[ib].qs[32*l+4*k+i+ 0] = x8[k][ib].qs[i+4*l+ 0];
y[ib].qs[32*l+4*k+i+128] = x8[k][ib].qs[i+4*l+16];
}
}
#ifdef HAVE_FANCY_SIMD
if (online) {
for (int l = 0; l < 4; ++l) {
auto v = _mm512_add_epi8(_mm512_loadu_si512((const __m512i *)y[ib].qs + l), _mm512_set1_epi8(127));
_mm512_storeu_si512((__m512i *)y[ib].qs + l, v);
}
}
#endif
}
x += 8*nblock;
y += nblock;
}
}
#ifdef HAVE_FANCY_SIMD
static void modify_q8_0_r8(int64_t k, char * cy) {
auto y = (block_q8_0_r8 *)cy;
int nb = k/(32*8);
for (int ib = 0; ib < nb; ++ib) {
for (int l = 0; l < 4; ++l) {
auto v = _mm512_add_epi8(_mm512_loadu_si512((const __m512i *)y[ib].qs + l), _mm512_set1_epi8(127));
_mm512_storeu_si512((__m512i *)y[ib].qs + l, v);
}
}
}
#endif
size_t quantize_q8_0_r8(const float * src, void * dst, int64_t nrows, int64_t n_per_row, const float * imatrix) {
GGML_ASSERT(nrows%8 == 0);
auto row_size_0 = ggml_row_size(GGML_TYPE_Q8_0, n_per_row);
std::vector<char> qtmp(8*row_size_0);
char * qrow = (char *)dst;
for (int row = 0; row < nrows; row += 8) {
quantize_q8_0(src, qtmp.data(), 8, n_per_row, imatrix);
repack_q8_0(8, n_per_row, (const block_q8_0 *)qtmp.data(), (block_q8_0_r8 *)qrow, false);
src += 8*n_per_row;
qrow += 8*row_size_0;
}
return nrows*row_size_0;
}
void dequantize_row_q8_0_r8(const block_q8_0_r8 * x, float * y, int64_t k) {
// we assume we are called with 4 rows
int n_per_row = k/8;
int nb = n_per_row/QK8_0;
float * yk[8];
for (int k = 0; k < 8; ++k) yk[k] = y + k*n_per_row;
for (int ib = 0; ib < nb; ++ib) {
for (int k = 0; k < 8; ++k) {
float scale = GGML_FP16_TO_FP32(x[ib].d[k]);
for (int l = 0; l < 4; ++l) for (int i = 0; i < 4; ++i) {
yk[k][QK8_0*ib+4*l+i+ 0] = scale * x[ib].qs[32*l+4*k+i+ 0];
yk[k][QK8_0*ib+4*l+i+16] = scale * x[ib].qs[32*l+4*k+i+128];
}
}
}
}
void vec_dot_q8_0_r8_q8_0(int n, float * s, size_t bs, const void * vx, size_t bx, const void * vy, size_t by, int nrc) {
#if GGML_USE_IQK_MULMAT
if (iqk_mul_mat(1, 1, n, GGML_TYPE_Q8_0_R8, vx, 0, GGML_TYPE_Q8_0, vy, 0, s, 0, 0, 1)) {
return;
}
#endif
GGML_ASSERT(n%QK4_NL == 0);
GGML_ASSERT(nrc == 1);
GGML_UNUSED(bs);
GGML_UNUSED(bx);
GGML_UNUSED(by);
}
//
// ========================================= q5_0_r4
//
void quantize_row_q5_0_r4_ref(const float * x, block_q5_0_r4 * y, int64_t k) {
// we assume we are called with 4 rows
quantize_q5_0_r4(x, (void *)y, 4, k/4, nullptr);
}
void quantize_row_q5_0_r4(const float * x, void * y, int64_t k) {
// we assume we are called with 4 rows
quantize_q5_0_r4(x, y, 4, k/4, nullptr);
}
static inline void convert_q5_0(const block_q5_0& x, uint8_t * L) {
uint32_t qh;
memcpy(&qh, x.qh, sizeof(qh));
for (int j = 0; j < QK5_0/2; ++j) {
const uint8_t xh_0 = ((qh >> (j + 0)) << 4) & 0x10;
const uint8_t xh_1 = ((qh >> (j + 12)) ) & 0x10;
L[j ] = (x.qs[j] & 0x0F) | xh_0;
L[j + QK4_0/2] = (x.qs[j] >> 4) | xh_1;
}
}
static void repack_q5_0(int nrows, int n_per_row, const block_q5_0 * x, block_q5_0_r4 * y, [[maybe_unused]] bool online) {
GGML_ASSERT(nrows%4 == 0);
GGML_ASSERT(n_per_row%QK5_0 == 0);
int nblock = n_per_row/QK5_0;
const block_q5_0 * x4[4];
uint8_t L[QK5_0];
for (int row = 0; row < nrows; row += 4) {
for (int k = 0; k < 4; ++k) x4[k] = x + nblock*k;
for (int ib = 0; ib < nblock; ++ib) {
std::memset(y[ib].qh, 0, QK5_0/2);
for (int k = 0; k < 4; ++k) {
y[ib].d[k] = x4[k][ib].d;
convert_q5_0(x4[k][ib], L);
for (int l = 0; l < 4; ++l) {
int l1 = 4*(l/2) + 16*(l%2), l2 = l1 + 8;
for (int i = 0; i < 4; ++i) {
y[ib].qs[4*k+i+16*l] = (L[i + l1] & 0xf) | ((L[i + l2] & 0xf) << 4);
y[ib].qh[4*k+i] |= ((L[i + l1] >> 4) | ((L[i + l2] >> 4) << 4)) << l;
}
}
}
}
x += 4*nblock;
y += nblock;
}
}
size_t quantize_q5_0_r4(const float * src, void * dst, int64_t nrows, int64_t n_per_row, const float * imatrix) {
GGML_ASSERT(nrows%4 == 0);
auto row_size_0 = ggml_row_size(GGML_TYPE_Q5_0, n_per_row);
std::vector<char> qtmp(4*row_size_0);
char * qrow = (char *)dst;
for (int row = 0; row < nrows; row += 4) {
quantize_q5_0(src, qtmp.data(), 4, n_per_row, imatrix);
repack_q5_0(4, n_per_row, (const block_q5_0 *)qtmp.data(), (block_q5_0_r4 *)qrow, false);
src += 4*n_per_row;
qrow += 4*row_size_0;
}
return nrows*row_size_0;
}
void dequantize_row_q5_0_r4(const block_q5_0_r4 * x, float * y, int64_t k) {
// we assume we are called with 4 rows
int n_per_row = k/4;
int nb = n_per_row/QK8_0;
float * yk[4];
for (int k = 0; k < 4; ++k) yk[k] = y + k*n_per_row;
for (int ib = 0; ib < nb; ++ib) {
for (int k = 0; k < 4; ++k) {
float d = GGML_FP16_TO_FP32(x[ib].d[k]);
float m = -16*d;
for (int l = 0; l < 4; ++l) {
int ll = 16*(l%2) + 4*(l/2);
for (int i = 0; i < 4; ++i) {
yk[k][QK4_0*ib+i+ll+0] = d * ((x[ib].qs[4*k+i+16*l] & 0xf) | (((x[ib].qh[4*k+i] >> (l+0)) & 1) << 4)) + m;
yk[k][QK4_0*ib+i+ll+8] = d * ((x[ib].qs[4*k+i+16*l] >> 4) | (((x[ib].qh[4*k+i] >> (l+4)) & 1) << 4)) + m;
}
}
}
}
}
void vec_dot_q5_0_r4_q8_0(int n, float * s, size_t bs, const void * vx, size_t bx, const void * vy, size_t by, int nrc) {
#if GGML_USE_IQK_MULMAT
if (iqk_mul_mat(1, 1, n, GGML_TYPE_Q5_0_R4, vx, 0, GGML_TYPE_Q8_0, vy, 0, s, 0, 0, 1)) {
return;
}
#endif
GGML_ASSERT(n%QK4_NL == 0);
GGML_ASSERT(nrc == 1);
GGML_UNUSED(bs);
GGML_UNUSED(bx);
GGML_UNUSED(by);
}
//
// ========================================= q6_0_r4
//
void quantize_row_q6_0_r4_ref(const float * x, block_q6_0_r4 * y, int64_t k) {
// we assume we are called with 4 rows
quantize_q6_0_r4(x, (void *)y, 4, k/4, nullptr);
}
void quantize_row_q6_0_r4(const float * x, void * y, int64_t k) {
// we assume we are called with 4 rows
quantize_q6_0_r4(x, y, 4, k/4, nullptr);
}
static inline void convert_q6_0(const block_q6_0& x, uint8_t * L) {
for (int j = 0; j < QK6_0/2; ++j) {
const uint8_t h = x.qh[j%(QK6_0/4)] >> 4*(j/(QK6_0/4));
L[j ] = (x.qs[j] & 0x0F) | ((h << 4) & 0x30);
L[j + QK6_0/2] = (x.qs[j] >> 4) | ((h << 2) & 0x30);
}
}
static void repack_q6_0(int nrows, int n_per_row, const block_q6_0 * x, block_q6_0_r4 * y, [[maybe_unused]] bool online) {
GGML_ASSERT(nrows%4 == 0);
GGML_ASSERT(n_per_row%QK5_0 == 0);
int nblock = n_per_row/QK6_0;
const block_q6_0 * x4[4];
uint8_t L[QK6_0];
for (int row = 0; row < nrows; row += 4) {
for (int k = 0; k < 4; ++k) x4[k] = x + nblock*k;
for (int ib = 0; ib < nblock; ++ib) {
std::memset(y[ib].qh, 0, QK6_0);
for (int k = 0; k < 4; ++k) {
y[ib].d[k] = x4[k][ib].d;
convert_q6_0(x4[k][ib], L);
for (int l = 0; l < 4; ++l) {
int l1 = 4*(l/2) + 16*(l%2), l2 = l1 + 8;
for (int i = 0; i < 4; ++i) {
y[ib].qs[4*k+i+16*l] = (L[i + l1] & 0xf) | ((L[i + l2] & 0xf) << 4);
y[ib].qh[4*k+i+16*(l%2)] |= ((L[i + l1] >> 4) | ((L[i + l2] >> 4) << 4)) << 2*(l/2);
}
}
}
}
x += 4*nblock;
y += nblock;
}
}
size_t quantize_q6_0_r4(const float * src, void * dst, int64_t nrows, int64_t n_per_row, const float * imatrix) {
GGML_ASSERT(nrows%4 == 0);
auto row_size_0 = ggml_row_size(GGML_TYPE_Q6_0, n_per_row);
std::vector<char> qtmp(4*row_size_0);
char * qrow = (char *)dst;
for (int row = 0; row < nrows; row += 4) {
quantize_q6_0(src, qtmp.data(), 4, n_per_row, imatrix);
repack_q6_0(4, n_per_row, (const block_q6_0 *)qtmp.data(), (block_q6_0_r4 *)qrow, false);
src += 4*n_per_row;
qrow += 4*row_size_0;
}
return nrows*row_size_0;
}
void dequantize_row_q6_0_r4(const block_q6_0_r4 * x, float * y, int64_t k) {
// we assume we are called with 4 rows
int n_per_row = k/4;
int nb = n_per_row/QK6_0;
float * yk[4];
for (int k = 0; k < 4; ++k) yk[k] = y + k*n_per_row;
for (int ib = 0; ib < nb; ++ib) {
for (int k = 0; k < 4; ++k) {
float d = GGML_FP16_TO_FP32(x[ib].d[k]);
float m = -32*d;
for (int l = 0; l < 4; ++l) {
int ll = 16*(l%2) + 4*(l/2);
for (int i = 0; i < 4; ++i) {
yk[k][QK4_0*ib+i+ll+0] = d * ((x[ib].qs[4*k+i+16*l] & 0xf) | (((x[ib].qh[4*k+i+16*(l%2)] >> (2*(l/2)+0)) & 3) << 4)) + m;
yk[k][QK4_0*ib+i+ll+8] = d * ((x[ib].qs[4*k+i+16*l] >> 4) | (((x[ib].qh[4*k+i+16*(l%2)] >> (2*(l/2)+4)) & 3) << 4)) + m;
}
}
}
}
}
void vec_dot_q6_0_r4_q8_0(int n, float * s, size_t bs, const void * vx, size_t bx, const void * vy, size_t by, int nrc) {
#if GGML_USE_IQK_MULMAT
if (iqk_mul_mat(1, 1, n, GGML_TYPE_Q6_0_R4, vx, 0, GGML_TYPE_Q8_0, vy, 0, s, 0, 0, 1)) {
return;
}
#endif
GGML_ASSERT(n%QK4_NL == 0);
GGML_ASSERT(nrc == 1);
GGML_UNUSED(bs);
GGML_UNUSED(bx);
GGML_UNUSED(by);
}
//
// ========================================= iq4_xs_r8
//
void quantize_row_iq4_xs_r8_ref(const float * x, block_iq4_xs_r8 * y, int64_t k) {
quantize_iq4_xs_r8(x, (void *)y, 8, k/8, nullptr);
}
void quantize_row_iq4_xs_r8(const float * x, void * y, int64_t k) {
quantize_iq4_xs_r8(x, y, 8, k/8, nullptr);
}
static void repack_iq4_xs(int nrows, int n_per_row, const block_iq4_xs * x, block_iq4_xs_r8 * y, [[maybe_unused]] bool online) {
GGML_ASSERT(nrows%8 == 0);
GGML_ASSERT(n_per_row%QK_K == 0);
int nblock = n_per_row/QK_K;
const block_iq4_xs * x8[8];
for (int row = 0; row < nrows; row += 8) {
for (int k = 0; k < 8; ++k) x8[k] = x + nblock*k;
for (int ibl = 0; ibl < nblock; ++ibl) {
std::memset(y[ibl].scales_l, 0, QK_K/8);
std::memset(y[ibl].scales_h, 0, QK_K/16);
for (int k = 0; k < 8; ++k) {
y[ibl].d[k] = x8[k][ibl].d;
for (int ib = 0; ib < QK_K/32; ++ib) {
uint8_t sl = (x8[k][ibl].scales_l[ib/2] >> 4*(ib%2)) & 0xf;
uint8_t sh = (x8[k][ibl].scales_h >> 2*ib) & 3;
int i = 8*ib + k;
y[ibl].scales_l[i%32] |= (sl << 4*(i/32));
y[ibl].scales_h[i%16] |= (sh << 2*(i/16));
for (int i = 0; i < 4; ++i) {
y[ibl].qs[128*ib+4*k+i+ 0] = (x8[k][ibl].qs[16*ib+i+0] & 0xf) | ((x8[k][ibl].qs[16*ib+i+ 4] & 0xf) << 4);
y[ibl].qs[128*ib+4*k+i+32] = (x8[k][ibl].qs[16*ib+i+8] & 0xf) | ((x8[k][ibl].qs[16*ib+i+12] & 0xf) << 4);
y[ibl].qs[128*ib+4*k+i+64] = (x8[k][ibl].qs[16*ib+i+0] >> 4) | ((x8[k][ibl].qs[16*ib+i+ 4] >> 4) << 4);
y[ibl].qs[128*ib+4*k+i+96] = (x8[k][ibl].qs[16*ib+i+8] >> 4) | ((x8[k][ibl].qs[16*ib+i+12] >> 4) << 4);
}
}
}
}
x += 8*nblock;
y += nblock;
}
}
size_t quantize_iq4_xs_r8(const float * src, void * dst, int64_t nrows, int64_t n_per_row, const float * imatrix) {
GGML_ASSERT(nrows%8 == 0);
GGML_ASSERT(n_per_row%QK_K == 0);
char * qcur = (char *)dst;
auto row_size = ggml_row_size(GGML_TYPE_IQ4_XS, n_per_row);
std::vector<char> qtmp(8*row_size);
for (int row = 0; row < nrows; row += 8) {
quantize_iq4_xs(src, (void *)qtmp.data(), 8, n_per_row, imatrix);
repack_iq4_xs(8, n_per_row, (const block_iq4_xs *)qtmp.data(), (block_iq4_xs_r8 *)qcur, false);
qcur += 8*row_size;
src += 8*n_per_row;
}
return nrows*row_size;
}
void dequantize_row_iq4_xs_r8(const block_iq4_xs_r8 * x, float * y, int64_t k) {
auto n_per_row = k/8;
float * y8[8];
for (int k = 0; k < 8; ++k) y8[k] = y + n_per_row*k;
int nblock = n_per_row/QK_K;
for (int ibl = 0; ibl < nblock; ++ibl) {
for (int k = 0; k < 8; ++k) {
const float d = GGML_FP16_TO_FP32(x[ibl].d[k]);
for (int ib = 0; ib < QK_K/32; ++ib) {
int is = 8*ib + k;
float dl = d * ((((x[ibl].scales_l[is%32] >> 4*(is/32)) & 0xf) | (((x[ibl].scales_h[is%16] >> 2*(is/16)) & 3) << 4)) - 32);
for (int l = 0; l < 4; ++l) for (int i = 0; i < 4; ++i) {
y8[k][QK_K*ibl+32*ib+8*l+i+0] = dl * iq4k_values[x[ibl].qs[128*ib+4*k+i+32*l] & 0xf];
y8[k][QK_K*ibl+32*ib+8*l+i+4] = dl * iq4k_values[x[ibl].qs[128*ib+4*k+i+32*l] >> 4];
}
}
}
}
}
void vec_dot_iq4_xs_r8_q8_k(int n, float * s, size_t bs, const void * vx, size_t bx, const void * vy, size_t by, int nrc) {
#if GGML_USE_IQK_MULMAT
if (iqk_mul_mat(1, 1, n, GGML_TYPE_IQ4_XS_R8, vx, 0, GGML_TYPE_Q8_K, vy, 0, s, 0, 0, 1)) {
return;
}
#endif
GGML_ASSERT(n%QK4_NL == 0);
GGML_ASSERT(nrc == 1);
GGML_UNUSED(bs);
GGML_UNUSED(bx);
GGML_UNUSED(by);
}
//
// ========================================= iq4_ks_r4
//
void quantize_row_iq4_ks_r4_ref(const float * x, block_iq4_ks_r4 * y, int64_t k) {
quantize_iq4_ks_r4(x, (void *)y, 4, k/4, nullptr);
}
void quantize_row_iq4_ks_r4(const float * x, void * y, int64_t k) {
quantize_iq4_ks_r4(x, y, 4, k/4, nullptr);
}
static void repack_iq4_ks(int nrows, int n_per_row, const block_iq4_ks * x, block_iq4_ks_r4 * y, [[maybe_unused]] bool online) {
GGML_ASSERT(nrows%4 == 0);
GGML_ASSERT(n_per_row%QK_K == 0);
auto row_size = ggml_row_size(GGML_TYPE_IQ4_KS, n_per_row);
int nblock = n_per_row/QK_K;
char * cy = (char *)y;
const char * cx = (const char *)x;
const block_iq4_ks * x4[4];
for (int row = 0; row < nrows; row += 4) {
float * dptr = (float *)cy;
block_iq4_ks_r4 * y = (block_iq4_ks_r4 *)(dptr + 4);
for (int k = 0; k < 4; ++k) {
auto dk = (const float *)(cx + k*row_size);
dptr[k] = dk[0];
x4[k] = (const block_iq4_ks *)(dk + 1);
}
for (int ibl = 0; ibl < nblock; ++ibl) {
for (int k = 0; k < 4; ++k) {
for (int ib = 0; ib < QK_K/32; ++ib) {
y[ibl].scales[4*ib+k] = x4[k][ibl].scales[ib];
for (int i = 0; i < 4; ++i) {
y[ibl].qs[64*ib+4*k+i+ 0] = (x4[k][ibl].qs[16*ib+i+0] & 0xf) | ((x4[k][ibl].qs[16*ib+i+ 8] & 0x0f) << 4); // 0....3 + 8...11 from each row
y[ibl].qs[64*ib+4*k+i+16] = (x4[k][ibl].qs[16*ib+i+0] >> 4) | ((x4[k][ibl].qs[16*ib+i+ 8] & 0xf0)); // 16...19 + 24...27 from each row
y[ibl].qs[64*ib+4*k+i+32] = (x4[k][ibl].qs[16*ib+i+4] & 0xf) | ((x4[k][ibl].qs[16*ib+i+12] & 0x0f) << 4); // 4....7 + 12...15 from each row
y[ibl].qs[64*ib+4*k+i+48] = (x4[k][ibl].qs[16*ib+i+4] >> 4) | ((x4[k][ibl].qs[16*ib+i+12] & 0xf0)); // 20...23 + 28...31 from each row
}
}
}
}
cx += 4*row_size;
cy += 4*row_size;
}
}
size_t quantize_iq4_ks_r4(const float * src, void * dst, int64_t nrows, int64_t n_per_row, const float * imatrix) {
GGML_ASSERT(nrows%4 == 0);
GGML_ASSERT(n_per_row%QK_K == 0);
char * qcur = (char *)dst;
auto row_size = ggml_row_size(GGML_TYPE_IQ4_KS, n_per_row);
std::vector<char> qtmp(4*row_size);
for (int row = 0; row < nrows; row += 4) {
quantize_iq4_ks(src, (void *)qtmp.data(), 4, n_per_row, imatrix);
repack_iq4_ks(4, n_per_row, (const block_iq4_ks *)qtmp.data(), (block_iq4_ks_r4 *)qcur, false);
qcur += 4*row_size;
src += 4*n_per_row;
}
return nrows*row_size;
}
void dequantize_row_iq4_ks_r4(const block_iq4_ks_r4 * x, float * y, int64_t k) {
auto n_per_row = k/4;
float * y4[4] = {y, y + n_per_row, y + 2*n_per_row, y + 3*n_per_row};
int nblock = n_per_row/QK_K;
const float * dptr = (const float *)x;
x = (const block_iq4_ks_r4 *)(dptr + 4);
for (int ibl = 0; ibl < nblock; ++ibl) {
for (int k = 0; k < 4; ++k) {
const float d = dptr[k];
for (int ib = 0; ib < QK_K/32; ++ib) {
float dl = d * ((x[ibl].scales[4*ib + k] & 254) - 127);
auto values = iq4k_values + ((x[ibl].scales[4*ib + k] & 1) << 4);
for (int i = 0; i < 4; ++i) {
y4[k][QK_K*ibl+32*ib+i+ 0] = dl * values[x[ibl].qs[64*ib+4*k+i+ 0] & 0xf];
y4[k][QK_K*ibl+32*ib+i+ 8] = dl * values[x[ibl].qs[64*ib+4*k+i+ 0] >> 4];
y4[k][QK_K*ibl+32*ib+i+16] = dl * values[x[ibl].qs[64*ib+4*k+i+16] & 0xf];
y4[k][QK_K*ibl+32*ib+i+24] = dl * values[x[ibl].qs[64*ib+4*k+i+16] >> 4];
y4[k][QK_K*ibl+32*ib+i+ 4] = dl * values[x[ibl].qs[64*ib+4*k+i+32] & 0xf];
y4[k][QK_K*ibl+32*ib+i+12] = dl * values[x[ibl].qs[64*ib+4*k+i+32] >> 4];
y4[k][QK_K*ibl+32*ib+i+20] = dl * values[x[ibl].qs[64*ib+4*k+i+48] & 0xf];
y4[k][QK_K*ibl+32*ib+i+28] = dl * values[x[ibl].qs[64*ib+4*k+i+48] >> 4];
}
}
}
}
}
void vec_dot_iq4_ks_r4_q8_k(int n, float * s, size_t bs, const void * vx, size_t bx, const void * vy, size_t by, int nrc) {
#if GGML_USE_IQK_MULMAT
if (iqk_mul_mat(1, 1, n, GGML_TYPE_IQ4_KS_R4, vx, 0, GGML_TYPE_Q8_K, vy, 0, s, 0, 0, 1)) {
return;
}
#endif
GGML_ASSERT(n%QK4_NL == 0);
GGML_ASSERT(nrc == 1);
GGML_UNUSED(bs);
GGML_UNUSED(bx);
GGML_UNUSED(by);
}
//
// ========================================= iq2_bn_r4
//
void quantize_row_iq2_bn_r4_ref(const float * x, block_iq2_bn * y, int64_t k) {
quantize_iq2_bn_r4(x, (void *)y, 4, k/4, nullptr);
}
void quantize_row_iq2_bn_r4(const float * x, void * y, int64_t k) {
quantize_iq2_bn_r4(x, y, 4, k/4, nullptr);
}
namespace {
void repack_iq2_bn(int nrows, int n_per_row, const char * x, char * y, [[maybe_unused]] bool online) {
GGML_ASSERT(nrows%4 == 0);
GGML_ASSERT(n_per_row%QK_IQ1BN == 0);
int nblock = n_per_row/QK_IQ1BN;
auto row_size = ggml_row_size(GGML_TYPE_IQ2_BN, n_per_row);
const uint8_t * x4[4];
for (int row = 0; row < nrows; row += 4) {
float * dr4 = (float *)(y + 4*row*row_size);
for (int k = 0; k < 4; ++k) {
const float * dptr = (const float *)(x + (row + k)*row_size);
dr4[k] = *dptr;
x4[k] = (const uint8_t *)(dptr + 1);
}
uint8_t * y4 = (uint8_t *)(dr4 + 4);
//std::memset(y4, 0, n_per_row);
for (int ib = 0; ib < nblock; ++ib) {
// 0...3 from rows 0...3 go to 1st 2 bits of 0...15
// 16..19 from rows 0...3 go to 1st 2 bits of 16...31
// 32..35 from rows 0...3 go to 1st 2 bits of 32...47
// 48..51 from rows 0...3 go to 1st 2 bits of 48...63
// 4...7 from rows 0...3 go to 2nd 2 bits of 0...15
// 20..23 from rows 0...3 go to 2nd 2 bits of 16...31
// 36..39 from rows 0...3 go to 2nd 2 bits of 32...47
// 52..55 from rows 0...3 go to 2nd 2 bits of 48...63
// 8..11 from rows 0...3 go to 3rd 2 bits of 0...15
// 24..27 from rows 0...3 go to 3rd 2 bits of 16...31
// 40..43 from rows 0...3 go to 3rd 2 bits of 32...47
// 56..59 from rows 0...3 go to 3rd 2 bits of 48...63
// 12..15 from rows 0...3 go to 4th 2 bits of 0...15
// 28..31 from rows 0...3 go to 4th 2 bits of 16...31
// 44..47 from rows 0...3 go to 4th 2 bits of 32...47
// 60..63 from rows 0...3 go to 4th 2 bits of 48...63
for (int k = 0; k < 4; ++k) {
for (int l = 0; l < 4; ++l) for (int i = 0; i < 4; ++i) {
y4[64*ib + 4*k + i + 16*l] = (((x4[k][16*ib + i + 0] >> 2*l) & 3) << 0) |
(((x4[k][16*ib + i + 4] >> 2*l) & 3) << 2) |
(((x4[k][16*ib + i + 8] >> 2*l) & 3) << 4) |
(((x4[k][16*ib + i + 12] >> 2*l) & 3) << 6);
//y4[64*ib + 4*k + i + 0] |= (x4[k][16*ib + i] >> 0) & 3;
//y4[64*ib + 4*k + i + 16] |= (x4[k][16*ib + i] >> 2) & 3;
//y4[64*ib + 4*k + i + 32] |= (x4[k][16*ib + i] >> 4) & 3;
//y4[64*ib + 4*k + i + 48] |= (x4[k][16*ib + i] >> 6) & 3;
//y4[64*ib + 4*k + i + 0] |= ((x4[k][16*ib + i + 4] >> 0) & 3) << 2;
//y4[64*ib + 4*k + i + 16] |= ((x4[k][16*ib + i + 4] >> 2) & 3) << 2;
//y4[64*ib + 4*k + i + 32] |= ((x4[k][16*ib + i + 4] >> 4) & 3) << 2;
//y4[64*ib + 4*k + i + 48] |= ((x4[k][16*ib + i + 4] >> 6) & 3) << 2;
//y4[64*ib + 4*k + i + 0] |= ((x4[k][16*ib + i + 8] >> 0) & 3) << 4;
//y4[64*ib + 4*k + i + 16] |= ((x4[k][16*ib + i + 8] >> 2) & 3) << 4;
//y4[64*ib + 4*k + i + 32] |= ((x4[k][16*ib + i + 8] >> 4) & 3) << 4;
//y4[64*ib + 4*k + i + 48] |= ((x4[k][16*ib + i + 8] >> 6) & 3) << 4;
//y4[64*ib + 4*k + i + 0] |= ((x4[k][16*ib + i + 12] >> 0) & 3) << 6;
//y4[64*ib + 4*k + i + 16] |= ((x4[k][16*ib + i + 12] >> 2) & 3) << 6;
//y4[64*ib + 4*k + i + 32] |= ((x4[k][16*ib + i + 12] >> 4) & 3) << 6;
//y4[64*ib + 4*k + i + 48] |= ((x4[k][16*ib + i + 12] >> 6) & 3) << 6;
}
}
}
}
}
}
size_t quantize_iq2_bn_r4(const float * src, void * dst, int64_t nrows, int64_t n_per_row, const float * imatrix) {
GGML_ASSERT(nrows%4 == 0);
GGML_ASSERT(n_per_row%QK_IQ1BN == 0);
char * qcur = (char *)dst;
auto row_size = ggml_row_size(GGML_TYPE_IQ2_BN, n_per_row);
std::vector<char> qtmp(4*row_size);
for (int row = 0; row < nrows; row += 4) {
quantize_iq2_bn(src, (void *)qtmp.data(), 4, n_per_row, imatrix);
repack_iq2_bn(4, n_per_row, qtmp.data(), qcur, false);
qcur += 4*row_size;
src += 4*n_per_row;
}
return nrows*row_size;
}
void dequantize_row_iq2_bn_r4(const block_iq2_bn * x, float * y, int64_t k) {
static_assert(QK_IQ1BN == 64);
auto n_per_row = k/4;
float * y4[4] = {y, y + n_per_row, y + 2*n_per_row, y + 3*n_per_row};
const float * d4 = (const float *)x;
const uint8_t * qx = (const uint8_t *)(d4 + 4);
int nblock = n_per_row/QK_IQ1BN;
for (int ib = 0; ib < nblock; ++ib) {
for (int k = 0; k < 4; ++k) {
for (int l = 0; l < 4; ++l) for (int i = 0; i < 4; ++i) {
uint8_t q = qx[4*k + i + 16*l];
y4[k][64*ib + 16*l + i + 0] = d4[k] * (((q >> 0) & 3) - 1);
y4[k][64*ib + 16*l + i + 4] = d4[k] * (((q >> 2) & 3) - 1);
y4[k][64*ib + 16*l + i + 8] = d4[k] * (((q >> 4) & 3) - 1);
y4[k][64*ib + 16*l + i + 12] = d4[k] * (((q >> 6) & 3) - 1);
}
}
qx += 64;
}
}
void vec_dot_iq2_bn_r4_q8_K64(int n, float * s, size_t bs, const void * vx, size_t bx, const void * vy, size_t by, int nrc) {
#if GGML_USE_IQK_MULMAT
if (iqk_mul_mat(1, 1, n, GGML_TYPE_IQ2_BN_R4, vx, 0, GGML_TYPE_Q8_K64, vy, 0, s, 0, 0, 1)) {
return;
}
#endif
GGML_ASSERT(n%QK4_NL == 0);
GGML_ASSERT(nrc == 1);
GGML_UNUSED(bs);
GGML_UNUSED(bx);
GGML_UNUSED(by);
}
//
// ========================================= q4_k_r4
//
void quantize_row_q4_k_r4_ref(const float * x, block_q4_k_r4 * y, int64_t k) {
quantize_q4_k_r4(x, (void *)y, 4, k/4, nullptr);
}
void quantize_row_q4_k_r4(const float * x, void * y, int64_t k) {
quantize_q4_k_r4(x, y, 4, k/4, nullptr);
}
namespace {
inline void get_scale_min_k4(int j, const uint8_t * q, uint8_t& d, uint8_t& 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);
}
}
inline void convert_q4_k(const block_q4_K& x, uint8_t * L, uint8_t * Ld, uint8_t * Lm) {
for (int ib64 = 0; ib64 < QK_K/64; ++ib64) {
get_scale_min_k4(2*ib64+0, x.scales, Ld[2*ib64+0], Lm[2*ib64+0]);
get_scale_min_k4(2*ib64+1, x.scales, Ld[2*ib64+1], Lm[2*ib64+1]);
for (int j = 0; j < 32; ++j) {
L[64*ib64+j+ 0] = x.qs[32*ib64+j] & 0xf;
L[64*ib64+j+32] = x.qs[32*ib64+j] >> 4;
}
}
}
}
static void repack_q4_k(int nrows, int n_per_row, const block_q4_K * x, block_q4_k_r4 * y, [[maybe_unused]] bool online) {
GGML_ASSERT(nrows%4 == 0);
GGML_ASSERT(n_per_row%QK_K == 0);
int nblock = n_per_row/QK_K;
const block_q4_K * x4[4];
uint8_t L[QK_K], Ld[QK_K/32], Lm[QK_K/32];
for (int row = 0; row < nrows; row += 4) {
for (int k = 0; k < 4; ++k) x4[k] = x + nblock*k;
for (int ibl = 0; ibl < nblock; ++ibl) {
std::memset(y[ibl].scales_l, 0, QK_K/8);
std::memset(y[ibl].scales_h, 0, QK_K/16);
for (int k = 0; k < 4; ++k) {
y[ibl].d[k+0] = x4[k][ibl].d;
y[ibl].d[k+4] = x4[k][ibl].dmin;
convert_q4_k(x4[k][ibl], L, Ld, Lm);
for (int ib = 0; ib < QK_K/32; ++ib) {
y[ibl].scales_l[4*ib+k] = (Ld[ib] & 0xf) | ((Lm[ib] & 0xf) << 4);
uint8_t h = (Ld[ib] >> 4) | ((Lm[ib] >> 4) << 2);
y[ibl].scales_h[(4*ib+k)%16] |= (h << 4*((4*ib+k)/16));
for (int i = 0; i < 4; ++i) {
y[ibl].qs[64*ib+4*k+i+ 0] = L[32*ib+i+ 0] | (L[32*ib+i+ 8] << 4);
y[ibl].qs[64*ib+4*k+i+16] = L[32*ib+i+16] | (L[32*ib+i+24] << 4);
y[ibl].qs[64*ib+4*k+i+32] = L[32*ib+i+ 4] | (L[32*ib+i+12] << 4);
y[ibl].qs[64*ib+4*k+i+48] = L[32*ib+i+20] | (L[32*ib+i+28] << 4);
}
}
}
}
x += 4*nblock;
y += nblock;
}
}
size_t quantize_q4_k_r4(const float * src, void * dst, int64_t nrows, int64_t n_per_row, const float * imatrix) {
GGML_ASSERT(nrows%4 == 0);
GGML_ASSERT(n_per_row%QK_K == 0);
char * qcur = (char *)dst;
auto row_size = ggml_row_size(GGML_TYPE_Q4_K, n_per_row);
std::vector<char> qtmp(4*row_size);
for (int row = 0; row < nrows; row += 4) {
quantize_q4_K(src, (void *)qtmp.data(), 4, n_per_row, imatrix);
repack_q4_k(4, n_per_row, (const block_q4_K *)qtmp.data(), (block_q4_k_r4 *)qcur, false);
qcur += 4*row_size;
src += 4*n_per_row;
}
return nrows*row_size;
}
void dequantize_row_q4_k_r4(const block_q4_k_r4 * x, float * y, int64_t k) {
auto n_per_row = k/4;
float * y4[4] = {y, y + n_per_row, y + 2*n_per_row, y + 3*n_per_row};
int nblock = n_per_row/QK_K;
for (int ibl = 0; ibl < nblock; ++ibl) {
for (int k = 0; k < 4; ++k) {
const float d = GGML_FP16_TO_FP32(x[ibl].d[k+0]);
const float m = GGML_FP16_TO_FP32(x[ibl].d[k+4]);
for (int ib = 0; ib < QK_K/32; ++ib) {
int is = 4*ib + k;
float dl = d * ((x[ibl].scales_l[is] & 0xf) | (((x[ibl].scales_h[is%16] >> 4*(is/16)) & 0x03) << 4));
float ml = m * ((x[ibl].scales_l[is] >> 4) | (((x[ibl].scales_h[is%16] >> 4*(is/16)) & 0x0c) << 2));
for (int i = 0; i < 4; ++i) {
y4[k][QK_K*ibl+32*ib+i+ 0] = dl * (x[ibl].qs[64*ib+4*k+i+ 0] & 0xf) - ml;
y4[k][QK_K*ibl+32*ib+i+ 8] = dl * (x[ibl].qs[64*ib+4*k+i+ 0] >> 4) - ml;
y4[k][QK_K*ibl+32*ib+i+16] = dl * (x[ibl].qs[64*ib+4*k+i+16] & 0xf) - ml;
y4[k][QK_K*ibl+32*ib+i+24] = dl * (x[ibl].qs[64*ib+4*k+i+16] >> 4) - ml;
y4[k][QK_K*ibl+32*ib+i+ 4] = dl * (x[ibl].qs[64*ib+4*k+i+32] & 0xf) - ml;
y4[k][QK_K*ibl+32*ib+i+12] = dl * (x[ibl].qs[64*ib+4*k+i+32] >> 4) - ml;
y4[k][QK_K*ibl+32*ib+i+20] = dl * (x[ibl].qs[64*ib+4*k+i+48] & 0xf) - ml;
y4[k][QK_K*ibl+32*ib+i+28] = dl * (x[ibl].qs[64*ib+4*k+i+48] >> 4) - ml;
}
}
}
}
}
void vec_dot_q4_k_r4_q8_k(int n, float * s, size_t bs, const void * vx, size_t bx, const void * vy, size_t by, int nrc) {
#if GGML_USE_IQK_MULMAT
if (iqk_mul_mat(1, 1, n, GGML_TYPE_Q4_K_R4, vx, 0, GGML_TYPE_Q8_K, vy, 0, s, 0, 0, 1)) {
return;
}
#endif
GGML_ASSERT(n%QK4_NL == 0);
GGML_ASSERT(nrc == 1);
GGML_UNUSED(bs);
GGML_UNUSED(bx);
GGML_UNUSED(by);
}
//
// ========================================= q6_k_r4
//
void quantize_row_q6_k_r4_ref(const float * x, block_q6_k_r4 * y, int64_t k) {
quantize_q6_k_r4(x, (void *)y, 4, k/4, nullptr);
}
void quantize_row_q6_k_r4(const float * x, void * y, int64_t k) {
quantize_q6_k_r4(x, y, 4, k/4, nullptr);
}
namespace {
inline void convert_q6_k(const block_q6_K& x, uint8_t * L) {
const uint8_t * ql = x.ql;
const uint8_t * qh = x.qh;
for (int n = 0; n < QK_K; n += 128) {
for (int l = 0; l < 32; ++l) {
L[n + l + 0] = (ql[l + 0] & 0xF) | (((qh[l] >> 0) & 3) << 4);
L[n + l + 32] = (ql[l + 32] & 0xF) | (((qh[l] >> 2) & 3) << 4);
L[n + l + 64] = (ql[l + 0] >> 4) | (((qh[l] >> 4) & 3) << 4);
L[n + l + 96] = (ql[l + 32] >> 4) | (((qh[l] >> 6) & 3) << 4);
}
ql += 64;
qh += 32;
}
}
}
static void repack_q6_k(int nrows, int n_per_row, const block_q6_K * x, block_q6_k_r4 * y, [[maybe_unused]] bool online) {
GGML_ASSERT(nrows%4 == 0);
GGML_ASSERT(n_per_row%QK_K == 0);
int nblock = n_per_row/QK_K;
const block_q6_K * x4[4];
uint8_t L[QK_K];
for (int row = 0; row < nrows; row += 4) {
for (int k = 0; k < 4; ++k) x4[k] = x + nblock*k;
for (int ibl = 0; ibl < nblock; ++ibl) {
for (int k = 0; k < 4; ++k) {
y[ibl].d[k] = x4[k][ibl].d;
convert_q6_k(x4[k][ibl], L);
for (int ib = 0; ib < QK_K/32; ++ib) {
y[ibl].scales[8*ib+k+0] = x4[k][ibl].scales[2*ib+0];
y[ibl].scales[8*ib+k+4] = x4[k][ibl].scales[2*ib+1];
for (int i = 0; i < 4; ++i) {
y[ibl].ql[64*ib+4*k+i+ 0] = (L[32*ib+i+ 0] & 0xf) | ((L[32*ib+i+ 8] & 0xf) << 4);
y[ibl].ql[64*ib+4*k+i+16] = (L[32*ib+i+16] & 0xf) | ((L[32*ib+i+24] & 0xf) << 4);
y[ibl].ql[64*ib+4*k+i+32] = (L[32*ib+i+ 4] & 0xf) | ((L[32*ib+i+12] & 0xf) << 4);
y[ibl].ql[64*ib+4*k+i+48] = (L[32*ib+i+20] & 0xf) | ((L[32*ib+i+28] & 0xf) << 4);
y[ibl].qh[32*ib+4*k+i+ 0] = (L[32*ib+i+ 0] >> 4) | ((L[32*ib+i+ 8] >> 4) << 2) | ((L[32*ib+i+ 4] >> 4) << 4) | ((L[32*ib+i+12] >> 4) << 6);
y[ibl].qh[32*ib+4*k+i+16] = (L[32*ib+i+16] >> 4) | ((L[32*ib+i+24] >> 4) << 2) | ((L[32*ib+i+20] >> 4) << 4) | ((L[32*ib+i+28] >> 4) << 6);
}
}
}
}
x += 4*nblock;
y += nblock;
}
}
size_t quantize_q6_k_r4(const float * src, void * dst, int64_t nrows, int64_t n_per_row, const float * imatrix) {
GGML_ASSERT(nrows%4 == 0);
GGML_ASSERT(n_per_row%QK_K == 0);
char * qcur = (char *)dst;
auto row_size = ggml_row_size(GGML_TYPE_Q6_K, n_per_row);
std::vector<char> qtmp(4*row_size);
for (int row = 0; row < nrows; row += 4) {
quantize_q6_K(src, (void *)qtmp.data(), 4, n_per_row, imatrix);
repack_q6_k(4, n_per_row, (const block_q6_K *)qtmp.data(), (block_q6_k_r4 *)qcur, false);
qcur += 4*row_size;
src += 4*n_per_row;
}
return nrows*row_size;
}
void dequantize_row_q6_k_r4(const block_q6_k_r4 * x, float * y, int64_t k) {
auto n_per_row = k/4;
float * y4[4] = {y, y + n_per_row, y + 2*n_per_row, y + 3*n_per_row};
int nblock = n_per_row/QK_K;
for (int ibl = 0; ibl < nblock; ++ibl) {
for (int k = 0; k < 4; ++k) {
const float d = GGML_FP16_TO_FP32(x[ibl].d[k]);
auto ql = x[ibl].ql;
auto qh = x[ibl].qh;
for (int ib = 0; ib < QK_K/32; ++ib) {
float dl1 = d * x[ibl].scales[8*ib+k+0];
float dl2 = d * x[ibl].scales[8*ib+k+4];
for (int i = 0; i < 4; ++i) {
y4[k][QK_K*ibl+32*ib+i+ 0] = dl1 * (((ql[4*k+i+ 0] & 0xf) | ((qh[4*k+i+ 0] << 4) & 0x30)) - 32);
y4[k][QK_K*ibl+32*ib+i+ 8] = dl1 * (((ql[4*k+i+ 0] >> 4) | ((qh[4*k+i+ 0] << 2) & 0x30)) - 32);
y4[k][QK_K*ibl+32*ib+i+16] = dl2 * (((ql[4*k+i+16] & 0xf) | ((qh[4*k+i+16] << 4) & 0x30)) - 32);
y4[k][QK_K*ibl+32*ib+i+24] = dl2 * (((ql[4*k+i+16] >> 4) | ((qh[4*k+i+16] << 2) & 0x30)) - 32);
y4[k][QK_K*ibl+32*ib+i+ 4] = dl1 * (((ql[4*k+i+32] & 0xf) | ((qh[4*k+i+ 0] >> 0) & 0x30)) - 32);
y4[k][QK_K*ibl+32*ib+i+12] = dl1 * (((ql[4*k+i+32] >> 4) | ((qh[4*k+i+ 0] >> 2) & 0x30)) - 32);
y4[k][QK_K*ibl+32*ib+i+20] = dl2 * (((ql[4*k+i+48] & 0xf) | ((qh[4*k+i+16] >> 0) & 0x30)) - 32);
y4[k][QK_K*ibl+32*ib+i+28] = dl2 * (((ql[4*k+i+48] >> 4) | ((qh[4*k+i+16] >> 2) & 0x30)) - 32);
}
ql += 64;
qh += 32;
}
}
}
}
void vec_dot_q6_k_r4_q8_k(int n, float * s, size_t bs, const void * vx, size_t bx, const void * vy, size_t by, int nrc) {
#if GGML_USE_IQK_MULMAT
if (iqk_mul_mat(1, 1, n, GGML_TYPE_Q6_K_R4, vx, 0, GGML_TYPE_Q8_K, vy, 0, s, 0, 0, 1)) {
return;
}
#endif
GGML_ASSERT(n%QK4_NL == 0);
GGML_ASSERT(nrc == 1);
GGML_UNUSED(bs);
GGML_UNUSED(bx);
GGML_UNUSED(by);
}
//
// ========================================= q5_k_r4
//
void quantize_row_q5_k_r4_ref(const float * x, block_q5_k_r4 * y, int64_t k) {
quantize_q5_k_r4(x, (void *)y, 4, k/4, nullptr);
}
void quantize_row_q5_k_r4(const float * x, void * y, int64_t k) {
quantize_q5_k_r4(x, y, 4, k/4, nullptr);
}
namespace {
inline void convert_q5_k(const block_q5_K& x, uint8_t * L, uint8_t * Ld, uint8_t * Lm) {
for (int ib64 = 0; ib64 < QK_K/64; ++ib64) {
get_scale_min_k4(2*ib64+0, x.scales, Ld[2*ib64+0], Lm[2*ib64+0]);
get_scale_min_k4(2*ib64+1, x.scales, Ld[2*ib64+1], Lm[2*ib64+1]);
for (int j = 0; j < 32; ++j) {
L[64*ib64+j+ 0] = (x.qs[32*ib64+j] & 0xf) | (((x.qh[j] >> (2*ib64+0)) & 1) << 4);
L[64*ib64+j+32] = (x.qs[32*ib64+j] >> 4) | (((x.qh[j] >> (2*ib64+1)) & 1) << 4);
}
}
}
}
static void repack_q5_k(int nrows, int n_per_row, const block_q5_K * x, block_q5_k_r4 * y, [[maybe_unused]] bool online) {
GGML_ASSERT(nrows%4 == 0);
GGML_ASSERT(n_per_row%QK_K == 0);
int nblock = n_per_row/QK_K;
const block_q5_K * x4[4];
uint8_t L[QK_K], Ld[QK_K/32], Lm[QK_K/32];
for (int row = 0; row < nrows; row += 4) {
for (int k = 0; k < 4; ++k) x4[k] = x + nblock*k;
for (int ibl = 0; ibl < nblock; ++ibl) {
std::memset(y[ibl].scales_l, 0, QK_K/8);
std::memset(y[ibl].scales_h, 0, QK_K/16);
for (int k = 0; k < 4; ++k) {
y[ibl].d[k+0] = x4[k][ibl].d;
y[ibl].d[k+4] = x4[k][ibl].dmin;
convert_q5_k(x4[k][ibl], L, Ld, Lm);
for (int ib = 0; ib < QK_K/32; ++ib) {
y[ibl].scales_l[4*ib+k] = (Ld[ib] & 0xf) | ((Lm[ib] & 0xf) << 4);
uint8_t h = (Ld[ib] >> 4) | ((Lm[ib] >> 4) << 2);
y[ibl].scales_h[(4*ib+k)%16] |= (h << 4*((4*ib+k)/16));
for (int i = 0; i < 4; ++i) {
y[ibl].qs[64*ib+4*k+i+ 0] = (L[32*ib+i+ 0] & 0xf) | ((L[32*ib+i+ 8] & 0xf) << 4);
y[ibl].qs[64*ib+4*k+i+16] = (L[32*ib+i+16] & 0xf) | ((L[32*ib+i+24] & 0xf) << 4);
y[ibl].qs[64*ib+4*k+i+32] = (L[32*ib+i+ 4] & 0xf) | ((L[32*ib+i+12] & 0xf) << 4);
y[ibl].qs[64*ib+4*k+i+48] = (L[32*ib+i+20] & 0xf) | ((L[32*ib+i+28] & 0xf) << 4);
y[ibl].qh[16*ib+4*k+i+ 0] = ((L[32*ib+i+ 0] >> 4) << 0) | ((L[32*ib+i+ 8] >> 4) << 1) | ((L[32*ib+i+ 4] >> 4) << 2) | ((L[32*ib+i+12] >> 4) << 3) |
((L[32*ib+i+16] >> 4) << 4) | ((L[32*ib+i+24] >> 4) << 5) | ((L[32*ib+i+20] >> 4) << 6) | ((L[32*ib+i+28] >> 4) << 7);
}
}
}
}
x += 4*nblock;
y += nblock;
}
}
size_t quantize_q5_k_r4(const float * src, void * dst, int64_t nrows, int64_t n_per_row, const float * imatrix) {
GGML_ASSERT(nrows%4 == 0);
GGML_ASSERT(n_per_row%QK_K == 0);
char * qcur = (char *)dst;
auto row_size = ggml_row_size(GGML_TYPE_Q5_K, n_per_row);
std::vector<char> qtmp(4*row_size);
for (int row = 0; row < nrows; row += 4) {
quantize_q5_K(src, (void *)qtmp.data(), 4, n_per_row, imatrix);
repack_q5_k(4, n_per_row, (const block_q5_K *)qtmp.data(), (block_q5_k_r4 *)qcur, false);
qcur += 4*row_size;
src += 4*n_per_row;
}
return nrows*row_size;
}
void dequantize_row_q5_k_r4(const block_q5_k_r4 * x, float * y, int64_t k) {
auto n_per_row = k/4;
float * y4[4] = {y, y + n_per_row, y + 2*n_per_row, y + 3*n_per_row};
int nblock = n_per_row/QK_K;
for (int ibl = 0; ibl < nblock; ++ibl) {
for (int k = 0; k < 4; ++k) {
const float d = GGML_FP16_TO_FP32(x[ibl].d[k+0]);
const float m = GGML_FP16_TO_FP32(x[ibl].d[k+4]);
auto ql = x[ibl].qs;
auto qh = x[ibl].qh;
for (int ib = 0; ib < QK_K/32; ++ib) {
int is = 4*ib + k;
float dl = d * ((x[ibl].scales_l[is] & 0xf) | (((x[ibl].scales_h[is%16] >> 4*(is/16)) & 0x03) << 4));
float ml = m * ((x[ibl].scales_l[is] >> 4) | (((x[ibl].scales_h[is%16] >> 4*(is/16)) & 0x0c) << 2));
for (int i = 0; i < 4; ++i) {
y4[k][QK_K*ibl+32*ib+i+ 0] = dl * ((ql[4*k+i+ 0] & 0xf) | ((qh[4*k+i] << 4) & 0x10)) - ml;
y4[k][QK_K*ibl+32*ib+i+ 8] = dl * ((ql[4*k+i+ 0] >> 4) | ((qh[4*k+i] << 3) & 0x10)) - ml;
y4[k][QK_K*ibl+32*ib+i+16] = dl * ((ql[4*k+i+16] & 0xf) | ((qh[4*k+i] >> 0) & 0x10)) - ml;
y4[k][QK_K*ibl+32*ib+i+24] = dl * ((ql[4*k+i+16] >> 4) | ((qh[4*k+i] >> 1) & 0x10)) - ml;
y4[k][QK_K*ibl+32*ib+i+ 4] = dl * ((ql[4*k+i+32] & 0xf) | ((qh[4*k+i] << 2) & 0x10)) - ml;
y4[k][QK_K*ibl+32*ib+i+12] = dl * ((ql[4*k+i+32] >> 4) | ((qh[4*k+i] << 1) & 0x10)) - ml;
y4[k][QK_K*ibl+32*ib+i+20] = dl * ((ql[4*k+i+48] & 0xf) | ((qh[4*k+i] >> 2) & 0x10)) - ml;
y4[k][QK_K*ibl+32*ib+i+28] = dl * ((ql[4*k+i+48] >> 4) | ((qh[4*k+i] >> 3) & 0x10)) - ml;
}
ql += 64;
qh += 16;
}
}
}
}
void vec_dot_q5_k_r4_q8_k(int n, float * s, size_t bs, const void * vx, size_t bx, const void * vy, size_t by, int nrc) {
#if GGML_USE_IQK_MULMAT
if (iqk_mul_mat(1, 1, n, GGML_TYPE_Q5_K_R4, vx, 0, GGML_TYPE_Q8_K32, vy, 0, s, 0, 0, 1)) {
return;
}
#endif
GGML_ASSERT(n%QK4_NL == 0);
GGML_ASSERT(nrc == 1);
GGML_UNUSED(bs);
GGML_UNUSED(bx);
GGML_UNUSED(by);
}
//
// ========================================= q3_k_r4
//
void quantize_row_q3_k_r4_ref(const float * x, block_q3_k_r4 * y, int64_t k) {
quantize_q3_k_r4(x, (void *)y, 4, k/4, nullptr);
}
void quantize_row_q3_k_r4(const float * x, void * y, int64_t k) {
quantize_q3_k_r4(x, y, 4, k/4, nullptr);
}
namespace {
inline void convert_q3_k(const block_q3_K& x, uint8_t * L, uint8_t * Ld) {
constexpr uint32_t kmask1 = 0x03030303;
constexpr uint32_t kmask2 = 0x0f0f0f0f;
uint32_t aux[4];
memcpy(aux, x.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);
std::memcpy(Ld, aux, 16);
const uint8_t * q = x.qs;
const uint8_t * hm = x.hmask;
uint8_t m = 1;
for (int n = 0; n < QK_K; n += 128) {
int shift = 0;
for (int j = 0; j < 4; ++j) {
for (int l = 0; l < 32; ++l) {
*L++ = ((q[l] >> shift) & 3) + ((hm[l] & m) ? 4 : 0);
}
shift += 2;
m <<= 1;
}
q += 32;
}
}
}
static void repack_q3_k(int nrows, int n_per_row, const block_q3_K * x, block_q3_k_r4 * y, [[maybe_unused]] bool online) {
GGML_ASSERT(nrows%4 == 0);
GGML_ASSERT(n_per_row%QK_K == 0);
int nblock = n_per_row/QK_K;
const block_q3_K * x4[4];
uint8_t L[QK_K], Ld[QK_K/16];
for (int row = 0; row < nrows; row += 4) {
for (int k = 0; k < 4; ++k) x4[k] = x + nblock*k;
for (int ibl = 0; ibl < nblock; ++ibl) {
std::memset(y[ibl].scales_l, 0, QK_K/8);
std::memset(y[ibl].scales_h, 0, QK_K/16);
for (int k = 0; k < 4; ++k) {
y[ibl].d[k] = x4[k][ibl].d;
convert_q3_k(x4[k][ibl], L, Ld);
for (int ib = 0; ib < QK_K/32; ++ib) {
int is = 8*ib+k;
y[ibl].scales_l[is%32] |= (Ld[2*ib+0] & 0xf) << 4*(is/32);
y[ibl].scales_h[is%16] |= (Ld[2*ib+0] >> 4) << 2*(is/16);
is += 4;
y[ibl].scales_l[is%32] |= (Ld[2*ib+1] & 0xf) << 4*(is/32);
y[ibl].scales_h[is%16] |= (Ld[2*ib+1] >> 4) << 2*(is/16);
for (int i = 0; i < 4; ++i) {
y[ibl].qs[32*ib+4*k+i+ 0] = ((L[32*ib+i+ 0] & 0x3) << 0) | ((L[32*ib+i+ 4] & 0x3) << 2) | ((L[32*ib+i+ 8] & 0x3) << 4) | ((L[32*ib+i+12] & 0x3) << 6);
y[ibl].qs[32*ib+4*k+i+16] = ((L[32*ib+i+16] & 0x3) << 0) | ((L[32*ib+i+20] & 0x3) << 2) | ((L[32*ib+i+24] & 0x3) << 4) | ((L[32*ib+i+28] & 0x3) << 6);
y[ibl].qh[16*ib+4*k+i+ 0] = ((L[32*ib+i+ 0] >> 2) << 0) | ((L[32*ib+i+ 4] >> 2) << 1) | ((L[32*ib+i+ 8] >> 2) << 2) | ((L[32*ib+i+12] >> 2) << 3)
| ((L[32*ib+i+16] >> 2) << 4) | ((L[32*ib+i+20] >> 2) << 5) | ((L[32*ib+i+24] >> 2) << 6) | ((L[32*ib+i+28] >> 2) << 7);
}
}
}
}
x += 4*nblock;
y += nblock;
}
}
size_t quantize_q3_k_r4(const float * src, void * dst, int64_t nrows, int64_t n_per_row, const float * imatrix) {
GGML_ASSERT(nrows%4 == 0);
GGML_ASSERT(n_per_row%QK_K == 0);
char * qcur = (char *)dst;
auto row_size = ggml_row_size(GGML_TYPE_Q3_K, n_per_row);
std::vector<char> qtmp(4*row_size);
for (int row = 0; row < nrows; row += 4) {
quantize_q3_K(src, (void *)qtmp.data(), 4, n_per_row, imatrix);
repack_q3_k(4, n_per_row, (const block_q3_K *)qtmp.data(), (block_q3_k_r4 *)qcur, false);
qcur += 4*row_size;
src += 4*n_per_row;
}
return nrows*row_size;
}
void dequantize_row_q3_k_r4(const block_q3_k_r4 * x, float * y, int64_t k) {
auto n_per_row = k/4;
float * y4[4] = {y, y + n_per_row, y + 2*n_per_row, y + 3*n_per_row};
int nblock = n_per_row/QK_K;
for (int ibl = 0; ibl < nblock; ++ibl) {
for (int k = 0; k < 4; ++k) {
const float d = GGML_FP16_TO_FP32(x[ibl].d[k]);
auto ql = x[ibl].qs;
auto qh = x[ibl].qh;
for (int ib = 0; ib < QK_K/32; ++ib) {
int is = 8*ib + k;
float dl1 = d * ((((x[ibl].scales_l[is%32] >> 4*(is/32)) & 0xf) | (((x[ibl].scales_h[is%16] >> 2*(is/16)) & 0x03) << 4)) - 32);
is += 4;
float dl2 = d * ((((x[ibl].scales_l[is%32] >> 4*(is/32)) & 0xf) | (((x[ibl].scales_h[is%16] >> 2*(is/16)) & 0x03) << 4)) - 32);
for (int i = 0; i < 4; ++i) {
y4[k][QK_K*ibl+32*ib+i+ 0] = dl1 * ((((ql[4*k+i+ 0] >> 0) & 3) | ((qh[4*k+i] << 2) & 4)) - 4);
y4[k][QK_K*ibl+32*ib+i+ 4] = dl1 * ((((ql[4*k+i+ 0] >> 2) & 3) | ((qh[4*k+i] << 1) & 4)) - 4);
y4[k][QK_K*ibl+32*ib+i+ 8] = dl1 * ((((ql[4*k+i+ 0] >> 4) & 3) | ((qh[4*k+i] << 0) & 4)) - 4);
y4[k][QK_K*ibl+32*ib+i+12] = dl1 * ((((ql[4*k+i+ 0] >> 6) & 3) | ((qh[4*k+i] >> 1) & 4)) - 4);
y4[k][QK_K*ibl+32*ib+i+16] = dl2 * ((((ql[4*k+i+16] >> 0) & 3) | ((qh[4*k+i] >> 2) & 4)) - 4);
y4[k][QK_K*ibl+32*ib+i+20] = dl2 * ((((ql[4*k+i+16] >> 2) & 3) | ((qh[4*k+i] >> 3) & 4)) - 4);
y4[k][QK_K*ibl+32*ib+i+24] = dl2 * ((((ql[4*k+i+16] >> 4) & 3) | ((qh[4*k+i] >> 4) & 4)) - 4);
y4[k][QK_K*ibl+32*ib+i+28] = dl2 * ((((ql[4*k+i+16] >> 6) & 3) | ((qh[4*k+i] >> 5) & 4)) - 4);
}
ql += 32;
qh += 16;
}
}
}
}
void vec_dot_q3_k_r4_q8_k(int n, float * s, size_t bs, const void * vx, size_t bx, const void * vy, size_t by, int nrc) {
#if GGML_USE_IQK_MULMAT
if (iqk_mul_mat(1, 1, n, GGML_TYPE_Q3_K_R4, vx, 0, GGML_TYPE_Q8_K, vy, 0, s, 0, 0, 1)) {
return;
}
#endif
GGML_ASSERT(n%QK4_NL == 0);
GGML_ASSERT(nrc == 1);
GGML_UNUSED(bs);
GGML_UNUSED(bx);
GGML_UNUSED(by);
}
//
// ========================================= q2_k_r4
//
void quantize_row_q2_k_r4_ref(const float * x, block_q2_k_r4 * y, int64_t k) {
quantize_q3_k_r4(x, (void *)y, 4, k/4, nullptr);
}
void quantize_row_q2_k_r4(const float * x, void * y, int64_t k) {
quantize_q2_k_r4(x, y, 4, k/4, nullptr);
}
namespace {
inline void convert_q2_k(const block_q2_K& x, uint8_t * L) {
const uint8_t * qs = x.qs;
for (int n = 0; n < QK_K; n += 128) {
for (int j = 0; j < 32; ++j) {
L[n + j + 0] = (qs[j] >> 0) & 0x3;
L[n + j + 32] = (qs[j] >> 2) & 0x3;
L[n + j + 64] = (qs[j] >> 4) & 0x3;
L[n + j + 96] = (qs[j] >> 6) & 0x3;
}
qs += 32;
}
}
}
static void repack_q2_k(int nrows, int n_per_row, const block_q2_K * x, block_q2_k_r4 * y, [[maybe_unused]] bool online) {
GGML_ASSERT(nrows%4 == 0);
GGML_ASSERT(n_per_row%QK_K == 0);
int nblock = n_per_row/QK_K;
const block_q2_K * x4[4];
uint8_t L[QK_K];
for (int row = 0; row < nrows; row += 4) {
for (int k = 0; k < 4; ++k) x4[k] = x + nblock*k;
for (int ibl = 0; ibl < nblock; ++ibl) {
for (int k = 0; k < 4; ++k) {
y[ibl].d[k+0] = x4[k][ibl].d;
y[ibl].d[k+4] = x4[k][ibl].dmin;
for (int ib = 0; ib < QK_K/16; ++ib) {
y[ibl].scales[4*ib+k] = x4[k][ibl].scales[ib];
}
convert_q2_k(x4[k][ibl], L);
for (int ib = 0; ib < QK_K/32; ++ib) {
for (int i = 0; i < 4; ++i) {
y[ibl].qs[32*ib+4*k+i+ 0] = ((L[32*ib+i+ 0] & 0x3) << 0) | ((L[32*ib+i+ 4] & 0x3) << 2) | ((L[32*ib+i+ 8] & 0x3) << 4) | ((L[32*ib+i+12] & 0x3) << 6);
y[ibl].qs[32*ib+4*k+i+16] = ((L[32*ib+i+16] & 0x3) << 0) | ((L[32*ib+i+20] & 0x3) << 2) | ((L[32*ib+i+24] & 0x3) << 4) | ((L[32*ib+i+28] & 0x3) << 6);
}
}
}
}
x += 4*nblock;
y += nblock;
}
}
size_t quantize_q2_k_r4(const float * src, void * dst, int64_t nrows, int64_t n_per_row, const float * imatrix) {
GGML_ASSERT(nrows%4 == 0);
GGML_ASSERT(n_per_row%QK_K == 0);
char * qcur = (char *)dst;
auto row_size = ggml_row_size(GGML_TYPE_Q2_K, n_per_row);
std::vector<char> qtmp(4*row_size);
for (int row = 0; row < nrows; row += 4) {
quantize_q2_K(src, (void *)qtmp.data(), 4, n_per_row, imatrix);
repack_q2_k(4, n_per_row, (const block_q2_K *)qtmp.data(), (block_q2_k_r4 *)qcur, false);
qcur += 4*row_size;
src += 4*n_per_row;
}
return nrows*row_size;
}
void dequantize_row_q2_k_r4(const block_q2_k_r4 * x, float * y, int64_t k) {
auto n_per_row = k/4;
float * y4[4] = {y, y + n_per_row, y + 2*n_per_row, y + 3*n_per_row};
int nblock = n_per_row/QK_K;
for (int ibl = 0; ibl < nblock; ++ibl) {
for (int k = 0; k < 4; ++k) {
const float d = GGML_FP16_TO_FP32(x[ibl].d[k+0]);
const float m = GGML_FP16_TO_FP32(x[ibl].d[k+4]);
auto ql = x[ibl].qs;
for (int ib = 0; ib < QK_K/32; ++ib) {
float dl1 = d * (x[ibl].scales[8*ib + k + 0] & 0xf);
float ml1 = m * (x[ibl].scales[8*ib + k + 0] >> 4);
float dl2 = d * (x[ibl].scales[8*ib + k + 4] & 0xf);
float ml2 = m * (x[ibl].scales[8*ib + k + 4] >> 4);
for (int i = 0; i < 4; ++i) {
y4[k][QK_K*ibl+32*ib+i+ 0] = dl1 * ((ql[4*k+i+ 0] >> 0) & 3) - ml1;
y4[k][QK_K*ibl+32*ib+i+ 4] = dl1 * ((ql[4*k+i+ 0] >> 2) & 3) - ml1;
y4[k][QK_K*ibl+32*ib+i+ 8] = dl1 * ((ql[4*k+i+ 0] >> 4) & 3) - ml1;
y4[k][QK_K*ibl+32*ib+i+12] = dl1 * ((ql[4*k+i+ 0] >> 6) & 3) - ml1;
y4[k][QK_K*ibl+32*ib+i+16] = dl2 * ((ql[4*k+i+16] >> 0) & 3) - ml2;
y4[k][QK_K*ibl+32*ib+i+20] = dl2 * ((ql[4*k+i+16] >> 2) & 3) - ml2;
y4[k][QK_K*ibl+32*ib+i+24] = dl2 * ((ql[4*k+i+16] >> 4) & 3) - ml2;
y4[k][QK_K*ibl+32*ib+i+28] = dl2 * ((ql[4*k+i+16] >> 6) & 3) - ml2;
}
ql += 32;
}
}
}
}
void vec_dot_q2_k_r4_q8_k(int n, float * s, size_t bs, const void * vx, size_t bx, const void * vy, size_t by, int nrc) {
#if GGML_USE_IQK_MULMAT
if (iqk_mul_mat(1, 1, n, GGML_TYPE_Q2_K_R4, vx, 0, GGML_TYPE_Q8_K, vy, 0, s, 0, 0, 1)) {
return;
}
#endif
GGML_ASSERT(n%QK4_NL == 0);
GGML_ASSERT(nrc == 1);
GGML_UNUSED(bs);
GGML_UNUSED(bx);
GGML_UNUSED(by);
}
//
// ========================================= iq4_k_r4
//
void quantize_row_iq4_k_r4_ref(const float * x, block_iq4_k_r4 * y, int64_t k) {
quantize_iq4_k_r4(x, (void *)y, 4, k/4, nullptr);
}
void quantize_row_iq4_k_r4(const float * x, void * y, int64_t k) {
quantize_iq4_k_r4(x, y, 4, k/4, nullptr);
}
static void repack_iq4_k(int nrows, int n_per_row, const block_iq4_k * x, block_iq4_k_r4 * y, [[maybe_unused]] bool online) {
GGML_ASSERT(nrows%4 == 0);
GGML_ASSERT(n_per_row%QK_K == 0);
int nblock = n_per_row/QK_K;
const block_iq4_k * x4[4];
for (int row = 0; row < nrows; row += 4) {
for (int k = 0; k < 4; ++k) x4[k] = x + nblock*k;
for (int ibl = 0; ibl < nblock; ++ibl) {
std::memset(y[ibl].extra, 0, 8);
std::memset(y[ibl].scales_l, 0, QK_K/8);
std::memset(y[ibl].scales_h, 0, QK_K/16);
for (int k = 0; k < 4; ++k) {
y[ibl].d[k] = x4[k][ibl].d;
auto extra = x4[k][ibl].extra;
for (int ib = 0; ib < QK_K/32; ++ib) {
if (extra & 1) y[ibl].extra[k+0] |= (1 << ib);
if (extra & 2) y[ibl].extra[k+4] |= (1 << ib);
extra >>= 2;
uint8_t sl1 = x4[k][ibl].scales_l[ib] & 0xf;
uint8_t sl2 = x4[k][ibl].scales_l[ib] >> 4;
uint8_t sh = x4[k][ibl].scales_h[ib/2] >> 4*(ib%2);
uint8_t sh1 = (sh >> 0) & 3;
uint8_t sh2 = (sh >> 2) & 3;
int i = 8*ib + k;
y[ibl].scales_l[i%32] |= (sl1 << 4*(i/32));
y[ibl].scales_h[i%16] |= (sh1 << 2*(i/16));
i += 4;
y[ibl].scales_l[i%32] |= (sl2 << 4*(i/32));
y[ibl].scales_h[i%16] |= (sh2 << 2*(i/16));
}
}
for (int ib = 0; ib < QK_K/32; ++ib) {
for (int k = 0; k < 4; ++k) for (int i = 0; i < 4; ++i) {
y[ibl].qs[64*ib+4*k+i+ 0] = (x4[k][ibl].qs[16*ib+i+0] & 0xf) | ((x4[k][ibl].qs[16*ib+i+ 8] & 0x0f) << 4); // 0....3 + 8...11 from each row
y[ibl].qs[64*ib+4*k+i+16] = (x4[k][ibl].qs[16*ib+i+0] >> 4) | ((x4[k][ibl].qs[16*ib+i+ 8] & 0xf0)); // 16...19 + 24...27 from each row
y[ibl].qs[64*ib+4*k+i+32] = (x4[k][ibl].qs[16*ib+i+4] & 0xf) | ((x4[k][ibl].qs[16*ib+i+12] & 0x0f) << 4); // 4....7 + 12...15 from each row
y[ibl].qs[64*ib+4*k+i+48] = (x4[k][ibl].qs[16*ib+i+4] >> 4) | ((x4[k][ibl].qs[16*ib+i+12] & 0xf0)); // 20...23 + 28...31 from each row
}
}
}
x += 4*nblock;
y += nblock;
}
}
size_t quantize_iq4_k_r4(const float * src, void * dst, int64_t nrows, int64_t n_per_row, const float * imatrix) {
GGML_ASSERT(nrows%4 == 0);
GGML_ASSERT(n_per_row%QK_K == 0);
char * qcur = (char *)dst;
auto row_size = ggml_row_size(GGML_TYPE_IQ4_K, n_per_row);
std::vector<char> qtmp(4*row_size);
for (int row = 0; row < nrows; row += 4) {
quantize_iq4_k(src, (void *)qtmp.data(), 4, n_per_row, imatrix);
repack_iq4_k(4, n_per_row, (const block_iq4_k *)qtmp.data(), (block_iq4_k_r4 *)qcur, false);
qcur += 4*row_size;
src += 4*n_per_row;
}
return nrows*row_size;
}
void dequantize_row_iq4_k_r4(const block_iq4_k_r4 * x, float * y, int64_t k) {
auto n_per_row = k/4;
float * y4[4] = {y, y + n_per_row, y + 2*n_per_row, y + 3*n_per_row};
int nblock = n_per_row/QK_K;
for (int ibl = 0; ibl < nblock; ++ibl) {
for (int k = 0; k < 4; ++k) {
const float d = GGML_FP16_TO_FP32(x[ibl].d[k]);
for (int ib = 0; ib < QK_K/32; ++ib) {
int is = 8*ib + k;
float dl1 = d * ((((x[ibl].scales_l[is%32] >> 4*(is/32)) & 0xf) | (((x[ibl].scales_h[is%16] >> 2*(is/16)) & 3) << 4)) - 32);
is += 4;
float dl2 = d * ((((x[ibl].scales_l[is%32] >> 4*(is/32)) & 0xf) | (((x[ibl].scales_h[is%16] >> 2*(is/16)) & 3) << 4)) - 32);
auto values1 = iq4k_values + (x[ibl].extra[k+0] & (1 << ib) ? 16 : 0);
auto values2 = iq4k_values + (x[ibl].extra[k+4] & (1 << ib) ? 16 : 0);
for (int i = 0; i < 4; ++i) {
y4[k][QK_K*ibl+32*ib+i+ 0] = dl1 * values1[x[ibl].qs[64*ib+4*k+i+ 0] & 0xf];
y4[k][QK_K*ibl+32*ib+i+ 8] = dl1 * values1[x[ibl].qs[64*ib+4*k+i+ 0] >> 4];
y4[k][QK_K*ibl+32*ib+i+16] = dl2 * values2[x[ibl].qs[64*ib+4*k+i+16] & 0xf];
y4[k][QK_K*ibl+32*ib+i+24] = dl2 * values2[x[ibl].qs[64*ib+4*k+i+16] >> 4];
y4[k][QK_K*ibl+32*ib+i+ 4] = dl1 * values1[x[ibl].qs[64*ib+4*k+i+32] & 0xf];
y4[k][QK_K*ibl+32*ib+i+12] = dl1 * values1[x[ibl].qs[64*ib+4*k+i+32] >> 4];
y4[k][QK_K*ibl+32*ib+i+20] = dl2 * values2[x[ibl].qs[64*ib+4*k+i+48] & 0xf];
y4[k][QK_K*ibl+32*ib+i+28] = dl2 * values2[x[ibl].qs[64*ib+4*k+i+48] >> 4];
}
}
}
}
}
void vec_dot_iq4_k_r4_q8_k(int n, float * s, size_t bs, const void * vx, size_t bx, const void * vy, size_t by, int nrc) {
#if GGML_USE_IQK_MULMAT
if (iqk_mul_mat(1, 1, n, GGML_TYPE_IQ4_K_R4, vx, 0, GGML_TYPE_Q8_K, vy, 0, s, 0, 0, 1)) {
return;
}
#endif
GGML_ASSERT(n%QK4_NL == 0);
GGML_ASSERT(nrc == 1);
GGML_UNUSED(bs);
GGML_UNUSED(bx);
GGML_UNUSED(by);
}
//
// ========================================= iq5_k_r4
//
void quantize_row_iq5_k_r4_ref(const float * x, block_iq5_k_r4 * y, int64_t k) {
quantize_iq5_k_r4(x, (void *)y, 4, k/4, nullptr);
}
void quantize_row_iq5_k_r4(const float * x, void * y, int64_t k) {
quantize_iq5_k_r4(x, y, 4, k/4, nullptr);
}
namespace {
inline void convert_iq5_k(const block_iq5_k& x, uint8_t * L) {
const uint8_t * qs = x.qs;
const uint8_t * qh = x.qh;
int shift = 0;
for (int ib64 = 0; ib64 < QK_K/64; ++ib64) {
for (int j = 0; j < 16; ++j) {
L[j+ 0] = (qs[j+ 0] & 0xf) | (((qh[j+ 0] >> shift) & 1) << 4);
L[j+16] = (qs[j+16] & 0xf) | (((qh[j+16] >> shift) & 1) << 4);
L[j+32] = (qs[j+ 0] >> 4) | (((qh[j+ 0] >> shift) & 2) << 3);
L[j+48] = (qs[j+16] >> 4) | (((qh[j+16] >> shift) & 2) << 3);
}
L += 64;
qs += 32;
shift += 2;
if (shift == 8) { qh += 32; shift = 0; }
}
}
}
static void repack_iq5_k(int nrows, int n_per_row, const block_iq5_k * x, block_iq5_k_r4 * y, [[maybe_unused]] bool online) {
GGML_ASSERT(nrows%4 == 0);
GGML_ASSERT(n_per_row%QK_K == 0);
int nblock = n_per_row/QK_K;
const block_iq5_k * x4[4];
uint8_t L[QK_K];
for (int row = 0; row < nrows; row += 4) {
for (int k = 0; k < 4; ++k) x4[k] = x + nblock*k;
for (int ibl = 0; ibl < nblock; ++ibl) {
std::memset(y[ibl].extra, 0, 8);
std::memset(y[ibl].scales_l, 0, QK_K/8);
std::memset(y[ibl].scales_h, 0, QK_K/16);
for (int k = 0; k < 4; ++k) {
y[ibl].d[k] = x4[k][ibl].d;
auto extra = x4[k][ibl].extra;
convert_iq5_k(x4[k][ibl], L);
for (int ib = 0; ib < QK_K/32; ++ib) {
if (extra & 1) y[ibl].extra[k+0] |= (1 << ib);
if (extra & 2) y[ibl].extra[k+4] |= (1 << ib);
extra >>= 2;
uint8_t sl1 = x4[k][ibl].scales_l[ib] & 0xf;
uint8_t sl2 = x4[k][ibl].scales_l[ib] >> 4;
uint8_t sh = x4[k][ibl].scales_h[ib/2] >> 4*(ib%2);
uint8_t sh1 = (sh >> 0) & 3;
uint8_t sh2 = (sh >> 2) & 3;
int i = 8*ib + k;
y[ibl].scales_l[i%32] |= (sl1 << 4*(i/32));
y[ibl].scales_h[i%16] |= (sh1 << 2*(i/16));
i += 4;
y[ibl].scales_l[i%32] |= (sl2 << 4*(i/32));
y[ibl].scales_h[i%16] |= (sh2 << 2*(i/16));
for (int i = 0; i < 4; ++i) {
y[ibl].qs[64*ib+4*k+i+ 0] = (L[32*ib+i+ 0] & 0xf) | ((L[32*ib+i+ 8] & 0xf) << 4); // 0....3 + 8...11 from each row
y[ibl].qs[64*ib+4*k+i+16] = (L[32*ib+i+16] & 0xf) | ((L[32*ib+i+24] & 0xf) << 4); // 16...19 + 24...27 from each row
y[ibl].qs[64*ib+4*k+i+32] = (L[32*ib+i+ 4] & 0xf) | ((L[32*ib+i+12] & 0xf) << 4); // 4....7 + 12...15 from each row
y[ibl].qs[64*ib+4*k+i+48] = (L[32*ib+i+20] & 0xf) | ((L[32*ib+i+28] & 0xf) << 4); // 20...23 + 28...31 from each row
y[ibl].qh[16*ib+4*k+i ] = ((L[32*ib+i+ 0] >> 4) << 0) | ((L[32*ib+i+ 8] >> 4) << 1) | ((L[32*ib+i+16] >> 4) << 2) | ((L[32*ib+i+24] >> 4) << 3)
| ((L[32*ib+i+ 4] >> 4) << 4) | ((L[32*ib+i+12] >> 4) << 5) | ((L[32*ib+i+20] >> 4) << 6) | ((L[32*ib+i+28] >> 4) << 7);
}
}
}
}
x += 4*nblock;
y += nblock;
}
}
size_t quantize_iq5_k_r4(const float * src, void * dst, int64_t nrows, int64_t n_per_row, const float * imatrix) {
GGML_ASSERT(nrows%4 == 0);
GGML_ASSERT(n_per_row%QK_K == 0);
char * qcur = (char *)dst;
auto row_size = ggml_row_size(GGML_TYPE_IQ5_K, n_per_row);
std::vector<char> qtmp(4*row_size);
for (int row = 0; row < nrows; row += 4) {
quantize_iq5_k(src, (void *)qtmp.data(), 4, n_per_row, imatrix);
repack_iq5_k(4, n_per_row, (const block_iq5_k *)qtmp.data(), (block_iq5_k_r4 *)qcur, false);
qcur += 4*row_size;
src += 4*n_per_row;
}
return nrows*row_size;
}
void dequantize_row_iq5_k_r4(const block_iq5_k_r4 * x, float * y, int64_t k) {
auto n_per_row = k/4;
float * y4[4] = {y, y + n_per_row, y + 2*n_per_row, y + 3*n_per_row};
int nblock = n_per_row/QK_K;
for (int ibl = 0; ibl < nblock; ++ibl) {
for (int k = 0; k < 4; ++k) {
const float d = GGML_FP16_TO_FP32(x[ibl].d[k]);
for (int ib = 0; ib < QK_K/32; ++ib) {
int is = 8*ib + k;
float dl1 = d * ((((x[ibl].scales_l[is%32] >> 4*(is/32)) & 0xf) | (((x[ibl].scales_h[is%16] >> 2*(is/16)) & 3) << 4)) - 32);
is += 4;
float dl2 = d * ((((x[ibl].scales_l[is%32] >> 4*(is/32)) & 0xf) | (((x[ibl].scales_h[is%16] >> 2*(is/16)) & 3) << 4)) - 32);
auto values1 = iq5nl_values + (x[ibl].extra[k+0] & (1 << ib) ? 32 : 0);
auto values2 = iq5nl_values + (x[ibl].extra[k+4] & (1 << ib) ? 32 : 0);
for (int i = 0; i < 4; ++i) {
y4[k][QK_K*ibl+32*ib+i+ 0] = dl1 * values1[(x[ibl].qs[64*ib+4*k+i+ 0] & 0xf) | (((x[ibl].qh[16*ib+4*k+i] >> 0) & 1) << 4)];
y4[k][QK_K*ibl+32*ib+i+ 8] = dl1 * values1[(x[ibl].qs[64*ib+4*k+i+ 0] >> 4) | (((x[ibl].qh[16*ib+4*k+i] >> 1) & 1) << 4)];
y4[k][QK_K*ibl+32*ib+i+16] = dl2 * values2[(x[ibl].qs[64*ib+4*k+i+16] & 0xf) | (((x[ibl].qh[16*ib+4*k+i] >> 2) & 1) << 4)];
y4[k][QK_K*ibl+32*ib+i+24] = dl2 * values2[(x[ibl].qs[64*ib+4*k+i+16] >> 4) | (((x[ibl].qh[16*ib+4*k+i] >> 3) & 1) << 4)];
y4[k][QK_K*ibl+32*ib+i+ 4] = dl1 * values1[(x[ibl].qs[64*ib+4*k+i+32] & 0xf) | (((x[ibl].qh[16*ib+4*k+i] >> 4) & 1) << 4)];
y4[k][QK_K*ibl+32*ib+i+12] = dl1 * values1[(x[ibl].qs[64*ib+4*k+i+32] >> 4) | (((x[ibl].qh[16*ib+4*k+i] >> 5) & 1) << 4)];
y4[k][QK_K*ibl+32*ib+i+20] = dl2 * values2[(x[ibl].qs[64*ib+4*k+i+48] & 0xf) | (((x[ibl].qh[16*ib+4*k+i] >> 6) & 1) << 4)];
y4[k][QK_K*ibl+32*ib+i+28] = dl2 * values2[(x[ibl].qs[64*ib+4*k+i+48] >> 4) | (((x[ibl].qh[16*ib+4*k+i] >> 7) & 1) << 4)];
}
}
}
}
}
void vec_dot_iq5_k_r4_q8_k(int n, float * s, size_t bs, const void * vx, size_t bx, const void * vy, size_t by, int nrc) {
#if GGML_USE_IQK_MULMAT
if (iqk_mul_mat(1, 1, n, GGML_TYPE_IQ5_K_R4, vx, 0, GGML_TYPE_Q8_K, vy, 0, s, 0, 0, 1)) {
return;
}
#endif
GGML_ASSERT(n%QK4_NL == 0);
GGML_ASSERT(nrc == 1);
GGML_UNUSED(bs);
GGML_UNUSED(bx);
GGML_UNUSED(by);
}
//
// ========================================= q8_k_r8
//
void quantize_row_q8_k_r8_ref(const float * x, block_q8_k_r8 * y, int64_t k) {
quantize_q8_k_r8(x, (void *)y, 8, k/8, nullptr);
}
void quantize_row_q8_k_r8(const float * x, void * y, int64_t k) {
quantize_q8_k_r8(x, y, 8, k/8, nullptr);
}
static void repack_q8_k(int nrows, int n_per_row, const block_q8_K * x, block_q8_k_r8 * y, [[maybe_unused]] bool online) {
GGML_ASSERT(nrows%8 == 0);
GGML_ASSERT(n_per_row%QK_K == 0);
int nblock = n_per_row/QK_K;
const block_q8_K * x8[8];
for (int row = 0; row < nrows; row += 8) {
for (int k = 0; k < 8; ++k) x8[k] = x + nblock*k;
for (int ibl = 0; ibl < nblock; ++ibl) {
for (int k = 0; k < 8; ++k) {
y[ibl].d[k] = GGML_FP32_TO_FP16(x8[k][ibl].d);
for (int ib = 0; ib < QK_K/4; ++ib) {
for (int i = 0; i < 4; ++i) y[ibl].qs[32*ib + 4*k + i] = x8[k][ibl].qs[4*ib+i];
}
}
#ifdef HAVE_FANCY_SIMD
if (online) {
for (int l = 0; l < 32; ++l) {
auto v = _mm512_xor_si512(_mm512_loadu_si512((const __m512i *)y[ibl].qs + l), _mm512_set1_epi8(-128));
_mm512_storeu_si512((__m512i *)y[ibl].qs + l, v);
}
}
#endif
}
x += 8*nblock;
y += nblock;
}
}
#ifdef HAVE_FANCY_SIMD
static void modify_q8_k_r8(int64_t k, char * cy) {
auto y = (block_q8_k_r8 *)cy;
int nb = k/(256*8);
for (int ib = 0; ib < nb; ++ib) {
for (int l = 0; l < 32; ++l) {
auto v = _mm512_xor_si512(_mm512_loadu_si512((const __m512i *)y[ib].qs + l), _mm512_set1_epi8(-128));
_mm512_storeu_si512((__m512i *)y[ib].qs + l, v);
}
}
}
#endif
size_t quantize_q8_k_r8(const float * src, void * dst, int64_t nrows, int64_t n_per_row, [[maybe_unused]] const float * imatrix) {
GGML_ASSERT(nrows%8 == 0);
GGML_ASSERT(n_per_row%QK_K == 0);
char * qcur = (char *)dst;
auto row_size_0 = ggml_row_size(GGML_TYPE_Q8_K, n_per_row);
auto row_size_1 = ggml_row_size(GGML_TYPE_Q8_K_R8, n_per_row);
std::vector<char> qtmp(8*row_size_0);
for (int row = 0; row < nrows; row += 8) {
quantize_row_q8_K32(src, (void *)qtmp.data(), 8*n_per_row);
repack_q8_k(8, n_per_row, (const block_q8_K *)qtmp.data(), (block_q8_k_r8 *)qcur, false);
qcur += 8*row_size_1;
src += 8*n_per_row;
}
return nrows*row_size_1;
}
void dequantize_row_q8_k_r8(const block_q8_k_r8 * x, float * y, int64_t k) {
auto n_per_row = k/8;
float * y8[8];
for (int k = 0; k < 8; ++k) y8[k] = y + n_per_row*k;
int nblock = n_per_row/QK_K;
for (int ibl = 0; ibl < nblock; ++ibl) {
for (int k = 0; k < 8; ++k) {
const float d = GGML_FP16_TO_FP32(x[ibl].d[k]);
for (int ib = 0; ib < QK_K/4; ++ib) {
for (int i = 0; i < 4; ++i) {
y8[k][QK_K*ibl+4*ib+i] = d * x[ibl].qs[32*ib+4*k+i];
}
}
}
}
}
void vec_dot_q8_k_r8_q8_k(int n, float * s, size_t bs, const void * vx, size_t bx, const void * vy, size_t by, int nrc) {
#if GGML_USE_IQK_MULMAT
if (iqk_mul_mat(1, 1, n, GGML_TYPE_Q8_K_R8, vx, 0, GGML_TYPE_Q8_K, vy, 0, s, 0, 0, 1)) {
return;
}
#endif
GGML_ASSERT(n%QK4_NL == 0);
GGML_ASSERT(nrc == 1);
GGML_UNUSED(bs);
GGML_UNUSED(bx);
GGML_UNUSED(by);
}
//
// ========================================= q8_KV_r8
//
void quantize_row_q8_KV_r8_ref(const float * x, void * y, int64_t k) {
quantize_q8_KV_r8(x, y, 8, k/8, nullptr);
}
void quantize_row_q8_KV_r8(const float * x, void * y, int64_t k) {
quantize_q8_KV_r8(x, y, 8, k/8, nullptr);
}
static void repack_q8_KV(int nrows, int n_per_row, const char * cx, char * cy, [[maybe_unused]] bool online) {
GGML_ASSERT(nrows%8 == 0);
GGML_ASSERT(n_per_row%16 == 0);
auto row_size_x = ggml_row_size(GGML_TYPE_Q8_KV, n_per_row);
auto row_size_y = ggml_row_size(GGML_TYPE_Q8_KV_R8, n_per_row);
const int8_t * x8[8];
#ifdef __ARM_NEON
int8x16x2_t m0, m1, m2, m3;
#endif
for (int row = 0; row < nrows; row += 8) {
auto dy = (float *)cy;
auto qy = (int8_t *)(dy + 8);
for (int k = 0; k < 8; ++k) {
auto dx = (const float *)(cx + k*row_size_x);
dy[k] = dx[0];
x8[k] = (const int8_t *)(dx + 2);
}
for (int ib = 0; ib < n_per_row/16; ++ib) {
#ifdef __AVX2__
#define MM256_SET_M128I(a, b) _mm256_insertf128_si256(_mm256_castsi128_si256(b), (a), 1)
auto m0 = MM256_SET_M128I(_mm_loadu_si128((const __m128i *)x8[4]+ib), _mm_loadu_si128((const __m128i *)x8[0]+ib));
auto m1 = MM256_SET_M128I(_mm_loadu_si128((const __m128i *)x8[5]+ib), _mm_loadu_si128((const __m128i *)x8[1]+ib));
auto m2 = MM256_SET_M128I(_mm_loadu_si128((const __m128i *)x8[6]+ib), _mm_loadu_si128((const __m128i *)x8[2]+ib));
auto m3 = MM256_SET_M128I(_mm_loadu_si128((const __m128i *)x8[7]+ib), _mm_loadu_si128((const __m128i *)x8[3]+ib));
auto t0 = _mm256_unpacklo_epi32(m0, m1);
auto t1 = _mm256_unpacklo_epi32(m2, m3);
auto t2 = _mm256_unpackhi_epi32(m0, m1);
auto t3 = _mm256_unpackhi_epi32(m2, m3);
m0 = _mm256_unpacklo_epi64(t0, t1);
m1 = _mm256_unpackhi_epi64(t0, t1);
m2 = _mm256_unpacklo_epi64(t2, t3);
m3 = _mm256_unpackhi_epi64(t2, t3);
#ifdef HAVE_FANCY_SIMD
if (online) {
m0 = _mm256_add_epi8(m0, _mm256_set1_epi8(127));
m1 = _mm256_add_epi8(m1, _mm256_set1_epi8(127));
m2 = _mm256_add_epi8(m2, _mm256_set1_epi8(127));
m3 = _mm256_add_epi8(m3, _mm256_set1_epi8(127));
}
#endif
_mm256_storeu_si256((__m256i *)qy + 4*ib+0, m0);
_mm256_storeu_si256((__m256i *)qy + 4*ib+1, m1);
_mm256_storeu_si256((__m256i *)qy + 4*ib+2, m2);
_mm256_storeu_si256((__m256i *)qy + 4*ib+3, m3);
#elif defined __ARM_NEON
m0.val[0] = vld1q_s8(x8[0]+16*ib); m0.val[1] = vld1q_s8(x8[4]+16*ib);
m1.val[0] = vld1q_s8(x8[1]+16*ib); m1.val[1] = vld1q_s8(x8[5]+16*ib);
m2.val[0] = vld1q_s8(x8[2]+16*ib); m2.val[1] = vld1q_s8(x8[6]+16*ib);
m3.val[0] = vld1q_s8(x8[3]+16*ib); m3.val[1] = vld1q_s8(x8[7]+16*ib);
auto row01 = vtrnq_s32(vreinterpretq_s32_s8(m0.val[0]), vreinterpretq_s32_s8(m1.val[0]));
auto row23 = vtrnq_s32(vreinterpretq_s32_s8(m2.val[0]), vreinterpretq_s32_s8(m3.val[0]));
m0.val[0] = vreinterpretq_s8_s64(vtrn1q_s64(vreinterpretq_s64_s32(row01.val[0]), vreinterpretq_s64_s32(row23.val[0])));
m1.val[0] = vreinterpretq_s8_s64(vtrn1q_s64(vreinterpretq_s64_s32(row01.val[1]), vreinterpretq_s64_s32(row23.val[1])));
m2.val[0] = vreinterpretq_s8_s64(vtrn2q_s64(vreinterpretq_s64_s32(row01.val[0]), vreinterpretq_s64_s32(row23.val[0])));
m3.val[0] = vreinterpretq_s8_s64(vtrn2q_s64(vreinterpretq_s64_s32(row01.val[1]), vreinterpretq_s64_s32(row23.val[1])));
row01 = vtrnq_s32(vreinterpretq_s32_s8(m0.val[1]), vreinterpretq_s32_s8(m1.val[1]));
row23 = vtrnq_s32(vreinterpretq_s32_s8(m2.val[1]), vreinterpretq_s32_s8(m3.val[1]));
m0.val[1] = vreinterpretq_s8_s64(vtrn1q_s64(vreinterpretq_s64_s32(row01.val[0]), vreinterpretq_s64_s32(row23.val[0])));
m1.val[1] = vreinterpretq_s8_s64(vtrn1q_s64(vreinterpretq_s64_s32(row01.val[1]), vreinterpretq_s64_s32(row23.val[1])));
m2.val[1] = vreinterpretq_s8_s64(vtrn2q_s64(vreinterpretq_s64_s32(row01.val[0]), vreinterpretq_s64_s32(row23.val[0])));
m3.val[1] = vreinterpretq_s8_s64(vtrn2q_s64(vreinterpretq_s64_s32(row01.val[1]), vreinterpretq_s64_s32(row23.val[1])));
vst1q_s8_x2(qy + 0 + 128*ib, m0);
vst1q_s8_x2(qy + 32 + 128*ib, m1);
vst1q_s8_x2(qy + 64 + 128*ib, m2);
vst1q_s8_x2(qy + 96 + 128*ib, m3);
#else
// TODO
for (int l = 0; l < 4; ++l) {
for (int k = 0; k < 8; ++k) for (int i = 0; i < 4; ++i) {
y[ib].qs[32*l+4*k+i+ 0] = x8[k][ib].qs[i+4*l+ 0];
y[ib].qs[32*l+4*k+i+128] = x8[k][ib].qs[i+4*l+16];
}
}
#endif
}
cx += 8*row_size_x;
cy += online ? 8*row_size_x : 8*row_size_y;
//So, if we are run-time-repacking (online = true) we don't want to change the stride, so we just leave some unused space at the end of each row
}
}
#ifdef HAVE_FANCY_SIMD
static void modify_q8_KV_r8(int64_t k, char * cy) {
int8_t * q8 = (int8_t *)(cy + 8*sizeof(float));
for (int j = 0; j < k; ++j) q8[j] += 127;
}
#endif
size_t quantize_q8_KV_r8(const float * src, void * dst, int64_t nrows, int64_t n_per_row, [[maybe_unused]] const float * imatrix) {
GGML_ASSERT(nrows%8 == 0);
GGML_ASSERT(n_per_row%16 == 0);
char * qcur = (char *)dst;
auto row_size_0 = ggml_row_size(GGML_TYPE_Q8_KV, n_per_row);
auto row_size_1 = ggml_row_size(GGML_TYPE_Q8_KV_R8, n_per_row);
std::vector<char> qtmp(8*row_size_0);
for (int row = 0; row < nrows; row += 8) {
quantize_q8_KV(src, (void *)qtmp.data(), 8, n_per_row, imatrix);
repack_q8_KV(8, n_per_row, qtmp.data(), qcur, false);
qcur += 8*row_size_1;
src += 8*n_per_row;
}
return nrows*row_size_1;
}
void dequantize_row_q8_KV_r8(const void * vx, float * y, int64_t k) {
auto n_per_row = k/8;
float * y8[8];
for (int k = 0; k < 8; ++k) y8[k] = y + n_per_row*k;
auto dptr = (const float *)vx;
auto q8 = (const int8_t *)(dptr + 8);
for (int ib = 0; ib < n_per_row/16; ++ib) {
for (int k = 0; k < 8; ++k) {
for (int l = 0; l < 4; ++l) {
for (int i = 0; i < 4; ++i) y8[k][16*ib + 4*l + i] = dptr[k] * q8[128*ib + 32*l + 4*k + i];
}
}
}
}
void vec_dot_q8_KV_r8_q8_KV(int n, float * s, size_t bs, const void * vx, size_t bx, const void * vy, size_t by, int nrc) {
#if GGML_USE_IQK_MULMAT
if (iqk_mul_mat(1, 1, n, GGML_TYPE_Q8_KV_R8, vx, 0, GGML_TYPE_Q8_KV, vy, 0, s, 0, 0, 1)) {
return;
}
#endif
GGML_ASSERT(n%QK4_NL == 0);
GGML_ASSERT(nrc == 1);
GGML_UNUSED(bs);
GGML_UNUSED(bx);
GGML_UNUSED(by);
}
//
// ========================================= bf16_r4
//
namespace {
inline ggml_bf16_t to_bf16(const float& x) {
union { float f; uint32_t u; } helper;
helper.f = x;
return ggml_bf16_t{(uint16_t)(helper.u >> 16)};
}
inline ggml_bf16_t to_bf16(const ggml_half& x) { return to_bf16(GGML_FP16_TO_FP32(x)); }
inline ggml_bf16_t to_bf16(const ggml_bf16_t& x) { return x; }
template <typename T>
void repack_bf16(int nrows, int n_per_row, const T * x, ggml_bf16_t * y, [[maybe_unused]] bool online) {
GGML_ASSERT(nrows%16 == 0);
GGML_ASSERT(n_per_row%2 == 0);
for (int row = 0; row < nrows; row += 16) {
for (int k = 0; k < 16; ++k) {
auto x8 = x + k*n_per_row;
for (int ib = 0; ib < n_per_row/2; ++ib) {
y[32*ib + 2*k + 0] = to_bf16(x8[2*ib+0]);
y[32*ib + 2*k + 1] = to_bf16(x8[2*ib+1]);
}
}
x += 16*n_per_row;
y += 16*n_per_row;
}
}
}
void repack_f32_bf16_r16(const void * src, void * dst, int64_t nrows, int64_t n_per_row) {
repack_bf16(nrows, n_per_row, (const float *)src, (ggml_bf16_t *)dst, false);
}
void repack_bf16_bf16_r16(const void * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row) {
repack_bf16(nrows, n_per_row, (const ggml_bf16_t *)src, (ggml_bf16_t *)dst, false);
}
//
// ========================================= iq3_k_r4
//
void quantize_row_iq3_k_r4_ref(const float * x, block_iq3_k_r4 * y, int64_t k) {
quantize_iq3_k_r4(x, (void *)y, 4, k/4, nullptr);
}
void quantize_row_iq3_k_r4(const float * x, void * y, int64_t k) {
quantize_iq3_k_r4(x, y, 4, k/4, nullptr);
}
namespace {
inline void convert_iq3_k(const block_iq3_k& x, uint8_t * L) {
const uint8_t * qs = x.qs;
const uint8_t * qh = x.qh;
for (int ib32 = 0; ib32 < QK_K/32; ++ib32) {
int shift_l = 2*(ib32%4);
int shift_h = ib32%8;
for (int j = 0; j < 16; ++j) {
L[j+ 0] = ((qs[j+ 0] >> shift_l) & 3) | (((qh[j+ 0] >> shift_h) & 1) << 2);
L[j+16] = ((qs[j+16] >> shift_l) & 3) | (((qh[j+16] >> shift_h) & 1) << 2);
}
L += 32;
if (shift_l == 6) qs += 32;
}
}
}
static void repack_iq3_k(int nrows, int n_per_row, const block_iq3_k * x, block_iq3_k_r4 * y, [[maybe_unused]] bool online) {
GGML_ASSERT(nrows%4 == 0);
GGML_ASSERT(n_per_row%QK_K == 0);
int nblock = n_per_row/QK_K;
const block_iq3_k * x4[4];
uint8_t L[QK_K];
for (int row = 0; row < nrows; row += 4) {
for (int k = 0; k < 4; ++k) x4[k] = x + nblock*k;
for (int ibl = 0; ibl < nblock; ++ibl) {
std::memset(y[ibl].extra, 0, 8);
std::memset(y[ibl].scales_l, 0, QK_K/8);
std::memset(y[ibl].scales_h, 0, QK_K/32);
for (int k = 0; k < 4; ++k) {
y[ibl].d[k] = x4[k][ibl].d;
auto extra = x4[k][ibl].extra;
uint16_t sh = x4[k][ibl].scales_h;
convert_iq3_k(x4[k][ibl], L);
for (int ib = 0; ib < QK_K/32; ++ib) {
if (extra & 1) y[ibl].extra[k+0] |= (1 << ib);
if (extra & 2) y[ibl].extra[k+4] |= (1 << ib);
extra >>= 2;
uint8_t sl1 = x4[k][ibl].scales_l[ib] & 0xf;
uint8_t sl2 = x4[k][ibl].scales_l[ib] >> 4;
uint8_t sh1 = (sh >> 0) & 1;
uint8_t sh2 = (sh >> 1) & 1;
sh >>= 2;
int i = 8*ib + k;
y[ibl].scales_l[i%32] |= (sl1 << 4*(i/32));
y[ibl].scales_h[i%8 ] |= (sh1 << (i/8));
i += 4;
y[ibl].scales_l[i%32] |= (sl2 << 4*(i/32));
y[ibl].scales_h[i%8 ] |= (sh2 << (i/8));
for (int i = 0; i < 4; ++i) {
y[ibl].qs[32*ib+4*k+i+ 0] = ((L[32*ib+i+ 0] & 0x3) << 0) | ((L[32*ib+i+ 4] & 0x3) << 2) | ((L[32*ib+i+ 8] & 0x3) << 4) | ((L[32*ib+i+12] & 0x3) << 6);
y[ibl].qs[32*ib+4*k+i+16] = ((L[32*ib+i+16] & 0x3) << 0) | ((L[32*ib+i+20] & 0x3) << 2) | ((L[32*ib+i+24] & 0x3) << 4) | ((L[32*ib+i+28] & 0x3) << 6);
y[ibl].qh[16*ib+4*k+i+ 0] = ((L[32*ib+i+ 0] >> 2) << 0) | ((L[32*ib+i+ 4] >> 2) << 1) | ((L[32*ib+i+ 8] >> 2) << 2) | ((L[32*ib+i+12] >> 2) << 3)
| ((L[32*ib+i+16] >> 2) << 4) | ((L[32*ib+i+20] >> 2) << 5) | ((L[32*ib+i+24] >> 2) << 6) | ((L[32*ib+i+28] >> 2) << 7);
}
}
}
}
x += 4*nblock;
y += nblock;
}
}
size_t quantize_iq3_k_r4(const float * src, void * dst, int64_t nrows, int64_t n_per_row, const float * imatrix) {
GGML_ASSERT(nrows%4 == 0);
GGML_ASSERT(n_per_row%QK_K == 0);
char * qcur = (char *)dst;
auto row_size = ggml_row_size(GGML_TYPE_IQ3_K, n_per_row);
std::vector<char> qtmp(4*row_size);
for (int row = 0; row < nrows; row += 4) {
quantize_iq3_k(src, (void *)qtmp.data(), 4, n_per_row, imatrix);
repack_iq3_k(4, n_per_row, (const block_iq3_k *)qtmp.data(), (block_iq3_k_r4 *)qcur, false);
qcur += 4*row_size;
src += 4*n_per_row;
}
return nrows*row_size;
}
void dequantize_row_iq3_k_r4(const block_iq3_k_r4 * x, float * y, int64_t k) {
auto n_per_row = k/4;
float * y4[4] = {y, y + n_per_row, y + 2*n_per_row, y + 3*n_per_row};
int nblock = n_per_row/QK_K;
for (int ibl = 0; ibl < nblock; ++ibl) {
for (int k = 0; k < 4; ++k) {
const float d = GGML_FP16_TO_FP32(x[ibl].d[k]);
auto ql = x[ibl].qs;
auto qh = x[ibl].qh;
for (int ib = 0; ib < QK_K/32; ++ib) {
int is = 8*ib + k;
float dl1 = d * (2*((x[ibl].scales_l[is%32] >> 4*(is/32)) & 0xf) + 1) * ((x[ibl].scales_h[is%8] >> (is/8)) & 1 ? -1 : 1);
is += 4;
float dl2 = d * (2*((x[ibl].scales_l[is%32] >> 4*(is/32)) & 0xf) + 1) * ((x[ibl].scales_h[is%8] >> (is/8)) & 1 ? -1 : 1);
auto values1 = iq3nl_values + (x[ibl].extra[k+0] & (1 << ib) ? 8 : 0);
auto values2 = iq3nl_values + (x[ibl].extra[k+4] & (1 << ib) ? 8 : 0);
for (int i = 0; i < 4; ++i) {
y4[k][QK_K*ibl+32*ib+i+ 0] = dl1 * values1[((ql[4*k+i+ 0] >> 0) & 3) | ((qh[4*k+i] << 2) & 4)];
y4[k][QK_K*ibl+32*ib+i+ 4] = dl1 * values1[((ql[4*k+i+ 0] >> 2) & 3) | ((qh[4*k+i] << 1) & 4)];
y4[k][QK_K*ibl+32*ib+i+ 8] = dl1 * values1[((ql[4*k+i+ 0] >> 4) & 3) | ((qh[4*k+i] << 0) & 4)];
y4[k][QK_K*ibl+32*ib+i+12] = dl1 * values1[((ql[4*k+i+ 0] >> 6) & 3) | ((qh[4*k+i] >> 1) & 4)];
y4[k][QK_K*ibl+32*ib+i+16] = dl2 * values2[((ql[4*k+i+16] >> 0) & 3) | ((qh[4*k+i] >> 2) & 4)];
y4[k][QK_K*ibl+32*ib+i+20] = dl2 * values2[((ql[4*k+i+16] >> 2) & 3) | ((qh[4*k+i] >> 3) & 4)];
y4[k][QK_K*ibl+32*ib+i+24] = dl2 * values2[((ql[4*k+i+16] >> 4) & 3) | ((qh[4*k+i] >> 4) & 4)];
y4[k][QK_K*ibl+32*ib+i+28] = dl2 * values2[((ql[4*k+i+16] >> 6) & 3) | ((qh[4*k+i] >> 5) & 4)];
}
ql += 32;
qh += 16;
}
}
}
}
void vec_dot_iq3_k_r4_q8_k(int n, float * s, size_t bs, const void * vx, size_t bx, const void * vy, size_t by, int nrc) {
#if GGML_USE_IQK_MULMAT
if (iqk_mul_mat(1, 1, n, GGML_TYPE_IQ3_K_R4, vx, 0, GGML_TYPE_Q8_K, vy, 0, s, 0, 0, 1)) {
return;
}
#endif
GGML_ASSERT(n%QK4_NL == 0);
GGML_ASSERT(nrc == 1);
GGML_UNUSED(bs);
GGML_UNUSED(bx);
GGML_UNUSED(by);
}
//
// ========================================= iq2_k_r4
//
void quantize_row_iq2_k_r4_ref(const float * x, block_iq2_k_r4 * y, int64_t k) {
quantize_iq2_k_r4(x, (void *)y, 4, k/4, nullptr);
}
void quantize_row_iq2_k_r4(const float * x, void * y, int64_t k) {
quantize_iq2_k_r4(x, y, 4, k/4, nullptr);
}
namespace {
inline void convert_iq2_k(const block_iq2_k& x, uint8_t * L) {
const uint8_t * qs = x.qs;
for (int ib32 = 0; ib32 < QK_K/32; ++ib32) {
int shift_l = 2*(ib32%4);
for (int j = 0; j < 16; ++j) {
L[j+ 0] = ((qs[j+ 0] >> shift_l) & 3);
L[j+16] = ((qs[j+16] >> shift_l) & 3);
}
L += 32;
if (shift_l == 6) qs += 32;
}
}
}
static void repack_iq2_k(int nrows, int n_per_row, const block_iq2_k * x, block_iq2_k_r4 * y, [[maybe_unused]] bool online) {
GGML_ASSERT(nrows%4 == 0);
GGML_ASSERT(n_per_row%QK_K == 0);
int nblock = n_per_row/QK_K;
const block_iq2_k * x4[4];
uint8_t L[QK_K];
for (int row = 0; row < nrows; row += 4) {
for (int k = 0; k < 4; ++k) x4[k] = x + nblock*k;
for (int ibl = 0; ibl < nblock; ++ibl) {
std::memset(y[ibl].extra, 0, 8);
std::memset(y[ibl].scales, 0, QK_K/8);
for (int k = 0; k < 4; ++k) {
y[ibl].d[k] = x4[k][ibl].d;
auto extra = x4[k][ibl].extra;
convert_iq2_k(x4[k][ibl], L);
for (int ib = 0; ib < QK_K/32; ++ib) {
if (extra & 1) y[ibl].extra[k+0] |= (1 << ib);
if (extra & 2) y[ibl].extra[k+4] |= (1 << ib);
extra >>= 2;
uint8_t sl1 = x4[k][ibl].scales[ib] & 0xf;
uint8_t sl2 = x4[k][ibl].scales[ib] >> 4;
int i = 8*ib + k;
y[ibl].scales[i%32] |= (sl1 << 4*(i/32));
i += 4;
y[ibl].scales[i%32] |= (sl2 << 4*(i/32));
for (int i = 0; i < 4; ++i) {
y[ibl].qs[32*ib+4*k+i+ 0] = ((L[32*ib+i+ 0] & 0x3) << 0) | ((L[32*ib+i+ 4] & 0x3) << 2) | ((L[32*ib+i+ 8] & 0x3) << 4) | ((L[32*ib+i+12] & 0x3) << 6);
y[ibl].qs[32*ib+4*k+i+16] = ((L[32*ib+i+16] & 0x3) << 0) | ((L[32*ib+i+20] & 0x3) << 2) | ((L[32*ib+i+24] & 0x3) << 4) | ((L[32*ib+i+28] & 0x3) << 6);
}
}
}
}
x += 4*nblock;
y += nblock;
}
}
size_t quantize_iq2_k_r4(const float * src, void * dst, int64_t nrows, int64_t n_per_row, const float * imatrix) {
GGML_ASSERT(nrows%4 == 0);
GGML_ASSERT(n_per_row%QK_K == 0);
char * qcur = (char *)dst;
auto row_size = ggml_row_size(GGML_TYPE_IQ2_K, n_per_row);
std::vector<char> qtmp(4*row_size);
for (int row = 0; row < nrows; row += 4) {
quantize_iq2_k(src, (void *)qtmp.data(), 4, n_per_row, imatrix);
repack_iq2_k(4, n_per_row, (const block_iq2_k *)qtmp.data(), (block_iq2_k_r4 *)qcur, false);
qcur += 4*row_size;
src += 4*n_per_row;
}
return nrows*row_size;
}
void dequantize_row_iq2_k_r4(const block_iq2_k_r4 * x, float * y, int64_t k) {
auto n_per_row = k/4;
float * y4[4] = {y, y + n_per_row, y + 2*n_per_row, y + 3*n_per_row};
int nblock = n_per_row/QK_K;
for (int ibl = 0; ibl < nblock; ++ibl) {
for (int k = 0; k < 4; ++k) {
const float d = GGML_FP16_TO_FP32(x[ibl].d[k]);
auto ql = x[ibl].qs;
for (int ib = 0; ib < QK_K/32; ++ib) {
int is = 8*ib + k;
float dl1 = d * (((x[ibl].scales[is%32] >> 4*(is/32)) & 0xf) - 8);
is += 4;
float dl2 = d * (((x[ibl].scales[is%32] >> 4*(is/32)) & 0xf) - 8);
auto values1 = iq2nl_values + (x[ibl].extra[k+0] & (1 << ib) ? 4 : 0);
auto values2 = iq2nl_values + (x[ibl].extra[k+4] & (1 << ib) ? 4 : 0);
for (int i = 0; i < 4; ++i) {
y4[k][QK_K*ibl+32*ib+i+ 0] = dl1 * values1[(ql[4*k+i+ 0] >> 0) & 3];
y4[k][QK_K*ibl+32*ib+i+ 4] = dl1 * values1[(ql[4*k+i+ 0] >> 2) & 3];
y4[k][QK_K*ibl+32*ib+i+ 8] = dl1 * values1[(ql[4*k+i+ 0] >> 4) & 3];
y4[k][QK_K*ibl+32*ib+i+12] = dl1 * values1[(ql[4*k+i+ 0] >> 6) & 3];
y4[k][QK_K*ibl+32*ib+i+16] = dl2 * values2[(ql[4*k+i+16] >> 0) & 3];
y4[k][QK_K*ibl+32*ib+i+20] = dl2 * values2[(ql[4*k+i+16] >> 2) & 3];
y4[k][QK_K*ibl+32*ib+i+24] = dl2 * values2[(ql[4*k+i+16] >> 4) & 3];
y4[k][QK_K*ibl+32*ib+i+28] = dl2 * values2[(ql[4*k+i+16] >> 6) & 3];
}
ql += 32;
}
}
}
}
void vec_dot_iq2_k_r4_q8_k(int n, float * s, size_t bs, const void * vx, size_t bx, const void * vy, size_t by, int nrc) {
#if GGML_USE_IQK_MULMAT
if (iqk_mul_mat(1, 1, n, GGML_TYPE_IQ2_K_R4, vx, 0, GGML_TYPE_Q8_K, vy, 0, s, 0, 0, 1)) {
return;
}
#endif
GGML_ASSERT(n%QK4_NL == 0);
GGML_ASSERT(nrc == 1);
GGML_UNUSED(bs);
GGML_UNUSED(bx);
GGML_UNUSED(by);
}
namespace {
inline uint8_t scrambled_sign(uint8_t s) {
static const uint8_t k_table[128] = {
0x00, 0x7f, 0x7e, 0x01, 0x7c, 0x03, 0x02, 0x7d, 0x78, 0x07, 0x06, 0x79, 0x04, 0x7b, 0x7a, 0x05,
0x70, 0x0f, 0x0e, 0x71, 0x0c, 0x73, 0x72, 0x0d, 0x08, 0x77, 0x76, 0x09, 0x74, 0x0b, 0x0a, 0x75,
0x60, 0x1f, 0x1e, 0x61, 0x1c, 0x63, 0x62, 0x1d, 0x18, 0x67, 0x66, 0x19, 0x64, 0x1b, 0x1a, 0x65,
0x10, 0x6f, 0x6e, 0x11, 0x6c, 0x13, 0x12, 0x6d, 0x68, 0x17, 0x16, 0x69, 0x14, 0x6b, 0x6a, 0x15,
0x40, 0x3f, 0x3e, 0x41, 0x3c, 0x43, 0x42, 0x3d, 0x38, 0x47, 0x46, 0x39, 0x44, 0x3b, 0x3a, 0x45,
0x30, 0x4f, 0x4e, 0x31, 0x4c, 0x33, 0x32, 0x4d, 0x48, 0x37, 0x36, 0x49, 0x34, 0x4b, 0x4a, 0x35,
0x20, 0x5f, 0x5e, 0x21, 0x5c, 0x23, 0x22, 0x5d, 0x58, 0x27, 0x26, 0x59, 0x24, 0x5b, 0x5a, 0x25,
0x50, 0x2f, 0x2e, 0x51, 0x2c, 0x53, 0x52, 0x2d, 0x28, 0x57, 0x56, 0x29, 0x54, 0x2b, 0x2a, 0x55,
};
return k_table[s];
}
}
//
// ========================================= iq2_xxs_r4
//
void quantize_row_iq2_xxs_r4_ref(const float * x, block_iq2_xxs_r4 * y, int64_t k) {
quantize_iq2_xxs_r4(x, (void *)y, 4, k/4, nullptr);
}
void quantize_row_iq2_xxs_r4(const float * x, void * y, int64_t k) {
quantize_iq2_xxs_r4(x, y, 4, k/4, nullptr);
}
static void repack_iq2_xxs(int nrows, int n_per_row, const block_iq2_xxs * x, block_iq2_xxs_r4 * y, [[maybe_unused]] bool online) {
GGML_ASSERT(nrows%4 == 0);
GGML_ASSERT(n_per_row%QK_K == 0);
int nblock = n_per_row/QK_K;
const block_iq2_xxs * x4[4];
uint32_t aux32[2];
const uint8_t * aux8 = (const uint8_t *)aux32;
for (int row = 0; row < nrows; row += 4) {
for (int k = 0; k < 4; ++k) x4[k] = x + nblock*k;
for (int ibl = 0; ibl < nblock; ++ibl) {
auto ysas = (uint32_t *)y[ibl].sas;
for (int k = 0; k < 4; ++k) {
y[ibl].d[k] = x4[k][ibl].d;
for (int ib = 0; ib < QK_K/32; ++ib) {
std::memcpy(aux32, x4[k][ibl].qs + 4*ib, 2*sizeof(uint32_t));
for (int i = 0; i < 4; ++i) {
y[ibl].qs[16*ib+4*k+i] = aux8[i];
}
uint8_t scale = aux32[1] >> 28;
uint8_t s1 = (scrambled_sign((aux32[1] >> 0) & 127) << 1) | ((scale >> 0) & 1);
uint8_t s2 = (scrambled_sign((aux32[1] >> 7) & 127) << 1) | ((scale >> 1) & 1);
uint8_t s3 = (scrambled_sign((aux32[1] >> 14) & 127) << 1) | ((scale >> 2) & 1);
uint8_t s4 = (scrambled_sign((aux32[1] >> 21) & 127) << 1) | ((scale >> 3) & 1);
aux32[1] = uint32_t(s1) | (uint32_t(s2) << 8) | (uint32_t(s3) << 16) | (uint32_t(s4) << 24);
ysas[4*ib+k] = aux32[1];
}
}
}
x += 4*nblock;
y += nblock;
}
}
size_t quantize_iq2_xxs_r4(const float * src, void * dst, int64_t nrows, int64_t n_per_row, const float * imatrix) {
GGML_ASSERT(nrows%4 == 0);
GGML_ASSERT(n_per_row%QK_K == 0);
char * qcur = (char *)dst;
auto row_size = ggml_row_size(GGML_TYPE_IQ2_XXS, n_per_row);
std::vector<char> qtmp(4*row_size);
for (int row = 0; row < nrows; row += 4) {
quantize_iq2_xxs(src, (void *)qtmp.data(), 4, n_per_row, imatrix);
repack_iq2_xxs(4, n_per_row, (const block_iq2_xxs *)qtmp.data(), (block_iq2_xxs_r4 *)qcur, false);
qcur += 4*row_size;
src += 4*n_per_row;
}
return nrows*row_size;
}
void dequantize_row_iq2_xxs_r4(const block_iq2_xxs_r4 * x, float * y, int64_t k) {
auto n_per_row = k/4;
float * y4[4] = {y, y + n_per_row, y + 2*n_per_row, y + 3*n_per_row};
int nblock = n_per_row/QK_K;
uint32_t s32;
const uint8_t * s8 = (const uint8_t *)&s32;
for (int ibl = 0; ibl < nblock; ++ibl) {
const uint32_t * sas = (const uint32_t *)x[ibl].sas;
for (int k = 0; k < 4; ++k) {
const float d = 0.125f*GGML_FP16_TO_FP32(x[ibl].d[k]);
for (int ib = 0; ib < QK_K/32; ++ib) {
uint32_t aux32 = sas[4*ib+k];
s32 = aux32 & 0x01010101;
uint8_t scale = s8[0] | (s8[1] << 1) | (s8[2] << 2) | (s8[3] << 3);
float dl = d*(2*scale+1);
aux32 &= 0xfefefefe;
aux32 ^= (aux32 >> 1);
for (int i = 0; i < 4; ++i) {
auto val = (const int8_t *)(iq2xxs_grid + x[ibl].qs[16*ib+4*k+i]);
for (int j = 0; j < 8; ++j) y4[k][QK_K*ibl+32*ib+8*i+j] = dl * val[j] * (aux32 & (1 << j) ? -1 : 1);
aux32 >>= 8;
}
}
}
}
}
void vec_dot_iq2_xxs_r4_q8_k(int n, float * s, size_t bs, const void * vx, size_t bx, const void * vy, size_t by, int nrc) {
#if GGML_USE_IQK_MULMAT
if (iqk_mul_mat(1, 1, n, GGML_TYPE_IQ2_XXS_R4, vx, 0, GGML_TYPE_Q8_K, vy, 0, s, 0, 0, 1)) {
return;
}
#endif
GGML_ASSERT(n%QK4_NL == 0);
GGML_ASSERT(nrc == 1);
GGML_UNUSED(bs);
GGML_UNUSED(bx);
GGML_UNUSED(by);
}
//
// ========================================= iq2_xs_r4
//
void quantize_row_iq2_xs_r4_ref(const float * x, block_iq2_xs_r4 * y, int64_t k) {
quantize_iq2_xs_r4(x, (void *)y, 4, k/4, nullptr);
}
void quantize_row_iq2_xs_r4(const float * x, void * y, int64_t k) {
quantize_iq2_xs_r4(x, y, 4, k/4, nullptr);
}
static void repack_iq2_xs(int nrows, int n_per_row, const block_iq2_xs * x, block_iq2_xs_r4 * y, [[maybe_unused]] bool online) {
GGML_ASSERT(nrows%4 == 0);
GGML_ASSERT(n_per_row%QK_K == 0);
int nblock = n_per_row/QK_K;
const block_iq2_xs * x4[4];
for (int row = 0; row < nrows; row += 4) {
for (int k = 0; k < 4; ++k) x4[k] = x + nblock*k;
for (int ibl = 0; ibl < nblock; ++ibl) {
for (int k = 0; k < 4; ++k) {
y[ibl].d[k] = x4[k][ibl].d;
for (int ib = 0; ib < QK_K/32; ++ib) {
for (int i = 0; i < 4; ++i) {
uint16_t v = x4[k][ibl].qs[4*ib+i];
uint8_t s = v >> 9;
y[ibl].qs[16*ib+4*k+i] = (v & 511) | (scrambled_sign(s) << 9);
}
y[ibl].scales[4*ib+k] = x4[k][ibl].scales[ib];
}
}
}
x += 4*nblock;
y += nblock;
}
}
size_t quantize_iq2_xs_r4(const float * src, void * dst, int64_t nrows, int64_t n_per_row, const float * imatrix) {
GGML_ASSERT(nrows%4 == 0);
GGML_ASSERT(n_per_row%QK_K == 0);
char * qcur = (char *)dst;
auto row_size = ggml_row_size(GGML_TYPE_IQ2_XS, n_per_row);
std::vector<char> qtmp(4*row_size);
for (int row = 0; row < nrows; row += 4) {
quantize_iq2_xs(src, (void *)qtmp.data(), 4, n_per_row, imatrix);
repack_iq2_xs(4, n_per_row, (const block_iq2_xs *)qtmp.data(), (block_iq2_xs_r4 *)qcur, false);
qcur += 4*row_size;
src += 4*n_per_row;
}
return nrows*row_size;
}
void dequantize_row_iq2_xs_r4(const block_iq2_xs_r4 * x, float * y, int64_t k) {
auto n_per_row = k/4;
float * y4[4] = {y, y + n_per_row, y + 2*n_per_row, y + 3*n_per_row};
int nblock = n_per_row/QK_K;
for (int ibl = 0; ibl < nblock; ++ibl) {
for (int k = 0; k < 4; ++k) {
const float d = 0.125f*GGML_FP16_TO_FP32(x[ibl].d[k]);
for (int ib = 0; ib < QK_K/32; ++ib) {
float dl1 = d * (2*(x[ibl].scales[4*ib+k] & 0xf) + 1);
float dl2 = d * (2*(x[ibl].scales[4*ib+k] >> 4) + 1);
for (int i = 0; i < 4; ++i) {
auto val = (const int8_t *)(iq2xs_grid + (x[ibl].qs[16*ib+4*k+i] & 511));
auto signs = x[ibl].qs[16*ib+4*k+i] >> 9;
signs ^= (signs << 1);
float dl = i < 2 ? dl1 : dl2;
for (int j = 0; j < 8; ++j) y4[k][QK_K*ibl+32*ib+8*i+j] = dl * val[j] * (signs & (1 << j) ? -1 : 1);
}
}
}
}
}
void vec_dot_iq2_xs_r4_q8_k(int n, float * s, size_t bs, const void * vx, size_t bx, const void * vy, size_t by, int nrc) {
#if GGML_USE_IQK_MULMAT
if (iqk_mul_mat(1, 1, n, GGML_TYPE_IQ2_XS_R4, vx, 0, GGML_TYPE_Q8_K, vy, 0, s, 0, 0, 1)) {
return;
}
#endif
GGML_ASSERT(n%QK4_NL == 0);
GGML_ASSERT(nrc == 1);
GGML_UNUSED(bs);
GGML_UNUSED(bx);
GGML_UNUSED(by);
}
//
// ========================================= iq2_s_r4
//
void quantize_row_iq2_s_r4_ref(const float * x, block_iq2_s_r4 * y, int64_t k) {
quantize_iq2_s_r4(x, (void *)y, 4, k/4, nullptr);
}
void quantize_row_iq2_s_r4(const float * x, void * y, int64_t k) {
quantize_iq2_s_r4(x, y, 4, k/4, nullptr);
}
static void repack_iq2_s(int nrows, int n_per_row, const block_iq2_s * x, block_iq2_s_r4 * y, [[maybe_unused]] bool online) {
GGML_ASSERT(nrows%4 == 0);
GGML_ASSERT(n_per_row%QK_K == 0);
int nblock = n_per_row/QK_K;
const block_iq2_s * x4[4];
for (int row = 0; row < nrows; row += 4) {
for (int k = 0; k < 4; ++k) x4[k] = x + nblock*k;
for (int ibl = 0; ibl < nblock; ++ibl) {
for (int k = 0; k < 4; ++k) {
auto signs = x4[k][ibl].qs + QK_K/8;
y[ibl].d[k] = x4[k][ibl].d;
for (int ib = 0; ib < QK_K/32; ++ib) {
y[ibl].scales[4*ib+k] = x4[k][ibl].scales[ib];
for (int i = 0; i < 4; ++i) {
y[ibl].qs[16*ib+4*k+i] = x4[k][ibl].qs[4*ib+i];
y[ibl].signs[16*ib+4*k+i] = signs[4*ib+i];
}
y[ibl].qh[4*ib+k] = x4[k][ibl].qh[ib];
}
}
}
x += 4*nblock;
y += nblock;
}
}
size_t quantize_iq2_s_r4(const float * src, void * dst, int64_t nrows, int64_t n_per_row, const float * imatrix) {
GGML_ASSERT(nrows%4 == 0);
GGML_ASSERT(n_per_row%QK_K == 0);
char * qcur = (char *)dst;
auto row_size = ggml_row_size(GGML_TYPE_IQ2_S, n_per_row);
std::vector<char> qtmp(4*row_size);
for (int row = 0; row < nrows; row += 4) {
quantize_iq2_s(src, (void *)qtmp.data(), 4, n_per_row, imatrix);
repack_iq2_s(4, n_per_row, (const block_iq2_s *)qtmp.data(), (block_iq2_s_r4 *)qcur, false);
qcur += 4*row_size;
src += 4*n_per_row;
}
return nrows*row_size;
}
void dequantize_row_iq2_s_r4(const block_iq2_s_r4 * x, float * y, int64_t k) {
auto n_per_row = k/4;
float * y4[4] = {y, y + n_per_row, y + 2*n_per_row, y + 3*n_per_row};
int nblock = n_per_row/QK_K;
for (int ibl = 0; ibl < nblock; ++ibl) {
for (int k = 0; k < 4; ++k) {
const float d = 0.125f*GGML_FP16_TO_FP32(x[ibl].d[k]);
for (int ib = 0; ib < QK_K/32; ++ib) {
float dl1 = d * (2*(x[ibl].scales[4*ib+k] & 0xf) + 1);
float dl2 = d * (2*(x[ibl].scales[4*ib+k] >> 4) + 1);
for (int i = 0; i < 4; ++i) {
auto val = (const int8_t *)(iq2s_grid + (x[ibl].qs[16*ib+4*k+i] | ((x[ibl].qh[4*ib+k] << (8 - 2*i)) & 0x300)));
auto signs = x[ibl].signs[16*ib+4*k+i];
float dl = i < 2 ? dl1 : dl2;
for (int j = 0; j < 8; ++j) y4[k][QK_K*ibl+32*ib+8*i+j] = dl * val[j] * (signs & (1 << j) ? -1 : 1);
}
}
}
}
}
void vec_dot_iq2_s_r4_q8_k(int n, float * s, size_t bs, const void * vx, size_t bx, const void * vy, size_t by, int nrc) {
#if GGML_USE_IQK_MULMAT
if (iqk_mul_mat(1, 1, n, GGML_TYPE_IQ2_S_R4, vx, 0, GGML_TYPE_Q8_K, vy, 0, s, 0, 0, 1)) {
return;
}
#endif
GGML_ASSERT(n%QK4_NL == 0);
GGML_ASSERT(nrc == 1);
GGML_UNUSED(bs);
GGML_UNUSED(bx);
GGML_UNUSED(by);
}
//
// ========================================= iq3_xxs_r4
//
void quantize_row_iq3_xxs_r4_ref(const float * x, block_iq3_xxs_r4 * y, int64_t k) {
quantize_iq3_xxs_r4(x, (void *)y, 4, k/4, nullptr);
}
void quantize_row_iq3_xxs_r4(const float * x, void * y, int64_t k) {
quantize_iq3_xxs_r4(x, y, 4, k/4, nullptr);
}
namespace {
}
static void repack_iq3_xxs(int nrows, int n_per_row, const block_iq3_xxs * x, block_iq3_xxs_r4 * y, [[maybe_unused]] bool online) {
GGML_ASSERT(nrows%4 == 0);
GGML_ASSERT(n_per_row%QK_K == 0);
int nblock = n_per_row/QK_K;
const block_iq3_xxs * x4[4];
uint32_t aux32;
for (int row = 0; row < nrows; row += 4) {
for (int k = 0; k < 4; ++k) x4[k] = x + nblock*k;
for (int ibl = 0; ibl < nblock; ++ibl) {
auto ysas = (uint32_t *)y[ibl].sas;
for (int k = 0; k < 4; ++k) {
y[ibl].d[k] = x4[k][ibl].d;
auto xsas = x4[k][ibl].qs + QK_K/4;
for (int ib = 0; ib < QK_K/32; ++ib) {
for (int i = 0; i < 8; ++i) {
y[ibl].qs[32*ib+8*k+i] = x4[k][ibl].qs[8*ib+i];
}
std::memcpy(&aux32, xsas + 4*ib, 4);
uint8_t scale = aux32 >> 28;
uint8_t s1 = (scrambled_sign((aux32 >> 0) & 127) << 1) | ((scale >> 0) & 1);
uint8_t s2 = (scrambled_sign((aux32 >> 7) & 127) << 1) | ((scale >> 1) & 1);
uint8_t s3 = (scrambled_sign((aux32 >> 14) & 127) << 1) | ((scale >> 2) & 1);
uint8_t s4 = (scrambled_sign((aux32 >> 21) & 127) << 1) | ((scale >> 3) & 1);
aux32 = uint32_t(s1) | (uint32_t(s2) << 8) | (uint32_t(s3) << 16) | (uint32_t(s4) << 24);
ysas[4*ib+k] = aux32;
}
}
}
x += 4*nblock;
y += nblock;
}
}
size_t quantize_iq3_xxs_r4(const float * src, void * dst, int64_t nrows, int64_t n_per_row, const float * imatrix) {
GGML_ASSERT(nrows%4 == 0);
GGML_ASSERT(n_per_row%QK_K == 0);
char * qcur = (char *)dst;
auto row_size = ggml_row_size(GGML_TYPE_IQ3_XXS, n_per_row);
std::vector<char> qtmp(4*row_size);
for (int row = 0; row < nrows; row += 4) {
quantize_iq3_xxs(src, (void *)qtmp.data(), 4, n_per_row, imatrix);
repack_iq3_xxs(4, n_per_row, (const block_iq3_xxs *)qtmp.data(), (block_iq3_xxs_r4 *)qcur, false);
qcur += 4*row_size;
src += 4*n_per_row;
}
return nrows*row_size;
}
void dequantize_row_iq3_xxs_r4(const block_iq3_xxs_r4 * x, float * y, int64_t k) {
auto n_per_row = k/4;
float * y4[4] = {y, y + n_per_row, y + 2*n_per_row, y + 3*n_per_row};
int nblock = n_per_row/QK_K;
uint32_t s32;
const uint8_t * s8 = (const uint8_t *)&s32;
for (int ibl = 0; ibl < nblock; ++ibl) {
const uint32_t * sas = (const uint32_t *)x[ibl].sas;
for (int k = 0; k < 4; ++k) {
const float d = 0.25f*GGML_FP16_TO_FP32(x[ibl].d[k]);
for (int ib = 0; ib < QK_K/32; ++ib) {
uint32_t aux32 = sas[4*ib+k];
s32 = aux32 & 0x01010101;
uint8_t scale = s8[0] | (s8[1] << 1) | (s8[2] << 2) | (s8[3] << 3);
float dl = d*(2*scale+1);
aux32 &= 0xfefefefe;
aux32 ^= (aux32 >> 1);
for (int i = 0; i < 8; ++i) {
auto val = (const int8_t *)(iq3xxs_grid + x[ibl].qs[32*ib+8*k+i]);
for (int j = 0; j < 4; ++j) y4[k][QK_K*ibl+32*ib+4*i+j] = dl * val[j] * (aux32 & (1 << j) ? -1 : 1);
aux32 >>= 4;
}
}
}
}
}
void vec_dot_iq3_xxs_r4_q8_k(int n, float * s, size_t bs, const void * vx, size_t bx, const void * vy, size_t by, int nrc) {
#if GGML_USE_IQK_MULMAT
if (iqk_mul_mat(1, 1, n, GGML_TYPE_IQ3_XXS_R4, vx, 0, GGML_TYPE_Q8_K, vy, 0, s, 0, 0, 1)) {
return;
}
#endif
GGML_ASSERT(n%QK4_NL == 0);
GGML_ASSERT(nrc == 1);
GGML_UNUSED(bs);
GGML_UNUSED(bx);
GGML_UNUSED(by);
}
//
// ========================================= iq3_s_r4
//
void quantize_row_iq3_s_r4_ref(const float * x, block_iq3_s_r4 * y, int64_t k) {
quantize_iq3_s_r4(x, (void *)y, 4, k/4, nullptr);
}
void quantize_row_iq3_s_r4(const float * x, void * y, int64_t k) {
quantize_iq3_s_r4(x, y, 4, k/4, nullptr);
}
static void repack_iq3_s(int nrows, int n_per_row, const block_iq3_s * x, block_iq3_s_r4 * y, [[maybe_unused]] bool online) {
GGML_ASSERT(nrows%4 == 0);
GGML_ASSERT(n_per_row%QK_K == 0);
int nblock = n_per_row/QK_K;
const block_iq3_s * x4[4];
for (int row = 0; row < nrows; row += 4) {
for (int k = 0; k < 4; ++k) x4[k] = x + nblock*k;
for (int ibl = 0; ibl < nblock; ++ibl) {
std::memset(y[ibl].scales, 0, QK_K/16);
std::memset(y[ibl].signs, 0, QK_K/2);
std::memset(y[ibl].qh, 0, QK_K/8);
for (int k = 0; k < 4; ++k) {
y[ibl].d[k] = x4[k][ibl].d;
for (int ib = 0; ib < QK_K/64; ++ib) {
int j = 8*ib + k;
y[ibl].scales[(j+0)%16] |= ((x4[k][ibl].scales[ib] & 0xf) << 4*((j+0)/16));
y[ibl].scales[(j+4)%16] |= ((x4[k][ibl].scales[ib] >> 4) << 4*((j+4)/16));
}
for (int ib = 0; ib < QK_K/32; ++ib) {
y[ibl].qh[4*ib+k] = x4[k][ibl].qh[ib]; // leave ot like this?
for (int i = 0; i < 4; ++i) {
y[ibl].qs[32*ib+k+8*i+0] = x4[k][ibl].qs[8*ib+i+0];
y[ibl].qs[32*ib+k+8*i+4] = x4[k][ibl].qs[8*ib+i+4];
}
for (int i = 0; i < 4; ++i) {
y[ibl].signs[16*ib+4*k+i] = (((x4[k][ibl].signs[4*ib+0] >> i) & 1) << 0) | (((x4[k][ibl].signs[4*ib+0] >> (4+i)) & 1) << 1) |
(((x4[k][ibl].signs[4*ib+1] >> i) & 1) << 2) | (((x4[k][ibl].signs[4*ib+1] >> (4+i)) & 1) << 3) |
(((x4[k][ibl].signs[4*ib+2] >> i) & 1) << 4) | (((x4[k][ibl].signs[4*ib+2] >> (4+i)) & 1) << 5) |
(((x4[k][ibl].signs[4*ib+3] >> i) & 1) << 6) | (((x4[k][ibl].signs[4*ib+3] >> (4+i)) & 1) << 7);
}
}
}
}
x += 4*nblock;
y += nblock;
}
}
size_t quantize_iq3_s_r4(const float * src, void * dst, int64_t nrows, int64_t n_per_row, const float * imatrix) {
GGML_ASSERT(nrows%4 == 0);
GGML_ASSERT(n_per_row%QK_K == 0);
char * qcur = (char *)dst;
auto row_size = ggml_row_size(GGML_TYPE_IQ3_S, n_per_row);
std::vector<char> qtmp(4*row_size);
for (int row = 0; row < nrows; row += 4) {
quantize_iq3_s(src, (void *)qtmp.data(), 4, n_per_row, imatrix);
repack_iq3_s(4, n_per_row, (const block_iq3_s *)qtmp.data(), (block_iq3_s_r4 *)qcur, false);
qcur += 4*row_size;
src += 4*n_per_row;
}
return nrows*row_size;
}
void dequantize_row_iq3_s_r4(const block_iq3_s_r4 * x, float * y, int64_t k) {
auto n_per_row = k/4;
float * y4[4] = {y, y + n_per_row, y + 2*n_per_row, y + 3*n_per_row};
int nblock = n_per_row/QK_K;
for (int ibl = 0; ibl < nblock; ++ibl) {
for (int k = 0; k < 4; ++k) {
const float d = GGML_FP16_TO_FP32(x[ibl].d[k]);
for (int ib = 0; ib < QK_K/32; ++ib) {
int l = 4*ib + k;
float dl = d * (1 + 2*((x[ibl].scales[l%16] >> 4*(l/16)) & 0xf));
for (int i = 0; i < 4; ++i) {
auto grid1 = (const uint8_t *)(iq3s_grid + x[ibl].qs[32*ib+k+8*i+0] + ((x[ibl].qh[4*ib+k] << (8-i)) & 0x100));
auto grid2 = (const uint8_t *)(iq3s_grid + x[ibl].qs[32*ib+k+8*i+4] + ((x[ibl].qh[4*ib+k] << (4-i)) & 0x100));
for (int j = 0; j < 4; ++j) {
y4[k][QK_K*ibl+32*ib+4*i+ 0+j] = dl * grid1[j] * (x[ibl].signs[16*ib+4*k+j] & (1 << (i+0)) ? -1 : 1);
y4[k][QK_K*ibl+32*ib+4*i+16+j] = dl * grid2[j] * (x[ibl].signs[16*ib+4*k+j] & (1 << (i+4)) ? -1 : 1);
}
}
}
}
}
}
void vec_dot_iq3_s_r4_q8_k(int n, float * s, size_t bs, const void * vx, size_t bx, const void * vy, size_t by, int nrc) {
#if GGML_USE_IQK_MULMAT
if (iqk_mul_mat(1, 1, n, GGML_TYPE_IQ3_S_R4, vx, 0, GGML_TYPE_Q8_K, vy, 0, s, 0, 0, 1)) {
return;
}
#endif
GGML_ASSERT(n%QK4_NL == 0);
GGML_ASSERT(nrc == 1);
GGML_UNUSED(bs);
GGML_UNUSED(bx);
GGML_UNUSED(by);
}
void quantize_row_iq1_s_r4_ref(const float * x, block_iq1_s_r4 * y, int64_t k) {
quantize_iq1_s_r4(x, y, 4, k/4, nullptr);
}
void quantize_row_iq1_s_r4(const float * x, void * y, int64_t k) {
quantize_iq1_s_r4(x, y, 4, k/4, nullptr);
}
size_t quantize_iq1_s_r4(const float * src, void * dst, int64_t nrows, int64_t n_per_row, const float * imatrix) {
constexpr int kBlockSize = 32;
GGML_ASSERT(nrows%4 == 0);
GGML_ASSERT(n_per_row%kBlockSize == 0);
int nblock = n_per_row/kBlockSize;
float weight[kBlockSize];
int8_t L[kBlockSize];
float pairs[2*kBlockSize];
float sumx[kBlockSize+1], sumw[kBlockSize+1];
float max[4];
uint16_t index[4];
int shift;
float invd[4];
std::vector<float> scales(4*nblock);
auto row_size = ggml_row_size(GGML_TYPE_IQ1_S_R4, n_per_row);
char * cy = (char *)dst;
for (int row = 0; row < nrows; row += 4) {
ggml_half * dptr = (ggml_half *)cy;
auto y = (block_iq1_s_r4 *)(dptr + 4);
for (int k = 0; k < 4; ++k) max[k] = 0;
for (int ibl = 0; ibl < nblock; ++ibl) {
for (int k = 0; k < 4; ++k) {
auto xb = src + k*n_per_row + kBlockSize*ibl;
float sumx2 = 0;
for (int j = 0; j < kBlockSize; ++j) sumx2 += xb[j]*xb[j];
if (sumx2 < 1e-14f) {
//printf("Found block with all zeros\n");
// all zero
int ind = 1029; // this is the grid entry with all zeros
scales[4*ibl+k] = 0;
uint16_t h = 0;
for (int i = 0; i < 4; ++i) {
y[ibl].qs[4*i + k] = ind & 255;
h |= (ind >> 8) << 3*i;
}
y[ibl].qh[k] = h;
continue;
}
float sigma2 = 1.5f*sumx2/kBlockSize;
bool have_imatrix = false;
if (imatrix) {
have_imatrix = true;
float sumwx = 0;
for (int j = 0; j < kBlockSize; ++j) {
weight[j] = imatrix[kBlockSize*ibl + j]*sqrt(sigma2 + xb[j]*xb[j]);
sumwx += weight[j]*std::abs(xb[j]);
}
if (!sumwx) {
printf("Found block with mismatching importance/model weights\n");
// Either all weights are zero, or xb is zero where weight is not zero.
// In both of these cases it is better to simply ignore the imatrix
have_imatrix = false;
}
}
if (!have_imatrix) {
for (int j = 0; j < kBlockSize; ++j) weight[j] = sqrt(sigma2 + xb[j]*xb[j]);
}
iq1s_process_1block(kBlockSize, xb, weight, L, scales.data() + 4*ibl + k, index, &shift, pairs, sumx, sumw);
GGML_ASSERT(scales[4*ibl+k] >= 0);
max[k] = std::max(max[k], scales[4*ibl+k]);
uint16_t h = 0;
for (int i = 0; i < 4; ++i) {
GGML_ASSERT(index[i] >= 0 && index[i] < 2048);
y[ibl].qs[4*i + k] = index[i] & 255;
h |= (index[i] >> 8) << 3*i;
}
if (shift < 0) h |= 0x8000;
y[ibl].qh[k] = h;
}
}
for (int k = 0; k < 4; ++k) {
dptr[k] = GGML_FP32_TO_FP16(1.0625f*max[k]/15);;
invd[k] = max[k] ? 15/max[k] : 0.f;
}
for (int ibl = 0; ibl < nblock; ++ibl) {
for (int k = 0; k < 4; ++k) {
int ls = nearest_int(0.5f*(scales[4*ibl+k]*invd[k] - 1));
ls = std::max(0, std::min(7, ls));
y[ibl].qh[k] |= (ls << 12);
}
}
cy += 4*row_size;
src += 4*n_per_row;
}
return nrows*row_size;
}
void dequantize_row_iq1_s_r4(const block_iq1_s_r4 * x, float * y, int64_t n) {
auto dptr = (const ggml_half *)x;
x = (const block_iq1_s_r4 *)(dptr + 4);
float d[4];
for (int k = 0; k < 4; ++k) d[k] = GGML_FP16_TO_FP32(dptr[k]);
int n_per_row = n/4;
GGML_ASSERT(n_per_row%32 == 0);
int nblock = n_per_row/32;
float * yk[4];
for (int k = 0; k < 4; ++k) yk[k] = y + k*n_per_row;
for (int ib = 0; ib < nblock; ++ib) {
for (int k = 0; k < 4; ++k) {
float shift = x[ib].qh[k] & 0x8000 ? -IQ1S_DELTA : IQ1S_DELTA;
float dl = d[k]*(2*((x[ib].qh[k] >> 12) & 7) + 1);
for (int i = 0; i < 4; ++i) {
auto idx = x[ib].qs[4*i+k] | (((x[ib].qh[k] >> 3*i) & 7) << 8);
auto grid = (const int8_t *)(iq1s_grid + idx);
for (int j = 0; j < 8; ++j) yk[k][32*ib + 8*i + j] = dl*(grid[j] + shift);
}
}
}
}
void vec_dot_iq1_s_r4_q8_k(int n, float * s, size_t bs, const void * vx, size_t bx, const void * vy, size_t by, int nrc) {
#if GGML_USE_IQK_MULMAT
if (iqk_mul_mat(1, 1, n, GGML_TYPE_IQ1_S_R4, vx, 0, GGML_TYPE_Q8_K, vy, 0, s, 0, 0, 1)) {
return;
}
#endif
GGML_ASSERT(n%QK4_NL == 0);
GGML_ASSERT(nrc == 1);
GGML_UNUSED(bs);
GGML_UNUSED(bx);
GGML_UNUSED(by);
}
void quantize_row_iq1_m_r4_ref(const float * x, block_iq1_m_r4 * y, int64_t k) {
quantize_iq1_m_r4(x, y, 4, k/4, nullptr);
}
void quantize_row_iq1_m_r4(const float * x, void * y, int64_t k) {
quantize_iq1_m_r4(x, y, 4, k/4, nullptr);
}
size_t quantize_iq1_m_r4(const float * src, void * dst, int64_t nrows, int64_t n_per_row, const float * imatrix) {
constexpr int kBlockSize = 32;
GGML_ASSERT(nrows%4 == 0);
GGML_ASSERT(n_per_row%kBlockSize == 0);
int nblock = n_per_row/kBlockSize;
float weight[kBlockSize];
int8_t L[kBlockSize];
float pairs[2*kBlockSize];
float max[4];
uint16_t index[4];
int shift1, shift2;
float invd[4];
const uint8_t masks[4] = {0x00, 0x80, 0x08, 0x88};
std::vector<float> scales(8*nblock);
auto row_size = ggml_row_size(GGML_TYPE_IQ1_M_R4, n_per_row);
char * cy = (char *)dst;
for (int row = 0; row < nrows; row += 4) {
ggml_half * dptr = (ggml_half *)cy;
auto y = (block_iq1_m_r4 *)(dptr + 4);
for (int k = 0; k < 4; ++k) max[k] = 0;
for (int ibl = 0; ibl < nblock; ++ibl) {
for (int k = 0; k < 4; ++k) {
auto xb = src + k*n_per_row + kBlockSize*ibl;
float sumx2 = 0;
for (int j = 0; j < kBlockSize; ++j) sumx2 += xb[j]*xb[j];
if (sumx2 < 1e-14f) {
scales[8*ibl+2*k+0] = scales[8*ibl+2*k+1] = 0;
continue;
}
float sigma2 = 1.5f*sumx2/kBlockSize;
if (imatrix) {
for (int j = 0; j < kBlockSize; ++j) weight[j] = imatrix[kBlockSize*ibl + j]*sqrt(sigma2 + xb[j]*xb[j]);
float sumwx = 0;
for (int j = 0; j < kBlockSize; ++j) sumwx += weight[j]*std::abs(xb[j]);
if (!sumwx) {
for (int j = 0; j < kBlockSize; ++j) weight[j] = sqrt(sigma2 + xb[j]*xb[j]);
}
} else {
for (int j = 0; j < kBlockSize; ++j) weight[j] = sqrt(sigma2 + xb[j]*xb[j]);
}
iq1m_process_1block(xb+ 0, weight+ 0, L, scales.data() + 8*ibl + 2*k+0, index+0, &shift1, pairs);
iq1m_process_1block(xb+16, weight+16, L, scales.data() + 8*ibl + 2*k+1, index+2, &shift2, pairs);
max[k] = std::max(max[k], std::max(scales[8*ibl+2*k+0], scales[8*ibl+2*k+1]));
for (int i = 0; i < 4; ++i) {
y[ibl].qs[4*i + k] = index[i] & 255;
}
for (int i = 0; i < 2; ++i) {
y[ibl].qh[4*i+k] = (index[2*i+0] >> 8) | ((index[2*i+1] >> 8) << 4);
}
y[ibl].qh[0+k] |= masks[shift1];
y[ibl].qh[4+k] |= masks[shift2];
}
}
for (int k = 0; k < 4; ++k) {
dptr[k] = GGML_FP32_TO_FP16(1.0625f*max[k]/15);;
invd[k] = max[k] ? 15/max[k] : 0.f;
}
for (int ibl = 0; ibl < nblock; ++ibl) {
for (int k = 0; k < 4; ++k) {
int ls1 = nearest_int(scales[8*ibl+2*k+0]*invd[k]);
int ls2 = nearest_int(scales[8*ibl+2*k+1]*invd[k]);
ls1 = std::max(0, std::min(15, ls1));
ls2 = std::max(0, std::min(15, ls2));
y[ibl].scales[k] = ls1 | (ls2 << 4);
}
}
cy += 4*row_size;
src += 4*n_per_row;
}
return nrows*row_size;
}
void dequantize_row_iq1_m_r4(const block_iq1_m_r4 * x, float * y, int64_t n) {
auto dptr = (const ggml_half *)x;
x = (const block_iq1_m_r4 *)(dptr + 4);
float d[4];
for (int k = 0; k < 4; ++k) d[k] = GGML_FP16_TO_FP32(dptr[k]);
int n_per_row = n/4;
GGML_ASSERT(n_per_row%32 == 0);
int nblock = n_per_row/32;
float dl[2];
float * yk[4];
for (int k = 0; k < 4; ++k) yk[k] = y + k*n_per_row;
for (int ib = 0; ib < nblock; ++ib) {
for (int k = 0; k < 4; ++k) {
dl[0] = d[k]*(x[ib].scales[k] & 0xf);
dl[1] = d[k]*(x[ib].scales[k] >> 4);
for (int i = 0; i < 2; ++i) {
auto idx1 = x[ib].qs[8*i+k+0] | ((x[ib].qh[4*i+k] & 0x07) << 8);
auto idx2 = x[ib].qs[8*i+k+4] | ((x[ib].qh[4*i+k] & 0x70) << 4);
auto grid1 = (const int8_t *)(iq1s_grid + idx1);
auto grid2 = (const int8_t *)(iq1s_grid + idx2);
auto delta1 = x[ib].qh[4*i+k] & 0x08 ? -IQ1M_DELTA : IQ1M_DELTA;
auto delta2 = x[ib].qh[4*i+k] & 0x80 ? -IQ1M_DELTA : IQ1M_DELTA;
for (int j = 0; j < 8; ++j) yk[k][32*ib + 16*i + j + 0] = dl[i]*(grid1[j] + delta1);
for (int j = 0; j < 8; ++j) yk[k][32*ib + 16*i + j + 8] = dl[i]*(grid2[j] + delta2);
}
}
}
}
void vec_dot_iq1_m_r4_q8_k(int n, float * s, size_t bs, const void * vx, size_t bx, const void * vy, size_t by, int nrc) {
#if GGML_USE_IQK_MULMAT
if (iqk_mul_mat(1, 1, n, GGML_TYPE_IQ1_M_R4, vx, 0, GGML_TYPE_Q8_K, vy, 0, s, 0, 0, 1)) {
return;
}
#endif
GGML_ASSERT(n%QK4_NL == 0);
GGML_ASSERT(nrc == 1);
GGML_UNUSED(bs);
GGML_UNUSED(bx);
GGML_UNUSED(by);
}
void quantize_row_q8_KV(const float * x, void * vy, int64_t k) {
iqk_quantize_row_q8_KV(x, vy, k);
}
void quantize_row_q8_KV_ref(const float * x, void * y, int64_t k) {
quantize_row_q8_KV(x, y, k);
}
size_t quantize_q8_KV(const float * src, void * dst, int64_t nrows, int64_t n_per_row, const float * imatrix) {
(void)imatrix;
auto row_size = ggml_row_size(GGML_TYPE_Q8_KV, n_per_row);
auto q = (char *)dst;
for (int row = 0; row < nrows; ++row) {
quantize_row_q8_KV(src, q, n_per_row);
src += n_per_row;
q += row_size;
}
return row_size*nrows;
}
void dequantize_row_q8_KV(const void * x, float * y, int64_t k) {
auto dptr = (const float *)x;
float d = dptr[0];
auto q8 = (const int8_t *)(dptr + 2);
for (int j = 0; j < k; ++j) y[j] = d * q8[j];
}
void vec_dot_q8_KV_q8_KV(int n, float * s, size_t bs, const void * vx, size_t bx, const void * vy, size_t by, int nrc) {
#if GGML_USE_IQK_MULMAT
if (iqk_mul_mat(1, 1, n, GGML_TYPE_Q8_KV, vx, 0, GGML_TYPE_Q8_KV, vy, 0, s, 0, 0, 1)) {
return;
}
#endif
GGML_ASSERT(n%QK4_NL == 0);
GGML_ASSERT(nrc == 1);
GGML_UNUSED(bs);
GGML_UNUSED(bx);
GGML_UNUSED(by);
}
//================================================
namespace {
struct Repack {
using repack_func = void (*) (int nrows, int n_per_row, const char * src, char * dst, bool online);
ggml_type new_type;
int num_rows;
repack_func repack;
};
struct Modify {
using modify_func_t = void (*)(int64_t k, char * src_dst);
modify_func_t mod_func;
int nrows;
};
const Modify * get_modify_info(ggml_type type) {
static const std::unordered_map<ggml_type, Modify> k_mod_map = {
#ifdef __ARM_NEON
{ GGML_TYPE_Q4_0_R8, {modify_q4_0_r8, 8} },
#endif
#ifdef HAVE_FANCY_SIMD
{ GGML_TYPE_Q8_0_R8, {modify_q8_0_r8, 8} },
{ GGML_TYPE_Q8_K_R8, {modify_q8_k_r8, 8} },
{ GGML_TYPE_Q8_KV_R8, {modify_q8_KV_r8, 8} },
#endif
};
auto it = k_mod_map.find(type);
return it != k_mod_map.end() ? &it->second : nullptr;
}
bool is_forbidden_tensor(const std::string& name) {
static const std::string kTokenEmbd{"token_embd.weight"};
if (name == kTokenEmbd) return true;
//if (auto pos = name.find("attn_kv_b.weight"); pos != std::string::npos) return true;
return false;
}
}
bool iqk_should_modify_tensor([[maybe_unused]] const struct ggml_tensor * tensor) {
return false;
//if (is_forbidden_tensor(tensor->name)) return false;
//auto mptr = get_modify_info(tensor->type);
//return mptr ? true : false;
}
bool iqk_modify_tensor(struct ggml_tensor * tensor) {
return false;
auto mptr = get_modify_info(tensor->type);
if (!mptr) return false;
if (is_forbidden_tensor(std::string{tensor->name})) return false;
auto& m = *mptr;
int nrows = ggml_nrows(tensor);
int nchunks = nrows/m.nrows;
int max_thread = std::max(1, int(std::thread::hardware_concurrency()/2));
int nthread = std::min(nchunks, max_thread);
auto row_size = ggml_row_size(tensor->type, tensor->ne[0]);
std::atomic<int> counter(0);
auto compute = [&counter, &m, tensor, row_size, nchunks] () {
int64_t n_per_call = m.nrows*tensor->ne[0];
while (true) {
int row = counter.fetch_add(1);
if (row >= nchunks) break;
m.mod_func(n_per_call, (char *)tensor->data + row_size*row*m.nrows);
}
};
std::vector<std::thread> workers(nthread-1);
for (auto& w : workers) w = std::thread(compute);
compute();
for (auto& w : workers) w.join();
return true;
}
namespace {
const Repack * get_repack_info(ggml_type type) {
static const std::unordered_map<ggml_type, Repack> k_map = {
{ GGML_TYPE_IQ2_K, { GGML_TYPE_IQ2_K_R4, 4, (Repack::repack_func)repack_iq2_k} },
{ GGML_TYPE_IQ3_K, { GGML_TYPE_IQ3_K_R4, 4, (Repack::repack_func)repack_iq3_k} },
{ GGML_TYPE_IQ4_K, { GGML_TYPE_IQ4_K_R4, 4, (Repack::repack_func)repack_iq4_k} },
{ GGML_TYPE_IQ5_K, { GGML_TYPE_IQ5_K_R4, 4, (Repack::repack_func)repack_iq5_k} },
{ GGML_TYPE_IQ4_XS, { GGML_TYPE_IQ4_XS_R8, 8, (Repack::repack_func)repack_iq4_xs} },
{ GGML_TYPE_IQ4_KS, { GGML_TYPE_IQ4_KS_R4, 4, (Repack::repack_func)repack_iq4_ks} },
{ GGML_TYPE_IQ4_NL, { GGML_TYPE_IQ4_NL_R4, 4, (Repack::repack_func)repack_iq4_nl} },
{ GGML_TYPE_IQ2_BN, { GGML_TYPE_IQ2_BN_R4, 4, (Repack::repack_func)repack_iq2_bn} },
{ GGML_TYPE_IQ2_XXS,{ GGML_TYPE_IQ2_XXS_R4,4, (Repack::repack_func)repack_iq2_xxs} },
{ GGML_TYPE_IQ2_XS, { GGML_TYPE_IQ2_XS_R4, 4, (Repack::repack_func)repack_iq2_xs} },
{ GGML_TYPE_IQ2_S, { GGML_TYPE_IQ2_S_R4, 4, (Repack::repack_func)repack_iq2_s} },
{ GGML_TYPE_IQ3_XXS,{ GGML_TYPE_IQ3_XXS_R4,4, (Repack::repack_func)repack_iq3_xxs} },
{ GGML_TYPE_IQ3_S, { GGML_TYPE_IQ3_S_R4, 4, (Repack::repack_func)repack_iq3_s} },
{ GGML_TYPE_Q2_K, { GGML_TYPE_Q2_K_R4, 4, (Repack::repack_func)repack_q2_k} },
{ GGML_TYPE_Q3_K, { GGML_TYPE_Q3_K_R4, 4, (Repack::repack_func)repack_q3_k} },
{ GGML_TYPE_Q4_K, { GGML_TYPE_Q4_K_R4, 4, (Repack::repack_func)repack_q4_k} },
{ GGML_TYPE_Q5_K, { GGML_TYPE_Q5_K_R4, 4, (Repack::repack_func)repack_q5_k} },
{ GGML_TYPE_Q6_K, { GGML_TYPE_Q6_K_R4, 4, (Repack::repack_func)repack_q6_k} },
{ GGML_TYPE_Q4_0, { GGML_TYPE_Q4_0_R8, 8, (Repack::repack_func)repack_q4_0} },
{ GGML_TYPE_Q5_0, { GGML_TYPE_Q5_0_R4, 4, (Repack::repack_func)repack_q5_0} },
{ GGML_TYPE_Q6_0, { GGML_TYPE_Q6_0_R4, 4, (Repack::repack_func)repack_q6_0} },
{ GGML_TYPE_Q8_0, { GGML_TYPE_Q8_0_R8, 8, (Repack::repack_func)repack_q8_0} },
{ GGML_TYPE_Q8_K, { GGML_TYPE_Q8_K_R8, 8, (Repack::repack_func)repack_q8_k} },
{ GGML_TYPE_Q8_KV, { GGML_TYPE_Q8_KV_R8, 8, (Repack::repack_func)repack_q8_KV} },
#ifdef __AVX512BF16__
{ GGML_TYPE_BF16, { GGML_TYPE_BF16_R16, 16, (Repack::repack_func)repack_bf16<ggml_bf16_t>}},
{ GGML_TYPE_F16, { GGML_TYPE_BF16_R16, 16, (Repack::repack_func)repack_bf16<ggml_half>} },
#endif
};
auto it = k_map.find(type);
return it != k_map.end() ? &it->second : nullptr;
}
}
int iqk_repacked_type(const struct ggml_tensor * tensor) {
if (!ggml_is_contiguous(tensor)) return (int)tensor->type;
if (is_forbidden_tensor(tensor->name)) return (int)tensor->type;
auto rptr = get_repack_info(tensor->type);
return rptr && tensor->ne[1] % rptr->num_rows == 0 ? (int)rptr->new_type : (int)tensor->type;
}
void iqk_repack_tensor(struct ggml_tensor * tensor) {
constexpr int kChunk = 8;
if (!tensor) return;
if (!ggml_is_contiguous(tensor)) return;
if (is_forbidden_tensor(tensor->name)) return;
if (tensor->ne[1] % 4) return;
auto rptr = get_repack_info(tensor->type);
if (!rptr) return;
if (tensor->ne[1] % rptr->num_rows) return;
auto& r = *rptr;
auto nrows = ggml_nrows(tensor);
int max_thread = std::max(1, int(std::thread::hardware_concurrency()/2));
int num_chunks = (nrows + kChunk*r.num_rows - 1)/(kChunk*r.num_rows);
int nthread = std::min(num_chunks, max_thread);
//printf("%s(%s): %s -> %s. %d rows, %d chunks, %d threads\n", __func__, tensor->name, ggml_type_name(tensor->type), ggml_type_name(r.new_type),
// int(tensor->ne[1]), num_chunks, nthread);
std::atomic<int> counter(0);;
auto compute = [&counter, &r, tensor, num_chunks, chunkSize = kChunk] () {
int nrows = ggml_nrows(tensor);
int n_per_row = tensor->ne[0];
auto row_size = ggml_row_size(tensor->type, n_per_row);
std::vector<char> qtmp(r.num_rows*row_size);
auto data = (char *)tensor->data;
while (true) {
int chunk = counter.fetch_add(1);
if (chunk >= num_chunks) break;
int first_row = chunk*chunkSize*r.num_rows;
int last_row = std::min(first_row + chunkSize*r.num_rows, nrows);
for (int row = first_row; row < last_row; row += r.num_rows) {
std::memcpy(qtmp.data(), data + row*row_size, r.num_rows*row_size);
//r.repack(r.num_rows, n_per_row, qtmp.data(), data + row*row_size, true);
r.repack(r.num_rows, n_per_row, qtmp.data(), data + row*row_size, false);
}
}
};
std::vector<std::thread> workers(nthread-1);
for (auto& w : workers) w = std::thread(compute);
compute();
for (auto& w : workers) w.join();
tensor->type = r.new_type;
}
void dequantize_row_ms_i2s(const void * vx, float * y, int64_t k) {
constexpr int kBlockSize = 128;
constexpr int kGroupSize = kBlockSize/4;
GGML_ASSERT(k % kBlockSize == 0);
const uint8_t * x = (const uint8_t *)vx;
const float * dptr = (const float *)(x + k/4);
const float d = dptr[0];
int nb = k/kBlockSize;
for (int ib = 0; ib < nb; ++ib) {
for (int ig = 0; ig < kBlockSize/kGroupSize; ++ig) {
int shift = 6 - 2*ig;
for (int j = 0; j < kGroupSize; ++j) {
y[j] = d * (((x[j] >> shift) & 3) - 1);
}
y += kGroupSize;
}
x += kGroupSize;
}
}
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