sanitize imatrix: iq2_ks and iq2_kl

This commit is contained in:
Iwan Kawrakow
2025-08-27 14:19:27 +03:00
parent e935625f12
commit 63efad8978

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@@ -1464,12 +1464,11 @@ size_t quantize_iq2_ks(const float * src, void * dst, int64_t nrows, int64_t n_p
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;
}
auto q_func = [&all_scales, &all_sw, &all_Ls] (const float * x, void * vy, int n_per_row, const float * imatrix) {
quantize_row_iq2_ks_impl(x, vy, n_per_row, imatrix, all_scales.data(), all_sw.data(), all_Ls.data());
};
QHelper helper(imatrix, n_per_row, kBlockSize);
helper.quantize(nrows, src, dst, row_size, q_func);
return nrows * row_size;
}
@@ -1829,12 +1828,11 @@ size_t quantize_iq2_kl(const float * src, void * dst, int64_t nrows, int64_t n_p
auto row_size = ggml_row_size(GGML_TYPE_IQ2_KL, n_per_row);
int nblock = n_per_row/QK_K;
std::vector<float> all_scales(nblock*(QK_K/kBlockSize));
char * qrow = (char *)dst;
for (int64_t row = 0; row < nrows; ++row) {
quantize_row_iq2_kl_impl(src, (void *)qrow, n_per_row, imatrix, all_scales.data());
src += n_per_row;
qrow += row_size;
}
auto q_func = [&all_scales] (const float * x, void * vy, int n_per_row, const float * imatrix) {
quantize_row_iq2_kl_impl(x, vy, n_per_row, imatrix, all_scales.data());
};
QHelper helper(imatrix, n_per_row, kBlockSize);
helper.quantize(nrows, src, dst, row_size, q_func);
return nrows * row_size;
}
@@ -4638,75 +4636,6 @@ static void quantize_row_iq4_kss_impl(int n_per_row, const float * x, char * cy,
}
if (sumq2 > 0) *dptr = sumqx/sumq2 * 1.01f;
}
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) {
@@ -4741,19 +4670,6 @@ void dequantize_row_iq4_kss(const block_iq4_kss * x, float * y, int64_t k) {
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;