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iq2_xxs: tune quantization (llama/5320)

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We get slightly better PPL, and we cut quantization time in
nearly half.

The trick is to 1st quantize without forcing points onto the E8-lattice.
We can then use a narrower search range around the block scale that we
got that way.

Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
This commit is contained in:
Kawrakow 2024-02-05 10:46:06 +02:00 committed by Georgi Gerganov
parent 1b5bb7792e
commit 0ed762d691
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1 changed files with 6 additions and 52 deletions
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58
ggml-quants.c
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@ -9048,8 +9048,6 @@ static void quantize_row_iq2_xxs_impl(const float * restrict x, void * restrict
int8_t L[32];
int8_t Laux[32];
float waux[32];
bool is_on_grid[4];
bool is_on_grid_aux[4];
uint8_t block_signs[4];
uint32_t q2[2*(QK_K/32)];
@ -9099,10 +9097,11 @@ static void quantize_row_iq2_xxs_impl(const float * restrict x, void * restrict
memset(L, 0, 32);
continue;
}
float scale = make_qp_quants(32, kMaxQ+1, xval, (uint8_t*)L, weight);
float eff_max = scale*kMaxQ;
float best = 0;
float scale = max/(2*kMaxQ-1);
for (int is = -9; is <= 9; ++is) {
float id = (2*kMaxQ-1+is*0.1f)/max;
for (int is = -6; is <= 6; ++is) {
float id = (2*kMaxQ-1+is*0.1f)/eff_max;
float this_scale = 1/id;
for (int k = 0; k < 4; ++k) {
for (int i = 0; i < 8; ++i) {
@ -9112,9 +9111,7 @@ static void quantize_row_iq2_xxs_impl(const float * restrict x, void * restrict
uint16_t u = 0;
for (int i = 0; i < 8; ++i) u |= (Laux[8*k+i] << 2*i);
int grid_index = kmap_q2xs[u];
is_on_grid_aux[k] = true;
if (grid_index < 0) {
is_on_grid_aux[k] = false;
const uint16_t * neighbours = kneighbors_q2xs - kmap_q2xs[u] - 1;
grid_index = iq2_find_best_neighbour(neighbours, kgrid_q2xs, xval + 8*k, waux + 8*k, this_scale, Laux + 8*k);
}
@ -9128,16 +9125,12 @@ static void quantize_row_iq2_xxs_impl(const float * restrict x, void * restrict
}
if (sumq2 > 0 && sumqx*sumqx > best*sumq2) {
scale = sumqx/sumq2; best = scale*sumqx;
for (int i = 0; i < 32; ++i) L[i] = Laux[i];
for (int k = 0; k < 4; ++k) is_on_grid[k] = is_on_grid_aux[k];
memcpy(L, Laux, 32);
}
}
int n_not_ongrid = 0;
for (int k = 0; k < 4; ++k) if (!is_on_grid[k]) ++n_not_ongrid;
if (n_not_ongrid > 0 && scale > 0) {
if (scale > 0) {
float id = 1/scale;
for (int k = 0; k < 4; ++k) {
if (is_on_grid[k]) continue;
uint16_t u = 0;
for (int i = 0; i < 8; ++i) {
int l = nearest_int(0.5f*(id*xval[8*k+i]-1));
@ -9193,49 +9186,10 @@ static void quantize_row_iq2_xxs_impl(const float * restrict x, void * restrict
float d = max_scale/31;
y[ibl].d = GGML_FP32_TO_FP16(d);
float id = 1/d;
float sumqx = 0, sumq2 = 0;
for (int ib = 0; ib < QK_K/32; ++ib) {
int l = nearest_int(0.5f*(id*scales[ib]-1));
l = MAX(0, MIN(15, l));
q2[2*ib+1] |= ((uint32_t)l << 28);
const float * xb = xbl + 32*ib;
const float * qw = quant_weights + QK_K*ibl + 32*ib;
for (int i = 0; i < 32; ++i) weight[i] = qw[i] * sqrtf(sigma2 + xb[i]*xb[i]);
const uint8_t * aux8 = (const uint8_t *)(q2 + 2*ib);
const float db = d * (1 + 2*l);
uint32_t u = 0;
for (int k = 0; k < 4; ++k) {
const int8_t * signs = keven_signs_q2xs + 8*((q2[2*ib+1] >> 7*k) & 127);
const float * xk = xb + 8*k;
const float * wk = weight + 8*k;
const uint8_t * grid = (const uint8_t *)(kgrid_q2xs + aux8[k]);
float best_mse = 0; int best_index = aux8[k];
for (int j = 0; j < 8; ++j) {
float diff = db * grid[j] * signs[j] - xk[j];
best_mse += wk[j] * diff * diff;
}
for (int idx = 0; idx < 256; ++idx) {
grid = (const uint8_t *)(kgrid_q2xs + idx);
float mse = 0;
for (int j = 0; j < 8; ++j) {
float diff = db * grid[j] * signs[j] - xk[j];
mse += wk[j] * diff * diff;
}
if (mse < best_mse) {
best_mse = mse; best_index = idx;
}
}
u |= (best_index << 8*k);
grid = (const uint8_t *)(kgrid_q2xs + best_index);
//grid = (const uint8_t *)(kgrid_q2xs + aux8[k]);
for (int j = 0; j < 8; ++j) {
float q = db * grid[j] * signs[j];
sumqx += wk[j] * q * xk[j];
sumq2 += wk[j] * q * q;
}
}
q2[2*ib] = u;
if (sumq2 > 0) y[ibl].d = GGML_FP32_TO_FP16(d*sumqx/sumq2);
}
memcpy(y[ibl].qs, q2, QK_K/4);
}