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https://github.com/ikawrakow/ik_llama.cpp.git
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iq3_k: Basics
Quantize/dequantize, CUDA dequantize. PPL of LLaMA-3.1-8B is better than iq3_s and iq3_m.
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Kawrakow
@@ -628,6 +628,274 @@ void vec_dot_iq2_k_q8_k(int n, float * GGML_RESTRICT s, size_t bs, const void *
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const block_q8_K * y = (const block_q8_K *)vy;
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}
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//
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// ============================================== iq3_k
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//
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namespace {
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static int8_t iq3nl_index[69] = {
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1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3,
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3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5,
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5, 5, 5, 5, 5
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};
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static inline int best_index_iq3nl(const int8_t * values, float x) {
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int index = x < values[1] ? 0 : x >= values[6] ? 6 : iq3nl_index[(int)x - values[1]];
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return x - values[index] < values[index+1] - x ? index : index+1;
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}
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static void quantize_row_iq3_k_impl(const float * x, void * vy, int n_per_row, const float * quant_weights) {
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const int ntry = 5;
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block_iq3_k * y = (block_iq3_k *)vy;
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float scales[QK_K/16];
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float weight[16];
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const int8_t * shifted_values = iq3nl_values + 8;
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for (int ibl = 0; ibl < n_per_row/QK_K; ++ibl) {
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memset(&y[ibl], 0, sizeof(block_iq3_k));
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y[ibl].d = GGML_FP32_TO_FP16(0.f);
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const float * xbl = x + ibl*QK_K;
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float sumx2 = 0;
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for (int j = 0; j < QK_K; ++j) sumx2 += xbl[j]*xbl[j];
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const float sigma2 = sumx2/QK_K;
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uint16_t extra = 0;
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float max_abs_scale = 0;
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for (int ib = 0; ib < QK_K/16; ++ib) {
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const float * xb = xbl + 16*ib;
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if (quant_weights) {
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const float * qw = quant_weights + ibl*QK_K + ib*16;
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for (int j = 0; j < 16; ++j) weight[j] = qw[j] * sqrtf(sigma2 + xb[j]*xb[j]);
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} else {
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for (int j = 0; j < 16; ++j) weight[j] = 0.25f*sigma2 + xb[j]*xb[j];
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}
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float amax = 0, max = 0;
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for (int j = 0; j < 16; ++j) {
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float ax = fabsf(xb[j]);
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if (ax > amax) {
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amax = ax; max = xb[j];
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}
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}
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if (!amax) {
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scales[ib] = 0;
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continue;
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}
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float d = ntry > 0 ? -max/iq3nl_values[0] : max/iq3nl_values[0];
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float id = 1/d;
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float sumqx_p = 0, sumq2_p = 0;
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float sumqx_m = 0, sumq2_m = 0;
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for (int j = 0; j < 16; ++j) {
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float w = weight[j];
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float al = id*xb[j];
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int l = best_index_iq3nl(iq3nl_values, al);
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float q = iq3nl_values[l];
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sumqx_p += w*q*xb[j];
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sumq2_p += w*q*q;
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l = best_index_iq3nl(iq3nl_values, -al);
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q = iq3nl_values[l];
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sumqx_m += w*q*xb[j];
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sumq2_m += w*q*q;
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}
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d = sumqx_p/sumq2_p;
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float best = d*sumqx_p;
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if (sumq2_m > 0 && sumqx_m*sumqx_m > best*sumq2_m) {
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d = sumqx_m/sumq2_m; best = d*sumqx_m;
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}
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bool is_shifted = false;
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for (int itry = -ntry; itry <= ntry; ++itry) {
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id = (itry + iq3nl_values[0])/max;
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sumqx_p = sumq2_p = 0;
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sumqx_m = sumq2_m = 0;
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for (int j = 0; j < 16; ++j) {
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float w = weight[j];
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float al = id*xb[j];
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int l = best_index_iq3nl(iq3nl_values, al);
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float q = iq3nl_values[l];
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sumqx_p += w*q*xb[j];
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sumq2_p += w*q*q;
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l = best_index_iq3nl(iq3nl_values, -al);
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q = iq3nl_values[l];
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sumqx_m += w*q*xb[j];
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sumq2_m += w*q*q;
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}
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if (sumq2_p > 0 && sumqx_p*sumqx_p > best*sumq2_p) {
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d = sumqx_p/sumq2_p; best = d * sumqx_p; is_shifted = false;
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}
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if (sumq2_m > 0 && sumqx_m*sumqx_m > best*sumq2_m) {
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d = sumqx_m/sumq2_m; best = d * sumqx_m; is_shifted = false;
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}
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id = (itry + shifted_values[0])/max;
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sumqx_p = sumq2_p = 0;
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sumqx_m = sumq2_m = 0;
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for (int j = 0; j < 16; ++j) {
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float w = weight[j];
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float al = id*xb[j];
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int l = best_index_iq3nl(shifted_values, al);
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float q = shifted_values[l];
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sumqx_p += w*q*xb[j];
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sumq2_p += w*q*q;
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l = best_index_iq3nl(shifted_values, -al);
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q = shifted_values[l];
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sumqx_m += w*q*xb[j];
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sumq2_m += w*q*q;
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}
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if (sumq2_p > 0 && sumqx_p*sumqx_p > best*sumq2_p) {
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d = sumqx_p/sumq2_p; best = d * sumqx_p; is_shifted = true;
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}
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if (sumq2_m > 0 && sumqx_m*sumqx_m > best*sumq2_m) {
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d = sumqx_m/sumq2_m; best = d * sumqx_m; is_shifted = true;
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}
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}
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if (d) {
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const int8_t * block_values = is_shifted ? shifted_values : iq3nl_values;
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float sumqx = 0, sumq2 = 0;
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id = 1/d;
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for (int j = 0; j < 16; ++j) {
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float w = weight[j];
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float al = id*xb[j];
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int l = best_index_iq3nl(block_values, al);
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float q = block_values[l];
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sumqx += w*q*xb[j];
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sumq2 += w*q*q;
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}
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if (sumq2 > 0) d = sumqx/sumq2;
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}
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scales[ib] = d;
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if (is_shifted) extra |= (1 << ib);
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float abs_scale = fabsf(scales[ib]);
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max_abs_scale = MAX(max_abs_scale, abs_scale);
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}
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if (!max_abs_scale) continue;
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float d = max_abs_scale/31;
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y[ibl].d = GGML_FP32_TO_FP16(d);
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y[ibl].extra = extra;
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float id = 1/d;
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float sumqx = 0, sumq2 = 0;
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for (int ib = 0; ib < QK_K/16; ++ib) {
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int ls = nearest_int(0.5f*(id*fabsf(scales[ib])-1));
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ls = MAX(0, MIN(15, ls));
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y[ibl].scales_l[ib/2] |= (ls << 4*(ib%2));
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if (scales[ib] < 0) y[ibl].scales_h |= (1 << ib);
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ls = (2*ls + 1) * (scales[ib] < 0 ? -1 : 1);
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float dl = d * ls;
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if (dl) {
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const int8_t * block_values = y[ibl].extra & (1 << ib) ? shifted_values : iq3nl_values;
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const float * xb = xbl + 16*ib;
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if (quant_weights) {
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const float * qw = quant_weights + ibl*QK_K + ib*16;
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for (int j = 0; j < 16; ++j) weight[j] = qw[j] * sqrtf(sigma2 + xb[j]*xb[j]);
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} else {
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for (int j = 0; j < 16; ++j) weight[j] = 0.25f*sigma2 + xb[j]*xb[j];
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}
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float idl = 1/dl;
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int ib32 = ib/2;
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int offset = 16*(ib%2);
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uint8_t * qs = y[ibl].qs + 32*(ib32/4) + offset;
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uint8_t * qh = y[ibl].qh + 32*(ib32/8) + offset;
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for (int j = 0; j < 16; ++j) {
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const float al = idl*xb[j];
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int ibest = best_index_iq3nl(block_values, al);
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qs[j] |= ((ibest & 3) << 2*(ib32%4));
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qh[j] |= ((ibest >> 2) << (ib32%8));
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float w = weight[j];
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float q = block_values[ibest]*ls;
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sumqx += w*q*xb[j];
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sumq2 += w*q*q;
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}
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}
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}
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if (sumq2 > 0) y[ibl].d = GGML_FP32_TO_FP16(sumqx/sumq2);
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}
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}
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}
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void quantize_row_iq3_k_ref(const float * x, block_iq3_k * y, int64_t k) {
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assert(k % QK_K == 0);
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quantize_iq3_k(x, (void *)y, 1, k, nullptr);
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}
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void quantize_row_iq3_k(const float * x, void * vy, int64_t k) {
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assert(k % QK_K == 0);
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block_iq3_k * y = (block_iq3_k *)vy;
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quantize_row_iq3_k_ref(x, y, k);
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}
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size_t quantize_iq3_k(const float * src, void * dst, int64_t nrows, int64_t n_per_row, const float * imatrix) {
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GGML_ASSERT(n_per_row%QK_K == 0);
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int nblock = n_per_row/QK_K;
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char * qrow = (char *)dst;
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for (int64_t row = 0; row < nrows; ++row) {
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quantize_row_iq3_k_impl(src, (void *)qrow, n_per_row, imatrix);
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src += n_per_row;
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qrow += nblock*sizeof(block_iq3_k);
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}
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return nrows * nblock * sizeof(block_iq3_k);
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}
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void dequantize_row_iq3_k(const block_iq3_k * x, float * y, int64_t k) {
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assert(k % QK_K == 0);
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const int nb = k / QK_K;
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for (int i = 0; i < nb; i++) {
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const float d = GGML_FP16_TO_FP32(x[i].d);
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const uint8_t * qs = x[i].qs;
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const uint8_t * qh = x[i].qh;
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uint16_t sh = x[i].scales_h;
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uint16_t extra = x[i].extra;
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for (int ib32 = 0; ib32 < QK_K/32; ++ib32) {
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float dl1 = d * ((2*(x[i].scales_l[ib32] & 0xf) + 1) * ((sh & 1) ? -1 : 1));
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float dl2 = d * ((2*(x[i].scales_l[ib32] >> 4) + 1) * ((sh & 2) ? -1 : 1));
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sh >>= 2;
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const int8_t * values1 = extra & 1 ? iq3nl_values + 8 : iq3nl_values;
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const int8_t * values2 = extra & 2 ? iq3nl_values + 8 : iq3nl_values;
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extra >>= 2;
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int shift_l = 2*(ib32%4);
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int shift_h = ib32%8;
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for (int j = 0; j < 16; ++j) {
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y[j+ 0] = dl1 * values1[((qs[j+ 0] >> shift_l) & 3) | (((qh[j+ 0] >> shift_h) & 1) << 2)];
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y[j+16] = dl2 * values2[((qs[j+16] >> shift_l) & 3) | (((qh[j+16] >> shift_h) & 1) << 2)];
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}
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y += 32;
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if (shift_l == 6) qs += 32;
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}
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}
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}
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void vec_dot_iq3_k_q8_k(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc) {
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assert(n % QK_K == 0);
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assert(nrc == 1);
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GGML_UNUSED(nrc);
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GGML_UNUSED(bx);
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GGML_UNUSED(by);
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GGML_UNUSED(bs);
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if (iqk_mul_mat(1, 1, n, GGML_TYPE_IQ3_K, vx, 0, GGML_TYPE_Q8_K, vy, 0, s, 0, 0, 1)) {
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return;
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}
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const int nb = n / QK_K;
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const block_iq2_k * x = (const block_iq2_k *)vx;
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const block_q8_K * y = (const block_q8_K *)vy;
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}
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//
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// ============================================== iq4_K
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//
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