diff options
| -rw-r--r-- | examples/quantize/quantize.cpp | 1 | ||||
| -rw-r--r-- | ggml/include/ggml.h | 2 | ||||
| -rw-r--r-- | ggml/src/ggml-common.h | 9 | ||||
| -rw-r--r-- | ggml/src/ggml-quants.c | 1 | ||||
| -rw-r--r-- | ggml/src/ggml.c | 22 | ||||
| -rw-r--r-- | ggml/src/iqk/iqk_mul_mat.cpp | 280 | ||||
| -rw-r--r-- | ggml/src/iqk/iqk_quantize.cpp | 119 | ||||
| -rw-r--r-- | ggml/src/iqk/iqk_quantize.h | 6 | ||||
| -rw-r--r-- | include/llama.h | 1 | ||||
| -rw-r--r-- | src/llama.cpp | 14 |
10 files changed, 454 insertions, 1 deletions
diff --git a/examples/quantize/quantize.cpp b/examples/quantize/quantize.cpp index 00cd3cf0..db0fc0d4 100644 --- a/examples/quantize/quantize.cpp +++ b/examples/quantize/quantize.cpp @@ -62,6 +62,7 @@ static const std::vector<struct quant_option> QUANT_OPTIONS = { { "Q4_K_S", LLAMA_FTYPE_MOSTLY_Q4_K_S, " 3.59G, +0.0992 ppl @ LLaMA-v1-7B", }, { "Q4_K_M", LLAMA_FTYPE_MOSTLY_Q4_K_M, " 3.80G, +0.0532 ppl @ LLaMA-v1-7B", }, { "Q5_K", LLAMA_FTYPE_MOSTLY_Q5_K_M, "alias for Q5_K_M", }, + { "Q5_K_R4", LLAMA_FTYPE_MOSTLY_Q5_K_R4, "Q5_K_S repacked", }, { "Q5_K_S", LLAMA_FTYPE_MOSTLY_Q5_K_S, " 4.33G, +0.0400 ppl @ LLaMA-v1-7B", }, { "Q5_K_M", LLAMA_FTYPE_MOSTLY_Q5_K_M, " 4.45G, +0.0122 ppl @ LLaMA-v1-7B", }, { "Q6_K", LLAMA_FTYPE_MOSTLY_Q6_K, " 5.15G, +0.0008 ppl @ LLaMA-v1-7B", }, diff --git a/ggml/include/ggml.h b/ggml/include/ggml.h index 6486407f..7f766497 100644 --- a/ggml/include/ggml.h +++ b/ggml/include/ggml.h @@ -413,6 +413,7 @@ extern "C" { GGML_TYPE_Q5_0_R4 = 206, GGML_TYPE_Q8_0_R4 = 208, GGML_TYPE_Q4_K_R4 = 212, + GGML_TYPE_Q5_K_R4 = 213, GGML_TYPE_Q6_K_R4 = 214, GGML_TYPE_IQ4_NL_R4 = 220, GGML_TYPE_IQ4_XS_R4 = 223, @@ -481,6 +482,7 @@ extern "C" { GGML_FTYPE_MOSTLY_Q8_0_R4 = 207, // except 1d tensors GGML_FTYPE_MOSTLY_Q5_0_R4 = 208, // except 1d tensors GGML_FTYPE_MOSTLY_Q4_K_R4 = 212, // except 1d tensors + GGML_FTYPE_MOSTLY_Q5_K_R4 = 215, // except 1d tensors GGML_FTYPE_MOSTLY_Q6_K_R4 = 214, // except 1d tensors GGML_FTYPE_MOSTLY_IQ4_NL_R4 = 219, // except 1d tensors GGML_FTYPE_MOSTLY_IQ4_XS_R4 = 222, // except 1d tensors diff --git a/ggml/src/ggml-common.h b/ggml/src/ggml-common.h index 8ace3d6f..2d73d3f8 100644 --- a/ggml/src/ggml-common.h +++ b/ggml/src/ggml-common.h @@ -319,6 +319,15 @@ typedef struct { } block_q5_K; static_assert(sizeof(block_q5_K) == 2*sizeof(ggml_half) + K_SCALE_SIZE + QK_K/2 + QK_K/8, "wrong q5_K block size/padding"); +typedef struct { + ggml_half d[8]; + uint8_t scales_h[QK_K/16];// scales and mins, quantized with 6 bits + uint8_t scales_l[QK_K/8]; // scales and mins, quantized with 6 bits + uint8_t qh[QK_K/2]; // quants, high bit + uint8_t qs[QK_K*2]; // quants, low 4 bits +} block_q5_k_r4; +static_assert(sizeof(block_q5_k_r4) == 8*sizeof(ggml_half) + QK_K/16 + QK_K/8 + QK_K/2 + QK_K*2, "wrong q5_k_r4 block size/padding"); + // 6-bit quantization // weight is represented as x = a * q // 16 blocks of 16 elements each diff --git a/ggml/src/ggml-quants.c b/ggml/src/ggml-quants.c index 67f54da7..f4f375c9 100644 --- a/ggml/src/ggml-quants.c +++ b/ggml/src/ggml-quants.c @@ -15203,6 +15203,7 @@ bool ggml_validate_row_data(enum ggml_type type, const void * data, size_t nbyte case GGML_TYPE_Q6_0_R4: break; case GGML_TYPE_Q8_0_R4: break; case GGML_TYPE_Q4_K_R4: break; + case GGML_TYPE_Q5_K_R4: break; case GGML_TYPE_Q6_K_R4: break; case GGML_TYPE_Q4_0_4_4: case GGML_TYPE_Q4_0_4_8: diff --git a/ggml/src/ggml.c b/ggml/src/ggml.c index b92c2352..53c51ba6 100644 --- a/ggml/src/ggml.c +++ b/ggml/src/ggml.c @@ -914,6 +914,19 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = { .nrows = 1, .row_meta_size = 0, }, + [GGML_TYPE_Q5_K_R4] = { + .type_name = "q5_k_r4", + .blck_size = QK_K, + .type_size = sizeof(block_q5_K), + .is_quantized = true, + .to_float = (ggml_to_float_t) dequantize_row_q5_k_r4, + .from_float = quantize_row_q5_k_r4, + .from_float_ref = (ggml_from_float_t) quantize_row_q5_k_r4_ref, + .vec_dot = vec_dot_q5_k_r4_q8_k, + .vec_dot_type = GGML_TYPE_Q8_K32, + .nrows = 1, + .row_meta_size = 0, + }, [GGML_TYPE_Q6_K] = { .type_name = "q6_K", .blck_size = QK_K, @@ -4048,6 +4061,7 @@ enum ggml_type ggml_ftype_to_ggml_type(enum ggml_ftype ftype) { case GGML_FTYPE_MOSTLY_Q4_K: wtype = GGML_TYPE_Q4_K; break; case GGML_FTYPE_MOSTLY_Q4_K_R4: wtype = GGML_TYPE_Q4_K_R4; break; case GGML_FTYPE_MOSTLY_Q5_K: wtype = GGML_TYPE_Q5_K; break; + case GGML_FTYPE_MOSTLY_Q5_K_R4: wtype = GGML_TYPE_Q5_K_R4; break; case GGML_FTYPE_MOSTLY_Q6_K: wtype = GGML_TYPE_Q6_K; break; case GGML_FTYPE_MOSTLY_Q6_K_R4: wtype = GGML_TYPE_Q6_K_R4; break; case GGML_FTYPE_MOSTLY_IQ2_XXS: wtype = GGML_TYPE_IQ2_XXS; break; @@ -10580,6 +10594,7 @@ static void ggml_compute_forward_add( case GGML_TYPE_Q4_K: case GGML_TYPE_Q4_K_R4: case GGML_TYPE_Q5_K: + case GGML_TYPE_Q5_K_R4: case GGML_TYPE_Q6_K: case GGML_TYPE_Q6_K_R4: case GGML_TYPE_IQ2_XXS: @@ -11031,6 +11046,7 @@ static void ggml_compute_forward_add1( case GGML_TYPE_Q4_K: case GGML_TYPE_Q4_K_R4: case GGML_TYPE_Q5_K: + case GGML_TYPE_Q5_K_R4: case GGML_TYPE_Q6_K: case GGML_TYPE_Q6_K_R4: case GGML_TYPE_IQ2_XXS: @@ -11179,6 +11195,7 @@ static void ggml_compute_forward_acc( case GGML_TYPE_Q4_K: case GGML_TYPE_Q4_K_R4: case GGML_TYPE_Q5_K: + case GGML_TYPE_Q5_K_R4: case GGML_TYPE_Q6_K: case GGML_TYPE_Q6_K_R4: case GGML_TYPE_IQ2_XXS: @@ -14373,6 +14390,7 @@ static void ggml_compute_forward_out_prod( case GGML_TYPE_Q4_K: case GGML_TYPE_Q4_K_R4: case GGML_TYPE_Q5_K: + case GGML_TYPE_Q5_K_R4: case GGML_TYPE_Q6_K: case GGML_TYPE_Q6_K_R4: case GGML_TYPE_IQ2_XXS: @@ -14761,6 +14779,7 @@ static void ggml_compute_forward_set( case GGML_TYPE_Q4_K: case GGML_TYPE_Q4_K_R4: case GGML_TYPE_Q5_K: + case GGML_TYPE_Q5_K_R4: case GGML_TYPE_Q6_K: case GGML_TYPE_Q6_K_R4: case GGML_TYPE_IQ2_XXS: @@ -15043,6 +15062,7 @@ static void ggml_compute_forward_get_rows( case GGML_TYPE_Q4_K: case GGML_TYPE_Q4_K_R4: case GGML_TYPE_Q5_K: + case GGML_TYPE_Q5_K_R4: case GGML_TYPE_Q6_K: case GGML_TYPE_Q6_K_R4: case GGML_TYPE_IQ2_XXS: @@ -15652,6 +15672,7 @@ static void ggml_compute_forward_clamp( case GGML_TYPE_Q4_K: case GGML_TYPE_Q4_K_R4: case GGML_TYPE_Q5_K: + case GGML_TYPE_Q5_K_R4: case GGML_TYPE_Q6_K: case GGML_TYPE_Q6_K_R4: case GGML_TYPE_IQ2_XXS: @@ -22489,6 +22510,7 @@ size_t ggml_quantize_chunk( case GGML_TYPE_Q4_K: result = quantize_q4_K(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break; case GGML_TYPE_Q4_K_R4: result = quantize_q4_k_r4(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break; case GGML_TYPE_Q5_K: result = quantize_q5_K(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break; + case GGML_TYPE_Q5_K_R4: result = quantize_q5_k_r4(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break; case GGML_TYPE_Q6_K: result = quantize_q6_K(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break; case GGML_TYPE_Q6_K_R4: result = quantize_q6_k_r4(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break; case GGML_TYPE_IQ2_XXS: result = quantize_iq2_xxs(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break; diff --git a/ggml/src/iqk/iqk_mul_mat.cpp b/ggml/src/iqk/iqk_mul_mat.cpp index 5cf9013d..a1600cbc 100644 --- a/ggml/src/iqk/iqk_mul_mat.cpp +++ b/ggml/src/iqk/iqk_mul_mat.cpp @@ -3256,6 +3256,190 @@ static void mul_mat_q4_k_r4_q8_k(int n, const void * vx, size_t bx, const DataIn #endif template <int nrc_y> +static void mul_mat_q5_k_r4_q8_k_avx2(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + GGML_ASSERT(nrc_x%4 == 0); + Q8<nrc_y, block_q8_K> q8(info); + auto mf = _mm256_set1_epi8(0xf); + auto m10 = _mm256_set1_epi8(0x10); + auto m30 = _mm256_set1_epi8(0x30); +#ifndef HAVE_FANCY_SIMD + auto m1 = _mm256_set1_epi16(1); +#endif + int nbl = n / QK_K; + union { __m256i vec; uint32_t val[8]; } hd; + __m256 acc[nrc_y] = {}; + __m256i qx[4]; + for (int ix = 0; ix < nrc_x; ix += 4) { + const block_q5_k_r4 * iq5 = (const block_q5_k_r4 *)((const char *)vx + (ix+0)*bx); + for (int ibl = 0; ibl < nbl; ++ibl) { // Block of 256 + auto dl = _mm256_cvtph_ps(_mm_loadu_si128((const __m128i *)iq5[ibl].d)); + auto d4 = _mm256_set_m128(_mm256_castps256_ps128(dl), _mm256_castps256_ps128(dl)); + auto m4 = _mm256_mul_ps(_mm256_set1_ps(-1.0f), _mm256_set_m128(_mm256_extractf128_ps(dl, 1), _mm256_extractf128_ps(dl, 1))); + if constexpr (nrc_y == 1) { + d4 = _mm256_mul_ps(d4, _mm256_set1_ps(q8.scale(0, ibl))); + } + auto lbits = _mm256_loadu_si256((const __m256i *)iq5[ibl].scales_l); + auto hbits128 = _mm_loadu_si128((const __m128i *)iq5[ibl].scales_h); + auto hbits = MM256_SET_M128I(hbits128, _mm_slli_epi16(hbits128, 4)); + hd.vec = _mm256_or_si256(_mm256_and_si256(lbits, mf), _mm256_and_si256(hbits, m30)); + auto mins = _mm256_or_si256(_mm256_and_si256(_mm256_srli_epi16(lbits, 4), mf), _mm256_and_si256(_mm256_srli_epi16(hbits, 2), m30)); + auto shuffle = _mm256_set1_epi64x(0x0000000400000000); + auto c1 = _mm256_mul_ps(m4, _mm256_cvtepi32_ps(_mm256_cvtepi8_epi32(_mm256_castsi256_si128(_mm256_permutevar8x32_epi32(mins, shuffle))))); + shuffle = _mm256_add_epi32(shuffle, _mm256_set1_epi32(1)); + auto c2 = _mm256_mul_ps(m4, _mm256_cvtepi32_ps(_mm256_cvtepi8_epi32(_mm256_castsi256_si128(_mm256_permutevar8x32_epi32(mins, shuffle))))); + shuffle = _mm256_add_epi32(shuffle, _mm256_set1_epi32(1)); + auto c3 = _mm256_mul_ps(m4, _mm256_cvtepi32_ps(_mm256_cvtepi8_epi32(_mm256_castsi256_si128(_mm256_permutevar8x32_epi32(mins, shuffle))))); + shuffle = _mm256_add_epi32(shuffle, _mm256_set1_epi32(1)); + auto c4 = _mm256_mul_ps(m4, _mm256_cvtepi32_ps(_mm256_cvtepi8_epi32(_mm256_castsi256_si128(_mm256_permutevar8x32_epi32(mins, shuffle))))); + for (int iy = 0; iy < nrc_y; ++iy) { + auto bs = _mm256_loadu_ps((const float *)q8.y[iy][ibl].bsums); + acc[iy] = _mm256_fmadd_ps(c1, _mm256_shuffle_ps(bs, bs, 0x00), acc[iy]); + acc[iy] = _mm256_fmadd_ps(c2, _mm256_shuffle_ps(bs, bs, 0x55), acc[iy]); + acc[iy] = _mm256_fmadd_ps(c3, _mm256_shuffle_ps(bs, bs, 0xaa), acc[iy]); + acc[iy] = _mm256_fmadd_ps(c4, _mm256_shuffle_ps(bs, bs, 0xff), acc[iy]); + } + for (int ib = 0; ib < QK_K/32; ++ib) { + auto scales_d = _mm256_mul_ps(d4, _mm256_cvtepi32_ps(_mm256_cvtepi8_epi32(_mm_set1_epi32(hd.val[ib])))); + auto lbits1 = _mm256_loadu_si256((const __m256i *)iq5[ibl].qs+2*ib+0); + auto lbits2 = _mm256_loadu_si256((const __m256i *)iq5[ibl].qs+2*ib+1); + auto hbits128 = _mm_loadu_si128((const __m128i*)iq5[ibl].qh + ib); + auto hbits = MM256_SET_M128I(hbits128, _mm_slli_epi16(hbits128, 4)); + qx[0] = _mm256_or_si256(_mm256_and_si256(lbits1, mf), _mm256_and_si256(m10, hbits)); + qx[1] = _mm256_or_si256(_mm256_and_si256(lbits2, mf), _mm256_and_si256(m10, _mm256_srli_epi16(hbits, 2))); + qx[2] = _mm256_or_si256(_mm256_and_si256(_mm256_srli_epi16(lbits1, 4), mf), _mm256_and_si256(m10, _mm256_srli_epi16(hbits, 1))); + qx[3] = _mm256_or_si256(_mm256_and_si256(_mm256_srli_epi16(lbits2, 4), mf), _mm256_and_si256(m10, _mm256_srli_epi16(hbits, 3))); + for (int iy = 0; iy < nrc_y; ++iy) { + auto y = _mm256_loadu_si256((const __m256i*)q8.y[iy][ibl].qs+ib); +#ifdef HAVE_FANCY_SIMD + auto sumi = _mm256_setzero_si256(); + sumi = _mm256_dpbusd_epi32(sumi, qx[0], _mm256_shuffle_epi32(y, 0x00)); + sumi = _mm256_dpbusd_epi32(sumi, qx[1], _mm256_shuffle_epi32(y, 0x55)); + sumi = _mm256_dpbusd_epi32(sumi, qx[2], _mm256_shuffle_epi32(y, 0xaa)); + sumi = _mm256_dpbusd_epi32(sumi, qx[3], _mm256_shuffle_epi32(y, 0xff)); +#else + auto sumi1 = _mm256_add_epi16(_mm256_maddubs_epi16(qx[0], _mm256_shuffle_epi32(y, 0x00)), + _mm256_maddubs_epi16(qx[1], _mm256_shuffle_epi32(y, 0x55))); + auto sumi2 = _mm256_add_epi16(_mm256_maddubs_epi16(qx[2], _mm256_shuffle_epi32(y, 0xaa)), + _mm256_maddubs_epi16(qx[3], _mm256_shuffle_epi32(y, 0xff))); + auto sumi = _mm256_madd_epi16(m1, _mm256_add_epi16(sumi1, sumi2)); +#endif + if constexpr (nrc_y == 1) { + acc[iy] = _mm256_fmadd_ps(scales_d, _mm256_cvtepi32_ps(sumi), acc[iy]); + } else { + float d8 = q8.scale(iy, ibl); + acc[iy] = _mm256_fmadd_ps(_mm256_mul_ps(scales_d, _mm256_set1_ps(d8)), _mm256_cvtepi32_ps(sumi), acc[iy]); + } + } + } + } + for (int iy = 0; iy < nrc_y; ++iy) { + auto sum = _mm_add_ps(_mm256_castps256_ps128(acc[iy]), _mm256_extractf128_ps(acc[iy], 1)); + acc[iy] = _mm256_setzero_ps(); + info.store(ix+0, iy, sum); + } + } +} + +#ifdef HAVE_FANCY_SIMD +template <int nrc_y> +static void mul_mat_q5_k_r4_q8_k(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + if constexpr (nrc_y == 1){ + mul_mat_q4_k_r4_q8_k_avx2<1>(n, vx, bx, info, nrc_x); + } else { + GGML_ASSERT(nrc_x%8 == 0); + Q8<nrc_y, block_q8_K> q8(info); + auto mf = _mm512_set1_epi8(0xf); + auto m10 = _mm512_set1_epi8(0x10); + int nbl = n / QK_K; + using helper_t = union { __m512i vec; uint32_t val[16]; }; + helper_t hd, hm; + __m512 acc[nrc_y] = {}; + __m512 d4s[nrc_y]; + __m512i qx[4]; + for (int ix = 0; ix < nrc_x; ix += 8) { + const block_q5_k_r4 * iq5l = (const block_q5_k_r4 *)((const char *)vx + (ix+0)*bx); + const block_q5_k_r4 * iq5h = (const block_q5_k_r4 *)((const char *)vx + (ix+4)*bx); + for (int ibl = 0; ibl < nbl; ++ibl) { // Block of 256 + auto d1 = _mm256_cvtph_ps(_mm_loadu_si128((const __m128i *)iq5l[ibl].d)); + auto d2 = _mm256_cvtph_ps(_mm_loadu_si128((const __m128i *)iq5h[ibl].d)); + auto dl = _mm256_castps256_ps128(d1); + auto ml = _mm256_extractf128_ps(d1, 1); + auto dh = _mm256_castps256_ps128(d2); + auto mh = _mm256_extractf128_ps(d2, 1); + auto d4 = _mm512_insertf32x8(_mm512_castps256_ps512(_mm256_set_m128(dl, dl)), _mm256_set_m128(dh, dh), 1); + for (int iy = 0; iy < nrc_y; ++iy) { + d4s[iy] = _mm512_mul_ps(d4, _mm512_set1_ps(q8.scale(iy, ibl))); + } + auto m4 = _mm512_insertf32x8(_mm512_castps256_ps512(_mm256_set_m128(ml, ml)), _mm256_set_m128(mh, mh), 1); + m4 = _mm512_mul_ps(m4, _mm512_set1_ps(-0.5f)); + auto slbits_l = _mm256_loadu_si256((const __m256i *)iq5l[ibl].scales_l); + auto shbits_l = _mm256_loadu_si256((const __m256i *)iq5h[ibl].scales_l); + auto slb = _mm512_inserti32x8(_mm512_castsi256_si512(slbits_l), shbits_l, 1); + auto sld = _mm512_and_si512(slb, mf); + auto slm = _mm512_and_si512(_mm512_srli_epi16(slb, 4), mf); + auto slbits_h = _mm_loadu_si128((const __m128i *)iq5l[ibl].scales_h); + auto shbits_h = _mm_loadu_si128((const __m128i *)iq5h[ibl].scales_h); + auto slbits_h2 = MM256_SET_M128I(_mm_srli_epi16(slbits_h, 4), slbits_h); + auto shbits_h2 = MM256_SET_M128I(_mm_srli_epi16(shbits_h, 4), shbits_h); + auto shb = _mm512_inserti32x8(_mm512_castsi256_si512(slbits_h2), shbits_h2, 1); + auto shd = _mm512_and_si512(_mm512_slli_epi16(shb, 4), _mm512_set1_epi8(0x30)); + auto shm = _mm512_and_si512(_mm512_slli_epi16(shb, 2), _mm512_set1_epi8(0x30)); + hd.vec = _mm512_or_si512(sld, shd); + hm.vec = _mm512_or_si512(slm, shm); + for (int ib = 0; ib < QK_K/32; ++ib) { + auto scales1 = _mm256_cvtepi8_epi32(_mm_set1_epi32(hd.val[ib+0])); + auto scales2 = _mm256_cvtepi8_epi32(_mm_set1_epi32(hd.val[ib+8])); + auto iscales = _mm512_inserti32x8(_mm512_castsi256_si512(scales1), scales2, 1); + auto scales = _mm512_cvtepi32_ps(iscales); + scales1 = _mm256_cvtepi8_epi32(_mm_set1_epi32(hm.val[ib+0])); + scales2 = _mm256_cvtepi8_epi32(_mm_set1_epi32(hm.val[ib+8])); + iscales = _mm512_inserti32x8(_mm512_castsi256_si512(scales1), scales2, 1); + auto scales_m = _mm512_mul_ps(m4, _mm512_cvtepi32_ps(iscales)); + auto lbits1 = _mm512_inserti32x8(_mm512_castsi256_si512(_mm256_loadu_si256((const __m256i *)iq5l[ibl].qs+2*ib+0)), + _mm256_loadu_si256((const __m256i *)iq5h[ibl].qs+2*ib+0), 1); + auto lbits2 = _mm512_inserti32x8(_mm512_castsi256_si512(_mm256_loadu_si256((const __m256i *)iq5l[ibl].qs+2*ib+1)), + _mm256_loadu_si256((const __m256i *)iq5h[ibl].qs+2*ib+1), 1); + auto hbits1 = _mm_loadu_si128((const __m128i*)iq5l[ibl].qh+ib); + auto hbits2 = _mm_loadu_si128((const __m128i*)iq5h[ibl].qh+ib); + auto hbl = MM256_SET_M128I(hbits1, _mm_slli_epi16(hbits1, 4)); + auto hbh = MM256_SET_M128I(hbits2, _mm_slli_epi16(hbits2, 4)); + auto hbits = _mm512_inserti32x8(_mm512_castsi256_si512(hbl), hbh, 1); + qx[0] = _mm512_or_si512(_mm512_and_si512(lbits1, mf), _mm512_and_si512(m10, hbits)); + qx[1] = _mm512_or_si512(_mm512_and_si512(lbits2, mf), _mm512_and_si512(m10, _mm512_srli_epi16(hbits, 2))); + qx[2] = _mm512_or_si512(_mm512_and_si512(_mm512_srli_epi16(lbits1, 4), mf), _mm512_and_si512(m10, _mm512_srli_epi16(hbits, 1))); + qx[3] = _mm512_or_si512(_mm512_and_si512(_mm512_srli_epi16(lbits2, 4), mf), _mm512_and_si512(m10, _mm512_srli_epi16(hbits, 3))); + for (int iy = 0; iy < nrc_y; ++iy) { + auto y8 = _mm256_loadu_si256((const __m256i*)q8.y[iy][ibl].qs+ib); + auto y = _mm512_inserti32x8(_mm512_castsi256_si512(y8), y8, 1); + auto sumi = _mm512_setzero_si512(); + sumi = _mm512_dpbusd_epi32(sumi, qx[0], _mm512_shuffle_epi32(y, _MM_PERM_ENUM(0x00))); + sumi = _mm512_dpbusd_epi32(sumi, qx[1], _mm512_shuffle_epi32(y, _MM_PERM_ENUM(0x55))); + sumi = _mm512_dpbusd_epi32(sumi, qx[2], _mm512_shuffle_epi32(y, _MM_PERM_ENUM(0xaa))); + sumi = _mm512_dpbusd_epi32(sumi, qx[3], _mm512_shuffle_epi32(y, _MM_PERM_ENUM(0xff))); + acc[iy] = _mm512_fmadd_ps(_mm512_mul_ps(scales, d4s[iy]), _mm512_cvtepi32_ps(sumi), acc[iy]); + float m8 = ((const float *)q8.y[iy][ibl].bsums)[ib]; + acc[iy] = _mm512_fmadd_ps(scales_m, _mm512_set1_ps(m8), acc[iy]); + } + } + } + for (int iy = 0; iy < nrc_y; ++iy) { + auto sum1 = _mm_add_ps(_mm512_extractf32x4_ps(acc[iy], 0), _mm512_extractf32x4_ps(acc[iy], 1)); + auto sum2 = _mm_add_ps(_mm512_extractf32x4_ps(acc[iy], 2), _mm512_extractf32x4_ps(acc[iy], 3)); + info.store(ix+0, iy, sum1); + info.store(ix+4, iy, sum2); + acc[iy] = _mm512_setzero_ps(); + } + } + } +} +#else +template <int nrc_y> +static void mul_mat_q5_k_r4_q8_k(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + mul_mat_q5_k_r4_q8_k_avx2<nrc_y>(n, vx, bx, info, nrc_x); +} +#endif + +template <int nrc_y> static void mul_mat_q6_k_r4_q8_k(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { GGML_ASSERT(nrc_x%4 == 0); Q8<nrc_y, block_q8_K> q8(info); @@ -5374,6 +5558,18 @@ bool MulMat::prepare(int typeA, int typeB, int ne00, MulMat& mm, int Ny) { mm.funcs[7] = mul_mat_q4_k_r4_q8_k<8>; expected_typeB = GGML_TYPE_Q8_K32; break; + case GGML_TYPE_Q5_K_R4: + assert (ne00 % QK_K == 0); + mm.funcs[0] = mul_mat_q5_k_r4_q8_k<1>; + mm.funcs[1] = mul_mat_q5_k_r4_q8_k<2>; + mm.funcs[2] = mul_mat_q5_k_r4_q8_k<3>; + mm.funcs[3] = mul_mat_q5_k_r4_q8_k<4>; + mm.funcs[4] = mul_mat_q5_k_r4_q8_k<5>; + mm.funcs[5] = mul_mat_q5_k_r4_q8_k<6>; + mm.funcs[6] = mul_mat_q5_k_r4_q8_k<7>; + mm.funcs[7] = mul_mat_q5_k_r4_q8_k<8>; + expected_typeB = GGML_TYPE_Q8_K32; + break; case GGML_TYPE_Q6_K_R4: assert (ne00 % QK_K == 0); mm.funcs[0] = mul_mat_q6_k_r4_q8_k<1>; @@ -8147,6 +8343,86 @@ void mul_mat_q4_k_r4_q8_k(int n, const void * vx, size_t bx, const DataInfo& inf } template <int nrc_y> +void mul_mat_q5_k_r4_q8_k(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + GGML_ASSERT(nrc_x%4 == 0); + Q8<nrc_y, block_q8_K> q8(info); + auto mf = vdupq_n_u8(0xf); + auto m30 = vdupq_n_u8(0x30); + auto m10 = vdupq_n_u8(0x10); + int nbl = n / QK_K; + int8x16_t qx[8]; + int8x16x4_t iscales; + float32x4x4_t scales; + float32x4_t acc[nrc_y] = {}; + for (int ix = 0; ix < nrc_x; ix += 4) { + const block_q5_k_r4 * iq5 = (const block_q5_k_r4 *)((const char *)vx + ix*bx); + for (int ibl = 0; ibl < nbl; ++ibl) { + auto d4 = vcvt_f32_f16(vld1_f16((const float16_t *)iq5[ibl].d)); + auto m4 = vcvt_f32_f16(vld1_f16((const float16_t *)iq5[ibl].d+4)); + m4 = vmulq_f32(m4, vdupq_n_f32(-1.f)); + if constexpr (nrc_y == 1) { + d4 = vmulq_f32(d4, vdupq_n_f32(q8.scale(0, ibl))); + } + auto sl = vld1q_u8_x2(iq5[ibl].scales_l); + auto sh = vld1q_u8(iq5[ibl].scales_h); + iscales.val[0] = vorrq_u8(vandq_u8(sl.val[0], mf), vandq_u8(vshlq_n_u8(sh, 4), m30)); + iscales.val[1] = vorrq_u8(vandq_u8(sl.val[1], mf), vandq_u8(sh, m30)); + iscales.val[2] = vorrq_u8(vshrq_n_u8(sl.val[0], 4), vandq_u8(vshlq_n_u8(sh, 2), m30)); + iscales.val[3] = vorrq_u8(vshrq_n_u8(sl.val[1], 4), vandq_u8(vshrq_n_u8(sh, 2), m30)); + for (int is = 0; is < 2; ++is) { + auto iscales16_1 = vmovl_s8(vget_low_s8(iscales.val[is+2])); + auto iscales16_2 = vmovl_s8(vget_high_s8(iscales.val[is+2])); + scales.val[0] = vmulq_f32(m4, vcvtq_f32_s32(vmovl_s16(vget_low_s16(iscales16_1)))); + scales.val[1] = vmulq_f32(m4, vcvtq_f32_s32(vmovl_s16(vget_high_s16(iscales16_1)))); + scales.val[2] = vmulq_f32(m4, vcvtq_f32_s32(vmovl_s16(vget_low_s16(iscales16_2)))); + scales.val[3] = vmulq_f32(m4, vcvtq_f32_s32(vmovl_s16(vget_high_s16(iscales16_2)))); + for (int iy = 0; iy < nrc_y; ++iy) { + auto m8 = vld1q_f32((const float *)q8.y[iy][ibl].bsums + 4*is); + acc[iy] = vmlaq_laneq_f32(acc[iy], scales.val[0], m8, 0); + acc[iy] = vmlaq_laneq_f32(acc[iy], scales.val[1], m8, 1); + acc[iy] = vmlaq_laneq_f32(acc[iy], scales.val[2], m8, 2); + acc[iy] = vmlaq_laneq_f32(acc[iy], scales.val[3], m8, 3); + } + iscales16_1 = vmovl_s8(vget_low_s8(iscales.val[is])); + iscales16_2 = vmovl_s8(vget_high_s8(iscales.val[is])); + scales.val[0] = vmulq_f32(d4, vcvtq_f32_s32(vmovl_s16(vget_low_s16(iscales16_1)))); + scales.val[1] = vmulq_f32(d4, vcvtq_f32_s32(vmovl_s16(vget_high_s16(iscales16_1)))); + scales.val[2] = vmulq_f32(d4, vcvtq_f32_s32(vmovl_s16(vget_low_s16(iscales16_2)))); + scales.val[3] = vmulq_f32(d4, vcvtq_f32_s32(vmovl_s16(vget_high_s16(iscales16_2)))); + for (int ib = 0; ib < 4; ++ib) { + auto lbits = vld1q_u8_x4(iq5[ibl].qs + 256*is + 64*ib); + auto hbits2 = vld1q_u8(iq5[ibl].qh + 64*is + 16*ib); + auto hbits1 = vshlq_n_u8(hbits2, 4); + prepare_q4_k_quants(mf, lbits, qx); + qx[0] = vorrq_u8(qx[0], vandq_u8(m10, hbits1)); + qx[1] = vorrq_u8(qx[1], vandq_u8(m10, hbits2)); + qx[2] = vorrq_u8(qx[2], vandq_u8(m10, vshrq_n_u8(hbits1, 2))); + qx[3] = vorrq_u8(qx[3], vandq_u8(m10, vshrq_n_u8(hbits2, 2))); + qx[4] = vorrq_u8(qx[4], vandq_u8(m10, vshrq_n_u8(hbits1, 1))); + qx[5] = vorrq_u8(qx[5], vandq_u8(m10, vshrq_n_u8(hbits2, 1))); + qx[6] = vorrq_u8(qx[6], vandq_u8(m10, vshrq_n_u8(hbits1, 3))); + qx[7] = vorrq_u8(qx[7], vandq_u8(m10, vshrq_n_u8(hbits2, 3))); + for (int iy = 0; iy < nrc_y; ++iy) { + auto y = vld1q_s8_x2(q8.y[iy][ibl].qs+128*is+32*ib); + auto sumi = interleaved_dotq(qx, y); + if constexpr (nrc_y == 1) { + acc[iy] = vfmaq_f32(acc[iy], scales.val[ib], vcvtq_f32_s32(sumi)); + } else { + auto d4d8 = vmulq_f32(scales.val[ib], vdupq_n_f32(q8.scale(iy, ibl))); + acc[iy] = vfmaq_f32(acc[iy], d4d8, vcvtq_f32_s32(sumi)); + } + } + } + } + } + for (int iy = 0; iy < nrc_y; ++iy) { + info.store(ix, iy, acc[iy]); + acc[iy] = vdupq_n_f32(0.f); + } + } +} + +template <int nrc_y> void mul_mat_q6_k_r4_q8_k(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { GGML_ASSERT(nrc_x%4 == 0); Q8<nrc_y, block_q8_K> q8(info); @@ -8602,6 +8878,10 @@ bool MulMat::prepare(int typeA, int typeB, int ne00, MulMat& m, int /*Ny*/) { SET_MUL_MAT_FUNCTIONS(m, mul_mat_q4_k_r4_q8_k); expected_Btype = GGML_TYPE_Q8_K32; break; + case GGML_TYPE_Q5_K_R4: + SET_MUL_MAT_FUNCTIONS(m, mul_mat_q5_k_r4_q8_k); + expected_Btype = GGML_TYPE_Q8_K32; + break; case GGML_TYPE_Q6_K_R4: SET_MUL_MAT_FUNCTIONS(m, mul_mat_q6_k_r4_q8_k); expected_Btype = GGML_TYPE_Q8_K; diff --git a/ggml/src/iqk/iqk_quantize.cpp b/ggml/src/iqk/iqk_quantize.cpp index 71578bf8..8ca18060 100644 --- a/ggml/src/iqk/iqk_quantize.cpp +++ b/ggml/src/iqk/iqk_quantize.cpp @@ -4182,3 +4182,122 @@ void vec_dot_q6_k_r4_q8_k(int n, float * s, size_t bs, const void * vx, size_t b } +// +// ========================================= 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) { + 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); + 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); +} + diff --git a/ggml/src/iqk/iqk_quantize.h b/ggml/src/iqk/iqk_quantize.h index 8819620d..77c34fea 100644 --- a/ggml/src/iqk/iqk_quantize.h +++ b/ggml/src/iqk/iqk_quantize.h @@ -115,6 +115,12 @@ size_t quantize_q4_k_r4(const float * GGML_RESTRICT src, void * GGML_RESTRICT ds void dequantize_row_q4_k_r4(const block_q4_k_r4 * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k); void vec_dot_q4_k_r4_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); +void quantize_row_q5_k_r4_ref(const float * GGML_RESTRICT x, block_q5_k_r4 * GGML_RESTRICT y, int64_t k); +void quantize_row_q5_k_r4(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k); +size_t quantize_q5_k_r4(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix); +void dequantize_row_q5_k_r4(const block_q5_k_r4 * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k); +void vec_dot_q5_k_r4_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); + void quantize_row_q6_k_r4_ref(const float * GGML_RESTRICT x, block_q6_k_r4 * GGML_RESTRICT y, int64_t k); void quantize_row_q6_k_r4(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k); size_t quantize_q6_k_r4(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix); diff --git a/include/llama.h b/include/llama.h index 92234d6c..7290f18f 100644 --- a/include/llama.h +++ b/include/llama.h @@ -184,6 +184,7 @@ extern "C" { LLAMA_FTYPE_MOSTLY_Q8_0_R4 = 207, // except 1d tensors LLAMA_FTYPE_MOSTLY_Q5_0_R4 = 208, // except 1d tensors LLAMA_FTYPE_MOSTLY_Q4_K_R4 = 214, // except 1d tensors + LLAMA_FTYPE_MOSTLY_Q5_K_R4 = 216, // except 1d tensors LLAMA_FTYPE_MOSTLY_Q6_K_R4 = 218, // except 1d tensors LLAMA_FTYPE_MOSTLY_IQ4_NL_R4 = 225, // except 1d tensors LLAMA_FTYPE_MOSTLY_IQ4_XS_R4 = 230, // except 1d tensors diff --git a/src/llama.cpp b/src/llama.cpp index 3b617b06..dc6d307d 100644 --- a/src/llama.cpp +++ b/src/llama.cpp @@ -3839,6 +3839,7 @@ struct llama_model_loader { case GGML_TYPE_Q4_K: ftype = LLAMA_FTYPE_MOSTLY_Q4_K_M; break; case GGML_TYPE_Q4_K_R4: ftype = LLAMA_FTYPE_MOSTLY_Q4_K_R4; break; case GGML_TYPE_Q5_K: ftype = LLAMA_FTYPE_MOSTLY_Q5_K_M; break; + case GGML_TYPE_Q5_K_R4: ftype = LLAMA_FTYPE_MOSTLY_Q5_K_R4; break; case GGML_TYPE_Q6_K: ftype = LLAMA_FTYPE_MOSTLY_Q6_K; break; case GGML_TYPE_Q6_K_R4: ftype = LLAMA_FTYPE_MOSTLY_Q6_K_R4; break; case GGML_TYPE_IQ2_XXS: ftype = LLAMA_FTYPE_MOSTLY_IQ2_XXS; break; @@ -4551,6 +4552,7 @@ static std::string llama_model_ftype_name(llama_ftype ftype) { case LLAMA_FTYPE_MOSTLY_Q4_K_R4: return "Q4_K_R4"; case LLAMA_FTYPE_MOSTLY_Q4_K_M: return "Q4_K - Medium"; case LLAMA_FTYPE_MOSTLY_Q5_K_S: return "Q5_K - Small"; + case LLAMA_FTYPE_MOSTLY_Q5_K_R4: return "Q5_K_R4"; case LLAMA_FTYPE_MOSTLY_Q5_K_M: return "Q5_K - Medium"; case LLAMA_FTYPE_MOSTLY_Q6_K: return "Q6_K"; case LLAMA_FTYPE_MOSTLY_Q6_K_R4: return "Q6_K_R4"; @@ -15793,6 +15795,9 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n else if (new_type == GGML_TYPE_Q4_K_R4) { new_type = GGML_TYPE_Q4_K; } + else if (new_type == GGML_TYPE_Q5_K_R4) { + new_type = GGML_TYPE_Q5_K; + } else if (new_type == GGML_TYPE_Q6_K_R4) { new_type = GGML_TYPE_Q6_K; } @@ -16067,7 +16072,8 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n new_type == GGML_TYPE_IQ1_M || new_type == GGML_TYPE_IQ4_K || new_type == GGML_TYPE_IQ2_K || new_type == GGML_TYPE_IQ5_K || new_type == GGML_TYPE_IQ3_K || new_type == GGML_TYPE_Q4_K_R4 || new_type == GGML_TYPE_IQ6_K || new_type == GGML_TYPE_IQ4_KS || new_type == GGML_TYPE_IQ4_XS_R4 || - new_type == GGML_TYPE_IQ2_KS || new_type == GGML_TYPE_IQ4_KSS || new_type == GGML_TYPE_Q6_K_R4) { + new_type == GGML_TYPE_IQ2_KS || new_type == GGML_TYPE_IQ4_KSS || new_type == GGML_TYPE_Q6_K_R4 || + new_type == GGML_TYPE_Q5_K_R4) { int nx = tensor->ne[0]; int ny = tensor->ne[1]; if (nx % QK_K != 0) { @@ -16105,6 +16111,7 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n case GGML_TYPE_Q4_K_R4: case GGML_TYPE_Q4_K: new_type = GGML_TYPE_Q5_0; break; case GGML_TYPE_IQ5_K: + case GGML_TYPE_Q5_K_R4: case GGML_TYPE_Q5_K: new_type = GGML_TYPE_Q6_0; break; case GGML_TYPE_IQ6_K: case GGML_TYPE_Q6_K_R4: @@ -16199,6 +16206,7 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s case LLAMA_FTYPE_MOSTLY_Q4_K_R4: default_type = GGML_TYPE_Q4_K_R4; break; case LLAMA_FTYPE_MOSTLY_Q5_K_S: case LLAMA_FTYPE_MOSTLY_Q5_K_M: default_type = GGML_TYPE_Q5_K; break; + case LLAMA_FTYPE_MOSTLY_Q5_K_R4: default_type = GGML_TYPE_Q5_K_R4; break; case LLAMA_FTYPE_MOSTLY_Q6_K: default_type = GGML_TYPE_Q6_K; break; case LLAMA_FTYPE_MOSTLY_Q6_K_R4: default_type = GGML_TYPE_Q6_K_R4; break; case LLAMA_FTYPE_MOSTLY_IQ2_XXS: default_type = GGML_TYPE_IQ2_XXS; break; @@ -16604,6 +16612,10 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s if (tensor->ne[1] % 4 != 0) new_type = GGML_TYPE_Q4_K; else chunk_size_multiplier = 4; } + else if (new_type == GGML_TYPE_Q5_K_R4) { + if (tensor->ne[1] % 4 != 0) new_type = GGML_TYPE_Q5_K; + else chunk_size_multiplier = 4; + } else if (new_type == GGML_TYPE_Q6_K_R4) { if (tensor->ne[1] % 4 != 0) new_type = GGML_TYPE_Q6_K; else chunk_size_multiplier = 4; |