// // 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 #include #include #include #include #include #include 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; } 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; } static constexpr uint8_t 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; 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) < 1e-6f ? 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) < 1e-6f ? 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; 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]) < 1e-6f ? 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); } } } } size_t quantize_iq1_bn(const float * src, void * dst, int64_t nrows, int64_t n_per_row, const float * imatrix) { IQ1BNQuantizer iq1bn; int nblock = n_per_row/QK_IQ1BN; block_iq1_bn * y = (block_iq1_bn *)dst; for (int row = 0; row < nrows; ++row) { iq1bn.quantize_one_row_1bn(src + row*n_per_row, y, n_per_row, imatrix); y += nblock; } return sizeof(block_iq1_bn)*nblock*nrows; } 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; int nblock = n_per_row/QK_IQ1BN; block_iq2_bn * y = (block_iq2_bn *)dst; for (int row = 0; row < nrows; ++row) { iq1bn.quantize_one_row_2bn(src + row*n_per_row, y, n_per_row, imatrix); y += nblock; } return sizeof(block_iq2_bn)*nblock*nrows; } 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 ggml_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 (iqk_mul_mat(1, 1, n, GGML_TYPE_IQ2_BN, vx, 0, GGML_TYPE_Q8_K64, vy, 0, s, 0, 0, 1)) { return; } 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) { float * dptr = (float *)y; auto qs = (int8_t *)(dptr + 4); #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; 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); q.val[i] = vreinterpretq_s8_s32(vcvtnq_s32_f32(val)); } auto qi = vqtbl4q_s8(q, shuffle); vst1q_s8(qs, qi); qs += 16; } #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]; 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); _mm_storeu_si128((__m128i *)qs, qi); qs += 16; } #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; } 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]); } } #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); }