diff --git a/examples/quantize/quantize.cpp b/examples/quantize/quantize.cpp index 1ad112f7c..947b40202 100644 --- a/examples/quantize/quantize.cpp +++ b/examples/quantize/quantize.cpp @@ -12,6 +12,7 @@ static const std::map LLAMA_FTYPE_MAP = { {"q5_0", LLAMA_FTYPE_MOSTLY_Q5_0}, {"q5_1", LLAMA_FTYPE_MOSTLY_Q5_1}, {"q8_0", LLAMA_FTYPE_MOSTLY_Q8_0}, + {"q2_K", LLAMA_FTYPE_MOSTLY_Q2_K}, {"q3_K", LLAMA_FTYPE_MOSTLY_Q3_K_M}, {"q3_K_S", LLAMA_FTYPE_MOSTLY_Q3_K_S}, {"q3_K_M", LLAMA_FTYPE_MOSTLY_Q3_K_M}, diff --git a/ggml-cuda.cu b/ggml-cuda.cu index 6d9673b5c..71e99ad85 100644 --- a/ggml-cuda.cu +++ b/ggml-cuda.cu @@ -89,6 +89,14 @@ static_assert(sizeof(block_q8_0) == sizeof(ggml_fp16_t) + QK8_0, "wrong q8_0 blo #define QK_K 256 +typedef struct { + uint8_t scales[QK_K/16]; // scales and mins, quantized with 4 bits + uint8_t qs[QK_K/4]; // quants + half d; // super-block scale for quantized scales + half dmin; // super-block scale for quantized mins +} block_q2_K; +static_assert(sizeof(block_q2_K) == 2*sizeof(ggml_fp16_t) + QK_K/16 + QK_K/4, "wrong q2_K block size/padding"); + typedef struct { uint8_t hmask[QK_K/8]; uint8_t qs[QK_K/4]; // nibbles / quants @@ -225,6 +233,59 @@ static __device__ void dequantize_q8_0(const void * vx, const int ib, const int //================================== k-quants +static __global__ void dequantize_block_q2_K(const void * vx, float * yy) { + + const int i = blockIdx.x; + const int tid = threadIdx.x; + const int n = tid/32; + const int l = tid - 32*n; + const int is = 8*n + l/16; + + const block_q2_K * x = (const block_q2_K *) vx; + + const uint8_t q = x[i].qs[32*n + l]; + float * y = yy + i*QK_K + 128*n; + + float dall = x[i].d; + float dmin = x[i].dmin; + y[l+ 0] = dall * (x[i].scales[is+0] & 0xF) * ((q >> 0) & 3) - dmin * (x[i].scales[is+0] >> 4); + y[l+32] = dall * (x[i].scales[is+2] & 0xF) * ((q >> 2) & 3) - dmin * (x[i].scales[is+2] >> 4); + y[l+64] = dall * (x[i].scales[is+4] & 0xF) * ((q >> 4) & 3) - dmin * (x[i].scales[is+4] >> 4); + y[l+96] = dall * (x[i].scales[is+6] & 0xF) * ((q >> 6) & 3) - dmin * (x[i].scales[is+6] >> 4); + +} + +static __device__ void vec_dot_q2_K(const void * vx, const int ib, const int iqs, const float * yy, float & result) { + + const block_q2_K * x = (const block_q2_K *) vx; + + // if n is 0, we want to do the lower 128, else the upper 128, + // covering y[l+0], y[l+32], y[l+64], y[l+96] and + // y[l+16], y[l+48], y[l+80], y[l+112] + int n = iqs/128; // 0 or 1 + int r = iqs - 128*n; // 0...120 in steps of 8 + int l = r/8; // 0...15 in steps of 1 + + const float * y = yy + 128*n + l; + const uint8_t * q = x[ib].qs + 32*n + l; + const uint8_t * s = x[ib].scales + 8*n; + + const float dall = x[ib].d; + const float dmin = x[ib].dmin; + + float sum = y[ 0] * (dall * ((s[0] & 0xF) * ((q[ 0] >> 0) & 3)) - dmin * (s[0] >> 4)) + + y[ 32] * (dall * ((s[2] & 0xF) * ((q[ 0] >> 2) & 3)) - dmin * (s[2] >> 4)) + + y[ 64] * (dall * ((s[4] & 0xF) * ((q[ 0] >> 4) & 3)) - dmin * (s[4] >> 4)) + + y[ 96] * (dall * ((s[6] & 0xF) * ((q[ 0] >> 6) & 3)) - dmin * (s[6] >> 4)) + + y[ 16] * (dall * ((s[1] & 0xF) * ((q[16] >> 0) & 3)) - dmin * (s[1] >> 4)) + + y[ 48] * (dall * ((s[3] & 0xF) * ((q[16] >> 2) & 3)) - dmin * (s[1] >> 4)) + + y[ 80] * (dall * ((s[5] & 0xF) * ((q[16] >> 4) & 3)) - dmin * (s[5] >> 4)) + + y[112] * (dall * ((s[7] & 0xF) * ((q[16] >> 6) & 3)) - dmin * (s[7] >> 4)); + + result = sum; + +} + static __global__ void dequantize_block_q3_K(const void * vx, float * yy) { int r = threadIdx.x/4; @@ -625,6 +686,11 @@ static void dequantize_row_q8_0_cuda(const void * vx, float * y, const int k, cu dequantize_block<<>>(vx, y, k); } +static void dequantize_row_q2_K_cuda(const void * vx, float * y, const int k, cudaStream_t stream) { + const int nb = k / QK_K; + dequantize_block_q2_K<<>>(vx, y); +} + static void dequantize_row_q3_K_cuda(const void * vx, float * y, const int k, cudaStream_t stream) { const int nb = k / QK_K; dequantize_block_q3_K<<>>(vx, y); @@ -685,6 +751,12 @@ static void dequantize_mul_mat_vec_q8_0_cuda(const void * vx, const float * y, f <<>>(vx, y, dst, ncols); } +static void dequantize_mul_mat_vec_q2_K_cuda(const void * vx, const float * y, float * dst, const int ncols, const int nrows, cudaStream_t stream) { + GGML_ASSERT(ncols % QK_K == 0); + const dim3 block_dims(32, 2, 1); + dequantize_mul_mat_vec_k<32, vec_dot_q2_K><<>>(vx, y, dst, ncols); +} + static void dequantize_mul_mat_vec_q3_K_cuda(const void * vx, const float * y, float * dst, const int ncols, const int nrows, cudaStream_t stream) { GGML_ASSERT(ncols % QK_K == 0); const dim3 block_dims(32, 2, 1); @@ -734,6 +806,8 @@ static to_fp32_cuda_t ggml_get_to_fp32_cuda(ggml_type type) { return dequantize_row_q5_1_cuda; case GGML_TYPE_Q8_0: return dequantize_row_q8_0_cuda; + case GGML_TYPE_Q2_K: + return dequantize_row_q2_K_cuda; case GGML_TYPE_Q3_K: return dequantize_row_q3_K_cuda; case GGML_TYPE_Q4_K: @@ -761,6 +835,8 @@ static dequantize_mul_mat_vec_cuda_t ggml_get_dequantize_mul_mat_vec_cuda(ggml_t return dequantize_mul_mat_vec_q5_1_cuda; case GGML_TYPE_Q8_0: return dequantize_mul_mat_vec_q8_0_cuda; + case GGML_TYPE_Q2_K: + return dequantize_mul_mat_vec_q2_K_cuda; case GGML_TYPE_Q3_K: return dequantize_mul_mat_vec_q3_K_cuda; case GGML_TYPE_Q4_K: diff --git a/ggml.c b/ggml.c index 8bb5144d6..4b983adc3 100644 --- a/ggml.c +++ b/ggml.c @@ -1566,6 +1566,14 @@ static const quantize_fns_t quantize_fns[GGML_TYPE_COUNT] = { .vec_dot_q = NULL, // TODO .vec_dot_type = GGML_TYPE_Q8_1, }, + [GGML_TYPE_Q2_K] = { + .dequantize_row_q = (dequantize_row_q_t) dequantize_row_q2_K, + .quantize_row_q = quantize_row_q2_K, + .quantize_row_q_reference = (quantize_row_q_t) quantize_row_q2_K_reference, + .quantize_row_q_dot = quantize_row_q8_K, + .vec_dot_q = NULL, //ggml_vec_dot_q2_K_q8_K, + .vec_dot_type = GGML_TYPE_Q8_K, + }, [GGML_TYPE_Q3_K] = { .dequantize_row_q = (dequantize_row_q_t) dequantize_row_q3_K, .quantize_row_q = quantize_row_q3_K, @@ -3477,6 +3485,7 @@ static const int GGML_BLCK_SIZE[GGML_TYPE_COUNT] = { [GGML_TYPE_Q5_1] = QK5_1, [GGML_TYPE_Q8_0] = QK8_0, [GGML_TYPE_Q8_1] = QK8_1, + [GGML_TYPE_Q2_K] = QK_K, [GGML_TYPE_Q3_K] = QK_K, [GGML_TYPE_Q4_K] = QK_K, [GGML_TYPE_Q5_K] = QK_K, @@ -3486,7 +3495,7 @@ static const int GGML_BLCK_SIZE[GGML_TYPE_COUNT] = { [GGML_TYPE_I16] = 1, [GGML_TYPE_I32] = 1, }; -static_assert(GGML_TYPE_COUNT == 18, "GGML_BLCK_SIZE is outdated"); +static_assert(GGML_TYPE_COUNT == 19, "GGML_BLCK_SIZE is outdated"); static const size_t GGML_TYPE_SIZE[GGML_TYPE_COUNT] = { [GGML_TYPE_F32] = sizeof(float), @@ -3497,6 +3506,7 @@ static const size_t GGML_TYPE_SIZE[GGML_TYPE_COUNT] = { [GGML_TYPE_Q5_1] = sizeof(block_q5_1), [GGML_TYPE_Q8_0] = sizeof(block_q8_0), [GGML_TYPE_Q8_1] = sizeof(block_q8_1), + [GGML_TYPE_Q2_K] = sizeof(block_q2_K), [GGML_TYPE_Q3_K] = sizeof(block_q3_K), [GGML_TYPE_Q4_K] = sizeof(block_q4_K), [GGML_TYPE_Q5_K] = sizeof(block_q5_K), @@ -3506,7 +3516,7 @@ static const size_t GGML_TYPE_SIZE[GGML_TYPE_COUNT] = { [GGML_TYPE_I16] = sizeof(int16_t), [GGML_TYPE_I32] = sizeof(int32_t), }; -static_assert(GGML_TYPE_COUNT == 18, "GGML_TYPE_SIZE is outdated"); +static_assert(GGML_TYPE_COUNT == 19, "GGML_TYPE_SIZE is outdated"); static const char * GGML_TYPE_NAME[GGML_TYPE_COUNT] = { @@ -3518,6 +3528,7 @@ static const char * GGML_TYPE_NAME[GGML_TYPE_COUNT] = { [GGML_TYPE_Q5_1] = "q5_1", [GGML_TYPE_Q8_0] = "q8_0", [GGML_TYPE_Q8_1] = "q8_1", + [GGML_TYPE_Q2_K] = "q2_K", [GGML_TYPE_Q3_K] = "q3_K", [GGML_TYPE_Q4_K] = "q4_K", [GGML_TYPE_Q5_K] = "q5_K", @@ -3527,7 +3538,7 @@ static const char * GGML_TYPE_NAME[GGML_TYPE_COUNT] = { [GGML_TYPE_I16] = "i16", [GGML_TYPE_I32] = "i32", }; -static_assert(GGML_TYPE_COUNT == 18, "GGML_TYPE_NAME is outdated"); +static_assert(GGML_TYPE_COUNT == 19, "GGML_TYPE_NAME is outdated"); static bool GGML_IS_QUANTIZED[GGML_TYPE_COUNT] = { [GGML_TYPE_F32] = false, @@ -3538,6 +3549,7 @@ static bool GGML_IS_QUANTIZED[GGML_TYPE_COUNT] = { [GGML_TYPE_Q5_1] = true, [GGML_TYPE_Q8_0] = true, [GGML_TYPE_Q8_1] = true, + [GGML_TYPE_Q2_K] = true, [GGML_TYPE_Q3_K] = true, [GGML_TYPE_Q4_K] = true, [GGML_TYPE_Q5_K] = true, @@ -3547,7 +3559,7 @@ static bool GGML_IS_QUANTIZED[GGML_TYPE_COUNT] = { [GGML_TYPE_I16] = false, [GGML_TYPE_I32] = false, }; -static_assert(GGML_TYPE_COUNT == 18, "GGML_IS_QUANTIZED is outdated"); +static_assert(GGML_TYPE_COUNT == 19, "GGML_IS_QUANTIZED is outdated"); static const char * GGML_OP_NAME[GGML_OP_COUNT] = { "NONE", @@ -3854,6 +3866,7 @@ enum ggml_type ggml_ftype_to_ggml_type(enum ggml_ftype ftype) { case GGML_FTYPE_MOSTLY_Q5_0: wtype = GGML_TYPE_Q5_0; break; case GGML_FTYPE_MOSTLY_Q5_1: wtype = GGML_TYPE_Q5_1; break; case GGML_FTYPE_MOSTLY_Q8_0: wtype = GGML_TYPE_Q8_0; break; + case GGML_FTYPE_MOSTLY_Q2_K: wtype = GGML_TYPE_Q2_K; break; case GGML_FTYPE_MOSTLY_Q3_K: wtype = GGML_TYPE_Q3_K; break; case GGML_FTYPE_MOSTLY_Q4_K: wtype = GGML_TYPE_Q4_K; break; case GGML_FTYPE_MOSTLY_Q5_K: wtype = GGML_TYPE_Q5_K; break; @@ -7641,6 +7654,7 @@ static void ggml_compute_forward_add( case GGML_TYPE_Q5_0: case GGML_TYPE_Q5_1: case GGML_TYPE_Q8_0: + case GGML_TYPE_Q2_K: case GGML_TYPE_Q3_K: case GGML_TYPE_Q4_K: case GGML_TYPE_Q5_K: @@ -7948,6 +7962,7 @@ static void ggml_compute_forward_add1( case GGML_TYPE_Q5_1: case GGML_TYPE_Q8_0: case GGML_TYPE_Q8_1: + case GGML_TYPE_Q2_K: case GGML_TYPE_Q3_K: case GGML_TYPE_Q4_K: case GGML_TYPE_Q5_K: @@ -8074,6 +8089,7 @@ static void ggml_compute_forward_acc( case GGML_TYPE_Q5_1: case GGML_TYPE_Q8_0: case GGML_TYPE_Q8_1: + case GGML_TYPE_Q2_K: case GGML_TYPE_Q3_K: case GGML_TYPE_Q4_K: case GGML_TYPE_Q5_K: @@ -10171,6 +10187,7 @@ static void ggml_compute_forward_mul_mat( case GGML_TYPE_Q5_1: case GGML_TYPE_Q8_0: case GGML_TYPE_Q8_1: + case GGML_TYPE_Q2_K: case GGML_TYPE_Q3_K: case GGML_TYPE_Q4_K: case GGML_TYPE_Q5_K: @@ -10358,6 +10375,7 @@ static void ggml_compute_forward_set( case GGML_TYPE_Q5_1: case GGML_TYPE_Q8_0: case GGML_TYPE_Q8_1: + case GGML_TYPE_Q2_K: case GGML_TYPE_Q3_K: case GGML_TYPE_Q4_K: case GGML_TYPE_Q5_K: @@ -10527,6 +10545,7 @@ static void ggml_compute_forward_get_rows( case GGML_TYPE_Q5_1: case GGML_TYPE_Q8_0: case GGML_TYPE_Q8_1: + case GGML_TYPE_Q2_K: case GGML_TYPE_Q3_K: case GGML_TYPE_Q4_K: case GGML_TYPE_Q5_K: @@ -11077,6 +11096,7 @@ static void ggml_compute_forward_alibi( case GGML_TYPE_Q5_1: case GGML_TYPE_Q8_0: case GGML_TYPE_Q8_1: + case GGML_TYPE_Q2_K: case GGML_TYPE_Q3_K: case GGML_TYPE_Q4_K: case GGML_TYPE_Q5_K: @@ -11153,6 +11173,7 @@ static void ggml_compute_forward_clamp( case GGML_TYPE_Q5_1: case GGML_TYPE_Q8_0: case GGML_TYPE_Q8_1: + case GGML_TYPE_Q2_K: case GGML_TYPE_Q3_K: case GGML_TYPE_Q4_K: case GGML_TYPE_Q5_K: @@ -16161,6 +16182,12 @@ size_t ggml_quantize_chunk(enum ggml_type type, const float * src, void * dst, i block_q8_0 * block = (block_q8_0*)dst + start / QK8_0; result = ggml_quantize_q8_0(src + start, block, n, n, hist); } break; + case GGML_TYPE_Q2_K: + { + GGML_ASSERT(start % QK_K == 0); + block_q2_K * block = (block_q2_K*)dst + start / QK_K; + result = ggml_quantize_q2_K(src + start, block, n, n, hist); + } break; case GGML_TYPE_Q3_K: { GGML_ASSERT(start % QK_K == 0); diff --git a/ggml.h b/ggml.h index 9ad2cb7c0..f1b14511f 100644 --- a/ggml.h +++ b/ggml.h @@ -242,11 +242,12 @@ extern "C" { GGML_TYPE_Q8_0 = 8, GGML_TYPE_Q8_1 = 9, // k-quantizations - GGML_TYPE_Q3_K = 10, - GGML_TYPE_Q4_K = 11, - GGML_TYPE_Q5_K = 12, - GGML_TYPE_Q6_K = 13, - GGML_TYPE_Q8_K = 14, + GGML_TYPE_Q2_K = 10, + GGML_TYPE_Q3_K = 11, + GGML_TYPE_Q4_K = 12, + GGML_TYPE_Q5_K = 13, + GGML_TYPE_Q6_K = 14, + GGML_TYPE_Q8_K = 15, GGML_TYPE_I8, GGML_TYPE_I16, GGML_TYPE_I32, @@ -270,10 +271,11 @@ extern "C" { GGML_FTYPE_MOSTLY_Q8_0 = 7, // except 1d tensors GGML_FTYPE_MOSTLY_Q5_0 = 8, // except 1d tensors GGML_FTYPE_MOSTLY_Q5_1 = 9, // except 1d tensors - GGML_FTYPE_MOSTLY_Q3_K = 10, // except 1d tensors - GGML_FTYPE_MOSTLY_Q4_K = 11, // except 1d tensors - GGML_FTYPE_MOSTLY_Q5_K = 12, // except 1d tensors - GGML_FTYPE_MOSTLY_Q6_K = 13, // except 1d tensors + GGML_FTYPE_MOSTLY_Q2_K = 10, // except 1d tensors + GGML_FTYPE_MOSTLY_Q3_K = 11, // except 1d tensors + GGML_FTYPE_MOSTLY_Q4_K = 12, // except 1d tensors + GGML_FTYPE_MOSTLY_Q5_K = 13, // except 1d tensors + GGML_FTYPE_MOSTLY_Q6_K = 14, // except 1d tensors }; // available tensor operations: diff --git a/k_quants.c b/k_quants.c index ecf17d7ba..cf42869f6 100644 --- a/k_quants.c +++ b/k_quants.c @@ -270,6 +270,127 @@ static inline void get_scale_min_k4(int j, const uint8_t * restrict q, uint8_t * } } +//========================- 2-bit (de)-quantization + +void quantize_row_q2_K_reference(const float * restrict x, block_q2_K * restrict y, int k) { + assert(k % QK_K == 0); + const int nb = k / QK_K; + + uint8_t L[QK_K]; + float mins[QK_K/16]; + float scales[QK_K/16]; + + const float q4scale = 15.f; + + for (int i = 0; i < nb; i++) { + + float max_scale = 0; // as we are deducting the min, scales are always positive + float max_min = 0; + for (int j = 0; j < QK_K/16; ++j) { + scales[j] = make_qkx1_quants(16, 3, x + 16*j, L + 16*j, &mins[j], 5); + float scale = scales[j]; + if (scale > max_scale) { + max_scale = scale; + } + float min = mins[j]; + if (min > max_min) { + max_min = min; + } + } + + if (max_scale > 0) { + float iscale = q4scale/max_scale; + for (int j = 0; j < QK_K/16; ++j) { + int l = nearest_int(iscale*scales[j]); + y[i].scales[j] = l; + } + y[i].d = ggml_fp32_to_fp16(max_scale/q4scale); + } else { + for (int j = 0; j < QK_K/16; ++j) y[i].scales[j] = 0; + y[i].d = ggml_fp32_to_fp16(0.f); + } + if (max_min > 0) { + float iscale = q4scale/max_min; + for (int j = 0; j < QK_K/16; ++j) { + int l = nearest_int(iscale*mins[j]); + y[i].scales[j] |= (l << 4); + } + y[i].dmin = ggml_fp32_to_fp16(max_min/q4scale); + } else { + y[i].dmin = ggml_fp32_to_fp16(0.f); + } + for (int j = 0; j < QK_K/16; ++j) { + const float d = ggml_fp16_to_fp32(y[i].d) * (y[i].scales[j] & 0xF); + if (!d) continue; + const float dm = ggml_fp16_to_fp32(y[i].dmin) * (y[i].scales[j] >> 4); + for (int ii = 0; ii < 16; ++ii) { + int l = nearest_int((x[16*j + ii] + dm)/d); + l = MAX(0, MIN(3, l)); + L[16*j + ii] = l; + } + } + + for (int j = 0; j < QK_K; j += 128) { + for (int l = 0; l < 32; ++l) { + y[i].qs[j/4 + l] = L[j + l] | (L[j + l + 32] << 2) | (L[j + l + 64] << 4) | (L[j + l + 96] << 6); + } + } + + x += QK_K; + + } +} + +void dequantize_row_q2_K(const block_q2_K * restrict x, float * restrict y, int k) { + assert(k % QK_K == 0); + const int nb = k / QK_K; + + for (int i = 0; i < nb; i++) { + + const float d = ggml_fp16_to_fp32(x[i].d); + const float min = ggml_fp16_to_fp32(x[i].dmin); + + const uint8_t * q = x[i].qs; + + int is = 0; + float dl, ml; + for (int n = 0; n < QK_K; n += 128) { + int shift = 0; + for (int j = 0; j < 4; ++j) { + + uint8_t sc = x[i].scales[is++]; + dl = d * (sc & 0xF); ml = min * (sc >> 4); + for (int l = 0; l < 16; ++l) *y++ = dl * ((int8_t)((q[l] >> shift) & 3)) - ml; + + sc = x[i].scales[is++]; + dl = d * (sc & 0xF); ml = min * (sc >> 4); + for (int l = 0; l < 16; ++l) *y++ = dl * ((int8_t)((q[l+16] >> shift) & 3)) - ml; + + shift += 2; + } + q += 32; + } + + } +} + +void quantize_row_q2_K(const float * restrict x, void * restrict vy, int k) { + quantize_row_q2_K_reference(x, vy, k); +} + +size_t ggml_quantize_q2_K(const float * restrict src, void * restrict dst, int n, int k, int64_t * restrict hist) { + const int nb = k / QK_K; + + // TODO - collect histograms - although, at a second thought, I don't really care about them + (void)hist; + + for (int j = 0; j < nb; j += k) { + block_q2_K * restrict y = (block_q2_K *)dst + j/QK_K; + quantize_row_q2_K_reference(src + j, y, k); + } + return (n/QK_K*sizeof(block_q2_K)); +} + //========================= 3-bit (de)-quantization void quantize_row_q3_K_reference(const float * restrict x, block_q3_K * restrict y, int k) { diff --git a/k_quants.h b/k_quants.h index 2742b6810..10a0baac7 100644 --- a/k_quants.h +++ b/k_quants.h @@ -13,6 +13,18 @@ // Super-block quantization structures // +// 2-bit quantization +// weight is represented as x = a * q + b +// 16 blocks of 16 elemenets each +// Effectively 2.5625 bits per weight +typedef struct { + uint8_t scales[QK_K/16]; // scales and mins, quantized with 4 bits + uint8_t qs[QK_K/4]; // quants + ggml_fp16_t d; // super-block scale for quantized scales + ggml_fp16_t dmin; // super-block scale for quantized mins +} block_q2_K; +static_assert(sizeof(block_q2_K) == 2*sizeof(ggml_fp16_t) + QK_K/16 + QK_K/4, "wrong q2_K block size/padding"); + // 3-bit quantization // weight is represented as x = a * q // 16 blocks of 16 elemenets each @@ -32,7 +44,7 @@ static_assert(sizeof(block_q3_K) == sizeof(ggml_fp16_t) + QK_K / 4 + 11 * QK_K / typedef struct { ggml_fp16_t d; // super-block scale for quantized scales ggml_fp16_t dmin; // super-block scale for quantized mins - uint8_t scales[3*QK_K/64]; // scales, quantized with 6 bits + uint8_t scales[3*QK_K/64]; // scales and mins, quantized with 6 bits uint8_t qs[QK_K/2]; // 4--bit quants } block_q4_K; static_assert(sizeof(block_q4_K) == 2*sizeof(ggml_fp16_t) + 3*QK_K/64 + QK_K/2, "wrong q4_K block size/padding"); @@ -44,7 +56,7 @@ static_assert(sizeof(block_q4_K) == 2*sizeof(ggml_fp16_t) + 3*QK_K/64 + QK_K/2, typedef struct { ggml_fp16_t d; // super-block scale for quantized scales ggml_fp16_t dmin; // super-block scale for quantized mins - uint8_t scales[3*QK_K/64]; // scales, quantized with 6 bits + uint8_t scales[3*QK_K/64]; // scales and mins, quantized with 6 bits uint8_t qh[QK_K/8]; // quants, high bit uint8_t qs[QK_K/2]; // quants, low 4 bits } block_q5_K; @@ -72,12 +84,14 @@ static_assert(sizeof(block_q8_K) == sizeof(float) + QK_K + QK_K/16*sizeof(int16_ // Quantization +void quantize_row_q2_K_reference(const float * restrict x, block_q2_K * restrict y, int k); void quantize_row_q3_K_reference(const float * restrict x, block_q3_K * restrict y, int k); void quantize_row_q4_K_reference(const float * restrict x, block_q4_K * restrict y, int k); void quantize_row_q5_K_reference(const float * restrict x, block_q5_K * restrict y, int k); void quantize_row_q6_K_reference(const float * restrict x, block_q6_K * restrict y, int k); void quantize_row_q8_K_reference(const float * restrict x, block_q8_K * restrict y, int k); +void quantize_row_q2_K(const float * restrict x, void * restrict y, int k); void quantize_row_q3_K(const float * restrict x, void * restrict y, int k); void quantize_row_q4_K(const float * restrict x, void * restrict y, int k); void quantize_row_q5_K(const float * restrict x, void * restrict y, int k); @@ -85,6 +99,7 @@ void quantize_row_q6_K(const float * restrict x, void * restrict y, int k); void quantize_row_q8_K(const float * restrict x, void * restrict y, int k); // Dequantization +void dequantize_row_q2_K(const block_q2_K * restrict x, float * restrict y, int k); void dequantize_row_q3_K(const block_q3_K * restrict x, float * restrict y, int k); void dequantize_row_q4_K(const block_q4_K * restrict x, float * restrict y, int k); void dequantize_row_q5_K(const block_q5_K * restrict x, float * restrict y, int k); @@ -92,12 +107,14 @@ void dequantize_row_q6_K(const block_q6_K * restrict x, float * restrict y, int void dequantize_row_q8_K(const block_q8_K * restrict x, float * restrict y, int k); // Dot product +void ggml_vec_dot_q2_K_q8_K(int n, float * restrict s, const void * restrict vx, const void * restrict vy); void ggml_vec_dot_q3_K_q8_K(int n, float * restrict s, const void * restrict vx, const void * restrict vy); void ggml_vec_dot_q4_K_q8_K(int n, float * restrict s, const void * restrict vx, const void * restrict vy); void ggml_vec_dot_q5_K_q8_K(int n, float * restrict s, const void * restrict vx, const void * restrict vy); void ggml_vec_dot_q6_K_q8_K(int n, float * restrict s, const void * restrict vx, const void * restrict vy); // Quantization with histogram collection +size_t ggml_quantize_q2_K(const float * src, void * dst, int n, int k, int64_t * hist); size_t ggml_quantize_q3_K(const float * src, void * dst, int n, int k, int64_t * hist); size_t ggml_quantize_q4_K(const float * src, void * dst, int n, int k, int64_t * hist); size_t ggml_quantize_q5_K(const float * src, void * dst, int n, int k, int64_t * hist); diff --git a/llama.cpp b/llama.cpp index 7f6b86ab4..f351844aa 100644 --- a/llama.cpp +++ b/llama.cpp @@ -507,6 +507,7 @@ struct llama_file_loader { case GGML_TYPE_Q5_0: case GGML_TYPE_Q5_1: case GGML_TYPE_Q8_0: + case GGML_TYPE_Q2_K: case GGML_TYPE_Q3_K: case GGML_TYPE_Q4_K: case GGML_TYPE_Q5_K: @@ -586,6 +587,7 @@ struct llama_file_saver { case GGML_TYPE_Q5_0: case GGML_TYPE_Q5_1: case GGML_TYPE_Q8_0: + case GGML_TYPE_Q2_K: case GGML_TYPE_Q3_K: case GGML_TYPE_Q4_K: case GGML_TYPE_Q5_K: @@ -907,6 +909,7 @@ static const char *llama_ftype_name(enum llama_ftype ftype) { case LLAMA_FTYPE_MOSTLY_Q5_1: return "mostly Q5_1"; case LLAMA_FTYPE_MOSTLY_Q8_0: return "mostly Q8_0"; // K-quants + case LLAMA_FTYPE_MOSTLY_Q2_K: return "mostly Q2_K"; case LLAMA_FTYPE_MOSTLY_Q3_K_S: return "mostly Q3_K - Small"; case LLAMA_FTYPE_MOSTLY_Q3_K_M: return "mostly Q3_K - Medium"; case LLAMA_FTYPE_MOSTLY_Q3_K_L: return "mostly Q3_K - Large"; @@ -2081,6 +2084,7 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s case LLAMA_FTYPE_MOSTLY_Q5_1: quantized_type = GGML_TYPE_Q5_1; break; case LLAMA_FTYPE_MOSTLY_Q8_0: quantized_type = GGML_TYPE_Q8_0; break; // K-quants + case LLAMA_FTYPE_MOSTLY_Q2_K: quantized_type = GGML_TYPE_Q2_K; break; case LLAMA_FTYPE_MOSTLY_Q3_K_S: case LLAMA_FTYPE_MOSTLY_Q3_K_M: case LLAMA_FTYPE_MOSTLY_Q3_K_L: quantized_type = GGML_TYPE_Q3_K; break; @@ -2158,7 +2162,7 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s new_type = quantized_type; if (tensor.name == "output.weight") new_type = GGML_TYPE_Q6_K; else if (tensor.name.find("attention.wv.weight") != std::string::npos) { - if (ftype == LLAMA_FTYPE_MOSTLY_Q3_K_M) new_type = GGML_TYPE_Q4_K; + if (ftype == LLAMA_FTYPE_MOSTLY_Q3_K_M || ftype == LLAMA_FTYPE_MOSTLY_Q2_K) new_type = GGML_TYPE_Q4_K; else if (ftype == LLAMA_FTYPE_MOSTLY_Q3_K_L) new_type = GGML_TYPE_Q5_K; else if ((ftype == LLAMA_FTYPE_MOSTLY_Q4_K_M || ftype == LLAMA_FTYPE_MOSTLY_Q5_K_M) && (i_attention_wv < n_attention_wv/8 || i_attention_wv >= 7*n_attention_wv/8 || @@ -2166,7 +2170,7 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s ++i_attention_wv; } else if (tensor.name.find("feed_forward.w2.weight") != std::string::npos) { - if (ftype == LLAMA_FTYPE_MOSTLY_Q3_K_M) new_type = GGML_TYPE_Q4_K; + if (ftype == LLAMA_FTYPE_MOSTLY_Q3_K_M || ftype == LLAMA_FTYPE_MOSTLY_Q2_K) new_type = GGML_TYPE_Q4_K; else if (ftype == LLAMA_FTYPE_MOSTLY_Q3_K_L) new_type = GGML_TYPE_Q5_K; else if ((ftype == LLAMA_FTYPE_MOSTLY_Q4_K_M || ftype == LLAMA_FTYPE_MOSTLY_Q5_K_M) && (i_feed_forward_w2 < n_feed_forward_w2/8 || i_feed_forward_w2 >= 7*n_feed_forward_w2/8 || @@ -2174,7 +2178,7 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s ++i_feed_forward_w2; } else if (tensor.name.find("attention.wo.weight") != std::string::npos) { - if (ftype == LLAMA_FTYPE_MOSTLY_Q3_K_M) new_type = GGML_TYPE_Q4_K; + if (ftype == LLAMA_FTYPE_MOSTLY_Q3_K_M || ftype == LLAMA_FTYPE_MOSTLY_Q2_K) new_type = GGML_TYPE_Q4_K; else if (ftype == LLAMA_FTYPE_MOSTLY_Q3_K_L) new_type = GGML_TYPE_Q5_K; } float * f32_data; diff --git a/llama.h b/llama.h index 1ffc30963..af8ea1075 100644 --- a/llama.h +++ b/llama.h @@ -94,14 +94,15 @@ extern "C" { LLAMA_FTYPE_MOSTLY_Q8_0 = 7, // except 1d tensors LLAMA_FTYPE_MOSTLY_Q5_0 = 8, // except 1d tensors LLAMA_FTYPE_MOSTLY_Q5_1 = 9, // except 1d tensors - LLAMA_FTYPE_MOSTLY_Q3_K_S = 10,// except 1d tensors - LLAMA_FTYPE_MOSTLY_Q3_K_M = 11,// except 1d tensors - LLAMA_FTYPE_MOSTLY_Q3_K_L = 12,// except 1d tensors - LLAMA_FTYPE_MOSTLY_Q4_K_S = 13,// except 1d tensors - LLAMA_FTYPE_MOSTLY_Q4_K_M = 14,// except 1d tensors - LLAMA_FTYPE_MOSTLY_Q5_K_S = 15,// except 1d tensors - LLAMA_FTYPE_MOSTLY_Q5_K_M = 16,// except 1d tensors - LLAMA_FTYPE_MOSTLY_Q6_K = 17,// except 1d tensors + LLAMA_FTYPE_MOSTLY_Q2_K = 10,// except 1d tensors + LLAMA_FTYPE_MOSTLY_Q3_K_S = 11,// except 1d tensors + LLAMA_FTYPE_MOSTLY_Q3_K_M = 12,// except 1d tensors + LLAMA_FTYPE_MOSTLY_Q3_K_L = 13,// except 1d tensors + LLAMA_FTYPE_MOSTLY_Q4_K_S = 14,// except 1d tensors + LLAMA_FTYPE_MOSTLY_Q4_K_M = 15,// except 1d tensors + LLAMA_FTYPE_MOSTLY_Q5_K_S = 16,// except 1d tensors + LLAMA_FTYPE_MOSTLY_Q5_K_M = 17,// except 1d tensors + LLAMA_FTYPE_MOSTLY_Q6_K = 18,// except 1d tensors }; LLAMA_API struct llama_context_params llama_context_default_params();