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https://github.com/ikawrakow/ik_llama.cpp.git
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Q5_K_R4 (#132)
* q5_k_r4: WIP * q5_k_r4: Zen4 and AVX2 We get PP-512(LLaMA-3.1-8B) = 248.3 t/s on Zen4. Q5_K_S has PP-512 = 190 t/s. * q5_k_r4: NEON We get PP-512(LLaMA-3.1-8B) = 96.1 t/s. --------- Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
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@ -62,6 +62,7 @@ static const std::vector<struct quant_option> QUANT_OPTIONS = {
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{ "Q4_K_S", LLAMA_FTYPE_MOSTLY_Q4_K_S, " 3.59G, +0.0992 ppl @ LLaMA-v1-7B", },
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{ "Q4_K_M", LLAMA_FTYPE_MOSTLY_Q4_K_M, " 3.80G, +0.0532 ppl @ LLaMA-v1-7B", },
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{ "Q5_K", LLAMA_FTYPE_MOSTLY_Q5_K_M, "alias for Q5_K_M", },
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{ "Q5_K_R4", LLAMA_FTYPE_MOSTLY_Q5_K_R4, "Q5_K_S repacked", },
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{ "Q5_K_S", LLAMA_FTYPE_MOSTLY_Q5_K_S, " 4.33G, +0.0400 ppl @ LLaMA-v1-7B", },
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{ "Q5_K_M", LLAMA_FTYPE_MOSTLY_Q5_K_M, " 4.45G, +0.0122 ppl @ LLaMA-v1-7B", },
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{ "Q6_K", LLAMA_FTYPE_MOSTLY_Q6_K, " 5.15G, +0.0008 ppl @ LLaMA-v1-7B", },
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@ -413,6 +413,7 @@ extern "C" {
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GGML_TYPE_Q5_0_R4 = 206,
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GGML_TYPE_Q8_0_R4 = 208,
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GGML_TYPE_Q4_K_R4 = 212,
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GGML_TYPE_Q5_K_R4 = 213,
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GGML_TYPE_Q6_K_R4 = 214,
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GGML_TYPE_IQ4_NL_R4 = 220,
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GGML_TYPE_IQ4_XS_R4 = 223,
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@ -481,6 +482,7 @@ extern "C" {
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GGML_FTYPE_MOSTLY_Q8_0_R4 = 207, // except 1d tensors
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GGML_FTYPE_MOSTLY_Q5_0_R4 = 208, // except 1d tensors
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GGML_FTYPE_MOSTLY_Q4_K_R4 = 212, // except 1d tensors
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GGML_FTYPE_MOSTLY_Q5_K_R4 = 215, // except 1d tensors
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GGML_FTYPE_MOSTLY_Q6_K_R4 = 214, // except 1d tensors
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GGML_FTYPE_MOSTLY_IQ4_NL_R4 = 219, // except 1d tensors
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GGML_FTYPE_MOSTLY_IQ4_XS_R4 = 222, // except 1d tensors
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@ -319,6 +319,15 @@ typedef struct {
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} block_q5_K;
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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");
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typedef struct {
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ggml_half d[8];
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uint8_t scales_h[QK_K/16];// scales and mins, quantized with 6 bits
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uint8_t scales_l[QK_K/8]; // scales and mins, quantized with 6 bits
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uint8_t qh[QK_K/2]; // quants, high bit
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uint8_t qs[QK_K*2]; // quants, low 4 bits
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} block_q5_k_r4;
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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");
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// 6-bit quantization
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// weight is represented as x = a * q
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// 16 blocks of 16 elements each
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@ -15203,6 +15203,7 @@ bool ggml_validate_row_data(enum ggml_type type, const void * data, size_t nbyte
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case GGML_TYPE_Q6_0_R4: break;
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case GGML_TYPE_Q8_0_R4: break;
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case GGML_TYPE_Q4_K_R4: break;
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case GGML_TYPE_Q5_K_R4: break;
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case GGML_TYPE_Q6_K_R4: break;
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case GGML_TYPE_Q4_0_4_4:
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case GGML_TYPE_Q4_0_4_8:
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@ -914,6 +914,19 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = {
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.nrows = 1,
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.row_meta_size = 0,
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},
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[GGML_TYPE_Q5_K_R4] = {
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.type_name = "q5_k_r4",
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.blck_size = QK_K,
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.type_size = sizeof(block_q5_K),
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.is_quantized = true,
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.to_float = (ggml_to_float_t) dequantize_row_q5_k_r4,
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.from_float = quantize_row_q5_k_r4,
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.from_float_ref = (ggml_from_float_t) quantize_row_q5_k_r4_ref,
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.vec_dot = vec_dot_q5_k_r4_q8_k,
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.vec_dot_type = GGML_TYPE_Q8_K32,
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.nrows = 1,
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.row_meta_size = 0,
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},
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[GGML_TYPE_Q6_K] = {
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.type_name = "q6_K",
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.blck_size = QK_K,
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@ -4048,6 +4061,7 @@ enum ggml_type ggml_ftype_to_ggml_type(enum ggml_ftype ftype) {
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case GGML_FTYPE_MOSTLY_Q4_K: wtype = GGML_TYPE_Q4_K; break;
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case GGML_FTYPE_MOSTLY_Q4_K_R4: wtype = GGML_TYPE_Q4_K_R4; break;
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case GGML_FTYPE_MOSTLY_Q5_K: wtype = GGML_TYPE_Q5_K; break;
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case GGML_FTYPE_MOSTLY_Q5_K_R4: wtype = GGML_TYPE_Q5_K_R4; break;
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case GGML_FTYPE_MOSTLY_Q6_K: wtype = GGML_TYPE_Q6_K; break;
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case GGML_FTYPE_MOSTLY_Q6_K_R4: wtype = GGML_TYPE_Q6_K_R4; break;
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case GGML_FTYPE_MOSTLY_IQ2_XXS: wtype = GGML_TYPE_IQ2_XXS; break;
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@ -10580,6 +10594,7 @@ static void ggml_compute_forward_add(
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case GGML_TYPE_Q4_K:
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case GGML_TYPE_Q4_K_R4:
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case GGML_TYPE_Q5_K:
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case GGML_TYPE_Q5_K_R4:
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case GGML_TYPE_Q6_K:
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case GGML_TYPE_Q6_K_R4:
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case GGML_TYPE_IQ2_XXS:
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@ -11031,6 +11046,7 @@ static void ggml_compute_forward_add1(
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case GGML_TYPE_Q4_K:
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case GGML_TYPE_Q4_K_R4:
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case GGML_TYPE_Q5_K:
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case GGML_TYPE_Q5_K_R4:
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case GGML_TYPE_Q6_K:
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case GGML_TYPE_Q6_K_R4:
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case GGML_TYPE_IQ2_XXS:
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@ -11179,6 +11195,7 @@ static void ggml_compute_forward_acc(
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case GGML_TYPE_Q4_K:
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case GGML_TYPE_Q4_K_R4:
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case GGML_TYPE_Q5_K:
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case GGML_TYPE_Q5_K_R4:
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case GGML_TYPE_Q6_K:
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case GGML_TYPE_Q6_K_R4:
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case GGML_TYPE_IQ2_XXS:
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@ -14373,6 +14390,7 @@ static void ggml_compute_forward_out_prod(
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case GGML_TYPE_Q4_K:
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case GGML_TYPE_Q4_K_R4:
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case GGML_TYPE_Q5_K:
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case GGML_TYPE_Q5_K_R4:
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case GGML_TYPE_Q6_K:
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case GGML_TYPE_Q6_K_R4:
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case GGML_TYPE_IQ2_XXS:
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@ -14761,6 +14779,7 @@ static void ggml_compute_forward_set(
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case GGML_TYPE_Q4_K:
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case GGML_TYPE_Q4_K_R4:
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case GGML_TYPE_Q5_K:
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case GGML_TYPE_Q5_K_R4:
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case GGML_TYPE_Q6_K:
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case GGML_TYPE_Q6_K_R4:
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case GGML_TYPE_IQ2_XXS:
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@ -15043,6 +15062,7 @@ static void ggml_compute_forward_get_rows(
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case GGML_TYPE_Q4_K:
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case GGML_TYPE_Q4_K_R4:
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case GGML_TYPE_Q5_K:
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case GGML_TYPE_Q5_K_R4:
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case GGML_TYPE_Q6_K:
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case GGML_TYPE_Q6_K_R4:
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case GGML_TYPE_IQ2_XXS:
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@ -15652,6 +15672,7 @@ static void ggml_compute_forward_clamp(
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case GGML_TYPE_Q4_K:
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case GGML_TYPE_Q4_K_R4:
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case GGML_TYPE_Q5_K:
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case GGML_TYPE_Q5_K_R4:
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case GGML_TYPE_Q6_K:
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case GGML_TYPE_Q6_K_R4:
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case GGML_TYPE_IQ2_XXS:
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@ -22489,6 +22510,7 @@ size_t ggml_quantize_chunk(
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case GGML_TYPE_Q4_K: result = quantize_q4_K(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
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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;
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case GGML_TYPE_Q5_K: result = quantize_q5_K(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
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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;
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case GGML_TYPE_Q6_K: result = quantize_q6_K(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
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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;
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case GGML_TYPE_IQ2_XXS: result = quantize_iq2_xxs(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
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@ -3255,6 +3255,190 @@ static void mul_mat_q4_k_r4_q8_k(int n, const void * vx, size_t bx, const DataIn
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}
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#endif
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template <int nrc_y>
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static void mul_mat_q5_k_r4_q8_k_avx2(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) {
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GGML_ASSERT(nrc_x%4 == 0);
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Q8<nrc_y, block_q8_K> q8(info);
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auto mf = _mm256_set1_epi8(0xf);
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auto m10 = _mm256_set1_epi8(0x10);
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auto m30 = _mm256_set1_epi8(0x30);
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#ifndef HAVE_FANCY_SIMD
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auto m1 = _mm256_set1_epi16(1);
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#endif
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int nbl = n / QK_K;
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union { __m256i vec; uint32_t val[8]; } hd;
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__m256 acc[nrc_y] = {};
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__m256i qx[4];
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for (int ix = 0; ix < nrc_x; ix += 4) {
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const block_q5_k_r4 * iq5 = (const block_q5_k_r4 *)((const char *)vx + (ix+0)*bx);
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for (int ibl = 0; ibl < nbl; ++ibl) { // Block of 256
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auto dl = _mm256_cvtph_ps(_mm_loadu_si128((const __m128i *)iq5[ibl].d));
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auto d4 = _mm256_set_m128(_mm256_castps256_ps128(dl), _mm256_castps256_ps128(dl));
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auto m4 = _mm256_mul_ps(_mm256_set1_ps(-1.0f), _mm256_set_m128(_mm256_extractf128_ps(dl, 1), _mm256_extractf128_ps(dl, 1)));
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if constexpr (nrc_y == 1) {
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d4 = _mm256_mul_ps(d4, _mm256_set1_ps(q8.scale(0, ibl)));
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}
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auto lbits = _mm256_loadu_si256((const __m256i *)iq5[ibl].scales_l);
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auto hbits128 = _mm_loadu_si128((const __m128i *)iq5[ibl].scales_h);
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auto hbits = MM256_SET_M128I(hbits128, _mm_slli_epi16(hbits128, 4));
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hd.vec = _mm256_or_si256(_mm256_and_si256(lbits, mf), _mm256_and_si256(hbits, m30));
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auto mins = _mm256_or_si256(_mm256_and_si256(_mm256_srli_epi16(lbits, 4), mf), _mm256_and_si256(_mm256_srli_epi16(hbits, 2), m30));
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auto shuffle = _mm256_set1_epi64x(0x0000000400000000);
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auto c1 = _mm256_mul_ps(m4, _mm256_cvtepi32_ps(_mm256_cvtepi8_epi32(_mm256_castsi256_si128(_mm256_permutevar8x32_epi32(mins, shuffle)))));
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shuffle = _mm256_add_epi32(shuffle, _mm256_set1_epi32(1));
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auto c2 = _mm256_mul_ps(m4, _mm256_cvtepi32_ps(_mm256_cvtepi8_epi32(_mm256_castsi256_si128(_mm256_permutevar8x32_epi32(mins, shuffle)))));
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shuffle = _mm256_add_epi32(shuffle, _mm256_set1_epi32(1));
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auto c3 = _mm256_mul_ps(m4, _mm256_cvtepi32_ps(_mm256_cvtepi8_epi32(_mm256_castsi256_si128(_mm256_permutevar8x32_epi32(mins, shuffle)))));
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shuffle = _mm256_add_epi32(shuffle, _mm256_set1_epi32(1));
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auto c4 = _mm256_mul_ps(m4, _mm256_cvtepi32_ps(_mm256_cvtepi8_epi32(_mm256_castsi256_si128(_mm256_permutevar8x32_epi32(mins, shuffle)))));
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for (int iy = 0; iy < nrc_y; ++iy) {
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auto bs = _mm256_loadu_ps((const float *)q8.y[iy][ibl].bsums);
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acc[iy] = _mm256_fmadd_ps(c1, _mm256_shuffle_ps(bs, bs, 0x00), acc[iy]);
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acc[iy] = _mm256_fmadd_ps(c2, _mm256_shuffle_ps(bs, bs, 0x55), acc[iy]);
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acc[iy] = _mm256_fmadd_ps(c3, _mm256_shuffle_ps(bs, bs, 0xaa), acc[iy]);
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acc[iy] = _mm256_fmadd_ps(c4, _mm256_shuffle_ps(bs, bs, 0xff), acc[iy]);
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}
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for (int ib = 0; ib < QK_K/32; ++ib) {
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auto scales_d = _mm256_mul_ps(d4, _mm256_cvtepi32_ps(_mm256_cvtepi8_epi32(_mm_set1_epi32(hd.val[ib]))));
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auto lbits1 = _mm256_loadu_si256((const __m256i *)iq5[ibl].qs+2*ib+0);
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auto lbits2 = _mm256_loadu_si256((const __m256i *)iq5[ibl].qs+2*ib+1);
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auto hbits128 = _mm_loadu_si128((const __m128i*)iq5[ibl].qh + ib);
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auto hbits = MM256_SET_M128I(hbits128, _mm_slli_epi16(hbits128, 4));
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qx[0] = _mm256_or_si256(_mm256_and_si256(lbits1, mf), _mm256_and_si256(m10, hbits));
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qx[1] = _mm256_or_si256(_mm256_and_si256(lbits2, mf), _mm256_and_si256(m10, _mm256_srli_epi16(hbits, 2)));
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qx[2] = _mm256_or_si256(_mm256_and_si256(_mm256_srli_epi16(lbits1, 4), mf), _mm256_and_si256(m10, _mm256_srli_epi16(hbits, 1)));
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qx[3] = _mm256_or_si256(_mm256_and_si256(_mm256_srli_epi16(lbits2, 4), mf), _mm256_and_si256(m10, _mm256_srli_epi16(hbits, 3)));
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for (int iy = 0; iy < nrc_y; ++iy) {
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auto y = _mm256_loadu_si256((const __m256i*)q8.y[iy][ibl].qs+ib);
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#ifdef HAVE_FANCY_SIMD
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auto sumi = _mm256_setzero_si256();
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sumi = _mm256_dpbusd_epi32(sumi, qx[0], _mm256_shuffle_epi32(y, 0x00));
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sumi = _mm256_dpbusd_epi32(sumi, qx[1], _mm256_shuffle_epi32(y, 0x55));
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sumi = _mm256_dpbusd_epi32(sumi, qx[2], _mm256_shuffle_epi32(y, 0xaa));
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sumi = _mm256_dpbusd_epi32(sumi, qx[3], _mm256_shuffle_epi32(y, 0xff));
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#else
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auto sumi1 = _mm256_add_epi16(_mm256_maddubs_epi16(qx[0], _mm256_shuffle_epi32(y, 0x00)),
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_mm256_maddubs_epi16(qx[1], _mm256_shuffle_epi32(y, 0x55)));
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auto sumi2 = _mm256_add_epi16(_mm256_maddubs_epi16(qx[2], _mm256_shuffle_epi32(y, 0xaa)),
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_mm256_maddubs_epi16(qx[3], _mm256_shuffle_epi32(y, 0xff)));
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auto sumi = _mm256_madd_epi16(m1, _mm256_add_epi16(sumi1, sumi2));
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#endif
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if constexpr (nrc_y == 1) {
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acc[iy] = _mm256_fmadd_ps(scales_d, _mm256_cvtepi32_ps(sumi), acc[iy]);
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} else {
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float d8 = q8.scale(iy, ibl);
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acc[iy] = _mm256_fmadd_ps(_mm256_mul_ps(scales_d, _mm256_set1_ps(d8)), _mm256_cvtepi32_ps(sumi), acc[iy]);
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}
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}
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}
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}
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for (int iy = 0; iy < nrc_y; ++iy) {
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auto sum = _mm_add_ps(_mm256_castps256_ps128(acc[iy]), _mm256_extractf128_ps(acc[iy], 1));
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acc[iy] = _mm256_setzero_ps();
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info.store(ix+0, iy, sum);
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}
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}
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}
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#ifdef HAVE_FANCY_SIMD
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template <int nrc_y>
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static void mul_mat_q5_k_r4_q8_k(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) {
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if constexpr (nrc_y == 1){
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mul_mat_q4_k_r4_q8_k_avx2<1>(n, vx, bx, info, nrc_x);
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} else {
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GGML_ASSERT(nrc_x%8 == 0);
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Q8<nrc_y, block_q8_K> q8(info);
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auto mf = _mm512_set1_epi8(0xf);
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auto m10 = _mm512_set1_epi8(0x10);
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int nbl = n / QK_K;
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using helper_t = union { __m512i vec; uint32_t val[16]; };
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helper_t hd, hm;
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__m512 acc[nrc_y] = {};
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__m512 d4s[nrc_y];
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__m512i qx[4];
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for (int ix = 0; ix < nrc_x; ix += 8) {
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const block_q5_k_r4 * iq5l = (const block_q5_k_r4 *)((const char *)vx + (ix+0)*bx);
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const block_q5_k_r4 * iq5h = (const block_q5_k_r4 *)((const char *)vx + (ix+4)*bx);
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for (int ibl = 0; ibl < nbl; ++ibl) { // Block of 256
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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);
|
||||
@ -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>;
|
||||
@ -8146,6 +8342,86 @@ 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);
|
||||
@ -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;
|
||||
|
||||
@ -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);
|
||||
}
|
||||
|
||||
|
||||
@ -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);
|
||||
|
||||
@ -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
|
||||
|
||||
@ -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;
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user