IQ5_K_R4 (#149)
* iq5_k_r4: Zen4 Much slower than the others. * iq5_k_r5: WIP * Minor * iq5_k_r4: fix AVX2 nrc_y = 1 case * iq5_k_r4: better Zen4 But TG is still slower than iq5_k * iq5_k_r4: slightly better AVX2 * iq5_k_r4: NEON --------- Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
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Kawrakow
GitHub
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2247afa967
commit
c208fec2f2
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@ -61,6 +61,7 @@ static const std::vector<struct quant_option> QUANT_OPTIONS = {
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{ "IQ4_K", LLAMA_FTYPE_MOSTLY_IQ4_K, " 4.5 bpw non-linear quantization", },
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{ "IQ4_K_R4", LLAMA_FTYPE_MOSTLY_IQ4_K_R4, "IQ4_K repacked", },
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{ "IQ5_K", LLAMA_FTYPE_MOSTLY_IQ5_K, " 5.5 bpw non-linear quantization", },
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{ "IQ5_K_R4", LLAMA_FTYPE_MOSTLY_IQ5_K_R4, "IQ5_K repacked", },
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{ "IQ6_K", LLAMA_FTYPE_MOSTLY_IQ6_K, " 6.6 bpw non-linear quantization", },
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{ "Q4_K", LLAMA_FTYPE_MOSTLY_Q4_K_M, "alias for Q4_K_M", },
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{ "Q4_K_R4", LLAMA_FTYPE_MOSTLY_Q4_K_R4, "Q4_K_S repacked", },
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@ -426,6 +426,7 @@ extern "C" {
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GGML_TYPE_IQ2_K_R4 = 337,
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GGML_TYPE_IQ3_K_R4 = 338,
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GGML_TYPE_IQ4_K_R4 = 339,
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GGML_TYPE_IQ5_K_R4 = 340,
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GGML_TYPE_Q8_K_R8 = 399,
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GGML_TYPE_COUNT,
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};
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@ -502,6 +503,7 @@ extern "C" {
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GGML_FTYPE_MOSTLY_IQ2_K_R4 = 330, // except 1d tensors
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GGML_FTYPE_MOSTLY_IQ3_K_R4 = 331, // except 1d tensors
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GGML_FTYPE_MOSTLY_IQ4_K_R4 = 332, // except 1d tensors
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GGML_FTYPE_MOSTLY_IQ5_K_R4 = 333, // except 1d tensors
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GGML_FTYPE_MOSTLY_Q8_K_R8 = 399, // except 1d tensors
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};
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@ -584,6 +584,16 @@ typedef struct {
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} block_iq5_k;
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static_assert(sizeof(block_iq5_k) == sizeof(ggml_half) + sizeof(uint16_t) + QK_K/2 + QK_K/8 + 3*QK_K/64, "wrong iq5_k block size/padding");
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typedef struct {
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ggml_half d[4];
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uint8_t extra[8];
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uint8_t scales_h[QK_K/16];
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uint8_t scales_l[QK_K/8 ];
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uint8_t qs[QK_K*2];
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uint8_t qh[QK_K/2];
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} block_iq5_k_r4;
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static_assert(sizeof(block_iq5_k_r4) == 4*sizeof(block_iq5_k), "wrong iq5_k_r4 block size/padding");
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typedef struct {
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ggml_half d;
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uint16_t extra;
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@ -15210,6 +15210,7 @@ bool ggml_validate_row_data(enum ggml_type type, const void * data, size_t nbyte
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case GGML_TYPE_IQ2_K_R4: break;
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case GGML_TYPE_IQ3_K_R4: break;
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case GGML_TYPE_IQ4_K_R4: break;
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case GGML_TYPE_IQ5_K_R4: break;
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case GGML_TYPE_Q8_K_R8: break;
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case GGML_TYPE_BF16_R16: break;
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case GGML_TYPE_Q4_0_4_4:
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@ -1399,6 +1399,19 @@ 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_IQ5_K_R4] = {
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.type_name = "iq5_k_r4",
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.blck_size = QK_K,
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.type_size = sizeof(block_iq5_k),
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.is_quantized = true,
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.to_float = (ggml_to_float_t) dequantize_row_iq5_k_r4,
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.from_float = quantize_row_iq5_k_r4,
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.from_float_ref = (ggml_from_float_t)quantize_row_iq5_k_r4_ref,
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.vec_dot = vec_dot_iq5_k_r4_q8_k,
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.vec_dot_type = GGML_TYPE_Q8_K,
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.nrows = 1,
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.row_meta_size = 0,
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},
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[GGML_TYPE_IQ6_K] = {
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.type_name = "iq6_k",
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.blck_size = QK_K,
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@ -4193,6 +4206,7 @@ enum ggml_type ggml_ftype_to_ggml_type(enum ggml_ftype ftype) {
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case GGML_FTYPE_MOSTLY_IQ3_K_R4: wtype = GGML_TYPE_IQ3_K_R4; break;
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case GGML_FTYPE_MOSTLY_IQ4_K_R4: wtype = GGML_TYPE_IQ4_K_R4; break;
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case GGML_FTYPE_MOSTLY_IQ5_K: wtype = GGML_TYPE_IQ5_K; break;
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case GGML_FTYPE_MOSTLY_IQ5_K_R4: wtype = GGML_TYPE_IQ5_K_R4; break;
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case GGML_FTYPE_MOSTLY_IQ6_K: wtype = GGML_TYPE_IQ6_K; break;
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case GGML_FTYPE_MOSTLY_IQ3_S: wtype = GGML_TYPE_IQ3_S; break;
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case GGML_FTYPE_MOSTLY_IQ2_S: wtype = GGML_TYPE_IQ2_S; break;
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@ -10732,6 +10746,7 @@ static void ggml_compute_forward_add(
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case GGML_TYPE_IQ3_K_R4:
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case GGML_TYPE_IQ4_K_R4:
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case GGML_TYPE_IQ5_K:
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case GGML_TYPE_IQ5_K_R4:
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case GGML_TYPE_IQ6_K:
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case GGML_TYPE_IQ3_S:
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case GGML_TYPE_IQ2_S:
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@ -11190,6 +11205,7 @@ static void ggml_compute_forward_add1(
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case GGML_TYPE_IQ3_K_R4:
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case GGML_TYPE_IQ4_K_R4:
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case GGML_TYPE_IQ5_K:
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case GGML_TYPE_IQ5_K_R4:
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case GGML_TYPE_IQ6_K:
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case GGML_TYPE_IQ3_S:
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case GGML_TYPE_IQ2_S:
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@ -11345,6 +11361,7 @@ static void ggml_compute_forward_acc(
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case GGML_TYPE_IQ3_K_R4:
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case GGML_TYPE_IQ4_K_R4:
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case GGML_TYPE_IQ5_K:
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case GGML_TYPE_IQ5_K_R4:
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case GGML_TYPE_IQ6_K:
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case GGML_TYPE_IQ3_S:
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case GGML_TYPE_IQ2_S:
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@ -14546,6 +14563,7 @@ static void ggml_compute_forward_out_prod(
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case GGML_TYPE_IQ3_K_R4:
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case GGML_TYPE_IQ4_K_R4:
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case GGML_TYPE_IQ5_K:
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case GGML_TYPE_IQ5_K_R4:
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case GGML_TYPE_IQ6_K:
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case GGML_TYPE_IQ3_S:
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case GGML_TYPE_IQ2_S:
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@ -14941,6 +14959,7 @@ static void ggml_compute_forward_set(
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case GGML_TYPE_IQ3_K_R4:
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case GGML_TYPE_IQ4_K_R4:
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case GGML_TYPE_IQ5_K:
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case GGML_TYPE_IQ5_K_R4:
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case GGML_TYPE_IQ6_K:
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case GGML_TYPE_IQ3_S:
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case GGML_TYPE_IQ2_S:
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@ -15230,6 +15249,7 @@ static void ggml_compute_forward_get_rows(
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case GGML_TYPE_IQ3_K_R4:
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case GGML_TYPE_IQ4_K_R4:
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case GGML_TYPE_IQ5_K:
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case GGML_TYPE_IQ5_K_R4:
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case GGML_TYPE_IQ6_K:
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case GGML_TYPE_IQ3_S:
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case GGML_TYPE_IQ2_S:
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@ -15848,6 +15868,7 @@ static void ggml_compute_forward_clamp(
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case GGML_TYPE_IQ3_K_R4:
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case GGML_TYPE_IQ4_K_R4:
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case GGML_TYPE_IQ5_K:
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case GGML_TYPE_IQ5_K_R4:
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case GGML_TYPE_IQ6_K:
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case GGML_TYPE_IQ3_S:
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case GGML_TYPE_IQ2_S:
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@ -22694,6 +22715,7 @@ size_t ggml_quantize_chunk(
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case GGML_TYPE_IQ3_K_R4:result = quantize_iq3_k_r4(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
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case GGML_TYPE_IQ4_K_R4:result = quantize_iq4_k_r4(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
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case GGML_TYPE_IQ5_K: result = quantize_iq5_k (src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
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case GGML_TYPE_IQ5_K_R4:result = quantize_iq5_k_r4(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
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case GGML_TYPE_IQ6_K: result = quantize_iq6_k (src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
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case GGML_TYPE_Q4_0_4_4: result = quantize_q4_0_4x4(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
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case GGML_TYPE_Q4_0_4_8: result = quantize_q4_0_4x8(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
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@ -185,6 +185,7 @@ struct MulMat {
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case GGML_TYPE_IQ2_K_R4:
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case GGML_TYPE_IQ3_K_R4:
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case GGML_TYPE_IQ4_K_R4:
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case GGML_TYPE_IQ5_K_R4:
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case GGML_TYPE_IQ2_BN_R4: return 4;
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case GGML_TYPE_Q8_K_R8: return 8;
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case GGML_TYPE_BF16_R16: return 16;
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@ -3959,7 +3960,8 @@ static void mul_mat_bf16_r16_bf16(int n, const void * vx, size_t bx, const DataI
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#endif
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template <int nrc_y>
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IQK_ALWAYS_INLINE void iq234_k_accum_mins(int ibl, __m256i i8scales1, __m256i i8scales2, const Q8<nrc_y, block_q8_K>& q8, __m256i shuff,
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//IQK_ALWAYS_INLINE void iq234_k_accum_mins(int ibl, __m256i i8scales1, __m256i i8scales2, const Q8<nrc_y, block_q8_K>& q8, __m256i shuff,
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inline void iq234_k_accum_mins(int ibl, __m256i i8scales1, __m256i i8scales2, const Q8<nrc_y, block_q8_K>& q8, __m256i shuff,
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__m256i * isum, int16_t min) {
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auto t1 = _mm256_shuffle_epi8(_mm256_cvtepi8_epi16(_mm256_extracti128_si256(i8scales1, 0)), shuff); // blocks 0, 1, 2, 3 for each row
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auto t2 = _mm256_shuffle_epi8(_mm256_cvtepi8_epi16(_mm256_extracti128_si256(i8scales1, 1)), shuff); // blocks 4, 5, 6, 7 for each row
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@ -4007,6 +4009,46 @@ IQK_ALWAYS_INLINE void iq234_k_accum_mins(int ibl, __m256i i8scales1, __m256i i8
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}
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}
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template <int nrc_y>
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inline void iq2345_k_accum_mins(int ibl, __m256i i8scales1, __m256i i8scales2, const Q8<nrc_y, block_q8_K>& q8, __m256i shuff,
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__m256i extra, __m256i * isum, int8_t min, int8_t delta) {
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auto mask = _mm256_set_epi64x(0x0808080808080808, 0x0404040404040404, 0x0202020202020202, 0x0101010101010101);
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auto vdelta = _mm256_set1_epi8(delta);
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auto vmin = _mm256_set1_epi8(min);
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auto min1 = _mm256_add_epi8(vmin, _mm256_and_si256(vdelta, _mm256_cmpeq_epi8(_mm256_and_si256(extra, mask), mask)));
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auto min2 = _mm256_add_epi8(vmin, _mm256_and_si256(vdelta, _mm256_cmpeq_epi8(_mm256_and_si256(_mm256_srli_epi16(extra, 4), mask), mask)));
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auto t1 = _mm256_shuffle_epi8(_mm256_cvtepi8_epi16(_mm256_extracti128_si256(i8scales1, 0)), shuff); // blocks 0, 1, 2, 3 for each row
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auto t2 = _mm256_shuffle_epi8(_mm256_cvtepi8_epi16(_mm256_extracti128_si256(i8scales1, 1)), shuff); // blocks 4, 5, 6, 7 for each row
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auto t3 = _mm256_shuffle_epi8(_mm256_cvtepi8_epi16(_mm256_extracti128_si256(i8scales2, 0)), shuff); // blocks 8, 9, 10, 11 for each row
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auto t4 = _mm256_shuffle_epi8(_mm256_cvtepi8_epi16(_mm256_extracti128_si256(i8scales2, 1)), shuff); // blocks 12, 13, 14, 15 for each row
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auto m1 = _mm256_shuffle_epi8(_mm256_cvtepi8_epi16(_mm256_extracti128_si256(min1, 0)), shuff); // blocks 0, 1, 2, 3 for each row
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auto m2 = _mm256_shuffle_epi8(_mm256_cvtepi8_epi16(_mm256_extracti128_si256(min1, 1)), shuff); // blocks 4, 5, 6, 7 for each row
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auto m3 = _mm256_shuffle_epi8(_mm256_cvtepi8_epi16(_mm256_extracti128_si256(min2, 0)), shuff); // blocks 8, 9, 10, 11 for each row
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auto m4 = _mm256_shuffle_epi8(_mm256_cvtepi8_epi16(_mm256_extracti128_si256(min2, 1)), shuff); // blocks 12, 13, 14, 15 for each row
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auto s1 = _mm256_mullo_epi16(MM256_SET_M128I(_mm256_extracti128_si256(m3, 0), _mm256_extracti128_si256(m1, 0)),
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MM256_SET_M128I(_mm256_extracti128_si256(t3, 0), _mm256_extracti128_si256(t1, 0))); // blocks 0, 1, 8, 9
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auto s2 = _mm256_mullo_epi16(MM256_SET_M128I(_mm256_extracti128_si256(m3, 1), _mm256_extracti128_si256(m1, 1)),
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MM256_SET_M128I(_mm256_extracti128_si256(t3, 1), _mm256_extracti128_si256(t1, 1))); // blocks 2, 3, 10, 11
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auto s3 = _mm256_mullo_epi16(MM256_SET_M128I(_mm256_extracti128_si256(m4, 0), _mm256_extracti128_si256(m2, 0)),
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MM256_SET_M128I(_mm256_extracti128_si256(t4, 0), _mm256_extracti128_si256(t2, 0))); // blocks 4, 5, 12, 13
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auto s4 = _mm256_mullo_epi16(MM256_SET_M128I(_mm256_extracti128_si256(m4, 1), _mm256_extracti128_si256(m2, 1)),
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MM256_SET_M128I(_mm256_extracti128_si256(t4, 1), _mm256_extracti128_si256(t2, 1))); // blocks 6, 7, 14, 15
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for (int iy = 0; iy < nrc_y; ++iy) {
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auto bsums = q8.load_bsums(iy, ibl);
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#ifdef HAVE_FANCY_SIMD
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isum[iy] = _mm256_dpwssd_epi32(isum[iy], s1, _mm256_shuffle_epi32(bsums, 0x00));
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isum[iy] = _mm256_dpwssd_epi32(isum[iy], s2, _mm256_shuffle_epi32(bsums, 0x55));
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isum[iy] = _mm256_dpwssd_epi32(isum[iy], s3, _mm256_shuffle_epi32(bsums, 0xaa));
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isum[iy] = _mm256_dpwssd_epi32(isum[iy], s4, _mm256_shuffle_epi32(bsums, 0xff));
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#else
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isum[iy] = _mm256_add_epi32(isum[iy], _mm256_madd_epi16(s1, _mm256_shuffle_epi32(bsums, 0x00)));
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isum[iy] = _mm256_add_epi32(isum[iy], _mm256_madd_epi16(s2, _mm256_shuffle_epi32(bsums, 0x55)));
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isum[iy] = _mm256_add_epi32(isum[iy], _mm256_madd_epi16(s3, _mm256_shuffle_epi32(bsums, 0xaa)));
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isum[iy] = _mm256_add_epi32(isum[iy], _mm256_madd_epi16(s4, _mm256_shuffle_epi32(bsums, 0xff)));
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#endif
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}
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}
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template <int nrc_y>
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static void mul_mat_iq2_k_r4_q8_k(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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@ -4268,6 +4310,159 @@ static void mul_mat_iq4_k_r4_q8_k(int n, const void * vx, size_t bx, const DataI
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}
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}
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template <int nrc_y>
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static void mul_mat_iq5_k_r4_q8_k(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 m4 = _mm256_set1_epi8(0xf);
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auto m30 = _mm256_set1_epi8(0x30);
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auto m32 = _mm256_set1_epi8(32);
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auto ms = _mm256_set1_epi8(2);
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auto shift_shuffle = _mm256_set_epi64x(0x0707070706060606, 0x0505050504040404, 0x0303030302020202, 0x0101010100000000);
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__m256i values[2];
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{
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auto val1 = _mm_loadu_si128((const __m128i *)iq5nl_values+0);
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auto val2 = _mm_loadu_si128((const __m128i *)iq5nl_values+1);
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values[0] = MM256_SET_M128I(val1, val1);
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values[1] = MM256_SET_M128I(val2, val2);
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#ifdef HAVE_FANCY_SIMD
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values[0] = _mm256_sub_epi8(values[0], _mm256_set1_epi8(-128));
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values[1] = _mm256_sub_epi8(values[1], _mm256_set1_epi8(-128));
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#endif
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}
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#ifdef HAVE_FANCY_SIMD
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static const uint8_t k_shuff[32] = {0, 1, 8, 9, 2, 3, 10, 11, 4, 5, 12, 13, 6, 7, 14, 15, 0, 1, 8, 9, 2, 3, 10, 11, 4, 5, 12, 13, 6, 7, 14, 15};
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auto shuff = _mm256_loadu_si256((const __m256i *)k_shuff);
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#else
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auto s_shuffle = _mm256_set_epi64x(0x0f0e0f0e0d0c0d0c, 0x0b0a0b0a09080908, 0x0706070605040504, 0x0302030201000100);
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#endif
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int nbl = n / QK_K;
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__m256 acc[nrc_y] = {};
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__m256i qx[4];
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uint64_t stored_scales[8];
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for (int ix = 0; ix < nrc_x; ix += 4) {
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const block_iq5_k_r4 * iq5 = (const block_iq5_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 = _mm_cvtph_ps(_mm_loadl_epi64((const __m128i *)iq5[ibl].d));
|
||||
auto d4 = _mm256_set_m128(dl, dl);
|
||||
auto extra = _mm256_set1_epi64x(*(const uint64_t *)iq5[ibl].extra);
|
||||
auto slbits = _mm256_loadu_si256((const __m256i *)iq5[ibl].scales_l);
|
||||
auto sl1 = _mm256_and_si256(slbits, m4);
|
||||
auto sl2 = _mm256_and_si256(_mm256_srli_epi16(slbits, 4), m4);
|
||||
auto shbits = _mm_loadu_si128((const __m128i*)iq5[ibl].scales_h);
|
||||
auto sh = MM256_SET_M128I(_mm_srli_epi16(shbits, 2), shbits);
|
||||
auto i8scales1 = _mm256_sub_epi8(_mm256_or_si256(sl1, _mm256_and_si256(m30, _mm256_slli_epi16(sh, 4))), m32);
|
||||
auto i8scales2 = _mm256_sub_epi8(_mm256_or_si256(sl2, _mm256_and_si256(m30, sh)), m32);
|
||||
_mm256_storeu_si256((__m256i *)stored_scales+0, i8scales1);
|
||||
_mm256_storeu_si256((__m256i *)stored_scales+1, i8scales2);
|
||||
__m256i isum[nrc_y] = {};
|
||||
#ifdef HAVE_FANCY_SIMD
|
||||
if constexpr (nrc_y == 1) {
|
||||
iq234_k_accum_mins(ibl, i8scales1, i8scales2, q8, shuff, isum, -128);
|
||||
} else {
|
||||
iq2345_k_accum_mins(ibl, i8scales1, i8scales2, q8, shuff, extra, isum, -128, 2);
|
||||
}
|
||||
#endif
|
||||
for (int ib = 0; ib < QK_K/32; ++ib) {
|
||||
#ifdef HAVE_FANCY_SIMD
|
||||
auto scales = _mm256_cvtepi8_epi32(_mm_loadl_epi64((const __m128i *)(stored_scales + ib)));
|
||||
#else
|
||||
auto scales = _mm256_shuffle_epi8(_mm256_cvtepi8_epi16(_mm_set1_epi64x(stored_scales[ib])), s_shuffle);
|
||||
#endif
|
||||
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 hbits = _mm_loadu_si128((const __m128i *)iq5[ibl].qh+ib);
|
||||
auto hb = MM256_SET_M128I(_mm_srli_epi16(hbits, 2), hbits);
|
||||
qx[0] = _mm256_and_si256(lbits1, m4);
|
||||
qx[1] = _mm256_and_si256(lbits2, m4);
|
||||
qx[2] = _mm256_and_si256(_mm256_srli_epi16(lbits1, 4), m4);
|
||||
qx[3] = _mm256_and_si256(_mm256_srli_epi16(lbits2, 4), m4);
|
||||
|
||||
#ifdef HAVE_FANCY_SIMD
|
||||
auto q5vl = _mm256_shuffle_epi8(values[0], qx[0]);
|
||||
auto q5vh = _mm256_shuffle_epi8(values[1], qx[0]);
|
||||
qx[0] = _mm256_mask_blend_epi8(_mm256_cmpeq_epi8_mask(_mm256_and_si256(hb, _mm256_set1_epi8(0x01)), _mm256_set1_epi8(0x01)), q5vl, q5vh);
|
||||
|
||||
q5vl = _mm256_shuffle_epi8(values[0], qx[1]);
|
||||
q5vh = _mm256_shuffle_epi8(values[1], qx[1]);
|
||||
qx[1] = _mm256_mask_blend_epi8(_mm256_cmpeq_epi8_mask(_mm256_and_si256(hb, _mm256_set1_epi8(0x10)), _mm256_set1_epi8(0x10)), q5vl, q5vh);
|
||||
|
||||
q5vl = _mm256_shuffle_epi8(values[0], qx[2]);
|
||||
q5vh = _mm256_shuffle_epi8(values[1], qx[2]);
|
||||
qx[2] = _mm256_mask_blend_epi8(_mm256_cmpeq_epi8_mask(_mm256_and_si256(hb, _mm256_set1_epi8(0x02)), _mm256_set1_epi8(0x02)), q5vl, q5vh);
|
||||
|
||||
q5vl = _mm256_shuffle_epi8(values[0], qx[3]);
|
||||
q5vh = _mm256_shuffle_epi8(values[1], qx[3]);
|
||||
qx[3] = _mm256_mask_blend_epi8(_mm256_cmpeq_epi8_mask(_mm256_and_si256(hb, _mm256_set1_epi8(0x20)), _mm256_set1_epi8(0x20)), q5vl, q5vh);
|
||||
|
||||
if constexpr (nrc_y == 1) {
|
||||
auto shift = _mm256_and_si256(ms, _mm256_slli_epi16(extra, 1)); extra = _mm256_srli_epi16(extra, 1);
|
||||
shift = _mm256_shuffle_epi8(shift, shift_shuffle);
|
||||
qx[0] = _mm256_add_epi8(qx[0], shift);
|
||||
qx[1] = _mm256_add_epi8(qx[1], shift);
|
||||
qx[2] = _mm256_add_epi8(qx[2], shift);
|
||||
qx[3] = _mm256_add_epi8(qx[3], shift);
|
||||
}
|
||||
#else
|
||||
|
||||
auto q5vl = _mm256_shuffle_epi8(values[0], qx[0]);
|
||||
auto q5vh = _mm256_shuffle_epi8(values[1], qx[0]);
|
||||
qx[0] = _mm256_blendv_epi8(q5vl, q5vh, _mm256_cmpeq_epi8(_mm256_and_si256(hb, _mm256_set1_epi8(0x01)), _mm256_set1_epi8(0x01)));
|
||||
|
||||
q5vl = _mm256_shuffle_epi8(values[0], qx[1]);
|
||||
q5vh = _mm256_shuffle_epi8(values[1], qx[1]);
|
||||
qx[1] = _mm256_blendv_epi8(q5vl, q5vh, _mm256_cmpeq_epi8(_mm256_and_si256(hb, _mm256_set1_epi8(0x10)), _mm256_set1_epi8(0x10)));
|
||||
|
||||
q5vl = _mm256_shuffle_epi8(values[0], qx[2]);
|
||||
q5vh = _mm256_shuffle_epi8(values[1], qx[2]);
|
||||
qx[2] = _mm256_blendv_epi8(q5vl, q5vh, _mm256_cmpeq_epi8(_mm256_and_si256(hb, _mm256_set1_epi8(0x02)), _mm256_set1_epi8(0x02)));
|
||||
|
||||
q5vl = _mm256_shuffle_epi8(values[0], qx[3]);
|
||||
q5vh = _mm256_shuffle_epi8(values[1], qx[3]);
|
||||
qx[3] = _mm256_blendv_epi8(q5vl, q5vh, _mm256_cmpeq_epi8(_mm256_and_si256(hb, _mm256_set1_epi8(0x20)), _mm256_set1_epi8(0x20)));
|
||||
|
||||
auto shift = _mm256_and_si256(ms, _mm256_slli_epi16(extra, 1)); extra = _mm256_srli_epi16(extra, 1);
|
||||
shift = _mm256_shuffle_epi8(shift, shift_shuffle);
|
||||
qx[0] = _mm256_add_epi8(qx[0], shift);
|
||||
qx[1] = _mm256_add_epi8(qx[1], shift);
|
||||
qx[2] = _mm256_add_epi8(qx[2], shift);
|
||||
qx[3] = _mm256_add_epi8(qx[3], shift);
|
||||
auto s1 = _mm256_sign_epi8(qx[0], qx[0]);
|
||||
auto s2 = _mm256_sign_epi8(qx[1], qx[1]);
|
||||
auto s3 = _mm256_sign_epi8(qx[2], qx[2]);
|
||||
auto s4 = _mm256_sign_epi8(qx[3], qx[3]);
|
||||
#endif
|
||||
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));
|
||||
isum[iy] = _mm256_add_epi32(isum[iy], _mm256_mullo_epi32(scales, sumi));
|
||||
#else
|
||||
auto sumi1 = _mm256_maddubs_epi16(s1, _mm256_sign_epi8(_mm256_shuffle_epi32(y, 0x00), qx[0]));
|
||||
auto sumi2 = _mm256_maddubs_epi16(s2, _mm256_sign_epi8(_mm256_shuffle_epi32(y, 0x55), qx[1]));
|
||||
auto sumi3 = _mm256_maddubs_epi16(s3, _mm256_sign_epi8(_mm256_shuffle_epi32(y, 0xaa), qx[2]));
|
||||
auto sumi4 = _mm256_maddubs_epi16(s4, _mm256_sign_epi8(_mm256_shuffle_epi32(y, 0xff), qx[3]));
|
||||
isum[iy] = _mm256_add_epi32(isum[iy], _mm256_add_epi32(_mm256_madd_epi16(scales, sumi1), _mm256_madd_epi16(scales, sumi2)));
|
||||
isum[iy] = _mm256_add_epi32(isum[iy], _mm256_add_epi32(_mm256_madd_epi16(scales, sumi3), _mm256_madd_epi16(scales, sumi4)));
|
||||
#endif
|
||||
}
|
||||
}
|
||||
for (int iy = 0; iy < nrc_y; ++iy) {
|
||||
acc[iy] = _mm256_fmadd_ps(_mm256_mul_ps(d4, _mm256_set1_ps(q8.scale(iy, ibl))), _mm256_cvtepi32_ps(isum[iy]), 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);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
template <typename Bits>
|
||||
inline void multiply_add_1(int j, const Bits& bits, const __m256i * scales, const __m256i * q8, __m256i * sumi) {
|
||||
if (j == 0) {
|
||||
|
|
@ -6371,6 +6566,18 @@ bool MulMat::prepare(int typeA, int typeB, int ne00, MulMat& mm, int Ny) {
|
|||
mm.funcs[7] = mul_mat_iq4_k_r4_q8_k<8>;
|
||||
expected_typeB = GGML_TYPE_Q8_K;
|
||||
break;
|
||||
case GGML_TYPE_IQ5_K_R4:
|
||||
assert (ne00 % QK_K == 0);
|
||||
mm.funcs[0] = mul_mat_iq5_k_r4_q8_k<1>;
|
||||
mm.funcs[1] = mul_mat_iq5_k_r4_q8_k<2>;
|
||||
mm.funcs[2] = mul_mat_iq5_k_r4_q8_k<3>;
|
||||
mm.funcs[3] = mul_mat_iq5_k_r4_q8_k<4>;
|
||||
mm.funcs[4] = mul_mat_iq5_k_r4_q8_k<5>;
|
||||
mm.funcs[5] = mul_mat_iq5_k_r4_q8_k<6>;
|
||||
mm.funcs[6] = mul_mat_iq5_k_r4_q8_k<7>;
|
||||
mm.funcs[7] = mul_mat_iq5_k_r4_q8_k<8>;
|
||||
expected_typeB = GGML_TYPE_Q8_K;
|
||||
break;
|
||||
case GGML_TYPE_IQ2_K_R4:
|
||||
assert (ne00 % QK_K == 0);
|
||||
mm.funcs[0] = mul_mat_iq2_k_r4_q8_k<1>;
|
||||
|
|
@ -9071,18 +9278,23 @@ void mul_mat_iq4_xs_r4_q8_k(int n, const void * vx, size_t bx, const DataInfo& i
|
|||
}
|
||||
}
|
||||
|
||||
template <int nrc_y, bool is_iq2k>
|
||||
template <int nrc_y, int k_shift>
|
||||
inline void iq3_4_add_shift(int ibl, const Q8<nrc_y, block_q8_K>& q8, const int8x16x4_t& i8scales, uint8x16_t extra,
|
||||
int32x4_t * isum) {
|
||||
auto ms = is_iq2k ? vdupq_n_s8(5) : vdupq_n_s8(4);
|
||||
auto ms = vdupq_n_s8(k_shift);
|
||||
int8x16_t s8_1, s8_2;
|
||||
if constexpr (is_iq2k) {
|
||||
if constexpr (k_shift == 5) {
|
||||
auto m1 = vdupq_n_u8(1);
|
||||
s8_1 = vmulq_s8(i8scales.val[0], vandq_s8(ms, vceqq_u8(vandq_u8(extra, m1), m1))); extra = vshrq_n_u8(extra, 2);
|
||||
s8_2 = vmulq_s8(i8scales.val[1], vandq_s8(ms, vceqq_u8(vandq_u8(extra, m1), m1))); extra = vshrq_n_u8(extra, 2);
|
||||
} else {
|
||||
s8_1 = vmulq_s8(i8scales.val[0], vandq_u8(ms, vshlq_n_u8(extra, 2)));
|
||||
s8_2 = vmulq_s8(i8scales.val[1], vandq_u8(ms, extra));
|
||||
if constexpr (k_shift == 4) {
|
||||
s8_1 = vmulq_s8(i8scales.val[0], vandq_u8(ms, vshlq_n_u8(extra, 2)));
|
||||
s8_2 = vmulq_s8(i8scales.val[1], vandq_u8(ms, extra));
|
||||
} else {
|
||||
s8_1 = vmulq_s8(i8scales.val[0], vandq_u8(ms, vshlq_n_u8(extra, 1)));
|
||||
s8_2 = vmulq_s8(i8scales.val[1], vandq_u8(ms, vshrq_n_u8(extra, 1)));
|
||||
}
|
||||
}
|
||||
auto s16_1 = vmovl_s8(vget_low_s8 (s8_1));
|
||||
auto s16_2 = vmovl_s8(vget_high_s8(s8_1));
|
||||
|
|
@ -9100,13 +9312,18 @@ inline void iq3_4_add_shift(int ibl, const Q8<nrc_y, block_q8_K>& q8, const int8
|
|||
isum[iy] = vmlal_lane_s16(isum[iy], vget_low_s16 (s16_4), b8, 2);
|
||||
isum[iy] = vmlal_lane_s16(isum[iy], vget_high_s16(s16_4), b8, 3);
|
||||
}
|
||||
if constexpr (is_iq2k) {
|
||||
if constexpr (k_shift == 5) {
|
||||
auto m1 = vdupq_n_u8(1);
|
||||
s8_1 = vmulq_s8(i8scales.val[2], vandq_s8(ms, vceqq_u8(vandq_u8(extra, m1), m1))); extra = vshrq_n_u8(extra, 2);
|
||||
s8_2 = vmulq_s8(i8scales.val[3], vandq_s8(ms, vceqq_u8(vandq_u8(extra, m1), m1))); extra = vshrq_n_u8(extra, 2);
|
||||
} else {
|
||||
s8_1 = vmulq_s8(i8scales.val[2], vandq_u8(ms, vshrq_n_u8(extra, 2)));
|
||||
s8_2 = vmulq_s8(i8scales.val[3], vandq_u8(ms, vshrq_n_u8(extra, 4)));
|
||||
if constexpr (k_shift == 4) {
|
||||
s8_1 = vmulq_s8(i8scales.val[2], vandq_u8(ms, vshrq_n_u8(extra, 2)));
|
||||
s8_2 = vmulq_s8(i8scales.val[3], vandq_u8(ms, vshrq_n_u8(extra, 4)));
|
||||
} else {
|
||||
s8_1 = vmulq_s8(i8scales.val[2], vandq_u8(ms, vshrq_n_u8(extra, 3)));
|
||||
s8_2 = vmulq_s8(i8scales.val[3], vandq_u8(ms, vshrq_n_u8(extra, 5)));
|
||||
}
|
||||
}
|
||||
s16_1 = vmovl_s8(vget_low_s8 (s8_1));
|
||||
s16_2 = vmovl_s8(vget_high_s8(s8_1));
|
||||
|
|
@ -9162,7 +9379,7 @@ void mul_mat_iq2_k_r4_q8_k(int n, const void * vx, size_t bx, const DataInfo& in
|
|||
i8scales.val[3] = vaddq_s8(vshrq_n_u8(sl.val[1], 4), vdupq_n_s8(-8));
|
||||
int32x4_t isum[nrc_y] = {};
|
||||
if constexpr (nrc_y == 1) {
|
||||
iq3_4_add_shift<nrc_y, true>(ibl, q8, i8scales, extra, isum);
|
||||
iq3_4_add_shift<nrc_y, 5>(ibl, q8, i8scales, extra, isum);
|
||||
}
|
||||
for (int is = 0; is < 2; ++is) {
|
||||
i16scales.val[0] = vmovl_s8(vget_low_s8 (i8scales.val[2*is+0]));
|
||||
|
|
@ -9275,7 +9492,7 @@ void mul_mat_iq3_k_r4_q8_k(int n, const void * vx, size_t bx, const DataInfo& in
|
|||
i8scales.val[3] = vmulq_s8(i8scales.val[3], vorrq_u8(vceqq_u8(vandq_u8(sh, smask.val[1]), smask.val[1]), vdupq_n_u8(1)));
|
||||
int32x4_t isum[nrc_y] = {};
|
||||
if constexpr (nrc_y == 1) {
|
||||
iq3_4_add_shift<nrc_y, false>(ibl, q8, i8scales, extra, isum);
|
||||
iq3_4_add_shift<nrc_y, 4>(ibl, q8, i8scales, extra, isum);
|
||||
}
|
||||
for (int is = 0; is < 2; ++is) {
|
||||
i16scales.val[0] = vmovl_s8(vget_low_s8 (i8scales.val[2*is+0]));
|
||||
|
|
@ -9382,7 +9599,7 @@ void mul_mat_iq4_k_r4_q8_k(int n, const void * vx, size_t bx, const DataInfo& in
|
|||
i8scales.val[3] = vaddq_s8(vorrq_u8(vshrq_n_u8(sl.val[1], 4), vandq_u8(vshrq_n_u8(sh, 2), m3)), m32);
|
||||
int32x4_t isum[nrc_y] = {};
|
||||
if constexpr (nrc_y == 1) {
|
||||
iq3_4_add_shift<nrc_y, false>(ibl, q8, i8scales, extra, isum);
|
||||
iq3_4_add_shift<nrc_y, 4>(ibl, q8, i8scales, extra, isum);
|
||||
}
|
||||
for (int is = 0; is < 2; ++is) {
|
||||
i16scales.val[0] = vmovl_s8(vget_low_s8 (i8scales.val[2*is+0]));
|
||||
|
|
@ -9443,6 +9660,114 @@ void mul_mat_iq4_k_r4_q8_k(int n, const void * vx, size_t bx, const DataInfo& in
|
|||
}
|
||||
}
|
||||
|
||||
template <int nrc_y>
|
||||
void mul_mat_iq5_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 m4 = vdupq_n_u8(0xf);
|
||||
auto m3 = vdupq_n_u8(0x30);
|
||||
auto ms = vdupq_n_u8(2);
|
||||
auto m32 = vdupq_n_s8(-32);
|
||||
auto m10 = vdupq_n_u8(0x10);
|
||||
uint8x16x2_t shift_shuffle = {
|
||||
vreinterpretq_u8_u64(uint64x2_t{0x0101010100000000, 0x0303030302020202}),
|
||||
vreinterpretq_u8_u64(uint64x2_t{0x0505050504040404, 0x0707070706060606})
|
||||
};
|
||||
auto values = vld1q_s8_x2(iq5nl_values);
|
||||
int nbl = n / QK_K;
|
||||
int8x16_t qx[4];
|
||||
int8x16x4_t i8scales;
|
||||
int16x8x4_t i16scales;
|
||||
float32x4_t acc[nrc_y] = {};
|
||||
for (int ix = 0; ix < nrc_x; ix += 4) {
|
||||
const block_iq5_k_r4 * iq5 = (const block_iq5_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 extra8 = vld1_u8(iq5[ibl].extra);
|
||||
uint8x16_t extra;
|
||||
if constexpr (nrc_y == 1) {
|
||||
extra = vcombine_u8(extra8, vshr_n_u8(extra8,1));
|
||||
} else {
|
||||
extra = vcombine_u8(extra8, extra8);
|
||||
}
|
||||
auto sl = vld1q_u8_x2(iq5[ibl].scales_l);
|
||||
auto sh = vld1q_u8(iq5[ibl].scales_h);
|
||||
i8scales.val[0] = vaddq_s8(vorrq_u8(vandq_u8(sl.val[0], m4), vandq_u8(vshlq_n_u8(sh, 4), m3)), m32);
|
||||
i8scales.val[1] = vaddq_s8(vorrq_u8(vandq_u8(sl.val[1], m4), vandq_u8(vshlq_n_u8(sh, 2), m3)), m32);
|
||||
i8scales.val[2] = vaddq_s8(vorrq_u8(vshrq_n_u8(sl.val[0], 4), vandq_u8(sh, m3)), m32);
|
||||
i8scales.val[3] = vaddq_s8(vorrq_u8(vshrq_n_u8(sl.val[1], 4), vandq_u8(vshrq_n_u8(sh, 2), m3)), m32);
|
||||
int32x4_t isum[nrc_y] = {};
|
||||
if constexpr (nrc_y == 1) {
|
||||
iq3_4_add_shift<nrc_y, 2>(ibl, q8, i8scales, extra, isum);
|
||||
}
|
||||
for (int is = 0; is < 2; ++is) {
|
||||
i16scales.val[0] = vmovl_s8(vget_low_s8 (i8scales.val[2*is+0]));
|
||||
i16scales.val[1] = vmovl_s8(vget_high_s8(i8scales.val[2*is+0]));
|
||||
i16scales.val[2] = vmovl_s8(vget_low_s8 (i8scales.val[2*is+1]));
|
||||
i16scales.val[3] = vmovl_s8(vget_high_s8(i8scales.val[2*is+1]));
|
||||
for (int ib = 0; ib < 4; ++ib) {
|
||||
auto lbits = vld1q_u8_x4(iq5[ibl].qs + 256*is + 64*ib);
|
||||
auto hbits = vld1q_u8(iq5[ibl].qh + 64*is + 16*ib);
|
||||
qx[0] = vorrq_u8(vandq_u8(lbits.val[0], m4), vandq_u8(m10, vshlq_n_u8(hbits, 4))); // aligns with 1st half of qx[0] in AVX2
|
||||
qx[1] = vorrq_u8(vandq_u8(lbits.val[2], m4), vandq_u8(m10, hbits)); // aligns with 1st half of qx[1] in AVX2
|
||||
qx[2] = vorrq_u8(vshrq_n_u8(lbits.val[0], 4), vandq_u8(m10, vshlq_n_u8(hbits, 3))); // aligns with 1st half of qx[2] in AVX2
|
||||
qx[3] = vorrq_u8(vshrq_n_u8(lbits.val[2], 4), vandq_u8(m10, vshrq_n_u8(hbits, 1))); // aligns with 1st half of qx[3] in AVX2
|
||||
uint8x16_t shifts;
|
||||
if constexpr (nrc_y == 1) {
|
||||
qx[0] = vqtbl2q_s8(values, qx[0]); // 0...3 from the 4 rows
|
||||
qx[1] = vqtbl2q_s8(values, qx[1]); // 4...7
|
||||
qx[2] = vqtbl2q_s8(values, qx[2]); // 8..11
|
||||
qx[3] = vqtbl2q_s8(values, qx[3]); // 12..15
|
||||
} else {
|
||||
shifts = vandq_u8(ms, vshlq_n_u8(extra, 1));
|
||||
auto shift = vqtbl1q_u8(shifts, shift_shuffle.val[0]);
|
||||
extra = vshrq_n_u8(extra, 1);
|
||||
qx[0] = vaddq_s8(shift, vqtbl2q_s8(values, qx[0])); // 0...3 from the 4 rows
|
||||
qx[1] = vaddq_s8(shift, vqtbl2q_s8(values, qx[1])); // 4...7
|
||||
qx[2] = vaddq_s8(shift, vqtbl2q_s8(values, qx[2])); // 8..11
|
||||
qx[3] = vaddq_s8(shift, vqtbl2q_s8(values, qx[3])); // 12..15
|
||||
}
|
||||
auto scales = vmovl_s16(vget_low_s16 (i16scales.val[ib]));
|
||||
for (int iy = 0; iy < nrc_y; ++iy) {
|
||||
auto y = vld1q_s8(q8.y[iy][ibl].qs+128*is+32*ib);
|
||||
auto sumi = interleaved_dotq(qx, y);
|
||||
isum[iy] = vmlaq_s32(isum[iy], scales, sumi);
|
||||
}
|
||||
qx[0] = vorrq_u8(vandq_u8(lbits.val[1], m4), vandq_u8(m10, vshlq_n_u8(hbits, 2))); // aligns with 2nd half of qx[0] in AVX2
|
||||
qx[1] = vorrq_u8(vandq_u8(lbits.val[3], m4), vandq_u8(m10, vshrq_n_u8(hbits, 2))); // aligns with 2nd half of qx[1] in AVX2
|
||||
qx[2] = vorrq_u8(vshrq_n_u8(lbits.val[1], 4), vandq_u8(m10, vshlq_n_u8(hbits, 1))); // aligns with 2nd half of qx[2] in AVX2
|
||||
qx[3] = vorrq_u8(vshrq_n_u8(lbits.val[3], 4), vandq_u8(m10, vshrq_n_u8(hbits, 3))); // aligns with 2nd half of qx[3] in AVX2
|
||||
if constexpr (nrc_y == 1) {
|
||||
qx[0] = vqtbl2q_s8(values, qx[0]); // 0...3 from the 4 rows
|
||||
qx[1] = vqtbl2q_s8(values, qx[1]); // 4...7
|
||||
qx[2] = vqtbl2q_s8(values, qx[2]); // 8..11
|
||||
qx[3] = vqtbl2q_s8(values, qx[3]); // 12..15
|
||||
} else {
|
||||
auto shift = vqtbl1q_u8(shifts, shift_shuffle.val[1]);
|
||||
qx[0] = vaddq_s8(shift, vqtbl2q_s8(values, qx[0])); // 0...3 from the 4 rows
|
||||
qx[1] = vaddq_s8(shift, vqtbl2q_s8(values, qx[1])); // 4...7
|
||||
qx[2] = vaddq_s8(shift, vqtbl2q_s8(values, qx[2])); // 8..11
|
||||
qx[3] = vaddq_s8(shift, vqtbl2q_s8(values, qx[3])); // 12..15
|
||||
}
|
||||
scales = vmovl_s16(vget_high_s16(i16scales.val[ib]));
|
||||
for (int iy = 0; iy < nrc_y; ++iy) {
|
||||
auto y = vld1q_s8(q8.y[iy][ibl].qs+128*is+32*ib+16);
|
||||
auto sumi = interleaved_dotq(qx, y);
|
||||
isum[iy] = vmlaq_s32(isum[iy], scales, sumi);
|
||||
}
|
||||
}
|
||||
}
|
||||
for (int iy = 0; iy < nrc_y; ++iy) {
|
||||
acc[iy] = vfmaq_f32(acc[iy], vmulq_f32(d4, vdupq_n_f32(q8.scale(iy, ibl))), vcvtq_f32_s32(isum[iy]));
|
||||
}
|
||||
}
|
||||
for (int iy = 0; iy < nrc_y; ++iy) {
|
||||
info.store(ix, iy, acc[iy]);
|
||||
acc[iy] = vdupq_n_f32(0.f);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
IQK_ALWAYS_INLINE void prepare_q4_k_quants(const uint8x16_t& m4, const uint8x16x4_t& bits, int8x16_t * qx) {
|
||||
qx[0] = vandq_u8(bits.val[0], m4); // 0...3 from the 4 rows
|
||||
qx[1] = vandq_u8(bits.val[1], m4); // 16..19
|
||||
|
|
@ -10282,6 +10607,10 @@ bool MulMat::prepare(int typeA, int typeB, int ne00, MulMat& m, int /*Ny*/) {
|
|||
SET_MUL_MAT_FUNCTIONS(m, mul_mat_iq4_k_r4_q8_k);
|
||||
expected_Btype = GGML_TYPE_Q8_K;
|
||||
break;
|
||||
case GGML_TYPE_IQ5_K_R4:
|
||||
SET_MUL_MAT_FUNCTIONS(m, mul_mat_iq5_k_r4_q8_k);
|
||||
expected_Btype = GGML_TYPE_Q8_K;
|
||||
break;
|
||||
case GGML_TYPE_Q4_0_R4:
|
||||
SET_MUL_MAT_FUNCTIONS_T(m, mul_mat_qx_r4_q8_0, Q4_0_R4_Dequantizer);
|
||||
expected_Btype = GGML_TYPE_Q8_0;
|
||||
|
|
|
|||
|
|
@ -4684,6 +4684,142 @@ void vec_dot_iq4_k_r4_q8_k(int n, float * s, size_t bs, const void * vx, size_t
|
|||
GGML_UNUSED(by);
|
||||
}
|
||||
|
||||
//
|
||||
// ========================================= iq5_k_r4
|
||||
//
|
||||
|
||||
void quantize_row_iq5_k_r4_ref(const float * x, block_iq5_k_r4 * y, int64_t k) {
|
||||
quantize_iq5_k_r4(x, (void *)y, 4, k/4, nullptr);
|
||||
}
|
||||
|
||||
void quantize_row_iq5_k_r4(const float * x, void * y, int64_t k) {
|
||||
quantize_iq5_k_r4(x, y, 4, k/4, nullptr);
|
||||
}
|
||||
|
||||
namespace {
|
||||
inline void convert_iq5_k(const block_iq5_k& x, uint8_t * L) {
|
||||
const uint8_t * qs = x.qs;
|
||||
const uint8_t * qh = x.qh;
|
||||
int shift = 0;
|
||||
for (int ib64 = 0; ib64 < QK_K/64; ++ib64) {
|
||||
for (int j = 0; j < 16; ++j) {
|
||||
L[j+ 0] = (qs[j+ 0] & 0xf) | (((qh[j+ 0] >> shift) & 1) << 4);
|
||||
L[j+16] = (qs[j+16] & 0xf) | (((qh[j+16] >> shift) & 1) << 4);
|
||||
L[j+32] = (qs[j+ 0] >> 4) | (((qh[j+ 0] >> shift) & 2) << 3);
|
||||
L[j+48] = (qs[j+16] >> 4) | (((qh[j+16] >> shift) & 2) << 3);
|
||||
}
|
||||
L += 64;
|
||||
qs += 32;
|
||||
shift += 2;
|
||||
if (shift == 8) { qh += 32; shift = 0; }
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
static void repack_iq5_k(int nrows, int n_per_row, const block_iq5_k * x, block_iq5_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_iq5_k * x4[4];
|
||||
uint8_t L[QK_K];
|
||||
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].extra, 0, 8);
|
||||
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] = x4[k][ibl].d;
|
||||
auto extra = x4[k][ibl].extra;
|
||||
convert_iq5_k(x4[k][ibl], L);
|
||||
for (int ib = 0; ib < QK_K/32; ++ib) {
|
||||
if (extra & 1) y[ibl].extra[k+0] |= (1 << ib);
|
||||
if (extra & 2) y[ibl].extra[k+4] |= (1 << ib);
|
||||
extra >>= 2;
|
||||
uint8_t sl1 = x4[k][ibl].scales_l[ib] & 0xf;
|
||||
uint8_t sl2 = x4[k][ibl].scales_l[ib] >> 4;
|
||||
uint8_t sh = x4[k][ibl].scales_h[ib/2] >> 4*(ib%2);
|
||||
uint8_t sh1 = (sh >> 0) & 3;
|
||||
uint8_t sh2 = (sh >> 2) & 3;
|
||||
int i = 8*ib + k;
|
||||
y[ibl].scales_l[i%32] |= (sl1 << 4*(i/32));
|
||||
y[ibl].scales_h[i%16] |= (sh1 << 2*(i/16));
|
||||
i += 4;
|
||||
y[ibl].scales_l[i%32] |= (sl2 << 4*(i/32));
|
||||
y[ibl].scales_h[i%16] |= (sh2 << 2*(i/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); // 0....3 + 8...11 from each row
|
||||
y[ibl].qs[64*ib+4*k+i+16] = (L[32*ib+i+16] & 0xf) | ((L[32*ib+i+24] & 0xf) << 4); // 16...19 + 24...27 from each row
|
||||
y[ibl].qs[64*ib+4*k+i+32] = (L[32*ib+i+ 4] & 0xf) | ((L[32*ib+i+12] & 0xf) << 4); // 4....7 + 12...15 from each row
|
||||
y[ibl].qs[64*ib+4*k+i+48] = (L[32*ib+i+20] & 0xf) | ((L[32*ib+i+28] & 0xf) << 4); // 20...23 + 28...31 from each row
|
||||
y[ibl].qh[16*ib+4*k+i ] = ((L[32*ib+i+ 0] >> 4) << 0) | ((L[32*ib+i+ 8] >> 4) << 1) | ((L[32*ib+i+16] >> 4) << 2) | ((L[32*ib+i+24] >> 4) << 3)
|
||||
| ((L[32*ib+i+ 4] >> 4) << 4) | ((L[32*ib+i+12] >> 4) << 5) | ((L[32*ib+i+20] >> 4) << 6) | ((L[32*ib+i+28] >> 4) << 7);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
x += 4*nblock;
|
||||
y += nblock;
|
||||
}
|
||||
}
|
||||
|
||||
size_t quantize_iq5_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_IQ5_K, n_per_row);
|
||||
std::vector<char> qtmp(4*row_size);
|
||||
for (int row = 0; row < nrows; row += 4) {
|
||||
quantize_iq5_k(src, (void *)qtmp.data(), 4, n_per_row, imatrix);
|
||||
repack_iq5_k(4, n_per_row, (const block_iq5_k *)qtmp.data(), (block_iq5_k_r4 *)qcur);
|
||||
qcur += 4*row_size;
|
||||
src += 4*n_per_row;
|
||||
}
|
||||
return nrows*row_size;
|
||||
}
|
||||
|
||||
void dequantize_row_iq5_k_r4(const block_iq5_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]);
|
||||
for (int ib = 0; ib < QK_K/32; ++ib) {
|
||||
int is = 8*ib + k;
|
||||
float dl1 = d * ((((x[ibl].scales_l[is%32] >> 4*(is/32)) & 0xf) | (((x[ibl].scales_h[is%16] >> 2*(is/16)) & 3) << 4)) - 32);
|
||||
is += 4;
|
||||
float dl2 = d * ((((x[ibl].scales_l[is%32] >> 4*(is/32)) & 0xf) | (((x[ibl].scales_h[is%16] >> 2*(is/16)) & 3) << 4)) - 32);
|
||||
auto values1 = iq5nl_values + (x[ibl].extra[k+0] & (1 << ib) ? 32 : 0);
|
||||
auto values2 = iq5nl_values + (x[ibl].extra[k+4] & (1 << ib) ? 32 : 0);
|
||||
for (int i = 0; i < 4; ++i) {
|
||||
y4[k][QK_K*ibl+32*ib+i+ 0] = dl1 * values1[(x[ibl].qs[64*ib+4*k+i+ 0] & 0xf) | (((x[ibl].qh[16*ib+4*k+i] >> 0) & 1) << 4)];
|
||||
y4[k][QK_K*ibl+32*ib+i+ 8] = dl1 * values1[(x[ibl].qs[64*ib+4*k+i+ 0] >> 4) | (((x[ibl].qh[16*ib+4*k+i] >> 1) & 1) << 4)];
|
||||
y4[k][QK_K*ibl+32*ib+i+16] = dl2 * values2[(x[ibl].qs[64*ib+4*k+i+16] & 0xf) | (((x[ibl].qh[16*ib+4*k+i] >> 2) & 1) << 4)];
|
||||
y4[k][QK_K*ibl+32*ib+i+24] = dl2 * values2[(x[ibl].qs[64*ib+4*k+i+16] >> 4) | (((x[ibl].qh[16*ib+4*k+i] >> 3) & 1) << 4)];
|
||||
y4[k][QK_K*ibl+32*ib+i+ 4] = dl1 * values1[(x[ibl].qs[64*ib+4*k+i+32] & 0xf) | (((x[ibl].qh[16*ib+4*k+i] >> 4) & 1) << 4)];
|
||||
y4[k][QK_K*ibl+32*ib+i+12] = dl1 * values1[(x[ibl].qs[64*ib+4*k+i+32] >> 4) | (((x[ibl].qh[16*ib+4*k+i] >> 5) & 1) << 4)];
|
||||
y4[k][QK_K*ibl+32*ib+i+20] = dl2 * values2[(x[ibl].qs[64*ib+4*k+i+48] & 0xf) | (((x[ibl].qh[16*ib+4*k+i] >> 6) & 1) << 4)];
|
||||
y4[k][QK_K*ibl+32*ib+i+28] = dl2 * values2[(x[ibl].qs[64*ib+4*k+i+48] >> 4) | (((x[ibl].qh[16*ib+4*k+i] >> 7) & 1) << 4)];
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
void vec_dot_iq5_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_IQ5_K_R4, vx, 0, GGML_TYPE_Q8_K, 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);
|
||||
}
|
||||
|
||||
//
|
||||
// ========================================= q8_k_r8
|
||||
//
|
||||
|
|
|
|||
|
|
@ -139,6 +139,12 @@ size_t quantize_q6_k_r4(const float * GGML_RESTRICT src, void * GGML_RESTRICT ds
|
|||
void dequantize_row_q6_k_r4(const block_q6_k_r4 * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
|
||||
void vec_dot_q6_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_iq5_k_r4_ref(const float * GGML_RESTRICT x, block_iq5_k_r4 * GGML_RESTRICT y, int64_t k);
|
||||
void quantize_row_iq5_k_r4(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
|
||||
size_t quantize_iq5_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_iq5_k_r4(const block_iq5_k_r4 * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
|
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void vec_dot_iq5_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);
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||||
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void quantize_row_iq4_k_r4_ref(const float * GGML_RESTRICT x, block_iq4_k_r4 * GGML_RESTRICT y, int64_t k);
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||||
void quantize_row_iq4_k_r4(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
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||||
size_t quantize_iq4_k_r4(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
|
||||
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|
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|||
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|
@ -196,6 +196,7 @@ extern "C" {
|
|||
LLAMA_FTYPE_MOSTLY_IQ2_K_R4 = 338, // except 1d tensors
|
||||
LLAMA_FTYPE_MOSTLY_IQ3_K_R4 = 339, // except 1d tensors
|
||||
LLAMA_FTYPE_MOSTLY_IQ4_K_R4 = 340, // except 1d tensors
|
||||
LLAMA_FTYPE_MOSTLY_IQ5_K_R4 = 341, // except 1d tensors
|
||||
LLAMA_FTYPE_MOSTLY_Q8_K_R8 = 399, // except 1d tensors
|
||||
|
||||
LLAMA_FTYPE_GUESSED = 1024, // not specified in the model file
|
||||
|
|
|
|||
|
|
@ -3876,6 +3876,7 @@ struct llama_model_loader {
|
|||
case GGML_TYPE_IQ4_K: ftype = LLAMA_FTYPE_MOSTLY_IQ4_K; break;
|
||||
case GGML_TYPE_IQ4_K_R4:ftype = LLAMA_FTYPE_MOSTLY_IQ4_K_R4;break;
|
||||
case GGML_TYPE_IQ5_K: ftype = LLAMA_FTYPE_MOSTLY_IQ5_K; break;
|
||||
case GGML_TYPE_IQ5_K_R4:ftype = LLAMA_FTYPE_MOSTLY_IQ5_K_R4;break;
|
||||
case GGML_TYPE_IQ6_K: ftype = LLAMA_FTYPE_MOSTLY_IQ6_K; break;
|
||||
case GGML_TYPE_IQ3_S: ftype = LLAMA_FTYPE_MOSTLY_IQ3_S; break;
|
||||
case GGML_TYPE_Q4_0_4_4: ftype = LLAMA_FTYPE_MOSTLY_Q4_0_4_4; break;
|
||||
|
|
@ -4601,6 +4602,7 @@ static std::string llama_model_ftype_name(llama_ftype ftype) {
|
|||
case LLAMA_FTYPE_MOSTLY_IQ4_K: return "IQ4_K - 4.5 bpw";
|
||||
case LLAMA_FTYPE_MOSTLY_IQ4_K_R4: return "IQ4_K_R4 - 4.5 bpw";
|
||||
case LLAMA_FTYPE_MOSTLY_IQ5_K: return "IQ5_K - 5.5 bpw";
|
||||
case LLAMA_FTYPE_MOSTLY_IQ5_K_R4: return "IQ5_K_R4 - 5.5 bpw";
|
||||
case LLAMA_FTYPE_MOSTLY_IQ6_K: return "IQ6_K - 6.6 bpw";
|
||||
case LLAMA_FTYPE_MOSTLY_IQ1_BN: return "IQ1_BN - 1.625 bpw Bitnet";
|
||||
case LLAMA_FTYPE_MOSTLY_IQ2_BN: return "IQ2_BN - 2.00 bpw Bitnet";
|
||||
|
|
@ -15854,6 +15856,9 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
|
|||
else if (new_type == GGML_TYPE_IQ4_K_R4) {
|
||||
new_type = GGML_TYPE_IQ4_K;
|
||||
}
|
||||
else if (new_type == GGML_TYPE_IQ5_K_R4) {
|
||||
new_type = GGML_TYPE_IQ5_K;
|
||||
}
|
||||
else if (new_type == GGML_TYPE_Q4_0_R4) {
|
||||
new_type = GGML_TYPE_Q4_0;
|
||||
}
|
||||
|
|
@ -16150,7 +16155,7 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
|
|||
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 || new_type == GGML_TYPE_Q3_K_R4 || new_type == GGML_TYPE_Q2_K_R4 ||
|
||||
new_type == GGML_TYPE_IQ4_K_R4|| new_type == GGML_TYPE_Q8_K_R8 || new_type == GGML_TYPE_IQ3_K_R4||
|
||||
new_type == GGML_TYPE_IQ2_K_R4) {
|
||||
new_type == GGML_TYPE_IQ2_K_R4|| new_type == GGML_TYPE_IQ5_K_R4) {
|
||||
int nx = tensor->ne[0];
|
||||
int ny = tensor->ne[1];
|
||||
if (nx % QK_K != 0) {
|
||||
|
|
@ -16193,6 +16198,7 @@ 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_IQ5_K_R4:
|
||||
case GGML_TYPE_Q5_K_R4:
|
||||
case GGML_TYPE_Q5_K: new_type = GGML_TYPE_Q6_0; break;
|
||||
case GGML_TYPE_IQ6_K:
|
||||
|
|
@ -16325,6 +16331,7 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
|
|||
case LLAMA_FTYPE_MOSTLY_IQ4_K: default_type = GGML_TYPE_IQ4_K; break;
|
||||
case LLAMA_FTYPE_MOSTLY_IQ4_K_R4:default_type = GGML_TYPE_IQ4_K_R4;break;
|
||||
case LLAMA_FTYPE_MOSTLY_IQ5_K: default_type = GGML_TYPE_IQ5_K; break;
|
||||
case LLAMA_FTYPE_MOSTLY_IQ5_K_R4:default_type = GGML_TYPE_IQ5_K_R4;break;
|
||||
case LLAMA_FTYPE_MOSTLY_IQ6_K: default_type = GGML_TYPE_IQ6_K; break;
|
||||
case LLAMA_FTYPE_MOSTLY_IQ3_S: default_type = GGML_TYPE_IQ3_S; break;
|
||||
case LLAMA_FTYPE_MOSTLY_IQ3_M: default_type = GGML_TYPE_IQ3_S; break;
|
||||
|
|
@ -16741,6 +16748,10 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
|
|||
if (tensor->ne[1] % 4 != 0) new_type = GGML_TYPE_IQ4_K;
|
||||
else chunk_size_multiplier = 4;
|
||||
}
|
||||
else if (new_type == GGML_TYPE_IQ5_K_R4) {
|
||||
if (tensor->ne[1] % 4 != 0) new_type = GGML_TYPE_IQ5_K;
|
||||
else chunk_size_multiplier = 4;
|
||||
}
|
||||
else if (new_type == GGML_TYPE_BF16_R16) {
|
||||
if (tensor->ne[1] % 16 != 0) new_type = GGML_TYPE_BF16;
|
||||
else chunk_size_multiplier = 16;
|
||||
|
|
|
|||
Loading…
Reference in New Issue