mirror of
https://github.com/ikawrakow/ik_llama.cpp.git
synced 2026-06-28 04:30:15 -05:00
Rename iq4_nl_x4 to iq4_nl_r4 (#126)
Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
This commit is contained in:
Kawrakow
GitHub
parent
cc9acdbcff
commit
daf5f52022
@ -41,7 +41,7 @@ static const std::vector<struct quant_option> QUANT_OPTIONS = {
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{ "Q3_K_M", LLAMA_FTYPE_MOSTLY_Q3_K_M, " 3.07G, +0.2496 ppl @ LLaMA-v1-7B", },
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{ "Q3_K_L", LLAMA_FTYPE_MOSTLY_Q3_K_L, " 3.35G, +0.1764 ppl @ LLaMA-v1-7B", },
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{ "IQ4_NL", LLAMA_FTYPE_MOSTLY_IQ4_NL, " 4.50 bpw non-linear quantization", },
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{ "IQ4_NL_X4",LLAMA_FTYPE_MOSTLY_IQ4_NL_X4," 4.50 bpw non-linear quantization", },
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{ "IQ4_NL_R4",LLAMA_FTYPE_MOSTLY_IQ4_NL_R4," 4.50 bpw non-linear quantization", },
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{ "IQ4_XS_R4",LLAMA_FTYPE_MOSTLY_IQ4_XS_R4," 4.25 bpw non-linear quantization", },
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{ "Q4_0_R4", LLAMA_FTYPE_MOSTLY_Q4_0_R4, " 4.50 bpw quantization", },
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{ "Q5_0_R4", LLAMA_FTYPE_MOSTLY_Q5_0_R4, " 5.50 bpw quantization", },
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@ -411,7 +411,7 @@ extern "C" {
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GGML_TYPE_Q4_0_R4 = 202,
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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_IQ4_NL_X4 = 220, // TODO: rename GGML_TYPE_IQ4_NL_X4 to GGML_TYPE_IQ4_NL_R4
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GGML_TYPE_IQ4_NL_R4 = 220,
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GGML_TYPE_IQ4_XS_R4 = 223,
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GGML_TYPE_Q6_0_R4 = 233,
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GGML_TYPE_IQ2_BN_R4 = 335,
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@ -477,7 +477,7 @@ extern "C" {
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GGML_FTYPE_MOSTLY_Q4_0_R4 = 202, // except 1d tensors
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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_IQ4_NL_X4 = 219, // 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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GGML_FTYPE_MOSTLY_Q6_0_R4 = 227, // except 1d tensors
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GGML_FTYPE_MOSTLY_IQ2_BN_R4 = 329, // except 1d tensors
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@ -436,8 +436,8 @@ static_assert(sizeof(block_iq4_nl) == sizeof(ggml_half) + QK4_NL/2, "wrong iq4_n
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typedef struct {
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ggml_half d[4];
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uint8_t qs[2*QK4_NL];
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} block_iq4_nl_x4;
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static_assert(sizeof(block_iq4_nl_x4) == 4*sizeof(ggml_half) + 2*QK4_NL, "wrong iq4_nl_x4 block size/padding");
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} block_iq4_nl_r4;
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static_assert(sizeof(block_iq4_nl_r4) == 4*sizeof(ggml_half) + 2*QK4_NL, "wrong iq4_nl_x4 block size/padding");
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typedef struct {
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ggml_half d;
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@ -15196,7 +15196,7 @@ bool ggml_validate_row_data(enum ggml_type type, const void * data, size_t nbyte
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case GGML_TYPE_IQ6_K: break;
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case GGML_TYPE_IQ4_KS: break;
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case GGML_TYPE_IQ4_KSS: break;
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case GGML_TYPE_IQ4_NL_X4: break;
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case GGML_TYPE_IQ4_NL_R4: break;
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case GGML_TYPE_IQ4_XS_R4: break;
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case GGML_TYPE_Q4_0_R4: break;
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case GGML_TYPE_Q5_0_R4: break;
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@ -1266,15 +1266,15 @@ 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_IQ4_NL_X4] = {
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.type_name = "iq4_nl_x4",
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[GGML_TYPE_IQ4_NL_R4] = {
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.type_name = "iq4_nl_r4",
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.blck_size = QK4_NL,
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.type_size = sizeof(block_iq4_nl),
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.is_quantized = true,
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.to_float = (ggml_to_float_t) dequantize_row_iq4_nl_x4,
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.from_float = quantize_row_iq4_nl_x4,
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.from_float_ref = (ggml_from_float_t)quantize_row_iq4_nl_x4_ref,
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.vec_dot = vec_dot_iq4_nl_x4_q8_0,
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.to_float = (ggml_to_float_t) dequantize_row_iq4_nl_r4,
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.from_float = quantize_row_iq4_nl_r4,
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.from_float_ref = (ggml_from_float_t)quantize_row_iq4_nl_r4_ref,
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.vec_dot = vec_dot_iq4_nl_r4_q8_0,
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#if GGML_USE_IQK_MULMAT && defined __AVX2__
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.vec_dot_type = GGML_TYPE_Q8_1,
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#else
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@ -4023,7 +4023,7 @@ enum ggml_type ggml_ftype_to_ggml_type(enum ggml_ftype ftype) {
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case GGML_FTYPE_MOSTLY_IQ2_BN: wtype = GGML_TYPE_IQ2_BN; break;
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case GGML_FTYPE_MOSTLY_IQ2_BN_R4: wtype = GGML_TYPE_IQ2_BN_R4;break;
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case GGML_FTYPE_MOSTLY_IQ4_NL: wtype = GGML_TYPE_IQ4_NL; break;
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case GGML_FTYPE_MOSTLY_IQ4_NL_X4: wtype = GGML_TYPE_IQ4_NL_X4;break;
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case GGML_FTYPE_MOSTLY_IQ4_NL_R4: wtype = GGML_TYPE_IQ4_NL_R4;break;
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case GGML_FTYPE_MOSTLY_IQ4_XS_R4: wtype = GGML_TYPE_IQ4_XS_R4;break;
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case GGML_FTYPE_MOSTLY_Q4_0_R4: wtype = GGML_TYPE_Q4_0_R4; break;
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case GGML_FTYPE_MOSTLY_Q5_0_R4: wtype = GGML_TYPE_Q5_0_R4; break;
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@ -10553,7 +10553,7 @@ static void ggml_compute_forward_add(
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case GGML_TYPE_IQ2_BN:
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case GGML_TYPE_IQ2_BN_R4:
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case GGML_TYPE_IQ4_NL:
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case GGML_TYPE_IQ4_NL_X4:
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case GGML_TYPE_IQ4_NL_R4:
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case GGML_TYPE_IQ4_XS_R4:
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case GGML_TYPE_Q4_0_R4:
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case GGML_TYPE_Q5_0_R4:
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@ -11002,7 +11002,7 @@ static void ggml_compute_forward_add1(
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case GGML_TYPE_IQ2_BN:
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case GGML_TYPE_IQ2_BN_R4:
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case GGML_TYPE_IQ4_NL:
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case GGML_TYPE_IQ4_NL_X4:
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case GGML_TYPE_IQ4_NL_R4:
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case GGML_TYPE_IQ4_XS_R4:
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case GGML_TYPE_Q4_0_R4:
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case GGML_TYPE_Q5_0_R4:
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@ -11148,7 +11148,7 @@ static void ggml_compute_forward_acc(
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case GGML_TYPE_IQ2_BN:
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case GGML_TYPE_IQ2_BN_R4:
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case GGML_TYPE_IQ4_NL:
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case GGML_TYPE_IQ4_NL_X4:
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case GGML_TYPE_IQ4_NL_R4:
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case GGML_TYPE_IQ4_XS_R4:
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case GGML_TYPE_Q4_0_R4:
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case GGML_TYPE_Q5_0_R4:
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@ -14340,7 +14340,7 @@ static void ggml_compute_forward_out_prod(
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case GGML_TYPE_IQ2_BN:
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case GGML_TYPE_IQ2_BN_R4:
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case GGML_TYPE_IQ4_NL:
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case GGML_TYPE_IQ4_NL_X4:
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case GGML_TYPE_IQ4_NL_R4:
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case GGML_TYPE_IQ4_XS_R4:
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case GGML_TYPE_Q4_0_R4:
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case GGML_TYPE_Q5_0_R4:
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@ -14726,7 +14726,7 @@ static void ggml_compute_forward_set(
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case GGML_TYPE_IQ2_BN:
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case GGML_TYPE_IQ2_BN_R4:
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case GGML_TYPE_IQ4_NL:
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case GGML_TYPE_IQ4_NL_X4:
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case GGML_TYPE_IQ4_NL_R4:
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case GGML_TYPE_IQ4_XS_R4:
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case GGML_TYPE_Q4_0_R4:
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case GGML_TYPE_Q5_0_R4:
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@ -15006,7 +15006,7 @@ static void ggml_compute_forward_get_rows(
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case GGML_TYPE_IQ2_BN:
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case GGML_TYPE_IQ2_BN_R4:
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case GGML_TYPE_IQ4_NL:
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case GGML_TYPE_IQ4_NL_X4:
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case GGML_TYPE_IQ4_NL_R4:
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case GGML_TYPE_IQ4_XS_R4:
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case GGML_TYPE_Q4_0_R4:
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case GGML_TYPE_Q5_0_R4:
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@ -15613,7 +15613,7 @@ static void ggml_compute_forward_clamp(
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case GGML_TYPE_IQ2_BN:
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case GGML_TYPE_IQ2_BN_R4:
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case GGML_TYPE_IQ4_NL:
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case GGML_TYPE_IQ4_NL_X4:
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case GGML_TYPE_IQ4_NL_R4:
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case GGML_TYPE_IQ4_XS_R4:
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case GGML_TYPE_Q4_0_R4:
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case GGML_TYPE_Q5_0_R4:
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@ -22449,7 +22449,7 @@ size_t ggml_quantize_chunk(
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case GGML_TYPE_IQ2_BN: result = quantize_iq2_bn (src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
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case GGML_TYPE_IQ2_BN_R4:result = quantize_iq2_bn_r4(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
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case GGML_TYPE_IQ4_NL: result = quantize_iq4_nl (src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
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case GGML_TYPE_IQ4_NL_X4: result = quantize_iq4_nl_x4(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
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case GGML_TYPE_IQ4_NL_R4: result = quantize_iq4_nl_r4(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
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case GGML_TYPE_IQ4_XS_R4: result = quantize_iq4_xs_r4(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
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case GGML_TYPE_Q4_0_R4: result = quantize_q4_0_r4(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
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case GGML_TYPE_Q5_0_R4: result = quantize_q5_0_r4(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
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@ -167,7 +167,7 @@ struct MulMat {
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case GGML_TYPE_Q5_0_R4:
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case GGML_TYPE_Q6_0_R4:
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case GGML_TYPE_Q8_0_R4:
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case GGML_TYPE_IQ4_NL_X4:
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case GGML_TYPE_IQ4_NL_R4:
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case GGML_TYPE_IQ2_BN_R4: return 4;
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default: return 1;
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}
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@ -2340,7 +2340,7 @@ static void mul_mat_iq2_bn_r4_q8_k16(int n, const void * vx, size_t bx, const Da
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#ifdef HAVE_FANCY_SIMD
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template <int nrc_y>
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static void mul_mat_iq4_nl_x4_q8_1(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) {
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static void mul_mat_iq4_nl_r4_q8_1(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) {
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GGML_ASSERT(nrc_x%8 == 0);
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Q8<nrc_y, block_q8_1_x4> q8(info);
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auto m4 = _mm512_set1_epi8(0xf);
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@ -2350,8 +2350,8 @@ static void mul_mat_iq4_nl_x4_q8_1(int n, const void * vx, size_t bx, const Data
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__m512 acc[2*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_iq4_nl_x4 * iq4l = (const block_iq4_nl_x4 *)((const char *)vx + (ix+0)*bx);
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const block_iq4_nl_x4 * iq4h = (const block_iq4_nl_x4 *)((const char *)vx + (ix+4)*bx);
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const block_iq4_nl_r4 * iq4l = (const block_iq4_nl_r4 *)((const char *)vx + (ix+0)*bx);
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const block_iq4_nl_r4 * iq4h = (const block_iq4_nl_r4 *)((const char *)vx + (ix+4)*bx);
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for (int ib4 = 0; ib4 < nb/4; ++ib4) {
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for (int k = 0; k < 4; ++k) {
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auto scales128 = _mm_cvtph_ps(_mm_loadl_epi64((const __m128i *)iq4l[4*ib4+k].d));
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@ -2394,7 +2394,7 @@ static void mul_mat_iq4_nl_x4_q8_1(int n, const void * vx, size_t bx, const Data
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}
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#else
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template <int nrc_y>
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static void mul_mat_iq4_nl_x4_q8_1(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) {
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static void mul_mat_iq4_nl_r4_q8_1(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_1_x4> q8(info);
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auto m4 = _mm256_set1_epi8(0xf);
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@ -2405,7 +2405,7 @@ static void mul_mat_iq4_nl_x4_q8_1(int n, const void * vx, size_t bx, const Data
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__m256 acc[nrc_y] = {};
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//__m256 acc[2*nrc_y] = {};
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for (int ix = 0; ix < nrc_x; ix += 4) {
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const block_iq4_nl_x4 * iq4 = (const block_iq4_nl_x4 *)((const char *)vx + ix*bx);
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const block_iq4_nl_r4 * iq4 = (const block_iq4_nl_r4 *)((const char *)vx + ix*bx);
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for (int ib4 = 0; ib4 < nb/4; ++ib4) {
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for (int k = 0; k < 4; ++k) {
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auto scales128 = _mm_cvtph_ps(_mm_loadl_epi64((const __m128i *)iq4[4*ib4+k].d));
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@ -2455,8 +2455,8 @@ static void mul_mat_q4_0_r4_q8_1(int n, const void * vx, size_t bx, const DataIn
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__m512 acc[2*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_iq4_nl_x4 * iq4l = (const block_iq4_nl_x4 *)((const char *)vx + (ix+0)*bx);
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const block_iq4_nl_x4 * iq4h = (const block_iq4_nl_x4 *)((const char *)vx + (ix+4)*bx);
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const block_iq4_nl_r4 * iq4l = (const block_iq4_nl_r4 *)((const char *)vx + (ix+0)*bx);
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const block_iq4_nl_r4 * iq4h = (const block_iq4_nl_r4 *)((const char *)vx + (ix+4)*bx);
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for (int ib4 = 0; ib4 < nb/4; ++ib4) {
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for (int k = 0; k < 4; ++k) {
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auto scales128 = _mm_cvtph_ps(_mm_loadl_epi64((const __m128i *)iq4l[4*ib4+k].d));
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@ -2508,7 +2508,7 @@ static void mul_mat_q4_0_r4_q8_1(int n, const void * vx, size_t bx, const DataIn
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GGML_ASSERT(nb%4 == 0);
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__m256 acc[nrc_y] = {};
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for (int ix = 0; ix < nrc_x; ix += 4) {
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const block_iq4_nl_x4 * iq4 = (const block_iq4_nl_x4 *)((const char *)vx + ix*bx);
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const block_iq4_nl_r4 * iq4 = (const block_iq4_nl_r4 *)((const char *)vx + ix*bx);
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for (int ib4 = 0; ib4 < nb/4; ++ib4) {
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for (int k = 0; k < 4; ++k) {
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auto scales128 = _mm_cvtph_ps(_mm_loadl_epi64((const __m128i *)iq4[4*ib4+k].d));
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@ -5052,16 +5052,16 @@ bool MulMat::prepare(int typeA, int typeB, int ne00, MulMat& mm, int Ny) {
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MulMat::set_functions<IQ4_NL_Unpacker>(mm);
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expected_typeB = GGML_TYPE_Q8_1;
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break;
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case GGML_TYPE_IQ4_NL_X4:
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case GGML_TYPE_IQ4_NL_R4:
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assert (ne00 % QK4_NL == 0);
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mm.funcs[0] = mul_mat_iq4_nl_x4_q8_1<1>;
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mm.funcs[1] = mul_mat_iq4_nl_x4_q8_1<2>;
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mm.funcs[2] = mul_mat_iq4_nl_x4_q8_1<3>;
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mm.funcs[3] = mul_mat_iq4_nl_x4_q8_1<4>;
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mm.funcs[4] = mul_mat_iq4_nl_x4_q8_1<5>;
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mm.funcs[5] = mul_mat_iq4_nl_x4_q8_1<6>;
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mm.funcs[6] = mul_mat_iq4_nl_x4_q8_1<7>;
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mm.funcs[7] = mul_mat_iq4_nl_x4_q8_1<8>;
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mm.funcs[0] = mul_mat_iq4_nl_r4_q8_1<1>;
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mm.funcs[1] = mul_mat_iq4_nl_r4_q8_1<2>;
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mm.funcs[2] = mul_mat_iq4_nl_r4_q8_1<3>;
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mm.funcs[3] = mul_mat_iq4_nl_r4_q8_1<4>;
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mm.funcs[4] = mul_mat_iq4_nl_r4_q8_1<5>;
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mm.funcs[5] = mul_mat_iq4_nl_r4_q8_1<6>;
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mm.funcs[6] = mul_mat_iq4_nl_r4_q8_1<7>;
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mm.funcs[7] = mul_mat_iq4_nl_r4_q8_1<8>;
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expected_typeB = GGML_TYPE_Q8_1;
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break;
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case GGML_TYPE_IQ4_XS_R4:
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@ -7734,7 +7734,7 @@ void mul_mat_iq4_xs_r4_q8_k(int n, const void * vx, size_t bx, const DataInfo& i
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}
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}
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void mul_mat_iq4_nl_x4_q8_0_1(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) {
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void mul_mat_iq4_nl_r4_q8_0_1(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<1, block_q8_0_x4> q8(info);
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auto m4 = vdupq_n_u8(0xf);
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@ -7744,7 +7744,7 @@ void mul_mat_iq4_nl_x4_q8_0_1(int n, const void * vx, size_t bx, const DataInfo&
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int8x16_t qx[8];
|
||||
for (int ix = 0; ix < nrc_x; ix += 4) {
|
||||
auto acc = vdupq_n_f32(0.f);
|
||||
const block_iq4_nl_x4 * iq4 = (const block_iq4_nl_x4 *)((const char *)vx + ix*bx);
|
||||
const block_iq4_nl_r4 * iq4 = (const block_iq4_nl_r4 *)((const char *)vx + ix*bx);
|
||||
for (int ib4 = 0; ib4 < nb/4; ++ib4) {
|
||||
auto y1 = vld1q_s8_x4(q8.y[0][ib4].qs);
|
||||
auto y2 = vld1q_s8_x4(q8.y[0][ib4].qs+64);
|
||||
@ -7812,7 +7812,7 @@ void mul_mat_qx_r4_q8_0(int n, const void * vx, size_t bx, const DataInfo& info,
|
||||
|
||||
struct IQ4_NL_R4_Dequantizer {
|
||||
IQ4_NL_R4_Dequantizer(const void * vx, size_t bx) : cx((const char *)vx), bx(bx), values(vld1q_s8(iq4k_values)) {}
|
||||
inline void new_row(int ix) { iq4 = (const block_iq4_nl_x4 *)(cx + ix*bx); }
|
||||
inline void new_row(int ix) { iq4 = (const block_iq4_nl_r4 *)(cx + ix*bx); }
|
||||
inline float32x4_t prepare(int ib4, int k, int8x16_t * qx) const {
|
||||
auto scales = vcvt_f32_f16(vld1_f16((const float16_t *)iq4[4*ib4+k].d));
|
||||
auto bits = vld1q_u8_x4(iq4[4*ib4+k].qs);
|
||||
@ -7825,14 +7825,14 @@ struct IQ4_NL_R4_Dequantizer {
|
||||
|
||||
const char * cx;
|
||||
const size_t bx;
|
||||
const block_iq4_nl_x4 * iq4;
|
||||
const block_iq4_nl_r4 * iq4;
|
||||
const uint8x16_t m4 = vdupq_n_u8(0x0f);
|
||||
const int8x16_t values;
|
||||
};
|
||||
|
||||
struct Q4_0_R4_Dequantizer {
|
||||
Q4_0_R4_Dequantizer(const void * vx, size_t bx) : cx((const char *)vx), bx(bx) {}
|
||||
inline void new_row(int ix) { iq4 = (const block_iq4_nl_x4 *)(cx + ix*bx); }
|
||||
inline void new_row(int ix) { iq4 = (const block_iq4_nl_r4 *)(cx + ix*bx); }
|
||||
inline float32x4_t prepare(int ib4, int k, int8x16_t * qx) const {
|
||||
auto scales = vcvt_f32_f16(vld1_f16((const float16_t *)iq4[4*ib4+k].d));
|
||||
auto bits = vld1q_u8_x4(iq4[4*ib4+k].qs);
|
||||
@ -7853,7 +7853,7 @@ struct Q4_0_R4_Dequantizer {
|
||||
|
||||
const char * cx;
|
||||
const size_t bx;
|
||||
const block_iq4_nl_x4 * iq4;
|
||||
const block_iq4_nl_r4 * iq4;
|
||||
const uint8x16_t m4 = vdupq_n_u8(0xf0);
|
||||
const uint8x16_t m88 = vdupq_n_u8(0x88);
|
||||
const float32x4_t norm = vdupq_n_f32(1.f/16);
|
||||
@ -8123,7 +8123,7 @@ bool MulMat::prepare(int typeA, int typeB, int ne00, MulMat& m, int /*Ny*/) {
|
||||
MulMat::set_functions<DequantizerIQ4NL>(m);
|
||||
expected_Btype = GGML_TYPE_Q8_0;
|
||||
break;
|
||||
case GGML_TYPE_IQ4_NL_X4:
|
||||
case GGML_TYPE_IQ4_NL_R4:
|
||||
SET_MUL_MAT_FUNCTIONS_T(m, mul_mat_qx_r4_q8_0, IQ4_NL_R4_Dequantizer);
|
||||
expected_Btype = GGML_TYPE_Q8_0;
|
||||
break;
|
||||
|
||||
@ -3233,19 +3233,19 @@ void vec_dot_iq4_kss_q8_k(int n, float * s, size_t bs, const void * vx, size_t b
|
||||
}
|
||||
|
||||
//
|
||||
// ========================================= iq4_nl_x4
|
||||
// ========================================= iq4_nl_r4
|
||||
//
|
||||
void quantize_row_iq4_nl_x4_ref(const float * x, block_iq4_nl_x4 * y, int64_t k) {
|
||||
void quantize_row_iq4_nl_r4_ref(const float * x, block_iq4_nl_r4 * y, int64_t k) {
|
||||
// we assume we are called with 4 rows
|
||||
quantize_iq4_nl_x4(x, (void *)y, 4, k/4, nullptr);
|
||||
quantize_iq4_nl_r4(x, (void *)y, 4, k/4, nullptr);
|
||||
}
|
||||
|
||||
void quantize_row_iq4_nl_x4(const float * x, void * y, int64_t k) {
|
||||
void quantize_row_iq4_nl_r4(const float * x, void * y, int64_t k) {
|
||||
// we assume we are called with 4 rows
|
||||
quantize_iq4_nl_x4(x, y, 4, k/4, nullptr);
|
||||
quantize_iq4_nl_r4(x, y, 4, k/4, nullptr);
|
||||
}
|
||||
|
||||
static void repack_iq4_nl(int nrows, int n_per_row, const block_iq4_nl * x, block_iq4_nl_x4 * y) {
|
||||
static void repack_iq4_nl(int nrows, int n_per_row, const block_iq4_nl * x, block_iq4_nl_r4 * y) {
|
||||
GGML_ASSERT(nrows%4 == 0);
|
||||
GGML_ASSERT(n_per_row%QK4_NL == 0);
|
||||
int nblock = n_per_row/QK4_NL;
|
||||
@ -3266,21 +3266,21 @@ static void repack_iq4_nl(int nrows, int n_per_row, const block_iq4_nl * x, bloc
|
||||
}
|
||||
}
|
||||
|
||||
size_t quantize_iq4_nl_x4(const float * src, void * dst, int64_t nrows, int64_t n_per_row, const float * imatrix) {
|
||||
size_t quantize_iq4_nl_r4(const float * src, void * dst, int64_t nrows, int64_t n_per_row, const float * imatrix) {
|
||||
GGML_ASSERT(nrows%4 == 0);
|
||||
auto row_size_nl = ggml_row_size(GGML_TYPE_IQ4_NL, n_per_row);
|
||||
std::vector<char> qtmp(4*row_size_nl);
|
||||
char * qrow = (char *)dst;
|
||||
for (int row = 0; row < nrows; row += 4) {
|
||||
quantize_iq4_nl(src, qtmp.data(), 4, n_per_row, imatrix);
|
||||
repack_iq4_nl(4, n_per_row, (const block_iq4_nl *)qtmp.data(), (block_iq4_nl_x4 *)qrow);
|
||||
repack_iq4_nl(4, n_per_row, (const block_iq4_nl *)qtmp.data(), (block_iq4_nl_r4 *)qrow);
|
||||
src += 4*n_per_row;
|
||||
qrow += 4*row_size_nl;
|
||||
}
|
||||
return nrows*row_size_nl;
|
||||
}
|
||||
|
||||
void dequantize_row_iq4_nl_x4(const block_iq4_nl_x4 * x, float * y, int64_t k) {
|
||||
void dequantize_row_iq4_nl_r4(const block_iq4_nl_r4 * x, float * y, int64_t k) {
|
||||
// we assume we are called with 4 rows
|
||||
int n_per_row = k/4;
|
||||
int nb = n_per_row/QK4_NL;
|
||||
@ -3303,9 +3303,9 @@ void dequantize_row_iq4_nl_x4(const block_iq4_nl_x4 * x, float * y, int64_t k) {
|
||||
}
|
||||
}
|
||||
|
||||
void vec_dot_iq4_nl_x4_q8_0(int n, float * s, size_t bs, const void * vx, size_t bx, const void * vy, size_t by, int nrc) {
|
||||
void vec_dot_iq4_nl_r4_q8_0(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_IQ4_NL_X4, vx, 0, GGML_TYPE_Q8_0, vy, 0, s, 0, 0, 1)) {
|
||||
if (iqk_mul_mat(1, 1, n, GGML_TYPE_IQ4_NL_R4, vx, 0, GGML_TYPE_Q8_0, vy, 0, s, 0, 0, 1)) {
|
||||
return;
|
||||
}
|
||||
#endif
|
||||
@ -3319,7 +3319,7 @@ void vec_dot_iq4_nl_x4_q8_0(int n, float * s, size_t bs, const void * vx, size_t
|
||||
//
|
||||
// ========================================= q4_0_r4
|
||||
//
|
||||
void quantize_row_q4_0_r4_ref(const float * x, block_iq4_nl_x4 * y, int64_t k) {
|
||||
void quantize_row_q4_0_r4_ref(const float * x, block_iq4_nl_r4 * y, int64_t k) {
|
||||
// we assume we are called with 4 rows
|
||||
quantize_q4_0_r4(x, (void *)y, 4, k/4, nullptr);
|
||||
}
|
||||
@ -3329,7 +3329,7 @@ void quantize_row_q4_0_r4(const float * x, void * y, int64_t k) {
|
||||
quantize_q4_0_r4(x, y, 4, k/4, nullptr);
|
||||
}
|
||||
|
||||
static void repack_q4_0(int nrows, int n_per_row, const block_q4_0 * x, block_iq4_nl_x4 * y) {
|
||||
static void repack_q4_0(int nrows, int n_per_row, const block_q4_0 * x, block_iq4_nl_r4 * y) {
|
||||
GGML_ASSERT(nrows%4 == 0);
|
||||
GGML_ASSERT(n_per_row%QK4_NL == 0);
|
||||
int nblock = n_per_row/QK4_NL;
|
||||
@ -3369,14 +3369,14 @@ size_t quantize_q4_0_r4(const float * src, void * dst, int64_t nrows, int64_t n_
|
||||
char * qrow = (char *)dst;
|
||||
for (int row = 0; row < nrows; row += 4) {
|
||||
quantize_q4_0(src, qtmp.data(), 4, n_per_row, imatrix);
|
||||
repack_iq4_nl(4, n_per_row, (const block_iq4_nl *)qtmp.data(), (block_iq4_nl_x4 *)qrow);
|
||||
repack_iq4_nl(4, n_per_row, (const block_iq4_nl *)qtmp.data(), (block_iq4_nl_r4 *)qrow);
|
||||
src += 4*n_per_row;
|
||||
qrow += 4*row_size_nl;
|
||||
}
|
||||
return nrows*row_size_nl;
|
||||
}
|
||||
|
||||
void dequantize_row_q4_0_r4(const block_iq4_nl_x4 * x, float * y, int64_t k) {
|
||||
void dequantize_row_q4_0_r4(const block_iq4_nl_r4 * x, float * y, int64_t k) {
|
||||
// we assume we are called with 4 rows
|
||||
int n_per_row = k/4;
|
||||
int nb = n_per_row/QK4_0;
|
||||
|
||||
@ -63,16 +63,16 @@ void vec_dot_iq2_ks_q8_k(int n, float * GGML_RESTRICT s, size_t bs, const void
|
||||
|
||||
void iqk_quantize_row_q8_K(const float * GGML_RESTRICT x, void * GGML_RESTRICT vy, int64_t k);
|
||||
|
||||
void quantize_row_iq4_nl_x4_ref(const float * GGML_RESTRICT x, block_iq4_nl_x4 * GGML_RESTRICT y, int64_t k);
|
||||
void quantize_row_iq4_nl_x4(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
|
||||
size_t quantize_iq4_nl_x4(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
|
||||
void dequantize_row_iq4_nl_x4(const block_iq4_nl_x4 * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
|
||||
void vec_dot_iq4_nl_x4_q8_0(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_iq4_nl_r4_ref(const float * GGML_RESTRICT x, block_iq4_nl_r4 * GGML_RESTRICT y, int64_t k);
|
||||
void quantize_row_iq4_nl_r4(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
|
||||
size_t quantize_iq4_nl_r4(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
|
||||
void dequantize_row_iq4_nl_r4(const block_iq4_nl_r4 * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
|
||||
void vec_dot_iq4_nl_r4_q8_0(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_q4_0_r4_ref(const float * GGML_RESTRICT x, block_iq4_nl_x4 * GGML_RESTRICT y, int64_t k);
|
||||
void quantize_row_q4_0_r4_ref(const float * GGML_RESTRICT x, block_iq4_nl_r4 * GGML_RESTRICT y, int64_t k);
|
||||
void quantize_row_q4_0_r4(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
|
||||
size_t quantize_q4_0_r4(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
|
||||
void dequantize_row_q4_0_r4(const block_iq4_nl_x4 * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
|
||||
void dequantize_row_q4_0_r4(const block_iq4_nl_r4 * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
|
||||
void vec_dot_q4_0_r4_q8_0(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_q8_0_r4_ref(const float * GGML_RESTRICT x, block_q8_0_x4 * GGML_RESTRICT y, int64_t k);
|
||||
|
||||
@ -183,7 +183,7 @@ extern "C" {
|
||||
LLAMA_FTYPE_MOSTLY_Q4_0_R4 = 202, // except 1d tensors
|
||||
LLAMA_FTYPE_MOSTLY_Q8_0_R4 = 207, // except 1d tensors
|
||||
LLAMA_FTYPE_MOSTLY_Q5_0_R4 = 208, // except 1d tensors
|
||||
LLAMA_FTYPE_MOSTLY_IQ4_NL_X4 = 225, // except 1d tensors
|
||||
LLAMA_FTYPE_MOSTLY_IQ4_NL_R4 = 225, // except 1d tensors
|
||||
LLAMA_FTYPE_MOSTLY_IQ4_XS_R4 = 230, // except 1d tensors
|
||||
LLAMA_FTYPE_MOSTLY_Q6_0_R4 = 235, // except 1d tensors
|
||||
LLAMA_FTYPE_MOSTLY_IQ2_BN_R4 = 237, // except 1d tensors
|
||||
|
||||
@ -3850,7 +3850,7 @@ struct llama_model_loader {
|
||||
case GGML_TYPE_IQ2_BN: ftype = LLAMA_FTYPE_MOSTLY_IQ2_BN; break;
|
||||
case GGML_TYPE_IQ2_BN_R4:ftype = LLAMA_FTYPE_MOSTLY_IQ2_BN_R4;break;
|
||||
case GGML_TYPE_IQ4_NL: ftype = LLAMA_FTYPE_MOSTLY_IQ4_NL; break;
|
||||
case GGML_TYPE_IQ4_NL_X4:ftype = LLAMA_FTYPE_MOSTLY_IQ4_NL_X4;break;
|
||||
case GGML_TYPE_IQ4_NL_R4:ftype = LLAMA_FTYPE_MOSTLY_IQ4_NL_R4;break;
|
||||
case GGML_TYPE_IQ4_XS_R4:ftype = LLAMA_FTYPE_MOSTLY_IQ4_XS_R4;break;
|
||||
case GGML_TYPE_Q4_0_R4: ftype = LLAMA_FTYPE_MOSTLY_Q4_0_R4; break;
|
||||
case GGML_TYPE_Q5_0_R4: ftype = LLAMA_FTYPE_MOSTLY_Q5_0_R4; break;
|
||||
@ -4560,7 +4560,7 @@ static std::string llama_model_ftype_name(llama_ftype ftype) {
|
||||
case LLAMA_FTYPE_MOSTLY_IQ1_S: return "IQ1_S - 1.5625 bpw";
|
||||
case LLAMA_FTYPE_MOSTLY_IQ1_M: return "IQ1_M - 1.75 bpw";
|
||||
case LLAMA_FTYPE_MOSTLY_IQ4_NL: return "IQ4_NL - 4.5 bpw";
|
||||
case LLAMA_FTYPE_MOSTLY_IQ4_NL_X4:return "IQ4_NL_X4 - 4.5 bpw";
|
||||
case LLAMA_FTYPE_MOSTLY_IQ4_NL_R4:return "IQ4_NL_R4 - 4.5 bpw";
|
||||
case LLAMA_FTYPE_MOSTLY_IQ4_XS_R4:return "IQ4_XS_R4 - 4.25 bpw";
|
||||
case LLAMA_FTYPE_MOSTLY_Q4_0_R4: return "Q4_0_R4 - 4.5 bpw";
|
||||
case LLAMA_FTYPE_MOSTLY_Q5_0_R4: return "Q5_0_R4 - 5.5 bpw";
|
||||
@ -15780,7 +15780,7 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
|
||||
new_type == GGML_TYPE_Q4_0_8_8) {
|
||||
new_type = GGML_TYPE_Q4_0;
|
||||
}
|
||||
else if (new_type == GGML_TYPE_IQ4_NL_X4) {
|
||||
else if (new_type == GGML_TYPE_IQ4_NL_R4) {
|
||||
new_type = GGML_TYPE_IQ4_NL;
|
||||
}
|
||||
else if (new_type == GGML_TYPE_IQ4_XS_R4) {
|
||||
@ -15860,7 +15860,7 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
|
||||
}
|
||||
else if (ftype == LLAMA_FTYPE_MOSTLY_Q3_K_L) new_type = GGML_TYPE_Q5_K;
|
||||
else if ((ftype == LLAMA_FTYPE_MOSTLY_IQ4_NL || ftype == LLAMA_FTYPE_MOSTLY_IQ4_XS ||
|
||||
ftype == LLAMA_FTYPE_MOSTLY_IQ4_NL_X4 || ftype == LLAMA_FTYPE_MOSTLY_IQ4_XS_R4 ||
|
||||
ftype == LLAMA_FTYPE_MOSTLY_IQ4_NL_R4 || ftype == LLAMA_FTYPE_MOSTLY_IQ4_XS_R4 ||
|
||||
ftype == LLAMA_FTYPE_MOSTLY_IQ4_KS || ftype == LLAMA_FTYPE_MOSTLY_IQ4_KSS) && qs.model.hparams.n_gqa() >= 2) {
|
||||
new_type = GGML_TYPE_IQ5_K;
|
||||
}
|
||||
@ -15890,7 +15890,7 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
|
||||
else if (new_type == GGML_TYPE_Q3_K || new_type == GGML_TYPE_IQ3_S ) new_type = GGML_TYPE_Q4_K;
|
||||
else if (new_type == GGML_TYPE_Q4_K || new_type == GGML_TYPE_IQ4_XS) new_type = GGML_TYPE_Q5_K;
|
||||
else if (new_type == GGML_TYPE_IQ4_NL) new_type = GGML_TYPE_Q5_K;
|
||||
else if (new_type == GGML_TYPE_IQ4_NL_X4) new_type = GGML_TYPE_Q5_K;
|
||||
else if (new_type == GGML_TYPE_IQ4_NL_R4) new_type = GGML_TYPE_Q5_K;
|
||||
else if (new_type == GGML_TYPE_IQ4_XS_R4) new_type = GGML_TYPE_Q5_K;
|
||||
else if (new_type == GGML_TYPE_Q5_K) new_type = GGML_TYPE_Q6_K;
|
||||
}
|
||||
@ -15957,7 +15957,7 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
|
||||
else if (i_layer < n_layer/8 && !qs.has_imatrix &&
|
||||
(ftype == LLAMA_FTYPE_MOSTLY_IQ4_NL || ftype == LLAMA_FTYPE_MOSTLY_IQ4_XS ||
|
||||
ftype == LLAMA_FTYPE_MOSTLY_IQ4_KS || ftype == LLAMA_FTYPE_MOSTLY_IQ4_KSS ||
|
||||
ftype == LLAMA_FTYPE_MOSTLY_IQ4_NL_X4 || ftype == LLAMA_FTYPE_MOSTLY_IQ4_XS_R4)) {
|
||||
ftype == LLAMA_FTYPE_MOSTLY_IQ4_NL_R4 || ftype == LLAMA_FTYPE_MOSTLY_IQ4_XS_R4)) {
|
||||
new_type = GGML_TYPE_Q5_K;
|
||||
}
|
||||
else if (ftype == LLAMA_FTYPE_MOSTLY_Q5_K_M && use_more_bits(i_layer, n_layer)) new_type = GGML_TYPE_Q6_K;
|
||||
@ -15972,7 +15972,7 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
|
||||
new_type = ftype == LLAMA_FTYPE_MOSTLY_Q4_0 ? GGML_TYPE_Q4_1 : GGML_TYPE_Q5_1;
|
||||
}
|
||||
else if (ftype == LLAMA_FTYPE_MOSTLY_Q4_0_R4 && qs.has_imatrix && i_layer < n_layer/8) {
|
||||
new_type = GGML_TYPE_IQ4_NL_X4;
|
||||
new_type = GGML_TYPE_IQ4_NL_R4;
|
||||
}
|
||||
++qs.i_ffn_down;
|
||||
} else if (name.find("attn_output.weight") != std::string::npos) {
|
||||
@ -15984,7 +15984,7 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
|
||||
ftype == LLAMA_FTYPE_MOSTLY_Q4_K_S || ftype == LLAMA_FTYPE_MOSTLY_Q4_K_M || ftype == LLAMA_FTYPE_MOSTLY_IQ3_S ||
|
||||
ftype == LLAMA_FTYPE_MOSTLY_IQ3_M || ftype == LLAMA_FTYPE_MOSTLY_IQ4_XS || ftype == LLAMA_FTYPE_MOSTLY_IQ4_K ||
|
||||
ftype == LLAMA_FTYPE_MOSTLY_IQ2_K || ftype == LLAMA_FTYPE_MOSTLY_IQ3_K ||
|
||||
ftype == LLAMA_FTYPE_MOSTLY_IQ4_NL_X4 || ftype == LLAMA_FTYPE_MOSTLY_IQ4_XS_R4) {
|
||||
ftype == LLAMA_FTYPE_MOSTLY_IQ4_NL_R4 || ftype == LLAMA_FTYPE_MOSTLY_IQ4_XS_R4) {
|
||||
new_type = GGML_TYPE_Q5_K;
|
||||
}
|
||||
} else {
|
||||
@ -16194,7 +16194,7 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
|
||||
case LLAMA_FTYPE_MOSTLY_IQ2_BN: default_type = GGML_TYPE_IQ2_BN; break;
|
||||
case LLAMA_FTYPE_MOSTLY_IQ2_BN_R4:default_type = GGML_TYPE_IQ2_BN_R4;break;
|
||||
case LLAMA_FTYPE_MOSTLY_IQ4_NL: default_type = GGML_TYPE_IQ4_NL; break;
|
||||
case LLAMA_FTYPE_MOSTLY_IQ4_NL_X4:default_type = GGML_TYPE_IQ4_NL_X4;break;
|
||||
case LLAMA_FTYPE_MOSTLY_IQ4_NL_R4:default_type = GGML_TYPE_IQ4_NL_R4;break;
|
||||
case LLAMA_FTYPE_MOSTLY_IQ4_XS_R4:default_type = GGML_TYPE_IQ4_XS_R4;break;
|
||||
case LLAMA_FTYPE_MOSTLY_Q4_0_R4: default_type = GGML_TYPE_Q4_0_R4; break;
|
||||
case LLAMA_FTYPE_MOSTLY_Q5_0_R4: default_type = GGML_TYPE_Q5_0_R4; break;
|
||||
@ -16557,7 +16557,7 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
|
||||
if (new_type == GGML_TYPE_Q4_0_8_8) chunk_size_multiplier = 8;
|
||||
else if (new_type == GGML_TYPE_Q4_0_4_4 || new_type == GGML_TYPE_Q4_0_4_8) chunk_size_multiplier = 4;
|
||||
}
|
||||
else if (new_type == GGML_TYPE_IQ4_NL_X4) {
|
||||
else if (new_type == GGML_TYPE_IQ4_NL_R4) {
|
||||
if (tensor->ne[1] % 4 != 0) new_type = GGML_TYPE_IQ4_NL;
|
||||
else chunk_size_multiplier = 4;
|
||||
}
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user