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ggml : fix MUL_MAT_ID repack with Q8_K

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ggml-ci
This commit is contained in:
Georgi Gerganov
2025-03-24 13:07:10 +02:00
parent 9b169a4d4e
commit 87cd537a29
1 changed files with 34 additions and 33 deletions
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21
ggml/src/ggml-cpu/ggml-cpu-aarch64.cpp
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@@ -5295,8 +5295,7 @@ template <> void gemv<block_q4_K, 8, 8>(int n, float * s, size_t bs, const void
ggml_gemv_q4_K_8x8_q8_K(n, s, bs, vx, vy, nr, nc);
}
template <>
void gemv<block_iq4_nl, 4, 4>(int n, float * s, size_t bs, const void * vx, const void * vy, int nr, int nc) {
template <> void gemv<block_iq4_nl, 4, 4>(int n, float * s, size_t bs, const void * vx, const void * vy, int nr, int nc) {
ggml_gemv_iq4_nl_4x4_q8_0(n, s, bs, vx, vy, nr, nc);
}
@@ -5320,8 +5319,7 @@ template <> void gemm<block_q4_K, 8, 8>(int n, float * s, size_t bs, const void
ggml_gemm_q4_K_8x8_q8_K(n, s, bs, vx, vy, nr, nc);
}
template <>
void gemm<block_iq4_nl, 4, 4>(int n, float * s, size_t bs, const void * vx, const void * vy, int nr, int nc) {
template <> void gemm<block_iq4_nl, 4, 4>(int n, float * s, size_t bs, const void * vx, const void * vy, int nr, int nc) {
ggml_gemm_iq4_nl_4x4_q8_0(n, s, bs, vx, vy, nr, nc);
}
@@ -5405,6 +5403,7 @@ template <typename BLOC_TYPE, int64_t INTER_SIZE, int64_t NB_COLS, ggml_type PAR
INTER_SIZE);
}
} else {
GGML_ASSERT(PARAM_TYPE == GGML_TYPE_Q8_0);
for (int64_t i11 = ith * 4; i11 < ne11 - ne11 % 4; i11 += nth * 4) {
quantize_mat_q8_0((float *) ((char *) src1->data + i11 * nb11), (void *) (wdata + i11 * nbw1), 4, ne10,
INTER_SIZE);
@@ -5452,7 +5451,7 @@ template <typename BLOC_TYPE, int64_t INTER_SIZE, int64_t NB_COLS, ggml_type PAR
const int ith = params->ith;
const int nth = params->nth;
const ggml_from_float_t from_float = ggml_get_type_traits_cpu(GGML_TYPE_Q8_0)->from_float;
const ggml_from_float_t from_float = ggml_get_type_traits_cpu(PARAM_TYPE)->from_float;
// we don't support permuted src0 or src1
GGML_ASSERT(nb00 == ggml_type_size(src0->type));
@@ -5474,7 +5473,7 @@ template <typename BLOC_TYPE, int64_t INTER_SIZE, int64_t NB_COLS, ggml_type PAR
const int n_ids = ids->ne[0]; // n_expert_used
const int n_as = ne02; // n_expert
const size_t nbw1 = ggml_row_size(GGML_TYPE_Q8_0, ne10);
const size_t nbw1 = ggml_row_size(PARAM_TYPE, ne10);
const size_t nbw2 = nbw1*ne11;
const size_t nbw3 = nbw2*ne12;
@@ -5489,9 +5488,10 @@ template <typename BLOC_TYPE, int64_t INTER_SIZE, int64_t NB_COLS, ggml_type PAR
auto wdata = (char *) params->wdata;
auto wdata_src1_end = (char *) wdata + GGML_PAD(nbw3, sizeof(int64_t));
int64_t * matrix_row_counts = (int64_t *) (wdata_src1_end); // [n_as]
struct mmid_row_mapping * matrix_rows = (struct mmid_row_mapping *) (matrix_row_counts + n_as); // [n_as][ne12]
// src1: float32 => block_q8_0
// src1: float32 => param type
for (int64_t i12 = 0; i12 < ne12; ++i12) {
for (int64_t i11 = ith; i11 < ne11; i11 += nth) {
from_float((float *)((char *) src1->data + i12 * nb12 + i11 * nb11),
@@ -5537,14 +5537,15 @@ template <typename BLOC_TYPE, int64_t INTER_SIZE, int64_t NB_COLS, ggml_type PAR
int64_t src0_cur_start = (ith * ne01) / nth;
int64_t src0_cur_end = ((ith + 1) * ne01) / nth;
src0_cur_start =
(src0_cur_start % NB_COLS) ? src0_cur_start + NB_COLS - (src0_cur_start % NB_COLS) : src0_cur_start;
src0_cur_start = (src0_cur_start % NB_COLS) ? src0_cur_start + NB_COLS - (src0_cur_start % NB_COLS) : src0_cur_start;
src0_cur_end = (src0_cur_end % NB_COLS) ? src0_cur_end + NB_COLS - (src0_cur_end % NB_COLS) : src0_cur_end;
if (src0_cur_start >= src0_cur_end) return;
for (int ir1 = 0; ir1 < nr1; ir1++) {
struct mmid_row_mapping row_mapping = MMID_MATRIX_ROW(cur_a, ir1);
const int id = row_mapping.i1; // selected expert index
const int64_t i11 = id % ne11;
@@ -5578,7 +5579,7 @@ static const tensor_traits<block_q4_0, 8, 8, GGML_TYPE_Q8_0> q4_0_8x8_q8_0;
static const tensor_traits<block_q4_K, 8, 8, GGML_TYPE_Q8_K> q4_K_8x8_q8_K;
// instance for IQ4
static const tensor_traits<block_iq4_nl, 4, 4, GGML_TYPE_IQ4_NL> iq4_nl_4x4_q8_0;
static const tensor_traits<block_iq4_nl, 4, 4, GGML_TYPE_Q8_0> iq4_nl_4x4_q8_0;
} // namespace ggml::cpu::aarch64