haraldwolff/llama.cpp
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ggml : remove old quantization functions (#5942)

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* ggml : remove old quantization functions

ggml-ci

* ggml : simplify ggml_quantize_chunk

ggml-ci

* ggml : restrict correctness

ggml-ci

* ggml : remove hist data from the quantization API

ggml-ci

* tests : remove hist usage in test-backend-ops

ggml-ci

* vulkan : remove hist and fix typo
This commit is contained in:
Georgi Gerganov 2024-03-09 15:53:59 +02:00 committed by GitHub
parent 97c09585d6
commit 5b09797321
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GPG key ID: B5690EEEBB952194
9 changed files with 131 additions and 568 deletions
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6
examples/benchmark/benchmark-matmult.cpp
View file

@ -189,12 +189,10 @@ int main(int argc, char ** argv) {
int32_t nelements = sizex*sizey;
std::vector<int64_t> hist_cur(1 << 4, 0);
// Set up a the benchmark matrices
// printf("Creating new tensor q11 & Running quantize\n");
struct ggml_tensor * q11 = ggml_new_tensor_2d(ctx, qtype, sizex, sizey);
ggml_quantize_chunk(qtype, (const float *) m11->data, q11->data, 0, nelements/m11->ne[0], m11->ne[0], hist_cur.data(), nullptr);
ggml_quantize_chunk(qtype, (const float *) m11->data, q11->data, 0, nelements/m11->ne[0], m11->ne[0], nullptr);
// Set up a the compute graph
// printf("Creating new tensor q31\n");
@ -207,7 +205,7 @@ int main(int argc, char ** argv) {
// Set up a second graph computation to make sure we override the CPU cache lines
// printf("Creating new tensor q12 & Running quantize\n");
struct ggml_tensor * q12 = ggml_new_tensor_2d(ctx, qtype, sizex, sizey);
ggml_quantize_chunk(qtype, (const float *) m12->data, q12->data, 0, nelements/m12->ne[0], m12->ne[0], hist_cur.data(), nullptr);
ggml_quantize_chunk(qtype, (const float *) m12->data, q12->data, 0, nelements/m12->ne[0], m12->ne[0], nullptr);
// printf("Creating new tensor q32\n");
struct ggml_tensor * q32 = ggml_mul_mat(ctx, q12, m2);

55
examples/llava/clip.cpp
View file

@ -1862,7 +1862,6 @@ bool clip_model_quantize(const char * fname_inp, const char * fname_out, const i
std::vector<uint8_t> work(512);
std::vector<float> conv_buf(512);
std::vector<int64_t> hist_all(1 << 4, 0);
size_t total_size_org = 0;
size_t total_size_new = 0;
@ -1917,48 +1916,7 @@ bool clip_model_quantize(const char * fname_inp, const char * fname_out, const i
}
new_data = work.data();
std::vector<int64_t> hist_cur(1 << 4, 0);
switch (new_type) {
case GGML_TYPE_Q4_0: {
new_size = ggml_quantize_q4_0(f32_data, new_data, n_elms, cur->ne[0], hist_cur.data());
} break;
case GGML_TYPE_Q4_1: {
new_size = ggml_quantize_q4_1(f32_data, new_data, n_elms, cur->ne[0], hist_cur.data());
} break;
case GGML_TYPE_Q5_0: {
new_size = ggml_quantize_q5_0(f32_data, new_data, n_elms, cur->ne[0], hist_cur.data());
} break;
case GGML_TYPE_Q5_1: {
new_size = ggml_quantize_q5_1(f32_data, new_data, n_elms, cur->ne[0], hist_cur.data());
} break;
case GGML_TYPE_Q8_0: {
new_size = ggml_quantize_q8_0(f32_data, new_data, n_elms, cur->ne[0], hist_cur.data());
} break;
case GGML_TYPE_Q2_K: {
new_size = ggml_quantize_q2_K(f32_data, new_data, n_elms, cur->ne[0], hist_cur.data());
} break;
case GGML_TYPE_Q3_K: {
new_size = ggml_quantize_q3_K(f32_data, new_data, n_elms, cur->ne[0], hist_cur.data());
} break;
case GGML_TYPE_Q4_K: {
new_size = ggml_quantize_q4_K(f32_data, new_data, n_elms, cur->ne[0], hist_cur.data());
} break;
case GGML_TYPE_Q5_K: {
new_size = ggml_quantize_q5_K(f32_data, new_data, n_elms, cur->ne[0], hist_cur.data());
} break;
case GGML_TYPE_Q6_K: {
new_size = ggml_quantize_q6_K(f32_data, new_data, n_elms, cur->ne[0], hist_cur.data());
} break;
default: {
fprintf(stderr, "%s: unsupported quantization type %d\n", __func__, new_type);
return false;
}
}
for (size_t j = 0; j < hist_cur.size(); ++j) {
hist_all[j] += hist_cur[j];
}
new_size = ggml_quantize_chunk(new_type, f32_data, new_data, 0, n_elms/cur->ne[0], cur->ne[0], nullptr);
} else {
new_type = cur->type;
new_data = cur->data;
@ -1993,17 +1951,6 @@ bool clip_model_quantize(const char * fname_inp, const char * fname_out, const i
{
printf("%s: original size = %8.2f MB\n", __func__, total_size_org / 1024.0 / 1024.0);
printf("%s: quantized size = %8.2f MB\n", __func__, total_size_new / 1024.0 / 1024.0);
int64_t sum_all = 0;
for (size_t i = 0; i < hist_all.size(); ++i) {
sum_all += hist_all[i];
}
printf("%s: hist: ", __func__);
for (size_t i = 0; i < hist_all.size(); ++i) {
printf("%5.3f ", hist_all[i] / (float)sum_all);
}
printf("\n");
}
return true;

143
ggml-quants.c
View file

@ -1704,16 +1704,6 @@ void quantize_row_q2_K(const float * restrict x, void * restrict vy, int k) {
quantize_row_q2_K_reference(x, vy, k);
}
size_t ggml_quantize_q2_K(const float * restrict src, void * restrict dst, int n, int k, int64_t * restrict hist) {
(void)hist; // TODO: collect histograms
for (int j = 0; j < n; j += k) {
block_q2_K * restrict y = (block_q2_K *)dst + j/QK_K;
quantize_row_q2_K_reference(src + j, y, k);
}
return (n/QK_K*sizeof(block_q2_K));
}
static float make_qkx3_quants(int n, int nmax, const float * restrict x, const float * restrict weights,
uint8_t * restrict L, float * restrict the_min, uint8_t * restrict Laux,
float rmin, float rdelta, int nstep, bool use_mad) {
@ -1966,8 +1956,7 @@ static void quantize_row_q2_K_impl(const float * restrict x, block_q2_K * restri
}
}
size_t quantize_q2_K(const float * src, void * dst, int nrow, int n_per_row, int64_t * hist, const float * quant_weights) {
(void)hist;
size_t quantize_q2_K(const float * restrict src, void * restrict dst, int nrow, int n_per_row, const float * quant_weights) {
size_t row_size = ggml_row_size(GGML_TYPE_Q2_K, n_per_row);
if (!quant_weights) {
quantize_row_q2_K_reference(src, dst, nrow*n_per_row);
@ -2186,16 +2175,6 @@ void quantize_row_q3_K(const float * restrict x, void * restrict vy, int k) {
quantize_row_q3_K_reference(x, vy, k);
}
size_t ggml_quantize_q3_K(const float * restrict src, void * restrict dst, int n, int k, int64_t * restrict hist) {
(void)hist; // TODO: collect histograms
for (int j = 0; j < n; j += k) {
block_q3_K * restrict y = (block_q3_K *)dst + j/QK_K;
quantize_row_q3_K_reference(src + j, y, k);
}
return (n/QK_K*sizeof(block_q3_K));
}
static void quantize_row_q3_K_impl(const float * restrict x, block_q3_K * restrict y, int n_per_row, const float * restrict quant_weights) {
#if QK_K != 256
(void)quant_weights;
@ -2285,8 +2264,7 @@ static void quantize_row_q3_K_impl(const float * restrict x, block_q3_K * restri
#endif
}
size_t quantize_q3_K(const float * src, void * dst, int nrow, int n_per_row, int64_t * hist, const float * quant_weights) {
(void)hist;
size_t quantize_q3_K(const float * restrict src, void * restrict dst, int nrow, int n_per_row, const float * quant_weights) {
size_t row_size = ggml_row_size(GGML_TYPE_Q3_K, n_per_row);
if (!quant_weights) {
quantize_row_q3_K_reference(src, dst, nrow*n_per_row);
@ -2456,17 +2434,6 @@ void quantize_row_q4_K(const float * restrict x, void * restrict vy, int k) {
quantize_row_q4_K_reference(x, y, k);
}
size_t ggml_quantize_q4_K(const float * restrict src, void * restrict dst, int n, int k, int64_t * restrict hist) {
assert(k % QK_K == 0);
(void)hist; // TODO: collect histograms
for (int j = 0; j < n; j += k) {
block_q4_K * restrict y = (block_q4_K *)dst + j/QK_K;
quantize_row_q4_K_reference(src + j, y, k);
}
return (n/QK_K*sizeof(block_q4_K));
}
static void quantize_row_q4_K_impl(const float * restrict x, block_q4_K * restrict y, int n_per_row, const float * quant_weights) {
#if QK_K != 256
(void)quant_weights;
@ -2545,8 +2512,7 @@ static void quantize_row_q4_K_impl(const float * restrict x, block_q4_K * restri
#endif
}
size_t quantize_q4_K(const float * src, void * dst, int nrow, int n_per_row, int64_t * hist, const float * quant_weights) {
(void)hist;
size_t quantize_q4_K(const float * restrict src, void * restrict dst, int nrow, int n_per_row, const float * quant_weights) {
size_t row_size = ggml_row_size(GGML_TYPE_Q4_K, n_per_row);
if (!quant_weights) {
quantize_row_q4_K_reference(src, dst, nrow*n_per_row);
@ -2757,17 +2723,6 @@ void quantize_row_q5_K(const float * restrict x, void * restrict vy, int k) {
quantize_row_q5_K_reference(x, y, k);
}
size_t ggml_quantize_q5_K(const float * restrict src, void * restrict dst, int n, int k, int64_t * restrict hist) {
assert(k % QK_K == 0);
(void)hist; // TODO: collect histograms
for (int j = 0; j < n; j += k) {
block_q5_K * restrict y = (block_q5_K *)dst + j/QK_K;
quantize_row_q5_K_reference(src + j, y, k);
}
return (n/QK_K*sizeof(block_q5_K));
}
static void quantize_row_q5_K_impl(const float * restrict x, block_q5_K * restrict y, int n_per_row, const float * quant_weights) {
#if QK_K != 256
(void)quant_weights;
@ -2866,8 +2821,7 @@ static void quantize_row_q5_K_impl(const float * restrict x, block_q5_K * restri
#endif
}
size_t quantize_q5_K(const float * src, void * dst, int nrow, int n_per_row, int64_t * hist, const float * quant_weights) {
(void)hist;
size_t quantize_q5_K(const float * restrict src, void * restrict dst, int nrow, int n_per_row, const float * quant_weights) {
size_t row_size = ggml_row_size(GGML_TYPE_Q5_K, n_per_row);
if (!quant_weights) {
quantize_row_q5_K_reference(src, dst, nrow*n_per_row);
@ -3020,17 +2974,6 @@ void quantize_row_q6_K(const float * restrict x, void * restrict vy, int k) {
quantize_row_q6_K_reference(x, y, k);
}
size_t ggml_quantize_q6_K(const float * src, void * dst, int n, int k, int64_t * hist) {
assert(k % QK_K == 0);
(void)hist; // TODO: collect histograms
for (int j = 0; j < n; j += k) {
block_q6_K * restrict y = (block_q6_K *)dst + j/QK_K;
quantize_row_q6_K_reference(src + j, y, k);
}
return (n/QK_K*sizeof(block_q6_K));
}
static void quantize_row_q6_K_impl(const float * restrict x, block_q6_K * restrict y, int n_per_row, const float * quant_weights) {
#if QK_K != 256
(void)quant_weights;
@ -3120,8 +3063,7 @@ static void quantize_row_q6_K_impl(const float * restrict x, block_q6_K * restri
#endif
}
size_t quantize_q6_K(const float * src, void * dst, int nrow, int n_per_row, int64_t * hist, const float * quant_weights) {
(void)hist;
size_t quantize_q6_K(const float * restrict src, void * restrict dst, int nrow, int n_per_row, const float * quant_weights) {
size_t row_size = ggml_row_size(GGML_TYPE_Q6_K, n_per_row);
if (!quant_weights) {
quantize_row_q6_K_reference(src, dst, nrow*n_per_row);
@ -3165,9 +3107,10 @@ static void quantize_row_q4_0_impl(const float * restrict x, block_q4_0 * restri
}
}
size_t quantize_q4_0(const float * src, void * dst, int nrow, int n_per_row, int64_t * hist, const float * quant_weights) {
size_t quantize_q4_0(const float * restrict src, void * restrict dst, int nrow, int n_per_row, const float * quant_weights) {
if (!quant_weights) {
return ggml_quantize_q4_0(src, dst, nrow*n_per_row, n_per_row, hist);
quantize_row_q4_0_reference(src, dst, nrow*n_per_row);
return nrow * ggml_row_size(GGML_TYPE_Q4_0, n_per_row);
}
size_t row_size = ggml_row_size(GGML_TYPE_Q4_0, n_per_row);
char * qrow = (char *)dst;
@ -3209,9 +3152,10 @@ static void quantize_row_q4_1_impl(const float * restrict x, block_q4_1 * restri
}
}
size_t quantize_q4_1(const float * src, void * dst, int nrow, int n_per_row, int64_t * hist, const float * quant_weights) {
size_t quantize_q4_1(const float * restrict src, void * restrict dst, int nrow, int n_per_row, const float * quant_weights) {
if (!quant_weights) {
return ggml_quantize_q4_1(src, dst, nrow*n_per_row, n_per_row, hist);
quantize_row_q4_1_reference(src, dst, nrow*n_per_row);
return nrow * ggml_row_size(GGML_TYPE_Q4_1, n_per_row);
}
size_t row_size = ggml_row_size(GGML_TYPE_Q4_1, n_per_row);
char * qrow = (char *)dst;
@ -3262,9 +3206,10 @@ static void quantize_row_q5_0_impl(const float * restrict x, block_q5_0 * restri
}
}
size_t quantize_q5_0(const float * src, void * dst, int nrow, int n_per_row, int64_t * hist, const float * quant_weights) {
size_t quantize_q5_0(const float * restrict src, void * restrict dst, int nrow, int n_per_row, const float * quant_weights) {
if (!quant_weights) {
return ggml_quantize_q5_0(src, dst, nrow*n_per_row, n_per_row, hist);
quantize_row_q5_0_reference(src, dst, nrow*n_per_row);
return nrow * ggml_row_size(GGML_TYPE_Q5_0, n_per_row);
}
size_t row_size = ggml_row_size(GGML_TYPE_Q5_0, n_per_row);
char * qrow = (char *)dst;
@ -3314,9 +3259,10 @@ static void quantize_row_q5_1_impl(const float * restrict x, block_q5_1 * restri
}
}
size_t quantize_q5_1(const float * src, void * dst, int nrow, int n_per_row, int64_t * hist, const float * quant_weights) {
size_t quantize_q5_1(const float * restrict src, void * restrict dst, int nrow, int n_per_row, const float * quant_weights) {
if (!quant_weights) {
return ggml_quantize_q5_1(src, dst, nrow*n_per_row, n_per_row, hist);
quantize_row_q5_1_reference(src, dst, nrow*n_per_row);
return nrow * ggml_row_size(GGML_TYPE_Q5_1, n_per_row);
}
size_t row_size = ggml_row_size(GGML_TYPE_Q5_1, n_per_row);
char * qrow = (char *)dst;
@ -3328,6 +3274,13 @@ size_t quantize_q5_1(const float * src, void * dst, int nrow, int n_per_row, int
return nrow * row_size;
}
size_t quantize_q8_0(const float * restrict src, void * restrict dst, int nrow, int n_per_row, const float * quant_weights) {
(void)quant_weights; // not used
const size_t row_size = ggml_row_size(GGML_TYPE_Q8_0, n_per_row);
quantize_row_q8_0_reference(src, dst, nrow*n_per_row);
return nrow * row_size;
}
// ====================== "True" 2-bit (de)-quantization
void dequantize_row_iq2_xxs(const block_iq2_xxs * restrict x, float * restrict y, int k) {
@ -9373,7 +9326,7 @@ void ggml_vec_dot_iq3_xxs_q8_K(int n, float * restrict s, size_t bs, const void
#endif
}
void ggml_vec_dot_iq3_s_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 ggml_vec_dot_iq3_s_q8_K (int n, float * restrict s, size_t bs, const void * restrict vx, size_t bx, const void * restrict vy, size_t by, int nrc) {
assert(n % QK_K == 0);
assert(nrc == 1);
UNUSED(nrc);
@ -9620,7 +9573,7 @@ static inline __m256i mul_add_epi8(const __m256i x, const __m256i y) {
}
#endif
void ggml_vec_dot_iq1_s_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 ggml_vec_dot_iq1_s_q8_K (int n, float * restrict s, size_t bs, const void * restrict vx, size_t bx, const void * restrict vy, size_t by, int nrc) {
assert(n % QK_K == 0);
assert(nrc == 1);
UNUSED(nrc);
@ -10220,7 +10173,7 @@ void iq2xs_init_impl(enum ggml_type type) {
int * kmap_q2xs;
uint16_t * kneighbors_q2xs;
printf("================================================================= %s(grid_size = %d)\n", __func__, grid_size);
//printf("================================================================= %s(grid_size = %d)\n", __func__, grid_size);
uint64_t * the_grid = (uint64_t *)malloc(grid_size*sizeof(uint64_t));
for (int k = 0; k < grid_size; ++k) {
int8_t * pos = (int8_t *)(the_grid + k);
@ -10275,7 +10228,7 @@ void iq2xs_init_impl(enum ggml_type type) {
}
num_neighbors += n;
}
printf("%s: %d neighbours in total\n", __func__, num_neighbors);
//printf("%s: %d neighbours in total\n", __func__, num_neighbors);
kneighbors_q2xs = (uint16_t *)malloc((num_neighbors + num_not_in_map)*sizeof(uint16_t));
iq2_data[gindex].neighbours = kneighbors_q2xs;
int counter = 0;
@ -10698,8 +10651,7 @@ static void quantize_row_iq2_xs_impl(const float * restrict x, void * restrict v
}
}
size_t quantize_iq2_xxs(const float * src, void * dst, int nrow, int n_per_row, int64_t * hist, const float * quant_weights) {
(void)hist;
size_t quantize_iq2_xxs(const float * restrict src, void * restrict dst, int nrow, int n_per_row, const float * quant_weights) {
GGML_ASSERT(n_per_row%QK_K == 0);
int nblock = n_per_row/QK_K;
char * qrow = (char *)dst;
@ -10711,8 +10663,7 @@ size_t quantize_iq2_xxs(const float * src, void * dst, int nrow, int n_per_row,
return nrow * nblock * sizeof(block_iq2_xxs);
}
size_t quantize_iq2_xs(const float * src, void * dst, int nrow, int n_per_row, int64_t * hist, const float * quant_weights) {
(void)hist;
size_t quantize_iq2_xs(const float * restrict src, void * restrict dst, int nrow, int n_per_row, const float * quant_weights) {
GGML_ASSERT(n_per_row%QK_K == 0);
int nblock = n_per_row/QK_K;
char * qrow = (char *)dst;
@ -10816,7 +10767,7 @@ void iq3xs_init_impl(int grid_size) {
int * kmap_q3xs;
uint16_t * kneighbors_q3xs;
printf("================================================================= %s(grid_size = %d)\n", __func__, grid_size);
//printf("================================================================= %s(grid_size = %d)\n", __func__, grid_size);
uint32_t * the_grid = (uint32_t *)malloc(grid_size*sizeof(uint32_t));
for (int k = 0; k < grid_size; ++k) {
int8_t * pos = (int8_t *)(the_grid + k);
@ -10871,7 +10822,7 @@ void iq3xs_init_impl(int grid_size) {
}
num_neighbors += n;
}
printf("%s: %d neighbours in total\n", __func__, num_neighbors);
//printf("%s: %d neighbours in total\n", __func__, num_neighbors);
kneighbors_q3xs = (uint16_t *)malloc((num_neighbors + num_not_in_map)*sizeof(uint16_t));
iq3_data[gindex].neighbours = kneighbors_q3xs;
int counter = 0;
@ -11154,8 +11105,7 @@ static void quantize_row_iq3_xxs_impl(int grid_size, const float * restrict x, v
}
}
size_t quantize_iq3_xxs(const float * src, void * dst, int nrow, int n_per_row, int64_t * hist, const float * quant_weights) {
(void)hist;
size_t quantize_iq3_xxs(const float * restrict src, void * restrict dst, int nrow, int n_per_row, const float * quant_weights) {
GGML_ASSERT(n_per_row%QK_K == 0);
int nblock = n_per_row/QK_K;
char * qrow = (char *)dst;
@ -11361,8 +11311,7 @@ static void quantize_row_iq3_s_impl(int block_size, const float * restrict x, vo
}
#define IQ3S_BLOCK_SIZE 32
size_t quantize_iq3_s(const float * src, void * dst, int nrow, int n_per_row, int64_t * hist, const float * quant_weights) {
(void)hist;
size_t quantize_iq3_s(const float * restrict src, void * restrict dst, int nrow, int n_per_row, const float * quant_weights) {
GGML_ASSERT(n_per_row%QK_K == 0);
int nblock = n_per_row/QK_K;
float scales[QK_K/IQ3S_BLOCK_SIZE];
@ -11392,7 +11341,7 @@ void quantize_row_iq3_s(const float * restrict x, void * restrict vy, int k) {
void quantize_row_iq3_s_reference(const float * restrict x, block_iq3_s * restrict y, int k) {
assert(k % QK_K == 0);
quantize_iq3_s(x, y, 1, k, NULL, NULL);
quantize_iq3_s(x, y, 1, k, NULL);
}
@ -11587,8 +11536,7 @@ static void quantize_row_iq1_s_impl(const float * restrict x, void * restrict vy
}
}
size_t quantize_iq1_s(const float * src, void * dst, int nrow, int n_per_row, int64_t * hist, const float * quant_weights) {
(void)hist;
size_t quantize_iq1_s(const float * restrict src, void * restrict dst, int nrow, int n_per_row, const float * quant_weights) {
GGML_ASSERT(n_per_row%QK_K == 0);
int nblock = n_per_row/QK_K;
char * qrow = (char *)dst;
@ -11613,7 +11561,7 @@ static inline int best_index_int8(int n, const int8_t * val, float x) {
return x - val[mu-1] < val[mu] - x ? mu-1 : mu;
}
static void quantize_row_iq4_nl_impl(const int super_block_size, const int block_size, const float * GGML_RESTRICT x,
static void quantize_row_iq4_nl_impl(const int super_block_size, const int block_size, const float * restrict x,
ggml_fp16_t * dh, uint8_t * q4, uint16_t * scales_h, uint8_t * scales_l,
float * scales, float * weight, uint8_t * L,
const int8_t * values,
@ -11721,8 +11669,7 @@ static void quantize_row_iq4_nl_impl(const int super_block_size, const int block
}
}
size_t quantize_iq4_nl(const float * src, void * dst, int nrow, int n_per_row, int64_t * hist, const float * quant_weights) {
(void)hist;
size_t quantize_iq4_nl(const float * restrict src, void * restrict dst, int nrow, int n_per_row, const float * quant_weights) {
GGML_ASSERT(n_per_row%QK4_NL == 0);
int nblock = n_per_row/QK4_NL;
char * qrow = (char *)dst;
@ -11752,14 +11699,13 @@ void quantize_row_iq4_nl(const float * restrict x, void * restrict vy, int k) {
void quantize_row_iq4_nl_reference(const float * restrict x, block_iq4_nl * restrict y, int k) {
assert(k % QK4_NL == 0);
quantize_iq4_nl(x, y, 1, k, NULL, NULL);
quantize_iq4_nl(x, y, 1, k, NULL);
}
size_t quantize_iq4_xs(const float * src, void * dst, int nrow, int n_per_row, int64_t * hist, const float * quant_weights) {
size_t quantize_iq4_xs(const float * restrict src, void * restrict dst, int nrow, int n_per_row, const float * quant_weights) {
#if QK_K == 64
return quantize_iq4_nl(src, dst, nrow, n_per_row, hist, quant_weights);
return quantize_iq4_nl(src, dst, nrow, n_per_row, quant_weights);
#else
(void)hist;
GGML_ASSERT(n_per_row%QK_K == 0);
int nblock = n_per_row/QK_K;
char * qrow = (char *)dst;
@ -11788,7 +11734,7 @@ void quantize_row_iq4_xs(const float * restrict x, void * restrict vy, int k) {
void quantize_row_iq4_xs_reference(const float * restrict x, block_iq4_xs * restrict y, int k) {
assert(k % QK_K == 0);
quantize_iq4_xs(x, y, 1, k, NULL, NULL);
quantize_iq4_xs(x, y, 1, k, NULL);
}
// =============================== 2.5625 bpw
@ -11961,8 +11907,7 @@ static void quantize_row_iq2_s_impl(const float * restrict x, void * restrict vy
}
}
size_t quantize_iq2_s(const float * src, void * dst, int nrow, int n_per_row, int64_t * hist, const float * quant_weights) {
(void)hist;
size_t quantize_iq2_s(const float * restrict src, void * restrict dst, int nrow, int n_per_row, const float * quant_weights) {
GGML_ASSERT(n_per_row%QK_K == 0);
int nblock = n_per_row/QK_K;
char * qrow = (char *)dst;
@ -11976,7 +11921,7 @@ size_t quantize_iq2_s(const float * src, void * dst, int nrow, int n_per_row, in
void quantize_row_iq2_s_reference(const float * restrict x, block_iq2_s * restrict y, int k) {
assert(k % QK_K == 0);
quantize_iq2_s(x, y, 1, k, NULL, NULL);
quantize_iq2_s(x, y, 1, k, NULL);
}
void quantize_row_iq2_s(const float * restrict x, void * restrict vy, int k) {

42
ggml-quants.h
View file

@ -261,6 +261,7 @@ void quantize_row_q4_K_reference(const float * GGML_RESTRICT x, block_q4_K * GGM
void quantize_row_q5_K_reference(const float * GGML_RESTRICT x, block_q5_K * GGML_RESTRICT y, int k);
void quantize_row_q6_K_reference(const float * GGML_RESTRICT x, block_q6_K * GGML_RESTRICT y, int k);
void quantize_row_q8_K_reference(const float * GGML_RESTRICT x, block_q8_K * GGML_RESTRICT y, int k);
void quantize_row_iq3_xxs_reference(const float * GGML_RESTRICT x, block_iq3_xxs * GGML_RESTRICT y, int k);
void quantize_row_iq4_nl_reference (const float * GGML_RESTRICT x, block_iq4_nl * GGML_RESTRICT y, int k);
void quantize_row_iq4_xs_reference (const float * GGML_RESTRICT x, block_iq4_xs * GGML_RESTRICT y, int k);
@ -280,6 +281,7 @@ void quantize_row_q4_K(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, in
void quantize_row_q5_K(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int k);
void quantize_row_q6_K(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int k);
void quantize_row_q8_K(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int k);
void quantize_row_iq3_xxs(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int k);
void quantize_row_iq4_nl (const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int k);
void quantize_row_iq4_xs (const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int k);
@ -300,6 +302,7 @@ void dequantize_row_q4_K(const block_q4_K * GGML_RESTRICT x, float * GGML_RESTRI
void dequantize_row_q5_K(const block_q5_K * GGML_RESTRICT x, float * GGML_RESTRICT y, int k);
void dequantize_row_q6_K(const block_q6_K * GGML_RESTRICT x, float * GGML_RESTRICT y, int k);
void dequantize_row_q8_K(const block_q8_K * GGML_RESTRICT x, float * GGML_RESTRICT y, int k);
void dequantize_row_iq2_xxs(const block_iq2_xxs * GGML_RESTRICT x, float * GGML_RESTRICT y, int k);
void dequantize_row_iq2_xs (const block_iq2_xs * GGML_RESTRICT x, float * GGML_RESTRICT y, int k);
void dequantize_row_iq2_s (const block_iq2_s * GGML_RESTRICT x, float * GGML_RESTRICT y, int k);
@ -321,6 +324,7 @@ void ggml_vec_dot_q3_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
void ggml_vec_dot_q4_K_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 ggml_vec_dot_q5_K_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 ggml_vec_dot_q6_K_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 ggml_vec_dot_iq2_xxs_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 ggml_vec_dot_iq2_xs_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 ggml_vec_dot_iq2_s_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);
@ -330,26 +334,26 @@ void ggml_vec_dot_iq4_nl_q8_0 (int n, float * GGML_RESTRICT s, size_t bs, const
void ggml_vec_dot_iq4_xs_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 ggml_vec_dot_iq3_s_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);
//
// Quantization utilizing an importance matrix (a.k.a. "Activation aWare Quantization")
//
size_t quantize_iq2_xxs(const float * src, void * dst, int nrows, int n_per_row, int64_t * hist, const float * imatrix);
size_t quantize_iq2_xs (const float * src, void * dst, int nrows, int n_per_row, int64_t * hist, const float * imatrix);
size_t quantize_iq2_s (const float * src, void * dst, int nrows, int n_per_row, int64_t * hist, const float * imatrix);
size_t quantize_iq3_xxs(const float * src, void * dst, int nrows, int n_per_row, int64_t * hist, const float * imatrix);
size_t quantize_iq1_s (const float * src, void * dst, int nrows, int n_per_row, int64_t * hist, const float * imatrix);
size_t quantize_iq4_nl (const float * src, void * dst, int nrows, int n_per_row, int64_t * hist, const float * imatrix);
size_t quantize_iq4_xs (const float * src, void * dst, int nrows, int n_per_row, int64_t * hist, const float * imatrix);
size_t quantize_iq3_s (const float * src, void * dst, int nrows, int n_per_row, int64_t * hist, const float * imatrix);
size_t quantize_q2_K (const float * src, void * dst, int nrows, int n_per_row, int64_t * hist, const float * imatrix);
size_t quantize_q3_K (const float * src, void * dst, int nrows, int n_per_row, int64_t * hist, const float * imatrix);
size_t quantize_q4_K (const float * src, void * dst, int nrows, int n_per_row, int64_t * hist, const float * imatrix);
size_t quantize_q5_K (const float * src, void * dst, int nrows, int n_per_row, int64_t * hist, const float * imatrix);
size_t quantize_q6_K (const float * src, void * dst, int nrows, int n_per_row, int64_t * hist, const float * imatrix);
size_t quantize_q4_0 (const float * src, void * dst, int nrows, int n_per_row, int64_t * hist, const float * imatrix);
size_t quantize_q4_1 (const float * src, void * dst, int nrows, int n_per_row, int64_t * hist, const float * imatrix);
size_t quantize_q5_0 (const float * src, void * dst, int nrows, int n_per_row, int64_t * hist, const float * imatrix);
size_t quantize_q5_1 (const float * src, void * dst, int nrows, int n_per_row, int64_t * hist, const float * imatrix);
size_t quantize_iq2_xxs(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
size_t quantize_iq2_xs (const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
size_t quantize_iq2_s (const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
size_t quantize_iq3_xxs(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
size_t quantize_iq1_s (const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
size_t quantize_iq4_nl (const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
size_t quantize_iq4_xs (const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
size_t quantize_iq3_s (const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
size_t quantize_q2_K(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
size_t quantize_q3_K(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
size_t quantize_q4_K(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
size_t quantize_q5_K(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
size_t quantize_q6_K(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
size_t quantize_q4_0(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
size_t quantize_q4_1(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
size_t quantize_q5_0(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
size_t quantize_q5_1(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
size_t quantize_q8_0(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
void iq2xs_init_impl(enum ggml_type type);
void iq2xs_free_impl(enum ggml_type type);

40
ggml-vulkan.cpp
View file

@ -4102,45 +4102,7 @@ static void ggml_vk_test_transfer(ggml_backend_vk_context * ctx, size_t ne, bool
}
static void ggml_vk_quantize_data(const float * from, void * to, size_t ne, ggml_type quant) {
std::vector<int64_t> hist_cur(1 << 4, 0);
switch(quant) {
case GGML_TYPE_F32:
memcpy(to, from, sizeof(float) * ne);
break;
case GGML_TYPE_Q4_0:
ggml_quantize_q4_0(from, to, ne, ne, hist_cur.data());
break;
case GGML_TYPE_Q4_1:
ggml_quantize_q4_1(from, to, ne, ne, hist_cur.data());
break;
case GGML_TYPE_Q5_0:
ggml_quantize_q5_0(from, to, ne, ne, hist_cur.data());
break;
case GGML_TYPE_Q5_1:
ggml_quantize_q5_1(from, to, ne, ne, hist_cur.data());
break;
case GGML_TYPE_Q8_0:
ggml_quantize_q8_0(from, to, ne, ne, hist_cur.data());
break;
case GGML_TYPE_Q2_K:
ggml_quantize_q2_K(from, to, ne, ne, hist_cur.data());
break;
case GGML_TYPE_Q3_K:
ggml_quantize_q3_K(from, to, ne, ne, hist_cur.data());
break;
case GGML_TYPE_Q4_K:
ggml_quantize_q4_K(from, to, ne, ne, hist_cur.data());
break;
case GGML_TYPE_Q5_K:
ggml_quantize_q5_K(from, to, ne, ne, hist_cur.data());
break;
case GGML_TYPE_Q6_K:
ggml_quantize_q6_K(from, to, ne, ne, hist_cur.data());
break;
default:
GGML_ASSERT(false);
}
ggml_quantize_chunk(quant, from, to, 0, 1, ne, nullptr);
}
static void ggml_vk_test_dequant(ggml_backend_vk_context * ctx, size_t ne, ggml_type quant) {

339
ggml.c
View file

@ -20159,133 +20159,6 @@ void ggml_quantize_free(void) {
ggml_critical_section_end();
}
size_t ggml_quantize_q4_0(const float * src, void * dst, int n, int k, int64_t * hist) {
assert(k % QK4_0 == 0);
const int nb = k / QK4_0;
for (int b = 0; b < n; b += k) {
block_q4_0 * restrict y = (block_q4_0 *) dst + b/QK4_0;
quantize_row_q4_0_reference(src + b, y, k);
for (int i = 0; i < nb; i++) {
for (int j = 0; j < QK4_0; j += 2) {
const uint8_t vi0 = y[i].qs[j/2] & 0x0F;
const uint8_t vi1 = y[i].qs[j/2] >> 4;
hist[vi0]++;
hist[vi1]++;
}
}
}
return (n/QK4_0*sizeof(block_q4_0));
}
size_t ggml_quantize_q4_1(const float * src, void * dst, int n, int k, int64_t * hist) {
assert(k % QK4_1 == 0);
const int nb = k / QK4_1;
for (int b = 0; b < n; b += k) {
block_q4_1 * restrict y = (block_q4_1 *) dst + b/QK4_1;
quantize_row_q4_1_reference(src + b, y, k);
for (int i = 0; i < nb; i++) {
for (int j = 0; j < QK4_1; j += 2) {
const uint8_t vi0 = y[i].qs[j/2] & 0x0F;
const uint8_t vi1 = y[i].qs[j/2] >> 4;
hist[vi0]++;
hist[vi1]++;
}
}
}
return (n/QK4_1*sizeof(block_q4_1));
}
size_t ggml_quantize_q5_0(const float * src, void * dst, int n, int k, int64_t * hist) {
assert(k % QK5_0 == 0);
const int nb = k / QK5_0;
for (int b = 0; b < n; b += k) {
block_q5_0 * restrict y = (block_q5_0 *)dst + b/QK5_0;
quantize_row_q5_0_reference(src + b, y, k);
for (int i = 0; i < nb; i++) {
uint32_t qh;
memcpy(&qh, &y[i].qh, sizeof(qh));
for (int j = 0; j < QK5_0; j += 2) {
const uint8_t vh0 = ((qh & (1u << (j/2 + 0 ))) >> (j/2 + 0 )) << 4;
const uint8_t vh1 = ((qh & (1u << (j/2 + 16))) >> (j/2 + 12));
// cast to 16 bins
const uint8_t vi0 = ((y[i].qs[j/2] & 0x0F) | vh0) / 2;
const uint8_t vi1 = ((y[i].qs[j/2] >> 4) | vh1) / 2;
hist[vi0]++;
hist[vi1]++;
}
}
}
return (n/QK5_0*sizeof(block_q5_0));
}
size_t ggml_quantize_q5_1(const float * src, void * dst, int n, int k, int64_t * hist) {
assert(k % QK5_1 == 0);
const int nb = k / QK5_1;
for (int b = 0; b < n; b += k) {
block_q5_1 * restrict y = (block_q5_1 *)dst + b/QK5_1;
quantize_row_q5_1_reference(src + b, y, k);
for (int i = 0; i < nb; i++) {
uint32_t qh;
memcpy(&qh, &y[i].qh, sizeof(qh));
for (int j = 0; j < QK5_1; j += 2) {
const uint8_t vh0 = ((qh & (1u << (j/2 + 0 ))) >> (j/2 + 0 )) << 4;
const uint8_t vh1 = ((qh & (1u << (j/2 + 16))) >> (j/2 + 12));
// cast to 16 bins
const uint8_t vi0 = ((y[i].qs[j/2] & 0x0F) | vh0) / 2;
const uint8_t vi1 = ((y[i].qs[j/2] >> 4) | vh1) / 2;
hist[vi0]++;
hist[vi1]++;
}
}
}
return (n/QK5_1*sizeof(block_q5_1));
}
size_t ggml_quantize_q8_0(const float * src, void * dst, int n, int k, int64_t * hist) {
assert(k % QK8_0 == 0);
const int nb = k / QK8_0;
for (int b = 0; b < n; b += k) {
block_q8_0 * restrict y = (block_q8_0 *)dst + b/QK8_0;
quantize_row_q8_0_reference(src + b, y, k);
for (int i = 0; i < nb; i++) {
for (int j = 0; j < QK8_0; ++j) {
const int8_t vi = y[i].qs[j];
hist[vi/16 + 8]++;
}
}
}
return (n/QK8_0*sizeof(block_q8_0));
}
bool ggml_quantize_requires_imatrix(enum ggml_type type) {
return
type == GGML_TYPE_IQ2_XXS ||
@ -20293,177 +20166,52 @@ bool ggml_quantize_requires_imatrix(enum ggml_type type) {
type == GGML_TYPE_IQ1_S;
}
size_t ggml_quantize_chunk(enum ggml_type type, const float * src, void * dst, int start,
int nrows, int n_per_row, int64_t * hist, const float * imatrix) {
size_t ggml_quantize_chunk(
enum ggml_type type,
const float * src,
void * dst,
int start,
int nrows,
int n_per_row,
const float * imatrix) {
const int n = nrows * n_per_row;
if (ggml_quantize_requires_imatrix(type)) {
GGML_ASSERT(imatrix != NULL);
}
GGML_ASSERT(start % type_traits[type].blck_size == 0);
GGML_ASSERT(start % n_per_row == 0);
ggml_quantize_init(type); // this is noop if already initialized
const size_t start_row = start / n_per_row;
const size_t row_size = ggml_row_size(type, n_per_row);
size_t result = 0;
int n = nrows * n_per_row;
switch (type) {
case GGML_TYPE_Q4_0:
{
GGML_ASSERT(start % QK4_0 == 0);
GGML_ASSERT(start % n_per_row == 0);
size_t start_row = start / n_per_row;
size_t row_size = ggml_row_size(type, n_per_row);
result = quantize_q4_0(src + start, (char *)dst + start_row * row_size, nrows, n_per_row, hist, imatrix);
GGML_ASSERT(result == row_size * nrows);
} break;
case GGML_TYPE_Q4_1:
{
GGML_ASSERT(start % QK4_1 == 0);
GGML_ASSERT(start % n_per_row == 0);
size_t start_row = start / n_per_row;
size_t row_size = ggml_row_size(type, n_per_row);
result = quantize_q4_1(src + start, (char *)dst + start_row * row_size, nrows, n_per_row, hist, imatrix);
GGML_ASSERT(result == row_size * nrows);
} break;
case GGML_TYPE_Q5_0:
{
GGML_ASSERT(start % QK5_0 == 0);
GGML_ASSERT(start % n_per_row == 0);
size_t start_row = start / n_per_row;
size_t row_size = ggml_row_size(type, n_per_row);
result = quantize_q5_0(src + start, (char *)dst + start_row * row_size, nrows, n_per_row, hist, imatrix);
GGML_ASSERT(result == row_size * nrows);
} break;
case GGML_TYPE_Q5_1:
{
GGML_ASSERT(start % QK5_1 == 0);
GGML_ASSERT(start % n_per_row == 0);
size_t start_row = start / n_per_row;
size_t row_size = ggml_row_size(type, n_per_row);
result = quantize_q5_1(src + start, (char *)dst + start_row * row_size, nrows, n_per_row, hist, imatrix);
GGML_ASSERT(result == row_size * nrows);
} break;
case GGML_TYPE_Q8_0:
{
GGML_ASSERT(start % QK8_0 == 0);
block_q8_0 * block = (block_q8_0*)dst + start / QK8_0;
result = ggml_quantize_q8_0(src + start, block, n, n, hist);
} break;
case GGML_TYPE_Q2_K:
{
GGML_ASSERT(start % QK_K == 0);
GGML_ASSERT(start % n_per_row == 0);
size_t start_row = start / n_per_row;
size_t row_size = ggml_row_size(type, n_per_row);
result = quantize_q2_K(src + start, (char *)dst + start_row * row_size, nrows, n_per_row, hist, imatrix);
GGML_ASSERT(result == row_size * nrows);
} break;
case GGML_TYPE_Q3_K:
{
GGML_ASSERT(start % QK_K == 0);
GGML_ASSERT(start % n_per_row == 0);
size_t start_row = start / n_per_row;
size_t row_size = ggml_row_size(type, n_per_row);
result = quantize_q3_K(src + start, (char *)dst + start_row * row_size, nrows, n_per_row, hist, imatrix);
GGML_ASSERT(result == row_size * nrows);
} break;
case GGML_TYPE_Q4_K:
{
GGML_ASSERT(start % QK_K == 0);
GGML_ASSERT(start % n_per_row == 0);
size_t start_row = start / n_per_row;
size_t row_size = ggml_row_size(type, n_per_row);
result = quantize_q4_K(src + start, (char *)dst + start_row * row_size, nrows, n_per_row, hist, imatrix);
GGML_ASSERT(result == row_size * nrows);
} break;
case GGML_TYPE_Q5_K:
{
GGML_ASSERT(start % QK_K == 0);
GGML_ASSERT(start % n_per_row == 0);
size_t start_row = start / n_per_row;
size_t row_size = ggml_row_size(type, n_per_row);
result = quantize_q5_K(src + start, (char *)dst + start_row * row_size, nrows, n_per_row, hist, imatrix);
GGML_ASSERT(result == row_size * nrows);
} break;
case GGML_TYPE_Q6_K:
{
GGML_ASSERT(start % QK_K == 0);
GGML_ASSERT(start % n_per_row == 0);
size_t start_row = start / n_per_row;
size_t row_size = ggml_row_size(type, n_per_row);
result = quantize_q6_K(src + start, (char *)dst + start_row * row_size, nrows, n_per_row, hist, imatrix);
GGML_ASSERT(result == row_size * nrows);
} break;
case GGML_TYPE_IQ2_XXS:
{
GGML_ASSERT(start % QK_K == 0);
GGML_ASSERT(start % n_per_row == 0);
GGML_ASSERT(imatrix);
size_t start_row = start / n_per_row;
size_t row_size = ggml_row_size(type, n_per_row);
result = quantize_iq2_xxs(src + start, (char *)dst + start_row * row_size, nrows, n_per_row, hist, imatrix);
GGML_ASSERT(result == row_size * nrows);
} break;
case GGML_TYPE_IQ2_XS:
{
GGML_ASSERT(start % QK_K == 0);
GGML_ASSERT(start % n_per_row == 0);
GGML_ASSERT(imatrix);
size_t start_row = start / n_per_row;
size_t row_size = ggml_row_size(type, n_per_row);
result = quantize_iq2_xs(src + start, (char *)dst + start_row * row_size, nrows, n_per_row, hist, imatrix);
GGML_ASSERT(result == row_size * nrows);
} break;
case GGML_TYPE_IQ3_XXS:
{
GGML_ASSERT(start % QK_K == 0);
GGML_ASSERT(start % n_per_row == 0);
size_t start_row = start / n_per_row;
size_t row_size = ggml_row_size(type, n_per_row);
result = quantize_iq3_xxs(src + start, (char *)dst + start_row * row_size, nrows, n_per_row, hist, imatrix);
GGML_ASSERT(result == row_size * nrows);
} break;
case GGML_TYPE_IQ3_S:
{
GGML_ASSERT(start % QK_K == 0);
GGML_ASSERT(start % n_per_row == 0);
size_t start_row = start / n_per_row;
size_t row_size = ggml_row_size(type, n_per_row);
result = quantize_iq3_s(src + start, (char *)dst + start_row * row_size, nrows, n_per_row, hist, imatrix);
GGML_ASSERT(result == row_size * nrows);
} break;
case GGML_TYPE_IQ2_S:
{
GGML_ASSERT(start % QK_K == 0);
GGML_ASSERT(start % n_per_row == 0);
size_t start_row = start / n_per_row;
size_t row_size = ggml_row_size(type, n_per_row);
result = quantize_iq2_s(src + start, (char *)dst + start_row * row_size, nrows, n_per_row, hist, imatrix);
GGML_ASSERT(result == row_size * nrows);
} break;
case GGML_TYPE_IQ1_S:
{
GGML_ASSERT(start % QK_K == 0);
GGML_ASSERT(start % n_per_row == 0);
size_t start_row = start / n_per_row;
size_t row_size = ggml_row_size(type, n_per_row);
result = quantize_iq1_s(src + start, (char *)dst + start_row * row_size, nrows, n_per_row, hist, imatrix);
GGML_ASSERT(result == row_size * nrows);
} break;
case GGML_TYPE_IQ4_NL:
case GGML_TYPE_Q4_0: result = quantize_q4_0(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
case GGML_TYPE_Q4_1: result = quantize_q4_1(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
case GGML_TYPE_Q5_0: result = quantize_q5_0(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
case GGML_TYPE_Q5_1: result = quantize_q5_1(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
case GGML_TYPE_Q8_0: result = quantize_q8_0(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
case GGML_TYPE_Q2_K: result = quantize_q2_K(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
case GGML_TYPE_Q3_K: result = quantize_q3_K(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
case GGML_TYPE_Q4_K: result = quantize_q4_K(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
case GGML_TYPE_Q5_K: result = quantize_q5_K(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
case GGML_TYPE_Q6_K: result = quantize_q6_K(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
case GGML_TYPE_IQ2_XXS: result = quantize_iq2_xxs(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
case GGML_TYPE_IQ2_XS: result = quantize_iq2_xs (src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
case GGML_TYPE_IQ3_XXS: result = quantize_iq3_xxs(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
case GGML_TYPE_IQ3_S: result = quantize_iq3_s (src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
case GGML_TYPE_IQ2_S: result = quantize_iq2_s (src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
case GGML_TYPE_IQ1_S: result = quantize_iq1_s (src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
case GGML_TYPE_IQ4_NL: result = quantize_iq4_nl (src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
#if QK_K == 64
case GGML_TYPE_IQ4_XS:
#endif
{
GGML_ASSERT(start % QK4_NL == 0);
GGML_ASSERT(start % n_per_row == 0);
size_t start_row = start / n_per_row;
size_t row_size = ggml_row_size(type, n_per_row);
result = quantize_iq4_nl(src + start, (char *)dst + start_row * row_size, nrows, n_per_row, hist, imatrix);
GGML_ASSERT(result == row_size * nrows);
} break;
#if QK_K != 64
case GGML_TYPE_IQ4_XS:
{
GGML_ASSERT(start % QK_K == 0);
GGML_ASSERT(start % n_per_row == 0);
size_t start_row = start / n_per_row;
size_t row_size = ggml_row_size(type, n_per_row);
result = quantize_iq4_xs(src + start, (char *)dst + start_row * row_size, nrows, n_per_row, hist, imatrix);
GGML_ASSERT(result == row_size * nrows);
} break;
case GGML_TYPE_IQ4_XS: result = quantize_iq4_nl (src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
#else
case GGML_TYPE_IQ4_XS: result = quantize_iq4_xs (src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
#endif
case GGML_TYPE_F16:
{
@ -20480,6 +20228,9 @@ size_t ggml_quantize_chunk(enum ggml_type type, const float * src, void * dst, i
default:
assert(false);
}
GGML_ASSERT(result == nrows * row_size);
return result;
}

23
ggml.h
View file

@ -2194,25 +2194,18 @@ extern "C" {
GGML_API void ggml_quantize_init(enum ggml_type type);
GGML_API void ggml_quantize_free(void);
// TODO: these would probably get removed in favor of the more general ggml_quantize_chunk
GGML_API size_t ggml_quantize_q4_0(const float * src, void * dst, int n, int k, int64_t * hist);
GGML_API size_t ggml_quantize_q4_1(const float * src, void * dst, int n, int k, int64_t * hist);
GGML_API size_t ggml_quantize_q5_0(const float * src, void * dst, int n, int k, int64_t * hist);
GGML_API size_t ggml_quantize_q5_1(const float * src, void * dst, int n, int k, int64_t * hist);
GGML_API size_t ggml_quantize_q8_0(const float * src, void * dst, int n, int k, int64_t * hist);
GGML_API size_t ggml_quantize_q2_K(const float * src, void * dst, int n, int k, int64_t * hist);
GGML_API size_t ggml_quantize_q3_K(const float * src, void * dst, int n, int k, int64_t * hist);
GGML_API size_t ggml_quantize_q4_K(const float * src, void * dst, int n, int k, int64_t * hist);
GGML_API size_t ggml_quantize_q5_K(const float * src, void * dst, int n, int k, int64_t * hist);
GGML_API size_t ggml_quantize_q6_K(const float * src, void * dst, int n, int k, int64_t * hist);
// some quantization type cannot be used without an importance matrix
GGML_API bool ggml_quantize_requires_imatrix(enum ggml_type type);
// calls ggml_quantize_init internally (i.e. can allocate memory)
GGML_API size_t ggml_quantize_chunk(enum ggml_type type, const float * src, void * dst,
int start, int nrows, int n_per_row, int64_t * hist, const float * imatrix);
GGML_API size_t ggml_quantize_chunk(
enum ggml_type type,
const float * src,
void * dst,
int start,
int nrows,
int n_per_row,
const float * imatrix);
//
// gguf

48
llama.cpp
View file

@ -11890,17 +11890,16 @@ static ggml_type get_k_quant_type(quantize_state_internal & qs, ggml_type new_ty
return new_type;
}
static int32_t llama_tensor_quantize_internal(enum ggml_type new_type, const float * f32_data, void * new_data, const int chunk_size, int nrows, int n_per_row, int64_t * hist_cur, const float * imatrix, std::vector<std::thread> & workers, const int nthread) {
static int32_t llama_tensor_quantize_internal(enum ggml_type new_type, const float * f32_data, void * new_data, const int chunk_size, int nrows, int n_per_row, const float * imatrix, std::vector<std::thread> & workers, const int nthread) {
std::mutex mutex;
int counter = 0;
size_t new_size = 0;
if (nthread < 2) {
// single-thread
return ggml_quantize_chunk(new_type, f32_data, new_data, 0, nrows, n_per_row, hist_cur, imatrix);
return ggml_quantize_chunk(new_type, f32_data, new_data, 0, nrows, n_per_row, imatrix);
}
auto compute = [&mutex, &counter, &hist_cur, &new_size, new_type, f32_data, new_data, chunk_size,
auto compute = [&mutex, &counter, &new_size, new_type, f32_data, new_data, chunk_size,
nrows, n_per_row, imatrix]() {
std::array<int64_t, 1 << 4> local_hist = {};
const int nrows_per_chunk = chunk_size / n_per_row;
size_t local_size = 0;
while (true) {
@ -11908,17 +11907,13 @@ static int32_t llama_tensor_quantize_internal(enum ggml_type new_type, const flo
int first_row = counter; counter += nrows_per_chunk;
if (first_row >= nrows) {
if (local_size > 0) {
for (int j=0; j<int(local_hist.size()); ++j) {
hist_cur[j] += local_hist[j];
}
new_size += local_size;
}
break;
}
lock.unlock();
const int this_nrow = std::min(nrows - first_row, nrows_per_chunk);
local_size += ggml_quantize_chunk(new_type, f32_data, new_data,
first_row * n_per_row, this_nrow, n_per_row, local_hist.data(), imatrix);
local_size += ggml_quantize_chunk(new_type, f32_data, new_data, first_row * n_per_row, this_nrow, n_per_row, imatrix);
}
};
for (int it = 0; it < nthread - 1; ++it) {
@ -12041,7 +12036,6 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
size_t total_size_org = 0;
size_t total_size_new = 0;
std::vector<int64_t> hist_all(1 << 4, 0);
std::vector<std::thread> workers;
workers.reserve(nthread);
@ -12175,7 +12169,6 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
work.resize(nelements * 4); // upper bound on size
}
new_data = work.data();
std::array<int64_t, 1 << 4> hist_cur = {};
const int n_per_row = tensor->ne[0];
const int nrows = nelements / n_per_row;
@ -12185,22 +12178,9 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
const int nchunk = (nelements + chunk_size - 1)/chunk_size;
const int nthread_use = nthread > 1 ? std::max(1, std::min(nthread, nchunk)) : 1;
new_size = llama_tensor_quantize_internal(new_type, f32_data, new_data, chunk_size, nrows, n_per_row, hist_cur.data(), imatrix, workers, nthread_use);
new_size = llama_tensor_quantize_internal(new_type, f32_data, new_data, chunk_size, nrows, n_per_row, imatrix, workers, nthread_use);
LLAMA_LOG_INFO("size = %8.2f MiB -> %8.2f MiB", ggml_nbytes(tensor)/1024.0/1024.0, new_size/1024.0/1024.0);
int64_t tot_count = 0;
for (size_t i = 0; i < hist_cur.size(); i++) {
hist_all[i] += hist_cur[i];
tot_count += hist_cur[i];
}
if (tot_count > 0) {
LLAMA_LOG_INFO(" | hist: ");
for (size_t i = 0; i < hist_cur.size(); i++) {
LLAMA_LOG_INFO("%5.3f ", hist_cur[i] / float(nelements));
}
}
LLAMA_LOG_INFO("\n");
LLAMA_LOG_INFO("size = %8.2f MiB -> %8.2f MiB\n", ggml_nbytes(tensor)/1024.0/1024.0, new_size/1024.0/1024.0);
}
total_size_org += ggml_nbytes(tensor);
total_size_new += new_size;
@ -12229,22 +12209,6 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
LLAMA_LOG_INFO("%s: model size = %8.2f MB\n", __func__, total_size_org/1024.0/1024.0);
LLAMA_LOG_INFO("%s: quant size = %8.2f MB\n", __func__, total_size_new/1024.0/1024.0);
// print histogram for all tensors
{
int64_t sum_all = 0;
for (size_t i = 0; i < hist_all.size(); i++) {
sum_all += hist_all[i];
}
if (sum_all > 0) {
LLAMA_LOG_INFO("%s: hist: ", __func__);
for (size_t i = 0; i < hist_all.size(); i++) {
LLAMA_LOG_INFO("%5.3f ", hist_all[i] / float(sum_all));
}
LLAMA_LOG_INFO("\n");
}
}
if (qs.n_fallback > 0) {
LLAMA_LOG_WARN("%s: WARNING: %d of %d tensor(s) incompatible with k-quants and required fallback quantization\n",
__func__, qs.n_fallback, qs.n_k_quantized + qs.n_fallback);

3
tests/test-backend-ops.cpp
View file

@ -53,7 +53,6 @@ static void init_tensor_uniform(ggml_tensor * tensor, float min = -1.0f, float m
} else if (ggml_is_quantized(tensor->type) || tensor->type == GGML_TYPE_F16) {
GGML_ASSERT(size % ggml_blck_size(tensor->type) == 0);
std::vector<uint8_t> dataq(ggml_row_size(tensor->type, size));
int64_t hist[16];
std::vector<float> imatrix(tensor->ne[0], 1.0f); // dummy importance matrix
const float * im = imatrix.data();
if (!ggml_quantize_requires_imatrix(tensor->type)) {
@ -63,7 +62,7 @@ static void init_tensor_uniform(ggml_tensor * tensor, float min = -1.0f, float m
im = nullptr;
}
}
ggml_quantize_chunk(tensor->type, data.data(), dataq.data(), 0, size/tensor->ne[0], tensor->ne[0], hist, im);
ggml_quantize_chunk(tensor->type, data.data(), dataq.data(), 0, size/tensor->ne[0], tensor->ne[0], im);
ggml_backend_tensor_set(tensor, dataq.data(), 0, dataq.size());
} else if (tensor->type == GGML_TYPE_I8 || tensor->type == GGML_TYPE_I16 || tensor->type == GGML_TYPE_I32) {
// This is going to create some weird integers though.