Mirrors/llama.cpp
1
0
Fork 0
mirror of https://github.com/ggerganov/llama.cpp.git synced 2024-10-29 22:20:15 +01:00
Code Issues Packages Projects Releases Wiki Activity

ggml : use F16 instead of F32 in Q4_0, Q4_1, Q8_0 (#1508)

Browse Source 
* ggml : use F16 instead of F32 in Q4_0, Q4_1 and Q8_0

* llama : bump LLAMA_FILE_VERSION to 3

* cuda : update Q4 and Q8 dequantize kernels

* ggml : fix AVX dot products

* readme : update performance table + hot topics
This commit is contained in:
Georgi Gerganov 2023-05-19 22:17:18 +03:00 committed by GitHub
parent 6986c7835a
commit 2d5db48371
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
6 changed files with 109 additions and 102 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

21
README.md
View File

@ -9,6 +9,7 @@ Inference of [LLaMA](https://arxiv.org/abs/2302.13971) model in pure C/C++
**Hot topics:**
- Quantization formats `Q4` and `Q8` have changed again (19 May) - [(info)](https://github.com/ggerganov/llama.cpp/pull/1508)
- Quantization formats `Q4` and `Q5` have changed - requantize any old models [(info)](https://github.com/ggerganov/llama.cpp/pull/1405)
- [Roadmap May 2023](https://github.com/ggerganov/llama.cpp/discussions/1220)
@ -334,16 +335,16 @@ Several quantization methods are supported. They differ in the resulting model d
| Model | Measure | F16 | Q4_0 | Q4_1 | Q5_0 | Q5_1 | Q8_0 |
|------:|--------------|-------:|-------:|-------:|-------:|-------:|-------:|
| 7B | perplexity | 5.9066 | 6.1565 | 6.0910 | 5.9862 | 5.9481 | 5.9069 |
| 7B | file size | 13.0G | 4.0G | 4.8G | 4.4G | 4.8G | 7.1G |
| 7B | ms/tok @ 4th | 128 | 50 | 54 | 75 | 83 | 75 |
| 7B | ms/tok @ 8th | 123 | 44 | 52 | 53 | 58 | 72 |
| 7B | bits/weight | 16.0 | 5.0 | 6.0 | 5.5 | 6.0 | 9.0 |
| 13B | perplexity | 5.2543 | 5.3860 | 5.3607 | 5.2856 | 5.2706 | 5.2548 |
| 13B | file size | 25.0G | 7.6G | 9.1G | 8.4G | 9.1G | 14G |
| 13B | ms/tok @ 4th | 239 | 93 | 101 | 150 | 164 | 141 |
| 13B | ms/tok @ 8th | 240 | 81 | 96 | 96 | 104 | 136 |
| 13B | bits/weight | 16.0 | 5.0 | 6.0 | 5.5 | 6.0 | 9.0 |
| 7B | perplexity | 5.9066 | 6.1565 | 6.0912 | 5.9862 | 5.9481 | 5.9070 |
| 7B | file size | 13.0G | 3.5G | 3.9G | 4.3G | 4.7G | 6.7G |
| 7B | ms/tok @ 4th | 127 | 55 | 54 | 76 | 83 | 72 |
| 7B | ms/tok @ 8th | 122 | 43 | 45 | 52 | 56 | 67 |
| 7B | bits/weight | 16.0 | 4.5 | 5.0 | 5.5 | 6.0 | 8.5 |
| 13B | perplexity | 5.2543 | 5.3860 | 5.3608 | 5.2856 | 5.2706 | 5.2548 |
| 13B | file size | 25.0G | 6.8G | 7.6G | 8.3G | 9.1G | 13G |
| 13B | ms/tok @ 4th | - | 103 | 105 | 148 | 160 | 131 |
| 13B | ms/tok @ 8th | - | 73 | 82 | 98 | 105 | 128 |
| 13B | bits/weight | 16.0 | 4.5 | 5.0 | 5.5 | 6.0 | 8.5 |
### Perplexity (measuring model quality)

14
ggml-cuda.cu
View File

@ -42,19 +42,19 @@ typedef void (*dequantize_mul_mat_vec_cuda_t)(const void * vx, const float * y,
#define QK4_0 32
#define QR4_0 2
typedef struct {
float d; // delta
half d; // delta
uint8_t qs[QK4_0 / 2]; // nibbles / quants
} block_q4_0;
static_assert(sizeof(block_q4_0) == sizeof(float) + QK4_0 / 2, "wrong q4_0 block size/padding");
static_assert(sizeof(block_q4_0) == sizeof(ggml_fp16_t) + QK4_0 / 2, "wrong q4_0 block size/padding");
#define QK4_1 32
#define QR4_1 2
typedef struct {
float d; // delta
float m; // min
half d; // delta
half m; // min
uint8_t qs[QK4_1 / 2]; // nibbles / quants
} block_q4_1;
static_assert(sizeof(block_q4_1) == sizeof(float) * 2 + QK4_1 / 2, "wrong q4_1 block size/padding");
static_assert(sizeof(block_q4_1) == sizeof(ggml_fp16_t) * 2 + QK4_1 / 2, "wrong q4_1 block size/padding");
#define QK5_0 32
#define QR5_0 2
@ -78,10 +78,10 @@ static_assert(sizeof(block_q5_1) == 2 * sizeof(ggml_fp16_t) + sizeof(uint32_t) +
#define QK8_0 32
#define QR8_0 1
typedef struct {
float d; // delta
half d; // delta
int8_t qs[QK8_0]; // quants
} block_q8_0;
static_assert(sizeof(block_q8_0) == sizeof(float) + QK8_0, "wrong q8_0 block size/padding");
static_assert(sizeof(block_q8_0) == sizeof(ggml_fp16_t) + QK8_0, "wrong q8_0 block size/padding");
#define CUDA_DEQUANTIZE_BLOCK_SIZE 256
#define CUDA_DMMV_BLOCK_SIZE 32 // dmmv = dequantize_mul_mat_vec

154
ggml.c
View File

@ -769,18 +769,18 @@ int32x4_t vcvtnq_s32_f32(float32x4_t v) {
#define QK4_0 32
typedef struct {
float d; // delta
ggml_fp16_t d; // delta
uint8_t qs[QK4_0 / 2]; // nibbles / quants
} block_q4_0;
static_assert(sizeof(block_q4_0) == sizeof(float) + QK4_0 / 2, "wrong q4_0 block size/padding");
static_assert(sizeof(block_q4_0) == sizeof(ggml_fp16_t) + QK4_0 / 2, "wrong q4_0 block size/padding");
#define QK4_1 32
typedef struct {
float d; // delta
float m; // min
ggml_fp16_t d; // delta
ggml_fp16_t m; // min
uint8_t qs[QK4_1 / 2]; // nibbles / quants
} block_q4_1;
static_assert(sizeof(block_q4_1) == 2 * sizeof(float) + QK4_1 / 2, "wrong q4_1 block size/padding");
static_assert(sizeof(block_q4_1) == 2 * sizeof(ggml_fp16_t) + QK4_1 / 2, "wrong q4_1 block size/padding");
#define QK5_0 32
typedef struct {
@ -801,16 +801,16 @@ static_assert(sizeof(block_q5_1) == 2 * sizeof(ggml_fp16_t) + sizeof(uint32_t) +
#define QK8_0 32
typedef struct {
float d; // delta
int8_t qs[QK8_0]; // quants
ggml_fp16_t d; // delta
int8_t qs[QK8_0]; // quants
} block_q8_0;
static_assert(sizeof(block_q8_0) == sizeof(float) + QK8_0, "wrong q8_0 block size/padding");
static_assert(sizeof(block_q8_0) == sizeof(ggml_fp16_t) + QK8_0, "wrong q8_0 block size/padding");
#define QK8_1 32
typedef struct {
float d; // delta
float s; // d * sum(qs[i])
int8_t qs[QK8_1]; // quants
float d; // delta
float s; // d * sum(qs[i])
int8_t qs[QK8_1]; // quants
} block_q8_1;
static_assert(sizeof(block_q8_1) == 2*sizeof(float) + QK8_1, "wrong q8_1 block size/padding");
@ -837,7 +837,7 @@ static void quantize_row_q4_0_reference(const float * restrict x, block_q4_0 * r
const float d = max / -8;
const float id = d ? 1.0f/d : 0.0f;
y[i].d = d;
y[i].d = GGML_FP32_TO_FP16(d);
for (int j = 0; j < qk/2; ++j) {
const float x0 = x[i*qk + 0 + j]*id;
@ -877,8 +877,8 @@ static void quantize_row_q4_1_reference(const float * restrict x, block_q4_1 * r
const float d = (max - min) / ((1 << 4) - 1);
const float id = d ? 1.0f/d : 0.0f;
y[i].d = d;
y[i].m = min;
y[i].d = GGML_FP32_TO_FP16(d);
y[i].m = GGML_FP32_TO_FP16(min);
for (int j = 0; j < qk/2; ++j) {
const float x0 = (x[i*qk + 0 + j] - min)*id;
@ -1009,7 +1009,7 @@ static void quantize_row_q8_0_reference(const float * restrict x, block_q8_0 * r
const float d = amax / ((1 << 7) - 1);
const float id = d ? 1.0f/d : 0.0f;
y[i].d = d;
y[i].d = GGML_FP32_TO_FP16(d);
for (int j = 0; j < QK8_0; ++j) {
const float x0 = x[i*QK8_0 + j]*id;
@ -1044,7 +1044,7 @@ static void quantize_row_q8_0(const float * restrict x, void * restrict vy, int
const float d = amax / ((1 << 7) - 1);
const float id = d ? 1.0f/d : 0.0f;
y[i].d = d;
y[i].d = GGML_FP32_TO_FP16(d);
for (int j = 0; j < 8; j++) {
const float32x4_t v = vmulq_n_f32(srcv[j], id);
@ -1079,7 +1079,7 @@ static void quantize_row_q8_0(const float * restrict x, void * restrict vy, int
// Quantize these floats
const float d = maxScalar / 127.f;
y[i].d = d;
y[i].d = GGML_FP32_TO_FP16(d);
const float id = ( maxScalar != 0.0f ) ? 127.f / maxScalar : 0.0f;
const __m256 mul = _mm256_set1_ps( id );
@ -1178,7 +1178,7 @@ static void quantize_row_q8_1_reference(const float * restrict x, block_q8_1 * r
sum += y[i].qs[QK8_1/2 + j];
}
y[i].s = d * sum;
y[i].s = sum*d;
}
}
@ -1330,7 +1330,7 @@ static void dequantize_row_q4_0(const block_q4_0 * restrict x, float * restrict
const int nb = k / qk;
for (int i = 0; i < nb; i++) {
const float d = x[i].d;
const float d = GGML_FP16_TO_FP32(x[i].d);
for (int j = 0; j < qk/2; ++j) {
const int x0 = (x[i].qs[j] & 0x0F) - 8;
@ -1350,8 +1350,8 @@ static void dequantize_row_q4_1(const block_q4_1 * restrict x, float * restrict
const int nb = k / qk;
for (int i = 0; i < nb; i++) {
const float d = x[i].d;
const float m = x[i].m;
const float d = GGML_FP16_TO_FP32(x[i].d);
const float m = GGML_FP16_TO_FP32(x[i].m);
for (int j = 0; j < qk/2; ++j) {
const int x0 = (x[i].qs[j] & 0x0F);
@ -1426,7 +1426,7 @@ static void dequantize_row_q8_0(const void * restrict vx, float * restrict y, in
const block_q8_0 * restrict x = vx;
for (int i = 0; i < nb; i++) {
const float d = x[i].d;
const float d = GGML_FP16_TO_FP32(x[i].d);
for (int j = 0; j < qk; ++j) {
y[i*qk + j] = x[i].qs[j]*d;
@ -1690,8 +1690,9 @@ quantize_fns_t ggml_internal_get_quantize_fn(size_t i) {
static inline __m256 __avx_f32cx8_load(ggml_fp16_t *x) {
float tmp[8];
for (int i = 0; i < 8; i++)
for (int i = 0; i < 8; i++) {
tmp[i] = GGML_FP16_TO_FP32(x[i]);
}
return _mm256_loadu_ps(tmp);
}
@ -2111,8 +2112,8 @@ static void ggml_vec_dot_q4_0_q8_0(const int n, float * restrict s, const void *
const block_q8_0 * restrict y0 = &y[i + 0];
const block_q8_0 * restrict y1 = &y[i + 1];
const uint8x16_t m4b = vdupq_n_u8(0x0F);
const int8x16_t s8b = vdupq_n_s8(0x8);
const uint8x16_t m4b = vdupq_n_u8(0x0F);
const int8x16_t s8b = vdupq_n_s8(0x8);
const uint8x16_t v0_0 = vld1q_u8(x0->qs);
const uint8x16_t v0_1 = vld1q_u8(x1->qs);
@ -2140,8 +2141,8 @@ static void ggml_vec_dot_q4_0_q8_0(const int n, float * restrict s, const void *
const int32x4_t p_0 = vdotq_s32(vdotq_s32(vdupq_n_s32(0), v0_0ls, v1_0l), v0_0hs, v1_0h);
const int32x4_t p_1 = vdotq_s32(vdotq_s32(vdupq_n_s32(0), v0_1ls, v1_1l), v0_1hs, v1_1h);
sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(p_0), x0->d*y0->d);
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(p_1), x1->d*y1->d);
sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(p_0), GGML_FP16_TO_FP32(x0->d)*GGML_FP16_TO_FP32(y0->d));
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(p_1), GGML_FP16_TO_FP32(x1->d)*GGML_FP16_TO_FP32(y1->d));
#else
const int16x8_t pl0l = vmull_s8(vget_low_s8 (v0_0ls), vget_low_s8 (v1_0l));
const int16x8_t pl0h = vmull_s8(vget_high_s8(v0_0ls), vget_high_s8(v1_0l));
@ -2158,8 +2159,8 @@ static void ggml_vec_dot_q4_0_q8_0(const int n, float * restrict s, const void *
const int32x4_t pl1 = vaddq_s32(vpaddlq_s16(pl1l), vpaddlq_s16(pl1h));
const int32x4_t ph1 = vaddq_s32(vpaddlq_s16(ph1l), vpaddlq_s16(ph1h));
sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(vaddq_s32(pl0, ph0)), x0->d*y0->d);
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(vaddq_s32(pl1, ph1)), x1->d*y1->d);
sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(vaddq_s32(pl0, ph0)), GGML_FP16_TO_FP32(x0->d)*GGML_FP16_TO_FP32(y0->d));
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(vaddq_s32(pl1, ph1)), GGML_FP16_TO_FP32(x1->d)*GGML_FP16_TO_FP32(y1->d));
#endif
}
@ -2171,7 +2172,7 @@ static void ggml_vec_dot_q4_0_q8_0(const int n, float * restrict s, const void *
// Main loop
for (int i = 0; i < nb; ++i) {
/* Compute combined scale for the block */
const __m256 d = _mm256_mul_ps( _mm256_broadcast_ss( &x[i].d ), _mm256_broadcast_ss( &y[i].d ) );
const __m256 d = _mm256_set1_ps( GGML_FP16_TO_FP32(x[i].d) * GGML_FP16_TO_FP32(y[i].d) );
__m256i bx = bytes_from_nibbles_32(x[i].qs);
@ -2195,7 +2196,7 @@ static void ggml_vec_dot_q4_0_q8_0(const int n, float * restrict s, const void *
// Main loop
for (int i = 0; i < nb; ++i) {
// Compute combined scale for the block
const __m256 d = _mm256_mul_ps( _mm256_broadcast_ss( &x[i].d ), _mm256_broadcast_ss( &y[i].d ) );
const __m256 d = _mm256_set1_ps( GGML_FP16_TO_FP32(x[i].d) * GGML_FP16_TO_FP32(y[i].d) );
const __m128i lowMask = _mm_set1_epi8(0xF);
const __m128i off = _mm_set1_epi8(8);
@ -2237,7 +2238,7 @@ static void ggml_vec_dot_q4_0_q8_0(const int n, float * restrict s, const void *
_mm_prefetch(&y[0] + sizeof(block_q8_0), _MM_HINT_T0);
// Compute combined scale for the block 0 and 1
const __m128 d_0_1 = _mm_mul_ps( _mm_set1_ps( x[0].d ), _mm_set1_ps( y[0].d ) );
const __m128 d_0_1 = _mm_set1_ps( GGML_FP16_TO_FP32(x[0].d) * GGML_FP16_TO_FP32(y[0].d) );
const __m128i tmp_0_1 = _mm_loadu_si128((const __m128i *)x[0].qs);
@ -2255,7 +2256,7 @@ static void ggml_vec_dot_q4_0_q8_0(const int n, float * restrict s, const void *
_mm_prefetch(&y[1] + sizeof(block_q8_0), _MM_HINT_T0);
// Compute combined scale for the block 2 and 3
const __m128 d_2_3 = _mm_mul_ps( _mm_set1_ps( x[1].d ), _mm_set1_ps( y[1].d ) );
const __m128 d_2_3 = _mm_set1_ps( GGML_FP16_TO_FP32(x[1].d) * GGML_FP16_TO_FP32(y[1].d) );
const __m128i tmp_2_3 = _mm_loadu_si128((const __m128i *)x[1].qs);
@ -2288,7 +2289,7 @@ static void ggml_vec_dot_q4_0_q8_0(const int n, float * restrict s, const void *
_mm_prefetch(&y[i] + sizeof(block_q8_0), _MM_HINT_T0);
// Compute combined scale for the block 0 and 1
const __m128 d_0_1 = _mm_mul_ps( _mm_set1_ps( x[i].d ), _mm_set1_ps( y[i].d ) );
const __m128 d_0_1 = _mm_set1_ps( GGML_FP16_TO_FP32(x[i].d) * GGML_FP16_TO_FP32(y[i].d) );
const __m128i tmp_0_1 = _mm_loadu_si128((const __m128i *)x[i].qs);
@ -2306,7 +2307,7 @@ static void ggml_vec_dot_q4_0_q8_0(const int n, float * restrict s, const void *
_mm_prefetch(&y[i] + 2 * sizeof(block_q8_0), _MM_HINT_T0);
// Compute combined scale for the block 2 and 3
const __m128 d_2_3 = _mm_mul_ps( _mm_set1_ps( x[i + 1].d ), _mm_set1_ps( y[i + 1].d ) );
const __m128 d_2_3 = _mm_set1_ps( GGML_FP16_TO_FP32(x[i + 1].d) * GGML_FP16_TO_FP32(y[i + 1].d) );
const __m128i tmp_2_3 = _mm_loadu_si128((const __m128i *)x[i + 1].qs);
@ -2354,7 +2355,7 @@ static void ggml_vec_dot_q4_0_q8_0(const int n, float * restrict s, const void *
sumi += (v0 * y[i].qs[j]) + (v1 * y[i].qs[j + qk/2]);
}
sumf += (x[i].d*y[i].d)*sumi;
sumf += sumi*GGML_FP16_TO_FP32(x[i].d)*GGML_FP16_TO_FP32(y[i].d);
}
*s = sumf;
@ -2384,7 +2385,7 @@ static void ggml_vec_dot_q4_1_q8_1(const int n, float * restrict s, const void *
const block_q8_1 * restrict y0 = &y[i + 0];
const block_q8_1 * restrict y1 = &y[i + 1];
summs += x0->m * y0->s + x1->m * y1->s;
summs += GGML_FP16_TO_FP32(x0->m) * y0->s + GGML_FP16_TO_FP32(x1->m) * y1->s;
const uint8x16_t m4b = vdupq_n_u8(0x0F);
@ -2408,8 +2409,8 @@ static void ggml_vec_dot_q4_1_q8_1(const int n, float * restrict s, const void *
const int32x4_t p_0 = vdotq_s32(vdotq_s32(vdupq_n_s32(0), v0_0l, v1_0l), v0_0h, v1_0h);
const int32x4_t p_1 = vdotq_s32(vdotq_s32(vdupq_n_s32(0), v0_1l, v1_1l), v0_1h, v1_1h);
sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(p_0), x0->d*y0->d);
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(p_1), x1->d*y1->d);
sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(p_0), GGML_FP16_TO_FP32(x0->d)*y0->d);
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(p_1), GGML_FP16_TO_FP32(x1->d)*y1->d);
#else
const int16x8_t pl0l = vmull_s8(vget_low_s8 (v0_0l), vget_low_s8 (v1_0l));
const int16x8_t pl0h = vmull_s8(vget_high_s8(v0_0l), vget_high_s8(v1_0l));
@ -2426,8 +2427,8 @@ static void ggml_vec_dot_q4_1_q8_1(const int n, float * restrict s, const void *
const int32x4_t pl1 = vaddq_s32(vpaddlq_s16(pl1l), vpaddlq_s16(pl1h));
const int32x4_t ph1 = vaddq_s32(vpaddlq_s16(ph1l), vpaddlq_s16(ph1h));
sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(vaddq_s32(pl0, ph0)), x0->d*y0->d);
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(vaddq_s32(pl1, ph1)), x1->d*y1->d);
sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(vaddq_s32(pl0, ph0)), GGML_FP16_TO_FP32(x0->d)*y0->d);
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(vaddq_s32(pl1, ph1)), GGML_FP16_TO_FP32(x1->d)*y1->d);
#endif
}
@ -2440,13 +2441,13 @@ static void ggml_vec_dot_q4_1_q8_1(const int n, float * restrict s, const void *
// Main loop
for (int i = 0; i < nb; ++i) {
const float * d0 = &x[i].d;
const float * d1 = &y[i].d;
const float d0 = GGML_FP16_TO_FP32(x[i].d);
const float d1 = y[i].d;
summs += x[i].m * y[i].s;
summs += GGML_FP16_TO_FP32(x[i].m) * y[i].s;
const __m256 d0v = _mm256_broadcast_ss( d0 );
const __m256 d1v = _mm256_broadcast_ss( d1 );
const __m256 d0v = _mm256_set1_ps( d0 );
const __m256 d1v = _mm256_set1_ps( d1 );
// Compute combined scales
const __m256 d0d1 = _mm256_mul_ps( d0v, d1v );
@ -2480,7 +2481,7 @@ static void ggml_vec_dot_q4_1_q8_1(const int n, float * restrict s, const void *
sumi += (v0 * y[i].qs[j]) + (v1 * y[i].qs[j + qk/2]);
}
sumf += (x[i].d*y[i].d)*sumi + x[i].m*y[i].s;
sumf += (GGML_FP16_TO_FP32(x[i]).d*y[i].d)*sumi + GGML_FP16_TO_FP32(x[i].m)*y[i].s;
}
*s = sumf;
@ -2556,16 +2557,13 @@ static void ggml_vec_dot_q5_0_q8_0(const int n, float * restrict s, const void *
const int8x16_t v1_1l = vld1q_s8(y1->qs);
const int8x16_t v1_1h = vld1q_s8(y1->qs + 16);
const float x0d = GGML_FP16_TO_FP32(x0->d);
const float x1d = GGML_FP16_TO_FP32(x1->d);
#if defined(__ARM_FEATURE_DOTPROD)
sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(vaddq_s32(
vdotq_s32(vdupq_n_s32(0), v0_0lf, v1_0l),
vdotq_s32(vdupq_n_s32(0), v0_0hf, v1_0h))), x0d*y0->d);
vdotq_s32(vdupq_n_s32(0), v0_0hf, v1_0h))), GGML_FP16_TO_FP32(x0->d)*GGML_FP16_TO_FP32(y0->d));
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(vaddq_s32(
vdotq_s32(vdupq_n_s32(0), v0_1lf, v1_1l),
vdotq_s32(vdupq_n_s32(0), v0_1hf, v1_1h))), x1d*y1->d);
vdotq_s32(vdupq_n_s32(0), v0_1hf, v1_1h))), GGML_FP16_TO_FP32(x1->d)*GGML_FP16_TO_FP32(y1->d));
#else
const int16x8_t pl0l = vmull_s8(vget_low_s8 (v0_0lf), vget_low_s8 (v1_0l));
const int16x8_t pl0h = vmull_s8(vget_high_s8(v0_0lf), vget_high_s8(v1_0l));
@ -2582,8 +2580,8 @@ static void ggml_vec_dot_q5_0_q8_0(const int n, float * restrict s, const void *
const int32x4_t pl1 = vaddq_s32(vpaddlq_s16(pl1l), vpaddlq_s16(pl1h));
const int32x4_t ph1 = vaddq_s32(vpaddlq_s16(ph1l), vpaddlq_s16(ph1h));
sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(vaddq_s32(pl0, ph0)), x0d*y0->d);
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(vaddq_s32(pl1, ph1)), x1d*y1->d);
sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(vaddq_s32(pl0, ph0)), GGML_FP16_TO_FP32(x0->d)*GGML_FP16_TO_FP32(y0->d));
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(vaddq_s32(pl1, ph1)), GGML_FP16_TO_FP32(x1->d)*GGML_FP16_TO_FP32(y1->d));
#endif
}
@ -2658,7 +2656,7 @@ static void ggml_vec_dot_q5_0_q8_0(const int n, float * restrict s, const void *
// Main loop
for (int i = 0; i < nb; i++) {
/* Compute combined scale for the block */
const __m256 d = _mm256_mul_ps(_mm256_set1_ps(GGML_FP16_TO_FP32(x[i].d)), _mm256_broadcast_ss(&y[i].d));
const __m256 d = _mm256_set1_ps(GGML_FP16_TO_FP32(x[i].d) * GGML_FP16_TO_FP32(y[i].d));
__m256i bx = bytes_from_nibbles_32(x[i].qs);
__m256i bxhi = bytes_from_bits_32(x[i].qh);
@ -2682,7 +2680,7 @@ static void ggml_vec_dot_q5_0_q8_0(const int n, float * restrict s, const void *
// Main loop
for (int i = 0; i < nb; i++) {
/* Compute combined scale for the block */
const __m256 d = _mm256_mul_ps(_mm256_set1_ps(GGML_FP16_TO_FP32(x[i].d)), _mm256_broadcast_ss(&y[i].d));
const __m256 d = _mm256_set1_ps(GGML_FP16_TO_FP32(x[i].d) * GGML_FP16_TO_FP32(y[i].d));
__m256i bx = bytes_from_nibbles_32(x[i].qs);
const __m256i bxhi = bytes_from_bits_32(x[i].qh);
@ -2725,7 +2723,7 @@ static void ggml_vec_dot_q5_0_q8_0(const int n, float * restrict s, const void *
sumi += (x0 * y[i].qs[j]) + (x1 * y[i].qs[j + qk/2]);
}
sumf += (GGML_FP16_TO_FP32(x[i].d)*y[i].d)*sumi;
sumf += (GGML_FP16_TO_FP32(x[i].d)*GGML_FP16_TO_FP32(y[i].d)) * sumi;
}
*s = sumf;
@ -2807,16 +2805,13 @@ static void ggml_vec_dot_q5_1_q8_1(const int n, float * restrict s, const void *
const int8x16_t v1_1l = vld1q_s8(y1->qs);
const int8x16_t v1_1h = vld1q_s8(y1->qs + 16);
const float x0d = GGML_FP16_TO_FP32(x0->d);
const float x1d = GGML_FP16_TO_FP32(x1->d);
#if defined(__ARM_FEATURE_DOTPROD)
sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(vaddq_s32(
vdotq_s32(vdupq_n_s32(0), v0_0lf, v1_0l),
vdotq_s32(vdupq_n_s32(0), v0_0hf, v1_0h))), x0d*y0->d);
vdotq_s32(vdupq_n_s32(0), v0_0hf, v1_0h))), GGML_FP16_TO_FP32(x0->d)*y0->d);
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(vaddq_s32(
vdotq_s32(vdupq_n_s32(0), v0_1lf, v1_1l),
vdotq_s32(vdupq_n_s32(0), v0_1hf, v1_1h))), x1d*y1->d);
vdotq_s32(vdupq_n_s32(0), v0_1hf, v1_1h))), GGML_FP16_TO_FP32(x1->d)*y1->d);
#else
const int16x8_t pl0l = vmull_s8(vget_low_s8 (v0_0lf), vget_low_s8 (v1_0l));
const int16x8_t pl0h = vmull_s8(vget_high_s8(v0_0lf), vget_high_s8(v1_0l));
@ -2833,8 +2828,8 @@ static void ggml_vec_dot_q5_1_q8_1(const int n, float * restrict s, const void *
const int32x4_t pl1 = vaddq_s32(vpaddlq_s16(pl1l), vpaddlq_s16(pl1h));
const int32x4_t ph1 = vaddq_s32(vpaddlq_s16(ph1l), vpaddlq_s16(ph1h));
sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(vaddq_s32(pl0, ph0)), x0d*y0->d);
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(vaddq_s32(pl1, ph1)), x1d*y1->d);
sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(vaddq_s32(pl0, ph0)), GGML_FP16_TO_FP32(x0->d)*y0->d);
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(vaddq_s32(pl1, ph1)), GGML_FP16_TO_FP32(x1->d)*y1->d);
#endif
}
@ -2894,15 +2889,14 @@ static void ggml_vec_dot_q5_1_q8_1(const int n, float * restrict s, const void *
const v128_t v1hl = wasm_i16x8_extend_low_i8x16 (v1h);
const v128_t v1hh = wasm_i16x8_extend_high_i8x16(v1h);
const float x0d = GGML_FP16_TO_FP32(x0->d);
// dot product
sumv = wasm_f32x4_add(sumv, wasm_f32x4_mul(wasm_f32x4_convert_i32x4(
wasm_i32x4_add(
wasm_i32x4_add(wasm_i32x4_dot_i16x8(v0lfl, v1ll),
wasm_i32x4_dot_i16x8(v0lfh, v1lh)),
wasm_i32x4_add(wasm_i32x4_dot_i16x8(v0hfl, v1hl),
wasm_i32x4_dot_i16x8(v0hfh, v1hh)))), wasm_f32x4_splat(x0d*y0->d)));
sumv = wasm_f32x4_add(sumv,
wasm_f32x4_mul(wasm_f32x4_convert_i32x4(wasm_i32x4_add(
wasm_i32x4_add(wasm_i32x4_dot_i16x8(v0lfl, v1ll),
wasm_i32x4_dot_i16x8(v0lfh, v1lh)),
wasm_i32x4_add(wasm_i32x4_dot_i16x8(v0hfl, v1hl),
wasm_i32x4_dot_i16x8(v0hfh, v1hh)))),
wasm_f32x4_splat(GGML_FP16_TO_FP32(x0->d) * y0->d));
}
*s = wasm_f32x4_extract_lane(sumv, 0) + wasm_f32x4_extract_lane(sumv, 1) +
@ -2924,7 +2918,7 @@ static void ggml_vec_dot_q5_1_q8_1(const int n, float * restrict s, const void *
bxhi = _mm256_and_si256(bxhi, _mm256_set1_epi8(0x10));
bx = _mm256_or_si256(bx, bxhi);
const __m256 dy = _mm256_broadcast_ss(&y[i].d);
const __m256 dy = _mm256_set1_ps(y[i].d);
const __m256i by = _mm256_loadu_si256((const __m256i *)y[i].qs);
const __m256 q = mul_sum_us8_pairs_float(bx, by);
@ -2958,7 +2952,7 @@ static void ggml_vec_dot_q5_1_q8_1(const int n, float * restrict s, const void *
bxh = _mm_or_si128(bxh, bxhih);
bx = _mm256_set_m128i(bxh, bxl);
const __m256 dy = _mm256_broadcast_ss(&y[i].d);
const __m256 dy = _mm256_set1_ps(y[i].d);
const __m256i by = _mm256_loadu_si256((const __m256i *)y[i].qs);
const __m256 q = mul_sum_us8_pairs_float(bx, by);
@ -3028,11 +3022,11 @@ static void ggml_vec_dot_q8_0_q8_0(const int n, float * restrict s, const void *
#if defined(__ARM_FEATURE_DOTPROD)
sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(vaddq_s32(
vdotq_s32(vdupq_n_s32(0), x0_0, y0_0),
vdotq_s32(vdupq_n_s32(0), x0_1, y0_1))), x0->d*y0->d);
vdotq_s32(vdupq_n_s32(0), x0_1, y0_1))), GGML_FP16_TO_FP32(x0->d)*GGML_FP16_TO_FP32(y0->d));
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(vaddq_s32(
vdotq_s32(vdupq_n_s32(0), x1_0, y1_0),
vdotq_s32(vdupq_n_s32(0), x1_1, y1_1))), x1->d*y1->d);
vdotq_s32(vdupq_n_s32(0), x1_1, y1_1))), GGML_FP16_TO_FP32(x1->d)*GGML_FP16_TO_FP32(y1->d));
#else
const int16x8_t p0_0 = vmull_s8(vget_low_s8 (x0_0), vget_low_s8 (y0_0));
@ -3050,8 +3044,8 @@ static void ggml_vec_dot_q8_0_q8_0(const int n, float * restrict s, const void *
const int32x4_t p2 = vaddq_s32(vpaddlq_s16(p1_0), vpaddlq_s16(p1_1));
const int32x4_t p3 = vaddq_s32(vpaddlq_s16(p1_2), vpaddlq_s16(p1_3));
sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(vaddq_s32(p0, p1)), x0->d*y0->d);
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(vaddq_s32(p2, p3)), x1->d*y1->d);
sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(vaddq_s32(p0, p1)), GGML_FP16_TO_FP32(x0->d)*GGML_FP16_TO_FP32(y0->d));
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(vaddq_s32(p2, p3)), GGML_FP16_TO_FP32(x1->d)*GGML_FP16_TO_FP32(y1->d));
#endif
}
@ -3063,7 +3057,7 @@ static void ggml_vec_dot_q8_0_q8_0(const int n, float * restrict s, const void *
// Main loop
for (int i = 0; i < nb; ++i) {
// Compute combined scale for the block
const __m256 d = _mm256_mul_ps( _mm256_broadcast_ss( &x[i].d ), _mm256_broadcast_ss( &y[i].d ) );
const __m256 d = _mm256_set1_ps(GGML_FP16_TO_FP32(x[i].d) * GGML_FP16_TO_FP32(y[i].d));
__m256i bx = _mm256_loadu_si256((const __m256i *)x[i].qs);
__m256i by = _mm256_loadu_si256((const __m256i *)y[i].qs);
@ -3089,7 +3083,7 @@ static void ggml_vec_dot_q8_0_q8_0(const int n, float * restrict s, const void *
sumi += x[i].qs[j]*y[i].qs[j];
}
sumf += (x[i].d*y[i].d)*sumi;
sumf += sumi*(GGML_FP16_TO_FP32(x[i].d)*GGML_FP16_TO_FP32(y[i].d));
}
*s = sumf;

2
ggml.h
View File

@ -190,7 +190,7 @@
#define GGML_FILE_MAGIC 0x67676d6c // "ggml"
#define GGML_FILE_VERSION 1
#define GGML_QNT_VERSION 1 // bump this on quantization format changes
#define GGML_QNT_VERSION 2 // bump this on quantization format changes
#define GGML_QNT_VERSION_FACTOR 1000 // do not change this
#define GGML_MAX_DIMS 4

18
llama.cpp
View File

@ -406,6 +406,7 @@ enum llama_file_version {
LLAMA_FILE_VERSION_GGMF_V1, // added version field and scores in vocab
LLAMA_FILE_VERSION_GGJT_V1, // added padding
LLAMA_FILE_VERSION_GGJT_V2, // changed quantization format
LLAMA_FILE_VERSION_GGJT_V3, // changed Q4 and Q8 quantization format
};
struct llama_file_loader {
@ -438,6 +439,8 @@ struct llama_file_loader {
file_version = LLAMA_FILE_VERSION_GGJT_V1;
} else if (magic == 'ggjt' && version == 2) {
file_version = LLAMA_FILE_VERSION_GGJT_V2;
} else if (magic == 'ggjt' && version == 3) {
file_version = LLAMA_FILE_VERSION_GGJT_V3;
} else {
throw format("unknown (magic, version) combination: %08x, %08x; is this really a GGML file?",
magic, version);
@ -844,7 +847,8 @@ static const char *llama_file_version_name(llama_file_version version) {
case LLAMA_FILE_VERSION_GGML: return "'ggml' (old version with low tokenizer quality and no mmap support)";
case LLAMA_FILE_VERSION_GGMF_V1: return "ggmf v1 (old version with no mmap support)";
case LLAMA_FILE_VERSION_GGJT_V1: return "ggjt v1 (pre #1405)";
case LLAMA_FILE_VERSION_GGJT_V2: return "ggjt v2 (latest)";
case LLAMA_FILE_VERSION_GGJT_V2: return "ggjt v2 (pre #1508)";
case LLAMA_FILE_VERSION_GGJT_V3: return "ggjt v3 (latest)";
}
return "unknown";
@ -924,11 +928,19 @@ static void llama_model_load_internal(
fprintf(stderr, "%s: model size = %s\n", __func__, llama_model_type_name(model.type));
}
if (file_version != LLAMA_FILE_VERSION_GGJT_V2) {
if (file_version < LLAMA_FILE_VERSION_GGJT_V2) {
if (hparams.ftype != LLAMA_FTYPE_ALL_F32 &&
hparams.ftype != LLAMA_FTYPE_MOSTLY_F16 &&
hparams.ftype != LLAMA_FTYPE_MOSTLY_Q8_0) {
throw format("this format is no longer supported (see https://github.com/ggerganov/llama.cpp/pull/1305)");
throw format("this format is no longer supported (see https://github.com/ggerganov/llama.cpp/pull/1405)");
}
}
if (file_version < LLAMA_FILE_VERSION_GGJT_V3) {
if (hparams.ftype == LLAMA_FTYPE_MOSTLY_Q4_0 ||
hparams.ftype == LLAMA_FTYPE_MOSTLY_Q4_1 ||
hparams.ftype == LLAMA_FTYPE_MOSTLY_Q8_0) {
throw format("this format is no longer supported (see https://github.com/ggerganov/llama.cpp/pull/1508)");
}
}

2
llama.h
View File

@ -19,7 +19,7 @@
# define LLAMA_API
#endif
#define LLAMA_FILE_VERSION 2
#define LLAMA_FILE_VERSION 3
#define LLAMA_FILE_MAGIC 'ggjt'
#define LLAMA_FILE_MAGIC_UNVERSIONED 'ggml'
#define LLAMA_SESSION_MAGIC 'ggsn'