vbatts/llama.cpp
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# Conflicts:
#	llama.cpp
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Concedo 2023-04-22 16:07:27 +08:00
commit 1ea0e15292
4 changed files with 304 additions and 202 deletions
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11
examples/alpaca.sh
View file

@ -7,4 +7,13 @@
cd `dirname $0`
cd ..
./main -m ./models/ggml-alpaca-7b-q4.bin --color -f ./prompts/alpaca.txt --ctx_size 2048 -n -1 -ins -b 256 --top_k 10000 --temp 0.2 --repeat_penalty 1 -t 7
./main -m ./models/ggml-alpaca-7b-q4.bin \
--color \
-f ./prompts/alpaca.txt \
--ctx_size 2048 \
-n -1 \
-ins -b 256 \
--top_k 10000 \
--temp 0.2 \
--repeat_penalty 1.1 \
-t 7

359
ggml.c
View file

@ -452,6 +452,24 @@ static inline __m128i bytes_from_nibbles_16(const uint8_t * rsi)
return bytes;
}
// horizontally add 8 floats
static inline float hsum_float_8(const __m256 x) {
__m128 res = _mm256_extractf128_ps(x, 1);
res = _mm_add_ps(res, _mm256_castps256_ps128(x));
res = _mm_add_ps(res, _mm_movehl_ps(res, res));
res = _mm_add_ss(res, _mm_movehdup_ps(res));
return _mm_cvtss_f32(res);
}
// horizontally add 8 int32_t
static inline int hsum_i32_8(const __m256i a) {
const __m128i sum128 = _mm_add_epi32(_mm256_castsi256_si128(a), _mm256_extractf128_si256(a, 1));
const __m128i hi64 = _mm_unpackhi_epi64(sum128, sum128);
const __m128i sum64 = _mm_add_epi32(hi64, sum128);
const __m128i hi32 = _mm_shuffle_epi32(sum64, _MM_SHUFFLE(2, 3, 0, 1));
return _mm_cvtsi128_si32(_mm_add_epi32(sum64, hi32));
}
#if __AVX2__ || __AVX512F__
// Unpack 32 4-bit fields into 32 bytes
// The output vector contains 32 bytes, each one in [ 0 .. 15 ] interval
@ -472,6 +490,24 @@ static inline __m256i bytes_from_nibbles_32(const uint8_t * rsi)
return bytes;
}
// add int16_t pairwise and return as float vector
static inline __m256 sum_i16_pairs_float(const __m256i x) {
const __m256i ones = _mm256_set1_epi16(1);
const __m256i summed_pairs = _mm256_madd_epi16(ones, x);
return _mm256_cvtepi32_ps(summed_pairs);
}
// multiply int8_t, add results pairwise twice and return as float vector
static inline __m256 mul_sum_i8_pairs_float(const __m256i x, const __m256i y) {
// Get absolute values of x vectors
const __m256i ax = _mm256_sign_epi8(x, x);
// Sign the values of the y vectors
const __m256i sy = _mm256_sign_epi8(y, x);
// Perform multiplication and create 16-bit values
const __m256i dot = _mm256_maddubs_epi16(ax, sy);
return sum_i16_pairs_float(dot);
}
static inline __m128i packNibbles( __m256i bytes )
{
// Move bits within 16-bit lanes from 0000_abcd_0000_efgh into 0000_0000_abcd_efgh
@ -622,10 +658,11 @@ static_assert(sizeof(block_q4_3) == 2 * sizeof(ggml_fp16_t) + QK4_3 / 2, "wrong
#define QK8_0 32
typedef struct {
float d; // delta
float s; // d * sum(qs[i])
float s0; // d * sum(qs[i]) low
float s1; // d * sum(qs[i]) high
int8_t qs[QK8_0]; // quants
} block_q8_0;
static_assert(sizeof(block_q8_0) == 2*sizeof(float) + QK8_0, "wrong q8_0 block size/padding");
static_assert(sizeof(block_q8_0) == 3*sizeof(float) + QK8_0, "wrong q8_0 block size/padding");
// reference implementation for deterministic creation of model files
@ -1265,39 +1302,25 @@ static void quantize_row_q8_0_reference(const float * restrict x, block_q8_0 * r
y[i].d = d;
int sum = 0;
for (int l = 0; l < QK8_0; ++l) {
const float v = x[i*QK8_0 + l]*id;
y[i].qs[l] = roundf(v);
sum += y[i].qs[l];
int sum0 = 0;
int sum1 = 0;
for (int l = 0; l < QK8_0/2; ++l) {
const float v0 = x[i*QK8_0 + l]*id;
const float v1 = x[i*QK8_0 + QK8_0/2 + l]*id;
y[i].qs[ l] = roundf(v0);
y[i].qs[QK8_0/2 + l] = roundf(v1);
sum0 += y[i].qs[ l];
sum1 += y[i].qs[QK8_0/2 + l];
}
y[i].s = d * sum;
y[i].s0 = d * sum0;
y[i].s1 = d * sum1;
}
}
#ifdef __AVX2__
// There is no better way of doing this?
// I guess not, AVX is not very good at horizontal sums.
// The commented solution for a hotrizontal sum was suggested by @pubby as being slightly
// faster than the solution below. As I don't have an AVX2 system handt right now to test,
// keeping the original.
// TODO: Please try and if it does make a differece, uncomment and remove the implementation below.
//static inline float horizontal_sum(__m256i a) {
// __m256i b = _mm256_castps_si256(_mm256_movehdup_ps(_mm256_castsi256_ps(a)));
// __m256i sum = _mm256_add_epi32(a, b);
// __m256i hi = _mm256_unpackhi_epi64(sum, sum);
// sum = _mm256_add_epi32(sum, hi);
// return _mm256_cvtsi256_si32(sum) + _mm256_extract_epi32(sum, 4);
//}
static inline float horizontal_sum(__m256i a) {
__m128i sum128 = _mm_add_epi32(_mm256_castsi256_si128(a), _mm256_extracti128_si256(a, 1));
__m128i hi64 = _mm_unpackhi_epi64(sum128, sum128);
__m128i sum64 = _mm_add_epi32(hi64, sum128);
__m128i hi32 = _mm_shuffle_epi32(sum64, _MM_SHUFFLE(2, 3, 0, 1));
return _mm_cvtsi128_si32(_mm_add_epi32(sum64, hi32));
}
#endif
static void quantize_row_q8_0(const float * restrict x, void * restrict vy, int k) {
assert(k % QK8_0 == 0);
const int nb = k / QK8_0;
@ -1324,9 +1347,11 @@ static void quantize_row_q8_0(const float * restrict x, void * restrict vy, int
y[i].d = d;
int32x4_t accv = vdupq_n_s32(0);
int32x4_t accv0 = vdupq_n_s32(0);
int32x4_t accv1 = vdupq_n_s32(0);
for (int l = 0; l < 8; l++) {
// low half
for (int l = 0; l < 4; l++) {
const float32x4_t v = vmulq_n_f32(srcv[l], id);
const int32x4_t vi = vcvtnq_s32_f32(v);
@ -1335,12 +1360,30 @@ static void quantize_row_q8_0(const float * restrict x, void * restrict vy, int
y[i].qs[4*l + 2] = vgetq_lane_s32(vi, 2);
y[i].qs[4*l + 3] = vgetq_lane_s32(vi, 3);
accv = vaddq_s32(accv, vi);
accv0 = vaddq_s32(accv0, vi);
}
int32_t sum = vaddvq_s32(accv);
y[i].s = d * sum;
// high half
for (int l = 4; l < 8; l++) {
const float32x4_t v = vmulq_n_f32(srcv[l], id);
const int32x4_t vi = vcvtnq_s32_f32(v);
y[i].qs[4*l + 0] = vgetq_lane_s32(vi, 0);
y[i].qs[4*l + 1] = vgetq_lane_s32(vi, 1);
y[i].qs[4*l + 2] = vgetq_lane_s32(vi, 2);
y[i].qs[4*l + 3] = vgetq_lane_s32(vi, 3);
accv1 = vaddq_s32(accv1, vi);
}
const int32_t sum0 = vaddvq_s32(accv0);
const int32_t sum1 = vaddvq_s32(accv1);
y[i].s0 = d * sum0;
y[i].s1 = d * sum1;
}
#elif defined(__AVX2__) || defined(__AVX__)
// TODO !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
for (int i = 0; i < nb; i++) {
// Load elements into 4 AVX vectors
__m256 v0 = _mm256_loadu_ps( x );
@ -1386,9 +1429,10 @@ static void quantize_row_q8_0(const float * restrict x, void * restrict vy, int
__m256i i3 = _mm256_cvtps_epi32( v3 );
#if defined(__AVX2__)
// Compute the sum of the quants and set y[i].s
y[i].s = d * horizontal_sum(_mm256_add_epi32(_mm256_add_epi32(i0, i1), _mm256_add_epi32(i2, i3)));
//y[i].s = d * hsum_i32_8(_mm256_add_epi32(_mm256_add_epi32(i0, i1), _mm256_add_epi32(i2, i3)));
y[i].s0 = d * hsum_i32_8(_mm256_add_epi32(i0, i1));
y[i].s1 = d * hsum_i32_8(_mm256_add_epi32(i2, i3));
// Convert int32 to int16
i0 = _mm256_packs_epi32( i0, i1 ); // 0, 1, 2, 3, 8, 9, 10, 11, 4, 5, 6, 7, 12, 13, 14, 15
@ -1415,6 +1459,11 @@ static void quantize_row_q8_0(const float * restrict x, void * restrict vy, int
__m128i ni6 = _mm256_castsi256_si128( i3 );
__m128i ni7 = _mm256_extractf128_si256( i3, 1);
// Compute the sum of the quants and set y[i].s
const __m128i s0 = _mm_add_epi32(_mm_add_epi32(ni0, ni1), _mm_add_epi32(ni2, ni3));
const __m128i s1 = _mm_add_epi32(_mm_add_epi32(ni4, ni5), _mm_add_epi32(ni6, ni7));
y[i].s = d * hsum_i32_8(_mm256_set_m128i(s1, s0));
// Convert int32 to int16
ni0 = _mm_packs_epi32( ni0, ni1 );
ni2 = _mm_packs_epi32( ni2, ni3 );
@ -1432,14 +1481,6 @@ static void quantize_row_q8_0(const float * restrict x, void * restrict vy, int
// scalar
quantize_row_q8_0_reference(x, y, k);
#endif
#if defined __AVX__
// TODO: vectorize this
for (int i=0; i<nb; ++i) {
int sum = 0;
for (int l=0; l<QK8_0; ++l) sum += y[i].qs[l];
y[i].s = y[i].d * sum;
}
#endif
}
static void dequantize_row_q4_0(const void * restrict vx, float * restrict y, int k) {
@ -2376,8 +2417,6 @@ static void ggml_vec_dot_q4_0_q8_0(const int n, float * restrict s, const void *
const block_q4_0 * restrict x = vx;
const block_q8_0 * restrict y = vy;
float sumf = 0.0;
#if defined(__ARM_NEON)
float32x4_t sumv0 = vdupq_n_f32(0.0f);
float32x4_t sumv1 = vdupq_n_f32(0.0f);
@ -2390,7 +2429,7 @@ 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];
sum8 += x0->d * y0->s + x1->d * y1->s;
sum8 += x0->d * (y0->s0 + y0->s1) + x1->d * (y1->s0 + y1->s1);
const uint8x16_t m4b = vdupq_n_u8(0xf);
@ -2443,7 +2482,7 @@ static void ggml_vec_dot_q4_0_q8_0(const int n, float * restrict s, const void *
#endif
}
sumf = vaddvq_f32(sumv0) + vaddvq_f32(sumv1) - 8 * sum8;
*s = vaddvq_f32(sumv0) + vaddvq_f32(sumv1) - 8 * sum8;
#elif defined(__AVX2__)
// Initialize accumulator with zeros
__m256 acc = _mm256_setzero_ps();
@ -2461,32 +2500,13 @@ static void ggml_vec_dot_q4_0_q8_0(const int n, float * restrict s, const void *
__m256i by = _mm256_loadu_si256((const __m256i *)y[i].qs);
// Get absolute values of x vectors
const __m256i ax = _mm256_sign_epi8(bx, bx);
// Sign the values of the y vectors
const __m256i sy = _mm256_sign_epi8(by, bx);
// Perform multiplication and create 16-bit values
const __m256i dot = _mm256_maddubs_epi16(ax, sy);
const __m256i ones = _mm256_set1_epi16(1);
__m256i xy_q = _mm256_madd_epi16(ones, dot);
/* Convert to vectore of 8 int32_t to 8 floats */
__m256 q = _mm256_cvtepi32_ps( xy_q );
const __m256 q = mul_sum_i8_pairs_float(bx, by);
/* Multiply q with scale and accumulate */
acc = _mm256_fmadd_ps( d, q, acc );
}
// Return horizontal sum of the acc vector
__m128 res = _mm256_extractf128_ps( acc, 1 );
res = _mm_add_ps( res, _mm256_castps256_ps128( acc ) );
res = _mm_add_ps( res, _mm_movehl_ps( res, res ) );
res = _mm_add_ss( res, _mm_movehdup_ps( res ) );
sumf = _mm_cvtss_f32( res );
*s = hsum_float_8(acc);
#elif defined(__AVX__)
// Initialize accumulator with zeros
__m256 acc = _mm256_setzero_ps();
@ -2525,15 +2545,10 @@ static void ggml_vec_dot_q4_0_q8_0(const int n, float * restrict s, const void *
acc = _mm256_add_ps(_mm256_mul_ps( d, p ), acc);
}
// Return horizontal sum of the acc vector
__m128 res = _mm256_extractf128_ps( acc, 1 );
res = _mm_add_ps( res, _mm256_castps256_ps128( acc ) );
res = _mm_add_ps( res, _mm_movehl_ps( res, res ) );
res = _mm_add_ss( res, _mm_movehdup_ps( res ) );
sumf = _mm_cvtss_f32( res );
*s = hsum_float_8(acc);
#else
// scalar
float sumf = 0.0;
for (int i = 0; i < nb; i++) {
const float d0 = x[i].d;
const float d1 = y[i].d;
@ -2555,9 +2570,8 @@ static void ggml_vec_dot_q4_0_q8_0(const int n, float * restrict s, const void *
}
sumf += d0*d1*sumi;
}
#endif
*s = sumf;
#endif
}
static void ggml_vec_dot_q4_1_q8_0(const int n, float * restrict s, const void * restrict vx, const void * restrict vy) {
@ -2569,8 +2583,6 @@ static void ggml_vec_dot_q4_1_q8_0(const int n, float * restrict s, const void *
const block_q4_1 * restrict x = vx;
const block_q8_0 * restrict y = vy;
float sumf = 0.0;
// TODO: add AVX / WASM SIMD / etc
#if defined(__ARM_NEON)
float32x4_t sumv0 = vdupq_n_f32(0.0f);
@ -2584,7 +2596,7 @@ static void ggml_vec_dot_q4_1_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];
summs += x0->m * y0->s + x1->m * y1->s;
summs += x0->m * (y0->s0 + y0->s1) + x1->m * (y1->s0 + y1->s1);
const uint8x16_t m4b = vdupq_n_u8(0xf);
@ -2597,22 +2609,22 @@ static void ggml_vec_dot_q4_1_q8_0(const int n, float * restrict s, const void *
const int8x16_t v0_1l = vreinterpretq_s8_u8(vandq_u8 (v0_1, m4b));
const int8x16_t v0_1h = vreinterpretq_s8_u8(vshrq_n_u8(v0_1, 4));
// interleave
const int8x16_t v0_0lz = vzip1q_s8(v0_0l, v0_0h);
const int8x16_t v0_0hz = vzip2q_s8(v0_0l, v0_0h);
const int8x16_t v0_1lz = vzip1q_s8(v0_1l, v0_1h);
const int8x16_t v0_1hz = vzip2q_s8(v0_1l, v0_1h);
// load y
const int8x16_t v1_0l = vld1q_s8(y0->qs);
const int8x16_t v1_0h = vld1q_s8(y0->qs + 16);
const int8x16_t v1_1l = vld1q_s8(y1->qs);
const int8x16_t v1_1h = vld1q_s8(y1->qs + 16);
// interleave
const int8x16_t v1_0ls = vuzp1q_s8(v1_0l, v1_0h);
const int8x16_t v1_0hs = vuzp2q_s8(v1_0l, v1_0h);
const int8x16_t v1_1ls = vuzp1q_s8(v1_1l, v1_1h);
const int8x16_t v1_1hs = vuzp2q_s8(v1_1l, v1_1h);
#if defined(__ARM_FEATURE_DOTPROD)
// dot product into int32x4_t
const int32x4_t p_0 = vdotq_s32(vdotq_s32(vdupq_n_s32(0), v0_0l, v1_0ls), v0_0h, v1_0hs);
const int32x4_t p_1 = vdotq_s32(vdotq_s32(vdupq_n_s32(0), v0_1l, v1_1ls), v0_1h, v1_1hs);
const int32x4_t p_0 = vdotq_s32(vdotq_s32(vdupq_n_s32(0), v0_0lz, v1_0l), v0_0hz, v1_0h);
const int32x4_t p_1 = vdotq_s32(vdotq_s32(vdupq_n_s32(0), v0_1lz, v1_1l), v0_1hz, 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);
@ -2637,7 +2649,7 @@ static void ggml_vec_dot_q4_1_q8_0(const int n, float * restrict s, const void *
#endif
}
sumf = vaddvq_f32(sumv0) + vaddvq_f32(sumv1) + summs;
*s = vaddvq_f32(sumv0) + vaddvq_f32(sumv1) + summs;
#elif defined(__AVX2__)
// Initialize accumulator with zeros
__m256 acc = _mm256_setzero_ps();
@ -2648,9 +2660,8 @@ static void ggml_vec_dot_q4_1_q8_0(const int n, float * restrict s, const void *
for (int i = 0; i < nb; ++i) {
const float * d0 = &x[i].d;
const float * d1 = &y[i].d;
//const float * m0 = &x[i].m;
summs += x[i].m * y[i].s;
summs += x[i].m * (y[i].s0 + y[i].s1);
const __m256 d0v = _mm256_broadcast_ss( d0 );
const __m256 d1v = _mm256_broadcast_ss( d1 );
@ -2662,33 +2673,16 @@ static void ggml_vec_dot_q4_1_q8_0(const int n, float * restrict s, const void *
const __m256i bx = bytes_from_nibbles_32(x[i].qs);
const __m256i by = _mm256_loadu_si256( (const __m256i *)y[i].qs );
// Get absolute values of x vectors
const __m256i ax = _mm256_sign_epi8( bx, bx );
// Sign the values of the y vectors
const __m256i sy = _mm256_sign_epi8( by, bx );
// Perform multiplication and create 16-bit values
const __m256i dot = _mm256_maddubs_epi16( ax, sy );
const __m256i ones = _mm256_set1_epi16( 1 );
const __m256i xy_q = _mm256_madd_epi16( ones, dot );
// Convert to vector of 8 int32_t to 8 floats
const __m256 xy = _mm256_cvtepi32_ps( xy_q );
const __m256 xy = mul_sum_i8_pairs_float(bx, by);
// Accumulate d0*d1*x*y
acc = _mm256_fmadd_ps( d0d1, xy, acc );
}
// Return horizontal sum of the acc vector
__m128 res = _mm256_extractf128_ps( acc, 1 );
res = _mm_add_ps( res, _mm256_castps256_ps128( acc ) );
res = _mm_add_ps( res, _mm_movehl_ps( res, res ) );
res = _mm_add_ss( res, _mm_movehdup_ps( res ) );
sumf = _mm_cvtss_f32( res ) + summs;
*s = hsum_float_8(acc) + summs;
#else
// scalar
float sumf = 0.0;
for (int i = 0; i < nb; i++) {
const float d0 = x[i].d;
const float m0 = x[i].m;
@ -2710,9 +2704,8 @@ static void ggml_vec_dot_q4_1_q8_0(const int n, float * restrict s, const void *
sumf += f0*f2 + f1*f3;
}
}
#endif
*s = sumf;
#endif
}
static void ggml_vec_dot_q4_2_q8_0(const int n, float * restrict s, const void * restrict vx, const void * restrict vy) {
@ -2725,8 +2718,6 @@ static void ggml_vec_dot_q4_2_q8_0(const int n, float * restrict s, const void *
const block_q4_2 * restrict x = vx;
const block_q8_0 * restrict y = vy;
float sumf = 0.0;
#if defined(__ARM_NEON)
float32x4_t sumv0 = vdupq_n_f32(0.0f);
float32x4_t sumv1 = vdupq_n_f32(0.0f);
@ -2804,7 +2795,7 @@ static void ggml_vec_dot_q4_2_q8_0(const int n, float * restrict s, const void *
#endif
}
sumf = vaddvq_f32(sumv0) + vaddvq_f32(sumv1);
*s = vaddvq_f32(sumv0) + vaddvq_f32(sumv1);
#elif defined(__AVX2__)
// Initialize accumulator with zeros
__m256 acc = _mm256_setzero_ps();
@ -2826,32 +2817,16 @@ static void ggml_vec_dot_q4_2_q8_0(const int n, float * restrict s, const void *
__m256i by = _mm256_loadu_si256((const __m256i *)y[i].qs);
// Get absolute values of x vectors
const __m256i ax = _mm256_sign_epi8(bx, bx);
// Sign the values of the y vectors
const __m256i sy = _mm256_sign_epi8(by, bx);
// Perform multiplication and create 16-bit values
const __m256i dot = _mm256_maddubs_epi16(ax, sy);
const __m256i ones = _mm256_set1_epi16(1);
__m256i xy_q = _mm256_madd_epi16(ones, dot);
/* Convert to vectore of 8 int32_t to 8 floats */
__m256 q = _mm256_cvtepi32_ps(xy_q);
const __m256 q = mul_sum_i8_pairs_float(bx, by);
/* Multiply q with scale and accumulate */
acc = _mm256_fmadd_ps(d, q, acc);
}
// Return horizontal sum of the acc vector
__m128 res = _mm256_extractf128_ps(acc, 1);
res = _mm_add_ps(res, _mm256_castps256_ps128(acc));
res = _mm_add_ps(res, _mm_movehl_ps(res, res));
res = _mm_add_ss(res, _mm_movehdup_ps(res));
sumf = _mm_cvtss_f32(res);
*s = hsum_float_8(acc);
#else
// scalar
float sumf = 0.0;
for (int i = 0; i < nb; i++) {
const uint8_t * restrict x0 = x[2*i + 0].qs;
const uint8_t * restrict x1 = x[2*i + 1].qs;
@ -2886,9 +2861,8 @@ static void ggml_vec_dot_q4_2_q8_0(const int n, float * restrict s, const void *
sumf += (d0 * y[i].d) * sumi_0;
sumf += (d1 * y[i].d) * sumi_1;
}
#endif
*s = sumf;
#endif
}
static void ggml_vec_dot_q4_3_q8_0(const int n, float * restrict s, const void * restrict vx, const void * restrict vy) {
@ -2901,96 +2875,91 @@ static void ggml_vec_dot_q4_3_q8_0(const int n, float * restrict s, const void *
const block_q4_3 * restrict x = vx;
const block_q8_0 * restrict y = vy;
float sumf = 0.0;
#if defined(__ARM_NEON)
float32x4_t sumv0 = vdupq_n_f32(0.0f);
float32x4_t sumv1 = vdupq_n_f32(0.0f);
for (int i = 0; i < nb; i += 2) {
float summs0 = 0.0f;
float summs1 = 0.0f;
for (int i = 0; i < nb; ++i) {
const block_q4_3 * restrict x0_0 = &x[2*(i + 0) + 0];
const block_q4_3 * restrict x0_1 = &x[2*(i + 0) + 1];
const block_q4_3 * restrict x1_0 = &x[2*(i + 1) + 0];
const block_q4_3 * restrict x1_1 = &x[2*(i + 1) + 1];
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(0xf);
const float x0_0d = GGML_FP16_TO_FP32(x0_0->d);
const float x0_1d = GGML_FP16_TO_FP32(x0_1->d);
const float x1_0d = GGML_FP16_TO_FP32(x1_0->d);
const float x1_1d = GGML_FP16_TO_FP32(x1_1->d);
const float x0_0m = GGML_FP16_TO_FP32(x0_0->m);
const float x0_1m = GGML_FP16_TO_FP32(x0_1->m);
const float x1_0m = GGML_FP16_TO_FP32(x1_0->m);
const float x1_1m = GGML_FP16_TO_FP32(x1_1->m);
summs0 += GGML_FP16_TO_FP32(x0_0->m) * y0->s0;
summs1 += GGML_FP16_TO_FP32(x0_1->m) * y0->s1;
const uint8x16_t v0_0 = vcombine_u8(vld1_u8(x0_0->qs), vld1_u8(x0_1->qs));
const uint8x16_t v0_1 = vcombine_u8(vld1_u8(x1_0->qs), vld1_u8(x1_1->qs));
// 4-bit -> 8-bit
const int8x16_t v0_0l = vreinterpretq_s8_u8(vandq_u8 (v0_0, m4b));
const int8x16_t v0_0l = vreinterpretq_s8_u8(vandq_u8 (v0_0, vdupq_n_u8(0xf)));
const int8x16_t v0_0h = vreinterpretq_s8_u8(vshrq_n_u8(v0_0, 4));
const int8x16_t v0_1l = vreinterpretq_s8_u8(vandq_u8 (v0_1, m4b));
const int8x16_t v0_1h = vreinterpretq_s8_u8(vshrq_n_u8(v0_1, 4));
// interleave
const int8x16_t v0_0lz = vzip1q_s8(v0_0l, v0_0h);
const int8x16_t v0_0hz = vzip2q_s8(v0_0l, v0_0h);
const int8x16_t v0_1lz = vzip1q_s8(v0_1l, v0_1h);
const int8x16_t v0_1hz = vzip2q_s8(v0_1l, v0_1h);
// load y
const int8x16_t v1_0l = vld1q_s8(y0->qs);
const int8x16_t v1_0h = vld1q_s8(y0->qs + 16);
const int8x16_t v1_1l = vld1q_s8(y1->qs);
const int8x16_t v1_1h = vld1q_s8(y1->qs + 16);
const int16x8_t sy0_0 = vaddq_s16(vmovl_s8(vget_low_s8(v1_0l)), vmovl_s8(vget_high_s8(v1_0l)));
const int16x8_t sy0_1 = vaddq_s16(vmovl_s8(vget_low_s8(v1_0h)), vmovl_s8(vget_high_s8(v1_0h)));
const int16x8_t sy1_0 = vaddq_s16(vmovl_s8(vget_low_s8(v1_1l)), vmovl_s8(vget_high_s8(v1_1l)));
const int16x8_t sy1_1 = vaddq_s16(vmovl_s8(vget_low_s8(v1_1h)), vmovl_s8(vget_high_s8(v1_1h)));
sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(vaddl_s16(vget_low_s16(sy0_0), vget_high_s16(sy0_0))), x0_0m*y0->d);
sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(vaddl_s16(vget_low_s16(sy0_1), vget_high_s16(sy0_1))), x0_1m*y0->d);
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(vaddl_s16(vget_low_s16(sy1_0), vget_high_s16(sy1_0))), x1_0m*y1->d);
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(vaddl_s16(vget_low_s16(sy1_1), vget_high_s16(sy1_1))), x1_1m*y1->d);
const float x0_0d = GGML_FP16_TO_FP32(x0_0->d);
const float x0_1d = GGML_FP16_TO_FP32(x0_1->d);
#if defined(__ARM_FEATURE_DOTPROD)
sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(vdotq_s32(vdupq_n_s32(0), v0_0lz, v1_0l)), x0_0d*y0->d);
sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(vdotq_s32(vdupq_n_s32(0), v0_0hz, v1_0h)), x0_1d*y0->d);
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(vdotq_s32(vdupq_n_s32(0), v0_1lz, v1_1l)), x1_0d*y1->d);
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(vdotq_s32(vdupq_n_s32(0), v0_1hz, v1_1h)), x1_1d*y1->d);
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(vdotq_s32(vdupq_n_s32(0), v0_0hz, v1_0h)), x0_1d*y0->d);
#else
const int16x8_t pl0l = vmull_s8(vget_low_s8 (v0_0lz), vget_low_s8 (v1_0l));
const int16x8_t pl0h = vmull_s8(vget_high_s8(v0_0lz), vget_high_s8(v1_0l));
const int16x8_t ph0l = vmull_s8(vget_low_s8 (v0_0hz), vget_low_s8 (v1_0h));
const int16x8_t ph0h = vmull_s8(vget_high_s8(v0_0hz), vget_high_s8(v1_0h));
const int16x8_t pl1l = vmull_s8(vget_low_s8 (v0_1lz), vget_low_s8 (v1_1l));
const int16x8_t pl1h = vmull_s8(vget_high_s8(v0_1lz), vget_high_s8(v1_1l));
const int16x8_t ph1l = vmull_s8(vget_low_s8 (v0_1hz), vget_low_s8 (v1_1h));
const int16x8_t ph1h = vmull_s8(vget_high_s8(v0_1hz), vget_high_s8(v1_1h));
const int32x4_t pl0 = vaddq_s32(vpaddlq_s16(pl0l), vpaddlq_s16(pl0h));
const int32x4_t ph0 = vaddq_s32(vpaddlq_s16(ph0l), vpaddlq_s16(ph0h));
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(pl0), x0_0d*y0->d);
sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(ph0), x0_1d*y0->d);
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(pl1), x1_0d*y1->d);
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(ph1), x1_1d*y1->d);
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(ph0), x0_1d*y0->d);
#endif
}
sumf = vaddvq_f32(sumv0) + vaddvq_f32(sumv1);
*s = vaddvq_f32(vaddq_f32(sumv0, sumv1)) + summs0 + summs1;
#elif defined(__AVX2__)
// Initialize accumulator with zeros
__m256 acc = _mm256_setzero_ps();
// Main loop
for (int i = 0; i < nb; i++) {
const __m128 d0 = _mm_set1_ps(GGML_FP16_TO_FP32(x[2*i + 0].d));
const __m128 d1 = _mm_set1_ps(GGML_FP16_TO_FP32(x[2*i + 1].d));
const __m256 dx = _mm256_set_m128(d1, d0);
const __m128 m0 = _mm_set1_ps(GGML_FP16_TO_FP32(x[2*i + 0].m));
const __m128 m1 = _mm_set1_ps(GGML_FP16_TO_FP32(x[2*i + 1].m));
const __m256 mx = _mm256_set_m128(m1, m0);
const __m128i bx0 = bytes_from_nibbles_16(x[2*i + 0].qs);
const __m128i bx1 = bytes_from_nibbles_16(x[2*i + 1].qs);
const __m256i bx = _mm256_set_m128i(bx1, bx0);
const __m256 dy = _mm256_broadcast_ss(&y[i].d);
const __m256i by = _mm256_loadu_si256((const __m256i *)y[i].qs);
const __m256i syi = _mm256_maddubs_epi16(_mm256_set1_epi8(1), by);
const __m256 syf = sum_i16_pairs_float(syi);
const __m256 q = mul_sum_i8_pairs_float(bx, by);
const __m256 sxy = _mm256_fmadd_ps(q, dx, _mm256_mul_ps(mx, syf));
acc = _mm256_fmadd_ps(sxy, dy, acc);
}
*s = hsum_float_8(acc);
#else
// scalar
float sumf = 0.0;
for (int i = 0; i < nb; i++) {
const uint8_t * restrict x0 = x[2*i + 0].qs;
const uint8_t * restrict x1 = x[2*i + 1].qs;
@ -3001,9 +2970,6 @@ static void ggml_vec_dot_q4_3_q8_0(const int n, float * restrict s, const void *
const float d1 = GGML_FP16_TO_FP32(x[2*i + 1].d);
const float m1 = GGML_FP16_TO_FP32(x[2*i + 1].m);
int sy_0 = 0;
int sy_1 = 0;
int sxy_0 = 0;
int sxy_1 = 0;
@ -3023,19 +2989,14 @@ static void ggml_vec_dot_q4_3_q8_0(const int n, float * restrict s, const void *
const int y0_1 = y0[2*(j + QK8_0/4) + 0];
const int y1_1 = y0[2*(j + QK8_0/4) + 1];
sy_0 += y0_0 + y1_0;
sy_1 += y0_1 + y1_1;
sxy_0 += x0_0*y0_0 + x1_0*y1_0;
sxy_1 += x0_1*y0_1 + x1_1*y1_1;
}
sumf += (d0*sxy_0 + m0*sy_0)*y[i].d;
sumf += (d1*sxy_1 + m1*sy_1)*y[i].d;
sumf += (d0*sxy_0 + d1*sxy_1)*y[i].d + m0*y[i].s0 + m1*y[i].s1;
}
#endif
*s = sumf;
#endif
}

124
llama.cpp
View file

@ -27,6 +27,7 @@
#include <thread>
#include <atomic>
#include <mutex>
#include <sstream>
#define LLAMA_USE_SCRATCH
#define LLAMA_MAX_SCRATCH_BUFFERS 16
@ -1794,7 +1795,7 @@ struct llama_context * llama_init_from_file(
if (params.logits_all) {
ctx->logits.reserve(hparams.n_ctx*hparams.n_vocab);
} else {
ctx->logits.reserve(hparams.n_ctx);
ctx->logits.reserve(hparams.n_vocab);
}
if (params.embedding){
@ -2258,4 +2259,123 @@ const char * llama_print_system_info(void) {
// For internal test use
std::vector<std::pair<std::string, struct ggml_tensor *>>& llama_internal_get_tensor_map(struct llama_context * ctx) {
return ctx->model.tensors_by_name;
}
}
// Returns the size of the state
size_t llama_get_state_size(struct llama_context * ctx) {
const size_t s_bool = sizeof(int32_t);
// we don't know size of rng until we actually serialize it. so reserve more than enough memory for its serialized state.
// for reference, std::mt19937(1337) serializes to 6701 bytes.
const size_t s_rng_size = sizeof(size_t);
const size_t s_rng = 64*1024;
const size_t s_logits_capacity = sizeof(size_t);
const size_t s_logits_size = sizeof(size_t);
const size_t s_logits = ctx->logits.capacity() * sizeof(float);
const size_t s_embedding_size = sizeof(size_t);
const size_t s_embedding = ctx->embedding.size() * sizeof(float);
const size_t s_kv_size = sizeof(size_t);
const size_t s_kv_ntok = sizeof(int);
const size_t s_kv = llama_get_kv_cache_size(ctx);
const size_t s_total = (
+ s_rng_size
+ s_rng
+ s_logits_capacity
+ s_logits_size
+ s_logits
+ s_embedding_size
+ s_embedding
+ s_kv_size
+ s_kv_ntok
+ s_kv
);
return s_total;
}
// Copies the state to the specified destination address
size_t llama_copy_state_data(struct llama_context * ctx, uint8_t * dest) {
std::stringstream rng_ss;
rng_ss << ctx->rng;
const size_t rng_size = rng_ss.str().size();
char rng_buf[64*1024];
memset(&rng_buf[0], 0, 64*1024);
memcpy(&rng_buf[0], rng_ss.str().data(), rng_ss.str().size());
const size_t logits_capacity = ctx->logits.capacity();
const size_t logits_size = ctx->logits.size();
const size_t embedding_size = ctx->embedding.size();
const size_t kv_size = llama_get_kv_cache_size(ctx);
const int kv_ntok = llama_get_kv_cache_token_count(ctx);
uint8_t * out = dest;
memcpy(out, &rng_size, sizeof(size_t)); out += sizeof(size_t);
memcpy(out, &rng_buf[0], 64*1024); out += 64*1024;
memcpy(out, &logits_capacity, sizeof(size_t)); out += sizeof(size_t);
memcpy(out, &logits_size, sizeof(size_t)); out += sizeof(size_t);
if (logits_size) {
memcpy(out, ctx->logits.data(), logits_size * sizeof(float));
}
out += logits_capacity * sizeof(float);
memcpy(out, &embedding_size, sizeof(size_t)); out += sizeof(size_t);
if (embedding_size) {
memcpy(out, ctx->embedding.data(), embedding_size * sizeof(float)); out += embedding_size * sizeof(float);
}
memcpy(out, &kv_size, sizeof(size_t)); out += sizeof(size_t);
memcpy(out, &kv_ntok, sizeof(int)); out += sizeof(int);
if (kv_size) {
memcpy(out, llama_get_kv_cache(ctx), kv_size); out += kv_size;
}
const size_t written = out - dest;
const size_t expected = llama_get_state_size(ctx);
LLAMA_ASSERT(written == expected);
return written;
}
// Sets the state reading from the specified source address
size_t llama_set_state_data(struct llama_context * ctx, const uint8_t * src) {
size_t rng_size;
char rng_buf[64*1024];
std::stringstream rng_ss;
const uint8_t * in = src;
memcpy(&rng_size, in, sizeof(size_t)); in += sizeof(size_t);
memcpy(&rng_buf[0], in, 64*1024); in += 64*1024;
rng_ss.str(std::string(&rng_buf[0], rng_size));
rng_ss >> ctx->rng;
LLAMA_ASSERT(rng_ss.fail() == false);
size_t logits_capacity;
size_t logits_size;
size_t embedding_size;
size_t kv_size;
int kv_ntok;
memcpy(&logits_capacity, in, sizeof(size_t)); in += sizeof(size_t);
memcpy(&logits_size, in, sizeof(size_t)); in += sizeof(size_t);
LLAMA_ASSERT(ctx->logits.capacity() == logits_capacity);
if (logits_size) {
ctx->logits.resize(logits_size);
memcpy(ctx->logits.data(), in, logits_size * sizeof(float));
}
in += logits_capacity * sizeof(float);
memcpy(&embedding_size, in, sizeof(size_t)); in += sizeof(size_t);
LLAMA_ASSERT(ctx->embedding.capacity() == embedding_size);
if (embedding_size) {
memcpy(ctx->embedding.data(), in, embedding_size * sizeof(float));
in += embedding_size * sizeof(float);
}
memcpy(&kv_size, in, sizeof(size_t)); in += sizeof(size_t);
memcpy(&kv_ntok, in, sizeof(int)); in += sizeof(int);
if (kv_size) {
LLAMA_ASSERT(ctx->model.kv_self.buf.size == kv_size);
void * k_data = ctx->model.kv_self.k->data; // remember data pointers
void * v_data = ctx->model.kv_self.v->data; // because their value is stored in buf and overwritten by memcpy
memcpy(ctx->model.kv_self.buf.addr, in, kv_size);
ctx->model.kv_self.k->data = k_data; // restore correct data pointers
ctx->model.kv_self.v->data = v_data;
in += kv_size;
}
ctx->model.kv_self.n = kv_ntok;
const size_t nread = in - src;
const size_t expected = llama_get_state_size(ctx);
LLAMA_ASSERT(nread == expected);
return nread;
}

12
llama.h
View file

@ -129,6 +129,18 @@ extern "C" {
size_t n_size,
int n_token_count);
// Returns the size in bytes of the state (rng, logits, embedding and kv_cache)
LLAMA_API size_t llama_get_state_size(struct llama_context * ctx);
// Copies the state to the specified destination address.
// Destination needs to have allocated enough memory.
// Returns the number of bytes copied
LLAMA_API size_t llama_copy_state_data(struct llama_context * ctx, uint8_t * dest);
// Set the state reading from the specified address
// Returns the number of bytes read
LLAMA_API size_t llama_set_state_data(struct llama_context * ctx, const uint8_t * src);
// Run the llama inference to obtain the logits and probabilities for the next token.
// tokens + n_tokens is the provided batch of new tokens to process
// n_past is the number of tokens to use from previous eval calls