mirror of
https://github.com/ggerganov/llama.cpp.git
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ggml : add Q8_0 quantization format (rename the old one to Q8_1) (ARM NEON) (#1179)
* ggml : add Q8_0 quantization format (rename the old one to Q8_1) * tests : fix test-quantize-fns * ggml : finalize Q8_0 implementation * ggml : use q4_0_q8_0 and q4_2_q8_0 * ggml : fix Q8_0 dot product bug (ARM) * ggml : Q8_0 unroll x2 * ggml : fix bug - using wrong block type * ggml : extend quantize_fns_t with "vec_dot_type" * ggml : fix Q8_0 to use 255 values out of 256 * ggml : fix assert using wrong QK4_2 instead of QK4_3
This commit is contained in:
Georgi Gerganov
GitHub
parent
dd0eabc049
commit
7a32fcb3b2
@ -16,6 +16,7 @@ int main(int argc, char ** argv) {
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fprintf(stderr, " type = %d - q4_1\n", LLAMA_FTYPE_MOSTLY_Q4_1);
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fprintf(stderr, " type = %d - q4_2\n", LLAMA_FTYPE_MOSTLY_Q4_2);
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fprintf(stderr, " type = %d - q4_3\n", LLAMA_FTYPE_MOSTLY_Q4_3);
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fprintf(stderr, " type = %d - q8_0\n", LLAMA_FTYPE_MOSTLY_Q8_0);
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return 1;
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}
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28
ggml-cuda.cu
28
ggml-cuda.cu
@ -37,6 +37,13 @@ typedef struct {
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} block_q4_3;
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static_assert(sizeof(block_q4_3) == 2 * sizeof(ggml_fp16_t) + QK4_3 / 2, "wrong q4_3 block size/padding");
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#define QK8_0 32
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typedef struct {
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float d; // delta
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int8_t qs[QK8_0]; // quants
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} block_q8_0;
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static_assert(sizeof(block_q8_0) == sizeof(float) + QK8_0, "wrong q8_0 block size/padding");
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static __global__ void dequantize_block_q4_0(const void * vx, float * y) {
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const block_q4_0 * x = (const block_q4_0 *) vx;
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@ -131,6 +138,22 @@ static __global__ void dequantize_block_q4_3(const void * vx, float * y) {
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}
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}
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static __global__ void dequantize_block_q8_0(const void * vx, float * y) {
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const block_q8_0 * x = (const block_q8_0 *) vx;
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const int i = blockIdx.x;
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const float d = x[i].d;
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const int8_t * pp = x[i].qs;
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for (int l = 0; l < QK8_0; l++) {
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const int8_t vi = pp[l];
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y[i*QK8_0 + l] = vi*d;
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}
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}
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void dequantize_row_q4_0_cuda(const void * vx, float * y, int k, cudaStream_t stream) {
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const int nb = k / QK4_0;
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dequantize_block_q4_0<<<nb, 1, 0, stream>>>(vx, y);
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@ -151,6 +174,11 @@ void dequantize_row_q4_3_cuda(const void * vx, float * y, int k, cudaStream_t st
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dequantize_block_q4_3<<<nb, 1, 0, stream>>>(vx, y);
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}
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void dequantize_row_q8_0_cuda(const void * vx, float * y, int k, cudaStream_t stream) {
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const int nb = k / QK8_0;
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dequantize_block_q8_0<<<nb, 1, 0, stream>>>(vx, y);
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}
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// buffer pool for cuda
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#define MAX_CUDA_BUFFERS 16
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@ -35,6 +35,7 @@ void dequantize_row_q4_0_cuda(const void * vx, float * y, int k, cudaStream_t st
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void dequantize_row_q4_1_cuda(const void * vx, float * y, int k, cudaStream_t stream);
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void dequantize_row_q4_2_cuda(const void * vx, float * y, int k, cudaStream_t stream);
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void dequantize_row_q4_3_cuda(const void * vx, float * y, int k, cudaStream_t stream);
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void dequantize_row_q8_0_cuda(const void * vx, float * y, int k, cudaStream_t stream);
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#ifdef __cplusplus
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}
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407
ggml.c
407
ggml.c
@ -676,12 +676,18 @@ static_assert(sizeof(block_q4_3) == 2 * sizeof(ggml_fp16_t) + QK4_3 / 2, "wrong
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#define QK8_0 32
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typedef struct {
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float d; // delta
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float s0; // d * sum(qs[i]) low
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float s1; // d * sum(qs[i]) high
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int8_t qs[QK8_0]; // quants
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} block_q8_0;
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static_assert(sizeof(block_q8_0) == 3*sizeof(float) + QK8_0, "wrong q8_0 block size/padding");
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static_assert(sizeof(block_q8_0) == sizeof(float) + QK8_0, "wrong q8_0 block size/padding");
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#define QK8_1 32
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typedef struct {
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float d; // delta
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float s0; // d * sum(qs[i]) low
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float s1; // d * sum(qs[i]) high
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int8_t qs[QK8_1]; // quants
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} block_q8_1;
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static_assert(sizeof(block_q8_1) == 3*sizeof(float) + QK8_1, "wrong q8_1 block size/padding");
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// reference implementation for deterministic creation of model files
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static void quantize_row_q4_0_reference(const float * restrict x, block_q4_0 * restrict y, int k) {
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@ -1231,85 +1237,6 @@ static void quantize_row_q4_2_reference(const float * restrict x, block_q4_2 * r
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}
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}
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static inline int nearest_int(float fval) {
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assert(fval <= 4194303.f);
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float val = fval + 12582912.f;
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int i; memcpy(&i, &val, sizeof(int));
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return (i & 0x007fffff) - 0x00400000;
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}
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static float kquantize_q4_with_bounds(int n, int nmin, int nmax, const float * restrict X, int nCandidates,
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const float * restrict candidates, int8_t * restrict L) {
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assert (nmin >= INT8_MIN);
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assert (nmax <= INT8_MAX);
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float amax = 0;
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for (int i=0; i<n; ++i) amax = MAX(amax, fabsf(X[i]));
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if (!amax) { // all zero
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for (int i=0; i<n; ++i) L[i] = 0;
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return 1.f;
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}
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float best = 0, bestScale = 0;
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for (int si=0; si<nCandidates; ++si) {
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float iscale = candidates[si]/amax;
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float sumlxP = 0; int suml2P = 0;
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float sumlxM = 0; int suml2M = 0;
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for (int i=0; i<n; ++i) {
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int l = nearest_int(iscale*X[i]);
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int lp = MAX(nmin, MIN(nmax, +l));
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int lm = MAX(nmin, MIN(nmax, -l));
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sumlxP += X[i]*lp; suml2P += lp*lp;
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sumlxM += X[i]*lm; suml2M += lm*lm;
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}
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float sumlxP2 = sumlxP*sumlxP;
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float sumlxM2 = sumlxM*sumlxM;
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if (sumlxP2*suml2M > sumlxM2*suml2P) {
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if (sumlxP2 > best*suml2P) {
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best = sumlxP2/suml2P; bestScale = iscale;
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}
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} else {
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if (sumlxM2 > best*suml2M) {
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best = sumlxM2/suml2M; bestScale = -iscale;
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}
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}
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}
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float sumlx = 0; int suml2 = 0;
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for (int i=0; i<n; ++i) {
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int l = nearest_int(bestScale*X[i]);
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l = MAX(nmin, MIN(nmax, l));
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sumlx += X[i]*l; suml2 += l*l;
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L[i] = l;
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}
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float scale = sumlx/suml2;
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return scale;
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}
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static void quantize_row_q4_2_rmse(const float * restrict x, block_q4_2 * restrict y, int k) {
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#define CANDIDATE_COUNT 8
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static const float candidates[CANDIDATE_COUNT] = { +8.7f, +8.3f, +8.1f, +7.8f, +7.3f, +7.0f, +6.3f, +5.7f };
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assert(k % QK4_2 == 0);
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int8_t L[QK4_2];
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const int nb = k / QK4_2;
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for (int i = 0; i < nb; i++) {
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float scale = kquantize_q4_with_bounds(QK4_2, -8, 7, x, CANDIDATE_COUNT, candidates, L);
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y[i].d = GGML_FP32_TO_FP16(scale);
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for (int l = 0; l < QK4_2; l += 2) {
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const uint8_t vi0 = (uint8_t)(L[l+0] + 8);
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const uint8_t vi1 = (uint8_t)(L[l+1] + 8);
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assert(vi0 < 16);
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assert(vi1 < 16);
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y[i].qs[l/2] = vi0 | (vi1 << 4);
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}
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x += QK4_2;
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}
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}
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static void quantize_row_q4_2(const float * restrict x, void * restrict vy, int k) {
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assert(k % QK4_2 == 0);
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@ -1379,18 +1306,52 @@ static void quantize_row_q8_0_reference(const float * restrict x, block_q8_0 * r
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y[i].d = d;
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for (int l = 0; l < QK8_0; ++l) {
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const float v0 = x[i*QK8_0 + l]*id;
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y[i].qs[l] = roundf(v0);
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}
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}
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}
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static void quantize_row_q8_0(const float * restrict x, void * restrict vy, int k) {
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assert(k % QK8_0 == 0);
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block_q8_0 * restrict y = vy;
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quantize_row_q8_0_reference(x, y, k);
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}
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// reference implementation for deterministic creation of model files
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static void quantize_row_q8_1_reference(const float * restrict x, block_q8_1 * restrict y, int k) {
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assert(k % QK8_1 == 0);
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const int nb = k / QK8_1;
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for (int i = 0; i < nb; i++) {
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float amax = 0.0f; // absolute max
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for (int l = 0; l < QK8_1; l++) {
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const float v = x[i*QK8_1 + l];
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amax = MAX(amax, fabsf(v));
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}
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const float d = amax / ((1 << 7) - 1);
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const float id = d ? 1.0f/d : 0.0f;
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y[i].d = d;
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int sum0 = 0;
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int sum1 = 0;
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for (int l = 0; l < QK8_0/2; ++l) {
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const float v0 = x[i*QK8_0 + l]*id;
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const float v1 = x[i*QK8_0 + QK8_0/2 + l]*id;
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for (int l = 0; l < QK8_1/2; ++l) {
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const float v0 = x[i*QK8_1 + l]*id;
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const float v1 = x[i*QK8_1 + QK8_1/2 + l]*id;
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y[i].qs[ l] = roundf(v0);
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y[i].qs[QK8_0/2 + l] = roundf(v1);
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y[i].qs[QK8_1/2 + l] = roundf(v1);
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sum0 += y[i].qs[ l];
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sum1 += y[i].qs[QK8_0/2 + l];
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sum1 += y[i].qs[QK8_1/2 + l];
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}
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y[i].s0 = d * sum0;
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@ -1398,11 +1359,11 @@ static void quantize_row_q8_0_reference(const float * restrict x, block_q8_0 * r
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}
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}
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static void quantize_row_q8_0(const float * restrict x, void * restrict vy, int k) {
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assert(k % QK8_0 == 0);
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const int nb = k / QK8_0;
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static void quantize_row_q8_1(const float * restrict x, void * restrict vy, int k) {
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assert(k % QK8_1 == 0);
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const int nb = k / QK8_1;
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block_q8_0 * restrict y = vy;
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block_q8_1 * restrict y = vy;
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#if defined(__ARM_NEON)
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for (int i = 0; i < nb; i++) {
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@ -1556,7 +1517,7 @@ static void quantize_row_q8_0(const float * restrict x, void * restrict vy, int
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}
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#else
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// scalar
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quantize_row_q8_0_reference(x, y, k);
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quantize_row_q8_1_reference(x, y, k);
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#endif
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}
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@ -1843,10 +1804,28 @@ static void dequantize_row_q4_3(const void * restrict vx, float * restrict y, in
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}
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}
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static void dequantize_row_q8_0(const void * restrict vx, float * restrict y, int k) {
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assert(k % QK8_0 == 0);
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const int nb = k / QK8_0;
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const block_q8_0 * restrict x = vx;
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for (int i = 0; i < nb; i++) {
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const float d = x[i].d;
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const int8_t * restrict pp = x[i].qs;
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for (int l = 0; l < QK8_0; ++l) {
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y[i*QK8_0 + l] = pp[l]*d;
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}
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}
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}
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static void ggml_vec_dot_q4_0_q8_0(const int n, float * restrict s, const void * restrict vx, const void * restrict vy);
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static void ggml_vec_dot_q4_1_q8_0(const int n, float * restrict s, const void * restrict vx, const void * restrict vy);
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static void ggml_vec_dot_q4_1_q8_1(const int n, float * restrict s, const void * restrict vx, const void * restrict vy);
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static void ggml_vec_dot_q4_2_q8_0(const int n, float * restrict s, const void * restrict vx, const void * restrict vy);
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static void ggml_vec_dot_q4_3_q8_0(const int n, float * restrict s, const void * restrict vx, const void * restrict vy);
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static void ggml_vec_dot_q4_3_q8_1(const int n, float * restrict s, const void * restrict vx, const void * restrict vy);
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static void ggml_vec_dot_q8_0_q8_0(const int n, float * restrict s, const void * restrict vx, const void * restrict vy);
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static const quantize_fns_t quantize_fns[GGML_TYPE_COUNT] = {
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[GGML_TYPE_Q4_0] = {
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@ -1855,13 +1834,15 @@ static const quantize_fns_t quantize_fns[GGML_TYPE_COUNT] = {
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.quantize_row_q_reference = (quantize_row_q_t) quantize_row_q4_0_reference,
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.quantize_row_q_dot = quantize_row_q8_0,
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.vec_dot_q = ggml_vec_dot_q4_0_q8_0,
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.vec_dot_type = GGML_TYPE_Q8_0,
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},
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[GGML_TYPE_Q4_1] = {
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.dequantize_row_q = dequantize_row_q4_1,
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.quantize_row_q = quantize_row_q4_1,
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.quantize_row_q_reference = (quantize_row_q_t) quantize_row_q4_1_reference,
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.quantize_row_q_dot = quantize_row_q8_0,
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.vec_dot_q = ggml_vec_dot_q4_1_q8_0,
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.quantize_row_q_dot = quantize_row_q8_1,
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.vec_dot_q = ggml_vec_dot_q4_1_q8_1,
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.vec_dot_type = GGML_TYPE_Q8_1,
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},
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[GGML_TYPE_Q4_2] = {
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.dequantize_row_q = dequantize_row_q4_2,
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@ -1869,20 +1850,31 @@ static const quantize_fns_t quantize_fns[GGML_TYPE_COUNT] = {
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.quantize_row_q_reference = (quantize_row_q_t) quantize_row_q4_2_reference,
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.quantize_row_q_dot = quantize_row_q8_0,
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.vec_dot_q = ggml_vec_dot_q4_2_q8_0,
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.vec_dot_type = GGML_TYPE_Q8_0,
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},
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[GGML_TYPE_Q4_3] = {
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.dequantize_row_q = dequantize_row_q4_3,
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.quantize_row_q = quantize_row_q4_3,
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.quantize_row_q_reference = (quantize_row_q_t) quantize_row_q4_3_reference, // TODO: RMSE optimization
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.quantize_row_q_dot = quantize_row_q8_0,
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.vec_dot_q = ggml_vec_dot_q4_3_q8_0,
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.quantize_row_q_reference = (quantize_row_q_t) quantize_row_q4_3_reference,
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.quantize_row_q_dot = quantize_row_q8_1,
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.vec_dot_q = ggml_vec_dot_q4_3_q8_1,
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.vec_dot_type = GGML_TYPE_Q8_1,
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},
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[GGML_TYPE_Q8_0] = {
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.dequantize_row_q = NULL, // TODO
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.dequantize_row_q = dequantize_row_q8_0,
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.quantize_row_q = quantize_row_q8_0,
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.quantize_row_q_reference = (quantize_row_q_t) quantize_row_q8_0_reference,
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.quantize_row_q_dot = quantize_row_q8_0,
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.vec_dot_q = ggml_vec_dot_q8_0_q8_0,
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.vec_dot_type = GGML_TYPE_Q8_0,
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},
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[GGML_TYPE_Q8_1] = {
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.dequantize_row_q = NULL, // TODO
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.quantize_row_q = quantize_row_q8_1,
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.quantize_row_q_reference = (quantize_row_q_t) quantize_row_q8_1_reference,
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.quantize_row_q_dot = quantize_row_q8_1,
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.vec_dot_q = NULL, // TODO
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.vec_dot_type = GGML_TYPE_Q8_1,
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},
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};
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@ -2498,17 +2490,14 @@ static void ggml_vec_dot_q4_0_q8_0(const int n, float * restrict s, const void *
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float32x4_t sumv0 = vdupq_n_f32(0.0f);
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float32x4_t sumv1 = vdupq_n_f32(0.0f);
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float sum8 = 0;
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||||
for (int i = 0; i < nb; i += 2) {
|
||||
const block_q4_0 * restrict x0 = &x[i + 0];
|
||||
const block_q4_0 * restrict x1 = &x[i + 1];
|
||||
const block_q8_0 * restrict y0 = &y[i + 0];
|
||||
const block_q8_0 * restrict y1 = &y[i + 1];
|
||||
|
||||
sum8 += x0->d * (y0->s0 + y0->s1) + x1->d * (y1->s0 + y1->s1);
|
||||
|
||||
const uint8x16_t m4b = vdupq_n_u8(0xf);
|
||||
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);
|
||||
@ -2519,6 +2508,12 @@ static void ggml_vec_dot_q4_0_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));
|
||||
|
||||
// sub 8
|
||||
const int8x16_t v0_0ls = vsubq_s8(v0_0l, s8b);
|
||||
const int8x16_t v0_0hs = vsubq_s8(v0_0h, s8b);
|
||||
const int8x16_t v0_1ls = vsubq_s8(v0_1l, s8b);
|
||||
const int8x16_t v0_1hs = vsubq_s8(v0_1h, s8b);
|
||||
|
||||
// load y
|
||||
const int8x16_t v1_0l = vld1q_s8(y0->qs);
|
||||
const int8x16_t v1_0h = vld1q_s8(y0->qs + 16);
|
||||
@ -2533,21 +2528,21 @@ static void ggml_vec_dot_q4_0_q8_0(const int n, float * restrict s, const void *
|
||||
|
||||
#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_0ls, v1_0ls), v0_0hs, v1_0hs);
|
||||
const int32x4_t p_1 = vdotq_s32(vdotq_s32(vdupq_n_s32(0), v0_1ls, v1_1ls), v0_1hs, v1_1hs);
|
||||
|
||||
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);
|
||||
#else
|
||||
const int16x8_t pl0l = vmull_s8(vget_low_s8 (v0_0l), vget_low_s8 (v1_0ls));
|
||||
const int16x8_t pl0h = vmull_s8(vget_high_s8(v0_0l), vget_high_s8(v1_0ls));
|
||||
const int16x8_t ph0l = vmull_s8(vget_low_s8 (v0_0h), vget_low_s8 (v1_0hs));
|
||||
const int16x8_t ph0h = vmull_s8(vget_high_s8(v0_0h), vget_high_s8(v1_0hs));
|
||||
const int16x8_t pl0l = vmull_s8(vget_low_s8 (v0_0ls), vget_low_s8 (v1_0ls));
|
||||
const int16x8_t pl0h = vmull_s8(vget_high_s8(v0_0ls), vget_high_s8(v1_0ls));
|
||||
const int16x8_t ph0l = vmull_s8(vget_low_s8 (v0_0hs), vget_low_s8 (v1_0hs));
|
||||
const int16x8_t ph0h = vmull_s8(vget_high_s8(v0_0hs), vget_high_s8(v1_0hs));
|
||||
|
||||
const int16x8_t pl1l = vmull_s8(vget_low_s8 (v0_1l), vget_low_s8 (v1_1ls));
|
||||
const int16x8_t pl1h = vmull_s8(vget_high_s8(v0_1l), vget_high_s8(v1_1ls));
|
||||
const int16x8_t ph1l = vmull_s8(vget_low_s8 (v0_1h), vget_low_s8 (v1_1hs));
|
||||
const int16x8_t ph1h = vmull_s8(vget_high_s8(v0_1h), vget_high_s8(v1_1hs));
|
||||
const int16x8_t pl1l = vmull_s8(vget_low_s8 (v0_1ls), vget_low_s8 (v1_1ls));
|
||||
const int16x8_t pl1h = vmull_s8(vget_high_s8(v0_1ls), vget_high_s8(v1_1ls));
|
||||
const int16x8_t ph1l = vmull_s8(vget_low_s8 (v0_1hs), vget_low_s8 (v1_1hs));
|
||||
const int16x8_t ph1h = vmull_s8(vget_high_s8(v0_1hs), vget_high_s8(v1_1hs));
|
||||
|
||||
const int32x4_t pl0 = vaddq_s32(vpaddlq_s16(pl0l), vpaddlq_s16(pl0h));
|
||||
const int32x4_t ph0 = vaddq_s32(vpaddlq_s16(ph0l), vpaddlq_s16(ph0h));
|
||||
@ -2559,7 +2554,7 @@ static void ggml_vec_dot_q4_0_q8_0(const int n, float * restrict s, const void *
|
||||
#endif
|
||||
}
|
||||
|
||||
*s = vaddvq_f32(sumv0) + vaddvq_f32(sumv1) - 8 * sum8;
|
||||
*s = vaddvq_f32(sumv0) + vaddvq_f32(sumv1);
|
||||
#elif defined(__AVX2__)
|
||||
// Initialize accumulator with zeros
|
||||
__m256 acc = _mm256_setzero_ps();
|
||||
@ -2651,14 +2646,14 @@ static void ggml_vec_dot_q4_0_q8_0(const int n, float * restrict s, const void *
|
||||
#endif
|
||||
}
|
||||
|
||||
static void ggml_vec_dot_q4_1_q8_0(const int n, float * restrict s, const void * restrict vx, const void * restrict vy) {
|
||||
const int nb = n / QK8_0;
|
||||
static void ggml_vec_dot_q4_1_q8_1(const int n, float * restrict s, const void * restrict vx, const void * restrict vy) {
|
||||
const int nb = n / QK8_1;
|
||||
|
||||
assert(n % QK8_0 == 0);
|
||||
assert(n % QK8_1 == 0);
|
||||
assert(nb % 2 == 0);
|
||||
|
||||
const block_q4_1 * restrict x = vx;
|
||||
const block_q8_0 * restrict y = vy;
|
||||
const block_q8_1 * restrict y = vy;
|
||||
|
||||
// TODO: add AVX / WASM SIMD / etc
|
||||
#if defined(__ARM_NEON)
|
||||
@ -2670,8 +2665,8 @@ static void ggml_vec_dot_q4_1_q8_0(const int n, float * restrict s, const void *
|
||||
for (int i = 0; i < nb; i += 2) {
|
||||
const block_q4_1 * restrict x0 = &x[i + 0];
|
||||
const block_q4_1 * restrict x1 = &x[i + 1];
|
||||
const block_q8_0 * restrict y0 = &y[i + 0];
|
||||
const block_q8_0 * restrict y1 = &y[i + 1];
|
||||
const block_q8_1 * restrict y0 = &y[i + 0];
|
||||
const block_q8_1 * restrict y1 = &y[i + 1];
|
||||
|
||||
summs += x0->m * (y0->s0 + y0->s1) + x1->m * (y1->s0 + y1->s1);
|
||||
|
||||
@ -2769,7 +2764,7 @@ static void ggml_vec_dot_q4_1_q8_0(const int n, float * restrict s, const void *
|
||||
const int8_t * restrict p1 = y[i].qs;
|
||||
|
||||
// TODO: this is very slow ..
|
||||
for (int j = 0; j < QK8_0/2; j++) {
|
||||
for (int j = 0; j < QK8_1/2; j++) {
|
||||
const uint8_t v0 = p0[j];
|
||||
|
||||
const float f0 = d0*(v0 & 0xf) + m0;
|
||||
@ -2942,15 +2937,15 @@ static void ggml_vec_dot_q4_2_q8_0(const int n, float * restrict s, const void *
|
||||
#endif
|
||||
}
|
||||
|
||||
static void ggml_vec_dot_q4_3_q8_0(const int n, float * restrict s, const void * restrict vx, const void * restrict vy) {
|
||||
const int nb = n / QK8_0;
|
||||
static void ggml_vec_dot_q4_3_q8_1(const int n, float * restrict s, const void * restrict vx, const void * restrict vy) {
|
||||
const int nb = n / QK8_1;
|
||||
|
||||
assert(n % QK8_0 == 0);
|
||||
assert(n % QK8_1 == 0);
|
||||
assert(nb % 2 == 0);
|
||||
assert(QK8_0 == 2*QK4_2);
|
||||
assert(QK8_1 == 2*QK4_3);
|
||||
|
||||
const block_q4_3 * restrict x = vx;
|
||||
const block_q8_0 * restrict y = vy;
|
||||
const block_q8_1 * restrict y = vy;
|
||||
|
||||
#if defined(__ARM_NEON)
|
||||
float32x4_t sumv0 = vdupq_n_f32(0.0f);
|
||||
@ -2963,7 +2958,7 @@ static void ggml_vec_dot_q4_3_q8_0(const int n, float * restrict s, const void *
|
||||
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_q8_0 * restrict y0 = &y[i + 0];
|
||||
const block_q8_1 * restrict y0 = &y[i + 0];
|
||||
|
||||
summs0 += GGML_FP16_TO_FP32(x0_0->m) * y0->s0;
|
||||
summs1 += GGML_FP16_TO_FP32(x0_1->m) * y0->s1;
|
||||
@ -3046,7 +3041,7 @@ static void ggml_vec_dot_q4_3_q8_0(const int n, float * restrict s, const void *
|
||||
int sxy_0 = 0;
|
||||
int sxy_1 = 0;
|
||||
|
||||
for (int j = 0; j < QK8_0/4; j++) {
|
||||
for (int j = 0; j < QK8_1/4; j++) {
|
||||
const uint8_t v0 = x0[j];
|
||||
const uint8_t v1 = x1[j];
|
||||
|
||||
@ -3059,8 +3054,8 @@ static void ggml_vec_dot_q4_3_q8_0(const int n, float * restrict s, const void *
|
||||
const int y0_0 = y0[2*j + 0];
|
||||
const int y1_0 = y0[2*j + 1];
|
||||
|
||||
const int y0_1 = y0[2*(j + QK8_0/4) + 0];
|
||||
const int y1_1 = y0[2*(j + QK8_0/4) + 1];
|
||||
const int y0_1 = y0[2*(j + QK8_1/4) + 0];
|
||||
const int y1_1 = y0[2*(j + QK8_1/4) + 1];
|
||||
|
||||
sxy_0 += x0_0*y0_0 + x1_0*y1_0;
|
||||
sxy_1 += x0_1*y0_1 + x1_1*y1_1;
|
||||
@ -3072,6 +3067,91 @@ static void ggml_vec_dot_q4_3_q8_0(const int n, float * restrict s, const void *
|
||||
#endif
|
||||
}
|
||||
|
||||
static void ggml_vec_dot_q8_0_q8_0(const int n, float * restrict s, const void * restrict vx, const void * restrict vy) {
|
||||
const int nb = n / QK8_0;
|
||||
|
||||
assert(n % QK8_0 == 0);
|
||||
assert(nb % 2 == 0);
|
||||
assert(QK8_0 == QK8_0);
|
||||
|
||||
const block_q8_0 * restrict x = vx;
|
||||
const block_q8_0 * restrict y = vy;
|
||||
|
||||
#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) {
|
||||
const block_q8_0 * restrict x0 = &x[i + 0];
|
||||
const block_q8_0 * restrict x1 = &x[i + 1];
|
||||
const block_q8_0 * restrict y0 = &y[i + 0];
|
||||
const block_q8_0 * restrict y1 = &y[i + 1];
|
||||
|
||||
const int8x16_t x0_0 = vld1q_s8(x0->qs);
|
||||
const int8x16_t x0_1 = vld1q_s8(x0->qs + 16);
|
||||
const int8x16_t x1_0 = vld1q_s8(x1->qs);
|
||||
const int8x16_t x1_1 = vld1q_s8(x1->qs + 16);
|
||||
|
||||
// load y
|
||||
const int8x16_t y0_0 = vld1q_s8(y0->qs);
|
||||
const int8x16_t y0_1 = vld1q_s8(y0->qs + 16);
|
||||
const int8x16_t y1_0 = vld1q_s8(y1->qs);
|
||||
const int8x16_t y1_1 = vld1q_s8(y1->qs + 16);
|
||||
|
||||
#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);
|
||||
|
||||
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);
|
||||
|
||||
#else
|
||||
const int16x8_t p0_0 = vmull_s8(vget_low_s8 (x0_0), vget_low_s8 (y0_0));
|
||||
const int16x8_t p0_1 = vmull_s8(vget_high_s8(x0_0), vget_high_s8(y0_0));
|
||||
const int16x8_t p0_2 = vmull_s8(vget_low_s8 (x0_1), vget_low_s8 (y0_1));
|
||||
const int16x8_t p0_3 = vmull_s8(vget_high_s8(x0_1), vget_high_s8(y0_1));
|
||||
|
||||
const int16x8_t p1_0 = vmull_s8(vget_low_s8 (x1_0), vget_low_s8 (y1_0));
|
||||
const int16x8_t p1_1 = vmull_s8(vget_high_s8(x1_0), vget_high_s8(y1_0));
|
||||
const int16x8_t p1_2 = vmull_s8(vget_low_s8 (x1_1), vget_low_s8 (y1_1));
|
||||
const int16x8_t p1_3 = vmull_s8(vget_high_s8(x1_1), vget_high_s8(y1_1));
|
||||
|
||||
const int32x4_t p0 = vaddq_s32(vpaddlq_s16(p0_0), vpaddlq_s16(p0_1));
|
||||
const int32x4_t p1 = vaddq_s32(vpaddlq_s16(p0_2), vpaddlq_s16(p0_3));
|
||||
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);
|
||||
#endif
|
||||
}
|
||||
|
||||
*s = vaddvq_f32(sumv0) + vaddvq_f32(sumv1);
|
||||
#else
|
||||
// scalar
|
||||
float sumf = 0.0;
|
||||
|
||||
for (int i = 0; i < nb; i++) {
|
||||
const int8_t * restrict x0 = x[i].qs;
|
||||
const int8_t * restrict y0 = y[i].qs;
|
||||
|
||||
int sumi = 0;
|
||||
|
||||
for (int j = 0; j < QK8_0; j++) {
|
||||
const int v0 = x0[j];
|
||||
const int v1 = y0[j];
|
||||
|
||||
sumi += v0*v1;
|
||||
}
|
||||
|
||||
sumf += (x[i].d*y[i].d)*sumi;
|
||||
}
|
||||
|
||||
*s = sumf;
|
||||
#endif
|
||||
}
|
||||
|
||||
// compute GGML_VEC_DOT_UNROLL dot products at once
|
||||
// xs - x row stride in bytes
|
||||
@ -3269,6 +3349,14 @@ inline static void ggml_vec_sum_f32(const int n, float * s, const float * x) {
|
||||
#endif
|
||||
}
|
||||
|
||||
inline static void ggml_vec_sum_ggf(const int n, ggml_float * s, const float * x) {
|
||||
ggml_float sum = 0.0;
|
||||
for (int i = 0; i < n; ++i) {
|
||||
sum += (ggml_float)x[i];
|
||||
}
|
||||
*s = sum;
|
||||
}
|
||||
|
||||
inline static void ggml_vec_max_f32(const int n, float * s, const float * x) {
|
||||
#ifndef GGML_USE_ACCELERATE
|
||||
float max = -INFINITY;
|
||||
@ -3322,11 +3410,12 @@ static const int GGML_BLCK_SIZE[GGML_TYPE_COUNT] = {
|
||||
[GGML_TYPE_Q4_2] = QK4_2,
|
||||
[GGML_TYPE_Q4_3] = QK4_3,
|
||||
[GGML_TYPE_Q8_0] = QK8_0,
|
||||
[GGML_TYPE_Q8_1] = QK8_1,
|
||||
[GGML_TYPE_I8] = 1,
|
||||
[GGML_TYPE_I16] = 1,
|
||||
[GGML_TYPE_I32] = 1,
|
||||
};
|
||||
static_assert(GGML_TYPE_COUNT == 10, "GGML_BLCK_SIZE is outdated");
|
||||
static_assert(GGML_TYPE_COUNT == 11, "GGML_BLCK_SIZE is outdated");
|
||||
|
||||
static const size_t GGML_TYPE_SIZE[GGML_TYPE_COUNT] = {
|
||||
[GGML_TYPE_F32] = sizeof(float),
|
||||
@ -3336,11 +3425,12 @@ static const size_t GGML_TYPE_SIZE[GGML_TYPE_COUNT] = {
|
||||
[GGML_TYPE_Q4_2] = sizeof(block_q4_2),
|
||||
[GGML_TYPE_Q4_3] = sizeof(block_q4_3),
|
||||
[GGML_TYPE_Q8_0] = sizeof(block_q8_0),
|
||||
[GGML_TYPE_Q8_1] = sizeof(block_q8_1),
|
||||
[GGML_TYPE_I8] = sizeof(int8_t),
|
||||
[GGML_TYPE_I16] = sizeof(int16_t),
|
||||
[GGML_TYPE_I32] = sizeof(int32_t),
|
||||
};
|
||||
static_assert(GGML_TYPE_COUNT == 10, "GGML_TYPE_SIZE is outdated");
|
||||
static_assert(GGML_TYPE_COUNT == 11, "GGML_TYPE_SIZE is outdated");
|
||||
|
||||
|
||||
static const char * GGML_TYPE_NAME[GGML_TYPE_COUNT] = {
|
||||
@ -3351,11 +3441,12 @@ static const char * GGML_TYPE_NAME[GGML_TYPE_COUNT] = {
|
||||
[GGML_TYPE_Q4_2] = "q4_2",
|
||||
[GGML_TYPE_Q4_3] = "q4_3",
|
||||
[GGML_TYPE_Q8_0] = "q8_0",
|
||||
[GGML_TYPE_Q8_1] = "q8_1",
|
||||
[GGML_TYPE_I8] = "i8",
|
||||
[GGML_TYPE_I16] = "i16",
|
||||
[GGML_TYPE_I32] = "i32",
|
||||
};
|
||||
static_assert(GGML_TYPE_COUNT == 10, "GGML_TYPE_NAME is outdated");
|
||||
static_assert(GGML_TYPE_COUNT == 11, "GGML_TYPE_NAME is outdated");
|
||||
|
||||
static bool GGML_IS_QUANTIZED[GGML_TYPE_COUNT] = {
|
||||
[GGML_TYPE_F32] = false,
|
||||
@ -3365,11 +3456,12 @@ static bool GGML_IS_QUANTIZED[GGML_TYPE_COUNT] = {
|
||||
[GGML_TYPE_Q4_2] = true,
|
||||
[GGML_TYPE_Q4_3] = true,
|
||||
[GGML_TYPE_Q8_0] = true,
|
||||
[GGML_TYPE_Q8_1] = true,
|
||||
[GGML_TYPE_I8] = false,
|
||||
[GGML_TYPE_I16] = false,
|
||||
[GGML_TYPE_I32] = false,
|
||||
};
|
||||
static_assert(GGML_TYPE_COUNT == 10, "GGML_IS_QUANTIZED is outdated");
|
||||
static_assert(GGML_TYPE_COUNT == 11, "GGML_IS_QUANTIZED is outdated");
|
||||
|
||||
static const char * GGML_OP_LABEL[GGML_OP_COUNT] = {
|
||||
"NONE",
|
||||
@ -6581,6 +6673,7 @@ static void ggml_compute_forward_add(
|
||||
case GGML_TYPE_Q4_1:
|
||||
case GGML_TYPE_Q4_2:
|
||||
case GGML_TYPE_Q4_3:
|
||||
case GGML_TYPE_Q8_0:
|
||||
{
|
||||
ggml_compute_forward_add_q_f32(params, src0, src1, dst);
|
||||
} break;
|
||||
@ -6839,12 +6932,12 @@ static void ggml_compute_forward_sum_f32(
|
||||
const size_t nb03 = src0->nb[3];
|
||||
|
||||
ggml_float sum = 0;
|
||||
float row_sum = 0;
|
||||
ggml_float row_sum = 0;
|
||||
|
||||
for (int64_t i03 = 0; i03 < ne03; i03++) {
|
||||
for (int64_t i02 = 0; i02 < ne02; i02++) {
|
||||
for (int64_t i01 = 0; i01 < ne01; i01++) {
|
||||
ggml_vec_sum_f32(ne00,
|
||||
ggml_vec_sum_ggf(ne00,
|
||||
&row_sum,
|
||||
(float *) ((char *) src0->data + i01*nb01 + i02*nb02 + i03*nb03));
|
||||
sum += row_sum;
|
||||
@ -8008,6 +8101,7 @@ static void ggml_compute_forward_mul_mat_q_f32(
|
||||
const enum ggml_type type = src0->type;
|
||||
quantize_row_q_t const quantize_row_q_dot = quantize_fns[type].quantize_row_q_dot;
|
||||
vec_dot_q_t const vec_dot_q = quantize_fns[type].vec_dot_q;
|
||||
enum ggml_type const vec_dot_type = quantize_fns[type].vec_dot_type;
|
||||
|
||||
// we don't support permuted src0 or src1
|
||||
GGML_ASSERT(nb00 == (int) GGML_TYPE_SIZE[type]);
|
||||
@ -8067,6 +8161,9 @@ static void ggml_compute_forward_mul_mat_q_f32(
|
||||
else if (type == GGML_TYPE_Q4_3) {
|
||||
dequantize_row_q_cuda = dequantize_row_q4_3_cuda;
|
||||
}
|
||||
else if (type == GGML_TYPE_Q8_0) {
|
||||
dequantize_row_q_cuda = dequantize_row_q8_0_cuda;
|
||||
}
|
||||
else {
|
||||
GGML_ASSERT(false);
|
||||
}
|
||||
@ -8141,7 +8238,7 @@ static void ggml_compute_forward_mul_mat_q_f32(
|
||||
|
||||
if (params->type == GGML_TASK_INIT) {
|
||||
char * wdata = params->wdata;
|
||||
const size_t row_size = ne10*GGML_TYPE_SIZE[GGML_TYPE_Q8_0]/GGML_BLCK_SIZE[GGML_TYPE_Q8_0];
|
||||
const size_t row_size = ne10*GGML_TYPE_SIZE[vec_dot_type]/GGML_BLCK_SIZE[vec_dot_type];
|
||||
|
||||
for (int64_t i13 = 0; i13 < ne13; ++i13) {
|
||||
for (int64_t i12 = 0; i12 < ne12; ++i12) {
|
||||
@ -8172,7 +8269,7 @@ static void ggml_compute_forward_mul_mat_q_f32(
|
||||
const int ir1 = MIN(ir0 + dr, nr);
|
||||
|
||||
void * wdata = params->wdata;
|
||||
const size_t row_size = ne00*GGML_TYPE_SIZE[GGML_TYPE_Q8_0]/GGML_BLCK_SIZE[GGML_TYPE_Q8_0];
|
||||
const size_t row_size = ne00*GGML_TYPE_SIZE[vec_dot_type]/GGML_BLCK_SIZE[vec_dot_type];
|
||||
|
||||
for (int ir = ir0; ir < ir1; ++ir) {
|
||||
// src0 indices
|
||||
@ -8223,6 +8320,7 @@ static void ggml_compute_forward_mul_mat(
|
||||
case GGML_TYPE_Q4_2:
|
||||
case GGML_TYPE_Q4_3:
|
||||
case GGML_TYPE_Q8_0:
|
||||
case GGML_TYPE_Q8_1:
|
||||
{
|
||||
ggml_compute_forward_mul_mat_q_f32(params, src0, src1, dst);
|
||||
} break;
|
||||
@ -8452,6 +8550,7 @@ static void ggml_compute_forward_get_rows(
|
||||
case GGML_TYPE_Q4_2:
|
||||
case GGML_TYPE_Q4_3:
|
||||
case GGML_TYPE_Q8_0:
|
||||
case GGML_TYPE_Q8_1:
|
||||
{
|
||||
ggml_compute_forward_get_rows_q(params, src0, src1, dst);
|
||||
} break;
|
||||
@ -10973,7 +11072,8 @@ void ggml_graph_compute(struct ggml_context * ctx, struct ggml_cgraph * cgraph)
|
||||
} else
|
||||
#endif
|
||||
{
|
||||
cur = GGML_TYPE_SIZE[GGML_TYPE_Q8_0]*ggml_nelements(node->src1)/GGML_BLCK_SIZE[GGML_TYPE_Q8_0];
|
||||
const enum ggml_type type_q = quantize_fns[node->src0->type].vec_dot_type;
|
||||
cur = GGML_TYPE_SIZE[type_q]*ggml_nelements(node->src1)/GGML_BLCK_SIZE[type_q];
|
||||
}
|
||||
} else {
|
||||
GGML_ASSERT(false);
|
||||
@ -12242,6 +12342,27 @@ size_t ggml_quantize_q4_3(const float * src, void * dst, int n, int k, int64_t *
|
||||
return (n/QK4_3*sizeof(block_q4_3));
|
||||
}
|
||||
|
||||
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 j = 0; j < n; j += k) {
|
||||
block_q8_0 * restrict y = (block_q8_0 *)dst + j/QK8_0;
|
||||
|
||||
quantize_row_q8_0_reference(src + j, y, k);
|
||||
|
||||
for (int i = 0; i < nb; i++) {
|
||||
for (int l = 0; l < QK8_0; ++l) {
|
||||
const int8_t vi = y[i].qs[l];
|
||||
|
||||
hist[vi/16 + 8]++;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
return (n/QK8_0*sizeof(block_q8_0));
|
||||
}
|
||||
|
||||
size_t ggml_quantize_chunk(enum ggml_type type, const float * src, void * dst, int start, int n, int64_t * hist) {
|
||||
size_t result = 0;
|
||||
switch (type) {
|
||||
@ -12269,6 +12390,12 @@ size_t ggml_quantize_chunk(enum ggml_type type, const float * src, void * dst, i
|
||||
block_q4_3 * block = (block_q4_3*)dst + start / QK4_3;
|
||||
result = ggml_quantize_q4_3(src + start, block, n, n, hist);
|
||||
} 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;
|
||||
default:
|
||||
assert(false);
|
||||
}
|
||||
|
||||
3
ggml.h
3
ggml.h
@ -223,6 +223,7 @@ extern "C" {
|
||||
GGML_TYPE_Q4_2 = 4,
|
||||
GGML_TYPE_Q4_3 = 5,
|
||||
GGML_TYPE_Q8_0 = 6,
|
||||
GGML_TYPE_Q8_1 = 7,
|
||||
GGML_TYPE_I8,
|
||||
GGML_TYPE_I16,
|
||||
GGML_TYPE_I32,
|
||||
@ -832,6 +833,7 @@ extern "C" {
|
||||
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_q4_2(const float * src, void * dst, int n, int k, int64_t * hist);
|
||||
GGML_API size_t ggml_quantize_q4_3(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_chunk(enum ggml_type type, const float * src, void * dst, int start, int n, int64_t * hist);
|
||||
|
||||
@ -876,6 +878,7 @@ extern "C" {
|
||||
quantize_row_q_t quantize_row_q_reference;
|
||||
quantize_row_q_t quantize_row_q_dot;
|
||||
vec_dot_q_t vec_dot_q;
|
||||
enum ggml_type vec_dot_type;
|
||||
} quantize_fns_t;
|
||||
|
||||
quantize_fns_t ggml_internal_get_quantize_fn(size_t i);
|
||||
|
||||
@ -484,6 +484,7 @@ struct llama_file_loader {
|
||||
case GGML_TYPE_Q4_1:
|
||||
case GGML_TYPE_Q4_2:
|
||||
case GGML_TYPE_Q4_3:
|
||||
case GGML_TYPE_Q8_0:
|
||||
break;
|
||||
default: {
|
||||
throw format("unrecognized tensor type %u\n", shard.type);
|
||||
@ -558,6 +559,7 @@ struct llama_file_saver {
|
||||
case GGML_TYPE_Q4_1:
|
||||
case GGML_TYPE_Q4_2:
|
||||
case GGML_TYPE_Q4_3:
|
||||
case GGML_TYPE_Q8_0:
|
||||
break;
|
||||
default: LLAMA_ASSERT(false);
|
||||
}
|
||||
@ -848,6 +850,7 @@ static const char *llama_ftype_name(enum llama_ftype ftype) {
|
||||
return "mostly Q4_1, some F16";
|
||||
case LLAMA_FTYPE_MOSTLY_Q4_2: return "mostly Q4_2";
|
||||
case LLAMA_FTYPE_MOSTLY_Q4_3: return "mostly Q4_3";
|
||||
case LLAMA_FTYPE_MOSTLY_Q8_0: return "mostly Q8_0";
|
||||
default: return "unknown, may not work";
|
||||
}
|
||||
}
|
||||
@ -1585,6 +1588,7 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
|
||||
case LLAMA_FTYPE_MOSTLY_Q4_1: quantized_type = GGML_TYPE_Q4_1; break;
|
||||
case LLAMA_FTYPE_MOSTLY_Q4_2: quantized_type = GGML_TYPE_Q4_2; break;
|
||||
case LLAMA_FTYPE_MOSTLY_Q4_3: quantized_type = GGML_TYPE_Q4_3; break;
|
||||
case LLAMA_FTYPE_MOSTLY_Q8_0: quantized_type = GGML_TYPE_Q8_0; break;
|
||||
default: throw format("invalid output file type %d\n", ftype);
|
||||
};
|
||||
|
||||
|
||||
1
llama.h
1
llama.h
@ -74,6 +74,7 @@ extern "C" {
|
||||
LLAMA_FTYPE_MOSTLY_Q4_1_SOME_F16 = 4, // tok_embeddings.weight and output.weight are F16
|
||||
LLAMA_FTYPE_MOSTLY_Q4_2 = 5, // except 1d tensors
|
||||
LLAMA_FTYPE_MOSTLY_Q4_3 = 6, // except 1d tensors
|
||||
LLAMA_FTYPE_MOSTLY_Q8_0 = 7, // except 1d tensors
|
||||
};
|
||||
|
||||
LLAMA_API struct llama_context_params llama_context_default_params();
|
||||
|
||||
@ -36,7 +36,7 @@ float array_rmse(const float * a1, const float * a2, size_t n) {
|
||||
|
||||
// Total quantization error on test data
|
||||
float total_quantization_error(quantize_fns_t & qfns, size_t test_size, const float * test_data) {
|
||||
std::vector<uint8_t> tmp_q(test_size);
|
||||
std::vector<uint8_t> tmp_q(2*test_size);
|
||||
std::vector<float> tmp_out(test_size);
|
||||
|
||||
qfns.quantize_row_q(test_data, tmp_q.data(), test_size);
|
||||
@ -46,7 +46,7 @@ float total_quantization_error(quantize_fns_t & qfns, size_t test_size, const fl
|
||||
|
||||
// Total quantization error on test data
|
||||
float reference_quantization_error(quantize_fns_t & qfns, size_t test_size, const float * test_data) {
|
||||
std::vector<uint8_t> tmp_q(test_size);
|
||||
std::vector<uint8_t> tmp_q(2*test_size);
|
||||
std::vector<float> tmp_out(test_size);
|
||||
std::vector<float> tmp_out_ref(test_size);
|
||||
|
||||
@ -69,10 +69,10 @@ float dot_product(const float * a1, const float * a2, size_t test_size) {
|
||||
|
||||
// Total dot product error
|
||||
float dot_product_error(quantize_fns_t & qfns, size_t test_size, const float * test_data1, const float *test_data2) {
|
||||
std::vector<uint8_t> tmp_q1(test_size);
|
||||
std::vector<uint8_t> tmp_q2(test_size*2);
|
||||
std::vector<uint8_t> tmp_q1(2*test_size);
|
||||
std::vector<uint8_t> tmp_q2(2*test_size);
|
||||
|
||||
qfns.quantize_row_q(test_data1, tmp_q1.data(), test_size);
|
||||
qfns.quantize_row_q (test_data1, tmp_q1.data(), test_size);
|
||||
qfns.quantize_row_q_dot(test_data2, tmp_q2.data(), test_size);
|
||||
|
||||
float result = INFINITY;
|
||||
|
||||
Loading…
Reference in New Issue
Block a user