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utils : print quantization histograms
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@ggerganov
ggerganov committed Mar 6, 2023
1 parent 05e7d26 commit 3adf02e
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Showing 5 changed files with 200 additions and 321 deletions.
135 changes: 28 additions & 107 deletions examples/gpt-2/quantize.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -12,112 +12,9 @@
#include <vector>
#include <regex>

// TODO: move somewhere else
#define QK 32

size_t ggml_quantize_q4_0(float * src, void * dst, int n, int k) {
const int nb = k / QK;
const size_t row_size = nb*(sizeof(float) + sizeof(uint8_t)*QK/2);

assert(k % QK == 0);

uint8_t pp[QK/2];

char * pdst = (char *) dst;

for (int j = 0; j < n; j += k) {
float * pd = (float *) (pdst + (j/k)*row_size);
uint8_t * pb = (uint8_t *) (pd + nb);

for (int i = 0; i < nb; i++) {
float amax = 0.0f; // absolute max

{
for (int l = 0; l < QK; l++) {
const float v = src[j + i*QK + l];
amax = std::max(amax, fabsf(v));
}

const float d = amax / ((1 << 3) - 1);
const float id = d ? 1.0f/d : 0.0f;

pd[i] = d;

for (int l = 0; l < QK; l += 2) {
const float v0 = (src[j + i*QK + l + 0])*id;
const float v1 = (src[j + i*QK + l + 1])*id;

const uint8_t vi0 = ((int8_t) (round(v0))) + 8;
const uint8_t vi1 = ((int8_t) (round(v1))) + 8;

assert(vi0 >= 0 && vi0 < 16);
assert(vi1 >= 0 && vi1 < 16);

pp[l/2] = vi0 | (vi1 << 4);
}

memcpy(pb + i*QK/2, pp, sizeof(pp));
}
}
}

return (n/k)*row_size;
}

size_t ggml_quantize_q4_1(float * src, void * dst, int n, int k) {
const int nb = k / QK;
const size_t row_size = nb*(2*sizeof(float) + sizeof(uint8_t)*QK/2);

assert(k % QK == 0);

uint8_t pp[QK/2];

char * pdst = (char *) dst;

for (int j = 0; j < n; j += k) {
float * pm = (float *) (pdst + (j/k)*row_size);
float * pd = (float *) (pm + nb);
uint8_t * pb = (uint8_t *) (pd + nb);

//printf("n = %d, k = %d, nb = %d, row_size = %d, j = %d, pm = %p, pd = %p, pb = %p\n", n, k, nb, row_size, j, pm, pd, pb);

for (int i = 0; i < nb; i++) {
float min = std::numeric_limits<float>::max();
float max = std::numeric_limits<float>::min();

{
for (int l = 0; l < QK; l++) {
const float v = src[j + i*QK + l];
if (v < min) min = v;
if (v > max) max = v;
}

const float d = (max - min) / ((1 << 4) - 1);
const float id = d ? 1.0f/d : 0.0f;

pm[i] = min;
pd[i] = d;

for (int l = 0; l < QK; l += 2) {
const float v0 = (src[j + i*QK + l + 0] - min)*id;
const float v1 = (src[j + i*QK + l + 1] - min)*id;

const uint8_t vi0 = round(v0);
const uint8_t vi1 = round(v1);

assert(vi0 >= 0 && vi0 < 16);
assert(vi1 >= 0 && vi1 < 16);

pp[l/2] = vi0 | (vi1 << 4);
}

memcpy(pb + i*QK/2, pp, sizeof(pp));
}
}
}

return (n/k)*row_size;
}

// default hparams (GPT-2 117M)
struct gpt2_hparams {
int32_t n_vocab = 50257;
Expand Down Expand Up @@ -235,6 +132,8 @@ bool gpt2_model_quantize(const std::string & fname_inp, const std::string & fnam
std::vector<ggml_fp16_t> data_f16;
std::vector<float> data_f32;

std::vector<int64_t> hist_all(1 << 4, 0);

while (true) {
int32_t n_dims;
int32_t length;
Expand Down Expand Up @@ -319,15 +218,16 @@ bool gpt2_model_quantize(const std::string & fname_inp, const std::string & fnam
work.resize(nelements); // for quantization

size_t cur_size = 0;
std::vector<int64_t> hist_cur(1 << 4, 0);

switch (type) {
case GGML_TYPE_Q4_0:
{
cur_size = ggml_quantize_q4_0(data_f32.data(), work.data(), nelements, ne[0]);
cur_size = ggml_quantize_q4_0(data_f32.data(), work.data(), nelements, ne[0], QK, hist_cur.data());
} break;
case GGML_TYPE_Q4_1:
{
cur_size = ggml_quantize_q4_1(data_f32.data(), work.data(), nelements, ne[0]);
cur_size = ggml_quantize_q4_1(data_f32.data(), work.data(), nelements, ne[0], QK, hist_cur.data());
} break;
default:
{
Expand All @@ -339,7 +239,15 @@ bool gpt2_model_quantize(const std::string & fname_inp, const std::string & fnam
fout.write(reinterpret_cast<char *>(work.data()), cur_size);
total_size_new += cur_size;

printf("size = %8.2f MB -> %8.2f MB\n", nelements * sizeof(float)/1024.0/1024.0, cur_size/1024.0/1024.0);
printf("size = %8.2f MB -> %8.2f MB | hist: ", nelements * sizeof(float)/1024.0/1024.0, cur_size/1024.0/1024.0);
for (int i = 0; i < hist_cur.size(); ++i) {
hist_all[i] += hist_cur[i];
}

for (int i = 0; i < hist_cur.size(); ++i) {
printf("%5.3f ", hist_cur[i] / (float)nelements);
}
printf("\n");
} else {
printf("size = %8.3f MB\n", data_u8.size()/1024.0/1024.0);
fout.write(reinterpret_cast<char *>(data_u8.data()), data_u8.size());
Expand All @@ -351,6 +259,19 @@ bool gpt2_model_quantize(const std::string & fname_inp, const std::string & fnam

printf("%s: model size = %8.2f MB\n", __func__, total_size_org/1024.0/1024.0);
printf("%s: quant size = %8.2f MB\n", __func__, total_size_new/1024.0/1024.0);

{
int64_t sum_all = 0;
for (int i = 0; i < hist_all.size(); ++i) {
sum_all += hist_all[i];
}

printf("%s: hist: ", __func__);
for (int i = 0; i < hist_all.size(); ++i) {
printf("%5.3f ", hist_all[i] / (float)sum_all);
}
printf("\n");
}
}

finp.close();
Expand Down
135 changes: 28 additions & 107 deletions examples/gpt-j/quantize.cpp
View file
Original file line number Diff line number Diff line change
Expand Up @@ -12,112 +12,9 @@
#include <vector>
#include <regex>

// TODO: move somewhere else
#define QK 32

size_t ggml_quantize_q4_0(float * src, void * dst, int n, int k) {
const int nb = k / QK;
const size_t row_size = nb*(sizeof(float) + sizeof(uint8_t)*QK/2);

assert(k % QK == 0);

uint8_t pp[QK/2];

char * pdst = (char *) dst;

for (int j = 0; j < n; j += k) {
float * pd = (float *) (pdst + (j/k)*row_size);
uint8_t * pb = (uint8_t *) (pd + nb);

for (int i = 0; i < nb; i++) {
float amax = 0.0f; // absolute max

{
for (int l = 0; l < QK; l++) {
const float v = src[j + i*QK + l];
amax = std::max(amax, fabsf(v));
}

const float d = amax / ((1 << 3) - 1);
const float id = d ? 1.0f/d : 0.0f;

pd[i] = d;

for (int l = 0; l < QK; l += 2) {
const float v0 = (src[j + i*QK + l + 0])*id;
const float v1 = (src[j + i*QK + l + 1])*id;

const uint8_t vi0 = ((int8_t) (round(v0))) + 8;
const uint8_t vi1 = ((int8_t) (round(v1))) + 8;

assert(vi0 >= 0 && vi0 < 16);
assert(vi1 >= 0 && vi1 < 16);

pp[l/2] = vi0 | (vi1 << 4);
}

memcpy(pb + i*QK/2, pp, sizeof(pp));
}
}
}

return (n/k)*row_size;
}

size_t ggml_quantize_q4_1(float * src, void * dst, int n, int k) {
const int nb = k / QK;
const size_t row_size = nb*(2*sizeof(float) + sizeof(uint8_t)*QK/2);

assert(k % QK == 0);

uint8_t pp[QK/2];

char * pdst = (char *) dst;

for (int j = 0; j < n; j += k) {
float * pm = (float *) (pdst + (j/k)*row_size);
float * pd = (float *) (pm + nb);
uint8_t * pb = (uint8_t *) (pd + nb);

//printf("n = %d, k = %d, nb = %d, row_size = %d, j = %d, pm = %p, pd = %p, pb = %p\n", n, k, nb, row_size, j, pm, pd, pb);

for (int i = 0; i < nb; i++) {
float min = std::numeric_limits<float>::max();
float max = std::numeric_limits<float>::min();

{
for (int l = 0; l < QK; l++) {
const float v = src[j + i*QK + l];
if (v < min) min = v;
if (v > max) max = v;
}

const float d = (max - min) / ((1 << 4) - 1);
const float id = d ? 1.0f/d : 0.0f;

pm[i] = min;
pd[i] = d;

for (int l = 0; l < QK; l += 2) {
const float v0 = (src[j + i*QK + l + 0] - min)*id;
const float v1 = (src[j + i*QK + l + 1] - min)*id;

const uint8_t vi0 = round(v0);
const uint8_t vi1 = round(v1);

assert(vi0 >= 0 && vi0 < 16);
assert(vi1 >= 0 && vi1 < 16);

pp[l/2] = vi0 | (vi1 << 4);
}

memcpy(pb + i*QK/2, pp, sizeof(pp));
}
}
}

return (n/k)*row_size;
}

// default hparams (GPT-J 6B)
struct gptj_hparams {
int32_t n_vocab = 50400;
Expand Down Expand Up @@ -238,6 +135,8 @@ bool gptj_model_quantize(const std::string & fname_inp, const std::string & fnam
std::vector<ggml_fp16_t> data_f16;
std::vector<float> data_f32;

std::vector<int64_t> hist_all(1 << 4, 0);

while (true) {
int32_t n_dims;
int32_t length;
Expand Down Expand Up @@ -321,15 +220,16 @@ bool gptj_model_quantize(const std::string & fname_inp, const std::string & fnam
work.resize(nelements); // for quantization

size_t cur_size = 0;
std::vector<int64_t> hist_cur(1 << 4, 0);

switch (type) {
case GGML_TYPE_Q4_0:
{
cur_size = ggml_quantize_q4_0(data_f32.data(), work.data(), nelements, ne[0]);
cur_size = ggml_quantize_q4_0(data_f32.data(), work.data(), nelements, ne[0], QK, hist_cur.data());
} break;
case GGML_TYPE_Q4_1:
{
cur_size = ggml_quantize_q4_1(data_f32.data(), work.data(), nelements, ne[0]);
cur_size = ggml_quantize_q4_1(data_f32.data(), work.data(), nelements, ne[0], QK, hist_cur.data());
} break;
default:
{
Expand All @@ -341,7 +241,15 @@ bool gptj_model_quantize(const std::string & fname_inp, const std::string & fnam
fout.write(reinterpret_cast<char *>(work.data()), cur_size);
total_size_new += cur_size;

printf("size = %8.2f MB -> %8.2f MB\n", nelements * sizeof(float)/1024.0/1024.0, cur_size/1024.0/1024.0);
printf("size = %8.2f MB -> %8.2f MB | hist: ", nelements * sizeof(float)/1024.0/1024.0, cur_size/1024.0/1024.0);
for (int i = 0; i < hist_cur.size(); ++i) {
hist_all[i] += hist_cur[i];
}

for (int i = 0; i < hist_cur.size(); ++i) {
printf("%5.3f ", hist_cur[i] / (float)nelements);
}
printf("\n");
} else {
printf("size = %8.3f MB\n", data_u8.size()/1024.0/1024.0);
fout.write(reinterpret_cast<char *>(data_u8.data()), data_u8.size());
Expand All @@ -353,6 +261,19 @@ bool gptj_model_quantize(const std::string & fname_inp, const std::string & fnam

printf("%s: model size = %8.2f MB\n", __func__, total_size_org/1024.0/1024.0);
printf("%s: quant size = %8.2f MB\n", __func__, total_size_new/1024.0/1024.0);

{
int64_t sum_all = 0;
for (int i = 0; i < hist_all.size(); ++i) {
sum_all += hist_all[i];
}

printf("%s: hist: ", __func__);
for (int i = 0; i < hist_all.size(); ++i) {
printf("%5.3f ", hist_all[i] / (float)sum_all);
}
printf("\n");
}
}

finp.close();
Expand Down
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