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ggml : add IQ2 to test-backend-ops + refactoring

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ggml-ci
This commit is contained in:
Georgi Gerganov 2024-01-14 13:15:30 +02:00
parent bee938da74
commit bc0bb3009c
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GPG Key ID: 449E073F9DC10735
7 changed files with 99 additions and 64 deletions
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2
ggml-backend.c
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@ -692,6 +692,8 @@ GGML_CALL static bool ggml_backend_cpu_graph_compute(ggml_backend_t backend, str
GGML_CALL static bool ggml_backend_cpu_supports_op(ggml_backend_t backend, const struct ggml_tensor * op) {
switch (op->op) {
case GGML_OP_CPY:
return op->type != GGML_TYPE_IQ2_XXS && op->type != GGML_TYPE_IQ2_XS; // missing type_traits.from_float
case GGML_OP_MUL_MAT:
return op->src[1]->type == GGML_TYPE_F32 || op->src[1]->type == ggml_internal_get_type_traits(op->src[0]->type).vec_dot_type;
default:

74
ggml-quants.c
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@ -1274,7 +1274,12 @@ static float make_qx_quants(int n, int nmax, const float * restrict x, int8_t *
}
float sumlx = 0;
float suml2 = 0;
#ifdef HAVE_BUGGY_APPLE_LINKER
// use 'volatile' to prevent unroll and work around a bug in Apple ld64 1015.7
for (volatile int i = 0; i < n; ++i) {
#else
for (int i = 0; i < n; ++i) {
#endif
int l = nearest_int(iscale * x[i]);
l = MAX(-nmax, MIN(nmax-1, l));
L[i] = l + nmax;
@ -1649,7 +1654,12 @@ static float make_qkx3_quants(int n, int nmax, const float * restrict x, const f
float max = x[0];
float sum_w = weights ? weights[0] : x[0]*x[0];
float sum_x = sum_w * x[0];
#ifdef HAVE_BUGGY_APPLE_LINKER
// use 'volatile' to prevent unroll and work around a bug in Apple ld64 1015.7
for (volatile int i = 1; i < n; ++i) {
#else
for (int i = 1; i < n; ++i) {
#endif
if (x[i] < min) min = x[i];
if (x[i] > max) max = x[i];
float w = weights ? weights[i] : x[i]*x[i];
@ -1660,7 +1670,7 @@ static float make_qkx3_quants(int n, int nmax, const float * restrict x, const f
min = 0;
}
if (max <= min) {
for (int i = 0; i < n; ++i) L[i] = 0;
memset(L, 0, n);
*the_min = -min;
return 0.f;
}
@ -1862,7 +1872,7 @@ static void quantize_row_q2_K_impl(const float * restrict x, block_q2_K * restri
size_t quantize_q2_K(const float * src, void * dst, int nrow, int n_per_row, int64_t * hist, const float * quant_weights) {
(void)hist;
int row_size = ggml_row_size(GGML_TYPE_Q2_K, n_per_row);
size_t row_size = ggml_row_size(GGML_TYPE_Q2_K, n_per_row);
if (!quant_weights) {
quantize_row_q2_K_reference(src, dst, nrow*n_per_row);
}
@ -2181,7 +2191,7 @@ static void quantize_row_q3_K_impl(const float * restrict x, block_q3_K * restri
size_t quantize_q3_K(const float * src, void * dst, int nrow, int n_per_row, int64_t * hist, const float * quant_weights) {
(void)hist;
int row_size = ggml_row_size(GGML_TYPE_Q3_K, n_per_row);
size_t row_size = ggml_row_size(GGML_TYPE_Q3_K, n_per_row);
if (!quant_weights) {
quantize_row_q3_K_reference(src, dst, nrow*n_per_row);
}
@ -2448,7 +2458,7 @@ static void quantize_row_q4_K_impl(const float * restrict x, block_q4_K * restri
size_t quantize_q4_K(const float * src, void * dst, int nrow, int n_per_row, int64_t * hist, const float * quant_weights) {
(void)hist;
int row_size = ggml_row_size(GGML_TYPE_Q4_K, n_per_row);
size_t row_size = ggml_row_size(GGML_TYPE_Q4_K, n_per_row);
if (!quant_weights) {
quantize_row_q4_K_reference(src, dst, nrow*n_per_row);
}
@ -2771,7 +2781,7 @@ static void quantize_row_q5_K_impl(const float * restrict x, block_q5_K * restri
size_t quantize_q5_K(const float * src, void * dst, int nrow, int n_per_row, int64_t * hist, const float * quant_weights) {
(void)hist;
int row_size = ggml_row_size(GGML_TYPE_Q5_K, n_per_row);
size_t row_size = ggml_row_size(GGML_TYPE_Q5_K, n_per_row);
if (!quant_weights) {
quantize_row_q5_K_reference(src, dst, nrow*n_per_row);
}
@ -3025,7 +3035,7 @@ static void quantize_row_q6_K_impl(const float * restrict x, block_q6_K * restri
size_t quantize_q6_K(const float * src, void * dst, int nrow, int n_per_row, int64_t * hist, const float * quant_weights) {
(void)hist;
int row_size = ggml_row_size(GGML_TYPE_Q6_K, n_per_row);
size_t row_size = ggml_row_size(GGML_TYPE_Q6_K, n_per_row);
if (!quant_weights) {
quantize_row_q6_K_reference(src, dst, nrow*n_per_row);
}
@ -3072,7 +3082,7 @@ size_t quantize_q4_0(const float * src, void * dst, int nrow, int n_per_row, int
if (!quant_weights) {
return ggml_quantize_q4_0(src, dst, nrow*n_per_row, n_per_row, hist);
}
int row_size = ggml_row_size(GGML_TYPE_Q4_0, n_per_row);
size_t row_size = ggml_row_size(GGML_TYPE_Q4_0, n_per_row);
char * qrow = (char *)dst;
for (int row = 0; row < nrow; ++row) {
quantize_row_q4_0_impl(src, (block_q4_0*)qrow, n_per_row, quant_weights);
@ -3116,7 +3126,7 @@ size_t quantize_q4_1(const float * src, void * dst, int nrow, int n_per_row, int
if (!quant_weights) {
return ggml_quantize_q4_1(src, dst, nrow*n_per_row, n_per_row, hist);
}
int row_size = ggml_row_size(GGML_TYPE_Q4_1, n_per_row);
size_t row_size = ggml_row_size(GGML_TYPE_Q4_1, n_per_row);
char * qrow = (char *)dst;
for (int row = 0; row < nrow; ++row) {
quantize_row_q4_1_impl(src, (block_q4_1*)qrow, n_per_row, quant_weights);
@ -3169,7 +3179,7 @@ size_t quantize_q5_0(const float * src, void * dst, int nrow, int n_per_row, int
if (!quant_weights) {
return ggml_quantize_q5_0(src, dst, nrow*n_per_row, n_per_row, hist);
}
int row_size = ggml_row_size(GGML_TYPE_Q5_0, n_per_row);
size_t row_size = ggml_row_size(GGML_TYPE_Q5_0, n_per_row);
char * qrow = (char *)dst;
for (int row = 0; row < nrow; ++row) {
quantize_row_q5_0_impl(src, (block_q5_0*)qrow, n_per_row, quant_weights);
@ -3221,7 +3231,7 @@ size_t quantize_q5_1(const float * src, void * dst, int nrow, int n_per_row, int
if (!quant_weights) {
return ggml_quantize_q5_1(src, dst, nrow*n_per_row, n_per_row, hist);
}
int row_size = ggml_row_size(GGML_TYPE_Q5_1, n_per_row);
size_t row_size = ggml_row_size(GGML_TYPE_Q5_1, n_per_row);
char * qrow = (char *)dst;
for (int row = 0; row < nrow; ++row) {
quantize_row_q5_1_impl(src, (block_q5_1*)qrow, n_per_row, quant_weights);
@ -8565,7 +8575,7 @@ static int iq2_compare_func(const void * left, const void * right) {
return l[0] < r[0] ? -1 : l[0] > r[0] ? 1 : l[1] < r[1] ? -1 : l[1] > r[1] ? 1 : 0;
}
static void q2xs_init_impl(int grid_size) {
void iq2xs_init_impl(int grid_size) {
const int gindex = iq2_data_index(grid_size);
if (iq2_data[gindex].grid) {
return;
@ -8720,19 +8730,7 @@ static void q2xs_init_impl(int grid_size) {
free(dist2);
}
void ggml_init_iq2_quantization(enum ggml_type type) {
if (type == GGML_TYPE_IQ2_XXS) {
q2xs_init_impl(256);
}
else if (type == GGML_TYPE_IQ2_XS) {
q2xs_init_impl(512);
}
else {
fprintf(stderr, "======================== Why are you calling %s with type %d?\n", __func__, (int)type);
}
}
static void q2xs_deinit_impl(int grid_size) {
void iq2xs_free_impl(int grid_size) {
GGML_ASSERT(grid_size == 256 || grid_size == 512 || grid_size == 1024);
const int gindex = iq2_data_index(grid_size);
if (iq2_data[gindex].grid) {
@ -8742,18 +8740,6 @@ static void q2xs_deinit_impl(int grid_size) {
}
}
void ggml_deinit_iq2_quantization(enum ggml_type type) {
if (type == GGML_TYPE_IQ2_XXS) {
q2xs_deinit_impl(256);
}
else if (type == GGML_TYPE_IQ2_XS) {
q2xs_deinit_impl(512);
}
else {
fprintf(stderr, "======================== Why are you calling %s with type %d?\n", __func__, (int)type);
}
}
static int iq2_find_best_neighbour(const uint16_t * restrict neighbours, const uint64_t * restrict grid,
const float * restrict xval, const float * restrict weight, float scale, int8_t * restrict L) {
int num_neighbors = neighbours[0];
@ -8786,10 +8772,10 @@ static void quantize_row_iq2_xxs_impl(const float * restrict x, void * restrict
const int * kmap_q2xs = iq2_data[gindex].map;
const uint16_t * kneighbors_q2xs = iq2_data[gindex].neighbours;
GGML_ASSERT(quant_weights);
GGML_ASSERT(kgrid_q2xs);
GGML_ASSERT(kmap_q2xs);
GGML_ASSERT(kneighbors_q2xs);
GGML_ASSERT(quant_weights && "missing quantization weights");
GGML_ASSERT(kgrid_q2xs && "forgot to call ggml_quantize_init()?");
GGML_ASSERT(kmap_q2xs && "forgot to call ggml_quantize_init()?");
GGML_ASSERT(kneighbors_q2xs && "forgot to call ggml_quantize_init()?");
GGML_ASSERT(n%QK_K == 0);
const int kMaxQ = 3;
@ -9005,10 +8991,10 @@ static void quantize_row_iq2_xs_impl(const float * restrict x, void * restrict v
const int * kmap_q2xs = iq2_data[gindex].map;
const uint16_t * kneighbors_q2xs = iq2_data[gindex].neighbours;
GGML_ASSERT(quant_weights);
GGML_ASSERT(kmap_q2xs);
GGML_ASSERT(kgrid_q2xs);
GGML_ASSERT(kneighbors_q2xs);
GGML_ASSERT(quant_weights && "missing quantization weights");
GGML_ASSERT(kmap_q2xs && "forgot to call ggml_quantize_init()?");
GGML_ASSERT(kgrid_q2xs && "forgot to call ggml_quantize_init()?");
GGML_ASSERT(kneighbors_q2xs && "forgot to call ggml_quantize_init()?");
GGML_ASSERT(n%QK_K == 0);
const int kMaxQ = 3;

3
ggml-quants.h
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@ -257,3 +257,6 @@ size_t quantize_q4_0 (const float * src, void * dst, int nrows, int n_per_row,
size_t quantize_q4_1 (const float * src, void * dst, int nrows, int n_per_row, int64_t * hist, const float * imatrix);
size_t quantize_q5_0 (const float * src, void * dst, int nrows, int n_per_row, int64_t * hist, const float * imatrix);
size_t quantize_q5_1 (const float * src, void * dst, int nrows, int n_per_row, int64_t * hist, const float * imatrix);
void iq2xs_init_impl(int grid_size);
void iq2xs_free_impl(int grid_size);

34
ggml.c
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@ -18538,6 +18538,28 @@ enum ggml_opt_result ggml_opt_resume_g(
////////////////////////////////////////////////////////////////////////////////
void ggml_quantize_init(enum ggml_type type) {
ggml_critical_section_start();
switch (type) {
case GGML_TYPE_IQ2_XXS: iq2xs_init_impl(256); break;
case GGML_TYPE_IQ2_XS: iq2xs_init_impl(512); break;
default: // nothing
break;
}
ggml_critical_section_end();
}
void ggml_quantize_free(void) {
ggml_critical_section_start();
iq2xs_free_impl(256);
iq2xs_free_impl(512);
ggml_critical_section_end();
}
size_t ggml_quantize_q4_0(const float * src, void * dst, int n, int k, int64_t * hist) {
assert(k % QK4_0 == 0);
const int nb = k / QK4_0;
@ -18665,9 +18687,15 @@ size_t ggml_quantize_q8_0(const float * src, void * dst, int n, int k, int64_t *
return (n/QK8_0*sizeof(block_q8_0));
}
bool ggml_quantize_requires_imatrix(enum ggml_type type) {
return
type == GGML_TYPE_IQ2_XXS ||
type == GGML_TYPE_IQ2_XS;
}
size_t ggml_quantize_chunk(enum ggml_type type, const float * src, void * dst, int start,
int nrows, int n_per_row, int64_t * hist, const float * imatrix) {
(void)imatrix;
ggml_quantize_init(type); // this is noop if already initialized
size_t result = 0;
int n = nrows * n_per_row;
switch (type) {
@ -18780,13 +18808,13 @@ size_t ggml_quantize_chunk(enum ggml_type type, const float * src, void * dst, i
} break;
case GGML_TYPE_F16:
{
int elemsize = sizeof(ggml_fp16_t);
size_t elemsize = sizeof(ggml_fp16_t);
ggml_fp32_to_fp16_row(src + start, (ggml_fp16_t *)dst + start, n);
result = n * elemsize;
} break;
case GGML_TYPE_F32:
{
int elemsize = sizeof(float);
size_t elemsize = sizeof(float);
result = n * elemsize;
memcpy((uint8_t *)dst + start * elemsize, src + start, result);
} break;

20
ggml.h
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@ -2065,6 +2065,18 @@ extern "C" {
// quantization
//
// - ggml_quantize_init can be called multiple times with the same type
// it will only initialize the quantization tables for the first call or after ggml_quantize_free
// automatically called by ggml_quantize_chunk for convenience
//
// - ggml_quantize_free will free any memory allocated by ggml_quantize_init
// call this at the end of the program to avoid memory leaks
//
// note: these are thread-safe
//
GGML_API void ggml_quantize_init(enum ggml_type type);
GGML_API void ggml_quantize_free(void);
// TODO: these would probably get removed in favor of the more general ggml_quantize_chunk
GGML_API size_t ggml_quantize_q4_0(const float * src, void * dst, int n, int k, int64_t * hist);
GGML_API size_t ggml_quantize_q4_1(const float * src, void * dst, int n, int k, int64_t * hist);
@ -2078,13 +2090,13 @@ extern "C" {
GGML_API size_t ggml_quantize_q5_K(const float * src, void * dst, int n, int k, int64_t * hist);
GGML_API size_t ggml_quantize_q6_K(const float * src, void * dst, int n, int k, int64_t * hist);
// some quantization type cannot be used without an importance matrix
GGML_API bool ggml_quantize_requires_imatrix(enum ggml_type type);
// calls ggml_quantize_init internally (i.e. can allocate memory)
GGML_API size_t ggml_quantize_chunk(enum ggml_type type, const float * src, void * dst,
int start, int nrows, int n_per_row, int64_t * hist, const float * imatrix);
// These are needed for IQ2_XS and IQ2_XXS quantizations
GGML_API void ggml_init_iq2_quantization(enum ggml_type type);
GGML_API void ggml_deinit_iq2_quantization(enum ggml_type type);
//
// Importance matrix
//

12
llama.cpp
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@ -8738,8 +8738,6 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
// placeholder for the meta data
::zeros(fout, meta_size);
std::set<ggml_type> used_iq2;
for (int i = 0; i < ml.n_tensors; ++i) {
struct ggml_tensor * tensor = ml.get_tensor_meta(i);
@ -8792,11 +8790,6 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
} else {
const size_t nelements = ggml_nelements(tensor);
if ((new_type == GGML_TYPE_IQ2_XXS || new_type == GGML_TYPE_IQ2_XS) && used_iq2.find(new_type) == used_iq2.end()) {
ggml_init_iq2_quantization(new_type);
used_iq2.insert(new_type);
}
const float * imatrix = nullptr;
if (imatrix_data) {
auto it = imatrix_data->find(tensor->name);
@ -8922,10 +8915,6 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
fout.close();
for (auto type : used_iq2) {
ggml_deinit_iq2_quantization(type);
}
gguf_free(ctx_out);
LLAMA_LOG_INFO("%s: model size = %8.2f MB\n", __func__, total_size_org/1024.0/1024.0);
@ -9331,6 +9320,7 @@ void llama_backend_free(void) {
#ifdef GGML_USE_MPI
ggml_mpi_backend_free();
#endif
ggml_quantize_free();
}
int64_t llama_time_us(void) {

18
tests/test-backend-ops.cpp
View File

@ -56,7 +56,18 @@ static void init_tensor_uniform(ggml_tensor * tensor, float min = -1.0f, float m
GGML_ASSERT(size % ggml_blck_size(tensor->type) == 0);
std::vector<uint8_t> dataq(ggml_row_size(tensor->type, size));
int64_t hist[16];
ggml_quantize_chunk(tensor->type, data.data(), dataq.data(), 0, size/tensor->ne[0], tensor->ne[0], hist, nullptr);
std::vector<float> imatrix(tensor->ne[0], 1.0f); // dummy importance matrix
const float * im = imatrix.data();
if (!ggml_quantize_requires_imatrix(tensor->type)) {
// when the imatrix is optional, we want to test both quantization with and without imatrix
std::random_device rd;
std::default_random_engine generator(rd());
std::uniform_int_distribution<int> distribution(0, 1);
if (distribution(generator)) {
im = nullptr;
}
}
ggml_quantize_chunk(tensor->type, data.data(), dataq.data(), 0, size/tensor->ne[0], tensor->ne[0], hist, im);
ggml_backend_tensor_set(tensor, dataq.data(), 0, dataq.size());
} else if (tensor->type == GGML_TYPE_I8 || tensor->type == GGML_TYPE_I16 || tensor->type == GGML_TYPE_I32) {
// This is going to create some weird integers though.
@ -1472,7 +1483,8 @@ static bool test_backend(ggml_backend_t backend, test_mode mode, const char * op
GGML_TYPE_Q8_0,
GGML_TYPE_Q2_K, GGML_TYPE_Q3_K,
GGML_TYPE_Q4_K, GGML_TYPE_Q5_K,
GGML_TYPE_Q6_K
GGML_TYPE_Q6_K,
GGML_TYPE_IQ2_XXS, GGML_TYPE_IQ2_XS,
};
// unary ops
@ -1752,6 +1764,8 @@ int main(int argc, char ** argv) {
return 1;
}
ggml_quantize_free();
printf("\033[1;32mOK\033[0m\n");
return 0;
}