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ggerganovggerganov
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minor : indentation + assert
1 parent f4a0e0e commit 797088a

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3 files changed

+100
-90
lines changed

3 files changed

+100
-90
lines changed

‎examples/gguf/gguf.cpp‎

Lines changed: 14 additions & 7 deletions
Original file line numberDiff line numberDiff line change
@@ -8,6 +8,12 @@
88
#include <sstream>
99
#include <fstream>
1010
#include <vector>
11+
12+
#undef MIN
13+
#undef MAX
14+
#define MIN(a, b) ((a) < (b) ? (a) : (b))
15+
#define MAX(a, b) ((a) > (b) ? (a) : (b))
16+
1117
/*
1218
template<typename T>
1319
static std::string to_string(const T & val) {
@@ -16,6 +22,7 @@ static std::string to_string(const T & val) {
1622
return ss.str();
1723
}
1824
*/
25+
1926
void gguf_ex_write_str(std::ofstream & fout, const std::string & val) {
2027
const int32_t n = val.size();
2128
fout.write((const char *) &n, sizeof(n));
@@ -377,28 +384,28 @@ bool gguf_ex_read_2(const std::string & fname) {
377384

378385
struct gguf_file file(fname.c_str(), "rb");
379386
gguf_mmap data_mmap(&file, 0, false);
387+
380388
const int n_tensors = gguf_get_n_tensors(ctx);
381389

382390
for (int i = 0; i < n_tensors; ++i) {
383-
const char * name = gguf_get_tensor_name(ctx, i);
384-
const size_t offset = gguf_get_data_offset(ctx) + gguf_get_tensor_offset(ctx, i);
391+
const char * name = gguf_get_tensor_name(ctx, i);
392+
const size_t offset = gguf_get_data_offset(ctx) + gguf_get_tensor_offset(ctx, i);
393+
385394
struct ggml_tensor * cur = ggml_get_tensor(ctx_data, name);
386395

387396
cur->data = static_cast<char *>(data_mmap.addr) + offset;
388397

389398
// print first 10 elements
390-
const float * data = (const float *) cur->data;
399+
const float * data = (const float *) cur->data;
391400

392401
printf("%s data[:10] : ", name);
393-
394-
for (int j = 0; j < 10; ++j) {
402+
for (int j = 0; j < MIN(10, ggml_nelements(cur)); ++j) {
395403
printf("%f ", data[j]);
396404
}
397-
398405
printf("\n\n");
399406
}
400407

401-
fprintf(stdout, "%s: ctx_data size: %zu\n", __func__, ggml_get_mem_size(ctx_data));
408+
fprintf(stdout, "%s: ctx_data size: %zu\n", __func__, ggml_get_mem_size(ctx_data));
402409

403410
ggml_free(ctx_data);
404411
gguf_free(ctx);

‎gguf-llama.cpp‎

Lines changed: 85 additions & 82 deletions
Original file line numberDiff line numberDiff line change
@@ -508,17 +508,16 @@ struct gguf_load_tensors_map {
508508

509509
enum gguf_file_version {
510510
GGUF_FILE_VERSION_V1 = 1,
511-
512511
};
513512

514-
515513
struct gguf_file_loader {
516514
gguf_file file;
517515
gguf_context * gguf_ctx;
518516
gguf_file_version file_version;
519517
llama_hparams hparams;
520518
llama_vocab vocab;
521-
struct ggml_context * ctx_data = NULL;
519+
520+
struct ggml_context * ctx_data = NULL;
522521

523522
gguf_file_loader(const char * fname, gguf_load_tensors_map & tensors_map)
524523
: file(fname, "rb") {
@@ -537,7 +536,7 @@ struct ggml_context * ctx_data = NULL;
537536
read_tensor_metadata(tensors_map);
538537
}
539538

540-
uint32_t read_u32(const char * key) {
539+
uint32_t read_u32(const char * key) const {
541540
int i = gguf_find_key(gguf_ctx, key);
542541
if (i == -1) {
543542
throw std::runtime_error(format("cannot find param with key %s\n", key));
@@ -546,7 +545,7 @@ struct ggml_context * ctx_data = NULL;
546545
return gguf_get_val_u32(gguf_ctx, i);
547546
}
548547

549-
float read_f32(const char * key) {
548+
float read_f32(const char * key) const {
550549
int i = gguf_find_key(gguf_ctx, key);
551550
if (i == -1) {
552551
throw std::runtime_error(format("cannot find param with key %s\n", key));
@@ -555,27 +554,26 @@ struct ggml_context * ctx_data = NULL;
555554
return gguf_get_val_f32(gguf_ctx, i);
556555
}
557556

558-
int read_n_vocab() {
557+
int read_n_vocab() const {
559558
int i = gguf_find_key(gguf_ctx, "tokenizer.ggml.tokens");
560-
if (i == -1) {
561-
throw std::runtime_error("cannot find token list in GGUF file\n");
562-
}
559+
if (i == -1) {
560+
throw std::runtime_error("cannot find token list in GGUF file\n");
561+
}
563562

564-
return gguf_get_arr_n(gguf_ctx, i);
563+
return gguf_get_arr_n(gguf_ctx, i);
565564
}
566565

567566
void read_hparams() {
568-
569567
// TODO define keys as constants in header
570568
// TODO: read all hparams from file
571569

572-
hparams.n_vocab = read_n_vocab();
573-
hparams.n_ctx = read_u32("llama.context_length");
574-
hparams.n_embd = read_u32("llama.embedding_length");
575-
hparams.n_ff = read_u32("llama.feed_forward_length");
576-
hparams.n_head = read_u32("llama.attention.head_count");
577-
hparams.n_layer = read_u32("llama.layer_count");
578-
hparams.n_rot = read_u32("llama.rope.dimension_count");
570+
hparams.n_vocab = read_n_vocab();
571+
hparams.n_ctx = read_u32("llama.context_length");
572+
hparams.n_embd = read_u32("llama.embedding_length");
573+
hparams.n_ff = read_u32("llama.feed_forward_length");
574+
hparams.n_head = read_u32("llama.attention.head_count");
575+
hparams.n_layer = read_u32("llama.layer_count");
576+
hparams.n_rot = read_u32("llama.rope.dimension_count");
579577
hparams.f_rms_norm_eps = read_f32("llama.attention.layer_norm_rms_epsilon");
580578

581579
// LLaMAv2
@@ -606,24 +604,27 @@ struct ggml_context * ctx_data = NULL;
606604
}
607605
}
608606

609-
void read_tensor_metadata(gguf_load_tensors_map & tensors_map) {
607+
void read_tensor_metadata(gguf_load_tensors_map & tensors_map) const {
610608
const int n_tensors = gguf_get_n_tensors(gguf_ctx);
611609

612610
for (int i = 0; i < n_tensors; ++i) {
613611
gguf_load_tensor tensor;
614612
const char * name = gguf_get_tensor_name(gguf_ctx, i);
615613

616614
struct ggml_tensor * cur = ggml_get_tensor(ctx_data, name);
617-
uint32_t n_dims = cur->n_dims;
615+
616+
const uint32_t n_dims = cur->n_dims;
618617
tensor.type = cur->type;
619618
tensor.ne.resize(n_dims);
619+
620620
for (uint32_t j = 0; j < n_dims; ++j) {
621-
tensor.ne[j] = cur->ne[j];
621+
tensor.ne[j] = cur->ne[j];
622622
}
623623

624624
if (n_dims < 1 || n_dims > 2) {
625625
throw std::runtime_error(format("llama.cpp: tensor '%s' should not be %u-dimensional", name, n_dims));
626626
}
627+
627628
switch (tensor.type) {
628629
case GGML_TYPE_F32:
629630
case GGML_TYPE_F16:
@@ -643,7 +644,6 @@ struct ggml_context * ctx_data = NULL;
643644
}
644645
}
645646

646-
647647
tensor.file_off = gguf_get_data_offset(gguf_ctx) + gguf_get_tensor_offset(gguf_ctx, i);
648648

649649
tensor.name = name;
@@ -670,47 +670,47 @@ struct gguf_file_saver {
670670

671671
gguf_file_saver(const char * fname, gguf_file_loader * fl, enum llama_ftype new_ftype)
672672
: file(fname, "wb"), fl(fl) {
673-
fprintf(stderr, "llama.cpp: saving model to %s\n", fname);
674-
write_header();
675-
write_hparams(new_ftype);
676-
}
673+
fprintf(stderr, "llama.cpp: saving model to %s\n", fname);
674+
write_header();
675+
write_hparams(new_ftype);
676+
}
677677

678678
void write_header() {
679679
const int32_t magic = GGUF_MAGIC;
680680
file.write_i32(magic);
681681

682-
const int32_t version = GGUF_VERSION;
683-
file.write_i32(version);
682+
const int32_t version = GGUF_VERSION;
683+
file.write_i32(version);
684684

685-
const int32_t n_tensors = gguf_get_n_tensors(fl->gguf_ctx);
686-
file.write_i32(n_tensors);
685+
const int32_t n_tensors = gguf_get_n_tensors(fl->gguf_ctx);
686+
file.write_i32(n_tensors);
687687

688-
const int32_t n_kv = gguf_get_n_kv(fl->gguf_ctx);
689-
file.write_i32(n_kv);
690-
}
688+
const int32_t n_kv = gguf_get_n_kv(fl->gguf_ctx);
689+
file.write_i32(n_kv);
690+
}
691691

692-
void write_hparam_arr_str(const std::string & key, enum gguf_type type, int i, int n_arr) {
693-
std::vector<std::string> data(n_arr);
692+
void write_hparam_arr_str(const std::string & key, enum gguf_type type, int i, int n_arr) {
693+
std::vector<std::string> data(n_arr);
694694

695-
for (int j = 0; j < n_arr; ++j) {
696-
std::string val = gguf_get_arr_str(fl->gguf_ctx, i, j);
697-
data[j] = val;
698-
}
699-
700-
file.write_arr<std::string>(key, type, data);
695+
for (int j = 0; j < n_arr; ++j) {
696+
std::string val = gguf_get_arr_str(fl->gguf_ctx, i, j);
697+
data[j] = val;
701698
}
702699

703-
void write_hparam_arr_f32(const std::string & key, enum gguf_type type, int i, int n_arr) {
704-
std::vector<float> data(n_arr);
700+
file.write_arr<std::string>(key, type, data);
701+
}
705702

706-
for (int j = 0; j < n_arr; ++j) {
707-
float val = gguf_get_arr_f32(fl->gguf_ctx, i, j);
708-
data[j] = val;
709-
}
703+
void write_hparam_arr_f32(const std::string & key, enum gguf_type type, int i, int n_arr) {
704+
std::vector<float> data(n_arr);
710705

711-
file.write_arr<float>(key, type, data);
706+
for (int j = 0; j < n_arr; ++j) {
707+
float val = gguf_get_arr_f32(fl->gguf_ctx, i, j);
708+
data[j] = val;
712709
}
713710

711+
file.write_arr<float>(key, type, data);
712+
}
713+
714714
void write_hparams(enum llama_ftype new_ftype) {
715715
const int32_t n_kv = gguf_get_n_kv(fl->gguf_ctx);
716716
for (int i = 0; i < n_kv; ++i) {
@@ -734,59 +734,62 @@ struct gguf_file_saver {
734734

735735
switch(vtype) {
736736
case GGUF_TYPE_BOOL:
737-
bool_val = gguf_get_val_bool(fl->gguf_ctx, i);
738-
file.write_val<bool>(key, GGUF_TYPE_BOOL, bool_val);
739-
break;
737+
bool_val = gguf_get_val_bool(fl->gguf_ctx, i);
738+
file.write_val<bool>(key, GGUF_TYPE_BOOL, bool_val);
739+
break;
740740
case GGUF_TYPE_FLOAT32:
741-
f32_val = gguf_get_val_f32(fl->gguf_ctx, i);
742-
file.write_val<float>(key, GGUF_TYPE_FLOAT32, f32_val);
743-
break;
741+
f32_val = gguf_get_val_f32(fl->gguf_ctx, i);
742+
file.write_val<float>(key, GGUF_TYPE_FLOAT32, f32_val);
743+
break;
744744
case GGUF_TYPE_INT16:
745-
i16_val = gguf_get_val_i16(fl->gguf_ctx, i);
746-
file.write_val<int16_t>(key, GGUF_TYPE_INT16, i16_val);
747-
break;
745+
i16_val = gguf_get_val_i16(fl->gguf_ctx, i);
746+
file.write_val<int16_t>(key, GGUF_TYPE_INT16, i16_val);
747+
break;
748748
case GGUF_TYPE_INT32:
749-
i32_val = gguf_get_val_i32(fl->gguf_ctx, i);
750-
file.write_val<int32_t>(key, GGUF_TYPE_INT32, i32_val);
751-
break;
749+
i32_val = gguf_get_val_i32(fl->gguf_ctx, i);
750+
file.write_val<int32_t>(key, GGUF_TYPE_INT32, i32_val);
751+
break;
752752
case GGUF_TYPE_INT8:
753-
i8_val = gguf_get_val_i8(fl->gguf_ctx, i);
754-
file.write_val<int8_t>(key, GGUF_TYPE_INT8, i8_val);
755-
break;
753+
i8_val = gguf_get_val_i8(fl->gguf_ctx, i);
754+
file.write_val<int8_t>(key, GGUF_TYPE_INT8, i8_val);
755+
break;
756756
case GGUF_TYPE_STRING:
757-
str_val = gguf_get_val_str(fl->gguf_ctx, i);
758-
file.write_val<std::string>(key, GGUF_TYPE_STRING, str_val);
759-
break;
757+
str_val = gguf_get_val_str(fl->gguf_ctx, i);
758+
file.write_val<std::string>(key, GGUF_TYPE_STRING, str_val);
759+
break;
760760
case GGUF_TYPE_UINT16:
761-
u16_val = gguf_get_val_u16(fl->gguf_ctx, i);
762-
file.write_val<uint16_t>(key, GGUF_TYPE_UINT16, u16_val);
763-
break;
761+
u16_val = gguf_get_val_u16(fl->gguf_ctx, i);
762+
file.write_val<uint16_t>(key, GGUF_TYPE_UINT16, u16_val);
763+
break;
764764
case GGUF_TYPE_UINT32:
765-
u32_val = gguf_get_val_u32(fl->gguf_ctx, i);
766-
file.write_val<uint32_t>(key, GGUF_TYPE_UINT32, u32_val);
767-
break;
765+
u32_val = gguf_get_val_u32(fl->gguf_ctx, i);
766+
file.write_val<uint32_t>(key, GGUF_TYPE_UINT32, u32_val);
767+
break;
768768
case GGUF_TYPE_UINT8:
769-
u8_val = gguf_get_val_u8(fl->gguf_ctx, i);
770-
file.write_val<uint8_t>(key, GGUF_TYPE_UINT8, u8_val);
771-
break;
769+
u8_val = gguf_get_val_u8(fl->gguf_ctx, i);
770+
file.write_val<uint8_t>(key, GGUF_TYPE_UINT8, u8_val);
771+
break;
772772
case GGUF_TYPE_ARRAY:
773-
arr_type = gguf_get_arr_type(fl->gguf_ctx, i);
774-
n_arr = gguf_get_arr_n(fl->gguf_ctx, i);
775-
if (arr_type == GGUF_TYPE_FLOAT32) {
776-
write_hparam_arr_f32(key, arr_type, i, n_arr);
773+
arr_type = gguf_get_arr_type(fl->gguf_ctx, i);
774+
n_arr = gguf_get_arr_n(fl->gguf_ctx, i);
775+
if (arr_type == GGUF_TYPE_FLOAT32) {
776+
write_hparam_arr_f32(key, arr_type, i, n_arr);
777777
} else if (arr_type == GGUF_TYPE_STRING) {
778778
write_hparam_arr_str(key, GGUF_TYPE_STRING, i, n_arr);
779779
} else {
780780
throw std::runtime_error("not implemented");
781781
}
782-
break;
782+
break;
783783
default:
784-
throw std::runtime_error(format("cannot recognize value type for key %s\n", key));
784+
throw std::runtime_error(format("cannot recognize value type for key %s\n", key));
785785
}
786786
}
787787
}
788788

789-
info_offset = file.tell();
789+
info_offset = file.tell();
790+
791+
GGML_ASSERT(gguf_get_data_offset(fl->gguf_ctx) >= info_offset);
792+
790793
size_t count = gguf_get_data_offset(fl->gguf_ctx) - info_offset;
791794
file.write_zeros(count);
792795
file.seek(info_offset, SEEK_SET);

‎gguf-llama.h‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -137,7 +137,7 @@ extern "C" {
137137
// model quantization parameters
138138
typedef struct llama_model_quantize_params {
139139
int nthread; // number of threads to use for quantizing, if <=0 will use std::thread::hardware_concurrency()
140-
enum llama_ftype ftype; // quantize to this llama_ftype
140+
enum llama_ftype ftype; // quantize to this llama_ftype
141141
bool allow_requantize; // allow quantizing non-f32/f16 tensors
142142
bool quantize_output_tensor; // quantize output.weight
143143
} llama_model_quantize_params;

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