Files
ik_llama.cpp/examples/mtmd/clip-impl.h
T
NexesenexandGitHub c3b075f069 Chores : tidy up more typos project wide (ggml directory excluded), new -ptcall alias (#2237)
* common: fix coding mistakes (typos in identifiers, flags and log strings)

Fix misspelled identifiers and user-facing strings across common, server
and model loading:

- allow_ruless -> allow_rules (misspelled identifier used in the allowlist
  CLI parsing and the server slot/context code)
- get_formated_timings/get_formated_generation -> get_formatted_*
- 'termionated' -> 'terminated' in the fit-margin assert message
- 'defaulr' -> 'default' in the YAML dump
- 'overriden' -> 'overridden' in tensor buffer type override logs
- 'becausee' -> 'because' in the output-tensor split log
- 'etected NaNs' -> 'detected NaNs' in the imatrix error message

* common: fix comment typos across src, common, include and examples

Fix misspelled words in code comments:

- llama.h: 'typy' -> 'type', 'transfrom' -> 'transform', 'ecoder' ->
  'encoder', 'indicies' -> 'indices', 'Intializes' -> 'Initializes'
- common.h: 'embendings' -> 'embeddings', 'pr' -> 'or' in the
  fused-indexer-topk comment
- chat.cpp: 'overridde' -> 'override'
- ngram-map: 'occurences' -> 'occurrences', 'stastistics' -> 'statistics'
- speculative.cpp: 'dont'/'inehit' -> 'don't'/'inherit'
- llama-mmap.cpp: 'dont't' -> 'don't'
- llama-model.h: 'hcurrently andle' -> 'currently handle'
- build_gemma3/4.cpp: 'emdeddings' -> 'embeddings'
- examples: 'quantizuation', 'logprobe', 'throught', 'retrun', 'swich',
  'convinient', 'temporally' (-> 'temporary'), 'temproal', 'preceed'

* common: remove duplicate definitions and duplicate help entries

- clip-impl.h: drop the second, identical #define TN_FFN_GATE
- common.cpp: remove the duplicate '-t, --threads N' help entry that was
  misplaced in the export-lora section (already listed in the general
  section)
- common.cpp: merge the two 'embedding' help groups into a single group
  so the embedding options are listed together
- llama.cpp: remove the redundant LLAMA_MAX_LAYERS define (llama-hparams.h
  already defines the same value and is included by llama.cpp)

* common: fix remaining typos (accomodate, recommanded, occurences, occassionally)

- accomodate -> accommodate in src/llama.cpp comment
- recommanded -> recommended in quantize.cpp user-facing output
- occurences -> occurrences in test-chat.cpp JSON string
- occassionally -> occasionally in vendor/stb/stb_image_resize2.h comment

Note: tokenizer.ggml.seperator_token_id kept as-is to match GGUF spec

* common: remove duplicate help entries

- remove the duplicate '--reasoning-budget N' help entry that was repeated
  in the main section (introduced in e0596bf614 'Autoparser - complete
  refactoring of parser architecture (PR 1376)')
- remove the second '--parallel-tool-calls' help entry that advertised the
  '-ptc' short flag, which belongs to '--print-token-count' (introduced in
  e0596bf614 'Autoparser - complete refactoring of parser architecture
  (PR 1376)'); the '-ptc' alias was non-functional for '--parallel-tool-calls'
  because the parser only binds it to '--print-token-count'

The canonical help entries are kept:
- '--reasoning-budget N' is listed once
- '--parallel-tool-calls' is listed once (without the conflicting '-ptc' alias)

* common: remove duplicate LOG_ENABLE define

- the '#undef LOG_ENABLE / #define LOG_ENABLE() // dummy stub' pair was
  repeated verbatim inside the LOG_DISABLE_LOGS section
- remove the second occurrence (introduced in a2588b53e1 'main : log
  file (PR 2748)')

* llama-bench: align MLA and attention-max-batch flags with common tools

llama-bench used '--mla-attn' and '--attn-max-batch' while the common
CLI parsing (common/common.cpp) uses '--mla-use' and
'--attention-max-batch' for the same features. This made the flags
inconsistent across tools.

- update the help text to advertise the canonical names
  '--mla-use' and '--attention-max-batch'
- keep the old '--mla-attn' and '--attn-max-batch' spellings working
  as aliases so existing scripts are not broken

The divergent names were introduced in 3e536b95b0 'Add optional MLA
(PR 188)'.

* fix typos in comments and user-facing strings

- ngram-map.cpp: 'Do we haven a existing' -> 'Do we have an existing'
  (introduced in 1cb7e1bf39 'spec : add self speculative decoding,
  ngram and refactor (PR 1261)')
- build_mamba.cpp: 'weigth' -> 'weight' (introduced in 8befd92ea5
  'Refactor model compute graphs (PR 1651)')
- gguf-split.cpp: 'one of splits have 0 tensors' -> 'one of the splits
  has 0 tensors' (introduced in 75b580db0a 'split: allow
  --split-max-size option (PR 6343)')
- gguf-split.cpp: 'merged from %d split' -> 'merged from %d splits'
  (introduced in 1b5523dc79 'gguf-split: split and merge gguf per
  batch of tensors (PR 6135)')
- convert-llama2c-to-ggml.cpp: missing opening quote in the help line,
  '(default %s\\')' -> '(default '%s\\')' (introduced in bb9ebb4394
  'Adding support for llama2.c models (PR 2559)')

* harmonize British and American spelling to American English

The codebase uses American English (e.g. --embd-normalize, --color),
but a few strings/comments still used British spellings. Unify them:

- 'normalisation' -> 'normalization' in common.h, common.cpp help text
  and code comment, and llama-build-context.cpp comment
- 'colorise' -> 'colorize' in the --color help text (common.cpp)
- 'behaviour' -> 'behavior' in a chat.cpp warning and a llama.cpp comment
- also fix 'openai' -> 'OpenAI' capitalization in the embedding help
  text and common.h comment (embedding output format is OpenAI-style)

* common: fix help text formatting inconsistencies

- '-smf16'/'--split-mode-f16' and '-smf32'/'--split-mode-f32' help
  entries displayed hardcoded 'true'/'false' as the default value;
  show the actual state derived from params.reduce_type instead
- '-no-mmad' help entry had 'fused_mmad?' without a space before the
  ternary operator
- '--reasoning-tokens' help continuation lines used tab characters for
  indentation while the sibling '--reasoning-format' entry uses spaces;
  convert to consistent space indentation

* common: revert smf16/smf32 help text default display change

Revert the '-smf16'/'--split-mode-f16' and '-smf32'/'--split-mode-f32'
help entries back to their original hardcoded 'true'/'false' default
display. The change to derive the default from params.reduce_type was
not desired; the split-mode options are legacy and the hardcoded
defaults reflect their intended meaning.

The other formatting fixes in the same area (fused_mmad ternary
spacing and the reasoning-tokens tab-to-space indentation) are kept.

* llama-bench: fix help text column alignment

The --mla-use and --attention-max-batch help lines introduced by the
flag alignment landed one column off from the sibling entries
((default: at column 51 instead of 50). Adjust the padding so all
help lines align.

* common: fix help text defaults for graph-reduce-type and log-format

Mismatch 1: -grt, --graph-reduce-type help shows default "f32", but actual default (common.h:463) is "f16" and llama.cpp uses GGML_TYPE_F16.

Mismatch 2: --log-format help shows default "json", but actual default (common.h:536 log_json=false) is text.

* common: add -ptcall short flag for --parallel-tool-calls

* typo
2026-08-03 08:01:18 +03:00

517 lines
18 KiB
C++

#include "ggml.h"
#include "clip.h"
#include <climits>
#include <cstdarg>
#include <cinttypes>
#include <string>
#include <map>
#include <sstream>
#include <vector>
#include <memory>
// Internal header for clip.cpp
#define KEY_FTYPE "general.file_type"
#define KEY_NAME "general.name"
#define KEY_DESCRIPTION "general.description"
#define KEY_PROJ_TYPE "clip.projector_type"
#define KEY_HAS_AUDIO_ENC "clip.has_audio_encoder"
#define KEY_HAS_VISION_ENC "clip.has_vision_encoder"
#define KEY_USE_GELU "clip.use_gelu"
#define KEY_USE_SILU "clip.use_silu"
#define KEY_N_EMBD "clip.%s.embedding_length"
#define KEY_N_FF "clip.%s.feed_forward_length"
#define KEY_N_BLOCK "clip.%s.block_count"
#define KEY_PROJ_DIM "clip.%s.projection_dim"
#define KEY_N_HEAD "clip.%s.attention.head_count"
#define KEY_LAYER_NORM_EPS "clip.%s.attention.layer_norm_epsilon"
// vision-specific
#define KEY_VISION_PROJ_TYPE "clip.vision.projector_type" // for models with mixed modalities
#define KEY_IMAGE_SIZE "clip.vision.image_size"
#define KEY_IMAGE_MIN_PIXELS "clip.vision.image_min_pixels"
#define KEY_IMAGE_MAX_PIXELS "clip.vision.image_max_pixels"
#define KEY_PREPROC_IMAGE_SIZE "clip.vision.preproc_image_size"
#define KEY_PATCH_SIZE "clip.vision.patch_size"
#define KEY_IMAGE_MEAN "clip.vision.image_mean"
#define KEY_IMAGE_STD "clip.vision.image_std"
#define KEY_FEATURE_LAYER "clip.vision.feature_layer"
#define KEY_PROJ_SCALE_FACTOR "clip.vision.projector.scale_factor"
#define KEY_SPATIAL_MERGE_SIZE "clip.vision.spatial_merge_size"
#define KEY_TEMPORAL_PATCH_SIZE "clip.vision.temporal_patch_size"
#define KEY_IS_DEEPSTACK_LAYERS "clip.vision.is_deepstack_layers"
#define KEY_MM_PATCH_MERGE_TYPE "clip.vision.mm_patch_merge_type"
#define KEY_IMAGE_GRID_PINPOINTS "clip.vision.image_grid_pinpoints"
#define KEY_IMAGE_CROP_RESOLUTION "clip.vision.image_crop_resolution"
#define KEY_WIN_ATTN_PATTERN "clip.vision.n_wa_pattern"
#define KEY_ATTN_WINDOW_SIZE "clip.vision.window_size"
#define KEY_MINICPMV_VERSION "clip.minicpmv_version"
#define KEY_MINICPMV_QUERY_NUM "clip.minicpmv_query_num"
// audio-specific
#define KEY_AUDIO_PROJ_TYPE "clip.audio.projector_type" // for models with mixed modalities
#define KEY_A_NUM_MEL_BINS "clip.audio.num_mel_bins"
#define KEY_A_PROJ_STACK_FACTOR "clip.audio.projector.stack_factor"
//
// tensor name constants
//
#define TN_POS_EMBD "%s.position_embd.weight"
#define TN_CLASS_EMBD "v.class_embd"
#define TN_PATCH_EMBD "v.patch_embd.weight" // not rename tensor with ".0" postfix for backwrad compat
#define TN_PATCH_EMBD_1 "v.patch_embd.weight.1"
#define TN_PATCH_BIAS "v.patch_embd.bias"
#define TN_ATTN_QKV "%s.blk.%d.attn_qkv.%s"
#define TN_ATTN_K "%s.blk.%d.attn_k.%s"
#define TN_ATTN_Q "%s.blk.%d.attn_q.%s"
#define TN_ATTN_V "%s.blk.%d.attn_v.%s"
#define TN_ATTN_OUTPUT "%s.blk.%d.attn_out.%s"
#define TN_ATTN_K_NORM "%s.blk.%d.attn_k_norm.%s"
#define TN_ATTN_Q_NORM "%s.blk.%d.attn_q_norm.%s"
#define TN_FFN_DOWN "%s.blk.%d.ffn_down.%s"
#define TN_FFN_UP "%s.blk.%d.ffn_up.%s"
#define TN_FFN_GATE "%s.blk.%d.ffn_gate.%s"
#define TN_LN_1 "%s.blk.%d.ln1.%s" // layer norm
#define TN_LN_2 "%s.blk.%d.ln2.%s" // layer norm
#define TN_LS_1 "%s.blk.%d.ls1.%s" // layer scale
#define TN_LS_2 "%s.blk.%d.ls2.%s" // layer scale
#define TN_LS_OUT "%s.blk.%d.out_scale.%s" // layer out scale (gemma4)
#define TN_ATTN_POST_NORM "%s.blk.%d.attn_post_norm.%s" // post-attn norm (gemma4)
#define TN_FFN_POST_NORM "%s.blk.%d.ffn_post_norm.%s" // post-FFN norm (gemma4)
#define TN_LN_PRE "%s.pre_ln.%s"
#define TN_LN_POST "%s.post_ln.%s"
#define TN_LLAVA_PROJ "mm.%d.%s"
#define TN_MVLM_PROJ_MLP "mm.model.mlp.%d.%s"
#define TN_MVLM_PROJ_BLOCK "mm.model.mb_block.%d.block.%d.%s"
#define TN_MVLM_PROJ_PEG "mm.model.peg.%d.%s"
#define TN_IMAGE_NEWLINE "model.image_newline"
#define TN_MM_INP_NORM "mm.input_norm.weight"
#define TN_MM_INP_NORM_B "mm.input_norm.bias"
#define TN_MM_INP_PROJ "mm.input_projection.weight" // gemma3
#define TN_MM_SOFT_EMB_N "mm.soft_emb_norm.weight" // gemma3
#define TN_MM_PROJECTOR "mm.model.fc.weight" // idefics3
#define TN_MM_PATCH_MERGER "mm.patch_merger.weight" // mistral small 3.1
#define TN_TOK_IMG_BREAK "v.token_embd.img_break" // pixtral
#define TN_TOK_GLM_BOI "adapter.boi" // glm-edge (these embeddings are not in text model)
#define TN_TOK_GLM_EOI "adapter.eoi" // glm-edge (these embeddings are not in text model)
#define TN_DEEPSTACK_NORM "v.deepstack.%d.norm.%s" // qwen3vl deepstack
#define TN_DEEPSTACK_FC1 "v.deepstack.%d.fc1.%s" // qwen3vl deepstack
#define TN_DEEPSTACK_FC2 "v.deepstack.%d.fc2.%s" // qwen3vl deepstack
// mimicpmv
#define TN_MINICPMV_POS_EMBD_K "resampler.pos_embed_k"
#define TN_MINICPMV_QUERY "resampler.query"
#define TN_MINICPMV_PROJ "resampler.proj.weight"
#define TN_MINICPMV_KV_PROJ "resampler.kv.weight"
#define TN_MINICPMV_ATTN "resampler.attn.%s.%s"
#define TN_MINICPMV_LN "resampler.ln_%s.%s"
#define TN_GLM_ADAPER_CONV "adapter.conv.%s"
#define TN_GLM_ADAPTER_LINEAR "adapter.linear.linear.%s"
#define TN_GLM_ADAPTER_NORM_1 "adapter.linear.norm1.%s"
#define TN_GLM_ADAPTER_D_H_2_4H "adapter.linear.dense_h_to_4h.%s"
#define TN_GLM_ADAPTER_GATE "adapter.linear.gate.%s"
#define TN_GLM_ADAPTER_D_4H_2_H "adapter.linear.dense_4h_to_h.%s"
// ultravox
#define TN_CONV1D "a.conv1d.%d.%s"
#define TN_MM_AUDIO_MLP "mm.a.mlp.%d.%s"
#define TN_MM_AUDIO_FC "mm.a.fc.%s" // fully connected layer
#define TN_MM_NORM_PRE "mm.a.norm_pre.%s"
#define TN_MM_NORM_MID "mm.a.norm_mid.%s"
// gemma4
#define TN_STD_BIAS "v.std_bias"
#define TN_STD_SCALE "v.std_scale"
// cogvlm
#define TN_MM_POST_FC_NORM "mm.post_fc_norm.%s"
#define TN_MM_H_TO_4H "mm.up.%s"
#define TN_MM_GATE "mm.gate.%s"
#define TN_MM_4H_TO_H "mm.down.%s"
#define TN_TOK_BOI "v.boi"
#define TN_TOK_EOI "v.eoi"
// align x to upper multiple of n
#define CLIP_ALIGN(x, n) ((((x) + (n) - 1) / (n)) * (n))
enum projector_type {
PROJECTOR_TYPE_MLP,
PROJECTOR_TYPE_MLP_NORM,
PROJECTOR_TYPE_LDP,
PROJECTOR_TYPE_LDPV2,
PROJECTOR_TYPE_MINICPMV,
PROJECTOR_TYPE_GLM_EDGE,
PROJECTOR_TYPE_QWEN2VL,
PROJECTOR_TYPE_QWEN3VL,
PROJECTOR_TYPE_GEMMA3,
PROJECTOR_TYPE_GEMMA4V,
PROJECTOR_TYPE_GEMMA4A,
PROJECTOR_TYPE_IDEFICS3,
PROJECTOR_TYPE_PIXTRAL,
PROJECTOR_TYPE_QWEN25VL,
PROJECTOR_TYPE_ULTRAVOX,
PROJECTOR_TYPE_INTERNVL,
PROJECTOR_TYPE_LLAMA4,
PROJECTOR_TYPE_QWEN2A,
PROJECTOR_TYPE_QWEN25O, // will be replaced by QWEN2A or QWEN25VL depending on clip_ctx
PROJECTOR_TYPE_VOXTRAL,
PROJECTOR_TYPE_LFM2,
PROJECTOR_TYPE_KIMIVL,
PROJECTOR_TYPE_KIMIK25,
PROJECTOR_TYPE_LIGHTONOCR,
PROJECTOR_TYPE_COGVLM,
PROJECTOR_TYPE_JANUS_PRO,
PROJECTOR_TYPE_MINIMAX_M3_VL,
PROJECTOR_TYPE_UNKNOWN,
};
static std::map<projector_type, std::string> PROJECTOR_TYPE_NAMES = {
{ PROJECTOR_TYPE_MLP, "mlp" },
{ PROJECTOR_TYPE_LDP, "ldp" },
{ PROJECTOR_TYPE_LDPV2, "ldpv2"},
{ PROJECTOR_TYPE_MINICPMV, "resampler"},
{ PROJECTOR_TYPE_GLM_EDGE, "adapter"},
{ PROJECTOR_TYPE_QWEN2VL, "qwen2vl_merger"},
{ PROJECTOR_TYPE_QWEN25VL, "qwen2.5vl_merger"},
{ PROJECTOR_TYPE_QWEN3VL, "qwen3vl_merger"},
{ PROJECTOR_TYPE_GEMMA3, "gemma3"},
{ PROJECTOR_TYPE_GEMMA4V, "gemma4v"},
{ PROJECTOR_TYPE_GEMMA4A, "gemma4a"},
{ PROJECTOR_TYPE_IDEFICS3, "idefics3"},
{ PROJECTOR_TYPE_PIXTRAL, "pixtral"},
{ PROJECTOR_TYPE_ULTRAVOX, "ultravox"},
{ PROJECTOR_TYPE_INTERNVL, "internvl"},
{ PROJECTOR_TYPE_LLAMA4, "llama4"},
{ PROJECTOR_TYPE_QWEN2A, "qwen2a"},
{ PROJECTOR_TYPE_QWEN25O, "qwen2.5o"},
{ PROJECTOR_TYPE_VOXTRAL, "voxtral"},
{ PROJECTOR_TYPE_LFM2, "lfm2"},
{ PROJECTOR_TYPE_KIMIVL, "kimivl"},
{ PROJECTOR_TYPE_KIMIK25, "kimik25"},
{ PROJECTOR_TYPE_LIGHTONOCR,"lightonocr"},
{ PROJECTOR_TYPE_COGVLM, "cogvlm"},
{ PROJECTOR_TYPE_JANUS_PRO, "janus_pro"},
{ PROJECTOR_TYPE_MINIMAX_M3_VL, "minimax_m3_vl"},
};
static projector_type clip_projector_type_from_string(const std::string & str) {
for (const auto & pair : PROJECTOR_TYPE_NAMES) {
if (pair.second == str) {
return pair.first;
}
}
return PROJECTOR_TYPE_UNKNOWN;
}
// RGB uint8 image
struct clip_image_u8 {
int nx;
int ny;
std::vector<uint8_t> buf;
};
// For images, buf.size() == nx*ny*3
// Memory layout: RGBRGBRGB...
// For audio, only one channel is used, buf.size() == nx*ny
// nx will be n_frames and ny will be n_mel
struct clip_image_f32 {
int nx;
int ny;
std::vector<float> buf;
};
//
// logging
//
static void clip_log_callback_default(enum ggml_log_level level, const char * text, void * user_data) {
(void) level;
(void) user_data;
fputs(text, stderr);
fflush(stderr);
}
struct clip_logger_state {
ggml_log_level verbosity_thold;
ggml_log_callback log_callback;
void * log_callback_user_data;
};
extern struct clip_logger_state g_logger_state;
static void clip_log_internal_v(enum ggml_log_level level, const char * format, va_list args) {
if (format == NULL) {
return;
}
va_list args_copy;
va_copy(args_copy, args);
char buffer[128];
int len = vsnprintf(buffer, 128, format, args);
if (len < 128) {
g_logger_state.log_callback(level, buffer, g_logger_state.log_callback_user_data);
} else {
char * buffer2 = (char *) calloc(len + 1, sizeof(char));
vsnprintf(buffer2, len + 1, format, args_copy);
buffer2[len] = 0;
g_logger_state.log_callback(level, buffer2, g_logger_state.log_callback_user_data);
free(buffer2);
}
va_end(args_copy);
}
static void clip_log_internal(enum ggml_log_level level, const char * format, ...) {
va_list args;
va_start(args, format);
clip_log_internal_v(level, format, args);
va_end(args);
}
#define LOG_TMPL(level, ...) \
do { \
if ((level) >= g_logger_state.verbosity_thold) { \
clip_log_internal((level), __VA_ARGS__); \
} \
} while (0)
#define LOG_INF(...) LOG_TMPL(GGML_LOG_LEVEL_INFO, __VA_ARGS__)
#define LOG_WRN(...) LOG_TMPL(GGML_LOG_LEVEL_WARN, __VA_ARGS__)
#define LOG_ERR(...) LOG_TMPL(GGML_LOG_LEVEL_ERROR, __VA_ARGS__)
#define LOG_DBG(...) LOG_TMPL(GGML_LOG_LEVEL_DEBUG, __VA_ARGS__)
#define LOG_CNT(...) LOG_TMPL(GGML_LOG_LEVEL_CONT, __VA_ARGS__)
//
// cpp wrappers
//
// wrapper for clip_image_size
struct clip_image_size_deleter {
void operator()(clip_image_size * val) { clip_image_size_free(val); }
};
typedef std::unique_ptr<clip_image_size, clip_image_size_deleter> clip_image_size_ptr;
// wrapper for clip_image_u8
struct clip_image_u8_deleter {
void operator()(clip_image_u8 * val) { clip_image_u8_free(val); }
};
typedef std::unique_ptr<clip_image_u8, clip_image_u8_deleter> clip_image_u8_ptr;
// wrapper for clip_image_f32
struct clip_image_f32_deleter {
void operator()(clip_image_f32 * val) { clip_image_f32_free(val); }
};
typedef std::unique_ptr<clip_image_f32, clip_image_f32_deleter> clip_image_f32_ptr;
struct clip_image_u8_batch {
std::vector<clip_image_u8_ptr> entries;
};
struct clip_image_f32_batch {
std::vector<clip_image_f32_ptr> entries;
bool is_audio = false;
// for llava-uhd style models, we need to know the grid size
// note: entries.size() == grid_x * grid_y + 1 (one overview image)
int grid_x = 0;
int grid_y = 0;
clip_image_f32_batch clone() const {
clip_image_f32_batch new_batch{
/* entries */ {},
/* is_audio */ is_audio,
/* grid_x */ grid_x,
/* grid_y */ grid_y,
};
new_batch.entries.reserve(entries.size());
for (const auto & entry : entries) {
new_batch.entries.emplace_back(new clip_image_f32(*entry));
}
return new_batch;
}
};
//
// common utils
//
static std::string string_format(const char * fmt, ...) {
va_list ap;
va_list ap2;
va_start(ap, fmt);
va_copy(ap2, ap);
int size = vsnprintf(NULL, 0, fmt, ap);
GGML_ASSERT(size >= 0 && size < INT_MAX); // NOLINT
std::vector<char> buf(size + 1);
int size2 = vsnprintf(buf.data(), size + 1, fmt, ap2);
GGML_ASSERT(size2 == size);
va_end(ap2);
va_end(ap);
return std::string(buf.data(), buf.size());
}
static void string_replace_all(std::string & s, const std::string & search, const std::string & replace) {
if (search.empty()) {
return;
}
std::string builder;
builder.reserve(s.length());
size_t pos = 0;
size_t last_pos = 0;
while ((pos = s.find(search, last_pos)) != std::string::npos) {
builder.append(s, last_pos, pos - last_pos);
builder.append(replace);
last_pos = pos + search.length();
}
builder.append(s, last_pos, std::string::npos);
s = std::move(builder);
}
// split string by a `std::string delim` instead of `char delim`
static std::vector<std::string> string_split_str(std::string s, const std::string & delimiter) {
std::vector<std::string> tokens;
size_t pos = 0;
std::string token;
while ((pos = s.find(delimiter)) != std::string::npos) {
token = s.substr(0, pos);
tokens.push_back(token);
s.erase(0, pos + delimiter.length());
}
tokens.push_back(s);
return tokens;
}
//
// gguf utils
//
static std::string gguf_data_to_str(enum gguf_type type, const void * data, int i) {
switch (type) {
case GGUF_TYPE_UINT8: return std::to_string(((const uint8_t *)data)[i]);
case GGUF_TYPE_INT8: return std::to_string(((const int8_t *)data)[i]);
case GGUF_TYPE_UINT16: return std::to_string(((const uint16_t *)data)[i]);
case GGUF_TYPE_INT16: return std::to_string(((const int16_t *)data)[i]);
case GGUF_TYPE_UINT32: return std::to_string(((const uint32_t *)data)[i]);
case GGUF_TYPE_INT32: return std::to_string(((const int32_t *)data)[i]);
case GGUF_TYPE_UINT64: return std::to_string(((const uint64_t *)data)[i]);
case GGUF_TYPE_INT64: return std::to_string(((const int64_t *)data)[i]);
case GGUF_TYPE_FLOAT32: return std::to_string(((const float *)data)[i]);
case GGUF_TYPE_FLOAT64: return std::to_string(((const double *)data)[i]);
case GGUF_TYPE_BOOL: return ((const int8_t *)data)[i] != 0 ? "true" : "false";
default: return string_format("unknown type %d", type);
}
}
static std::string gguf_kv_to_str(const struct gguf_context * ctx_gguf, int i) {
const enum gguf_type type = gguf_get_kv_type(ctx_gguf, i);
switch (type) {
case GGUF_TYPE_STRING:
return gguf_get_val_str(ctx_gguf, i);
case GGUF_TYPE_ARRAY:
{
const enum gguf_type arr_type = gguf_get_arr_type(ctx_gguf, i);
int arr_n = gguf_get_arr_n(ctx_gguf, i);
const void * data = arr_type == GGUF_TYPE_STRING ? nullptr : gguf_get_arr_data(ctx_gguf, i);
std::stringstream ss;
ss << "[";
for (int j = 0; j < arr_n; j++) {
if (arr_type == GGUF_TYPE_STRING) {
std::string val = gguf_get_arr_str(ctx_gguf, i, j);
// escape quotes
string_replace_all(val, "\\", "\\\\");
string_replace_all(val, "\"", "\\\"");
ss << '"' << val << '"';
} else if (arr_type == GGUF_TYPE_ARRAY) {
ss << "???";
} else {
ss << gguf_data_to_str(arr_type, data, j);
}
if (j < arr_n - 1) {
ss << ", ";
}
}
ss << "]";
return ss.str();
}
default:
return gguf_data_to_str(type, gguf_get_val_data(ctx_gguf, i), 0);
}
}
//
// debugging
//
static void print_tensor_shape(ggml_tensor * t) {
printf("%s.shape = [", t->name);
for (int i = 0; i < ggml_n_dims(t); ++i) {
printf("%" PRId64, t->ne[i]);
if (i < ggml_n_dims(t) - 1) {
printf(", ");
}
}
printf("]\n");
}
static void print_tensor_data(ggml_tensor * t, uint8_t * data, int64_t n) {
ggml_type type = t->type;
int64_t * ne = t->ne;
size_t * nb = t->nb;
for (int64_t i3 = 0; i3 < ne[3]; i3++) {
printf("%s.data: [\n", t->name);
for (int64_t i2 = 0; i2 < ne[2]; i2++) {
if (i2 == n && ne[2] > 2*n) {
printf(" ..., \n");
i2 = ne[2] - n;
}
printf(" [\n");
for (int64_t i1 = 0; i1 < ne[1]; i1++) {
if (i1 == n && ne[1] > 2*n) {
printf(" ..., \n");
i1 = ne[1] - n;
}
printf(" [");
for (int64_t i0 = 0; i0 < ne[0]; i0++) {
if (i0 == n && ne[0] > 2*n) {
printf("..., ");
i0 = ne[0] - n;
}
size_t i = i3 * nb[3] + i2 * nb[2] + i1 * nb[1] + i0 * nb[0];
float v;
if (type == GGML_TYPE_F16) {
v = ggml_fp16_to_fp32(*(ggml_fp16_t *) &data[i]);
} else if (type == GGML_TYPE_F32) {
v = *(float *) &data[i];
} else if (type == GGML_TYPE_I32) {
v = (float) *(int32_t *) &data[i];
} else if (type == GGML_TYPE_I16) {
v = (float) *(int16_t *) &data[i];
} else if (type == GGML_TYPE_I8) {
v = (float) *(int8_t *) &data[i];
} else {
GGML_ABORT("fatal error");
}
printf("%8.4f", v);
if (i0 < ne[0] - 1) printf(", ");
}
printf("],\n");
}
printf(" ],\n");
}
printf(" ]\n");
}
}
//
// API used internally with mtmd
//
projector_type clip_get_projector_type(const struct clip_ctx * ctx);