mtmd: support Qwen3-TTS (note: breaking change to llama-tts binary) (#26254)

* convert text model

* main model load ok

* convert encoder ok

* speaker encoder loading ok

* speaker enc graph

* adapt vocab for backbone (with some tricks)

* add suppress_tokens

* poc new mtmd gen api

* convert code_predictor to gguf

* load gen_code model ok

* add clip_encode

* wire up

* code gen cgraph init version

Co-authored-by: Pascal <admin@serveurperso.com>

* code2wav convert to gguf

* code2wav graph ok

* wire up in/out

* (wip) subgraph

* wire up

* wip, correct code2wav

* demo (to be removed)

* code2wav preserve kv between calls

* demo voice clone

* llama: add llama_model_get_tok_embd

* mtmd_helper_gen_audio API

* fix clamp cold prefix

Co-authored-by: Pascal <admin@serveurperso.com>

* fuse snake op

Co-authored-by: Pascal <admin@serveurperso.com>

* demo: use proper sampling

* update dev docs

* polymorphism helper

* revamp llama-tts binary

* update docs

* fix compile

* fix lint

* nits

* add guide + docs

* more timings info

* clean up code comments

* security fixes

* update docs

* use ggml_build_forward_select, clean up comments

* fix ci

* use ISO 639-1 language code

* rename CODE2WAV --> GEN_WAV, update docs

* clean up

* clean up tts.cpp

* add seq_id

* add step_prompt()

* mtmd_helper_model_can_chat

* clean up comments

---------

Co-authored-by: Pascal <admin@serveurperso.com>
This commit is contained in:
Xuan-Son Nguyen
2026-08-04 17:26:15 +02:00
committed by GitHub
co-authored by Pascal
parent 1c3c9674de
commit 0713275082
42 changed files with 3808 additions and 1895 deletions
+180
View File
@@ -0,0 +1,180 @@
#pragma once
// shared internal utilities for the mtmd-helper-*.cpp translation units
// (mtmd-helper.cpp, mtmd-helper-gen.cpp)
// NOT part of the public mtmd-helper.h API
#include "ggml.h"
#include "llama.h"
#include "mtmd.h"
#include <cstdarg>
#include <cstdio>
#include <cstdlib>
#include <vector>
//
// logging
//
struct mtmd_helper_logger {
ggml_log_callback default_callback = [](ggml_log_level level, const char * text, void * user_data) {
(void) level;
(void) user_data;
fputs(text, stderr);
fflush(stderr);
};
ggml_log_callback log_callback = default_callback;
void * log_callback_user_data;
void log_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) {
log_callback(level, buffer, log_callback_user_data);
} else {
char * buffer2 = (char *) calloc(len + 1, sizeof(char));
vsnprintf(buffer2, len + 1, format, args_copy);
buffer2[len] = 0;
log_callback(level, buffer2, log_callback_user_data);
free(buffer2);
}
va_end(args_copy);
}
void log(enum ggml_log_level level, const char * format, ...) {
va_list args;
va_start(args, format);
log_v(level, format, args);
va_end(args);
}
};
// inline, so all TUs including this header share one instance
inline mtmd_helper_logger g_logger;
#define LOG_DBG(...) g_logger.log(GGML_LOG_LEVEL_DEBUG, __VA_ARGS__)
#define LOG_INF(...) g_logger.log(GGML_LOG_LEVEL_INFO, __VA_ARGS__)
#define LOG_WRN(...) g_logger.log(GGML_LOG_LEVEL_WARN, __VA_ARGS__)
#define LOG_ERR(...) g_logger.log(GGML_LOG_LEVEL_ERROR, __VA_ARGS__)
//
// embd batch
//
// helper struct to make working with embd batch easier
// note: this will be removed after llama_batch_ext refactoring
struct decode_embd_batch {
int n_pos_per_embd;
int n_mmproj_embd;
std::vector<llama_pos> pos;
std::vector<llama_pos> pos_view; // used by mrope
std::vector<int32_t> n_seq_id;
std::vector<llama_seq_id> seq_id_0;
std::vector<llama_seq_id *> seq_ids;
std::vector<int8_t> logits;
llama_batch batch;
decode_embd_batch(float * embd, int32_t n_tokens, int n_pos_per_embd, int n_mmproj_embd) : n_pos_per_embd(n_pos_per_embd), n_mmproj_embd(n_mmproj_embd) {
GGML_ASSERT(n_tokens > 0 && n_pos_per_embd > 0 && n_mmproj_embd > 0);
pos .resize(n_tokens * n_pos_per_embd);
n_seq_id.resize(n_tokens);
seq_ids .resize(n_tokens + 1);
logits .resize(n_tokens);
seq_id_0.resize(1);
seq_ids [n_tokens] = nullptr;
batch = {
/*n_tokens =*/ n_tokens,
/*tokens =*/ nullptr,
/*embd =*/ embd,
/*pos =*/ pos.data(),
/*n_seq_id =*/ n_seq_id.data(),
/*seq_id =*/ seq_ids.data(),
/*logits =*/ logits.data(),
};
}
void set_position_normal(llama_pos pos_0, llama_seq_id seq_id) {
seq_id_0[0] = seq_id;
for (int i = 0; i < batch.n_tokens; i++) {
batch.pos [i] = pos_0 + i;
batch.n_seq_id[i] = 1;
batch.seq_id [i] = seq_id_0.data();
batch.logits [i] = false;
}
}
// M-RoPE for image
void set_position_mrope_2d(const std::vector<mtmd_decoder_pos> & rel_pos, llama_seq_id seq_id) {
GGML_ASSERT(n_pos_per_embd == 4);
GGML_ASSERT(!rel_pos.empty() && (int32_t)rel_pos.size() == batch.n_tokens);
seq_id_0[0] = seq_id;
for (int32_t i = 0; i < batch.n_tokens; i++) {
pos[i ] = rel_pos[i].t;
pos[i + batch.n_tokens ] = rel_pos[i].y;
pos[i + batch.n_tokens * 2] = rel_pos[i].x;
pos[i + batch.n_tokens * 3] = rel_pos[i].z;
}
for (int i = 0; i < batch.n_tokens; i++) {
batch.n_seq_id[i] = 1;
batch.seq_id [i] = seq_id_0.data();
batch.logits [i] = false;
}
}
// M-RoPE for audio
void set_position_mrope_1d(llama_pos pos_0, llama_seq_id seq_id) {
GGML_ASSERT(n_pos_per_embd == 4);
seq_id_0[0] = seq_id;
for (int i = 0; i < batch.n_tokens; i++) {
pos[i ] = pos_0 + i;
pos[i + batch.n_tokens ] = pos_0 + i;
pos[i + batch.n_tokens * 2] = pos_0 + i;
pos[i + batch.n_tokens * 3] = pos_0 + i;
}
for (int i = 0; i < batch.n_tokens; i++) {
batch.n_seq_id[i] = 1;
batch.seq_id [i] = seq_id_0.data();
batch.logits [i] = false;
}
}
llama_batch get_view(int offset, int n_tokens) {
GGML_ASSERT(offset >= 0 && n_tokens > 0 && offset + n_tokens <= batch.n_tokens);
llama_pos * pos_ptr;
pos_view.clear();
pos_view.reserve(n_tokens * n_pos_per_embd);
if (n_pos_per_embd > 1) {
// mrope
// for example, with layout of src: 1234...1234...1234...1234...
// offset 2 will give us dst: 34...34...34...34...
for (int i = 0; i < n_pos_per_embd; i++) {
// assume n_tokens is less than or equal to batch.n_tokens
// batch.n_tokens is number of **total** tokens
// n_tokens is number of viewed token
size_t src_idx = i * batch.n_tokens + offset;
pos_view.insert(pos_view.end(),
pos.data() + src_idx,
pos.data() + src_idx + n_tokens);
}
pos_ptr = pos_view.data();
} else {
// normal
pos_ptr = pos.data() + offset;
}
return {
/*n_tokens =*/ n_tokens,
/*tokens =*/ nullptr,
/*embd =*/ batch.embd + offset * n_mmproj_embd,
/*pos =*/ pos_ptr,
/*n_seq_id =*/ batch.n_seq_id + offset,
/*seq_id =*/ batch.seq_id + offset,
/*logits =*/ batch.logits + offset,
};
}
};