mirror of
https://github.com/ggml-org/llama.cpp.git
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* 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>
134 lines
4.4 KiB
C++
134 lines
4.4 KiB
C++
#pragma once
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#include "ggml.h"
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#include "mtmd.h"
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#include <stddef.h>
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#include <stdint.h>
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#include <map>
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// !!! Internal header, to be used by mtmd only !!!
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#define MTMD_INTERNAL_HEADER
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struct clip_ctx;
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struct clip_image_size {
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int width;
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int height;
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bool operator==(const clip_image_size & other) const {
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return width == other.width && height == other.height;
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}
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bool operator!=(const clip_image_size & other) const {
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return !(*this == other);
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}
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int area() const {
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// avoid overflow when computing area
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GGML_ASSERT(width >= 0 && width <= 46000);
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GGML_ASSERT(height >= 0 && height <= 46000);
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return width * height;
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}
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};
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struct clip_image_f32;
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struct clip_image_f32_batch;
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enum clip_modality {
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CLIP_MODALITY_VISION,
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CLIP_MODALITY_AUDIO,
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CLIP_MODALITY_GEN_AUDIO,
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};
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enum clip_flash_attn_type {
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CLIP_FLASH_ATTN_TYPE_AUTO = -1,
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CLIP_FLASH_ATTN_TYPE_DISABLED = 0,
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CLIP_FLASH_ATTN_TYPE_ENABLED = 1,
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};
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struct clip_context_params {
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bool use_gpu;
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enum clip_flash_attn_type flash_attn_type;
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int image_min_tokens;
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int image_max_tokens;
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bool warmup;
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ggml_backend_sched_eval_callback cb_eval;
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void * cb_eval_user_data;
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bool no_alloc;
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mtmd_progress_callback progress_callback;
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void * progress_callback_user_data;
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};
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struct clip_init_result {
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struct clip_ctx * ctx_v; // vision context
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struct clip_ctx * ctx_a; // audio context
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struct clip_ctx * ctx_gen_a; // audio generation context
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};
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struct clip_init_result clip_init(const char * fname, struct clip_context_params ctx_params);
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void clip_free(struct clip_ctx * ctx);
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// TODO: should be enum, not string
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const char * clip_patch_merge_type(const struct clip_ctx * ctx);
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int clip_n_output_tokens(const clip_ctx * ctx, const clip_image_f32 * img);
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// for M-RoPE, this will be the number of token positions in X and Y directions
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// for other models, X will be the total number of tokens and Y will be 1
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int clip_n_output_tokens_x(const clip_ctx * ctx, const clip_image_f32 * img);
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int clip_n_output_tokens_y(const clip_ctx * ctx, const clip_image_f32 * img);
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// this should be equal to the embedding dimension of the text model
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int clip_n_mmproj_embd(const struct clip_ctx * ctx);
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// TODO: remove clip_image_encode() and always use batched version
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bool clip_image_encode (struct clip_ctx * ctx, int n_threads, const clip_image_f32 * img, std::vector<float> & out_vec);
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bool clip_image_batch_encode(struct clip_ctx * ctx, int n_threads, const struct clip_image_f32_batch * imgs, std::vector<float> & out_batch_embd);
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enum clip_gen_process_type {
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CLIP_GEN_PROCESS_GEN_UNKNOWN,
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CLIP_GEN_PROCESS_GEN_CODE, // h_state to codes
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CLIP_GEN_PROCESS_GEN_WAV, // codes to raw PCM audio
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};
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struct clip_encode_params {
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int n_threads = 1;
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const clip_image_f32_batch * imgs = nullptr;
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std::vector<float> * out_embd = nullptr;
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// for audio gen, imgs has exactly one entry: hidden state from backbone (GEN_CODE) or unused (GEN_WAV)
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clip_gen_process_type gen_process = CLIP_GEN_PROCESS_GEN_UNKNOWN;
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// GEN_CODE: out_embd receives the embd to feed back to the backbone
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int32_t code0 = 0; // semantic code sampled by the backbone
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int32_t top_k = 50;
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float top_p = 1.0f;
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std::vector<int32_t> * out_codes = nullptr; // this frame's 16 sampled codes
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// GEN_WAV
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const std::vector<int32_t> * codes = nullptr; // this frame's 16 RVQ codes
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std::vector<float> * out_audio = nullptr; // decoded PCM samples, F32
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const std::vector<uint8_t> * state_in = nullptr; // state from previous call, null or wrong size means cold start
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std::vector<uint8_t> * state_out = nullptr; // state for the next call
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};
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bool clip_encode(struct clip_ctx * ctx, struct clip_encode_params * params);
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bool clip_is_llava(const struct clip_ctx * ctx);
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// note for contributor: this clip_is_(model) pattern is deprecated
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// do NOT add new functions like this
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bool clip_has_vision_encoder(const struct clip_ctx * ctx);
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bool clip_has_audio_encoder(const struct clip_ctx * ctx);
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bool clip_support_batch(const struct clip_ctx * ctx);
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int clip_model_n_temporal_merge(const struct clip_ctx * ctx); // TODO @ngxson : remove, refactor this
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std::map<ggml_backend_dev_t, size_t> clip_get_mem_usage(const struct clip_ctx * ctx);
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struct clip_cap {
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bool has_vision;
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bool has_audio;
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};
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struct clip_cap clip_get_cap(const char * fname);
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