voice_audio_multi/include/engine/community_models/lfm3_audio/assets.h
Fabio c36510c21e
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Initial import: audio.cpp with Orange Pi documentation
2026-11-04 19:05:22 +01:00

83 lines
3.3 KiB
C++

#pragma once
// LFM3-Audio assets. The model is one checkpoint: the backbone with its ASR
// encoder and MaskGIT depth decoder ("model" tensors, HF names such as
// lfm.model.layers.0...), and the LiquidCodec decoder ("codec" tensors). It
// loads from the upstream safetensors directory, with config.json,
// generation_config.json, tokenizer.json and audio_tokenizer/config.json, or
// from Liquid's published GGUFs (published_gguf.h), which give the same.
#include "engine/community_models/lfm3_audio/blocks.h"
#include "engine/framework/assets/resource_bundle.h"
#include "engine/framework/assets/tensor_source.h"
#include "engine/framework/tokenizers/llama_bpe.h"
#include <cstdint>
#include <filesystem>
#include <memory>
#include <vector>
namespace engine::community_models::lfm3_audio {
struct Lfm3TokenSpecials { // from generation_config.json
std::vector<int32_t> eos_ids; // [124900, 125014]
};
struct Lfm3BackboneConfig { // lfm.* ; vocab 128000, tied head
blocks::StackConfig stack;
int64_t vocab_size = 0;
};
struct Lfm3EncoderConfig {
int64_t n_mels = 128, conv_channels = 256, mel_after_downsample = 16; // 128/8
blocks::StackConfig stack; // LFM2 names, 17 layers, conv k3, all attention = sliding(32), theta 1e6
int64_t output_size = 2048;
};
struct Lfm3DepthConfig {
blocks::StackConfig stack; // 3 layers, bidirectional, gate, no sandwich, theta 1e6, hd 32
int64_t input_size = 2048, codebooks = 12, audio_vocab_size = 2017;
std::vector<int64_t> maskgit_schedule; // [4,4,4] (config maskgit_steps=3)
[[nodiscard]] int32_t end_of_audio() const noexcept { return static_cast<int32_t>(audio_vocab_size - 1); }
};
struct Lfm3CodecConfig {
blocks::StackConfig stack; // dims from tensor shapes: the upstream python hard-codes them
std::vector<int64_t> fsq_levels; // [8,7,6,6]
int64_t codebooks = 12, quantizer_dim = 256, upsample = 6, n_fft = 1280, hop = 320;
int sample_rate = 24000;
};
// generation_config.json audio_* (the published GGUF's clip.gen.audio.sampling.*): the speech sampling of
// TTS and S2S when a request sets none; the model card's settings when the file has none.
struct Lfm3SpeechSampling {
float temperature = 1.0f;
int64_t top_k = 128;
float repetition_penalty = 1.1f;
int64_t repetition_window = 4096; // frames of history per codebook
};
struct Lfm3GenerationConfig {
int64_t interleaved_text = 6, interleaved_audio = 12;
Lfm3TokenSpecials specials;
Lfm3SpeechSampling speech;
};
struct Lfm3AudioAssets {
assets::ResourceBundle resources; // required by SpecBackedVoiceModelLoader::inspect
Lfm3BackboneConfig backbone;
Lfm3EncoderConfig encoder;
Lfm3DepthConfig depth;
Lfm3CodecConfig codec;
Lfm3GenerationConfig generation;
std::shared_ptr<const assets::TensorSource> model;
std::shared_ptr<const assets::TensorSource> codec_weights; // resource id "codec" (decoder.*, quantizer.*, from_quantizer.*)
std::filesystem::path tokenizer_json;
// Published GGUFs: no resources or tokenizer.json, but the backbone's vocabulary and its path.
tokenizers::LlamaBpeGgufVocabulary vocabulary;
std::filesystem::path published_backbone;
};
std::shared_ptr<const Lfm3AudioAssets> load_lfm3_audio_assets(const std::filesystem::path & model_path);
} // namespace engine::community_models::lfm3_audio