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

109 lines
2.7 KiB
C++

#pragma once
#include "engine/models/pocket_tts_small/assets.h"
#include "engine/models/pocket_tts_small/flow_lm.h"
#include "engine/framework/assets/tensor_source.h"
#include <cstddef>
#include <cstdint>
#include <ggml-backend.h>
#include <memory>
#include <optional>
#include <string>
#include <vector>
namespace engine::models::pocket_tts_small {
struct Assets;
struct HostWeights;
struct TextConditionerConfig {
int64_t hidden_size = 512;
};
struct TextConditioningResult {
std::string prepared_text;
std::vector<int32_t> tokens;
std::vector<float> text_embeddings;
};
class TextConditioner {
public:
explicit TextConditioner(TextConditionerConfig config = {});
TextConditioningResult prepare(
const Assets & manifest,
const HostWeights & weights,
const std::string & text,
ggml_backend_t backend = nullptr,
int threads = 1) const;
// Splits a prompt the way the reference implementation does (pocket_tts_small
// split_into_best_sentences): sentence boundaries found on the model's own
// end-of-sentence tokens, sentences longer than max_tokens split again on
// ",;:", then regrouped into chunks of at most max_tokens tokens.
std::vector<std::string> split_into_sentence_chunks(
const Assets & manifest,
const std::string & text,
int64_t max_tokens) const;
private:
TextConditionerConfig config_;
mutable std::optional<assets::TensorDataF32> projected_embeddings_;
};
struct Assets;
struct BackendWeights;
struct MimiPromptEmbedding {
std::vector<float> values;
int64_t frames = 0;
};
class MimiEncoder {
public:
MimiEncoder();
~MimiEncoder();
MimiPromptEmbedding encode_prompt_embedding(
ggml_backend_t backend,
int threads,
const Assets & manifest,
const BackendWeights & weights,
const std::vector<float> & waveform,
size_t graph_context_bytes) const;
private:
struct Runtime;
mutable std::unique_ptr<Runtime> runtime_;
};
struct Assets;
struct BackendWeights;
struct VoiceConditioningResult {
VoiceConditioningPlan plan;
FlowLMState acoustic_state;
};
class VoiceConditioner {
public:
explicit VoiceConditioner(FlowLMConfig flow_config = {});
VoiceConditioningResult prepare(
const VoiceConditioningPlan & plan,
const Assets & manifest,
const BackendWeights & weights,
ggml_backend_t backend,
int threads,
size_t mimi_encoder_graph_context_bytes,
size_t flow_weights_view_context_bytes,
size_t flow_step_graph_context_bytes) const;
private:
FlowLM flow_lm_;
MimiEncoder mimi_encoder_;
};
} // namespace engine::models::pocket_tts_small