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enginex_bi_series-sherpa-onnx/sherpa-onnx/csrc/offline-lm.h
Askars Salimbajevs f0960342ad Add LODR support to online and offline recognizers (#2026)
This PR integrates LODR (Level-Ordered Deterministic Rescoring) support from Icefall into both online and offline recognizers, enabling LODR for LM shallow fusion and LM rescore.

- Extended OnlineLMConfig and OfflineLMConfig to include lodr_fst, lodr_scale, and lodr_backoff_id.
- Implemented LodrFst and LodrStateCost classes and wired them into RNN LM scoring in both online and offline code paths.
- Updated Python bindings, CLI entry points, examples, and CI test scripts to accept and exercise the new LODR options.
2025-07-09 16:23:46 +08:00

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2.1 KiB
C++

// sherpa-onnx/csrc/offline-lm.h
//
// Copyright (c) 2023 Xiaomi Corporation
#ifndef SHERPA_ONNX_CSRC_OFFLINE_LM_H_
#define SHERPA_ONNX_CSRC_OFFLINE_LM_H_
#include <memory>
#include <vector>
#include "onnxruntime_cxx_api.h" // NOLINT
#include "sherpa-onnx/csrc/hypothesis.h"
#include "sherpa-onnx/csrc/lodr-fst.h"
#include "sherpa-onnx/csrc/offline-lm-config.h"
namespace sherpa_onnx {
class OfflineLM {
public:
explicit OfflineLM(const OfflineLMConfig &config) : config_(config) {
if (!config_.lodr_fst.empty()) {
try {
lodr_fst_ = std::make_unique<LodrFst>(LodrFst(config_.lodr_fst,
config_.lodr_backoff_id));
} catch (const std::exception& e) {
throw std::runtime_error("Failed to load LODR FST from: " +
config_.lodr_fst + ". Error: " + e.what());
}
}
}
virtual ~OfflineLM() = default;
static std::unique_ptr<OfflineLM> Create(const OfflineLMConfig &config);
template <typename Manager>
static std::unique_ptr<OfflineLM> Create(Manager *mgr,
const OfflineLMConfig &config);
/** Rescore a batch of sentences.
*
* @param x A 2-D tensor of shape (N, L) with data type int64.
* @param x_lens A 1-D tensor of shape (N,) with data type int64.
* It contains number of valid tokens in x before padding.
* @return Return a 1-D tensor of shape (N,) containing the negative log
* likelihood of each utterance. Its data type is float32.
*
* Caution: It returns negative log likelihood (nll), not log likelihood
*/
virtual Ort::Value Rescore(Ort::Value x, Ort::Value x_lens) = 0;
// This function updates hyp.lm_lob_prob of hyps.
//
// @param scale LM score
// @param context_size Context size of the transducer decoder model
// @param hyps It is changed in-place.
void ComputeLMScore(float scale, int32_t context_size,
std::vector<Hypotheses> *hyps);
private:
std::unique_ptr<LodrFst> lodr_fst_;
float lodr_scale_;
OfflineLMConfig config_;
};
} // namespace sherpa_onnx
#endif // SHERPA_ONNX_CSRC_OFFLINE_LM_H_