// 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 #include #if __ANDROID_API__ >= 9 #include "android/asset_manager.h" #include "android/asset_manager_jni.h" #endif #include "onnxruntime_cxx_api.h" // NOLINT #include "sherpa-onnx/csrc/hypothesis.h" #include "sherpa-onnx/csrc/offline-lm-config.h" namespace sherpa_onnx { class OfflineLM { public: virtual ~OfflineLM() = default; static std::unique_ptr Create(const OfflineLMConfig &config); #if __ANDROID_API__ >= 9 static std::unique_ptr Create(AAssetManager *mgr, const OfflineLMConfig &config); #endif /** 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 *hyps); }; } // namespace sherpa_onnx #endif // SHERPA_ONNX_CSRC_OFFLINE_LM_H_