57 lines
1.7 KiB
C++
57 lines
1.7 KiB
C++
// sherpa-onnx/csrc/offline-lm.h
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//
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// Copyright (c) 2023 Xiaomi Corporation
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#ifndef SHERPA_ONNX_CSRC_OFFLINE_LM_H_
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#define SHERPA_ONNX_CSRC_OFFLINE_LM_H_
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#include <memory>
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#include <vector>
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#if __ANDROID_API__ >= 9
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#include "android/asset_manager.h"
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#include "android/asset_manager_jni.h"
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#endif
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#include "onnxruntime_cxx_api.h" // NOLINT
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#include "sherpa-onnx/csrc/hypothesis.h"
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#include "sherpa-onnx/csrc/offline-lm-config.h"
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namespace sherpa_onnx {
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class OfflineLM {
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public:
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virtual ~OfflineLM() = default;
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static std::unique_ptr<OfflineLM> Create(const OfflineLMConfig &config);
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#if __ANDROID_API__ >= 9
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static std::unique_ptr<OfflineLM> Create(AAssetManager *mgr,
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const OfflineLMConfig &config);
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#endif
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/** Rescore a batch of sentences.
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*
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* @param x A 2-D tensor of shape (N, L) with data type int64.
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* @param x_lens A 1-D tensor of shape (N,) with data type int64.
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* It contains number of valid tokens in x before padding.
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* @return Return a 1-D tensor of shape (N,) containing the negative log
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* likelihood of each utterance. Its data type is float32.
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*
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* Caution: It returns negative log likelihood (nll), not log likelihood
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*/
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virtual Ort::Value Rescore(Ort::Value x, Ort::Value x_lens) = 0;
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// This function updates hyp.lm_lob_prob of hyps.
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//
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// @param scale LM score
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// @param context_size Context size of the transducer decoder model
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// @param hyps It is changed in-place.
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void ComputeLMScore(float scale, int32_t context_size,
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std::vector<Hypotheses> *hyps);
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};
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} // namespace sherpa_onnx
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#endif // SHERPA_ONNX_CSRC_OFFLINE_LM_H_
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