offline-paraformer-model.h
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// sherpa-onnx/csrc/offline-paraformer-model.h
//
// Copyright (c) 2022-2023 Xiaomi Corporation
#ifndef SHERPA_ONNX_CSRC_OFFLINE_PARAFORMER_MODEL_H_
#define SHERPA_ONNX_CSRC_OFFLINE_PARAFORMER_MODEL_H_
#include <memory>
#include <vector>
#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/offline-model-config.h"
namespace sherpa_onnx {
class OfflineParaformerModel {
public:
explicit OfflineParaformerModel(const OfflineModelConfig &config);
#if __ANDROID_API__ >= 9
OfflineParaformerModel(AAssetManager *mgr, const OfflineModelConfig &config);
#endif
~OfflineParaformerModel();
/** Run the forward method of the model.
*
* @param features A tensor of shape (N, T, C). It is changed in-place.
* @param features_length A 1-D tensor of shape (N,) containing number of
* valid frames in `features` before padding.
* Its dtype is int32_t.
*
* @return Return a vector containing:
* - log_probs: A 3-D tensor of shape (N, T', vocab_size)
* - token_num: A 1-D tensor of shape (N, T') containing number
* of valid tokens in each utterance. Its dtype is int64_t.
* If it is a model supporting timestamps, then there are additional two
* outputs:
* - us_alphas
* - us_cif_peak
*/
std::vector<Ort::Value> Forward(Ort::Value features,
Ort::Value features_length);
/** Return the vocabulary size of the model
*/
int32_t VocabSize() const;
/** It is lfr_m in config.yaml
*/
int32_t LfrWindowSize() const;
/** It is lfr_n in config.yaml
*/
int32_t LfrWindowShift() const;
/** Return negative mean for CMVN
*/
const std::vector<float> &NegativeMean() const;
/** Return inverse stddev for CMVN
*/
const std::vector<float> &InverseStdDev() const;
/** Return an allocator for allocating memory
*/
OrtAllocator *Allocator() const;
private:
class Impl;
std::unique_ptr<Impl> impl_;
};
} // namespace sherpa_onnx
#endif // SHERPA_ONNX_CSRC_OFFLINE_PARAFORMER_MODEL_H_