offline-zipformer-ctc-model.h
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// sherpa-onnx/csrc/offline-zipformer-ctc-model.h
//
// Copyright (c) 2023 Xiaomi Corporation
#ifndef SHERPA_ONNX_CSRC_OFFLINE_ZIPFORMER_CTC_MODEL_H_
#define SHERPA_ONNX_CSRC_OFFLINE_ZIPFORMER_CTC_MODEL_H_
#include <memory>
#include <utility>
#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-ctc-model.h"
#include "sherpa-onnx/csrc/offline-model-config.h"
namespace sherpa_onnx {
/** This class implements the zipformer CTC model of the librispeech recipe
* from icefall.
*
* See
* https://github.com/k2-fsa/icefall/blob/master/egs/librispeech/ASR/zipformer/export-onnx-ctc.py
*/
class OfflineZipformerCtcModel : public OfflineCtcModel {
public:
explicit OfflineZipformerCtcModel(const OfflineModelConfig &config);
#if __ANDROID_API__ >= 9
OfflineZipformerCtcModel(AAssetManager *mgr,
const OfflineModelConfig &config);
#endif
~OfflineZipformerCtcModel() override;
/** Run the forward method of the model.
*
* @param features A tensor of shape (N, T, C).
* @param features_length A 1-D tensor of shape (N,) containing number of
* valid frames in `features` before padding.
* Its dtype is int64_t.
*
* @return Return a vector containing:
* - log_probs: A 3-D tensor of shape (N, T', vocab_size).
* - log_probs_length A 1-D tensor of shape (N,). Its dtype is int64_t
*/
std::vector<Ort::Value> Forward(Ort::Value features,
Ort::Value features_length) override;
/** Return the vocabulary size of the model
*/
int32_t VocabSize() const override;
/** Return an allocator for allocating memory
*/
OrtAllocator *Allocator() const override;
int32_t SubsamplingFactor() const override;
private:
class Impl;
std::unique_ptr<Impl> impl_;
};
} // namespace sherpa_onnx
#endif // SHERPA_ONNX_CSRC_OFFLINE_ZIPFORMER_CTC_MODEL_H_