// 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 #include #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/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 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_; }; } // namespace sherpa_onnx #endif // SHERPA_ONNX_CSRC_OFFLINE_ZIPFORMER_CTC_MODEL_H_