// sherpa-onnx/csrc/offline-dolphin-model.h // // Copyright (c) 2025 Xiaomi Corporation #ifndef SHERPA_ONNX_CSRC_OFFLINE_DOLPHIN_MODEL_H_ #define SHERPA_ONNX_CSRC_OFFLINE_DOLPHIN_MODEL_H_ #include #include #include "onnxruntime_cxx_api.h" // NOLINT #include "sherpa-onnx/csrc/offline-ctc-model.h" #include "sherpa-onnx/csrc/offline-dolphin-model-meta-data.h" #include "sherpa-onnx/csrc/offline-model-config.h" namespace sherpa_onnx { class OfflineDolphinModel : public OfflineCtcModel { public: explicit OfflineDolphinModel(const OfflineModelConfig &config); template OfflineDolphinModel(Manager *mgr, const OfflineModelConfig &config); ~OfflineDolphinModel() 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; /** SubsamplingFactor of the model * * For Citrinet, the subsampling factor is usually 4. * For Conformer CTC, the subsampling factor is usually 8. */ int32_t SubsamplingFactor() const override; /** Return an allocator for allocating memory */ OrtAllocator *Allocator() const override; bool SupportBatchProcessing() const override { return true; } void NormalizeFeatures(float *features, int32_t num_frames, int32_t feat_dim) const override; private: class Impl; std::unique_ptr impl_; }; } // namespace sherpa_onnx #endif // SHERPA_ONNX_CSRC_OFFLINE_DOLPHIN_MODEL_H_