Add C++ and Python API for Dolphin CTC models (#2085)
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sherpa-onnx/csrc/offline-dolphin-model.h
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67
sherpa-onnx/csrc/offline-dolphin-model.h
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// sherpa-onnx/csrc/offline-dolphin-model.h
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//
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// Copyright (c) 2025 Xiaomi Corporation
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#ifndef SHERPA_ONNX_CSRC_OFFLINE_DOLPHIN_MODEL_H_
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#define SHERPA_ONNX_CSRC_OFFLINE_DOLPHIN_MODEL_H_
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#include <memory>
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#include <vector>
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#include "onnxruntime_cxx_api.h" // NOLINT
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#include "sherpa-onnx/csrc/offline-ctc-model.h"
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#include "sherpa-onnx/csrc/offline-dolphin-model-meta-data.h"
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#include "sherpa-onnx/csrc/offline-model-config.h"
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namespace sherpa_onnx {
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class OfflineDolphinModel : public OfflineCtcModel {
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public:
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explicit OfflineDolphinModel(const OfflineModelConfig &config);
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template <typename Manager>
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OfflineDolphinModel(Manager *mgr, const OfflineModelConfig &config);
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~OfflineDolphinModel() override;
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/** Run the forward method of the model.
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*
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* @param features A tensor of shape (N, T, C).
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* @param features_length A 1-D tensor of shape (N,) containing number of
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* valid frames in `features` before padding.
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* Its dtype is int64_t.
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*
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* @return Return a vector containing:
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* - log_probs: A 3-D tensor of shape (N, T', vocab_size).
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* - log_probs_length A 1-D tensor of shape (N,). Its dtype is int64_t
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*/
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std::vector<Ort::Value> Forward(Ort::Value features,
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Ort::Value features_length) override;
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/** Return the vocabulary size of the model
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*/
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int32_t VocabSize() const override;
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/** SubsamplingFactor of the model
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*
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* For Citrinet, the subsampling factor is usually 4.
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* For Conformer CTC, the subsampling factor is usually 8.
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*/
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int32_t SubsamplingFactor() const override;
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/** Return an allocator for allocating memory
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*/
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OrtAllocator *Allocator() const override;
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bool SupportBatchProcessing() const override { return true; }
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void NormalizeFeatures(float *features, int32_t num_frames,
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int32_t feat_dim) const override;
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private:
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class Impl;
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std::unique_ptr<Impl> impl_;
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};
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} // namespace sherpa_onnx
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#endif // SHERPA_ONNX_CSRC_OFFLINE_DOLPHIN_MODEL_H_
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