87 lines
2.6 KiB
C++
87 lines
2.6 KiB
C++
// sherpa-onnx/csrc/online-ctc-model.h
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//
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// Copyright (c) 2023 Xiaomi Corporation
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#ifndef SHERPA_ONNX_CSRC_ONLINE_CTC_MODEL_H_
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#define SHERPA_ONNX_CSRC_ONLINE_CTC_MODEL_H_
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#include <memory>
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#include <utility>
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#include <vector>
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#include "onnxruntime_cxx_api.h" // NOLINT
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#include "sherpa-onnx/csrc/online-model-config.h"
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namespace sherpa_onnx {
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class OnlineCtcModel {
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public:
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virtual ~OnlineCtcModel() = default;
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static std::unique_ptr<OnlineCtcModel> Create(
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const OnlineModelConfig &config);
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template <typename Manager>
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static std::unique_ptr<OnlineCtcModel> Create(
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Manager *mgr, const OnlineModelConfig &config);
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// Return a list of tensors containing the initial states
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virtual std::vector<Ort::Value> GetInitStates() const = 0;
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/** Stack a list of individual states into a batch.
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*
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* It is the inverse operation of `UnStackStates`.
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*
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* @param states states[i] contains the state for the i-th utterance.
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* @return Return a single value representing the batched state.
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*/
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virtual std::vector<Ort::Value> StackStates(
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std::vector<std::vector<Ort::Value>> states) const = 0;
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/** Unstack a batch state into a list of individual states.
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*
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* It is the inverse operation of `StackStates`.
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*
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* @param states A batched state.
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* @return ans[i] contains the state for the i-th utterance.
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*/
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virtual std::vector<std::vector<Ort::Value>> UnStackStates(
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std::vector<Ort::Value> states) const = 0;
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/**
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*
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* @param x A 3-D tensor of shape (N, T, C). N has to be 1.
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* @param states It is from GetInitStates() or returned from this method.
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*
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* @return Return a list of tensors
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* - ans[0] contains log_probs, of shape (N, T, C)
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* - ans[1:] contains next_states
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*/
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virtual std::vector<Ort::Value> Forward(
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Ort::Value x, std::vector<Ort::Value> states) const = 0;
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/** Return the vocabulary size of the model
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*/
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virtual int32_t VocabSize() const = 0;
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/** Return an allocator for allocating memory
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*/
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virtual OrtAllocator *Allocator() const = 0;
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// The model accepts this number of frames before subsampling as input
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virtual int32_t ChunkLength() const = 0;
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// Similar to frame_shift in feature extractor, after processing
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// ChunkLength() frames, we advance by ChunkShift() frames
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// before we process the next chunk.
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virtual int32_t ChunkShift() const = 0;
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// Return true if the model supports batch size > 1
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virtual bool SupportBatchProcessing() const { return true; }
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virtual bool UseWhisperFeature() const { return false; }
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};
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} // namespace sherpa_onnx
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#endif // SHERPA_ONNX_CSRC_ONLINE_CTC_MODEL_H_
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