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