f835642b1c
Adds support for Zipformer transducer ASR models that use Whisper-style features by introducing a new feature flag, parsing metadata, and integrating per-chunk normalization. - Introduce UseWhisperFeature in the model interface and Zipformer implementation - Parse "feature" metadata to set the whisper flag and wire it into the recognizer - Update feature extraction logic to handle Whisper filterbanks with early returns
117 lines
3.7 KiB
C++
117 lines
3.7 KiB
C++
// sherpa-onnx/csrc/online-zipformer2-transducer-model.h
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//
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// Copyright (c) 2023 Xiaomi Corporation
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#ifndef SHERPA_ONNX_CSRC_ONLINE_ZIPFORMER2_TRANSDUCER_MODEL_H_
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#define SHERPA_ONNX_CSRC_ONLINE_ZIPFORMER2_TRANSDUCER_MODEL_H_
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#include <memory>
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#include <string>
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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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#include "sherpa-onnx/csrc/online-transducer-model.h"
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namespace sherpa_onnx {
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class OnlineZipformer2TransducerModel : public OnlineTransducerModel {
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public:
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explicit OnlineZipformer2TransducerModel(const OnlineModelConfig &config);
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template <typename Manager>
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OnlineZipformer2TransducerModel(Manager *mgr,
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const OnlineModelConfig &config);
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std::vector<Ort::Value> StackStates(
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const std::vector<std::vector<Ort::Value>> &states) const override;
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std::vector<std::vector<Ort::Value>> UnStackStates(
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const std::vector<Ort::Value> &states) const override;
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std::vector<Ort::Value> GetEncoderInitStates() override;
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void SetFeatureDim(int32_t feature_dim) override {
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feature_dim_ = feature_dim;
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}
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std::pair<Ort::Value, std::vector<Ort::Value>> RunEncoder(
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Ort::Value features, std::vector<Ort::Value> states,
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Ort::Value processed_frames) override;
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Ort::Value RunDecoder(Ort::Value decoder_input) override;
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Ort::Value RunJoiner(Ort::Value encoder_out, Ort::Value decoder_out) override;
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int32_t ContextSize() const override { return context_size_; }
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int32_t ChunkSize() const override { return T_; }
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int32_t ChunkShift() const override { return decode_chunk_len_; }
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int32_t VocabSize() const override { return vocab_size_; }
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OrtAllocator *Allocator() override { return allocator_; }
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bool UseWhisperFeature() const override { return use_whisper_feature_; }
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private:
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void InitEncoder(void *model_data, size_t model_data_length);
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void InitDecoder(void *model_data, size_t model_data_length);
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void InitJoiner(void *model_data, size_t model_data_length);
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private:
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Ort::Env env_;
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Ort::SessionOptions encoder_sess_opts_;
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Ort::SessionOptions decoder_sess_opts_;
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Ort::SessionOptions joiner_sess_opts_;
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Ort::AllocatorWithDefaultOptions allocator_;
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std::unique_ptr<Ort::Session> encoder_sess_;
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std::unique_ptr<Ort::Session> decoder_sess_;
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std::unique_ptr<Ort::Session> joiner_sess_;
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std::vector<std::string> encoder_input_names_;
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std::vector<const char *> encoder_input_names_ptr_;
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std::vector<std::string> encoder_output_names_;
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std::vector<const char *> encoder_output_names_ptr_;
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std::vector<std::string> decoder_input_names_;
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std::vector<const char *> decoder_input_names_ptr_;
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std::vector<std::string> decoder_output_names_;
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std::vector<const char *> decoder_output_names_ptr_;
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std::vector<std::string> joiner_input_names_;
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std::vector<const char *> joiner_input_names_ptr_;
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std::vector<std::string> joiner_output_names_;
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std::vector<const char *> joiner_output_names_ptr_;
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OnlineModelConfig config_;
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std::vector<int32_t> encoder_dims_;
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std::vector<int32_t> query_head_dims_;
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std::vector<int32_t> value_head_dims_;
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std::vector<int32_t> num_heads_;
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std::vector<int32_t> num_encoder_layers_;
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std::vector<int32_t> cnn_module_kernels_;
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std::vector<int32_t> left_context_len_;
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int32_t T_ = 0;
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int32_t decode_chunk_len_ = 0;
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int32_t context_size_ = 0;
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int32_t vocab_size_ = 0;
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int32_t feature_dim_ = 80;
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// for models from
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// https://github.com/k2-fsa/icefall/blob/master/egs/multi_zh-hans/ASR/RESULTS.md#streaming-with-ctc-head
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bool use_whisper_feature_ = false;
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};
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} // namespace sherpa_onnx
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#endif // SHERPA_ONNX_CSRC_ONLINE_ZIPFORMER2_TRANSDUCER_MODEL_H_
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