Thanks to @Peakyxh for providing pre-built onnxruntime libraries with CUDA support for Linux aarch64. Tested on Jetson nano b01
139 lines
4.3 KiB
C++
139 lines
4.3 KiB
C++
// sherpa-onnx/csrc/online-cnn-bilstm-model.cc
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//
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// Copyright (c) 2024 Jian You (jianyou@cisco.com, Cisco Systems)
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#include "sherpa-onnx/csrc/online-cnn-bilstm-model.h"
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#include <string>
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#include <vector>
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#include "sherpa-onnx/csrc/onnx-utils.h"
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#include "sherpa-onnx/csrc/session.h"
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#include "sherpa-onnx/csrc/text-utils.h"
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namespace sherpa_onnx {
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class OnlineCNNBiLSTMModel::Impl {
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public:
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explicit Impl(const OnlinePunctuationModelConfig &config)
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: config_(config),
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env_(ORT_LOGGING_LEVEL_ERROR),
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sess_opts_(GetSessionOptions(config)),
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allocator_{} {
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auto buf = ReadFile(config_.cnn_bilstm);
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Init(buf.data(), buf.size());
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}
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#if __ANDROID_API__ >= 9
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Impl(AAssetManager *mgr, const OnlinePunctuationModelConfig &config)
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: config_(config),
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env_(ORT_LOGGING_LEVEL_ERROR),
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sess_opts_(GetSessionOptions(config)),
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allocator_{} {
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auto buf = ReadFile(mgr, config_.cnn_bilstm);
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Init(buf.data(), buf.size());
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}
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#endif
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std::pair<Ort::Value, Ort::Value> Forward(Ort::Value token_ids,
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Ort::Value valid_ids,
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Ort::Value label_lens) {
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std::array<Ort::Value, 3> inputs = {
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std::move(token_ids), std::move(valid_ids), std::move(label_lens)};
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auto ans =
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sess_->Run({}, input_names_ptr_.data(), inputs.data(), inputs.size(),
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output_names_ptr_.data(), output_names_ptr_.size());
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return {std::move(ans[0]), std::move(ans[1])};
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}
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OrtAllocator *Allocator() { return allocator_; }
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const OnlineCNNBiLSTMModelMetaData &GetModelMetadata() const {
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return meta_data_;
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}
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private:
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void Init(void *model_data, size_t model_data_length) {
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sess_ = std::make_unique<Ort::Session>(env_, model_data, model_data_length,
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sess_opts_);
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GetInputNames(sess_.get(), &input_names_, &input_names_ptr_);
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GetOutputNames(sess_.get(), &output_names_, &output_names_ptr_);
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// get meta data
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Ort::ModelMetadata meta_data = sess_->GetModelMetadata();
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Ort::AllocatorWithDefaultOptions allocator; // used in the macro below
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SHERPA_ONNX_READ_META_DATA(meta_data_.comma_id, "COMMA");
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SHERPA_ONNX_READ_META_DATA(meta_data_.period_id, "PERIOD");
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SHERPA_ONNX_READ_META_DATA(meta_data_.quest_id, "QUESTION");
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// assert here, because we will use the constant value
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assert(meta_data_.comma_id == 1);
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assert(meta_data_.period_id == 2);
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assert(meta_data_.quest_id == 3);
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SHERPA_ONNX_READ_META_DATA(meta_data_.upper_id, "UPPER");
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SHERPA_ONNX_READ_META_DATA(meta_data_.cap_id, "CAP");
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SHERPA_ONNX_READ_META_DATA(meta_data_.mix_case_id, "MIX_CASE");
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assert(meta_data_.upper_id == 1);
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assert(meta_data_.cap_id == 2);
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assert(meta_data_.mix_case_id == 3);
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// output shape is (T', num_cases)
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meta_data_.num_cases =
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sess_->GetOutputTypeInfo(0).GetTensorTypeAndShapeInfo().GetShape()[1];
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meta_data_.num_punctuations =
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sess_->GetOutputTypeInfo(1).GetTensorTypeAndShapeInfo().GetShape()[1];
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}
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private:
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OnlinePunctuationModelConfig config_;
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Ort::Env env_;
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Ort::SessionOptions sess_opts_;
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Ort::AllocatorWithDefaultOptions allocator_;
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std::unique_ptr<Ort::Session> sess_;
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std::vector<std::string> input_names_;
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std::vector<const char *> input_names_ptr_;
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std::vector<std::string> output_names_;
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std::vector<const char *> output_names_ptr_;
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OnlineCNNBiLSTMModelMetaData meta_data_;
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};
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OnlineCNNBiLSTMModel::OnlineCNNBiLSTMModel(
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const OnlinePunctuationModelConfig &config)
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: impl_(std::make_unique<Impl>(config)) {}
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#if __ANDROID_API__ >= 9
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OnlineCNNBiLSTMModel::OnlineCNNBiLSTMModel(
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AAssetManager *mgr, const OnlinePunctuationModelConfig &config)
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: impl_(std::make_unique<Impl>(mgr, config)) {}
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#endif
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OnlineCNNBiLSTMModel::~OnlineCNNBiLSTMModel() = default;
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std::pair<Ort::Value, Ort::Value> OnlineCNNBiLSTMModel::Forward(
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Ort::Value token_ids, Ort::Value valid_ids, Ort::Value label_lens) const {
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return impl_->Forward(std::move(token_ids), std::move(valid_ids),
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std::move(label_lens));
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}
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OrtAllocator *OnlineCNNBiLSTMModel::Allocator() const {
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return impl_->Allocator();
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}
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const OnlineCNNBiLSTMModelMetaData &OnlineCNNBiLSTMModel::GetModelMetadata()
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const {
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return impl_->GetModelMetadata();
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}
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} // namespace sherpa_onnx
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