f0960342ad
This PR integrates LODR (Level-Ordered Deterministic Rescoring) support from Icefall into both online and offline recognizers, enabling LODR for LM shallow fusion and LM rescore. - Extended OnlineLMConfig and OfflineLMConfig to include lodr_fst, lodr_scale, and lodr_backoff_id. - Implemented LodrFst and LodrStateCost classes and wired them into RNN LM scoring in both online and offline code paths. - Updated Python bindings, CLI entry points, examples, and CI test scripts to accept and exercise the new LODR options.
109 lines
3.0 KiB
C++
109 lines
3.0 KiB
C++
// sherpa-onnx/csrc/offline-rnn-lm.cc
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//
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// Copyright (c) 2023 Xiaomi Corporation
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#include "sherpa-onnx/csrc/offline-rnn-lm.h"
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#include <string>
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#include <utility>
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#include <vector>
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#if __ANDROID_API__ >= 9
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#include "android/asset_manager.h"
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#include "android/asset_manager_jni.h"
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#endif
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#if __OHOS__
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#include "rawfile/raw_file_manager.h"
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#endif
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#include "onnxruntime_cxx_api.h" // NOLINT
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#include "sherpa-onnx/csrc/file-utils.h"
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#include "sherpa-onnx/csrc/macros.h"
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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 OfflineRnnLM::Impl {
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public:
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explicit Impl(const OfflineLMConfig &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_.model);
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Init(buf.data(), buf.size());
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}
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template <typename Manager>
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Impl(Manager *mgr, const OfflineLMConfig &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_.model);
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Init(buf.data(), buf.size());
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}
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Ort::Value Rescore(Ort::Value x, Ort::Value x_lens) {
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std::array<Ort::Value, 2> inputs = {std::move(x), std::move(x_lens)};
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auto out =
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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(out[0]);
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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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}
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private:
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OfflineLMConfig 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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};
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OfflineRnnLM::OfflineRnnLM(const OfflineLMConfig &config)
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: impl_(std::make_unique<Impl>(config)), OfflineLM(config) {}
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template <typename Manager>
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OfflineRnnLM::OfflineRnnLM(Manager *mgr, const OfflineLMConfig &config)
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: impl_(std::make_unique<Impl>(mgr, config)), OfflineLM(config) {}
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OfflineRnnLM::~OfflineRnnLM() = default;
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Ort::Value OfflineRnnLM::Rescore(Ort::Value x, Ort::Value x_lens) {
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return impl_->Rescore(std::move(x), std::move(x_lens));
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}
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#if __ANDROID_API__ >= 9
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template OfflineRnnLM::OfflineRnnLM(AAssetManager *mgr,
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const OfflineLMConfig &config);
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#endif
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#if __OHOS__
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template OfflineRnnLM::OfflineRnnLM(NativeResourceManager *mgr,
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const OfflineLMConfig &config);
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#endif
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} // namespace sherpa_onnx
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