145 lines
4.3 KiB
C++
145 lines
4.3 KiB
C++
// sherpa-onnx/csrc/offline-telespeech-ctc-model.cc
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//
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// Copyright (c) 2023-2024 Xiaomi Corporation
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#include "sherpa-onnx/csrc/offline-telespeech-ctc-model.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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#include "sherpa-onnx/csrc/transpose.h"
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namespace sherpa_onnx {
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class OfflineTeleSpeechCtcModel::Impl {
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public:
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explicit Impl(const OfflineModelConfig &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_.telespeech_ctc);
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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 OfflineModelConfig &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_.telespeech_ctc);
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Init(buf.data(), buf.size());
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}
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#endif
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std::vector<Ort::Value> Forward(Ort::Value features,
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Ort::Value /*features_length*/) {
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std::vector<int64_t> shape =
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features.GetTensorTypeAndShapeInfo().GetShape();
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if (static_cast<int32_t>(shape[0]) != 1) {
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SHERPA_ONNX_LOGE("This model supports only batch size 1. Given %d",
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static_cast<int32_t>(shape[0]));
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}
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auto out = sess_->Run({}, input_names_ptr_.data(), &features, 1,
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output_names_ptr_.data(), output_names_ptr_.size());
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std::vector<int64_t> logits_shape = {1};
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Ort::Value logits_length = Ort::Value::CreateTensor<int64_t>(
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allocator_, logits_shape.data(), logits_shape.size());
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int64_t *dst = logits_length.GetTensorMutableData<int64_t>();
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dst[0] = out[0].GetTensorTypeAndShapeInfo().GetShape()[0];
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// (T, B, C) -> (B, T, C)
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Ort::Value logits = Transpose01(allocator_, &out[0]);
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std::vector<Ort::Value> ans;
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ans.reserve(2);
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ans.push_back(std::move(logits));
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ans.push_back(std::move(logits_length));
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return ans;
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}
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int32_t VocabSize() const { return vocab_size_; }
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int32_t SubsamplingFactor() const { return subsampling_factor_; }
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OrtAllocator *Allocator() const { return allocator_; }
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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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if (config_.debug) {
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std::ostringstream os;
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PrintModelMetadata(os, meta_data);
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SHERPA_ONNX_LOGE("%s\n", os.str().c_str());
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}
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{
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auto shape =
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sess_->GetOutputTypeInfo(0).GetTensorTypeAndShapeInfo().GetShape();
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vocab_size_ = shape[2];
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}
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}
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private:
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OfflineModelConfig 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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int32_t vocab_size_ = 0;
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int32_t subsampling_factor_ = 4;
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};
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OfflineTeleSpeechCtcModel::OfflineTeleSpeechCtcModel(
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const OfflineModelConfig &config)
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: impl_(std::make_unique<Impl>(config)) {}
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#if __ANDROID_API__ >= 9
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OfflineTeleSpeechCtcModel::OfflineTeleSpeechCtcModel(
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AAssetManager *mgr, const OfflineModelConfig &config)
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: impl_(std::make_unique<Impl>(mgr, config)) {}
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#endif
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OfflineTeleSpeechCtcModel::~OfflineTeleSpeechCtcModel() = default;
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std::vector<Ort::Value> OfflineTeleSpeechCtcModel::Forward(
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Ort::Value features, Ort::Value features_length) {
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return impl_->Forward(std::move(features), std::move(features_length));
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}
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int32_t OfflineTeleSpeechCtcModel::VocabSize() const {
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return impl_->VocabSize();
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}
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int32_t OfflineTeleSpeechCtcModel::SubsamplingFactor() const {
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return impl_->SubsamplingFactor();
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}
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OrtAllocator *OfflineTeleSpeechCtcModel::Allocator() const {
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return impl_->Allocator();
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}
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} // namespace sherpa_onnx
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