// sherpa-onnx/csrc/offline-telespeech-ctc-model.cc // // Copyright (c) 2023-2024 Xiaomi Corporation #include "sherpa-onnx/csrc/offline-telespeech-ctc-model.h" #include "sherpa-onnx/csrc/macros.h" #include "sherpa-onnx/csrc/onnx-utils.h" #include "sherpa-onnx/csrc/session.h" #include "sherpa-onnx/csrc/text-utils.h" #include "sherpa-onnx/csrc/transpose.h" namespace sherpa_onnx { class OfflineTeleSpeechCtcModel::Impl { public: explicit Impl(const OfflineModelConfig &config) : config_(config), env_(ORT_LOGGING_LEVEL_ERROR), sess_opts_(GetSessionOptions(config)), allocator_{} { auto buf = ReadFile(config_.telespeech_ctc); Init(buf.data(), buf.size()); } #if __ANDROID_API__ >= 9 Impl(AAssetManager *mgr, const OfflineModelConfig &config) : config_(config), env_(ORT_LOGGING_LEVEL_ERROR), sess_opts_(GetSessionOptions(config)), allocator_{} { auto buf = ReadFile(mgr, config_.telespeech_ctc); Init(buf.data(), buf.size()); } #endif std::vector Forward(Ort::Value features, Ort::Value /*features_length*/) { std::vector shape = features.GetTensorTypeAndShapeInfo().GetShape(); if (static_cast(shape[0]) != 1) { SHERPA_ONNX_LOGE("This model supports only batch size 1. Given %d", static_cast(shape[0])); } auto out = sess_->Run({}, input_names_ptr_.data(), &features, 1, output_names_ptr_.data(), output_names_ptr_.size()); std::vector logits_shape = {1}; Ort::Value logits_length = Ort::Value::CreateTensor( allocator_, logits_shape.data(), logits_shape.size()); int64_t *dst = logits_length.GetTensorMutableData(); dst[0] = out[0].GetTensorTypeAndShapeInfo().GetShape()[0]; // (T, B, C) -> (B, T, C) Ort::Value logits = Transpose01(allocator_, &out[0]); std::vector ans; ans.reserve(2); ans.push_back(std::move(logits)); ans.push_back(std::move(logits_length)); return ans; } int32_t VocabSize() const { return vocab_size_; } int32_t SubsamplingFactor() const { return subsampling_factor_; } OrtAllocator *Allocator() const { return allocator_; } private: void Init(void *model_data, size_t model_data_length) { sess_ = std::make_unique(env_, model_data, model_data_length, sess_opts_); GetInputNames(sess_.get(), &input_names_, &input_names_ptr_); GetOutputNames(sess_.get(), &output_names_, &output_names_ptr_); // get meta data Ort::ModelMetadata meta_data = sess_->GetModelMetadata(); if (config_.debug) { std::ostringstream os; PrintModelMetadata(os, meta_data); SHERPA_ONNX_LOGE("%s\n", os.str().c_str()); } { auto shape = sess_->GetOutputTypeInfo(0).GetTensorTypeAndShapeInfo().GetShape(); vocab_size_ = shape[2]; } } private: OfflineModelConfig config_; Ort::Env env_; Ort::SessionOptions sess_opts_; Ort::AllocatorWithDefaultOptions allocator_; std::unique_ptr sess_; std::vector input_names_; std::vector input_names_ptr_; std::vector output_names_; std::vector output_names_ptr_; int32_t vocab_size_ = 0; int32_t subsampling_factor_ = 4; }; OfflineTeleSpeechCtcModel::OfflineTeleSpeechCtcModel( const OfflineModelConfig &config) : impl_(std::make_unique(config)) {} #if __ANDROID_API__ >= 9 OfflineTeleSpeechCtcModel::OfflineTeleSpeechCtcModel( AAssetManager *mgr, const OfflineModelConfig &config) : impl_(std::make_unique(mgr, config)) {} #endif OfflineTeleSpeechCtcModel::~OfflineTeleSpeechCtcModel() = default; std::vector OfflineTeleSpeechCtcModel::Forward( Ort::Value features, Ort::Value features_length) { return impl_->Forward(std::move(features), std::move(features_length)); } int32_t OfflineTeleSpeechCtcModel::VocabSize() const { return impl_->VocabSize(); } int32_t OfflineTeleSpeechCtcModel::SubsamplingFactor() const { return impl_->SubsamplingFactor(); } OrtAllocator *OfflineTeleSpeechCtcModel::Allocator() const { return impl_->Allocator(); } } // namespace sherpa_onnx