107 lines
3.1 KiB
C++
107 lines
3.1 KiB
C++
// sherpa-onnx/csrc/offline-tdnn-ctc-model.cc
|
|
//
|
|
// Copyright (c) 2023 Xiaomi Corporation
|
|
|
|
#include "sherpa-onnx/csrc/offline-tdnn-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 OfflineTdnnCtcModel::Impl {
|
|
public:
|
|
explicit Impl(const OfflineModelConfig &config)
|
|
: config_(config),
|
|
env_(ORT_LOGGING_LEVEL_ERROR),
|
|
sess_opts_(GetSessionOptions(config)),
|
|
allocator_{} {
|
|
Init();
|
|
}
|
|
|
|
std::pair<Ort::Value, Ort::Value> Forward(Ort::Value features) {
|
|
auto nnet_out =
|
|
sess_->Run({}, input_names_ptr_.data(), &features, 1,
|
|
output_names_ptr_.data(), output_names_ptr_.size());
|
|
|
|
std::vector<int64_t> nnet_out_shape =
|
|
nnet_out[0].GetTensorTypeAndShapeInfo().GetShape();
|
|
|
|
std::vector<int64_t> out_length_vec(nnet_out_shape[0], nnet_out_shape[1]);
|
|
std::vector<int64_t> out_length_shape(1, nnet_out_shape[0]);
|
|
|
|
auto memory_info =
|
|
Ort::MemoryInfo::CreateCpu(OrtDeviceAllocator, OrtMemTypeDefault);
|
|
|
|
Ort::Value nnet_out_length = Ort::Value::CreateTensor(
|
|
memory_info, out_length_vec.data(), out_length_vec.size(),
|
|
out_length_shape.data(), out_length_shape.size());
|
|
|
|
return {std::move(nnet_out[0]), Clone(Allocator(), &nnet_out_length)};
|
|
}
|
|
|
|
int32_t VocabSize() const { return vocab_size_; }
|
|
|
|
OrtAllocator *Allocator() const { return allocator_; }
|
|
|
|
private:
|
|
void Init() {
|
|
auto buf = ReadFile(config_.tdnn.model);
|
|
|
|
sess_ = std::make_unique<Ort::Session>(env_, buf.data(), buf.size(),
|
|
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());
|
|
}
|
|
|
|
Ort::AllocatorWithDefaultOptions allocator; // used in the macro below
|
|
SHERPA_ONNX_READ_META_DATA(vocab_size_, "vocab_size");
|
|
}
|
|
|
|
private:
|
|
OfflineModelConfig config_;
|
|
Ort::Env env_;
|
|
Ort::SessionOptions sess_opts_;
|
|
Ort::AllocatorWithDefaultOptions allocator_;
|
|
|
|
std::unique_ptr<Ort::Session> sess_;
|
|
|
|
std::vector<std::string> input_names_;
|
|
std::vector<const char *> input_names_ptr_;
|
|
|
|
std::vector<std::string> output_names_;
|
|
std::vector<const char *> output_names_ptr_;
|
|
|
|
int32_t vocab_size_ = 0;
|
|
};
|
|
|
|
OfflineTdnnCtcModel::OfflineTdnnCtcModel(const OfflineModelConfig &config)
|
|
: impl_(std::make_unique<Impl>(config)) {}
|
|
|
|
OfflineTdnnCtcModel::~OfflineTdnnCtcModel() = default;
|
|
|
|
std::pair<Ort::Value, Ort::Value> OfflineTdnnCtcModel::Forward(
|
|
Ort::Value features, Ort::Value /*features_length*/) {
|
|
return impl_->Forward(std::move(features));
|
|
}
|
|
|
|
int32_t OfflineTdnnCtcModel::VocabSize() const { return impl_->VocabSize(); }
|
|
|
|
OrtAllocator *OfflineTdnnCtcModel::Allocator() const {
|
|
return impl_->Allocator();
|
|
}
|
|
|
|
} // namespace sherpa_onnx
|