void TranslationModel::loadBackend()

in inference/src/translator/translation_model.cpp [56:104]

• 41 lines of code
• 7 McCabe index (conditional complexity)

void TranslationModel::loadBackend(size_t idx) {
  auto &graph = backend_[idx].graph;
  auto &scorerEnsemble = backend_[idx].scorerEnsemble;

  marian::DeviceId device_(idx, DeviceType::cpu);
  graph = New<ExpressionGraph>(/*inference=*/true);  // set the graph to be inference only
  auto prec = options_->get<std::vector<std::string>>("precision", {"float32"});
  graph->setDefaultElementType(typeFromString(prec[0]));
  graph->setDevice(device_);
  graph->getBackend()->configureDevice(options_);
  graph->reserveWorkspaceMB(5);

  // if memory_.models is populated, then all models were of binary format
  if (memory_.models.size() >= 1) {
    const std::vector<const void *> container = std::invoke([&]() {
      std::vector<const void *> model_ptrs(memory_.models.size());
      for (size_t i = 0; i < memory_.models.size(); ++i) {
        const AlignedMemory &model = memory_.models[i];

        ABORT_IF(model.size() == 0 || model.begin() == nullptr, "The provided memory is empty. Cannot load the model.");
        ABORT_IF(
            (uintptr_t)model.begin() % 256 != 0,
            "The provided memory is not aligned to 256 bytes and will crash when vector instructions are used on it.");
        if (options_->get<bool>("check-bytearray", false)) {
          ABORT_IF(!validateBinaryModel(model, model.size()),
                   "The binary file is invalid. Incomplete or corrupted download?");
        }

        model_ptrs[i] = model.begin();
        LOG(debug, "Loaded model {} of {} from memory", (i + 1), model_ptrs.size());
      }
      return model_ptrs;
    });

    scorerEnsemble = createScorers(options_, container);
  } else {
    // load npz format models, or a mixture of binary/npz formats
    scorerEnsemble = createScorers(options_);
    LOG(debug, "Loaded {} model(s) from file", scorerEnsemble.size());
  }

  for (auto scorer : scorerEnsemble) {
    scorer->init(graph);
    if (shortlistGenerator_) {
      scorer->setShortlistGenerator(shortlistGenerator_);
    }
  }
  graph->forward();
}