FastText

fasttext.cc

void Model::computeHidden(const std::vector<int32_t>& input, Vector& hidden) const {
  assert(hidden.size() == hsz_);
  hidden.zero();
  for (auto it = input.cbegin(); it != input.cend(); ++it) {
    if(quant_) {
      hidden.addRow(*qwi_, *it);
    } else {
      hidden.addRow(*wi_, *it);
    }
  }
  hidden.mul(1.0 / input.size());
}

void Model::update(const std::vector<int32_t>& input, int32_t target, real lr) {
  assert(target >= 0);
  assert(target < osz_);
  if (input.size() == 0) return;
  computeHidden(input, hidden_);
  if (args_->loss == loss_name::ns) {
    loss_ += negativeSampling(target, lr);
  } else if (args_->loss == loss_name::hs) {
    loss_ += hierarchicalSoftmax(target, lr);
  } else {
    loss_ += softmax(target, lr);
  }
  nexamples_ += 1;

  if (args_->model == model_name::sup) {
    grad_.mul(1.0 / input.size());
  }
  for (auto it = input.cbegin(); it != input.cend(); ++it) {
    wi_->addRow(grad_, *it, 1.0);
  }
}