| 188 | } |
| 189 | |
| 190 | const std::pair<float, float> FeedForwardNet::TrainOnBatch(int epoch, |
| 191 | const Tensor& x, |
| 192 | const Tensor& y) { |
| 193 | int flag = kTrain; |
| 194 | const Tensor fea = Forward(flag, x); |
| 195 | float loss = loss_->Evaluate(flag, fea, y); |
| 196 | float metric = metric_->Evaluate(fea, y); |
| 197 | const Tensor grad = loss_->Backward(); |
| 198 | auto grads = Backward(kTrain, grad / static_cast<float>(x.shape(0))); |
| 199 | auto names = GetParamNames(); |
| 200 | auto values = GetParamValues(); |
| 201 | for (size_t k = 0; k < grads.size(); k++) { |
| 202 | updater_->Apply(epoch, names[k], grads[k], values.at(k)); |
| 203 | } |
| 204 | return std::make_pair(loss, metric); |
| 205 | } |
| 206 | |
| 207 | const Tensor FeedForwardNet::Forward(int flag, const Tensor& data) { |
| 208 | Tensor input = data, output; |