(self, dy_model, metrics_list, batch_data, config)
| 84 | |
| 85 | # construct train forward phase |
| 86 | def train_forward(self, dy_model, metrics_list, batch_data, config): |
| 87 | sparse_tensor, label_ctr, label_ctcvr = self.create_feeds(batch_data, |
| 88 | config) |
| 89 | |
| 90 | ctr_out, ctr_out_one, cvr_out, cvr_out_one, ctcvr_prop, ctcvr_prop_one = dy_model.forward( |
| 91 | sparse_tensor) |
| 92 | loss = self.create_loss(ctr_out_one, label_ctr, ctcvr_prop_one, |
| 93 | label_ctcvr) |
| 94 | # update metrics |
| 95 | metrics_list[0].update(preds=ctr_out.numpy(), labels=label_ctr.numpy()) |
| 96 | metrics_list[1].update( |
| 97 | preds=ctcvr_prop.numpy(), labels=label_ctcvr.numpy()) |
| 98 | |
| 99 | # print_dict format :{'loss': loss} |
| 100 | print_dict = {'loss': loss} |
| 101 | return loss, metrics_list, print_dict |
| 102 | |
| 103 | def infer_forward(self, dy_model, metrics_list, batch_data, config): |
| 104 | sparse_tensor, label_ctr, label_ctcvr = self.create_feeds(batch_data, |
nothing calls this directly
no test coverage detected