8648d437573e2e41b92b8fea13b4afe5e01851e8,baseline/tf/seq2seq/training/eager.py,Seq2SeqTrainerEagerTf,test,#Seq2SeqTrainerEagerTf#Any#Any#Any#Any#,157

Before Change

            features["dst"] = tgt[:, :-1]
            top_preds = self.model.predict(features, beam=1)
            loss_value = loss(self.model, features, tgt).numpy()
            toks = self._num_toks(features["tgt_len"])
            total_loss += loss_value * toks
            total_toks += toks
            preds.extend(convert_seq2seq_preds(top_preds[:, 0, :], self.tgt_rlut))
            golds.extend(convert_seq2seq_golds(tgt, features["tgt_len"], self.tgt_rlut))

After Change

            features["dst"] = tgt[:, :-1]
            top_preds = self.model.predict(features, beam=1)
            loss_value = loss(self.model, features, tgt).numpy()
            toks = tf.cast(self._num_toks(features["tgt_len"]), tf.float32).numpy()
            total_loss += loss_value * toks
            total_toks += toks
            preds.extend(convert_seq2seq_preds(top_preds[:, 0, :], self.tgt_rlut))
            golds.extend(convert_seq2seq_golds(tgt, features["tgt_len"], self.tgt_rlut))

Instances