Positional Encoding to Control Output Sequence Length
This repository contains source files we used in our paper
Sho Takase, Naoaki Okazaki
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
- Python 3.6 or later for training
- Python 2.7 for calculating rouge
- PyTorch 0.4
- To use new version PyTorch (e.g., 1.4.0), please use this code without one-emb option.
Test data used in our paper for each length
- Each file contains
SOURCE PART tab HEADLINE
The following file contains pre-trained LRPE + PE model in English dataset. This model outputs
@@@@ as a space, namely, a segmentation marker of words.
The file also contains BPE code to split a plane English text into BPE with this code.