Official repository for "PAIR: Planning and Iterative Refinement in Pre-trained Transformers for Long Text Generation"

Related tags

Deep Learningpair-emnlp2020
Overview

pair-emnlp2020

Official repository for the paper:

Xinyu Hua and Lu Wang: PAIR: Planning and Iterative Refinement in Pre-trained Transformers for Long Text Generation

If you find our work useful, please cite:

@inproceedings{hua-wang-2020-pair,
    title = "PAIR: Planning and Iterative Refinement in Pre-trained Transformersfor Long Text Generation",
    author = "Hua, Xinyu  and
      Wang, Lu",
    booktitle = "Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing",
    month = nov,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
}

Requirements

  • Python 3.7
  • PyTorch 1.4.0
  • PyTorchLightning 0.9.0
  • transformers 3.3.0
  • numpy
  • tqdm
  • pycorenlp (for preprocessing nytimes data)
  • nltk (for preprocessing nytimes data)

Data

We release the data sets in the following link(1.2G uncompressed) Please download and uncompress the file, and put under ./data directory. For opinion and news domains, the The New York Times Annotated Corpus is licensed by LDC. We therefore only provide the ids for train/dev/test. Please follow the instructions to generate the dataset.

Text Planning

To train a BERT planner:

cd planning
python train.py \
    --data-path=../data/ \
    --domain=[arggen,opinion,news] \
    --exp-name=demo \
    --save-interval=1 \ # how frequent to save checkpoints 
    --max-epoch=30 \
    --lr=5e-4 \
    --warmup-updates=5000 \
    --train-set=train \
    --valid-set=dev \
    --tensorboard-logdir=tboard/ \
    --predict-keyphrase-offset \
    --max-samples=32 \ # max number of samples per batch
    [--quiet] \ # whether to print intermediate information

The checkpoints will be dumped to checkpoints/planning/[domain]/[exp-name]. Tensorboard will be available under planning/tboard/.

To run inference using a trained model, with greedy decoding:

cd planning
python decode.py \
    --data-path=../data/ \
    --domain=arggen \
    --test-set=test \
    --max-samples=32 \
    --predict-keyphrase-offset \
    --exp-name=demo \
    [--quiet]

The results will be saved to planning/output/.

Iterative Refinement

We provide implementations for four different setups:

  • Seq2seq: prompt -> tgt
  • KPSeq2seq: prompt + kp-set -> tgt
  • PAIR-light: prompt + kp-plan + masks -> tgt
  • PAIR-full: prompt + kp-plan + template -> tgt

To train a model:

cd refinement
python train.py \
    --domain=[arggen,opinion,news] \
    --setup=[seq2seq,kpseq2seq,pair-light,pair-full] \
    --train-set=train \
    --valid-set=dev \
    --train-batch-size=10 \
    --valid-batch-size=5 \
    --num-train-epochs=20 \
    --ckpt-dir=../checkpoints/[domain]/[setup]/demo \
    --tensorboard-dir=demo \
    [--quiet]

To run iterative refinement:

cd refinement
python generate.py \
    --domain=[arggen,opinion,news] \
    --setup=[seq2seq,kpseq2seq,pair-light,pair-full] \
    --test-set=test \
    --output-name=test_demo \
    --enforce-template-strategy=flexible \
    --do-sampling \
    --sampling-topk=100 \
    --sampling-topp=0.9 \
    --sample-times=3 \
    --ckpt-dir=../checkpoints/[domain]/[setup]/demo

Contact

Xinyu Hua (hua.x [at] northeastern.edu)

License

See the LICENSE file for details.

Owner
Xinyu Hua
PhD student at Northeastern University
Xinyu Hua
GitHub Repository
Eff video representation - Efficient video representation through neural fields

Neural Residual Flow Fields for Efficient Video Representations 1. Download MPI

41 Jan 06, 2023
Created as part of CS50 AI's coursework. This AI makes use of knowledge entailment to calculate the best probabilities to win Minesweeper.

Minesweeper-AI Created as part of CS50 AI's coursework. This AI makes use of knowledge entailment to calculate the best probabilities to win Minesweep

Beckham 0 Jul 20, 2022
Using machine learning to predict undergrad college admissions.

College-Prediction Project- Overview: Many have tried, many have failed. Few trailblazers are ambitious enought to chase acceptance into the top 15 un

John H Klinges 1 Jan 05, 2022
[CVPR 2022 Oral] EPro-PnP: Generalized End-to-End Probabilistic Perspective-n-Points for Monocular Object Pose Estimation

EPro-PnP EPro-PnP: Generalized End-to-End Probabilistic Perspective-n-Points for Monocular Object Pose Estimation In CVPR 2022 (Oral). [paper] Hanshen

同济大学智能汽车研究所综合感知研究组 ( Comprehensive Perception Research Group under Institute of Intelligent Vehicles, School of Automotive Studies, Tongji University) 842 Jan 04, 2023
A library built upon PyTorch for building embeddings on discrete event sequences using self-supervision

pytorch-lifestream a library built upon PyTorch for building embeddings on discrete event sequences using self-supervision. It can process terabyte-si

Dmitri Babaev 103 Dec 17, 2022
The MATH Dataset

Measuring Mathematical Problem Solving With the MATH Dataset This is the repository for Measuring Mathematical Problem Solving With the MATH Dataset b

Dan Hendrycks 267 Dec 26, 2022
Improving Non-autoregressive Generation with Mixup Training

MIST Training MIST TRAIN_FILE=/your/path/to/train.json VALID_FILE=/your/path/to/valid.json OUTPUT_DIR=/your/path/to/save_checkpoints CACHE_DIR=/your/p

7 Nov 22, 2022
FLSim a flexible, standalone library written in PyTorch that simulates FL settings with a minimal, easy-to-use API

Federated Learning Simulator (FLSim) is a flexible, standalone core library that simulates FL settings with a minimal, easy-to-use API. FLSim is domain-agnostic and accommodates many use cases such a

Meta Research 162 Jan 02, 2023
Orbivator AI - To Determine which features of data (measurements) are most important for diagnosing breast cancer and find out if breast cancer occurs or not.

Orbivator_AI Breast Cancer Wisconsin (Diagnostic) GOAL To Determine which features of data (measurements) are most important for diagnosing breast can

anurag kumar singh 1 Jan 02, 2022
Simple command line tool for text to image generation using OpenAI's CLIP and Siren (Implicit neural representation network)

Deep Daze mist over green hills shattered plates on the grass cosmic love and attention a time traveler in the crowd life during the plague meditative

Phil Wang 4.4k Jan 03, 2023
[CVPR 2022] Thin-Plate Spline Motion Model for Image Animation.

[CVPR2022] Thin-Plate Spline Motion Model for Image Animation Source code of the CVPR'2022 paper "Thin-Plate Spline Motion Model for Image Animation"

yoyo-nb 1.4k Dec 30, 2022
Anime Face Detector using mmdet and mmpose

Anime Face Detector This is an anime face detector using mmdetection and mmpose. (To avoid copyright issues, I use generated images by the TADNE model

198 Jan 07, 2023
Pytorch implementation of few-shot semantic image synthesis

Few-shot Semantic Image Synthesis Using StyleGAN Prior Our method can synthesize photorealistic images from dense or sparse semantic annotations using

40 Sep 26, 2022
Tightness-aware Evaluation Protocol for Scene Text Detection

TIoU-metric Release on 27/03/2019. This repository is built on the ICDAR 2015 evaluation code. If you propose a better metric and require further eval

Yuliang Liu 206 Nov 18, 2022
AsymmetricGAN - Dual Generator Generative Adversarial Networks for Multi-Domain Image-to-Image Translation

AsymmetricGAN for Image-to-Image Translation AsymmetricGAN Framework for Multi-Domain Image-to-Image Translation AsymmetricGAN Framework for Hand Gest

Hao Tang 42 Jan 15, 2022
A repository built on the Flow software package to explore cyber-security attacks on intelligent transportation systems.

A repository built on the Flow software package to explore cyber-security attacks on intelligent transportation systems.

George Gunter 4 Nov 14, 2022
Learning Dynamic Network Using a Reuse Gate Function in Semi-supervised Video Object Segmentation.

Training Script for Reuse-VOS This code implementation of CVPR 2021 paper : Learning Dynamic Network Using a Reuse Gate Function in Semi-supervised Vi

HYOJINPARK 22 Jan 01, 2023
RL agent to play μRTS with Stable-Baselines3

Gym-μRTS with Stable-Baselines3/PyTorch This repo contains an attempt to reproduce Gridnet PPO with invalid action masking algorithm to play μRTS usin

Oleksii Kachaiev 24 Nov 11, 2022
For holding anime-related object classification and detection models

Animesion An end-to-end framework for anime-related object classification, detection, segmentation, and other models. Update: 01/22/2020. Due to time-

Edwin Arkel Rios 72 Nov 30, 2022
The first public PyTorch implementation of Attentive Recurrent Comparators

arc-pytorch PyTorch implementation of Attentive Recurrent Comparators by Shyam et al. A blog explaining Attentive Recurrent Comparators Visualizing At

Sanyam Agarwal 150 Oct 14, 2022