Skip to content
master
Go to file
Code

Latest commit

 

Git stats

Files

Permalink
Failed to load latest commit information.
Type
Name
Latest commit message
Commit time
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

README.md

GAN for Text Summarization

Tensorflow re-implementation of Generative Adversarial Network for Abstractive Text Summarization.

Requirements

  • Python3
  • Tensorflow >= 1.4 (tested on Tensorflow 1.4.1)
  • numpy
  • tqdm
  • sklearn
  • rouge
  • pyrouge

You can use the python package manager of your choice (pip/conda) to install the dependencies. The code is tested on Ubuntu 16.04 operating system.

Quickstart

  • Dataset

    Please follow the instructions here for downloading and preprocessing the CNN/DailyMail dataset. After that, store data files train.bin, val.bin, test.bin and vocabulary file vocab into specified data directory, e.g., ./data/.

  • Prepare negative samples for discriminator

    You can download the prepared data discriminator_train_data.npz for discriminator from dropbox and store into specified data directory, e.g., ./data/.

  • Train the full model

    python3 main.py --mode=train --data_path=./data/train.bin --vocab_path=./data/vocab --log_root=./log --pretrain_dis_data_path=./data/discriminator_train_data.npz --restore_best_model=False
    
  • Decode

    python3 main.py --mode=decode --data_path=./data/test.bin --vocab_path=./data/vocab --log_root=./log --single_pass=True
    

References

About

Tensorflow re-implementation of GAN for text summarization

Topics

Resources

Releases

No releases published

Packages

No packages published

Languages

You can’t perform that action at this time.