https://github.com/jiesutd/text-attention-heatmap-visualization

Plot the vector graph of attention based text visualisation
https://github.com/jiesutd/text-attention-heatmap-visualization

attention-lstm attention-visualization heatmap text-heatmap text-visualisation vectogram vector-graphics

Last synced: about 21 hours ago
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Plot the vector graph of attention based text visualisation

• Host: GitHub
• URL: https://github.com/jiesutd/text-attention-heatmap-visualization
• Owner: jiesutd
• Created: 2019-04-01T17:09:27.000Z (almost 6 years ago)
• Default Branch: master
• Last Pushed: 2019-04-12T13:59:40.000Z (over 5 years ago)
• Last Synced: 2024-12-26T08:09:56.083Z (8 days ago)
• Topics: attention-lstm, attention-visualization, heatmap, text-heatmap, text-visualisation, vectogram, vector-graphics
• Language: Python
• Homepage:
• Size: 1.33 MB
• Stars: 370
• Watchers: 8
• Forks: 58
• Open Issues: 1
• Metadata Files:
  • Readme: README.md

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README

        
# TAHV：Text Attention Heatmap Visualization

This repository provides a simple visualization tool for the attention based NLP tasks. 

Many attention based NLP tasks visualize the text with attention weights as background. This code takes word list and the corresponding weights as input and generate the Latex code to visualize the attention based text. The Latex code will generates a standalone `.pdf` visulization file. Users can use this `.pdf` visulization file as vector diagram to demonstrate the attention ability of the model in their papers/slides/demos.

## Usage

It is very simple to use this code. Feed the word list and weight list in function `generate` with output Latex file directory and color configuration. The Latex file will be generated. Then compile the Latex file, the `.pdf` file will be generated.

* Notice the weight range: [0-100]

![alt text](red.png "Red demo")

![alt text](blue.png "Blue demo")

![alt text](CN.png "Chinese demo")

## Citation:   

This repository will be part of new [NCRF++](https://github.com/jiesutd/NCRFpp). Please cite our [ACL demo paper](https://arxiv.org/abs/1806.05626) if you use this code.

    @inproceedings{yang2018ncrf,  

     title={NCRF++: An Open-source Neural Sequence Labeling Toolkit},  

     author={Yang, Jie and Zhang, Yue},  

     booktitle={Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics},

     Url = {http://aclweb.org/anthology/P18-4013},

     year={2018}  

    }

## Update

* 2019-Apr-12, support Chinese

* 2019-Apr-01, init version