Pytorch implementation of Integrating Tree Path in Transformer for Code Representation

Related tags

Deep LearningTPTrans
Overview

This is an official Pytorch implementation of the approaches proposed in:

Han Peng, Ge Li, Wenhan Wang, Yunfei Zhao, Zhi Jin “Integrating Tree Path in Transformer for Code Representation”

which appeared at NeurIPS 2021[Paper Link][Poster][Slides].

In this paper, we investigate the interaction between the absolute and relative path encoding, and propose novel code representation model TPTrans and its variants, which introduce path encoding inductive bias into the attention module of Transformer and power Transformer to know the structure of source codes.

Please cite our paper if you use the model, experimental results, or our code in your own work.

1.1 Raw data

To run experiments with TPTrans and its variants, please first create datasets from raw code snippets of CodeSearchNet dataset. Download and unzip the raw jsonl data of CSN into the raw_data dir like that

├── raw_data        
│   ├── python         
│   │   ├── train    
│   │   │   ├── XXXX.jsonl...
│   │   ├── test    
│   │   ├── valid   
│   ├── ruby          
│   ├── go        
│   ├── javascript        

1.2 Tree-Sitter

The Tree-Sitter is a open-source parser for multi-language programming languages. Please install it and then download the grammer files into vendor dir for four different programming languages like that

├── vendor        
│   ├── tree-sitter-python  (from https://github.com/tree-sitter/tree-sitter-python)         
│   ├── tree-sitter-javascript  (from https://github.com/tree-sitter/tree-sitter-javascript)     
│   ├── tree-sitter-go  (from https://github.com/tree-sitter/tree-sitter-go)
│   ├── tree-sitter-ruby  (from https://github.com/tree-sitter/tree-sitter-ruby)

After that, run the multi_language_parse.py in parser dir to parse the raw code snippets into the data dir.

1.3 Training

After preprocessing, run the _main.py_ to train the model.

To run the TPTrans, please specify the relation_path=True and absolute_path=False.

To run the TPTrans-\alpha, please specify the relation_path=True and absolute_path=True.

For other command triggers, please refer the comment inline for details.

Contact If you have any questions, please contact me via email: [email protected] or open issue on Github.

Owner
Han Peng
Han Peng
BridgeGAN - Tensorflow implementation of Bridging the Gap between Label- and Reference-based Synthesis in Multi-attribute Image-to-Image Translation.

Bridging the Gap between Label- and Reference based Synthesis(ICCV 2021) Tensorflow implementation of Bridging the Gap between Label- and Reference-ba

huangqiusheng 8 Jul 13, 2022
data/code repository of "C2F-FWN: Coarse-to-Fine Flow Warping Network for Spatial-Temporal Consistent Motion Transfer"

C2F-FWN data/code repository of "C2F-FWN: Coarse-to-Fine Flow Warping Network for Spatial-Temporal Consistent Motion Transfer" (https://arxiv.org/abs/

EKILI 46 Dec 14, 2022
PyTorch implementation of Deep HDR Imaging via A Non-Local Network (TIP 2020).

NHDRRNet-PyTorch This is the PyTorch implementation of Deep HDR Imaging via A Non-Local Network (TIP 2020). 0. Differences between Original Paper and

Yutong Zhang 1 Mar 01, 2022
TransZero++: Cross Attribute-guided Transformer for Zero-Shot Learning

TransZero++ This repository contains the testing code for the paper "TransZero++: Cross Attribute-guided Transformer for Zero-Shot Learning" submitted

Shiming Chen 6 Aug 16, 2022
Model of an AI powered sign language interpreter.

TEXT AND SPEECH TO SIGN LANGUAGE. A web application which takes in text or live audio speech recording as input, converts and displays the relevant Si

Mark Gatere 4 Mar 30, 2022
dyld_shared_cache processing / Single-Image loading for BinaryNinja

Dyld Shared Cache Parser Author: cynder (kat) Dyld Shared Cache Support for BinaryNinja Without any of the fuss of requiring manually loading several

cynder 76 Dec 28, 2022
Fake videos detection by tracing the source using video hashing retrieval.

Vision Transformer Based Video Hashing Retrieval for Tracing the Source of Fake Videos 🎉️ 📜 Directory Introduction VTL Trace Samples and Acc of Hash

56 Dec 22, 2022
Homepage of paper: Paint Transformer: Feed Forward Neural Painting with Stroke Prediction, ICCV 2021.

Paint Transformer: Feed Forward Neural Painting with Stroke Prediction [Paper] [PaddlePaddle Implementation] Homepage of paper: Paint Transformer: Fee

442 Dec 16, 2022
House-GAN++: Generative Adversarial Layout Refinement Network towards Intelligent Computational Agent for Professional Architects

House-GAN++ Code and instructions for our paper: House-GAN++: Generative Adversarial Layout Refinement Network towards Intelligent Computational Agent

122 Dec 28, 2022
Negative Sample is Negative in Its Own Way: Tailoring Negative Sentences forImage-Text Retrieval

NSGDC Some codes in this repo are copied/modified from opensource implementations made available by UNITER, PyTorch, HuggingFace, OpenNMT, and Nvidia.

Zhihao Fan 2 Nov 07, 2022
An Official Repo of CVPR '20 "MSeg: A Composite Dataset for Multi-Domain Segmentation"

This is the code for the paper: MSeg: A Composite Dataset for Multi-domain Semantic Segmentation (CVPR 2020, Official Repo) [CVPR PDF] [Journal PDF] J

226 Nov 05, 2022
Implementation of "Glancing Transformer for Non-Autoregressive Neural Machine Translation"

GLAT Implementation for the ACL2021 paper "Glancing Transformer for Non-Autoregressive Neural Machine Translation" Requirements Python = 3.7 Pytorch

117 Jan 09, 2023
The backbone CSPDarkNet of YOLOX.

YOLOX-Backbone The backbone CSPDarkNet of YOLOX. In this project, you can enjoy: CSPDarkNet-S CSPDarkNet-M CSPDarkNet-L CSPDarkNet-X CSPDarkNet-Tiny C

Jianhua Yang 9 Aug 22, 2022
Airborne magnetic data of the Osborne Mine and Lightning Creek sill complex, Australia

Osborne Mine, Australia - Airborne total-field magnetic anomaly This is a section of a survey acquired in 1990 by the Queensland Government, Australia

Fatiando a Terra Datasets 1 Jan 21, 2022
Convert human motion from video to .bvh

video_to_bvh Convert human motion from video to .bvh with Google Colab Usage 1. Open video_to_bvh.ipynb in Google Colab Go to https://colab.research.g

Dene 306 Dec 10, 2022
A machine learning project which can detect and predict the skin disease through image recognition.

ML-Project-2021 A machine learning project which can detect and predict the skin disease through image recognition. The dataset used for this is the H

Debshishu Ghosh 1 Jan 13, 2022
🙄 Difficult algorithm, Simple code.

🎉TensorFlow2.0-Examples🎉! "Talk is cheap, show me the code." ----- Linus Torvalds Created by YunYang1994 This tutorial was designed for easily divin

1.7k Dec 25, 2022
Predict Breast Cancer Wisconsin (Diagnostic) using Naive Bayes

Naive-Bayes Predict Breast Cancer Wisconsin (Diagnostic) using Naive Bayes Downloading Data Set Use our Breast Cancer Wisconsin Data Set Also you can

Faeze Habibi 0 Apr 06, 2022
Does Oversizing Improve Prosumer Profitability in a Flexibility Market? - A Sensitivity Analysis using PV-battery System

Does Oversizing Improve Prosumer Profitability in a Flexibility Market? - A Sensitivity Analysis using PV-battery System The possibilities to involve

Babu Kumaran Nalini 0 Nov 19, 2021
Automated Attendance Project Using Face Recognition

dependencies for project: cmake 3.22.1 dlib 19.22.1 face-recognition 1.3.0 openc

Rohail Taha 1 Jan 09, 2022