# summarization_tf

**Repository Path**: wxwxzhang/summarization_tf

## Basic Information

- **Project Name**: summarization_tf
- **Description**: Implementation of "Automatic Source Code Summarization with Extended Tree-LSTM"
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2019-11-04
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Attention-based Tree-to-Sequence Code Summarization Model

The TensorFlow Eager Execution implementation of [Source Code Summarization with Extended Tree-LSTM](https://arxiv.org/abs/1906.08094) (Shido+, 2019)

including:

- **Multi-way Tree-LSTM model (Ours)**
- Child-sum Tree-LSTM model
- N-ary Tree-LSTM model
- DeepCom (Hu et al.)
- CODE-NN (Iyer et al.)

## Dataset

1. Download raw dataset from [https://github.com/xing-hu/DeepCom]
2. Parse them with parser.jar

## Usage

1. Prepare tree-structured data with `dataset.py`
    - Run `$ python dataset.py [dir]`
2. Train and evaluate model with `train.py`
    - See `$ python train.py -h`