AutoTGRL

• AutoTGRL is an automatic text graph representation learning (AutoTGRL) framework, which can automatically achieve text graph representation learning for text classification tasks.

• The framework of AutoTGRL is as follows:

Installing For Ubuntu 16.04

• Ensure you have installed CUDA 10.2 before installing other packages

1. Nvidia and CUDA 10.2:

[Nvidia Driver] 
https://www.nvidia.cn/Download/index.aspx?lang=cn

[CUDA 10.2 Download and Install Command] 
#Download:
wget https://developer.download.nvidia.com/compute/cuda/10.2/Prod/local_installers/cuda_10.2.89_440.33.01_linux.run
#Install:
sudo sh cuda_10.2.89_440.33.01_linux.run

2. Python environment: recommending using Conda package manager to install

conda create -n autotgrl python=3.7
source activate autotgrl

3. Pytorch 1.8.1: execute the following command in your conda env mvgnas

pip install torch==1.8.1+cu102 torchvision==0.9.1+cu102 torchaudio==0.8.1 -f https://download.pytorch.org/whl/torch_stable.html

4. Pytorch Geometric 2.0.2: execute the following command in your conda env autotgrl

pip install torch-scatter==2.0.9 torch-sparse==0.6.12 torch-cluster==1.5.9 torch-spline-conv==1.2.1 torch-geometric==2.0.2 -f https://data.pyg.org/whl/torch-1.8.0+cu102.html

5. transformers: execute the following command in your conda env autotgrl

pip install transformers

6. pytorch-ignite: execute the following command in your conda env autotgrl

pip install pytorch-ignite

Running the Experiment

For cleaning text dataset, please refer to the script 'main_clean_data.py'

python main_clean_data.py --dataset R52 --model_type 'transductive'

For text graph representation, please refer to the script 'main_build_graph.py'

python main_build_graph.py --dataset R52 --model_type 'transductive'

For generating initial document embedding, please refer to the script 'finetune_bert.py'

python large_scale_embd/finetune_bert.py --dataset R52 --bert_lr 1e-4  --bert_init  'roberta-base'

For training, please refer to the script 'main.py'

python main.py --dataset R52 --model_type 'transductive'

Note: more details will be added soon.