DPCNN

Deep Pyramid Convolutional Neural Networks for Text Categorization

This is the implementation of DPCNN in tensorflow.

The key operation of this paper is

• fixed feature map:250
• 2 stride downsampling which can compress effective information of long distance.

The format of data :

• .csv file
• it has two columns,one column is content,the other column is label.
• you can modify value of parameter --file_name to use your train,val,test dataset.
• example in data/
• you should put your dataset in data/

python run.py --train --model_name DPCNN --write_vocab True --experiment_name test

When you run the code first time,you should set write_vocab True to write vocab for the data.