This repository contains codes to get raw text Chinese couplets, codes to train four models, and codes to generate a couplet response using saved models.
pytorch 1.2
Crawling raw text couplets and preprocessing raw texts are in utils folder.
The models are in model.py. The training configuration of each model is in .py files with heading train. transformer.py contains the implementation of the submodule of models and large part of codes come from annotated-transformer.
The codes where saved models are used to generate couplet responses is in test.py.
Codes in measure folder are used to calculate BLEU score (from BLEU4Python).
Note: The models use pre-trained word vectors as part of the embedding. Models use this embedding. The specific embedding used in this repository can be downloaded from here. To run the codes, the word vectors have to be downloaded first.
| Model Name | Description |
|---|---|
| Vanilla Transformer | The standard transformer model |
| Oneway Model | The model is basically a transformer encoder |
| Twoway Model | The model is basically a transformer decoder where the source is sent to decoder as input while partially decoded couplet response is fed to decoder as context. |
| Memory Model | The model is basically a transformer followed by a memory network. The memory network is different from common ones. The memory network is basically a transformer decoder without self-attention. Similarly, the partially decoded response is used as the memory. |
These two samples are generated using Twoway Model (run test.py).
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