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Automatic-Opinion-Question-Generation

Implementation of Automatic Opinion Question Generation paper in PyTorch.

Place your data in data/raw .

Generate the processed data:

python file_convertion.py

Preprocessing:

python preprocess.py -train_src data/src-train.txt -train_tgt data/tgt-train.txt -valid_src data/src-val.txt -valid_tgt data/tgt-val.txt -save_data data/data -lower

Generate embedding files:

python embedding.py 
-embedding  <path to embedding txt file>
-dict data/data.{src,tgt}.dict 
-output data/{src,tgt}.840B.300d

Training:

python train.py -data data/data.train.pt -save_model model/model -coverage_attn -brnn -rnn_size 600 -word_vec_size 300 -epochs 20 -start_decay_at 10 -layers 2 -pre_word_vecs_enc data/src.840B.300d -pre_word_vecs_dec data/tgt.840B.300d

Use -gpus if a GPU is available.

Generating:

python translate.py -model model/model_epochX_PPL.pt -src data/src-test.txt -output result/pred.txt -replace_unk -verbose

Evaluation:

cd Evaluation
./eval.py --out_file ../result/pred.txt 

Acknowledgment

Our implementation is adapted from OpenNMT. The evaluation scripts are adapted from coco-caption repo.

License

Code is released under the MIT license.

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