From 729dfdf6c4f8feda3011f5157a0055398cba435c Mon Sep 17 00:00:00 2001 From: ranqiu Date: Tue, 14 Nov 2017 11:48:45 +0800 Subject: [PATCH] Add Readme to convs2s --- conv_seq_to_seq/README.md | 51 ++++++++++++++++++++++++++++++++++++++- 1 file changed, 50 insertions(+), 1 deletion(-) diff --git a/conv_seq_to_seq/README.md b/conv_seq_to_seq/README.md index f6a09ed2..5b4bcfff 100644 --- a/conv_seq_to_seq/README.md +++ b/conv_seq_to_seq/README.md @@ -1 +1,50 @@ -[TBD] +# Convolutional Sequence to Sequence Learning +This model implements the work in the following paper: + +Jonas Gehring, Micheal Auli, David Grangier, et al. Convolutional Sequence to Sequence Learning. Association for Computational Linguistics (ACL), 2017 + +# Training a Model +- Modify the following script if needed and then run: + + ```bash + python train.py \ + --train_data_path ./data/train_data \ + --test_data_path ./data/test_data \ + --src_dict_path ./data/src_dict \ + --trg_dict_path ./data/trg_dict \ + --enc_blocks "[(256, 3)] * 5" \ + --dec_blocks "[(256, 3)] * 3" \ + --emb_size 256 \ + --pos_size 200 \ + --drop_rate 0.1 \ + --use_gpu False \ + --trainer_count 1 \ + --batch_size 32 \ + --num_passes 20 \ + >train.log 2>&1 + ``` + +# Inferring by a Trained Model +- Infer by a trained model by running: + + ```bash + python infer.py \ + --infer_data_path ./data/infer_data \ + --src_dict_path ./data/src_dict \ + --trg_dict_path ./data/trg_dict \ + --enc_blocks "[(256, 3)] * 5" \ + --dec_blocks "[(256, 3)] * 3" \ + --emb_size 256 \ + --pos_size 200 \ + --drop_rate 0.1 \ + --use_gpu False \ + --trainer_count 1 \ + --max_len 100 \ + --beam_size 1 \ + --model_path ./params.pass-0.tar.gz \ + 1>infer_result 2>infer.log + ``` + +# Notes + +Currently, the beam search will forward the whole network when predicting every word, which is a waste of time. And we will fix it later. -- GitLab