Related resources for our EMNLP 2021 paper

Related tags

Deep Learning PlanGen
Overview

Plan-then-Generate: Controlled Data-to-Text Generation via Planning

Authors: Yixuan Su, David Vandyke, Sihui Wang, Yimai Fang, and Nigel Collier

Code for EMNLP 2021 paper Plan-then-Generate: Controlled Data-to-Text Generation via Planning

1. Environment Setup:

(1) Hardware Requirement:

The code in this repo is thoroughly tested on our machine with a single Nvida V100 GPU (16GB)

(2) Installation:

chmod +x ./config_setup.sh
./config_setup.sh

2. ToTTo Data Preprocessing:

Option (1): Preprocess the ToTTo data from scratch by yourself:

cd ./data
chmod +x ./prepare_data.sh
./prepare_data.sh

This process could take up to 1 hour

Option (2): Download the our processed data here

unzip data.zip and replace with the empty ./data folder

For more details about ToTTo dataset, please refer to the original Google Research repo

3. Content Planner:

Please refer to README.md in ./content_planner folder

4. Sequence Generator:

Please refer to README.md in ./generator folder

5. Citation

If you find our paper and resources useful, please kindly cite our paper:

@inproceedings{su2021plangen,
    title={Plan-then-Generate: Controlled Data-to-Text Generation via Planning}, 
     author={Yixuan Su and David Vandyke and Sihui Wang and Yimai Fang and Nigel Collier},
    booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2021",
    month = nov,
    year = "2021",
    publisher = "Association for Computational Linguistics",
}
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Comments
  • the code of content_planner not provided

    the code of content_planner not provided

    Hi,I'm greatly interested in your "Plan-then-Generate" work,but the content planner mentioned in your paper is not provided code,i doubt how to joint the Bert model and CRF to generate the conent planner.I'm looking forward to reading your code in this part.Could you please provide the complete code as soon as possible?Thanks~

    opened by jiangliqin 5
  • Could you provide the processing code for RDF (WebNLG) data and the processed RDF data?

    Could you provide the processing code for RDF (WebNLG) data and the processed RDF data?

    Hi, could you provide the processing code for RDF data and the processed RDF data with content plan? I find it difficult to parse the content plan using the method proposed in the paper because it is hard to align objects in the reference text with those in the input graph. These objects often appear in different representations in reference text and input graphs.

    opened by Nicoleqwerty 3
  • Require code for content planner

    Require code for content planner

    Hi Yixuan @yxuansu,

    Your paper is an interesting read, thanks for sharing your work and code.

    Could you please provide the missing code for the Content Planner module? I would appreciate it, even if it is an initial/unrefined version that you have at the moment.

    Thanks!

    opened by prajwalgatti 2
  • Content Planner Issues

    Content Planner Issues

    Start Training: Traceback (most recent call last): File "train.py", line 99, in ckpt_save_path, cuda_available, device) File "/home/fanyongfeng/PyCharm/PlanGen/content_planner/trainer.py", line 83, in model_training train_batch_src_tensor, train_batch_tgt_tensor, _ = data.get_next_train_batch(batch_size_per_gpu * number_of_gpu) File "/home/fanyongfeng/PyCharm/PlanGen/content_planner/dataclass.py", line 87, in get_next_train_batch batch_idx_list = random.sample(self.train_idx_list, batch_size) File "/home/fanyongfeng/.conda/envs/fanyfeng/lib/python3.6/random.py", line 320, in sample raise ValueError("Sample larger than population or is negative") ValueError: Sample larger than population or is negative

    Hello, I'm using prepare_ After the data.sh command runs the data, this problem occurs when using train.sh. Do you know why? thank you

    opened by FYF1997 0
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Yixuan Su
Yixuan Su
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