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This repo contains the source code of the models described in the following paper

  • "Learning and Analyzing Generation Order for Undirected Sequence Models" in Findings of EMNLP, 2021. (paper).

The basic code structure was adapted from the NYU dl4mt-seqgen. We also use the pybleu from fairseq to calculate BLEU scores during the reinforcement learning.

0. Preparation

0.1 Dependencies

  • PyTorch 1.4.0/1.6.0/1.8.0

0.2 Data

The WMT'14 De-En data and the pretrained De-En MLM model are provided in the dl4mt-seqgen.

  • Download WMT'14 De-En valid/test data.
  • Then organize the data in data/ and make sure it follows such a structure:
------ data
--------- de-en
  • Download pretrained models.
  • Then organize the pretrained masked language models in models/ make sure it follows such a structure:
------ models
--------- best-valid_en-de_mt_bleu.pth
--------- best-valid_de-en_mt_bleu.pth

2. Training the order policy network with reinforcement learning

Train a policy network to predict the generation order for a pretrained De-En masked language model:

  • By defaults, the model checkpoints will be saved in models/learned_order_deen_uniform_4gpu/00_maxlen30_minlen5_bsz32.
  • By using this script, we are only training the model on De-En sentence pairs where both the German and English sentences with a maximum length of 30 and a minimum length of 5. You can change the training parameters max_len and min_len to change the length limits.

3. Decode the undirected generation model with learned orders

  • Set the MODEL_CKPT parameter to the corresponding path found under models/00_maxlen30_minlen5_bsz32. For example:
export MODEL_CKPT=wj8oc8kab4/checkpoint_epoch30+iter96875.pth
  • Evaluate the model on the SCAN MCD1 splits by running:
export MODEL_CKPT=...
./eval_scripts/ $MODEL_CKPT

4. Decode the undirected generation model with heuristic orders

  • Left2Right
./eval_scripts/ left_right_greedy_1iter
  • Least2Most
./eval_scripts/ least_most_greedy_1iter
  • EasyFirst
./eval_scripts/ easy_first_greedy_1iter
  • Uniform
./eval_scripts/ uniform_greedy_1iter


    title = "Learning and Analyzing Generation Order for Undirected Sequence Models",
    author = "Jiang, Yichen  and
      Bansal, Mohit",
    booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2021",
    month = nov,
    year = "2021",
    address = "Punta Cana, Dominican Republic",
    publisher = "Association for Computational Linguistics",
    url = "",
    pages = "3513--3523",


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