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PyTorch implementation of "Learning Compositional Rules via Neural Program Synthesis"

This is the codebase for the NeurIPS 2020 paper:

Learning Compositional Rules via Neural Program Synthsis
Maxwell I. Nye, Armando Solar-Lezama, Joshua B. Tenenbaum, Brenden M. Lake
https://arxiv.org/pdf/2003.05562.pdf
NeurIPS 2020 Proceedings

Much of this code is based on the meta seq2seq code by Brenden Lake.

Requirements

Python 3.7

PyTorch 1.4.0

PHP intl (installed via sudo apt install php7.0-intl on ubuntu 16.04)

pyro (pip3 install pyro-ppl)

pyprob (installed from source)

Add necessary folders:

mkdir out_models
mkdir results
mkdir logs
mkdir testnums

We use zsh, though bash should also work for running the .sh scripts.

MiniSCAN experiments

to train synthesis network:

python synthTrain.py --fn_out_model 'miniscan_final.p' --batchsize 128 --episode_type 'rules_gen'

to train meta seq2seq network:

python train_metanet_attn.py --fn_out_model 'metas2s_baseline.p' --episode_type 'rules_gen'

to run evaluation:

zsh miniscan_test.sh

to run evaluation of human tested domain in Figure 2:

zsh human_miniscan.sh

SCAN experiments

to train synthesis network:

python synthTrain.py --fn_out_model 'scan_final.p' --batchsize 128 --episode_type 'scan_random' --num_pretrain_episodes 1000000

to train meta seq2seq network:

python train_metanet_attn.py --num_episodes 10000000 --fn_out_model 'scan_metas2s_baseline.p' --episode_type 'scan_random'

to replicate baselines in Table 1:

zsh SCAN_baselines.sh

to replicate results of full synthesis model with search (Table 1, top row) and search budget details (Table 2):

zsh scan_search_run.sh

to replicate results of full synthesis model with fixed example sets (Supplement Table 6):

zsh SCAN_fixed_budget.sh

Number word experments

to train synthesis network:

python synthTrain.py --episode_type wordToNumber --type WordToNumber --print_freq 50 --batchsize 128 --save_freq 150 --fn_out_model WordToNum.p 

to train meta seq2seq network:

python train_metanet_attn.py --fn_out_model 'MetaNetw2num.p' --episode_type 'wordToNumber'

to run evaluation:

zsh number_test.sh

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