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ARC DreamCoder

Neural networks for abstraction and reasoning: Towards broad generalization in machines
Mikel Bober-Irizar & Soumya Banerjee

https://arxiv.org/abs/2402.03507

Repo overview

Most of this repo follows the primary DreamCoder repo: https://github.com/ellisk42/ec.

Some helpful ARC-specific files:

  • ec/arcbin/arc_mikel2.py: The main entry-point for DreamCoder on ARC
  • ec/dreamcoder/domains/arc/arcPrimitivesIC2.py: PeARL definitions (domain-specific language).
  • ec/dreamcoder/domains/arc/main.py: Recognition model
  • ec/arcbin/test_primitives_mikel2.py: Very rough test harness to check that primitives aren't broken
  • arckit/: Vendored early version of the arckit library.
  • solved_tasks.md shows a list of tasks solved by DreamCoder with corresponding programs.

Building the DreamCoder environment

Since DreamCoder requires a complex set of dependencies, we follow the original repo in using Singularity containers. If you're familiar with Docker, this is quite similar.

The build is a 2-stage process. To use wandb, add a key in singularity_mod and create an arc project in your repo (or modify the entrypoint script to disable wandb).

cd ec/
# Build original DreamCoder (with fixes)
sudo singularity build container.img singularity

# Build additional packages and environment variables.
cd ..
sudo singularity build container_mod.img singularity_mod

Now, you have a container.img in the root of the repo which can be used to run the DreamCoder environment.

Running experiments

# See all command-line arguments
../container_mod.img python -u arcbin/arc_mikel.py --help

# Getting 70/400 on training set
../container_mod.img python -u arcbin/arc_mikel2.py -c 76 -t 3600 -R 2400 -i 1
# -c 76: Run on 76 cores
# -t 3600: 3600 core-seconds per task
# -R 2400: Train recognition model for 2400s per iteration (all cores)
# -i 1: Run for one iteration

# 18/400 on evaluation set:
../container_mod.img python -u arcbin/arc_mikel2.py -c 76 -t 3600 -R 2400 -i 1 --evalset
# --evalset: Run on ARC-Hard

# Ablation without recognition model (1min per task)
../container_mod.img python -u arcbin/arc_mikel2.py -c 76 -t 60 -g -i 5 --task-isolation
# -g: disable recognition model
# --task-isolation: Don't share programs across multiple tasks

Acknowledgements

The codebase in this repo is primarily based on the original DreamCoder repository, licensed under MIT.

Additionally, I brought in some changes from Simon Alford's bidir-synth repository as a starting point (https://github.com/mxbi/arc/commit/a04da2471d327c7e39352048fed2fcd63408c3fd). The starting point was a combination of these two repos with some additional patches to get it compiling again after a couple years of changes in dependencies.

License

The code in this repository is licensed under the MIT license. The original DreamCoder and bidir-synth repos are licened under the same license from their respective authors.

The ARC dataset (arckit/arc1.json) is licensed instead under the Apache license.

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