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‎CITATION.cff‎

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cff-version: 1.2.0
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message: "If you use this software, please cite it as below."
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authors:
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- family-names: "Maene"
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given-names: "Jaron"
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orcid: "https://orcid.org/0000-0001-9474-6150"
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- family-names: "Derkinderen"
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given-names: "Vincent"
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orcid: "https://orcid.org/0000-0002-8894-270X"
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- family-names: "Zuidberg Dos Martires"
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given-names: "Pedro"
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orcid: "https://orcid.org/0000-0001-5834-0188"
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title: "KLay: Accelerating Arithmetic Circuits for Neurosymbolic AI"
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version: 0.0.2
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date-released: 2024-12-10
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url: "https://github.com/ML-KULeuven/klay/"
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keywords:
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- Neurosymbolic AI
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- Arithmetic Circuits
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- Sparse Inference
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preferred-citation:
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type: conference-paper
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authors:
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- family-names: "Maene"
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given-names: "Jaron"
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orcid: "https://orcid.org/0000-0001-9474-6150"
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- family-names: "Derkinderen"
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given-names: "Vincent"
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orcid: "https://orcid.org/0000-0002-8894-270X"
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- family-names: "Zuidberg Dos Martires"
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given-names: "Pedro"
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orcid: "https://orcid.org/0000-0001-5834-0188"
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title: "KLay: Accelerating Arithmetic Circuits for Neurosymbolic AI"
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year: 2025
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publisher:
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name: OpenReview.net
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collection-title: "ICLR"
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‎LICENSE‎

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‎README.md‎

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# KLay
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C++ implementation of the Knowledge Layers. Includes support for:
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- SDD and d-DNNF circuits compiled by PySDD and D4.
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- Evaluation in Jax and PyTorch, on CPU and GPU.
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- Evaluation in various semirings (e.g. real, log, tropical).
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_KLay is a Python library for evaluating sparse arithmetic circuits on the GPU._
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## Installation
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To get started, install KLay using pip and check out [the documentation](todo).
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KLay has been tested on Linux (x86) and Mac (x86/ARM), no guarantees are made for Windows. KLay requires a C++ compiler and Python 3.9 or higher.
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```bash
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pip install .
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pip install klaycircuits
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```
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Most dependencies are optional. However, to replicate all the experiments, make sure to install the following:
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```bash
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pip install jax torch torchvision matplotlib numpy pysdd tqdm graphviz
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```
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Features include:
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- Evaluation in Jax and PyTorch, on CPU and GPU.
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- Loading SDD and d-DNNF circuits compiled by PySDD or D4.
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- Evaluation in various semirings (e.g. real, log, tropical).
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- Propagating constants and merging duplicate nodes.
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## Experiments
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The experiments in the paper can be replicated as follows.
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## 📃 Paper
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### Synthetic
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The synthetic experiments take a couple of hours to run.
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If you use KLay in your research, consider citing [our paper](https://openreview.net/pdf?id=Zes7Wyif8G).
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To run all the synthetic experiments of Figure 6.
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```bash
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bash experiments/synthetic/run_sdd.sh
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```
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To replicate the exact results and figures of the paper, use [this code](https://github.com/ML-KULeuven/klay/tree/d3b81491c34603ba9271d25af7c789d3ba368ede).
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Similarly, to run all the same synthetic experiments with d4 (as in Figure 7).
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```bash
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bash experiments/synthetic/run_d4.sh
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```
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And for the synthetic experiments in the real semiring (as in Figure 8).
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```bash
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bash experiments/synthetic/run_real.sh
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```
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To run the juice baseline, install [Julia](https://julialang.org/) and the [LogicCircuits.jl](https://github.com/Tractables/LogicCircuits.jl) package.
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Then run:
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```bash
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julia experiments/synthetic/benchmark_juice.jl
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```
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You can reproduce the plots of the paper using:
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```bash
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python experiments/synthetic/plot_figure.py
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```
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### NeSy experiments
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```bash
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python experiments/nesy/run.py
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```
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### MNIST-addition experiments
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```bash
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python experiments/mnist_addition/run.py -d cuda -b 128 -n 2
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```bibtex
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@inproceedings{
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maene2025klay,
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title={{KL}ay: Accelerating Arithmetic Circuits for Neurosymbolic {AI}},
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author = {Maene, Jaron and Derkinderen, Vincent and Zuidberg Dos Martires, Pedro},
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booktitle={The Thirteenth International Conference on Learning Representations},
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year={2025},
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url={https://openreview.net/forum?id=Zes7Wyif8G}
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}
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```

‎docs/Makefile‎

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# Minimal makefile for Sphinx documentation
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#
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# You can set these variables from the command line, and also
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# from the environment for the first two.
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SPHINXOPTS ?=
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SPHINXBUILD ?= sphinx-build
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SOURCEDIR = .
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BUILDDIR = _build
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# Put it first so that "make" without argument is like "make help".
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help:
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@$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
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.PHONY: help Makefile
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# Catch-all target: route all unknown targets to Sphinx using the new
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# "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS).
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%: Makefile
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@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)

‎docs/_static/scatter_reduce.png‎

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‎docs/api.rst‎

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API Reference
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=============
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.. autoclass:: klay.Circuit
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.. automethod:: nb_nodes
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.. automethod:: nb_root_nodes
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.. automethod:: true_node
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.. automethod:: false_node
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.. automethod:: literal_node
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.. automethod:: and_node
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.. automethod:: or_node
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.. automethod:: set_root
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.. automethod:: remove_unused_nodes
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.. automethod:: add_sdd
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.. automethod:: add_sdd_from_file
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.. automethod:: add_d4_from_file
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.. automethod:: to_torch_module
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.. automethod:: to_jax_function

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