https://github.com/graph-com/layerdag
code for the paper "LayerDAG: A Layerwise Autoregressive Diffusion Model of Directed Acyclic Graphs"
https://github.com/graph-com/layerdag
autoregressive-models dataflows ddpm directed-acyclic-graph generative-model graph-generation graph-neural-networks intermediate-representation pytorch synthetic-data-generation
Last synced: 6 months ago
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code for the paper "LayerDAG: A Layerwise Autoregressive Diffusion Model of Directed Acyclic Graphs"
- Host: GitHub
- URL: https://github.com/graph-com/layerdag
- Owner: Graph-COM
- License: apache-2.0
- Created: 2024-06-06T04:30:54.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2024-11-09T16:37:43.000Z (7 months ago)
- Last Synced: 2024-11-09T16:39:07.766Z (7 months ago)
- Topics: autoregressive-models, dataflows, ddpm, directed-acyclic-graph, generative-model, graph-generation, graph-neural-networks, intermediate-representation, pytorch, synthetic-data-generation
- Language: Python
- Homepage:
- Size: 1.23 MB
- Stars: 7
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# LayerDAG
[[Paper]](https://arxiv.org/abs/2411.02322)
## Table of Contents
- [Installation](#installation)
- [Train](#train)
- [Sample](#sample)
- [Eval](#eval)
- [Frequently Asked Questions](#frequently-asked-questions)
* [Q1: libcusparse.so](#q1-libcusparseso)
- [Citation](#citation)
## Installation
```bash
conda create -n LayerDAG python=3.10 -y
conda activate LayerDAG
pip install torch==1.12.0+cu116 --extra-index-url https://download.pytorch.org/whl/cu116
conda install -c conda-forge cudatoolkit=11.6
conda clean --all -y
pip install dgl==1.1.0+cu116 -f https://data.dgl.ai/wheels/cu116/repo.html
pip install tqdm einops wandb pydantic pandas
pip install numpy==1.26.3
```
## Train
To train a LayerDAG model,
```bash
python train.py --config_file configs/LayerDAG/tpu_tile.yaml
```
The trained model checkpoint will be saved to a file `model_tpu_tile_{time_stamp}.pth`.
## Sample
For sampling and evaluation,
```bash
python sample.py --model_path X
```
where `X` is the file `model_tpu_tile_{time_stamp}.pth` saved above.
## Frequently Asked Questions
### Q1: libcusparse.so
**An error occurs that the program cannot find `libcusparse.so`**, e.g., OSError: libcusparse.so.11: cannot open shared object file: No such file or directory.
To search for the location of it on linux,
```bash
find /path/to/directory -name libcusparse.so.11 -exec realpath {} \;
```
where `/path/to/directory` is the directory you want to search. Assume that the search returns `/home/miniconda3/envs/LayerDAG/lib/libcusparse.so.11`. Then you need to manually specify the environment variable as follows.
```bash
export LD_LIBRARY_PATH=/home/miniconda3/envs/LayerDAG/lib:$LD_LIBRARY_PATH
```
## Citation
```
@article{li2024layerdag,
title={Layer{DAG}: A Layerwise Autoregressive Diffusion Model for Directed Acyclic Graph Generation},
author={Mufei Li and Viraj Shitole and Eli Chien and Changhai Man and Zhaodong Wang and Srinivas Sridharan and Ying Zhang and Tushar Krishna and Pan Li},
journal={arXiv preprint arXiv:2411.02322},
year={2024}
}
```