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# HGSL
Source code of AAAI submission "Heterogeneous Graph Structure Learning for Graph Neural Networks"
# Requirements
## Python Packages
- Python >= 3.6.8
- Pytorch >= 1.3.0
## GPU Memmory Requirements
- ACM >= 8G
- DBLP >=5G
- Yelp >=3G
# Usage
Take DBLP dataset as an example:
python train.py --dataset='dblp'
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# FAQ
## Code of preprocessing data?
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Please kindly note that the data is originally preprocessed by GTN project (https://github.com/seongjunyun/Graph_Transformer_Networks).
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_I received quite a lot email asking me about the dataset. I will not respond to them anymore as I cannot provide the code._
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## How to generate semantic embeddings?
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The semantic embeddings, i.e. $\mathcal{Z}$ in the paper, are generated by metapath2vec algorithm. Users may refer to https://github.com/dmlc/dgl/tree/master/examples/pytorch/metapath2vec for an implementation.
