dmlc--dgl
e2f33fd5cc
* [Model][Core] GATv2 * lint * gatv2conv.py * lint * lint * style and docs * lint * gatv2conv fix Co-authored-by: Shaked Brody shakedbr@campus.technion.ac.il <shakedbr@tangerine.cslcs.technion.ac.il> Co-authored-by: Mufei Li <mufeili1996@gmail.com>
40 行
812 B
Markdown
40 行
812 B
Markdown
Graph Attention Networks v2 (GATv2)
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============
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- Paper link: [How Attentive are Graph Attention Networks?](https://arxiv.org/pdf/2105.14491.pdf)
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- Author's code repo: [https://github.com/tech-srl/how_attentive_are_gats](https://github.com/tech-srl/how_attentive_are_gats).
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- Annotated implemetnation: [https://nn.labml.ai/graphs/gatv2/index.html]
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Dependencies
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------------
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- torch
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- requests
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- sklearn
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How to run
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----------
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Run with following:
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```bash
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python3 train.py --dataset=cora
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```
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```bash
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python3 train.py --dataset=citeseer
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```
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```bash
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python3 train.py --dataset=pubmed
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```
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Results
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-------
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| Dataset | Test Accuracy |
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| -------- | ------------- |
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| Cora | 82.10 |
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| Citeseer | 70.00 |
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| Pubmed | 77.2 |
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* All the accuracy numbers are obtained after 200 epochs. |