dmlc--dgl
Hao Zhang
788d8dd4ad
* Create ppi.py * Create train_ppi.py * Update train_ppi.py * Update train_ppi.py * Create gat.py * Update train.py * Update train_ppi.py * Update ppi.py * Update train_ppi.py * Update ppi.py * Update train_ppi.py * Update train_ppi.py * Update ppi.py * Update train_ppi.py * update docs and readme
55 行
1.4 KiB
Markdown
55 行
1.4 KiB
Markdown
Graph Attention Networks (GAT)
|
|
============
|
|
|
|
- Paper link: [https://arxiv.org/abs/1710.10903](https://arxiv.org/abs/1710.10903)
|
|
- Author's code repo (in Tensorflow):
|
|
[https://github.com/PetarV-/GAT](https://github.com/PetarV-/GAT).
|
|
- Popular pytorch implementation:
|
|
[https://github.com/Diego999/pyGAT](https://github.com/Diego999/pyGAT).
|
|
|
|
Dependencies
|
|
------------
|
|
- torch v1.0: the autograd support for sparse mm is only available in v1.0.
|
|
- requests
|
|
- sklearn
|
|
|
|
```bash
|
|
pip install torch==1.0.0 requests
|
|
```
|
|
|
|
How to run
|
|
----------
|
|
|
|
Run with following:
|
|
|
|
```bash
|
|
python train.py --dataset=cora --gpu=0
|
|
```
|
|
|
|
```bash
|
|
python train.py --dataset=citeseer --gpu=0
|
|
```
|
|
|
|
```bash
|
|
python train.py --dataset=pubmed --gpu=0 --num-out-heads=8 --weight-decay=0.001
|
|
```
|
|
|
|
```bash
|
|
python train_ppi.py --gpu=0
|
|
```
|
|
|
|
Results
|
|
-------
|
|
|
|
| Dataset | Test Accuracy | Time(s) | Baseline#1 times(s) | Baseline#2 times(s) |
|
|
| ------- | ------------- | ------- | ------------------- | ------------------- |
|
|
| Cora | 84.0% | 0.0127 | 0.0982 (**7.7x**) | 0.0424 (**3.3x**) |
|
|
| Citeseer | 70.7% | 0.0123 | n/a | n/a |
|
|
| Pubmed | 78.1% | 0.0302 | n/a | n/a |
|
|
|
|
* All the accuracy numbers are obtained after 300 epochs.
|
|
* The time measures how long it takes to train one epoch.
|
|
* All time is measured on EC2 p3.2xlarge instance w/ V100 GPU.
|
|
* Baseline#1: [https://github.com/PetarV-/GAT](https://github.com/PetarV-/GAT).
|
|
* Baseline#2: [https://github.com/Diego999/pyGAT](https://github.com/Diego999/pyGAT).
|