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Commit 82bb9a9b authored by Lingfan Yu's avatar Lingfan Yu Committed by Da Zheng
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[README] Update speed numbers in README (#661) 

* update speed numbers in readme

* numbers in examples/pytorch/readme
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README.md
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...@@ -15,11 +15,11 @@ A summary of the model accuracy and training speed with the Pytorch backend (on ...@@ -15,11 +15,11 @@ A summary of the model accuracy and training speed with the Pytorch backend (on
| Model | Reported <br> Accuracy | DGL <br> Accuracy | Author's training speed (epoch time) | DGL speed (epoch time) | Improvement | | Model | Reported <br> Accuracy | DGL <br> Accuracy | Author's training speed (epoch time) | DGL speed (epoch time) | Improvement |
| ----- | ----------------- | ------------ | ------------------------------------ | ---------------------- | ----------- | | ----- | ----------------- | ------------ | ------------------------------------ | ---------------------- | ----------- |
| [GCN](https://arxiv.org/abs/1609.02907) | 81.5% | 81.0% | [0.0051s (TF)](https://github.com/tkipf/gcn) | 0.0038s | 1.34x | | [GCN](https://arxiv.org/abs/1609.02907) | 81.5% | 81.0% | [0.0051s (TF)](https://github.com/tkipf/gcn) | 0.0031s | 1.64x |
| [GAT](https://arxiv.org/abs/1710.10903) | 83.0% | 83.9% | [0.0982s (TF)](https://github.com/PetarV-/GAT) | 0.0076s | 12.9x | | [GAT](https://arxiv.org/abs/1710.10903) | 83.0% | 83.9% | [0.0982s (TF)](https://github.com/PetarV-/GAT) | 0.0113s | 8.69x |
| [SGC](https://arxiv.org/abs/1902.07153) | 81.0% | 81.9% | n/a | 0.0008s | n/a | | [SGC](https://arxiv.org/abs/1902.07153) | 81.0% | 81.9% | n/a | 0.0008s | n/a |
| [TreeLSTM](http://arxiv.org/abs/1503.00075) | 51.0% | 51.72% | [14.02s (DyNet)](https://github.com/clab/dynet/tree/master/examples/treelstm) | 3.18s | 4.3x | | [TreeLSTM](http://arxiv.org/abs/1503.00075) | 51.0% | 51.72% | [14.02s (DyNet)](https://github.com/clab/dynet/tree/master/examples/treelstm) | 3.18s | 4.3x |
| [R-GCN <br> (classification)](https://arxiv.org/abs/1703.06103) | 73.23% | 73.53% | [0.2853s (Theano)](https://github.com/tkipf/relational-gcn) | 0.0097s | 29.4x | | [R-GCN <br> (classification)](https://arxiv.org/abs/1703.06103) | 73.23% | 73.53% | [0.2853s (Theano)](https://github.com/tkipf/relational-gcn) | 0.0075s | 38.2x |
| [R-GCN <br> (link prediction)](https://arxiv.org/abs/1703.06103) | 0.158 | 0.151 | [2.204s (TF)](https://github.com/MichSchli/RelationPrediction) | 0.453s | 4.86x | | [R-GCN <br> (link prediction)](https://arxiv.org/abs/1703.06103) | 0.158 | 0.151 | [2.204s (TF)](https://github.com/MichSchli/RelationPrediction) | 0.453s | 4.86x |
| [JTNN](https://arxiv.org/abs/1802.04364) | 96.44% | 96.44% | [1826s (Pytorch)](https://github.com/wengong-jin/icml18-jtnn) | 743s | 2.5x | | [JTNN](https://arxiv.org/abs/1802.04364) | 96.44% | 96.44% | [1826s (Pytorch)](https://github.com/wengong-jin/icml18-jtnn) | 743s | 2.5x |
| [LGNN](https://arxiv.org/abs/1705.08415) | 94% | 94% | n/a | 1.45s | n/a | | [LGNN](https://arxiv.org/abs/1705.08415) | 94% | 94% | n/a | 1.45s | n/a |
......
examples/pytorch/README.md
View file @ 82bb9a9b
...@@ -12,11 +12,12 @@ Here is a summary of the model accuracy and training speed. Our testbed is Amazo ...@@ -12,11 +12,12 @@ Here is a summary of the model accuracy and training speed. Our testbed is Amazo
| Model | Reported <br> Accuracy | DGL <br> Accuracy | Author's training speed (epoch time) | DGL speed (epoch time) | Improvement | | Model | Reported <br> Accuracy | DGL <br> Accuracy | Author's training speed (epoch time) | DGL speed (epoch time) | Improvement |
| ----- | ----------------- | ------------ | ------------------------------------ | ---------------------- | ----------- | | ----- | ----------------- | ------------ | ------------------------------------ | ---------------------- | ----------- |
| [GCN](https://arxiv.org/abs/1609.02907) | 81.5% | 81.0% | [0.0051s (TF)](https://github.com/tkipf/gcn) | 0.0042s | 1.17x | | [GCN](https://arxiv.org/abs/1609.02907) | 81.5% | 81.0% | [0.0051s (TF)](https://github.com/tkipf/gcn) | 0.0031s | 1.64x |
| [GAT](https://arxiv.org/abs/1710.10903) | 83.0% | 83.9% | [0.0982s (TF)](https://github.com/PetarV-/GAT) | 0.0113s | 8.69x |
| [SGC](https://arxiv.org/abs/1902.07153) | 81.0% | 81.9% | n/a | 0.0008s | n/a | | [SGC](https://arxiv.org/abs/1902.07153) | 81.0% | 81.9% | n/a | 0.0008s | n/a |
| [TreeLSTM](http://arxiv.org/abs/1503.00075) | 51.0% | 51.72% | [14.02s (DyNet)](https://github.com/clab/dynet/tree/master/examples/treelstm) | 3.18s | 4.3x | | [TreeLSTM](http://arxiv.org/abs/1503.00075) | 51.0% | 51.72% | [14.02s (DyNet)](https://github.com/clab/dynet/tree/master/examples/treelstm) | 3.18s | 4.3x |
| [R-GCN <br> (classification)](https://arxiv.org/abs/1703.06103) | 73.23% | 73.53% | [0.2853s (Theano)](https://github.com/tkipf/relational-gcn) | 0.0273s | 10.4x | | [R-GCN <br> (classification)](https://arxiv.org/abs/1703.06103) | 73.23% | 73.53% | [0.2853s (Theano)](https://github.com/tkipf/relational-gcn) | 0.0075s | 38.2x |
| [R-GCN <br> (link prediction)](https://arxiv.org/abs/1703.06103) | 0.158 | 0.151 | [2.204s (TF)](https://github.com/MichSchli/RelationPrediction) | 0.633s | 3.5x | | [R-GCN <br> (link prediction)](https://arxiv.org/abs/1703.06103) | 0.158 | 0.151 | [2.204s (TF)](https://github.com/MichSchli/RelationPrediction) | 0.453s | 4.86x |
| [JTNN](https://arxiv.org/abs/1802.04364) | 96.44% | 96.44% | [1826s (Pytorch)](https://github.com/wengong-jin/icml18-jtnn) | 743s | 2.5x | | [JTNN](https://arxiv.org/abs/1802.04364) | 96.44% | 96.44% | [1826s (Pytorch)](https://github.com/wengong-jin/icml18-jtnn) | 743s | 2.5x |
| [LGNN](https://arxiv.org/abs/1705.08415) | 94% | 94% | n/a | 1.45s | n/a | | [LGNN](https://arxiv.org/abs/1705.08415) | 94% | 94% | n/a | 1.45s | n/a |
| [DGMG](https://arxiv.org/pdf/1803.03324.pdf) | 84% | 90% | n/a | 238s | n/a | | [DGMG](https://arxiv.org/pdf/1803.03324.pdf) | 84% | 90% | n/a | 238s | n/a |
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