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[Bug Fix][Example] hgp-sl: More info for running (#2634)
* [Bug Fix][Example] hgp-sl: More info for running * change list to table * change dataset summary in gxn and sagpool * remove redundent Co-authored-by: Tong He <hetong007@gmail.com>
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Tianqi Zhang (张天启)
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@@ -10,47 +10,13 @@ The DGL's built-in LegacyTUDataset. This is a serial of graph kernel datasets fo
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NOTE: Follow the setting of the author's implementation, for 'DD' and 'PROTEINS', we use one-hot node label as input node features. For ENZYMES', 'IMDB-BINARY', 'IMDB-MULTI' and 'COLLAB', we use the concatenation of one-hot node label (if available) and one-hot node degree as input node features.
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DD
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- NumGraphs: 1178
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- AvgNodesPerGraph: 284.32
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- AvgEdgesPerGraph: 715.66
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- NumFeats: 89
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- NumClasses: 2
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PROTEINS
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- NumGraphs: 1113
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- AvgNodesPerGraph: 39.06
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- AvgEdgesPerGraph: 72.82
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- NumFeats: 1
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- NumClasses: 2
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ENZYMES
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- NumGraphs: 600
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- AvgNodesPerGraph: 32.63
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- AvgEdgesPerGraph: 62.14
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- NumFeats: 18
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- NumClasses: 6
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IMDB-BINARY
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- NumGraphs: 1000
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- AvgNodesPerGraph: 19.77
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- AvgEdgesPerGraph: 96.53
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- NumFeats: -
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- NumClasses: 2
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IMDB-MULTI
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- NumGraphs: 1500
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- AvgNodesPerGraph: 13.00
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- AvgEdgesPerGraph: 65.94
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- NumFeats: -
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- NumClasses: 3
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COLLAB
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- NumGraphs: 5000
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- AvgNodesPerGraph: 74.49
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- AvgEdgesPerGraph: 2457.78
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- NumFeats: -
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- NumClasses: 3
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| | DD | PROTEINS | ENZYMES | IMDB-BINARY | IMDB-MULTI | COLLAB |
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| ---------------- | ------ | -------- | ------- | ------------ | ---------- | -------- |
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| NumGraphs | 1178 | 1113 | 600 | 1000 | 1500 | 5000 |
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| AvgNodesPerGraph | 284.32 | 39.06 | 32.63 | 19.77 | 13.00 | 74.49 |
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| AvgEdgesPerGraph | 715.66 | 72.82 | 62.14 | 96.53 | 65.94 | 2457.78 |
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| NumFeats | 89 | 1 | 18 | - | - | - |
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| NumClasses | 2 | 2 | 6 | 2 | 3 | 2 |
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How to run example files
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@@ -15,62 +15,39 @@ The DGL's built-in [LegacyTUDataset](https://docs.dgl.ai/api/python/dgl.data.htm
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NOTE: Since there is no data attributes in some of these datasets, we use node_id (in one-hot vector whose length is the max number of nodes across all graphs) as the node feature. Also note that the node_id in some datasets is not unique (e.g. a graph may has two nodes with the same id).
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DD
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- NumGraphs: 1178
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- AvgNodesPerGraph: 284.32
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- AvgEdgesPerGraph: 715.66
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- NumFeats: 89
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- NumClasses: 2
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| | DD | PROTEINS | NCI1 | NCI109 | Mutagenicity | ENZYMES |
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| ---------------- | ------ | -------- | ----- | ------ | ------------ | ------- |
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| NumGraphs | 1178 | 1113 | 4110 | 4127 | 4337 | 600 |
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| AvgNodesPerGraph | 284.32 | 39.06 | 29.87 | 29.68 | 30.32 | 32.63 |
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| AvgEdgesPerGraph | 715.66 | 72.82 | 32.30 | 32.13 | 30.77 | 62.14 |
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| NumFeats | 89 | 1 | 37 | 38 | 14 | 18 |
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| NumClasses | 2 | 2 | 2 | 2 | 2 | 6 |
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PROTEINS
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- NumGraphs: 1113
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- AvgNodesPerGraph: 39.06
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- AvgEdgesPerGraph: 72.82
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- NumFeats: 1
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- NumClasses: 2
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NCI1
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- NumGraphs: 4110
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- AvgNodesPerGraph: 29.87
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- AvgEdgesPerGraph: 32.30
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- NumFeats: 37
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- NumClasses: 2
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NCI109
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- NumGraphs: 4127
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- AvgNodesPerGraph: 29.68
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- AvgEdgesPerGraph: 32.13
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- NumFeats: 38
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- NumClasses: 2
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Mutagenicity
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- NumGraphs: 4337
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- AvgNodesPerGraph: 30.32
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- AvgEdgesPerGraph: 30.77
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- NumFeats: 14
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- NumClasses: 2
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ENZYMES
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- NumGraphs: 600
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- AvgNodesPerGraph: 32.63
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- AvgEdgesPerGraph: 62.14
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- NumFeats: 18
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- NumClasses: 6
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How to run example files
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--------------------------------
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In the HGP-SL-DGL folder, run
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```bash
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python main.py --dataset ${your_dataset_name_here}
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python main.py --dataset ${your_dataset_name_here} [hyper-parameters]
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```
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If want to use a GPU, run
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```bash
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python main.py --device ${your_device_id_here} --dataset ${your_dataset_name_here}
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python main.py --device ${your_device_id_here} --dataset ${your_dataset_name_here} [hyper-parameters]
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```
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For example, to perform experiments on DD dataset on GPU, run:
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```bash
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python main.py --device 0 --dataset DD --lr 0.0001 --batch_size 64 --pool_ratio 0.3 --dropout 0.5 --conv_layers 2
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```
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NOTE: Be careful when modifying `batch_size` and `pool_ratio` for large dataset like DD. Too large batch size or pooling ratio may cause out-of-memory and other severe errors.
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You can find the detailed hyper-parameter settings below (in the Performance section).
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Performance
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-------------------------
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@@ -10,40 +10,13 @@ The DGL's built-in LegacyTUDataset. This is a serial of graph kernel datasets fo
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NOTE: Since there is no data attributes in some of these datasets, we use node_id (in one-hot vector whose length is the max number of nodes across all graphs) as the node feature. Also note that the node_id in some datasets is not unique (e.g. a graph may has two nodes with the same id).
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DD
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- NumGraphs: 1178
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- AvgNodesPerGraph: 284.32
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- AvgEdgesPerGraph: 715.66
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- NumFeats: 89
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- NumClasses: 2
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PROTEINS
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- NumGraphs: 1113
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- AvgNodesPerGraph: 39.06
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- AvgEdgesPerGraph: 72.82
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- NumFeats: 1
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- NumClasses: 2
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NCI1
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- NumGraphs: 4110
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- AvgNodesPerGraph: 29.87
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- AvgEdgesPerGraph: 32.30
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- NumFeats: 37
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- NumClasses: 2
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NCI109
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- NumGraphs: 4127
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- AvgNodesPerGraph: 29.68
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- AvgEdgesPerGraph: 32.13
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- NumFeats: 38
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- NumClasses: 2
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Mutagenicity
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- NumGraphs: 4337
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- AvgNodesPerGraph: 30.32
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- AvgEdgesPerGraph: 30.77
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- NumFeats: 14
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- NumClasses: 2
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| | DD | PROTEINS | NCI1 | NCI109 | Mutagenicity |
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| ---------------- | ------ | -------- | ----- | ------ | ------------ |
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| NumGraphs | 1178 | 1113 | 4110 | 4127 | 4337 |
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| AvgNodesPerGraph | 284.32 | 39.06 | 29.87 | 29.68 | 30.32 |
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| AvgEdgesPerGraph | 715.66 | 72.82 | 32.30 | 32.13 | 30.77 |
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| NumFeats | 89 | 1 | 37 | 38 | 14 |
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| NumClasses | 2 | 2 | 2 | 2 | 2 |
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How to run example files
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