Comments (12)
The outputs of the forward for GraphSAGE are all equal for the same iteration, which I think makes sense since the features are all 1.
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Also outputs after first layer(x, edge_index) are all equal for the same training iterations.
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Same thing occurs for IMDB-MULTI, the accuracies don't go higher than 30%
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Hi, I'm investigating. It's possible it has to do with the newer version of PyG compared to 2020. Have you tried other social/chemical datasets rather than IMDB?
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It is working on my laptop. IMDB-BINARY learns when considering the degree.
Here are the steps to reproduce
source install.sh
Could you please double check that you are executing the commands correctly?
python PrepareDatasets.py DATA/SOCIAL_DEGREE --dataset-name IMDB-BINARY --use-degree --outer-k 10
cp -r DATA/SOCIAL_DEGREE/IMDB-BINARY/ DATA
python Launch_Experiments.py --config-file config_GraphSAGE.yml --dataset-name IMDB-BINARY --result-folder RESULTS --debug
Thanks,
Federico
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I ran the same exact commands and the error persists :(
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Deleted the folder Data and ran the commands you mention and now it seems to work. I don't know what was blocking it from learning but anyways thank you.
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I''m baffled as well.. happy to help! :)
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python PrepareDatasets.py DATA/SOCIAL_1 --dataset-name IMDB-BINARY --use-one --outer-k 10
cp -r DATA/SOCIAL_1/IMDB-BINARY/ DATA
python Launch_Experiments.py --config-file config_GraphSAGE.yml --dataset-name IMDB-BINARY --result-folder RESULTS --debug
For SOCIAL_1 keeps not working :(
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And this happens for all social datasets with use_one
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Thanks for raising the problem. Apparently setting conv.aggr
after initialization does not work anymore, so I updated the code and now GraphSAGE learns with "add" aggregation on SOCIAL_1 IMDB-BINARY.
Please pull and retry!
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Working now. Thank you.
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Related Issues (20)
- Best configs / splits HOT 3
- It takes long time to train DiffPool HOT 1
- The program crashes without "--debug" flag being set when using Cuda. HOT 1
- Using DGCNN with new data HOT 1
- Using dropout in last layer HOT 1
- Call each other HOT 2
- additional features HOT 1
- PyTorch -- multiple threads for each process HOT 2
- Is there a mistake in Data Preprocessing? HOT 2
- error message HOT 1
- OUTER_TS is 20.0 FOR M5k(GraphSAGE) HOT 2
- Different best config in each k_fold HOT 6
- Can't find device = cuda in config files HOT 1
- DiffPool breaks on ENZYMES? HOT 5
- Results don't match - am I running something in the wrong way? HOT 2
- Not a question, the code is running well. Thanks.
- the dataset for the experiments HOT 1
- Multi-process running errors HOT 4
- The position of "config_id += 1" in the 84 of evaluation/model_selection/HoldOutSelector.py HOT 1
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