Comments (3)
ChrisZhangcx
commented on August 15, 2024
2
It turns out to me that the set() method in utils.py line 7 contributes to this issue.
Cuz every time we transform a list into a set, the order will be different.
There are two methods to solve this:
- Change set to hashset.
- Replace origin line 7 with 'classes = sorted(set(labels))'.
I utilized the second method and this problem have been solved. Please check this out.
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ChrisZhangcx
commented on August 15, 2024
I met with the same problem. Did you figure out how to solve this?
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xuuuluuu
commented on August 15, 2024
It turns out to me that the set() method in utils.py line 7 contributes to this issue.
Cuz every time we transform a list into a set, the order will be different.
There are two methods to solve this:
- Change set to hashset.
- Replace origin line 7 with 'classes = sorted(set(labels))'.
I utilized the second method and this problem have been solved. Please check this out.
I think you are right. the set is not ordered by default.
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Related Issues (20)
- specifying modes train, validation and test HOT 1
- Where is Filter parameters in the code? HOT 1
- Hi, does pandas make the data preprocessing more simple?
- Normalization of features, batch-wise training, feature extraction
- question about the adjacency matrix HOT 2
- citeseer dataset seems doesnot work HOT 2
- Difference between TF and Pytorch version code HOT 5
- In tensor flow code you used early stopping,isn't it needed in pytorch???
- In `utils.py` line 36, wouldnt `adj = adj + (adj.T > adj)` also work? HOT 2
- Invoice node classification / meta-data extraction / single prediction with trained model
- How to do a semi-supervised learning? HOT 6
- Predicting node degree
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- Error: 'pybind11' must be installed before running the build.
- transform to other scope dataset
- Why do row normalization instead of column normalization？ HOT 2
- About the dataset split HOT 3
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