graphless-neural-networks
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Fixed some bugs (see commit details and implementation for details)
已更正代码中的一些bug,请审查
@ShichangZh
Thank you so much for bringing up these issues and providing potential solutions to help improve our code quality. I have a few comments.
- For the output_path, it is indeed a bug when special parameters like feature_noise are set and num_exp > 1. Thank you for catching it. However, regarding the fix, I would prefer accessing
num_expinside the run function withargs.num_expinstead of adding an extra argument to the run function. This will keep the function arguments clean. - For the implementation of the
rand_train_test_idxfunction. I think there could be a mismatch between the intended non-negative node index and the actual non-negative node index when ignore_negative is set to true, aslabel = label[label >= 0]changes all the node indices without mapping them back. - What are these
.idea/files for?
Please kindly let me know whether you would agree with these comments.
- Yes! You are right, but I think the parameter
args.seedis a better choise, Becauseargs.num_expdoes not represent the current state of the experiment, it is just a number that specifies the number of times the experiment is performed. - Yes! Thank you for your correction!
.idea/folder was added automatically when I imported the project into IDE-PyCharm, and I forgot to exclude it from the.gitignorefile.
@ShichangZh
Thank you for the quick update. I agree that using args.seed is a more reasonable choice for the first point. For the second point of the rand_train_test_idx function, a minor comment is that the variable name valid_idx is overloaded for "valid (nonnegative) labels" and "labels for validation". Maybe the first valid_idx in line 253 can be renamed to something like nonnegative_idx to avoid confusion?
The fix looks good to me. I think this pull request can be merged. @nshah171