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View Code? Open in Web Editor NEWACL 2020: A Re-evaluation of Knowledge Graph Completion Methods
License: Apache License 2.0
ACL 2020: A Re-evaluation of Knowledge Graph Completion Methods
License: Apache License 2.0
File "conve.py", line 312, in
model = Main(args)
File "conve.py", line 82, in init
self.logger = get_logger(self.p.name, self.p.log_dir, self.p.config_dir)
File "C:\Users\Kano_Hayashi\Desktop\kg-reeval-master\ConvE\helper.py", line 52, in get_logger
logging.config.dictConfig(config_dict)
File "C:\Users\Kano_Hayashi.conda\envs\rota\lib\logging\config.py", line 800, in dictConfig
dictConfigClass(config).configure()
File "C:\Users\Kano_Hayashi.conda\envs\rota\lib\logging\config.py", line 571, in configure
'%r' % name) from e
ValueError: Unable to configure handler 'file_handler'
Hi, Have you studied whether RGHAT has the same data leakage problem as KBGAT?
I want to know whether the result reported in your paper about KBAT is the result after fix. I only saw the content of the evaluation protocol modified in the code, and did not see the modification of the valid_triples_dict you mentioned, thanks.
In RotatE new evaluation, you change the order of scores
before sorting. So the key problem becomes the sort algorithm used in torch.argsort
should be stable. I am not sure about this. But I google it. Seems like it's not. So I think it would be a problem. Maybe we should change to np.argsort(xxx, kind='stable')
?
Try to this:
import torch
a = torch.tensor(
[[ 0., 3.],
[ 2., 3.],
[ 2., 2.],
[10., 2.],
[ 0., 2.],
[ 6., 2.],
[10., 1.],
[ 2., 1.],
[ 0., 1.],
[ 6., 1.],
[10., 0.],
[12., 0.]]
)
print(a[torch.argsort(a[:, 0])])
Output:
tensor([[ 0., 3.],
[ 0., 2.],
[ 0., 1.],
[ 2., 1.],
[ 2., 2.],
[ 2., 3.],
[ 6., 1.],
[ 6., 2.],
[10., 1.],
[10., 2.],
[10., 0.],
[12., 0.]])
I am very interested in KBAT. Can you provide the best hyper-parameter for each dataset after correcting the test leakage problem? Thanks a lot. Moreover, have you done any work at SpGAT+ConvE? I'm trying to do this. But the results are not good enough on UMLS and Kinship.
Hi Zhiqing, Shikhar,
I was trying to run RotatE baselines.
I got this error,
UnboundLocalError: local variable 'positive_arg' referenced before assignment
I could see in the model.py file 'positive_arg' is defined before its usage. Could you please let me know if I am missing something obvious?
Thanks for your help!
when I run the code of KBAT, it raises an error that can not find the file entity2vec.txt, where can I find that file , or just revise the pre_embed to be false default?
Hi, I'm really interested in your paper A Re-evaluation of Knowledge Graph Completion Methods
in 2020ACL which is excellent work. But I find it hard to understand your meaning about figure 3. May I ask your explanations about figure 3? In other words,:
relu
function, can we use prelu
instead to improve the performance?请问您完善的代码在哪个文件,暂时没有找到,谢谢
I used the following command to run the code:
python conve.py -name reprod_fb15k_237 -data FB15k-237 -gpu 0 -eval_type random
Error after 1 epoch:
Traceback (most recent call last):
File "conve.py", line 318, in <module>
model.fit()
File "conve.py", line 250, in fit
val_results = self.evaluate('valid', epoch)
File "conve.py", line 139, in evaluate
left_results, left_scores = self.predict(split=split, mode='tail_batch')
File "conve.py", line 158, in predict
pred, zero_cnt = self.model.forward(sub, rel, None, zero_cnt=True)
TypeError: forward() got multiple values for argument 'zero_cnt'
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