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执行命令“ bash scripts/run_wn18rr.sh /log 0”,后报错:Traceback (most recent call last): File "/root/LERP-main/graph_completion/src/eval/evaluate.py", line 89, in <module> evaluate() File "/root/LERP-main/graph_completion/src/eval/evaluate.py", line 33, in evaluate lines = [l.strip().split(",") for l in open(option.preds).readlines()] FileNotFoundError: [Errno 2] No such file or directory: './log/WN18RR/test_predictions.txt'

经在lerp同级目录中新建了log文件夹。
请问这个报错如何解决呢?是缺少文件吗

On data sets with many relationships, does the memory usage of the model increase exponentially?

Many thanks to the author for such excellent work!

I would like to ask the author whether he has tried the FB15K-237 data set? I was going to experiment with this data set and found that the GPU memory fluctuated greatly when the model was running. Even the 80G A100 could not be fully trained and could only be trained for a short period of time.

I would like to ask the author why this happens. Will the memory gradually accumulate?

Parameters for reproducing experimental results

Hi there. I'm really impressed with your work.

I was wondering if you could share the config you used in your experiments as I am trying to reproduce the experiments in your paper.

Thanks again for all your hard work.

How to interprete generated rules

Hi, I tried to generate rules after training with the LERP training script you uploaded. I got the following results, can you tell me how to interpret them?

Also, after training on WN18 and WN18RR datasets, how can I check the trained rules?

script:

for i in range(option.rank):
    print(learner.lerp.interpret_rule(j, i, [*data.relation_to_number.keys()]))

for i in range(option.width):
    print(learner.lerp.interpret_lerp(-1, i,  [*data.relation_to_number.keys()]))

generated rules:

1 brother 
(1.6279151624268816e-15, 'X(AND aunt^T)--daughter--father^T(AND Not(son^T))') 
(2.116390064830938e-20, 'X(AND uncle)--brother^T(AND daughter^T)--nephew(AND sister)') 
(9.526430003514366e-17, 'X(AND Not(aunt^T))--wife--wife^T(AND Not(mother))--sister^T') 
(1.3220911569078453e-05, 'X--daughter^T--nephew') 
(1.6444326225356957e-15, 'X(AND Not(mother))--nephew^T(AND uncle--niece)') 
(1.6161735402420163e-05, 'X--uncle--daughter') 
(4.633622290229241e-19, 'X(AND Not(wife))--father(AND Not(nephew))(AND Not(son))') 
(6.584387202135389e-11, 'X(AND And(son, husband))') 
(4.159390922901551e-23, 'X(AND And(mother, uncle^T))--mother(AND Not(uncle))(AND Not(son^T))--sister^T') 
(5.01396240336089e-14, 'X(AND Not(son^T))(AND sister--nephew^T)') 

If you can tell me how to extract the trained rules and interpret them, it will be very helpful for me to find the rules in the dataset.

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