I encountered a KeyError when running the data_redundancy.duplicates function on the WN18 dataset. The code works correctly with other datasets (e.g., FB13), but fails with WN18, and with my own KG as well, with the same error.
Here is the code that triggers the error:
from torchkge.utils.datasets import load_wn18
from torchkge.utils import data_redundancy
kg_train, kg_val, kg_test = load_wn18()
dups, reverse_dups = data_redundancy.duplicates(kg_train, kg_val, kg_test)
And the error:
{
"name": "KeyError",
"message": "18",
"stack": "---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
Cell In[5], line 5
2 from torchkge.utils import data_redundancy
4 kg_train, kg_val, kg_test = load_wn18()
----> 5 dups, reverse_dups = data_redundancy.duplicates(kg_train, kg_val, kg_test)
File ~/anaconda3/envs/benchmark/lib/python3.9/site-packages/torchkge/utils/data_redundancy.py:150, in duplicates(kg_tr, kg_val, kg_te, theta1, theta2, verbose, counts, reverses)
147 iter_ = list(combinations(range(1345), 2))
149 for r1, r2 in tqdm(iter_):
--> 150 a = len(T[r1].intersection(T[r2])) / lengths[r1]
151 b = len(T[r1].intersection(T[r2])) / lengths[r2]
153 if a > theta1 and b > theta2:
KeyError: 18"
}
Potential solution
To my understanding, this can be fixed by modifying:
iter_ = list(combinations(range(1345), 2))
to
iter_ = list(combinations(range(kg_tr.n_rel), 2))
Description
I encountered a KeyError when running the
data_redundancy.duplicatesfunction on the WN18 dataset. The code works correctly with other datasets (e.g., FB13), but fails with WN18, and with my own KG as well, with the same error.Here is the code that triggers the error:
And the error:
Potential solution
To my understanding, this can be fixed by modifying:
iter_ = list(combinations(range(1345), 2))toiter_ = list(combinations(range(kg_tr.n_rel), 2))