I have a somewhat silly use case. I'm running retriever.retrieve, with a queries dict with only 1 entry. However, this causes an IndexError with pytorch due to how pytorch indexes 2D arrays where the first dim is of size 1:
File "<dir>/script.py", line 83, in <module>
results = retriever.retrieve(para_d, one_query_d)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "<env>/beir/retrieval/evaluation.py", line 20, in retrieve
return self.retriever.search(corpus, queries, self.top_k, self.score_function, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "<env>/beir/retrieval/search/dense/exact_search.py", line 73, in search
scores_dim = cos_scores[1]
~~~~~~~~~~^^^
IndexError: index 1 is out of bounds for dimension 0 with size 1
I was able to fix this by changing the below line:
|
cos_scores_top_k_values, cos_scores_top_k_idx = torch.topk(cos_scores, min(top_k+1, len(cos_scores[1])), dim=1, largest=True, sorted=return_sorted) |
And swapping out cos_scores[1] with scores_dim:
scores_dim = cos_scores[1] if cos_scores.shape[0] != 1 else cos_scores[0]
This monkey patch works for me, but I'm just curious if there's a more appropriate way to retrieve given only 1 query. Thanks!
I have a somewhat silly use case. I'm running
retriever.retrieve, with aqueriesdict with only 1 entry. However, this causes an IndexError with pytorch due to how pytorch indexes 2D arrays where the first dim is of size 1:I was able to fix this by changing the below line:
beir/beir/retrieval/search/dense/exact_search.py
Line 73 in f062f03
And swapping out
cos_scores[1]withscores_dim:This monkey patch works for me, but I'm just curious if there's a more appropriate way to retrieve given only 1 query. Thanks!