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model.recommend(user_label, sparse_user_items[user_label])
IndexError Traceback (most recent call last) Cell In[33], line 1 ----> 1 model.recommend(user_label, sparse_user_items[user_label])
File ~\anaconda3\Lib\site-packages\implicit\cpu\matrix_factorization_base.py:79, in MatrixFactorizationBase.recommend(self, userid, user_items, N, filter_already_liked_items, filter_items, recalculate_user, items) 76 if items is not None: 77 filter_query_items = _filter_items_from_sparse_matrix(items, filter_query_items) ---> 79 ids, scores = topk( 80 item_factors, 81 user, 82 N, 83 filter_query_items=filter_query_items, 84 filter_items=filter_items, 85 num_threads=self.num_threads, 86 ) 88 if np.isscalar(userid): 89 ids, scores = ids[0], scores[0]
File topk.pyx:32, in implicit.cpu.topk.topk()
File topk.pyx:54, in implicit.cpu.topk._topk_batch()
IndexError: index 977 is out of bounds for axis 1 with size 944
for the reference: #535
The text was updated successfully, but these errors were encountered:
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model.recommend(user_label, sparse_user_items[user_label])
IndexError Traceback (most recent call last)
Cell In[33], line 1
----> 1 model.recommend(user_label, sparse_user_items[user_label])
File ~\anaconda3\Lib\site-packages\implicit\cpu\matrix_factorization_base.py:79, in MatrixFactorizationBase.recommend(self, userid, user_items, N, filter_already_liked_items, filter_items, recalculate_user, items)
76 if items is not None:
77 filter_query_items = _filter_items_from_sparse_matrix(items, filter_query_items)
---> 79 ids, scores = topk(
80 item_factors,
81 user,
82 N,
83 filter_query_items=filter_query_items,
84 filter_items=filter_items,
85 num_threads=self.num_threads,
86 )
88 if np.isscalar(userid):
89 ids, scores = ids[0], scores[0]
File topk.pyx:32, in implicit.cpu.topk.topk()
File topk.pyx:54, in implicit.cpu.topk._topk_batch()
IndexError: index 977 is out of bounds for axis 1 with size 944
for the reference: #535
The text was updated successfully, but these errors were encountered: