Hard negatives运行时一直卡顿，没有正常输出

[karong398]

运行命令 python -m FlagEmbedding.baai_general_embedding.finetune.hn_mine
--model_name_or_path '/Volumes/移动硬盘/ptrain/output/encoder_model'
--input_file toy_finetune_data.jsonl
--output_file toy_finetune_data_minedHN.jsonl
--range_for_sampling 1-200
--negative_number 15

非GPU运行时，一直卡顿在 _torch_pytree._register_pytree_node( inferencing embedding for corpus (number=15)-------------- inferencing embedding for queries (number=10)-------------- create index and search------------------

[karong398]

[ ](ur

[staoxiao]

@karong398 , if you have many candidates, searching using the CPU takes a lot of time. You can use GPUs or reduce the size of the corpus to speed up the searching process.