Hi, I got some questions with this code. I converted the part0_train and part1_test parts of the MS1M data set into npy files as you described in the readme. The feature files were directly converted into npy files after l2 regularization and label file reading. And I followed the steps suggested by the readme. In the end, I only calculated the pairwise indicator (sim_thres was set to increase from 0.5 to 0.8 in steps of 0.05), but the results kept prompting that ave_pre was 0, ave_rec and fscore were nan. , I would like to ask how to solve this situation?
By the way, when running the faiss_search.sh file, since my GPU is not compatible with faiss-gpu, I used faiss-cpu to solve this problem.
Environment
GPU A100
CUDA 11.0
Python3.6 or Python 3.9
torch 1.7.1+cu110 or torch 1.10.1
Problem Description
Hi, I got some questions with this code. I converted the part0_train and part1_test parts of the MS1M data set into npy files as you described in the readme. The feature files were directly converted into npy files after l2 regularization and label file reading. And I followed the steps suggested by the readme. In the end, I only calculated the pairwise indicator (sim_thres was set to increase from 0.5 to 0.8 in steps of 0.05), but the results kept prompting that ave_pre was 0, ave_rec and fscore were nan. , I would like to ask how to solve this situation?
By the way, when running the faiss_search.sh file, since my GPU is not compatible with faiss-gpu, I used faiss-cpu to solve this problem.
Environment
GPU A100 CUDA 11.0 Python3.6 or Python 3.9 torch 1.7.1+cu110 or torch 1.10.1