ABOUT PGPR baseline
Zxy0207 opened this issue · comments
When executing the adapted PGPR baseline, I had some problems;
I tried to use python main.py --dataset=ml1m --opt=soft --metrics=LIR/s_to_opt. and some other changes . However, they were all wrong
The wrong wae showen as follows:
main.py [-h] [--dataset DATASET] [--agent_topk AGENT_TOPK] [--opt OPT] [--alpha ALPHA] [--eval_baseline EVAL_BASELINE] [--log_enabled LOG_ENABLED] [--save_baseline_rec_quality_avgs SAVE_BASELINE_REC_QUALITY_AVGS]
[--save_baseline_exp_quality_avgs SAVE_BASELINE_EXP_QUALITY_AVGS] [--save_baseline_rec_quality_distributions SAVE_BASELINE_REC_QUALITY_DISTRIBUTIONS]
[--save_baseline_exp_quality_distributions SAVE_BASELINE_EXP_QUALITY_DISTRIBUTIONS] [--save_after_rec_quality_avgs SAVE_AFTER_REC_QUALITY_AVGS] [--save_after_exp_quality_avgs SAVE_AFTER_EXP_QUALITY_AVGS]
[--save_after_rec_quality_distributions SAVE_AFTER_REC_QUALITY_DISTRIBUTIONS] [--save_after_exp_quality_distributions SAVE_AFTER_EXP_QUALITY_DISTRIBUTIONS] [--save_overall SAVE_OVERALL]
main.py: error: unrecognized arguments: --metrics=SEP/s_to_opt
As the error says main.py: error: unrecognized arguments: --metrics=SEP/s_to_opt
The argument SEP/s_to_opt for the parameter --metrics is not supported. If you would like to optimize for SEP using the soft optimization you should specify when running --opt=soft --metrics=SEP
I just noticed the readme wasn't updated with the latest changes, I updated it according to the current parameters
Thank you very much. The problem has been solved