5f465041619a63bf1de99c55d1298865bf70fd9e,embed.py,,async_eval,#Any#Any#Any#Any#,38
 
Before Change
            "loss": loss,
            "sqnorm_min": sqnorms.min().item(),
            "sqnorm_avg": sqnorms.mean().item(),
            "sqnorm_max": sqnorms.max().item(),
            "mean_rank": meanrank,
            "map_rank": maprank
        }
After Change
        elif opt.eval == "hypernymy":
            lmsg = hypernymy_eval(epoch, elapsed, loss, pth, best)
        else:
            raise ValueError(f"Unrecognized evaluation: {opt.eval}")
        best = lmsg if lmsg["best"] else best
        logQ.put((lmsg, pth))

In pattern: SUPERPATTERN
Frequency: 3
Non-data size: 4
Instances
 Project Name: facebookresearch/poincare-embeddings
 Commit Name: 5f465041619a63bf1de99c55d1298865bf70fd9e
 Time: 2020-01-07
 Author: mattle@fb.com
 File Name: embed.py
 Class Name: 
 Method Name: async_eval
 Project Name: pytorch/ignite
 Commit Name: 62f82c45fff316da25968228502f2960b4d14b95
 Time: 2020-12-22
 Author: uribgp@gmail.com
 File Name: ignite/metrics/recall.py
 Class Name: Recall
 Method Name: update
 Project Name: pytorch/ignite
 Commit Name: 62f82c45fff316da25968228502f2960b4d14b95
 Time: 2020-12-22
 Author: uribgp@gmail.com
 File Name: ignite/metrics/precision.py
 Class Name: Precision
 Method Name: update