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