- src/tsmm/train/losses.py:
* lm_loss(logits, labels): shifted masked CE (answer span only); clean 0.0
when all positions masked.
* infonce_contrastive_loss(z1, z2): symmetric CLIP-style InfoNCE in TS-
embedding space; positive = original vs light-augmentation view.
- tests/test_losses.py: 9 tests. 100 tests passing.
Spec clarification (small tier): InfoNCE operates in TS-embedding space
(encoder/projector output) rather than answer-embedding space; light
augmentations are positives. T3.3 strong-perturbation sensitivity is a
separate downstream check.
张宗平