Fix survival calculation in cifs_from_exponential_logits: broadcast mask for compatibility with tensor shapes

2026-01-10 11:42:03 +08:00
parent f231a2e4e5
commit f795aa5604
1 changed files with 3 additions and 2 deletions
--- a/evaluate_models.py
+++ b/evaluate_models.py
@@ -342,8 +342,9 @@ def cifs_from_exponential_logits(
        return cif

    survival = torch.exp(-total_h * taus_t).squeeze(1)  # (B,H)
-    survival = torch.where(total.squeeze(1) > 0, survival,
-                           torch.ones_like(survival))
+    # Broadcast mask (B,) -> (B,1) for torch.where with (B,H) tensors.
+    nonzero = (total.squeeze(1) > 0).unsqueeze(1)
+    survival = torch.where(nonzero, survival, torch.ones_like(survival))
    return cif, survival