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Add dist_mode parameter to evaluate_landmark_auc for improved flexibility in evaluation

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Jiarui Li
2026-06-22 09:40:08 +08:00
parent 615f395058
commit 56421eb3f5
1 changed files with 6 additions and 2 deletions
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8
evaluate_auc_v2.py
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@@ -1138,6 +1138,7 @@ def evaluate_landmark_auc(
disease_ids: Sequence[int],
disease_chunk_size: int,
score_mode: str,
dist_mode: str,
horizons: np.ndarray,
device: torch.device,
model_target_mode: str,
@@ -1208,7 +1209,8 @@ def evaluate_landmark_auc(
death_token_ids=np.asarray(
landmark_dataset.death_token_ids, dtype=np.int64),
dist_mode=dist_mode,
model_death_idx=int(getattr(model, "death_idx", dataset.vocab_size - 1)),
model_death_idx=int(getattr(
model, "death_idx", getattr(model, "vocab_size", 1) - 1)),
)
nested = [_eval_token(t) for t in tqdm(
tasks, desc=f"AUC chunk {chunk_idx}", leave=False, dynamic_ncols=True)]
@@ -1236,7 +1238,8 @@ def evaluate_landmark_auc(
np.asarray(landmark_dataset.death_token_ids,
dtype=np.int64),
dist_mode,
int(getattr(model, "death_idx", dataset.vocab_size - 1)),
int(getattr(
model, "death_idx", getattr(model, "vocab_size", 1) - 1)),
),
) as ex:
nested = list(
@@ -1607,6 +1610,7 @@ def main() -> None:
disease_ids=disease_ids,
disease_chunk_size=disease_chunk_size,
score_mode=score_mode,
dist_mode=dist_mode,
horizons=horizons,
device=device,
model_target_mode=model_target_mode,