Re-enable 10k checkpoints — accumulates across T4 preemptions

scripts/cloud/embed_modal.py

@@ -210,8 +210,23 @@ def embed_year(year: str = "2022", model_name: str = "ViT-L-14",
         if len(batch_imgs) >= batch_size:
             flush_batch()
 
-        # Checkpointing disabled — push once at end to avoid upload timeouts
-        # causing function cancellation mid-scan
+        # Checkpoint every 10k to HF — accumulates progress across preemptions
+        current_boundary = len(all_ids) // 10000
+        if current_boundary > last_checkpoint_n:
+            _vecs_cp = np.vstack(all_vecs).astype(np.float32)
+            _norms_cp = np.linalg.norm(_vecs_cp, axis=1, keepdims=True)
+            _vecs_cp /= np.maximum(_norms_cp, 1e-8)
+            _df_cp = pd.DataFrame({"figure_id": list(all_ids), "embedding": list(_vecs_cp)})
+            _out_cp = f"/tmp/{year}_cp.parquet"
+            _df_cp.to_parquet(_out_cp, index=False)
+            HfApi(token=token).upload_file(
+                path_or_fileobj=_out_cp,
+                path_in_repo=f"embeddings/{year}_vitl14.parquet",
+                repo_id=OUT_REPO, repo_type="dataset",
+                commit_message=f"Checkpoint {len(all_ids):,} for {year}",
+            )
+            print(f"  Checkpoint: {len(all_ids):,} embeddings on HF")
+            last_checkpoint_n = current_boundary
 
     flush_batch()
     print(f"Scan complete: {n_processed:,} files scanned, {len(all_ids):,} embedded")