[Score API] Hoist query placeholder scan and specialize PositionalEmbeds stacking (#23513)

Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

python/sglang/srt/managers/embed_types.py

@@ -41,11 +41,17 @@ class PositionalEmbeds:
     positions: List[int]
 
     def __post_init__(self):
-        # Stack list of tensors into a single [N, hidden_dim] tensor
+        # Normalize list of tensors into a single [N, hidden_dim] tensor.
+        # Dispatch by element rank to avoid a per-element unsqueeze.
         if isinstance(self.embeds, list):
-            self.embeds = torch.cat(
-                [e if e.dim() == 2 else e.unsqueeze(0) for e in self.embeds], dim=0
-            )
+            if not self.embeds:
+                self.embeds = torch.cat(self.embeds, dim=0)  # raises — empty is invalid
+            elif self.embeds[0].dim() == 1:
+                # [hidden_dim] elements → stack adds the leading dim.
+                self.embeds = torch.stack(self.embeds, dim=0)
+            else:
+                # [1, hidden_dim] (already has the leading dim) → plain concat.
+                self.embeds = torch.cat(self.embeds, dim=0)
         if self.embeds.shape[0] != len(self.positions):
             raise ValueError(
                 f"embeds length ({self.embeds.shape[0]}) != "

python/sglang/srt/managers/tokenizer_manager_score_mixin.py

@@ -416,6 +416,16 @@ class TokenizerManagerScoreMixin:
             query_embed_overrides is not None or item_embed_overrides is not None
         )
 
+        # Query placeholder positions are invariant across items — resolve once.
+        # (No-op returning ([], []) if has_embeds is False or query_embed_overrides is None.)
+        q_embeds, q_positions = self._resolve_overrides_for_sequence(
+            query,
+            query_embed_overrides,
+            embed_override_token_id,
+            position_offset=0,
+            label="query",
+        )
+
         if use_multi_item_scoring:
             # Multi-item scoring: concatenate with placeholder delimiter token.
             # Positions are derived from item lengths (delimiter_indices), not
@@ -429,33 +439,27 @@ class TokenizerManagerScoreMixin:
             if not has_embeds:
                 return None, input_ids, None, delimiter_indices
 
-            # Resolve embed overrides across the combined multi-item-scoring sequence
-            all_embeds: List[torch.Tensor] = []
-            all_positions: List[int] = []
+            # Resolve embed overrides across the combined multi-item-scoring sequence.
+            all_embeds: List[torch.Tensor] = list(q_embeds)
+            all_positions: List[int] = list(q_positions)
             current_offset = len(query) + 1  # +1 for first delimiter
             for i, item in enumerate(items):
                 item_embs = item_embed_overrides[i] if item_embed_overrides else None
-                pe = self._resolve_embed_overrides_for_request(
-                    query if i == 0 else [],  # only resolve query overrides once
+                i_embeds, i_positions = self._resolve_overrides_for_sequence(
                     item,
-                    embed_override_token_id,
-                    query_embed_overrides if i == 0 else None,
                     item_embs,
-                    current_offset,
-                    f"items[{i}]",
+                    embed_override_token_id,
+                    position_offset=current_offset,
+                    label=f"items[{i}]",
                 )
-                if pe is not None:
-                    # pe.embeds is a stacked tensor after PositionalEmbeds.__post_init__
-                    all_embeds.append(pe.embeds)
-                    all_positions.extend(pe.positions)
+                all_embeds.extend(i_embeds)
+                all_positions.extend(i_positions)
                 current_offset += len(item) + 1  # +1 for delimiter
 
             if all_embeds:
+                # PositionalEmbeds.__post_init__ does the single torch.cat stack.
                 positional_embed_overrides = [
-                    PositionalEmbeds(
-                        embeds=torch.cat(all_embeds, dim=0),
-                        positions=all_positions,
-                    )
+                    PositionalEmbeds(embeds=all_embeds, positions=all_positions)
                 ]
             else:
                 positional_embed_overrides = None
@@ -472,25 +476,34 @@ class TokenizerManagerScoreMixin:
                 return None, input_ids, None, None
 
             positional_embed_overrides = []
+            any_overrides = False
             for i, item in enumerate(items):
                 item_embs = item_embed_overrides[i] if item_embed_overrides else None
-                pe = self._resolve_embed_overrides_for_request(
-                    query,
+                i_embeds, i_positions = self._resolve_overrides_for_sequence(
                     item,
-                    embed_override_token_id,
-                    query_embed_overrides,
                     item_embs,
-                    item_position_offset=len(query),
-                    item_label=f"items[{i}]",
+                    embed_override_token_id,
+                    position_offset=len(query),
+                    label=f"items[{i}]",
                 )
-                positional_embed_overrides.append(pe)
+                combined_embeds = q_embeds + i_embeds
+                if combined_embeds:
+                    positional_embed_overrides.append(
+                        PositionalEmbeds(
+                            embeds=combined_embeds,
+                            positions=q_positions + i_positions,
+                        )
+                    )
+                    any_overrides = True
+                else:
+                    positional_embed_overrides.append(None)
 
-            positional_embed_overrides = (
-                positional_embed_overrides
-                if any(pe is not None for pe in positional_embed_overrides)
-                else None
+            return (
+                None,
+                input_ids,
+                positional_embed_overrides if any_overrides else None,
+                None,
             )
-            return None, input_ids, positional_embed_overrides, None
 
     # ------------------------------------------------------------------
     # Main entry point