vlm: reject moss vision metadata mismatches (#31957)

python/sglang/srt/multimodal/processors/moss_vl.py

@@ -234,7 +234,15 @@ class MossVLImageProcessor(SGLangBaseProcessor):
             device=device,
         )
 
-        if len(flat_eff_h) == 0 or len(image_token_indices) == 0:
+        frame_count = len(flat_eff_h)
+        image_token_count = len(image_token_indices)
+        if frame_count != image_token_count:
+            raise ValueError(
+                "Moss-VL vision metadata must map one-to-one to image tokens: "
+                f"found {frame_count} frame(s) and {image_token_count} token(s)"
+            )
+
+        if frame_count == 0:
             rope_deltas = (
                 position_ids.max(dim=0).values.max(dim=-1).values
                 + 1
@@ -242,18 +250,11 @@ class MossVLImageProcessor(SGLangBaseProcessor):
             )
             return vision_pos_ids, position_ids, rope_deltas
 
-        num_matches = min(len(flat_eff_h), len(image_token_indices))
+        flat_eff_h = torch.tensor(flat_eff_h, device=device, dtype=torch.long)
-        flat_eff_h = torch.tensor(
+        flat_eff_w = torch.tensor(flat_eff_w, device=device, dtype=torch.long)
-            flat_eff_h[:num_matches], device=device, dtype=torch.long
+        flat_vis_starts = torch.tensor(flat_vis_starts, device=device, dtype=torch.long)
-        )
-        flat_eff_w = torch.tensor(
-            flat_eff_w[:num_matches], device=device, dtype=torch.long
-        )
-        flat_vis_starts = torch.tensor(
-            flat_vis_starts[:num_matches], device=device, dtype=torch.long
-        )
 
-        target_indices = image_token_indices[:num_matches]
+        target_indices = image_token_indices
         batch_rows = target_indices[:, 0]
         text_cols = target_indices[:, 1]
 

test/registered/unit/models/test_moss_vl_processor.py

@@ -0,0 +1,85 @@
+import re
+from types import SimpleNamespace
+
+import pytest
+import torch
+
+from sglang.srt.multimodal.processors.moss_vl import MossVLImageProcessor
+from sglang.test.ci.ci_register import register_cpu_ci
+
+register_cpu_ci(est_time=1, suite="base-a-test-cpu")
+
+
+def _vision_info(frame_count: int):
+    return [
+        {
+            "medias": [
+                {
+                    "num_frames": frame_count,
+                    "grid_h": 4,
+                    "grid_w": 4,
+                    "start": 0,
+                    "vision_tokens_per_frame": 4,
+                }
+            ]
+        }
+    ]
+
+
+def _processor():
+    processor = object.__new__(MossVLImageProcessor)
+    processor.image_token_id = 99
+    processor.hf_config = SimpleNamespace(
+        vision_config=SimpleNamespace(spatial_merge_size=2)
+    )
+    return processor
+
+
+@pytest.mark.parametrize(
+    ("input_ids", "frame_count", "expected_counts"),
+    [
+        ([[1, 99, 2]], 2, "2 frame(s) and 1 token(s)"),
+        ([[99, 99]], 1, "1 frame(s) and 2 token(s)"),
+        ([[1, 2]], 1, "1 frame(s) and 0 token(s)"),
+        ([[1, 99, 2]], 0, "0 frame(s) and 1 token(s)"),
+    ],
+)
+def test_moss_vl_rejects_vision_metadata_token_mismatch(
+    input_ids, frame_count, expected_counts
+):
+    processor = _processor()
+    input_ids = torch.tensor(input_ids)
+    position_ids = processor._compute_position_ids(input_ids)
+
+    with pytest.raises(ValueError, match=re.escape(expected_counts)):
+        processor._compute_vision_position_ids(
+            input_ids=input_ids,
+            position_ids=position_ids,
+            vision_token_info=_vision_info(frame_count),
+            max_vision_seq_len=16,
+            attention_mask=None,
+        )
+
+
+def test_moss_vl_accepts_matching_vision_metadata_and_tokens():
+    processor = _processor()
+    input_ids = torch.tensor([[1, 99, 2]])
+    position_ids = processor._compute_position_ids(input_ids)
+
+    vision_positions, updated_positions, rope_deltas = (
+        processor._compute_vision_position_ids(
+            input_ids=input_ids,
+            position_ids=position_ids,
+            vision_token_info=_vision_info(1),
+            max_vision_seq_len=16,
+            attention_mask=None,
+        )
+    )
+
+    assert vision_positions.shape == (3, 1, 16)
+    assert updated_positions.shape == position_ids.shape
+    assert rope_deltas.shape == (1,)
+
+
+if __name__ == "__main__":
+    raise SystemExit(pytest.main([__file__, "-v"]))