[BugFix][VLM] keep Qwen3-VL MoE inference deepstack order (#34690)

test/registered/vlm/test_vision_openai_server_a.py

@@ -4,9 +4,13 @@ python3 -m unittest test_vision_openai_server.TestOpenAIVisionServer.test_mixed_
 python3 -m unittest test_vision_openai_server.TestOpenAIVisionServer.test_multi_images_chat_completion
 """
 
+import base64
+import io
+import re
 import unittest
 
 import openai
+from PIL import Image, ImageDraw
 
 from sglang.srt.environ import envs
 from sglang.test.ci.ci_register import register_cuda_ci
@@ -28,6 +32,34 @@ from sglang.test.vlm_utils import (
 register_cuda_ci(est_time=560, stage="base-b", runner_config="1-gpu-large")
 
 
+# --- Qwen3-VL grounding regression (deepstack fusion) --------------------------
+# Guards Qwen3MoeLLMModel.forward: deepstack (multi-scale ViT features) injection
+# must keep its original inference order. PR #14636 rerouted it through
+# post_residual_addition (for RL on-policy / FSDP), which is FP-order-sensitive
+# and regresses FP8 visual grounding (the predicted point drifts by ~150+ px).
+_GROUNDING_IMG_SIZE = 1000
+# Target box in pixels; on a 1000x1000 canvas this equals the 0-1000 normalized
+# coordinate, so the check is robust to normalized-vs-pixel conventions.
+_GROUNDING_BOX = (620, 180, 880, 360)  # (x0, y0, x1, y1), center (750, 270)
+_GROUNDING_MARGIN = 60
+_GROUNDING_SYSTEM = (
+    "You are a UI grounding model. Treat the image as a 1000x1000 normalized "
+    "coordinate system with the top-left at (0,0) and the bottom-right at "
+    "(1000,1000). Return the geometric center of the requested element. "
+    "Output ONLY one coordinate in the form (x, y) and nothing else."
+)
+_GROUNDING_COORD_RE = re.compile(r"\(?\s*(\d{1,4})\s*,\s*(\d{1,4})\s*\)?")
+
+
+def _make_grounding_image() -> str:
+    """White canvas with a single red box at _GROUNDING_BOX; base64 data URI."""
+    img = Image.new("RGB", (_GROUNDING_IMG_SIZE, _GROUNDING_IMG_SIZE), (255, 255, 255))
+    ImageDraw.Draw(img).rectangle(_GROUNDING_BOX, fill=(220, 30, 30))
+    buf = io.BytesIO()
+    img.save(buf, format="PNG")
+    return "data:image/png;base64," + base64.b64encode(buf.getvalue()).decode("utf-8")
+
+
 class TestLlavaServer(ImageOpenAITestMixin):
     model = "lmms-lab/llava-onevision-qwen2-0.5b-ov"
 
@@ -52,6 +84,47 @@ class TestQwen3VLServer(ImageOpenAITestMixin, VideoOpenAITestMixin):
         with envs.SGLANG_MM_FEATURE_CACHE_MB.override(512):
             super().setUpClass()
 
+    def test_deepstack_grounding_hits_target_box(self):
+        # Regression guard for the Qwen3-VL MoE deepstack fusion order: the
+        # predicted point must land inside the target box; a deepstack corruption
+        # drifts it out (see PR #14636).
+        client = openai.Client(api_key=self.api_key, base_url=self.base_url)
+        response = client.chat.completions.create(
+            model="default",
+            messages=[
+                {"role": "system", "content": _GROUNDING_SYSTEM},
+                {
+                    "role": "user",
+                    "content": [
+                        {
+                            "type": "image_url",
+                            "image_url": {"url": _make_grounding_image()},
+                        },
+                        {
+                            "type": "text",
+                            "text": "Point at the center of the red rectangle.",
+                        },
+                    ],
+                },
+            ],
+            temperature=0,
+            **(self.get_vision_request_kwargs()),
+        )
+        out = response.choices[0].message.content
+        match = _GROUNDING_COORD_RE.search(out or "")
+        self.assertIsNotNone(match, f"could not parse a coordinate from: {out!r}")
+        x, y = int(match.group(1)), int(match.group(2))
+        x0, y0, x1, y1 = _GROUNDING_BOX
+        inside = (x0 - _GROUNDING_MARGIN <= x <= x1 + _GROUNDING_MARGIN) and (
+            y0 - _GROUNDING_MARGIN <= y <= y1 + _GROUNDING_MARGIN
+        )
+        self.assertTrue(
+            inside,
+            f"grounding output {out!r} -> ({x}, {y}) fell outside target box "
+            f"{_GROUNDING_BOX} (margin {_GROUNDING_MARGIN}); deepstack fusion "
+            f"likely regressed grounding.",
+        )
+
 
 class TestQwen2VLContextLengthServer(CustomTestCase):
     # --context-length 300 is calibrated to this model's mm-token expansion: