[diffusion] fix: fix Qwen-Image-Layered string image paths (#28790)

python/sglang/multimodal_gen/runtime/pipelines_core/stages/model_specific_stages/qwen_image_layered.py

@@ -56,6 +56,14 @@ def _seq_lens_from_optional_mask(
     return [int(x) for x in prompt_embeds_mask.sum(dim=1).tolist()]
 
 
+def _resolve_layered_image_path(image_path: str | list[str]) -> str:
+    if isinstance(image_path, str):
+        return image_path
+    if isinstance(image_path, list) and image_path:
+        return image_path[0]
+    raise ValueError("Qwen-Image-Layered requires a non-empty image_path.")
+
+
 # Copied from diffusers.pipelines.qwenimage.pipeline_qwenimage_edit_plus.calculate_dimensions
 def calculate_dimensions(target_area, ratio):
     width = math.sqrt(target_area * ratio)
@@ -490,7 +498,7 @@ the image\n<|vision_start|><|image_pad|><|vision_end|><|im_end|>\n<|im_start|>as
         generator = batch.generator
 
         assert batch.image_path is not None
-        image = load_image(batch.image_path[0])
+        image = load_image(_resolve_layered_image_path(batch.image_path))
         image = image.convert("RGBA")
         image_size = image.size
         resolution = server_args.pipeline_config.resolution

python/sglang/multimodal_gen/test/unit/test_disagg_roles.py

@@ -59,6 +59,7 @@ from sglang.multimodal_gen.runtime.pipelines_core.stages.model_specific_stages.m
 )
 from sglang.multimodal_gen.runtime.pipelines_core.stages.model_specific_stages.qwen_image_layered import (
     QwenImageLayeredBeforeDenoisingStage,
+    _resolve_layered_image_path,
     _resolve_text_encoder_dtype,
 )
 from sglang.multimodal_gen.runtime.server_args import set_global_server_args
@@ -429,6 +430,20 @@ class TestPipelineSpecificExtraModules(unittest.TestCase):
 
 
 class TestQwenImageLayeredDtype(_GlobalStageArgsMixin, unittest.TestCase):
+    def test_layered_image_path_accepts_string_and_list(self):
+        self.assertEqual(
+            _resolve_layered_image_path("/tmp/input.png"),
+            "/tmp/input.png",
+        )
+        self.assertEqual(
+            _resolve_layered_image_path(["/tmp/input.png"]),
+            "/tmp/input.png",
+        )
+
+    def test_layered_image_path_rejects_empty_list(self):
+        with self.assertRaisesRegex(ValueError, "non-empty image_path"):
+            _resolve_layered_image_path([])
+
     def test_text_encoder_dtype_uses_parameter_dtype_without_dtype_attr(self):
         text_encoder = torch.nn.Linear(1, 1, bias=False).to(dtype=torch.bfloat16)
         self.assertEqual(