fix(verl): match rollout alpha compositing for RGBA images

agentlightning/verl/rollout_adapter.py

@@ -297,10 +297,10 @@ def _load_pil_image(url: str) -> Any:
 
     if url.startswith("data:"):
         _, _, payload = url.partition(",")
-        return Image.open(io.BytesIO(base64.b64decode(payload))).convert("RGB")
-    if url.startswith("file://"):
-        return Image.open(url2pathname(url.removeprefix("file:"))).convert("RGB")
-    if url.startswith(("http://", "https://")):
+        image_source = io.BytesIO(base64.b64decode(payload))
+    elif url.startswith("file://"):
+        image_source = url2pathname(url.removeprefix("file:"))
+    elif url.startswith(("http://", "https://")):
         # [multimodal-patch] Remote images are fetched from the trainer process with
         # content-type and size validation.
         import httpx
@@ -313,8 +313,17 @@ def _load_pil_image(url: str) -> Any:
         max_bytes = 50 * 1024 * 1024
         if len(response.content) > max_bytes:
             raise ValueError(f"[multimodal-patch] remote image exceeds {max_bytes} bytes")
-        return Image.open(io.BytesIO(response.content)).convert("RGB")
-    raise ValueError(f"[multimodal-patch] unsupported image url scheme: {url[:64]}")
+        image_source = io.BytesIO(response.content)
+    else:
+        raise ValueError(f"[multimodal-patch] unsupported image url scheme: {url[:64]}")
+
+    with Image.open(image_source) as image:
+        if image.mode == "RGBA":
+            # Match vLLM's default image decoding so rollout and training see the same pixels.
+            rgb_image = Image.new("RGB", image.size, (255, 255, 255))
+            rgb_image.paste(image, mask=image.getchannel("A"))
+            return rgb_image
+        return image.convert("RGB")
 
 
 def _build_multi_modal_inputs(processor: Any, image_urls: list[str]) -> tuple[dict[str, Any], bool]:

docs/80-example-multimodal-qa.md

@@ -18,6 +18,8 @@ The dataset is generated with PIL at startup — there is nothing to download:
 
 For images already stored on the trainer host, construct each `image_url` with `Path("images/frame 1.png").resolve().as_uri()` (from `pathlib`). Local file URIs preserve spaces, Unicode, and literal percent characters in filenames.
 
+RGBA images are composited onto a white background before training, matching vLLM's default image decoder. If your rollout server uses a custom `rgba_background_color`, pre-composite the images to RGB with that background before sending them so rollout and training use identical pixels.
+
 Any mrope VLM supported by verl works; pass `--model` to change the default model.
 
 ## Training

tests/verl/test_rollout_adapter.py

@@ -1087,3 +1087,41 @@ def raise_for_status(self) -> None:
 
     assert image.size == (2, 2)
     assert image.mode == "RGB"
+
+
+@pytest.mark.parametrize("scheme", ["data", "file", "https"])
+@pytest.mark.parametrize("mode", ["RGB", "RGBA"])
+def test_load_pil_image_matches_rollout_rgb_conversion(
+    tmp_path: Path, monkeypatch: pytest.MonkeyPatch, scheme: str, mode: str
+) -> None:
+    import httpx
+    from PIL import Image
+
+    source = Image.new(mode, (3, 1))
+    pixels = [(10, 20, 30), (10, 20, 30), (10, 20, 30)]
+    source.putdata(
+        [(*rgb, alpha) for rgb, alpha in zip(pixels, [0, 128, 255], strict=True)] if mode == "RGBA" else pixels
+    )
+    buffer = io.BytesIO()
+    source.save(buffer, format="PNG")
+    payload = buffer.getvalue()
+    if scheme == "data":
+        url = "data:image/png;base64," + base64.b64encode(payload).decode()
+    elif scheme == "file":
+        path = tmp_path / "transparent image.png"
+        path.write_bytes(payload)
+        url = path.as_uri()
+    else:
+        url = "https://example.com/transparent.png"
+        response = httpx.Response(
+            200, content=payload, headers={"content-type": "image/png"}, request=httpx.Request("GET", url)
+        )
+        monkeypatch.setattr(httpx, "get", lambda *args, **kwargs: response)
+
+    image = rollout_adapter_module._load_pil_image(url)
+
+    # vLLM composites RGBA onto white before producing rollout vision inputs.
+    expected = [(255, 255, 255), (132, 137, 142), (10, 20, 30)] if mode == "RGBA" else pixels
+    assert image.mode == "RGB"
+    assert image.size == (3, 1)
+    assert [image.getpixel((x, 0)) for x in range(3)] == expected