[Refactor][OutputProcessor 2/8]: OmniRequestOutput should inherit RequestOutput and no nested wrap-up (#5146)

Signed-off-by: Boao Shi <aoibosh@connect.hku.hk>
Signed-off-by: bowieshi <aoibosh@connect.hku.hk>
Signed-off-by: princepride <wangzhipeng628@gmail.com>
Signed-off-by: R2-Y <ruiruyang2@gmail.com>
Signed-off-by: amy-why-3459 <wuhaiyan17@huawei.com>
Signed-off-by: Shi Boao Bowie <aoibosh@connect.hku.hk>
Co-authored-by: 汪志鹏 <wangzhipeng628@gmail.com>
Co-authored-by: ruirui(rein) yang <73573651+R2-Y@users.noreply.github.com>
Co-authored-by: amy-why-3459 <wuhaiyan17@huawei.com>
Co-authored-by: Gao Han <hgaoaf@connect.ust.hk>
Co-authored-by: Hongsheng Liu <liuhongsheng4@huawei.com>

tests/diffusion/batching/test_diffusion_batching.py

@@ -125,7 +125,7 @@ def _extract_images(output: OmniRequestOutput) -> list:
         return output.images
     # When the output comes from the orchestrator pipeline, images may be
     # nested inside request_output.
-    inner = getattr(output, "request_output", None)
+    inner = output
     if inner is not None and hasattr(inner, "images") and inner.images:
         return inner.images
     return []

tests/diffusion/cache/test_teacache.py

@@ -56,10 +56,10 @@ def test_teacache(model_name: str):
         # Extract images from request_output['images']
         first_output = outputs[0]
         assert first_output.final_output_type == "image"
-        if not hasattr(first_output, "request_output") or not first_output.request_output:
+        if not isinstance(first_output, OmniRequestOutput) or not first_output:
             raise ValueError("No request_output found in OmniRequestOutput")
 
-        req_out = first_output.request_output
+        req_out = first_output
         if not isinstance(req_out, OmniRequestOutput) or not hasattr(req_out, "images"):
             raise ValueError("Invalid request_output structure or missing 'images' key")
 

tests/diffusion/distributed/test_sequence_parallel.py

@@ -131,7 +131,7 @@ def _run_inference(
             elapsed_ms = (time.time() - start) * 1000
 
             return InferenceResult(
-                images=outputs[0].request_output.images,
+                images=outputs[0].images,
                 elapsed_ms=elapsed_ms,
             )
     finally:

tests/diffusion/distributed/test_tensor_parallel.py

@@ -49,10 +49,10 @@ def _diff_metrics(a: Image.Image, b: Image.Image) -> tuple[float, float]:
 def _extract_single_image(outputs) -> Image.Image:
     first_output = outputs[0]
     assert first_output.final_output_type == "image"
-    if not hasattr(first_output, "request_output") or not first_output.request_output:
+    if not isinstance(first_output, OmniRequestOutput) or not first_output:
         raise ValueError("No request_output found in OmniRequestOutput")
 
-    req_out = first_output.request_output
+    req_out = first_output
     if not isinstance(req_out, OmniRequestOutput) or not hasattr(req_out, "images"):
         raise ValueError("Invalid request_output structure or missing 'images' key")
 

tests/diffusion/lora/test_diffusion_lora.py

@@ -29,10 +29,10 @@ def test_diffusion_model(tmp_path: Path, omni_runner):
             raise ValueError("Empty outputs from Omni.generate()")
         first_output = outputs[0]
         assert first_output.final_output_type == "image"
-        if not hasattr(first_output, "request_output") or not first_output.request_output:
+        if not isinstance(first_output, OmniRequestOutput) or not first_output:
             raise ValueError("No request_output found in OmniRequestOutput")
 
-        req_out = first_output.request_output
+        req_out = first_output
         if not isinstance(req_out, OmniRequestOutput) or not hasattr(req_out, "images"):
             raise ValueError("Invalid request_output structure or missing 'images' key")
         return req_out.images

tests/diffusion/offloader/test_diffusion_cpu_offload.py

@@ -122,8 +122,8 @@ def test_cpu_offload_diffusion_model(model_name: str):
     print(f"No offload peak memory: {no_offload_peak_memory} MB")
 
     if model_name == "stabilityai/stable-audio-open-1.0":
-        audio_offload = output_offload[0].request_output.multimodal_output.get("audio")
-        audio_no_offload = output_no_offload[0].request_output.multimodal_output.get("audio")
+        audio_offload = output_offload[0].multimodal_output.get("audio")
+        audio_no_offload = output_no_offload[0].multimodal_output.get("audio")
         check_audio_determinism(audio_offload, audio_no_offload, atol=1e-2)
 
     # Set platform-specific VRAM saving thresholds to account

tests/diffusion/offloader/test_diffusion_layerwise_offload.py

@@ -20,18 +20,10 @@ IMAGE_VIDEO_MODELS = {
 
 MODELS = {**AUDIO_MODEL, **IMAGE_VIDEO_MODELS}
 
-LAYERWISE_MODEL_CASES = [
-    pytest.param(
-        "stabilityai/stable-audio-open-1.0",
-        marks=[pytest.mark.full_model, pytest.mark.diffusion],
-        id="stable_audio",
-    ),
-    pytest.param(
-        "riverclouds/qwen_image_random",
-        marks=[pytest.mark.core_model, pytest.mark.diffusion],
-        id="qwen_image_random",
-    ),
-]
+MODEL_MARKS = {
+    "riverclouds/qwen_image_random": pytest.mark.core_model,
+    "stabilityai/stable-audio-open-1.0": pytest.mark.full_model,
+}
 
 AUDIO_MODEL_PARAMS = {
     "runner_params": {},
@@ -101,8 +93,9 @@ def run_inference(
     return peak, output
 
 
+@pytest.mark.diffusion
 @hardware_test(res={"cuda": "L4", "rocm": "MI325"})
-@pytest.mark.parametrize("model_name", LAYERWISE_MODEL_CASES)
+@pytest.mark.parametrize("model_name", list(MODELS.keys()))
 def test_layerwise_offload_diffusion_model(model_name: str):
     """Test that layerwise offloading reduces GPU memory usage.
 
@@ -134,8 +127,8 @@ def test_layerwise_offload_diffusion_model(model_name: str):
     print(f"No offload peak memory: {no_offload_peak_memory} MB")
 
     if model_name == "stabilityai/stable-audio-open-1.0":
-        audio_offload = output_offload[0].request_output.multimodal_output.get("audio")
-        audio_no_offload = output_no_offload[0].request_output.multimodal_output.get("audio")
+        audio_offload = output_offload[0].multimodal_output.get("audio")
+        audio_no_offload = output_no_offload[0].multimodal_output.get("audio")
         # Match the sibling cpu-offload test's tolerance: layerwise offload moves
         # blocks across the PCIe bus on a side stream, which can perturb cuBLAS
         # algorithm selection and produce ~ULP-level drift larger than 1e-3.

tests/diffusion/quantization/test_gguf_diffusion.py

@@ -94,8 +94,8 @@ def _generate_single_stage_image(
     if hasattr(first_output, "images") and first_output.images:
         images = first_output.images
     else:
-        assert hasattr(first_output, "request_output") and first_output.request_output
-        request_output = first_output.request_output
+        assert isinstance(first_output, OmniRequestOutput) and first_output
+        request_output = first_output
         if isinstance(request_output, list):
             req_out = request_output[0]
         else:

tests/diffusion/quantization/test_quantization_fp8.py

@@ -88,8 +88,8 @@ def _generate_single_stage_image(
         if hasattr(first_output, "images") and first_output.images:
             images = first_output.images
         else:
-            assert hasattr(first_output, "request_output") and first_output.request_output
-            request_output = first_output.request_output
+            assert isinstance(first_output, OmniRequestOutput) and first_output
+            request_output = first_output
             if isinstance(request_output, list):
                 req_out = request_output[0]
             else:
@@ -147,10 +147,10 @@ def _generate_single_stage_video(
 
         first = outputs[0]
 
-        # Unwrap pipeline-style outputs (multi-stage / OmniRequestOutput.request_output).
+        # Unwrap pipeline-style outputs (multi-stage / OmniRequestOutput).
         frames: Any = None
-        if hasattr(first, "request_output") and isinstance(first.request_output, list):
-            inner = first.request_output[0]
+        if isinstance(first, OmniRequestOutput) and isinstance(first, list):
+            inner = first[0]
             if isinstance(inner, OmniRequestOutput) and inner.images:
                 frames = inner.images[0]
         if frames is None and hasattr(first, "images") and first.images:
@@ -234,8 +234,8 @@ def _generate_bagel_image(
             if images := getattr(req_output, "images", None):
                 generated_image = images[0]
                 break
-            if hasattr(req_output, "request_output") and req_output.request_output:
-                stage_outputs = req_output.request_output
+            if isinstance(req_output, OmniRequestOutput) and req_output:
+                stage_outputs = req_output
                 if not isinstance(stage_outputs, list):
                     stage_outputs = [stage_outputs]
                 for stage_out in stage_outputs:
@@ -250,8 +250,8 @@ def _generate_bagel_image(
 
         # Check LLM stage output — should have finish_reason=stop (not length)
         for req_output in omni_outputs:
-            if hasattr(req_output, "request_output") and req_output.request_output:
-                stage_outputs = req_output.request_output
+            if isinstance(req_output, OmniRequestOutput) and req_output:
+                stage_outputs = req_output
                 if not isinstance(stage_outputs, list):
                     stage_outputs = [stage_outputs]
                 for stage_out in stage_outputs:

tests/diffusion/quantization/test_quantization_quality.py

@@ -310,7 +310,7 @@ def _generate_image(omni, config: QualityTestConfig):
     first = outputs[0]
     if hasattr(first, "images") and first.images:
         return first.images[0], peak_mem
-    inner = first.request_output
+    inner = first
     if inner is not None and hasattr(inner, "images") and inner.images:
         return inner.images[0], peak_mem
     raise ValueError("Could not extract image from output.")
@@ -341,15 +341,15 @@ def _generate_video(omni, config: QualityTestConfig):
     )
 
     peak_mem = torch.accelerator.max_memory_allocated() / (1024**3)
-    first = outputs[0]
-    if hasattr(first, "request_output") and isinstance(first.request_output, list):
-        inner = first.request_output[0]
-        if isinstance(inner, OmniRequestOutput) and hasattr(inner, "images"):
-            frames = inner.images[0] if inner.images else None
-        else:
-            frames = inner
-    elif hasattr(first, "images") and first.images:
-        frames = first.images[0]
+    if isinstance(outputs, list) and isinstance(outputs[0], OmniRequestOutput):
+        first = outputs[0]
+    elif isinstance(outputs, OmniRequestOutput):
+        first = outputs
+    else:
+        raise ValueError("Could not extract video frames from output.")
+
+    if hasattr(first, "images"):
+        frames = first.images[0] if first.images else None
     else:
         raise ValueError("Could not extract video frames from output.")
 
@@ -444,11 +444,11 @@ def test_benchmark_generate_image_unwraps_nested_omni_request_output(monkeypatch
 
     image = Image.new("RGB", (2, 2))
     inner = OmniRequestOutput.from_diffusion(request_id="req", images=[image])
-    outer = OmniRequestOutput(
+    outer = OmniRequestOutput.from_stage_output(
+        inner,
         request_id="req",
         stage_id=0,
         final_output_type="image",
-        request_output=inner,
         finished=True,
     )
 

tests/diffusion/quantization/test_trajectory_similarity_tool.py

@@ -73,11 +73,9 @@ def test_run_summary_reports_worker_peak_memory():
     assert summary["per_run_peak_memory_mb"] == [100.0, 150.0]
 
 
-def test_request_peak_memory_prefers_inner_diffusion_output():
-    inner = type("InnerOutput", (), {"peak_memory_mb": 321.0})()
-    outer = type("OuterOutput", (), {"request_output": inner, "peak_memory_mb": 123.0})()
-
-    assert _request_peak_memory_mb(outer) == 321.0
+def test_request_peak_memory_reads_peak_memory_mb_directly():
+    result = type("Output", (), {"peak_memory_mb": 123.0})()
+    assert _request_peak_memory_mb(result) == 123.0
 
 
 def test_metric_guidance_describes_thresholds():

tests/diffusion/test_diffusion_streaming_output.py

@@ -273,7 +273,7 @@ class TestPipelineStreamingOutputToEntrypoint:
             await _wait_for(lambda: len(pipeline.requests) == 1)
             assert pipeline.requests[0].request_id.startswith("req-omni-")
             assert [output.multimodal_output["metadata"]["stream"]["chunk"] for output in outputs] == [0, 1]
-            assert [getattr(output.request_output, "finished", output.finished) for output in outputs] == [False, True]
+            assert [output.finished for output in outputs] == [False, True]
         finally:
             await self._shutdown_pipeline_omni_harness(omni, fixture, inline_client)