[Refactor][CI] Reorganize test tree, and move slow e2e to weekly (#4951)

Signed-off-by: wangyu <410167048@qq.com>

tests/diffusion/test_diffusion_engine.py

@@ -14,6 +14,7 @@ import torch
 from pytest_mock import MockerFixture
 
 import vllm_omni.diffusion.diffusion_engine as diffusion_engine_module
+from tests.helpers.mark import hardware_test
 from vllm_omni.diffusion.data import DiffusionOutput, OmniDiffusionConfig
 from vllm_omni.diffusion.diffusion_engine import (
     DiffusionEngine,
@@ -30,6 +31,8 @@ from vllm_omni.diffusion.sched.interface import (
 )
 from vllm_omni.inputs.data import OmniDiffusionSamplingParams
 
+pytestmark = [pytest.mark.core_model, pytest.mark.diffusion]
+
 
 @dataclass
 class DiffusionSchedulerOutput:
@@ -56,6 +59,8 @@ class MockScheduler:
     def __init__(self):
         self._waiting_queue = []
         self._step_id = 0
+        # Match RequestScheduler API used by request-batch admission wait.
+        self.max_num_running_reqs = 5
 
     def add_request(self, request):
         self._waiting_queue.append(request)
@@ -64,6 +69,12 @@ class MockScheduler:
     def has_requests(self):
         return len(self._waiting_queue) > 0
 
+    def num_waiting_requests(self) -> int:
+        return len(self._waiting_queue)
+
+    def num_running_requests(self) -> int:
+        return 0
+
     def schedule(self) -> DiffusionSchedulerOutput:
         if not self._waiting_queue:
             return DiffusionSchedulerOutput(step_id=self._step_id)
@@ -582,9 +593,7 @@ def test_move_tensor_tree_returns_non_tensor_values_unchanged() -> None:
     assert moved is value
 
 
-@pytest.mark.diffusion
-@pytest.mark.cuda
-@pytest.mark.skipif(not torch.cuda.is_available(), reason="CUDA required")
+@hardware_test(res={"cuda": "L4"}, num_cards=1)
 def test_move_tensor_tree_moves_nested_cuda_tensors_to_cpu() -> None:
     tensor = torch.arange(8, dtype=torch.float32, device="cuda")
     other = torch.arange(4, dtype=torch.int64, device="cuda")
@@ -610,6 +619,7 @@ async def _consume_final_output(generator):
     return final_output
 
 
+@pytest.mark.cpu
 @pytest.mark.asyncio
 async def test_async_add_req_and_stream_response():
     engine = object.__new__(DiffusionEngine)
@@ -621,13 +631,24 @@ async def test_async_add_req_and_stream_response():
     engine._cv = threading.Condition(engine._rpc_lock)
     engine._init_lock = asyncio.Lock()
     engine._closed = False
-    engine.od_config = SimpleNamespace(streaming_output=False)
+    # Enable admission wait so concurrent adds land in one schedule wave;
+    # otherwise the first request can execute alone (~1s) and the rest in a
+    # second wave (~2s), failing the latency-spread assertion.
+    engine.od_config = SimpleNamespace(
+        streaming_output=False,
+        request_batch_max_wait_ms=500.0,
+    )
     engine._loop_started = False
     engine.main_loop = None
-    engine.supports_request_batch = False
+    engine.supports_request_batch = True
+    engine.step_execution = False
     engine.execution_mode = DiffusionExecutionMode.REQUEST_BATCH
 
-    engine._finalize_finished_request = lambda rid, out, err: out.result
+    def _finalize(rid, out, err=None):
+        # Stream consumers stop on ``finished``; keep result_data for assertions.
+        return SimpleNamespace(result_data=out.result.result_data, finished=True)
+
+    engine._finalize_finished_request = _finalize
 
     def mock_execute_batch(sched_output):
         request_ids = sched_output.scheduled_request_ids