[V1][PP] Support pp with ray backend in V1 (#1800)

### What this PR does / why we need it?
Support pipeline parallel with ray backend in V1Engine.

Fixes #1751

### Does this PR introduce _any_ user-facing change?
Users could specify ray as distributed backend when inferencing with pp

### How was this patch tested?
CI passed with new added test.


- vLLM version: v0.9.2
- vLLM main:
32142b3c62

---------

Signed-off-by: MengqingCao <cmq0113@163.com>

tests/e2e/multicard/test_pipeline_parallel.py

@@ -24,6 +24,7 @@ MODELS = [
 
 TENSOR_PARALLELS = [2]
 PIPELINE_PARALLELS = [2]
+DIST_EXECUTOR_BACKEND = ["mp", "ray"]
 
 prompts = [
     "Hello, my name is",
@@ -34,10 +35,13 @@ prompts = [
 @pytest.mark.parametrize("model", MODELS)
 @pytest.mark.parametrize("tp_size", TENSOR_PARALLELS)
 @pytest.mark.parametrize("pp_size", PIPELINE_PARALLELS)
-def test_models(model: str, tp_size: int, pp_size: int) -> None:
+@pytest.mark.parametrize("distributed_executor_backend", DIST_EXECUTOR_BACKEND)
+def test_models(model: str, tp_size: int, pp_size: int,
+                distributed_executor_backend: str) -> None:
     with VllmRunner(model,
                     tensor_parallel_size=tp_size,
                     pipeline_parallel_size=pp_size,
+                    distributed_executor_backend=distributed_executor_backend,
                     enforce_eager=True,
                     gpu_memory_utilization=0.7) as vllm_model:
         vllm_model.generate_greedy(prompts, 64)