[Main2Main] Upgrade vLLM to 0303 (#6944)

### What this PR does / why we need it?
break:
- https://github.com/vllm-project/vllm/pull/34102 
Disable_full param replaced with valid_modes/invalid_modes API
- https://github.com/vllm-project/vllm/pull/35503
Now must return float compilation_time
- https://github.com/vllm-project/vllm/pull/35564
New sequence_lengths param added
- https://github.com/vllm-project/vllm/pull/33807
A check was performed (if runner_backend != "auto")
- https://github.com/vllm-project/vllm/pull/34861
`BaseDeviceCommunicator` now accesses PyTorch's internal `pg_map` to
check process group state
- https://github.com/vllm-project/vllm/pull/35274

**Important change:**
- https://github.com/vllm-project/vllm/pull/28672

`matcher_utils` directly accesses `torch.ops._C.*` during the import
phase. In the Ascend environment, some unregistered ops trigger
`AttributeError`, causing e2e initialization failure.

https://github.com/vllm-project/vllm-ascend/actions/runs/22607260487/job/65502047131#step:10:2323

https://github.com/vllm-project/vllm/blob/main/vllm/compilation/passes/fusion/matcher_utils.py#L29

This PR adds temporary compatibility placeholders (rms_norm,
fused_add_rms_norm, rotate_embedding, static/dynamic fp8 quant,
silu_and_mul) to
`vllm_ascend/patch/platform/patch_fusion_matcher_compat_ops.py` to
ensure no crashes during the import phase. Upstream repairs will be
considered later.

### Does this PR introduce _any_ user-facing change?

### How was this patch tested?

- vLLM version: v0.16.0
- vLLM main:
15d76f74e2

---------

Signed-off-by: MrZ20 <2609716663@qq.com>
Signed-off-by: gcanlin <canlinguosdu@gmail.com>
Co-authored-by: Meihan-chen <jcccx.cmh@gmail.com>
Co-authored-by: Claude Code <noreply@anthropic.com>
Co-authored-by: gcanlin <canlinguosdu@gmail.com>

tests/ut/distributed/test_communicator.py

@@ -44,7 +44,8 @@ class TestNPUCommunicator(unittest.TestCase):
         gather_sizes = [2, 2]
         input_ = torch.tensor([10, 20, 30, 40])
 
-        comm = NPUCommunicator(cpu_group=dist.group.WORLD)
+        with patch.dict(dist.distributed_c10d._world.pg_map, {dist.group.WORLD: MagicMock()}, clear=False):
+            comm = NPUCommunicator(cpu_group=dist.group.WORLD)
 
         output = comm.all_to_all(input_,
                                  scatter_sizes=scatter_sizes,
@@ -84,7 +85,8 @@ class TestNPUCommunicator(unittest.TestCase):
 
         input_ = torch.tensor([[10, 20], [30, 40]])
 
-        comm = NPUCommunicator(cpu_group=dist.group.WORLD)
-        output = comm.all_to_all(input_, scatter_dim=0, gather_dim=0)
+        with patch.dict(dist.distributed_c10d._world.pg_map, {dist.group.WORLD: MagicMock()}, clear=False):
+            comm = NPUCommunicator(cpu_group=dist.group.WORLD)
+            output = comm.all_to_all(input_, scatter_dim=0, gather_dim=0)
 
         assert output.tolist() == [[10, 20], [50, 60]]