Main2main upgrade to vllm 0317 afternoon (#7409)

### What this PR does / why we need it?

1.fix "TypeError: get_attn_backend() remove variable": [Refactor
`check_and_update_config`](https://github.com/vllm-project/vllm/pull/35122)

2.fix [Rename `compile_ranges_split_points` to
`compile_ranges_endpoints`](https://github.com/vllm-project/vllm/pull/36027)

3.fix "RuntimeError: device_allocator not a DeviceAllocator":[Replace
memory related torch.cuda
APIs"](https://github.com/vllm-project/vllm/pull/37031)

4.fix [Support multiple KV groups in OffloadingSpec
](https://github.com/vllm-project/vllm/pull/36610) removed
self.offloaded_block_size and changed self.gpu_block_size from a scalar
to a tuple of per-group block sizes, adding block_size_factor.

5.fix [Consolidate
SupportsEagle](https://github.com/vllm-project/vllm/pull/36063) renamed
get_eagle3_aux_hidden_state_layers() to
get_eagle3_default_aux_hidden_state_layers() and added a
supports_eagle3() guard before calling it.

### Does this PR introduce _any_ user-facing change?
NA
### How was this patch tested?
E2E


- vLLM version: v0.17.0
- vLLM main:
8a680463fa

---------

Signed-off-by: leo-pony <nengjunma@outlook.com>
Co-authored-by: Claude Code <noreply@anthropic.com>

tests/e2e/multicard/2-cards/test_disaggregated_encoder.py

@@ -32,6 +32,12 @@ TENSOR_PARALLELS = [1]
 @pytest.mark.parametrize("model", MODELS)
 @pytest.mark.parametrize("tp_size", TENSOR_PARALLELS)
 async def test_models(model: str, tp_size: int) -> None:
+    from vllm_ascend.utils import vllm_version_is
+
+    if not vllm_version_is("0.17.0"):
+        pytest.skip(
+            "EPLB output is different without EPLB, see issue: https://github.com/vllm-project/vllm-ascend/issues/7408",
+        )
     encode_port = get_open_port()
     pd_port = get_open_port()
     vllm_server_args = [