[Main2Main] Upgrade vllm commit to 0123 (#6169)

### What this PR does / why we need it?
1. ✅ Upgrade vllm commit to: 0115
(8471b27df97c3eb79f891802fc0e858f8f7ac6a0)
Modify import paths due to the refactors：
https://github.com/vllm-project/vllm/pull/32245
https://github.com/vllm-project/vllm/pull/32060
Test result:
https://github.com/vllm-project/vllm-ascend/actions/runs/21034239336/job/60490156965?pr=5913
2. ✅Upgrade vllm commit to: 0119
(9a1f16da1e423ede2c2f52a9850cbfbb39cefe96)
Fix `WorkerProc.__init__() missing 1 required positional argument:
'is_driver_worker'` due to
https://github.com/vllm-project/vllm/pull/28506
Test result:
https://github.com/vllm-project/vllm-ascend/actions/runs/21156263050/job/60841668755?5569
3. ✅Upgrade vllm commit to:
0120(148117ea2e689cd43df4be6892671a17cdae5833)
1. Add `skip_compiled` param in `set_forward_context` due to
https://github.com/vllm-project/vllm/pull/30385
2. Modify `tests/ut/spec_decode/test_eagle_proposer.py` due to
https://github.com/vllm-project/vllm/pull/24322
change `self.max_num_tokens =
vllm_config.scheduler_config.max_num_batched_tokens + max_batch_size`
3. Modify UT import paths due to the
refactors：https://github.com/vllm-project/vllm/pull/32060
Test result:
https://github.com/vllm-project/vllm-ascend/actions/runs/21204851770/job/60999046946
4. ✅Upgrade vllm commit to:
0121(f23fb5a7c1b61350c5c40ca1115d3bf8cf2b8cc9)
1. vLLM switched `uses_mrope` from target to draft model config, making
`positions`/`mrope_positions` mutually exclusive, breaking vllm-ascend's
direct self.positions access and tests missing
`draft_model_config.uses_mrope`.
https://github.com/vllm-project/vllm/pull/32048
2. Moved bs_to_padded_graph_size from CompilationConfig to
CudagraphDispatcher due to the refactor
https://github.com/vllm-project/vllm/pull/30143
3. Remove unused `maybe_setup_kv_connector` due to
https://github.com/vllm-project/vllm/pull/32077
Test result:
https://github.com/vllm-project/vllm-ascend/actions/runs/21217728738/job/61043738834
6. ✅Upgrade vllm commit to:
0122(8ebf271bb6d1e7e9b1a55be73d755ef1a57dbbe5)
Updating FusedMoEParallelConfig (added enable_eplb) and FusedMoEConfig
due to https://github.com/vllm-project/vllm/pull/32414
Test result:
https://github.com/vllm-project/vllm-ascend/actions/runs/21249922546/job/61148613054
8. ✅Upgrade vllm commit to:
0123(dc917cceb877dfd13f98c538c4c96158047d98bd)
Setting temperature=0.0 due to the removal of the default temperature
value in https://github.com/vllm-project/vllm/pull/32723
Test result:
https://github.com/vllm-project/vllm-ascend/actions/runs/21280796875
### Does this PR introduce _any_ user-facing change?

### How was this patch tested?

- vLLM version: v0.14.0
- vLLM main:
d68209402d

---------

Signed-off-by: wjunLu <wjunlu217@gmail.com>
Signed-off-by: Meihan-chen <jcccx.cmh@gmail.com>
Co-authored-by: wjunLu <wjunlu217@gmail.com>

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

@@ -109,8 +109,6 @@ def _run_worker_process(
             quantization="ascend" if "W8A8" in model_path else None,
             enable_expert_parallel=True if "DeepSeek" in model_path else False,
             trust_remote_code=True,
-            # vllm enables async scheduling by default, remove below when vllm >= 0.14.0
-            async_scheduling=False,
         )
 
         # Expose model config to the main test process
@@ -206,7 +204,8 @@ def test_models_aclgraph_capture_replay_metrics_dp2(
     # 2. Generation steps (max_tokens)
     # 3. Final step (likely EOS/idle step), no replay here
     total_steps = max_tokens + 1  # this includes the 1 and 2 above
-    expected_exec_model = (total_steps + 1) * dp_size
+    # vllm default enables Async scheduler, this will take 1 more steps
+    expected_exec_model = (total_steps + 1 + 1) * dp_size
 
     assert (
         num_execute_model == expected_exec_model

tests/e2e/multicard/2-cards/test_qwen3_performance.py

@@ -42,6 +42,7 @@ vllm_bench_cases = {
     "random_input_len": 128,
     "max_concurrency": 40,
     "random_output_len": 100,
+    "temperature": 0.0,
 }
 
 # NOTE: Any changes for the baseline throughput should be approved by team members.