[CI] Fix broken CI (#6599)

Revert
4fb3d5e1b2
it breaks E2E Test

- vLLM version: v0.15.0
- vLLM main:
d7e17aaacd

vllm_ascend/spec_decode/suffix_proposer.py

@@ -1,11 +1,13 @@
 import torch
 from vllm.config import CUDAGraphMode
-from vllm.v1.spec_decode.suffix_decoding import SuffixDecodingProposer as VllmSuffixDecodingProposer
+from vllm.v1.spec_decode.suffix_decoding import \
+    SuffixDecodingProposer as VllmSuffixDecodingProposer
 
 from vllm_ascend.spec_decode.interface import Proposer, SpecDcodeType
 
 
 class SuffixDecodingProposer(VllmSuffixDecodingProposer, Proposer):
+
     def __init__(self, vllm_config, device, runner):
         super().__init__(vllm_config)
         self.name = SpecDcodeType.SUFFIX
@@ -17,30 +19,27 @@ class SuffixDecodingProposer(VllmSuffixDecodingProposer, Proposer):
         pass
 
     @torch.inference_mode()
-    def dummy_run(
-        self,
-        num_tokens,
-        with_prefill=None,
-        in_graph_capturing=None,
-        num_reqs=None,
-        num_tokens_across_dp=None,
-        aclgraph_runtime_mode: CUDAGraphMode = CUDAGraphMode.NONE,
-        batch_descriptor=None,
-        dummy_compute_logits=lambda hidden_states: None,
-        is_profile=False,
-    ):
+    def dummy_run(self,
+                  num_tokens,
+                  with_prefill=None,
+                  in_graph_capturing=None,
+                  num_reqs=None,
+                  num_tokens_across_dp=None,
+                  aclgraph_runtime_mode: CUDAGraphMode = CUDAGraphMode.NONE,
+                  batch_descriptor=None,
+                  dummy_compute_logits=lambda hidden_states: None,
+                  is_profile=False):
         pass
 
-    def generate_token_ids(
-        self,
-        valid_sampled_token_ids,
-        sampling_metadata=None,
-        scheduler_output=None,
-        spec_decode_metadata=None,
-        positions=None,
-        num_scheduled_tokens=None,
-        hidden_states=None,
-        aux_hidden_states=None,
-    ) -> list[list[int]]:
-        draft_token_ids = self.propose(self.runner.input_batch, valid_sampled_token_ids)
+    def generate_token_ids(self,
+                           valid_sampled_token_ids,
+                           sampling_metadata=None,
+                           scheduler_output=None,
+                           spec_decode_metadata=None,
+                           positions=None,
+                           num_scheduled_tokens=None,
+                           hidden_states=None,
+                           aux_hidden_states=None) -> list[list[int]]:
+        draft_token_ids = self.propose(self.runner.input_batch,
+                                       valid_sampled_token_ids)
         return draft_token_ids