[Refactor] Refactor Spec Decode (#2668)

### What this PR does / why we need it?
Refactor spec decode

### Does this PR introduce _any_ user-facing change?
N/A

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


- vLLM version: v0.10.1.1
- vLLM main:
6997a25ac6

---------

Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
Signed-off-by: Icey <1790571317@qq.com>
Co-authored-by: wangxiyuan <wangxiyuan1007@gmail.com>

vllm_ascend/spec_decode/interface.py

@@ -0,0 +1,51 @@
+import enum
+from typing import Optional
+
+import torch
+from vllm.config import VllmConfig
+from vllm.v1.core.sched.output import SchedulerOutput
+from vllm.v1.sample.metadata import SamplingMetadata
+from vllm.v1.spec_decode.metadata import SpecDecodeMetadata
+
+
+class SpecDcodeType(enum.Enum):
+    NGRAM = 0
+    EAGLE = 1
+    EAGLE3 = 2
+    MTP = 4
+
+
+class Proposer:
+
+    def __init__(self,
+                 vllm_config: VllmConfig,
+                 device: torch.device = None,
+                 runner=None):
+        pass
+
+    def load_model(self, model):
+        """Called by load_model in model_runner"""
+        raise NotImplementedError
+
+    @torch.inference_mode()
+    def dummy_run(self,
+                  num_tokens: int,
+                  with_prefill: bool = False,
+                  skip_attn: bool = False,
+                  num_reqs: int = 0,
+                  num_tokens_across_dp: Optional[torch.Tensor] = None):
+        """Called by dummy_run in modle_runner"""
+        raise NotImplementedError
+
+    def generate_token_ids(self,
+                           valid_sampled_token_ids: list[list[int]],
+                           sampling_metadata: SamplingMetadata = None,
+                           scheduler_output: SchedulerOutput = None,
+                           spec_decode_metadata: SpecDecodeMetadata = None,
+                           positions: torch.Tensor = None,
+                           num_scheduled_tokens: int = 0,
+                           hidden_states: torch.Tensor = None,
+                           attn_metadata=None,
+                           aux_hidden_states: torch.Tensor = None):
+        """Called by execute_model in model_runner"""
+        raise NotImplementedError