[Version] Drop 0.16.0 support (#7153)

### What this PR does / why we need it?
Drop 0.16.0 support in main
- Fix eagle proposer break introduced by
https://github.com/vllm-project/vllm/pull/34552. Mainly change to use
the draft attention group to initialize the attention metadata builder.
- Fix the `ModelRunner` has no attribute `cudagraph_capture_sizes`
error, which is a bug in vLLM v0.17.0, and fixed by a later pr
https://github.com/vllm-project/vllm/pull/30515

- vLLM version: v0.16.0
- vLLM main:
4034c3d32e
---------
Signed-off-by: MengqingCao <cmq0113@163.com>

vllm_ascend/_310p/fused_moe/fused_moe.py

@@ -26,7 +26,6 @@ from vllm_ascend.ascend_forward_context import _EXTRA_CTX, MoECommType
 from vllm_ascend.ops.fused_moe.experts_selector import zero_experts_compute
 from vllm_ascend.ops.fused_moe.moe_comm_method import FusedExpertsResult, _MoECommMethods
 from vllm_ascend.quantization.methods.base import QuantType
-from vllm_ascend.utils import vllm_version_is
 
 from .experts_selector import select_experts
 from .moe_comm_method import AllGatherCommImpl310
@@ -152,25 +151,22 @@ class AscendFusedMoE310(FusedMoE):
         self.quant_type = self.get_quant_type()
 
         _MoECommMethods[MoECommType.ALLGATHER] = AllGatherCommImpl310(self.moe_config)
-        if not vllm_version_is("0.16.0"):
-            self.runner = self._init_runner()
+        self.runner = self._init_runner()
 
-    if not vllm_version_is("0.16.0"):
+    def _init_runner(self):
+        from vllm_ascend.ops.fused_moe.fused_moe import AscendMoERunner
 
-        def _init_runner(self):
-            from vllm_ascend.ops.fused_moe.fused_moe import AscendMoERunner
-
-            return AscendMoERunner(
-                layer=self,
-                moe_config=self.moe_config,
-                router=self.router,
-                routed_input_transform=self._routed_input_transform,
-                gate=self.gate,
-                shared_experts=self.shared_experts,
-                quant_method=self.quant_method,
-                reduce_results=self.reduce_results,
-                enable_dbo=self.vllm_config.parallel_config.enable_dbo,
-            )
+        return AscendMoERunner(
+            layer=self,
+            moe_config=self.moe_config,
+            router=self.router,
+            routed_input_transform=self._routed_input_transform,
+            gate=self.gate,
+            shared_experts=self.shared_experts,
+            quant_method=self.quant_method,
+            reduce_results=self.reduce_results,
+            enable_dbo=self.vllm_config.parallel_config.enable_dbo,
+        )
 
     def init_experts_map(self, moe_config):
         """