[Feature] support aclgraph for model runner v2 (#7110)

### What this PR does / why we need it?
This PR aims to support aclgraph for model runner v2, please see RFC
#5208. The PR contains these modifications:
- adapt to newest commit of vllm main branch.
- supply a unified interface of extra forward context for both model
runner v1 and model runner v2.
- implement graph mode for main model. 

### Does this PR introduce _any_ user-facing change?
no

### How was this patch tested?

- vLLM version: v0.16.0
- vLLM main:
4034c3d32e

---------

Signed-off-by: Ronald1995 <ronaldautomobile@163.com>

vllm_ascend/_310p/fused_moe/fused_moe.py

@@ -18,12 +18,11 @@ from collections.abc import Callable
 
 import torch
 from vllm.distributed import get_dp_group, get_ep_group, get_tp_group
-from vllm.forward_context import get_forward_context
 from vllm.model_executor.layers.fused_moe.config import FusedMoEConfig
 from vllm.model_executor.layers.fused_moe.layer import FusedMoE, UnquantizedFusedMoEMethod
 from vllm.model_executor.layers.fused_moe.shared_fused_moe import SharedFusedMoE
 
-from vllm_ascend.ascend_forward_context import MoECommType
+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
@@ -93,7 +92,7 @@ class AscendUnquantizedFusedMoEMethod310(UnquantizedFusedMoEMethod):
 
         topk_weights = topk_weights.to(x.dtype)
 
-        moe_comm_method = get_forward_context().moe_comm_method
+        moe_comm_method = _EXTRA_CTX.moe_comm_method
         final_hidden_states = moe_comm_method.fused_experts(
             hidden_states=x,
             w1=layer.w13_weight,
@@ -222,9 +221,8 @@ class AscendFusedMoE310(FusedMoE):
     ) -> torch.Tensor:
         assert self.quant_method is not None
         assert self.routed_scaling_factor == 1.0, "routed_scaling_factor != 1.0 is not supported."
-        forward_context = get_forward_context()
 
-        hidden_states, router_logits, _, context_metadata = forward_context.moe_comm_method.prepare(
+        hidden_states, router_logits, _, context_metadata = _EXTRA_CTX.moe_comm_method.prepare(
             hidden_states=hidden_states, router_logits=router_logits, quant_type=self.quant_type
         )
 
@@ -246,7 +244,7 @@ class AscendFusedMoE310(FusedMoE):
             apply_router_weight_on_input=self.apply_router_weight_on_input,
         )
 
-        routed_out = forward_context.moe_comm_method.finalize(
+        routed_out = _EXTRA_CTX.moe_comm_method.finalize(
             hidden_states=fused_experts_results.routed_out,
             reduce_results=self.reduce_results,
             context_metadata=context_metadata,

vllm_ascend/_310p/fused_moe/moe_comm_method.py

@@ -16,8 +16,8 @@
 from __future__ import annotations
 
 import torch
-from vllm.forward_context import get_forward_context
 
+from vllm_ascend.ascend_forward_context import _EXTRA_CTX
 from vllm_ascend.ops.fused_moe.moe_comm_method import AllGatherCommImpl, FusedExpertsResult
 
 from .moe_mlp import unified_apply_mlp
@@ -50,7 +50,7 @@ class AllGatherCommImpl310(AllGatherCommImpl):
     ) -> FusedExpertsResult:
         # This method is overridden to use the 310p-specific unified_apply_mlp
         # which provides optimized MLP computation for the 310p platform
-        moe_comm_method = get_forward_context().moe_comm_method
+        moe_comm_method = _EXTRA_CTX.moe_comm_method
         assert moe_comm_method is not None, "Missing communication context"
 
         dispatch_results = self.token_dispatcher.token_dispatch(

vllm_ascend/_310p/quantization/methods/w8a8_dynamic.py

@@ -21,9 +21,9 @@ from typing import Any
 import torch
 from vllm.config import get_current_vllm_config
 from vllm.distributed import get_ep_group
-from vllm.forward_context import get_forward_context
 
 from vllm_ascend._310p.fused_moe.experts_selector import select_experts
+from vllm_ascend.ascend_forward_context import _EXTRA_CTX
 from vllm_ascend.ops.fused_moe.experts_selector import zero_experts_compute
 from vllm_ascend.quantization.methods.base import AscendMoEScheme, QuantType
 
@@ -125,7 +125,7 @@ class AscendW8A8DynamicFusedMoEMethod310(AscendMoEScheme):
 
         topk_weights = topk_weights.to(self.in_dtype)
 
-        moe_comm_method = get_forward_context().moe_comm_method
+        moe_comm_method = _EXTRA_CTX.moe_comm_method
 
         final_hidden_states = moe_comm_method.fused_experts(
             hidden_states=x,