[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/attention/sfa_v1.py

@@ -7,16 +7,20 @@ import vllm.envs as envs_vllm
 from torch import nn
 from vllm.config import VllmConfig, get_current_vllm_config
 from vllm.distributed import get_tensor_model_parallel_world_size, get_tp_group
-from vllm.forward_context import get_forward_context
 from vllm.logger import logger
 from vllm.model_executor.layers.attention.mla_attention import MLACommonMetadataBuilder
 from vllm.model_executor.layers.linear import UnquantizedLinearMethod
 from vllm.triton_utils import HAS_TRITON
-from vllm.v1.attention.backend import AttentionBackend, AttentionCGSupport, MLAAttentionImpl  # type: ignore
+from vllm.v1.attention.backend import (
+    AttentionBackend,  # type: ignore
+    AttentionCGSupport,
+    MLAAttentionImpl,
+)
 from vllm.v1.kv_cache_interface import AttentionSpec
 
 from vllm_ascend import envs
 from vllm_ascend.ascend_config import get_ascend_config
+from vllm_ascend.ascend_forward_context import _EXTRA_CTX
 from vllm_ascend.attention.attention_mask import AttentionMaskBuilder
 from vllm_ascend.attention.attention_v1 import AscendAttentionState
 from vllm_ascend.attention.context_parallel.common_cp import AscendPCPMetadata
@@ -967,10 +971,9 @@ class AscendSFAImpl(MLAAttentionImpl):
         output: torch.Tensor | None = None,
     ) -> torch.Tensor:
         assert output is not None, "Output tensor must be provided."
-        forward_context = get_forward_context()
         if attn_metadata is None:
             # Profiling run.
-            if self.enable_dsa_cp_with_layer_shard and not forward_context.in_profile_run:
+            if self.enable_dsa_cp_with_layer_shard and not _EXTRA_CTX.in_profile_run:
                 for layer in self.layer_sharding_kwargs or []:
                     if is_hidden_layer(layer):
                         reach_layer_for_shard_weight_series(layer)