[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/ops/mla.py

@@ -32,6 +32,7 @@ from vllm.utils.torch_utils import direct_register_custom_op
 from vllm.v1.attention.backend import AttentionMetadata  # type: ignore
 
 from vllm_ascend.ascend_config import get_ascend_config
+from vllm_ascend.ascend_forward_context import _EXTRA_CTX
 
 
 class IndexerWrapper(nn.Module):
@@ -144,7 +145,7 @@ class AscendMultiHeadLatentAttention(MultiHeadLatentAttentionWrapper):
         kv_cache: torch.Tensor | None = None,
         attn_metadata: AttentionMetadata | None = None,
     ) -> torch.Tensor:
-        need_gather_q_kv = get_forward_context().flash_comm_v1_enabled
+        need_gather_q_kv = _EXTRA_CTX.flash_comm_v1_enabled
         output_shape = hidden_states.shape
         # FIXME: This does not seem right, should make sure the buffer is fixed
         output = torch.empty(output_shape, dtype=hidden_states.dtype, device=hidden_states.device)