[feat][torchair] support super kernel feat for quantized dsr1 (#3485)

### What this PR does / why we need it?
Port #1916 and #2157 to master branch to fuse operators in deepseek moe
layers, which can reduce scheduling overhead on devices. Note that this
feature is valid only when `tp_size = 1` and
`multistream_overlap_shared_expert` is enabled with torchair graph mode.

### Does this PR introduce _any_ user-facing change?
Users can enable this feature with `--additional-config
'{"torchair_graph_config":{"enabled":true, "enable_super_kernel":true},
"multistream_overlap_shared_expert":true}'`.

### How was this patch tested?
E2E deepseek serving with 2P1D disaggregated prefill scenarios.


- vLLM version: v0.11.0rc3
- vLLM main: https://github.com/vllm-project/vllm/commit/v0.11.0

---------

Signed-off-by: linfeng-yuan <1102311262@qq.com>

vllm_ascend/torchair/utils.py

@@ -6,6 +6,7 @@ from dataclasses import dataclass
 
 import torch
 import torch_npu
+from torchair.scope import super_kernel as _super_kernel
 
 try:
     # Recent release of torchair has moved these ops to `.scope`.
@@ -231,3 +232,7 @@ def torchair_ops_patch():
     AscendRMSNorm.forward_oot = torchair_layernorm.torchair_rmsnorm_forward_oot  # type: ignore[method-assign]
     AscendSiluAndMul.forward_oot = torchair_activation.torchair_silu_and_mul_forward_oot  # type: ignore[method-assign]
     AscendVocabParallelEmbedding.forward = vocab_embedding_forward  # type: ignore[method-assign]
+
+
+def super_kernel(prefix: str, option: str, enabled: bool = True):
+    return _super_kernel(prefix, option) if enabled else nullcontext()