[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/ops/linear.py

@@ -44,7 +44,8 @@ class AscendUnquantizedLinearMethod(UnquantizedLinearMethod):
 
     def process_weights_after_loading(self, layer: torch.nn.Module) -> None:
         super().process_weights_after_loading(layer)
-        if is_enable_nz() and torch.version.cann.startswith("8.3"):
+        if (is_enable_nz() and torch.version.cann.startswith("8.3") and
+                layer.weight.data.dtype in [torch.float16, torch.bfloat16]):
             layer.weight.data = torch_npu.npu_format_cast(
                 layer.weight.data, ACL_FORMAT_FRACTAL_NZ)