[Feature]refactor the npugraph_ex config, support online-infer with static kernel (#5775)

### What this PR does / why we need it?
This is a part of
https://github.com/vllm-project/vllm-ascend/issues/4715#issue-3694310762
1. refactor the npugraph_ex config，modified the default configuration of
the static kernel, new default value of static kernel is false
2. support online-infer with static kernel
3. fixed the issue where manually modifying FX graphs caused an abnormal
model return type, and removed the related redundant code.

### Does this PR introduce _any_ user-facing change?
yes，the new config of npugraph_ex is as follow:
```
additional_config={
            "npugraph_ex_config": {
                "enable": True,
                "enable_static_kernel": False
            }
        }
```
### How was this patch tested?
```
vllm serve /data/DeepSeek-V3.1-Terminus-w4a8 \
    --host 0.0.0.0 \
    --port 8004 \
    --data-parallel-size 4 \
    --tensor-parallel-size 4 \
    --quantization ascend \
    --seed 1024 \
    --served-model-name deepseek_v3 \
    --enable-expert-parallel \
    --max-num-seqs 48 \
    --max-model-len 40000 \
    --async-scheduling \
    --max-num-batched-tokens 9000 \
    --trust-remote-code \
    --no-enable-prefix-caching \
    --speculative-config '{"num_speculative_tokens": 3, "method":"deepseek_mtp","disable_padded_drafter_batch": false}' \
    --gpu-memory-utilization 0.9 \
    --compilation-config '{"cudagraph_capture_sizes":[4,32,64,112,160,176,192], "cudagraph_mode": "FULL_DECODE_ONLY"}' \
    --additional-config \
    '{"enable_shared_expert_dp": true,"multistream_overlap_shared_expert": true,"npugraph_ex_config":{"enable":true}}'
```

- vLLM version: v0.13.0
- vLLM main:
2f4e6548ef

---------

Signed-off-by: chencangtao <chencangtao@huawei.com>
Signed-off-by: ChenCangtao <50493711+ChenCangtao@users.noreply.github.com>
Co-authored-by: chencangtao <chencangtao@huawei.com>

vllm_ascend/compilation/compiler_interface.py

@@ -26,9 +26,10 @@ from torch._inductor.compile_fx import graph_returns_tuple, make_graph_return_tu
 from torch._inductor.decomposition import select_decomp_table
 from torch.fx import GraphModule
 from vllm.compilation.compiler_interface import CompilerInterface
+from vllm.config import VllmConfig
 from vllm.config.utils import Range
 
-from vllm_ascend.ascend_config import get_ascend_config
+from vllm_ascend.ascend_config import NpugraphExConfig, get_ascend_config
 from vllm_ascend.utils import COMPILATION_PASS_KEY
 
 
@@ -68,6 +69,8 @@ def npugraph_ex_compile(
     graph: fx.GraphModule,
     example_inputs: list[Any],
     compiler_config: dict[str, Any],
+    vllm_config: VllmConfig,
+    npugraph_ex_config: NpugraphExConfig,
     compile_range: Range,
     key: str | None = None,
 ) -> tuple[Callable | None, Any | None]:
@@ -85,7 +88,6 @@ def npugraph_ex_compile(
             tuple_node = fx_graph.create_node("call_function", tuple, args=([return_value],))
         output_node.args = (tuple_node,)
         graph.recompile()
-
     import torchair
 
     # TODO: use a better way to lazy register replacement, instead of import one by one
@@ -98,10 +100,24 @@ def npugraph_ex_compile(
     config.mode = "reduce-overhead"
     # execute FX graph in eager mode before graph mode to optimize FX graph.
     config.debug.run_eagerly = True
-    # static kernel switch, suitable for static shapes or scenes with less shape changes.
-    config.experimental_config.aclgraph._aclnn_static_shape_kernel = True
+    if npugraph_ex_config.enable_static_kernel:
+        config.experimental_config.aclgraph._aclnn_static_shape_kernel = True
+        # According to the cudagraph_capture_size configuration, set the shapes
+        # that can trigger the compilation of static kernel. If this configuration is
+        # not applied, new shapes will trigger the compilation of static kernels,
+        # affecting program execution.
+        num_spec_tokens = vllm_config.speculative_config.num_speculative_token if vllm_config.speculative_config else 0
+        uniform_decode_query_len = num_spec_tokens + 1
+        max_num_tokens = vllm_config.scheduler_config.max_num_seq * uniform_decode_query_len
+        decode_cudagraph_batch_sizes = [
+            x
+            for x in vllm_config.compilation_config.cudagraph_capture_size
+            if max_num_tokens >= x >= uniform_decode_query_len
+        ]
+        config.experimental_config.aclgraph._aclnn_static_shape_kernel_sym_value_range = decode_cudagraph_batch_sizes
 
     npugraph_ex = torchair.get_npu_backend(compiler_config=config)
+
     compile_graph = npugraph_ex(graph, example_inputs)
     return compile_graph, None
 
@@ -115,6 +131,12 @@ class AscendCompiler(CompilerInterface):
 
     name = "AscendCompiler"
 
+    def compute_hash(self, vllm_config: VllmConfig) -> str:
+        npugraph_ex_config = get_ascend_config().npugraph_ex_config
+        if npugraph_ex_config.enable:
+            self.vllm_config = vllm_config
+        return vllm_config.compute_hash()
+
     def compile(
         self,
         graph: fx.GraphModule,
@@ -123,8 +145,11 @@ class AscendCompiler(CompilerInterface):
         compile_range: Range,
         key: str | None = None,
     ) -> tuple[Callable | None, Any | None]:
-        ascend_config = get_ascend_config()
-        if ascend_config.enable_npugraph_ex:
-            return npugraph_ex_compile(graph, example_inputs, compiler_config, compile_range, key)
+        npugraph_ex_config = get_ascend_config().npugraph_ex_config
+        if npugraph_ex_config.enable:
+            assert hasattr(self, "vllm_config")
+            return npugraph_ex_compile(
+                graph, example_inputs, compiler_config, self.vllm_config, npugraph_ex_config, compile_range, key
+            )
         else:
             return fusion_pass_compile(graph, example_inputs, compiler_config, compile_range, key)