[bugfix][npugraph_ex]duplicate pattern issue (#6513)

### What this PR does / why we need it?
When the draft model also uses vllmbackend for graph compilation, the
fusion pass registration occurs again, resulting in errors due to
duplicate patterns.
### Does this PR introduce _any_ user-facing change?

### How was this patch tested?

- vLLM version: v0.15.0
- vLLM main: https://github.com/vllm-project/vllm/commit/v0.15.0

---------

Signed-off-by: chencangtao <chencangtao@huawei.com>
Co-authored-by: chencangtao <chencangtao@huawei.com>

vllm_ascend/compilation/npugraph_ex_passes/graphex_allreduce_rmsnorm_fusion_pass.py

@@ -23,7 +23,10 @@ from vllm.config.compilation import Range
 from vllm.distributed import get_tensor_model_parallel_world_size, tensor_model_parallel_all_reduce
 from vllm.distributed.parallel_state import get_tp_group
 
-from vllm_ascend.compilation.npugraph_ex_passes.utils.npugraph_ex_utils_check import extra_stream_scope_check
+from vllm_ascend.compilation.npugraph_ex_passes.utils.npugraph_ex_utils_check import (
+    check_and_register_fusion_pass,
+    extra_stream_scope_check,
+)
 
 # computation-communication tiling block is 512
 ALLREDUCE_NORM_FUSE_THREHOLD = 512
@@ -143,8 +146,8 @@ class GraphEXLastLayerMatmulAllReduceAddRMSNormPattern:
 
 class GraphEXMatmulAllReduceAddRMSNormPass:
     def __init__(self, vllm_config: VllmConfig):
-        GraphEXMiddleLayerMatmulAllReduceAddRMSNormPattern(vllm_config).register()
-        GraphEXLastLayerMatmulAllReduceAddRMSNormPattern(vllm_config).register()
+        check_and_register_fusion_pass(GraphEXMiddleLayerMatmulAllReduceAddRMSNormPattern, vllm_config=vllm_config)
+        check_and_register_fusion_pass(GraphEXLastLayerMatmulAllReduceAddRMSNormPattern, vllm_config=vllm_config)
 
     def __call__(self, graph: torch.fx.Graph):
         pass

vllm_ascend/compilation/npugraph_ex_passes/graphex_norm_quant_fusion_pass.py

@@ -22,7 +22,10 @@ from vllm.config import VllmConfig
 from vllm.config.compilation import Range
 from vllm.logger import logger
 
-from vllm_ascend.compilation.npugraph_ex_passes.utils.npugraph_ex_utils_check import extra_stream_scope_check
+from vllm_ascend.compilation.npugraph_ex_passes.utils.npugraph_ex_utils_check import (
+    check_and_register_fusion_pass,
+    extra_stream_scope_check,
+)
 
 
 class GraphEXAddRMSNormQuantPattern:
@@ -301,10 +304,10 @@ class GraphEXAddRMSNormFusionPass:
 
         common_epsilons = [1e-5, 1e-6]
         for eps in common_epsilons:
-            GraphEXAddRMSNormQuantPattern(vllm_config, eps=eps).register()
-            GraphEXAddRMSNormQuantPatternWithBias(vllm_config, eps=eps).register()
-            GraphEXAddRMSNormQuantSPPattern(vllm_config, eps=eps).register()
-            GraphEXAddRMSNormQuantSPPatternWithBias(vllm_config, eps=eps).register()
+            check_and_register_fusion_pass(GraphEXAddRMSNormQuantPattern, vllm_config=vllm_config, eps=eps)
+            check_and_register_fusion_pass(GraphEXAddRMSNormQuantPatternWithBias, vllm_config=vllm_config, eps=eps)
+            check_and_register_fusion_pass(GraphEXAddRMSNormQuantSPPattern, vllm_config=vllm_config, eps=eps)
+            check_and_register_fusion_pass(GraphEXAddRMSNormQuantSPPatternWithBias, vllm_config=vllm_config, eps=eps)
 
     def __call__(self, graph: torch.fx.Graph):
         pass

vllm_ascend/compilation/npugraph_ex_passes/graphex_qknorm_rope_fusion_pass.py

@@ -23,7 +23,10 @@ from vllm.config import VllmConfig, get_layers_from_vllm_config
 from vllm.config.compilation import Range
 from vllm.logger import logger
 
-from vllm_ascend.compilation.npugraph_ex_passes.utils.npugraph_ex_utils_check import extra_stream_scope_check
+from vllm_ascend.compilation.npugraph_ex_passes.utils.npugraph_ex_utils_check import (
+    check_and_register_fusion_pass,
+    extra_stream_scope_check,
+)
 
 
 class GraphEXQKNormRopeFusionPattern:
@@ -202,20 +205,22 @@ class GraphEXQKNormRopeFusionPass:
             if layer.head_size != 128:
                 logger.debug("QKNorm and Rope fusion not enabled: head_dim %d is not equal of 128", layer.head_size)
                 continue
-            GraphEXQKNormRopeFusionPattern(
+            check_and_register_fusion_pass(
+                GraphEXQKNormRopeFusionPattern,
                 vllm_config=vllm_config,
                 head_dim=layer.head_size,
                 num_heads=layer.num_heads,
                 num_kv_heads=layer.num_kv_heads,
                 eps=epsilon,
-            ).register()
-            GraphEXQKNormRopeFusionPatternWithBias(
+            )
+            check_and_register_fusion_pass(
+                GraphEXQKNormRopeFusionPatternWithBias,
                 vllm_config=vllm_config,
                 head_dim=layer.head_size,
                 num_heads=layer.num_heads,
                 num_kv_heads=layer.num_kv_heads,
                 eps=epsilon,
-            ).register()
+            )
 
     def __call__(self, graph: torch.fx.Graph):
         pass

vllm_ascend/compilation/npugraph_ex_passes/utils/npugraph_ex_utils_check.py

@@ -51,3 +51,25 @@ def extra_stream_scope_check(match: Match) -> bool:
         return False
 
     return True
+
+
+_register_patterns = set()
+
+
+def check_and_register_fusion_pass(pattern_class: type, **kwargs):
+    global _register_patterns
+    eps = kwargs.get("eps", 1e-6)
+    pattern_key = str(pattern_class.__name__) + str(eps)
+    if pattern_key in _register_patterns:
+        return
+
+    pattern = pattern_class(**kwargs)
+    try:
+        pattern.register()
+        _register_patterns.add(pattern_key)
+    except RuntimeError as e:
+        if "Duplicate pattern" in str(e):
+            logger.warning(f"Pattern {pattern_class.__name__} eps {eps} has been registered")
+            _register_patterns.add(pattern_key)
+        else:
+            raise e