[Cherry-Pick][RL] Add clear_graph_opt_backend for glm4_mtp (#7378) (#7379)

* add clear_grpah func

* fix spell

fastdeploy/model_executor/graph_optimization/decorator.py

@@ -92,7 +92,7 @@ class GraphOptWrapper:
     def __call__(self, **kwargs):
         return self.graph_opt_backend(**kwargs)
 
-    def clear_grpah_opt_backend(self, fd_config):
+    def clear_graph_opt_backend(self, fd_config):
         """ """
         # TODO(gongshaotian): Resolve the bug of static graphs not being able to update weights
         assert (

fastdeploy/model_executor/models/deepseek_v3.py

@@ -1306,9 +1306,9 @@ class DeepseekV3ForCausalLM(ModelForCasualLM):
         )
         return hidden_states
 
-    def clear_grpah_opt_backend(self):
+    def clear_graph_opt_backend(self):
         """Clear graph optimization backend, the captured cuda graph will be cleaned"""
-        self.model.clear_grpah_opt_backend(fd_config=self.fd_config)
+        self.model.clear_graph_opt_backend(fd_config=self.fd_config)
 
 
 class DeepSeekV3PretrainedModel(PretrainedModel):

fastdeploy/model_executor/models/ernie4_5_moe.py

@@ -701,9 +701,9 @@ class Ernie4_5_MoeForCausalLM(ModelForCasualLM):
 
         return hidden_states
 
-    def clear_grpah_opt_backend(self):
+    def clear_graph_opt_backend(self):
         """Clear graph optimization backend, the captured cuda graph will be cleaned"""
-        self.ernie.clear_grpah_opt_backend(fd_config=self.fd_config)
+        self.ernie.clear_graph_opt_backend(fd_config=self.fd_config)
 
 
 @ModelRegistry.register_model_class(

fastdeploy/model_executor/models/ernie4_5_vl/ernie4_5_vl_moe.py

@@ -829,9 +829,9 @@ class Ernie4_5_VLMoeForConditionalGeneration(ModelForCasualLM):
 
         return hidden_states
 
-    def clear_grpah_opt_backend(self):
+    def clear_graph_opt_backend(self):
         """Clear graph optimization backend, the captured cuda graph will be cleaned"""
-        self.ernie.clear_grpah_opt_backend(fd_config=self.fd_config)
+        self.ernie.clear_graph_opt_backend(fd_config=self.fd_config)
 
 
 class Ernie4_5_VLPretrainedModel(PretrainedModel):

fastdeploy/model_executor/models/glm4_moe.py

@@ -563,9 +563,9 @@ class Glm4MoeForCausalLM(ModelForCasualLM):
 
         return hidden_states
 
-    def clear_grpah_opt_backend(self):
+    def clear_graph_opt_backend(self):
         """Clear graph optimization backend, the captured cuda graph will be cleaned"""
-        self.model.clear_grpah_opt_backend(fd_config=self.fd_config)
+        self.model.clear_graph_opt_backend(fd_config=self.fd_config)
 
 
 class Glm4MoePretrainedModel(PretrainedModel):

fastdeploy/model_executor/models/glm4_mtp.py

@@ -369,3 +369,7 @@ class Glm4MTPForCausalLM(ModelForCasualLM):
         )
 
         return hidden_states
+
+    def clear_graph_opt_backend(self):
+        """Clear graph optimization backend, the captured cuda graph will be cleaned"""
+        self.model.clear_graph_opt_backend(fd_config=self.fd_config)

fastdeploy/model_executor/models/qwen2.py

@@ -417,9 +417,9 @@ class Qwen2ForCausalLM(ModelForCasualLM):
 
         return hidden_states
 
-    def clear_grpah_opt_backend(self):
+    def clear_graph_opt_backend(self):
         """Clear graph optimization backend, the captured cuda graph will be cleaned"""
-        self.qwen2.clear_grpah_opt_backend(fd_config=self.fd_config)
+        self.qwen2.clear_graph_opt_backend(fd_config=self.fd_config)
 
 
 class Qwen2PretrainedModel(PretrainedModel):

fastdeploy/model_executor/models/qwen3.py

@@ -341,9 +341,9 @@ class Qwen3ForCausalLM(ModelForCasualLM):
 
         return hidden_states
 
-    def clear_grpah_opt_backend(self):
+    def clear_graph_opt_backend(self):
         """Clear graph optimization backend, the captured cuda graph will be cleaned"""
-        self.model.clear_grpah_opt_backend(fd_config=self.fd_config)
+        self.model.clear_graph_opt_backend(fd_config=self.fd_config)
 
 
 class Qwen3PretrainedModel(PretrainedModel):

fastdeploy/model_executor/models/qwen3_vl/qwen3_vl.py

@@ -382,9 +382,9 @@ class Qwen3VLForConditionalGeneration(ModelForCasualLM):
 
         return hidden_states
 
-    def clear_grpah_opt_backend(self):
+    def clear_graph_opt_backend(self):
         """Clear graph optimization backend, the captured cuda graph will be cleaned"""
-        self.model.clear_grpah_opt_backend(fd_config=self.fd_config)
+        self.model.clear_graph_opt_backend(fd_config=self.fd_config)
 
 
 class Qwen3VLPretrainedModel(PretrainedModel):

fastdeploy/model_executor/models/qwen3moe.py

@@ -453,9 +453,9 @@ class Qwen3MoeForCausalLM(ModelForCasualLM):
 
         return hidden_states
 
-    def clear_grpah_opt_backend(self):
+    def clear_graph_opt_backend(self):
         """Clear graph optimization backend, the captured cuda graph will be cleaned"""
-        self.model.clear_grpah_opt_backend(fd_config=self.fd_config)
+        self.model.clear_graph_opt_backend(fd_config=self.fd_config)
 
 
 class Qwen3MoePretrainedModel(PretrainedModel):

fastdeploy/worker/gpu_model_runner.py

@@ -2692,13 +2692,13 @@ class GPUModelRunner(ModelRunnerBase):
         """Dynamic model loader use to clear parameters use for RL"""
         # Clear CUDAGraph
         if self.use_cudagraph:
-            self.model.clear_grpah_opt_backend()
+            self.model.clear_graph_opt_backend()
         # Clear parameters and Send single
         self.dynamic_weight_manager.clear_parameters(
             pid, self.fd_config.parallel_config.shutdown_comm_group_if_worker_idle
         )
         if self.spec_method == SpecMethod.MTP:
-            self.proposer.model.clear_grpah_opt_backend()
+            self.proposer.model.clear_graph_opt_backend()
             self.proposer.clear_mtp_cache()
         self.clear_cache()
         paddle.device.cuda.empty_cache()
@@ -2752,7 +2752,7 @@ class GPUModelRunner(ModelRunnerBase):
                 logger.info("GPU model runner's weight is already sleeping, no need to sleep again!")
                 return
             if self.use_cudagraph:
-                self.model.clear_grpah_opt_backend()
+                self.model.clear_graph_opt_backend()
             if self.fd_config.parallel_config.enable_expert_parallel:
                 self.dynamic_weight_manager.clear_deepep_buffer()
             self.dynamic_weight_manager.clear_model_weight()

fastdeploy/worker/metax_model_runner.py

@@ -2511,7 +2511,7 @@ class MetaxModelRunner(ModelRunnerBase):
         """Dynamic model loader use to clear parameters use for RL"""
         # Clear CUDAGraph
         if self.use_cudagraph:
-            self.model.clear_grpah_opt_backend()
+            self.model.clear_graph_opt_backend()
         # Clear parameters and Send single
         self.dynamic_weight_manager.clear_parameters(
             pid, self.fd_config.parallel_config.shutdown_comm_group_if_worker_idle

tests/graph_optimization/test_cuda_graph_recapture.py

@@ -91,10 +91,10 @@ class TestModel1(paddle.nn.Layer):
 
         return sublayer2_output
 
-    def clear_grpah_opt_backend(self):
+    def clear_graph_opt_backend(self):
         """ """
-        self.sublayer1.clear_grpah_opt_backend(fd_config=self.fd_config)
-        self.sublayer2.clear_grpah_opt_backend(fd_config=self.fd_config)
+        self.sublayer1.clear_graph_opt_backend(fd_config=self.fd_config)
+        self.sublayer2.clear_graph_opt_backend(fd_config=self.fd_config)
 
 
 class TestCUDAGrpahRecapture(unittest.TestCase):
@@ -152,7 +152,7 @@ class TestCUDAGrpahRecapture(unittest.TestCase):
 
         # Destroy
         print_gpu_memory_use("before destroy", 0)
-        self.test_model1.clear_grpah_opt_backend()
+        self.test_model1.clear_graph_opt_backend()
         print_gpu_memory_use("after destroy", 0)
 
     def recapture_and_replay(self, input_tensor1, forward_meta1):
@@ -168,7 +168,7 @@ class TestCUDAGrpahRecapture(unittest.TestCase):
 
         # Destroy
         print_gpu_memory_use("before destroy", 0)
-        self.test_model1.clear_grpah_opt_backend()
+        self.test_model1.clear_graph_opt_backend()
         print_gpu_memory_use("after destroy", 0)
 
 

tests/worker/test_gpu_model_runner.py

@@ -487,7 +487,7 @@ class TestSleepWakeupBehavior(unittest.TestCase):
         runner.local_rank = 0
         runner.device_id = 1
         runner.num_gpu_blocks = 8
-        runner.model = Mock(clear_grpah_opt_backend=Mock())
+        runner.model = Mock(clear_graph_opt_backend=Mock())
         runner.clear_cache = Mock()
         runner.initialize_kv_cache = Mock()
         runner.capture_model = Mock()
@@ -523,7 +523,7 @@ class TestSleepWakeupBehavior(unittest.TestCase):
 
         runner.sleep("weight,kv_cache")
 
-        runner.model.clear_grpah_opt_backend.assert_called_once()
+        runner.model.clear_graph_opt_backend.assert_called_once()
         runner.dynamic_weight_manager.clear_deepep_buffer.assert_called_once()
         runner.dynamic_weight_manager.clear_model_weight.assert_called_once()
         runner.dynamic_weight_manager.clear_communication_group.assert_called_once()