[Executor] CUDAGraph support RL training (#3265)

* add clear graph opt backend

* cuda graph support rl

* add branch

* 1.fix dynamic_weight_manager bug 2.add clear api for CasualLM

* open test case

* fix typo

* update mkdocs.yaml

* [Docs]Update mkdocs.yml

* update test case

* use unittest in graph test case

fastdeploy/worker/gpu_model_runner.py

@@ -876,6 +876,7 @@ class GPUModelRunner(ModelRunnerBase):
         # 1. Load original model
         model_loader = get_model_loader(load_config=self.fd_config.load_config)
         self.model = model_loader.load_model(fd_config=self.fd_config)
+
         # 1.1 Load RL dynamic model
         if self.fd_config.load_config.dynamic_load_weight:
             from fastdeploy.rl.dynamic_weight_manager import DynamicWeightManager
@@ -1595,12 +1596,22 @@ class GPUModelRunner(ModelRunnerBase):
         self.dynamic_weight_manager.clear_parameters(pid)
         self.clear_cache()
         paddle.device.cuda.empty_cache()
+
+        # Clear CudaGraph
+        if self.use_cudagraph:
+            self.model.clear_grpah_opt_backend()
+
         self.dynamic_weight_manager._log_memory("dynamic weight manager clear all memory")
 
     def update_parameters(self, pid):
         """ " Dynamic model loader use to update parameters use for RL"""
         self.dynamic_weight_manager.update_parameters(pid)
         self.initialize_kv_cache()
+
+        # Recapture CudaGraph
+        if self.use_cudagraph:
+            self.capture_model()
+
         self.dynamic_weight_manager._log_memory("dynamic weight manager update all memory")
 
     def padding_cudagraph_inputs(self) -> None: