[Executor] CUDA Graph support padding batch (#2844)

* cuda graph support padding batch

* Integrate the startup parameters for the graph optimization backend and provide support for user - defined capture sizes.

* Do not insert max_num_seqs when the user specifies a capture list

* Support set graph optimization config from YAML file

* update cuda graph ci

* fix ci bug

* fix ci bug

fastdeploy/engine/config.py

@@ -430,6 +430,77 @@ class SpeculativeConfig:
         llm_logger.info(
             "=============================================================")
 
+    def __str__(self) -> str:
+        return self.to_json_string()
+
+
+class GraphOptimizationConfig:
+    def __init__(
+        self,
+        graph_opt_level: Optional[int] = 0,
+        use_cudagraph: Optional[bool] = None,
+        cudagraph_capture_sizes: Optional[List[int]] = None,
+        **kwargs
+    ):
+        """
+        Graph Optimization Configuration class.
+
+        Attributes:
+            graph_opt_level: Compute graph optimization level
+            use_cudagraph: Use CUDA Graph or not
+            cudagraph_capture_sizes: Batch size list will be captured by CUDA Graph
+        """
+        self.check_legality_parameters(graph_opt_level, use_cudagraph, cudagraph_capture_sizes, **kwargs)
+
+        self.graph_opt_level = graph_opt_level
+        self.use_cudagraph = use_cudagraph
+        self.cudagraph_capture_sizes = cudagraph_capture_sizes
+
+    def to_json_string(self):
+        """
+        Convert speculative_config to json string.
+        """
+        return json.dumps({
+            key: value
+            for key, value in self.__dict__.items()
+        })
+
+    def __str__(self) -> str:
+        return self.to_json_string()
+
+    def check_legality_parameters(
+        self,
+        graph_opt_level: Optional[int] = None,
+        use_cudagraph: Optional[bool] = None,
+        cudagraph_capture_sizes: Optional[List[int]] = None,
+        **kwargs
+    ) -> None:
+        """ Check the legality of parameters passed in from the command line """
+
+        if graph_opt_level is not None:
+            assert graph_opt_level in [0, 1, 2], "In graph optimization config, graph_opt_level can only take the values of 0, 1 and 2."
+        if use_cudagraph is not None:
+            assert type(use_cudagraph) is bool, "In graph optimization config, type of use_cudagraph must is bool."
+        if cudagraph_capture_sizes is not None:
+            assert type(cudagraph_capture_sizes) is list, "In graph optimization config, type of cudagraph_capture_sizes must is list."
+            assert len(cudagraph_capture_sizes) > 0, "In graph optimization config, When opening the CUDA graph, it is forbidden to set the capture sizes to an empty list."
+
+        for key, value in kwargs.items():
+            raise ValueError(f"Invalid --graph-optimization-config parameter {key}")
+
+    def update_use_cudagraph(self, argument:bool):
+        """
+        Unified user specifies the use_cudagraph parameter through two methods,
+        '--use-cudagraph' and '--graph-optimization-config'
+        """
+        if self.use_cudagraph is None:
+            # User only set '--use-cudagraph'
+            self.use_cudagraph = argument
+        else:
+            # User both set '--use-cudagraph' and '--graph-optimization-config'
+            if self.use_cudagraph is False and argument is True:
+                raise ValueError("Invalid parameter: Cannot set --use-cudagraph and --graph-optimization-config '{\"use_cudagraph\":false}' simultaneously.")
+            argument = self.use_cudagraph
 
 class ParallelConfig:
     """
@@ -573,6 +644,7 @@ class Config:
         max_num_batched_tokens: Optional[int] = None,
         pod_ips: Optional[List[str]] = None,
         speculative_config: Optional[Dict[str, Any]] = None,
+        graph_optimization_config: Optional[Dict[str, Any]] = None,
         use_warmup: bool = False,
         engine_worker_queue_port: int = 8002,
         limit_mm_per_prompt: Optional[Dict[str, Any]] = None,
@@ -584,9 +656,6 @@ class Config:
         max_long_partial_prefills: int = 1,
         long_prefill_token_threshold: int = 0,
         reasoning_parser: str = None,
-        enable_static_graph_inference: bool = False,
-        use_cudagraph: bool = False,
-        max_capture_batch_size: int = 64,
         guided_decoding_backend: Optional[str] = None,
         disable_any_whitespace: bool = False,
         enable_custom_all_reduce: bool = False,
@@ -609,6 +678,7 @@ class Config:
             pod_ips (Optional[List[str]]): List of POD IPs. Default is None.
             mm_processor_kwargs (Optional[Dict[str, Any]]): Additional arguments for multi-modal processor. Default is None.
             speculative_config (Optional[Dict[str, Any]]): Speculative execution configuration. Default is None.
+            graph_optimization_config (Optional[Dict[str, Any]]): Graph optimizaion backend execution configuration. Default is None.
             use_warmup (bool): Flag to use warmup. Default is False.
             engine_worker_queue_port (int): Engine worker queue port. Default is 8002.
             enable_mm (bool): Flag to enable multi-modal processing. Default is False.
@@ -643,9 +713,7 @@ class Config:
         self.max_long_partial_prefills = max_long_partial_prefills
         self.long_prefill_token_threshold = long_prefill_token_threshold
         self.reasoning_parser = reasoning_parser
-        self.enable_static_graph_inference = enable_static_graph_inference
-        self.use_cudagraph = use_cudagraph
-        self.max_capture_batch_size = max_capture_batch_size
+        self.graph_optimization_config = graph_optimization_config
         self.guided_decoding_backend = guided_decoding_backend
         self.disable_any_whitespace = disable_any_whitespace
         self.is_master = True