[LLM] First commit the llm deployment code

test/worker/test_cuda_graph.py

@@ -0,0 +1,54 @@
+"""
+# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""
+
+import paddle
+
+from fastdeploy.config import GraphOptimizationConfig, LLMConfig
+from fastdeploy.model_executor.graph_optimization.decorator import \
+    support_graph_opt
+
+
+@support_graph_opt
+class TestModel(paddle.nn.Layer):
+    """ Tast Model """
+
+    def __init__(self, llm_config: LLMConfig, **kwargs):
+        self.llm_config = llm_config
+
+    def __call__(self, **kwargs):
+        return self.forward(**kwargs)
+
+    def forward(self, **kwargs):
+        """前向传播"""
+        input_ids: paddle.Tensor = kwargs["input_ids"]
+        return input_ids + input_ids
+
+
+if __name__ == '__main__':
+    graph_opt_config = GraphOptimizationConfig()
+    graph_opt_config.use_cudagraph = True
+    graph_opt_config.cudagraph_capture_sizes = [1, 4]
+    llm_config = LLMConfig(graph_opt_config=graph_opt_config)
+    model = TestModel(llm_config=llm_config)
+
+    output = model(input_ids=paddle.zeros([1, 8]))
+    print(output)
+    output = model(input_ids=paddle.ones([1, 8]))
+    print(output)
+    output = model(input_ids=paddle.zeros([4, 9]))
+    print(output)
+    output = model(input_ids=paddle.ones([4, 9]))
+    print(output)