【SCU】【PPSCI Export&Infer No.8】amgnet_cylinder

docs/zh/examples/amgnet.md

@@ -6,6 +6,18 @@
 
     本案例运行前需通过 `pip install -r requirements.txt` 命令，安装 [**P**addle **G**raph **L**earning](https://github.com/PaddlePaddle/PGL) 图学习工具和 [PyAMG](https://github.com/pyamg/pyamg) 代数多重网格工具。
 
+=== "模型导出命令"
+
+    ``` sh
+    python amgnet_cylinder.py mode=export
+    ```
+
+=== "模型推理命令"
+
+    ``` sh
+    python amgnet_cylinder.py mode=infer
+    ```
+
 === "模型训练命令"
 
     === "amgnet_airfoil"

examples/amgnet/amgnet_cylinder.py

@@ -26,6 +26,8 @@
 
 import ppsci
 from ppsci.utils import logger
+import paddle
+import numpy as np
 
 if TYPE_CHECKING:
     import paddle
@@ -212,6 +214,37 @@ def evaluate(cfg: DictConfig):
             )
 
 
+def inference(model_path: str, input_data_path: str):
+
+    model = paddle.jit.load(model_path)
+    model.eval()
+
+    input_data = np.load(input_data_path, allow_pickle=True)
+    input_graph = input_data["input_graph"]
+
+    graph = ppsci.utils.GraphData(
+        nodes=input_graph["node_features"],
+        edges=input_graph["edges"],
+        edge_features=input_graph["edge_features"],
+    )
+
+    with paddle.no_grad():
+        predictions = model(graph)
+
+    return {
+        "velocity_x": predictions["velocity_x"].numpy(),
+        "velocity_y": predictions["velocity_y"].numpy(),
+        "pressure": predictions["pressure"].numpy(),
+    }
+
+
+result = inference("pretrained_model.pdparams", "input_graph_data.npz")
+print("Velocity X:", result["velocity_x"])
+print("Velocity Y:", result["velocity_y"])
+print("Pressure:", result["pressure"])
+
+
+
 @hydra.main(version_base=None, config_path="./conf", config_name="amgnet_cylinder.yaml")
 def main(cfg: DictConfig):
     if cfg.mode == "train":

examples/amgnet/conf/amgnet_cylinder.yaml

@@ -64,3 +64,20 @@ EVAL:
   batch_size: 1
   pretrained_model_path: null
   eval_with_no_grad: true
+
+INFER:
+  pretrained_model_path: https://paddle-org.bj.bcebos.com/paddlescience/models/amgnet/amgnet_cylinder_pretrained.pdparams
+  export_path: ./inference/laplace2d
+  pdmodel_path: ${INFER.export_path}.pdmodel
+  pdpiparams_path: ${INFER.export_path}.pdiparams
+  device: gpu
+  engine: native
+  precision: fp32
+  onnx_path: ${INFER.export_path}.onnx
+  ir_optim: true
+  min_subgraph_size: 10
+  gpu_mem: 4000
+  gpu_id: 0
+  max_batch_size: 64
+  num_cpu_threads: 4
+  batch_size: 64