[New Sample] Add test example of PaddleScience

Author: HeyDavid633

paddle_samples/PaddleScience/euler_beam/subgraph_0/graph_hash.txt

@@ -1 +1 @@
-575d5d352922c60e30a16abad214b160599626321cca4c8ab7ae59a4fdf36cf2
+6f3dcd3f048c2f76bf01f0b9d90372d402b7ed0431ad5102bd9f54d53cbada4c

paddle_samples/PaddleScience/euler_beam/subgraph_0/graph_net.json

@@ -1,6 +1,6 @@
 {
     "framework": "paddle",
-    "model_name": "euler_beam",
+    "model_name": "",
     "num_devices_required": 1,
     "num_nodes_required": 1
 }

paddle_samples/PaddleScience/euler_beam/subgraph_0/input_meta.py

@@ -2,41 +2,33 @@ class Program_weight_tensor_data_0:
     name = "data_0"
     shape = [100, 1]
     dtype = "float32"
-    min_val = 0
-    max_val = 0.5
-    mean = None
-    std = None
+    min_val = float("0")
+    max_val = float("0.5")
     data = None
 
 
 class Program_weight_tensor_data_1:
     name = "data_1"
     shape = [100, 1]
     dtype = "float32"
-    min_val = 0
-    max_val = 0.5
-    mean = None
-    std = None
+    min_val = float("0")
+    max_val = float("0.5")
     data = None
 
 
 class Program_weight_tensor_data_2:
     name = "data_2"
     shape = [100, 1]
     dtype = "float32"
-    min_val = 0
-    max_val = 0.5
-    mean = None
-    std = None
+    min_val = float("0")
+    max_val = float("0.5")
     data = None
 
 
 class Program_weight_tensor_data_3:
     name = "data_3"
     shape = [100, 1]
     dtype = "float32"
-    min_val = 0
-    max_val = 0.5
-    mean = None
-    std = None
+    min_val = float("0")
+    max_val = float("0.5")
     data = None

paddle_samples/PaddleScience/euler_beam/subgraph_0/model.py

@@ -25,47 +25,47 @@ def forward(
         del data_1, parameter_7
 
         # pd_op.add: (100x20xf32) <- (100x20xf32, 20xf32)
-        add_1 = paddle._C_ops.add(matmul_0, parameter_6)
+        add_0 = paddle._C_ops.add(matmul_0, parameter_6)
         del matmul_0, parameter_6
 
         # pd_op.tanh: (100x20xf32) <- (100x20xf32)
-        tanh_0 = paddle._C_ops.tanh(add_1)
-        del add_1
+        tanh_0 = paddle._C_ops.tanh(add_0)
+        del add_0
 
         # pd_op.matmul: (100x20xf32) <- (100x20xf32, 20x20xf32)
         matmul_1 = paddle._C_ops.matmul(tanh_0, parameter_5, False, False)
         del parameter_5, tanh_0
 
         # pd_op.add: (100x20xf32) <- (100x20xf32, 20xf32)
-        add_2 = paddle._C_ops.add(matmul_1, parameter_4)
+        add_1 = paddle._C_ops.add(matmul_1, parameter_4)
         del matmul_1, parameter_4
 
         # pd_op.tanh: (100x20xf32) <- (100x20xf32)
-        tanh_1 = paddle._C_ops.tanh(add_2)
-        del add_2
+        tanh_1 = paddle._C_ops.tanh(add_1)
+        del add_1
 
         # pd_op.matmul: (100x20xf32) <- (100x20xf32, 20x20xf32)
         matmul_2 = paddle._C_ops.matmul(tanh_1, parameter_3, False, False)
         del parameter_3, tanh_1
 
         # pd_op.add: (100x20xf32) <- (100x20xf32, 20xf32)
-        add_3 = paddle._C_ops.add(matmul_2, parameter_2)
+        add_2 = paddle._C_ops.add(matmul_2, parameter_2)
         del matmul_2, parameter_2
 
         # pd_op.tanh: (100x20xf32) <- (100x20xf32)
-        tanh_2 = paddle._C_ops.tanh(add_3)
-        del add_3
+        tanh_2 = paddle._C_ops.tanh(add_2)
+        del add_2
 
         # pd_op.matmul: (100x1xf32) <- (100x20xf32, 20x1xf32)
         matmul_3 = paddle._C_ops.matmul(tanh_2, parameter_1, False, False)
         del parameter_1, tanh_2
 
         # pd_op.add: (100x1xf32) <- (100x1xf32, 1xf32)
-        add_0 = paddle._C_ops.add(matmul_3, parameter_0)
+        add_3 = paddle._C_ops.add(matmul_3, parameter_0)
         del matmul_3, parameter_0
 
         # pd_op.subtract: (100x1xf32) <- (100x1xf32, 100x1xf32)
-        subtract_0 = paddle._C_ops.subtract(add_0, data_2)
+        subtract_0 = paddle._C_ops.subtract(add_3, data_2)
         del data_2
 
         # pd_op.full: (xf32) <- ()
@@ -98,6 +98,6 @@ def forward(
 
         # pd_op.divide: (xf32) <- (xf32, xf32)
         divide_0 = paddle._C_ops.divide(sum_0, full_1)
-        del full_1, sum_0
+        del add_3, full_1, sum_0
 
-        return add_0, divide_0
+        return divide_0

paddle_samples/PaddleScience/euler_beam/subgraph_0/weight_meta.py

@@ -2,85 +2,69 @@ class Program_weight_tensor_parameter_0:
     name = "parameter_0"
     shape = [1]
     dtype = "float32"
-    min_val = 0
-    max_val = 0.5
-    mean = None
-    std = None
+    min_val = float("0")
+    max_val = float("0.5")
     data = None
 
 
 class Program_weight_tensor_parameter_1:
     name = "parameter_1"
     shape = [20, 1]
     dtype = "float32"
-    min_val = 0
-    max_val = 0.5
-    mean = None
-    std = None
+    min_val = float("0")
+    max_val = float("0.5")
     data = None
 
 
 class Program_weight_tensor_parameter_2:
     name = "parameter_2"
     shape = [20]
     dtype = "float32"
-    min_val = 0
-    max_val = 0.5
-    mean = None
-    std = None
+    min_val = float("0")
+    max_val = float("0.5")
     data = None
 
 
 class Program_weight_tensor_parameter_3:
     name = "parameter_3"
     shape = [20, 20]
     dtype = "float32"
-    min_val = 0
-    max_val = 0.5
-    mean = None
-    std = None
+    min_val = float("0")
+    max_val = float("0.5")
     data = None
 
 
 class Program_weight_tensor_parameter_4:
     name = "parameter_4"
     shape = [20]
     dtype = "float32"
-    min_val = 0
-    max_val = 0.5
-    mean = None
-    std = None
+    min_val = float("0")
+    max_val = float("0.5")
     data = None
 
 
 class Program_weight_tensor_parameter_5:
     name = "parameter_5"
     shape = [20, 20]
     dtype = "float32"
-    min_val = 0
-    max_val = 0.5
-    mean = None
-    std = None
+    min_val = float("0")
+    max_val = float("0.5")
     data = None
 
 
 class Program_weight_tensor_parameter_6:
     name = "parameter_6"
     shape = [20]
     dtype = "float32"
-    min_val = 0
-    max_val = 0.5
-    mean = None
-    std = None
+    min_val = float("0")
+    max_val = float("0.5")
     data = None
 
 
 class Program_weight_tensor_parameter_7:
     name = "parameter_7"
     shape = [1, 20]
     dtype = "float32"
-    min_val = 0
-    max_val = 0.5
-    mean = None
-    std = None
+    min_val = float("0")
+    max_val = float("0.5")
     data = None

paddle_samples/PaddleScience/euler_beam/subgraph_1/graph_net.json

@@ -1,6 +1,6 @@
 {
     "framework": "paddle",
-    "model_name": "euler_beam",
+    "model_name": "",
     "num_devices_required": 1,
     "num_nodes_required": 1
 }

paddle_samples/PaddleScience/euler_beam/subgraph_1/input_meta.py

@@ -2,21 +2,17 @@ class Program_weight_tensor_data_0:
     name = "data_0"
     shape = [100, 1]
     dtype = "float32"
-    min_val = 0
-    max_val = 0.5
-    mean = None
-    std = None
+    min_val = float("0")
+    max_val = float("0.5")
     data = None
 
 
 class Program_weight_tensor_data_1:
     name = "data_1"
     shape = [100, 1]
     dtype = "float32"
-    min_val = 0
-    max_val = 0.5
-    mean = None
-    std = None
+    min_val = float("0")
+    max_val = float("0.5")
     data = None
 
 
@@ -38,10 +34,8 @@ class Program_weight_tensor_data_4:
     name = "data_4"
     shape = [100, 1]
     dtype = "float32"
-    min_val = 0
-    max_val = 0.5
-    mean = None
-    std = None
+    min_val = float("0")
+    max_val = float("0.5")
     data = None