diff --git a/ppsci/arch/deeponet.py b/ppsci/arch/deeponet.py
index 374c09cd3..16a8807d8 100644
--- a/ppsci/arch/deeponet.py
+++ b/ppsci/arch/deeponet.py
@@ -51,6 +51,7 @@ class DeepONet(base.Arch):
         use_bias (bool, optional): Whether to add bias on predicted G(u)(y). Defaults to True.
 
     Examples:
+        >>> import paddle
         >>> import ppsci
         >>> model = ppsci.arch.DeepONet(
         ...     "u", "y", "G",
@@ -60,6 +61,11 @@ class DeepONet(base.Arch):
         ...     branch_activation="relu", trunk_activation="relu",
         ...     use_bias=True,
         ... )
+        >>> input_dict = {"u": paddle.rand([200, 100]),
+        ...               "y": paddle.rand([200, 1])}
+        >>> output_dict = model(input_dict)
+        >>> print(output_dict["G"].shape)
+        [200, 1]
     """
 
     def __init__(
diff --git a/ppsci/arch/mlp.py b/ppsci/arch/mlp.py
index b4e5f9858..0bc87a447 100644
--- a/ppsci/arch/mlp.py
+++ b/ppsci/arch/mlp.py
@@ -66,8 +66,21 @@ class MLP(base.Arch):
         output_dim (Optional[int]): Number of output's dimension. Defaults to None.
 
     Examples:
+        >>> import paddle
         >>> import ppsci
-        >>> model = ppsci.arch.MLP(("x", "y"), ("u", "v"), 5, 128)
+        >>> model = ppsci.arch.MLP(
+        ...     input_keys=("x", "y"),
+        ...     output_keys=("u", "v"),
+        ...     num_layers=5,
+        ...     hidden_size=128
+        ... )
+        >>> input_dict = {"x": paddle.rand([64, 64, 1]),
+        ...               "y": paddle.rand([64, 64, 1])}
+        >>> output_dict = model(input_dict)
+        >>> print(output_dict["u"].shape)
+        [64, 64, 1]
+        >>> print(output_dict["v"].shape)
+        [64, 64, 1]
     """
 
     def __init__(