diff --git a/ppsci/metric/func.py b/ppsci/metric/func.py
index 7cc74dd3f..56273784d 100644
--- a/ppsci/metric/func.py
+++ b/ppsci/metric/func.py
@@ -27,17 +27,23 @@ class FunctionalMetric(base.Metric):
         keep_batch (bool, optional): Whether keep batch axis. Defaults to False.
 
     Examples:
-        >>> import ppsci
         >>> import paddle
+        >>> from ppsci.metric import FunctionalMetric
         >>> def metric_expr(output_dict, *args):
         ...     rel_l2 = 0
         ...     for key in output_dict:
         ...         length = int(len(output_dict[key])/2)
-        ...         out_dict = {key: output_dict[key][:length]}
-        ...         label_dict = {key: output_dict[key][length:]}
+        ...         out_dict = output_dict[key][:length]
+        ...         label_dict = output_dict[key][length:]
         ...         rel_l2 += paddle.norm(out_dict - label_dict) / paddle.norm(label_dict)
-        ...     return {"l2": rel_l2}
-        >>> metric_dict = ppsci.metric.FunctionalMetric(metric_expr)
+        ...     return {"rel_l2": rel_l2}
+        >>> metric_dict = FunctionalMetric(metric_expr)
+        >>> output_dict = {'u': paddle.to_tensor([[0.5, 0.9], [1.1, -1.3], [-0.2, 1.5], [-0.1, -0.3]]),
+        ...                'v': paddle.to_tensor([[0.5, 0.9], [1.1, -1.3], [-1.8, 1.0], [-0.2, 2.5]])}
+        >>> result = metric_dict(output_dict)
+        >>> print(result)
+        {'rel_l2': Tensor(shape=[], dtype=float32, place=Place(gpu:0), stop_gradient=True,
+               2.59985542)}
     """
 
     def __init__(
diff --git a/ppsci/metric/l2_rel.py b/ppsci/metric/l2_rel.py
index 4de9c186d..6bb162006 100644
--- a/ppsci/metric/l2_rel.py
+++ b/ppsci/metric/l2_rel.py
@@ -40,8 +40,18 @@ class L2Rel(base.Metric):
         keep_batch (bool, optional): Whether keep batch axis. Defaults to False.
 
     Examples:
-        >>> import ppsci
-        >>> metric = ppsci.metric.L2Rel()
+        >>> import paddle
+        >>> from ppsci.metric import L2Rel
+        >>> output_dict = {'u': paddle.to_tensor([[0.5, 0.9], [1.1, -1.3]]),
+        ...                'v': paddle.to_tensor([[0.5, 0.9], [1.1, -1.3]])}
+        >>> label_dict = {'u': paddle.to_tensor([[-1.8, 1.0], [-0.2, 2.5]]),
+        ...               'v': paddle.to_tensor([[0.1, 0.1], [0.1, 0.1]])}
+        >>> loss = L2Rel()
+        >>> result = loss(output_dict, label_dict)
+        >>> print(result)
+        {'u': Tensor(shape=[], dtype=float32, place=Place(gpu:0), stop_gradient=True,
+               1.42658269), 'v': Tensor(shape=[], dtype=float32, place=Place(gpu:0), stop_gradient=True,
+               9.69535923)}
     """
 
     # NOTE: Avoid divide by zero in result
@@ -85,8 +95,24 @@ class MeanL2Rel(base.Metric):
         keep_batch (bool, optional): Whether keep batch axis. Defaults to False.
 
     Examples:
-        >>> import ppsci
-        >>> metric = ppsci.metric.MeanL2Rel()
+        >>> import paddle
+        >>> from ppsci.metric import MeanL2Rel
+        >>> output_dict = {'u': paddle.to_tensor([[0.5, 0.9], [1.1, -1.3]]),
+        ...                'v': paddle.to_tensor([[0.5, 0.9], [1.1, -1.3]])}
+        >>> label_dict = {'u': paddle.to_tensor([[-1.8, 1.0], [-0.2, 2.5]]),
+        ...               'v': paddle.to_tensor([[0.1, 0.1], [0.1, 0.1]])}
+        >>> loss = MeanL2Rel()
+        >>> result = loss(output_dict, label_dict)
+        >>> print(result)
+        {'u': Tensor(shape=[], dtype=float32, place=Place(gpu:0), stop_gradient=True,
+               1.35970235), 'v': Tensor(shape=[], dtype=float32, place=Place(gpu:0), stop_gradient=True,
+               9.24504089)}
+        >>> loss = MeanL2Rel(keep_batch=True)
+        >>> result = loss(output_dict, label_dict)
+        >>> print(result)
+        {'u': Tensor(shape=[2], dtype=float32, place=Place(gpu:0), stop_gradient=True,
+               [1.11803389, 1.60137081]), 'v': Tensor(shape=[2], dtype=float32, place=Place(gpu:0), stop_gradient=True,
+               [6.32455540 , 12.16552544])}
     """
 
     # NOTE: Avoid divide by zero in result
diff --git a/ppsci/metric/mae.py b/ppsci/metric/mae.py
index 10a491f7f..0554a3cc5 100644
--- a/ppsci/metric/mae.py
+++ b/ppsci/metric/mae.py
@@ -35,8 +35,24 @@ class MAE(base.Metric):
         keep_batch (bool, optional): Whether keep batch axis. Defaults to False.
 
     Examples:
-        >>> import ppsci
-        >>> metric = ppsci.metric.MAE()
+        >>> import paddle
+        >>> from ppsci.metric import MAE
+        >>> output_dict = {'u': paddle.to_tensor([[0.5, 0.9], [1.1, -1.3]]),
+        ...                'v': paddle.to_tensor([[0.5, 0.9], [1.1, -1.3]])}
+        >>> label_dict = {'u': paddle.to_tensor([[-1.8, 1.0], [-0.2, 2.5]]),
+        ...               'v': paddle.to_tensor([[0.1, 0.1], [0.1, 0.1]])}
+        >>> loss = MAE()
+        >>> result = loss(output_dict, label_dict)
+        >>> print(result)
+        {'u': Tensor(shape=[], dtype=float32, place=Place(gpu:0), stop_gradient=True,
+               1.87500000), 'v': Tensor(shape=[], dtype=float32, place=Place(gpu:0), stop_gradient=True,
+               0.89999998)}
+        >>> loss = MAE(keep_batch=True)
+        >>> result = loss(output_dict, label_dict)
+        >>> print(result)
+        {'u': Tensor(shape=[2], dtype=float32, place=Place(gpu:0), stop_gradient=True,
+               [1.20000005, 2.54999995]), 'v': Tensor(shape=[2], dtype=float32, place=Place(gpu:0), stop_gradient=True,
+               [0.59999996, 1.20000005])}
     """
 
     def __init__(self, keep_batch: bool = False):
diff --git a/ppsci/metric/mse.py b/ppsci/metric/mse.py
index ee21f6b0c..9b42f3646 100644
--- a/ppsci/metric/mse.py
+++ b/ppsci/metric/mse.py
@@ -35,8 +35,24 @@ class MSE(base.Metric):
         keep_batch (bool, optional): Whether keep batch axis. Defaults to False.
 
     Examples:
-        >>> import ppsci
-        >>> metric = ppsci.metric.MSE()
+        >>> import paddle
+        >>> from ppsci.metric import MSE
+        >>> output_dict = {'u': paddle.to_tensor([[0.5, 0.9], [1.1, -1.3]]),
+        ...                'v': paddle.to_tensor([[0.5, 0.9], [1.1, -1.3]])}
+        >>> label_dict = {'u': paddle.to_tensor([[-1.8, 1.0], [-0.2, 2.5]]),
+        ...               'v': paddle.to_tensor([[0.1, 0.1], [0.1, 0.1]])}
+        >>> loss = MSE()
+        >>> result = loss(output_dict, label_dict)
+        >>> print(result)
+        {'u': Tensor(shape=[], dtype=float32, place=Place(gpu:0), stop_gradient=True,
+               5.35750008), 'v': Tensor(shape=[], dtype=float32, place=Place(gpu:0), stop_gradient=True,
+               0.94000000)}
+        >>> loss = MSE(keep_batch=True)
+        >>> result = loss(output_dict, label_dict)
+        >>> print(result)
+        {'u': Tensor(shape=[2], dtype=float32, place=Place(gpu:0), stop_gradient=True,
+               [2.65000010, 8.06499958]), 'v': Tensor(shape=[2], dtype=float32, place=Place(gpu:0), stop_gradient=True,
+               [0.39999998, 1.48000002])}
     """
 
     def __init__(self, keep_batch: bool = False):
diff --git a/ppsci/metric/rmse.py b/ppsci/metric/rmse.py
index 238aed186..625538088 100644
--- a/ppsci/metric/rmse.py
+++ b/ppsci/metric/rmse.py
@@ -41,8 +41,18 @@ class RMSE(base.Metric):
         keep_batch (bool, optional): Whether keep batch axis. Defaults to False.
 
     Examples:
-        >>> import ppsci
-        >>> metric = ppsci.metric.RMSE()
+        >>> import paddle
+        >>> from ppsci.metric import RMSE
+        >>> output_dict = {'u': paddle.to_tensor([[0.5, 0.9], [1.1, -1.3]]),
+        ...                'v': paddle.to_tensor([[0.5, 0.9], [1.1, -1.3]])}
+        >>> label_dict = {'u': paddle.to_tensor([[-1.8, 1.0], [-0.2, 2.5]]),
+        ...               'v': paddle.to_tensor([[0.1, 0.1], [0.1, 0.1]])}
+        >>> loss = RMSE()
+        >>> result = loss(output_dict, label_dict)
+        >>> print(result)
+        {'u': Tensor(shape=[], dtype=float32, place=Place(gpu:0), stop_gradient=True,
+               2.31462741), 'v': Tensor(shape=[], dtype=float32, place=Place(gpu:0), stop_gradient=True,
+               0.96953595)}
     """
 
     def __init__(self, keep_batch: bool = False):
diff --git a/ppsci/solver/solver.py b/ppsci/solver/solver.py
index 4b8d8643f..3f3fbcd29 100644
--- a/ppsci/solver/solver.py
+++ b/ppsci/solver/solver.py
@@ -520,6 +520,21 @@ def predict(
 
         Returns:
             Dict[str, Union[paddle.Tensor, np.ndarray]]: Prediction in dict.
+
+        Examples:
+            >>> import paddle
+            >>> import ppsci
+            >>> paddle.seed(42)  # doctest: +SKIP
+            >>> model = ppsci.arch.MLP(('x', 'y'), ('u', 'v'), num_layers=None, hidden_size=[32, 8])
+            >>> solver = ppsci.solver.Solver(model)  # doctest: +SKIP
+            >>> input_dict = {'x': paddle.rand((2, 1)),
+            ...               'y': paddle.rand((2, 1))}
+            >>> solver.predict(input_dict) # doctest: +SKIP
+            {'u': Tensor(shape=[2, 1], dtype=float32, place=Place(gpu:0), stop_gradient=True,
+                   [[-0.17509711],
+                    [-0.03884222]]), 'v': Tensor(shape=[2, 1], dtype=float32, place=Place(gpu:0), stop_gradient=True,
+                   [[0.27433380],
+                    [0.42387512]])}
         """
         num_samples = len(next(iter(input_dict.values())))
         num_pad = (self.world_size - num_samples % self.world_size) % self.world_size