[Docathon][Fix System Message No.3、9、14、15] (#58664)

python/paddle/amp/debugging.py

@@ -466,6 +466,7 @@ def enable_operator_stats_collection():
     Examples:
 
         ..  code-block:: python
+
             >>> # doctest: +REQUIRES(env:GPU)
             >>> import paddle
             >>> paddle.device.set_device('gpu')

python/paddle/framework/random.py

@@ -67,14 +67,18 @@ def seed(seed):
 def get_rng_state(device=None):
     """
     Get all random states of random generators of specified device.
+
     Args:
         device(str): This parameter determines the specific running device.
             It can be ``cpu``, ``gpu``, ``xpu``, Default is None.
             If None, return the generators of current device (specified by ``set_device``).
+
     Returns:
         GeneratorState:  object.
+
     Examples:
         .. code-block:: python
+
             >>> import paddle
             >>> sts = paddle.get_rng_state()
     """

python/paddle/hapi/model.py

@@ -1829,6 +1829,7 @@ def fit(
             .. code-block:: python
                 :name: code-example3
 
+                >>> # doctest: +TIMEOUT(80)
                 >>> import paddle
                 >>> import paddle.vision.transforms as T
                 >>> from paddle.vision.datasets import MNIST
@@ -1861,12 +1862,14 @@ def fit(
                 ...             batch_size=64,
                 ...             save_dir='mnist_checkpoint')
                 ...
+
             2. An example use DataLoader, batch size and shuffle is set in
                DataLoader.
 
             .. code-block:: python
                 :name: code-example4
 
+                >>> # doctest: +TIMEOUT(80)
                 >>> import paddle
                 >>> import paddle.vision.transforms as T
                 >>> from paddle.vision.datasets import MNIST

python/paddle/nn/layer/loss.py

@@ -1742,18 +1742,18 @@ class TripletMarginWithDistanceLoss(Layer):
             For more information, please refer to :ref:`api_guide_Name`.
 
     Shapes:
-        input (Tensor):Input tensor, the data type is float32 or float64.
-    the shape is [N, \*], N is batch size and `\*` means any number of additional dimensions, available dtype is float32, float64.
+      - input (Tensor):Input tensor, the data type is float32 or float64.
+        the shape is [N, \*], N is batch size and `\*` means any number of additional dimensions, available dtype is float32, float64.
 
-        positive (Tensor):Positive tensor, the data type is float32 or float64.
-    The shape of label is the same as the shape of input.
+      - positive (Tensor):Positive tensor, the data type is float32 or float64.
+        The shape of label is the same as the shape of input.
 
-        negative (Tensor):Negative tensor, the data type is float32 or float64.
-    The shape of label is the same as the shape of input.
+      - negative (Tensor):Negative tensor, the data type is float32 or float64.
+        The shape of label is the same as the shape of input.
 
-        output(Tensor): The tensor variable storing the triplet_margin_with_distance_loss of input and positive and negative.
+      - output(Tensor): The tensor variable storing the triplet_margin_with_distance_loss of input and positive and negative.
 
-    Return：
+    Return:
         A callable object of TripletMarginWithDistanceLoss
 
     Examples: