fix some docs (#29011)

* fix some docs test=develop;test=document_fix

* add code example test=develop;test=document_fix

* fix code example test=develop;test=document_fix

* fix code example test=develop;test=document_fix

* fix code example test=develop;test=document_fix

python/paddle/compat.py

@@ -36,6 +36,7 @@ else:
 def to_text(obj, encoding='utf-8', inplace=False):
     """
     All string in PaddlePaddle should be represented as a literal string.
+    
     This function will convert object to a literal string without any encoding.
     Especially, if the object type is a list or set container, we will iterate
     all items in the object and convert them to literal string.
@@ -53,6 +54,17 @@ def to_text(obj, encoding='utf-8', inplace=False):
 
     Returns:
         Decoded result of obj
+    
+    Examples:
+
+        .. code-block:: python
+
+            import paddle
+
+            data = "paddlepaddle"
+            data = paddle.compat.to_text(data)
+            # paddlepaddle
+
     """
     if obj is None:
         return obj
@@ -120,6 +132,7 @@ def _to_text(obj, encoding):
 def to_bytes(obj, encoding='utf-8', inplace=False):
     """
     All string in PaddlePaddle should be represented as a literal string.
+    
     This function will convert object to a bytes with specific encoding.
     Especially, if the object type is a list or set container, we will iterate
     all items in the object and convert them to bytes.
@@ -138,6 +151,17 @@ def to_bytes(obj, encoding='utf-8', inplace=False):
 
     Returns:
         Decoded result of obj
+    
+    Examples:
+
+        .. code-block:: python
+
+            import paddle
+
+            data = "paddlepaddle"
+            data = paddle.compat.to_bytes(data)
+            # b'paddlepaddle'
+
     """
     if obj is None:
         return obj

python/paddle/fluid/dygraph/nn.py

@@ -2979,11 +2979,7 @@ class GroupNorm(layers.Layer):
 
 
 class SpectralNorm(layers.Layer):
-    r"""
-    :alias_main: paddle.nn.SpectralNorm
-	:alias: paddle.nn.SpectralNorm,paddle.nn.layer.SpectralNorm,paddle.nn.layer.norm.SpectralNorm
-	:old_api: paddle.fluid.dygraph.SpectralNorm
-
+    """
     This interface is used to construct a callable object of the ``SpectralNorm`` class.
     For more details, refer to code examples. It implements the function of the Spectral Normalization Layer.
     This layer calculates the spectral normalization value of weight parameters of
@@ -3031,13 +3027,13 @@ class SpectralNorm(layers.Layer):
     Examples:
        .. code-block:: python
 
-            import paddle.fluid as fluid
-            import numpy as np
+            import paddle
+            x = paddle.rand((2,8,32,32))
 
-            with fluid.dygraph.guard():
-                weight = np.random.random((2, 8, 32, 32)).astype('float32')
-                spectralNorm = fluid.dygraph.nn.SpectralNorm(weight.shape, dim=1, power_iters=2)
-                ret = spectralNorm(fluid.dygraph.base.to_variable(weight))
+            spectral_norm = paddle.nn.SpectralNorm(x.shape, dim=1, power_iters=2)
+            spectral_norm_out = spectral_norm(x)
+
+            print(spectral_norm_out.shape) # [2, 8, 32, 32]
 
     """
 

python/paddle/fluid/layers/nn.py

@@ -3554,7 +3554,7 @@ def group_norm(input,
     Refer to `Group Normalization <https://arxiv.org/abs/1803.08494>`_ .
 
     Parameters:
-        input(Variable): 4-D Tensor, the data type is float32 or float64.
+        input(Tensor): 4-D Tensor, the data type is float32 or float64.
         groups(int): The number of groups that divided from channels, the data type
             is int32.
         epsilon(float, optional): The small value added to the variance to prevent
@@ -3576,26 +3576,17 @@ def group_norm(input,
             property. For more information, please refer to :ref:`api_guide_Name` .
 
     Returns:
-        Variable: A 4-D Tensor has same data type and data format with `input`.
-
-    Raises:
-        ValueError: If `data_layout` is neither 'NCHW' nor 'NHWC'.
-        ValueError: If `groups` is greater than the number of input channels.
-        ValueError: If `groups` is less than 1.
-        ShapeError: If the param_attr(Scale) is not 1-D Tensor.
-        ShapeError: If the param_attr(Scale)'s first dimension size is not equal to the input channels.
-        ShapeError: If the bias_attr(Bias) is not 1-D Tensor.
-        ShapeError: If the bias_attr(Bias)'s first dimension size is not equal to the input channels.
+        Tensor: A 4-D Tensor has same data type and data format with `input`.
 
     Examples:
        .. code-block:: python
 
-            import paddle.fluid as fluid
             import paddle
             paddle.enable_static()
             
-            data = fluid.data(name='data', shape=[None, 8, 32, 32], dtype='float32')
-            x = fluid.layers.group_norm(input=data, groups=4)
+            data = paddle.static.data(name='data', shape=[2, 8, 32, 32], dtype='float32')
+            x = paddle.static.nn.group_norm(input=data, groups=4)
+            print(x.shape) # [2, 8, 32, 32]
     """
     helper = LayerHelper('group_norm', **locals())
     dtype = helper.input_dtype()
@@ -3685,7 +3676,7 @@ def spectral_norm(weight, dim=0, power_iters=1, eps=1e-12, name=None):
     Refer to `Spectral Normalization <https://arxiv.org/abs/1802.05957>`_ .
 
     Args:
-        weight(${weight_type}): ${weight_comment}
+        weight(Tensor): ${weight_comment}
         dim(int): ${dim_comment}
         power_iters(int): ${power_iters_comment}
         eps(float): ${eps_comment}
@@ -3694,7 +3685,7 @@ def spectral_norm(weight, dim=0, power_iters=1, eps=1e-12, name=None):
                              None by default.
 
     Returns:
-        Variable: A tensor variable of weight parameters after spectral normalization.
+        Tensor: A tensor of weight parameters after spectral normalization.
                   The data type and shape is same as input tensor.
 
     Examples:
@@ -3703,8 +3694,9 @@ def spectral_norm(weight, dim=0, power_iters=1, eps=1e-12, name=None):
             import paddle
 
             paddle.enable_static()
-            weight = paddle.data(name='weight', shape=[2, 8, 32, 32], dtype='float32')
+            weight = paddle.static.data(name='weight', shape=[2, 8, 32, 32], dtype='float32')
             x = paddle.static.nn.spectral_norm(weight=weight, dim=1, power_iters=2)
+            print(x.shape) # [2, 8, 32, 32]
     """
     helper = LayerHelper('spectral_norm', **locals())
     check_variable_and_dtype(weight, 'weight', ['float32', 'float64'],