cherry-pick optimize the api test=develop test=release/1.6 (#20350)

python/paddle/fluid/layers/tensor.py

@@ -65,24 +65,26 @@ def create_parameter(shape,
                      is_bias=False,
                      default_initializer=None):
     """
-    Create a parameter. The parameter is a learnable variable, which can have
+    This function creates a parameter. The parameter is a learnable variable, which can have
     gradient, and can be optimized.
 
     NOTE: this is a very low-level API. This API is useful when you create
     operator by your self. instead of using layers.
 
-    Args:
-        shape(list[int]): shape of the parameter
-        dtype(string): element type of the parameter
-        attr(ParamAttr): attributes of the parameter
-        is_bias(bool): This can affect which default initializer is chosen
+    Parameters:
+        shape (list of int): Shape of the parameter
+        dtype (str): Data type of the parameter
+        name (str, optional): For detailed information, please refer to
+           :ref:`api_guide_Name` . Usually name is no need to set and None by default.
+        attr (ParamAttr, optional): Attributes of the parameter
+        is_bias (bool, optional): This can affect which default initializer is chosen
                        when default_initializer is None. If is_bias,
                        initializer.Constant(0.0) will be used. Otherwise,
                        Xavier() will be used.
-        default_initializer(Initializer): initializer for the parameter
+        default_initializer (Initializer, optional): Initializer for the parameter
 
     Returns:
-        the created parameter.
+        The created parameter.
 
     Examples:
         .. code-block:: python
@@ -105,23 +107,22 @@ def create_global_var(shape,
                       force_cpu=False,
                       name=None):
     """
-    Create a new tensor variable with value in the global block(block 0).
+    This function creates a new tensor variable with value in the global block(block 0).
 
-    Args:
-        shape(list[int]): shape of the variable
-        value(float): the value of the variable. The new created
+    Parameters:
+        shape (list of int): Shape of the variable
+        value (float): The value of the variable. The new created
                       variable will be filled with it.
-        dtype(string): data type of the variable
-        persistable(bool): if this variable is persistable.
+        dtype (str): Data type of the variable
+        persistable (bool, optional): If this variable is persistable.
                            Default: False
-        force_cpu(bool): force this variable to be on CPU.
+        force_cpu (bool, optional): Force this variable to be on CPU.
                          Default: False
-        name(str|None): The name of the variable. If set to None the variable
-                        name will be generated automatically.
-                        Default: None
+        name (str, optional): For detailed information, please refer to
+           :ref:`api_guide_Name` . Usually name is no need to set and None by default.
 
     Returns:
-        Variable: the created Variable
+        Variable: The created Variable
 
     Examples:
         .. code-block:: python

python/paddle/fluid/optimizer.py

@@ -695,12 +695,13 @@ class SGDOptimizer(Optimizer):
 
         param\_out = param - learning\_rate * grad
 
-    Args:
-        learning_rate (float|Variable): the learning rate used to update parameters. \
+    Parameters:
+        learning_rate (float|Variable): The learning rate used to update parameters. \
             Can be a float value or a Variable with one float value as data element.
-        regularization: A Regularizer, such as
-                        fluid.regularizer.L2DecayRegularizer.
-        name: A optional name prefix.
+        regularization: A Regularizer, such as :ref:`api_fluid_regularizer_L2DecayRegularizer`. \
+            Optional, default is None.
+        name (str, optional): This parameter is used by developers to print debugging information. \
+            For details, please refer to :ref:`api_guide_Name`. Default is None.
 
     Examples:
         .. code-block:: python
@@ -778,14 +779,15 @@ class MomentumOptimizer(Optimizer):
 
         &\quad   param = param - learning\_rate * velocity
 
-    Args:
-        learning_rate (float|Variable): the learning rate used to update parameters. \
+    Parameters:
+        learning_rate (float|Variable): The learning rate used to update parameters. \
             Can be a float value or a Variable with one float value as data element.
-        momentum (float): momentum factor
-        use_nesterov (bool): enables Nesterov momentum
-        regularization: A Regularizer, such as
-                        fluid.regularizer.L2DecayRegularizer.
-        name: A optional name prefix.
+        momentum (float): Momentum factor
+        use_nesterov (bool, optional): Enables Nesterov momentum, default is false.
+        regularization: A Regularizer, such as :ref:`api_fluid_regularizer_L2DecayRegularizer`. \
+            Optional, default is None.
+        name (str, optional): This parameter is used by developers to print debugging information. \
+            For details, please refer to :ref:`api_guide_Name`. Default is None.
 
     Examples:
         .. code-block:: python
@@ -1142,16 +1144,16 @@ class LarsMomentumOptimizer(Optimizer):
 
         & param = param - velocity
 
-    Args:
-        learning_rate (float|Variable): the learning rate used to update parameters. \
-        Can be a float value or a Variable with one float value as data element.
+    Parameters:
+        learning_rate (float|Variable): The learning rate used to update parameters. \
+            Can be a float value or a Variable with one float value as data element. \
             momentum (float): momentum factor
-        lars_coeff (float): defines how much we trust the layer to change its weights.
-        lars_weight_decay (float): weight decay coefficient for decaying using LARS.
-        regularization: A Regularizer, such as
-                        fluid.regularizer.L2DecayRegularizer.
-        name: A optional name prefix.
-
+        lars_coeff (float): Defines how much we trust the layer to change its weights.
+        lars_weight_decay (float): Weight decay coefficient for decaying using LARS.
+        regularization: A Regularizer, such as :ref:`api_fluid_regularizer_L2DecayRegularizer`.
+            Optional, default is None.
+        name (str, optional): This parameter is used by developers to print debugging information. \
+            For details, please refer to :ref:`api_guide_Name`. Default is None.
 
     Examples:
         .. code-block:: python
@@ -2015,20 +2017,21 @@ class RMSPropOptimizer(Optimizer):
     from 1e-4 to 1e-8.
 
 
-    Args:
-        learning_rate(float): global learning rate.
-        rho(float): rho is :math: `\\rho` in equation, set 0.95 by default.
+    Parameters:
+        learning_rate(float): Global learning rate.
+        rho(float): rho is :math: `\\rho` in equation, default is 0.95.
         epsilon(float): :math: `\\epsilon` in equation is smoothing term to
-            avoid division by zero, set 1e-6 by default.
+            avoid division by zero, default is 1e-6.
         momentum(float): :math:`\\beta` in equation is the momentum term,
-            set 0.0 by default.
+            default is 0.0.
         centered(bool): If True, gradients are normalized by the estimated variance of
             the gradient; if False, by the uncentered second moment. Setting this to
             True may help with training, but is slightly more expensive in terms of
             computation and memory. Defaults to False.
-        regularization: A Regularizer, such as
-                        fluid.regularizer.L2DecayRegularizer.
-        name: A optional name prefix.
+        regularization: A Regularizer, such as :ref:`api_fluid_regularizer_L2DecayRegularizer`. \
+            Optional, default is None.
+        name (str, optional): This parameter is used by developers to print debugging information. \
+            For details, please refer to :ref:`api_guide_Name`. Default is None.
 
     Raises:
         ValueError: If learning_rate, rho, epsilon, momentum are None.
@@ -2180,14 +2183,15 @@ class FtrlOptimizer(Optimizer):
 
         &squared\_accum += grad^2
 
-    Args:
-        learning_rate (float|Variable): global learning rate.
-        l1 (float): L1 regularization strength.
-        l2 (float): L2 regularization strength.
-        lr_power (float): Learning Rate Power.
-        regularization: A Regularizer, such as
-                        fluid.regularizer.L2DecayRegularizer.
-        name: A optional name prefix.
+    Parameters:
+        learning_rate (float|Variable): Global learning rate.
+        l1 (float): L1 regularization strength, default is 0.0.
+        l2 (float): L2 regularization strength, default is 0.0.
+        lr_power (float): Learning Rate Power, default is -0.5.
+        regularization: A Regularizer, such as :ref:`api_fluid_regularizer_L2DecayRegularizer`. \
+            Optional, default is None.
+        name (str, optional): This parameter is used by developers to print debugging information. \
+            For details, please refer to :ref:`api_guide_Name`. Default is None.
 
     Raises:
         ValueError: If learning_rate, rho, epsilon, momentum are None.
@@ -2220,7 +2224,7 @@ class FtrlOptimizer(Optimizer):
                 for data in train_reader():
                     exe.run(main, feed=feeder.feed(data), fetch_list=fetch_list)
 
-    Notes:
+    NOTE:
        Currently, FtrlOptimizer doesn't support sparse parameter optimization.
     """