diff --git a/python/paddle/fluid/layers/tensor.py b/python/paddle/fluid/layers/tensor.py index 10596f80c2f2b1d91c42b7a56e0ddba1da24f78b..9777e8505f9337627440960ab0c26ebaa3ddb8a0 100644 --- a/python/paddle/fluid/layers/tensor.py +++ b/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 diff --git a/python/paddle/fluid/optimizer.py b/python/paddle/fluid/optimizer.py index 377cd2aa49cc4a60311f1997133478642a75cf0c..c85433576c0f53de873b2cd280e24548ae80897d 100644 --- a/python/paddle/fluid/optimizer.py +++ b/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. \ - 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. + 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 :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. \ - 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. + 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, 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. - 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. - + 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 :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. """