add doc for L1DecayRegularizer and L2DecayRegularizer

python/paddle/fluid/regularizer.py

@@ -16,8 +16,8 @@ import framework
 from . import core
 
 __all__ = [
-    'append_regularization_ops', 'WeightDecayRegularizer', 'L1Decay', 'L2Decay',
-    'L1DecayRegularizer', 'L2DecayRegularizer'
+    'append_regularization_ops', 'L1Decay', 'L2Decay', 'L1DecayRegularizer',
+    'L2DecayRegularizer'
 ]
 
 
@@ -36,7 +36,8 @@ def append_regularization_ops(parameters_and_grads, regularization=None):
                         set. It will be applied with regularizer.
 
     Returns:
-        list of (parameters, gradients) pair with the regularized gradient
+        list[(Variable, Variable)]: list of (parameters, gradients) \
+        pair with the regularized gradient
 
     Raises:
         Exception: Unknown regularization type
@@ -100,6 +101,24 @@ class WeightDecayRegularizer(object):
 
 class L2DecayRegularizer(WeightDecayRegularizer):
     """Implements the L2 Weight Decay Regularization
+
+    Small values of L2 can help prevent over fitting the training data.
+
+    .. math::
+
+        L2WeightDecay = reg\_coeff * parameter
+
+    Args:
+        regularization_coeff(float): regularization coeff
+
+    Examples:
+        .. code-block:: python
+
+            optimizer = fluid.optimizer.Adagrad(
+                learning_rate=1e-4,
+                regularization=fluid.regularizer.L2DecayRegularizer(
+                    regularization_coeff=0.1))
+            optimizer.minimize(avg_cost)
     """
 
     def __init__(self, regularization_coeff=0.0):
@@ -154,6 +173,27 @@ class L2DecayRegularizer(WeightDecayRegularizer):
 
 class L1DecayRegularizer(WeightDecayRegularizer):
     """Implements the L1 Weight Decay Regularization
+
+    L1 regularization encourages sparsity.
+
+    .. math::
+
+        L1WeightDecay = reg\_coeff * sign(parameter)
+
+    Args:
+        regularization_coeff(float): regularization coeff
+
+    Examples:
+        .. code-block:: python
+
+            program = fluid.framework.Program()
+            block = program.global_block()
+            mul_x = block.create_parameter(
+                dtype="float32",
+                shape=[5, 10],
+                lod_level=0,
+                name="mul.x",
+                regularizer=fluid.regularizer.L1DecayRegularizer(0.5))
     """
 
     def __init__(self, regularization_coeff=0.0):