diff --git a/python/paddle/fluid/regularizer.py b/python/paddle/fluid/regularizer.py index c4d6829599616cb3ea7791a189e7070974de6ae3..dac474d5ee76590a75311d6bf2c4cb2fe85b6c40 100644 --- a/python/paddle/fluid/regularizer.py +++ b/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):