113 lines
3.1 KiB
Python
113 lines
3.1 KiB
Python
|
# Copyright 2015 The TensorFlow Authors. All Rights Reserved.
|
||
|
|
#
|
||
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
||
|
|
# you may not use this file except in compliance with the License.
|
||
|
|
# You may obtain a copy of the License at
|
||
|
|
#
|
||
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
||
|
|
#
|
||
|
|
# Unless required by applicable law or agreed to in writing, software
|
||
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
||
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||
|
|
# See the License for the specific language governing permissions and
|
||
|
|
# limitations under the License.
|
||
|
|
# ==============================================================================
|
||
|
|
"""Built-in regularizers.
|
||
|
|
"""
|
||
|
|
from __future__ import absolute_import
|
||
|
|
from __future__ import division
|
||
|
|
from __future__ import print_function
|
||
|
|
|
||
|
|
import six
|
||
|
|
|
||
|
|
from tensorflow.python.keras import backend as K
|
||
|
|
from tensorflow.python.keras.utils.generic_utils import deserialize_keras_object
|
||
|
|
from tensorflow.python.keras.utils.generic_utils import serialize_keras_object
|
||
|
|
from tensorflow.python.ops import math_ops
|
||
|
|
from tensorflow.python.util.tf_export import tf_export
|
||
|
|
|
||
|
|
|
||
|
|
@tf_export('keras.regularizers.Regularizer')
|
||
|
|
class Regularizer(object):
|
||
|
|
"""Regularizer base class.
|
||
|
|
"""
|
||
|
|
|
||
|
|
def __call__(self, x):
|
||
|
|
return 0.
|
||
|
|
|
||
|
|
@classmethod
|
||
|
|
def from_config(cls, config):
|
||
|
|
return cls(**config)
|
||
|
|
|
||
|
|
|
||
|
|
@tf_export('keras.regularizers.L1L2')
|
||
|
|
class L1L2(Regularizer):
|
||
|
|
"""Regularizer for L1 and L2 regularization.
|
||
|
|
|
||
|
|
Arguments:
|
||
|
|
l1: Float; L1 regularization factor.
|
||
|
|
l2: Float; L2 regularization factor.
|
||
|
|
"""
|
||
|
|
|
||
|
|
def __init__(self, l1=0., l2=0.): # pylint: disable=redefined-outer-name
|
||
|
|
self.l1 = K.cast_to_floatx(l1)
|
||
|
|
self.l2 = K.cast_to_floatx(l2)
|
||
|
|
|
||
|
|
def __call__(self, x):
|
||
|
|
regularization = 0.
|
||
|
|
if self.l1:
|
||
|
|
regularization += math_ops.reduce_sum(self.l1 * math_ops.abs(x))
|
||
|
|
if self.l2:
|
||
|
|
regularization += math_ops.reduce_sum(self.l2 * math_ops.square(x))
|
||
|
|
return regularization
|
||
|
|
|
||
|
|
def get_config(self):
|
||
|
|
return {'l1': float(self.l1), 'l2': float(self.l2)}
|
||
|
|
|
||
|
|
|
||
|
|
# Aliases.
|
||
|
|
|
||
|
|
|
||
|
|
@tf_export('keras.regularizers.l1')
|
||
|
|
def l1(l=0.01):
|
||
|
|
return L1L2(l1=l)
|
||
|
|
|
||
|
|
|
||
|
|
@tf_export('keras.regularizers.l2')
|
||
|
|
def l2(l=0.01):
|
||
|
|
return L1L2(l2=l)
|
||
|
|
|
||
|
|
|
||
|
|
@tf_export('keras.regularizers.l1_l2')
|
||
|
|
def l1_l2(l1=0.01, l2=0.01): # pylint: disable=redefined-outer-name
|
||
|
|
return L1L2(l1=l1, l2=l2)
|
||
|
|
|
||
|
|
|
||
|
|
@tf_export('keras.regularizers.serialize')
|
||
|
|
def serialize(regularizer):
|
||
|
|
return serialize_keras_object(regularizer)
|
||
|
|
|
||
|
|
|
||
|
|
@tf_export('keras.regularizers.deserialize')
|
||
|
|
def deserialize(config, custom_objects=None):
|
||
|
|
return deserialize_keras_object(
|
||
|
|
config,
|
||
|
|
module_objects=globals(),
|
||
|
|
custom_objects=custom_objects,
|
||
|
|
printable_module_name='regularizer')
|
||
|
|
|
||
|
|
|
||
|
|
@tf_export('keras.regularizers.get')
|
||
|
|
def get(identifier):
|
||
|
|
if identifier is None:
|
||
|
|
return None
|
||
|
|
if isinstance(identifier, dict):
|
||
|
|
return deserialize(identifier)
|
||
|
|
elif isinstance(identifier, six.string_types):
|
||
|
|
config = {'class_name': str(identifier), 'config': {}}
|
||
|
|
return deserialize(config)
|
||
|
|
elif callable(identifier):
|
||
|
|
return identifier
|
||
|
|
else:
|
||
|
|
raise ValueError('Could not interpret regularizer identifier:', identifier)
|