def get_regularizer(desc):
"""Get regularizer function."""
if desc.type == 'l1_regularizer':
return slim.l1_regularizer(scale=float(desc.weight))
elif desc.type == 'l2_regularizer':
return slim.l2_regularizer(scale=float(desc.weight))
else:
raise ValueError('Unknown regularizer type: {}'.format(desc.type))
def get_real_model(self):
"""Get real model of regularizer."""
if self.model:
return self.model
else:
if self.type == 'l1_regularizer':
self.model = slim.l1_regularizer(scale=float(self.weight))
elif self.type == 'l2_regularizer':
self.model = slim.l2_regularizer(scale=float(self.weight))
else:
self.model = None
raise ValueError('Unknown regularizer type: {}'.format(
self.type))
return self.model
def _build_slim_regularizer(regularizer):
"""Builds a tf-slim regularizer from config.
Args:
regularizer: hyperparams_pb2.Hyperparams.regularizer proto.
Returns:
tf-slim regularizer.
Raises:
ValueError: On unknown regularizer.
"""
regularizer_oneof = regularizer.WhichOneof('regularizer_oneof')
if regularizer_oneof == 'l1_regularizer':
return slim.l1_regularizer(scale=float(regularizer.l1_regularizer.weight))
if regularizer_oneof == 'l2_regularizer':
return slim.l2_regularizer(scale=float(regularizer.l2_regularizer.weight))
if regularizer_oneof is None:
return None
raise ValueError('Unknown regularizer function: {}'.format(regularizer_oneof))