Source code for das.morpholayers.regularizers
from tensorflow.keras import backend as K
from tensorflow.keras.regularizers import Regularizer
MIN_LATT = -1
[docs]class L1L2Lattice(Regularizer):
"""Regularizer for L1 and L2 regularization in a lattice. Computes L1/L2 distance to MIN_LATT.
Args:
l1 (float): L1 regularization factor.
l2 (float): L2 regularization factor.
"""
def __init__(self, l1=0.0, l2=0.0):
self.l1 = K.cast_to_floatx(l1)
self.l2 = K.cast_to_floatx(l2)
def __call__(self, x):
"""Compute L1L2Lattice regularization.
Args:
x (tf.Tensor): Input tensor.
Returns:
tf.Tensor: Regularization term.
"""
regularization = 0.0
if self.l1:
regularization += self.l1 * K.sum(K.abs(x - MIN_LATT))
if self.l2:
regularization += self.l2 * K.sum(K.square(x - MIN_LATT))
return regularization
[docs] def get_config(self):
"""Get configuration of the regularizer.
Returns:
dict: Regularizer configuration.
"""
return {"l1": float(self.l1), "l2": float(self.l2)}
[docs]def l1lattice(l=0.01):
"""Alias for L1L2Lattice with L1 regularization.
Args:
l (float): L1 regularization factor.
Returns:
L1L2Lattice: L1L2Lattice regularizer instance.
"""
return L1L2Lattice(l1=l)
[docs]def l2lattice(l=0.01):
"""Alias for L1L2Lattice with L2 regularization.
Args:
l (float): L2 regularization factor.
Returns:
L1L2Lattice: L1L2Lattice regularizer instance.
"""
return L1L2Lattice(l2=l)
[docs]def l1_l2lattice(l1=0.01, l2=0.01):
"""Alias for L1L2Lattice with both L1 and L2 regularization.
Args:
l1 (float): L1 regularization factor.
l2 (float): L2 regularization factor.
Returns:
L1L2Lattice: L1L2Lattice regularizer instance.
"""
return L1L2Lattice(l1=l1, l2=l2)