"""
Implementations of weight constraints for initializers
"""
import tensorflow as tf
from tensorflow.keras import backend as K
from tensorflow.keras.constraints import MinMaxNorm
[docs]class MinMaxWeight(MinMaxNorm):
"""
Small override to the MinMaxNorm Keras class to not look at the absolute value
This version looks at the sum instead of at the norm
"""
def __init__(self, min_value, max_value, **kwargs):
super().__init__(min_value=min_value, max_value=max_value, axis=1, **kwargs)
def __call__(self, w):
norms = K.sum(w, axis=self.axis, keepdims=True)
desired = (
self.rate * K.clip(norms, self.min_value, self.max_value) + (1 - self.rate) * norms
)
return w * desired / (K.epsilon() + norms)