EVOLUTION-MANAGER

Edit File: _batch_normalization.py

import keras class BatchNormalization(keras.layers.BatchNormalization): """ Identical to keras.layers.BatchNormalization, but adds the option to freeze parameters. """ def __init__(self, freeze, *args, **kwargs): self.freeze = freeze super(BatchNormalization, self).__init__(*args, **kwargs) # set to non-trainable if freeze is true self.trainable = not self.freeze def call(self, *args, **kwargs): # Force test mode if frozen, otherwise use default behaviour (i.e., training=None). if self.freeze: kwargs['training'] = False return super(BatchNormalization, self).call(*args, **kwargs) def get_config(self): config = super(BatchNormalization, self).get_config() config.update({'freeze': self.freeze}) return config