adgm.py 文件源码

def create_architecture(self, mode, tag=None):

        training = mode == 'TRAIN'
        testing = mode == 'TEST'

        assert tag != None

        # handle most of the regularizers here
        weights_regularizer = tf.contrib.layers.l2_regularizer(cfg.TRAIN.WEIGHT_DECAY)
        biases_regularizer = weights_regularizer

        # list as many types of layers as possible, even if they are not used now
        with arg_scope([slim.conv2d, slim.conv2d_in_plane,
                        slim.conv2d_transpose, slim.separable_conv2d, slim.fully_connected],
                       weights_regularizer=weights_regularizer,
                       biases_regularizer=biases_regularizer,
                       biases_initializer=tf.constant_initializer(0.0)):
            self.build_network()

        elbo = self.add_losses()
        self._summary_op = tf.summary.merge_all()
        return elbo