batch_norm.py 文件源码

def init_var(self):
        trainable = self.trainable
        with tf.variable_scope(self.scope):
            if self.init_beta is None:
                self.init_beta = tf.constant(0.0, shape=[self.n_out])
            if self.init_gamma is None:
                self.init_gamma = tf.constant(1.0, shape=[self.n_out])
            self.beta = self.declare_var(
                [self.n_out], init_val=self.init_beta, name='beta',
                trainable=trainable)
            self.gamma = self.declare_var(
                [self.n_out], init_val=self.init_gamma, name='gamma',
                trainable=trainable)
            self.ema = tf.train.ExponentialMovingAverage(decay=self.decay)
            self.batch_mean = None
            self.batch_var = None
            self.ema_apply_op = None
            pass
        pass