68bea038ee799cfd4397621fb1f6023b657c2bdf,tensorlayer/layers.py,BatchNormLayer,__init__,#BatchNormLayer#Any#Any#Any#Any#Any#Any#Any#Any#,1721

Before Change

            if not is_train:    // test : mean=0, std=1
            // if is_train:      // train : mean=0, std=1
                is_train = tf.cast(tf.ones([]), tf.bool)
            else:
                is_train = tf.cast(tf.zeros([]), tf.bool)

After Change

                mean, var = mean_var_with_update()
                self.outputs = act( tf.nn.batch_normalization(self.inputs, mean, var, beta, gamma, epsilon) )
            else:
                self.outputs = act( tf.nn.batch_normalization(self.inputs, moving_mean, moving_variance, beta, gamma, epsilon) )
                
            // variables = tf.get_collection(TF_GRAPHKEYS_VARIABLES, scope=vs.name)  // 8 params in TF12 if zero_debias=True
            variables = tf.get_collection(tf.GraphKeys.TRAINABLE_VARIABLES, scope=vs.name)    // 2 params beta, gamma

Instances