d42df89c351e0c2a031ea3a9ae17fb7b844e7b79,tensorlayer/layers.py,BatchNormLayer,__init__,#BatchNormLayer#Any#Any#Any#Any#Any#Any#Any#Any#,1680

Before Change

            if is_train:
                is_train = tf.cast(tf.ones([]), tf.bool)
            else:
                is_train = tf.cast(tf.zeros([]), tf.bool)

            mean, variance = control_flow_ops.cond(
                // is_train, lambda: (mean, variance),     // when training, (x-mean(x))/var(x)

After Change

                                      trainable=False,)//   restore=restore)
            moving_variance = tf.get_variable("moving_variance",
                                          params_shape,
                                          initializer=tf.constant_initializer(1.),
                                          trainable=False,)//   restore=restore)

            //// 3.

Instances