def deconv_bn_relu(input, output_chn, is_training, name):
    with tf.variable_scope(name):
        conv = Deconv3d(input, output_chn, name='deconv')
        bn = tf.contrib.layers.batch_norm(conv, decay=0.9, updates_collections=None, epsilon=1e-05, scale=True, is_training=is_training, scope='batch_norm')
        relu = tf.nn.relu(bn, name='relu')
    return relu
def deconv_bn_relu(input, output_chn, is_training, name):
    with tf.variable_scope(name):
        conv = Deconv3d(input, output_chn, name='deconv')
        bn = tf.contrib.layers.batch_norm(conv, decay=0.9, updates_collections=None, epsilon=1e-05, scale=True, is_training=is_training, scope='batch_norm')
        relu = tf.nn.relu(bn, name='relu')
    return relu