import tensorflow as tf

            utils.add_gradient_summary(grad, var)
    return optimizer.apply_gradients(grads)


def main(argv=None):
    keep_probability = tf.placeholder(tf.float32, name="keep_probabilty")
    image = tf.placeholder(tf.float32, shape=[None, IMAGE_SIZE, IMAGE_SIZE, 3], name="input_image")

#debug
    annotation = tf.placeholder(tf.int32, shape=[None, IMAGE_SIZE, IMAGE_SIZE, 1], name="annotation")
#    annotation = tf.placeholder(tf.int32, shape=[None, IMAGE_SIZE, IMAGE_SIZE, 3], name="annotation")

