import tensorflow as tf

		crit_dis = tf.reduce_mean(tf.square(crit_real - tf.ones_like(crit_real))) + tf.reduce_mean(tf.square(crit_fake - tf.zeros_like(crit_fake)))
		crit_gen = tf.reduce_mean(tf.square(crit_fake - tf.ones_like(crit_fake)))

		rep_loss = tf.reduce_mean(tf.square(pred - x2d))

		KK = tf.matmul(K, K, transpose_b=True)
