import tensorflow as tf


	def loss(self, logits, forward_only=None):
		cost = tf.nn.softmax_cross_entropy_with_logits(logits=logits, labels=tf.cast(self.y, tf.float32))
		mean_cost = tf.reduce_mean(cost)
		y_pred = tf.argmax(logits, 1)
		correct_pred = tf.equal(y_pred, tf.argmax(self.y, 1))
		accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.float32))

		if forward_only:
			str_summary_type = 'eval'
