import tensorflow as tf

			'''
			self.value,  self.next_loc_mean, self.loc_std, self.next_loc, self.state_out, self.state_in, self.state_init = self._build_net(self.inputs, self.prev_loc, RNN_SIZE, TRAINING, a_size)  # self.goal_pos


		if TRAINING:
			self.target_v               = tf.placeholder(tf.float32, [None], 'Vtarget')
			self.advantages             = tf.placeholder(shape=[None], dtype=tf.float32)

			self.sampled_next_locs      = tf.placeholder(tf.float32, [None,2])									# sampled action is stored here
			self.policy   = gaussian_pdf(self.next_loc_mean, self.loc_std, self.sampled_next_locs)		 # Distribution == Policy


