import tensorflow as tf

		self.dropout_input = args.dropout_input
		self.clip_norm = args.clip_norm

		self.embedding_init = embedding_init
		self.x = tf.placeholder(tf.int32, [None, None], 'input')
		self.y = tf.placeholder(tf.int32, [None, self.num_classes], 'labels')
		self.seq_len = tf.placeholder(tf.int64, [None], 'input_length')


	def inference(self, forward_only=None):

		embed_inputs = tf.nn.embedding_lookup(self.embedding_init, self.x) ## (batch_size, seq_len, 100)
