import tensorflow as tf

            Q = tf.tile(tf.expand_dims(self.q_embed_encoding, 1), [1, self.max_p_len, 1, 1])
            S = trilinear([C, Q, C * Q], input_keep_prob=1.0 - self.dropout)
            mask_q = tf.expand_dims(self.q_mask, 1)
            S_ = tf.nn.softmax(mask_logits(S, mask=mask_q))
