import tensorflow as tf

        self.head_scores = util.projection(context_outputs, 1) # [num_words, 1]
      span_head_scores = tf.gather(self.head_scores, span_indices) # [k, max_span_width, 1]
      span_mask = tf.expand_dims(tf.sequence_mask(span_width, self.config["max_span_width"], dtype=tf.float32), 2) # [k, max_span_width, 1]
      span_head_scores += tf.log(span_mask) # [k, max_span_width, 1]
      span_attention = tf.nn.softmax(span_head_scores, 1) # [k, max_span_width, 1]
      span_head_emb = tf.reduce_sum(span_attention * span_text_emb, 1) # [k, emb]
      span_emb_list.append(span_head_emb)

    span_emb = tf.concat(span_emb_list, 1) # [k, emb]
    return span_emb # [k, emb]
