nn.py 文件源码

def soft_attn(self, top_recur):
    """"""

    reuse = (self.moving_params is not None) or None

    input_size = top_recur.get_shape().as_list()[-1]
    with tf.variable_scope('MLP', reuse=reuse):
      head_mlp, dep_mlp = self.MLP(top_recur, self.info_mlp_size,
                                   func=self.info_func,
                                   keep_prob=self.info_keep_prob,
                                   n_splits=2)
    with tf.variable_scope('Arcs', reuse=reuse):
      arc_logits = self.bilinear_classifier(dep_mlp, head_mlp, keep_prob=self.info_keep_prob)
      arc_prob = self.softmax(arc_logits)
      head_lin = tf.batch_matmul(arc_prob, top_recur)
      top_recur = tf.concat(2, [top_recur, head_lin])
    top_recur.set_shape([tf.Dimension(None), tf.Dimension(None), tf.Dimension(4*self.recur_size)])
    return top_recur

  #=============================================================