import tensorflow as tf

          logits=logits, labels=tf.nn.softmax(logits)))
        entropy += curr_ent
        prev_layers.append(anchors.read(tf.reduce_sum(index)))
        inputs = prev_layers[-1]

      for i in range(2):  # op_1, op_2
        next_c, next_h = stack_lstm(inputs, prev_c, prev_h, self.w_lstm)
        prev_c, prev_h = next_c, next_h
        logits = tf.matmul(next_h[-1], self.w_soft) + self.b_soft
        if self.temperature is not None:
          logits /= self.temperature
        if self.tanh_constant is not None:
          op_tanh = self.tanh_constant / self.op_tanh_reduce
          logits = op_tanh * tf.tanh(logits)
        if use_bias:
          logits += self.b_soft_no_learn
