def robotsrulesetOfDomain(self, domain):
		'''检查domain是否在数据库中,
			否 --> (False, None)
			是 --> (True, 数据库中存储的robots.txt内容)
		'''
		exist = False
		cur = self.conn.cursor()
		# 是否存在
		cur.execute("SELECT 1 FROM Domains WHERE domain=?", (domain,))
		if cur.fetchone() :
			exist = True
		# 存在的话,结果是什么
		cur.execute("SELECT rules FROM Domains,Rulesets "
			"WHERE domain=? AND Domains.did=Rulesets.did"
			,(domain,) )
		ruleset = cur.fetchone()
		return (exist, ruleset)
def batch_norm(inputs, training, data_format, name=''):
  """Performs a batch normalization using a standard set of parameters."""
  # We set fused=True for a significant performance boost. See
  # https://www.tensorflow.org/performance/performance_guide#common_fused_ops
  return tf.compat.v1.layers.batch_normalization(
      inputs=inputs,
      axis=1 if data_format == 'channels_first' else 3,
      momentum=_BATCH_NORM_DECAY,
      epsilon=_BATCH_NORM_EPSILON,
      center=True,
      scale=True,
      training=training,
      fused=True,
      name=name)