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 testWrapperWeights(self, wrapper):
    """Tests that wrapper weights contain wrapped cells weights."""
    base_cell = layers.SimpleRNNCell(1, name="basic_rnn_cell")
    rnn_cell = wrapper(base_cell)
    rnn_layer = layers.RNN(rnn_cell)
    inputs = ops.convert_to_tensor_v2_with_dispatch([[[1]]],
                                                    dtype=dtypes.float32)
    rnn_layer(inputs)

    wrapper_name = generic_utils.to_snake_case(wrapper.__name__)
    expected_weights = ["rnn/" + wrapper_name + "/" + var for var in
                        ("kernel:0", "recurrent_kernel:0", "bias:0")]
    self.assertLen(rnn_cell.weights, 3)
    self.assertCountEqual([v.name for v in rnn_cell.weights], expected_weights)
    self.assertCountEqual([v.name for v in rnn_cell.trainable_variables],
                          expected_weights)
    self.assertCountEqual([v.name for v in rnn_cell.non_trainable_variables],
                          [])
    self.assertCountEqual([v.name for v in rnn_cell.cell.weights],
                          expected_weights)