def insertWebsite(self, url, domain):
		'''增加一个网页,标记为未访问,并对相应的domain增加其入度'''
		cur = self.conn.cursor()
		cur.execute("SELECT 1 FROM Domains WHERE domain=?", (domain,))
		result = cur.fetchone()
		if not result:
			# 未有对应domain记录, 先创建domain, 把入度设为1
			if VERBOSE:
				print 'Spot Domain:',domain
			self.insertDomain(domain, indegree=1)
			cur.execute("SELECT did FROM Domains WHERE domain=?", (domain,))
			did = cur.fetchone()[0]
		else:
			did = result[0]
			# 对应的domain记录已经存在, 对其入度+1
			cur.execute("UPDATE Domains SET outdegree=outdegree+1 WHERE domain=?", (domain,))

		cur.execute("INSERT INTO Websites VALUES (NULL,?,?,NULL,0)", (did, url,))
		# 写入到文件
		self.conn.commit()
def nonlinear_1d(module, grad_input, grad_output):
    delta_out = module.y[: int(module.y.shape[0] / 2)] - module.y[int(module.y.shape[0] / 2):]

    delta_in = module.x[: int(module.x.shape[0] / 2)] - module.x[int(module.x.shape[0] / 2):]
    dup0 = [2] + [1 for i in delta_in.shape[1:]]
    # handles numerical instabilities where delta_in is very small by
    # just taking the gradient in those cases
    grads = [None for _ in grad_input]
    grads[0] = torch.where(torch.abs(delta_in.repeat(dup0)) < 1e-6, grad_input[0],
                           grad_output[0] * (delta_out / delta_in).repeat(dup0))
    return tuple(grads)