当分支条件为1时（使用topk），打印查找fc.w_0@GRAD 返回空，没有正确生成反向梯度
当分钟条件为0是（不适用topk），可以正常工作

def test_topn_grad():
    input = fluid.layers.data(name='input', shape=[1], dtype='float32')
    fc = fluid.layers.fc(name='fc', input=input, size=10, bias_attr=False)

    if 1:
        top_fc, top_index = fluid.layers.topk(fc, k=10)
        loss = fluid.layers.reduce_sum(input=top_fc)
    else:
        loss = fluid.layers.reduce_sum(input=fc)

    optimizer = fluid.optimizer.SGD(learning_rate=1.0)
    opts = optimizer.minimize(loss)
    place = fluid.CPUPlace()
    exe = fluid.Executor(place)
    exe.run(fluid.default_startup_program())

    def find_var(varname):
        return [x for x in fluid.default_main_program().list_vars() if x.name == varname]

    grad = find_var('fc.w_0@GRAD')
    print(grad)