Created by: aprilvkuo

背景： Paddle训练， 是否支持多线程或者多进程同时触发多个不同的训练任务呢？

# 训练代码

def run_model():
    train_program = fluid.Program()
    startup_program = fluid.Program()
    with fluid.program_guard(train_program, startup_program):
        data = fluid.data(name='X', shape=[None, 1], dtype='float32')
        hidden = fluid.layers.fc(input=data, size=10)
        loss = fluid.layers.mean(hidden)
        sgd = fluid.optimizer.SGD(learning_rate=0.001)
        sgd.minimize(loss)

    use_cuda = False
    place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
    exe = fluid.Executor(place)

    # Run the startup program once and only once.
    # Not need to optimize/compile the startup program.
    startup_program.random_seed=1
    exe.run(startup_program)

    # Run the main program directly without compile.
    x = numpy.random.random(size=(10, 1)).astype('float32')
    loss_data, = exe.run(train_program,
                        feed={"X": x},
                        fetch_list=[loss.name])

    # Or use CompiledProgram:
    compiled_prog = fluid.CompiledProgram(train_program)
    loss_data, = exe.run(compiled_prog,
                feed={"X": x},
                fetch_list=[loss.name])
    return 0, "success"


# 线程池调用代码
import logging
from concurrent.futures import ThreadPoolExecutor, as_completed



def train_model():
    """[summary]

    """
    code, mes = run_model()
    return code, mes


if __name__ == "__main__":
    repeat_times = 1000
    task_list = 100
    executor = ThreadPoolExecutor(12)
    all_tasks = []
    cnt = 0
    for _ in range(repeat_times):
        for i in range(task_list):
            all_tasks.append(executor.submit(train_model))
            cnt +=  1
        for index, future in enumerate(as_completed(all_tasks)):
            result = future.result()
            print(result)
            code, mes = result
            if code == 0:
                logging.info("task %d: quick slu train success" % index)
            else:
                logging.error("task %d: quick slu train failed, [%s]" % (index, mes))