小编Gol*_*ken的帖子

我试图使用 WorkManager 每 10 秒运行一个简单的工作。当应用程序在后台或前台运行时，它可以完美运行。当我关闭应用程序（杀死应用程序）时，该工作将不再被调用。

我在创建 MainActivity 时调用以下代码

fun scheduleNotification(context: Context) {
    val workRequest = OneTimeWorkRequest.Builder(NotificationWorker::class.java).setInitialDelay(10000, TimeUnit.MILLISECONDS)
    WorkManager.getInstance().enqueueUniqueWork("NotificationWorker", ExistingWorkPolicy.REPLACE, workRequest.build())
    Log.d("NotificationWorker", "start")
}

工人阶级

class NotificationWorker(context: Context, params: WorkerParameters) : Worker(context, params) {

override fun doWork(): Result {
    Log.d("NotificationWorker", "Working")
    NotificationUtil.scheduleNotification(applicationContext) // n times
    return Result.success()
}
}

当我的应用程序未关闭时，这些代码运行良好。

即使应用程序关闭，我怎样才能让它运行？

我关注了这些主题：

1. https://devtalk.nvidia.com/default/topic/1044958/jetson-agx-xavier/scikit-learn-for-python-3-on-jetson-xavier/
2. https://devtalk.nvidia.com/default/topic/1049684/jetson-nano/errors-during-install-sklearn-/
3. https://github.com/scikit-learn/scikit-learn/issues/12707

蟒蛇版本：3.6.9

这是我运行的所有命令：

sudo apt-get update
sudo apt-get install libhdf5-serial-dev hdf5-tools libhdf5-dev zlib1g-dev zip libjpeg8-dev

sudo apt-get install python3-pip
sudo pip3 install -U pip testresources setuptools

sudo pip3 install -U numpy==1.16.1 future==0.17.1 mock==3.0.5 h5py==2.9.0 keras_preprocessing==1.0.5 keras_applications==1.0.8 gast==0.2.2 enum34 futures protobuf

sudo pip3 install --extra-index-url https://developer.download.nvidia.com/compute/redist/jp/v43 tensorflow-gpu==1.15.0+nv19.12

sudo apt-get install python3-opencv
sudo apt-get install python3-pandas
sudo apt-get install python3-keras
sudo apt-get install gfortran
sudo apt-get install python3-scipy
sudo apt-get install python3-matplotlib
sudo apt-get install python3-imageio

pip3 install dlib …