Tensorflow应用程序在docker容器中冻结
我有一个tensorflow应用程序，在ubuntu 16.04上运行良好，但是当我试图在tensorflow / tensorflow泊坞窗图像w / nvidia-docker中运行它时，它到了这一点，然后冻结：
2017-07-12 22:06:10.917255: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations. 2017-07-12 22:06:10.917289: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations. 2017-07-12 22:06:11.023765: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:901] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2017-07-12 22:06:11.024133: I tensorflow/core/common_runtime/gpu/gpu_device.cc:887] Found device 0 with properties: name: Quadro M4000 major: 5 minor: 2 memoryClockRate (GHz) 0.7725 pciBusID 0000:00:05.0 Total memory: 7.93GiB Free memory: 7.87GiB 2017-07-12 22:06:11.024159: I tensorflow/core/common_runtime/gpu/gpu_device.cc:908] DMA: 0 2017-07-12 22:06:11.024168: I tensorflow/core/common_runtime/gpu/gpu_device.cc:918] 0: Y 2017-07-12 22:06:11.024190: I tensorflow/core/common_runtime/gpu/gpu_device.cc:977] Creating TensorFlow device (/gpu:0) -> (device: 0, name: Quadro M4000, pci bus id: 0000:00:05.0) 由于不输出错误信息，我不知道从哪里开始。 对于我可能会丢失的东西的任何build议或进一步排除故障的步骤？
我确认我的nvidia-docker安装运行正常。
事实certificate，应用程序正在运行，它似乎已经被冻结，因为在docker容器中运行的python应用程序的输出往往会卡在缓冲区中，并且永远不会显示在docker日志中。 要解决我通过-u传递给python的问题，我现在可以在Docker日志中看到我的应用程序的输出，一切都很好。