Hi all, my final step in this instruction has not completed, in run this command:
python3 rest-server.py
Then my terminal logged the text bellow, then the application auto stopped, so i could not access the URL https://127.0.0.1:5000
Could anyone help me, please?

nvidia@tegra-ubuntu:~/workspace/Face_Recognition/server$ python3 rest-server.py
2019-03-11 07:48:13.520030: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:864] ARM64 does not support NUMA - returning NUMA node zero
2019-03-11 07:48:13.520155: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1392] Found device 0 with properties:
name: NVIDIA Tegra X2 major: 6 minor: 2 memoryClockRate(GHz): 1.3005
pciBusID: 0000:00:00.0
totalMemory: 7.66GiB freeMemory: 4.46GiB
2019-03-11 07:48:13.520212: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1471] Adding visible gpu devices: 0
2019-03-11 07:48:15.078106: I tensorflow/core/common_runtime/gpu/gpu_device.cc:952] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-03-11 07:48:15.078177: I tensorflow/core/common_runtime/gpu/gpu_device.cc:958] 0
2019-03-11 07:48:15.078202: I tensorflow/core/common_runtime/gpu/gpu_device.cc:971] 0: N
2019-03-11 07:48:15.078343: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1084] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 3824 MB memory) -> physical GPU (device: 0, name: NVIDIA Tegra X2, pci bus id: 0000:00:00.0, compute capability: 6.2)
WARNING:tensorflow:The saved meta_graph is possibly from an older release:
'model_variables' collection should be of type 'byte_list', but instead is of type 'node_list'.

• Serving Flask app "rest-server" (lazy loading)
• Environment: production
  WARNING: Do not use the development server in a production environment.
  Use a production WSGI server instead.
• Debug mode: on
• Running on http://0.0.0.0:5000/ (Press CTRL+C to quit)
• Restarting with stat
  2019-03-11 07:54:39.575332: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:864] ARM64 does not support NUMA - returning NUMA node zero
  2019-03-11 07:54:39.575470: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1392] Found device 0 with properties:
  name: NVIDIA Tegra X2 major: 6 minor: 2 memoryClockRate(GHz): 1.3005
  pciBusID: 0000:00:00.0
  totalMemory: 7.66GiB freeMemory: 39.86MiB
  2019-03-11 07:54:39.575525: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1471] Adding visible gpu devices: 0
  2019-03-11 07:54:41.252788: I tensorflow/core/common_runtime/gpu/gpu_device.cc:952] Device interconnect StreamExecutor with strength 1 edge matrix:
  2019-03-11 07:54:41.256160: I tensorflow/core/common_runtime/gpu/gpu_device.cc:958] 0
  2019-03-11 07:54:41.256192: I tensorflow/core/common_runtime/gpu/gpu_device.cc:971] 0: N
  2019-03-11 07:54:41.256432: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1084] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 43 MB memory) -> physical GPU (device: 0, name: NVIDIA Tegra X2, pci bus id: 0000:00:00.0, compute capability: 6.2)
  nvidia@tegra-ubuntu:~/workspace/Face_Recognition/server$